income_starts,\\n income_df.loc[:, 'high_inc_benefit_base'] * inc_payout_factor, 0)\\n\\n for counter in years:\\n if counter == 0:\\n income_df.loc[counter, 'contract_value'] = premium * (1 + contract_bonus)\\n\\n elif income_df.loc[counter, 'strategy_term'] == 1:\\n x1 = income_df.loc[counter - 1, 'contract_value'] - income_df.loc[counter, 'rider_fee']\\n x2 = (x1 * (1 + income_df.loc[counter, 'term_ret_netspr'])) - income_df.loc[counter, 'eoy_income']\\n income_df.loc[counter, 'contract_value'] = x2\\n\\n else:\\n x1 = income_df.loc[counter - 1, 'contract_value'] - income_df.loc[counter, 'rider_fee'] - \\\\\\n income_df.loc[counter, 'eoy_income']\\n\\n income_df.loc[counter, 'contract_value'] = x1\\n\\n # variable stores the income number that is used in the base and fia portfolio calcs.\\n\\n income_from_fia = income_df.loc[income_df.index[-1], 'eoy_income']\\n\\n income_df.loc[:, 'contract_value'] = income_df.loc[:, 'contract_value'].apply(lambda x: 0 if x <= 0 else x)\\n\\n sim_fia_cv.loc[:, str(runs)] = income_df.loc[:, 'contract_value']\\n\\n # ---------------------------------BASE MODEL---------------------------------------------\\n\\n base_wts = read_asset_weights.loc[:, 'base']\\n base_assets = list(base_wts.index)\\n base_weights = list(base_wts.values)\\n base_returns = list(read_returns_est.loc[:, 'Annualized Returns'].values)\\n base_std = list(read_returns_est.loc[:, 'Annualized Risk'].values)\\n\\n base_investment = float(read_income_inputs.loc['risky_assets', 'Base'])\\n adv_fees = float(read_income_inputs.loc['advisor_fees', 'Base'])\\n\\n # -------------------------------------required income--------------------------------\\n req_annual_income = float(read_income_inputs.loc['annual_income', 'inputs'])\\n income_needed = req_annual_income - social\\n income_net_fia_income = max(0, income_needed - income_from_fia)\\n cpn_income_base = base_investment * wtd_cpn_yield\\n\\n # --------------------------------------------RANDOM RETURNS-----------------------------------\\n r_cols = base_assets\\n boy_value = ['bv_{}'.format(name) for name in base_assets]\\n eoy_value = ['ev_{}'.format(name) for name in base_assets]\\n\\n random_returns = pd.DataFrame(index=income_df.index, columns=r_cols)\\n\\n for c in range(len(r_cols)):\\n ret = np.random.normal(base_returns[c], base_std[c], size=(len(random_returns.index), 1))\\n\\n if method == 'smallest':\\n random_returns = read_small.copy()\\n\\n elif method == 'largest':\\n random_returns = read_large.copy()\\n\\n else:\\n random_returns = read_normal.copy()\\n\\n base_df = random_returns.copy()\\n fia_portfolio_df = random_returns.copy()\\n port_investment = float(read_income_inputs.loc['risky_assets', 'FIA'])\\n cpn_income_port = port_investment * wtd_cpn_yield\\n\\n # -------------------------------------BASE PORTFOLIO----------------------------\\n for name in boy_value:\\n base_df.loc[:, name] = 0.0\\n\\n for counter in years:\\n period_returns = list(random_returns.loc[counter, :])\\n if counter == 0:\\n\\n base_df.loc[counter, boy_value] = [base_weights[c] * base_investment for c in range(len(boy_value))]\\n base_df.loc[counter, 'total'] = base_df.loc[counter, boy_value].sum()\\n base_df.loc[counter, 'total_net_fees'] = 0.0\\n base_df.loc[counter, 'income'] = 0.0\\n base_investment = base_df.loc[counter, boy_value].sum()\\n\\n elif (counter > 0) and (counter < income_starts):\\n\\n base_df.loc[counter, boy_value] = [base_weights[c] * base_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n base_df.loc[counter, 'total'] = base_df.loc[counter, boy_value].sum()\\n base_df.loc[counter, 'adv_fees'] = base_df.loc[counter, 'total'] * adv_fees\\n base_df.loc[counter, 'total_net_fees'] = base_df.loc[counter, 'total'] - base_df.loc[\\n counter, 'adv_fees']\\n\\n # --coupon payment is invested back into the risky portfolio until the income is withdrawn----\\n base_investment = base_df.loc[counter, 'total_net_fees'] + cpn_income_base\\n\\n else:\\n\\n base_df.loc[counter, boy_value] = [base_weights[c] * base_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n base_df.loc[counter, 'total'] = base_df.loc[counter, boy_value].sum()\\n base_df.loc[counter, 'adv_fees'] = base_df.loc[counter, 'total'] * adv_fees\\n\\n # ---req. income is adjusted for inflation from the second year of withdrawal. Reinvestment of coupon\\n # stops from the year income starts. Req. income is reduced by the coupon payments\\n\\n if counter == income_starts:\\n\\n income_needed = req_annual_income - social\\n base_df.loc[counter, 'income'] = income_needed - cpn_income_base\\n income_needed = req_annual_income\\n\\n else:\\n income_needed = income_needed * (1 + inflation) - social\\n base_df.loc[counter, 'income'] = income_needed - cpn_income_base\\n income_needed = income_needed + social\\n\\n base_df.loc[counter, 'total_net_fees'] = base_df.loc[counter, 'total'] - \\\\\\n base_df.loc[counter, 'adv_fees'] - \\\\\\n base_df.loc[counter, 'income']\\n\\n base_investment = base_df.loc[counter, 'total_net_fees']\\n\\n base_df.loc[:, 'adj_total'] = base_df.loc[:, 'total_net_fees'].apply(lambda x: x if x > 0 else 0)\\n sim_base_total.loc[:, 's_{}'.format(str(runs))] = base_df.loc[:, 'total_net_fees']\\n sim_base_income.loc[:, 's_{}'.format(str(runs))] = base_df.loc[:, 'income']\\n\\n # -------------------required income----------------------------------\\n req_annual_income = float(read_income_inputs.loc['annual_income', 'inputs'])\\n income_needed = req_annual_income - social\\n # income_net_fia_income = max(0, income_needed - income_from_fia)\\n cpn_income_base = base_investment * wtd_cpn_yield\\n\\n # ----------------------------FIA PORTFOLIO----------------------------------------------\\n for name in boy_value:\\n fia_portfolio_df.loc[:, name] = 0.0\\n\\n for counter in years:\\n period_returns = list(random_returns.loc[counter, :])\\n if counter == 0:\\n\\n fia_portfolio_df.loc[counter, boy_value] = [base_weights[c] * port_investment\\n for c in range(len(boy_value))]\\n fia_portfolio_df.loc[counter, 'total'] = fia_portfolio_df.loc[counter, boy_value].sum()\\n fia_portfolio_df.loc[counter, 'total_net_fees'] = 0.0\\n fia_portfolio_df.loc[counter, 'income'] = 0.0\\n port_investment = fia_portfolio_df.loc[counter, boy_value].sum()\\n\\n elif (counter > 0) and (counter < income_starts):\\n\\n fia_portfolio_df.loc[counter, boy_value] = [base_weights[c] * port_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n fia_portfolio_df.loc[counter, 'total'] = fia_portfolio_df.loc[counter, boy_value].sum()\\n fia_portfolio_df.loc[counter, 'adv_fees'] = fia_portfolio_df.loc[counter, 'total'] * adv_fees\\n fia_portfolio_df.loc[counter, 'total_net_fees'] = fia_portfolio_df.loc[counter, 'total'] - \\\\\\n fia_portfolio_df.loc[counter, 'adv_fees']\\n\\n port_investment = fia_portfolio_df.loc[counter, 'total_net_fees'] + cpn_income_port\\n\\n else:\\n fia_portfolio_df.loc[counter, boy_value] = [base_weights[c] * port_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n fia_portfolio_df.loc[counter, 'total'] = fia_portfolio_df.loc[counter, boy_value].sum()\\n fia_portfolio_df.loc[counter, 'adv_fees'] = fia_portfolio_df.loc[counter, 'total'] * adv_fees\\n\\n # ---req. income is adjusted for inflation from the second year of withdrawal. Reinvestment of coupon\\n # stops from the year income starts. Req. income is reduced by the coupon payments\\n\\n if counter == income_starts:\\n\\n income_needed = req_annual_income - social\\n income_net_fia_income = max(0, income_needed - income_from_fia)\\n fia_portfolio_df.loc[counter, 'income'] = max(0, income_net_fia_income - cpn_income_port)\\n income_needed = req_annual_income\\n\\n else:\\n income_needed = income_needed * (1 + inflation) - social\\n income_net_fia_income = max(0, income_needed - income_from_fia)\\n fia_portfolio_df.loc[counter, 'income'] = max(0, income_net_fia_income - cpn_income_port)\\n income_needed = income_needed + social\\n\\n fia_portfolio_df.loc[counter, 'total_net_fees'] = fia_portfolio_df.loc[counter, 'total'] - \\\\\\n fia_portfolio_df.loc[counter, 'adv_fees'] - \\\\\\n fia_portfolio_df.loc[counter, 'income']\\n\\n port_investment = fia_portfolio_df.loc[counter, 'total_net_fees']\\n\\n sim_port_total.loc[:, 's_{}'.format(str(runs))] = fia_portfolio_df.loc[:, 'total_net_fees'] + \\\\\\n income_df.loc[:, 'contract_value']\\n\\n sim_port_income.loc[:, 's_{}'.format(str(runs))] = fia_portfolio_df.loc[:, 'income']\\n\\n fia_portfolio_df.loc[:, 'adj_total'] = fia_portfolio_df.loc[:, 'total_net_fees'].apply(\\n lambda x: x if x > 0 else 0)\\n\\n # -------------------------------------income breakdown for Base portfolio----------------------------------\\n base_df.to_csv(src + method + '_base_port_detail.csv')\\n sim_base_total.to_csv(src + 'base_ending_values.csv')\\n income_breakdown_base = pd.DataFrame(sim_base_total.quantile(0.5, axis=1))\\n income_breakdown_base.loc[:, 'income_from_portfolio'] = sim_base_income.quantile(0.5, axis=1)\\n income_breakdown_base.loc[:, 'fia_income'] = 0.0\\n income_breakdown_base.loc[:, 'social_security_income'] = social\\n income_breakdown_base.loc[:, 'coupon_income'] = cpn_income_base\\n\\n income_breakdown_base.rename(columns={income_breakdown_base.columns[0]: 'portfolio_ending_value'}, inplace=True)\\n income_breakdown_base.loc[:, 'income_from_portfolio'][\\n income_breakdown_base.loc[:, 'portfolio_ending_value'] <= 0] = 0\\n income_breakdown_base.loc[:, 'total_income'] = income_breakdown_base.loc[:, income_breakdown_base.columns[1:]].sum(\\n axis=1)\\n\\n # ------------------------------------Block Ends-------------------------------------------------------------\\n\\n # ------------------------------income breakdown for FIA portfolio----------------------------------\\n fia_portfolio_df.loc[:, 'contract_value'] = income_df.loc[:, 'contract_value']\\n fia_portfolio_df.to_csv(src + method + '_fia_port_detail.csv')\\n sim_port_total.to_csv(src + 'fiaport_ending_values.csv')\\n\\n income_breakdown_port = pd.DataFrame(sim_port_total.quantile(0.5, axis=1))\\n income_breakdown_port.loc[:, 'income_from_portfolio'] = sim_port_income.quantile(0.5, axis=1)\\n income_breakdown_port.loc[:, 'fia_income'] = income_from_fia\\n income_breakdown_port.loc[:, 'social_security_income'] = social\\n income_breakdown_port.loc[:, 'coupon_income'] = cpn_income_port\\n\\n income_breakdown_port.rename(columns={income_breakdown_port.columns[0]: 'portfolio_ending_value'}, inplace=True)\\n income_breakdown_port.loc[:, 'income_from_portfolio'][\\n income_breakdown_port.loc[:, 'portfolio_ending_value'] <= 0] = 0\\n income_breakdown_port.loc[:, 'total_income'] = income_breakdown_port.loc[:, income_breakdown_port.columns[1:]].sum(\\n axis=1)\\n\\n # ------------------------------------Block Ends-------------------------------------------------------------\\n q_cut = [0.0, .05, 0.25, 0.5, 0.75, 0.95, 1.0]\\n sim_base_income[sim_base_total < income_needed] = 0.0\\n\\n sim_port_income[sim_port_total < income_net_fia_income] = 0\\n\\n sim_port_income = sim_port_income + income_from_fia\\n\\n base_quantile = sim_base_total.loc[sim_base_total.index[-1]].quantile(q_cut)\\n\\n port_quantile = sim_port_total.loc[sim_port_total.index[-1]].quantile(q_cut)\\n\\n cols = ['Min', '5th', '25th', '50th', '75th', '90th', 'Max']\\n\\n # ----------------------------------drop year 0---------------------------------\\n sim_base_total = sim_base_total[1:]\\n sim_port_total = sim_port_total[1:]\\n\\n # --------------------------------quantile analysis for base terminal value-----------------------------\\n base_qcut = pd.DataFrame(index=sim_base_total.index, columns=cols)\\n for c in range(len(cols)):\\n base_qcut.loc[:, cols[c]] = sim_base_total.quantile(q_cut[c], axis=1)\\n\\n base_qcut.clip(lower=0, inplace=True)\\n\\n # ----------------------------------quantile analysis for base income----------------------------\\n base_income_qcut = pd.DataFrame(index=sim_base_income.index, columns=cols)\\n for c in range(len(cols)):\\n base_income_qcut.loc[:, cols[c]] = sim_base_income.quantile(q_cut[c], axis=1)\\n\\n # ----Remove NaN's prior to the income start years------------\\n # base_income_qcut = base_income_qcut.loc[income_starts:]\\n\\n # -------------quantile analysis for portfolio terminal value ---------------\\n\\n port_qcut = pd.DataFrame(index=sim_port_total.index, columns=cols)\\n for c in range(len(cols)):\\n port_qcut.loc[:, cols[c]] = sim_port_total.quantile(q_cut[c], axis=1)\\n\\n port_qcut.clip(lower=0, inplace=True)\\n\\n # ---------------quantile analysis for portfolio income----------------------------\\n port_income_qcut = pd.DataFrame(index=sim_port_income.index, columns=cols)\\n for c in range(len(cols)):\\n port_income_qcut.loc[:, cols[c]] = sim_port_income.quantile(q_cut[c], axis=1)\\n\\n # ----Remove NaN's prior to the income start years------------\\n # port_income_qcut = port_income_qcut.loc[income_starts:]\\n\\n # ----------probability ending value will be less than 0 at the end of the horizon -------------------------\\n\\n base_legacy_risk = (sim_base_total.loc[sim_base_total.index[life_expectancy - clients_age]] < 0).sum() / (\\n trials + 1)\\n port_legacy_risk = (sim_port_total.loc[sim_port_total.index[life_expectancy - clients_age]] < 0).sum() / (\\n trials + 1)\\n\\n legacy_risk = pd.DataFrame([base_legacy_risk, port_legacy_risk,\\n 'Prob. of portfolio value less than 0 at the end of the expected life'],\\n index=['base', 'fia_portfolio', 'Notes'],\\n columns=['Ruin Probability'])\\n\\n # -----------Year-wise probability of ending value greater than 0 -----------------\\n base_psuccess = sim_base_total.apply(lambda x: x > 0).sum(axis=1) / (trials + 1)\\n port_psuccess = sim_port_total.apply(lambda x: x > 0).sum(axis=1) / (trials + 1)\\n\\n # -----------------------WRITING FILES TO EXCEL ---------------------------\\n col_names = ['50th', 'age', 'comment']\\n writer = pd.ExcelWriter(src + method + '_historical_simulated_income_summary.xlsx', engine='xlsxwriter')\\n read_income_inputs.to_excel(writer, sheet_name='inputs_for_income')\\n\\n read_returns_est.to_excel(writer, sheet_name='asset_returns_estimates')\\n\\n age_index = list(range(clients_age + 1, clients_age + len(base_qcut) + 1))\\n base_qcut.loc[:, 'age'] = age_index\\n base_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n base_qcut.loc[income_starts:, col_names].to_excel(writer, sheet_name='base_ending_value_quantiles')\\n\\n base_income_qcut = base_income_qcut.loc[1:, :]\\n base_income_qcut.loc[:, 'age'] = age_index\\n base_income_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n base_income_qcut.loc[income_starts:, col_names].to_excel(writer, sheet_name='base_income_quantiles')\\n\\n port_qcut.loc[:, 'age'] = age_index\\n port_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n port_qcut.loc[income_starts:, col_names].to_excel(writer, sheet_name='fia_port_ending_value_quantiles')\\n\\n port_income_qcut = port_income_qcut.loc[1:, :]\\n port_income_qcut.loc[:, 'age'] = age_index\\n port_income_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n port_income_qcut.loc[income_starts:, col_names].to_excel(writer, sheet_name='fia_port_income_quantiles')\\n\\n # prob_success_df = pd.concat([base_psuccess, port_psuccess], axis=1)\\n # prob_success_df.rename(columns={prob_success_df.columns[0]: 'prob(ending_value>0)_base',\\n # prob_success_df.columns[1]: 'prob(ending_value>0)_port'}, inplace=True)\\n\\n # prob_success_df.loc[:, 'age'] = age_index\\n # prob_success_df.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n # prob_success_df.to_excel(writer, sheet_name='success_probability')\\n\\n income_breakdown_base = income_breakdown_base.loc[1:, :]\\n income_breakdown_base.loc[:, 'age'] = age_index\\n income_breakdown_base.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n income_breakdown_base.loc[income_starts:, :].to_excel(writer, sheet_name='base_income_breakdown_median')\\n\\n income_breakdown_port = income_breakdown_port.loc[1:, :]\\n income_breakdown_port.loc[:, 'age'] = age_index\\n income_breakdown_port.loc[:, 'ending contract value'] = income_df.loc[:, 'contract_value'].fillna(0)\\n income_breakdown_port.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n\\n income_breakdown_port.loc[income_starts:, :].to_excel(writer, sheet_name='fia_income_breakdown_median')\\n\\n if method == 'normal':\\n # median_returns_normal.loc[:, 'fia_median_returns'] = median_normal_fia\\n # median_returns_normal.to_excel(writer, sheet_name='unsorted_port_return')\\n save_normal.to_excel(writer, sheet_name='port_return_unsorted')\\n\\n elif method == 'smallest':\\n # median_returns_smallest.loc[:, 'fia_median_returns'] = median_smallest_fia\\n # median_returns_smallest.to_excel(writer, sheet_name='port_return_asc')\\n save_asc.to_excel(writer, sheet_name='port_return_asc')\\n\\n else:\\n # median_returns_largest.loc[:, 'fia_median_returns'] = median_largest_fia\\n # median_returns_largest.to_excel(writer, sheet_name='port_return_desc')\\n save_desc.to_excel(writer, sheet_name='port_return_desc')\\n\\n # terminal_val = pd.read_csv(src + 'terminal_values.csv', index_col=[0])\\n # ending_val = pd.read_csv(src + 'ending_values.csv', index_col=[0])\\n # ending_val_ror = pd.read_csv(src + 'ending_values_ror.csv', index_col=[0])\\n\\n # terminal_val.to_excel(writer, sheet_name='terminal_values')\\n # ending_val.to_excel(writer, sheet_name='port_ending_values')\\n # ending_val_ror.to_excel(writer, sheet_name='port_annual_growth')\\n\\n writer.save()\\n\\n # -----------------Plotting charts--------------------------------------------\\n # base_qcut.loc[income_starts:].plot(grid=True, title='Quantile Terminal Value - Base Portfolio')\\n # plt.savefig(src + \\\"quantile_terminal_base.png\\\")\\n # plt.close('all')\\n #\\n # base_income_qcut.plot(grid=True, title='Quantile Income - Base Portfolio')\\n # plt.savefig(src + \\\"quantile_income_base.png\\\")\\n # plt.close('all')\\n #\\n # base_psuccess.plot(grid=True, title='Probability of Success (Portfolio Ending Value > 0) - Base Portfolio')\\n # plt.savefig(src + \\\"success_probabilty_base.png\\\")\\n # plt.close('all')\\n #\\n # (1 - base_psuccess).plot(grid=True, title='Probability of Ruin (Portfolio Ending Value < 0) - Base Portfolio')\\n # plt.savefig(src + \\\"ruin_probability_base.png\\\")\\n # plt.close('all')\\n #\\n # port_qcut.loc[income_starts:].plot(grid=True, title='Quantile Terminal Value - FIA Portfolio')\\n # plt.savefig(src + \\\"quantile_terminal_fia.png\\\")\\n # plt.close('all')\\n #\\n # port_income_qcut.plot(grid=True, title='Quantile Income - FIA Portfolio')\\n # plt.savefig(src + \\\"quantile_income_fia.png\\\")\\n # plt.close('all')\\n #\\n # port_psuccess.plot(grid=True, title='Probability of Success (Portfolio Ending Value > 0) - FIA Portfolio')\\n # plt.savefig(src + \\\"success_probabilty_fia.png\\\")\\n # plt.close('all')\\n #\\n # (1 - port_psuccess).plot(grid=True, title='Probability of Ruin (Portfolio Ending Value < 0) - FIA Portfolio')\\n # plt.savefig(src + \\\"ruin_probability_fia.png\\\")\\n # plt.close('all')\\n\\n print(\\\"simulation completed for {}\\\".format(method))\",\n \"def target_portfolio_simulation(num_of_years=30, trials=100, method='normal'):\\n print(\\\"Running method target_portfolio_simulation()\\\")\\n\\n sim_fia_cv = pd.DataFrame(index=range(num_of_years + 1))\\n\\n sim_base_total = pd.DataFrame(index=range(num_of_years + 1))\\n sim_base_income = pd.DataFrame(index=range(num_of_years + 1))\\n\\n sim_port_total = pd.DataFrame(index=range(num_of_years + 1))\\n sim_port_income = pd.DataFrame(index=range(num_of_years + 1))\\n\\n read_income_inputs = pd.read_excel(src + \\\"portfolio_information.xlsx\\\", sheet_name='income_model_inputs',\\n index_col=[0])\\n\\n read_returns_est = pd.read_excel(src + \\\"portfolio_information.xlsx\\\", sheet_name='income_assets_returns_estimates',\\n index_col=[0])\\n\\n read_asset_weights = pd.read_excel(src + \\\"portfolio_information.xlsx\\\", sheet_name='asset_weights',\\n index_col=[0])\\n\\n # read_asset_weights.drop(read_asset_weights.index[-1], axis=0, inplace=True)\\n\\n # read random returns for simulation\\n read_normal = pd.read_csv(src + 'median_returns_unsorted.csv', index_col=[0], parse_dates=True)\\n cols = [read_normal.columns[c].split('_')[1] for c in np.arange(len(read_normal.columns))]\\n read_normal.rename(columns=dict(zip(list(read_normal.columns), cols)), inplace=True)\\n\\n read_small = pd.read_csv(src + 'median_returns_smallest.csv', index_col=[0], parse_dates=True)\\n read_small.rename(columns=dict(zip(list(read_small.columns), cols)), inplace=True)\\n\\n read_large = pd.read_csv(src + 'median_returns_largest.csv', index_col=[0], parse_dates=True)\\n read_large.rename(columns=dict(zip(list(read_large.columns), cols)), inplace=True)\\n\\n assets_col_names = list(read_normal.columns)\\n\\n tickers = list(read_asset_weights.index)\\n wts = np.array(read_asset_weights.loc[:, 'base'])\\n\\n def asset_median_returns(data, ticker):\\n return data.filter(regex=ticker).median(axis=1)\\n\\n # dataframe for unsorted returns (normal)\\n median_returns_normal = read_normal.copy()\\n median_returns_normal.loc[:, 'portfolio_return'] = median_returns_normal.dot(wts)\\n median_normal_fia = pd.DataFrame({'FIA': asset_median_returns(read_normal, 'FIA')})\\n\\n # dataframe for smallest to largest returns\\n median_returns_smallest = read_small.copy()\\n median_returns_smallest.loc[:, 'portfolio_return'] = median_returns_smallest.dot(wts)\\n median_smallest_fia = pd.DataFrame({'FIA': asset_median_returns(read_small, 'FIA')})\\n\\n # dataframe for largest to smallest returns\\n median_returns_largest = read_large.copy()\\n median_returns_largest.loc[:, 'portfolio_return'] = median_returns_largest.dot(wts)\\n median_largest_fia = pd.DataFrame({'FIA': asset_median_returns(read_large, 'FIA')})\\n\\n years = list(range(0, num_of_years + 1))\\n income_cols = ['year', 'strategy_term', 'index_returns', 'term_ret', 'term_ret_with_par', 'term_annualize',\\n 'ann_net_spread', 'term_ret_netspr', 'high_inc_benefit_base', 'rider_fee', 'eoy_income',\\n 'contract_value']\\n\\n term = int(read_income_inputs.loc['term', 'inputs'])\\n fia_ret = read_returns_est.loc[read_returns_est.index[-1], 'Annualized Returns']\\n fia_risk = read_returns_est.loc[read_returns_est.index[-1], 'Annualized Risk']\\n par_rate = float(read_income_inputs.loc['par_rate', 'inputs'])\\n spread = float(read_income_inputs.loc['spread', 'inputs'])\\n bonus_term = int(read_income_inputs.loc['bonus_term', 'inputs'])\\n premium = float(read_income_inputs.loc['premium', 'inputs'])\\n income_bonus = float(read_income_inputs.loc['income_bonus', 'inputs'])\\n\\n income_starts = int(read_income_inputs.loc['start_income_years', 'inputs'])\\n income_growth = float(read_income_inputs.loc['income_growth', 'inputs'])\\n rider_fee = float(read_income_inputs.loc['rider_fee', 'inputs'])\\n inc_payout_factor = float(read_income_inputs.loc['income_payout_factor', 'inputs'])\\n contract_bonus = float(read_income_inputs.loc['contract_bonus', 'inputs'])\\n social = float(read_income_inputs.loc['social', 'inputs'])\\n inflation = float(read_income_inputs.loc['inflation', 'inputs'])\\n wtd_cpn_yield = float(read_income_inputs.loc['wtd_coupon_yld', 'inputs'])\\n life_expectancy = int(read_income_inputs.loc['life_expectancy_age', 'inputs'])\\n clients_age = int(read_income_inputs.loc['clients_age', 'inputs'])\\n\\n # ---------------INCOME MODEL--------------------------------------------\\n runs = 0\\n returns_dict = {}\\n asset_dict = {}\\n fia_dict = {}\\n\\n income_df = pd.DataFrame(index=years, columns=income_cols)\\n income_df.loc[:, 'year'] = years\\n income_df.loc[:, 'strategy_term'] = income_df.loc[:, 'year'] % term\\n income_df.loc[:, 'strategy_term'] = income_df['strategy_term'].apply(lambda x: 1 if x == 0 else 0)\\n\\n if method == 'normal':\\n income_df.loc[:, 'index_returns'] = read_normal.loc[:, 'FIA']\\n\\n elif method == 'smallest':\\n income_df.loc[:, 'index_returns'] = read_small.loc[:, 'FIA']\\n\\n else:\\n income_df.loc[:, 'index_returns'] = read_large.loc[:, 'FIA']\\n\\n # income_df.loc[:, 'index_returns'] = np.random.normal(fia_ret, fia_risk, size=(len(years), 1))\\n\\n cumprod = (1. + income_df['index_returns']).rolling(window=term).agg(lambda x: x.prod()) - 1\\n income_df.loc[:, 'term_ret'] = np.where(income_df.loc[:, 'strategy_term'] == 1, cumprod, 0)\\n income_df.loc[:, 'term_ret_with_par'] = income_df.loc[:, 'term_ret'] * par_rate\\n income_df.loc[:, 'term_annualize'] = income_df.loc[:, 'term_ret_with_par'].apply(\\n lambda x: (1 + x) ** (1 / term) - 1)\\n income_df.loc[:, 'ann_net_spread'] = income_df.loc[:, 'term_annualize'] - spread\\n income_df.loc[:, 'ann_net_spread'] = np.where(income_df.loc[:, 'strategy_term'] == 1,\\n income_df.loc[:, 'ann_net_spread'], 0)\\n income_df.loc[:, 'term_ret_netspr'] = income_df.loc[:, 'ann_net_spread'].apply(lambda x: (1 + x) ** term - 1)\\n\\n for counter in years:\\n if counter == 0:\\n income_df.loc[counter, 'high_inc_benefit_base'] = premium * (1 + income_bonus)\\n\\n elif counter <= min(bonus_term, income_starts):\\n income_df.loc[counter, 'high_inc_benefit_base'] = income_df.loc[counter - 1, 'high_inc_benefit_base'] * \\\\\\n (1 + income_growth)\\n else:\\n income_df.loc[counter, 'high_inc_benefit_base'] = income_df.loc[counter - 1, 'high_inc_benefit_base']\\n\\n income_df.loc[:, 'rider_fee'] = income_df.loc[:, 'high_inc_benefit_base'] * rider_fee\\n income_df.loc[:, 'eoy_income'] = np.where(income_df.loc[:, 'year'] > income_starts,\\n income_df.loc[:, 'high_inc_benefit_base'] * inc_payout_factor, 0)\\n\\n for counter in years:\\n if counter == 0:\\n income_df.loc[counter, 'contract_value'] = premium * (1 + contract_bonus)\\n\\n elif income_df.loc[counter, 'strategy_term'] == 1:\\n x1 = income_df.loc[counter - 1, 'contract_value'] - income_df.loc[counter, 'rider_fee']\\n x2 = (x1 * (1 + income_df.loc[counter, 'term_ret_netspr'])) - income_df.loc[counter, 'eoy_income']\\n income_df.loc[counter, 'contract_value'] = x2\\n\\n else:\\n x1 = income_df.loc[counter - 1, 'contract_value'] - income_df.loc[counter, 'rider_fee'] - \\\\\\n income_df.loc[counter, 'eoy_income']\\n\\n income_df.loc[counter, 'contract_value'] = x1\\n\\n # variable stores the income number that is used in the base and fia portfolio calcs.\\n\\n income_from_fia = income_df.loc[income_df.index[-1], 'eoy_income']\\n\\n income_df.loc[:, 'contract_value'] = income_df.loc[:, 'contract_value'].apply(lambda x: 0 if x <= 0 else x)\\n\\n sim_fia_cv.loc[:, str(runs)] = income_df.loc[:, 'contract_value']\\n\\n # --------------------BASE MODEL---------------------------------------------\\n base_wts = read_asset_weights.loc[:, 'base']\\n base_assets = list(base_wts.index)\\n base_weights = list(base_wts.values)\\n base_returns = list(read_returns_est.loc[:, 'Annualized Returns'].values)\\n base_std = list(read_returns_est.loc[:, 'Annualized Risk'].values)\\n\\n base_investment = float(read_income_inputs.loc['risky_assets', 'Base'])\\n adv_fees = float(read_income_inputs.loc['advisor_fees', 'Base'])\\n\\n # -------------------required income----------------------------------\\n req_annual_income = float(read_income_inputs.loc['annual_income', 'inputs'])\\n income_needed = req_annual_income - social\\n income_net_fia_income = max(0, income_needed - income_from_fia)\\n cpn_income_base = base_investment * wtd_cpn_yield\\n\\n # ----------------------RANDOM RETURNS--------------------------\\n r_cols = base_assets\\n boy_value = ['bv_{}'.format(name) for name in base_assets]\\n eoy_value = ['ev_{}'.format(name) for name in base_assets]\\n\\n random_returns = pd.DataFrame(index=income_df.index, columns=r_cols)\\n\\n for c in range(len(r_cols)):\\n ret = np.random.normal(base_returns[c], base_std[c], size=(len(random_returns.index), 1))\\n\\n if method == 'smallest':\\n random_returns = read_small.copy()\\n\\n elif method == 'largest':\\n random_returns = read_large.copy()\\n\\n else:\\n random_returns = read_normal.copy()\\n\\n base_df = random_returns.copy()\\n fia_portfolio_df = random_returns.copy()\\n port_investment = float(read_income_inputs.loc['risky_assets', 'FIA'])\\n cpn_income_port = port_investment * wtd_cpn_yield\\n\\n # -------------BASE PORTFOLIO----------------------------\\n for name in boy_value:\\n base_df.loc[:, name] = 0.0\\n\\n for counter in years:\\n period_returns = list(random_returns.loc[counter, :])\\n if counter == 0:\\n\\n base_df.loc[counter, boy_value] = [base_weights[c] * base_investment for c in range(len(boy_value))]\\n\\n base_df.loc[counter, 'total'] = base_df.loc[counter, boy_value].sum()\\n base_df.loc[counter, 'total_net_fees'] = 0.0\\n base_df.loc[counter, 'income'] = 0.0\\n base_investment = base_df.loc[counter, boy_value].sum()\\n\\n elif (counter > 0) and (counter < income_starts):\\n\\n base_df.loc[counter, boy_value] = [base_weights[c] * base_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n base_df.loc[counter, 'total'] = base_df.loc[counter, boy_value].sum()\\n base_df.loc[counter, 'adv_fees'] = base_df.loc[counter, 'total'] * adv_fees\\n base_df.loc[counter, 'total_net_fees'] = base_df.loc[counter, 'total'] - base_df.loc[\\n counter, 'adv_fees']\\n\\n # --coupon payment is invested back into the risky portfolio until the income is withdrawn----\\n base_investment = base_df.loc[counter, 'total_net_fees'] + cpn_income_base\\n\\n else:\\n\\n base_df.loc[counter, boy_value] = [base_weights[c] * base_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n base_df.loc[counter, 'total'] = base_df.loc[counter, boy_value].sum()\\n base_df.loc[counter, 'adv_fees'] = base_df.loc[counter, 'total'] * adv_fees\\n\\n # ---req. income is adjusted for inflation from the second year of withdrawal. Reinvestment of coupon\\n # stops from the year income starts. Req. income is reduced by the coupon payments\\n\\n if counter == income_starts:\\n\\n income_needed = req_annual_income - social\\n base_df.loc[counter, 'income'] = income_needed - cpn_income_base\\n income_needed = req_annual_income\\n\\n else:\\n income_needed = income_needed * (1 + inflation) - social\\n base_df.loc[counter, 'income'] = income_needed - cpn_income_base\\n income_needed = income_needed + social\\n\\n base_df.loc[counter, 'total_net_fees'] = base_df.loc[counter, 'total'] - \\\\\\n base_df.loc[counter, 'adv_fees'] - \\\\\\n base_df.loc[counter, 'income']\\n\\n base_investment = base_df.loc[counter, 'total_net_fees']\\n\\n base_df.loc[:, 'adj_total'] = base_df.loc[:, 'total_net_fees'].apply(lambda x: x if x > 0 else 0)\\n sim_base_total.loc[:, 's_{}'.format(str(runs))] = base_df.loc[:, 'total_net_fees']\\n sim_base_income.loc[:, 's_{}'.format(str(runs))] = base_df.loc[:, 'income']\\n\\n # ----------------------------FIA PORTFOLIO----------------------------------------------\\n for name in boy_value:\\n fia_portfolio_df.loc[:, name] = 0.0\\n\\n for counter in years:\\n period_returns = list(random_returns.loc[counter, :])\\n if counter == 0:\\n\\n fia_portfolio_df.loc[counter, boy_value] = [base_weights[c] * port_investment\\n for c in range(len(boy_value))]\\n fia_portfolio_df.loc[counter, 'total'] = fia_portfolio_df.loc[counter, boy_value].sum()\\n fia_portfolio_df.loc[counter, 'total_net_fees'] = 0.0\\n fia_portfolio_df.loc[counter, 'income'] = 0.0\\n port_investment = fia_portfolio_df.loc[counter, boy_value].sum()\\n\\n elif (counter > 0) and (counter < income_starts):\\n\\n fia_portfolio_df.loc[counter, boy_value] = [base_weights[c] * port_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n fia_portfolio_df.loc[counter, 'total'] = fia_portfolio_df.loc[counter, boy_value].sum()\\n fia_portfolio_df.loc[counter, 'adv_fees'] = fia_portfolio_df.loc[counter, 'total'] * adv_fees\\n fia_portfolio_df.loc[counter, 'total_net_fees'] = fia_portfolio_df.loc[counter, 'total'] - \\\\\\n fia_portfolio_df.loc[counter, 'adv_fees']\\n\\n port_investment = fia_portfolio_df.loc[counter, 'total_net_fees'] + cpn_income_port\\n\\n else:\\n fia_portfolio_df.loc[counter, boy_value] = [base_weights[c] * port_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n fia_portfolio_df.loc[counter, 'total'] = fia_portfolio_df.loc[counter, boy_value].sum()\\n fia_portfolio_df.loc[counter, 'adv_fees'] = fia_portfolio_df.loc[counter, 'total'] * adv_fees\\n\\n # ---req. income is adjusted for inflation from the second year of withdrawal. Reinvestment of coupon\\n # stops from the year income starts. Req. income is reduced by the coupon payments\\n\\n if counter == income_starts:\\n\\n income_needed = req_annual_income - social\\n income_net_fia_income = max(0, income_needed - income_from_fia)\\n fia_portfolio_df.loc[counter, 'income'] = max(0, income_net_fia_income - cpn_income_port)\\n income_needed = req_annual_income\\n\\n else:\\n income_needed = income_needed * (1 + inflation) - social\\n income_net_fia_income = max(0, income_needed - income_from_fia)\\n fia_portfolio_df.loc[counter, 'income'] = max(0, income_net_fia_income - cpn_income_port)\\n income_needed = income_needed + social\\n\\n fia_portfolio_df.loc[counter, 'total_net_fees'] = fia_portfolio_df.loc[counter, 'total'] - \\\\\\n fia_portfolio_df.loc[counter, 'adv_fees'] - \\\\\\n fia_portfolio_df.loc[counter, 'income']\\n\\n port_investment = fia_portfolio_df.loc[counter, 'total_net_fees']\\n\\n sim_port_total.loc[:, 's_{}'.format(str(runs))] = fia_portfolio_df.loc[:, 'total_net_fees'] + \\\\\\n income_df.loc[:, 'contract_value']\\n\\n sim_port_income.loc[:, 's_{}'.format(str(runs))] = fia_portfolio_df.loc[:, 'income']\\n\\n fia_portfolio_df.loc[:, 'adj_total'] = fia_portfolio_df.loc[:, 'total_net_fees'].apply(\\n lambda x: x if x > 0 else 0)\\n\\n # ---------income breakdown for Base portfolio----------------------------------\\n base_df.to_csv(src + 'base_port_detail.csv')\\n sim_base_total.to_csv(src + 'base_ending_values.csv')\\n income_breakdown_base = pd.DataFrame(sim_base_total.quantile(0.5, axis=1))\\n income_breakdown_base.loc[:, 'income_from_portfolio'] = sim_base_income.quantile(0.5, axis=1)\\n income_breakdown_base.loc[:, 'fia_income'] = 0.0\\n income_breakdown_base.loc[:, 'social_security_income'] = social\\n income_breakdown_base.loc[:, 'coupon_income'] = cpn_income_base\\n\\n income_breakdown_base.rename(columns={income_breakdown_base.columns[0]: 'portfolio_ending_value'}, inplace=True)\\n income_breakdown_base.loc[:, 'income_from_portfolio'][\\n income_breakdown_base.loc[:, 'portfolio_ending_value'] <= 0] = 0\\n income_breakdown_base.loc[:, 'total_income'] = income_breakdown_base.loc[:, income_breakdown_base.columns[1:]].sum(\\n axis=1)\\n\\n # ------------Block Ends-------------------------------------------------------------\\n\\n # ---------income breakdown for FIA portfolio----------------------------------\\n fia_portfolio_df.to_csv(src + 'fia_port_detail.csv')\\n sim_port_total.to_csv(src + 'fiaport_ending_values.csv')\\n\\n income_breakdown_port = pd.DataFrame(sim_port_total.quantile(0.5, axis=1))\\n income_breakdown_port.loc[:, 'income_from_portfolio'] = sim_port_income.quantile(0.5, axis=1)\\n income_breakdown_port.loc[:, 'fia_income'] = income_from_fia\\n income_breakdown_port.loc[:, 'social_security_income'] = social\\n income_breakdown_port.loc[:, 'coupon_income'] = cpn_income_port\\n\\n income_breakdown_port.rename(columns={income_breakdown_port.columns[0]: 'portfolio_ending_value'}, inplace=True)\\n income_breakdown_port.loc[:, 'income_from_portfolio'][\\n income_breakdown_port.loc[:, 'portfolio_ending_value'] <= 0] = 0\\n income_breakdown_port.loc[:, 'total_income'] = income_breakdown_port.loc[:, income_breakdown_port.columns[1:]].sum(\\n axis=1)\\n\\n # ------------Block Ends-------------------------------------------------------------\\n q_cut = [0.0, 0.05, 0.25, 0.5, 0.75, 0.95, 1.0]\\n sim_base_income[sim_base_total < income_needed] = 0.0\\n\\n sim_port_income[sim_port_total < income_net_fia_income] = 0\\n\\n sim_port_income = sim_port_income + income_from_fia\\n\\n # base_quantile = sim_base_total.loc[sim_base_total.index[-1]].quantile([0.05, 0.25, 0.50, 0.75, 0.90])\\n\\n # port_quantile = sim_port_total.loc[sim_port_total.index[-1]].quantile([0.05, 0.25, 0.50, 0.75, 0.90])\\n\\n base_quantile = sim_base_total.loc[sim_base_total.index[-1]].quantile(q_cut)\\n\\n port_quantile = sim_port_total.loc[sim_port_total.index[-1]].quantile(q_cut)\\n\\n # q_cut = [0.0, .05, 0.25, 0.5, 0.75, 0.95, 1.0]\\n cols = ['Min', '5th', '25th', '50th', '75th', '90th', 'Max']\\n\\n # ----drop year 0--------\\n sim_base_total = sim_base_total[1:]\\n sim_port_total = sim_port_total[1:]\\n\\n # ----------------quantile analysis for base terminal value--------------------------\\n base_qcut = pd.DataFrame(index=sim_base_total.index, columns=cols)\\n for c in range(len(cols)):\\n base_qcut.loc[:, cols[c]] = sim_base_total.quantile(q_cut[c], axis=1)\\n\\n base_qcut.clip(lower=0, inplace=True)\\n\\n # ----------------------quantile analysis for base income----------------------------\\n base_income_qcut = pd.DataFrame(index=sim_base_income.index, columns=cols)\\n for c in range(len(cols)):\\n base_income_qcut.loc[:, cols[c]] = sim_base_income.quantile(q_cut[c], axis=1)\\n\\n # ----Remove NaN's prior to the income start years------------\\n # base_income_qcut = base_income_qcut.loc[income_starts:]\\n\\n # -------------quantile analysis for portfolio terminal value ----------------\\n port_qcut = pd.DataFrame(index=sim_port_total.index, columns=cols)\\n for c in range(len(cols)):\\n port_qcut.loc[:, cols[c]] = sim_port_total.quantile(q_cut[c], axis=1)\\n\\n port_qcut.clip(lower=0, inplace=True)\\n\\n # ---------------quantile analysis for portfolio income----------------------------\\n port_income_qcut = pd.DataFrame(index=sim_port_income.index, columns=cols)\\n for c in range(len(cols)):\\n port_income_qcut.loc[:, cols[c]] = sim_port_income.quantile(q_cut[c], axis=1)\\n\\n # ----Remove NaN's prior to the income start years------------\\n # port_income_qcut = port_income_qcut.loc[income_starts:]\\n\\n # ----------probability ending value will be less than 0 at the end of the horizon -----------------------\\n base_legacy_risk = (sim_base_total.loc[sim_base_total.index[life_expectancy - clients_age]] < 0).sum() / (\\n trials + 1)\\n port_legacy_risk = (sim_port_total.loc[sim_port_total.index[life_expectancy - clients_age]] < 0).sum() / (\\n trials + 1)\\n\\n legacy_risk = pd.DataFrame([base_legacy_risk, port_legacy_risk,\\n 'Prob. of portfolio value less than 0 at the end of the expected life'],\\n index=['base', 'fia_portfolio', 'Notes'],\\n columns=['Ruin Probability'])\\n\\n # -----------Year-wise probability of ending value greater than 0 -----------------\\n base_psuccess = sim_base_total.apply(lambda x: x > 0).sum(axis=1) / (trials + 1)\\n port_psuccess = sim_port_total.apply(lambda x: x > 0).sum(axis=1) / (trials + 1)\\n\\n # -----------------------WRITING FILES TO EXCEL ---------------------------\\n col_names = ['50th', 'age', 'comment']\\n writer = pd.ExcelWriter(src + method + '_simulated_income_summary.xlsx', engine='xlsxwriter')\\n read_income_inputs.to_excel(writer, sheet_name='inputs_for_income')\\n\\n read_returns_est.to_excel(writer, sheet_name='asset_returns_estimates')\\n\\n age_index = list(range(clients_age + 1, clients_age + len(base_qcut) + 1))\\n base_qcut.loc[:, 'age'] = age_index\\n base_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n base_qcut.loc[income_starts:, col_names].to_excel(writer, sheet_name='base_ending_value_quantiles')\\n\\n base_income_qcut = base_income_qcut.loc[1:, :]\\n base_income_qcut.loc[:, 'age'] = age_index\\n base_income_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n base_income_qcut.loc[income_starts:, col_names].to_excel(writer, sheet_name='base_income_quantiles')\\n\\n port_qcut.loc[:, 'age'] = age_index\\n port_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n port_qcut.loc[income_starts:, col_names].to_excel(writer, sheet_name='fia_port_ending_value_quantiles')\\n\\n port_income_qcut = port_income_qcut.loc[1:, :]\\n port_income_qcut.loc[:, 'age'] = age_index\\n port_income_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n # port_income_qcut.loc[:, 'ending_contract_value'] = sim_fia_cv\\n port_income_qcut.loc[income_starts:, col_names].to_excel(writer, sheet_name='fia_port_income_quantiles')\\n\\n # prob_success_df = pd.concat([base_psuccess, port_psuccess], axis=1)\\n # prob_success_df.rename(columns={prob_success_df.columns[0]: 'prob(ending_value>0)_base',\\n # prob_success_df.columns[1]: 'prob(ending_value>0)_port'}, inplace=True)\\n\\n # prob_success_df.loc[:, 'age'] = age_index\\n # prob_success_df.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n # prob_success_df.to_excel(writer, sheet_name='success_probability')\\n\\n income_breakdown_base = income_breakdown_base.loc[1:, :]\\n income_breakdown_base.loc[:, 'age'] = age_index\\n income_breakdown_base.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n income_breakdown_base.loc[income_starts:, :].to_excel(writer, sheet_name='base_income_breakdown_median')\\n\\n income_breakdown_port = income_breakdown_port.loc[1:, :]\\n income_breakdown_port.loc[:, 'age'] = age_index\\n income_breakdown_port.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n income_breakdown_port.loc[:, 'ending_contract_value'] = income_df.loc[:, 'contract_value']\\n income_breakdown_port.loc[income_starts:, :].to_excel(writer, sheet_name='fia_income_breakdown_median')\\n\\n if method == 'normal':\\n # median_returns_normal.loc[:, 'fia_median_returns'] = median_normal_fia\\n median_returns_normal.to_excel(writer, sheet_name='gr_port_median_normal')\\n\\n elif method == 'smallest':\\n # median_returns_smallest.loc[:, 'fia_median_returns'] = median_smallest_fia\\n median_returns_smallest.to_excel(writer, sheet_name='gr_port_median_asc')\\n\\n else:\\n # median_returns_largest.loc[:, 'fia_median_returns'] = median_largest_fia\\n median_returns_largest.to_excel(writer, sheet_name='gr_port_median_desc')\\n\\n terminal_val = pd.read_csv(src + 'terminal_values.csv', index_col=[0])\\n ending_val = pd.read_csv(src + 'ending_values.csv', index_col=[0])\\n ending_val_ror = pd.read_csv(src + 'ending_values_ror.csv', index_col=[0])\\n\\n terminal_val.to_excel(writer, sheet_name='terminal_values')\\n ending_val.to_excel(writer, sheet_name='port_ending_values')\\n ending_val_ror.to_excel(writer, sheet_name='port_annual_growth')\\n\\n writer.save()\\n\\n # -----------------Plotting charts--------------------------------------------\\n base_qcut.loc[income_starts:].plot(grid=True, title='Quantile Terminal Value - Base Portfolio')\\n plt.savefig(src + \\\"quantile_terminal_base.png\\\")\\n plt.close('all')\\n\\n base_income_qcut.plot(grid=True, title='Quantile Income - Base Portfolio')\\n plt.savefig(src + \\\"quantile_income_base.png\\\")\\n plt.close('all')\\n\\n base_psuccess.plot(grid=True, title='Probability of Success (Portfolio Ending Value > 0) - Base Portfolio')\\n plt.savefig(src + \\\"success_probabilty_base.png\\\")\\n plt.close('all')\\n\\n (1 - base_psuccess).plot(grid=True, title='Probability of Ruin (Portfolio Ending Value < 0) - Base Portfolio')\\n plt.savefig(src + \\\"ruin_probability_base.png\\\")\\n plt.close('all')\\n\\n port_qcut.loc[income_starts:].plot(grid=True, title='Quantile Terminal Value - FIA Portfolio')\\n plt.savefig(src + \\\"quantile_terminal_fia.png\\\")\\n plt.close('all')\\n\\n port_income_qcut.plot(grid=True, title='Quantile Income - FIA Portfolio')\\n plt.savefig(src + \\\"quantile_income_fia.png\\\")\\n plt.close('all')\\n\\n port_psuccess.plot(grid=True, title='Probability of Success (Portfolio Ending Value > 0) - FIA Portfolio')\\n plt.savefig(src + \\\"success_probabilty_fia.png\\\")\\n plt.close('all')\\n\\n (1 - port_psuccess).plot(grid=True, title='Probability of Ruin (Portfolio Ending Value < 0) - FIA Portfolio')\\n plt.savefig(src + \\\"ruin_probability_fia.png\\\")\\n plt.close('all')\\n\\n print(\\\"simulation completed for {}\\\".format(method))\",\n \"def po_analysis():\\r\\n\\r\\n global params\\r\\n n = params['n']\\r\\n level = params['level']\\r\\n pomin = params['pomin']\\r\\n pomax = params['pomax']\\r\\n postep = params['postep']\\r\\n ns = params['ns']\\r\\n nt = params['nt']\\r\\n pe = params['pe']\\r\\n pf = params['pf']\\r\\n po_dir = create_dir(TIMES_PATH + 'po')\\r\\n filename = datetime.datetime.now().strftime(DATE_FORMAT) + '.csv'\\r\\n with open(po_dir + filename, 'wb') as csvfile:\\r\\n fw = csv.writer(csvfile)\\r\\n fw.writerow(('lv', 'ns', 'nt', 'po', 'no', 'ne', 'nf',\\r\\n 'method1', 'method2', 'method3_1', 'method3_2'))\\r\\n po = pomin\\r\\n while po <= pomax:\\r\\n no = max(int(round(po * nt)), 1)\\r\\n ne = max(int(round(pe * no)), 1)\\r\\n nf = max(int(round(pf * nt)), 1)\\r\\n times = [0] * 4\\r\\n for i in range(n):\\r\\n times = map(sum, zip(times, get_times(level, ns, nt, no, ne, nf)))\\r\\n show_progress('po', po, pomin, pomax, postep, i, n)\\r\\n times = map(lambda x: float(x) / n, times)\\r\\n fw.writerow((level, ns, nt, po, no, ne, nf) + tuple(times))\\r\\n po += postep\\r\\n csvfile.close()\",\n \"def get_filters():\\n\\n print(\\\"Hello there! Let's explore some data!\\\")\\n\\n legit_cities = ['chicago', 'new york city', 'washington'] # cities im gonna accept\\n city = input(\\\"\\\\nWhich city do you want to analyze? Chicago, New York City or Washington?\\\\n\\\").lower()\\n while city not in legit_cities:\\n print(\\\"There is no such city in database!\\\")\\n city = input(\\\"\\\\nWhich city do you want to analyze?\\\\n\\\").lower()\\n\\n city = city.replace(\\\" \\\", \\\"_\\\")\\n\\n possible_answers = ['month', 'day', 'both', 'none'] # answers im gonna accept - 4 possibilities\\n answer = input(\\\"\\\\nFilter by 'month','day' or 'both'? If you don't want to filter type 'none'\\\\n\\\").lower()\\n while answer not in possible_answers:\\n print(\\\"WAAT?!\\\")\\n answer = input(\\\"\\\\nFilter by 'month','day' or 'both'? If you don't want to filter type 'none'\\\\n\\\").lower()\\n\\n\\n legit_months = ['Jan', \\\"Feb\\\", \\\"Mar\\\", \\\"Apr\\\", \\\"May\\\", \\\"Jun\\\"]\\n legit_days = ['Mon', 'Tue', 'Wed', 'Thu', 'Fry', 'Sat', 'Sun']\\n month, day = 'all_months', 'all_days'\\n\\n if answer == 'both':\\n month = input(\\\"\\\\nWhich month do you want to analyze? Jan, Feb ,.., Jun\\\\n\\\").capitalize()\\n while month not in legit_months:\\n print('There is no such month! Try again.')\\n month = input(\\\"\\\\nWhich month do you want to analyze?\\\\n\\\").capitalize()\\n day = input(\\\"\\\\nChoose a day of interest - Mon, Tue, ...\\\\n\\\").capitalize()\\n while day not in legit_days:\\n print(\\\"There is no such day! Try again.\\\")\\n day = input(\\\"\\\\nWhich day do you want to analyze? Mon, Tue, Wed...\\\\n\\\").capitalize()\\n elif answer == \\\"month\\\":\\n month = input(\\\"\\\\nWhich month do you want to analyze? Jan, Feb, ..., Jun\\\\n\\\").capitalize()\\n while month not in legit_months:\\n print('There is no such month! Try again.')\\n month = input(\\\"\\\\nWhich month do you want to analyze?\\\\n\\\").capitalize()\\n elif answer == 'day':\\n day = input(\\\"\\\\nChoose a day of interest - Mon, Tue, Wed...\\\\n\\\").capitalize()\\n while day not in legit_days:\\n print(\\\"There is no such day! Try again.\\\")\\n day = input(\\\"\\\\nWhich day do you want to analyze?\\\\n\\\").capitalize()\\n return city, month, day\\n print('-'*40)\",\n \"def income_model_constant_portfolio_return(num_of_years=30, trials=100, method='normal'):\\n\\n sim_fia_cv = pd.DataFrame(index=range(num_of_years + 1))\\n\\n sim_base_total = pd.DataFrame(index=range(num_of_years + 1))\\n sim_base_income = pd.DataFrame(index=range(num_of_years + 1))\\n\\n sim_port_total = pd.DataFrame(index=range(num_of_years + 1))\\n sim_port_income = pd.DataFrame(index=range(num_of_years + 1))\\n\\n sim_base_total_pre_income = pd.DataFrame(index=range(num_of_years + 1))\\n sim_port_total_pre_income = pd.DataFrame(index=range(num_of_years + 1))\\n\\n sim_base_total_preincome = pd.DataFrame(index=range(num_of_years + 1))\\n sim_port_total_preincome = pd.DataFrame(index=range(num_of_years + 1))\\n\\n # read_income_inputs = pd.read_csv(src + \\\"income_model_inputs.csv\\\", index_col='Items')\\n read_income_inputs = pd.read_excel(src + \\\"portfolio_information.xlsx\\\", sheet_name='income_model_inputs',\\n index_col=[0])\\n\\n # read_returns_est = pd.read_csv(src + \\\"income_assets_returns_estimates.csv\\\", index_col='Symbol')\\n read_returns_est = pd.read_excel(src + \\\"portfolio_information.xlsx\\\", sheet_name='income_assets_returns_estimates',\\n index_col=[0])\\n\\n # read_returns_est.drop(['BM', read_returns_est.index[-1]], axis=0, inplace=True)\\n # read_portfolio_inputs = pd.read_csv(src + \\\"income_portfolio_inputs.csv\\\", index_col='Items')\\n\\n # read_asset_weights = pd.read_csv(src + \\\"asset_weights.csv\\\", index_col='Asset')\\n read_asset_weights = pd.read_excel(src + \\\"portfolio_information.xlsx\\\", sheet_name='asset_weights',\\n index_col=[0])\\n\\n read_asset_weights.drop(read_asset_weights.index[-1], axis=0, inplace=True)\\n\\n # read random returns for simulation\\n read_normal = pd.read_csv(src + 'sort_normal.csv', index_col=[0], parse_dates=True)\\n read_small = pd.read_csv(src + 'sort_small_to_large.csv', index_col=[0], parse_dates=True)\\n read_large = pd.read_csv(src + 'sort_large_to_small.csv', index_col=[0], parse_dates=True)\\n assets_col_names = list(read_normal.columns)\\n\\n tickers = list(read_asset_weights.index)\\n wts = np.array(read_asset_weights.loc[:, 'base'])\\n\\n def asset_median_returns(data, ticker):\\n return data.filter(regex=ticker).median(axis=1)\\n\\n # # dataframe for unsorted returns (normal)\\n # median_returns_normal = pd.DataFrame({t: asset_median_returns(read_normal, t) for t in tickers})\\n # median_returns_normal.loc[:, 'portfolio_return'] = median_returns_normal.dot(wts)\\n # median_normal_fia = pd.DataFrame({'FIA': asset_median_returns(read_normal, 'r_FIA')})\\n #\\n # # dataframe for smallest to largest returns\\n # median_returns_smallest = pd.DataFrame({t: asset_median_returns(read_small, t) for t in tickers})\\n # median_returns_smallest.loc[:, 'portfolio_return'] = median_returns_smallest.dot(wts)\\n # median_smallest_fia = pd.DataFrame({'FIA': asset_median_returns(read_small, 'r_FIA')})\\n #\\n # # dataframe for unsorted returns (normal)\\n # median_returns_largest = pd.DataFrame({t: asset_median_returns(read_large, t) for t in tickers})\\n # median_returns_largest.loc[:, 'portfolio_return'] = median_returns_largest.dot(wts)\\n # median_largest_fia = pd.DataFrame({'FIA': asset_median_returns(read_large, 'r_FIA')})\\n\\n years = list(range(0, num_of_years + 1))\\n income_cols = ['year', 'strategy_term', 'index_returns', 'term_ret', 'term_ret_with_par', 'term_annualize',\\n 'ann_net_spread', 'term_ret_netspr', 'high_inc_benefit_base', 'rider_fee', 'eoy_income',\\n 'contract_value']\\n\\n term = int(read_income_inputs.loc['term', 'inputs'])\\n fia_ret = read_returns_est.loc[read_returns_est.index[-1], 'Annualized Returns']\\n fia_risk = read_returns_est.loc[read_returns_est.index[-1], 'Annualized Risk']\\n par_rate = float(read_income_inputs.loc['par_rate', 'inputs'])\\n spread = float(read_income_inputs.loc['spread', 'inputs'])\\n bonus_term = int(read_income_inputs.loc['bonus_term', 'inputs'])\\n premium = float(read_income_inputs.loc['premium', 'inputs'])\\n income_bonus = float(read_income_inputs.loc['income_bonus', 'inputs'])\\n\\n income_starts = int(read_income_inputs.loc['start_income_years', 'inputs'])\\n income_growth = float(read_income_inputs.loc['income_growth', 'inputs'])\\n rider_fee = float(read_income_inputs.loc['rider_fee', 'inputs'])\\n inc_payout_factor = float(read_income_inputs.loc['income_payout_factor', 'inputs'])\\n contract_bonus = float(read_income_inputs.loc['contract_bonus', 'inputs'])\\n social = float(read_income_inputs.loc['social', 'inputs'])\\n inflation = float(read_income_inputs.loc['inflation', 'inputs'])\\n wtd_cpn_yield = float(read_income_inputs.loc['wtd_coupon_yld', 'inputs'])\\n life_expectancy = int(read_income_inputs.loc['life_expectancy_age', 'inputs'])\\n clients_age = int(read_income_inputs.loc['clients_age', 'inputs'])\\n \\n # -------------For Constant Growth Rates------------------------\\n const_fia_index_ret = float(read_income_inputs.loc['const_fia_index_ret', 'inputs'])\\n const_risky_port_ret = float(read_income_inputs.loc['const_risky_port_ret', 'inputs'])\\n\\n # ---------------INCOME MODEL--------------------------------------------\\n runs = 0\\n returns_dict = {}\\n asset_dict = {}\\n fia_dict = {}\\n\\n income_df = pd.DataFrame(index=years, columns=income_cols)\\n income_df.loc[:, 'year'] = years\\n income_df.loc[:, 'strategy_term'] = income_df.loc[:, 'year'] % term\\n income_df.loc[:, 'strategy_term'] = income_df['strategy_term'].apply(lambda x: 1 if x == 0 else 0)\\n\\n if method == 'normal':\\n # income_df.loc[:, 'index_returns'] = read_normal.loc[:, '{}_{}'.format('r_FIA', str(runs))]\\n # ----------CONSTANT FIA INDEX GROWTH RATE-------------------\\n income_df.loc[:, 'index_returns'] = const_fia_index_ret\\n\\n elif method == 'smallest':\\n income_df.loc[:, 'index_returns'] = read_small.loc[:, '{}_{}'.format('r_FIA', str(runs))]\\n\\n else:\\n income_df.loc[:, 'index_returns'] = read_large.loc[:, '{}_{}'.format('r_FIA', str(runs))]\\n\\n # income_df.loc[:, 'index_returns'] = np.random.normal(fia_ret, fia_risk, size=(len(years), 1))\\n\\n cumprod = (1. + income_df['index_returns']).rolling(window=term).agg(lambda x: x.prod()) - 1\\n income_df.loc[:, 'term_ret'] = np.where(income_df.loc[:, 'strategy_term'] == 1, cumprod, 0)\\n income_df.loc[:, 'term_ret_with_par'] = income_df.loc[:, 'term_ret'] * par_rate\\n income_df.loc[:, 'term_annualize'] = income_df.loc[:, 'term_ret_with_par'].apply(\\n lambda x: (1 + x) ** (1 / term) - 1)\\n income_df.loc[:, 'ann_net_spread'] = income_df.loc[:, 'term_annualize'] - spread\\n income_df.loc[:, 'ann_net_spread'] = np.where(income_df.loc[:, 'strategy_term'] == 1,\\n income_df.loc[:, 'ann_net_spread'], 0)\\n income_df.loc[:, 'term_ret_netspr'] = income_df.loc[:, 'ann_net_spread'].apply(lambda x: (1 + x) ** term - 1)\\n\\n for counter in years:\\n if counter == 0:\\n income_df.loc[counter, 'high_inc_benefit_base'] = premium * (1 + income_bonus)\\n\\n elif counter <= min(bonus_term, income_starts):\\n income_df.loc[counter, 'high_inc_benefit_base'] = income_df.loc[counter - 1, 'high_inc_benefit_base'] * \\\\\\n (1 + income_growth)\\n else:\\n income_df.loc[counter, 'high_inc_benefit_base'] = income_df.loc[counter - 1, 'high_inc_benefit_base']\\n\\n income_df.loc[:, 'rider_fee'] = income_df.loc[:, 'high_inc_benefit_base'] * rider_fee\\n income_df.loc[:, 'eoy_income'] = np.where(income_df.loc[:, 'year'] > income_starts,\\n income_df.loc[:, 'high_inc_benefit_base'] * inc_payout_factor, 0)\\n\\n for counter in years:\\n if counter == 0:\\n income_df.loc[counter, 'contract_value'] = premium * (1 + contract_bonus)\\n\\n elif income_df.loc[counter, 'strategy_term'] == 1:\\n x1 = income_df.loc[counter - 1, 'contract_value'] - income_df.loc[counter, 'rider_fee']\\n x2 = (x1 * (1 + income_df.loc[counter, 'term_ret_netspr'])) - income_df.loc[counter, 'eoy_income']\\n income_df.loc[counter, 'contract_value'] = x2\\n\\n else:\\n x1 = income_df.loc[counter - 1, 'contract_value'] - income_df.loc[counter, 'rider_fee'] - \\\\\\n income_df.loc[counter, 'eoy_income']\\n\\n income_df.loc[counter, 'contract_value'] = x1\\n\\n # variable stores the income number that is used in the base and fia portfolio calcs.\\n\\n income_from_fia = income_df.loc[income_df.index[-1], 'eoy_income']\\n\\n income_df.loc[:, 'contract_value'] = income_df.loc[:, 'contract_value'].apply(lambda x: 0 if x <= 0 else x)\\n\\n sim_fia_cv.loc[:, str(runs)] = income_df.loc[:, 'contract_value']\\n\\n # -------------------------------------BASE MODEL---------------------------------------------\\n\\n base_wts = read_asset_weights.loc[:, 'base']\\n base_assets = list(base_wts.index)\\n base_weights = list(base_wts.values)\\n base_returns = list(read_returns_est.loc[:, 'Annualized Returns'].values)\\n base_std = list(read_returns_est.loc[:, 'Annualized Risk'].values)\\n\\n base_investment = float(read_income_inputs.loc['risky_assets', 'Base'])\\n adv_fees = float(read_income_inputs.loc['advisor_fees', 'Base'])\\n\\n # -------------------required income----------------------------------\\n req_annual_income = float(read_income_inputs.loc['annual_income', 'inputs'])\\n income_needed = req_annual_income - social\\n income_net_fia_income = max(0, income_needed - income_from_fia)\\n cpn_income_base = base_investment * wtd_cpn_yield\\n\\n # ----------------------RANDOM RETURNS--------------------------\\n r_cols = ['r_{}'.format(name) for name in base_assets]\\n boy_value = ['bv_{}'.format(name) for name in base_assets]\\n eoy_value = ['ev_{}'.format(name) for name in base_assets]\\n\\n random_returns = pd.DataFrame(index=income_df.index, columns=r_cols)\\n\\n # for c in range(len(r_cols)):\\n # ret = np.random.normal(base_returns[c], base_std[c], size=(len(random_returns.index), 1))\\n\\n if method == 'smallest':\\n this_run_cols = ['{}_{}'.format(cname, str(runs)) for cname in r_cols]\\n random_returns = read_small.loc[:, this_run_cols]\\n\\n # random_returns.loc[:, r_cols[c]] = np.sort(ret.flatten())\\n # asset_dict.update({'{}_{}'.format(r_cols[c], str(runs)): np.sort(ret.flatten())})\\n\\n elif method == 'largest':\\n this_run_cols = ['{}_{}'.format(cname, str(runs)) for cname in r_cols]\\n random_returns = read_large.loc[:, this_run_cols]\\n\\n # random_returns.loc[:, r_cols[c]] = np.flip(np.sort(ret.flatten()))\\n # asset_dict.update({'{}_{}'.format(r_cols[c], str(runs)): np.flip(np.sort(ret.flatten()))})\\n\\n else:\\n this_run_cols = ['{}_{}'.format(cname, str(runs)) for cname in r_cols]\\n random_returns = read_normal.loc[:, this_run_cols]\\n\\n # random_returns.loc[:, r_cols[c]] = ret.flatten()\\n # asset_dict.update({'{}_{}'.format(r_cols[c], str(runs)): ret.flatten()})\\n\\n # store the simulated assets returns in one dictionary\\n # returns_dict.update({str(runs): random_returns})\\n\\n # collect the asset based returns from all simulation and calculate the median returns.\\n # def get_median_returns(sym):\\n # cols = [sym + '_' + str(c) for c in np.arange(trials)]\\n # asset_df = pd.DataFrame({c: asset_dict.get(c) for c in cols})\\n # return asset_df.median(axis=1)\\n #\\n # asset_median_returns = pd.DataFrame({symbol: get_median_returns(symbol) for symbol in r_cols})\\n #\\n # asset_median_returns.loc[:, 'simulated_portfolio_median_returns'] = asset_median_returns.dot(base_weights)\\n\\n base_df = random_returns.copy()\\n pre_income_base_df = random_returns.copy()\\n\\n # base_investment = float(read_portfolio_inputs.loc['risky_assets', 'Base'])\\n\\n fia_portfolio_df = random_returns.copy()\\n pre_income_port_df = random_returns.copy()\\n port_investment = float(read_income_inputs.loc['risky_assets', 'FIA'])\\n cpn_income_port = port_investment * wtd_cpn_yield\\n\\n # ---------Initial Investments for pre-income account values---------------------\\n pre_income_base_inv = base_investment\\n pre_income_port_inv = port_investment\\n # ----------------------------------------BASE PORTFOLIO----------------------------\\n for name in boy_value:\\n base_df.loc[:, name] = 0.0\\n pre_income_base_df.loc[:, name] = 0.0\\n\\n for counter in years:\\n period_returns = list(random_returns.loc[counter, :])\\n if counter == 0:\\n # ---------------For year 0, the year of investment------------\\n\\n # ------------Calculate the annual portfolio returns - Gross Returns--------------------\\n base_df.loc[counter, boy_value] = [base_weights[c] * base_investment for c in range(len(boy_value))]\\n\\n # -------------Record the Pre Income Base Portfolio-----------------------------\\n\\n pre_income_base_df.loc[counter, boy_value] = [base_weights[c] *\\n pre_income_base_inv for c in range(len(boy_value))]\\n pre_income_base_df.loc[counter, 'total'] = pre_income_base_df.loc[counter, boy_value].sum()\\n pre_income_base_inv = pre_income_base_df.loc[counter, boy_value].sum()\\n\\n # ------------------Pre Income Block Ends------------------------\\n\\n base_df.loc[counter, 'total'] = base_df.loc[counter, boy_value].sum()\\n\\n base_df.loc[counter, 'total_net_fees'] = 0.0\\n base_df.loc[counter, 'income'] = 0.0\\n # base_investment = base_df.loc[counter, boy_value].sum()\\n base_df.loc[counter, 'total_pre_income'] = base_investment\\n\\n elif (counter > 0) and (counter < income_starts):\\n\\n # ----For years between the start of the investment and start if the income---------------\\n base_df.loc[counter, boy_value] = [base_weights[c] * base_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n\\n # -------------Record the Pre Income Base Portfolio-----------------------------\\n pre_income_base_df.loc[counter, boy_value] = [\\n base_weights[c] * pre_income_base_inv * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n\\n # pre_income_base_df.loc[counter, 'total'] = pre_income_base_df.loc[counter, boy_value].sum()\\n pre_income_base_df.loc[counter, 'total'] = base_investment * (1 + const_risky_port_ret)\\n pre_income_base_df.loc[counter, 'adv_fees'] = pre_income_base_df.loc[counter, 'total'] * adv_fees\\n pre_income_base_df.loc[counter, 'total_net_fees'] = pre_income_base_df.loc[counter, 'total'] - \\\\\\n pre_income_base_df.loc[counter, 'adv_fees']\\n pre_income_base_inv = pre_income_base_df.loc[counter, 'total_net_fees'] + cpn_income_base\\n\\n # ------------------Pre Income Block Ends------------------------\\n\\n # base_df.loc[counter, 'total'] = base_df.loc[counter, boy_value].sum()\\n base_df.loc[counter, 'total'] = base_investment * (1 + 0.06)\\n base_df.loc[counter, 'adv_fees'] = base_df.loc[counter, 'total'] * adv_fees\\n base_df.loc[counter, 'total_net_fees'] = base_df.loc[counter, 'total'] - base_df.loc[\\n counter, 'adv_fees']\\n\\n # --coupon payment is invested back into the risky portfolio until the income is withdrawn----\\n base_investment = base_df.loc[counter, 'total_net_fees'] + cpn_income_base\\n base_df.loc[counter, 'total_pre_income'] = base_df.loc[counter, 'total_net_fees']\\n\\n else:\\n\\n # -------------For Years after the income started----------------------\\n base_df.loc[counter, boy_value] = [base_weights[c] * base_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n\\n # -------------Record the Pre Income Base Portfolio-----------------------------\\n pre_income_base_df.loc[counter, boy_value] = [\\n base_weights[c] * pre_income_base_inv * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n\\n # pre_income_base_df.loc[counter, 'total'] = pre_income_base_df.loc[counter, boy_value].sum()\\n pre_income_base_df.loc[counter, 'total'] = base_investment * (1 + const_risky_port_ret)\\n pre_income_base_df.loc[counter, 'adv_fees'] = pre_income_base_df.loc[counter, 'total'] * adv_fees\\n pre_income_base_df.loc[counter, 'total_net_fees'] = pre_income_base_df.loc[counter, 'total'] - \\\\\\n pre_income_base_df.loc[counter, 'adv_fees']\\n pre_income_base_inv = pre_income_base_df.loc[counter, 'total_net_fees'] + cpn_income_base\\n\\n # ------------------Pre Income Block Ends------------------------\\n\\n # base_df.loc[counter, 'total'] = base_df.loc[counter, boy_value].sum()\\n base_df.loc[counter, 'total'] = base_investment * (1 + const_risky_port_ret)\\n base_df.loc[counter, 'adv_fees'] = base_df.loc[counter, 'total'] * adv_fees\\n\\n # ---req. income is adjusted for inflation from the second year of withdrawal. Reinvestment of coupon\\n # stops from the year income starts. Req. income is reduced by the coupon payments\\n\\n if counter == income_starts:\\n\\n income_needed = req_annual_income - social\\n base_df.loc[counter, 'income'] = income_needed - cpn_income_base\\n income_needed = req_annual_income\\n\\n else:\\n income_needed = income_needed * (1 + inflation) - social\\n base_df.loc[counter, 'income'] = income_needed - cpn_income_base\\n income_needed = income_needed + social\\n\\n base_df.loc[counter, 'total_net_fees'] = base_df.loc[counter, 'total'] - \\\\\\n base_df.loc[counter, 'adv_fees'] - \\\\\\n base_df.loc[counter, 'income']\\n\\n base_df.loc[counter, 'total_pre_income'] = base_df.loc[counter, 'total'] - \\\\\\n base_df.loc[counter, 'adv_fees']\\n\\n base_investment = base_df.loc[counter, 'total_net_fees']\\n\\n # -------------------Portfolio with PreIncome Values----------------------------\\n sim_base_total_preincome.loc[:, 's_{}'.format(str(runs))] = pre_income_base_df.loc[:, 'total_net_fees']\\n sim_base_total_preincome.fillna(float(read_income_inputs.loc['risky_assets', 'Base']), inplace=True)\\n # --------------------------------PreIncome Block Ends----------------------------\\n\\n base_df.loc[:, 'adj_total'] = base_df.loc[:, 'total_net_fees'].apply(lambda x: x if x > 0 else 0)\\n sim_base_total.loc[:, 's_{}'.format(str(runs))] = base_df.loc[:, 'total_net_fees']\\n sim_base_income.loc[:, 's_{}'.format(str(runs))] = base_df.loc[:, 'income']\\n sim_base_total_pre_income.loc[:, 's_{}'.format(str(runs))] = base_df.loc[:, 'total_pre_income']\\n\\n # ----------------------------FIA PORTFOLIO----------------------------------------------\\n for name in boy_value:\\n fia_portfolio_df.loc[:, name] = 0.0\\n pre_income_port_df.loc[:, name] = 0.0\\n\\n for counter in years:\\n period_returns = list(random_returns.loc[counter, :])\\n if counter == 0:\\n\\n fia_portfolio_df.loc[counter, boy_value] = [base_weights[c] * port_investment\\n for c in range(len(boy_value))]\\n\\n # -------------Record the Pre Income Base Portfolio-----------------------------\\n\\n pre_income_port_df.loc[counter, boy_value] = [base_weights[c] *\\n pre_income_port_inv for c in range(len(boy_value))]\\n pre_income_port_df.loc[counter, 'total'] = pre_income_port_df.loc[counter, boy_value].sum()\\n pre_income_port_inv = pre_income_port_df.loc[counter, boy_value].sum()\\n\\n # ------------------Pre Income Block Ends------------------------\\n\\n fia_portfolio_df.loc[counter, 'total'] = fia_portfolio_df.loc[counter, boy_value].sum()\\n fia_portfolio_df.loc[counter, 'total_net_fees'] = 0.0\\n fia_portfolio_df.loc[counter, 'income'] = 0.0\\n # port_investment = fia_portfolio_df.loc[counter, boy_value].sum()\\n fia_portfolio_df.loc[counter, 'total_pre_income'] = port_investment\\n\\n elif (counter > 0) and (counter < income_starts):\\n\\n fia_portfolio_df.loc[counter, boy_value] = [base_weights[c] * port_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n\\n # ------------------Record the Pre Income Base Portfolio-----------------------------\\n pre_income_port_df.loc[counter, boy_value] = [\\n base_weights[c] * pre_income_port_inv * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n\\n # pre_income_port_df.loc[counter, 'total'] = pre_income_port_df.loc[counter, boy_value].sum()\\n \\n # -----------------------CONSTANT GROWTH RATE-----------------\\n pre_income_port_df.loc[counter, 'total'] = port_investment * (1 + const_risky_port_ret)\\n\\n pre_income_port_df.loc[counter, 'adv_fees'] = pre_income_port_df.loc[counter, 'total'] * adv_fees\\n pre_income_port_df.loc[counter, 'total_net_fees'] = pre_income_port_df.loc[counter, 'total'] - \\\\\\n pre_income_port_df.loc[counter, 'adv_fees']\\n pre_income_port_inv = pre_income_port_df.loc[counter, 'total_net_fees'] + cpn_income_base\\n\\n # ------------------Pre Income Block Ends------------------------\\n\\n # fia_portfolio_df.loc[counter, 'total'] = fia_portfolio_df.loc[counter, boy_value].sum()\\n \\n # -------CONSTANT GROWTH RATE-----------------\\n fia_portfolio_df.loc[counter, 'total'] = port_investment * (1 + const_risky_port_ret)\\n\\n fia_portfolio_df.loc[counter, 'adv_fees'] = fia_portfolio_df.loc[counter, 'total'] * adv_fees\\n fia_portfolio_df.loc[counter, 'total_net_fees'] = fia_portfolio_df.loc[counter, 'total'] - \\\\\\n fia_portfolio_df.loc[counter, 'adv_fees']\\n fia_portfolio_df.loc[counter, 'total_pre_income'] = fia_portfolio_df.loc[counter, 'total_net_fees']\\n\\n port_investment = fia_portfolio_df.loc[counter, 'total_net_fees'] + cpn_income_port\\n\\n else:\\n fia_portfolio_df.loc[counter, boy_value] = [base_weights[c] * port_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n\\n # -------------Record the Pre Income Base Portfolio-----------------------------\\n pre_income_port_df.loc[counter, boy_value] = [\\n base_weights[c] * pre_income_port_inv * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n\\n # pre_income_port_df.loc[counter, 'total'] = pre_income_port_df.loc[counter, boy_value].sum()\\n pre_income_port_df.loc[counter, 'total'] = port_investment * (1 + const_risky_port_ret)\\n pre_income_port_df.loc[counter, 'adv_fees'] = pre_income_port_df.loc[counter, 'total'] * adv_fees\\n pre_income_port_df.loc[counter, 'total_net_fees'] = pre_income_port_df.loc[counter, 'total'] - \\\\\\n pre_income_port_df.loc[counter, 'adv_fees']\\n pre_income_port_inv = pre_income_port_df.loc[counter, 'total_net_fees'] + cpn_income_base\\n\\n # ------------------Pre Income Block Ends------------------------\\n\\n # fia_portfolio_df.loc[counter, 'total'] = fia_portfolio_df.loc[counter, boy_value].sum()\\n fia_portfolio_df.loc[counter, 'total'] = port_investment * (1 + const_risky_port_ret)\\n fia_portfolio_df.loc[counter, 'adv_fees'] = fia_portfolio_df.loc[counter, 'total'] * adv_fees\\n\\n # ---req. income is adjusted for inflation from the second year of withdrawal. Reinvestment of coupon\\n # stops from the year income starts. Req. income is reduced by the coupon payments\\n\\n if counter == income_starts:\\n\\n income_needed = req_annual_income - social\\n income_net_fia_income = max(0, income_needed - income_from_fia)\\n fia_portfolio_df.loc[counter, 'income'] = max(0, income_net_fia_income - cpn_income_port)\\n income_needed = req_annual_income\\n\\n else:\\n income_needed = income_needed * (1 + inflation) - social\\n income_net_fia_income = max(0, income_needed - income_from_fia)\\n fia_portfolio_df.loc[counter, 'income'] = max(0, income_net_fia_income - cpn_income_port)\\n income_needed = income_needed + social\\n\\n fia_portfolio_df.loc[counter, 'total_net_fees'] = fia_portfolio_df.loc[counter, 'total'] - \\\\\\n fia_portfolio_df.loc[counter, 'adv_fees'] - \\\\\\n fia_portfolio_df.loc[counter, 'income']\\n\\n fia_portfolio_df.loc[counter, 'total_pre_income'] = fia_portfolio_df.loc[counter, 'total'] - \\\\\\n fia_portfolio_df.loc[counter, 'adv_fees']\\n\\n port_investment = fia_portfolio_df.loc[counter, 'total_net_fees']\\n\\n sim_port_total.loc[:, 's_{}'.format(str(runs))] = fia_portfolio_df.loc[:, 'total_net_fees'] + \\\\\\n income_df.loc[:, 'contract_value']\\n\\n sim_port_income.loc[:, 's_{}'.format(str(runs))] = fia_portfolio_df.loc[:, 'income']\\n\\n fia_portfolio_df.loc[:, 'adj_total'] = fia_portfolio_df.loc[:, 'total_net_fees'].apply(\\n lambda x: x if x > 0 else 0)\\n\\n sim_port_total_pre_income.loc[:, 's_{}'.format(str(runs))] = fia_portfolio_df.loc[:, 'total_pre_income']\\n\\n # -------------------Portfolio with PreIncome Values----------------------------\\n sim_port_total_preincome.loc[:, 's_{}'.format(str(runs))] = pre_income_port_df.loc[:, 'total_net_fees'] + \\\\\\n income_df.loc[:, 'contract_value']\\n\\n sim_port_total_preincome.fillna(float(read_income_inputs.loc['risky_assets', 'FIA']), inplace=True)\\n \\n # --------------------------------PreIncome Block Ends----------------------------\\n\\n # ------------------Calculate % of portfolios ending value greater than required LIFETIME cumm. income---------\\n total_income_by_age = sim_base_income.loc[:, sim_base_income.columns[0]].cumsum()\\n total_income_by_acturial_age = total_income_by_age.loc[life_expectancy - clients_age]\\n total_income_by_age.fillna(0, inplace=True)\\n income_dataframe = pd.DataFrame(total_income_by_age)\\n income_dataframe.loc[:, 'remaining_income_by_acturial_age'] = total_income_by_age.apply(\\n lambda x: total_income_by_acturial_age - x)\\n\\n s = income_dataframe.loc[:, 'remaining_income_by_acturial_age']\\n base_prob_of_success = sim_base_total.gt(s, axis=0).sum(axis=1)\\n port_prob_of_success = sim_port_total.gt(s, axis=0).sum(axis=1)\\n\\n # ----------------------------Portfolio sufficient for NEXT YEARS income needs-------------------\\n next_year_income = sim_base_income.loc[:, sim_base_income.columns[0]].shift(-1).fillna(0) # Yearly Income Reqd.\\n base_success_next_year = sim_base_total.gt(next_year_income, axis=0).sum(axis=1)\\n\\n base_for_next_year_need = sim_base_total[sim_base_total.gt(next_year_income, axis=0)]\\n\\n port_success_next_year = sim_port_total.gt(next_year_income, axis=0).sum(axis=1)\\n\\n port_for_next_year_need = sim_port_total[sim_port_total.gt(next_year_income, axis=0)]\\n\\n # ---------------Portfolio for 45 years of simulation---------------------------------------\\n base_success_portfolio = sim_base_total[sim_base_total.gt(next_year_income, axis=0)]\\n port_success_portfolio = sim_port_total[sim_port_total.gt(next_year_income, axis=0)]\\n\\n # ----------------Portfolio Simulation until the acturial age------------------------------\\n acturial_years = life_expectancy - clients_age\\n base_success_portfolio_act_age = base_success_portfolio.loc[acturial_years, :]\\n port_success_portfolio_act_age = port_success_portfolio.loc[acturial_years, :]\\n\\n # -------------------------Base Portfolio TS with max Terminal Value ----------------------------\\n if base_success_portfolio_act_age.isnull().sum() == trials:\\n base_max_portfolio = 0.0\\n else:\\n base_max_portfolio = base_success_portfolio.loc[:, base_success_portfolio_act_age.idxmax()]\\n\\n # -------------------------FIA Portfolio TS with max Terminal Value ----------------------------\\n if port_success_portfolio_act_age.isnull().sum() == trials:\\n port_max_portfolio = 0.0\\n else:\\n port_max_portfolio = port_success_portfolio.loc[:, port_success_portfolio_act_age.idxmax()]\\n\\n # ------------------------------Average age with full income------------------------------\\n base_mean_age = ((life_expectancy - clients_age) - base_success_portfolio.loc[1:life_expectancy - clients_age, :]\\n .isnull().sum()).mean()\\n\\n port_mean_age = ((life_expectancy - clients_age) - port_success_portfolio.loc[1:life_expectancy - clients_age, :]\\n .isnull().sum()).mean()\\n\\n # ----------------------------Median Age with full Income------------------------------------------\\n base_median_age = ((life_expectancy - clients_age) - base_success_portfolio.loc[1:life_expectancy - clients_age, :]\\n .isnull().sum()).median()\\n\\n port_median_age = ((life_expectancy - clients_age) - port_success_portfolio.loc[1:life_expectancy - clients_age, :]\\n .isnull().sum()).median()\\n\\n # --------------Mean Value for all the portfolios at end of the acturial age--------------------\\n base_act_avg_porfolio = base_success_portfolio.loc[life_expectancy - clients_age, :].fillna(0).mean()\\n port_act_avg_porfolio = port_success_portfolio.loc[life_expectancy - clients_age, :].fillna(0).mean()\\n\\n # --------------Median Value for all the portfolios at end of the acturial age--------------------\\n base_act_median_porfolio = base_success_portfolio.loc[life_expectancy - clients_age, :].fillna(0).median()\\n port_act_median_porfolio = port_success_portfolio.loc[life_expectancy - clients_age, :].fillna(0).median()\\n\\n # # --------------Mean Value for all the portfolios in the simulation--------------------\\n # base_sim_mean = base_success_portfolio.loc[1:life_expectancy - clients_age, :].mean().mean()\\n # port_sim_mean = port_success_portfolio.loc[1:life_expectancy - clients_age, :].mean().mean()\\n #\\n # # --------------Median Value for all the portfolios in the simulation--------------------\\n # base_sim_mean = base_success_portfolio.loc[1:life_expectancy - clients_age, :].mean().median()\\n # port_sim_mean = port_success_portfolio.loc[1:life_expectancy - clients_age, :].mean().median()\\n\\n # -------Max Portfolio value at the end of acturial age----------------------------------------\\n base_act_max = base_success_portfolio.loc[life_expectancy - clients_age, :].max()\\n port_act_max = port_success_portfolio.loc[life_expectancy - clients_age, :].max()\\n\\n # -------Min Portfolio value at the end of acturial age----------------------------------------\\n base_act_min = base_success_portfolio.loc[life_expectancy - clients_age, :].min()\\n port_act_min = port_success_portfolio.loc[life_expectancy - clients_age, :].min()\\n\\n # ---------------------Lifetime Average Income----------------------------------\\n base_total_income = sim_base_income.cumsum().loc[acturial_years, :].mean()\\n port_total_income = income_from_fia + sim_port_income\\n port_total_income = port_total_income.cumsum().loc[acturial_years, :].mean()\\n\\n simulation_stats = pd.DataFrame(index=['Average Years', 'Median Years', 'Average Age', 'Median Age',\\n 'Average Portfolio (act.age)', 'Median Portfolio (act.age)',\\n 'Max Portfolio Value', 'Min Portfolio Value',\\n 'Average Lifetime Income'], columns=['Base', 'FIA'])\\n\\n simulation_stats.loc['Average Years', :] = [base_mean_age, base_mean_age]\\n simulation_stats.loc['Median Years', :] = [base_median_age, base_median_age]\\n simulation_stats.loc['Average Age', :] = [base_mean_age + clients_age, base_mean_age + clients_age]\\n simulation_stats.loc['Median Age', :] = [base_median_age + clients_age, base_median_age + clients_age]\\n simulation_stats.loc['Average Portfolio (act.age)', :] = [base_act_avg_porfolio, port_act_avg_porfolio]\\n simulation_stats.loc['Median Portfolio (act.age)', :] = [base_act_median_porfolio, port_act_median_porfolio]\\n simulation_stats.loc['Max Portfolio Value', :] = [base_act_max, port_act_max]\\n simulation_stats.loc['Min Portfolio Value', :] = [base_act_min, port_act_min]\\n simulation_stats.loc['Average Lifetime Income', :] = [base_total_income, port_total_income]\\n comments = ['Average years of portfolios that meet the next years income needs for the lifetime',\\n 'Median years of portfolios that meet the next years income needs for the lifetime',\\n 'Average Clients Age',\\n 'Median Clients Age',\\n 'Average of terminal values for the portfolios at the end of the acturial life',\\n 'Median of terminal values for the portfolios at the end of the acturial life',\\n 'Maximum of terminal values for the portfolios at the end of the acturial life',\\n 'Minimum of terminal values for the portfolios at the end of the acturial life',\\n 'Average of total income generated by all portfolios at the end of the acturial life']\\n\\n simulation_stats.loc[:, 'Notes'] = comments\\n\\n # --------------------------------------------------------------------------------\\n\\n # # -----------------------------------income breakdown for Base portfolio----------------------------------\\n # base_df.to_csv(src + 'base_port_detail.csv')\\n # sim_base_total.to_csv(src + 'base_ending_values.csv')\\n # income_breakdown_base = pd.DataFrame(sim_base_total.quantile(0.5, axis=1))\\n # income_breakdown_base.loc[:, 'income_from_portfolio'] = sim_base_income.quantile(0.5, axis=1)\\n # income_breakdown_base.loc[:, 'fia_income'] = 0.0\\n # income_breakdown_base.loc[:, 'social_security_income'] = social\\n # income_breakdown_base.loc[:, 'coupon_income'] = cpn_income_base\\n #\\n # income_breakdown_base.rename(columns={income_breakdown_base.columns[0]: 'portfolio_ending_value'}, inplace=True)\\n # income_breakdown_base.loc[:, 'income_from_portfolio'][\\n # income_breakdown_base.loc[:, 'portfolio_ending_value'] <= 0] = 0\\n # income_breakdown_base.loc[:, 'total_income'] = income_breakdown_base.loc[:, income_breakdown_base.columns[1:]].sum(\\n # axis=1)\\n #\\n # # --------------------------------------Block Ends-----------------------------------------------------------\\n #\\n # # ---------------------------------------income breakdown for FIA portfolio----------------------------------\\n # fia_portfolio_df.to_csv(src + 'fia_port_detail.csv')\\n # sim_port_total.to_csv(src + 'fiaport_ending_values.csv')\\n #\\n # income_breakdown_port = pd.DataFrame(sim_port_total.quantile(0.5, axis=1))\\n # income_breakdown_port.loc[:, 'income_from_portfolio'] = sim_port_income.quantile(0.5, axis=1)\\n # income_breakdown_port.loc[:, 'fia_income'] = income_from_fia\\n # income_breakdown_port.loc[:, 'social_security_income'] = social\\n # income_breakdown_port.loc[:, 'coupon_income'] = cpn_income_port\\n #\\n # income_breakdown_port.rename(columns={income_breakdown_port.columns[0]: 'portfolio_ending_value'}, inplace=True)\\n # income_breakdown_port.loc[:, 'income_from_portfolio'][\\n # income_breakdown_port.loc[:, 'portfolio_ending_value'] <= 0] = 0\\n # income_breakdown_port.loc[:, 'total_income'] = income_breakdown_port.loc[:, income_breakdown_port.columns[1:]].sum(\\n # axis=1)\\n #\\n # # ----------------------------------Block Ends-------------------------------------------------------------\\n q_cut = [0.0, 0.1, 0.25, 0.5, 0.75, 0.95, 1.0]\\n sim_base_income[sim_base_total < income_needed] = 0.0\\n\\n sim_port_income[sim_port_total < income_net_fia_income] = 0\\n\\n sim_port_income = sim_port_income + income_from_fia\\n\\n # base_quantile = sim_base_total.loc[sim_base_total.index[-1]].quantile([0.05, 0.25, 0.50, 0.75, 0.90])\\n #\\n # port_quantile = sim_port_total.loc[sim_port_total.index[-1]].quantile([0.05, 0.25, 0.50, 0.75, 0.90])\\n\\n base_quantile = sim_base_total.loc[sim_base_total.index[-1]].quantile(q_cut)\\n\\n port_quantile = sim_port_total.loc[sim_port_total.index[-1]].quantile(q_cut)\\n\\n # q_cut = [0.0, .05, 0.25, 0.5, 0.75, 0.95, 1.0]\\n cols = ['Min', '10th', '25th', '50th', '75th', '90th', 'Max']\\n\\n # ------------------------------------------drop year 0-----------------------------------------\\n sim_base_total = sim_base_total[1:]\\n sim_port_total = sim_port_total[1:]\\n\\n # ---------------------------------plot for histogram for porfolios--------------------------------------\\n # base_term_value = sim_base_total.loc[sim_base_total.index[:life_expectancy - clients_age], :]\\n # fact = 1 / len(base_term_value)\\n # base_ann_ret = (base_term_value.iloc[-1] / base_term_value.iloc[0]) ** fact - 1\\n # counts, bins, bars = plt.hist(base_ann_ret)\\n\\n # ------------------------quantile analysis for base terminal value-----------------------------\\n base_qcut = pd.DataFrame(index=sim_base_total.index, columns=cols)\\n for c in range(len(cols)):\\n base_qcut.loc[:, cols[c]] = sim_base_total.quantile(q_cut[c], axis=1)\\n\\n base_qcut.clip(lower=0, inplace=True)\\n\\n sim_base_total.clip(lower=0, inplace=True)\\n\\n # -------------------------------------quantile analysis for base income----------------------------\\n base_income_qcut = pd.DataFrame(index=sim_base_income.index, columns=cols)\\n for c in range(len(cols)):\\n base_income_qcut.loc[:, cols[c]] = sim_base_income.quantile(q_cut[c], axis=1)\\n\\n # ----Remove NaN's prior to the income start years------------\\n # base_income_qcut = base_income_qcut.loc[income_starts:]\\n\\n # ---------------------------------quantile analysis for portfolio terminal value ---------------\\n\\n port_qcut = pd.DataFrame(index=sim_port_total.index, columns=cols)\\n for c in range(len(cols)):\\n port_qcut.loc[:, cols[c]] = sim_port_total.quantile(q_cut[c], axis=1)\\n\\n port_qcut.clip(lower=0, inplace=True)\\n\\n # ----------------------------------quantile analysis for portfolio income----------------------------\\n port_income_qcut = pd.DataFrame(index=sim_port_income.index, columns=cols)\\n for c in range(len(cols)):\\n port_income_qcut.loc[:, cols[c]] = sim_port_income.quantile(q_cut[c], axis=1)\\n\\n # ----Remove NaN's prior to the income start years------------\\n # port_income_qcut = port_income_qcut.loc[income_starts:]\\n\\n # ----------probability ending value will be less than 0 at the end of the horizon -----------------------\\n # base_legacy_risk = (sim_base_total.loc[sim_base_total.index[-1]] < 0).sum() / (trials)\\n\\n base_legacy_risk = (sim_base_total.loc[sim_base_total.index[life_expectancy - clients_age]] < 0).sum() / trials\\n port_legacy_risk = (sim_port_total.loc[sim_port_total.index[life_expectancy - clients_age]] < 0).sum() / trials\\n\\n # port_legacy_risk = (sim_port_total.loc[sim_port_total.index[-1]] <= 0).sum() / (trials)\\n\\n legacy_risk = pd.DataFrame([base_legacy_risk, port_legacy_risk,\\n 'Prob. of portfolio value less than 0 at the end of the expected life'],\\n index=['base', 'fia_portfolio', 'Notes'],\\n columns=['Ruin Probability'])\\n\\n # -----------Year-wise probability of ending value greater than 0 -----------------\\n base_psuccess = sim_base_total.apply(lambda x: x > 0).sum(axis=1) / trials\\n port_psuccess = sim_port_total.apply(lambda x: x > 0).sum(axis=1) / trials\\n\\n # -----------------------WRITING FILES TO EXCEL ---------------------------\\n\\n writer = pd.ExcelWriter(dest_simulation + method + '_leveled_growth_simulation.xlsx', engine='xlsxwriter')\\n read_income_inputs.to_excel(writer, sheet_name='inputs_for_income')\\n\\n read_returns_est.to_excel(writer, sheet_name='asset_returns_estimates')\\n # read_portfolio_inputs.to_excel(writer, sheet_name='portfolio_inputs')\\n\\n age_index = list(range(clients_age + 1, clients_age + len(base_qcut) + 1))\\n # base_qcut.loc[:, 'clients_age'] = age_index\\n # base_qcut.loc[:, 'comment'] = ''\\n # base_qcut.loc[:, 'comment'] = np.where(base_qcut.clients_age == life_expectancy, 'expected_life', \\\"\\\")\\n base_inv = float(read_income_inputs.loc['risky_assets', 'Base'])\\n base_qcut.loc[:, 'age'] = age_index\\n base_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n\\n # -----------------------To start with year 0---------------------------------\\n insert_col = [base_inv, base_inv, base_inv, base_inv, base_inv, base_inv,\\n base_inv, clients_age, np.nan]\\n base_qcut.loc[len(base_qcut) + 1, :] = 0.0\\n base_qcut = base_qcut.shift(1)\\n base_qcut.iloc[0] = insert_col\\n base_qcut.reset_index(drop=True, inplace=True)\\n base_qcut.to_excel(writer, sheet_name='base_ending_value_quantiles')\\n # base_qcut.loc[income_starts:, :].to_excel(writer, sheet_name='base_ending_value_quantiles')\\n\\n # base_income_qcut = base_income_qcut[1:] base_income_qcut.loc[:, 'clients_age'] = age_index\\n # base_income_qcut.loc[:, 'comment'] = '' base_income_qcut.loc[:, 'comment'] = np.where(\\n # base_income_qcut.clients_age == life_expectancy, 'expected_life', \\\"\\\")\\n\\n base_income_qcut = base_income_qcut.loc[1:, :]\\n base_income_qcut.loc[:, 'age'] = age_index\\n base_income_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n base_income_qcut.loc[income_starts:, :].to_excel(writer, sheet_name='base_income_quantiles')\\n\\n # age_index = list(range(clients_age+1, clients_age + len(port_qcut)+1))\\n # port_qcut.loc[:, 'clients_age'] = age_index\\n # port_qcut.loc[:, 'comment'] = ''\\n # port_qcut.loc[:, 'comment'] = np.where(port_qcut.clients_age == life_expectancy, 'expected_life', \\\"\\\")\\n\\n port_qcut.loc[:, 'age'] = age_index\\n port_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n port_qcut.loc[len(port_qcut) + 1, :] = 0.0\\n port_qcut = port_qcut.shift(1)\\n port_qcut.iloc[0] = insert_col\\n port_qcut.reset_index(drop=True, inplace=True)\\n port_qcut.to_excel(writer, sheet_name='fia_port_ending_value_quantiles')\\n # port_qcut.loc[income_starts:, :].to_excel(writer, sheet_name='fia_port_ending_value_quantiles')\\n\\n # port_income_qcut = port_income_qcut[1:] port_income_qcut.loc[:, 'clients_age'] = age_index\\n # port_income_qcut.loc[:, 'comment'] = '' port_income_qcut.loc[:, 'comment'] = np.where(\\n # port_income_qcut.clients_age == life_expectancy, 'expected_life', \\\"\\\")\\n\\n port_income_qcut = port_income_qcut.loc[1:, :]\\n port_income_qcut.loc[:, 'age'] = age_index\\n port_income_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n port_income_qcut.loc[income_starts:, :].to_excel(writer, sheet_name='fia_port_income_quantiles')\\n\\n prob_success_df = pd.concat([base_psuccess, port_psuccess], axis=1)\\n prob_success_df.rename(columns={prob_success_df.columns[0]: 'prob(ending_value>0)_base',\\n prob_success_df.columns[1]: 'prob(ending_value>0)_port'}, inplace=True)\\n\\n # prob_success_df.loc[:, 'clients_age'] = age_index\\n # prob_success_df.loc[:, 'comment'] = ''\\n # prob_success_df.loc[:, 'comment'] = np.where(prob_success_df.clients_age == life_expectancy, 'expected_life', \\\"\\\")\\n\\n prob_success_df.loc[:, 'age'] = age_index\\n prob_success_df.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n prob_success_df.loc[:, 'prob(ending_value>lifetime_req income)_base'] = base_prob_of_success / trials\\n prob_success_df.loc[:, 'prob(ending_value>lifetime_req income)_port'] = port_prob_of_success / trials\\n prob_success_df.loc[:, 'prob(ending_value>next_year_req_income)_base'] = base_success_next_year / trials\\n prob_success_df.loc[:, 'prob(ending_value>next_year_req_income)_port'] = port_success_next_year / trials\\n prob_success_df.loc[:, 'base_max_portfolio_at_acturial_age'] = base_max_portfolio\\n prob_success_df.loc[:, 'port_max_portfolio_at_acturial_age'] = port_max_portfolio\\n\\n # --------------------Percentile Portfolio's based on Acturial Life------------------------\\n base_success = prob_success_df.loc[life_expectancy - clients_age, 'prob(ending_value>next_year_req_income)_base']\\n port_success = prob_success_df.loc[life_expectancy - clients_age, 'prob(ending_value>next_year_req_income)_port']\\n\\n # acturial_age_base_tv = sim_base_total.loc[:life_expectancy - clients_age, ]\\n # percentile_base_tv = sim_base_total.apply(lambda x: np.nanpercentile(x, base_success), axis=1)\\n\\n # ----------------Year wise percentile portfolio to meet next year income. Based on the success at acturial age.\\n # Yearly portfolio values that can provide the next year income below the success rate at end of life (Percentile)-\\n\\n # acturial_age_base = base_for_next_year_need.loc[:life_expectancy - clients_age, ]\\n # acturial_age_base = base_for_next_year_need.copy().fillna(0)\\n percentile_base = base_for_next_year_need.apply(lambda x: np.nanpercentile(x, base_success), axis=1)\\n\\n # ----Pre Income Portfolio based on the Probab. of Success to meet next year's income at the end on the Act. Age\\n base_pre_income_success = sim_base_total_preincome.apply(lambda x: np.nanpercentile(x, base_success), axis=1)\\n base_ann_ret_pre_income = base_pre_income_success.pct_change().fillna(0)\\n\\n # acturial_age_port_tv = sim_port_total.loc[:life_expectancy - clients_age, ]\\n # percentile_port_tv = sim_port_total.apply(lambda x: np.nanpercentile(x, port_success), axis=1)\\n\\n # ----------------Year wise percentile portfolio to meet next year income. Based on the success at acturial age.\\n # Yearly portfolio values that can provide the next year income below the success rate at end of life (Percentile)-\\n\\n # acturial_age_port = port_for_next_year_need.loc[:life_expectancy - clients_age, ]\\n # acturial_age_base = port_for_next_year_need.copy().fillna(0)\\n percentile_port = port_for_next_year_need.apply(lambda x: np.nanpercentile(x, port_success), axis=1)\\n\\n # ----Pre Income Portfolio based on the Probab. of Success to meet next year's income at the end on the Act. Age\\n port_pre_income_success = sim_port_total_preincome.apply(lambda x: np.nanpercentile(x, port_success), axis=1)\\n port_ann_ret_pre_income = port_pre_income_success.pct_change().fillna(0)\\n\\n prob_success_df.loc[:, 'acturial_success_percentile_base_portfolio'] = percentile_base\\n prob_success_df.loc[:, 'acturial_success_percentile_port_portfolio'] = percentile_port\\n\\n prob_success_df.loc[:, 'base_pre_income_ann_ret'] = base_ann_ret_pre_income\\n prob_success_df.loc[:, 'port_pre_income_ann_ret'] = port_ann_ret_pre_income\\n\\n # prob_success_df.loc[:, 'terminalVal_success_percentile_base_portfolio'] = percentile_base_tv\\n # prob_success_df.loc[:, 'terminalVal_success_percentile_port_portfolio'] = percentile_port_tv\\n\\n sim_base_total_preincome.to_excel(writer, sheet_name='base_preincome_portfolios')\\n # -------Add premium to year 0 value to get total portfolio value---------\\n sim_port_total_preincome.iloc[0] = sim_port_total_preincome.iloc[0] + premium\\n sim_port_total_preincome.to_excel(writer, sheet_name='port_preincome_portfolios')\\n\\n # -------------For Simulation slide - BASE Portfolio - Can Delete --------------------\\n # base_qcut_preinc = pd.DataFrame(index=sim_base_total_preincome.index, columns=cols)\\n # for c in range(len(cols)):\\n # base_qcut_preinc.loc[:, cols[c]] = sim_base_total_preincome.quantile(q_cut[c], axis=1)\\n #\\n # # -------------For Simulation slide - Proposed Portfolio --------------------\\n # port_qcut_preinc = pd.DataFrame(index=sim_port_total_preincome.index, columns=cols)\\n # for c in range(len(cols)):\\n # port_qcut_preinc.loc[:, cols[c]] = sim_port_total_preincome.quantile(q_cut[c], axis=1)\\n #\\n # base_qcut_preinc.to_excel(writer, sheet_name='base_preincome_quantiles')\\n # port_qcut_preinc.to_excel(writer, sheet_name='port_preincome_quantiles')\\n\\n prob_success_df.to_excel(writer, sheet_name='success_probability')\\n\\n # --------------BASE - Accumulation and Income Breakdown based on the success percentile portfolio---------------\\n base_df.to_csv(src + 'base_port_detail.csv')\\n sim_base_total.to_csv(src + 'base_ending_values.csv')\\n income_breakdown_base = pd.DataFrame(sim_base_total.quantile(base_success, axis=1))\\n income_breakdown_base.loc[:, 'income_from_risky_assets'] = sim_base_income.quantile(base_success, axis=1) \\\\\\n - social - cpn_income_port\\n income_breakdown_base.loc[:, 'guaranteed_income'] = 0.0\\n income_breakdown_base.loc[:, 'social_security_income'] = social\\n income_breakdown_base.loc[:, 'coupon_income'] = cpn_income_base\\n\\n income_breakdown_base.rename(columns={income_breakdown_base.columns[0]: 'portfolio_ending_value'}, inplace=True)\\n income_breakdown_base.loc[:, 'income_from_risky_assets'][\\n income_breakdown_base.loc[:, 'portfolio_ending_value'] <= 0] = 0\\n income_breakdown_base.loc[:, 'total_income'] = income_breakdown_base.loc[:, income_breakdown_base.columns[1:]].sum(\\n axis=1)\\n\\n # ----------FIA PORTFOLIO - Accumulation and Income Breakdown based on the success percentile portfolio-----------\\n fia_portfolio_df.to_csv(src + 'fia_port_detail.csv')\\n sim_port_total.to_csv(src + 'fiaport_ending_values.csv')\\n\\n income_breakdown_port = pd.DataFrame(sim_port_total.quantile(port_success, axis=1))\\n income_breakdown_port.loc[:, 'income_from_risky_assets'] = sim_port_income.quantile(port_success, axis=1) \\\\\\n - income_from_fia - social - cpn_income_port\\n income_breakdown_port.loc[:, 'guaranteed_income'] = income_from_fia\\n income_breakdown_port.loc[:, 'social_security_income'] = social\\n income_breakdown_port.loc[:, 'coupon_income'] = cpn_income_port\\n\\n income_breakdown_port.rename(columns={income_breakdown_port.columns[0]: 'portfolio_ending_value'}, inplace=True)\\n income_breakdown_port.loc[:, 'income_from_risky_assets'][\\n income_breakdown_port.loc[:, 'portfolio_ending_value'] <= 0] = 0\\n income_breakdown_port.loc[:, 'total_income'] = income_breakdown_port.loc[:, income_breakdown_port.columns[1:]].sum(\\n axis=1)\\n\\n # -------------------Write simulation Statistics-------------------------------------\\n simulation_stats.to_excel(writer, sheet_name='simulation_statistics')\\n\\n # port_psuccess.to_excel(writer, sheet_name='fia_port_success_probability')\\n\\n income_breakdown_base = income_breakdown_base.loc[1:, :]\\n income_breakdown_base.loc[:, 'age'] = age_index\\n income_breakdown_base.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n income_breakdown_base.loc[income_starts:, :].to_excel(writer, sheet_name='base_income_breakdown_median')\\n\\n income_breakdown_port = income_breakdown_port.loc[1:, :]\\n income_breakdown_port.loc[:, 'age'] = age_index\\n income_breakdown_port.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n income_breakdown_port.loc[income_starts:, :].to_excel(writer, sheet_name='fia_income_breakdown_median')\\n\\n legacy_risk.to_excel(writer, sheet_name='ruin_probability')\\n\\n # if method == 'normal':\\n # median_returns_normal.loc[:, 'fia_median_returns'] = median_normal_fia\\n # median_returns_normal.to_excel(writer, sheet_name='gr_port_median_normal')\\n #\\n # elif method == 'smallest':\\n # median_returns_smallest.loc[:, 'fia_median_returns'] = median_smallest_fia\\n # median_returns_smallest.to_excel(writer, sheet_name='gr_port_median_asc')\\n #\\n # else:\\n # median_returns_largest.loc[:, 'fia_median_returns'] = median_largest_fia\\n # median_returns_largest.to_excel(writer, sheet_name='gr_port_median_desc')\\n\\n # ---------------------Histogram for S&P Forecast---------------------------------------\\n sp_returns = read_returns_est.loc['SPXT Index', 'Annualized Returns']\\n sp_risk = read_returns_est.loc['SPXT Index', 'Annualized Risk']\\n sp_random_ret = np.random.normal(loc=sp_returns, scale=sp_risk, size=10000)\\n bins, data = np.histogram(sp_random_ret, bins=20)\\n df_ret = pd.DataFrame(data, columns=['Return_range'])\\n df_bins = pd.DataFrame(bins, columns=['Count'])\\n df_hist = df_ret.join(df_bins)\\n\\n df_hist.to_excel(writer, sheet_name='sp500_histogram')\\n writer.save()\\n\\n print(\\\"simulation completed....\\\")\",\n \"def calculate(self, data, *args, **kwargs):\\n \\n # Sets up priority queue, where data is prioritized by date\\n queue = []\\n \\n # Sets up data dictionaries that will be used to contain calculated data\\n severity_data = OrderedDict()\\n status_data = OrderedDict()\\n current_state = { }\\n \\n # List of fields used\\n fields = [PROJECT, TRANS, STATUS, PRIORITY]\\n \\n # Populates priority queue with appropriate data\\n for key, param_data in data.iteritems():\\n # Grabs param_data fields\\n priority = param_data.get(PRIORITY, None)\\n hist = param_data.get(HIST, None)\\n proj = param_data.get(PROJECT, self.project)\\n \\n # Adds the historical statuses of the current JIRA item to the queue\\n if (hist):\\n for i, date in enumerate(hist[TRANS]):\\n heapq.heappush(queue, (date, proj, key, hist[NEW][i], priority))\\n \\n # Iterates through dates to populate status and severity data dictionaries\\n if (queue):\\n earliest = queue[0][0]\\n for date in get_historical_dates(earliest, self.extraction_day, False):\\n # Pops items off queue until queue is empty or date limit is reached\\n while(queue and queue[0][0].date() <= date):\\n curr, proj, key, status, priority = heapq.heappop(queue)\\n \\n # Maps the key's current parameters, overwriting previous mapping\\n current_state[key] = { }\\n for field, value in zip(fields, [proj, curr, status, priority]):\\n current_state[key][field] = value\\n \\n # Sets severity and status metric data at the given date\\n severity_data[date] = self._get_severity_data(current_state)\\n status_data[date] = self._get_status_data(current_state)\\n \\n # Gets age data separately from status and severity\\n age_map = self._get_average_age_data(data)\\n \\n return severity_data, status_data, age_map\",\n \"def get_filters():\\n print('\\\\t\\\\tHello! Let\\\\'s explore some US bikeshare data!')\\n \\n # initially\\n city, month, day = None, None, None \\n cities = ['chicago', 'washington', 'new york']\\n months = ['all','january', 'february', 'march', 'april', 'may', 'june']\\n days = ['all','sunday', 'monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday']\\n \\n # TO DO: get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n city = input('\\\\nEnter a city:[ Chicago, Washington or New York ] OR Press e to exit: ').lower() # to ensure consistency of input.\\n while True:\\n if city == 'e': # it means that the user wants to exit the program.\\n break\\n elif city in cities:\\n # to be consistent with the dictionary keys.\\n if city == 'new york': \\n city+=' city' \\n print('You selected to process data about: ', city + '\\\\n')\\n break \\n else: \\n city = input('\\\\nInvalid City.\\\\nEnter Only Chicago, Washigton, New York: ').lower() \\n \\n# -----------------------------End of city selection-----------------------------------------------#\\n \\n # continue the program logic only if the user wants to do so. otherwise, skip.\\n if city != 'e':\\n \\n # TO DO: get user input for month (all, january, february, ... , june)\\n month = input('\\\\nWhich month to filter data with?: \\\\nJanuary\\\\nFebruary\\\\nMarch\\\\nApril\\\\nMay\\\\nJune Or\\\\\\n \\\\n[ all ] if not to filter data by month at all: ').lower()\\n \\n while month not in months:\\n month = input('\\\\nInvalid month.\\\\nEnter a month from January to .. June only or [ all ]\\\\\\n \\\\nto cancel filtering data by month:').lower()\\n if month == 'all':\\n print('You selected not to do any filtering for data by month.\\\\n')\\n else:\\n print('You selected to filter data by: ', month + '\\\\n') \\n \\n # ----------------------------End of month selection------------------------------------------------#\\n \\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n day = input('\\\\nWhich day of the week to filter data with?:\\\\nSaturday\\\\nSunday\\\\nMonday\\\\nTuesday\\\\\\n \\\\nWednesday\\\\nThursday\\\\nFriday Or\\\\n[ all ] if not to filter data by day at all: ').lower()\\n while day not in days:\\n day = input('\\\\nInvalid week day.\\\\nEnter a day from Saturday to .. Friday only or [ all ] to cancel\\\\nfiltering data by day of the week: ').lower()\\n \\n if day == 'all':\\n print('You selected not to do any filtering for data by day.\\\\n')\\n else:\\n print('You selected to filter data by: ', day + '\\\\n\\\\n') \\n \\n # ------------------------End of day selection----------------------------------------------------# \\n \\n print('-'*40)\\n return city, month, day\",\n \"def income_model_user_defined_returns(num_of_years=30, trials=100, method='normal'):\\n\\n print(\\\"Running method income_model_user_defined_returns()\\\")\\n\\n sim_fia_cv = pd.DataFrame(index=range(num_of_years + 1))\\n\\n sim_base_total = pd.DataFrame(index=range(num_of_years + 1))\\n sim_base_income = pd.DataFrame(index=range(num_of_years + 1))\\n\\n sim_port_total = pd.DataFrame(index=range(num_of_years + 1))\\n sim_port_income = pd.DataFrame(index=range(num_of_years + 1))\\n\\n read_income_inputs = pd.read_excel(src + \\\"portfolio_information.xlsx\\\", sheet_name='income_model_inputs',\\n index_col=[0])\\n\\n read_returns_est = pd.read_excel(src + \\\"portfolio_information.xlsx\\\", sheet_name='income_assets_returns_estimates',\\n index_col=[0])\\n clean_names = list(read_returns_est.index)\\n clean_names = [s.split(' ')[0] for s in clean_names]\\n read_returns_est.loc[:, 'names'] = clean_names\\n read_returns_est.set_index('names', drop=True, inplace=True)\\n read_returns_est = read_returns_est[:-1]\\n read_returns_est.rename(index={'SBMMTB3': 'Cash', read_returns_est.index[-1]: 'FIA'}, inplace=True)\\n\\n # ---------------Returns DataFrame based on the user input------------------------------------\\n ann_ret = np.full((num_of_years + 1, len(read_returns_est)), read_returns_est.loc[:, 'Annualized Returns'])\\n read_normal = pd.DataFrame(ann_ret, index=np.arange(num_of_years + 1), columns=read_returns_est.index)\\n # read_normal.rename(columns={read_normal.columns[-1]: 'FIA'}, inplace=True)\\n user_est_fia_return = float(read_income_inputs.loc['fia_forecast', 'inputs'])\\n read_normal.loc[:, 'FIA'] = user_est_fia_return\\n\\n read_asset_weights = pd.read_excel(src + \\\"portfolio_information.xlsx\\\", sheet_name='asset_weights',\\n index_col=[0])\\n\\n # read_asset_weights.drop(read_asset_weights.index[-1], axis=0, inplace=True)\\n\\n # read random returns for simulation\\n read_normal = pd.read_csv(src + 'median_returns_unsorted.csv', index_col=[0], parse_dates=True)\\n cols = [read_normal.columns[c].split('_')[1] for c in np.arange(len(read_normal.columns))]\\n read_normal.rename(columns=dict(zip(list(read_normal.columns), cols)), inplace=True)\\n\\n # ann_ret = np.full((num_of_years+1, len(read_returns_est)), read_returns_est.loc[:, 'Annualized Returns'])\\n # read_normal = pd.DataFrame(ann_ret, index=np.arange(num_of_years+1), columns=read_returns_est.index)\\n # # read_normal.rename(columns={read_normal.columns[-1]: 'FIA'}, inplace=True)\\n # user_est_fia_return = float(read_income_inputs.loc['fia_forecast', 'inputs'])\\n # read_normal.loc[:, 'FIA'] = user_est_fia_return\\n\\n assets_col_names = list(read_normal.columns)\\n\\n tickers = list(read_asset_weights.index)\\n wts = np.array(read_asset_weights.loc[:, 'base'])\\n\\n def asset_median_returns(data, ticker):\\n return data.filter(regex=ticker).median(axis=1)\\n\\n # dataframe for unsorted returns (normal)\\n median_returns_normal = read_normal.copy()\\n median_returns_normal.loc[:, 'portfolio_return'] = median_returns_normal.dot(wts)\\n median_normal_fia = pd.DataFrame({'FIA': asset_median_returns(read_normal, 'FIA')})\\n\\n years = list(range(0, num_of_years + 1))\\n income_cols = ['year', 'strategy_term', 'index_returns', 'term_ret', 'term_ret_with_par', 'term_annualize',\\n 'ann_net_spread', 'term_ret_netspr', 'high_inc_benefit_base', 'rider_fee', 'eoy_income',\\n 'contract_value']\\n\\n term = int(read_income_inputs.loc['term', 'inputs'])\\n fia_ret = read_returns_est.loc[read_returns_est.index[-1], 'Annualized Returns']\\n fia_risk = read_returns_est.loc[read_returns_est.index[-1], 'Annualized Risk']\\n par_rate = float(read_income_inputs.loc['par_rate', 'inputs'])\\n spread = float(read_income_inputs.loc['spread', 'inputs'])\\n bonus_term = int(read_income_inputs.loc['bonus_term', 'inputs'])\\n premium = float(read_income_inputs.loc['premium', 'inputs'])\\n income_bonus = float(read_income_inputs.loc['income_bonus', 'inputs'])\\n\\n income_starts = int(read_income_inputs.loc['start_income_years', 'inputs'])\\n income_growth = float(read_income_inputs.loc['income_growth', 'inputs'])\\n rider_fee = float(read_income_inputs.loc['rider_fee', 'inputs'])\\n inc_payout_factor = float(read_income_inputs.loc['income_payout_factor', 'inputs'])\\n contract_bonus = float(read_income_inputs.loc['contract_bonus', 'inputs'])\\n social = float(read_income_inputs.loc['social', 'inputs'])\\n inflation = float(read_income_inputs.loc['inflation', 'inputs'])\\n wtd_cpn_yield = float(read_income_inputs.loc['wtd_coupon_yld', 'inputs'])\\n life_expectancy = int(read_income_inputs.loc['life_expectancy_age', 'inputs'])\\n clients_age = int(read_income_inputs.loc['clients_age', 'inputs'])\\n\\n # ---------------INCOME MODEL--------------------------------------------\\n runs = 0\\n returns_dict = {}\\n asset_dict = {}\\n fia_dict = {}\\n\\n income_df = pd.DataFrame(index=years, columns=income_cols)\\n income_df.loc[:, 'year'] = years\\n income_df.loc[:, 'strategy_term'] = income_df.loc[:, 'year'] % term\\n income_df.loc[:, 'strategy_term'] = income_df['strategy_term'].apply(lambda x: 1 if x == 0 else 0)\\n income_df.loc[:, 'index_returns'] = read_normal.loc[:, 'FIA']\\n\\n # income_df.loc[:, 'index_returns'] = np.random.normal(fia_ret, fia_risk, size=(len(years), 1))\\n cumprod = (1. + income_df['index_returns']).rolling(window=term).agg(lambda x: x.prod()) - 1\\n income_df.loc[:, 'term_ret'] = np.where(income_df.loc[:, 'strategy_term'] == 1, cumprod, 0)\\n income_df.loc[:, 'term_ret_with_par'] = income_df.loc[:, 'term_ret'] * par_rate\\n income_df.loc[:, 'term_annualize'] = income_df.loc[:, 'term_ret_with_par'].apply(\\n lambda x: (1 + x) ** (1 / term) - 1)\\n income_df.loc[:, 'ann_net_spread'] = income_df.loc[:, 'term_annualize'] - spread\\n income_df.loc[:, 'ann_net_spread'] = np.where(income_df.loc[:, 'strategy_term'] == 1,\\n income_df.loc[:, 'ann_net_spread'], 0)\\n income_df.loc[:, 'term_ret_netspr'] = income_df.loc[:, 'ann_net_spread'].apply(lambda x: (1 + x) ** term - 1)\\n\\n for counter in years:\\n if counter == 0:\\n income_df.loc[counter, 'high_inc_benefit_base'] = premium * (1 + income_bonus)\\n\\n elif counter <= min(bonus_term, income_starts):\\n income_df.loc[counter, 'high_inc_benefit_base'] = income_df.loc[counter - 1, 'high_inc_benefit_base'] * \\\\\\n (1 + income_growth)\\n else:\\n income_df.loc[counter, 'high_inc_benefit_base'] = income_df.loc[counter - 1, 'high_inc_benefit_base']\\n\\n income_df.loc[:, 'rider_fee'] = income_df.loc[:, 'high_inc_benefit_base'] * rider_fee\\n income_df.loc[:, 'eoy_income'] = np.where(income_df.loc[:, 'year'] > income_starts,\\n income_df.loc[:, 'high_inc_benefit_base'] * inc_payout_factor, 0)\\n\\n for counter in years:\\n if counter == 0:\\n income_df.loc[counter, 'contract_value'] = premium * (1 + contract_bonus)\\n\\n elif income_df.loc[counter, 'strategy_term'] == 1:\\n x1 = income_df.loc[counter - 1, 'contract_value'] - income_df.loc[counter, 'rider_fee']\\n x2 = (x1 * (1 + income_df.loc[counter, 'term_ret_netspr'])) - income_df.loc[counter, 'eoy_income']\\n income_df.loc[counter, 'contract_value'] = x2\\n\\n else:\\n x1 = income_df.loc[counter - 1, 'contract_value'] - income_df.loc[counter, 'rider_fee'] - \\\\\\n income_df.loc[counter, 'eoy_income']\\n\\n income_df.loc[counter, 'contract_value'] = x1\\n\\n # variable stores the income number that is used in the base and fia portfolio calcs.\\n\\n income_from_fia = income_df.loc[income_df.index[-1], 'eoy_income']\\n\\n income_df.loc[:, 'contract_value'] = income_df.loc[:, 'contract_value'].apply(lambda x: 0 if x <= 0 else x)\\n\\n sim_fia_cv.loc[:, str(runs)] = income_df.loc[:, 'contract_value']\\n\\n # --------------------BASE MODEL---------------------------------------------\\n base_wts = read_asset_weights.loc[:, 'base']\\n base_assets = list(base_wts.index)\\n base_weights = list(base_wts.values)\\n base_returns = list(read_returns_est.loc[:, 'Annualized Returns'].values)\\n base_std = list(read_returns_est.loc[:, 'Annualized Risk'].values)\\n\\n base_investment = float(read_income_inputs.loc['risky_assets', 'Base'])\\n adv_fees = float(read_income_inputs.loc['advisor_fees', 'Base'])\\n\\n # -------------------required income----------------------------------\\n req_annual_income = float(read_income_inputs.loc['annual_income', 'inputs'])\\n income_needed = req_annual_income - social\\n income_net_fia_income = max(0, income_needed - income_from_fia)\\n cpn_income_base = base_investment * wtd_cpn_yield\\n\\n # ----------------------RANDOM RETURNS--------------------------\\n r_cols = base_assets\\n boy_value = ['bv_{}'.format(name) for name in base_assets]\\n eoy_value = ['ev_{}'.format(name) for name in base_assets]\\n\\n random_returns = pd.DataFrame(index=income_df.index, columns=r_cols)\\n\\n for c in range(len(r_cols)):\\n ret = np.random.normal(base_returns[c], base_std[c], size=(len(random_returns.index), 1))\\n\\n random_returns = read_normal.copy()\\n\\n base_df = random_returns.copy()\\n fia_portfolio_df = random_returns.copy()\\n port_investment = float(read_income_inputs.loc['risky_assets', 'FIA'])\\n cpn_income_port = port_investment * wtd_cpn_yield\\n\\n # -------------BASE PORTFOLIO----------------------------\\n for name in boy_value:\\n base_df.loc[:, name] = 0.0\\n\\n for counter in years:\\n period_returns = list(random_returns.loc[counter, :])\\n if counter == 0:\\n\\n base_df.loc[counter, boy_value] = [base_weights[c] * base_investment for c in range(len(boy_value))]\\n\\n base_df.loc[counter, 'total'] = base_df.loc[counter, boy_value].sum()\\n base_df.loc[counter, 'total_net_fees'] = 0.0\\n base_df.loc[counter, 'income'] = 0.0\\n base_investment = base_df.loc[counter, boy_value].sum()\\n\\n elif (counter > 0) and (counter < income_starts):\\n\\n base_df.loc[counter, boy_value] = [base_weights[c] * base_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n base_df.loc[counter, 'total'] = base_df.loc[counter, boy_value].sum()\\n base_df.loc[counter, 'adv_fees'] = base_df.loc[counter, 'total'] * adv_fees\\n base_df.loc[counter, 'total_net_fees'] = base_df.loc[counter, 'total'] - base_df.loc[\\n counter, 'adv_fees']\\n\\n # --coupon payment is invested back into the risky portfolio until the income is withdrawn----\\n base_investment = base_df.loc[counter, 'total_net_fees'] + cpn_income_base\\n\\n else:\\n\\n base_df.loc[counter, boy_value] = [base_weights[c] * base_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n base_df.loc[counter, 'total'] = base_df.loc[counter, boy_value].sum()\\n base_df.loc[counter, 'adv_fees'] = base_df.loc[counter, 'total'] * adv_fees\\n\\n # ---req. income is adjusted for inflation from the second year of withdrawal. Reinvestment of coupon\\n # stops from the year income starts. Req. income is reduced by the coupon payments\\n\\n if counter == income_starts:\\n\\n income_needed = req_annual_income - social\\n base_df.loc[counter, 'income'] = income_needed - cpn_income_base\\n income_needed = req_annual_income\\n\\n else:\\n income_needed = income_needed * (1 + inflation) - social\\n base_df.loc[counter, 'income'] = income_needed - cpn_income_base\\n income_needed = income_needed + social\\n\\n base_df.loc[counter, 'total_net_fees'] = base_df.loc[counter, 'total'] - \\\\\\n base_df.loc[counter, 'adv_fees'] - \\\\\\n base_df.loc[counter, 'income']\\n\\n base_investment = base_df.loc[counter, 'total_net_fees']\\n\\n base_df.loc[:, 'adj_total'] = base_df.loc[:, 'total_net_fees'].apply(lambda x: x if x > 0 else 0)\\n sim_base_total.loc[:, 's_{}'.format(str(runs))] = base_df.loc[:, 'total_net_fees']\\n sim_base_income.loc[:, 's_{}'.format(str(runs))] = base_df.loc[:, 'income']\\n\\n # ----------------------------FIA PORTFOLIO----------------------------------------------\\n for name in boy_value:\\n fia_portfolio_df.loc[:, name] = 0.0\\n\\n for counter in years:\\n period_returns = list(random_returns.loc[counter, :])\\n if counter == 0:\\n\\n fia_portfolio_df.loc[counter, boy_value] = [base_weights[c] * port_investment\\n for c in range(len(boy_value))]\\n fia_portfolio_df.loc[counter, 'total'] = fia_portfolio_df.loc[counter, boy_value].sum()\\n fia_portfolio_df.loc[counter, 'total_net_fees'] = 0.0\\n fia_portfolio_df.loc[counter, 'income'] = 0.0\\n port_investment = fia_portfolio_df.loc[counter, boy_value].sum()\\n\\n elif (counter > 0) and (counter < income_starts):\\n\\n fia_portfolio_df.loc[counter, boy_value] = [base_weights[c] * port_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n fia_portfolio_df.loc[counter, 'total'] = fia_portfolio_df.loc[counter, boy_value].sum()\\n fia_portfolio_df.loc[counter, 'adv_fees'] = fia_portfolio_df.loc[counter, 'total'] * adv_fees\\n fia_portfolio_df.loc[counter, 'total_net_fees'] = fia_portfolio_df.loc[counter, 'total'] - \\\\\\n fia_portfolio_df.loc[counter, 'adv_fees']\\n\\n port_investment = fia_portfolio_df.loc[counter, 'total_net_fees'] + cpn_income_port\\n\\n else:\\n fia_portfolio_df.loc[counter, boy_value] = [base_weights[c] * port_investment * (1 + period_returns[c])\\n for c in range(len(boy_value))]\\n fia_portfolio_df.loc[counter, 'total'] = fia_portfolio_df.loc[counter, boy_value].sum()\\n fia_portfolio_df.loc[counter, 'adv_fees'] = fia_portfolio_df.loc[counter, 'total'] * adv_fees\\n\\n # ---req. income is adjusted for inflation from the second year of withdrawal. Reinvestment of coupon\\n # stops from the year income starts. Req. income is reduced by the coupon payments\\n\\n if counter == income_starts:\\n\\n income_needed = req_annual_income - social\\n income_net_fia_income = max(0, income_needed - income_from_fia)\\n fia_portfolio_df.loc[counter, 'income'] = max(0, income_net_fia_income - cpn_income_port)\\n income_needed = req_annual_income\\n\\n else:\\n income_needed = income_needed * (1 + inflation) - social\\n income_net_fia_income = max(0, income_needed - income_from_fia)\\n fia_portfolio_df.loc[counter, 'income'] = max(0, income_net_fia_income - cpn_income_port)\\n income_needed = income_needed + social\\n\\n fia_portfolio_df.loc[counter, 'total_net_fees'] = fia_portfolio_df.loc[counter, 'total'] - \\\\\\n fia_portfolio_df.loc[counter, 'adv_fees'] - \\\\\\n fia_portfolio_df.loc[counter, 'income']\\n\\n port_investment = fia_portfolio_df.loc[counter, 'total_net_fees']\\n\\n sim_port_total.loc[:, 's_{}'.format(str(runs))] = fia_portfolio_df.loc[:, 'total_net_fees'] + \\\\\\n income_df.loc[:, 'contract_value']\\n\\n sim_port_income.loc[:, 's_{}'.format(str(runs))] = fia_portfolio_df.loc[:, 'income']\\n\\n fia_portfolio_df.loc[:, 'adj_total'] = fia_portfolio_df.loc[:, 'total_net_fees'].apply(\\n lambda x: x if x > 0 else 0)\\n\\n # ---------income breakdown for Base portfolio----------------------------------\\n base_df.to_csv(src + 'base_port_detail.csv')\\n sim_base_total.to_csv(src + 'base_ending_values.csv')\\n income_breakdown_base = pd.DataFrame(sim_base_total.quantile(0.5, axis=1))\\n income_breakdown_base.loc[:, 'income_from_portfolio'] = sim_base_income.quantile(0.5, axis=1)\\n income_breakdown_base.loc[:, 'fia_income'] = 0.0\\n income_breakdown_base.loc[:, 'social_security_income'] = social\\n income_breakdown_base.loc[:, 'coupon_income'] = cpn_income_base\\n\\n income_breakdown_base.rename(columns={income_breakdown_base.columns[0]: 'portfolio_ending_value'}, inplace=True)\\n income_breakdown_base.loc[:, 'income_from_portfolio'][\\n income_breakdown_base.loc[:, 'portfolio_ending_value'] <= 0] = 0\\n income_breakdown_base.loc[:, 'total_income'] = income_breakdown_base.loc[:, income_breakdown_base.columns[1:]].sum(\\n axis=1)\\n\\n # ------------Block Ends-------------------------------------------------------------\\n\\n # ---------income breakdown for FIA portfolio----------------------------------\\n fia_portfolio_df.to_csv(src + 'fia_port_detail.csv')\\n sim_port_total.to_csv(src + 'fiaport_ending_values.csv')\\n\\n income_breakdown_port = pd.DataFrame(sim_port_total.quantile(0.5, axis=1))\\n income_breakdown_port.loc[:, 'income_from_portfolio'] = sim_port_income.quantile(0.5, axis=1)\\n income_breakdown_port.loc[:, 'fia_income'] = income_from_fia\\n income_breakdown_port.loc[:, 'social_security_income'] = social\\n income_breakdown_port.loc[:, 'coupon_income'] = cpn_income_port\\n\\n income_breakdown_port.rename(columns={income_breakdown_port.columns[0]: 'portfolio_ending_value'}, inplace=True)\\n income_breakdown_port.loc[:, 'income_from_portfolio'][\\n income_breakdown_port.loc[:, 'portfolio_ending_value'] <= 0] = 0\\n income_breakdown_port.loc[:, 'total_income'] = income_breakdown_port.loc[:, income_breakdown_port.columns[1:]].sum(\\n axis=1)\\n\\n # ------------Block Ends-------------------------------------------------------------\\n q_cut = [0.0, 0.05, 0.25, 0.5, 0.75, 0.95, 1.0]\\n sim_base_income[sim_base_total < income_needed] = 0.0\\n\\n sim_port_income[sim_port_total < income_net_fia_income] = 0\\n\\n sim_port_income = sim_port_income + income_from_fia\\n\\n # base_quantile = sim_base_total.loc[sim_base_total.index[-1]].quantile([0.05, 0.25, 0.50, 0.75, 0.90])\\n\\n # port_quantile = sim_port_total.loc[sim_port_total.index[-1]].quantile([0.05, 0.25, 0.50, 0.75, 0.90])\\n\\n base_quantile = sim_base_total.loc[sim_base_total.index[-1]].quantile(q_cut)\\n\\n port_quantile = sim_port_total.loc[sim_port_total.index[-1]].quantile(q_cut)\\n\\n # q_cut = [0.0, .05, 0.25, 0.5, 0.75, 0.95, 1.0]\\n cols = ['Min', '5th', '25th', '50th', '75th', '90th', 'Max']\\n\\n # ----drop year 0--------\\n sim_base_total = sim_base_total[1:]\\n sim_port_total = sim_port_total[1:]\\n\\n # ----------------quantile analysis for base terminal value--------------------------\\n base_qcut = pd.DataFrame(index=sim_base_total.index, columns=cols)\\n for c in range(len(cols)):\\n base_qcut.loc[:, cols[c]] = sim_base_total.quantile(q_cut[c], axis=1)\\n\\n base_qcut.clip(lower=0, inplace=True)\\n\\n # ----------------------quantile analysis for base income----------------------------\\n base_income_qcut = pd.DataFrame(index=sim_base_income.index, columns=cols)\\n for c in range(len(cols)):\\n base_income_qcut.loc[:, cols[c]] = sim_base_income.quantile(q_cut[c], axis=1)\\n\\n # ----Remove NaN's prior to the income start years------------\\n # base_income_qcut = base_income_qcut.loc[income_starts:]\\n\\n # -------------quantile analysis for portfolio terminal value ----------------\\n port_qcut = pd.DataFrame(index=sim_port_total.index, columns=cols)\\n for c in range(len(cols)):\\n port_qcut.loc[:, cols[c]] = sim_port_total.quantile(q_cut[c], axis=1)\\n\\n port_qcut.clip(lower=0, inplace=True)\\n\\n # ---------------quantile analysis for portfolio income----------------------------\\n port_income_qcut = pd.DataFrame(index=sim_port_income.index, columns=cols)\\n for c in range(len(cols)):\\n port_income_qcut.loc[:, cols[c]] = sim_port_income.quantile(q_cut[c], axis=1)\\n\\n # ----Remove NaN's prior to the income start years------------\\n # port_income_qcut = port_income_qcut.loc[income_starts:]\\n\\n # ----------probability ending value will be less than 0 at the end of the horizon -----------------------\\n base_legacy_risk = (sim_base_total.loc[sim_base_total.index[life_expectancy - clients_age]] < 0).sum() / (\\n trials + 1)\\n port_legacy_risk = (sim_port_total.loc[sim_port_total.index[life_expectancy - clients_age]] < 0).sum() / (\\n trials + 1)\\n\\n legacy_risk = pd.DataFrame([base_legacy_risk, port_legacy_risk,\\n 'Prob. of portfolio value less than 0 at the end of the expected life'],\\n index=['base', 'fia_portfolio', 'Notes'],\\n columns=['Ruin Probability'])\\n\\n # -----------Year-wise probability of ending value greater than 0 -----------------\\n base_psuccess = sim_base_total.apply(lambda x: x > 0).sum(axis=1) / (trials + 1)\\n port_psuccess = sim_port_total.apply(lambda x: x > 0).sum(axis=1) / (trials + 1)\\n\\n # -----------------------WRITING FILES TO EXCEL ---------------------------\\n col_names = ['50th', 'age', 'comment']\\n writer = pd.ExcelWriter(src + method + '_simulated_income_summary_custom.xlsx', engine='xlsxwriter')\\n read_income_inputs.to_excel(writer, sheet_name='inputs_for_income')\\n\\n read_returns_est.to_excel(writer, sheet_name='asset_returns_estimates')\\n\\n age_index = list(range(clients_age + 1, clients_age + len(base_qcut) + 1))\\n base_qcut.loc[:, 'age'] = age_index\\n base_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n base_qcut.loc[income_starts:, col_names].to_excel(writer, sheet_name='base_ending_value_quantiles')\\n\\n base_income_qcut = base_income_qcut.loc[1:, :]\\n base_income_qcut.loc[:, 'age'] = age_index\\n base_income_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n base_income_qcut.loc[income_starts:, col_names].to_excel(writer, sheet_name='base_income_quantiles')\\n\\n port_qcut.loc[:, 'age'] = age_index\\n port_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n port_qcut.loc[income_starts:, col_names].to_excel(writer, sheet_name='fia_port_ending_value_quantiles')\\n\\n port_income_qcut = port_income_qcut.loc[1:, :]\\n port_income_qcut.loc[:, 'age'] = age_index\\n port_income_qcut.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n port_income_qcut.loc[income_starts:, col_names].to_excel(writer, sheet_name='fia_port_income_quantiles')\\n\\n income_breakdown_base = income_breakdown_base.loc[1:, :]\\n income_breakdown_base.loc[:, 'age'] = age_index\\n income_breakdown_base.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n income_breakdown_base.loc[income_starts:, :].to_excel(writer, sheet_name='base_income_breakdown_median')\\n\\n income_breakdown_port = income_breakdown_port.loc[1:, :]\\n income_breakdown_port.loc[:, 'age'] = age_index\\n income_breakdown_port.loc[life_expectancy - clients_age, 'comment'] = 'expected_life'\\n income_breakdown_port.loc[:, 'ending_contract_value'] = income_df.loc[:, 'contract_value']\\n income_breakdown_port.loc[income_starts:, :].to_excel(writer, sheet_name='fia_income_breakdown_median')\\n\\n median_returns_normal.to_excel(writer, sheet_name='gr_port_median_normal')\\n\\n terminal_val = pd.read_csv(src + 'terminal_values.csv', index_col=[0])\\n ending_val = pd.read_csv(src + 'ending_values.csv', index_col=[0])\\n ending_val_ror = pd.read_csv(src + 'ending_values_ror.csv', index_col=[0])\\n\\n terminal_val.to_excel(writer, sheet_name='terminal_values')\\n ending_val.to_excel(writer, sheet_name='port_ending_values')\\n ending_val_ror.to_excel(writer, sheet_name='port_annual_growth')\\n\\n writer.save()\\n\\n # -----------------Plotting charts--------------------------------------------\\n base_qcut.loc[income_starts:].plot(grid=True, title='Quantile Terminal Value - Base Portfolio')\\n plt.savefig(src + \\\"quantile_terminal_base.png\\\")\\n plt.close('all')\\n\\n base_income_qcut.plot(grid=True, title='Quantile Income - Base Portfolio')\\n plt.savefig(src + \\\"quantile_income_base.png\\\")\\n plt.close('all')\\n\\n base_psuccess.plot(grid=True, title='Probability of Success (Portfolio Ending Value > 0) - Base Portfolio')\\n plt.savefig(src + \\\"success_probabilty_base.png\\\")\\n plt.close('all')\\n\\n (1 - base_psuccess).plot(grid=True, title='Probability of Ruin (Portfolio Ending Value < 0) - Base Portfolio')\\n plt.savefig(src + \\\"ruin_probability_base.png\\\")\\n plt.close('all')\\n\\n port_qcut.loc[income_starts:].plot(grid=True, title='Quantile Terminal Value - FIA Portfolio')\\n plt.savefig(src + \\\"quantile_terminal_fia.png\\\")\\n plt.close('all')\\n\\n port_income_qcut.plot(grid=True, title='Quantile Income - FIA Portfolio')\\n plt.savefig(src + \\\"quantile_income_fia.png\\\")\\n plt.close('all')\\n\\n port_psuccess.plot(grid=True, title='Probability of Success (Portfolio Ending Value > 0) - FIA Portfolio')\\n plt.savefig(src + \\\"success_probabilty_fia.png\\\")\\n plt.close('all')\\n\\n (1 - port_psuccess).plot(grid=True, title='Probability of Ruin (Portfolio Ending Value < 0) - FIA Portfolio')\\n plt.savefig(src + \\\"ruin_probability_fia.png\\\")\\n plt.close('all')\\n\\n print(\\\"simulation completed for {}\\\".format(method))\",\n \"def get_filters():\\n print('Welcome! Let\\\\'s explore some US bikeshare data!')\\n # TO DO: get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n\\n while True:\\n try:\\n city = input(\\\"Enter the name of the city you want to explore the data of (chicago, new york city, or washington): \\\")\\n if city not in dict.keys(CITY_DATA):\\n raise Exception ('Invalid city name')\\n print (\\\"You have selected: {}.\\\\n\\\".format(city.title()))\\n break\\n except Exception :\\n print (\\\"Invalid name of city, please choose chicago, new york city, or washington (writtent in this format)\\\\n\\\")\\n\\n # TO DO: get user input for month (all, january, february, ... , june)\\n\\n while True:\\n valid_months_names =('all', 'january', 'february', 'march', 'april', 'may', 'june')\\n try:\\n month = input(\\\"Enter the month that you wish to explore (use 'all' for the entire timeframe): \\\")\\n if month not in valid_months_names:\\n raise Exception ('Invalid month name')\\n print (\\\"You have selected: {}.\\\\n\\\".format(month.title()))\\n break\\n except Exception :\\n print (\\\"Invalid month: Please choose from all, january, february, march, april, may, june\\\\n\\\")\\n\\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n\\n while True:\\n valid_day_names =('all', 'monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday')\\n try:\\n day = input(\\\"Enter the day that you wish to explore (use 'all' for exploring all days): \\\")\\n if day not in valid_day_names:\\n raise Exception ('Invalid day name')\\n print (\\\"You have selected: {}.\\\\n\\\".format(day.title()))\\n break\\n except Exception :\\n print (\\\"Invalid day: Please choose from all, monday, tuesday, wednesday, thursday, friday, saturday, sunday\\\\n\\\")\\n\\n print('-'*40)\\n return city, month, day\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data!')\\n\\n# Get user input for city (chicago, new york city, washington)\\n\\n input_city = input(\\\"Do you want to look at data from Chicago, New York City, or Washington? Enter the city name: \\\").lower()\\n while input_city != 'chicago' and input_city != 'new york city' and input_city != 'washington':\\n print('Please enter a valid city name. There is only data of Chicago, NYC, and Washington.')\\n input_city = input(\\\"Do you want to look at data from Chicago, New York City, or Washington? Enter the city name: \\\").lower()\\n continue\\n\\n if input_city == 'chicago'or input_city == 'new york city' or input_city == 'washington':\\n city = input_city\\n print(\\\"\\\\nGreat! Let's look at {} then!\\\".format(city))\\n\\n\\n # Get user input for month (all, january, february, ... , june)\\n\\n input_month = input(\\\"What month do you want to look at? If you don't want to specify, type 'all'. Please enter the month: \\\").lower()\\n while input_month not in ('january', 'february', 'march', 'april', 'may', 'june', 'july', 'august', 'september', 'october', 'november', 'december', 'all'):\\n print('Sorry, this seems to be an unvalid entry. Please enter a valid month.')\\n input_month = input(\\\"What month do you want to look at? If you don't want to specify, type 'all'. Please enter the month: \\\").lower()\\n continue\\n\\n if input_month in ('january', 'february', 'march', 'april', 'may', 'june', 'july', 'august', 'september', 'october', 'november', 'december', 'all'):\\n month = input_month\\n print(\\\"\\\\nGreat! Let's look at {} then!\\\".format(month))\\n\\n # Get user input for day of week (all, monday, tuesday, ... sunday)\\n\\n input_day = input(\\\"Do you want to filter by day of the week? If not, type 'all'. If yes, please enter the name of the weekday: \\\").lower()\\n while input_day not in ('monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday', 'all'):\\n print('Sorry, this seems to be an unvalid entry. Please enter a valid name of a weekday.')\\n input_day = input(\\\"Do you want to filter by day of the week? If not, type 'all'. If yes, please enter the name of the weekday: \\\").lower()\\n continue\\n\\n if input_day in ('monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday', 'all'):\\n day = input_day\\n print(\\\"\\\\nGreat! Let's look at {} then!\\\".format(day))\\n\\n print('-'*40)\\n return city, month, day\",\n \"def generate_report(df, start_date, end_date):\\n # Remove any transactions that had to do with collecting or returning security\\n security_df = df[(df[CATEGORY] == 'Security') | (df[CATEGORY] == 'Security-Income')]\\n df = df[(df[CATEGORY] != 'Security')]\\n\\n # Exclude the data for everything except our quarter\\n period_data = df.loc[start_date:end_date] # Note: NOT using extended quarter range\\n rental_income = period_data[period_data[CATEGORY] == 'Rent']\\n utilities = period_data[(period_data[CATEGORY] == 'Utilities')]\\n other_income = period_data[(period_data['Transaction Type'] == 'credit') & (period_data[CATEGORY] != 'Rent')]\\n expenses = period_data[(period_data['Transaction Type'] == 'debit')]\\n unpaid_util_overages = float(0)\\n\\n # print(rental_income)\\n # print(other_income)\\n # print(expenses)\\n \\n html_config.initialize()\\n print(html_config.HTML_OPEN)\\n\\n print('<H1>Income and Expense Report for %s-%s:' % (start_date, end_date), '</H1><p>')\\n\\n # List all unit specific rents and expenses for the quarter\\n for UNIT in sorted(rental_income['Unit'].unique()):\\n # Show rental income info\\n temp_df = rental_income[rental_income['Unit'] == UNIT]\\n print('<br><H2>Total rent for Unit ', UNIT, ': ${:,.2f}'.format(temp_df['Amount'].sum()), '</H2>')\\n print(temp_df[['Description', 'Amount']].to_html())\\n \\n if not SKIP_UTIL_ANALYSIS:\\n # Show utilities payments and calculate any overage due\\n temp_df = utilities[(utilities['Unit'] == UNIT) & (utilities['Transaction Type'] == 'debit')]\\n print('<br><H2>Utilities Expenses for Unit', UNIT, ': ${:,.2f}'.format(temp_df['Amount'].sum()), '</h2>')\\n overage = temp_df.assign(Overage=lambda x: x.Amount - limit_df.loc[UNIT].Amount)\\n # Disable warning when setting negative overage values to zero\\n pd.set_option('mode.chained_assignment', None)\\n overage.Overage[overage.Overage < 0] = 0\\n pd.set_option('mode.chained_assignment', 'warn')\\n print(overage[['Description', 'Amount', 'Overage']].to_html())\\n # Show if utilties costs exceeded allotted amount\\n if (overage['Overage'].sum() > 0):\\n print('<h3>Utilities overage for unit', UNIT, ': ${:,.2f}'.format(overage['Overage'].sum()), '</h3>')\\n unpaid_util_overages += overage['Overage'].sum()\\n # Show any untilities that were collected \\n overage_collected = utilities[(utilities['Unit'] == UNIT) & (utilities['Transaction Type'] == 'credit')]\\n if not overage_collected.empty:\\n print('<br><H2>Util overages collected for Unit ', UNIT, ': ${:,.2f}'.format(overage_collected['Amount'].sum()), '</H2>')\\n print(overage_collected[['Description', 'Amount', CATEGORY]].to_html())\\n print('<h3>Net Utils overage for unit', UNIT, 'for period: ${:,.2f}'.format(overage['Overage'].sum() - overage_collected['Amount'].sum()), '</h3>')\\n \\n\\n \\n # Generate unit specific Utility usage reports\\n if GEN_TENANT_UTIL_REPORTS and OUTPUT_DIRECTORY:\\n TENANT_FILE = '%s/122-Spring-St-%s-%s-Unit-%s-utils.html' % (OUTPUT_DIRECTORY, start_date, end_date, UNIT)\\n TENANT_REPORTS.append(TENANT_FILE)\\n sys.stdout = open(TENANT_FILE, 'w')\\n print(html_config.HTML_OPEN)\\n\\n print('<H1>Unit', UNIT, '</H1>')\\n print('<br><H2>Utilities Expenses for: %s-%s' % (start_date, end_date))\\n print('<br>Utilites included in rent: ${:,.2f}'.format(limit_df.loc[UNIT].Amount))\\n print('</H2>')\\n print(overage[['Description', 'Amount', 'Overage']].to_html())\\n # Show if any utilties overage may be due\\n if (overage['Overage'].sum() > 0):\\n print('<h3>Utilities overage for unit', UNIT, ': ${:,.2f}'.format(overage['Overage'].sum()), '</h3>')\\n if not overage_collected.empty:\\n print('<br><H2>Util overages collected for Unit ', UNIT, ': ${:,.2f}'.format(overage_collected['Amount'].sum()), '</H2>')\\n print(overage_collected[['Description', 'Amount', CATEGORY]].to_html())\\n print('<h3>Net Utils overage for unit', UNIT, 'for period: ${:,.2f}'.format(overage['Overage'].sum() - overage_collected['Amount'].sum()), '</h3>')\\n\\n print(html_config.HTML_CLOSE)\\n\\n # Restore stdout to the main report file\\n sys.stdout = open(REPORT_FILE, 'a')\\n \\n # Show other unit specific transactions\\n if SKIP_UTIL_ANALYSIS:\\n unit_exp = expenses[(expenses['Unit'] == UNIT)]\\n unit_income = other_income[other_income['Unit'] == UNIT]\\n else:\\n unit_exp = expenses[(expenses['Unit'] == UNIT) & (expenses[CATEGORY] != 'Utilities')]\\n unit_income = other_income[(other_income['Unit'] == UNIT) & (other_income[CATEGORY] != 'Utilities')]\\n \\n if not unit_exp.empty:\\n print('<br><H2>Other Unit specific expenses for: ', UNIT, ': ${:,.2f}'.format(unit_exp['Amount'].sum()), '</h2>')\\n print(unit_exp[['Description', 'Amount', 'Unit', CATEGORY]].to_html())\\n print('<p>')\\n \\n # Show any other unit specific credit\\n other_income = other_income[other_income['Unit'] == UNIT]\\n if not other_income.empty:\\n print('<br><H2>Expense offsets for Unit ', UNIT, ': ${:,.2f}'.format(other_income['Amount'].sum()), '</H2>')\\n print(other_income[['Description', 'Amount', CATEGORY]].to_html())\\n \\n # Add a line between units\\n print('<hr>')\\n \\n # List the shared income and expenses for the quarter\\n temp_df = other_income[other_income['Unit'].isnull()]\\n if not temp_df.empty:\\n print ('<br><H2>Non unit specific income: ${:,.2f}'.format(temp_df['Amount'].sum()), '</h2>')\\n print(temp_df[['Description', 'Amount', CATEGORY]].to_html())\\n gen_expenses = expenses[expenses['Unit'].isnull()]\\n if not gen_expenses.empty:\\n print ('<br><H1>Non unit specific expenses</h1>')\\n # Get the list of expense categories and generate summary for each\\n for category in sorted(gen_expenses[CATEGORY].unique()):\\n temp_df = gen_expenses[(gen_expenses[CATEGORY] == category)]\\n print ('<br><H2>'+ category +': ${:,.2f}'.format(temp_df['Amount'].sum()), '</h2>')\\n print(temp_df[['Description', 'Amount', CATEGORY]].to_html())\\n \\n # If there were any security transactions in the period give a security report\\n if not security_df.loc[start_date:end_date].empty:\\n temp_df = security_df.loc[start_date:end_date] \\n print('<hr><H2>Security related transactions:</H2>')\\n print(temp_df[['Description', 'Amount', 'Transaction Type', 'Unit']].to_html())\\n for UNIT in sorted(rental_income['Unit'].unique()):\\n unit_df = security_df[security_df['Unit'] == UNIT]\\n collected = unit_df[(unit_df['Transaction Type'] == 'credit')]['Amount'].sum()\\n returned = unit_df[(unit_df['Transaction Type'] == 'debit')]['Amount'].sum()\\n print('<center><H4>Current Liability on Unit '+str(UNIT)+': ${:,.2f}'.format(collected-returned), '</H4></center>')\\n \\n # # Summarize the periods income and expenses -- old way to be discarded...\\n # print('<br><H3>Total income for period: ${:,.2f}'.format(rental_income['Amount'].sum()), '</H3>')\\n # print('<H3>Total expense for period: ${:,.2f}'.format(expenses['Amount'].sum() - other_income['Amount'].sum()), '</H3>')\\n # print('<H3>Profit for period: ${:,.2f}'.format(rental_income['Amount'].sum() + other_income['Amount'].sum() -expenses['Amount'].sum()), '</H3>')\\n # Summarize the periods income and expenses\\n print('<br><H3>Total income for period: ${:,.2f}'.format(rental_income['Amount'].sum()))\\n print('<br><H3>Total expense for period: ${:,.2f}'.format(expenses['Amount'].sum() - other_income['Amount'].sum()), '</H3>')\\n print('<H3>Profit for period: ${:,.2f}'.format(rental_income['Amount'].sum() + other_income['Amount'].sum() -expenses['Amount'].sum()), '</H3>')\\n# print('</H3>')\\n \\n print(html_config.HTML_CLOSE)\\n sys.stdout.flush()\",\n \"def generate_portfolio_data(self):\\n self.__load_portfolio_historical_prices()\\n self.__populate_historical_trade_data()\\n self.__calculate_portfolio_returns()\\n self.__calculate_portfolio_performance()\",\n \"def get_annual_energy_demand(cfg):\\n houses_dict = cfg['houses']\\n houses_list = sorted(houses_dict.keys())\\n\\n # Calculate annual energy demand of houses\\n # and store the result in the dict containing the house info\\n for house_name in houses_list:\\n house_type = houses_dict[house_name]['house_type']\\n N_Pers = houses_dict[house_name].get('N_Pers', None)\\n N_WE = houses_dict[house_name].get('N_WE', None)\\n\\n # Assign defaults if values are not defined\\n if house_type == 'EFH' and pd.isna(N_Pers):\\n N_Pers = 3\\n houses_dict[house_name]['N_Pers'] = N_Pers\\n logger.warning('N_Pers not defined for ' + str(house_name)\\n + '. Using default ' + str(N_Pers))\\n if house_type == 'MFH' and pd.isna(N_WE):\\n N_WE = 2\\n houses_dict[house_name]['N_WE'] = N_WE\\n logger.warning('N_WE not defined for ' + str(house_name)\\n + '. Using default ' + str(N_WE))\\n\\n # Implement the restrictions defined on page 3:\\n if house_type == 'EFH' and N_Pers > 12:\\n logger.warning('VDI 4655 is only defined for N_Pers <= 12. '\\n + str(house_name) + ' uses N_Pers = ' + str(N_Pers)\\n + '. Proceeding with your input...')\\n if house_type == 'MFH' and N_WE > 40:\\n logger.warning('VDI 4655 is only defined for N_WE <= 40. '\\n + str(house_name) + ' uses N_WE = ' + str(N_WE)\\n + '. Proceeding with your input...')\\n\\n # Calculate annual energy demand estimates\\n if house_type == 'EFH':\\n # (6.2.2) Calculate annual electrical energy demand of houses:\\n if N_Pers < 3:\\n W_a = N_Pers * 2000 # kWh\\n elif N_Pers <= 6:\\n W_a = N_Pers * 1750 # kWh\\n else:\\n W_a = N_Pers * 1500 # kWh\\n\\n # (6.2.3) Calculate annual DHW energy demand of houses:\\n Q_TWW_a = N_Pers * 500 # kWh\\n\\n elif house_type == 'MFH':\\n # (6.2.2) Calculate annual electrical energy demand of houses:\\n W_a = N_WE * 3000 # kWh\\n\\n # (6.2.3) Calculate annual DHW energy demand of houses:\\n Q_TWW_a = N_WE * 1000 # kWh\\n\\n else:\\n # No house category given. Just use annual demand of 1 kWh\\n W_a = 1\\n Q_TWW_a = 1\\n\\n # If W_a and/or Q_TWW_a were already defined by the user in the yaml\\n # file, we use those values instead of the calculated ones:\\n W_a = houses_dict[house_name].get('W_a', W_a)\\n Q_TWW_a = houses_dict[house_name].get('Q_TWW_a', Q_TWW_a)\\n\\n # Store the results in the dict\\n houses_dict[house_name]['W_a'] = W_a\\n houses_dict[house_name]['Q_TWW_a'] = Q_TWW_a\\n\\n # Assign defaults if values are not defined\\n if houses_dict[house_name].get('Q_Heiz_a', None) is None:\\n Q_Heiz_a = 1 # kWh\\n houses_dict[house_name]['Q_Heiz_a'] = Q_Heiz_a\\n logger.warning('Q_Heiz_a not defined for ' + house_name\\n + '. Using default ' + str(Q_Heiz_a) + ' kWh')\\n\\n # Apply the adjustment factors\\n houses_dict[house_name]['Q_Heiz_a'] *= \\\\\\n cfg.get('adjustment_factors', dict()).get('f_Q_Heiz', 1)\\n\\n houses_dict[house_name]['W_a'] *= \\\\\\n cfg.get('adjustment_factors', dict()).get('f_W', 1)\\n\\n houses_dict[house_name]['Q_TWW_a'] *= \\\\\\n cfg.get('adjustment_factors', dict()).get('f_Q_TWW', 1)\\n\\n return houses_dict\",\n \"def step(self, actions):\\n\\n representative_data = []\\n original_data = []\\n\\n actions = np.array(actions).reshape(3, -1)\\n\\n for np_data, df_data, calculator, som, action in zip(self.np_data_list, self.df_data_list, self.calculators, self.som_objects, actions):\\n\\n representative_days, cluster_numbers = calculator.get_representative_days(\\n som, np_data, action)\\n\\n representative_days = pd.DataFrame(representative_days)\\n\\n representative_days = self.wide_to_long(representative_days)\\n approximation_calc = ApproximateData(df_data, 4)\\n representative_days = ApproximateData(df_data, 4).get_load_duration_curve(\\n representative_days, cluster_numbers)\\n\\n representative_data.append(representative_days)\\n\\n # original_days = approximation_calc.get_load_duration_curve(\\n # year=\\\"2013\\\")\\n\\n\\n\\n # original_data.append(original_days)\\n\\n # metrics_calculator = Metrics(original_data[0], representative_data[0], original_data[1],\\n # representative_data[1], original_data[2], representative_data[2], \\\"dc\\\")\\n\\n pv_original = pd.read_csv(\\n '{}data/processed/resources/pv_processed.csv'.format(project_dir))\\n wind_original = pd.read_csv(\\n '{}data/processed/resources/onshore_processed.csv'.format(project_dir))\\n load_original = pd.read_csv(\\n '{}data/processed/demand/load_NG/load_processed_normalised.csv'.format(project_dir))\\n\\n pv_original_ldcs, wind_original_ldcs, load_original_ldcs = get_each_ldc(pv_original, wind_original, load_original)\\n\\n multi_year_metrics_calculator = MultiYearMetrics(pv_original_ldcs, representative_data[0], wind_original_ldcs, representative_data[1], load_original_ldcs, representative_data[2], self.year_start)\\n multi_year_metrics = multi_year_metrics_calculator.get_multi_year_average_metrics(\\\"dc\\\")\\n multi_year_metrics = multi_year_metrics.reset_index()\\n # logger.debug(\\\"multi_year_metrics: \\\\n{}\\\".format(multi_year_metrics))\\n\\n nrmse = multi_year_metrics[multi_year_metrics['metric'] == 'nrmse dc'].iloc[0].value\\n rae = multi_year_metrics[multi_year_metrics['metric'] == 'rae dc'].iloc[0].value\\n correlation = multi_year_metrics[multi_year_metrics['metric'] == 'correlation'].iloc[0].value\\n\\n # error_metrics = metrics_calculator.get_mean_error_metrics()\\n # nrmse = error_metrics.iloc[1].value\\n # rae = error_metrics.iloc[2].value\\n # correlation = error_metrics.iloc[0].value\\n # reward = -error_metrics.value.sum()\\n # logger.info(\\\"error_metrics: {}\\\".format(error_metrics))\\n # logger.info(\\\"error_metrics: {}\\\".format(error_metrics.iloc[0]))\\n\\n # return reward\\n return nrmse, rae, correlation\",\n \"def pe_analysis():\\r\\n\\r\\n global params\\r\\n n = params['n']\\r\\n level = params['level']\\r\\n pemin = params['pemin']\\r\\n pemax = params['pemax']\\r\\n pestep = params['pestep']\\r\\n ns = params['ns']\\r\\n nt = params['nt']\\r\\n po = params['po']\\r\\n pf = params['pf']\\r\\n pe_dir = create_dir(TIMES_PATH + 'pe')\\r\\n filename = datetime.datetime.now().strftime(DATE_FORMAT) + '.csv'\\r\\n with open(pe_dir + filename, 'wb') as csvfile:\\r\\n fw = csv.writer(csvfile)\\r\\n fw.writerow(('lv', 'ns', 'nt', 'no', 'pe', 'ne', 'nf',\\r\\n 'method1', 'method2', 'method3_1', 'method3_2'))\\r\\n pe = pemin\\r\\n while pe <= pemax:\\r\\n no = max(int(round(po * nt)), 1)\\r\\n ne = max(int(round(pe * no)), 1)\\r\\n nf = max(int(round(pf * nt)), 1)\\r\\n times = [0] * 4\\r\\n for i in range(n):\\r\\n times = map(sum, zip(times, get_times(level, ns, nt, no, ne, nf)))\\r\\n show_progress('pe', pe, pemin, pemax, pestep, i, n)\\r\\n times = map(lambda x: float(x) / n, times)\\r\\n fw.writerow((level, ns, nt, no, pe, ne, nf) + tuple(times))\\r\\n pe += pestep\\r\\n csvfile.close()\",\n \"def get_filters():\\n print('='*65)\\n print('Hello! Welcome to explore some US bikeshare data!')\\n print('='*65)\\n # get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n city = ''\\n while city not in CITY_DATA.keys():\\n print(\\\"\\\\nPlease enter city (chicago, new york city or washington):\\\")\\n #Taking user input and converting into lower to standardize them\\n city = input().lower()\\n\\n if city not in CITY_DATA.keys():\\n print(\\\"\\\\nInvalid input. Please try again in the accepted input format.\\\")\\n\\n # get user input for month (all, january, february, ... , june)\\n #Creating a dictionary to store all the months including the 'all' option\\n MONTH_DATA = {'january': 1, 'february': 2, 'march': 3, 'april': 4, 'may': 5, 'june': 6, 'all': 7}\\n month = ''\\n while month not in MONTH_DATA.keys():\\n print(\\\"\\\\nPlease enter the month (between January and June) or all, for which you're seeking data:\\\")\\n month = input().lower()\\n\\n if month not in MONTH_DATA.keys():\\n print(\\\"\\\\nInvalid input. Please try again in the accepted input format.\\\")\\n\\n # get user input for day of week (all, monday, tuesday, ... sunday)\\n #Creating a list to store all the days including the 'all' option\\n DAY_DATA = ['all', 'monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday']\\n day = ''\\n while day not in DAY_DATA:\\n print(\\\"\\\\nPlease enter a day in the week or all, for which you're seeking data:\\\")\\n day = input().lower()\\n\\n if day not in DAY_DATA:\\n print(\\\"\\\\nInvalid input. Please try again in one of the accepted input formats.\\\")\\n\\n print(f\\\"\\\\nYou have chosen: city: {city.upper()}, month/s: {month.upper()} and day/s: {day.upper()}.\\\")\\n print('-'*65)\\n\\n #Returning the city, month and day selections\\n return city, month, day\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data!')\\n # TO DO: get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n\\n # Get the names of the cities \\n city = ''\\n while city not in CITY_DATA.keys():\\n print(\\\"\\\\nPlease enter the name of the city to analyze\\\")\\n print(\\\"\\\\nValid values are Chicago, New York City, Washington. Note the city name is not case sensitive\\\")\\n city = input(\\\"\\\\nCity: \\\").lower()\\n\\n if city not in CITY_DATA.keys():\\n print(\\\"\\\\nInvalid or unknown city specified.\\\")\\n \\n print(f\\\"\\\\nYou selected '{city.title()}' as city\\\")\\n\\n # TO DO: get user input for month (all, january, february, ... , june)\\n\\n month = ''\\n MONTH_OPTS = ['january','february','march','april','may','june','all']\\n while month not in MONTH_OPTS:\\n print(\\\"\\\\nPlease enter the month(s) for which to get data to analyze\\\")\\n print(\\\"\\\\nOptions are january to june\\\")\\n print(\\\"\\\\nYou can also enter 'all' to view data for all months\\\")\\n month = input(\\\"\\\\nMonth: \\\").lower()\\n\\n if month not in MONTH_OPTS:\\n print(\\\"\\\\nInvalid or unknown month specified.\\\")\\n \\n print(f\\\"\\\\nYou selected '{month.title()}' as month\\\")\\n\\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n DAY_OPTS = ['all','monday','tuesday','wednesday','thursday','friday','saturday','sunday']\\n day = ''\\n while day not in DAY_OPTS:\\n print(\\\"\\\\nPlease enter the day(s) for which to get data to analyze\\\")\\n print(\\\"\\\\nOptions are monday to sunday\\\")\\n print(\\\"\\\\nYou can also enter 'all' to view data for all days\\\")\\n day = input(\\\"\\\\nDay: \\\").lower()\\n\\n if day not in DAY_OPTS:\\n print(\\\"\\\\nInvalid or unknown day specified. Retrying ...\\\")\\n \\n print(f\\\"\\\\nYou selected '{day.title()}' as day\\\")\\n\\n print('-'*40)\\n return city, month, day\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data!')\\n # TO DO: get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n \\n cities = ['Chicago', 'New York', 'Washington']\\n filterValues = ['Month', 'Day', 'Both', 'None']\\n months = ['January', 'February', 'March', 'April', 'May', 'June'] \\n days = ['1', '2', '3', '4', '5', '6', '7']\\n \\n \\n print('What city do you want to look into ? Chicago, New York or Washington?')\\n city = get_valid_input(cities)\\n \\n # TO DO: get user input for month (all, january, february, ... , june)\\n \\n print('Do you want to filter the data by Month, Day, Both or not at all? Type \\\"None\\\" for no time filter!')\\n filter = get_valid_input(filterValues)\\n \\n if filter == 'month':\\n print('Which month? January, February, March, April, May or June?')\\n month = get_valid_input(months)\\n day = 'all'\\n \\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n\\n elif filter == 'day':\\n print('Which day? Monday(1), Tuesday(2), ..., ? Please enter number!')\\n day = int(get_valid_input(days))-1\\n month = 'all'\\n \\n elif filter == 'both':\\n print('Which month? January, February, March, April, May or June?')\\n month = get_valid_input(months)\\n print('Which day? Monday(1), Tuesday(2), ..., ? Please enter number!')\\n day = int(get_valid_input(days))-1\\n \\n elif filter == 'none':\\n month = 'all'\\n day = 'all'\\n \\n else:\\n return -1\\n \\n if month !='all': \\n month = [element.lower() for element in months].index(month) + 1\\n \\n\\n print('-'*40)\\n return city, month, day\",\n \"def get_filters():\\n\\n # Setting filters to none\\n selected_day = None\\n selected_month = None\\n selected_city = None\\n\\n # Interact with the user by their name\\n name = input(\\\"Please Enter your name and let's have some fun!\\\\nMy name is: \\\")\\n \\n\\n # Communicate with the user by first name and capitalizing the initial\\n name = name.split()[0].capitalize()\\n\\n # initializing the names of months and days.\\n days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']\\n months = ['January', 'February', 'March', 'April', 'May', 'June']\\n print()\\n\\n # get user input for city (chicago, new york city, washington).\\n print(f\\\"Hello {name}, Which city's data do you want to explore?\\\\n1. Chicago\\\\n2. New York City\\\\n3. Washington\\\")\\n citystr = input('{Enter an Option}')\\n\\n # Checking the validation of the and converting to string to identify the preferred data\\n while True:\\n try:\\n city = int(citystr)\\n if city == 1:\\n selected_city = 'Chicago'\\n elif city == 2:\\n selected_city = 'New York City'\\n elif city == 3:\\n selected_city = 'Washington'\\n else:\\n print()\\n print(\\n f\\\"{name}, Make sure your option falls within 1 and 3 inclusive\\\\n1. Chicago\\\\n2. New York \\\"\\n f\\\"City\\\\n3. Washington\\\")\\n citystr = input('{Enter an Option} ')\\n continue\\n break\\n except ValueError:\\n\\n print()\\n print(f\\\"OOh {name}, Kindly enter a numerical value\\\\n1. Chicago\\\\n2. New York City\\\\n3. Washington\\\")\\n citystr = input('{Enter an Option} ')\\n print()\\n\\n # Displaying options for the user to select\\n print(f\\\"Well done! now select a Month to explore the data in {selected_city}\\\\nYou can also enter '0' to select \\\"\\n f\\\"all months\\\")\\n for month in enumerate(months):\\n print(f'{month[0] + 1}. {month[1]}')\\n\\n # Getting the preferred month and checking the input validation\\n monthstr = input(\\\"{Enter an Option} \\\")\\n while True:\\n try:\\n month = int(monthstr)\\n if month == 1:\\n selected_month = 'January'\\n elif month == 2:\\n selected_month = 'February'\\n elif month == 3:\\n selected_month = 'March'\\n elif month == 4:\\n selected_month = 'April'\\n elif month == 5:\\n selected_month = 'May'\\n elif month == 6:\\n selected_month = 'June'\\n elif month == 0:\\n selected_month = 'all'\\n else:\\n print()\\n print(f\\\"{name}, Make sure your option falls within 1 and 6 inclusive!\\\")\\n for month in enumerate(months):\\n print(f'{month[0] + 1}. {month[1]}')\\n\\n monthstr = input(\\\"{Enter an Option} \\\")\\n continue\\n break\\n except ValueError:\\n print()\\n print(f\\\"Hi {name}, ensure a numerical value was entered\\\")\\n for month in enumerate(months):\\n print(f'{month[0] + 1}. {month[1]}')\\n monthstr = input(\\\"{Enter an Option} \\\")\\n print()\\n\\n # Printing and displaying the filter to the user\\n if selected_month != 'all':\\n print(\\n f\\\"Great! now choose a day in {selected_month} to have an insight?\\\\nYou can also enter '0' to select all \\\"\\n f\\\"days in {selected_month} \\\")\\n else:\\n print(\\\"Great! now choose a day to have an insight in the months from January to June!\\\\nYou can enter '0' to \\\"\\n \\\"select all days\\\")\\n for day in enumerate(days):\\n print(f'{day[0] + 1}. {day[1]}')\\n\\n # Getting the preferred month and checking the input validation with try and except\\n daystr = input(\\\"{Enter an Option} \\\")\\n\\n while True:\\n try:\\n day = int(daystr)\\n if day == 1:\\n selected_day = days[0]\\n elif day == 2:\\n selected_day = days[1]\\n elif day == 3:\\n selected_day = days[2]\\n elif day == 4:\\n selected_day = days[3]\\n elif day == 5:\\n selected_day = days[4]\\n elif day == 6:\\n selected_day = days[5]\\n elif day == 7:\\n selected_day = days[6]\\n elif day == 0:\\n selected_day = 'all'\\n else:\\n print()\\n print(f\\\"{name}, Make sure your option falls within 1 and 7 inclusive!\\\")\\n for day in enumerate(days):\\n print(f'{day[0] + 1}. {day[1]}')\\n\\n daystr = input(\\\"{Enter an Option} \\\")\\n continue\\n break\\n except ValueError:\\n print(f\\\"Hi {name}!, Select an option with it's numeric value!\\\")\\n for month in enumerate(months):\\n print(f'{month[0] + 1}. {month[1]}')\\n daystr = input(\\\"{Enter an Option} \\\")\\n\\n print()\\n\\n # Printing the filter based on the user's selection\\n if selected_month != 'all' and selected_day != 'all':\\n print(\\n f\\\"Well done {name.capitalize()}! Let's explore some {selected_city}\\\\nbikeshare data on {selected_day}s \\\"\\n f\\\"in the month of {selected_month}!\\\")\\n\\n elif selected_month == 'all' and selected_day != 'all':\\n\\n print(\\n f\\\"Well done {name.capitalize()}! Let's explore some {selected_city}\\\\nbikeshare data on {selected_day}s \\\"\\n f\\\"in January to June!\\\")\\n\\n elif selected_month != 'all' and selected_day == 'all':\\n print(\\n f\\\"Well done {name.capitalize()}! Let's explore some {selected_city}\\\\nbikeshare data on Mondays to \\\"\\n f\\\"Sundays in the month of {selected_month}!\\\")\\n\\n else:\\n print(\\n f\\\"Well done {name.capitalize()}! Let's explore some {selected_city}\\\\nbikeshare data on Mondays to \\\"\\n f\\\"Sundays in January to June!\\\")\\n\\n print('-' * 50)\\n\\n # Returning the filter needed for further computation.\\n return selected_city, selected_month, selected_day\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data!')\\n # get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n #city = input ('Select from the following cities that you would like information for:\\\\n : ')\\n \\n # For all user inputs, I took the approach of locking down the choices to prevent user input error\\n while True:\\n try:\\n city = int(input ('Select from the following cities that you would like information for:\\\\n 1. Chicago,\\\\n 2. New York City,\\\\n 3. Washington DC\\\\n : '))\\n if city == 1:\\n city = 'chicago'\\n elif city == 2:\\n city = 'new york city'\\n elif city == 3:\\n city = 'washington'\\n print()\\n print('OK then. You have elected to review data for :',city.title())\\n break\\n except:\\n print('Please only respond with 1, 2, or 3')\\n\\n # get user input for month (all, january, february, ... , june)\\n while True:\\n try:\\n month = int(input('Select from the following months:\\\\n 1. Jan,\\\\n 2. Feb,\\\\n 3. Mar,\\\\n 4. Apr,\\\\n 5. May,\\\\n 6. Jun,\\\\n 7. All\\\\n: '))\\n if month == 1:\\n month = 'january'\\n elif month == 2:\\n month = 'february'\\n elif month == 3:\\n month = 'march'\\n elif month == 4:\\n month = 'april'\\n elif month == 5:\\n month = 'may'\\n elif month == 6:\\n month = 'june'\\n elif month == 7:\\n month = 'all'\\n print()\\n print('OK then. You have elected to review data for the month of:',month.title())\\n break\\n except:\\n print('Please only respond with numbers 1 - 7 only')\\n \\n # get user input for day of week (all, monday, tuesday, ... sunday)\\n while True:\\n try:\\n day = int(input('Select from the following days of the week for which you would like information:\\\\n 1. Monday,\\\\n 2. Tuesday,\\\\n 3. Wednesday,\\\\n 4. Thursday,\\\\n 5. Friday,\\\\n 6. Saturday,\\\\n 7. Sunday,\\\\n 8. All\\\\n: '))\\n if day == 1:\\n day = 'monday'\\n elif day == 2:\\n day = 'tuesday'\\n elif day == 3:\\n day = 'wednesday'\\n elif day == 4:\\n day = 'thursday'\\n elif day == 5:\\n day = 'friday'\\n elif day == 6:\\n day = 'saturday'\\n elif day == 7:\\n day = 'sunday'\\n elif day == 8:\\n day = 'all' \\n print()\\n print('OK then. You have elected to review data for :',day.title())\\n break\\n except:\\n print('Please only respond with 1 - 8 only')\\n \\n print('-'*40)\\n return city, month, day\",\n \"def get_filters():\\r\\n\\r\\n # TO DO: get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\r\\n print(\\\"Hello! Let\\\\'s explore some US bikeshare data!\\\")\\r\\n while True:\\r\\n city = input(\\\"Would you like to see data for Chicago, New York City or Washington?\\\\n\\\").split(\\\": \\\")[0].lower()\\r\\n try:\\r\\n if city not in CITY_DATA:\\r\\n print(\\\"Sorry, {} is not a valid city. Please type again by entering either 'Chicago', 'New York City' OR 'Washington' again\\\".format(city))\\r\\n continue\\r\\n else:\\r\\n break\\r\\n except ValueError as e:\\r\\n print(\\\"Exception occurred: {}\\\".format(e))\\r\\n\\r\\n # TO DO: get user input for month (all, january, february, ... , june)\\r\\n while True:\\r\\n month = input(\\\"Which month? January, February, March, April or June?..Enter 'all' if no month filter\\\\n\\\").lower()\\r\\n try:\\r\\n months = ['january', 'february', 'march', 'april', 'may', 'june','all']\\r\\n if month not in months:\\r\\n print(\\\"Sorry, {} is not a valid month. Please type again by entering again\\\".format(month))\\r\\n continue\\r\\n else:\\r\\n break\\r\\n except ValueError as e:\\r\\n print(\\\"Exception occurred: {}\\\".format(e))\\r\\n\\r\\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\r\\n while True:\\r\\n day_of_week = input(\\\"Which day? Enter the response in integer. Ex: 1 = Sunday..Enter 'all' if no day filter\\\\n\\\")\\r\\n try:\\r\\n if day_of_week.isnumeric():\\r\\n day_of_week = int(day_of_week)\\r\\n if day_of_week == 1:\\r\\n day = \\\"Sunday\\\"\\r\\n break\\r\\n elif day_of_week == 2:\\r\\n day = \\\"Monday\\\"\\r\\n break\\r\\n elif day_of_week == 3:\\r\\n day = \\\"Tuesday\\\"\\r\\n break\\r\\n elif day_of_week == 4:\\r\\n day = \\\"Wednesday\\\"\\r\\n break\\r\\n elif day_of_week == 5:\\r\\n day = \\\"Thursday\\\"\\r\\n break\\r\\n elif day_of_week == 6:\\r\\n day = \\\"Friday\\\"\\r\\n break\\r\\n elif day_of_week == 7:\\r\\n day = \\\"Saturday\\\"\\r\\n break\\r\\n else:\\r\\n print(\\\"Sorry, {} is not a valid day. Please type again by entering either the day of week in integer ex: 1 = Sunday\\\".format(day_of_week))\\r\\n continue\\r\\n else:\\r\\n if day_of_week == \\\"all\\\":\\r\\n day = \\\"all\\\"\\r\\n break\\r\\n else:\\r\\n continue\\r\\n except ValueError as e:\\r\\n print(\\\"Exception occurred: {}\\\".format(e))\\r\\n\\r\\n print('-'*40)\\r\\n return city, month, day\",\n \"def acis_dose_control_step():\\n\\n print 'Please specify the year and the month you want to run the scripts for.'\\n syear = raw_input('Year: ')\\n year = int(syear)\\n smonth= raw_input('Month: ')\\n month = int(smonth)\\n\\n smon = str(month)\\n if month < 10:\\n smon = '0' + smon\\n\\n print 'Please choose which processes you want to run\\\\n'\\n\\n chk0 = raw_input('Do you want to run the entire process(y/n)?: ')\\n m = re.search('y', chk0)\\n if m is not None:\\n chk1 = 'y'\\n chk2 = 'y'\\n chk3 = 'y'\\n chk4 = 'y'\\n chk5 = 'y'\\n chk6 = 'y'\\n else:\\n chk1 = raw_input('Extracting Data (y/n): ')\\n chk2 = raw_input('Compute Statistics (y/n): ')\\n chk3 = raw_input('Plot Data (y/n): ')\\n chk4 = raw_input('Create Images (y/n): ')\\n chk5 = raw_input('Updata HTML pages (y/n): ')\\n chk6 = raw_input('Create Table for Monthly Report (y/n): ')\\n#\\n#--- extract data\\n#\\n m = re.search('y', chk1)\\n if m is not None:\\n getd.acis_dose_get_data(year, month, year, month)\\n#\\n#--- create cumulative data and sectioned data for bot month and cumulative data\\n#\\n file = 'ACIS_' + smon + '_' + syear + '.fits'\\n file2= 'ACIS_' + smon + '_' + syear + '.fits.gz'\\n\\n chk = 0\\n for test in os.listdir('./'):\\n if fnmatch.fnmatch(test, file2):\\n chk = 1\\n break\\n \\n if chk == 0:\\n cuml.acis_create_cumulative(file)\\n else:\\n cuml.acis_create_cumulative(file2)\\n \\n#\\n#--- compute statistics\\n#\\n m = re.search('y', chk2)\\n if m is not None:\\n astat.acis_dose_extract_stat_data_month(year, month)\\n#\\n#--- plot data\\n#\\n m = re.search('y', chk3)\\n if m is not None:\\n aplot.acis_dose_plot_exposure_stat(clean='Yes')\\n#\\n#--- create images (you need to use ds9 to create a better image)\\n#\\n m = re.search('y', chk4)\\n if m is not None:\\n aimg.create_acis_maps(year, month)\\n#\\n#--- update html pages\\n#\\n m = re.search('y', chk5)\\n if m is not None:\\n ahtml.acis_dose_make_data_html()\\n\\n#\\n#--- print monthly output\\n#\\n m = re.search('y', chk6)\\n if m is not None:\\n areport.acis_dose_monthly_report()\",\n \"def __init__(self, instrumentsNAmounts, totalInvest):\\n # add all necessary attributes here which link to portfolio and\\n # will be tracked.\\n self.portfolio = instrumentsNAmounts\\n self.totalInvest = totalInvest\",\n \"def calculate(self):\\r\\n if self.__calculation_type == self.__DIFFERENTIATED_PAY:\\r\\n for month in range(1, self.__principal_term+1):\\r\\n self.__differentiated_pay.append(\\r\\n ceil(\\r\\n (self.__credit_principal/self.__principal_term)\\r\\n + self.__credit_interest*(self.__credit_principal\\r\\n - (self.__credit_principal\\r\\n * (month-1))\\r\\n / self.__principal_term)\\r\\n )\\r\\n )\\r\\n self.__overpayment = sum(self.__differentiated_pay) - self.__credit_principal\\r\\n\\r\\n for i, dp in enumerate(self.__differentiated_pay, 1):\\r\\n print(f'Month {i}: paid out {dp}')\\r\\n print()\\r\\n print(f'Overpayment = {self.__overpayment}')\\r\\n\\r\\n elif self.__calculation_type == self.__ANNUITY:\\r\\n if self.__user_choice == self.__SEEK_ANNUITY_MONTHLY:\\r\\n self.__annuity_monthly = ceil(\\r\\n self.__credit_principal * ((self.__credit_interest\\r\\n * pow(1+self.__credit_interest\\r\\n , self.__principal_term)\\r\\n )\\r\\n / (pow(1+self.__credit_interest\\r\\n , self.__principal_term)\\r\\n - 1)\\r\\n )\\r\\n )\\r\\n self.__overpayment = (self.__annuity_monthly * self.__principal_term\\r\\n - self.__credit_principal\\r\\n )\\r\\n print(f'Your annuity payment = {self.__annuity_monthly}!')\\r\\n\\r\\n elif self.__user_choice == self.__SEEK_TERM:\\r\\n self.__principal_term = ceil(\\r\\n log(self.__annuity_monthly / (self.__annuity_monthly\\r\\n - (self.__credit_interest\\r\\n * self.__credit_principal))\\r\\n , 1+self.__credit_interest)\\r\\n )\\r\\n self.__overpayment = ceil(self.__annuity_monthly\\r\\n * self.__principal_term\\r\\n - self.__credit_principal\\r\\n )\\r\\n years = self.__principal_term // 12\\r\\n months = self.__principal_term % 12\\r\\n\\r\\n print(f'You need {years} year{\\\"s\\\" if self.__principal_term > 1 else \\\"\\\"}'\\r\\n f'{\\\" and \\\" + str(months) + \\\" months\\\" if months > 0 else \\\"\\\"}'\\r\\n f' to repay this credit!')\\r\\n\\r\\n elif self.__user_choice == self.__SEEK_CREDIT_PRINCIPAL:\\r\\n self.__credit_principal = ceil(\\r\\n self.__annuity_monthly\\r\\n / ((self.__credit_interest\\r\\n * pow(1+self.__credit_interest, self.__principal_term)\\r\\n )\\r\\n / (pow(1+self.__credit_interest, self.__principal_term)\\r\\n - 1)\\r\\n )\\r\\n )\\r\\n self.__overpayment = ceil(self.__annuity_monthly\\r\\n * self.__principal_term\\r\\n - self.__credit_principal)\\r\\n\\r\\n print(f'Your credit principal = {self.__credit_principal}!')\\r\\n print(f'Overpayment = {self.__overpayment}')\\r\\n\\r\\n else:\\r\\n print('Incorrect parameters')\\r\\n self.usage()\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data!')\\n\\n # get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n cities = [\\\"chicago\\\", \\\"new york city\\\", \\\"washington\\\"]\\n\\n while True:\\n try:\\n x = input(\\\"Enter chicago, new york city or washington: \\\")\\n # verify that input is in list of cities and retrieve index\\n cityindex = cities.index(x)\\n city = cities[cityindex]\\n break\\n except:\\n print(\\\"Invalid input; enter chicago, new york city or washington\\\")\\n\\n # get user input for month (all, january, february, ... , june)\\n months = ['january', 'february', 'march', 'april', 'may', 'june']\\n\\n while True:\\n try:\\n month = input(\\\"Enter all, january, february, march, april, may or june: \\\")\\n # filter by month if applicable\\n if month != \\\"all\\\":\\n # use the index of the months list to get the corresponding int; in df jan = 1...jun = 6\\n month = months.index(month)+1\\n break\\n elif month == \\\"all\\\":\\n break\\n except:\\n print(\\\"Invalid input; enter all, january, february, march, april, may or june:\\\")\\n\\n # get user input for day of week (all, monday, tuesday, ... sunday)\\n days = [\\\"all\\\", \\\"Monday\\\", \\\"Tuesday\\\", \\\"Wednesday\\\", \\\"Thursday\\\", \\\"Friday\\\", \\\"Saturday\\\", \\\"Sunday\\\"]\\n\\n while True:\\n try:\\n day = input(\\\"Enter all, Monday, Tuesday, Wednesday, Thursday, Friday, Saturday or Sunday: \\\")\\n if day != \\\"all\\\":\\n day = day.title()\\n if day in days:\\n break\\n except:\\n print(\\\"Invalid input; enter all, Monday, Tuesday, Wednesday, Thursday, Friday, Saturday or Sunday:\\\")\\n\\n print(\\\"-\\\"*40)\\n return city, month, day\",\n \"def main() -> None:\\n\\n download_data_tools.initial_message()\\n\\n # S&P 500 companies, initial year and time step\\n stocks: List[str] = download_data_tools.get_stocks(['all'])\\n dates: List[str] = ['1992-01', '2012-12']\\n time_step: str = '1d'\\n\\n # Basic folders\\n download_data_tools.start_folders()\\n\\n # Run analysis\\n # Download data\\n portfolio_download_data(stocks, dates, time_step)\\n\\n print('Ay vamos!!!')\",\n \"def finish_project_processing(year):\\n\\n generators = filter_plants_by_region_id(13, year)\\n generators = assign_heat_rates_to_projects(generators, year)\\n existing_gens = generators[generators['Operational Status']=='Operable']\\n proposed_gens = generators[generators['Operational Status']=='Proposed']\\n\\n fname = 'existing_generation_projects_{}.tab'.format(year)\\n with open(os.path.join(outputs_directory, fname),'w') as f:\\n existing_gens.to_csv(f, sep='\\\\t', encoding='utf-8', index=False)\\n\\n uprates = pd.DataFrame()\\n new_gens = pd.DataFrame()\\n for idx in proposed_gens.index:\\n pc = proposed_gens.loc[idx,'EIA Plant Code']\\n pm = proposed_gens.loc[idx,'Prime Mover']\\n es = proposed_gens.loc[idx,'Energy Source']\\n existing_units_for_proposed_gen = existing_gens[\\n (existing_gens['EIA Plant Code'] == pc) &\\n (existing_gens['Prime Mover'] == pm) &\\n (existing_gens['Energy Source'] == es)]\\n if len(existing_units_for_proposed_gen) == 0:\\n new_gens = pd.concat([new_gens, pd.DataFrame(proposed_gens.loc[idx,:]).T], axis=0)\\n elif len(existing_units_for_proposed_gen) == 1:\\n uprates = pd.concat([uprates, pd.DataFrame(proposed_gens.loc[idx,:]).T], axis=0)\\n else:\\n print \\\"There is more than one option for uprating plant id {}, prime mover {} and energy source {}\\\".format(int(pc), pm, es)\\n\\n fname = 'new_generation_projects_{}.tab'.format(year)\\n with open(os.path.join(outputs_directory, fname),'w') as f:\\n new_gens.to_csv(f, sep='\\\\t', encoding='utf-8', index=False)\\n\\n fname = 'uprates_to_generation_projects_{}.tab'.format(year)\\n with open(os.path.join(outputs_directory, fname),'w') as f:\\n uprates.to_csv(f, sep='\\\\t', encoding='utf-8', index=False)\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data!')\\n\\n # TO DO: get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n cities = ['chicago', 'new york city', 'washington']\\n city_good = 'n'\\n while city_good == 'n':\\n city = input(\\\"Enter the name of the city to analyze (Chicago, New York City, Washington): \\\").lower()\\n if city in cities:\\n print(Fore.GREEN + '{} it is!\\\\n'.format(city.capitalize()) + Style.RESET_ALL)\\n city_good = 'y'\\n else:\\n print(Fore.RED + 'Error! \\\"{}\\\" is not a valid entry, please try again!\\\\n'.format(city) + Style.RESET_ALL)\\n city_good = 'n'\\n\\n # TO DO: get user input for month (all, january, february, ... , june)\\n months = ['all', 'january', 'february', 'march', 'april', 'may', 'june']\\n month_good = 'n'\\n while month_good == 'n':\\n month = input(\\\"Enter the month to analyze (All, January, February, March, April, May, June): \\\").lower()\\n if month in months:\\n print(Fore.GREEN + '{} it is!\\\\n'.format(month.capitalize()) + Style.RESET_ALL)\\n month_good = 'y'\\n else:\\n print(Fore.RED + 'Error! \\\"{}\\\" is not a valid entry, please try again!\\\\n'.format(month) + Style.RESET_ALL)\\n month_good = 'n'\\n\\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n days = ['all', 'sunday', 'monday', 'tuesday', 'wednesday', 'thursday',\\n 'friday', 'saturday']\\n day_good = 'n'\\n while day_good == 'n':\\n day = input(\\\"Enter the day of the week to analyze (All, Sunday, Monday, Tuesday, Wednesday, Thursday, Friday, Saturday): \\\").lower()\\n if day in days:\\n print(Fore.GREEN + '{} it is!\\\\n'.format(day.capitalize()) + Style.RESET_ALL)\\n day_good = 'y'\\n else:\\n print(Fore.RED + 'Error! \\\"{}\\\" is not a valid entry, please try again!\\\\n'.format(day) + Style.RESET_ALL)\\n day_good = 'n'\\n\\n print('='*70)\\n return city, month, day\",\n \"def run_analysis(self):\\n ### skip some snapshots for testing purposes\\n nskip = 199\\n read_char.skip_snapshots(self.hfile, self.ifile, nskip)\\n ### read in the first two steps (required for velocity related computations\\n xs_old, ys_old, lx_old, ly_old, tstep_old, natoms_old = read_char.read_snapshot(self.hfile, self.ifile)\\n x_old = xs_old*lx_old\\n y_old = ys_old*ly_old\\n xs,ys,lx,ly,tstep,natoms = read_char.read_snapshot(self.hfile, self.ifile)\\n x = xs*lx\\n y = ys*ly\\n ### loop over all steps of the input file\\n for step in range(nskip+1,self.nsteps-1):\\n print step\\n ### read in coordinates (as required)\\n xs_new,ys_new,lx_new,ly_new,tstep_new,natoms_new = read_char.read_snapshot(self.hfile, self.ifile)\\n x_new = xs_new*lx_new\\n y_new = ys_new*ly_new\\n ### compute further current per/atom quantities\\n phi = misc_tools.compute_orientation(x,y,lx,ly,self.npol)\\n vx,vy = misc_tools.compute_velocity(x_old,y_old, x_new, y_new, lx, ly, tstep_old, tstep_new, natoms)\\n ### start desired analysis methods\\n # density\\n if self.density_flag:\\n self.density.compute(step,x,y,lx,ly,natoms, plot = 'False')\\n # number fluctuations\\n if self.nf_flag:\\n self.numberfluctuation.compute(step,xs,ys, plot = 'False')\\n # voronoi density\\n if self.voronoi_flag:\\n self.voronoidensity.compute(step,x,y,lx,ly,natoms, plot = 'False')\\n # velocity / worticity\\n if self.velocity_flag:\\n self.velocityworticity.compute(step,x,y,vx,vy,natoms,lx,ly, plot = 'False')\\n # orientation / velocity\\n if self.orientvel_flag:\\n self.orientvel.compute(step,x,y,vx,vy,phi,natoms, plot = 'False')\\n # defect points\\n if self.pointdefects_flag:\\n self.pointdefects.compute(step,x,y,phi,lx,ly,natoms)\\n ### move coordinate arrays\\n xs_old = np.copy(xs)\\n ys_old = np.copy(ys)\\n x_old = np.copy(x)\\n y_old = np.copy(y)\\n tstep_old = tstep\\n xs = np.copy(xs_new)\\n ys = np.copy(ys_new)\\n x = np.copy(x_new)\\n y = np.copy(y_new)\\n tstep = tstep_new\\n return\",\n \"def collect_data(self,\\n day_selection,\\n exposure_schedule=[1.0],\\n year_selection=[0],\\n units=[\\\"SED\\\"],\\n bin_width=None):\\n\\n # this subroutine handles keyword inputs (monthly, seasonal, etc)\\n self.day_selection, self.day_input_flt, self.day_nonstring = str2daysofyear(day_selection)\\n\\n self.exposure_schedule = exposure_schedule\\n\\n self.year_selection = year_selection\\n\\n if units is not None :\\n self.units = units\\n \\n if bin_width is not None :\\n self.bin_width = bin_width\\n\\n self = self.interpret_parameters()\\n\\n ############################################################################\\n\\n lengths = {'day_selection' : len(self.day_selection),\\n 'exposure_schedule' : len(self.exposure_schedule),\\n 'year_selection' : len(self.year_selection),\\n 'units' : len(self.units),\\n 'bin_width' : len(self.bin_width)}\\n\\n self.num_hists = max(lengths.items(), key=lambda x: x[1])[1]\\n assert all(x == self.num_hists or x == 1 for x in lengths.values()), (\\n \\\"Inputs must be lists of length 1 or num_hists\\\")\\n \\n self.iterators = [x[0] for x in lengths.items() if x[1]==self.num_hists]\\n\\n\\n self.hist_specs = []\\n\\n for i in range(self.num_hists) :\\n hist_spec = {\\n 'day_selection' : self.day_selection[0],\\n 'exposure_schedule' : self.exposure_schedule[0],\\n 'year_selection' : self.year_selection[0],\\n 'units' : self.units[0],\\n 'bin_width' : self.bin_width[0]}\\n for x in self.iterators :\\n hist_spec[x] = self.__dict__[x][i]\\n self.hist_specs = self.hist_specs + [hist_spec]\\n \\n \\n # find unique years to be loaded (probably all years but have to check)\\n unique_years = set(self.year_selection[0])\\n if len(self.year_selection) > 1 :\\n for i in range(1,len(self.year_selection)) :\\n unique_years.update(self.year_selection[i])\\n unique_years = sorted(unique_years)\\n\\n # declare empty hists\\n self.hists = [None for x in range(self.num_hists)]\\n\\n for i in range(len(unique_years)) :\\n year = unique_years[i]\\n print(\\\"Processing year \\\"+str(year)) #should use logging, don't yet know how\\n dataset=nc.Dataset(self.src_directory+self.src_filename_format.replace('yyyy',str(year))) \\n dataset.set_auto_mask(False) #to get normal arrays (faster than default masked arrays)\\n\\n if i == 0 :\\n # TODO: this should also be done by some initial dataset analysis, but that's a drastic\\n # design overhaul\\n self.lat = dataset['lat'][:]\\n self.lon = dataset['lon'][:]\\n\\n # now to determine the unique days for the specific year\\n unique_days = set()\\n for j in range(self.num_hists) :\\n if year in self.hist_specs[j]['year_selection'] :\\n unique_days.update(self.hist_specs[j]['day_selection'])\\n unique_days = sorted(unique_days)\\n\\n # TODO: when metadata fixed, update this to actually interpret dates (cftime)\\n # reformat to index for netCDF\\n nc_day_sel = [False for i in range(365*24)] \\n # reshape false array to have first dimension 24 (hours in day)\\n nc_day_sel = assert_data_shape_24(nc_day_sel) \\n # set the appropriate days as true\\n nc_day_sel[:,np.array(unique_days)-1] = True \\n # correct for leap years (skip feb 29)\\n if year % 4 == 0 :\\n nc_day_sel = np.concatenate(\\n (nc_day_sel[:,0:59],np.full((24,1),False),nc_day_sel[:,59:]),axis=1)\\n # flatten time_subset array back to one dimension\\n nc_day_sel = nc_day_sel.flatten(order='F')\\n\\n #load data\\n data_year = assert_data_shape_24(dataset['UV_AS'][nc_day_sel,:,:])\\n\\n #sort data into histograms\\n for j in range(self.num_hists) :\\n if year in self.hist_specs[j]['year_selection'] :\\n sub_day_sel = [ True if x in self.hist_specs[j]['day_selection'] \\n else False for x in unique_days ]\\n temp_data = data_year[:,sub_day_sel,:,:]\\n\\n # Apply the exposure schedule, differently for doses vs intensity\\n if self.hist_specs[j]['units'] in [\\\"SED\\\",\\\"J m-2\\\",\\\"UVIh\\\"] :\\n # if calculating doses\\n print(' Calculating doses')\\n temp_data = np.sum(np.reshape(\\n self.hist_specs[j]['exposure_schedule'],[24,1,1,1]) * temp_data,axis=0)\\n # more complex when doing intensity\\n else :\\n # assume elsewise calculating intensity (i.e. UV-index) then limit data selection\\n # to schedule (remembering that default schedule is just ones)\\n print(' Slicing data with exposure schedule')\\n # select only those hours with nonzero entry in exposure schedule\\n temp_data = temp_data[self.hist_specs[j]['exposure_schedule'] != 0,:,:,:]\\n # select nonzero values from exposure schedule\\n exposure_schedule_nonzero = self.hist_specs[j]['exposure_schedule'][\\n self.hist_specs[j]['exposure_schedule'] != 0]\\n # if any nonzero entries aren't 1, multiply data accordingly\\n if (exposure_schedule_nonzero != 1).any() :\\n temp_data *= np.reshape(exposure_schedule_nonzero,[len(exposure_schedule_nonzero),1,1,1])\\n # recombine first two dimensions (hour and day) back into time ready for histogram\\n temp_data = assert_data_shape_24(temp_data,reverse=True) \\n\\n # now multiply data by conversion factor according to desired untis\\n # TODO: Should expand upon this in reference files\\n temp_data *= {\\\"SED\\\":0.9, \\\"J m-2\\\":90, \\\"UVIh\\\":1, \\\"UVI\\\":1, \\\"W m-2\\\":0.025, \\\"mW m-2\\\":25}[self.hist_specs[j]['units']]\\n\\n # if this is the first iteration, declare a hist\\n if 'num_bins' not in self.hist_specs[j] :\\n # seems like useful metadata to know bin n and edges\\n self.hist_specs[j]['num_bins'] = int(np.nanmax(temp_data) // self.hist_specs[j]['bin_width'] ) + 2\\n self.hist_specs[j]['bin_edges'] = (np.array(range(self.hist_specs[j]['num_bins']+1))\\n - 0.5) * self.hist_specs[j]['bin_width'] \\n # this form allows for weird custom bin edges, but probably will never use that\\n self.hist_specs[j]['bin_centers'] = (self.hist_specs[j]['bin_edges'][:-1] \\n + 0.5 * np.diff(self.hist_specs[j]['bin_edges']))\\n\\n # TODO: think about possible cases where dimensions could differ\\n self.hists[j]=np.zeros([self.hist_specs[j]['num_bins'],\\n np.shape(temp_data)[-2],np.shape(temp_data)[-1]], dtype=np.int16)\\n\\n else :\\n new_num_bins = int(np.nanmax(temp_data) // self.hist_specs[j]['bin_width']) + 2 - self.hist_specs[j]['num_bins']\\n # check if new data requires extra bins in pix_hist\\n if new_num_bins > 0 :\\n # append zeros to pix hist to make room for larger values\\n self.hists[j] = np.concatenate((self.hists[j],np.zeros(\\n [new_num_bins,np.shape(self.hists[j])[-2],np.shape(self.hists[j])[-1]],\\n dtype=np.int16)),axis=0)\\n # update bin information\\n self.hist_specs[j]['num_bins'] = self.hist_specs[j]['num_bins'] + new_num_bins\\n self.hist_specs[j]['bin_edges'] = (np.array(range(self.hist_specs[j]['num_bins']+1))\\n - 0.5) * self.hist_specs[j]['bin_width'] \\n self.hist_specs[j]['bin_centers'] = (self.hist_specs[j]['bin_edges'][:-1] \\n + 0.5 * np.diff(self.hist_specs[j]['bin_edges']))\\n\\n # TODO: Add check in case bins get \\\"full\\\" (i.e. approach int16 max value)\\n # now put data into hist using apply_along_axis to perform histogram for each pixel\\n print(\\\" Calculating and adding to pixel histograms\\\")\\n self.hists[j][:,:,:] += np.apply_along_axis(lambda x: \\n np.histogram(x,bins=self.hist_specs[j]['bin_edges'])[0],0,temp_data)\\n\\n return self\",\n \"def main():\\n \\n Y1, Y2 = 2005, 2017 ### range with coordinates supplied in pre-2018 generated archive\\n\\n if len(sys.argv) > 1 and int(sys.argv[1]) > 0:\\n Y1 = int(sys.argv[1])\\n \\n if len(sys.argv) > 2 and int(sys.argv[2]) > Y1:\\n Y2 = int(sys.argv[2])\\n \\n with open('data/audit.log','w') as output:\\n for Y in range(Y1, Y2):\\n df = pd.read_csv('data/{}.csv'.format(Y), low_memory = False)\\n output.write('\\\\n--- {} --------------------\\\\n'.format(Y))\\n\\n # remove `deleted` records\\n df['deleted'] = df['deleted'].apply(yes_no)\\n df = df[df['deleted'] == 0]\\n\\n # remove misc misdemeanors\\n df = df[~df['category'].isin(drop)]\\n\\n # validate date and expand into Y,N,D,W,H\\n df['dt'] = df['incident_date'].apply(extract)\\n df = df[~df['dt'].isnull()]\\n\\n # convert from plane state to longitude-latitude\\n df['ll'] = df.apply(to_lnglat, axis = 1)\\n\\n # init features\\n features = df.loc[:,['category','stat','address','city','zip']]\\n features['id'] = df['incident_id']\\n dt = ['year','month','day','weekday','hour']\\n for i in range(len(dt)):\\n features[dt[i]] = df['dt'].apply(lambda x: x[i] )\\n\\n features['lng'] = df['ll'].apply(lambda x: x[0])\\n features['lat'] = df['ll'].apply(lambda x: x[1])\\n\\n features['gang'] = df['gang_related'].apply(yes_no)\\n features['category'] = df['category'].apply(collapse)\\n cat = set(features.groupby(['category']).size().reset_index(name='count')['category'].tolist())\\n output.write('Categories: {}\\\\n'.format(len(cat)))\\n\\n output.write('Date miss: {:.4f}%\\\\n'\\\\\\n .format(100 * (1 - len(features[(features['year'] > 2000) & (~features['weekday'].isnull())])/len(features))))\\n output.write('Location miss: {:.4f}%\\\\n'\\\\\\n .format(100 * (1 - len(features[(features['zip'] > 0) | (features['lat'] > 0)])/len(features))))\\n\\n # keep records with valid date\\n features['date'] = df['dt'].apply(lambda x: datetime.date(x[0], x[1], x[2]))\\n features = features[(features['year'] > 2000) & (~features['weekday'].isnull())]\\n output.write('Time miss: {:.4f}%\\\\n'.format(100 * len(features[features['hour'] == -1])/len(features)))\\n\\n # potential `time-unknown` issue\\n output.write('Hour ZERO: {:.4f}%\\\\n'.format(100 * len(features[features['hour'] == 0])/len(features)))\\n output.write('Hour NOON: {:.4f}%\\\\n'.format(100 * len(features[features['hour'] == 12])/len(features)))\\n\\n features = features[(features['zip'] > 0) | (features['lat'] > 0)]\\n\\n # get the best possible coordinates + zipcode assessment\\n features[['zip','lng','lat']] = features[['zip','lng','lat']].apply(fix_location, axis = 1)\\n output.write('Failed location: {:.4f}%\\\\n'.format(100 * len(features[features['zip'].isnull()])/len(features)))\\n features = features[~features['zip'].isnull()]\\n features['zip'] = df['zip'].apply(lambda x: str(x)[:5])\\n \\n # normalize city attr\\n features = features.join(zipcodes[['zip','city']].set_index('zip'), on = 'zip', lsuffix = '_orig', rsuffix = '')\\n features.loc[features['city'].isnull(), 'city'] = features.loc[features['city'].isnull(), 'city_orig']\\\\\\n .apply(lambda x: x if type(x) == float else ' '.join([l[0].upper() + l[1:] for l in x.split()]))\\n\\n # reduce to LA bounding-box\\n features = features[(features['lng'] > -119) & (features['lng'] < -116)]\\n features = features[(features['lat'] > 32) & (features['lat'] < 35)]\\n\\n # save csv\\n features[fields].to_csv('data/F{}.csv'.format(Y), index = False)\\n features[fields].to_json('data/F{}.json'.format(Y), orient = 'records')\\n output.close()\",\n \"def process_paving_data(mode='sdif', **kwargs):\\n moratorium_string = \\\"Post Construction\\\"\\n phone_UTLY = \\\"858-627-3200\\\"\\n phone_OTHER = \\\"619-527-7500\\\"\\n TSW_PM = \\\"JLahmann@sandiego.gov\\\"\\n UTLY_PM = \\\"Engineering@sandiego.gov\\\"\\n ACT_OVERLAY_CONCRETE_PM = \\\"CHudson@sandiego.gov\\\"\\n ACT_SLURRY_SERIES_PM = \\\"AVance@sandiego.gov\\\"\\n ACT_SERIES_CIRCUIT_PM = \\\"CHoenes@sandiego.gov\\\"\\n\\n today = general.today()\\n\\n date_cols = ['wo_design_start_dt','wo_design_end_dt','job_start_dt','job_end_dt']\\n\\n df = pd.read_csv(temp_file,low_memory=False, parse_dates=date_cols)\\n\\n # Update column types\\n\\n float_cols = ['pve_id','rd_seg_id','seg_council_district']\\n\\n for i in float_cols:\\n df[i] = number_str_cols(df[i])\\n\\n str_cols = ['seg_id','wo_proj_type','wo_id','wo_name']\\n\\n df.loc[:,str_cols] = df.loc[:,str_cols].replace(np.nan, '')\\n\\n #*** Update project types for consistency ***\\n\\n logging.info(\\\"Updating project type to Concrete, Slurry or Overlay\\\")\\n\\n # Search Strings\\n concrete_search = \\\"panel rep|pcc - reconstruc\\\"\\n slurry_search = \\\"surface treatment|scrub seal|cape seal|central mix\\\"\\n overlay_search = \\\"resurfacing|overlay|ac overlay|mill|ac - overlay|ac - ac overlay|ac - reconstruct|ac inlay\\\"\\n\\n # Set Proj Type to NA\\n df['wo_proj_type'] = None\\n # Concrete\\n df.loc[df.job_activity.str.contains(\\n concrete_search, regex=True, case=False, na=False), 'wo_proj_type'] = 'Concrete'\\n # Slurry\\n df.loc[df.job_activity.str.contains(\\n slurry_search, regex=True, case=False, na=False), 'wo_proj_type'] = 'Slurry'\\n # Overlay\\n df.loc[df.job_activity.str.contains(\\n overlay_search, regex=True, case=False, na=False), 'wo_proj_type'] = 'Overlay'\\n\\n #*** Update job status ***\\n\\n logging.info(f\\\"Creating new status column with fixed status\\\")\\n\\n df['status'] = df['wo_status']\\n\\n df.loc[(df.job_completed_cbox == 1), \\\"status\\\"] = moratorium_string\\n \\n df.loc[(df.job_completed_cbox != 1) &\\n (df.wo_status.str.contains('post construction|moratorium|post-construction',\\n regex=True,\\n case=False)), \\\"status\\\"] = \\\"Construction\\\"\\n\\n # Set Dates in The future for TSW work orders as Construction.\\n df.loc[(df.wo_id == 'TSW') &\\n (df.job_end_dt.notnull()) &\\n (df.job_end_dt > today), \\\"status\\\"] = \\\"Construction\\\"\\n\\n # Set other TSW works orders as Construction\\n df.loc[(df.wo_id == \\\"TSW\\\") & \\n (df.job_completed_cbox == 0),'status'] = \\\"Construction\\\"\\n\\n #*** Update project manager ***\\n\\n logging.info(f\\\"Updating project manager names and phone\\\")\\n\\n # Set Phone # For UTLY\\n df.loc[df.wo_id == 'UTLY', 'wo_pm_phone'] = phone_UTLY\\n\\n # Set Phone # for Everything else\\n df.loc[df.wo_id != 'UTLY', 'wo_pm_phone'] = phone_OTHER\\n\\n # Set PM for UTLY\\n df.loc[df.wo_id == 'UTLY', 'wo_pm'] = UTLY_PM\\n\\n # Set PM for TSW\\n df.loc[df.wo_id == 'TSW', 'wo_pm'] = TSW_PM\\n\\n # Set PM for Overlay / Concrete\\n df.loc[(df.wo_pm.isnull()) & \\n ((df.wo_proj_type == 'Overlay') |\\n (df.wo_proj_type == 'Concrete')), 'wo_pm'] = ACT_OVERLAY_CONCRETE_PM\\n\\n # Set PM for Slurry\\n df.loc[((df.wo_pm.isnull()) & \\n (df.wo_proj_type == 'Slurry')), 'wo_pm'] = ACT_SLURRY_SERIES_PM\\n\\n # Set PM for Series \\n df.loc[((df.wo_pm.isnull()) & \\n (df.wo_proj_type == 'Series Circuit')), 'wo_pm'] = ACT_SERIES_CIRCUIT_PM\\n\\n #*** Update moratorium, start and end dates ***\\n\\n logging.info(f\\\"Updating moratorium, start, and end dates\\\")\\n \\n # Create separate moratorium column based on job end dt\\n df['moratorium'] = df['job_end_dt']\\n \\n # But do not set moratorium for concrete\\n df.loc[df.wo_proj_type == 'Concrete','moratorium'] = None\\n df.loc[df.status != moratorium_string,'moratorium'] = None\\n \\n # Start/end column is by default the wo_design_start/wo_design_end \\n df['start'] = df['wo_design_start_dt']\\n df['end'] = df['wo_design_end_dt']\\n\\n # But here, we get an update based on a few criteria\\n new_dates = df.apply(get_start_end_dates,axis=1)\\n dates_final = new_dates.apply(pd.Series)\\n df['start'] = dates_final[0]\\n df['end'] = dates_final[1]\\n\\n #*** Calculate paving miles ***\\n \\n paving_miles = df.apply(get_paving_miles, axis=1)\\n df = df.assign(paving_miles=paving_miles)\\n\\n #*** Remove unneeded records ***\\n\\n logging.info(f\\\"Starting with {df.shape[0]} rows before removing records\\\")\\n\\n start_no = df.shape[0]\\n logging.info(df.iloc[0])\\n\\n # UTLY jobs where job end date is missing\\n df = df[~((df.wo_id == \\\"UTLY\\\") & (df.job_end_dt.isnull()))]\\n logging.info(f\\\"Removed {start_no - df.shape[0]} UTLY records with missing job end\\\")\\n start_no = df.shape[0]\\n\\n # Records for data entry, mill / pave, structure widening, and patching\\n remove_search = 'data entry|mill|structure wid|patching'\\n df = df[~(df.job_activity.str.contains(\\n remove_search, regex=True, case=False, na=False))]\\n logging.info(f\\\"Removed {start_no - df.shape[0]} records for data entry, etc\\\")\\n start_no = df.shape[0] \\n\\n five_yrs_ago = today.replace(year=(today.year - 5))\\n three_yrs_ago = today.replace(year=(today.year - 3))\\n \\n start_no = df.shape[0]\\n\\n # All older than 5 years plus slurry records older than 3 years for imcat\\n if mode == 'imcat':\\n df = df[(df.job_end_dt > five_yrs_ago) | (df.job_end_dt.isnull())]\\n logging.info(f\\\"Removed {start_no - df.shape[0]} records older than 5 years\\\")\\n df = df[~((df.wo_proj_type == 'Slurry') &\\n (df.job_end_dt < three_yrs_ago))]\\n logging.info(f\\\"Removed {start_no - df.shape[0]} Slurry records older than 3 years\\\")\\n else:\\n df = df[(df.job_end_dt >= '07/01/2013') | (df.job_end_dt.isnull())]\\n logging.info(f\\\"Removed {start_no - df.shape[0]} records older than July 1, 2013\\\")\\n\\n # Records with no activity, type or status\\n mask = (df.job_activity.isnull()) | (df.job_activity == None) | (df.job_activity == 'None') | (df.job_activity == '')\\\\\\n |(df.wo_proj_type.isnull()) | (df.wo_proj_type == None) | (df.wo_proj_type == 'None') | (df.wo_proj_type == '')\\\\\\n |(df.wo_status.isnull()) | (df.wo_status == None) | (df.wo_status == 'None') | (df.wo_status == '')\\n\\n spot_unknown = df[mask]\\n\\n logging.info('Found {} records with no activity, type or status'.format(\\n spot_unknown.shape[0]))\\n\\n # Remove unknown\\n df = df[~mask]\\n\\n logging.info(f\\\"End with {df.shape[0]} rows after removing records\\\")\\n\\n #*** Rename columns and create subsets ***\\n\\n # For IMCAT uppercase status\\n if mode == 'imcat':\\n\\n logging.info(\\\"Flagging duplicates for removal\\\")\\n\\n duplicates = []\\n df = df.sort_values(by=['seg_id','job_end_dt'], na_position='first', ascending=[True,False])\\n df_seg_groups = df.groupby(['seg_id'])\\n for name, group in df_seg_groups:\\n if group.shape[0] > 1:\\n selection = group.loc[group['moratorium'].notnull()]\\n if selection.shape[0] > 1:\\n index_list = selection.index.tolist()\\n select_remove = index_list[1:]\\n duplicates.extend(select_remove)\\n\\n df['to_delete'] = 0\\n df.loc[duplicates,['to_delete']] = 1\\n\\n df = df.rename(columns={'wo_id':'projectid',\\n 'wo_name':'title',\\n 'wo_pm':'pm',\\n 'wo_pm_phone':'pm_phone',\\n 'job_completed_cbox':'completed',\\n 'wo_proj_type':'proj_type',\\n 'job_activity':'activity',\\n 'wo_resident_engineer':'resident_engineer',\\n 'seg_placed_in_srvc':'seg_in_serv',\\n 'seg_func_class':'seg_fun_class',\\n 'seg_length_ft':'length',\\n 'seg_width_ft':'width',\\n 'seg_council_district':'seg_cd',\\n 'job_entry_dt':'entry_dt',\\n 'seg_func_class':'seg_fun',\\n 'job_updated_dt':'last_update'\\n })\\n\\n final_cols = ['to_delete','pve_id','rd_seg_id','seg_id','projectid','title',\\n 'pm','pm_phone','moratorium','status','proj_type','resident_engineer',\\n 'start','end','completed','job_start_dt','job_end_dt',\\n 'wo_design_start_dt','wo_design_end_dt','wo_status','activity',\\n 'entry_dt','last_update','street','street_from','street_to',\\n 'seg_fun','seg_cd','length','width','seg_in_serv','paving_miles']\\n\\n df_final = df[final_cols].copy()\\n\\n df_final.columns = [x.upper() for x in df_final.columns]\\n df_final['STATUS'] = df_final['STATUS'].str.upper()\\n\\n else:\\n\\n # Remove duplicates\\n #df = df.sort_values(by='job_end_dt', na_position='last', ascending=False)\\n #df = df.drop_duplicates('seg_id', keep='first')\\n\\n df = df.sort_values(by=['seg_id','job_end_dt'], na_position='last', ascending=[True,False])\\n\\n # Drop additional columns for public dataset\\n\\n df = df.drop(columns=['rd_seg_id',\\n 'job_completed_cbox',\\n 'job_activity',\\n 'job_entry_dt',\\n 'job_updated_dt',\\n 'seg_placed_in_srvc',\\n 'seg_func_class',\\n 'seg_council_district'\\n ])\\n\\n df = df.rename(columns={'wo_id':'project_id',\\n 'wo_name':'title',\\n 'wo_pm':'project_manager',\\n 'wo_pm_phone':'project_manager_phone',\\n 'wo_proj_type':'type',\\n 'wo_resident_engineer':'resident_engineer',\\n 'street':'address_street',\\n 'seg_length_ft':'length',\\n 'seg_width_ft':'width',\\n 'moratorium':'date_moratorium',\\n 'start':'date_start',\\n 'end':'date_end'\\n })\\n\\n final_cols = ['pve_id','seg_id','project_id','title','project_manager',\\n 'project_manager_phone','status','type','resident_engineer','address_street',\\n 'street_from','street_to','length','width','date_moratorium',\\n 'date_start','date_end','paving_miles']\\n\\n df_final = df[final_cols].copy()\\n\\n df_final['status'] = df_final['status'].str.lower()\\n\\n \\n # Write csv\\n logging.info('Writing ' + str(df_final.shape[0]) + ' rows in mode ' + mode)\\n general.pos_write_csv(\\n df_final, prod_file[mode], date_format=conf['date_format_ymd'])\\n \\n return \\\"Successfully wrote prod file at \\\" + prod_file[mode]\",\n \"def main(input, output):\\n # turn csv to dataframe\\n df = pd.read_csv(f\\\"./data/{input}\\\", index_col=0)\\n\\n # split training and test\\n X = df.drop(columns=['DEFAULT_NEXT_MONTH'])\\n y = df['DEFAULT_NEXT_MONTH']\\n X_train, X_test, y_train, y_test = train_test_split(\\n X, y, test_size=0.25, random_state=122)\\n\\n # We use robust scalar as most of our data is not normally distributed and we have a high amount of outliers.\\n columns = ['LIMIT_BAL', 'SEX', 'EDUCATION', 'MARRIAGE', 'AGE', 'PAY_1', 'PAY_2',\\n 'PAY_3', 'PAY_4', 'PAY_5', 'PAY_6', 'BILL_AMT1', 'BILL_AMT2',\\n 'BILL_AMT3', 'BILL_AMT4', 'BILL_AMT5', 'BILL_AMT6', 'PAY_AMT1',\\n 'PAY_AMT2', 'PAY_AMT3', 'PAY_AMT4', 'PAY_AMT5', 'PAY_AMT6']\\n scaler = preprocessing.RobustScaler()\\n X_train = pd.DataFrame(scaler.fit_transform(X_train), columns=columns)\\n X_test = pd.DataFrame(scaler.transform(X_test), columns=columns)\\n\\n # Use RFE to identify the most identify the most useful predictors.\\n # Then we will drop those columns that are deemed as less useful.\\n logreg = LogisticRegression(solver=\\\"lbfgs\\\")\\n\\n get_report(X_train, y_train, X_test, y_test, logreg, 'results_baseline')\\n rfe = RFE(logreg, 7)\\n rfe = rfe.fit(X_train, y_train.values.ravel())\\n columns_to_drop = list()\\n for i in range(len(rfe.support_)):\\n include = rfe.support_[i]\\n if include == False:\\n columns_to_drop.append(columns[i])\\n X_train = X_train.drop(columns_to_drop, axis=1)\\n X_test = X_test.drop(columns_to_drop, axis=1)\\n get_report(X_train, y_train, X_test, y_test, logreg, output)\\n\\n # write compounded dataframe with results of two get_report calls\\n accuracies_output_df.to_csv(f'./{output}/accuracies.csv', index=False)\",\n \"def calculate_flows_for_airport(origin_airport_id, start_date, end_date, sim_group):\\n SIMULATED_PASSENGERS = 10000\\n start_date = datetime.datetime.strptime(start_date, '%Y-%m-%d')\\n end_date = datetime.datetime.strptime(end_date, '%Y-%m-%d')\\n period_days = (end_date - start_date).days\\n direct_passenger_flows = get_direct_passenger_flows(start_date, end_date)\\n db = get_database()\\n my_airport_flow_calculator = get_airport_flow_calculator()\\n # Drop all results for origin airport\\n db.passengerFlows.delete_many({\\n 'departureAirport': origin_airport_id,\\n 'simGroup': sim_group\\n })\\n results = my_airport_flow_calculator.calculate(\\n origin_airport_id,\\n simulated_passengers=SIMULATED_PASSENGERS,\\n start_date=start_date,\\n end_date=end_date)\\n if len(results) > 0:\\n seats_per_pasenger = sum(legs * value for legs, value in AirportFlowCalculator.LEG_PROBABILITY_DISTRIBUTION.items())\\n total_direct_passengers = sum(direct_passenger_flows[origin_airport_id].values())\\n total_passengers = int(float(total_direct_passengers) / seats_per_pasenger)\\n db.passengerFlows.insert_many({\\n 'departureAirport': origin_airport_id,\\n 'arrivalAirport': k,\\n 'estimatedPassengers': v['terminal_flow'] * total_passengers,\\n 'averageDistance': v['average_distance'],\\n 'recordDate': datetime.datetime.now(),\\n 'startDateTime': start_date,\\n 'endDateTime': end_date,\\n 'periodDays': period_days,\\n 'simGroup': sim_group\\n } for k, v in results.items())\\n return len(results)\\n else:\\n print \\\"No flights from: \\\" + origin_airport_id\\n return 0\",\n \"def get_filters():\\n print('\\\\nHello! Let\\\\'s explore some US bikeshare data!')\\n\\n # get user input for city (chicago, new york city, washington).\\n city=input('Please, introduce the name of the city you want to obtain information about [chicago/new york city/washington]: ')\\n city=city.lower()\\n #Let us now check that it is actually a valid input. We give 3 chances before exiting the program\\n i=0\\n while (city != 'chicago') and (city != 'new york city') and (city != 'washington'):\\n city=input('Please, introduce a valid city [chicago/new york city/washington]: ')\\n i += 1\\n if i==3:\\n sys.exit()\\n\\n # get user input for month (all, january, february, ... , june)\\n ans_month=input('Do you want to filter by month? [y/n]: ')\\n if ans_month=='n':\\n month='all'\\n elif ans_month=='y':\\n month=input('Which month? [january/february/.../june]: ')\\n month=month.lower()\\n #we check that it is actually a valid input. We give 3 chances before exiting the program:\\n i=0\\n set_months=['january','february','march','april','may','june']\\n while month not in set_months:\\n month=input('Please, introduce a valid month [january/february/.../june]: ')\\n i += 1\\n if i==3:\\n sys.exit()\\n\\n # get user input for day of week (all, monday, tuesday, ... sunday)\\n ans_day=input('Do you want to filter by day of week? [y/n]: ')\\n if ans_day=='n':\\n day='all'\\n elif ans_day=='y':\\n day=input('Which day? [monday/tuesday/.../sunday]: ')\\n day=day.lower()\\n #check that it is actually a valid input. We give 3 chances before exiting the program:\\n i=0\\n set_days=['monday','tuesday','wednesday','thursday','friday','saturday','sunday']\\n while day not in set_days:\\n day=input('Please, introduce a valid day [monday/tuesday/.../sunday]: ')\\n i += 1\\n if i==3:\\n sys.exit()\\n\\n print('-'*40)\\n return city, month, day\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data!')\\n # TO DO: get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n # improving user input for city\\n city = input(\\\"\\\\nWhat city do you intend to filter by? New York City, Chicago or Washington?\\\\n\\\").lower()\\n ### The following checks will ensure that the user inputs one of the expected cities.\\n while(True):\\n if(city == 'chicago' or city == 'new york city' or city == 'washington' or city == 'all'):\\n break\\n else:\\n city = input('Enter Correct city: ').lower()\\n\\n # TO DO: get user input for month (all, january, february, ... , june)\\n month = input('\\\\nWhich or the following months will you want to filter by? January, February, March, April, May, or June?\\\\n').lower()\\n \\n # Here we validate user input for month to ensure that it is one of the expected values.\\n while(True):\\n if(month == 'january' or month == 'february' or month == 'march' or month == 'april' or month == 'may' or month == 'june' or month == 'all'):\\n break\\n else:\\n month = input('Enter a valid month\\\\n').lower()\\n\\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n \\n day = input('Which or the following days ? monday, tuesday, wednesday, thursday, friday, saturday , sunday or all will you want to display the data for?\\\\n').lower()\\n \\n # Ensuring that the correct value is inputted for day of the week.\\n while(True):\\n \\n if(day == 'monday' or day == 'tuesday' or day == 'wednesday' or day == 'thursday' or day == 'friday' or day == 'saturday' or day == 'sunday' or day == 'all'):\\n break\\n else:\\n day = input('Enter Correct day: ').lower()\\n\\n print('-'*40)\\n return city, month, day\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data!')\\n # get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n \\n city = input('\\\\nWould you like to see data for.?: Simply type the Name \\\\n-> Chicago \\\\n-> New York\\\\n-> Washington\\\\n').lower()\\n #lower() command is used to take input of any type formate\\n\\n while(True):\\n if(city == 'chicago' or city == 'new york' or city == 'washington' or city == 'all of them'):\\n break\\n else:\\n city = input('Sorry, I do not understand your input. Please input either '\\n 'Chicago, New York, or Washington.\\\\n(Enter Correct city):\\\\t ').lower()\\n #lower() command is used to take input of any type formate\\n \\n # TO DO: get user input for month (all, january, february, ... , june)\\n month = input('\\\\nWhich month Data you want..?: Simply type the Name \\\\n-> January \\\\n-> February \\\\n-> March \\\\n-> April \\\\n-> May \\\\n-> June \\\\n').lower()\\n #.lower() command is used to take input of any type formate\\n \\n while(True):\\n if(month == 'january' or month == 'february' or month == 'march' or month == 'april' or month == 'may' or month == 'june' or month == 'all'):\\n break\\n else:\\n month = input('\\\\nPlease try to Enter valid month otherwise it will invalid and Not showing any result:\\\\n').lower()\\n #lower() command is used to take input of any type formate \\n\\n \\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n day = input('Which day Data you want..? simply type the name \\\\n-> Monday \\\\n-> Tuesday \\\\n-> Wednesday \\\\n-> Thursday \\\\n-> Friday \\\\n-> Saturday \\\\n-> Sunday \\\\n-> all to display data of all days\\\\n').lower()\\n #lower() command is used to take input of any type formate \\n while(True):\\n \\n if(day == 'monday' or day == 'tuesday' or day == 'wednesday' or day == 'thursday' or day == 'friday' or day == 'saturday' or day == 'sunday' or day == 'all'):\\n break;\\n else:\\n day = input('\\\\nPlease try to Enter valid Day otherwise it will invalid and Not showing any result:\\\\nEnter Correct day:\\\\t ').lower()\\n #lower() command is used to take input of any type formate \\n \\n #return day\\n\\n print('-'*40)\\n return city, month, day\",\n \"def api_analyze():\\n output = {}\\n\\n #retrieve the json from the ajax call\\n json_file = ''\\n if request.method == 'POST':\\n json_file = request.json\\n print (\\\"post request\\\")\\n\\n #if json_file successfully posted..\\n if json_file != '':\\n # check all required arguments are present:\\n if not all(arg in json_file for arg in [\\\"portfolio\\\",\\\"riskfactor\\\", \\\"shockmag\\\"]):\\n print(\\\"Missing arguments in post request\\\")\\n return json.dumps({\\\"status\\\":\\\"Error\\\", \\\"messages\\\":\\\"Missing arguments\\\"}), 422\\n portfolio = json_file[\\\"portfolio\\\"]\\n riskfactor = json_file[\\\"riskfactor\\\"]\\n shockmag = json_file[\\\"shockmag\\\"]\\n print(\\\"retreived data: \\\" + str(portfolio) + \\\" | \\\" + str(riskfactor) + \\\" | \\\" + str(shockmag))\\n\\n #run Predictive Market Scenario service\\n PMS_status = predictivemarketscenario.generate_scenario(riskfactor, shockmag)\\n #if error in the call, return with error\\n if PMS_status != 200:\\n print(\\\"Unable to create csv from Predictive Market Scenario service\\\")\\n return json.dumps({'error': str(PMS_status) + \\\" Unable to create csv from Predictive Market Scenario service\\\"})\\n print (\\\"CREATED CSV\\\")\\n\\n #get holdings data\\n holdings_data = investmentportfolio.get_portfolio_holdings(portfolio)\\n\\n #go through each holding in the portfolio\\n asset_output = []\\n for holding in holdings_data[\\\"holdings\\\"][-1][\\\"holdings\\\"]:\\n\\n #call the simulatedinstrumentanalytics module\\n data = simulatedinstrumentanalytics.compute_simulated_analytics(instrument_id=holding[\\\"instrumentId\\\"])\\n\\n #if returned as json would mean error, assign N/A, else assing the values from the list of objects\\n if isinstance(data, dict):\\n value1 = \\\"N/A\\\"\\n value2 = \\\"N/A\\\"\\n else:\\n value1 = data[0][\\\"values\\\"][0][\\\"THEO/Price\\\"]\\n value2 = data[1][\\\"values\\\"][0][\\\"THEO/Price\\\"]\\n\\n #create obj with the output values\\n asset = holding[\\\"asset\\\"]\\n instrumentId = holding[\\\"instrumentId\\\"]\\n quantity = holding[\\\"quantity\\\"]\\n companyName = holding[\\\"companyName\\\"]\\n obj = {\\n 'Asset': asset,\\n 'InstrumentId': instrumentId,\\n 'Quantity': quantity,\\n 'CompanyName': companyName,\\n 'BaseVal': value1,\\n 'NewVal': value2\\n }\\n asset_output.append(obj)\\n\\n #get the market_conditions as list\\n if os.path.exists(\\\"output_PMS.csv\\\"):\\n market_conditions = get_market_conditions(\\\"output_PMS.csv\\\")\\n\\n #create the output json\\n output = {\\\"holdingsInfo\\\": asset_output, \\\"marketConditions\\\": market_conditions}\\n\\n return json.dumps(output)\",\n \"def __init__(self):\\n self.portfolios = list()\\n self.value = 0\",\n \"def main(input_scenario):\\n\\n print(\\\"Program running for demand scenario \\\" + str(input_scenario))\\n\\n policy_f = open(\\\"./Policy/policy_result\\\" + str(input_scenario) + \\\".csv\\\", \\\"w\\\", newline='')\\n policy_writer = csv.writer(policy_f)\\n\\n # Read case data\\n ds, orig_fl = get_data_case(input_scenario, htime, zone)\\n\\n # Initialize operator location\\n location = initialize_location(zone, vec)\\n\\n # Initialize cluster\\n assignment, centre = initialize_cluster(cluster, zone, mindis)\\n\\n # Run\\n # Timestep 0\\n ds = update_ds(zone, cp, ds, mindis, orig_fl[0])\\n\\n # Timestep 1:\\n for timestep in range(1, htime):\\n\\n print(\\\"Running for timestep \\\" + str(timestep))\\n\\n # Extract demand flows in current timestep\\n train_fl = [fl[ts][timestep] for ts in range(trainsample)]\\n\\n # Compute total demand flows in and out of each station\\n train_fl_out = [[0 for s in range(zone)] for ts in range(trainsample)]\\n train_fl_in = [[0 for s in range(zone)] for ts in range(trainsample)]\\n\\n for ts in range(trainsample):\\n for s in range(zone):\\n train_fl_out[ts][s] = sum(train_fl[ts][s])\\n for z in range(zone):\\n train_fl_in[ts][s] += train_fl[ts][z][s]\\n\\n # Modify cluster based on demand flows\\n assignment = modify_cluster(cluster, assignment, centre, zone, cp, ds, mindis, trainsample, train_fl)\\n print(\\\"Clusters generated.\\\")\\n\\n # Initialize global intra-cluster rebalancing result\\n yp_total = [0.0 for s in range(zone)]\\n yn_total = [0.0 for s in range(zone)]\\n bn = [[0 for s in range(zone)] for v in range(vec)]\\n\\n # Intra-cluster rebalancing\\n for c in range(cluster):\\n\\n # Extract local data\\n local_list = [s for s in range(zone) if assignment[s] == c]\\n\\n local_zone = len(local_list)\\n\\n local_cp = [cp[s] for s in local_list]\\n local_ds = [ds[s] for s in local_list]\\n\\n local_vec_list = []\\n local_vec = 0\\n local_cap = []\\n local_location = []\\n\\n for v in range(vec):\\n if location[v].index(1) in local_list:\\n local_vec_list.append(v)\\n local_vec += 1\\n local_cap.append(cap[v])\\n local_location.append([1 if (s == location[v].index(1)) else 0 for s in local_list])\\n \\n local_dis = [[dis[s][z] for z in local_list] for s in local_list]\\n\\n local_train_fl_out = [[train_fl_out[ts][s] for s in local_list] for ts in range(trainsample)]\\n local_train_fl_in = [[train_fl_in[ts][s] for s in local_list] for ts in range(trainsample)]\\n\\n # Apply local rebalance\\n status, local_yp_total, local_yn_total, local_bn = intra_redeployment(local_zone, local_cp, local_ds, local_vec, local_cap, local_location, local_dis, trainsample, local_train_fl_out, local_train_fl_in, dismaxpick, dismaxdrop)\\n\\n # Make error report if no solution\\n if status == 1:\\n error_f = open(\\\"./error_report.csv\\\", \\\"a\\\", newline='')\\n error_writer = csv.writer(error_f)\\n error_writer.writerow([str(cluster), str(input_scenario), str(timestep), str(c)])\\n error_f.close()\\n\\n # Translate to global indexing\\n for s in range(local_zone):\\n yp_total[local_list[s]] = local_yp_total[s]\\n yn_total[local_list[s]] = local_yn_total[s]\\n \\n for v in range(local_vec):\\n for s in range(local_zone):\\n bn[local_vec_list[v]][local_list[s]] = local_bn[v][s]\\n \\n print(\\\"Cluster done is: \\\" + str(c))\\n \\n for s in range(zone):\\n policy_writer.writerow([str(timestep), str(s), str(yp_total[s]), str(yn_total[s])])\\n \\n # Update ds\\n update_ds(zone, cp, ds, mindis, orig_fl[timestep], yp_total, yn_total)\\n\\n # Update operator location\\n for v in range(vec):\\n for s in range(zone):\\n if round(bn[v][s]) == 1:\\n location[v][s] = 1\\n else:\\n location[v][s] = 0\\n \\n print(\\\"Timestep done is: \\\" + str(timestep))\\n \\n policy_f.close()\",\n \"def run():\\n\\n title_list = [\\\"* id of item\\\",\\n \\\"* title\\\",\\n \\\"* price\\\",\\n \\\"* month of the sale\\\",\\n \\\"* day of the sale\\\",\\n \\\"* year of the sale\\\",\\n \\\"* customer's id\\\"]\\n\\n # ! sign with a position is unfinished function but added in options\\n # !8. Show the sale numbers of games for each customer-292\\n # !11. Show the customer who spent the most and the amount spent-365\\\"\\n # !12. Show the customer's id who spent the most and the amount spent-376\\\"\\n # !13. Show the most frequent buyers-387\\n # !14. Show the if of the most freuent buyers-\\n\\n options = [\\\"Print table\\\",\\n \\\"Get game title by id\\\",\\n \\\"Show the most recently sold game\\\",\\n \\\"Get the sum of games' prices by their id\\\",\\n \\\"Get the customer's id by the id of a game\\\",\\n \\\"Show ids of all customers who purchased games\\\",\\n \\\"Show sale ids of all customers\\\",\\n \\\"Show the owner of a recently sold game\\\",\\n \\\"Show the owner's id of a recently sold game\\\",\\n \\\"Show the most frequent buyers\\\",\\n \\\"Show the ids of the most frequent buyers\\\",\\n \\\"Get the customer by id\\\"]\\n\\n os.system('clear')\\n file = \\\"model/sales/sales.csv\\\"\\n choice = None\\n while choice != \\\"0\\\":\\n os.system('clear')\\n terminal_view.print_predator()\\n terminal_view.print_menu(\\\"What do you want to do:\\\", options, \\\"Back to main menu\\\")\\n choice = terminal_view.get_choice(options)\\n\\n if choice == \\\"1\\\":\\n os.system(\\\"clear\\\")\\n common.all_print_table(title_list, file)\\n\\n elif choice == \\\"2\\\":\\n os.system(\\\"clear\\\")\\n print(\\\"Get game title by id\\\\n\\\")\\n file_name = common.get_file()\\n if file_name == \\\"\\\":\\n file_name = file\\n table = common.get_table_from_file(file_name)\\n terminal_view.print_table(table, title_list)\\n identification = common.get_input(\\\"Enter the id: \\\")\\n print(sales.get_title_by_id_from_table(table, identification))\\n common.waiting()\\n os.system(\\\"clear\\\")\\n\\n elif choice == \\\"3\\\":\\n file_name = common.get_file()\\n if file_name == \\\"\\\":\\n file_name = file\\n table = common.get_table_from_file(file_name)\\n most_recently_sold_game = sales.get_item_id_title_sold_last(table)\\n print(\\\"The most recently sold game is: \\\")\\n terminal_view.print_table([most_recently_sold_game], [\\\"* id\\\", \\\"* title\\\"])\\n common.waiting()\\n os.system(\\\"clear\\\")\\n\\n elif choice == \\\"4\\\":\\n os.system(\\\"clear\\\")\\n print(\\\"Get the sum of games' prices by their id\\\\n\\\")\\n file_name = common.get_file()\\n if file_name == \\\"\\\":\\n file_name = file\\n table = common.get_table_from_file(file_name)\\n terminal_view.print_table(table, title_list)\\n item_ids = []\\n x = True\\n while x:\\n add_id = common.get_input(\\\"Enter the id or 'x' to exit: \\\")\\n if add_id == \\\"x\\\":\\n x = False\\n item_ids.append(add_id)\\n print(sales.get_the_sum_of_prices_from_table(table, item_ids))\\n common.waiting()\\n os.system(\\\"clear\\\")\\n\\n elif choice == \\\"5\\\":\\n os.system(\\\"clear\\\")\\n print(\\\"Get the customer's id by the id of a game\\\\n\\\")\\n file_name = common.get_file()\\n if file_name == \\\"\\\":\\n file_name = file\\n table = common.get_table_from_file(file_name)\\n terminal_view.print_table(table, title_list)\\n sale_id = common.get_input(\\\"Enter the id of a game: \\\")\\n print(sales.get_customer_id_by_sale_id_from_table(table, sale_id))\\n common.waiting()\\n os.system(\\\"clear\\\")\\n\\n elif choice == \\\"6\\\":\\n file_name = common.get_file()\\n if file_name == \\\"\\\":\\n file_name = file\\n table = common.get_table_from_file(file_name)\\n ids_of_all_customers = sales.get_all_customer_ids_from_table(table)\\n print(\\\"ids of all customers who purchased games:\\\\n\\\", ids_of_all_customers)\\n common.waiting()\\n os.system(\\\"clear\\\")\\n\\n elif choice == \\\"7\\\":\\n file_name = common.get_file()\\n if file_name == \\\"\\\":\\n file_name = file\\n table = common.get_table_from_file(file_name)\\n sale_ids_of_all_customers = sales.get_all_sales_ids_for_customer_ids_form_table(table)\\n print(\\\"Sale ids of all customers:\\\\n\\\\n\\\", sale_ids_of_all_customers)\\n common.waiting()\\n os.system(\\\"clear\\\")\\n\\n elif choice == \\\"8\\\":\\n file_name_sales = common.get_double_file(\\\"Choose a file with sales: \\\")\\n if file_name_sales == \\\"\\\":\\n file_name_sales = file\\n file_name_customer = common.get_double_file(\\\"Choose a file with customers: \\\")\\n if file_name_customer == \\\"\\\":\\n file_name_customer = \\\"model/crm/customers.csv\\\"\\n table_from_customers = common.get_table_from_file(file_name_customer)\\n table_from_sales = common.get_table_from_file(file_name_sales)\\n last_buyer = sales.get_the_last_buyer_name(table_from_customers, table_from_sales)\\n print(\\\"Owner of a recently sold game: \\\", last_buyer)\\n common.waiting()\\n os.system(\\\"clear\\\")\\n\\n elif choice == \\\"9\\\":\\n file_name = common.get_file()\\n if file_name == \\\"\\\":\\n file_name = file\\n table = common.get_table_from_file(file_name)\\n last_buyer_id = sales.get_the_last_buyer_id(table)\\n print(\\\"Owner's id of a recently sold game: \\\", last_buyer_id)\\n common.waiting()\\n os.system(\\\"clear\\\")\\n\\n elif choice == \\\"10\\\":\\n file_name_sales = common.get_double_file(\\\"Choose a file with sales: \\\")\\n if file_name_sales == \\\"\\\":\\n file_name_sales = file\\n file_name_customer = common.get_double_file(\\\"Choose a file with customers: \\\")\\n if file_name_customer == \\\"\\\":\\n file_name_customer = \\\"model/crm/customers.csv\\\"\\n table_from_customers = common.get_table_from_file(file_name_customer)\\n table_from_sales = common.get_table_from_file(file_name_sales)\\n the_most_frequent_buyers = sales.get_the_most_frequent_buyers_names(table_from_customers,\\n table_from_sales,\\n num=1)\\n print(\\\"The most frequent buyers:\\\\n\\\", the_most_frequent_buyers)\\n common.waiting()\\n os.system(\\\"clear\\\")\\n\\n elif choice == \\\"11\\\":\\n file_name = common.get_file()\\n if file_name == \\\"\\\":\\n file_name = file\\n table = common.get_table_from_file(file_name)\\n the_most_frequent_buyers_ids = sales.get_the_most_frequent_buyers_ids(table, num=1)\\n print(\\\"ids of the most frequent buyers:\\\\n\\\", the_most_frequent_buyers_ids)\\n common.waiting()\\n os.system(\\\"clear\\\")\\n\\n elif choice == \\\"12\\\":\\n os.system(\\\"clear\\\")\\n print(\\\"Get the customer by id\\\\n\\\")\\n file_name = common.get_file()\\n if file_name == \\\"\\\":\\n file_name = \\\"model/crm/customers.csv\\\"\\n table = common.get_table_from_file(file_name)\\n terminal_view.print_table(table, [\\\"* id\\\", \\\"* name\\\", \\\"* email\\\", \\\"* subscribed\\\"])\\n identification = common.get_input(\\\"Enter the id: \\\")\\n print(crm.get_name_by_id_from_table(table, identification))\\n common.waiting()\\n os.system(\\\"clear\\\")\\n\\n else:\\n if choice != \\\"0\\\":\\n terminal_view.print_error_message(\\\"There is no such choice.\\\\n\\\")\\n common.waiting()\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data!\\\\n')\\n\\n while True:\\n city_input = input('Please type your city of choice: ').lower()\\n if city_input not in CITY_DATA:\\n print(\\\"\\\\nSorry, this is not a valid city. Please select between: Chicago, New York City and Washington\\\\n\\\")\\n continue\\n else:\\n city = city_input\\n print(\\\"\\\\nThank you ! {} is a great city\\\".format(city.title()))\\n break\\n\\n # TO DO: get user input for month (all, january, february, ... , june)\\n months = ['january', 'february', 'march', 'abril', 'may', 'june', 'all']\\n\\n while True:\\n month_input = input('\\\\nNow, please select a month: ').lower()\\n if month_input not in months:\\n print(\\\"\\\\nSorry, this is not a valid month.\\\\nSelect between the months of January to June.\\\\nPlease spell it out like January, February, etc.\\\\nFor all months type 'all'\\\\n\\\")\\n continue\\n else:\\n month = month_input\\n print(\\\"\\\\nThat's great. Thank you for selecting {} as your month.\\\".format(month.title()))\\n break\\n\\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n\\n days = ['monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday','all']\\n\\n while True:\\n day_input = input('\\\\nI promise this is the last step.\\\\n\\\\nPlease choose a day of the week: ').lower()\\n if day_input not in days:\\n print(\\\"\\\\nSorry, this is not a valid day of the week.\\\\nPlease spell it out like Monday, Tuesday, etc.\\\\nFor all days type 'all'\\\\n\\\")\\n continue\\n else:\\n day = day_input\\n print(\\\"\\\\nThank you for selecting {} as your day of the week.\\\\n\\\".format(day.title()))\\n break\\n\\n print(\\\"\\\\nWe're all done now. But before we move on, let's re-cap your selections:\\\")\\n print(\\\"City: {}\\\\nMonth: {}\\\\nDay of week: {}\\\".format(city.title(),month.title(),day.title()))\\n\\n # Ask user if wants to see 5 lines of data for the selected city\\n print('\\\\nActually, before we move on, would you like to take a peak at 5 lines of the {} data?\\\\n'.format(city.title()))\\n word = input(\\\"Please enter 'Y' if you would like to see 5 lines of raw data: \\\\n\\\").lower()\\n if word == 'y':\\n a = 0\\n b = a + 4\\n with open(CITY_DATA[city],'r') as f:\\n lines = f.readlines()[a:b]\\n print(lines)\\n # in case answer above was 'Y' - ask user if wants to see 5 more lines of data (loops until the answer is different than 'Y'\\n while True:\\n word = input(\\\"\\\\nWanna see some more? Please enter 'Y' if you would like to see 5 more lines of data: \\\").lower()\\n if word == 'y':\\n c = b + 1\\n d = c + 4\\n with open(CITY_DATA[city],'r') as f:\\n lines = f.readlines()[c:d]\\n print(lines)\\n b = d\\n continue\\n else:\\n print('Finished')\\n break\\n\\n else:\\n print('Finished')\\n\\n print('-'*40)\\n return city, month, day\",\n \"def run(self, max_risk=0, min_return=0, num=0, init_holdings=None):\\n if not self.dates:\\n self.dates = ['2010-01-01', '2012-12-31']\\n self.load_data()\\n\\n num_months = len(self.df_all)\\n first_purchase = True\\n result = {}\\n baseline_result = {}\\n self.baseline_values = [0]\\n self.update_values = [0]\\n months = []\\n\\n # Define dataframe to save output data \\n headers = ['Date', 'Value'] + self.stocks + ['Variance', 'Returns']\\n self.opt_results_df = pd.DataFrame(columns=headers)\\n row = []\\n\\n self.price_df = pd.DataFrame(columns=self.stocks)\\n\\n # Initialize the plot\\n plt.ylim(ymax = 1.5*self.budget, ymin = -1.5*self.budget)\\n plt.xticks(list(range(0, num_months, 2)), \\n self.df_baseline.index.strftime('%b')[::2], rotation='vertical')\\n plt.locator_params(axis='x', nbins=num_months/2)\\n plt.plot(list(range(0, num_months)), [0]*(num_months), \\n color='red', label=\\\"Break-even\\\", linewidth=0.5)\\n\\n for i in range(3, num_months):\\n\\n # Look at just the data up to the current month\\n df = self.df_all.iloc[0:i+1,:].copy()\\n baseline_df_current = self.df_baseline.iloc[0:i+1,:]\\n print(\\\"\\\\nDate:\\\", df.last_valid_index())\\n months.append(df.last_valid_index().date()) \\n\\n if first_purchase:\\n budget = self.budget\\n initial_budget = self.budget\\n baseline_shares = (budget / baseline_df_current.iloc[-1])\\n baseline_result = {self.baseline[0]: baseline_shares} \\n else:\\n # Compute profit of current portfolio\\n budget = sum([df.iloc[-1][s]*result['stocks'][s] for s in self.stocks]) \\n self.update_values.append(budget - initial_budget)\\n\\n # Compute profit of fund portfolio\\n fund_value = sum([baseline_df_current.iloc[-1][s]*baseline_result[s] \\n for s in self.baseline]) \\n self.baseline_values.append(fund_value - initial_budget)\\n\\n self.budget = budget \\n\\n self.load_data(df=df)\\n\\n self.price_df.loc[i-2] = list(self.price.values)\\n\\n # Output for user on command-line and plot\\n update_values = np.array(self.update_values, dtype=object)\\n baseline_values = np.array(self.baseline_values, dtype=object)\\n plt.plot(range(3, i+1), update_values, \\n color='blue', label=\\\"Optimized portfolio\\\")\\n plt.plot(range(3, i+1), baseline_values, \\n color='gray', label=\\\"Fund portfolio\\\", linewidth=0.5)\\n \\n if first_purchase:\\n plt.legend(loc=\\\"lower left\\\")\\n plt.title(\\\"Start: {start}, End: {end}\\\".format\\\\\\n (start=self.df_all.first_valid_index().date(), \\n end=self.df_all.last_valid_index().date()))\\n\\n plt.savefig(\\\"portfolio.png\\\")\\n plt.pause(0.05)\\n \\n # Making solve run\\n if self.model_type == 'DQM':\\n print(f\\\"\\\\nMulti-Period DQM Run...\\\")\\n \\n self.build_dqm()\\n self.solution['DQM'] = self.solve_dqm()\\n result = self.solution['DQM']\\n else:\\n print(f\\\"\\\\nMulti-Period CQM Run...\\\")\\n\\n # Set budget to 0 to enforce that portfolio is self-financing \\n if self.t_cost and not first_purchase:\\n self.budget = 0 \\n\\n self.solution['CQM'] = self.solve_cqm(max_risk=max_risk, \\n min_return=min_return,\\n init_holdings=init_holdings)\\n result = self.solution['CQM']\\n init_holdings = result['stocks']\\n\\n # Print results to command-line\\n value = sum([self.price[s]*result['stocks'][s] for s in self.stocks])\\n returns = result['return']\\n variance = result['risk'] \\n\\n row = [months[-1].strftime('%Y-%m-%d'), value] + \\\\\\n [result['stocks'][s] for s in self.stocks] + \\\\\\n [variance, returns] \\n self.opt_results_df.loc[i-2] = row \\n \\n first_purchase = False\\n\\n print(self.opt_results_df)\\n print(f'\\\\nRun completed.\\\\n')\\n\\n plt.savefig(\\\"portfolio.png\\\")\\n plt.show(block=False)\",\n \"def get_filters():\\n print(\\\"Welcome to bikeshare data! \\\\n\\\")\\n\\n # Taksk0.1: Users choose a city, create a list with length=CITY_DATA , \\n #in future, it other cities are added codes will updated automatically\\n all_cities=list(CITY_DATA)\\n for i in range(len(all_cities)):\\n message = (\\\"For the city of {} ,The code is {}\\\\n\\\".format(all_cities[i],i+1))\\n print(message)\\n ##output of the for loop will code each city with a number, according to it's (position+1) in the dictionary \\n ## position is from 0 to 2, city codes are from 1 to 3, no manual recoding for city names\\n ## user chooses a city \\\"user input\\\" by entering 1,2,3\\n \\n print(\\\"***choose a city to start\\\\n***\\\")\\n city_code=input()\\n \\n ## check if user choice is valid, if enter a number out of range code restarts until a correct city chosen\\n ## decode the user input number into city name\\n ## print a confirmation message to the user with his choice\\n while int(city_code) > (len(all_cities)):\\n print(\\\"Sorry, City choice invalid\\\")\\n city_code = input (\\\"Please choose a number from 1 to 3\\\\n\\\")\\n city_code=int(city_code)\\n else:\\n city= all_cities[int(city_code)-1] \\n print(\\\"Nice! you will get statistics for**\\\",city.title())\\n\\n # Task0.2: get user input for month (all, january, february, ... , june)\\n ##user enter month number from 1 to 6 representing january to June or all for all month\\n print(\\\"Choose a month from January to June\\\\n\\\") \\n month = input (\\\"Please type (all) to see all months \\\\nor select a number from 1 to 6 : January is 1 \\\\n---------------------------\\\\n\\\\n\\\")\\n ## if user chooses all month, no filtering, if month choice greater than 6 print warning and loop, until a correct choice\\n if month != \\\"all\\\":\\n month=int(month)\\n while month > 6:\\n print('**Warning** OUT OF RANGE!only months from 1 to 6 available')\\n month = input (\\\"Please choose a number from 1 to 6\\\\n\\\\n\\\")\\n month=int(month)\\n else:\\n month==month\\n print(\\\"\\\\n Month chosen is ***\\\" ,month, \\\"***\\\")\\n else:\\n print(\\\"No Month filter applied\\\")\\n \\n print(\\\"-\\\"*40)\\n\\n\\n #task0.3: TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n ##create a list matching week days short names to their full name, write the list in title for \\\"first letter capital\\\"\\n days_dict = {\\\"Su\\\": \\\"Sunday\\\",\\n \\\"Mo\\\": \\\"Monday\\\",\\n \\\"Tu\\\": \\\"Tuesday\\\",\\n \\\"We\\\": \\\"Wednesday\\\", \\n \\\"Th\\\": \\\"Thursday\\\",\\n \\\"Fr\\\": \\\"Friday\\\",\\n \\\"Sa\\\": \\\"Saturday\\\"}\\n ## ask user to choose a day name by giving at least the first 2 letters of the day\\n ## conver user input to title format NOTE!! dont trim now as user may choose \\\"all\\\" days\\n ## if user choose all days, no warnings\\n ## if user enters a day name, trim only the first 2 letters to avoid Typos, look up if the letters correspond to day name\\n ## by consulting the dictionay, then return the day full name\\n print(\\\"Choose a day? \\\") \\n day= input (\\\"Please type (all) for no filtering \\\\nor choose a weeek day \\\\n \\\")\\n day=day.title()\\n \\n if day != \\\"All\\\":\\n day=(day[0:2]).title() \\n while day not in days_dict:\\n print('**Warning** not a valid day')\\n day = input (\\\"please enter at least first 2 characters of the day \\\\n\\\\n\\\")\\n day=(day[0:2]).title()\\n else:\\n day=days_dict[day]\\n print(\\\"\\\\n Day chosen is ***\\\" ,day, \\\"***\\\")\\n \\n else:\\n print(\\\"No day filter applied\\\") \\n \\n print('-'*40)\\n ## end of first function to gather user choices\\n ## return values for city name, month and day selction or all\\n ## saved as 3 inputs city,month,day\\n ##print a confirmation method to the user with his choices! city,month and day\\n print(\\\"you will see data for ** {}** city, for month *{}* and day * {}*\\\".format(city,month,day))\\n print(\\\"-\\\"*40)\\n return city, month, day\",\n \"def OnSolutionCallback(self):\\n self.total_plans += 1\\n print('Feasible Project Plan #{c}:'.format(c=self.total_plans))\\n for idx in range(0, len(self.p_)):\\n if self.Value(self.p_vars_[idx]):\\n print(' - Project ID: {p} (Cost={c}, Value={v})'.format(\\n p=(idx + 1), c=self.p_[idx][4], v=self.p_[idx][3]))\\n print(' - Total Cost : {c}'.format(c=self.Value(self.total_cost_)))\\n print(' - Total Value : {v}'.format(v=self.Value(self.total_value_)))\",\n \"def get_filters():\\n # Get the user to input their name. Characters, hypens, spaces and brackets are valid - numbers are not\\n valid_characters = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ -_(){}[]&'\\n while True:\\n name = input(\\\"\\\\nPlease enter your name, using only characters, spaces and hypens: \\\")\\n if all(char in valid_characters for char in name):\\n print('\\\\nHello {}! Let\\\\'s explore some US bikeshare data!'.format(name.title()))\\n break\\n print(\\\"\\\\nNumbers are not valid inputs. Please try again.\\\")\\n\\n # TO DO: get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n # city_input = 'chicago'\\n CITIES = ['chicago', 'new york city', 'washington']\\n while True:\\n city_input = input('\\\\nPlease choose the city you would like to see data for: Chicago, New York City, Washington.\\\\n').lower()\\n if city_input in CITIES:\\n print('\\\\nThank-you for selecting {}!'.format(city_input.title()))\\n break\\n else:\\n print(\\\"\\\\nI'm not sure what city you are referring to. Please try again!\\\")\\n\\n # TO DO: get user input for month (all, january, february, ... , june)\\n # month_input = 'all'\\n MONTHS = ['january', 'february', 'march', 'april', 'may', 'june', 'all']\\n while True:\\n month_input = input('\\\\nPlease choose from one or ALL of the following months: January, February, March, April, May, June or All. \\\\n').lower()\\n if month_input in MONTHS:\\n print('\\\\nThank-you for selecting {}!'.format(month_input.title()))\\n break\\n print(\\\"\\\\nI'm not sure what month you are referring to. Please try again!\\\")\\n\\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n # day_input = 'Thursday'\\n DAYS = ['monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday', 'all']\\n while True:\\n day_input = input('\\\\nPlease choose from one or ALL of the following days: Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday or All. \\\\n').lower()\\n if day_input in DAYS:\\n print('\\\\nThank-you for selecting {}!'.format(day_input.title()))\\n break\\n print(\\\"\\\\nI'm not sure what day you are referring to. Please try again!\\\")\\n\\n print('-'*40)\\n return city_input, month_input, day_input\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data! Including data from Chicago, Washington, and New York City')\\n # get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n while True:\\n city = input(\\\"Please choose a city you want to learn more about from the following: Chicago, New York City or Washington. \\\\n> \\\").lower(\\n ).replace(\\\" \\\", \\\"\\\")\\n if city in cities_data:\\n break\\n else:\\n print(\\\"\\\\n\\\\t\\\" + city + \\\" isn't valid, please enter a valid city.\\\")\\n\\n # get user input for month (all, january, february, ... , june)\\n while True:\\n month = input(\\\"Please choose a month or type 'all' to apply no month filter.\\\\n (Choices: all, january, february, march, april, may or june)\\\\n>\\\").lower(\\n ).replace(\\\" \\\", \\\"\\\")\\n if month in months_data or month == \\\"all\\\":\\n break\\n else:\\n print(\\\"\\\\n\\\\t ERROR: \\\" + month + \\\" isn't valid, please enter a month or 'all'.\\\")\\n\\n # get user input for day of week (all, monday, tuesday, ... sunday)\\n while True:\\n day = input(\\\"Please choose a day of the week or type 'all' to apply no day filter.\\\\n (Choices: all, monday, tuesday, wednesday, thursday, friday, saturday or sunday)\\\\n>\\\").lower().replace(\\\" \\\", \\\"\\\")\\n if day in days_data or day == \\\"all\\\":\\n break\\n else:\\n print(\\\"\\\\n\\\\t ERROR: \\\" + day + \\\" isn't valid, please enter a week day name or 'all'.\\\")\\n\\n print('-'*40)\\n return city, month, day\",\n \"def initialize(context): \\r\\n context.lookback_window = 3 # look back window for technical indicator calculations.\\r\\n context.data_history_window = 150 # we will accumulate data from the past 1000 days.\\r\\n context.price_current = [] # initialize empty current price list. This is a float.\\r\\n context.equities = [] # list of type string. Will contain the names of all equities traded by the algorithm\\r\\n context.technical_indicator_data = pd.DataFrame() # initialize an empty pandas dataframe that can hold data of three technical indicators\\r\\n context.leverage_buffer = 0.95 # limits leverage, or equities brought on credit. This will solve problems of overshorting our portfolio \\r\\n context.weight = {}\\r\\n context.ENSEMBLE_PREDICTION = 0.0\\r\\n \\r\\n # gather the technical indicators at 10 AM each stock-trading day \\r\\n schedule_function(get_initial_price, \\r\\n date_rules.every_day(),\\r\\n time_rules.market_open(minutes = 1))\\r\\n # conduct calculations using the NN and KNN\\r\\n schedule_function(predict_and_weigh,\\r\\n date_rules.every_day(), \\r\\n time_rules.market_open(minutes = 2))\\r\\n # trade\\r\\n schedule_function(trade, \\r\\n date_rules.every_day(),\\r\\n time_rules.market_open(minutes = 3))\\r\\n # close all the positions made in previous day\\r\\n schedule_function(close_position,\\r\\n date_rules.every_day(),\\r\\n time_rules.market_close(minutes = 1))\\r\\n # Record tracking variables at the end of each day. Variables will include the correlation of training data\\r\\n schedule_function(my_record_vars, \\r\\n date_rules.every_day(), \\r\\n time_rules.market_close())\\r\\n # Create our dynamic stock selector.\\r\\n attach_pipeline(make_pipeline(), 'my_pipeline')\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data!')\\n # TO DO: get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n city_temp = ''\\n while city_temp.lower() not in CITY_DATA:\\n city_temp = str(input('For which city would you like to see data? Chicago, New York, or Washington?\\\\n').lower()) \\n if city_temp.lower() in CITY_DATA:\\n city = city_temp\\n break\\n else:\\n print('This city is not available.')\\n continue\\n \\n # TO DO: get user input for month (all, january, february, ... , june)\\n month_temp = ''\\n while month_temp.lower() not in MONTH_DATA:\\n month_temp = input('For which month would you like to see the data?\\\\nPlease enter any month from January to June or enter all to see data for all the months available\\\\n')\\n if month_temp.lower() in MONTH_DATA:\\n month = month_temp.lower()\\n else:\\n print('This month is not available or does not exist.') # Error message\\n\\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n day_temp = ''\\n while day_temp.lower() not in DAY_DATA:\\n day_temp = input ('For which day of the week would you like to see the data?\\\\nPlease enter any day from Monday to Sunday or enter all to see data for all the days\\\\n')\\n if day_temp.lower() in DAY_DATA:\\n day = day_temp.lower()\\n else:\\n print('This day of the week does not exist') # Error message\\n \\n print('-'*40)\\n return city, month, day\",\n \"def main():\\n\\t#first check args and file paths\\n\\tcheckArgs(args)\\n\\t\\n\\tdata = args.dataset_file\\n\\tf_name = data.split(\\\".\\\")\\n\\tprint \\\"\\\\n[AP]\\\\t\\\"+\\\"######## \\\"+f_name[0] + '.' + f_name[1]+\\\" ########\\\"\\n\\tprint \\\"\\\\n[AP]\\\\tChecked inputs, now acquiring data\\\"\\n\\n\\thost = \\\"localhost\\\"\\n\\tuser = \\\"readonly\\\"\\n\\tpasswd = \\\"readonlypswd\\\"\\n\\tdb = args.db_schema\\n\\tdb_table = args.db_table\\n\\n\\tnameFile = data[0:-20]\\n\\tdataset = queryDataset(host,user,passwd,db,db_table,\\\"tmpFile.txt\\\",nameFile)\\n\\tif dataset is not None:\\n\\t\\tdataset = dataset.rstrip('\\\\n')\\n\\t\\tdataset = dataset.replace(\\\"/\\\",\\\"-\\\")\\n\\n\\t\\tlocations_list, length_list = generateDataset(data)\\n\\n\\t\\tif len(locations_list) < 2:\\n\\t\\t\\tprint \\\"\\\\n[SKIP]\\\\t{dataset} has only one unique line! Can't estimate anything.\\\\n\\\\tSKIP THIS FILE!\\\\n\\\".format(dataset=str(dataset))\\n\\t\\t\\treturn 0\\n\\n\\t\\t# Alias for estAbund calling\\n\\t\\testAbund = sonicLength.estAbund\\n\\n\\t\\t# Call estAbund and store returned object in results\\n\\t\\tresults = estAbund(robjects.StrVector(locations_list), robjects.FloatVector(length_list))\\n\\n\\t\\t# Put estimation for theta in estimations_theta and associated locations in locations_theta; then organize data in dic_of_theta\\n\\t\\ttheta = results.rx2(\\\"theta\\\")\\n\\t\\testimations_theta = tuple(theta)\\n\\t\\tlocations_theta = tuple(theta.names)\\n\\t\\t# dic_of_theta\\n\\t\\tdic_of_theta = {}\\n\\t\\tfor i in range(len(locations_theta)):\\n\\t\\t\\tdic_of_theta.update({locations_theta[i]:estimations_theta[i]})\\n\\n\\t\\t# Put different fragment lengths in length_phi and associated frequencies in freq_phi\\n\\t\\tphi = results.rx2(\\\"phi\\\")\\n\\t\\tfreq_phi = tuple(phi)\\n\\t\\tlength_phi = tuple(phi.names)\\n\\n\\t\\tlength_phi_numbers = fragmentsLengthPlot(length_phi,freq_phi,length_list,nameFile,dataset)\\n\\n\\t\\tprintThetaInfo(estimations_theta,locations_theta,nameFile)\\n\\n\\t\\t# Retrieving redundant reads data\\n\\t\\tdic_of_redundant_reads_count, sequence_count_list = redundant_reads_count(from_file_to_list(data,'.tsv'))\\n\\n\\t\\t# Box Plot\\n\\t\\tsequence_count = []\\n\\t\\tfor v in sequence_count_list:\\n\\t\\t\\tsequence_count.append(int(v))\\n\\t\\tbox_plot(sequence_count, estimations_theta, nameFile,dataset)\\n\\n\\t\\t# Plot: unique lengths retrieved for a genomic location VS expected number of parent fragment for the same location\\n\\t\\tphi_VS_theta(length_phi, freq_phi, nameFile, dataset)\\n\\n\\n\\t\\t#######################################################################################################\\n\\t\\t# Produce .tsv output about measured redundant reads count, abundance-corrected redundant reads count # \\n\\t\\t# and some descriptive of unique fragments lengths #\\n\\t\\t#######################################################################################################\\n\\n\\t\\t# Retrieving data\\n\\t\\tdic_of_relative_abundance, dic_of_corrected_reads_count, dic_of_percentage_difference = corrected_reads_count(dic_of_redundant_reads_count, dic_of_theta)\\n\\t\\tdic_of_unique_lengths, dic_of_unique_lengths_number, dic_of_median_of_unique_lengths, dic_of_MAD = fragment_lengths_statistics(data)\\n\\t\\tdic_of_lengths = lengths_explicit_list(from_file_to_list(data,'.txt'))\\n\\n\\t\\t# Writing File\\n\\t\\tcorrected_file = open(dataset + \\\".\\\" + nameFile+\\\".outcomes\\\"+\\\".tsv\\\", 'w')\\n\\t\\tcorrected_file.write(\\\"Chromosome\\\\tIntegration_locus\\\\tStrand\\\\tSequence_Count\\\\tEstimated_Relative_Abundance\\\\tCorrected_Sequence_Count\\\\tPercentage_Variation\\\\tNumber_of_fragments_of_unique_lengths\\\\tLength_Min\\\\tLength_Max\\\\tLenght_Median\\\\tRounded_Lenght_Median\\\\tMAD\\\\tUnique_Lengths_List\\\\tUnique_Lengths_Amount\\\\tCEM_region_?\\\") ## ! NB ! ## \\\\tCEM_region_?\\\" has to remain the last!!!\\n\\t\\tgenome_locations = dic_of_redundant_reads_count.keys()\\n\\t\\tgenome_locations.sort()\\n\\t\\tfor key in genome_locations:\\n\\t\\t\\tsplitted_location = key.split(' ')\\n\\t\\t\\tcorrected_file.write(\\\"\\\\n\\\" + splitted_location[0] + \\\"\\\\t\\\" + splitted_location[1] + \\\"\\\\t\\\" + splitted_location[2] + \\\"\\\\t\\\" + str(dic_of_redundant_reads_count[key]) + \\\"\\\\t\\\" + str(round(dic_of_relative_abundance[key],5)) + \\\"\\\\t\\\" + str(round(dic_of_corrected_reads_count[key],0)) + \\\"\\\\t\\\" + str(dic_of_percentage_difference[key]) + \\\"\\\\t\\\" + str(dic_of_unique_lengths_number[key]) + \\\"\\\\t\\\" + str(min(dic_of_unique_lengths[key])) + \\\"\\\\t\\\" + str(max(dic_of_unique_lengths[key])) + \\\"\\\\t\\\" + str(dic_of_median_of_unique_lengths[key]) + \\\"\\\\t\\\" + str(math.ceil(dic_of_median_of_unique_lengths[key]))+ \\\"\\\\t\\\" + str(dic_of_MAD[key]) + \\\"\\\\t\\\" + str(dic_of_unique_lengths[key]) + \\\"\\\\t\\\" + str(dic_of_lengths[key]))\\n\\t\\t\\tresponse, cem_symbol, cem_coordinates = is_CEM(key)\\n\\t\\t\\tif (response == True):\\n\\t\\t\\t\\tcorrected_file.write(\\\"\\\\t\\\" + cem_symbol)\\n\\n\\t\\t# Write database file - Like corrected_file with more field appended in the end\\n\\t\\tdb_file = open(dataset + \\\".\\\" + nameFile+\\\".db_file\\\"+\\\".tsv\\\", 'w')\\n\\t\\tgenome_locations = dic_of_redundant_reads_count.keys()\\n\\t\\tgenome_locations.sort()\\n\\t\\tdataset_split = dataset.split('.')\\n\\t\\tdataset_label = '_'.join(dataset_split)\\n\\t\\tfor key in genome_locations:\\n\\t\\t\\tsplitted_location = key.split(' ')\\n\\t\\t\\tdb_file.write(splitted_location[0] + \\\"\\\\t\\\" + splitted_location[1] + \\\"\\\\t\\\" + splitted_location[2] + \\\"\\\\t\\\" + str(dic_of_redundant_reads_count[key]) + \\\"\\\\t\\\" + str(round(dic_of_relative_abundance[key],5)) + \\\"\\\\t\\\" + str(round(dic_of_corrected_reads_count[key],0)) + \\\"\\\\t\\\" + str(dic_of_percentage_difference[key]) + \\\"\\\\t\\\" + str(dic_of_unique_lengths_number[key]) + \\\"\\\\t\\\" + str(min(dic_of_unique_lengths[key])) + \\\"\\\\t\\\" + str(max(dic_of_unique_lengths[key])) + \\\"\\\\t\\\" + str(dic_of_median_of_unique_lengths[key]) + \\\"\\\\t\\\" + str(math.ceil(dic_of_median_of_unique_lengths[key]))+ \\\"\\\\t\\\" + str(dic_of_MAD[key]) + \\\"\\\\t\\\" + str(dic_of_unique_lengths[key])[1:-1] + \\\"\\\\t\\\" + str(dic_of_lengths[key])[1:-1] + \\\"\\\\t\\\")\\n\\t\\t\\tdb_file.write(\\\"\\\\t\\\".join(dataset_split) + \\\"\\\\t\\\" + dataset_label + \\\"\\\\t\\\")\\n\\t\\t\\tresponse, cem_symbol, cem_coordinates = is_CEM(key)\\n\\t\\t\\tif (response == True):\\n\\t\\t\\t\\tdb_file.write(cem_symbol + \\\"\\\\t\\\" + cem_coordinates)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tdb_file.write(\\\"\\\\t\\\")\\n\\t\\t\\tdb_file.write(\\\"\\\\n\\\")\\n\\n\\t\\tdb_file.close()\\n\\n\\t\\t#######################################################################################################\\n\\n\\t\\t# Last print for user\\n\\t\\tprint \\\"\\\\n[AP]\\\\tTask Finished, closing.\\\\n\\\"\\n\\telse:\\n\\t\\tprint \\\"\\\\n[AP]\\\\tThe dataset is not in the reference DB. Skipped.\\\\n\\\"\\n\\n\\treturn 0\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data!')\\n day = days[0]\\n month = months[0]\\n\\n # get user input for city (chicago, new york city, washington).\\n while True:\\n print('Choose a city! Chicago, New York city or Washington. Which you prefer to analyze?\\\\n')\\n city = input() \\n if city.lower() not in cities:\\n print('Sorry, invalid entry. Please try again!\\\\n')\\n else:\\n while True:\\n filter = input('Do you prefer to filter by Month, Day or show all? Type \\\"all\\\" to skip filtering date\\\\n')\\n if filter.lower() not in ['month', 'day', 'all']:\\n print('Sorry, invalid entry. Please try again!\\\\n')\\n else:\\n if filter.lower() == 'month':\\n print('You have choosen {}!\\\\n'.format(filter))\\n # While loop used to avoid errors\\n while True:\\n # get user input for month (all, january, february, ... , june)\\n month = int(input('Which month are you looking for? Type 0 for all, 1 for January, 2 for February, 3 for March and so on\\\\n'))\\n if month not in range(0, 7):\\n print('Sorry, invalid entry. Please try again!\\\\n')\\n else:\\n month = months[int(month)]\\n print('You have choosen {}\\\\n'.format(month))\\n break\\n break\\n elif filter.lower() == 'day':\\n print('You have choosen {}!\\\\n'.format(filter))\\n # While loop used to avoid errors\\n while True:\\n # get user input for day of week (all, monday, tuesday, ... sunday)\\n day = int(input('Which day are you looking for? Type 0 for all, 1 for Sunday, 2 for Monday...\\\\n'))\\n if day not in range(0, 8):\\n print('Sorry, invalid entry. Please try again!\\\\n')\\n else:\\n day = days[int(day)]\\n print(\\\"You have choosen {}\\\\n\\\".format(day))\\n break\\n break\\n elif filter.lower() == 'all':\\n print('You have choosen {}!\\\\n'.format(filter))\\n break\\n break\\n print('It seems you want to see the data of {}, filter by {} and {}\\\\n'.format(city, month, day))\\n\\n print('-'*40)\\n return city, month, day\",\n \"def budget_for_activities(endcity, activity_list, num_traveler): # calculate new budget\\n # displaying activity list based on endcity\\n print(\\\"====== Displaying\\\", endcity, \\\"activities options =====\\\")\\n for i in range(len(activity_list)):\\n print(\\\" -- Enter\\\", i+1, \\\"to choose -- \\\")\\n activity_list[i].print_activities()\\n print(\\\" \\\")\\n print(\\\"Choose the activities you like to do in\\\", endcity)\\n print(\\\"[ Enter Q or q to quit after finish]\\\")\\n # calculate activity cost with based on number of travelers\\n user_chosen_activities = []\\n while True:\\n try:\\n user_activity_num = input(\\\"Enter an activity number: \\\")\\n if user_activity_num == 'q' or user_activity_num == 'Q' or int(user_activity_num) == 0: break\\n user_activity_num = int(user_activity_num) - 1\\n while activity_list[user_activity_num] not in user_chosen_activities:\\n user_chosen_activities += [activity_list[user_activity_num]]\\n except ValueError:\\n print(\\\"Please enter a number between 1 to 5...\\\")\\n # calculate total activity cost\\n total_activity_cost = 0\\n for i in user_chosen_activities:\\n activity_price = i.get_unitprice() * num_traveler\\n total_activity_cost += activity_price\\n # calculate remaining budget and/or ask for higher budget\\n user_budget.calculate_new_budget(total_activity_cost)\\n return total_activity_cost, user_chosen_activities\",\n \"def main():\\n\\n file_name_base = \\\"./lab-record/result/fairness/\\\"\\n scenarios = ['lan', 'wan1', 'wan2']\\n scenario = scenarios[2]\\n\\n algorithms = [\\\"bbr\\\", \\\"scalable\\\", \\\"bic\\\", \\\"highspeed\\\", \\\"htcp\\\", \\\"hybla\\\",\\n \\\"illinois\\\", \\\"vegas\\\", \\\"yeah\\\"]\\n names = [\\\"BBR\\\", \\\"Scalable\\\", \\\"BIC\\\", \\\"High Speed\\\",\\n \\\"H-TCP\\\", \\\"Hybla\\\", \\\"Illinois\\\", \\\"Vegas\\\", \\\"YeAH\\\"]\\n\\n test_types = [\\\"vs_reno\\\", \\\"vs_cubic\\\", \\\"vs_itself\\\"]\\n\\n fsize = 36\\n \\n index_reno = []\\n index_cubic = []\\n index_itself = []\\n\\n data = []\\n \\n print 'Loadint statistics for ' + file_name_base + '/' + scenario\\n\\n for algorithm in algorithms:\\n for test in test_types:\\n path_base = file_name_base + \\\"/\\\" + scenario + \\\"/\\\" + test + \\\"/\\\" + \\\\\\n algorithm + \\\"/\\\"\\n if test == \\\"vs_itself\\\":\\n exp_name = names[algorithms.index(algorithm)] + \\\"_1\\\"\\n con_name = names[algorithms.index(algorithm)] + \\\"_2\\\"\\n print path_base + exp_name\\n print path_base + con_name\\n exp_filename = \\\"/\\\" + algorithm + \\\"_1.log\\\"\\n con_filename = \\\"/\\\" + algorithm + \\\"_2.log\\\"\\n process(path_base, exp_filename, con_filename, index_itself)\\n if test == \\\"vs_reno\\\":\\n exp_name = names[algorithms.index(algorithm)]\\n con_name = \\\"Reno\\\"\\n print path_base + exp_name\\n print path_base + con_name\\n exp_filename = \\\"/\\\" + algorithm + \\\".log\\\"\\n con_filename = \\\"/reno.log\\\"\\n process(path_base, exp_filename, con_filename, index_reno)\\n if test == \\\"vs_cubic\\\":\\n con_name = \\\"CUBIC\\\"\\n exp_name = names[algorithms.index(algorithm)]\\n print path_base + exp_name\\n print path_base + con_name\\n exp_filename = \\\"/\\\" + algorithm + \\\".log\\\"\\n con_filename = \\\"/cubic.log\\\"\\n process(path_base, exp_filename, con_filename, index_cubic)\\n\\n size = 9\\n x = numpy.arange(size)\\n\\n total_width, n = 1.2, 2.5\\n width = 1.0 / n\\n x = x - (total_width - width) / 2\\n\\n for i in range(0, len(x)):\\n x[i] += 0.5 * i\\n\\n # Exp\\n fig = plt.figure()\\n\\n # Con\\n con_reno = plt.bar(x + 0 * width - 1.2,\\n index_reno,\\n width=width,\\n label='Against Reno',\\n alpha=0.5,\\n color=\\\"darkorange\\\")\\n\\n con_cubic = plt.bar(x + 1 * width - 1.2,\\n index_cubic,\\n width=width,\\n label='Against CUBIC',\\n alpha=0.5,\\n color=\\\"lawngreen\\\")\\n\\n con_itself = plt.bar(x + 2 * width - 1.2,\\n index_itself,\\n width=width,\\n label='Against Another Same CCA',\\n alpha=0.5,\\n color=\\\"dodgerblue\\\")\\n\\n # Index\\n plt.xticks(x + 1.5 * width - 1.2, [\\\"BBR\\\", \\\"Scalable\\\", \\\"BIC\\\", \\\"High Speed\\\",\\n \\\"H-TCP\\\", \\\"Hybla\\\", \\\"Illinois\\\", \\\"Vegas\\\",\\n \\\"YeAH\\\"],\\n fontsize=fsize,\\n rotation=\\\"45\\\")\\n plt.ylabel(\\\"Jain`s Fairness Index\\\", fontsize=fsize)\\n plt.yticks(fontsize=fsize)\\n plt.ylim(0.5, 1.1)\\n\\n ax = plt.subplot(111)\\n ax.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3,\\n ncol=3, mode=\\\"expand\\\", borderaxespad=0., fontsize=fsize)\\n\\n plt.subplots_adjust(left=0.07, right=0.98, top=0.9, bottom=0.2)\\n\\n plt.show()\",\n \"def main():\\r\\n\\r\\n # Pre-pandemic period\\r\\n # Step 1 (might take 2-3 mins to categorise 16724 records)\\r\\n pre = RQ2('../csv_files/precovid_filtered.csv')\\r\\n pre.cateActions()\\r\\n\\r\\n # Step 2\\r\\n for detail in pre.li_detail[:10]:\\r\\n print(detail)\\r\\n plot_lev(pre.od)\\r\\n\\r\\n # Step 3\\r\\n df_new_fixed_pre = manFix(pre.df_new,option='precovid')\\r\\n\\r\\n # Step 4 \\r\\n li_pre_final = cal_group_actions(df_new_fixed_pre,option='precovid')\\r\\n\\r\\n # ================================================================\\r\\n # Post-pandemic period\\r\\n # Step 1 (might take 2-3 mins to categorise 25827 records)\\r\\n post = RQ2('../csv_files/postcovid_filtered.csv')\\r\\n post.cateActions()\\r\\n\\r\\n # Step 2 is similar to pre-pandemic period (commented to keep the result clear)\\r\\n # for detail in post.li_detail[:10]:\\r\\n # print(detail)\\r\\n\\r\\n # Step 3\\r\\n df_new_fixed_post = manFix(post.df_new, option='postcovid')\\r\\n\\r\\n # Step 4 \\r\\n li_post_final = cal_group_actions(df_new_fixed_post,option='postcovid')\\r\\n\\r\\n # ================================================================\\r\\n # Step 5\\r\\n meanTest(li_pre_final,li_post_final)\\r\\n\\r\\n # Step 6\\r\\n li_merge = li_pre_final + li_post_final\\r\\n boxplot(li_merge)\",\n \"def get_filters():\\n print('Hello! Let\\\\'s explore some US bikeshare data!')\\n # TO DO: get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs\\n city = input('The bicycle mobility study is available for any of these three cities: Chicago, New York City or Washington; please type the name of one of them. ').lower()\\n\\n while city not in CITY_DATA:\\n print('Sorry, the city entered does not have a mobility study. Please try again.')\\n city = input('The bicycle mobility study is available for any of these three cities: Chicago, New York City or Washington; please type the name of one of them.').lower()\\n print('The selected city is: {}'.format(city))\\n\\n # TO DO: get user input for month (all, january, february, ... , june)\\n MONTH_DATA=('all','january', 'february', 'march', 'april', 'may', 'june')\\n\\n month = input('Type a month between January and June or enter all to select the semester. ').lower()\\n\\n while month not in MONTH_DATA:\\n print ('Error entering the month, please try again.')\\n month = input('Type a month between January and June or enter all to select the semester. ').lower()\\n print('The selected month is: {}'.format(month))\\n\\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n DAY_DATA=('all','monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday')\\n\\n day = input('Write a day of the week or type all to select the seven days. ').lower()\\n\\n while day not in DAY_DATA:\\n print ('The day entered does not exist, please try again.')\\n day = input('Write a day of the week or type all to select the seven days. ').lower()\\n print('The selected day is: {}'.format(day))\\n\\n print('-'*40)\\n return city, month, day\",\n \"def main(gage_id: str, inputs_path: str = '', outputs_dir: str = '', data_type: str = 'Q', version: str = '2_2', \\r\\n max_cl: float = 0.99, adj_flows: float = 1.0, round_decimals: int = 1, verbose: bool = True, \\r\\n display_plots: bool = True, extrapolate: bool = True, exclude_tails: bool = True) -> pd.DataFrame:\\r\\n standard_aep = [0.9, 0.5, 0.2, 0.1, 0.05, 0.02, 0.01, 0.005, 0.002, 0.001, 5E-04, 2E-04, 1E-04, 5E-05, 2E-05, 1E-05,\\r\\n 5E-06, 2E-06, 1E-06] \\r\\n\\r\\n inputs_path = pl.Path(inputs_path)\\r\\n if inputs_path.suffix == '':\\r\\n if verbose:\\r\\n print('Specified inputs_path is to a directory, identifying .rpt files:')\\r\\n ssp_results = list_ssp_files(inputs_path, max_cl, verbose) \\r\\n df = make_ssp_table(ssp_results, version) \\r\\n elif inputs_path.suffix == '.csv':\\r\\n df = pd.read_csv(inputs_path, index_col = 0)\\r\\n assert df.index.name == 'AEP', ('The first column of the specified csv must be titled \\\"AEP\\\" and contain annual '\\r\\n 'exceedance probabilites.')\\r\\n if verbose:\\r\\n print('Specified inputs_path is to a csv, loaded table.\\\\n')\\r\\n else:\\r\\n raise NameError('The specified inputs_path is not a directory of .rpt files or a path to a csv file as '\\r\\n 'expected.')\\r\\n if data_type not in ['Q', 'P']:\\r\\n raise ValueError('The specified data_type may only be \\\"Q\\\" or \\\"P\\\" corresponding to discharge or precipitation, '\\r\\n 'respectively') \\r\\n df = monotonic_test(df, adj_flows, verbose)\\r\\n cl = list(map(float, df.columns)) \\r\\n clz = zvar(cl) \\r\\n aep = df.index \\r\\n aepz = zvar(aep) \\r\\n data = np.log10(df) \\r\\n q = binq(data)\\r\\n res = interp_aep(data, q, clz, aepz, extrapolate) \\r\\n restrans = zvar_inv(res, cl)\\r\\n aepm = mean_aep(restrans, exclude_tails) \\r\\n aepmz = zvar(aepm) \\r\\n standard_aepz = zvar(standard_aep) \\r\\n table = ffc_summary(standard_aep, standard_aepz) \\r\\n table['Q_Mean_cfs'] = np.round(10**table['AEPz'].apply(interp_q(aepmz, q)), round_decimals)\\r\\n table['Q_Median_cfs'] = np.round(10**table['AEPz'].apply(interp_q(aepz, np.array(data['0.5']))), round_decimals)\\r\\n mean_curve_table = table.copy().drop(columns=['AEPz'])\\r\\n if display_plots: \\r\\n plot_ssp_meanmedffc(table, gage_id, data_type) \\r\\n if data_type == 'P':\\r\\n mean_curve_table.rename(columns = {'Q_Mean_cfs': 'P_Mean_in', 'Q_Median_cfs': 'P_Median_in'}, inplace = True)\\r\\n if verbose:\\r\\n display(mean_curve_table.head(2)) \\r\\n if outputs_dir!='':\\r\\n make_directories([outputs_dir], verbose)\\r\\n mean_curve_table.to_csv(pl.Path(outputs_dir)/f'MeanCurve_{gage_id}.csv') \\r\\n return mean_curve_table\",\n \"def payment_info_and_status(report):\\n\\n order_data = open(report)\\n for line in order_data:\\n order = lines_into_list(line) # function will split each line by '|' and get a list of strings\\n # each order has 4 strings\\n order[0:1] = []\\n name = order.pop(0)\\n order_as_floats = convert_to_floats(order)\\n melon_count, paid = order_as_floats\\n expected_cost = calculate_expected_cost(melon_cost, melon_count)\\n print(f\\\"{name} paid ${paid:.2f}, expected ${expected_cost:.2f}\\\")\\n check_order(name, expected_cost, paid)\\n order_data.close()\",\n \"def do_analysis(ckpt, queries_type, entities_type, request):\\n global currently_analyzing, results, d, analysis_user\\n try:\\n print(\\\"starting analysis!\\\")\\n if entities_type == \\\"all\\\":\\n print(\\\"using all entities detected!\\\")\\n elif entities_type == \\\"uploaded\\\":\\n print(\\\"using only entities specified in csv file!\\\")\\n \\n currently_analyzing = True\\n analysis_user = request.user.username\\n results = []\\n proj_path = os.path.abspath(os.path.dirname(__file__)).split(\\\"FYP_Web_App\\\")[0]\\n ckpt = proj_path + \\\"FewRel/checkpoint/\\\" + ckpt\\n if d is None or d.ckpt_path != ckpt:\\n d = DetectionFramework(ckpt_path=ckpt)\\n if cancel_flag[0]:\\n return\\n d.clear_support_queries()\\n if len([i for i in os.listdir(\\\"temp/relation_support_datasets\\\") if 'csv' in i and request.user.username in i]) == 0:\\n raise ValueError(\\\"Please upload relation support dataset!\\\")\\n \\n d.load_support_files(\\\"temp/relation_support_datasets\\\", request.user.username)\\n if queries_type == \\\"csv_option\\\":\\n if not os.path.exists(\\\"temp/queries.csv\\\"):\\n raise ValueError(\\\"Please upload query CSV dataset!\\\")\\n d.load_queries_csv(\\\"temp/queries.csv\\\")\\n \\n elif queries_type == \\\"url_option\\\":\\n if not os.path.exists(\\\"temp/url.txt\\\"):\\n raise ValueError(\\\"Please specify news article url!\\\")\\n with open(\\\"temp/url.txt\\\") as f:\\n url = f.read()\\n d.load_url(url)\\n \\n elif queries_type == \\\"txt_option\\\":\\n d.load_text_files(os.path.abspath(\\\"temp/text_files\\\"))\\n \\n elif queries_type == \\\"ind_sentence_option\\\":\\n ind_sentence = request.POST.get('ind_sent')\\n d.load_ind_sentence(ind_sentence)\\n \\n elif queries_type == \\\"html_option\\\":\\n d.load_html_file_queries(os.path.abspath(\\\"temp/html_files\\\"))\\n \\n if entities_type == \\\"uploaded\\\":\\n d.trim_queries_based_on_entities_file(os.path.abspath(\\\"temp/entities_csv_file.csv\\\"))\\n\\n if cancel_flag[0]:\\n return\\n d.detect(rt_results=results, cancel_flag=cancel_flag)\\n if cancel_flag[0]:\\n return\\n src=None\\n if queries_type == \\\"csv_option\\\":\\n src = \\\"queries_csv\\\"\\n elif queries_type == \\\"txt_option\\\":\\n src = \\\"queries_text_file\\\"\\n elif queries_type == \\\"ind_sentence_option\\\":\\n src = \\\"ind_sentence\\\"\\n elif queries_type == \\\"url_option\\\":\\n with open(\\\"temp/url.txt\\\") as f:\\n src = f.read()\\n elif queries_type == \\\"html_option\\\":\\n src = \\\"html_files\\\"\\n \\n s = Source(source=src, user=request.user)\\n s.save()\\n for r in results:\\n er = ExtractedRelation(sentence=r['sentence'],head=r['head'],tail=r['tail'],pred_relation=r['pred_relation'],sentiment=r['sent'],conf=r['conf'],ckpt=ckpt, source=s)\\n er.save()\\n except Exception as e:\\n print(len(str(e)))\\n print(str(e))\\n errors.append(str(e))\\n tb = traceback.format_exc()\\n print(tb)\\n finally:\\n currently_analyzing = False\\n analysis_user = None\",\n \"def main():\\n \\n file = open(\\\"profit.txt\\\",\\\"r\\\")\\n profits = file.readlines()\\n file = open(\\\"revenue.txt\\\",\\\"r\\\")\\n revenues = file.readlines()\\n file.close()\\n \\n totalProfits = 0\\n for i in range(len(profits)):\\n totalProfits += float(profits[i])\\n \\n print \\\"Total Fortune 500 profits, \\\" + os.environ['YEAR'] + \\\": $\\\" + str(totalProfits) + \\\"M\\\"\\n \\n totalRevenues = 0\\n for j in range(len(revenues)):\\n totalRevenues += float(revenues[i])\\n \\n print \\\"Total Fortune 500 revenues, \\\" + os.environ['YEAR'] + \\\": $\\\" + str(totalRevenues) + \\\"M\\\"\",\n \"def f_columnas_pips(param_data, init_invest=5000):\\n\\n # calcular ganancia o perdida expresada en pips\\n param_data['pips'] = [\\n (param_data.loc[i, 'closeprice'] - param_data.loc[i, 'openprice']) * f_pip_size(param_data.loc[i, 'symbol'])\\n if param_data.loc[i, 'type'] == 'buy'\\n else (param_data.loc[i, 'openprice'] - param_data.loc[i, 'closeprice']) * f_pip_size(\\n param_data.loc[i, 'symbol'])\\n for i in param_data.index\\n ]\\n\\n # calcular los pips acumulados de perdidas o ganancias\\n param_data['pips_acum'] = param_data['pips'].cumsum()\\n\\n # calcular la ganancia o perdida acumulada de la cuenta\\n param_data['profit_acum'] = param_data['profit'].cumsum()\\n\\n # calcular el capital acumulado por operacion\\n param_data['capital_acum'] = [init_invest + param_data['profit_acum'][i] for i in param_data.index]\\n\\n return param_data\",\n \"def statistical_analysis(var1, var2, var3, var4, var5, var6, var7, var8, var9, var10, var11, var12, param):\\n \\n valueCount_prov1 = round(valueCounter([var1, var4, var7, var10]),3) #how many valid OpenWeatherMap forecasts are available\\n valueCount_prov2 = round(valueCounter([var2, var5, var8, var11]),3) #how many valid Weatherbit forecasts are available\\n valueCount_prov4 = round(valueCounter([var3, var6, var9, var12]),3) #how many valid WorldWeatherOnline forecasts are available\\n \\n average_discrepancy_prov1 = round(averageOfList([var1, var4, var7, var10]),3) #average forecast discrepancy for each provider\\n average_discrepancy_prov2 = round(averageOfList([var2, var5, var8, var11]),3)\\n average_discrepancy_prov4 = round(averageOfList([var3, var6, var9, var12]),3)\\n \\n absolute_average_discrepancy_prov1 = round(absoluteAverageOfList([var1, var4, var7, var10]),3) #average absolute forecast discrepancy for each provider\\n absolute_average_discrepancy_prov2 = round(absoluteAverageOfList([var2, var5, var8, var11]),3)\\n absolute_average_discrepancy_prov4 = round(absoluteAverageOfList([var3, var6, var9, var12]),3)\\n \\n median_discrepancy_prov1 = round(medianErrorOfList([var1, var4, var7, var10]),3) #median forecast discrepancy for each provider\\n median_discrepancy_prov2 = round(medianErrorOfList([var2, var5, var8, var11]),3)\\n median_discrepancy_prov4 = round(medianErrorOfList([var3, var6, var9, var12]),3)\\n\\n sd_discrepancy_prov1 = sampleStandardDeviation([var1, var4, var7, var10]) #standard deviation forecast discrepancy for each provider\\n sd_discrepancy_prov2 = sampleStandardDeviation([var2, var5, var8, var11]) #if there are at least two values available\\n sd_discrepancy_prov4 = sampleStandardDeviation([var3, var6, var9, var12])\\n\\n #which is the best forecast: defined by minimal absolute average discrepancy\\n if min([absolute_average_discrepancy_prov1,absolute_average_discrepancy_prov2,absolute_average_discrepancy_prov4]) == absolute_average_discrepancy_prov1:\\n most_accurate_forecast = \\\"OpenWeatherMap\\\"\\n if min([absolute_average_discrepancy_prov1,absolute_average_discrepancy_prov2,absolute_average_discrepancy_prov4]) == absolute_average_discrepancy_prov2:\\n most_accurate_forecast = \\\"Weatherbit\\\"\\n if min([absolute_average_discrepancy_prov1,absolute_average_discrepancy_prov2,absolute_average_discrepancy_prov4]) == absolute_average_discrepancy_prov4:\\n most_accurate_forecast = \\\"WorldWeatherOnline\\\"\\n if min([absolute_average_discrepancy_prov1,absolute_average_discrepancy_prov2,absolute_average_discrepancy_prov4]) == absolute_average_discrepancy_prov1 and min([absolute_average_discrepancy_prov1,absolute_average_discrepancy_prov2,absolute_average_discrepancy_prov4]) == absolute_average_discrepancy_prov2:\\n most_accurate_forecast = \\\"OpenWeatherMap and Weatherbit\\\"\\n if min([absolute_average_discrepancy_prov1,absolute_average_discrepancy_prov2,absolute_average_discrepancy_prov4]) == absolute_average_discrepancy_prov1 and min([absolute_average_discrepancy_prov1,absolute_average_discrepancy_prov2,absolute_average_discrepancy_prov4]) == absolute_average_discrepancy_prov4:\\n most_accurate_forecast = \\\"OpenWeatherMap and WorldWeatherOnline\\\" \\n if min([absolute_average_discrepancy_prov1,absolute_average_discrepancy_prov2,absolute_average_discrepancy_prov4]) == absolute_average_discrepancy_prov2 and min([absolute_average_discrepancy_prov1,absolute_average_discrepancy_prov2,absolute_average_discrepancy_prov4]) == absolute_average_discrepancy_prov4:\\n most_accurate_forecast = \\\"Weatherbit and WorldWeatherOnline\\\"\\n if min([absolute_average_discrepancy_prov1,absolute_average_discrepancy_prov2,absolute_average_discrepancy_prov4]) == absolute_average_discrepancy_prov2 and min([absolute_average_discrepancy_prov1,absolute_average_discrepancy_prov2,absolute_average_discrepancy_prov4]) == absolute_average_discrepancy_prov4 and min([absolute_average_discrepancy_prov1,absolute_average_discrepancy_prov2,absolute_average_discrepancy_prov4]) == absolute_average_discrepancy_prov1:\\n most_accurate_forecast = \\\"all three forecasts\\\"\\n \\n dictionary = { #save the values to dictionary to make them accessible for the HTML template\\n 'valueCount_prov1_'+str(param) : valueCount_prov1,\\n 'valueCount_prov2_'+str(param) : valueCount_prov2,\\n 'valueCount_prov4_'+str(param) : valueCount_prov4,\\n 'average_discrepancy_prov1_'+str(param) : average_discrepancy_prov1,\\n 'average_discrepancy_prov2_'+str(param) : average_discrepancy_prov2,\\n 'average_discrepancy_prov4_'+str(param) : average_discrepancy_prov4,\\n 'absolute_average_discrepancy_prov1_'+str(param) : absolute_average_discrepancy_prov1,\\n 'absolute_average_discrepancy_prov2_'+str(param) : absolute_average_discrepancy_prov2,\\n 'absolute_average_discrepancy_prov4_'+str(param) : absolute_average_discrepancy_prov4,\\n 'median_discrepancy_prov1_'+str(param) : median_discrepancy_prov1,\\n 'median_discrepancy_prov2_'+str(param) : median_discrepancy_prov2,\\n 'median_discrepancy_prov4_'+str(param) : median_discrepancy_prov4,\\n 'sd_discrepancy_prov1_'+str(param) : sd_discrepancy_prov1,\\n 'sd_discrepancy_prov2_'+str(param) : sd_discrepancy_prov2,\\n 'sd_discrepancy_prov4_'+str(param) : sd_discrepancy_prov4,\\n 'weatherDay_'+str(param) : most_accurate_forecast,\\n }\\n \\n return dictionary\",\n \"def objective(trial):\\n # The parameters that we will calibrate the model for are shown here.\\n # Optuna trial i\\n BOD = trial.suggest_uniform(\\\"BOD\\\", 0, 1) #Review ranges here\\n k_r = trial.suggest_uniform(\\\"k_r\\\", 0, 1) #Review Ranges here \\n \\n def ChLa(t):\\n return 1 # Need to link to data\\n\\n def I(x):\\n return 1 # Need to link to data\\n\\n K_z = 2 * 10**(-5) # p.51\\n a = K_z\\n k_b = 0.1 # Table 5\\n th_b = 1.047 # Table 5\\n k_r = 0.1 # Table 5\\n YCHO2 = 0.0083 # Table 5\\n th_p = 1.036 # Table 5\\n th_s = 1.065 # Table 5\\n th_r = 1.047 # Table 5\\n\\n def Temp(t):\\n \\\"\\\"\\\"\\n Function that maps time to temperature\\n \\\"\\\"\\\"\\n return 20 # Need to link to data\\n\\n def P_max(t):\\n return 9.6 * 1.036 **(Temp(t) - 20) # Eq. 4\\n\\n def L_min(t):\\n I = 1 # Need to link to PAR data\\n K_1 = 0.687 * 1.086**(Temp(t) - 20)\\n K_2 = 15\\n return I * (1 + 2 * np.sqrt(K_1 / K_2)) / (I + K_1 + I**2 / K_2) # Eq. 5\\n \\n # f deals with sink and source terms \\n def f(x, t):\\n return -1 / YCHO2 * k_r * th_r**(Temp(t) - 20) * ChLa(t) + P_max(t) * L_min(t) * ChLa(t) - k_b * th_b**(Temp(t)-20) * BOD \\n\\n L = 200 # Length of domain\\n dt = 1 / 48 # Mesh spacing in t\\n F = a * dt # a * dt / dx**2\\n T = 100 # Simulation time stop\\n\\n # Solving the PDE\\n DO, x, t, _ = solver_FE_simple(I, a, f, L, dt, F, T)\\n \\n # Creating some bogus targets while database errors are happening\\n DO_data = DO + np.random.random(len(DO))\\n\\n # Using mean squared error as the measure of fit, where we want\\n # to minimize this number\\n return ((DO - DO_data)**2).mean()\",\n \"def getArguments(Comm):\\n input_dir=''\\n dataset=''\\n l=0.0\\n if len(Comm)==4:\\n input_dir=str(Comm[1])\\n dataset=str(Comm[2])\\n l=float(Comm[3])\\n else:\\n print \\\"To run this program you have to provide a training file, a test file, an output file and a smoothing parameter\\\"\\n print \\\"the chemicals must be integer indexed. This script read chemical feature files based on chemical index in integer\\\"\\n print \\\"example: python PRW_10cv.py /path/to/N1/L1to5/ N1L1to5 0.9\\\"\\n exit(1)\\n feature=get_feature()\\n RCRS=[]\\n TPR35=[]\\n for i in range(1,11):\\n #10cv for 1 to 10\\n trainfile=input_dir+\\\"train\\\"+str(i)+\\\".csv\\\"\\n Train=get_train(trainfile,feature)\\n\\n testfile=input_dir+\\\"test\\\"+str(i)+\\\".csv\\\"\\n \\n testrow=[]\\n testcol=[]\\n print \\\"Reading test instances : \\\",testfile\\n for line in open(testfile,\\\"r\\\").xreadlines():\\n z=line.strip().split(\\\",\\\")\\n chem=str(z[0])\\n prot=str(z[1])\\n testrow.append(chem)\\n testcol.append(prot)\\n rcrs=get_PRW_rcrs(feature,Train,zip(testrow,testcol),l)\\n tpr35=TPRbyRowRank(rcrs,35)\\n TPR35.append(tpr35)\\n RCRS=RCRS+rcrs\\n avgtpr35=np.average(TPR35)\\n semtpr35=(np.std(TPR35)/math.sqrt(len(TPR35)))\\n print \\\"Dataset=%s, Avg.TPR35=%s, S.E.M.TPR35=%s\\\"%(dataset,str(avgtpr35),str(semtpr35))\\n print TPR35\\n print \\\"Rank\\\\tTPR\\\"\\n for i in range(1,351):\\n tpr=TPRbyRowRank(RCRS,i)\\n print \\\"%s\\\\t%s\\\"%(str(i),str(tpr))\\n return\",\n \"def main():\\n\\n parser = argparse.ArgumentParser(description='Get university tuition fee')\\n parser.add_argument(\\n '--wolframalpha', \\n dest='wa_app_id', \\n default='None',\\n help='Please provide the wolfram alpha app id here'\\n )\\n \\n parser.add_argument(\\n '--input', \\n dest='input_file', \\n default='data/input.csv',\\n help='Please provide the path to university list'\\n )\\n\\n parser.add_argument(\\n '--output', \\n dest='output_file', \\n default='data/output.csv',\\n help='Please provide the path to university list'\\n )\\n \\n parser.add_argument(\\n '--start', \\n dest='start_name', \\n default='None',\\n help='Start from a certain university'\\n )\\n parser.add_argument(\\n '--sleep', \\n dest='sleep_seconds', \\n default='10',\\n help='Time to sleep before start the next university; This is added to prevent the ip from being banned.'\\n )\\n\\n args = parser.parse_args()\\n wa_app_id = args.wa_app_id\\n input_file = args.input_file\\n output_file = args.output_file\\n start_name = args.start_name\\n sleep_seconds = int(args.sleep_seconds)\\n\\n print('Using wolframalpha app_id: {}'.format(wa_app_id))\\n if wa_app_id == 'None':\\n raise Exception('Please provide a wolfram alpha app_id using the --wolframalpha option')\\n else:\\n logging.debug('Using wolframalpha app_id: {}'.format(wa_app_id) )\\n\\n if start_name == 'None':\\n start_name = None\\n\\n try:\\n client = wolframalpha.Client(wa_app_id)\\n except Exception as ee:\\n raise Exception('Could not initialize wolframalpha client: {}'.format(ee) )\\n\\n\\n try: \\n uni_list_to_be_queried = _extract_universities(\\n input_file, start=start_name\\n )\\n except Exception as ee:\\n raise Exception('Could not extract list of universities: {}'.format(ee) )\\n\\n with open(output_file, 'a+') as fp:\\n for uni in uni_list_to_be_queried:\\n the_tuition = _tuition_pipe(client, uni)\\n fp.write(json.dumps(the_tuition) + '\\\\n' )\\n logging.info( \\\"{} - {} - {}\\\".format(\\n datetime.datetime.now() , uni, the_tuition) \\n )\\n time.sleep(sleep_seconds)\",\n \"def calc_visible( observatory, date_start, date_end, sigtype='transits', \\\\\\n ofilename_byplanet='default', ofilename_chronolog='default',\\n sun_alt_max=-6, sun_alt_twil=-12, sun_alt_dark=-18, \\\\\\n moon_alt_set=-6, target_elev_min=25, oot_deltdur=0.5, \\\\\\n tr_signals='signals_transits.txt', ec_signals='signals_eclipses.txt', \\\\\\n exclude_unranked=False, max_rank=None ):\\n\\n # Convert the minimum target altitude to a maximum zenith angle:\\n zenith_max = 90 - target_elev_min\\n\\n # Read in the basic target information for all transiting exoplanets:\\n targets, vmags, ras, decs, ttrs, pers, durs = read_eph( EPH_FILE )\\n\\n # Read in the rankings for transit and eclipse signals:\\n targets_ec, ranks_ec = eclipse_ranks( ec_signals )\\n targets_tr, ranks_tr = transit_ranks( tr_signals ) \\n\\n # Create the databases that will be used by pyephem for calculating\\n # ephemerides for each object:\\n ntargets = len( targets )\\n dbs = []\\n for i in range( ntargets ):\\n db_str = '{targ},f|S,{ra},{dec},{vmag}'.format( targ=targets[i], \\\\\\n ra=ras[i], \\\\\\n dec=decs[i], \\\\\\n vmag=vmags[i] )\\n dbs += [ db_str ]\\n\\n # Open the output file and write a header:\\n if ofilename_byplanet=='default':\\n if sigtype=='transits':\\n ofilename_byplanet = '{0}_transits_byplanet.txt'.format( observatory )\\n ofilename_chronolog = '{0}_transits_chronolog.txt'.format( observatory )\\n elif sigtype=='eclipses':\\n ofilename_byplanet = '{0}_eclipses_byplanet.txt'.format( observatory )\\n ofilename_chronolog = '{0}_eclipses_chronolog.txt'.format( observatory ) \\n else:\\n pdb.set_trace() #this shouldn't happen\\n\\n # Create the strings that will be used for column headers:\\n colheadingsa_bp, colheadingsb_bp = make_colheadings( 'byplanet' )\\n colheadingsa_ch, colheadingsb_ch = make_colheadings( 'chronolog' )\\n nchar_bp = np.max( [ len( colheadingsa_bp ), len( colheadingsb_bp ) ] )\\n nchar_ch = np.max( [ len( colheadingsa_ch ), len( colheadingsb_ch ) ] )\\n\\n ofile_bp = open( ofilename_byplanet, 'w' )\\n ofile_bp.write( '{0}\\\\n#\\\\n'.format( '#'*nchar_bp ) )\\n\\n ofile_ch = open( ofilename_chronolog, 'w' )\\n ofile_ch.write( '{0}\\\\n#\\\\n#'.format( '#'*nchar_ch ) )\\n \\n if sigtype=='transits':\\n sigtype_lower_singular = 'transit'\\n sigtype_upper_singular = 'Transit'\\n else:\\n sigtype_lower_singular = 'eclipse'\\n sigtype_upper_singular = 'Eclipse'\\n\\n ofile_bp.write( '# Visible primary {0}s from {1} between {2} and {3}, arranged by planet\\\\n#\\\\n'\\\\\\n .format( sigtype_lower_singular, observatory, date_start, date_end ) )\\n ofile_ch.write( '# Visible primary {0}s from {1} between {2} and {3}, arranged in chronological order\\\\n#\\\\n'\\\\\\n .format( sigtype_lower_singular, observatory, date_start, date_end ) )\\n if max_rank!=None:\\n header_str = '# Only considered the top {0} ranked signals and of these only those with {1}s\\\\n'\\\\\\n .format( max_rank, sigtype_lower_singular )\\n header_str += '# where the mid-time occurs at a zenith angle <{0}deg\\\\n#\\\\n'\\\\\\n .format( zenith_max )\\n else:\\n header_str = '# Considered all published transiting planets but output only printed where the\\\\n'\\n header_str += '# {0} mid-time occurs at a zenith angle <{0}deg\\\\n#\\\\n'.format( zenith_max )\\n if oot_deltdur>0:\\n header_str += '# Accounts for {0:.2f} transit durations before and after the transit to sample\\\\n'.format( oot_deltdur )\\n header_str += '# the out-of-transit baseline flux level\\\\n#\\\\n'\\n else:\\n header_str += '# No allowance made for time required to sample the out-of-transit baseline flux\\\\n'\\n header_str += '# before and after the transit\\\\n#\\\\n'\\n header_str += '# The sun elevation angle has been divided into the following ranges:\\\\n#\\\\n'\\n header_str += '# 1. Maximum acceptable = {0}deg\\\\n'.format( sun_alt_max )\\n header_str += '# 2. Dawn/Dusk = [ {0}deg to {1}deg ]\\\\n'.format( sun_alt_twil, sun_alt_max )\\n header_str += '# 3. Twilight = [ {0}deg to {1}deg ]\\\\n'.format( sun_alt_dark, sun_alt_twil )\\n header_str += '# 4. Dark < {0}deg\\\\n#\\\\n'.format( sun_alt_dark )\\n header_str += '# {0}s are described by a string with format {{type}}-{{details}}, where:\\\\n#\\\\n'\\\\\\n .format( sigtype_upper_singular )\\n header_str += '# {{type}} refers to whether or not we get all of the {0} with the sun below its\\\\n'.format( sigtype_lower_singular )\\n header_str += '# maximum acceptable value:\\\\n'\\n header_str += '# - \\\\'full\\\\' if the sun elevation is less than the maximum acceptable value for the\\\\n'\\n header_str += '# entire duration of the {0}\\\\n'.format( sigtype_lower_singular )\\n header_str += '# - \\\\'partial\\\\' if the sun elevation is less than the maximum acceptable value at\\\\n'\\n header_str += '# the {0} mid-time, but not for the entire duration of the {0}\\\\n#\\\\n'\\\\\\n .format( sigtype_lower_singular )\\n if oot_deltdur==0:\\n header_str += '# {details} can have the following values:\\\\n'\\n else:\\n header_str += '# {{details}} refer to the full span of the observations including the {0:.2f} transit\\\\n'.format( oot_deltdur )\\n header_str += '# durations before and after the {0} itself for sampling the baseline flux:\\\\n'.format( sigtype_lower_singular )\\n header_str += '# - \\\\'all_in_darktime\\\\' if the sun elevation is within the dark range for the entire\\\\n'\\n header_str += '# duration of the observations\\\\n'\\n header_str += '# - \\\\'dark_to_twilight\\\\' if the sun elevation is within the dark range at the start\\\\n'\\n header_str += '# of the observations and within the twilight range at the end of the observations\\\\n'\\n header_str += '# - \\\\'twilight_to_dark\\\\' if the sun elevation is within the twilight range at the \\\\n'\\n header_str += '# start of the observations and within the dark range at the end of the observations\\\\n'\\n header_str += '# - \\\\'start_at_dusk\\\\' if the sun elevation is within the twilight range at the start\\\\n'\\n header_str += '# of the observations\\\\n'\\n header_str += '# - \\\\'end_at_dawn\\\\' if the sun elevation is within the twilight range at the end of\\\\n'\\n header_str += '# the observations\\\\n'\\n if oot_deltdur>0:\\n header_str += '# - \\\\'partial_oot\\\\' if the sun elevation is above the maximum acceptable value at some\\\\n'\\n header_str += '# time during either the pre- or post-{0} baseline flux observations\\\\n'.format( sigtype_lower_singular )\\n header_str += '# - \\\\'miss_ingress\\\\' if the sun elevation is above the maximum acceptable value at\\\\n'\\n header_str += '# ingress but below this value at egress\\\\n'\\n header_str += '# - \\\\'miss_ingress\\\\' if the sun elevation is below the maximum acceptable value at\\\\n'\\n header_str += '# ingress but above this value at egress\\\\n'\\n header_str += '# - \\\\'only_middle\\\\' if the sun elevation is above the maximum acceptable value at\\\\n'\\n header_str += '# value at both ingress and egress, but descends below this value at some point\\\\n'\\n header_str += '# during the {0}\\\\n#\\\\n'.format( sigtype_lower_singular )\\n ofile_bp.write( header_str )\\n ofile_ch.write( header_str )\\n\\n # Create the observatory and timezone objects:\\n obs, tz = setup_observatory( observatory )\\n if ( obs==None ) and ( tz==None ):\\n ofile_bp.close()\\n os.remove( ofilename_byplanet )\\n return None\\n\\n # Generate instances of the Sun and Moon:\\n sun = ephem.Sun()\\n moon = ephem.Moon()\\n\\n # Convert start and end dates of observing period\\n # to pyephem float objects:\\n date_start = ephem.Date( date_start )\\n date_end = ephem.Date( date_end )\\n\\n # Go through the targets one-at-a-time, checking for visible transits:\\n mjds = []\\n date_floats = []\\n outstrs_ch = []\\n print '\\\\nCalculating visible transits for:'\\n for i in range( ntargets ):\\n\\n print ' ... target {0:d} of {1:d} --> {2} '\\\\\\n .format( i+1, ntargets, targets[i] )\\n first_i = True\\n per_i = pers[i]\\n dur_i = durs[i] / 24.\\n \\n # Initiate the ephem object for the target:\\n target_i = ephem.readdb( dbs[i] )\\n\\n # Check to see if the current target's signal has been ranked,\\n # and if it has, make sure that it was ranked highly enough,\\n # otherwise we skip to the next target straight away:\\n if sigtype=='transits':\\n nranked = len( targets_tr )\\n for j in range( nranked ):\\n if targets_tr[j]==target_i.name:\\n rank_i = int( ranks_tr[j] )\\n if ( max_rank!=None ):\\n if ( max_rank != -1 ) * ( rank_i>max_rank ):\\n include = False\\n else:\\n include = True\\n unranked = False\\n break\\n else:\\n if j==nranked-1:\\n unranked = True\\n elif sigtype=='eclipses':\\n nranked = len( targets_ec )\\n for j in range( nranked ):\\n if targets_ec[j]==target_i.name:\\n rank_i = int( ranks_ec[j] )\\n if ( max_rank!=None ):\\n if ( max_rank!=-1 ) * ( rank_i>max_rank ):\\n include = False\\n else:\\n include = True\\n unranked = False\\n break\\n else:\\n if j==nranked-1:\\n unranked = True\\n # See if we want to skip the current target for some reason:\\n if unranked==True:\\n if exclude_unranked==True:\\n continue\\n else:\\n if include==False:\\n continue\\n \\n # Convert the JD transit time to a pyephem date:\\n ttr_i = jd2pyephemdate( ttrs[i] )\\n\\n # If we're wanting eclipse information, approximate the eclipse\\n # time by subtracting half a period (the more eccentric the orbit,\\n # the worse this approximation will be):\\n if sigtype=='eclipses':\\n ttr_i -= 0.5 * per_i\\n\\n # Find the transit with mid-time occurring immediately\\n # before the observing run:\\n if ttr_i>date_start:\\n while ttr_i>date_start:\\n ttr_i -= per_i\\n else:\\n while ttr_i<date_start:\\n ttr_i += per_i\\n ttr_i -= per_i\\n\\n # If it's not even partially visible, start at the next transit: \\n if ( ttr_i + 0.5*dur_i )<date_start:\\n ttr_i += per_i\\n\\n # Now that we have a starting time, loop over successive transits\\n # until we reach the one with mid-time immediately before the end\\n # of the observing window:\\n while ttr_i<date_end:\\n\\n # Set the UT date of the current transit within the\\n # observatory object:\\n obs.date = ttr_i\\n\\n # Update the target ephemerides and calculate its\\n # elevation in the sky:\\n target_i.compute( obs )\\n target_i_alt_midtime = np.rad2deg( float( target_i.alt ) )\\n # If the target is not above the minimum elevation, bump up to\\n # the next transit and go back to the top of the loop:\\n if target_i_alt_midtime<target_elev_min:\\n ttr_i += per_i\\n continue\\n\\n # Given the altitude, calculate the approximate airmass:\\n zenith_i_midtime = 90 - target_i_alt_midtime\\n airmass = calc_airmass( zenith_i_midtime )\\n \\n # Update the Sun and Moon ephemerides and work out\\n # their elevations with respect to the horizon:\\n sun.compute( obs )\\n sun_alt_midtime = np.rad2deg( float( sun.alt ) )\\n moon.compute( obs )\\n moon_alt_midtime = np.rad2deg( float( moon.alt ) )\\n # If the Sun is above the maximum elevation limit, bump up to\\n # the next transit and go back to the top of the loop:\\n if sun_alt_midtime>sun_alt_max:\\n ttr_i += per_i\\n continue\\n # Get the Moon phase as a percentage of the illuminated face:\\n moonphase = '{0:d}'.format( int( np.round( moon.phase ) ) )\\n # Get the target-Moon angular separation:\\n moondist = int( np.round( np.rad2deg( ephem.separation( ( target_i.az, target_i.alt ), \\\\\\n ( moon.az, moon.alt ) ) ) ) )\\n moondist = '{0:d}'.format( moondist )\\n\\n # If we make it to here we will consider the transit potentially\\n # observable. Next, evaluate whether or not its detectability rank\\n # meets our requirements:\\n if first_i==True:\\n\\n # Write the header for the current object to the output file:\\n nchar = max( [ len( colheadingsa_bp ), len( colheadingsb_bp ) ] )\\n ofile_bp.write( '\\\\n\\\\n{0}\\\\n#\\\\n'.format( '#'*( nchar_bp ) ) )\\n if unranked==True:\\n if sigtype=='transits':\\n header_str = '# {0} --> not enough information to rank primary transit signal \\\\n#\\\\n'\\\\\\n .format( targets[i] )\\n else:\\n header_str = '# {0} --> not enough information to rank secondary eclipse signal \\\\n#\\\\n'\\\\\\n .format( targets[i] )\\n else:\\n if sigtype=='transits':\\n header_str = '# {0} --> primary transit signal ranked {1} out of {2} \\\\n#\\\\n'\\\\\\n .format( targets[i], str( rank_i ), str( nranked ) )\\n else:\\n header_str = '# {0} --> secondary eclipse signal ranked {1} out of {2} \\\\n#\\\\n'\\\\\\n .format( targets[i], str( rank_i ), str( nranked ) )\\n header_str += '# RA (hh mm ss.s) Dec (dd mm ss.s)\\\\n'\\n ra_str = ras[i].replace( ':', ' ' )\\n dec_str = decs[i].replace( ':', ' ' )\\n header_str += '# {0} {1}\\\\n#\\\\n'.format( ra_str, dec_str )\\n header_str += colheadingsa_bp\\n header_str += colheadingsb_bp\\n\\n ofile_bp.write( header_str )\\n ofile_bp.write( '{0}{1}\\\\n'.format( '#', '-'*( nchar_bp-1 ) ) )\\n \\n first_i = False\\n \\n # Now we want to work out some more details about\\n # what kind of transit it will be.\\n\\n # Determine the Sun, Moon and target elevations\\n # at the start of the observations:\\n obs.date = ttr_i - dur_i*( 0.5 + oot_deltdur )\\n sun.compute( obs )\\n sun_alt_start = np.rad2deg( float( sun.alt ) )\\n moon.compute( obs )\\n moon_alt_start = np.rad2deg( float( moon.alt ) )\\n target_i.compute( obs )\\n target_i_alt_start = np.rad2deg( float( target_i.alt ) ) \\n\\n # Do the same for the end of the observations:\\n obs.date = ttr_i + dur_i*( 0.5 + oot_deltdur )\\n sun.compute( obs )\\n sun_alt_end = np.rad2deg( float( sun.alt ) )\\n moon.compute( obs )\\n moon_alt_end = np.rad2deg( float( moon.alt ) )\\n target_i.compute( obs )\\n target_i_alt_end = np.rad2deg( float( target_i.alt ) )\\n\\n # Determine the Sun, Moon and target elevations\\n # at ingress:\\n obs.date = ttr_i-0.5*dur_i\\n sun.compute( obs )\\n sun_alt_ingress = np.rad2deg( float( sun.alt ) )\\n moon.compute( obs )\\n moon_alt_ingress = np.rad2deg( float( moon.alt ) )\\n target_i.compute( obs )\\n target_i_alt_ingress = np.rad2deg( float( target_i.alt ) ) \\n\\n # Do the same for egress:\\n obs.date = ttr_i+0.5*dur_i\\n sun.compute( obs )\\n sun_alt_egress = np.rad2deg( float( sun.alt ) )\\n moon.compute( obs )\\n moon_alt_egress = np.rad2deg( float( moon.alt ) )\\n target_i.compute( obs )\\n target_i_alt_egress = np.rad2deg( float( target_i.alt ) )\\n\\n # First category of transits are those where the entire transit and\\n # requested out-of-transit baselines either side of ingress and egress\\n # occur while the Sun is below the maximum acceptable altitude:\\n if ( sun_alt_start<sun_alt_max )*( sun_alt_end<sun_alt_max ):\\n\\n # Case 1 = The Sun is always below our dark night time threshold:\\n if ( sun_alt_start<sun_alt_dark )*( sun_alt_end<sun_alt_dark ):\\n trtype = 'full-all_in_darktime'\\n\\n # Case 2 = The Sun remains within the twilight range for the entire transit:\\n elif ( sun_alt_start>sun_alt_dark )*( sun_alt_start<sun_alt_twil )*\\\\\\n ( sun_alt_end>sun_alt_dark )*( sun_alt_end<sun_alt_twil ):\\n trtype = 'full-all_in_twilight'\\n \\n # Case 3 = The Sun starts low enough to be classified as twilight,\\n # but not low enough to be classified dark, and by the end of the\\n # transit has descended low enough to be considered dark: \\n elif ( sun_alt_start<sun_alt_twil )*( sun_alt_start>sun_alt_dark )* \\\\\\n ( sun_alt_end<sun_alt_dark ):\\n trtype = 'full-twilight_to_dark'\\n\\n # Case 4 = The Sun starts low enough to be considered at dark, but\\n # by the end of the transit it has ascended enough that it is no\\n # longer considered dark but twilight instead:\\n elif ( sun_alt_end<sun_alt_twil )*( sun_alt_end>sun_alt_dark)* \\\\\\n ( sun_alt_start<sun_alt_dark ):\\n trtype = 'full-dark_to_twilight'\\n\\n # Case 5 = At the start of the transit, the Sun is at an altitude\\n # somewhere between its maximum acceptable value and the twilight\\n # value, so we say the transit starts at 'dusk':\\n elif ( sun_alt_start<sun_alt_max )*( sun_alt_start>sun_alt_twil ):\\n trtype = 'full-start_at_dusk'\\n\\n # Case 6 = At the end of the transit, the Sun is at an altitude\\n # somewhere between its maximum acceptable value and the twilight\\n # value, so we say the transit ends at 'dawn':\\n elif ( sun_alt_end<sun_alt_max )*( sun_alt_end>sun_alt_twil ):\\n trtype = 'full-end_at_dawn'\\n\\n # Don't think there should be any other cases?\\n else:\\n pdb.set_trace() #if this happens, need to work out what the Case should be\\n print 'backstop'\\n pdb.set_trace()\\n \\n # The following variations describe cases where we do not get the\\n # full transit plus out-of-transit baseline:\\n\\n elif ( sun_alt_ingress<sun_alt_max )*( sun_alt_egress<sun_alt_max ):\\n\\n # Case 6 = The sky darkness was within our acceptable range for the\\n # full duration of the transit but we don't get the full out-of-transit\\n # baseline either before or after the transit within this range:\\n trtype = 'full-partial_oot'\\n\\n elif ( sun_alt_ingress>sun_alt_max )*( sun_alt_end<sun_alt_max ):\\n\\n # Case 7 = At the start of the transit, the Sun was above our minimum\\n # acceptable altitude, but by the time of mid-transit it had descended\\n # below this level and remained acceptable until the end of the transit:\\n trtype = 'partial-miss_ingress'\\n\\n elif ( sun_alt_start<sun_alt_max )*( sun_alt_egress>sun_alt_max ):\\n\\n # Case 8 = At the start of the transit, the Sun was above our minimum\\n # acceptable altitude, but by the time of mid-transit it had descended\\n # below this level and remained acceptable until the end of the transit:\\n trtype = 'partial-miss_egress'\\n\\n else:\\n # Case 9 = In the case of a transit lasting longer than the entire night,\\n # the Sun altitude meets the minimum requirement at the transit mid-time,\\n # but it's at an unacceptable altitude for both the start and end:\\n trtype = 'partial-only_middle'\\n\\n # Now work out if the Moon is above or below the horizon:\\n if ( moon_alt_start<moon_alt_set )*( moon_alt_end<moon_alt_set ):\\n moonpos = 'moon-down'\\n moonphase = '-'\\n moondist = '-'\\n else:\\n if ( moon_alt_start>0 )*( moon_alt_end>0 ):\\n moonpos = 'moon-up'\\n elif ( moon_alt_start<0 )*( moon_alt_end>moon_alt_set ):\\n moonpos = 'moon-rising'\\n elif ( moon_alt_start>moon_alt_set )*( moon_alt_end<0 ):\\n moonpos = 'moon-setting'\\n else:\\n pdb.set_trace() #this shouldn't happen\\n\\n # Determine the start and end times of transit in UT: \\n utc_tstart_tuple = ephem.date( ttr_i-0.5*dur_i ).tuple()\\n utc_tstart_dt = datetime.datetime( int(utc_tstart_tuple[0]), \\\\\\n int(utc_tstart_tuple[1]), \\\\\\n int(utc_tstart_tuple[2]), \\\\\\n int(utc_tstart_tuple[3]), \\\\\\n int(utc_tstart_tuple[4]), \\\\\\n int(utc_tstart_tuple[5]), \\\\\\n tzinfo=pytz.utc )\\n\\n utc_tend_tuple = ephem.date( ttr_i+0.5*dur_i ).tuple()\\n utc_tend_dt = datetime.datetime( int(utc_tend_tuple[0]), \\\\\\n int(utc_tend_tuple[1]), \\\\\\n int(utc_tend_tuple[2]), \\\\\\n int(utc_tend_tuple[3]), \\\\\\n int(utc_tend_tuple[4]), \\\\\\n int(utc_tend_tuple[5]), \\\\\\n tzinfo=pytz.utc )\\n \\n # Express the transit mid-time as a Modified Julian Date:\\n mjd = ephem.julian_date( ttr_i ) - 2400000.5\\n\\n # Prepare and write output line to file:\\n outstr_bp = make_outstr_bp( mjd, utc_tstart_dt, utc_tend_dt, zenith_i_midtime, \\\\\\n airmass, trtype, moonpos, moondist, moonphase )\\n ofile_bp.write( outstr_bp )\\n\\n # Also save the lines to be written to other chronological output file later:\\n mjds += [ mjd ]\\n date_floats += [ ephem.Date( utc_tstart_dt )+1.0 ] # number of days since midday on 1 Jan 1900 \\n\\n outstr_ch = make_outstr_ch( targets[i], mjd, utc_tstart_dt, utc_tend_dt, zenith_i_midtime, \\\\\\n airmass, trtype, moonpos, moondist, moonphase )\\n outstrs_ch += [ outstr_ch ]\\n\\n # Tick over to the next transit for the next loop:\\n ttr_i += per_i\\n\\n # Now that we've identified all of the transits, sort them into\\n # chronological order and write this information to output:\\n header_str = '#\\\\n#\\\\n{0}\\\\n'.format( '#'*nchar_ch )\\n header_str += colheadingsa_ch\\n header_str += colheadingsb_ch\\n ofile_ch.write( header_str )\\n ofile_ch.write( '{0}{1}\\\\n'.format( '#', '-'*( nchar_ch-1 ) ) )\\n mjds = np.array( mjds )\\n date_floats = np.array( date_floats )\\n ixs = np.argsort( mjds )\\n for i in range( len( mjds ) ):\\n j = ixs[i]\\n df = np.floor( date_floats[j] )\\n if i!=0:\\n df_prev = np.floor( date_floats[ixs[i-1]] )\\n if df-df_prev>=1.0:\\n ofile_ch.write( '#{0}\\\\n'.format( '-'*( nchar_ch-1 ) ) )\\n ofile_ch.write( outstrs_ch[j] )\\n ofile_ch.write( '{0}{1}\\\\n'.format( '#', '-'*( nchar-1 ) ) )\\n\\n # Save the output files and finish:\\n ofile_bp.close()\\n ofile_ch.close()\\n print '\\\\nSaved output in:'\\n print ' %s' % ofilename_byplanet\\n print ' %s' % ofilename_chronolog\\n\\n return ofilename_byplanet, ofilename_chronolog\",\n \"def getInputData():\\n\\n # Get current allocations.\\n current_alloc_dict = DataIO.getCurrentData('data/current_allocations.csv')\\n\\n # Get tickers and expense ratios.\\n ticker_list, expense_ratio_dict = DataIO.getTickerList(\\n 'data/tickers_expenses.csv')\\n\\n # Get raw data.\\n raw_data = DataIO.getRawData(ticker_list)\\n\\n # Create all stock objects.\\n stock_dict = {}\\n for ticker in raw_data.keys():\\n stock_dict[ticker] = Stock(\\n raw_data[ticker], ticker, expense_ratio_dict[ticker])\\n\\n if not len(stock_dict.keys()):\\n raise ValueError('No keys found.')\\n\\n # Create stock database.\\n stock_db = StockDatabase(stock_dict)\\n\\n # Create current portfolio.\\n current_portfolio = Portfolio(\\n stock_db, percent_allocations_dict=current_alloc_dict)\\n\\n return current_portfolio, stock_db\",\n \"def poker(project):\\r\\n total_stories = len(project.unestimated_stories())\\r\\n for idx, story in enumerate(project.unestimated_stories()):\\r\\n clear()\\r\\n rows, cols = _get_column_dimensions()\\r\\n print \\\"{} PLANNING POKER SESSION [{}]\\\".format(project.name.upper(), bold(\\\"{}/{} Stories Estimated\\\".format(idx+1, total_stories)))\\r\\n print \\\"-\\\" * cols\\r\\n pretty_print_story(story)\\r\\n prompt_estimation(project, story)\\r\\n else:\\r\\n print \\\"KaBoom!!! Nice Work Team\\\"\",\n \"def execute(filters=None):\\n\\tdata = []\\n\\tif filters and validate(filters):\\n\\t\\tfn = 'temporary_against_account_number'\\n\\t\\tfilters[fn] = frappe.get_value('DATEV Settings', filters.get('company'), fn)\\n\\t\\tdata = get_transactions(filters, as_dict=0)\\n\\n\\treturn COLUMNS, data\",\n \"def process(self):\\n\\n log.info(\\\"Feature Engineering of pred_analys_record_personal_access data of school: \\\" + self.school_kind.value)\\n log.debug(\\\"QuadrimestersFeatureEngineering.process()\\\")\\n\\n global pr_plan_subject_call, pr_scholarship_per_year\\n\\n analys_record_personal_access = self.input_dfs[0]\\n pr_plan_subject_call = self.input_dfs[1]\\n pr_scholarship_per_year = self.input_dfs[2]\\n\\n cols_before = len(self.input_dfs[0].columns)\\n col_list_before = self.input_dfs[0].columns\\n\\n analys_record_personal_access[keys.CUM_PASS_RATIO_KEY] = analys_record_personal_access.apply(\\n lambda func: get_cum_pass_ratio(func, course=self.course, quadrimester=self.quadrimester), axis=1\\n )\\n analys_record_personal_access[keys.SCHOLARSHIP_KEY] = analys_record_personal_access.apply(\\n lambda func: get_scholarship(func, course=self.course), axis=1\\n )\\n analys_record_personal_access[keys.CUM_ABSENT_RATIO_KEY] = analys_record_personal_access.apply(\\n lambda func: get_cum_absent_ratio(func, course=self.course, quadrimester=self.quadrimester), axis=1\\n )\\n analys_record_personal_access[keys.CUM_MEDIAN_KEY] = analys_record_personal_access.apply(\\n lambda func: get_cum_median(func, course=self.course, quadrimester=self.quadrimester), axis=1\\n )\\n\\n if self.course > 1:\\n analys_record_personal_access[keys.CUM_MORE_1ST_CALL_RATIO_KEY] = analys_record_personal_access.apply(\\n lambda func: get_cum_more_1st_call_ratio(func, course=self.course, quadrimester=self.quadrimester),\\n axis=1\\n )\\n cols_after = len(self.input_dfs[0].columns)\\n col_list_after = self.input_dfs[0].columns\\n self.changes[\\\"add new columns with information of quadrimester\\\"] = cols_after - cols_before\\n log.info(\\\"new columns are :\\\" + str(list(set(col_list_after) - set(col_list_before))))\\n log.info(\\\"final columns are: \\\" + str(col_list_after))\\n\\n rows_before = len(analys_record_personal_access.index)\\n analys_record_personal_access = analys_record_personal_access[analys_record_personal_access\\n [keys.CUM_PASS_RATIO_KEY] != -1]\\n rows_after = len(analys_record_personal_access.index)\\n\\n self.changes[\\\"removes people who have dropped out in this quadrimester\\\"] = rows_before - rows_after\\n self.changes[\\\"number of final rows\\\"] = rows_after\\n\\n self.output_df = analys_record_personal_access\",\n \"def init_params():\\n p = {}\\n \\n # p['rootFolder'] = 'C:/Users/Umberto Gostoli/SPHSU/Social Care Model II'\\n # p['rootFolder'] = 'N:/Social Care Model Paper III'\\n \\n p['noPolicySim'] = False\\n p['multiprocessing'] = True\\n p['numberProcessors'] = 9\\n p['numRepeats'] = 3\\n \\n p['startYear'] = 1860\\n p['endYear'] = 2040\\n p['thePresent'] = 2012\\n p['statsCollectFrom'] = 1990\\n p['regressionCollectFrom'] = 1960 \\n p['implementPoliciesFromYear'] = 2020\\n p['yearOutcome'] = 2015\\n \\n p['favouriteSeed'] = 123\\n p['loadFromFile'] = False\\n p['verboseDebugging'] = False\\n p['singleRunGraphs'] = False\\n p['saveChecks'] = True\\n p['getCheckVariablesAtYear'] = 2015\\n # To change through command-line arguments\\n\\n p['numberPolicyParameters'] = 2\\n p['valuesPerParam'] = 1\\n p['numberScenarios'] = 3\\n \\n ############ Policy Parameters #######################\\n p['incomeCareParam'] = 0.0005 #[0.00025 - 0.001]\\n p['taxBreakRate'] = 0.0\\n p['ageOfRetirement'] = 65\\n p['socialSupportLevel'] = 5\\n # p['educationCosts']\\n #############################################################\\n p['socialCareCreditShare'] = 0.0\\n p['maxWtWChildAge'] = 5\\n # The basics: starting population and year, etc.\\n \\n p['discountingFactor'] = 0.03\\n \\n \\n p['initialPop'] = 600 \\n \\n p['minStartAge'] = 24\\n p['maxStartAge'] = 45\\n p['numberClasses'] = 5\\n p['socialClasses'] = ['unskilled', 'skilled', 'lower', 'middle', 'upper']\\n p['initialClassShares'] = [0.2, 0.25, 0.3, 0.2, 0.05]\\n p['initialUnemployment'] = [0.25, 0.2, 0.15, 0.1, 0.1]\\n p['unemploymentAgeBandParam'] = 0.3\\n \\n # doDeath function parameters\\n p['mortalityBias'] = 0.85 # After 1950\\n p['careNeedBias'] = 0.9\\n p['unmetCareNeedBias'] = 0.5\\n p['baseDieProb'] = 0.0001\\n p['babyDieProb'] = 0.005\\n p['maleAgeScaling'] = 14.0\\n p['maleAgeDieProb'] = 0.00021\\n p['femaleAgeScaling'] = 15.5\\n p['femaleAgeDieProb'] = 0.00019\\n \\n p['orphansRelocationParam'] = 0.5\\n \\n # doBirths function parameters\\n p['minPregnancyAge'] = 17\\n p['maxPregnancyAge'] = 42\\n p['growingPopBirthProb'] = 0.215\\n p['fertilityCorrector'] = 1.0\\n p['fertilityBias'] = 0.9\\n \\n # careTransitions function parameters\\n p['zeroYearCare'] = 80.0\\n p['childcareDecreaseRate'] = 0.25\\n p['personCareProb'] = 0.0008\\n p['maleAgeCareScaling'] = 18.0 # p['maleAgeCareProb'] = 0.0008\\n p['femaleAgeCareScaling'] = 19.0 # p['femaleAgeCareProb'] = 0.0008\\n p['baseCareProb'] = 0.0002\\n p['careBias'] = 0.9\\n p['careTransitionRate'] = 0.7\\n\\n p['unmetNeedExponent'] = 1.0 # 0.005 #[0.005 - 0.02]\\n \\n p['numCareLevels'] = 5\\n p['careLevelNames'] = ['none','low','moderate','substantial','critical']\\n p['careDemandInHours'] = [ 0.0, 8.0, 16.0, 32.0, 80.0 ]\\n p['quantumCare'] = 4.0\\n \\n # careSupplies getCare and probSuppliers function parameters\\n \\n ######## Key parameter 1 ##############\\n \\n \\n p['weeklyHours'] = 40.0\\n \\n \\n p['priceChildCare'] = 0.76 # 6 \\n p['schoolAge'] = 5\\n p['maxFormalChildcareHours'] = 48\\n p['schoolHours'] = 30\\n p['freeChildcareHours'] = 15\\n p['workingParentsFreeChildcareHours'] = 30\\n p['minAgeStartChildCareSupport'] = 3\\n p['minAgeStartChildCareSupportByIncome'] = 2\\n p['maxHouseholdIncomeChildCareSupport'] = 40 # 320\\n \\n ######## Key parameter 2 ##############\\n # 5: No public supply \\n \\n p['retiredHours'] = [48.0, 36.0, 20.0, 10.0] # 60.0\\n p['studentHours'] = [24.0, 16.0, 8.0, 4.0]\\n p['teenAgersHours'] = [16.0, 0.0, 0.0, 0.0]\\n p['unemployedHours'] = [32.0, 24.0, 16.0, 8.0]\\n p['employedHours'] = [28.0, 20.0, 12.0, 8.0]\\n p['formalCareDiscountFactor'] = 0.5\\n \\n p['socialNetworkDistances'] = [0.0, 1.0, 2.0, 1.0, 2.0, 2.0, 3.0, 3.0]\\n p['networkDistanceParam'] = 2.0\\n p['socialCareWeightBias'] = 1.0\\n p['unmetCareNeedDiscountParam'] = 0.5\\n p['shareUnmetNeedDiscountParam'] = 0.5\\n # p['pastShareUnmetNeedWeight'] = 0.5\\n \\n \\n \\n p['networkSizeParam'] = 10.0 # 1.0\\n \\n p['careSupplyBias'] = 0.5\\n p['careIncomeParam'] = 0.001\\n \\n # Hospitalization Costs\\n p['qalyBeta'] = 0.18\\n p['qalyAlpha'] = 1.5\\n p['qalyDiscountRate'] = 0.035\\n p['qalyIndexes'] = [1.0, 0.8, 0.6, 0.4, 0.2]\\n p['unmetCareHealthParam'] = 0.1\\n p['hospitalizationParam'] = 0.5\\n p['needLevelParam'] = 2.0\\n p['unmetSocialCareParam'] = 2.0\\n p['costHospitalizationPerDay'] = 400\\n \\n # ageTransitions, enterWorkForce and marketWage functions parameters\\n p['ageTeenagers'] = 12\\n p['minWorkingAge'] = 16\\n \\n ######## Key parameter 3 ##############\\n \\n p['careBankingSchemeOn'] = False\\n p['socialCareBankingAge'] = 65\\n \\n p['absoluteCreditQuantity'] = False\\n p['quantityYearlyIncrease'] = 0.0\\n p['socialCareCreditQuantity'] = 0\\n p['kinshipNetworkCarePropension'] = 0.5\\n p['volunteersCarePropensionCoefficient'] = 0.01\\n p['pensionContributionRate'] = 0.05\\n \\n p['hillHealthLevelThreshold'] = 3\\n p['seriouslyHillSupportRate'] = 0.5\\n \\n ### Prices ####\\n p['pricePublicSocialCare'] = 20.0 # [2.55] # 20\\n p['priceSocialCare'] = 17.0 # [2.29] # 18\\n p['taxBrackets'] = [663, 228, 0] # [28.16, 110.23] # [221, 865]\\n p['taxBandsNumber'] = 3\\n p['bandsTaxationRates'] = [0.4, 0.2, 0.0] # [0.0, 0.2, 0.4]\\n # Tax Break Policy\\n\\n \\n p['pensionWage'] = [5.0, 7.0, 10.0, 13.0, 18.0] # [0.64, 0.89, 1.27, 1.66, 2.29] # \\n p['incomeInitialLevels'] = [5.0, 7.0, 9.0, 11.0, 14.0] #[0.64, 0.89, 1.15, 1.40, 1.78] # \\n p['incomeFinalLevels'] = [10.0, 15.0, 22.0, 33.0, 50.0] #[1.27, 1.91, 2.80, 4.21, 6.37] # \\n p['educationCosts'] = [0.0, 100.0, 150.0, 200.0] #[0.0, 12.74, 19.12, 25.49] # \\n \\n # Priced growth #####\\n p['wageGrowthRate'] = 1.0 # 1.01338 # \\n\\n p['incomeGrowthRate'] = [0.4, 0.35, 0.35, 0.3, 0.25]\\n \\n # SES inter-generational mobility parameters\\n p['leaveHomeStudentsProb'] = 0.5\\n \\n p['eduWageSensitivity'] = 0.2 # 0.5\\n p['eduRankSensitivity'] = 3.0 # 5.0\\n p['costantIncomeParam'] = 80.0 # 20.0\\n p['costantEduParam'] = 10.0 # 10.0\\n p['careEducationParam'] = 0.005 # 0.04\\n \\n \\n \\n # p['incEduExp'] = 0.25\\n p['educationLevels'] = ['GCSE', 'A-Level', 'HND', 'Degree', 'Higher Degree']\\n p['workingAge'] = [16, 18, 20, 22, 24]\\n \\n # doDivorce function parameters\\n p['basicDivorceRate'] = 0.06\\n p['variableDivorce'] = 0.06\\n p['divorceModifierByDecade'] = [ 0.0, 1.0, 0.9, 0.5, 0.4, 0.2, 0.1, 0.03, 0.01, 0.001, 0.001, 0.001, 0.0, 0.0, 0.0, 0.0, 0.0 ]\\n p['divorceBias'] = 1.0\\n \\n # doMarriages function parameters\\n p['deltageProb'] = [0.0, 0.1, 0.25, 0.4, 0.2, 0.05]\\n p['incomeMarriageParam'] = 0.025\\n p['studentFactorParam'] = 0.5\\n ######## Key parameter 4 ##############\\n p['betaGeoExp'] = 2.0 #[1.0 - 4.0]\\n \\n p['betaSocExp'] = 2.0\\n p['rankGenderBias'] = 0.5\\n p['basicMaleMarriageProb'] = 0.9\\n p['maleMarriageModifierByDecade'] = [ 0.0, 0.16, 0.5, 1.0, 0.8, 0.7, 0.66, 0.5, 0.4, 0.2, 0.1, 0.05, 0.01, 0.0, 0.0, 0.0, 0.0 ]\\n \\n # jobMarket, updateWork and unemploymentRate functions parameters\\n p['unemploymentClassBias'] = 0.75\\n p['unemploymentAgeBias'] = [1.0, 0.55, 0.35, 0.25, 0.2, 0.2]\\n p['numberAgeBands'] = 6\\n p['jobMobilitySlope'] = 0.004\\n p['jobMobilityIntercept'] = 0.05\\n p['ageBiasParam'] = [7.0, 3.0, 1.0, 0.5, 0.35, 0.15]\\n p['deltaIncomeExp'] = 0.05\\n p['unemployedCareBurdernParam'] = 0.025\\n # Potential key parameter\\n p['relocationCareLossExp'] = 1.0 # 40.0 # \\n p['incomeSocialCostRelativeWeight'] = 0.5\\n \\n p['firingParam'] = 0.2\\n p['wageVar'] = 0.06\\n p['workDiscountingTime'] = 0.75 # 0.8\\n p['sizeWeightParam'] = 0.7\\n p['minClassWeightParam'] = 1.0\\n p['incomeDiscountingExponent'] = 4.0\\n p['discountingMultiplier'] = 2.0\\n #p['incomeDiscountingParam'] = 2.0\\n \\n # relocationPensioners function parameters\\n p['agingParentsMoveInWithKids'] = 0.1\\n p['variableMoveBack'] = 0.1\\n p['retiredRelocationParam'] = 0.001 # 0.005\\n \\n # houseMap function parameters\\n p['geoDistanceSensitivityParam'] = 2.0\\n p['socDistanceSensitivityParam'] = 2.0\\n p['classAffinityWeight'] = 4.0\\n p['distanceSensitivityParam'] = 0.5\\n \\n # relocationProb function parameters\\n p['baseRelocatingProb'] = 0.05\\n p['relocationParameter'] = 1.0 \\n p['apprenticesRelocationProb'] = 0.5\\n #p['expReloc'] = 1.0\\n \\n # computeRelocationCost and relocation Propensity functions parameters\\n p['yearsInTownSensitivityParam'] = 0.5\\n \\n ######## Key parameter 5 ##############\\n p['relocationCostParam'] = 0.5 # 1.0 \\n \\n ######## Key parameter 6 ##############\\n p['propensityRelocationParam'] = 2.0 # 2.0 \\n p['denRelocationWeight'] = 0.5\\n \\n \\n ## Description of the map, towns, and houses\\n p['mapGridXDimension'] = 8\\n p['mapGridYDimension'] = 12 \\n p['townGridDimension'] = 70\\n p['cdfHouseClasses'] = [ 0.6, 0.9, 5.0 ]\\n p['ukMap'] = [[ 0.0, 0.1, 0.2, 0.1, 0.0, 0.0, 0.0, 0.0 ],\\n [ 0.1, 0.1, 0.2, 0.2, 0.3, 0.0, 0.0, 0.0 ],\\n [ 0.0, 0.2, 0.2, 0.3, 0.0, 0.0, 0.0, 0.0 ],\\n [ 0.0, 0.2, 1.0, 0.5, 0.0, 0.0, 0.0, 0.0 ],\\n [ 0.4, 0.0, 0.2, 0.2, 0.4, 0.0, 0.0, 0.0 ],\\n [ 0.6, 0.0, 0.0, 0.3, 0.8, 0.2, 0.0, 0.0 ],\\n [ 0.0, 0.0, 0.0, 0.6, 0.8, 0.4, 0.0, 0.0 ],\\n [ 0.0, 0.0, 0.2, 1.0, 0.8, 0.6, 0.1, 0.0 ],\\n [ 0.0, 0.0, 0.1, 0.2, 1.0, 0.6, 0.3, 0.4 ],\\n [ 0.0, 0.0, 0.5, 0.7, 0.5, 1.0, 1.0, 0.0 ],\\n [ 0.0, 0.0, 0.2, 0.4, 0.6, 1.0, 1.0, 0.0 ],\\n [ 0.0, 0.2, 0.3, 0.0, 0.0, 0.0, 0.0, 0.0 ]]\\n p['ukClassBias'] = [[ 0.0, -0.05, -0.05, -0.05, 0.0, 0.0, 0.0, 0.0 ],\\n [ -0.05, -0.05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ],\\n [ 0.0, -0.05, -0.05, 0.0, 0.0, 0.0, 0.0, 0.0 ],\\n [ 0.0, -0.05, -0.05, 0.05, 0.0, 0.0, 0.0, 0.0 ],\\n [ -0.05, 0.0, -0.05, -0.05, 0.0, 0.0, 0.0, 0.0 ],\\n [ -0.05, 0.0, 0.0, -0.05, -0.05, -0.05, 0.0, 0.0 ],\\n [ 0.0, 0.0, 0.0, -0.05, -0.05, -0.05, 0.0, 0.0 ],\\n [ 0.0, 0.0, -0.05, -0.05, 0.0, 0.0, 0.0, 0.0 ],\\n [ 0.0, 0.0, -0.05, 0.0, -0.05, 0.0, 0.0, 0.0 ],\\n [ 0.0, 0.0, 0.0, -0.05, 0.0, 0.2, 0.15, 0.0 ],\\n [ 0.0, 0.0, 0.0, 0.0, 0.1, 0.2, 0.15, 0.0 ],\\n [ 0.0, 0.0, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0 ] ]\\n p['mapDensityModifier'] = 0.6\\n # p['numHouseClasses'] = 3\\n # p['houseClasses'] = ['small','medium','large']\\n \\n ## Graphical interface details\\n p['interactiveGraphics'] = False #True\\n p['delayTime'] = 0.0\\n p['screenWidth'] = 1300\\n p['screenHeight'] = 700\\n p['bgColour'] = 'black'\\n p['mainFont'] = 'Helvetica 18'\\n p['fontColour'] = 'white'\\n p['dateX'] = 70\\n p['dateY'] = 20\\n p['popX'] = 70\\n p['popY'] = 50\\n p['pixelsInPopPyramid'] = 2000\\n p['num5YearAgeClasses'] = 28\\n p['careLevelColour'] = ['blue','green','yellow','orange','red']\\n p['houseSizeColour'] = ['brown','purple','yellow']\\n p['pixelsPerTown'] = 56\\n p['maxTextUpdateList'] = 22\\n \\n # p['eduEduSensitivity'] = 0.5\\n # p['mortalityBias'] = [1.0, 0.92, 0.84, 0.76, 0.68]\\n # p['fertilityBias'] = [1.0, 0.92, 0.84, 0.76, 0.68]\\n # p['divorceBias'] = [2.0, 1.5, 1.0, 0.75, 0.5]\\n\\n ## Transitions to care statistics\\n \\n ## Availability of care statistics\\n \\n #p['childHours'] = 5.0\\n # p['employedHours'] = 12.0\\n #p['homeAdultHours'] = 30.0\\n #p['workingAdultHours'] = 25.0\\n #p['maxEmployedHours'] = 60.0\\n \\n #p['lowCareHandicap'] = 0.5\\n #p['hourlyCostOfCare'] = 20.0\\n \\n ## Fertility statistics\\n \\n # p['steadyPopBirthProb'] = 0.13\\n # p['transitionYear'] = 1965\\n \\n ## Class and employment statistics\\n # p['numClasses'] = 5\\n # p['occupationClasses'] = ['lower','intermediate','higher']\\n # p['cdfOccupationClasses'] = [ 0.6, 0.9, 1.0 ]\\n\\n ## Age transition statistics\\n # p['ageOfAdulthood'] = 17\\n \\n ## Marriage function parameters\\n \\n # p['basicFemaleMarriageProb'] = 0.25\\n # p['femaleMarriageModifierByDecade'] = [ 0.0, 0.5, 1.0, 1.0, 1.0, 0.6, 0.5, 0.4, 0.1, 0.01, 0.01, 0.0, 0.0, 0.0, 0.0, 0.0 ]\\n # p['femaleMarriageProb'] = [0.01, 0.15, 0.3, 0.2, 0.1, 0.1, 0.06, 0.05, 0.02, 0.01, 0.01, 0.005]\\n # p['maleMarriageProb'] = [0.005, 0.08, 0.25, 0.25, 0.15, 0.1, 0.07, 0.05, 0.03, 0.02, 0.01, 0.005]\\n \\n ## Leaving home and moving around statistics\\n # p['probApartWillMoveTogether'] = 0.3\\n # p['coupleMovesToExistingHousehold'] = 0.3\\n # p['basicProbAdultMoveOut'] = 0.22\\n # p['probAdultMoveOutModifierByDecade'] = [ 0.0, 0.2, 1.0, 0.6, 0.3, 0.15, 0.03, 0.03, 0.01, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]\\n # p['basicProbSingleMove'] = 0.05\\n # p['probSingleMoveModifierByDecade'] = [ 0.0, 1.0, 1.0, 0.8, 0.4, 0.06, 0.04, 0.02, 0.02, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]\\n # p['basicProbFamilyMove'] = 0.03\\n # p['probFamilyMoveModifierByDecade'] = [ 0.0, 0.5, 0.8, 0.5, 0.2, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1 ]\\n\\n \\n return p\",\n \"def get_filters():\\n #initialize month and day (if time_filter = 'none' month and day are kept equal to zero)\\n month = 0\\n day = 0\\n\\n print('Hello! Let\\\\'s explore some US bikeshare data!')\\n\\n #GET CITY\\n city = input(\\\"\\\\n Would you like to see data from Chicago, New York or Washington? \\\\n\\\").lower()\\n while city not in CITY_DATA:\\n city = input('Wrong input! \\\\nWrite a city from the following list: Chicago, New York, Washington. \\\\n').lower()\\n\\n #GET TYPE OF TIME FILTER\\n time_filter = input('\\\\n Would you like to filter data by day, month, or none at all?\\\\n').lower()\\n viable_input_time = ['day','month','none']\\n\\n while time_filter not in viable_input_time:\\n time_filter = input('\\\\nWrong input! \\\\nWrite a filter type from the following list: day, month, none. \\\\n').lower()\\n #GET DAY\\n if time_filter == 'day':\\n day = input('\\\\n Which day? Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday. \\\\n').lower()\\n viable_input_day = ['monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday','sunday']\\n while day not in viable_input_day:\\n day = input('\\\\n Wrong input! Write a day from the following list Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday\\\\n').lower()\\n else:\\n #GET MONTH\\n if time_filter == 'month':\\n month = input('\\\\n Which month? January, February, March, April, May or June ?\\\\n').lower()\\n viable_input_month = ['january', 'february', 'march','april','may','june']\\n while month not in viable_input_month:\\n month = input('\\\\n Wrong input! \\\\nWrite a month from the following list: January, February, March, April, May, June\\\\n').lower()\\n\\n return city, time_filter, month, day\",\n \"def main(): \\n while True:\\n city, month, day = get_filters()\\n\\n df = generate_stats(city, month, day)\\n\\n # step through data\\n step_through = input('\\\\nWould you like to step through raw data? Type \\\"yes\\\" to step through: \\\\n')\\n if step_through.lower() == 'yes':\\n step_through_data(df)\\n\\n # restart\\n restart = input('\\\\nWould you like to restart? Type \\\"yes\\\" to restart.\\\\n')\\n if restart.lower() != 'yes':\\n break\",\n \"def get_filters():\\n \\n \\\"\\\"\\\"\\\"\\\"\\\"\\\"\\\"\\n \\n \\\"\\\"\\\"Messeges to genrate filters\\\"\\\"\\\"\\n\\tnote_messege = 'In this project, we make use of Python to explore data related to bike share systems for three major cities in the United States\\\\n'\\n welcome_messege = 'Hello! Let\\\\'s explore some US bikeshare data!\\\\n'\\n enter_city_name_messege = 'Which city would you like to filter by? Chicago, New York City or Washington? '\\n filter_definition_messege = '\\\\nWould you like to filter the data by - \\\\n1. Month\\\\n2. Day\\\\n3. Both\\\\n4. No Filter\\\\n\\\\nPlease choose the appropriate filter name.\\\\nNote: Incorrect filter name will result as \\\\'no filter selected\\\\' by the user.\\\\n'\\n enter_filter_messege = 'Desired filter (e.g: Month, Day, Both or No Filter): '\\n enter_month_name_messege = 'Enter month name (e.g: january, february, march, april, may or june): '\\n enter_day_name_messege = 'Enter day of the week (e.g: monday, tuesday, wednesday, thursday, friday, saturday, sunday): '\\n exception_messege = '\\\\nWarning! That is not a valid input.\\\\n'\\n warning_city_name_messege = '\\\\nWarning! Invalid city name. Select city name from the following cities only - Chicago, New York City or Washington.' \\n warning_month_name_messege = '\\\\nWarning! Invalid month name. Select month name from the following months only - january, february, march, april, may or june'\\n warning_day_name_messege = '\\\\nWarning! Invalid day name. Select day name from the following days only - monday, tuesday, wednesday, thursday, friday, saturday, sunday'\\n \\\"\\\"\\\"\\\"\\\"\\\"\\\"\\\"\\n \\n \\\"\\\"\\\"City, Month and Day List\\\"\\\"\\\"\\n city_list = ['chicago', 'new york city', 'washington']\\n month_list = ['january', 'february', 'march', 'april', 'may', 'june']\\n day_list = ['monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday']\\n \\\"\\\"\\\"\\\"\\\"\\\"\\\"\\\"\\n \\n\\tprint(note_messege)\\n print(welcome_messege)\\n \\n # TO DO: get user input for city (chicago, new york city, washington). HINT: Use a while loop to handle invalid inputs \\n while True:\\n try:\\n city = input(enter_city_name_messege)\\n break\\n except:\\n print(exception_messege)\\n \\n while city.lower() not in city_list:\\n while True:\\n try: \\n print(warning_city_name_messege)\\n city = input(enter_city_name_messege)\\n break\\n except:\\n print(exception_messege)\\n \\n print(filter_definition_messege)\\n while True:\\n try:\\n filter_choice = input(enter_filter_messege)\\n break\\n except:\\n print(exception_messege)\\n while True: \\n if filter_choice.lower() == 'month':\\n # TO DO: get user input for month (all, january, february, ... , june)\\n while True:\\n try:\\n month = input(enter_month_name_messege) \\n break\\n except:\\n print(exception_messege)\\n while month.lower() not in month_list:\\n while True:\\n try: \\n print(warning_month_name_messege)\\n month = input(enter_month_name_messege) \\n break\\n except:\\n print(exception_messege)\\n day = 'all'\\n break\\n \\n elif filter_choice.lower() == 'day':\\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday) \\n while True:\\n try:\\n day = input(enter_day_name_messege)\\n break\\n except:\\n print(exception_messege)\\n while day.lower() not in day_list:\\n while True:\\n try: \\n print(warning_day_name_messege)\\n day = input(enter_day_name_messege) \\n break\\n except:\\n print(exception_messege)\\n month = 'all'\\n break\\n \\n elif filter_choice.lower() == 'both':\\n # TO DO: get user input for month (all, january, february, ... , june)\\n while True:\\n try:\\n month = input(enter_month_name_messege)\\n break\\n except:\\n print(exception_messege)\\n while month.lower() not in month_list:\\n while True:\\n try: \\n print(warning_month_name_messege)\\n month = input(enter_month_name_messege) \\n break\\n except:\\n print(exception_messege)\\n # TO DO: get user input for day of week (all, monday, tuesday, ... sunday)\\n while True:\\n try:\\n day = input(enter_day_name_messege)\\n break\\n except:\\n print(exception_messege)\\n while day.lower() not in day_list:\\n while True:\\n try: \\n print(warning_day_name_messege)\\n day = input(enter_day_name_messege) \\n break\\n except:\\n print(exception_messege)\\n break\\n \\n else:\\n month = 'all'\\n day = 'all'\\n break\\n \\n\\n print('-'*40)\\n return city.lower(), month.lower(), day.lower()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6095031","0.5822337","0.58005035","0.5798782","0.5752552","0.57133955","0.5679745","0.56412446","0.5630844","0.5596643","0.5596643","0.5586385","0.55733144","0.55497605","0.55235076","0.54996634","0.54918146","0.5452439","0.54508233","0.54480547","0.5379182","0.53632486","0.53521216","0.5308785","0.5290236","0.5286493","0.5285896","0.5270669","0.5245444","0.5241223","0.52347785","0.5224553","0.52157116","0.5210318","0.5206071","0.5186969","0.51754117","0.51745546","0.51739824","0.51667756","0.51625925","0.5143395","0.51404","0.5126642","0.5123552","0.51209843","0.5117211","0.511521","0.50978756","0.5093959","0.509109","0.5087402","0.50811636","0.50776935","0.5077627","0.50749266","0.5074837","0.50732905","0.5061439","0.50595444","0.50567883","0.50540364","0.5052249","0.505115","0.50492257","0.5044806","0.5041487","0.5040985","0.50394666","0.50367075","0.5036352","0.50362015","0.50347465","0.503433","0.50331587","0.50329274","0.50307614","0.5028623","0.5028306","0.5022428","0.5019409","0.5018199","0.5009225","0.500381","0.49985927","0.49952778","0.49920443","0.49870223","0.4986694","0.49856278","0.49813306","0.49731308","0.49720553","0.49700588","0.49639314","0.49625325","0.49618626","0.49614665","0.4959454","0.49587834"],"string":"[\n \"0.6095031\",\n \"0.5822337\",\n \"0.58005035\",\n \"0.5798782\",\n \"0.5752552\",\n \"0.57133955\",\n \"0.5679745\",\n \"0.56412446\",\n \"0.5630844\",\n \"0.5596643\",\n \"0.5596643\",\n \"0.5586385\",\n \"0.55733144\",\n \"0.55497605\",\n \"0.55235076\",\n \"0.54996634\",\n \"0.54918146\",\n \"0.5452439\",\n \"0.54508233\",\n \"0.54480547\",\n \"0.5379182\",\n \"0.53632486\",\n \"0.53521216\",\n \"0.5308785\",\n \"0.5290236\",\n \"0.5286493\",\n \"0.5285896\",\n \"0.5270669\",\n \"0.5245444\",\n \"0.5241223\",\n \"0.52347785\",\n \"0.5224553\",\n \"0.52157116\",\n \"0.5210318\",\n \"0.5206071\",\n \"0.5186969\",\n \"0.51754117\",\n \"0.51745546\",\n \"0.51739824\",\n \"0.51667756\",\n \"0.51625925\",\n \"0.5143395\",\n \"0.51404\",\n \"0.5126642\",\n \"0.5123552\",\n \"0.51209843\",\n \"0.5117211\",\n \"0.511521\",\n \"0.50978756\",\n \"0.5093959\",\n \"0.509109\",\n \"0.5087402\",\n \"0.50811636\",\n \"0.50776935\",\n \"0.5077627\",\n \"0.50749266\",\n \"0.5074837\",\n \"0.50732905\",\n \"0.5061439\",\n \"0.50595444\",\n \"0.50567883\",\n \"0.50540364\",\n \"0.5052249\",\n \"0.505115\",\n \"0.50492257\",\n \"0.5044806\",\n \"0.5041487\",\n \"0.5040985\",\n \"0.50394666\",\n \"0.50367075\",\n \"0.5036352\",\n \"0.50362015\",\n \"0.50347465\",\n \"0.503433\",\n \"0.50331587\",\n \"0.50329274\",\n \"0.50307614\",\n \"0.5028623\",\n \"0.5028306\",\n \"0.5022428\",\n \"0.5019409\",\n \"0.5018199\",\n \"0.5009225\",\n \"0.500381\",\n \"0.49985927\",\n \"0.49952778\",\n \"0.49920443\",\n \"0.49870223\",\n \"0.4986694\",\n \"0.49856278\",\n \"0.49813306\",\n \"0.49731308\",\n \"0.49720553\",\n \"0.49700588\",\n \"0.49639314\",\n \"0.49625325\",\n \"0.49618626\",\n \"0.49614665\",\n \"0.4959454\",\n \"0.49587834\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5986981"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":88558,"cells":{"query":{"kind":"string","value":"Convert the character in the [ ] for a task into a TaskStatus"},"document":{"kind":"string","value":"def _get_status_from_char(char: str) -> TaskStatus:\n if char == \"c\":\n return TaskStatus.CANCELED\n elif char == \"b\":\n return TaskStatus.BLOCKED\n elif char == \" \":\n return TaskStatus.UNSCHEDULED\n elif char == \"x\":\n return TaskStatus.DONE\n elif char == \"?\":\n return TaskStatus.IDEA\n elif char == \"-\":\n return TaskStatus.IN_PROGRESS\n else:\n raise Exception(\"unknown status character {char}\".format(char=char))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def task_status():\n pass","def task_status(self) -> str:\n return self._task_status","async def get_task_status(task_id: TaskId):","def fuota_task_status(self) -> Optional[str]:\n return pulumi.get(self, \"fuota_task_status\")","def _parse_status(self, status):\n if status in (STATUS_FINISHED, 'FINISHED'):\n return STATUS_FINISHED\n elif status in (STATUS_ERROR, 'ERROR'):\n return STATUS_ERROR\n elif status in (STATUS_CANCELED, 'CANCELED'):\n return STATUS_CANCELED\n return STATUS_STARTED","def parse_filter_unlabelled(task_output):\n task_list = []\n for item in task_output:\n item = item.split(\",\")\n if len(item) == 3:\n if check_status(item):\n task_list.append(item)\n\n return task_list","def _validate_task(task: str) -> str:\n supported = (\"regression\", \"binary\")\n if not any([task in item for item in supported]):\n raise ValueError(f\"{task} is not a supported task.\")\n return task","def mesos_status(self, submissionId):\n get_tasks = self.driver.getTasks()['get_tasks']\n task_state = None\n\n tasks = get_tasks['tasks'] + get_tasks.get('completed_tasks')\n tasks_list = list(filter(lambda x: x['task_id']['value'] == submissionId, tasks))\n if len(tasks_list) > 0:\n task = tasks_list[0]\n task_state = task['state']\n self._log.debug(\"Task state = \" + task_state)\n else:\n self._log.debug(\"Task not found\")\n\n return task_state","def Get_Status(n, way):\n s = n.split(way)\n if len(s) > 1:\n return \"1\"\n else:\n return \"0\"","def getNodeTaskStatusByUPID(self,node,upid):\n data = self.connect('get','nodes/%s/tasks/%s/status' % (node,upid),None)\n return data","def _get_instructor_task_status(task_id):\r\n instructor_task = get_updated_instructor_task(task_id)\r\n status = get_status_from_instructor_task(instructor_task)\r\n if instructor_task is not None and instructor_task.task_state in STATES_WITH_STATUS:\r\n succeeded, message = get_task_completion_info(instructor_task)\r\n status['message'] = message\r\n status['succeeded'] = succeeded\r\n return status","def get_task_status(task_id):\r\n mock_request = Mock()\r\n mock_request.REQUEST = {'task_id': task_id}\r\n response = instructor_task_status(mock_request)\r\n status = json.loads(response.content)\r\n return status","def parse_task(task: str) -> tuple[int, int]:\n parts = task.strip().split()\n return int(parts[0]), int(parts[6])","def status_str(status):\n\n status_map = {\n 0: 'MATCH',\n 10: 'OK',\n 15: 'SKIP',\n 20: 'FAIL',\n 30: 'CRASH'\n }\n return status_map.get(status, 'UNKNOWN')","def _decode_sensor_status(self, status: str) -> str:\n k = int(status)\n return self.SENSOR_STATUSES[k]","def get_status_from_instructor_task(instructor_task):\r\n status = {}\r\n\r\n if instructor_task is not None:\r\n # status basic information matching what's stored in InstructorTask:\r\n status['task_id'] = instructor_task.task_id\r\n status['task_state'] = instructor_task.task_state\r\n status['in_progress'] = instructor_task.task_state not in READY_STATES\r\n if instructor_task.task_output is not None:\r\n status['task_progress'] = json.loads(instructor_task.task_output)\r\n\r\n return status","def task_status(self, task_status: str):\n if task_status is None:\n raise ValueError(\"Invalid value for `task_status`, must not be `None`\") # noqa: E501\n\n self._task_status = task_status","def parse_completed(self, in_str):\n if not in_str:\n self.completed = False\n elif in_str.lower() == \"x\":\n self.completed = True\n else:\n self.completed = False","def _status_to_state(status):\n if status == 'failed':\n return Finding.State.ACTIVE\n elif status == 'passed' or status == 'skipped':\n return Finding.State.INACTIVE\n else:\n return Finding.State.STATE_UNSPECIFIED","def status2word(self,status):\n if status == 'T':\n return \"Toggle\"\n elif status == 'S':\n return \"Signature\"\n elif status == 'R':\n return \"Random\"\n elif status == 'N':\n return \"Normal\"\n elif status == 'E':\n return \"FE Error\"\n elif status == 'X':\n return \"NO TIN\"\n else:\n print \"Unknown status !\"\n return \"BUG\"","def task_state(task_id):\n tag_task = parse_html_tags.AsyncResult(task_id)\n return jsonify({'task_id': task_id, 'task_state': tag_task.state,\n 'result_url': url_for('task_result', task_id=tag_task.id)}), 202, {}","def status_to_event_code(status: str):\n return {\n \"sent\": \"txSent\",\n \"pending\": \"txPool\",\n \"pending-simulation\": \"txPoolSimulation\",\n \"stuck\": \"txStuck\",\n \"confirmed\": \"txConfirmed\",\n \"failed\": \"txFailed\",\n \"speedup\": \"txSpeedUp\",\n \"cancel\": \"txCancel\",\n \"dropped\": \"txDropped\",\n }[status]","def work_status(value):\n for status in models.WORK_STATUS:\n if status[0]==value:\n return status[1]\n\n return \"WORK STATUS NOT FOUND\"","def convert_to_rp_status(behave_status):\n if behave_status == \"passed\":\n return \"PASSED\"\n elif behave_status == \"failed\":\n return \"FAILED\"\n elif behave_status == \"skipped\":\n return \"SKIPPED\"\n else:\n # todo define what to do\n return \"PASSED\"","def get_task_status(id):\n # obtain the task and validate it\n global background_tasks\n rv = background_tasks.get(id)\n if rv is None:\n return not_found(None)\n\n # if the task object is a Thread object that means that the task is still\n # running. In this case return the 202 status message again.\n if isinstance(rv, Thread):\n return jsonify({}), 202, {'Location': url_for('get_task_status', id=id)}\n\n # If the task object is not a Thread then it is assumed to be the response\n # of the finished task, so that is the response that is returned.\n # If the application is configured to auto-delete task status resources once\n # the task is done then the deletion happens now, if not the client is\n # expected to send a delete request.\n if app.config['AUTO_DELETE_BG_TASKS']:\n del background_tasks[id]\n return rv","def check_indicator_files(tasks):\n\n for task in tasks:\n if task[\"status\"]==\"unknown\":\n if os.path.exists(task[\"result\"]):\n task[\"status\"]=\"previously completed\"\n else:\n task[\"status\"]=\"to do\"\n return","def check_task(self): \n return self.buffer[0]","def update_task_status(project_id, task_id):\n completion_status = request.get_json()['completion_status']\n\n project = Project.query.filter_by(id=project_id).first()\n if not project:\n return {\n 'success': False,\n 'message': f\"No project with the specified id {project_id} found.\",\n }\n \n else:\n permission = has_project_permission(project, g.user)\n task = Task.query.filter_by(id=task_id).first()\n if not task:\n abort(404, f'There is no task with ID of {task_id}.')\n if task:\n task.completion_status = completion_status\n db_session.add(task)\n db_session.commit()\n return {\n 'success': True,\n 'result': task_schema.dump(task),\n 'message': f\"Successfully Updated the Completion Status of {task.name}.\"\n }","def getJobStatusStr(status):\n if not isinstance(status, int):\n return ''\n\n return JobUtils.JOB_STATUS.get(status, '')","def container_status(self):\n if self.status == 'complete':\n return 'complete'\n try:\n task_status = self._ecs.describe_tasks(tasks=[self.name])['tasks'][0]['lastStatus']\n return task_status\n except (IndexError, ClientError):\n return 'STOPPED'","def getStatus(self, blTaskName, statusFile=None, statusFamilyType='status'):\n\n # fill the filename\n filename = str(statusFile)\n\n if not blTaskName:\n raise CrabException('Exception while getting the task unique name')\n return ''\n\n # get the data and fill the file content\n statusMsg = self.asSession.getTaskStatus(statusFamilyType, blTaskName)\n if 'Error:' in statusMsg[:6] or len(statusMsg)==0:\n if statusFamilyType != 'isServerDrained':\n raise CrabException('Error in retrieving task %s status from server %s'%(self.crab_task_name, self.serverName) )\n else:\n statusFile = None\n statusMMsg = \"\"\n\n if statusFile is not None:\n f = open(statusFile, 'w')\n f.write(statusMsg)\n f.close()\n return statusFile\n return statusMsg","def valid_status(cls, status_str):\n status_str = status_str.upper()\n if status_str not in [\"OPEN\", \"CLOSED\"]:\n raise ValueError(f\"invalid ticket status '{status_str}'\")\n return status_str","def _reverted_task_status(task_audit, revert_before):\n task = Task.objects.get(id=task_audit['task']['id'])\n\n flattened_iterations = [\n iteration_audit\n for assignment_audit in task_audit['assignments']\n for iteration_audit in assignment_audit['iterations']]\n changed_items = _parse_changed_items(flattened_iterations, 'iteration')\n\n latest_iterations = (\n get_iteration_history(task, reverse=True)\n .exclude(id__in=changed_items[RevertChange.DELETED.value]))\n\n num_iterations = latest_iterations.count()\n if num_iterations == 0:\n return Task.Status.AWAITING_PROCESSING\n elif revert_before:\n # Reverting before the first iteration in an assignment means the task\n # is pending review, since at least one iteration exists\n return Task.Status.PENDING_REVIEW\n else:\n # Revert to a processing iteration state\n if num_iterations == 1:\n return Task.Status.PROCESSING\n else:\n previous_status = latest_iterations[1].status\n if previous_status == Iteration.Status.REQUESTED_REVIEW:\n return Task.Status.REVIEWING\n else:\n return Task.Status.POST_REVIEW_PROCESSING","def _get_status(self):\n return u'%s' % (self.get_status_display())","def _format_task_summary(task_summary: _TaskSummary) -> str:\n lookup = { # noqa: DAR101, DAR201\n _TaskExitCode.PASS: (fg.green, 'was successful'),\n _TaskExitCode.FAIL: (fg.red, 'failed'),\n _TaskExitCode.NOT_RUN: (fg.white, 'was not run'),\n _TaskExitCode.SKIP_IGNORED: (fg.yellow, 'was ignored'),\n _TaskExitCode.SKIP_UP_TO_DATE: (fg.yellow, 'was skipped'),\n }\n foreground, exit_summary = lookup.get(task_summary.exit_code, ('', 'is UNKNOWN'))\n return f'{foreground}{task_summary.name} {exit_summary}' + fg.rs","def parse_homework_status(homework: Dict) -> str:\n homework_name = homework[0].get(\"homework_name\")\n statuses = {\n \"rejected\": \"К сожалению в работе нашлись ошибки.\",\n \"reviewed\": \"Проект взят в работу ревьювером.\",\n \"approved\": (\n \"Ревьюеру всё понравилось, можно приступать к следующему уроку.\"\n ),\n }\n return (\n f'У вас проверили работу \"{homework_name}\"!\\n\\n'\n f'{statuses[homework[0].get(\"status\")]}'\n )","def task_scanned(now_task):","def solve(task: str, preamble_length: int = 25) -> int:\n data = [int(num) for num in task.strip().split(\"\\n\")]\n return first_invalid(data, preamble_length)","def __repr__(self):\r\n return 'SubtaskStatus<%r>' % (self.to_dict(),)","def status(a):\n return a","async def rndactivity_parse(self, ctx: commands.Context, *, status: str):\n shard = getattr(ctx.guild, \"shard_id\", 0)\n\n try:\n result, result_type = self.format_status(status, shard=shard)\n except KeyError as e:\n await fmt(\n ctx,\n warning(\n _(\n \"Placeholder {placeholder} does not exist\\n\\n\"\n \"See `{prefix}help rndactivity add` for the list of placeholder strings\"\n )\n ),\n placeholder=escape(str(e), mass_mentions=True),\n )\n else:\n await fmt(\n ctx,\n _(\"\\N{INBOX TRAY} **Input:**\\n{input}\\n\\N{OUTBOX TRAY} **Result:** {result}\"),\n input=escape(status, mass_mentions=True),\n result=escape(result, mass_mentions=True),\n )","def task_format_check():\n return {\"actions\": [[\"black\", HERE, \"--check\"]], \"verbosity\": 1}","def _parse_json_to_status_update(self, json_message):\n if len(json_message['failing']) > 0:\n return BuildStatusUpdate(BuildStatus.Failing)\n elif len(json_message['acknowledged']) > 0:\n return BuildStatusUpdate(BuildStatus.Acknowledged)\n else:\n return BuildStatusUpdate(BuildStatus.Passing)","def state_to_task(self, states):\n tasks = states\n return tasks","def retrieve_task(self, task_id):\n r = requests.get('/'.join([self.base_url, self.ENDPOINT_TASK_STATUS,\n str(task_id)]))\n return r.json()","def get_tasks_ids_by_status(self, status=\"Done\"):\n if status not in (\"Done\", \"Paused\", \"Running\", \"Stopped\"):\n raise ValueError(\"Requested status are not allowed\")\n\n\n m_task_ids = {}\n\n for x in self.get_tasks().findall(\"task\"):\n if x.find(\"status\").text == status:\n m_task_ids[x.find(\"name\").text] = x.attrib[\"id\"]\n\n return m_task_ids","def find_task(self, task_str):\n task_str = task_str.replace('é', 'e').title()\n task_not_found = True\n custom_quest = False\n if \":\" in task_str:\n task_strs = task_str.split(\":\")\n task_str = task_strs[0]\n quest_str = task_strs[1]\n custom_quest = True\n while task_not_found:\n for task in self.tasks:\n if (task_str == task.reward.title()) or (task_str == task.quest.replace('é', 'e').title()) or (task_str in (reward.title() for reward in task.rewards)) or (task_str in (nickname.title() for nickname in task.nicknames)):\n out_task = task\n task_not_found = False\n if custom_quest:\n out_task = copy.copy(task)\n out_task.quest = quest_str.title()\n return out_task\n break\n if task_not_found:\n raise TaskNotFound()","def status_class(status):\n status = status.split('-')[-1] # e.g. \"overall-passed\" -> \"passed\"\n classes = {\n 'passed': 'success',\n 'failed': 'danger',\n 'skipped': 'warning',\n 'match': 'success',\n 'diff': 'danger',\n 'missing': 'warning',\n 'generated': 'warning',\n }\n return classes[status]","def get_completed_tasks_in_tod():\n try:\n tod_file_data = load_data(os.getenv('TOD_FP'))\n except FileNotFoundError:\n return []\n completed_tasks = []\n tod_file_data = tod_file_data.split('\\n')\n\n for line in tod_file_data:\n if line == '' or line[0] != '[' or line[1] != 'X':\n continue\n completed_task = (f\"{line[4:-7]} {line[-6:]}\"\n if line[-6:] != '(0:00)'\n else line[4:-7])\n completed_tasks.append(completed_task)\n\n return completed_tasks","def extract_human_name_from_task(self, task_xml):\r\n tree = etree.fromstring(task_xml)\r\n payload = tree.xpath(\"/openended/openendedparam/grader_payload\")\r\n if len(payload) == 0:\r\n task_name = \"selfassessment\"\r\n else:\r\n inner_payload = json.loads(payload[0].text)\r\n task_name = inner_payload['grader_settings']\r\n\r\n human_task = HUMAN_TASK_TYPE[task_name]\r\n return human_task","def my_update_subtask_status(entry_id, current_task_id, new_subtask_status):\r\n entry = InstructorTask.objects.get(pk=entry_id)\r\n subtask_dict = json.loads(entry.subtasks)\r\n subtask_status_info = subtask_dict['status']\r\n current_subtask_status = SubtaskStatus.from_dict(subtask_status_info[current_task_id])\r\n current_retry_count = current_subtask_status.get_retry_count()\r\n new_retry_count = new_subtask_status.get_retry_count()\r\n if current_retry_count <= new_retry_count:\r\n update_subtask_status(entry_id, current_task_id, new_subtask_status)","def tasks_to_html_table(tasks):\n s = \"\"\n s += \"<table>\\n\"\n status_seen = []\n for i,task in enumerate(tasks):\n s += \"<tr><td>\"\n\n if task[\"status\"] not in status_seen:\n status_seen.append(task[\"status\"])\n s += \"<a name=\\\"%s\\\"></a>\"%(task[\"status\"])\n \n s += \"%i.</td>\"%(i+1)\n s += \"<td>%s</td>\"%task[\"command\"]\n stl = \"color:%s\"%status_colors.get(task[\"status\"],\"gray\")\n details = \"\"\n if task[\"status\"]==\"running\":\n if \"started\" in list(task.keys()):\n details = \" [started %s]\"%task[\"started\"]\n \n if task[\"status\"]==\"completed\" or task[\"status\"]==\"previously completed\":\n if \"finished\" in list(task.keys()):\n details += \" [%s]\"%task[\"finished\"]\n if \"duration\" in list(task.keys()):\n details += \" %.2f hours\"%(task[\"duration\"]/3600.)\n s += \"<td style=\\\"%s\\\">%s %s</td>\"%(stl,task[\"status\"],details)\n if \"logfname\" in list(task.keys()):\n s += \"<td><a href=\\\"%s\\\">log</a></td>\"%task[\"logfname\"]\n s += \"</tr>\\n\"\n\n s += \"</table>\\n\"\n return s","def get_status(self):\n if self._is_running():\n return \"RUNNING\"\n elif self._has_error():\n # The run started but failed\n return \"FAILED\"\n elif self._is_finished():\n # The run was finished\n return \"FINISHED\"\n elif self.current_step() >= 0:\n # The run started at some point but was not completed\n return \"INCOMPLETE\"\n else:\n # The run did not start\n return \"NOT STARTED\"","def _update_subtask_status(entry_id, current_task_id, new_subtask_status):\r\n TASK_LOG.info(\"Preparing to update status for subtask %s for instructor task %d with status %s\",\r\n current_task_id, entry_id, new_subtask_status)\r\n\r\n try:\r\n entry = InstructorTask.objects.select_for_update().get(pk=entry_id)\r\n subtask_dict = json.loads(entry.subtasks)\r\n subtask_status_info = subtask_dict['status']\r\n if current_task_id not in subtask_status_info:\r\n # unexpected error -- raise an exception\r\n format_str = \"Unexpected task_id '{}': unable to update status for subtask of instructor task '{}'\"\r\n msg = format_str.format(current_task_id, entry_id)\r\n TASK_LOG.warning(msg)\r\n raise ValueError(msg)\r\n\r\n # Update status:\r\n subtask_status_info[current_task_id] = new_subtask_status.to_dict()\r\n\r\n # Update the parent task progress.\r\n # Set the estimate of duration, but only if it\r\n # increases. Clock skew between time() returned by different machines\r\n # may result in non-monotonic values for duration.\r\n task_progress = json.loads(entry.task_output)\r\n start_time = task_progress['start_time']\r\n prev_duration = task_progress['duration_ms']\r\n new_duration = int((time() - start_time) * 1000)\r\n task_progress['duration_ms'] = max(prev_duration, new_duration)\r\n\r\n # Update counts only when subtask is done.\r\n # In future, we can make this more responsive by updating status\r\n # between retries, by comparing counts that change from previous\r\n # retry.\r\n new_state = new_subtask_status.state\r\n if new_subtask_status is not None and new_state in READY_STATES:\r\n for statname in ['attempted', 'succeeded', 'failed', 'skipped']:\r\n task_progress[statname] += getattr(new_subtask_status, statname)\r\n\r\n # Figure out if we're actually done (i.e. this is the last task to complete).\r\n # This is easier if we just maintain a counter, rather than scanning the\r\n # entire new_subtask_status dict.\r\n if new_state == SUCCESS:\r\n subtask_dict['succeeded'] += 1\r\n elif new_state in READY_STATES:\r\n subtask_dict['failed'] += 1\r\n num_remaining = subtask_dict['total'] - subtask_dict['succeeded'] - subtask_dict['failed']\r\n\r\n # If we're done with the last task, update the parent status to indicate that.\r\n # At present, we mark the task as having succeeded. In future, we should see\r\n # if there was a catastrophic failure that occurred, and figure out how to\r\n # report that here.\r\n if num_remaining <= 0:\r\n entry.task_state = SUCCESS\r\n entry.subtasks = json.dumps(subtask_dict)\r\n entry.task_output = InstructorTask.create_output_for_success(task_progress)\r\n\r\n TASK_LOG.debug(\"about to save....\")\r\n entry.save()\r\n TASK_LOG.info(\"Task output updated to %s for subtask %s of instructor task %d\",\r\n entry.task_output, current_task_id, entry_id)\r\n except Exception:\r\n TASK_LOG.exception(\"Unexpected error while updating InstructorTask.\")\r\n transaction.rollback()\r\n dog_stats_api.increment('instructor_task.subtask.update_exception')\r\n raise\r\n else:\r\n TASK_LOG.debug(\"about to commit....\")\r\n transaction.commit()","def __str__(self):\n return self.task","def _format_terminated_task(tinfo: TerminatedTaskInfo) -> str:\n status = []\n if tinfo.cancelled:\n status.append(\"cancelled\")\n if tinfo.exc_repr and not tinfo.cancelled:\n status.append(f\"exc={tinfo.exc_repr}\")\n return f\"<TerminatedTask name={tinfo.name} coro={tinfo.coro} {' '.join(status)}>\"","def format_status(report_status: Status) -> str:\n if report_status in (Status.FAILED, Status.ERROR):\n return Status.FAILED.title()\n return report_status.title()","def get_short_task_id(task_id: str) -> str:\n return task_id.split(MESOS_TASK_SPACER)[-1]","def task_format():\n print(HERE)\n return {\"actions\": [\"isort -y \", [\"black\", HERE]], \"verbosity\": 1}","def get_status_as_string(self):\n if self.downloaded == 0:\n return \"[Starting... ]\"\n return \"[%s, %s, %s]\" % self.get_status()","def test_convert_video_status(self):\n video = self.previous_uploads[0]\n\n # video status should be failed if it's in upload state for more than 24 hours\n video['created'] = datetime(2016, 1, 1, 10, 10, 10, 0, pytz.UTC)\n status = convert_video_status(video)\n self.assertEqual(status, StatusDisplayStrings.get('upload_failed'))\n\n # `invalid_token` should be converted to `youtube_duplicate`\n video['created'] = datetime.now(pytz.UTC)\n video['status'] = 'invalid_token'\n status = convert_video_status(video)\n self.assertEqual(status, StatusDisplayStrings.get('youtube_duplicate'))\n\n # The \"encode status\" should be converted to `file_complete` if video encodes are complete\n video['status'] = 'transcription_in_progress'\n status = convert_video_status(video, is_video_encodes_ready=True)\n self.assertEqual(status, StatusDisplayStrings.get('file_complete'))\n\n # If encoding is not complete return the status as it is\n video['status'] = 's3_upload_failed'\n status = convert_video_status(video)\n self.assertEqual(status, StatusDisplayStrings.get('s3_upload_failed'))\n\n # for all other status, there should not be any conversion\n statuses = list(StatusDisplayStrings._STATUS_MAP.keys()) # pylint: disable=protected-access\n statuses.remove('invalid_token')\n for status in statuses:\n video['status'] = status\n new_status = convert_video_status(video)\n self.assertEqual(new_status, StatusDisplayStrings.get(status))","def task_failed(task_state):\n return task_state in {\"TASK_LOST\", \"TASK_KILLED\", \"TASK_FAILED\", \"TASK_TERMINATING\"}","def label_transformation(self, ind_task, label):\n\n # if self.disjoint class 0 of second task become class 10, class 1 -> class 11, ...\n if self.disjoint_classes:\n label = label + self.num_classes * ind_task\n\n return label","def instructor_task_status(request):\r\n output = {}\r\n if 'task_id' in request.REQUEST:\r\n task_id = request.REQUEST['task_id']\r\n output = _get_instructor_task_status(task_id)\r\n elif 'task_ids[]' in request.REQUEST:\r\n tasks = request.REQUEST.getlist('task_ids[]')\r\n for task_id in tasks:\r\n task_output = _get_instructor_task_status(task_id)\r\n if task_output is not None:\r\n output[task_id] = task_output\r\n\r\n return HttpResponse(json.dumps(output, indent=4))","def task(self) -> str:\n return self._task","def read_all_status_characters(self):\n return self.STATUS_CHARACTERS","def status_check(task_id):\n logger.info(f\"Checking task status for {task_id}\")\n task = Task.objects.get(kf_id=task_id)\n task.status_check()","def get_status(id):\n task = run_ctx_request.AsyncResult(id)\n if task.state == states.PENDING:\n abort(404)\n if task.state == states.RECEIVED or task.state == states.STARTED:\n return '', 202, {'Location': url_for('api.get_status', id=id)}\n return task.info","def grip_status_to_str(status):\n return 'gACT:{}, gGTO:{}, gSTA:{}, gOBJ:{}, ' \\\n 'gFLT:{}, gPR:{}, gPO:{}, gCU:{}'.format(\n status.gACT,\n status.gGTO,\n status.gSTA,\n status.gOBJ,\n status.gFLT,\n status.gPR,\n status.gPO,\n status.gCU\n )","def status(self):\n return STATUS[self.fields['status']]","def task_is_failure(task):\n\n if task and task.state == 'FAILURE':\n return True\n return False","def taskStatus(self, task_id, timeout=90, log_progress=True):\n start = time.time()\n elapsed = 0\n last_check = 0\n while True:\n elapsed = time.time() - start\n status = ee.data.getTaskStatus(task_id)[0]\n state = status['state']\n if state in TASK_FINISHED_STATES:\n error_message = status.get('error_message', None)\n print('Task %s ended at state: %s after %.2f seconds'\n % (task_id, state, elapsed))\n if error_message:\n raise ValueError(error_message)\n return\n if log_progress and elapsed - last_check >= 30:\n print('[{:%H:%M:%S}] Current state for task {}: {}'\n .format(datetime.now(), task_id, state))\n last_check = elapsed\n remaining = timeout - elapsed\n if remaining > 0:\n time.sleep(min(10, remaining))\n else:\n break\n print('Wait for task %s timed out after %.2f seconds' % (task_id, elapsed))","def custom_wait_for_completion(task_description, output):\n state = 'UNSUBMITTED'\n while not (state == 'COMPLETED' or state =='FAILED'):\n output.add_live_msg(ms.STATUS.format(state))\n time.sleep(5)\n \n #search for the task in task_list\n for task in task_description:\n current_task = gs.isTask(task)\n if current_task:\n state = current_task.state\n if state == 'RUNNING' or state == 'FAILED': \n break\n \n return state","def show_tasks_status(user, tasks):\n employee_name = user[0]['username']\n all_tasks = tasks\n completed = 0\n title_completed_tasks = ''\n for task in all_tasks:\n if task['completed'] is True:\n completed += 1\n title_completed_tasks += '\\t ' + task['title'] + '\\n'\n print('Employee {} is done with tasks({}/{}):'\n .format(employee_name, completed, len(all_tasks)))\n print(title_completed_tasks, end='')","def _cleanTask(task, org_admin):\n\n errors = []\n\n # check title\n if not task['title']:\n errors.append('No valid title present.')\n\n # clean description\n try:\n cleaner = HtmlSanitizer.Cleaner()\n cleaner.string = task['description']\n cleaner.clean()\n task['description'] = cleaner.string.strip().replace('\\r\\n', '\\n') \n except (HTMLParseError, safe_html.IllegalHTML, TypeError), e:\n logging.warning('Cleaning of description failed with: %s' %e)\n errors.append(\n 'Failed to clean the description, do not use naughty HTML such as '\n '<script>.')\n\n # clean time to complete\n try:\n task['time_to_complete'] = int(task['time_to_complete'])\n except (ValueError, TypeError), e:\n errors.append('No valid time to completion found, given was: %s.' \n %task['time_to_complete'])\n\n # clean mentors\n mentor_ids = set(task['mentors'].split(','))\n\n mentor_fields = {'scope': org_admin.scope,\n 'status': 'active'}\n mentors = []\n for mentor_id in mentor_ids:\n mentor_fields['link_id'] = mentor_id.strip()\n mentor = mentor_logic.getForFields(mentor_fields, unique=True)\n if mentor:\n mentors.append(mentor.key())\n else:\n errors.append('%s is not a mentor.' %mentor_id)\n\n task['mentors'] = mentors\n\n program_entity = org_admin.program\n\n # clean task difficulty\n difficulty = task['difficulty'].strip()\n allowed_difficulties = [\n str(x) for x in \n task_model.TaskDifficultyTag.get_by_scope(program_entity)]\n if not difficulty or difficulty not in allowed_difficulties:\n # no valid difficulty found\n errors.append('No valid task difficulty found, given %s.' %difficulty)\n else:\n task['difficulty'] = {\n 'tags': task['difficulty'],\n 'scope': program_entity\n }\n\n # clean task types\n task_types = []\n allowed_types = [\n str(x) for x in task_model.TaskTypeTag.get_by_scope(program_entity)]\n for task_type in set(task['task_type'].split(',')):\n task_type = task_type.strip()\n if task_type in allowed_types:\n task_types.append(task_type)\n else:\n errors.append('%s is not a valid task type.' %task_type)\n\n task['task_type'] = {\n 'tags': task_types,\n 'scope': program_entity\n }\n\n # clean task tags\n arbit_tags = []\n for tag in set(task['arbit_tag'].split(',')):\n arbit_tags.append(tag.strip())\n task['arbit_tag'] = {\n 'tags': arbit_tags,\n 'scope': program_entity\n }\n\n return errors","def get_job_status(self, mission):\n\n # initialize task status\n status = dict(active=0, running=0, succeeded=0, failed=0)\n\n # get job status if it exists. Otherwise, return N/A\n try:\n the_job = self.batch_client.job.get(job_id=mission.job_name)\n\n # get counts of tasks in different statuses\n status_counts = self.batch_client.job.get_task_counts(mission.job_name)\n except azure.batch.models.BatchErrorException as err:\n if err.message.value.startswith(\"The specified job does not exist\"):\n return \"N/A\", status\n # raise an exception for other kinds of errors\n raise\n\n # update the dictionary\n status[\"active\"] = status_counts.active\n status[\"running\"] = status_counts.running\n status[\"succeeded\"] = status_counts.succeeded\n status[\"failed\"] = status_counts.failed\n\n return the_job.state.name, status","def get_roof_status_from_tcs():\n\t\n\ttarget = send_command('getstatus dome')\n\tsplit_ans = target.split()\n\t\n\treturn split_ans","def test_translated_names(self):\r\n func = lambda t: t.upper()\r\n # status is in the mapping\r\n statobj = inputtypes.Status('queued', func)\r\n self.assertEqual(statobj.display_name, u'PROCESSING')\r\n\r\n # status is not in the mapping\r\n statobj = inputtypes.Status('test', func)\r\n self.assertEqual(statobj.display_name, u'test')\r\n self.assertEqual(str(statobj), 'test')\r\n self.assertEqual(statobj.classname, 'test')","def dummy_update_subtask_status(entry_id, _current_task_id, new_subtask_status):\r\n bogus_task_id = \"this-is-bogus\"\r\n update_subtask_status(entry_id, bogus_task_id, new_subtask_status)","def tasks_by_status(self) -> Dict[TaskStatus, Sequence[str]]:\n out = {}\n for key in self.task_graph.keys():\n info = self.task_graph.get_info(key)\n out.setdefault(info.status, []).append(key)\n return out","def port_status_from_hex(hex_status):\n hexmap = {1: 'ESTABLISHED',\n 2: 'TCP_SYN_SENT',\n 3: 'TCP_SYN_RECV',\n 4: 'TCP_FIN_WAIT1',\n 5: 'TCP_FIN_WAIT2',\n 6: 'TCP_TIME_WAIT',\n 7: 'TCP_CLOSE',\n 8: 'TCP_CLOSE_WAIT',\n 9: 'TCP_LAST_ACK',\n 10: 'TCP_LISTEN',\n 11: 'TCP_CLOSING',\n 12: 'TCP_MAX_STATES'}\n\n return hexmap(int(hex_status, 16))","def getStatusString(self, statClass=None):\n return self.convertStatus(self.getStatus(statClass=statClass))","def get_status(self):\n # find status\n # search in summary file first\n self.status = \"running\"\n status = self.search_summary(\"status\")\n if status:\n self.status = status.split()[1]\n # define running time\n # search in summary file first\n self.running_time = \"00:00:00\"\n running_time = self.search_summary(\"running-time\")\n if running_time:\n self.running_time = running_time.split()[1]\n # calculate running time\n else:\n now = datetime.datetime.now()\n elapsed_time = (now - self.ctime).seconds\n hours, remainder = divmod(elapsed_time, 3600)\n minutes, seconds = divmod(remainder, 60)\n self.running_time = (\n f\"{int(hours):02}:{int(minutes):02}:{int(seconds):02}\"\n )","def taskbystatus(self, **kwargs):\n rows = self.api.query(None, None, self.Task.TaskByStatus_sql, username_=kwargs[\"username\"], taskstatus=kwargs[\"taskstatus\"])\n\n return rows","async def get_status():","def status(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"status\")","def status(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"status\")","def TaskState(self):\n return symbol_by_name(\"etools_datamart.apps.etl.models.EtlTask\")","def is_task_stagnant(task):","def get_status(pos, neg, names):\n status = {}\n for i in names:\n #print str(i) +'\\n'+ str(pos) +'\\n'+ str(neg)+'\\n'+'\\n'\n if i in pos:\n status[i] = \"1\"\n elif i in neg:\n status[i] = \"0\"\n else:\n status[i] = \"NA\"\n return status","async def get_status(self) -> dict[str, Any]:\n\n def check_int(s):\n if s[0] in (\"-\", \"+\"):\n return s[1:].isdigit()\n return s.isdigit()\n\n cmd = await self.send_command(\"STATUS\", timeout=1)\n if not cmd.succeeded():\n raise ArchonError(f\"Command finished with status {cmd.status.name!r}\")\n\n keywords = str(cmd.replies[0].reply).split()\n status = {\n key.lower(): int(value) if check_int(value) else float(value)\n for (key, value) in map(lambda k: k.split(\"=\"), keywords)\n }\n\n return status","def GetTaskPriority(cls, task):\n if not task: return None\n\n task = cls.TaskRelativeName(task)\n\n priority = ''\n parts = task.split(os.sep)\n for part in parts:\n priority_name = part.split('_', 1)\n if len(priority_name) < 2 or not priority_name[0].isdigit(): return None\n priority += priority_name[0]\n return priority","def test_support_STATUSMSG(self):\n self.assertEqual(self._parseFeature(\"STATUSMSG\", \"@+\"), \"@+\")","def patch(self, id):\n try:\n task = update_status(get_db(), id, Status[api.payload[\"status\"]])\n if not task:\n api.abort(404, \"Invalid Task\")\n return task_to_dict(task)\n except ValueError:\n api.abort(422, \"Invalid Status\")","def test_parse_task_time(self):\n ret = parse_task_time(\"asdf:adsf\")\n self.assertEqual(None, ret)\n\n ret = parse_task_time('\\n')\n self.assertEqual(None, ret)","def state_name(self):\n return TASK_STATE.get(self.state, 'UNKNOWN')","def parse_task_assign_msg(msg_str: str) -> TaskAssignMessage:\n return __parse_message_as(TaskAssignMessage, msg_str)","def status(self):\n if self.to_phone:\n phone = '(%s) %s - %s' % (self.to_phone[:3], self.to_phone[3:6], self.to_phone[6:])\n else:\n phone = ''\n\n name = self.to_name if self.to_name else ''\n\n return ' poll in %ds | %s | %s ' % (self.step, name, phone)","def set_status_(self, task: Task):\n tic = time.time()\n self._database[task.name] = tic\n self.save()\n return self","def test_in_sync_status_emoji(self):\n self.assertEqual(get_emoji_for_status('IN_SYNC'), \":heavy_check_mark:\")"],"string":"[\n \"def task_status():\\n pass\",\n \"def task_status(self) -> str:\\n return self._task_status\",\n \"async def get_task_status(task_id: TaskId):\",\n \"def fuota_task_status(self) -> Optional[str]:\\n return pulumi.get(self, \\\"fuota_task_status\\\")\",\n \"def _parse_status(self, status):\\n if status in (STATUS_FINISHED, 'FINISHED'):\\n return STATUS_FINISHED\\n elif status in (STATUS_ERROR, 'ERROR'):\\n return STATUS_ERROR\\n elif status in (STATUS_CANCELED, 'CANCELED'):\\n return STATUS_CANCELED\\n return STATUS_STARTED\",\n \"def parse_filter_unlabelled(task_output):\\n task_list = []\\n for item in task_output:\\n item = item.split(\\\",\\\")\\n if len(item) == 3:\\n if check_status(item):\\n task_list.append(item)\\n\\n return task_list\",\n \"def _validate_task(task: str) -> str:\\n supported = (\\\"regression\\\", \\\"binary\\\")\\n if not any([task in item for item in supported]):\\n raise ValueError(f\\\"{task} is not a supported task.\\\")\\n return task\",\n \"def mesos_status(self, submissionId):\\n get_tasks = self.driver.getTasks()['get_tasks']\\n task_state = None\\n\\n tasks = get_tasks['tasks'] + get_tasks.get('completed_tasks')\\n tasks_list = list(filter(lambda x: x['task_id']['value'] == submissionId, tasks))\\n if len(tasks_list) > 0:\\n task = tasks_list[0]\\n task_state = task['state']\\n self._log.debug(\\\"Task state = \\\" + task_state)\\n else:\\n self._log.debug(\\\"Task not found\\\")\\n\\n return task_state\",\n \"def Get_Status(n, way):\\n s = n.split(way)\\n if len(s) > 1:\\n return \\\"1\\\"\\n else:\\n return \\\"0\\\"\",\n \"def getNodeTaskStatusByUPID(self,node,upid):\\n data = self.connect('get','nodes/%s/tasks/%s/status' % (node,upid),None)\\n return data\",\n \"def _get_instructor_task_status(task_id):\\r\\n instructor_task = get_updated_instructor_task(task_id)\\r\\n status = get_status_from_instructor_task(instructor_task)\\r\\n if instructor_task is not None and instructor_task.task_state in STATES_WITH_STATUS:\\r\\n succeeded, message = get_task_completion_info(instructor_task)\\r\\n status['message'] = message\\r\\n status['succeeded'] = succeeded\\r\\n return status\",\n \"def get_task_status(task_id):\\r\\n mock_request = Mock()\\r\\n mock_request.REQUEST = {'task_id': task_id}\\r\\n response = instructor_task_status(mock_request)\\r\\n status = json.loads(response.content)\\r\\n return status\",\n \"def parse_task(task: str) -> tuple[int, int]:\\n parts = task.strip().split()\\n return int(parts[0]), int(parts[6])\",\n \"def status_str(status):\\n\\n status_map = {\\n 0: 'MATCH',\\n 10: 'OK',\\n 15: 'SKIP',\\n 20: 'FAIL',\\n 30: 'CRASH'\\n }\\n return status_map.get(status, 'UNKNOWN')\",\n \"def _decode_sensor_status(self, status: str) -> str:\\n k = int(status)\\n return self.SENSOR_STATUSES[k]\",\n \"def get_status_from_instructor_task(instructor_task):\\r\\n status = {}\\r\\n\\r\\n if instructor_task is not None:\\r\\n # status basic information matching what's stored in InstructorTask:\\r\\n status['task_id'] = instructor_task.task_id\\r\\n status['task_state'] = instructor_task.task_state\\r\\n status['in_progress'] = instructor_task.task_state not in READY_STATES\\r\\n if instructor_task.task_output is not None:\\r\\n status['task_progress'] = json.loads(instructor_task.task_output)\\r\\n\\r\\n return status\",\n \"def task_status(self, task_status: str):\\n if task_status is None:\\n raise ValueError(\\\"Invalid value for `task_status`, must not be `None`\\\") # noqa: E501\\n\\n self._task_status = task_status\",\n \"def parse_completed(self, in_str):\\n if not in_str:\\n self.completed = False\\n elif in_str.lower() == \\\"x\\\":\\n self.completed = True\\n else:\\n self.completed = False\",\n \"def _status_to_state(status):\\n if status == 'failed':\\n return Finding.State.ACTIVE\\n elif status == 'passed' or status == 'skipped':\\n return Finding.State.INACTIVE\\n else:\\n return Finding.State.STATE_UNSPECIFIED\",\n \"def status2word(self,status):\\n if status == 'T':\\n return \\\"Toggle\\\"\\n elif status == 'S':\\n return \\\"Signature\\\"\\n elif status == 'R':\\n return \\\"Random\\\"\\n elif status == 'N':\\n return \\\"Normal\\\"\\n elif status == 'E':\\n return \\\"FE Error\\\"\\n elif status == 'X':\\n return \\\"NO TIN\\\"\\n else:\\n print \\\"Unknown status !\\\"\\n return \\\"BUG\\\"\",\n \"def task_state(task_id):\\n tag_task = parse_html_tags.AsyncResult(task_id)\\n return jsonify({'task_id': task_id, 'task_state': tag_task.state,\\n 'result_url': url_for('task_result', task_id=tag_task.id)}), 202, {}\",\n \"def status_to_event_code(status: str):\\n return {\\n \\\"sent\\\": \\\"txSent\\\",\\n \\\"pending\\\": \\\"txPool\\\",\\n \\\"pending-simulation\\\": \\\"txPoolSimulation\\\",\\n \\\"stuck\\\": \\\"txStuck\\\",\\n \\\"confirmed\\\": \\\"txConfirmed\\\",\\n \\\"failed\\\": \\\"txFailed\\\",\\n \\\"speedup\\\": \\\"txSpeedUp\\\",\\n \\\"cancel\\\": \\\"txCancel\\\",\\n \\\"dropped\\\": \\\"txDropped\\\",\\n }[status]\",\n \"def work_status(value):\\n for status in models.WORK_STATUS:\\n if status[0]==value:\\n return status[1]\\n\\n return \\\"WORK STATUS NOT FOUND\\\"\",\n \"def convert_to_rp_status(behave_status):\\n if behave_status == \\\"passed\\\":\\n return \\\"PASSED\\\"\\n elif behave_status == \\\"failed\\\":\\n return \\\"FAILED\\\"\\n elif behave_status == \\\"skipped\\\":\\n return \\\"SKIPPED\\\"\\n else:\\n # todo define what to do\\n return \\\"PASSED\\\"\",\n \"def get_task_status(id):\\n # obtain the task and validate it\\n global background_tasks\\n rv = background_tasks.get(id)\\n if rv is None:\\n return not_found(None)\\n\\n # if the task object is a Thread object that means that the task is still\\n # running. In this case return the 202 status message again.\\n if isinstance(rv, Thread):\\n return jsonify({}), 202, {'Location': url_for('get_task_status', id=id)}\\n\\n # If the task object is not a Thread then it is assumed to be the response\\n # of the finished task, so that is the response that is returned.\\n # If the application is configured to auto-delete task status resources once\\n # the task is done then the deletion happens now, if not the client is\\n # expected to send a delete request.\\n if app.config['AUTO_DELETE_BG_TASKS']:\\n del background_tasks[id]\\n return rv\",\n \"def check_indicator_files(tasks):\\n\\n for task in tasks:\\n if task[\\\"status\\\"]==\\\"unknown\\\":\\n if os.path.exists(task[\\\"result\\\"]):\\n task[\\\"status\\\"]=\\\"previously completed\\\"\\n else:\\n task[\\\"status\\\"]=\\\"to do\\\"\\n return\",\n \"def check_task(self): \\n return self.buffer[0]\",\n \"def update_task_status(project_id, task_id):\\n completion_status = request.get_json()['completion_status']\\n\\n project = Project.query.filter_by(id=project_id).first()\\n if not project:\\n return {\\n 'success': False,\\n 'message': f\\\"No project with the specified id {project_id} found.\\\",\\n }\\n \\n else:\\n permission = has_project_permission(project, g.user)\\n task = Task.query.filter_by(id=task_id).first()\\n if not task:\\n abort(404, f'There is no task with ID of {task_id}.')\\n if task:\\n task.completion_status = completion_status\\n db_session.add(task)\\n db_session.commit()\\n return {\\n 'success': True,\\n 'result': task_schema.dump(task),\\n 'message': f\\\"Successfully Updated the Completion Status of {task.name}.\\\"\\n }\",\n \"def getJobStatusStr(status):\\n if not isinstance(status, int):\\n return ''\\n\\n return JobUtils.JOB_STATUS.get(status, '')\",\n \"def container_status(self):\\n if self.status == 'complete':\\n return 'complete'\\n try:\\n task_status = self._ecs.describe_tasks(tasks=[self.name])['tasks'][0]['lastStatus']\\n return task_status\\n except (IndexError, ClientError):\\n return 'STOPPED'\",\n \"def getStatus(self, blTaskName, statusFile=None, statusFamilyType='status'):\\n\\n # fill the filename\\n filename = str(statusFile)\\n\\n if not blTaskName:\\n raise CrabException('Exception while getting the task unique name')\\n return ''\\n\\n # get the data and fill the file content\\n statusMsg = self.asSession.getTaskStatus(statusFamilyType, blTaskName)\\n if 'Error:' in statusMsg[:6] or len(statusMsg)==0:\\n if statusFamilyType != 'isServerDrained':\\n raise CrabException('Error in retrieving task %s status from server %s'%(self.crab_task_name, self.serverName) )\\n else:\\n statusFile = None\\n statusMMsg = \\\"\\\"\\n\\n if statusFile is not None:\\n f = open(statusFile, 'w')\\n f.write(statusMsg)\\n f.close()\\n return statusFile\\n return statusMsg\",\n \"def valid_status(cls, status_str):\\n status_str = status_str.upper()\\n if status_str not in [\\\"OPEN\\\", \\\"CLOSED\\\"]:\\n raise ValueError(f\\\"invalid ticket status '{status_str}'\\\")\\n return status_str\",\n \"def _reverted_task_status(task_audit, revert_before):\\n task = Task.objects.get(id=task_audit['task']['id'])\\n\\n flattened_iterations = [\\n iteration_audit\\n for assignment_audit in task_audit['assignments']\\n for iteration_audit in assignment_audit['iterations']]\\n changed_items = _parse_changed_items(flattened_iterations, 'iteration')\\n\\n latest_iterations = (\\n get_iteration_history(task, reverse=True)\\n .exclude(id__in=changed_items[RevertChange.DELETED.value]))\\n\\n num_iterations = latest_iterations.count()\\n if num_iterations == 0:\\n return Task.Status.AWAITING_PROCESSING\\n elif revert_before:\\n # Reverting before the first iteration in an assignment means the task\\n # is pending review, since at least one iteration exists\\n return Task.Status.PENDING_REVIEW\\n else:\\n # Revert to a processing iteration state\\n if num_iterations == 1:\\n return Task.Status.PROCESSING\\n else:\\n previous_status = latest_iterations[1].status\\n if previous_status == Iteration.Status.REQUESTED_REVIEW:\\n return Task.Status.REVIEWING\\n else:\\n return Task.Status.POST_REVIEW_PROCESSING\",\n \"def _get_status(self):\\n return u'%s' % (self.get_status_display())\",\n \"def _format_task_summary(task_summary: _TaskSummary) -> str:\\n lookup = { # noqa: DAR101, DAR201\\n _TaskExitCode.PASS: (fg.green, 'was successful'),\\n _TaskExitCode.FAIL: (fg.red, 'failed'),\\n _TaskExitCode.NOT_RUN: (fg.white, 'was not run'),\\n _TaskExitCode.SKIP_IGNORED: (fg.yellow, 'was ignored'),\\n _TaskExitCode.SKIP_UP_TO_DATE: (fg.yellow, 'was skipped'),\\n }\\n foreground, exit_summary = lookup.get(task_summary.exit_code, ('', 'is UNKNOWN'))\\n return f'{foreground}{task_summary.name} {exit_summary}' + fg.rs\",\n \"def parse_homework_status(homework: Dict) -> str:\\n homework_name = homework[0].get(\\\"homework_name\\\")\\n statuses = {\\n \\\"rejected\\\": \\\"К сожалению в работе нашлись ошибки.\\\",\\n \\\"reviewed\\\": \\\"Проект взят в работу ревьювером.\\\",\\n \\\"approved\\\": (\\n \\\"Ревьюеру всё понравилось, можно приступать к следующему уроку.\\\"\\n ),\\n }\\n return (\\n f'У вас проверили работу \\\"{homework_name}\\\"!\\\\n\\\\n'\\n f'{statuses[homework[0].get(\\\"status\\\")]}'\\n )\",\n \"def task_scanned(now_task):\",\n \"def solve(task: str, preamble_length: int = 25) -> int:\\n data = [int(num) for num in task.strip().split(\\\"\\\\n\\\")]\\n return first_invalid(data, preamble_length)\",\n \"def __repr__(self):\\r\\n return 'SubtaskStatus<%r>' % (self.to_dict(),)\",\n \"def status(a):\\n return a\",\n \"async def rndactivity_parse(self, ctx: commands.Context, *, status: str):\\n shard = getattr(ctx.guild, \\\"shard_id\\\", 0)\\n\\n try:\\n result, result_type = self.format_status(status, shard=shard)\\n except KeyError as e:\\n await fmt(\\n ctx,\\n warning(\\n _(\\n \\\"Placeholder {placeholder} does not exist\\\\n\\\\n\\\"\\n \\\"See `{prefix}help rndactivity add` for the list of placeholder strings\\\"\\n )\\n ),\\n placeholder=escape(str(e), mass_mentions=True),\\n )\\n else:\\n await fmt(\\n ctx,\\n _(\\\"\\\\N{INBOX TRAY} **Input:**\\\\n{input}\\\\n\\\\N{OUTBOX TRAY} **Result:** {result}\\\"),\\n input=escape(status, mass_mentions=True),\\n result=escape(result, mass_mentions=True),\\n )\",\n \"def task_format_check():\\n return {\\\"actions\\\": [[\\\"black\\\", HERE, \\\"--check\\\"]], \\\"verbosity\\\": 1}\",\n \"def _parse_json_to_status_update(self, json_message):\\n if len(json_message['failing']) > 0:\\n return BuildStatusUpdate(BuildStatus.Failing)\\n elif len(json_message['acknowledged']) > 0:\\n return BuildStatusUpdate(BuildStatus.Acknowledged)\\n else:\\n return BuildStatusUpdate(BuildStatus.Passing)\",\n \"def state_to_task(self, states):\\n tasks = states\\n return tasks\",\n \"def retrieve_task(self, task_id):\\n r = requests.get('/'.join([self.base_url, self.ENDPOINT_TASK_STATUS,\\n str(task_id)]))\\n return r.json()\",\n \"def get_tasks_ids_by_status(self, status=\\\"Done\\\"):\\n if status not in (\\\"Done\\\", \\\"Paused\\\", \\\"Running\\\", \\\"Stopped\\\"):\\n raise ValueError(\\\"Requested status are not allowed\\\")\\n\\n\\n m_task_ids = {}\\n\\n for x in self.get_tasks().findall(\\\"task\\\"):\\n if x.find(\\\"status\\\").text == status:\\n m_task_ids[x.find(\\\"name\\\").text] = x.attrib[\\\"id\\\"]\\n\\n return m_task_ids\",\n \"def find_task(self, task_str):\\n task_str = task_str.replace('é', 'e').title()\\n task_not_found = True\\n custom_quest = False\\n if \\\":\\\" in task_str:\\n task_strs = task_str.split(\\\":\\\")\\n task_str = task_strs[0]\\n quest_str = task_strs[1]\\n custom_quest = True\\n while task_not_found:\\n for task in self.tasks:\\n if (task_str == task.reward.title()) or (task_str == task.quest.replace('é', 'e').title()) or (task_str in (reward.title() for reward in task.rewards)) or (task_str in (nickname.title() for nickname in task.nicknames)):\\n out_task = task\\n task_not_found = False\\n if custom_quest:\\n out_task = copy.copy(task)\\n out_task.quest = quest_str.title()\\n return out_task\\n break\\n if task_not_found:\\n raise TaskNotFound()\",\n \"def status_class(status):\\n status = status.split('-')[-1] # e.g. \\\"overall-passed\\\" -> \\\"passed\\\"\\n classes = {\\n 'passed': 'success',\\n 'failed': 'danger',\\n 'skipped': 'warning',\\n 'match': 'success',\\n 'diff': 'danger',\\n 'missing': 'warning',\\n 'generated': 'warning',\\n }\\n return classes[status]\",\n \"def get_completed_tasks_in_tod():\\n try:\\n tod_file_data = load_data(os.getenv('TOD_FP'))\\n except FileNotFoundError:\\n return []\\n completed_tasks = []\\n tod_file_data = tod_file_data.split('\\\\n')\\n\\n for line in tod_file_data:\\n if line == '' or line[0] != '[' or line[1] != 'X':\\n continue\\n completed_task = (f\\\"{line[4:-7]} {line[-6:]}\\\"\\n if line[-6:] != '(0:00)'\\n else line[4:-7])\\n completed_tasks.append(completed_task)\\n\\n return completed_tasks\",\n \"def extract_human_name_from_task(self, task_xml):\\r\\n tree = etree.fromstring(task_xml)\\r\\n payload = tree.xpath(\\\"/openended/openendedparam/grader_payload\\\")\\r\\n if len(payload) == 0:\\r\\n task_name = \\\"selfassessment\\\"\\r\\n else:\\r\\n inner_payload = json.loads(payload[0].text)\\r\\n task_name = inner_payload['grader_settings']\\r\\n\\r\\n human_task = HUMAN_TASK_TYPE[task_name]\\r\\n return human_task\",\n \"def my_update_subtask_status(entry_id, current_task_id, new_subtask_status):\\r\\n entry = InstructorTask.objects.get(pk=entry_id)\\r\\n subtask_dict = json.loads(entry.subtasks)\\r\\n subtask_status_info = subtask_dict['status']\\r\\n current_subtask_status = SubtaskStatus.from_dict(subtask_status_info[current_task_id])\\r\\n current_retry_count = current_subtask_status.get_retry_count()\\r\\n new_retry_count = new_subtask_status.get_retry_count()\\r\\n if current_retry_count <= new_retry_count:\\r\\n update_subtask_status(entry_id, current_task_id, new_subtask_status)\",\n \"def tasks_to_html_table(tasks):\\n s = \\\"\\\"\\n s += \\\"<table>\\\\n\\\"\\n status_seen = []\\n for i,task in enumerate(tasks):\\n s += \\\"<tr><td>\\\"\\n\\n if task[\\\"status\\\"] not in status_seen:\\n status_seen.append(task[\\\"status\\\"])\\n s += \\\"<a name=\\\\\\\"%s\\\\\\\"></a>\\\"%(task[\\\"status\\\"])\\n \\n s += \\\"%i.</td>\\\"%(i+1)\\n s += \\\"<td>%s</td>\\\"%task[\\\"command\\\"]\\n stl = \\\"color:%s\\\"%status_colors.get(task[\\\"status\\\"],\\\"gray\\\")\\n details = \\\"\\\"\\n if task[\\\"status\\\"]==\\\"running\\\":\\n if \\\"started\\\" in list(task.keys()):\\n details = \\\" [started %s]\\\"%task[\\\"started\\\"]\\n \\n if task[\\\"status\\\"]==\\\"completed\\\" or task[\\\"status\\\"]==\\\"previously completed\\\":\\n if \\\"finished\\\" in list(task.keys()):\\n details += \\\" [%s]\\\"%task[\\\"finished\\\"]\\n if \\\"duration\\\" in list(task.keys()):\\n details += \\\" %.2f hours\\\"%(task[\\\"duration\\\"]/3600.)\\n s += \\\"<td style=\\\\\\\"%s\\\\\\\">%s %s</td>\\\"%(stl,task[\\\"status\\\"],details)\\n if \\\"logfname\\\" in list(task.keys()):\\n s += \\\"<td><a href=\\\\\\\"%s\\\\\\\">log</a></td>\\\"%task[\\\"logfname\\\"]\\n s += \\\"</tr>\\\\n\\\"\\n\\n s += \\\"</table>\\\\n\\\"\\n return s\",\n \"def get_status(self):\\n if self._is_running():\\n return \\\"RUNNING\\\"\\n elif self._has_error():\\n # The run started but failed\\n return \\\"FAILED\\\"\\n elif self._is_finished():\\n # The run was finished\\n return \\\"FINISHED\\\"\\n elif self.current_step() >= 0:\\n # The run started at some point but was not completed\\n return \\\"INCOMPLETE\\\"\\n else:\\n # The run did not start\\n return \\\"NOT STARTED\\\"\",\n \"def _update_subtask_status(entry_id, current_task_id, new_subtask_status):\\r\\n TASK_LOG.info(\\\"Preparing to update status for subtask %s for instructor task %d with status %s\\\",\\r\\n current_task_id, entry_id, new_subtask_status)\\r\\n\\r\\n try:\\r\\n entry = InstructorTask.objects.select_for_update().get(pk=entry_id)\\r\\n subtask_dict = json.loads(entry.subtasks)\\r\\n subtask_status_info = subtask_dict['status']\\r\\n if current_task_id not in subtask_status_info:\\r\\n # unexpected error -- raise an exception\\r\\n format_str = \\\"Unexpected task_id '{}': unable to update status for subtask of instructor task '{}'\\\"\\r\\n msg = format_str.format(current_task_id, entry_id)\\r\\n TASK_LOG.warning(msg)\\r\\n raise ValueError(msg)\\r\\n\\r\\n # Update status:\\r\\n subtask_status_info[current_task_id] = new_subtask_status.to_dict()\\r\\n\\r\\n # Update the parent task progress.\\r\\n # Set the estimate of duration, but only if it\\r\\n # increases. Clock skew between time() returned by different machines\\r\\n # may result in non-monotonic values for duration.\\r\\n task_progress = json.loads(entry.task_output)\\r\\n start_time = task_progress['start_time']\\r\\n prev_duration = task_progress['duration_ms']\\r\\n new_duration = int((time() - start_time) * 1000)\\r\\n task_progress['duration_ms'] = max(prev_duration, new_duration)\\r\\n\\r\\n # Update counts only when subtask is done.\\r\\n # In future, we can make this more responsive by updating status\\r\\n # between retries, by comparing counts that change from previous\\r\\n # retry.\\r\\n new_state = new_subtask_status.state\\r\\n if new_subtask_status is not None and new_state in READY_STATES:\\r\\n for statname in ['attempted', 'succeeded', 'failed', 'skipped']:\\r\\n task_progress[statname] += getattr(new_subtask_status, statname)\\r\\n\\r\\n # Figure out if we're actually done (i.e. this is the last task to complete).\\r\\n # This is easier if we just maintain a counter, rather than scanning the\\r\\n # entire new_subtask_status dict.\\r\\n if new_state == SUCCESS:\\r\\n subtask_dict['succeeded'] += 1\\r\\n elif new_state in READY_STATES:\\r\\n subtask_dict['failed'] += 1\\r\\n num_remaining = subtask_dict['total'] - subtask_dict['succeeded'] - subtask_dict['failed']\\r\\n\\r\\n # If we're done with the last task, update the parent status to indicate that.\\r\\n # At present, we mark the task as having succeeded. In future, we should see\\r\\n # if there was a catastrophic failure that occurred, and figure out how to\\r\\n # report that here.\\r\\n if num_remaining <= 0:\\r\\n entry.task_state = SUCCESS\\r\\n entry.subtasks = json.dumps(subtask_dict)\\r\\n entry.task_output = InstructorTask.create_output_for_success(task_progress)\\r\\n\\r\\n TASK_LOG.debug(\\\"about to save....\\\")\\r\\n entry.save()\\r\\n TASK_LOG.info(\\\"Task output updated to %s for subtask %s of instructor task %d\\\",\\r\\n entry.task_output, current_task_id, entry_id)\\r\\n except Exception:\\r\\n TASK_LOG.exception(\\\"Unexpected error while updating InstructorTask.\\\")\\r\\n transaction.rollback()\\r\\n dog_stats_api.increment('instructor_task.subtask.update_exception')\\r\\n raise\\r\\n else:\\r\\n TASK_LOG.debug(\\\"about to commit....\\\")\\r\\n transaction.commit()\",\n \"def __str__(self):\\n return self.task\",\n \"def _format_terminated_task(tinfo: TerminatedTaskInfo) -> str:\\n status = []\\n if tinfo.cancelled:\\n status.append(\\\"cancelled\\\")\\n if tinfo.exc_repr and not tinfo.cancelled:\\n status.append(f\\\"exc={tinfo.exc_repr}\\\")\\n return f\\\"<TerminatedTask name={tinfo.name} coro={tinfo.coro} {' '.join(status)}>\\\"\",\n \"def format_status(report_status: Status) -> str:\\n if report_status in (Status.FAILED, Status.ERROR):\\n return Status.FAILED.title()\\n return report_status.title()\",\n \"def get_short_task_id(task_id: str) -> str:\\n return task_id.split(MESOS_TASK_SPACER)[-1]\",\n \"def task_format():\\n print(HERE)\\n return {\\\"actions\\\": [\\\"isort -y \\\", [\\\"black\\\", HERE]], \\\"verbosity\\\": 1}\",\n \"def get_status_as_string(self):\\n if self.downloaded == 0:\\n return \\\"[Starting... ]\\\"\\n return \\\"[%s, %s, %s]\\\" % self.get_status()\",\n \"def test_convert_video_status(self):\\n video = self.previous_uploads[0]\\n\\n # video status should be failed if it's in upload state for more than 24 hours\\n video['created'] = datetime(2016, 1, 1, 10, 10, 10, 0, pytz.UTC)\\n status = convert_video_status(video)\\n self.assertEqual(status, StatusDisplayStrings.get('upload_failed'))\\n\\n # `invalid_token` should be converted to `youtube_duplicate`\\n video['created'] = datetime.now(pytz.UTC)\\n video['status'] = 'invalid_token'\\n status = convert_video_status(video)\\n self.assertEqual(status, StatusDisplayStrings.get('youtube_duplicate'))\\n\\n # The \\\"encode status\\\" should be converted to `file_complete` if video encodes are complete\\n video['status'] = 'transcription_in_progress'\\n status = convert_video_status(video, is_video_encodes_ready=True)\\n self.assertEqual(status, StatusDisplayStrings.get('file_complete'))\\n\\n # If encoding is not complete return the status as it is\\n video['status'] = 's3_upload_failed'\\n status = convert_video_status(video)\\n self.assertEqual(status, StatusDisplayStrings.get('s3_upload_failed'))\\n\\n # for all other status, there should not be any conversion\\n statuses = list(StatusDisplayStrings._STATUS_MAP.keys()) # pylint: disable=protected-access\\n statuses.remove('invalid_token')\\n for status in statuses:\\n video['status'] = status\\n new_status = convert_video_status(video)\\n self.assertEqual(new_status, StatusDisplayStrings.get(status))\",\n \"def task_failed(task_state):\\n return task_state in {\\\"TASK_LOST\\\", \\\"TASK_KILLED\\\", \\\"TASK_FAILED\\\", \\\"TASK_TERMINATING\\\"}\",\n \"def label_transformation(self, ind_task, label):\\n\\n # if self.disjoint class 0 of second task become class 10, class 1 -> class 11, ...\\n if self.disjoint_classes:\\n label = label + self.num_classes * ind_task\\n\\n return label\",\n \"def instructor_task_status(request):\\r\\n output = {}\\r\\n if 'task_id' in request.REQUEST:\\r\\n task_id = request.REQUEST['task_id']\\r\\n output = _get_instructor_task_status(task_id)\\r\\n elif 'task_ids[]' in request.REQUEST:\\r\\n tasks = request.REQUEST.getlist('task_ids[]')\\r\\n for task_id in tasks:\\r\\n task_output = _get_instructor_task_status(task_id)\\r\\n if task_output is not None:\\r\\n output[task_id] = task_output\\r\\n\\r\\n return HttpResponse(json.dumps(output, indent=4))\",\n \"def task(self) -> str:\\n return self._task\",\n \"def read_all_status_characters(self):\\n return self.STATUS_CHARACTERS\",\n \"def status_check(task_id):\\n logger.info(f\\\"Checking task status for {task_id}\\\")\\n task = Task.objects.get(kf_id=task_id)\\n task.status_check()\",\n \"def get_status(id):\\n task = run_ctx_request.AsyncResult(id)\\n if task.state == states.PENDING:\\n abort(404)\\n if task.state == states.RECEIVED or task.state == states.STARTED:\\n return '', 202, {'Location': url_for('api.get_status', id=id)}\\n return task.info\",\n \"def grip_status_to_str(status):\\n return 'gACT:{}, gGTO:{}, gSTA:{}, gOBJ:{}, ' \\\\\\n 'gFLT:{}, gPR:{}, gPO:{}, gCU:{}'.format(\\n status.gACT,\\n status.gGTO,\\n status.gSTA,\\n status.gOBJ,\\n status.gFLT,\\n status.gPR,\\n status.gPO,\\n status.gCU\\n )\",\n \"def status(self):\\n return STATUS[self.fields['status']]\",\n \"def task_is_failure(task):\\n\\n if task and task.state == 'FAILURE':\\n return True\\n return False\",\n \"def taskStatus(self, task_id, timeout=90, log_progress=True):\\n start = time.time()\\n elapsed = 0\\n last_check = 0\\n while True:\\n elapsed = time.time() - start\\n status = ee.data.getTaskStatus(task_id)[0]\\n state = status['state']\\n if state in TASK_FINISHED_STATES:\\n error_message = status.get('error_message', None)\\n print('Task %s ended at state: %s after %.2f seconds'\\n % (task_id, state, elapsed))\\n if error_message:\\n raise ValueError(error_message)\\n return\\n if log_progress and elapsed - last_check >= 30:\\n print('[{:%H:%M:%S}] Current state for task {}: {}'\\n .format(datetime.now(), task_id, state))\\n last_check = elapsed\\n remaining = timeout - elapsed\\n if remaining > 0:\\n time.sleep(min(10, remaining))\\n else:\\n break\\n print('Wait for task %s timed out after %.2f seconds' % (task_id, elapsed))\",\n \"def custom_wait_for_completion(task_description, output):\\n state = 'UNSUBMITTED'\\n while not (state == 'COMPLETED' or state =='FAILED'):\\n output.add_live_msg(ms.STATUS.format(state))\\n time.sleep(5)\\n \\n #search for the task in task_list\\n for task in task_description:\\n current_task = gs.isTask(task)\\n if current_task:\\n state = current_task.state\\n if state == 'RUNNING' or state == 'FAILED': \\n break\\n \\n return state\",\n \"def show_tasks_status(user, tasks):\\n employee_name = user[0]['username']\\n all_tasks = tasks\\n completed = 0\\n title_completed_tasks = ''\\n for task in all_tasks:\\n if task['completed'] is True:\\n completed += 1\\n title_completed_tasks += '\\\\t ' + task['title'] + '\\\\n'\\n print('Employee {} is done with tasks({}/{}):'\\n .format(employee_name, completed, len(all_tasks)))\\n print(title_completed_tasks, end='')\",\n \"def _cleanTask(task, org_admin):\\n\\n errors = []\\n\\n # check title\\n if not task['title']:\\n errors.append('No valid title present.')\\n\\n # clean description\\n try:\\n cleaner = HtmlSanitizer.Cleaner()\\n cleaner.string = task['description']\\n cleaner.clean()\\n task['description'] = cleaner.string.strip().replace('\\\\r\\\\n', '\\\\n') \\n except (HTMLParseError, safe_html.IllegalHTML, TypeError), e:\\n logging.warning('Cleaning of description failed with: %s' %e)\\n errors.append(\\n 'Failed to clean the description, do not use naughty HTML such as '\\n '<script>.')\\n\\n # clean time to complete\\n try:\\n task['time_to_complete'] = int(task['time_to_complete'])\\n except (ValueError, TypeError), e:\\n errors.append('No valid time to completion found, given was: %s.' \\n %task['time_to_complete'])\\n\\n # clean mentors\\n mentor_ids = set(task['mentors'].split(','))\\n\\n mentor_fields = {'scope': org_admin.scope,\\n 'status': 'active'}\\n mentors = []\\n for mentor_id in mentor_ids:\\n mentor_fields['link_id'] = mentor_id.strip()\\n mentor = mentor_logic.getForFields(mentor_fields, unique=True)\\n if mentor:\\n mentors.append(mentor.key())\\n else:\\n errors.append('%s is not a mentor.' %mentor_id)\\n\\n task['mentors'] = mentors\\n\\n program_entity = org_admin.program\\n\\n # clean task difficulty\\n difficulty = task['difficulty'].strip()\\n allowed_difficulties = [\\n str(x) for x in \\n task_model.TaskDifficultyTag.get_by_scope(program_entity)]\\n if not difficulty or difficulty not in allowed_difficulties:\\n # no valid difficulty found\\n errors.append('No valid task difficulty found, given %s.' %difficulty)\\n else:\\n task['difficulty'] = {\\n 'tags': task['difficulty'],\\n 'scope': program_entity\\n }\\n\\n # clean task types\\n task_types = []\\n allowed_types = [\\n str(x) for x in task_model.TaskTypeTag.get_by_scope(program_entity)]\\n for task_type in set(task['task_type'].split(',')):\\n task_type = task_type.strip()\\n if task_type in allowed_types:\\n task_types.append(task_type)\\n else:\\n errors.append('%s is not a valid task type.' %task_type)\\n\\n task['task_type'] = {\\n 'tags': task_types,\\n 'scope': program_entity\\n }\\n\\n # clean task tags\\n arbit_tags = []\\n for tag in set(task['arbit_tag'].split(',')):\\n arbit_tags.append(tag.strip())\\n task['arbit_tag'] = {\\n 'tags': arbit_tags,\\n 'scope': program_entity\\n }\\n\\n return errors\",\n \"def get_job_status(self, mission):\\n\\n # initialize task status\\n status = dict(active=0, running=0, succeeded=0, failed=0)\\n\\n # get job status if it exists. Otherwise, return N/A\\n try:\\n the_job = self.batch_client.job.get(job_id=mission.job_name)\\n\\n # get counts of tasks in different statuses\\n status_counts = self.batch_client.job.get_task_counts(mission.job_name)\\n except azure.batch.models.BatchErrorException as err:\\n if err.message.value.startswith(\\\"The specified job does not exist\\\"):\\n return \\\"N/A\\\", status\\n # raise an exception for other kinds of errors\\n raise\\n\\n # update the dictionary\\n status[\\\"active\\\"] = status_counts.active\\n status[\\\"running\\\"] = status_counts.running\\n status[\\\"succeeded\\\"] = status_counts.succeeded\\n status[\\\"failed\\\"] = status_counts.failed\\n\\n return the_job.state.name, status\",\n \"def get_roof_status_from_tcs():\\n\\t\\n\\ttarget = send_command('getstatus dome')\\n\\tsplit_ans = target.split()\\n\\t\\n\\treturn split_ans\",\n \"def test_translated_names(self):\\r\\n func = lambda t: t.upper()\\r\\n # status is in the mapping\\r\\n statobj = inputtypes.Status('queued', func)\\r\\n self.assertEqual(statobj.display_name, u'PROCESSING')\\r\\n\\r\\n # status is not in the mapping\\r\\n statobj = inputtypes.Status('test', func)\\r\\n self.assertEqual(statobj.display_name, u'test')\\r\\n self.assertEqual(str(statobj), 'test')\\r\\n self.assertEqual(statobj.classname, 'test')\",\n \"def dummy_update_subtask_status(entry_id, _current_task_id, new_subtask_status):\\r\\n bogus_task_id = \\\"this-is-bogus\\\"\\r\\n update_subtask_status(entry_id, bogus_task_id, new_subtask_status)\",\n \"def tasks_by_status(self) -> Dict[TaskStatus, Sequence[str]]:\\n out = {}\\n for key in self.task_graph.keys():\\n info = self.task_graph.get_info(key)\\n out.setdefault(info.status, []).append(key)\\n return out\",\n \"def port_status_from_hex(hex_status):\\n hexmap = {1: 'ESTABLISHED',\\n 2: 'TCP_SYN_SENT',\\n 3: 'TCP_SYN_RECV',\\n 4: 'TCP_FIN_WAIT1',\\n 5: 'TCP_FIN_WAIT2',\\n 6: 'TCP_TIME_WAIT',\\n 7: 'TCP_CLOSE',\\n 8: 'TCP_CLOSE_WAIT',\\n 9: 'TCP_LAST_ACK',\\n 10: 'TCP_LISTEN',\\n 11: 'TCP_CLOSING',\\n 12: 'TCP_MAX_STATES'}\\n\\n return hexmap(int(hex_status, 16))\",\n \"def getStatusString(self, statClass=None):\\n return self.convertStatus(self.getStatus(statClass=statClass))\",\n \"def get_status(self):\\n # find status\\n # search in summary file first\\n self.status = \\\"running\\\"\\n status = self.search_summary(\\\"status\\\")\\n if status:\\n self.status = status.split()[1]\\n # define running time\\n # search in summary file first\\n self.running_time = \\\"00:00:00\\\"\\n running_time = self.search_summary(\\\"running-time\\\")\\n if running_time:\\n self.running_time = running_time.split()[1]\\n # calculate running time\\n else:\\n now = datetime.datetime.now()\\n elapsed_time = (now - self.ctime).seconds\\n hours, remainder = divmod(elapsed_time, 3600)\\n minutes, seconds = divmod(remainder, 60)\\n self.running_time = (\\n f\\\"{int(hours):02}:{int(minutes):02}:{int(seconds):02}\\\"\\n )\",\n \"def taskbystatus(self, **kwargs):\\n rows = self.api.query(None, None, self.Task.TaskByStatus_sql, username_=kwargs[\\\"username\\\"], taskstatus=kwargs[\\\"taskstatus\\\"])\\n\\n return rows\",\n \"async def get_status():\",\n \"def status(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"status\\\")\",\n \"def status(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"status\\\")\",\n \"def TaskState(self):\\n return symbol_by_name(\\\"etools_datamart.apps.etl.models.EtlTask\\\")\",\n \"def is_task_stagnant(task):\",\n \"def get_status(pos, neg, names):\\n status = {}\\n for i in names:\\n #print str(i) +'\\\\n'+ str(pos) +'\\\\n'+ str(neg)+'\\\\n'+'\\\\n'\\n if i in pos:\\n status[i] = \\\"1\\\"\\n elif i in neg:\\n status[i] = \\\"0\\\"\\n else:\\n status[i] = \\\"NA\\\"\\n return status\",\n \"async def get_status(self) -> dict[str, Any]:\\n\\n def check_int(s):\\n if s[0] in (\\\"-\\\", \\\"+\\\"):\\n return s[1:].isdigit()\\n return s.isdigit()\\n\\n cmd = await self.send_command(\\\"STATUS\\\", timeout=1)\\n if not cmd.succeeded():\\n raise ArchonError(f\\\"Command finished with status {cmd.status.name!r}\\\")\\n\\n keywords = str(cmd.replies[0].reply).split()\\n status = {\\n key.lower(): int(value) if check_int(value) else float(value)\\n for (key, value) in map(lambda k: k.split(\\\"=\\\"), keywords)\\n }\\n\\n return status\",\n \"def GetTaskPriority(cls, task):\\n if not task: return None\\n\\n task = cls.TaskRelativeName(task)\\n\\n priority = ''\\n parts = task.split(os.sep)\\n for part in parts:\\n priority_name = part.split('_', 1)\\n if len(priority_name) < 2 or not priority_name[0].isdigit(): return None\\n priority += priority_name[0]\\n return priority\",\n \"def test_support_STATUSMSG(self):\\n self.assertEqual(self._parseFeature(\\\"STATUSMSG\\\", \\\"@+\\\"), \\\"@+\\\")\",\n \"def patch(self, id):\\n try:\\n task = update_status(get_db(), id, Status[api.payload[\\\"status\\\"]])\\n if not task:\\n api.abort(404, \\\"Invalid Task\\\")\\n return task_to_dict(task)\\n except ValueError:\\n api.abort(422, \\\"Invalid Status\\\")\",\n \"def test_parse_task_time(self):\\n ret = parse_task_time(\\\"asdf:adsf\\\")\\n self.assertEqual(None, ret)\\n\\n ret = parse_task_time('\\\\n')\\n self.assertEqual(None, ret)\",\n \"def state_name(self):\\n return TASK_STATE.get(self.state, 'UNKNOWN')\",\n \"def parse_task_assign_msg(msg_str: str) -> TaskAssignMessage:\\n return __parse_message_as(TaskAssignMessage, msg_str)\",\n \"def status(self):\\n if self.to_phone:\\n phone = '(%s) %s - %s' % (self.to_phone[:3], self.to_phone[3:6], self.to_phone[6:])\\n else:\\n phone = ''\\n\\n name = self.to_name if self.to_name else ''\\n\\n return ' poll in %ds | %s | %s ' % (self.step, name, phone)\",\n \"def set_status_(self, task: Task):\\n tic = time.time()\\n self._database[task.name] = tic\\n self.save()\\n return self\",\n \"def test_in_sync_status_emoji(self):\\n self.assertEqual(get_emoji_for_status('IN_SYNC'), \\\":heavy_check_mark:\\\")\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6113151","0.60610837","0.5982466","0.58361703","0.5676092","0.562448","0.5620659","0.5590581","0.5534794","0.5493304","0.5449712","0.5449053","0.5443019","0.54307556","0.54105866","0.53677195","0.5367107","0.53506756","0.53475046","0.5340073","0.5264325","0.5222125","0.51682514","0.51476747","0.5141771","0.513566","0.5119017","0.5108635","0.5072759","0.50602585","0.5058419","0.50374365","0.49623173","0.49450022","0.49286106","0.49077767","0.49048042","0.48904416","0.48885012","0.48601913","0.4841493","0.48401016","0.48252484","0.48229092","0.48182195","0.48162442","0.4814464","0.48134065","0.48025504","0.4798425","0.47960705","0.47914627","0.47775686","0.47567046","0.47503996","0.47380742","0.47360262","0.47351393","0.47268957","0.47219774","0.47140658","0.47082213","0.4698546","0.46958822","0.46935388","0.4692173","0.46877998","0.46820265","0.46808377","0.467802","0.46723667","0.46517825","0.4650797","0.4650247","0.46492964","0.4648305","0.46437186","0.46401688","0.4638168","0.4634527","0.463343","0.46322274","0.46279442","0.4616618","0.46152407","0.46135688","0.46135688","0.46117646","0.46078104","0.45957997","0.45917356","0.4587843","0.4587035","0.4580304","0.45779786","0.45774052","0.45655748","0.45618194","0.45578626","0.455486"],"string":"[\n \"0.6113151\",\n \"0.60610837\",\n \"0.5982466\",\n \"0.58361703\",\n \"0.5676092\",\n \"0.562448\",\n \"0.5620659\",\n \"0.5590581\",\n \"0.5534794\",\n \"0.5493304\",\n \"0.5449712\",\n \"0.5449053\",\n \"0.5443019\",\n \"0.54307556\",\n \"0.54105866\",\n \"0.53677195\",\n \"0.5367107\",\n \"0.53506756\",\n \"0.53475046\",\n \"0.5340073\",\n \"0.5264325\",\n \"0.5222125\",\n \"0.51682514\",\n \"0.51476747\",\n \"0.5141771\",\n \"0.513566\",\n \"0.5119017\",\n \"0.5108635\",\n \"0.5072759\",\n \"0.50602585\",\n \"0.5058419\",\n \"0.50374365\",\n \"0.49623173\",\n \"0.49450022\",\n \"0.49286106\",\n \"0.49077767\",\n \"0.49048042\",\n \"0.48904416\",\n \"0.48885012\",\n \"0.48601913\",\n \"0.4841493\",\n \"0.48401016\",\n \"0.48252484\",\n \"0.48229092\",\n \"0.48182195\",\n \"0.48162442\",\n \"0.4814464\",\n \"0.48134065\",\n \"0.48025504\",\n \"0.4798425\",\n \"0.47960705\",\n \"0.47914627\",\n \"0.47775686\",\n \"0.47567046\",\n \"0.47503996\",\n \"0.47380742\",\n \"0.47360262\",\n \"0.47351393\",\n \"0.47268957\",\n \"0.47219774\",\n \"0.47140658\",\n \"0.47082213\",\n \"0.4698546\",\n \"0.46958822\",\n \"0.46935388\",\n \"0.4692173\",\n \"0.46877998\",\n \"0.46820265\",\n \"0.46808377\",\n \"0.467802\",\n \"0.46723667\",\n \"0.46517825\",\n \"0.4650797\",\n \"0.4650247\",\n \"0.46492964\",\n \"0.4648305\",\n \"0.46437186\",\n \"0.46401688\",\n \"0.4638168\",\n \"0.4634527\",\n \"0.463343\",\n \"0.46322274\",\n \"0.46279442\",\n \"0.4616618\",\n \"0.46152407\",\n \"0.46135688\",\n \"0.46135688\",\n \"0.46117646\",\n \"0.46078104\",\n \"0.45957997\",\n \"0.45917356\",\n \"0.4587843\",\n \"0.4587035\",\n \"0.4580304\",\n \"0.45779786\",\n \"0.45774052\",\n \"0.45655748\",\n \"0.45618194\",\n \"0.45578626\",\n \"0.455486\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7188169"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88559,"cells":{"query":{"kind":"string","value":"Slices a panel once at an angle into two new panels"},"document":{"kind":"string","value":"def single_slice_panels(page,\n horizontal_vertical=None,\n type_choice=None,\n skew_side=None,\n number_to_slice=0\n ):\n\n # Remove panels which are too small\n relevant_panels = []\n if len(page.children) > 0:\n get_min_area_panels(page,\n cfg.slice_minimum_panel_area,\n ret_panels=relevant_panels\n )\n else:\n relevant_panels = [page]\n\n # Shuffle panels for randomness\n random.shuffle(relevant_panels)\n\n # single slice close\n if type_choice is None:\n type_choice_prob = np.random.random()\n if type_choice_prob < cfg.center_side_ratio:\n type_choice = \"center\"\n else:\n type_choice = \"side\"\n\n num_panels_added = 0\n\n # Slice panels down the center\n if type_choice == \"center\":\n if len(relevant_panels) < 1:\n return page\n\n if number_to_slice == 0:\n if len(relevant_panels) > 1:\n number_to_slice = np.random.randint(1, len(relevant_panels))\n else:\n number_to_slice = 1\n\n for idx in range(0, number_to_slice):\n panel = relevant_panels[idx]\n num_panels_added += 1\n\n # Decide which direction to cut in\n if horizontal_vertical is None:\n horizontal_vertical = np.random.choice([\"h\", \"v\"])\n\n # Get center line\n # Vertical slice\n if horizontal_vertical == \"v\":\n panel_chosen_coord_length = (panel.x2y2[0] - panel.x1y1[0])/2\n\n # Slice panel\n draw_n(2, panel, \"v\")\n\n # Skew it left or right\n if skew_side is None:\n skew_side = np.random.choice([\"left\", \"right\"])\n\n # Skew it by a percentage\n skew_amount = np.random.randint(20, 100)/100\n skew_amount = skew_amount*panel_chosen_coord_length\n\n # Perform transform\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n\n p1.sliced = True\n p2.sliced = True\n if skew_side == \"left\":\n p1.x2y2 = (p1.x2y2[0] - skew_amount, p1.x2y2[1])\n p1.x3y3 = (p1.x3y3[0] + skew_amount, p1.x3y3[1])\n\n p1.refresh_coords()\n\n p2.x1y1 = (p2.x1y1[0] - skew_amount, p2.x1y1[1])\n p2.x4y4 = (p2.x4y4[0] + skew_amount, p2.x4y4[1])\n\n p2.refresh_coords()\n\n elif skew_side == \"right\":\n p1.x2y2 = (p1.x2y2[0] + skew_amount, p1.x2y2[1])\n p1.x3y3 = (p1.x3y3[0] - skew_amount, p1.x3y3[1])\n\n p1.refresh_coords()\n\n p2.x1y1 = (p2.x1y1[0] + skew_amount, p2.x1y1[1])\n p2.x4y4 = (p2.x4y4[0] - skew_amount, p2.x4y4[1])\n\n p2.refresh_coords()\n\n else:\n print(\"Chosen incorrect skew side\")\n return None\n\n # Horizontal slice\n else:\n panel_chosen_coord_length = (panel.x3y3[1] - panel.x2y2[1])/2\n\n # Slice panel\n draw_n(2, panel, \"h\")\n\n # Skew it left or right\n if skew_side is None:\n skew_side = np.random.choice([\"down\", \"up\"])\n\n # Skew it by a percentage\n skew_amount = np.random.randint(20, 100)/100\n skew_amount = skew_amount*panel_chosen_coord_length\n\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n\n p1.sliced = True\n p2.sliced = True\n if skew_side == \"down\":\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] + skew_amount)\n p1.x3y3 = (p1.x3y3[0], p1.x3y3[1] - skew_amount)\n\n p1.refresh_coords()\n\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] + skew_amount)\n p2.x2y2 = (p2.x2y2[0], p2.x2y2[1] - skew_amount)\n\n p2.refresh_coords()\n\n elif skew_side == \"up\":\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] - skew_amount)\n p1.x3y3 = (p1.x3y3[0], p1.x3y3[1] + skew_amount)\n\n p1.refresh_coords()\n\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] - skew_amount)\n p2.x2y2 = (p2.x2y2[0], p2.x2y2[1] + skew_amount)\n\n p2.refresh_coords()\n else:\n print(\"Chose incorrect skew_side\")\n\n # Slice panel sides\n else:\n if len(relevant_panels) < 1:\n return page\n\n if number_to_slice == 0:\n if len(relevant_panels) > 1:\n number_to_slice = np.random.choice([1, 3])\n else:\n number_to_slice = 1\n\n for panel in relevant_panels[0:number_to_slice]:\n\n if skew_side is None:\n skew_side = np.random.choice([\"tr\", \"tl\", \"br\", \"bl\"])\n\n draw_n(2, panel, \"h\")\n num_panels_added += 1\n\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n\n # Panels are non standard polygons\n p1.non_rect = True\n p2.non_rect = True\n\n p1.sliced = True\n p2.sliced = True\n\n cut_y_proportion = np.random.randint(25, 75)/100\n cut_x_proportion = np.random.randint(25, 75)/100\n\n cut_y_length = (panel.x4y4[1] - panel.x1y1[1])*cut_y_proportion\n cut_x_length = (panel.x3y3[0] - panel.x4y4[0])*cut_x_proportion\n\n # bottom left corner\n if skew_side == \"bl\":\n\n p1_cut_x1y1 = (panel.x4y4[0], panel.x4y4[1] - cut_y_length)\n p1_cut_x2y2 = (panel.x4y4[0] + cut_x_length, panel.x4y4[1])\n p1_cut_x3y3 = (panel.x4y4)\n\n p1.coords = [p1_cut_x1y1, p1_cut_x2y2,\n p1_cut_x3y3, p1_cut_x1y1]\n\n p2.coords = [panel.x1y1, panel.x2y2, panel.x3y3,\n p1_cut_x2y2, p1_cut_x1y1, panel.x1y1]\n\n # bottom right corner\n elif skew_side == \"br\":\n\n p1_cut_x1y1 = (panel.x3y3[0], panel.x3y3[1] - cut_y_length)\n p1_cut_x2y2 = (panel.x3y3)\n p1_cut_x3y3 = (panel.x3y3[0] - cut_x_length, panel.x3y3[1])\n\n p1.coords = [p1_cut_x1y1, p1_cut_x2y2,\n p1_cut_x3y3, p1_cut_x1y1]\n\n p2.coords = [panel.x1y1, panel.x2y2, p1_cut_x1y1,\n p1_cut_x3y3, panel.x4y4, panel.x1y1]\n\n # top left corner\n elif skew_side == \"tl\":\n\n p1_cut_x1y1 = panel.x1y1\n p1_cut_x2y2 = (panel.x1y1[0] + cut_x_length, panel.x1y1[1])\n p1_cut_x3y3 = (panel.x1y1[0], panel.x1y1[1] + cut_y_length)\n\n p1.coords = [p1_cut_x1y1, p1_cut_x2y2,\n p1_cut_x3y3, p1_cut_x1y1]\n p2.coords = [p1_cut_x2y2, panel.x2y2, panel.x3y3,\n panel.x4y4, p1_cut_x3y3, p1_cut_x1y1]\n\n # top right corner\n elif skew_side == \"tr\":\n p1_cut_x1y1 = (panel.x2y2[0] - cut_x_length, panel.x2y2[1])\n p1_cut_x2y2 = panel.x2y2\n p1_cut_x3y3 = (panel.x2y2[0], panel.x2y2[1] + cut_y_length)\n\n p1.coords = [p1_cut_x1y1, p1_cut_x2y2,\n p1_cut_x3y3, p1_cut_x1y1]\n\n p2.coords = [panel.x1y1, p1_cut_x1y1, p1_cut_x3y3,\n panel.x3y3, panel.x4y4, panel.x1y1]\n else:\n print(\"Chose incorrect skew side\")\n return None\n\n page.num_panels += num_panels_added\n\n return page"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _slice_at_axis(sl, axis):\n return (slice(None),) * axis + (sl,) + (...,)","def animate_slices_multi(field='uu1', datadir1='data/', datadir2='data/', proc=-1, extension='xz',\n format='native', tmin=0., tmax=1.e38, wait=0.,\n amin=0., amax=1., transform='', oldfile=False,\n makemovie=False):\n\n import pylab as plt\n\n datadir1 = os.path.expanduser(datadir1)\n if proc < 0:\n filename1 = join(datadir1, 'slice_' + field + '.' + extension)\n else:\n filename1 = join(datadir1, 'proc' + str(proc),\n 'slice_' + field + '.' + extension)\n\n datadir2 = os.path.expanduser(datadir2)\n if proc < 0:\n filename2 = join(datadir2, 'slice_' + field + '.' + extension)\n else:\n filename2 = join(datadir2, 'proc' + str(proc),\n 'slice_' + field + '.' + extension)\n\n # Read the global dimensions.\n dim = read_dim(datadir1, proc)\n if dim.precision == 'D':\n precision = 'd'\n else:\n precision = 'f'\n\n # Set up slice plane.\n if extension == 'xy' or extension == 'Xy':\n hsize = dim.nx\n vsize = dim.ny\n if extension == 'xz':\n hsize = dim.nx\n vsize = dim.nz\n if extension == 'yz':\n hsize = dim.ny\n vsize = dim.nz\n plane1 = np.zeros((vsize, hsize), dtype=precision)\n plane2 = np.zeros((vsize, hsize), dtype=precision)\n\n infile1 = npfile(filename1, endian=format)\n infile2 = npfile(filename2, endian=format)\n\n #ax = plt.axes()\n #ax.set_xlabel('')\n #ax.set_ylabel('')\n #ax.set_ylim\n #ax.get_xaxis().set_visible(False)\n #ax.get_yaxis().set_visible(False)\n\n fig, (ax1,ax2) = plt.subplots(1,2)\n #fig.suptitle('Re = 400', fontsize=20)\n image1 = ax1.imshow(plane1, vmin=amin, vmax=amax)\n image2 = ax2.imshow(plane2, vmin=amin, vmax=amax)\n ax1.set_xlabel('')\n ax1.set_ylabel('')\n ax1.get_xaxis().set_visible(False)\n ax1.get_yaxis().set_visible(False)\n ax2.set_xlabel('')\n ax2.set_ylabel('')\n ax2.get_xaxis().set_visible(False)\n ax2.get_yaxis().set_visible(False)\n\n # Get the figure manager for real-time image display.\n manager = plt.get_current_fig_manager()\n manager.show()\n\n ifirst = True\n islice = 0\n files = []\n\n while True:\n try:\n raw_data1 = infile1.fort_read(precision)\n raw_data2 = infile2.fort_read(precision)\n except ValueError:\n break\n except TypeError:\n break\n\n if oldfile:\n t = raw_data1[-1]\n plane1 = raw_data1[:-1].reshape(vsize, hsize)\n plane2 = raw_data2[:-1].reshape(vsize, hsize)\n else:\n t = raw_data1[-2]\n plane1 = raw_data1[:-2].reshape(vsize, hsize)\n plane2 = raw_data2[:-2].reshape(vsize, hsize)\n\n if transform:\n exec('plane = plane' + transform)\n\n if t > tmin and t < tmax:\n title = 't = %11.3e' % t\n #fig.set_title(title)\n image1.set_data(plane1)\n image2.set_data(plane2)\n manager.canvas.draw()\n\n if ifirst:\n #print \"----islice----------t---------min-------max-------delta\" # Python 2\n print(\"----islice----------t---------min-------max-------delta\")\n #print \"%10i %10.3e %10.3e %10.3e %10.3e\" \\ # Python 2\n #% (islice, t, plane.min(), plane.max(), plane.max() - plane.min()) # Python 2\n print(\"{0:10} {1:10.3e} {2:10.3e} {3:10.3e} {4:10.3e}\".format(islice, t, plane1.min(), plane1.max(), plane1.max() - plane1.min()))\n\n if(makemovie):\n fname = '_tmp%03d.png' % islice\n fig.savefig(fname)\n files.append(fname)\n\n ifirst = False\n islice += 1\n\n sleep(wait)\n\n infile1.close()\n infile2.close()\n\n if(makemovie):\n print('Making movie animation.mpg - this make take a while')\n # SC: Not all systems use mencoder. Need to change this into ffmpeg.\n os.system(\"mencoder 'mf://_tmp*.png' -mf type=png:fps=24 -ovc lavc -lavcopts vcodec=wmv2 -oac copy -o animation.mpg\")\n os.system(\"rm _tmp*.png\")","def get_2D_slices(atlas: str):\n if atlas == \"avg\":\n AVGT, metaAVGT = nrr.read(\"nrrd/average_template_10.nrrd\")\n folder = \"avg\"\n elif atlas == \"nissl\":\n AVGT, metaAVGT = nrr.read(\"nrrd/ara_nissl_10.nrrd\")\n folder = \"nissl\"\n else:\n raise Exception(\"Wrong argument for var atlas\")\n\n degress = [i for i in range(-15, 16, 3)]\n\n for degree in tqdm(degress):\n rotated = rot(AVGT, angle=degree, mode=\"nearest\", order=0, reshape=True)\n print(degree)\n for plate_no in tqdm(range(300, 1300, 5)):\n save_img(rotated[plate_no], folder=folder, plate_no=plate_no, degree=degree)","def get_slice(P1, P2, name):\n \n centre_dist = distance_3D(P1, P2)\n plot_img = np.zeros((ceil(centre_dist / 2. + 1), centre_dist + 2 ))\n Xrange = np.arange(-centre_dist / 4., centre_dist / 4. + 1)\n \n # time goes along the vector between P1 and P2\n # since it might be at an angle, I can't loop in 1\n # pixel increments - this will miss certain slices. Therefore,\n # I need to loop through by 1/cosA, where A is angle between\n # the xy plane and vector P1->P2\n sampling = sample_rate(P1, P2)\n \n for time in np.linspace(0, centre_dist + 1,\n centre_dist * sampling):\n # Go up along the line\n new_pt = vector_3D(P1, P2, time)\n old_pt = vector_3D(P1, P2, time - centre_dist / 2. * sampling)\n\n if time == 0:\n input_file = name % int(round(new_pt[2], 0))\n img = io.imread(input_file)\n \n # Check if the previous slice is the same as the next\n # don't load it again if it is - save computation time\n if int(round(new_pt[2], 0)) != int(round(old_pt[2], 0)):\n \n input_file = name % int(round(new_pt[2], 0))\n img = io.imread(input_file)\n \n for X in Xrange:\n \n # Get along the X direction for every height\n x, y, z = vector_perpendicular_3D(new_pt, P2, 1, 0, X)\n \n pixel_value = interpolation(x, y, img)\n \n plot_img[X + centre_dist / 4., time] = pixel_value\n else:\n for X in Xrange:\n \n # Get along the X direction for every height\n x, y, z = vector_perpendicular_3D(new_pt, P2, 1, 0, X)\n\n pixel_value = interpolation(x, y, img)\n \n plot_img[X + centre_dist / 4., time] = pixel_value\n \n return plot_img","def splitLayer(self, src, dire):\n\n (rowN, colN) = src.shape\n res = []\n ## UNSURE ABOUT SLICING\n if (dire == self.VERTICAL):\n # range(start, stop, step)\n for i in range(0, rowN - self.slideThickness, self.slideThickness):\n # croping is much easier in Python, it is basically just slicing\n tmp = src[i:i+self.slideThickness, 0:colN]\n \n res.append(tmp)\n\n else:\n\n for i in range(0, colN - self.slideThickness, self.slideThickness):\n # croping is much easier in Python, it is basically just slicing\n tmp = src[0:self.slideThickness, i:i+rowN]\n res.append(tmp)\n\n return res","def alternatingSlice(self,geom,polyLayer,targetArea,granularity,direction,method):\r\n global recurs\r\n recurs+=1\r\n if self.debug: print \"******************************\"\r\n if self.debug: print \"Slicing, No of part: \",str(recurs)\r\n if self.debug: print \"Slicing, Granularity remaining: \", str(granularity)\r\n bbox=[geom.boundingBox().xMinimum(),geom.boundingBox().yMinimum(),geom.boundingBox().xMaximum(),geom.boundingBox().yMaximum()]\r\n if direction==\"h\":\r\n step=(bbox[2]-bbox[0])/granularity\r\n pointer=bbox[0]\r\n else:\r\n step=(bbox[3]-bbox[1])/granularity\r\n pointer=bbox[1]\r\n totalArea=0\r\n slices=0\r\n #save the original geom\r\n tempGeom=QgsGeometry(geom)\r\n #start slicing until targetArea is reached\r\n while totalArea<targetArea*0.999:\r\n pointer+=step\r\n if direction==\"h\":\r\n startPt=QgsPoint(pointer,bbox[1])\r\n endPt=QgsPoint(pointer,bbox[3])\r\n (multiGeom,tempGeom)=self.cutPoly(tempGeom,startPt,endPt)\r\n else:\r\n startPt=QgsPoint(bbox[0],pointer)\r\n endPt=QgsPoint(bbox[2],pointer)\r\n (tempGeom,multiGeom)=self.cutPoly(tempGeom,startPt,endPt)\r\n if multiGeom!=None:\r\n totalArea+=multiGeom.area();\r\n slices+=1\r\n if self.debug: print \"Slicing, Slices: \", str(slices)\r\n #do the real cutting when reached targetArea and add \"left\" feature to layer\r\n if self.debug: print \"Cutting with line, Cutline:\", startPt,\",\",endPt\r\n if direction==\"h\":\r\n (multiGeom,geom)=self.cutPoly(geom,startPt,endPt,True)\r\n if multiGeom:\r\n if self.debug: print \"After split, Parts to the left:\",str(len(multiGeom.asGeometryCollection()))\r\n if geom:\r\n if self.debug: print \"After split, Parts to the right:\",str(len(geom.asGeometryCollection()))\r\n else:\r\n (geom,multiGeom)=self.cutPoly(geom,startPt,endPt,True)\r\n if geom:\r\n if self.debug: print \"After split, Parts above:\",str(len(geom.asGeometryCollection()))\r\n if multiGeom:\r\n if self.debug: print \"After split, Parts under:\",str(len(multiGeom.asGeometryCollection()))\r\n self.addGeomToLayer(multiGeom,polyLayer)\r\n #self.addGeomToLayer(QgsGeometry.fromPolyline([startPt,endPt]),lineLayer)\r\n if geom:\r\n if geom.area()>targetArea:\r\n if (method==\"v\") or ((method==\"a\") and (direction==\"h\")):\r\n self.alternatingSlice(geom,polyLayer,targetArea,granularity-slices,\"v\",method)\r\n else:\r\n self.alternatingSlice(geom,polyLayer,targetArea,granularity-slices,\"h\",method)\r\n else:\r\n self.addGeomToLayer(geom,polyLayer)","def __slicer(self, bg, ol, tgPng):\n cmd = 'slicer ' + bg + ' '\n if ol != None:\n cmd += ol + ' '\n cmd += '-a ' + tgPng\n self.launchCommand(cmd)","def make_panel_in_array(array_elt, reference_panel):\n\n px_size = tuple((e / 3.0) for e in reference_panel.get_pixel_size())\n ref_panel_size = reference_panel.get_image_size_mm()\n x_shift = array_elt[0] * ref_panel_size[0] / 3.0\n y_shift = array_elt[1] * ref_panel_size[1] / 3.0\n origin = (\n matrix.col(reference_panel.get_origin())\n + x_shift * matrix.col(reference_panel.get_fast_axis())\n + y_shift * matrix.col(reference_panel.get_slow_axis())\n )\n return Panel(\n type=\"PAD\",\n name=\"Panel\",\n fast_axis=reference_panel.get_fast_axis(),\n slow_axis=reference_panel.get_slow_axis(),\n origin=origin,\n pixel_size=px_size,\n image_size=reference_panel.get_image_size(),\n trusted_range=(0, 1.0e6),\n thickness=0.0,\n material=\"\",\n )","def rotate2(A, dr, dc):\n def rotate(R, d):\n # Negative slice indices count from the right.\n if d < 0:\n return R[-len(R)-d: ] + R[0: -d]\n else:\n return R[-d:] + R[0: len(R)-d]\n rows = tuple(map(lambda row: rotate(row, dc), A))\n return rotate(rows, dr)","def chain(self,slices):\n for proj in self.projs[::-1]:\n slices = proj(slices)\n return","def reshape(self,bottom,top):\n pass","def slice(\n sample, \n ei, psi_axis,\n hkl0, hkl_dir, x_axis, \n instrument, erange,\n out):\n from mcvine.workflow.sample import loadSampleYml\n sample = loadSampleYml(sample)\n code = \"from mcvine.workflow.DGS import %s as mod\" % instrument\n d = {}; exec(code, d); mod = d['mod']\n psi_angles = np.arange(*tuple(psi_axis))\n x_axis = np.arange(*tuple(x_axis))\n from matplotlib import pyplot as plt\n plt.figure()\n from ...singlextal import dynrange\n dynrange.plotDynRangeOfSlice(\n sample, psi_angles, ei, hkl0, hkl_dir, x_axis,\n mod.scattering_angle_constraints,\n Erange=erange)\n if out:\n plt.savefig(out)\n else:\n plt.show()\n return","def test_slicing_containers(self):\n\n pattern = midi.Pattern()\n pattern.extend([midi.Track()] * 5)\n result1 = pattern[1]\n result2 = pattern[1:5]\n result3 = pattern[::2]\n\n track = midi.Track()\n track.extend([midi.Event()] * 5)\n result1 = track[1]\n result2 = track[1:5]\n result3 = track[::2]","def pie_slice(self, x, y, r, t0, t1, cls=None, style=None):\n tr0 = math.radians(t0)\n tr1 = math.radians(t1)\n x0 = x + r * math.cos(tr0)\n y0 = y + r * math.sin(tr0)\n x1 = x + r * math.cos(tr1)\n y1 = y + r * math.sin(tr1)\n laf = int(abs(t1 - t0) > 180)\n self.path(['M', x, y, 'L', x0, y0, 'A', r, r, 0, laf, 1, x1, y1, 'Z'], cls, style)\n return self","def pie_slice(self, x, y, r, t0, t1, cls=None, style=None):\n tr0 = math.radians(t0)\n tr1 = math.radians(t1)\n x0 = x + r * math.cos(tr0)\n y0 = y + r * math.sin(tr0)\n x1 = x + r * math.cos(tr1)\n y1 = y + r * math.sin(tr1)\n laf = int(abs(t1 - t0) > 180)\n self.path(['M', x, y, 'L', x0, y0, 'A', r, r, 0, laf, 1, x1, y1, 'Z'], cls, style)\n return self","def animate_slices_crossflow(field='uu1', datadir='data/', proc=-1, extension='yz',\n format='native', tmin=0., tmax=1.e38, wait=0.,\n amin=0., amax=1., transform='', oldfile=False):\n\n import pylab as plt\n import matplotlib.patches as ptc\n import matplotlib.ticker as ticker\n\n datadir = os.path.expanduser(datadir)\n if proc < 0:\n filename = join(datadir, 'slice_' + field + '.' + extension)\n else:\n filename = join(datadir, 'proc' + str(proc),\n 'slice_' + field + '.' + extension)\n\n # Read the global dimensions.\n dim = read_dim(datadir, proc)\n if dim.precision == 'D':\n precision = 'd'\n else:\n precision = 'f'\n\n # Set up slice plane.\n if extension == 'xy' or extension == 'Xy':\n hsize = dim.nx\n vsize = dim.ny\n if extension == 'xz':\n hsize = dim.nx\n vsize = dim.nz\n if extension == 'yz':\n hsize = dim.ny\n vsize = dim.nz\n plane = np.zeros((vsize, hsize), dtype=precision)\n\n infile = npfile(filename, endian=format)\n\n ax = plt.axes()\n ax.set_xlabel('y')\n ax.set_ylabel('x')\n ax.set_ylim\n\n\n name_list_x = ('0', '2D', '4D', '6D')\n #name_list_z = ('12D', '10D', '8D', '6D', '4D','2D','0')\n name_list_z = ( '0', '2D', '4D', '6D','8D','10D','12D',)\n pos_list_x = np.array([0,80,160,240])\n pos_list_z = np.array([0,80,160,240,320,400,480])\n\n name_list_x = ('0', '5D', '10D')\n name_list_z = ( '0', '5D', '10D', '15D','20D')\n pos_list_x = np.array([0,159,319])\n pos_list_z = np.array([0,159,319,479,639])\n #pos_list = np.arange(len(name_list))\n\n#ax = plt.axes()\n #ax.xaxis.set_major_locator(ticker.FixedLocator((pos_list_x)))\n #ax.xaxis.set_major_formatter(ticker.FixedFormatter((name_list_x)))\n #ax.yaxis.set_major_locator(ticker.FixedLocator((pos_list_z)))\n #ax.yaxis.set_major_formatter(ticker.FixedFormatter((name_list_z)))\n ax.get_xaxis().set_visible(False)\n ax.get_yaxis().set_visible(False)\n\n\n # turbulent particle sim xy-vew, Ddx=40\n #r=20\n #xy = [120,240]\n# art = ptc.Circle(xy,r,color='black')\n# ax.add_artist(art)\n # uniform flow sim xy-vew, Ddx=64\n # r=16\n # xy = [160,320]\n # Pencil-tests, Re=400, Ddx=96\n #r=48\n #xy = [480,960]\n # Pencil-tests, Re=100, Ddx=64\n r=32\n xy = [320,640]\n art = ptc.Circle(xy,r,color='black')\n ax.add_artist(art)\n \n\n #ax.add_patch(patches.Rectangle(\n # (220,0),\n # 40,\n # 320,\n # color='gray'\n # )\n #)\n\n image = plt.imshow(plane, vmin=amin, vmax=amax)\n\n # Get the figure manager for real-time image display.\n manager = plt.get_current_fig_manager()\n manager.show()\n\n ifirst = True\n islice = 0\n while True:\n try:\n raw_data = infile.fort_read(precision)\n except ValueError:\n break\n except TypeError:\n break\n\n if oldfile:\n t = raw_data[-1]\n plane = raw_data[:-1].reshape(vsize, hsize)\n else:\n t = raw_data[-2]\n plane = raw_data[:-2].reshape(vsize, hsize)\n\n if transform:\n exec('plane = plane' + transform)\n\n if t > tmin and t < tmax:\n #title = 't = %11.3e' % t\n #ax.set_title(title)\n image.set_data(plane)\n manager.canvas.draw()\n\n if ifirst:\n #print \"----islice----------t---------min-------max-------delta\" # Python 2\n print(\"----islice----------t---------min-------max-------delta\")\n #print \"%10i %10.3e %10.3e %10.3e %10.3e\" \\ # Python 2\n #% (islice, t, plane.min(), plane.max(), plane.max() - plane.min()) # Python 2\n print(\"{0:10} {1:10.3e} {2:10.3e} {3:10.3e} {4:10.3e}\".format(islice, t, plane.min(), plane.max(), plane.max() - plane.min()))\n\n ifirst = False\n fname = '_tmp%03d.eps' % islice\n plt.savefig(fname,fonttype=42,\n bbox_inches = 'tight', \n # pad_inches = 0,\n dpi = 600, transparant=True)\n #plt.savefig(fname,fonttype=42)\n islice += 1\n\n sleep(wait)\n\n infile.close()","def _set_view_slice(self):\n nd = self.dims.not_displayed\n\n if self.multichannel:\n # if multichannel need to keep the final axis fixed during the\n # transpose. The index of the final axis depends on how many\n # axes are displayed.\n order = self.dims.displayed_order + (self.dims.ndisplay,)\n else:\n order = self.dims.displayed_order\n\n # Slice thumbnail\n indices = np.array(self.dims.indices)\n downsampled = indices[nd] / self.level_downsamples[-1, nd]\n downsampled = np.round(downsampled.astype(float)).astype(int)\n downsampled = np.clip(downsampled, 0, self.level_shapes[-1, nd] - 1)\n indices[nd] = downsampled\n\n image = np.asarray(self.data[-1][tuple(indices)]).transpose(order)\n\n if self.multichannel and image.dtype.kind == 'f':\n self._data_thumbnail = np.clip(image, 0, 1)\n else:\n self._data_thumbnail = image\n\n # Slice currently viewed level\n indices = np.array(self.dims.indices)\n level = self.data_level\n downsampled = indices[nd] / self.level_downsamples[level, nd]\n downsampled = np.round(downsampled.astype(float)).astype(int)\n downsampled = np.clip(downsampled, 0, self.level_shapes[level, nd] - 1)\n indices[nd] = downsampled\n\n disp_shape = self.level_shapes[level, self.dims.displayed]\n scale = np.ones(self.ndim)\n for d in self.dims.displayed:\n scale[d] = self.level_downsamples[self.data_level][d]\n self._scale = scale\n self.events.scale()\n\n if np.any(disp_shape > self._max_tile_shape):\n for d in self.dims.displayed:\n indices[d] = slice(\n self._top_left[d],\n self._top_left[d] + self._max_tile_shape,\n 1,\n )\n self.translate = self._top_left * self.scale\n else:\n self.translate = [0] * self.ndim\n\n image = np.asarray(self.data[level][tuple(indices)]).transpose(order)\n\n if self.multichannel and image.dtype.kind == 'f':\n self._data_view = np.clip(image, 0, 1)\n else:\n self._data_view = image\n\n self._update_thumbnail()\n self._update_coordinates()\n self.events.set_data()","def box_transform_panels(page, type_choice=None, pattern=None):\n\n if type_choice is None:\n type_choice_prob = np.random.random()\n if type_choice_prob < cfg.panel_box_trapezoid_ratio:\n type_choice = \"trapezoid\"\n else:\n type_choice = \"rhombus\"\n\n if type_choice == \"trapezoid\":\n if page.num_panels > 2:\n\n # Get parent panel which satisfies the criteria for the transform\n relevant_panels = find_parent_with_multiple_children(page, 3)\n\n if len(relevant_panels) > 0:\n if len(relevant_panels) > 1:\n num_panels = np.random.randint(1, len(relevant_panels))\n else:\n num_panels = 1\n\n # For each panel\n for idx in range(0, num_panels):\n panel = relevant_panels[idx]\n\n # Get the three child panels\n # Since panels are created in order\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n p3 = panel.get_child(2)\n\n min_width = math.inf\n min_height = math.inf\n\n # Get the smallest height and width\n for child in [p1, p2, p3]:\n\n if child.width < min_width:\n min_width = child.width\n\n if child.height < min_height:\n min_height = child.height\n\n # Choose trapezoid pattern\n if pattern is None:\n trapezoid_pattern = np.random.choice([\"A\", \"V\"])\n else:\n trapezoid_pattern = pattern\n\n movement_proportion = np.random.randint(\n 10,\n cfg.trapezoid_movement_limit)\n\n # If parent panel is horizontal the children are vertical\n if panel.orientation == \"h\":\n\n # Get how much the lines of the child panels move\n # on the x axis to make the trapezoid\n x_movement = min_width*(movement_proportion/100)\n\n # Make an A pattern horizontally\n if trapezoid_pattern == \"A\":\n\n # Get the coords of the first line to be moved\n line_one_top = (p1.x2y2[0] + x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] - x_movement,\n p1.x3y3[1])\n\n # Move line between child 1 and 2\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n # Get the coords of the second line to be moved\n line_two_top = (p2.x2y2[0] - x_movement,\n p2.x2y2[1])\n line_two_bottom = (p2.x3y3[0] + x_movement,\n p2.x3y3[1])\n\n # Move line two between child 2 and 3\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n\n # Make a V pattern horizontally\n else:\n\n # Get the coords of the first line to be moved\n line_one_top = (p1.x2y2[0] - x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] + x_movement,\n p1.x3y3[1])\n\n # Move line between child 1 and 2\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n # Get the coords of the second line to be moved\n line_two_top = (p2.x2y2[0] + x_movement,\n p2.x2y2[1])\n\n line_two_bottom = (p2.x3y3[0] - x_movement,\n p2.x3y3[1])\n\n # Move line two between child 2 and 3\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n\n # If panel is vertical children are horizontal\n # so the A and the V are at 90 degrees to the page\n else:\n # Get how much the lines of the child panels move\n # on the y axis to make the trapezoid\n y_movement = min_height*(movement_proportion/100)\n\n # Make an A pattern vertically\n if trapezoid_pattern == \"A\":\n\n # Get the coords of the first line to be moved\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] + y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] - y_movement)\n\n # Move line between child 1 and 2\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n\n # Get the coords of the second line to be moved\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] - y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] + y_movement)\n\n # Move line two between child 2 and 3\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n # Make a V pattern vertically\n else:\n\n # Get the coords of the first line to be moved\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] - y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] + y_movement)\n\n # Move line between child 1 and 2\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n # Get the coords of the second line to be moved\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] + y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] - y_movement)\n\n # Move line two between child 2 and 3\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n\n elif type_choice == \"rhombus\":\n\n if page.num_panels > 1:\n\n # Get parent panel which satisfies the criteria for the transform\n relevant_panels = find_parent_with_multiple_children(page, 3)\n\n if len(relevant_panels) > 0:\n\n if len(relevant_panels) > 1:\n num_panels = np.random.randint(1, len(relevant_panels))\n else:\n num_panels = 1\n\n for idx in range(0, num_panels):\n\n panel = relevant_panels[idx]\n\n # Since panels are created in order\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n p3 = panel.get_child(2)\n\n min_width = math.inf\n min_height = math.inf\n\n # Get the smallest height and width\n for child in [p1, p2, p3]:\n\n if child.width < min_width:\n min_width = child.width\n\n if child.height < min_height:\n min_height = child.height\n\n if pattern is None:\n rhombus_pattern = np.random.choice([\"left\", \"right\"])\n else:\n rhombus_pattern = pattern\n\n movement_proportion = np.random.randint(\n 10,\n cfg.rhombus_movement_limit\n )\n\n # Logic for the section below is the same as the\n # trapezoid with the exception of the fact that the\n # rhombus pattern happens to move both lines in the\n # same direction\n\n if panel.orientation == \"h\":\n\n x_movement = min_width*(movement_proportion/100)\n\n if rhombus_pattern == \"left\":\n line_one_top = (p1.x2y2[0] - x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] + x_movement,\n p1.x3y3[1])\n\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n line_two_top = (p2.x2y2[0] - x_movement,\n p2.x2y2[1])\n\n line_two_bottom = (p2.x3y3[0] + x_movement,\n p2.x3y3[1])\n\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n\n else:\n\n line_one_top = (p1.x2y2[0] + x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] - x_movement,\n p1.x3y3[1])\n\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n line_two_top = (p2.x2y2[0] + x_movement,\n p2.x2y2[1])\n\n line_two_bottom = (p2.x3y3[0] - x_movement,\n p2.x3y3[1])\n\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n else:\n y_movement = min_height*(movement_proportion/100)\n\n if rhombus_pattern == \"right\":\n\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] + y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] - y_movement)\n\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] + y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] - y_movement)\n\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n else:\n\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] - y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] + y_movement)\n\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] - y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] + y_movement)\n\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n\n return page","def part2(mem):\n panels = paint_panels(mem, 1)\n min_x, min_y, max_x, max_y = tuple(\n f(k[i] for k in panels.keys()) for f in (min, max) for i in (0, 1)\n )\n drawing = [[\" \"] * (max_x - min_x + 1) for _ in range(min_y, max_y + 1)]\n for (x, y), col in panels.items():\n if col:\n drawing[y][x] = \"\\u2588\"\n return \"\\n\".join(f\" {''.join(line)}\" for line in drawing)","def make_fwd_slice(shape, slices, reverse=None, cull_second=True):\n if reverse is None:\n reverse = []\n if not isinstance(shape, (list, tuple, np.ndarray)):\n shape = [shape]\n if not isinstance(slices, (list, tuple)):\n slices = [slices]\n if not isinstance(reverse, (list, tuple)):\n reverse = [reverse]\n\n newax_inds = [i for i, x in enumerate(slices) if x == np.newaxis]\n shape = list(shape)\n for i in newax_inds:\n shape.insert(i, 1)\n\n # ya know, lets just go through all the dimensions in shape\n # just to be safe and default to an empty slice / no reverse\n slices = slices + [slice(None)] * (len(shape) - len(slices))\n reverse = reverse + [False] * (len(slices) - len(reverse))\n\n first_slc = [slice(None)] * len(slices)\n second_slc = [slice(None, None, 1)] * len(first_slc)\n\n for i, slc, L, rev in izip(count(), slices, shape, reverse):\n if isinstance(slc, slice):\n step = slc.step if slc.step is not None else 1\n start = slc.start if slc.start is not None else 0\n stop = slc.stop if slc.stop is not None else L\n if start < 0:\n start += L\n if stop < 0:\n stop += L\n\n # sanity check the start/stop since we're gunna be playing\n # fast and loose with them\n if start < 0 or stop < 0:\n raise IndexError(\"((start = {0}) or (stop = {1})) < 0\"\n \"\".format(start, stop))\n if start > L or stop > L:\n raise IndexError(\"((start={0}) or (stop={1})) > (L={2})\"\n \"\".format(start, stop, L))\n\n # now do the math of flipping the slice if needed, these branches\n # change start, stop, and step so they can be used to create a new\n # slice below\n if rev:\n if step < 0:\n step = -step\n if slc.start is None:\n start = L - 1\n if slc.stop is None:\n start = L - 1 - start\n stop = None\n else:\n start, stop = L - 1 - start, L - 1 - stop\n else:\n start, stop = L - stop, L - start\n start += ((stop - 1 - start) % step)\n second_slc[i] = slice(None, None, -1)\n elif step < 0:\n step = -step\n if slc.start is None:\n start = L - 1\n\n if slc.stop is None:\n start, stop = 0, start + 1\n start = ((stop - 1 - start) % step)\n else:\n start, stop = stop + 1, start + 1\n start += ((stop - 1 - start) % step)\n\n second_slc[i] = slice(None, None, -1)\n\n # check that our slice is valid\n assert start is None or (0 <= start and start <= L), \\\n \"start (={0}) is outside range\".format(start)\n assert start is None or (0 <= start and start <= L), \\\n \"start (={0}) is outside range\".format(start)\n assert start is None or stop is None or start < stop, \\\n \"bad slice ordering: {0} !< {1}\".format(start, stop)\n assert step > 0\n slc = slice(start, stop, step)\n\n elif isinstance(slc, (int, np.integer)):\n second_slc[i] = None\n if rev:\n slc = (L - 1) - slc\n\n elif slc == np.newaxis:\n second_slc[i] = \"NEWAXIS\"\n\n first_slc[i] = slc\n\n first_slc = [s for s in first_slc if s is not np.newaxis]\n if cull_second:\n second_slc = [s for s in second_slc if s is not None]\n second_slc = [np.newaxis if s == \"NEWAXIS\" else s for s in second_slc]\n return first_slc, second_slc","def slide(x1, y1, x2, y2):\n gui.mouseDown(x1, y1)\n gui.moveTo(x2, y2)\n release()","def _independent_panel(width, height):\n\n from maya import cmds\n\n # center panel on screen\n screen_width, screen_height = _get_screen_size()\n topLeft = [int((screen_height-height)/2.0),\n int((screen_width-width)/2.0)]\n\n window = cmds.window(width=width,\n height=height,\n topLeftCorner=topLeft,\n menuBarVisible=False,\n titleBar=False)\n cmds.paneLayout()\n panel = cmds.modelPanel(menuBarVisible=False,\n label='CapturePanel')\n\n # Hide icons under panel menus\n bar_layout = cmds.modelPanel(panel, q=True, barLayout=True)\n cmds.frameLayout(bar_layout, e=True, collapse=True)\n\n cmds.showWindow(window)\n\n # Set the modelEditor of the modelPanel as the active view so it takes\n # the playback focus. Does seem redundant with the `refresh` added in.\n editor = cmds.modelPanel(panel, query=True, modelEditor=True)\n cmds.modelEditor(editor, e=1, activeView=True)\n\n # Force a draw refresh of Maya so it keeps focus on the new panel\n # This focus is required to force preview playback in the independent panel\n cmds.refresh(force=True)\n\n try:\n yield panel\n finally:\n # Delete the panel to fix memory leak (about 5 mb per capture)\n cmds.deleteUI(panel, panel=True)\n cmds.deleteUI(window)","def DrawPanel(screen, panel_x, panel_y, panel_len, panel_width):\n pygame.draw.rect(screen, (255,0,0),(panel_x, panel_y, panel_len*2, panel_width*2), 4)","def slice(self, s=0, e=0):\r\n self.p = self.p[s:e]\r\n self.r = self.r[s:e]\r\n self.alpha = self.alpha[s:e]\r\n self.v = self.v[s:e]\r\n self.w = self.w[s:e]\r\n self.a = self.a[s:e]","def split_window(num_x, num_y):\n\n viewPorts = np.zeros((num_x*num_y, 4))\n counter = 0\n for i in range(num_x):\n for j in range(num_y):\n viewPorts[num_x*j + i, :] = [i*(1.0/float(num_x)),\n 1.0 - (j+1.0)*(1.0/float(num_y)),\n (i+1.0)*1.0/float(num_x),\n 1.0 - j*(1.0/float(num_y))\n ] # [num_y*i + j,:] for vertical fill first\n\n return viewPorts","def reshape(self, bottom, top):\r\n pass","def UnsplitDClick(self, part, sash_size, pos):\r\n\r\n if not self._sash_dclick_unsplit:\r\n # Unsplit not allowed\r\n return\r\n\r\n pos1 = wx.Point(*pos)\r\n pos2 = wx.Point(*pos)\r\n if part.orientation == wx.HORIZONTAL:\r\n pos1.y -= 2*sash_size\r\n pos2.y += 2*sash_size + self.GetTabCtrlHeight()\r\n elif part.orientation == wx.VERTICAL:\r\n pos1.x -= 2*sash_size\r\n pos2.x += 2*sash_size\r\n else:\r\n raise Exception(\"Invalid UI part orientation\")\r\n\r\n pos1, pos2 = self.ClientToScreen(pos1), self.ClientToScreen(pos2)\r\n win1, win2 = wx.FindWindowAtPoint(pos1), wx.FindWindowAtPoint(pos2)\r\n\r\n if isinstance(win1, wx.ScrollBar):\r\n # Hopefully it will work\r\n pos1 = wx.Point(*pos)\r\n shift = wx.SystemSettings.GetMetric(wx.SYS_VSCROLL_X) + 2*(sash_size+1)\r\n if part.orientation == wx.HORIZONTAL:\r\n pos1.y -= shift\r\n else:\r\n pos1.x -= shift\r\n \r\n pos1 = self.ClientToScreen(pos1)\r\n win1 = wx.FindWindowAtPoint(pos1)\r\n\r\n if isinstance(win2, wx.ScrollBar):\r\n pos2 = wx.Point(*pos)\r\n shift = wx.SystemSettings.GetMetric(wx.SYS_VSCROLL_X) + 2*(sash_size+1)\r\n if part.orientation == wx.HORIZONTAL:\r\n pos2.y += shift\r\n else:\r\n pos2.x += shift\r\n\r\n pos2 = self.ClientToScreen(pos2)\r\n win2 = wx.FindWindowAtPoint(pos2)\r\n\r\n if not win1 or not win2:\r\n # How did we get here?\r\n return\r\n\r\n if isinstance(win1, AuiNotebook) or isinstance(win2, AuiNotebook):\r\n # This is a bug on MSW, for disabled pages wx.FindWindowAtPoint\r\n # returns the wrong window.\r\n # See http://trac.wxwidgets.org/ticket/2942\r\n return\r\n\r\n tab_frame1, tab_frame2 = self.GetTabFrameFromWindow(win1), self.GetTabFrameFromWindow(win2)\r\n\r\n if not tab_frame1 or not tab_frame2:\r\n return\r\n\r\n tab_ctrl_1, tab_ctrl_2 = tab_frame1._tabs, tab_frame2._tabs\r\n\r\n if tab_ctrl_1.GetPageCount() > tab_ctrl_2.GetPageCount():\r\n src_tabs = tab_ctrl_2\r\n dest_tabs = tab_ctrl_1\r\n else:\r\n src_tabs = tab_ctrl_1\r\n dest_tabs = tab_ctrl_2\r\n\r\n selection = -1\r\n page_count = dest_tabs.GetPageCount()\r\n \r\n for page in xrange(src_tabs.GetPageCount()-1, -1, -1):\r\n # remove the page from the source tabs\r\n page_info = src_tabs.GetPage(page)\r\n if page_info.active:\r\n selection = page_count + page\r\n src_tabs.RemovePage(page_info.window)\r\n\r\n # add the page to the destination tabs\r\n dest_tabs.AddPage(page_info.window, page_info)\r\n if page_info.control:\r\n self.ReparentControl(page_info.control, dest_tabs)\r\n \r\n self.RemoveEmptyTabFrames()\r\n\r\n dest_tabs.DoShowHide()\r\n self.DoSizing()\r\n dest_tabs.Refresh()\r\n self._mgr.Update()\r\n if selection > 0:\r\n wx.CallAfter(dest_tabs.MakeTabVisible, selection, self)","def dest(side):\n return (side - 1) % 3 # cw(side)","def reshape(self, bottom, top):\n\t\tpass","def new_part(self, indices, master_axis_to_position, master_flip):\n shape = self.shape\n\n if indices == [slice(0, stop, 1) for stop in shape]:\n return\n\n # ------------------------------------------------------------\n # If a dimension runs in the wrong direction then change its\n # index to account for this.\n #\n # For example, if a dimension with the wrong direction has\n # size 10 and its index is slice(3,8,2) then after the\n # direction is set correctly, the index needs to changed to\n # slice(6,0,-2):\n #\n # >>> a = [9, 8, 7, 6, 5, 4, 3, 2, 1, 0]\n # >>> a[slice(3, 8, 2)]\n # [6, 4, 2]\n # >>> a.reverse()\n # >>> print(a)\n # >>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n # >>> a[slice(6, 0, -2)]\n # [6, 4, 2]\n # ------------------------------------------------------------\n\n if self._subarray.size > 1:\n indices = indices[:]\n\n p_flip = self.flip\n\n for axis, i in master_axis_to_position.items():\n\n if (axis not in p_flip and axis not in master_flip) or (\n axis in p_flip and axis in master_flip\n ):\n # This axis runs in the correct direction\n continue\n\n # Still here? Then this axis runs in the wrong\n # direction.\n\n # Reset the direction\n p_flip = p_flip[:]\n if axis in self.flip:\n p_flip.remove(axis)\n else:\n p_flip.append(axis)\n\n # Modify the index to account for the changed\n # direction\n size = shape[i]\n\n if isinstance(indices[i], slice):\n start, stop, step = indices[i].indices(size)\n # Note that step is assumed to be always +ve here\n div, mod = divmod(stop - start - 1, step)\n start = size - 1 - start\n stop = start - div * step - 1\n if stop < 0:\n stop = None\n indices[i] = slice(start, stop, -step)\n else:\n size -= 1\n indices[i] = [size - j for j in indices[i]]\n # --- End: for\n\n self.flip = p_flip\n # --- End: if\n\n slice_None = slice(None)\n\n # Reorder the new indices\n indices = [\n (\n indices[master_axis_to_position[axis]]\n if axis in master_axis_to_position\n else slice_None\n )\n for axis in self.axes\n ]\n\n part = self.part\n\n if not part:\n self.part = indices\n return\n\n # Still here? update an existing part\n p_part = []\n for part_index, index, size in zip(\n part, indices, self._subarray.shape\n ):\n\n if index == slice_None:\n p_part.append(part_index)\n continue\n\n if isinstance(part_index, slice):\n if isinstance(index, slice):\n\n start, stop, step = part_index.indices(size)\n\n size1, mod = divmod(stop - start - 1, step)\n\n start1, stop1, step1 = index.indices(size1 + 1)\n\n size2, mod = divmod(stop1 - start1, step1)\n\n if mod != 0:\n size2 += 1\n\n start += start1 * step\n step *= step1\n stop = start + (size2 - 1) * step\n\n if step > 0:\n stop += 1\n else:\n stop -= 1\n if stop < 0:\n stop = None\n p_part.append(slice(start, stop, step))\n\n continue\n else:\n new_part = list(range(*part_index.indices(size)))\n new_part = [new_part[i] for i in index]\n else:\n if isinstance(index, slice):\n new_part = part_index[index]\n else:\n new_part = [part_index[i] for i in index]\n # --- End: if\n\n # Still here? Then the new element of p_part is a list of\n # integers, so let's see if we can convert it to a slice\n # before appending it.\n new_part0 = new_part[0]\n if len(new_part) == 1:\n # Convert a single element list to a slice object\n new_part = slice(new_part0, new_part0 + 1, 1)\n else:\n step = new_part[1] - new_part0\n if step:\n if step > 0:\n start, stop = new_part0, new_part[-1] + 1\n else:\n start, stop = new_part0, new_part[-1] - 1\n if new_part == list(range(start, stop, step)):\n if stop < 0:\n stop = None\n new_part = slice(start, stop, step)\n # --- End: if\n\n p_part.append(new_part)\n # --- End: for\n\n self.part = p_part","def plot_slices(hists, slice_width, fibre_pos):\n pmt_info = rat.utility().GetPMTInfo()\n # Find max angle\n max_angle = 0\n pmtIDs = hists.keys()\n for pmtID in pmtIDs:\n angle = taf.fibre_to_pmt_angle(fibre_pos, pmt_info.GetPosition(pmtID))\n if angle > max_angle:\n max_angle = angle\n print max_angle\n\n # Step between 0 and max_angle in slices of slice_width\n # create a plot of all pmt time spectra within each slice\n ROOT.gStyle.SetPalette(1) \n cuts = np.arange(0., max_angle+slice_width, slice_width)\n for i, cut in enumerate(cuts): \n tmpHists = []\n if i > 0:\n low_range = cuts[i-1]\n hi_range = cuts[i]\n s = ROOT.THStack(\"stack\", \"Slice: %1.1f - %1.1f deg\" % (low_range, hi_range)) \n count = 0\n for pmtID in pmtIDs:\n angle = taf.fibre_to_pmt_angle(fibre_pos, pmt_info.GetPosition(pmtID))\n if angle > low_range and angle < hi_range:\n #print pmtID\n count = count + 1\n hists[pmtID].SetLineColor(count)\n s.Add(hists[pmtID])\n print \"Drawing...\"\n s.Draw(\"nostack\")\n s.GetHistogram().GetXaxis().SetTitle(\"Time (ns)\")\n #s.Write()\n #c1.BuildLegend(0.5, 0.2, 0.88, 0.88)\n c1.Update()\n c1.Modified()\n c1.Print(\"./results/slices/Slice_%1.1f.png\" % low_range)\n s.Delete()\n #time.sleep(1)","def pyramid_slice(x1,y1,x2,y2,z,delta,deltaz,taper_x,taper_y,taper_straight,layers):\r\n\tcutlist = []\r\n\ty_max = abs(y1-y2)\r\n\tfor a in range(layers):\r\n\t\ti = 0\r\n\t\tnew_x1, new_y1, new_x2, new_y2 = x1 - a*taper_x, y1-a*taper_straight, x2+a*taper_x, y2+a*taper_y\r\n\t\twhile abs(new_y1 - (y1 - a*taper_straight)) < y_max and x1 > 0:\r\n\t\t\tif i % 2 == 0:\r\n\t\t\t\tcutlist.append([\"jump\", f\"{new_x1:.6f}\", f\"{new_y1:.6f}\"])\r\n\t\t\t\tcutlist.append([\"mark\", f\"{new_x2:.6f}\", f\"{new_y1:.6f}\"])\r\n\t\t\telse:\r\n\t\t\t\tcutlist.append([\"jump\", f\"{new_x2:.6f}\", f\"{new_y1:.6f}\"])\r\n\t\t\t\tcutlist.append([\"mark\", f\"{new_x1:.6f}\", f\"{new_y1:.6f}\"])\r\n\t\t\tnew_y1 = new_y1-delta\r\n\t\t\ti = i + 1\r\n\t\tif a < layers - 1:\r\n\t\t\tcutlist.append([\"z_step\", str(-deltaz)])\r\n\t\ty_max = y_max - taper_straight - taper_y\r\n\r\n\treturn cutlist","def initialize_2panel_centy(Wfig=360, Hfig=270, fontsize=12, wsfrac=0.4, wssfrac=0.3, x0frac=0.1, hspace=10,\n right3o4=False, right4o3=False):\n fig = sps.figure_in_mm(Wfig, Hfig)\n ws = wsfrac * Wfig\n hs = ws\n wss = wssfrac * Wfig\n if right3o4:\n hss = wss * 3. / 4.\n elif right4o3:\n hss = wss * 4. / 3.\n else:\n hss = wss\n x0 = x0frac * Wfig\n label_params = dict(size=fontsize, fontweight='normal')\n ax = [sps.axes_in_mm(x0, y0, width, height, label=part, label_params=label_params)\n for x0, y0, width, height, part in (\n [x0, (Hfig - hs) * 0.5, ws, hs, ''],\n [x0 + ws + hspace, (Hfig - hss) * 0.5, wss, hss, ''] # right panel\n )]\n return fig, ax","def generate_panel(self):\r\n \r\n self.PanelData = self.RawData.filter(['ID', 'X', 'Z', 'W', 'R', 'β', 'LFP', 'H'], axis=1)","def animate_slices(field='uu1', datadir='data/', proc=-1, extension='xz',\n format='native', tmin=0., tmax=1.e38, wait=0.,\n amin=0., amax=1., transform='', oldfile=False):\n\n import pylab as plt\n\n datadir = os.path.expanduser(datadir)\n if proc < 0:\n filename = join(datadir, 'slice_' + field + '.' + extension)\n else:\n filename = join(datadir, 'proc' + str(proc),\n 'slice_' + field + '.' + extension)\n\n # Read the global dimensions.\n dim = read_dim(datadir, proc)\n if dim.precision == 'D':\n precision = 'd'\n else:\n precision = 'f'\n\n # Set up slice plane.\n if extension == 'xy' or extension == 'Xy':\n hsize = dim.nx\n vsize = dim.ny\n if extension == 'xz':\n hsize = dim.nx\n vsize = dim.nz\n if extension == 'yz':\n hsize = dim.ny\n vsize = dim.nz\n plane = np.zeros((vsize, hsize), dtype=precision)\n\n infile = npfile(filename, endian=format)\n\n ax = plt.axes()\n ax.set_xlabel('x')\n ax.set_ylabel('y')\n ax.set_ylim\n\n image = plt.imshow(plane, vmin=amin, vmax=amax)\n\n # Get the figure manager for real-time image display.\n manager = plt.get_current_fig_manager()\n manager.show()\n\n ifirst = True\n islice = 0\n while True:\n try:\n raw_data = infile.fort_read(precision)\n except ValueError:\n break\n except TypeError:\n break\n\n if oldfile:\n t = raw_data[-1]\n plane = raw_data[:-1].reshape(vsize, hsize)\n else:\n t = raw_data[-2]\n plane = raw_data[:-2].reshape(vsize, hsize)\n\n if transform:\n exec('plane = plane' + transform)\n\n if t > tmin and t < tmax:\n title = 't = %11.3e' % t\n ax.set_title(title)\n image.set_data(plane)\n manager.canvas.draw()\n\n if ifirst:\n #print \"----islice----------t---------min-------max-------delta\" # Python 2\n print(\"----islice----------t---------min-------max-------delta\")\n #print \"%10i %10.3e %10.3e %10.3e %10.3e\" \\ # Python 2\n #% (islice, t, plane.min(), plane.max(), plane.max() - plane.min()) # Python 2\n print(\"{0:10} {1:10.3e} {2:10.3e} {3:10.3e} {4:10.3e}\".format(islice, t, plane.min(), plane.max(), plane.max() - plane.min()))\n\n ifirst = False\n islice += 1\n\n sleep(wait)\n\n infile.close()","def slice_explorer(data, cmap='gray'):\n data_len = len(data)\n\n @interact(plane=(0, data_len-1), continuous_update=False)\n def display_slice(plane=data_len/2):\n fig, axis = plt.subplots(figsize=(20, 7))\n axis_3d = fig.add_subplot(133, projection='3d')\n show_plane(axis, data[plane], title='Plane {}'.format(plane), cmap=cmap)\n slice_in_3d(axis=axis_3d, shape=data.shape, plane=plane)\n plt.show()\n\n return display_slice","def show_slices(slices):\n fig, axes = plt.subplots(1, len(slices))\n for i, slice in enumerate(slices):\n axes[i].imshow(slice.T, cmap=\"gray\", origin=\"lower\")","def animate_multislices(field=['uu1'], datadir='data/', proc=-1,\n extension='xz', format='native', tmin=0., tmax=1.e38,\n amin=0., amax=1., transform='plane[0]',\n oldfile=False, outfile=\"\"):\n\n import pylab as plt\n\n datadir = os.path.expanduser(datadir)\n if outfile != \"\":\n outslice = open(outfile, \"w\")\n filename = []\n if proc < 0:\n for i in field:\n filename += [datadir + '/slice_' + i + '.' + extension]\n else:\n for i in field:\n filename += [datadir + '/proc' +\n str(proc) + '/slice_' + i + '.' + extension]\n\n # Read the global dimensions.\n dim = read_dim(datadir, proc)\n if dim.precision == 'D':\n precision = 'd'\n else:\n precision = 'f'\n\n # Set up slice plane.\n if extension == 'xy' or extension == 'Xy':\n hsize = dim.nx\n vsize = dim.ny\n if extension == 'xz':\n hsize = dim.nx\n vsize = dim.nz\n if extension == 'yz':\n hsize = dim.ny\n vsize = dim.nz\n plane = []\n infile = []\n for i in filename:\n plane += [np.zeros((vsize, hsize), dtype=precision)]\n\n infile += [npfile(i, endian=format)]\n\n ax = plt.axes()\n ax.set_xlabel('x')\n ax.set_ylabel('y')\n ax.set_ylim\n\n exec('plotplane =' + transform)\n image = plt.imshow(plotplane, vmin=amin, vmax=amax)\n\n # Get the figure manager for real-time image display.\n manager = plt.get_current_fig_manager()\n manager.show()\n\n ifirst = True\n islice = 0\n while True:\n try:\n raw_data = []\n for i in infile:\n raw_data += [i.fort_read(precision)]\n except ValueError:\n break\n except TypeError:\n break\n\n if oldfile:\n t = raw_data[0][-1]\n for i in range(len(raw_data)):\n plane[i] = raw_data[i][:-1].reshape(vsize, hsize)\n else:\n t = raw_data[0][-2]\n for i in range(len(raw_data)):\n plane[i] = raw_data[i][:-2].reshape(vsize, hsize)\n\n exec('plotplane =' + transform)\n\n if t > tmin and t < tmax:\n title = 't = %11.3e' % t\n ax.set_title(title)\n image.set_data(plotplane)\n manager.canvas.draw()\n\n if ifirst:\n #print \"----islice----------t---------min-------max-------delta\" # Python 2\n print(\"----islice----------t---------min-------max-------delta\")\n #print \"%10i %10.3e %10.3e %10.3e %10.3e\" % \\ # Python 2\n #(islice, t, plotplane.min(), plotplane.max(), # Python 2\n #plotplane.max() - plotplane.min()) # Python 2\n print(\"{0:10} {1:10.3e} {2:10.3e} {3:10.3e} {4:10.3e}\".format(islice, t, plotplane.min(), plotplane.max(),\n plotplane.max() - plotplane.min()))\n if outfile != \"\":\n #outslice.write(\"%10i %10.3e %10.3e %10.3e %10.3e\" % # Python 2\n #(islice, t, plotplane.min(), plotplane.max(), # Python 2\n #plotplane.max() - plotplane.min())) # Python 2\n outslice.write(\"{0:10} {1:10.3e} {2:10.3e} {3:10.3e} {4:10.3e}\".format(islice, t, plotplane.min(), plotplane.max(), plotplane.max() - plotplane.min()))\n outslice.write(\"\\n\")\n\n ifirst = False\n islice += 1\n\n for i in infile:\n i.close()\n if outfile != \"\":\n outslice.close()","def add_frame_shift(self, basis, axis_settings):\n angle, axis = angle_and_axis(basis)\n\n if angle == 0:\n axis = (0,0,1)\n\n if basis.include_translation:\n translation = basis.translation\n else:\n translation = (0,0,0)\n\n self.add_row([basis.axis_name,\"rotation\",\"detector\",basis.depends_on,\n str(axis[0]),str(axis[1]),str(axis[2]),\n str(translation[0]),\n str(translation[1]),\n str(translation[2]),\n basis.equipment_component])\n\n axis_settings.append([basis.axis_name, \"FRAME1\", str(angle), \"0\"])","def create_panel(self):\n return\n # return Panel(self)","def show_slices(slices,clims=[0.0,0.0]):\n fig, axes = plt.subplots(1,len(slices))\n for i, slice in enumerate(slices):\n if clims==[0.0,0.0]:\n axes[i].imshow(slice.T, cmap='gray', origin=\"lower\")\n else:\n axes[i].imshow(slice.T, cmap='gray', origin=\"lower\", clim=clims)","def show_slices(slices):\n fig, axes = plt.subplots(1, len(slices))\n for i, slice in enumerate(slices):\n axes[i].imshow(slice.T, cmap=\"gray\", origin=\"lower\")","def reshape(self, bottom, top):\n pass","def reshape(self, bottom, top):\n pass","def reshape(self, bottom, top):\n pass","def reshape(self, bottom, top):\n pass","def reshape(self, bottom, top):\n pass","def reshape(self, bottom, top):\n pass","def reshape(self, bottom, top):\n pass","def reshape(self, bottom, top):\n pass","def reshape(self, bottom, top):\n pass","def reshape(self, bottom, top):\n pass","def reshape(self, bottom, top):\n pass","def splice(features, left_num, right_num):\n shape = tf.shape(features)\n splices = []\n pp = tf.pad(features, [[left_num, right_num], [0, 0]])\n for i in range(left_num + right_num + 1):\n splices.append(tf.slice(pp, [i, 0], shape))\n splices = tf.concat(axis=1, values=splices)\n\n return splices","def show_slices(self, slices):\n fig, axes = plt.subplots(1, len(slices))\n for i, slice in enumerate(slices):\n axes[i].imshow(slice.T, cmap=\"gray\", origin=\"lower\")","def planeSliceTOAFig(uxmax, uymax, dso, dsl, f, dm, m, n, ax, ay, npoints, xax = True, yax = True):\n \n # Calculate coefficients\n rF2 = rFsqr(dso, dsl, f)\n uF2x, uF2y = rF2*np.array([1./ax**2, 1./ay**2])\n lc = lensc(dm, f)\n alp = rF2*lc\n coeff = alp*np.array([1./ax**2, 1./ay**2])\n tg0 = tg0coeff(dso, dsl)\n tdm0 = tdm0coeff(dm, f)\n\n # Calculate caustic intersections\n ucross = polishedRoots(causticEqSlice, uxmax, uymax, args=(alp, m, n, ax, ay))\n ncross = len(ucross)\n upcross = mapToUp(ucross.T, alp, ax, ay)\n p = np.argsort(upcross[0])\n upcross = upcross.T[p]\n ucross = ucross[p]\n # print(upcross)\n \n # Set up quantities for proper u' plane slicing\n ymin = -m*uxmax + n\n ymax = m*uxmax + n\n if ymin < -uymax:\n xmin = (-uymax - n)/m\n ymin = m*xmin + n\n else:\n xmin = -uxmax\n if ymax > uymax:\n xmax = (uymax - n)/m\n ymax = m*xmax + n\n else:\n xmax = uxmax\n \n cdist = uxmax/(np.abs(50*lc))\n \n bound = np.insert(upcross, 0, np.array([[xmin, ymin]]), axis = 0) # set up boundaries\n bound = np.append(bound, np.array([[xmax, ymax]]), axis = 0)\n midpoints = [(bound[i] + bound[i+1])/2. for i in range(len(bound) - 1)] # find middle point between boundaries\n nzones = len(midpoints)\n nreal = np.zeros(nzones, dtype = int)\n for i in range(nzones): # find number of roots at each midpoint\n mpoint = midpoints[i]\n nreal[i] = len(findRoots(lensEq, 2*uxmax, 2*uymax, args = (mpoint, coeff)))\n upxvecs = np.array([np.linspace(bound[i-1][0] + cdist, bound[i][0] - cdist, npoints) for i in range(1, ncross + 2)]) # generate upx vector\n segs = np.asarray([lineVert(upx, m, n) for upx in upxvecs]) # generate slice across plane\n ncomplex = np.zeros(nzones) # don't care about complex solutions in this case\n print(nreal)\n \n # Find roots\n allroots = rootFinder(segs, nreal, ncomplex, npoints, ucross, uxmax, uymax, coeff)\n \n # Calculate TOAs\n alltoas = []\n for i in range(nzones):\n toas = obsCalc(deltat, allroots[i], int(nreal[i]), npoints, 1, args = (tg0, tdm0, alp, ax, ay)).real\n alltoas.append(toas)\n \n # Plots\n fig, ax1 = plt.subplots(figsize=(10, 8), dpi = 100)\n # grid = gs.GridSpec(2, 2, width_ratios=[4, 1])\n # ax0 = plt.subplot(grid[1:, 1])\n # ax1 = plt.subplot(grid[0, 1])\n \n \n # ax2 = plt.subplot(grid[:, 0]) # Plot results\n colors = assignColor(allroots, nreal)\n l = []\n for i in range(len(upxvecs)):\n zone = alltoas[i]\n for j in range(len(zone)):\n line = ax1.plot(upxvecs[i], zone[j], color = colors[i][j], lw = 3.)\n l.append(line)\n for i in range(ncross):\n ax1.plot([upcross[i][0], upcross[i][0]], [-100, 100], color = 'black', ls = 'dashed', scaley = False, scalex = False, lw = 2.5)\n label = r'$\\nu = $' + str(f/GHz) + ' GHz'\n ax1.text(0.05, 0.9, label, transform=ax1.transAxes, fontsize = 28, bbox=dict(facecolor = 'white', alpha=1.))\n # ax1.set_ylim(min(alltoas.flatten() - 1), max(alltoas.flatten() + 1))\n if not xax:\n ax1.xaxis.set_ticklabels([])\n else:\n ax1.set_xlabel(r\"$u'_x$\", fontsize=28)\n if not yax:\n ax1.yaxis.set_ticklabels([])\n else:\n ax1.set_ylabel(r'$\\Delta t \\: (\\mu s)$', fontsize=28)\n if dm > 0:\n ax1.set_ylim(-0.5, 15.)\n else:\n ax1.set_ylim(-2.5, 10.)\n ax1.tick_params(labelsize = 22)\n ax1.grid()\n \n ax2 = inset_axes(ax1, width='18%', height='23%', loc=1)\n rx = np.linspace(-uxmax, uxmax, 1000) # Plot caustic surfaces\n ry = np.linspace(-uxmax, uxmax, 1000)\n uvec = np.meshgrid(rx, ry)\n ucaus = causCurve(uvec, coeff)\n cs = ax2.contour(rx, ry, ucaus, levels = [0, np.inf], linewidths = 0)\n paths = cs.collections[0].get_paths()\n uppaths = []\n for p in paths:\n cuvert = np.array(p.vertices).T\n upx, upy = mapToUp(cuvert, alp, ax, ay)\n ax2.plot(upx, upy, color = 'blue')\n ax2.plot(np.linspace(xmin, xmax, 10), np.linspace(ymin, ymax, 10), color = 'green')\n ax2.scatter(upcross.T[0], upcross.T[1], color = 'green')\n # ax2.set_xlabel(r\"$u'_x$\")\n # ax2.set_ylabel(r\"$u'_y$\")\n ax2.set_xlim(-uxmax, uxmax)\n ax2.tick_params(labelsize = 16)\n # ax1.set_title(\"Caustic curves\")\n # ax1.set_aspect('equal', anchor = 'N')\n ax2.grid()\n # ax2.tight_layout()\n \n plt.tight_layout()\n plt.show()\n return","def _fix_slice(self, inputs, new_attr):\n begin = new_attr.get('begin')\n end = new_attr.get('end')\n axes = new_attr.get('axis', tuple(range(len(begin))))\n slice_op = mx.sym.slice_axis(inputs[0], axis=axes[0], begin=begin[0], end=end[0])\n if len(axes) > 1:\n for i, axis in enumerate(axes):\n slice_op = mx.sym.slice_axis(slice_op, axis=axis, begin=begin[i], end=end[i])\n return slice_op","def moveX(self, slice, dir=1):\n\n for p in self.pieces:\n if slice > 1 or p.x == slice: # Filter pieces not in slice.\n # Use PMatrix2D() to calculate position from rotation.\n t = PMatrix2D()\n t.rotate(dir * HALF_PI)\n t.translate(p.y, p.z)\n p.rX(dir)\n p.pos(round(p.x), round(t.m02), round(t.m12))","def _slice(self, start, stop, step=None):\n\n slices = [slice(None)] * self.data.ndim\n slices[self.axis] = slice(start, stop, step)\n return tuple(slices)","def steerright(self):\n self.direction = self.direction-self.steering\n if self.direction < 0:\n self.direction = 360-90\n self.image, self.rect = rot_center(self.image_orig,self.rect,self.direction)","def moveY(self, slice, dir=1):\n\n for p in self.pieces: # Filter pieces not in slice.\n if slice > 1 or p.y == slice:\n # Use PMatrix2D() to calculate position from rotation.\n t = PMatrix2D()\n t.rotate(dir * HALF_PI)\n t.translate(p.x, p.z)\n p.rY(dir)\n p.pos(round(t.m02), round(p.y), round(t.m12))","def slice_im(image_path, out_name, out_dir, sliceHeight=256, sliceWidth=256,\n zero_frac_thresh=0.2, overlap=0.2, slice_sep='|',\n out_ext='.png', verbose=False):\n\n use_cv2 = True\n # read in image, cv2 fails on large files\n print(\"Read in image:\", image_path)\n try:\n # convert to rgb (cv2 reads in bgr)\n img_cv2 = cv2.imread(image_path, 1)\n # print (\"img_cv2.shape:\", img_cv2.shape)\n image0 = cv2.cvtColor(img_cv2, cv2.COLOR_BGR2RGB)\n except:\n image0 = skimage.io.imread(\n image_path, as_grey=False).astype(np.uint8) # [::-1]\n use_cv2 = False\n print(\"image.shape:\", image0.shape)\n # image0 = cv2.imread(image_path, 1) # color\n\n if len(out_ext) == 0:\n ext = '.' + image_path.split('.')[-1]\n else:\n ext = out_ext\n\n win_h, win_w = image0.shape[:2]\n\n # if slice sizes are larger than image, pad the edges\n pad = 0\n if sliceHeight > win_h:\n pad = sliceHeight - win_h\n if sliceWidth > win_w:\n pad = max(pad, sliceWidth - win_w)\n # pad the edge of the image with black pixels\n if pad > 0:\n border_color = (0, 0, 0)\n image0 = cv2.copyMakeBorder(image0, pad, pad, pad, pad,\n cv2.BORDER_CONSTANT, value=border_color)\n\n win_size = sliceHeight*sliceWidth\n\n t0 = time.time()\n n_ims = 0\n n_ims_nonull = 0\n dx = int((1. - overlap) * sliceWidth)\n dy = int((1. - overlap) * sliceHeight)\n\n # for y0 in xrange(0, image0.shape[0], dy):#sliceHeight):\n # for x0 in xrange(0, image0.shape[1], dx):#sliceWidth):\n for y0 in range(0, image0.shape[0], dy): # sliceHeight):\n for x0 in range(0, image0.shape[1], dx): # sliceWidth):\n n_ims += 1\n\n if (n_ims % 50) == 0:\n print(n_ims)\n\n # make sure we don't have a tiny image on the edge\n if y0+sliceHeight > image0.shape[0]:\n y = image0.shape[0] - sliceHeight\n else:\n y = y0\n if x0+sliceWidth > image0.shape[1]:\n x = image0.shape[1] - sliceWidth\n else:\n x = x0\n\n # extract image\n window_c = image0[y:y + sliceHeight, x:x + sliceWidth]\n # get black and white image\n if use_cv2:\n window = cv2.cvtColor(window_c, cv2.COLOR_BGR2GRAY)\n else:\n window = cv2.cvtColor(window_c, cv2.COLOR_RGB2GRAY)\n\n # find threshold that's not black\n # https://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_imgproc/py_thresholding/py_thresholding.html?highlight=threshold\n ret, thresh1 = cv2.threshold(window, 2, 255, cv2.THRESH_BINARY)\n non_zero_counts = cv2.countNonZero(thresh1)\n zero_counts = win_size - non_zero_counts\n zero_frac = float(zero_counts) / win_size\n # print \"zero_frac\", zero_fra\n # skip if image is mostly empty\n if zero_frac >= zero_frac_thresh:\n if verbose:\n print(\"Zero frac too high at:\", zero_frac)\n continue\n # else save\n else:\n # outpath = os.path.join(out_dir, out_name + \\\n # '|' + str(y) + '_' + str(x) + '_' + str(sliceHeight) + '_' + str(sliceWidth) +\\\n # '_' + str(pad) + ext)\n outpath = os.path.join(\n out_dir,\n out_name + slice_sep + str(y) + '_' + str(x) + '_'\n + str(sliceHeight) + '_' + str(sliceWidth)\n + '_' + str(pad) + '_' + str(win_w) + '_' + str(win_h)\n + ext)\n\n # outpath = os.path.join(out_dir, 'slice_' + out_name + \\\n # '_' + str(y) + '_' + str(x) + '_' + str(sliceHeight) + '_' + str(sliceWidth) +\\\n # '_' + str(pad) + '.jpg')\n if verbose:\n print(\"outpath:\", outpath)\n # if large image, convert to bgr prior to saving\n if not use_cv2:\n skimage.io.imsave(outpath, window_c)\n else:\n cv2.imwrite(outpath, window_c)\n n_ims_nonull += 1\n\n print(\"Num slices:\", n_ims, \"Num non-null slices:\", n_ims_nonull,\n \"sliceHeight\", sliceHeight, \"sliceWidth\", sliceWidth)\n print(\"Time to slice\", image_path, time.time()-t0, \"seconds\")\n\n return","def panel_callback():\n if self.minwidth is None:\n self.minwidth = self.button_stack.winfo_width()\n\n if self.current_panel:\n self.sashpos = self.paned.sashpos(0)\n self.current_panel.forget()\n if isinstance(self.current_panel, class_obj):\n self.current_panel = None\n self.paned.sashpos(0, self.minwidth)\n return\n\n if class_obj.__name__ in self.panels:\n panel = self.panels[class_name]\n else:\n panel = self.panels[class_name] = class_obj(self, self.app)\n\n panel.pack(side=tk.LEFT, expand=1, fill=tk.BOTH)\n\n if self.sashpos is None:\n self.sashpos = 300\n\n self.paned.sashpos(0, self.sashpos)\n\n self.current_panel = panel","def plot_slices(num_rows, num_columns, width, height, data):\n# data = np.rot90(np.array(data))\n data = np.transpose(data)\n data = np.reshape(data, (num_rows, num_columns, width, height))\n rows_data, columns_data = data.shape[0], data.shape[1]\n heights = [slc[0].shape[0] for slc in data]\n widths = [slc.shape[1] for slc in data[0]]\n fig_width = 12.0\n fig_height = fig_width * sum(heights) / sum(widths)\n f, axarr = plt.subplots(\n rows_data,\n columns_data,\n figsize=(fig_width, fig_height),\n gridspec_kw={\"height_ratios\": heights},\n )\n for i in range(rows_data):\n for j in range(columns_data):\n axarr[i, j].imshow(data[i][j], cmap=\"gray\")\n axarr[i, j].axis(\"off\")\n plt.subplots_adjust(wspace=0, hspace=0, left=0, right=1, bottom=0, top=1)\n plt.show()","def _rotate(self):\n \r\n if self.clr == 1: # (default rotation) \r\n # o o o o \r\n # o x x o x o o x\r\n # o o o o\r\n _colOffsets = [[-1,-1, 0, 0], [-1, 0, 0, 1], [ 1, 1, 0, 0], [ 1, 0, 0,-1]] #\r\n _rowOffsets = [[ 1, 0, 0,-1], [-1,-1, 0, 0], [-1, 0, 0, 1], [ 1, 1, 0, 0]] #\r\n elif self.clr == 2:\r\n # o o o o \r\n # o x o x x o x o\r\n # o o o o\r\n _colOffsets = [[-1,-1, 0, 0], [ 1, 0, 0,-1], [ 1, 1, 0, 0], [-1, 0, 0, 1]] #\r\n _rowOffsets = [[-1, 0, 0, 1], [-1,-1, 0, 0], [ 1, 0, 0,-1], [ 1, 1, 0, 0]] #\n \r\n elif self.clr == 3: # \r\n # o o o o \r\n # x o x o x o x o\r\n # o o o o\n \r\n _colOffsets = [[-1, 0, 0, 0], [-1,-1, 0, 1], [ 1, 0, 0, 0], [ 1, 1, 0,-1]] #\r\n _rowOffsets = [[ 1, 1, 0,-1], [-1, 0, 0, 0], [-1,-1, 0, 1], [ 1, 0, 0, 0]] #\n \r\n elif self.clr == 4:\r\n # o o o o \r\n # x o x o x o x o\r\n # o o o o\r\n _colOffsets = [[-1, 0, 0, 0], [1, 1, 0, -1], [1, 0, 0,0], [-1, -1, 0,1]]\n _rowOffsets = [[-1,-1, 0, 1], [-1,0, 0, 0], [1,1, 0,-1], [1,0, 0, 0]]\n \r\n elif self.clr == 5: # o o\r\n # o x \r\n # x o x o o o o o x o\r\n # o o \r\n _colOffsets = [[ 0, 0, 0, 0], [ 2, 1, 0,-1], [ 0, 0, 0, 0], [-2,-1, 0, 1]] #\r\n _rowOffsets = [[-2,-1, 0, 1], [ 0, 0, 0, 0], [ 2, 1, 0,-1], [ 0, 0, 0, 0]] #\r\n elif self.clr == 6: #\r\n # o o o \r\n # o x o x o x o o x o\r\n # o o o \r\n _colOffsets = [[ 0,-1, 0, 0], [-1, 0, 0, 1], [ 0, 1, 0, 0], [ 1, 0, 0,-1]] #\r\n _rowOffsets = [[ 1, 0, 0,-1], [ 0,-1, 0, 0], [-1, 0, 0, 1], [ 0, 1, 0, 0]] #\r\n elif self.clr == 7: # \r\n # o o o o o o o o\r\n # o x o x o x o x\r\n # \r\n _colOffsets = [[-1,-1, 0, 0], [-1,-1, 0, 0], [-1,-1, 0, 0], [-1,-1, 0, 0]] #@@\r\n _rowOffsets = [[ 0,-1, 0,-1], [ 0,-1, 0,-1], [ 0,-1, 0,-1], [ 0,-1, 0,-1]] #@@\n \r\n self._colOffsets = _colOffsets[self._rot] #@@\r\n self._rowOffsets = _rowOffsets[self._rot] #@@\r\n self._update() #@@\r","def transform_slice_backward(mat, coord_mat=None):\n (nrow, ncol) = mat.shape\n if nrow != ncol:\n raise ValueError(\"Height and width of the image is not the same!\")\n if coord_mat is None:\n (r_mat, theta_mat) = polar_from_rectangular(ncol, ncol, ncol, ncol)\n else:\n (r_mat, theta_mat) = coord_mat\n if (r_mat.shape != mat.shape) or (theta_mat.shape != mat.shape):\n raise ValueError(\"Shape of the coordinate array is not the same as\"\n \" the shape of the image!\")\n return mapping(mat, r_mat, theta_mat)","def cutout(self, slices: tuple):\n if len(slices) == self.ndim - 1:\n slices = (slice(0, self.shape[0]), ) + slices\n internalSlices = self._get_internal_slices(slices)\n arr = self.array[internalSlices]\n global_offset = tuple(s.start for s in slices)\n return Chunk(arr, global_offset=global_offset)","def get2DSlice( self, slices: list ):\n assert(len(slices)==self._nDims-2)\n slices.extend([slice(self._nGlobalCoords[self._layout.dims_order[-2]]),\n slice(self._nGlobalCoords[self._layout.dims_order[-1]])])\n return self._f[tuple(slices)]","def image_clip_to_segment_and_convert(image_ms_array, image_pan_array, mask_array, factor, image_height_size, \r\n image_width_size):\r\n \r\n img_pan_list = []\r\n img_ms_list = []\r\n mask_list = []\r\n \r\n n_bands = image_ms_array.shape[2]\r\n \r\n for i in range(0, image_pan_array.shape[0] - image_height_size, int(factor)):\r\n for j in range(0, image_pan_array.shape[1] - image_width_size, int(factor)):\r\n M_90 = cv2.getRotationMatrix2D((image_width_size / 2, image_height_size / 2), 90, 1.0)\r\n M_180 = cv2.getRotationMatrix2D((image_width_size / 2, image_height_size / 2), 180, 1.0)\r\n M_270 = cv2.getRotationMatrix2D((image_width_size / 2, image_height_size / 2), 270, 1.0)\r\n \r\n img_original = image_pan_array[i : i + image_height_size, j : j + image_width_size, 0]\r\n img_rotate_90 = cv2.warpAffine(img_original, M_90, (image_height_size, image_width_size))\r\n img_rotate_180 = cv2.warpAffine(img_original, M_180, (image_width_size, image_height_size))\r\n img_rotate_270 = cv2.warpAffine(img_original, M_270, (image_height_size, image_width_size))\r\n img_flip_hor = cv2.flip(img_original, 0)\r\n img_flip_vert = cv2.flip(img_original, 1)\r\n img_flip_both = cv2.flip(img_original, -1)\r\n img_pan_list.extend([img_original, img_rotate_90, img_rotate_180, img_rotate_270, img_flip_hor, img_flip_vert, \r\n img_flip_both])\r\n mask_patch = mask_array[i : i + image_height_size, j : j + image_width_size, 0]\r\n label = mask_patch[int(image_height_size / 2), int(image_width_size / 2)]\r\n mask_list.extend([label] * 7)\r\n \r\n for i in range(0, int(image_ms_array.shape[0] - (image_height_size / factor)), 1):\r\n for j in range(0, int(image_ms_array.shape[1] - (image_width_size / factor)), 1):\r\n M_90_ms = cv2.getRotationMatrix2D(((image_width_size / factor) / 2, (image_height_size / factor) / 2), 90, 1.0)\r\n M_180_ms = cv2.getRotationMatrix2D(((image_width_size / factor) / 2, (image_height_size / factor) / 2), 180, 1.0)\r\n M_270_ms = cv2.getRotationMatrix2D(((image_width_size / factor) / 2, (image_height_size / factor) / 2), 270, 1.0)\r\n \r\n img_original = image_ms_array[i : i + image_height_size, j : j + image_width_size, 0 : n_bands]\r\n img_rotate_90 = cv2.warpAffine(img_original, M_90_ms, (image_height_size, image_width_size))\r\n img_rotate_180 = cv2.warpAffine(img_original, M_180_ms, (image_width_size, image_height_size))\r\n img_rotate_270 = cv2.warpAffine(img_original, M_270_ms, (image_height_size, image_width_size))\r\n img_flip_hor = cv2.flip(img_original, 0)\r\n img_flip_vert = cv2.flip(img_original, 1)\r\n img_flip_both = cv2.flip(img_original, -1)\r\n img_ms_list.extend([img_original, img_rotate_90, img_rotate_180, img_rotate_270, img_flip_hor, img_flip_vert, \r\n img_flip_both])\r\n \r\n image_pan_segment_array = np.zeros((len(img_pan_list), image_height_size, image_width_size, image_pan_array.shape[2]))\r\n image_ms_segment_array = np.zeros((len(img_ms_list), int(image_height_size / factor), int(image_width_size / factor), \r\n image_ms_array.shape[2]))\r\n \r\n for index in range(len(img_pan_list)):\r\n image_pan_segment_array[index] = img_pan_list[index]\r\n image_ms_segment_array[index] = img_ms_list[index]\r\n \r\n mask_array = np.array(mask_list)\r\n \r\n return image_ms_segment_array, image_pan_segment_array, mask_array","def sub(slice_left, slice_right):\n start = 0\n stop = 0\n if slice_left.start == slice_right.start:\n start = min(slice_left.stop, slice_right.stop)\n stop = max(slice_left.stop, slice_right.stop)\n if slice_left.stop == slice_right.stop:\n start = min(slice_left.start, slice_right.start)\n stop = max(slice_left.start, slice_right.start)\n\n return slice(start, stop)","def make_slice_plot(aa=0.2000,Npix=128,Lbox=1024.):\n # Set up some parameters.\n Npart = 10240.\n mpart = 0.3*2.7755e11*(Lbox/Npart)**3\n scales = [1.0,10.0,100.0]\t\t# The zoom levels.\n dscale = [1.0, 5.,25.]\t\t# The density scaling for the arcsinh.\n dmaxs = [5.0,10.,100]\t\t# The density scaling for the arcsinh.\n # Work out the centering position.\n ff=open(dbh+\"000000\",\"rb\")\n pos=np.fromfile(ff,dtype=('f4',3))\n ff.close()\n pos/=Lbox\n ctr=pos[0,:]\n print(\"Centering at \",ctr)\n # Set the bounds.\n xmin,xmax = -0.5000,0.5000\n ymin,ymax = -0.5000,0.5000\n zmin,zmax = -5/Lbox,5/Lbox\n area = (xmax-xmin)*(ymax-ymin)\n # Now make the figure.\n clab = 'silver'\t# Color for the label.\n cbar = 'silver'\t# Color for the scale bar.\n fig,ax = plt.subplots(2,3,figsize=(6,4),sharex=True,sharey=True)\n for ix in range(ax.shape[0]):\n for iy in range(ax.shape[1]):\n ii = ix*ax.shape[1] + iy\n ss = scales[ii%len(scales)]\n dd = np.zeros( (Npix,Npix) ,dtype='float')\n # Read the data from file. We re-read the data each time,\n # which is I/O inefficient but reduces the memory footprint.\n if ix==0:\t# DM.\n ntotal=0\n for fn in sorted(glob.glob(dbm+\"0000*\")):\n ff=open(fn,\"rb\")\n pos=np.fromfile(ff,dtype=('f4',3))\n ff.close()\n pos/=Lbox\n # Periodically rewrap around ctr.\n rr = pos-ctr\n rr[rr<-0.5] += 1.0\n rr[rr> 0.5] -= 1.0\n # Trim to the slice in z -- this is always the same\n # width. Also keep track of how many particles pass.\n ww=np.nonzero( (rr[:,2]>zmin)&(rr[:,2]<zmax) )[0]\n rr=rr[ww,:2]\n ntotal+=rr.shape[0]\n # Scale the data and cut to the required region (area).\n rr *= ss\t# Scale.\n yy = np.histogram2d(rr[:,0]+0.5,rr[:,1]+0.5,\\\n bins=Npix,range=[[0,1],[0,1]])[0]\n dd += yy.astype('float')\n # Assume the slice as a whole is at mean density.\n mdens = ntotal*area/ss**2/float(Npix**2)\n dd = dd/mdens\n print(ii,ntotal,mdens,np.min(dd),np.max(dd))\n else:\t# HI\n ntotal=0\n for fn in sorted(glob.glob(dbh+\"0000*\")):\n ff=open(fn,\"rb\")\n pos=np.fromfile(ff,dtype=('f4',3))\n ff.close()\n pos/=Lbox\n ff=open(fn.replace(\"Position\",\"Length\"),\"rb\")\n mh=np.fromfile(ff,dtype='i4') * mpart\n ff.close()\n # Periodically rewrap around ctr.\n rr = pos-ctr\n rr[rr<-0.5] += 1.0\n rr[rr> 0.5] -= 1.0\n # Trim to the slice in z -- this is always the same\n # width. Also keep track of how many halos pass.\n ww=np.nonzero( (rr[:,2]>zmin)&(rr[:,2]<zmax) )[0]\n rr=rr[ww,:2]\n mh=mh[ww]\n # Scale the data and cut to the required region (area).\n mHI = HI_mass(mh,aa)\n rr *= ss\t# Scale.\n yy = np.histogram2d(rr[:,0]+0.5,rr[:,1]+0.5,\\\n weights=mHI,\\\n bins=Npix,range=[[0,1],[0,1]])[0]\n dd += yy.astype('float')\n ntotal+= np.sum(mHI)\n # Assume the slice as a whole is at mean density.\n mdens = ntotal*area/ss**2/float(Npix**2)\n dd = dd/mdens\n print(ii,ntotal,mdens,np.min(dd),np.max(dd))\n # Plot the data, scaled.\n #ax[ix,iy].imshow(np.arcsinh(dd.T/dscale[ii%len(dscale)]),\\\n # aspect='equal',extent=[0,1,0,1],\\\n # vmin=0,vmax=np.arcsinh(5.0))\n #ax[ix,iy].imshow(np.arcsinh(dd.T),\\\n # aspect='equal',extent=[0,1,0,1],\\\n # vmin=0,vmax=np.arcsinh(dmaxs[ii%len(dmaxs)]), cmap='hot')\n ax[ix,iy].imshow(np.log(1+dd.T),\\\n aspect='equal',extent=[0,1,0,1],\\\n vmin=0,vmax=np.log(1+dd.max()), cmap='hot')\n # Put on a scale bar.\n xmin,xmax,yval = 0.10,0.10+0.1*(1e3/Lbox),0.95\n scale_text = r'$\\mathbf{'+\"{:.0f}\".format(100./ss)+\\\n r'\\,h^{-1}}$Mpc'\n ax[ix,iy].plot([xmin,xmax],[yval,yval],'-',color=cbar,lw=2)\n ax[ix,iy].text(xmin,yval-0.05,scale_text,fontweight='bold',\\\n ha='left',va='top',color=cbar)\n # Tidy up the plot.\n ax[ix,iy].set_aspect('equal')\n ax[ix,iy].set_xticks([])\n ax[ix,iy].set_yticklabels('')\n ax[ix,iy].set_xticks([])\n ax[ix,iy].set_yticklabels('')\n #\n # Put on some more labels.\n ax[0,0].text(0.05,0.05,r'DM',color=clab,fontweight='bold')\n ax[1,0].text(0.05,0.05,r'HI',color=clab,fontweight='bold')\n # and finish up.\n plt.tight_layout()\n plt.savefig('../../figs/slices.pdf')\n #","def rotate_half(x):\n x1 = x[..., : x.shape[-1] // 2]\n x2 = x[..., x.shape[-1] // 2 :]\n return torch.cat((-x2, x1), dim=-1)","def chained_slice(s1, s2):\n\n assert (s1.start >= 0 and s2.start >= 0 and s1.stop >= 0 and s2.stop >= 0)\n s1_start = s1.start or 0\n s2_start = s2.start or 0\n s1_step = s1.step or 1\n s2_step = s2.step or 1\n\n start = s1_start + s2_start * s1_step\n step = s1_step * s2_step\n if s1.stop is None and s2.stop is None:\n stop = None\n elif s1.stop is None:\n stop = start + step * (s2.stop - s2_start) // s2_step\n elif s2.stop is None:\n stop = s1.stop\n else:\n stop_s2 = start + step * (s2.stop - s2_start) // s2_step\n stop_s1 = s1.stop\n stop = stop_s2 if stop_s2 < stop_s1 else stop_s1\n return slice(start, stop, step)","def close_mask_in(im_slice_2d, side):\n new_slice = im_slice_2d.copy()\n \n x_no_0, y_no_0 = np.nonzero(im_slice_2d)\n if len(x_no_0) == 0: return new_slice, new_slice\n #breakpoint()\n x1 = x_no_0.min() \n x2 = x_no_0.max()\n if side == \"l\":\n x_mid = x2; x_aux1 = x_mid - 9 + 1; x_aux2 = x2 + 1\n elif side == \"r\":\n x_mid = x1; x_aux2 = x_mid + 9; x_aux1 = x1\n \n y_mid = y_no_0[np.where(x_no_0==x_mid)[0]].min()\n y_min = y_no_0.min()\n \n # inferior line\n new_slice[x1:x2+1, y_min] = 1\n # medial line\n new_slice[x_mid, y_min:y_mid+1] = 1\n new_slice = binary_fill_holes(new_slice)\n # in_short array:\n other_slice = new_slice.copy() \n other_slice[x_aux1:x_aux2, :] = 0\n \n return new_slice, other_slice","def _data_move_out_last_dim_lt_one_block(tik_inst, dst, src, data_pos_info):\n sub_axis_1, sub_axis_0, axis_0, axis_1, axis_2, out_offset = data_pos_info\n data_size_one_block = _get_elment_cnt_one_block(src.dtype)\n\n with tik_inst.if_scope(sub_axis_1 == 1):\n with tik_inst.if_scope(sub_axis_0 * axis_2 > data_size_one_block):\n sub_axis_0_2 = sub_axis_0 * axis_2\n sub_axis_0_block_align = sub_axis_0_2 // data_size_one_block\n left_data = sub_axis_0_2 % data_size_one_block\n tik_inst.data_move(dst[out_offset], src, 0, 1, sub_axis_0_block_align, 0, 0)\n with tik_inst.if_scope(left_data > 0):\n with tik_inst.new_stmt_scope():\n reg_temp = [tik_inst.Scalar(src.dtype)\n for i in ADDR_IDX_LIST[:data_size_one_block]]\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\n reg_temp[idx].set_as(src[sub_axis_0_2 - data_size_one_block + idx])\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\n src[idx].set_as(reg_temp[idx])\n tik_inst.data_move(dst[out_offset + sub_axis_0_2 - data_size_one_block],\n src, 0, 1, 1, 0, 0)\n with tik_inst.else_scope():\n # for case sub_axis_0 * axis_2 < data_size_one_block\n with tik_inst.if_scope(axis_0 * axis_1 * axis_2 > data_size_one_block):\n m_sub_axis_0 = _ceil_div(data_size_one_block, axis_2)\n sub_axis_0_2 = m_sub_axis_0 * axis_2\n sub_axis_0_block_align = sub_axis_0_2 // data_size_one_block\n left_data = sub_axis_0_2 % data_size_one_block\n tik_inst.data_move(dst[out_offset + (sub_axis_0 - m_sub_axis_0) * axis_2],\n src, 0, 1, sub_axis_0_block_align, 0, 0)\n with tik_inst.if_scope(left_data > 0):\n with tik_inst.new_stmt_scope():\n reg_temp = [tik_inst.Scalar(src.dtype)\n for i in ADDR_IDX_LIST[:data_size_one_block]]\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\n reg_temp[idx].set_as(src[sub_axis_0_2 - data_size_one_block + idx])\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\n src[idx].set_as(reg_temp[idx])\n tik_inst.data_move(dst[out_offset + sub_axis_0 * axis_2 -\n data_size_one_block],\n src, 0, 1, 1, 0, 0)\n with tik_inst.else_scope():\n # the shape size is not bigger than one block size\n tik_inst.data_move(dst[out_offset], src, 0, 1,\n _ceil_div(axis_0 * axis_1 * axis_2, data_size_one_block), 0, 0)\n\n with tik_inst.else_scope():\n with tik_inst.if_scope(sub_axis_1 * axis_0 * axis_2 > data_size_one_block):\n sub_axis_1_0_2 = sub_axis_1 * axis_0 * axis_2\n sub_axis_1_0_2_block_align = sub_axis_1_0_2 // data_size_one_block\n left_data = sub_axis_1_0_2 % data_size_one_block\n tik_inst.data_move(dst[out_offset], src, 0, 1, sub_axis_1_0_2_block_align, 0, 0)\n with tik_inst.if_scope(left_data > 0):\n with tik_inst.new_stmt_scope():\n reg_temp = [tik_inst.Scalar(src.dtype)\n for i in ADDR_IDX_LIST[:data_size_one_block]]\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\n reg_temp[idx].set_as(src[sub_axis_1_0_2 - data_size_one_block + idx])\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\n src[idx].set_as(reg_temp[idx])\n tik_inst.data_move(dst[out_offset + sub_axis_1_0_2 - data_size_one_block],\n src, 0, 1, 1, 0, 0)\n with tik_inst.else_scope():\n # to make sure move in data size is not less than one block\n with tik_inst.if_scope(axis_0 * axis_1 * axis_2 > data_size_one_block):\n m_sub_axis_1 = _ceil_div(data_size_one_block, axis_0 * axis_2)\n sub_axis_1_0_2 = m_sub_axis_1 * axis_0 * axis_2\n sub_axis_0_block_align = sub_axis_1_0_2 // data_size_one_block\n left_data = sub_axis_1_0_2 % data_size_one_block\n tik_inst.data_move(dst[out_offset + (sub_axis_1 - m_sub_axis_1) * axis_0 * axis_2],\n src, 0, 1, sub_axis_0_block_align, 0, 0)\n with tik_inst.if_scope(left_data > 0):\n with tik_inst.new_stmt_scope():\n reg_temp = [tik_inst.Scalar(src.dtype)\n for i in ADDR_IDX_LIST[:data_size_one_block]]\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\n reg_temp[idx].set_as(src[sub_axis_1_0_2 - data_size_one_block + idx])\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\n src[idx].set_as(reg_temp[idx])\n tik_inst.data_move(dst[out_offset + sub_axis_1 * axis_0 * axis_2 -\n data_size_one_block],\n src, 0, 1, 1, 0, 0)\n with tik_inst.else_scope():\n # the shape size is not bigger than one block size\n tik_inst.data_move(dst[out_offset], src, 0, 1,\n _ceil_div(axis_0 * axis_1 * axis_2, data_size_one_block), 0, 0)","def squeeze_slices(self, slices):\n return tuple(\n slice(\n None if sl.start is None else sl.start if sl.start > bounds.start else bounds.start,\n None if sl.stop is None else sl.stop if sl.stop < bounds.stop else bounds.stop,\n )\n for bounds, sl in zip(self.data.bounds(), slices)\n )","def slice_layer(start, end, step=None, axis=1):\n if axis < 0:\n raise ValueError(\"'slice_layer' can only work on a specified axis > 0\")\n\n def slice_func(x):\n slices = [slice(None)] * axis\n slices.append(slice(start, end, step))\n return x[tuple(slices)]\n\n return Lambda(slice_func)","def carve_slice(\n self, x_index=0, width=config()[\"panel\"][\"width\"],\n ):\n piece = []\n for row in self.grid:\n piece.append(row[x_index : x_index + width])\n\n return piece","def get_4d(slice, copylayers=[], transparancy=0):\n assert slice.ndim < 3\n img = np.zeros(slice.shape)\n img = img[:, :, np.newaxis]\n img = np.repeat(img, 4, 2)\n transparancy = 255 - (255 * transparancy)\n img[:, :, -1] = transparancy\n for layer in copylayers:\n img[:, :, layer] = slice\n return(img)","def RotateSliceView (self, Node, sliceViewName):\n volNode = Node\n sliceNode = slicer.app.layoutManager().sliceWidget(sliceViewName).mrmlSliceNode()\n sliceToRas = sliceNode.GetSliceToRAS()\n VtkMatrix = vtk.vtkMatrix4x4()\n volNode.GetIJKToRASMatrix(VtkMatrix)\n M = np.zeros((4,4)) #### IJK To RAS Numpy Matrix \n for i in range (4):\n for j in range (4):\n M[i,j] = VtkMatrix.GetElement(i,j)\n\n Dim = volNode.GetImageData().GetDimensions()\n t = M.dot(np.array([(Dim[0]-1)/2,(Dim[1]-1)/2,0,1]))\n for i in range (4):\n VtkMatrix.SetElement(i,3,t[i])\n VtkMatrix.SetElement(i,2,VtkMatrix.GetElement(i,2)/-10) \n VtkMatrix.SetElement(i,1,VtkMatrix.GetElement(i,1)*-1) # The minus sign, above and here, is a Pi rotation around the X axis.\n\n sliceToRas.DeepCopy(VtkMatrix)\n sliceNode.UpdateMatrices()\n sliceNode.RotateToVolumePlane(volNode)","def _sidepanel(self):\n global curdir\n global sidepanel_layout\n global root\n\n #Create the sidepanel layout.\n sidepanel_layout = BoxLayout(orientation=\"vertical\", pos_hint={\"x\": 0.0, \"top\": 0.92}, size_hint=(0.1, 0.92))\n\n #If \"curdir\" contains folders, a button is created for each, and bind the button to update the\n # showphotos layout.\n if curdir == \" \":\n return sidepanel_layout\n else:\n root.remove_widget(sidepanel_layout)\n for folders in sorted(glob(join(curdir, \"thumb\", \"*\"))):\n name = basename(folders)\n btn = Button(text=name, on_press=lambda n=name: self._update_scroll(n.text))\n sidepanel_layout.add_widget(btn)\n root.add_widget(sidepanel_layout)\n sidepanel_layout.do_layout()","def RotatedPlaneArray(plane,tot_ang,divs,axis):\n out_planes=[]\n plane.Rotate(-tot_ang*0.5,axis)\n out_planes.append(Rhino.Geometry.Plane(plane))\n inc=tot_ang/(divs-1)\n for i in range(divs-1):\n plane.Rotate(inc,axis)\n out_planes.append(Rhino.Geometry.Plane(plane))\n return out_planes","def plotwithslices(data,figsize=(16,4),slices=5, RollingDistance=20,rollingwidth=1,stdwidth = 1, Testoutput = 0, doubleaxis=True):\r\n print(\"\\n -- Plotting Data with %i Slices and RollingDist of %i and %i-- \" %(slices,RollingDistance,RollingDistance*5))\r\n totallen=len(data)\r\n slicelens=int(totallen/slices)\r\n fig, ax1=plt.subplots(figsize=figsize)\r\n plt.plot(data,label = 'Data',linewidth = 2)\r\n plt.plot(data.rolling(RollingDistance).mean(),label = '%i R Mean' %(RollingDistance), linestyle=':', linewidth=rollingwidth)\r\n plt.plot(data.rolling(RollingDistance*5).mean(),label = '%i R Mean' %(RollingDistance*5), linestyle=':', linewidth=rollingwidth);plt.legend()\r\n if (doubleaxis==True):\r\n ax2 = ax1.twinx()\r\n plt.plot(data.rolling(RollingDistance).std(),color='r',linewidth=stdwidth, label = '%i R Std' %(RollingDistance-1))\r\n for i in range(slices-1): \r\n plt.axvline(x=data.index[int(totallen/slices)*(i+1)],color='r',linestyle='--',linewidth=1)\r\n plt.legend();\r\n plt.show()\r\n \r\n if (Testoutput == True):\r\n print(' Slice 0 S: %4i E: %4i ' %(0, totallen), end=\"\")\r\n DickeyFullerPrint(data[0:totallen])\r\n normalitytest(data[0:totallen])\r\n for i in range(slices): \r\n print('\\n Slice %2i S: %4i E: %4i ' %(i+1, slicelens*(i), slicelens*(i+1)), end=\"\")\r\n DickeyFullerPrint(data[slicelens*(i):slicelens*(i+1)])\r\n normalitytest(data[slicelens*(i):slicelens*(i+1)])\r\n return","def middlemakevisible(self, pos):\n pass","def orient_img_hwd(data, slice_axis):\n if slice_axis == 0:\n return data.transpose(2, 1, 0)\n elif slice_axis == 1:\n return data.transpose(2, 0, 1)\n elif slice_axis == 2:\n return data","def rotaxis(proj, N_steps):\n a = proj.shape[1]//4\n b = 3 * proj.shape[1]//4\n c = proj.shape[2]//4\n d = 3 * proj.shape[2]//4\n \n \n cent = []\n N_rot = proj.shape[0] - 180 * N_steps\n \n for i in range(N_rot):\n distances = shift(proj[i, a:b, c:d], np.flip(proj[i + N_steps*180, a:b, c:d] ,1))\n cent.append(proj[i].shape[1]/2 + distances[1]/2)\n \n return cent","def get_band_panel(self):\n return pn.Column(\n pn.Column(\n pn.Row(self.get_controls(), margin = (0, 0, -25, 0)),\n pn.pane.HoloViews(self.get_band_dmap(), linked_axes=False)\n ), \n )","def quadriview_old(nifti_image, slice_sag, slice_orth,\n slice_cor_1, slice_cor_2):\n view_1 = nifti_image[slice_sag, :, :]\n view_2 = nifti_image[:, slice_orth, :]\n view_3 = nifti_image[:, :, slice_cor_1]\n view_4 = nifti_image[:, :, slice_cor_2]\n\n pad_lign = max(view_1.shape[0] + view_2.shape[0], view_3.shape[0] + view_4.shape[0])\n pad_col = max(view_1.shape[1] + view_3.shape[1], view_2.shape[1] + view_4.shape[1])\n pad = np.zeros((pad_lign, pad_col), dtype=np.float64)\n\n pad[:view_1.shape[0], :view_1.shape[1]] = view_1\n pad[-view_2.shape[0]:, :view_2.shape[1]] = view_2\n pad[:view_3.shape[0], -view_3.shape[1]:] = view_3\n pad[-view_4.shape[0]:, -view_4.shape[1]:] = view_4\n\n return pad","def slice_array():\n img = Image.open(\"flamingo.jpg\")\n image_as_array = np.array(img)\n width, height, depth = image_as_array.shape\n\n red_channel = image_as_array[:, :, 0]\n green_channel = image_as_array[:, :, 1]\n blue_channel = image_as_array[:, :, 2]\n\n top_left_corner = image_as_array[:height // 2, :width // 2, :]\n top_right_corner = image_as_array[:height // 2, width // 2:, :]\n random_middle_pixels = image_as_array[11:29, 101:400, :]","def animate_scatters(iteration, ax, pos):\n \n # Change viewing angle\n ax.view_init(pos[iteration][0], pos[iteration][1])","def sharpen_slide(self):\r\n std_input = self.horizontal.get() # Get the std defined by user\r\n c_input = self.vertical.get() # get the constant defined by the user\r\n img = self.master.images[-1] # Use the most recent displayed image for sharpening\r\n sharpened_image = sharpen.gaussian_unsharp_masking(img, std_input, c_input) # Apply unsharp masking on image\r\n self.master.display_image.display_image(img=sharpened_image) # display sharpened image\r\n self.master.images.append(sharpened_image) # Append the sharpened image on the stack\r","def make_door_split(bm, face, size, off, **kwargs):\n return split(bm, face, size.y, size.x, off.x, off.y, off.z)","def __make_slide(self):\n # Create base rectangle for slide\n length = self.parameters['slide_base_length'] + self.parameters['bearing_slide_travel']\n width = self.parameters['slide_width']\n height = self.parameters['slide_height']\n slide = fso.Box(x=length,y=width,z=height)\n # Create the mounting holes\n radius = 0.5*self.parameters['slide_screw_size']\n base_hole = fso.Cylinder(r=radius, l=2*height)\n hole_list = []\n for i in (-1,1):\n for j in (-1,1):\n xpos = i*(0.5*length - self.parameters['slide_screw_inset'])\n ypos = j*(0.5*self.parameters['slide_screw_dW'])\n hole = base_hole.copy()\n hole.translate([xpos,ypos,0])\n hole_list.append(hole)\n # Remove hole material\n slide -= hole_list\n slide.set_color(self.slide_color,recursive=True)\n self.slide = slide","def axis(ind):\n return ind % 15, ind // 15","def orig(side):\n return (side + 1) % 3 # ccw(side)","def create_sat_panels(self):\n\n # Dimensions of body\n SAT_SIZE = self.ANI_SCALE*self.SAT_SCALE*np.asarray(self.SAT_PROPS[\"Size\"])/2\n bx = SAT_SIZE[0]\n by = SAT_SIZE[1]\n bz = SAT_SIZE[2]\n\n # Panel length\n L = bx\n\n # Panels\n theta = self.PANEL_ANGLE*pi/180\n px1 = bx - L*sin(theta)\n py1 = by + L*cos(theta)\n pz1 = bz\n px2 = px1 + L*sin(theta)\n py2 = py1 + L*cos(theta)\n pz2 = pz1\n\n # Vertices\n V = [\n (-bx, by, -bz),\n (-bx, by, bz),\n (-px1, py1, pz1),\n (-px1, py1, -pz1),\n (-px1, py1, -pz1),\n (-px1, py1, pz1),\n (-px2, py2, pz2),\n (-px2, py2, -pz2),\n (-bx, -by, -bz),\n (-bx, -by, bz),\n (-px1, -py1, pz1),\n (-px1, -py1, -pz1),\n (-px1, -py1, -pz1),\n (-px1, -py1, pz1),\n (-px2, -py2, pz2),\n (-px2, -py2, -pz2)\n ]\n\n # Create faces\n F = [\n (0, 1, 2, 3),\n (4, 5, 6, 7),\n (8, 9, 10, 11),\n (12, 13, 14, 15)\n ]\n\n # Create building blocks of polydata\n sat = vtk.vtkPolyData()\n points = vtk.vtkPoints()\n polys = vtk.vtkCellArray()\n scalars = vtk.vtkFloatArray()\n\n # Load the point, cell and data attributes\n for i in range(len(V)):\n points.InsertPoint(i, V[i])\n for i in range(len(F)):\n polys.InsertNextCell(self.mkVtkIdList(F[i]))\n for i in range(len(V)):\n scalars.InsertTuple1(i, i)\n \n # Assign the pieces to the vtkPolyData.\n sat.SetPoints(points)\n del points\n sat.SetPolys(polys)\n del polys\n sat.GetPointData().SetScalars(scalars)\n del scalars\n\n # Mapper\n mapper = vtk.vtkPolyDataMapper()\n mapper.SetInputData(sat)\n mapper.ScalarVisibilityOff()\n\n # Actor\n actor = vtk.vtkActor()\n actor.SetMapper(mapper)\n actor.GetProperty().SetColor(0., 0., 0.8)\n actor.GetProperty().SetAmbient(0.5)\n actor.GetProperty().SetSpecular(.5)\n actor.GetProperty().SetSpecularPower(10.0)\n actor.GetProperty().SetDiffuse(0.2)\n\n # Move to sat position\n actor.SetPosition(0, 0, -self.SAT_PROPS[\"Alt\"])\n\n return actor","def left_right(steps):\n lengths = lens(steps)\n a_side = []\n b_side = []\n for i in range(len(lengths)):\n if i % 2 == 0:\n a_side.append(steps[i])\n else:\n b_side.append(steps[i])\n return a_side, b_side","def scroll(get_frame, t):\r\n frame = get_frame(t)\r\n frame_region = frame[int(t):int(t)+360,:]\r\n return frame_region","def _crop_concat(self, upsampled, bypass):\n c = (bypass.size()[2] - upsampled.size()[2]) // 2\n bypass = F.pad(bypass, (-c, -c, -c, -c))\n\n return torch.cat((upsampled, bypass), 1)","def spinAround(self):"],"string":"[\n \"def _slice_at_axis(sl, axis):\\n return (slice(None),) * axis + (sl,) + (...,)\",\n \"def animate_slices_multi(field='uu1', datadir1='data/', datadir2='data/', proc=-1, extension='xz',\\n format='native', tmin=0., tmax=1.e38, wait=0.,\\n amin=0., amax=1., transform='', oldfile=False,\\n makemovie=False):\\n\\n import pylab as plt\\n\\n datadir1 = os.path.expanduser(datadir1)\\n if proc < 0:\\n filename1 = join(datadir1, 'slice_' + field + '.' + extension)\\n else:\\n filename1 = join(datadir1, 'proc' + str(proc),\\n 'slice_' + field + '.' + extension)\\n\\n datadir2 = os.path.expanduser(datadir2)\\n if proc < 0:\\n filename2 = join(datadir2, 'slice_' + field + '.' + extension)\\n else:\\n filename2 = join(datadir2, 'proc' + str(proc),\\n 'slice_' + field + '.' + extension)\\n\\n # Read the global dimensions.\\n dim = read_dim(datadir1, proc)\\n if dim.precision == 'D':\\n precision = 'd'\\n else:\\n precision = 'f'\\n\\n # Set up slice plane.\\n if extension == 'xy' or extension == 'Xy':\\n hsize = dim.nx\\n vsize = dim.ny\\n if extension == 'xz':\\n hsize = dim.nx\\n vsize = dim.nz\\n if extension == 'yz':\\n hsize = dim.ny\\n vsize = dim.nz\\n plane1 = np.zeros((vsize, hsize), dtype=precision)\\n plane2 = np.zeros((vsize, hsize), dtype=precision)\\n\\n infile1 = npfile(filename1, endian=format)\\n infile2 = npfile(filename2, endian=format)\\n\\n #ax = plt.axes()\\n #ax.set_xlabel('')\\n #ax.set_ylabel('')\\n #ax.set_ylim\\n #ax.get_xaxis().set_visible(False)\\n #ax.get_yaxis().set_visible(False)\\n\\n fig, (ax1,ax2) = plt.subplots(1,2)\\n #fig.suptitle('Re = 400', fontsize=20)\\n image1 = ax1.imshow(plane1, vmin=amin, vmax=amax)\\n image2 = ax2.imshow(plane2, vmin=amin, vmax=amax)\\n ax1.set_xlabel('')\\n ax1.set_ylabel('')\\n ax1.get_xaxis().set_visible(False)\\n ax1.get_yaxis().set_visible(False)\\n ax2.set_xlabel('')\\n ax2.set_ylabel('')\\n ax2.get_xaxis().set_visible(False)\\n ax2.get_yaxis().set_visible(False)\\n\\n # Get the figure manager for real-time image display.\\n manager = plt.get_current_fig_manager()\\n manager.show()\\n\\n ifirst = True\\n islice = 0\\n files = []\\n\\n while True:\\n try:\\n raw_data1 = infile1.fort_read(precision)\\n raw_data2 = infile2.fort_read(precision)\\n except ValueError:\\n break\\n except TypeError:\\n break\\n\\n if oldfile:\\n t = raw_data1[-1]\\n plane1 = raw_data1[:-1].reshape(vsize, hsize)\\n plane2 = raw_data2[:-1].reshape(vsize, hsize)\\n else:\\n t = raw_data1[-2]\\n plane1 = raw_data1[:-2].reshape(vsize, hsize)\\n plane2 = raw_data2[:-2].reshape(vsize, hsize)\\n\\n if transform:\\n exec('plane = plane' + transform)\\n\\n if t > tmin and t < tmax:\\n title = 't = %11.3e' % t\\n #fig.set_title(title)\\n image1.set_data(plane1)\\n image2.set_data(plane2)\\n manager.canvas.draw()\\n\\n if ifirst:\\n #print \\\"----islice----------t---------min-------max-------delta\\\" # Python 2\\n print(\\\"----islice----------t---------min-------max-------delta\\\")\\n #print \\\"%10i %10.3e %10.3e %10.3e %10.3e\\\" \\\\ # Python 2\\n #% (islice, t, plane.min(), plane.max(), plane.max() - plane.min()) # Python 2\\n print(\\\"{0:10} {1:10.3e} {2:10.3e} {3:10.3e} {4:10.3e}\\\".format(islice, t, plane1.min(), plane1.max(), plane1.max() - plane1.min()))\\n\\n if(makemovie):\\n fname = '_tmp%03d.png' % islice\\n fig.savefig(fname)\\n files.append(fname)\\n\\n ifirst = False\\n islice += 1\\n\\n sleep(wait)\\n\\n infile1.close()\\n infile2.close()\\n\\n if(makemovie):\\n print('Making movie animation.mpg - this make take a while')\\n # SC: Not all systems use mencoder. Need to change this into ffmpeg.\\n os.system(\\\"mencoder 'mf://_tmp*.png' -mf type=png:fps=24 -ovc lavc -lavcopts vcodec=wmv2 -oac copy -o animation.mpg\\\")\\n os.system(\\\"rm _tmp*.png\\\")\",\n \"def get_2D_slices(atlas: str):\\n if atlas == \\\"avg\\\":\\n AVGT, metaAVGT = nrr.read(\\\"nrrd/average_template_10.nrrd\\\")\\n folder = \\\"avg\\\"\\n elif atlas == \\\"nissl\\\":\\n AVGT, metaAVGT = nrr.read(\\\"nrrd/ara_nissl_10.nrrd\\\")\\n folder = \\\"nissl\\\"\\n else:\\n raise Exception(\\\"Wrong argument for var atlas\\\")\\n\\n degress = [i for i in range(-15, 16, 3)]\\n\\n for degree in tqdm(degress):\\n rotated = rot(AVGT, angle=degree, mode=\\\"nearest\\\", order=0, reshape=True)\\n print(degree)\\n for plate_no in tqdm(range(300, 1300, 5)):\\n save_img(rotated[plate_no], folder=folder, plate_no=plate_no, degree=degree)\",\n \"def get_slice(P1, P2, name):\\n \\n centre_dist = distance_3D(P1, P2)\\n plot_img = np.zeros((ceil(centre_dist / 2. + 1), centre_dist + 2 ))\\n Xrange = np.arange(-centre_dist / 4., centre_dist / 4. + 1)\\n \\n # time goes along the vector between P1 and P2\\n # since it might be at an angle, I can't loop in 1\\n # pixel increments - this will miss certain slices. Therefore,\\n # I need to loop through by 1/cosA, where A is angle between\\n # the xy plane and vector P1->P2\\n sampling = sample_rate(P1, P2)\\n \\n for time in np.linspace(0, centre_dist + 1,\\n centre_dist * sampling):\\n # Go up along the line\\n new_pt = vector_3D(P1, P2, time)\\n old_pt = vector_3D(P1, P2, time - centre_dist / 2. * sampling)\\n\\n if time == 0:\\n input_file = name % int(round(new_pt[2], 0))\\n img = io.imread(input_file)\\n \\n # Check if the previous slice is the same as the next\\n # don't load it again if it is - save computation time\\n if int(round(new_pt[2], 0)) != int(round(old_pt[2], 0)):\\n \\n input_file = name % int(round(new_pt[2], 0))\\n img = io.imread(input_file)\\n \\n for X in Xrange:\\n \\n # Get along the X direction for every height\\n x, y, z = vector_perpendicular_3D(new_pt, P2, 1, 0, X)\\n \\n pixel_value = interpolation(x, y, img)\\n \\n plot_img[X + centre_dist / 4., time] = pixel_value\\n else:\\n for X in Xrange:\\n \\n # Get along the X direction for every height\\n x, y, z = vector_perpendicular_3D(new_pt, P2, 1, 0, X)\\n\\n pixel_value = interpolation(x, y, img)\\n \\n plot_img[X + centre_dist / 4., time] = pixel_value\\n \\n return plot_img\",\n \"def splitLayer(self, src, dire):\\n\\n (rowN, colN) = src.shape\\n res = []\\n ## UNSURE ABOUT SLICING\\n if (dire == self.VERTICAL):\\n # range(start, stop, step)\\n for i in range(0, rowN - self.slideThickness, self.slideThickness):\\n # croping is much easier in Python, it is basically just slicing\\n tmp = src[i:i+self.slideThickness, 0:colN]\\n \\n res.append(tmp)\\n\\n else:\\n\\n for i in range(0, colN - self.slideThickness, self.slideThickness):\\n # croping is much easier in Python, it is basically just slicing\\n tmp = src[0:self.slideThickness, i:i+rowN]\\n res.append(tmp)\\n\\n return res\",\n \"def alternatingSlice(self,geom,polyLayer,targetArea,granularity,direction,method):\\r\\n global recurs\\r\\n recurs+=1\\r\\n if self.debug: print \\\"******************************\\\"\\r\\n if self.debug: print \\\"Slicing, No of part: \\\",str(recurs)\\r\\n if self.debug: print \\\"Slicing, Granularity remaining: \\\", str(granularity)\\r\\n bbox=[geom.boundingBox().xMinimum(),geom.boundingBox().yMinimum(),geom.boundingBox().xMaximum(),geom.boundingBox().yMaximum()]\\r\\n if direction==\\\"h\\\":\\r\\n step=(bbox[2]-bbox[0])/granularity\\r\\n pointer=bbox[0]\\r\\n else:\\r\\n step=(bbox[3]-bbox[1])/granularity\\r\\n pointer=bbox[1]\\r\\n totalArea=0\\r\\n slices=0\\r\\n #save the original geom\\r\\n tempGeom=QgsGeometry(geom)\\r\\n #start slicing until targetArea is reached\\r\\n while totalArea<targetArea*0.999:\\r\\n pointer+=step\\r\\n if direction==\\\"h\\\":\\r\\n startPt=QgsPoint(pointer,bbox[1])\\r\\n endPt=QgsPoint(pointer,bbox[3])\\r\\n (multiGeom,tempGeom)=self.cutPoly(tempGeom,startPt,endPt)\\r\\n else:\\r\\n startPt=QgsPoint(bbox[0],pointer)\\r\\n endPt=QgsPoint(bbox[2],pointer)\\r\\n (tempGeom,multiGeom)=self.cutPoly(tempGeom,startPt,endPt)\\r\\n if multiGeom!=None:\\r\\n totalArea+=multiGeom.area();\\r\\n slices+=1\\r\\n if self.debug: print \\\"Slicing, Slices: \\\", str(slices)\\r\\n #do the real cutting when reached targetArea and add \\\"left\\\" feature to layer\\r\\n if self.debug: print \\\"Cutting with line, Cutline:\\\", startPt,\\\",\\\",endPt\\r\\n if direction==\\\"h\\\":\\r\\n (multiGeom,geom)=self.cutPoly(geom,startPt,endPt,True)\\r\\n if multiGeom:\\r\\n if self.debug: print \\\"After split, Parts to the left:\\\",str(len(multiGeom.asGeometryCollection()))\\r\\n if geom:\\r\\n if self.debug: print \\\"After split, Parts to the right:\\\",str(len(geom.asGeometryCollection()))\\r\\n else:\\r\\n (geom,multiGeom)=self.cutPoly(geom,startPt,endPt,True)\\r\\n if geom:\\r\\n if self.debug: print \\\"After split, Parts above:\\\",str(len(geom.asGeometryCollection()))\\r\\n if multiGeom:\\r\\n if self.debug: print \\\"After split, Parts under:\\\",str(len(multiGeom.asGeometryCollection()))\\r\\n self.addGeomToLayer(multiGeom,polyLayer)\\r\\n #self.addGeomToLayer(QgsGeometry.fromPolyline([startPt,endPt]),lineLayer)\\r\\n if geom:\\r\\n if geom.area()>targetArea:\\r\\n if (method==\\\"v\\\") or ((method==\\\"a\\\") and (direction==\\\"h\\\")):\\r\\n self.alternatingSlice(geom,polyLayer,targetArea,granularity-slices,\\\"v\\\",method)\\r\\n else:\\r\\n self.alternatingSlice(geom,polyLayer,targetArea,granularity-slices,\\\"h\\\",method)\\r\\n else:\\r\\n self.addGeomToLayer(geom,polyLayer)\",\n \"def __slicer(self, bg, ol, tgPng):\\n cmd = 'slicer ' + bg + ' '\\n if ol != None:\\n cmd += ol + ' '\\n cmd += '-a ' + tgPng\\n self.launchCommand(cmd)\",\n \"def make_panel_in_array(array_elt, reference_panel):\\n\\n px_size = tuple((e / 3.0) for e in reference_panel.get_pixel_size())\\n ref_panel_size = reference_panel.get_image_size_mm()\\n x_shift = array_elt[0] * ref_panel_size[0] / 3.0\\n y_shift = array_elt[1] * ref_panel_size[1] / 3.0\\n origin = (\\n matrix.col(reference_panel.get_origin())\\n + x_shift * matrix.col(reference_panel.get_fast_axis())\\n + y_shift * matrix.col(reference_panel.get_slow_axis())\\n )\\n return Panel(\\n type=\\\"PAD\\\",\\n name=\\\"Panel\\\",\\n fast_axis=reference_panel.get_fast_axis(),\\n slow_axis=reference_panel.get_slow_axis(),\\n origin=origin,\\n pixel_size=px_size,\\n image_size=reference_panel.get_image_size(),\\n trusted_range=(0, 1.0e6),\\n thickness=0.0,\\n material=\\\"\\\",\\n )\",\n \"def rotate2(A, dr, dc):\\n def rotate(R, d):\\n # Negative slice indices count from the right.\\n if d < 0:\\n return R[-len(R)-d: ] + R[0: -d]\\n else:\\n return R[-d:] + R[0: len(R)-d]\\n rows = tuple(map(lambda row: rotate(row, dc), A))\\n return rotate(rows, dr)\",\n \"def chain(self,slices):\\n for proj in self.projs[::-1]:\\n slices = proj(slices)\\n return\",\n \"def reshape(self,bottom,top):\\n pass\",\n \"def slice(\\n sample, \\n ei, psi_axis,\\n hkl0, hkl_dir, x_axis, \\n instrument, erange,\\n out):\\n from mcvine.workflow.sample import loadSampleYml\\n sample = loadSampleYml(sample)\\n code = \\\"from mcvine.workflow.DGS import %s as mod\\\" % instrument\\n d = {}; exec(code, d); mod = d['mod']\\n psi_angles = np.arange(*tuple(psi_axis))\\n x_axis = np.arange(*tuple(x_axis))\\n from matplotlib import pyplot as plt\\n plt.figure()\\n from ...singlextal import dynrange\\n dynrange.plotDynRangeOfSlice(\\n sample, psi_angles, ei, hkl0, hkl_dir, x_axis,\\n mod.scattering_angle_constraints,\\n Erange=erange)\\n if out:\\n plt.savefig(out)\\n else:\\n plt.show()\\n return\",\n \"def test_slicing_containers(self):\\n\\n pattern = midi.Pattern()\\n pattern.extend([midi.Track()] * 5)\\n result1 = pattern[1]\\n result2 = pattern[1:5]\\n result3 = pattern[::2]\\n\\n track = midi.Track()\\n track.extend([midi.Event()] * 5)\\n result1 = track[1]\\n result2 = track[1:5]\\n result3 = track[::2]\",\n \"def pie_slice(self, x, y, r, t0, t1, cls=None, style=None):\\n tr0 = math.radians(t0)\\n tr1 = math.radians(t1)\\n x0 = x + r * math.cos(tr0)\\n y0 = y + r * math.sin(tr0)\\n x1 = x + r * math.cos(tr1)\\n y1 = y + r * math.sin(tr1)\\n laf = int(abs(t1 - t0) > 180)\\n self.path(['M', x, y, 'L', x0, y0, 'A', r, r, 0, laf, 1, x1, y1, 'Z'], cls, style)\\n return self\",\n \"def pie_slice(self, x, y, r, t0, t1, cls=None, style=None):\\n tr0 = math.radians(t0)\\n tr1 = math.radians(t1)\\n x0 = x + r * math.cos(tr0)\\n y0 = y + r * math.sin(tr0)\\n x1 = x + r * math.cos(tr1)\\n y1 = y + r * math.sin(tr1)\\n laf = int(abs(t1 - t0) > 180)\\n self.path(['M', x, y, 'L', x0, y0, 'A', r, r, 0, laf, 1, x1, y1, 'Z'], cls, style)\\n return self\",\n \"def animate_slices_crossflow(field='uu1', datadir='data/', proc=-1, extension='yz',\\n format='native', tmin=0., tmax=1.e38, wait=0.,\\n amin=0., amax=1., transform='', oldfile=False):\\n\\n import pylab as plt\\n import matplotlib.patches as ptc\\n import matplotlib.ticker as ticker\\n\\n datadir = os.path.expanduser(datadir)\\n if proc < 0:\\n filename = join(datadir, 'slice_' + field + '.' + extension)\\n else:\\n filename = join(datadir, 'proc' + str(proc),\\n 'slice_' + field + '.' + extension)\\n\\n # Read the global dimensions.\\n dim = read_dim(datadir, proc)\\n if dim.precision == 'D':\\n precision = 'd'\\n else:\\n precision = 'f'\\n\\n # Set up slice plane.\\n if extension == 'xy' or extension == 'Xy':\\n hsize = dim.nx\\n vsize = dim.ny\\n if extension == 'xz':\\n hsize = dim.nx\\n vsize = dim.nz\\n if extension == 'yz':\\n hsize = dim.ny\\n vsize = dim.nz\\n plane = np.zeros((vsize, hsize), dtype=precision)\\n\\n infile = npfile(filename, endian=format)\\n\\n ax = plt.axes()\\n ax.set_xlabel('y')\\n ax.set_ylabel('x')\\n ax.set_ylim\\n\\n\\n name_list_x = ('0', '2D', '4D', '6D')\\n #name_list_z = ('12D', '10D', '8D', '6D', '4D','2D','0')\\n name_list_z = ( '0', '2D', '4D', '6D','8D','10D','12D',)\\n pos_list_x = np.array([0,80,160,240])\\n pos_list_z = np.array([0,80,160,240,320,400,480])\\n\\n name_list_x = ('0', '5D', '10D')\\n name_list_z = ( '0', '5D', '10D', '15D','20D')\\n pos_list_x = np.array([0,159,319])\\n pos_list_z = np.array([0,159,319,479,639])\\n #pos_list = np.arange(len(name_list))\\n\\n#ax = plt.axes()\\n #ax.xaxis.set_major_locator(ticker.FixedLocator((pos_list_x)))\\n #ax.xaxis.set_major_formatter(ticker.FixedFormatter((name_list_x)))\\n #ax.yaxis.set_major_locator(ticker.FixedLocator((pos_list_z)))\\n #ax.yaxis.set_major_formatter(ticker.FixedFormatter((name_list_z)))\\n ax.get_xaxis().set_visible(False)\\n ax.get_yaxis().set_visible(False)\\n\\n\\n # turbulent particle sim xy-vew, Ddx=40\\n #r=20\\n #xy = [120,240]\\n# art = ptc.Circle(xy,r,color='black')\\n# ax.add_artist(art)\\n # uniform flow sim xy-vew, Ddx=64\\n # r=16\\n # xy = [160,320]\\n # Pencil-tests, Re=400, Ddx=96\\n #r=48\\n #xy = [480,960]\\n # Pencil-tests, Re=100, Ddx=64\\n r=32\\n xy = [320,640]\\n art = ptc.Circle(xy,r,color='black')\\n ax.add_artist(art)\\n \\n\\n #ax.add_patch(patches.Rectangle(\\n # (220,0),\\n # 40,\\n # 320,\\n # color='gray'\\n # )\\n #)\\n\\n image = plt.imshow(plane, vmin=amin, vmax=amax)\\n\\n # Get the figure manager for real-time image display.\\n manager = plt.get_current_fig_manager()\\n manager.show()\\n\\n ifirst = True\\n islice = 0\\n while True:\\n try:\\n raw_data = infile.fort_read(precision)\\n except ValueError:\\n break\\n except TypeError:\\n break\\n\\n if oldfile:\\n t = raw_data[-1]\\n plane = raw_data[:-1].reshape(vsize, hsize)\\n else:\\n t = raw_data[-2]\\n plane = raw_data[:-2].reshape(vsize, hsize)\\n\\n if transform:\\n exec('plane = plane' + transform)\\n\\n if t > tmin and t < tmax:\\n #title = 't = %11.3e' % t\\n #ax.set_title(title)\\n image.set_data(plane)\\n manager.canvas.draw()\\n\\n if ifirst:\\n #print \\\"----islice----------t---------min-------max-------delta\\\" # Python 2\\n print(\\\"----islice----------t---------min-------max-------delta\\\")\\n #print \\\"%10i %10.3e %10.3e %10.3e %10.3e\\\" \\\\ # Python 2\\n #% (islice, t, plane.min(), plane.max(), plane.max() - plane.min()) # Python 2\\n print(\\\"{0:10} {1:10.3e} {2:10.3e} {3:10.3e} {4:10.3e}\\\".format(islice, t, plane.min(), plane.max(), plane.max() - plane.min()))\\n\\n ifirst = False\\n fname = '_tmp%03d.eps' % islice\\n plt.savefig(fname,fonttype=42,\\n bbox_inches = 'tight', \\n # pad_inches = 0,\\n dpi = 600, transparant=True)\\n #plt.savefig(fname,fonttype=42)\\n islice += 1\\n\\n sleep(wait)\\n\\n infile.close()\",\n \"def _set_view_slice(self):\\n nd = self.dims.not_displayed\\n\\n if self.multichannel:\\n # if multichannel need to keep the final axis fixed during the\\n # transpose. The index of the final axis depends on how many\\n # axes are displayed.\\n order = self.dims.displayed_order + (self.dims.ndisplay,)\\n else:\\n order = self.dims.displayed_order\\n\\n # Slice thumbnail\\n indices = np.array(self.dims.indices)\\n downsampled = indices[nd] / self.level_downsamples[-1, nd]\\n downsampled = np.round(downsampled.astype(float)).astype(int)\\n downsampled = np.clip(downsampled, 0, self.level_shapes[-1, nd] - 1)\\n indices[nd] = downsampled\\n\\n image = np.asarray(self.data[-1][tuple(indices)]).transpose(order)\\n\\n if self.multichannel and image.dtype.kind == 'f':\\n self._data_thumbnail = np.clip(image, 0, 1)\\n else:\\n self._data_thumbnail = image\\n\\n # Slice currently viewed level\\n indices = np.array(self.dims.indices)\\n level = self.data_level\\n downsampled = indices[nd] / self.level_downsamples[level, nd]\\n downsampled = np.round(downsampled.astype(float)).astype(int)\\n downsampled = np.clip(downsampled, 0, self.level_shapes[level, nd] - 1)\\n indices[nd] = downsampled\\n\\n disp_shape = self.level_shapes[level, self.dims.displayed]\\n scale = np.ones(self.ndim)\\n for d in self.dims.displayed:\\n scale[d] = self.level_downsamples[self.data_level][d]\\n self._scale = scale\\n self.events.scale()\\n\\n if np.any(disp_shape > self._max_tile_shape):\\n for d in self.dims.displayed:\\n indices[d] = slice(\\n self._top_left[d],\\n self._top_left[d] + self._max_tile_shape,\\n 1,\\n )\\n self.translate = self._top_left * self.scale\\n else:\\n self.translate = [0] * self.ndim\\n\\n image = np.asarray(self.data[level][tuple(indices)]).transpose(order)\\n\\n if self.multichannel and image.dtype.kind == 'f':\\n self._data_view = np.clip(image, 0, 1)\\n else:\\n self._data_view = image\\n\\n self._update_thumbnail()\\n self._update_coordinates()\\n self.events.set_data()\",\n \"def box_transform_panels(page, type_choice=None, pattern=None):\\n\\n if type_choice is None:\\n type_choice_prob = np.random.random()\\n if type_choice_prob < cfg.panel_box_trapezoid_ratio:\\n type_choice = \\\"trapezoid\\\"\\n else:\\n type_choice = \\\"rhombus\\\"\\n\\n if type_choice == \\\"trapezoid\\\":\\n if page.num_panels > 2:\\n\\n # Get parent panel which satisfies the criteria for the transform\\n relevant_panels = find_parent_with_multiple_children(page, 3)\\n\\n if len(relevant_panels) > 0:\\n if len(relevant_panels) > 1:\\n num_panels = np.random.randint(1, len(relevant_panels))\\n else:\\n num_panels = 1\\n\\n # For each panel\\n for idx in range(0, num_panels):\\n panel = relevant_panels[idx]\\n\\n # Get the three child panels\\n # Since panels are created in order\\n p1 = panel.get_child(0)\\n p2 = panel.get_child(1)\\n p3 = panel.get_child(2)\\n\\n min_width = math.inf\\n min_height = math.inf\\n\\n # Get the smallest height and width\\n for child in [p1, p2, p3]:\\n\\n if child.width < min_width:\\n min_width = child.width\\n\\n if child.height < min_height:\\n min_height = child.height\\n\\n # Choose trapezoid pattern\\n if pattern is None:\\n trapezoid_pattern = np.random.choice([\\\"A\\\", \\\"V\\\"])\\n else:\\n trapezoid_pattern = pattern\\n\\n movement_proportion = np.random.randint(\\n 10,\\n cfg.trapezoid_movement_limit)\\n\\n # If parent panel is horizontal the children are vertical\\n if panel.orientation == \\\"h\\\":\\n\\n # Get how much the lines of the child panels move\\n # on the x axis to make the trapezoid\\n x_movement = min_width*(movement_proportion/100)\\n\\n # Make an A pattern horizontally\\n if trapezoid_pattern == \\\"A\\\":\\n\\n # Get the coords of the first line to be moved\\n line_one_top = (p1.x2y2[0] + x_movement,\\n p1.x2y2[1])\\n\\n line_one_bottom = (p1.x3y3[0] - x_movement,\\n p1.x3y3[1])\\n\\n # Move line between child 1 and 2\\n p1.x2y2 = line_one_top\\n p1.x3y3 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = line_one_top\\n p2.x4y4 = line_one_bottom\\n\\n # Get the coords of the second line to be moved\\n line_two_top = (p2.x2y2[0] - x_movement,\\n p2.x2y2[1])\\n line_two_bottom = (p2.x3y3[0] + x_movement,\\n p2.x3y3[1])\\n\\n # Move line two between child 2 and 3\\n p2.x2y2 = line_two_top\\n p2.x3y3 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_top\\n p3.x4y4 = line_two_bottom\\n\\n p3.refresh_coords()\\n\\n # Make a V pattern horizontally\\n else:\\n\\n # Get the coords of the first line to be moved\\n line_one_top = (p1.x2y2[0] - x_movement,\\n p1.x2y2[1])\\n\\n line_one_bottom = (p1.x3y3[0] + x_movement,\\n p1.x3y3[1])\\n\\n # Move line between child 1 and 2\\n p1.x2y2 = line_one_top\\n p1.x3y3 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = line_one_top\\n p2.x4y4 = line_one_bottom\\n\\n # Get the coords of the second line to be moved\\n line_two_top = (p2.x2y2[0] + x_movement,\\n p2.x2y2[1])\\n\\n line_two_bottom = (p2.x3y3[0] - x_movement,\\n p2.x3y3[1])\\n\\n # Move line two between child 2 and 3\\n p2.x2y2 = line_two_top\\n p2.x3y3 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_top\\n p3.x4y4 = line_two_bottom\\n\\n p3.refresh_coords()\\n\\n # If panel is vertical children are horizontal\\n # so the A and the V are at 90 degrees to the page\\n else:\\n # Get how much the lines of the child panels move\\n # on the y axis to make the trapezoid\\n y_movement = min_height*(movement_proportion/100)\\n\\n # Make an A pattern vertically\\n if trapezoid_pattern == \\\"A\\\":\\n\\n # Get the coords of the first line to be moved\\n line_one_top = (p2.x2y2[0],\\n p2.x2y2[1] + y_movement)\\n\\n line_one_bottom = (p2.x1y1[0],\\n p2.x1y1[1] - y_movement)\\n\\n # Move line between child 1 and 2\\n p2.x2y2 = line_one_top\\n p2.x1y1 = line_one_bottom\\n\\n p1.x3y3 = line_one_top\\n p1.x4y4 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n # Get the coords of the second line to be moved\\n line_two_top = (p2.x3y3[0],\\n p2.x3y3[1] - y_movement)\\n\\n line_two_bottom = (p2.x4y4[0],\\n p2.x4y4[1] + y_movement)\\n\\n # Move line two between child 2 and 3\\n p2.x3y3 = line_two_top\\n p2.x4y4 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_bottom\\n p3.x2y2 = line_two_top\\n\\n p3.refresh_coords()\\n # Make a V pattern vertically\\n else:\\n\\n # Get the coords of the first line to be moved\\n line_one_top = (p2.x2y2[0],\\n p2.x2y2[1] - y_movement)\\n\\n line_one_bottom = (p2.x1y1[0],\\n p2.x1y1[1] + y_movement)\\n\\n # Move line between child 1 and 2\\n p2.x2y2 = line_one_top\\n p2.x1y1 = line_one_bottom\\n\\n p1.x3y3 = line_one_top\\n p1.x4y4 = line_one_bottom\\n\\n p1.refresh_coords()\\n # Get the coords of the second line to be moved\\n line_two_top = (p2.x3y3[0],\\n p2.x3y3[1] + y_movement)\\n\\n line_two_bottom = (p2.x4y4[0],\\n p2.x4y4[1] - y_movement)\\n\\n # Move line two between child 2 and 3\\n p2.x3y3 = line_two_top\\n p2.x4y4 = line_two_bottom\\n\\n p2.refresh_coords()\\n p3.x1y1 = line_two_bottom\\n p3.x2y2 = line_two_top\\n\\n p3.refresh_coords()\\n\\n elif type_choice == \\\"rhombus\\\":\\n\\n if page.num_panels > 1:\\n\\n # Get parent panel which satisfies the criteria for the transform\\n relevant_panels = find_parent_with_multiple_children(page, 3)\\n\\n if len(relevant_panels) > 0:\\n\\n if len(relevant_panels) > 1:\\n num_panels = np.random.randint(1, len(relevant_panels))\\n else:\\n num_panels = 1\\n\\n for idx in range(0, num_panels):\\n\\n panel = relevant_panels[idx]\\n\\n # Since panels are created in order\\n p1 = panel.get_child(0)\\n p2 = panel.get_child(1)\\n p3 = panel.get_child(2)\\n\\n min_width = math.inf\\n min_height = math.inf\\n\\n # Get the smallest height and width\\n for child in [p1, p2, p3]:\\n\\n if child.width < min_width:\\n min_width = child.width\\n\\n if child.height < min_height:\\n min_height = child.height\\n\\n if pattern is None:\\n rhombus_pattern = np.random.choice([\\\"left\\\", \\\"right\\\"])\\n else:\\n rhombus_pattern = pattern\\n\\n movement_proportion = np.random.randint(\\n 10,\\n cfg.rhombus_movement_limit\\n )\\n\\n # Logic for the section below is the same as the\\n # trapezoid with the exception of the fact that the\\n # rhombus pattern happens to move both lines in the\\n # same direction\\n\\n if panel.orientation == \\\"h\\\":\\n\\n x_movement = min_width*(movement_proportion/100)\\n\\n if rhombus_pattern == \\\"left\\\":\\n line_one_top = (p1.x2y2[0] - x_movement,\\n p1.x2y2[1])\\n\\n line_one_bottom = (p1.x3y3[0] + x_movement,\\n p1.x3y3[1])\\n\\n p1.x2y2 = line_one_top\\n p1.x3y3 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = line_one_top\\n p2.x4y4 = line_one_bottom\\n\\n line_two_top = (p2.x2y2[0] - x_movement,\\n p2.x2y2[1])\\n\\n line_two_bottom = (p2.x3y3[0] + x_movement,\\n p2.x3y3[1])\\n\\n p2.x2y2 = line_two_top\\n p2.x3y3 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_top\\n p3.x4y4 = line_two_bottom\\n\\n p3.refresh_coords()\\n\\n else:\\n\\n line_one_top = (p1.x2y2[0] + x_movement,\\n p1.x2y2[1])\\n\\n line_one_bottom = (p1.x3y3[0] - x_movement,\\n p1.x3y3[1])\\n\\n p1.x2y2 = line_one_top\\n p1.x3y3 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = line_one_top\\n p2.x4y4 = line_one_bottom\\n\\n line_two_top = (p2.x2y2[0] + x_movement,\\n p2.x2y2[1])\\n\\n line_two_bottom = (p2.x3y3[0] - x_movement,\\n p2.x3y3[1])\\n\\n p2.x2y2 = line_two_top\\n p2.x3y3 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_top\\n p3.x4y4 = line_two_bottom\\n\\n p3.refresh_coords()\\n else:\\n y_movement = min_height*(movement_proportion/100)\\n\\n if rhombus_pattern == \\\"right\\\":\\n\\n line_one_top = (p2.x2y2[0],\\n p2.x2y2[1] + y_movement)\\n\\n line_one_bottom = (p2.x1y1[0],\\n p2.x1y1[1] - y_movement)\\n\\n p2.x2y2 = line_one_top\\n p2.x1y1 = line_one_bottom\\n\\n p1.x3y3 = line_one_top\\n p1.x4y4 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n line_two_top = (p2.x3y3[0],\\n p2.x3y3[1] + y_movement)\\n\\n line_two_bottom = (p2.x4y4[0],\\n p2.x4y4[1] - y_movement)\\n\\n p2.x3y3 = line_two_top\\n p2.x4y4 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_bottom\\n p3.x2y2 = line_two_top\\n\\n p3.refresh_coords()\\n else:\\n\\n line_one_top = (p2.x2y2[0],\\n p2.x2y2[1] - y_movement)\\n\\n line_one_bottom = (p2.x1y1[0],\\n p2.x1y1[1] + y_movement)\\n\\n p2.x2y2 = line_one_top\\n p2.x1y1 = line_one_bottom\\n\\n p1.x3y3 = line_one_top\\n p1.x4y4 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n line_two_top = (p2.x3y3[0],\\n p2.x3y3[1] - y_movement)\\n\\n line_two_bottom = (p2.x4y4[0],\\n p2.x4y4[1] + y_movement)\\n\\n p2.x3y3 = line_two_top\\n p2.x4y4 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_bottom\\n p3.x2y2 = line_two_top\\n\\n p3.refresh_coords()\\n\\n return page\",\n \"def part2(mem):\\n panels = paint_panels(mem, 1)\\n min_x, min_y, max_x, max_y = tuple(\\n f(k[i] for k in panels.keys()) for f in (min, max) for i in (0, 1)\\n )\\n drawing = [[\\\" \\\"] * (max_x - min_x + 1) for _ in range(min_y, max_y + 1)]\\n for (x, y), col in panels.items():\\n if col:\\n drawing[y][x] = \\\"\\\\u2588\\\"\\n return \\\"\\\\n\\\".join(f\\\" {''.join(line)}\\\" for line in drawing)\",\n \"def make_fwd_slice(shape, slices, reverse=None, cull_second=True):\\n if reverse is None:\\n reverse = []\\n if not isinstance(shape, (list, tuple, np.ndarray)):\\n shape = [shape]\\n if not isinstance(slices, (list, tuple)):\\n slices = [slices]\\n if not isinstance(reverse, (list, tuple)):\\n reverse = [reverse]\\n\\n newax_inds = [i for i, x in enumerate(slices) if x == np.newaxis]\\n shape = list(shape)\\n for i in newax_inds:\\n shape.insert(i, 1)\\n\\n # ya know, lets just go through all the dimensions in shape\\n # just to be safe and default to an empty slice / no reverse\\n slices = slices + [slice(None)] * (len(shape) - len(slices))\\n reverse = reverse + [False] * (len(slices) - len(reverse))\\n\\n first_slc = [slice(None)] * len(slices)\\n second_slc = [slice(None, None, 1)] * len(first_slc)\\n\\n for i, slc, L, rev in izip(count(), slices, shape, reverse):\\n if isinstance(slc, slice):\\n step = slc.step if slc.step is not None else 1\\n start = slc.start if slc.start is not None else 0\\n stop = slc.stop if slc.stop is not None else L\\n if start < 0:\\n start += L\\n if stop < 0:\\n stop += L\\n\\n # sanity check the start/stop since we're gunna be playing\\n # fast and loose with them\\n if start < 0 or stop < 0:\\n raise IndexError(\\\"((start = {0}) or (stop = {1})) < 0\\\"\\n \\\"\\\".format(start, stop))\\n if start > L or stop > L:\\n raise IndexError(\\\"((start={0}) or (stop={1})) > (L={2})\\\"\\n \\\"\\\".format(start, stop, L))\\n\\n # now do the math of flipping the slice if needed, these branches\\n # change start, stop, and step so they can be used to create a new\\n # slice below\\n if rev:\\n if step < 0:\\n step = -step\\n if slc.start is None:\\n start = L - 1\\n if slc.stop is None:\\n start = L - 1 - start\\n stop = None\\n else:\\n start, stop = L - 1 - start, L - 1 - stop\\n else:\\n start, stop = L - stop, L - start\\n start += ((stop - 1 - start) % step)\\n second_slc[i] = slice(None, None, -1)\\n elif step < 0:\\n step = -step\\n if slc.start is None:\\n start = L - 1\\n\\n if slc.stop is None:\\n start, stop = 0, start + 1\\n start = ((stop - 1 - start) % step)\\n else:\\n start, stop = stop + 1, start + 1\\n start += ((stop - 1 - start) % step)\\n\\n second_slc[i] = slice(None, None, -1)\\n\\n # check that our slice is valid\\n assert start is None or (0 <= start and start <= L), \\\\\\n \\\"start (={0}) is outside range\\\".format(start)\\n assert start is None or (0 <= start and start <= L), \\\\\\n \\\"start (={0}) is outside range\\\".format(start)\\n assert start is None or stop is None or start < stop, \\\\\\n \\\"bad slice ordering: {0} !< {1}\\\".format(start, stop)\\n assert step > 0\\n slc = slice(start, stop, step)\\n\\n elif isinstance(slc, (int, np.integer)):\\n second_slc[i] = None\\n if rev:\\n slc = (L - 1) - slc\\n\\n elif slc == np.newaxis:\\n second_slc[i] = \\\"NEWAXIS\\\"\\n\\n first_slc[i] = slc\\n\\n first_slc = [s for s in first_slc if s is not np.newaxis]\\n if cull_second:\\n second_slc = [s for s in second_slc if s is not None]\\n second_slc = [np.newaxis if s == \\\"NEWAXIS\\\" else s for s in second_slc]\\n return first_slc, second_slc\",\n \"def slide(x1, y1, x2, y2):\\n gui.mouseDown(x1, y1)\\n gui.moveTo(x2, y2)\\n release()\",\n \"def _independent_panel(width, height):\\n\\n from maya import cmds\\n\\n # center panel on screen\\n screen_width, screen_height = _get_screen_size()\\n topLeft = [int((screen_height-height)/2.0),\\n int((screen_width-width)/2.0)]\\n\\n window = cmds.window(width=width,\\n height=height,\\n topLeftCorner=topLeft,\\n menuBarVisible=False,\\n titleBar=False)\\n cmds.paneLayout()\\n panel = cmds.modelPanel(menuBarVisible=False,\\n label='CapturePanel')\\n\\n # Hide icons under panel menus\\n bar_layout = cmds.modelPanel(panel, q=True, barLayout=True)\\n cmds.frameLayout(bar_layout, e=True, collapse=True)\\n\\n cmds.showWindow(window)\\n\\n # Set the modelEditor of the modelPanel as the active view so it takes\\n # the playback focus. Does seem redundant with the `refresh` added in.\\n editor = cmds.modelPanel(panel, query=True, modelEditor=True)\\n cmds.modelEditor(editor, e=1, activeView=True)\\n\\n # Force a draw refresh of Maya so it keeps focus on the new panel\\n # This focus is required to force preview playback in the independent panel\\n cmds.refresh(force=True)\\n\\n try:\\n yield panel\\n finally:\\n # Delete the panel to fix memory leak (about 5 mb per capture)\\n cmds.deleteUI(panel, panel=True)\\n cmds.deleteUI(window)\",\n \"def DrawPanel(screen, panel_x, panel_y, panel_len, panel_width):\\n pygame.draw.rect(screen, (255,0,0),(panel_x, panel_y, panel_len*2, panel_width*2), 4)\",\n \"def slice(self, s=0, e=0):\\r\\n self.p = self.p[s:e]\\r\\n self.r = self.r[s:e]\\r\\n self.alpha = self.alpha[s:e]\\r\\n self.v = self.v[s:e]\\r\\n self.w = self.w[s:e]\\r\\n self.a = self.a[s:e]\",\n \"def split_window(num_x, num_y):\\n\\n viewPorts = np.zeros((num_x*num_y, 4))\\n counter = 0\\n for i in range(num_x):\\n for j in range(num_y):\\n viewPorts[num_x*j + i, :] = [i*(1.0/float(num_x)),\\n 1.0 - (j+1.0)*(1.0/float(num_y)),\\n (i+1.0)*1.0/float(num_x),\\n 1.0 - j*(1.0/float(num_y))\\n ] # [num_y*i + j,:] for vertical fill first\\n\\n return viewPorts\",\n \"def reshape(self, bottom, top):\\r\\n pass\",\n \"def UnsplitDClick(self, part, sash_size, pos):\\r\\n\\r\\n if not self._sash_dclick_unsplit:\\r\\n # Unsplit not allowed\\r\\n return\\r\\n\\r\\n pos1 = wx.Point(*pos)\\r\\n pos2 = wx.Point(*pos)\\r\\n if part.orientation == wx.HORIZONTAL:\\r\\n pos1.y -= 2*sash_size\\r\\n pos2.y += 2*sash_size + self.GetTabCtrlHeight()\\r\\n elif part.orientation == wx.VERTICAL:\\r\\n pos1.x -= 2*sash_size\\r\\n pos2.x += 2*sash_size\\r\\n else:\\r\\n raise Exception(\\\"Invalid UI part orientation\\\")\\r\\n\\r\\n pos1, pos2 = self.ClientToScreen(pos1), self.ClientToScreen(pos2)\\r\\n win1, win2 = wx.FindWindowAtPoint(pos1), wx.FindWindowAtPoint(pos2)\\r\\n\\r\\n if isinstance(win1, wx.ScrollBar):\\r\\n # Hopefully it will work\\r\\n pos1 = wx.Point(*pos)\\r\\n shift = wx.SystemSettings.GetMetric(wx.SYS_VSCROLL_X) + 2*(sash_size+1)\\r\\n if part.orientation == wx.HORIZONTAL:\\r\\n pos1.y -= shift\\r\\n else:\\r\\n pos1.x -= shift\\r\\n \\r\\n pos1 = self.ClientToScreen(pos1)\\r\\n win1 = wx.FindWindowAtPoint(pos1)\\r\\n\\r\\n if isinstance(win2, wx.ScrollBar):\\r\\n pos2 = wx.Point(*pos)\\r\\n shift = wx.SystemSettings.GetMetric(wx.SYS_VSCROLL_X) + 2*(sash_size+1)\\r\\n if part.orientation == wx.HORIZONTAL:\\r\\n pos2.y += shift\\r\\n else:\\r\\n pos2.x += shift\\r\\n\\r\\n pos2 = self.ClientToScreen(pos2)\\r\\n win2 = wx.FindWindowAtPoint(pos2)\\r\\n\\r\\n if not win1 or not win2:\\r\\n # How did we get here?\\r\\n return\\r\\n\\r\\n if isinstance(win1, AuiNotebook) or isinstance(win2, AuiNotebook):\\r\\n # This is a bug on MSW, for disabled pages wx.FindWindowAtPoint\\r\\n # returns the wrong window.\\r\\n # See http://trac.wxwidgets.org/ticket/2942\\r\\n return\\r\\n\\r\\n tab_frame1, tab_frame2 = self.GetTabFrameFromWindow(win1), self.GetTabFrameFromWindow(win2)\\r\\n\\r\\n if not tab_frame1 or not tab_frame2:\\r\\n return\\r\\n\\r\\n tab_ctrl_1, tab_ctrl_2 = tab_frame1._tabs, tab_frame2._tabs\\r\\n\\r\\n if tab_ctrl_1.GetPageCount() > tab_ctrl_2.GetPageCount():\\r\\n src_tabs = tab_ctrl_2\\r\\n dest_tabs = tab_ctrl_1\\r\\n else:\\r\\n src_tabs = tab_ctrl_1\\r\\n dest_tabs = tab_ctrl_2\\r\\n\\r\\n selection = -1\\r\\n page_count = dest_tabs.GetPageCount()\\r\\n \\r\\n for page in xrange(src_tabs.GetPageCount()-1, -1, -1):\\r\\n # remove the page from the source tabs\\r\\n page_info = src_tabs.GetPage(page)\\r\\n if page_info.active:\\r\\n selection = page_count + page\\r\\n src_tabs.RemovePage(page_info.window)\\r\\n\\r\\n # add the page to the destination tabs\\r\\n dest_tabs.AddPage(page_info.window, page_info)\\r\\n if page_info.control:\\r\\n self.ReparentControl(page_info.control, dest_tabs)\\r\\n \\r\\n self.RemoveEmptyTabFrames()\\r\\n\\r\\n dest_tabs.DoShowHide()\\r\\n self.DoSizing()\\r\\n dest_tabs.Refresh()\\r\\n self._mgr.Update()\\r\\n if selection > 0:\\r\\n wx.CallAfter(dest_tabs.MakeTabVisible, selection, self)\",\n \"def dest(side):\\n return (side - 1) % 3 # cw(side)\",\n \"def reshape(self, bottom, top):\\n\\t\\tpass\",\n \"def new_part(self, indices, master_axis_to_position, master_flip):\\n shape = self.shape\\n\\n if indices == [slice(0, stop, 1) for stop in shape]:\\n return\\n\\n # ------------------------------------------------------------\\n # If a dimension runs in the wrong direction then change its\\n # index to account for this.\\n #\\n # For example, if a dimension with the wrong direction has\\n # size 10 and its index is slice(3,8,2) then after the\\n # direction is set correctly, the index needs to changed to\\n # slice(6,0,-2):\\n #\\n # >>> a = [9, 8, 7, 6, 5, 4, 3, 2, 1, 0]\\n # >>> a[slice(3, 8, 2)]\\n # [6, 4, 2]\\n # >>> a.reverse()\\n # >>> print(a)\\n # >>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\\n # >>> a[slice(6, 0, -2)]\\n # [6, 4, 2]\\n # ------------------------------------------------------------\\n\\n if self._subarray.size > 1:\\n indices = indices[:]\\n\\n p_flip = self.flip\\n\\n for axis, i in master_axis_to_position.items():\\n\\n if (axis not in p_flip and axis not in master_flip) or (\\n axis in p_flip and axis in master_flip\\n ):\\n # This axis runs in the correct direction\\n continue\\n\\n # Still here? Then this axis runs in the wrong\\n # direction.\\n\\n # Reset the direction\\n p_flip = p_flip[:]\\n if axis in self.flip:\\n p_flip.remove(axis)\\n else:\\n p_flip.append(axis)\\n\\n # Modify the index to account for the changed\\n # direction\\n size = shape[i]\\n\\n if isinstance(indices[i], slice):\\n start, stop, step = indices[i].indices(size)\\n # Note that step is assumed to be always +ve here\\n div, mod = divmod(stop - start - 1, step)\\n start = size - 1 - start\\n stop = start - div * step - 1\\n if stop < 0:\\n stop = None\\n indices[i] = slice(start, stop, -step)\\n else:\\n size -= 1\\n indices[i] = [size - j for j in indices[i]]\\n # --- End: for\\n\\n self.flip = p_flip\\n # --- End: if\\n\\n slice_None = slice(None)\\n\\n # Reorder the new indices\\n indices = [\\n (\\n indices[master_axis_to_position[axis]]\\n if axis in master_axis_to_position\\n else slice_None\\n )\\n for axis in self.axes\\n ]\\n\\n part = self.part\\n\\n if not part:\\n self.part = indices\\n return\\n\\n # Still here? update an existing part\\n p_part = []\\n for part_index, index, size in zip(\\n part, indices, self._subarray.shape\\n ):\\n\\n if index == slice_None:\\n p_part.append(part_index)\\n continue\\n\\n if isinstance(part_index, slice):\\n if isinstance(index, slice):\\n\\n start, stop, step = part_index.indices(size)\\n\\n size1, mod = divmod(stop - start - 1, step)\\n\\n start1, stop1, step1 = index.indices(size1 + 1)\\n\\n size2, mod = divmod(stop1 - start1, step1)\\n\\n if mod != 0:\\n size2 += 1\\n\\n start += start1 * step\\n step *= step1\\n stop = start + (size2 - 1) * step\\n\\n if step > 0:\\n stop += 1\\n else:\\n stop -= 1\\n if stop < 0:\\n stop = None\\n p_part.append(slice(start, stop, step))\\n\\n continue\\n else:\\n new_part = list(range(*part_index.indices(size)))\\n new_part = [new_part[i] for i in index]\\n else:\\n if isinstance(index, slice):\\n new_part = part_index[index]\\n else:\\n new_part = [part_index[i] for i in index]\\n # --- End: if\\n\\n # Still here? Then the new element of p_part is a list of\\n # integers, so let's see if we can convert it to a slice\\n # before appending it.\\n new_part0 = new_part[0]\\n if len(new_part) == 1:\\n # Convert a single element list to a slice object\\n new_part = slice(new_part0, new_part0 + 1, 1)\\n else:\\n step = new_part[1] - new_part0\\n if step:\\n if step > 0:\\n start, stop = new_part0, new_part[-1] + 1\\n else:\\n start, stop = new_part0, new_part[-1] - 1\\n if new_part == list(range(start, stop, step)):\\n if stop < 0:\\n stop = None\\n new_part = slice(start, stop, step)\\n # --- End: if\\n\\n p_part.append(new_part)\\n # --- End: for\\n\\n self.part = p_part\",\n \"def plot_slices(hists, slice_width, fibre_pos):\\n pmt_info = rat.utility().GetPMTInfo()\\n # Find max angle\\n max_angle = 0\\n pmtIDs = hists.keys()\\n for pmtID in pmtIDs:\\n angle = taf.fibre_to_pmt_angle(fibre_pos, pmt_info.GetPosition(pmtID))\\n if angle > max_angle:\\n max_angle = angle\\n print max_angle\\n\\n # Step between 0 and max_angle in slices of slice_width\\n # create a plot of all pmt time spectra within each slice\\n ROOT.gStyle.SetPalette(1) \\n cuts = np.arange(0., max_angle+slice_width, slice_width)\\n for i, cut in enumerate(cuts): \\n tmpHists = []\\n if i > 0:\\n low_range = cuts[i-1]\\n hi_range = cuts[i]\\n s = ROOT.THStack(\\\"stack\\\", \\\"Slice: %1.1f - %1.1f deg\\\" % (low_range, hi_range)) \\n count = 0\\n for pmtID in pmtIDs:\\n angle = taf.fibre_to_pmt_angle(fibre_pos, pmt_info.GetPosition(pmtID))\\n if angle > low_range and angle < hi_range:\\n #print pmtID\\n count = count + 1\\n hists[pmtID].SetLineColor(count)\\n s.Add(hists[pmtID])\\n print \\\"Drawing...\\\"\\n s.Draw(\\\"nostack\\\")\\n s.GetHistogram().GetXaxis().SetTitle(\\\"Time (ns)\\\")\\n #s.Write()\\n #c1.BuildLegend(0.5, 0.2, 0.88, 0.88)\\n c1.Update()\\n c1.Modified()\\n c1.Print(\\\"./results/slices/Slice_%1.1f.png\\\" % low_range)\\n s.Delete()\\n #time.sleep(1)\",\n \"def pyramid_slice(x1,y1,x2,y2,z,delta,deltaz,taper_x,taper_y,taper_straight,layers):\\r\\n\\tcutlist = []\\r\\n\\ty_max = abs(y1-y2)\\r\\n\\tfor a in range(layers):\\r\\n\\t\\ti = 0\\r\\n\\t\\tnew_x1, new_y1, new_x2, new_y2 = x1 - a*taper_x, y1-a*taper_straight, x2+a*taper_x, y2+a*taper_y\\r\\n\\t\\twhile abs(new_y1 - (y1 - a*taper_straight)) < y_max and x1 > 0:\\r\\n\\t\\t\\tif i % 2 == 0:\\r\\n\\t\\t\\t\\tcutlist.append([\\\"jump\\\", f\\\"{new_x1:.6f}\\\", f\\\"{new_y1:.6f}\\\"])\\r\\n\\t\\t\\t\\tcutlist.append([\\\"mark\\\", f\\\"{new_x2:.6f}\\\", f\\\"{new_y1:.6f}\\\"])\\r\\n\\t\\t\\telse:\\r\\n\\t\\t\\t\\tcutlist.append([\\\"jump\\\", f\\\"{new_x2:.6f}\\\", f\\\"{new_y1:.6f}\\\"])\\r\\n\\t\\t\\t\\tcutlist.append([\\\"mark\\\", f\\\"{new_x1:.6f}\\\", f\\\"{new_y1:.6f}\\\"])\\r\\n\\t\\t\\tnew_y1 = new_y1-delta\\r\\n\\t\\t\\ti = i + 1\\r\\n\\t\\tif a < layers - 1:\\r\\n\\t\\t\\tcutlist.append([\\\"z_step\\\", str(-deltaz)])\\r\\n\\t\\ty_max = y_max - taper_straight - taper_y\\r\\n\\r\\n\\treturn cutlist\",\n \"def initialize_2panel_centy(Wfig=360, Hfig=270, fontsize=12, wsfrac=0.4, wssfrac=0.3, x0frac=0.1, hspace=10,\\n right3o4=False, right4o3=False):\\n fig = sps.figure_in_mm(Wfig, Hfig)\\n ws = wsfrac * Wfig\\n hs = ws\\n wss = wssfrac * Wfig\\n if right3o4:\\n hss = wss * 3. / 4.\\n elif right4o3:\\n hss = wss * 4. / 3.\\n else:\\n hss = wss\\n x0 = x0frac * Wfig\\n label_params = dict(size=fontsize, fontweight='normal')\\n ax = [sps.axes_in_mm(x0, y0, width, height, label=part, label_params=label_params)\\n for x0, y0, width, height, part in (\\n [x0, (Hfig - hs) * 0.5, ws, hs, ''],\\n [x0 + ws + hspace, (Hfig - hss) * 0.5, wss, hss, ''] # right panel\\n )]\\n return fig, ax\",\n \"def generate_panel(self):\\r\\n \\r\\n self.PanelData = self.RawData.filter(['ID', 'X', 'Z', 'W', 'R', 'β', 'LFP', 'H'], axis=1)\",\n \"def animate_slices(field='uu1', datadir='data/', proc=-1, extension='xz',\\n format='native', tmin=0., tmax=1.e38, wait=0.,\\n amin=0., amax=1., transform='', oldfile=False):\\n\\n import pylab as plt\\n\\n datadir = os.path.expanduser(datadir)\\n if proc < 0:\\n filename = join(datadir, 'slice_' + field + '.' + extension)\\n else:\\n filename = join(datadir, 'proc' + str(proc),\\n 'slice_' + field + '.' + extension)\\n\\n # Read the global dimensions.\\n dim = read_dim(datadir, proc)\\n if dim.precision == 'D':\\n precision = 'd'\\n else:\\n precision = 'f'\\n\\n # Set up slice plane.\\n if extension == 'xy' or extension == 'Xy':\\n hsize = dim.nx\\n vsize = dim.ny\\n if extension == 'xz':\\n hsize = dim.nx\\n vsize = dim.nz\\n if extension == 'yz':\\n hsize = dim.ny\\n vsize = dim.nz\\n plane = np.zeros((vsize, hsize), dtype=precision)\\n\\n infile = npfile(filename, endian=format)\\n\\n ax = plt.axes()\\n ax.set_xlabel('x')\\n ax.set_ylabel('y')\\n ax.set_ylim\\n\\n image = plt.imshow(plane, vmin=amin, vmax=amax)\\n\\n # Get the figure manager for real-time image display.\\n manager = plt.get_current_fig_manager()\\n manager.show()\\n\\n ifirst = True\\n islice = 0\\n while True:\\n try:\\n raw_data = infile.fort_read(precision)\\n except ValueError:\\n break\\n except TypeError:\\n break\\n\\n if oldfile:\\n t = raw_data[-1]\\n plane = raw_data[:-1].reshape(vsize, hsize)\\n else:\\n t = raw_data[-2]\\n plane = raw_data[:-2].reshape(vsize, hsize)\\n\\n if transform:\\n exec('plane = plane' + transform)\\n\\n if t > tmin and t < tmax:\\n title = 't = %11.3e' % t\\n ax.set_title(title)\\n image.set_data(plane)\\n manager.canvas.draw()\\n\\n if ifirst:\\n #print \\\"----islice----------t---------min-------max-------delta\\\" # Python 2\\n print(\\\"----islice----------t---------min-------max-------delta\\\")\\n #print \\\"%10i %10.3e %10.3e %10.3e %10.3e\\\" \\\\ # Python 2\\n #% (islice, t, plane.min(), plane.max(), plane.max() - plane.min()) # Python 2\\n print(\\\"{0:10} {1:10.3e} {2:10.3e} {3:10.3e} {4:10.3e}\\\".format(islice, t, plane.min(), plane.max(), plane.max() - plane.min()))\\n\\n ifirst = False\\n islice += 1\\n\\n sleep(wait)\\n\\n infile.close()\",\n \"def slice_explorer(data, cmap='gray'):\\n data_len = len(data)\\n\\n @interact(plane=(0, data_len-1), continuous_update=False)\\n def display_slice(plane=data_len/2):\\n fig, axis = plt.subplots(figsize=(20, 7))\\n axis_3d = fig.add_subplot(133, projection='3d')\\n show_plane(axis, data[plane], title='Plane {}'.format(plane), cmap=cmap)\\n slice_in_3d(axis=axis_3d, shape=data.shape, plane=plane)\\n plt.show()\\n\\n return display_slice\",\n \"def show_slices(slices):\\n fig, axes = plt.subplots(1, len(slices))\\n for i, slice in enumerate(slices):\\n axes[i].imshow(slice.T, cmap=\\\"gray\\\", origin=\\\"lower\\\")\",\n \"def animate_multislices(field=['uu1'], datadir='data/', proc=-1,\\n extension='xz', format='native', tmin=0., tmax=1.e38,\\n amin=0., amax=1., transform='plane[0]',\\n oldfile=False, outfile=\\\"\\\"):\\n\\n import pylab as plt\\n\\n datadir = os.path.expanduser(datadir)\\n if outfile != \\\"\\\":\\n outslice = open(outfile, \\\"w\\\")\\n filename = []\\n if proc < 0:\\n for i in field:\\n filename += [datadir + '/slice_' + i + '.' + extension]\\n else:\\n for i in field:\\n filename += [datadir + '/proc' +\\n str(proc) + '/slice_' + i + '.' + extension]\\n\\n # Read the global dimensions.\\n dim = read_dim(datadir, proc)\\n if dim.precision == 'D':\\n precision = 'd'\\n else:\\n precision = 'f'\\n\\n # Set up slice plane.\\n if extension == 'xy' or extension == 'Xy':\\n hsize = dim.nx\\n vsize = dim.ny\\n if extension == 'xz':\\n hsize = dim.nx\\n vsize = dim.nz\\n if extension == 'yz':\\n hsize = dim.ny\\n vsize = dim.nz\\n plane = []\\n infile = []\\n for i in filename:\\n plane += [np.zeros((vsize, hsize), dtype=precision)]\\n\\n infile += [npfile(i, endian=format)]\\n\\n ax = plt.axes()\\n ax.set_xlabel('x')\\n ax.set_ylabel('y')\\n ax.set_ylim\\n\\n exec('plotplane =' + transform)\\n image = plt.imshow(plotplane, vmin=amin, vmax=amax)\\n\\n # Get the figure manager for real-time image display.\\n manager = plt.get_current_fig_manager()\\n manager.show()\\n\\n ifirst = True\\n islice = 0\\n while True:\\n try:\\n raw_data = []\\n for i in infile:\\n raw_data += [i.fort_read(precision)]\\n except ValueError:\\n break\\n except TypeError:\\n break\\n\\n if oldfile:\\n t = raw_data[0][-1]\\n for i in range(len(raw_data)):\\n plane[i] = raw_data[i][:-1].reshape(vsize, hsize)\\n else:\\n t = raw_data[0][-2]\\n for i in range(len(raw_data)):\\n plane[i] = raw_data[i][:-2].reshape(vsize, hsize)\\n\\n exec('plotplane =' + transform)\\n\\n if t > tmin and t < tmax:\\n title = 't = %11.3e' % t\\n ax.set_title(title)\\n image.set_data(plotplane)\\n manager.canvas.draw()\\n\\n if ifirst:\\n #print \\\"----islice----------t---------min-------max-------delta\\\" # Python 2\\n print(\\\"----islice----------t---------min-------max-------delta\\\")\\n #print \\\"%10i %10.3e %10.3e %10.3e %10.3e\\\" % \\\\ # Python 2\\n #(islice, t, plotplane.min(), plotplane.max(), # Python 2\\n #plotplane.max() - plotplane.min()) # Python 2\\n print(\\\"{0:10} {1:10.3e} {2:10.3e} {3:10.3e} {4:10.3e}\\\".format(islice, t, plotplane.min(), plotplane.max(),\\n plotplane.max() - plotplane.min()))\\n if outfile != \\\"\\\":\\n #outslice.write(\\\"%10i %10.3e %10.3e %10.3e %10.3e\\\" % # Python 2\\n #(islice, t, plotplane.min(), plotplane.max(), # Python 2\\n #plotplane.max() - plotplane.min())) # Python 2\\n outslice.write(\\\"{0:10} {1:10.3e} {2:10.3e} {3:10.3e} {4:10.3e}\\\".format(islice, t, plotplane.min(), plotplane.max(), plotplane.max() - plotplane.min()))\\n outslice.write(\\\"\\\\n\\\")\\n\\n ifirst = False\\n islice += 1\\n\\n for i in infile:\\n i.close()\\n if outfile != \\\"\\\":\\n outslice.close()\",\n \"def add_frame_shift(self, basis, axis_settings):\\n angle, axis = angle_and_axis(basis)\\n\\n if angle == 0:\\n axis = (0,0,1)\\n\\n if basis.include_translation:\\n translation = basis.translation\\n else:\\n translation = (0,0,0)\\n\\n self.add_row([basis.axis_name,\\\"rotation\\\",\\\"detector\\\",basis.depends_on,\\n str(axis[0]),str(axis[1]),str(axis[2]),\\n str(translation[0]),\\n str(translation[1]),\\n str(translation[2]),\\n basis.equipment_component])\\n\\n axis_settings.append([basis.axis_name, \\\"FRAME1\\\", str(angle), \\\"0\\\"])\",\n \"def create_panel(self):\\n return\\n # return Panel(self)\",\n \"def show_slices(slices,clims=[0.0,0.0]):\\n fig, axes = plt.subplots(1,len(slices))\\n for i, slice in enumerate(slices):\\n if clims==[0.0,0.0]:\\n axes[i].imshow(slice.T, cmap='gray', origin=\\\"lower\\\")\\n else:\\n axes[i].imshow(slice.T, cmap='gray', origin=\\\"lower\\\", clim=clims)\",\n \"def show_slices(slices):\\n fig, axes = plt.subplots(1, len(slices))\\n for i, slice in enumerate(slices):\\n axes[i].imshow(slice.T, cmap=\\\"gray\\\", origin=\\\"lower\\\")\",\n \"def reshape(self, bottom, top):\\n pass\",\n \"def reshape(self, bottom, top):\\n pass\",\n \"def reshape(self, bottom, top):\\n pass\",\n \"def reshape(self, bottom, top):\\n pass\",\n \"def reshape(self, bottom, top):\\n pass\",\n \"def reshape(self, bottom, top):\\n pass\",\n \"def reshape(self, bottom, top):\\n pass\",\n \"def reshape(self, bottom, top):\\n pass\",\n \"def reshape(self, bottom, top):\\n pass\",\n \"def reshape(self, bottom, top):\\n pass\",\n \"def reshape(self, bottom, top):\\n pass\",\n \"def splice(features, left_num, right_num):\\n shape = tf.shape(features)\\n splices = []\\n pp = tf.pad(features, [[left_num, right_num], [0, 0]])\\n for i in range(left_num + right_num + 1):\\n splices.append(tf.slice(pp, [i, 0], shape))\\n splices = tf.concat(axis=1, values=splices)\\n\\n return splices\",\n \"def show_slices(self, slices):\\n fig, axes = plt.subplots(1, len(slices))\\n for i, slice in enumerate(slices):\\n axes[i].imshow(slice.T, cmap=\\\"gray\\\", origin=\\\"lower\\\")\",\n \"def planeSliceTOAFig(uxmax, uymax, dso, dsl, f, dm, m, n, ax, ay, npoints, xax = True, yax = True):\\n \\n # Calculate coefficients\\n rF2 = rFsqr(dso, dsl, f)\\n uF2x, uF2y = rF2*np.array([1./ax**2, 1./ay**2])\\n lc = lensc(dm, f)\\n alp = rF2*lc\\n coeff = alp*np.array([1./ax**2, 1./ay**2])\\n tg0 = tg0coeff(dso, dsl)\\n tdm0 = tdm0coeff(dm, f)\\n\\n # Calculate caustic intersections\\n ucross = polishedRoots(causticEqSlice, uxmax, uymax, args=(alp, m, n, ax, ay))\\n ncross = len(ucross)\\n upcross = mapToUp(ucross.T, alp, ax, ay)\\n p = np.argsort(upcross[0])\\n upcross = upcross.T[p]\\n ucross = ucross[p]\\n # print(upcross)\\n \\n # Set up quantities for proper u' plane slicing\\n ymin = -m*uxmax + n\\n ymax = m*uxmax + n\\n if ymin < -uymax:\\n xmin = (-uymax - n)/m\\n ymin = m*xmin + n\\n else:\\n xmin = -uxmax\\n if ymax > uymax:\\n xmax = (uymax - n)/m\\n ymax = m*xmax + n\\n else:\\n xmax = uxmax\\n \\n cdist = uxmax/(np.abs(50*lc))\\n \\n bound = np.insert(upcross, 0, np.array([[xmin, ymin]]), axis = 0) # set up boundaries\\n bound = np.append(bound, np.array([[xmax, ymax]]), axis = 0)\\n midpoints = [(bound[i] + bound[i+1])/2. for i in range(len(bound) - 1)] # find middle point between boundaries\\n nzones = len(midpoints)\\n nreal = np.zeros(nzones, dtype = int)\\n for i in range(nzones): # find number of roots at each midpoint\\n mpoint = midpoints[i]\\n nreal[i] = len(findRoots(lensEq, 2*uxmax, 2*uymax, args = (mpoint, coeff)))\\n upxvecs = np.array([np.linspace(bound[i-1][0] + cdist, bound[i][0] - cdist, npoints) for i in range(1, ncross + 2)]) # generate upx vector\\n segs = np.asarray([lineVert(upx, m, n) for upx in upxvecs]) # generate slice across plane\\n ncomplex = np.zeros(nzones) # don't care about complex solutions in this case\\n print(nreal)\\n \\n # Find roots\\n allroots = rootFinder(segs, nreal, ncomplex, npoints, ucross, uxmax, uymax, coeff)\\n \\n # Calculate TOAs\\n alltoas = []\\n for i in range(nzones):\\n toas = obsCalc(deltat, allroots[i], int(nreal[i]), npoints, 1, args = (tg0, tdm0, alp, ax, ay)).real\\n alltoas.append(toas)\\n \\n # Plots\\n fig, ax1 = plt.subplots(figsize=(10, 8), dpi = 100)\\n # grid = gs.GridSpec(2, 2, width_ratios=[4, 1])\\n # ax0 = plt.subplot(grid[1:, 1])\\n # ax1 = plt.subplot(grid[0, 1])\\n \\n \\n # ax2 = plt.subplot(grid[:, 0]) # Plot results\\n colors = assignColor(allroots, nreal)\\n l = []\\n for i in range(len(upxvecs)):\\n zone = alltoas[i]\\n for j in range(len(zone)):\\n line = ax1.plot(upxvecs[i], zone[j], color = colors[i][j], lw = 3.)\\n l.append(line)\\n for i in range(ncross):\\n ax1.plot([upcross[i][0], upcross[i][0]], [-100, 100], color = 'black', ls = 'dashed', scaley = False, scalex = False, lw = 2.5)\\n label = r'$\\\\nu = $' + str(f/GHz) + ' GHz'\\n ax1.text(0.05, 0.9, label, transform=ax1.transAxes, fontsize = 28, bbox=dict(facecolor = 'white', alpha=1.))\\n # ax1.set_ylim(min(alltoas.flatten() - 1), max(alltoas.flatten() + 1))\\n if not xax:\\n ax1.xaxis.set_ticklabels([])\\n else:\\n ax1.set_xlabel(r\\\"$u'_x$\\\", fontsize=28)\\n if not yax:\\n ax1.yaxis.set_ticklabels([])\\n else:\\n ax1.set_ylabel(r'$\\\\Delta t \\\\: (\\\\mu s)$', fontsize=28)\\n if dm > 0:\\n ax1.set_ylim(-0.5, 15.)\\n else:\\n ax1.set_ylim(-2.5, 10.)\\n ax1.tick_params(labelsize = 22)\\n ax1.grid()\\n \\n ax2 = inset_axes(ax1, width='18%', height='23%', loc=1)\\n rx = np.linspace(-uxmax, uxmax, 1000) # Plot caustic surfaces\\n ry = np.linspace(-uxmax, uxmax, 1000)\\n uvec = np.meshgrid(rx, ry)\\n ucaus = causCurve(uvec, coeff)\\n cs = ax2.contour(rx, ry, ucaus, levels = [0, np.inf], linewidths = 0)\\n paths = cs.collections[0].get_paths()\\n uppaths = []\\n for p in paths:\\n cuvert = np.array(p.vertices).T\\n upx, upy = mapToUp(cuvert, alp, ax, ay)\\n ax2.plot(upx, upy, color = 'blue')\\n ax2.plot(np.linspace(xmin, xmax, 10), np.linspace(ymin, ymax, 10), color = 'green')\\n ax2.scatter(upcross.T[0], upcross.T[1], color = 'green')\\n # ax2.set_xlabel(r\\\"$u'_x$\\\")\\n # ax2.set_ylabel(r\\\"$u'_y$\\\")\\n ax2.set_xlim(-uxmax, uxmax)\\n ax2.tick_params(labelsize = 16)\\n # ax1.set_title(\\\"Caustic curves\\\")\\n # ax1.set_aspect('equal', anchor = 'N')\\n ax2.grid()\\n # ax2.tight_layout()\\n \\n plt.tight_layout()\\n plt.show()\\n return\",\n \"def _fix_slice(self, inputs, new_attr):\\n begin = new_attr.get('begin')\\n end = new_attr.get('end')\\n axes = new_attr.get('axis', tuple(range(len(begin))))\\n slice_op = mx.sym.slice_axis(inputs[0], axis=axes[0], begin=begin[0], end=end[0])\\n if len(axes) > 1:\\n for i, axis in enumerate(axes):\\n slice_op = mx.sym.slice_axis(slice_op, axis=axis, begin=begin[i], end=end[i])\\n return slice_op\",\n \"def moveX(self, slice, dir=1):\\n\\n for p in self.pieces:\\n if slice > 1 or p.x == slice: # Filter pieces not in slice.\\n # Use PMatrix2D() to calculate position from rotation.\\n t = PMatrix2D()\\n t.rotate(dir * HALF_PI)\\n t.translate(p.y, p.z)\\n p.rX(dir)\\n p.pos(round(p.x), round(t.m02), round(t.m12))\",\n \"def _slice(self, start, stop, step=None):\\n\\n slices = [slice(None)] * self.data.ndim\\n slices[self.axis] = slice(start, stop, step)\\n return tuple(slices)\",\n \"def steerright(self):\\n self.direction = self.direction-self.steering\\n if self.direction < 0:\\n self.direction = 360-90\\n self.image, self.rect = rot_center(self.image_orig,self.rect,self.direction)\",\n \"def moveY(self, slice, dir=1):\\n\\n for p in self.pieces: # Filter pieces not in slice.\\n if slice > 1 or p.y == slice:\\n # Use PMatrix2D() to calculate position from rotation.\\n t = PMatrix2D()\\n t.rotate(dir * HALF_PI)\\n t.translate(p.x, p.z)\\n p.rY(dir)\\n p.pos(round(t.m02), round(p.y), round(t.m12))\",\n \"def slice_im(image_path, out_name, out_dir, sliceHeight=256, sliceWidth=256,\\n zero_frac_thresh=0.2, overlap=0.2, slice_sep='|',\\n out_ext='.png', verbose=False):\\n\\n use_cv2 = True\\n # read in image, cv2 fails on large files\\n print(\\\"Read in image:\\\", image_path)\\n try:\\n # convert to rgb (cv2 reads in bgr)\\n img_cv2 = cv2.imread(image_path, 1)\\n # print (\\\"img_cv2.shape:\\\", img_cv2.shape)\\n image0 = cv2.cvtColor(img_cv2, cv2.COLOR_BGR2RGB)\\n except:\\n image0 = skimage.io.imread(\\n image_path, as_grey=False).astype(np.uint8) # [::-1]\\n use_cv2 = False\\n print(\\\"image.shape:\\\", image0.shape)\\n # image0 = cv2.imread(image_path, 1) # color\\n\\n if len(out_ext) == 0:\\n ext = '.' + image_path.split('.')[-1]\\n else:\\n ext = out_ext\\n\\n win_h, win_w = image0.shape[:2]\\n\\n # if slice sizes are larger than image, pad the edges\\n pad = 0\\n if sliceHeight > win_h:\\n pad = sliceHeight - win_h\\n if sliceWidth > win_w:\\n pad = max(pad, sliceWidth - win_w)\\n # pad the edge of the image with black pixels\\n if pad > 0:\\n border_color = (0, 0, 0)\\n image0 = cv2.copyMakeBorder(image0, pad, pad, pad, pad,\\n cv2.BORDER_CONSTANT, value=border_color)\\n\\n win_size = sliceHeight*sliceWidth\\n\\n t0 = time.time()\\n n_ims = 0\\n n_ims_nonull = 0\\n dx = int((1. - overlap) * sliceWidth)\\n dy = int((1. - overlap) * sliceHeight)\\n\\n # for y0 in xrange(0, image0.shape[0], dy):#sliceHeight):\\n # for x0 in xrange(0, image0.shape[1], dx):#sliceWidth):\\n for y0 in range(0, image0.shape[0], dy): # sliceHeight):\\n for x0 in range(0, image0.shape[1], dx): # sliceWidth):\\n n_ims += 1\\n\\n if (n_ims % 50) == 0:\\n print(n_ims)\\n\\n # make sure we don't have a tiny image on the edge\\n if y0+sliceHeight > image0.shape[0]:\\n y = image0.shape[0] - sliceHeight\\n else:\\n y = y0\\n if x0+sliceWidth > image0.shape[1]:\\n x = image0.shape[1] - sliceWidth\\n else:\\n x = x0\\n\\n # extract image\\n window_c = image0[y:y + sliceHeight, x:x + sliceWidth]\\n # get black and white image\\n if use_cv2:\\n window = cv2.cvtColor(window_c, cv2.COLOR_BGR2GRAY)\\n else:\\n window = cv2.cvtColor(window_c, cv2.COLOR_RGB2GRAY)\\n\\n # find threshold that's not black\\n # https://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_imgproc/py_thresholding/py_thresholding.html?highlight=threshold\\n ret, thresh1 = cv2.threshold(window, 2, 255, cv2.THRESH_BINARY)\\n non_zero_counts = cv2.countNonZero(thresh1)\\n zero_counts = win_size - non_zero_counts\\n zero_frac = float(zero_counts) / win_size\\n # print \\\"zero_frac\\\", zero_fra\\n # skip if image is mostly empty\\n if zero_frac >= zero_frac_thresh:\\n if verbose:\\n print(\\\"Zero frac too high at:\\\", zero_frac)\\n continue\\n # else save\\n else:\\n # outpath = os.path.join(out_dir, out_name + \\\\\\n # '|' + str(y) + '_' + str(x) + '_' + str(sliceHeight) + '_' + str(sliceWidth) +\\\\\\n # '_' + str(pad) + ext)\\n outpath = os.path.join(\\n out_dir,\\n out_name + slice_sep + str(y) + '_' + str(x) + '_'\\n + str(sliceHeight) + '_' + str(sliceWidth)\\n + '_' + str(pad) + '_' + str(win_w) + '_' + str(win_h)\\n + ext)\\n\\n # outpath = os.path.join(out_dir, 'slice_' + out_name + \\\\\\n # '_' + str(y) + '_' + str(x) + '_' + str(sliceHeight) + '_' + str(sliceWidth) +\\\\\\n # '_' + str(pad) + '.jpg')\\n if verbose:\\n print(\\\"outpath:\\\", outpath)\\n # if large image, convert to bgr prior to saving\\n if not use_cv2:\\n skimage.io.imsave(outpath, window_c)\\n else:\\n cv2.imwrite(outpath, window_c)\\n n_ims_nonull += 1\\n\\n print(\\\"Num slices:\\\", n_ims, \\\"Num non-null slices:\\\", n_ims_nonull,\\n \\\"sliceHeight\\\", sliceHeight, \\\"sliceWidth\\\", sliceWidth)\\n print(\\\"Time to slice\\\", image_path, time.time()-t0, \\\"seconds\\\")\\n\\n return\",\n \"def panel_callback():\\n if self.minwidth is None:\\n self.minwidth = self.button_stack.winfo_width()\\n\\n if self.current_panel:\\n self.sashpos = self.paned.sashpos(0)\\n self.current_panel.forget()\\n if isinstance(self.current_panel, class_obj):\\n self.current_panel = None\\n self.paned.sashpos(0, self.minwidth)\\n return\\n\\n if class_obj.__name__ in self.panels:\\n panel = self.panels[class_name]\\n else:\\n panel = self.panels[class_name] = class_obj(self, self.app)\\n\\n panel.pack(side=tk.LEFT, expand=1, fill=tk.BOTH)\\n\\n if self.sashpos is None:\\n self.sashpos = 300\\n\\n self.paned.sashpos(0, self.sashpos)\\n\\n self.current_panel = panel\",\n \"def plot_slices(num_rows, num_columns, width, height, data):\\n# data = np.rot90(np.array(data))\\n data = np.transpose(data)\\n data = np.reshape(data, (num_rows, num_columns, width, height))\\n rows_data, columns_data = data.shape[0], data.shape[1]\\n heights = [slc[0].shape[0] for slc in data]\\n widths = [slc.shape[1] for slc in data[0]]\\n fig_width = 12.0\\n fig_height = fig_width * sum(heights) / sum(widths)\\n f, axarr = plt.subplots(\\n rows_data,\\n columns_data,\\n figsize=(fig_width, fig_height),\\n gridspec_kw={\\\"height_ratios\\\": heights},\\n )\\n for i in range(rows_data):\\n for j in range(columns_data):\\n axarr[i, j].imshow(data[i][j], cmap=\\\"gray\\\")\\n axarr[i, j].axis(\\\"off\\\")\\n plt.subplots_adjust(wspace=0, hspace=0, left=0, right=1, bottom=0, top=1)\\n plt.show()\",\n \"def _rotate(self):\\n \\r\\n if self.clr == 1: # (default rotation) \\r\\n # o o o o \\r\\n # o x x o x o o x\\r\\n # o o o o\\r\\n _colOffsets = [[-1,-1, 0, 0], [-1, 0, 0, 1], [ 1, 1, 0, 0], [ 1, 0, 0,-1]] #\\r\\n _rowOffsets = [[ 1, 0, 0,-1], [-1,-1, 0, 0], [-1, 0, 0, 1], [ 1, 1, 0, 0]] #\\r\\n elif self.clr == 2:\\r\\n # o o o o \\r\\n # o x o x x o x o\\r\\n # o o o o\\r\\n _colOffsets = [[-1,-1, 0, 0], [ 1, 0, 0,-1], [ 1, 1, 0, 0], [-1, 0, 0, 1]] #\\r\\n _rowOffsets = [[-1, 0, 0, 1], [-1,-1, 0, 0], [ 1, 0, 0,-1], [ 1, 1, 0, 0]] #\\n \\r\\n elif self.clr == 3: # \\r\\n # o o o o \\r\\n # x o x o x o x o\\r\\n # o o o o\\n \\r\\n _colOffsets = [[-1, 0, 0, 0], [-1,-1, 0, 1], [ 1, 0, 0, 0], [ 1, 1, 0,-1]] #\\r\\n _rowOffsets = [[ 1, 1, 0,-1], [-1, 0, 0, 0], [-1,-1, 0, 1], [ 1, 0, 0, 0]] #\\n \\r\\n elif self.clr == 4:\\r\\n # o o o o \\r\\n # x o x o x o x o\\r\\n # o o o o\\r\\n _colOffsets = [[-1, 0, 0, 0], [1, 1, 0, -1], [1, 0, 0,0], [-1, -1, 0,1]]\\n _rowOffsets = [[-1,-1, 0, 1], [-1,0, 0, 0], [1,1, 0,-1], [1,0, 0, 0]]\\n \\r\\n elif self.clr == 5: # o o\\r\\n # o x \\r\\n # x o x o o o o o x o\\r\\n # o o \\r\\n _colOffsets = [[ 0, 0, 0, 0], [ 2, 1, 0,-1], [ 0, 0, 0, 0], [-2,-1, 0, 1]] #\\r\\n _rowOffsets = [[-2,-1, 0, 1], [ 0, 0, 0, 0], [ 2, 1, 0,-1], [ 0, 0, 0, 0]] #\\r\\n elif self.clr == 6: #\\r\\n # o o o \\r\\n # o x o x o x o o x o\\r\\n # o o o \\r\\n _colOffsets = [[ 0,-1, 0, 0], [-1, 0, 0, 1], [ 0, 1, 0, 0], [ 1, 0, 0,-1]] #\\r\\n _rowOffsets = [[ 1, 0, 0,-1], [ 0,-1, 0, 0], [-1, 0, 0, 1], [ 0, 1, 0, 0]] #\\r\\n elif self.clr == 7: # \\r\\n # o o o o o o o o\\r\\n # o x o x o x o x\\r\\n # \\r\\n _colOffsets = [[-1,-1, 0, 0], [-1,-1, 0, 0], [-1,-1, 0, 0], [-1,-1, 0, 0]] #@@\\r\\n _rowOffsets = [[ 0,-1, 0,-1], [ 0,-1, 0,-1], [ 0,-1, 0,-1], [ 0,-1, 0,-1]] #@@\\n \\r\\n self._colOffsets = _colOffsets[self._rot] #@@\\r\\n self._rowOffsets = _rowOffsets[self._rot] #@@\\r\\n self._update() #@@\\r\",\n \"def transform_slice_backward(mat, coord_mat=None):\\n (nrow, ncol) = mat.shape\\n if nrow != ncol:\\n raise ValueError(\\\"Height and width of the image is not the same!\\\")\\n if coord_mat is None:\\n (r_mat, theta_mat) = polar_from_rectangular(ncol, ncol, ncol, ncol)\\n else:\\n (r_mat, theta_mat) = coord_mat\\n if (r_mat.shape != mat.shape) or (theta_mat.shape != mat.shape):\\n raise ValueError(\\\"Shape of the coordinate array is not the same as\\\"\\n \\\" the shape of the image!\\\")\\n return mapping(mat, r_mat, theta_mat)\",\n \"def cutout(self, slices: tuple):\\n if len(slices) == self.ndim - 1:\\n slices = (slice(0, self.shape[0]), ) + slices\\n internalSlices = self._get_internal_slices(slices)\\n arr = self.array[internalSlices]\\n global_offset = tuple(s.start for s in slices)\\n return Chunk(arr, global_offset=global_offset)\",\n \"def get2DSlice( self, slices: list ):\\n assert(len(slices)==self._nDims-2)\\n slices.extend([slice(self._nGlobalCoords[self._layout.dims_order[-2]]),\\n slice(self._nGlobalCoords[self._layout.dims_order[-1]])])\\n return self._f[tuple(slices)]\",\n \"def image_clip_to_segment_and_convert(image_ms_array, image_pan_array, mask_array, factor, image_height_size, \\r\\n image_width_size):\\r\\n \\r\\n img_pan_list = []\\r\\n img_ms_list = []\\r\\n mask_list = []\\r\\n \\r\\n n_bands = image_ms_array.shape[2]\\r\\n \\r\\n for i in range(0, image_pan_array.shape[0] - image_height_size, int(factor)):\\r\\n for j in range(0, image_pan_array.shape[1] - image_width_size, int(factor)):\\r\\n M_90 = cv2.getRotationMatrix2D((image_width_size / 2, image_height_size / 2), 90, 1.0)\\r\\n M_180 = cv2.getRotationMatrix2D((image_width_size / 2, image_height_size / 2), 180, 1.0)\\r\\n M_270 = cv2.getRotationMatrix2D((image_width_size / 2, image_height_size / 2), 270, 1.0)\\r\\n \\r\\n img_original = image_pan_array[i : i + image_height_size, j : j + image_width_size, 0]\\r\\n img_rotate_90 = cv2.warpAffine(img_original, M_90, (image_height_size, image_width_size))\\r\\n img_rotate_180 = cv2.warpAffine(img_original, M_180, (image_width_size, image_height_size))\\r\\n img_rotate_270 = cv2.warpAffine(img_original, M_270, (image_height_size, image_width_size))\\r\\n img_flip_hor = cv2.flip(img_original, 0)\\r\\n img_flip_vert = cv2.flip(img_original, 1)\\r\\n img_flip_both = cv2.flip(img_original, -1)\\r\\n img_pan_list.extend([img_original, img_rotate_90, img_rotate_180, img_rotate_270, img_flip_hor, img_flip_vert, \\r\\n img_flip_both])\\r\\n mask_patch = mask_array[i : i + image_height_size, j : j + image_width_size, 0]\\r\\n label = mask_patch[int(image_height_size / 2), int(image_width_size / 2)]\\r\\n mask_list.extend([label] * 7)\\r\\n \\r\\n for i in range(0, int(image_ms_array.shape[0] - (image_height_size / factor)), 1):\\r\\n for j in range(0, int(image_ms_array.shape[1] - (image_width_size / factor)), 1):\\r\\n M_90_ms = cv2.getRotationMatrix2D(((image_width_size / factor) / 2, (image_height_size / factor) / 2), 90, 1.0)\\r\\n M_180_ms = cv2.getRotationMatrix2D(((image_width_size / factor) / 2, (image_height_size / factor) / 2), 180, 1.0)\\r\\n M_270_ms = cv2.getRotationMatrix2D(((image_width_size / factor) / 2, (image_height_size / factor) / 2), 270, 1.0)\\r\\n \\r\\n img_original = image_ms_array[i : i + image_height_size, j : j + image_width_size, 0 : n_bands]\\r\\n img_rotate_90 = cv2.warpAffine(img_original, M_90_ms, (image_height_size, image_width_size))\\r\\n img_rotate_180 = cv2.warpAffine(img_original, M_180_ms, (image_width_size, image_height_size))\\r\\n img_rotate_270 = cv2.warpAffine(img_original, M_270_ms, (image_height_size, image_width_size))\\r\\n img_flip_hor = cv2.flip(img_original, 0)\\r\\n img_flip_vert = cv2.flip(img_original, 1)\\r\\n img_flip_both = cv2.flip(img_original, -1)\\r\\n img_ms_list.extend([img_original, img_rotate_90, img_rotate_180, img_rotate_270, img_flip_hor, img_flip_vert, \\r\\n img_flip_both])\\r\\n \\r\\n image_pan_segment_array = np.zeros((len(img_pan_list), image_height_size, image_width_size, image_pan_array.shape[2]))\\r\\n image_ms_segment_array = np.zeros((len(img_ms_list), int(image_height_size / factor), int(image_width_size / factor), \\r\\n image_ms_array.shape[2]))\\r\\n \\r\\n for index in range(len(img_pan_list)):\\r\\n image_pan_segment_array[index] = img_pan_list[index]\\r\\n image_ms_segment_array[index] = img_ms_list[index]\\r\\n \\r\\n mask_array = np.array(mask_list)\\r\\n \\r\\n return image_ms_segment_array, image_pan_segment_array, mask_array\",\n \"def sub(slice_left, slice_right):\\n start = 0\\n stop = 0\\n if slice_left.start == slice_right.start:\\n start = min(slice_left.stop, slice_right.stop)\\n stop = max(slice_left.stop, slice_right.stop)\\n if slice_left.stop == slice_right.stop:\\n start = min(slice_left.start, slice_right.start)\\n stop = max(slice_left.start, slice_right.start)\\n\\n return slice(start, stop)\",\n \"def make_slice_plot(aa=0.2000,Npix=128,Lbox=1024.):\\n # Set up some parameters.\\n Npart = 10240.\\n mpart = 0.3*2.7755e11*(Lbox/Npart)**3\\n scales = [1.0,10.0,100.0]\\t\\t# The zoom levels.\\n dscale = [1.0, 5.,25.]\\t\\t# The density scaling for the arcsinh.\\n dmaxs = [5.0,10.,100]\\t\\t# The density scaling for the arcsinh.\\n # Work out the centering position.\\n ff=open(dbh+\\\"000000\\\",\\\"rb\\\")\\n pos=np.fromfile(ff,dtype=('f4',3))\\n ff.close()\\n pos/=Lbox\\n ctr=pos[0,:]\\n print(\\\"Centering at \\\",ctr)\\n # Set the bounds.\\n xmin,xmax = -0.5000,0.5000\\n ymin,ymax = -0.5000,0.5000\\n zmin,zmax = -5/Lbox,5/Lbox\\n area = (xmax-xmin)*(ymax-ymin)\\n # Now make the figure.\\n clab = 'silver'\\t# Color for the label.\\n cbar = 'silver'\\t# Color for the scale bar.\\n fig,ax = plt.subplots(2,3,figsize=(6,4),sharex=True,sharey=True)\\n for ix in range(ax.shape[0]):\\n for iy in range(ax.shape[1]):\\n ii = ix*ax.shape[1] + iy\\n ss = scales[ii%len(scales)]\\n dd = np.zeros( (Npix,Npix) ,dtype='float')\\n # Read the data from file. We re-read the data each time,\\n # which is I/O inefficient but reduces the memory footprint.\\n if ix==0:\\t# DM.\\n ntotal=0\\n for fn in sorted(glob.glob(dbm+\\\"0000*\\\")):\\n ff=open(fn,\\\"rb\\\")\\n pos=np.fromfile(ff,dtype=('f4',3))\\n ff.close()\\n pos/=Lbox\\n # Periodically rewrap around ctr.\\n rr = pos-ctr\\n rr[rr<-0.5] += 1.0\\n rr[rr> 0.5] -= 1.0\\n # Trim to the slice in z -- this is always the same\\n # width. Also keep track of how many particles pass.\\n ww=np.nonzero( (rr[:,2]>zmin)&(rr[:,2]<zmax) )[0]\\n rr=rr[ww,:2]\\n ntotal+=rr.shape[0]\\n # Scale the data and cut to the required region (area).\\n rr *= ss\\t# Scale.\\n yy = np.histogram2d(rr[:,0]+0.5,rr[:,1]+0.5,\\\\\\n bins=Npix,range=[[0,1],[0,1]])[0]\\n dd += yy.astype('float')\\n # Assume the slice as a whole is at mean density.\\n mdens = ntotal*area/ss**2/float(Npix**2)\\n dd = dd/mdens\\n print(ii,ntotal,mdens,np.min(dd),np.max(dd))\\n else:\\t# HI\\n ntotal=0\\n for fn in sorted(glob.glob(dbh+\\\"0000*\\\")):\\n ff=open(fn,\\\"rb\\\")\\n pos=np.fromfile(ff,dtype=('f4',3))\\n ff.close()\\n pos/=Lbox\\n ff=open(fn.replace(\\\"Position\\\",\\\"Length\\\"),\\\"rb\\\")\\n mh=np.fromfile(ff,dtype='i4') * mpart\\n ff.close()\\n # Periodically rewrap around ctr.\\n rr = pos-ctr\\n rr[rr<-0.5] += 1.0\\n rr[rr> 0.5] -= 1.0\\n # Trim to the slice in z -- this is always the same\\n # width. Also keep track of how many halos pass.\\n ww=np.nonzero( (rr[:,2]>zmin)&(rr[:,2]<zmax) )[0]\\n rr=rr[ww,:2]\\n mh=mh[ww]\\n # Scale the data and cut to the required region (area).\\n mHI = HI_mass(mh,aa)\\n rr *= ss\\t# Scale.\\n yy = np.histogram2d(rr[:,0]+0.5,rr[:,1]+0.5,\\\\\\n weights=mHI,\\\\\\n bins=Npix,range=[[0,1],[0,1]])[0]\\n dd += yy.astype('float')\\n ntotal+= np.sum(mHI)\\n # Assume the slice as a whole is at mean density.\\n mdens = ntotal*area/ss**2/float(Npix**2)\\n dd = dd/mdens\\n print(ii,ntotal,mdens,np.min(dd),np.max(dd))\\n # Plot the data, scaled.\\n #ax[ix,iy].imshow(np.arcsinh(dd.T/dscale[ii%len(dscale)]),\\\\\\n # aspect='equal',extent=[0,1,0,1],\\\\\\n # vmin=0,vmax=np.arcsinh(5.0))\\n #ax[ix,iy].imshow(np.arcsinh(dd.T),\\\\\\n # aspect='equal',extent=[0,1,0,1],\\\\\\n # vmin=0,vmax=np.arcsinh(dmaxs[ii%len(dmaxs)]), cmap='hot')\\n ax[ix,iy].imshow(np.log(1+dd.T),\\\\\\n aspect='equal',extent=[0,1,0,1],\\\\\\n vmin=0,vmax=np.log(1+dd.max()), cmap='hot')\\n # Put on a scale bar.\\n xmin,xmax,yval = 0.10,0.10+0.1*(1e3/Lbox),0.95\\n scale_text = r'$\\\\mathbf{'+\\\"{:.0f}\\\".format(100./ss)+\\\\\\n r'\\\\,h^{-1}}$Mpc'\\n ax[ix,iy].plot([xmin,xmax],[yval,yval],'-',color=cbar,lw=2)\\n ax[ix,iy].text(xmin,yval-0.05,scale_text,fontweight='bold',\\\\\\n ha='left',va='top',color=cbar)\\n # Tidy up the plot.\\n ax[ix,iy].set_aspect('equal')\\n ax[ix,iy].set_xticks([])\\n ax[ix,iy].set_yticklabels('')\\n ax[ix,iy].set_xticks([])\\n ax[ix,iy].set_yticklabels('')\\n #\\n # Put on some more labels.\\n ax[0,0].text(0.05,0.05,r'DM',color=clab,fontweight='bold')\\n ax[1,0].text(0.05,0.05,r'HI',color=clab,fontweight='bold')\\n # and finish up.\\n plt.tight_layout()\\n plt.savefig('../../figs/slices.pdf')\\n #\",\n \"def rotate_half(x):\\n x1 = x[..., : x.shape[-1] // 2]\\n x2 = x[..., x.shape[-1] // 2 :]\\n return torch.cat((-x2, x1), dim=-1)\",\n \"def chained_slice(s1, s2):\\n\\n assert (s1.start >= 0 and s2.start >= 0 and s1.stop >= 0 and s2.stop >= 0)\\n s1_start = s1.start or 0\\n s2_start = s2.start or 0\\n s1_step = s1.step or 1\\n s2_step = s2.step or 1\\n\\n start = s1_start + s2_start * s1_step\\n step = s1_step * s2_step\\n if s1.stop is None and s2.stop is None:\\n stop = None\\n elif s1.stop is None:\\n stop = start + step * (s2.stop - s2_start) // s2_step\\n elif s2.stop is None:\\n stop = s1.stop\\n else:\\n stop_s2 = start + step * (s2.stop - s2_start) // s2_step\\n stop_s1 = s1.stop\\n stop = stop_s2 if stop_s2 < stop_s1 else stop_s1\\n return slice(start, stop, step)\",\n \"def close_mask_in(im_slice_2d, side):\\n new_slice = im_slice_2d.copy()\\n \\n x_no_0, y_no_0 = np.nonzero(im_slice_2d)\\n if len(x_no_0) == 0: return new_slice, new_slice\\n #breakpoint()\\n x1 = x_no_0.min() \\n x2 = x_no_0.max()\\n if side == \\\"l\\\":\\n x_mid = x2; x_aux1 = x_mid - 9 + 1; x_aux2 = x2 + 1\\n elif side == \\\"r\\\":\\n x_mid = x1; x_aux2 = x_mid + 9; x_aux1 = x1\\n \\n y_mid = y_no_0[np.where(x_no_0==x_mid)[0]].min()\\n y_min = y_no_0.min()\\n \\n # inferior line\\n new_slice[x1:x2+1, y_min] = 1\\n # medial line\\n new_slice[x_mid, y_min:y_mid+1] = 1\\n new_slice = binary_fill_holes(new_slice)\\n # in_short array:\\n other_slice = new_slice.copy() \\n other_slice[x_aux1:x_aux2, :] = 0\\n \\n return new_slice, other_slice\",\n \"def _data_move_out_last_dim_lt_one_block(tik_inst, dst, src, data_pos_info):\\n sub_axis_1, sub_axis_0, axis_0, axis_1, axis_2, out_offset = data_pos_info\\n data_size_one_block = _get_elment_cnt_one_block(src.dtype)\\n\\n with tik_inst.if_scope(sub_axis_1 == 1):\\n with tik_inst.if_scope(sub_axis_0 * axis_2 > data_size_one_block):\\n sub_axis_0_2 = sub_axis_0 * axis_2\\n sub_axis_0_block_align = sub_axis_0_2 // data_size_one_block\\n left_data = sub_axis_0_2 % data_size_one_block\\n tik_inst.data_move(dst[out_offset], src, 0, 1, sub_axis_0_block_align, 0, 0)\\n with tik_inst.if_scope(left_data > 0):\\n with tik_inst.new_stmt_scope():\\n reg_temp = [tik_inst.Scalar(src.dtype)\\n for i in ADDR_IDX_LIST[:data_size_one_block]]\\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\\n reg_temp[idx].set_as(src[sub_axis_0_2 - data_size_one_block + idx])\\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\\n src[idx].set_as(reg_temp[idx])\\n tik_inst.data_move(dst[out_offset + sub_axis_0_2 - data_size_one_block],\\n src, 0, 1, 1, 0, 0)\\n with tik_inst.else_scope():\\n # for case sub_axis_0 * axis_2 < data_size_one_block\\n with tik_inst.if_scope(axis_0 * axis_1 * axis_2 > data_size_one_block):\\n m_sub_axis_0 = _ceil_div(data_size_one_block, axis_2)\\n sub_axis_0_2 = m_sub_axis_0 * axis_2\\n sub_axis_0_block_align = sub_axis_0_2 // data_size_one_block\\n left_data = sub_axis_0_2 % data_size_one_block\\n tik_inst.data_move(dst[out_offset + (sub_axis_0 - m_sub_axis_0) * axis_2],\\n src, 0, 1, sub_axis_0_block_align, 0, 0)\\n with tik_inst.if_scope(left_data > 0):\\n with tik_inst.new_stmt_scope():\\n reg_temp = [tik_inst.Scalar(src.dtype)\\n for i in ADDR_IDX_LIST[:data_size_one_block]]\\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\\n reg_temp[idx].set_as(src[sub_axis_0_2 - data_size_one_block + idx])\\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\\n src[idx].set_as(reg_temp[idx])\\n tik_inst.data_move(dst[out_offset + sub_axis_0 * axis_2 -\\n data_size_one_block],\\n src, 0, 1, 1, 0, 0)\\n with tik_inst.else_scope():\\n # the shape size is not bigger than one block size\\n tik_inst.data_move(dst[out_offset], src, 0, 1,\\n _ceil_div(axis_0 * axis_1 * axis_2, data_size_one_block), 0, 0)\\n\\n with tik_inst.else_scope():\\n with tik_inst.if_scope(sub_axis_1 * axis_0 * axis_2 > data_size_one_block):\\n sub_axis_1_0_2 = sub_axis_1 * axis_0 * axis_2\\n sub_axis_1_0_2_block_align = sub_axis_1_0_2 // data_size_one_block\\n left_data = sub_axis_1_0_2 % data_size_one_block\\n tik_inst.data_move(dst[out_offset], src, 0, 1, sub_axis_1_0_2_block_align, 0, 0)\\n with tik_inst.if_scope(left_data > 0):\\n with tik_inst.new_stmt_scope():\\n reg_temp = [tik_inst.Scalar(src.dtype)\\n for i in ADDR_IDX_LIST[:data_size_one_block]]\\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\\n reg_temp[idx].set_as(src[sub_axis_1_0_2 - data_size_one_block + idx])\\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\\n src[idx].set_as(reg_temp[idx])\\n tik_inst.data_move(dst[out_offset + sub_axis_1_0_2 - data_size_one_block],\\n src, 0, 1, 1, 0, 0)\\n with tik_inst.else_scope():\\n # to make sure move in data size is not less than one block\\n with tik_inst.if_scope(axis_0 * axis_1 * axis_2 > data_size_one_block):\\n m_sub_axis_1 = _ceil_div(data_size_one_block, axis_0 * axis_2)\\n sub_axis_1_0_2 = m_sub_axis_1 * axis_0 * axis_2\\n sub_axis_0_block_align = sub_axis_1_0_2 // data_size_one_block\\n left_data = sub_axis_1_0_2 % data_size_one_block\\n tik_inst.data_move(dst[out_offset + (sub_axis_1 - m_sub_axis_1) * axis_0 * axis_2],\\n src, 0, 1, sub_axis_0_block_align, 0, 0)\\n with tik_inst.if_scope(left_data > 0):\\n with tik_inst.new_stmt_scope():\\n reg_temp = [tik_inst.Scalar(src.dtype)\\n for i in ADDR_IDX_LIST[:data_size_one_block]]\\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\\n reg_temp[idx].set_as(src[sub_axis_1_0_2 - data_size_one_block + idx])\\n for idx in ADDR_IDX_LIST[:data_size_one_block]:\\n src[idx].set_as(reg_temp[idx])\\n tik_inst.data_move(dst[out_offset + sub_axis_1 * axis_0 * axis_2 -\\n data_size_one_block],\\n src, 0, 1, 1, 0, 0)\\n with tik_inst.else_scope():\\n # the shape size is not bigger than one block size\\n tik_inst.data_move(dst[out_offset], src, 0, 1,\\n _ceil_div(axis_0 * axis_1 * axis_2, data_size_one_block), 0, 0)\",\n \"def squeeze_slices(self, slices):\\n return tuple(\\n slice(\\n None if sl.start is None else sl.start if sl.start > bounds.start else bounds.start,\\n None if sl.stop is None else sl.stop if sl.stop < bounds.stop else bounds.stop,\\n )\\n for bounds, sl in zip(self.data.bounds(), slices)\\n )\",\n \"def slice_layer(start, end, step=None, axis=1):\\n if axis < 0:\\n raise ValueError(\\\"'slice_layer' can only work on a specified axis > 0\\\")\\n\\n def slice_func(x):\\n slices = [slice(None)] * axis\\n slices.append(slice(start, end, step))\\n return x[tuple(slices)]\\n\\n return Lambda(slice_func)\",\n \"def carve_slice(\\n self, x_index=0, width=config()[\\\"panel\\\"][\\\"width\\\"],\\n ):\\n piece = []\\n for row in self.grid:\\n piece.append(row[x_index : x_index + width])\\n\\n return piece\",\n \"def get_4d(slice, copylayers=[], transparancy=0):\\n assert slice.ndim < 3\\n img = np.zeros(slice.shape)\\n img = img[:, :, np.newaxis]\\n img = np.repeat(img, 4, 2)\\n transparancy = 255 - (255 * transparancy)\\n img[:, :, -1] = transparancy\\n for layer in copylayers:\\n img[:, :, layer] = slice\\n return(img)\",\n \"def RotateSliceView (self, Node, sliceViewName):\\n volNode = Node\\n sliceNode = slicer.app.layoutManager().sliceWidget(sliceViewName).mrmlSliceNode()\\n sliceToRas = sliceNode.GetSliceToRAS()\\n VtkMatrix = vtk.vtkMatrix4x4()\\n volNode.GetIJKToRASMatrix(VtkMatrix)\\n M = np.zeros((4,4)) #### IJK To RAS Numpy Matrix \\n for i in range (4):\\n for j in range (4):\\n M[i,j] = VtkMatrix.GetElement(i,j)\\n\\n Dim = volNode.GetImageData().GetDimensions()\\n t = M.dot(np.array([(Dim[0]-1)/2,(Dim[1]-1)/2,0,1]))\\n for i in range (4):\\n VtkMatrix.SetElement(i,3,t[i])\\n VtkMatrix.SetElement(i,2,VtkMatrix.GetElement(i,2)/-10) \\n VtkMatrix.SetElement(i,1,VtkMatrix.GetElement(i,1)*-1) # The minus sign, above and here, is a Pi rotation around the X axis.\\n\\n sliceToRas.DeepCopy(VtkMatrix)\\n sliceNode.UpdateMatrices()\\n sliceNode.RotateToVolumePlane(volNode)\",\n \"def _sidepanel(self):\\n global curdir\\n global sidepanel_layout\\n global root\\n\\n #Create the sidepanel layout.\\n sidepanel_layout = BoxLayout(orientation=\\\"vertical\\\", pos_hint={\\\"x\\\": 0.0, \\\"top\\\": 0.92}, size_hint=(0.1, 0.92))\\n\\n #If \\\"curdir\\\" contains folders, a button is created for each, and bind the button to update the\\n # showphotos layout.\\n if curdir == \\\" \\\":\\n return sidepanel_layout\\n else:\\n root.remove_widget(sidepanel_layout)\\n for folders in sorted(glob(join(curdir, \\\"thumb\\\", \\\"*\\\"))):\\n name = basename(folders)\\n btn = Button(text=name, on_press=lambda n=name: self._update_scroll(n.text))\\n sidepanel_layout.add_widget(btn)\\n root.add_widget(sidepanel_layout)\\n sidepanel_layout.do_layout()\",\n \"def RotatedPlaneArray(plane,tot_ang,divs,axis):\\n out_planes=[]\\n plane.Rotate(-tot_ang*0.5,axis)\\n out_planes.append(Rhino.Geometry.Plane(plane))\\n inc=tot_ang/(divs-1)\\n for i in range(divs-1):\\n plane.Rotate(inc,axis)\\n out_planes.append(Rhino.Geometry.Plane(plane))\\n return out_planes\",\n \"def plotwithslices(data,figsize=(16,4),slices=5, RollingDistance=20,rollingwidth=1,stdwidth = 1, Testoutput = 0, doubleaxis=True):\\r\\n print(\\\"\\\\n -- Plotting Data with %i Slices and RollingDist of %i and %i-- \\\" %(slices,RollingDistance,RollingDistance*5))\\r\\n totallen=len(data)\\r\\n slicelens=int(totallen/slices)\\r\\n fig, ax1=plt.subplots(figsize=figsize)\\r\\n plt.plot(data,label = 'Data',linewidth = 2)\\r\\n plt.plot(data.rolling(RollingDistance).mean(),label = '%i R Mean' %(RollingDistance), linestyle=':', linewidth=rollingwidth)\\r\\n plt.plot(data.rolling(RollingDistance*5).mean(),label = '%i R Mean' %(RollingDistance*5), linestyle=':', linewidth=rollingwidth);plt.legend()\\r\\n if (doubleaxis==True):\\r\\n ax2 = ax1.twinx()\\r\\n plt.plot(data.rolling(RollingDistance).std(),color='r',linewidth=stdwidth, label = '%i R Std' %(RollingDistance-1))\\r\\n for i in range(slices-1): \\r\\n plt.axvline(x=data.index[int(totallen/slices)*(i+1)],color='r',linestyle='--',linewidth=1)\\r\\n plt.legend();\\r\\n plt.show()\\r\\n \\r\\n if (Testoutput == True):\\r\\n print(' Slice 0 S: %4i E: %4i ' %(0, totallen), end=\\\"\\\")\\r\\n DickeyFullerPrint(data[0:totallen])\\r\\n normalitytest(data[0:totallen])\\r\\n for i in range(slices): \\r\\n print('\\\\n Slice %2i S: %4i E: %4i ' %(i+1, slicelens*(i), slicelens*(i+1)), end=\\\"\\\")\\r\\n DickeyFullerPrint(data[slicelens*(i):slicelens*(i+1)])\\r\\n normalitytest(data[slicelens*(i):slicelens*(i+1)])\\r\\n return\",\n \"def middlemakevisible(self, pos):\\n pass\",\n \"def orient_img_hwd(data, slice_axis):\\n if slice_axis == 0:\\n return data.transpose(2, 1, 0)\\n elif slice_axis == 1:\\n return data.transpose(2, 0, 1)\\n elif slice_axis == 2:\\n return data\",\n \"def rotaxis(proj, N_steps):\\n a = proj.shape[1]//4\\n b = 3 * proj.shape[1]//4\\n c = proj.shape[2]//4\\n d = 3 * proj.shape[2]//4\\n \\n \\n cent = []\\n N_rot = proj.shape[0] - 180 * N_steps\\n \\n for i in range(N_rot):\\n distances = shift(proj[i, a:b, c:d], np.flip(proj[i + N_steps*180, a:b, c:d] ,1))\\n cent.append(proj[i].shape[1]/2 + distances[1]/2)\\n \\n return cent\",\n \"def get_band_panel(self):\\n return pn.Column(\\n pn.Column(\\n pn.Row(self.get_controls(), margin = (0, 0, -25, 0)),\\n pn.pane.HoloViews(self.get_band_dmap(), linked_axes=False)\\n ), \\n )\",\n \"def quadriview_old(nifti_image, slice_sag, slice_orth,\\n slice_cor_1, slice_cor_2):\\n view_1 = nifti_image[slice_sag, :, :]\\n view_2 = nifti_image[:, slice_orth, :]\\n view_3 = nifti_image[:, :, slice_cor_1]\\n view_4 = nifti_image[:, :, slice_cor_2]\\n\\n pad_lign = max(view_1.shape[0] + view_2.shape[0], view_3.shape[0] + view_4.shape[0])\\n pad_col = max(view_1.shape[1] + view_3.shape[1], view_2.shape[1] + view_4.shape[1])\\n pad = np.zeros((pad_lign, pad_col), dtype=np.float64)\\n\\n pad[:view_1.shape[0], :view_1.shape[1]] = view_1\\n pad[-view_2.shape[0]:, :view_2.shape[1]] = view_2\\n pad[:view_3.shape[0], -view_3.shape[1]:] = view_3\\n pad[-view_4.shape[0]:, -view_4.shape[1]:] = view_4\\n\\n return pad\",\n \"def slice_array():\\n img = Image.open(\\\"flamingo.jpg\\\")\\n image_as_array = np.array(img)\\n width, height, depth = image_as_array.shape\\n\\n red_channel = image_as_array[:, :, 0]\\n green_channel = image_as_array[:, :, 1]\\n blue_channel = image_as_array[:, :, 2]\\n\\n top_left_corner = image_as_array[:height // 2, :width // 2, :]\\n top_right_corner = image_as_array[:height // 2, width // 2:, :]\\n random_middle_pixels = image_as_array[11:29, 101:400, :]\",\n \"def animate_scatters(iteration, ax, pos):\\n \\n # Change viewing angle\\n ax.view_init(pos[iteration][0], pos[iteration][1])\",\n \"def sharpen_slide(self):\\r\\n std_input = self.horizontal.get() # Get the std defined by user\\r\\n c_input = self.vertical.get() # get the constant defined by the user\\r\\n img = self.master.images[-1] # Use the most recent displayed image for sharpening\\r\\n sharpened_image = sharpen.gaussian_unsharp_masking(img, std_input, c_input) # Apply unsharp masking on image\\r\\n self.master.display_image.display_image(img=sharpened_image) # display sharpened image\\r\\n self.master.images.append(sharpened_image) # Append the sharpened image on the stack\\r\",\n \"def make_door_split(bm, face, size, off, **kwargs):\\n return split(bm, face, size.y, size.x, off.x, off.y, off.z)\",\n \"def __make_slide(self):\\n # Create base rectangle for slide\\n length = self.parameters['slide_base_length'] + self.parameters['bearing_slide_travel']\\n width = self.parameters['slide_width']\\n height = self.parameters['slide_height']\\n slide = fso.Box(x=length,y=width,z=height)\\n # Create the mounting holes\\n radius = 0.5*self.parameters['slide_screw_size']\\n base_hole = fso.Cylinder(r=radius, l=2*height)\\n hole_list = []\\n for i in (-1,1):\\n for j in (-1,1):\\n xpos = i*(0.5*length - self.parameters['slide_screw_inset'])\\n ypos = j*(0.5*self.parameters['slide_screw_dW'])\\n hole = base_hole.copy()\\n hole.translate([xpos,ypos,0])\\n hole_list.append(hole)\\n # Remove hole material\\n slide -= hole_list\\n slide.set_color(self.slide_color,recursive=True)\\n self.slide = slide\",\n \"def axis(ind):\\n return ind % 15, ind // 15\",\n \"def orig(side):\\n return (side + 1) % 3 # ccw(side)\",\n \"def create_sat_panels(self):\\n\\n # Dimensions of body\\n SAT_SIZE = self.ANI_SCALE*self.SAT_SCALE*np.asarray(self.SAT_PROPS[\\\"Size\\\"])/2\\n bx = SAT_SIZE[0]\\n by = SAT_SIZE[1]\\n bz = SAT_SIZE[2]\\n\\n # Panel length\\n L = bx\\n\\n # Panels\\n theta = self.PANEL_ANGLE*pi/180\\n px1 = bx - L*sin(theta)\\n py1 = by + L*cos(theta)\\n pz1 = bz\\n px2 = px1 + L*sin(theta)\\n py2 = py1 + L*cos(theta)\\n pz2 = pz1\\n\\n # Vertices\\n V = [\\n (-bx, by, -bz),\\n (-bx, by, bz),\\n (-px1, py1, pz1),\\n (-px1, py1, -pz1),\\n (-px1, py1, -pz1),\\n (-px1, py1, pz1),\\n (-px2, py2, pz2),\\n (-px2, py2, -pz2),\\n (-bx, -by, -bz),\\n (-bx, -by, bz),\\n (-px1, -py1, pz1),\\n (-px1, -py1, -pz1),\\n (-px1, -py1, -pz1),\\n (-px1, -py1, pz1),\\n (-px2, -py2, pz2),\\n (-px2, -py2, -pz2)\\n ]\\n\\n # Create faces\\n F = [\\n (0, 1, 2, 3),\\n (4, 5, 6, 7),\\n (8, 9, 10, 11),\\n (12, 13, 14, 15)\\n ]\\n\\n # Create building blocks of polydata\\n sat = vtk.vtkPolyData()\\n points = vtk.vtkPoints()\\n polys = vtk.vtkCellArray()\\n scalars = vtk.vtkFloatArray()\\n\\n # Load the point, cell and data attributes\\n for i in range(len(V)):\\n points.InsertPoint(i, V[i])\\n for i in range(len(F)):\\n polys.InsertNextCell(self.mkVtkIdList(F[i]))\\n for i in range(len(V)):\\n scalars.InsertTuple1(i, i)\\n \\n # Assign the pieces to the vtkPolyData.\\n sat.SetPoints(points)\\n del points\\n sat.SetPolys(polys)\\n del polys\\n sat.GetPointData().SetScalars(scalars)\\n del scalars\\n\\n # Mapper\\n mapper = vtk.vtkPolyDataMapper()\\n mapper.SetInputData(sat)\\n mapper.ScalarVisibilityOff()\\n\\n # Actor\\n actor = vtk.vtkActor()\\n actor.SetMapper(mapper)\\n actor.GetProperty().SetColor(0., 0., 0.8)\\n actor.GetProperty().SetAmbient(0.5)\\n actor.GetProperty().SetSpecular(.5)\\n actor.GetProperty().SetSpecularPower(10.0)\\n actor.GetProperty().SetDiffuse(0.2)\\n\\n # Move to sat position\\n actor.SetPosition(0, 0, -self.SAT_PROPS[\\\"Alt\\\"])\\n\\n return actor\",\n \"def left_right(steps):\\n lengths = lens(steps)\\n a_side = []\\n b_side = []\\n for i in range(len(lengths)):\\n if i % 2 == 0:\\n a_side.append(steps[i])\\n else:\\n b_side.append(steps[i])\\n return a_side, b_side\",\n \"def scroll(get_frame, t):\\r\\n frame = get_frame(t)\\r\\n frame_region = frame[int(t):int(t)+360,:]\\r\\n return frame_region\",\n \"def _crop_concat(self, upsampled, bypass):\\n c = (bypass.size()[2] - upsampled.size()[2]) // 2\\n bypass = F.pad(bypass, (-c, -c, -c, -c))\\n\\n return torch.cat((upsampled, bypass), 1)\",\n \"def spinAround(self):\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.57020974","0.5570688","0.5558747","0.545153","0.5445056","0.543105","0.535599","0.5348452","0.5087993","0.50807226","0.50238377","0.50055045","0.5003114","0.49961782","0.49961782","0.49851263","0.49696037","0.49594927","0.49540603","0.49380317","0.4912734","0.4898903","0.4896575","0.48889488","0.48869932","0.48733133","0.48653576","0.4863322","0.4854335","0.4853837","0.48369893","0.4818215","0.48157597","0.48056313","0.4804768","0.48031425","0.47887963","0.4770898","0.47667697","0.47639382","0.47557122","0.47421345","0.4737738","0.4737738","0.4737738","0.4737738","0.4737738","0.4737738","0.4737738","0.4737738","0.4737738","0.4737738","0.4737738","0.47284114","0.4725739","0.4721634","0.47193795","0.4716829","0.47160664","0.47149864","0.47117338","0.47034582","0.46983021","0.46866426","0.46863478","0.46854594","0.46839356","0.4659878","0.4654571","0.46477753","0.4639758","0.46380186","0.46343315","0.46334973","0.4623702","0.46216324","0.46179405","0.4607892","0.460674","0.4601228","0.45970562","0.45911023","0.45892984","0.45844927","0.45664886","0.4565632","0.4563711","0.45609602","0.4560573","0.4556429","0.45560437","0.455543","0.45459396","0.4544863","0.4541251","0.45352647","0.45325157","0.45317256","0.45303977","0.4529912"],"string":"[\n \"0.57020974\",\n \"0.5570688\",\n \"0.5558747\",\n \"0.545153\",\n \"0.5445056\",\n \"0.543105\",\n \"0.535599\",\n \"0.5348452\",\n \"0.5087993\",\n \"0.50807226\",\n \"0.50238377\",\n \"0.50055045\",\n \"0.5003114\",\n \"0.49961782\",\n \"0.49961782\",\n \"0.49851263\",\n \"0.49696037\",\n \"0.49594927\",\n \"0.49540603\",\n \"0.49380317\",\n \"0.4912734\",\n \"0.4898903\",\n \"0.4896575\",\n \"0.48889488\",\n \"0.48869932\",\n \"0.48733133\",\n \"0.48653576\",\n \"0.4863322\",\n \"0.4854335\",\n \"0.4853837\",\n \"0.48369893\",\n \"0.4818215\",\n \"0.48157597\",\n \"0.48056313\",\n \"0.4804768\",\n \"0.48031425\",\n \"0.47887963\",\n \"0.4770898\",\n \"0.47667697\",\n \"0.47639382\",\n \"0.47557122\",\n \"0.47421345\",\n \"0.4737738\",\n \"0.4737738\",\n \"0.4737738\",\n \"0.4737738\",\n \"0.4737738\",\n \"0.4737738\",\n \"0.4737738\",\n \"0.4737738\",\n \"0.4737738\",\n \"0.4737738\",\n \"0.4737738\",\n \"0.47284114\",\n \"0.4725739\",\n \"0.4721634\",\n \"0.47193795\",\n \"0.4716829\",\n \"0.47160664\",\n \"0.47149864\",\n \"0.47117338\",\n \"0.47034582\",\n \"0.46983021\",\n \"0.46866426\",\n \"0.46863478\",\n \"0.46854594\",\n \"0.46839356\",\n \"0.4659878\",\n \"0.4654571\",\n \"0.46477753\",\n \"0.4639758\",\n \"0.46380186\",\n \"0.46343315\",\n \"0.46334973\",\n \"0.4623702\",\n \"0.46216324\",\n \"0.46179405\",\n \"0.4607892\",\n \"0.460674\",\n \"0.4601228\",\n \"0.45970562\",\n \"0.45911023\",\n \"0.45892984\",\n \"0.45844927\",\n \"0.45664886\",\n \"0.4565632\",\n \"0.4563711\",\n \"0.45609602\",\n \"0.4560573\",\n \"0.4556429\",\n \"0.45560437\",\n \"0.455543\",\n \"0.45459396\",\n \"0.4544863\",\n \"0.4541251\",\n \"0.45352647\",\n \"0.45325157\",\n \"0.45317256\",\n \"0.45303977\",\n \"0.4529912\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.63570553"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88560,"cells":{"query":{"kind":"string","value":"This function move panel boundaries to transform them into trapezoids and rhombuses"},"document":{"kind":"string","value":"def box_transform_panels(page, type_choice=None, pattern=None):\n\n if type_choice is None:\n type_choice_prob = np.random.random()\n if type_choice_prob < cfg.panel_box_trapezoid_ratio:\n type_choice = \"trapezoid\"\n else:\n type_choice = \"rhombus\"\n\n if type_choice == \"trapezoid\":\n if page.num_panels > 2:\n\n # Get parent panel which satisfies the criteria for the transform\n relevant_panels = find_parent_with_multiple_children(page, 3)\n\n if len(relevant_panels) > 0:\n if len(relevant_panels) > 1:\n num_panels = np.random.randint(1, len(relevant_panels))\n else:\n num_panels = 1\n\n # For each panel\n for idx in range(0, num_panels):\n panel = relevant_panels[idx]\n\n # Get the three child panels\n # Since panels are created in order\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n p3 = panel.get_child(2)\n\n min_width = math.inf\n min_height = math.inf\n\n # Get the smallest height and width\n for child in [p1, p2, p3]:\n\n if child.width < min_width:\n min_width = child.width\n\n if child.height < min_height:\n min_height = child.height\n\n # Choose trapezoid pattern\n if pattern is None:\n trapezoid_pattern = np.random.choice([\"A\", \"V\"])\n else:\n trapezoid_pattern = pattern\n\n movement_proportion = np.random.randint(\n 10,\n cfg.trapezoid_movement_limit)\n\n # If parent panel is horizontal the children are vertical\n if panel.orientation == \"h\":\n\n # Get how much the lines of the child panels move\n # on the x axis to make the trapezoid\n x_movement = min_width*(movement_proportion/100)\n\n # Make an A pattern horizontally\n if trapezoid_pattern == \"A\":\n\n # Get the coords of the first line to be moved\n line_one_top = (p1.x2y2[0] + x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] - x_movement,\n p1.x3y3[1])\n\n # Move line between child 1 and 2\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n # Get the coords of the second line to be moved\n line_two_top = (p2.x2y2[0] - x_movement,\n p2.x2y2[1])\n line_two_bottom = (p2.x3y3[0] + x_movement,\n p2.x3y3[1])\n\n # Move line two between child 2 and 3\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n\n # Make a V pattern horizontally\n else:\n\n # Get the coords of the first line to be moved\n line_one_top = (p1.x2y2[0] - x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] + x_movement,\n p1.x3y3[1])\n\n # Move line between child 1 and 2\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n # Get the coords of the second line to be moved\n line_two_top = (p2.x2y2[0] + x_movement,\n p2.x2y2[1])\n\n line_two_bottom = (p2.x3y3[0] - x_movement,\n p2.x3y3[1])\n\n # Move line two between child 2 and 3\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n\n # If panel is vertical children are horizontal\n # so the A and the V are at 90 degrees to the page\n else:\n # Get how much the lines of the child panels move\n # on the y axis to make the trapezoid\n y_movement = min_height*(movement_proportion/100)\n\n # Make an A pattern vertically\n if trapezoid_pattern == \"A\":\n\n # Get the coords of the first line to be moved\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] + y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] - y_movement)\n\n # Move line between child 1 and 2\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n\n # Get the coords of the second line to be moved\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] - y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] + y_movement)\n\n # Move line two between child 2 and 3\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n # Make a V pattern vertically\n else:\n\n # Get the coords of the first line to be moved\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] - y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] + y_movement)\n\n # Move line between child 1 and 2\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n # Get the coords of the second line to be moved\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] + y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] - y_movement)\n\n # Move line two between child 2 and 3\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n\n elif type_choice == \"rhombus\":\n\n if page.num_panels > 1:\n\n # Get parent panel which satisfies the criteria for the transform\n relevant_panels = find_parent_with_multiple_children(page, 3)\n\n if len(relevant_panels) > 0:\n\n if len(relevant_panels) > 1:\n num_panels = np.random.randint(1, len(relevant_panels))\n else:\n num_panels = 1\n\n for idx in range(0, num_panels):\n\n panel = relevant_panels[idx]\n\n # Since panels are created in order\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n p3 = panel.get_child(2)\n\n min_width = math.inf\n min_height = math.inf\n\n # Get the smallest height and width\n for child in [p1, p2, p3]:\n\n if child.width < min_width:\n min_width = child.width\n\n if child.height < min_height:\n min_height = child.height\n\n if pattern is None:\n rhombus_pattern = np.random.choice([\"left\", \"right\"])\n else:\n rhombus_pattern = pattern\n\n movement_proportion = np.random.randint(\n 10,\n cfg.rhombus_movement_limit\n )\n\n # Logic for the section below is the same as the\n # trapezoid with the exception of the fact that the\n # rhombus pattern happens to move both lines in the\n # same direction\n\n if panel.orientation == \"h\":\n\n x_movement = min_width*(movement_proportion/100)\n\n if rhombus_pattern == \"left\":\n line_one_top = (p1.x2y2[0] - x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] + x_movement,\n p1.x3y3[1])\n\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n line_two_top = (p2.x2y2[0] - x_movement,\n p2.x2y2[1])\n\n line_two_bottom = (p2.x3y3[0] + x_movement,\n p2.x3y3[1])\n\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n\n else:\n\n line_one_top = (p1.x2y2[0] + x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] - x_movement,\n p1.x3y3[1])\n\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n line_two_top = (p2.x2y2[0] + x_movement,\n p2.x2y2[1])\n\n line_two_bottom = (p2.x3y3[0] - x_movement,\n p2.x3y3[1])\n\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n else:\n y_movement = min_height*(movement_proportion/100)\n\n if rhombus_pattern == \"right\":\n\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] + y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] - y_movement)\n\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] + y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] - y_movement)\n\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n else:\n\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] - y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] + y_movement)\n\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] - y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] + y_movement)\n\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n\n return page"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def adjust_mario_position(self):\n self.last_x_position = self.mario.rect.right\n self.mario.rect.x += round(self.mario.x_vel)\n self.check_mario_x_collisions()\n\n if self.mario.in_transition_state == False:\n self.mario.rect.y += round(self.mario.y_vel)\n self.check_mario_y_collisions()","def __init__(self, \n nd = 2, \n goal = np.array([1.0,1.0]),\n state_bound = [[0,1],[0,1]],\n nA = 4,\n action_list = [[0,1],[0,-1],[1,0],[-1,0]],\n<<<<<<< HEAD:archive-code/puddleworld.py\n ngrid = [10.0,10.0],\n maxStep = 40):\n ngrid = [40, 40]\n x_vec = np.linspace(0,1,ngrid[0])\n y_vec = np.linspace(0,1,ngrid[1])\n for x in x_vec:\n for y in y_vec:\n if ~self.inPuddle([x,y]):\n puddle.append([x,y])\n # puddle is a closed loop \n outpuddlepts = np.asarray(puddle)\n \"\"\"\n\n\n # Horizontal wing of puddle consists of \n # 1) rectangle area xch1<= x <=xc2 && ych1-radius <= y <=ych2+radius\n # (xchi,ychi) is the center points (h ==> horizantal)\n # x, y = state[0], state[1]\n xch1, ych1 = 0.3, 0.7\n xch2, ych2 = 0.65, ych1\n radius = 0.1\n\n\n #Vertical wing of puddle consists of \n # 1) rectangle area xcv1-radius<= x <=xcv2+radius && ycv1 <= y <= ycv2\n # where (xcvi,ycvi) is the center points (v ==> vertical)\n xcv1 = 0.45; ycv1=0.4;\n xcv2 = xcv1; ycv2 = 0.8;\n\n # % 2) two half-circle at end edges of rectangle\n \n # POINTS ON HORIZANTAL LINES OF PUDDLE BOUNDARY\n for x in np.arange(xch1,xcv1-radius,self.meshsize[0]/2):\n puddle.append([x,ych1-radius])\n puddle.append([xcv1-radius,ych1-radius])\n \n for x in np.arange(xcv1+radius,xch2,self.meshsize[0]/2):\n puddle.append([x,ych1-radius])\n \n for x in np.arange(xch1,xcv1-radius,self.meshsize[0]/2):\n puddle.append([x,ych1+radius])\n \n puddle.append([xcv1-radius,ych1+radius])\n\n\n for x in np.arange(xcv1+radius,xch2,self.meshsize[0]/2):\n puddle.append([x,ych1+radius])\n\n # POINTS ON VERTICAL LINES OF PUDDLE BOUNDARY\n for y in np.arange(ycv1,ych1-radius,self.meshsize[1]/2):\n puddle.append([xcv1-radius,y])\n \n for y in np.arange(ycv1,ych1-radius,self.meshsize[1]/2):\n puddle.append([xcv1+radius,y])\n \"\"\"\n for y in np.arrange():\n puddle.append([])\n \n for y in np.arrange():\n puddle.append([])\n \"\"\"\n\n # HALF CIRCLES\n ngridTheta = 10\n thetaVec = np.linspace(0,pi,ngridTheta)\n\n for t in thetaVec:\n puddle.append([xch1+radius*np.cos(pi/2+t),ych1+radius*np.sin(pi/2+t)])\n\n for t in thetaVec:\n puddle.append([xch2+radius*np.cos(-pi/2+t),ych2+radius*np.sin(-pi/2+t)])\n\n for t in thetaVec:\n puddle.append([xcv1+radius*np.cos(pi+t),ycv1+radius*np.sin(pi+t)])\n\n for t in thetaVec:\n puddle.append([xcv2+radius*np.cos(t),ycv2+radius*np.sin(t)])\n\n \n outpuddlepts = np.asarray(puddle)\n return outpuddlepts","def update(self):\n self.center_x += self.change_x\n self.center_y += self.change_y\n\n # boundary for the sides of the screen\n if self.left < 0:\n self.left = 0\n if self.right > settings.WIDTH:\n self.right = settings.WIDTH\n\n # boundary for the top and bottom of the screen\n if self.bottom < 0:\n self.bottom = 3\n if self.top > settings.HEIGHT:\n self.top = settings.HEIGHT\n\n # boundary of wall left up\n if (self.right > 185 and self.left < 180 and self.top > 338 and\n self.bottom < 464):\n self.right = 184\n if (self.left < 212 and self.left > 190 and self.bottom < 435 and\n self.top > 338):\n self.left = 212\n if (self.right > 185 and self.left < 312 and self.bottom < 464 and\n self.top > 460):\n self.bottom = 464\n if (self.top > 435 and self.top < 450 and self.left >= 212 and\n self.left < 311):\n self.top = 435\n if (self.top > 336 and self.bottom < 350 and self.left < 211 and\n self.right > 185):\n self.top = 336\n if (self.left < 312 and self.right > 290 and self.bottom < 464 and\n self.top > 436):\n self.left = 312\n\n # boundary of wall right up\n if (self.right > 590 and self.left < 586 and self.top > 338 and\n self.bottom < 464):\n self.left = 586\n if (self.right > 560 and self.right < 582 and self.bottom < 435 and\n self.top > 338):\n self.right = 560\n if (self.right > 462 and self.left < 586 and self.bottom < 464 and\n self.top > 460):\n self.bottom = 464\n if (self.top > 435 and self.top < 450 and self.right <= 560 and\n self.right > 462):\n self.top = 435\n if (self.top > 336 and self.bottom < 350 and self.left < 586 and\n self.right > 561):\n self.top = 336\n if (self.left < 440 and self.right > 462 and self.bottom < 464 and\n self.top > 436):\n self.right = 462\n\n # boundary of wall left down\n if (self.right > 185 and self.left < 180 and self.top > 88 and\n self.bottom < 213):\n self.right = 184\n if (self.left < 212 and self.right > 200 and self.top > 111 and\n self.bottom < 213):\n self.left = 212\n if (self.right > 185 and self.left < 312 and self.top > 88 and self.top < 100):\n self.top = 88\n if (self.bottom < 111 and self.bottom > 100 and self.left >= 212 and\n self.left < 311):\n self.bottom = 112\n if (self.top > 336 and self.bottom < 213 and self.left < 211 and\n self.right > 185):\n self.bottom = 213\n if (self.left < 312 and self.right > 290 and self.top > 88 and\n self.bottom < 111):\n self.left = 312\n\n # boundary of wall lef right down\n if (self.right > 590 and self.left < 586 and self.top > 88 and\n self.bottom < 213):\n self.left = 586\n if (self.right > 560 and self.left < 582 and self.top > 111 and\n self.bottom < 213):\n self.right = 560\n if (self.right > 462 and self.left < 586 and self.top > 88 and self.top < 100):\n self.top = 88\n if (self.bottom < 111 and self.bottom > 100 and self.right <= 560 and\n self.right > 462):\n self.bottom = 112\n if (self.top > 336 and self.bottom < 213 and self.left < 586 and\n self.right > 561):\n self.bottom = 213\n if (self.left < 440 and self.right > 462 and self.top > 88 and\n self.bottom < 111):\n self.right = 462","def move(self, walls):\n \n # Move left/right\n self.rect.x += self.change_x\n \n # Did this update cause us to hit a wall?\n block_hit_list = pygame.sprite.spritecollide(self, walls, False)\n for block in block_hit_list:\n # If we are moving right, set our right side to the left side of\n # the item we hit\n if self.change_x > 0:\n self.rect.right = block.rect.left\n else:\n # Otherwise if we are moving left, do the opposite.\n self.rect.left = block.rect.right\n \n # Move up/down\n self.rect.y += self.change_y\n \n # Check and see if we hit anything\n block_hit_list = pygame.sprite.spritecollide(self, walls, False)\n for block in block_hit_list:\n \n # Reset our position based on the top/bottom of the object.\n if self.change_y > 0:\n self.rect.bottom = block.rect.top\n else:\n self.rect.top = block.rect.bottom","def check_borders(self):\n # Go Homer!\n # https://en.wikipedia.org/wiki/Torus#Flat_torus\n if self._posn.x < 0:\n self._posn.x += self._win_w\n elif self._posn.x > self._win_w:\n self._posn.x -= self._win_w\n if self._posn.y < 0:\n self._posn.y += self._win_h\n elif self._posn.y > self._win_h:\n self._posn.y -= self._win_h","def grasp_planning(object, object_pose1_world, object_pose2_world,\n palm_pose_l_object, palm_pose_r_object, N=200, init=True):\n primitive_name = 'grasping'\n # 0. get initial palm poses in world frame\n palm_poses_initial_world = planning_helper.palm_poses_from_object(\n object_pose=object_pose1_world,\n palm_pose_l_object=palm_pose_l_object,\n palm_pose_r_object=palm_pose_r_object)\n\n grasp_width = planning_helper.grasp_width_from_palm_poses(\n palm_pose_l_object, palm_pose_r_object)\n # grasp_width = grasp_width/1.025\n # grasp_width = 0.086 - 0.006\n # grasp_width = 0.086\n # grasp_width = 0.05206\n # grasp_width = 0.135\n # print(\"grasp width: \" + str(grasp_width))\n\n # 1. get lifted object poses\n object_pose_lifted_world = copy.deepcopy(object_pose1_world)\n\n if init:\n object_pose_lifted_world.pose.position.z += 0.05\n # object_pose_lifted_world.pose.position.z += 0.05\n object_pose2_world.pose.position.z += 0.0025\n\n # 2. get lifted palm poses\n palm_poses_lifted_world = planning_helper.palm_poses_from_object(\n object_pose=object_pose_lifted_world,\n palm_pose_l_object=palm_pose_l_object,\n palm_pose_r_object=palm_pose_r_object)\n\n # 3. get rotated object pose\n object_pose_rotated_world = copy.deepcopy(object_pose2_world)\n\n # if init:\n # object_pose_rotated_world.pose.position.z += 0.05\n object_pose_rotated_world.pose.position.z += 0.05\n\n palm_poses_rotated_world = planning_helper.palm_poses_from_object(\n object_pose=object_pose_rotated_world,\n palm_pose_l_object=palm_pose_l_object,\n palm_pose_r_object=palm_pose_r_object)\n\n # 4. get final configuration\n palm_poses_final_world = planning_helper.palm_poses_from_object(\n object_pose=object_pose2_world,\n palm_pose_l_object=palm_pose_l_object,\n palm_pose_r_object=palm_pose_r_object)\n\n # 3. generate pose plans\n # 3.1. initialize plan\n initial_plan = planning_helper.initialize_plan(\n palm_poses_initial=palm_poses_initial_world,\n object_pose_initial=object_pose1_world,\n primitive=primitive_name,\n plan_name='initial_config')\n\n # 3.2. lift the object\n lift_plan = planning_helper.move_cart_synchro(\n palm_poses_final=palm_poses_lifted_world,\n grasp_width=grasp_width,\n plan_previous=initial_plan,\n primitive=primitive_name,\n plan_name='lift_object',\n N=10)\n\n # 3.3. rotate the object\n rotate_plan = planning_helper.move_cart_synchro(\n palm_poses_final=palm_poses_rotated_world,\n grasp_width=grasp_width,\n plan_previous=lift_plan,\n primitive=primitive_name,\n plan_name='rotate_object_final',\n N=N/2,\n is_replan=True)\n\n # 3.4. place the object\n place_plan = planning_helper.move_cart_synchro(\n palm_poses_final=palm_poses_final_world,\n grasp_width=grasp_width,\n plan_previous=rotate_plan,\n primitive=primitive_name,\n plan_name='place_object',\n N=20)\n return [lift_plan] + [rotate_plan] + [place_plan]","def drawCoordinatePlane_region():\r\n turtle2 = t.Screen()\r\n turtle2.title(\"Life Expectancy versus Region\")\r\n t2.speed(0)\r\n t3.speed(0)\r\n setTurtle(t0)\r\n setTurtle(t1)\r\n setTurtle(t2)\r\n setTurtle(t3)\r\n drawAxes(t0)\r\n t1.left(90)\r\n drawAxes(t1)\r\n t0.pu()\r\n t0.fd(-80)\r\n t0.lt(90)\r\n drawlabels(t0, t1)\r\n drawPoints(t0, t1)\r\n t0.pu()\r\n t1.pu()\r\n t2.pu()\r\n t3.pu()\r\n t0.goto(initialCoordinates())\r\n t1.goto(initialCoordinates())\r\n t2.goto(initialCoordinates())\r\n t3.goto(initialCoordinates())\r\n t1.lt(90)","def __check_boundary(self):\n\t\tif self.rect.left <= self.left_boundary:\n\t\t\tself.move_right()\n\t\tif self.rect.right >= self.right_boundary:\n\t\t\tself.move_left()","def boundary(active, objects):\n limit = SIZE[1]\n for obj in objects:\n if active.pos_x == obj.pos_x:\n limit = min(limit, obj.pos_y)\n active.pos_y = limit-active.height\n active.col_d = True","def move(self, playersList):\n land = pygame.Rect(283, 468, 635, 210)\n leftCroc = pygame.Rect(300, 373, 105, 20)\n leftStand = pygame.Rect(485, 300, 76, 10)\n rightStand = pygame.Rect(639, 300, 76, 10)\n rightBirb = pygame.Rect(795, 373, 105, 20)\n bottomland = pygame.Rect(0, 750, 1500, 1)\n platformsList = [land, leftCroc, rightBirb, leftStand, rightStand,bottomland]\n\n # Push\n if self.count <= 0:\n self.count = 10\n self.push = False\n self.moveRight = False\n\n if self.push == True and self.moveRight:\n self.count -= 1\n self.rect.x +=(self.count**2)*0.5\n\n if self.push == True and self.moveRight == False:\n self.count -= 1\n self.rect.x -=(self.count**2)*0.5\n\n # mover horizontal\n if self.left:\n self.rect.x -= self.speed_x\n if self.right:\n self.rect.x += self.speed_x\n\n # Revisar si pegó con la tierra\n if self.rect.colliderect(land) and self.rect.bottom > land.top + 50: # ///// Aquí el land.top+n lo tiene que ajustar para que sea como el piso máximo de los maecitos\n if self.left:\n self.rect.left = land.right\n elif self.right:\n self.rect.right = land.left\n\n # revisar si está en medio de una plataforma (por si está saltando a través de una)\n insidePlatform = self.rect.collidelist(platformsList)\n # mover vertical\n if self.falling or self.rising:\n self.rect.y += self.speed_y\n for platform in platformsList:\n # si choca con una plataforma\n if self.rect.colliderect(bottomland):\n self.rect.bottom = land.top\n self.rect.x = 750\n if self.rect.colliderect(platform):\n # y específicamente está cayéndose y no es la plataforma que ya vimos por la que estaba pasando\n if self.falling and platform is not platformsList[insidePlatform]:\n self.rect.bottom = platform.top\n self.speed_y = 0\n self.falling = False\n\n # Manejar velocidad vertical\n if self.falling or self.rising: # lo vuelvo a revisar porque pudo haber parado de estar falling al caer en una plataforma\n self.speed_y += 1 # /////Aquí se cambia la aceleración vertical del jugador//////\n if self.speed_y > 20:\n self.speed_y = 20 # /////Aquí se cambia la velocidad máxima de caída/////\n if self.rising and self.speed_y > 0: # aquí es si pasa de estar subiendo a estar cayendo\n self.rising = False\n self.falling = True\n\n # si se queda sin plataforma por debajo\n if self.falling == False and self.rising == False:\n self.falling = True\n tryoutRect = self.rect.copy()\n tryoutRect.y += 1\n for platform in platformsList:\n # si choca con una plataforma\n if tryoutRect.colliderect(platform):\n self.falling = False\n\n self.collide(playersList)","def mover_bm_arriba(self):\n self.nueva_posicion_posible_parte_superior = self.mapa.consultar_casilla_por_movimiento([self.casilla[0],\n self.casilla[1] - 1],\n [self.vertice_1[0] ,self.vertice_1[1] - self.velocidad],\n [self.vertice_1[0], self.vertice_1[1] - 5 -5])\n self.nueva_posicion_posible_parte_inferior = self.mapa.consultar_casilla_por_movimiento([self.casilla[0] + 1,\n self.casilla[1] - 1],\n [self.vertice_2[0] ,self.vertice_2[1] - self.velocidad],\n [self.vertice_1[0],self.vertice_1[1]])\n self.y -= self.velocidad * (self.y >= 15) *(self.nueva_posicion_posible_parte_inferior[0] != 1) * (self.nueva_posicion_posible_parte_superior[0] != 1)\n self.posicion = [self.posicion[0],self.y]\n self.casilla = [self.casilla[0],self.casilla[1] - self.nueva_posicion_posible_parte_superior[1] * (self.nueva_posicion_posible_parte_inferior[0] != 1) * (self.nueva_posicion_posible_parte_superior[0] != 1)]\n self.redefinir_vertices()","def check_boundaries(self):\n # Checks if the enemy bar has gone of the net\n if self.rect.left <= self.settings.WINDOW_WIDTH / 2:\n self.rect.left = self.settings.WINDOW_WIDTH / 2\n self.isMovingUp = False\n\n # Checks if the enemy bar has gone out of bound to the right\n if self.rect.right >= self.settings.WINDOW_WIDTH:\n self.rect.right = self.settings.WINDOW_WIDTH\n self.isMovingUp = True","def move_to_refine(self, des_img_pos, act_img_pos, current_world_pos, increment, img_thresh):\n des_img_x = des_img_pos[0]\n des_img_y = des_img_pos[1]\n act_img_x = act_img_pos[0]\n act_img_y = act_img_pos[1]\n cur_wld_x = current_world_pos[0]\n cur_wld_y = current_world_pos[1]\n new_wld_x = cur_wld_x\n new_wld_y = cur_wld_y\n \n #object to the left -> move left (-wld_y)\n if (act_img_x < des_img_x-img_thresh):\n print(' Moving left')\n new_wld_y = cur_wld_y + increment\n #object to the right -> move right (+wld_y)\n elif (act_img_x > des_img_x+img_thresh):\n new_wld_y = cur_wld_y - increment\n print(' Moving right')\n #object to the top -> move forward (+wld_x)\n if (act_img_y < des_img_y-img_thresh):\n new_wld_x = cur_wld_x + increment\n print(' Moving forward')\n #object to the bottom -> move backward (-wld_x)\n elif (act_img_y > des_img_y+img_thresh):\n new_wld_x = cur_wld_x - increment\n print(' Moving backward')\n \n #move arm to new coordinates\n self.move_to(new_wld_x, new_wld_y, self.move_to_height)\n \n #return new arm position\n return [new_wld_x, new_wld_y]","def mouse_move(self, obj, event):\n last_pos = self.iren.GetLastEventPosition()\n next_pos = self.iren.GetEventPosition()\n last_disp_coords = np.asarray([last_pos[0], last_pos[1], 0])\n next_disp_coords = np.asarray([next_pos[0], next_pos[1], 0])\n last_world_coords = self.display_to_world(last_disp_coords)\n next_world_coords = self.display_to_world(next_disp_coords)\n world_direction = (last_world_coords - next_world_coords)[0]\n\n if world_direction > 0:\n direction = 'forwards'\n elif world_direction < 0:\n direction = 'backwards'\n else:\n direction = 'none'\n\n if self.cone_dir == 'start':\n if direction == 'backwards':\n self.start_base_x += .5\n if self.start_base_x.is_integer():\n ind = str(int(self.start_base_x))\n isvalid = self.gaps.set_dragged_start(ind)\n if isvalid:\n self.ren_win.Render()\n else:\n self.start_base_x -= .5\n return\n\n elif direction == 'forwards':\n if self.start_base_x > 0:\n self.start_base_x -= .5\n if self.start_base_x.is_integer():\n ind = str(int(self.start_base_x))\n self.gaps.set_dragged_start(ind)\n self.ren_win.Render()\n\n if self.cone_dir == 'end':\n if direction == 'backwards':\n if self.end_base_x > 0:\n self.end_base_x -= .5\n if self.end_base_x.is_integer():\n ind = str(int(self.end_base_x))\n self.gaps.set_dragged_end(ind)\n self.ren_win.Render()\n\n elif direction == 'forwards':\n self.end_base_x += .5\n if self.end_base_x.is_integer():\n ind = str(int(self.end_base_x))\n isvalid = self.gaps.set_dragged_end(ind)\n if isvalid:\n self.ren_win.Render()\n else:\n self.end_base_x -= .5\n return","def update(self):\r\n if self.change_x < 0 and self.left - self.speed <= Costanti.LEVEL_INFO['left']:\r\n # raggiunto limite sinistro\r\n self.left = Costanti.LEVEL_INFO['left'] + 1\r\n elif self.change_x > 0 and Costanti.LEVEL_INFO['right'] <= self.right + self.speed:\r\n # raggiunto limite destro\r\n self.right = Costanti.LEVEL_INFO[\"right\"] - 1\r\n elif self.left > Costanti.LEVEL_INFO[\"left\"] and self.right < Costanti.LEVEL_INFO[\"right\"]:\r\n # sposta il paddle\r\n self.center_x += self.change_x * self.speed\r\n\r\n # aggiorno l'immagine per l'animazione\r\n super().update_animation()\r\n\r\n # ristabilisco le giuste dimensioni del paddle e non quelle dell'immagine originale\r\n self.width = Costanti.Paddle_WIDTH\r\n self.height = Costanti.Paddle_HEIGHT","def _add_boundaries(self):\n logger.info(\"add_boundaries: start of method\")\n\n import scipy.spatial as sptl\n import scipy.sparse as sprs\n Lx = self._Lx\n Ly = self._Ly\n Lz = self._Lz\n Np = self.num_pores()\n btype = self._btype\n boffset = 0.05\n\n #Translate internal pores to each face of domain\n poffset = np.zeros((7,3))\n poffset[[2,5],0] = [-Lx, Lx]\n poffset[[3,4],1] = [-Ly, Ly]\n poffset[[1,6],2] = [-Lz, Lz]\n pcoords = pcoords0 = self['pore.coords']\n for i in np.r_[1:7]:\n pcoords = np.concatenate((pcoords,pcoords0 + poffset[i,:]),axis=0)\n\n #Use some twisted logic to get bval list of + for boundary and - for periodic faces\n bval = [0, 1, 2, 3, 4, 5, 6]*(np.array([0, btype[2], btype[0], btype[1], btype[1], btype[0], btype[2]])*-2+1)\n ptype = np.zeros((Np,),dtype=int)\n for i in np.r_[1:7]:\n ptype = np.concatenate((ptype,np.ones((Np,),dtype=int)*bval[i]),axis=0)\n\n #pnum contains the internal ID number of the boundary pores (for connecting periodic points)\n pnum = self.pores()\n pnum = np.tile(pnum,7)\n\n Tri = sptl.Delaunay(pcoords)\n adjmat = sprs.lil_matrix((np.shape(pcoords)[0],np.shape(pcoords)[0]),dtype=int)\n for i in np.arange(0,np.shape(Tri.simplices)[0]):\n #Keep only simplices that are fully in real domain\n adjmat[Tri.simplices[i],Tri.simplices[i]] = 1\n adjmat = sprs.triu(adjmat,k=1,format=\"lil\")\n for i in np.arange(0,Np):\n #Add periodic throats to the netowrk (if any)\n tpore2 = pnum[adjmat.rows[i]][ptype[adjmat.rows[i]]<0]\n tpore1 = np.ones_like(tpore2,dtype=int)*i\n conns = self['throat.conns']\n conns = np.concatenate((conns,np.vstack((tpore1,tpore2)).T),axis=0)\n #Add boundary pores and throats to the network\n newporetyps = np.unique(ptype[adjmat.rows[i]][ptype[adjmat.rows[i]]>0])\n newporenums = np.r_[self.num_pores():self.num_pores()+np.size(newporetyps)]\n tpore2 = newporenums\n tpore1 = np.ones_like(tpore2,dtype=int)*i\n conns = np.concatenate((conns,np.vstack((tpore1,tpore2)).T),axis=0)\n self['throat.conns'] = conns\n bcoords = np.zeros((7,3),dtype=float)\n coords = self['pore.coords']\n bcoords[1,:] = [coords[i,0], coords[i,1], 0-Lz*boffset]\n bcoords[2,:] = [0-Lx*boffset, coords[i,1], coords[i,2]]\n bcoords[3,:] = [coords[i,0], -Ly*boffset, coords[i,2]]\n bcoords[4,:] = [coords[i,0], Ly+Ly*boffset, coords[i,2]]\n bcoords[5,:] = [Lx+Lx*boffset, coords[i,1], coords[i,2]]\n bcoords[6,:] = [coords[i,0], coords[i,1], Lz+Lz*boffset]\n newporecoords = bcoords[newporetyps,:]\n coords = np.concatenate((coords,newporecoords),axis=0)\n self['pore.coords'] = coords\n #Reset number of pores and throats (easier than tracking it)\n nums = np.r_[0:np.shape(coords)[0]]\n self['pore.numbering'] = nums\n self['pore.numbering'] = np.ones((nums[-1]+1,),dtype=bool)\n nums = np.r_[0:np.shape(conns)[0]]\n self['throat.numbering'] = nums\n self['throat.numbering'] = np.ones((nums[-1]+1,),dtype=bool)\n logger.debug(\"add_boundaries: end of method\")","def mover_bm_izquierda(self):\n self.nueva_posicion_posible_parte_superior = self.mapa.consultar_casilla_por_movimiento([self.casilla[0] - 1,\n self.casilla[1]],\n [self.vertice_1[0] - self.velocidad,self.vertice_1[1]], \n [self.vertice_1[0] - 5 - 5, self.vertice_1[1]])\n self.nueva_posicion_posible_parte_inferior = self.mapa.consultar_casilla_por_movimiento([self.casilla[0] - 1,\n self.casilla[1] + 1],\n [self.vertice_3[0] - self.velocidad,self.vertice_3[1]],\n [self.vertice_3[0] - 5,self.vertice_3[1]]) \n if self.nueva_posicion_posible_parte_superior[0] != 1 and self.nueva_posicion_posible_parte_inferior[0] != 1:\n self.x -= self.velocidad * (self.x >= 15)\n self.posicion = [self.x,self.posicion[1]]\n self.casilla = [self.casilla[0] - self.nueva_posicion_posible_parte_superior[1] *(self.nueva_posicion_posible_parte_inferior[0] != 1) * (self.nueva_posicion_posible_parte_superior[0] != 1), self.casilla[1]]\n self.redefinir_vertices()","def _change_shape(self,x,y,w,h):\n top = y \n left = x\n right = x + w\n bottom = y + h\n return top,right,bottom,left","def PINTARMATRIXDEBOTONES(self):\n for i in range(0, 26):\n for j in range(0, 26):\n x0 = ((i+1)*24) + 26\n y0 = ((j)*21) \n self.telaMAPA.create_rectangle(x0, 545 - y0, x0 + 10, 550 - y0, tag=str(i)+\"-\"+str(j))\n # Se guarda la inforamcion\n info = (x0, 545 - y0, str(i)+\"-\"+str(j))\n self.bononesPlanoXY.append(info)","def _add_opposing_boundaries(self,btype=[1,6]):\n logger.info(\"add_opposing_boundaries: start of method\")\n\n if btype==[2,5]:\n D=0\n W=1\n H=2\n elif btype==[3,4]:\n D=1\n W=0\n H=2\n elif btype==[1,6]:\n D=2\n W=1\n H=0\n\n Lx = self.domain_size[D]\n Ly = self.domain_size[W]\n Lz = self.domain_size[H]\n #Rotate pore coordinates (use only internal pores)\n pnum = self._net.pore_data['numbering'][self._net.pore_data['type']==0]\n pcoords = np.zeros_like(self._net.pore_data['coords'][pnum,:])\n pcoords[:,0] = self._net.pore_data['coords'][pnum,D]\n pcoords[:,1] = self._net.pore_data['coords'][pnum,W]\n pcoords[:,2] = self._net.pore_data['coords'][pnum,H]\n\n #Determine dimensions of image from dimensions of domain\n f = 100 #minimum image dimension\n im_dim = [0,0,0]\n im_dim[0] = np.floor(f*Lx/np.min([Lx,Ly,Lz]))\n im_dim[1] = np.floor(f*Ly/np.min([Lx,Ly,Lz]))\n im_dim[2] = np.floor(f*Lz/np.min([Lx,Ly,Lz]))\n im_dim = np.array(im_dim,dtype=int)\n\n #Convert pore coordinates into image subscripts\n im_subs = np.zeros_like(pcoords,dtype=int)\n im_subs[:,0] = pcoords[:,0]*im_dim[0]/Lx\n im_subs[:,1] = pcoords[:,1]*im_dim[1]/Ly\n im_subs[:,2] = pcoords[:,2]*im_dim[2]/Lz\n #Find linear indices of each pore in the new image\n im_inds = np.ravel_multi_index((im_subs[:,0], im_subs[:,1], im_subs[:,2]), dims=(im_dim), order='F')\n\n #Generate 3D image of points (place pore numbers at each site for use later)\n img = np.zeros(im_dim,dtype=int)\n img[im_subs[:,0],im_subs[:,1],im_subs[:,2]] = pnum\n\n #Perform distance transform on points and also get 'indicies' of each point\n img_dt, ind_dt = spim.distance_transform_edt(img==0)\n\n #Project all* internal points to x face\n #*Note that it's possible/likely that mutliple internal points map to the same boundary point\n img_bd0 = np.zeros([im_dim[1],im_dim[2]],dtype=int)\n img_bd1 = np.zeros([im_dim[1],im_dim[2]],dtype=int)\n img_bd0[im_subs[:,1],im_subs[:,2]] = im_inds\n img_bd1[im_subs[:,1],im_subs[:,2]] = im_inds\n\n #Create 2D array of distance transform indices for 0 and end faces\n dt_D0 = ind_dt[0,0,:,:]*(img_bd0>0) #0 face\n dt_D1 = ind_dt[0,-1,:,:]*(img_bd1>0) #end face\n\n #Create a 2D mask containing x coordinates of internal points and -1 elsewhere\n img_D0 = -np.ones([im_dim[1],im_dim[2]],dtype=int)\n img_D1 = -np.ones([im_dim[1],im_dim[2]],dtype=int)\n img_D0[im_subs[:,1],im_subs[:,2]] = im_subs[:,0]\n img_D1[im_subs[:,1],im_subs[:,2]] = im_subs[:,0]\n\n #Find where x value of internal points corresponds to x value of distance transform indices\n img_bd0 = (img_D0 == dt_D0)*img_bd0\n img_bd1 = (img_D1 == dt_D1)*img_bd1\n\n #Convert boundary sites to linear indices\n inds_bd0 = img_bd0[np.nonzero(img_bd0)]\n inds_bd1 = img_bd1[np.nonzero(img_bd1)]\n\n #Use linear indices to find pore ID nums\n nums_bd0 = img[np.unravel_index(inds_bd0, dims=(im_dim), order='F')]\n nums_bd1 = img[np.unravel_index(inds_bd1, dims=(im_dim), order='F')]\n nums_bd = np.append(nums_bd0,nums_bd1)\n types_bd = np.append(np.zeros_like(nums_bd0),np.ones_like(nums_bd1))\n\n #Add new boundary pores and throats to the network\n Np = self._net.num_pores() #Get all pores including previously added boundaries\n bp_numbering = np.r_[Np:Np+np.size(nums_bd)]\n bp_type = (types_bd==0)*btype[0] + (types_bd==1)*btype[1]\n bp_coords = np.zeros([np.size(nums_bd),3])\n bp_coords[types_bd==0,D] = np.zeros_like(nums_bd0)-.0001\n bp_coords[types_bd==0,W] = pcoords[nums_bd0,1]\n bp_coords[types_bd==0,H] = pcoords[nums_bd0,2]\n bp_coords[types_bd==1,D] = np.ones_like(nums_bd1)*Lx+0.0001\n bp_coords[types_bd==1,W] = pcoords[nums_bd1,1]\n bp_coords[types_bd==1,H] = pcoords[nums_bd1,2]\n self._net.pore_data['numbering'] = np.append(self._net.pore_data['numbering'],bp_numbering)\n self._net.pore_data['type'] = np.append(self._net.pore_data['type'],bp_type)\n self._net.pore_data['coords'] = np.concatenate((self._net.pore_data['coords'],bp_coords))\n Nt = self._net.num_throats()\n bt_numbering = np.r_[Nt:Nt+np.size(nums_bd)]\n bt_type = np.ones(np.size(nums_bd),dtype=int)*2\n bt_connections = np.zeros([np.size(nums_bd),2],dtype=int)\n bt_connections[:,0] = nums_bd\n bt_connections[:,1] = bp_numbering\n self._net.throat_data['numbering'] = np.append(self._net.throat_data['numbering'],bt_numbering)\n self._net.throat_data['type'] = np.append(self._net.throat_data['type'],bt_type)\n self._net.throat_data['conns'] = np.concatenate((self._net.throat_data['conns'],bt_connections))","def project(self):\n # update positions compared to observer\n pos = self.pos.copy()\n\n # center coordinates around obs coords\n pos[:, 0] -= np.sin(self.theta) * self.V * self.time_elapsed\n pos[:, 2] -= np.cos(self.theta) * self.V * self.time_elapsed\n\n # wrap in a novel box around obs coords\n for i in range(3):\n pos[:, i] = self.bounds[2*i] + np.mod(pos[:, i], self.bounds[2*i + 1]-self.bounds[2*i])\n\n d = (pos**2).sum(axis=1)**.5\n # ind_visible = (pos[:, 2] > 0) * (self.d_min<d) * (d<self.d_max)\n ind_visible = (pos[:, 2] > self.d_min) * (d < self.d_max)\n N_visible = int(np.sum(ind_visible))\n\n # self.state = [X, Y, size]\n self.state = np.ones((N_visible, 7))\n for i in range(2):\n self.state[:, i] = self.mag * pos[ind_visible, i] / pos[ind_visible, 2]\n print(i, self.state[:, i].min(), self.state[:, i].max())\n self.state[:, 2] = self.size / d[ind_visible]\n\n # colors do not change\n self.state[:, 3:] = pos[ind_visible, 3:]\n\n # TODO: larger transparency at larger distance => too fancy :-)\n # self.state[:, 2] = self.size / d[ind_visible]\n\n # for i in range(3):\n # self.state[:, i] *= (self.bounds[2*i+1] - self.bounds[2*i])\n # self.state[:, i] -= self.bounds[2*i]","def _walk(self):\n \n newpos= self.rect.move((self.move, 0)) # x方向移動 .move, y方向不動。\n \n # 偵測碰撞左右牆壁，並處理(反彈)\n if not self.area.contains(newpos):\n if self.rect.left < self.area.left or \\\n self.rect.right > self.area.right:\n self.move = -self.move\n newpos = self.rect.move((self.move, 0))\n self.image = pygame.transform.flip(self.image, 1, 0)\n self.rect = newpos","def left_obj_points(grid_size, dx):\r\n objp = np.zeros((grid_size[1] * grid_size[2], 3), np.float32)\r\n objp[:,1:3] = np.mgrid[0:grid_size[2], 0:grid_size[1]].T.reshape(-1, 2)\r\n u=objp.T; y=0*u; y[1]=u[2]; y[2]=u[1]\r\n\r\n return y.T * dx","def obstacles(self):\r\n\r\n #Radious arround the head\r\n limit_sight = self.snake_sight\r\n head = self.body[0].position\r\n binary_map_complete = self.complete_mapping()\r\n map_matrix = np.matrix(binary_map_complete)\r\n obstacles = []\r\n\r\n #limits in all directions\r\n left_x = head[0] - limit_sight\r\n right_x = head[0] + limit_sight\r\n up_y = head[1] - limit_sight\r\n down_y = head[1] + limit_sight\r\n\r\n #submatrix with limits size\r\n snake_sight = map_matrix[up_y:down_y+1, left_x:right_x+1]\r\n\r\n #Special cases where the snake approximates to the borders\r\n ##Corners\r\n if left_x < 0 and up_y < 0:\r\n snake_sight = map_matrix[0:down_y+1, 0:right_x+1]\r\n interval_x = [self.limits[0] + left_x, self.limits[0]]\r\n interval_y = [self.limits[1] + up_y, self.limits[1]]\r\n interval_x_matrix = map_matrix[0:down_y+1, interval_x[0]:interval_x[1]]\r\n interval_y_matrix = map_matrix[interval_y[0]:interval_y[1], 0:right_x+1]\r\n interval_x_y_matrix = map_matrix[interval_y[0]:interval_y[1], interval_x[0]:interval_x[1]]\r\n temporal = np.c_[interval_x_y_matrix, interval_y_matrix]\r\n snake_sight = np.c_[interval_x_matrix, snake_sight]\r\n snake_sight = np.r_[temporal, snake_sight] \r\n return snake_sight\r\n \r\n if left_x < 0 and down_y > self.limits[1] - 1:\r\n snake_sight = map_matrix[up_y:self.limits[1], 0:right_x+1]\r\n interval_x = [self.limits[0] + left_x, self.limits[0]]\r\n interval_y = [0, down_y - self.limits[1] + 1]\r\n interval_x_matrix = map_matrix[up_y:self.limits[1], interval_x[0]:interval_x[1]]\r\n interval_y_matrix = map_matrix[interval_y[0]:interval_y[1], 0:right_x+1]\r\n interval_x_y_matrix = map_matrix[interval_y[0]:interval_y[1], interval_x[0]:interval_x[1]]\r\n temporal = np.c_[interval_x_y_matrix, interval_y_matrix]\r\n snake_sight = np.c_[interval_x_matrix, snake_sight]\r\n snake_sight = np.r_[snake_sight, temporal]\r\n return snake_sight\r\n \r\n if right_x > self.limits[0]-1 and up_y < 0:\r\n snake_sight = map_matrix[0:down_y+1, left_x:self.limits[0]]\r\n interval_x = [0, right_x - self.limits[0] + 1]\r\n interval_y = [self.limits[1] + up_y, self.limits[1]]\r\n interval_x_matrix = map_matrix[0:down_y+1, interval_x[0]:interval_x[1]]\r\n interval_y_matrix = map_matrix[interval_y[0]:interval_y[1], left_x:self.limits[0]]\r\n interval_x_y_matrix = map_matrix[interval_y[0]:interval_y[1], interval_x[0]:interval_x[1]]\r\n temporal = np.c_[interval_y_matrix, interval_x_y_matrix]\r\n snake_sight = np.c_[snake_sight, interval_x_matrix]\r\n snake_sight = np.r_[temporal, snake_sight]\r\n return snake_sight\r\n \r\n if right_x > self.limits[0]-1 and down_y > self.limits[1]-1:\r\n snake_sight = map_matrix[up_y:self.limits[1], left_x:self.limits[0]]\r\n interval_x = [0, right_x - self.limits[0] + 1]\r\n interval_y = [0, down_y - self.limits[1] + 1]\r\n interval_x_matrix = map_matrix[up_y:self.limits[1], interval_x[0]:interval_x[1]]\r\n interval_y_matrix = map_matrix[interval_y[0]:interval_y[1], left_x:self.limits[0]]\r\n interval_x_y_matrix = map_matrix[interval_y[0]:interval_y[1], interval_x[0]:interval_x[1]]\r\n temporal = np.c_[interval_y_matrix, interval_x_y_matrix]\r\n snake_sight = np.c_[snake_sight, interval_x_matrix]\r\n snake_sight = np.r_[snake_sight, temporal]\r\n return snake_sight\r\n\r\n ##Middle\r\n if left_x < 0:\r\n snake_sight = map_matrix[up_y:down_y+1, 0:right_x+1]\r\n interval_x = [self.limits[0] + left_x, self.limits[0]]\r\n interval_x_matrix = map_matrix[up_y:down_y+1, interval_x[0]:interval_x[1]]\r\n snake_sight = np.c_[interval_x_matrix, snake_sight]\r\n return snake_sight\r\n\r\n if right_x > self.limits[0]-1:\r\n snake_sight = map_matrix[up_y:down_y+1, left_x:self.limits[0]]\r\n interval_x = [0, right_x - self.limits[0] + 1]\r\n interval_x_matrix = map_matrix[up_y:down_y+1, interval_x[0]:interval_x[1]]\r\n snake_sight = np.c_[snake_sight, interval_x_matrix]\r\n return snake_sight\r\n\r\n if up_y < 0:\r\n snake_sight = map_matrix[0:down_y+1, left_x:right_x+1]\r\n interval_y = [self.limits[1] + up_y, self.limits[1]]\r\n interval_y_matrix = map_matrix[interval_y[0]:interval_y[1], left_x:right_x+1]\r\n snake_sight = np.r_[interval_y_matrix, snake_sight]\r\n return snake_sight\r\n \r\n if down_y > self.limits[1]-1:\r\n snake_sight = map_matrix[up_y:self.limits[1], left_x:right_x+1]\r\n interval_y = [0, down_y - self.limits[1] + 1]\r\n interval_y_matrix = map_matrix[interval_y[0]:interval_y[1], left_x:right_x+1]\r\n snake_sight = np.r_[snake_sight, interval_y_matrix]\r\n return snake_sight\r\n\r\n return snake_sight","def box_transform_page(page, direction_list=[]):\n\n if len(page.children) > 1:\n\n # For all children of the page\n for idx in range(0, len(page.children)-1):\n\n # Take two children at a time\n p1 = page.get_child(idx)\n p2 = page.get_child(idx+1)\n\n change_proportion = np.random.randint(\n 10,\n cfg.full_page_movement_proportion_limit\n )\n\n change_proportion /= 100\n\n # Randomly move the line between them up or down one side\n if len(direction_list) < 1:\n direction = np.random.choice([\"rup\", \"lup\"])\n else:\n direction = direction_list[idx]\n\n # If the first panel is horizontal therefore the second is too\n if p1.orientation == \"h\":\n\n # Get the maximum amount the line can move\n change_max = min([(p1.x4y4[1] - p1.x1y1[1]),\n (p2.x4y4[1] - p2.x1y1[1])])\n\n change = change_max*change_proportion\n\n # Specify the line to move\n line_top = p2.x1y1\n line_bottom = p2.x2y2\n\n # If the panel has children then recursively\n # find the leaf children and move them to the new line\n if len(p1.children) > 0:\n move_children_to_line(p1,\n (line_top, line_bottom),\n change,\n \"h\",\n direction\n )\n\n # Otherwise move the current panels to line\n else:\n if direction == \"rup\":\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] + change)\n p1.refresh_coords()\n else:\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] - change)\n p1.refresh_coords()\n\n if len(p2.children) > 0:\n move_children_to_line(p2,\n (line_top, line_bottom),\n change,\n \"h\",\n direction\n )\n else:\n if direction == \"rup\":\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] + change)\n p2.refresh_coords()\n else:\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] - change)\n p2.refresh_coords()\n\n # If the first panel is vertical therefore the second\n # is too since they are siblings\n else:\n # Get the maximum amount the line can move\n change_max = min([(p1.x2y2[0] - p1.x1y1[0]),\n (p2.x2y2[0] - p2.x1y1[0])])\n\n change = change_max*change_proportion\n\n # Specify the line to move\n line_top = p2.x1y1\n line_bottom = p2.x4y4\n\n # If the panel has children then recursively\n # find the leaf children and move them to the new line\n if len(p1.children) > 0:\n move_children_to_line(p1,\n (line_top, line_bottom),\n change,\n \"v\",\n direction\n )\n\n # Otherwise just move the panel since it's a leaf\n else:\n if direction == \"rup\":\n p1.x2y2 = (p1.x2y2[0] - change, p1.x2y2[1])\n else:\n p1.x2y2 = (p1.x2y2[0] + change, p1.x2y2[1])\n\n if len(p2.children) > 0:\n move_children_to_line(p2,\n (line_top, line_bottom),\n change,\n \"v\",\n direction\n )\n else:\n if direction == \"rup\":\n p2.x1y1 = (p2.x1y1[0] - change, p2.x1y1[1])\n else:\n p2.x1y1 = (p2.x1y1[0] + change, p2.x1y1[1])\n\n return page","def _move_receptor_to_grid_center(self):\n lower_receptor_corner = np.array([self._crd[:,i].min() for i in range(3)], dtype=float)\n upper_receptor_corner = np.array([self._crd[:,i].max() for i in range(3)], dtype=float)\n \n receptor_box_center = (upper_receptor_corner + lower_receptor_corner) / 2.\n grid_center = (self._origin_crd + self._uper_most_corner_crd) / 2.\n displacement = grid_center - receptor_box_center\n\n print(\"Receptor is translated by \", displacement)\n\n for atom_ind in range(len(self._crd)):\n self._crd[atom_ind] += displacement\n return None","def define_grid():\n grid_left = np.array([[-13.1000000000000, -35.5000000000000, -48.3000000000000, -60, -16.9000000000000,\n -34.8000000000000, -67.5000000000000, -46.1000000000000, -59.8000000000000,\n -14.2000000000000, -28.3000000000000, -42.3000000000000, -67.6000000000000,\n -50.5000000000000, -14.6000000000000, -60.9000000000000, -31.6000000000000,\n -5.10000000000000, -65.6000000000000, -41.8000000000000, -55.1000000000000,\n -22.7000000000000, -5.80000000000000, -49.2000000000000, -34.5000000000000,\n -61.5500000000000, -63.6000000000000, -40.4000000000000, -48.7000000000000,\n -21.8000000000000, -58.2000000000000, -7, -36.3000000000000, -48.1000000000000,\n -56.8000000000000, -7.30000000000000, -22.2000000000000, -36.8000000000000,\n -46.8000000000000],\n [-67.7000000000000, -60, -55.1000000000000, -51.8000000000000, -51.6000000000000,\n -49.3000000000000, -47.1000000000000, -43.7000000000000, -39.6000000000000,\n -39.1000000000000, -31.2000000000000, -30.7000000000000, -30.1000000000000,\n -24.4000000000000, -22.7000000000000, -18.7000000000000, -16.9000000000000,\n -12.6000000000000, -10.8000000000000, -10.2000000000000, -4.01000000000000, 1.20000000000000,\n 2.80000000000000, 3.70000000000000, 3.90000000000000, 6.20000000000000, 8.30000000000000,\n 11.8000000000000, 14.5000000000000, 16, 18.2000000000000, 18.4000000000000, 19.9000000000000,\n 24.6000000000000, 28.5200000000000, 33.8000000000000, 35, 35.4000000000000,\n 35.6000000000000],\n [69.1000000000000, 66, 58.2000000000000, 48, 78, 71.7000000000000, 31, 61.1000000000000,\n 53.3000000000000, 81.1000000000000, 76, 70.2000000000000, 41.2000000000000, 64.4000000000000,\n 80.2000000000000, 50.9000000000000, 75.2000000000000, 77.3000000000000, 37.8000000000000, 67,\n 53.2000000000000, 72, 74.8000000000000, 54.7000000000000, 66.5000000000000, 35.9000000000000,\n 25.7000000000000, 60.7000000000000, 50.5000000000000, 68.9000000000000, 27.3000000000000,\n 70.3000000000000, 59.6000000000000, 44, 20.8000000000000, 61.7000000000000, 57.2000000000000,\n 47, 36]])\n stn_left = np.array([[-14.6, -13.2, -11.7, -9.10, -11.7, -13.2, -7.90, -10],\n [-15.1, -15.1, -15.1, -12.6, -12.6, -12.6, -9.40, -10.1],\n [-5.40, -7.20, -8.70, -8.70, -7.50, -5.10, -10.3, -7.80]])\n grid_right = np.copy(grid_left)\n grid_right[0, :] = grid_right[0, :] * -1\n stn_right = np.copy(stn_left)\n stn_right[0, :] = stn_right[0, :] * -1\n\n return grid_left, grid_right, stn_left, stn_right","def breaking_of_the_box(size = (10, 10), verbose = False):\n import numpy as np\n r, l, u, d = \"R\", \"L\", \"U\", \"D\" # initiating walkind directions\n np.random.seed(int(time.time()))\n \n # initiating field with walking directions\n field = np.random.randint(1, 5, size = (10, 10))\n field = np.where(field ==1, r, field)\n field = np.where(field =='2', l, field)\n field = np.where(field =='3', u, field)\n field = np.where(field =='4', d, field)\n\n i, j = 0, 0\n coordinates = []\n \n # iterating in a field\n while (i<field.shape[0] and i>-1) and (j<field.shape[1] and j>-1):\n prev_i,prev_j = i, j\n coordinates.append((i, j)) \n \n copy_field = field.copy()\n \n if field[i][j] == r:\n j+=1\n elif field[i][j] == l:\n j-=1\n elif field[i][j] == u:\n i-=1\n elif field[i][j] == d:\n i+=1\n copy_field[i][j] = \"X\"\n if verbose == True:\n print(copy_field, \"#\"*48, sep = \"\\n\") #printing step by step position of a player\n if (i, j) in coordinates:\n # in case of infitine loop break\n print(\"Player is stucked inside of a box\")\n break\n\n else:\n print(\"Player came out of the box\")\n print(\"Coordinates of a breaking point\", \"(\", prev_i, prev_j, \")\")","def move(self, ax, animate):\n for obstacle in self.obstacles:\n obstacle.pose[0] = obstacle.pose[0] + obstacle.dir[0] #add x direction vector\n obstacle.pose[1] = obstacle.pose[1] + obstacle.dir[1] #add y direction vector\n obstacle.pose[2] = obstacle.pose[2] + obstacle.dir[2] #add z direction vector\n\n if animate:\n self.draw(ax)\n\n self.change_dir_if_Collide_boundary()","def unstuck(self):\n mask = Map.current_map.mask\n \n x_max, y_max = mask.get_size()\n orig_x, orig_y = round(self.x), round(self.y)\n x, y = orig_x , orig_y\n unstuck_aggr = COLLISION_UNSTUCK_AGGRESSION\n \n # Vertical check for any open spots we could put the entity on...\n while y > 0:\n if not mask.get_at((x, y)):\n self.y = y\n self.vy = -unstuck_aggr\n return\n y -= unstuck_aggr\n y = orig_y\n while y < y_max:\n if not mask.get_at((x, y)):\n self.y = y\n self.vy = unstuck_aggr\n return\n y += unstuck_aggr\n y = orig_y\n \n # Horizontal spots?\n while x > 0:\n if not mask.get_at((x, y)):\n self.x = x\n self.vx = -unstuck_aggr\n return\n x -= unstuck_aggr\n x = orig_x\n while x < x_max:\n if not mask.get_at((x, y)):\n self.x = x\n self.vx = unstuck_aggr\n return\n x += unstuck_aggr\n x = orig_x\n \n # Diagonal spots\n while x > 0 and y > 0:\n if not mask.get_at((x, y)):\n self.x, self.y = x, y\n self.vx, self.vy = -unstuck_aggr, -unstuck_aggr\n return\n x, y = x - unstuck_aggr, y - unstuck_aggr\n x, y = orig_x, orig_y\n while x < x_max and y < y_max:\n if not mask.get_at((x, y)):\n self.x, self.y = x, y\n self.vx, self.vy = unstuck_aggr, unstuck_aggr\n return\n x, y = x + unstuck_aggr, y + unstuck_aggr\n x, y = orig_x, orig_y\n while x > 0 and y < y_max:\n if not mask.get_at((x, y)):\n self.x, self.y = x, y\n return\n x, y = x - unstuck_aggr, y + unstuck_aggr\n x, y = orig_x, orig_y\n while x < x_max and y > 0:\n if not mask.get_at((x, y)):\n self.x, self.y = x, y\n return\n x, y = x + unstuck_aggr, y - unstuck_aggr\n x, y = orig_x, orig_y\n \n # All right, I officially give up now.\n print(\"Couldn't unstuck object!\")","def boundary(self):\n if self.pos.x < 0:\n self.pos.x = 0\n if self.pos.x > WIDTH - 48:\n self.pos.x = WIDTH - 48\n if self.pos.y < 0:\n self.pos.y = 0\n if self.pos.y > HEIGHT - 48:\n self.pos.y = HEIGHT - 48\n\n self.rect.topleft = self.pos","def move_west(self):\n self.horizontal = (self.horizontal * 2)[1:5]\n self.vertical[0] = self.horizontal[1]\n self.vertical[2] = self.horizontal[3]","def move_of_king_and_rook(self, from_row, from_col, to_row, to_col): \n #provjere da li su kraljevi ili topovi inicirali pomijeranje\n if(from_row == 7 and from_col == 0):\n self.wrl_moved = True\n elif(from_row == 7 and from_col == 7):\n self.wrr_moved = True\n elif(from_row == 7 and from_col == 4):\n self.wk_moved = True\n elif(from_row == 0 and from_col == 0):\n self.brl_moved = True\n elif(from_row == 0 and from_col == 7):\n self.brr_moved = True\n elif(from_row == 0 and from_col == 4):\n self.bk_moved = True\n \n #provjera da li je neko pojeo topove\n if(to_row == 7 and to_col == 0):\n self.wrl_moved = True\n elif(to_row == 7 and to_col == 7):\n self.wrr_moved = True\n elif(to_row == 0 and to_col == 0):\n self.brl_moved = True\n elif(to_row == 0 and to_col == 7):\n self.brr_moved = True","def calculate_leg_xy_limits(self, visualize=False):\n \n #Find the fixed plate position at the \"0\" point\n gonio_zero = copy.copy(self)\n gonio_zero.relative_sample_position = column([0.0, 0.0, 0.0]) #Tell the sample to be centered well.\n gonio_zero.getplatepos(0.0, 0.0, 0.0)\n fixed_plate_zero = np.copy(gonio_zero.fixed_plate)\n #This defines the center of the following matrices\n self.fixed_plate_zero = fixed_plate_zero\n \n #Now we generate a matrix of allowed positions around those points.\n self.leg_safe_xaxis = np.arange(-self.travel, self.travel, self.leg_safe_resolution)\n self.leg_safe_zaxis = np.copy(self.leg_safe_xaxis)\n\n #Create the \"safe zone\" array, initialized to False\n self.leg_safe_zone = np.zeros( (3, self.leg_safe_xaxis.size, self.leg_safe_zaxis.size), dtype=bool ) \n\n #Now make a reasonable approximation\n real_travel_x = 12.5\n real_travel_z = real_travel_x\n for leg in range(3):\n for i_x in range(self.leg_safe_xaxis.size):\n x = self.leg_safe_xaxis[i_x]\n if abs(x)<real_travel_x:\n for i_z in range(self.leg_safe_zaxis.size):\n z = self.leg_safe_zaxis[i_z]\n if abs(z)<real_travel_z:\n self.leg_safe_zone[leg, i_x, i_z] = True\n# #Upper left corner of leg A (0)\n# center = int(len(self.leg_safe_xaxis)/2)\n# self.leg_safe_zone[0, :, :] = False\n# self.leg_safe_zone[0, :center, :center] = True\n# self.leg_safe_zone[1, :, :] = False\n# self.leg_safe_zone[1, center:, 0:center] = True\n# self.leg_safe_zone[2, :, :center] = False\n\n\n if visualize:\n pylab.figure(0)\n pylab.hold(True)\n for leg in range(3):\n pylab.pcolor(self.leg_safe_xaxis+fixed_plate_zero[COORD_X, leg], self.leg_safe_zaxis+fixed_plate_zero[COORD_Z, leg], self.leg_safe_zone[leg, :, :].transpose())\n pylab.xlabel(\"x\")\n pylab.ylabel(\"z\")\n pylab.title(\"Allowable XZ leg positions for the 3 legs.\")\n pylab.draw()\n pylab.axis('equal')\n #pylab.show()","def movement(self, walls: list):\r\n keys = pygame.key.get_pressed()\r\n\r\n if keys[pygame.K_LEFT]: # Angle of vue\r\n self.angle -= self.turn_speed\r\n if keys[pygame.K_RIGHT]:\r\n self.angle += self.turn_speed\r\n\r\n if keys[pygame.K_w]:\r\n next_x = self.x + round(self.speed * math.cos(self.angle)) # same formula then in raycast.ray_casting\r\n next_y = self.y + round(self.speed * math.sin(self.angle))\r\n if walls[int(next_y / game_settings.TILE)][int(next_x / game_settings.TILE)]:\r\n # if we're going into a wall,\r\n # we dont go into the wall.\r\n return\r\n\r\n self.x = next_x\r\n self.y = next_y\r\n\r\n if keys[pygame.K_s]:\r\n next_x = self.x - round(self.speed * math.cos(self.angle))\r\n next_y = self.y - round(self.speed * math.sin(self.angle))\r\n if walls[int(next_y / game_settings.TILE)][int(next_x / game_settings.TILE)]:\r\n return\r\n\r\n self.x = next_x\r\n self.y = next_y\r\n\r\n if keys[pygame.K_a]:\r\n next_x = self.x + round(self.speed * math.sin(self.angle))\r\n next_y = self.y - round(self.speed * math.cos(self.angle))\r\n if walls[int(next_y / game_settings.TILE)][int(next_x / game_settings.TILE)]:\r\n return\r\n\r\n self.x = next_x\r\n self.y = next_y\r\n\r\n if keys[pygame.K_d]:\r\n next_x = self.x - round(self.speed * math.sin(self.angle))\r\n next_y = self.y + round(self.speed * math.cos(self.angle))\r\n if walls[int(next_y / game_settings.TILE)][int(next_x / game_settings.TILE)]:\r\n return\r\n\r\n self.x = next_x\r\n self.y = next_y","def get_target_zone_corners(self):\n EL2 = self._zone_length / 2\n self.c1_position = self.apply(self.zone_pose, (-EL2, -EL2, 0))\n self.c2_position = self.apply(self.zone_pose, (-EL2, EL2, 0))\n self.c3_position = self.apply(self.zone_pose, ( EL2, EL2, 0))\n self.c4_position = self.apply(self.zone_pose, ( EL2, -EL2, 0))","def detectBorders(self, points):\n lane1 = []; lane2 = []\n self.leftLane = [None for _ in range(int(np.floor(self.BIRDVIEW_HEIGHT / self.slideThickness)))]\n self.rightLane = [None for _ in range(int(np.floor(self.BIRDVIEW_HEIGHT / self.slideThickness)))]\n\n pointMap = np.zeros((points.shape[0], 20))\n prePoint = np.zeros((points.shape[0], 20))\n postPoint = np.zeros((points.shape[0], 20))\n\n dis = 10\n max1 = -1; max2 = -1\n\n ##\n ## /!\\ UNSAFE LOOP, TODO: FIX\n ##\n for i in range(points.shape[0]):\n for j in range(len(points[i])):\n pointMap[i][j] = 1\n prePoint[i][j] = -1\n postPoint[i][j] = -1\n\n for i in reversed(range(points.shape[0] - 2)):\n\n for j in range(len(points[i])):\n\n err = 320\n for m in range(1, min(points.shape[0] - 1 - i, 5)):\n check = False ## TODO: why unused ?\n\n for k in range(len(points[i + 1])):\n\n (x_m, y_m) = points[i + m][k].pt\n (x, y) = points[i][j].pt\n\n if (abs(x_m - x) < dis and abs(y_m - y) < err):\n err = abs(x_m - x)\n\n pointMap[i][j] = pointMap[i + m][k] + 1\n prePoint[i][j] = k\n postPoint[i + m][k] = j\n check = True\n\n break ## breaks out of the m loop. Why is it not conditioned by check ? TODO: ???\n\n if (pointMap[i][j] > max1):\n max1 = pointMap[i][j]\n posMax = cv2.KeyPoint(i, j, _size=0)\n \n else:\n posMax = None\n\n for i in range(points.shape[0]):\n for j in range(len(points[i])):\n if posMax:\n if (pointMap[i][j] > max2 and (i != posMax.pt[0] or j != posMax.pt[1]) and postPoint[i][j] == -1): #FIXME \"local variable 'posMax' referenced before assignment\" possible\n max2 = pointMap[i][j]\n posMax2 = cv2.KeyPoint(i, j, _size=0)\n\n\n\n if max1 == -1:\n return\n\n # DEFINES LANE 1 POINTS\n while (max1 >= 1):\n (x,y) = points[int(posMax.pt[0])][int(posMax.pt[1])].pt\n lane1.append(\n [x,y]\n )\n if (max1 == 1):\n break\n\n posMax = cv2.KeyPoint(\n posMax.pt[0]+1,\n prePoint[int(posMax.pt[0])][int(posMax.pt[1])],\n _size=0\n )\n\n max1 -= 1\n\n # DEFINES LANE 2 POINTS\n while (max2 >= 1):\n (x,y) = points[int(posMax2.pt[0])][int(posMax2.pt[1])].pt\n lane2.append(\n [x, y]\n )\n if (max2 == 1):\n break\n\n posMax2 = cv2.KeyPoint(\n posMax2.pt[0]+1,\n prePoint[int(posMax2.pt[0])][int(posMax2.pt[1])],\n _size=0\n )\n\n max2-= 1\n\n subLane1 = np.array(lane1[0:5])\n subLane2 = np.array(lane2[0:5])\n\n # checking if sublane has an empty value\n\n line1 = cv2.fitLine(subLane1, 2, 0, 0.01, 0.01)\n line2 = cv2.fitLine(subLane2, 2, 0, 0.01, 0.01)\n\n try:\n lane1X = (self.BIRDVIEW_WIDTH - line1[3]) * line1[0] / line1[1] + line1[2]\n except:\n lane1X = 0\n\n try:\n lane2X = (self.BIRDVIEW_WIDTH - line2[3]) * line2[0] / line2[1] + line2[2]\n except:\n lane2X = 0\n \n if (lane1X < lane2X):\n for i in range(len(lane1)):\n self.leftLane[int(np.floor(lane1[i][1] / self.slideThickness ))] = lane1[i]\n\n for i in range(len(lane2)):\n self.rightLane[int(np.floor(lane2[i][1] / self.slideThickness ))] = lane2[i]\n\n else:\n\n for i in range(len(lane1)):\n self.rightLane[int(np.floor(lane1[i][1] / self.slideThickness ))] = lane1[i]\n\n for i in range(len(lane2)):\n self.leftLane[int(np.floor(lane2[i][1] / self.slideThickness ))] = lane2[i]","def init(self, windowsize:tuple):\r\n y_count, x_count = 3, 0 #< Set the starting counter for the look_up_table. y starts with three because the first three lines are just Nones\r\n # Creating the constant maze \r\n maze_size = windowsize[0], windowsize[1] - 2 * self.grid_size\r\n self.maze = pg.Surface(maze_size) \r\n \r\n \r\n \r\n # Draw the outermost rectangles on self.maze\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((0, 3 * self.grid_size), (28 * self.grid_size, 31 * self.grid_size)), 4)\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((0 + self.grid_size // 2, 3 * self.grid_size + self.grid_size // 2),(27 * self.grid_size, 30 * self.grid_size)), 4) \r\n # Draw the inner rectangles\r\n for y in self.look_up_table[3 : -2]: #< y is a list of one row from the maze\r\n for x in y: #< x is a string that is decoded as already explained\r\n pos = [self.grid_size * x_count, self.grid_size * y_count]\r\n # Set reference position in the middle of one square\r\n pos[0] += self.grid_size // 2\r\n pos[1] += self.grid_size // 2\r\n x_count += 1\r\n # Check if x is rectangle\r\n if x != None and x[0] == 'r':\r\n # When the size of the string is equal or greater than 4 it's rectangle with a specific size and not just a border.\r\n if len(x) >= 4:\r\n # get the x and y size of the rectangle. x will be something like 'rx1_y1' x1 resprestens the size in x direction and y1 in y direction.\r\n xy_dim = x[1:].split(\"_\") \r\n xy_dim[0] = int(xy_dim[0])\r\n xy_dim[1] = int(xy_dim[1])\r\n rect = tuple(pos), (xy_dim[0] * self.grid_size , xy_dim[1] * self.grid_size )\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], rect, self.width)\r\n # If the last char is a w (white), u (up) or l (left) a line gets draw one a specific position \r\n if x[-1] == 'w':\r\n self.draw_line(self.maze, 'u', (x_count,y_count), True)\r\n if x[-1] == 'u' or x[-1] == 'l':\r\n if x_count == 0:\r\n self.draw_line(self.maze, x[-1], (len(y), y_count))\r\n else:\r\n self.draw_line(self.maze, x[-1], (x_count, y_count))\r\n \r\n y_count += 1\r\n x_count = 0\r\n # Just some cosmetic drawing\r\n pg.draw.rect(self.maze, Colors.colors['BLACK'], ((0, 12 * self.grid_size + self.grid_size // 2 + 4), (self.grid_size // 2 + 1, 10 * self.grid_size - 4)), 4)\r\n pg.draw.rect(self.maze, Colors.colors['BLACK'], ((28 * self.grid_size - self.grid_size // 2 - 1, 12 * self.grid_size + self.grid_size // 2 + 4), (self.grid_size // 2 + 1, 10 * self.grid_size - 4)), 4)\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((-self.width, 13 * self.grid_size), (5 * self.grid_size, 3 * self.grid_size)), self.width)\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((-self.width, 19 * self.grid_size), (5 * self.grid_size, 3 * self.grid_size)), self.width)\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((23 * self.grid_size, 13 * self.grid_size), (5 * self.grid_size + 10, 3 * self.grid_size)), self.width)\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((23 * self.grid_size, 19 * self.grid_size), (5 * self.grid_size + 10, 3 * self.grid_size)), self.width)\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((11 * self.grid_size, 16 * self.grid_size), (6 * self.grid_size, 3 * self.grid_size)), self.width)\r\n \r\n pg.draw.line(self.maze, Colors.colors['BLUE'], (0, 16 * self.grid_size + self.grid_size // 2 - 1), (self.grid_size // 2 + self.width, 16 * self.grid_size + self.grid_size // 2 - 1), self.width)\r\n pg.draw.line(self.maze, Colors.colors['BLUE'], (0, 18 * self.grid_size + self.grid_size // 2), (self.grid_size // 2 + self.width, 18 * self.grid_size + self.grid_size // 2), self.width)\r\n pg.draw.line(self.maze, Colors.colors['BLUE'], (self.grid_size * 28 - self.grid_size, 16 * self.grid_size + self.grid_size // 2 - 1), (self.grid_size * 28 + self.width, 16 * self.grid_size + self.grid_size // 2 - 1), self.width)\r\n pg.draw.line(self.maze, Colors.colors['BLUE'], (self.grid_size * 28 - self.grid_size, 18 * self.grid_size + self.grid_size // 2), (self.grid_size * 28 + self.width, 18 * self.grid_size + self.grid_size // 2), self.width)\r\n self.is_init = True","def drawSolu(self): \n vinemaze = MakeMaze()\n solulist = vinemaze.build_maze(self.width-4, 0, (8,24))\n \n #draw starting point square at bottom right corner\n start = pygame.Rect(self.width, self.height, -4, -4)\n pygame.draw.rect(gameView.background, self.color, start)\n dimenlist = []\n \n #determine the rectangle's starting coordinate, width, and height\n for i in range(1, len(solulist)):\n cur_coord = solulist[i]\n prev_coord = solulist[i-1]\n RectW = prev_coord[0] - cur_coord[0]\n RectH = prev_coord[1] - cur_coord[1]\n\n #keep track of coordinates where non-overlapping vines occur \n if RectH > 0:\n dimenlist.append(prev_coord)\n \n #Increase thickness of vines, depending on if they lie vertical or horizontal \n if abs(RectW) < abs(RectH):\n newRectW = self.increasepix(RectW)\n vine = pygame.Rect(cur_coord[0], cur_coord[1], newRectW, RectH) \n else:\n newRectH = self.increasepix(RectH)\n vine = pygame.Rect(cur_coord[0], cur_coord[1], RectW, newRectH)\n pygame.draw.rect(gameView.background, self.color, vine)\n \n #fill in the missing corners due to non-overlapping vines\n for i in range(1, len(dimenlist)):\n prevW = dimenlist[i][0]\n prevH = dimenlist[i][1]\n if prevW > 0:\n fillcoord = (prevW, prevH)\n fill = pygame.Rect(fillcoord[0], fillcoord[1], 4, 4)\n pygame.draw.rect(gameView.background, self.color, fill)\n\n gameView.screen.blit(gameView.background,(0,0))\n pygame.display.update()","def world_to_grid(mapdata, wp):\n WX = wp.x\n WY = wp.y\n resol = mapdata.info.resolution\n # -0.5 but coordinates to center\n gx = math.floor((WX - mapdata.info.origin.position.x) / resol - 0.5)\n gy = math.floor((WY - mapdata.info.origin.position.y) / resol - 0.5)\n return gx, gy","def update(self):\n self.on_left = (abs(self.x - self.maze.LEFT_VERT) <\n self.WALL_TOLERANCE)\n self.on_right = (abs(self.x - self.maze.RIGHT_VERT) <\n self.WALL_TOLERANCE)\n\n self.on_top = (abs(self.y - self.maze.TOP_HORIZ) <\n self.WALL_TOLERANCE)\n self.on_bottom = (abs(self.y - self.maze.BOTTOM_HORIZ) <\n self.WALL_TOLERANCE)\n self.x = self.x + self.x_add\n self.y = self.y + self.y_add\n\n # If the game is over and Pacman wins, stop moving\n if self.gc.player_wins:\n self.x_add = 0\n self.y_add = 0\n # If the game is over and Pacman loses, top moving and\n # Open mouth to oblivion.\n elif self.gc.pinky_wins:\n self.open_close = 1\n self.x_add = 0\n self.y_add = 0\n self.mouth_angle = self.mouth_angle + self.open_close\n else:\n if self.mouth_angle < 45:\n self.open_close = self.mouth_speed\n self.mouth_angle = self.mouth_angle + self.open_close\n if self.mouth_angle < 0:\n self.open_close = - self.mouth_speed\n self.mouth_angle = self.mouth_angle + self.open_close\n else:\n while self.mouth_angle > 0:\n self.open_close = - self.mouth_speed\n self.mouth_angle = self.mouth_angle + self.open_close\n self.eat_dots()","def update_pos(self, game_field, all_ghost_out, windowsize):\r\n\r\n # If Pac-Man wants to change the direction into a direction, that is not the same or the opposite of the current direction, it could possible be a pre- or postturn\r\n if self.direction != self.last_dir and find_opposite(self.last_dir) != self.direction and self.state != '':\r\n self.pre_or_post_turn(game_field, all_ghost_out)\r\n\r\n # If Pac-Man moves, update his position depending on his direction\r\n if self.state == 'm':\r\n fak = 1\r\n if self.direction == 'u':\r\n self.pos[1] -= fak * self.speed\r\n elif self.direction == 'd':\r\n self.pos[1] += fak * self.speed\r\n elif self.direction == 'l':\r\n self.pos[0] -= fak * self.speed\r\n elif self.direction == 'r':\r\n self.pos[0] += fak * self.speed\r\n\r\n ongrid = (self.pos[0] % self.grid_size == 0 and self.pos[1] % self.grid_size == 0)\r\n\r\n # When Pac-Man is on grid check the field type he's on and in front of him\r\n if ongrid :\r\n field = game_field.possible_way(self.pos, self.last_dir)\r\n self.cnt_points(field, all_ghost_out)\r\n\r\n # When the next field is a wall of the maze, make Pac-Man stop moving, otherwise let him continue moving\r\n if field != None and field[0] == 'r':\r\n field2 = game_field.possible_way(self.pos, self.direction)\r\n self.cnt_points(field2, all_ghost_out)\r\n if field2 != None and field2[0] == 'r':\r\n self.state = ''\r\n else:\r\n self.state = 'm'\r\n\r\n # When the field in front of him is the end of a tunnel move Pac-Man to the other side\r\n if field == 'os':\r\n if self.direction == 'l':\r\n self.pos[0] = windowsize[0] \r\n elif self.direction == 'r':\r\n self.pos[0] = -self.grid_size\r\n\r\n # When the next field is a field Pac-Man can move on to, safe the latest direction in direction\r\n if (field == None or field[0] != 'r'):\r\n self.direction = self.last_dir[:]\r\n\r\n # Force Pacmans direction to drive through the tunnel, just to avoid graphical bugs\r\n if self.pos[0] < 0:\r\n self.direction = 'r'\r\n self.last_dir = 'r'\r\n elif self.pos[0] > windowsize[0] - self.grid_size:\r\n self.direction = 'l'\r\n self.last_dir = 'l'","def _move_cursors_to_pos(self):\n for axis in range(3):\n x, y = self._vox[list(self._xy_idx[axis])]\n self._images['cursor_v'][axis].set_xdata([x, x])\n self._images['cursor_h'][axis].set_ydata([y, y])\n self._zoom(0) # doesn't actually zoom just resets view to center\n self._update_images(draw=True)\n self._update_moved()","def move(self):\n # neighbor offsets\n offset = [(-1, 1),(0, 1),(1, 1),(-1, 0),(1, 0),(-1, -1),(0, -1),(1, -1)]\n for i in range(len(offset)):\n x = self.x + offset[i][0] # neighboring coordinates\n y = self.y + offset[i][1]\n if self.island.animal(x, y) == 0: # neighboring spot is open\n self.island.remove(self) # remove from current spot\n self.x = x # new coordinates\n self.y = y\n self.island.register(self) # register new coordinates\n break # finished with move","def move(self):\n # neighbor offsets\n offset = [(-1, 1),(0, 1),(1, 1),(-1, 0),(1, 0),(-1, -1),(0, -1),(1, -1)]\n for i in range(len(offset)):\n x = self.x + offset[i][0] # neighboring coordinates\n y = self.y + offset[i][1]\n if self.island.animal(x, y) == 0: # neighboring spot is open\n self.island.remove(self) # remove from current spot\n self.x = x # new coordinates\n self.y = y\n self.island.register(self) # register new coordinates\n break # finished with move","async def unwindGrid(fps):\n\n rg = homeGrid() # get a grid\n # overwrite the positions to the positions that the robots\n # are reporting\n for r in rg.robotDict.values():\n await fps.positioners[r.id].update_position()\n alpha, beta = fps.positioners[r.id].position\n r.setAlphaBeta(alpha, beta)\n\n forwardPath, reversePath = generatePath(rg)\n\n await fps.send_trajectory(reversePath)","def move(self, dx=0, dy=0):\n\n\t\tcurr = self.rots[self.rot]\n\n\t\t# within the NxM grid of this piece, what's the min/max x/y coords\n\t\t# (ie, \"bounding box of pixels actually used\")\n\t\t\n\t\t# TODO: this isn't right!\n\n\t\t# min_x = min(b[y][0] for y in range(height) if \n\t\t# max_x = max(r[-1] for r in curr)\n\t\t# min_y = min(b[0][x] for x in range(width))\n\t\t# max_y = max(b[-1][x] for x in range(width))\n\n\t\t# if ","def move(self):\n\n if self.rect.right >= SCREEN_WIDTH:\n self.rect.right = SCREEN_WIDTH\n elif self.rect.left <= 0:\n self.rect.left = 0\n #elif self.rect.right < SCREEN_WIDTH and self.rect.left: \n \n self.rect.move_ip(self.speed_p,0)","def update(self):\n\n # move left - right\n if self.left:\n self.rect.x -= 2\n else:\n self.rect.x += 2\n if abs(self.rect.x - self.originx) == 150:\n self.left = True\n elif abs(self.rect.x - self.originx) == 0:\n self.left = False","def update(self):\r\n if self.right > games.screen.width or self.left < 0:\r\n self.dx = -self.dx\r\n \r\n if self.bottom > games.screen.height or self.top < 0:\r\n self.dy = -self.dy","def calculate_next_move(self, visit):\n self.depth += 1\n new_boards = []\n for vehicle_id in range(len(self.vehicles)):\n vehicle = self.vehicles[vehicle_id]\n state = self.get_board()\n if vehicle.orientation == 0: #horizontal\n if vehicle.x > 0: #left\n if state[vehicle.y][vehicle.x-1] == \"..\":\n self.vehicles[vehicle_id].x -=1\n if not self.get_board().tostring() in visit:\n if not self.get_board().all in new_boards:\n new_board = deepcopy(self)\n self.vehicles[vehicle_id].x += 1\n new_board.parent = self\n new_boards.append(new_board)\n else:\n self.vehicles[vehicle_id].x += 1\n\n if vehicle.x + vehicle.length <= (len(state)-1): #right\n if state[vehicle.y][vehicle.x+vehicle.length] == \"..\":\n self.vehicles[vehicle_id].x += 1\n if not self.get_board().tostring() in visit:\n if not self.get_board().all in new_boards:\n new_board = deepcopy(self)\n self.vehicles[vehicle_id].x -= 1\n new_board.parent = self\n new_boards.append(new_board)\n else:\n self.vehicles[vehicle_id].x -= 1\n\n else: #vertical\n if vehicle.y - 1 >= 0: #up\n if state[vehicle.y-1][vehicle.x] == \"..\":\n self.vehicles[vehicle_id].y -= 1\n if not self.get_board().tostring() in visit:\n if not self.get_board().all in new_boards:\n new_board = deepcopy(self)\n self.vehicles[vehicle_id].y += 1\n new_board.parent = self\n new_boards.append(new_board)\n else:\n self.vehicles[vehicle_id].y += 1\n\n if vehicle.y + vehicle.length <= (len(state)-1):\n if state[vehicle.y + vehicle.length][vehicle.x] == \"..\":#down\n self.vehicles[vehicle_id].y += 1\n if not self.get_board().tostring() in visit:\n if not self.get_board().all in new_boards:\n new_board = deepcopy(self)\n self.vehicles[vehicle_id].y -= 1\n new_board.parent = self\n new_boards.append(new_board)\n else:\n self.vehicles[vehicle_id].y -= 1\n self.depth -= 1\n return new_boards","def fill_walk(self):\n\n #Seguir tomando caminos hasta que se alcance la cantidad establecida.\n while len(self.x_values) < self.num_points:\n\n #Decidir cual direccion tomar y cuan lejos ir hacia esa direccion.\n x_direction = choice([1, -1])\n x_distance = choice([0, 1, 2, 3, 4])\n x_step = x_direction * x_distance\n\n y_direction = choice([1,-1])\n y_distance = choice([0, 1, 2, 3, 4])\n y_step = y_direction * y_distance\n\n #Ignorar movimientos nulos.\n if x_step == 0 and y_step == 0:\n continue\n\n #Calcular la nueva posicion.\n x = self.x_values[-1] + x_step\n y = self.y_values[-1] + y_step\n\n self.x_values.append(x)\n self.y_values.append(y)","def draw(self, win, player, displayList, enemyHitboxList, mapWidth, mapHeight):\n cameraX = player.rect.left + (player.rect.width // 2) - (SCREEN_WIDTH // 2)\n cameraY = player.rect.top + (player.rect.height // 2) - (SCREEN_HEIGHT // 2)\n\n # On centre la camera tant que le joueurs n'atteind pas les bords\n if cameraX >= 0 and cameraX < mapWidth - SCREEN_WIDTH:\n self.x = cameraX\n\n if cameraY >= 0 and cameraY < mapHeight - SCREEN_HEIGHT:\n self.y = cameraY\n\n # Calcul de l'X du joueur en fonction s'il est en haut, bas ou entre les 2\n if cameraX >= 0 and cameraX < mapWidth - SCREEN_WIDTH:\n playerX = (SCREEN_WIDTH // 2) - (player.rect.width // 2)\n else:\n # Si le joueur est a droite\"\"\"\n if cameraX >= mapWidth - SCREEN_WIDTH:\n self.x = mapWidth - SCREEN_WIDTH\n playerX = player.rect.left - mapWidth + SCREEN_WIDTH\n # Si le joueur est a gauche\"\"\"\n else:\n self.x = 0\n playerX = player.rect.left\n\n\n # Calcul de l'Y du joueur en fonction s'il est a gauche, droite ou entre les 2\n if cameraY >= 0 and cameraY < mapHeight - SCREEN_HEIGHT:\n playerY = (SCREEN_HEIGHT // 2) - (player.rect.height // 2)\n else:\n # Si le joueur est en dessous\n if cameraY >= mapHeight - SCREEN_HEIGHT:\n self.y = mapHeight - SCREEN_HEIGHT\n playerY = player.rect.top - mapHeight + SCREEN_HEIGHT\n # Si le joueur est au dessus \n else:\n self.y = 0\n playerY = player.rect.top\n\n for element in displayList:\n element.draw(win,element.rect.left - self.x,element.rect.top - self.y)\n #for elem in enemyHitboxList:\n #pg.draw.rect(win, (200, 200, 200), pg.Rect(elem.left - self.x,elem.top - self.y, elem.width, elem.height))\n player.draw(win, playerX, playerY)","def updatePositionAndClean(self):\n #X direction (num. rows) wall limit is the width of rectangular room\n #Y direction (num. cols) wall limit is the height of rectangular room\n #So (0,0) is in bottom LEFT corner--since rows start at zero at BOTTOM, not top\n #direction works as you would think, with east at 0 or 360 degrees, 90 degrees at north,\n #180 degrees at west, and 270 degrees at south direction\n\n #so each time unit, getNewPosition in SAME direction if you don't hit the wall\n #if you hit the wall, then get a new RANDOM direction and then recalculate new position,\n #making sure it is a valid position on grid, has not already been cleaned (tile visited)\n\n #So it makes no difference which direction you are moving in--the getNewPosition() function\n #figures out mathematically what the next position is, based on grid, and you just have to\n #determine whether you have hit the wall in that same direction--don't have to look at the\n #number the degrees or radians in that particular direction--just moving in same direction,\n #get next position, do you hit the wall, if so get new random direction, move that way, if you\n #won't hit a wall that way.\n\n #If you don't hit a wall when you calculate a new direction, but the tile is clean already, then\n #just go through the tiles and find one that is not clean yet, and move in the same direction.\n \n robotPos = self.getRobotPosition()\n posx = robotPos.getX()\n posy = robotPos.getY()\n posx = math.floor(posx)\n posy = math.floor(posy)\n #First check if this position is clean:\n #if (self.room.isTileCleaned(posx,posy) == False):\n #then clean this tile!\n #self.room.cleanTileAtPosition(robotPos)\n #Now see where to move robot next on floor and clean that tile if it is not clean\n #So first try moving in same direction--will you hit a wall?\n newPos = self.position.getNewPosition(self.direction,self.speed)\n newPosx = newPos.getX()\n newPosy = newPos.getY()\n newPosx = math.floor(newPosx)\n newPosy = math.floor(newPosy)\n if (self.room.isPositionInRoom(newPos)) and (self.room.isTileCleaned(newPosx,newPosy) == False):\n #position is in room AND the tile has NOT been visited yet--since it's still DIRTY\n #Should NOT have to check whether you hit a wall, since new position is in room\n #so NO NEW DIRECTION needed yet--move in SAME direction\n self.setRobotPosition(newPos)\n self.room.cleanTileAtPosition(newPos)\n #print \"Moved in SAME DIRECTION I was moving in last time, direction = \" + str(self.direction)\n else: # (self.room.isPositionInRoom(newPos) == False) or (self.room.isTileCleaned(newPosx, newPosy) == True):\n # either HIT WALL -- OR -- tile already cleaned -- so calculate new RANDOM direction\n\n #NOTE: this works until you are surrounded by tiles that have no next step tile that has not already been\n #cleaned?\n #?? think a problem is that if all surrounding tiles are already clean, then, in that case,\n #you can get stuck in situation where you keep recalculating a new random direction, but when you take a step,\n #all the next tiles have already been cleaned, and you get stuck in a loop, so in this case, you must\n #not recalculate a new direction, but rather keep going in same direction until you find a tile not clean,\n #and jump to that tile instead, and go from there.\n #So find this case--see if that corrects this issue!\n \n keepTryingNewDirection = True\n while (keepTryingNewDirection == True):\n self.direction = random.randrange(0,359) #get new random direction\n newPos = self.position.getNewPosition(self.direction,self.speed) #get new next position step with new direc.\n newPosx = newPos.getX()\n newPosy = newPos.getY()\n newPosx = math.floor(newPosx)\n newPosy = math.floor(newPosy)\n if (self.room.isPositionInRoom(newPos)) and (self.room.isTileCleaned(newPosx,newPosy) == False):\n #new position in new direction is in room, and the tile has not been cleaned yet\n #so new direction and new tile to clean found!\n self.setRobotPosition(newPos)\n self.room.cleanTileAtPosition(newPos)\n #print \"Moved in NEW DIRECTION I was moving in last time, direction = \" + str(self.direction)\n keepTryingNewDirection = False\n elif (self.room.isPositionInRoom(newPos) == False):\n #new position in new direction NOT in room -- try again!\n #print \"new direction found a new position not in room --hit wall--try again! direction = \" + str(self.direction)\n continue\n else:\n #print \"new direction produced new position in room but tile already clean--try again?! direction = \" + str(self.direction)\n #print \"first check to see if all tiles have already been cleaned.\"\n #?? Any other checks needed here? list of tiles visited? is this really needed??\n #calculate list of cells not clean yet\n tilesCleaned = []\n allSurroundingTilesClean = False\n foundTileUnclean = False\n saveWidth = 0\n saveHeight = 0\n for i in range(0,self.room.width):\n for j in range(0,self.room.height):\n if (self.room.isTileCleaned(i,j) == False):\n saveWidth = i\n saveHeight = j\n foundTileUnclean = True\n else:\n #print \"appending to tiles cleaned: tile: i = \" + str(i) + \" j = \" + str(j)\n tilesCleaned.append((i,j)) #make list of tiles cleaned\n if (foundTileUnclean == True):\n #print \"not all tiles are clean!--start here rather than getting new direc. i = \" + str(saveWidth) + \" j = \" + str(saveHeight)\n newPos = Position(saveWidth,saveHeight)\n self.setRobotPosition(newPos)\n self.room.cleanTileAtPosition(newPos)\n #print \"Found new tile that was not clean! current direc. \" + str(self.direction)\n #print \"tile location x = \" + str(saveWidth) + \" y = \" + str(saveHeight)\n keepTryingNewDirection = False\n else:\n keepTryingNewDirection = False\n #print \"all tiles clean! stop cleaning!-- do not look for new direction! should be done.\"\n\n #for tile in tilesCleaned:\n #print tile","def pushing_planning(object, object_pose1_world, object_pose2_world,\n palm_pose_l_object, palm_pose_r_object, arm='r', pusher_angle=0.0):\n primitive_name = 'pushing'\n #0. get initial palm poses in world frame\n palm_poses_initial_world = planning_helper.palm_poses_from_object(\n object_pose=object_pose1_world,\n palm_pose_l_object=palm_pose_l_object,\n palm_pose_r_object=palm_pose_r_object)\n\n #1. Convert pose to 2d pose\n object_initial_planar_pose = planning_helper.get_2d_pose(object_pose1_world)\n object_final_planar_pose = planning_helper.get_2d_pose(object_pose2_world)\n\n #2.\n configurations_transformed, N_star, object_pose_2d_list, t_star = planning_helper.dubins_trajectory(\n q0=object_initial_planar_pose,\n qf=object_final_planar_pose,\n radius=0.125,\n velocity_real=0.05,\n step_size=0.015,\n contact_angle=pusher_angle)\n # 3. iterate through trajectory and compute robot i)poses and ii)joints\n object_pose_world_list = []\n palm_poses_world_list = []\n palm_pose_l_world_list = []\n palm_pose_r_world_list = []\n for counter, object_pose_2d in enumerate(object_pose_2d_list):\n # 4. get 3d object pose from 2d\n object_pose__world = planning_helper.get3dpose_object(\n pose2d=object_pose_2d,\n pose3d_nominal=object_pose1_world)\n if arm=='r':\n palm_pose_l_world = palm_poses_initial_world[0]\n palm_pose_r_world = util.convert_reference_frame(\n pose_source=palm_pose_r_object,\n pose_frame_target=util.unit_pose(),\n pose_frame_source=object_pose__world,\n frame_id=\"yumi_body\",\n )\n else:\n palm_pose_l_world = util.convert_reference_frame(\n pose_source=palm_pose_l_object,\n pose_frame_target=util.unit_pose(),\n pose_frame_source=object_pose__world,\n frame_id=\"yumi_body\",\n )\n palm_pose_r_world = palm_poses_initial_world[1]\n object_pose_world_list.append(object_pose__world)\n palm_poses_world_list.append([palm_pose_l_world, palm_pose_r_world])\n palm_pose_l_world_list.append(palm_pose_l_world)\n palm_pose_r_world_list.append(palm_pose_r_world)\n #5. return final plan\n plan_dict = {}\n plan_dict['palm_poses_world'] = palm_poses_world_list\n plan_dict['palm_pose_l_world'] = palm_pose_l_world_list\n plan_dict['palm_pose_r_world'] = palm_pose_r_world_list\n plan_dict['primitive'] = primitive_name\n plan_dict['object_poses_world'] = object_pose_world_list\n plan_dict['name'] = 'push_object'\n plan_dict['t'] = t_star\n plan_dict['N'] = len(N_star)\n return [plan_dict]","def update(self):\n # Desplazar izquierda/derecha\n self.rect.x += self.cambio_x\n global COL\n COL = False\n # Hemos chocado contra la pared despues de esta actualizacion?\n lista_impactos_bloques = pygame.sprite.spritecollide(self, self.paredes, False)\n for bloque in lista_impactos_bloques:\n #Si nos estamos desplazando hacia la derecha, hacemos que nuestro lado derecho sea el lado izquierdo del objeto que hemos tocado-\n if self.cambio_x > 0:\n self.rect.right = bloque.rect.left\n else:\n # En caso contrario, si nos desplazamos hacia la izquierda, hacemos lo opuesto.\n self.rect.left = bloque.rect.right\n COL = True\n \n # Desplazar arriba/izquierda\n self.rect.y += self.cambio_y\n \n # Comprobamos si hemos chocado contra algo\n lista_impactos_bloques = pygame.sprite.spritecollide(self, self.paredes, False) \n for bloque in lista_impactos_bloques:\n \n # Reseteamos nuestra posicion basandonos en la parte superior/inferior del objeto.\n if self.cambio_y > 0:\n self.rect.bottom = bloque.rect.top \n else:\n self.rect.top = bloque.rect.bottom \n COL = True","def orientWP(self):\n import DraftGeomUtils\n if hasattr(App, \"DraftWorkingPlane\"):\n if len(self.node) > 1 and self.obj:\n n = DraftGeomUtils.getNormal(self.obj.Shape)\n if not n:\n n = App.DraftWorkingPlane.axis\n p = self.node[-1]\n v = self.node[-2].sub(self.node[-1])\n v = v.negative()\n if not self.oldWP:\n self.oldWP = App.DraftWorkingPlane.copy()\n App.DraftWorkingPlane.alignToPointAndAxis(p, n, upvec=v)\n if hasattr(Gui, \"Snapper\"):\n Gui.Snapper.setGrid()\n Gui.Snapper.restack()\n if self.planetrack:\n self.planetrack.set(self.node[-1])","def adjust_position(self):\n\n # Adjust position for x-axis\n r = self.rect.x % 30\n if r != 0:\n if r <= 16:\n x = self.rect.x - r\n else:\n x = self.rect.x + (30 - r)\n\n else:\n x = self.rect.x\n\n # Adjust position for y-axis\n r = self.rect.y % 30\n if r != 0:\n if r <= 16:\n y = self.rect.y - r\n else:\n y = self.rect.y + (30 - r)\n else:\n y = self.rect.y\n\n return x, y","def update(self):\n self.rect.x += self.dx\n self.rect.y += self.dy\n # Verifica se o bloco atingiu a borda\n if self.rect.x < LARG_BORDA:\n self.rect.x = LARG_BORDA\n if self.rect.x > WINDOWWIDTH - LARG_BORDA - self.rect.width:\n self.rect.x = WINDOWWIDTH - LARG_BORDA - self.rect.width\n if self.rect.y < LARG_BORDA:\n self.rect.y = LARG_BORDA\n if self.rect.y > WINDOWHEIGHT - LARG_BORDA - self.rect.height:\n self.rect.y = WINDOWHEIGHT - LARG_BORDA - self.rect.height\n\n if self.vel_max != 0:\n self.dx = random.randint(-self.vel_max, self.vel_max)\n self.dy = random.randint(-self.vel_max, self.vel_max)","def move(s, a, beta):\n # update velocity with probability 1-beta\n global V\n if np.random.choice(2, p=[beta, 1-beta]) == 1:\n if a in [0, 3, 6] and V > 0: V -= 1\n elif a in [2, 5, 8] and V < 3: V += 1\n # else:\n # print \"velocity not updated!\"\n\n r_border = range(6, 49, 7) # states on the right border\n l_border = range(0, 49, 7) # states on the left border\n t_border = range(7) # states on the top border\n\n units = range(V)\n # move RIGHT of V units:\n if a < len(ACTIONS) / 3:\n for i in units:\n WORLD[STATE2WORLD[s+i]] = '~' # draw my path gradualy in the world\n # crash: reset world and velocities, return to start state\n if s+i in r_border or s+i+1 in WALLS:\n reset()\n return START, CRASH\n # nothing special: draw where I end up & return\n WORLD[STATE2WORLD[s+V]] = 'O'\n return s+V, STEP\n\n # move UP of V units:\n elif a < 2*len(ACTIONS) / 3:\n for i in units:\n WORLD[STATE2WORLD[s-i*7]] = '|' # draw my path gradualy in the world\n # crash: reset world and velocities, return to start state\n if s-i*7 in t_border or s-(i+1)*7 in WALLS:\n reset()\n return START, CRASH\n # nothing special: draw where I end up & return\n WORLD[STATE2WORLD[s-V*7]] = 'O'\n return s-V*7, STEP\n\n # move LEFT of V units:\n elif a < len(ACTIONS):\n for i in units:\n WORLD[STATE2WORLD[s-i]] = '~' # draw my path gradualy in the world\n # goal: draw where I end up & return\n if s-i-1 in GOALS:\n WORLD[STATE2WORLD[s-i-1]] = 'O'\n return s-i-1, WIN\n # crash: reset world and velocities, return to start state\n elif s-i in l_border or s-i-1 in WALLS:\n reset()\n return START, CRASH\n # nothing special: draw where I end up & return\n WORLD[STATE2WORLD[s-V]] = 'O'\n return s-V, STEP\n\n return s, STEP # should never happen","def move_buildings(self):","def move(self, rel_pos):\n self.pos = (self.pos[0] + rel_pos[0] * GRID, self.pos[1] + rel_pos[1] * GRID)","def _walk(self):\n new_pos = self.rect.move((self.move, 0)) # move 9 pixel to the right per frame\n if self.rect.left < self.area.left or self.rect.right > self.area.right:\n self.move = -self.move # move to the opposite direction when the chimp position exceeds the screen\n new_pos = self.rect.move((self.move, 0))\n self.image = pygame.transform.flip(\n self.image, 1, 0\n ) # mirror the chimp to make it looks like turning around\n self.rect = new_pos","def apply_sliding_windows(self, binary_warped, leftx_base, rightx_base):\r\n # Choose the number of sliding windows\r\n nwindows = 9\r\n # Set height of windows\r\n window_height = np.int(binary_warped.shape[0] / nwindows)\r\n # Identify the x and y positions of all nonzero pixels in the image\r\n nonzero = binary_warped.nonzero()\r\n nonzeroy, nonzerox = np.array(nonzero[0]), np.array(nonzero[1])\r\n # Current positions to be updated for each window\r\n leftx_current, rightx_current = leftx_base, rightx_base\r\n # Set the width of the windows +/- margin\r\n margin = 100\r\n # Set minimum number of pixels found to recenter window\r\n minpix = 50\r\n # Create empty lists to receive left and right lane pixel indices\r\n left_lane_inds, right_lane_inds = [], []\r\n\r\n # Step through the windows one by one\r\n # Create an output image to draw on and visualize the result\r\n out_img = np.dstack((binary_warped, binary_warped, binary_warped)) * 255\r\n for window in range(nwindows):\r\n # Identify window boundaries in x and y (and right and left)\r\n win_y_low = binary_warped.shape[0] - (window + 1) * window_height\r\n win_y_high = binary_warped.shape[0] - window * window_height\r\n win_xleft_low, win_xleft_high = leftx_current - margin, leftx_current + margin\r\n win_xright_low, win_xright_high = rightx_current - margin, rightx_current + margin\r\n # Draw the windows on the visualization image\r\n if self.debug:\r\n cv2.rectangle(out_img,(win_xleft_low,win_y_low),(win_xleft_high,win_y_high),(0,255,0), 2)\r\n cv2.rectangle(out_img,(win_xright_low,win_y_low),(win_xright_high,win_y_high),(0,255,0), 2)\r\n # Identify the nonzero pixels in x and y within the window\r\n good_left_inds = ((nonzeroy >= win_y_low) & (nonzeroy < win_y_high) & (nonzerox >= win_xleft_low) & (\r\n nonzerox < win_xleft_high)).nonzero()[0]\r\n good_right_inds = ((nonzeroy >= win_y_low) & (nonzeroy < win_y_high) & (nonzerox >= win_xright_low) & (\r\n nonzerox < win_xright_high)).nonzero()[0]\r\n # Append these indices to the lists\r\n left_lane_inds.append(good_left_inds)\r\n right_lane_inds.append(good_right_inds)\r\n # If you found > minpix pixels, recenter next window on their mean position\r\n if len(good_left_inds) > minpix:\r\n leftx_current = np.int(np.mean(nonzerox[good_left_inds]))\r\n if len(good_right_inds) > minpix:\r\n rightx_current = np.int(np.mean(nonzerox[good_right_inds]))\r\n if self.debug:\r\n cv_rgb = cv2.cvtColor(out_img.astype(np.uint8), cv2.COLOR_BGR2RGB)\r\n plt.imshow(cv_rgb)\r\n #cv2.imshow('Sliding window computation',out_img)\r\n # Concatenate the arrays of indices\r\n left_lane_inds = np.concatenate(left_lane_inds)\r\n right_lane_inds = np.concatenate(right_lane_inds)\r\n if self.debug:\r\n self.fit_dict['left_lane_inds'] = left_lane_inds\r\n self.fit_dict['right_lane_inds'] = right_lane_inds\r\n\r\n # Extract left and right line pixel positions\r\n leftx, lefty = nonzerox[left_lane_inds], nonzeroy[left_lane_inds]\r\n rightx, righty = nonzerox[right_lane_inds], nonzeroy[right_lane_inds]\r\n return leftx, lefty, rightx, righty","def cleanUpRigPose(self):\n\n # show the proxy geo\n cmds.select(self.name + \"_mover_grp\", hi=True)\n allNodes = cmds.ls(sl=True)\n for node in allNodes:\n if node.find(\"_proxy_geo\") != -1:\n if cmds.nodeType(node) == \"mesh\":\n parent = cmds.listRelatives(node, parent=True)[0]\n cmds.lockNode(parent, lock=False)\n cmds.setAttr(parent + \".v\", lock=False)\n cmds.setAttr(parent + \".v\", 1)\n cmds.lockNode(parent, lock=True)\n\n # unlock mover group for this module and make invisible\n cmds.lockNode(self.name + \"_mover_grp\", lock=False)\n cmds.setAttr(self.name + \"_mover_grp.v\", lock=False)\n\n cmds.setAttr(self.name + \"_mover_grp.v\", 0)\n\n cmds.setAttr(self.name + \"_mover_grp.v\", lock=True)\n cmds.lockNode(self.name + \"_mover_grp\", lock=True)\n\n # get the joints created by this module and remove the constraints\n joints = self.returnCreatedJoints\n\n # create mover name\n networkNode = self.returnNetworkNode\n baseName = cmds.getAttr(networkNode + \".baseName\")\n\n for joint in joints:\n if cmds.objExists(joint + \"_mover_offset\"):\n cmds.select(joint)\n cmds.delete(constraints=True)\n\n else:\n jointBaseName = joint\n if self.name != baseName:\n nameData = self.name.split(baseName)\n\n if nameData[0] != \"\":\n jointBaseName = jointBaseName.partition(nameData[0])[2]\n if nameData[1] != \"\":\n jointBaseName = jointBaseName.partition(nameData[1])[0]\n\n if cmds.objExists(self.name + \"_\" + jointBaseName + \"_mover_offset\"):\n cmds.select(joint)\n cmds.delete(constraints=True)","def move_dart(self):\n global level\n if level == 0:\n self.rect.centerx+=self.delta\n if self.rect.centerx >= 1000: \n self.delta = -1\n elif self.rect.centerx < 500:\n self.delta = 1\n elif level == 1:\n self.rect.centery+=self.delta\n if self.rect.centery <= 150: \n self.delta = 2\n elif self.rect.centery > 650:\n self.delta = -2\n elif level == 2:\n self.rect.centerx+=self.delta #To make changes in both x and y direction\n self.rect.centery+=self.delta\n if self.rect.centerx < 100 or self.rect.centery <= 100: \n self.delta = random.randint(1,10) #adds random speeds to the motion\n elif self.rect.centerx >= 900 or self.rect.centery > 700:\n self.delta = -random.randint(1,10)","def update(self):\r\n # Desplaza el bloque un píxel hacia abajo. s\r\n if self.rect.left < 50 or self.rect.right > 600:\r\n self.speed[0] = -self.speed[0]\r\n if self.rect.top < 0 or self.rect.bottom > 200:\r\n self.speed[1] = -self.speed[1]\r\n self.rect.move_ip((self.speed[0], self.speed[1])) \r\n if self.rect.y > 500:\r\n self.rect.x = random.randrange(10,600) \r\n self.rect.y = random.randrange(-400,-200)\r\n self.rect.y += 5","def update_position(self):\n # clamp on upper and lower bounds\n new_pos = self.position[1] + self.velocity\n # TODO: proper centering on borders\n if new_pos >= (config['globals']['HEIGHT'] - int(config['globals']['PAD_HEIGHT'] / 2)\n or new_pos <= int(config['globals']['PAD_HEIGHT'] / 2)):\n pass\n else:\n self.position[1] = new_pos","def compute_refl(self, step, borders,obstacle):\n\n r = self.radius\n v = self.velocity\n x = self.position\n projx = step*abs(np.dot(v,np.array([1.,0.])))\n projy = step*abs(np.dot(v,np.array([0.,1.])))\n\n a = pygame.Rect(0,0,borders[3][0],borders[3][0])\n b = pygame.Rect(0,borders[0][1]+borders[0][3],borders[3][0],borders[3][1]+borders[3][3])\n c = pygame.Rect(borders[2][0]+borders[2][2],0,borders[3][0],borders[3][0])\n d = pygame.Rect(borders[3][0]+borders[3][2],borders[1][1]+borders[1][3],borders[3][0],borders[3][0])\n\n if(a.collidepoint(*self.position) or b.collidepoint(*self.position) or c.collidepoint(*self.position) or d.collidepoint(*self.position)):\n self.vafter *= 0\n self.delete = True\n\n\n\n\n else:\n if (abs(x[0])-r -borders[0][0]-borders[0][2] < projx ) or (abs(borders[1][0]- x[0])-r < projx):\n self.vafter[0] *= -1\n\n if abs(x[1])-r -(borders[2][1]+borders[2][3]) < projy or abs(borders[3][1]-x[1])-r < projy:\n self.vafter[1] *= -1.\n\n if obstacle != None:\n obs = pygame.Rect(*obstacle)\n if obs.collidepoint(x[0] + r,x[1]):\n self.vafter[0] = -20\n if obs.collidepoint(x[0] - r,x[1]):\n self.vafter[0] = 20\n if obs.collidepoint(x[0],x[1]- r):\n self.vafter[1] = 20\n if obs.collidepoint(x[0], x[1]+ r):\n self.vafter[1] = -20","def move_all_boids_to_new_positions(self):\r\n #print(\"move boids to new positions\")\r\n for boid in self.boids:\r\n closeBoids = self.get_neighbouring_boids(boid, self.boids)\r\n \r\n # apply the boid algorithm\r\n boid.moveCloser(closeBoids)\r\n boid.moveWith(closeBoids) \r\n boid.moveAway(closeBoids, self.minDistance)\r\n \r\n # check for border so the boid deosn't fly into oblivion or migrate\r\n # North out of season\r\n if boid.x < (self.border - (self.ballrect.width/2)) and boid.velocity_x < 0:\r\n boid.velocity_x = -boid.velocity_x * random.random()\r\n if boid.x > (self.width - (self.ballrect.width/2)) and boid.velocity_x > 0:\r\n boid.velocity_x = -boid.velocity_x * random.random()\r\n if boid.y < (self.border - (self.ballrect.height/2)) and boid.velocity_y < 0:\r\n boid.velocity_y = -boid.velocity_y * random.random()\r\n if boid.y > (self.height - (self.border + (self.ballrect.height/2))) and boid.velocity_y > 0:\r\n boid.velocity_y = -boid.velocity_y * random.random()\r\n \r\n # velocity and position tweaked, let's move!\r\n boid.move(self.maxVelocity)","def draw_world(est_pose, particles, world):\r\n\r\n # Fix the origin of the coordinate system\r\n offsetX = 100\r\n offsetY = 250\r\n\r\n # Constant needed for transforming from world coordinates to screen coordinates (flip the y-axis)\r\n ymax = world.shape[0]\r\n\r\n world[:] = CWHITE # Clear background to white\r\n\r\n # Find largest weight\r\n max_weight = 0\r\n for particle in particles:\r\n max_weight = max(max_weight, particle.getWeight())\r\n\r\n # Draw particles\r\n for particle in particles:\r\n x = int(particle.getX()) + offsetX\r\n y = ymax - (int(particle.getY()) + offsetY)\r\n colour = jet(particle.getWeight() / max_weight)\r\n cv2.circle(world, (x, y), 2, colour, 2)\r\n b = (int(particle.getX() + 15.0 * np.cos(particle.getTheta())) + offsetX,\r\n ymax - (int(particle.getY() - 15.0 * np.sin(particle.getTheta())) + offsetY))\r\n cv2.line(world, (x, y), b, colour, 2)\r\n\r\n # Draw landmarks\r\n lm0 = (int(landmarks[0][0] + offsetX),\r\n int(ymax - (landmarks[0][1] + offsetY)))\r\n lm1 = (int(landmarks[1][0] + offsetX),\r\n int(ymax - (landmarks[1][1] + offsetY)))\r\n lm2 = (int(landmarks[2][0] + offsetX),\r\n int(ymax - (landmarks[2][1] + offsetY)))\r\n lm3 = (int(landmarks[3][0] + offsetX),\r\n int(ymax - (landmarks[3][1] + offsetY)))\r\n \r\n cv2.circle(world, lm0, 5, CRED, 2)\r\n cv2.circle(world, lm1, 5, CGREEN, 2)\r\n cv2.circle(world, lm2, 5, CBLUE, 2)\r\n cv2.circle(world, lm3, 5, CYELLOW, 2)\r\n cv2.putText(world, 'LM 1',lm0, cv2.FONT_HERSHEY_SIMPLEX, 1, 255)\r\n cv2.putText(world, 'LM 2',lm1, cv2.FONT_HERSHEY_SIMPLEX, 1, 255)\r\n cv2.putText(world, 'LM 3',lm2, cv2.FONT_HERSHEY_SIMPLEX, 1, 255)\r\n cv2.putText(world, 'LM 4',lm3, cv2.FONT_HERSHEY_SIMPLEX, 1, 255)\r\n\r\n\r\n\r\n\r\n # Draw estimated robot pose\r\n a = (int(est_pose.getX()) + offsetX, ymax - (int(est_pose.getY()) + offsetY))\r\n b = (int(est_pose.getX() + 15.0 * np.cos(est_pose.getTheta())) + offsetX,\r\n ymax - (int(est_pose.getY() - 15.0 * np.sin(est_pose.getTheta())) + offsetY))\r\n cv2.circle(world, a, 5, CMAGENTA, 2)\r\n cv2.line(world, a, b, CMAGENTA, 2)","def rotateRect(rectList, breakingBrick, itemsList, enemiesList, bullets, gunsList, points):\n X, Y, ENMYVX, ENMYVY, ENMYIDLE, ENMYINFLOOR = 0, 1, 4, 5, 6, 7\n GUNSTATE, GUNCOUNT, GUNTYPE = 4, 5, 6\n # Deleting any offscreen Rects\n for index in range(len(breakingBrick) - 1, -1, -1): # Going through all of the brick debris and deleting them once they exit below the screen\n if breakingBrick[index][1] > 600:\n del breakingBrick[index]\n for list in range(len(itemsList)): # Going through all of the items and deleting them once they scroll off the screen\n for item in range(len(itemsList[list]) - 1, -1, -1):\n if itemsList[list][item][0] < -300 or itemsList[list][item][1] > 650:\n del itemsList[list][item]\n for list in range(len(rectList)): # Going through all of the rects and deleting them once they scroll off the screen\n for rect in range(len(rectList[list]) - 1, -1, -1):\n if rectList[list][rect][0] < -700:\n del rectList[list][rect]\n for list in range(len(enemiesList)): # Going through all of the enemies and deleting them once they scroll off the screen\n for rect in range(len(enemiesList[list]) - 1, -1, -1):\n if enemiesList[list][rect][0] < -300 or enemiesList[list][rect][1] > 650:\n del enemiesList[list][rect]\n for point in range(len(points) - 1, -1, -1): # Going through all of the points indicators and deleting them once the counter reaches zero\n if points[point][2] == 0:\n del points[point]\n # Activating and deactivating all enemies\n for list in range(len(enemiesList)): # Going through all of the enemies\n for enemy in range(len(enemiesList[list]) - 1, -1, -1):\n if enemiesList[list] == goombas or enemiesList[list] == spinys: # If they are goombas or spinys\n # Activating goombas and spinys if they get close to the screen\n if enemiesList[list][enemy][ENMYIDLE] == 0 and enemiesList[list][enemy][X] < 800:\n enemiesList[list][enemy][ENMYIDLE] = 1\n # Deleting them if they are crushed by mario and the death counter reaches zero\n elif enemiesList[list][enemy][ENMYIDLE] == 2 and enemiesList[list][enemy][ENMYINFLOOR] == 0:\n points.append([enemiesList[list][enemy][0], enemiesList[list][enemy][1], 40, 100])\n del enemiesList[list][enemy]\n elif enemiesList[list] == bullets: # If they are bullets\n # Deleting bullets if they are too far off screen\n if enemiesList[list][enemy][0] < -1600 or enemiesList[list][enemy][0] > 1600:\n del enemiesList[list][enemy]\n for gun in range(len(gunsList) - 1, -1, -1): # Going through all of the guns\n # Activating guns if they get close and deleting them if they get too far back\n if gunsList[gun][0] < 1600:\n gunsList[gun][GUNSTATE] = 1\n if gunsList[gun][0] < -1600:\n del gunsList[gun]","def grasp_planning_wf(palm_pose_l_world, palm_pose_r_world,\n transformation, N=200, init=True):\n primitive_name = 'grasping'\n # 0. get initial palm poses in world frame\n palm_poses_initial_world = [palm_pose_l_world, palm_pose_r_world]\n\n grasp_width = planning_helper.grasp_width_from_palm_poses(\n palm_pose_l_world, palm_pose_r_world)\n\n # 1. get lifted palm poses in world frame\n palm_poses_lifted_world = []\n for pose in palm_poses_initial_world:\n lifted_pose = copy.deepcopy(pose)\n lifted_pose.pose.position.z += 0.05\n palm_poses_lifted_world.append(lifted_pose)\n\n # 2. get final configuration\n palm_poses_final_world = []\n for pose in palm_poses_initial_world:\n final_pose = util.transform_pose(\n pose_source=pose,\n pose_transform=transformation)\n final_pose.pose.position.z += 0.0025\n palm_poses_final_world.append(final_pose)\n\n # 3. get rotated + lifted palm pose in world frame\n palm_poses_rotated_world = []\n for pose in palm_poses_final_world:\n rotated_pose = copy.deepcopy(pose)\n rotated_pose.pose.position.z += 0.05\n palm_poses_rotated_world.append(rotated_pose)\n\n # 3. generate pose plans\n # 3.1. initialize plan\n initial_plan = planning_helper.initialize_plan_wf(\n palm_poses_initial=palm_poses_initial_world,\n transformation=transformation,\n primitive=primitive_name,\n plan_name='initial_config')\n\n # 3.2. lift the object\n lift_plan = planning_helper.move_cart_synchro_wf(\n palm_poses_final=palm_poses_lifted_world,\n grasp_width=grasp_width,\n plan_previous=initial_plan,\n primitive=primitive_name,\n plan_name='lift_object',\n N=10)\n\n # 3.3. rotate the object\n rotate_plan = planning_helper.move_cart_synchro_wf(\n palm_poses_final=palm_poses_rotated_world,\n grasp_width=grasp_width,\n plan_previous=lift_plan,\n primitive=primitive_name,\n plan_name='rotate_object_final',\n N=N/2,\n is_replan=True)\n\n # 3.4. place the object\n place_plan = planning_helper.move_cart_synchro_wf(\n palm_poses_final=palm_poses_final_world,\n grasp_width=grasp_width,\n plan_previous=rotate_plan,\n primitive=primitive_name,\n plan_name='place_object',\n N=20)\n return [lift_plan] + [rotate_plan] + [place_plan]","def mover_bm_abajo(self):\n self.nueva_posicion_posible_parte_superior = self.mapa.consultar_casilla_por_movimiento([self.casilla[0],\n self.casilla[1] + 1],\n [self.vertice_3[0], self.vertice_3[1] + self.velocidad],\n [self.vertice_1[0], self.vertice_1[1]+ 5])\n self.nueva_posicion_posible_parte_inferior = self.mapa.consultar_casilla_por_movimiento([self.casilla[0] + 1,\n self.casilla[1] + 1],\n [self.vertice_4[0],self.vertice_4[1] + self.velocidad],\n self.vertice_1)\n if self.nueva_posicion_posible_parte_superior[0] != 1 and self.nueva_posicion_posible_parte_inferior[0] != 1:\n self.y += self.velocidad * (self.y <= 655)\n self.posicion = [self.posicion[0],self.y]\n self.casilla = [self.casilla[0], self.casilla[1] + self.nueva_posicion_posible_parte_superior[1]]\n self.redefinir_vertices()","def _align_toplevel_grid(self):\n\n # align origin with nearest multple of 128\n self.mins[0] -= self.mins[0] % 128\n self.mins[1] -= self.mins[1] % 128\n\n width = self.maxs[0] - self.mins[0]\n height = self.maxs[1] - self.mins[1]\n greatest_dim = max(width, height)\n nearest_pow_two = int(2 ** np.ceil(np.log2(greatest_dim)))\n width_adjustment = (nearest_pow_two - width)\n height_adjustment = (nearest_pow_two - height)\n\n self.maxs[0] += width_adjustment\n self.maxs[1] += height_adjustment","def moveSpecialOb(self):\n\t\tfor obJ in self.special:\n\t\t\tobJ.moveStep()","def pad(self):\n if self._mg_problem.boundaries[0] == 'periodic':\n # left side\n self.left[:] = self.mid[-self.borders[0]:]\n # right side\n self.right[:] = self.mid[:self.borders[1]]\n elif self._mg_problem.boundaries[0] == 'dirichlet':\n\n # left from border\n l_f_b = self.space_tensor[0:self.borders[0]]\n # right_from_border\n r_f_b = self.space_tensor[-self.borders[1]:]\n # left side\n self.left[:] = self.fl(l_f_b)\n # right side\n self.right[:] = self.fr(r_f_b)","def drawmaze(self):\n win=GraphWin(\"Perfect Maze\",600,600) \n win.setBackground(\"White\")\n scale=600/self.N #Used to generalize the size difference for the input of larger numbers. The background resolution/ grid size, N\n\n x1=scale\n y1=0\n x2=scale\n y2=scale\n\n ##VERTICAL LINES ####\n for i in range(self.N,0,-1):\n for j in range(1,self.N):\n if self.East[j][i]: #If East is true, draw a line.\n \n line=Line(Point(x1,y1),Point(x2,y2)) #lines | |\n line.setFill(\"red\")\n line.draw(win)\n x1+=scale #Increment causes |->|\n x2+=scale #Increment causes |->|\n y1+=scale #Used to draw two more\n y2+=scale #of the same spaced lines further down.\n x1=scale #Reset\n x2=scale #Reset\n\n\n ##HORIZONTAL LINES##\n x1=0\n y1=scale\n x2=scale\n y2=scale\n\n\n for i in range(self.N,1,-1):\n for j in range(1,self.N+1):\n if self.South[j][i]: #If South is true, draw a line.\n \n line=Line(Point(x1,y1),Point(x2,y2))\n line.setFill(\"red\")\n line.draw(win)\n x1+=scale\n x2+=scale\n y1+=scale\n y2+=scale\n x1=0\n x2=scale\n\n const=scale//5 #Very useful const which helps in placing circles on grid.\n x=scale//2\n y=600-scale//2\n #radius=(scale-(4*scale//self.N))/2\n radius=scale//2-(const)\n start=Point(x,y) #START POINT HERE \n circ=Circle(start,radius)\n circ.setFill(\"Red\")\n label=Text(start,\"Start\")\n label.setFill(\"Black\")\n circ.draw(win)\n label.draw(win)\n #print(self.CurrentCell)\n #Using the current cell from the finished algorithm(last place visited), a circle can be placed at that point.\n endpointx=(self.CurrentCell[0]-1)*scale +scale//2 ####MAKING END POINT X\n endpointy=600-(self.CurrentCell[1]-1)*scale-scale//2 ####MAKING END POINT Y\n endpoint=Point(endpointx,endpointy)\n circ2=Circle(endpoint,radius)\n circ2.setFill(\"White\")\n label2=Text(endpoint,\"End\")\n circ2.draw(win)\n label2.draw(win)\n \n ###############CREATE KEY########################\n \n \n keypointx=(self.MazeKey[0]-1)*scale +scale//2 ####MAKING END POINT X\n keypointy=600-(self.MazeKey[1]-1)*scale-scale//2 ####MAKING END POINT Y\n keypoint=Point(keypointx,keypointy)\n circ3=Circle(keypoint,radius)\n circ3.setFill(\"Blue\")\n label3=Text(keypoint,\"Key\")\n circ3.draw(win)\n label3.draw(win)\n pathcol=\"Yellow\"\n##\n\n \n for i in range(1,len(self.EntirePath)): \n pathpointx=(self.EntirePath[i][0]-1)*scale +scale//2 ####MAKING END POINT X\n pathpointy=600-(self.EntirePath[i][1]-1)*scale-scale//2 ####MAKING END POINT Y\n pathpoint=Point(pathpointx,pathpointy)\n drawpath=Circle(pathpoint,radius)\n drawpath.setFill(pathcol)\n if self.EntirePath[i]==self.KeyPath[-1]:\n pathcol=\"Violet\"\n label4=Text(keypoint,\"Key\")\n label4.draw(win) \n drawpath.draw(win)\n drawpath.setWidth(1)\n sleep(0.1)\n \n #drawpath.draw(win)\n \n label5=Text(endpoint,\"Maze Solved \")\n label5.draw(win)\n circ4=Circle(start,radius)\n circ4.setFill(\"Red\")\n circ4.draw(win) \n label6=Text(start,\"Start \")\n label6.draw(win)","def move(self):\r\n if self.d == 'NORTH' and (self.y + 1) <= table_max_y:\r\n self.y += 1\r\n elif self.d == 'EAST' and (self.x + 1) <= table_max_x:\r\n self.x += 1\r\n elif self.d == 'SOUTH' and (self.y - 1) >= 0:\r\n self.y -= 1\r\n elif self.d == 'WEST' and (self.x - 1) >= 0:\r\n self.x -= 1\r\n else:\r\n print(\"Edge of Table Reached!\")","def modify_box_coordinates(self, image, poles_detected):\n for window, poles in poles_detected.items():\n # Let's consider all poles detected on an image and modify their coordinates.\n # If only one pole's been detected, just widen the box 60% both sides\n if len(poles) == 1:\n new_left_boundary = int(poles[0].BB_left * 0.4)\n new_right_boundary = int(poles[0].BB_right * 1.6) if int(poles[0].BB_right * 1.6) <\\\n image.shape[1] else (image.shape[1] - 2)\n # Move upper border way up, often when a pole is close up many components do not get\n # included in the box, as a result they do not get found\n new_top_boundary = int(poles[0].BB_top * 0.1)\n new_bot_boundary = int(poles[0].BB_bottom * 1.1) if int(poles[0].BB_bottom * 1.1) <\\\n image.shape[0] else (image.shape[0] - 2)\n\n poles[0].update_object_coordinates(left=new_left_boundary,\n top=new_top_boundary,\n right=new_right_boundary,\n bottom=new_bot_boundary)\n else:\n for pole in poles:\n # If we've got 1+ poles on one frame or image, hence the shot was likely taken from\n # further distance.\n\n # TO DO: Overlapping check here. If BBs overlap and a component happens to be in between,\n # it will be detected twice\n\n new_left_boundary = int(pole.BB_left * 0.9)\n new_right_boundary = int(pole.BB_right * 1.1) if int(pole.BB_right * 1.1) < \\\n image.shape[1] else (image.shape[1] - 2)\n new_top_boundary = int(pole.BB_top * 0.5)\n new_bot_boundary = int(pole.BB_bottom * 1.1) if int(pole.BB_bottom * 1.1) < \\\n image.shape[0] else (image.shape[0] - 2)\n\n pole.update_object_coordinates(left=new_left_boundary,\n top=new_top_boundary,\n right=new_right_boundary,\n bottom=new_bot_boundary)","def movePole(mario, marioStats, marioScore, frame, flagInfo, unisprite, isDone, forceTime):\n PTS, COIN, LIVES = 0, 1, 2\n X, Y, VX, VY, DIR, STATE = 0, 1, 2, 3, 4, 5\n ONGROUND, JUMPFRAMES, INGROUND, ISCROUCH, ONPLATFORM, ISFALLING, ISANIMATING, INVULFRAMES = 0, 1, 2, 3, 4, 5, 6, 7\n # Declaring flag pole Rects\n poleRect = Rect(flagInfo[0][0], flagInfo[0][1], flagInfo[0][2], flagInfo[0][3])\n flagRect = Rect(flagInfo[1][0], flagInfo[1][1], flagInfo[1][2], flagInfo[1][3])\n offset = 0 # Offset for height\n endPoint = 650 # Variable for the X coordinate of the castle door\n if levelNum == 5: # If the level is 5, change the castle door position\n endPoint = 690\n if mario[STATE] == 1: # If Mario is big, change the offset\n offset = 42\n if flagRect.y < 451: # If the flag Y position is not past 451, bring it lower\n flagInfo[1][1] += 4\n if mario[Y] < 451 - offset: # If Mario is not att the bottom the pole\n mario[Y] += 4 # Bring him lower\n frame[0], frame[1] = 3, (unisprite * 0.8 % 2 + mario[STATE] * 2) # Rotate is sprite\n if mario[Y] >= 451 - offset and flagRect.y >= 451 and frame[2] < 20: # If both Mario and the flag are at the bottom, and the animation counter hasn't reached 20\n mario[X] = poleRect.x + 16 # Put Mario on the other side of the pole (still holding)\n frame[0], frame[1] = 3, 4 + mario[STATE] # Keep his sprite of the grabbing pole sprite\n frame[2] += 1 # Add to the animation counter\n elif mario[Y] >= 451 - offset and flagRect.y >= 451 and frame[2] == 20: # If both Mario and the flag are at the bottom, and the animation counter is at 20\n mario[X] = poleRect.right # Put Mario to the left of the pole\n mario[Y] = 496 - offset # Put Mario on the ground, according to Mario's state\n frame[2] += 1 # Add to the frame counter\n if levelNum != 5: # If the level is 5, play the game done sound\n playSound(doneSound, \"music\")\n else: # If it's any other level, play the level done sound\n playSound(doneworldSound, \"music\")\n elif mario[Y] >= 451 - offset and flagRect.y >= 451: # If both the above are done\n mario[VX] = 5 # Make Mario's speed 5\n mario[VY] = 0 # Make his VY 0\n mario[X] += 3.5 # Keep moving Mario right\n marioStats[ONGROUND] = True\n moveSprites(mario,marioStats,frame) # Use the moveSprites function to rotate sprites\n if mario[X] > endPoint and mario[X] < 800: # If Mario reaches the castle and hasn't been moved yet\n mario[X] = 800 # Move Mario off screen\n playSound(timepointsSound, \"effect\") # Play the time to points conversion sound\n if mario[X] > 800 and forceTime != 0: # If Mario has been moved off screen (meaning the time conversion has started)\n forceTime -= 1 # Remove a second from the forced time\n marioScore[PTS] += 100 # Add 100 to Marios points for each second removed\n if forceTime == 0: # If the force time has reached zero (meaning the time conversion is done)\n mixer.Channel(1).stop() # Stop the conversion sound\n if not mixer.Channel(0).get_busy(): # If the end level sound is done, go to the next level\n isDone = True\n return [isDone, forceTime] # Return the isDone and forced time values for the game function to handle","def swipeBase (self) :\n grid = self.grid\n\n #we start by putting every tile up\n for columnNbr in range(4) :\n nbrZeros = 4 - np.count_nonzero(grid[:,columnNbr])\n\n for lineNbr in range(4) :\n counter = 0\n while (grid[lineNbr, columnNbr] == 0) and (counter < 4):\n counter += 1\n if np.count_nonzero(grid[lineNbr:4, columnNbr]) != 0 :\n for remainingLine in range (lineNbr, 3) :\n grid[remainingLine, columnNbr] = grid[remainingLine+1, columnNbr]\n grid[3, columnNbr] = 0\n\n #now we do the additions\n for lineNbr in range(3) :\n if grid[lineNbr, columnNbr] == grid[lineNbr+1, columnNbr] :\n grid[lineNbr, columnNbr] *= 2\n for remainingLine in range (lineNbr+1, 3) :\n grid[remainingLine, columnNbr] = grid[remainingLine+1, columnNbr]\n grid[3, columnNbr] = 0\n\n return (grid)","def detectWallCollision(self): \n if self.posn_x > cw - self.ball_width: # Collision with right-hand container wall. \n self.velocity_x = -self.velocity_x * self.coef_restitution # reverse direction. \n self.posn_x = cw - self.ball_width * 1.1 # anti-stick to the wall \n if self.posn_x < 1: # Collision with left-hand wall. \n self.velocity_x = -self.velocity_x * self.coef_restitution \n self.posn_x = 2 # anti-stick to the wall \n if self.posn_y < self.ball_height: # Collision with ceiling. \n self.velocity_y = -self.velocity_y * self.coef_restitution \n self.posn_y = self.ball_height * 1.1 # ceiling collision anti-stick \n if self.posn_y > ch - self.ball_height * 1.1 : # Floor collision. \n self.velocity_y = - self.velocity_y * self.coef_restitution \n self.posn_y = ch - self.ball_height * 1.1 # anti-stick. Prevents out-of-bounds ball loss (stickiness) ","def adjust_mario_for_y_ground_pipe_collisions(self, collider):\n if self.mario.rect.bottom < collider.rect.bottom:\n self.mario.y_vel = 0\n self.mario.rect.bottom = collider.rect.top\n elif self.mario.rect.top > collider.rect.top:\n self.mario.y_vel = 7\n self.mario.rect.top = collider.rect.bottom","def move (self):\n\t\tself.x += self.direction[0]\n\t\tself.y += self.direction[1]\n\t\tself.row = (self.y - 15) / 30\n\t\tself.col = (self.x - 15) / 30\n\t\tself.rowcol = (self.row,self.col)\n\t\tself.draw()","def _edit_border_tiles(self, vmf: VMF, seg_min: Vec, seg_max: Vec, border: bool, blacken: bool) -> None:\n up = abs(self.up_axis)\n forward = (seg_max - seg_min).norm()\n norm_dir = self.normal().axis()\n\n tiledefs_up: list[tiling.TileDef] = []\n tiledefs_dn: list[tiling.TileDef] = []\n\n overlay_len = int((seg_max - seg_min).mag())\n\n # We need to snap the axis normal_axis to the grid, since it could\n # be forward or back.\n min_pos = seg_min.copy()\n min_pos[norm_dir] = min_pos[norm_dir] // 128 * 128 + 64\n\n u_ax, v_ax = Vec.INV_AXIS[up.axis()]\n side_dir = Vec.dot(abs(Vec.cross(up, forward)), seg_min - min_pos)\n side_ind = round((side_dir + 48) / 32, 2) # 0/1/2/3 for the center of tiles.\n # 4.5 -> [4, 5] and 4 -> [4].\n pos_iter = sorted({round(side_ind - 0.25), round(side_ind + 0.25)})\n if u_ax == forward.axis():\n uv_pos = [\n (u, v)\n for u in range(4)\n for v in pos_iter\n ]\n elif v_ax == forward.axis():\n uv_pos = [\n (u, v)\n for u in pos_iter\n for v in range(4)\n ]\n else: # Should be impossible?\n uv_pos = []\n\n for offset in range(64, overlay_len, 128):\n # Each position on top or bottom, inset 64 from each end.\n # First check if the tiles themselves are present, then check if any of the\n # subtiles are present - blackening on the way if required.\n pos = min_pos + offset * forward\n tile_cat = []\n try:\n top_tile = tiling.TILES[\n (pos + 128 * up).as_tuple(),\n (-up).as_tuple()\n ]\n except KeyError:\n pass\n else:\n tile_cat.append((tiledefs_up, top_tile))\n try:\n btm_tile = tiling.TILES[\n (pos - 128 * up).as_tuple(),\n up.as_tuple()\n ]\n except KeyError:\n pass\n else:\n tile_cat.append((tiledefs_dn, btm_tile))\n for tiledefs, tile in tile_cat:\n found = False\n for u, v in uv_pos:\n subtile = tile[u, v]\n if subtile.is_tile:\n found = True\n if blacken:\n tile[u, v] = subtile.as_black\n if found:\n tiledefs.append(tile)\n\n if not border or (not tiledefs_up and not tiledefs_dn):\n return\n\n overlay_thickness = options.get(int, 'fizz_border_thickness')\n overlay_repeat = options.get(int, 'fizz_border_repeat')\n flip_uv = options.get(bool, 'fizz_border_vertical')\n\n if flip_uv:\n u_rep = 1.0\n v_rep = overlay_len / overlay_repeat\n else:\n u_rep = overlay_len / overlay_repeat\n v_rep = 1.0\n\n cent_pos = (seg_min + seg_max) / 2\n\n if tiledefs_up:\n over = srctools.vmf.make_overlay(\n vmf,\n normal=-up,\n origin=cent_pos + 64 * up,\n uax=forward * overlay_len,\n vax=Vec.cross(up, forward) * overlay_thickness,\n material=texturing.SPECIAL.get(cent_pos + 64 * up, 'fizz_border'),\n surfaces=[],\n u_repeat=u_rep,\n v_repeat=v_rep,\n swap=flip_uv,\n )\n for tile in tiledefs_up:\n tile.bind_overlay(over)\n\n if tiledefs_dn:\n over = srctools.vmf.make_overlay(\n vmf,\n normal=up,\n origin=cent_pos - 64 * up,\n uax=forward * overlay_len,\n vax=Vec.cross(-up, forward) * overlay_thickness,\n material=texturing.SPECIAL.get(cent_pos - 64 * up, 'fizz_border'),\n surfaces=[],\n u_repeat=u_rep,\n v_repeat=v_rep,\n swap=flip_uv,\n )\n for tile in tiledefs_dn:\n tile.bind_overlay(over)","def make_move(self, direction):\r\n\t\tif direction == 0:\r\n\t\t\tself.board[self.x][self.y], self.board[self.x-1][self.y] = self.board[self.x-1][self.y], self.board[self.x][self.y]\r\n\t\t\tself.x -= 1\r\n\r\n\t\telif direction == 1:\r\n\t\t\tself.board[self.x][self.y], self.board[self.x][self.y+1] = self.board[self.x][self.y+1], self.board[self.x][self.y]\r\n\t\t\tself.y += 1\r\n\r\n\t\telif direction == 2:\r\n\t\t\tself.board[self.x][self.y], self.board[self.x+1][self.y] = self.board[self.x+1][self.y], self.board[self.x][self.y]\r\n\t\t\tself.x += 1\r\n\r\n\t\telif direction == 3:\r\n\t\t\tself.board[self.x][self.y], self.board[self.x][self.y-1] = self.board[self.x][self.y-1], self.board[self.x][self.y]\r\n\t\t\tself.y -= 1","def create_grid(self):\n\n # initial point of the path\n self.p0 = np.array([self.start_x, self.start_y])\n self.pf = np.array([self.end_x, self.end_y]) # final point of the path\n\n self.l1 = np.linalg.norm(np.subtract(self.pf, self.p0))\n self.l2 = 0.2 * self.l1\n\n # we define the 2 unit vectors self.d1 and self.d2 in which directions we are moving along\n # then we apply to them the size of the desired displacement\n self.d1 = np.subtract(self.pf, self.p0) / \\\n (np.linalg.norm(np.subtract(self.pf, self.p0)))\n\n self.d2 = np.array([-self.d1[1], self.d1[0]])\n self.d2 = self.d2/(np.linalg.norm(self.d2))\n\n # we create our grid moving with self.d1 and self.d2\n # each point of the grid has the following properties:\n # position, distance to self.d1, distance to self.pf, velocity\n n_displacements_2 = 0\n self.lines_list = []\n\n # variables for making easier the plotting afterwards\n self.x_list_grid = []\n self.y_list_grid = []\n time_n = 1\n\n while True:\n current_point = np.subtract(\n self.p0, self.d2*(n_displacements_2*self.displacement))\n current_length_2 = np.linalg.norm(\n np.subtract(current_point, self.p0))\n if current_length_2 > self.l2/2:\n if time_n == 2:\n break\n else:\n time_n += 1\n self.lines_list = list(reversed(self.lines_list))\n self.d2 = -1 * self.d2\n n_displacements_2 = 1\n current_point = np.subtract(\n self.p0, self.d2*(n_displacements_2*self.displacement))\n\n line_points = []\n self.x_list_grid.append(current_point[0])\n self.y_list_grid.append(current_point[1])\n\n # TODO: add fish real prediction\n line_points.append({\n \"position\": current_point.tolist(),\n \"distance_to_l1\": n_displacements_2*self.displacement,\n \"distance_to_pf\": np.linalg.norm(np.subtract(self.pf, current_point)),\n \"fish\": random.random()\n })\n\n initial_point_1 = current_point\n while True:\n current_point = np.sum(\n [current_point, self.d1 * self.displacement], axis=0)\n current_length_1 = np.linalg.norm(\n np.subtract(current_point, initial_point_1))\n if current_length_1 >= self.l1:\n current_point = self.pf - self.d2*n_displacements_2*self.displacement\n self.x_list_grid.append(current_point[0])\n self.y_list_grid.append(current_point[1])\n # TODO: add fish real prediction\n line_points.append({\n \"position\": current_point.tolist(),\n \"distance_to_l1\": n_displacements_2*self.displacement,\n \"distance_to_pf\": np.linalg.norm(np.subtract(self.pf, current_point)),\n \"fish\": random.random()\n })\n break\n\n self.x_list_grid.append(current_point[0])\n self.y_list_grid.append(current_point[1])\n\n # TODO: add fish real prediction\n line_points.append({\n \"position\": current_point.tolist(),\n \"distance_to_l1\": n_displacements_2*self.displacement,\n \"distance_to_pf\": np.linalg.norm(np.subtract(self.pf, current_point)),\n \"fish\": random.random()\n })\n\n self.lines_list.append(line_points)\n n_displacements_2 += 1","def expanded_boundaries(self):\n width = self._points[0][3][0] - self._points[0][1][0]\n height = self._points[0][3][1] - self._points[0][1][1]\n factor = np.multiply((width, height), Window.BORDER)\n return (\n np.subtract(self._points[0][1], factor),\n np.add(self._points[0][3], factor))","def update(self):\n super().update()\n if self.center_y > TOP_LIMIT:\n self.center_y = BOTTOM_LIMIT\n if self.center_y < BOTTOM_LIMIT:\n self.center_y = TOP_LIMIT\n\n if self.center_x < 250:\n self.change_x = (0.2) * OBJECTS_SPEED\n elif self.center_x > SCREEN_WIDTH - 250:\n self.change_x = (-0.2) * OBJECTS_SPEED","def place_targets():\n\n \n coords = []\n while len(coords)<self.N_targets:\n x = np.random.randint(self.BORDER_MARGIN,self.map_dimensions[1]+1-self.BORDER_MARGIN,size=1)[0]\n y = np.random.randint(self.BORDER_MARGIN,self.map_dimensions[0]+1-self.BORDER_MARGIN,size=1)[0]\n p = (x,y)\n all_valid = True\n for rect in self.coordinates__obstacles:\n if not check_valid_placement(p,rect):\n all_valid = False\n break\n if all_valid:\n coords +=[p]\n self.coordinates__targets = coords","def move(self):\n \n self.rect.move_ip(0,self.speed) # Funcion para mover el enemigo especificando la velocidad xy\n \n if (self.rect.top > SCREEN_HEIGHT): # Condicion cuando llega a la parte inferior y no colisiono con el jugador\n del self.surf #Libera memoria\n del self.rect\n self.randomNumber = random.choice([70,64,32]) # Su tamaño se asigna nuevamente\n self.size = (self.randomNumber,self.randomNumber) #Se genera su tamaño como un cuadrado de lado aleatorio\n self.surf = pygame.Surface(self.size) #Se genera la superficie que aparecera la pantalla\n self.surf.fill(RED)\n self.rect = self.surf.get_rect(center = (random.randint(40,SCREEN_WIDTH-40),0))# me da info de las coordenadas de surf\n if(self.randomNumber == 32):\n self.surf = self.imagen\n elif(self.randomNumber ==64):\n self.surf = self.imagen2\n elif self.randomNumber ==70 :\n self.surf = self.imagen3","def moveStep(self):\n\t\tif self.pos[0] < self.boundsX[0] or \\\n\t\t\tself.pos[0] > (self.boundsX[1] - self.width):\n\t\t\t\tself.dir[0] *= -1\n\t\tif self.pos[1] < self.boundsY[0] or \\\n\t\t self.pos[1] > (self.boundsY[1] - self.height):\n\t\t\t\tself.dir[1] *= -1\n\t\t\t\n\t\tself.pos[0] += self.dir[0]*self.speed\n\t\tself.pos[1] += self.dir[1]*self.speed","def place_obstacles():\n #Randomly generate different sized rectangles\n #Soem may overlap, which gives more variety in shape of obstacles\n xvals = np.random.randint(0,self.map_dimensions[1],size=self.N_obstacles)\n yvals = np.random.randint(0,self.map_dimensions[0],size=self.N_obstacles)\n lower_left = zip(xvals,yvals)\n rects = []\n for LL in lower_left:\n x = LL[0]\n y = LL[1]\n wmax = self.map_dimensions[1] - x\n w = np.random.randint(0,wmax,size=1)[0]\n hmax = self.map_dimensions[0] - y\n h = np.random.randint(0,hmax,size=1)[0]\n rects += [(x,y,w,h)]\n self.coordinates__obstacles = rects","def _move(self, event):\n if self._current_tower.get_value() > self._coins:\n return\n\n #move the shadow tower to mouse position\n position = event.x, event.y\n self._current_tower.position = position\n\n legal, grid_path = self._game.attempt_placement(position)\n\n #find the best path and covert positions to pixel positions\n path = [self._game.grid.cell_to_pixel_centre(position)\n for position in grid_path.get_shortest()]\n\n #Task 1.2 (Tower placement): Draw the tower preview here\n self._view.draw_preview(self._current_tower, legal)\n self._view.draw_path(path)","def _poses_town02(self):\n def _simple_straight_forward():\n return [[64, 55], [54, 63], [51, 46], [45, 49], [29, 50], [61, 40]]\n\n def _simple_left_turn():\n return [[73, 62], [62, 7], [29, 43], [45, 79]]\n\n def _simple_right_turn():\n return [[78, 46], [44, 40], [18, 60], [60, 71]]\n\n return [_simple_straight_forward(),\n _simple_right_turn(),\n _simple_left_turn(),\n ]","def move(self, direction):\r\n direc = list(OFFSETS[direction])\r\n line = []\r\n dummy_board = self.board[:]\r\n if direction == 3:\r\n for i in range(self.height):\r\n self.board[i] = merge(self.board[i])\r\n self.compare(dummy_board)\r\n return self.board\r\n \r\n elif direction == 4:\r\n for i in range(self.height):\r\n line = self.board[i][::-1]\r\n self.board[i] = merge(line)\r\n self.board[i] = self.board[i][::-1]\r\n self.compare(dummy_board)\r\n return self.board\r\n \r\n \r\n elif direction == 1 or 2:\r\n dummy_board = str(self.board[:])\r\n if direction == 1:\r\n tile = [0,0]\r\n elif direction == 2:\r\n tile = [self.height - 1, 0]\r\n for i in range(self.width):\r\n tile2 = tile[:]\r\n while len(line) < self.height:\r\n line.append(self.get_tile(*tile2))\r\n tile2 = [x+y for x,y in zip(direc, tile2)]\r\n line = merge(line)\r\n tile2 = tile[:]\r\n for i in range(self.height):\r\n self.set_tile(*(tile2+[line[0]]))\r\n line.remove(line[0])\r\n tile2 = [x+y for x,y in zip(direc, tile2)]\r\n tile = [x+y for x,y in zip(tile, [0,1])]\r\n if dummy_board != self.__str__():\r\n self.new_tile()\r\n return self.board","def movement(self):","def _bounce(self):\n right = self.surface.get_width() - self.size\n left = self.size\n top = self.size\n bottom = self.surface.get_height() - self.size\n if self.pos.x > right: # right border\n self.pos.x = right\n self.direction = self.direction.elementwise() * pygame.Vector2(-1.0, 1.0)\n elif self.pos.x < left: # left border\n self.pos.x = left\n self.direction = self.direction.elementwise() * pygame.Vector2(-1.0, 1.0)\n if self.pos.y > bottom: # bottom border\n self.pos.y = bottom\n self.direction = self.direction.elementwise() * pygame.Vector2(1.0, -1.0)\n elif self.pos.y < top: # top border\n self.pos.y = top\n self.direction = self.direction.elementwise() * pygame.Vector2(1.0, -1.0)","def update_position(self, canvas):\n pts = []\n for P in self.get_points():\n if P[0] <= 0:\n if self.direction == \"SW\":\n self.direction = \"SE\"\n if self.direction == \"W\":\n self.direction = \"E\"\n if self.direction == \"NW\":\n self.direction = \"NE\"\n if P[0] >= canvas.width:\n if self.direction == \"SE\":\n self.direction = \"SW\"\n if self.direction == \"E\":\n self.direction = \"W\"\n if self.direction == \"NE\":\n self.direction = \"NW\"\n if P[1] <= 0:\n if self.direction == \"NW\":\n self.direction = \"SW\"\n if self.direction == \"N\":\n self.direction = \"S\"\n if self.direction == \"NE\":\n self.direction = \"SE\"\n if P[1] >= canvas.height:\n if self.direction == \"SW\":\n self.direction = \"NW\"\n if self.direction == \"S\":\n self.direction = \"N\"\n if self.direction == \"SE\":\n self.direction = \"NE\"\n for P in self.get_points():\n if self.direction == \"N\":\n pts.append((P[0],P[1]-1)) \n# P.y -= 1\n if self.direction == \"NE\":\n pts.append((P[0]+1,P[1]-1))\n# P.y -= 1\n# P.x += 1\n if self.direction == \"E\":\n pts.append((P[0]+1,P[1]))\n# P.x += 1\n if self.direction == \"SE\":\n pts.append((P[0]+1,P[1]+1))\n# P.x += 1\n# P.y += 1\n if self.direction == \"S\":\n pts.append((P[0],P[1]+1))\n# P.y += 1\n if self.direction == \"SW\":\n pts.append((P[0]-1,P[1]+1))\n# P.x -= 1\n# P.y += 1\n if self.direction == \"W\":\n pts.append((P[0]-1,P[1]))\n# P.x -= 1\n if self.direction == \"NW\":\n pts.append((P[0]-1,P[1]-1))\n# P.y -= 1\n# P.x -= 1 \n self.set_points(pts)"],"string":"[\n \"def adjust_mario_position(self):\\n self.last_x_position = self.mario.rect.right\\n self.mario.rect.x += round(self.mario.x_vel)\\n self.check_mario_x_collisions()\\n\\n if self.mario.in_transition_state == False:\\n self.mario.rect.y += round(self.mario.y_vel)\\n self.check_mario_y_collisions()\",\n \"def __init__(self, \\n nd = 2, \\n goal = np.array([1.0,1.0]),\\n state_bound = [[0,1],[0,1]],\\n nA = 4,\\n action_list = [[0,1],[0,-1],[1,0],[-1,0]],\\n<<<<<<< HEAD:archive-code/puddleworld.py\\n ngrid = [10.0,10.0],\\n maxStep = 40):\\n ngrid = [40, 40]\\n x_vec = np.linspace(0,1,ngrid[0])\\n y_vec = np.linspace(0,1,ngrid[1])\\n for x in x_vec:\\n for y in y_vec:\\n if ~self.inPuddle([x,y]):\\n puddle.append([x,y])\\n # puddle is a closed loop \\n outpuddlepts = np.asarray(puddle)\\n \\\"\\\"\\\"\\n\\n\\n # Horizontal wing of puddle consists of \\n # 1) rectangle area xch1<= x <=xc2 && ych1-radius <= y <=ych2+radius\\n # (xchi,ychi) is the center points (h ==> horizantal)\\n # x, y = state[0], state[1]\\n xch1, ych1 = 0.3, 0.7\\n xch2, ych2 = 0.65, ych1\\n radius = 0.1\\n\\n\\n #Vertical wing of puddle consists of \\n # 1) rectangle area xcv1-radius<= x <=xcv2+radius && ycv1 <= y <= ycv2\\n # where (xcvi,ycvi) is the center points (v ==> vertical)\\n xcv1 = 0.45; ycv1=0.4;\\n xcv2 = xcv1; ycv2 = 0.8;\\n\\n # % 2) two half-circle at end edges of rectangle\\n \\n # POINTS ON HORIZANTAL LINES OF PUDDLE BOUNDARY\\n for x in np.arange(xch1,xcv1-radius,self.meshsize[0]/2):\\n puddle.append([x,ych1-radius])\\n puddle.append([xcv1-radius,ych1-radius])\\n \\n for x in np.arange(xcv1+radius,xch2,self.meshsize[0]/2):\\n puddle.append([x,ych1-radius])\\n \\n for x in np.arange(xch1,xcv1-radius,self.meshsize[0]/2):\\n puddle.append([x,ych1+radius])\\n \\n puddle.append([xcv1-radius,ych1+radius])\\n\\n\\n for x in np.arange(xcv1+radius,xch2,self.meshsize[0]/2):\\n puddle.append([x,ych1+radius])\\n\\n # POINTS ON VERTICAL LINES OF PUDDLE BOUNDARY\\n for y in np.arange(ycv1,ych1-radius,self.meshsize[1]/2):\\n puddle.append([xcv1-radius,y])\\n \\n for y in np.arange(ycv1,ych1-radius,self.meshsize[1]/2):\\n puddle.append([xcv1+radius,y])\\n \\\"\\\"\\\"\\n for y in np.arrange():\\n puddle.append([])\\n \\n for y in np.arrange():\\n puddle.append([])\\n \\\"\\\"\\\"\\n\\n # HALF CIRCLES\\n ngridTheta = 10\\n thetaVec = np.linspace(0,pi,ngridTheta)\\n\\n for t in thetaVec:\\n puddle.append([xch1+radius*np.cos(pi/2+t),ych1+radius*np.sin(pi/2+t)])\\n\\n for t in thetaVec:\\n puddle.append([xch2+radius*np.cos(-pi/2+t),ych2+radius*np.sin(-pi/2+t)])\\n\\n for t in thetaVec:\\n puddle.append([xcv1+radius*np.cos(pi+t),ycv1+radius*np.sin(pi+t)])\\n\\n for t in thetaVec:\\n puddle.append([xcv2+radius*np.cos(t),ycv2+radius*np.sin(t)])\\n\\n \\n outpuddlepts = np.asarray(puddle)\\n return outpuddlepts\",\n \"def update(self):\\n self.center_x += self.change_x\\n self.center_y += self.change_y\\n\\n # boundary for the sides of the screen\\n if self.left < 0:\\n self.left = 0\\n if self.right > settings.WIDTH:\\n self.right = settings.WIDTH\\n\\n # boundary for the top and bottom of the screen\\n if self.bottom < 0:\\n self.bottom = 3\\n if self.top > settings.HEIGHT:\\n self.top = settings.HEIGHT\\n\\n # boundary of wall left up\\n if (self.right > 185 and self.left < 180 and self.top > 338 and\\n self.bottom < 464):\\n self.right = 184\\n if (self.left < 212 and self.left > 190 and self.bottom < 435 and\\n self.top > 338):\\n self.left = 212\\n if (self.right > 185 and self.left < 312 and self.bottom < 464 and\\n self.top > 460):\\n self.bottom = 464\\n if (self.top > 435 and self.top < 450 and self.left >= 212 and\\n self.left < 311):\\n self.top = 435\\n if (self.top > 336 and self.bottom < 350 and self.left < 211 and\\n self.right > 185):\\n self.top = 336\\n if (self.left < 312 and self.right > 290 and self.bottom < 464 and\\n self.top > 436):\\n self.left = 312\\n\\n # boundary of wall right up\\n if (self.right > 590 and self.left < 586 and self.top > 338 and\\n self.bottom < 464):\\n self.left = 586\\n if (self.right > 560 and self.right < 582 and self.bottom < 435 and\\n self.top > 338):\\n self.right = 560\\n if (self.right > 462 and self.left < 586 and self.bottom < 464 and\\n self.top > 460):\\n self.bottom = 464\\n if (self.top > 435 and self.top < 450 and self.right <= 560 and\\n self.right > 462):\\n self.top = 435\\n if (self.top > 336 and self.bottom < 350 and self.left < 586 and\\n self.right > 561):\\n self.top = 336\\n if (self.left < 440 and self.right > 462 and self.bottom < 464 and\\n self.top > 436):\\n self.right = 462\\n\\n # boundary of wall left down\\n if (self.right > 185 and self.left < 180 and self.top > 88 and\\n self.bottom < 213):\\n self.right = 184\\n if (self.left < 212 and self.right > 200 and self.top > 111 and\\n self.bottom < 213):\\n self.left = 212\\n if (self.right > 185 and self.left < 312 and self.top > 88 and self.top < 100):\\n self.top = 88\\n if (self.bottom < 111 and self.bottom > 100 and self.left >= 212 and\\n self.left < 311):\\n self.bottom = 112\\n if (self.top > 336 and self.bottom < 213 and self.left < 211 and\\n self.right > 185):\\n self.bottom = 213\\n if (self.left < 312 and self.right > 290 and self.top > 88 and\\n self.bottom < 111):\\n self.left = 312\\n\\n # boundary of wall lef right down\\n if (self.right > 590 and self.left < 586 and self.top > 88 and\\n self.bottom < 213):\\n self.left = 586\\n if (self.right > 560 and self.left < 582 and self.top > 111 and\\n self.bottom < 213):\\n self.right = 560\\n if (self.right > 462 and self.left < 586 and self.top > 88 and self.top < 100):\\n self.top = 88\\n if (self.bottom < 111 and self.bottom > 100 and self.right <= 560 and\\n self.right > 462):\\n self.bottom = 112\\n if (self.top > 336 and self.bottom < 213 and self.left < 586 and\\n self.right > 561):\\n self.bottom = 213\\n if (self.left < 440 and self.right > 462 and self.top > 88 and\\n self.bottom < 111):\\n self.right = 462\",\n \"def move(self, walls):\\n \\n # Move left/right\\n self.rect.x += self.change_x\\n \\n # Did this update cause us to hit a wall?\\n block_hit_list = pygame.sprite.spritecollide(self, walls, False)\\n for block in block_hit_list:\\n # If we are moving right, set our right side to the left side of\\n # the item we hit\\n if self.change_x > 0:\\n self.rect.right = block.rect.left\\n else:\\n # Otherwise if we are moving left, do the opposite.\\n self.rect.left = block.rect.right\\n \\n # Move up/down\\n self.rect.y += self.change_y\\n \\n # Check and see if we hit anything\\n block_hit_list = pygame.sprite.spritecollide(self, walls, False)\\n for block in block_hit_list:\\n \\n # Reset our position based on the top/bottom of the object.\\n if self.change_y > 0:\\n self.rect.bottom = block.rect.top\\n else:\\n self.rect.top = block.rect.bottom\",\n \"def check_borders(self):\\n # Go Homer!\\n # https://en.wikipedia.org/wiki/Torus#Flat_torus\\n if self._posn.x < 0:\\n self._posn.x += self._win_w\\n elif self._posn.x > self._win_w:\\n self._posn.x -= self._win_w\\n if self._posn.y < 0:\\n self._posn.y += self._win_h\\n elif self._posn.y > self._win_h:\\n self._posn.y -= self._win_h\",\n \"def grasp_planning(object, object_pose1_world, object_pose2_world,\\n palm_pose_l_object, palm_pose_r_object, N=200, init=True):\\n primitive_name = 'grasping'\\n # 0. get initial palm poses in world frame\\n palm_poses_initial_world = planning_helper.palm_poses_from_object(\\n object_pose=object_pose1_world,\\n palm_pose_l_object=palm_pose_l_object,\\n palm_pose_r_object=palm_pose_r_object)\\n\\n grasp_width = planning_helper.grasp_width_from_palm_poses(\\n palm_pose_l_object, palm_pose_r_object)\\n # grasp_width = grasp_width/1.025\\n # grasp_width = 0.086 - 0.006\\n # grasp_width = 0.086\\n # grasp_width = 0.05206\\n # grasp_width = 0.135\\n # print(\\\"grasp width: \\\" + str(grasp_width))\\n\\n # 1. get lifted object poses\\n object_pose_lifted_world = copy.deepcopy(object_pose1_world)\\n\\n if init:\\n object_pose_lifted_world.pose.position.z += 0.05\\n # object_pose_lifted_world.pose.position.z += 0.05\\n object_pose2_world.pose.position.z += 0.0025\\n\\n # 2. get lifted palm poses\\n palm_poses_lifted_world = planning_helper.palm_poses_from_object(\\n object_pose=object_pose_lifted_world,\\n palm_pose_l_object=palm_pose_l_object,\\n palm_pose_r_object=palm_pose_r_object)\\n\\n # 3. get rotated object pose\\n object_pose_rotated_world = copy.deepcopy(object_pose2_world)\\n\\n # if init:\\n # object_pose_rotated_world.pose.position.z += 0.05\\n object_pose_rotated_world.pose.position.z += 0.05\\n\\n palm_poses_rotated_world = planning_helper.palm_poses_from_object(\\n object_pose=object_pose_rotated_world,\\n palm_pose_l_object=palm_pose_l_object,\\n palm_pose_r_object=palm_pose_r_object)\\n\\n # 4. get final configuration\\n palm_poses_final_world = planning_helper.palm_poses_from_object(\\n object_pose=object_pose2_world,\\n palm_pose_l_object=palm_pose_l_object,\\n palm_pose_r_object=palm_pose_r_object)\\n\\n # 3. generate pose plans\\n # 3.1. initialize plan\\n initial_plan = planning_helper.initialize_plan(\\n palm_poses_initial=palm_poses_initial_world,\\n object_pose_initial=object_pose1_world,\\n primitive=primitive_name,\\n plan_name='initial_config')\\n\\n # 3.2. lift the object\\n lift_plan = planning_helper.move_cart_synchro(\\n palm_poses_final=palm_poses_lifted_world,\\n grasp_width=grasp_width,\\n plan_previous=initial_plan,\\n primitive=primitive_name,\\n plan_name='lift_object',\\n N=10)\\n\\n # 3.3. rotate the object\\n rotate_plan = planning_helper.move_cart_synchro(\\n palm_poses_final=palm_poses_rotated_world,\\n grasp_width=grasp_width,\\n plan_previous=lift_plan,\\n primitive=primitive_name,\\n plan_name='rotate_object_final',\\n N=N/2,\\n is_replan=True)\\n\\n # 3.4. place the object\\n place_plan = planning_helper.move_cart_synchro(\\n palm_poses_final=palm_poses_final_world,\\n grasp_width=grasp_width,\\n plan_previous=rotate_plan,\\n primitive=primitive_name,\\n plan_name='place_object',\\n N=20)\\n return [lift_plan] + [rotate_plan] + [place_plan]\",\n \"def drawCoordinatePlane_region():\\r\\n turtle2 = t.Screen()\\r\\n turtle2.title(\\\"Life Expectancy versus Region\\\")\\r\\n t2.speed(0)\\r\\n t3.speed(0)\\r\\n setTurtle(t0)\\r\\n setTurtle(t1)\\r\\n setTurtle(t2)\\r\\n setTurtle(t3)\\r\\n drawAxes(t0)\\r\\n t1.left(90)\\r\\n drawAxes(t1)\\r\\n t0.pu()\\r\\n t0.fd(-80)\\r\\n t0.lt(90)\\r\\n drawlabels(t0, t1)\\r\\n drawPoints(t0, t1)\\r\\n t0.pu()\\r\\n t1.pu()\\r\\n t2.pu()\\r\\n t3.pu()\\r\\n t0.goto(initialCoordinates())\\r\\n t1.goto(initialCoordinates())\\r\\n t2.goto(initialCoordinates())\\r\\n t3.goto(initialCoordinates())\\r\\n t1.lt(90)\",\n \"def __check_boundary(self):\\n\\t\\tif self.rect.left <= self.left_boundary:\\n\\t\\t\\tself.move_right()\\n\\t\\tif self.rect.right >= self.right_boundary:\\n\\t\\t\\tself.move_left()\",\n \"def boundary(active, objects):\\n limit = SIZE[1]\\n for obj in objects:\\n if active.pos_x == obj.pos_x:\\n limit = min(limit, obj.pos_y)\\n active.pos_y = limit-active.height\\n active.col_d = True\",\n \"def move(self, playersList):\\n land = pygame.Rect(283, 468, 635, 210)\\n leftCroc = pygame.Rect(300, 373, 105, 20)\\n leftStand = pygame.Rect(485, 300, 76, 10)\\n rightStand = pygame.Rect(639, 300, 76, 10)\\n rightBirb = pygame.Rect(795, 373, 105, 20)\\n bottomland = pygame.Rect(0, 750, 1500, 1)\\n platformsList = [land, leftCroc, rightBirb, leftStand, rightStand,bottomland]\\n\\n # Push\\n if self.count <= 0:\\n self.count = 10\\n self.push = False\\n self.moveRight = False\\n\\n if self.push == True and self.moveRight:\\n self.count -= 1\\n self.rect.x +=(self.count**2)*0.5\\n\\n if self.push == True and self.moveRight == False:\\n self.count -= 1\\n self.rect.x -=(self.count**2)*0.5\\n\\n # mover horizontal\\n if self.left:\\n self.rect.x -= self.speed_x\\n if self.right:\\n self.rect.x += self.speed_x\\n\\n # Revisar si pegó con la tierra\\n if self.rect.colliderect(land) and self.rect.bottom > land.top + 50: # ///// Aquí el land.top+n lo tiene que ajustar para que sea como el piso máximo de los maecitos\\n if self.left:\\n self.rect.left = land.right\\n elif self.right:\\n self.rect.right = land.left\\n\\n # revisar si está en medio de una plataforma (por si está saltando a través de una)\\n insidePlatform = self.rect.collidelist(platformsList)\\n # mover vertical\\n if self.falling or self.rising:\\n self.rect.y += self.speed_y\\n for platform in platformsList:\\n # si choca con una plataforma\\n if self.rect.colliderect(bottomland):\\n self.rect.bottom = land.top\\n self.rect.x = 750\\n if self.rect.colliderect(platform):\\n # y específicamente está cayéndose y no es la plataforma que ya vimos por la que estaba pasando\\n if self.falling and platform is not platformsList[insidePlatform]:\\n self.rect.bottom = platform.top\\n self.speed_y = 0\\n self.falling = False\\n\\n # Manejar velocidad vertical\\n if self.falling or self.rising: # lo vuelvo a revisar porque pudo haber parado de estar falling al caer en una plataforma\\n self.speed_y += 1 # /////Aquí se cambia la aceleración vertical del jugador//////\\n if self.speed_y > 20:\\n self.speed_y = 20 # /////Aquí se cambia la velocidad máxima de caída/////\\n if self.rising and self.speed_y > 0: # aquí es si pasa de estar subiendo a estar cayendo\\n self.rising = False\\n self.falling = True\\n\\n # si se queda sin plataforma por debajo\\n if self.falling == False and self.rising == False:\\n self.falling = True\\n tryoutRect = self.rect.copy()\\n tryoutRect.y += 1\\n for platform in platformsList:\\n # si choca con una plataforma\\n if tryoutRect.colliderect(platform):\\n self.falling = False\\n\\n self.collide(playersList)\",\n \"def mover_bm_arriba(self):\\n self.nueva_posicion_posible_parte_superior = self.mapa.consultar_casilla_por_movimiento([self.casilla[0],\\n self.casilla[1] - 1],\\n [self.vertice_1[0] ,self.vertice_1[1] - self.velocidad],\\n [self.vertice_1[0], self.vertice_1[1] - 5 -5])\\n self.nueva_posicion_posible_parte_inferior = self.mapa.consultar_casilla_por_movimiento([self.casilla[0] + 1,\\n self.casilla[1] - 1],\\n [self.vertice_2[0] ,self.vertice_2[1] - self.velocidad],\\n [self.vertice_1[0],self.vertice_1[1]])\\n self.y -= self.velocidad * (self.y >= 15) *(self.nueva_posicion_posible_parte_inferior[0] != 1) * (self.nueva_posicion_posible_parte_superior[0] != 1)\\n self.posicion = [self.posicion[0],self.y]\\n self.casilla = [self.casilla[0],self.casilla[1] - self.nueva_posicion_posible_parte_superior[1] * (self.nueva_posicion_posible_parte_inferior[0] != 1) * (self.nueva_posicion_posible_parte_superior[0] != 1)]\\n self.redefinir_vertices()\",\n \"def check_boundaries(self):\\n # Checks if the enemy bar has gone of the net\\n if self.rect.left <= self.settings.WINDOW_WIDTH / 2:\\n self.rect.left = self.settings.WINDOW_WIDTH / 2\\n self.isMovingUp = False\\n\\n # Checks if the enemy bar has gone out of bound to the right\\n if self.rect.right >= self.settings.WINDOW_WIDTH:\\n self.rect.right = self.settings.WINDOW_WIDTH\\n self.isMovingUp = True\",\n \"def move_to_refine(self, des_img_pos, act_img_pos, current_world_pos, increment, img_thresh):\\n des_img_x = des_img_pos[0]\\n des_img_y = des_img_pos[1]\\n act_img_x = act_img_pos[0]\\n act_img_y = act_img_pos[1]\\n cur_wld_x = current_world_pos[0]\\n cur_wld_y = current_world_pos[1]\\n new_wld_x = cur_wld_x\\n new_wld_y = cur_wld_y\\n \\n #object to the left -> move left (-wld_y)\\n if (act_img_x < des_img_x-img_thresh):\\n print(' Moving left')\\n new_wld_y = cur_wld_y + increment\\n #object to the right -> move right (+wld_y)\\n elif (act_img_x > des_img_x+img_thresh):\\n new_wld_y = cur_wld_y - increment\\n print(' Moving right')\\n #object to the top -> move forward (+wld_x)\\n if (act_img_y < des_img_y-img_thresh):\\n new_wld_x = cur_wld_x + increment\\n print(' Moving forward')\\n #object to the bottom -> move backward (-wld_x)\\n elif (act_img_y > des_img_y+img_thresh):\\n new_wld_x = cur_wld_x - increment\\n print(' Moving backward')\\n \\n #move arm to new coordinates\\n self.move_to(new_wld_x, new_wld_y, self.move_to_height)\\n \\n #return new arm position\\n return [new_wld_x, new_wld_y]\",\n \"def mouse_move(self, obj, event):\\n last_pos = self.iren.GetLastEventPosition()\\n next_pos = self.iren.GetEventPosition()\\n last_disp_coords = np.asarray([last_pos[0], last_pos[1], 0])\\n next_disp_coords = np.asarray([next_pos[0], next_pos[1], 0])\\n last_world_coords = self.display_to_world(last_disp_coords)\\n next_world_coords = self.display_to_world(next_disp_coords)\\n world_direction = (last_world_coords - next_world_coords)[0]\\n\\n if world_direction > 0:\\n direction = 'forwards'\\n elif world_direction < 0:\\n direction = 'backwards'\\n else:\\n direction = 'none'\\n\\n if self.cone_dir == 'start':\\n if direction == 'backwards':\\n self.start_base_x += .5\\n if self.start_base_x.is_integer():\\n ind = str(int(self.start_base_x))\\n isvalid = self.gaps.set_dragged_start(ind)\\n if isvalid:\\n self.ren_win.Render()\\n else:\\n self.start_base_x -= .5\\n return\\n\\n elif direction == 'forwards':\\n if self.start_base_x > 0:\\n self.start_base_x -= .5\\n if self.start_base_x.is_integer():\\n ind = str(int(self.start_base_x))\\n self.gaps.set_dragged_start(ind)\\n self.ren_win.Render()\\n\\n if self.cone_dir == 'end':\\n if direction == 'backwards':\\n if self.end_base_x > 0:\\n self.end_base_x -= .5\\n if self.end_base_x.is_integer():\\n ind = str(int(self.end_base_x))\\n self.gaps.set_dragged_end(ind)\\n self.ren_win.Render()\\n\\n elif direction == 'forwards':\\n self.end_base_x += .5\\n if self.end_base_x.is_integer():\\n ind = str(int(self.end_base_x))\\n isvalid = self.gaps.set_dragged_end(ind)\\n if isvalid:\\n self.ren_win.Render()\\n else:\\n self.end_base_x -= .5\\n return\",\n \"def update(self):\\r\\n if self.change_x < 0 and self.left - self.speed <= Costanti.LEVEL_INFO['left']:\\r\\n # raggiunto limite sinistro\\r\\n self.left = Costanti.LEVEL_INFO['left'] + 1\\r\\n elif self.change_x > 0 and Costanti.LEVEL_INFO['right'] <= self.right + self.speed:\\r\\n # raggiunto limite destro\\r\\n self.right = Costanti.LEVEL_INFO[\\\"right\\\"] - 1\\r\\n elif self.left > Costanti.LEVEL_INFO[\\\"left\\\"] and self.right < Costanti.LEVEL_INFO[\\\"right\\\"]:\\r\\n # sposta il paddle\\r\\n self.center_x += self.change_x * self.speed\\r\\n\\r\\n # aggiorno l'immagine per l'animazione\\r\\n super().update_animation()\\r\\n\\r\\n # ristabilisco le giuste dimensioni del paddle e non quelle dell'immagine originale\\r\\n self.width = Costanti.Paddle_WIDTH\\r\\n self.height = Costanti.Paddle_HEIGHT\",\n \"def _add_boundaries(self):\\n logger.info(\\\"add_boundaries: start of method\\\")\\n\\n import scipy.spatial as sptl\\n import scipy.sparse as sprs\\n Lx = self._Lx\\n Ly = self._Ly\\n Lz = self._Lz\\n Np = self.num_pores()\\n btype = self._btype\\n boffset = 0.05\\n\\n #Translate internal pores to each face of domain\\n poffset = np.zeros((7,3))\\n poffset[[2,5],0] = [-Lx, Lx]\\n poffset[[3,4],1] = [-Ly, Ly]\\n poffset[[1,6],2] = [-Lz, Lz]\\n pcoords = pcoords0 = self['pore.coords']\\n for i in np.r_[1:7]:\\n pcoords = np.concatenate((pcoords,pcoords0 + poffset[i,:]),axis=0)\\n\\n #Use some twisted logic to get bval list of + for boundary and - for periodic faces\\n bval = [0, 1, 2, 3, 4, 5, 6]*(np.array([0, btype[2], btype[0], btype[1], btype[1], btype[0], btype[2]])*-2+1)\\n ptype = np.zeros((Np,),dtype=int)\\n for i in np.r_[1:7]:\\n ptype = np.concatenate((ptype,np.ones((Np,),dtype=int)*bval[i]),axis=0)\\n\\n #pnum contains the internal ID number of the boundary pores (for connecting periodic points)\\n pnum = self.pores()\\n pnum = np.tile(pnum,7)\\n\\n Tri = sptl.Delaunay(pcoords)\\n adjmat = sprs.lil_matrix((np.shape(pcoords)[0],np.shape(pcoords)[0]),dtype=int)\\n for i in np.arange(0,np.shape(Tri.simplices)[0]):\\n #Keep only simplices that are fully in real domain\\n adjmat[Tri.simplices[i],Tri.simplices[i]] = 1\\n adjmat = sprs.triu(adjmat,k=1,format=\\\"lil\\\")\\n for i in np.arange(0,Np):\\n #Add periodic throats to the netowrk (if any)\\n tpore2 = pnum[adjmat.rows[i]][ptype[adjmat.rows[i]]<0]\\n tpore1 = np.ones_like(tpore2,dtype=int)*i\\n conns = self['throat.conns']\\n conns = np.concatenate((conns,np.vstack((tpore1,tpore2)).T),axis=0)\\n #Add boundary pores and throats to the network\\n newporetyps = np.unique(ptype[adjmat.rows[i]][ptype[adjmat.rows[i]]>0])\\n newporenums = np.r_[self.num_pores():self.num_pores()+np.size(newporetyps)]\\n tpore2 = newporenums\\n tpore1 = np.ones_like(tpore2,dtype=int)*i\\n conns = np.concatenate((conns,np.vstack((tpore1,tpore2)).T),axis=0)\\n self['throat.conns'] = conns\\n bcoords = np.zeros((7,3),dtype=float)\\n coords = self['pore.coords']\\n bcoords[1,:] = [coords[i,0], coords[i,1], 0-Lz*boffset]\\n bcoords[2,:] = [0-Lx*boffset, coords[i,1], coords[i,2]]\\n bcoords[3,:] = [coords[i,0], -Ly*boffset, coords[i,2]]\\n bcoords[4,:] = [coords[i,0], Ly+Ly*boffset, coords[i,2]]\\n bcoords[5,:] = [Lx+Lx*boffset, coords[i,1], coords[i,2]]\\n bcoords[6,:] = [coords[i,0], coords[i,1], Lz+Lz*boffset]\\n newporecoords = bcoords[newporetyps,:]\\n coords = np.concatenate((coords,newporecoords),axis=0)\\n self['pore.coords'] = coords\\n #Reset number of pores and throats (easier than tracking it)\\n nums = np.r_[0:np.shape(coords)[0]]\\n self['pore.numbering'] = nums\\n self['pore.numbering'] = np.ones((nums[-1]+1,),dtype=bool)\\n nums = np.r_[0:np.shape(conns)[0]]\\n self['throat.numbering'] = nums\\n self['throat.numbering'] = np.ones((nums[-1]+1,),dtype=bool)\\n logger.debug(\\\"add_boundaries: end of method\\\")\",\n \"def mover_bm_izquierda(self):\\n self.nueva_posicion_posible_parte_superior = self.mapa.consultar_casilla_por_movimiento([self.casilla[0] - 1,\\n self.casilla[1]],\\n [self.vertice_1[0] - self.velocidad,self.vertice_1[1]], \\n [self.vertice_1[0] - 5 - 5, self.vertice_1[1]])\\n self.nueva_posicion_posible_parte_inferior = self.mapa.consultar_casilla_por_movimiento([self.casilla[0] - 1,\\n self.casilla[1] + 1],\\n [self.vertice_3[0] - self.velocidad,self.vertice_3[1]],\\n [self.vertice_3[0] - 5,self.vertice_3[1]]) \\n if self.nueva_posicion_posible_parte_superior[0] != 1 and self.nueva_posicion_posible_parte_inferior[0] != 1:\\n self.x -= self.velocidad * (self.x >= 15)\\n self.posicion = [self.x,self.posicion[1]]\\n self.casilla = [self.casilla[0] - self.nueva_posicion_posible_parte_superior[1] *(self.nueva_posicion_posible_parte_inferior[0] != 1) * (self.nueva_posicion_posible_parte_superior[0] != 1), self.casilla[1]]\\n self.redefinir_vertices()\",\n \"def _change_shape(self,x,y,w,h):\\n top = y \\n left = x\\n right = x + w\\n bottom = y + h\\n return top,right,bottom,left\",\n \"def PINTARMATRIXDEBOTONES(self):\\n for i in range(0, 26):\\n for j in range(0, 26):\\n x0 = ((i+1)*24) + 26\\n y0 = ((j)*21) \\n self.telaMAPA.create_rectangle(x0, 545 - y0, x0 + 10, 550 - y0, tag=str(i)+\\\"-\\\"+str(j))\\n # Se guarda la inforamcion\\n info = (x0, 545 - y0, str(i)+\\\"-\\\"+str(j))\\n self.bononesPlanoXY.append(info)\",\n \"def _add_opposing_boundaries(self,btype=[1,6]):\\n logger.info(\\\"add_opposing_boundaries: start of method\\\")\\n\\n if btype==[2,5]:\\n D=0\\n W=1\\n H=2\\n elif btype==[3,4]:\\n D=1\\n W=0\\n H=2\\n elif btype==[1,6]:\\n D=2\\n W=1\\n H=0\\n\\n Lx = self.domain_size[D]\\n Ly = self.domain_size[W]\\n Lz = self.domain_size[H]\\n #Rotate pore coordinates (use only internal pores)\\n pnum = self._net.pore_data['numbering'][self._net.pore_data['type']==0]\\n pcoords = np.zeros_like(self._net.pore_data['coords'][pnum,:])\\n pcoords[:,0] = self._net.pore_data['coords'][pnum,D]\\n pcoords[:,1] = self._net.pore_data['coords'][pnum,W]\\n pcoords[:,2] = self._net.pore_data['coords'][pnum,H]\\n\\n #Determine dimensions of image from dimensions of domain\\n f = 100 #minimum image dimension\\n im_dim = [0,0,0]\\n im_dim[0] = np.floor(f*Lx/np.min([Lx,Ly,Lz]))\\n im_dim[1] = np.floor(f*Ly/np.min([Lx,Ly,Lz]))\\n im_dim[2] = np.floor(f*Lz/np.min([Lx,Ly,Lz]))\\n im_dim = np.array(im_dim,dtype=int)\\n\\n #Convert pore coordinates into image subscripts\\n im_subs = np.zeros_like(pcoords,dtype=int)\\n im_subs[:,0] = pcoords[:,0]*im_dim[0]/Lx\\n im_subs[:,1] = pcoords[:,1]*im_dim[1]/Ly\\n im_subs[:,2] = pcoords[:,2]*im_dim[2]/Lz\\n #Find linear indices of each pore in the new image\\n im_inds = np.ravel_multi_index((im_subs[:,0], im_subs[:,1], im_subs[:,2]), dims=(im_dim), order='F')\\n\\n #Generate 3D image of points (place pore numbers at each site for use later)\\n img = np.zeros(im_dim,dtype=int)\\n img[im_subs[:,0],im_subs[:,1],im_subs[:,2]] = pnum\\n\\n #Perform distance transform on points and also get 'indicies' of each point\\n img_dt, ind_dt = spim.distance_transform_edt(img==0)\\n\\n #Project all* internal points to x face\\n #*Note that it's possible/likely that mutliple internal points map to the same boundary point\\n img_bd0 = np.zeros([im_dim[1],im_dim[2]],dtype=int)\\n img_bd1 = np.zeros([im_dim[1],im_dim[2]],dtype=int)\\n img_bd0[im_subs[:,1],im_subs[:,2]] = im_inds\\n img_bd1[im_subs[:,1],im_subs[:,2]] = im_inds\\n\\n #Create 2D array of distance transform indices for 0 and end faces\\n dt_D0 = ind_dt[0,0,:,:]*(img_bd0>0) #0 face\\n dt_D1 = ind_dt[0,-1,:,:]*(img_bd1>0) #end face\\n\\n #Create a 2D mask containing x coordinates of internal points and -1 elsewhere\\n img_D0 = -np.ones([im_dim[1],im_dim[2]],dtype=int)\\n img_D1 = -np.ones([im_dim[1],im_dim[2]],dtype=int)\\n img_D0[im_subs[:,1],im_subs[:,2]] = im_subs[:,0]\\n img_D1[im_subs[:,1],im_subs[:,2]] = im_subs[:,0]\\n\\n #Find where x value of internal points corresponds to x value of distance transform indices\\n img_bd0 = (img_D0 == dt_D0)*img_bd0\\n img_bd1 = (img_D1 == dt_D1)*img_bd1\\n\\n #Convert boundary sites to linear indices\\n inds_bd0 = img_bd0[np.nonzero(img_bd0)]\\n inds_bd1 = img_bd1[np.nonzero(img_bd1)]\\n\\n #Use linear indices to find pore ID nums\\n nums_bd0 = img[np.unravel_index(inds_bd0, dims=(im_dim), order='F')]\\n nums_bd1 = img[np.unravel_index(inds_bd1, dims=(im_dim), order='F')]\\n nums_bd = np.append(nums_bd0,nums_bd1)\\n types_bd = np.append(np.zeros_like(nums_bd0),np.ones_like(nums_bd1))\\n\\n #Add new boundary pores and throats to the network\\n Np = self._net.num_pores() #Get all pores including previously added boundaries\\n bp_numbering = np.r_[Np:Np+np.size(nums_bd)]\\n bp_type = (types_bd==0)*btype[0] + (types_bd==1)*btype[1]\\n bp_coords = np.zeros([np.size(nums_bd),3])\\n bp_coords[types_bd==0,D] = np.zeros_like(nums_bd0)-.0001\\n bp_coords[types_bd==0,W] = pcoords[nums_bd0,1]\\n bp_coords[types_bd==0,H] = pcoords[nums_bd0,2]\\n bp_coords[types_bd==1,D] = np.ones_like(nums_bd1)*Lx+0.0001\\n bp_coords[types_bd==1,W] = pcoords[nums_bd1,1]\\n bp_coords[types_bd==1,H] = pcoords[nums_bd1,2]\\n self._net.pore_data['numbering'] = np.append(self._net.pore_data['numbering'],bp_numbering)\\n self._net.pore_data['type'] = np.append(self._net.pore_data['type'],bp_type)\\n self._net.pore_data['coords'] = np.concatenate((self._net.pore_data['coords'],bp_coords))\\n Nt = self._net.num_throats()\\n bt_numbering = np.r_[Nt:Nt+np.size(nums_bd)]\\n bt_type = np.ones(np.size(nums_bd),dtype=int)*2\\n bt_connections = np.zeros([np.size(nums_bd),2],dtype=int)\\n bt_connections[:,0] = nums_bd\\n bt_connections[:,1] = bp_numbering\\n self._net.throat_data['numbering'] = np.append(self._net.throat_data['numbering'],bt_numbering)\\n self._net.throat_data['type'] = np.append(self._net.throat_data['type'],bt_type)\\n self._net.throat_data['conns'] = np.concatenate((self._net.throat_data['conns'],bt_connections))\",\n \"def project(self):\\n # update positions compared to observer\\n pos = self.pos.copy()\\n\\n # center coordinates around obs coords\\n pos[:, 0] -= np.sin(self.theta) * self.V * self.time_elapsed\\n pos[:, 2] -= np.cos(self.theta) * self.V * self.time_elapsed\\n\\n # wrap in a novel box around obs coords\\n for i in range(3):\\n pos[:, i] = self.bounds[2*i] + np.mod(pos[:, i], self.bounds[2*i + 1]-self.bounds[2*i])\\n\\n d = (pos**2).sum(axis=1)**.5\\n # ind_visible = (pos[:, 2] > 0) * (self.d_min<d) * (d<self.d_max)\\n ind_visible = (pos[:, 2] > self.d_min) * (d < self.d_max)\\n N_visible = int(np.sum(ind_visible))\\n\\n # self.state = [X, Y, size]\\n self.state = np.ones((N_visible, 7))\\n for i in range(2):\\n self.state[:, i] = self.mag * pos[ind_visible, i] / pos[ind_visible, 2]\\n print(i, self.state[:, i].min(), self.state[:, i].max())\\n self.state[:, 2] = self.size / d[ind_visible]\\n\\n # colors do not change\\n self.state[:, 3:] = pos[ind_visible, 3:]\\n\\n # TODO: larger transparency at larger distance => too fancy :-)\\n # self.state[:, 2] = self.size / d[ind_visible]\\n\\n # for i in range(3):\\n # self.state[:, i] *= (self.bounds[2*i+1] - self.bounds[2*i])\\n # self.state[:, i] -= self.bounds[2*i]\",\n \"def _walk(self):\\n \\n newpos= self.rect.move((self.move, 0)) # x方向移動 .move, y方向不動。\\n \\n # 偵測碰撞左右牆壁，並處理(反彈)\\n if not self.area.contains(newpos):\\n if self.rect.left < self.area.left or \\\\\\n self.rect.right > self.area.right:\\n self.move = -self.move\\n newpos = self.rect.move((self.move, 0))\\n self.image = pygame.transform.flip(self.image, 1, 0)\\n self.rect = newpos\",\n \"def left_obj_points(grid_size, dx):\\r\\n objp = np.zeros((grid_size[1] * grid_size[2], 3), np.float32)\\r\\n objp[:,1:3] = np.mgrid[0:grid_size[2], 0:grid_size[1]].T.reshape(-1, 2)\\r\\n u=objp.T; y=0*u; y[1]=u[2]; y[2]=u[1]\\r\\n\\r\\n return y.T * dx\",\n \"def obstacles(self):\\r\\n\\r\\n #Radious arround the head\\r\\n limit_sight = self.snake_sight\\r\\n head = self.body[0].position\\r\\n binary_map_complete = self.complete_mapping()\\r\\n map_matrix = np.matrix(binary_map_complete)\\r\\n obstacles = []\\r\\n\\r\\n #limits in all directions\\r\\n left_x = head[0] - limit_sight\\r\\n right_x = head[0] + limit_sight\\r\\n up_y = head[1] - limit_sight\\r\\n down_y = head[1] + limit_sight\\r\\n\\r\\n #submatrix with limits size\\r\\n snake_sight = map_matrix[up_y:down_y+1, left_x:right_x+1]\\r\\n\\r\\n #Special cases where the snake approximates to the borders\\r\\n ##Corners\\r\\n if left_x < 0 and up_y < 0:\\r\\n snake_sight = map_matrix[0:down_y+1, 0:right_x+1]\\r\\n interval_x = [self.limits[0] + left_x, self.limits[0]]\\r\\n interval_y = [self.limits[1] + up_y, self.limits[1]]\\r\\n interval_x_matrix = map_matrix[0:down_y+1, interval_x[0]:interval_x[1]]\\r\\n interval_y_matrix = map_matrix[interval_y[0]:interval_y[1], 0:right_x+1]\\r\\n interval_x_y_matrix = map_matrix[interval_y[0]:interval_y[1], interval_x[0]:interval_x[1]]\\r\\n temporal = np.c_[interval_x_y_matrix, interval_y_matrix]\\r\\n snake_sight = np.c_[interval_x_matrix, snake_sight]\\r\\n snake_sight = np.r_[temporal, snake_sight] \\r\\n return snake_sight\\r\\n \\r\\n if left_x < 0 and down_y > self.limits[1] - 1:\\r\\n snake_sight = map_matrix[up_y:self.limits[1], 0:right_x+1]\\r\\n interval_x = [self.limits[0] + left_x, self.limits[0]]\\r\\n interval_y = [0, down_y - self.limits[1] + 1]\\r\\n interval_x_matrix = map_matrix[up_y:self.limits[1], interval_x[0]:interval_x[1]]\\r\\n interval_y_matrix = map_matrix[interval_y[0]:interval_y[1], 0:right_x+1]\\r\\n interval_x_y_matrix = map_matrix[interval_y[0]:interval_y[1], interval_x[0]:interval_x[1]]\\r\\n temporal = np.c_[interval_x_y_matrix, interval_y_matrix]\\r\\n snake_sight = np.c_[interval_x_matrix, snake_sight]\\r\\n snake_sight = np.r_[snake_sight, temporal]\\r\\n return snake_sight\\r\\n \\r\\n if right_x > self.limits[0]-1 and up_y < 0:\\r\\n snake_sight = map_matrix[0:down_y+1, left_x:self.limits[0]]\\r\\n interval_x = [0, right_x - self.limits[0] + 1]\\r\\n interval_y = [self.limits[1] + up_y, self.limits[1]]\\r\\n interval_x_matrix = map_matrix[0:down_y+1, interval_x[0]:interval_x[1]]\\r\\n interval_y_matrix = map_matrix[interval_y[0]:interval_y[1], left_x:self.limits[0]]\\r\\n interval_x_y_matrix = map_matrix[interval_y[0]:interval_y[1], interval_x[0]:interval_x[1]]\\r\\n temporal = np.c_[interval_y_matrix, interval_x_y_matrix]\\r\\n snake_sight = np.c_[snake_sight, interval_x_matrix]\\r\\n snake_sight = np.r_[temporal, snake_sight]\\r\\n return snake_sight\\r\\n \\r\\n if right_x > self.limits[0]-1 and down_y > self.limits[1]-1:\\r\\n snake_sight = map_matrix[up_y:self.limits[1], left_x:self.limits[0]]\\r\\n interval_x = [0, right_x - self.limits[0] + 1]\\r\\n interval_y = [0, down_y - self.limits[1] + 1]\\r\\n interval_x_matrix = map_matrix[up_y:self.limits[1], interval_x[0]:interval_x[1]]\\r\\n interval_y_matrix = map_matrix[interval_y[0]:interval_y[1], left_x:self.limits[0]]\\r\\n interval_x_y_matrix = map_matrix[interval_y[0]:interval_y[1], interval_x[0]:interval_x[1]]\\r\\n temporal = np.c_[interval_y_matrix, interval_x_y_matrix]\\r\\n snake_sight = np.c_[snake_sight, interval_x_matrix]\\r\\n snake_sight = np.r_[snake_sight, temporal]\\r\\n return snake_sight\\r\\n\\r\\n ##Middle\\r\\n if left_x < 0:\\r\\n snake_sight = map_matrix[up_y:down_y+1, 0:right_x+1]\\r\\n interval_x = [self.limits[0] + left_x, self.limits[0]]\\r\\n interval_x_matrix = map_matrix[up_y:down_y+1, interval_x[0]:interval_x[1]]\\r\\n snake_sight = np.c_[interval_x_matrix, snake_sight]\\r\\n return snake_sight\\r\\n\\r\\n if right_x > self.limits[0]-1:\\r\\n snake_sight = map_matrix[up_y:down_y+1, left_x:self.limits[0]]\\r\\n interval_x = [0, right_x - self.limits[0] + 1]\\r\\n interval_x_matrix = map_matrix[up_y:down_y+1, interval_x[0]:interval_x[1]]\\r\\n snake_sight = np.c_[snake_sight, interval_x_matrix]\\r\\n return snake_sight\\r\\n\\r\\n if up_y < 0:\\r\\n snake_sight = map_matrix[0:down_y+1, left_x:right_x+1]\\r\\n interval_y = [self.limits[1] + up_y, self.limits[1]]\\r\\n interval_y_matrix = map_matrix[interval_y[0]:interval_y[1], left_x:right_x+1]\\r\\n snake_sight = np.r_[interval_y_matrix, snake_sight]\\r\\n return snake_sight\\r\\n \\r\\n if down_y > self.limits[1]-1:\\r\\n snake_sight = map_matrix[up_y:self.limits[1], left_x:right_x+1]\\r\\n interval_y = [0, down_y - self.limits[1] + 1]\\r\\n interval_y_matrix = map_matrix[interval_y[0]:interval_y[1], left_x:right_x+1]\\r\\n snake_sight = np.r_[snake_sight, interval_y_matrix]\\r\\n return snake_sight\\r\\n\\r\\n return snake_sight\",\n \"def box_transform_page(page, direction_list=[]):\\n\\n if len(page.children) > 1:\\n\\n # For all children of the page\\n for idx in range(0, len(page.children)-1):\\n\\n # Take two children at a time\\n p1 = page.get_child(idx)\\n p2 = page.get_child(idx+1)\\n\\n change_proportion = np.random.randint(\\n 10,\\n cfg.full_page_movement_proportion_limit\\n )\\n\\n change_proportion /= 100\\n\\n # Randomly move the line between them up or down one side\\n if len(direction_list) < 1:\\n direction = np.random.choice([\\\"rup\\\", \\\"lup\\\"])\\n else:\\n direction = direction_list[idx]\\n\\n # If the first panel is horizontal therefore the second is too\\n if p1.orientation == \\\"h\\\":\\n\\n # Get the maximum amount the line can move\\n change_max = min([(p1.x4y4[1] - p1.x1y1[1]),\\n (p2.x4y4[1] - p2.x1y1[1])])\\n\\n change = change_max*change_proportion\\n\\n # Specify the line to move\\n line_top = p2.x1y1\\n line_bottom = p2.x2y2\\n\\n # If the panel has children then recursively\\n # find the leaf children and move them to the new line\\n if len(p1.children) > 0:\\n move_children_to_line(p1,\\n (line_top, line_bottom),\\n change,\\n \\\"h\\\",\\n direction\\n )\\n\\n # Otherwise move the current panels to line\\n else:\\n if direction == \\\"rup\\\":\\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] + change)\\n p1.refresh_coords()\\n else:\\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] - change)\\n p1.refresh_coords()\\n\\n if len(p2.children) > 0:\\n move_children_to_line(p2,\\n (line_top, line_bottom),\\n change,\\n \\\"h\\\",\\n direction\\n )\\n else:\\n if direction == \\\"rup\\\":\\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] + change)\\n p2.refresh_coords()\\n else:\\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] - change)\\n p2.refresh_coords()\\n\\n # If the first panel is vertical therefore the second\\n # is too since they are siblings\\n else:\\n # Get the maximum amount the line can move\\n change_max = min([(p1.x2y2[0] - p1.x1y1[0]),\\n (p2.x2y2[0] - p2.x1y1[0])])\\n\\n change = change_max*change_proportion\\n\\n # Specify the line to move\\n line_top = p2.x1y1\\n line_bottom = p2.x4y4\\n\\n # If the panel has children then recursively\\n # find the leaf children and move them to the new line\\n if len(p1.children) > 0:\\n move_children_to_line(p1,\\n (line_top, line_bottom),\\n change,\\n \\\"v\\\",\\n direction\\n )\\n\\n # Otherwise just move the panel since it's a leaf\\n else:\\n if direction == \\\"rup\\\":\\n p1.x2y2 = (p1.x2y2[0] - change, p1.x2y2[1])\\n else:\\n p1.x2y2 = (p1.x2y2[0] + change, p1.x2y2[1])\\n\\n if len(p2.children) > 0:\\n move_children_to_line(p2,\\n (line_top, line_bottom),\\n change,\\n \\\"v\\\",\\n direction\\n )\\n else:\\n if direction == \\\"rup\\\":\\n p2.x1y1 = (p2.x1y1[0] - change, p2.x1y1[1])\\n else:\\n p2.x1y1 = (p2.x1y1[0] + change, p2.x1y1[1])\\n\\n return page\",\n \"def _move_receptor_to_grid_center(self):\\n lower_receptor_corner = np.array([self._crd[:,i].min() for i in range(3)], dtype=float)\\n upper_receptor_corner = np.array([self._crd[:,i].max() for i in range(3)], dtype=float)\\n \\n receptor_box_center = (upper_receptor_corner + lower_receptor_corner) / 2.\\n grid_center = (self._origin_crd + self._uper_most_corner_crd) / 2.\\n displacement = grid_center - receptor_box_center\\n\\n print(\\\"Receptor is translated by \\\", displacement)\\n\\n for atom_ind in range(len(self._crd)):\\n self._crd[atom_ind] += displacement\\n return None\",\n \"def define_grid():\\n grid_left = np.array([[-13.1000000000000, -35.5000000000000, -48.3000000000000, -60, -16.9000000000000,\\n -34.8000000000000, -67.5000000000000, -46.1000000000000, -59.8000000000000,\\n -14.2000000000000, -28.3000000000000, -42.3000000000000, -67.6000000000000,\\n -50.5000000000000, -14.6000000000000, -60.9000000000000, -31.6000000000000,\\n -5.10000000000000, -65.6000000000000, -41.8000000000000, -55.1000000000000,\\n -22.7000000000000, -5.80000000000000, -49.2000000000000, -34.5000000000000,\\n -61.5500000000000, -63.6000000000000, -40.4000000000000, -48.7000000000000,\\n -21.8000000000000, -58.2000000000000, -7, -36.3000000000000, -48.1000000000000,\\n -56.8000000000000, -7.30000000000000, -22.2000000000000, -36.8000000000000,\\n -46.8000000000000],\\n [-67.7000000000000, -60, -55.1000000000000, -51.8000000000000, -51.6000000000000,\\n -49.3000000000000, -47.1000000000000, -43.7000000000000, -39.6000000000000,\\n -39.1000000000000, -31.2000000000000, -30.7000000000000, -30.1000000000000,\\n -24.4000000000000, -22.7000000000000, -18.7000000000000, -16.9000000000000,\\n -12.6000000000000, -10.8000000000000, -10.2000000000000, -4.01000000000000, 1.20000000000000,\\n 2.80000000000000, 3.70000000000000, 3.90000000000000, 6.20000000000000, 8.30000000000000,\\n 11.8000000000000, 14.5000000000000, 16, 18.2000000000000, 18.4000000000000, 19.9000000000000,\\n 24.6000000000000, 28.5200000000000, 33.8000000000000, 35, 35.4000000000000,\\n 35.6000000000000],\\n [69.1000000000000, 66, 58.2000000000000, 48, 78, 71.7000000000000, 31, 61.1000000000000,\\n 53.3000000000000, 81.1000000000000, 76, 70.2000000000000, 41.2000000000000, 64.4000000000000,\\n 80.2000000000000, 50.9000000000000, 75.2000000000000, 77.3000000000000, 37.8000000000000, 67,\\n 53.2000000000000, 72, 74.8000000000000, 54.7000000000000, 66.5000000000000, 35.9000000000000,\\n 25.7000000000000, 60.7000000000000, 50.5000000000000, 68.9000000000000, 27.3000000000000,\\n 70.3000000000000, 59.6000000000000, 44, 20.8000000000000, 61.7000000000000, 57.2000000000000,\\n 47, 36]])\\n stn_left = np.array([[-14.6, -13.2, -11.7, -9.10, -11.7, -13.2, -7.90, -10],\\n [-15.1, -15.1, -15.1, -12.6, -12.6, -12.6, -9.40, -10.1],\\n [-5.40, -7.20, -8.70, -8.70, -7.50, -5.10, -10.3, -7.80]])\\n grid_right = np.copy(grid_left)\\n grid_right[0, :] = grid_right[0, :] * -1\\n stn_right = np.copy(stn_left)\\n stn_right[0, :] = stn_right[0, :] * -1\\n\\n return grid_left, grid_right, stn_left, stn_right\",\n \"def breaking_of_the_box(size = (10, 10), verbose = False):\\n import numpy as np\\n r, l, u, d = \\\"R\\\", \\\"L\\\", \\\"U\\\", \\\"D\\\" # initiating walkind directions\\n np.random.seed(int(time.time()))\\n \\n # initiating field with walking directions\\n field = np.random.randint(1, 5, size = (10, 10))\\n field = np.where(field ==1, r, field)\\n field = np.where(field =='2', l, field)\\n field = np.where(field =='3', u, field)\\n field = np.where(field =='4', d, field)\\n\\n i, j = 0, 0\\n coordinates = []\\n \\n # iterating in a field\\n while (i<field.shape[0] and i>-1) and (j<field.shape[1] and j>-1):\\n prev_i,prev_j = i, j\\n coordinates.append((i, j)) \\n \\n copy_field = field.copy()\\n \\n if field[i][j] == r:\\n j+=1\\n elif field[i][j] == l:\\n j-=1\\n elif field[i][j] == u:\\n i-=1\\n elif field[i][j] == d:\\n i+=1\\n copy_field[i][j] = \\\"X\\\"\\n if verbose == True:\\n print(copy_field, \\\"#\\\"*48, sep = \\\"\\\\n\\\") #printing step by step position of a player\\n if (i, j) in coordinates:\\n # in case of infitine loop break\\n print(\\\"Player is stucked inside of a box\\\")\\n break\\n\\n else:\\n print(\\\"Player came out of the box\\\")\\n print(\\\"Coordinates of a breaking point\\\", \\\"(\\\", prev_i, prev_j, \\\")\\\")\",\n \"def move(self, ax, animate):\\n for obstacle in self.obstacles:\\n obstacle.pose[0] = obstacle.pose[0] + obstacle.dir[0] #add x direction vector\\n obstacle.pose[1] = obstacle.pose[1] + obstacle.dir[1] #add y direction vector\\n obstacle.pose[2] = obstacle.pose[2] + obstacle.dir[2] #add z direction vector\\n\\n if animate:\\n self.draw(ax)\\n\\n self.change_dir_if_Collide_boundary()\",\n \"def unstuck(self):\\n mask = Map.current_map.mask\\n \\n x_max, y_max = mask.get_size()\\n orig_x, orig_y = round(self.x), round(self.y)\\n x, y = orig_x , orig_y\\n unstuck_aggr = COLLISION_UNSTUCK_AGGRESSION\\n \\n # Vertical check for any open spots we could put the entity on...\\n while y > 0:\\n if not mask.get_at((x, y)):\\n self.y = y\\n self.vy = -unstuck_aggr\\n return\\n y -= unstuck_aggr\\n y = orig_y\\n while y < y_max:\\n if not mask.get_at((x, y)):\\n self.y = y\\n self.vy = unstuck_aggr\\n return\\n y += unstuck_aggr\\n y = orig_y\\n \\n # Horizontal spots?\\n while x > 0:\\n if not mask.get_at((x, y)):\\n self.x = x\\n self.vx = -unstuck_aggr\\n return\\n x -= unstuck_aggr\\n x = orig_x\\n while x < x_max:\\n if not mask.get_at((x, y)):\\n self.x = x\\n self.vx = unstuck_aggr\\n return\\n x += unstuck_aggr\\n x = orig_x\\n \\n # Diagonal spots\\n while x > 0 and y > 0:\\n if not mask.get_at((x, y)):\\n self.x, self.y = x, y\\n self.vx, self.vy = -unstuck_aggr, -unstuck_aggr\\n return\\n x, y = x - unstuck_aggr, y - unstuck_aggr\\n x, y = orig_x, orig_y\\n while x < x_max and y < y_max:\\n if not mask.get_at((x, y)):\\n self.x, self.y = x, y\\n self.vx, self.vy = unstuck_aggr, unstuck_aggr\\n return\\n x, y = x + unstuck_aggr, y + unstuck_aggr\\n x, y = orig_x, orig_y\\n while x > 0 and y < y_max:\\n if not mask.get_at((x, y)):\\n self.x, self.y = x, y\\n return\\n x, y = x - unstuck_aggr, y + unstuck_aggr\\n x, y = orig_x, orig_y\\n while x < x_max and y > 0:\\n if not mask.get_at((x, y)):\\n self.x, self.y = x, y\\n return\\n x, y = x + unstuck_aggr, y - unstuck_aggr\\n x, y = orig_x, orig_y\\n \\n # All right, I officially give up now.\\n print(\\\"Couldn't unstuck object!\\\")\",\n \"def boundary(self):\\n if self.pos.x < 0:\\n self.pos.x = 0\\n if self.pos.x > WIDTH - 48:\\n self.pos.x = WIDTH - 48\\n if self.pos.y < 0:\\n self.pos.y = 0\\n if self.pos.y > HEIGHT - 48:\\n self.pos.y = HEIGHT - 48\\n\\n self.rect.topleft = self.pos\",\n \"def move_west(self):\\n self.horizontal = (self.horizontal * 2)[1:5]\\n self.vertical[0] = self.horizontal[1]\\n self.vertical[2] = self.horizontal[3]\",\n \"def move_of_king_and_rook(self, from_row, from_col, to_row, to_col): \\n #provjere da li su kraljevi ili topovi inicirali pomijeranje\\n if(from_row == 7 and from_col == 0):\\n self.wrl_moved = True\\n elif(from_row == 7 and from_col == 7):\\n self.wrr_moved = True\\n elif(from_row == 7 and from_col == 4):\\n self.wk_moved = True\\n elif(from_row == 0 and from_col == 0):\\n self.brl_moved = True\\n elif(from_row == 0 and from_col == 7):\\n self.brr_moved = True\\n elif(from_row == 0 and from_col == 4):\\n self.bk_moved = True\\n \\n #provjera da li je neko pojeo topove\\n if(to_row == 7 and to_col == 0):\\n self.wrl_moved = True\\n elif(to_row == 7 and to_col == 7):\\n self.wrr_moved = True\\n elif(to_row == 0 and to_col == 0):\\n self.brl_moved = True\\n elif(to_row == 0 and to_col == 7):\\n self.brr_moved = True\",\n \"def calculate_leg_xy_limits(self, visualize=False):\\n \\n #Find the fixed plate position at the \\\"0\\\" point\\n gonio_zero = copy.copy(self)\\n gonio_zero.relative_sample_position = column([0.0, 0.0, 0.0]) #Tell the sample to be centered well.\\n gonio_zero.getplatepos(0.0, 0.0, 0.0)\\n fixed_plate_zero = np.copy(gonio_zero.fixed_plate)\\n #This defines the center of the following matrices\\n self.fixed_plate_zero = fixed_plate_zero\\n \\n #Now we generate a matrix of allowed positions around those points.\\n self.leg_safe_xaxis = np.arange(-self.travel, self.travel, self.leg_safe_resolution)\\n self.leg_safe_zaxis = np.copy(self.leg_safe_xaxis)\\n\\n #Create the \\\"safe zone\\\" array, initialized to False\\n self.leg_safe_zone = np.zeros( (3, self.leg_safe_xaxis.size, self.leg_safe_zaxis.size), dtype=bool ) \\n\\n #Now make a reasonable approximation\\n real_travel_x = 12.5\\n real_travel_z = real_travel_x\\n for leg in range(3):\\n for i_x in range(self.leg_safe_xaxis.size):\\n x = self.leg_safe_xaxis[i_x]\\n if abs(x)<real_travel_x:\\n for i_z in range(self.leg_safe_zaxis.size):\\n z = self.leg_safe_zaxis[i_z]\\n if abs(z)<real_travel_z:\\n self.leg_safe_zone[leg, i_x, i_z] = True\\n# #Upper left corner of leg A (0)\\n# center = int(len(self.leg_safe_xaxis)/2)\\n# self.leg_safe_zone[0, :, :] = False\\n# self.leg_safe_zone[0, :center, :center] = True\\n# self.leg_safe_zone[1, :, :] = False\\n# self.leg_safe_zone[1, center:, 0:center] = True\\n# self.leg_safe_zone[2, :, :center] = False\\n\\n\\n if visualize:\\n pylab.figure(0)\\n pylab.hold(True)\\n for leg in range(3):\\n pylab.pcolor(self.leg_safe_xaxis+fixed_plate_zero[COORD_X, leg], self.leg_safe_zaxis+fixed_plate_zero[COORD_Z, leg], self.leg_safe_zone[leg, :, :].transpose())\\n pylab.xlabel(\\\"x\\\")\\n pylab.ylabel(\\\"z\\\")\\n pylab.title(\\\"Allowable XZ leg positions for the 3 legs.\\\")\\n pylab.draw()\\n pylab.axis('equal')\\n #pylab.show()\",\n \"def movement(self, walls: list):\\r\\n keys = pygame.key.get_pressed()\\r\\n\\r\\n if keys[pygame.K_LEFT]: # Angle of vue\\r\\n self.angle -= self.turn_speed\\r\\n if keys[pygame.K_RIGHT]:\\r\\n self.angle += self.turn_speed\\r\\n\\r\\n if keys[pygame.K_w]:\\r\\n next_x = self.x + round(self.speed * math.cos(self.angle)) # same formula then in raycast.ray_casting\\r\\n next_y = self.y + round(self.speed * math.sin(self.angle))\\r\\n if walls[int(next_y / game_settings.TILE)][int(next_x / game_settings.TILE)]:\\r\\n # if we're going into a wall,\\r\\n # we dont go into the wall.\\r\\n return\\r\\n\\r\\n self.x = next_x\\r\\n self.y = next_y\\r\\n\\r\\n if keys[pygame.K_s]:\\r\\n next_x = self.x - round(self.speed * math.cos(self.angle))\\r\\n next_y = self.y - round(self.speed * math.sin(self.angle))\\r\\n if walls[int(next_y / game_settings.TILE)][int(next_x / game_settings.TILE)]:\\r\\n return\\r\\n\\r\\n self.x = next_x\\r\\n self.y = next_y\\r\\n\\r\\n if keys[pygame.K_a]:\\r\\n next_x = self.x + round(self.speed * math.sin(self.angle))\\r\\n next_y = self.y - round(self.speed * math.cos(self.angle))\\r\\n if walls[int(next_y / game_settings.TILE)][int(next_x / game_settings.TILE)]:\\r\\n return\\r\\n\\r\\n self.x = next_x\\r\\n self.y = next_y\\r\\n\\r\\n if keys[pygame.K_d]:\\r\\n next_x = self.x - round(self.speed * math.sin(self.angle))\\r\\n next_y = self.y + round(self.speed * math.cos(self.angle))\\r\\n if walls[int(next_y / game_settings.TILE)][int(next_x / game_settings.TILE)]:\\r\\n return\\r\\n\\r\\n self.x = next_x\\r\\n self.y = next_y\",\n \"def get_target_zone_corners(self):\\n EL2 = self._zone_length / 2\\n self.c1_position = self.apply(self.zone_pose, (-EL2, -EL2, 0))\\n self.c2_position = self.apply(self.zone_pose, (-EL2, EL2, 0))\\n self.c3_position = self.apply(self.zone_pose, ( EL2, EL2, 0))\\n self.c4_position = self.apply(self.zone_pose, ( EL2, -EL2, 0))\",\n \"def detectBorders(self, points):\\n lane1 = []; lane2 = []\\n self.leftLane = [None for _ in range(int(np.floor(self.BIRDVIEW_HEIGHT / self.slideThickness)))]\\n self.rightLane = [None for _ in range(int(np.floor(self.BIRDVIEW_HEIGHT / self.slideThickness)))]\\n\\n pointMap = np.zeros((points.shape[0], 20))\\n prePoint = np.zeros((points.shape[0], 20))\\n postPoint = np.zeros((points.shape[0], 20))\\n\\n dis = 10\\n max1 = -1; max2 = -1\\n\\n ##\\n ## /!\\\\ UNSAFE LOOP, TODO: FIX\\n ##\\n for i in range(points.shape[0]):\\n for j in range(len(points[i])):\\n pointMap[i][j] = 1\\n prePoint[i][j] = -1\\n postPoint[i][j] = -1\\n\\n for i in reversed(range(points.shape[0] - 2)):\\n\\n for j in range(len(points[i])):\\n\\n err = 320\\n for m in range(1, min(points.shape[0] - 1 - i, 5)):\\n check = False ## TODO: why unused ?\\n\\n for k in range(len(points[i + 1])):\\n\\n (x_m, y_m) = points[i + m][k].pt\\n (x, y) = points[i][j].pt\\n\\n if (abs(x_m - x) < dis and abs(y_m - y) < err):\\n err = abs(x_m - x)\\n\\n pointMap[i][j] = pointMap[i + m][k] + 1\\n prePoint[i][j] = k\\n postPoint[i + m][k] = j\\n check = True\\n\\n break ## breaks out of the m loop. Why is it not conditioned by check ? TODO: ???\\n\\n if (pointMap[i][j] > max1):\\n max1 = pointMap[i][j]\\n posMax = cv2.KeyPoint(i, j, _size=0)\\n \\n else:\\n posMax = None\\n\\n for i in range(points.shape[0]):\\n for j in range(len(points[i])):\\n if posMax:\\n if (pointMap[i][j] > max2 and (i != posMax.pt[0] or j != posMax.pt[1]) and postPoint[i][j] == -1): #FIXME \\\"local variable 'posMax' referenced before assignment\\\" possible\\n max2 = pointMap[i][j]\\n posMax2 = cv2.KeyPoint(i, j, _size=0)\\n\\n\\n\\n if max1 == -1:\\n return\\n\\n # DEFINES LANE 1 POINTS\\n while (max1 >= 1):\\n (x,y) = points[int(posMax.pt[0])][int(posMax.pt[1])].pt\\n lane1.append(\\n [x,y]\\n )\\n if (max1 == 1):\\n break\\n\\n posMax = cv2.KeyPoint(\\n posMax.pt[0]+1,\\n prePoint[int(posMax.pt[0])][int(posMax.pt[1])],\\n _size=0\\n )\\n\\n max1 -= 1\\n\\n # DEFINES LANE 2 POINTS\\n while (max2 >= 1):\\n (x,y) = points[int(posMax2.pt[0])][int(posMax2.pt[1])].pt\\n lane2.append(\\n [x, y]\\n )\\n if (max2 == 1):\\n break\\n\\n posMax2 = cv2.KeyPoint(\\n posMax2.pt[0]+1,\\n prePoint[int(posMax2.pt[0])][int(posMax2.pt[1])],\\n _size=0\\n )\\n\\n max2-= 1\\n\\n subLane1 = np.array(lane1[0:5])\\n subLane2 = np.array(lane2[0:5])\\n\\n # checking if sublane has an empty value\\n\\n line1 = cv2.fitLine(subLane1, 2, 0, 0.01, 0.01)\\n line2 = cv2.fitLine(subLane2, 2, 0, 0.01, 0.01)\\n\\n try:\\n lane1X = (self.BIRDVIEW_WIDTH - line1[3]) * line1[0] / line1[1] + line1[2]\\n except:\\n lane1X = 0\\n\\n try:\\n lane2X = (self.BIRDVIEW_WIDTH - line2[3]) * line2[0] / line2[1] + line2[2]\\n except:\\n lane2X = 0\\n \\n if (lane1X < lane2X):\\n for i in range(len(lane1)):\\n self.leftLane[int(np.floor(lane1[i][1] / self.slideThickness ))] = lane1[i]\\n\\n for i in range(len(lane2)):\\n self.rightLane[int(np.floor(lane2[i][1] / self.slideThickness ))] = lane2[i]\\n\\n else:\\n\\n for i in range(len(lane1)):\\n self.rightLane[int(np.floor(lane1[i][1] / self.slideThickness ))] = lane1[i]\\n\\n for i in range(len(lane2)):\\n self.leftLane[int(np.floor(lane2[i][1] / self.slideThickness ))] = lane2[i]\",\n \"def init(self, windowsize:tuple):\\r\\n y_count, x_count = 3, 0 #< Set the starting counter for the look_up_table. y starts with three because the first three lines are just Nones\\r\\n # Creating the constant maze \\r\\n maze_size = windowsize[0], windowsize[1] - 2 * self.grid_size\\r\\n self.maze = pg.Surface(maze_size) \\r\\n \\r\\n \\r\\n \\r\\n # Draw the outermost rectangles on self.maze\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((0, 3 * self.grid_size), (28 * self.grid_size, 31 * self.grid_size)), 4)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((0 + self.grid_size // 2, 3 * self.grid_size + self.grid_size // 2),(27 * self.grid_size, 30 * self.grid_size)), 4) \\r\\n # Draw the inner rectangles\\r\\n for y in self.look_up_table[3 : -2]: #< y is a list of one row from the maze\\r\\n for x in y: #< x is a string that is decoded as already explained\\r\\n pos = [self.grid_size * x_count, self.grid_size * y_count]\\r\\n # Set reference position in the middle of one square\\r\\n pos[0] += self.grid_size // 2\\r\\n pos[1] += self.grid_size // 2\\r\\n x_count += 1\\r\\n # Check if x is rectangle\\r\\n if x != None and x[0] == 'r':\\r\\n # When the size of the string is equal or greater than 4 it's rectangle with a specific size and not just a border.\\r\\n if len(x) >= 4:\\r\\n # get the x and y size of the rectangle. x will be something like 'rx1_y1' x1 resprestens the size in x direction and y1 in y direction.\\r\\n xy_dim = x[1:].split(\\\"_\\\") \\r\\n xy_dim[0] = int(xy_dim[0])\\r\\n xy_dim[1] = int(xy_dim[1])\\r\\n rect = tuple(pos), (xy_dim[0] * self.grid_size , xy_dim[1] * self.grid_size )\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], rect, self.width)\\r\\n # If the last char is a w (white), u (up) or l (left) a line gets draw one a specific position \\r\\n if x[-1] == 'w':\\r\\n self.draw_line(self.maze, 'u', (x_count,y_count), True)\\r\\n if x[-1] == 'u' or x[-1] == 'l':\\r\\n if x_count == 0:\\r\\n self.draw_line(self.maze, x[-1], (len(y), y_count))\\r\\n else:\\r\\n self.draw_line(self.maze, x[-1], (x_count, y_count))\\r\\n \\r\\n y_count += 1\\r\\n x_count = 0\\r\\n # Just some cosmetic drawing\\r\\n pg.draw.rect(self.maze, Colors.colors['BLACK'], ((0, 12 * self.grid_size + self.grid_size // 2 + 4), (self.grid_size // 2 + 1, 10 * self.grid_size - 4)), 4)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLACK'], ((28 * self.grid_size - self.grid_size // 2 - 1, 12 * self.grid_size + self.grid_size // 2 + 4), (self.grid_size // 2 + 1, 10 * self.grid_size - 4)), 4)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((-self.width, 13 * self.grid_size), (5 * self.grid_size, 3 * self.grid_size)), self.width)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((-self.width, 19 * self.grid_size), (5 * self.grid_size, 3 * self.grid_size)), self.width)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((23 * self.grid_size, 13 * self.grid_size), (5 * self.grid_size + 10, 3 * self.grid_size)), self.width)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((23 * self.grid_size, 19 * self.grid_size), (5 * self.grid_size + 10, 3 * self.grid_size)), self.width)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((11 * self.grid_size, 16 * self.grid_size), (6 * self.grid_size, 3 * self.grid_size)), self.width)\\r\\n \\r\\n pg.draw.line(self.maze, Colors.colors['BLUE'], (0, 16 * self.grid_size + self.grid_size // 2 - 1), (self.grid_size // 2 + self.width, 16 * self.grid_size + self.grid_size // 2 - 1), self.width)\\r\\n pg.draw.line(self.maze, Colors.colors['BLUE'], (0, 18 * self.grid_size + self.grid_size // 2), (self.grid_size // 2 + self.width, 18 * self.grid_size + self.grid_size // 2), self.width)\\r\\n pg.draw.line(self.maze, Colors.colors['BLUE'], (self.grid_size * 28 - self.grid_size, 16 * self.grid_size + self.grid_size // 2 - 1), (self.grid_size * 28 + self.width, 16 * self.grid_size + self.grid_size // 2 - 1), self.width)\\r\\n pg.draw.line(self.maze, Colors.colors['BLUE'], (self.grid_size * 28 - self.grid_size, 18 * self.grid_size + self.grid_size // 2), (self.grid_size * 28 + self.width, 18 * self.grid_size + self.grid_size // 2), self.width)\\r\\n self.is_init = True\",\n \"def drawSolu(self): \\n vinemaze = MakeMaze()\\n solulist = vinemaze.build_maze(self.width-4, 0, (8,24))\\n \\n #draw starting point square at bottom right corner\\n start = pygame.Rect(self.width, self.height, -4, -4)\\n pygame.draw.rect(gameView.background, self.color, start)\\n dimenlist = []\\n \\n #determine the rectangle's starting coordinate, width, and height\\n for i in range(1, len(solulist)):\\n cur_coord = solulist[i]\\n prev_coord = solulist[i-1]\\n RectW = prev_coord[0] - cur_coord[0]\\n RectH = prev_coord[1] - cur_coord[1]\\n\\n #keep track of coordinates where non-overlapping vines occur \\n if RectH > 0:\\n dimenlist.append(prev_coord)\\n \\n #Increase thickness of vines, depending on if they lie vertical or horizontal \\n if abs(RectW) < abs(RectH):\\n newRectW = self.increasepix(RectW)\\n vine = pygame.Rect(cur_coord[0], cur_coord[1], newRectW, RectH) \\n else:\\n newRectH = self.increasepix(RectH)\\n vine = pygame.Rect(cur_coord[0], cur_coord[1], RectW, newRectH)\\n pygame.draw.rect(gameView.background, self.color, vine)\\n \\n #fill in the missing corners due to non-overlapping vines\\n for i in range(1, len(dimenlist)):\\n prevW = dimenlist[i][0]\\n prevH = dimenlist[i][1]\\n if prevW > 0:\\n fillcoord = (prevW, prevH)\\n fill = pygame.Rect(fillcoord[0], fillcoord[1], 4, 4)\\n pygame.draw.rect(gameView.background, self.color, fill)\\n\\n gameView.screen.blit(gameView.background,(0,0))\\n pygame.display.update()\",\n \"def world_to_grid(mapdata, wp):\\n WX = wp.x\\n WY = wp.y\\n resol = mapdata.info.resolution\\n # -0.5 but coordinates to center\\n gx = math.floor((WX - mapdata.info.origin.position.x) / resol - 0.5)\\n gy = math.floor((WY - mapdata.info.origin.position.y) / resol - 0.5)\\n return gx, gy\",\n \"def update(self):\\n self.on_left = (abs(self.x - self.maze.LEFT_VERT) <\\n self.WALL_TOLERANCE)\\n self.on_right = (abs(self.x - self.maze.RIGHT_VERT) <\\n self.WALL_TOLERANCE)\\n\\n self.on_top = (abs(self.y - self.maze.TOP_HORIZ) <\\n self.WALL_TOLERANCE)\\n self.on_bottom = (abs(self.y - self.maze.BOTTOM_HORIZ) <\\n self.WALL_TOLERANCE)\\n self.x = self.x + self.x_add\\n self.y = self.y + self.y_add\\n\\n # If the game is over and Pacman wins, stop moving\\n if self.gc.player_wins:\\n self.x_add = 0\\n self.y_add = 0\\n # If the game is over and Pacman loses, top moving and\\n # Open mouth to oblivion.\\n elif self.gc.pinky_wins:\\n self.open_close = 1\\n self.x_add = 0\\n self.y_add = 0\\n self.mouth_angle = self.mouth_angle + self.open_close\\n else:\\n if self.mouth_angle < 45:\\n self.open_close = self.mouth_speed\\n self.mouth_angle = self.mouth_angle + self.open_close\\n if self.mouth_angle < 0:\\n self.open_close = - self.mouth_speed\\n self.mouth_angle = self.mouth_angle + self.open_close\\n else:\\n while self.mouth_angle > 0:\\n self.open_close = - self.mouth_speed\\n self.mouth_angle = self.mouth_angle + self.open_close\\n self.eat_dots()\",\n \"def update_pos(self, game_field, all_ghost_out, windowsize):\\r\\n\\r\\n # If Pac-Man wants to change the direction into a direction, that is not the same or the opposite of the current direction, it could possible be a pre- or postturn\\r\\n if self.direction != self.last_dir and find_opposite(self.last_dir) != self.direction and self.state != '':\\r\\n self.pre_or_post_turn(game_field, all_ghost_out)\\r\\n\\r\\n # If Pac-Man moves, update his position depending on his direction\\r\\n if self.state == 'm':\\r\\n fak = 1\\r\\n if self.direction == 'u':\\r\\n self.pos[1] -= fak * self.speed\\r\\n elif self.direction == 'd':\\r\\n self.pos[1] += fak * self.speed\\r\\n elif self.direction == 'l':\\r\\n self.pos[0] -= fak * self.speed\\r\\n elif self.direction == 'r':\\r\\n self.pos[0] += fak * self.speed\\r\\n\\r\\n ongrid = (self.pos[0] % self.grid_size == 0 and self.pos[1] % self.grid_size == 0)\\r\\n\\r\\n # When Pac-Man is on grid check the field type he's on and in front of him\\r\\n if ongrid :\\r\\n field = game_field.possible_way(self.pos, self.last_dir)\\r\\n self.cnt_points(field, all_ghost_out)\\r\\n\\r\\n # When the next field is a wall of the maze, make Pac-Man stop moving, otherwise let him continue moving\\r\\n if field != None and field[0] == 'r':\\r\\n field2 = game_field.possible_way(self.pos, self.direction)\\r\\n self.cnt_points(field2, all_ghost_out)\\r\\n if field2 != None and field2[0] == 'r':\\r\\n self.state = ''\\r\\n else:\\r\\n self.state = 'm'\\r\\n\\r\\n # When the field in front of him is the end of a tunnel move Pac-Man to the other side\\r\\n if field == 'os':\\r\\n if self.direction == 'l':\\r\\n self.pos[0] = windowsize[0] \\r\\n elif self.direction == 'r':\\r\\n self.pos[0] = -self.grid_size\\r\\n\\r\\n # When the next field is a field Pac-Man can move on to, safe the latest direction in direction\\r\\n if (field == None or field[0] != 'r'):\\r\\n self.direction = self.last_dir[:]\\r\\n\\r\\n # Force Pacmans direction to drive through the tunnel, just to avoid graphical bugs\\r\\n if self.pos[0] < 0:\\r\\n self.direction = 'r'\\r\\n self.last_dir = 'r'\\r\\n elif self.pos[0] > windowsize[0] - self.grid_size:\\r\\n self.direction = 'l'\\r\\n self.last_dir = 'l'\",\n \"def _move_cursors_to_pos(self):\\n for axis in range(3):\\n x, y = self._vox[list(self._xy_idx[axis])]\\n self._images['cursor_v'][axis].set_xdata([x, x])\\n self._images['cursor_h'][axis].set_ydata([y, y])\\n self._zoom(0) # doesn't actually zoom just resets view to center\\n self._update_images(draw=True)\\n self._update_moved()\",\n \"def move(self):\\n # neighbor offsets\\n offset = [(-1, 1),(0, 1),(1, 1),(-1, 0),(1, 0),(-1, -1),(0, -1),(1, -1)]\\n for i in range(len(offset)):\\n x = self.x + offset[i][0] # neighboring coordinates\\n y = self.y + offset[i][1]\\n if self.island.animal(x, y) == 0: # neighboring spot is open\\n self.island.remove(self) # remove from current spot\\n self.x = x # new coordinates\\n self.y = y\\n self.island.register(self) # register new coordinates\\n break # finished with move\",\n \"def move(self):\\n # neighbor offsets\\n offset = [(-1, 1),(0, 1),(1, 1),(-1, 0),(1, 0),(-1, -1),(0, -1),(1, -1)]\\n for i in range(len(offset)):\\n x = self.x + offset[i][0] # neighboring coordinates\\n y = self.y + offset[i][1]\\n if self.island.animal(x, y) == 0: # neighboring spot is open\\n self.island.remove(self) # remove from current spot\\n self.x = x # new coordinates\\n self.y = y\\n self.island.register(self) # register new coordinates\\n break # finished with move\",\n \"async def unwindGrid(fps):\\n\\n rg = homeGrid() # get a grid\\n # overwrite the positions to the positions that the robots\\n # are reporting\\n for r in rg.robotDict.values():\\n await fps.positioners[r.id].update_position()\\n alpha, beta = fps.positioners[r.id].position\\n r.setAlphaBeta(alpha, beta)\\n\\n forwardPath, reversePath = generatePath(rg)\\n\\n await fps.send_trajectory(reversePath)\",\n \"def move(self, dx=0, dy=0):\\n\\n\\t\\tcurr = self.rots[self.rot]\\n\\n\\t\\t# within the NxM grid of this piece, what's the min/max x/y coords\\n\\t\\t# (ie, \\\"bounding box of pixels actually used\\\")\\n\\t\\t\\n\\t\\t# TODO: this isn't right!\\n\\n\\t\\t# min_x = min(b[y][0] for y in range(height) if \\n\\t\\t# max_x = max(r[-1] for r in curr)\\n\\t\\t# min_y = min(b[0][x] for x in range(width))\\n\\t\\t# max_y = max(b[-1][x] for x in range(width))\\n\\n\\t\\t# if \",\n \"def move(self):\\n\\n if self.rect.right >= SCREEN_WIDTH:\\n self.rect.right = SCREEN_WIDTH\\n elif self.rect.left <= 0:\\n self.rect.left = 0\\n #elif self.rect.right < SCREEN_WIDTH and self.rect.left: \\n \\n self.rect.move_ip(self.speed_p,0)\",\n \"def update(self):\\n\\n # move left - right\\n if self.left:\\n self.rect.x -= 2\\n else:\\n self.rect.x += 2\\n if abs(self.rect.x - self.originx) == 150:\\n self.left = True\\n elif abs(self.rect.x - self.originx) == 0:\\n self.left = False\",\n \"def update(self):\\r\\n if self.right > games.screen.width or self.left < 0:\\r\\n self.dx = -self.dx\\r\\n \\r\\n if self.bottom > games.screen.height or self.top < 0:\\r\\n self.dy = -self.dy\",\n \"def calculate_next_move(self, visit):\\n self.depth += 1\\n new_boards = []\\n for vehicle_id in range(len(self.vehicles)):\\n vehicle = self.vehicles[vehicle_id]\\n state = self.get_board()\\n if vehicle.orientation == 0: #horizontal\\n if vehicle.x > 0: #left\\n if state[vehicle.y][vehicle.x-1] == \\\"..\\\":\\n self.vehicles[vehicle_id].x -=1\\n if not self.get_board().tostring() in visit:\\n if not self.get_board().all in new_boards:\\n new_board = deepcopy(self)\\n self.vehicles[vehicle_id].x += 1\\n new_board.parent = self\\n new_boards.append(new_board)\\n else:\\n self.vehicles[vehicle_id].x += 1\\n\\n if vehicle.x + vehicle.length <= (len(state)-1): #right\\n if state[vehicle.y][vehicle.x+vehicle.length] == \\\"..\\\":\\n self.vehicles[vehicle_id].x += 1\\n if not self.get_board().tostring() in visit:\\n if not self.get_board().all in new_boards:\\n new_board = deepcopy(self)\\n self.vehicles[vehicle_id].x -= 1\\n new_board.parent = self\\n new_boards.append(new_board)\\n else:\\n self.vehicles[vehicle_id].x -= 1\\n\\n else: #vertical\\n if vehicle.y - 1 >= 0: #up\\n if state[vehicle.y-1][vehicle.x] == \\\"..\\\":\\n self.vehicles[vehicle_id].y -= 1\\n if not self.get_board().tostring() in visit:\\n if not self.get_board().all in new_boards:\\n new_board = deepcopy(self)\\n self.vehicles[vehicle_id].y += 1\\n new_board.parent = self\\n new_boards.append(new_board)\\n else:\\n self.vehicles[vehicle_id].y += 1\\n\\n if vehicle.y + vehicle.length <= (len(state)-1):\\n if state[vehicle.y + vehicle.length][vehicle.x] == \\\"..\\\":#down\\n self.vehicles[vehicle_id].y += 1\\n if not self.get_board().tostring() in visit:\\n if not self.get_board().all in new_boards:\\n new_board = deepcopy(self)\\n self.vehicles[vehicle_id].y -= 1\\n new_board.parent = self\\n new_boards.append(new_board)\\n else:\\n self.vehicles[vehicle_id].y -= 1\\n self.depth -= 1\\n return new_boards\",\n \"def fill_walk(self):\\n\\n #Seguir tomando caminos hasta que se alcance la cantidad establecida.\\n while len(self.x_values) < self.num_points:\\n\\n #Decidir cual direccion tomar y cuan lejos ir hacia esa direccion.\\n x_direction = choice([1, -1])\\n x_distance = choice([0, 1, 2, 3, 4])\\n x_step = x_direction * x_distance\\n\\n y_direction = choice([1,-1])\\n y_distance = choice([0, 1, 2, 3, 4])\\n y_step = y_direction * y_distance\\n\\n #Ignorar movimientos nulos.\\n if x_step == 0 and y_step == 0:\\n continue\\n\\n #Calcular la nueva posicion.\\n x = self.x_values[-1] + x_step\\n y = self.y_values[-1] + y_step\\n\\n self.x_values.append(x)\\n self.y_values.append(y)\",\n \"def draw(self, win, player, displayList, enemyHitboxList, mapWidth, mapHeight):\\n cameraX = player.rect.left + (player.rect.width // 2) - (SCREEN_WIDTH // 2)\\n cameraY = player.rect.top + (player.rect.height // 2) - (SCREEN_HEIGHT // 2)\\n\\n # On centre la camera tant que le joueurs n'atteind pas les bords\\n if cameraX >= 0 and cameraX < mapWidth - SCREEN_WIDTH:\\n self.x = cameraX\\n\\n if cameraY >= 0 and cameraY < mapHeight - SCREEN_HEIGHT:\\n self.y = cameraY\\n\\n # Calcul de l'X du joueur en fonction s'il est en haut, bas ou entre les 2\\n if cameraX >= 0 and cameraX < mapWidth - SCREEN_WIDTH:\\n playerX = (SCREEN_WIDTH // 2) - (player.rect.width // 2)\\n else:\\n # Si le joueur est a droite\\\"\\\"\\\"\\n if cameraX >= mapWidth - SCREEN_WIDTH:\\n self.x = mapWidth - SCREEN_WIDTH\\n playerX = player.rect.left - mapWidth + SCREEN_WIDTH\\n # Si le joueur est a gauche\\\"\\\"\\\"\\n else:\\n self.x = 0\\n playerX = player.rect.left\\n\\n\\n # Calcul de l'Y du joueur en fonction s'il est a gauche, droite ou entre les 2\\n if cameraY >= 0 and cameraY < mapHeight - SCREEN_HEIGHT:\\n playerY = (SCREEN_HEIGHT // 2) - (player.rect.height // 2)\\n else:\\n # Si le joueur est en dessous\\n if cameraY >= mapHeight - SCREEN_HEIGHT:\\n self.y = mapHeight - SCREEN_HEIGHT\\n playerY = player.rect.top - mapHeight + SCREEN_HEIGHT\\n # Si le joueur est au dessus \\n else:\\n self.y = 0\\n playerY = player.rect.top\\n\\n for element in displayList:\\n element.draw(win,element.rect.left - self.x,element.rect.top - self.y)\\n #for elem in enemyHitboxList:\\n #pg.draw.rect(win, (200, 200, 200), pg.Rect(elem.left - self.x,elem.top - self.y, elem.width, elem.height))\\n player.draw(win, playerX, playerY)\",\n \"def updatePositionAndClean(self):\\n #X direction (num. rows) wall limit is the width of rectangular room\\n #Y direction (num. cols) wall limit is the height of rectangular room\\n #So (0,0) is in bottom LEFT corner--since rows start at zero at BOTTOM, not top\\n #direction works as you would think, with east at 0 or 360 degrees, 90 degrees at north,\\n #180 degrees at west, and 270 degrees at south direction\\n\\n #so each time unit, getNewPosition in SAME direction if you don't hit the wall\\n #if you hit the wall, then get a new RANDOM direction and then recalculate new position,\\n #making sure it is a valid position on grid, has not already been cleaned (tile visited)\\n\\n #So it makes no difference which direction you are moving in--the getNewPosition() function\\n #figures out mathematically what the next position is, based on grid, and you just have to\\n #determine whether you have hit the wall in that same direction--don't have to look at the\\n #number the degrees or radians in that particular direction--just moving in same direction,\\n #get next position, do you hit the wall, if so get new random direction, move that way, if you\\n #won't hit a wall that way.\\n\\n #If you don't hit a wall when you calculate a new direction, but the tile is clean already, then\\n #just go through the tiles and find one that is not clean yet, and move in the same direction.\\n \\n robotPos = self.getRobotPosition()\\n posx = robotPos.getX()\\n posy = robotPos.getY()\\n posx = math.floor(posx)\\n posy = math.floor(posy)\\n #First check if this position is clean:\\n #if (self.room.isTileCleaned(posx,posy) == False):\\n #then clean this tile!\\n #self.room.cleanTileAtPosition(robotPos)\\n #Now see where to move robot next on floor and clean that tile if it is not clean\\n #So first try moving in same direction--will you hit a wall?\\n newPos = self.position.getNewPosition(self.direction,self.speed)\\n newPosx = newPos.getX()\\n newPosy = newPos.getY()\\n newPosx = math.floor(newPosx)\\n newPosy = math.floor(newPosy)\\n if (self.room.isPositionInRoom(newPos)) and (self.room.isTileCleaned(newPosx,newPosy) == False):\\n #position is in room AND the tile has NOT been visited yet--since it's still DIRTY\\n #Should NOT have to check whether you hit a wall, since new position is in room\\n #so NO NEW DIRECTION needed yet--move in SAME direction\\n self.setRobotPosition(newPos)\\n self.room.cleanTileAtPosition(newPos)\\n #print \\\"Moved in SAME DIRECTION I was moving in last time, direction = \\\" + str(self.direction)\\n else: # (self.room.isPositionInRoom(newPos) == False) or (self.room.isTileCleaned(newPosx, newPosy) == True):\\n # either HIT WALL -- OR -- tile already cleaned -- so calculate new RANDOM direction\\n\\n #NOTE: this works until you are surrounded by tiles that have no next step tile that has not already been\\n #cleaned?\\n #?? think a problem is that if all surrounding tiles are already clean, then, in that case,\\n #you can get stuck in situation where you keep recalculating a new random direction, but when you take a step,\\n #all the next tiles have already been cleaned, and you get stuck in a loop, so in this case, you must\\n #not recalculate a new direction, but rather keep going in same direction until you find a tile not clean,\\n #and jump to that tile instead, and go from there.\\n #So find this case--see if that corrects this issue!\\n \\n keepTryingNewDirection = True\\n while (keepTryingNewDirection == True):\\n self.direction = random.randrange(0,359) #get new random direction\\n newPos = self.position.getNewPosition(self.direction,self.speed) #get new next position step with new direc.\\n newPosx = newPos.getX()\\n newPosy = newPos.getY()\\n newPosx = math.floor(newPosx)\\n newPosy = math.floor(newPosy)\\n if (self.room.isPositionInRoom(newPos)) and (self.room.isTileCleaned(newPosx,newPosy) == False):\\n #new position in new direction is in room, and the tile has not been cleaned yet\\n #so new direction and new tile to clean found!\\n self.setRobotPosition(newPos)\\n self.room.cleanTileAtPosition(newPos)\\n #print \\\"Moved in NEW DIRECTION I was moving in last time, direction = \\\" + str(self.direction)\\n keepTryingNewDirection = False\\n elif (self.room.isPositionInRoom(newPos) == False):\\n #new position in new direction NOT in room -- try again!\\n #print \\\"new direction found a new position not in room --hit wall--try again! direction = \\\" + str(self.direction)\\n continue\\n else:\\n #print \\\"new direction produced new position in room but tile already clean--try again?! direction = \\\" + str(self.direction)\\n #print \\\"first check to see if all tiles have already been cleaned.\\\"\\n #?? Any other checks needed here? list of tiles visited? is this really needed??\\n #calculate list of cells not clean yet\\n tilesCleaned = []\\n allSurroundingTilesClean = False\\n foundTileUnclean = False\\n saveWidth = 0\\n saveHeight = 0\\n for i in range(0,self.room.width):\\n for j in range(0,self.room.height):\\n if (self.room.isTileCleaned(i,j) == False):\\n saveWidth = i\\n saveHeight = j\\n foundTileUnclean = True\\n else:\\n #print \\\"appending to tiles cleaned: tile: i = \\\" + str(i) + \\\" j = \\\" + str(j)\\n tilesCleaned.append((i,j)) #make list of tiles cleaned\\n if (foundTileUnclean == True):\\n #print \\\"not all tiles are clean!--start here rather than getting new direc. i = \\\" + str(saveWidth) + \\\" j = \\\" + str(saveHeight)\\n newPos = Position(saveWidth,saveHeight)\\n self.setRobotPosition(newPos)\\n self.room.cleanTileAtPosition(newPos)\\n #print \\\"Found new tile that was not clean! current direc. \\\" + str(self.direction)\\n #print \\\"tile location x = \\\" + str(saveWidth) + \\\" y = \\\" + str(saveHeight)\\n keepTryingNewDirection = False\\n else:\\n keepTryingNewDirection = False\\n #print \\\"all tiles clean! stop cleaning!-- do not look for new direction! should be done.\\\"\\n\\n #for tile in tilesCleaned:\\n #print tile\",\n \"def pushing_planning(object, object_pose1_world, object_pose2_world,\\n palm_pose_l_object, palm_pose_r_object, arm='r', pusher_angle=0.0):\\n primitive_name = 'pushing'\\n #0. get initial palm poses in world frame\\n palm_poses_initial_world = planning_helper.palm_poses_from_object(\\n object_pose=object_pose1_world,\\n palm_pose_l_object=palm_pose_l_object,\\n palm_pose_r_object=palm_pose_r_object)\\n\\n #1. Convert pose to 2d pose\\n object_initial_planar_pose = planning_helper.get_2d_pose(object_pose1_world)\\n object_final_planar_pose = planning_helper.get_2d_pose(object_pose2_world)\\n\\n #2.\\n configurations_transformed, N_star, object_pose_2d_list, t_star = planning_helper.dubins_trajectory(\\n q0=object_initial_planar_pose,\\n qf=object_final_planar_pose,\\n radius=0.125,\\n velocity_real=0.05,\\n step_size=0.015,\\n contact_angle=pusher_angle)\\n # 3. iterate through trajectory and compute robot i)poses and ii)joints\\n object_pose_world_list = []\\n palm_poses_world_list = []\\n palm_pose_l_world_list = []\\n palm_pose_r_world_list = []\\n for counter, object_pose_2d in enumerate(object_pose_2d_list):\\n # 4. get 3d object pose from 2d\\n object_pose__world = planning_helper.get3dpose_object(\\n pose2d=object_pose_2d,\\n pose3d_nominal=object_pose1_world)\\n if arm=='r':\\n palm_pose_l_world = palm_poses_initial_world[0]\\n palm_pose_r_world = util.convert_reference_frame(\\n pose_source=palm_pose_r_object,\\n pose_frame_target=util.unit_pose(),\\n pose_frame_source=object_pose__world,\\n frame_id=\\\"yumi_body\\\",\\n )\\n else:\\n palm_pose_l_world = util.convert_reference_frame(\\n pose_source=palm_pose_l_object,\\n pose_frame_target=util.unit_pose(),\\n pose_frame_source=object_pose__world,\\n frame_id=\\\"yumi_body\\\",\\n )\\n palm_pose_r_world = palm_poses_initial_world[1]\\n object_pose_world_list.append(object_pose__world)\\n palm_poses_world_list.append([palm_pose_l_world, palm_pose_r_world])\\n palm_pose_l_world_list.append(palm_pose_l_world)\\n palm_pose_r_world_list.append(palm_pose_r_world)\\n #5. return final plan\\n plan_dict = {}\\n plan_dict['palm_poses_world'] = palm_poses_world_list\\n plan_dict['palm_pose_l_world'] = palm_pose_l_world_list\\n plan_dict['palm_pose_r_world'] = palm_pose_r_world_list\\n plan_dict['primitive'] = primitive_name\\n plan_dict['object_poses_world'] = object_pose_world_list\\n plan_dict['name'] = 'push_object'\\n plan_dict['t'] = t_star\\n plan_dict['N'] = len(N_star)\\n return [plan_dict]\",\n \"def update(self):\\n # Desplazar izquierda/derecha\\n self.rect.x += self.cambio_x\\n global COL\\n COL = False\\n # Hemos chocado contra la pared despues de esta actualizacion?\\n lista_impactos_bloques = pygame.sprite.spritecollide(self, self.paredes, False)\\n for bloque in lista_impactos_bloques:\\n #Si nos estamos desplazando hacia la derecha, hacemos que nuestro lado derecho sea el lado izquierdo del objeto que hemos tocado-\\n if self.cambio_x > 0:\\n self.rect.right = bloque.rect.left\\n else:\\n # En caso contrario, si nos desplazamos hacia la izquierda, hacemos lo opuesto.\\n self.rect.left = bloque.rect.right\\n COL = True\\n \\n # Desplazar arriba/izquierda\\n self.rect.y += self.cambio_y\\n \\n # Comprobamos si hemos chocado contra algo\\n lista_impactos_bloques = pygame.sprite.spritecollide(self, self.paredes, False) \\n for bloque in lista_impactos_bloques:\\n \\n # Reseteamos nuestra posicion basandonos en la parte superior/inferior del objeto.\\n if self.cambio_y > 0:\\n self.rect.bottom = bloque.rect.top \\n else:\\n self.rect.top = bloque.rect.bottom \\n COL = True\",\n \"def orientWP(self):\\n import DraftGeomUtils\\n if hasattr(App, \\\"DraftWorkingPlane\\\"):\\n if len(self.node) > 1 and self.obj:\\n n = DraftGeomUtils.getNormal(self.obj.Shape)\\n if not n:\\n n = App.DraftWorkingPlane.axis\\n p = self.node[-1]\\n v = self.node[-2].sub(self.node[-1])\\n v = v.negative()\\n if not self.oldWP:\\n self.oldWP = App.DraftWorkingPlane.copy()\\n App.DraftWorkingPlane.alignToPointAndAxis(p, n, upvec=v)\\n if hasattr(Gui, \\\"Snapper\\\"):\\n Gui.Snapper.setGrid()\\n Gui.Snapper.restack()\\n if self.planetrack:\\n self.planetrack.set(self.node[-1])\",\n \"def adjust_position(self):\\n\\n # Adjust position for x-axis\\n r = self.rect.x % 30\\n if r != 0:\\n if r <= 16:\\n x = self.rect.x - r\\n else:\\n x = self.rect.x + (30 - r)\\n\\n else:\\n x = self.rect.x\\n\\n # Adjust position for y-axis\\n r = self.rect.y % 30\\n if r != 0:\\n if r <= 16:\\n y = self.rect.y - r\\n else:\\n y = self.rect.y + (30 - r)\\n else:\\n y = self.rect.y\\n\\n return x, y\",\n \"def update(self):\\n self.rect.x += self.dx\\n self.rect.y += self.dy\\n # Verifica se o bloco atingiu a borda\\n if self.rect.x < LARG_BORDA:\\n self.rect.x = LARG_BORDA\\n if self.rect.x > WINDOWWIDTH - LARG_BORDA - self.rect.width:\\n self.rect.x = WINDOWWIDTH - LARG_BORDA - self.rect.width\\n if self.rect.y < LARG_BORDA:\\n self.rect.y = LARG_BORDA\\n if self.rect.y > WINDOWHEIGHT - LARG_BORDA - self.rect.height:\\n self.rect.y = WINDOWHEIGHT - LARG_BORDA - self.rect.height\\n\\n if self.vel_max != 0:\\n self.dx = random.randint(-self.vel_max, self.vel_max)\\n self.dy = random.randint(-self.vel_max, self.vel_max)\",\n \"def move(s, a, beta):\\n # update velocity with probability 1-beta\\n global V\\n if np.random.choice(2, p=[beta, 1-beta]) == 1:\\n if a in [0, 3, 6] and V > 0: V -= 1\\n elif a in [2, 5, 8] and V < 3: V += 1\\n # else:\\n # print \\\"velocity not updated!\\\"\\n\\n r_border = range(6, 49, 7) # states on the right border\\n l_border = range(0, 49, 7) # states on the left border\\n t_border = range(7) # states on the top border\\n\\n units = range(V)\\n # move RIGHT of V units:\\n if a < len(ACTIONS) / 3:\\n for i in units:\\n WORLD[STATE2WORLD[s+i]] = '~' # draw my path gradualy in the world\\n # crash: reset world and velocities, return to start state\\n if s+i in r_border or s+i+1 in WALLS:\\n reset()\\n return START, CRASH\\n # nothing special: draw where I end up & return\\n WORLD[STATE2WORLD[s+V]] = 'O'\\n return s+V, STEP\\n\\n # move UP of V units:\\n elif a < 2*len(ACTIONS) / 3:\\n for i in units:\\n WORLD[STATE2WORLD[s-i*7]] = '|' # draw my path gradualy in the world\\n # crash: reset world and velocities, return to start state\\n if s-i*7 in t_border or s-(i+1)*7 in WALLS:\\n reset()\\n return START, CRASH\\n # nothing special: draw where I end up & return\\n WORLD[STATE2WORLD[s-V*7]] = 'O'\\n return s-V*7, STEP\\n\\n # move LEFT of V units:\\n elif a < len(ACTIONS):\\n for i in units:\\n WORLD[STATE2WORLD[s-i]] = '~' # draw my path gradualy in the world\\n # goal: draw where I end up & return\\n if s-i-1 in GOALS:\\n WORLD[STATE2WORLD[s-i-1]] = 'O'\\n return s-i-1, WIN\\n # crash: reset world and velocities, return to start state\\n elif s-i in l_border or s-i-1 in WALLS:\\n reset()\\n return START, CRASH\\n # nothing special: draw where I end up & return\\n WORLD[STATE2WORLD[s-V]] = 'O'\\n return s-V, STEP\\n\\n return s, STEP # should never happen\",\n \"def move_buildings(self):\",\n \"def move(self, rel_pos):\\n self.pos = (self.pos[0] + rel_pos[0] * GRID, self.pos[1] + rel_pos[1] * GRID)\",\n \"def _walk(self):\\n new_pos = self.rect.move((self.move, 0)) # move 9 pixel to the right per frame\\n if self.rect.left < self.area.left or self.rect.right > self.area.right:\\n self.move = -self.move # move to the opposite direction when the chimp position exceeds the screen\\n new_pos = self.rect.move((self.move, 0))\\n self.image = pygame.transform.flip(\\n self.image, 1, 0\\n ) # mirror the chimp to make it looks like turning around\\n self.rect = new_pos\",\n \"def apply_sliding_windows(self, binary_warped, leftx_base, rightx_base):\\r\\n # Choose the number of sliding windows\\r\\n nwindows = 9\\r\\n # Set height of windows\\r\\n window_height = np.int(binary_warped.shape[0] / nwindows)\\r\\n # Identify the x and y positions of all nonzero pixels in the image\\r\\n nonzero = binary_warped.nonzero()\\r\\n nonzeroy, nonzerox = np.array(nonzero[0]), np.array(nonzero[1])\\r\\n # Current positions to be updated for each window\\r\\n leftx_current, rightx_current = leftx_base, rightx_base\\r\\n # Set the width of the windows +/- margin\\r\\n margin = 100\\r\\n # Set minimum number of pixels found to recenter window\\r\\n minpix = 50\\r\\n # Create empty lists to receive left and right lane pixel indices\\r\\n left_lane_inds, right_lane_inds = [], []\\r\\n\\r\\n # Step through the windows one by one\\r\\n # Create an output image to draw on and visualize the result\\r\\n out_img = np.dstack((binary_warped, binary_warped, binary_warped)) * 255\\r\\n for window in range(nwindows):\\r\\n # Identify window boundaries in x and y (and right and left)\\r\\n win_y_low = binary_warped.shape[0] - (window + 1) * window_height\\r\\n win_y_high = binary_warped.shape[0] - window * window_height\\r\\n win_xleft_low, win_xleft_high = leftx_current - margin, leftx_current + margin\\r\\n win_xright_low, win_xright_high = rightx_current - margin, rightx_current + margin\\r\\n # Draw the windows on the visualization image\\r\\n if self.debug:\\r\\n cv2.rectangle(out_img,(win_xleft_low,win_y_low),(win_xleft_high,win_y_high),(0,255,0), 2)\\r\\n cv2.rectangle(out_img,(win_xright_low,win_y_low),(win_xright_high,win_y_high),(0,255,0), 2)\\r\\n # Identify the nonzero pixels in x and y within the window\\r\\n good_left_inds = ((nonzeroy >= win_y_low) & (nonzeroy < win_y_high) & (nonzerox >= win_xleft_low) & (\\r\\n nonzerox < win_xleft_high)).nonzero()[0]\\r\\n good_right_inds = ((nonzeroy >= win_y_low) & (nonzeroy < win_y_high) & (nonzerox >= win_xright_low) & (\\r\\n nonzerox < win_xright_high)).nonzero()[0]\\r\\n # Append these indices to the lists\\r\\n left_lane_inds.append(good_left_inds)\\r\\n right_lane_inds.append(good_right_inds)\\r\\n # If you found > minpix pixels, recenter next window on their mean position\\r\\n if len(good_left_inds) > minpix:\\r\\n leftx_current = np.int(np.mean(nonzerox[good_left_inds]))\\r\\n if len(good_right_inds) > minpix:\\r\\n rightx_current = np.int(np.mean(nonzerox[good_right_inds]))\\r\\n if self.debug:\\r\\n cv_rgb = cv2.cvtColor(out_img.astype(np.uint8), cv2.COLOR_BGR2RGB)\\r\\n plt.imshow(cv_rgb)\\r\\n #cv2.imshow('Sliding window computation',out_img)\\r\\n # Concatenate the arrays of indices\\r\\n left_lane_inds = np.concatenate(left_lane_inds)\\r\\n right_lane_inds = np.concatenate(right_lane_inds)\\r\\n if self.debug:\\r\\n self.fit_dict['left_lane_inds'] = left_lane_inds\\r\\n self.fit_dict['right_lane_inds'] = right_lane_inds\\r\\n\\r\\n # Extract left and right line pixel positions\\r\\n leftx, lefty = nonzerox[left_lane_inds], nonzeroy[left_lane_inds]\\r\\n rightx, righty = nonzerox[right_lane_inds], nonzeroy[right_lane_inds]\\r\\n return leftx, lefty, rightx, righty\",\n \"def cleanUpRigPose(self):\\n\\n # show the proxy geo\\n cmds.select(self.name + \\\"_mover_grp\\\", hi=True)\\n allNodes = cmds.ls(sl=True)\\n for node in allNodes:\\n if node.find(\\\"_proxy_geo\\\") != -1:\\n if cmds.nodeType(node) == \\\"mesh\\\":\\n parent = cmds.listRelatives(node, parent=True)[0]\\n cmds.lockNode(parent, lock=False)\\n cmds.setAttr(parent + \\\".v\\\", lock=False)\\n cmds.setAttr(parent + \\\".v\\\", 1)\\n cmds.lockNode(parent, lock=True)\\n\\n # unlock mover group for this module and make invisible\\n cmds.lockNode(self.name + \\\"_mover_grp\\\", lock=False)\\n cmds.setAttr(self.name + \\\"_mover_grp.v\\\", lock=False)\\n\\n cmds.setAttr(self.name + \\\"_mover_grp.v\\\", 0)\\n\\n cmds.setAttr(self.name + \\\"_mover_grp.v\\\", lock=True)\\n cmds.lockNode(self.name + \\\"_mover_grp\\\", lock=True)\\n\\n # get the joints created by this module and remove the constraints\\n joints = self.returnCreatedJoints\\n\\n # create mover name\\n networkNode = self.returnNetworkNode\\n baseName = cmds.getAttr(networkNode + \\\".baseName\\\")\\n\\n for joint in joints:\\n if cmds.objExists(joint + \\\"_mover_offset\\\"):\\n cmds.select(joint)\\n cmds.delete(constraints=True)\\n\\n else:\\n jointBaseName = joint\\n if self.name != baseName:\\n nameData = self.name.split(baseName)\\n\\n if nameData[0] != \\\"\\\":\\n jointBaseName = jointBaseName.partition(nameData[0])[2]\\n if nameData[1] != \\\"\\\":\\n jointBaseName = jointBaseName.partition(nameData[1])[0]\\n\\n if cmds.objExists(self.name + \\\"_\\\" + jointBaseName + \\\"_mover_offset\\\"):\\n cmds.select(joint)\\n cmds.delete(constraints=True)\",\n \"def move_dart(self):\\n global level\\n if level == 0:\\n self.rect.centerx+=self.delta\\n if self.rect.centerx >= 1000: \\n self.delta = -1\\n elif self.rect.centerx < 500:\\n self.delta = 1\\n elif level == 1:\\n self.rect.centery+=self.delta\\n if self.rect.centery <= 150: \\n self.delta = 2\\n elif self.rect.centery > 650:\\n self.delta = -2\\n elif level == 2:\\n self.rect.centerx+=self.delta #To make changes in both x and y direction\\n self.rect.centery+=self.delta\\n if self.rect.centerx < 100 or self.rect.centery <= 100: \\n self.delta = random.randint(1,10) #adds random speeds to the motion\\n elif self.rect.centerx >= 900 or self.rect.centery > 700:\\n self.delta = -random.randint(1,10)\",\n \"def update(self):\\r\\n # Desplaza el bloque un píxel hacia abajo. s\\r\\n if self.rect.left < 50 or self.rect.right > 600:\\r\\n self.speed[0] = -self.speed[0]\\r\\n if self.rect.top < 0 or self.rect.bottom > 200:\\r\\n self.speed[1] = -self.speed[1]\\r\\n self.rect.move_ip((self.speed[0], self.speed[1])) \\r\\n if self.rect.y > 500:\\r\\n self.rect.x = random.randrange(10,600) \\r\\n self.rect.y = random.randrange(-400,-200)\\r\\n self.rect.y += 5\",\n \"def update_position(self):\\n # clamp on upper and lower bounds\\n new_pos = self.position[1] + self.velocity\\n # TODO: proper centering on borders\\n if new_pos >= (config['globals']['HEIGHT'] - int(config['globals']['PAD_HEIGHT'] / 2)\\n or new_pos <= int(config['globals']['PAD_HEIGHT'] / 2)):\\n pass\\n else:\\n self.position[1] = new_pos\",\n \"def compute_refl(self, step, borders,obstacle):\\n\\n r = self.radius\\n v = self.velocity\\n x = self.position\\n projx = step*abs(np.dot(v,np.array([1.,0.])))\\n projy = step*abs(np.dot(v,np.array([0.,1.])))\\n\\n a = pygame.Rect(0,0,borders[3][0],borders[3][0])\\n b = pygame.Rect(0,borders[0][1]+borders[0][3],borders[3][0],borders[3][1]+borders[3][3])\\n c = pygame.Rect(borders[2][0]+borders[2][2],0,borders[3][0],borders[3][0])\\n d = pygame.Rect(borders[3][0]+borders[3][2],borders[1][1]+borders[1][3],borders[3][0],borders[3][0])\\n\\n if(a.collidepoint(*self.position) or b.collidepoint(*self.position) or c.collidepoint(*self.position) or d.collidepoint(*self.position)):\\n self.vafter *= 0\\n self.delete = True\\n\\n\\n\\n\\n else:\\n if (abs(x[0])-r -borders[0][0]-borders[0][2] < projx ) or (abs(borders[1][0]- x[0])-r < projx):\\n self.vafter[0] *= -1\\n\\n if abs(x[1])-r -(borders[2][1]+borders[2][3]) < projy or abs(borders[3][1]-x[1])-r < projy:\\n self.vafter[1] *= -1.\\n\\n if obstacle != None:\\n obs = pygame.Rect(*obstacle)\\n if obs.collidepoint(x[0] + r,x[1]):\\n self.vafter[0] = -20\\n if obs.collidepoint(x[0] - r,x[1]):\\n self.vafter[0] = 20\\n if obs.collidepoint(x[0],x[1]- r):\\n self.vafter[1] = 20\\n if obs.collidepoint(x[0], x[1]+ r):\\n self.vafter[1] = -20\",\n \"def move_all_boids_to_new_positions(self):\\r\\n #print(\\\"move boids to new positions\\\")\\r\\n for boid in self.boids:\\r\\n closeBoids = self.get_neighbouring_boids(boid, self.boids)\\r\\n \\r\\n # apply the boid algorithm\\r\\n boid.moveCloser(closeBoids)\\r\\n boid.moveWith(closeBoids) \\r\\n boid.moveAway(closeBoids, self.minDistance)\\r\\n \\r\\n # check for border so the boid deosn't fly into oblivion or migrate\\r\\n # North out of season\\r\\n if boid.x < (self.border - (self.ballrect.width/2)) and boid.velocity_x < 0:\\r\\n boid.velocity_x = -boid.velocity_x * random.random()\\r\\n if boid.x > (self.width - (self.ballrect.width/2)) and boid.velocity_x > 0:\\r\\n boid.velocity_x = -boid.velocity_x * random.random()\\r\\n if boid.y < (self.border - (self.ballrect.height/2)) and boid.velocity_y < 0:\\r\\n boid.velocity_y = -boid.velocity_y * random.random()\\r\\n if boid.y > (self.height - (self.border + (self.ballrect.height/2))) and boid.velocity_y > 0:\\r\\n boid.velocity_y = -boid.velocity_y * random.random()\\r\\n \\r\\n # velocity and position tweaked, let's move!\\r\\n boid.move(self.maxVelocity)\",\n \"def draw_world(est_pose, particles, world):\\r\\n\\r\\n # Fix the origin of the coordinate system\\r\\n offsetX = 100\\r\\n offsetY = 250\\r\\n\\r\\n # Constant needed for transforming from world coordinates to screen coordinates (flip the y-axis)\\r\\n ymax = world.shape[0]\\r\\n\\r\\n world[:] = CWHITE # Clear background to white\\r\\n\\r\\n # Find largest weight\\r\\n max_weight = 0\\r\\n for particle in particles:\\r\\n max_weight = max(max_weight, particle.getWeight())\\r\\n\\r\\n # Draw particles\\r\\n for particle in particles:\\r\\n x = int(particle.getX()) + offsetX\\r\\n y = ymax - (int(particle.getY()) + offsetY)\\r\\n colour = jet(particle.getWeight() / max_weight)\\r\\n cv2.circle(world, (x, y), 2, colour, 2)\\r\\n b = (int(particle.getX() + 15.0 * np.cos(particle.getTheta())) + offsetX,\\r\\n ymax - (int(particle.getY() - 15.0 * np.sin(particle.getTheta())) + offsetY))\\r\\n cv2.line(world, (x, y), b, colour, 2)\\r\\n\\r\\n # Draw landmarks\\r\\n lm0 = (int(landmarks[0][0] + offsetX),\\r\\n int(ymax - (landmarks[0][1] + offsetY)))\\r\\n lm1 = (int(landmarks[1][0] + offsetX),\\r\\n int(ymax - (landmarks[1][1] + offsetY)))\\r\\n lm2 = (int(landmarks[2][0] + offsetX),\\r\\n int(ymax - (landmarks[2][1] + offsetY)))\\r\\n lm3 = (int(landmarks[3][0] + offsetX),\\r\\n int(ymax - (landmarks[3][1] + offsetY)))\\r\\n \\r\\n cv2.circle(world, lm0, 5, CRED, 2)\\r\\n cv2.circle(world, lm1, 5, CGREEN, 2)\\r\\n cv2.circle(world, lm2, 5, CBLUE, 2)\\r\\n cv2.circle(world, lm3, 5, CYELLOW, 2)\\r\\n cv2.putText(world, 'LM 1',lm0, cv2.FONT_HERSHEY_SIMPLEX, 1, 255)\\r\\n cv2.putText(world, 'LM 2',lm1, cv2.FONT_HERSHEY_SIMPLEX, 1, 255)\\r\\n cv2.putText(world, 'LM 3',lm2, cv2.FONT_HERSHEY_SIMPLEX, 1, 255)\\r\\n cv2.putText(world, 'LM 4',lm3, cv2.FONT_HERSHEY_SIMPLEX, 1, 255)\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n # Draw estimated robot pose\\r\\n a = (int(est_pose.getX()) + offsetX, ymax - (int(est_pose.getY()) + offsetY))\\r\\n b = (int(est_pose.getX() + 15.0 * np.cos(est_pose.getTheta())) + offsetX,\\r\\n ymax - (int(est_pose.getY() - 15.0 * np.sin(est_pose.getTheta())) + offsetY))\\r\\n cv2.circle(world, a, 5, CMAGENTA, 2)\\r\\n cv2.line(world, a, b, CMAGENTA, 2)\",\n \"def rotateRect(rectList, breakingBrick, itemsList, enemiesList, bullets, gunsList, points):\\n X, Y, ENMYVX, ENMYVY, ENMYIDLE, ENMYINFLOOR = 0, 1, 4, 5, 6, 7\\n GUNSTATE, GUNCOUNT, GUNTYPE = 4, 5, 6\\n # Deleting any offscreen Rects\\n for index in range(len(breakingBrick) - 1, -1, -1): # Going through all of the brick debris and deleting them once they exit below the screen\\n if breakingBrick[index][1] > 600:\\n del breakingBrick[index]\\n for list in range(len(itemsList)): # Going through all of the items and deleting them once they scroll off the screen\\n for item in range(len(itemsList[list]) - 1, -1, -1):\\n if itemsList[list][item][0] < -300 or itemsList[list][item][1] > 650:\\n del itemsList[list][item]\\n for list in range(len(rectList)): # Going through all of the rects and deleting them once they scroll off the screen\\n for rect in range(len(rectList[list]) - 1, -1, -1):\\n if rectList[list][rect][0] < -700:\\n del rectList[list][rect]\\n for list in range(len(enemiesList)): # Going through all of the enemies and deleting them once they scroll off the screen\\n for rect in range(len(enemiesList[list]) - 1, -1, -1):\\n if enemiesList[list][rect][0] < -300 or enemiesList[list][rect][1] > 650:\\n del enemiesList[list][rect]\\n for point in range(len(points) - 1, -1, -1): # Going through all of the points indicators and deleting them once the counter reaches zero\\n if points[point][2] == 0:\\n del points[point]\\n # Activating and deactivating all enemies\\n for list in range(len(enemiesList)): # Going through all of the enemies\\n for enemy in range(len(enemiesList[list]) - 1, -1, -1):\\n if enemiesList[list] == goombas or enemiesList[list] == spinys: # If they are goombas or spinys\\n # Activating goombas and spinys if they get close to the screen\\n if enemiesList[list][enemy][ENMYIDLE] == 0 and enemiesList[list][enemy][X] < 800:\\n enemiesList[list][enemy][ENMYIDLE] = 1\\n # Deleting them if they are crushed by mario and the death counter reaches zero\\n elif enemiesList[list][enemy][ENMYIDLE] == 2 and enemiesList[list][enemy][ENMYINFLOOR] == 0:\\n points.append([enemiesList[list][enemy][0], enemiesList[list][enemy][1], 40, 100])\\n del enemiesList[list][enemy]\\n elif enemiesList[list] == bullets: # If they are bullets\\n # Deleting bullets if they are too far off screen\\n if enemiesList[list][enemy][0] < -1600 or enemiesList[list][enemy][0] > 1600:\\n del enemiesList[list][enemy]\\n for gun in range(len(gunsList) - 1, -1, -1): # Going through all of the guns\\n # Activating guns if they get close and deleting them if they get too far back\\n if gunsList[gun][0] < 1600:\\n gunsList[gun][GUNSTATE] = 1\\n if gunsList[gun][0] < -1600:\\n del gunsList[gun]\",\n \"def grasp_planning_wf(palm_pose_l_world, palm_pose_r_world,\\n transformation, N=200, init=True):\\n primitive_name = 'grasping'\\n # 0. get initial palm poses in world frame\\n palm_poses_initial_world = [palm_pose_l_world, palm_pose_r_world]\\n\\n grasp_width = planning_helper.grasp_width_from_palm_poses(\\n palm_pose_l_world, palm_pose_r_world)\\n\\n # 1. get lifted palm poses in world frame\\n palm_poses_lifted_world = []\\n for pose in palm_poses_initial_world:\\n lifted_pose = copy.deepcopy(pose)\\n lifted_pose.pose.position.z += 0.05\\n palm_poses_lifted_world.append(lifted_pose)\\n\\n # 2. get final configuration\\n palm_poses_final_world = []\\n for pose in palm_poses_initial_world:\\n final_pose = util.transform_pose(\\n pose_source=pose,\\n pose_transform=transformation)\\n final_pose.pose.position.z += 0.0025\\n palm_poses_final_world.append(final_pose)\\n\\n # 3. get rotated + lifted palm pose in world frame\\n palm_poses_rotated_world = []\\n for pose in palm_poses_final_world:\\n rotated_pose = copy.deepcopy(pose)\\n rotated_pose.pose.position.z += 0.05\\n palm_poses_rotated_world.append(rotated_pose)\\n\\n # 3. generate pose plans\\n # 3.1. initialize plan\\n initial_plan = planning_helper.initialize_plan_wf(\\n palm_poses_initial=palm_poses_initial_world,\\n transformation=transformation,\\n primitive=primitive_name,\\n plan_name='initial_config')\\n\\n # 3.2. lift the object\\n lift_plan = planning_helper.move_cart_synchro_wf(\\n palm_poses_final=palm_poses_lifted_world,\\n grasp_width=grasp_width,\\n plan_previous=initial_plan,\\n primitive=primitive_name,\\n plan_name='lift_object',\\n N=10)\\n\\n # 3.3. rotate the object\\n rotate_plan = planning_helper.move_cart_synchro_wf(\\n palm_poses_final=palm_poses_rotated_world,\\n grasp_width=grasp_width,\\n plan_previous=lift_plan,\\n primitive=primitive_name,\\n plan_name='rotate_object_final',\\n N=N/2,\\n is_replan=True)\\n\\n # 3.4. place the object\\n place_plan = planning_helper.move_cart_synchro_wf(\\n palm_poses_final=palm_poses_final_world,\\n grasp_width=grasp_width,\\n plan_previous=rotate_plan,\\n primitive=primitive_name,\\n plan_name='place_object',\\n N=20)\\n return [lift_plan] + [rotate_plan] + [place_plan]\",\n \"def mover_bm_abajo(self):\\n self.nueva_posicion_posible_parte_superior = self.mapa.consultar_casilla_por_movimiento([self.casilla[0],\\n self.casilla[1] + 1],\\n [self.vertice_3[0], self.vertice_3[1] + self.velocidad],\\n [self.vertice_1[0], self.vertice_1[1]+ 5])\\n self.nueva_posicion_posible_parte_inferior = self.mapa.consultar_casilla_por_movimiento([self.casilla[0] + 1,\\n self.casilla[1] + 1],\\n [self.vertice_4[0],self.vertice_4[1] + self.velocidad],\\n self.vertice_1)\\n if self.nueva_posicion_posible_parte_superior[0] != 1 and self.nueva_posicion_posible_parte_inferior[0] != 1:\\n self.y += self.velocidad * (self.y <= 655)\\n self.posicion = [self.posicion[0],self.y]\\n self.casilla = [self.casilla[0], self.casilla[1] + self.nueva_posicion_posible_parte_superior[1]]\\n self.redefinir_vertices()\",\n \"def _align_toplevel_grid(self):\\n\\n # align origin with nearest multple of 128\\n self.mins[0] -= self.mins[0] % 128\\n self.mins[1] -= self.mins[1] % 128\\n\\n width = self.maxs[0] - self.mins[0]\\n height = self.maxs[1] - self.mins[1]\\n greatest_dim = max(width, height)\\n nearest_pow_two = int(2 ** np.ceil(np.log2(greatest_dim)))\\n width_adjustment = (nearest_pow_two - width)\\n height_adjustment = (nearest_pow_two - height)\\n\\n self.maxs[0] += width_adjustment\\n self.maxs[1] += height_adjustment\",\n \"def moveSpecialOb(self):\\n\\t\\tfor obJ in self.special:\\n\\t\\t\\tobJ.moveStep()\",\n \"def pad(self):\\n if self._mg_problem.boundaries[0] == 'periodic':\\n # left side\\n self.left[:] = self.mid[-self.borders[0]:]\\n # right side\\n self.right[:] = self.mid[:self.borders[1]]\\n elif self._mg_problem.boundaries[0] == 'dirichlet':\\n\\n # left from border\\n l_f_b = self.space_tensor[0:self.borders[0]]\\n # right_from_border\\n r_f_b = self.space_tensor[-self.borders[1]:]\\n # left side\\n self.left[:] = self.fl(l_f_b)\\n # right side\\n self.right[:] = self.fr(r_f_b)\",\n \"def drawmaze(self):\\n win=GraphWin(\\\"Perfect Maze\\\",600,600) \\n win.setBackground(\\\"White\\\")\\n scale=600/self.N #Used to generalize the size difference for the input of larger numbers. The background resolution/ grid size, N\\n\\n x1=scale\\n y1=0\\n x2=scale\\n y2=scale\\n\\n ##VERTICAL LINES ####\\n for i in range(self.N,0,-1):\\n for j in range(1,self.N):\\n if self.East[j][i]: #If East is true, draw a line.\\n \\n line=Line(Point(x1,y1),Point(x2,y2)) #lines | |\\n line.setFill(\\\"red\\\")\\n line.draw(win)\\n x1+=scale #Increment causes |->|\\n x2+=scale #Increment causes |->|\\n y1+=scale #Used to draw two more\\n y2+=scale #of the same spaced lines further down.\\n x1=scale #Reset\\n x2=scale #Reset\\n\\n\\n ##HORIZONTAL LINES##\\n x1=0\\n y1=scale\\n x2=scale\\n y2=scale\\n\\n\\n for i in range(self.N,1,-1):\\n for j in range(1,self.N+1):\\n if self.South[j][i]: #If South is true, draw a line.\\n \\n line=Line(Point(x1,y1),Point(x2,y2))\\n line.setFill(\\\"red\\\")\\n line.draw(win)\\n x1+=scale\\n x2+=scale\\n y1+=scale\\n y2+=scale\\n x1=0\\n x2=scale\\n\\n const=scale//5 #Very useful const which helps in placing circles on grid.\\n x=scale//2\\n y=600-scale//2\\n #radius=(scale-(4*scale//self.N))/2\\n radius=scale//2-(const)\\n start=Point(x,y) #START POINT HERE \\n circ=Circle(start,radius)\\n circ.setFill(\\\"Red\\\")\\n label=Text(start,\\\"Start\\\")\\n label.setFill(\\\"Black\\\")\\n circ.draw(win)\\n label.draw(win)\\n #print(self.CurrentCell)\\n #Using the current cell from the finished algorithm(last place visited), a circle can be placed at that point.\\n endpointx=(self.CurrentCell[0]-1)*scale +scale//2 ####MAKING END POINT X\\n endpointy=600-(self.CurrentCell[1]-1)*scale-scale//2 ####MAKING END POINT Y\\n endpoint=Point(endpointx,endpointy)\\n circ2=Circle(endpoint,radius)\\n circ2.setFill(\\\"White\\\")\\n label2=Text(endpoint,\\\"End\\\")\\n circ2.draw(win)\\n label2.draw(win)\\n \\n ###############CREATE KEY########################\\n \\n \\n keypointx=(self.MazeKey[0]-1)*scale +scale//2 ####MAKING END POINT X\\n keypointy=600-(self.MazeKey[1]-1)*scale-scale//2 ####MAKING END POINT Y\\n keypoint=Point(keypointx,keypointy)\\n circ3=Circle(keypoint,radius)\\n circ3.setFill(\\\"Blue\\\")\\n label3=Text(keypoint,\\\"Key\\\")\\n circ3.draw(win)\\n label3.draw(win)\\n pathcol=\\\"Yellow\\\"\\n##\\n\\n \\n for i in range(1,len(self.EntirePath)): \\n pathpointx=(self.EntirePath[i][0]-1)*scale +scale//2 ####MAKING END POINT X\\n pathpointy=600-(self.EntirePath[i][1]-1)*scale-scale//2 ####MAKING END POINT Y\\n pathpoint=Point(pathpointx,pathpointy)\\n drawpath=Circle(pathpoint,radius)\\n drawpath.setFill(pathcol)\\n if self.EntirePath[i]==self.KeyPath[-1]:\\n pathcol=\\\"Violet\\\"\\n label4=Text(keypoint,\\\"Key\\\")\\n label4.draw(win) \\n drawpath.draw(win)\\n drawpath.setWidth(1)\\n sleep(0.1)\\n \\n #drawpath.draw(win)\\n \\n label5=Text(endpoint,\\\"Maze Solved \\\")\\n label5.draw(win)\\n circ4=Circle(start,radius)\\n circ4.setFill(\\\"Red\\\")\\n circ4.draw(win) \\n label6=Text(start,\\\"Start \\\")\\n label6.draw(win)\",\n \"def move(self):\\r\\n if self.d == 'NORTH' and (self.y + 1) <= table_max_y:\\r\\n self.y += 1\\r\\n elif self.d == 'EAST' and (self.x + 1) <= table_max_x:\\r\\n self.x += 1\\r\\n elif self.d == 'SOUTH' and (self.y - 1) >= 0:\\r\\n self.y -= 1\\r\\n elif self.d == 'WEST' and (self.x - 1) >= 0:\\r\\n self.x -= 1\\r\\n else:\\r\\n print(\\\"Edge of Table Reached!\\\")\",\n \"def modify_box_coordinates(self, image, poles_detected):\\n for window, poles in poles_detected.items():\\n # Let's consider all poles detected on an image and modify their coordinates.\\n # If only one pole's been detected, just widen the box 60% both sides\\n if len(poles) == 1:\\n new_left_boundary = int(poles[0].BB_left * 0.4)\\n new_right_boundary = int(poles[0].BB_right * 1.6) if int(poles[0].BB_right * 1.6) <\\\\\\n image.shape[1] else (image.shape[1] - 2)\\n # Move upper border way up, often when a pole is close up many components do not get\\n # included in the box, as a result they do not get found\\n new_top_boundary = int(poles[0].BB_top * 0.1)\\n new_bot_boundary = int(poles[0].BB_bottom * 1.1) if int(poles[0].BB_bottom * 1.1) <\\\\\\n image.shape[0] else (image.shape[0] - 2)\\n\\n poles[0].update_object_coordinates(left=new_left_boundary,\\n top=new_top_boundary,\\n right=new_right_boundary,\\n bottom=new_bot_boundary)\\n else:\\n for pole in poles:\\n # If we've got 1+ poles on one frame or image, hence the shot was likely taken from\\n # further distance.\\n\\n # TO DO: Overlapping check here. If BBs overlap and a component happens to be in between,\\n # it will be detected twice\\n\\n new_left_boundary = int(pole.BB_left * 0.9)\\n new_right_boundary = int(pole.BB_right * 1.1) if int(pole.BB_right * 1.1) < \\\\\\n image.shape[1] else (image.shape[1] - 2)\\n new_top_boundary = int(pole.BB_top * 0.5)\\n new_bot_boundary = int(pole.BB_bottom * 1.1) if int(pole.BB_bottom * 1.1) < \\\\\\n image.shape[0] else (image.shape[0] - 2)\\n\\n pole.update_object_coordinates(left=new_left_boundary,\\n top=new_top_boundary,\\n right=new_right_boundary,\\n bottom=new_bot_boundary)\",\n \"def movePole(mario, marioStats, marioScore, frame, flagInfo, unisprite, isDone, forceTime):\\n PTS, COIN, LIVES = 0, 1, 2\\n X, Y, VX, VY, DIR, STATE = 0, 1, 2, 3, 4, 5\\n ONGROUND, JUMPFRAMES, INGROUND, ISCROUCH, ONPLATFORM, ISFALLING, ISANIMATING, INVULFRAMES = 0, 1, 2, 3, 4, 5, 6, 7\\n # Declaring flag pole Rects\\n poleRect = Rect(flagInfo[0][0], flagInfo[0][1], flagInfo[0][2], flagInfo[0][3])\\n flagRect = Rect(flagInfo[1][0], flagInfo[1][1], flagInfo[1][2], flagInfo[1][3])\\n offset = 0 # Offset for height\\n endPoint = 650 # Variable for the X coordinate of the castle door\\n if levelNum == 5: # If the level is 5, change the castle door position\\n endPoint = 690\\n if mario[STATE] == 1: # If Mario is big, change the offset\\n offset = 42\\n if flagRect.y < 451: # If the flag Y position is not past 451, bring it lower\\n flagInfo[1][1] += 4\\n if mario[Y] < 451 - offset: # If Mario is not att the bottom the pole\\n mario[Y] += 4 # Bring him lower\\n frame[0], frame[1] = 3, (unisprite * 0.8 % 2 + mario[STATE] * 2) # Rotate is sprite\\n if mario[Y] >= 451 - offset and flagRect.y >= 451 and frame[2] < 20: # If both Mario and the flag are at the bottom, and the animation counter hasn't reached 20\\n mario[X] = poleRect.x + 16 # Put Mario on the other side of the pole (still holding)\\n frame[0], frame[1] = 3, 4 + mario[STATE] # Keep his sprite of the grabbing pole sprite\\n frame[2] += 1 # Add to the animation counter\\n elif mario[Y] >= 451 - offset and flagRect.y >= 451 and frame[2] == 20: # If both Mario and the flag are at the bottom, and the animation counter is at 20\\n mario[X] = poleRect.right # Put Mario to the left of the pole\\n mario[Y] = 496 - offset # Put Mario on the ground, according to Mario's state\\n frame[2] += 1 # Add to the frame counter\\n if levelNum != 5: # If the level is 5, play the game done sound\\n playSound(doneSound, \\\"music\\\")\\n else: # If it's any other level, play the level done sound\\n playSound(doneworldSound, \\\"music\\\")\\n elif mario[Y] >= 451 - offset and flagRect.y >= 451: # If both the above are done\\n mario[VX] = 5 # Make Mario's speed 5\\n mario[VY] = 0 # Make his VY 0\\n mario[X] += 3.5 # Keep moving Mario right\\n marioStats[ONGROUND] = True\\n moveSprites(mario,marioStats,frame) # Use the moveSprites function to rotate sprites\\n if mario[X] > endPoint and mario[X] < 800: # If Mario reaches the castle and hasn't been moved yet\\n mario[X] = 800 # Move Mario off screen\\n playSound(timepointsSound, \\\"effect\\\") # Play the time to points conversion sound\\n if mario[X] > 800 and forceTime != 0: # If Mario has been moved off screen (meaning the time conversion has started)\\n forceTime -= 1 # Remove a second from the forced time\\n marioScore[PTS] += 100 # Add 100 to Marios points for each second removed\\n if forceTime == 0: # If the force time has reached zero (meaning the time conversion is done)\\n mixer.Channel(1).stop() # Stop the conversion sound\\n if not mixer.Channel(0).get_busy(): # If the end level sound is done, go to the next level\\n isDone = True\\n return [isDone, forceTime] # Return the isDone and forced time values for the game function to handle\",\n \"def swipeBase (self) :\\n grid = self.grid\\n\\n #we start by putting every tile up\\n for columnNbr in range(4) :\\n nbrZeros = 4 - np.count_nonzero(grid[:,columnNbr])\\n\\n for lineNbr in range(4) :\\n counter = 0\\n while (grid[lineNbr, columnNbr] == 0) and (counter < 4):\\n counter += 1\\n if np.count_nonzero(grid[lineNbr:4, columnNbr]) != 0 :\\n for remainingLine in range (lineNbr, 3) :\\n grid[remainingLine, columnNbr] = grid[remainingLine+1, columnNbr]\\n grid[3, columnNbr] = 0\\n\\n #now we do the additions\\n for lineNbr in range(3) :\\n if grid[lineNbr, columnNbr] == grid[lineNbr+1, columnNbr] :\\n grid[lineNbr, columnNbr] *= 2\\n for remainingLine in range (lineNbr+1, 3) :\\n grid[remainingLine, columnNbr] = grid[remainingLine+1, columnNbr]\\n grid[3, columnNbr] = 0\\n\\n return (grid)\",\n \"def detectWallCollision(self): \\n if self.posn_x > cw - self.ball_width: # Collision with right-hand container wall. \\n self.velocity_x = -self.velocity_x * self.coef_restitution # reverse direction. \\n self.posn_x = cw - self.ball_width * 1.1 # anti-stick to the wall \\n if self.posn_x < 1: # Collision with left-hand wall. \\n self.velocity_x = -self.velocity_x * self.coef_restitution \\n self.posn_x = 2 # anti-stick to the wall \\n if self.posn_y < self.ball_height: # Collision with ceiling. \\n self.velocity_y = -self.velocity_y * self.coef_restitution \\n self.posn_y = self.ball_height * 1.1 # ceiling collision anti-stick \\n if self.posn_y > ch - self.ball_height * 1.1 : # Floor collision. \\n self.velocity_y = - self.velocity_y * self.coef_restitution \\n self.posn_y = ch - self.ball_height * 1.1 # anti-stick. Prevents out-of-bounds ball loss (stickiness) \",\n \"def adjust_mario_for_y_ground_pipe_collisions(self, collider):\\n if self.mario.rect.bottom < collider.rect.bottom:\\n self.mario.y_vel = 0\\n self.mario.rect.bottom = collider.rect.top\\n elif self.mario.rect.top > collider.rect.top:\\n self.mario.y_vel = 7\\n self.mario.rect.top = collider.rect.bottom\",\n \"def move (self):\\n\\t\\tself.x += self.direction[0]\\n\\t\\tself.y += self.direction[1]\\n\\t\\tself.row = (self.y - 15) / 30\\n\\t\\tself.col = (self.x - 15) / 30\\n\\t\\tself.rowcol = (self.row,self.col)\\n\\t\\tself.draw()\",\n \"def _edit_border_tiles(self, vmf: VMF, seg_min: Vec, seg_max: Vec, border: bool, blacken: bool) -> None:\\n up = abs(self.up_axis)\\n forward = (seg_max - seg_min).norm()\\n norm_dir = self.normal().axis()\\n\\n tiledefs_up: list[tiling.TileDef] = []\\n tiledefs_dn: list[tiling.TileDef] = []\\n\\n overlay_len = int((seg_max - seg_min).mag())\\n\\n # We need to snap the axis normal_axis to the grid, since it could\\n # be forward or back.\\n min_pos = seg_min.copy()\\n min_pos[norm_dir] = min_pos[norm_dir] // 128 * 128 + 64\\n\\n u_ax, v_ax = Vec.INV_AXIS[up.axis()]\\n side_dir = Vec.dot(abs(Vec.cross(up, forward)), seg_min - min_pos)\\n side_ind = round((side_dir + 48) / 32, 2) # 0/1/2/3 for the center of tiles.\\n # 4.5 -> [4, 5] and 4 -> [4].\\n pos_iter = sorted({round(side_ind - 0.25), round(side_ind + 0.25)})\\n if u_ax == forward.axis():\\n uv_pos = [\\n (u, v)\\n for u in range(4)\\n for v in pos_iter\\n ]\\n elif v_ax == forward.axis():\\n uv_pos = [\\n (u, v)\\n for u in pos_iter\\n for v in range(4)\\n ]\\n else: # Should be impossible?\\n uv_pos = []\\n\\n for offset in range(64, overlay_len, 128):\\n # Each position on top or bottom, inset 64 from each end.\\n # First check if the tiles themselves are present, then check if any of the\\n # subtiles are present - blackening on the way if required.\\n pos = min_pos + offset * forward\\n tile_cat = []\\n try:\\n top_tile = tiling.TILES[\\n (pos + 128 * up).as_tuple(),\\n (-up).as_tuple()\\n ]\\n except KeyError:\\n pass\\n else:\\n tile_cat.append((tiledefs_up, top_tile))\\n try:\\n btm_tile = tiling.TILES[\\n (pos - 128 * up).as_tuple(),\\n up.as_tuple()\\n ]\\n except KeyError:\\n pass\\n else:\\n tile_cat.append((tiledefs_dn, btm_tile))\\n for tiledefs, tile in tile_cat:\\n found = False\\n for u, v in uv_pos:\\n subtile = tile[u, v]\\n if subtile.is_tile:\\n found = True\\n if blacken:\\n tile[u, v] = subtile.as_black\\n if found:\\n tiledefs.append(tile)\\n\\n if not border or (not tiledefs_up and not tiledefs_dn):\\n return\\n\\n overlay_thickness = options.get(int, 'fizz_border_thickness')\\n overlay_repeat = options.get(int, 'fizz_border_repeat')\\n flip_uv = options.get(bool, 'fizz_border_vertical')\\n\\n if flip_uv:\\n u_rep = 1.0\\n v_rep = overlay_len / overlay_repeat\\n else:\\n u_rep = overlay_len / overlay_repeat\\n v_rep = 1.0\\n\\n cent_pos = (seg_min + seg_max) / 2\\n\\n if tiledefs_up:\\n over = srctools.vmf.make_overlay(\\n vmf,\\n normal=-up,\\n origin=cent_pos + 64 * up,\\n uax=forward * overlay_len,\\n vax=Vec.cross(up, forward) * overlay_thickness,\\n material=texturing.SPECIAL.get(cent_pos + 64 * up, 'fizz_border'),\\n surfaces=[],\\n u_repeat=u_rep,\\n v_repeat=v_rep,\\n swap=flip_uv,\\n )\\n for tile in tiledefs_up:\\n tile.bind_overlay(over)\\n\\n if tiledefs_dn:\\n over = srctools.vmf.make_overlay(\\n vmf,\\n normal=up,\\n origin=cent_pos - 64 * up,\\n uax=forward * overlay_len,\\n vax=Vec.cross(-up, forward) * overlay_thickness,\\n material=texturing.SPECIAL.get(cent_pos - 64 * up, 'fizz_border'),\\n surfaces=[],\\n u_repeat=u_rep,\\n v_repeat=v_rep,\\n swap=flip_uv,\\n )\\n for tile in tiledefs_dn:\\n tile.bind_overlay(over)\",\n \"def make_move(self, direction):\\r\\n\\t\\tif direction == 0:\\r\\n\\t\\t\\tself.board[self.x][self.y], self.board[self.x-1][self.y] = self.board[self.x-1][self.y], self.board[self.x][self.y]\\r\\n\\t\\t\\tself.x -= 1\\r\\n\\r\\n\\t\\telif direction == 1:\\r\\n\\t\\t\\tself.board[self.x][self.y], self.board[self.x][self.y+1] = self.board[self.x][self.y+1], self.board[self.x][self.y]\\r\\n\\t\\t\\tself.y += 1\\r\\n\\r\\n\\t\\telif direction == 2:\\r\\n\\t\\t\\tself.board[self.x][self.y], self.board[self.x+1][self.y] = self.board[self.x+1][self.y], self.board[self.x][self.y]\\r\\n\\t\\t\\tself.x += 1\\r\\n\\r\\n\\t\\telif direction == 3:\\r\\n\\t\\t\\tself.board[self.x][self.y], self.board[self.x][self.y-1] = self.board[self.x][self.y-1], self.board[self.x][self.y]\\r\\n\\t\\t\\tself.y -= 1\",\n \"def create_grid(self):\\n\\n # initial point of the path\\n self.p0 = np.array([self.start_x, self.start_y])\\n self.pf = np.array([self.end_x, self.end_y]) # final point of the path\\n\\n self.l1 = np.linalg.norm(np.subtract(self.pf, self.p0))\\n self.l2 = 0.2 * self.l1\\n\\n # we define the 2 unit vectors self.d1 and self.d2 in which directions we are moving along\\n # then we apply to them the size of the desired displacement\\n self.d1 = np.subtract(self.pf, self.p0) / \\\\\\n (np.linalg.norm(np.subtract(self.pf, self.p0)))\\n\\n self.d2 = np.array([-self.d1[1], self.d1[0]])\\n self.d2 = self.d2/(np.linalg.norm(self.d2))\\n\\n # we create our grid moving with self.d1 and self.d2\\n # each point of the grid has the following properties:\\n # position, distance to self.d1, distance to self.pf, velocity\\n n_displacements_2 = 0\\n self.lines_list = []\\n\\n # variables for making easier the plotting afterwards\\n self.x_list_grid = []\\n self.y_list_grid = []\\n time_n = 1\\n\\n while True:\\n current_point = np.subtract(\\n self.p0, self.d2*(n_displacements_2*self.displacement))\\n current_length_2 = np.linalg.norm(\\n np.subtract(current_point, self.p0))\\n if current_length_2 > self.l2/2:\\n if time_n == 2:\\n break\\n else:\\n time_n += 1\\n self.lines_list = list(reversed(self.lines_list))\\n self.d2 = -1 * self.d2\\n n_displacements_2 = 1\\n current_point = np.subtract(\\n self.p0, self.d2*(n_displacements_2*self.displacement))\\n\\n line_points = []\\n self.x_list_grid.append(current_point[0])\\n self.y_list_grid.append(current_point[1])\\n\\n # TODO: add fish real prediction\\n line_points.append({\\n \\\"position\\\": current_point.tolist(),\\n \\\"distance_to_l1\\\": n_displacements_2*self.displacement,\\n \\\"distance_to_pf\\\": np.linalg.norm(np.subtract(self.pf, current_point)),\\n \\\"fish\\\": random.random()\\n })\\n\\n initial_point_1 = current_point\\n while True:\\n current_point = np.sum(\\n [current_point, self.d1 * self.displacement], axis=0)\\n current_length_1 = np.linalg.norm(\\n np.subtract(current_point, initial_point_1))\\n if current_length_1 >= self.l1:\\n current_point = self.pf - self.d2*n_displacements_2*self.displacement\\n self.x_list_grid.append(current_point[0])\\n self.y_list_grid.append(current_point[1])\\n # TODO: add fish real prediction\\n line_points.append({\\n \\\"position\\\": current_point.tolist(),\\n \\\"distance_to_l1\\\": n_displacements_2*self.displacement,\\n \\\"distance_to_pf\\\": np.linalg.norm(np.subtract(self.pf, current_point)),\\n \\\"fish\\\": random.random()\\n })\\n break\\n\\n self.x_list_grid.append(current_point[0])\\n self.y_list_grid.append(current_point[1])\\n\\n # TODO: add fish real prediction\\n line_points.append({\\n \\\"position\\\": current_point.tolist(),\\n \\\"distance_to_l1\\\": n_displacements_2*self.displacement,\\n \\\"distance_to_pf\\\": np.linalg.norm(np.subtract(self.pf, current_point)),\\n \\\"fish\\\": random.random()\\n })\\n\\n self.lines_list.append(line_points)\\n n_displacements_2 += 1\",\n \"def expanded_boundaries(self):\\n width = self._points[0][3][0] - self._points[0][1][0]\\n height = self._points[0][3][1] - self._points[0][1][1]\\n factor = np.multiply((width, height), Window.BORDER)\\n return (\\n np.subtract(self._points[0][1], factor),\\n np.add(self._points[0][3], factor))\",\n \"def update(self):\\n super().update()\\n if self.center_y > TOP_LIMIT:\\n self.center_y = BOTTOM_LIMIT\\n if self.center_y < BOTTOM_LIMIT:\\n self.center_y = TOP_LIMIT\\n\\n if self.center_x < 250:\\n self.change_x = (0.2) * OBJECTS_SPEED\\n elif self.center_x > SCREEN_WIDTH - 250:\\n self.change_x = (-0.2) * OBJECTS_SPEED\",\n \"def place_targets():\\n\\n \\n coords = []\\n while len(coords)<self.N_targets:\\n x = np.random.randint(self.BORDER_MARGIN,self.map_dimensions[1]+1-self.BORDER_MARGIN,size=1)[0]\\n y = np.random.randint(self.BORDER_MARGIN,self.map_dimensions[0]+1-self.BORDER_MARGIN,size=1)[0]\\n p = (x,y)\\n all_valid = True\\n for rect in self.coordinates__obstacles:\\n if not check_valid_placement(p,rect):\\n all_valid = False\\n break\\n if all_valid:\\n coords +=[p]\\n self.coordinates__targets = coords\",\n \"def move(self):\\n \\n self.rect.move_ip(0,self.speed) # Funcion para mover el enemigo especificando la velocidad xy\\n \\n if (self.rect.top > SCREEN_HEIGHT): # Condicion cuando llega a la parte inferior y no colisiono con el jugador\\n del self.surf #Libera memoria\\n del self.rect\\n self.randomNumber = random.choice([70,64,32]) # Su tamaño se asigna nuevamente\\n self.size = (self.randomNumber,self.randomNumber) #Se genera su tamaño como un cuadrado de lado aleatorio\\n self.surf = pygame.Surface(self.size) #Se genera la superficie que aparecera la pantalla\\n self.surf.fill(RED)\\n self.rect = self.surf.get_rect(center = (random.randint(40,SCREEN_WIDTH-40),0))# me da info de las coordenadas de surf\\n if(self.randomNumber == 32):\\n self.surf = self.imagen\\n elif(self.randomNumber ==64):\\n self.surf = self.imagen2\\n elif self.randomNumber ==70 :\\n self.surf = self.imagen3\",\n \"def moveStep(self):\\n\\t\\tif self.pos[0] < self.boundsX[0] or \\\\\\n\\t\\t\\tself.pos[0] > (self.boundsX[1] - self.width):\\n\\t\\t\\t\\tself.dir[0] *= -1\\n\\t\\tif self.pos[1] < self.boundsY[0] or \\\\\\n\\t\\t self.pos[1] > (self.boundsY[1] - self.height):\\n\\t\\t\\t\\tself.dir[1] *= -1\\n\\t\\t\\t\\n\\t\\tself.pos[0] += self.dir[0]*self.speed\\n\\t\\tself.pos[1] += self.dir[1]*self.speed\",\n \"def place_obstacles():\\n #Randomly generate different sized rectangles\\n #Soem may overlap, which gives more variety in shape of obstacles\\n xvals = np.random.randint(0,self.map_dimensions[1],size=self.N_obstacles)\\n yvals = np.random.randint(0,self.map_dimensions[0],size=self.N_obstacles)\\n lower_left = zip(xvals,yvals)\\n rects = []\\n for LL in lower_left:\\n x = LL[0]\\n y = LL[1]\\n wmax = self.map_dimensions[1] - x\\n w = np.random.randint(0,wmax,size=1)[0]\\n hmax = self.map_dimensions[0] - y\\n h = np.random.randint(0,hmax,size=1)[0]\\n rects += [(x,y,w,h)]\\n self.coordinates__obstacles = rects\",\n \"def _move(self, event):\\n if self._current_tower.get_value() > self._coins:\\n return\\n\\n #move the shadow tower to mouse position\\n position = event.x, event.y\\n self._current_tower.position = position\\n\\n legal, grid_path = self._game.attempt_placement(position)\\n\\n #find the best path and covert positions to pixel positions\\n path = [self._game.grid.cell_to_pixel_centre(position)\\n for position in grid_path.get_shortest()]\\n\\n #Task 1.2 (Tower placement): Draw the tower preview here\\n self._view.draw_preview(self._current_tower, legal)\\n self._view.draw_path(path)\",\n \"def _poses_town02(self):\\n def _simple_straight_forward():\\n return [[64, 55], [54, 63], [51, 46], [45, 49], [29, 50], [61, 40]]\\n\\n def _simple_left_turn():\\n return [[73, 62], [62, 7], [29, 43], [45, 79]]\\n\\n def _simple_right_turn():\\n return [[78, 46], [44, 40], [18, 60], [60, 71]]\\n\\n return [_simple_straight_forward(),\\n _simple_right_turn(),\\n _simple_left_turn(),\\n ]\",\n \"def move(self, direction):\\r\\n direc = list(OFFSETS[direction])\\r\\n line = []\\r\\n dummy_board = self.board[:]\\r\\n if direction == 3:\\r\\n for i in range(self.height):\\r\\n self.board[i] = merge(self.board[i])\\r\\n self.compare(dummy_board)\\r\\n return self.board\\r\\n \\r\\n elif direction == 4:\\r\\n for i in range(self.height):\\r\\n line = self.board[i][::-1]\\r\\n self.board[i] = merge(line)\\r\\n self.board[i] = self.board[i][::-1]\\r\\n self.compare(dummy_board)\\r\\n return self.board\\r\\n \\r\\n \\r\\n elif direction == 1 or 2:\\r\\n dummy_board = str(self.board[:])\\r\\n if direction == 1:\\r\\n tile = [0,0]\\r\\n elif direction == 2:\\r\\n tile = [self.height - 1, 0]\\r\\n for i in range(self.width):\\r\\n tile2 = tile[:]\\r\\n while len(line) < self.height:\\r\\n line.append(self.get_tile(*tile2))\\r\\n tile2 = [x+y for x,y in zip(direc, tile2)]\\r\\n line = merge(line)\\r\\n tile2 = tile[:]\\r\\n for i in range(self.height):\\r\\n self.set_tile(*(tile2+[line[0]]))\\r\\n line.remove(line[0])\\r\\n tile2 = [x+y for x,y in zip(direc, tile2)]\\r\\n tile = [x+y for x,y in zip(tile, [0,1])]\\r\\n if dummy_board != self.__str__():\\r\\n self.new_tile()\\r\\n return self.board\",\n \"def movement(self):\",\n \"def _bounce(self):\\n right = self.surface.get_width() - self.size\\n left = self.size\\n top = self.size\\n bottom = self.surface.get_height() - self.size\\n if self.pos.x > right: # right border\\n self.pos.x = right\\n self.direction = self.direction.elementwise() * pygame.Vector2(-1.0, 1.0)\\n elif self.pos.x < left: # left border\\n self.pos.x = left\\n self.direction = self.direction.elementwise() * pygame.Vector2(-1.0, 1.0)\\n if self.pos.y > bottom: # bottom border\\n self.pos.y = bottom\\n self.direction = self.direction.elementwise() * pygame.Vector2(1.0, -1.0)\\n elif self.pos.y < top: # top border\\n self.pos.y = top\\n self.direction = self.direction.elementwise() * pygame.Vector2(1.0, -1.0)\",\n \"def update_position(self, canvas):\\n pts = []\\n for P in self.get_points():\\n if P[0] <= 0:\\n if self.direction == \\\"SW\\\":\\n self.direction = \\\"SE\\\"\\n if self.direction == \\\"W\\\":\\n self.direction = \\\"E\\\"\\n if self.direction == \\\"NW\\\":\\n self.direction = \\\"NE\\\"\\n if P[0] >= canvas.width:\\n if self.direction == \\\"SE\\\":\\n self.direction = \\\"SW\\\"\\n if self.direction == \\\"E\\\":\\n self.direction = \\\"W\\\"\\n if self.direction == \\\"NE\\\":\\n self.direction = \\\"NW\\\"\\n if P[1] <= 0:\\n if self.direction == \\\"NW\\\":\\n self.direction = \\\"SW\\\"\\n if self.direction == \\\"N\\\":\\n self.direction = \\\"S\\\"\\n if self.direction == \\\"NE\\\":\\n self.direction = \\\"SE\\\"\\n if P[1] >= canvas.height:\\n if self.direction == \\\"SW\\\":\\n self.direction = \\\"NW\\\"\\n if self.direction == \\\"S\\\":\\n self.direction = \\\"N\\\"\\n if self.direction == \\\"SE\\\":\\n self.direction = \\\"NE\\\"\\n for P in self.get_points():\\n if self.direction == \\\"N\\\":\\n pts.append((P[0],P[1]-1)) \\n# P.y -= 1\\n if self.direction == \\\"NE\\\":\\n pts.append((P[0]+1,P[1]-1))\\n# P.y -= 1\\n# P.x += 1\\n if self.direction == \\\"E\\\":\\n pts.append((P[0]+1,P[1]))\\n# P.x += 1\\n if self.direction == \\\"SE\\\":\\n pts.append((P[0]+1,P[1]+1))\\n# P.x += 1\\n# P.y += 1\\n if self.direction == \\\"S\\\":\\n pts.append((P[0],P[1]+1))\\n# P.y += 1\\n if self.direction == \\\"SW\\\":\\n pts.append((P[0]-1,P[1]+1))\\n# P.x -= 1\\n# P.y += 1\\n if self.direction == \\\"W\\\":\\n pts.append((P[0]-1,P[1]))\\n# P.x -= 1\\n if self.direction == \\\"NW\\\":\\n pts.append((P[0]-1,P[1]-1))\\n# P.y -= 1\\n# P.x -= 1 \\n self.set_points(pts)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6025496","0.5948489","0.58940256","0.5790465","0.5725575","0.56771463","0.5674935","0.567056","0.5657837","0.56499887","0.56087935","0.55989015","0.5590386","0.55410814","0.55279523","0.54960006","0.54941237","0.54902667","0.54861367","0.5482337","0.5481442","0.54577315","0.5426281","0.54172724","0.54127735","0.54100245","0.5406042","0.5394075","0.537862","0.5369004","0.5345195","0.53408736","0.53403103","0.53397864","0.5310131","0.5309641","0.5302088","0.5293222","0.52913857","0.5280154","0.5279995","0.5278259","0.5261695","0.5257351","0.5257351","0.5245078","0.52408445","0.5235457","0.5228219","0.5228155","0.52264184","0.52070516","0.5198858","0.5186017","0.5185785","0.5185316","0.51834977","0.5180978","0.517916","0.5175188","0.51732755","0.5169105","0.5159204","0.51591015","0.5150087","0.51492363","0.51414615","0.51285964","0.5127874","0.51272297","0.5125835","0.5123923","0.5121087","0.5116627","0.511395","0.5113629","0.51120716","0.511177","0.5109894","0.5102606","0.5097463","0.50937897","0.50936574","0.50927174","0.5090313","0.50893414","0.50889367","0.5088831","0.50867707","0.50851345","0.50792235","0.5077186","0.5069396","0.50683004","0.5056015","0.5055422","0.5055027","0.5050167","0.5044979","0.50433815"],"string":"[\n \"0.6025496\",\n \"0.5948489\",\n \"0.58940256\",\n \"0.5790465\",\n \"0.5725575\",\n \"0.56771463\",\n \"0.5674935\",\n \"0.567056\",\n \"0.5657837\",\n \"0.56499887\",\n \"0.56087935\",\n \"0.55989015\",\n \"0.5590386\",\n \"0.55410814\",\n \"0.55279523\",\n \"0.54960006\",\n \"0.54941237\",\n \"0.54902667\",\n \"0.54861367\",\n \"0.5482337\",\n \"0.5481442\",\n \"0.54577315\",\n \"0.5426281\",\n \"0.54172724\",\n \"0.54127735\",\n \"0.54100245\",\n \"0.5406042\",\n \"0.5394075\",\n \"0.537862\",\n \"0.5369004\",\n \"0.5345195\",\n \"0.53408736\",\n \"0.53403103\",\n \"0.53397864\",\n \"0.5310131\",\n \"0.5309641\",\n \"0.5302088\",\n \"0.5293222\",\n \"0.52913857\",\n \"0.5280154\",\n \"0.5279995\",\n \"0.5278259\",\n \"0.5261695\",\n \"0.5257351\",\n \"0.5257351\",\n \"0.5245078\",\n \"0.52408445\",\n \"0.5235457\",\n \"0.5228219\",\n \"0.5228155\",\n \"0.52264184\",\n \"0.52070516\",\n \"0.5198858\",\n \"0.5186017\",\n \"0.5185785\",\n \"0.5185316\",\n \"0.51834977\",\n \"0.5180978\",\n \"0.517916\",\n \"0.5175188\",\n \"0.51732755\",\n \"0.5169105\",\n \"0.5159204\",\n \"0.51591015\",\n \"0.5150087\",\n \"0.51492363\",\n \"0.51414615\",\n \"0.51285964\",\n \"0.5127874\",\n \"0.51272297\",\n \"0.5125835\",\n \"0.5123923\",\n \"0.5121087\",\n \"0.5116627\",\n \"0.511395\",\n \"0.5113629\",\n \"0.51120716\",\n \"0.511177\",\n \"0.5109894\",\n \"0.5102606\",\n \"0.5097463\",\n \"0.50937897\",\n \"0.50936574\",\n \"0.50927174\",\n \"0.5090313\",\n \"0.50893414\",\n \"0.50889367\",\n \"0.5088831\",\n \"0.50867707\",\n \"0.50851345\",\n \"0.50792235\",\n \"0.5077186\",\n \"0.5069396\",\n \"0.50683004\",\n \"0.5056015\",\n \"0.5055422\",\n \"0.5055027\",\n \"0.5050167\",\n \"0.5044979\",\n \"0.50433815\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5458356"},"document_rank":{"kind":"string","value":"21"}}},{"rowIdx":88561,"cells":{"query":{"kind":"string","value":"This function takes all the first child panels of a page and moves them to form a zigzag or a rhombus pattern"},"document":{"kind":"string","value":"def box_transform_page(page, direction_list=[]):\n\n if len(page.children) > 1:\n\n # For all children of the page\n for idx in range(0, len(page.children)-1):\n\n # Take two children at a time\n p1 = page.get_child(idx)\n p2 = page.get_child(idx+1)\n\n change_proportion = np.random.randint(\n 10,\n cfg.full_page_movement_proportion_limit\n )\n\n change_proportion /= 100\n\n # Randomly move the line between them up or down one side\n if len(direction_list) < 1:\n direction = np.random.choice([\"rup\", \"lup\"])\n else:\n direction = direction_list[idx]\n\n # If the first panel is horizontal therefore the second is too\n if p1.orientation == \"h\":\n\n # Get the maximum amount the line can move\n change_max = min([(p1.x4y4[1] - p1.x1y1[1]),\n (p2.x4y4[1] - p2.x1y1[1])])\n\n change = change_max*change_proportion\n\n # Specify the line to move\n line_top = p2.x1y1\n line_bottom = p2.x2y2\n\n # If the panel has children then recursively\n # find the leaf children and move them to the new line\n if len(p1.children) > 0:\n move_children_to_line(p1,\n (line_top, line_bottom),\n change,\n \"h\",\n direction\n )\n\n # Otherwise move the current panels to line\n else:\n if direction == \"rup\":\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] + change)\n p1.refresh_coords()\n else:\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] - change)\n p1.refresh_coords()\n\n if len(p2.children) > 0:\n move_children_to_line(p2,\n (line_top, line_bottom),\n change,\n \"h\",\n direction\n )\n else:\n if direction == \"rup\":\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] + change)\n p2.refresh_coords()\n else:\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] - change)\n p2.refresh_coords()\n\n # If the first panel is vertical therefore the second\n # is too since they are siblings\n else:\n # Get the maximum amount the line can move\n change_max = min([(p1.x2y2[0] - p1.x1y1[0]),\n (p2.x2y2[0] - p2.x1y1[0])])\n\n change = change_max*change_proportion\n\n # Specify the line to move\n line_top = p2.x1y1\n line_bottom = p2.x4y4\n\n # If the panel has children then recursively\n # find the leaf children and move them to the new line\n if len(p1.children) > 0:\n move_children_to_line(p1,\n (line_top, line_bottom),\n change,\n \"v\",\n direction\n )\n\n # Otherwise just move the panel since it's a leaf\n else:\n if direction == \"rup\":\n p1.x2y2 = (p1.x2y2[0] - change, p1.x2y2[1])\n else:\n p1.x2y2 = (p1.x2y2[0] + change, p1.x2y2[1])\n\n if len(p2.children) > 0:\n move_children_to_line(p2,\n (line_top, line_bottom),\n change,\n \"v\",\n direction\n )\n else:\n if direction == \"rup\":\n p2.x1y1 = (p2.x1y1[0] - change, p2.x1y1[1])\n else:\n p2.x1y1 = (p2.x1y1[0] + change, p2.x1y1[1])\n\n return page"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def box_transform_panels(page, type_choice=None, pattern=None):\n\n if type_choice is None:\n type_choice_prob = np.random.random()\n if type_choice_prob < cfg.panel_box_trapezoid_ratio:\n type_choice = \"trapezoid\"\n else:\n type_choice = \"rhombus\"\n\n if type_choice == \"trapezoid\":\n if page.num_panels > 2:\n\n # Get parent panel which satisfies the criteria for the transform\n relevant_panels = find_parent_with_multiple_children(page, 3)\n\n if len(relevant_panels) > 0:\n if len(relevant_panels) > 1:\n num_panels = np.random.randint(1, len(relevant_panels))\n else:\n num_panels = 1\n\n # For each panel\n for idx in range(0, num_panels):\n panel = relevant_panels[idx]\n\n # Get the three child panels\n # Since panels are created in order\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n p3 = panel.get_child(2)\n\n min_width = math.inf\n min_height = math.inf\n\n # Get the smallest height and width\n for child in [p1, p2, p3]:\n\n if child.width < min_width:\n min_width = child.width\n\n if child.height < min_height:\n min_height = child.height\n\n # Choose trapezoid pattern\n if pattern is None:\n trapezoid_pattern = np.random.choice([\"A\", \"V\"])\n else:\n trapezoid_pattern = pattern\n\n movement_proportion = np.random.randint(\n 10,\n cfg.trapezoid_movement_limit)\n\n # If parent panel is horizontal the children are vertical\n if panel.orientation == \"h\":\n\n # Get how much the lines of the child panels move\n # on the x axis to make the trapezoid\n x_movement = min_width*(movement_proportion/100)\n\n # Make an A pattern horizontally\n if trapezoid_pattern == \"A\":\n\n # Get the coords of the first line to be moved\n line_one_top = (p1.x2y2[0] + x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] - x_movement,\n p1.x3y3[1])\n\n # Move line between child 1 and 2\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n # Get the coords of the second line to be moved\n line_two_top = (p2.x2y2[0] - x_movement,\n p2.x2y2[1])\n line_two_bottom = (p2.x3y3[0] + x_movement,\n p2.x3y3[1])\n\n # Move line two between child 2 and 3\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n\n # Make a V pattern horizontally\n else:\n\n # Get the coords of the first line to be moved\n line_one_top = (p1.x2y2[0] - x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] + x_movement,\n p1.x3y3[1])\n\n # Move line between child 1 and 2\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n # Get the coords of the second line to be moved\n line_two_top = (p2.x2y2[0] + x_movement,\n p2.x2y2[1])\n\n line_two_bottom = (p2.x3y3[0] - x_movement,\n p2.x3y3[1])\n\n # Move line two between child 2 and 3\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n\n # If panel is vertical children are horizontal\n # so the A and the V are at 90 degrees to the page\n else:\n # Get how much the lines of the child panels move\n # on the y axis to make the trapezoid\n y_movement = min_height*(movement_proportion/100)\n\n # Make an A pattern vertically\n if trapezoid_pattern == \"A\":\n\n # Get the coords of the first line to be moved\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] + y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] - y_movement)\n\n # Move line between child 1 and 2\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n\n # Get the coords of the second line to be moved\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] - y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] + y_movement)\n\n # Move line two between child 2 and 3\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n # Make a V pattern vertically\n else:\n\n # Get the coords of the first line to be moved\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] - y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] + y_movement)\n\n # Move line between child 1 and 2\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n # Get the coords of the second line to be moved\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] + y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] - y_movement)\n\n # Move line two between child 2 and 3\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n\n elif type_choice == \"rhombus\":\n\n if page.num_panels > 1:\n\n # Get parent panel which satisfies the criteria for the transform\n relevant_panels = find_parent_with_multiple_children(page, 3)\n\n if len(relevant_panels) > 0:\n\n if len(relevant_panels) > 1:\n num_panels = np.random.randint(1, len(relevant_panels))\n else:\n num_panels = 1\n\n for idx in range(0, num_panels):\n\n panel = relevant_panels[idx]\n\n # Since panels are created in order\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n p3 = panel.get_child(2)\n\n min_width = math.inf\n min_height = math.inf\n\n # Get the smallest height and width\n for child in [p1, p2, p3]:\n\n if child.width < min_width:\n min_width = child.width\n\n if child.height < min_height:\n min_height = child.height\n\n if pattern is None:\n rhombus_pattern = np.random.choice([\"left\", \"right\"])\n else:\n rhombus_pattern = pattern\n\n movement_proportion = np.random.randint(\n 10,\n cfg.rhombus_movement_limit\n )\n\n # Logic for the section below is the same as the\n # trapezoid with the exception of the fact that the\n # rhombus pattern happens to move both lines in the\n # same direction\n\n if panel.orientation == \"h\":\n\n x_movement = min_width*(movement_proportion/100)\n\n if rhombus_pattern == \"left\":\n line_one_top = (p1.x2y2[0] - x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] + x_movement,\n p1.x3y3[1])\n\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n line_two_top = (p2.x2y2[0] - x_movement,\n p2.x2y2[1])\n\n line_two_bottom = (p2.x3y3[0] + x_movement,\n p2.x3y3[1])\n\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n\n else:\n\n line_one_top = (p1.x2y2[0] + x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] - x_movement,\n p1.x3y3[1])\n\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n line_two_top = (p2.x2y2[0] + x_movement,\n p2.x2y2[1])\n\n line_two_bottom = (p2.x3y3[0] - x_movement,\n p2.x3y3[1])\n\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n else:\n y_movement = min_height*(movement_proportion/100)\n\n if rhombus_pattern == \"right\":\n\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] + y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] - y_movement)\n\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] + y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] - y_movement)\n\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n else:\n\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] - y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] + y_movement)\n\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] - y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] + y_movement)\n\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n\n return page","def LoadPerspective(self, layout):\r\n \r\n # Remove all tab ctrls (but still keep them in main index)\r\n tab_count = self._tabs.GetPageCount()\r\n for i in xrange(tab_count):\r\n wnd = self._tabs.GetWindowFromIdx(i)\r\n\r\n # find out which onscreen tab ctrl owns this tab\r\n ctrl, ctrl_idx = self.FindTab(wnd)\r\n if not ctrl:\r\n return False\r\n\r\n # remove the tab from ctrl\r\n if not ctrl.RemovePage(wnd):\r\n return False\r\n\r\n self.RemoveEmptyTabFrames()\r\n\r\n sel_page = 0\r\n tabs = layout[0:layout.index(\"@\")]\r\n to_break1 = False\r\n \r\n while 1:\r\n\r\n if \"|\" not in tabs:\r\n to_break1 = True\r\n tab_part = tabs\r\n else:\r\n tab_part = tabs[0:tabs.index('|')]\r\n \r\n if \"=\" not in tab_part:\r\n # No pages in this perspective...\r\n return False\r\n\r\n # Get pane name\r\n pane_name = tab_part[0:tab_part.index(\"=\")]\r\n\r\n # create a new tab frame\r\n new_tabs = TabFrame(self)\r\n self._tab_id_counter += 1\r\n new_tabs._tabs = AuiTabCtrl(self, self._tab_id_counter)\r\n new_tabs._tabs.SetArtProvider(self._tabs.GetArtProvider().Clone())\r\n new_tabs.SetTabCtrlHeight(self._tab_ctrl_height)\r\n new_tabs._tabs.SetAGWFlags(self._agwFlags)\r\n dest_tabs = new_tabs._tabs\r\n\r\n # create a pane info structure with the information\r\n # about where the pane should be added\r\n pane_info = framemanager.AuiPaneInfo().Name(pane_name).Bottom().CaptionVisible(False)\r\n self._mgr.AddPane(new_tabs, pane_info)\r\n\r\n # Get list of tab id's and move them to pane\r\n tab_list = tab_part[tab_part.index(\"=\")+1:]\r\n to_break2, active_found = False, False\r\n \r\n while 1:\r\n if \",\" not in tab_list:\r\n to_break2 = True\r\n tab = tab_list\r\n else:\r\n tab = tab_list[0:tab_list.index(\",\")] \r\n tab_list = tab_list[tab_list.index(\",\")+1:]\r\n\r\n # Check if this page has an 'active' marker\r\n c = tab[0]\r\n if c in ['+', '*']:\r\n tab = tab[1:]\r\n\r\n tab_idx = int(tab)\r\n if tab_idx >= self.GetPageCount():\r\n continue\r\n\r\n # Move tab to pane\r\n page = self._tabs.GetPage(tab_idx)\r\n newpage_idx = dest_tabs.GetPageCount()\r\n dest_tabs.InsertPage(page.window, page, newpage_idx)\r\n\r\n if c == '+':\r\n dest_tabs.SetActivePage(newpage_idx)\r\n active_found = True\r\n elif c == '*':\r\n sel_page = tab_idx\r\n\r\n if to_break2:\r\n break\r\n\r\n if not active_found:\r\n dest_tabs.SetActivePage(0)\r\n\r\n new_tabs.DoSizing()\r\n dest_tabs.DoShowHide()\r\n dest_tabs.Refresh()\r\n \r\n if to_break1:\r\n break\r\n \r\n tabs = tabs[tabs.index('|')+1:]\r\n\r\n # Load the frame perspective\r\n frames = layout[layout.index('@')+1:]\r\n self._mgr.LoadPerspective(frames)\r\n\r\n # Force refresh of selection\r\n self._curpage = -1\r\n self.SetSelection(sel_page)\r\n\r\n return True","def push_down (grid):\r\n \r\n for row in range (4):\r\n section = []\r\n for col in range (4):\r\n section.append(grid[3-col][row])\r\n add(section)\r\n for i in range (4):\r\n grid[i][row] = section[3-i]","def createInitialChildren(dash_instance):\n\t\n\t# create the header for the page\n\tamerenImage = createLogo(dash_instance)\n\theader = html.Div([\n\t\t\tamerenImage,\n\t\t\thtml.Label(\n\t\t\t\t\"Solarwinds Dashboard\",\n\t\t\t\tstyle=dict(fontSize=60, fontWeight='bold', fontStyle='italic')\n\t\t\t)\n\t\t],\n\t\tid='header',\n\t\tstyle={\n\t\t\t'height': '250px',\n 'backgroundColor': 'green',\n\t\t\t'textAlign': 'center',\n\t\t\t'verticalAlign': 'middle',\n\t\t\t'align': 'center'\n\t\t}\n\t)\n\t\n\tdown_item_fieldset = defineDownItemFieldset(dash_instance)\n\tstatistics_fieldset = defineStatisticsFieldset(dash_instance)\n\tpage_break = createPageBreak(dash_instance)\n\t\n\t# add the children\n\tdash_instance.addChildren(\n\t\theader,\n\t\tdown_item_fieldset,\n\t\tpage_break,\n\t\tstatistics_fieldset,\n\t\tdcc.Location(id='startPage', refresh=False)\n\t)","def prep_naves(self):\r\n self.naves = Group()\r\n for nave_num in range(self.stats.nave_left):\r\n nave = Nave(self.ik_game)\r\n nave.image = pygame.transform.rotate(pygame.transform.scale(\r\n pygame.image.load(os.path.join('complemento/aventine_ship.bmp')), (50, 20)), 90)\r\n nave.rect.x = 10 + nave_num * nave.rect.width\r\n nave.rect.y = 10\r\n self.naves.add(nave)","def Split(self, page, direction):\r\n \r\n cli_size = self.GetClientSize()\r\n\r\n # get the page's window pointer\r\n wnd = self.GetPage(page)\r\n if not wnd:\r\n return\r\n\r\n # notebooks with 1 or less pages can't be split\r\n if self.GetPageCount() < 2:\r\n return\r\n\r\n # find out which tab control the page currently belongs to\r\n\r\n src_tabs, src_idx = self.FindTab(wnd)\r\n if not src_tabs:\r\n return\r\n \r\n # choose a split size\r\n if self.GetPageCount() > 2:\r\n split_size = self.CalculateNewSplitSize()\r\n else: \r\n # because there are two panes, always split them\r\n # equally\r\n split_size = self.GetClientSize()\r\n split_size.x /= 2\r\n split_size.y /= 2\r\n\r\n # create a new tab frame\r\n new_tabs = TabFrame(self)\r\n new_tabs._rect = wx.RectPS(wx.Point(0, 0), split_size)\r\n new_tabs.SetTabCtrlHeight(self._tab_ctrl_height)\r\n self._tab_id_counter += 1\r\n new_tabs._tabs = AuiTabCtrl(self, self._tab_id_counter)\r\n \r\n new_tabs._tabs.SetArtProvider(self._tabs.GetArtProvider().Clone())\r\n new_tabs._tabs.SetAGWFlags(self._agwFlags)\r\n dest_tabs = new_tabs._tabs\r\n\r\n page_info = src_tabs.GetPage(src_idx)\r\n if page_info.control:\r\n self.ReparentControl(page_info.control, dest_tabs)\r\n \r\n # create a pane info structure with the information\r\n # about where the pane should be added\r\n pane_info = framemanager.AuiPaneInfo().Bottom().CaptionVisible(False)\r\n\r\n if direction == wx.LEFT:\r\n \r\n pane_info.Left()\r\n mouse_pt = wx.Point(0, cli_size.y/2)\r\n \r\n elif direction == wx.RIGHT:\r\n \r\n pane_info.Right()\r\n mouse_pt = wx.Point(cli_size.x, cli_size.y/2)\r\n \r\n elif direction == wx.TOP:\r\n \r\n pane_info.Top()\r\n mouse_pt = wx.Point(cli_size.x/2, 0)\r\n \r\n elif direction == wx.BOTTOM:\r\n \r\n pane_info.Bottom()\r\n mouse_pt = wx.Point(cli_size.x/2, cli_size.y)\r\n \r\n self._mgr.AddPane(new_tabs, pane_info, mouse_pt)\r\n self._mgr.Update()\r\n\r\n # remove the page from the source tabs\r\n page_info.active = False\r\n \r\n src_tabs.RemovePage(page_info.window)\r\n \r\n if src_tabs.GetPageCount() > 0:\r\n src_tabs.SetActivePage(0)\r\n src_tabs.DoShowHide()\r\n src_tabs.Refresh()\r\n \r\n # add the page to the destination tabs\r\n dest_tabs.InsertPage(page_info.window, page_info, 0)\r\n\r\n if src_tabs.GetPageCount() == 0:\r\n self.RemoveEmptyTabFrames()\r\n \r\n self.DoSizing()\r\n dest_tabs.DoShowHide()\r\n dest_tabs.Refresh()\r\n\r\n # force the set selection function reset the selection\r\n self._curpage = -1\r\n\r\n # set the active page to the one we just split off\r\n self.SetSelectionToPage(page_info)\r\n\r\n self.UpdateHintWindowSize()","def childAfterMove(self, m):\n indexOfZero = self.tiles.index(0)\n initial = self.tiles[:]\n child = Board(initial)\n if m == 'Up':\n assert(indexOfZero > 2)\n temp = self.tiles[indexOfZero - 3]\n child.tiles[indexOfZero] = temp\n child.tiles[indexOfZero - 3] = 0\n elif m == 'Down':\n assert(indexOfZero < 6)\n temp = self.tiles[indexOfZero + 3]\n child.tiles[indexOfZero] = temp\n child.tiles[indexOfZero + 3] = 0\n elif m == 'Left':\n assert(indexOfZero != 0 and indexOfZero != 3 and indexOfZero != 6)\n temp = self.tiles[indexOfZero - 1]\n child.tiles[indexOfZero] = temp\n child.tiles[indexOfZero - 1] = 0\n elif m == 'Right':\n assert(indexOfZero != 2 and indexOfZero != 5 and indexOfZero != 8)\n temp = self.tiles[indexOfZero + 1]\n child.tiles[indexOfZero] = temp\n child.tiles[indexOfZero + 1] = 0\n else:\n print(m + ' is not a legal movement')\n return child","def step(self):\n self.turn_on_corners()\n part_1.Grid.step(self)\n self.turn_on_corners()","def playout(self, state):\n node = self.root\n isTerminal = False\n depth = 0\n\n while not isTerminal and depth < self.playout_depth:\n #A = len(node.children) # num_children\n A = len(node.children[0]) + len(node.children[1]) \n if A < self.num_initActions:\n #if len(node.children[0]) < self.num_initActions:\n node, init_action_xy, init_spin = self.initChildren(node, state, depth)\n _, ShotVec = CreateShot(_ShotPos(init_action_xy[0], init_action_xy[1], init_spin))\n success, ResShot = Simulation(state, ShotVec, Config.RAND, -1)\n isTerminal = (state.ShotNum==0)\n \n depth += 1\n break\n \n n_a = [c.n_visits for c in node.children[0].values()] + [c.n_visits for c in node.children[1].values()]\n # progressive widening\n # if chilren node has been visited much times then expand\n #if np.sqrt(sum(n_a)) >= A:\n if sum(n_a) >= 10 * A: \n # expand\n node, expanded_action_xy, expanded_spin = self.expand(node)\n _, ShotVec = CreateShot(_ShotPos(expanded_action_xy[0],expanded_action_xy[1], expanded_spin))\n success, ResShot = Simulation(state, ShotVec, Config.RAND, -1)\n isTerminal = (state.ShotNum==0) # one end game\n \n depth += 1\n break\n\n # select\n node, selected_action_xy, selected_spin = self.ucb_select(node)\n _, ShotVec = CreateShot(_ShotPos(selected_action_xy[0], selected_action_xy[1], selected_spin))\n success, ResShot = Simulation(state, ShotVec, Config.RAND, -1)\n isTerminal = (state.ShotNum==0) # one end game\n \n depth += 1\n\n if isTerminal:\n break\n\n if not isTerminal and depth < self.playout_depth:\n # save the rollout_state for speed.\n #if node.rollout_state is None:\n state = self.rollOut(node, state, depth)\n #node.rollout_state = state\n #else:\n # state = node.rollout_state\n \n self.update(node, state)","def main():\n row1()\n move_up_left()\n row2()\n move_up_right()\n row3()\n move_up_left()\n row4()\n move_up_right()\n row5()\n move_up_left()\n row6()\n move_up_right()\n row7()\n move_up_left()\n row8()\n move_up_right()\n row9()\n move_up_left()\n row10()\n move_up_right()\n row11()\n move_up_left()\n row12()\n move_up_right()\n row13()\n move_up_left()\n row14()\n move_up_right()\n row15()\n move_up_left()\n row16()\n move_up_right()\n row17()\n move_up_left()\n row18()\n move_up_right()\n row19()\n move_up_left()\n row20()","def get_product_panels(self, product_bp, panel_list):\n for child in product_bp.children:\n props = props_closet.get_object_props(child)\n if props.is_panel_bp:\n assembly = fd_types.Assembly(child)\n if common_closet_utils.part_is_not_hidden(assembly):\n panel_list.append(child)\n self.get_product_panels(child, panel_list)\n panel_list.sort(key=lambda obj: obj.location.x, reverse=False)\n return panel_list","def goToFirstFrame():\n nuke.frame(int(nuke.root()[\"first_frame\"].getValue()))","def go_home(self):\n self.set_all_positions([0]*self.nleaflets)","def children(self):\n n = []\n zi = 0\n zj = 0\n for i in range(self.board_size):\n for j in range(self.board_size):\n if self.arr[i][j] == 0:\n zi = i\n zj = j\n break\n i = zi\n j = zj\n # \"UDLR\" order; that is, [‘Up’, ‘Down’, ‘Left’, ‘Right’]\n if 0 <= i-1: # up\n self.arr[i][j], self.arr[i-1][j] = self.arr[i -\n 1][j], self.arr[i][j] # do the move\n x = state([item for row in self.arr for item in row],\n self) # create a copy\n x.move = \"Up\" # set the movement that leads for this copy\n n.append(x) # add the copy to the list\n # undo the move so we can continue finding the other children\n self.arr[i][j], self.arr[i-1][j] = self.arr[i-1][j], self.arr[i][j]\n if self.board_size > i+1: # down\n self.arr[i][j], self.arr[i+1][j] = self.arr[i+1][j], self.arr[i][j]\n x = state([item for row in self.arr for item in row], self)\n x.move = \"Down\"\n n.append(x)\n self.arr[i][j], self.arr[i+1][j] = self.arr[i+1][j], self.arr[i][j]\n if 0 <= j-1: # left\n self.arr[i][j], self.arr[i][j-1] = self.arr[i][j-1], self.arr[i][j]\n x = state([item for row in self.arr for item in row], self)\n x.move = \"Left\"\n n.append(x)\n self.arr[i][j], self.arr[i][j-1] = self.arr[i][j-1], self.arr[i][j]\n if self.board_size > j+1: # right\n self.arr[i][j], self.arr[i][j+1] = self.arr[i][j+1], self.arr[i][j]\n x = state([item for row in self.arr for item in row], self)\n x.move = \"Right\"\n n.append(x)\n self.arr[i][j], self.arr[i][j+1] = self.arr[i][j+1], self.arr[i][j]\n\n return n","def create_open_positions_grid(self):\n\n counter = 0\n col = 0\n row = 0\n\n for i in range(0, 99):\n if counter % 3 == 0:\n col = 0\n row += 1\n self.gp.addWidget(PositionPanel(), row, col)\n counter += 1\n col += 1","def swipeBase (self) :\n grid = self.grid\n\n #we start by putting every tile up\n for columnNbr in range(4) :\n nbrZeros = 4 - np.count_nonzero(grid[:,columnNbr])\n\n for lineNbr in range(4) :\n counter = 0\n while (grid[lineNbr, columnNbr] == 0) and (counter < 4):\n counter += 1\n if np.count_nonzero(grid[lineNbr:4, columnNbr]) != 0 :\n for remainingLine in range (lineNbr, 3) :\n grid[remainingLine, columnNbr] = grid[remainingLine+1, columnNbr]\n grid[3, columnNbr] = 0\n\n #now we do the additions\n for lineNbr in range(3) :\n if grid[lineNbr, columnNbr] == grid[lineNbr+1, columnNbr] :\n grid[lineNbr, columnNbr] *= 2\n for remainingLine in range (lineNbr+1, 3) :\n grid[remainingLine, columnNbr] = grid[remainingLine+1, columnNbr]\n grid[3, columnNbr] = 0\n\n return (grid)","def create_panel_navigation(self, frame_parent):\r\n panel = ttk.Frame(frame_parent)\r\n\r\n tree = ttk.Treeview(panel, selectmode=\"browse\") # \"browse\" mode limits to one selection only\r\n tree.heading(\"#0\", text=\"Category\")\r\n tree.column(\"#0\", width=130)\r\n #tree.bind(\"<ButtonRelease-1>\", self.on_category_select) # left-button release\r\n tree.bind(\"<<TreeviewSelect>>\", self.on_category_select)\r\n #\r\n tree.insert('', tk.END, text=\"Email\")\r\n tree.insert('', tk.END, text=\"Access Restriction\")\r\n tree.selection_set(tree.get_children()[0]) # select the first item on init\r\n tree.grid(sticky=\"NS\")\r\n\r\n # http://stackoverflow.com/questions/25940217/python-getting-started-with-tk-widget-not-resizing-on-grid\r\n # or you can just do this: tree.pack(fill=tk.BOTH, expand=1)\r\n tree.rowconfigure(0, weight=1)\r\n tree.columnconfigure(0, weight=1)\r\n return panel","def LayoutAll(self, panes, docks, uiparts, spacer_only=False, oncheck=True):\r\n \r\n container = wx.BoxSizer(wx.VERTICAL)\r\n\r\n pane_border_size = self._art.GetMetric(AUI_DOCKART_PANE_BORDER_SIZE)\r\n caption_size = self._art.GetMetric(AUI_DOCKART_CAPTION_SIZE)\r\n cli_size = self._frame.GetClientSize()\r\n \r\n # empty all docks out\r\n for dock in docks:\r\n dock.panes = []\r\n if dock.fixed:\r\n # always reset fixed docks' sizes, because\r\n # the contained windows may have been resized\r\n dock.size = 0\r\n \r\n dock_count = len(docks)\r\n \r\n # iterate through all known panes, filing each\r\n # of them into the appropriate dock. If the\r\n # pane does not exist in the dock, add it\r\n for p in panes:\r\n\r\n # don't layout hidden panes.\r\n if p.IsShown():\r\n \r\n # find any docks with the same dock direction, dock layer, and\r\n # dock row as the pane we are working on\r\n arr = FindDocks(docks, p.dock_direction, p.dock_layer, p.dock_row)\r\n\r\n if arr:\r\n dock = arr[0]\r\n\r\n else:\r\n # dock was not found, so we need to create a new one\r\n d = AuiDockInfo()\r\n d.dock_direction = p.dock_direction\r\n d.dock_layer = p.dock_layer\r\n d.dock_row = p.dock_row\r\n docks.append(d)\r\n dock = docks[-1]\r\n\r\n if p.HasFlag(p.needsRestore) and not p.HasFlag(p.wasMaximized):\r\n \r\n isHor = dock.IsHorizontal()\r\n sashSize = self._art.GetMetric(AUI_DOCKART_SASH_SIZE)\r\n\r\n # get the sizes of any docks that might \r\n # overlap with our restored dock\r\n\r\n # make list of widths or heights from the size in the dock rects\r\n sizes = [d.rect[2:][isHor] for \\\r\n d in docks if d.IsOk() and \\\r\n (d.IsHorizontal() == isHor) and \\\r\n not d.toolbar and \\\r\n d.dock_direction != AUI_DOCK_CENTER]\r\n \r\n frameRect = GetInternalFrameRect(self._frame, self._docks)\r\n\r\n # set max size allowing for sashes and absolute minimum\r\n maxsize = frameRect[2:][isHor] - sum(sizes) - (len(sizes)*10) - (sashSize*len(sizes))\r\n dock.size = min(p.previousDockSize,maxsize)\r\n\r\n else:\r\n dock.size = 0\r\n\r\n if p.HasFlag(p.wasMaximized):\r\n self.MaximizePane(p, savesizes=False)\r\n p.SetFlag(p.wasMaximized, False)\r\n\r\n if p.HasFlag(p.needsRestore):\r\n if p.previousDockPos is not None:\r\n DoInsertPane(dock.panes, dock.dock_direction, dock.dock_layer, dock.dock_row, p.previousDockPos)\r\n p.dock_pos = p.previousDockPos\r\n p.previousDockPos = None\r\n p.SetFlag(p.needsRestore, False)\r\n\r\n if p.IsDocked():\r\n # remove the pane from any existing docks except this one\r\n docks = RemovePaneFromDocks(docks, p, dock)\r\n\r\n # pane needs to be added to the dock,\r\n # if it doesn't already exist \r\n if not FindPaneInDock(dock, p.window):\r\n dock.panes.append(p)\r\n else:\r\n # remove the pane from any existing docks\r\n docks = RemovePaneFromDocks(docks, p)\r\n \r\n # remove any empty docks\r\n docks = [dock for dock in docks if dock.panes]\r\n\r\n dock_count = len(docks)\r\n # configure the docks further\r\n for ii, dock in enumerate(docks):\r\n # sort the dock pane array by the pane's\r\n # dock position (dock_pos), in ascending order\r\n dock.panes.sort(PaneSortFunc)\r\n dock_pane_count = len(dock.panes)\r\n \r\n # for newly created docks, set up their initial size\r\n if dock.size == 0:\r\n size = 0\r\n for pane in dock.panes:\r\n pane_size = pane.best_size\r\n if pane_size == wx.Size(-1, -1):\r\n pane_size = pane.min_size\r\n if pane_size == wx.Size(-1, -1) and pane.window:\r\n pane_size = pane.window.GetSize()\r\n if dock.IsHorizontal():\r\n size = max(pane_size.y, size)\r\n else:\r\n size = max(pane_size.x, size)\r\n \r\n # add space for the border (two times), but only\r\n # if at least one pane inside the dock has a pane border\r\n for pane in dock.panes:\r\n if pane.HasBorder():\r\n size = size + pane_border_size*2\r\n break\r\n \r\n # if pane is on the top or bottom, add the caption height,\r\n # but only if at least one pane inside the dock has a caption\r\n if dock.IsHorizontal():\r\n for pane in dock.panes:\r\n if pane.HasCaption() and not pane.HasCaptionLeft():\r\n size = size + caption_size\r\n break\r\n else:\r\n for pane in dock.panes:\r\n if pane.HasCaptionLeft() and not pane.HasCaption():\r\n size = size + caption_size\r\n break\r\n \r\n # new dock's size may not be more than the dock constraint\r\n # parameter specifies. See SetDockSizeConstraint()\r\n max_dock_x_size = int(self._dock_constraint_x*float(cli_size.x))\r\n max_dock_y_size = int(self._dock_constraint_y*float(cli_size.y))\r\n if cli_size <= wx.Size(20, 20):\r\n max_dock_x_size = 10000\r\n max_dock_y_size = 10000\r\n\r\n if dock.IsHorizontal():\r\n size = min(size, max_dock_y_size)\r\n else:\r\n size = min(size, max_dock_x_size)\r\n\r\n # absolute minimum size for a dock is 10 pixels\r\n if size < 10:\r\n size = 10\r\n\r\n dock.size = size\r\n\r\n # determine the dock's minimum size\r\n plus_border = False\r\n plus_caption = False\r\n plus_caption_left = False\r\n dock_min_size = 0\r\n for pane in dock.panes:\r\n if pane.min_size != wx.Size(-1, -1):\r\n if pane.HasBorder():\r\n plus_border = True\r\n if pane.HasCaption():\r\n plus_caption = True\r\n if pane.HasCaptionLeft():\r\n plus_caption_left = True\r\n if dock.IsHorizontal():\r\n if pane.min_size.y > dock_min_size:\r\n dock_min_size = pane.min_size.y\r\n else:\r\n if pane.min_size.x > dock_min_size:\r\n dock_min_size = pane.min_size.x\r\n \r\n if plus_border:\r\n dock_min_size += pane_border_size*2\r\n if plus_caption and dock.IsHorizontal():\r\n dock_min_size += caption_size\r\n if plus_caption_left and dock.IsVertical():\r\n dock_min_size += caption_size\r\n \r\n dock.min_size = dock_min_size\r\n \r\n # if the pane's current size is less than it's\r\n # minimum, increase the dock's size to it's minimum\r\n if dock.size < dock.min_size:\r\n dock.size = dock.min_size\r\n\r\n # determine the dock's mode (fixed or proportional)\r\n # determine whether the dock has only toolbars\r\n action_pane_marked = False\r\n dock.fixed = True\r\n dock.toolbar = True\r\n for pane in dock.panes:\r\n if not pane.IsFixed():\r\n dock.fixed = False\r\n if not pane.IsToolbar():\r\n dock.toolbar = False\r\n if pane.HasFlag(AuiPaneInfo.optionDockFixed):\r\n dock.fixed = True\r\n if pane.HasFlag(AuiPaneInfo.actionPane):\r\n action_pane_marked = True\r\n\r\n # if the dock mode is proportional and not fixed-pixel,\r\n # reassign the dock_pos to the sequential 0, 1, 2, 3\r\n # e.g. remove gaps like 1, 2, 30, 500\r\n if not dock.fixed:\r\n for jj in xrange(dock_pane_count):\r\n pane = dock.panes[jj]\r\n pane.dock_pos = jj\r\n \r\n # if the dock mode is fixed, and none of the panes\r\n # are being moved right now, make sure the panes\r\n # do not overlap each other. If they do, we will\r\n # adjust the panes' positions\r\n if dock.fixed and not action_pane_marked:\r\n pane_positions, pane_sizes = self.GetPanePositionsAndSizes(dock)\r\n offset = 0\r\n for jj in xrange(dock_pane_count):\r\n pane = dock.panes[jj]\r\n pane.dock_pos = pane_positions[jj]\r\n amount = pane.dock_pos - offset\r\n if amount >= 0:\r\n offset += amount\r\n else:\r\n pane.dock_pos += -amount\r\n\r\n offset += pane_sizes[jj]\r\n dock.panes[jj] = pane\r\n\r\n if oncheck:\r\n self._docks[ii] = dock \r\n\r\n # shrink docks if needed \r\n## docks = self.SmartShrink(docks, AUI_DOCK_TOP)\r\n## docks = self.SmartShrink(docks, AUI_DOCK_LEFT)\r\n\r\n if oncheck:\r\n self._docks = docks\r\n \r\n # discover the maximum dock layer\r\n max_layer = 0\r\n dock_count = len(docks)\r\n \r\n for ii in xrange(dock_count):\r\n max_layer = max(max_layer, docks[ii].dock_layer)\r\n\r\n # clear out uiparts\r\n uiparts = []\r\n\r\n # create a bunch of box sizers,\r\n # from the innermost level outwards.\r\n cont = None\r\n middle = None\r\n\r\n if oncheck:\r\n docks = self._docks\r\n \r\n for layer in xrange(max_layer+1):\r\n # find any docks in this layer\r\n arr = FindDocks(docks, -1, layer, -1)\r\n # if there aren't any, skip to the next layer\r\n if not arr:\r\n continue\r\n\r\n old_cont = cont\r\n\r\n # create a container which will hold this layer's\r\n # docks (top, bottom, left, right)\r\n cont = wx.BoxSizer(wx.VERTICAL)\r\n\r\n # find any top docks in this layer\r\n arr = FindDocks(docks, AUI_DOCK_TOP, layer, -1)\r\n for row in arr:\r\n uiparts = self.LayoutAddDock(cont, row, uiparts, spacer_only)\r\n \r\n # fill out the middle layer (which consists\r\n # of left docks, content area and right docks)\r\n \r\n middle = wx.BoxSizer(wx.HORIZONTAL)\r\n\r\n # find any left docks in this layer\r\n arr = FindDocks(docks, AUI_DOCK_LEFT, layer, -1)\r\n for row in arr:\r\n uiparts = self.LayoutAddDock(middle, row, uiparts, spacer_only)\r\n \r\n # add content dock (or previous layer's sizer\r\n # to the middle\r\n if not old_cont:\r\n # find any center docks\r\n arr = FindDocks(docks, AUI_DOCK_CENTER, -1, -1)\r\n if arr:\r\n for row in arr:\r\n uiparts = self.LayoutAddDock(middle, row, uiparts, spacer_only)\r\n \r\n elif not self._has_maximized:\r\n # there are no center docks, add a background area\r\n sizer_item = middle.Add((1, 1), 1, wx.EXPAND)\r\n part = AuiDockUIPart()\r\n part.type = AuiDockUIPart.typeBackground\r\n part.pane = None\r\n part.dock = None\r\n part.button = None\r\n part.cont_sizer = middle\r\n part.sizer_item = sizer_item\r\n uiparts.append(part)\r\n else:\r\n middle.Add(old_cont, 1, wx.EXPAND)\r\n \r\n # find any right docks in this layer\r\n arr = FindDocks(docks, AUI_DOCK_RIGHT, layer, -1, reverse=True)\r\n for row in arr:\r\n uiparts = self.LayoutAddDock(middle, row, uiparts, spacer_only)\r\n \r\n if len(middle.GetChildren()) > 0:\r\n cont.Add(middle, 1, wx.EXPAND)\r\n\r\n # find any bottom docks in this layer\r\n arr = FindDocks(docks, AUI_DOCK_BOTTOM, layer, -1, reverse=True)\r\n for row in arr:\r\n uiparts = self.LayoutAddDock(cont, row, uiparts, spacer_only)\r\n\r\n if not cont:\r\n # no sizer available, because there are no docks,\r\n # therefore we will create a simple background area\r\n cont = wx.BoxSizer(wx.VERTICAL)\r\n sizer_item = cont.Add((1, 1), 1, wx.EXPAND)\r\n part = AuiDockUIPart()\r\n part.type = AuiDockUIPart.typeBackground\r\n part.pane = None\r\n part.dock = None\r\n part.button = None\r\n part.cont_sizer = middle\r\n part.sizer_item = sizer_item\r\n uiparts.append(part)\r\n\r\n if oncheck:\r\n self._uiparts = uiparts\r\n self._docks = docks\r\n\r\n container.Add(cont, 1, wx.EXPAND)\r\n\r\n if oncheck:\r\n return container\r\n else:\r\n return container, panes, docks, uiparts","def ress_move_on_page(self, content=None):\n outside_ress = self.outside_ress\n content = content or self.content\n\n for blo in outside_ress:\n\n mch = re.search(r'(\\s|\\t)-block %s'%blo, content) # blo = links, onload etc\n\n if not mch:\n\n warn(blo+' block is undefined in root template %s'%self.origin.__str__()) # raise Exception(blo+' block is undefined in root template %s'%origin.__str__())\n\n super_block = r'\\t\\t={ block.super }\\n'\n content = re.sub(\n r'(-extends \"[\\w\\.]+\")\"', r'\\1\\n\\t-block %s%s%s'%(\n blo, super_block, __indent_block(r'\\t\\t', outside_ress[blo].value)\n ),\n content\n )\n\n else:\n _blo = self.__indent_block(mch.groups()[0]+' '*4, outside_ress[blo].value)\n\n # (\\s|\\t)-block \\w+(([\\s:]*={ *block.super *})|) ={ *block.super *} - \\2\n\n content = re.sub(r'(\\s|\\t)(-block %s)'%blo, r'\\1\\2\\n'+_blo, content)\n\n## _blo = _indent_block(mch.groups()[0]+' '*8, blo)\n## _blo = '\\n\\1 :javascript\\n' + _blo\n\n return content","def main():\n while front_is_clear():\n repair_column()\n for i in range(4):\n move()\n repair_column()","def calculate_next_move(self, visit):\n self.depth += 1\n new_boards = []\n for vehicle_id in range(len(self.vehicles)):\n vehicle = self.vehicles[vehicle_id]\n state = self.get_board()\n if vehicle.orientation == 0: #horizontal\n if vehicle.x > 0: #left\n if state[vehicle.y][vehicle.x-1] == \"..\":\n self.vehicles[vehicle_id].x -=1\n if not self.get_board().tostring() in visit:\n if not self.get_board().all in new_boards:\n new_board = deepcopy(self)\n self.vehicles[vehicle_id].x += 1\n new_board.parent = self\n new_boards.append(new_board)\n else:\n self.vehicles[vehicle_id].x += 1\n\n if vehicle.x + vehicle.length <= (len(state)-1): #right\n if state[vehicle.y][vehicle.x+vehicle.length] == \"..\":\n self.vehicles[vehicle_id].x += 1\n if not self.get_board().tostring() in visit:\n if not self.get_board().all in new_boards:\n new_board = deepcopy(self)\n self.vehicles[vehicle_id].x -= 1\n new_board.parent = self\n new_boards.append(new_board)\n else:\n self.vehicles[vehicle_id].x -= 1\n\n else: #vertical\n if vehicle.y - 1 >= 0: #up\n if state[vehicle.y-1][vehicle.x] == \"..\":\n self.vehicles[vehicle_id].y -= 1\n if not self.get_board().tostring() in visit:\n if not self.get_board().all in new_boards:\n new_board = deepcopy(self)\n self.vehicles[vehicle_id].y += 1\n new_board.parent = self\n new_boards.append(new_board)\n else:\n self.vehicles[vehicle_id].y += 1\n\n if vehicle.y + vehicle.length <= (len(state)-1):\n if state[vehicle.y + vehicle.length][vehicle.x] == \"..\":#down\n self.vehicles[vehicle_id].y += 1\n if not self.get_board().tostring() in visit:\n if not self.get_board().all in new_boards:\n new_board = deepcopy(self)\n self.vehicles[vehicle_id].y -= 1\n new_board.parent = self\n new_boards.append(new_board)\n else:\n self.vehicles[vehicle_id].y -= 1\n self.depth -= 1\n return new_boards","def main():\n global fenetre, gr_grid,grid,steps,btn\n fenetre = Frame()\n fenetre.grid()\n fenetre.master.title('Rush Hour')\n flabel = Frame(fenetre)\n flabel.grid()\n steps=StringVar()\n Label(flabel, textvariable=steps).pack()\n steps.set(str(len(l))+\" steps remaining\")\n background = Frame(fenetre, bg = game_bg, width=game_size, height=game_size)\n background.grid()\n gr_grid = []\n for i in range(6):\n gr_line = []\n for j in range(6):\n cell = Frame(background, bg = tiles_empty_bg, width = tiles_size, height = tiles_size)\n cell.grid(row=i, column=j,padx=1, pady=1)\n t = Label(master = cell, text = \"\", bg = tiles_empty_bg, justify = CENTER, font = tiles_font, width=4, height=2)\n t.grid()\n gr_line.append(t)\n gr_grid.append(gr_line)\n\n board_display(my_board)\n button=Frame(fenetre)\n button.grid()\n btn=StringVar()\n Button(button, textvariable=btn, command=next_step).pack(side=BOTTOM)\n btn.set(\"Next step\")\n fenetre.mainloop()","def _setup_children(self):\n\n for i in xrange(self._nhalos):\n self._halos[i+1].properties['children'] = []\n\n for i in xrange(self._nhalos):\n host = self._halos[i+1].properties.get('hostHalo', -2)\n if host > -1:\n try:\n self._halos[host+1].properties['children'].append(i+1)\n except KeyError:\n pass","def main():\n for i in range(4):\n fix_tower()\n if front_is_clear():\n move_to_next()","def _setup_children(self):\n\n for i in xrange(self._nhalos):\n self._halos[i + 1].properties['children'] = []\n\n for i in xrange(self._nhalos):\n host = self._halos[i + 1].properties.get('hostHalo', -2)\n if host > -1:\n try:\n self._halos[host + 1].properties['children'].append(i + 1)\n except KeyError:\n pass","def setup(self):\n for lane in self.lanes.values():\n for p in range(lane.starting_patrons):\n patron = Patron(\n lane=lane,\n lane_speed=self.patron_speed,\n pause_duration=self.patron_pause,\n )\n\n patron.pos = patron.pos[0], patron.pos[1] + 15\n lane.puck_area.add_widget(patron)\n lane.patrons.append(patron)","def run():\n while True:\n try:\n top_layout = cpanel.top_panel().userptr()\n top_layout.run_ctr()\n except AttributeError:\n sys.exit(\"Please create at least one view layout.\")","def initializePage(self):\n WizardPage.initialize(self)\n self.page.use(qt.QVBoxLayout())\n\n dims = [(\"DX\", 0.), (\"DY\", 0.)]\n if self.give_field(\"model\").dim == 3:\n dims.append((\"DZ\", 0.))\n exp = self.give_field(\"exp-store\").give_exp(\"boundaries\")\n lst = exp.find_groups(self.give_field(\"mesh\"))\n tit = u\"Adding imposed degrees of freedom on groups\"\n add_condition_selector(self, lst, dims, \"group-boundaries*\", tit)","def build_frames(dialbox):\n #Buttons Frame\n dialbox.button_frame = tk.Frame(dialbox.master_frame)\n dialbox.button_frame.grid(row=3, column=1)\n #Output Frame\n dialbox.output_frame = tk.Frame(dialbox.master_frame)\n dialbox.output_frame.grid(row=4, column=0, columnspan=2)","def create_page(self, parent):\n ui = self.edit_traits(parent=parent, kind=\"subpanel\")\n return ui.control","def _sidepanel(self):\n global curdir\n global sidepanel_layout\n global root\n\n #Create the sidepanel layout.\n sidepanel_layout = BoxLayout(orientation=\"vertical\", pos_hint={\"x\": 0.0, \"top\": 0.92}, size_hint=(0.1, 0.92))\n\n #If \"curdir\" contains folders, a button is created for each, and bind the button to update the\n # showphotos layout.\n if curdir == \" \":\n return sidepanel_layout\n else:\n root.remove_widget(sidepanel_layout)\n for folders in sorted(glob(join(curdir, \"thumb\", \"*\"))):\n name = basename(folders)\n btn = Button(text=name, on_press=lambda n=name: self._update_scroll(n.text))\n sidepanel_layout.add_widget(btn)\n root.add_widget(sidepanel_layout)\n sidepanel_layout.do_layout()","def create_board(self):\n for field in self.fields_start_locs:\n loc = self.loc_to_view(field[0], field[1])\n new_field = Field(loc, self.piece_size)\n self.sprite_group.add(new_field)\n self.click_sprites.add(new_field)\n self.fields.append(new_field)","def initializePage(self):\n WC.WizardPage.initialize(self)\n self.page.use(qt.QVBoxLayout())\n exp = self.give_field(\"exp-store\").give_exp(\"pressure\")\n grps = exp.find_groups(self.give_field(\"mesh\"))\n dims = [(u\"Pressure\", 1.)]\n tit = u\"Adding pressure on meshes groups\"\n # The last groups should be seen first\n grps.reverse()\n WC.add_condition_selector(self, grps, dims, \"pressure-loading*\", tit)","def create_sat_panels(self):\n\n # Dimensions of body\n SAT_SIZE = self.ANI_SCALE*self.SAT_SCALE*np.asarray(self.SAT_PROPS[\"Size\"])/2\n bx = SAT_SIZE[0]\n by = SAT_SIZE[1]\n bz = SAT_SIZE[2]\n\n # Panel length\n L = bx\n\n # Panels\n theta = self.PANEL_ANGLE*pi/180\n px1 = bx - L*sin(theta)\n py1 = by + L*cos(theta)\n pz1 = bz\n px2 = px1 + L*sin(theta)\n py2 = py1 + L*cos(theta)\n pz2 = pz1\n\n # Vertices\n V = [\n (-bx, by, -bz),\n (-bx, by, bz),\n (-px1, py1, pz1),\n (-px1, py1, -pz1),\n (-px1, py1, -pz1),\n (-px1, py1, pz1),\n (-px2, py2, pz2),\n (-px2, py2, -pz2),\n (-bx, -by, -bz),\n (-bx, -by, bz),\n (-px1, -py1, pz1),\n (-px1, -py1, -pz1),\n (-px1, -py1, -pz1),\n (-px1, -py1, pz1),\n (-px2, -py2, pz2),\n (-px2, -py2, -pz2)\n ]\n\n # Create faces\n F = [\n (0, 1, 2, 3),\n (4, 5, 6, 7),\n (8, 9, 10, 11),\n (12, 13, 14, 15)\n ]\n\n # Create building blocks of polydata\n sat = vtk.vtkPolyData()\n points = vtk.vtkPoints()\n polys = vtk.vtkCellArray()\n scalars = vtk.vtkFloatArray()\n\n # Load the point, cell and data attributes\n for i in range(len(V)):\n points.InsertPoint(i, V[i])\n for i in range(len(F)):\n polys.InsertNextCell(self.mkVtkIdList(F[i]))\n for i in range(len(V)):\n scalars.InsertTuple1(i, i)\n \n # Assign the pieces to the vtkPolyData.\n sat.SetPoints(points)\n del points\n sat.SetPolys(polys)\n del polys\n sat.GetPointData().SetScalars(scalars)\n del scalars\n\n # Mapper\n mapper = vtk.vtkPolyDataMapper()\n mapper.SetInputData(sat)\n mapper.ScalarVisibilityOff()\n\n # Actor\n actor = vtk.vtkActor()\n actor.SetMapper(mapper)\n actor.GetProperty().SetColor(0., 0., 0.8)\n actor.GetProperty().SetAmbient(0.5)\n actor.GetProperty().SetSpecular(.5)\n actor.GetProperty().SetSpecularPower(10.0)\n actor.GetProperty().SetDiffuse(0.2)\n\n # Move to sat position\n actor.SetPosition(0, 0, -self.SAT_PROPS[\"Alt\"])\n\n return actor","def single_slice_panels(page,\n horizontal_vertical=None,\n type_choice=None,\n skew_side=None,\n number_to_slice=0\n ):\n\n # Remove panels which are too small\n relevant_panels = []\n if len(page.children) > 0:\n get_min_area_panels(page,\n cfg.slice_minimum_panel_area,\n ret_panels=relevant_panels\n )\n else:\n relevant_panels = [page]\n\n # Shuffle panels for randomness\n random.shuffle(relevant_panels)\n\n # single slice close\n if type_choice is None:\n type_choice_prob = np.random.random()\n if type_choice_prob < cfg.center_side_ratio:\n type_choice = \"center\"\n else:\n type_choice = \"side\"\n\n num_panels_added = 0\n\n # Slice panels down the center\n if type_choice == \"center\":\n if len(relevant_panels) < 1:\n return page\n\n if number_to_slice == 0:\n if len(relevant_panels) > 1:\n number_to_slice = np.random.randint(1, len(relevant_panels))\n else:\n number_to_slice = 1\n\n for idx in range(0, number_to_slice):\n panel = relevant_panels[idx]\n num_panels_added += 1\n\n # Decide which direction to cut in\n if horizontal_vertical is None:\n horizontal_vertical = np.random.choice([\"h\", \"v\"])\n\n # Get center line\n # Vertical slice\n if horizontal_vertical == \"v\":\n panel_chosen_coord_length = (panel.x2y2[0] - panel.x1y1[0])/2\n\n # Slice panel\n draw_n(2, panel, \"v\")\n\n # Skew it left or right\n if skew_side is None:\n skew_side = np.random.choice([\"left\", \"right\"])\n\n # Skew it by a percentage\n skew_amount = np.random.randint(20, 100)/100\n skew_amount = skew_amount*panel_chosen_coord_length\n\n # Perform transform\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n\n p1.sliced = True\n p2.sliced = True\n if skew_side == \"left\":\n p1.x2y2 = (p1.x2y2[0] - skew_amount, p1.x2y2[1])\n p1.x3y3 = (p1.x3y3[0] + skew_amount, p1.x3y3[1])\n\n p1.refresh_coords()\n\n p2.x1y1 = (p2.x1y1[0] - skew_amount, p2.x1y1[1])\n p2.x4y4 = (p2.x4y4[0] + skew_amount, p2.x4y4[1])\n\n p2.refresh_coords()\n\n elif skew_side == \"right\":\n p1.x2y2 = (p1.x2y2[0] + skew_amount, p1.x2y2[1])\n p1.x3y3 = (p1.x3y3[0] - skew_amount, p1.x3y3[1])\n\n p1.refresh_coords()\n\n p2.x1y1 = (p2.x1y1[0] + skew_amount, p2.x1y1[1])\n p2.x4y4 = (p2.x4y4[0] - skew_amount, p2.x4y4[1])\n\n p2.refresh_coords()\n\n else:\n print(\"Chosen incorrect skew side\")\n return None\n\n # Horizontal slice\n else:\n panel_chosen_coord_length = (panel.x3y3[1] - panel.x2y2[1])/2\n\n # Slice panel\n draw_n(2, panel, \"h\")\n\n # Skew it left or right\n if skew_side is None:\n skew_side = np.random.choice([\"down\", \"up\"])\n\n # Skew it by a percentage\n skew_amount = np.random.randint(20, 100)/100\n skew_amount = skew_amount*panel_chosen_coord_length\n\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n\n p1.sliced = True\n p2.sliced = True\n if skew_side == \"down\":\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] + skew_amount)\n p1.x3y3 = (p1.x3y3[0], p1.x3y3[1] - skew_amount)\n\n p1.refresh_coords()\n\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] + skew_amount)\n p2.x2y2 = (p2.x2y2[0], p2.x2y2[1] - skew_amount)\n\n p2.refresh_coords()\n\n elif skew_side == \"up\":\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] - skew_amount)\n p1.x3y3 = (p1.x3y3[0], p1.x3y3[1] + skew_amount)\n\n p1.refresh_coords()\n\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] - skew_amount)\n p2.x2y2 = (p2.x2y2[0], p2.x2y2[1] + skew_amount)\n\n p2.refresh_coords()\n else:\n print(\"Chose incorrect skew_side\")\n\n # Slice panel sides\n else:\n if len(relevant_panels) < 1:\n return page\n\n if number_to_slice == 0:\n if len(relevant_panels) > 1:\n number_to_slice = np.random.choice([1, 3])\n else:\n number_to_slice = 1\n\n for panel in relevant_panels[0:number_to_slice]:\n\n if skew_side is None:\n skew_side = np.random.choice([\"tr\", \"tl\", \"br\", \"bl\"])\n\n draw_n(2, panel, \"h\")\n num_panels_added += 1\n\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n\n # Panels are non standard polygons\n p1.non_rect = True\n p2.non_rect = True\n\n p1.sliced = True\n p2.sliced = True\n\n cut_y_proportion = np.random.randint(25, 75)/100\n cut_x_proportion = np.random.randint(25, 75)/100\n\n cut_y_length = (panel.x4y4[1] - panel.x1y1[1])*cut_y_proportion\n cut_x_length = (panel.x3y3[0] - panel.x4y4[0])*cut_x_proportion\n\n # bottom left corner\n if skew_side == \"bl\":\n\n p1_cut_x1y1 = (panel.x4y4[0], panel.x4y4[1] - cut_y_length)\n p1_cut_x2y2 = (panel.x4y4[0] + cut_x_length, panel.x4y4[1])\n p1_cut_x3y3 = (panel.x4y4)\n\n p1.coords = [p1_cut_x1y1, p1_cut_x2y2,\n p1_cut_x3y3, p1_cut_x1y1]\n\n p2.coords = [panel.x1y1, panel.x2y2, panel.x3y3,\n p1_cut_x2y2, p1_cut_x1y1, panel.x1y1]\n\n # bottom right corner\n elif skew_side == \"br\":\n\n p1_cut_x1y1 = (panel.x3y3[0], panel.x3y3[1] - cut_y_length)\n p1_cut_x2y2 = (panel.x3y3)\n p1_cut_x3y3 = (panel.x3y3[0] - cut_x_length, panel.x3y3[1])\n\n p1.coords = [p1_cut_x1y1, p1_cut_x2y2,\n p1_cut_x3y3, p1_cut_x1y1]\n\n p2.coords = [panel.x1y1, panel.x2y2, p1_cut_x1y1,\n p1_cut_x3y3, panel.x4y4, panel.x1y1]\n\n # top left corner\n elif skew_side == \"tl\":\n\n p1_cut_x1y1 = panel.x1y1\n p1_cut_x2y2 = (panel.x1y1[0] + cut_x_length, panel.x1y1[1])\n p1_cut_x3y3 = (panel.x1y1[0], panel.x1y1[1] + cut_y_length)\n\n p1.coords = [p1_cut_x1y1, p1_cut_x2y2,\n p1_cut_x3y3, p1_cut_x1y1]\n p2.coords = [p1_cut_x2y2, panel.x2y2, panel.x3y3,\n panel.x4y4, p1_cut_x3y3, p1_cut_x1y1]\n\n # top right corner\n elif skew_side == \"tr\":\n p1_cut_x1y1 = (panel.x2y2[0] - cut_x_length, panel.x2y2[1])\n p1_cut_x2y2 = panel.x2y2\n p1_cut_x3y3 = (panel.x2y2[0], panel.x2y2[1] + cut_y_length)\n\n p1.coords = [p1_cut_x1y1, p1_cut_x2y2,\n p1_cut_x3y3, p1_cut_x1y1]\n\n p2.coords = [panel.x1y1, p1_cut_x1y1, p1_cut_x3y3,\n panel.x3y3, panel.x4y4, panel.x1y1]\n else:\n print(\"Chose incorrect skew side\")\n return None\n\n page.num_panels += num_panels_added\n\n return page","def test_7_replay_4(self):\n self._execute_replay_nr(4)\n\n self.grid.add_pawn(5, 'H')\n self.grid.add_pawn(3, 'B')\n self.grid.add_pawn(2, 'H')\n self.grid.add_pawn(1, 'B')\n self.grid.add_pawn(1, 'H')\n\n # self.grid.print_grid()\n # print(self.minmaxBot_7.choose_move(self.grid))","def _generateNamedContainingPanel(self, obj, **args):\n result = []\n parent = obj.parent\n while parent and (parent.parent != parent):\n if parent.getRole() == pyatspi.ROLE_PANEL:\n label = self._generateLabelAndName(parent)\n if label:\n result.extend(label)\n break\n parent = parent.parent\n return result","def ReDockPage(self, pane):\r\n\r\n root_manager = framemanager.GetManager(self) \r\n\r\n pane.window.__floating_size__ = wx.Size(*pane.floating_size)\r\n page_index = pane.window.__page_index__\r\n text_colour = pane.window.__text_colour__\r\n control = pane.window.__control__\r\n \r\n root_manager.DetachPane(pane.window)\r\n self.InsertPage(page_index, pane.window, pane.caption, True, pane.icon, control=control)\r\n\r\n self.SetPageTextColour(page_index, text_colour)\r\n self.GetActiveTabCtrl().DoShowHide()\r\n self.DoSizing()\r\n if control:\r\n self.UpdateTabCtrlHeight(force=True)\r\n \r\n self._mgr.Update()\r\n root_manager.Update()","def first_step(self, plan, sequence, imgnum):\n def max_diaphragmatic_level(levels):\n \"\"\"\n As a column in the 2DST image may have more than one point representing the\n diaphragmatic level, this function retrieves only the biggest point, which\n will represent the diaphragmatic level\n\n Parameters\n ----------\n levels: list\n List of lists of int that represents the diafragmatics levels\n \"\"\"\n return [max(x) for x in levels]\n\n # Define the dimension of the matrixes\n mat_dim = (len(self.sag_sequences), len(self.cor_sequences))\n self.matRegistration = np.zeros(mat_dim)\n self.matX = np.zeros(mat_dim)\n self.matY = np.zeros(mat_dim)\n self.matZ = np.zeros(mat_dim)\n self.matDL = np.zeros(mat_dim)\n self.matRP = np.zeros(mat_dim)\n\n # Respiratory patterns linked to the sequence containing the root image\n lpatterns = [x for x in self.dataset if int(x.split('-')[1]) == sequence]\n # print('Patterns coronal: {} ({})\\n'.format(lpatterns, len(lpatterns)))\n\n # Represents the column in the register matrix that represents the sequence used\n column = self.cor_sequences.index(sequence)\n # print('Index: {}\\n'.format(column))\n\n \"\"\" Retrieves the diaphragmatic levels of the root image (coronal plan) and stores\n them in the correct positions of the register matrix \"\"\"\n for i in range(self.matrows):\n # print('{}.png'.format(lpatterns[i]))\n\n pts_pattern = self.pattern_coronal('{}.png'.format(lpatterns[i]))\n diaph_lvl = self.diaphragmatic_level_coronal(pts_pattern)\n max_diaph_lvl = max_diaphragmatic_level(diaph_lvl)\n resp_phase = self.respiratory_phase_coronal(diaph_lvl)\n\n self.matDL[i, column] = max_diaph_lvl[imgnum - 1] # -1\n self.matRP[i, column] = resp_phase[i]\n self.matRegistration[i, column] = self.blue\n\n # print(\"(Step 1) Diaphragmatic level matrix:\\n{}\\n\".format(self.matDL))\n # print(\"(Step 1) Registration matrix:\\n{}\\n\".format(self.matRegistration))\n # print(\"(Step 1) Respiratory phase:\\n{}\\n\".format(self.matRP))\n\n dlvl = [self.matDL[i, column] for i in range(len(self.sag_sequences))]\n rphase = [int(self.matRP[i, column]) for i in range(len(self.sag_sequences))]\n # print(\"(Step 1) DL: {}\\n\".format(dlvl))\n\n return dlvl, rphase","def define_panel_structure(self):\n w, h = self.parent.GetSize()\n self.vbox = wx.BoxSizer(wx.VERTICAL)\n self.sizer1 = wx.BoxSizer(wx.VERTICAL)\n self.sizer1.SetMinSize(wx.Size(w/13, h*2/5))\n\n self.sizer2 = wx.BoxSizer(wx.VERTICAL)\n self.sizer3 = wx.FlexGridSizer(9, 2, 4, 1)\n self.sizer4 = wx.BoxSizer(wx.VERTICAL)\n self.sizer5 = wx.BoxSizer(wx.VERTICAL)\n\n self.vbox.Add(self.sizer5, 0, wx.EXPAND | wx.ALL, 1)\n self.vbox.Add(self.sizer1, 1, wx.EXPAND | wx.ALL, 0)\n self.vbox.Add(self.sizer2, 0, wx.EXPAND | wx.ALL, 1)\n self.vbox.Add(self.sizer3, 0, wx.EXPAND | wx.ALL, 10)\n # self.vbox.Add(self.sizer4, 0, wx.EXPAND|wx.ALL,5)\n\n self.SetSizer(self.vbox)","def draw_window_pane():\n houseturtle.begin_fill()\n for y in range(4):\n houseturtle.pendown()\n houseturtle.forward(35)\n houseturtle.left(90)\n houseturtle.penup()\n houseturtle.end_fill()","def set_pieces(self):\n\n for i in range(len(self._game_board)):\n\n # Row 1\n if i == 0:\n for ii in range(len(self._game_board[i])):\n if ii == 0 or ii == 8:\n self._game_board[i][ii] = Chariot(\"black\", \"BCHA\")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 1 or ii == 7:\n self._game_board[i][ii] = Horse(\"black\", \" BH \")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 2 or ii == 6:\n self._game_board[i][ii] = Elephant(\"black\", \" BE \")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 3 or ii == 5:\n self._game_board[i][ii] = Advisor(\"black\", \" BA \")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 4:\n self._game_board[i][ii] = General(\"black\", \" BG \")\n self._game_board[i][ii].update_location([i, ii])\n\n # Row 3\n if i == 2:\n for ii in range(len(self._game_board[i])):\n if ii == 1 or ii == 7:\n self._game_board[i][ii] = Cannon(\"black\", \"BCAN\")\n self._game_board[i][ii].update_location([i, ii])\n\n # Row 4\n if i == 3:\n for ii in range(len(self._game_board[i])):\n if ii % 2 == 0:\n self._game_board[i][ii] = Soldier(\"black\", \"BSOL\")\n self._game_board[i][ii].update_location([i, ii])\n\n # Row 7\n if i == 6:\n for ii in range(len(self._game_board[i])):\n if ii % 2 == 0:\n self._game_board[i][ii] = Soldier(\"red\", \"RSOL\")\n self._game_board[i][ii].update_location([i, ii])\n\n # Row 8\n if i == 7:\n for ii in range(len(self._game_board[i])):\n if ii == 1 or ii == 7:\n self._game_board[i][ii] = Cannon(\"red\", \"RCAN\")\n self._game_board[i][ii].update_location([i, ii])\n\n # Row 10\n if i == 9:\n for ii in range(len(self._game_board[i])):\n if ii == 0 or ii == 8:\n self._game_board[i][ii] = Chariot(\"red\", \"RCHA\")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 1 or ii == 7:\n self._game_board[i][ii] = Horse(\"red\", \" RH \")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 2 or ii == 6:\n self._game_board[i][ii] = Elephant(\"red\", \" RE \")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 3 or ii == 5:\n self._game_board[i][ii] = Advisor(\"red\", \" RA \")\n self._game_board[i][ii].update_location([i, ii])\n if ii == 4:\n self._game_board[i][ii] = General(\"red\", \" RG \")\n self._game_board[i][ii].update_location([i, ii])","def create_portal(self, maze, portal_type):\n\n # use adjusted position to add size of brick to find nearest brick in grid\n x, y = self.adjust_position()\n found = False\n\n # Pacman facing right\n if self.image in self.animated_right:\n\n # Find nearest brick on the right\n while x < self.screen_rect.width and not found:\n x += maze.brick_size\n\n for brick in maze.bricks:\n if x == brick.rect.x and y == brick.rect.y:\n\n # Add a portal\n self.add_portal(portal_type, \"left\", (x, y))\n found = True\n break\n\n # Pacman facing left\n elif self.image in self.animated_left:\n\n # Find nearest brick on the left\n while x >= 0 and not found:\n x -= maze.brick_size\n\n for brick in maze.bricks:\n if x == brick.rect.x and y == brick.rect.y:\n\n # Add a portal\n self.add_portal(portal_type, \"right\", (x, y))\n found = True\n break\n\n # Pacman facing up\n elif self.image in self.animated_up:\n\n # Find nearest brick above\n while y >= 0 and not found:\n y -= maze.brick_size\n\n for brick in maze.bricks:\n if x == brick.rect.x and y == brick.rect.y:\n\n # Add a portal\n self.add_portal(portal_type, \"down\", (x, y))\n found = True\n break\n\n # Pacman facing down\n elif self.image in self.animated_down:\n\n # Find nearest brick below\n while y <= self.screen_rect.height and not found:\n y += maze.brick_size\n\n for brick in maze.bricks:\n if x == brick.rect.x and y == brick.rect.y:\n\n # Add a portal\n self.add_portal(portal_type, \"up\", (x, y))\n found = True\n break","def paneLayout(*args, activeFrameThickness: Union[int, bool]=0, activePane: Union[AnyStr,\n bool]=\"\", activePaneIndex: Union[int, bool]=0, annotation: Union[AnyStr,\n bool]=\"\", backgroundColor: Union[List[float, float, float], bool]=None,\n childArray: bool=True, configuration: Union[AnyStr, bool]=\"\", defineTemplate:\n AnyStr=\"\", docTag: Union[AnyStr, bool]=\"\", dragCallback: Script=None,\n dropCallback: Script=None, enable: bool=True, enableBackground: bool=True,\n enableKeyboardFocus: bool=True, exists: bool=True, fullPathName: bool=True,\n height: Union[int, bool]=0, highlightColor: Union[List[float, float, float],\n bool]=None, isObscured: bool=True, manage: bool=True, noBackground: bool=True,\n numberOfChildren: bool=True, numberOfPopupMenus: bool=True,\n numberOfVisiblePanes: bool=True, pane1: bool=True, pane2: bool=True, pane3:\n bool=True, pane4: bool=True, paneSize: Union[List[int, int, int], List[List[int,\n int, int]], bool]=None, paneUnderPointer: bool=True, parent: Union[AnyStr,\n bool]=\"\", popupMenuArray: bool=True, preventOverride: bool=True,\n separatorMovedCommand: Script=None, separatorThickness: Union[int, bool]=0,\n setPane: Union[List[AnyStr, int], List[List[AnyStr, int]]]=None,\n staticHeightPane: int=0, staticWidthPane: int=0, statusBarMessage: AnyStr=\"\",\n useTemplate: AnyStr=\"\", visible: bool=True, visibleChangeCommand: Union[Script,\n bool]=None, width: Union[int, bool]=0, q=True, query=True, e=True, edit=True,\n **kwargs)->Union[AnyStr, Any]:\n pass","def floorplan(PAN, tilt1 = None): #---- placement floorplan\r\n if tilt1 is not None: PAN.img1_tilt = tilt1; # setup tilt angle for image 1\r\n PAN.H = np.zeros((PAN.count, 8)); # Transform matrix for floorplan\r\n print('---- floorplanning:')\r\n for k in range(PAN.count):\r\n PAN.H[k,0]= PAN.imgc[k].shape[0]; # set image height\r\n PAN.H[k,1]= PAN.imgc[k].shape[1]; # set image width\r\n PAN.H[k,2]= (0.5/np.tan(PAN.hfov/180*np.pi))* PAN.imgs[k].shape[1]; \r\n PAN.H[k,4]= 1; # set initial sizing = 1\r\n PAN.H[0,3]= PAN.img1_tilt/180*np.pi; # set tilt \r\n #--- compute new floorplan for image 2 ~ ... ---\r\n for k in range(1, PAN.count): # \r\n #for k in range(1, 2): # debug only \r\n KPS1 = PAN.KPDBs[k-1]; # load keypoint database\r\n KPS2 = PAN.KPDBs[k]; # \r\n H1 = PAN.H[k-1]; # transform function\r\n H2 = PAN.H[k]; # \r\n for m in range(0, PAN.match_seq.shape[0]):\r\n if PAN.match_seq[m, 0]== (k-1) and PAN.match_seq[m, 1]== k: \r\n match = PAN.matchinfo[m];\r\n pano_tools.stitch(KPS1, KPS2, H1, H2, match);","def push_down (grid):\r\n for i in range (3):\r\n for row in range(2,-1, -1):\r\n for col in range(4):\r\n if grid[row+1][col] == 0:\r\n grid[row+1][col] = grid[row][col]\r\n grid[row][col] = 0 \r\n for row in range(1,4):\r\n for col in range(4):\r\n if grid[row-1][col] == grid[row][col]:\r\n grid[row-1][col] = grid[row-1][col]*2\r\n grid[row][col]=0 \r\n for i in range (3):\r\n for row in range(2,-1, -1):\r\n for col in range(4):\r\n if grid[row+1][col] == 0:\r\n grid[row+1][col] = grid[row][col]\r\n grid[row][col] = 0 \r\n return grid","def _addPanes(self):\n\n self._addPaneMapWindow()\n self._addPaneToolbar(name = 'digitMap')","def put_next_tiles(p,tiles):\n if tiles['mode'].upper() == \"INIT\":\n set_value(p,tiles['0']['lig'],tiles['0']['col'],tiles['0']['val']) # mettre la vleur dans le plateau avec la position donnee de tiles\n set_value(p,tiles['1']['lig'],tiles['1']['col'],tiles['1']['val'])\n else:\n set_value(p,tiles['0']['lig'],tiles['0']['col'],tiles['0']['val'])","def foward_shimmey(self):\n for x in range(6):\n self.right(primary=60, counter=30)\n time.sleep(.5)\n self.left(primary=70, counter=30)\n time.sleep(.5)\n self.back()\n time.sleep(2) \n self.stop()","def reshape(self, bottom, top):\n\t\tpass","def get_wall_panels(self, wall_bp):\n wall_panels = []\n products = self.get_wall_products(wall_bp)\n for product in products:\n product_panel_list = self.get_product_panels(product, [])\n for product_panel in product_panel_list:\n wall_panels.append(product_panel)\n return wall_panels","def add_transforms(page):\n # Transform types\n\n # Allow choosing multiple\n transform_choice = [\"slice\", \"box\"]\n\n # Slicing panels into multiple panels\n # Works best with large panels\n if \"slice\" in transform_choice:\n page = single_slice_panels(page)\n\n # Makes v cuts happen more often 1/4 chance\n if np.random.random() < cfg.double_slice_chance:\n page = single_slice_panels(page)\n\n if \"box\" in transform_choice:\n\n if np.random.random() < cfg.box_transform_panel_chance:\n page = box_transform_panels(page)\n\n page = box_transform_page(page)\n\n return page","def treeBuddy():\n camera_move_offset_horiz = WIDTH / 70\n camera_move_offset_vert = HEIGHT / 70\n tree_found = False\n ctrl.resetCamera()\n for i in range(15):\n ctrl.moveCamera('left',camera_move_offset_horiz)\n img_obj.updateImg()\n img_obj.cropImg(Coords.crosshair_box)\n img_obj.modImg(1)\n img_obj.readPixels()\n if img_obj.isTree():\n print 'Tree...maybe'\n tree_found = False\n for i in range(2):\n ctrl.moveCamera('up',camera_move_offset_vert)\n img_obj.updateImg()\n img_obj.cropImg(Coords.crosshair_box)\n img_obj.modImg(1)\n img_obj.readPixels()\n if not img_obj.isTree():\n tree_found = False\n break\n tree_found = True\n ctrl.resetCamera()\n if tree_found:\n approachTree_getWood()","def move_buildings(self):","def push_up (grid):\r\n \r\n for row in range (4):\r\n section = []\r\n for col in range (4):\r\n section.append(grid[col][row])\r\n add(section)\r\n for i in range (4):\r\n grid[i][row] = section[i]","def controlOrder():\n return ['OverlayListPanel',\n 'LocationPanel',\n 'OverlayInfoPanel',\n 'OverlayDisplayPanel',\n 'CanvasSettingsPanel',\n 'AtlasPanel',\n 'OverlayDisplayToolBar',\n 'OrthoToolBar',\n 'FileTreePanel']","def next(self):\n if self.index.get() != len(self.frame_list) - 1:\n for i in range(len(self.frame_list)):\n self.frame_list[i].pack_forget()\n\n self.index.set(self.index.get() + 1)\n self.frame_list[self.index.get()].pack(fill=\"both\", expand=True)\n\n self.work_out_pages()","def actions(self):\n def create_move(de, vers):\n return lambda: self._move(de, vers)\n\n deplacements = []\n #itertools.product = boucle for imbriqué avec en parametre a,b\n # ici la longueur et la largeur du tableau\n for i, j in itertools.product(range(self.width),\n range(self.width)):\n #D : droite , G : gauche , B : bas , H : haut.\n directions = {'La gauche':(i, j-1),\n 'La droite':(i, j+1),\n 'Le haut':(i-1, j),\n 'Le bas':(i+1, j)}\n\n for action, (r, c) in directions.items():\n if r >= 0 and c >= 0 and r < self.width and c < self.width and \\\n self.plateau[r][c] == 0:\n deplacement = create_move((i,j), (r,c)), action\n deplacements.append(deplacement)\n return deplacements","def build_frames(self):\n self.cntrl_frame = tk.PanedWindow(self.root)\n self.cntrl_frame.pack(side = tk.TOP, padx = 1, pady = 1, fill = tk.Y)\n self.info_frame_1 = tk.PanedWindow(self.root)\n self.info_frame_1.pack(side = tk.TOP, padx = 1, pady = 2, fill = tk.Y)","def DoInsertPane(panes, dock_direction, dock_layer, dock_row, dock_pos):\r\n\r\n for ii in xrange(len(panes)):\r\n pane = panes[ii]\r\n if not pane.IsFloating() and pane.dock_direction == dock_direction and \\\r\n pane.dock_layer == dock_layer and pane.dock_row == dock_row and \\\r\n pane.dock_pos >= dock_pos:\r\n pane.dock_pos = pane.dock_pos + 1\r\n\r\n panes[ii] = pane\r\n\r\n return panes","def display(field):\n side = int(math.sqrt(len(field))) # in number of elements (tiles)\n \n def pos():\n cy, cx = win.getyx()\n stdscr.addstr(0, 0, \"cy: \"+str(cy)+\", cx: \"+str(cx))\n\n def br():\n while True:\n c = stdscr.getch()\n if c == curses.KEY_RIGHT:\n break\n win.refresh()\n\n win.addstr(0, 0, '┏')\n for _ in range(side-1):\n win.addstr('━━━━━━')\n win.addstr('┳')\n win.addstr('━━━━━━')\n win.addstr('┓ ')\n\n for y in range(side):\n \n win.addstr('┃')\n for x in range(side):\n #stdscr.addstr(0, 0, \"side: \" + str(x))\n idx = y * side + x\n if field[idx] == 0:\n win.addstr(' '.center(6))\n else:\n n = field[idx]\n color = curses.color_pair(0)\n if n < 0:\n field[idx] *= -1\n n = field[idx]\n color = curses.A_BOLD | curses.A_STANDOUT\n elif n == 4:\n color = curses.color_pair(3)\n elif n == 8:\n color = curses.color_pair(4)\n elif n >= 16:\n color = curses.color_pair(1)\n \n #win.addstr(str(n).center(6), color)\n \n n = str(n)\n left = (6-len(n)) // 2\n right = 6 - (left + len(n))\n win.addstr(left*' ')\n win.addstr(n, color)\n win.addstr(right*' ')\n\n \n win.addstr('┃')\n win.addstr(' ')\n if y == side-1:\n break\n else: \n win.addstr('┣')\n for _ in range(side-1):\n win.addstr('━━━━━━')\n win.addstr('╋')\n win.addstr('━━━━━━')\n win.addstr('┫ ')\n \n win.addstr('┗')\n for _ in range(side-1):\n win.addstr('━━━━━━')\n win.addstr('┻')\n win.addstr('━━━━━━')\n #pos()\n #br()\n win.addstr('┛')\n\n #win.border()\n win.refresh()","def cycle_option():\n winlist = create_win_list()\n winlist.insert(0,winlist[len(winlist)-1])\n winlist = winlist[:-1]\n arrange(get_simple_tile(len(winlist)),winlist)","def reshape(self,bottom,top):\n pass","def pobj_to_html5_ccs3_grid(pcode_obj, global_opts):\n html_str = []\n pkve = opts_load(global_opts[0])[2]\n pcode = (pcode_obj.asDict())['pcode'][0] # no multiple pcode blocks - no delimiter\n pcodeopts = pcode.pop('pcodeopts', [['']]) # {:::: } # pcodeopts = pcode['pcodeopts']\n\n galleries = pcode.pop('gallery', '')\n for gallery in galleries:\n galleryopts = gallery.pop('galleryopts', [['']]) # {::: }\n gkve = opts_load(galleryopts[0])[2] # aw, kvw, kvw =\n try:\n imgpath = gkve['imgpath']\n except KeyError:\n try:\n imgpath = pkve['imgpath']\n except KeyError:\n imgpath = ''\n html_str.append('<div class=\"gallery ' + opts_render(global_opts[0]) + ' ' + opts_render(galleryopts[0]) + '\">' + '\\n')\n\n spreads = gallery.pop('spread', '')\n g_layout_counter = 0\n for spread in spreads:\n spreadopts = spread.pop('spreadopts', [['']]) # {:: }\n html_str.append(' <div class=\"spread ' + opts_render(spreadopts[0]) + '\">' + '\\n')\n\n layouts = spread.pop('layout', '')\n for layout in layouts:\n g_layout_counter += 1\n panelcounter = 0\n panelskip = 0 # for blank x z panels\n layoutopts = layout.pop('layoutopts', [['']]) # {: }\n kve = opts_load(layoutopts[0])[2] # aw, kvw, kvw =\n i_before, i_str, i_after = img_render(\n kve, opts_render(layoutopts[0]),\n opts_render(spreadopts[0]),\n opts_render(galleryopts[0]),\n opts_render(pcodeopts[0]),\n opts_render(global_opts[0]),\n imgpath\n )\n html_str.append(i_before)\n if 'url' in kve:\n if 'http' not in kve['url']:\n html_str.append(' <a href=\"http://' + kve['url'] + '\">' + '\\n')\n else:\n html_str.append(' <a href=\"' + kve['url'] + '\">' + '\\n')\n html_str.append(' <div class=\"layout ' + opts_render(layoutopts[0]) + '\">' + '\\n')\n label_str_html = ''\n\n panelgroups = layout.pop('panelgroup', '')\n for panelgroup in panelgroups:\n panelgroupopts = panelgroup.pop('panelgroupopts', [['']]) # {}\n terms = panelgroup.pop('terms', [['']])\n # build row list -- grouped by commas and skipping +\n row_list = [[]]\n for term in terms[0]:\n # , adds row sublist\n if term == [',']:\n row_list.append([])\n # skip +\n elif term == ['+']:\n continue\n # missing counts = 1, e.g. ['']['r2'] = ['1']['r2']\n elif term[0] == '':\n term[0] = '1'\n row_list[-1].append(term)\n # 0 indicates a blank / spacer panel\n elif term[0] == '0':\n term[0] = '1'\n term.append('x') # or z? based on setting?\n row_list[-1].append(term)\n # setting panels to x or z will impact panel numbering and total count\n # just append anything else\n else:\n row_list[-1].append(term)\n\n # Find the panelgroup width. This is either:\n # 1. Defined above, in the pcode, gallery, spread, or layout level.\n # For example, newspaper comics might be defined at the spread\n # or layout level for reflow.\n # 2. ...or else: Defined in panelgroupopts.\n # 3. ...or else: Calculated from the longest row.\n # (i.e. discovered via comma placement)\n #\n # In the css3 renderer width must be specified in the panelgroup class.\n allopts = [pcodeopts[0], galleryopts[0],\n spreadopts[0], layoutopts[0], panelgroupopts[0]]\n pgroup_width = 0\n while allopts and pgroup_width == 0:\n opts = allopts.pop(0)\n for opt in opts:\n if isinstance(opt, basestring) and opt.startswith('w'):\n pgroup_width = int(opt[1:])\n break\n if pgroup_width == 0:\n # Find the length in panel spans of the longest row.\n # e.g. c3 + 2 = 5\n # This could be the first row, but not necessarily.\n # Rows are *not* the same length in groups with rowspans.\n # Rows could also be ragged. (in theory) although this\n # isn't explicitly supported.\n row_lengths = []\n for row in row_list:\n row_len = 0\n for panel in row:\n # check for 'c2' style column span arugment\n # ...there should be only one c arg, but the\n # max is taken if there are many, 1 if no arg.\n c_args = [int(arg[1:]) for arg in panel\n if isinstance(arg, basestring)\n and arg.startswith('c')\n and len(arg) > 1\n and arg[1:].isdigit()]\n # # print(c_args)\n try:\n c_max = max(c_args)\n except ValueError:\n c_max = 1\n # multiply panel width by panel count\n panel_len = int(panel[0]) * c_max\n # append panel length to total row length\n row_len = row_len + panel_len\n # append row length to list\n row_lengths.append(row_len)\n # set width to max\n pgroup_width = max(row_lengths)\n panelgroupopts[0][0] = panelgroupopts[0][0] + ' w' + unicode(pgroup_width)\n html_str.append(' <div class=\"panelgroup ' + panelgroupopts[0][0] + '\">' + '\\n')\n\n for row in row_list:\n # load panel arguments\n for panel in row:\n arg_add = []\n for idx, arg in enumerate(panel):\n # intercept generic u for CSS styling and add count\n if arg.startswith('u') and isinstance(arg, basestring):\n if len(arg) == 1:\n arg_add.append('u1')\n elif len(arg) > 1 and arg[1:].isdigit():\n arg_add.append('u')\n # note that the edge case e.g. u.u3 is not handled\n # this will be fine for renderer (u_max=3, correct label)\n # but will become u u1 u2 in css -- works but unclear\n panel = panel + arg_add\n panel_args = ' ' + ' '.join(panel[1:])\n panel_count = int(panel[0])\n # print panels, assigning counts and id labels\n for idx in range(0, panel_count):\n pas = panel_args.strip()\n # blank panels\n if 'x' in panel_args or 'z' in panel_args:\n panelcounter += 1\n panelskip += 1\n html_str.append(\n ' <div class=\"panel '\n + pas + '\">*</div>' + '\\n'\n )\n # unencoded (multi)panels -- mutually exclusive with blanks\n elif 'u' in panel_args:\n # ignore generic u and check for u# count\n u_args = [int(arg[1:]) for arg in panel\n if (arg.startswith('u')\n and len(arg) > 1)\n and arg[1:].isdigit()\n ]\n # after loading u_args, add generic u in-place for CSS styling\n try:\n u_max = max(u_args)\n except ValueError:\n u_max = 1\n if u_max == 0:\n panelcounter += 1\n panelskip += 1\n html_str.append(\n ' <div class=\"panel '\n + pas + '\">*</div>' + '\\n'\n )\n elif u_max == 1:\n panelcounter += 1\n label = unicode(panelcounter - panelskip)\n html_str.append(\n ' <div class=\"panel '\n + pas + '\">' + label + '</div>' + '\\n'\n )\n else:\n label = unicode(panelcounter + 1 - panelskip) + '-' + unicode(panelcounter + (u_max) - panelskip)\n html_str.append(\n ' <div class=\"panel '\n + pas + '\">' + label + '</div>' + '\\n'\n )\n panelcounter += u_max\n # regular panels\n else:\n panelcounter += 1\n label = unicode(panelcounter - panelskip)\n html_str.append(\n ' <div class=\"panel '\n + pas + '\">' + label + '</div>' + '\\n'\n )\n\n html_str.append(' </div>' + '\\n')\n\n html_str.append(i_str)\n try:\n label_str_html = ''\n for opt_str in [opts_render(layoutopts[0]),\n opts_render(spreadopts[0]),\n opts_render(galleryopts[0]),\n opts_render(pcodeopts[0])\n ]:\n if 'autolabel' in opt_str:\n try:\n label_str = os.path.splitext(os.path.basename(kve['img']))[0]\n except:\n label_str = unicode(g_layout_counter)\n label_str_html = ' <div class=\"label bottom\">' \\\n + label_str + '</div>' + '\\n'\n if 'label' in kve:\n label_str = kve['label']\n label_str_html = ' <div class=\"label bottom\"><div>' + label_str + '</div></div>' + '\\n'\n if label_str_html:\n html_str.append(' ' + label_str_html)\n except TypeError:\n pass\n html_str.append(' </div>' + '\\n')\n if 'url' in kve:\n html_str.append(' </a>' + '\\n')\n html_str.append(i_after)\n html_str.append(' </div>' + '\\n')\n html_str.append('</div>' + '\\n')\n\n return html_str","def __navigate_scroll(self):\n try:\n _title = self.browser.title\n _body = self.browser.find_element_by_tag_name('body')\n\n i = 0\n while i < 3:\n _html = str(self.browser.page_source)\n _content = Content(_html, _title)\n _attrs = _content.last_divs\n\n scroll_items = []\n for _attr in _attrs:\n xpath_string = '//div'\n\n for k, v in _attr.items():\n if not v:\n xpath_string = xpath_string + \"[@\" + str(k) + \"]\"\n else:\n if isinstance(v, list):\n _vstring = [\"contains(@\" + str(k) + \", '\" + str(_v) + \"')\" for _v in v]\n vstring = \" and \".join(_vstring)\n\n xpath_string = xpath_string + \"[\" + vstring + \"]\"\n\n div = self.browser.find_elements_by_xpath(xpath_string)\n\n for d in div: scroll_items.append(d)\n\n if len(scroll_items) > 10:\n j = 0\n while j < 10:\n try:\n self.browser.execute_script(\"arguments[0].scrollIntoView(true)\", scroll_items[j])\n self.browser.execute_script(\"arguments[0].scrollIntoView(true)\", scroll_items[0])\n time.sleep(1)\n j += 1\n except Exception as e:\n print(e)\n j += 1\n continue\n \n else:\n for item in scroll_items:\n try:\n self.browser.execute_script(\"arguments[0].scrollIntoView(true)\", item)\n self.browser.execute_script(\"arguments[0].scrollIntoView(true)\", scroll_items[0])\n _body.send_keys(Keys.HOME)\n time.sleep(1)\n except Exception as e:\n print(e)\n continue\n\n self.browser.execute_script(\"arguments[0].scrollIntoView(true)\", scroll_items[0])\n new_html = str(self.driver.page_source)\n new_content = Content(new_html, _title)\n new_attrs = new_content.last_divs\n\n i += 1\n if new_attrs == _attrs:\n break\n else:\n continue\n\n return self.browser.page_source\n\n except:\n return None","def _splay(self):\n\n if self.parent is not None: # case 1: already the root -> do nothing\n grandparent = self.parent.parent\n\n if grandparent is None: # case 2: one rotation to root\n self._zig()\n\n else: # case 3: multiple rotations to root\n rightOfLeft = self.parent.right is self and grandparent.left is self.parent\n leftOfRight = self.parent.left is self and grandparent.right is self.parent\n\n if rightOfLeft or leftOfRight: # case 3a: zigzag\n self._zig()\n self._zig()\n\n else: # case 3b: zigzig\n self.parent._zig()\n self._zig()\n\n self._splay() # recur until case 1 or 2 applies","def to_exam_root(self):\n self._bottom_tab(4)\n self._goto(\"exam_icon\")","def slideTile(self, i, j, direct):\n tile = self.getTile(i,j)\n if direct==Move.UP: # if the direction is up\n iRange = list(range(i - 1, -1, -1)) # list the squares above i,j\n jRange = [j]*len(iRange) # in iRange,jRange\n elif direct==Move.DOWN:\n iRange = list(range(i + 1, 4))\n jRange = [j]*len(iRange)\n elif direct==Move.LEFT:\n jRange = list(range(j - 1, -1, -1))\n iRange = [i]*len(jRange)\n else:\n jRange = list(range(j + 1, 4))\n iRange = [i]*len(jRange)\n\n # For each tile in the range above, below, to the left or right\n for k in range(len(iRange)):\n nextTile = self.getTile(iRange[k], jRange[k])\n nextTileCombined = self.getCombined(iRange[k], jRange[k])\n # If the next tile isn't empty\n if nextTile != 0:\n # And it's the same as the original tile and the next tile\n # hasn't already been combined\n if nextTile == tile and not nextTileCombined:\n totalVal = tile*2\n # Combine the tiles in the place of the hit tile, set\n # combined, and empty original tile.\n self.setTile(iRange[k],jRange[k],totalVal)\n self.setCombined(iRange[k],jRange[k])\n self.emptyTile(i,j)\n return totalVal\n # If the tiles are different and it's the first tile\n elif k == 0:\n return 0 # Do nothing\n # Of they are different and it's after the first tile\n else:\n # Move tile to place before next tile\n self.emptyTile(i,j)\n # Set the space before the nonempty tile to the current\n self.setTile(iRange[k - 1],jRange[k - 1],tile)\n return 0\n # If it has gone through all squares and they were all empty\n elif k == len(iRange) - 1:\n self.setTile(iRange[k],jRange[k],tile)\n self.emptyTile(i,j)\n return 0","def front_wall(self):\n self.place = \"bed\"\n print(\"You are infront of the bed.\"\n \"You look under it and find a notebook.\")\n nb = Notebook('notebook')\n nb.clue()","def make_sub_views(root, loi, func):\n item_frame = Frame(root)\n item_frame.grid()\n for i, item in enumerate(loi):\n func(item_frame, item).pack(side=\"left\", fill=\"y\")","def push_down (grid):\r\n for a in range(4): \r\n for i in range(2,-1,-1): \r\n for j in range(4): \r\n if grid[i+1][j]==0: \r\n grid[i+1][j]=grid[i][j] \r\n grid[i][j]=0\r\n \r\n for i in range(2,-1,-1): \r\n for j in range(4): \r\n if grid[i][j]==grid[i+1][j]: \r\n grid[i+1][j]=(grid[i+1][j])*2\r\n grid[i][j]=0\r\n \r\n for a in range(4): \r\n for i in range(2,-1,-1): \r\n for j in range(4): \r\n if grid[i+1][j]==0: \r\n grid[i+1][j]=grid[i][j] \r\n grid[i][j]=0","def select_walls(matrix, xaxis, yaxis, zaxis):\n clear()\n print(\"Now we're going to construct the interior of the rooms.\")\n print(\"I'm going to present you with all rooms that have been selected.\")\n print(\"I want you to indicate where the walls should be placed in each room.\")\n print(\"Just like room selection, you will indicate, by a list of numbers,\")\n print(\"where the walls should be placed.\")\n print()\n print(\"In locations where a room is adjacent to a void space, a non-optional\")\n print(\"will automatically be inserted. Later some of these can be removed\")\n print(\"to create vertical trasversals, but for now, just consider each\")\n print(\"floor individually.\")","def panel_callback():\n if self.minwidth is None:\n self.minwidth = self.button_stack.winfo_width()\n\n if self.current_panel:\n self.sashpos = self.paned.sashpos(0)\n self.current_panel.forget()\n if isinstance(self.current_panel, class_obj):\n self.current_panel = None\n self.paned.sashpos(0, self.minwidth)\n return\n\n if class_obj.__name__ in self.panels:\n panel = self.panels[class_name]\n else:\n panel = self.panels[class_name] = class_obj(self, self.app)\n\n panel.pack(side=tk.LEFT, expand=1, fill=tk.BOTH)\n\n if self.sashpos is None:\n self.sashpos = 300\n\n self.paned.sashpos(0, self.sashpos)\n\n self.current_panel = panel","def generate_children(self, current_state):\n # Define a list of the possible moves that this current state can make\n list_of_possible_moves = []\n\n # Find the index of the '0' tile\n index = current_state.index('0')\n\n # Check all the possible moves and see which are possible for this current state\n move_up_copy = current_state.copy()\n result = self.move_up(move_up_copy)\n if result[0] > 0:\n list_of_possible_moves.append((move_up_copy, self.cost_of_move_up, 'move_up', result[1]))\n\n move_down_copy = current_state.copy()\n result = self.move_down(move_down_copy)\n if result[0] > 0:\n list_of_possible_moves.append((move_down_copy, self.cost_of_move_down, 'move_down', result[1]))\n\n move_left_copy = current_state.copy()\n result = self.move_left(move_left_copy)\n if result[0] > 0:\n list_of_possible_moves.append((move_left_copy, self.cost_of_move_left, 'move_left', result[1]))\n\n move_right_copy = current_state.copy()\n result = self.move_right(move_right_copy)\n if result[0] > 0:\n list_of_possible_moves.append((move_right_copy, self.cost_of_move_right, 'move_right', result[1]))\n\n # Two possible moves can be done if the wrap is allowed\n if self.can_move_wrap(index):\n # The regular (horizontal) wrap\n regular_wrap_copy = current_state.copy()\n result = self.wrap(regular_wrap_copy)\n if result[0] > 0:\n list_of_possible_moves.append((regular_wrap_copy, self.cost_of_wrap_move, 'wrap', result[1]))\n\n # The scaled-up (vertical) wrap\n scaled_wrap_copy = current_state.copy()\n result = self.wrap_scale(scaled_wrap_copy)\n if result[0] > 0:\n list_of_possible_moves.append((scaled_wrap_copy, self.cost_of_wrap_move, 'wrap_scale', result[1]))\n # end: if\n\n # Two possible moves can be done if the diagonal action is allowed\n if self.can_move_diagonally(index):\n # The diagonal adjacent:\n diagonal_adjacent_copy = current_state.copy()\n result = self.diagonal_adjacent(diagonal_adjacent_copy)\n list_of_possible_moves.append(\n (diagonal_adjacent_copy, self.cost_of_diagonal_adjacent, 'diagonal_adjacent', result[1]))\n\n # The diagonal across:\n diagonal_across_copy = current_state.copy()\n result = self.diagonal_across(diagonal_across_copy)\n list_of_possible_moves.append(\n (diagonal_across_copy, self.cost_of_diagonal_across, 'diagonal_across', result[1]))\n # end: if\n\n # Return the list of possible moves\n return list_of_possible_moves","def last_pg_results(self, graham_picks, lynch_picks, *args):\n crrnt_pg, container, parent = args\n\n frame = PageEleven(self.container, parent, graham_picks, lynch_picks)\n self.frames[PageEleven] = frame\n frame.grid(row=0, column=0, sticky=\"nsew\")\n frame.tkraise()","def marathon(self):\n self.buttons = []\n self.screen.blit(self.background_image, (0, 0))\n button_height = 200\n button_width = 200\n row_height = self.height // 2 - button_height\n row_starting_width = self.width // 10\n # First line of buttons\n for i in range(5):\n self.create_button((row_starting_width * (3 + (i - 1) * 2) - 100, row_height),\n button_width,\n button_height,\n Colors.BLACK,\n str(i))\n # Second line of buttons\n row_height = row_height + button_height + 100\n for i in range(5):\n self.create_button((row_starting_width * (3 + (i - 1) * 2) - 100, row_height),\n button_width,\n button_height,\n Colors.BLACK,\n str(i + 5))\n self.show_buttons()\n self.show_text_in_buttons()\n pygame.display.flip()","def init(self, windowsize:tuple):\r\n y_count, x_count = 3, 0 #< Set the starting counter for the look_up_table. y starts with three because the first three lines are just Nones\r\n # Creating the constant maze \r\n maze_size = windowsize[0], windowsize[1] - 2 * self.grid_size\r\n self.maze = pg.Surface(maze_size) \r\n \r\n \r\n \r\n # Draw the outermost rectangles on self.maze\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((0, 3 * self.grid_size), (28 * self.grid_size, 31 * self.grid_size)), 4)\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((0 + self.grid_size // 2, 3 * self.grid_size + self.grid_size // 2),(27 * self.grid_size, 30 * self.grid_size)), 4) \r\n # Draw the inner rectangles\r\n for y in self.look_up_table[3 : -2]: #< y is a list of one row from the maze\r\n for x in y: #< x is a string that is decoded as already explained\r\n pos = [self.grid_size * x_count, self.grid_size * y_count]\r\n # Set reference position in the middle of one square\r\n pos[0] += self.grid_size // 2\r\n pos[1] += self.grid_size // 2\r\n x_count += 1\r\n # Check if x is rectangle\r\n if x != None and x[0] == 'r':\r\n # When the size of the string is equal or greater than 4 it's rectangle with a specific size and not just a border.\r\n if len(x) >= 4:\r\n # get the x and y size of the rectangle. x will be something like 'rx1_y1' x1 resprestens the size in x direction and y1 in y direction.\r\n xy_dim = x[1:].split(\"_\") \r\n xy_dim[0] = int(xy_dim[0])\r\n xy_dim[1] = int(xy_dim[1])\r\n rect = tuple(pos), (xy_dim[0] * self.grid_size , xy_dim[1] * self.grid_size )\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], rect, self.width)\r\n # If the last char is a w (white), u (up) or l (left) a line gets draw one a specific position \r\n if x[-1] == 'w':\r\n self.draw_line(self.maze, 'u', (x_count,y_count), True)\r\n if x[-1] == 'u' or x[-1] == 'l':\r\n if x_count == 0:\r\n self.draw_line(self.maze, x[-1], (len(y), y_count))\r\n else:\r\n self.draw_line(self.maze, x[-1], (x_count, y_count))\r\n \r\n y_count += 1\r\n x_count = 0\r\n # Just some cosmetic drawing\r\n pg.draw.rect(self.maze, Colors.colors['BLACK'], ((0, 12 * self.grid_size + self.grid_size // 2 + 4), (self.grid_size // 2 + 1, 10 * self.grid_size - 4)), 4)\r\n pg.draw.rect(self.maze, Colors.colors['BLACK'], ((28 * self.grid_size - self.grid_size // 2 - 1, 12 * self.grid_size + self.grid_size // 2 + 4), (self.grid_size // 2 + 1, 10 * self.grid_size - 4)), 4)\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((-self.width, 13 * self.grid_size), (5 * self.grid_size, 3 * self.grid_size)), self.width)\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((-self.width, 19 * self.grid_size), (5 * self.grid_size, 3 * self.grid_size)), self.width)\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((23 * self.grid_size, 13 * self.grid_size), (5 * self.grid_size + 10, 3 * self.grid_size)), self.width)\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((23 * self.grid_size, 19 * self.grid_size), (5 * self.grid_size + 10, 3 * self.grid_size)), self.width)\r\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((11 * self.grid_size, 16 * self.grid_size), (6 * self.grid_size, 3 * self.grid_size)), self.width)\r\n \r\n pg.draw.line(self.maze, Colors.colors['BLUE'], (0, 16 * self.grid_size + self.grid_size // 2 - 1), (self.grid_size // 2 + self.width, 16 * self.grid_size + self.grid_size // 2 - 1), self.width)\r\n pg.draw.line(self.maze, Colors.colors['BLUE'], (0, 18 * self.grid_size + self.grid_size // 2), (self.grid_size // 2 + self.width, 18 * self.grid_size + self.grid_size // 2), self.width)\r\n pg.draw.line(self.maze, Colors.colors['BLUE'], (self.grid_size * 28 - self.grid_size, 16 * self.grid_size + self.grid_size // 2 - 1), (self.grid_size * 28 + self.width, 16 * self.grid_size + self.grid_size // 2 - 1), self.width)\r\n pg.draw.line(self.maze, Colors.colors['BLUE'], (self.grid_size * 28 - self.grid_size, 18 * self.grid_size + self.grid_size // 2), (self.grid_size * 28 + self.width, 18 * self.grid_size + self.grid_size // 2), self.width)\r\n self.is_init = True","def startPresentation(ntrials):\n\n for trialIdx in range(ntrials):\n\n # draw the fixcross followed by the star\n drawFixCross(1.0)\n drawStar(4.0)","def reshape(self, bottom, top):\r\n pass","def main():\n LayoutsWithPanels().mainloop()","def LoadPerspective(self, layout, update=True):\r\n\r\n input = layout\r\n\r\n # check layout string version\r\n # 'layout1' = wxAUI 0.9.0 - wxAUI 0.9.2\r\n # 'layout2' = wxAUI 0.9.2 (wxWidgets 2.8)\r\n index = input.find(\"|\")\r\n part = input[0:index].strip()\r\n input = input[index+1:]\r\n \r\n if part != \"layout2\":\r\n return False\r\n\r\n # mark all panes currently managed as docked and hidden\r\n for pane in self._panes:\r\n pane.Dock().Hide()\r\n\r\n # clear out the dock array; this will be reconstructed\r\n self._docks = []\r\n\r\n # replace escaped characters so we can\r\n # split up the string easily\r\n input = input.replace(\"\\\\|\", \"\\a\")\r\n input = input.replace(\"\\\\;\", \"\\b\")\r\n\r\n while 1:\r\n\r\n pane = AuiPaneInfo()\r\n index = input.find(\"|\")\r\n pane_part = input[0:index].strip()\r\n input = input[index+1:]\r\n\r\n # if the string is empty, we're done parsing\r\n if pane_part == \"\":\r\n break\r\n\r\n if pane_part[0:9] == \"dock_size\":\r\n index = pane_part.find(\"=\")\r\n val_name = pane_part[0:index]\r\n value = pane_part[index+1:]\r\n\r\n index = val_name.find(\"(\")\r\n piece = val_name[index+1:]\r\n index = piece.find(\")\")\r\n piece = piece[0:index]\r\n\r\n vals = piece.split(\",\")\r\n dir = int(vals[0])\r\n layer = int(vals[1])\r\n row = int(vals[2])\r\n size = int(value)\r\n \r\n dock = AuiDockInfo()\r\n dock.dock_direction = dir\r\n dock.dock_layer = layer\r\n dock.dock_row = row\r\n dock.size = size\r\n self._docks.append(dock)\r\n \r\n continue\r\n\r\n # Undo our escaping as LoadPaneInfo needs to take an unescaped\r\n # name so it can be called by external callers\r\n pane_part = pane_part.replace(\"\\a\", \"|\")\r\n pane_part = pane_part.replace(\"\\b\", \";\")\r\n\r\n pane = self.LoadPaneInfo(pane_part, pane)\r\n\r\n p = self.GetPane(pane.name)\r\n \r\n if not p.IsOk():\r\n if pane.IsNotebookControl():\r\n # notebook controls - auto add...\r\n self._panes.append(pane)\r\n indx = self._panes.index(pane)\r\n else:\r\n # the pane window couldn't be found\r\n # in the existing layout -- skip it\r\n continue\r\n\r\n else:\r\n indx = self._panes.index(p)\r\n pane.window = p.window\r\n pane.frame = p.frame\r\n pane.buttons = p.buttons\r\n self._panes[indx] = pane\r\n\r\n if isinstance(pane.window, auibar.AuiToolBar) and (pane.IsFloatable() or pane.IsDockable()):\r\n pane.window.SetGripperVisible(True)\r\n \r\n if update:\r\n self.Update()\r\n\r\n return True","def elements_page(self):\n self.list_frame = tk.Frame(self.page)\n self.data_frame = tk.Frame(self.page)\n p2_label_2 = ttk.Label(self.page, text=self.lang.VP_CON_DDBB, font=FONT_BENVINGUDA)\n p2_button_1 = ttk.Button(self.page, text=self.lang.BACK, command=self.tornar_main)\n self.crear_elements_viewer()\n self.page.grid(row=0, column=0, sticky=\"NESW\")\n p2_label_2.pack(pady=20)\n p2_button_1.pack(pady=0, ipadx=15)\n self.list_frame.pack()\n self.data_frame.pack()\n self.p2_frame_list.pack(pady=15, padx=5, expand=False, side=tk.LEFT)\n self.evo_frame.pack(pady=15, padx=5, expand=False, side=tk.RIGHT)\n self.p2_frame_list_2.pack(pady=15, padx=5, expand=False, side=tk.RIGHT)\n self.p2_frame_list_1.pack(pady=15, padx=5, expand=False, side=tk.RIGHT)\n self.p2_frame_elements.pack(pady=0, padx=10, side=tk.LEFT)\n self.p2_frame_img.grid(row=1, column=1, pady=5, padx=20, sticky=\"w\")\n self.p2_frame_metadata.grid(row=1, column=2, pady=20, padx=20, sticky=\"w\")","def UnsplitDClick(self, part, sash_size, pos):\r\n\r\n if not self._sash_dclick_unsplit:\r\n # Unsplit not allowed\r\n return\r\n\r\n pos1 = wx.Point(*pos)\r\n pos2 = wx.Point(*pos)\r\n if part.orientation == wx.HORIZONTAL:\r\n pos1.y -= 2*sash_size\r\n pos2.y += 2*sash_size + self.GetTabCtrlHeight()\r\n elif part.orientation == wx.VERTICAL:\r\n pos1.x -= 2*sash_size\r\n pos2.x += 2*sash_size\r\n else:\r\n raise Exception(\"Invalid UI part orientation\")\r\n\r\n pos1, pos2 = self.ClientToScreen(pos1), self.ClientToScreen(pos2)\r\n win1, win2 = wx.FindWindowAtPoint(pos1), wx.FindWindowAtPoint(pos2)\r\n\r\n if isinstance(win1, wx.ScrollBar):\r\n # Hopefully it will work\r\n pos1 = wx.Point(*pos)\r\n shift = wx.SystemSettings.GetMetric(wx.SYS_VSCROLL_X) + 2*(sash_size+1)\r\n if part.orientation == wx.HORIZONTAL:\r\n pos1.y -= shift\r\n else:\r\n pos1.x -= shift\r\n \r\n pos1 = self.ClientToScreen(pos1)\r\n win1 = wx.FindWindowAtPoint(pos1)\r\n\r\n if isinstance(win2, wx.ScrollBar):\r\n pos2 = wx.Point(*pos)\r\n shift = wx.SystemSettings.GetMetric(wx.SYS_VSCROLL_X) + 2*(sash_size+1)\r\n if part.orientation == wx.HORIZONTAL:\r\n pos2.y += shift\r\n else:\r\n pos2.x += shift\r\n\r\n pos2 = self.ClientToScreen(pos2)\r\n win2 = wx.FindWindowAtPoint(pos2)\r\n\r\n if not win1 or not win2:\r\n # How did we get here?\r\n return\r\n\r\n if isinstance(win1, AuiNotebook) or isinstance(win2, AuiNotebook):\r\n # This is a bug on MSW, for disabled pages wx.FindWindowAtPoint\r\n # returns the wrong window.\r\n # See http://trac.wxwidgets.org/ticket/2942\r\n return\r\n\r\n tab_frame1, tab_frame2 = self.GetTabFrameFromWindow(win1), self.GetTabFrameFromWindow(win2)\r\n\r\n if not tab_frame1 or not tab_frame2:\r\n return\r\n\r\n tab_ctrl_1, tab_ctrl_2 = tab_frame1._tabs, tab_frame2._tabs\r\n\r\n if tab_ctrl_1.GetPageCount() > tab_ctrl_2.GetPageCount():\r\n src_tabs = tab_ctrl_2\r\n dest_tabs = tab_ctrl_1\r\n else:\r\n src_tabs = tab_ctrl_1\r\n dest_tabs = tab_ctrl_2\r\n\r\n selection = -1\r\n page_count = dest_tabs.GetPageCount()\r\n \r\n for page in xrange(src_tabs.GetPageCount()-1, -1, -1):\r\n # remove the page from the source tabs\r\n page_info = src_tabs.GetPage(page)\r\n if page_info.active:\r\n selection = page_count + page\r\n src_tabs.RemovePage(page_info.window)\r\n\r\n # add the page to the destination tabs\r\n dest_tabs.AddPage(page_info.window, page_info)\r\n if page_info.control:\r\n self.ReparentControl(page_info.control, dest_tabs)\r\n \r\n self.RemoveEmptyTabFrames()\r\n\r\n dest_tabs.DoShowHide()\r\n self.DoSizing()\r\n dest_tabs.Refresh()\r\n self._mgr.Update()\r\n if selection > 0:\r\n wx.CallAfter(dest_tabs.MakeTabVisible, selection, self)","def on_btnHabita_clicked(self,widget):\n try:\n panelactual = variables.panel.get_current_page()\n if panelactual != 2:\n variables.panel.set_current_page(2)\n else:\n pass\n except:\n print(\"error botón habitacion barra herramientas\")","def make_chf_panel(self) :\n\n chf_panel = JPanel()\n chf_panel.setLayout(MigLayout('insets 0'))\n\n\n chf_files_label = JLabel('Hemisegment cells')\n chf_files_text = JTextArea(BobGui.archetype_to_str(self.exper.hseg_cell_files_cab().archetype))\n\n chf_panel.add(chf_files_label, 'growx, wrap')\n chf_panel.add(chf_files_text, 'grow, wrap')\n\n\n chf_files_label = JLabel('Hemisegment binary image files')\n chf_files_text = JTextArea(BobGui.archetype_to_str(self.exper.hseg_bin_files_cab().archetype))\n\n chf_panel.add(chf_files_label, 'growx, wrap')\n chf_panel.add(chf_files_text, 'grow, wrap')\n\n\n chf_files_label = JLabel('Intensity Image Files')\n # chf_files_text = JTextArea(BobGui.archetype_to_str(self.exper.hseg_intens_im_files_cab().archetype))\n # print(self.exper.hseg_intens_im_files_cab().archetype)\n\n # chf_panel.add(chf_files_label, 'growx, wrap')\n # chf_panel.add(chf_files_text, 'grow, wrap')\n\n\n self.intens_im_boxes = []\n intens_im_panel = JPanel()\n intens_im_panel.setLayout(MigLayout('insets 0'))\n for poss_im_file in self.exper.hseg_intens_im_files_cab().archetype:\n self.intens_im_boxes.append(JCheckBox(poss_im_file))\n intens_im_panel.add(self.intens_im_boxes[-1], 'wrap')\n\n\n chf_panel.add(chf_files_label, 'growx, wrap')\n chf_panel.add(intens_im_panel, 'grow, wrap')\n\n\n mdf_create_button = JButton('Create meta_data file from default outline')\n # mdf_create_button = JButton('<html>Create meta_data file<br>from default outline</html>')\n mdf_create_button.addActionListener(ActionListenerFactory(self, self.mdf_create_al))\n mdf_open_button = JButton('Open existing meta_data file')\n mdf_open_button.addActionListener(ActionListenerFactory(self, self.mdf_open_al))\n\n # meta_data_file_buttton = JButton('Open/Create meta_data file')\n # meta_data_file_buttton.addActionListener(ActionListenerFactory(self, self.meta_data_al))\n\n # chf_panel.add(meta_data_file_buttton)\n chf_panel.add(mdf_create_button, 'wrap')\n chf_panel.add(mdf_open_button, 'wrap')\n chf_scroll_pane = JScrollPane()\n chf_scroll_pane.getViewport().setView(chf_panel)\n\n return chf_scroll_pane","def handle(self, event):\n for panel in self.sub_panels:\n panel.handle(event)\n\n # KEY EVENTS\n if event.type == pg.KEYDOWN:\n # moving across the map\n if event.key == pg.K_d:\n self.city_graphics.add_move_speed((-self.SCROLL_SPEED, 0))\n elif event.key == pg.K_s:\n self.city_graphics.add_move_speed((0, -self.SCROLL_SPEED))\n elif event.key == pg.K_a:\n self.city_graphics.add_move_speed((self.SCROLL_SPEED, 0))\n elif event.key == pg.K_w:\n self.city_graphics.add_move_speed((0, self.SCROLL_SPEED))\n\n if event.type == pg.KEYUP:\n # moving across the map\n if event.key == pg.K_d:\n self.city_graphics.add_move_speed((self.SCROLL_SPEED, 0))\n elif event.key == pg.K_s:\n self.city_graphics.add_move_speed((0, self.SCROLL_SPEED))\n elif event.key == pg.K_a:\n self.city_graphics.add_move_speed((-self.SCROLL_SPEED, 0))\n elif event.key == pg.K_w:\n self.city_graphics.add_move_speed((0, -self.SCROLL_SPEED))\n\n # MOUSE EVENTS\n for panel in self.sub_panels:\n if panel.collide():\n self.city_graphics.hovered(None, self.mode)\n self.button_down = False\n return\n\n # !!! only if mouse isn't above another panel !!!#\n\n if event.type == pg.MOUSEBUTTONUP:\n if event.button == pg.BUTTON_LEFT:\n self.button_down = False\n\n # zooming in\n if event.button == 4:\n self.city_graphics.zoom(self.ZOOM_VALUE)\n\n if event.type == pg.MOUSEBUTTONDOWN:\n bought = False\n self.menu_panel.option_panel.disable()\n if self.warning_panel:\n self.warning_panel.disable()\n self.warning_panel = None\n\n if event.button == pg.BUTTON_LEFT:\n self.button_down = True\n if self.construct_to_buy:\n clicked_lot = self.city_graphics.get_clicked_lot(\n pg.mouse.get_pos())\n if clicked_lot.set_construct(self.construct_to_buy):\n self.simulator.integrate_construct(clicked_lot)\n self.construct_to_buy = None\n bought = True\n\n if self.mode == 'road_placing':\n if event.button == pg.BUTTON_RIGHT:\n self.city_space.road_system.hovered_direction *= -1\n elif event.button == pg.BUTTON_LEFT:\n self.city_space.road_clicked()\n\n elif not self.zoning:\n if event.button == pg.BUTTON_LEFT:\n self.city_graphics.select_lot(pg.mouse.get_pos())\n if not self.bulldozing and not bought and self.mode != 'access_highlighting':\n self.set_upgrade_panel()\n\n # zooming out\n if event.button == 5:\n self.city_graphics.zoom(1 / self.ZOOM_VALUE)\n\n if event.type == pg.MOUSEMOTION or event.type or event.type == pg.MOUSEBUTTONDOWN:\n clicked_lot = self.city_graphics.get_clicked_lot(\n pg.mouse.get_pos())\n if self.button_down:\n if self.zoning and self.simulator.can_buy(zone=self.zoning_type):\n if clicked_lot and clicked_lot.set_zone(self.zoning_type):\n self.simulator.integrate_construct(clicked_lot)\n\n elif self.bulldozing:\n if clicked_lot and clicked_lot.remove_construct():\n self.simulator.integrate_construct(\n clicked_lot, remove=True)\n\n else:\n self.city_graphics.hovered(\n pg.mouse.get_pos(), self.mode)","def ubicar_naves():\n tablero.clear()\n crear_tablero(tablero)\n ubicar_portaviones()\n ubicar_fragata()\n ubicar_submarino()","def next_widget(self):\r\n for i in self.widgets[1:]:\r\n if i.get_visible():\r\n self.set_top_widget(i)\r\n return","def expand(self):\n\t\tfor move in self.moves:\n\t\t\tm = self.Game.create_move(self.State, move.row, move.column, move.shift, False)\n\t\t\tchildstate = self.Game.apply_move(copy.deepcopy(self.State), m)\n\t\t\tchild = GameNode(self.Game, m, childstate, self.Game.get_moves(childstate), self)\n\t\t\tself.addChild(child)","def setup_containers(self):\r\n self.container_widgets[\"main_frame\"].grid(row=0, column=0, sticky='news')\r\n self.container_widgets[\"panel_frame\"].grid(row=0, column=0)\r\n self.container_widgets[\"order_frame\"].grid(row=1, column=0, sticky='nw')\r\n self.container_widgets[\"order_frame\"].grid_rowconfigure(0, weight=5)\r\n self.container_widgets[\"order_frame\"].grid_columnconfigure(0, weight=5)\r\n self.container_widgets[\"order_canvas\"].grid(row=0, column=0, sticky='news')\r\n self.container_widgets[\"orders_container\"].grid(column=0, row=0)","def separate_frontier(self):\n\t#print self.frontier\n region = [] # a list of tuples\n region_list = [] # a list of regions\n in_list = False\n region_size = 7\n num_regions = 25\n n = 0\n h = 0\n print \"separate frontier\"\n while(region_size>0):\n for i in range(len(self.frontier)):\n if (h < num_regions):\n region = []\n self.find_region(self.frontier[i], region)\n\t\t #rospy.loginfo(region)\n in_list = region in region_list\n if (len(region) > region_size) and (not in_list):\n region_list.append(region)\n h += 1\n self.regions = region_list\n region_size -= 1\n\t#print self.regions","def _layout(self):\n top = 2.0\n y = 0.0\n x = 0.0\n maxend = 0.0\n for track in self._tracks:\n track.set_view(self.view.species, self.view.seqname, \n self.view.start, self.view.end)\n tracksize = track.get_size()\n y -= tracksize[1]\n track.set_pos(track.pos_offset[0] + x, track.pos_offset[1] + y)\n self.size = [self.view.end - self.view.start + 1, 0 - y]","def blank(self, index=-1):\n self.displays[0].start() # call only once to support shift chain\n if index < 0:\n for d in self.displays:\n d.blank()\n else:\n self.displays[index].blank()\n self.displays[0].latch() # call only once to support shift chain","def printBoard(self):\n if self.side == self.WHITE or self.side == None:\n for r in [8,7,6,5,4,3,2,1]:\n for c in 'abcdefgh':\n p = self.getPiece(c,r) # print a8 first\n if p == None:\n print \" \",\n else:\n print self.getPieceName(p.type),\n print \"\"\n else:\n for r in [1,2,3,4,5,6,7,8]:\n for c in 'hgfedcba':\n p = self.getPiece(c,r) # print h1 first\n if p == None:\n print \" \",\n else:\n print self.getPieceName(p.type),\n print \"\"","def _generate_maze(self):\n grid = [[GridCell(x, y, self._treasure_prob) for x in range(self._map_size)] for y in range(self._map_size)]\n\n center_x = self._map_size // 2\n center_y = self._map_size // 2\n\n for _ in range(self._sparsity):\n current = grid[center_x][center_y]\n stack = list()\n start = True\n while len(stack) or start:\n start = False\n current.visited = True\n children = current.has_children(grid)\n\n if children:\n choice = np.random.choice(children)\n choice.visited = True\n\n stack.append(current)\n\n self._remove_walls(current, choice)\n\n current = choice\n\n elif stack:\n current = stack.pop()\n for row in grid:\n for cell in row:\n cell.visited = False\n\n # edit center area\n grid[center_x][center_y].set_treasury()\n for x in range(center_x - 1, center_x + 2):\n for y in range(center_y - 1, center_y + 2):\n grid[x][y].erase_walls()\n return grid","def recreate_grid(self):\n\n self.print_numlist = arcade.SpriteList()\n for row in range(ROW_COUNT):\n for column in range(COLUMN_COUNT):\n sprite = arcade.Sprite(\n f\"Numbers/{self.grid[row][column]}.png\", scale=0.2\n )\n x = (MARGIN + WIDTH) * column + MARGIN + WIDTH // 2\n y = (MARGIN + HEIGHT) * row + MARGIN + HEIGHT // 2\n sprite.center_x = x\n sprite.center_y = y\n self.print_numlist.append(sprite)\n # Check to see if all squares have been filled in\n if 0 not in self.grid:\n # if Cameron.Check_for_Completion(self.grid) == True:\n self.done = True","def move_to_position1(self):","def traverse_scaffold(self):\n\n y, x, theta = self.find_start_pose()\n dy, dx = -np.sin(theta), np.cos(theta)\n straight, instruction_string = 0, ''\n\n while True:\n # Either scaffold infront of us\n if self.mp[y+dy,x+dx] == ord('#') or self.mp[y+dy,x+dx] == ord('O'):\n self.mp[y,x] = ord('O')\n straight += 1\n y, x = y+dy, x+dx\n # Otherwise, it is to our left or right\n else:\n if self.mp[y-1,x] == ord('#'): theta_ = np.pi/2\n elif self.mp[y+1,x] == ord('#'): theta_ = -np.pi/2\n elif self.mp[y,x-1] == ord('#'): theta_ = -np.pi\n elif self.mp[y,x+1] == ord('#'): theta_ = 0\n\n # Reached the end\n else:\n self.mp[y,x] = ord('x')\n if straight > 0:\n instruction_string = instruction_string + str(straight)\n\n return instruction_string\n\n if straight > 0:\n instruction_string = instruction_string + str(straight) + ','\n straight = 0\n\n # Find angle between directions\n d = np.arccos(np.dot([np.sin(theta+np.pi/2), np.cos(theta+np.pi/2)],\n [np.sin(theta_), np.cos(theta_)]))\n \n if d == 0:\n instruction_string += 'L,'\n theta = theta+np.pi/2\n else:\n instruction_string += 'R,'\n theta = theta-np.pi/2\n # Update orientation\n \n dy,dx = np.int(-np.sin(theta)),np.int(np.cos(theta))","def do_layout(self):\n self.define_panel_structure()\n self.layout_selection()\n self.layout_data_list()\n self.layout_batch()\n self.layout_button()","def _scroll_screen(direction: int) -> Callable:\n def _inner(qtile: Qtile):\n if len(qtile.screens) == 1:\n current = qtile.groups.index(qtile.current_group)\n destination = (current + direction) % 6\n qtile.groups[destination].cmd_toscreen()\n return\n\n current = qtile.groups.index(qtile.current_group)\n if current < 3:\n destination = (current + direction) % 3\n else:\n destination = ((current - 3 + direction) % 3) + 3\n qtile.groups[destination].cmd_toscreen()\n\n return _inner"],"string":"[\n \"def box_transform_panels(page, type_choice=None, pattern=None):\\n\\n if type_choice is None:\\n type_choice_prob = np.random.random()\\n if type_choice_prob < cfg.panel_box_trapezoid_ratio:\\n type_choice = \\\"trapezoid\\\"\\n else:\\n type_choice = \\\"rhombus\\\"\\n\\n if type_choice == \\\"trapezoid\\\":\\n if page.num_panels > 2:\\n\\n # Get parent panel which satisfies the criteria for the transform\\n relevant_panels = find_parent_with_multiple_children(page, 3)\\n\\n if len(relevant_panels) > 0:\\n if len(relevant_panels) > 1:\\n num_panels = np.random.randint(1, len(relevant_panels))\\n else:\\n num_panels = 1\\n\\n # For each panel\\n for idx in range(0, num_panels):\\n panel = relevant_panels[idx]\\n\\n # Get the three child panels\\n # Since panels are created in order\\n p1 = panel.get_child(0)\\n p2 = panel.get_child(1)\\n p3 = panel.get_child(2)\\n\\n min_width = math.inf\\n min_height = math.inf\\n\\n # Get the smallest height and width\\n for child in [p1, p2, p3]:\\n\\n if child.width < min_width:\\n min_width = child.width\\n\\n if child.height < min_height:\\n min_height = child.height\\n\\n # Choose trapezoid pattern\\n if pattern is None:\\n trapezoid_pattern = np.random.choice([\\\"A\\\", \\\"V\\\"])\\n else:\\n trapezoid_pattern = pattern\\n\\n movement_proportion = np.random.randint(\\n 10,\\n cfg.trapezoid_movement_limit)\\n\\n # If parent panel is horizontal the children are vertical\\n if panel.orientation == \\\"h\\\":\\n\\n # Get how much the lines of the child panels move\\n # on the x axis to make the trapezoid\\n x_movement = min_width*(movement_proportion/100)\\n\\n # Make an A pattern horizontally\\n if trapezoid_pattern == \\\"A\\\":\\n\\n # Get the coords of the first line to be moved\\n line_one_top = (p1.x2y2[0] + x_movement,\\n p1.x2y2[1])\\n\\n line_one_bottom = (p1.x3y3[0] - x_movement,\\n p1.x3y3[1])\\n\\n # Move line between child 1 and 2\\n p1.x2y2 = line_one_top\\n p1.x3y3 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = line_one_top\\n p2.x4y4 = line_one_bottom\\n\\n # Get the coords of the second line to be moved\\n line_two_top = (p2.x2y2[0] - x_movement,\\n p2.x2y2[1])\\n line_two_bottom = (p2.x3y3[0] + x_movement,\\n p2.x3y3[1])\\n\\n # Move line two between child 2 and 3\\n p2.x2y2 = line_two_top\\n p2.x3y3 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_top\\n p3.x4y4 = line_two_bottom\\n\\n p3.refresh_coords()\\n\\n # Make a V pattern horizontally\\n else:\\n\\n # Get the coords of the first line to be moved\\n line_one_top = (p1.x2y2[0] - x_movement,\\n p1.x2y2[1])\\n\\n line_one_bottom = (p1.x3y3[0] + x_movement,\\n p1.x3y3[1])\\n\\n # Move line between child 1 and 2\\n p1.x2y2 = line_one_top\\n p1.x3y3 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = line_one_top\\n p2.x4y4 = line_one_bottom\\n\\n # Get the coords of the second line to be moved\\n line_two_top = (p2.x2y2[0] + x_movement,\\n p2.x2y2[1])\\n\\n line_two_bottom = (p2.x3y3[0] - x_movement,\\n p2.x3y3[1])\\n\\n # Move line two between child 2 and 3\\n p2.x2y2 = line_two_top\\n p2.x3y3 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_top\\n p3.x4y4 = line_two_bottom\\n\\n p3.refresh_coords()\\n\\n # If panel is vertical children are horizontal\\n # so the A and the V are at 90 degrees to the page\\n else:\\n # Get how much the lines of the child panels move\\n # on the y axis to make the trapezoid\\n y_movement = min_height*(movement_proportion/100)\\n\\n # Make an A pattern vertically\\n if trapezoid_pattern == \\\"A\\\":\\n\\n # Get the coords of the first line to be moved\\n line_one_top = (p2.x2y2[0],\\n p2.x2y2[1] + y_movement)\\n\\n line_one_bottom = (p2.x1y1[0],\\n p2.x1y1[1] - y_movement)\\n\\n # Move line between child 1 and 2\\n p2.x2y2 = line_one_top\\n p2.x1y1 = line_one_bottom\\n\\n p1.x3y3 = line_one_top\\n p1.x4y4 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n # Get the coords of the second line to be moved\\n line_two_top = (p2.x3y3[0],\\n p2.x3y3[1] - y_movement)\\n\\n line_two_bottom = (p2.x4y4[0],\\n p2.x4y4[1] + y_movement)\\n\\n # Move line two between child 2 and 3\\n p2.x3y3 = line_two_top\\n p2.x4y4 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_bottom\\n p3.x2y2 = line_two_top\\n\\n p3.refresh_coords()\\n # Make a V pattern vertically\\n else:\\n\\n # Get the coords of the first line to be moved\\n line_one_top = (p2.x2y2[0],\\n p2.x2y2[1] - y_movement)\\n\\n line_one_bottom = (p2.x1y1[0],\\n p2.x1y1[1] + y_movement)\\n\\n # Move line between child 1 and 2\\n p2.x2y2 = line_one_top\\n p2.x1y1 = line_one_bottom\\n\\n p1.x3y3 = line_one_top\\n p1.x4y4 = line_one_bottom\\n\\n p1.refresh_coords()\\n # Get the coords of the second line to be moved\\n line_two_top = (p2.x3y3[0],\\n p2.x3y3[1] + y_movement)\\n\\n line_two_bottom = (p2.x4y4[0],\\n p2.x4y4[1] - y_movement)\\n\\n # Move line two between child 2 and 3\\n p2.x3y3 = line_two_top\\n p2.x4y4 = line_two_bottom\\n\\n p2.refresh_coords()\\n p3.x1y1 = line_two_bottom\\n p3.x2y2 = line_two_top\\n\\n p3.refresh_coords()\\n\\n elif type_choice == \\\"rhombus\\\":\\n\\n if page.num_panels > 1:\\n\\n # Get parent panel which satisfies the criteria for the transform\\n relevant_panels = find_parent_with_multiple_children(page, 3)\\n\\n if len(relevant_panels) > 0:\\n\\n if len(relevant_panels) > 1:\\n num_panels = np.random.randint(1, len(relevant_panels))\\n else:\\n num_panels = 1\\n\\n for idx in range(0, num_panels):\\n\\n panel = relevant_panels[idx]\\n\\n # Since panels are created in order\\n p1 = panel.get_child(0)\\n p2 = panel.get_child(1)\\n p3 = panel.get_child(2)\\n\\n min_width = math.inf\\n min_height = math.inf\\n\\n # Get the smallest height and width\\n for child in [p1, p2, p3]:\\n\\n if child.width < min_width:\\n min_width = child.width\\n\\n if child.height < min_height:\\n min_height = child.height\\n\\n if pattern is None:\\n rhombus_pattern = np.random.choice([\\\"left\\\", \\\"right\\\"])\\n else:\\n rhombus_pattern = pattern\\n\\n movement_proportion = np.random.randint(\\n 10,\\n cfg.rhombus_movement_limit\\n )\\n\\n # Logic for the section below is the same as the\\n # trapezoid with the exception of the fact that the\\n # rhombus pattern happens to move both lines in the\\n # same direction\\n\\n if panel.orientation == \\\"h\\\":\\n\\n x_movement = min_width*(movement_proportion/100)\\n\\n if rhombus_pattern == \\\"left\\\":\\n line_one_top = (p1.x2y2[0] - x_movement,\\n p1.x2y2[1])\\n\\n line_one_bottom = (p1.x3y3[0] + x_movement,\\n p1.x3y3[1])\\n\\n p1.x2y2 = line_one_top\\n p1.x3y3 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = line_one_top\\n p2.x4y4 = line_one_bottom\\n\\n line_two_top = (p2.x2y2[0] - x_movement,\\n p2.x2y2[1])\\n\\n line_two_bottom = (p2.x3y3[0] + x_movement,\\n p2.x3y3[1])\\n\\n p2.x2y2 = line_two_top\\n p2.x3y3 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_top\\n p3.x4y4 = line_two_bottom\\n\\n p3.refresh_coords()\\n\\n else:\\n\\n line_one_top = (p1.x2y2[0] + x_movement,\\n p1.x2y2[1])\\n\\n line_one_bottom = (p1.x3y3[0] - x_movement,\\n p1.x3y3[1])\\n\\n p1.x2y2 = line_one_top\\n p1.x3y3 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = line_one_top\\n p2.x4y4 = line_one_bottom\\n\\n line_two_top = (p2.x2y2[0] + x_movement,\\n p2.x2y2[1])\\n\\n line_two_bottom = (p2.x3y3[0] - x_movement,\\n p2.x3y3[1])\\n\\n p2.x2y2 = line_two_top\\n p2.x3y3 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_top\\n p3.x4y4 = line_two_bottom\\n\\n p3.refresh_coords()\\n else:\\n y_movement = min_height*(movement_proportion/100)\\n\\n if rhombus_pattern == \\\"right\\\":\\n\\n line_one_top = (p2.x2y2[0],\\n p2.x2y2[1] + y_movement)\\n\\n line_one_bottom = (p2.x1y1[0],\\n p2.x1y1[1] - y_movement)\\n\\n p2.x2y2 = line_one_top\\n p2.x1y1 = line_one_bottom\\n\\n p1.x3y3 = line_one_top\\n p1.x4y4 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n line_two_top = (p2.x3y3[0],\\n p2.x3y3[1] + y_movement)\\n\\n line_two_bottom = (p2.x4y4[0],\\n p2.x4y4[1] - y_movement)\\n\\n p2.x3y3 = line_two_top\\n p2.x4y4 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_bottom\\n p3.x2y2 = line_two_top\\n\\n p3.refresh_coords()\\n else:\\n\\n line_one_top = (p2.x2y2[0],\\n p2.x2y2[1] - y_movement)\\n\\n line_one_bottom = (p2.x1y1[0],\\n p2.x1y1[1] + y_movement)\\n\\n p2.x2y2 = line_one_top\\n p2.x1y1 = line_one_bottom\\n\\n p1.x3y3 = line_one_top\\n p1.x4y4 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n line_two_top = (p2.x3y3[0],\\n p2.x3y3[1] - y_movement)\\n\\n line_two_bottom = (p2.x4y4[0],\\n p2.x4y4[1] + y_movement)\\n\\n p2.x3y3 = line_two_top\\n p2.x4y4 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_bottom\\n p3.x2y2 = line_two_top\\n\\n p3.refresh_coords()\\n\\n return page\",\n \"def LoadPerspective(self, layout):\\r\\n \\r\\n # Remove all tab ctrls (but still keep them in main index)\\r\\n tab_count = self._tabs.GetPageCount()\\r\\n for i in xrange(tab_count):\\r\\n wnd = self._tabs.GetWindowFromIdx(i)\\r\\n\\r\\n # find out which onscreen tab ctrl owns this tab\\r\\n ctrl, ctrl_idx = self.FindTab(wnd)\\r\\n if not ctrl:\\r\\n return False\\r\\n\\r\\n # remove the tab from ctrl\\r\\n if not ctrl.RemovePage(wnd):\\r\\n return False\\r\\n\\r\\n self.RemoveEmptyTabFrames()\\r\\n\\r\\n sel_page = 0\\r\\n tabs = layout[0:layout.index(\\\"@\\\")]\\r\\n to_break1 = False\\r\\n \\r\\n while 1:\\r\\n\\r\\n if \\\"|\\\" not in tabs:\\r\\n to_break1 = True\\r\\n tab_part = tabs\\r\\n else:\\r\\n tab_part = tabs[0:tabs.index('|')]\\r\\n \\r\\n if \\\"=\\\" not in tab_part:\\r\\n # No pages in this perspective...\\r\\n return False\\r\\n\\r\\n # Get pane name\\r\\n pane_name = tab_part[0:tab_part.index(\\\"=\\\")]\\r\\n\\r\\n # create a new tab frame\\r\\n new_tabs = TabFrame(self)\\r\\n self._tab_id_counter += 1\\r\\n new_tabs._tabs = AuiTabCtrl(self, self._tab_id_counter)\\r\\n new_tabs._tabs.SetArtProvider(self._tabs.GetArtProvider().Clone())\\r\\n new_tabs.SetTabCtrlHeight(self._tab_ctrl_height)\\r\\n new_tabs._tabs.SetAGWFlags(self._agwFlags)\\r\\n dest_tabs = new_tabs._tabs\\r\\n\\r\\n # create a pane info structure with the information\\r\\n # about where the pane should be added\\r\\n pane_info = framemanager.AuiPaneInfo().Name(pane_name).Bottom().CaptionVisible(False)\\r\\n self._mgr.AddPane(new_tabs, pane_info)\\r\\n\\r\\n # Get list of tab id's and move them to pane\\r\\n tab_list = tab_part[tab_part.index(\\\"=\\\")+1:]\\r\\n to_break2, active_found = False, False\\r\\n \\r\\n while 1:\\r\\n if \\\",\\\" not in tab_list:\\r\\n to_break2 = True\\r\\n tab = tab_list\\r\\n else:\\r\\n tab = tab_list[0:tab_list.index(\\\",\\\")] \\r\\n tab_list = tab_list[tab_list.index(\\\",\\\")+1:]\\r\\n\\r\\n # Check if this page has an 'active' marker\\r\\n c = tab[0]\\r\\n if c in ['+', '*']:\\r\\n tab = tab[1:]\\r\\n\\r\\n tab_idx = int(tab)\\r\\n if tab_idx >= self.GetPageCount():\\r\\n continue\\r\\n\\r\\n # Move tab to pane\\r\\n page = self._tabs.GetPage(tab_idx)\\r\\n newpage_idx = dest_tabs.GetPageCount()\\r\\n dest_tabs.InsertPage(page.window, page, newpage_idx)\\r\\n\\r\\n if c == '+':\\r\\n dest_tabs.SetActivePage(newpage_idx)\\r\\n active_found = True\\r\\n elif c == '*':\\r\\n sel_page = tab_idx\\r\\n\\r\\n if to_break2:\\r\\n break\\r\\n\\r\\n if not active_found:\\r\\n dest_tabs.SetActivePage(0)\\r\\n\\r\\n new_tabs.DoSizing()\\r\\n dest_tabs.DoShowHide()\\r\\n dest_tabs.Refresh()\\r\\n \\r\\n if to_break1:\\r\\n break\\r\\n \\r\\n tabs = tabs[tabs.index('|')+1:]\\r\\n\\r\\n # Load the frame perspective\\r\\n frames = layout[layout.index('@')+1:]\\r\\n self._mgr.LoadPerspective(frames)\\r\\n\\r\\n # Force refresh of selection\\r\\n self._curpage = -1\\r\\n self.SetSelection(sel_page)\\r\\n\\r\\n return True\",\n \"def push_down (grid):\\r\\n \\r\\n for row in range (4):\\r\\n section = []\\r\\n for col in range (4):\\r\\n section.append(grid[3-col][row])\\r\\n add(section)\\r\\n for i in range (4):\\r\\n grid[i][row] = section[3-i]\",\n \"def createInitialChildren(dash_instance):\\n\\t\\n\\t# create the header for the page\\n\\tamerenImage = createLogo(dash_instance)\\n\\theader = html.Div([\\n\\t\\t\\tamerenImage,\\n\\t\\t\\thtml.Label(\\n\\t\\t\\t\\t\\\"Solarwinds Dashboard\\\",\\n\\t\\t\\t\\tstyle=dict(fontSize=60, fontWeight='bold', fontStyle='italic')\\n\\t\\t\\t)\\n\\t\\t],\\n\\t\\tid='header',\\n\\t\\tstyle={\\n\\t\\t\\t'height': '250px',\\n 'backgroundColor': 'green',\\n\\t\\t\\t'textAlign': 'center',\\n\\t\\t\\t'verticalAlign': 'middle',\\n\\t\\t\\t'align': 'center'\\n\\t\\t}\\n\\t)\\n\\t\\n\\tdown_item_fieldset = defineDownItemFieldset(dash_instance)\\n\\tstatistics_fieldset = defineStatisticsFieldset(dash_instance)\\n\\tpage_break = createPageBreak(dash_instance)\\n\\t\\n\\t# add the children\\n\\tdash_instance.addChildren(\\n\\t\\theader,\\n\\t\\tdown_item_fieldset,\\n\\t\\tpage_break,\\n\\t\\tstatistics_fieldset,\\n\\t\\tdcc.Location(id='startPage', refresh=False)\\n\\t)\",\n \"def prep_naves(self):\\r\\n self.naves = Group()\\r\\n for nave_num in range(self.stats.nave_left):\\r\\n nave = Nave(self.ik_game)\\r\\n nave.image = pygame.transform.rotate(pygame.transform.scale(\\r\\n pygame.image.load(os.path.join('complemento/aventine_ship.bmp')), (50, 20)), 90)\\r\\n nave.rect.x = 10 + nave_num * nave.rect.width\\r\\n nave.rect.y = 10\\r\\n self.naves.add(nave)\",\n \"def Split(self, page, direction):\\r\\n \\r\\n cli_size = self.GetClientSize()\\r\\n\\r\\n # get the page's window pointer\\r\\n wnd = self.GetPage(page)\\r\\n if not wnd:\\r\\n return\\r\\n\\r\\n # notebooks with 1 or less pages can't be split\\r\\n if self.GetPageCount() < 2:\\r\\n return\\r\\n\\r\\n # find out which tab control the page currently belongs to\\r\\n\\r\\n src_tabs, src_idx = self.FindTab(wnd)\\r\\n if not src_tabs:\\r\\n return\\r\\n \\r\\n # choose a split size\\r\\n if self.GetPageCount() > 2:\\r\\n split_size = self.CalculateNewSplitSize()\\r\\n else: \\r\\n # because there are two panes, always split them\\r\\n # equally\\r\\n split_size = self.GetClientSize()\\r\\n split_size.x /= 2\\r\\n split_size.y /= 2\\r\\n\\r\\n # create a new tab frame\\r\\n new_tabs = TabFrame(self)\\r\\n new_tabs._rect = wx.RectPS(wx.Point(0, 0), split_size)\\r\\n new_tabs.SetTabCtrlHeight(self._tab_ctrl_height)\\r\\n self._tab_id_counter += 1\\r\\n new_tabs._tabs = AuiTabCtrl(self, self._tab_id_counter)\\r\\n \\r\\n new_tabs._tabs.SetArtProvider(self._tabs.GetArtProvider().Clone())\\r\\n new_tabs._tabs.SetAGWFlags(self._agwFlags)\\r\\n dest_tabs = new_tabs._tabs\\r\\n\\r\\n page_info = src_tabs.GetPage(src_idx)\\r\\n if page_info.control:\\r\\n self.ReparentControl(page_info.control, dest_tabs)\\r\\n \\r\\n # create a pane info structure with the information\\r\\n # about where the pane should be added\\r\\n pane_info = framemanager.AuiPaneInfo().Bottom().CaptionVisible(False)\\r\\n\\r\\n if direction == wx.LEFT:\\r\\n \\r\\n pane_info.Left()\\r\\n mouse_pt = wx.Point(0, cli_size.y/2)\\r\\n \\r\\n elif direction == wx.RIGHT:\\r\\n \\r\\n pane_info.Right()\\r\\n mouse_pt = wx.Point(cli_size.x, cli_size.y/2)\\r\\n \\r\\n elif direction == wx.TOP:\\r\\n \\r\\n pane_info.Top()\\r\\n mouse_pt = wx.Point(cli_size.x/2, 0)\\r\\n \\r\\n elif direction == wx.BOTTOM:\\r\\n \\r\\n pane_info.Bottom()\\r\\n mouse_pt = wx.Point(cli_size.x/2, cli_size.y)\\r\\n \\r\\n self._mgr.AddPane(new_tabs, pane_info, mouse_pt)\\r\\n self._mgr.Update()\\r\\n\\r\\n # remove the page from the source tabs\\r\\n page_info.active = False\\r\\n \\r\\n src_tabs.RemovePage(page_info.window)\\r\\n \\r\\n if src_tabs.GetPageCount() > 0:\\r\\n src_tabs.SetActivePage(0)\\r\\n src_tabs.DoShowHide()\\r\\n src_tabs.Refresh()\\r\\n \\r\\n # add the page to the destination tabs\\r\\n dest_tabs.InsertPage(page_info.window, page_info, 0)\\r\\n\\r\\n if src_tabs.GetPageCount() == 0:\\r\\n self.RemoveEmptyTabFrames()\\r\\n \\r\\n self.DoSizing()\\r\\n dest_tabs.DoShowHide()\\r\\n dest_tabs.Refresh()\\r\\n\\r\\n # force the set selection function reset the selection\\r\\n self._curpage = -1\\r\\n\\r\\n # set the active page to the one we just split off\\r\\n self.SetSelectionToPage(page_info)\\r\\n\\r\\n self.UpdateHintWindowSize()\",\n \"def childAfterMove(self, m):\\n indexOfZero = self.tiles.index(0)\\n initial = self.tiles[:]\\n child = Board(initial)\\n if m == 'Up':\\n assert(indexOfZero > 2)\\n temp = self.tiles[indexOfZero - 3]\\n child.tiles[indexOfZero] = temp\\n child.tiles[indexOfZero - 3] = 0\\n elif m == 'Down':\\n assert(indexOfZero < 6)\\n temp = self.tiles[indexOfZero + 3]\\n child.tiles[indexOfZero] = temp\\n child.tiles[indexOfZero + 3] = 0\\n elif m == 'Left':\\n assert(indexOfZero != 0 and indexOfZero != 3 and indexOfZero != 6)\\n temp = self.tiles[indexOfZero - 1]\\n child.tiles[indexOfZero] = temp\\n child.tiles[indexOfZero - 1] = 0\\n elif m == 'Right':\\n assert(indexOfZero != 2 and indexOfZero != 5 and indexOfZero != 8)\\n temp = self.tiles[indexOfZero + 1]\\n child.tiles[indexOfZero] = temp\\n child.tiles[indexOfZero + 1] = 0\\n else:\\n print(m + ' is not a legal movement')\\n return child\",\n \"def step(self):\\n self.turn_on_corners()\\n part_1.Grid.step(self)\\n self.turn_on_corners()\",\n \"def playout(self, state):\\n node = self.root\\n isTerminal = False\\n depth = 0\\n\\n while not isTerminal and depth < self.playout_depth:\\n #A = len(node.children) # num_children\\n A = len(node.children[0]) + len(node.children[1]) \\n if A < self.num_initActions:\\n #if len(node.children[0]) < self.num_initActions:\\n node, init_action_xy, init_spin = self.initChildren(node, state, depth)\\n _, ShotVec = CreateShot(_ShotPos(init_action_xy[0], init_action_xy[1], init_spin))\\n success, ResShot = Simulation(state, ShotVec, Config.RAND, -1)\\n isTerminal = (state.ShotNum==0)\\n \\n depth += 1\\n break\\n \\n n_a = [c.n_visits for c in node.children[0].values()] + [c.n_visits for c in node.children[1].values()]\\n # progressive widening\\n # if chilren node has been visited much times then expand\\n #if np.sqrt(sum(n_a)) >= A:\\n if sum(n_a) >= 10 * A: \\n # expand\\n node, expanded_action_xy, expanded_spin = self.expand(node)\\n _, ShotVec = CreateShot(_ShotPos(expanded_action_xy[0],expanded_action_xy[1], expanded_spin))\\n success, ResShot = Simulation(state, ShotVec, Config.RAND, -1)\\n isTerminal = (state.ShotNum==0) # one end game\\n \\n depth += 1\\n break\\n\\n # select\\n node, selected_action_xy, selected_spin = self.ucb_select(node)\\n _, ShotVec = CreateShot(_ShotPos(selected_action_xy[0], selected_action_xy[1], selected_spin))\\n success, ResShot = Simulation(state, ShotVec, Config.RAND, -1)\\n isTerminal = (state.ShotNum==0) # one end game\\n \\n depth += 1\\n\\n if isTerminal:\\n break\\n\\n if not isTerminal and depth < self.playout_depth:\\n # save the rollout_state for speed.\\n #if node.rollout_state is None:\\n state = self.rollOut(node, state, depth)\\n #node.rollout_state = state\\n #else:\\n # state = node.rollout_state\\n \\n self.update(node, state)\",\n \"def main():\\n row1()\\n move_up_left()\\n row2()\\n move_up_right()\\n row3()\\n move_up_left()\\n row4()\\n move_up_right()\\n row5()\\n move_up_left()\\n row6()\\n move_up_right()\\n row7()\\n move_up_left()\\n row8()\\n move_up_right()\\n row9()\\n move_up_left()\\n row10()\\n move_up_right()\\n row11()\\n move_up_left()\\n row12()\\n move_up_right()\\n row13()\\n move_up_left()\\n row14()\\n move_up_right()\\n row15()\\n move_up_left()\\n row16()\\n move_up_right()\\n row17()\\n move_up_left()\\n row18()\\n move_up_right()\\n row19()\\n move_up_left()\\n row20()\",\n \"def get_product_panels(self, product_bp, panel_list):\\n for child in product_bp.children:\\n props = props_closet.get_object_props(child)\\n if props.is_panel_bp:\\n assembly = fd_types.Assembly(child)\\n if common_closet_utils.part_is_not_hidden(assembly):\\n panel_list.append(child)\\n self.get_product_panels(child, panel_list)\\n panel_list.sort(key=lambda obj: obj.location.x, reverse=False)\\n return panel_list\",\n \"def goToFirstFrame():\\n nuke.frame(int(nuke.root()[\\\"first_frame\\\"].getValue()))\",\n \"def go_home(self):\\n self.set_all_positions([0]*self.nleaflets)\",\n \"def children(self):\\n n = []\\n zi = 0\\n zj = 0\\n for i in range(self.board_size):\\n for j in range(self.board_size):\\n if self.arr[i][j] == 0:\\n zi = i\\n zj = j\\n break\\n i = zi\\n j = zj\\n # \\\"UDLR\\\" order; that is, [‘Up’, ‘Down’, ‘Left’, ‘Right’]\\n if 0 <= i-1: # up\\n self.arr[i][j], self.arr[i-1][j] = self.arr[i -\\n 1][j], self.arr[i][j] # do the move\\n x = state([item for row in self.arr for item in row],\\n self) # create a copy\\n x.move = \\\"Up\\\" # set the movement that leads for this copy\\n n.append(x) # add the copy to the list\\n # undo the move so we can continue finding the other children\\n self.arr[i][j], self.arr[i-1][j] = self.arr[i-1][j], self.arr[i][j]\\n if self.board_size > i+1: # down\\n self.arr[i][j], self.arr[i+1][j] = self.arr[i+1][j], self.arr[i][j]\\n x = state([item for row in self.arr for item in row], self)\\n x.move = \\\"Down\\\"\\n n.append(x)\\n self.arr[i][j], self.arr[i+1][j] = self.arr[i+1][j], self.arr[i][j]\\n if 0 <= j-1: # left\\n self.arr[i][j], self.arr[i][j-1] = self.arr[i][j-1], self.arr[i][j]\\n x = state([item for row in self.arr for item in row], self)\\n x.move = \\\"Left\\\"\\n n.append(x)\\n self.arr[i][j], self.arr[i][j-1] = self.arr[i][j-1], self.arr[i][j]\\n if self.board_size > j+1: # right\\n self.arr[i][j], self.arr[i][j+1] = self.arr[i][j+1], self.arr[i][j]\\n x = state([item for row in self.arr for item in row], self)\\n x.move = \\\"Right\\\"\\n n.append(x)\\n self.arr[i][j], self.arr[i][j+1] = self.arr[i][j+1], self.arr[i][j]\\n\\n return n\",\n \"def create_open_positions_grid(self):\\n\\n counter = 0\\n col = 0\\n row = 0\\n\\n for i in range(0, 99):\\n if counter % 3 == 0:\\n col = 0\\n row += 1\\n self.gp.addWidget(PositionPanel(), row, col)\\n counter += 1\\n col += 1\",\n \"def swipeBase (self) :\\n grid = self.grid\\n\\n #we start by putting every tile up\\n for columnNbr in range(4) :\\n nbrZeros = 4 - np.count_nonzero(grid[:,columnNbr])\\n\\n for lineNbr in range(4) :\\n counter = 0\\n while (grid[lineNbr, columnNbr] == 0) and (counter < 4):\\n counter += 1\\n if np.count_nonzero(grid[lineNbr:4, columnNbr]) != 0 :\\n for remainingLine in range (lineNbr, 3) :\\n grid[remainingLine, columnNbr] = grid[remainingLine+1, columnNbr]\\n grid[3, columnNbr] = 0\\n\\n #now we do the additions\\n for lineNbr in range(3) :\\n if grid[lineNbr, columnNbr] == grid[lineNbr+1, columnNbr] :\\n grid[lineNbr, columnNbr] *= 2\\n for remainingLine in range (lineNbr+1, 3) :\\n grid[remainingLine, columnNbr] = grid[remainingLine+1, columnNbr]\\n grid[3, columnNbr] = 0\\n\\n return (grid)\",\n \"def create_panel_navigation(self, frame_parent):\\r\\n panel = ttk.Frame(frame_parent)\\r\\n\\r\\n tree = ttk.Treeview(panel, selectmode=\\\"browse\\\") # \\\"browse\\\" mode limits to one selection only\\r\\n tree.heading(\\\"#0\\\", text=\\\"Category\\\")\\r\\n tree.column(\\\"#0\\\", width=130)\\r\\n #tree.bind(\\\"<ButtonRelease-1>\\\", self.on_category_select) # left-button release\\r\\n tree.bind(\\\"<<TreeviewSelect>>\\\", self.on_category_select)\\r\\n #\\r\\n tree.insert('', tk.END, text=\\\"Email\\\")\\r\\n tree.insert('', tk.END, text=\\\"Access Restriction\\\")\\r\\n tree.selection_set(tree.get_children()[0]) # select the first item on init\\r\\n tree.grid(sticky=\\\"NS\\\")\\r\\n\\r\\n # http://stackoverflow.com/questions/25940217/python-getting-started-with-tk-widget-not-resizing-on-grid\\r\\n # or you can just do this: tree.pack(fill=tk.BOTH, expand=1)\\r\\n tree.rowconfigure(0, weight=1)\\r\\n tree.columnconfigure(0, weight=1)\\r\\n return panel\",\n \"def LayoutAll(self, panes, docks, uiparts, spacer_only=False, oncheck=True):\\r\\n \\r\\n container = wx.BoxSizer(wx.VERTICAL)\\r\\n\\r\\n pane_border_size = self._art.GetMetric(AUI_DOCKART_PANE_BORDER_SIZE)\\r\\n caption_size = self._art.GetMetric(AUI_DOCKART_CAPTION_SIZE)\\r\\n cli_size = self._frame.GetClientSize()\\r\\n \\r\\n # empty all docks out\\r\\n for dock in docks:\\r\\n dock.panes = []\\r\\n if dock.fixed:\\r\\n # always reset fixed docks' sizes, because\\r\\n # the contained windows may have been resized\\r\\n dock.size = 0\\r\\n \\r\\n dock_count = len(docks)\\r\\n \\r\\n # iterate through all known panes, filing each\\r\\n # of them into the appropriate dock. If the\\r\\n # pane does not exist in the dock, add it\\r\\n for p in panes:\\r\\n\\r\\n # don't layout hidden panes.\\r\\n if p.IsShown():\\r\\n \\r\\n # find any docks with the same dock direction, dock layer, and\\r\\n # dock row as the pane we are working on\\r\\n arr = FindDocks(docks, p.dock_direction, p.dock_layer, p.dock_row)\\r\\n\\r\\n if arr:\\r\\n dock = arr[0]\\r\\n\\r\\n else:\\r\\n # dock was not found, so we need to create a new one\\r\\n d = AuiDockInfo()\\r\\n d.dock_direction = p.dock_direction\\r\\n d.dock_layer = p.dock_layer\\r\\n d.dock_row = p.dock_row\\r\\n docks.append(d)\\r\\n dock = docks[-1]\\r\\n\\r\\n if p.HasFlag(p.needsRestore) and not p.HasFlag(p.wasMaximized):\\r\\n \\r\\n isHor = dock.IsHorizontal()\\r\\n sashSize = self._art.GetMetric(AUI_DOCKART_SASH_SIZE)\\r\\n\\r\\n # get the sizes of any docks that might \\r\\n # overlap with our restored dock\\r\\n\\r\\n # make list of widths or heights from the size in the dock rects\\r\\n sizes = [d.rect[2:][isHor] for \\\\\\r\\n d in docks if d.IsOk() and \\\\\\r\\n (d.IsHorizontal() == isHor) and \\\\\\r\\n not d.toolbar and \\\\\\r\\n d.dock_direction != AUI_DOCK_CENTER]\\r\\n \\r\\n frameRect = GetInternalFrameRect(self._frame, self._docks)\\r\\n\\r\\n # set max size allowing for sashes and absolute minimum\\r\\n maxsize = frameRect[2:][isHor] - sum(sizes) - (len(sizes)*10) - (sashSize*len(sizes))\\r\\n dock.size = min(p.previousDockSize,maxsize)\\r\\n\\r\\n else:\\r\\n dock.size = 0\\r\\n\\r\\n if p.HasFlag(p.wasMaximized):\\r\\n self.MaximizePane(p, savesizes=False)\\r\\n p.SetFlag(p.wasMaximized, False)\\r\\n\\r\\n if p.HasFlag(p.needsRestore):\\r\\n if p.previousDockPos is not None:\\r\\n DoInsertPane(dock.panes, dock.dock_direction, dock.dock_layer, dock.dock_row, p.previousDockPos)\\r\\n p.dock_pos = p.previousDockPos\\r\\n p.previousDockPos = None\\r\\n p.SetFlag(p.needsRestore, False)\\r\\n\\r\\n if p.IsDocked():\\r\\n # remove the pane from any existing docks except this one\\r\\n docks = RemovePaneFromDocks(docks, p, dock)\\r\\n\\r\\n # pane needs to be added to the dock,\\r\\n # if it doesn't already exist \\r\\n if not FindPaneInDock(dock, p.window):\\r\\n dock.panes.append(p)\\r\\n else:\\r\\n # remove the pane from any existing docks\\r\\n docks = RemovePaneFromDocks(docks, p)\\r\\n \\r\\n # remove any empty docks\\r\\n docks = [dock for dock in docks if dock.panes]\\r\\n\\r\\n dock_count = len(docks)\\r\\n # configure the docks further\\r\\n for ii, dock in enumerate(docks):\\r\\n # sort the dock pane array by the pane's\\r\\n # dock position (dock_pos), in ascending order\\r\\n dock.panes.sort(PaneSortFunc)\\r\\n dock_pane_count = len(dock.panes)\\r\\n \\r\\n # for newly created docks, set up their initial size\\r\\n if dock.size == 0:\\r\\n size = 0\\r\\n for pane in dock.panes:\\r\\n pane_size = pane.best_size\\r\\n if pane_size == wx.Size(-1, -1):\\r\\n pane_size = pane.min_size\\r\\n if pane_size == wx.Size(-1, -1) and pane.window:\\r\\n pane_size = pane.window.GetSize()\\r\\n if dock.IsHorizontal():\\r\\n size = max(pane_size.y, size)\\r\\n else:\\r\\n size = max(pane_size.x, size)\\r\\n \\r\\n # add space for the border (two times), but only\\r\\n # if at least one pane inside the dock has a pane border\\r\\n for pane in dock.panes:\\r\\n if pane.HasBorder():\\r\\n size = size + pane_border_size*2\\r\\n break\\r\\n \\r\\n # if pane is on the top or bottom, add the caption height,\\r\\n # but only if at least one pane inside the dock has a caption\\r\\n if dock.IsHorizontal():\\r\\n for pane in dock.panes:\\r\\n if pane.HasCaption() and not pane.HasCaptionLeft():\\r\\n size = size + caption_size\\r\\n break\\r\\n else:\\r\\n for pane in dock.panes:\\r\\n if pane.HasCaptionLeft() and not pane.HasCaption():\\r\\n size = size + caption_size\\r\\n break\\r\\n \\r\\n # new dock's size may not be more than the dock constraint\\r\\n # parameter specifies. See SetDockSizeConstraint()\\r\\n max_dock_x_size = int(self._dock_constraint_x*float(cli_size.x))\\r\\n max_dock_y_size = int(self._dock_constraint_y*float(cli_size.y))\\r\\n if cli_size <= wx.Size(20, 20):\\r\\n max_dock_x_size = 10000\\r\\n max_dock_y_size = 10000\\r\\n\\r\\n if dock.IsHorizontal():\\r\\n size = min(size, max_dock_y_size)\\r\\n else:\\r\\n size = min(size, max_dock_x_size)\\r\\n\\r\\n # absolute minimum size for a dock is 10 pixels\\r\\n if size < 10:\\r\\n size = 10\\r\\n\\r\\n dock.size = size\\r\\n\\r\\n # determine the dock's minimum size\\r\\n plus_border = False\\r\\n plus_caption = False\\r\\n plus_caption_left = False\\r\\n dock_min_size = 0\\r\\n for pane in dock.panes:\\r\\n if pane.min_size != wx.Size(-1, -1):\\r\\n if pane.HasBorder():\\r\\n plus_border = True\\r\\n if pane.HasCaption():\\r\\n plus_caption = True\\r\\n if pane.HasCaptionLeft():\\r\\n plus_caption_left = True\\r\\n if dock.IsHorizontal():\\r\\n if pane.min_size.y > dock_min_size:\\r\\n dock_min_size = pane.min_size.y\\r\\n else:\\r\\n if pane.min_size.x > dock_min_size:\\r\\n dock_min_size = pane.min_size.x\\r\\n \\r\\n if plus_border:\\r\\n dock_min_size += pane_border_size*2\\r\\n if plus_caption and dock.IsHorizontal():\\r\\n dock_min_size += caption_size\\r\\n if plus_caption_left and dock.IsVertical():\\r\\n dock_min_size += caption_size\\r\\n \\r\\n dock.min_size = dock_min_size\\r\\n \\r\\n # if the pane's current size is less than it's\\r\\n # minimum, increase the dock's size to it's minimum\\r\\n if dock.size < dock.min_size:\\r\\n dock.size = dock.min_size\\r\\n\\r\\n # determine the dock's mode (fixed or proportional)\\r\\n # determine whether the dock has only toolbars\\r\\n action_pane_marked = False\\r\\n dock.fixed = True\\r\\n dock.toolbar = True\\r\\n for pane in dock.panes:\\r\\n if not pane.IsFixed():\\r\\n dock.fixed = False\\r\\n if not pane.IsToolbar():\\r\\n dock.toolbar = False\\r\\n if pane.HasFlag(AuiPaneInfo.optionDockFixed):\\r\\n dock.fixed = True\\r\\n if pane.HasFlag(AuiPaneInfo.actionPane):\\r\\n action_pane_marked = True\\r\\n\\r\\n # if the dock mode is proportional and not fixed-pixel,\\r\\n # reassign the dock_pos to the sequential 0, 1, 2, 3\\r\\n # e.g. remove gaps like 1, 2, 30, 500\\r\\n if not dock.fixed:\\r\\n for jj in xrange(dock_pane_count):\\r\\n pane = dock.panes[jj]\\r\\n pane.dock_pos = jj\\r\\n \\r\\n # if the dock mode is fixed, and none of the panes\\r\\n # are being moved right now, make sure the panes\\r\\n # do not overlap each other. If they do, we will\\r\\n # adjust the panes' positions\\r\\n if dock.fixed and not action_pane_marked:\\r\\n pane_positions, pane_sizes = self.GetPanePositionsAndSizes(dock)\\r\\n offset = 0\\r\\n for jj in xrange(dock_pane_count):\\r\\n pane = dock.panes[jj]\\r\\n pane.dock_pos = pane_positions[jj]\\r\\n amount = pane.dock_pos - offset\\r\\n if amount >= 0:\\r\\n offset += amount\\r\\n else:\\r\\n pane.dock_pos += -amount\\r\\n\\r\\n offset += pane_sizes[jj]\\r\\n dock.panes[jj] = pane\\r\\n\\r\\n if oncheck:\\r\\n self._docks[ii] = dock \\r\\n\\r\\n # shrink docks if needed \\r\\n## docks = self.SmartShrink(docks, AUI_DOCK_TOP)\\r\\n## docks = self.SmartShrink(docks, AUI_DOCK_LEFT)\\r\\n\\r\\n if oncheck:\\r\\n self._docks = docks\\r\\n \\r\\n # discover the maximum dock layer\\r\\n max_layer = 0\\r\\n dock_count = len(docks)\\r\\n \\r\\n for ii in xrange(dock_count):\\r\\n max_layer = max(max_layer, docks[ii].dock_layer)\\r\\n\\r\\n # clear out uiparts\\r\\n uiparts = []\\r\\n\\r\\n # create a bunch of box sizers,\\r\\n # from the innermost level outwards.\\r\\n cont = None\\r\\n middle = None\\r\\n\\r\\n if oncheck:\\r\\n docks = self._docks\\r\\n \\r\\n for layer in xrange(max_layer+1):\\r\\n # find any docks in this layer\\r\\n arr = FindDocks(docks, -1, layer, -1)\\r\\n # if there aren't any, skip to the next layer\\r\\n if not arr:\\r\\n continue\\r\\n\\r\\n old_cont = cont\\r\\n\\r\\n # create a container which will hold this layer's\\r\\n # docks (top, bottom, left, right)\\r\\n cont = wx.BoxSizer(wx.VERTICAL)\\r\\n\\r\\n # find any top docks in this layer\\r\\n arr = FindDocks(docks, AUI_DOCK_TOP, layer, -1)\\r\\n for row in arr:\\r\\n uiparts = self.LayoutAddDock(cont, row, uiparts, spacer_only)\\r\\n \\r\\n # fill out the middle layer (which consists\\r\\n # of left docks, content area and right docks)\\r\\n \\r\\n middle = wx.BoxSizer(wx.HORIZONTAL)\\r\\n\\r\\n # find any left docks in this layer\\r\\n arr = FindDocks(docks, AUI_DOCK_LEFT, layer, -1)\\r\\n for row in arr:\\r\\n uiparts = self.LayoutAddDock(middle, row, uiparts, spacer_only)\\r\\n \\r\\n # add content dock (or previous layer's sizer\\r\\n # to the middle\\r\\n if not old_cont:\\r\\n # find any center docks\\r\\n arr = FindDocks(docks, AUI_DOCK_CENTER, -1, -1)\\r\\n if arr:\\r\\n for row in arr:\\r\\n uiparts = self.LayoutAddDock(middle, row, uiparts, spacer_only)\\r\\n \\r\\n elif not self._has_maximized:\\r\\n # there are no center docks, add a background area\\r\\n sizer_item = middle.Add((1, 1), 1, wx.EXPAND)\\r\\n part = AuiDockUIPart()\\r\\n part.type = AuiDockUIPart.typeBackground\\r\\n part.pane = None\\r\\n part.dock = None\\r\\n part.button = None\\r\\n part.cont_sizer = middle\\r\\n part.sizer_item = sizer_item\\r\\n uiparts.append(part)\\r\\n else:\\r\\n middle.Add(old_cont, 1, wx.EXPAND)\\r\\n \\r\\n # find any right docks in this layer\\r\\n arr = FindDocks(docks, AUI_DOCK_RIGHT, layer, -1, reverse=True)\\r\\n for row in arr:\\r\\n uiparts = self.LayoutAddDock(middle, row, uiparts, spacer_only)\\r\\n \\r\\n if len(middle.GetChildren()) > 0:\\r\\n cont.Add(middle, 1, wx.EXPAND)\\r\\n\\r\\n # find any bottom docks in this layer\\r\\n arr = FindDocks(docks, AUI_DOCK_BOTTOM, layer, -1, reverse=True)\\r\\n for row in arr:\\r\\n uiparts = self.LayoutAddDock(cont, row, uiparts, spacer_only)\\r\\n\\r\\n if not cont:\\r\\n # no sizer available, because there are no docks,\\r\\n # therefore we will create a simple background area\\r\\n cont = wx.BoxSizer(wx.VERTICAL)\\r\\n sizer_item = cont.Add((1, 1), 1, wx.EXPAND)\\r\\n part = AuiDockUIPart()\\r\\n part.type = AuiDockUIPart.typeBackground\\r\\n part.pane = None\\r\\n part.dock = None\\r\\n part.button = None\\r\\n part.cont_sizer = middle\\r\\n part.sizer_item = sizer_item\\r\\n uiparts.append(part)\\r\\n\\r\\n if oncheck:\\r\\n self._uiparts = uiparts\\r\\n self._docks = docks\\r\\n\\r\\n container.Add(cont, 1, wx.EXPAND)\\r\\n\\r\\n if oncheck:\\r\\n return container\\r\\n else:\\r\\n return container, panes, docks, uiparts\",\n \"def ress_move_on_page(self, content=None):\\n outside_ress = self.outside_ress\\n content = content or self.content\\n\\n for blo in outside_ress:\\n\\n mch = re.search(r'(\\\\s|\\\\t)-block %s'%blo, content) # blo = links, onload etc\\n\\n if not mch:\\n\\n warn(blo+' block is undefined in root template %s'%self.origin.__str__()) # raise Exception(blo+' block is undefined in root template %s'%origin.__str__())\\n\\n super_block = r'\\\\t\\\\t={ block.super }\\\\n'\\n content = re.sub(\\n r'(-extends \\\"[\\\\w\\\\.]+\\\")\\\"', r'\\\\1\\\\n\\\\t-block %s%s%s'%(\\n blo, super_block, __indent_block(r'\\\\t\\\\t', outside_ress[blo].value)\\n ),\\n content\\n )\\n\\n else:\\n _blo = self.__indent_block(mch.groups()[0]+' '*4, outside_ress[blo].value)\\n\\n # (\\\\s|\\\\t)-block \\\\w+(([\\\\s:]*={ *block.super *})|) ={ *block.super *} - \\\\2\\n\\n content = re.sub(r'(\\\\s|\\\\t)(-block %s)'%blo, r'\\\\1\\\\2\\\\n'+_blo, content)\\n\\n## _blo = _indent_block(mch.groups()[0]+' '*8, blo)\\n## _blo = '\\\\n\\\\1 :javascript\\\\n' + _blo\\n\\n return content\",\n \"def main():\\n while front_is_clear():\\n repair_column()\\n for i in range(4):\\n move()\\n repair_column()\",\n \"def calculate_next_move(self, visit):\\n self.depth += 1\\n new_boards = []\\n for vehicle_id in range(len(self.vehicles)):\\n vehicle = self.vehicles[vehicle_id]\\n state = self.get_board()\\n if vehicle.orientation == 0: #horizontal\\n if vehicle.x > 0: #left\\n if state[vehicle.y][vehicle.x-1] == \\\"..\\\":\\n self.vehicles[vehicle_id].x -=1\\n if not self.get_board().tostring() in visit:\\n if not self.get_board().all in new_boards:\\n new_board = deepcopy(self)\\n self.vehicles[vehicle_id].x += 1\\n new_board.parent = self\\n new_boards.append(new_board)\\n else:\\n self.vehicles[vehicle_id].x += 1\\n\\n if vehicle.x + vehicle.length <= (len(state)-1): #right\\n if state[vehicle.y][vehicle.x+vehicle.length] == \\\"..\\\":\\n self.vehicles[vehicle_id].x += 1\\n if not self.get_board().tostring() in visit:\\n if not self.get_board().all in new_boards:\\n new_board = deepcopy(self)\\n self.vehicles[vehicle_id].x -= 1\\n new_board.parent = self\\n new_boards.append(new_board)\\n else:\\n self.vehicles[vehicle_id].x -= 1\\n\\n else: #vertical\\n if vehicle.y - 1 >= 0: #up\\n if state[vehicle.y-1][vehicle.x] == \\\"..\\\":\\n self.vehicles[vehicle_id].y -= 1\\n if not self.get_board().tostring() in visit:\\n if not self.get_board().all in new_boards:\\n new_board = deepcopy(self)\\n self.vehicles[vehicle_id].y += 1\\n new_board.parent = self\\n new_boards.append(new_board)\\n else:\\n self.vehicles[vehicle_id].y += 1\\n\\n if vehicle.y + vehicle.length <= (len(state)-1):\\n if state[vehicle.y + vehicle.length][vehicle.x] == \\\"..\\\":#down\\n self.vehicles[vehicle_id].y += 1\\n if not self.get_board().tostring() in visit:\\n if not self.get_board().all in new_boards:\\n new_board = deepcopy(self)\\n self.vehicles[vehicle_id].y -= 1\\n new_board.parent = self\\n new_boards.append(new_board)\\n else:\\n self.vehicles[vehicle_id].y -= 1\\n self.depth -= 1\\n return new_boards\",\n \"def main():\\n global fenetre, gr_grid,grid,steps,btn\\n fenetre = Frame()\\n fenetre.grid()\\n fenetre.master.title('Rush Hour')\\n flabel = Frame(fenetre)\\n flabel.grid()\\n steps=StringVar()\\n Label(flabel, textvariable=steps).pack()\\n steps.set(str(len(l))+\\\" steps remaining\\\")\\n background = Frame(fenetre, bg = game_bg, width=game_size, height=game_size)\\n background.grid()\\n gr_grid = []\\n for i in range(6):\\n gr_line = []\\n for j in range(6):\\n cell = Frame(background, bg = tiles_empty_bg, width = tiles_size, height = tiles_size)\\n cell.grid(row=i, column=j,padx=1, pady=1)\\n t = Label(master = cell, text = \\\"\\\", bg = tiles_empty_bg, justify = CENTER, font = tiles_font, width=4, height=2)\\n t.grid()\\n gr_line.append(t)\\n gr_grid.append(gr_line)\\n\\n board_display(my_board)\\n button=Frame(fenetre)\\n button.grid()\\n btn=StringVar()\\n Button(button, textvariable=btn, command=next_step).pack(side=BOTTOM)\\n btn.set(\\\"Next step\\\")\\n fenetre.mainloop()\",\n \"def _setup_children(self):\\n\\n for i in xrange(self._nhalos):\\n self._halos[i+1].properties['children'] = []\\n\\n for i in xrange(self._nhalos):\\n host = self._halos[i+1].properties.get('hostHalo', -2)\\n if host > -1:\\n try:\\n self._halos[host+1].properties['children'].append(i+1)\\n except KeyError:\\n pass\",\n \"def main():\\n for i in range(4):\\n fix_tower()\\n if front_is_clear():\\n move_to_next()\",\n \"def _setup_children(self):\\n\\n for i in xrange(self._nhalos):\\n self._halos[i + 1].properties['children'] = []\\n\\n for i in xrange(self._nhalos):\\n host = self._halos[i + 1].properties.get('hostHalo', -2)\\n if host > -1:\\n try:\\n self._halos[host + 1].properties['children'].append(i + 1)\\n except KeyError:\\n pass\",\n \"def setup(self):\\n for lane in self.lanes.values():\\n for p in range(lane.starting_patrons):\\n patron = Patron(\\n lane=lane,\\n lane_speed=self.patron_speed,\\n pause_duration=self.patron_pause,\\n )\\n\\n patron.pos = patron.pos[0], patron.pos[1] + 15\\n lane.puck_area.add_widget(patron)\\n lane.patrons.append(patron)\",\n \"def run():\\n while True:\\n try:\\n top_layout = cpanel.top_panel().userptr()\\n top_layout.run_ctr()\\n except AttributeError:\\n sys.exit(\\\"Please create at least one view layout.\\\")\",\n \"def initializePage(self):\\n WizardPage.initialize(self)\\n self.page.use(qt.QVBoxLayout())\\n\\n dims = [(\\\"DX\\\", 0.), (\\\"DY\\\", 0.)]\\n if self.give_field(\\\"model\\\").dim == 3:\\n dims.append((\\\"DZ\\\", 0.))\\n exp = self.give_field(\\\"exp-store\\\").give_exp(\\\"boundaries\\\")\\n lst = exp.find_groups(self.give_field(\\\"mesh\\\"))\\n tit = u\\\"Adding imposed degrees of freedom on groups\\\"\\n add_condition_selector(self, lst, dims, \\\"group-boundaries*\\\", tit)\",\n \"def build_frames(dialbox):\\n #Buttons Frame\\n dialbox.button_frame = tk.Frame(dialbox.master_frame)\\n dialbox.button_frame.grid(row=3, column=1)\\n #Output Frame\\n dialbox.output_frame = tk.Frame(dialbox.master_frame)\\n dialbox.output_frame.grid(row=4, column=0, columnspan=2)\",\n \"def create_page(self, parent):\\n ui = self.edit_traits(parent=parent, kind=\\\"subpanel\\\")\\n return ui.control\",\n \"def _sidepanel(self):\\n global curdir\\n global sidepanel_layout\\n global root\\n\\n #Create the sidepanel layout.\\n sidepanel_layout = BoxLayout(orientation=\\\"vertical\\\", pos_hint={\\\"x\\\": 0.0, \\\"top\\\": 0.92}, size_hint=(0.1, 0.92))\\n\\n #If \\\"curdir\\\" contains folders, a button is created for each, and bind the button to update the\\n # showphotos layout.\\n if curdir == \\\" \\\":\\n return sidepanel_layout\\n else:\\n root.remove_widget(sidepanel_layout)\\n for folders in sorted(glob(join(curdir, \\\"thumb\\\", \\\"*\\\"))):\\n name = basename(folders)\\n btn = Button(text=name, on_press=lambda n=name: self._update_scroll(n.text))\\n sidepanel_layout.add_widget(btn)\\n root.add_widget(sidepanel_layout)\\n sidepanel_layout.do_layout()\",\n \"def create_board(self):\\n for field in self.fields_start_locs:\\n loc = self.loc_to_view(field[0], field[1])\\n new_field = Field(loc, self.piece_size)\\n self.sprite_group.add(new_field)\\n self.click_sprites.add(new_field)\\n self.fields.append(new_field)\",\n \"def initializePage(self):\\n WC.WizardPage.initialize(self)\\n self.page.use(qt.QVBoxLayout())\\n exp = self.give_field(\\\"exp-store\\\").give_exp(\\\"pressure\\\")\\n grps = exp.find_groups(self.give_field(\\\"mesh\\\"))\\n dims = [(u\\\"Pressure\\\", 1.)]\\n tit = u\\\"Adding pressure on meshes groups\\\"\\n # The last groups should be seen first\\n grps.reverse()\\n WC.add_condition_selector(self, grps, dims, \\\"pressure-loading*\\\", tit)\",\n \"def create_sat_panels(self):\\n\\n # Dimensions of body\\n SAT_SIZE = self.ANI_SCALE*self.SAT_SCALE*np.asarray(self.SAT_PROPS[\\\"Size\\\"])/2\\n bx = SAT_SIZE[0]\\n by = SAT_SIZE[1]\\n bz = SAT_SIZE[2]\\n\\n # Panel length\\n L = bx\\n\\n # Panels\\n theta = self.PANEL_ANGLE*pi/180\\n px1 = bx - L*sin(theta)\\n py1 = by + L*cos(theta)\\n pz1 = bz\\n px2 = px1 + L*sin(theta)\\n py2 = py1 + L*cos(theta)\\n pz2 = pz1\\n\\n # Vertices\\n V = [\\n (-bx, by, -bz),\\n (-bx, by, bz),\\n (-px1, py1, pz1),\\n (-px1, py1, -pz1),\\n (-px1, py1, -pz1),\\n (-px1, py1, pz1),\\n (-px2, py2, pz2),\\n (-px2, py2, -pz2),\\n (-bx, -by, -bz),\\n (-bx, -by, bz),\\n (-px1, -py1, pz1),\\n (-px1, -py1, -pz1),\\n (-px1, -py1, -pz1),\\n (-px1, -py1, pz1),\\n (-px2, -py2, pz2),\\n (-px2, -py2, -pz2)\\n ]\\n\\n # Create faces\\n F = [\\n (0, 1, 2, 3),\\n (4, 5, 6, 7),\\n (8, 9, 10, 11),\\n (12, 13, 14, 15)\\n ]\\n\\n # Create building blocks of polydata\\n sat = vtk.vtkPolyData()\\n points = vtk.vtkPoints()\\n polys = vtk.vtkCellArray()\\n scalars = vtk.vtkFloatArray()\\n\\n # Load the point, cell and data attributes\\n for i in range(len(V)):\\n points.InsertPoint(i, V[i])\\n for i in range(len(F)):\\n polys.InsertNextCell(self.mkVtkIdList(F[i]))\\n for i in range(len(V)):\\n scalars.InsertTuple1(i, i)\\n \\n # Assign the pieces to the vtkPolyData.\\n sat.SetPoints(points)\\n del points\\n sat.SetPolys(polys)\\n del polys\\n sat.GetPointData().SetScalars(scalars)\\n del scalars\\n\\n # Mapper\\n mapper = vtk.vtkPolyDataMapper()\\n mapper.SetInputData(sat)\\n mapper.ScalarVisibilityOff()\\n\\n # Actor\\n actor = vtk.vtkActor()\\n actor.SetMapper(mapper)\\n actor.GetProperty().SetColor(0., 0., 0.8)\\n actor.GetProperty().SetAmbient(0.5)\\n actor.GetProperty().SetSpecular(.5)\\n actor.GetProperty().SetSpecularPower(10.0)\\n actor.GetProperty().SetDiffuse(0.2)\\n\\n # Move to sat position\\n actor.SetPosition(0, 0, -self.SAT_PROPS[\\\"Alt\\\"])\\n\\n return actor\",\n \"def single_slice_panels(page,\\n horizontal_vertical=None,\\n type_choice=None,\\n skew_side=None,\\n number_to_slice=0\\n ):\\n\\n # Remove panels which are too small\\n relevant_panels = []\\n if len(page.children) > 0:\\n get_min_area_panels(page,\\n cfg.slice_minimum_panel_area,\\n ret_panels=relevant_panels\\n )\\n else:\\n relevant_panels = [page]\\n\\n # Shuffle panels for randomness\\n random.shuffle(relevant_panels)\\n\\n # single slice close\\n if type_choice is None:\\n type_choice_prob = np.random.random()\\n if type_choice_prob < cfg.center_side_ratio:\\n type_choice = \\\"center\\\"\\n else:\\n type_choice = \\\"side\\\"\\n\\n num_panels_added = 0\\n\\n # Slice panels down the center\\n if type_choice == \\\"center\\\":\\n if len(relevant_panels) < 1:\\n return page\\n\\n if number_to_slice == 0:\\n if len(relevant_panels) > 1:\\n number_to_slice = np.random.randint(1, len(relevant_panels))\\n else:\\n number_to_slice = 1\\n\\n for idx in range(0, number_to_slice):\\n panel = relevant_panels[idx]\\n num_panels_added += 1\\n\\n # Decide which direction to cut in\\n if horizontal_vertical is None:\\n horizontal_vertical = np.random.choice([\\\"h\\\", \\\"v\\\"])\\n\\n # Get center line\\n # Vertical slice\\n if horizontal_vertical == \\\"v\\\":\\n panel_chosen_coord_length = (panel.x2y2[0] - panel.x1y1[0])/2\\n\\n # Slice panel\\n draw_n(2, panel, \\\"v\\\")\\n\\n # Skew it left or right\\n if skew_side is None:\\n skew_side = np.random.choice([\\\"left\\\", \\\"right\\\"])\\n\\n # Skew it by a percentage\\n skew_amount = np.random.randint(20, 100)/100\\n skew_amount = skew_amount*panel_chosen_coord_length\\n\\n # Perform transform\\n p1 = panel.get_child(0)\\n p2 = panel.get_child(1)\\n\\n p1.sliced = True\\n p2.sliced = True\\n if skew_side == \\\"left\\\":\\n p1.x2y2 = (p1.x2y2[0] - skew_amount, p1.x2y2[1])\\n p1.x3y3 = (p1.x3y3[0] + skew_amount, p1.x3y3[1])\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = (p2.x1y1[0] - skew_amount, p2.x1y1[1])\\n p2.x4y4 = (p2.x4y4[0] + skew_amount, p2.x4y4[1])\\n\\n p2.refresh_coords()\\n\\n elif skew_side == \\\"right\\\":\\n p1.x2y2 = (p1.x2y2[0] + skew_amount, p1.x2y2[1])\\n p1.x3y3 = (p1.x3y3[0] - skew_amount, p1.x3y3[1])\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = (p2.x1y1[0] + skew_amount, p2.x1y1[1])\\n p2.x4y4 = (p2.x4y4[0] - skew_amount, p2.x4y4[1])\\n\\n p2.refresh_coords()\\n\\n else:\\n print(\\\"Chosen incorrect skew side\\\")\\n return None\\n\\n # Horizontal slice\\n else:\\n panel_chosen_coord_length = (panel.x3y3[1] - panel.x2y2[1])/2\\n\\n # Slice panel\\n draw_n(2, panel, \\\"h\\\")\\n\\n # Skew it left or right\\n if skew_side is None:\\n skew_side = np.random.choice([\\\"down\\\", \\\"up\\\"])\\n\\n # Skew it by a percentage\\n skew_amount = np.random.randint(20, 100)/100\\n skew_amount = skew_amount*panel_chosen_coord_length\\n\\n p1 = panel.get_child(0)\\n p2 = panel.get_child(1)\\n\\n p1.sliced = True\\n p2.sliced = True\\n if skew_side == \\\"down\\\":\\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] + skew_amount)\\n p1.x3y3 = (p1.x3y3[0], p1.x3y3[1] - skew_amount)\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] + skew_amount)\\n p2.x2y2 = (p2.x2y2[0], p2.x2y2[1] - skew_amount)\\n\\n p2.refresh_coords()\\n\\n elif skew_side == \\\"up\\\":\\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] - skew_amount)\\n p1.x3y3 = (p1.x3y3[0], p1.x3y3[1] + skew_amount)\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] - skew_amount)\\n p2.x2y2 = (p2.x2y2[0], p2.x2y2[1] + skew_amount)\\n\\n p2.refresh_coords()\\n else:\\n print(\\\"Chose incorrect skew_side\\\")\\n\\n # Slice panel sides\\n else:\\n if len(relevant_panels) < 1:\\n return page\\n\\n if number_to_slice == 0:\\n if len(relevant_panels) > 1:\\n number_to_slice = np.random.choice([1, 3])\\n else:\\n number_to_slice = 1\\n\\n for panel in relevant_panels[0:number_to_slice]:\\n\\n if skew_side is None:\\n skew_side = np.random.choice([\\\"tr\\\", \\\"tl\\\", \\\"br\\\", \\\"bl\\\"])\\n\\n draw_n(2, panel, \\\"h\\\")\\n num_panels_added += 1\\n\\n p1 = panel.get_child(0)\\n p2 = panel.get_child(1)\\n\\n # Panels are non standard polygons\\n p1.non_rect = True\\n p2.non_rect = True\\n\\n p1.sliced = True\\n p2.sliced = True\\n\\n cut_y_proportion = np.random.randint(25, 75)/100\\n cut_x_proportion = np.random.randint(25, 75)/100\\n\\n cut_y_length = (panel.x4y4[1] - panel.x1y1[1])*cut_y_proportion\\n cut_x_length = (panel.x3y3[0] - panel.x4y4[0])*cut_x_proportion\\n\\n # bottom left corner\\n if skew_side == \\\"bl\\\":\\n\\n p1_cut_x1y1 = (panel.x4y4[0], panel.x4y4[1] - cut_y_length)\\n p1_cut_x2y2 = (panel.x4y4[0] + cut_x_length, panel.x4y4[1])\\n p1_cut_x3y3 = (panel.x4y4)\\n\\n p1.coords = [p1_cut_x1y1, p1_cut_x2y2,\\n p1_cut_x3y3, p1_cut_x1y1]\\n\\n p2.coords = [panel.x1y1, panel.x2y2, panel.x3y3,\\n p1_cut_x2y2, p1_cut_x1y1, panel.x1y1]\\n\\n # bottom right corner\\n elif skew_side == \\\"br\\\":\\n\\n p1_cut_x1y1 = (panel.x3y3[0], panel.x3y3[1] - cut_y_length)\\n p1_cut_x2y2 = (panel.x3y3)\\n p1_cut_x3y3 = (panel.x3y3[0] - cut_x_length, panel.x3y3[1])\\n\\n p1.coords = [p1_cut_x1y1, p1_cut_x2y2,\\n p1_cut_x3y3, p1_cut_x1y1]\\n\\n p2.coords = [panel.x1y1, panel.x2y2, p1_cut_x1y1,\\n p1_cut_x3y3, panel.x4y4, panel.x1y1]\\n\\n # top left corner\\n elif skew_side == \\\"tl\\\":\\n\\n p1_cut_x1y1 = panel.x1y1\\n p1_cut_x2y2 = (panel.x1y1[0] + cut_x_length, panel.x1y1[1])\\n p1_cut_x3y3 = (panel.x1y1[0], panel.x1y1[1] + cut_y_length)\\n\\n p1.coords = [p1_cut_x1y1, p1_cut_x2y2,\\n p1_cut_x3y3, p1_cut_x1y1]\\n p2.coords = [p1_cut_x2y2, panel.x2y2, panel.x3y3,\\n panel.x4y4, p1_cut_x3y3, p1_cut_x1y1]\\n\\n # top right corner\\n elif skew_side == \\\"tr\\\":\\n p1_cut_x1y1 = (panel.x2y2[0] - cut_x_length, panel.x2y2[1])\\n p1_cut_x2y2 = panel.x2y2\\n p1_cut_x3y3 = (panel.x2y2[0], panel.x2y2[1] + cut_y_length)\\n\\n p1.coords = [p1_cut_x1y1, p1_cut_x2y2,\\n p1_cut_x3y3, p1_cut_x1y1]\\n\\n p2.coords = [panel.x1y1, p1_cut_x1y1, p1_cut_x3y3,\\n panel.x3y3, panel.x4y4, panel.x1y1]\\n else:\\n print(\\\"Chose incorrect skew side\\\")\\n return None\\n\\n page.num_panels += num_panels_added\\n\\n return page\",\n \"def test_7_replay_4(self):\\n self._execute_replay_nr(4)\\n\\n self.grid.add_pawn(5, 'H')\\n self.grid.add_pawn(3, 'B')\\n self.grid.add_pawn(2, 'H')\\n self.grid.add_pawn(1, 'B')\\n self.grid.add_pawn(1, 'H')\\n\\n # self.grid.print_grid()\\n # print(self.minmaxBot_7.choose_move(self.grid))\",\n \"def _generateNamedContainingPanel(self, obj, **args):\\n result = []\\n parent = obj.parent\\n while parent and (parent.parent != parent):\\n if parent.getRole() == pyatspi.ROLE_PANEL:\\n label = self._generateLabelAndName(parent)\\n if label:\\n result.extend(label)\\n break\\n parent = parent.parent\\n return result\",\n \"def ReDockPage(self, pane):\\r\\n\\r\\n root_manager = framemanager.GetManager(self) \\r\\n\\r\\n pane.window.__floating_size__ = wx.Size(*pane.floating_size)\\r\\n page_index = pane.window.__page_index__\\r\\n text_colour = pane.window.__text_colour__\\r\\n control = pane.window.__control__\\r\\n \\r\\n root_manager.DetachPane(pane.window)\\r\\n self.InsertPage(page_index, pane.window, pane.caption, True, pane.icon, control=control)\\r\\n\\r\\n self.SetPageTextColour(page_index, text_colour)\\r\\n self.GetActiveTabCtrl().DoShowHide()\\r\\n self.DoSizing()\\r\\n if control:\\r\\n self.UpdateTabCtrlHeight(force=True)\\r\\n \\r\\n self._mgr.Update()\\r\\n root_manager.Update()\",\n \"def first_step(self, plan, sequence, imgnum):\\n def max_diaphragmatic_level(levels):\\n \\\"\\\"\\\"\\n As a column in the 2DST image may have more than one point representing the\\n diaphragmatic level, this function retrieves only the biggest point, which\\n will represent the diaphragmatic level\\n\\n Parameters\\n ----------\\n levels: list\\n List of lists of int that represents the diafragmatics levels\\n \\\"\\\"\\\"\\n return [max(x) for x in levels]\\n\\n # Define the dimension of the matrixes\\n mat_dim = (len(self.sag_sequences), len(self.cor_sequences))\\n self.matRegistration = np.zeros(mat_dim)\\n self.matX = np.zeros(mat_dim)\\n self.matY = np.zeros(mat_dim)\\n self.matZ = np.zeros(mat_dim)\\n self.matDL = np.zeros(mat_dim)\\n self.matRP = np.zeros(mat_dim)\\n\\n # Respiratory patterns linked to the sequence containing the root image\\n lpatterns = [x for x in self.dataset if int(x.split('-')[1]) == sequence]\\n # print('Patterns coronal: {} ({})\\\\n'.format(lpatterns, len(lpatterns)))\\n\\n # Represents the column in the register matrix that represents the sequence used\\n column = self.cor_sequences.index(sequence)\\n # print('Index: {}\\\\n'.format(column))\\n\\n \\\"\\\"\\\" Retrieves the diaphragmatic levels of the root image (coronal plan) and stores\\n them in the correct positions of the register matrix \\\"\\\"\\\"\\n for i in range(self.matrows):\\n # print('{}.png'.format(lpatterns[i]))\\n\\n pts_pattern = self.pattern_coronal('{}.png'.format(lpatterns[i]))\\n diaph_lvl = self.diaphragmatic_level_coronal(pts_pattern)\\n max_diaph_lvl = max_diaphragmatic_level(diaph_lvl)\\n resp_phase = self.respiratory_phase_coronal(diaph_lvl)\\n\\n self.matDL[i, column] = max_diaph_lvl[imgnum - 1] # -1\\n self.matRP[i, column] = resp_phase[i]\\n self.matRegistration[i, column] = self.blue\\n\\n # print(\\\"(Step 1) Diaphragmatic level matrix:\\\\n{}\\\\n\\\".format(self.matDL))\\n # print(\\\"(Step 1) Registration matrix:\\\\n{}\\\\n\\\".format(self.matRegistration))\\n # print(\\\"(Step 1) Respiratory phase:\\\\n{}\\\\n\\\".format(self.matRP))\\n\\n dlvl = [self.matDL[i, column] for i in range(len(self.sag_sequences))]\\n rphase = [int(self.matRP[i, column]) for i in range(len(self.sag_sequences))]\\n # print(\\\"(Step 1) DL: {}\\\\n\\\".format(dlvl))\\n\\n return dlvl, rphase\",\n \"def define_panel_structure(self):\\n w, h = self.parent.GetSize()\\n self.vbox = wx.BoxSizer(wx.VERTICAL)\\n self.sizer1 = wx.BoxSizer(wx.VERTICAL)\\n self.sizer1.SetMinSize(wx.Size(w/13, h*2/5))\\n\\n self.sizer2 = wx.BoxSizer(wx.VERTICAL)\\n self.sizer3 = wx.FlexGridSizer(9, 2, 4, 1)\\n self.sizer4 = wx.BoxSizer(wx.VERTICAL)\\n self.sizer5 = wx.BoxSizer(wx.VERTICAL)\\n\\n self.vbox.Add(self.sizer5, 0, wx.EXPAND | wx.ALL, 1)\\n self.vbox.Add(self.sizer1, 1, wx.EXPAND | wx.ALL, 0)\\n self.vbox.Add(self.sizer2, 0, wx.EXPAND | wx.ALL, 1)\\n self.vbox.Add(self.sizer3, 0, wx.EXPAND | wx.ALL, 10)\\n # self.vbox.Add(self.sizer4, 0, wx.EXPAND|wx.ALL,5)\\n\\n self.SetSizer(self.vbox)\",\n \"def draw_window_pane():\\n houseturtle.begin_fill()\\n for y in range(4):\\n houseturtle.pendown()\\n houseturtle.forward(35)\\n houseturtle.left(90)\\n houseturtle.penup()\\n houseturtle.end_fill()\",\n \"def set_pieces(self):\\n\\n for i in range(len(self._game_board)):\\n\\n # Row 1\\n if i == 0:\\n for ii in range(len(self._game_board[i])):\\n if ii == 0 or ii == 8:\\n self._game_board[i][ii] = Chariot(\\\"black\\\", \\\"BCHA\\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 1 or ii == 7:\\n self._game_board[i][ii] = Horse(\\\"black\\\", \\\" BH \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 2 or ii == 6:\\n self._game_board[i][ii] = Elephant(\\\"black\\\", \\\" BE \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 3 or ii == 5:\\n self._game_board[i][ii] = Advisor(\\\"black\\\", \\\" BA \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 4:\\n self._game_board[i][ii] = General(\\\"black\\\", \\\" BG \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n\\n # Row 3\\n if i == 2:\\n for ii in range(len(self._game_board[i])):\\n if ii == 1 or ii == 7:\\n self._game_board[i][ii] = Cannon(\\\"black\\\", \\\"BCAN\\\")\\n self._game_board[i][ii].update_location([i, ii])\\n\\n # Row 4\\n if i == 3:\\n for ii in range(len(self._game_board[i])):\\n if ii % 2 == 0:\\n self._game_board[i][ii] = Soldier(\\\"black\\\", \\\"BSOL\\\")\\n self._game_board[i][ii].update_location([i, ii])\\n\\n # Row 7\\n if i == 6:\\n for ii in range(len(self._game_board[i])):\\n if ii % 2 == 0:\\n self._game_board[i][ii] = Soldier(\\\"red\\\", \\\"RSOL\\\")\\n self._game_board[i][ii].update_location([i, ii])\\n\\n # Row 8\\n if i == 7:\\n for ii in range(len(self._game_board[i])):\\n if ii == 1 or ii == 7:\\n self._game_board[i][ii] = Cannon(\\\"red\\\", \\\"RCAN\\\")\\n self._game_board[i][ii].update_location([i, ii])\\n\\n # Row 10\\n if i == 9:\\n for ii in range(len(self._game_board[i])):\\n if ii == 0 or ii == 8:\\n self._game_board[i][ii] = Chariot(\\\"red\\\", \\\"RCHA\\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 1 or ii == 7:\\n self._game_board[i][ii] = Horse(\\\"red\\\", \\\" RH \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 2 or ii == 6:\\n self._game_board[i][ii] = Elephant(\\\"red\\\", \\\" RE \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 3 or ii == 5:\\n self._game_board[i][ii] = Advisor(\\\"red\\\", \\\" RA \\\")\\n self._game_board[i][ii].update_location([i, ii])\\n if ii == 4:\\n self._game_board[i][ii] = General(\\\"red\\\", \\\" RG \\\")\\n self._game_board[i][ii].update_location([i, ii])\",\n \"def create_portal(self, maze, portal_type):\\n\\n # use adjusted position to add size of brick to find nearest brick in grid\\n x, y = self.adjust_position()\\n found = False\\n\\n # Pacman facing right\\n if self.image in self.animated_right:\\n\\n # Find nearest brick on the right\\n while x < self.screen_rect.width and not found:\\n x += maze.brick_size\\n\\n for brick in maze.bricks:\\n if x == brick.rect.x and y == brick.rect.y:\\n\\n # Add a portal\\n self.add_portal(portal_type, \\\"left\\\", (x, y))\\n found = True\\n break\\n\\n # Pacman facing left\\n elif self.image in self.animated_left:\\n\\n # Find nearest brick on the left\\n while x >= 0 and not found:\\n x -= maze.brick_size\\n\\n for brick in maze.bricks:\\n if x == brick.rect.x and y == brick.rect.y:\\n\\n # Add a portal\\n self.add_portal(portal_type, \\\"right\\\", (x, y))\\n found = True\\n break\\n\\n # Pacman facing up\\n elif self.image in self.animated_up:\\n\\n # Find nearest brick above\\n while y >= 0 and not found:\\n y -= maze.brick_size\\n\\n for brick in maze.bricks:\\n if x == brick.rect.x and y == brick.rect.y:\\n\\n # Add a portal\\n self.add_portal(portal_type, \\\"down\\\", (x, y))\\n found = True\\n break\\n\\n # Pacman facing down\\n elif self.image in self.animated_down:\\n\\n # Find nearest brick below\\n while y <= self.screen_rect.height and not found:\\n y += maze.brick_size\\n\\n for brick in maze.bricks:\\n if x == brick.rect.x and y == brick.rect.y:\\n\\n # Add a portal\\n self.add_portal(portal_type, \\\"up\\\", (x, y))\\n found = True\\n break\",\n \"def paneLayout(*args, activeFrameThickness: Union[int, bool]=0, activePane: Union[AnyStr,\\n bool]=\\\"\\\", activePaneIndex: Union[int, bool]=0, annotation: Union[AnyStr,\\n bool]=\\\"\\\", backgroundColor: Union[List[float, float, float], bool]=None,\\n childArray: bool=True, configuration: Union[AnyStr, bool]=\\\"\\\", defineTemplate:\\n AnyStr=\\\"\\\", docTag: Union[AnyStr, bool]=\\\"\\\", dragCallback: Script=None,\\n dropCallback: Script=None, enable: bool=True, enableBackground: bool=True,\\n enableKeyboardFocus: bool=True, exists: bool=True, fullPathName: bool=True,\\n height: Union[int, bool]=0, highlightColor: Union[List[float, float, float],\\n bool]=None, isObscured: bool=True, manage: bool=True, noBackground: bool=True,\\n numberOfChildren: bool=True, numberOfPopupMenus: bool=True,\\n numberOfVisiblePanes: bool=True, pane1: bool=True, pane2: bool=True, pane3:\\n bool=True, pane4: bool=True, paneSize: Union[List[int, int, int], List[List[int,\\n int, int]], bool]=None, paneUnderPointer: bool=True, parent: Union[AnyStr,\\n bool]=\\\"\\\", popupMenuArray: bool=True, preventOverride: bool=True,\\n separatorMovedCommand: Script=None, separatorThickness: Union[int, bool]=0,\\n setPane: Union[List[AnyStr, int], List[List[AnyStr, int]]]=None,\\n staticHeightPane: int=0, staticWidthPane: int=0, statusBarMessage: AnyStr=\\\"\\\",\\n useTemplate: AnyStr=\\\"\\\", visible: bool=True, visibleChangeCommand: Union[Script,\\n bool]=None, width: Union[int, bool]=0, q=True, query=True, e=True, edit=True,\\n **kwargs)->Union[AnyStr, Any]:\\n pass\",\n \"def floorplan(PAN, tilt1 = None): #---- placement floorplan\\r\\n if tilt1 is not None: PAN.img1_tilt = tilt1; # setup tilt angle for image 1\\r\\n PAN.H = np.zeros((PAN.count, 8)); # Transform matrix for floorplan\\r\\n print('---- floorplanning:')\\r\\n for k in range(PAN.count):\\r\\n PAN.H[k,0]= PAN.imgc[k].shape[0]; # set image height\\r\\n PAN.H[k,1]= PAN.imgc[k].shape[1]; # set image width\\r\\n PAN.H[k,2]= (0.5/np.tan(PAN.hfov/180*np.pi))* PAN.imgs[k].shape[1]; \\r\\n PAN.H[k,4]= 1; # set initial sizing = 1\\r\\n PAN.H[0,3]= PAN.img1_tilt/180*np.pi; # set tilt \\r\\n #--- compute new floorplan for image 2 ~ ... ---\\r\\n for k in range(1, PAN.count): # \\r\\n #for k in range(1, 2): # debug only \\r\\n KPS1 = PAN.KPDBs[k-1]; # load keypoint database\\r\\n KPS2 = PAN.KPDBs[k]; # \\r\\n H1 = PAN.H[k-1]; # transform function\\r\\n H2 = PAN.H[k]; # \\r\\n for m in range(0, PAN.match_seq.shape[0]):\\r\\n if PAN.match_seq[m, 0]== (k-1) and PAN.match_seq[m, 1]== k: \\r\\n match = PAN.matchinfo[m];\\r\\n pano_tools.stitch(KPS1, KPS2, H1, H2, match);\",\n \"def push_down (grid):\\r\\n for i in range (3):\\r\\n for row in range(2,-1, -1):\\r\\n for col in range(4):\\r\\n if grid[row+1][col] == 0:\\r\\n grid[row+1][col] = grid[row][col]\\r\\n grid[row][col] = 0 \\r\\n for row in range(1,4):\\r\\n for col in range(4):\\r\\n if grid[row-1][col] == grid[row][col]:\\r\\n grid[row-1][col] = grid[row-1][col]*2\\r\\n grid[row][col]=0 \\r\\n for i in range (3):\\r\\n for row in range(2,-1, -1):\\r\\n for col in range(4):\\r\\n if grid[row+1][col] == 0:\\r\\n grid[row+1][col] = grid[row][col]\\r\\n grid[row][col] = 0 \\r\\n return grid\",\n \"def _addPanes(self):\\n\\n self._addPaneMapWindow()\\n self._addPaneToolbar(name = 'digitMap')\",\n \"def put_next_tiles(p,tiles):\\n if tiles['mode'].upper() == \\\"INIT\\\":\\n set_value(p,tiles['0']['lig'],tiles['0']['col'],tiles['0']['val']) # mettre la vleur dans le plateau avec la position donnee de tiles\\n set_value(p,tiles['1']['lig'],tiles['1']['col'],tiles['1']['val'])\\n else:\\n set_value(p,tiles['0']['lig'],tiles['0']['col'],tiles['0']['val'])\",\n \"def foward_shimmey(self):\\n for x in range(6):\\n self.right(primary=60, counter=30)\\n time.sleep(.5)\\n self.left(primary=70, counter=30)\\n time.sleep(.5)\\n self.back()\\n time.sleep(2) \\n self.stop()\",\n \"def reshape(self, bottom, top):\\n\\t\\tpass\",\n \"def get_wall_panels(self, wall_bp):\\n wall_panels = []\\n products = self.get_wall_products(wall_bp)\\n for product in products:\\n product_panel_list = self.get_product_panels(product, [])\\n for product_panel in product_panel_list:\\n wall_panels.append(product_panel)\\n return wall_panels\",\n \"def add_transforms(page):\\n # Transform types\\n\\n # Allow choosing multiple\\n transform_choice = [\\\"slice\\\", \\\"box\\\"]\\n\\n # Slicing panels into multiple panels\\n # Works best with large panels\\n if \\\"slice\\\" in transform_choice:\\n page = single_slice_panels(page)\\n\\n # Makes v cuts happen more often 1/4 chance\\n if np.random.random() < cfg.double_slice_chance:\\n page = single_slice_panels(page)\\n\\n if \\\"box\\\" in transform_choice:\\n\\n if np.random.random() < cfg.box_transform_panel_chance:\\n page = box_transform_panels(page)\\n\\n page = box_transform_page(page)\\n\\n return page\",\n \"def treeBuddy():\\n camera_move_offset_horiz = WIDTH / 70\\n camera_move_offset_vert = HEIGHT / 70\\n tree_found = False\\n ctrl.resetCamera()\\n for i in range(15):\\n ctrl.moveCamera('left',camera_move_offset_horiz)\\n img_obj.updateImg()\\n img_obj.cropImg(Coords.crosshair_box)\\n img_obj.modImg(1)\\n img_obj.readPixels()\\n if img_obj.isTree():\\n print 'Tree...maybe'\\n tree_found = False\\n for i in range(2):\\n ctrl.moveCamera('up',camera_move_offset_vert)\\n img_obj.updateImg()\\n img_obj.cropImg(Coords.crosshair_box)\\n img_obj.modImg(1)\\n img_obj.readPixels()\\n if not img_obj.isTree():\\n tree_found = False\\n break\\n tree_found = True\\n ctrl.resetCamera()\\n if tree_found:\\n approachTree_getWood()\",\n \"def move_buildings(self):\",\n \"def push_up (grid):\\r\\n \\r\\n for row in range (4):\\r\\n section = []\\r\\n for col in range (4):\\r\\n section.append(grid[col][row])\\r\\n add(section)\\r\\n for i in range (4):\\r\\n grid[i][row] = section[i]\",\n \"def controlOrder():\\n return ['OverlayListPanel',\\n 'LocationPanel',\\n 'OverlayInfoPanel',\\n 'OverlayDisplayPanel',\\n 'CanvasSettingsPanel',\\n 'AtlasPanel',\\n 'OverlayDisplayToolBar',\\n 'OrthoToolBar',\\n 'FileTreePanel']\",\n \"def next(self):\\n if self.index.get() != len(self.frame_list) - 1:\\n for i in range(len(self.frame_list)):\\n self.frame_list[i].pack_forget()\\n\\n self.index.set(self.index.get() + 1)\\n self.frame_list[self.index.get()].pack(fill=\\\"both\\\", expand=True)\\n\\n self.work_out_pages()\",\n \"def actions(self):\\n def create_move(de, vers):\\n return lambda: self._move(de, vers)\\n\\n deplacements = []\\n #itertools.product = boucle for imbriqué avec en parametre a,b\\n # ici la longueur et la largeur du tableau\\n for i, j in itertools.product(range(self.width),\\n range(self.width)):\\n #D : droite , G : gauche , B : bas , H : haut.\\n directions = {'La gauche':(i, j-1),\\n 'La droite':(i, j+1),\\n 'Le haut':(i-1, j),\\n 'Le bas':(i+1, j)}\\n\\n for action, (r, c) in directions.items():\\n if r >= 0 and c >= 0 and r < self.width and c < self.width and \\\\\\n self.plateau[r][c] == 0:\\n deplacement = create_move((i,j), (r,c)), action\\n deplacements.append(deplacement)\\n return deplacements\",\n \"def build_frames(self):\\n self.cntrl_frame = tk.PanedWindow(self.root)\\n self.cntrl_frame.pack(side = tk.TOP, padx = 1, pady = 1, fill = tk.Y)\\n self.info_frame_1 = tk.PanedWindow(self.root)\\n self.info_frame_1.pack(side = tk.TOP, padx = 1, pady = 2, fill = tk.Y)\",\n \"def DoInsertPane(panes, dock_direction, dock_layer, dock_row, dock_pos):\\r\\n\\r\\n for ii in xrange(len(panes)):\\r\\n pane = panes[ii]\\r\\n if not pane.IsFloating() and pane.dock_direction == dock_direction and \\\\\\r\\n pane.dock_layer == dock_layer and pane.dock_row == dock_row and \\\\\\r\\n pane.dock_pos >= dock_pos:\\r\\n pane.dock_pos = pane.dock_pos + 1\\r\\n\\r\\n panes[ii] = pane\\r\\n\\r\\n return panes\",\n \"def display(field):\\n side = int(math.sqrt(len(field))) # in number of elements (tiles)\\n \\n def pos():\\n cy, cx = win.getyx()\\n stdscr.addstr(0, 0, \\\"cy: \\\"+str(cy)+\\\", cx: \\\"+str(cx))\\n\\n def br():\\n while True:\\n c = stdscr.getch()\\n if c == curses.KEY_RIGHT:\\n break\\n win.refresh()\\n\\n win.addstr(0, 0, '┏')\\n for _ in range(side-1):\\n win.addstr('━━━━━━')\\n win.addstr('┳')\\n win.addstr('━━━━━━')\\n win.addstr('┓ ')\\n\\n for y in range(side):\\n \\n win.addstr('┃')\\n for x in range(side):\\n #stdscr.addstr(0, 0, \\\"side: \\\" + str(x))\\n idx = y * side + x\\n if field[idx] == 0:\\n win.addstr(' '.center(6))\\n else:\\n n = field[idx]\\n color = curses.color_pair(0)\\n if n < 0:\\n field[idx] *= -1\\n n = field[idx]\\n color = curses.A_BOLD | curses.A_STANDOUT\\n elif n == 4:\\n color = curses.color_pair(3)\\n elif n == 8:\\n color = curses.color_pair(4)\\n elif n >= 16:\\n color = curses.color_pair(1)\\n \\n #win.addstr(str(n).center(6), color)\\n \\n n = str(n)\\n left = (6-len(n)) // 2\\n right = 6 - (left + len(n))\\n win.addstr(left*' ')\\n win.addstr(n, color)\\n win.addstr(right*' ')\\n\\n \\n win.addstr('┃')\\n win.addstr(' ')\\n if y == side-1:\\n break\\n else: \\n win.addstr('┣')\\n for _ in range(side-1):\\n win.addstr('━━━━━━')\\n win.addstr('╋')\\n win.addstr('━━━━━━')\\n win.addstr('┫ ')\\n \\n win.addstr('┗')\\n for _ in range(side-1):\\n win.addstr('━━━━━━')\\n win.addstr('┻')\\n win.addstr('━━━━━━')\\n #pos()\\n #br()\\n win.addstr('┛')\\n\\n #win.border()\\n win.refresh()\",\n \"def cycle_option():\\n winlist = create_win_list()\\n winlist.insert(0,winlist[len(winlist)-1])\\n winlist = winlist[:-1]\\n arrange(get_simple_tile(len(winlist)),winlist)\",\n \"def reshape(self,bottom,top):\\n pass\",\n \"def pobj_to_html5_ccs3_grid(pcode_obj, global_opts):\\n html_str = []\\n pkve = opts_load(global_opts[0])[2]\\n pcode = (pcode_obj.asDict())['pcode'][0] # no multiple pcode blocks - no delimiter\\n pcodeopts = pcode.pop('pcodeopts', [['']]) # {:::: } # pcodeopts = pcode['pcodeopts']\\n\\n galleries = pcode.pop('gallery', '')\\n for gallery in galleries:\\n galleryopts = gallery.pop('galleryopts', [['']]) # {::: }\\n gkve = opts_load(galleryopts[0])[2] # aw, kvw, kvw =\\n try:\\n imgpath = gkve['imgpath']\\n except KeyError:\\n try:\\n imgpath = pkve['imgpath']\\n except KeyError:\\n imgpath = ''\\n html_str.append('<div class=\\\"gallery ' + opts_render(global_opts[0]) + ' ' + opts_render(galleryopts[0]) + '\\\">' + '\\\\n')\\n\\n spreads = gallery.pop('spread', '')\\n g_layout_counter = 0\\n for spread in spreads:\\n spreadopts = spread.pop('spreadopts', [['']]) # {:: }\\n html_str.append(' <div class=\\\"spread ' + opts_render(spreadopts[0]) + '\\\">' + '\\\\n')\\n\\n layouts = spread.pop('layout', '')\\n for layout in layouts:\\n g_layout_counter += 1\\n panelcounter = 0\\n panelskip = 0 # for blank x z panels\\n layoutopts = layout.pop('layoutopts', [['']]) # {: }\\n kve = opts_load(layoutopts[0])[2] # aw, kvw, kvw =\\n i_before, i_str, i_after = img_render(\\n kve, opts_render(layoutopts[0]),\\n opts_render(spreadopts[0]),\\n opts_render(galleryopts[0]),\\n opts_render(pcodeopts[0]),\\n opts_render(global_opts[0]),\\n imgpath\\n )\\n html_str.append(i_before)\\n if 'url' in kve:\\n if 'http' not in kve['url']:\\n html_str.append(' <a href=\\\"http://' + kve['url'] + '\\\">' + '\\\\n')\\n else:\\n html_str.append(' <a href=\\\"' + kve['url'] + '\\\">' + '\\\\n')\\n html_str.append(' <div class=\\\"layout ' + opts_render(layoutopts[0]) + '\\\">' + '\\\\n')\\n label_str_html = ''\\n\\n panelgroups = layout.pop('panelgroup', '')\\n for panelgroup in panelgroups:\\n panelgroupopts = panelgroup.pop('panelgroupopts', [['']]) # {}\\n terms = panelgroup.pop('terms', [['']])\\n # build row list -- grouped by commas and skipping +\\n row_list = [[]]\\n for term in terms[0]:\\n # , adds row sublist\\n if term == [',']:\\n row_list.append([])\\n # skip +\\n elif term == ['+']:\\n continue\\n # missing counts = 1, e.g. ['']['r2'] = ['1']['r2']\\n elif term[0] == '':\\n term[0] = '1'\\n row_list[-1].append(term)\\n # 0 indicates a blank / spacer panel\\n elif term[0] == '0':\\n term[0] = '1'\\n term.append('x') # or z? based on setting?\\n row_list[-1].append(term)\\n # setting panels to x or z will impact panel numbering and total count\\n # just append anything else\\n else:\\n row_list[-1].append(term)\\n\\n # Find the panelgroup width. This is either:\\n # 1. Defined above, in the pcode, gallery, spread, or layout level.\\n # For example, newspaper comics might be defined at the spread\\n # or layout level for reflow.\\n # 2. ...or else: Defined in panelgroupopts.\\n # 3. ...or else: Calculated from the longest row.\\n # (i.e. discovered via comma placement)\\n #\\n # In the css3 renderer width must be specified in the panelgroup class.\\n allopts = [pcodeopts[0], galleryopts[0],\\n spreadopts[0], layoutopts[0], panelgroupopts[0]]\\n pgroup_width = 0\\n while allopts and pgroup_width == 0:\\n opts = allopts.pop(0)\\n for opt in opts:\\n if isinstance(opt, basestring) and opt.startswith('w'):\\n pgroup_width = int(opt[1:])\\n break\\n if pgroup_width == 0:\\n # Find the length in panel spans of the longest row.\\n # e.g. c3 + 2 = 5\\n # This could be the first row, but not necessarily.\\n # Rows are *not* the same length in groups with rowspans.\\n # Rows could also be ragged. (in theory) although this\\n # isn't explicitly supported.\\n row_lengths = []\\n for row in row_list:\\n row_len = 0\\n for panel in row:\\n # check for 'c2' style column span arugment\\n # ...there should be only one c arg, but the\\n # max is taken if there are many, 1 if no arg.\\n c_args = [int(arg[1:]) for arg in panel\\n if isinstance(arg, basestring)\\n and arg.startswith('c')\\n and len(arg) > 1\\n and arg[1:].isdigit()]\\n # # print(c_args)\\n try:\\n c_max = max(c_args)\\n except ValueError:\\n c_max = 1\\n # multiply panel width by panel count\\n panel_len = int(panel[0]) * c_max\\n # append panel length to total row length\\n row_len = row_len + panel_len\\n # append row length to list\\n row_lengths.append(row_len)\\n # set width to max\\n pgroup_width = max(row_lengths)\\n panelgroupopts[0][0] = panelgroupopts[0][0] + ' w' + unicode(pgroup_width)\\n html_str.append(' <div class=\\\"panelgroup ' + panelgroupopts[0][0] + '\\\">' + '\\\\n')\\n\\n for row in row_list:\\n # load panel arguments\\n for panel in row:\\n arg_add = []\\n for idx, arg in enumerate(panel):\\n # intercept generic u for CSS styling and add count\\n if arg.startswith('u') and isinstance(arg, basestring):\\n if len(arg) == 1:\\n arg_add.append('u1')\\n elif len(arg) > 1 and arg[1:].isdigit():\\n arg_add.append('u')\\n # note that the edge case e.g. u.u3 is not handled\\n # this will be fine for renderer (u_max=3, correct label)\\n # but will become u u1 u2 in css -- works but unclear\\n panel = panel + arg_add\\n panel_args = ' ' + ' '.join(panel[1:])\\n panel_count = int(panel[0])\\n # print panels, assigning counts and id labels\\n for idx in range(0, panel_count):\\n pas = panel_args.strip()\\n # blank panels\\n if 'x' in panel_args or 'z' in panel_args:\\n panelcounter += 1\\n panelskip += 1\\n html_str.append(\\n ' <div class=\\\"panel '\\n + pas + '\\\">*</div>' + '\\\\n'\\n )\\n # unencoded (multi)panels -- mutually exclusive with blanks\\n elif 'u' in panel_args:\\n # ignore generic u and check for u# count\\n u_args = [int(arg[1:]) for arg in panel\\n if (arg.startswith('u')\\n and len(arg) > 1)\\n and arg[1:].isdigit()\\n ]\\n # after loading u_args, add generic u in-place for CSS styling\\n try:\\n u_max = max(u_args)\\n except ValueError:\\n u_max = 1\\n if u_max == 0:\\n panelcounter += 1\\n panelskip += 1\\n html_str.append(\\n ' <div class=\\\"panel '\\n + pas + '\\\">*</div>' + '\\\\n'\\n )\\n elif u_max == 1:\\n panelcounter += 1\\n label = unicode(panelcounter - panelskip)\\n html_str.append(\\n ' <div class=\\\"panel '\\n + pas + '\\\">' + label + '</div>' + '\\\\n'\\n )\\n else:\\n label = unicode(panelcounter + 1 - panelskip) + '-' + unicode(panelcounter + (u_max) - panelskip)\\n html_str.append(\\n ' <div class=\\\"panel '\\n + pas + '\\\">' + label + '</div>' + '\\\\n'\\n )\\n panelcounter += u_max\\n # regular panels\\n else:\\n panelcounter += 1\\n label = unicode(panelcounter - panelskip)\\n html_str.append(\\n ' <div class=\\\"panel '\\n + pas + '\\\">' + label + '</div>' + '\\\\n'\\n )\\n\\n html_str.append(' </div>' + '\\\\n')\\n\\n html_str.append(i_str)\\n try:\\n label_str_html = ''\\n for opt_str in [opts_render(layoutopts[0]),\\n opts_render(spreadopts[0]),\\n opts_render(galleryopts[0]),\\n opts_render(pcodeopts[0])\\n ]:\\n if 'autolabel' in opt_str:\\n try:\\n label_str = os.path.splitext(os.path.basename(kve['img']))[0]\\n except:\\n label_str = unicode(g_layout_counter)\\n label_str_html = ' <div class=\\\"label bottom\\\">' \\\\\\n + label_str + '</div>' + '\\\\n'\\n if 'label' in kve:\\n label_str = kve['label']\\n label_str_html = ' <div class=\\\"label bottom\\\"><div>' + label_str + '</div></div>' + '\\\\n'\\n if label_str_html:\\n html_str.append(' ' + label_str_html)\\n except TypeError:\\n pass\\n html_str.append(' </div>' + '\\\\n')\\n if 'url' in kve:\\n html_str.append(' </a>' + '\\\\n')\\n html_str.append(i_after)\\n html_str.append(' </div>' + '\\\\n')\\n html_str.append('</div>' + '\\\\n')\\n\\n return html_str\",\n \"def __navigate_scroll(self):\\n try:\\n _title = self.browser.title\\n _body = self.browser.find_element_by_tag_name('body')\\n\\n i = 0\\n while i < 3:\\n _html = str(self.browser.page_source)\\n _content = Content(_html, _title)\\n _attrs = _content.last_divs\\n\\n scroll_items = []\\n for _attr in _attrs:\\n xpath_string = '//div'\\n\\n for k, v in _attr.items():\\n if not v:\\n xpath_string = xpath_string + \\\"[@\\\" + str(k) + \\\"]\\\"\\n else:\\n if isinstance(v, list):\\n _vstring = [\\\"contains(@\\\" + str(k) + \\\", '\\\" + str(_v) + \\\"')\\\" for _v in v]\\n vstring = \\\" and \\\".join(_vstring)\\n\\n xpath_string = xpath_string + \\\"[\\\" + vstring + \\\"]\\\"\\n\\n div = self.browser.find_elements_by_xpath(xpath_string)\\n\\n for d in div: scroll_items.append(d)\\n\\n if len(scroll_items) > 10:\\n j = 0\\n while j < 10:\\n try:\\n self.browser.execute_script(\\\"arguments[0].scrollIntoView(true)\\\", scroll_items[j])\\n self.browser.execute_script(\\\"arguments[0].scrollIntoView(true)\\\", scroll_items[0])\\n time.sleep(1)\\n j += 1\\n except Exception as e:\\n print(e)\\n j += 1\\n continue\\n \\n else:\\n for item in scroll_items:\\n try:\\n self.browser.execute_script(\\\"arguments[0].scrollIntoView(true)\\\", item)\\n self.browser.execute_script(\\\"arguments[0].scrollIntoView(true)\\\", scroll_items[0])\\n _body.send_keys(Keys.HOME)\\n time.sleep(1)\\n except Exception as e:\\n print(e)\\n continue\\n\\n self.browser.execute_script(\\\"arguments[0].scrollIntoView(true)\\\", scroll_items[0])\\n new_html = str(self.driver.page_source)\\n new_content = Content(new_html, _title)\\n new_attrs = new_content.last_divs\\n\\n i += 1\\n if new_attrs == _attrs:\\n break\\n else:\\n continue\\n\\n return self.browser.page_source\\n\\n except:\\n return None\",\n \"def _splay(self):\\n\\n if self.parent is not None: # case 1: already the root -> do nothing\\n grandparent = self.parent.parent\\n\\n if grandparent is None: # case 2: one rotation to root\\n self._zig()\\n\\n else: # case 3: multiple rotations to root\\n rightOfLeft = self.parent.right is self and grandparent.left is self.parent\\n leftOfRight = self.parent.left is self and grandparent.right is self.parent\\n\\n if rightOfLeft or leftOfRight: # case 3a: zigzag\\n self._zig()\\n self._zig()\\n\\n else: # case 3b: zigzig\\n self.parent._zig()\\n self._zig()\\n\\n self._splay() # recur until case 1 or 2 applies\",\n \"def to_exam_root(self):\\n self._bottom_tab(4)\\n self._goto(\\\"exam_icon\\\")\",\n \"def slideTile(self, i, j, direct):\\n tile = self.getTile(i,j)\\n if direct==Move.UP: # if the direction is up\\n iRange = list(range(i - 1, -1, -1)) # list the squares above i,j\\n jRange = [j]*len(iRange) # in iRange,jRange\\n elif direct==Move.DOWN:\\n iRange = list(range(i + 1, 4))\\n jRange = [j]*len(iRange)\\n elif direct==Move.LEFT:\\n jRange = list(range(j - 1, -1, -1))\\n iRange = [i]*len(jRange)\\n else:\\n jRange = list(range(j + 1, 4))\\n iRange = [i]*len(jRange)\\n\\n # For each tile in the range above, below, to the left or right\\n for k in range(len(iRange)):\\n nextTile = self.getTile(iRange[k], jRange[k])\\n nextTileCombined = self.getCombined(iRange[k], jRange[k])\\n # If the next tile isn't empty\\n if nextTile != 0:\\n # And it's the same as the original tile and the next tile\\n # hasn't already been combined\\n if nextTile == tile and not nextTileCombined:\\n totalVal = tile*2\\n # Combine the tiles in the place of the hit tile, set\\n # combined, and empty original tile.\\n self.setTile(iRange[k],jRange[k],totalVal)\\n self.setCombined(iRange[k],jRange[k])\\n self.emptyTile(i,j)\\n return totalVal\\n # If the tiles are different and it's the first tile\\n elif k == 0:\\n return 0 # Do nothing\\n # Of they are different and it's after the first tile\\n else:\\n # Move tile to place before next tile\\n self.emptyTile(i,j)\\n # Set the space before the nonempty tile to the current\\n self.setTile(iRange[k - 1],jRange[k - 1],tile)\\n return 0\\n # If it has gone through all squares and they were all empty\\n elif k == len(iRange) - 1:\\n self.setTile(iRange[k],jRange[k],tile)\\n self.emptyTile(i,j)\\n return 0\",\n \"def front_wall(self):\\n self.place = \\\"bed\\\"\\n print(\\\"You are infront of the bed.\\\"\\n \\\"You look under it and find a notebook.\\\")\\n nb = Notebook('notebook')\\n nb.clue()\",\n \"def make_sub_views(root, loi, func):\\n item_frame = Frame(root)\\n item_frame.grid()\\n for i, item in enumerate(loi):\\n func(item_frame, item).pack(side=\\\"left\\\", fill=\\\"y\\\")\",\n \"def push_down (grid):\\r\\n for a in range(4): \\r\\n for i in range(2,-1,-1): \\r\\n for j in range(4): \\r\\n if grid[i+1][j]==0: \\r\\n grid[i+1][j]=grid[i][j] \\r\\n grid[i][j]=0\\r\\n \\r\\n for i in range(2,-1,-1): \\r\\n for j in range(4): \\r\\n if grid[i][j]==grid[i+1][j]: \\r\\n grid[i+1][j]=(grid[i+1][j])*2\\r\\n grid[i][j]=0\\r\\n \\r\\n for a in range(4): \\r\\n for i in range(2,-1,-1): \\r\\n for j in range(4): \\r\\n if grid[i+1][j]==0: \\r\\n grid[i+1][j]=grid[i][j] \\r\\n grid[i][j]=0\",\n \"def select_walls(matrix, xaxis, yaxis, zaxis):\\n clear()\\n print(\\\"Now we're going to construct the interior of the rooms.\\\")\\n print(\\\"I'm going to present you with all rooms that have been selected.\\\")\\n print(\\\"I want you to indicate where the walls should be placed in each room.\\\")\\n print(\\\"Just like room selection, you will indicate, by a list of numbers,\\\")\\n print(\\\"where the walls should be placed.\\\")\\n print()\\n print(\\\"In locations where a room is adjacent to a void space, a non-optional\\\")\\n print(\\\"will automatically be inserted. Later some of these can be removed\\\")\\n print(\\\"to create vertical trasversals, but for now, just consider each\\\")\\n print(\\\"floor individually.\\\")\",\n \"def panel_callback():\\n if self.minwidth is None:\\n self.minwidth = self.button_stack.winfo_width()\\n\\n if self.current_panel:\\n self.sashpos = self.paned.sashpos(0)\\n self.current_panel.forget()\\n if isinstance(self.current_panel, class_obj):\\n self.current_panel = None\\n self.paned.sashpos(0, self.minwidth)\\n return\\n\\n if class_obj.__name__ in self.panels:\\n panel = self.panels[class_name]\\n else:\\n panel = self.panels[class_name] = class_obj(self, self.app)\\n\\n panel.pack(side=tk.LEFT, expand=1, fill=tk.BOTH)\\n\\n if self.sashpos is None:\\n self.sashpos = 300\\n\\n self.paned.sashpos(0, self.sashpos)\\n\\n self.current_panel = panel\",\n \"def generate_children(self, current_state):\\n # Define a list of the possible moves that this current state can make\\n list_of_possible_moves = []\\n\\n # Find the index of the '0' tile\\n index = current_state.index('0')\\n\\n # Check all the possible moves and see which are possible for this current state\\n move_up_copy = current_state.copy()\\n result = self.move_up(move_up_copy)\\n if result[0] > 0:\\n list_of_possible_moves.append((move_up_copy, self.cost_of_move_up, 'move_up', result[1]))\\n\\n move_down_copy = current_state.copy()\\n result = self.move_down(move_down_copy)\\n if result[0] > 0:\\n list_of_possible_moves.append((move_down_copy, self.cost_of_move_down, 'move_down', result[1]))\\n\\n move_left_copy = current_state.copy()\\n result = self.move_left(move_left_copy)\\n if result[0] > 0:\\n list_of_possible_moves.append((move_left_copy, self.cost_of_move_left, 'move_left', result[1]))\\n\\n move_right_copy = current_state.copy()\\n result = self.move_right(move_right_copy)\\n if result[0] > 0:\\n list_of_possible_moves.append((move_right_copy, self.cost_of_move_right, 'move_right', result[1]))\\n\\n # Two possible moves can be done if the wrap is allowed\\n if self.can_move_wrap(index):\\n # The regular (horizontal) wrap\\n regular_wrap_copy = current_state.copy()\\n result = self.wrap(regular_wrap_copy)\\n if result[0] > 0:\\n list_of_possible_moves.append((regular_wrap_copy, self.cost_of_wrap_move, 'wrap', result[1]))\\n\\n # The scaled-up (vertical) wrap\\n scaled_wrap_copy = current_state.copy()\\n result = self.wrap_scale(scaled_wrap_copy)\\n if result[0] > 0:\\n list_of_possible_moves.append((scaled_wrap_copy, self.cost_of_wrap_move, 'wrap_scale', result[1]))\\n # end: if\\n\\n # Two possible moves can be done if the diagonal action is allowed\\n if self.can_move_diagonally(index):\\n # The diagonal adjacent:\\n diagonal_adjacent_copy = current_state.copy()\\n result = self.diagonal_adjacent(diagonal_adjacent_copy)\\n list_of_possible_moves.append(\\n (diagonal_adjacent_copy, self.cost_of_diagonal_adjacent, 'diagonal_adjacent', result[1]))\\n\\n # The diagonal across:\\n diagonal_across_copy = current_state.copy()\\n result = self.diagonal_across(diagonal_across_copy)\\n list_of_possible_moves.append(\\n (diagonal_across_copy, self.cost_of_diagonal_across, 'diagonal_across', result[1]))\\n # end: if\\n\\n # Return the list of possible moves\\n return list_of_possible_moves\",\n \"def last_pg_results(self, graham_picks, lynch_picks, *args):\\n crrnt_pg, container, parent = args\\n\\n frame = PageEleven(self.container, parent, graham_picks, lynch_picks)\\n self.frames[PageEleven] = frame\\n frame.grid(row=0, column=0, sticky=\\\"nsew\\\")\\n frame.tkraise()\",\n \"def marathon(self):\\n self.buttons = []\\n self.screen.blit(self.background_image, (0, 0))\\n button_height = 200\\n button_width = 200\\n row_height = self.height // 2 - button_height\\n row_starting_width = self.width // 10\\n # First line of buttons\\n for i in range(5):\\n self.create_button((row_starting_width * (3 + (i - 1) * 2) - 100, row_height),\\n button_width,\\n button_height,\\n Colors.BLACK,\\n str(i))\\n # Second line of buttons\\n row_height = row_height + button_height + 100\\n for i in range(5):\\n self.create_button((row_starting_width * (3 + (i - 1) * 2) - 100, row_height),\\n button_width,\\n button_height,\\n Colors.BLACK,\\n str(i + 5))\\n self.show_buttons()\\n self.show_text_in_buttons()\\n pygame.display.flip()\",\n \"def init(self, windowsize:tuple):\\r\\n y_count, x_count = 3, 0 #< Set the starting counter for the look_up_table. y starts with three because the first three lines are just Nones\\r\\n # Creating the constant maze \\r\\n maze_size = windowsize[0], windowsize[1] - 2 * self.grid_size\\r\\n self.maze = pg.Surface(maze_size) \\r\\n \\r\\n \\r\\n \\r\\n # Draw the outermost rectangles on self.maze\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((0, 3 * self.grid_size), (28 * self.grid_size, 31 * self.grid_size)), 4)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((0 + self.grid_size // 2, 3 * self.grid_size + self.grid_size // 2),(27 * self.grid_size, 30 * self.grid_size)), 4) \\r\\n # Draw the inner rectangles\\r\\n for y in self.look_up_table[3 : -2]: #< y is a list of one row from the maze\\r\\n for x in y: #< x is a string that is decoded as already explained\\r\\n pos = [self.grid_size * x_count, self.grid_size * y_count]\\r\\n # Set reference position in the middle of one square\\r\\n pos[0] += self.grid_size // 2\\r\\n pos[1] += self.grid_size // 2\\r\\n x_count += 1\\r\\n # Check if x is rectangle\\r\\n if x != None and x[0] == 'r':\\r\\n # When the size of the string is equal or greater than 4 it's rectangle with a specific size and not just a border.\\r\\n if len(x) >= 4:\\r\\n # get the x and y size of the rectangle. x will be something like 'rx1_y1' x1 resprestens the size in x direction and y1 in y direction.\\r\\n xy_dim = x[1:].split(\\\"_\\\") \\r\\n xy_dim[0] = int(xy_dim[0])\\r\\n xy_dim[1] = int(xy_dim[1])\\r\\n rect = tuple(pos), (xy_dim[0] * self.grid_size , xy_dim[1] * self.grid_size )\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], rect, self.width)\\r\\n # If the last char is a w (white), u (up) or l (left) a line gets draw one a specific position \\r\\n if x[-1] == 'w':\\r\\n self.draw_line(self.maze, 'u', (x_count,y_count), True)\\r\\n if x[-1] == 'u' or x[-1] == 'l':\\r\\n if x_count == 0:\\r\\n self.draw_line(self.maze, x[-1], (len(y), y_count))\\r\\n else:\\r\\n self.draw_line(self.maze, x[-1], (x_count, y_count))\\r\\n \\r\\n y_count += 1\\r\\n x_count = 0\\r\\n # Just some cosmetic drawing\\r\\n pg.draw.rect(self.maze, Colors.colors['BLACK'], ((0, 12 * self.grid_size + self.grid_size // 2 + 4), (self.grid_size // 2 + 1, 10 * self.grid_size - 4)), 4)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLACK'], ((28 * self.grid_size - self.grid_size // 2 - 1, 12 * self.grid_size + self.grid_size // 2 + 4), (self.grid_size // 2 + 1, 10 * self.grid_size - 4)), 4)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((-self.width, 13 * self.grid_size), (5 * self.grid_size, 3 * self.grid_size)), self.width)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((-self.width, 19 * self.grid_size), (5 * self.grid_size, 3 * self.grid_size)), self.width)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((23 * self.grid_size, 13 * self.grid_size), (5 * self.grid_size + 10, 3 * self.grid_size)), self.width)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((23 * self.grid_size, 19 * self.grid_size), (5 * self.grid_size + 10, 3 * self.grid_size)), self.width)\\r\\n pg.draw.rect(self.maze, Colors.colors['BLUE'], ((11 * self.grid_size, 16 * self.grid_size), (6 * self.grid_size, 3 * self.grid_size)), self.width)\\r\\n \\r\\n pg.draw.line(self.maze, Colors.colors['BLUE'], (0, 16 * self.grid_size + self.grid_size // 2 - 1), (self.grid_size // 2 + self.width, 16 * self.grid_size + self.grid_size // 2 - 1), self.width)\\r\\n pg.draw.line(self.maze, Colors.colors['BLUE'], (0, 18 * self.grid_size + self.grid_size // 2), (self.grid_size // 2 + self.width, 18 * self.grid_size + self.grid_size // 2), self.width)\\r\\n pg.draw.line(self.maze, Colors.colors['BLUE'], (self.grid_size * 28 - self.grid_size, 16 * self.grid_size + self.grid_size // 2 - 1), (self.grid_size * 28 + self.width, 16 * self.grid_size + self.grid_size // 2 - 1), self.width)\\r\\n pg.draw.line(self.maze, Colors.colors['BLUE'], (self.grid_size * 28 - self.grid_size, 18 * self.grid_size + self.grid_size // 2), (self.grid_size * 28 + self.width, 18 * self.grid_size + self.grid_size // 2), self.width)\\r\\n self.is_init = True\",\n \"def startPresentation(ntrials):\\n\\n for trialIdx in range(ntrials):\\n\\n # draw the fixcross followed by the star\\n drawFixCross(1.0)\\n drawStar(4.0)\",\n \"def reshape(self, bottom, top):\\r\\n pass\",\n \"def main():\\n LayoutsWithPanels().mainloop()\",\n \"def LoadPerspective(self, layout, update=True):\\r\\n\\r\\n input = layout\\r\\n\\r\\n # check layout string version\\r\\n # 'layout1' = wxAUI 0.9.0 - wxAUI 0.9.2\\r\\n # 'layout2' = wxAUI 0.9.2 (wxWidgets 2.8)\\r\\n index = input.find(\\\"|\\\")\\r\\n part = input[0:index].strip()\\r\\n input = input[index+1:]\\r\\n \\r\\n if part != \\\"layout2\\\":\\r\\n return False\\r\\n\\r\\n # mark all panes currently managed as docked and hidden\\r\\n for pane in self._panes:\\r\\n pane.Dock().Hide()\\r\\n\\r\\n # clear out the dock array; this will be reconstructed\\r\\n self._docks = []\\r\\n\\r\\n # replace escaped characters so we can\\r\\n # split up the string easily\\r\\n input = input.replace(\\\"\\\\\\\\|\\\", \\\"\\\\a\\\")\\r\\n input = input.replace(\\\"\\\\\\\\;\\\", \\\"\\\\b\\\")\\r\\n\\r\\n while 1:\\r\\n\\r\\n pane = AuiPaneInfo()\\r\\n index = input.find(\\\"|\\\")\\r\\n pane_part = input[0:index].strip()\\r\\n input = input[index+1:]\\r\\n\\r\\n # if the string is empty, we're done parsing\\r\\n if pane_part == \\\"\\\":\\r\\n break\\r\\n\\r\\n if pane_part[0:9] == \\\"dock_size\\\":\\r\\n index = pane_part.find(\\\"=\\\")\\r\\n val_name = pane_part[0:index]\\r\\n value = pane_part[index+1:]\\r\\n\\r\\n index = val_name.find(\\\"(\\\")\\r\\n piece = val_name[index+1:]\\r\\n index = piece.find(\\\")\\\")\\r\\n piece = piece[0:index]\\r\\n\\r\\n vals = piece.split(\\\",\\\")\\r\\n dir = int(vals[0])\\r\\n layer = int(vals[1])\\r\\n row = int(vals[2])\\r\\n size = int(value)\\r\\n \\r\\n dock = AuiDockInfo()\\r\\n dock.dock_direction = dir\\r\\n dock.dock_layer = layer\\r\\n dock.dock_row = row\\r\\n dock.size = size\\r\\n self._docks.append(dock)\\r\\n \\r\\n continue\\r\\n\\r\\n # Undo our escaping as LoadPaneInfo needs to take an unescaped\\r\\n # name so it can be called by external callers\\r\\n pane_part = pane_part.replace(\\\"\\\\a\\\", \\\"|\\\")\\r\\n pane_part = pane_part.replace(\\\"\\\\b\\\", \\\";\\\")\\r\\n\\r\\n pane = self.LoadPaneInfo(pane_part, pane)\\r\\n\\r\\n p = self.GetPane(pane.name)\\r\\n \\r\\n if not p.IsOk():\\r\\n if pane.IsNotebookControl():\\r\\n # notebook controls - auto add...\\r\\n self._panes.append(pane)\\r\\n indx = self._panes.index(pane)\\r\\n else:\\r\\n # the pane window couldn't be found\\r\\n # in the existing layout -- skip it\\r\\n continue\\r\\n\\r\\n else:\\r\\n indx = self._panes.index(p)\\r\\n pane.window = p.window\\r\\n pane.frame = p.frame\\r\\n pane.buttons = p.buttons\\r\\n self._panes[indx] = pane\\r\\n\\r\\n if isinstance(pane.window, auibar.AuiToolBar) and (pane.IsFloatable() or pane.IsDockable()):\\r\\n pane.window.SetGripperVisible(True)\\r\\n \\r\\n if update:\\r\\n self.Update()\\r\\n\\r\\n return True\",\n \"def elements_page(self):\\n self.list_frame = tk.Frame(self.page)\\n self.data_frame = tk.Frame(self.page)\\n p2_label_2 = ttk.Label(self.page, text=self.lang.VP_CON_DDBB, font=FONT_BENVINGUDA)\\n p2_button_1 = ttk.Button(self.page, text=self.lang.BACK, command=self.tornar_main)\\n self.crear_elements_viewer()\\n self.page.grid(row=0, column=0, sticky=\\\"NESW\\\")\\n p2_label_2.pack(pady=20)\\n p2_button_1.pack(pady=0, ipadx=15)\\n self.list_frame.pack()\\n self.data_frame.pack()\\n self.p2_frame_list.pack(pady=15, padx=5, expand=False, side=tk.LEFT)\\n self.evo_frame.pack(pady=15, padx=5, expand=False, side=tk.RIGHT)\\n self.p2_frame_list_2.pack(pady=15, padx=5, expand=False, side=tk.RIGHT)\\n self.p2_frame_list_1.pack(pady=15, padx=5, expand=False, side=tk.RIGHT)\\n self.p2_frame_elements.pack(pady=0, padx=10, side=tk.LEFT)\\n self.p2_frame_img.grid(row=1, column=1, pady=5, padx=20, sticky=\\\"w\\\")\\n self.p2_frame_metadata.grid(row=1, column=2, pady=20, padx=20, sticky=\\\"w\\\")\",\n \"def UnsplitDClick(self, part, sash_size, pos):\\r\\n\\r\\n if not self._sash_dclick_unsplit:\\r\\n # Unsplit not allowed\\r\\n return\\r\\n\\r\\n pos1 = wx.Point(*pos)\\r\\n pos2 = wx.Point(*pos)\\r\\n if part.orientation == wx.HORIZONTAL:\\r\\n pos1.y -= 2*sash_size\\r\\n pos2.y += 2*sash_size + self.GetTabCtrlHeight()\\r\\n elif part.orientation == wx.VERTICAL:\\r\\n pos1.x -= 2*sash_size\\r\\n pos2.x += 2*sash_size\\r\\n else:\\r\\n raise Exception(\\\"Invalid UI part orientation\\\")\\r\\n\\r\\n pos1, pos2 = self.ClientToScreen(pos1), self.ClientToScreen(pos2)\\r\\n win1, win2 = wx.FindWindowAtPoint(pos1), wx.FindWindowAtPoint(pos2)\\r\\n\\r\\n if isinstance(win1, wx.ScrollBar):\\r\\n # Hopefully it will work\\r\\n pos1 = wx.Point(*pos)\\r\\n shift = wx.SystemSettings.GetMetric(wx.SYS_VSCROLL_X) + 2*(sash_size+1)\\r\\n if part.orientation == wx.HORIZONTAL:\\r\\n pos1.y -= shift\\r\\n else:\\r\\n pos1.x -= shift\\r\\n \\r\\n pos1 = self.ClientToScreen(pos1)\\r\\n win1 = wx.FindWindowAtPoint(pos1)\\r\\n\\r\\n if isinstance(win2, wx.ScrollBar):\\r\\n pos2 = wx.Point(*pos)\\r\\n shift = wx.SystemSettings.GetMetric(wx.SYS_VSCROLL_X) + 2*(sash_size+1)\\r\\n if part.orientation == wx.HORIZONTAL:\\r\\n pos2.y += shift\\r\\n else:\\r\\n pos2.x += shift\\r\\n\\r\\n pos2 = self.ClientToScreen(pos2)\\r\\n win2 = wx.FindWindowAtPoint(pos2)\\r\\n\\r\\n if not win1 or not win2:\\r\\n # How did we get here?\\r\\n return\\r\\n\\r\\n if isinstance(win1, AuiNotebook) or isinstance(win2, AuiNotebook):\\r\\n # This is a bug on MSW, for disabled pages wx.FindWindowAtPoint\\r\\n # returns the wrong window.\\r\\n # See http://trac.wxwidgets.org/ticket/2942\\r\\n return\\r\\n\\r\\n tab_frame1, tab_frame2 = self.GetTabFrameFromWindow(win1), self.GetTabFrameFromWindow(win2)\\r\\n\\r\\n if not tab_frame1 or not tab_frame2:\\r\\n return\\r\\n\\r\\n tab_ctrl_1, tab_ctrl_2 = tab_frame1._tabs, tab_frame2._tabs\\r\\n\\r\\n if tab_ctrl_1.GetPageCount() > tab_ctrl_2.GetPageCount():\\r\\n src_tabs = tab_ctrl_2\\r\\n dest_tabs = tab_ctrl_1\\r\\n else:\\r\\n src_tabs = tab_ctrl_1\\r\\n dest_tabs = tab_ctrl_2\\r\\n\\r\\n selection = -1\\r\\n page_count = dest_tabs.GetPageCount()\\r\\n \\r\\n for page in xrange(src_tabs.GetPageCount()-1, -1, -1):\\r\\n # remove the page from the source tabs\\r\\n page_info = src_tabs.GetPage(page)\\r\\n if page_info.active:\\r\\n selection = page_count + page\\r\\n src_tabs.RemovePage(page_info.window)\\r\\n\\r\\n # add the page to the destination tabs\\r\\n dest_tabs.AddPage(page_info.window, page_info)\\r\\n if page_info.control:\\r\\n self.ReparentControl(page_info.control, dest_tabs)\\r\\n \\r\\n self.RemoveEmptyTabFrames()\\r\\n\\r\\n dest_tabs.DoShowHide()\\r\\n self.DoSizing()\\r\\n dest_tabs.Refresh()\\r\\n self._mgr.Update()\\r\\n if selection > 0:\\r\\n wx.CallAfter(dest_tabs.MakeTabVisible, selection, self)\",\n \"def on_btnHabita_clicked(self,widget):\\n try:\\n panelactual = variables.panel.get_current_page()\\n if panelactual != 2:\\n variables.panel.set_current_page(2)\\n else:\\n pass\\n except:\\n print(\\\"error botón habitacion barra herramientas\\\")\",\n \"def make_chf_panel(self) :\\n\\n chf_panel = JPanel()\\n chf_panel.setLayout(MigLayout('insets 0'))\\n\\n\\n chf_files_label = JLabel('Hemisegment cells')\\n chf_files_text = JTextArea(BobGui.archetype_to_str(self.exper.hseg_cell_files_cab().archetype))\\n\\n chf_panel.add(chf_files_label, 'growx, wrap')\\n chf_panel.add(chf_files_text, 'grow, wrap')\\n\\n\\n chf_files_label = JLabel('Hemisegment binary image files')\\n chf_files_text = JTextArea(BobGui.archetype_to_str(self.exper.hseg_bin_files_cab().archetype))\\n\\n chf_panel.add(chf_files_label, 'growx, wrap')\\n chf_panel.add(chf_files_text, 'grow, wrap')\\n\\n\\n chf_files_label = JLabel('Intensity Image Files')\\n # chf_files_text = JTextArea(BobGui.archetype_to_str(self.exper.hseg_intens_im_files_cab().archetype))\\n # print(self.exper.hseg_intens_im_files_cab().archetype)\\n\\n # chf_panel.add(chf_files_label, 'growx, wrap')\\n # chf_panel.add(chf_files_text, 'grow, wrap')\\n\\n\\n self.intens_im_boxes = []\\n intens_im_panel = JPanel()\\n intens_im_panel.setLayout(MigLayout('insets 0'))\\n for poss_im_file in self.exper.hseg_intens_im_files_cab().archetype:\\n self.intens_im_boxes.append(JCheckBox(poss_im_file))\\n intens_im_panel.add(self.intens_im_boxes[-1], 'wrap')\\n\\n\\n chf_panel.add(chf_files_label, 'growx, wrap')\\n chf_panel.add(intens_im_panel, 'grow, wrap')\\n\\n\\n mdf_create_button = JButton('Create meta_data file from default outline')\\n # mdf_create_button = JButton('<html>Create meta_data file<br>from default outline</html>')\\n mdf_create_button.addActionListener(ActionListenerFactory(self, self.mdf_create_al))\\n mdf_open_button = JButton('Open existing meta_data file')\\n mdf_open_button.addActionListener(ActionListenerFactory(self, self.mdf_open_al))\\n\\n # meta_data_file_buttton = JButton('Open/Create meta_data file')\\n # meta_data_file_buttton.addActionListener(ActionListenerFactory(self, self.meta_data_al))\\n\\n # chf_panel.add(meta_data_file_buttton)\\n chf_panel.add(mdf_create_button, 'wrap')\\n chf_panel.add(mdf_open_button, 'wrap')\\n chf_scroll_pane = JScrollPane()\\n chf_scroll_pane.getViewport().setView(chf_panel)\\n\\n return chf_scroll_pane\",\n \"def handle(self, event):\\n for panel in self.sub_panels:\\n panel.handle(event)\\n\\n # KEY EVENTS\\n if event.type == pg.KEYDOWN:\\n # moving across the map\\n if event.key == pg.K_d:\\n self.city_graphics.add_move_speed((-self.SCROLL_SPEED, 0))\\n elif event.key == pg.K_s:\\n self.city_graphics.add_move_speed((0, -self.SCROLL_SPEED))\\n elif event.key == pg.K_a:\\n self.city_graphics.add_move_speed((self.SCROLL_SPEED, 0))\\n elif event.key == pg.K_w:\\n self.city_graphics.add_move_speed((0, self.SCROLL_SPEED))\\n\\n if event.type == pg.KEYUP:\\n # moving across the map\\n if event.key == pg.K_d:\\n self.city_graphics.add_move_speed((self.SCROLL_SPEED, 0))\\n elif event.key == pg.K_s:\\n self.city_graphics.add_move_speed((0, self.SCROLL_SPEED))\\n elif event.key == pg.K_a:\\n self.city_graphics.add_move_speed((-self.SCROLL_SPEED, 0))\\n elif event.key == pg.K_w:\\n self.city_graphics.add_move_speed((0, -self.SCROLL_SPEED))\\n\\n # MOUSE EVENTS\\n for panel in self.sub_panels:\\n if panel.collide():\\n self.city_graphics.hovered(None, self.mode)\\n self.button_down = False\\n return\\n\\n # !!! only if mouse isn't above another panel !!!#\\n\\n if event.type == pg.MOUSEBUTTONUP:\\n if event.button == pg.BUTTON_LEFT:\\n self.button_down = False\\n\\n # zooming in\\n if event.button == 4:\\n self.city_graphics.zoom(self.ZOOM_VALUE)\\n\\n if event.type == pg.MOUSEBUTTONDOWN:\\n bought = False\\n self.menu_panel.option_panel.disable()\\n if self.warning_panel:\\n self.warning_panel.disable()\\n self.warning_panel = None\\n\\n if event.button == pg.BUTTON_LEFT:\\n self.button_down = True\\n if self.construct_to_buy:\\n clicked_lot = self.city_graphics.get_clicked_lot(\\n pg.mouse.get_pos())\\n if clicked_lot.set_construct(self.construct_to_buy):\\n self.simulator.integrate_construct(clicked_lot)\\n self.construct_to_buy = None\\n bought = True\\n\\n if self.mode == 'road_placing':\\n if event.button == pg.BUTTON_RIGHT:\\n self.city_space.road_system.hovered_direction *= -1\\n elif event.button == pg.BUTTON_LEFT:\\n self.city_space.road_clicked()\\n\\n elif not self.zoning:\\n if event.button == pg.BUTTON_LEFT:\\n self.city_graphics.select_lot(pg.mouse.get_pos())\\n if not self.bulldozing and not bought and self.mode != 'access_highlighting':\\n self.set_upgrade_panel()\\n\\n # zooming out\\n if event.button == 5:\\n self.city_graphics.zoom(1 / self.ZOOM_VALUE)\\n\\n if event.type == pg.MOUSEMOTION or event.type or event.type == pg.MOUSEBUTTONDOWN:\\n clicked_lot = self.city_graphics.get_clicked_lot(\\n pg.mouse.get_pos())\\n if self.button_down:\\n if self.zoning and self.simulator.can_buy(zone=self.zoning_type):\\n if clicked_lot and clicked_lot.set_zone(self.zoning_type):\\n self.simulator.integrate_construct(clicked_lot)\\n\\n elif self.bulldozing:\\n if clicked_lot and clicked_lot.remove_construct():\\n self.simulator.integrate_construct(\\n clicked_lot, remove=True)\\n\\n else:\\n self.city_graphics.hovered(\\n pg.mouse.get_pos(), self.mode)\",\n \"def ubicar_naves():\\n tablero.clear()\\n crear_tablero(tablero)\\n ubicar_portaviones()\\n ubicar_fragata()\\n ubicar_submarino()\",\n \"def next_widget(self):\\r\\n for i in self.widgets[1:]:\\r\\n if i.get_visible():\\r\\n self.set_top_widget(i)\\r\\n return\",\n \"def expand(self):\\n\\t\\tfor move in self.moves:\\n\\t\\t\\tm = self.Game.create_move(self.State, move.row, move.column, move.shift, False)\\n\\t\\t\\tchildstate = self.Game.apply_move(copy.deepcopy(self.State), m)\\n\\t\\t\\tchild = GameNode(self.Game, m, childstate, self.Game.get_moves(childstate), self)\\n\\t\\t\\tself.addChild(child)\",\n \"def setup_containers(self):\\r\\n self.container_widgets[\\\"main_frame\\\"].grid(row=0, column=0, sticky='news')\\r\\n self.container_widgets[\\\"panel_frame\\\"].grid(row=0, column=0)\\r\\n self.container_widgets[\\\"order_frame\\\"].grid(row=1, column=0, sticky='nw')\\r\\n self.container_widgets[\\\"order_frame\\\"].grid_rowconfigure(0, weight=5)\\r\\n self.container_widgets[\\\"order_frame\\\"].grid_columnconfigure(0, weight=5)\\r\\n self.container_widgets[\\\"order_canvas\\\"].grid(row=0, column=0, sticky='news')\\r\\n self.container_widgets[\\\"orders_container\\\"].grid(column=0, row=0)\",\n \"def separate_frontier(self):\\n\\t#print self.frontier\\n region = [] # a list of tuples\\n region_list = [] # a list of regions\\n in_list = False\\n region_size = 7\\n num_regions = 25\\n n = 0\\n h = 0\\n print \\\"separate frontier\\\"\\n while(region_size>0):\\n for i in range(len(self.frontier)):\\n if (h < num_regions):\\n region = []\\n self.find_region(self.frontier[i], region)\\n\\t\\t #rospy.loginfo(region)\\n in_list = region in region_list\\n if (len(region) > region_size) and (not in_list):\\n region_list.append(region)\\n h += 1\\n self.regions = region_list\\n region_size -= 1\\n\\t#print self.regions\",\n \"def _layout(self):\\n top = 2.0\\n y = 0.0\\n x = 0.0\\n maxend = 0.0\\n for track in self._tracks:\\n track.set_view(self.view.species, self.view.seqname, \\n self.view.start, self.view.end)\\n tracksize = track.get_size()\\n y -= tracksize[1]\\n track.set_pos(track.pos_offset[0] + x, track.pos_offset[1] + y)\\n self.size = [self.view.end - self.view.start + 1, 0 - y]\",\n \"def blank(self, index=-1):\\n self.displays[0].start() # call only once to support shift chain\\n if index < 0:\\n for d in self.displays:\\n d.blank()\\n else:\\n self.displays[index].blank()\\n self.displays[0].latch() # call only once to support shift chain\",\n \"def printBoard(self):\\n if self.side == self.WHITE or self.side == None:\\n for r in [8,7,6,5,4,3,2,1]:\\n for c in 'abcdefgh':\\n p = self.getPiece(c,r) # print a8 first\\n if p == None:\\n print \\\" \\\",\\n else:\\n print self.getPieceName(p.type),\\n print \\\"\\\"\\n else:\\n for r in [1,2,3,4,5,6,7,8]:\\n for c in 'hgfedcba':\\n p = self.getPiece(c,r) # print h1 first\\n if p == None:\\n print \\\" \\\",\\n else:\\n print self.getPieceName(p.type),\\n print \\\"\\\"\",\n \"def _generate_maze(self):\\n grid = [[GridCell(x, y, self._treasure_prob) for x in range(self._map_size)] for y in range(self._map_size)]\\n\\n center_x = self._map_size // 2\\n center_y = self._map_size // 2\\n\\n for _ in range(self._sparsity):\\n current = grid[center_x][center_y]\\n stack = list()\\n start = True\\n while len(stack) or start:\\n start = False\\n current.visited = True\\n children = current.has_children(grid)\\n\\n if children:\\n choice = np.random.choice(children)\\n choice.visited = True\\n\\n stack.append(current)\\n\\n self._remove_walls(current, choice)\\n\\n current = choice\\n\\n elif stack:\\n current = stack.pop()\\n for row in grid:\\n for cell in row:\\n cell.visited = False\\n\\n # edit center area\\n grid[center_x][center_y].set_treasury()\\n for x in range(center_x - 1, center_x + 2):\\n for y in range(center_y - 1, center_y + 2):\\n grid[x][y].erase_walls()\\n return grid\",\n \"def recreate_grid(self):\\n\\n self.print_numlist = arcade.SpriteList()\\n for row in range(ROW_COUNT):\\n for column in range(COLUMN_COUNT):\\n sprite = arcade.Sprite(\\n f\\\"Numbers/{self.grid[row][column]}.png\\\", scale=0.2\\n )\\n x = (MARGIN + WIDTH) * column + MARGIN + WIDTH // 2\\n y = (MARGIN + HEIGHT) * row + MARGIN + HEIGHT // 2\\n sprite.center_x = x\\n sprite.center_y = y\\n self.print_numlist.append(sprite)\\n # Check to see if all squares have been filled in\\n if 0 not in self.grid:\\n # if Cameron.Check_for_Completion(self.grid) == True:\\n self.done = True\",\n \"def move_to_position1(self):\",\n \"def traverse_scaffold(self):\\n\\n y, x, theta = self.find_start_pose()\\n dy, dx = -np.sin(theta), np.cos(theta)\\n straight, instruction_string = 0, ''\\n\\n while True:\\n # Either scaffold infront of us\\n if self.mp[y+dy,x+dx] == ord('#') or self.mp[y+dy,x+dx] == ord('O'):\\n self.mp[y,x] = ord('O')\\n straight += 1\\n y, x = y+dy, x+dx\\n # Otherwise, it is to our left or right\\n else:\\n if self.mp[y-1,x] == ord('#'): theta_ = np.pi/2\\n elif self.mp[y+1,x] == ord('#'): theta_ = -np.pi/2\\n elif self.mp[y,x-1] == ord('#'): theta_ = -np.pi\\n elif self.mp[y,x+1] == ord('#'): theta_ = 0\\n\\n # Reached the end\\n else:\\n self.mp[y,x] = ord('x')\\n if straight > 0:\\n instruction_string = instruction_string + str(straight)\\n\\n return instruction_string\\n\\n if straight > 0:\\n instruction_string = instruction_string + str(straight) + ','\\n straight = 0\\n\\n # Find angle between directions\\n d = np.arccos(np.dot([np.sin(theta+np.pi/2), np.cos(theta+np.pi/2)],\\n [np.sin(theta_), np.cos(theta_)]))\\n \\n if d == 0:\\n instruction_string += 'L,'\\n theta = theta+np.pi/2\\n else:\\n instruction_string += 'R,'\\n theta = theta-np.pi/2\\n # Update orientation\\n \\n dy,dx = np.int(-np.sin(theta)),np.int(np.cos(theta))\",\n \"def do_layout(self):\\n self.define_panel_structure()\\n self.layout_selection()\\n self.layout_data_list()\\n self.layout_batch()\\n self.layout_button()\",\n \"def _scroll_screen(direction: int) -> Callable:\\n def _inner(qtile: Qtile):\\n if len(qtile.screens) == 1:\\n current = qtile.groups.index(qtile.current_group)\\n destination = (current + direction) % 6\\n qtile.groups[destination].cmd_toscreen()\\n return\\n\\n current = qtile.groups.index(qtile.current_group)\\n if current < 3:\\n destination = (current + direction) % 3\\n else:\\n destination = ((current - 3 + direction) % 3) + 3\\n qtile.groups[destination].cmd_toscreen()\\n\\n return _inner\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6271615","0.54973686","0.5387132","0.5235147","0.52252686","0.5174454","0.5173184","0.5033678","0.5033185","0.5014299","0.5011081","0.50006324","0.49946687","0.49603772","0.49424213","0.49365565","0.49298054","0.49220905","0.49138784","0.48819068","0.48780358","0.48676798","0.48545146","0.48463354","0.48247865","0.479901","0.4793508","0.4776079","0.47662902","0.47634643","0.47601807","0.47596574","0.47485408","0.47469553","0.47364375","0.4735744","0.47314888","0.47236398","0.47233123","0.47205546","0.47099805","0.47052774","0.4701336","0.4698788","0.46962318","0.4696001","0.46937758","0.4691581","0.46889555","0.46882555","0.4686171","0.46844015","0.4681556","0.468129","0.46778926","0.4674712","0.46730116","0.4672449","0.46723145","0.46706703","0.4666411","0.4665887","0.46612012","0.46605858","0.46604016","0.46570215","0.465648","0.46521646","0.46458447","0.46241167","0.461886","0.46171474","0.461446","0.4612178","0.4610899","0.46100515","0.46092972","0.46054158","0.46040252","0.46017936","0.46006835","0.45979697","0.4595556","0.45920092","0.45895576","0.45884228","0.45757732","0.45731393","0.4571472","0.45710728","0.45661902","0.45655164","0.45630452","0.4559629","0.45578927","0.45493644","0.45457733","0.4544795","0.45405513","0.4539434"],"string":"[\n \"0.6271615\",\n \"0.54973686\",\n \"0.5387132\",\n \"0.5235147\",\n \"0.52252686\",\n \"0.5174454\",\n \"0.5173184\",\n \"0.5033678\",\n \"0.5033185\",\n \"0.5014299\",\n \"0.5011081\",\n \"0.50006324\",\n \"0.49946687\",\n \"0.49603772\",\n \"0.49424213\",\n \"0.49365565\",\n \"0.49298054\",\n \"0.49220905\",\n \"0.49138784\",\n \"0.48819068\",\n \"0.48780358\",\n \"0.48676798\",\n \"0.48545146\",\n \"0.48463354\",\n \"0.48247865\",\n \"0.479901\",\n \"0.4793508\",\n \"0.4776079\",\n \"0.47662902\",\n \"0.47634643\",\n \"0.47601807\",\n \"0.47596574\",\n \"0.47485408\",\n \"0.47469553\",\n \"0.47364375\",\n \"0.4735744\",\n \"0.47314888\",\n \"0.47236398\",\n \"0.47233123\",\n \"0.47205546\",\n \"0.47099805\",\n \"0.47052774\",\n \"0.4701336\",\n \"0.4698788\",\n \"0.46962318\",\n \"0.4696001\",\n \"0.46937758\",\n \"0.4691581\",\n \"0.46889555\",\n \"0.46882555\",\n \"0.4686171\",\n \"0.46844015\",\n \"0.4681556\",\n \"0.468129\",\n \"0.46778926\",\n \"0.4674712\",\n \"0.46730116\",\n \"0.4672449\",\n \"0.46723145\",\n \"0.46706703\",\n \"0.4666411\",\n \"0.4665887\",\n \"0.46612012\",\n \"0.46605858\",\n \"0.46604016\",\n \"0.46570215\",\n \"0.465648\",\n \"0.46521646\",\n \"0.46458447\",\n \"0.46241167\",\n \"0.461886\",\n \"0.46171474\",\n \"0.461446\",\n \"0.4612178\",\n \"0.4610899\",\n \"0.46100515\",\n \"0.46092972\",\n \"0.46054158\",\n \"0.46040252\",\n \"0.46017936\",\n \"0.46006835\",\n \"0.45979697\",\n \"0.4595556\",\n \"0.45920092\",\n \"0.45895576\",\n \"0.45884228\",\n \"0.45757732\",\n \"0.45731393\",\n \"0.4571472\",\n \"0.45710728\",\n \"0.45661902\",\n \"0.45655164\",\n \"0.45630452\",\n \"0.4559629\",\n \"0.45578927\",\n \"0.45493644\",\n \"0.45457733\",\n \"0.4544795\",\n \"0.45405513\",\n \"0.4539434\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.62816256"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88562,"cells":{"query":{"kind":"string","value":"Adds panel boundary transformations to the page"},"document":{"kind":"string","value":"def add_transforms(page):\n # Transform types\n\n # Allow choosing multiple\n transform_choice = [\"slice\", \"box\"]\n\n # Slicing panels into multiple panels\n # Works best with large panels\n if \"slice\" in transform_choice:\n page = single_slice_panels(page)\n\n # Makes v cuts happen more often 1/4 chance\n if np.random.random() < cfg.double_slice_chance:\n page = single_slice_panels(page)\n\n if \"box\" in transform_choice:\n\n if np.random.random() < cfg.box_transform_panel_chance:\n page = box_transform_panels(page)\n\n page = box_transform_page(page)\n\n return page"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_main_panel(self):\n self.panel = wx.Panel(self)\n\n self.init_plot()\n self.canvas = FigCanvas(self.panel, -1, self.fig)\n\n self.control_box = VSControlBox(self.panel, -1, 'Information board')\n\n self.vbox = wx.BoxSizer(wx.VERTICAL)\n self.vbox.Add(self.canvas, 1, wx.LEFT | wx.TOP | wx.GROW)\n self.vbox.Add(self.control_box, 0, wx.ALIGN_LEFT | wx.TOP | wx.EXPAND)\n \n self.panel.SetSizer(self.vbox)\n self.vbox.Fit(self)","def create(self):\n self.panel = pg.rect.Rect(self.position, self.dimensions)","def get_band_panel(self):\n return pn.Column(\n pn.Column(\n pn.Row(self.get_controls(), margin = (0, 0, -25, 0)),\n pn.pane.HoloViews(self.get_band_dmap(), linked_axes=False)\n ), \n )","def box_transform_panels(page, type_choice=None, pattern=None):\n\n if type_choice is None:\n type_choice_prob = np.random.random()\n if type_choice_prob < cfg.panel_box_trapezoid_ratio:\n type_choice = \"trapezoid\"\n else:\n type_choice = \"rhombus\"\n\n if type_choice == \"trapezoid\":\n if page.num_panels > 2:\n\n # Get parent panel which satisfies the criteria for the transform\n relevant_panels = find_parent_with_multiple_children(page, 3)\n\n if len(relevant_panels) > 0:\n if len(relevant_panels) > 1:\n num_panels = np.random.randint(1, len(relevant_panels))\n else:\n num_panels = 1\n\n # For each panel\n for idx in range(0, num_panels):\n panel = relevant_panels[idx]\n\n # Get the three child panels\n # Since panels are created in order\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n p3 = panel.get_child(2)\n\n min_width = math.inf\n min_height = math.inf\n\n # Get the smallest height and width\n for child in [p1, p2, p3]:\n\n if child.width < min_width:\n min_width = child.width\n\n if child.height < min_height:\n min_height = child.height\n\n # Choose trapezoid pattern\n if pattern is None:\n trapezoid_pattern = np.random.choice([\"A\", \"V\"])\n else:\n trapezoid_pattern = pattern\n\n movement_proportion = np.random.randint(\n 10,\n cfg.trapezoid_movement_limit)\n\n # If parent panel is horizontal the children are vertical\n if panel.orientation == \"h\":\n\n # Get how much the lines of the child panels move\n # on the x axis to make the trapezoid\n x_movement = min_width*(movement_proportion/100)\n\n # Make an A pattern horizontally\n if trapezoid_pattern == \"A\":\n\n # Get the coords of the first line to be moved\n line_one_top = (p1.x2y2[0] + x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] - x_movement,\n p1.x3y3[1])\n\n # Move line between child 1 and 2\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n # Get the coords of the second line to be moved\n line_two_top = (p2.x2y2[0] - x_movement,\n p2.x2y2[1])\n line_two_bottom = (p2.x3y3[0] + x_movement,\n p2.x3y3[1])\n\n # Move line two between child 2 and 3\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n\n # Make a V pattern horizontally\n else:\n\n # Get the coords of the first line to be moved\n line_one_top = (p1.x2y2[0] - x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] + x_movement,\n p1.x3y3[1])\n\n # Move line between child 1 and 2\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n # Get the coords of the second line to be moved\n line_two_top = (p2.x2y2[0] + x_movement,\n p2.x2y2[1])\n\n line_two_bottom = (p2.x3y3[0] - x_movement,\n p2.x3y3[1])\n\n # Move line two between child 2 and 3\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n\n # If panel is vertical children are horizontal\n # so the A and the V are at 90 degrees to the page\n else:\n # Get how much the lines of the child panels move\n # on the y axis to make the trapezoid\n y_movement = min_height*(movement_proportion/100)\n\n # Make an A pattern vertically\n if trapezoid_pattern == \"A\":\n\n # Get the coords of the first line to be moved\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] + y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] - y_movement)\n\n # Move line between child 1 and 2\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n\n # Get the coords of the second line to be moved\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] - y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] + y_movement)\n\n # Move line two between child 2 and 3\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n # Make a V pattern vertically\n else:\n\n # Get the coords of the first line to be moved\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] - y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] + y_movement)\n\n # Move line between child 1 and 2\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n # Get the coords of the second line to be moved\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] + y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] - y_movement)\n\n # Move line two between child 2 and 3\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n\n elif type_choice == \"rhombus\":\n\n if page.num_panels > 1:\n\n # Get parent panel which satisfies the criteria for the transform\n relevant_panels = find_parent_with_multiple_children(page, 3)\n\n if len(relevant_panels) > 0:\n\n if len(relevant_panels) > 1:\n num_panels = np.random.randint(1, len(relevant_panels))\n else:\n num_panels = 1\n\n for idx in range(0, num_panels):\n\n panel = relevant_panels[idx]\n\n # Since panels are created in order\n p1 = panel.get_child(0)\n p2 = panel.get_child(1)\n p3 = panel.get_child(2)\n\n min_width = math.inf\n min_height = math.inf\n\n # Get the smallest height and width\n for child in [p1, p2, p3]:\n\n if child.width < min_width:\n min_width = child.width\n\n if child.height < min_height:\n min_height = child.height\n\n if pattern is None:\n rhombus_pattern = np.random.choice([\"left\", \"right\"])\n else:\n rhombus_pattern = pattern\n\n movement_proportion = np.random.randint(\n 10,\n cfg.rhombus_movement_limit\n )\n\n # Logic for the section below is the same as the\n # trapezoid with the exception of the fact that the\n # rhombus pattern happens to move both lines in the\n # same direction\n\n if panel.orientation == \"h\":\n\n x_movement = min_width*(movement_proportion/100)\n\n if rhombus_pattern == \"left\":\n line_one_top = (p1.x2y2[0] - x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] + x_movement,\n p1.x3y3[1])\n\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n line_two_top = (p2.x2y2[0] - x_movement,\n p2.x2y2[1])\n\n line_two_bottom = (p2.x3y3[0] + x_movement,\n p2.x3y3[1])\n\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n\n else:\n\n line_one_top = (p1.x2y2[0] + x_movement,\n p1.x2y2[1])\n\n line_one_bottom = (p1.x3y3[0] - x_movement,\n p1.x3y3[1])\n\n p1.x2y2 = line_one_top\n p1.x3y3 = line_one_bottom\n\n p1.refresh_coords()\n\n p2.x1y1 = line_one_top\n p2.x4y4 = line_one_bottom\n\n line_two_top = (p2.x2y2[0] + x_movement,\n p2.x2y2[1])\n\n line_two_bottom = (p2.x3y3[0] - x_movement,\n p2.x3y3[1])\n\n p2.x2y2 = line_two_top\n p2.x3y3 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_top\n p3.x4y4 = line_two_bottom\n\n p3.refresh_coords()\n else:\n y_movement = min_height*(movement_proportion/100)\n\n if rhombus_pattern == \"right\":\n\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] + y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] - y_movement)\n\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] + y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] - y_movement)\n\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n else:\n\n line_one_top = (p2.x2y2[0],\n p2.x2y2[1] - y_movement)\n\n line_one_bottom = (p2.x1y1[0],\n p2.x1y1[1] + y_movement)\n\n p2.x2y2 = line_one_top\n p2.x1y1 = line_one_bottom\n\n p1.x3y3 = line_one_top\n p1.x4y4 = line_one_bottom\n\n p1.refresh_coords()\n\n line_two_top = (p2.x3y3[0],\n p2.x3y3[1] - y_movement)\n\n line_two_bottom = (p2.x4y4[0],\n p2.x4y4[1] + y_movement)\n\n p2.x3y3 = line_two_top\n p2.x4y4 = line_two_bottom\n\n p2.refresh_coords()\n\n p3.x1y1 = line_two_bottom\n p3.x2y2 = line_two_top\n\n p3.refresh_coords()\n\n return page","def get_controls(self):\n return pn.Column(\n pn.Column(\n pn.Row(super().get_controls(), margin = (0, 0, -25, 0)),\n pn.pane.HoloViews(self.get_band_dmap(), linked_axes=False)\n ), \n )","def __call__(self, axes, renderer):\n bbox0 = self.get_original_position(axes, renderer)\n bbox = bbox0\n\n x1, y1, w, h = bbox.bounds\n extesion_fraction = self.extesion_fraction\n dw, dh = w*extesion_fraction, h*extesion_fraction\n\n if self.extend in [\"min\", \"both\"]:\n if self.orientation == \"horizontal\":\n x1 = x1 + dw\n else:\n y1 = y1+dh\n\n if self.extend in [\"max\", \"both\"]:\n if self.orientation == \"horizontal\":\n w = w-2*dw\n else:\n h = h-2*dh\n\n return Bbox.from_bounds(x1, y1, w, h)","def _create_barplot_pane(self):\n \n panel = wx.Panel(self, -1)\n\t\t\n self.figb = Figure()\n self.axb = self.figb.add_subplot(111)\n\t\t\n self.axb.set_xlabel(\"Isodoses\", fontsize=14, fontweight = 'semibold') #fontsize=24\n self.axb.set_ylabel(\"Probability\", fontsize = 14, fontweight = 'semibold')\n self.axb.set_xlim(68, 93)\n self.axb.set_ylim(0, 1)\n\t\t\n self.canvasb = FigureCanvas(panel, -1, self.figb)\n self.toolbarb = NavigationToolbar(self.canvasb)\n\t\t\n vbox = wx.BoxSizer(wx.VERTICAL)\n vbox.Add(self.canvasb, 1, wx.EXPAND|wx.BOTTOM, 7)\n vbox.Add(self.toolbarb, 0, wx.EXPAND)\n\t\t\n panel.SetSizer(vbox)\n vbox.Fit(panel)\n\t\t\n return panel","def add_boundaries_page(wiz):\n page = wiz.add_page(u\"Boundaries conditions\", BoundariesPage())\n page.register(\"group-boundaries*\", None)","def panel_callback():\n if self.minwidth is None:\n self.minwidth = self.button_stack.winfo_width()\n\n if self.current_panel:\n self.sashpos = self.paned.sashpos(0)\n self.current_panel.forget()\n if isinstance(self.current_panel, class_obj):\n self.current_panel = None\n self.paned.sashpos(0, self.minwidth)\n return\n\n if class_obj.__name__ in self.panels:\n panel = self.panels[class_name]\n else:\n panel = self.panels[class_name] = class_obj(self, self.app)\n\n panel.pack(side=tk.LEFT, expand=1, fill=tk.BOTH)\n\n if self.sashpos is None:\n self.sashpos = 300\n\n self.paned.sashpos(0, self.sashpos)\n\n self.current_panel = panel","def apply_transforms(self):\n self.axes.set_xlim(self._curr_xlim)\n self.axes.set_ylim(self._curr_ylim)","def boxen(self, paneel):\n \n boxje = wx.BoxSizer(wx.VERTICAL)\n boxje.Add(paneel, 1, wx.EXPAND | wx.ALL)\n \n #boxje.Add(vbox, 8, wx.EXPAND | wx.ALL)\n return boxje","def set_base_transforms(self):\n self._curr_xlim = self.axes.get_xlim()\n self._curr_ylim = self.axes.get_ylim()","def _create_3D_pane(self):\n\t\t\n panel = wx.Panel(self,-1)\n self.interactor3d = wxVTKRenderWindowInteractor(panel, -1, (600,800))\n self.generate_button = wx.Button(panel, label=\"Generate 3D view\")\n self.text_position = wx.StaticText(panel, -1, \"Dose (Gy) \" , wx.Point(0, 0))\n self.slider_dose3d = wx.Slider(panel, -1, 75, 60, 100, wx.DefaultPosition, wx.Size( 100,-1 ), wx.SL_HORIZONTAL)\n self.spin_dose3d = wx.SpinCtrl(panel, wx.ID_ANY, str(self.slider_dose3d.GetValue()), wx.DefaultPosition, wx.Size( 70,-1 ), wx.SP_ARROW_KEYS, min=0, max=100, initial=11)\t\n\t\t\n button_sizer = wx.BoxSizer(wx.HORIZONTAL)\n button_sizer.AddSpacer(30)\n button_sizer.Add(self.generate_button)\n button_sizer.AddSpacer(30)\n button_sizer.Add(self.text_position)\n button_sizer.Add(self.slider_dose3d)\n button_sizer.Add(self.spin_dose3d)\n\t\t\n listsizer = wx.BoxSizer(wx.VERTICAL)\n listsizer.Add(self.interactor3d, 1, wx.EXPAND|wx.BOTTOM, 7)\n listsizer.Add(button_sizer)\n panel.SetSizer(listsizer)\n listsizer.Fit(panel)\n\t\t\n self._create_orientation_widget(self.interactor3d)\n return panel","def box_transform_page(page, direction_list=[]):\n\n if len(page.children) > 1:\n\n # For all children of the page\n for idx in range(0, len(page.children)-1):\n\n # Take two children at a time\n p1 = page.get_child(idx)\n p2 = page.get_child(idx+1)\n\n change_proportion = np.random.randint(\n 10,\n cfg.full_page_movement_proportion_limit\n )\n\n change_proportion /= 100\n\n # Randomly move the line between them up or down one side\n if len(direction_list) < 1:\n direction = np.random.choice([\"rup\", \"lup\"])\n else:\n direction = direction_list[idx]\n\n # If the first panel is horizontal therefore the second is too\n if p1.orientation == \"h\":\n\n # Get the maximum amount the line can move\n change_max = min([(p1.x4y4[1] - p1.x1y1[1]),\n (p2.x4y4[1] - p2.x1y1[1])])\n\n change = change_max*change_proportion\n\n # Specify the line to move\n line_top = p2.x1y1\n line_bottom = p2.x2y2\n\n # If the panel has children then recursively\n # find the leaf children and move them to the new line\n if len(p1.children) > 0:\n move_children_to_line(p1,\n (line_top, line_bottom),\n change,\n \"h\",\n direction\n )\n\n # Otherwise move the current panels to line\n else:\n if direction == \"rup\":\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] + change)\n p1.refresh_coords()\n else:\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] - change)\n p1.refresh_coords()\n\n if len(p2.children) > 0:\n move_children_to_line(p2,\n (line_top, line_bottom),\n change,\n \"h\",\n direction\n )\n else:\n if direction == \"rup\":\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] + change)\n p2.refresh_coords()\n else:\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] - change)\n p2.refresh_coords()\n\n # If the first panel is vertical therefore the second\n # is too since they are siblings\n else:\n # Get the maximum amount the line can move\n change_max = min([(p1.x2y2[0] - p1.x1y1[0]),\n (p2.x2y2[0] - p2.x1y1[0])])\n\n change = change_max*change_proportion\n\n # Specify the line to move\n line_top = p2.x1y1\n line_bottom = p2.x4y4\n\n # If the panel has children then recursively\n # find the leaf children and move them to the new line\n if len(p1.children) > 0:\n move_children_to_line(p1,\n (line_top, line_bottom),\n change,\n \"v\",\n direction\n )\n\n # Otherwise just move the panel since it's a leaf\n else:\n if direction == \"rup\":\n p1.x2y2 = (p1.x2y2[0] - change, p1.x2y2[1])\n else:\n p1.x2y2 = (p1.x2y2[0] + change, p1.x2y2[1])\n\n if len(p2.children) > 0:\n move_children_to_line(p2,\n (line_top, line_bottom),\n change,\n \"v\",\n direction\n )\n else:\n if direction == \"rup\":\n p2.x1y1 = (p2.x1y1[0] - change, p2.x1y1[1])\n else:\n p2.x1y1 = (p2.x1y1[0] + change, p2.x1y1[1])\n\n return page","def _buidUISizer(self):\n flagsR = wx.RIGHT | wx.ALIGN_CENTER_VERTICAL\n mSizer = wx.BoxSizer(wx.HORIZONTAL)\n mSizer.AddSpacer(5)\n gv.iMapPanel = self.mapPanel = gp.PanelMap(self)\n mSizer.Add(self.mapPanel, flag=flagsR, border=2)\n mSizer.AddSpacer(5)\n mSizer.Add(wx.StaticLine(self, wx.ID_ANY, size=(-1, 560),\n style=wx.LI_VERTICAL), flag=flagsR, border=2)\n mSizer.AddSpacer(5)\n gv.iCtrlPanel = gp.PanelCtrl(self)\n mSizer.Add(gv.iCtrlPanel)\n return mSizer","def _addPanes(self):\n\n self._addPaneMapWindow()\n self._addPaneToolbar(name = 'digitMap')","def paint_mini_axes(self):\n w, h = self.width(), self.height()\n vt = self.getTranslation() # this is in eye coordinates\n GL.glViewport(0, 0, w//8, h//8) # mini viewport at bottom left of widget\n self.setTranslation((0, 0, -3)) # draw in center of this mini viewport\n self.paint_axes()\n self.setTranslation(vt) # restore translation vector to MV matrix\n GL.glViewport(0, 0, w, h) # restore full viewport","def paint_mini_axes(self):\n w, h = self.width(), self.height()\n vt = self.getTranslation() # this is in eye coordinates\n GL.glViewport(0, 0, w//8, h//8) # mini viewport at bottom left of widget\n self.setTranslation((0, 0, -3)) # draw in center of this mini viewport\n self.paint_axes()\n self.setTranslation(vt) # restore translation vector to MV matrix\n GL.glViewport(0, 0, w, h) # restore full viewport","def create_mplframe(self):\r\n #create figure and axes objects\r\n self.fig = Figure()\r\n self.subplot = self.fig.add_subplot(111)\r\n #disable axis, because it will only show an image\r\n self.subplot.get_yaxis().set_visible(False)\r\n self.subplot.get_xaxis().set_visible(False)\r\n \r\n #create canvas and toolbar\r\n self.canvas = FigureCanvas(self.fig)\r\n self.toolbar = MyNavigationToolbar(self.canvas, None)\r\n\r\n #add the canvas and toolbar to the gui\r\n self.ui.imageLayout.addWidget(self.canvas)\r\n self.ui.imageLayout.addWidget(self.toolbar)\r\n\r\n #connect the toolbar selection to matploblib as a callback\r\n self.canvas.mpl_connect('selection_changed',self.toolbar_selection)","def create_panel(self):\n return\n # return Panel(self)","def add_frame_shift(self, basis, axis_settings):\n angle, axis = angle_and_axis(basis)\n\n if angle == 0:\n axis = (0,0,1)\n\n if basis.include_translation:\n translation = basis.translation\n else:\n translation = (0,0,0)\n\n self.add_row([basis.axis_name,\"rotation\",\"detector\",basis.depends_on,\n str(axis[0]),str(axis[1]),str(axis[2]),\n str(translation[0]),\n str(translation[1]),\n str(translation[2]),\n basis.equipment_component])\n\n axis_settings.append([basis.axis_name, \"FRAME1\", str(angle), \"0\"])","def adjust_visual(self):\n\n if (self.direction is bs.Direction.LEFT):\n self.rect.x -= 0.5 * CELL_SIZE","def generate_panel(self):\r\n \r\n self.PanelData = self.RawData.filter(['ID', 'X', 'Z', 'W', 'R', 'β', 'LFP', 'H'], axis=1)","def plot_overlay2axes(self, axes) -> None:\n # calculate height (based on leaf analysis ratio)\n upper_point = (\n self.leaf_center_px - self.leaf_width_px / 2 * self._analysis_ratio\n )\n lower_point = (\n self.leaf_center_px + self.leaf_width_px / 2 * self._analysis_ratio\n )\n height = abs(upper_point - lower_point) * 0.8\n\n for idx, line in enumerate(self.marker_lines):\n width = abs(self.error[idx]) * self._image.dpmm\n y = line.center.y\n x = self.position[idx] - (self.error[idx] * self._image.dpmm) / 2\n\n if self._orientation == Orientation.UP_DOWN:\n r = Rectangle(width, height, center=(x, y))\n # if any of the values are over tolerance, show another larger rectangle to draw the eye\n if not self.passed[idx] or not self.passed_action[idx]:\n re = Rectangle(\n self._image_window.shape[1] * 0.2, height * 1.2, center=(x, y)\n )\n re.plot2axes(\n axes,\n edgecolor=\"none\",\n fill=True,\n alpha=0.5,\n facecolor=self.bg_color[idx],\n )\n else:\n r = Rectangle(height, width, center=(x, y))\n if not self.passed[idx] or not self.passed_action[idx]:\n re = Rectangle(\n self._image_window.shape[1] * 0.2, height * 1.2, center=(x, y)\n )\n re.plot2axes(\n axes,\n edgecolor=\"none\",\n fill=True,\n alpha=0.5,\n facecolor=self.bg_color[idx],\n )\n r.plot2axes(\n axes, edgecolor=\"none\", fill=True, alpha=1, facecolor=self.bg_color[idx]\n )","def postRefRender(self):\n self.logger.debug(\"Running postRefRender\")\n\n # add the lattice frame\n self.addLatticeFrame()\n\n # add the axes\n self.axes.add()\n\n # set camera to cell\n self.setCameraToCell()\n\n # reinitialise\n self.reinit()","def __init__(self):\n self.fig = pl.figure(1,figsize=(8,6), dpi=80 , frameon = True , facecolor = '0.75' , edgecolor = 'w')\n self.fig.add_subplot(111 , axisbg = 'w' , projection = 'rectilinear') #if you want to add axes on particular place: fig.add_axes([0.15, 0.1, 0.7, 0.3]) where -> [begin , bottom to start axes , width , height ]\n self.separated = True #if we have a list and need to plot the plots separated","def define_panel_structure(self):\n w, h = self.parent.GetSize()\n self.vbox = wx.BoxSizer(wx.VERTICAL)\n self.sizer1 = wx.BoxSizer(wx.VERTICAL)\n self.sizer1.SetMinSize(wx.Size(w/13, h*2/5))\n\n self.sizer2 = wx.BoxSizer(wx.VERTICAL)\n self.sizer3 = wx.FlexGridSizer(9, 2, 4, 1)\n self.sizer4 = wx.BoxSizer(wx.VERTICAL)\n self.sizer5 = wx.BoxSizer(wx.VERTICAL)\n\n self.vbox.Add(self.sizer5, 0, wx.EXPAND | wx.ALL, 1)\n self.vbox.Add(self.sizer1, 1, wx.EXPAND | wx.ALL, 0)\n self.vbox.Add(self.sizer2, 0, wx.EXPAND | wx.ALL, 1)\n self.vbox.Add(self.sizer3, 0, wx.EXPAND | wx.ALL, 10)\n # self.vbox.Add(self.sizer4, 0, wx.EXPAND|wx.ALL,5)\n\n self.SetSizer(self.vbox)","def draw_window_pane():\n houseturtle.begin_fill()\n for y in range(4):\n houseturtle.pendown()\n houseturtle.forward(35)\n houseturtle.left(90)\n houseturtle.penup()\n houseturtle.end_fill()","def create_base(self):\n if self.debug:\n print(\"Creating base\")\n self.console_panel = ConsolePanel(self.root)\n self.side_panel = SidePanel(self.root, self.populate_main_panel)\n self.side_panel.set_separator(\"word_word\")\n self.main_panel = MainPanel(self.root, action=\"word_word\")","def SetupView(self):\r\n size = self.GetClientSizeTuple()\r\n height = self.maxtop - self.maxbottom\r\n width = self.maxright - self.maxleft\r\n \r\n #The ratio of the width to the height in the client-area\r\n screenratio = float(size[0]) / float(size[1])\r\n \r\n #The ratio of the world window. Because of divide-by-0, we have to make a special-case assignment\r\n if height == 0 or width == 0:\r\n ratio = screenratio\r\n else:\r\n ratio = width / height\r\n\r\n #Should seem familiar, since we did it in class...\r\n if ratio > screenratio:\r\n glViewport(0, (size[1] - (size[0] / ratio)) / 2, size[0], size[0] / ratio)\r\n if ratio < screenratio:\r\n glViewport((size[0] - size[1] * ratio) / 2, 0, size[1] * ratio, size[1])\r\n \r\n \r\n #I need to find an appropriate border value. It's scaled by the client-area because the world-window zooms, thus skewing any normal border given.\r\n if width == 0 or height == 0:\r\n xborder = 1\r\n yborder = 1\r\n else:\r\n xscale = size[0] / width\r\n xborder = 10 / xscale\r\n yscale = size[1] / height\r\n yborder = 10 / yscale\r\n \r\n glMatrixMode(GL_PROJECTION)\r\n glLoadIdentity()\r\n gluOrtho2D(self.maxleft - xborder, self.maxright + xborder, self.maxbottom - yborder, self.maxtop + yborder)","def update_transform(self):\n\n self.a = self.scale * self.pixel_size * math.cos(self.angle)\n self.d = self.scale * self.pixel_size * math.sin(self.angle)\n self.b = self.d\n self.e = -self.a\n self.c = self.point.x() - self.a*self.width/2.0 - self.b*self.height/2.0\n self.f = self.point.y() - self.d*self.width/2.0 - self.e*self.height/2.0\n\n self.bounding_box = [[self.c,self.f],[self.c+self.a*self.width,self.f+self.d*self.width],[self.c+self.a*self.width+self.b*self.height,self.f+self.d*self.width+self.e*self.height],[self.c+self.b*self.height,self.f+self.e*self.height],]","def __init__(self):\n Page.__init__(self, u\"Paraboloide Elíptico<br><br>F(x,y)=(x, y, x<sup>2</sup>/a<sup>2</sup> + y<sup>2</sup>/b<sup>2</sup>)\")\n\n z = 0.5\n par = RevolutionPlot3D(lambda r, t: r ** 2 + z, (0, 1), (0, 2 * pi))\n\n x, y, z2, u, v, cose, sen, t = createVars(['x', 'y', 'z', 'u', 'v', 'cos', 'sen', 't'])\n\n mesh1 = Plot3D(lambda x, y, h: h * (x ** 2 + y ** 2 + z - .01), (-1, 1), (-1, 1))\n mesh1.addEqn(x**2+y**2 - z2**2 == 1)\n mesh1.addFunction(lambda x, y, h: h * (x ** 2 + y ** 2 + z + .01))\n mesh1.setLinesVisible(True)\n mesh1.setMeshVisible(False)\n mesh1.setBoundingBox(zrange=(-1, 1.5))\n par.setAmbientColor(_1(145, 61, 74))\n par.setDiffuseColor(_1(145, 61, 74))\n par.setSpecularColor(_1(145, 61, 74))\n baseplane = BasePlane()\n baseplane.setHeight(0)\n baseplane.setRange((-2, 2, 7))\n\n self.addChild(par)\n self.addChild(mesh1)\n self.addChild(baseplane)","def make_panel_in_array(array_elt, reference_panel):\n\n px_size = tuple((e / 3.0) for e in reference_panel.get_pixel_size())\n ref_panel_size = reference_panel.get_image_size_mm()\n x_shift = array_elt[0] * ref_panel_size[0] / 3.0\n y_shift = array_elt[1] * ref_panel_size[1] / 3.0\n origin = (\n matrix.col(reference_panel.get_origin())\n + x_shift * matrix.col(reference_panel.get_fast_axis())\n + y_shift * matrix.col(reference_panel.get_slow_axis())\n )\n return Panel(\n type=\"PAD\",\n name=\"Panel\",\n fast_axis=reference_panel.get_fast_axis(),\n slow_axis=reference_panel.get_slow_axis(),\n origin=origin,\n pixel_size=px_size,\n image_size=reference_panel.get_image_size(),\n trusted_range=(0, 1.0e6),\n thickness=0.0,\n material=\"\",\n )","def create_panel(self):\n # Main Frame creation\n frame1 = Frame(self.window)\n frame1.pack(fill=\"both\")\n tablayout = Notebook(frame1)\n \n ##### TRACKER #####\n tab = Frame(tablayout) # creating 1st nested frame\n tab.pack(fill=\"both\")\n table = Frame(tab)\n table.pack(fill=\"both\")\n self.show_table(self.t.timeline[\"week\" + str(self.week)], table) # Grids the week with data\n self.add_buttons(tab, table)\n tablayout.add(tab, text=\"Current Week\") \n \n \n ##### STATS #####\n tab = Frame(tablayout) # creating 2nd nested frame\n tab.pack(fill=\"both\")\n self.stats.create_canvas(tab)\n\n\n # once its packed you can add it to the window object under a title\n tablayout.add(tab, text=\"Statistics\") \n tablayout.pack(fill=\"both\") # once everything is done now you pack the tablayout","def __init__(self):\n self.degrees = 60.0\n self.aspect_ratio = 1.0\n self.front_pane = 0.1\n self.back_pane = 100.0","def reshape(self, w, h):\n glViewport(0, 0, w, h)\n\n glMatrixMode(GL_PROJECTION)\n glLoadIdentity()\n gluPerspective(40.0, w/h, 1.0, 1000.0)\n glutPostRedisplay()","def DrawTransform(self, xf):\r\n p1 = xf.position\r\n p2 = self.to_screen(p1 + self.axisScale * xf.R.col1)\r\n p3 = self.to_screen(p1 + self.axisScale * xf.R.col2)\r\n p1 = self.to_screen(p1)\r\n\r\n pygame.draw.aaline(self.surface, (255, 0, 0), p1, p2)\r\n pygame.draw.aaline(self.surface, (0, 255, 0), p1, p3)","def expanded_boundaries(self):\n width = self._points[0][3][0] - self._points[0][1][0]\n height = self._points[0][3][1] - self._points[0][1][1]\n factor = np.multiply((width, height), Window.BORDER)\n return (\n np.subtract(self._points[0][1], factor),\n np.add(self._points[0][3], factor))","def __init__(self, **kwargs):\n\n tmp = defs.copy()\n tmp.update(kwargs)\n\n for kw in tmp:\n setattr(self, kw, tmp[kw])\n \n if self.left is None:\n self.left = pl.rcParams['figure.subplot.left']\n if self.right is None:\n self.right = pl.rcParams['figure.subplot.right']\n if self.bottom is None:\n self.bottom = pl.rcParams['figure.subplot.bottom']\n if self.top is None:\n self.top = pl.rcParams['figure.subplot.top']\n \n self.l = self.left\n self.r = self.right\n self.b = self.bottom\n self.t = self.top \n \n self.square = self.dims[0] == self.dims[1]\n \n if (self.diagonal is not None) and not self.square:\n raise ValueError('Must have square matrix to use diagonal=True')\n\n self.dims = tuple(self.dims)\n self.J, self.K = self.dims # J = nrows, K = ncols\n self.nrows = self.J\n self.ncols = self.K\n \n if type(self.padding) is float:\n self.padding = tuple([self.padding]* 2)\n \n # Size of an individual panel (in inches)\n self.pane_size = np.array(self.figsize) * np.array([self.r-self.l, self.t-self.b])\n self.pane_size *= np.array(self.panel_size)\n\n # Now, figure out the size of the entire figure (in inches)\n self.panel_size = np.zeros(2)\n \n # After these two lines, self.panel_size is equal to the size of the\n # panel-filled area of the window (in inches)\n self.panel_size[0] = self.pane_size[0] * self.K + self.padding[0] * (self.K - 1)\n self.panel_size[1] = self.pane_size[1] * self.J + self.padding[1] * (self.J - 1) \n\n # Add empty area above/below and left/right of panel-filled area\n self.panel_size[0] += self.figsize[0] * (self.left + (1. - self.right))\n self.panel_size[1] += self.figsize[1] * (self.bottom + (1. - self.top))\n\n self.panel_size_rel = self.pane_size / self.panel_size\n\n self.share_x = self.padding[1] <= 0.2\n self.share_y = self.padding[0] <= 0.2 \n self.share_all = self.share_x and self.share_y\n\n self.dx = self.shift_x\n self.dy = self.shift_y\n\n # Create figure\n if type(self.fig) is not int:\n new_fig = False\n l, r = self.fig.subplotpars.left, self.fig.subplotpars.right\n b, t = self.fig.subplotpars.bottom, self.fig.subplotpars.top\n else:\n self.fig = pl.figure(self.fig, self.panel_size)\n new_fig = True\n\n # Adjust padding\n if self.preserve_margins:\n l = self.left * self.figsize[0] / self.panel_size[0]\n r = (self.left * self.figsize[0] + self.K * self.pane_size[0]) \\\n / self.panel_size[0]\n b = self.bottom * self.figsize[1] / self.panel_size[1]\n t = (self.bottom * self.figsize[1] + self.J * self.pane_size[1]) \\\n / self.panel_size[1]\n else:\n l, r, b, t = self.left, self.right, self.bottom, self.top\n \n self.fig.subplots_adjust(left=l, right=r, bottom=b, top=t, \n wspace=self.padding[0], hspace=self.padding[1])\n \n self.l, self.r, self.b, self.t = l, r, b, t\n\n # Important attributes for identifying individual panels\n self.N = int(np.prod(self.dims))\n self.elements = list(np.reshape(np.arange(self.N), self.dims))\n self.elements.reverse()\n self.elements = np.array(self.elements)\n\n # Dimensions of everything (in fractional units)\n #self.window = {'left': l, 'right': r, 'top': t, \n # 'bottom': b, 'pane': ((r-l) / float(dims[0]), (t-b) / float(dims[1]))}\n\n self.xaxes = self.elements[-1]\n self.yaxes = list(zip(*self.elements))[0] \n self.lowerleft = self.elements[-1][0]\n self.lowerright = self.elements[-1][-1]\n self.upperleft = self.elements[0][0]\n self.upperright = self.elements[0][-1]\n \n if self.square:\n self.diag = np.diag(self.elements) \n self.interior = list(self.elements.ravel())\n for element in self.diag:\n self.interior.remove(element)\n else:\n self.diag = None \n \n self.left = []\n self.right = []\n self.bottom = []\n self.top = []\n for i in range(self.N):\n k, j = self.axis_position(i) # col, row\n \n if j == 0:\n self.bottom.append(i)\n if j == self.nrows - 1:\n self.top.append(i) \n if k == 0:\n self.left.append(i)\n if k == self.ncols - 1:\n self.right.append(i) \n\n self.interior = []\n for i in range(self.N):\n if i in self.left:\n continue\n if i in self.bottom:\n continue\n \n self.interior.append(i)\n\n # Create subplots\n e_fl = self.elements.flatten()\n self.grid = [None for i in range(self.N)]\n for i in range(self.N): \n j, k = self.axis_position(i)\n \n if self.diagonal == 'lower':\n if k >= (self.dims[1] - j) and i not in self.diag:\n continue\n if self.diagonal == 'upper':\n if k < (self.dims[1] - j) and i not in self.diag:\n continue \n \n #if self.diagonal == 'lower' and j == k and (j, k) != (0, 0):\n # continue\n #if self.diagonal == 'upper' and j == k and (j, k) != (self.J-1, self.K-1):\n # continue\n \n if self.square:\n if i in self.diag and not self.keep_diagonal:\n continue\n \n if new_fig:\n self.grid[i] = AxisConstructor(self.fig, self.J, self.K, e_fl[i]+1)\n else:\n\n # col, row = j, k\n\n lef = l + j * self.panel_size_rel[0] \\\n + self.padding[0] + self.dx\n bot = b + k * self.panel_size_rel[1] \\\n + self.padding[1] + self.dy\n\n rect = [lef, bot, self.panel_size_rel[0], self.panel_size_rel[1]]\n\n self.grid[i] = self.fig.add_axes(rect)","def onFrameConfigure(self, event):\n self.panel_002.config(scrollregion=self.panel_002.bbox(\"all\"))","def warp(self):\n self.maingui.scene.center_on(self.spin_x.value(), self.spin_y.value())\n self.close()","def pixel_space(self):\n self.drawer.settransform()\n self.coordspace_bbox = [0, 0, self.width, self.height]\n self.coordspace_transform = (1, 0, 0,\n 0, 1, 0)","def warp_to_dashboard(self, overhead_img):\n return cv2.warpPerspective(overhead_img, self.inverse_overhead_transform,\n dsize=(self.img_width, self.img_height))","def _create_distplot_pane(self):\n panel = wx.Panel(self, -1)\n\t\t\n self.fig_violin = Figure()\n self.ax_violin = self.fig_violin.add_subplot(111)\n\t\t\n self.ax_violin.set_xlabel(\"Voxel values\")\n self.ax_violin.set_ylabel(\"Density\")\n self.ax_violin.set_xlim(60, 120)\n self.ax_violin.set_ylim(0, 0.3)\n\t\t\n self.canvas_violin = FigureCanvas(panel, -1, self.fig_violin)\n self.toolbar_violin = NavigationToolbar(self.canvas_violin)\n\t\t\n self.canvas_violin.mpl_connect('pick_event', self.onPickdist)\n\t\t\n vbox = wx.BoxSizer(wx.VERTICAL)\n vbox.Add(self.canvas_violin, 1, wx.EXPAND|wx.BOTTOM, 7)\n vbox.Add(self.toolbar_violin, 0, wx.EXPAND)\n\t\t\n panel.SetSizer(vbox)\n vbox.Fit(panel)\n\t\t\n return panel","def _locator(self, axes, renderer):\n x0, y0, x1, y1 = self.rect\n width_dict = dict()\n cut_ax_dict = self.axes\n x_ax = cut_ax_dict['x']\n y_ax = cut_ax_dict['y']\n z_ax = cut_ax_dict['z']\n for cut_ax in cut_ax_dict.values():\n bounds = cut_ax.get_object_bounds()\n if not bounds:\n # This happens if the call to _map_show was not\n # succesful. As it happens asyncroniously (during a\n # refresh of the figure) we capture the problem and\n # ignore it: it only adds a non informative traceback\n bounds = [0, 1, 0, 1]\n xmin, xmax, ymin, ymax = bounds\n width_dict[cut_ax.ax] = (xmax - xmin)\n total_width = float(sum(width_dict.values()))\n for ax, width in width_dict.items():\n width_dict[ax] = width/total_width*(x1 -x0)\n left_dict = dict()\n left_dict[y_ax.ax] = x0\n left_dict[x_ax.ax] = x0 + width_dict[y_ax.ax]\n left_dict[z_ax.ax] = x0 + width_dict[x_ax.ax] + width_dict[y_ax.ax]\n return transforms.Bbox([[left_dict[axes], y0],\n [left_dict[axes] + width_dict[axes], y1]])","def panel_axes(self, side, **kwargs):\n return self.figure._add_axes_panel(self, side, **kwargs)","def make_layers(self):\n w, h = self.image.get_size()\n shrink = pg.transform.smoothscale(self.image, (w//2, h//2))\n self.mid_image = tools.tile_surface((w,h), shrink, True)\n shrink = pg.transform.smoothscale(self.image, (w//4, h//4))\n self.base = tools.tile_surface(prepare.SCREEN_SIZE, shrink, True)","def draw_reference_frame_axes(se3_pose, scene): # pragma nocover\n\n origin = get_pose_pos(se3_pose)\n x_axis = get_pose_x_vec(se3_pose)\n y_axis = get_pose_y_vec(se3_pose)\n\n # Create Basic Frame\n # Draw X Axis\n x_arrow = arrow(\n canvas=scene, pos=origin, axis=x_axis_vector,\n length=0.25, color=color.red)\n\n # Draw Y Axis\n y_arrow = arrow(\n canvas=scene, pos=origin, axis=y_axis_vector,\n length=0.25, color=color.green)\n\n # Draw Z Axis\n z_arrow = arrow(\n canvas=scene, pos=origin, axis=z_axis_vector,\n length=0.25, color=color.blue)\n\n # Combine all to manipulate together\n # Set origin to where axis converge (instead of the middle of\n # the resulting object bounding box)\n frame_ref = compound(\n [x_arrow, y_arrow, z_arrow], origin=origin, canvas=scene)\n\n # Set frame axes\n frame_ref.axis = x_axis\n frame_ref.up = y_axis\n\n return frame_ref","def canvas_bounds(self) -> utils.BoxRegion:","def _add_boundaries(self):\n logger.info(\"add_boundaries: start of method\")\n\n import scipy.spatial as sptl\n import scipy.sparse as sprs\n Lx = self._Lx\n Ly = self._Ly\n Lz = self._Lz\n Np = self.num_pores()\n btype = self._btype\n boffset = 0.05\n\n #Translate internal pores to each face of domain\n poffset = np.zeros((7,3))\n poffset[[2,5],0] = [-Lx, Lx]\n poffset[[3,4],1] = [-Ly, Ly]\n poffset[[1,6],2] = [-Lz, Lz]\n pcoords = pcoords0 = self['pore.coords']\n for i in np.r_[1:7]:\n pcoords = np.concatenate((pcoords,pcoords0 + poffset[i,:]),axis=0)\n\n #Use some twisted logic to get bval list of + for boundary and - for periodic faces\n bval = [0, 1, 2, 3, 4, 5, 6]*(np.array([0, btype[2], btype[0], btype[1], btype[1], btype[0], btype[2]])*-2+1)\n ptype = np.zeros((Np,),dtype=int)\n for i in np.r_[1:7]:\n ptype = np.concatenate((ptype,np.ones((Np,),dtype=int)*bval[i]),axis=0)\n\n #pnum contains the internal ID number of the boundary pores (for connecting periodic points)\n pnum = self.pores()\n pnum = np.tile(pnum,7)\n\n Tri = sptl.Delaunay(pcoords)\n adjmat = sprs.lil_matrix((np.shape(pcoords)[0],np.shape(pcoords)[0]),dtype=int)\n for i in np.arange(0,np.shape(Tri.simplices)[0]):\n #Keep only simplices that are fully in real domain\n adjmat[Tri.simplices[i],Tri.simplices[i]] = 1\n adjmat = sprs.triu(adjmat,k=1,format=\"lil\")\n for i in np.arange(0,Np):\n #Add periodic throats to the netowrk (if any)\n tpore2 = pnum[adjmat.rows[i]][ptype[adjmat.rows[i]]<0]\n tpore1 = np.ones_like(tpore2,dtype=int)*i\n conns = self['throat.conns']\n conns = np.concatenate((conns,np.vstack((tpore1,tpore2)).T),axis=0)\n #Add boundary pores and throats to the network\n newporetyps = np.unique(ptype[adjmat.rows[i]][ptype[adjmat.rows[i]]>0])\n newporenums = np.r_[self.num_pores():self.num_pores()+np.size(newporetyps)]\n tpore2 = newporenums\n tpore1 = np.ones_like(tpore2,dtype=int)*i\n conns = np.concatenate((conns,np.vstack((tpore1,tpore2)).T),axis=0)\n self['throat.conns'] = conns\n bcoords = np.zeros((7,3),dtype=float)\n coords = self['pore.coords']\n bcoords[1,:] = [coords[i,0], coords[i,1], 0-Lz*boffset]\n bcoords[2,:] = [0-Lx*boffset, coords[i,1], coords[i,2]]\n bcoords[3,:] = [coords[i,0], -Ly*boffset, coords[i,2]]\n bcoords[4,:] = [coords[i,0], Ly+Ly*boffset, coords[i,2]]\n bcoords[5,:] = [Lx+Lx*boffset, coords[i,1], coords[i,2]]\n bcoords[6,:] = [coords[i,0], coords[i,1], Lz+Lz*boffset]\n newporecoords = bcoords[newporetyps,:]\n coords = np.concatenate((coords,newporecoords),axis=0)\n self['pore.coords'] = coords\n #Reset number of pores and throats (easier than tracking it)\n nums = np.r_[0:np.shape(coords)[0]]\n self['pore.numbering'] = nums\n self['pore.numbering'] = np.ones((nums[-1]+1,),dtype=bool)\n nums = np.r_[0:np.shape(conns)[0]]\n self['throat.numbering'] = nums\n self['throat.numbering'] = np.ones((nums[-1]+1,),dtype=bool)\n logger.debug(\"add_boundaries: end of method\")","def __init__(self, parent, tile_dir=None, start_level=None,\n min_level=None, max_level=None, **kwargs):\n\n # create and initialise the base panel\n wx.Panel.__init__(self, parent=parent, id=wx.ID_ANY, **kwargs)\n self.SetBackgroundColour(pySlip.BackgroundColour)\n\n # get tile info\n self.tiles = pySlip.Tiles(tile_dir)\n self.max_level = max_level\n if max_level is None:\n self.max_level = self.tiles.max_level\n self.min_level = min_level\n if min_level is None:\n self.min_level = self.tiles.min_level\n self.level = start_level\n if start_level is None:\n self.level = self.min_level\n\n self.tile_size_x = self.tiles.tile_size_x\n self.tile_size_y = self.tiles.tile_size_y\n\n # set some internal state\n self.view_width = None # view size in pixels\n self.view_height = None # set on onResize()\n\n self.ppd_x = 0 # pixel_per_degree for current tileset\n self.ppd_y = 0\n\n self.view_offset_x = 0 # pixel offset at left & top of view\n self.view_offset_y = 0\n\n self.view_llon = self.view_rlon = None # view limits\n self.view_tlat = self.view_blat = None\n\n self.was_dragging = False # True if dragging map\n self.move_dx = 0 # drag delta values\n self.move_dy = 0\n self.last_drag_x = None # previous drag position\n self.last_drag_y = None\n\n self.ignore_next_up = False # flag to ignore next UP event\n\n self.is_box_select = False # True if box selection\n self.sbox_1_x = self.sbox_1_y = None # box size\n\n # layer stuff\n self.next_layer_id = 1 # source of unique layer IDs\n self.layer_z_order = [] # layer Z order, contains layer IDs\n self.layer_mapping = {} # maps layer ID to (...layer data...)\n\n # callback to report mouse position in view\n self.mouse_position_callback = None\n\n # callback on right mouse click (right button up event)\n self.rightclick_callback = None\n\n # callback on level change\n self.change_level_callback = None\n\n # bind events\n self.Bind(wx.EVT_SIZE, self.onResize) # widget events\n self.Bind(wx.EVT_PAINT, self.onPaint)\n\n self.Bind(wx.EVT_MOTION, self.onMove) # mouse events\n self.Bind(wx.EVT_LEFT_DOWN, self.onLeftDown)\n self.Bind(wx.EVT_LEFT_DCLICK, self.onLeftDClick)\n self.Bind(wx.EVT_LEFT_UP, self.onLeftUp)\n self.Bind(wx.EVT_RIGHT_DOWN, self.onRightDown)\n self.Bind(wx.EVT_RIGHT_UP, self.onRightUp)\n self.Bind(wx.EVT_MIDDLE_DOWN, self.onMiddleDown)\n self.Bind(wx.EVT_MIDDLE_UP, self.onMiddleUp)\n self.Bind(wx.EVT_MOUSEWHEEL, self.onMouseWheel)\n\n # OK, use the tile level the user wants\n self.use_level(self.level)\n\n # force a resize, which sets up the rest of the state\n self.onResize()","def _create_scatterplot_pane(self):\n panel = wx.Panel(self, -1)\n\t\t\n self.fig_scatter = Figure()\n self.ax_scatter = self.fig_scatter.add_subplot(111)\n\t\t\n families = ['serif', 'sans-serif', 'cursive', 'fantasy', 'monospace']\n\t\t\n self.ax_scatter.set_xlabel(\"Mean\") #fontsize = 14, fontweight = 'semibold', name = families[2]\n self.ax_scatter.set_ylabel(\"Standard Deviation\")\n #self.ax_scatter.grid(color='black', alpha=0.5, linestyle='-', linewidth=1.0)\n self.ax_scatter.set_axis_bgcolor((0.8,0.8,0.8))\n #self.ax_scatter.set_ylim(0, 35)\n #self.ax_scatter.set_ylim(0, 90)\n\t\t\n self.canvas_scatter = FigureCanvas(panel, -1, self.fig_scatter)\n self.toolbar_scatter = NavigationToolbar(self.canvas_scatter)\n\t\t\n vbox = wx.BoxSizer(wx.VERTICAL)\n vbox.Add(self.canvas_scatter, 1, wx.EXPAND|wx.BOTTOM, 7)\n vbox.Add(self.toolbar_scatter, 0, wx.EXPAND)\n\t\t\n panel.SetSizer(vbox)\n vbox.Fit(panel)\n\t\t\n return panel","def relayout(self): \n\t\t#self.urmaswin.Layout()\n\t\t#wx.CallAfter(self.urmaswin.Layout)\n\t\t#wx.CallAfter(self.visualizer.OnSize)","def _set_lim_and_transforms(self):\n # There are three important coordinate spaces going on here:\n #\n # 1. Data space: The space of the data itself\n #\n # 2. Axes space: The unit rectangle (0, 0) to (1, 1)\n # covering the entire plot area.\n #\n # 3. Display space: The coordinates of the resulting image,\n # often in pixels or dpi/inch.\n\n # This function makes heavy use of the Transform classes in\n # ``lib/matplotlib/transforms.py.`` For more information, see\n # the inline documentation there.\n\n # The goal of the first two transformations is to get from the\n # data space (in this case longitude and latitude) to axes\n # space. It is separated into a non-affine and affine part so\n # that the non-affine part does not have to be recomputed when\n # a simple affine change to the figure has been made (such as\n # resizing the window or changing the dpi).\n\n # 1) The core transformation from data space into\n # rectilinear space defined in the HammerTransform class.\n self.transProjection = IdentityTransform()\n # 2) The above has an output range that is not in the unit\n # rectangle, so scale and translate it so it fits correctly\n # within the axes. The peculiar calculations of xscale and\n # yscale are specific to a Aitoff-Hammer projection, so don't\n # worry about them too much.\n self.transAffine = Affine2D.from_values(\n 1., 0, 0.5, np.sqrt(3)/2., 0, 0)\n self.transAffinedep = Affine2D.from_values(\n 1., 0, -0.5, np.sqrt(3)/2., 0, 0)\n #self.transAffine = IdentityTransform()\n \n # 3) This is the transformation from axes space to display\n # space.\n self.transAxes = BboxTransformTo(self.bbox)\n\n # Now put these 3 transforms together -- from data all the way\n # to display coordinates. Using the '+' operator, these\n # transforms will be applied \"in order\". The transforms are\n # automatically simplified, if possible, by the underlying\n # transformation framework.\n self.transData = \\\n self.transProjection + \\\n self.transAffine + \\\n self.transAxes\n\n # The main data transformation is set up. Now deal with\n # gridlines and tick labels.\n\n # Longitude gridlines and ticklabels. The input to these\n # transforms are in display space in x and axes space in y.\n # Therefore, the input values will be in range (-xmin, 0),\n # (xmax, 1). The goal of these transforms is to go from that\n # space to display space. The tick labels will be offset 4\n # pixels from the equator.\n\n self._xaxis_pretransform = IdentityTransform()\n self._xaxis_transform = \\\n self._xaxis_pretransform + \\\n self.transData\n self._xaxis_text1_transform = \\\n Affine2D().scale(1.0, 0.0) + \\\n self.transData + \\\n Affine2D().translate(0.0, -20.0)\n self._xaxis_text2_transform = \\\n Affine2D().scale(1.0, 0.0) + \\\n self.transData + \\\n Affine2D().translate(0.0, -4.0)\n\n # Now set up the transforms for the latitude ticks. The input to\n # these transforms are in axes space in x and display space in\n # y. Therefore, the input values will be in range (0, -ymin),\n # (1, ymax). The goal of these transforms is to go from that\n # space to display space. The tick labels will be offset 4\n # pixels from the edge of the axes ellipse.\n\n self._yaxis_transform = self.transData\n yaxis_text_base = \\\n self.transProjection + \\\n (self.transAffine + \\\n self.transAxes)\n self._yaxis_text1_transform = \\\n yaxis_text_base + \\\n Affine2D().translate(-8.0, 0.0)\n self._yaxis_text2_transform = \\\n yaxis_text_base + \\\n Affine2D().translate(8.0, 0.0)","def _constructClippingPlane( self, viewProj, positive, axis):\r\n if positive: scale = 1\r\n else: scale = -1\r\n\r\n return Plane(viewProj[0,3] + scale*viewProj[0, axis],\r\n viewProj[1,3] + scale*viewProj[1, axis],\r\n viewProj[2,3] + scale*viewProj[2, axis],\r\n viewProj[3,3] + scale*viewProj[3, axis] )","def boundary(active, objects):\n limit = SIZE[1]\n for obj in objects:\n if active.pos_x == obj.pos_x:\n limit = min(limit, obj.pos_y)\n active.pos_y = limit-active.height\n active.col_d = True","def add_panel(self, panel):\n assert panel.PANEL_ID not in self.panels\n assert not self.tools, \"tools must be added after panels\"\n self.panels[panel.PANEL_ID] = panel\n panel.register_panel(self)","def compare(self, other, scale=1.0):\n import matplotlib.pyplot as plt\n from matplotlib.collections import PatchCollection\n from matplotlib.patches import Polygon, FancyArrow\n\n fig = plt.figure(figsize=(10, 10))\n ax = fig.add_subplot(1, 1, 1)\n\n rects = []\n arrows = []\n for p, module in enumerate(self.modules):\n for a, fragment in enumerate(module):\n corners = fragment.corners()[:, :2] # Drop the Z dimension\n corner1, corner1_opp = corners[0], corners[2]\n\n rects.append(Polygon(corners))\n if a in {0, 7}:\n cx, cy, _ = fragment.centre()\n ax.text(cx, cy, str(a),\n verticalalignment='center',\n horizontalalignment='center')\n elif a == 4:\n cx, cy, _ = fragment.centre()\n ax.text(cx, cy, 'p{}'.format(p),\n verticalalignment='center',\n horizontalalignment='center')\n\n panel2 = other.modules[p][a]\n corners2 = panel2.corners()[:, :2]\n corner2, corner2_opp = corners2[0], corners2[2]\n dx, dy = corner2 - corner1\n if not (dx == dy == 0):\n sx, sy = corner1\n arrows.append(FancyArrow(\n sx, sy, scale * dx, scale * dy, width=5, head_length=4\n ))\n\n dx, dy = corner2_opp - corner1_opp\n if not (dx == dy == 0):\n sx, sy = corner1_opp\n arrows.append(FancyArrow(\n sx, sy, scale * dx, scale * dy, width=5, head_length=5\n ))\n\n pc = PatchCollection(rects, facecolor=(0.75, 1.0, 0.75), edgecolor=None)\n ax.add_collection(pc)\n ac = PatchCollection(arrows)\n ax.add_collection(ac)\n\n # Set axis limits to fit all shapes, with some margin\n all_x = np.concatenate([s.xy[:, 0] for s in arrows + rects])\n all_y = np.concatenate([s.xy[:, 1] for s in arrows + rects])\n ax.set_xlim(all_x.min() - 20, all_x.max() + 20)\n ax.set_ylim(all_y.min() - 40, all_y.max() + 20)\n\n ax.set_title('Geometry comparison: {} → {}'\n .format(self.filename, other.filename))\n ax.text(1, 0, 'Arrows scaled: {}×'.format(scale),\n horizontalalignment=\"right\", verticalalignment=\"bottom\",\n transform=ax.transAxes)\n return ax","def render_panel(self):\n size = self.env.GRID_NUM\n panel = self.PANEL_HEIGHT\n margin = self.MARGIN\n screen = self.screen\n cellWidth = self.CELL_WIDTH\n\n radius = (panel - 2 * margin) // 2\n x_left = margin\n x_right = (cellWidth + margin) * (self.env.GRID_NUM // 2) + margin\n y = margin\n w = (cellWidth + margin) * (self.env.GRID_NUM // 2) - margin\n h = panel - margin\n screenWidth = (cellWidth + margin) * size + margin\n\n DrawRect(screen, Colors.GRAY, [x_left, y, w, h])\n DrawRect(screen, Colors.GRAY, [x_right, y, w, h])\n DrawCircle(screen, Colors.BLACK, (x_left + margin + radius, margin + h // 2), radius)\n DrawCircle(screen, Colors.WHITE, (x_right + margin + radius, margin + h // 2), radius)\n if self.env.isBlackTurn():\n DrawPolygon(screen, Colors.RED, ((margin, margin), (margin + panel // 3, margin), (margin, margin + panel // 3)))\n else:\n DrawPolygon(screen, Colors.RED, ((x_right, margin), (x_right + panel // 3, margin), (x_right, margin + panel // 3)))\n\n black_disks = self.env.num_black_disks()\n white_disks = self.env.num_white_disks()\n black_score = self.env.black_score\n white_score = self.env.white_score\n black_ai = self.agents[Player.BLACK].name\n white_ai = self.agents[Player.WHITE].name\n\n pygame.font.init()\n self.font = pygame.font.SysFont('Comic Sans MS', 16)\n\n text = self.font.render(f'{black_ai} ({black_score}) {black_disks}', False, (255, 255, 255))\n text_rect = text.get_rect(midleft=(x_left + 2 * (margin + radius), panel // 2))\n self.screen.blit(text, text_rect)\n\n text = self.font.render(f'{white_ai} ({white_score}) {white_disks}', False, (255, 255, 255))\n text_rect = text.get_rect(midleft=(x_right + 2 * (margin + radius), panel // 2))\n self.screen.blit(text, (x_right + 2 * (margin + radius), panel // 2 - 10))","def _InitUI( self, two_axes = False ):\n dpis = wx.ScreenDC().GetPPI()\n size = ( WIDGET_PREF_SIZE[ 0 ] / dpis[ 0 ], WIDGET_PREF_SIZE[ 1 ] / dpis[ 0 ] )\n self.fig = Figure( facecolor = '#ececec', figsize = size, dpi = dpis[ 0 ] )\n\n self._InitAxes()\n# if two_axes:\n# self.ax = self.fig.add_axes([ 0.1, 0.1, 0.85, 0.65 ])\n# self.ax2 = self.ax.twiny()\n# else:\n# self.ax = self.fig.add_subplot( 111 )\n self.canvas = FigureCanvas( self, -1, self.fig )\n self.canvas.SetMinClientSize( wx.Size( 200, 200 ) )\n self.toolbar = NavigationToolbar( self.canvas )\n #self.toolbar.Realize()\n self.toolbar.SetBackgroundColour( wx.Colour( 236, 236, 236, 255 ) )\n self.toolbar.Show( False )\n\n sizer = wx.BoxSizer( wx.VERTICAL )\n sizer.Add( self.toolbar, 0, wx.LEFT | wx.TOP | wx.BOTTOM | wx.EXPAND, 1 )\n sizer.Add( self.canvas, 1, wx.LEFT | wx.TOP | wx.BOTTOM | wx.EXPAND, 1 )\n self.SetSizer( sizer )\n\n self.callbackIds[ 'button_release_event' ] = \\\n self.canvas.mpl_connect( 'button_release_event', self._OnMplMouseRelease )\n self.callbackIds[ 'motion_notify_event' ] = \\\n self.canvas.mpl_connect( 'motion_notify_event', self._OnMplMouseMotion )\n\n self.Bind( wx.EVT_CLOSE, self._OnClose )\n self.Bind( wx.EVT_CONTEXT_MENU, self._OnContextMenu )\n self.Bind( wx.EVT_SIZE, self._OnSize )\n\n self.timer = wx.Timer( self, TIMERID_RESIZE )\n self.Bind( wx.EVT_TIMER, self._OnTimer )","def boundary(self):\n if self.pos.x < 0:\n self.pos.x = 0\n if self.pos.x > WIDTH - 48:\n self.pos.x = WIDTH - 48\n if self.pos.y < 0:\n self.pos.y = 0\n if self.pos.y > HEIGHT - 48:\n self.pos.y = HEIGHT - 48\n\n self.rect.topleft = self.pos","def transform_view(self):\n translation = self.get_translation()\n scale = self.get_scaling()\n # update all non static visuals\n for visual in self.paint_manager.get_visuals():\n if not visual.get('is_static', False):\n self.set_data(visual=visual['name'], \n scale=scale, translation=translation)","def __init__(self, parent):\n super(StageVisualizer, self).__init__(parent)\n\n self.figure = matplotlib.figure.Figure()\n self.axes = self.figure.add_subplot(111)\n self.figure.subplots_adjust(top=1, bottom=0, right=1, left=0)\n\n self.axes.get_xaxis().set_visible(False)\n self.axes.get_yaxis().set_visible(False)\n\n self.canvas = FigureCanvas(self, -1, self.figure)\n\n self.sizer = wx.BoxSizer(wx.VERTICAL)\n self.sizer.Add(self.canvas, 1, wx.LEFT | wx.TOP | wx.GROW)\n self.SetSizer(self.sizer)\n\n self.toolbar = NavigationToolbar(self.canvas)\n self.toolbar.pan()\n self.toolbar.Hide()\n\n self.Fit()\n\n self.zoomer = self.zoom_factory(self.axes, base_scale=1.5)\n\n self.canvas.Bind(wx.EVT_PAINT, self.on_paint)","def create_sat_panels(self):\n\n # Dimensions of body\n SAT_SIZE = self.ANI_SCALE*self.SAT_SCALE*np.asarray(self.SAT_PROPS[\"Size\"])/2\n bx = SAT_SIZE[0]\n by = SAT_SIZE[1]\n bz = SAT_SIZE[2]\n\n # Panel length\n L = bx\n\n # Panels\n theta = self.PANEL_ANGLE*pi/180\n px1 = bx - L*sin(theta)\n py1 = by + L*cos(theta)\n pz1 = bz\n px2 = px1 + L*sin(theta)\n py2 = py1 + L*cos(theta)\n pz2 = pz1\n\n # Vertices\n V = [\n (-bx, by, -bz),\n (-bx, by, bz),\n (-px1, py1, pz1),\n (-px1, py1, -pz1),\n (-px1, py1, -pz1),\n (-px1, py1, pz1),\n (-px2, py2, pz2),\n (-px2, py2, -pz2),\n (-bx, -by, -bz),\n (-bx, -by, bz),\n (-px1, -py1, pz1),\n (-px1, -py1, -pz1),\n (-px1, -py1, -pz1),\n (-px1, -py1, pz1),\n (-px2, -py2, pz2),\n (-px2, -py2, -pz2)\n ]\n\n # Create faces\n F = [\n (0, 1, 2, 3),\n (4, 5, 6, 7),\n (8, 9, 10, 11),\n (12, 13, 14, 15)\n ]\n\n # Create building blocks of polydata\n sat = vtk.vtkPolyData()\n points = vtk.vtkPoints()\n polys = vtk.vtkCellArray()\n scalars = vtk.vtkFloatArray()\n\n # Load the point, cell and data attributes\n for i in range(len(V)):\n points.InsertPoint(i, V[i])\n for i in range(len(F)):\n polys.InsertNextCell(self.mkVtkIdList(F[i]))\n for i in range(len(V)):\n scalars.InsertTuple1(i, i)\n \n # Assign the pieces to the vtkPolyData.\n sat.SetPoints(points)\n del points\n sat.SetPolys(polys)\n del polys\n sat.GetPointData().SetScalars(scalars)\n del scalars\n\n # Mapper\n mapper = vtk.vtkPolyDataMapper()\n mapper.SetInputData(sat)\n mapper.ScalarVisibilityOff()\n\n # Actor\n actor = vtk.vtkActor()\n actor.SetMapper(mapper)\n actor.GetProperty().SetColor(0., 0., 0.8)\n actor.GetProperty().SetAmbient(0.5)\n actor.GetProperty().SetSpecular(.5)\n actor.GetProperty().SetSpecularPower(10.0)\n actor.GetProperty().SetDiffuse(0.2)\n\n # Move to sat position\n actor.SetPosition(0, 0, -self.SAT_PROPS[\"Alt\"])\n\n return actor","def paintScreen(self):\n imgPath = GG.genteguada.GenteGuada.getInstance().getDataPath(BACKGROUND_LEFT)\n self.imgBackgroundLeft = guiobjects.OcempImageMapTransparent(imgPath)\n self.window.add_child(self.imgBackgroundLeft)\n imgPath = GG.genteguada.GenteGuada.getInstance().getDataPath(BACKGROUND_RIGHT)\n imgBackgroundRight = guiobjects.OcempImageMapTransparent(imgPath)\n imgBackgroundRight.topleft = 297, 0\n self.window.add_child(imgBackgroundRight)","def initializePage(self):\n WizardPage.initialize(self)\n self.page.use(qt.QVBoxLayout())\n\n dims = [(\"DX\", 0.), (\"DY\", 0.)]\n if self.give_field(\"model\").dim == 3:\n dims.append((\"DZ\", 0.))\n exp = self.give_field(\"exp-store\").give_exp(\"boundaries\")\n lst = exp.find_groups(self.give_field(\"mesh\"))\n tit = u\"Adding imposed degrees of freedom on groups\"\n add_condition_selector(self, lst, dims, \"group-boundaries*\", tit)","def vizualize_wall(self):\n\n\t\t#Points are converted from polar to cartesian here\n\t\tpoint1 = Point()\n\t\t#(-math.pi/4) represents the 45 degree rotation of the front point\n\t\t#from the front of the robot\n\t\tpoint1.x = math.cos((-math.pi/4))*self.front_point\n\t\tpoint1.y = math.sin((-math.pi/4))*self.front_point\n\t\tpoint2 = Point()\n\t\t#(-3*math.pi/4) represents the back point's 90 degree rotaion from\n\t\t#the front point\n\t\tpoint2.x = math.cos((-3*math.pi/4))*self.back_point\n\t\tpoint2.y = math.sin((-3*math.pi/4))*self.back_point\n\t\tmy_marker = Marker(type=Marker.LINE_STRIP)\n\t\tmy_marker.header.frame_id = \"base_link\"\n\t\tmy_marker.color.a = 1\n\t\tmy_marker.scale.x = .1\n\t\tmy_marker.points = [point1, point2]\n\t\tself.visualizer.publish(my_marker)","def finalize_layout(self):\n self.mbox.addLayout(self.hbtnbox)\n self.mbox.addLayout(self.hbox)\n self.setLayout(self.mbox)","def project_grid(self):\n\n # option 1: no shared axes. Trees are scaled(?)\n\n\n # option 2: shared axes. Spacing of tree","def _independent_panel(width, height):\n\n from maya import cmds\n\n # center panel on screen\n screen_width, screen_height = _get_screen_size()\n topLeft = [int((screen_height-height)/2.0),\n int((screen_width-width)/2.0)]\n\n window = cmds.window(width=width,\n height=height,\n topLeftCorner=topLeft,\n menuBarVisible=False,\n titleBar=False)\n cmds.paneLayout()\n panel = cmds.modelPanel(menuBarVisible=False,\n label='CapturePanel')\n\n # Hide icons under panel menus\n bar_layout = cmds.modelPanel(panel, q=True, barLayout=True)\n cmds.frameLayout(bar_layout, e=True, collapse=True)\n\n cmds.showWindow(window)\n\n # Set the modelEditor of the modelPanel as the active view so it takes\n # the playback focus. Does seem redundant with the `refresh` added in.\n editor = cmds.modelPanel(panel, query=True, modelEditor=True)\n cmds.modelEditor(editor, e=1, activeView=True)\n\n # Force a draw refresh of Maya so it keeps focus on the new panel\n # This focus is required to force preview playback in the independent panel\n cmds.refresh(force=True)\n\n try:\n yield panel\n finally:\n # Delete the panel to fix memory leak (about 5 mb per capture)\n cmds.deleteUI(panel, panel=True)\n cmds.deleteUI(window)","def _locator(self, axes, renderer):\n x0, y0, x1, y1 = self.rect\n width_dict = dict()\n cut_ax_dict = self.axes\n for cut_ax in cut_ax_dict.values():\n bounds = cut_ax.get_object_bounds()\n if not bounds:\n # This happens if the call to _map_show was not\n # succesful. As it happens asyncroniously (during a\n # refresh of the figure) we capture the problem and\n # ignore it: it only adds a non informative traceback\n bounds = [0, 1, 0, 1]\n xmin, xmax, ymin, ymax = bounds\n width_dict[cut_ax.ax] = (xmax - xmin)\n total_width = float(sum(width_dict.values()))\n for ax, width in width_dict.items():\n width_dict[ax] = width/total_width*(x1 -x0)\n left_dict = dict()\n left = float(x0)\n for coord, cut_ax in sorted(cut_ax_dict.items()):\n left_dict[cut_ax.ax] = left\n this_width = width_dict[cut_ax.ax]\n left += this_width\n return transforms.Bbox([[left_dict[axes], y0],\n [left_dict[axes] + width_dict[axes], y1]])","def bbox_shift_scale_rotate(bbox, angle, scale, dx, dy, rotate_method, rows, cols, **kwargs): # skipcq: PYL-W0613\n height, width = rows, cols\n center = (width / 2, height / 2)\n if rotate_method == \"ellipse\":\n x_min, y_min, x_max, y_max = bbox_rotate(bbox, angle, rotate_method, rows, cols)\n matrix = cv2.getRotationMatrix2D(center, 0, scale)\n else:\n x_min, y_min, x_max, y_max = bbox[:4]\n matrix = cv2.getRotationMatrix2D(center, angle, scale)\n matrix[0, 2] += dx * width\n matrix[1, 2] += dy * height\n x = np.array([x_min, x_max, x_max, x_min])\n y = np.array([y_min, y_min, y_max, y_max])\n ones = np.ones(shape=(len(x)))\n points_ones = np.vstack([x, y, ones]).transpose()\n points_ones[:, 0] *= width\n points_ones[:, 1] *= height\n tr_points = matrix.dot(points_ones.T).T\n tr_points[:, 0] /= width\n tr_points[:, 1] /= height\n\n x_min, x_max = min(tr_points[:, 0]), max(tr_points[:, 0])\n y_min, y_max = min(tr_points[:, 1]), max(tr_points[:, 1])\n\n return x_min, y_min, x_max, y_max","def toggleLatticeFrame(self):\n if self.parent.getCurrentPipelinePage().refState is None:\n return\n\n if self.latticeFrame.visible:\n self.removeLatticeFrame()\n\n else:\n self.addLatticeFrame()\n\n self.reinit()","def scene_adding_panel(self, context):\r\n \r\n AM = context.window_manager.asset_m\r\n layout = self.layout\r\n box = layout.box()\r\n view = context.space_data\r\n fx_settings = view.fx_settings\r\n ssao_settings = fx_settings.ssao\r\n thumbnails_path = get_directory('icons')\r\n extentions = (\".jpg\", \".jpeg\", \".png\")\r\n thumb_list = [thumb.rsplit(\".\", 1)[0] for thumb in listdir(thumbnails_path) if thumb.endswith(extentions)]\r\n \r\n if AM.scene_name not in thumb_list or AM.scene_name in thumb_list and AM.replace_rename == 'replace':\r\n if AM.scene_name in thumb_list and AM.replace_rename == 'replace':\r\n box.label(\"\\\" {} \\\" already exist\".format(AM.scene_name), icon='ERROR')\r\n box.separator()\r\n row = box.row(align=True)\r\n row.prop(AM, \"replace_rename\", text=\" \", expand=True)\r\n if AM.replace_rename == 'rename':\r\n box.prop(AM, \"scene_name\", text=\"\")\r\n \r\n row = box.row(align = True)\r\n row.label(\"Scene name:\")\r\n row.prop(AM, \"scene_name\", text = \"\")\r\n row = box.row(align = True)\r\n row.prop(AM, \"render_type\", text = \" \", expand = True)\r\n row = box.row()\r\n row.label(\"Thumbnail extention:\")\r\n row = box.row(align = True)\r\n row.prop(AM, \"thumb_ext\", expand = True)\r\n\r\n # --------------------- # \r\n # OPENGL THUMBNAIL #\r\n # --------------------- #\r\n \r\n if AM.render_type == 'opengl':\r\n row = box.row(align=True)\r\n row.operator(\"object.setup_ogl_render\", text=\"Setup OGL render\" if not \"AM_OGL_Camera\" in [obj.name for obj in context.scene.objects] else \"View camera\", icon='ZOOMIN')\r\n row.operator(\"object.remove_ogl_render\", text=\"\", icon='ZOOMOUT')\r\n row = layout.column()\r\n row = box.row(align=True) \r\n row.label(\"Background:\")\r\n row.prop(AM, \"background_alpha\", text=\"\")\r\n row = box.row(align=True)\r\n row.prop(view, \"show_only_render\")\r\n row = box.row(align=True)\r\n row.prop(view, \"use_matcap\")\r\n if view.use_matcap :\r\n row.prop(AM, \"matcap_options\", text=\"\", icon='TRIA_UP' if AM.matcap_options else 'TRIA_DOWN') \r\n if AM.matcap_options:\r\n row = box.row(align=True)\r\n row.template_icon_view(view, \"matcap_icon\")\r\n row = box.row(align=True)\r\n row.prop(fx_settings, \"use_ssao\", text=\"Ambient Occlusion\")\r\n if fx_settings.use_ssao:\r\n row.prop(AM, \"ao_options\", text=\"\", icon='TRIA_UP' if AM.ao_options else 'TRIA_DOWN') \r\n if AM.ao_options:\r\n subcol = box.column(align=True)\r\n subcol.prop(ssao_settings, \"factor\")\r\n subcol.prop(ssao_settings, \"distance_max\")\r\n subcol.prop(ssao_settings, \"attenuation\")\r\n subcol.prop(ssao_settings, \"samples\")\r\n subcol.prop(ssao_settings, \"color\")\r\n \r\n # -------------------- # \r\n # IMAGE THUMBNAIL #\r\n # -------------------- #\r\n \r\n elif AM.render_type == 'image':\r\n row = box.row(align=True)\r\n row.prop(AM, \"image_type\", text=\" \", expand=True)\r\n if AM.image_type == 'disk':\r\n box.label(\"Choose your thumbnail\")\r\n box.prop(AM, \"custom_thumbnail_path\", text=\"\")\r\n else:\r\n box.prop_search(AM, \"render_name\", bpy.data, \"images\", text=\"\") \r\n \r\n row = box.row(align=True)\r\n \r\n if AM.scene_name and ((AM.scene_name not in thumb_list or AM.replace_rename == 'replace') and AM.render_type == 'opengl' or AM.render_type == 'image' and (AM.image_type == 'disk' and AM.custom_thumbnail_path or AM.image_type == 'rendered' and AM.render_name)):\r\n \r\n row.operator(\"object.add_scene_in_library\", text=\"OK\", icon='FILE_TICK') \r\n row.operator(\"object.cancel_panel_choise\", text=\"Cancel\", icon='X')\r\n \r\n else:\r\n box.label(\"\\\" {} \\\" already exist\".format(AM.scene_name), icon='ERROR')\r\n box.separator()\r\n row = box.row(align=True)\r\n row.prop(AM, \"replace_rename\", text=\" \", expand=True)\r\n if AM.replace_rename == 'rename':\r\n box.prop(AM, \"scene_name\", text=\"\")\r\n row = box.row()\r\n row.operator(\"object.cancel_panel_choise\", text=\"Cancel\", icon='X')","def enableEditorDrop():\n\n perspPanel = cmds.getPanel( withLabel='Persp View')\n panelControl = cmds.panel( perspPanel, query=True, control=True)\n cmds.control(panelControl, edit=True, dropCallback=panelDropLoad)\n global viewportHeight\n viewportHeight = cmds.control(panelControl, query=True, h=True)","def ibl_options_panel(self, context):\r\n \r\n AM = context.window_manager.asset_m\r\n node_group = bpy.context.scene.world.node_tree.nodes\r\n layout = self.layout\r\n \r\n box = layout.box()\r\n row = box.row()\r\n row.alignment = 'CENTER'\r\n row.label(\"IMAGE\")\r\n row = box.row(align = True)\r\n row.label(\"Rotation:\")\r\n col = row.column()\r\n col.prop(node_group[\"Mapping\"], \"rotation\", text = \"\")\r\n row = box.row(align = True)\r\n row.label(\"Projection:\")\r\n row.prop(AM, \"projection\", text = \"\")\r\n row = box.row(align = True)\r\n row.label(\"Blur:\")\r\n row.prop(node_group[\"ImageBlur\"].inputs[1], \"default_value\", text = \"\")\r\n row = box.row(align = True)\r\n row.label(\"Visible:\")\r\n row.prop(bpy.context.scene.world.cycles_visibility, \"camera\")\r\n row = box.row(align = True)\r\n row.label(\"Transparent:\")\r\n row.prop(bpy.context.scene.cycles, \"film_transparent\")\r\n \r\n \r\n \r\n box = layout.box()\r\n row = box.row(align = True)\r\n row.label(\"Gamma:\")\r\n row.prop(node_group[\"AM_IBL_Tool\"].inputs[0], \"default_value\", text = \"\")\r\n \r\n box = layout.box()\r\n row = box.row()\r\n row.alignment = 'CENTER'\r\n row.label(\"LIGHT\")\r\n row = box.row(align = True)\r\n row.label(\"Strength:\")\r\n row.prop(node_group[\"AM_IBL_Tool\"].inputs[2], \"default_value\", text = \"\")\r\n row = box.row(align = True)\r\n row.label(\"Saturation:\")\r\n row.prop(node_group[\"AM_IBL_Tool\"].inputs[3], \"default_value\", text = \"\")\r\n row = box.row(align = True)\r\n row.label(\"Hue:\")\r\n row.prop(node_group[\"AM_IBL_Tool\"].inputs[4], \"default_value\", text = \"\")\r\n row = box.row(align = True)\r\n row.label(\"Mix Hue:\")\r\n row.prop(node_group[\"AM_IBL_Tool\"].inputs[5], \"default_value\", text = \"\")\r\n \r\n box = layout.box()\r\n row = box.row()\r\n row.alignment = 'CENTER'\r\n row.label(\"GLOSSY\")\r\n row = box.row(align = True)\r\n row.label(\"Strength:\")\r\n row.prop(node_group[\"AM_IBL_Tool\"].inputs[7], \"default_value\", text = \"\")\r\n row = box.row(align = True)\r\n row.label(\"Saturation:\")\r\n row.prop(node_group[\"AM_IBL_Tool\"].inputs[8], \"default_value\", text = \"\")\r\n row = box.row(align = True)\r\n row.label(\"Hue:\")\r\n row.prop(node_group[\"AM_IBL_Tool\"].inputs[9], \"default_value\", text = \"\")\r\n row = box.row(align = True)\r\n row.label(\"Mix Hue:\")\r\n row.prop(node_group[\"AM_IBL_Tool\"].inputs[10], \"default_value\", text = \"\")\r\n \r\n layout.operator(\"wm.save_ibl_settings\", text = \"Save settings\", icon = 'FILE_TICK')","def layout_graphics(self):\n # Graphics layout object to place viewboxes in\n self.g_layout = pg.GraphicsLayoutWidget(border=(80, 80, 80))\n self.g_layout.setCursor(QtCore.Qt.CrossCursor)\n\n # Viewboxes for images\n # aspect locked so that pixels are square\n # y inverted so that (0,0) is top left as in Thorlabs software\n options = {\"lockAspect\":True, \"invertY\":True}\n self.vb_image = self.g_layout.addViewBox(row=0, col=0, rowspan=2, **options)\n self.vb_zoom = self.g_layout.addViewBox(row=0, col=2, **options)\n self.vb_residuals = self.g_layout.addViewBox(row=1, col=2, **options)\n\n # Link zoom and residual views\n self.vb_zoom.setXLink(self.vb_residuals)\n self.vb_zoom.setYLink(self.vb_residuals)\n\n # Viewboxes for slice data\n # Both boxes have mouse disabled - range is fixed so we don't want to\n # scale them accidentally\n # Y box has y inverted to match the main image\n # Y box has x inverted so that zero pixel value is far from the image\n options = {\"enableMouse\":False, \"enableMenu\": False}\n self.vb_x = self.g_layout.addViewBox(row=2, col=0, **options)\n self.vb_y = self.g_layout.addViewBox(row=0, col=1, rowspan=2,\n invertX=True, invertY=True, **options)\n\n # Link the slice axes to the main image so that when we zoom/pan the\n # main image, our slices zoom/pan also\n self.vb_x.setXLink(self.vb_image)\n self.vb_y.setYLink(self.vb_image)\n\n # Disable autoscaling and fix range to maximum pixel intensity\n self.vb_x.setRange(yRange=(0,255))\n self.vb_y.setRange(xRange=(0,255))\n self.vb_x.disableAutoRange(axis=self.vb_x.YAxis)\n self.vb_y.disableAutoRange(axis=self.vb_y.XAxis)\n\n # Background color must not be black so that we can see where images\n # start/end\n color = pg.mkColor(40,40,40)\n self.vb_image.setBackgroundColor(color)\n self.vb_zoom.setBackgroundColor(color)\n self.vb_residuals.setBackgroundColor(color)\n self.vb_x.setBackgroundColor(color)\n self.vb_y.setBackgroundColor(color)\n self.g_layout.setBackground(color)\n\n self.vb_image.addItem(self.image)\n self.vb_image.addItem(self.fit_v_line)\n self.vb_image.addItem(self.fit_h_line)\n self.vb_image.addItem(self.mark_v_line)\n self.vb_image.addItem(self.mark_h_line)\n # self.vb_image.addItem(self.cursor_text)\n self.vb_image.addItem(self.cursor_delta)\n self.vb_image.addItem(self.beam_delta)\n self.vb_image.addItem(self.history_plot)\n # Figure out how to overlay properly?\n # self.vb_image.addItem(self.x_slice)\n # self.vb_image.addItem(self.x_fit)\n # self.vb_image.addItem(self.y_slice)\n # self.vb_image.addItem(self.y_fit)\n self.vb_zoom.addItem(self.zoom)\n self.vb_zoom.addItem(self.fit_maj_line)\n self.vb_zoom.addItem(self.fit_min_line)\n self.vb_zoom.addItem(self.zoom_text)\n self.vb_residuals.addItem(self.residuals)\n self.vb_residuals.addItem(self.residuals_text)\n self.vb_x.addItem(self.x_slice)\n self.vb_x.addItem(self.x_fit)\n self.vb_x.addItem(self.cursor_v)\n self.vb_y.addItem(self.y_slice)\n self.vb_y.addItem(self.y_fit)\n self.vb_y.addItem(self.cursor_h)\n\n self.res_legend.setParentItem(self.vb_residuals)\n self.cursor_text.setParentItem(self.vb_image)\n\n self.vb_image.setRange(QtCore.QRectF(0, 0, 1280, 1024))\n self.vb_zoom.setRange(QtCore.QRectF(0, 0, 50, 50))\n self.vb_residuals.setRange(QtCore.QRectF(0, 0, 50, 50))\n\n #\n # Size hints below here\n #\n self.g_layout.ci.layout.setColumnStretchFactor(0, 4)\n self.g_layout.ci.layout.setColumnStretchFactor(1, 1)\n self.g_layout.ci.layout.setColumnStretchFactor(2, 2)\n self.g_layout.ci.layout.setRowStretchFactor(0, 2)\n self.g_layout.ci.layout.setRowStretchFactor(1, 2)\n self.g_layout.ci.layout.setRowStretchFactor(2, 1)\n\n self.vb_x.setMinimumHeight(50)\n self.vb_y.setMinimumWidth(50)\n self.vb_x.setMaximumHeight(100)\n self.vb_y.setMaximumWidth(100)\n self.vb_image.setMinimumSize(640, 512)\n self.vb_zoom.setMinimumSize(320, 320)\n self.vb_residuals.setMinimumSize(320, 320)\n\n self.g_layout.setMinimumSize(1100,562)","def setup_mpl_visuals(self, axes=None) -> None:\n if axes is None:\n axes = self.subplot\n axes.patch.set_facecolor('white')\n axes.set_aspect('equal', 'box')\n axes.set_xlim(-10, 10, auto=True)\n axes.set_ylim(-10, 10, auto=True)\n # TODO: Make XYLim confort to window size/dimensions\n axes.set_xticks([])\n axes.set_yticks([])\n self.figure.subplots_adjust(bottom=0, top=1, left=0, right=1)\n axes.axis('off')","def drawCoordinatePlane_region():\r\n turtle2 = t.Screen()\r\n turtle2.title(\"Life Expectancy versus Region\")\r\n t2.speed(0)\r\n t3.speed(0)\r\n setTurtle(t0)\r\n setTurtle(t1)\r\n setTurtle(t2)\r\n setTurtle(t3)\r\n drawAxes(t0)\r\n t1.left(90)\r\n drawAxes(t1)\r\n t0.pu()\r\n t0.fd(-80)\r\n t0.lt(90)\r\n drawlabels(t0, t1)\r\n drawPoints(t0, t1)\r\n t0.pu()\r\n t1.pu()\r\n t2.pu()\r\n t3.pu()\r\n t0.goto(initialCoordinates())\r\n t1.goto(initialCoordinates())\r\n t2.goto(initialCoordinates())\r\n t3.goto(initialCoordinates())\r\n t1.lt(90)","def forward_phi(self):\n for f in self.component_fields:\n f.require_layout(self._layout1)","def page_up(self):\n self.set_initial_offset(self.initial_offset - self.my_surface.get_height())","def translate(self, vect):\n self.pl.Base = vect\n\n self.comp.Placement = self.pl\n self.box.Placement = self.pl","def postInit(self):\n self.save_transform = [\"root\", \"top\", \"bottom\", \"ext\", \"int\"]","def setup_pipeline(self):\n # Create the axes and set things up.\n axes = CubeAxesActor2D(number_of_labels= 2,\n font_factor=1.5,\n fly_mode='outer_edges',\n corner_offset=0.0,\n scaling=False)\n axes.axis_title_text_property.shadow = False\n axes.axis_label_text_property.shadow = False\n\n # Set the axes.\n self.axes = axes","def DrawPanel(screen, panel_x, panel_y, panel_len, panel_width):\n pygame.draw.rect(screen, (255,0,0),(panel_x, panel_y, panel_len*2, panel_width*2), 4)","def test_panel(self):\n p = MailToolbarPanel(*self.panel_args)\n self.assertEqual(p.toolbar, self.toolbar)","def render(self):\n\n theta = self.angle*math.pi/180.0\n cth = math.cos(theta)\n sth = math.sin(theta)\n pts = []\n cornerpts = []\n\n for vertex in self.points:\n x = vertex[0] + self.pos[0] - self.anchor[0]\n y = vertex[1] + self.pos[1] - self.anchor[1]\n\n xt = x * cth - y * sth\n yt = x * sth + y * cth\n\n x = xt + self.anchor[0]\n y = yt + self.anchor[1]\n\n cornerpts.append([x,y])\n pts.append(gr.Point(self.scale * x, self.win.getHeight() - self.scale*y))\n\n self.corners = cornerpts\n self.vis = [gr.Polygon(pts)]","def Bas():\r\n X1, Y1, X2, Y2 = canvas.coords(boule)\r\n canvas.coords(boule,X1,Y1+20,X2,Y2+20)","def frame():\n fig = plt.figure(figsize = (6, 3))\n\n plt.subplots_adjust(left=.15, bottom=.2, right=.95, top=.9)\n ax = fig.add_subplot(111)\n \n ax.tick_params(axis=\"x\", labelsize=12)\n ax.tick_params(axis=\"y\", labelsize=12)\n\n return fig, ax","def layoutRightPanel(self):\n nRow = 0\n self.rightPanel.removeAll()\n self.rightPanel.add(JLabel(\"State machine cache?\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n __nRow_5 = nRow\n nRow += 1\n self.rightPanel.add(self.cacheStateMachine, GridBagConstraints(1, __nRow_5, 1, 1, 1.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n if self.strategy.getSelectedItem().__str__() == \"Heuristic\":\n __nRow_6 = nRow\n nRow += 1\n __nRow_7 = nRow\n nRow += 1\n __nRow_8 = nRow\n nRow += 1\n __nRow_9 = nRow\n nRow += 1\n __nRow_10 = nRow\n nRow += 1\n self.rightPanel.add(JLabel(\"Max plys?\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n self.rightPanel.add(self.maxPlys, GridBagConstraints(1, __nRow_6, 1, 1, 0.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n self.rightPanel.add(JLabel(\"Focus Heuristic Weight\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n self.rightPanel.add(self.heuristicFocus, GridBagConstraints(1, __nRow_7, 1, 1, 0.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n self.rightPanel.add(JLabel(\"Mobility Heuristic Weight\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n self.rightPanel.add(self.heuristicMobility, GridBagConstraints(1, __nRow_8, 1, 1, 0.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n self.rightPanel.add(JLabel(\"Opponent Focus Heuristic Weight\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n self.rightPanel.add(self.heuristicOpponentFocus, GridBagConstraints(1, __nRow_9, 1, 1, 0.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n self.rightPanel.add(JLabel(\"Opponent Mobility Heuristic Weight\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n self.rightPanel.add(self.heuristicOpponentMobility, GridBagConstraints(1, __nRow_10, 1, 1, 0.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n if self.strategy.getSelectedItem().__str__() == \"Monte Carlo\":\n __nRow_11 = nRow\n nRow += 1\n self.rightPanel.add(JLabel(\"Goal Decay Rate\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n self.rightPanel.add(self.mcDecayRate, GridBagConstraints(1, __nRow_11, 1, 1, 0.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n __nRow_12 = nRow\n nRow += 1\n self.rightPanel.add(JLabel(), GridBagConstraints(2, __nRow_12, 1, 1, 1.0, 1.0, GridBagConstraints.SOUTHEAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\n self.rightPanel.repaint()","def add_lattice(): \n # Switch in object mode\n bpy.ops.object.mode_set(mode='OBJECT') \n \n # Get the active object\n obj = bpy.context.active_object\n \n # Check if there is a lattice object\n flagLattice = False\n for o in bpy.data.objects:\n if o.type == 'LATTICE':\n flagLattice = True\n \n # Add a lattice if there is not\n if flagLattice == False:\n # Get the name of the object\n nameObject = obj.name\n \n # Add the lattice\n bpy.ops.object.add(type='LATTICE', enter_editmode=False, align='WORLD', location=(0, 0, 0), scale=(1, 1, 1))\n \n # Select the object\n bpy.context.view_layer.objects.active = bpy.data.objects[nameObject]\n bpy.data.objects[nameObject].select_set(True)\n bpy.data.objects[\"Lattice\"].select_set(False)\n \n\n\n # Add the vertices location in an array and find the max and min coordinates of the mesh\n tabVertices = []\n xPlus = float('-inf')\n xMoins = float('inf')\n yPlus = float('-inf')\n yMoins = float('inf')\n zPlus = float('-inf')\n zMoins = float('inf')\n for vertex in obj.data.vertices:\n tabVertices.append(obj.matrix_world @ vertex.co)\n if xPlus < (obj.matrix_world @ vertex.co).x:\n xPlus = (obj.matrix_world @ vertex.co).x\n elif xMoins > (obj.matrix_world @ vertex.co).x:\n xMoins = (obj.matrix_world @ vertex.co).x\n \n if yPlus < (obj.matrix_world @ vertex.co).y:\n yPlus = (obj.matrix_world @ vertex.co).y\n elif yMoins > (obj.matrix_world @ vertex.co).y:\n yMoins = (obj.matrix_world @ vertex.co).y\n \n if zPlus < (obj.matrix_world @ vertex.co).z:\n zPlus = (obj.matrix_world @ vertex.co).z\n elif zMoins > (obj.matrix_world @ vertex.co).z:\n zMoins = (obj.matrix_world @ vertex.co).z\n\n # Set the size and the location of the lattice\n bpy.data.objects[\"Lattice\"].scale = (obj.dimensions[0], obj.dimensions[1], obj.dimensions[2])\n bpy.data.objects[\"Lattice\"].location = ((xPlus+xMoins)/2, (yPlus+yMoins)/2,(zPlus+zMoins)/2)\n\n # Update the float properties of the lattice and init them\n bpy.types.Scene.lattice_size_x = bpy.props.FloatProperty(name = \"Size X\", min = 0, max = 2*obj.dimensions[0], soft_min = 0, soft_max = 2*obj.dimensions[0], step = 10, get=Get_And_Set_Lattice.get_lattice_size_x, set=Get_And_Set_Lattice.set_lattice_size_x, unit = 'LENGTH')\n bpy.types.Scene.lattice_size_y = bpy.props.FloatProperty(name = \"Size Y\", min = 0, max = 2*obj.dimensions[1], soft_min = 0, soft_max = 2*obj.dimensions[1], step = 10, get=Get_And_Set_Lattice.get_lattice_size_y, set=Get_And_Set_Lattice.set_lattice_size_y, unit = 'LENGTH')\n bpy.types.Scene.lattice_size_z = bpy.props.FloatProperty(name = \"Size Z\", min = 0, max = 2*obj.dimensions[2], soft_min = 0, soft_max = 2*obj.dimensions[2], step = 10, get=Get_And_Set_Lattice.get_lattice_size_z, set=Get_And_Set_Lattice.set_lattice_size_z, unit = 'LENGTH')\n \n bpy.context.scene.lattice_size_x = obj.dimensions[0]\n bpy.context.scene.lattice_size_y = obj.dimensions[1]\n bpy.context.scene.lattice_size_z = obj.dimensions[2]\n \n bpy.types.Scene.lattice_offset_x = bpy.props.FloatProperty(name = \"Size X\", min = -obj.dimensions[0], max = obj.dimensions[0], soft_min = -obj.dimensions[0], soft_max = obj.dimensions[0], step = 10, get=Get_And_Set_Lattice.get_lattice_offset_x, set=Get_And_Set_Lattice.set_lattice_offset_x, unit = 'LENGTH')\n bpy.types.Scene.lattice_offset_y = bpy.props.FloatProperty(name = \"Size Y\", min = -obj.dimensions[1], max = obj.dimensions[1], soft_min = -obj.dimensions[1], soft_max = obj.dimensions[1], step = 10, get=Get_And_Set_Lattice.get_lattice_offset_y, set=Get_And_Set_Lattice.set_lattice_offset_y, unit = 'LENGTH')\n bpy.types.Scene.lattice_offset_z = bpy.props.FloatProperty(name = \"Size Z\", min = -obj.dimensions[2], max = obj.dimensions[2], soft_min = -obj.dimensions[2], soft_max = obj.dimensions[2], step = 10, get=Get_And_Set_Lattice.get_lattice_offset_z, set=Get_And_Set_Lattice.set_lattice_offset_z, unit = 'LENGTH')\n \n bpy.context.scene.lattice_offset_x = 0\n bpy.context.scene.lattice_offset_y = 0\n bpy.context.scene.lattice_offset_z = 0","def reshape(self,bottom,top):\n pass","def hflip(self):\n self.leftimg, self.rightimg = self.rightimg, self.leftimg","def _create_canvas(self, parent):\n # The panel lets us add additional controls.\n panel = wx.Panel(parent, -1, style=wx.CLIP_CHILDREN)\n sizer = wx.BoxSizer(wx.VERTICAL)\n panel.SetSizer(sizer)\n # matplotlib commands to create a canvas\n mpl_control = FigureCanvas(panel, -1, self.value)\n sizer.Add(mpl_control, 1, wx.LEFT | wx.TOP | wx.GROW)\n toolbar = NToolbar(mpl_control)\n sizer.Add(toolbar, 0, wx.EXPAND)\n self.value.canvas.SetMinSize((10,10))\n return panel","def orientWP(self):\n import DraftGeomUtils\n if hasattr(App, \"DraftWorkingPlane\"):\n if len(self.node) > 1 and self.obj:\n n = DraftGeomUtils.getNormal(self.obj.Shape)\n if not n:\n n = App.DraftWorkingPlane.axis\n p = self.node[-1]\n v = self.node[-2].sub(self.node[-1])\n v = v.negative()\n if not self.oldWP:\n self.oldWP = App.DraftWorkingPlane.copy()\n App.DraftWorkingPlane.alignToPointAndAxis(p, n, upvec=v)\n if hasattr(Gui, \"Snapper\"):\n Gui.Snapper.setGrid()\n Gui.Snapper.restack()\n if self.planetrack:\n self.planetrack.set(self.node[-1])","def draw(self, screen):\n self.draw_left_zone(screen)\n self.draw_middle_zone(screen)\n self.draw_right_zone(screen)","def recalculate_transform(self):\n bias_mat = wireframe.translationMatrix(*self.bias)\n rot_mat = wireframe.rotateMatrix(*self.view_angle)\n scale_mat = wireframe.scaleMatrix(*self.scale)\n\n self.tf_wireframe.nodes = (self.wireframe.nodes - self._center_half) @ \\\n rot_mat @ scale_mat @ bias_mat","def Split(self, page, direction):\r\n \r\n cli_size = self.GetClientSize()\r\n\r\n # get the page's window pointer\r\n wnd = self.GetPage(page)\r\n if not wnd:\r\n return\r\n\r\n # notebooks with 1 or less pages can't be split\r\n if self.GetPageCount() < 2:\r\n return\r\n\r\n # find out which tab control the page currently belongs to\r\n\r\n src_tabs, src_idx = self.FindTab(wnd)\r\n if not src_tabs:\r\n return\r\n \r\n # choose a split size\r\n if self.GetPageCount() > 2:\r\n split_size = self.CalculateNewSplitSize()\r\n else: \r\n # because there are two panes, always split them\r\n # equally\r\n split_size = self.GetClientSize()\r\n split_size.x /= 2\r\n split_size.y /= 2\r\n\r\n # create a new tab frame\r\n new_tabs = TabFrame(self)\r\n new_tabs._rect = wx.RectPS(wx.Point(0, 0), split_size)\r\n new_tabs.SetTabCtrlHeight(self._tab_ctrl_height)\r\n self._tab_id_counter += 1\r\n new_tabs._tabs = AuiTabCtrl(self, self._tab_id_counter)\r\n \r\n new_tabs._tabs.SetArtProvider(self._tabs.GetArtProvider().Clone())\r\n new_tabs._tabs.SetAGWFlags(self._agwFlags)\r\n dest_tabs = new_tabs._tabs\r\n\r\n page_info = src_tabs.GetPage(src_idx)\r\n if page_info.control:\r\n self.ReparentControl(page_info.control, dest_tabs)\r\n \r\n # create a pane info structure with the information\r\n # about where the pane should be added\r\n pane_info = framemanager.AuiPaneInfo().Bottom().CaptionVisible(False)\r\n\r\n if direction == wx.LEFT:\r\n \r\n pane_info.Left()\r\n mouse_pt = wx.Point(0, cli_size.y/2)\r\n \r\n elif direction == wx.RIGHT:\r\n \r\n pane_info.Right()\r\n mouse_pt = wx.Point(cli_size.x, cli_size.y/2)\r\n \r\n elif direction == wx.TOP:\r\n \r\n pane_info.Top()\r\n mouse_pt = wx.Point(cli_size.x/2, 0)\r\n \r\n elif direction == wx.BOTTOM:\r\n \r\n pane_info.Bottom()\r\n mouse_pt = wx.Point(cli_size.x/2, cli_size.y)\r\n \r\n self._mgr.AddPane(new_tabs, pane_info, mouse_pt)\r\n self._mgr.Update()\r\n\r\n # remove the page from the source tabs\r\n page_info.active = False\r\n \r\n src_tabs.RemovePage(page_info.window)\r\n \r\n if src_tabs.GetPageCount() > 0:\r\n src_tabs.SetActivePage(0)\r\n src_tabs.DoShowHide()\r\n src_tabs.Refresh()\r\n \r\n # add the page to the destination tabs\r\n dest_tabs.InsertPage(page_info.window, page_info, 0)\r\n\r\n if src_tabs.GetPageCount() == 0:\r\n self.RemoveEmptyTabFrames()\r\n \r\n self.DoSizing()\r\n dest_tabs.DoShowHide()\r\n dest_tabs.Refresh()\r\n\r\n # force the set selection function reset the selection\r\n self._curpage = -1\r\n\r\n # set the active page to the one we just split off\r\n self.SetSelectionToPage(page_info)\r\n\r\n self.UpdateHintWindowSize()","def __set_paddle_position(self):\n self.__window.remove(self.__paddle)\n self.__window.add(self.__paddle, (self.__window.width - self.__paddle.width) / 2,\n self.__window.height - self.__paddle_offset)","def __init__(self, cut_coords, axes=None, black_bg=False):\n self._cut_coords = cut_coords\n if axes is None:\n axes = pl.axes((0., 0., 1., 1.))\n axes.axis('off')\n self.frame_axes = axes\n axes.set_zorder(1)\n bb = axes.get_position()\n self.rect = (bb.x0, bb.y0, bb.x1, bb.y1)\n self._black_bg = black_bg\n self._init_axes()"],"string":"[\n \"def create_main_panel(self):\\n self.panel = wx.Panel(self)\\n\\n self.init_plot()\\n self.canvas = FigCanvas(self.panel, -1, self.fig)\\n\\n self.control_box = VSControlBox(self.panel, -1, 'Information board')\\n\\n self.vbox = wx.BoxSizer(wx.VERTICAL)\\n self.vbox.Add(self.canvas, 1, wx.LEFT | wx.TOP | wx.GROW)\\n self.vbox.Add(self.control_box, 0, wx.ALIGN_LEFT | wx.TOP | wx.EXPAND)\\n \\n self.panel.SetSizer(self.vbox)\\n self.vbox.Fit(self)\",\n \"def create(self):\\n self.panel = pg.rect.Rect(self.position, self.dimensions)\",\n \"def get_band_panel(self):\\n return pn.Column(\\n pn.Column(\\n pn.Row(self.get_controls(), margin = (0, 0, -25, 0)),\\n pn.pane.HoloViews(self.get_band_dmap(), linked_axes=False)\\n ), \\n )\",\n \"def box_transform_panels(page, type_choice=None, pattern=None):\\n\\n if type_choice is None:\\n type_choice_prob = np.random.random()\\n if type_choice_prob < cfg.panel_box_trapezoid_ratio:\\n type_choice = \\\"trapezoid\\\"\\n else:\\n type_choice = \\\"rhombus\\\"\\n\\n if type_choice == \\\"trapezoid\\\":\\n if page.num_panels > 2:\\n\\n # Get parent panel which satisfies the criteria for the transform\\n relevant_panels = find_parent_with_multiple_children(page, 3)\\n\\n if len(relevant_panels) > 0:\\n if len(relevant_panels) > 1:\\n num_panels = np.random.randint(1, len(relevant_panels))\\n else:\\n num_panels = 1\\n\\n # For each panel\\n for idx in range(0, num_panels):\\n panel = relevant_panels[idx]\\n\\n # Get the three child panels\\n # Since panels are created in order\\n p1 = panel.get_child(0)\\n p2 = panel.get_child(1)\\n p3 = panel.get_child(2)\\n\\n min_width = math.inf\\n min_height = math.inf\\n\\n # Get the smallest height and width\\n for child in [p1, p2, p3]:\\n\\n if child.width < min_width:\\n min_width = child.width\\n\\n if child.height < min_height:\\n min_height = child.height\\n\\n # Choose trapezoid pattern\\n if pattern is None:\\n trapezoid_pattern = np.random.choice([\\\"A\\\", \\\"V\\\"])\\n else:\\n trapezoid_pattern = pattern\\n\\n movement_proportion = np.random.randint(\\n 10,\\n cfg.trapezoid_movement_limit)\\n\\n # If parent panel is horizontal the children are vertical\\n if panel.orientation == \\\"h\\\":\\n\\n # Get how much the lines of the child panels move\\n # on the x axis to make the trapezoid\\n x_movement = min_width*(movement_proportion/100)\\n\\n # Make an A pattern horizontally\\n if trapezoid_pattern == \\\"A\\\":\\n\\n # Get the coords of the first line to be moved\\n line_one_top = (p1.x2y2[0] + x_movement,\\n p1.x2y2[1])\\n\\n line_one_bottom = (p1.x3y3[0] - x_movement,\\n p1.x3y3[1])\\n\\n # Move line between child 1 and 2\\n p1.x2y2 = line_one_top\\n p1.x3y3 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = line_one_top\\n p2.x4y4 = line_one_bottom\\n\\n # Get the coords of the second line to be moved\\n line_two_top = (p2.x2y2[0] - x_movement,\\n p2.x2y2[1])\\n line_two_bottom = (p2.x3y3[0] + x_movement,\\n p2.x3y3[1])\\n\\n # Move line two between child 2 and 3\\n p2.x2y2 = line_two_top\\n p2.x3y3 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_top\\n p3.x4y4 = line_two_bottom\\n\\n p3.refresh_coords()\\n\\n # Make a V pattern horizontally\\n else:\\n\\n # Get the coords of the first line to be moved\\n line_one_top = (p1.x2y2[0] - x_movement,\\n p1.x2y2[1])\\n\\n line_one_bottom = (p1.x3y3[0] + x_movement,\\n p1.x3y3[1])\\n\\n # Move line between child 1 and 2\\n p1.x2y2 = line_one_top\\n p1.x3y3 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = line_one_top\\n p2.x4y4 = line_one_bottom\\n\\n # Get the coords of the second line to be moved\\n line_two_top = (p2.x2y2[0] + x_movement,\\n p2.x2y2[1])\\n\\n line_two_bottom = (p2.x3y3[0] - x_movement,\\n p2.x3y3[1])\\n\\n # Move line two between child 2 and 3\\n p2.x2y2 = line_two_top\\n p2.x3y3 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_top\\n p3.x4y4 = line_two_bottom\\n\\n p3.refresh_coords()\\n\\n # If panel is vertical children are horizontal\\n # so the A and the V are at 90 degrees to the page\\n else:\\n # Get how much the lines of the child panels move\\n # on the y axis to make the trapezoid\\n y_movement = min_height*(movement_proportion/100)\\n\\n # Make an A pattern vertically\\n if trapezoid_pattern == \\\"A\\\":\\n\\n # Get the coords of the first line to be moved\\n line_one_top = (p2.x2y2[0],\\n p2.x2y2[1] + y_movement)\\n\\n line_one_bottom = (p2.x1y1[0],\\n p2.x1y1[1] - y_movement)\\n\\n # Move line between child 1 and 2\\n p2.x2y2 = line_one_top\\n p2.x1y1 = line_one_bottom\\n\\n p1.x3y3 = line_one_top\\n p1.x4y4 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n # Get the coords of the second line to be moved\\n line_two_top = (p2.x3y3[0],\\n p2.x3y3[1] - y_movement)\\n\\n line_two_bottom = (p2.x4y4[0],\\n p2.x4y4[1] + y_movement)\\n\\n # Move line two between child 2 and 3\\n p2.x3y3 = line_two_top\\n p2.x4y4 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_bottom\\n p3.x2y2 = line_two_top\\n\\n p3.refresh_coords()\\n # Make a V pattern vertically\\n else:\\n\\n # Get the coords of the first line to be moved\\n line_one_top = (p2.x2y2[0],\\n p2.x2y2[1] - y_movement)\\n\\n line_one_bottom = (p2.x1y1[0],\\n p2.x1y1[1] + y_movement)\\n\\n # Move line between child 1 and 2\\n p2.x2y2 = line_one_top\\n p2.x1y1 = line_one_bottom\\n\\n p1.x3y3 = line_one_top\\n p1.x4y4 = line_one_bottom\\n\\n p1.refresh_coords()\\n # Get the coords of the second line to be moved\\n line_two_top = (p2.x3y3[0],\\n p2.x3y3[1] + y_movement)\\n\\n line_two_bottom = (p2.x4y4[0],\\n p2.x4y4[1] - y_movement)\\n\\n # Move line two between child 2 and 3\\n p2.x3y3 = line_two_top\\n p2.x4y4 = line_two_bottom\\n\\n p2.refresh_coords()\\n p3.x1y1 = line_two_bottom\\n p3.x2y2 = line_two_top\\n\\n p3.refresh_coords()\\n\\n elif type_choice == \\\"rhombus\\\":\\n\\n if page.num_panels > 1:\\n\\n # Get parent panel which satisfies the criteria for the transform\\n relevant_panels = find_parent_with_multiple_children(page, 3)\\n\\n if len(relevant_panels) > 0:\\n\\n if len(relevant_panels) > 1:\\n num_panels = np.random.randint(1, len(relevant_panels))\\n else:\\n num_panels = 1\\n\\n for idx in range(0, num_panels):\\n\\n panel = relevant_panels[idx]\\n\\n # Since panels are created in order\\n p1 = panel.get_child(0)\\n p2 = panel.get_child(1)\\n p3 = panel.get_child(2)\\n\\n min_width = math.inf\\n min_height = math.inf\\n\\n # Get the smallest height and width\\n for child in [p1, p2, p3]:\\n\\n if child.width < min_width:\\n min_width = child.width\\n\\n if child.height < min_height:\\n min_height = child.height\\n\\n if pattern is None:\\n rhombus_pattern = np.random.choice([\\\"left\\\", \\\"right\\\"])\\n else:\\n rhombus_pattern = pattern\\n\\n movement_proportion = np.random.randint(\\n 10,\\n cfg.rhombus_movement_limit\\n )\\n\\n # Logic for the section below is the same as the\\n # trapezoid with the exception of the fact that the\\n # rhombus pattern happens to move both lines in the\\n # same direction\\n\\n if panel.orientation == \\\"h\\\":\\n\\n x_movement = min_width*(movement_proportion/100)\\n\\n if rhombus_pattern == \\\"left\\\":\\n line_one_top = (p1.x2y2[0] - x_movement,\\n p1.x2y2[1])\\n\\n line_one_bottom = (p1.x3y3[0] + x_movement,\\n p1.x3y3[1])\\n\\n p1.x2y2 = line_one_top\\n p1.x3y3 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = line_one_top\\n p2.x4y4 = line_one_bottom\\n\\n line_two_top = (p2.x2y2[0] - x_movement,\\n p2.x2y2[1])\\n\\n line_two_bottom = (p2.x3y3[0] + x_movement,\\n p2.x3y3[1])\\n\\n p2.x2y2 = line_two_top\\n p2.x3y3 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_top\\n p3.x4y4 = line_two_bottom\\n\\n p3.refresh_coords()\\n\\n else:\\n\\n line_one_top = (p1.x2y2[0] + x_movement,\\n p1.x2y2[1])\\n\\n line_one_bottom = (p1.x3y3[0] - x_movement,\\n p1.x3y3[1])\\n\\n p1.x2y2 = line_one_top\\n p1.x3y3 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n p2.x1y1 = line_one_top\\n p2.x4y4 = line_one_bottom\\n\\n line_two_top = (p2.x2y2[0] + x_movement,\\n p2.x2y2[1])\\n\\n line_two_bottom = (p2.x3y3[0] - x_movement,\\n p2.x3y3[1])\\n\\n p2.x2y2 = line_two_top\\n p2.x3y3 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_top\\n p3.x4y4 = line_two_bottom\\n\\n p3.refresh_coords()\\n else:\\n y_movement = min_height*(movement_proportion/100)\\n\\n if rhombus_pattern == \\\"right\\\":\\n\\n line_one_top = (p2.x2y2[0],\\n p2.x2y2[1] + y_movement)\\n\\n line_one_bottom = (p2.x1y1[0],\\n p2.x1y1[1] - y_movement)\\n\\n p2.x2y2 = line_one_top\\n p2.x1y1 = line_one_bottom\\n\\n p1.x3y3 = line_one_top\\n p1.x4y4 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n line_two_top = (p2.x3y3[0],\\n p2.x3y3[1] + y_movement)\\n\\n line_two_bottom = (p2.x4y4[0],\\n p2.x4y4[1] - y_movement)\\n\\n p2.x3y3 = line_two_top\\n p2.x4y4 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_bottom\\n p3.x2y2 = line_two_top\\n\\n p3.refresh_coords()\\n else:\\n\\n line_one_top = (p2.x2y2[0],\\n p2.x2y2[1] - y_movement)\\n\\n line_one_bottom = (p2.x1y1[0],\\n p2.x1y1[1] + y_movement)\\n\\n p2.x2y2 = line_one_top\\n p2.x1y1 = line_one_bottom\\n\\n p1.x3y3 = line_one_top\\n p1.x4y4 = line_one_bottom\\n\\n p1.refresh_coords()\\n\\n line_two_top = (p2.x3y3[0],\\n p2.x3y3[1] - y_movement)\\n\\n line_two_bottom = (p2.x4y4[0],\\n p2.x4y4[1] + y_movement)\\n\\n p2.x3y3 = line_two_top\\n p2.x4y4 = line_two_bottom\\n\\n p2.refresh_coords()\\n\\n p3.x1y1 = line_two_bottom\\n p3.x2y2 = line_two_top\\n\\n p3.refresh_coords()\\n\\n return page\",\n \"def get_controls(self):\\n return pn.Column(\\n pn.Column(\\n pn.Row(super().get_controls(), margin = (0, 0, -25, 0)),\\n pn.pane.HoloViews(self.get_band_dmap(), linked_axes=False)\\n ), \\n )\",\n \"def __call__(self, axes, renderer):\\n bbox0 = self.get_original_position(axes, renderer)\\n bbox = bbox0\\n\\n x1, y1, w, h = bbox.bounds\\n extesion_fraction = self.extesion_fraction\\n dw, dh = w*extesion_fraction, h*extesion_fraction\\n\\n if self.extend in [\\\"min\\\", \\\"both\\\"]:\\n if self.orientation == \\\"horizontal\\\":\\n x1 = x1 + dw\\n else:\\n y1 = y1+dh\\n\\n if self.extend in [\\\"max\\\", \\\"both\\\"]:\\n if self.orientation == \\\"horizontal\\\":\\n w = w-2*dw\\n else:\\n h = h-2*dh\\n\\n return Bbox.from_bounds(x1, y1, w, h)\",\n \"def _create_barplot_pane(self):\\n \\n panel = wx.Panel(self, -1)\\n\\t\\t\\n self.figb = Figure()\\n self.axb = self.figb.add_subplot(111)\\n\\t\\t\\n self.axb.set_xlabel(\\\"Isodoses\\\", fontsize=14, fontweight = 'semibold') #fontsize=24\\n self.axb.set_ylabel(\\\"Probability\\\", fontsize = 14, fontweight = 'semibold')\\n self.axb.set_xlim(68, 93)\\n self.axb.set_ylim(0, 1)\\n\\t\\t\\n self.canvasb = FigureCanvas(panel, -1, self.figb)\\n self.toolbarb = NavigationToolbar(self.canvasb)\\n\\t\\t\\n vbox = wx.BoxSizer(wx.VERTICAL)\\n vbox.Add(self.canvasb, 1, wx.EXPAND|wx.BOTTOM, 7)\\n vbox.Add(self.toolbarb, 0, wx.EXPAND)\\n\\t\\t\\n panel.SetSizer(vbox)\\n vbox.Fit(panel)\\n\\t\\t\\n return panel\",\n \"def add_boundaries_page(wiz):\\n page = wiz.add_page(u\\\"Boundaries conditions\\\", BoundariesPage())\\n page.register(\\\"group-boundaries*\\\", None)\",\n \"def panel_callback():\\n if self.minwidth is None:\\n self.minwidth = self.button_stack.winfo_width()\\n\\n if self.current_panel:\\n self.sashpos = self.paned.sashpos(0)\\n self.current_panel.forget()\\n if isinstance(self.current_panel, class_obj):\\n self.current_panel = None\\n self.paned.sashpos(0, self.minwidth)\\n return\\n\\n if class_obj.__name__ in self.panels:\\n panel = self.panels[class_name]\\n else:\\n panel = self.panels[class_name] = class_obj(self, self.app)\\n\\n panel.pack(side=tk.LEFT, expand=1, fill=tk.BOTH)\\n\\n if self.sashpos is None:\\n self.sashpos = 300\\n\\n self.paned.sashpos(0, self.sashpos)\\n\\n self.current_panel = panel\",\n \"def apply_transforms(self):\\n self.axes.set_xlim(self._curr_xlim)\\n self.axes.set_ylim(self._curr_ylim)\",\n \"def boxen(self, paneel):\\n \\n boxje = wx.BoxSizer(wx.VERTICAL)\\n boxje.Add(paneel, 1, wx.EXPAND | wx.ALL)\\n \\n #boxje.Add(vbox, 8, wx.EXPAND | wx.ALL)\\n return boxje\",\n \"def set_base_transforms(self):\\n self._curr_xlim = self.axes.get_xlim()\\n self._curr_ylim = self.axes.get_ylim()\",\n \"def _create_3D_pane(self):\\n\\t\\t\\n panel = wx.Panel(self,-1)\\n self.interactor3d = wxVTKRenderWindowInteractor(panel, -1, (600,800))\\n self.generate_button = wx.Button(panel, label=\\\"Generate 3D view\\\")\\n self.text_position = wx.StaticText(panel, -1, \\\"Dose (Gy) \\\" , wx.Point(0, 0))\\n self.slider_dose3d = wx.Slider(panel, -1, 75, 60, 100, wx.DefaultPosition, wx.Size( 100,-1 ), wx.SL_HORIZONTAL)\\n self.spin_dose3d = wx.SpinCtrl(panel, wx.ID_ANY, str(self.slider_dose3d.GetValue()), wx.DefaultPosition, wx.Size( 70,-1 ), wx.SP_ARROW_KEYS, min=0, max=100, initial=11)\\t\\n\\t\\t\\n button_sizer = wx.BoxSizer(wx.HORIZONTAL)\\n button_sizer.AddSpacer(30)\\n button_sizer.Add(self.generate_button)\\n button_sizer.AddSpacer(30)\\n button_sizer.Add(self.text_position)\\n button_sizer.Add(self.slider_dose3d)\\n button_sizer.Add(self.spin_dose3d)\\n\\t\\t\\n listsizer = wx.BoxSizer(wx.VERTICAL)\\n listsizer.Add(self.interactor3d, 1, wx.EXPAND|wx.BOTTOM, 7)\\n listsizer.Add(button_sizer)\\n panel.SetSizer(listsizer)\\n listsizer.Fit(panel)\\n\\t\\t\\n self._create_orientation_widget(self.interactor3d)\\n return panel\",\n \"def box_transform_page(page, direction_list=[]):\\n\\n if len(page.children) > 1:\\n\\n # For all children of the page\\n for idx in range(0, len(page.children)-1):\\n\\n # Take two children at a time\\n p1 = page.get_child(idx)\\n p2 = page.get_child(idx+1)\\n\\n change_proportion = np.random.randint(\\n 10,\\n cfg.full_page_movement_proportion_limit\\n )\\n\\n change_proportion /= 100\\n\\n # Randomly move the line between them up or down one side\\n if len(direction_list) < 1:\\n direction = np.random.choice([\\\"rup\\\", \\\"lup\\\"])\\n else:\\n direction = direction_list[idx]\\n\\n # If the first panel is horizontal therefore the second is too\\n if p1.orientation == \\\"h\\\":\\n\\n # Get the maximum amount the line can move\\n change_max = min([(p1.x4y4[1] - p1.x1y1[1]),\\n (p2.x4y4[1] - p2.x1y1[1])])\\n\\n change = change_max*change_proportion\\n\\n # Specify the line to move\\n line_top = p2.x1y1\\n line_bottom = p2.x2y2\\n\\n # If the panel has children then recursively\\n # find the leaf children and move them to the new line\\n if len(p1.children) > 0:\\n move_children_to_line(p1,\\n (line_top, line_bottom),\\n change,\\n \\\"h\\\",\\n direction\\n )\\n\\n # Otherwise move the current panels to line\\n else:\\n if direction == \\\"rup\\\":\\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] + change)\\n p1.refresh_coords()\\n else:\\n p1.x4y4 = (p1.x4y4[0], p1.x4y4[1] - change)\\n p1.refresh_coords()\\n\\n if len(p2.children) > 0:\\n move_children_to_line(p2,\\n (line_top, line_bottom),\\n change,\\n \\\"h\\\",\\n direction\\n )\\n else:\\n if direction == \\\"rup\\\":\\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] + change)\\n p2.refresh_coords()\\n else:\\n p2.x1y1 = (p2.x1y1[0], p2.x1y1[1] - change)\\n p2.refresh_coords()\\n\\n # If the first panel is vertical therefore the second\\n # is too since they are siblings\\n else:\\n # Get the maximum amount the line can move\\n change_max = min([(p1.x2y2[0] - p1.x1y1[0]),\\n (p2.x2y2[0] - p2.x1y1[0])])\\n\\n change = change_max*change_proportion\\n\\n # Specify the line to move\\n line_top = p2.x1y1\\n line_bottom = p2.x4y4\\n\\n # If the panel has children then recursively\\n # find the leaf children and move them to the new line\\n if len(p1.children) > 0:\\n move_children_to_line(p1,\\n (line_top, line_bottom),\\n change,\\n \\\"v\\\",\\n direction\\n )\\n\\n # Otherwise just move the panel since it's a leaf\\n else:\\n if direction == \\\"rup\\\":\\n p1.x2y2 = (p1.x2y2[0] - change, p1.x2y2[1])\\n else:\\n p1.x2y2 = (p1.x2y2[0] + change, p1.x2y2[1])\\n\\n if len(p2.children) > 0:\\n move_children_to_line(p2,\\n (line_top, line_bottom),\\n change,\\n \\\"v\\\",\\n direction\\n )\\n else:\\n if direction == \\\"rup\\\":\\n p2.x1y1 = (p2.x1y1[0] - change, p2.x1y1[1])\\n else:\\n p2.x1y1 = (p2.x1y1[0] + change, p2.x1y1[1])\\n\\n return page\",\n \"def _buidUISizer(self):\\n flagsR = wx.RIGHT | wx.ALIGN_CENTER_VERTICAL\\n mSizer = wx.BoxSizer(wx.HORIZONTAL)\\n mSizer.AddSpacer(5)\\n gv.iMapPanel = self.mapPanel = gp.PanelMap(self)\\n mSizer.Add(self.mapPanel, flag=flagsR, border=2)\\n mSizer.AddSpacer(5)\\n mSizer.Add(wx.StaticLine(self, wx.ID_ANY, size=(-1, 560),\\n style=wx.LI_VERTICAL), flag=flagsR, border=2)\\n mSizer.AddSpacer(5)\\n gv.iCtrlPanel = gp.PanelCtrl(self)\\n mSizer.Add(gv.iCtrlPanel)\\n return mSizer\",\n \"def _addPanes(self):\\n\\n self._addPaneMapWindow()\\n self._addPaneToolbar(name = 'digitMap')\",\n \"def paint_mini_axes(self):\\n w, h = self.width(), self.height()\\n vt = self.getTranslation() # this is in eye coordinates\\n GL.glViewport(0, 0, w//8, h//8) # mini viewport at bottom left of widget\\n self.setTranslation((0, 0, -3)) # draw in center of this mini viewport\\n self.paint_axes()\\n self.setTranslation(vt) # restore translation vector to MV matrix\\n GL.glViewport(0, 0, w, h) # restore full viewport\",\n \"def paint_mini_axes(self):\\n w, h = self.width(), self.height()\\n vt = self.getTranslation() # this is in eye coordinates\\n GL.glViewport(0, 0, w//8, h//8) # mini viewport at bottom left of widget\\n self.setTranslation((0, 0, -3)) # draw in center of this mini viewport\\n self.paint_axes()\\n self.setTranslation(vt) # restore translation vector to MV matrix\\n GL.glViewport(0, 0, w, h) # restore full viewport\",\n \"def create_mplframe(self):\\r\\n #create figure and axes objects\\r\\n self.fig = Figure()\\r\\n self.subplot = self.fig.add_subplot(111)\\r\\n #disable axis, because it will only show an image\\r\\n self.subplot.get_yaxis().set_visible(False)\\r\\n self.subplot.get_xaxis().set_visible(False)\\r\\n \\r\\n #create canvas and toolbar\\r\\n self.canvas = FigureCanvas(self.fig)\\r\\n self.toolbar = MyNavigationToolbar(self.canvas, None)\\r\\n\\r\\n #add the canvas and toolbar to the gui\\r\\n self.ui.imageLayout.addWidget(self.canvas)\\r\\n self.ui.imageLayout.addWidget(self.toolbar)\\r\\n\\r\\n #connect the toolbar selection to matploblib as a callback\\r\\n self.canvas.mpl_connect('selection_changed',self.toolbar_selection)\",\n \"def create_panel(self):\\n return\\n # return Panel(self)\",\n \"def add_frame_shift(self, basis, axis_settings):\\n angle, axis = angle_and_axis(basis)\\n\\n if angle == 0:\\n axis = (0,0,1)\\n\\n if basis.include_translation:\\n translation = basis.translation\\n else:\\n translation = (0,0,0)\\n\\n self.add_row([basis.axis_name,\\\"rotation\\\",\\\"detector\\\",basis.depends_on,\\n str(axis[0]),str(axis[1]),str(axis[2]),\\n str(translation[0]),\\n str(translation[1]),\\n str(translation[2]),\\n basis.equipment_component])\\n\\n axis_settings.append([basis.axis_name, \\\"FRAME1\\\", str(angle), \\\"0\\\"])\",\n \"def adjust_visual(self):\\n\\n if (self.direction is bs.Direction.LEFT):\\n self.rect.x -= 0.5 * CELL_SIZE\",\n \"def generate_panel(self):\\r\\n \\r\\n self.PanelData = self.RawData.filter(['ID', 'X', 'Z', 'W', 'R', 'β', 'LFP', 'H'], axis=1)\",\n \"def plot_overlay2axes(self, axes) -> None:\\n # calculate height (based on leaf analysis ratio)\\n upper_point = (\\n self.leaf_center_px - self.leaf_width_px / 2 * self._analysis_ratio\\n )\\n lower_point = (\\n self.leaf_center_px + self.leaf_width_px / 2 * self._analysis_ratio\\n )\\n height = abs(upper_point - lower_point) * 0.8\\n\\n for idx, line in enumerate(self.marker_lines):\\n width = abs(self.error[idx]) * self._image.dpmm\\n y = line.center.y\\n x = self.position[idx] - (self.error[idx] * self._image.dpmm) / 2\\n\\n if self._orientation == Orientation.UP_DOWN:\\n r = Rectangle(width, height, center=(x, y))\\n # if any of the values are over tolerance, show another larger rectangle to draw the eye\\n if not self.passed[idx] or not self.passed_action[idx]:\\n re = Rectangle(\\n self._image_window.shape[1] * 0.2, height * 1.2, center=(x, y)\\n )\\n re.plot2axes(\\n axes,\\n edgecolor=\\\"none\\\",\\n fill=True,\\n alpha=0.5,\\n facecolor=self.bg_color[idx],\\n )\\n else:\\n r = Rectangle(height, width, center=(x, y))\\n if not self.passed[idx] or not self.passed_action[idx]:\\n re = Rectangle(\\n self._image_window.shape[1] * 0.2, height * 1.2, center=(x, y)\\n )\\n re.plot2axes(\\n axes,\\n edgecolor=\\\"none\\\",\\n fill=True,\\n alpha=0.5,\\n facecolor=self.bg_color[idx],\\n )\\n r.plot2axes(\\n axes, edgecolor=\\\"none\\\", fill=True, alpha=1, facecolor=self.bg_color[idx]\\n )\",\n \"def postRefRender(self):\\n self.logger.debug(\\\"Running postRefRender\\\")\\n\\n # add the lattice frame\\n self.addLatticeFrame()\\n\\n # add the axes\\n self.axes.add()\\n\\n # set camera to cell\\n self.setCameraToCell()\\n\\n # reinitialise\\n self.reinit()\",\n \"def __init__(self):\\n self.fig = pl.figure(1,figsize=(8,6), dpi=80 , frameon = True , facecolor = '0.75' , edgecolor = 'w')\\n self.fig.add_subplot(111 , axisbg = 'w' , projection = 'rectilinear') #if you want to add axes on particular place: fig.add_axes([0.15, 0.1, 0.7, 0.3]) where -> [begin , bottom to start axes , width , height ]\\n self.separated = True #if we have a list and need to plot the plots separated\",\n \"def define_panel_structure(self):\\n w, h = self.parent.GetSize()\\n self.vbox = wx.BoxSizer(wx.VERTICAL)\\n self.sizer1 = wx.BoxSizer(wx.VERTICAL)\\n self.sizer1.SetMinSize(wx.Size(w/13, h*2/5))\\n\\n self.sizer2 = wx.BoxSizer(wx.VERTICAL)\\n self.sizer3 = wx.FlexGridSizer(9, 2, 4, 1)\\n self.sizer4 = wx.BoxSizer(wx.VERTICAL)\\n self.sizer5 = wx.BoxSizer(wx.VERTICAL)\\n\\n self.vbox.Add(self.sizer5, 0, wx.EXPAND | wx.ALL, 1)\\n self.vbox.Add(self.sizer1, 1, wx.EXPAND | wx.ALL, 0)\\n self.vbox.Add(self.sizer2, 0, wx.EXPAND | wx.ALL, 1)\\n self.vbox.Add(self.sizer3, 0, wx.EXPAND | wx.ALL, 10)\\n # self.vbox.Add(self.sizer4, 0, wx.EXPAND|wx.ALL,5)\\n\\n self.SetSizer(self.vbox)\",\n \"def draw_window_pane():\\n houseturtle.begin_fill()\\n for y in range(4):\\n houseturtle.pendown()\\n houseturtle.forward(35)\\n houseturtle.left(90)\\n houseturtle.penup()\\n houseturtle.end_fill()\",\n \"def create_base(self):\\n if self.debug:\\n print(\\\"Creating base\\\")\\n self.console_panel = ConsolePanel(self.root)\\n self.side_panel = SidePanel(self.root, self.populate_main_panel)\\n self.side_panel.set_separator(\\\"word_word\\\")\\n self.main_panel = MainPanel(self.root, action=\\\"word_word\\\")\",\n \"def SetupView(self):\\r\\n size = self.GetClientSizeTuple()\\r\\n height = self.maxtop - self.maxbottom\\r\\n width = self.maxright - self.maxleft\\r\\n \\r\\n #The ratio of the width to the height in the client-area\\r\\n screenratio = float(size[0]) / float(size[1])\\r\\n \\r\\n #The ratio of the world window. Because of divide-by-0, we have to make a special-case assignment\\r\\n if height == 0 or width == 0:\\r\\n ratio = screenratio\\r\\n else:\\r\\n ratio = width / height\\r\\n\\r\\n #Should seem familiar, since we did it in class...\\r\\n if ratio > screenratio:\\r\\n glViewport(0, (size[1] - (size[0] / ratio)) / 2, size[0], size[0] / ratio)\\r\\n if ratio < screenratio:\\r\\n glViewport((size[0] - size[1] * ratio) / 2, 0, size[1] * ratio, size[1])\\r\\n \\r\\n \\r\\n #I need to find an appropriate border value. It's scaled by the client-area because the world-window zooms, thus skewing any normal border given.\\r\\n if width == 0 or height == 0:\\r\\n xborder = 1\\r\\n yborder = 1\\r\\n else:\\r\\n xscale = size[0] / width\\r\\n xborder = 10 / xscale\\r\\n yscale = size[1] / height\\r\\n yborder = 10 / yscale\\r\\n \\r\\n glMatrixMode(GL_PROJECTION)\\r\\n glLoadIdentity()\\r\\n gluOrtho2D(self.maxleft - xborder, self.maxright + xborder, self.maxbottom - yborder, self.maxtop + yborder)\",\n \"def update_transform(self):\\n\\n self.a = self.scale * self.pixel_size * math.cos(self.angle)\\n self.d = self.scale * self.pixel_size * math.sin(self.angle)\\n self.b = self.d\\n self.e = -self.a\\n self.c = self.point.x() - self.a*self.width/2.0 - self.b*self.height/2.0\\n self.f = self.point.y() - self.d*self.width/2.0 - self.e*self.height/2.0\\n\\n self.bounding_box = [[self.c,self.f],[self.c+self.a*self.width,self.f+self.d*self.width],[self.c+self.a*self.width+self.b*self.height,self.f+self.d*self.width+self.e*self.height],[self.c+self.b*self.height,self.f+self.e*self.height],]\",\n \"def __init__(self):\\n Page.__init__(self, u\\\"Paraboloide Elíptico<br><br>F(x,y)=(x, y, x<sup>2</sup>/a<sup>2</sup> + y<sup>2</sup>/b<sup>2</sup>)\\\")\\n\\n z = 0.5\\n par = RevolutionPlot3D(lambda r, t: r ** 2 + z, (0, 1), (0, 2 * pi))\\n\\n x, y, z2, u, v, cose, sen, t = createVars(['x', 'y', 'z', 'u', 'v', 'cos', 'sen', 't'])\\n\\n mesh1 = Plot3D(lambda x, y, h: h * (x ** 2 + y ** 2 + z - .01), (-1, 1), (-1, 1))\\n mesh1.addEqn(x**2+y**2 - z2**2 == 1)\\n mesh1.addFunction(lambda x, y, h: h * (x ** 2 + y ** 2 + z + .01))\\n mesh1.setLinesVisible(True)\\n mesh1.setMeshVisible(False)\\n mesh1.setBoundingBox(zrange=(-1, 1.5))\\n par.setAmbientColor(_1(145, 61, 74))\\n par.setDiffuseColor(_1(145, 61, 74))\\n par.setSpecularColor(_1(145, 61, 74))\\n baseplane = BasePlane()\\n baseplane.setHeight(0)\\n baseplane.setRange((-2, 2, 7))\\n\\n self.addChild(par)\\n self.addChild(mesh1)\\n self.addChild(baseplane)\",\n \"def make_panel_in_array(array_elt, reference_panel):\\n\\n px_size = tuple((e / 3.0) for e in reference_panel.get_pixel_size())\\n ref_panel_size = reference_panel.get_image_size_mm()\\n x_shift = array_elt[0] * ref_panel_size[0] / 3.0\\n y_shift = array_elt[1] * ref_panel_size[1] / 3.0\\n origin = (\\n matrix.col(reference_panel.get_origin())\\n + x_shift * matrix.col(reference_panel.get_fast_axis())\\n + y_shift * matrix.col(reference_panel.get_slow_axis())\\n )\\n return Panel(\\n type=\\\"PAD\\\",\\n name=\\\"Panel\\\",\\n fast_axis=reference_panel.get_fast_axis(),\\n slow_axis=reference_panel.get_slow_axis(),\\n origin=origin,\\n pixel_size=px_size,\\n image_size=reference_panel.get_image_size(),\\n trusted_range=(0, 1.0e6),\\n thickness=0.0,\\n material=\\\"\\\",\\n )\",\n \"def create_panel(self):\\n # Main Frame creation\\n frame1 = Frame(self.window)\\n frame1.pack(fill=\\\"both\\\")\\n tablayout = Notebook(frame1)\\n \\n ##### TRACKER #####\\n tab = Frame(tablayout) # creating 1st nested frame\\n tab.pack(fill=\\\"both\\\")\\n table = Frame(tab)\\n table.pack(fill=\\\"both\\\")\\n self.show_table(self.t.timeline[\\\"week\\\" + str(self.week)], table) # Grids the week with data\\n self.add_buttons(tab, table)\\n tablayout.add(tab, text=\\\"Current Week\\\") \\n \\n \\n ##### STATS #####\\n tab = Frame(tablayout) # creating 2nd nested frame\\n tab.pack(fill=\\\"both\\\")\\n self.stats.create_canvas(tab)\\n\\n\\n # once its packed you can add it to the window object under a title\\n tablayout.add(tab, text=\\\"Statistics\\\") \\n tablayout.pack(fill=\\\"both\\\") # once everything is done now you pack the tablayout\",\n \"def __init__(self):\\n self.degrees = 60.0\\n self.aspect_ratio = 1.0\\n self.front_pane = 0.1\\n self.back_pane = 100.0\",\n \"def reshape(self, w, h):\\n glViewport(0, 0, w, h)\\n\\n glMatrixMode(GL_PROJECTION)\\n glLoadIdentity()\\n gluPerspective(40.0, w/h, 1.0, 1000.0)\\n glutPostRedisplay()\",\n \"def DrawTransform(self, xf):\\r\\n p1 = xf.position\\r\\n p2 = self.to_screen(p1 + self.axisScale * xf.R.col1)\\r\\n p3 = self.to_screen(p1 + self.axisScale * xf.R.col2)\\r\\n p1 = self.to_screen(p1)\\r\\n\\r\\n pygame.draw.aaline(self.surface, (255, 0, 0), p1, p2)\\r\\n pygame.draw.aaline(self.surface, (0, 255, 0), p1, p3)\",\n \"def expanded_boundaries(self):\\n width = self._points[0][3][0] - self._points[0][1][0]\\n height = self._points[0][3][1] - self._points[0][1][1]\\n factor = np.multiply((width, height), Window.BORDER)\\n return (\\n np.subtract(self._points[0][1], factor),\\n np.add(self._points[0][3], factor))\",\n \"def __init__(self, **kwargs):\\n\\n tmp = defs.copy()\\n tmp.update(kwargs)\\n\\n for kw in tmp:\\n setattr(self, kw, tmp[kw])\\n \\n if self.left is None:\\n self.left = pl.rcParams['figure.subplot.left']\\n if self.right is None:\\n self.right = pl.rcParams['figure.subplot.right']\\n if self.bottom is None:\\n self.bottom = pl.rcParams['figure.subplot.bottom']\\n if self.top is None:\\n self.top = pl.rcParams['figure.subplot.top']\\n \\n self.l = self.left\\n self.r = self.right\\n self.b = self.bottom\\n self.t = self.top \\n \\n self.square = self.dims[0] == self.dims[1]\\n \\n if (self.diagonal is not None) and not self.square:\\n raise ValueError('Must have square matrix to use diagonal=True')\\n\\n self.dims = tuple(self.dims)\\n self.J, self.K = self.dims # J = nrows, K = ncols\\n self.nrows = self.J\\n self.ncols = self.K\\n \\n if type(self.padding) is float:\\n self.padding = tuple([self.padding]* 2)\\n \\n # Size of an individual panel (in inches)\\n self.pane_size = np.array(self.figsize) * np.array([self.r-self.l, self.t-self.b])\\n self.pane_size *= np.array(self.panel_size)\\n\\n # Now, figure out the size of the entire figure (in inches)\\n self.panel_size = np.zeros(2)\\n \\n # After these two lines, self.panel_size is equal to the size of the\\n # panel-filled area of the window (in inches)\\n self.panel_size[0] = self.pane_size[0] * self.K + self.padding[0] * (self.K - 1)\\n self.panel_size[1] = self.pane_size[1] * self.J + self.padding[1] * (self.J - 1) \\n\\n # Add empty area above/below and left/right of panel-filled area\\n self.panel_size[0] += self.figsize[0] * (self.left + (1. - self.right))\\n self.panel_size[1] += self.figsize[1] * (self.bottom + (1. - self.top))\\n\\n self.panel_size_rel = self.pane_size / self.panel_size\\n\\n self.share_x = self.padding[1] <= 0.2\\n self.share_y = self.padding[0] <= 0.2 \\n self.share_all = self.share_x and self.share_y\\n\\n self.dx = self.shift_x\\n self.dy = self.shift_y\\n\\n # Create figure\\n if type(self.fig) is not int:\\n new_fig = False\\n l, r = self.fig.subplotpars.left, self.fig.subplotpars.right\\n b, t = self.fig.subplotpars.bottom, self.fig.subplotpars.top\\n else:\\n self.fig = pl.figure(self.fig, self.panel_size)\\n new_fig = True\\n\\n # Adjust padding\\n if self.preserve_margins:\\n l = self.left * self.figsize[0] / self.panel_size[0]\\n r = (self.left * self.figsize[0] + self.K * self.pane_size[0]) \\\\\\n / self.panel_size[0]\\n b = self.bottom * self.figsize[1] / self.panel_size[1]\\n t = (self.bottom * self.figsize[1] + self.J * self.pane_size[1]) \\\\\\n / self.panel_size[1]\\n else:\\n l, r, b, t = self.left, self.right, self.bottom, self.top\\n \\n self.fig.subplots_adjust(left=l, right=r, bottom=b, top=t, \\n wspace=self.padding[0], hspace=self.padding[1])\\n \\n self.l, self.r, self.b, self.t = l, r, b, t\\n\\n # Important attributes for identifying individual panels\\n self.N = int(np.prod(self.dims))\\n self.elements = list(np.reshape(np.arange(self.N), self.dims))\\n self.elements.reverse()\\n self.elements = np.array(self.elements)\\n\\n # Dimensions of everything (in fractional units)\\n #self.window = {'left': l, 'right': r, 'top': t, \\n # 'bottom': b, 'pane': ((r-l) / float(dims[0]), (t-b) / float(dims[1]))}\\n\\n self.xaxes = self.elements[-1]\\n self.yaxes = list(zip(*self.elements))[0] \\n self.lowerleft = self.elements[-1][0]\\n self.lowerright = self.elements[-1][-1]\\n self.upperleft = self.elements[0][0]\\n self.upperright = self.elements[0][-1]\\n \\n if self.square:\\n self.diag = np.diag(self.elements) \\n self.interior = list(self.elements.ravel())\\n for element in self.diag:\\n self.interior.remove(element)\\n else:\\n self.diag = None \\n \\n self.left = []\\n self.right = []\\n self.bottom = []\\n self.top = []\\n for i in range(self.N):\\n k, j = self.axis_position(i) # col, row\\n \\n if j == 0:\\n self.bottom.append(i)\\n if j == self.nrows - 1:\\n self.top.append(i) \\n if k == 0:\\n self.left.append(i)\\n if k == self.ncols - 1:\\n self.right.append(i) \\n\\n self.interior = []\\n for i in range(self.N):\\n if i in self.left:\\n continue\\n if i in self.bottom:\\n continue\\n \\n self.interior.append(i)\\n\\n # Create subplots\\n e_fl = self.elements.flatten()\\n self.grid = [None for i in range(self.N)]\\n for i in range(self.N): \\n j, k = self.axis_position(i)\\n \\n if self.diagonal == 'lower':\\n if k >= (self.dims[1] - j) and i not in self.diag:\\n continue\\n if self.diagonal == 'upper':\\n if k < (self.dims[1] - j) and i not in self.diag:\\n continue \\n \\n #if self.diagonal == 'lower' and j == k and (j, k) != (0, 0):\\n # continue\\n #if self.diagonal == 'upper' and j == k and (j, k) != (self.J-1, self.K-1):\\n # continue\\n \\n if self.square:\\n if i in self.diag and not self.keep_diagonal:\\n continue\\n \\n if new_fig:\\n self.grid[i] = AxisConstructor(self.fig, self.J, self.K, e_fl[i]+1)\\n else:\\n\\n # col, row = j, k\\n\\n lef = l + j * self.panel_size_rel[0] \\\\\\n + self.padding[0] + self.dx\\n bot = b + k * self.panel_size_rel[1] \\\\\\n + self.padding[1] + self.dy\\n\\n rect = [lef, bot, self.panel_size_rel[0], self.panel_size_rel[1]]\\n\\n self.grid[i] = self.fig.add_axes(rect)\",\n \"def onFrameConfigure(self, event):\\n self.panel_002.config(scrollregion=self.panel_002.bbox(\\\"all\\\"))\",\n \"def warp(self):\\n self.maingui.scene.center_on(self.spin_x.value(), self.spin_y.value())\\n self.close()\",\n \"def pixel_space(self):\\n self.drawer.settransform()\\n self.coordspace_bbox = [0, 0, self.width, self.height]\\n self.coordspace_transform = (1, 0, 0,\\n 0, 1, 0)\",\n \"def warp_to_dashboard(self, overhead_img):\\n return cv2.warpPerspective(overhead_img, self.inverse_overhead_transform,\\n dsize=(self.img_width, self.img_height))\",\n \"def _create_distplot_pane(self):\\n panel = wx.Panel(self, -1)\\n\\t\\t\\n self.fig_violin = Figure()\\n self.ax_violin = self.fig_violin.add_subplot(111)\\n\\t\\t\\n self.ax_violin.set_xlabel(\\\"Voxel values\\\")\\n self.ax_violin.set_ylabel(\\\"Density\\\")\\n self.ax_violin.set_xlim(60, 120)\\n self.ax_violin.set_ylim(0, 0.3)\\n\\t\\t\\n self.canvas_violin = FigureCanvas(panel, -1, self.fig_violin)\\n self.toolbar_violin = NavigationToolbar(self.canvas_violin)\\n\\t\\t\\n self.canvas_violin.mpl_connect('pick_event', self.onPickdist)\\n\\t\\t\\n vbox = wx.BoxSizer(wx.VERTICAL)\\n vbox.Add(self.canvas_violin, 1, wx.EXPAND|wx.BOTTOM, 7)\\n vbox.Add(self.toolbar_violin, 0, wx.EXPAND)\\n\\t\\t\\n panel.SetSizer(vbox)\\n vbox.Fit(panel)\\n\\t\\t\\n return panel\",\n \"def _locator(self, axes, renderer):\\n x0, y0, x1, y1 = self.rect\\n width_dict = dict()\\n cut_ax_dict = self.axes\\n x_ax = cut_ax_dict['x']\\n y_ax = cut_ax_dict['y']\\n z_ax = cut_ax_dict['z']\\n for cut_ax in cut_ax_dict.values():\\n bounds = cut_ax.get_object_bounds()\\n if not bounds:\\n # This happens if the call to _map_show was not\\n # succesful. As it happens asyncroniously (during a\\n # refresh of the figure) we capture the problem and\\n # ignore it: it only adds a non informative traceback\\n bounds = [0, 1, 0, 1]\\n xmin, xmax, ymin, ymax = bounds\\n width_dict[cut_ax.ax] = (xmax - xmin)\\n total_width = float(sum(width_dict.values()))\\n for ax, width in width_dict.items():\\n width_dict[ax] = width/total_width*(x1 -x0)\\n left_dict = dict()\\n left_dict[y_ax.ax] = x0\\n left_dict[x_ax.ax] = x0 + width_dict[y_ax.ax]\\n left_dict[z_ax.ax] = x0 + width_dict[x_ax.ax] + width_dict[y_ax.ax]\\n return transforms.Bbox([[left_dict[axes], y0],\\n [left_dict[axes] + width_dict[axes], y1]])\",\n \"def panel_axes(self, side, **kwargs):\\n return self.figure._add_axes_panel(self, side, **kwargs)\",\n \"def make_layers(self):\\n w, h = self.image.get_size()\\n shrink = pg.transform.smoothscale(self.image, (w//2, h//2))\\n self.mid_image = tools.tile_surface((w,h), shrink, True)\\n shrink = pg.transform.smoothscale(self.image, (w//4, h//4))\\n self.base = tools.tile_surface(prepare.SCREEN_SIZE, shrink, True)\",\n \"def draw_reference_frame_axes(se3_pose, scene): # pragma nocover\\n\\n origin = get_pose_pos(se3_pose)\\n x_axis = get_pose_x_vec(se3_pose)\\n y_axis = get_pose_y_vec(se3_pose)\\n\\n # Create Basic Frame\\n # Draw X Axis\\n x_arrow = arrow(\\n canvas=scene, pos=origin, axis=x_axis_vector,\\n length=0.25, color=color.red)\\n\\n # Draw Y Axis\\n y_arrow = arrow(\\n canvas=scene, pos=origin, axis=y_axis_vector,\\n length=0.25, color=color.green)\\n\\n # Draw Z Axis\\n z_arrow = arrow(\\n canvas=scene, pos=origin, axis=z_axis_vector,\\n length=0.25, color=color.blue)\\n\\n # Combine all to manipulate together\\n # Set origin to where axis converge (instead of the middle of\\n # the resulting object bounding box)\\n frame_ref = compound(\\n [x_arrow, y_arrow, z_arrow], origin=origin, canvas=scene)\\n\\n # Set frame axes\\n frame_ref.axis = x_axis\\n frame_ref.up = y_axis\\n\\n return frame_ref\",\n \"def canvas_bounds(self) -> utils.BoxRegion:\",\n \"def _add_boundaries(self):\\n logger.info(\\\"add_boundaries: start of method\\\")\\n\\n import scipy.spatial as sptl\\n import scipy.sparse as sprs\\n Lx = self._Lx\\n Ly = self._Ly\\n Lz = self._Lz\\n Np = self.num_pores()\\n btype = self._btype\\n boffset = 0.05\\n\\n #Translate internal pores to each face of domain\\n poffset = np.zeros((7,3))\\n poffset[[2,5],0] = [-Lx, Lx]\\n poffset[[3,4],1] = [-Ly, Ly]\\n poffset[[1,6],2] = [-Lz, Lz]\\n pcoords = pcoords0 = self['pore.coords']\\n for i in np.r_[1:7]:\\n pcoords = np.concatenate((pcoords,pcoords0 + poffset[i,:]),axis=0)\\n\\n #Use some twisted logic to get bval list of + for boundary and - for periodic faces\\n bval = [0, 1, 2, 3, 4, 5, 6]*(np.array([0, btype[2], btype[0], btype[1], btype[1], btype[0], btype[2]])*-2+1)\\n ptype = np.zeros((Np,),dtype=int)\\n for i in np.r_[1:7]:\\n ptype = np.concatenate((ptype,np.ones((Np,),dtype=int)*bval[i]),axis=0)\\n\\n #pnum contains the internal ID number of the boundary pores (for connecting periodic points)\\n pnum = self.pores()\\n pnum = np.tile(pnum,7)\\n\\n Tri = sptl.Delaunay(pcoords)\\n adjmat = sprs.lil_matrix((np.shape(pcoords)[0],np.shape(pcoords)[0]),dtype=int)\\n for i in np.arange(0,np.shape(Tri.simplices)[0]):\\n #Keep only simplices that are fully in real domain\\n adjmat[Tri.simplices[i],Tri.simplices[i]] = 1\\n adjmat = sprs.triu(adjmat,k=1,format=\\\"lil\\\")\\n for i in np.arange(0,Np):\\n #Add periodic throats to the netowrk (if any)\\n tpore2 = pnum[adjmat.rows[i]][ptype[adjmat.rows[i]]<0]\\n tpore1 = np.ones_like(tpore2,dtype=int)*i\\n conns = self['throat.conns']\\n conns = np.concatenate((conns,np.vstack((tpore1,tpore2)).T),axis=0)\\n #Add boundary pores and throats to the network\\n newporetyps = np.unique(ptype[adjmat.rows[i]][ptype[adjmat.rows[i]]>0])\\n newporenums = np.r_[self.num_pores():self.num_pores()+np.size(newporetyps)]\\n tpore2 = newporenums\\n tpore1 = np.ones_like(tpore2,dtype=int)*i\\n conns = np.concatenate((conns,np.vstack((tpore1,tpore2)).T),axis=0)\\n self['throat.conns'] = conns\\n bcoords = np.zeros((7,3),dtype=float)\\n coords = self['pore.coords']\\n bcoords[1,:] = [coords[i,0], coords[i,1], 0-Lz*boffset]\\n bcoords[2,:] = [0-Lx*boffset, coords[i,1], coords[i,2]]\\n bcoords[3,:] = [coords[i,0], -Ly*boffset, coords[i,2]]\\n bcoords[4,:] = [coords[i,0], Ly+Ly*boffset, coords[i,2]]\\n bcoords[5,:] = [Lx+Lx*boffset, coords[i,1], coords[i,2]]\\n bcoords[6,:] = [coords[i,0], coords[i,1], Lz+Lz*boffset]\\n newporecoords = bcoords[newporetyps,:]\\n coords = np.concatenate((coords,newporecoords),axis=0)\\n self['pore.coords'] = coords\\n #Reset number of pores and throats (easier than tracking it)\\n nums = np.r_[0:np.shape(coords)[0]]\\n self['pore.numbering'] = nums\\n self['pore.numbering'] = np.ones((nums[-1]+1,),dtype=bool)\\n nums = np.r_[0:np.shape(conns)[0]]\\n self['throat.numbering'] = nums\\n self['throat.numbering'] = np.ones((nums[-1]+1,),dtype=bool)\\n logger.debug(\\\"add_boundaries: end of method\\\")\",\n \"def __init__(self, parent, tile_dir=None, start_level=None,\\n min_level=None, max_level=None, **kwargs):\\n\\n # create and initialise the base panel\\n wx.Panel.__init__(self, parent=parent, id=wx.ID_ANY, **kwargs)\\n self.SetBackgroundColour(pySlip.BackgroundColour)\\n\\n # get tile info\\n self.tiles = pySlip.Tiles(tile_dir)\\n self.max_level = max_level\\n if max_level is None:\\n self.max_level = self.tiles.max_level\\n self.min_level = min_level\\n if min_level is None:\\n self.min_level = self.tiles.min_level\\n self.level = start_level\\n if start_level is None:\\n self.level = self.min_level\\n\\n self.tile_size_x = self.tiles.tile_size_x\\n self.tile_size_y = self.tiles.tile_size_y\\n\\n # set some internal state\\n self.view_width = None # view size in pixels\\n self.view_height = None # set on onResize()\\n\\n self.ppd_x = 0 # pixel_per_degree for current tileset\\n self.ppd_y = 0\\n\\n self.view_offset_x = 0 # pixel offset at left & top of view\\n self.view_offset_y = 0\\n\\n self.view_llon = self.view_rlon = None # view limits\\n self.view_tlat = self.view_blat = None\\n\\n self.was_dragging = False # True if dragging map\\n self.move_dx = 0 # drag delta values\\n self.move_dy = 0\\n self.last_drag_x = None # previous drag position\\n self.last_drag_y = None\\n\\n self.ignore_next_up = False # flag to ignore next UP event\\n\\n self.is_box_select = False # True if box selection\\n self.sbox_1_x = self.sbox_1_y = None # box size\\n\\n # layer stuff\\n self.next_layer_id = 1 # source of unique layer IDs\\n self.layer_z_order = [] # layer Z order, contains layer IDs\\n self.layer_mapping = {} # maps layer ID to (...layer data...)\\n\\n # callback to report mouse position in view\\n self.mouse_position_callback = None\\n\\n # callback on right mouse click (right button up event)\\n self.rightclick_callback = None\\n\\n # callback on level change\\n self.change_level_callback = None\\n\\n # bind events\\n self.Bind(wx.EVT_SIZE, self.onResize) # widget events\\n self.Bind(wx.EVT_PAINT, self.onPaint)\\n\\n self.Bind(wx.EVT_MOTION, self.onMove) # mouse events\\n self.Bind(wx.EVT_LEFT_DOWN, self.onLeftDown)\\n self.Bind(wx.EVT_LEFT_DCLICK, self.onLeftDClick)\\n self.Bind(wx.EVT_LEFT_UP, self.onLeftUp)\\n self.Bind(wx.EVT_RIGHT_DOWN, self.onRightDown)\\n self.Bind(wx.EVT_RIGHT_UP, self.onRightUp)\\n self.Bind(wx.EVT_MIDDLE_DOWN, self.onMiddleDown)\\n self.Bind(wx.EVT_MIDDLE_UP, self.onMiddleUp)\\n self.Bind(wx.EVT_MOUSEWHEEL, self.onMouseWheel)\\n\\n # OK, use the tile level the user wants\\n self.use_level(self.level)\\n\\n # force a resize, which sets up the rest of the state\\n self.onResize()\",\n \"def _create_scatterplot_pane(self):\\n panel = wx.Panel(self, -1)\\n\\t\\t\\n self.fig_scatter = Figure()\\n self.ax_scatter = self.fig_scatter.add_subplot(111)\\n\\t\\t\\n families = ['serif', 'sans-serif', 'cursive', 'fantasy', 'monospace']\\n\\t\\t\\n self.ax_scatter.set_xlabel(\\\"Mean\\\") #fontsize = 14, fontweight = 'semibold', name = families[2]\\n self.ax_scatter.set_ylabel(\\\"Standard Deviation\\\")\\n #self.ax_scatter.grid(color='black', alpha=0.5, linestyle='-', linewidth=1.0)\\n self.ax_scatter.set_axis_bgcolor((0.8,0.8,0.8))\\n #self.ax_scatter.set_ylim(0, 35)\\n #self.ax_scatter.set_ylim(0, 90)\\n\\t\\t\\n self.canvas_scatter = FigureCanvas(panel, -1, self.fig_scatter)\\n self.toolbar_scatter = NavigationToolbar(self.canvas_scatter)\\n\\t\\t\\n vbox = wx.BoxSizer(wx.VERTICAL)\\n vbox.Add(self.canvas_scatter, 1, wx.EXPAND|wx.BOTTOM, 7)\\n vbox.Add(self.toolbar_scatter, 0, wx.EXPAND)\\n\\t\\t\\n panel.SetSizer(vbox)\\n vbox.Fit(panel)\\n\\t\\t\\n return panel\",\n \"def relayout(self): \\n\\t\\t#self.urmaswin.Layout()\\n\\t\\t#wx.CallAfter(self.urmaswin.Layout)\\n\\t\\t#wx.CallAfter(self.visualizer.OnSize)\",\n \"def _set_lim_and_transforms(self):\\n # There are three important coordinate spaces going on here:\\n #\\n # 1. Data space: The space of the data itself\\n #\\n # 2. Axes space: The unit rectangle (0, 0) to (1, 1)\\n # covering the entire plot area.\\n #\\n # 3. Display space: The coordinates of the resulting image,\\n # often in pixels or dpi/inch.\\n\\n # This function makes heavy use of the Transform classes in\\n # ``lib/matplotlib/transforms.py.`` For more information, see\\n # the inline documentation there.\\n\\n # The goal of the first two transformations is to get from the\\n # data space (in this case longitude and latitude) to axes\\n # space. It is separated into a non-affine and affine part so\\n # that the non-affine part does not have to be recomputed when\\n # a simple affine change to the figure has been made (such as\\n # resizing the window or changing the dpi).\\n\\n # 1) The core transformation from data space into\\n # rectilinear space defined in the HammerTransform class.\\n self.transProjection = IdentityTransform()\\n # 2) The above has an output range that is not in the unit\\n # rectangle, so scale and translate it so it fits correctly\\n # within the axes. The peculiar calculations of xscale and\\n # yscale are specific to a Aitoff-Hammer projection, so don't\\n # worry about them too much.\\n self.transAffine = Affine2D.from_values(\\n 1., 0, 0.5, np.sqrt(3)/2., 0, 0)\\n self.transAffinedep = Affine2D.from_values(\\n 1., 0, -0.5, np.sqrt(3)/2., 0, 0)\\n #self.transAffine = IdentityTransform()\\n \\n # 3) This is the transformation from axes space to display\\n # space.\\n self.transAxes = BboxTransformTo(self.bbox)\\n\\n # Now put these 3 transforms together -- from data all the way\\n # to display coordinates. Using the '+' operator, these\\n # transforms will be applied \\\"in order\\\". The transforms are\\n # automatically simplified, if possible, by the underlying\\n # transformation framework.\\n self.transData = \\\\\\n self.transProjection + \\\\\\n self.transAffine + \\\\\\n self.transAxes\\n\\n # The main data transformation is set up. Now deal with\\n # gridlines and tick labels.\\n\\n # Longitude gridlines and ticklabels. The input to these\\n # transforms are in display space in x and axes space in y.\\n # Therefore, the input values will be in range (-xmin, 0),\\n # (xmax, 1). The goal of these transforms is to go from that\\n # space to display space. The tick labels will be offset 4\\n # pixels from the equator.\\n\\n self._xaxis_pretransform = IdentityTransform()\\n self._xaxis_transform = \\\\\\n self._xaxis_pretransform + \\\\\\n self.transData\\n self._xaxis_text1_transform = \\\\\\n Affine2D().scale(1.0, 0.0) + \\\\\\n self.transData + \\\\\\n Affine2D().translate(0.0, -20.0)\\n self._xaxis_text2_transform = \\\\\\n Affine2D().scale(1.0, 0.0) + \\\\\\n self.transData + \\\\\\n Affine2D().translate(0.0, -4.0)\\n\\n # Now set up the transforms for the latitude ticks. The input to\\n # these transforms are in axes space in x and display space in\\n # y. Therefore, the input values will be in range (0, -ymin),\\n # (1, ymax). The goal of these transforms is to go from that\\n # space to display space. The tick labels will be offset 4\\n # pixels from the edge of the axes ellipse.\\n\\n self._yaxis_transform = self.transData\\n yaxis_text_base = \\\\\\n self.transProjection + \\\\\\n (self.transAffine + \\\\\\n self.transAxes)\\n self._yaxis_text1_transform = \\\\\\n yaxis_text_base + \\\\\\n Affine2D().translate(-8.0, 0.0)\\n self._yaxis_text2_transform = \\\\\\n yaxis_text_base + \\\\\\n Affine2D().translate(8.0, 0.0)\",\n \"def _constructClippingPlane( self, viewProj, positive, axis):\\r\\n if positive: scale = 1\\r\\n else: scale = -1\\r\\n\\r\\n return Plane(viewProj[0,3] + scale*viewProj[0, axis],\\r\\n viewProj[1,3] + scale*viewProj[1, axis],\\r\\n viewProj[2,3] + scale*viewProj[2, axis],\\r\\n viewProj[3,3] + scale*viewProj[3, axis] )\",\n \"def boundary(active, objects):\\n limit = SIZE[1]\\n for obj in objects:\\n if active.pos_x == obj.pos_x:\\n limit = min(limit, obj.pos_y)\\n active.pos_y = limit-active.height\\n active.col_d = True\",\n \"def add_panel(self, panel):\\n assert panel.PANEL_ID not in self.panels\\n assert not self.tools, \\\"tools must be added after panels\\\"\\n self.panels[panel.PANEL_ID] = panel\\n panel.register_panel(self)\",\n \"def compare(self, other, scale=1.0):\\n import matplotlib.pyplot as plt\\n from matplotlib.collections import PatchCollection\\n from matplotlib.patches import Polygon, FancyArrow\\n\\n fig = plt.figure(figsize=(10, 10))\\n ax = fig.add_subplot(1, 1, 1)\\n\\n rects = []\\n arrows = []\\n for p, module in enumerate(self.modules):\\n for a, fragment in enumerate(module):\\n corners = fragment.corners()[:, :2] # Drop the Z dimension\\n corner1, corner1_opp = corners[0], corners[2]\\n\\n rects.append(Polygon(corners))\\n if a in {0, 7}:\\n cx, cy, _ = fragment.centre()\\n ax.text(cx, cy, str(a),\\n verticalalignment='center',\\n horizontalalignment='center')\\n elif a == 4:\\n cx, cy, _ = fragment.centre()\\n ax.text(cx, cy, 'p{}'.format(p),\\n verticalalignment='center',\\n horizontalalignment='center')\\n\\n panel2 = other.modules[p][a]\\n corners2 = panel2.corners()[:, :2]\\n corner2, corner2_opp = corners2[0], corners2[2]\\n dx, dy = corner2 - corner1\\n if not (dx == dy == 0):\\n sx, sy = corner1\\n arrows.append(FancyArrow(\\n sx, sy, scale * dx, scale * dy, width=5, head_length=4\\n ))\\n\\n dx, dy = corner2_opp - corner1_opp\\n if not (dx == dy == 0):\\n sx, sy = corner1_opp\\n arrows.append(FancyArrow(\\n sx, sy, scale * dx, scale * dy, width=5, head_length=5\\n ))\\n\\n pc = PatchCollection(rects, facecolor=(0.75, 1.0, 0.75), edgecolor=None)\\n ax.add_collection(pc)\\n ac = PatchCollection(arrows)\\n ax.add_collection(ac)\\n\\n # Set axis limits to fit all shapes, with some margin\\n all_x = np.concatenate([s.xy[:, 0] for s in arrows + rects])\\n all_y = np.concatenate([s.xy[:, 1] for s in arrows + rects])\\n ax.set_xlim(all_x.min() - 20, all_x.max() + 20)\\n ax.set_ylim(all_y.min() - 40, all_y.max() + 20)\\n\\n ax.set_title('Geometry comparison: {} → {}'\\n .format(self.filename, other.filename))\\n ax.text(1, 0, 'Arrows scaled: {}×'.format(scale),\\n horizontalalignment=\\\"right\\\", verticalalignment=\\\"bottom\\\",\\n transform=ax.transAxes)\\n return ax\",\n \"def render_panel(self):\\n size = self.env.GRID_NUM\\n panel = self.PANEL_HEIGHT\\n margin = self.MARGIN\\n screen = self.screen\\n cellWidth = self.CELL_WIDTH\\n\\n radius = (panel - 2 * margin) // 2\\n x_left = margin\\n x_right = (cellWidth + margin) * (self.env.GRID_NUM // 2) + margin\\n y = margin\\n w = (cellWidth + margin) * (self.env.GRID_NUM // 2) - margin\\n h = panel - margin\\n screenWidth = (cellWidth + margin) * size + margin\\n\\n DrawRect(screen, Colors.GRAY, [x_left, y, w, h])\\n DrawRect(screen, Colors.GRAY, [x_right, y, w, h])\\n DrawCircle(screen, Colors.BLACK, (x_left + margin + radius, margin + h // 2), radius)\\n DrawCircle(screen, Colors.WHITE, (x_right + margin + radius, margin + h // 2), radius)\\n if self.env.isBlackTurn():\\n DrawPolygon(screen, Colors.RED, ((margin, margin), (margin + panel // 3, margin), (margin, margin + panel // 3)))\\n else:\\n DrawPolygon(screen, Colors.RED, ((x_right, margin), (x_right + panel // 3, margin), (x_right, margin + panel // 3)))\\n\\n black_disks = self.env.num_black_disks()\\n white_disks = self.env.num_white_disks()\\n black_score = self.env.black_score\\n white_score = self.env.white_score\\n black_ai = self.agents[Player.BLACK].name\\n white_ai = self.agents[Player.WHITE].name\\n\\n pygame.font.init()\\n self.font = pygame.font.SysFont('Comic Sans MS', 16)\\n\\n text = self.font.render(f'{black_ai} ({black_score}) {black_disks}', False, (255, 255, 255))\\n text_rect = text.get_rect(midleft=(x_left + 2 * (margin + radius), panel // 2))\\n self.screen.blit(text, text_rect)\\n\\n text = self.font.render(f'{white_ai} ({white_score}) {white_disks}', False, (255, 255, 255))\\n text_rect = text.get_rect(midleft=(x_right + 2 * (margin + radius), panel // 2))\\n self.screen.blit(text, (x_right + 2 * (margin + radius), panel // 2 - 10))\",\n \"def _InitUI( self, two_axes = False ):\\n dpis = wx.ScreenDC().GetPPI()\\n size = ( WIDGET_PREF_SIZE[ 0 ] / dpis[ 0 ], WIDGET_PREF_SIZE[ 1 ] / dpis[ 0 ] )\\n self.fig = Figure( facecolor = '#ececec', figsize = size, dpi = dpis[ 0 ] )\\n\\n self._InitAxes()\\n# if two_axes:\\n# self.ax = self.fig.add_axes([ 0.1, 0.1, 0.85, 0.65 ])\\n# self.ax2 = self.ax.twiny()\\n# else:\\n# self.ax = self.fig.add_subplot( 111 )\\n self.canvas = FigureCanvas( self, -1, self.fig )\\n self.canvas.SetMinClientSize( wx.Size( 200, 200 ) )\\n self.toolbar = NavigationToolbar( self.canvas )\\n #self.toolbar.Realize()\\n self.toolbar.SetBackgroundColour( wx.Colour( 236, 236, 236, 255 ) )\\n self.toolbar.Show( False )\\n\\n sizer = wx.BoxSizer( wx.VERTICAL )\\n sizer.Add( self.toolbar, 0, wx.LEFT | wx.TOP | wx.BOTTOM | wx.EXPAND, 1 )\\n sizer.Add( self.canvas, 1, wx.LEFT | wx.TOP | wx.BOTTOM | wx.EXPAND, 1 )\\n self.SetSizer( sizer )\\n\\n self.callbackIds[ 'button_release_event' ] = \\\\\\n self.canvas.mpl_connect( 'button_release_event', self._OnMplMouseRelease )\\n self.callbackIds[ 'motion_notify_event' ] = \\\\\\n self.canvas.mpl_connect( 'motion_notify_event', self._OnMplMouseMotion )\\n\\n self.Bind( wx.EVT_CLOSE, self._OnClose )\\n self.Bind( wx.EVT_CONTEXT_MENU, self._OnContextMenu )\\n self.Bind( wx.EVT_SIZE, self._OnSize )\\n\\n self.timer = wx.Timer( self, TIMERID_RESIZE )\\n self.Bind( wx.EVT_TIMER, self._OnTimer )\",\n \"def boundary(self):\\n if self.pos.x < 0:\\n self.pos.x = 0\\n if self.pos.x > WIDTH - 48:\\n self.pos.x = WIDTH - 48\\n if self.pos.y < 0:\\n self.pos.y = 0\\n if self.pos.y > HEIGHT - 48:\\n self.pos.y = HEIGHT - 48\\n\\n self.rect.topleft = self.pos\",\n \"def transform_view(self):\\n translation = self.get_translation()\\n scale = self.get_scaling()\\n # update all non static visuals\\n for visual in self.paint_manager.get_visuals():\\n if not visual.get('is_static', False):\\n self.set_data(visual=visual['name'], \\n scale=scale, translation=translation)\",\n \"def __init__(self, parent):\\n super(StageVisualizer, self).__init__(parent)\\n\\n self.figure = matplotlib.figure.Figure()\\n self.axes = self.figure.add_subplot(111)\\n self.figure.subplots_adjust(top=1, bottom=0, right=1, left=0)\\n\\n self.axes.get_xaxis().set_visible(False)\\n self.axes.get_yaxis().set_visible(False)\\n\\n self.canvas = FigureCanvas(self, -1, self.figure)\\n\\n self.sizer = wx.BoxSizer(wx.VERTICAL)\\n self.sizer.Add(self.canvas, 1, wx.LEFT | wx.TOP | wx.GROW)\\n self.SetSizer(self.sizer)\\n\\n self.toolbar = NavigationToolbar(self.canvas)\\n self.toolbar.pan()\\n self.toolbar.Hide()\\n\\n self.Fit()\\n\\n self.zoomer = self.zoom_factory(self.axes, base_scale=1.5)\\n\\n self.canvas.Bind(wx.EVT_PAINT, self.on_paint)\",\n \"def create_sat_panels(self):\\n\\n # Dimensions of body\\n SAT_SIZE = self.ANI_SCALE*self.SAT_SCALE*np.asarray(self.SAT_PROPS[\\\"Size\\\"])/2\\n bx = SAT_SIZE[0]\\n by = SAT_SIZE[1]\\n bz = SAT_SIZE[2]\\n\\n # Panel length\\n L = bx\\n\\n # Panels\\n theta = self.PANEL_ANGLE*pi/180\\n px1 = bx - L*sin(theta)\\n py1 = by + L*cos(theta)\\n pz1 = bz\\n px2 = px1 + L*sin(theta)\\n py2 = py1 + L*cos(theta)\\n pz2 = pz1\\n\\n # Vertices\\n V = [\\n (-bx, by, -bz),\\n (-bx, by, bz),\\n (-px1, py1, pz1),\\n (-px1, py1, -pz1),\\n (-px1, py1, -pz1),\\n (-px1, py1, pz1),\\n (-px2, py2, pz2),\\n (-px2, py2, -pz2),\\n (-bx, -by, -bz),\\n (-bx, -by, bz),\\n (-px1, -py1, pz1),\\n (-px1, -py1, -pz1),\\n (-px1, -py1, -pz1),\\n (-px1, -py1, pz1),\\n (-px2, -py2, pz2),\\n (-px2, -py2, -pz2)\\n ]\\n\\n # Create faces\\n F = [\\n (0, 1, 2, 3),\\n (4, 5, 6, 7),\\n (8, 9, 10, 11),\\n (12, 13, 14, 15)\\n ]\\n\\n # Create building blocks of polydata\\n sat = vtk.vtkPolyData()\\n points = vtk.vtkPoints()\\n polys = vtk.vtkCellArray()\\n scalars = vtk.vtkFloatArray()\\n\\n # Load the point, cell and data attributes\\n for i in range(len(V)):\\n points.InsertPoint(i, V[i])\\n for i in range(len(F)):\\n polys.InsertNextCell(self.mkVtkIdList(F[i]))\\n for i in range(len(V)):\\n scalars.InsertTuple1(i, i)\\n \\n # Assign the pieces to the vtkPolyData.\\n sat.SetPoints(points)\\n del points\\n sat.SetPolys(polys)\\n del polys\\n sat.GetPointData().SetScalars(scalars)\\n del scalars\\n\\n # Mapper\\n mapper = vtk.vtkPolyDataMapper()\\n mapper.SetInputData(sat)\\n mapper.ScalarVisibilityOff()\\n\\n # Actor\\n actor = vtk.vtkActor()\\n actor.SetMapper(mapper)\\n actor.GetProperty().SetColor(0., 0., 0.8)\\n actor.GetProperty().SetAmbient(0.5)\\n actor.GetProperty().SetSpecular(.5)\\n actor.GetProperty().SetSpecularPower(10.0)\\n actor.GetProperty().SetDiffuse(0.2)\\n\\n # Move to sat position\\n actor.SetPosition(0, 0, -self.SAT_PROPS[\\\"Alt\\\"])\\n\\n return actor\",\n \"def paintScreen(self):\\n imgPath = GG.genteguada.GenteGuada.getInstance().getDataPath(BACKGROUND_LEFT)\\n self.imgBackgroundLeft = guiobjects.OcempImageMapTransparent(imgPath)\\n self.window.add_child(self.imgBackgroundLeft)\\n imgPath = GG.genteguada.GenteGuada.getInstance().getDataPath(BACKGROUND_RIGHT)\\n imgBackgroundRight = guiobjects.OcempImageMapTransparent(imgPath)\\n imgBackgroundRight.topleft = 297, 0\\n self.window.add_child(imgBackgroundRight)\",\n \"def initializePage(self):\\n WizardPage.initialize(self)\\n self.page.use(qt.QVBoxLayout())\\n\\n dims = [(\\\"DX\\\", 0.), (\\\"DY\\\", 0.)]\\n if self.give_field(\\\"model\\\").dim == 3:\\n dims.append((\\\"DZ\\\", 0.))\\n exp = self.give_field(\\\"exp-store\\\").give_exp(\\\"boundaries\\\")\\n lst = exp.find_groups(self.give_field(\\\"mesh\\\"))\\n tit = u\\\"Adding imposed degrees of freedom on groups\\\"\\n add_condition_selector(self, lst, dims, \\\"group-boundaries*\\\", tit)\",\n \"def vizualize_wall(self):\\n\\n\\t\\t#Points are converted from polar to cartesian here\\n\\t\\tpoint1 = Point()\\n\\t\\t#(-math.pi/4) represents the 45 degree rotation of the front point\\n\\t\\t#from the front of the robot\\n\\t\\tpoint1.x = math.cos((-math.pi/4))*self.front_point\\n\\t\\tpoint1.y = math.sin((-math.pi/4))*self.front_point\\n\\t\\tpoint2 = Point()\\n\\t\\t#(-3*math.pi/4) represents the back point's 90 degree rotaion from\\n\\t\\t#the front point\\n\\t\\tpoint2.x = math.cos((-3*math.pi/4))*self.back_point\\n\\t\\tpoint2.y = math.sin((-3*math.pi/4))*self.back_point\\n\\t\\tmy_marker = Marker(type=Marker.LINE_STRIP)\\n\\t\\tmy_marker.header.frame_id = \\\"base_link\\\"\\n\\t\\tmy_marker.color.a = 1\\n\\t\\tmy_marker.scale.x = .1\\n\\t\\tmy_marker.points = [point1, point2]\\n\\t\\tself.visualizer.publish(my_marker)\",\n \"def finalize_layout(self):\\n self.mbox.addLayout(self.hbtnbox)\\n self.mbox.addLayout(self.hbox)\\n self.setLayout(self.mbox)\",\n \"def project_grid(self):\\n\\n # option 1: no shared axes. Trees are scaled(?)\\n\\n\\n # option 2: shared axes. Spacing of tree\",\n \"def _independent_panel(width, height):\\n\\n from maya import cmds\\n\\n # center panel on screen\\n screen_width, screen_height = _get_screen_size()\\n topLeft = [int((screen_height-height)/2.0),\\n int((screen_width-width)/2.0)]\\n\\n window = cmds.window(width=width,\\n height=height,\\n topLeftCorner=topLeft,\\n menuBarVisible=False,\\n titleBar=False)\\n cmds.paneLayout()\\n panel = cmds.modelPanel(menuBarVisible=False,\\n label='CapturePanel')\\n\\n # Hide icons under panel menus\\n bar_layout = cmds.modelPanel(panel, q=True, barLayout=True)\\n cmds.frameLayout(bar_layout, e=True, collapse=True)\\n\\n cmds.showWindow(window)\\n\\n # Set the modelEditor of the modelPanel as the active view so it takes\\n # the playback focus. Does seem redundant with the `refresh` added in.\\n editor = cmds.modelPanel(panel, query=True, modelEditor=True)\\n cmds.modelEditor(editor, e=1, activeView=True)\\n\\n # Force a draw refresh of Maya so it keeps focus on the new panel\\n # This focus is required to force preview playback in the independent panel\\n cmds.refresh(force=True)\\n\\n try:\\n yield panel\\n finally:\\n # Delete the panel to fix memory leak (about 5 mb per capture)\\n cmds.deleteUI(panel, panel=True)\\n cmds.deleteUI(window)\",\n \"def _locator(self, axes, renderer):\\n x0, y0, x1, y1 = self.rect\\n width_dict = dict()\\n cut_ax_dict = self.axes\\n for cut_ax in cut_ax_dict.values():\\n bounds = cut_ax.get_object_bounds()\\n if not bounds:\\n # This happens if the call to _map_show was not\\n # succesful. As it happens asyncroniously (during a\\n # refresh of the figure) we capture the problem and\\n # ignore it: it only adds a non informative traceback\\n bounds = [0, 1, 0, 1]\\n xmin, xmax, ymin, ymax = bounds\\n width_dict[cut_ax.ax] = (xmax - xmin)\\n total_width = float(sum(width_dict.values()))\\n for ax, width in width_dict.items():\\n width_dict[ax] = width/total_width*(x1 -x0)\\n left_dict = dict()\\n left = float(x0)\\n for coord, cut_ax in sorted(cut_ax_dict.items()):\\n left_dict[cut_ax.ax] = left\\n this_width = width_dict[cut_ax.ax]\\n left += this_width\\n return transforms.Bbox([[left_dict[axes], y0],\\n [left_dict[axes] + width_dict[axes], y1]])\",\n \"def bbox_shift_scale_rotate(bbox, angle, scale, dx, dy, rotate_method, rows, cols, **kwargs): # skipcq: PYL-W0613\\n height, width = rows, cols\\n center = (width / 2, height / 2)\\n if rotate_method == \\\"ellipse\\\":\\n x_min, y_min, x_max, y_max = bbox_rotate(bbox, angle, rotate_method, rows, cols)\\n matrix = cv2.getRotationMatrix2D(center, 0, scale)\\n else:\\n x_min, y_min, x_max, y_max = bbox[:4]\\n matrix = cv2.getRotationMatrix2D(center, angle, scale)\\n matrix[0, 2] += dx * width\\n matrix[1, 2] += dy * height\\n x = np.array([x_min, x_max, x_max, x_min])\\n y = np.array([y_min, y_min, y_max, y_max])\\n ones = np.ones(shape=(len(x)))\\n points_ones = np.vstack([x, y, ones]).transpose()\\n points_ones[:, 0] *= width\\n points_ones[:, 1] *= height\\n tr_points = matrix.dot(points_ones.T).T\\n tr_points[:, 0] /= width\\n tr_points[:, 1] /= height\\n\\n x_min, x_max = min(tr_points[:, 0]), max(tr_points[:, 0])\\n y_min, y_max = min(tr_points[:, 1]), max(tr_points[:, 1])\\n\\n return x_min, y_min, x_max, y_max\",\n \"def toggleLatticeFrame(self):\\n if self.parent.getCurrentPipelinePage().refState is None:\\n return\\n\\n if self.latticeFrame.visible:\\n self.removeLatticeFrame()\\n\\n else:\\n self.addLatticeFrame()\\n\\n self.reinit()\",\n \"def scene_adding_panel(self, context):\\r\\n \\r\\n AM = context.window_manager.asset_m\\r\\n layout = self.layout\\r\\n box = layout.box()\\r\\n view = context.space_data\\r\\n fx_settings = view.fx_settings\\r\\n ssao_settings = fx_settings.ssao\\r\\n thumbnails_path = get_directory('icons')\\r\\n extentions = (\\\".jpg\\\", \\\".jpeg\\\", \\\".png\\\")\\r\\n thumb_list = [thumb.rsplit(\\\".\\\", 1)[0] for thumb in listdir(thumbnails_path) if thumb.endswith(extentions)]\\r\\n \\r\\n if AM.scene_name not in thumb_list or AM.scene_name in thumb_list and AM.replace_rename == 'replace':\\r\\n if AM.scene_name in thumb_list and AM.replace_rename == 'replace':\\r\\n box.label(\\\"\\\\\\\" {} \\\\\\\" already exist\\\".format(AM.scene_name), icon='ERROR')\\r\\n box.separator()\\r\\n row = box.row(align=True)\\r\\n row.prop(AM, \\\"replace_rename\\\", text=\\\" \\\", expand=True)\\r\\n if AM.replace_rename == 'rename':\\r\\n box.prop(AM, \\\"scene_name\\\", text=\\\"\\\")\\r\\n \\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Scene name:\\\")\\r\\n row.prop(AM, \\\"scene_name\\\", text = \\\"\\\")\\r\\n row = box.row(align = True)\\r\\n row.prop(AM, \\\"render_type\\\", text = \\\" \\\", expand = True)\\r\\n row = box.row()\\r\\n row.label(\\\"Thumbnail extention:\\\")\\r\\n row = box.row(align = True)\\r\\n row.prop(AM, \\\"thumb_ext\\\", expand = True)\\r\\n\\r\\n # --------------------- # \\r\\n # OPENGL THUMBNAIL #\\r\\n # --------------------- #\\r\\n \\r\\n if AM.render_type == 'opengl':\\r\\n row = box.row(align=True)\\r\\n row.operator(\\\"object.setup_ogl_render\\\", text=\\\"Setup OGL render\\\" if not \\\"AM_OGL_Camera\\\" in [obj.name for obj in context.scene.objects] else \\\"View camera\\\", icon='ZOOMIN')\\r\\n row.operator(\\\"object.remove_ogl_render\\\", text=\\\"\\\", icon='ZOOMOUT')\\r\\n row = layout.column()\\r\\n row = box.row(align=True) \\r\\n row.label(\\\"Background:\\\")\\r\\n row.prop(AM, \\\"background_alpha\\\", text=\\\"\\\")\\r\\n row = box.row(align=True)\\r\\n row.prop(view, \\\"show_only_render\\\")\\r\\n row = box.row(align=True)\\r\\n row.prop(view, \\\"use_matcap\\\")\\r\\n if view.use_matcap :\\r\\n row.prop(AM, \\\"matcap_options\\\", text=\\\"\\\", icon='TRIA_UP' if AM.matcap_options else 'TRIA_DOWN') \\r\\n if AM.matcap_options:\\r\\n row = box.row(align=True)\\r\\n row.template_icon_view(view, \\\"matcap_icon\\\")\\r\\n row = box.row(align=True)\\r\\n row.prop(fx_settings, \\\"use_ssao\\\", text=\\\"Ambient Occlusion\\\")\\r\\n if fx_settings.use_ssao:\\r\\n row.prop(AM, \\\"ao_options\\\", text=\\\"\\\", icon='TRIA_UP' if AM.ao_options else 'TRIA_DOWN') \\r\\n if AM.ao_options:\\r\\n subcol = box.column(align=True)\\r\\n subcol.prop(ssao_settings, \\\"factor\\\")\\r\\n subcol.prop(ssao_settings, \\\"distance_max\\\")\\r\\n subcol.prop(ssao_settings, \\\"attenuation\\\")\\r\\n subcol.prop(ssao_settings, \\\"samples\\\")\\r\\n subcol.prop(ssao_settings, \\\"color\\\")\\r\\n \\r\\n # -------------------- # \\r\\n # IMAGE THUMBNAIL #\\r\\n # -------------------- #\\r\\n \\r\\n elif AM.render_type == 'image':\\r\\n row = box.row(align=True)\\r\\n row.prop(AM, \\\"image_type\\\", text=\\\" \\\", expand=True)\\r\\n if AM.image_type == 'disk':\\r\\n box.label(\\\"Choose your thumbnail\\\")\\r\\n box.prop(AM, \\\"custom_thumbnail_path\\\", text=\\\"\\\")\\r\\n else:\\r\\n box.prop_search(AM, \\\"render_name\\\", bpy.data, \\\"images\\\", text=\\\"\\\") \\r\\n \\r\\n row = box.row(align=True)\\r\\n \\r\\n if AM.scene_name and ((AM.scene_name not in thumb_list or AM.replace_rename == 'replace') and AM.render_type == 'opengl' or AM.render_type == 'image' and (AM.image_type == 'disk' and AM.custom_thumbnail_path or AM.image_type == 'rendered' and AM.render_name)):\\r\\n \\r\\n row.operator(\\\"object.add_scene_in_library\\\", text=\\\"OK\\\", icon='FILE_TICK') \\r\\n row.operator(\\\"object.cancel_panel_choise\\\", text=\\\"Cancel\\\", icon='X')\\r\\n \\r\\n else:\\r\\n box.label(\\\"\\\\\\\" {} \\\\\\\" already exist\\\".format(AM.scene_name), icon='ERROR')\\r\\n box.separator()\\r\\n row = box.row(align=True)\\r\\n row.prop(AM, \\\"replace_rename\\\", text=\\\" \\\", expand=True)\\r\\n if AM.replace_rename == 'rename':\\r\\n box.prop(AM, \\\"scene_name\\\", text=\\\"\\\")\\r\\n row = box.row()\\r\\n row.operator(\\\"object.cancel_panel_choise\\\", text=\\\"Cancel\\\", icon='X')\",\n \"def enableEditorDrop():\\n\\n perspPanel = cmds.getPanel( withLabel='Persp View')\\n panelControl = cmds.panel( perspPanel, query=True, control=True)\\n cmds.control(panelControl, edit=True, dropCallback=panelDropLoad)\\n global viewportHeight\\n viewportHeight = cmds.control(panelControl, query=True, h=True)\",\n \"def ibl_options_panel(self, context):\\r\\n \\r\\n AM = context.window_manager.asset_m\\r\\n node_group = bpy.context.scene.world.node_tree.nodes\\r\\n layout = self.layout\\r\\n \\r\\n box = layout.box()\\r\\n row = box.row()\\r\\n row.alignment = 'CENTER'\\r\\n row.label(\\\"IMAGE\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Rotation:\\\")\\r\\n col = row.column()\\r\\n col.prop(node_group[\\\"Mapping\\\"], \\\"rotation\\\", text = \\\"\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Projection:\\\")\\r\\n row.prop(AM, \\\"projection\\\", text = \\\"\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Blur:\\\")\\r\\n row.prop(node_group[\\\"ImageBlur\\\"].inputs[1], \\\"default_value\\\", text = \\\"\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Visible:\\\")\\r\\n row.prop(bpy.context.scene.world.cycles_visibility, \\\"camera\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Transparent:\\\")\\r\\n row.prop(bpy.context.scene.cycles, \\\"film_transparent\\\")\\r\\n \\r\\n \\r\\n \\r\\n box = layout.box()\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Gamma:\\\")\\r\\n row.prop(node_group[\\\"AM_IBL_Tool\\\"].inputs[0], \\\"default_value\\\", text = \\\"\\\")\\r\\n \\r\\n box = layout.box()\\r\\n row = box.row()\\r\\n row.alignment = 'CENTER'\\r\\n row.label(\\\"LIGHT\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Strength:\\\")\\r\\n row.prop(node_group[\\\"AM_IBL_Tool\\\"].inputs[2], \\\"default_value\\\", text = \\\"\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Saturation:\\\")\\r\\n row.prop(node_group[\\\"AM_IBL_Tool\\\"].inputs[3], \\\"default_value\\\", text = \\\"\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Hue:\\\")\\r\\n row.prop(node_group[\\\"AM_IBL_Tool\\\"].inputs[4], \\\"default_value\\\", text = \\\"\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Mix Hue:\\\")\\r\\n row.prop(node_group[\\\"AM_IBL_Tool\\\"].inputs[5], \\\"default_value\\\", text = \\\"\\\")\\r\\n \\r\\n box = layout.box()\\r\\n row = box.row()\\r\\n row.alignment = 'CENTER'\\r\\n row.label(\\\"GLOSSY\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Strength:\\\")\\r\\n row.prop(node_group[\\\"AM_IBL_Tool\\\"].inputs[7], \\\"default_value\\\", text = \\\"\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Saturation:\\\")\\r\\n row.prop(node_group[\\\"AM_IBL_Tool\\\"].inputs[8], \\\"default_value\\\", text = \\\"\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Hue:\\\")\\r\\n row.prop(node_group[\\\"AM_IBL_Tool\\\"].inputs[9], \\\"default_value\\\", text = \\\"\\\")\\r\\n row = box.row(align = True)\\r\\n row.label(\\\"Mix Hue:\\\")\\r\\n row.prop(node_group[\\\"AM_IBL_Tool\\\"].inputs[10], \\\"default_value\\\", text = \\\"\\\")\\r\\n \\r\\n layout.operator(\\\"wm.save_ibl_settings\\\", text = \\\"Save settings\\\", icon = 'FILE_TICK')\",\n \"def layout_graphics(self):\\n # Graphics layout object to place viewboxes in\\n self.g_layout = pg.GraphicsLayoutWidget(border=(80, 80, 80))\\n self.g_layout.setCursor(QtCore.Qt.CrossCursor)\\n\\n # Viewboxes for images\\n # aspect locked so that pixels are square\\n # y inverted so that (0,0) is top left as in Thorlabs software\\n options = {\\\"lockAspect\\\":True, \\\"invertY\\\":True}\\n self.vb_image = self.g_layout.addViewBox(row=0, col=0, rowspan=2, **options)\\n self.vb_zoom = self.g_layout.addViewBox(row=0, col=2, **options)\\n self.vb_residuals = self.g_layout.addViewBox(row=1, col=2, **options)\\n\\n # Link zoom and residual views\\n self.vb_zoom.setXLink(self.vb_residuals)\\n self.vb_zoom.setYLink(self.vb_residuals)\\n\\n # Viewboxes for slice data\\n # Both boxes have mouse disabled - range is fixed so we don't want to\\n # scale them accidentally\\n # Y box has y inverted to match the main image\\n # Y box has x inverted so that zero pixel value is far from the image\\n options = {\\\"enableMouse\\\":False, \\\"enableMenu\\\": False}\\n self.vb_x = self.g_layout.addViewBox(row=2, col=0, **options)\\n self.vb_y = self.g_layout.addViewBox(row=0, col=1, rowspan=2,\\n invertX=True, invertY=True, **options)\\n\\n # Link the slice axes to the main image so that when we zoom/pan the\\n # main image, our slices zoom/pan also\\n self.vb_x.setXLink(self.vb_image)\\n self.vb_y.setYLink(self.vb_image)\\n\\n # Disable autoscaling and fix range to maximum pixel intensity\\n self.vb_x.setRange(yRange=(0,255))\\n self.vb_y.setRange(xRange=(0,255))\\n self.vb_x.disableAutoRange(axis=self.vb_x.YAxis)\\n self.vb_y.disableAutoRange(axis=self.vb_y.XAxis)\\n\\n # Background color must not be black so that we can see where images\\n # start/end\\n color = pg.mkColor(40,40,40)\\n self.vb_image.setBackgroundColor(color)\\n self.vb_zoom.setBackgroundColor(color)\\n self.vb_residuals.setBackgroundColor(color)\\n self.vb_x.setBackgroundColor(color)\\n self.vb_y.setBackgroundColor(color)\\n self.g_layout.setBackground(color)\\n\\n self.vb_image.addItem(self.image)\\n self.vb_image.addItem(self.fit_v_line)\\n self.vb_image.addItem(self.fit_h_line)\\n self.vb_image.addItem(self.mark_v_line)\\n self.vb_image.addItem(self.mark_h_line)\\n # self.vb_image.addItem(self.cursor_text)\\n self.vb_image.addItem(self.cursor_delta)\\n self.vb_image.addItem(self.beam_delta)\\n self.vb_image.addItem(self.history_plot)\\n # Figure out how to overlay properly?\\n # self.vb_image.addItem(self.x_slice)\\n # self.vb_image.addItem(self.x_fit)\\n # self.vb_image.addItem(self.y_slice)\\n # self.vb_image.addItem(self.y_fit)\\n self.vb_zoom.addItem(self.zoom)\\n self.vb_zoom.addItem(self.fit_maj_line)\\n self.vb_zoom.addItem(self.fit_min_line)\\n self.vb_zoom.addItem(self.zoom_text)\\n self.vb_residuals.addItem(self.residuals)\\n self.vb_residuals.addItem(self.residuals_text)\\n self.vb_x.addItem(self.x_slice)\\n self.vb_x.addItem(self.x_fit)\\n self.vb_x.addItem(self.cursor_v)\\n self.vb_y.addItem(self.y_slice)\\n self.vb_y.addItem(self.y_fit)\\n self.vb_y.addItem(self.cursor_h)\\n\\n self.res_legend.setParentItem(self.vb_residuals)\\n self.cursor_text.setParentItem(self.vb_image)\\n\\n self.vb_image.setRange(QtCore.QRectF(0, 0, 1280, 1024))\\n self.vb_zoom.setRange(QtCore.QRectF(0, 0, 50, 50))\\n self.vb_residuals.setRange(QtCore.QRectF(0, 0, 50, 50))\\n\\n #\\n # Size hints below here\\n #\\n self.g_layout.ci.layout.setColumnStretchFactor(0, 4)\\n self.g_layout.ci.layout.setColumnStretchFactor(1, 1)\\n self.g_layout.ci.layout.setColumnStretchFactor(2, 2)\\n self.g_layout.ci.layout.setRowStretchFactor(0, 2)\\n self.g_layout.ci.layout.setRowStretchFactor(1, 2)\\n self.g_layout.ci.layout.setRowStretchFactor(2, 1)\\n\\n self.vb_x.setMinimumHeight(50)\\n self.vb_y.setMinimumWidth(50)\\n self.vb_x.setMaximumHeight(100)\\n self.vb_y.setMaximumWidth(100)\\n self.vb_image.setMinimumSize(640, 512)\\n self.vb_zoom.setMinimumSize(320, 320)\\n self.vb_residuals.setMinimumSize(320, 320)\\n\\n self.g_layout.setMinimumSize(1100,562)\",\n \"def setup_mpl_visuals(self, axes=None) -> None:\\n if axes is None:\\n axes = self.subplot\\n axes.patch.set_facecolor('white')\\n axes.set_aspect('equal', 'box')\\n axes.set_xlim(-10, 10, auto=True)\\n axes.set_ylim(-10, 10, auto=True)\\n # TODO: Make XYLim confort to window size/dimensions\\n axes.set_xticks([])\\n axes.set_yticks([])\\n self.figure.subplots_adjust(bottom=0, top=1, left=0, right=1)\\n axes.axis('off')\",\n \"def drawCoordinatePlane_region():\\r\\n turtle2 = t.Screen()\\r\\n turtle2.title(\\\"Life Expectancy versus Region\\\")\\r\\n t2.speed(0)\\r\\n t3.speed(0)\\r\\n setTurtle(t0)\\r\\n setTurtle(t1)\\r\\n setTurtle(t2)\\r\\n setTurtle(t3)\\r\\n drawAxes(t0)\\r\\n t1.left(90)\\r\\n drawAxes(t1)\\r\\n t0.pu()\\r\\n t0.fd(-80)\\r\\n t0.lt(90)\\r\\n drawlabels(t0, t1)\\r\\n drawPoints(t0, t1)\\r\\n t0.pu()\\r\\n t1.pu()\\r\\n t2.pu()\\r\\n t3.pu()\\r\\n t0.goto(initialCoordinates())\\r\\n t1.goto(initialCoordinates())\\r\\n t2.goto(initialCoordinates())\\r\\n t3.goto(initialCoordinates())\\r\\n t1.lt(90)\",\n \"def forward_phi(self):\\n for f in self.component_fields:\\n f.require_layout(self._layout1)\",\n \"def page_up(self):\\n self.set_initial_offset(self.initial_offset - self.my_surface.get_height())\",\n \"def translate(self, vect):\\n self.pl.Base = vect\\n\\n self.comp.Placement = self.pl\\n self.box.Placement = self.pl\",\n \"def postInit(self):\\n self.save_transform = [\\\"root\\\", \\\"top\\\", \\\"bottom\\\", \\\"ext\\\", \\\"int\\\"]\",\n \"def setup_pipeline(self):\\n # Create the axes and set things up.\\n axes = CubeAxesActor2D(number_of_labels= 2,\\n font_factor=1.5,\\n fly_mode='outer_edges',\\n corner_offset=0.0,\\n scaling=False)\\n axes.axis_title_text_property.shadow = False\\n axes.axis_label_text_property.shadow = False\\n\\n # Set the axes.\\n self.axes = axes\",\n \"def DrawPanel(screen, panel_x, panel_y, panel_len, panel_width):\\n pygame.draw.rect(screen, (255,0,0),(panel_x, panel_y, panel_len*2, panel_width*2), 4)\",\n \"def test_panel(self):\\n p = MailToolbarPanel(*self.panel_args)\\n self.assertEqual(p.toolbar, self.toolbar)\",\n \"def render(self):\\n\\n theta = self.angle*math.pi/180.0\\n cth = math.cos(theta)\\n sth = math.sin(theta)\\n pts = []\\n cornerpts = []\\n\\n for vertex in self.points:\\n x = vertex[0] + self.pos[0] - self.anchor[0]\\n y = vertex[1] + self.pos[1] - self.anchor[1]\\n\\n xt = x * cth - y * sth\\n yt = x * sth + y * cth\\n\\n x = xt + self.anchor[0]\\n y = yt + self.anchor[1]\\n\\n cornerpts.append([x,y])\\n pts.append(gr.Point(self.scale * x, self.win.getHeight() - self.scale*y))\\n\\n self.corners = cornerpts\\n self.vis = [gr.Polygon(pts)]\",\n \"def Bas():\\r\\n X1, Y1, X2, Y2 = canvas.coords(boule)\\r\\n canvas.coords(boule,X1,Y1+20,X2,Y2+20)\",\n \"def frame():\\n fig = plt.figure(figsize = (6, 3))\\n\\n plt.subplots_adjust(left=.15, bottom=.2, right=.95, top=.9)\\n ax = fig.add_subplot(111)\\n \\n ax.tick_params(axis=\\\"x\\\", labelsize=12)\\n ax.tick_params(axis=\\\"y\\\", labelsize=12)\\n\\n return fig, ax\",\n \"def layoutRightPanel(self):\\n nRow = 0\\n self.rightPanel.removeAll()\\n self.rightPanel.add(JLabel(\\\"State machine cache?\\\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n __nRow_5 = nRow\\n nRow += 1\\n self.rightPanel.add(self.cacheStateMachine, GridBagConstraints(1, __nRow_5, 1, 1, 1.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n if self.strategy.getSelectedItem().__str__() == \\\"Heuristic\\\":\\n __nRow_6 = nRow\\n nRow += 1\\n __nRow_7 = nRow\\n nRow += 1\\n __nRow_8 = nRow\\n nRow += 1\\n __nRow_9 = nRow\\n nRow += 1\\n __nRow_10 = nRow\\n nRow += 1\\n self.rightPanel.add(JLabel(\\\"Max plys?\\\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n self.rightPanel.add(self.maxPlys, GridBagConstraints(1, __nRow_6, 1, 1, 0.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n self.rightPanel.add(JLabel(\\\"Focus Heuristic Weight\\\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n self.rightPanel.add(self.heuristicFocus, GridBagConstraints(1, __nRow_7, 1, 1, 0.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n self.rightPanel.add(JLabel(\\\"Mobility Heuristic Weight\\\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n self.rightPanel.add(self.heuristicMobility, GridBagConstraints(1, __nRow_8, 1, 1, 0.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n self.rightPanel.add(JLabel(\\\"Opponent Focus Heuristic Weight\\\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n self.rightPanel.add(self.heuristicOpponentFocus, GridBagConstraints(1, __nRow_9, 1, 1, 0.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n self.rightPanel.add(JLabel(\\\"Opponent Mobility Heuristic Weight\\\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n self.rightPanel.add(self.heuristicOpponentMobility, GridBagConstraints(1, __nRow_10, 1, 1, 0.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n if self.strategy.getSelectedItem().__str__() == \\\"Monte Carlo\\\":\\n __nRow_11 = nRow\\n nRow += 1\\n self.rightPanel.add(JLabel(\\\"Goal Decay Rate\\\"), GridBagConstraints(0, nRow, 1, 1, 0.0, 0.0, GridBagConstraints.EAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n self.rightPanel.add(self.mcDecayRate, GridBagConstraints(1, __nRow_11, 1, 1, 0.0, 0.0, GridBagConstraints.WEST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n __nRow_12 = nRow\\n nRow += 1\\n self.rightPanel.add(JLabel(), GridBagConstraints(2, __nRow_12, 1, 1, 1.0, 1.0, GridBagConstraints.SOUTHEAST, GridBagConstraints.NONE, Insets(5, 5, 5, 5), 5, 5))\\n self.rightPanel.repaint()\",\n \"def add_lattice(): \\n # Switch in object mode\\n bpy.ops.object.mode_set(mode='OBJECT') \\n \\n # Get the active object\\n obj = bpy.context.active_object\\n \\n # Check if there is a lattice object\\n flagLattice = False\\n for o in bpy.data.objects:\\n if o.type == 'LATTICE':\\n flagLattice = True\\n \\n # Add a lattice if there is not\\n if flagLattice == False:\\n # Get the name of the object\\n nameObject = obj.name\\n \\n # Add the lattice\\n bpy.ops.object.add(type='LATTICE', enter_editmode=False, align='WORLD', location=(0, 0, 0), scale=(1, 1, 1))\\n \\n # Select the object\\n bpy.context.view_layer.objects.active = bpy.data.objects[nameObject]\\n bpy.data.objects[nameObject].select_set(True)\\n bpy.data.objects[\\\"Lattice\\\"].select_set(False)\\n \\n\\n\\n # Add the vertices location in an array and find the max and min coordinates of the mesh\\n tabVertices = []\\n xPlus = float('-inf')\\n xMoins = float('inf')\\n yPlus = float('-inf')\\n yMoins = float('inf')\\n zPlus = float('-inf')\\n zMoins = float('inf')\\n for vertex in obj.data.vertices:\\n tabVertices.append(obj.matrix_world @ vertex.co)\\n if xPlus < (obj.matrix_world @ vertex.co).x:\\n xPlus = (obj.matrix_world @ vertex.co).x\\n elif xMoins > (obj.matrix_world @ vertex.co).x:\\n xMoins = (obj.matrix_world @ vertex.co).x\\n \\n if yPlus < (obj.matrix_world @ vertex.co).y:\\n yPlus = (obj.matrix_world @ vertex.co).y\\n elif yMoins > (obj.matrix_world @ vertex.co).y:\\n yMoins = (obj.matrix_world @ vertex.co).y\\n \\n if zPlus < (obj.matrix_world @ vertex.co).z:\\n zPlus = (obj.matrix_world @ vertex.co).z\\n elif zMoins > (obj.matrix_world @ vertex.co).z:\\n zMoins = (obj.matrix_world @ vertex.co).z\\n\\n # Set the size and the location of the lattice\\n bpy.data.objects[\\\"Lattice\\\"].scale = (obj.dimensions[0], obj.dimensions[1], obj.dimensions[2])\\n bpy.data.objects[\\\"Lattice\\\"].location = ((xPlus+xMoins)/2, (yPlus+yMoins)/2,(zPlus+zMoins)/2)\\n\\n # Update the float properties of the lattice and init them\\n bpy.types.Scene.lattice_size_x = bpy.props.FloatProperty(name = \\\"Size X\\\", min = 0, max = 2*obj.dimensions[0], soft_min = 0, soft_max = 2*obj.dimensions[0], step = 10, get=Get_And_Set_Lattice.get_lattice_size_x, set=Get_And_Set_Lattice.set_lattice_size_x, unit = 'LENGTH')\\n bpy.types.Scene.lattice_size_y = bpy.props.FloatProperty(name = \\\"Size Y\\\", min = 0, max = 2*obj.dimensions[1], soft_min = 0, soft_max = 2*obj.dimensions[1], step = 10, get=Get_And_Set_Lattice.get_lattice_size_y, set=Get_And_Set_Lattice.set_lattice_size_y, unit = 'LENGTH')\\n bpy.types.Scene.lattice_size_z = bpy.props.FloatProperty(name = \\\"Size Z\\\", min = 0, max = 2*obj.dimensions[2], soft_min = 0, soft_max = 2*obj.dimensions[2], step = 10, get=Get_And_Set_Lattice.get_lattice_size_z, set=Get_And_Set_Lattice.set_lattice_size_z, unit = 'LENGTH')\\n \\n bpy.context.scene.lattice_size_x = obj.dimensions[0]\\n bpy.context.scene.lattice_size_y = obj.dimensions[1]\\n bpy.context.scene.lattice_size_z = obj.dimensions[2]\\n \\n bpy.types.Scene.lattice_offset_x = bpy.props.FloatProperty(name = \\\"Size X\\\", min = -obj.dimensions[0], max = obj.dimensions[0], soft_min = -obj.dimensions[0], soft_max = obj.dimensions[0], step = 10, get=Get_And_Set_Lattice.get_lattice_offset_x, set=Get_And_Set_Lattice.set_lattice_offset_x, unit = 'LENGTH')\\n bpy.types.Scene.lattice_offset_y = bpy.props.FloatProperty(name = \\\"Size Y\\\", min = -obj.dimensions[1], max = obj.dimensions[1], soft_min = -obj.dimensions[1], soft_max = obj.dimensions[1], step = 10, get=Get_And_Set_Lattice.get_lattice_offset_y, set=Get_And_Set_Lattice.set_lattice_offset_y, unit = 'LENGTH')\\n bpy.types.Scene.lattice_offset_z = bpy.props.FloatProperty(name = \\\"Size Z\\\", min = -obj.dimensions[2], max = obj.dimensions[2], soft_min = -obj.dimensions[2], soft_max = obj.dimensions[2], step = 10, get=Get_And_Set_Lattice.get_lattice_offset_z, set=Get_And_Set_Lattice.set_lattice_offset_z, unit = 'LENGTH')\\n \\n bpy.context.scene.lattice_offset_x = 0\\n bpy.context.scene.lattice_offset_y = 0\\n bpy.context.scene.lattice_offset_z = 0\",\n \"def reshape(self,bottom,top):\\n pass\",\n \"def hflip(self):\\n self.leftimg, self.rightimg = self.rightimg, self.leftimg\",\n \"def _create_canvas(self, parent):\\n # The panel lets us add additional controls.\\n panel = wx.Panel(parent, -1, style=wx.CLIP_CHILDREN)\\n sizer = wx.BoxSizer(wx.VERTICAL)\\n panel.SetSizer(sizer)\\n # matplotlib commands to create a canvas\\n mpl_control = FigureCanvas(panel, -1, self.value)\\n sizer.Add(mpl_control, 1, wx.LEFT | wx.TOP | wx.GROW)\\n toolbar = NToolbar(mpl_control)\\n sizer.Add(toolbar, 0, wx.EXPAND)\\n self.value.canvas.SetMinSize((10,10))\\n return panel\",\n \"def orientWP(self):\\n import DraftGeomUtils\\n if hasattr(App, \\\"DraftWorkingPlane\\\"):\\n if len(self.node) > 1 and self.obj:\\n n = DraftGeomUtils.getNormal(self.obj.Shape)\\n if not n:\\n n = App.DraftWorkingPlane.axis\\n p = self.node[-1]\\n v = self.node[-2].sub(self.node[-1])\\n v = v.negative()\\n if not self.oldWP:\\n self.oldWP = App.DraftWorkingPlane.copy()\\n App.DraftWorkingPlane.alignToPointAndAxis(p, n, upvec=v)\\n if hasattr(Gui, \\\"Snapper\\\"):\\n Gui.Snapper.setGrid()\\n Gui.Snapper.restack()\\n if self.planetrack:\\n self.planetrack.set(self.node[-1])\",\n \"def draw(self, screen):\\n self.draw_left_zone(screen)\\n self.draw_middle_zone(screen)\\n self.draw_right_zone(screen)\",\n \"def recalculate_transform(self):\\n bias_mat = wireframe.translationMatrix(*self.bias)\\n rot_mat = wireframe.rotateMatrix(*self.view_angle)\\n scale_mat = wireframe.scaleMatrix(*self.scale)\\n\\n self.tf_wireframe.nodes = (self.wireframe.nodes - self._center_half) @ \\\\\\n rot_mat @ scale_mat @ bias_mat\",\n \"def Split(self, page, direction):\\r\\n \\r\\n cli_size = self.GetClientSize()\\r\\n\\r\\n # get the page's window pointer\\r\\n wnd = self.GetPage(page)\\r\\n if not wnd:\\r\\n return\\r\\n\\r\\n # notebooks with 1 or less pages can't be split\\r\\n if self.GetPageCount() < 2:\\r\\n return\\r\\n\\r\\n # find out which tab control the page currently belongs to\\r\\n\\r\\n src_tabs, src_idx = self.FindTab(wnd)\\r\\n if not src_tabs:\\r\\n return\\r\\n \\r\\n # choose a split size\\r\\n if self.GetPageCount() > 2:\\r\\n split_size = self.CalculateNewSplitSize()\\r\\n else: \\r\\n # because there are two panes, always split them\\r\\n # equally\\r\\n split_size = self.GetClientSize()\\r\\n split_size.x /= 2\\r\\n split_size.y /= 2\\r\\n\\r\\n # create a new tab frame\\r\\n new_tabs = TabFrame(self)\\r\\n new_tabs._rect = wx.RectPS(wx.Point(0, 0), split_size)\\r\\n new_tabs.SetTabCtrlHeight(self._tab_ctrl_height)\\r\\n self._tab_id_counter += 1\\r\\n new_tabs._tabs = AuiTabCtrl(self, self._tab_id_counter)\\r\\n \\r\\n new_tabs._tabs.SetArtProvider(self._tabs.GetArtProvider().Clone())\\r\\n new_tabs._tabs.SetAGWFlags(self._agwFlags)\\r\\n dest_tabs = new_tabs._tabs\\r\\n\\r\\n page_info = src_tabs.GetPage(src_idx)\\r\\n if page_info.control:\\r\\n self.ReparentControl(page_info.control, dest_tabs)\\r\\n \\r\\n # create a pane info structure with the information\\r\\n # about where the pane should be added\\r\\n pane_info = framemanager.AuiPaneInfo().Bottom().CaptionVisible(False)\\r\\n\\r\\n if direction == wx.LEFT:\\r\\n \\r\\n pane_info.Left()\\r\\n mouse_pt = wx.Point(0, cli_size.y/2)\\r\\n \\r\\n elif direction == wx.RIGHT:\\r\\n \\r\\n pane_info.Right()\\r\\n mouse_pt = wx.Point(cli_size.x, cli_size.y/2)\\r\\n \\r\\n elif direction == wx.TOP:\\r\\n \\r\\n pane_info.Top()\\r\\n mouse_pt = wx.Point(cli_size.x/2, 0)\\r\\n \\r\\n elif direction == wx.BOTTOM:\\r\\n \\r\\n pane_info.Bottom()\\r\\n mouse_pt = wx.Point(cli_size.x/2, cli_size.y)\\r\\n \\r\\n self._mgr.AddPane(new_tabs, pane_info, mouse_pt)\\r\\n self._mgr.Update()\\r\\n\\r\\n # remove the page from the source tabs\\r\\n page_info.active = False\\r\\n \\r\\n src_tabs.RemovePage(page_info.window)\\r\\n \\r\\n if src_tabs.GetPageCount() > 0:\\r\\n src_tabs.SetActivePage(0)\\r\\n src_tabs.DoShowHide()\\r\\n src_tabs.Refresh()\\r\\n \\r\\n # add the page to the destination tabs\\r\\n dest_tabs.InsertPage(page_info.window, page_info, 0)\\r\\n\\r\\n if src_tabs.GetPageCount() == 0:\\r\\n self.RemoveEmptyTabFrames()\\r\\n \\r\\n self.DoSizing()\\r\\n dest_tabs.DoShowHide()\\r\\n dest_tabs.Refresh()\\r\\n\\r\\n # force the set selection function reset the selection\\r\\n self._curpage = -1\\r\\n\\r\\n # set the active page to the one we just split off\\r\\n self.SetSelectionToPage(page_info)\\r\\n\\r\\n self.UpdateHintWindowSize()\",\n \"def __set_paddle_position(self):\\n self.__window.remove(self.__paddle)\\n self.__window.add(self.__paddle, (self.__window.width - self.__paddle.width) / 2,\\n self.__window.height - self.__paddle_offset)\",\n \"def __init__(self, cut_coords, axes=None, black_bg=False):\\n self._cut_coords = cut_coords\\n if axes is None:\\n axes = pl.axes((0., 0., 1., 1.))\\n axes.axis('off')\\n self.frame_axes = axes\\n axes.set_zorder(1)\\n bb = axes.get_position()\\n self.rect = (bb.x0, bb.y0, bb.x1, bb.y1)\\n self._black_bg = black_bg\\n self._init_axes()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5654674","0.55271375","0.5385923","0.5355535","0.53435576","0.53429335","0.5328772","0.52715266","0.5230099","0.52209806","0.5134633","0.50963074","0.50835866","0.506619","0.5044313","0.50324744","0.5028184","0.5028184","0.5023393","0.500031","0.49887872","0.49873328","0.49822322","0.49173924","0.4913711","0.48933786","0.488753","0.4887184","0.4881149","0.48570073","0.48338634","0.4822037","0.48023692","0.47821242","0.47789675","0.47775435","0.47765705","0.47749507","0.47719976","0.4769925","0.4766182","0.47657603","0.47543934","0.47375682","0.4729341","0.47239038","0.4717038","0.47073567","0.47056112","0.4705003","0.46988904","0.4698875","0.4690105","0.4685524","0.4673839","0.4669671","0.46657154","0.46609","0.46577373","0.46532086","0.46489382","0.4648324","0.4644323","0.4638698","0.46384865","0.46243614","0.46127635","0.46113053","0.4610001","0.4606511","0.46056432","0.4590305","0.45876566","0.45837167","0.45770973","0.45664272","0.4560571","0.4554073","0.45483047","0.45414665","0.45382765","0.45321375","0.45294374","0.45222515","0.4521247","0.45202938","0.45168114","0.45167473","0.45147562","0.45101193","0.45042872","0.4503241","0.45000237","0.4498698","0.44936833","0.4489867","0.4487382","0.44865382","0.4484087","0.44839272"],"string":"[\n \"0.5654674\",\n \"0.55271375\",\n \"0.5385923\",\n \"0.5355535\",\n \"0.53435576\",\n \"0.53429335\",\n \"0.5328772\",\n \"0.52715266\",\n \"0.5230099\",\n \"0.52209806\",\n \"0.5134633\",\n \"0.50963074\",\n \"0.50835866\",\n \"0.506619\",\n \"0.5044313\",\n \"0.50324744\",\n \"0.5028184\",\n \"0.5028184\",\n \"0.5023393\",\n \"0.500031\",\n \"0.49887872\",\n \"0.49873328\",\n \"0.49822322\",\n \"0.49173924\",\n \"0.4913711\",\n \"0.48933786\",\n \"0.488753\",\n \"0.4887184\",\n \"0.4881149\",\n \"0.48570073\",\n \"0.48338634\",\n \"0.4822037\",\n \"0.48023692\",\n \"0.47821242\",\n \"0.47789675\",\n \"0.47775435\",\n \"0.47765705\",\n \"0.47749507\",\n \"0.47719976\",\n \"0.4769925\",\n \"0.4766182\",\n \"0.47657603\",\n \"0.47543934\",\n \"0.47375682\",\n \"0.4729341\",\n \"0.47239038\",\n \"0.4717038\",\n \"0.47073567\",\n \"0.47056112\",\n \"0.4705003\",\n \"0.46988904\",\n \"0.4698875\",\n \"0.4690105\",\n \"0.4685524\",\n \"0.4673839\",\n \"0.4669671\",\n \"0.46657154\",\n \"0.46609\",\n \"0.46577373\",\n \"0.46532086\",\n \"0.46489382\",\n \"0.4648324\",\n \"0.4644323\",\n \"0.4638698\",\n \"0.46384865\",\n \"0.46243614\",\n \"0.46127635\",\n \"0.46113053\",\n \"0.4610001\",\n \"0.4606511\",\n \"0.46056432\",\n \"0.4590305\",\n \"0.45876566\",\n \"0.45837167\",\n \"0.45770973\",\n \"0.45664272\",\n \"0.4560571\",\n \"0.4554073\",\n \"0.45483047\",\n \"0.45414665\",\n \"0.45382765\",\n \"0.45321375\",\n \"0.45294374\",\n \"0.45222515\",\n \"0.4521247\",\n \"0.45202938\",\n \"0.45168114\",\n \"0.45167473\",\n \"0.45147562\",\n \"0.45101193\",\n \"0.45042872\",\n \"0.4503241\",\n \"0.45000237\",\n \"0.4498698\",\n \"0.44936833\",\n \"0.4489867\",\n \"0.4487382\",\n \"0.44865382\",\n \"0.4484087\",\n \"0.44839272\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.605634"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88563,"cells":{"query":{"kind":"string","value":"Convert a package (as found by setuptools.find_packages) e.g. \"foo.bar\" to usable path e.g. \"foo/bar\" No idea if this works on windows"},"document":{"kind":"string","value":"def package_to_path(package):\n return package.replace('.','/')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_package_path():\n package_name = get_package_name()\n return package_name.replace('.', '/')","def get_packages_path_from_package(package):\n root = finder.get_package_root(package)\n\n if is_built_package(package):\n package_name_folder = os.path.dirname(root)\n\n return os.path.dirname(package_name_folder)\n\n return os.path.dirname(root)","def package_path(pkg):\n fname = pkgutil.get_loader(pkg).get_filename()\n dirname = op.dirname(fname)\n dirname = op.abspath(op.join(dirname, '..'))\n return dirname","def _package_name(root_path, path):\n if not _under(path, root_path):\n raise ValueError('\"%s\" is not a subpath of \"%s\"' % (path, root_path))\n return path[len(root_path) + 1:].replace(os.sep, '.')","def get_package_path(ontology, parent, package):\n result = get_ontology_name(ontology)\n result += '.v'\n result += get_ontology_version(ontology)\n result += '.'\n result += get_package_name(parent)\n result += '.'\n result += get_package_name(package)\n return result","def get_pack_path():\r\n return get_package_path().replace(\"\\\\\", \"/\").replace(\"src\", \"\")","def get_package_root(package):\n path_to_package = package.resource.location\n\n if not os.path.isdir(path_to_package) and hasattr(package, \"filepath\"):\n return os.path.dirname(package.filepath)\n\n path = os.path.join(path_to_package, package.name, str(package.version))\n\n if not os.path.isdir(path):\n raise EnvironmentError(\n 'Package \"{package}\" has an invalid path \"{path}\".'\n \"\".format(package=package, path=path)\n )\n\n return path","def _package_root(name):\n return name.split('.', 1)[0]","def get_package_dir():\n return Path(__file__).parent","def get_path_from_package(package):\n if isinstance(package, str):\n pkg = package\n elif isinstance(package, _ModuleType):\n pkg = package.__package__\n else:\n raise ValueError('Invalid package type, must be str or module')\n dist = _pkg_resources.get_distribution(pkg)\n return dist.location, dist.version","def _resolve_name(path, package, start):\n\n if not hasattr(package, 'rindex'):\n raise ValueError(\"'package' not set to a string\")\n dot = len(package)\n for _ in range(start, 1, -1):\n try:\n dot = package.rindex('.', 0, dot)\n except ValueError:\n raise ValueError(\"attempted relative import beyond top-level \"\n \"package\")\n return \"{}.{}\".format(package[:dot], path)","def _get_package_directory(self, package_name: str) -> str:\n return os.path.abspath(\n os.path.join(\n os.path.dirname(__file__),\n '..', '..', 'assets', package_name, package_name,\n )\n )","def _pkg_path(self, pkg):\n r = rospkg.RosPack()\n pkg_path = r.get_path(pkg) \n return pkg_path","def _pkg_path(self, pkg):\n r = rospkg.RosPack()\n pkg_path = r.get_path(pkg) \n return pkg_path","def GetPackageDirectory():\n return os.path.dirname(__file__)","def get_package_directory(package, root_dir=None, sub_dir=None, suffix_root_dir=False):\n dir = get_ontology_directory(package.ontology, root_dir, sub_dir, suffix_root_dir)\n dir += '/'\n dir += get_package_name(package)\n return dir","def _namespace_package_path(fqname, pathnames, path=None):\n working_set = pkg_resources.WorkingSet(path)\n\n path = list(pathnames)\n\n for dist in working_set:\n if dist.has_metadata('namespace_packages.txt'):\n namespaces = dist.get_metadata(\n 'namespace_packages.txt').splitlines()\n if fqname in namespaces:\n nspath = os.path.join(dist.location, *fqname.split('.'))\n if nspath not in path:\n path.append(nspath)\n\n return path","def package_dir(self):\r\n return \".\"","def package_dest_path(self, package):\n\n if self.destdir is None:\n return self.package_final_path(package)\n else:\n return os.path.join(\n self.destdir,\n self.package_install_space(package).lstrip(os.sep))","def get_target_providers_package_folder(provider_package_id: str) -> str:\n return os.path.join(get_target_providers_folder(), *provider_package_id.split(\".\"))","def get_target_folder() -> str:\n return os.path.abspath(os.path.join(dirname(__file__), os.pardir, os.pardir, \"provider_packages\"))","def pypkgpath(self):\n pkgpath = None\n for parent in self.parts(reverse=True):\n if parent.isdir():\n if not parent.join(\"__init__.py\").exists():\n break\n if not isimportable(parent.basename):\n break\n pkgpath = parent\n return pkgpath","def _get_package_path(name): # 获取 模块包 路径, Flask() 中 引用\n try:\n return os.path.abspath(os.path.dirname(sys.modules[name].__file__))\n except (KeyError, AttributeError):\n return os.getcwd()","def name(self):\n\n if self.package:\n directory = self.package.directory\n if self.package.resolve_root:\n directory = directory.joinpath(self.package.resolve_root)\n rel = None\n try:\n rel = self.filename.with_suffix('').relative_to(directory)\n except ValueError as e:\n if self.package.resolve_root:\n # Possibly this module is required from a directory outside of\n # the package's resolve_root, and Path.relative_to() will raise a\n # ValueError if the file is not inside the specified directory.\n try:\n rel = type(self.filename)(os.path.relpath(str(self.filename.with_suffix('')), str(directory)))\n except ValueError as e:\n pass # On a different drive\n pass\n if rel:\n parts = filter(bool, utils.path.lparts(rel))\n return self.package.name + '/' + '/'.join(parts)\n\n return self.filename.stem","def find_package_path(path: Path) -> Optional[Path]:\n for package_path in path.iterdir():\n if is_package_dir(package_path):\n return package_path","def _replaceFind(self, match):\r\n path = self._loader.findPkgPath(match.group('pkg'))\r\n return '\"{0}\"'.format(path) if ' ' in path else path","def _get_package_dir(self, package, component):\n return join('pool', component, Repository.get_pool(package), package)","def _resolve_name(name, package, level):\n if not hasattr(package, 'rindex'):\n raise ValueError(\"'package' not set to a string\")\n dot = len(package)\n for x in xrange(level, 1, -1):\n try:\n dot = package.rindex('.', 0, dot)\n except ValueError:\n raise ValueError(\"attempted relative import beyond top-level package\")\n return \"%s.%s\" % (package[:dot], name)","def get_package_name(name):\n name = _strip_package_name(name)\n return name","def package_path(self, package_name):\n if not self.is_adb_available():\n return None\n\n _path = self._do_adb_command('shell pm path ' + package_name)\n if _path:\n try:\n _path = _path.join(_path.split()) # remove \\r\\n\n _path = _path.split(':')\n if len(_path) > 1 and _path[0] == 'package':\n ret = _path[1]\n if ret.endswith('apkpackage'):\n # handle new android packages\n ret = '/'.join(ret.split('/')[:-1])\n return ret\n except ValueError:\n pass\n\n return None","def linkpath(srcdir, pkg):\n home = os.getenv('HOME')\n if srcdir:\n rval = '{}/{}'.format(srcdir, pkg)\n else:\n rval = '{}/bin/{}'.format(home, pkg)\n return rval","def _package(module):\n return (\n module.__name__ if module.__package__ is None else module.__package__\n )","def _resolve_name(name, package, level):\r\n if not hasattr(package, 'rindex'):\r\n raise ValueError(\"'package' not set to a string\")\r\n dot = len(package)\r\n for x in xrange(level, 1, -1):\r\n try:\r\n dot = package.rindex('.', 0, dot)\r\n except ValueError:\r\n raise ValueError(\"attempted relative import beyond top-level \"\r\n \"package\")\r\n return \"%s.%s\" % (package[:dot], name)","def _replaceFind(self, match):\n path = self._loader.findPkgPath(match.group('pkg'))\n return '\"{0}\"'.format(path) if ' ' in path else path","def p(path):\n import os\n from os.path import abspath, dirname\n return dirname(abspath(sys.argv[0])).replace('library.zip', '') + os.sep \\\n + path","def package_space(self, package):\n space_abs = getattr(self, '__%s_space_abs' % space)\n return os.path.join(space_abs, package.name)","def get_source_package_path(provider_package_id: str) -> str:\n return os.path.join(PROVIDERS_PATH, *provider_package_id.split(\".\"))","def acquire_package_directory():\n top_plugin_dir = os.path.realpath(os.path.join(os.getcwd(),\n os.path.dirname(__file__)))\n expected_package_dir = '/extras/MockApp'\n app_dir = top_plugin_dir + expected_package_dir\n return app_dir","def get_build_dir(package_dir):\n return os.path.split(makepkg([\"--packagelist\"], True, package_dir)[0])[0]","def parse_package(package_path):\n\n if DEBUG: print \"Parsing package\",package_path\n\n package_path = os.path.normpath(package_path)\n dir,file = os.path.split(package_path)\n if dir == \"\":\n dir = \".\"\n return parse_subpackage(dir,file)","def get_package_share_path(package_name, print_warning=True):\n path = pathlib.Path(get_package_share_directory(package_name, print_warning=False))\n if print_warning and not path.exists():\n warnings.warn(f'Share path for {package_name} ({path}) does not exist.', stacklevel=2)\n return path","def check_package_path(pkg):\n src_dir_root = ''\n print(\"[root-get] DEBUG: Checking package path\")\n check_package_name = os.system('find %s -maxdepth 1 -type d -name \"%s\" ! -path \"*tutorials*\" ! -path \"*dictpch*\"' % (ROOT_SOURCES, pkg))\n if check_package_name != 0:\n print(\"Not a ROOT package (we are working only with ROOT packages for now.)\")\n return False\n else:\n # if have such directory in root then we can try to get it's real path\n path = PathChecker()\n src_dir_root = path.path4pkg(pkg, ROOT_SOURCES)\n print(\"[root-get] We would use a package from {0:s}\".format(src_dir_root))\n return src_dir_root","def convertString(path):\n if (\"win\" in sys.platform):\n return path.replace(\"/\",\"\\\\\")\n elif (\"linux\" in sys.platform):\n return path.replace(\"\\\\\",\"/\")","def package_metadata_path(self, package=None):\n profile_path, _ = metadata.get_paths(self.workspace, self.profile)\n if package is None:\n return os.path.join(profile_path, 'packages')\n return os.path.join(profile_path, 'packages', package.name)","def get_generated_package_path(provider_package_id: str) -> str:\n provider_package_path = os.path.join(GENERATED_PROVIDERS_PATH, *provider_package_id.split(\".\"))\n return provider_package_path","def _project_name_to_package_name(project_name):\n return project_name.lower().replace('-', '')","def package_final_path(self, package):\n\n if self.install:\n return self.package_install_space(package)\n else:\n if self.link_devel:\n return self.devel_space_abs\n else:\n return self.package_devel_space(package)","def app_package_path(self) -> str:\n return self._app_package_path","def insert_package_path():\n sys.path.insert(0, ospdn(ospdn(ospdn(ospap(__file__)))))","def package_from_path(path):\n\n partial_path, version = os.path.split(path)\n base_path, name = os.path.split(partial_path)\n\n p = Package(name, version, path)\n\n return p","def get_package_init_path(self, pkgname, pkgdir):\n\n pkgdir = os.path.abspath(pkgdir)\n\n # Try __init__.py\n pkginitfile = os.path.join(pkgdir, '__init__.py')\n # If it does not exist, try <pkgname>.py\n if not os.path.isfile(pkginitfile):\n pkginitfile = os.path.join(pkgdir,pkgname + '.py')\n\n if os.path.isfile(pkginitfile):\n return pkginitfile\n else:\n # Everything failed, return pkgdir itself!\n return pkgdir","def get_package_name(cls) -> str:\n return '.'.join(cls.__module__.split('.')[:-1])","def dir2ns(fname,checkfs=True):\n\tif checkfs: assert os.path.isdir(fname)\n\tif checkfs: fname = os.path.abspath(fname)\n\tfname = fname.rstrip(\"/\")\n\tmark = \"rosetta_source/src\"\n\tassert fname.find(mark) > 0\n\tfname = fname[fname.find(mark)+len(mark)+1:]\n\treturn fname.replace(\"/\",\"::\")","def getPackageName(rootDir=\"python\"):\n dirIter = os.walk(rootDir)\n (dirPath, dirList, fileList) = next(dirIter)\n dirList = [dirName for dirName in dirList if not dirName.startswith(\".\")]\n if len(dirList) != 1:\n raise RuntimeError(\"Found %s instead of 1 directory\" % (dirList,))\n return dirList[0]","def path(self):\n installed_packages_folder_path = site.getsitepackages()[0]\n return f'{installed_packages_folder_path}/{SITE_PACKAGES_FOLDER_NAME}'","def module_path():\n return os.path.dirname(unicode(__file__, sys.getfilesystemencoding( )))","def get_package_name():\n\tpackage = None\n\ttry:\n\t\tpackage = os.environ.get('LOCAL_PART', '') + os.environ.get('LOCAL_PART_SUFFIX', '') \n\t\tif not package and len(sys.argv) > 1:\n\t\t\tpackage = sys.argv[-1].lower()\n\texcept Exception,e:\n\t\tlog.error(str(e))\n\tfinally:\n\t\treturn package","def get_packages(package):\n return [str(path.parent) for path in Path(package).glob(\"**/__init__.py\")]","def get_absolute_name(package, relative_name):\n path = package.split('.') if package else []\n name = relative_name.lstrip('.')\n ndots = len(relative_name) - len(name)\n if ndots > len(path):\n return relative_name\n absolute_path = path[:len(path) + 1 - ndots]\n if name:\n absolute_path.append(name)\n return '.'.join(absolute_path)","def find_package(import_name):\n root_mod_name = import_name.split('.')[0]\n loader = pkgutil.get_loader(root_mod_name)\n if loader is None or import_name == '__main__':\n # import name is not found, or interactive/main module\n package_path = os.getcwd()\n else:\n # For .egg, zipimporter does not have get_filename until Python 2.7.\n if hasattr(loader, 'get_filename'):\n filename = loader.get_filename(root_mod_name)\n elif hasattr(loader, 'archive'):\n # zipimporter's loader.archive points to the .egg or .zip\n # archive filename is dropped in call to dirname below.\n filename = loader.archive\n else:\n # At least one loader is missing both get_filename and archive:\n # Google App Engine's HardenedModulesHook\n #\n # Fall back to imports.\n __import__(import_name)\n filename = sys.modules[import_name].__file__\n package_path = os.path.abspath(os.path.dirname(filename))\n\n # In case the root module is a package we need to chop of the\n # rightmost part. This needs to go through a helper function\n # because of python 3.3 namespace packages.\n if _is_package(loader, root_mod_name):\n package_path = os.path.dirname(package_path)\n\n site_parent, site_folder = os.path.split(package_path)\n py_prefix = os.path.abspath(sys.prefix)\n if package_path.startswith(py_prefix):\n return py_prefix, package_path\n elif site_folder.lower() == 'site-packages':\n parent, folder = os.path.split(site_parent)\n # Windows like installations\n if folder.lower() == 'lib':\n base_dir = parent\n # UNIX like installations\n elif os.path.basename(parent).lower() == 'lib':\n base_dir = os.path.dirname(parent)\n else:\n base_dir = site_parent\n return base_dir, package_path\n return None, package_path","def package_repo_resource(self, *path):\n return self._module.PACKAGE_REPO_ROOT.join(*path)","def str_to_path(name):\n import os;\n return(os.path.abspath(name));","def as_package(names: List[str]) -> str:\n return '.'.join(names)","def getPackagePath(self):\n return self._packagePath","def get_package_share_directory(package_name, print_warning=True):\n path = os.path.join(get_package_prefix(package_name), 'share', package_name)\n if print_warning and not os.path.exists(path):\n warnings.warn(f'Share directory for {package_name} ({path}) does not exist.', stacklevel=2)\n return path","def translate(self, package):\r\n if not isinstance(package, self._package_type):\r\n return None\r\n if not package.compatible(identity=self._identity, platform=self._platform):\r\n return None\r\n try:\r\n bdist = package.fetch(location=self._install_cache, conn_timeout=self._conn_timeout)\r\n except package.UnreadableLink as e:\r\n TRACER.log('Failed to fetch %s: %s' % (package, e))\r\n return None\r\n return DistributionHelper.distribution_from_path(bdist)","def infer_module_name(filename, fspath):\n filename, _ = os.path.splitext(filename)\n for f in fspath:\n short_name = f.relative_path(filename)\n if short_name:\n # The module name for __init__.py files is the directory.\n if short_name.endswith(os.path.sep + \"__init__\"):\n short_name = short_name[:short_name.rfind(os.path.sep)]\n return short_name.replace(os.path.sep, '.')\n # We have not found filename relative to anywhere in pythonpath.\n return ''","def sublime_haskell_package_path():\n return os.path.dirname(os.path.realpath(__file__))","def convert_packname_for_depsolver(packname):\n return packname.replace('-', '_')","def resolve_relative_name(package, module, relative):\n\n if relative.startswith('.'):\n \n # Add a dummy module onto the end if this is a package. It will be\n # pulled off in the loop below.\n if package == module:\n module += '.dummy'\n \n parts = module.split('.')\n while relative.startswith('.'):\n relative = relative[1:]\n parts.pop(-1)\n relative = '.'.join(parts) + ('.' if relative else '') + relative\n\n return relative","def _strip_package_name(name):\n name = _strip(name)\n if name.find('.') != -1:\n name = name.split('.')[0]\n return name","def package_folder(self):\n return self._base_package","def get_package_name():\n return try_get_project_property('packageName')","def findPkgPath(self, pkg):\r\n try:\r\n return self._rp.get_path(pkg)\r\n except rospkg.ResourceNotFound:\r\n raise ResourceNotFound('Can not find ROS package '\r\n '\"{0}\".'.format(pkg))","def get_module_path(module):\n return pathlib.Path(os.path.dirname(os.path.abspath(inspect.getfile(module))))","def get_module_release_path(module, src_pkg_file, prefer_maven_coords=False):\n\n group_id, artifact_id, version = extract_coordinates_from_pom(module)\n \n d = \"\"\n sd = module.subsystem\n if prefer_maven_coords and group_id is not None:\n sd = group_id\n if sd:\n if sd.startswith('org.gcube.'):\n sd = sd[10:]\n d += os.sep + sd.replace('.', os.sep)\n\n cd = module.name\n if prefer_maven_coords and artifact_id is not None:\n cd = artifact_id\n if cd.startswith('org.gcube.'):\n cd = cd[10:]\n if cd.startswith(sd):\n cd = cd[len(sd) + 1:]\n d += os.sep + cd\n\n v = extract_version_from_src_pkg(src_pkg_file)\n if v is None or prefer_maven_coords:\n v = version\n\n d += os.sep + v\n\n return d","def convert_packname_from_depsolver(depsolver_packname):\n return depsolver_packname.replace('_', '-')","def format_path (in_path):\n return os.path.realpath(os.path.expanduser(in_path))","def _path_to_string(path):\n return '.'.join(path)","def getmodulepath(modulename):\n return USERLIBDIR + '\\\\' + modulename + '.sikuli\\\\' + modulename + '.py'","def makePath(path):\n\n compatPath = os.path.abspath(os.path.expanduser(path))\n\n return compatPath","def _get_module(dotted_path):\n package, module = dotted_path.rsplit('.', 1)\n return getattr(import_module(package), module)","def tmpDir(package):\n\treturn 'debian/'+package","def find_packages( root ):\n for path, directories, files in os.walk( root ):\n if is_package( path ):\n yield path.replace( '/','.' )","def parse_package_or_module(path):\n path = os.path.normpath(path)\n if os.path.isdir(path):\n return parse_package(path)\n else:\n return parse_file(path,path)","def _get_koji_task_result_package_name(path):\n filename = path.split('/')[-1]\n trimmed = []\n for part in filename.split('-'):\n # assumes that when the next part is not a digit\n # we're past the name and at the version\n if part[0].isdigit():\n return '-'.join(trimmed)\n trimmed.append(part)\n\n return '-'.join(trimmed)","def import_package(name):\r\n mod = __import__(name)\r\n components = name.split('.')\r\n for comp in components[1:]:\r\n mod = getattr(mod, comp)\r\n return mod","def datapackage_path():\n return 'datapackage.json'","def _parent_path(pkg, pkg_path):\n parent = pkg_path[: -len(pkg)] if pkg_path.endswith(pkg) else pkg_path\n return parent.rstrip(\"/\" + os.sep)","def normalize_package_name(_s: str) -> str:\n return _s.replace('_', '-').lower()","def native(path):\n path = _os.path.sep.join(path.split('/'))\n return _os.path.normpath(_os.path.join(root, path))","def _get_package_dir ( self, pkg_name ):\n if not pkg_name in self._subdirs:\n self._lock.acquire()\n try:\n if not pkg_name in self._subdirs:\n newpkg = self.packagedir_cls (\n name = pkg_name,\n logger = self.logger,\n directory = self.physical_location + os.sep + pkg_name,\n get_header = self.get_header,\n runtime_incremental = self.runtime_incremental,\n parent = self\n )\n self._subdirs [pkg_name] = newpkg\n finally:\n self._lock.release()\n\n return self._subdirs [pkg_name]","def relativize(path: str):\n return join('.', path)","def path_to_module(path: str):\n if path[-3:] != '.py':\n raise ValueError(\"Not a python module path \", path)\n path_minus_py = path[:-3]\n path_w_dots = path_minus_py.replace(\"/\", \".\")\n # strip leading docs\n if path_w_dots[0] == '.':\n path_w_dots = path_w_dots[1:]\n # if there was an __init__ then strip that\n if path_w_dots[-9:] == \".__init__\":\n path_w_dots = path_w_dots[:-9]\n return path_w_dots","def module_path(module: 'ModuleType | str', subpath: str) -> str:\n\n parent = module_path_root(module)\n path = os.path.join(parent, subpath.strip('/'))\n\n # always be paranoid with path manipulation\n assert is_subpath(parent, path)\n\n return path","def get_packages(package):\n return [dirpath\n for dirpath, dirnames, filenames in os.walk(package)\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]","def get_packages(package):\n return [dirpath\n for dirpath, dirnames, filenames in os.walk(package)\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]","def get_packages(package):\n return [dirpath\n for dirpath, dirnames, filenames in os.walk(package)\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]","def shortpath(path):\r\n import os\r\n if path.startswith(base_dir):\r\n return path[len(base_dir) + len(os.path.sep) : ]\r\n return path","def resolved_path(path):\n path = os.path.abspath(path)\n elements = path_elements(path)\n result = \"\"\n for element in elements:\n segment = element\n segment_path = os.path.join(result, segment)\n if os.path.islink(segment_path):\n segment = os.readlink(segment_path)\n result = os.path.join(result, segment)\n result = os.path.normpath(result)\n return result"],"string":"[\n \"def get_package_path():\\n package_name = get_package_name()\\n return package_name.replace('.', '/')\",\n \"def get_packages_path_from_package(package):\\n root = finder.get_package_root(package)\\n\\n if is_built_package(package):\\n package_name_folder = os.path.dirname(root)\\n\\n return os.path.dirname(package_name_folder)\\n\\n return os.path.dirname(root)\",\n \"def package_path(pkg):\\n fname = pkgutil.get_loader(pkg).get_filename()\\n dirname = op.dirname(fname)\\n dirname = op.abspath(op.join(dirname, '..'))\\n return dirname\",\n \"def _package_name(root_path, path):\\n if not _under(path, root_path):\\n raise ValueError('\\\"%s\\\" is not a subpath of \\\"%s\\\"' % (path, root_path))\\n return path[len(root_path) + 1:].replace(os.sep, '.')\",\n \"def get_package_path(ontology, parent, package):\\n result = get_ontology_name(ontology)\\n result += '.v'\\n result += get_ontology_version(ontology)\\n result += '.'\\n result += get_package_name(parent)\\n result += '.'\\n result += get_package_name(package)\\n return result\",\n \"def get_pack_path():\\r\\n return get_package_path().replace(\\\"\\\\\\\\\\\", \\\"/\\\").replace(\\\"src\\\", \\\"\\\")\",\n \"def get_package_root(package):\\n path_to_package = package.resource.location\\n\\n if not os.path.isdir(path_to_package) and hasattr(package, \\\"filepath\\\"):\\n return os.path.dirname(package.filepath)\\n\\n path = os.path.join(path_to_package, package.name, str(package.version))\\n\\n if not os.path.isdir(path):\\n raise EnvironmentError(\\n 'Package \\\"{package}\\\" has an invalid path \\\"{path}\\\".'\\n \\\"\\\".format(package=package, path=path)\\n )\\n\\n return path\",\n \"def _package_root(name):\\n return name.split('.', 1)[0]\",\n \"def get_package_dir():\\n return Path(__file__).parent\",\n \"def get_path_from_package(package):\\n if isinstance(package, str):\\n pkg = package\\n elif isinstance(package, _ModuleType):\\n pkg = package.__package__\\n else:\\n raise ValueError('Invalid package type, must be str or module')\\n dist = _pkg_resources.get_distribution(pkg)\\n return dist.location, dist.version\",\n \"def _resolve_name(path, package, start):\\n\\n if not hasattr(package, 'rindex'):\\n raise ValueError(\\\"'package' not set to a string\\\")\\n dot = len(package)\\n for _ in range(start, 1, -1):\\n try:\\n dot = package.rindex('.', 0, dot)\\n except ValueError:\\n raise ValueError(\\\"attempted relative import beyond top-level \\\"\\n \\\"package\\\")\\n return \\\"{}.{}\\\".format(package[:dot], path)\",\n \"def _get_package_directory(self, package_name: str) -> str:\\n return os.path.abspath(\\n os.path.join(\\n os.path.dirname(__file__),\\n '..', '..', 'assets', package_name, package_name,\\n )\\n )\",\n \"def _pkg_path(self, pkg):\\n r = rospkg.RosPack()\\n pkg_path = r.get_path(pkg) \\n return pkg_path\",\n \"def _pkg_path(self, pkg):\\n r = rospkg.RosPack()\\n pkg_path = r.get_path(pkg) \\n return pkg_path\",\n \"def GetPackageDirectory():\\n return os.path.dirname(__file__)\",\n \"def get_package_directory(package, root_dir=None, sub_dir=None, suffix_root_dir=False):\\n dir = get_ontology_directory(package.ontology, root_dir, sub_dir, suffix_root_dir)\\n dir += '/'\\n dir += get_package_name(package)\\n return dir\",\n \"def _namespace_package_path(fqname, pathnames, path=None):\\n working_set = pkg_resources.WorkingSet(path)\\n\\n path = list(pathnames)\\n\\n for dist in working_set:\\n if dist.has_metadata('namespace_packages.txt'):\\n namespaces = dist.get_metadata(\\n 'namespace_packages.txt').splitlines()\\n if fqname in namespaces:\\n nspath = os.path.join(dist.location, *fqname.split('.'))\\n if nspath not in path:\\n path.append(nspath)\\n\\n return path\",\n \"def package_dir(self):\\r\\n return \\\".\\\"\",\n \"def package_dest_path(self, package):\\n\\n if self.destdir is None:\\n return self.package_final_path(package)\\n else:\\n return os.path.join(\\n self.destdir,\\n self.package_install_space(package).lstrip(os.sep))\",\n \"def get_target_providers_package_folder(provider_package_id: str) -> str:\\n return os.path.join(get_target_providers_folder(), *provider_package_id.split(\\\".\\\"))\",\n \"def get_target_folder() -> str:\\n return os.path.abspath(os.path.join(dirname(__file__), os.pardir, os.pardir, \\\"provider_packages\\\"))\",\n \"def pypkgpath(self):\\n pkgpath = None\\n for parent in self.parts(reverse=True):\\n if parent.isdir():\\n if not parent.join(\\\"__init__.py\\\").exists():\\n break\\n if not isimportable(parent.basename):\\n break\\n pkgpath = parent\\n return pkgpath\",\n \"def _get_package_path(name): # 获取 模块包 路径, Flask() 中 引用\\n try:\\n return os.path.abspath(os.path.dirname(sys.modules[name].__file__))\\n except (KeyError, AttributeError):\\n return os.getcwd()\",\n \"def name(self):\\n\\n if self.package:\\n directory = self.package.directory\\n if self.package.resolve_root:\\n directory = directory.joinpath(self.package.resolve_root)\\n rel = None\\n try:\\n rel = self.filename.with_suffix('').relative_to(directory)\\n except ValueError as e:\\n if self.package.resolve_root:\\n # Possibly this module is required from a directory outside of\\n # the package's resolve_root, and Path.relative_to() will raise a\\n # ValueError if the file is not inside the specified directory.\\n try:\\n rel = type(self.filename)(os.path.relpath(str(self.filename.with_suffix('')), str(directory)))\\n except ValueError as e:\\n pass # On a different drive\\n pass\\n if rel:\\n parts = filter(bool, utils.path.lparts(rel))\\n return self.package.name + '/' + '/'.join(parts)\\n\\n return self.filename.stem\",\n \"def find_package_path(path: Path) -> Optional[Path]:\\n for package_path in path.iterdir():\\n if is_package_dir(package_path):\\n return package_path\",\n \"def _replaceFind(self, match):\\r\\n path = self._loader.findPkgPath(match.group('pkg'))\\r\\n return '\\\"{0}\\\"'.format(path) if ' ' in path else path\",\n \"def _get_package_dir(self, package, component):\\n return join('pool', component, Repository.get_pool(package), package)\",\n \"def _resolve_name(name, package, level):\\n if not hasattr(package, 'rindex'):\\n raise ValueError(\\\"'package' not set to a string\\\")\\n dot = len(package)\\n for x in xrange(level, 1, -1):\\n try:\\n dot = package.rindex('.', 0, dot)\\n except ValueError:\\n raise ValueError(\\\"attempted relative import beyond top-level package\\\")\\n return \\\"%s.%s\\\" % (package[:dot], name)\",\n \"def get_package_name(name):\\n name = _strip_package_name(name)\\n return name\",\n \"def package_path(self, package_name):\\n if not self.is_adb_available():\\n return None\\n\\n _path = self._do_adb_command('shell pm path ' + package_name)\\n if _path:\\n try:\\n _path = _path.join(_path.split()) # remove \\\\r\\\\n\\n _path = _path.split(':')\\n if len(_path) > 1 and _path[0] == 'package':\\n ret = _path[1]\\n if ret.endswith('apkpackage'):\\n # handle new android packages\\n ret = '/'.join(ret.split('/')[:-1])\\n return ret\\n except ValueError:\\n pass\\n\\n return None\",\n \"def linkpath(srcdir, pkg):\\n home = os.getenv('HOME')\\n if srcdir:\\n rval = '{}/{}'.format(srcdir, pkg)\\n else:\\n rval = '{}/bin/{}'.format(home, pkg)\\n return rval\",\n \"def _package(module):\\n return (\\n module.__name__ if module.__package__ is None else module.__package__\\n )\",\n \"def _resolve_name(name, package, level):\\r\\n if not hasattr(package, 'rindex'):\\r\\n raise ValueError(\\\"'package' not set to a string\\\")\\r\\n dot = len(package)\\r\\n for x in xrange(level, 1, -1):\\r\\n try:\\r\\n dot = package.rindex('.', 0, dot)\\r\\n except ValueError:\\r\\n raise ValueError(\\\"attempted relative import beyond top-level \\\"\\r\\n \\\"package\\\")\\r\\n return \\\"%s.%s\\\" % (package[:dot], name)\",\n \"def _replaceFind(self, match):\\n path = self._loader.findPkgPath(match.group('pkg'))\\n return '\\\"{0}\\\"'.format(path) if ' ' in path else path\",\n \"def p(path):\\n import os\\n from os.path import abspath, dirname\\n return dirname(abspath(sys.argv[0])).replace('library.zip', '') + os.sep \\\\\\n + path\",\n \"def package_space(self, package):\\n space_abs = getattr(self, '__%s_space_abs' % space)\\n return os.path.join(space_abs, package.name)\",\n \"def get_source_package_path(provider_package_id: str) -> str:\\n return os.path.join(PROVIDERS_PATH, *provider_package_id.split(\\\".\\\"))\",\n \"def acquire_package_directory():\\n top_plugin_dir = os.path.realpath(os.path.join(os.getcwd(),\\n os.path.dirname(__file__)))\\n expected_package_dir = '/extras/MockApp'\\n app_dir = top_plugin_dir + expected_package_dir\\n return app_dir\",\n \"def get_build_dir(package_dir):\\n return os.path.split(makepkg([\\\"--packagelist\\\"], True, package_dir)[0])[0]\",\n \"def parse_package(package_path):\\n\\n if DEBUG: print \\\"Parsing package\\\",package_path\\n\\n package_path = os.path.normpath(package_path)\\n dir,file = os.path.split(package_path)\\n if dir == \\\"\\\":\\n dir = \\\".\\\"\\n return parse_subpackage(dir,file)\",\n \"def get_package_share_path(package_name, print_warning=True):\\n path = pathlib.Path(get_package_share_directory(package_name, print_warning=False))\\n if print_warning and not path.exists():\\n warnings.warn(f'Share path for {package_name} ({path}) does not exist.', stacklevel=2)\\n return path\",\n \"def check_package_path(pkg):\\n src_dir_root = ''\\n print(\\\"[root-get] DEBUG: Checking package path\\\")\\n check_package_name = os.system('find %s -maxdepth 1 -type d -name \\\"%s\\\" ! -path \\\"*tutorials*\\\" ! -path \\\"*dictpch*\\\"' % (ROOT_SOURCES, pkg))\\n if check_package_name != 0:\\n print(\\\"Not a ROOT package (we are working only with ROOT packages for now.)\\\")\\n return False\\n else:\\n # if have such directory in root then we can try to get it's real path\\n path = PathChecker()\\n src_dir_root = path.path4pkg(pkg, ROOT_SOURCES)\\n print(\\\"[root-get] We would use a package from {0:s}\\\".format(src_dir_root))\\n return src_dir_root\",\n \"def convertString(path):\\n if (\\\"win\\\" in sys.platform):\\n return path.replace(\\\"/\\\",\\\"\\\\\\\\\\\")\\n elif (\\\"linux\\\" in sys.platform):\\n return path.replace(\\\"\\\\\\\\\\\",\\\"/\\\")\",\n \"def package_metadata_path(self, package=None):\\n profile_path, _ = metadata.get_paths(self.workspace, self.profile)\\n if package is None:\\n return os.path.join(profile_path, 'packages')\\n return os.path.join(profile_path, 'packages', package.name)\",\n \"def get_generated_package_path(provider_package_id: str) -> str:\\n provider_package_path = os.path.join(GENERATED_PROVIDERS_PATH, *provider_package_id.split(\\\".\\\"))\\n return provider_package_path\",\n \"def _project_name_to_package_name(project_name):\\n return project_name.lower().replace('-', '')\",\n \"def package_final_path(self, package):\\n\\n if self.install:\\n return self.package_install_space(package)\\n else:\\n if self.link_devel:\\n return self.devel_space_abs\\n else:\\n return self.package_devel_space(package)\",\n \"def app_package_path(self) -> str:\\n return self._app_package_path\",\n \"def insert_package_path():\\n sys.path.insert(0, ospdn(ospdn(ospdn(ospap(__file__)))))\",\n \"def package_from_path(path):\\n\\n partial_path, version = os.path.split(path)\\n base_path, name = os.path.split(partial_path)\\n\\n p = Package(name, version, path)\\n\\n return p\",\n \"def get_package_init_path(self, pkgname, pkgdir):\\n\\n pkgdir = os.path.abspath(pkgdir)\\n\\n # Try __init__.py\\n pkginitfile = os.path.join(pkgdir, '__init__.py')\\n # If it does not exist, try <pkgname>.py\\n if not os.path.isfile(pkginitfile):\\n pkginitfile = os.path.join(pkgdir,pkgname + '.py')\\n\\n if os.path.isfile(pkginitfile):\\n return pkginitfile\\n else:\\n # Everything failed, return pkgdir itself!\\n return pkgdir\",\n \"def get_package_name(cls) -> str:\\n return '.'.join(cls.__module__.split('.')[:-1])\",\n \"def dir2ns(fname,checkfs=True):\\n\\tif checkfs: assert os.path.isdir(fname)\\n\\tif checkfs: fname = os.path.abspath(fname)\\n\\tfname = fname.rstrip(\\\"/\\\")\\n\\tmark = \\\"rosetta_source/src\\\"\\n\\tassert fname.find(mark) > 0\\n\\tfname = fname[fname.find(mark)+len(mark)+1:]\\n\\treturn fname.replace(\\\"/\\\",\\\"::\\\")\",\n \"def getPackageName(rootDir=\\\"python\\\"):\\n dirIter = os.walk(rootDir)\\n (dirPath, dirList, fileList) = next(dirIter)\\n dirList = [dirName for dirName in dirList if not dirName.startswith(\\\".\\\")]\\n if len(dirList) != 1:\\n raise RuntimeError(\\\"Found %s instead of 1 directory\\\" % (dirList,))\\n return dirList[0]\",\n \"def path(self):\\n installed_packages_folder_path = site.getsitepackages()[0]\\n return f'{installed_packages_folder_path}/{SITE_PACKAGES_FOLDER_NAME}'\",\n \"def module_path():\\n return os.path.dirname(unicode(__file__, sys.getfilesystemencoding( )))\",\n \"def get_package_name():\\n\\tpackage = None\\n\\ttry:\\n\\t\\tpackage = os.environ.get('LOCAL_PART', '') + os.environ.get('LOCAL_PART_SUFFIX', '') \\n\\t\\tif not package and len(sys.argv) > 1:\\n\\t\\t\\tpackage = sys.argv[-1].lower()\\n\\texcept Exception,e:\\n\\t\\tlog.error(str(e))\\n\\tfinally:\\n\\t\\treturn package\",\n \"def get_packages(package):\\n return [str(path.parent) for path in Path(package).glob(\\\"**/__init__.py\\\")]\",\n \"def get_absolute_name(package, relative_name):\\n path = package.split('.') if package else []\\n name = relative_name.lstrip('.')\\n ndots = len(relative_name) - len(name)\\n if ndots > len(path):\\n return relative_name\\n absolute_path = path[:len(path) + 1 - ndots]\\n if name:\\n absolute_path.append(name)\\n return '.'.join(absolute_path)\",\n \"def find_package(import_name):\\n root_mod_name = import_name.split('.')[0]\\n loader = pkgutil.get_loader(root_mod_name)\\n if loader is None or import_name == '__main__':\\n # import name is not found, or interactive/main module\\n package_path = os.getcwd()\\n else:\\n # For .egg, zipimporter does not have get_filename until Python 2.7.\\n if hasattr(loader, 'get_filename'):\\n filename = loader.get_filename(root_mod_name)\\n elif hasattr(loader, 'archive'):\\n # zipimporter's loader.archive points to the .egg or .zip\\n # archive filename is dropped in call to dirname below.\\n filename = loader.archive\\n else:\\n # At least one loader is missing both get_filename and archive:\\n # Google App Engine's HardenedModulesHook\\n #\\n # Fall back to imports.\\n __import__(import_name)\\n filename = sys.modules[import_name].__file__\\n package_path = os.path.abspath(os.path.dirname(filename))\\n\\n # In case the root module is a package we need to chop of the\\n # rightmost part. This needs to go through a helper function\\n # because of python 3.3 namespace packages.\\n if _is_package(loader, root_mod_name):\\n package_path = os.path.dirname(package_path)\\n\\n site_parent, site_folder = os.path.split(package_path)\\n py_prefix = os.path.abspath(sys.prefix)\\n if package_path.startswith(py_prefix):\\n return py_prefix, package_path\\n elif site_folder.lower() == 'site-packages':\\n parent, folder = os.path.split(site_parent)\\n # Windows like installations\\n if folder.lower() == 'lib':\\n base_dir = parent\\n # UNIX like installations\\n elif os.path.basename(parent).lower() == 'lib':\\n base_dir = os.path.dirname(parent)\\n else:\\n base_dir = site_parent\\n return base_dir, package_path\\n return None, package_path\",\n \"def package_repo_resource(self, *path):\\n return self._module.PACKAGE_REPO_ROOT.join(*path)\",\n \"def str_to_path(name):\\n import os;\\n return(os.path.abspath(name));\",\n \"def as_package(names: List[str]) -> str:\\n return '.'.join(names)\",\n \"def getPackagePath(self):\\n return self._packagePath\",\n \"def get_package_share_directory(package_name, print_warning=True):\\n path = os.path.join(get_package_prefix(package_name), 'share', package_name)\\n if print_warning and not os.path.exists(path):\\n warnings.warn(f'Share directory for {package_name} ({path}) does not exist.', stacklevel=2)\\n return path\",\n \"def translate(self, package):\\r\\n if not isinstance(package, self._package_type):\\r\\n return None\\r\\n if not package.compatible(identity=self._identity, platform=self._platform):\\r\\n return None\\r\\n try:\\r\\n bdist = package.fetch(location=self._install_cache, conn_timeout=self._conn_timeout)\\r\\n except package.UnreadableLink as e:\\r\\n TRACER.log('Failed to fetch %s: %s' % (package, e))\\r\\n return None\\r\\n return DistributionHelper.distribution_from_path(bdist)\",\n \"def infer_module_name(filename, fspath):\\n filename, _ = os.path.splitext(filename)\\n for f in fspath:\\n short_name = f.relative_path(filename)\\n if short_name:\\n # The module name for __init__.py files is the directory.\\n if short_name.endswith(os.path.sep + \\\"__init__\\\"):\\n short_name = short_name[:short_name.rfind(os.path.sep)]\\n return short_name.replace(os.path.sep, '.')\\n # We have not found filename relative to anywhere in pythonpath.\\n return ''\",\n \"def sublime_haskell_package_path():\\n return os.path.dirname(os.path.realpath(__file__))\",\n \"def convert_packname_for_depsolver(packname):\\n return packname.replace('-', '_')\",\n \"def resolve_relative_name(package, module, relative):\\n\\n if relative.startswith('.'):\\n \\n # Add a dummy module onto the end if this is a package. It will be\\n # pulled off in the loop below.\\n if package == module:\\n module += '.dummy'\\n \\n parts = module.split('.')\\n while relative.startswith('.'):\\n relative = relative[1:]\\n parts.pop(-1)\\n relative = '.'.join(parts) + ('.' if relative else '') + relative\\n\\n return relative\",\n \"def _strip_package_name(name):\\n name = _strip(name)\\n if name.find('.') != -1:\\n name = name.split('.')[0]\\n return name\",\n \"def package_folder(self):\\n return self._base_package\",\n \"def get_package_name():\\n return try_get_project_property('packageName')\",\n \"def findPkgPath(self, pkg):\\r\\n try:\\r\\n return self._rp.get_path(pkg)\\r\\n except rospkg.ResourceNotFound:\\r\\n raise ResourceNotFound('Can not find ROS package '\\r\\n '\\\"{0}\\\".'.format(pkg))\",\n \"def get_module_path(module):\\n return pathlib.Path(os.path.dirname(os.path.abspath(inspect.getfile(module))))\",\n \"def get_module_release_path(module, src_pkg_file, prefer_maven_coords=False):\\n\\n group_id, artifact_id, version = extract_coordinates_from_pom(module)\\n \\n d = \\\"\\\"\\n sd = module.subsystem\\n if prefer_maven_coords and group_id is not None:\\n sd = group_id\\n if sd:\\n if sd.startswith('org.gcube.'):\\n sd = sd[10:]\\n d += os.sep + sd.replace('.', os.sep)\\n\\n cd = module.name\\n if prefer_maven_coords and artifact_id is not None:\\n cd = artifact_id\\n if cd.startswith('org.gcube.'):\\n cd = cd[10:]\\n if cd.startswith(sd):\\n cd = cd[len(sd) + 1:]\\n d += os.sep + cd\\n\\n v = extract_version_from_src_pkg(src_pkg_file)\\n if v is None or prefer_maven_coords:\\n v = version\\n\\n d += os.sep + v\\n\\n return d\",\n \"def convert_packname_from_depsolver(depsolver_packname):\\n return depsolver_packname.replace('_', '-')\",\n \"def format_path (in_path):\\n return os.path.realpath(os.path.expanduser(in_path))\",\n \"def _path_to_string(path):\\n return '.'.join(path)\",\n \"def getmodulepath(modulename):\\n return USERLIBDIR + '\\\\\\\\' + modulename + '.sikuli\\\\\\\\' + modulename + '.py'\",\n \"def makePath(path):\\n\\n compatPath = os.path.abspath(os.path.expanduser(path))\\n\\n return compatPath\",\n \"def _get_module(dotted_path):\\n package, module = dotted_path.rsplit('.', 1)\\n return getattr(import_module(package), module)\",\n \"def tmpDir(package):\\n\\treturn 'debian/'+package\",\n \"def find_packages( root ):\\n for path, directories, files in os.walk( root ):\\n if is_package( path ):\\n yield path.replace( '/','.' )\",\n \"def parse_package_or_module(path):\\n path = os.path.normpath(path)\\n if os.path.isdir(path):\\n return parse_package(path)\\n else:\\n return parse_file(path,path)\",\n \"def _get_koji_task_result_package_name(path):\\n filename = path.split('/')[-1]\\n trimmed = []\\n for part in filename.split('-'):\\n # assumes that when the next part is not a digit\\n # we're past the name and at the version\\n if part[0].isdigit():\\n return '-'.join(trimmed)\\n trimmed.append(part)\\n\\n return '-'.join(trimmed)\",\n \"def import_package(name):\\r\\n mod = __import__(name)\\r\\n components = name.split('.')\\r\\n for comp in components[1:]:\\r\\n mod = getattr(mod, comp)\\r\\n return mod\",\n \"def datapackage_path():\\n return 'datapackage.json'\",\n \"def _parent_path(pkg, pkg_path):\\n parent = pkg_path[: -len(pkg)] if pkg_path.endswith(pkg) else pkg_path\\n return parent.rstrip(\\\"/\\\" + os.sep)\",\n \"def normalize_package_name(_s: str) -> str:\\n return _s.replace('_', '-').lower()\",\n \"def native(path):\\n path = _os.path.sep.join(path.split('/'))\\n return _os.path.normpath(_os.path.join(root, path))\",\n \"def _get_package_dir ( self, pkg_name ):\\n if not pkg_name in self._subdirs:\\n self._lock.acquire()\\n try:\\n if not pkg_name in self._subdirs:\\n newpkg = self.packagedir_cls (\\n name = pkg_name,\\n logger = self.logger,\\n directory = self.physical_location + os.sep + pkg_name,\\n get_header = self.get_header,\\n runtime_incremental = self.runtime_incremental,\\n parent = self\\n )\\n self._subdirs [pkg_name] = newpkg\\n finally:\\n self._lock.release()\\n\\n return self._subdirs [pkg_name]\",\n \"def relativize(path: str):\\n return join('.', path)\",\n \"def path_to_module(path: str):\\n if path[-3:] != '.py':\\n raise ValueError(\\\"Not a python module path \\\", path)\\n path_minus_py = path[:-3]\\n path_w_dots = path_minus_py.replace(\\\"/\\\", \\\".\\\")\\n # strip leading docs\\n if path_w_dots[0] == '.':\\n path_w_dots = path_w_dots[1:]\\n # if there was an __init__ then strip that\\n if path_w_dots[-9:] == \\\".__init__\\\":\\n path_w_dots = path_w_dots[:-9]\\n return path_w_dots\",\n \"def module_path(module: 'ModuleType | str', subpath: str) -> str:\\n\\n parent = module_path_root(module)\\n path = os.path.join(parent, subpath.strip('/'))\\n\\n # always be paranoid with path manipulation\\n assert is_subpath(parent, path)\\n\\n return path\",\n \"def get_packages(package):\\n return [dirpath\\n for dirpath, dirnames, filenames in os.walk(package)\\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]\",\n \"def get_packages(package):\\n return [dirpath\\n for dirpath, dirnames, filenames in os.walk(package)\\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]\",\n \"def get_packages(package):\\n return [dirpath\\n for dirpath, dirnames, filenames in os.walk(package)\\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]\",\n \"def shortpath(path):\\r\\n import os\\r\\n if path.startswith(base_dir):\\r\\n return path[len(base_dir) + len(os.path.sep) : ]\\r\\n return path\",\n \"def resolved_path(path):\\n path = os.path.abspath(path)\\n elements = path_elements(path)\\n result = \\\"\\\"\\n for element in elements:\\n segment = element\\n segment_path = os.path.join(result, segment)\\n if os.path.islink(segment_path):\\n segment = os.readlink(segment_path)\\n result = os.path.join(result, segment)\\n result = os.path.normpath(result)\\n return result\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7921618","0.7368294","0.7326123","0.70896804","0.70801365","0.6791065","0.6757227","0.67504627","0.6700731","0.66353977","0.66276276","0.6621615","0.6564424","0.6564424","0.65590894","0.6505718","0.63585734","0.6354153","0.62997335","0.6271722","0.62491447","0.62227815","0.62029034","0.6163243","0.6157202","0.61546636","0.6140349","0.6131135","0.6110399","0.6109375","0.6089527","0.6080316","0.6071157","0.6059321","0.6048973","0.60277236","0.60038656","0.596441","0.5939106","0.59354943","0.59274644","0.59056234","0.589848","0.58984405","0.58953565","0.5890464","0.5877229","0.58610517","0.5855756","0.5844676","0.58409286","0.58252907","0.5812436","0.5805732","0.579731","0.57861626","0.5781553","0.57806057","0.5766583","0.5762769","0.575859","0.5755728","0.5742891","0.571099","0.57074887","0.56918937","0.5690721","0.56899595","0.5673436","0.5657008","0.56493247","0.5628725","0.5625815","0.5623062","0.5622627","0.56064874","0.5597911","0.55958784","0.5593195","0.5585725","0.5581826","0.5569756","0.5568917","0.5556218","0.55548006","0.555164","0.55481815","0.5535377","0.55216223","0.5515611","0.55105186","0.55076087","0.55064785","0.55059093","0.55000854","0.548393","0.548393","0.548393","0.5480826","0.54797685"],"string":"[\n \"0.7921618\",\n \"0.7368294\",\n \"0.7326123\",\n \"0.70896804\",\n \"0.70801365\",\n \"0.6791065\",\n \"0.6757227\",\n \"0.67504627\",\n \"0.6700731\",\n \"0.66353977\",\n \"0.66276276\",\n \"0.6621615\",\n \"0.6564424\",\n \"0.6564424\",\n \"0.65590894\",\n \"0.6505718\",\n \"0.63585734\",\n \"0.6354153\",\n \"0.62997335\",\n \"0.6271722\",\n \"0.62491447\",\n \"0.62227815\",\n \"0.62029034\",\n \"0.6163243\",\n \"0.6157202\",\n \"0.61546636\",\n \"0.6140349\",\n \"0.6131135\",\n \"0.6110399\",\n \"0.6109375\",\n \"0.6089527\",\n \"0.6080316\",\n \"0.6071157\",\n \"0.6059321\",\n \"0.6048973\",\n \"0.60277236\",\n \"0.60038656\",\n \"0.596441\",\n \"0.5939106\",\n \"0.59354943\",\n \"0.59274644\",\n \"0.59056234\",\n \"0.589848\",\n \"0.58984405\",\n \"0.58953565\",\n \"0.5890464\",\n \"0.5877229\",\n \"0.58610517\",\n \"0.5855756\",\n \"0.5844676\",\n \"0.58409286\",\n \"0.58252907\",\n \"0.5812436\",\n \"0.5805732\",\n \"0.579731\",\n \"0.57861626\",\n \"0.5781553\",\n \"0.57806057\",\n \"0.5766583\",\n \"0.5762769\",\n \"0.575859\",\n \"0.5755728\",\n \"0.5742891\",\n \"0.571099\",\n \"0.57074887\",\n \"0.56918937\",\n \"0.5690721\",\n \"0.56899595\",\n \"0.5673436\",\n \"0.5657008\",\n \"0.56493247\",\n \"0.5628725\",\n \"0.5625815\",\n \"0.5623062\",\n \"0.5622627\",\n \"0.56064874\",\n \"0.5597911\",\n \"0.55958784\",\n \"0.5593195\",\n \"0.5585725\",\n \"0.5581826\",\n \"0.5569756\",\n \"0.5568917\",\n \"0.5556218\",\n \"0.55548006\",\n \"0.555164\",\n \"0.55481815\",\n \"0.5535377\",\n \"0.55216223\",\n \"0.5515611\",\n \"0.55105186\",\n \"0.55076087\",\n \"0.55064785\",\n \"0.55059093\",\n \"0.55000854\",\n \"0.548393\",\n \"0.548393\",\n \"0.548393\",\n \"0.5480826\",\n \"0.54797685\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.8622001"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88564,"cells":{"query":{"kind":"string","value":"Get the subdirectories within a package This will include resources (nonsubmodules) and submodules"},"document":{"kind":"string","value":"def find_subdirectories(package):\n try:\n subdirectories = next(os.walk(package_to_path(package)))[1]\n except StopIteration:\n subdirectories = []\n return subdirectories"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def walk_package(pkgname, root):\n dirs = []\n files = []\n for name in pkg_resources.resource_listdir(pkgname, str(root)):\n fullname = root / name\n if pkg_resources.resource_isdir(pkgname, str(fullname)):\n dirs.append(fullname)\n else:\n files.append(Path(name))\n for new_path in dirs:\n yield from walk_package(pkgname, new_path)\n yield root, dirs, files","def get_packages(package):\n return [str(path.parent) for path in Path(package).glob(\"**/__init__.py\")]","def find_packages( root ):\n for path, directories, files in os.walk( root ):\n if is_package( path ):\n yield path.replace( '/','.' )","def get_packages(package):\n return [\n dirpath\n for dirpath, dirnames, filenames in os.walk(package)\n if os.path.exists(os.path.join(dirpath, '__init__.py'))\n ]","def get_packages(package):\n return [dirpath\n for dirpath, dirnames, filenames in os.walk(package)\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]","def get_packages(package):\n return [dirpath\n for dirpath, dirnames, filenames in os.walk(package)\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]","def get_packages(package):\n return [dirpath\n for dirpath, dirnames, filenames in os.walk(package)\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]","def get_leaf_modules(package_path):\n assert os.path.isfile(os.path.join(package_path, '__init__.py'))\n res = []\n root = os.path.join(package_path, '..')\n for path, _, files in os.walk(package_path):\n for f in files:\n if f.endswith(\".py\") and not f == \"__init__.py\":\n full_file = os.path.relpath(os.path.join(path, f), start=root)\n module = full_file.replace(os.sep, \".\")[:-3]\n res.append(module)\n return res","def getImmediateSubdirectories(dir):","def get_package_data(package):\n walk = [(dirpath.replace(package + os.sep, '', 1), filenames)\n for dirpath, dirnames, filenames in os.walk(package)\n if not os.path.exists(os.path.join(dirpath, '__init__.py'))]\n\n filepaths = []\n for base, filenames in walk:\n filepaths.extend([os.path.join(base, filename)\n for filename in filenames])\n return {package: filepaths}","def get_packages_with_prefixes():\n return get_resources('packages')","def _getSubDirectoryFolders(module, subdirs):\n\n module_dir = module.getCompileTimeDirectory()\n file_list = []\n\n data_dirs = [os.path.join(module_dir, subdir) for subdir in subdirs]\n\n # Gather the full file list, probably makes no sense to include bytecode files\n file_list = sum(\n (\n getFileList(\n data_dir, ignore_dirs=(\"__pycache__\",), ignore_suffixes=(\".pyc\",)\n )\n for data_dir in data_dirs\n ),\n [],\n )\n\n if not file_list:\n msg = \"No files or folders found for '%s' in subfolder(s) %r (%r).\" % (\n module.getFullName(),\n subdirs,\n data_dirs,\n )\n NuitkaPluginDataFileCollector.warning(msg)\n\n is_package = module.isCompiledPythonPackage() or module.isUncompiledPythonPackage()\n\n # We need to preserve the package target path in the dist folder.\n if is_package:\n package_part = module.getFullName().asPath()\n else:\n package = module.getFullName().getPackageName()\n\n if package is None:\n package_part = \"\"\n else:\n package_part = package.asPath()\n\n item_set = OrderedSet()\n\n for f in file_list:\n target = os.path.join(package_part, os.path.relpath(f, module_dir))\n\n dir_name = os.path.dirname(target)\n item_set.add(dir_name)\n\n return makeIncludedEmptyDirectories(\n source_path=module_dir,\n dest_paths=item_set,\n reason=\"Subdirectories of module %s\" % module.getFullName(),\n )","def find_package_data(package):\n walk = [(dirpath.replace(package + os.sep, '', 1), filenames)\n for dirpath, dirnames, filenames in os.walk(package)]\n\n filepaths = []\n for base, filenames in walk:\n filepaths.extend([os.path.join(base, filename)\n for filename in filenames])\n return filepaths","def _subdirectories(self):\n for o in os.listdir(self.directory):\n if os.path.isdir(os.path.join(self.directory, o)):\n yield os.path.join(self.directory, o)","def get_package_data(package):\n walk = [\n (dirpath.replace(package + os.sep, '', 1), filenames)\n for dirpath, dirnames, filenames in os.walk(package)\n if not os.path.exists(\n os.path.join(dirpath, '__init__.py')\n )\n ]\n\n filepaths = []\n for base, filenames in walk:\n filepaths.extend([\n os.path.join(base, filename) for filename in filenames\n ])\n return {package: filepaths}","def my_find_packages(*args):\n import os\n packages = []\n for root_module_dir in args:\n for root, dirs, files in os.walk(root_module_dir):\n if '__init__.py' in files:\n packages.append(root)\n return packages","def modules():\n return [os.path.relpath(os.path.join(root, filename), 'groot_ansible')\n for root, _, filenames in os.walk('groot_ansible/playbooks/library') for filename in filenames if '.git' not in root.split(os.sep)\n ]","def find_package_data(module, path):\n files = []\n exclude = re.compile(\"\\.pyc$|~$\")\n for dirpath, dirnames, filenames in os.walk(os.path.join(module,path)):\n for filename in filenames:\n if not exclude.search(filename):\n files.append(os.path.relpath(os.path.join(dirpath,filename),module))\n return {module:files}","def list_packages ( self, name_only=False ):\n if name_only:\n for name, subdir in self._subdirs.items():\n if not subdir.empty():\n yield name\n else:\n for name, subdir in self._subdirs.items():\n if not subdir.empty():\n yield self.name + os.sep + name","def get_package_resources(self):\n resources = []\n for pkg in self.packages:\n resource_data = self.get_resource_data()\n resources.extend(pkg.get_resources(resource_data))\n return resources","def subdir(self):","def find_package_data(data_root, package_root):\n files = []\n for root, dirnames, filenames in os.walk(data_root):\n for fn in filenames:\n files.append(relpath(join(root, fn), package_root))\n return files","def get_packages(root):\n root = os.path.realpath(root)\n proot = parent(root) + \"/\"\n py_files = [file.rsplit(proot)[1] for file in listfiles(root)]\n packages = list(np.unique([parent(file).replace(\"/\", \".\") for file in py_files]))\n # return list(np.unique([parent(file).replace(\"/\", \".\").split(\".{name_root}.\".format(name_root=name(root)))[1]\n # for file in py_files]))\n return packages","def find_packages(self):\n\n # scan src_dir for __init__.py\n root = _Path(self.src_dir)\n reg_paths = set(\n [d.parent.relative_to(root) for d in root.rglob(\"**/__init__.py\")]\n )\n\n # add all namespace packages that houses regular packages\n pkg_paths = set(reg_paths)\n for dir in reg_paths:\n pkg_paths |= set(dir.parents)\n\n # convert path to str\n pkg_dirs = [path.as_posix() for path in pkg_paths]\n\n # convert dir to package notation\n return [_dir_to_pkg(self.package_name, dir) for dir in pkg_dirs]","def get_package_directory(package, root_dir=None, sub_dir=None, suffix_root_dir=False):\n dir = get_ontology_directory(package.ontology, root_dir, sub_dir, suffix_root_dir)\n dir += '/'\n dir += get_package_name(package)\n return dir","def subdir_findall(dir, subdir):\n strip_n = len(dir.split('/'))\n path = '/'.join((dir, subdir))\n return ['/'.join(s.split('/')[strip_n:]) for s in setuptools.findall(path)]","def __dir__():\n return __all__","def get_templates_dirs(self): \n from pkg_resources import resource_filename\n return [ resource_filename(__name__, 'templates') ]\n # return []","def recurse_tree(rootpath_or_module, excludes, opts, use_module):\n # use absolute path for root, as relative paths like '../../foo' cause\n # 'if \"/.\" in root ...' to filter out *all* modules otherwise\n if use_module:\n rootpath = get_module_path(rootpath_or_module)\n else:\n rootpath = os.path.abspath(rootpath_or_module)\n\n if use_module:\n package_name = rootpath_or_module\n else:\n # check if the base directory is a package and get is name\n if INITPY in os.listdir(rootpath):\n package_name = rootpath.split(path.sep)[-1]\n else:\n package_name = None\n toc = []\n tree = os.walk(rootpath, False)\n for root, subs, files in tree:\n # keep only the Python script files\n py_files = sorted([f for f in files if path.splitext(f)[1] == '.py'])\n if INITPY in py_files:\n py_files.remove(INITPY)\n py_files.insert(0, INITPY)\n # remove hidden ('.') and private ('_') directories\n subs = sorted([sub for sub in subs if sub[0] not in ['.', '_']])\n # check if there are valid files to process\n # could add check for windows hidden files\n if \"/.\" in root or \"/_\" in root \\\n or not py_files \\\n or is_excluded(root, excludes):\n continue\n if INITPY in py_files:\n # we are in package ...\n if ( # ... with subpackage(s)\n subs\n or\n # ... with some module(s)\n len(py_files) > 1\n or\n # ... with a not-to-be-skipped INITPY file\n not shall_skip(path.join(root, INITPY))\n ):\n subroot = root[len(rootpath):].lstrip(path.sep).\\\n replace(path.sep, '.')\n create_package_file(root, package_name, subroot,\n py_files, opts, subs)\n toc.append(makename(package_name, subroot))\n elif root == rootpath:\n # if we are at the root level, we don't require it to be a package\n for py_file in py_files:\n if not shall_skip(path.join(rootpath, py_file)):\n module = path.splitext(py_file)[0]\n create_module_file(package_name, module, opts)\n toc.append(makename(package_name, module))\n\n # create the module's index\n if not opts.notoc:\n create_modules_toc_file(package_name, toc, opts)","def find_packages(cls, chroot, log=None):\n base = os.path.join(chroot.path(), cls.SOURCE_ROOT)\n packages, namespace_packages = set(), set()\n resources = defaultdict(set)\n\n def iter_files():\n for root, _, files in safe_walk(base):\n module = os.path.relpath(root, base).replace(os.path.sep, '.')\n for filename in files:\n yield module, filename, os.path.join(root, filename)\n\n # establish packages, namespace packages in first pass\n for module, filename, real_filename in iter_files():\n if filename != '__init__.py':\n continue\n packages.add(module)\n if cls.declares_namespace_package(real_filename):\n namespace_packages.add(module)\n\n # second pass establishes non-source content (resources)\n for module, filename, real_filename in iter_files():\n if filename.endswith('.py'):\n if module not in packages:\n # TODO(wickman) Consider changing this to a full-on error as it\n # could indicate bad BUILD hygiene.\n # raise cls.UndefinedSource('%s is source but does not belong to a package!' % filename)\n if log:\n log.warn('%s is source but does not belong to a package.' % real_filename)\n else:\n continue\n submodule = cls.nearest_subpackage(module, packages)\n if submodule == module:\n resources[submodule].add(filename)\n else:\n assert module.startswith(submodule + '.')\n relative_module = module[len(submodule) + 1:]\n relative_filename = os.path.join(relative_module.replace('.', os.path.sep), filename)\n resources[submodule].add(relative_filename)\n\n return packages, namespace_packages, resources","def include_dirs(self):","def _find_files_to_package(self, path):\n for root, dirs, files in os.walk(path):\n root_parts = pathlib.Path(root).relative_to(path).parts\n if self._include_directory(root_parts):\n for f in files:\n if self._include_file(root_parts, f):\n yield pathlib.Path(root, f)","def getAllDirs(self):\n\n dirs = [ self ]\n for d in self._subdirs:\n if d.hasImages():\n dirs += d.getAllDirs()\n return dirs","def __dir__():\n import pkgutil\n\n names = [\n name\n for importer, name, ispkg in pkgutil.iter_modules(__path__)\n if not ispkg and name != \"base\"\n ]\n return names + [\"custom\", \"noData\"]","def library_dirs(self):","def list(self):\n for dir in subdirs('plugins'):\n print dir.replace('plugins/', '')","def getPackageName(rootDir=\"python\"):\n dirIter = os.walk(rootDir)\n (dirPath, dirList, fileList) = next(dirIter)\n dirList = [dirName for dirName in dirList if not dirName.startswith(\".\")]\n if len(dirList) != 1:\n raise RuntimeError(\"Found %s instead of 1 directory\" % (dirList,))\n return dirList[0]","def go_package_dirs(packages, build_tags):\n\n target_packages = []\n for pkg in packages:\n target_packages += (\n check_output(\n f\"go list -find -f \\\"{{{{ .Dir }}}}\\\" -mod=mod -tags \\\"{','.join(build_tags)}\\\" {pkg}\",\n shell=True,\n )\n .decode('utf-8')\n .strip()\n .split(\"\\n\")\n )\n\n return target_packages","def list_submodules(package, recursive=True):\n if isinstance(package, str):\n package = importlib.import_module(package)\n results = []\n for _loader, name, is_pkg in pkgutil.walk_packages(package.__path__):\n full_name = package.__name__ + '.' + name\n results.append(full_name)\n if recursive and is_pkg:\n results.extend(list_submodules(full_name))\n return results","def getsitepackages():\n\tpass","def list_resource_files(resource_name: str) -> List[str]:\n\n files = []\n dirs = []\n\n def inner_recursion(resource_name: str):\n\n if not pkg_resources.resource_exists(__name__, resource_name):\n raise RuntimeError(\n f\"The resource {resource_name}, does not seem to be available \"\n )\n\n # base case\n if not pkg_resources.resource_isdir(__name__, resource_name):\n files.append(resource_name)\n\n # recursive case\n else:\n if not resource_name.endswith(\"/\"):\n resource_name += \"/\"\n\n dirs.append(resource_name)\n children = pkg_resources.resource_listdir(__name__, resource_name)\n\n resource_names_extended = [f\"{resource_name}{c}\" for c in children]\n\n for child_resource in resource_names_extended:\n inner_recursion(child_resource)\n\n inner_recursion(resource_name)\n\n return files","def get_package_files(_dir):\n _files = []\n for root, _, files in os.walk(_dir):\n if('git' in root or '/tests' in root):\n continue\n for _name in files:\n _files.append((root, _name))\n return _files","def get_package_python_paths(package, paths):\n # Note: Here we're trying to get `package`'s specific changes to PYTHONPATH (if any)\n #\n # Unfortunately, the Rez API doesn't really support this yet.\n # There's 2 GitHub links that may one-day implement it though:\n # - https://github.com/nerdvegas/rez/issues/737\n # - https://github.com/nerdvegas/rez/pull/739\n #\n # Reference: https://rez-talk.slack.com/archives/CHELFCTFB/p1578604659006100\n #\n # Once that work is merged, replace `get_package_python_paths` with it.\n #\n root = finder.get_package_root(package)\n\n if is_built_package(package):\n return {path for path in paths if filer.in_directory(path, root, follow=False)}\n\n output = set()\n\n for path in paths:\n # If the Rez package is a source Rez package + has variants\n # we need to strip the \"variants\" out of `path`, before\n # returning it.\n #\n try:\n variant_less_path = next(\n _iter_variant_extracted_paths(root, path, package.variants or [])\n )\n except StopIteration:\n pass\n else:\n output.add(variant_less_path)\n\n continue\n\n if filer.in_directory(path, root, follow=False) or filer.in_directory(\n path, root, follow=True\n ):\n output.add(path)\n\n continue\n\n return output","def _package_files(directory: str, suffix: str) -> list:\n\n paths = []\n\n for (path, directories, filenames) in os.walk(directory):\n for filename in filenames:\n if filename.endswith(suffix):\n paths.append(os.path.join('..', path, filename))\n\n return paths","def get_dirs(hub: pop.hub.Hub, sub: pop.hub.Sub) -> List[str]:\n return sub._dirs","def get_public_modules(path, base_package=None):\n result = []\n for subdir, _, files in os.walk(path):\n # Skip folders that start with _.\n if any([part.startswith('_')\n for part in subdir.split(os.path.sep)]):\n continue\n _, rel_dir = subdir.split(path)\n rel_dir = rel_dir.lstrip(os.path.sep)\n for filename in files:\n if is_valid_module(filename):\n mod_name, _ = os.path.splitext(filename)\n rel_path = os.path.join(rel_dir, mod_name)\n if base_package is not None:\n rel_path = os.path.join(base_package, rel_path)\n # Turn into a Python module rather than a file path.\n result.append(rel_path.replace(os.path.sep, '.'))\n\n return result","def _get_submodules():\n import sh\n git = sh.git.bake(_tty_out=False)\n submodules = git.submodule().strip().split(\"\\n\")\n return [\n line.strip()[1:].split()[1]\n for line in submodules\n ]","def get_directories():\n # get current working dir\n directory = os.getcwd()\n # list of dir to look in repo for files\n directories = [\n directory,\n os.path.expanduser(os.path.join(directory, 'src')),\n os.path.expanduser(os.path.join(directory, 'tests'))\n ]\n return directories","def _get_package_data() -> list[list[str]]:\n moddata = []\n modlist: tuple[str, ...] = (\n \"click\",\n \"cryptography\",\n \"globus_cli\",\n \"globus_sdk\",\n \"jmespath\",\n \"requests\",\n )\n if verbosity() < 2:\n modlist = (\"globus_cli\", \"globus_sdk\", \"requests\")\n\n for mod in modlist:\n cur = [mod]\n try:\n loaded_mod = __import__(mod)\n except ImportError:\n loaded_mod = None\n\n for attr in (\"__version__\", \"__file__\", \"__path__\"):\n # if loading failed, be sure to pad with error messages\n if loaded_mod is None:\n cur.append(\"[import failed]\")\n continue\n\n try:\n attrval = getattr(loaded_mod, attr)\n except AttributeError:\n attrval = \"\"\n cur.append(attrval)\n moddata.append(cur)\n\n return moddata","def get_library_content(self):\n from glob import glob\n try:\n os.path.isdir(self.source)\n lst = glob(self.source + '/*')\n except TypeError:\n lst = self.source\n dircheck = True\n while dircheck is True:\n dircheck = False\n newlst = []\n for entry in lst:\n if os.path.isdir(entry):\n newlst.extend(glob(entry + '/*'))\n dircheck = True\n else:\n newlst.append(entry)\n lst = newlst\n return lst","def package_dir(self):\r\n return \".\"","def packages():","def finddirs(root):\n retval = []\n for root, dirs, files in os.walk(root):\n for d in dirs:\n retval.append(os.path.join(root, d))\n return retval","def getModules() -> tuple:\n return data.getFoldersOf(data.ETC)","def get_package_data_files(package, data, package_dir=None):\n if package_dir is None:\n package_dir = os.path.join(*package.split('.'))\n all_files = []\n for f in data:\n path = os.path.join(package_dir, f)\n if os.path.isfile(path):\n all_files.append(f)\n continue\n for root, _dirs, files in os.walk(path, followlinks=True):\n root = os.path.relpath(root, package_dir)\n for file in files:\n file = os.path.join(root, file)\n if file not in all_files:\n all_files.append(file)\n return all_files","def walkdirs(root):\r\n scriptype_paths = collections.defaultdict(set)\r\n for root, subdirs, files in os.walk(root):\r\n\r\n # Filter subdirs\r\n tmpdir = []\r\n for i in subdirs:\r\n if i.startswith(EXCLUDE_PATTERNS):\r\n continue\r\n if '__init__.py' in os.listdir(os.path.join(root, i)):\r\n scriptype_paths['python'].add(root)\r\n continue\r\n tmpdir.append(i)\r\n subdirs[:] = tmpdir\r\n\r\n # If files with extension exists add to right source type.\r\n if ext_exists('.py', files):\r\n scriptype_paths['python'].add(root)\r\n if ext_exists('.mel', files):\r\n scriptype_paths['mel'].add(root)\r\n return scriptype_paths","def _get_package_dir ( self, pkg_name ):\n if not pkg_name in self._subdirs:\n self._lock.acquire()\n try:\n if not pkg_name in self._subdirs:\n newpkg = self.packagedir_cls (\n name = pkg_name,\n logger = self.logger,\n directory = self.physical_location + os.sep + pkg_name,\n get_header = self.get_header,\n runtime_incremental = self.runtime_incremental,\n parent = self\n )\n self._subdirs [pkg_name] = newpkg\n finally:\n self._lock.release()\n\n return self._subdirs [pkg_name]","def get_subdirs(dir_path: str) -> list:\n res = list(x.name for x in os.scandir(dir_path) if x.is_dir())\n return res","def get_docs(root='assets/doc', depth=2):\n if depth == 0:\n return listdir(root)\n a = dict()\n for c in filter(lambda d: isdir(join(root, d)) and not d.startswith('.'), listdir(root)):\n a[c] = get_docs(join(root, c), depth-1)\n return a","def packages_in_folder(path):\n for pkg_path in catkin_pkg.packages.find_package_paths(path):\n yield os.path.join(path, pkg_path)","def get_directories_recursive(self, path) :\n\n if path.is_dir() :\n yield path\n for child in path.iterdir():\n yield from self.get_directories_recursive(child)\n elif path.is_file() :\n yield path","def collect_subdirs(path_to_walk):\n root, subdirs, _ = next(os.walk(path_to_walk))\n\n return [os.path.join(root, d) for d in subdirs]","def get_templates_dirs(self):\n\t\tfrom pkg_resources import resource_filename\n\t\treturn [resource_filename(__name__, 'templates')]","def find_modules(x):\n return Path(x).rglob('*.py')","def pkgDirIter(self):\r\n return self._pkgDir.__iter__()","def get_package_folders(which_folder: str = \"root\") -> Path:\n logg = logging.getLogger(f\"c.{__name__}.get_package_folders\")\n # logg.setLevel(\"INFO\")\n logg.debug(\"Start get_package_folders\")\n\n this_file_folder = Path(__file__).absolute().parent\n logg.debug(f\"{this_file_folder=}\")\n\n package_root_folder = this_file_folder.parent.parent.parent\n\n if which_folder == \"root\":\n return package_root_folder\n\n elif which_folder == \"tests\":\n tests_folder = package_root_folder / \"tests\"\n return tests_folder\n\n elif which_folder == \"template_epub\":\n template_epub_folder = package_root_folder / \"assets\" / \"template_epub\"\n return template_epub_folder\n\n elif which_folder == \"word_pairs\":\n word_pairs_folder = package_root_folder / \"assets\" / \"word_pairs\"\n return word_pairs_folder\n\n elif which_folder == \"common_words\":\n common_words_folder = package_root_folder / \"assets\" / \"common_words\"\n return common_words_folder\n\n else:\n raise KeyError(f\"Not recognized {which_folder}\")","def walk_recursive(root, pattern='*.py'):\r\n for root, dirnames, filenames in os.walk(root):\r\n for filename in fnmatch.filter(filenames, pattern):\r\n yield os.path.join(root, filename)","def get_subdirs(src_dir):\n img_dirs = sorted(next(os.walk(src_dir))[1])\n subdirs = [src_dir + img_dir for img_dir in img_dirs]\n return subdirs","def get_all_modules(package):\n base = Path(inspect.getabsfile(package)).parent\n\n for fl in base.glob(\"*.py\"):\n print(f\"loading module {fl}\")\n yield load_module(fl)","def _generatePythonPath(self, pkg):\r\n if pkg in self._packages:\r\n return []\r\n\r\n # short-circuit if this is a catkin-ized package\r\n m = self._rp.get_manifest(pkg)\r\n\r\n if m.is_catkin:\r\n self._packages.add(pkg)\r\n return []\r\n\r\n packages = self._getDepends(pkg)\r\n packages.append(pkg)\r\n\r\n paths = []\r\n\r\n try:\r\n for p in packages:\r\n m = self._rp.get_manifest(p)\r\n d = self._rp.get_path(p)\r\n self._appendPackagePaths(m, paths, d)\r\n self._packages.add(p)\r\n except:\r\n self._packages.discard(pkg)\r\n raise\r\n\r\n return paths","def get_ros_package_path(config):\n code_trees = []\n for tree_el in reversed(config.get_config_elements()):\n if not is_path_ros(tree_el.get_path()):\n if not os.path.isfile(tree_el.get_path()):\n code_trees.append(tree_el.get_path())\n return code_trees","def get_package_dir():\n return Path(__file__).parent","def walk_dir(path):\r\n\tassets = []\r\n\r\n\tfor file in os.listdir(path):\r\n\t\tif os.path.isdir(path + \"/\" + file):\r\n\t\t\tif not file.startswith(\".\"):\r\n\t\t\t\t# Ignore . dirs (e.g .svn)\r\n\t\t\t\tassets.extend(walk_dir(path + \"/\" + file))\r\n\t\telif file.endswith('.blend'):\r\n\t\t\tassets.append(path + \"/\" + file)\r\n\r\n\treturn assets","def get_rpaths(pkg):\n rpaths = [pkg.prefix.lib, pkg.prefix.lib64]\n deps = get_rpath_deps(pkg)\n rpaths.extend(d.prefix.lib for d in deps if os.path.isdir(d.prefix.lib))\n rpaths.extend(d.prefix.lib64 for d in deps if os.path.isdir(d.prefix.lib64))\n # Second module is our compiler mod name. We use that to get rpaths from\n # module show output.\n if pkg.compiler.modules and len(pkg.compiler.modules) > 1:\n rpaths.append(path_from_modules([pkg.compiler.modules[1]]))\n return list(dedupe(filter_system_paths(rpaths)))","def get_all_paths(dmt, directory_path=''):\n # Base case.\n if not dmt.children:\n return set()\n \n filesystem_items = set()\n for item in dmt.children.keys():\n filesystem_items.add(directory_path+item)\n # Also get the paths of subdirectory contents.\n if item[-1] == '/':\n subdir_name = item\n subdir_path = directory_path + subdir_name\n \n filesystem_items.add(subdir_path)\n filesystem_items.update(get_all_paths(dmt.children[subdir_name], subdir_path))\n \n return filesystem_items","def test_GetFilesInDirectory_subdir_relpath(tempdir: pathlib.Path):\n # Create files: [ sub/a, sub/sub/b ]\n (tempdir / \"sub\").mkdir()\n (tempdir / \"sub\" / \"a\").touch()\n (tempdir / \"sub\" / \"sub\").mkdir()\n (tempdir / \"sub\" / \"sub\" / \"b\").touch()\n assert set(dpack.GetFilesInDirectory(tempdir, [])) == {\n pathlib.Path(\"sub/a\"),\n pathlib.Path(\"sub/sub/b\"),\n }","def get_skins_and_extensions(base_dir):\n ext_paths = []\n for subdir in ['extensions', 'skins']:\n for name in os.listdir(os.path.join(base_dir, subdir)):\n if os.path.isdir(os.path.join(base_dir, subdir, name)):\n ext_paths.append(os.path.join(subdir, name))\n return ext_paths","def relative_to_buildroot(self):\n return [os.path.join(self.rel_path, source) for source in self.source_paths]","def files(self) -> Generator[Path, None, None]:\n return Path(self.package).resolve(strict=True).glob(self.glob)","def __dir__(self):\n result = list(new_module.__all__)\n result.extend(('__file__', '__path__', '__doc__', '__all__',\n '__docformat__', '__name__', '__path__',\n '__package__', '__version__'))\n return result","def get_paths():\n\n # Get repo name\n git_repo = git.Repo(__file__, search_parent_directories=True)\n repo = git_repo.git.rev_parse(\"--show-toplevel\")\n\n paths = {\"repo\": repo, \"base\":{}, \"src\":{}, \"data\":{}, \"app\":{}}\n\n for base_dir in [\"data\", \"notebooks\", \"src\", \"model\", \"logs\", \"app\"]:\n\n paths[\"base\"][base_dir] = os.path.join(repo, base_dir)\n test = paths[\"base\"][base_dir].split(base_dir)[-1]\n assert len(test) == 0\n\n for src_dir in [\"conf\", \"data\", \"notebooks\", \"tests\", \"utils\",\n \"visualize\", \"conf\", \"model\"]:\n\n src_base_dir = paths.get(\"base\").get(\"src\")\n paths[\"src\"][src_dir] = os.path.join(src_base_dir, src_dir)\n test = paths[\"src\"][src_dir].split(src_dir)[-1]\n assert len(test) == 0\n\n for data_dir in [\"raw\", \"interim\", \"processed\"]:\n\n data_base_dir = paths.get(\"base\").get(\"data\")\n paths[\"data\"][data_dir] = os.path.join(data_base_dir, data_dir)\n test = paths[\"data\"][data_dir].split(data_dir)[-1]\n assert len(test) == 0\n\n for app_dir in [\"templates\", \"static\"]:\n app_base_dir = paths.get(\"base\").get(\"app\")\n paths[\"app\"][app_dir] = os.path.join(app_base_dir, app_dir)\n\n return paths","def subdirs(dir):\n return [dir + '/' + name for name in os.listdir(dir)\n if os.path.isdir(os.path.join(dir, name))]","def get_builder_root_dirs(self, name: naming.DatasetName) -> List[epath.Path]:\n return [d / name.name for d in self._ns2data_dir[name.namespace]]","def get_content_directories() -> List[str]:\n result:list[str] = []\n for current_path in os.listdir(\"content\"):\n if os.path.isdir(os.path.join(\"content\", current_path)):\n result.append(os.path.join(\"content\", current_path))\n return result","def dcs_modules():\n\n dcs_dirname = os.path.dirname(__file__)\n module_prefix = __package__ + '.'\n\n if getattr(sys, 'frozen', False):\n importer = pkgutil.get_importer(dcs_dirname)\n return [module for module in list(importer.toc) if module.startswith(module_prefix) and module.count('.') == 2]\n else:\n return [module_prefix + name for _, name, is_pkg in pkgutil.iter_modules([dcs_dirname]) if not is_pkg]","def get_templates_dirs(self):\n from pkg_resources import resource_filename\n return [resource_filename(__name__, 'templates')]","def GetPackageDirectory():\n return os.path.dirname(__file__)","def scan ( self, **kw ):\n stats = self.STATS\n stats.scan_time.begin ( self.name )\n for subdir in os.listdir ( self.physical_location ):\n if self.has_dir ( subdir ):\n pkgdir = self._get_package_dir ( subdir )\n try:\n pkgdir.scan ( stats=stats, **kw )\n finally:\n if pkgdir.empty():\n del self._subdirs [subdir]\n\n stats.scan_time.end ( self.name )","def collect_children(self, recursive=True):\n self.children = []\n\n for fname in os.listdir(self.path):\n path = join(self.path, fname)\n\n if Package.is_pkg(path):\n child = Package.create(path, owner=self)\n if recursive:\n child.collect_children()\n\n elif Module.is_module(path):\n child = Module.create(path, owner=self)\n\n else:\n if util.get_verbosity_level() > 0:\n print(\"Skipping: {}\".format(path))\n continue\n\n self.children.append(child)","def find_bundles_dirs(charm_dir: Path) -> List[Path]:\n paths = (('tests', 'bundles'),\n ('tests', 'bundles', 'overlays'),\n ('src', 'tests', 'bundles'),\n ('src', 'tests', 'bundles', 'overlays'))\n\n found_list: List[Path] = []\n for path in paths:\n logging.debug(\"Searching: %s\", path)\n dir_ = charm_dir.joinpath(*path)\n if dir_.is_dir():\n found_list.append(dir_)\n return found_list","def __gitSubmodulesList(self):\n self.vcs.gitSubmoduleList(self.project.getProjectPath())","def expand_package(self, pkg):\n return [(pkg, c) for c in self.packages[pkg].components]","def _find_files(root_dir, should_include):\n paths = [] # Return value.\n\n is_module = lambda path: path.endswith(\".py\")\n\n # os.walk() is new in Python 2.3\n # http://docs.python.org/library/os.html#os.walk\n for dir_path, dir_names, file_names in os.walk(root_dir):\n new_paths = [os.path.join(dir_path, file_name) for file_name in file_names]\n new_paths = filter(is_module, new_paths)\n new_paths = filter(should_include, new_paths)\n paths.extend(new_paths)\n\n return paths","def lib_dirs(self):\r\n ret = []\r\n for x in [y.type for y in self.variables] + [\r\n y.op for y in self.node_order]:\r\n try:\r\n ret += x.c_lib_dirs()\r\n except utils.MethodNotDefined:\r\n pass\r\n return utils.uniq(ret)","def list_dir(self, path):","def moduleList(path):\n\n if os.path.isdir(path):\n folder_list = os.listdir(path)\n elif path.endswith('.egg'):\n try:\n folder_list = [f for f in zipimporter(path)._files]\n except:\n folder_list = []\n else:\n folder_list = []\n #folder_list = glob.glob(os.path.join(path,'*'))\n folder_list = [p for p in folder_list \\\n if os.path.exists(os.path.join(path, p,'__init__.py'))\\\n or p[-3:] in ('.py','.so')\\\n or p[-4:] in ('.pyc','.pyo','.pyd')]\n\n folder_list = [os.path.basename(p).split('.')[0] for p in folder_list]\n return folder_list","def get_files(self, include=[], exclude=[]):\r\n for (basepath, dpaths, fpaths) in os.walk(self.path, topdown=True):\r\n for subpath in dpaths + fpaths:\r\n path = os.path.join(self.chroot_path(basepath), subpath)\r\n if filter_path(path, include, exclude):\r\n yield path","def _load_dirs(self):\n rootdirs = self._docset.get_compounds(xml.Directory,\n lambda x: x.get_parent() is None)\n for dirdoc in rootdirs:\n self._load_dir(dirdoc, None)","def syspaths(self):\n res = []\n for path, jsmodule in self.jsmodules.items():\n if jsmodule.js_lib_path != \"\":\n js_lib_path = os.path.dirname(jsmodule.js_lib_path.rstrip(\"/\")) # get parent\n if not js_lib_path in res:\n res.append(js_lib_path)\n return res","def packages(self):\n return []"],"string":"[\n \"def walk_package(pkgname, root):\\n dirs = []\\n files = []\\n for name in pkg_resources.resource_listdir(pkgname, str(root)):\\n fullname = root / name\\n if pkg_resources.resource_isdir(pkgname, str(fullname)):\\n dirs.append(fullname)\\n else:\\n files.append(Path(name))\\n for new_path in dirs:\\n yield from walk_package(pkgname, new_path)\\n yield root, dirs, files\",\n \"def get_packages(package):\\n return [str(path.parent) for path in Path(package).glob(\\\"**/__init__.py\\\")]\",\n \"def find_packages( root ):\\n for path, directories, files in os.walk( root ):\\n if is_package( path ):\\n yield path.replace( '/','.' )\",\n \"def get_packages(package):\\n return [\\n dirpath\\n for dirpath, dirnames, filenames in os.walk(package)\\n if os.path.exists(os.path.join(dirpath, '__init__.py'))\\n ]\",\n \"def get_packages(package):\\n return [dirpath\\n for dirpath, dirnames, filenames in os.walk(package)\\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]\",\n \"def get_packages(package):\\n return [dirpath\\n for dirpath, dirnames, filenames in os.walk(package)\\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]\",\n \"def get_packages(package):\\n return [dirpath\\n for dirpath, dirnames, filenames in os.walk(package)\\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]\",\n \"def get_leaf_modules(package_path):\\n assert os.path.isfile(os.path.join(package_path, '__init__.py'))\\n res = []\\n root = os.path.join(package_path, '..')\\n for path, _, files in os.walk(package_path):\\n for f in files:\\n if f.endswith(\\\".py\\\") and not f == \\\"__init__.py\\\":\\n full_file = os.path.relpath(os.path.join(path, f), start=root)\\n module = full_file.replace(os.sep, \\\".\\\")[:-3]\\n res.append(module)\\n return res\",\n \"def getImmediateSubdirectories(dir):\",\n \"def get_package_data(package):\\n walk = [(dirpath.replace(package + os.sep, '', 1), filenames)\\n for dirpath, dirnames, filenames in os.walk(package)\\n if not os.path.exists(os.path.join(dirpath, '__init__.py'))]\\n\\n filepaths = []\\n for base, filenames in walk:\\n filepaths.extend([os.path.join(base, filename)\\n for filename in filenames])\\n return {package: filepaths}\",\n \"def get_packages_with_prefixes():\\n return get_resources('packages')\",\n \"def _getSubDirectoryFolders(module, subdirs):\\n\\n module_dir = module.getCompileTimeDirectory()\\n file_list = []\\n\\n data_dirs = [os.path.join(module_dir, subdir) for subdir in subdirs]\\n\\n # Gather the full file list, probably makes no sense to include bytecode files\\n file_list = sum(\\n (\\n getFileList(\\n data_dir, ignore_dirs=(\\\"__pycache__\\\",), ignore_suffixes=(\\\".pyc\\\",)\\n )\\n for data_dir in data_dirs\\n ),\\n [],\\n )\\n\\n if not file_list:\\n msg = \\\"No files or folders found for '%s' in subfolder(s) %r (%r).\\\" % (\\n module.getFullName(),\\n subdirs,\\n data_dirs,\\n )\\n NuitkaPluginDataFileCollector.warning(msg)\\n\\n is_package = module.isCompiledPythonPackage() or module.isUncompiledPythonPackage()\\n\\n # We need to preserve the package target path in the dist folder.\\n if is_package:\\n package_part = module.getFullName().asPath()\\n else:\\n package = module.getFullName().getPackageName()\\n\\n if package is None:\\n package_part = \\\"\\\"\\n else:\\n package_part = package.asPath()\\n\\n item_set = OrderedSet()\\n\\n for f in file_list:\\n target = os.path.join(package_part, os.path.relpath(f, module_dir))\\n\\n dir_name = os.path.dirname(target)\\n item_set.add(dir_name)\\n\\n return makeIncludedEmptyDirectories(\\n source_path=module_dir,\\n dest_paths=item_set,\\n reason=\\\"Subdirectories of module %s\\\" % module.getFullName(),\\n )\",\n \"def find_package_data(package):\\n walk = [(dirpath.replace(package + os.sep, '', 1), filenames)\\n for dirpath, dirnames, filenames in os.walk(package)]\\n\\n filepaths = []\\n for base, filenames in walk:\\n filepaths.extend([os.path.join(base, filename)\\n for filename in filenames])\\n return filepaths\",\n \"def _subdirectories(self):\\n for o in os.listdir(self.directory):\\n if os.path.isdir(os.path.join(self.directory, o)):\\n yield os.path.join(self.directory, o)\",\n \"def get_package_data(package):\\n walk = [\\n (dirpath.replace(package + os.sep, '', 1), filenames)\\n for dirpath, dirnames, filenames in os.walk(package)\\n if not os.path.exists(\\n os.path.join(dirpath, '__init__.py')\\n )\\n ]\\n\\n filepaths = []\\n for base, filenames in walk:\\n filepaths.extend([\\n os.path.join(base, filename) for filename in filenames\\n ])\\n return {package: filepaths}\",\n \"def my_find_packages(*args):\\n import os\\n packages = []\\n for root_module_dir in args:\\n for root, dirs, files in os.walk(root_module_dir):\\n if '__init__.py' in files:\\n packages.append(root)\\n return packages\",\n \"def modules():\\n return [os.path.relpath(os.path.join(root, filename), 'groot_ansible')\\n for root, _, filenames in os.walk('groot_ansible/playbooks/library') for filename in filenames if '.git' not in root.split(os.sep)\\n ]\",\n \"def find_package_data(module, path):\\n files = []\\n exclude = re.compile(\\\"\\\\.pyc$|~$\\\")\\n for dirpath, dirnames, filenames in os.walk(os.path.join(module,path)):\\n for filename in filenames:\\n if not exclude.search(filename):\\n files.append(os.path.relpath(os.path.join(dirpath,filename),module))\\n return {module:files}\",\n \"def list_packages ( self, name_only=False ):\\n if name_only:\\n for name, subdir in self._subdirs.items():\\n if not subdir.empty():\\n yield name\\n else:\\n for name, subdir in self._subdirs.items():\\n if not subdir.empty():\\n yield self.name + os.sep + name\",\n \"def get_package_resources(self):\\n resources = []\\n for pkg in self.packages:\\n resource_data = self.get_resource_data()\\n resources.extend(pkg.get_resources(resource_data))\\n return resources\",\n \"def subdir(self):\",\n \"def find_package_data(data_root, package_root):\\n files = []\\n for root, dirnames, filenames in os.walk(data_root):\\n for fn in filenames:\\n files.append(relpath(join(root, fn), package_root))\\n return files\",\n \"def get_packages(root):\\n root = os.path.realpath(root)\\n proot = parent(root) + \\\"/\\\"\\n py_files = [file.rsplit(proot)[1] for file in listfiles(root)]\\n packages = list(np.unique([parent(file).replace(\\\"/\\\", \\\".\\\") for file in py_files]))\\n # return list(np.unique([parent(file).replace(\\\"/\\\", \\\".\\\").split(\\\".{name_root}.\\\".format(name_root=name(root)))[1]\\n # for file in py_files]))\\n return packages\",\n \"def find_packages(self):\\n\\n # scan src_dir for __init__.py\\n root = _Path(self.src_dir)\\n reg_paths = set(\\n [d.parent.relative_to(root) for d in root.rglob(\\\"**/__init__.py\\\")]\\n )\\n\\n # add all namespace packages that houses regular packages\\n pkg_paths = set(reg_paths)\\n for dir in reg_paths:\\n pkg_paths |= set(dir.parents)\\n\\n # convert path to str\\n pkg_dirs = [path.as_posix() for path in pkg_paths]\\n\\n # convert dir to package notation\\n return [_dir_to_pkg(self.package_name, dir) for dir in pkg_dirs]\",\n \"def get_package_directory(package, root_dir=None, sub_dir=None, suffix_root_dir=False):\\n dir = get_ontology_directory(package.ontology, root_dir, sub_dir, suffix_root_dir)\\n dir += '/'\\n dir += get_package_name(package)\\n return dir\",\n \"def subdir_findall(dir, subdir):\\n strip_n = len(dir.split('/'))\\n path = '/'.join((dir, subdir))\\n return ['/'.join(s.split('/')[strip_n:]) for s in setuptools.findall(path)]\",\n \"def __dir__():\\n return __all__\",\n \"def get_templates_dirs(self): \\n from pkg_resources import resource_filename\\n return [ resource_filename(__name__, 'templates') ]\\n # return []\",\n \"def recurse_tree(rootpath_or_module, excludes, opts, use_module):\\n # use absolute path for root, as relative paths like '../../foo' cause\\n # 'if \\\"/.\\\" in root ...' to filter out *all* modules otherwise\\n if use_module:\\n rootpath = get_module_path(rootpath_or_module)\\n else:\\n rootpath = os.path.abspath(rootpath_or_module)\\n\\n if use_module:\\n package_name = rootpath_or_module\\n else:\\n # check if the base directory is a package and get is name\\n if INITPY in os.listdir(rootpath):\\n package_name = rootpath.split(path.sep)[-1]\\n else:\\n package_name = None\\n toc = []\\n tree = os.walk(rootpath, False)\\n for root, subs, files in tree:\\n # keep only the Python script files\\n py_files = sorted([f for f in files if path.splitext(f)[1] == '.py'])\\n if INITPY in py_files:\\n py_files.remove(INITPY)\\n py_files.insert(0, INITPY)\\n # remove hidden ('.') and private ('_') directories\\n subs = sorted([sub for sub in subs if sub[0] not in ['.', '_']])\\n # check if there are valid files to process\\n # could add check for windows hidden files\\n if \\\"/.\\\" in root or \\\"/_\\\" in root \\\\\\n or not py_files \\\\\\n or is_excluded(root, excludes):\\n continue\\n if INITPY in py_files:\\n # we are in package ...\\n if ( # ... with subpackage(s)\\n subs\\n or\\n # ... with some module(s)\\n len(py_files) > 1\\n or\\n # ... with a not-to-be-skipped INITPY file\\n not shall_skip(path.join(root, INITPY))\\n ):\\n subroot = root[len(rootpath):].lstrip(path.sep).\\\\\\n replace(path.sep, '.')\\n create_package_file(root, package_name, subroot,\\n py_files, opts, subs)\\n toc.append(makename(package_name, subroot))\\n elif root == rootpath:\\n # if we are at the root level, we don't require it to be a package\\n for py_file in py_files:\\n if not shall_skip(path.join(rootpath, py_file)):\\n module = path.splitext(py_file)[0]\\n create_module_file(package_name, module, opts)\\n toc.append(makename(package_name, module))\\n\\n # create the module's index\\n if not opts.notoc:\\n create_modules_toc_file(package_name, toc, opts)\",\n \"def find_packages(cls, chroot, log=None):\\n base = os.path.join(chroot.path(), cls.SOURCE_ROOT)\\n packages, namespace_packages = set(), set()\\n resources = defaultdict(set)\\n\\n def iter_files():\\n for root, _, files in safe_walk(base):\\n module = os.path.relpath(root, base).replace(os.path.sep, '.')\\n for filename in files:\\n yield module, filename, os.path.join(root, filename)\\n\\n # establish packages, namespace packages in first pass\\n for module, filename, real_filename in iter_files():\\n if filename != '__init__.py':\\n continue\\n packages.add(module)\\n if cls.declares_namespace_package(real_filename):\\n namespace_packages.add(module)\\n\\n # second pass establishes non-source content (resources)\\n for module, filename, real_filename in iter_files():\\n if filename.endswith('.py'):\\n if module not in packages:\\n # TODO(wickman) Consider changing this to a full-on error as it\\n # could indicate bad BUILD hygiene.\\n # raise cls.UndefinedSource('%s is source but does not belong to a package!' % filename)\\n if log:\\n log.warn('%s is source but does not belong to a package.' % real_filename)\\n else:\\n continue\\n submodule = cls.nearest_subpackage(module, packages)\\n if submodule == module:\\n resources[submodule].add(filename)\\n else:\\n assert module.startswith(submodule + '.')\\n relative_module = module[len(submodule) + 1:]\\n relative_filename = os.path.join(relative_module.replace('.', os.path.sep), filename)\\n resources[submodule].add(relative_filename)\\n\\n return packages, namespace_packages, resources\",\n \"def include_dirs(self):\",\n \"def _find_files_to_package(self, path):\\n for root, dirs, files in os.walk(path):\\n root_parts = pathlib.Path(root).relative_to(path).parts\\n if self._include_directory(root_parts):\\n for f in files:\\n if self._include_file(root_parts, f):\\n yield pathlib.Path(root, f)\",\n \"def getAllDirs(self):\\n\\n dirs = [ self ]\\n for d in self._subdirs:\\n if d.hasImages():\\n dirs += d.getAllDirs()\\n return dirs\",\n \"def __dir__():\\n import pkgutil\\n\\n names = [\\n name\\n for importer, name, ispkg in pkgutil.iter_modules(__path__)\\n if not ispkg and name != \\\"base\\\"\\n ]\\n return names + [\\\"custom\\\", \\\"noData\\\"]\",\n \"def library_dirs(self):\",\n \"def list(self):\\n for dir in subdirs('plugins'):\\n print dir.replace('plugins/', '')\",\n \"def getPackageName(rootDir=\\\"python\\\"):\\n dirIter = os.walk(rootDir)\\n (dirPath, dirList, fileList) = next(dirIter)\\n dirList = [dirName for dirName in dirList if not dirName.startswith(\\\".\\\")]\\n if len(dirList) != 1:\\n raise RuntimeError(\\\"Found %s instead of 1 directory\\\" % (dirList,))\\n return dirList[0]\",\n \"def go_package_dirs(packages, build_tags):\\n\\n target_packages = []\\n for pkg in packages:\\n target_packages += (\\n check_output(\\n f\\\"go list -find -f \\\\\\\"{{{{ .Dir }}}}\\\\\\\" -mod=mod -tags \\\\\\\"{','.join(build_tags)}\\\\\\\" {pkg}\\\",\\n shell=True,\\n )\\n .decode('utf-8')\\n .strip()\\n .split(\\\"\\\\n\\\")\\n )\\n\\n return target_packages\",\n \"def list_submodules(package, recursive=True):\\n if isinstance(package, str):\\n package = importlib.import_module(package)\\n results = []\\n for _loader, name, is_pkg in pkgutil.walk_packages(package.__path__):\\n full_name = package.__name__ + '.' + name\\n results.append(full_name)\\n if recursive and is_pkg:\\n results.extend(list_submodules(full_name))\\n return results\",\n \"def getsitepackages():\\n\\tpass\",\n \"def list_resource_files(resource_name: str) -> List[str]:\\n\\n files = []\\n dirs = []\\n\\n def inner_recursion(resource_name: str):\\n\\n if not pkg_resources.resource_exists(__name__, resource_name):\\n raise RuntimeError(\\n f\\\"The resource {resource_name}, does not seem to be available \\\"\\n )\\n\\n # base case\\n if not pkg_resources.resource_isdir(__name__, resource_name):\\n files.append(resource_name)\\n\\n # recursive case\\n else:\\n if not resource_name.endswith(\\\"/\\\"):\\n resource_name += \\\"/\\\"\\n\\n dirs.append(resource_name)\\n children = pkg_resources.resource_listdir(__name__, resource_name)\\n\\n resource_names_extended = [f\\\"{resource_name}{c}\\\" for c in children]\\n\\n for child_resource in resource_names_extended:\\n inner_recursion(child_resource)\\n\\n inner_recursion(resource_name)\\n\\n return files\",\n \"def get_package_files(_dir):\\n _files = []\\n for root, _, files in os.walk(_dir):\\n if('git' in root or '/tests' in root):\\n continue\\n for _name in files:\\n _files.append((root, _name))\\n return _files\",\n \"def get_package_python_paths(package, paths):\\n # Note: Here we're trying to get `package`'s specific changes to PYTHONPATH (if any)\\n #\\n # Unfortunately, the Rez API doesn't really support this yet.\\n # There's 2 GitHub links that may one-day implement it though:\\n # - https://github.com/nerdvegas/rez/issues/737\\n # - https://github.com/nerdvegas/rez/pull/739\\n #\\n # Reference: https://rez-talk.slack.com/archives/CHELFCTFB/p1578604659006100\\n #\\n # Once that work is merged, replace `get_package_python_paths` with it.\\n #\\n root = finder.get_package_root(package)\\n\\n if is_built_package(package):\\n return {path for path in paths if filer.in_directory(path, root, follow=False)}\\n\\n output = set()\\n\\n for path in paths:\\n # If the Rez package is a source Rez package + has variants\\n # we need to strip the \\\"variants\\\" out of `path`, before\\n # returning it.\\n #\\n try:\\n variant_less_path = next(\\n _iter_variant_extracted_paths(root, path, package.variants or [])\\n )\\n except StopIteration:\\n pass\\n else:\\n output.add(variant_less_path)\\n\\n continue\\n\\n if filer.in_directory(path, root, follow=False) or filer.in_directory(\\n path, root, follow=True\\n ):\\n output.add(path)\\n\\n continue\\n\\n return output\",\n \"def _package_files(directory: str, suffix: str) -> list:\\n\\n paths = []\\n\\n for (path, directories, filenames) in os.walk(directory):\\n for filename in filenames:\\n if filename.endswith(suffix):\\n paths.append(os.path.join('..', path, filename))\\n\\n return paths\",\n \"def get_dirs(hub: pop.hub.Hub, sub: pop.hub.Sub) -> List[str]:\\n return sub._dirs\",\n \"def get_public_modules(path, base_package=None):\\n result = []\\n for subdir, _, files in os.walk(path):\\n # Skip folders that start with _.\\n if any([part.startswith('_')\\n for part in subdir.split(os.path.sep)]):\\n continue\\n _, rel_dir = subdir.split(path)\\n rel_dir = rel_dir.lstrip(os.path.sep)\\n for filename in files:\\n if is_valid_module(filename):\\n mod_name, _ = os.path.splitext(filename)\\n rel_path = os.path.join(rel_dir, mod_name)\\n if base_package is not None:\\n rel_path = os.path.join(base_package, rel_path)\\n # Turn into a Python module rather than a file path.\\n result.append(rel_path.replace(os.path.sep, '.'))\\n\\n return result\",\n \"def _get_submodules():\\n import sh\\n git = sh.git.bake(_tty_out=False)\\n submodules = git.submodule().strip().split(\\\"\\\\n\\\")\\n return [\\n line.strip()[1:].split()[1]\\n for line in submodules\\n ]\",\n \"def get_directories():\\n # get current working dir\\n directory = os.getcwd()\\n # list of dir to look in repo for files\\n directories = [\\n directory,\\n os.path.expanduser(os.path.join(directory, 'src')),\\n os.path.expanduser(os.path.join(directory, 'tests'))\\n ]\\n return directories\",\n \"def _get_package_data() -> list[list[str]]:\\n moddata = []\\n modlist: tuple[str, ...] = (\\n \\\"click\\\",\\n \\\"cryptography\\\",\\n \\\"globus_cli\\\",\\n \\\"globus_sdk\\\",\\n \\\"jmespath\\\",\\n \\\"requests\\\",\\n )\\n if verbosity() < 2:\\n modlist = (\\\"globus_cli\\\", \\\"globus_sdk\\\", \\\"requests\\\")\\n\\n for mod in modlist:\\n cur = [mod]\\n try:\\n loaded_mod = __import__(mod)\\n except ImportError:\\n loaded_mod = None\\n\\n for attr in (\\\"__version__\\\", \\\"__file__\\\", \\\"__path__\\\"):\\n # if loading failed, be sure to pad with error messages\\n if loaded_mod is None:\\n cur.append(\\\"[import failed]\\\")\\n continue\\n\\n try:\\n attrval = getattr(loaded_mod, attr)\\n except AttributeError:\\n attrval = \\\"\\\"\\n cur.append(attrval)\\n moddata.append(cur)\\n\\n return moddata\",\n \"def get_library_content(self):\\n from glob import glob\\n try:\\n os.path.isdir(self.source)\\n lst = glob(self.source + '/*')\\n except TypeError:\\n lst = self.source\\n dircheck = True\\n while dircheck is True:\\n dircheck = False\\n newlst = []\\n for entry in lst:\\n if os.path.isdir(entry):\\n newlst.extend(glob(entry + '/*'))\\n dircheck = True\\n else:\\n newlst.append(entry)\\n lst = newlst\\n return lst\",\n \"def package_dir(self):\\r\\n return \\\".\\\"\",\n \"def packages():\",\n \"def finddirs(root):\\n retval = []\\n for root, dirs, files in os.walk(root):\\n for d in dirs:\\n retval.append(os.path.join(root, d))\\n return retval\",\n \"def getModules() -> tuple:\\n return data.getFoldersOf(data.ETC)\",\n \"def get_package_data_files(package, data, package_dir=None):\\n if package_dir is None:\\n package_dir = os.path.join(*package.split('.'))\\n all_files = []\\n for f in data:\\n path = os.path.join(package_dir, f)\\n if os.path.isfile(path):\\n all_files.append(f)\\n continue\\n for root, _dirs, files in os.walk(path, followlinks=True):\\n root = os.path.relpath(root, package_dir)\\n for file in files:\\n file = os.path.join(root, file)\\n if file not in all_files:\\n all_files.append(file)\\n return all_files\",\n \"def walkdirs(root):\\r\\n scriptype_paths = collections.defaultdict(set)\\r\\n for root, subdirs, files in os.walk(root):\\r\\n\\r\\n # Filter subdirs\\r\\n tmpdir = []\\r\\n for i in subdirs:\\r\\n if i.startswith(EXCLUDE_PATTERNS):\\r\\n continue\\r\\n if '__init__.py' in os.listdir(os.path.join(root, i)):\\r\\n scriptype_paths['python'].add(root)\\r\\n continue\\r\\n tmpdir.append(i)\\r\\n subdirs[:] = tmpdir\\r\\n\\r\\n # If files with extension exists add to right source type.\\r\\n if ext_exists('.py', files):\\r\\n scriptype_paths['python'].add(root)\\r\\n if ext_exists('.mel', files):\\r\\n scriptype_paths['mel'].add(root)\\r\\n return scriptype_paths\",\n \"def _get_package_dir ( self, pkg_name ):\\n if not pkg_name in self._subdirs:\\n self._lock.acquire()\\n try:\\n if not pkg_name in self._subdirs:\\n newpkg = self.packagedir_cls (\\n name = pkg_name,\\n logger = self.logger,\\n directory = self.physical_location + os.sep + pkg_name,\\n get_header = self.get_header,\\n runtime_incremental = self.runtime_incremental,\\n parent = self\\n )\\n self._subdirs [pkg_name] = newpkg\\n finally:\\n self._lock.release()\\n\\n return self._subdirs [pkg_name]\",\n \"def get_subdirs(dir_path: str) -> list:\\n res = list(x.name for x in os.scandir(dir_path) if x.is_dir())\\n return res\",\n \"def get_docs(root='assets/doc', depth=2):\\n if depth == 0:\\n return listdir(root)\\n a = dict()\\n for c in filter(lambda d: isdir(join(root, d)) and not d.startswith('.'), listdir(root)):\\n a[c] = get_docs(join(root, c), depth-1)\\n return a\",\n \"def packages_in_folder(path):\\n for pkg_path in catkin_pkg.packages.find_package_paths(path):\\n yield os.path.join(path, pkg_path)\",\n \"def get_directories_recursive(self, path) :\\n\\n if path.is_dir() :\\n yield path\\n for child in path.iterdir():\\n yield from self.get_directories_recursive(child)\\n elif path.is_file() :\\n yield path\",\n \"def collect_subdirs(path_to_walk):\\n root, subdirs, _ = next(os.walk(path_to_walk))\\n\\n return [os.path.join(root, d) for d in subdirs]\",\n \"def get_templates_dirs(self):\\n\\t\\tfrom pkg_resources import resource_filename\\n\\t\\treturn [resource_filename(__name__, 'templates')]\",\n \"def find_modules(x):\\n return Path(x).rglob('*.py')\",\n \"def pkgDirIter(self):\\r\\n return self._pkgDir.__iter__()\",\n \"def get_package_folders(which_folder: str = \\\"root\\\") -> Path:\\n logg = logging.getLogger(f\\\"c.{__name__}.get_package_folders\\\")\\n # logg.setLevel(\\\"INFO\\\")\\n logg.debug(\\\"Start get_package_folders\\\")\\n\\n this_file_folder = Path(__file__).absolute().parent\\n logg.debug(f\\\"{this_file_folder=}\\\")\\n\\n package_root_folder = this_file_folder.parent.parent.parent\\n\\n if which_folder == \\\"root\\\":\\n return package_root_folder\\n\\n elif which_folder == \\\"tests\\\":\\n tests_folder = package_root_folder / \\\"tests\\\"\\n return tests_folder\\n\\n elif which_folder == \\\"template_epub\\\":\\n template_epub_folder = package_root_folder / \\\"assets\\\" / \\\"template_epub\\\"\\n return template_epub_folder\\n\\n elif which_folder == \\\"word_pairs\\\":\\n word_pairs_folder = package_root_folder / \\\"assets\\\" / \\\"word_pairs\\\"\\n return word_pairs_folder\\n\\n elif which_folder == \\\"common_words\\\":\\n common_words_folder = package_root_folder / \\\"assets\\\" / \\\"common_words\\\"\\n return common_words_folder\\n\\n else:\\n raise KeyError(f\\\"Not recognized {which_folder}\\\")\",\n \"def walk_recursive(root, pattern='*.py'):\\r\\n for root, dirnames, filenames in os.walk(root):\\r\\n for filename in fnmatch.filter(filenames, pattern):\\r\\n yield os.path.join(root, filename)\",\n \"def get_subdirs(src_dir):\\n img_dirs = sorted(next(os.walk(src_dir))[1])\\n subdirs = [src_dir + img_dir for img_dir in img_dirs]\\n return subdirs\",\n \"def get_all_modules(package):\\n base = Path(inspect.getabsfile(package)).parent\\n\\n for fl in base.glob(\\\"*.py\\\"):\\n print(f\\\"loading module {fl}\\\")\\n yield load_module(fl)\",\n \"def _generatePythonPath(self, pkg):\\r\\n if pkg in self._packages:\\r\\n return []\\r\\n\\r\\n # short-circuit if this is a catkin-ized package\\r\\n m = self._rp.get_manifest(pkg)\\r\\n\\r\\n if m.is_catkin:\\r\\n self._packages.add(pkg)\\r\\n return []\\r\\n\\r\\n packages = self._getDepends(pkg)\\r\\n packages.append(pkg)\\r\\n\\r\\n paths = []\\r\\n\\r\\n try:\\r\\n for p in packages:\\r\\n m = self._rp.get_manifest(p)\\r\\n d = self._rp.get_path(p)\\r\\n self._appendPackagePaths(m, paths, d)\\r\\n self._packages.add(p)\\r\\n except:\\r\\n self._packages.discard(pkg)\\r\\n raise\\r\\n\\r\\n return paths\",\n \"def get_ros_package_path(config):\\n code_trees = []\\n for tree_el in reversed(config.get_config_elements()):\\n if not is_path_ros(tree_el.get_path()):\\n if not os.path.isfile(tree_el.get_path()):\\n code_trees.append(tree_el.get_path())\\n return code_trees\",\n \"def get_package_dir():\\n return Path(__file__).parent\",\n \"def walk_dir(path):\\r\\n\\tassets = []\\r\\n\\r\\n\\tfor file in os.listdir(path):\\r\\n\\t\\tif os.path.isdir(path + \\\"/\\\" + file):\\r\\n\\t\\t\\tif not file.startswith(\\\".\\\"):\\r\\n\\t\\t\\t\\t# Ignore . dirs (e.g .svn)\\r\\n\\t\\t\\t\\tassets.extend(walk_dir(path + \\\"/\\\" + file))\\r\\n\\t\\telif file.endswith('.blend'):\\r\\n\\t\\t\\tassets.append(path + \\\"/\\\" + file)\\r\\n\\r\\n\\treturn assets\",\n \"def get_rpaths(pkg):\\n rpaths = [pkg.prefix.lib, pkg.prefix.lib64]\\n deps = get_rpath_deps(pkg)\\n rpaths.extend(d.prefix.lib for d in deps if os.path.isdir(d.prefix.lib))\\n rpaths.extend(d.prefix.lib64 for d in deps if os.path.isdir(d.prefix.lib64))\\n # Second module is our compiler mod name. We use that to get rpaths from\\n # module show output.\\n if pkg.compiler.modules and len(pkg.compiler.modules) > 1:\\n rpaths.append(path_from_modules([pkg.compiler.modules[1]]))\\n return list(dedupe(filter_system_paths(rpaths)))\",\n \"def get_all_paths(dmt, directory_path=''):\\n # Base case.\\n if not dmt.children:\\n return set()\\n \\n filesystem_items = set()\\n for item in dmt.children.keys():\\n filesystem_items.add(directory_path+item)\\n # Also get the paths of subdirectory contents.\\n if item[-1] == '/':\\n subdir_name = item\\n subdir_path = directory_path + subdir_name\\n \\n filesystem_items.add(subdir_path)\\n filesystem_items.update(get_all_paths(dmt.children[subdir_name], subdir_path))\\n \\n return filesystem_items\",\n \"def test_GetFilesInDirectory_subdir_relpath(tempdir: pathlib.Path):\\n # Create files: [ sub/a, sub/sub/b ]\\n (tempdir / \\\"sub\\\").mkdir()\\n (tempdir / \\\"sub\\\" / \\\"a\\\").touch()\\n (tempdir / \\\"sub\\\" / \\\"sub\\\").mkdir()\\n (tempdir / \\\"sub\\\" / \\\"sub\\\" / \\\"b\\\").touch()\\n assert set(dpack.GetFilesInDirectory(tempdir, [])) == {\\n pathlib.Path(\\\"sub/a\\\"),\\n pathlib.Path(\\\"sub/sub/b\\\"),\\n }\",\n \"def get_skins_and_extensions(base_dir):\\n ext_paths = []\\n for subdir in ['extensions', 'skins']:\\n for name in os.listdir(os.path.join(base_dir, subdir)):\\n if os.path.isdir(os.path.join(base_dir, subdir, name)):\\n ext_paths.append(os.path.join(subdir, name))\\n return ext_paths\",\n \"def relative_to_buildroot(self):\\n return [os.path.join(self.rel_path, source) for source in self.source_paths]\",\n \"def files(self) -> Generator[Path, None, None]:\\n return Path(self.package).resolve(strict=True).glob(self.glob)\",\n \"def __dir__(self):\\n result = list(new_module.__all__)\\n result.extend(('__file__', '__path__', '__doc__', '__all__',\\n '__docformat__', '__name__', '__path__',\\n '__package__', '__version__'))\\n return result\",\n \"def get_paths():\\n\\n # Get repo name\\n git_repo = git.Repo(__file__, search_parent_directories=True)\\n repo = git_repo.git.rev_parse(\\\"--show-toplevel\\\")\\n\\n paths = {\\\"repo\\\": repo, \\\"base\\\":{}, \\\"src\\\":{}, \\\"data\\\":{}, \\\"app\\\":{}}\\n\\n for base_dir in [\\\"data\\\", \\\"notebooks\\\", \\\"src\\\", \\\"model\\\", \\\"logs\\\", \\\"app\\\"]:\\n\\n paths[\\\"base\\\"][base_dir] = os.path.join(repo, base_dir)\\n test = paths[\\\"base\\\"][base_dir].split(base_dir)[-1]\\n assert len(test) == 0\\n\\n for src_dir in [\\\"conf\\\", \\\"data\\\", \\\"notebooks\\\", \\\"tests\\\", \\\"utils\\\",\\n \\\"visualize\\\", \\\"conf\\\", \\\"model\\\"]:\\n\\n src_base_dir = paths.get(\\\"base\\\").get(\\\"src\\\")\\n paths[\\\"src\\\"][src_dir] = os.path.join(src_base_dir, src_dir)\\n test = paths[\\\"src\\\"][src_dir].split(src_dir)[-1]\\n assert len(test) == 0\\n\\n for data_dir in [\\\"raw\\\", \\\"interim\\\", \\\"processed\\\"]:\\n\\n data_base_dir = paths.get(\\\"base\\\").get(\\\"data\\\")\\n paths[\\\"data\\\"][data_dir] = os.path.join(data_base_dir, data_dir)\\n test = paths[\\\"data\\\"][data_dir].split(data_dir)[-1]\\n assert len(test) == 0\\n\\n for app_dir in [\\\"templates\\\", \\\"static\\\"]:\\n app_base_dir = paths.get(\\\"base\\\").get(\\\"app\\\")\\n paths[\\\"app\\\"][app_dir] = os.path.join(app_base_dir, app_dir)\\n\\n return paths\",\n \"def subdirs(dir):\\n return [dir + '/' + name for name in os.listdir(dir)\\n if os.path.isdir(os.path.join(dir, name))]\",\n \"def get_builder_root_dirs(self, name: naming.DatasetName) -> List[epath.Path]:\\n return [d / name.name for d in self._ns2data_dir[name.namespace]]\",\n \"def get_content_directories() -> List[str]:\\n result:list[str] = []\\n for current_path in os.listdir(\\\"content\\\"):\\n if os.path.isdir(os.path.join(\\\"content\\\", current_path)):\\n result.append(os.path.join(\\\"content\\\", current_path))\\n return result\",\n \"def dcs_modules():\\n\\n dcs_dirname = os.path.dirname(__file__)\\n module_prefix = __package__ + '.'\\n\\n if getattr(sys, 'frozen', False):\\n importer = pkgutil.get_importer(dcs_dirname)\\n return [module for module in list(importer.toc) if module.startswith(module_prefix) and module.count('.') == 2]\\n else:\\n return [module_prefix + name for _, name, is_pkg in pkgutil.iter_modules([dcs_dirname]) if not is_pkg]\",\n \"def get_templates_dirs(self):\\n from pkg_resources import resource_filename\\n return [resource_filename(__name__, 'templates')]\",\n \"def GetPackageDirectory():\\n return os.path.dirname(__file__)\",\n \"def scan ( self, **kw ):\\n stats = self.STATS\\n stats.scan_time.begin ( self.name )\\n for subdir in os.listdir ( self.physical_location ):\\n if self.has_dir ( subdir ):\\n pkgdir = self._get_package_dir ( subdir )\\n try:\\n pkgdir.scan ( stats=stats, **kw )\\n finally:\\n if pkgdir.empty():\\n del self._subdirs [subdir]\\n\\n stats.scan_time.end ( self.name )\",\n \"def collect_children(self, recursive=True):\\n self.children = []\\n\\n for fname in os.listdir(self.path):\\n path = join(self.path, fname)\\n\\n if Package.is_pkg(path):\\n child = Package.create(path, owner=self)\\n if recursive:\\n child.collect_children()\\n\\n elif Module.is_module(path):\\n child = Module.create(path, owner=self)\\n\\n else:\\n if util.get_verbosity_level() > 0:\\n print(\\\"Skipping: {}\\\".format(path))\\n continue\\n\\n self.children.append(child)\",\n \"def find_bundles_dirs(charm_dir: Path) -> List[Path]:\\n paths = (('tests', 'bundles'),\\n ('tests', 'bundles', 'overlays'),\\n ('src', 'tests', 'bundles'),\\n ('src', 'tests', 'bundles', 'overlays'))\\n\\n found_list: List[Path] = []\\n for path in paths:\\n logging.debug(\\\"Searching: %s\\\", path)\\n dir_ = charm_dir.joinpath(*path)\\n if dir_.is_dir():\\n found_list.append(dir_)\\n return found_list\",\n \"def __gitSubmodulesList(self):\\n self.vcs.gitSubmoduleList(self.project.getProjectPath())\",\n \"def expand_package(self, pkg):\\n return [(pkg, c) for c in self.packages[pkg].components]\",\n \"def _find_files(root_dir, should_include):\\n paths = [] # Return value.\\n\\n is_module = lambda path: path.endswith(\\\".py\\\")\\n\\n # os.walk() is new in Python 2.3\\n # http://docs.python.org/library/os.html#os.walk\\n for dir_path, dir_names, file_names in os.walk(root_dir):\\n new_paths = [os.path.join(dir_path, file_name) for file_name in file_names]\\n new_paths = filter(is_module, new_paths)\\n new_paths = filter(should_include, new_paths)\\n paths.extend(new_paths)\\n\\n return paths\",\n \"def lib_dirs(self):\\r\\n ret = []\\r\\n for x in [y.type for y in self.variables] + [\\r\\n y.op for y in self.node_order]:\\r\\n try:\\r\\n ret += x.c_lib_dirs()\\r\\n except utils.MethodNotDefined:\\r\\n pass\\r\\n return utils.uniq(ret)\",\n \"def list_dir(self, path):\",\n \"def moduleList(path):\\n\\n if os.path.isdir(path):\\n folder_list = os.listdir(path)\\n elif path.endswith('.egg'):\\n try:\\n folder_list = [f for f in zipimporter(path)._files]\\n except:\\n folder_list = []\\n else:\\n folder_list = []\\n #folder_list = glob.glob(os.path.join(path,'*'))\\n folder_list = [p for p in folder_list \\\\\\n if os.path.exists(os.path.join(path, p,'__init__.py'))\\\\\\n or p[-3:] in ('.py','.so')\\\\\\n or p[-4:] in ('.pyc','.pyo','.pyd')]\\n\\n folder_list = [os.path.basename(p).split('.')[0] for p in folder_list]\\n return folder_list\",\n \"def get_files(self, include=[], exclude=[]):\\r\\n for (basepath, dpaths, fpaths) in os.walk(self.path, topdown=True):\\r\\n for subpath in dpaths + fpaths:\\r\\n path = os.path.join(self.chroot_path(basepath), subpath)\\r\\n if filter_path(path, include, exclude):\\r\\n yield path\",\n \"def _load_dirs(self):\\n rootdirs = self._docset.get_compounds(xml.Directory,\\n lambda x: x.get_parent() is None)\\n for dirdoc in rootdirs:\\n self._load_dir(dirdoc, None)\",\n \"def syspaths(self):\\n res = []\\n for path, jsmodule in self.jsmodules.items():\\n if jsmodule.js_lib_path != \\\"\\\":\\n js_lib_path = os.path.dirname(jsmodule.js_lib_path.rstrip(\\\"/\\\")) # get parent\\n if not js_lib_path in res:\\n res.append(js_lib_path)\\n return res\",\n \"def packages(self):\\n return []\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7408176","0.6981932","0.6977739","0.69128346","0.6908319","0.6908319","0.6908319","0.68290293","0.67712396","0.6679647","0.6656998","0.6650802","0.66113985","0.65714127","0.65617687","0.6516385","0.65129155","0.65035087","0.6490898","0.64712936","0.64288765","0.6416123","0.64095396","0.6363771","0.636016","0.63492495","0.63337755","0.62812275","0.62618953","0.6232489","0.62197155","0.61479115","0.61385083","0.6138176","0.6126316","0.60808873","0.6032194","0.6025633","0.6022958","0.5993285","0.5967705","0.5967526","0.5957678","0.5941756","0.5934362","0.5928338","0.5926894","0.5920121","0.5917942","0.59168524","0.5915929","0.59048176","0.59001803","0.58885604","0.58843124","0.5877461","0.58685863","0.5851674","0.5851419","0.5849275","0.5841377","0.58165497","0.58150256","0.5792629","0.579119","0.5790333","0.57875717","0.57844734","0.5766239","0.57562","0.5753864","0.5745637","0.57220125","0.57209474","0.5701232","0.56961054","0.56916827","0.56894416","0.5688801","0.5685014","0.56822985","0.5676862","0.5662607","0.566202","0.566168","0.56574637","0.5654674","0.56433386","0.5642581","0.56418425","0.56415075","0.5641448","0.5635038","0.5629967","0.5629508","0.56271726","0.56271243","0.5615234","0.5611381","0.5608411"],"string":"[\n \"0.7408176\",\n \"0.6981932\",\n \"0.6977739\",\n \"0.69128346\",\n \"0.6908319\",\n \"0.6908319\",\n \"0.6908319\",\n \"0.68290293\",\n \"0.67712396\",\n \"0.6679647\",\n \"0.6656998\",\n \"0.6650802\",\n \"0.66113985\",\n \"0.65714127\",\n \"0.65617687\",\n \"0.6516385\",\n \"0.65129155\",\n \"0.65035087\",\n \"0.6490898\",\n \"0.64712936\",\n \"0.64288765\",\n \"0.6416123\",\n \"0.64095396\",\n \"0.6363771\",\n \"0.636016\",\n \"0.63492495\",\n \"0.63337755\",\n \"0.62812275\",\n \"0.62618953\",\n \"0.6232489\",\n \"0.62197155\",\n \"0.61479115\",\n \"0.61385083\",\n \"0.6138176\",\n \"0.6126316\",\n \"0.60808873\",\n \"0.6032194\",\n \"0.6025633\",\n \"0.6022958\",\n \"0.5993285\",\n \"0.5967705\",\n \"0.5967526\",\n \"0.5957678\",\n \"0.5941756\",\n \"0.5934362\",\n \"0.5928338\",\n \"0.5926894\",\n \"0.5920121\",\n \"0.5917942\",\n \"0.59168524\",\n \"0.5915929\",\n \"0.59048176\",\n \"0.59001803\",\n \"0.58885604\",\n \"0.58843124\",\n \"0.5877461\",\n \"0.58685863\",\n \"0.5851674\",\n \"0.5851419\",\n \"0.5849275\",\n \"0.5841377\",\n \"0.58165497\",\n \"0.58150256\",\n \"0.5792629\",\n \"0.579119\",\n \"0.5790333\",\n \"0.57875717\",\n \"0.57844734\",\n \"0.5766239\",\n \"0.57562\",\n \"0.5753864\",\n \"0.5745637\",\n \"0.57220125\",\n \"0.57209474\",\n \"0.5701232\",\n \"0.56961054\",\n \"0.56916827\",\n \"0.56894416\",\n \"0.5688801\",\n \"0.5685014\",\n \"0.56822985\",\n \"0.5676862\",\n \"0.5662607\",\n \"0.566202\",\n \"0.566168\",\n \"0.56574637\",\n \"0.5654674\",\n \"0.56433386\",\n \"0.5642581\",\n \"0.56418425\",\n \"0.56415075\",\n \"0.5641448\",\n \"0.5635038\",\n \"0.5629967\",\n \"0.5629508\",\n \"0.56271726\",\n \"0.56271243\",\n \"0.5615234\",\n \"0.5611381\",\n \"0.5608411\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7587221"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88565,"cells":{"query":{"kind":"string","value":"Find all files in a subdirectory and return paths relative to dir This is similar to (and uses) setuptools.findall However, the paths returned are in the form needed for package_data"},"document":{"kind":"string","value":"def subdir_findall(dir, subdir):\n strip_n = len(dir.split('/'))\n path = '/'.join((dir, subdir))\n return ['/'.join(s.split('/')[strip_n:]) for s in setuptools.findall(path)]"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _find_files_to_package(self, path):\n for root, dirs, files in os.walk(path):\n root_parts = pathlib.Path(root).relative_to(path).parts\n if self._include_directory(root_parts):\n for f in files:\n if self._include_file(root_parts, f):\n yield pathlib.Path(root, f)","def files_in_dir(root_dir):\n file_set = set()\n\n for dir_, _, files in os.walk(root_dir):\n for file_name in files:\n rel_dir = os.path.relpath(dir_, root_dir)\n rel_file = os.path.join(rel_dir, file_name)\n file_set.add(rel_file)\n\n return [Path(PureWindowsPath(f)) for f in file_set]","def find_files(d):\n for root, dirs, files in os.walk(d):\n for f in files:\n yield path.abspath(path.join(root, f))","def findFiles(target, path):\r\n\tfiles = []\r\n\tlyst = os.listdir(path)\r\n\tfor element in lyst:\r\n\t\tif os.path.isfile(element):\r\n\t\t\tif target in element:\r\n\t\t\t\tfiles.append(path + os.sep + element)\r\n\t\telse:\r\n\t\t\tos.chdir(element)\r\n\t\t\tfiles.extend(findFiles(target, os.getcwd()))\r\n\t\t\tos.chdir(\"..\")\r\n\treturn files","def search_dir(d: PosixPath, basepath, files, extension):\n scripts = []\n for path in d.iterdir():\n string_path = str(path).replace(basepath, '')[1:]\n if path.is_dir():\n recu_scripts = search_dir(path, basepath, files, extension)\n if recu_scripts:\n scripts.extend(recu_scripts)\n if string_path in files and path.suffix == extension:\n scripts.extend([string_path])\n return scripts","def _find_files(root_dir, should_include):\n paths = [] # Return value.\n\n is_module = lambda path: path.endswith(\".py\")\n\n # os.walk() is new in Python 2.3\n # http://docs.python.org/library/os.html#os.walk\n for dir_path, dir_names, file_names in os.walk(root_dir):\n new_paths = [os.path.join(dir_path, file_name) for file_name in file_names]\n new_paths = filter(is_module, new_paths)\n new_paths = filter(should_include, new_paths)\n paths.extend(new_paths)\n\n return paths","def find_package_data(package):\n walk = [(dirpath.replace(package + os.sep, '', 1), filenames)\n for dirpath, dirnames, filenames in os.walk(package)]\n\n filepaths = []\n for base, filenames in walk:\n filepaths.extend([os.path.join(base, filename)\n for filename in filenames])\n return filepaths","def test_GetFilesInDirectory_subdir_relpath(tempdir: pathlib.Path):\n # Create files: [ sub/a, sub/sub/b ]\n (tempdir / \"sub\").mkdir()\n (tempdir / \"sub\" / \"a\").touch()\n (tempdir / \"sub\" / \"sub\").mkdir()\n (tempdir / \"sub\" / \"sub\" / \"b\").touch()\n assert set(dpack.GetFilesInDirectory(tempdir, [])) == {\n pathlib.Path(\"sub/a\"),\n pathlib.Path(\"sub/sub/b\"),\n }","def find_package_data(data_root, package_root):\n files = []\n for root, dirnames, filenames in os.walk(data_root):\n for fn in filenames:\n files.append(relpath(join(root, fn), package_root))\n return files","def get_paths(pattern):\n if not in_source_tree:\n pattern = '../' + pattern\n\n files = glob.glob(os.path.normpath(os.path.join(top_dir, pattern)))\n return files","def find_all_files(path):\n for root, dirs, files in os.walk(os.path.join(path)):\n for filename in files:\n yield os.path.join(root, filename)","def _get_all_files(dir_path):\n for root, _, filenames in os.walk(dir_path):\n for name in filenames:\n target = os.path.join(root, name)\n yield target","def locate(root = '.', target = 'info'):\n \n matches = []\n \n for root, dirnames, filenames in os.walk(root):\n for dirnames in fnmatch.filter(dirnames, target):\n matches.append(os.path.join(root, dirnames))\n \n return matches","def all_files_under(path):\r\n for cur_path, dirnames, filenames in os.walk(path):\r\n for filename in filenames:\r\n yield os.path.join(cur_path, filename)","def GetAllFilepaths(root_directory):\n path_list = []\n for dirpath, _, filenames in os.walk(root_directory):\n for filename in filenames:\n path_list.append(os.path.abspath(os.path.join(dirpath, filename)))\n return path_list","def find_data_files_distutils(self, package, src_dir):\n from glob import glob\n import os\n from distutils.util import convert_path\n\n globs = (self.package_data.get('', [])\n + self.package_data.get(package, []))\n files = []\n for pattern in globs:\n # Each pattern has to be converted to a platform-specific path\n filelist = glob(os.path.join(src_dir, convert_path(pattern)))\n # Files that match more than one pattern are only added once\n files.extend([fn for fn in filelist if fn not in files\n and (os.path.isfile(fn) or os.path.islink(fn))])\n return files","def _package_files(directory: str, suffix: str) -> list:\n\n paths = []\n\n for (path, directories, filenames) in os.walk(directory):\n for filename in filenames:\n if filename.endswith(suffix):\n paths.append(os.path.join('..', path, filename))\n\n return paths","def getImmediateSubdirectories(dir):","def get_files(self, include=[], exclude=[]):\r\n for (basepath, dpaths, fpaths) in os.walk(self.path, topdown=True):\r\n for subpath in dpaths + fpaths:\r\n path = os.path.join(self.chroot_path(basepath), subpath)\r\n if filter_path(path, include, exclude):\r\n yield path","def findfiles(path, ext=\".pyc\"):\n results = []\n regex = re.compile(re.escape(ext)+\"$\", re.I)\n\n tree = os.walk(path)\n for d in tree:\n # Each element of a walker represents a directory and its contents.\n # Diagnostic, if you wish.\n #print(d)\n if d[2]:\n # Are there files in this directory?\n for f in d[2]:\n if regex.findall(f):\n relpath = os.path.join(d[0], f)\n results.append(os.path.realpath(relpath))\n\n return results","def getFiles(searchDir = './', extension = 'source'):\n from glob import glob \n\n return glob(searchDir+'/*.'+extension)","def _recursive_file_search(self, path, pattern):\n matches = []\n for root, dirnames, filenames in os.walk(path):\n for filename in fnmatch.filter(filenames, pattern):\n matches.append(os.path.join(root, filename))\n\n return matches","def getFilePaths(directory):\r\n\tfor folder, subs, files in os.walk(directory):\r\n\t\tfor filename in files:\r\n\t\t\tyield os.path.join(folder, filename)","def get_files_in_directory(dir_name: str):\n filenames = []\n\n for entry in walk(dir_name):\n root_dir = entry[0]\n dir_files = entry[2]\n filenames.extend([Path(root_dir).joinpath(file) for file in dir_files])\n\n return filenames","def finddirs(root):\n retval = []\n for root, dirs, files in os.walk(root):\n for d in dirs:\n retval.append(os.path.join(root, d))\n return retval","def get_all_files(cwd):\n return os.listdir(cwd)","def _get_files(self):\n # pylint: disable=unused-variable\n for dirpath, __, filenames in os.walk(self.start_location):\n for file_ in filenames:\n if file_.endswith('.py'):\n yield \"{0}{1}\".format(dirpath, file_)","def walk_recursive(root, pattern='*.py'):\r\n for root, dirnames, filenames in os.walk(root):\r\n for filename in fnmatch.filter(filenames, pattern):\r\n yield os.path.join(root, filename)","def _findFiles(self, topLevelDirectory, extension=\".py\", foundFiles=None):\n \n #mutable default arguments in Python are evaluated once when the function is defined, not each time the function is called.\n if foundFiles == None:\n foundFiles = []\n \n for dirpath, dirnames, filenames in os.walk(topLevelDirectory):\n for filename in filenames:\n #need to verify that the entity is a file (this avoids problems when directory names have file extensions)\n if filename[-len(extension):] == extension and filename[0:1] != '.' and os.path.isfile(dirpath+\"/\"+filename):\n foundFiles.append(dirpath+\"/\"+filename)\n #print dirpath+\"/\"+filename\n return foundFiles","def locate(pattern, root=os.curdir):\n for path, dirs, files in os.walk(os.path.abspath(root)):\n for filename in fnmatch.filter(files, pattern):\n yield os.path.join(path, filename)","def get_filepaths(directory):\n file_paths = []\n for root, directories, files in os.walk(directory):\n for filename in files:\n file_path = os.path.join(root, filename)\n file_paths.append(file_path)\n return file_paths","def _RecursiveDirectoryListing(dirpath):\n result = []\n for root, _, files in os.walk(dirpath):\n for f in files:\n result.append(os.path.relpath(os.path.join(root, f), dirpath))\n return result","def get_package_files(_dir):\n _files = []\n for root, _, files in os.walk(_dir):\n if('git' in root or '/tests' in root):\n continue\n for _name in files:\n _files.append((root, _name))\n return _files","def find_all_files(self):\n look4files = [ f for f in listdir(self.file_location) if isfile(join(self.file_location,f)) ]\n return look4files","def _get_filepaths(directory):\n file_paths = [] # List which will store all of the full filepaths.\n\n # Walk the tree.\n for root, directories, files in os.walk(directory):\n for filename in files:\n # Join the two strings in order to form the full filepath.\n filepath = os.path.join(root, filename)\n file_paths.append(filepath) # Add it to the list.\n\n return file_paths # Self-explanatory.","def get_files_in_dir(path):\n return [os.path.join(dir_name, file)\n for dir_name, subdirs, files in os.walk(path)\n for file in files]","def gather_files(path_specs, file_name_pattern, recursively=False):\n files = []\n for path_spec in path_specs:\n if os.path.isdir(path_spec):\n files.extend(IOUtils.find_files(path_spec, file_name_pattern, recursively))\n elif os.path.isfile(path_spec):\n files.append(path_spec)\n return files","def find_files(root, directory, filename):\n\n path_list = []\n walker = os.walk(root, followlinks=True)\n for root, dirs, files in walker:\n remove_vcs_dirs(dirs)\n\n #if dirs containt 'directory', don't walk others\n if directory in dirs: dirs[:] = [directory]\n\n if root.endswith(os.path.sep + directory):\n if filename in files:\n path_list.append(os.path.join(root, filename))\n dirs[:] = []\n\n return path_list","def get_filepaths(directory):\n file_paths = [] # List which will store all of the full filepaths.\n\n # Walk the tree.\n for root, directories, files in os.walk(directory):\n for filename in files:\n # Join the two strings in order to form the full filepath.\n if filename == \".DS_Store\":\n pass\n else:\n filepath = os.path.join(root, filename)\n file_paths.append(filepath) # Add it to the list.\n\n return file_paths","def GetFilesInDirectory(dir_path):\n\treturn [f for f in os.listdir(dir_path) if os.path.isfile(os.path.join(dir_path,f))]","def find_subdirectories(package):\n try:\n subdirectories = next(os.walk(package_to_path(package)))[1]\n except StopIteration:\n subdirectories = []\n return subdirectories","def matching_paths(dirpath, exts=None, recursive=True, relative=True):\n if recursive:\n for root, dirnames, filenames in os.walk(dirpath):\n for fname in filenames:\n if exts:\n for ext in exts:\n if fname.endswith(ext) and not fname.startswith(\".\"):\n if relative:\n yield os.path.relpath(\n os.path.join(root, fname), dirpath\n )\n else:\n yield os.path.join(root, fname)\n break\n else:\n if not fname.startswith(\".\"):\n if relative:\n yield os.path.relpath(os.path.join(root, fname), dirpath)\n else:\n yield os.path.join(root, fname)\n else:\n for fname in os.listdir(dirpath):\n full = os.path.join(dirpath, fname)\n if not os.path.isfile(full) or fname.startswith(\".\"):\n pass\n elif exts:\n for ext in exts:\n if fname.endswith(ext):\n if relative:\n yield os.path.relpath(full, dirpath)\n else:\n yield full\n break\n else:\n if relative:\n yield os.path.relpath(full, dirpath)\n else:\n yield full","def get_dir_recursive(path: str) -> List[str]:\n files = []\n for dir_entry in os.scandir(path):\n if dir_entry.is_dir(follow_symlinks=True):\n files.extend(get_dir_recursive(dir_entry))\n else:\n files.append(dir_entry.path)\n return files","def inferred_settings_files(self) -> List[Path]:\n prefix = self.env_parser.prefix.strip(self.env_parser.split_char).lower()\n base_pattern = f\"*{prefix}*settings\"\n extensions = [\n ext\n for loader in FileLoader.registered_loaders\n for ext in loader.valid_file_extensions\n ]\n\n def find_settings_files(path: Path, glob_pattern: str, recursive=False):\n glob = path.rglob if recursive else path.glob\n filepaths = []\n for ext in extensions:\n for filepath in glob(f\"{glob_pattern}{ext}\"):\n if filepath.is_file():\n filepaths.append(filepath)\n return sorted(filepaths)\n\n # Find all directories between current directory and project root\n search_directories: List[Path] = []\n project_root_candidates = [\n \".git\",\n \".hg\",\n \"setup.py\",\n \"requirements.txt\",\n \"environment.yml\",\n \"environment.yaml\",\n \"pyproject.toml\",\n ]\n current_path: Path = Path(\".\")\n while True:\n search_directories.append(current_path)\n new_current_path = current_path / \"..\"\n if (\n any(\n (current_path / candidate).exists()\n for candidate in project_root_candidates\n )\n or not new_current_path.is_dir()\n or new_current_path.resolve() == current_path.resolve()\n ):\n break\n current_path = new_current_path\n\n # Iterate over all directories and find files\n filepaths: List[Path] = []\n for directory in reversed(search_directories):\n filepaths.extend(find_settings_files(directory, base_pattern))\n for sub_dir in directory.glob(base_pattern):\n if not sub_dir.is_dir():\n continue\n # Use all files with valid file extensions if already in settings directory.\n filepaths.extend(find_settings_files(sub_dir, \"*\", recursive=True))\n\n return filepaths","def _get_files(self, path):\n result = []\n for f in os.listdir(path):\n if os.path.isdir(os.path.join(path, f)):\n result += self._get_files(os.path.join(path, f))\n else:\n result.append(os.path.join(path, f))\n return result","def read_filepaths(self, directory):\n folder_paths = [os.path.join(directory, folder) for folder in os.listdir(directory) if not folder.startswith('.')]\n filepaths = [[os.path.join(cur_folder, cur_file) for cur_file in os.listdir(cur_folder)] for cur_folder in folder_paths]\n return filepaths","def get_filepaths(directory):\n file_paths = [] # List which will store all of the full filepaths.\n\n # Walk the tree.\n for root, directories, files in os.walk(directory):\n for filename in files:\n # Join the two strings in order to form the full filepath.\n filepath = os.path.join(root, filename)\n file_paths.append(filepath) # Add it to the list.\n return file_paths","def _files_in_subdir(self, subdir, pattern, regex):\n all_files = glob(join(subdir, (pattern or '**')), recursive=True)\n all_files = [fp for fp in all_files if isfile(fp)]\n\n if pattern and regex:\n raise ValueError(\"Specify pattern OR regex, not both!\")\n elif pattern:\n files = [fn for fn in glob(join(subdir, pattern), recursive=True)]\n elif regex:\n files = [fn for fn in all_files if re.search(regex, fn)]\n else:\n files = all_files\n\n return sorted(files)","def find_data_files_setuptools(self, package, src_dir):\n from glob import glob\n import itertools\n import os\n\n patterns = self._get_platform_patterns(\n self.package_data,\n package,\n src_dir,\n )\n globs_expanded = map(glob, patterns)\n # flatten the expanded globs into an iterable of matches\n globs_matches = itertools.chain.from_iterable(globs_expanded)\n glob_files = [e for e in globs_matches if os.path.isfile(e) or os.path.islink(e)]\n files = itertools.chain(\n self.manifest_files.get(package, []),\n glob_files,\n )\n return self.exclude_data_files(package, src_dir, files)","def get_files_from_dir(dir_name):\n return [path.join(dir_name, f) for f in listdir(dir_name) if path.isfile(path.join(dir_name, f))]","def find_files(base_path,pattern):\n res=()\n print_verbose(2,\"\\t> Recursive search: Base path = %s, pattern = %s\" %(base_path,pattern))\n for root, dirs, files in os.walk(base_path, topdown=True):\n for f_name in fnmatch.filter(files, pattern):\n res= res + (os.path.join(root, f_name),)\n return res;","def get_filepaths(directory):\n file_paths = [] # List which will store all of the full filepaths.\n\n # Walk the tree.\n for root, directories, files in os.walk(directory):\n for filename in files:\n # Join the two strings in order to form the full filepath.\n filepath = os.path.join(root, filename)\n file_paths.append(filepath) # Add it to the list.\n\n return file_paths","def get_all_paths(dmt, directory_path=''):\n # Base case.\n if not dmt.children:\n return set()\n \n filesystem_items = set()\n for item in dmt.children.keys():\n filesystem_items.add(directory_path+item)\n # Also get the paths of subdirectory contents.\n if item[-1] == '/':\n subdir_name = item\n subdir_path = directory_path + subdir_name\n \n filesystem_items.add(subdir_path)\n filesystem_items.update(get_all_paths(dmt.children[subdir_name], subdir_path))\n \n return filesystem_items","def files_in_folder(folder):\n files = []\n for f in glob.glob(folder):\n if os.path.isdir(f):\n files.extend(files_in_folder(f + os.sep + \"**\"))\n else:\n files.append(f)\n return files","def get_filepaths(directory):\r\n file_paths = [] # List which will store all of the full filepaths.\r\n\r\n # Walk the tree.\r\n for root, directories, files in os.walk(directory):\r\n for filename in files:\r\n # Join the two strings in order to form the full filepath.\r\n filepath = os.path.join(root, filename)\r\n file_paths.append(filepath) # Add it to the list.\r\n\r\n return file_paths # Self-explanatory.\r","def get_all_img_paths(path_to_folder):\n all_subfolders = glob.glob(path_to_folder + '*')\n all_paths = []\n for folder in all_subfolders:\n all_paths.extend(glob.glob(folder + '/*'))\n # get relative paths\n common_prefix = path_to_folder\n relative_paths = [os.path.relpath(path, common_prefix) for path in all_paths]\n return relative_paths","def recursive_glob(rootdir=\".\", suffix=\"\"):\n image_paths = []\n for looproot, _, filenames in os.walk(rootdir):\n for filename in filenames:\n if filename.endswith(suffix):\n image_paths.append(os.path.join(looproot, filename))\n return image_paths","def recursive_glob(rootdir=\".\", suffix=\"\"):\n image_paths = []\n for looproot, _, filenames in os.walk(rootdir):\n for filename in filenames:\n if filename.endswith(suffix):\n image_paths.append(os.path.join(looproot, filename))\n return image_paths","def get_files_in_dir(dir: str):\n\n file_list = [f\"{dir}/{file}\" for file in listdir(dir) if isfile(join(dir, file))]\n\n return file_list","def get_filepaths(directory):\n file_paths = [] # List which will store all of the full filepaths.\n\n # Walk the tree.\n for root, directories, files in os.walk(directory):\n for filename in files:\n # Join the two strings in order to form the full filepath.\n filepath = os.path.join(root, filename)\n file_paths.append(filepath) # Add it to the list.\n\n return file_paths # Self-explanatory.","def get_filepaths(directory):\n file_paths = [] # List which will store all of the full filepaths.\n\n # Walk the tree.\n for root, directories, files in os.walk(directory):\n for filename in files:\n # Join the two strings in order to form the full filepath.\n filepath = os.path.join(root, filename)\n file_paths.append(filepath) # Add it to the list.\n\n return file_paths # Self-explanatory.","def get_filepaths(directory):\n file_paths = [] # List which will store all of the full filepaths.\n\n # Walk the tree.\n for root, directories, files in os.walk(directory):\n for filename in files:\n # Join the two strings in order to form the full filepath.\n filepath = os.path.join(root, filename)\n file_paths.append(filepath) # Add it to the list.\n\n return file_paths # Self-explanatory.","def LocateFiles(pattern, root=os.curdir):\n for path, _, files in os.walk(os.path.abspath(root)):\n for filename in fnmatch.filter(files, pattern):\n yield os.path.join(path, filename)","def get_filepaths(directory):\n file_paths = [] # List which will store all of the full filepaths.\n\n # Walk the tree.\n for root, directories, files in os.walk(directory):\n root = os.path.normpath(root)\n directories.sort()\n files.sort()\n for filename in files:\n # Join the two strings in order to form the full filepath.\n if not root.startswith('_') and not root.startswith('.') and filename.endswith(\".md\"):\n filepath = os.path.normpath(os.path.join(root, filename))\n file_paths.append(filepath) # Add it to the list.\n\n return file_paths # Self-explanatory.","def get_all_files(self):\n\t\tfiles_list = []\n\t\tfor path, subdirs, files in os.walk(self.root):\n\t\t for name in files:\n\t\t \tfiles_list.append(os.path.join(self.root, name))\n\t\treturn files_list[0:-1]","def walk_directory(self, path):\n files = []\n for dirpath, dirnames, filenames in os.walk(path):\n for filename in filenames:\n files.append(os.path.join(dirpath, filename))\n return files","def find(directory, slash='/', pattern=r'.+\\.out'):\n for directory, subdirectories, files in os.walk(directory):\n for file in files:\n if re.findall(pattern, str(file)):\n yield str(directory + slash + file)","def relative_to_buildroot(self):\n return [os.path.join(self.rel_path, source) for source in self.source_paths]","def get_paths(file_path):\n return glob(path.join(file_path, '*'))","def get_files_from_directory(path):\n return [f for f in listdir(path) if isfile(join(path, f))]","def recursive_glob(self, rootdir='.', suffix=''):\n return [os.path.join(rootdir, filename)\n for filename in sorted(os.listdir(rootdir)) if filename.endswith(suffix)]","def find(self, path_list):\n import fnmatch\n path_list2 = []\n for pattern in path_list:\n for root, _, filenames in os.walk('.'):\n for filename in fnmatch.filter(filenames, pattern):\n path_list2.append(os.path.join(root, filename))\n return path_list2","def get_files(dir: str) -> List[str]:\n ret = []\n for root, dirs, files in os.walk(dir):\n for name in dirs:\n ret.extend(get_files(os.path.join(root, name)))\n for name in files:\n ret.append(os.path.join(root, name))\n return ret","def _get_dir_entries(dir_name, subdir, *args):\n file_list = []\n for file in os.listdir(dir_name):\n dirfile = os.path.join(dir_name, file)\n if os.path.isfile(dirfile):\n if not args:\n file_list.append(dirfile)\n else:\n if os.path.splitext(dirfile)[1][1:] in args:\n file_list.append(dirfile)\n # recursively access file names in subdirectories\n elif os.path.isdir(dirfile) and subdir:\n file_list.extend(_get_dir_entries(dirfile, subdir, *args))\n return file_list","def find_packages( root ):\n for path, directories, files in os.walk( root ):\n if is_package( path ):\n yield path.replace( '/','.' )","def allfiles(dir, pattern=\"*\"):\n\tdir = uniformpath(dir)\n\tif not os.path.isdir(dir): # must be file\n\t\treturn [dir]\n\tmatching_files = []\n\tfor root, subFolders, files in os.walk(dir):\n\t\tmatching = fnmatch.filter(files, pattern)\n\t\tmatching_files.extend(os.path.join(root, f) for f in matching)\n\treturn matching_files","def GetDirFilesRecursive(directory):\n dirfiles = set()\n for dirpath, _, files in os.walk(directory):\n for name in files:\n dirfiles.add(os.path.normpath(os.path.join(dirpath, name)))\n return dirfiles","def files_in_dir(path):\n return os.listdir(path)","def walk_package(pkgname, root):\n dirs = []\n files = []\n for name in pkg_resources.resource_listdir(pkgname, str(root)):\n fullname = root / name\n if pkg_resources.resource_isdir(pkgname, str(fullname)):\n dirs.append(fullname)\n else:\n files.append(Path(name))\n for new_path in dirs:\n yield from walk_package(pkgname, new_path)\n yield root, dirs, files","def get_file_paths(dir, ext):\n files = []\n for root, dirs, filenames in os.walk(dir):\n for filename in filenames:\n if filename.endswith(ext):\n files.append(os.path.join(root, filename))\n return files","def files(self):\n self._printer('\\tFiles Walk')\n for directory in self.directory:\n for path in os.listdir(directory):\n full_path = os.path.join(directory, path)\n if os.path.isfile(full_path):\n if not path.startswith('.'):\n self.filepaths.append(full_path)\n return self._get_filepaths()","def _get_file_list(folder):\n tree = [x for x in os.walk(folder)]\n files = [os.path.join(t[0], y) for t in tree for y in t[2]]\n return [os.path.relpath(x, start=folder)\n for x in files if x != LOCAL_METADATA_FILE]","def find_files(suffix, path):\n\n \n result = []\n try:\n \n for file in os.listdir(path): \n if os.path.isfile(os.path.join(path,file)) and file.endswith(suffix): \n result.append(os.path.join(path,file))\n if os.path.isdir(os.path.join(path,file)):\n result.extend ( find_files(suffix, os.path.join(path,file)) )\n\n except Exception as e:\n print(str(e))\n\n return result","def find_files(basedir, regexp):\n regexp = re.compile(regexp)\n return sorted(fn for fn in glob.glob(os.path.join(basedir, '**'),\n recursive=True)\n if regexp.match(fn))","def get_files(self, dir):\n path = os.path.join(self.loc, dir)\n return [f for f in os.listdir(path)\n if os.path.isfile(os.path.join(path, f))]","def list_all_files(dir):\n\n result = []\n for root, _, filenames in os.walk(dir):\n for name in filenames:\n filename, ext = os.path.splitext(name)\n if ext == '.cs' or ext == '.xaml':\n result.append(os.path.join(root, name))\n return result","def scan_tree(path):\n list_of_file_paths = []\n for file_obj in scandir(path):\n if file_obj.is_dir(follow_symlinks=False):\n # yield from scan_tree(file_obj.path)\n list_of_file_paths.extend(scan_tree(file_obj.path))\n else:\n # yield file_path\n if 'DS_Store' not in file_obj.path:\n list_of_file_paths.append(file_obj.path)\n return list_of_file_paths","def files(self) -> Generator[Path, None, None]:\n return Path(self.package).resolve(strict=True).glob(self.glob)","def get_package_data_files(package, data, package_dir=None):\n if package_dir is None:\n package_dir = os.path.join(*package.split('.'))\n all_files = []\n for f in data:\n path = os.path.join(package_dir, f)\n if os.path.isfile(path):\n all_files.append(f)\n continue\n for root, _dirs, files in os.walk(path, followlinks=True):\n root = os.path.relpath(root, package_dir)\n for file in files:\n file = os.path.join(root, file)\n if file not in all_files:\n all_files.append(file)\n return all_files","def iglob_recursive(directory, file_pattern):\n for root, dir_names, file_names in os.walk(directory, followlinks=True):\n files = fnmatch.filter(file_names, file_pattern)\n for filename in files:\n yield os.path.join(root, filename)","def walkdir(folder):\n for dirpath, dirs, files in os.walk(folder):\n for filename in files:\n yield os.path.abspath(os.path.join(dirpath, filename))","def filepaths(self, langs) -> Generator[str, None, None]:\n for pv in self.projects(langs):\n yield from pv.filepaths()","def FindCheckerFiles(path):\n if not path:\n Logger.fail(\"No source path provided\")\n elif os.path.isfile(path):\n return [ path ]\n elif os.path.isdir(path):\n foundFiles = []\n for root, dirs, files in os.walk(path):\n for file in files:\n extension = os.path.splitext(file)[1]\n if extension in [\".java\", \".smali\"]:\n foundFiles.append(os.path.join(root, file))\n return foundFiles\n else:\n Logger.fail(\"Source path \\\"\" + path + \"\\\" not found\")","def get_files(dirs):\n for dir in dirs:\n for root, _, files in os.walk(dir):\n for file in files:\n path = Path(os.path.join(root, file))\n if path.suffix in EXTENSIONS:\n yield path","def _findFilesInDir(self, directory, extension=\".py\", foundFiles=None):\n\n #mutable default arguments in Python are evaluated once when the function is defined, not each time the function is called.\n if foundFiles == None:\n foundFiles = []\n \n filenames = os.listdir(directory)\n for filename in filenames:\n #need to verify that the entity is a file (this avoids problems when directory names have file extensions)\n if filename[-len(extension):] == extension and filename[0:1] != '.' and os.path.isfile(directory + '/' + filename):\n foundFiles.append(directory + '/' + filename)\n print ('===>' + filename)\n return foundFiles","def get_source_files(self):\n return [\n path.as_posix()\n for path in _Path(self.src_dir).rglob(\"*\")\n if not path.is_dir()\n ] + [\n (path / \"CMakeLists.txt\").as_posix()\n for path in _PurePath(self.src_dir).parents\n ]","def find_data(self):\n data_list = []\n for root, dirs, files in os.walk(pathfinder.data_path()):\n for name in files:\n data_list.append(os.path.join(root, name))\n return data_list","def get_all_fullpaths(self):\n files = []\n for mf in self.manifests:\n files.extend(self.manifests[mf].get_fullpaths())\n return files","def get_files(root_dir, recursive=True):\n\n ret_files = []\n\n for root, _, files in os.walk(root_dir, topdown=True):\n\n for name in files:\n ret_files.append(os.path.join(root, name))\n\n if not recursive:\n break\n\n return ret_files","def walkdir(self, folder):\n for dirpath, dirs, files in os.walk(folder):\n for filename in files:\n yield os.path.abspath(os.path.join(dirpath, filename))"],"string":"[\n \"def _find_files_to_package(self, path):\\n for root, dirs, files in os.walk(path):\\n root_parts = pathlib.Path(root).relative_to(path).parts\\n if self._include_directory(root_parts):\\n for f in files:\\n if self._include_file(root_parts, f):\\n yield pathlib.Path(root, f)\",\n \"def files_in_dir(root_dir):\\n file_set = set()\\n\\n for dir_, _, files in os.walk(root_dir):\\n for file_name in files:\\n rel_dir = os.path.relpath(dir_, root_dir)\\n rel_file = os.path.join(rel_dir, file_name)\\n file_set.add(rel_file)\\n\\n return [Path(PureWindowsPath(f)) for f in file_set]\",\n \"def find_files(d):\\n for root, dirs, files in os.walk(d):\\n for f in files:\\n yield path.abspath(path.join(root, f))\",\n \"def findFiles(target, path):\\r\\n\\tfiles = []\\r\\n\\tlyst = os.listdir(path)\\r\\n\\tfor element in lyst:\\r\\n\\t\\tif os.path.isfile(element):\\r\\n\\t\\t\\tif target in element:\\r\\n\\t\\t\\t\\tfiles.append(path + os.sep + element)\\r\\n\\t\\telse:\\r\\n\\t\\t\\tos.chdir(element)\\r\\n\\t\\t\\tfiles.extend(findFiles(target, os.getcwd()))\\r\\n\\t\\t\\tos.chdir(\\\"..\\\")\\r\\n\\treturn files\",\n \"def search_dir(d: PosixPath, basepath, files, extension):\\n scripts = []\\n for path in d.iterdir():\\n string_path = str(path).replace(basepath, '')[1:]\\n if path.is_dir():\\n recu_scripts = search_dir(path, basepath, files, extension)\\n if recu_scripts:\\n scripts.extend(recu_scripts)\\n if string_path in files and path.suffix == extension:\\n scripts.extend([string_path])\\n return scripts\",\n \"def _find_files(root_dir, should_include):\\n paths = [] # Return value.\\n\\n is_module = lambda path: path.endswith(\\\".py\\\")\\n\\n # os.walk() is new in Python 2.3\\n # http://docs.python.org/library/os.html#os.walk\\n for dir_path, dir_names, file_names in os.walk(root_dir):\\n new_paths = [os.path.join(dir_path, file_name) for file_name in file_names]\\n new_paths = filter(is_module, new_paths)\\n new_paths = filter(should_include, new_paths)\\n paths.extend(new_paths)\\n\\n return paths\",\n \"def find_package_data(package):\\n walk = [(dirpath.replace(package + os.sep, '', 1), filenames)\\n for dirpath, dirnames, filenames in os.walk(package)]\\n\\n filepaths = []\\n for base, filenames in walk:\\n filepaths.extend([os.path.join(base, filename)\\n for filename in filenames])\\n return filepaths\",\n \"def test_GetFilesInDirectory_subdir_relpath(tempdir: pathlib.Path):\\n # Create files: [ sub/a, sub/sub/b ]\\n (tempdir / \\\"sub\\\").mkdir()\\n (tempdir / \\\"sub\\\" / \\\"a\\\").touch()\\n (tempdir / \\\"sub\\\" / \\\"sub\\\").mkdir()\\n (tempdir / \\\"sub\\\" / \\\"sub\\\" / \\\"b\\\").touch()\\n assert set(dpack.GetFilesInDirectory(tempdir, [])) == {\\n pathlib.Path(\\\"sub/a\\\"),\\n pathlib.Path(\\\"sub/sub/b\\\"),\\n }\",\n \"def find_package_data(data_root, package_root):\\n files = []\\n for root, dirnames, filenames in os.walk(data_root):\\n for fn in filenames:\\n files.append(relpath(join(root, fn), package_root))\\n return files\",\n \"def get_paths(pattern):\\n if not in_source_tree:\\n pattern = '../' + pattern\\n\\n files = glob.glob(os.path.normpath(os.path.join(top_dir, pattern)))\\n return files\",\n \"def find_all_files(path):\\n for root, dirs, files in os.walk(os.path.join(path)):\\n for filename in files:\\n yield os.path.join(root, filename)\",\n \"def _get_all_files(dir_path):\\n for root, _, filenames in os.walk(dir_path):\\n for name in filenames:\\n target = os.path.join(root, name)\\n yield target\",\n \"def locate(root = '.', target = 'info'):\\n \\n matches = []\\n \\n for root, dirnames, filenames in os.walk(root):\\n for dirnames in fnmatch.filter(dirnames, target):\\n matches.append(os.path.join(root, dirnames))\\n \\n return matches\",\n \"def all_files_under(path):\\r\\n for cur_path, dirnames, filenames in os.walk(path):\\r\\n for filename in filenames:\\r\\n yield os.path.join(cur_path, filename)\",\n \"def GetAllFilepaths(root_directory):\\n path_list = []\\n for dirpath, _, filenames in os.walk(root_directory):\\n for filename in filenames:\\n path_list.append(os.path.abspath(os.path.join(dirpath, filename)))\\n return path_list\",\n \"def find_data_files_distutils(self, package, src_dir):\\n from glob import glob\\n import os\\n from distutils.util import convert_path\\n\\n globs = (self.package_data.get('', [])\\n + self.package_data.get(package, []))\\n files = []\\n for pattern in globs:\\n # Each pattern has to be converted to a platform-specific path\\n filelist = glob(os.path.join(src_dir, convert_path(pattern)))\\n # Files that match more than one pattern are only added once\\n files.extend([fn for fn in filelist if fn not in files\\n and (os.path.isfile(fn) or os.path.islink(fn))])\\n return files\",\n \"def _package_files(directory: str, suffix: str) -> list:\\n\\n paths = []\\n\\n for (path, directories, filenames) in os.walk(directory):\\n for filename in filenames:\\n if filename.endswith(suffix):\\n paths.append(os.path.join('..', path, filename))\\n\\n return paths\",\n \"def getImmediateSubdirectories(dir):\",\n \"def get_files(self, include=[], exclude=[]):\\r\\n for (basepath, dpaths, fpaths) in os.walk(self.path, topdown=True):\\r\\n for subpath in dpaths + fpaths:\\r\\n path = os.path.join(self.chroot_path(basepath), subpath)\\r\\n if filter_path(path, include, exclude):\\r\\n yield path\",\n \"def findfiles(path, ext=\\\".pyc\\\"):\\n results = []\\n regex = re.compile(re.escape(ext)+\\\"$\\\", re.I)\\n\\n tree = os.walk(path)\\n for d in tree:\\n # Each element of a walker represents a directory and its contents.\\n # Diagnostic, if you wish.\\n #print(d)\\n if d[2]:\\n # Are there files in this directory?\\n for f in d[2]:\\n if regex.findall(f):\\n relpath = os.path.join(d[0], f)\\n results.append(os.path.realpath(relpath))\\n\\n return results\",\n \"def getFiles(searchDir = './', extension = 'source'):\\n from glob import glob \\n\\n return glob(searchDir+'/*.'+extension)\",\n \"def _recursive_file_search(self, path, pattern):\\n matches = []\\n for root, dirnames, filenames in os.walk(path):\\n for filename in fnmatch.filter(filenames, pattern):\\n matches.append(os.path.join(root, filename))\\n\\n return matches\",\n \"def getFilePaths(directory):\\r\\n\\tfor folder, subs, files in os.walk(directory):\\r\\n\\t\\tfor filename in files:\\r\\n\\t\\t\\tyield os.path.join(folder, filename)\",\n \"def get_files_in_directory(dir_name: str):\\n filenames = []\\n\\n for entry in walk(dir_name):\\n root_dir = entry[0]\\n dir_files = entry[2]\\n filenames.extend([Path(root_dir).joinpath(file) for file in dir_files])\\n\\n return filenames\",\n \"def finddirs(root):\\n retval = []\\n for root, dirs, files in os.walk(root):\\n for d in dirs:\\n retval.append(os.path.join(root, d))\\n return retval\",\n \"def get_all_files(cwd):\\n return os.listdir(cwd)\",\n \"def _get_files(self):\\n # pylint: disable=unused-variable\\n for dirpath, __, filenames in os.walk(self.start_location):\\n for file_ in filenames:\\n if file_.endswith('.py'):\\n yield \\\"{0}{1}\\\".format(dirpath, file_)\",\n \"def walk_recursive(root, pattern='*.py'):\\r\\n for root, dirnames, filenames in os.walk(root):\\r\\n for filename in fnmatch.filter(filenames, pattern):\\r\\n yield os.path.join(root, filename)\",\n \"def _findFiles(self, topLevelDirectory, extension=\\\".py\\\", foundFiles=None):\\n \\n #mutable default arguments in Python are evaluated once when the function is defined, not each time the function is called.\\n if foundFiles == None:\\n foundFiles = []\\n \\n for dirpath, dirnames, filenames in os.walk(topLevelDirectory):\\n for filename in filenames:\\n #need to verify that the entity is a file (this avoids problems when directory names have file extensions)\\n if filename[-len(extension):] == extension and filename[0:1] != '.' and os.path.isfile(dirpath+\\\"/\\\"+filename):\\n foundFiles.append(dirpath+\\\"/\\\"+filename)\\n #print dirpath+\\\"/\\\"+filename\\n return foundFiles\",\n \"def locate(pattern, root=os.curdir):\\n for path, dirs, files in os.walk(os.path.abspath(root)):\\n for filename in fnmatch.filter(files, pattern):\\n yield os.path.join(path, filename)\",\n \"def get_filepaths(directory):\\n file_paths = []\\n for root, directories, files in os.walk(directory):\\n for filename in files:\\n file_path = os.path.join(root, filename)\\n file_paths.append(file_path)\\n return file_paths\",\n \"def _RecursiveDirectoryListing(dirpath):\\n result = []\\n for root, _, files in os.walk(dirpath):\\n for f in files:\\n result.append(os.path.relpath(os.path.join(root, f), dirpath))\\n return result\",\n \"def get_package_files(_dir):\\n _files = []\\n for root, _, files in os.walk(_dir):\\n if('git' in root or '/tests' in root):\\n continue\\n for _name in files:\\n _files.append((root, _name))\\n return _files\",\n \"def find_all_files(self):\\n look4files = [ f for f in listdir(self.file_location) if isfile(join(self.file_location,f)) ]\\n return look4files\",\n \"def _get_filepaths(directory):\\n file_paths = [] # List which will store all of the full filepaths.\\n\\n # Walk the tree.\\n for root, directories, files in os.walk(directory):\\n for filename in files:\\n # Join the two strings in order to form the full filepath.\\n filepath = os.path.join(root, filename)\\n file_paths.append(filepath) # Add it to the list.\\n\\n return file_paths # Self-explanatory.\",\n \"def get_files_in_dir(path):\\n return [os.path.join(dir_name, file)\\n for dir_name, subdirs, files in os.walk(path)\\n for file in files]\",\n \"def gather_files(path_specs, file_name_pattern, recursively=False):\\n files = []\\n for path_spec in path_specs:\\n if os.path.isdir(path_spec):\\n files.extend(IOUtils.find_files(path_spec, file_name_pattern, recursively))\\n elif os.path.isfile(path_spec):\\n files.append(path_spec)\\n return files\",\n \"def find_files(root, directory, filename):\\n\\n path_list = []\\n walker = os.walk(root, followlinks=True)\\n for root, dirs, files in walker:\\n remove_vcs_dirs(dirs)\\n\\n #if dirs containt 'directory', don't walk others\\n if directory in dirs: dirs[:] = [directory]\\n\\n if root.endswith(os.path.sep + directory):\\n if filename in files:\\n path_list.append(os.path.join(root, filename))\\n dirs[:] = []\\n\\n return path_list\",\n \"def get_filepaths(directory):\\n file_paths = [] # List which will store all of the full filepaths.\\n\\n # Walk the tree.\\n for root, directories, files in os.walk(directory):\\n for filename in files:\\n # Join the two strings in order to form the full filepath.\\n if filename == \\\".DS_Store\\\":\\n pass\\n else:\\n filepath = os.path.join(root, filename)\\n file_paths.append(filepath) # Add it to the list.\\n\\n return file_paths\",\n \"def GetFilesInDirectory(dir_path):\\n\\treturn [f for f in os.listdir(dir_path) if os.path.isfile(os.path.join(dir_path,f))]\",\n \"def find_subdirectories(package):\\n try:\\n subdirectories = next(os.walk(package_to_path(package)))[1]\\n except StopIteration:\\n subdirectories = []\\n return subdirectories\",\n \"def matching_paths(dirpath, exts=None, recursive=True, relative=True):\\n if recursive:\\n for root, dirnames, filenames in os.walk(dirpath):\\n for fname in filenames:\\n if exts:\\n for ext in exts:\\n if fname.endswith(ext) and not fname.startswith(\\\".\\\"):\\n if relative:\\n yield os.path.relpath(\\n os.path.join(root, fname), dirpath\\n )\\n else:\\n yield os.path.join(root, fname)\\n break\\n else:\\n if not fname.startswith(\\\".\\\"):\\n if relative:\\n yield os.path.relpath(os.path.join(root, fname), dirpath)\\n else:\\n yield os.path.join(root, fname)\\n else:\\n for fname in os.listdir(dirpath):\\n full = os.path.join(dirpath, fname)\\n if not os.path.isfile(full) or fname.startswith(\\\".\\\"):\\n pass\\n elif exts:\\n for ext in exts:\\n if fname.endswith(ext):\\n if relative:\\n yield os.path.relpath(full, dirpath)\\n else:\\n yield full\\n break\\n else:\\n if relative:\\n yield os.path.relpath(full, dirpath)\\n else:\\n yield full\",\n \"def get_dir_recursive(path: str) -> List[str]:\\n files = []\\n for dir_entry in os.scandir(path):\\n if dir_entry.is_dir(follow_symlinks=True):\\n files.extend(get_dir_recursive(dir_entry))\\n else:\\n files.append(dir_entry.path)\\n return files\",\n \"def inferred_settings_files(self) -> List[Path]:\\n prefix = self.env_parser.prefix.strip(self.env_parser.split_char).lower()\\n base_pattern = f\\\"*{prefix}*settings\\\"\\n extensions = [\\n ext\\n for loader in FileLoader.registered_loaders\\n for ext in loader.valid_file_extensions\\n ]\\n\\n def find_settings_files(path: Path, glob_pattern: str, recursive=False):\\n glob = path.rglob if recursive else path.glob\\n filepaths = []\\n for ext in extensions:\\n for filepath in glob(f\\\"{glob_pattern}{ext}\\\"):\\n if filepath.is_file():\\n filepaths.append(filepath)\\n return sorted(filepaths)\\n\\n # Find all directories between current directory and project root\\n search_directories: List[Path] = []\\n project_root_candidates = [\\n \\\".git\\\",\\n \\\".hg\\\",\\n \\\"setup.py\\\",\\n \\\"requirements.txt\\\",\\n \\\"environment.yml\\\",\\n \\\"environment.yaml\\\",\\n \\\"pyproject.toml\\\",\\n ]\\n current_path: Path = Path(\\\".\\\")\\n while True:\\n search_directories.append(current_path)\\n new_current_path = current_path / \\\"..\\\"\\n if (\\n any(\\n (current_path / candidate).exists()\\n for candidate in project_root_candidates\\n )\\n or not new_current_path.is_dir()\\n or new_current_path.resolve() == current_path.resolve()\\n ):\\n break\\n current_path = new_current_path\\n\\n # Iterate over all directories and find files\\n filepaths: List[Path] = []\\n for directory in reversed(search_directories):\\n filepaths.extend(find_settings_files(directory, base_pattern))\\n for sub_dir in directory.glob(base_pattern):\\n if not sub_dir.is_dir():\\n continue\\n # Use all files with valid file extensions if already in settings directory.\\n filepaths.extend(find_settings_files(sub_dir, \\\"*\\\", recursive=True))\\n\\n return filepaths\",\n \"def _get_files(self, path):\\n result = []\\n for f in os.listdir(path):\\n if os.path.isdir(os.path.join(path, f)):\\n result += self._get_files(os.path.join(path, f))\\n else:\\n result.append(os.path.join(path, f))\\n return result\",\n \"def read_filepaths(self, directory):\\n folder_paths = [os.path.join(directory, folder) for folder in os.listdir(directory) if not folder.startswith('.')]\\n filepaths = [[os.path.join(cur_folder, cur_file) for cur_file in os.listdir(cur_folder)] for cur_folder in folder_paths]\\n return filepaths\",\n \"def get_filepaths(directory):\\n file_paths = [] # List which will store all of the full filepaths.\\n\\n # Walk the tree.\\n for root, directories, files in os.walk(directory):\\n for filename in files:\\n # Join the two strings in order to form the full filepath.\\n filepath = os.path.join(root, filename)\\n file_paths.append(filepath) # Add it to the list.\\n return file_paths\",\n \"def _files_in_subdir(self, subdir, pattern, regex):\\n all_files = glob(join(subdir, (pattern or '**')), recursive=True)\\n all_files = [fp for fp in all_files if isfile(fp)]\\n\\n if pattern and regex:\\n raise ValueError(\\\"Specify pattern OR regex, not both!\\\")\\n elif pattern:\\n files = [fn for fn in glob(join(subdir, pattern), recursive=True)]\\n elif regex:\\n files = [fn for fn in all_files if re.search(regex, fn)]\\n else:\\n files = all_files\\n\\n return sorted(files)\",\n \"def find_data_files_setuptools(self, package, src_dir):\\n from glob import glob\\n import itertools\\n import os\\n\\n patterns = self._get_platform_patterns(\\n self.package_data,\\n package,\\n src_dir,\\n )\\n globs_expanded = map(glob, patterns)\\n # flatten the expanded globs into an iterable of matches\\n globs_matches = itertools.chain.from_iterable(globs_expanded)\\n glob_files = [e for e in globs_matches if os.path.isfile(e) or os.path.islink(e)]\\n files = itertools.chain(\\n self.manifest_files.get(package, []),\\n glob_files,\\n )\\n return self.exclude_data_files(package, src_dir, files)\",\n \"def get_files_from_dir(dir_name):\\n return [path.join(dir_name, f) for f in listdir(dir_name) if path.isfile(path.join(dir_name, f))]\",\n \"def find_files(base_path,pattern):\\n res=()\\n print_verbose(2,\\\"\\\\t> Recursive search: Base path = %s, pattern = %s\\\" %(base_path,pattern))\\n for root, dirs, files in os.walk(base_path, topdown=True):\\n for f_name in fnmatch.filter(files, pattern):\\n res= res + (os.path.join(root, f_name),)\\n return res;\",\n \"def get_filepaths(directory):\\n file_paths = [] # List which will store all of the full filepaths.\\n\\n # Walk the tree.\\n for root, directories, files in os.walk(directory):\\n for filename in files:\\n # Join the two strings in order to form the full filepath.\\n filepath = os.path.join(root, filename)\\n file_paths.append(filepath) # Add it to the list.\\n\\n return file_paths\",\n \"def get_all_paths(dmt, directory_path=''):\\n # Base case.\\n if not dmt.children:\\n return set()\\n \\n filesystem_items = set()\\n for item in dmt.children.keys():\\n filesystem_items.add(directory_path+item)\\n # Also get the paths of subdirectory contents.\\n if item[-1] == '/':\\n subdir_name = item\\n subdir_path = directory_path + subdir_name\\n \\n filesystem_items.add(subdir_path)\\n filesystem_items.update(get_all_paths(dmt.children[subdir_name], subdir_path))\\n \\n return filesystem_items\",\n \"def files_in_folder(folder):\\n files = []\\n for f in glob.glob(folder):\\n if os.path.isdir(f):\\n files.extend(files_in_folder(f + os.sep + \\\"**\\\"))\\n else:\\n files.append(f)\\n return files\",\n \"def get_filepaths(directory):\\r\\n file_paths = [] # List which will store all of the full filepaths.\\r\\n\\r\\n # Walk the tree.\\r\\n for root, directories, files in os.walk(directory):\\r\\n for filename in files:\\r\\n # Join the two strings in order to form the full filepath.\\r\\n filepath = os.path.join(root, filename)\\r\\n file_paths.append(filepath) # Add it to the list.\\r\\n\\r\\n return file_paths # Self-explanatory.\\r\",\n \"def get_all_img_paths(path_to_folder):\\n all_subfolders = glob.glob(path_to_folder + '*')\\n all_paths = []\\n for folder in all_subfolders:\\n all_paths.extend(glob.glob(folder + '/*'))\\n # get relative paths\\n common_prefix = path_to_folder\\n relative_paths = [os.path.relpath(path, common_prefix) for path in all_paths]\\n return relative_paths\",\n \"def recursive_glob(rootdir=\\\".\\\", suffix=\\\"\\\"):\\n image_paths = []\\n for looproot, _, filenames in os.walk(rootdir):\\n for filename in filenames:\\n if filename.endswith(suffix):\\n image_paths.append(os.path.join(looproot, filename))\\n return image_paths\",\n \"def recursive_glob(rootdir=\\\".\\\", suffix=\\\"\\\"):\\n image_paths = []\\n for looproot, _, filenames in os.walk(rootdir):\\n for filename in filenames:\\n if filename.endswith(suffix):\\n image_paths.append(os.path.join(looproot, filename))\\n return image_paths\",\n \"def get_files_in_dir(dir: str):\\n\\n file_list = [f\\\"{dir}/{file}\\\" for file in listdir(dir) if isfile(join(dir, file))]\\n\\n return file_list\",\n \"def get_filepaths(directory):\\n file_paths = [] # List which will store all of the full filepaths.\\n\\n # Walk the tree.\\n for root, directories, files in os.walk(directory):\\n for filename in files:\\n # Join the two strings in order to form the full filepath.\\n filepath = os.path.join(root, filename)\\n file_paths.append(filepath) # Add it to the list.\\n\\n return file_paths # Self-explanatory.\",\n \"def get_filepaths(directory):\\n file_paths = [] # List which will store all of the full filepaths.\\n\\n # Walk the tree.\\n for root, directories, files in os.walk(directory):\\n for filename in files:\\n # Join the two strings in order to form the full filepath.\\n filepath = os.path.join(root, filename)\\n file_paths.append(filepath) # Add it to the list.\\n\\n return file_paths # Self-explanatory.\",\n \"def get_filepaths(directory):\\n file_paths = [] # List which will store all of the full filepaths.\\n\\n # Walk the tree.\\n for root, directories, files in os.walk(directory):\\n for filename in files:\\n # Join the two strings in order to form the full filepath.\\n filepath = os.path.join(root, filename)\\n file_paths.append(filepath) # Add it to the list.\\n\\n return file_paths # Self-explanatory.\",\n \"def LocateFiles(pattern, root=os.curdir):\\n for path, _, files in os.walk(os.path.abspath(root)):\\n for filename in fnmatch.filter(files, pattern):\\n yield os.path.join(path, filename)\",\n \"def get_filepaths(directory):\\n file_paths = [] # List which will store all of the full filepaths.\\n\\n # Walk the tree.\\n for root, directories, files in os.walk(directory):\\n root = os.path.normpath(root)\\n directories.sort()\\n files.sort()\\n for filename in files:\\n # Join the two strings in order to form the full filepath.\\n if not root.startswith('_') and not root.startswith('.') and filename.endswith(\\\".md\\\"):\\n filepath = os.path.normpath(os.path.join(root, filename))\\n file_paths.append(filepath) # Add it to the list.\\n\\n return file_paths # Self-explanatory.\",\n \"def get_all_files(self):\\n\\t\\tfiles_list = []\\n\\t\\tfor path, subdirs, files in os.walk(self.root):\\n\\t\\t for name in files:\\n\\t\\t \\tfiles_list.append(os.path.join(self.root, name))\\n\\t\\treturn files_list[0:-1]\",\n \"def walk_directory(self, path):\\n files = []\\n for dirpath, dirnames, filenames in os.walk(path):\\n for filename in filenames:\\n files.append(os.path.join(dirpath, filename))\\n return files\",\n \"def find(directory, slash='/', pattern=r'.+\\\\.out'):\\n for directory, subdirectories, files in os.walk(directory):\\n for file in files:\\n if re.findall(pattern, str(file)):\\n yield str(directory + slash + file)\",\n \"def relative_to_buildroot(self):\\n return [os.path.join(self.rel_path, source) for source in self.source_paths]\",\n \"def get_paths(file_path):\\n return glob(path.join(file_path, '*'))\",\n \"def get_files_from_directory(path):\\n return [f for f in listdir(path) if isfile(join(path, f))]\",\n \"def recursive_glob(self, rootdir='.', suffix=''):\\n return [os.path.join(rootdir, filename)\\n for filename in sorted(os.listdir(rootdir)) if filename.endswith(suffix)]\",\n \"def find(self, path_list):\\n import fnmatch\\n path_list2 = []\\n for pattern in path_list:\\n for root, _, filenames in os.walk('.'):\\n for filename in fnmatch.filter(filenames, pattern):\\n path_list2.append(os.path.join(root, filename))\\n return path_list2\",\n \"def get_files(dir: str) -> List[str]:\\n ret = []\\n for root, dirs, files in os.walk(dir):\\n for name in dirs:\\n ret.extend(get_files(os.path.join(root, name)))\\n for name in files:\\n ret.append(os.path.join(root, name))\\n return ret\",\n \"def _get_dir_entries(dir_name, subdir, *args):\\n file_list = []\\n for file in os.listdir(dir_name):\\n dirfile = os.path.join(dir_name, file)\\n if os.path.isfile(dirfile):\\n if not args:\\n file_list.append(dirfile)\\n else:\\n if os.path.splitext(dirfile)[1][1:] in args:\\n file_list.append(dirfile)\\n # recursively access file names in subdirectories\\n elif os.path.isdir(dirfile) and subdir:\\n file_list.extend(_get_dir_entries(dirfile, subdir, *args))\\n return file_list\",\n \"def find_packages( root ):\\n for path, directories, files in os.walk( root ):\\n if is_package( path ):\\n yield path.replace( '/','.' )\",\n \"def allfiles(dir, pattern=\\\"*\\\"):\\n\\tdir = uniformpath(dir)\\n\\tif not os.path.isdir(dir): # must be file\\n\\t\\treturn [dir]\\n\\tmatching_files = []\\n\\tfor root, subFolders, files in os.walk(dir):\\n\\t\\tmatching = fnmatch.filter(files, pattern)\\n\\t\\tmatching_files.extend(os.path.join(root, f) for f in matching)\\n\\treturn matching_files\",\n \"def GetDirFilesRecursive(directory):\\n dirfiles = set()\\n for dirpath, _, files in os.walk(directory):\\n for name in files:\\n dirfiles.add(os.path.normpath(os.path.join(dirpath, name)))\\n return dirfiles\",\n \"def files_in_dir(path):\\n return os.listdir(path)\",\n \"def walk_package(pkgname, root):\\n dirs = []\\n files = []\\n for name in pkg_resources.resource_listdir(pkgname, str(root)):\\n fullname = root / name\\n if pkg_resources.resource_isdir(pkgname, str(fullname)):\\n dirs.append(fullname)\\n else:\\n files.append(Path(name))\\n for new_path in dirs:\\n yield from walk_package(pkgname, new_path)\\n yield root, dirs, files\",\n \"def get_file_paths(dir, ext):\\n files = []\\n for root, dirs, filenames in os.walk(dir):\\n for filename in filenames:\\n if filename.endswith(ext):\\n files.append(os.path.join(root, filename))\\n return files\",\n \"def files(self):\\n self._printer('\\\\tFiles Walk')\\n for directory in self.directory:\\n for path in os.listdir(directory):\\n full_path = os.path.join(directory, path)\\n if os.path.isfile(full_path):\\n if not path.startswith('.'):\\n self.filepaths.append(full_path)\\n return self._get_filepaths()\",\n \"def _get_file_list(folder):\\n tree = [x for x in os.walk(folder)]\\n files = [os.path.join(t[0], y) for t in tree for y in t[2]]\\n return [os.path.relpath(x, start=folder)\\n for x in files if x != LOCAL_METADATA_FILE]\",\n \"def find_files(suffix, path):\\n\\n \\n result = []\\n try:\\n \\n for file in os.listdir(path): \\n if os.path.isfile(os.path.join(path,file)) and file.endswith(suffix): \\n result.append(os.path.join(path,file))\\n if os.path.isdir(os.path.join(path,file)):\\n result.extend ( find_files(suffix, os.path.join(path,file)) )\\n\\n except Exception as e:\\n print(str(e))\\n\\n return result\",\n \"def find_files(basedir, regexp):\\n regexp = re.compile(regexp)\\n return sorted(fn for fn in glob.glob(os.path.join(basedir, '**'),\\n recursive=True)\\n if regexp.match(fn))\",\n \"def get_files(self, dir):\\n path = os.path.join(self.loc, dir)\\n return [f for f in os.listdir(path)\\n if os.path.isfile(os.path.join(path, f))]\",\n \"def list_all_files(dir):\\n\\n result = []\\n for root, _, filenames in os.walk(dir):\\n for name in filenames:\\n filename, ext = os.path.splitext(name)\\n if ext == '.cs' or ext == '.xaml':\\n result.append(os.path.join(root, name))\\n return result\",\n \"def scan_tree(path):\\n list_of_file_paths = []\\n for file_obj in scandir(path):\\n if file_obj.is_dir(follow_symlinks=False):\\n # yield from scan_tree(file_obj.path)\\n list_of_file_paths.extend(scan_tree(file_obj.path))\\n else:\\n # yield file_path\\n if 'DS_Store' not in file_obj.path:\\n list_of_file_paths.append(file_obj.path)\\n return list_of_file_paths\",\n \"def files(self) -> Generator[Path, None, None]:\\n return Path(self.package).resolve(strict=True).glob(self.glob)\",\n \"def get_package_data_files(package, data, package_dir=None):\\n if package_dir is None:\\n package_dir = os.path.join(*package.split('.'))\\n all_files = []\\n for f in data:\\n path = os.path.join(package_dir, f)\\n if os.path.isfile(path):\\n all_files.append(f)\\n continue\\n for root, _dirs, files in os.walk(path, followlinks=True):\\n root = os.path.relpath(root, package_dir)\\n for file in files:\\n file = os.path.join(root, file)\\n if file not in all_files:\\n all_files.append(file)\\n return all_files\",\n \"def iglob_recursive(directory, file_pattern):\\n for root, dir_names, file_names in os.walk(directory, followlinks=True):\\n files = fnmatch.filter(file_names, file_pattern)\\n for filename in files:\\n yield os.path.join(root, filename)\",\n \"def walkdir(folder):\\n for dirpath, dirs, files in os.walk(folder):\\n for filename in files:\\n yield os.path.abspath(os.path.join(dirpath, filename))\",\n \"def filepaths(self, langs) -> Generator[str, None, None]:\\n for pv in self.projects(langs):\\n yield from pv.filepaths()\",\n \"def FindCheckerFiles(path):\\n if not path:\\n Logger.fail(\\\"No source path provided\\\")\\n elif os.path.isfile(path):\\n return [ path ]\\n elif os.path.isdir(path):\\n foundFiles = []\\n for root, dirs, files in os.walk(path):\\n for file in files:\\n extension = os.path.splitext(file)[1]\\n if extension in [\\\".java\\\", \\\".smali\\\"]:\\n foundFiles.append(os.path.join(root, file))\\n return foundFiles\\n else:\\n Logger.fail(\\\"Source path \\\\\\\"\\\" + path + \\\"\\\\\\\" not found\\\")\",\n \"def get_files(dirs):\\n for dir in dirs:\\n for root, _, files in os.walk(dir):\\n for file in files:\\n path = Path(os.path.join(root, file))\\n if path.suffix in EXTENSIONS:\\n yield path\",\n \"def _findFilesInDir(self, directory, extension=\\\".py\\\", foundFiles=None):\\n\\n #mutable default arguments in Python are evaluated once when the function is defined, not each time the function is called.\\n if foundFiles == None:\\n foundFiles = []\\n \\n filenames = os.listdir(directory)\\n for filename in filenames:\\n #need to verify that the entity is a file (this avoids problems when directory names have file extensions)\\n if filename[-len(extension):] == extension and filename[0:1] != '.' and os.path.isfile(directory + '/' + filename):\\n foundFiles.append(directory + '/' + filename)\\n print ('===>' + filename)\\n return foundFiles\",\n \"def get_source_files(self):\\n return [\\n path.as_posix()\\n for path in _Path(self.src_dir).rglob(\\\"*\\\")\\n if not path.is_dir()\\n ] + [\\n (path / \\\"CMakeLists.txt\\\").as_posix()\\n for path in _PurePath(self.src_dir).parents\\n ]\",\n \"def find_data(self):\\n data_list = []\\n for root, dirs, files in os.walk(pathfinder.data_path()):\\n for name in files:\\n data_list.append(os.path.join(root, name))\\n return data_list\",\n \"def get_all_fullpaths(self):\\n files = []\\n for mf in self.manifests:\\n files.extend(self.manifests[mf].get_fullpaths())\\n return files\",\n \"def get_files(root_dir, recursive=True):\\n\\n ret_files = []\\n\\n for root, _, files in os.walk(root_dir, topdown=True):\\n\\n for name in files:\\n ret_files.append(os.path.join(root, name))\\n\\n if not recursive:\\n break\\n\\n return ret_files\",\n \"def walkdir(self, folder):\\n for dirpath, dirs, files in os.walk(folder):\\n for filename in files:\\n yield os.path.abspath(os.path.join(dirpath, filename))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7423802","0.73017514","0.72350556","0.7135453","0.7109446","0.7099377","0.7064924","0.70476","0.70066994","0.6970505","0.6923695","0.6891978","0.6889596","0.6840696","0.6823787","0.6811101","0.68091035","0.6807877","0.68076265","0.6768948","0.67390597","0.6706383","0.66786087","0.66707945","0.6669001","0.66659164","0.6649527","0.6640997","0.66364527","0.66337353","0.662022","0.6619813","0.6616121","0.66103256","0.660104","0.65860707","0.6583699","0.6580229","0.65742403","0.6556558","0.65552425","0.6548691","0.6548342","0.6543828","0.65423214","0.6535151","0.6534435","0.65253645","0.65241975","0.652255","0.6518348","0.6515845","0.6494966","0.6492553","0.64769936","0.64710706","0.6455551","0.6455551","0.6452857","0.64485496","0.64485496","0.64485496","0.64477926","0.6445457","0.644259","0.64343935","0.6401996","0.6400085","0.63993454","0.6397469","0.63904333","0.6377231","0.63691705","0.636813","0.6359914","0.6357955","0.63558334","0.6349657","0.63467646","0.63465106","0.6343891","0.6334193","0.6332725","0.6330065","0.63290656","0.63258904","0.6306285","0.63024837","0.6297997","0.6293621","0.6292391","0.6290045","0.62900066","0.62791806","0.627871","0.6277108","0.6275494","0.62724614","0.6271773","0.6259763"],"string":"[\n \"0.7423802\",\n \"0.73017514\",\n \"0.72350556\",\n \"0.7135453\",\n \"0.7109446\",\n \"0.7099377\",\n \"0.7064924\",\n \"0.70476\",\n \"0.70066994\",\n \"0.6970505\",\n \"0.6923695\",\n \"0.6891978\",\n \"0.6889596\",\n \"0.6840696\",\n \"0.6823787\",\n \"0.6811101\",\n \"0.68091035\",\n \"0.6807877\",\n \"0.68076265\",\n \"0.6768948\",\n \"0.67390597\",\n \"0.6706383\",\n \"0.66786087\",\n \"0.66707945\",\n \"0.6669001\",\n \"0.66659164\",\n \"0.6649527\",\n \"0.6640997\",\n \"0.66364527\",\n \"0.66337353\",\n \"0.662022\",\n \"0.6619813\",\n \"0.6616121\",\n \"0.66103256\",\n \"0.660104\",\n \"0.65860707\",\n \"0.6583699\",\n \"0.6580229\",\n \"0.65742403\",\n \"0.6556558\",\n \"0.65552425\",\n \"0.6548691\",\n \"0.6548342\",\n \"0.6543828\",\n \"0.65423214\",\n \"0.6535151\",\n \"0.6534435\",\n \"0.65253645\",\n \"0.65241975\",\n \"0.652255\",\n \"0.6518348\",\n \"0.6515845\",\n \"0.6494966\",\n \"0.6492553\",\n \"0.64769936\",\n \"0.64710706\",\n \"0.6455551\",\n \"0.6455551\",\n \"0.6452857\",\n \"0.64485496\",\n \"0.64485496\",\n \"0.64485496\",\n \"0.64477926\",\n \"0.6445457\",\n \"0.644259\",\n \"0.64343935\",\n \"0.6401996\",\n \"0.6400085\",\n \"0.63993454\",\n \"0.6397469\",\n \"0.63904333\",\n \"0.6377231\",\n \"0.63691705\",\n \"0.636813\",\n \"0.6359914\",\n \"0.6357955\",\n \"0.63558334\",\n \"0.6349657\",\n \"0.63467646\",\n \"0.63465106\",\n \"0.6343891\",\n \"0.6334193\",\n \"0.6332725\",\n \"0.6330065\",\n \"0.63290656\",\n \"0.63258904\",\n \"0.6306285\",\n \"0.63024837\",\n \"0.6297997\",\n \"0.6293621\",\n \"0.6292391\",\n \"0.6290045\",\n \"0.62900066\",\n \"0.62791806\",\n \"0.627871\",\n \"0.6277108\",\n \"0.6275494\",\n \"0.62724614\",\n \"0.6271773\",\n \"0.6259763\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7272002"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":88566,"cells":{"query":{"kind":"string","value":"For a list of packages, find the package_data This function scans the subdirectories of a package and considers all nonsubmodule subdirectories as resources, including them in the package_data Returns a dictionary suitable for setup(package_data=)"},"document":{"kind":"string","value":"def find_package_data(packages):\n package_data = {}\n for package in packages:\n package_data[package] = []\n for subdir in find_subdirectories(package):\n if '.'.join((package, subdir)) in packages: # skip submodules\n logging.debug(\"skipping submodule %s/%s\" % (package, subdir))\n continue\n if skip_tests and (subdir == 'tests'): # skip tests\n logging.debug(\"skipping tests %s/%s\" % (package, subdir))\n continue\n package_data[package] += subdir_findall(package_to_path(package), subdir)\n return package_data"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_package_data(package):\n walk = [(dirpath.replace(package + os.sep, '', 1), filenames)\n for dirpath, dirnames, filenames in os.walk(package)\n if not os.path.exists(os.path.join(dirpath, '__init__.py'))]\n\n filepaths = []\n for base, filenames in walk:\n filepaths.extend([os.path.join(base, filename)\n for filename in filenames])\n return {package: filepaths}","def get_package_data(package):\n walk = [\n (dirpath.replace(package + os.sep, '', 1), filenames)\n for dirpath, dirnames, filenames in os.walk(package)\n if not os.path.exists(\n os.path.join(dirpath, '__init__.py')\n )\n ]\n\n filepaths = []\n for base, filenames in walk:\n filepaths.extend([\n os.path.join(base, filename) for filename in filenames\n ])\n return {package: filepaths}","def find_package_data(data_root, package_root):\n files = []\n for root, dirnames, filenames in os.walk(data_root):\n for fn in filenames:\n files.append(relpath(join(root, fn), package_root))\n return files","def find_package_data(package):\n walk = [(dirpath.replace(package + os.sep, '', 1), filenames)\n for dirpath, dirnames, filenames in os.walk(package)]\n\n filepaths = []\n for base, filenames in walk:\n filepaths.extend([os.path.join(base, filename)\n for filename in filenames])\n return filepaths","def get_package_data_files(package, data, package_dir=None):\n if package_dir is None:\n package_dir = os.path.join(*package.split('.'))\n all_files = []\n for f in data:\n path = os.path.join(package_dir, f)\n if os.path.isfile(path):\n all_files.append(f)\n continue\n for root, _dirs, files in os.walk(path, followlinks=True):\n root = os.path.relpath(root, package_dir)\n for file in files:\n file = os.path.join(root, file)\n if file not in all_files:\n all_files.append(file)\n return all_files","def find_package_data(module, path):\n files = []\n exclude = re.compile(\"\\.pyc$|~$\")\n for dirpath, dirnames, filenames in os.walk(os.path.join(module,path)):\n for filename in filenames:\n if not exclude.search(filename):\n files.append(os.path.relpath(os.path.join(dirpath,filename),module))\n return {module:files}","def find_data_files_setuptools(self, package, src_dir):\n from glob import glob\n import itertools\n import os\n\n patterns = self._get_platform_patterns(\n self.package_data,\n package,\n src_dir,\n )\n globs_expanded = map(glob, patterns)\n # flatten the expanded globs into an iterable of matches\n globs_matches = itertools.chain.from_iterable(globs_expanded)\n glob_files = [e for e in globs_matches if os.path.isfile(e) or os.path.islink(e)]\n files = itertools.chain(\n self.manifest_files.get(package, []),\n glob_files,\n )\n return self.exclude_data_files(package, src_dir, files)","def walk_package(pkgname, root):\n dirs = []\n files = []\n for name in pkg_resources.resource_listdir(pkgname, str(root)):\n fullname = root / name\n if pkg_resources.resource_isdir(pkgname, str(fullname)):\n dirs.append(fullname)\n else:\n files.append(Path(name))\n for new_path in dirs:\n yield from walk_package(pkgname, new_path)\n yield root, dirs, files","def get_package_data(self, prefix=None):\n\n # glob all the files in dist_dir then filter out py & ext files\n root = _Path(self._get_dist_dir(prefix))\n excludes = [\".py\", sysconfig.get_config_var(\"EXT_SUFFIX\")]\n files = [\n f\n for f in root.rglob(\"**/*\")\n if f.is_file() and not any(f.name.endswith(e) for e in excludes)\n ]\n\n # find the parent package of each file and add to the package_data\n package_data = {}\n for f in files:\n pkg_dir = next(d for d in f.parents if (d / \"__init__.py\").is_file())\n pkg_name = _dir_to_pkg(\n self.package_name, pkg_dir.relative_to(root).as_posix()\n )\n pkg_path = f.relative_to(pkg_dir).as_posix()\n if pkg_name in package_data:\n package_data[pkg_name].append(pkg_path)\n else:\n package_data[pkg_name] = [pkg_path]\n\n return package_data","def find_packages(cls, chroot, log=None):\n base = os.path.join(chroot.path(), cls.SOURCE_ROOT)\n packages, namespace_packages = set(), set()\n resources = defaultdict(set)\n\n def iter_files():\n for root, _, files in safe_walk(base):\n module = os.path.relpath(root, base).replace(os.path.sep, '.')\n for filename in files:\n yield module, filename, os.path.join(root, filename)\n\n # establish packages, namespace packages in first pass\n for module, filename, real_filename in iter_files():\n if filename != '__init__.py':\n continue\n packages.add(module)\n if cls.declares_namespace_package(real_filename):\n namespace_packages.add(module)\n\n # second pass establishes non-source content (resources)\n for module, filename, real_filename in iter_files():\n if filename.endswith('.py'):\n if module not in packages:\n # TODO(wickman) Consider changing this to a full-on error as it\n # could indicate bad BUILD hygiene.\n # raise cls.UndefinedSource('%s is source but does not belong to a package!' % filename)\n if log:\n log.warn('%s is source but does not belong to a package.' % real_filename)\n else:\n continue\n submodule = cls.nearest_subpackage(module, packages)\n if submodule == module:\n resources[submodule].add(filename)\n else:\n assert module.startswith(submodule + '.')\n relative_module = module[len(submodule) + 1:]\n relative_filename = os.path.join(relative_module.replace('.', os.path.sep), filename)\n resources[submodule].add(relative_filename)\n\n return packages, namespace_packages, resources","def get_package_resources(self):\n resources = []\n for pkg in self.packages:\n resource_data = self.get_resource_data()\n resources.extend(pkg.get_resources(resource_data))\n return resources","def copy_package_data(self, package, target_dir):\n exts = [ i[0] for i in imp.get_suffixes() ]\n exts.append('.py')\n exts.append('.pyc')\n exts.append('.pyo')\n def datafilter(item):\n for e in exts:\n if item.endswith(e):\n return False\n return True\n\n target_dir = os.path.join(target_dir, *(package.identifier.split('.')))\n for dname in package.packagepath:\n filenames = list(filter(datafilter, zipio.listdir(dname)))\n for fname in filenames:\n if fname in ('.svn', 'CVS', '.hg', '.git'):\n # Scrub revision manager junk\n continue\n if fname in ('__pycache__',):\n # Ignore PEP 3147 bytecode cache\n continue\n if fname.startswith('.') and fname.endswith('.swp'):\n # Ignore vim(1) temporary files\n continue\n if fname.endswith('~') or fname.endswith('.orig'):\n # Ignore backup files for common tools (hg, emacs, ...)\n continue\n pth = os.path.join(dname, fname)\n\n # Check if we have found a package, exclude those\n if zipio.isdir(pth):\n # XXX: the 'and not' part is wrong, need to fix zipio.isdir\n for p in zipio.listdir(pth):\n if p.startswith('__init__.') and p[8:] in exts:\n break\n\n else:\n if os.path.isfile(pth):\n # Avoid extracting a resource file that happens\n # to be zipfile.\n # XXX: Need API in zipio for nicer code.\n copy_file(pth, os.path.join(target_dir, fname))\n else:\n copy_tree(pth, os.path.join(target_dir, fname))\n continue\n\n elif zipio.isdir(pth) and (\n zipio.isfile(os.path.join(pth, '__init__.py'))\n or zipio.isfile(os.path.join(pth, '__init__.pyc'))\n or zipio.isfile(os.path.join(pth, '__init__.pyo'))):\n # Subdirectory is a python package, these will get included later on\n # when the subpackage itself is included, ignore for now.\n pass\n\n else:\n copy_file(pth, os.path.join(target_dir, fname))","def __gather_package_data(arguments):\n ignore_patterns, packages_path, search_packages_path = _resolve_arguments(\n arguments.ignore_patterns,\n arguments.packages_path,\n arguments.search_packages_path,\n )\n rez_packages = set(arguments.rez_packages)\n\n package_finder = registry.get_package_finder(arguments.command)\n\n found_packages = []\n packages, invalid_packages, skips = package_finder(\n paths=packages_path + search_packages_path\n )\n\n for package in packages:\n if rez_packages and package.name not in rez_packages:\n skips.append(package)\n else:\n found_packages.append(package)\n\n ignored_packages, other_packages = _split_the_ignored_packages(\n found_packages, ignore_patterns\n )\n\n other_packages = sorted(other_packages, key=operator.attrgetter(\"name\"))\n\n return ignored_packages, other_packages, invalid_packages, skips","def find_packages( root ):\n for path, directories, files in os.walk( root ):\n if is_package( path ):\n yield path.replace( '/','.' )","def load_package_data() -> list[dict[str, Any]]:\n import jsonschema\n\n schema = _load_schema()\n result = []\n for provider_yaml_path in get_provider_yaml_paths():\n with open(provider_yaml_path) as yaml_file:\n provider = yaml.safe_load(yaml_file)\n try:\n jsonschema.validate(provider, schema=schema)\n except jsonschema.ValidationError:\n raise Exception(f\"Unable to parse: {provider_yaml_path}.\")\n if provider[\"suspended\"]:\n continue\n provider_yaml_dir = os.path.dirname(provider_yaml_path)\n provider[\"python-module\"] = _filepath_to_module(provider_yaml_dir)\n provider[\"package-dir\"] = provider_yaml_dir\n provider[\"system-tests-dir\"] = _filepath_to_system_tests(provider_yaml_dir)\n result.append(provider)\n return result","def find_packages(self):\n\n # scan src_dir for __init__.py\n root = _Path(self.src_dir)\n reg_paths = set(\n [d.parent.relative_to(root) for d in root.rglob(\"**/__init__.py\")]\n )\n\n # add all namespace packages that houses regular packages\n pkg_paths = set(reg_paths)\n for dir in reg_paths:\n pkg_paths |= set(dir.parents)\n\n # convert path to str\n pkg_dirs = [path.as_posix() for path in pkg_paths]\n\n # convert dir to package notation\n return [_dir_to_pkg(self.package_name, dir) for dir in pkg_dirs]","def find_data_files_distutils(self, package, src_dir):\n from glob import glob\n import os\n from distutils.util import convert_path\n\n globs = (self.package_data.get('', [])\n + self.package_data.get(package, []))\n files = []\n for pattern in globs:\n # Each pattern has to be converted to a platform-specific path\n filelist = glob(os.path.join(src_dir, convert_path(pattern)))\n # Files that match more than one pattern are only added once\n files.extend([fn for fn in filelist if fn not in files\n and (os.path.isfile(fn) or os.path.islink(fn))])\n return files","def _get_package_files(self) -> Dict[str, 'BinPackageFile']:\n\n if self._package_files is None:\n manifest_path = f\"{self.path}/packagemanifest\"\n manifest_urlpath = f\"{self.path}/packages/files/packagemanifest\"\n self.project.storage.download(manifest_urlpath, manifest_path)\n files = BinPackageFile.from_package_manifest(self.project.storage.fspath(manifest_path))\n self._package_files = {pf.extract_path: pf for pf in files}\n return self._package_files","def prepare_packages(self) -> None:\n self.local_packages = []\n self.remote_packages = []\n self.debuginfo_packages = []\n self.repository_packages = []\n\n # Detect local, debuginfo and repository packages\n for package in self.packages:\n if re.match(r\"^http(s)?://\", package):\n self.remote_packages.append(package)\n elif package.endswith(\".rpm\"):\n self.local_packages.append(Path(package))\n elif re.search(r\"-debug(info|source)(\\.|$)\", package):\n # Strip the '-debuginfo' string from package name\n # (installing with it doesn't work on RHEL7)\n package = re.sub(r\"-debuginfo((?=\\.)|$)\", \"\", package)\n self.debuginfo_packages.append(package)\n else:\n self.repository_packages.append(package)\n\n # Check rpm packages in local directories\n for directory in self.directories:\n self.info('directory', str(directory), 'green')\n if not directory.is_dir():\n raise tmt.utils.PrepareError(f\"Packages directory '{directory}' not found.\")\n for filepath in directory.iterdir():\n if filepath.suffix == '.rpm':\n self.debug(f\"Found rpm '{filepath}'.\", level=3)\n self.local_packages.append(filepath)","def get_packages(package):\n return [dirpath\n for dirpath, dirnames, filenames in os.walk(package)\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]","def get_packages(package):\n return [dirpath\n for dirpath, dirnames, filenames in os.walk(package)\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]","def get_packages(package):\n return [dirpath\n for dirpath, dirnames, filenames in os.walk(package)\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]","def get_packages(package):\n return [\n dirpath\n for dirpath, dirnames, filenames in os.walk(package)\n if os.path.exists(os.path.join(dirpath, '__init__.py'))\n ]","def load_all_packages():\n\n package_dict = dict((n, load_component_by_name(n))\n for n in list_packages())\n\n return package_dict","def get_data() -> dict:\n project_dir = Path(__file__).parent.parent\n metadata = toml.load(project_dir / \"pyproject.toml\")[\"tool\"][\"poetry\"]\n lock_data = toml.load(project_dir / \"poetry.lock\")\n project_name = metadata[\"name\"]\n\n poetry_dependencies = chain(metadata[\"dependencies\"].keys(), metadata[\"dev-dependencies\"].keys())\n direct_dependencies = sorted(dep.lower() for dep in poetry_dependencies)\n direct_dependencies.remove(\"python\")\n\n indirect_dependencies = sorted(\n pkg[\"name\"] for pkg in lock_data[\"package\"] if pkg[\"name\"] not in direct_dependencies\n )\n\n dependencies = direct_dependencies + indirect_dependencies\n packages = {pkg[\"name\"]: clean_info(pkg) for pkg in search_packages_info(dependencies)}\n # poetry.lock seems to always use lowercase for packages names\n packages.update({name.lower(): pkg for name, pkg in packages.items()}) # noqa: WPS221 (not that complex)\n\n for dependency in dependencies:\n if dependency not in packages:\n pkg_data = httpx.get(f\"https://pypi.python.org/pypi/{dependency}/json\").json()[\"info\"]\n home_page = pkg_data[\"home_page\"] or pkg_data[\"project_url\"] or pkg_data[\"package_url\"]\n pkg_name = pkg_data[\"name\"]\n pkg = {\"name\": pkg_name, \"home-page\": home_page}\n packages.update({pkg_name: pkg, pkg_name.lower(): pkg})\n\n return {\n \"project_name\": project_name,\n \"direct_dependencies\": direct_dependencies,\n \"indirect_dependencies\": indirect_dependencies,\n \"package_info\": packages,\n }","def find_subdirectories(package):\n try:\n subdirectories = next(os.walk(package_to_path(package)))[1]\n except StopIteration:\n subdirectories = []\n return subdirectories","def find_all_packages_to_test(root, options):\n if options.verbose:\n print_message(\"Locating packages under '%s'\" % root)\n tests = []\n dirs = os.listdir(root)\n dirs.sort()\n for packageName in dirs:\n if packageName.startswith(\".\"):\n continue\n package_dir = os.path.join(root, packageName)\n if not os.path.isdir(package_dir):\n continue\n bam_dir = os.path.join(package_dir, 'bam')\n if not os.path.isdir(bam_dir):\n continue\n xml_files = glob.glob(os.path.join(bam_dir, \"*.xml\"))\n if len(xml_files) == 0:\n continue\n if len(xml_files) > 1:\n raise RuntimeError(\"Too many XML files found in %s to identify a package definition file\" % bam_dir)\n package = Package.from_xml(xml_files[0])\n if options.verbose:\n print_message(\"\\t%s\" % package.get_id())\n tests.append(package)\n return tests","def my_find_packages(*args):\n import os\n packages = []\n for root_module_dir in args:\n for root, dirs, files in os.walk(root_module_dir):\n if '__init__.py' in files:\n packages.append(root)\n return packages","def find_packages(name, pkg_dir):\n for c in (FileSystemPackageBuilder, ZipPackageBuilder, ExcelPackageBuilder):\n\n package_path, cache_path = c.make_package_path(pkg_dir, name)\n\n if package_path.exists():\n\n yield c.type_code, package_path, cache_path #c(package_path, pkg_dir)","def packages():","def get_data_files():\n return [\n ('share/jupyter/nbextensions/{}'.format(PY_PACKAGE), TARGETS),\n ('share/jupyter/lab/extensions', [\n os.path.relpath(f, '.') for f in glob.glob(TAR_PATH)\n ])\n ]","def scan ( self, **kw ):\n stats = self.STATS\n stats.scan_time.begin ( self.name )\n for subdir in os.listdir ( self.physical_location ):\n if self.has_dir ( subdir ):\n pkgdir = self._get_package_dir ( subdir )\n try:\n pkgdir.scan ( stats=stats, **kw )\n finally:\n if pkgdir.empty():\n del self._subdirs [subdir]\n\n stats.scan_time.end ( self.name )","def _find_files_to_package(self, path):\n for root, dirs, files in os.walk(path):\n root_parts = pathlib.Path(root).relative_to(path).parts\n if self._include_directory(root_parts):\n for f in files:\n if self._include_file(root_parts, f):\n yield pathlib.Path(root, f)","def recurse_tree(rootpath_or_module, excludes, opts, use_module):\n # use absolute path for root, as relative paths like '../../foo' cause\n # 'if \"/.\" in root ...' to filter out *all* modules otherwise\n if use_module:\n rootpath = get_module_path(rootpath_or_module)\n else:\n rootpath = os.path.abspath(rootpath_or_module)\n\n if use_module:\n package_name = rootpath_or_module\n else:\n # check if the base directory is a package and get is name\n if INITPY in os.listdir(rootpath):\n package_name = rootpath.split(path.sep)[-1]\n else:\n package_name = None\n toc = []\n tree = os.walk(rootpath, False)\n for root, subs, files in tree:\n # keep only the Python script files\n py_files = sorted([f for f in files if path.splitext(f)[1] == '.py'])\n if INITPY in py_files:\n py_files.remove(INITPY)\n py_files.insert(0, INITPY)\n # remove hidden ('.') and private ('_') directories\n subs = sorted([sub for sub in subs if sub[0] not in ['.', '_']])\n # check if there are valid files to process\n # could add check for windows hidden files\n if \"/.\" in root or \"/_\" in root \\\n or not py_files \\\n or is_excluded(root, excludes):\n continue\n if INITPY in py_files:\n # we are in package ...\n if ( # ... with subpackage(s)\n subs\n or\n # ... with some module(s)\n len(py_files) > 1\n or\n # ... with a not-to-be-skipped INITPY file\n not shall_skip(path.join(root, INITPY))\n ):\n subroot = root[len(rootpath):].lstrip(path.sep).\\\n replace(path.sep, '.')\n create_package_file(root, package_name, subroot,\n py_files, opts, subs)\n toc.append(makename(package_name, subroot))\n elif root == rootpath:\n # if we are at the root level, we don't require it to be a package\n for py_file in py_files:\n if not shall_skip(path.join(rootpath, py_file)):\n module = path.splitext(py_file)[0]\n create_module_file(package_name, module, opts)\n toc.append(makename(package_name, module))\n\n # create the module's index\n if not opts.notoc:\n create_modules_toc_file(package_name, toc, opts)","def find_data(self):\n data_list = []\n for root, dirs, files in os.walk(pathfinder.data_path()):\n for name in files:\n data_list.append(os.path.join(root, name))\n return data_list","def get_packages_with_prefixes():\n return get_resources('packages')","def read_metadata():\n subdirs = next(os.walk(os.getcwd()))[1]\n\n for subdir in subdirs:\n if '__init__.py' in os.listdir(subdir):\n print('Found package:', subdir)\n break\n else:\n raise SetupError('No package found! Did you forget an __init__.py?')\n\n metadata = {'name': subdir, 'packages': [subdir]}\n relevant_keys = {'__version__': 'version',\n '__author__': 'author',\n '__email__': 'author_email',\n '__license__': 'license'}\n\n m = open(os.path.join(subdir), '__init__.py')\n first_line = next(m)\n metadata['description'] = first_line.strip(). strip('\\n \"')\n for line in m:\n if len(relevant_keys) == 0:\n break\n for key in relevant_keys:\n if line.startswith(key):\n break\n else:\n continue\n\n metadatum_name = relevant_keys.pop(key)\n metadata[metadatum_name] = line.split('=', 1)[1].strip('\\n\\'\\\" ')\n\n if relevant_keys:\n print('FYI; You didn\\'t put the following info in your __init__.py:')\n print(' ', ', '.join(relevant_keys))\n return metadata","def _get_package_data() -> list[list[str]]:\n moddata = []\n modlist: tuple[str, ...] = (\n \"click\",\n \"cryptography\",\n \"globus_cli\",\n \"globus_sdk\",\n \"jmespath\",\n \"requests\",\n )\n if verbosity() < 2:\n modlist = (\"globus_cli\", \"globus_sdk\", \"requests\")\n\n for mod in modlist:\n cur = [mod]\n try:\n loaded_mod = __import__(mod)\n except ImportError:\n loaded_mod = None\n\n for attr in (\"__version__\", \"__file__\", \"__path__\"):\n # if loading failed, be sure to pad with error messages\n if loaded_mod is None:\n cur.append(\"[import failed]\")\n continue\n\n try:\n attrval = getattr(loaded_mod, attr)\n except AttributeError:\n attrval = \"\"\n cur.append(attrval)\n moddata.append(cur)\n\n return moddata","def findPackages(self, pkgcode, packages=None):\n if not packages:\n if (self.system_pkgcode and pkgcode == self.system_pkgcode):\n scanlist = ['language-pack', 'language-support-fonts', 'language-support-input', 'language-support-writing']\n else:\n scanlist = ['language-pack']\n for x in scanlist:\n pkg = '%s-%s' % (x, pkgcode)\n if pkg in self._cache:\n if not self._cache[pkg].is_installed and \\\n not self._cache[pkg].marked_install:\n self.missing.add(pkg)\n else:\n self.installed.add(pkg)\n \n if pkgcode in self.pkg_translations:\n for (pkg, translation) in self.pkg_translations[pkgcode]:\n if packages:\n if pkg in packages and \\\n pkg in self._cache and \\\n translation in self._cache:\n if ((not self._cache[translation].is_installed and \\\n not self._cache[translation].marked_install and \\\n not self._cache[translation].marked_upgrade) or \\\n self._cache[translation].marked_delete):\n self.missing.add(translation)\n else:\n self.installed.add(translation)\n else:\n if pkg in self._cache and \\\n (self._cache[pkg].is_installed or \\\n self._cache[pkg].marked_install or \\\n self._cache[pkg].marked_upgrade) and \\\n translation in self._cache:\n if ((not self._cache[translation].is_installed and \\\n not self._cache[translation].marked_install and \\\n not self._cache[translation].marked_upgrade) or \\\n self._cache[translation].marked_delete):\n self.missing.add(translation)\n else:\n self.installed.add(translation)\n \n if pkgcode in self.pkg_writing and \\\n (pkgcode == self.system_pkgcode or \\\n ('language-support-writing-%s' % pkgcode in self._cache and \\\n self._cache['language-support-writing-%s' % pkgcode].is_installed) or \\\n ('language-support-writing-%s' % pkgcode in self._cache and \\\n self._cache['language-support-writing-%s' % pkgcode].mark_install) or \\\n ('language-support-writing-%s' % pkgcode in self._cache and \\\n self._cache['language-support-writing-%s' % pkgcode].markUpgrade)):\n for (pkg, pull_pkg) in self.pkg_writing[pkgcode]:\n if '|' in pkg:\n # multiple dependencies, if one of them is installed, pull the pull_pkg\n for p in pkg.split('|'):\n if packages:\n if p in packages and \\\n p in self._cache and \\\n pull_pkg in self._cache:\n if ((not self._cache[pull_pkg].is_installed and \\\n not self._cache[pull_pkg].marked_install and \\\n not self._cache[pull_pkg].marked_upgrade) or \\\n self._cache[pull_pkg].marked_delete):\n self.missing.add(pull_pkg)\n else:\n self.installed.add(pull_pkg)\n break\n else:\n if p in self._cache and \\\n (self._cache[p].is_installed or \\\n self._cache[p].marked_install or \\\n self._cache[p].marked_upgrade) and \\\n pull_pkg in self._cache:\n if ((not self._cache[pull_pkg].is_installed and \\\n not self._cache[pull_pkg].marked_install and \\\n not self._cache[pull_pkg].marked_upgrade) or \\\n self._cache[pull_pkg].marked_delete):\n self.missing.add(pull_pkg)\n else:\n self.installed.add(pull_pkg)\n break\n else:\n if packages:\n if pkg in packages and \\\n pkg in self._cache and \\\n pull_pkg in self._cache:\n if ((not self._cache[pull_pkg].is_installed and \\\n not self._cache[pull_pkg].marked_install and \\\n not self._cache[pull_pkg].marked_upgrade) or \\\n self._cache[pull_pkg].marked_delete):\n self.missing.add(pull_pkg)\n else:\n self.installed.add(pull_pkg)\n else:\n if pkg in self._cache and \\\n (self._cache[pkg].is_installed or \\\n self._cache[pkg].marked_install or \\\n self._cache[pkg].marked_upgrade) and \\\n pull_pkg in self._cache:\n if ((not self._cache[pull_pkg].is_installed and \\\n not self._cache[pull_pkg].marked_install and \\\n not self._cache[pull_pkg].marked_upgrade) or \\\n self._cache[pull_pkg].marked_delete):\n self.missing.add(pull_pkg)\n else:\n self.installed.add(pull_pkg)","def __init__(self, package_ymls=None, script_jsons=None, exclude_blocks=None):\n if package_ymls is None:\n package_ymls = []\n if script_jsons is None:\n script_jsons = []\n\n self.packages = {}\n self.unqualified_components = {}\n\n self.script_json_packages = []\n self.exclude_blocks = exclude_blocks\n\n package_ymls = package_ymls or []\n self.yaml_packages = [ YamlPackageData(f) for f in package_ymls ]\n self.script_json_packages = [ ScriptsJsonPackage(pkg_name, scripts_json_file) for \n pkg_name, scripts_json_file in script_jsons ]\n\n all_packages = self.yaml_packages + self.script_json_packages\n\n for p in all_packages:\n if p.key in self.packages:\n raise Exception(\"Duplicate package: \" + p.key)\n self.packages[p.key] = p\n for component_name, file_data in p.components.iteritems():\n self.unqualified_components.setdefault(component_name, []).append(file_data)\n\n # Resolve script_json dependencies\n for p in self.script_json_packages:\n for fd in p.components.itervalues():\n try:\n fd.resolve_dependencies(self)\n except: \n LOG.exception(\"Error in %s\" % p.scripts_json_filename)\n raise\n try:\n self.strip_blocks()\n except:\n LOG.exception(\"Depender could not strip the required code blocks.\")\n\n try:\n self.self_check()\n except:\n LOG.exception(\"Depender self check failed. Continuing with abandon.\")","def get_packages(root):\n root = os.path.realpath(root)\n proot = parent(root) + \"/\"\n py_files = [file.rsplit(proot)[1] for file in listfiles(root)]\n packages = list(np.unique([parent(file).replace(\"/\", \".\") for file in py_files]))\n # return list(np.unique([parent(file).replace(\"/\", \".\").split(\".{name_root}.\".format(name_root=name(root)))[1]\n # for file in py_files]))\n return packages","def describe_package(name: str, dev_directory: 'Path', uml_data: dict) -> dict:\n\n logging.getLogger('GUM Dispenser').info('Starting processing for package ' + name + '...')\n\n uml_data['packages'][name] = {'modules' : {}}\n\n expected_path = dev_directory.joinpath(name)\n\n logging.getLogger('GUM Dispenser').debug('Expecting package at ' + str(expected_path))\n\n # Stop if package doesn't exist\n\n if not expected_path.exists() or not expected_path.is_dir():\n\n raise(PackageNotFoundError(name))\n\n # Do __init__ check first to see if included modules are defined there\n\n logging.getLogger('GUM Dispenser').info('Checking for __init__.py...')\n\n init_path = Path(str(expected_path) + '/__init__.py')\n\n # Get a list of all the modules we are checking\n\n package_modules = check_init_file(name, init_path)\n\n # Get required data for UML markup\n\n for module_name in package_modules:\n\n uml_data = describe_module(name, module_name, expected_path, uml_data)\n\n return uml_data","def filepaths(self) -> Dict[str, 'BinPackageFile']:\n return self._get_package_files()","def get_package_list(*args):\n logger.debug(\"Loading package list\")\n package_list_filepath = Base.get_package_list_filepath()\n\n # check package list file is valid\n logger.debug(\"Checking filepath\")\n package_list_file_valid = Base.check_package_list_file(package_list_filepath)\n if package_list_file_valid == 1:\n logger.error(\"Package file missing, please run `gitget setup`\")\n exit(1)\n elif package_list_file_valid == 2:\n logger.error(\n \"Package file is a directory, please remove `.gitget.yaml` and run `gitget setup`\"\n )\n exit(1)\n elif package_list_file_valid == 0:\n logger.debug(\"Package file found\")\n\n # try loading the file\n logger.debug(\"Attempting to load file\")\n try:\n with open(package_list_filepath) as file:\n package_list = yaml.safe_load(file)\n except Exception as ex:\n logger.error(\"Could not load package list due to the following error:\")\n logger.error(ex)\n exit(1)\n logger.debug(\"Package list loaded\")\n\n # if the list is NONE, set to an empty dictionary to prevent iteration errors\n logger.debug(\"Checking if package list is None\")\n if package_list is None:\n package_list = {}\n logger.debug(\"Package list has no content, set to empty dict\")\n return package_list","def walkdirs(root):\r\n scriptype_paths = collections.defaultdict(set)\r\n for root, subdirs, files in os.walk(root):\r\n\r\n # Filter subdirs\r\n tmpdir = []\r\n for i in subdirs:\r\n if i.startswith(EXCLUDE_PATTERNS):\r\n continue\r\n if '__init__.py' in os.listdir(os.path.join(root, i)):\r\n scriptype_paths['python'].add(root)\r\n continue\r\n tmpdir.append(i)\r\n subdirs[:] = tmpdir\r\n\r\n # If files with extension exists add to right source type.\r\n if ext_exists('.py', files):\r\n scriptype_paths['python'].add(root)\r\n if ext_exists('.mel', files):\r\n scriptype_paths['mel'].add(root)\r\n return scriptype_paths","def get_package_data(dataname, asfile=False):\n import inspect\n import os\n dirpath = os.path.dirname(inspect.stack()[1][1])\n datapath = dirpath+'/data/'+dataname\n print datapath\n return get_data(datapath, asfile=asfile)","def scan_fixtures(path):\n results = list()\n for root, dirs, files in os.walk(path):\n relative_path = root.replace(path + \"/\", \"\")\n if relative_path.startswith(\"static\") or relative_path.startswith(\"theme\"):\n continue\n\n for f in files:\n if not f.endswith(\".json\"):\n continue\n\n app_name = os.path.basename(os.path.dirname(relative_path))\n\n results.append((app_name, f, relative_path))\n\n return results","def parse_all_controlfiles(dirs: List[Path]) -> Dict[str, BinaryPackage]:\n pkgs = {}\n for path in dirs:\n if not Path(path / \"debian/control\").exists():\n continue\n pkgs.update(parse_controlfile(path))\n return pkgs","def _get_all_pkg_info(self):\n all_pkgs = self._filter_pkgs(self._go_list(\"./...\"))\n # for every package, list the deps, the test files, the test imports, and the external package test imports\n big_list = self._go_list(\n \"-f\", \"{{.ImportPath}}:{{.Deps}}:{{.TestImports}}:{{.XTestImports}}\", *all_pkgs)\n recursive_deps = {}\n test_imports = {}\n\n for line in big_list:\n tokens = [token.strip().lstrip('[').rstrip(']').strip() for token in line.split(\":\", 3)]\n pkg = tokens[0].strip()\n\n recursive_deps[pkg] = set(self._filter_pkgs(tokens[1].split() + [pkg]))\n if tokens[2] or tokens[3]:\n test_imports[pkg] = set(\n self._filter_pkgs(tokens[2].split()) + self._filter_pkgs(tokens[3].split()))\n\n return recursive_deps, test_imports","def find_packages(paths=(os.curdir,), exclude=()):\n packages = []\n discarded = []\n\n def _discarded(path):\n for discard in discarded:\n if _under(path, discard):\n return True\n return False\n\n for path in paths:\n path = convert_path(path)\n for root, dirs, files in os.walk(path):\n for dir_ in dirs:\n fullpath = os.path.join(root, dir_)\n if _discarded(fullpath):\n continue\n # we work only with Python packages\n if not _is_package(fullpath):\n discarded.append(fullpath)\n continue\n # see if it's excluded\n excluded = False\n package_name = _package_name(path, fullpath)\n for pattern in exclude:\n if fnmatchcase(package_name, pattern):\n excluded = True\n break\n if excluded:\n continue\n\n # adding it to the list\n packages.append(package_name)\n return packages","def compare_resource_get_new_datasets(data_packages_path):\n \n for name in glob.glob(f'{data_packages_path}/data-json-*.json'):\n package = Package(name)\n data_json = package.get_resource('inline')\n data_json_data = data_json.source\n\n yield data_json_data\n\n # Delete the data.json file\n os.remove(name)","def find_data_dirs(cls, directory,\n basedata_dir=c.WORDS_DIR,\n markables_dir=c.MARKABLES_DIR,\n dirs_to_ignore=c.DIRS_TO_IGNORE):\n dirs_to_ignore = set(dirs_to_ignore)\n for subdir, subsubdirs, _ in os.walk(directory):\n if os.path.basename(subdir) in dirs_to_ignore:\n continue\n has_words = basedata_dir in subsubdirs\n has_markables = markables_dir in subsubdirs\n if has_words and has_markables:\n logger.debug(f\"subdir: {subdir}\")\n yield subdir\n elif has_markables:\n logger.warn(\n f\"{subdir} has a markables directory ({markables_dir}),\"\n f\" but no words directory ({basedata_dir}).\"\n )\n elif has_words:\n logger.warn(\n f\"{subdir} has a words directory ({basedata_dir}), but no\"\n f\" markables directory ({markables_dir}).\"\n )","def get_setup_data_files(self):\n data_files = CMakeBuilder.default_setup_data_files\n if gitutil.has_submodules():\n data_files.append(\".gitmodules\")\n data_files.append(\n os.path.join(self.dist_dir, gitutil.gitmodules_status_name)\n )\n return [(\"\", data_files)]","def get_packages(package):\n return [str(path.parent) for path in Path(package).glob(\"**/__init__.py\")]","def test_3_recursive(self):\n\n bronze = fmri.PkgFmri(self.published[4], None)\n\n # Retrieve bronze recursively to a directory, this should\n # also retrieve its dependency: amber, and amber's dependency:\n # tree.\n self.pkgrecv(self.durl1, \"--raw -r -k -d {0} {1}\".format(self.tempdir,\n bronze))\n\n amber = fmri.PkgFmri(self.published[1], None)\n tree = fmri.PkgFmri(self.published[5], None)\n\n # Verify that the manifests for each package was retrieved.\n for f in (amber, bronze, tree):\n mpath = os.path.join(self.tempdir, f.get_dir_path(),\n \"manifest\")\n self.assertTrue(os.path.isfile(mpath))","def packages_in_folder(path):\n for pkg_path in catkin_pkg.packages.find_package_paths(path):\n yield os.path.join(path, pkg_path)","def _find_rpms_in_packages(koji_api, name_list, major_minor):\n rpms_for_package = {}\n tags = _tags_for_version(major_minor)\n for package in name_list:\n for tag in tags:\n for build in koji_api.getLatestBuilds(tag=tag, package=package):\n rpm_list = set(rpm[\"name\"] for rpm in koji_api.listBuildRPMs(build[\"build_id\"]))\n rpms_for_package.setdefault(package, set()).update(rpm_list)\n\n if package not in rpms_for_package:\n # it wasn't in our tags; look for it by name\n pkg_info = koji_api.getPackage(package)\n if not pkg_info:\n continue\n latest_builds = koji_api.listBuilds(packageID=pkg_info[\"id\"], state=1, queryOpts=dict(limit=1))\n if not latest_builds:\n continue\n rpm_list = set(rpm[\"name\"] for rpm in koji_api.listBuildRPMs(latest_builds[0][\"build_id\"]))\n rpms_for_package[package] = set(rpm_list)\n\n return rpms_for_package","def get_data_files():\n\n data_files = []\n for d, dirs, filenames in os.walk(share_jupyterhub):\n rel_d = os.path.relpath(d, here)\n data_files.append((rel_d, [os.path.join(rel_d, f) for f in filenames]))\n return data_files","def get_package_python_paths(package, paths):\n # Note: Here we're trying to get `package`'s specific changes to PYTHONPATH (if any)\n #\n # Unfortunately, the Rez API doesn't really support this yet.\n # There's 2 GitHub links that may one-day implement it though:\n # - https://github.com/nerdvegas/rez/issues/737\n # - https://github.com/nerdvegas/rez/pull/739\n #\n # Reference: https://rez-talk.slack.com/archives/CHELFCTFB/p1578604659006100\n #\n # Once that work is merged, replace `get_package_python_paths` with it.\n #\n root = finder.get_package_root(package)\n\n if is_built_package(package):\n return {path for path in paths if filer.in_directory(path, root, follow=False)}\n\n output = set()\n\n for path in paths:\n # If the Rez package is a source Rez package + has variants\n # we need to strip the \"variants\" out of `path`, before\n # returning it.\n #\n try:\n variant_less_path = next(\n _iter_variant_extracted_paths(root, path, package.variants or [])\n )\n except StopIteration:\n pass\n else:\n output.add(variant_less_path)\n\n continue\n\n if filer.in_directory(path, root, follow=False) or filer.in_directory(\n path, root, follow=True\n ):\n output.add(path)\n\n continue\n\n return output","def load_data_files() -> Dict[str, Path]:\n default_path = paths.MISCELLANEOUS_DIRECTORY / \"portfolio\"\n custom_exports = (\n get_current_user().preferences.USER_PORTFOLIO_DATA_DIRECTORY / \"optimization\"\n )\n data_files = {}\n for directory in [default_path, custom_exports]:\n for file_type in [\"xlsx\", \"ini\"]:\n for filepath in Path(directory).rglob(f\"*.{file_type}\"):\n if filepath.is_file() and \"example\" not in filepath.name:\n data_files[filepath.name] = filepath\n\n return data_files","def FindPackagesToScan(settings, startdir, reposplit):\n\n\tdef AddPackagesInDir(path):\n\t\t\"\"\" Given a list of dirs, add any packages in it \"\"\"\n\t\tret = []\n\t\tpkgdirs = os.listdir(path)\n\t\tfor d in pkgdirs:\n\t\t\tif d == 'CVS' or d.startswith('.'):\n\t\t\t\tcontinue\n\t\t\tp = os.path.join(path, d)\n\n\t\t\tif os.path.isdir(p):\n\t\t\t\tcat_pkg_dir = os.path.join(*p.split(os.path.sep)[-2:])\n\t\t\t\tlogging.debug('adding %s to scanlist' % cat_pkg_dir)\n\t\t\t\tret.append(cat_pkg_dir)\n\t\treturn ret\n\n\tscanlist = []\n\trepolevel = len(reposplit)\n\tif repolevel == 1: # root of the tree, startdir = repodir\n\t\tfor cat in settings.categories:\n\t\t\tpath = os.path.join(startdir, cat)\n\t\t\tif not os.path.isdir(path):\n\t\t\t\tcontinue\n\t\t\tscanlist.extend(AddPackagesInDir(path))\n\telif repolevel == 2: # category level, startdir = catdir\n\t\t# We only want 1 segment of the directory,\n\t\t# this is why we use catdir instead of startdir.\n\t\tcatdir = reposplit[-2]\n\t\tif catdir not in settings.categories:\n\t\t\tlogging.warn(\n\t\t\t\t'%s is not a valid category according to profiles/categories, '\n\t\t\t\t'skipping checks in %s' % (catdir, catdir))\n\t\telse:\n\t\t\tscanlist = AddPackagesInDir(catdir)\n\telif repolevel == 3: # pkgdir level, startdir = pkgdir\n\t\tcatdir = reposplit[-2]\n\t\tpkgdir = reposplit[-1]\n\t\tif catdir not in settings.categories:\n\t\t\tlogging.warn(\n\t\t\t\t'%s is not a valid category according to profiles/categories, '\n\t\t\t\t'skipping checks in %s' % (catdir, catdir))\n\t\telse:\n\t\t\tpath = os.path.join(catdir, pkgdir)\n\t\t\tlogging.debug('adding %s to scanlist' % path)\n\t\t\tscanlist.append(path)\n\treturn scanlist","def collect_children(self, recursive=True):\n self.children = []\n\n for fname in os.listdir(self.path):\n path = join(self.path, fname)\n\n if Package.is_pkg(path):\n child = Package.create(path, owner=self)\n if recursive:\n child.collect_children()\n\n elif Module.is_module(path):\n child = Module.create(path, owner=self)\n\n else:\n if util.get_verbosity_level() > 0:\n print(\"Skipping: {}\".format(path))\n continue\n\n self.children.append(child)","def find_with_deps(self, package_names):","def find_packages(self, meta):\n package_name = None\n\n # find which package contains our binary\n dpkg_s_nginx_out, dpkg_s_nginx_err = subp.call('dpkg -S %s' % self.object.bin_path, check=False)\n for line in dpkg_s_nginx_out:\n kv = re.match(self.dpkg_s_re, line)\n if kv:\n package_name = kv.group(1)\n break\n\n if dpkg_s_nginx_err:\n if 'no_path' in dpkg_s_nginx_err[0]:\n meta['warnings'].append('self-made binary, is not from any nginx package')\n\n if not package_name:\n return\n\n # get version\n all_installed_packages = self.installed_nginx_packages()\n\n if package_name in all_installed_packages:\n meta['packages'] = {package_name: all_installed_packages[package_name]}","def get_data_files():\n data_files = []\n\n # Walk through the data directory, adding all files\n data_generator = os.walk('pypeit/data')\n for path, directories, files in data_generator:\n for f in files:\n data_path = '/'.join(path.split('/')[1:])\n data_files.append(os.path.join(data_path, f))\n\n # Add pipeline and spectrograph settings\n settings = glob.glob('pypeit/settings/settings.*')\n settings = ['/'.join(path.split('/')[1:]) for path in settings]\n data_files.extend(settings)\n\n return data_files","def get_resource(package_name, resource):\n # Path of the package, relative to the loader root:\n # For package 'foo.bar', this is 'foo/bar'.\n package_path = package_name.replace(\".\", \"/\")\n\n # Path of the resource, relative to the loader root:\n # For package 'foo.bar' and resource 'subdir/data.csv', this is \"foo/bar/subdir/data.csv\".\n resource_path = os.path.join(package_path, resource)\n\n # Iterate over all the contributors for the specified package:\n try:\n package = importlib.import_module(package_name)\n except ImportError:\n # Package or module does not exist:\n logging.debug(\"Resource %r from package %r not found\", resource, package_name)\n return None\n\n for path in package.__path__:\n # 'path' is the absolute package path within a specific loader:\n # For package 'foo.bar' in a loader for a Zip file '/path/to/archive.zip',\n # this is: '/path/to/archive.zip/foo/bar'.\n logging.debug(\"Attempting to load resource %r from %r\", resource, path)\n\n assert path.endswith(package_path), \\\n \"Package path mismatch: {!r} does not include package {!r}\".format(path, package_path)\n loader_path = path[:-(len(package_path) + 1)]\n if os.path.isdir(loader_path):\n # FileFinder importers do not implement get_data().\n # We have to handle direct files explicitly:\n resource_fullpath = os.path.join(loader_path, resource_path)\n if os.path.exists(resource_fullpath):\n with open(resource_fullpath, mode=\"rb\") as f:\n logging.debug(\"Found resource %r in %r\", resource, resource_fullpath)\n return f.read()\n else:\n # Handle ZIP (and other) file loaders:\n # Loaders are expected to implement get_data(resource_path).\n try:\n importer = sys.path_importer_cache[loader_path]\n content = importer.get_data(resource_path)\n logging.debug(\"Found resource %r in %r\",\n resource, os.path.join(loader_path, resource_path))\n return content\n except OSError:\n logging.debug(\"Resource %r not found in loader %r\", resource, loader_path)\n # Ignore error and try next package path.\n\n # Specified resource not found in any loader:\n logging.debug(\"Resource %r from package %r not found\", resource, package_name)\n return None","def collect_pypi_data():\n\n rclient = xmlrpc.client.ServerProxy('http://pypi.python.org/pypi')\n python = {'Programming Language :: Python': rclient.browse(['Programming Language :: Python'])}\n python_two = {}\n python_three = {}\n\n for classifier in [\n 'Programming Language :: Python :: 2',\n 'Programming Language :: Python :: 2.3',\n 'Programming Language :: Python :: 2.4',\n 'Programming Language :: Python :: 2.5',\n 'Programming Language :: Python :: 2.6',\n 'Programming Language :: Python :: 2.7',\n 'Programming Language :: Python :: 2 :: Only']:\n python_two[classifier] = rclient.browse([classifier])\n\n for classifier in [\n 'Programming Language :: Python :: 3',\n 'Programming Language :: Python :: 3.0',\n 'Programming Language :: Python :: 3.1',\n 'Programming Language :: Python :: 3.2',\n 'Programming Language :: Python :: 3.3',\n 'Programming Language :: Python :: 3.4']:\n python_three[classifier] = rclient.browse([classifier])\n\n return {datetime.datetime.now().strftime('%Y-%m-%dT%H:%M:%S'):\n {'python': python,\n 'python_two': python_two,\n 'python_three': python_three}}","def packages(self):\n\n if self._packages:\n return self._packages\n\n self._load()\n return self._packages","def list(self, ignore_patterns):\n for storage in six.itervalues(self.storages):\n if storage.exists(''): # check if storage location exists\n for path in utils.get_files(storage, ignore_patterns):\n # for packagers we only accept specifics packages, library and versions (meaning sublib needs lib)\n splitted_path = path.split(os.path.sep)\n\n packager = self.packagers.get(splitted_path[0], None)\n found = False\n\n # others prefix that are not specified into installed_packagers are\n # probably normal django applications\n if splitted_path[0] in self.installed_packagers:\n if packager:\n for library in packager:\n # split to have sublib when parent lib is not imported\n if splitted_path[2] == library[0].split('.')[0]:\n if splitted_path[3] in library[1]:\n # found package.library(version)\n found = True\n break\n else:\n found = True\n\n if not found:\n continue\n\n yield path, storage","def list_packages(self):\n\n # First extract loaded module names from sys.modules\n sys_modules = sys.modules.keys()\n\n packages = {}\n\n # First add moduels in sys.modules (built-ins,\n # preloads and already loaded ones)\n for name in sys_modules:\n d = self.find_package(name)\n if not d: continue\n try:\n pkginfo = packages[d['type']]\n pkginfo[d['name']] = d['path']\n except Exception, e:\n packages[d['type']] = { d['name'] : d['path'] }\n\n #import site\n # Loop through all directories in sys.path and check for modules\n # Dont iterate through <prefix>/lib directory\n libdir = os.path.join(sys.prefix, 'lib')\n\n walked = []\n for top_level in self.paths:\n if not os.path.isdir(top_level):\n continue\n\n # Dont iterate through libdir\n if os.path.abspath(top_level) == os.path.abspath(libdir):\n continue\n\n walked.append(top_level)\n for item in os.listdir(top_level):\n\n fullpath = os.path.join(top_level, item)\n if fullpath in walked: continue\n\n walked.append(fullpath)\n # Remove the extension\n idx = item.find('.')\n if idx != -1: item = item[:idx]\n d = self.find_package(item)\n if not d: continue\n try:\n pkginfo = packages[d['type']]\n pkginfo[d['name']] = d['path']\n except Exception, e:\n packages[d['type']] = { d['name'] : d['path'] } \n\n for key,item in packages.items():\n print\n print self.pkgTypeInfo(key)\n print\n\n # Print sorted\n listofitems = item.keys()\n listofitems.sort()\n\n for key2 in listofitems:\n print key2,':',item[key2]","def find_files_for_package(self, package, absolute_path=False):\n package_files = []\n for p in package.package_versions:\n package_files.extend(self.find_files_for_packageversion(p, absolute_path))\n return package_files","def go_package_dirs(packages, build_tags):\n\n target_packages = []\n for pkg in packages:\n target_packages += (\n check_output(\n f\"go list -find -f \\\"{{{{ .Dir }}}}\\\" -mod=mod -tags \\\"{','.join(build_tags)}\\\" {pkg}\",\n shell=True,\n )\n .decode('utf-8')\n .strip()\n .split(\"\\n\")\n )\n\n return target_packages","def collect():\n\n # Get database.\n with open(local_directory(path='file_diffs/packages.json'), 'r') as f:\n store = json.load(f)\n\n # UI.\n print('Checking files for differences...\\n')\n\n # Iterate database.\n for package_name in store:\n # Package variables.\n package_dir = os.path.join(package_directory, package_name)\n package = store[package_name]\n\n # Recursive (lazy) package searching.\n if type(package) == str:\n package = os.path.expanduser(package)\n for dirpath, dirnames, filenames in os.walk(package):\n for filename in filenames:\n sub_package_dir = package_dir + dirpath.replace(package, '')\n if not os.path.exists(sub_package_dir):\n os.makedirs(sub_package_dir)\n\n fp_local = os.path.join(dirpath, filename)\n fp_remote = os.path.join(sub_package_dir, filename)\n\n cs_local = file_checksum(fp=fp_local)\n cs_remote = file_checksum(fp=fp_remote)\n\n if cs_remote != cs_local:\n print('Found: {}/{}'.format(package_name, filename))\n shutil.copyfile(src=fp_local, dst=fp_remote)\n\n # Manual package searching.\n if type(package) == list:\n for fp in package:\n fn_local = fp['local']\n fn_remote = fp['remote']\n\n fp_local = os.path.expanduser(fn_local)\n fp_remote = os.path.join(package_dir, fn_remote)\n\n cs_local = file_checksum(fp=fp_local)\n cs_remote = file_checksum(fp=fp_remote)\n\n if cs_remote != cs_local:\n print('Found: {}/{}'.format(package_name, fn_remote))\n\n remote_dir_path = '/'.join(fp_remote.split('/')[:-1])\n if not os.path.exists(remote_dir_path):\n os.makedirs(remote_dir_path)\n shutil.copyfile(src=fp_local, dst=fp_remote)","def get_packages():\n\tapps=[]\n\tlspackages = glob.glob(u'/home/wpkg/packages/*.xml')\n\tfor fic in lspackages:\n #print fic\n\t\tif os.path.isfile(fic):\n\t\t\ttry:\n\t\t\t\txml = etree.parse(fic)\n\t\t\texcept:\n\t\t\t\t#si erreur on tente de corriger le fichier\n\t\t\t\toput = open(\"output.txt\",\"w\")\n\t\t\t\tdata = open(fic).read()\n\t\t\t\toput.write( re.sub('&(?!amp;|quot;|nbsp;|gt;|lt;|laquo;|raquo;|copy;|reg;|bul;|rsquo;)', '&', data) )\n\t\t\t\toput.close()\n\t\t\t\tshutil.move(\"output.txt\", fic)\n\n\t\t\tfinally:\n\t\t\t\tparser = etree.XMLParser(remove_comments=False)\n\t\t\t\txml = etree.parse(fic,parser)\n\t\t\t\tstrxml = etree.tostring(xml.getroot())\n\t\t\t\tfor group in xml.getiterator(u'package'):\n\t\t\t\t\tuid = group.get(u'id')\n\t\t\t\t\tname = group.get(u'name')\n\t\t\t\t\tdvars = dict()\n\t\t\t\t\tfor vars in xml.getiterator('variable'):\n\t\t\t\t\t\tdvars[vars.get('name').lower()] = vars.get('value').lower()\n\n\t\t\t\t#on remplit le dico des appli dispo\n\t\t\t\t#print fic,uid,name\n\t\t\t\tapps.append((fic,uid,name))\n\n\treturn apps","def getData(self):\n\t\treturn self.golang_project_packages","def command_package_ls(*args):\n\n # Setup build, install, and data directories\n package_dirs = os.listdir(packages_path())\n\n for packname in package_dirs:\n # Filter to directories with config files\n if not os.path.isdir(package_path(packname)): continue\n if not package_load_config(packname): continue\n\n # Check for installation\n installed_flag = ''\n installdir = install_dir(packname)\n bindir = os.path.join(installdir, 'bin')\n # This is just a very basic sanity check for binaries we\n # require\n binfiles = (os.path.exists(bindir) and os.listdir(bindir)) or []\n if ( ('space' in binfiles or 'space_d' in binfiles) and\n ('cppoh' in binfiles or 'cppoh_d' in binfiles) ):\n installed_flag = '*'\n\n print packname, installed_flag\n\n return 0","def get_templates_dirs(self): \n from pkg_resources import resource_filename\n return [ resource_filename(__name__, 'templates') ]\n # return []","def _po_package_contents(self, package):\n po_files = glob(os.path.join(package['source_dir'], '*.po'))\n for po_file in po_files:\n language = os.path.splitext(os.path.basename(po_file))[0]\n lang_dir = os.path.join(package['build_dir'], language)\n msg_dir = os.path.join(lang_dir, 'LC_MESSAGES')\n mo_file = os.path.join(msg_dir, package['name'] + '.mo')\n yield {'language': language,\n 'lang_dir': lang_dir,\n 'msg_dir': msg_dir,\n 'mo_file': mo_file,\n 'po_file': po_file}","def repo_fs():\n for root, dirs, files in os.walk(\".\"):\n dirs[:] = [ # add any extra dirs to ignore #\n d for d in dirs\n if '.' not in d\n and 'ENV' not in d\n and '__' not in d\n and 'build' not in d\n ]\n\n for f in files:\n if f.endswith(\".py\"):\n if not f.startswith('__'):\n ALL_PY_FILES.append(os.path.join(root, f))\n PY_FILES.append(os.path.join(root, f))\n if f.endswith(\".yml\"):\n YML_FILES.append(os.path.join(root, f))\n if f.startswith(\"requirements\"):\n PIP_FILES.append(os.path.join(root, f))\n if f.startswith(\"development\"):\n DEV_FILES.append(os.path.join(root, f))\n if f.startswith(\"README.md\"):\n README_FILES.append(os.path.join(root, f))\n if f.startswith(\"LICENSE\"):\n LICENSE.append(os.path.join(root, f))\n if f.startswith(\"CONTRIBUTIONS\"):\n CONTRIBUTIONS.append(os.path.join(root, f))\n\n if PY_FILES:\n parse_files()\n\n return { # dictionary with all lists of file path/names #\n 'PY_FILES': PY_FILES,\n 'YML_FILES': YML_FILES,\n 'PIP_FILES': PIP_FILES,\n 'README_FILES': README_FILES,\n 'TEST_FILES': TEST_FILES,\n 'LICENSE': LICENSE,\n 'URL_FILES': URL_FILES,\n 'CONTRIBUTIONS': CONTRIBUTIONS,\n 'SETUP_FILES': SETUP_FILES,\n 'MODEL_FILES': MODEL_FILES,\n 'SETTINGS_FILES': SETTINGS_FILES,\n 'DEV_FILES': DEV_FILES,\n }","def packages(self):\n return []","def fixture_sets(*args):\n return [os.path.join(*args, dir)\n for dir in os.listdir(os.path.join(FIXTURE_DATA, *args))\n if os.path.isdir(os.path.join(FIXTURE_DATA, *args, dir))\n ]","def get_resources(self, resource_data=None):\n if not resource_data and self.component:\n resource_data = self.component.get_resource_data()\n\n resources = []\n for resource in self.files:\n resource.update(resource_data)\n\n resource['storage_path'] = self.prefix + '/' + resource['name']\n relative_path = self.relative_path(data=resource)\n resource['relative_path'] = relative_path\n resource['url'] = resource['url'] + '/' + relative_path\n resources.append(resource)\n return resources","def get_fallback_packages(request, package_name):\n dists = request.locator.get_project(package_name)\n pkgs = {}\n for version, url_set in six.iteritems(dists.get('urls', {})):\n dist = dists[version]\n for url in url_set:\n filename = posixpath.basename(url)\n url = request.app_url('api', 'package', dist.name, filename)\n pkgs[filename] = url\n return pkgs","def write_manifest ( self, **manifest_kw ):\n for package in self._subdirs.values():\n package.write_manifest ( **manifest_kw )","def get_problematic_packages(\n package_data: List[Mapping[str, str]]\n) -> List[Mapping[str, str]]:\n white_listed_packages = get_whitelisted_packages()\n problematic_packages = []\n for p in package_data:\n license_name_upper = p[\"License\"].upper()\n package_name_upper = p[\"Name\"].upper()\n if (\n license_name_upper not in LICENSE_WHITELIST\n and package_name_upper not in white_listed_packages\n ):\n problematic_packages.append(p)\n elif (\n package_name_upper in white_listed_packages\n and white_listed_packages[package_name_upper]\n and white_listed_packages[package_name_upper] != license_name_upper\n ):\n problematic_packages.append(p)\n\n return problematic_packages","def _load_dirs(self):\n rootdirs = self._docset.get_compounds(xml.Directory,\n lambda x: x.get_parent() is None)\n for dirdoc in rootdirs:\n self._load_dir(dirdoc, None)","def parse_paths():\r\n sources = get_source_paths()\r\n results = collections.defaultdict(list)\r\n for root_dir in sources:\r\n\r\n for script_type, dirs in walkdirs(root_dir).iteritems():\r\n\r\n for d in dirs:\r\n logger.debug(d)\r\n\r\n # Add paths to environments\r\n if os.path.basename(d).lower().startswith(ICONS):\r\n results['XBMLANGPATH'].append(d)\r\n os.environ['XBMLANGPATH'] += os.pathsep + d\r\n\r\n if script_type == 'mel':\r\n results['MAYA_SCRIPT_PATH'].append(d)\r\n os.environ['MAYA_SCRIPT_PATH'] += os.pathsep + d\r\n else:\r\n results['PYTHONPATH'].append(d)\r\n site.addsitedir(d)\r\n return results","def _walk_dir_meta(self):\n for key, child in sorted(self._children.items()):\n if isinstance(child, PackageEntry):\n continue\n meta = child.meta\n if meta:\n yield key + '/', meta\n for child_key, child_meta in child._walk_dir_meta():\n yield key + '/' + child_key, child_meta","def find_requirements(root: str) -> Optional[Dict[str, bool]]:\n findings = {\n file_name: os.path.isfile(os.path.join(root, file_name))\n for file_name in [\"requirements.txt\", \"Pipfile\", \"Pipfile.lock\"]\n }\n\n if not sum(findings.values()):\n return None\n return findings","def getusersitepackages():\n\tpass","def fact():\n manifests = [x for x in os.walk(manifests_dir)]\n\n return { 'manifests': manifests }","def setup_module(module):\n for datafile in datafiles:\n src = get_pkg_data_filename(os.path.join('data', datafile))\n shutil.copyfile(src, datafile)","def get_package_files(self, package):\n with self._conn.begin():\n return {\n row.filename: row.filehash\n for row in self._conn.execute(\n \"SELECT filename, filehash \"\n \"FROM get_package_files(%s)\", (package,)\n )\n }","def group_by_filenames(self):\n package = self.container.config.output.package\n class_map = collections.group_by(self.container, key=get_location)\n groups = self.group_common_paths(class_map.keys())\n\n for keys in groups:\n if len(keys) == 1:\n common_path = os.path.dirname(keys[0])\n else:\n common_path = os.path.commonpath(keys)\n\n for key in keys:\n items = class_map[key]\n suffix = \".\".join(Path(key).parent.relative_to(common_path).parts)\n\n package_name = f\"{package}.{suffix}\" if suffix else package\n self.assign(items, package_name, module_name(key))","def _walk_dirs(self):\n for project_name in self.new_source_paths.keys():\n # print \"-------- Now mapping ---- \" + project_name\n search_path = self.root + project_name + '\\\\Data'\n for dirpath, subdirs, files in os.walk(search_path):\n for file in files:\n self.new_source_paths[project_name][file] = dirpath\n # print \"------------ Finished mapping ------- \" + project_name\n return self.new_source_paths","def scan(root: str, config: dict) -> dict:\n\n extensions = config['extensions']\n exceptions = config['exceptions']\n\n # get list of directories, with their contents (files and sub-directories)\n dirs_by_path = {\n get_path_from_common_root(dir_path, root): (\n dir_path,\n dir_names,\n [name for name in file_names if is_valid_file_name(name, config)]\n )\n for dir_path, dir_names, file_names in os.walk(root)\n }\n\n dirs_by_path = {key: value for key, value in dirs_by_path.items() if value[1] or value[2]}\n\n # get list of file paths\n file_path_list = [\n (file_dir, file_name)\n for file_dir, _, file_names in dirs_by_path.values()\n for file_name in file_names\n ]\n\n files_by_path = {}\n # todo: put below loop contents into function, used in above list comprehension\n for file_dir, file_name_with_extension in file_path_list:\n # todo: remove code file definition from here to allow this to be reused for non-code related files\n # todo: refactor to use inheritable File class instead of named tuple, to be reused for non-code files\n\n if file_name_with_extension in exceptions:\n continue\n\n file = CodeFile(\n imports=[],\n exports=[],\n local_params=[],\n blocks=[],\n dir=file_dir,\n name=file_name_with_extension.rsplit('.', 1)[0],\n extension=file_name_with_extension.rsplit('.', 1)[1]\n )\n\n parse_file(file, config)\n file_no_dupes = remove_duplicate_entries(file)\n\n dir_key = get_path_from_common_root(file_dir, root)\n if dir_key not in files_by_path:\n files_by_path[dir_key] = []\n\n files_by_path[dir_key].append(file_no_dupes)\n\n return {'dirs_by_path': dirs_by_path, 'files_by_path': files_by_path,\n 'starting_point': get_path_from_common_root(root, root)}","def get_package_folders(which_folder: str = \"root\") -> Path:\n logg = logging.getLogger(f\"c.{__name__}.get_package_folders\")\n # logg.setLevel(\"INFO\")\n logg.debug(\"Start get_package_folders\")\n\n this_file_folder = Path(__file__).absolute().parent\n logg.debug(f\"{this_file_folder=}\")\n\n package_root_folder = this_file_folder.parent.parent.parent\n\n if which_folder == \"root\":\n return package_root_folder\n\n elif which_folder == \"tests\":\n tests_folder = package_root_folder / \"tests\"\n return tests_folder\n\n elif which_folder == \"template_epub\":\n template_epub_folder = package_root_folder / \"assets\" / \"template_epub\"\n return template_epub_folder\n\n elif which_folder == \"word_pairs\":\n word_pairs_folder = package_root_folder / \"assets\" / \"word_pairs\"\n return word_pairs_folder\n\n elif which_folder == \"common_words\":\n common_words_folder = package_root_folder / \"assets\" / \"common_words\"\n return common_words_folder\n\n else:\n raise KeyError(f\"Not recognized {which_folder}\")","def data_files(self, pattern=None, regex=None):\n return self._files_in_subdir(self.data_dir, pattern, regex)","def _LoadPackages():\n return {module.__name__.split('.')[-1]: module for module in\n import_util.LoadModulesForPath(__path__, __name__)}","def check_init_file(name : str, init_path : 'Path') -> list:\n\n # Read __init__ if it exists\n\n package_modules = []\n\n try:\n\n # Check for __all__ global variable assignments\n\n pattern = re.compile(r\"\"\"(?:^__all__\\s*=\\s*)(\\[[^\\[\\]]*\\]$)\"\"\", re.MULTILINE)\n\n with open(str(init_path), 'r') as init_file:\n\n logging.getLogger('GUM Dispenser').info('Found __init__.py')\n\n init_contents = init_file.read()\n\n # Grab the capturing group\n\n init_results = [current_match.group(1).strip() for current_match in pattern.finditer(init_contents)\n if not current_match.group(1) is None and\n not (current_match.group(1).isspace() or current_match.group(1) == '')]\n\n logging.getLogger('GUM Dispenser').debug(init_results)\n\n if len(init_results) > 0:\n\n logging.getLogger('GUM Dispenser').info('Found __all__ declaration. Using ' +\n str(init_results[-1]) + ' as module list')\n\n package_modules = ast.literal_eval(init_results[-1])\n\n\n # Make sure specified modules exist before we go further\n\n ensure_modules_exist(package_modules, init_path.parent)\n\n else:\n\n logging.getLogger('GUM Dispenser').warning('__init__.py __all__ definition was not found for package ' +\n name + '. Treating all same level .py files' +\n ' as included modules...')\n\n # Safely handle case where __init__ does not exist\n except FileNotFoundError:\n\n logging.getLogger('GUM Dispenser').warning('__init__.py does not exist for package ' + name +\n '. Treating all same level .py files as included modules...')\n\n if len(package_modules) == 0:\n\n # Grab all .py files in package directory\n\n src_dir = init_path.parent\n\n logging.getLogger('GUM Dispenser').debug('Parent directory: ' + str(src_dir))\n\n os.chdir(src_dir)\n\n package_modules = glob.glob('*.py')\n\n package_modules = [name.rstrip('.py') for name in package_modules]\n\n\n return package_modules"],"string":"[\n \"def get_package_data(package):\\n walk = [(dirpath.replace(package + os.sep, '', 1), filenames)\\n for dirpath, dirnames, filenames in os.walk(package)\\n if not os.path.exists(os.path.join(dirpath, '__init__.py'))]\\n\\n filepaths = []\\n for base, filenames in walk:\\n filepaths.extend([os.path.join(base, filename)\\n for filename in filenames])\\n return {package: filepaths}\",\n \"def get_package_data(package):\\n walk = [\\n (dirpath.replace(package + os.sep, '', 1), filenames)\\n for dirpath, dirnames, filenames in os.walk(package)\\n if not os.path.exists(\\n os.path.join(dirpath, '__init__.py')\\n )\\n ]\\n\\n filepaths = []\\n for base, filenames in walk:\\n filepaths.extend([\\n os.path.join(base, filename) for filename in filenames\\n ])\\n return {package: filepaths}\",\n \"def find_package_data(data_root, package_root):\\n files = []\\n for root, dirnames, filenames in os.walk(data_root):\\n for fn in filenames:\\n files.append(relpath(join(root, fn), package_root))\\n return files\",\n \"def find_package_data(package):\\n walk = [(dirpath.replace(package + os.sep, '', 1), filenames)\\n for dirpath, dirnames, filenames in os.walk(package)]\\n\\n filepaths = []\\n for base, filenames in walk:\\n filepaths.extend([os.path.join(base, filename)\\n for filename in filenames])\\n return filepaths\",\n \"def get_package_data_files(package, data, package_dir=None):\\n if package_dir is None:\\n package_dir = os.path.join(*package.split('.'))\\n all_files = []\\n for f in data:\\n path = os.path.join(package_dir, f)\\n if os.path.isfile(path):\\n all_files.append(f)\\n continue\\n for root, _dirs, files in os.walk(path, followlinks=True):\\n root = os.path.relpath(root, package_dir)\\n for file in files:\\n file = os.path.join(root, file)\\n if file not in all_files:\\n all_files.append(file)\\n return all_files\",\n \"def find_package_data(module, path):\\n files = []\\n exclude = re.compile(\\\"\\\\.pyc$|~$\\\")\\n for dirpath, dirnames, filenames in os.walk(os.path.join(module,path)):\\n for filename in filenames:\\n if not exclude.search(filename):\\n files.append(os.path.relpath(os.path.join(dirpath,filename),module))\\n return {module:files}\",\n \"def find_data_files_setuptools(self, package, src_dir):\\n from glob import glob\\n import itertools\\n import os\\n\\n patterns = self._get_platform_patterns(\\n self.package_data,\\n package,\\n src_dir,\\n )\\n globs_expanded = map(glob, patterns)\\n # flatten the expanded globs into an iterable of matches\\n globs_matches = itertools.chain.from_iterable(globs_expanded)\\n glob_files = [e for e in globs_matches if os.path.isfile(e) or os.path.islink(e)]\\n files = itertools.chain(\\n self.manifest_files.get(package, []),\\n glob_files,\\n )\\n return self.exclude_data_files(package, src_dir, files)\",\n \"def walk_package(pkgname, root):\\n dirs = []\\n files = []\\n for name in pkg_resources.resource_listdir(pkgname, str(root)):\\n fullname = root / name\\n if pkg_resources.resource_isdir(pkgname, str(fullname)):\\n dirs.append(fullname)\\n else:\\n files.append(Path(name))\\n for new_path in dirs:\\n yield from walk_package(pkgname, new_path)\\n yield root, dirs, files\",\n \"def get_package_data(self, prefix=None):\\n\\n # glob all the files in dist_dir then filter out py & ext files\\n root = _Path(self._get_dist_dir(prefix))\\n excludes = [\\\".py\\\", sysconfig.get_config_var(\\\"EXT_SUFFIX\\\")]\\n files = [\\n f\\n for f in root.rglob(\\\"**/*\\\")\\n if f.is_file() and not any(f.name.endswith(e) for e in excludes)\\n ]\\n\\n # find the parent package of each file and add to the package_data\\n package_data = {}\\n for f in files:\\n pkg_dir = next(d for d in f.parents if (d / \\\"__init__.py\\\").is_file())\\n pkg_name = _dir_to_pkg(\\n self.package_name, pkg_dir.relative_to(root).as_posix()\\n )\\n pkg_path = f.relative_to(pkg_dir).as_posix()\\n if pkg_name in package_data:\\n package_data[pkg_name].append(pkg_path)\\n else:\\n package_data[pkg_name] = [pkg_path]\\n\\n return package_data\",\n \"def find_packages(cls, chroot, log=None):\\n base = os.path.join(chroot.path(), cls.SOURCE_ROOT)\\n packages, namespace_packages = set(), set()\\n resources = defaultdict(set)\\n\\n def iter_files():\\n for root, _, files in safe_walk(base):\\n module = os.path.relpath(root, base).replace(os.path.sep, '.')\\n for filename in files:\\n yield module, filename, os.path.join(root, filename)\\n\\n # establish packages, namespace packages in first pass\\n for module, filename, real_filename in iter_files():\\n if filename != '__init__.py':\\n continue\\n packages.add(module)\\n if cls.declares_namespace_package(real_filename):\\n namespace_packages.add(module)\\n\\n # second pass establishes non-source content (resources)\\n for module, filename, real_filename in iter_files():\\n if filename.endswith('.py'):\\n if module not in packages:\\n # TODO(wickman) Consider changing this to a full-on error as it\\n # could indicate bad BUILD hygiene.\\n # raise cls.UndefinedSource('%s is source but does not belong to a package!' % filename)\\n if log:\\n log.warn('%s is source but does not belong to a package.' % real_filename)\\n else:\\n continue\\n submodule = cls.nearest_subpackage(module, packages)\\n if submodule == module:\\n resources[submodule].add(filename)\\n else:\\n assert module.startswith(submodule + '.')\\n relative_module = module[len(submodule) + 1:]\\n relative_filename = os.path.join(relative_module.replace('.', os.path.sep), filename)\\n resources[submodule].add(relative_filename)\\n\\n return packages, namespace_packages, resources\",\n \"def get_package_resources(self):\\n resources = []\\n for pkg in self.packages:\\n resource_data = self.get_resource_data()\\n resources.extend(pkg.get_resources(resource_data))\\n return resources\",\n \"def copy_package_data(self, package, target_dir):\\n exts = [ i[0] for i in imp.get_suffixes() ]\\n exts.append('.py')\\n exts.append('.pyc')\\n exts.append('.pyo')\\n def datafilter(item):\\n for e in exts:\\n if item.endswith(e):\\n return False\\n return True\\n\\n target_dir = os.path.join(target_dir, *(package.identifier.split('.')))\\n for dname in package.packagepath:\\n filenames = list(filter(datafilter, zipio.listdir(dname)))\\n for fname in filenames:\\n if fname in ('.svn', 'CVS', '.hg', '.git'):\\n # Scrub revision manager junk\\n continue\\n if fname in ('__pycache__',):\\n # Ignore PEP 3147 bytecode cache\\n continue\\n if fname.startswith('.') and fname.endswith('.swp'):\\n # Ignore vim(1) temporary files\\n continue\\n if fname.endswith('~') or fname.endswith('.orig'):\\n # Ignore backup files for common tools (hg, emacs, ...)\\n continue\\n pth = os.path.join(dname, fname)\\n\\n # Check if we have found a package, exclude those\\n if zipio.isdir(pth):\\n # XXX: the 'and not' part is wrong, need to fix zipio.isdir\\n for p in zipio.listdir(pth):\\n if p.startswith('__init__.') and p[8:] in exts:\\n break\\n\\n else:\\n if os.path.isfile(pth):\\n # Avoid extracting a resource file that happens\\n # to be zipfile.\\n # XXX: Need API in zipio for nicer code.\\n copy_file(pth, os.path.join(target_dir, fname))\\n else:\\n copy_tree(pth, os.path.join(target_dir, fname))\\n continue\\n\\n elif zipio.isdir(pth) and (\\n zipio.isfile(os.path.join(pth, '__init__.py'))\\n or zipio.isfile(os.path.join(pth, '__init__.pyc'))\\n or zipio.isfile(os.path.join(pth, '__init__.pyo'))):\\n # Subdirectory is a python package, these will get included later on\\n # when the subpackage itself is included, ignore for now.\\n pass\\n\\n else:\\n copy_file(pth, os.path.join(target_dir, fname))\",\n \"def __gather_package_data(arguments):\\n ignore_patterns, packages_path, search_packages_path = _resolve_arguments(\\n arguments.ignore_patterns,\\n arguments.packages_path,\\n arguments.search_packages_path,\\n )\\n rez_packages = set(arguments.rez_packages)\\n\\n package_finder = registry.get_package_finder(arguments.command)\\n\\n found_packages = []\\n packages, invalid_packages, skips = package_finder(\\n paths=packages_path + search_packages_path\\n )\\n\\n for package in packages:\\n if rez_packages and package.name not in rez_packages:\\n skips.append(package)\\n else:\\n found_packages.append(package)\\n\\n ignored_packages, other_packages = _split_the_ignored_packages(\\n found_packages, ignore_patterns\\n )\\n\\n other_packages = sorted(other_packages, key=operator.attrgetter(\\\"name\\\"))\\n\\n return ignored_packages, other_packages, invalid_packages, skips\",\n \"def find_packages( root ):\\n for path, directories, files in os.walk( root ):\\n if is_package( path ):\\n yield path.replace( '/','.' )\",\n \"def load_package_data() -> list[dict[str, Any]]:\\n import jsonschema\\n\\n schema = _load_schema()\\n result = []\\n for provider_yaml_path in get_provider_yaml_paths():\\n with open(provider_yaml_path) as yaml_file:\\n provider = yaml.safe_load(yaml_file)\\n try:\\n jsonschema.validate(provider, schema=schema)\\n except jsonschema.ValidationError:\\n raise Exception(f\\\"Unable to parse: {provider_yaml_path}.\\\")\\n if provider[\\\"suspended\\\"]:\\n continue\\n provider_yaml_dir = os.path.dirname(provider_yaml_path)\\n provider[\\\"python-module\\\"] = _filepath_to_module(provider_yaml_dir)\\n provider[\\\"package-dir\\\"] = provider_yaml_dir\\n provider[\\\"system-tests-dir\\\"] = _filepath_to_system_tests(provider_yaml_dir)\\n result.append(provider)\\n return result\",\n \"def find_packages(self):\\n\\n # scan src_dir for __init__.py\\n root = _Path(self.src_dir)\\n reg_paths = set(\\n [d.parent.relative_to(root) for d in root.rglob(\\\"**/__init__.py\\\")]\\n )\\n\\n # add all namespace packages that houses regular packages\\n pkg_paths = set(reg_paths)\\n for dir in reg_paths:\\n pkg_paths |= set(dir.parents)\\n\\n # convert path to str\\n pkg_dirs = [path.as_posix() for path in pkg_paths]\\n\\n # convert dir to package notation\\n return [_dir_to_pkg(self.package_name, dir) for dir in pkg_dirs]\",\n \"def find_data_files_distutils(self, package, src_dir):\\n from glob import glob\\n import os\\n from distutils.util import convert_path\\n\\n globs = (self.package_data.get('', [])\\n + self.package_data.get(package, []))\\n files = []\\n for pattern in globs:\\n # Each pattern has to be converted to a platform-specific path\\n filelist = glob(os.path.join(src_dir, convert_path(pattern)))\\n # Files that match more than one pattern are only added once\\n files.extend([fn for fn in filelist if fn not in files\\n and (os.path.isfile(fn) or os.path.islink(fn))])\\n return files\",\n \"def _get_package_files(self) -> Dict[str, 'BinPackageFile']:\\n\\n if self._package_files is None:\\n manifest_path = f\\\"{self.path}/packagemanifest\\\"\\n manifest_urlpath = f\\\"{self.path}/packages/files/packagemanifest\\\"\\n self.project.storage.download(manifest_urlpath, manifest_path)\\n files = BinPackageFile.from_package_manifest(self.project.storage.fspath(manifest_path))\\n self._package_files = {pf.extract_path: pf for pf in files}\\n return self._package_files\",\n \"def prepare_packages(self) -> None:\\n self.local_packages = []\\n self.remote_packages = []\\n self.debuginfo_packages = []\\n self.repository_packages = []\\n\\n # Detect local, debuginfo and repository packages\\n for package in self.packages:\\n if re.match(r\\\"^http(s)?://\\\", package):\\n self.remote_packages.append(package)\\n elif package.endswith(\\\".rpm\\\"):\\n self.local_packages.append(Path(package))\\n elif re.search(r\\\"-debug(info|source)(\\\\.|$)\\\", package):\\n # Strip the '-debuginfo' string from package name\\n # (installing with it doesn't work on RHEL7)\\n package = re.sub(r\\\"-debuginfo((?=\\\\.)|$)\\\", \\\"\\\", package)\\n self.debuginfo_packages.append(package)\\n else:\\n self.repository_packages.append(package)\\n\\n # Check rpm packages in local directories\\n for directory in self.directories:\\n self.info('directory', str(directory), 'green')\\n if not directory.is_dir():\\n raise tmt.utils.PrepareError(f\\\"Packages directory '{directory}' not found.\\\")\\n for filepath in directory.iterdir():\\n if filepath.suffix == '.rpm':\\n self.debug(f\\\"Found rpm '{filepath}'.\\\", level=3)\\n self.local_packages.append(filepath)\",\n \"def get_packages(package):\\n return [dirpath\\n for dirpath, dirnames, filenames in os.walk(package)\\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]\",\n \"def get_packages(package):\\n return [dirpath\\n for dirpath, dirnames, filenames in os.walk(package)\\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]\",\n \"def get_packages(package):\\n return [dirpath\\n for dirpath, dirnames, filenames in os.walk(package)\\n if os.path.exists(os.path.join(dirpath, '__init__.py'))]\",\n \"def get_packages(package):\\n return [\\n dirpath\\n for dirpath, dirnames, filenames in os.walk(package)\\n if os.path.exists(os.path.join(dirpath, '__init__.py'))\\n ]\",\n \"def load_all_packages():\\n\\n package_dict = dict((n, load_component_by_name(n))\\n for n in list_packages())\\n\\n return package_dict\",\n \"def get_data() -> dict:\\n project_dir = Path(__file__).parent.parent\\n metadata = toml.load(project_dir / \\\"pyproject.toml\\\")[\\\"tool\\\"][\\\"poetry\\\"]\\n lock_data = toml.load(project_dir / \\\"poetry.lock\\\")\\n project_name = metadata[\\\"name\\\"]\\n\\n poetry_dependencies = chain(metadata[\\\"dependencies\\\"].keys(), metadata[\\\"dev-dependencies\\\"].keys())\\n direct_dependencies = sorted(dep.lower() for dep in poetry_dependencies)\\n direct_dependencies.remove(\\\"python\\\")\\n\\n indirect_dependencies = sorted(\\n pkg[\\\"name\\\"] for pkg in lock_data[\\\"package\\\"] if pkg[\\\"name\\\"] not in direct_dependencies\\n )\\n\\n dependencies = direct_dependencies + indirect_dependencies\\n packages = {pkg[\\\"name\\\"]: clean_info(pkg) for pkg in search_packages_info(dependencies)}\\n # poetry.lock seems to always use lowercase for packages names\\n packages.update({name.lower(): pkg for name, pkg in packages.items()}) # noqa: WPS221 (not that complex)\\n\\n for dependency in dependencies:\\n if dependency not in packages:\\n pkg_data = httpx.get(f\\\"https://pypi.python.org/pypi/{dependency}/json\\\").json()[\\\"info\\\"]\\n home_page = pkg_data[\\\"home_page\\\"] or pkg_data[\\\"project_url\\\"] or pkg_data[\\\"package_url\\\"]\\n pkg_name = pkg_data[\\\"name\\\"]\\n pkg = {\\\"name\\\": pkg_name, \\\"home-page\\\": home_page}\\n packages.update({pkg_name: pkg, pkg_name.lower(): pkg})\\n\\n return {\\n \\\"project_name\\\": project_name,\\n \\\"direct_dependencies\\\": direct_dependencies,\\n \\\"indirect_dependencies\\\": indirect_dependencies,\\n \\\"package_info\\\": packages,\\n }\",\n \"def find_subdirectories(package):\\n try:\\n subdirectories = next(os.walk(package_to_path(package)))[1]\\n except StopIteration:\\n subdirectories = []\\n return subdirectories\",\n \"def find_all_packages_to_test(root, options):\\n if options.verbose:\\n print_message(\\\"Locating packages under '%s'\\\" % root)\\n tests = []\\n dirs = os.listdir(root)\\n dirs.sort()\\n for packageName in dirs:\\n if packageName.startswith(\\\".\\\"):\\n continue\\n package_dir = os.path.join(root, packageName)\\n if not os.path.isdir(package_dir):\\n continue\\n bam_dir = os.path.join(package_dir, 'bam')\\n if not os.path.isdir(bam_dir):\\n continue\\n xml_files = glob.glob(os.path.join(bam_dir, \\\"*.xml\\\"))\\n if len(xml_files) == 0:\\n continue\\n if len(xml_files) > 1:\\n raise RuntimeError(\\\"Too many XML files found in %s to identify a package definition file\\\" % bam_dir)\\n package = Package.from_xml(xml_files[0])\\n if options.verbose:\\n print_message(\\\"\\\\t%s\\\" % package.get_id())\\n tests.append(package)\\n return tests\",\n \"def my_find_packages(*args):\\n import os\\n packages = []\\n for root_module_dir in args:\\n for root, dirs, files in os.walk(root_module_dir):\\n if '__init__.py' in files:\\n packages.append(root)\\n return packages\",\n \"def find_packages(name, pkg_dir):\\n for c in (FileSystemPackageBuilder, ZipPackageBuilder, ExcelPackageBuilder):\\n\\n package_path, cache_path = c.make_package_path(pkg_dir, name)\\n\\n if package_path.exists():\\n\\n yield c.type_code, package_path, cache_path #c(package_path, pkg_dir)\",\n \"def packages():\",\n \"def get_data_files():\\n return [\\n ('share/jupyter/nbextensions/{}'.format(PY_PACKAGE), TARGETS),\\n ('share/jupyter/lab/extensions', [\\n os.path.relpath(f, '.') for f in glob.glob(TAR_PATH)\\n ])\\n ]\",\n \"def scan ( self, **kw ):\\n stats = self.STATS\\n stats.scan_time.begin ( self.name )\\n for subdir in os.listdir ( self.physical_location ):\\n if self.has_dir ( subdir ):\\n pkgdir = self._get_package_dir ( subdir )\\n try:\\n pkgdir.scan ( stats=stats, **kw )\\n finally:\\n if pkgdir.empty():\\n del self._subdirs [subdir]\\n\\n stats.scan_time.end ( self.name )\",\n \"def _find_files_to_package(self, path):\\n for root, dirs, files in os.walk(path):\\n root_parts = pathlib.Path(root).relative_to(path).parts\\n if self._include_directory(root_parts):\\n for f in files:\\n if self._include_file(root_parts, f):\\n yield pathlib.Path(root, f)\",\n \"def recurse_tree(rootpath_or_module, excludes, opts, use_module):\\n # use absolute path for root, as relative paths like '../../foo' cause\\n # 'if \\\"/.\\\" in root ...' to filter out *all* modules otherwise\\n if use_module:\\n rootpath = get_module_path(rootpath_or_module)\\n else:\\n rootpath = os.path.abspath(rootpath_or_module)\\n\\n if use_module:\\n package_name = rootpath_or_module\\n else:\\n # check if the base directory is a package and get is name\\n if INITPY in os.listdir(rootpath):\\n package_name = rootpath.split(path.sep)[-1]\\n else:\\n package_name = None\\n toc = []\\n tree = os.walk(rootpath, False)\\n for root, subs, files in tree:\\n # keep only the Python script files\\n py_files = sorted([f for f in files if path.splitext(f)[1] == '.py'])\\n if INITPY in py_files:\\n py_files.remove(INITPY)\\n py_files.insert(0, INITPY)\\n # remove hidden ('.') and private ('_') directories\\n subs = sorted([sub for sub in subs if sub[0] not in ['.', '_']])\\n # check if there are valid files to process\\n # could add check for windows hidden files\\n if \\\"/.\\\" in root or \\\"/_\\\" in root \\\\\\n or not py_files \\\\\\n or is_excluded(root, excludes):\\n continue\\n if INITPY in py_files:\\n # we are in package ...\\n if ( # ... with subpackage(s)\\n subs\\n or\\n # ... with some module(s)\\n len(py_files) > 1\\n or\\n # ... with a not-to-be-skipped INITPY file\\n not shall_skip(path.join(root, INITPY))\\n ):\\n subroot = root[len(rootpath):].lstrip(path.sep).\\\\\\n replace(path.sep, '.')\\n create_package_file(root, package_name, subroot,\\n py_files, opts, subs)\\n toc.append(makename(package_name, subroot))\\n elif root == rootpath:\\n # if we are at the root level, we don't require it to be a package\\n for py_file in py_files:\\n if not shall_skip(path.join(rootpath, py_file)):\\n module = path.splitext(py_file)[0]\\n create_module_file(package_name, module, opts)\\n toc.append(makename(package_name, module))\\n\\n # create the module's index\\n if not opts.notoc:\\n create_modules_toc_file(package_name, toc, opts)\",\n \"def find_data(self):\\n data_list = []\\n for root, dirs, files in os.walk(pathfinder.data_path()):\\n for name in files:\\n data_list.append(os.path.join(root, name))\\n return data_list\",\n \"def get_packages_with_prefixes():\\n return get_resources('packages')\",\n \"def read_metadata():\\n subdirs = next(os.walk(os.getcwd()))[1]\\n\\n for subdir in subdirs:\\n if '__init__.py' in os.listdir(subdir):\\n print('Found package:', subdir)\\n break\\n else:\\n raise SetupError('No package found! Did you forget an __init__.py?')\\n\\n metadata = {'name': subdir, 'packages': [subdir]}\\n relevant_keys = {'__version__': 'version',\\n '__author__': 'author',\\n '__email__': 'author_email',\\n '__license__': 'license'}\\n\\n m = open(os.path.join(subdir), '__init__.py')\\n first_line = next(m)\\n metadata['description'] = first_line.strip(). strip('\\\\n \\\"')\\n for line in m:\\n if len(relevant_keys) == 0:\\n break\\n for key in relevant_keys:\\n if line.startswith(key):\\n break\\n else:\\n continue\\n\\n metadatum_name = relevant_keys.pop(key)\\n metadata[metadatum_name] = line.split('=', 1)[1].strip('\\\\n\\\\'\\\\\\\" ')\\n\\n if relevant_keys:\\n print('FYI; You didn\\\\'t put the following info in your __init__.py:')\\n print(' ', ', '.join(relevant_keys))\\n return metadata\",\n \"def _get_package_data() -> list[list[str]]:\\n moddata = []\\n modlist: tuple[str, ...] = (\\n \\\"click\\\",\\n \\\"cryptography\\\",\\n \\\"globus_cli\\\",\\n \\\"globus_sdk\\\",\\n \\\"jmespath\\\",\\n \\\"requests\\\",\\n )\\n if verbosity() < 2:\\n modlist = (\\\"globus_cli\\\", \\\"globus_sdk\\\", \\\"requests\\\")\\n\\n for mod in modlist:\\n cur = [mod]\\n try:\\n loaded_mod = __import__(mod)\\n except ImportError:\\n loaded_mod = None\\n\\n for attr in (\\\"__version__\\\", \\\"__file__\\\", \\\"__path__\\\"):\\n # if loading failed, be sure to pad with error messages\\n if loaded_mod is None:\\n cur.append(\\\"[import failed]\\\")\\n continue\\n\\n try:\\n attrval = getattr(loaded_mod, attr)\\n except AttributeError:\\n attrval = \\\"\\\"\\n cur.append(attrval)\\n moddata.append(cur)\\n\\n return moddata\",\n \"def findPackages(self, pkgcode, packages=None):\\n if not packages:\\n if (self.system_pkgcode and pkgcode == self.system_pkgcode):\\n scanlist = ['language-pack', 'language-support-fonts', 'language-support-input', 'language-support-writing']\\n else:\\n scanlist = ['language-pack']\\n for x in scanlist:\\n pkg = '%s-%s' % (x, pkgcode)\\n if pkg in self._cache:\\n if not self._cache[pkg].is_installed and \\\\\\n not self._cache[pkg].marked_install:\\n self.missing.add(pkg)\\n else:\\n self.installed.add(pkg)\\n \\n if pkgcode in self.pkg_translations:\\n for (pkg, translation) in self.pkg_translations[pkgcode]:\\n if packages:\\n if pkg in packages and \\\\\\n pkg in self._cache and \\\\\\n translation in self._cache:\\n if ((not self._cache[translation].is_installed and \\\\\\n not self._cache[translation].marked_install and \\\\\\n not self._cache[translation].marked_upgrade) or \\\\\\n self._cache[translation].marked_delete):\\n self.missing.add(translation)\\n else:\\n self.installed.add(translation)\\n else:\\n if pkg in self._cache and \\\\\\n (self._cache[pkg].is_installed or \\\\\\n self._cache[pkg].marked_install or \\\\\\n self._cache[pkg].marked_upgrade) and \\\\\\n translation in self._cache:\\n if ((not self._cache[translation].is_installed and \\\\\\n not self._cache[translation].marked_install and \\\\\\n not self._cache[translation].marked_upgrade) or \\\\\\n self._cache[translation].marked_delete):\\n self.missing.add(translation)\\n else:\\n self.installed.add(translation)\\n \\n if pkgcode in self.pkg_writing and \\\\\\n (pkgcode == self.system_pkgcode or \\\\\\n ('language-support-writing-%s' % pkgcode in self._cache and \\\\\\n self._cache['language-support-writing-%s' % pkgcode].is_installed) or \\\\\\n ('language-support-writing-%s' % pkgcode in self._cache and \\\\\\n self._cache['language-support-writing-%s' % pkgcode].mark_install) or \\\\\\n ('language-support-writing-%s' % pkgcode in self._cache and \\\\\\n self._cache['language-support-writing-%s' % pkgcode].markUpgrade)):\\n for (pkg, pull_pkg) in self.pkg_writing[pkgcode]:\\n if '|' in pkg:\\n # multiple dependencies, if one of them is installed, pull the pull_pkg\\n for p in pkg.split('|'):\\n if packages:\\n if p in packages and \\\\\\n p in self._cache and \\\\\\n pull_pkg in self._cache:\\n if ((not self._cache[pull_pkg].is_installed and \\\\\\n not self._cache[pull_pkg].marked_install and \\\\\\n not self._cache[pull_pkg].marked_upgrade) or \\\\\\n self._cache[pull_pkg].marked_delete):\\n self.missing.add(pull_pkg)\\n else:\\n self.installed.add(pull_pkg)\\n break\\n else:\\n if p in self._cache and \\\\\\n (self._cache[p].is_installed or \\\\\\n self._cache[p].marked_install or \\\\\\n self._cache[p].marked_upgrade) and \\\\\\n pull_pkg in self._cache:\\n if ((not self._cache[pull_pkg].is_installed and \\\\\\n not self._cache[pull_pkg].marked_install and \\\\\\n not self._cache[pull_pkg].marked_upgrade) or \\\\\\n self._cache[pull_pkg].marked_delete):\\n self.missing.add(pull_pkg)\\n else:\\n self.installed.add(pull_pkg)\\n break\\n else:\\n if packages:\\n if pkg in packages and \\\\\\n pkg in self._cache and \\\\\\n pull_pkg in self._cache:\\n if ((not self._cache[pull_pkg].is_installed and \\\\\\n not self._cache[pull_pkg].marked_install and \\\\\\n not self._cache[pull_pkg].marked_upgrade) or \\\\\\n self._cache[pull_pkg].marked_delete):\\n self.missing.add(pull_pkg)\\n else:\\n self.installed.add(pull_pkg)\\n else:\\n if pkg in self._cache and \\\\\\n (self._cache[pkg].is_installed or \\\\\\n self._cache[pkg].marked_install or \\\\\\n self._cache[pkg].marked_upgrade) and \\\\\\n pull_pkg in self._cache:\\n if ((not self._cache[pull_pkg].is_installed and \\\\\\n not self._cache[pull_pkg].marked_install and \\\\\\n not self._cache[pull_pkg].marked_upgrade) or \\\\\\n self._cache[pull_pkg].marked_delete):\\n self.missing.add(pull_pkg)\\n else:\\n self.installed.add(pull_pkg)\",\n \"def __init__(self, package_ymls=None, script_jsons=None, exclude_blocks=None):\\n if package_ymls is None:\\n package_ymls = []\\n if script_jsons is None:\\n script_jsons = []\\n\\n self.packages = {}\\n self.unqualified_components = {}\\n\\n self.script_json_packages = []\\n self.exclude_blocks = exclude_blocks\\n\\n package_ymls = package_ymls or []\\n self.yaml_packages = [ YamlPackageData(f) for f in package_ymls ]\\n self.script_json_packages = [ ScriptsJsonPackage(pkg_name, scripts_json_file) for \\n pkg_name, scripts_json_file in script_jsons ]\\n\\n all_packages = self.yaml_packages + self.script_json_packages\\n\\n for p in all_packages:\\n if p.key in self.packages:\\n raise Exception(\\\"Duplicate package: \\\" + p.key)\\n self.packages[p.key] = p\\n for component_name, file_data in p.components.iteritems():\\n self.unqualified_components.setdefault(component_name, []).append(file_data)\\n\\n # Resolve script_json dependencies\\n for p in self.script_json_packages:\\n for fd in p.components.itervalues():\\n try:\\n fd.resolve_dependencies(self)\\n except: \\n LOG.exception(\\\"Error in %s\\\" % p.scripts_json_filename)\\n raise\\n try:\\n self.strip_blocks()\\n except:\\n LOG.exception(\\\"Depender could not strip the required code blocks.\\\")\\n\\n try:\\n self.self_check()\\n except:\\n LOG.exception(\\\"Depender self check failed. Continuing with abandon.\\\")\",\n \"def get_packages(root):\\n root = os.path.realpath(root)\\n proot = parent(root) + \\\"/\\\"\\n py_files = [file.rsplit(proot)[1] for file in listfiles(root)]\\n packages = list(np.unique([parent(file).replace(\\\"/\\\", \\\".\\\") for file in py_files]))\\n # return list(np.unique([parent(file).replace(\\\"/\\\", \\\".\\\").split(\\\".{name_root}.\\\".format(name_root=name(root)))[1]\\n # for file in py_files]))\\n return packages\",\n \"def describe_package(name: str, dev_directory: 'Path', uml_data: dict) -> dict:\\n\\n logging.getLogger('GUM Dispenser').info('Starting processing for package ' + name + '...')\\n\\n uml_data['packages'][name] = {'modules' : {}}\\n\\n expected_path = dev_directory.joinpath(name)\\n\\n logging.getLogger('GUM Dispenser').debug('Expecting package at ' + str(expected_path))\\n\\n # Stop if package doesn't exist\\n\\n if not expected_path.exists() or not expected_path.is_dir():\\n\\n raise(PackageNotFoundError(name))\\n\\n # Do __init__ check first to see if included modules are defined there\\n\\n logging.getLogger('GUM Dispenser').info('Checking for __init__.py...')\\n\\n init_path = Path(str(expected_path) + '/__init__.py')\\n\\n # Get a list of all the modules we are checking\\n\\n package_modules = check_init_file(name, init_path)\\n\\n # Get required data for UML markup\\n\\n for module_name in package_modules:\\n\\n uml_data = describe_module(name, module_name, expected_path, uml_data)\\n\\n return uml_data\",\n \"def filepaths(self) -> Dict[str, 'BinPackageFile']:\\n return self._get_package_files()\",\n \"def get_package_list(*args):\\n logger.debug(\\\"Loading package list\\\")\\n package_list_filepath = Base.get_package_list_filepath()\\n\\n # check package list file is valid\\n logger.debug(\\\"Checking filepath\\\")\\n package_list_file_valid = Base.check_package_list_file(package_list_filepath)\\n if package_list_file_valid == 1:\\n logger.error(\\\"Package file missing, please run `gitget setup`\\\")\\n exit(1)\\n elif package_list_file_valid == 2:\\n logger.error(\\n \\\"Package file is a directory, please remove `.gitget.yaml` and run `gitget setup`\\\"\\n )\\n exit(1)\\n elif package_list_file_valid == 0:\\n logger.debug(\\\"Package file found\\\")\\n\\n # try loading the file\\n logger.debug(\\\"Attempting to load file\\\")\\n try:\\n with open(package_list_filepath) as file:\\n package_list = yaml.safe_load(file)\\n except Exception as ex:\\n logger.error(\\\"Could not load package list due to the following error:\\\")\\n logger.error(ex)\\n exit(1)\\n logger.debug(\\\"Package list loaded\\\")\\n\\n # if the list is NONE, set to an empty dictionary to prevent iteration errors\\n logger.debug(\\\"Checking if package list is None\\\")\\n if package_list is None:\\n package_list = {}\\n logger.debug(\\\"Package list has no content, set to empty dict\\\")\\n return package_list\",\n \"def walkdirs(root):\\r\\n scriptype_paths = collections.defaultdict(set)\\r\\n for root, subdirs, files in os.walk(root):\\r\\n\\r\\n # Filter subdirs\\r\\n tmpdir = []\\r\\n for i in subdirs:\\r\\n if i.startswith(EXCLUDE_PATTERNS):\\r\\n continue\\r\\n if '__init__.py' in os.listdir(os.path.join(root, i)):\\r\\n scriptype_paths['python'].add(root)\\r\\n continue\\r\\n tmpdir.append(i)\\r\\n subdirs[:] = tmpdir\\r\\n\\r\\n # If files with extension exists add to right source type.\\r\\n if ext_exists('.py', files):\\r\\n scriptype_paths['python'].add(root)\\r\\n if ext_exists('.mel', files):\\r\\n scriptype_paths['mel'].add(root)\\r\\n return scriptype_paths\",\n \"def get_package_data(dataname, asfile=False):\\n import inspect\\n import os\\n dirpath = os.path.dirname(inspect.stack()[1][1])\\n datapath = dirpath+'/data/'+dataname\\n print datapath\\n return get_data(datapath, asfile=asfile)\",\n \"def scan_fixtures(path):\\n results = list()\\n for root, dirs, files in os.walk(path):\\n relative_path = root.replace(path + \\\"/\\\", \\\"\\\")\\n if relative_path.startswith(\\\"static\\\") or relative_path.startswith(\\\"theme\\\"):\\n continue\\n\\n for f in files:\\n if not f.endswith(\\\".json\\\"):\\n continue\\n\\n app_name = os.path.basename(os.path.dirname(relative_path))\\n\\n results.append((app_name, f, relative_path))\\n\\n return results\",\n \"def parse_all_controlfiles(dirs: List[Path]) -> Dict[str, BinaryPackage]:\\n pkgs = {}\\n for path in dirs:\\n if not Path(path / \\\"debian/control\\\").exists():\\n continue\\n pkgs.update(parse_controlfile(path))\\n return pkgs\",\n \"def _get_all_pkg_info(self):\\n all_pkgs = self._filter_pkgs(self._go_list(\\\"./...\\\"))\\n # for every package, list the deps, the test files, the test imports, and the external package test imports\\n big_list = self._go_list(\\n \\\"-f\\\", \\\"{{.ImportPath}}:{{.Deps}}:{{.TestImports}}:{{.XTestImports}}\\\", *all_pkgs)\\n recursive_deps = {}\\n test_imports = {}\\n\\n for line in big_list:\\n tokens = [token.strip().lstrip('[').rstrip(']').strip() for token in line.split(\\\":\\\", 3)]\\n pkg = tokens[0].strip()\\n\\n recursive_deps[pkg] = set(self._filter_pkgs(tokens[1].split() + [pkg]))\\n if tokens[2] or tokens[3]:\\n test_imports[pkg] = set(\\n self._filter_pkgs(tokens[2].split()) + self._filter_pkgs(tokens[3].split()))\\n\\n return recursive_deps, test_imports\",\n \"def find_packages(paths=(os.curdir,), exclude=()):\\n packages = []\\n discarded = []\\n\\n def _discarded(path):\\n for discard in discarded:\\n if _under(path, discard):\\n return True\\n return False\\n\\n for path in paths:\\n path = convert_path(path)\\n for root, dirs, files in os.walk(path):\\n for dir_ in dirs:\\n fullpath = os.path.join(root, dir_)\\n if _discarded(fullpath):\\n continue\\n # we work only with Python packages\\n if not _is_package(fullpath):\\n discarded.append(fullpath)\\n continue\\n # see if it's excluded\\n excluded = False\\n package_name = _package_name(path, fullpath)\\n for pattern in exclude:\\n if fnmatchcase(package_name, pattern):\\n excluded = True\\n break\\n if excluded:\\n continue\\n\\n # adding it to the list\\n packages.append(package_name)\\n return packages\",\n \"def compare_resource_get_new_datasets(data_packages_path):\\n \\n for name in glob.glob(f'{data_packages_path}/data-json-*.json'):\\n package = Package(name)\\n data_json = package.get_resource('inline')\\n data_json_data = data_json.source\\n\\n yield data_json_data\\n\\n # Delete the data.json file\\n os.remove(name)\",\n \"def find_data_dirs(cls, directory,\\n basedata_dir=c.WORDS_DIR,\\n markables_dir=c.MARKABLES_DIR,\\n dirs_to_ignore=c.DIRS_TO_IGNORE):\\n dirs_to_ignore = set(dirs_to_ignore)\\n for subdir, subsubdirs, _ in os.walk(directory):\\n if os.path.basename(subdir) in dirs_to_ignore:\\n continue\\n has_words = basedata_dir in subsubdirs\\n has_markables = markables_dir in subsubdirs\\n if has_words and has_markables:\\n logger.debug(f\\\"subdir: {subdir}\\\")\\n yield subdir\\n elif has_markables:\\n logger.warn(\\n f\\\"{subdir} has a markables directory ({markables_dir}),\\\"\\n f\\\" but no words directory ({basedata_dir}).\\\"\\n )\\n elif has_words:\\n logger.warn(\\n f\\\"{subdir} has a words directory ({basedata_dir}), but no\\\"\\n f\\\" markables directory ({markables_dir}).\\\"\\n )\",\n \"def get_setup_data_files(self):\\n data_files = CMakeBuilder.default_setup_data_files\\n if gitutil.has_submodules():\\n data_files.append(\\\".gitmodules\\\")\\n data_files.append(\\n os.path.join(self.dist_dir, gitutil.gitmodules_status_name)\\n )\\n return [(\\\"\\\", data_files)]\",\n \"def get_packages(package):\\n return [str(path.parent) for path in Path(package).glob(\\\"**/__init__.py\\\")]\",\n \"def test_3_recursive(self):\\n\\n bronze = fmri.PkgFmri(self.published[4], None)\\n\\n # Retrieve bronze recursively to a directory, this should\\n # also retrieve its dependency: amber, and amber's dependency:\\n # tree.\\n self.pkgrecv(self.durl1, \\\"--raw -r -k -d {0} {1}\\\".format(self.tempdir,\\n bronze))\\n\\n amber = fmri.PkgFmri(self.published[1], None)\\n tree = fmri.PkgFmri(self.published[5], None)\\n\\n # Verify that the manifests for each package was retrieved.\\n for f in (amber, bronze, tree):\\n mpath = os.path.join(self.tempdir, f.get_dir_path(),\\n \\\"manifest\\\")\\n self.assertTrue(os.path.isfile(mpath))\",\n \"def packages_in_folder(path):\\n for pkg_path in catkin_pkg.packages.find_package_paths(path):\\n yield os.path.join(path, pkg_path)\",\n \"def _find_rpms_in_packages(koji_api, name_list, major_minor):\\n rpms_for_package = {}\\n tags = _tags_for_version(major_minor)\\n for package in name_list:\\n for tag in tags:\\n for build in koji_api.getLatestBuilds(tag=tag, package=package):\\n rpm_list = set(rpm[\\\"name\\\"] for rpm in koji_api.listBuildRPMs(build[\\\"build_id\\\"]))\\n rpms_for_package.setdefault(package, set()).update(rpm_list)\\n\\n if package not in rpms_for_package:\\n # it wasn't in our tags; look for it by name\\n pkg_info = koji_api.getPackage(package)\\n if not pkg_info:\\n continue\\n latest_builds = koji_api.listBuilds(packageID=pkg_info[\\\"id\\\"], state=1, queryOpts=dict(limit=1))\\n if not latest_builds:\\n continue\\n rpm_list = set(rpm[\\\"name\\\"] for rpm in koji_api.listBuildRPMs(latest_builds[0][\\\"build_id\\\"]))\\n rpms_for_package[package] = set(rpm_list)\\n\\n return rpms_for_package\",\n \"def get_data_files():\\n\\n data_files = []\\n for d, dirs, filenames in os.walk(share_jupyterhub):\\n rel_d = os.path.relpath(d, here)\\n data_files.append((rel_d, [os.path.join(rel_d, f) for f in filenames]))\\n return data_files\",\n \"def get_package_python_paths(package, paths):\\n # Note: Here we're trying to get `package`'s specific changes to PYTHONPATH (if any)\\n #\\n # Unfortunately, the Rez API doesn't really support this yet.\\n # There's 2 GitHub links that may one-day implement it though:\\n # - https://github.com/nerdvegas/rez/issues/737\\n # - https://github.com/nerdvegas/rez/pull/739\\n #\\n # Reference: https://rez-talk.slack.com/archives/CHELFCTFB/p1578604659006100\\n #\\n # Once that work is merged, replace `get_package_python_paths` with it.\\n #\\n root = finder.get_package_root(package)\\n\\n if is_built_package(package):\\n return {path for path in paths if filer.in_directory(path, root, follow=False)}\\n\\n output = set()\\n\\n for path in paths:\\n # If the Rez package is a source Rez package + has variants\\n # we need to strip the \\\"variants\\\" out of `path`, before\\n # returning it.\\n #\\n try:\\n variant_less_path = next(\\n _iter_variant_extracted_paths(root, path, package.variants or [])\\n )\\n except StopIteration:\\n pass\\n else:\\n output.add(variant_less_path)\\n\\n continue\\n\\n if filer.in_directory(path, root, follow=False) or filer.in_directory(\\n path, root, follow=True\\n ):\\n output.add(path)\\n\\n continue\\n\\n return output\",\n \"def load_data_files() -> Dict[str, Path]:\\n default_path = paths.MISCELLANEOUS_DIRECTORY / \\\"portfolio\\\"\\n custom_exports = (\\n get_current_user().preferences.USER_PORTFOLIO_DATA_DIRECTORY / \\\"optimization\\\"\\n )\\n data_files = {}\\n for directory in [default_path, custom_exports]:\\n for file_type in [\\\"xlsx\\\", \\\"ini\\\"]:\\n for filepath in Path(directory).rglob(f\\\"*.{file_type}\\\"):\\n if filepath.is_file() and \\\"example\\\" not in filepath.name:\\n data_files[filepath.name] = filepath\\n\\n return data_files\",\n \"def FindPackagesToScan(settings, startdir, reposplit):\\n\\n\\tdef AddPackagesInDir(path):\\n\\t\\t\\\"\\\"\\\" Given a list of dirs, add any packages in it \\\"\\\"\\\"\\n\\t\\tret = []\\n\\t\\tpkgdirs = os.listdir(path)\\n\\t\\tfor d in pkgdirs:\\n\\t\\t\\tif d == 'CVS' or d.startswith('.'):\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\tp = os.path.join(path, d)\\n\\n\\t\\t\\tif os.path.isdir(p):\\n\\t\\t\\t\\tcat_pkg_dir = os.path.join(*p.split(os.path.sep)[-2:])\\n\\t\\t\\t\\tlogging.debug('adding %s to scanlist' % cat_pkg_dir)\\n\\t\\t\\t\\tret.append(cat_pkg_dir)\\n\\t\\treturn ret\\n\\n\\tscanlist = []\\n\\trepolevel = len(reposplit)\\n\\tif repolevel == 1: # root of the tree, startdir = repodir\\n\\t\\tfor cat in settings.categories:\\n\\t\\t\\tpath = os.path.join(startdir, cat)\\n\\t\\t\\tif not os.path.isdir(path):\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\tscanlist.extend(AddPackagesInDir(path))\\n\\telif repolevel == 2: # category level, startdir = catdir\\n\\t\\t# We only want 1 segment of the directory,\\n\\t\\t# this is why we use catdir instead of startdir.\\n\\t\\tcatdir = reposplit[-2]\\n\\t\\tif catdir not in settings.categories:\\n\\t\\t\\tlogging.warn(\\n\\t\\t\\t\\t'%s is not a valid category according to profiles/categories, '\\n\\t\\t\\t\\t'skipping checks in %s' % (catdir, catdir))\\n\\t\\telse:\\n\\t\\t\\tscanlist = AddPackagesInDir(catdir)\\n\\telif repolevel == 3: # pkgdir level, startdir = pkgdir\\n\\t\\tcatdir = reposplit[-2]\\n\\t\\tpkgdir = reposplit[-1]\\n\\t\\tif catdir not in settings.categories:\\n\\t\\t\\tlogging.warn(\\n\\t\\t\\t\\t'%s is not a valid category according to profiles/categories, '\\n\\t\\t\\t\\t'skipping checks in %s' % (catdir, catdir))\\n\\t\\telse:\\n\\t\\t\\tpath = os.path.join(catdir, pkgdir)\\n\\t\\t\\tlogging.debug('adding %s to scanlist' % path)\\n\\t\\t\\tscanlist.append(path)\\n\\treturn scanlist\",\n \"def collect_children(self, recursive=True):\\n self.children = []\\n\\n for fname in os.listdir(self.path):\\n path = join(self.path, fname)\\n\\n if Package.is_pkg(path):\\n child = Package.create(path, owner=self)\\n if recursive:\\n child.collect_children()\\n\\n elif Module.is_module(path):\\n child = Module.create(path, owner=self)\\n\\n else:\\n if util.get_verbosity_level() > 0:\\n print(\\\"Skipping: {}\\\".format(path))\\n continue\\n\\n self.children.append(child)\",\n \"def find_with_deps(self, package_names):\",\n \"def find_packages(self, meta):\\n package_name = None\\n\\n # find which package contains our binary\\n dpkg_s_nginx_out, dpkg_s_nginx_err = subp.call('dpkg -S %s' % self.object.bin_path, check=False)\\n for line in dpkg_s_nginx_out:\\n kv = re.match(self.dpkg_s_re, line)\\n if kv:\\n package_name = kv.group(1)\\n break\\n\\n if dpkg_s_nginx_err:\\n if 'no_path' in dpkg_s_nginx_err[0]:\\n meta['warnings'].append('self-made binary, is not from any nginx package')\\n\\n if not package_name:\\n return\\n\\n # get version\\n all_installed_packages = self.installed_nginx_packages()\\n\\n if package_name in all_installed_packages:\\n meta['packages'] = {package_name: all_installed_packages[package_name]}\",\n \"def get_data_files():\\n data_files = []\\n\\n # Walk through the data directory, adding all files\\n data_generator = os.walk('pypeit/data')\\n for path, directories, files in data_generator:\\n for f in files:\\n data_path = '/'.join(path.split('/')[1:])\\n data_files.append(os.path.join(data_path, f))\\n\\n # Add pipeline and spectrograph settings\\n settings = glob.glob('pypeit/settings/settings.*')\\n settings = ['/'.join(path.split('/')[1:]) for path in settings]\\n data_files.extend(settings)\\n\\n return data_files\",\n \"def get_resource(package_name, resource):\\n # Path of the package, relative to the loader root:\\n # For package 'foo.bar', this is 'foo/bar'.\\n package_path = package_name.replace(\\\".\\\", \\\"/\\\")\\n\\n # Path of the resource, relative to the loader root:\\n # For package 'foo.bar' and resource 'subdir/data.csv', this is \\\"foo/bar/subdir/data.csv\\\".\\n resource_path = os.path.join(package_path, resource)\\n\\n # Iterate over all the contributors for the specified package:\\n try:\\n package = importlib.import_module(package_name)\\n except ImportError:\\n # Package or module does not exist:\\n logging.debug(\\\"Resource %r from package %r not found\\\", resource, package_name)\\n return None\\n\\n for path in package.__path__:\\n # 'path' is the absolute package path within a specific loader:\\n # For package 'foo.bar' in a loader for a Zip file '/path/to/archive.zip',\\n # this is: '/path/to/archive.zip/foo/bar'.\\n logging.debug(\\\"Attempting to load resource %r from %r\\\", resource, path)\\n\\n assert path.endswith(package_path), \\\\\\n \\\"Package path mismatch: {!r} does not include package {!r}\\\".format(path, package_path)\\n loader_path = path[:-(len(package_path) + 1)]\\n if os.path.isdir(loader_path):\\n # FileFinder importers do not implement get_data().\\n # We have to handle direct files explicitly:\\n resource_fullpath = os.path.join(loader_path, resource_path)\\n if os.path.exists(resource_fullpath):\\n with open(resource_fullpath, mode=\\\"rb\\\") as f:\\n logging.debug(\\\"Found resource %r in %r\\\", resource, resource_fullpath)\\n return f.read()\\n else:\\n # Handle ZIP (and other) file loaders:\\n # Loaders are expected to implement get_data(resource_path).\\n try:\\n importer = sys.path_importer_cache[loader_path]\\n content = importer.get_data(resource_path)\\n logging.debug(\\\"Found resource %r in %r\\\",\\n resource, os.path.join(loader_path, resource_path))\\n return content\\n except OSError:\\n logging.debug(\\\"Resource %r not found in loader %r\\\", resource, loader_path)\\n # Ignore error and try next package path.\\n\\n # Specified resource not found in any loader:\\n logging.debug(\\\"Resource %r from package %r not found\\\", resource, package_name)\\n return None\",\n \"def collect_pypi_data():\\n\\n rclient = xmlrpc.client.ServerProxy('http://pypi.python.org/pypi')\\n python = {'Programming Language :: Python': rclient.browse(['Programming Language :: Python'])}\\n python_two = {}\\n python_three = {}\\n\\n for classifier in [\\n 'Programming Language :: Python :: 2',\\n 'Programming Language :: Python :: 2.3',\\n 'Programming Language :: Python :: 2.4',\\n 'Programming Language :: Python :: 2.5',\\n 'Programming Language :: Python :: 2.6',\\n 'Programming Language :: Python :: 2.7',\\n 'Programming Language :: Python :: 2 :: Only']:\\n python_two[classifier] = rclient.browse([classifier])\\n\\n for classifier in [\\n 'Programming Language :: Python :: 3',\\n 'Programming Language :: Python :: 3.0',\\n 'Programming Language :: Python :: 3.1',\\n 'Programming Language :: Python :: 3.2',\\n 'Programming Language :: Python :: 3.3',\\n 'Programming Language :: Python :: 3.4']:\\n python_three[classifier] = rclient.browse([classifier])\\n\\n return {datetime.datetime.now().strftime('%Y-%m-%dT%H:%M:%S'):\\n {'python': python,\\n 'python_two': python_two,\\n 'python_three': python_three}}\",\n \"def packages(self):\\n\\n if self._packages:\\n return self._packages\\n\\n self._load()\\n return self._packages\",\n \"def list(self, ignore_patterns):\\n for storage in six.itervalues(self.storages):\\n if storage.exists(''): # check if storage location exists\\n for path in utils.get_files(storage, ignore_patterns):\\n # for packagers we only accept specifics packages, library and versions (meaning sublib needs lib)\\n splitted_path = path.split(os.path.sep)\\n\\n packager = self.packagers.get(splitted_path[0], None)\\n found = False\\n\\n # others prefix that are not specified into installed_packagers are\\n # probably normal django applications\\n if splitted_path[0] in self.installed_packagers:\\n if packager:\\n for library in packager:\\n # split to have sublib when parent lib is not imported\\n if splitted_path[2] == library[0].split('.')[0]:\\n if splitted_path[3] in library[1]:\\n # found package.library(version)\\n found = True\\n break\\n else:\\n found = True\\n\\n if not found:\\n continue\\n\\n yield path, storage\",\n \"def list_packages(self):\\n\\n # First extract loaded module names from sys.modules\\n sys_modules = sys.modules.keys()\\n\\n packages = {}\\n\\n # First add moduels in sys.modules (built-ins,\\n # preloads and already loaded ones)\\n for name in sys_modules:\\n d = self.find_package(name)\\n if not d: continue\\n try:\\n pkginfo = packages[d['type']]\\n pkginfo[d['name']] = d['path']\\n except Exception, e:\\n packages[d['type']] = { d['name'] : d['path'] }\\n\\n #import site\\n # Loop through all directories in sys.path and check for modules\\n # Dont iterate through <prefix>/lib directory\\n libdir = os.path.join(sys.prefix, 'lib')\\n\\n walked = []\\n for top_level in self.paths:\\n if not os.path.isdir(top_level):\\n continue\\n\\n # Dont iterate through libdir\\n if os.path.abspath(top_level) == os.path.abspath(libdir):\\n continue\\n\\n walked.append(top_level)\\n for item in os.listdir(top_level):\\n\\n fullpath = os.path.join(top_level, item)\\n if fullpath in walked: continue\\n\\n walked.append(fullpath)\\n # Remove the extension\\n idx = item.find('.')\\n if idx != -1: item = item[:idx]\\n d = self.find_package(item)\\n if not d: continue\\n try:\\n pkginfo = packages[d['type']]\\n pkginfo[d['name']] = d['path']\\n except Exception, e:\\n packages[d['type']] = { d['name'] : d['path'] } \\n\\n for key,item in packages.items():\\n print\\n print self.pkgTypeInfo(key)\\n print\\n\\n # Print sorted\\n listofitems = item.keys()\\n listofitems.sort()\\n\\n for key2 in listofitems:\\n print key2,':',item[key2]\",\n \"def find_files_for_package(self, package, absolute_path=False):\\n package_files = []\\n for p in package.package_versions:\\n package_files.extend(self.find_files_for_packageversion(p, absolute_path))\\n return package_files\",\n \"def go_package_dirs(packages, build_tags):\\n\\n target_packages = []\\n for pkg in packages:\\n target_packages += (\\n check_output(\\n f\\\"go list -find -f \\\\\\\"{{{{ .Dir }}}}\\\\\\\" -mod=mod -tags \\\\\\\"{','.join(build_tags)}\\\\\\\" {pkg}\\\",\\n shell=True,\\n )\\n .decode('utf-8')\\n .strip()\\n .split(\\\"\\\\n\\\")\\n )\\n\\n return target_packages\",\n \"def collect():\\n\\n # Get database.\\n with open(local_directory(path='file_diffs/packages.json'), 'r') as f:\\n store = json.load(f)\\n\\n # UI.\\n print('Checking files for differences...\\\\n')\\n\\n # Iterate database.\\n for package_name in store:\\n # Package variables.\\n package_dir = os.path.join(package_directory, package_name)\\n package = store[package_name]\\n\\n # Recursive (lazy) package searching.\\n if type(package) == str:\\n package = os.path.expanduser(package)\\n for dirpath, dirnames, filenames in os.walk(package):\\n for filename in filenames:\\n sub_package_dir = package_dir + dirpath.replace(package, '')\\n if not os.path.exists(sub_package_dir):\\n os.makedirs(sub_package_dir)\\n\\n fp_local = os.path.join(dirpath, filename)\\n fp_remote = os.path.join(sub_package_dir, filename)\\n\\n cs_local = file_checksum(fp=fp_local)\\n cs_remote = file_checksum(fp=fp_remote)\\n\\n if cs_remote != cs_local:\\n print('Found: {}/{}'.format(package_name, filename))\\n shutil.copyfile(src=fp_local, dst=fp_remote)\\n\\n # Manual package searching.\\n if type(package) == list:\\n for fp in package:\\n fn_local = fp['local']\\n fn_remote = fp['remote']\\n\\n fp_local = os.path.expanduser(fn_local)\\n fp_remote = os.path.join(package_dir, fn_remote)\\n\\n cs_local = file_checksum(fp=fp_local)\\n cs_remote = file_checksum(fp=fp_remote)\\n\\n if cs_remote != cs_local:\\n print('Found: {}/{}'.format(package_name, fn_remote))\\n\\n remote_dir_path = '/'.join(fp_remote.split('/')[:-1])\\n if not os.path.exists(remote_dir_path):\\n os.makedirs(remote_dir_path)\\n shutil.copyfile(src=fp_local, dst=fp_remote)\",\n \"def get_packages():\\n\\tapps=[]\\n\\tlspackages = glob.glob(u'/home/wpkg/packages/*.xml')\\n\\tfor fic in lspackages:\\n #print fic\\n\\t\\tif os.path.isfile(fic):\\n\\t\\t\\ttry:\\n\\t\\t\\t\\txml = etree.parse(fic)\\n\\t\\t\\texcept:\\n\\t\\t\\t\\t#si erreur on tente de corriger le fichier\\n\\t\\t\\t\\toput = open(\\\"output.txt\\\",\\\"w\\\")\\n\\t\\t\\t\\tdata = open(fic).read()\\n\\t\\t\\t\\toput.write( re.sub('&(?!amp;|quot;|nbsp;|gt;|lt;|laquo;|raquo;|copy;|reg;|bul;|rsquo;)', '&', data) )\\n\\t\\t\\t\\toput.close()\\n\\t\\t\\t\\tshutil.move(\\\"output.txt\\\", fic)\\n\\n\\t\\t\\tfinally:\\n\\t\\t\\t\\tparser = etree.XMLParser(remove_comments=False)\\n\\t\\t\\t\\txml = etree.parse(fic,parser)\\n\\t\\t\\t\\tstrxml = etree.tostring(xml.getroot())\\n\\t\\t\\t\\tfor group in xml.getiterator(u'package'):\\n\\t\\t\\t\\t\\tuid = group.get(u'id')\\n\\t\\t\\t\\t\\tname = group.get(u'name')\\n\\t\\t\\t\\t\\tdvars = dict()\\n\\t\\t\\t\\t\\tfor vars in xml.getiterator('variable'):\\n\\t\\t\\t\\t\\t\\tdvars[vars.get('name').lower()] = vars.get('value').lower()\\n\\n\\t\\t\\t\\t#on remplit le dico des appli dispo\\n\\t\\t\\t\\t#print fic,uid,name\\n\\t\\t\\t\\tapps.append((fic,uid,name))\\n\\n\\treturn apps\",\n \"def getData(self):\\n\\t\\treturn self.golang_project_packages\",\n \"def command_package_ls(*args):\\n\\n # Setup build, install, and data directories\\n package_dirs = os.listdir(packages_path())\\n\\n for packname in package_dirs:\\n # Filter to directories with config files\\n if not os.path.isdir(package_path(packname)): continue\\n if not package_load_config(packname): continue\\n\\n # Check for installation\\n installed_flag = ''\\n installdir = install_dir(packname)\\n bindir = os.path.join(installdir, 'bin')\\n # This is just a very basic sanity check for binaries we\\n # require\\n binfiles = (os.path.exists(bindir) and os.listdir(bindir)) or []\\n if ( ('space' in binfiles or 'space_d' in binfiles) and\\n ('cppoh' in binfiles or 'cppoh_d' in binfiles) ):\\n installed_flag = '*'\\n\\n print packname, installed_flag\\n\\n return 0\",\n \"def get_templates_dirs(self): \\n from pkg_resources import resource_filename\\n return [ resource_filename(__name__, 'templates') ]\\n # return []\",\n \"def _po_package_contents(self, package):\\n po_files = glob(os.path.join(package['source_dir'], '*.po'))\\n for po_file in po_files:\\n language = os.path.splitext(os.path.basename(po_file))[0]\\n lang_dir = os.path.join(package['build_dir'], language)\\n msg_dir = os.path.join(lang_dir, 'LC_MESSAGES')\\n mo_file = os.path.join(msg_dir, package['name'] + '.mo')\\n yield {'language': language,\\n 'lang_dir': lang_dir,\\n 'msg_dir': msg_dir,\\n 'mo_file': mo_file,\\n 'po_file': po_file}\",\n \"def repo_fs():\\n for root, dirs, files in os.walk(\\\".\\\"):\\n dirs[:] = [ # add any extra dirs to ignore #\\n d for d in dirs\\n if '.' not in d\\n and 'ENV' not in d\\n and '__' not in d\\n and 'build' not in d\\n ]\\n\\n for f in files:\\n if f.endswith(\\\".py\\\"):\\n if not f.startswith('__'):\\n ALL_PY_FILES.append(os.path.join(root, f))\\n PY_FILES.append(os.path.join(root, f))\\n if f.endswith(\\\".yml\\\"):\\n YML_FILES.append(os.path.join(root, f))\\n if f.startswith(\\\"requirements\\\"):\\n PIP_FILES.append(os.path.join(root, f))\\n if f.startswith(\\\"development\\\"):\\n DEV_FILES.append(os.path.join(root, f))\\n if f.startswith(\\\"README.md\\\"):\\n README_FILES.append(os.path.join(root, f))\\n if f.startswith(\\\"LICENSE\\\"):\\n LICENSE.append(os.path.join(root, f))\\n if f.startswith(\\\"CONTRIBUTIONS\\\"):\\n CONTRIBUTIONS.append(os.path.join(root, f))\\n\\n if PY_FILES:\\n parse_files()\\n\\n return { # dictionary with all lists of file path/names #\\n 'PY_FILES': PY_FILES,\\n 'YML_FILES': YML_FILES,\\n 'PIP_FILES': PIP_FILES,\\n 'README_FILES': README_FILES,\\n 'TEST_FILES': TEST_FILES,\\n 'LICENSE': LICENSE,\\n 'URL_FILES': URL_FILES,\\n 'CONTRIBUTIONS': CONTRIBUTIONS,\\n 'SETUP_FILES': SETUP_FILES,\\n 'MODEL_FILES': MODEL_FILES,\\n 'SETTINGS_FILES': SETTINGS_FILES,\\n 'DEV_FILES': DEV_FILES,\\n }\",\n \"def packages(self):\\n return []\",\n \"def fixture_sets(*args):\\n return [os.path.join(*args, dir)\\n for dir in os.listdir(os.path.join(FIXTURE_DATA, *args))\\n if os.path.isdir(os.path.join(FIXTURE_DATA, *args, dir))\\n ]\",\n \"def get_resources(self, resource_data=None):\\n if not resource_data and self.component:\\n resource_data = self.component.get_resource_data()\\n\\n resources = []\\n for resource in self.files:\\n resource.update(resource_data)\\n\\n resource['storage_path'] = self.prefix + '/' + resource['name']\\n relative_path = self.relative_path(data=resource)\\n resource['relative_path'] = relative_path\\n resource['url'] = resource['url'] + '/' + relative_path\\n resources.append(resource)\\n return resources\",\n \"def get_fallback_packages(request, package_name):\\n dists = request.locator.get_project(package_name)\\n pkgs = {}\\n for version, url_set in six.iteritems(dists.get('urls', {})):\\n dist = dists[version]\\n for url in url_set:\\n filename = posixpath.basename(url)\\n url = request.app_url('api', 'package', dist.name, filename)\\n pkgs[filename] = url\\n return pkgs\",\n \"def write_manifest ( self, **manifest_kw ):\\n for package in self._subdirs.values():\\n package.write_manifest ( **manifest_kw )\",\n \"def get_problematic_packages(\\n package_data: List[Mapping[str, str]]\\n) -> List[Mapping[str, str]]:\\n white_listed_packages = get_whitelisted_packages()\\n problematic_packages = []\\n for p in package_data:\\n license_name_upper = p[\\\"License\\\"].upper()\\n package_name_upper = p[\\\"Name\\\"].upper()\\n if (\\n license_name_upper not in LICENSE_WHITELIST\\n and package_name_upper not in white_listed_packages\\n ):\\n problematic_packages.append(p)\\n elif (\\n package_name_upper in white_listed_packages\\n and white_listed_packages[package_name_upper]\\n and white_listed_packages[package_name_upper] != license_name_upper\\n ):\\n problematic_packages.append(p)\\n\\n return problematic_packages\",\n \"def _load_dirs(self):\\n rootdirs = self._docset.get_compounds(xml.Directory,\\n lambda x: x.get_parent() is None)\\n for dirdoc in rootdirs:\\n self._load_dir(dirdoc, None)\",\n \"def parse_paths():\\r\\n sources = get_source_paths()\\r\\n results = collections.defaultdict(list)\\r\\n for root_dir in sources:\\r\\n\\r\\n for script_type, dirs in walkdirs(root_dir).iteritems():\\r\\n\\r\\n for d in dirs:\\r\\n logger.debug(d)\\r\\n\\r\\n # Add paths to environments\\r\\n if os.path.basename(d).lower().startswith(ICONS):\\r\\n results['XBMLANGPATH'].append(d)\\r\\n os.environ['XBMLANGPATH'] += os.pathsep + d\\r\\n\\r\\n if script_type == 'mel':\\r\\n results['MAYA_SCRIPT_PATH'].append(d)\\r\\n os.environ['MAYA_SCRIPT_PATH'] += os.pathsep + d\\r\\n else:\\r\\n results['PYTHONPATH'].append(d)\\r\\n site.addsitedir(d)\\r\\n return results\",\n \"def _walk_dir_meta(self):\\n for key, child in sorted(self._children.items()):\\n if isinstance(child, PackageEntry):\\n continue\\n meta = child.meta\\n if meta:\\n yield key + '/', meta\\n for child_key, child_meta in child._walk_dir_meta():\\n yield key + '/' + child_key, child_meta\",\n \"def find_requirements(root: str) -> Optional[Dict[str, bool]]:\\n findings = {\\n file_name: os.path.isfile(os.path.join(root, file_name))\\n for file_name in [\\\"requirements.txt\\\", \\\"Pipfile\\\", \\\"Pipfile.lock\\\"]\\n }\\n\\n if not sum(findings.values()):\\n return None\\n return findings\",\n \"def getusersitepackages():\\n\\tpass\",\n \"def fact():\\n manifests = [x for x in os.walk(manifests_dir)]\\n\\n return { 'manifests': manifests }\",\n \"def setup_module(module):\\n for datafile in datafiles:\\n src = get_pkg_data_filename(os.path.join('data', datafile))\\n shutil.copyfile(src, datafile)\",\n \"def get_package_files(self, package):\\n with self._conn.begin():\\n return {\\n row.filename: row.filehash\\n for row in self._conn.execute(\\n \\\"SELECT filename, filehash \\\"\\n \\\"FROM get_package_files(%s)\\\", (package,)\\n )\\n }\",\n \"def group_by_filenames(self):\\n package = self.container.config.output.package\\n class_map = collections.group_by(self.container, key=get_location)\\n groups = self.group_common_paths(class_map.keys())\\n\\n for keys in groups:\\n if len(keys) == 1:\\n common_path = os.path.dirname(keys[0])\\n else:\\n common_path = os.path.commonpath(keys)\\n\\n for key in keys:\\n items = class_map[key]\\n suffix = \\\".\\\".join(Path(key).parent.relative_to(common_path).parts)\\n\\n package_name = f\\\"{package}.{suffix}\\\" if suffix else package\\n self.assign(items, package_name, module_name(key))\",\n \"def _walk_dirs(self):\\n for project_name in self.new_source_paths.keys():\\n # print \\\"-------- Now mapping ---- \\\" + project_name\\n search_path = self.root + project_name + '\\\\\\\\Data'\\n for dirpath, subdirs, files in os.walk(search_path):\\n for file in files:\\n self.new_source_paths[project_name][file] = dirpath\\n # print \\\"------------ Finished mapping ------- \\\" + project_name\\n return self.new_source_paths\",\n \"def scan(root: str, config: dict) -> dict:\\n\\n extensions = config['extensions']\\n exceptions = config['exceptions']\\n\\n # get list of directories, with their contents (files and sub-directories)\\n dirs_by_path = {\\n get_path_from_common_root(dir_path, root): (\\n dir_path,\\n dir_names,\\n [name for name in file_names if is_valid_file_name(name, config)]\\n )\\n for dir_path, dir_names, file_names in os.walk(root)\\n }\\n\\n dirs_by_path = {key: value for key, value in dirs_by_path.items() if value[1] or value[2]}\\n\\n # get list of file paths\\n file_path_list = [\\n (file_dir, file_name)\\n for file_dir, _, file_names in dirs_by_path.values()\\n for file_name in file_names\\n ]\\n\\n files_by_path = {}\\n # todo: put below loop contents into function, used in above list comprehension\\n for file_dir, file_name_with_extension in file_path_list:\\n # todo: remove code file definition from here to allow this to be reused for non-code related files\\n # todo: refactor to use inheritable File class instead of named tuple, to be reused for non-code files\\n\\n if file_name_with_extension in exceptions:\\n continue\\n\\n file = CodeFile(\\n imports=[],\\n exports=[],\\n local_params=[],\\n blocks=[],\\n dir=file_dir,\\n name=file_name_with_extension.rsplit('.', 1)[0],\\n extension=file_name_with_extension.rsplit('.', 1)[1]\\n )\\n\\n parse_file(file, config)\\n file_no_dupes = remove_duplicate_entries(file)\\n\\n dir_key = get_path_from_common_root(file_dir, root)\\n if dir_key not in files_by_path:\\n files_by_path[dir_key] = []\\n\\n files_by_path[dir_key].append(file_no_dupes)\\n\\n return {'dirs_by_path': dirs_by_path, 'files_by_path': files_by_path,\\n 'starting_point': get_path_from_common_root(root, root)}\",\n \"def get_package_folders(which_folder: str = \\\"root\\\") -> Path:\\n logg = logging.getLogger(f\\\"c.{__name__}.get_package_folders\\\")\\n # logg.setLevel(\\\"INFO\\\")\\n logg.debug(\\\"Start get_package_folders\\\")\\n\\n this_file_folder = Path(__file__).absolute().parent\\n logg.debug(f\\\"{this_file_folder=}\\\")\\n\\n package_root_folder = this_file_folder.parent.parent.parent\\n\\n if which_folder == \\\"root\\\":\\n return package_root_folder\\n\\n elif which_folder == \\\"tests\\\":\\n tests_folder = package_root_folder / \\\"tests\\\"\\n return tests_folder\\n\\n elif which_folder == \\\"template_epub\\\":\\n template_epub_folder = package_root_folder / \\\"assets\\\" / \\\"template_epub\\\"\\n return template_epub_folder\\n\\n elif which_folder == \\\"word_pairs\\\":\\n word_pairs_folder = package_root_folder / \\\"assets\\\" / \\\"word_pairs\\\"\\n return word_pairs_folder\\n\\n elif which_folder == \\\"common_words\\\":\\n common_words_folder = package_root_folder / \\\"assets\\\" / \\\"common_words\\\"\\n return common_words_folder\\n\\n else:\\n raise KeyError(f\\\"Not recognized {which_folder}\\\")\",\n \"def data_files(self, pattern=None, regex=None):\\n return self._files_in_subdir(self.data_dir, pattern, regex)\",\n \"def _LoadPackages():\\n return {module.__name__.split('.')[-1]: module for module in\\n import_util.LoadModulesForPath(__path__, __name__)}\",\n \"def check_init_file(name : str, init_path : 'Path') -> list:\\n\\n # Read __init__ if it exists\\n\\n package_modules = []\\n\\n try:\\n\\n # Check for __all__ global variable assignments\\n\\n pattern = re.compile(r\\\"\\\"\\\"(?:^__all__\\\\s*=\\\\s*)(\\\\[[^\\\\[\\\\]]*\\\\]$)\\\"\\\"\\\", re.MULTILINE)\\n\\n with open(str(init_path), 'r') as init_file:\\n\\n logging.getLogger('GUM Dispenser').info('Found __init__.py')\\n\\n init_contents = init_file.read()\\n\\n # Grab the capturing group\\n\\n init_results = [current_match.group(1).strip() for current_match in pattern.finditer(init_contents)\\n if not current_match.group(1) is None and\\n not (current_match.group(1).isspace() or current_match.group(1) == '')]\\n\\n logging.getLogger('GUM Dispenser').debug(init_results)\\n\\n if len(init_results) > 0:\\n\\n logging.getLogger('GUM Dispenser').info('Found __all__ declaration. Using ' +\\n str(init_results[-1]) + ' as module list')\\n\\n package_modules = ast.literal_eval(init_results[-1])\\n\\n\\n # Make sure specified modules exist before we go further\\n\\n ensure_modules_exist(package_modules, init_path.parent)\\n\\n else:\\n\\n logging.getLogger('GUM Dispenser').warning('__init__.py __all__ definition was not found for package ' +\\n name + '. Treating all same level .py files' +\\n ' as included modules...')\\n\\n # Safely handle case where __init__ does not exist\\n except FileNotFoundError:\\n\\n logging.getLogger('GUM Dispenser').warning('__init__.py does not exist for package ' + name +\\n '. Treating all same level .py files as included modules...')\\n\\n if len(package_modules) == 0:\\n\\n # Grab all .py files in package directory\\n\\n src_dir = init_path.parent\\n\\n logging.getLogger('GUM Dispenser').debug('Parent directory: ' + str(src_dir))\\n\\n os.chdir(src_dir)\\n\\n package_modules = glob.glob('*.py')\\n\\n package_modules = [name.rstrip('.py') for name in package_modules]\\n\\n\\n return package_modules\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.74882954","0.7475205","0.7218244","0.7056486","0.68890065","0.68552727","0.66472167","0.6606134","0.6553142","0.6551368","0.6509173","0.62634075","0.6203264","0.6189386","0.61807597","0.6176723","0.61635065","0.6163499","0.6126401","0.6013186","0.6013186","0.6013186","0.59982294","0.5991891","0.5985914","0.5919948","0.5901651","0.5891826","0.58828723","0.5881818","0.58763814","0.5871244","0.58465886","0.5836759","0.58240426","0.5823247","0.5797995","0.57959783","0.57725155","0.5736104","0.5713632","0.57061285","0.56850183","0.5671833","0.56451637","0.56272614","0.561881","0.5611577","0.55949575","0.55932504","0.55894536","0.5549226","0.55349827","0.5529183","0.5519415","0.55157065","0.5499239","0.5485294","0.54779613","0.5477644","0.54738086","0.54604685","0.54566","0.54556435","0.54504985","0.5442249","0.54362655","0.54330295","0.54249454","0.5422479","0.5415186","0.5408065","0.54056966","0.5392541","0.5378612","0.5366916","0.5366458","0.53606135","0.53420305","0.534065","0.5320843","0.5310571","0.5307314","0.53032315","0.52779084","0.5274786","0.5266379","0.52641606","0.5263578","0.5257297","0.52527535","0.5252058","0.52453","0.5229838","0.5229617","0.5229178","0.52258766","0.52228457","0.5221789","0.52175117"],"string":"[\n \"0.74882954\",\n \"0.7475205\",\n \"0.7218244\",\n \"0.7056486\",\n \"0.68890065\",\n \"0.68552727\",\n \"0.66472167\",\n \"0.6606134\",\n \"0.6553142\",\n \"0.6551368\",\n \"0.6509173\",\n \"0.62634075\",\n \"0.6203264\",\n \"0.6189386\",\n \"0.61807597\",\n \"0.6176723\",\n \"0.61635065\",\n \"0.6163499\",\n \"0.6126401\",\n \"0.6013186\",\n \"0.6013186\",\n \"0.6013186\",\n \"0.59982294\",\n \"0.5991891\",\n \"0.5985914\",\n \"0.5919948\",\n \"0.5901651\",\n \"0.5891826\",\n \"0.58828723\",\n \"0.5881818\",\n \"0.58763814\",\n \"0.5871244\",\n \"0.58465886\",\n \"0.5836759\",\n \"0.58240426\",\n \"0.5823247\",\n \"0.5797995\",\n \"0.57959783\",\n \"0.57725155\",\n \"0.5736104\",\n \"0.5713632\",\n \"0.57061285\",\n \"0.56850183\",\n \"0.5671833\",\n \"0.56451637\",\n \"0.56272614\",\n \"0.561881\",\n \"0.5611577\",\n \"0.55949575\",\n \"0.55932504\",\n \"0.55894536\",\n \"0.5549226\",\n \"0.55349827\",\n \"0.5529183\",\n \"0.5519415\",\n \"0.55157065\",\n \"0.5499239\",\n \"0.5485294\",\n \"0.54779613\",\n \"0.5477644\",\n \"0.54738086\",\n \"0.54604685\",\n \"0.54566\",\n \"0.54556435\",\n \"0.54504985\",\n \"0.5442249\",\n \"0.54362655\",\n \"0.54330295\",\n \"0.54249454\",\n \"0.5422479\",\n \"0.5415186\",\n \"0.5408065\",\n \"0.54056966\",\n \"0.5392541\",\n \"0.5378612\",\n \"0.5366916\",\n \"0.5366458\",\n \"0.53606135\",\n \"0.53420305\",\n \"0.534065\",\n \"0.5320843\",\n \"0.5310571\",\n \"0.5307314\",\n \"0.53032315\",\n \"0.52779084\",\n \"0.5274786\",\n \"0.5266379\",\n \"0.52641606\",\n \"0.5263578\",\n \"0.5257297\",\n \"0.52527535\",\n \"0.5252058\",\n \"0.52453\",\n \"0.5229838\",\n \"0.5229617\",\n \"0.5229178\",\n \"0.52258766\",\n \"0.52228457\",\n \"0.5221789\",\n \"0.52175117\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.76023054"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88567,"cells":{"query":{"kind":"string","value":"r\"\"\"Compute the fixed point as described in the paper by Botev et al."},"document":{"kind":"string","value":"def _fixed_point(t, N, squared_integers, grid_data_dct2):\n # ell = 7 corresponds to the 5 steps recommended in the paper\n ell = tf.constant(7, ztypes.float)\n\n # Fast evaluation of |f^l|^2 using the DCT, see Plancherel theorem\n f = (\n tf.constant(0.5, ztypes.float)\n * tf.math.pow(\n tf.constant(np.pi, ztypes.float), (tf.constant(2.0, ztypes.float) * ell)\n )\n * tf.math.reduce_sum(\n tf.math.pow(squared_integers, ell)\n * grid_data_dct2\n * tf.math.exp(\n -squared_integers\n * tf.math.pow(\n tf.constant(np.pi, ztypes.float), tf.constant(2.0, ztypes.float)\n )\n * t\n )\n )\n )\n\n i = tf.constant(6.0, dtype=ztypes.float)\n while_condition = lambda i, f: i > 1\n\n def body(i, f):\n # do something here which you want to do in your loop\n # increment i\n f = calc_f(i, f, squared_integers, grid_data_dct2, N)\n return i - 1.0, f\n\n # do the loop:\n fnew = tf.while_loop(\n while_condition, body, (i, f), maximum_iterations=5, parallel_iterations=5\n )[1]\n\n # This is the minimizer of the AMISE\n t_opt = tf.math.pow(\n tf.constant(2 * np.sqrt(np.pi), ztypes.float) * N * fnew,\n tf.constant(-2.0 / 5.0, ztypes.float),\n )\n\n # Return the difference between the original t and the optimal value\n return t - t_opt"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def fixed_point(is_zero, plus, minus, f, x):\n\n @memo_Y\n def _fixed_point(fixed_point_fun):\n def __fixed_point(collected, new):\n diff = minus(new, collected)\n if is_zero(diff):\n return collected\n return fixed_point_fun(plus(collected, diff), f(diff))\n return __fixed_point\n\n return _fixed_point(x, f(x))","def fixed_point(x, int_bits, frac_bits):\n if int_bits == None and frac_bits == None: return x\n _frac = x - np.floor(x) #if x >= 0 else x - np.ceil(x)\n _int = np.floor(x) #if x>= 0 else np.ceil(x)\n _frac = np.round(_frac*2**frac_bits)/2**frac_bits\n _x = _int + _frac\n # if _x > 2**(int_bits-1)-1: _x = 2**(int_bits-1)-1\n # elif _x < -2**(int_bits-1): _x = -2**(int_bits-1)\n if _x > 2**(int_bits)-2**(-frac_bits): _x = 2**(int_bits)-2**(-frac_bits)\n elif _x < -2**(int_bits): _x = -2**(int_bits)\n return _x","def fixed(self):\n return self.f_fixed().m_fixed()","def test_fixed_point_system(testFunctions, tol, printFlag): \n pass","def test_fixed_point(testFunctions, tol, printFlag): \n pass","def fixed_point(func, init, **kwargs):\n\n def fixed_func(mix):\n \"\"\"Labeling function for a fixed point\"\"\"\n return np.argmin((mix == 0) - mix + func(mix))\n\n return labeled_subsimplex(fixed_func, init, **kwargs)","def fppp(x):\n return (-2000.00*math.cos(10.0.x+1))","def fix_point_arithmetic(self):\n\n return self._fixpntar","def f(x0: float, x1: float) -> float:\n return 8 - (x0 - 2) ** 2 - (x1 - 2) ** 2","def calculate_prp(self, ref_point: np.ndarray, f_current: np.ndarray) -> np.ndarray:\n\n # distance\n d = np.linalg.norm(np.atleast_2d(ref_point - f_current))\n\n # unit vectors\n ei = np.array([np.zeros(len(ref_point))])\n es = np.repeat(ei, len(ref_point), axis=0)\n\n for i, j in enumerate(es):\n for ind, _ in enumerate(j):\n if ind == i:\n j[ind] = 1\n\n return ref_point + (d * es)","def def_mpf_constant(fixed):\n def f(prec, rnd=round_fast):\n wp = prec + 20\n v = fixed(wp)\n if rnd in (round_up, round_ceiling):\n v += 1\n return normalize(0, v, -wp, bitcount(v), prec, rnd)\n f.__doc__ = fixed.__doc__\n return f","def ppf(self,x):\n ppfValue = self.invCDF(x)\n return ppfValue","def fpp(x):\n return (-200.0*math.sin(10.0*x+1.0))","def _correct_p(self, f0, f1):\n return self.p * np.exp(self.dbeta * (f0 + f1) / 2)","def return_zeropoint():\n return 22.5","def classify_fixedpoints(fps, scale):\n\n x_directions = []\n scale = scale\n for fp in fps:\n\n trace = np.matrix.trace(fp['jac'])\n det = np.linalg.det(fp['jac'])\n if det > 0 and trace == 0:\n print('center has been found. Watch out for limit cycles')\n elif trace**2 - 4 * det == 0:\n print(\"star nodes has been found.\")\n elif trace**2 - 4 * det < 0:\n print(\"spiral has been found\")\n e_val, e_vecs = np.linalg.eig(fp['jac'])\n ids = np.argwhere(np.real(e_val) > 0)\n countgreaterzero = np.sum(e_val > 0)\n if countgreaterzero == 0:\n print('stable fixed point was found.')\n fp['fp_stability'] = 'stable fixed point'\n elif countgreaterzero > 0:\n print('saddle point was found.')\n fp['fp_stability'] = 'saddle point'\n for id in ids:\n x_plus = fp['x'] + scale * e_val[id] * np.real(e_vecs[:, id].transpose())\n x_minus = fp['x'] - scale * e_val[id] * np.real(e_vecs[:, id].transpose())\n x_direction = np.vstack((x_plus, fp['x'], x_minus))\n x_directions.append(np.real(x_direction))\n\n return fps, x_directions","def PointMilieu(x,f):\n\tNx = f.shape[0]\n\tS=0.0\n\tfor i in range(0,Nx-1):\n\t\tS=S+f[i]*(x[i+1]-x[i]) \n\treturn S","def ppf(self,x):\n if self.base == 'natural':\n ppfValue = math.exp((self.upperBound-self.lowerBound)*x + self.lowerBound)\n else:\n ppfValue = 10.**((self.upperBound-self.lowerBound)*x + self.lowerBound)\n return ppfValue","def find_zero(f, df):\n def near_zero(x):\n return approx_eq(f(x), 0)\n return improve(newton_update(f, df), near_zero)","def _compute_f(self, p, dh, dv):\n return dh / (self.beta * p * dv)","def p2f (p):\n #return 11000**((p+1)/2)\n #return (p+1)*11000\n return (p+1)*5500","def p() -> float:\n return 0.9","def jacobian(kernel: Kern, variable_points: ndarray, fixed_points: ndarray) -> ndarray:\n if isinstance(kernel, RBF):\n lengthscale = kernel.lengthscale.values[0]\n k = kernel.K(variable_points, fixed_points)\n\n # The (i, j, k)-th element of this is the k-th component of X_i - D_j.\n differences = variable_points[:, newaxis, :] - fixed_points[newaxis, :, :]\n\n return -k[:, :, newaxis] * differences / (lengthscale ** 2)\n else:\n raise NotImplementedError","def fixed_points(self, epsilon = 0.000001):\n # (a b) (z) = (Lz)\n # (c d) (1) ( L) \n\n # az + b = c z^2 + d z\n # 0 = c z^2 + (d-a)z - b\n # z = ((a-d) \\pm sqrt( (a-d)^2 + 4 bc )) / 2c\n\n a, b, c, d = self\n\n assert abs(c) > epsilon\n zp = ((a - d) + sqrt( (a - d)**2 + 4*b*c)) / 2*c\n zm = ((a - d) - sqrt( (a - d)**2 + 4*b*c)) / 2*c\n Lp = c*zp + d\n Lm = c*zm + d\n if abs(Lp) < abs(Lm):\n Ls = [Lp, Lm]\n out = [zp, zm]\n else:\n Ls = [Lm, Lp]\n out = [zm, zp] \n assert abs(Ls[0]) < 1 - epsilon and 1 + epsilon < abs(Ls[1])\n return [CP1((z,1)) for z in out]","def fpr(self):\n return float(self.fp) / (self.fp + self.tn) if self.tn != 0 else 1","def phi_fixed(prec):\n prec += 10\n a = isqrt_fast(MPZ_FIVE<<(2*prec)) + (MPZ_ONE << prec)\n return a >> 11","def apoint(rpoint):\r\n tempy = gv[\"fixedLL\"][1] + gv[\"globalscale\"]*rpoint[1]*(gv[\"fixedUR\"][1]-gv[\"fixedLL\"][1])\r\n if gv[\"localxscale\"] != -1:\r\n tempx = gv[\"fixedLL\"][0] + gv[\"localxscale\"]*gv[\"globalscale\"]*rpoint[0]*(gv[\"fixedUR\"][0]-gv[\"fixedLL\"][0])\r\n else:\r\n tempx = gv[\"fixedLL\"][0] + gv[\"globalscale\"]*rpoint[0]*(gv[\"fixedUR\"][0]-gv[\"fixedLL\"][0])\r\n if tempx - gv[\"fixedUR\"][0] > 0 and tempx - gv[\"fixedUR\"][0] < 1e-7:\r\n tempx = gv[\"fixedUR\"][0]\r\n if tempx > gv[\"fixedUR\"][0]:\r\n print ( \"problem x value : \",tempx, \" max x allowed : \",gv[\"fixedUR\"][0])\r\n return [tempx,tempy]","def fCalc(self):\n # A dictionary composed of all internal and boundary points\n allPoints = dict(self.internalPoints.items() + self.boundaryPoints.items())\n\n for pointLabel in allPoints.keys():\n # Compute fE, fW, fN and fW only for internal mesh points\n if allPoints[pointLabel].type.lower() == 'internal':\n xLabel = pointLabel[0]\n yLabel = pointLabel[1]\n x = self.internalPoints[(xLabel,yLabel)].x\n y = self.internalPoints[(xLabel,yLabel)].y\n xE = allPoints[(xLabel + 1,yLabel)].x\n xW = allPoints[(xLabel - 1,yLabel)].x\n yN = allPoints[(xLabel,yLabel + 1)].y\n yS = allPoints[(xLabel,yLabel - 1)].y\n \n if (xE - x)/self.h < -0.000001 or (xE - x)/self.h > 1.000001:\n errorMessage = '**Error! (xE - x)/h for the point with label ('+str(xLabel) + ',' + str(yLabel) + ') and coordinate (' + str(x) + ',' + str(y) + ') is not between zero and one: (xE - x)/h = ' + str((xE - x)/self.h)\n raise customError(errorMessage)\n else:\n self.internalPoints[(xLabel,yLabel)].fE = (xE - x)/self.h\n\n # Note that in the following we use -0.000001 and 1.000001 \n # instead of 0 and 1, respectively, to avoid problems with\n # with very small fractions. For example if the fractions is\n # greater than one by 2.22e-16 the condition (x - xW)/self.h > 1\n # will be false and the code returns an error\n if (x - xW)/self.h < -0.000001 or (x - xW)/self.h > 1.000001:\n errorMessage = '**Error! (x - xW)/h for the point with label ('+str(xLabel) + ',' + str(yLabel) + ') and coordinate (' + str(x) + ',' + str(y) + ') is not between zero and one: (x - xW)/h = ' + str((x - xW)/self.h)\n raise customError(errorMessage)\n else:\n self.internalPoints[(xLabel,yLabel)].fW = (x - xW)/self.h\n \n if (yN - y)/self.h < -0.000001 or (yN - y)/self.h > 1.000001:\n errorMessage = '**Error! (yN - y)/h for the point with label ('+str(xLabel) + ',' + str(yLabel) + ') and coordinate (' + str(x) + ',' + str(y) + ') is not between zero and one: (yN - y)/h = ' + str((yN - y)/self.h)\n raise customError(errorMessage)\n else:\n self.internalPoints[(xLabel,yLabel)].fN = (yN - y)/self.h\n \n if (y - yS)/self.h < -0.000001 or (y - yS)/self.h > 1.000001:\n errorMessage = '**Error! (y - yS)/h for the point with label ('+str(xLabel) + ',' + str(yLabel) + ') and coordinate (' + str(x) + ',' + str(y) + ') is not between zero and one: (y - yS)/h = ' + str((y - yS)/self.h)\n raise customError(errorMessage)\n else:\n self.internalPoints[(xLabel,yLabel)].fS = (y - yS)/self.h\n \n # Calculate the coeeficients requried to compute the Laplacian \n self.internalPoints[(xLabel,yLabel)].LapCoeffCalc()","def ppf(self,x):\n if self.method == 'spline':\n ppfValue = self._distribution.inverseCdf(x,random())\n else:\n self.raiseAnError(NotImplementedError,'ppf is not yet implemented for ' + self.method + ' method')\n return ppfValue","def fixed_point_multiply(data, multiplier, shift):\n return _make.fixed_point_multiply(data, multiplier, shift)","def solve(self, f: sym.Function, start: float):\n if self.__doVisual:\n self.__visualisiere(f, style='r', description='f(' + str(self.__symbol) + ')=' + str(f))\n\n self.__ableitung = f.diff(self.__symbol)\n self.__funktion = f\n self.__tries = 0\n current_point = start\n current_div = abs(f.evalf(subs={self.__symbol: current_point}))\n # wiederholen bis genauigkeit erreicht oder das Maximum der Versuche erreicht ist\n while current_div > self.__precision and self.__tries < self.__max_tries:\n current_point = self.__do_newton(f, current_point)\n result = self.__evaluate(current_point)\n current_div = abs(result)\n self.__tries = self.__tries + 1\n\n if self.__doVisual:\n self.__visual_result()\n return current_point, current_div","def f_fixed(self):\n self.fx_free = self.fy_free = self.fz_free = False\n return self","def fd_center(f, h, x0):\n return (f(x0 + h) - 2*f(x0) + f(x0 - h))/(h**2)","def _fv(self):\n return self.beta * (self.x ** self.c)","def diff_1st_central(fp, fm, eps):\n \n return (fp - fm)/(2.0*eps)","def ppf(self,x):\n ppfValue = self._distribution.inverseCdf(x,random())\n return ppfValue","def ppf(self,x):\n ppfValue = self._distribution.inverseCdf(x,random())\n return ppfValue","def _centred_first_derivs(self, f):\n return ((f[2:, 1:-1] - f[0:-2, 1:-1]) / (2 * self._dx),\n (f[1:-1, 2:] - f[1:-1, 0:-2]) / (2 * self._dy))","def convergent_point_guarded(x0, x1, y, f):\n d0 = distance(x0, y, f)\n d1 = distance(x1, y, f)\n if d0 < d1:\n x1 = power_unary(x1, d1 - d0, f)\n elif d1 < d0:\n x0 = power_unary(x0, d0 - d1, f)\n return convergent_point(x0, x1, f)","def FindClosestPointWithinRadius(self, p_float, , p_float_4):\n ...","def compute_fpa_welfare(bidders, anonymous_reserve, points=1000):\r\n wel = 0.0\r\n for i in range(len(bidders[0].strategy.F_jump_points) - 1):\r\n bid_range_start = bidders[0].strategy.F_jump_points[i][0]\r\n bid_range_end = bidders[0].strategy.F_jump_points[i + 1][0]\r\n if bid_range_start < bid_range_end:\r\n num_points = max(100, int(points / (\r\n bidders[0].strategy.F_jump_points[-1][0] - bidders[0].strategy.F_jump_points[0][0]) *\r\n (bidders[0].strategy.F_jump_points[i + 1][0] - bidders[0].strategy.F_jump_points[i][0])))\r\n bid_range = np.linspace(bidders[0].strategy.F_jump_points[i][0],\r\n bidders[0].strategy.F_jump_points[i + 1][0],\r\n num=num_points)\r\n bid_range = bid_range[1:]\r\n\r\n wel_b = [0.0] * len(bid_range)\r\n for j in range(len(bid_range)):\r\n cdf, _, active_values = prob_dist(bidders, bid_range[j])\r\n if len(active_values) <= 1:\r\n wel_b[j] = 0.0\r\n else:\r\n wel_b[j] = np.prod(cdf) * (sum(active_values) / (len(active_values) - 1.0) *\r\n sum(1.0 / (np.array(active_values) - bid_range[j])) -\r\n sum(np.array(active_values) / (np.array(active_values) - bid_range[j])))\r\n wel += integrate.simps(wel_b, bid_range)\r\n\r\n # point mass at min winning bid\r\n min_winning_bid = max(compute_min_winning_bid(bidders), anonymous_reserve)\r\n values = [[-1.0] for _ in range(len(bidders))]\r\n probs = [[0.0] for _ in range(len(bidders))]\r\n for i in range(len(bidders)):\r\n bidder = bidders[i]\r\n F_min_winning_bid = bidder.strategy.F_jump_points[0][1]\r\n for j in range(len(bidder.prob)):\r\n if bidder.values[j] < min_winning_bid:\r\n probs[i][0] += bidder.prob[j]\r\n elif sum(bidder.prob[:j]) < F_min_winning_bid:\r\n values[i].append(bidder.values[j])\r\n probs[i].append(min(bidder.prob[j], F_min_winning_bid - sum(bidder.prob[:j])))\r\n else:\r\n break\r\n\r\n for i in range(len(bidders)):\r\n for i_value_idx in range(1, len(values[i])):\r\n i_value = values[i][i_value_idx]\r\n if i_value == 0.0:\r\n continue\r\n winning_prob = probs[i][i_value_idx]\r\n for j in range(len(bidders)):\r\n if j == i:\r\n continue\r\n j_losing_prob = 0.0\r\n for j_value_idx in range(len(values[j])):\r\n j_value = values[j][j_value_idx]\r\n if j_value < i_value or (j_value == i_value and j < i):\r\n j_losing_prob += probs[j][j_value_idx]\r\n winning_prob *= j_losing_prob\r\n wel += winning_prob * i_value\r\n return wel","def set_starting_point(f, x_input):\n\n k = 2\n bnd1_fda = FloatDPApproximation(x_input)\n bnd2_fda = bnd1_fda - k * (f(bnd1_fda) / derivative(f, bnd1_fda))\n bnd1_float = float(str(bnd1_fda))\n bnd2_float = float(str(bnd2_fda))\n if bnd1_float < bnd2_float:\n ix = UpperInterval({cast_exact(bnd1_float): cast_exact(bnd2_float)})\n else:\n ix = UpperInterval({cast_exact(bnd2_float): cast_exact(bnd1_float)})\n\n x = cast_singleton(ix)\n x_end = FloatDPApproximation(x)\n return x_end","def compute_fk(self, sigma, sigma_des, C, offset):\n if sigma >= sigma_des:\n # push robot away\n f = -((sigma - sigma_des) ** 2)/C + offset\n elif sigma < sigma_des:\n # pull robot in\n f = ((sigma - sigma_des) ** 2)/C + offset\n else:\n f = 0\n return f","def F(x):\n soln = x - (1.0/5.0)*math.cos(10.0*x+1.0) \n return soln","def fix_point(h, lower, upper):\n return brentq(lambda x: x - h(x), lower, upper)","def parabolic(self, f, x):\n\t # Requires real division. Insert float() somewhere to force it?\n\t xv = 1 / 2 * (f[x - 1] - f[x + 1]) / (f[x - 1] - 2 * f[x] + f[x + 1]) + x\n\t yv = f[x] - 1 / 4 * (f[x - 1] - f[x + 1]) * (xv - x)\n\t return (xv, yv)","def my_Newton( fct, df_dx, x0):\r\n xn = float(x0)\r\n eps = 1e-5\r\n N = 20\r\n i = 0\r\n while abs( fct( xn**(i + 1)) - fct( xn**i)) > eps and i < N:\r\n x_next = xn - fct(xn)/df_dx(xn)\r\n print( i, 'fct value', abs( fct(xn)), x_next)\r\n xn = x_next\r\n i += 1\r\n if abs( fct( xn)) < eps:\r\n return x_next\r\n else: #solution did not converge\r\n return np.nan","def convergent_point(x0, x1, f):\n while x0 != x1:\n x0, x1 = f(x0), f(x1)\n return x0","def pofd(self):\n return self.table[0, 1] / (self.table[0, 1] + self.table[1, 1])","def pointlength(x):\n return 0.0","def my_Newton(fct, df_dx, x0):\r\n xn = float(x0)\r\n eps = 1e-5\r\n N = 20\r\n i = 0\r\n while abs(fct (xn)) > eps and i < N:\r\n x_next = xn - fct(xn)/df_dx(xn)\r\n print(i , 'fct_value', abs(fct(xn)), x_next)\r\n xn = x_next\r\n i += 1\r\n if abs(fct(xn)) < eps:\r\n return x_next\r\n else: #solution did not converge\r\n return np.nan","def FrictionF(self,eta):\n return -3*3.14*eta*self.par.d*self.par.vel","def fpppp(x):\n return (20000.0*math.sin(10.0*x+1.0))","def F(self, points):\n\n # Perform calculation in the frame parallel to the ellipse\n # and then rotate it back\n rotatedP = self.rotatePoint(points)\n\n surface_pot = np.sqrt((rotatedP[..., 0]/self.axisA[:, None])**2 + (rotatedP[..., 1]/self.axisB[:, None])**2)\n\n # Force = -grad potential\n # swapaxes is necesary to make the created\n # force array of shape [N_samples, N-particles, 2]\n\n surface_force = - 1/surface_pot[..., None]*np.array([\n rotatedP[..., 0]/self.axisA[:, None]**2, \n rotatedP[..., 1]/self.axisB[:, None]**2\n ]).swapaxes(0, 2).swapaxes(0, 1) \n\n # Rotate back to the original frame\n surface_force = self.rotatePoint(surface_force, -1)\n\n # Force is scaled with A_conf and applied only if the particle is outside\n return self.A_conf*surface_force*self.isOutside(points)[:, :, None]","def ppf(self,x):\n if x > 1.0 or x < 0:\n self.raiseAnError(IOError,'Categorical distribution cannot calculate ppf for', str(x), '! Valid value should within [0,1]!')\n sortedMapping = sorted(self.mapping.items(), key=operator.itemgetter(0))\n if x == 1.0:\n return float(sortedMapping[-1][0]) if self.isFloat else sortedMapping[-1][0]\n else:\n cumulative=0.0\n for element in sortedMapping:\n cumulative += element[1]\n if cumulative >= x:\n return float(element[0]) if self.isFloat else element[0]","def p2f(self):\n\n stale = self.m_f\n self.m_f = self.v.b / self.m_v","def e_fixed(prec):\n # Slight overestimate of N needed for 1/N! < 2**(-prec)\n # This could be tightened for large N.\n N = int(1.1*prec/math.log(prec) + 20)\n p, q = bspe(0,N)\n return ((p+q)<<prec)//q","def calibrate_nopp(fundamental):\n thresh = 0.09682\n m1 = -0.1014\n b1 = 0.2839\n m2 = -0.065\n b2 = 0.21\n state1 = (fundamental < thresh)\n\n cal_fun = copy.copy(fundamental)\n cal_fun[state1] = 10**((fundamental[state1] - b1) / m1)\n cal_fun[~state1] = 10**((fundamental[~state1] - b2) / m2)\n return cal_fun","def erfc(x):\n return 0.0","def __v(pk: float, pna: float, pcl: float, pca: float) -> float:\n ex_ion = pk * ex_k + pna * ex_na + pcl * in_cl + pca * ex_ca\n in_ion = pk * in_k + pna * in_na + pcl * ex_cl + pca * in_ca\n v = r * t / f * np.log(ex_ion/in_ion) * 1000\n return v","def cal_frost_point(dew_point):\n\n nalts = dew_point.shape[0]\n frost_point = np.NaN * np.zeros_like(dew_point)\n log_es = -0.58002206e4 / dew_point + 1.3914993 - 0.48640239e-1 \\\n * dew_point + 0.41764768e-4 * dew_point ** 2 - 0.14452093e-7 \\\n * dew_point ** 3 + 0.65459673e1 * np.log(dew_point)\n\n for j in range(nalts):\n if dew_point[j] < 273.15 and np.isfinite(dew_point[ j]):\n try:\n frost_point[ j] = brentq(delta_es, 100, 273, args=log_es[j])\n except ValueError: \n frost_point[ j] = np.NaN\n else:\n frost_point[ j] = np.NaN\n return frost_point","def diff_1st_fwrdbwrd(fp, fm, eps):\n \n return (fp - fm)/eps","def fpb(x, y):\n if y == 0:\n return x\n else:\n return fpb(y, (x % y))","def aptd_ln_pl0_pl1_id_f0_f1__iea(aptd,ln,pl0,pl1,id,f0,f1):\n dsl = aptd['id__nu']\n f0ind = dsl_d_f__inda(dsl,id,f0)\n f1ind = dsl_d_f__inda(dsl,id,f1)\n pc0 = aptd[ln][pl__pstring(pl0)] # point cloud 0\n pc1 = aptd[ln][pl__pstring(pl1)] # point cloud 1\n return (pc0[f0ind]-pc0[f1ind])-(pc1[f0ind]-pc1[f1ind])","def f2p (f):\n #return 2*math.log(f, 11000) - 1\n #return f/11000 - 1\n return f/5500 - 1","def find_zero(f,p1,d):\n if p1 > 10:\n p1 = 0.5\n c = p1 - f(p1)*d/(f(p1+d)-f(p1)) # simple\n \n # we can do this in case derivative diverges because our function is symmetric\n if c < 0:\n c = -c\n \n global n_of_zeros\n \n if n_of_zeros > 8:\n print('Go linear')\n return find_zero_linear(f,d,c,d)\n \n n_of_zeros += 1\n print('#',n_of_zeros,' current zero: ',c)\n \n # if p1 and c are close together\n if np.abs(c-p1)<d or f(c)==0:\n return c\n else:\n return find_zero(f,c,d)","def neighbour_force(self, point):\n left_vector = np.array([\n self.neighbour1.x - point[0],\n self.neighbour1.y - point[1],\n ])\n right_vector = np.array([\n self.neighbour2.x - point[0],\n self.neighbour2.y - point[1],\n ])\n return 0.1 * (left_vector + right_vector)","def TestFunc2(x):\r\n return 10*(-0.02*x[0] + 0.5*x[0]*x[0] + x[1])**2 \\\r\n + 128*(-0.02*x[0] + 0.5*x[0]*x[0] - x[1]/4) \\\r\n - (8e-5)*x[0]","def f(z):\n a=1./(1.+z)\n #da=0.01\n da=0.01*a\n #da=1e-7\n gp,g,gm=[D(1./ia-1.) for ia in [a+da,a,a-da]]\n f=a*(gp-gm)/(2*g*da)\n #dz=0.01\n #gp,g,gm=[D(zi) for zi in [z+dz,z,z-dz]]\n #f=(z)*(gp-gm)/(2.*g*dz)\n return f","def _check_approx_fixed_point(V_current, V_previous, tol):\n\n # Compute the sup norm between `V_current` and `V_previous`\n sup_norm = np.max(np.abs(V_current - V_previous))\n\n # Algorithm termination condition\n fp = sup_norm <= tol\n\n return fp, sup_norm","def farenheit(ctemp):\n return round(9.0/5.0 * ctemp + 32)","def psi(x, y):\n return x","def f1(x, a, b):\n #return x**43 - b*x**42 + x**7 - x**6 * a + 84*x - 42 * b - 42 * a\n return (x**42 + 42)/(x-a) + (x**6 + 42)/(x-b)","def f_v(_a, _vs, _Ps, _Ps0): # _aはスカラ, _vsはベクトル, _Ps, _Ps0は３行2列の行列\n center_pos = _Ps[0]\n center_pos_0 = _Ps0[0]\n idx_iter = Index_iterator(1, 8)\n #中心点から各点へのベクトル\n x = []\n x0 = []\n for p in (_Ps):\n x.append(p - center_pos)\n for p in _Ps(_Ps0):\n x0.append(p - center_pos_0)\n\n x01 = (_Ps[1]-center_pos) \n x02 = (_Ps[2]-center_pos) \n x03 = (_Ps[3]-center_pos) \n x04 = (_Ps[4]-center_pos) \n x05 = (_Ps[5]-center_pos) \n x06 = (_Ps[6]-center_pos) \n x07 = (_Ps[7]-center_pos) \n x08 = (_Ps[8]-center_pos)\n print('p_id', center_pos, end='\\t')\n print('x01:', x01, end=\"\\t\")\n print('x03:', x03, end=\"\\t\")\n print('x05:', x05, end=\"\\t\")\n print('x07:', x07)\n x001 = (_Ps0[1]-_Ps0[0]) \n x002 = (_Ps0[2]-_Ps0[0]) \n x003 = (_Ps0[3]-_Ps0[0]) \n x004 = (_Ps0[4]-_Ps0[0]) \n x005 = (_Ps0[5]-_Ps0[0]) \n x006 = (_Ps0[6]-_Ps0[0]) \n x007 = (_Ps0[7]-_Ps0[0]) \n x008 = (_Ps0[8]-_Ps0[0]) \n \n #中心点周りの面の面積\n def calc_area(j,k,l):\n s = LA.norm(np.cross(x[j],x[k]))/2 \\\n + LA.norm(np.cross(x[k],x[l]))/2\n return s\n\n s = []\n s0 = []\n hen = [1,3,5,7]\n for i in range(4):\n j,k,l = [n for n in idx_iter.get_indexes(start_idx=hen[i], 3)]\n s[i] = calc_area(j,k,l)\n s0[i] = calc_area(j,k,l)\n\n # s0123 = LA.norm(np.cross(x[1],x[2]))/2\\\n # +LA.norm(np.cross(x[2],x[3]))/2\n # s4367 = LA.norm(np.cross(x[3],x[4]))/2\\\n # +LA.norm(np.cross(x[4],x[5]))/2\n # s4785 = LA.norm(np.cross(x[5],x[6]))/2\\\n # +LA.norm(np.cross(x[6],x[7]))/2\n # s4521 = LA.norm(np.cross(x[7],x[8]))/2\\\n # +LA.norm(np.cross(x[8],x[1]))/2\n # s04103 = LA.norm(np.cross(x0[1],x0[2]))/2\\\n # +LA.norm(np.cross(x0[2],x0[3]))/2\n # s04367 = LA.norm(np.cross(x0[3],x0[4]))/2\\\n # +LA.norm(np.cross(x0[4],x0[7]))/2\n # s04785 = LA.norm(np.cross(x0[7],x0[8]))/2\\\n # +LA.norm(np.cross(x0[8],x0[5]))/2\n # s04521 = LA.norm(np.cross(x0[5],x0[2]))/2\\\n # +LA.norm(np.cross(x0[2],x0[1]))/2\n \n #各方向への平均面積(ここだけ反時計回り順で設定してる)\n S_iminus = (s[1] + s[2]) / 2 #43方向\n S_Jminus = (s[1] + s[4]) / 2 #41方向\n S_iplus = (s[3] + s[4]) / 2 #45方向\n S_Jplus = (s[3] + s[2]) / 2 #47方向\n S_iminus0 = (s0[1] + s0[2]) / 2 #43方向\n S_Jminus0 = (s0[1] + s0[4]) / 2 #41方向\n S_iplus0 = (s0[3] + s0[4]) / 2 #45方向\n S_Jplus0 = (s0[3] + s0[2]) / 2 #47方向\n # 各方向への厚み\n h_iminus = h_0 / ((poisson/(1-poisson) * (S_iminus - S_iminus0) / S_iminus0) + 1) #43方向\n h_Jminus = h_0 / ((poisson/(1-poisson) * (S_Jminus - S_Jminus0) / S_Jminus0) + 1) #41方向\n h_iplus = h_0 / ((poisson/(1-poisson) * (S_iplus - S_iplus0) / S_iplus0) + 1) #45方向\n h_Jplus = h_0 / ((poisson/(1-poisson) * (S_Jplus - S_Jplus0) / S_Jplus0) + 1) #47方向\n # 各断片の重心\n g = []\n kado = [2,4,6,8]\n hen = [1,3,5,7]\n for i in range(len(kado)):\n _kado = kado[i]\n _hen1, _ = [idx for idx in idx_iter.get_indexes_reverse(_kado, 2)]\n _hen2, _ = [idx for idx in idx_iter.get_indexes(_kado, 2)]\n _hen = [_hen1, _hen2]\n _g1 = (center_pos + _Ps[_kado] + _Ps[_hen1])/3\n _g2 = (center_pos + _Ps[_kado] + _Ps[_hen2])/3\n g.append([_g1, _g2])\n\n g401 = (center_pos + _Ps[0] + _Ps[1]) / 3\n g430 = (center_pos + _Ps[3] + _Ps[0]) / 3\n g436 = (center_pos + _Ps[3] + _Ps[6]) / 3\n g467 = (center_pos + _Ps[6] + _Ps[7]) / 3\n g478 = (center_pos + _Ps[7] + _Ps[8]) / 3\n g485 = (center_pos + _Ps[8] + _Ps[5]) / 3\n g452 = (center_pos + _Ps[5] + _Ps[2]) / 3\n g421 = (center_pos + _Ps[2] + _Ps[1]) / 3\n g0401 = (_Ps0[4] + _Ps0[0] + _Ps0[1]) / 3\n g0430 = (_Ps0[4] + _Ps0[3] + _Ps0[0]) / 3\n g0436 = (_Ps0[4] + _Ps0[3] + _Ps0[6]) / 3\n g0467 = (_Ps0[4] + _Ps0[6] + _Ps0[7]) / 3\n g0478 = (_Ps0[4] + _Ps0[7] + _Ps0[8]) / 3\n g0485 = (_Ps0[4] + _Ps0[8] + _Ps0[5]) / 3\n g0452 = (_Ps0[4] + _Ps0[5] + _Ps0[2]) / 3\n g0421 = (_Ps0[4] + _Ps0[2] + _Ps0[1]) / 3\n \n # 各断片面積\n triangle_area = []\n kado = [2,4,6,8]\n for i in range(len(kado)):\n j, k = [idx for idx in idx_iter.get_indexes_reverse(kado[i], 1)]\n _s1 = LA.norm(np.cross(x[j],x[k]))/2\n j, k = [idx for idx in idx_iter.get_indexes(kado[i], 1)]\n _s2 = LA.norm(np.cross(x[j],x[k]))/2\n triangle_area.append([_s1, _s2])\n\n s410 = LA.norm(np.cross(x[1],x[2]))/2\n s403 = LA.norm(np.cross(x[2],x[3]))/2\n s436 = LA.norm(np.cross(x[3],x[4]))/2\n s467 = LA.norm(np.cross(x[4],x[5]))/2\n s478 = LA.norm(np.cross(x[5],x[6]))/2\n s485 = LA.norm(np.cross(x[6],x[7]))/2\n s452 = LA.norm(np.cross(x[7],x[8]))/2\n s421 = LA.norm(np.cross(x[8],x[1]))/2\n s0410 = LA.norm(np.cross(x0[1],x0[2]))/2\n s0403 = LA.norm(np.cross(x0[2],x0[3]))/2\n s0436 = LA.norm(np.cross(x0[3],x0[4]))/2\n s0467 = LA.norm(np.cross(x0[4],x0[5]))/2\n s0478 = LA.norm(np.cross(x0[5],x0[6]))/2\n s0485 = LA.norm(np.cross(x0[6],x0[7]))/2\n s0452 = LA.norm(np.cross(x0[7],x0[8]))/2\n s0421 = LA.norm(np.cross(x0[8],x0[1]))/2\n # 四角の重心\n\n center_g_square = []\n for i in range(len(g)):\n _g = (triangle_area[i][0]*g[i][0] + triangle_area[i][1]*g[i][1])/(triangle_area[i][0] + triangle_area[i][1])\n center_g.append(_g)\n g4103 = (s410*g401 + s403*g430) / (s410 + s403)\n g4367 = (s436*g436 + s467*g467) / (s436 + s467)\n g4785 = (s478*g478 + s485*g485) / (s478 + s485)\n g4521 = (s452*g452 + s421*g421) / (s452 + s421)\n g04103 = (s0410*g0401 + s0403*g0430) / (s0410 + s0403)\n g04367 = (s0436*g0436 + s0467*g0467) / (s0436 + s0467)\n g04785 = (s0478*g0478 + s0485*g0485) / (s0478 + s0485)\n g04521 = (s0452*g0452 + s0421*g0421) / (s0452 + s0421)\n # 各重心間の距離\n Lj82 = LA.norm(g4521 - g4103)\n Lj24 = LA.norm(g4103 - g4367)\n Lj46 = LA.norm(g4367 - g4785)\n Lj68 = LA.norm(g4785 - g4521)\n \n # ひずみ\n eps_i41 = (LA.norm(x01) - LA.norm(x041)) / LA.norm(x041)\n eps_J41 = (LA.norm(g4521 - g4103) - LA.norm(g04521 - g04103)) / LA.norm(g04521 - g04103)\n eps_i43 = (LA.norm(x03) - LA.norm(x043)) / LA.norm(x043)\n eps_J43 = (LA.norm(g4103 - g4367) - LA.norm(g04103 - g04367)) / LA.norm(g04103 - g04367)\n eps_i47 = (LA.norm(x01) - LA.norm(x041)) / LA.norm(x041)\n eps_J47 = (LA.norm(g4367 - g4785) - LA.norm(g04367 - g04785)) / LA.norm(g04367 - g04785)\n eps_i45 = (LA.norm(x01) - LA.norm(x041)) / LA.norm(x041)\n eps_J45 = (LA.norm(g4785 - g4521) - LA.norm(g04785 - g04521)) / LA.norm(g04785 - g04521)\n # 張力\n F_T1 = (young_modulus * h_Jminus * Lj82 * (eps_i41 + poisson * eps_J41) / (1 - poisson**2))*x01/LA.norm(x01)\n F_T3 = (young_modulus * h_iminus * Lj24 * (eps_i43 + poisson * eps_J43) / (1 - poisson**2))*x03/LA.norm(x03)\n F_T5 = (young_modulus * h_Jplus * Lj46 * (eps_i47 + poisson * eps_J47) / (1 - poisson**2))*x05/LA.norm(x05)\n F_T7 = (young_modulus * h_iplus * Lj68 * (eps_i45 + poisson * eps_J45) / (1 - poisson**2))*x07/LA.norm(x07)\n # せん断ひずみ\n gamma513 = (math.acos((np.dot(x07,x01))/(LA.norm(x07)*LA.norm(x01))) - math.acos((np.dot(x045,x041))/(LA.norm(x045)*LA.norm(x041)))\\\n + math.acos((np.dot(x03,x01))/(LA.norm(x03)*LA.norm(x01))) - math.acos((np.dot(x043,x041))/(LA.norm(x043)*LA.norm(x041))))/2\n gamma137 = (math.acos((np.dot(x01,x03))/(LA.norm(x01)*LA.norm(x03))) - math.acos((np.dot(x041,x043))/(LA.norm(x041)*LA.norm(x043)))\\\n + math.acos((np.dot(x03,x05))/(LA.norm(x03)*LA.norm(x05))) - math.acos((np.dot(x043,x047))/(LA.norm(x043)*LA.norm(x047))))/2\n gamma375 = (math.acos((np.dot(x05,x03))/(LA.norm(x05)*LA.norm(x03))) - math.acos((np.dot(x047,x043))/(LA.norm(x047)*LA.norm(x043)))\\\n + math.acos((np.dot(x07,x05))/(LA.norm(x07)*LA.norm(x05))) - math.acos((np.dot(x045,x047))/(LA.norm(x045)*LA.norm(x047))))/2\n gamma751 = (math.acos((np.dot(x05,x07))/(LA.norm(x05)*LA.norm(x07))) - math.acos((np.dot(x047,x045))/(LA.norm(x047)*LA.norm(x045)))\\\n + math.acos((np.dot(x07,x01))/(LA.norm(x07)*LA.norm(x01))) - math.acos((np.dot(x045,x041))/(LA.norm(x045)*LA.norm(x041))))/2\n # せん断力\n F_S41 = ((young_modulus * h_Jminus * LA.norm(x01) * gamma513)/(2 * (1 + poisson)))*x01/LA.norm(x01)\n F_S43 = ((young_modulus * h_Jminus * LA.norm(x03) * gamma137)/(2 * (1 + poisson)))*x03/LA.norm(x03)\n F_S47 = ((young_modulus * h_Jminus * LA.norm(x05) * gamma375)/(2 * (1 + poisson)))*x05/LA.norm(x05)\n F_S45 = ((young_modulus * h_Jminus * LA.norm(x07) * gamma751)/(2 * (1 + poisson)))*x07/LA.norm(x07)\n \n # J方向の曲げ力\n n_j_cross = np.cross(x05, x01)\n if any(n_j_cross):\n n_J = n_j_cross/LA.norm(n_j_cross)\n else: \n\n l_Jalfa = LA.norm(_Ps[1] - _Ps[7])\n cos_Jalfa = (LA.norm(x01)**2 + LA.norm(x05)**2 - l_Jalfa**2) / (2 * LA.norm(x01) * LA.norm(x05))\n if cos_Jalfa > 1.0:\n cos_Jalfa = 1.0\n elif cos_Jalfa < -1.0:\n cos_Jalfa = -1.0\n sin_Jalfa = math.sqrt(1 - cos_Jalfa**2)\n CJa2 = math.sqrt((cos_Jalfa + 1)/2)\n SJa2 = math.sqrt((1 - cos_Jalfa)/2)\n zJC = (_Ps[7][2]-_Ps[1][2])/(_Ps[7][0]-_Ps[1][0]) * (center_pos[0]-_Ps[1][0]) + _Ps[1][2] #曲げ力の方向の場合わけに必要\n if center_pos[2] > zJC:\n e_j = np.dot(np.array([[CJa2 + (n_J[0]**2) * (1 - CJa2), n_J[0] * n_J[1] * (1 - CJa2) + n_J[2] * SJa2, n_J[0] * n_J[2] * (1 - CJa2) - n_J[1] * SJa2],\\\n [n_J[1] * n_J[0] * (1 - CJa2) - n_J[2] * SJa2, CJa2 + (n_J[1]**2) * (1 - CJa2), n_J[1] * n_J[2] * (1 - CJa2) + n_J[0] * SJa2],\\\n [n_J[2] * n_J[0] * (1 - CJa2) + n_J[1] * SJa2, n_J[2] * n_J[1] * (1 - CJa2) - n_J[0] * SJa2, CJa2 + (n_J[2]**2) * (1 - CJa2)]]), (_Ps[7] - center_pos)/LA.norm(_Ps[7] - center_pos))\n else:\n e_j = np.dot(np.array([[CJa2 + (n_J[0]**2) * (1 - CJa2), n_J[0] * n_J[1] * (1 - CJa2) - n_J[2] * SJa2, n_J[0] * n_J[2] * (1 - CJa2) + n_J[1] * SJa2],\\\n [n_J[1] * n_J[0] * (1 - CJa2) + n_J[2] * SJa2, CJa2 + (n_J[1]**2) * (1 - CJa2), n_J[1] * n_J[2] * (1 - CJa2) - n_J[0] * SJa2],\\\n [n_J[2] * n_J[0] * (1 - CJa2) - n_J[1] * SJa2, n_J[2] * n_J[1] * (1 - CJa2) + n_J[0] * SJa2, CJa2 + (n_J[2]**2) * (1 - CJa2)]]), (_Ps[7] - center_pos)/LA.norm(_Ps[7] - center_pos))\n d_etha_J = (2 * sin_Jalfa / l_Jalfa) - (2 * math.sqrt(1 - np.dot(x041,x047)**2/(LA.norm(x041)*LA.norm(x047))**2)/(LA.norm(x041 - x047)))\n\n n_i = np.cross(x07,x03)/LA.norm(np.cross(x03,x07)) \n cos_ialfa = np.dot(x03,x07) / (LA.norm(x03) * LA.norm(x07))\n sin_ialfa = math.sqrt(1 - cos_ialfa**2)\n Cia2 = math.sqrt((cos_ialfa + 1)/2)\n Sia2 = math.sqrt((1 - cos_ialfa)/2)\n ziC = (_Ps[5][2]-_Ps[3][2])/(_Ps[5][0]-_Ps[3][0]) * (center_pos[0]-_Ps[3][0]) + _Ps[3][2]\n if center_pos[2] > ziC:\n e_i = np.dot(np.array([[Cia2 + (n_i[0]**2) * (1 - Cia2), n_i[0] * n_i[1] * (1 - Cia2) + n_i[2] * Sia2, n_i[0] * n_i[2] * (1 - Cia2) - n_i[1] * Sia2],\\\n [n_i[1] * n_i[0] * (1 - Cia2) - n_i[2] * Sia2, Cia2 + (n_i[1]**2) * (1 - Cia2), n_i[1] * n_i[2] * (1 - Cia2) + n_i[0] * Sia2],\\\n [n_i[2] * n_i[0] * (1 - Cia2) + n_i[1] * Sia2, n_i[2] * n_i[1] * (1 - Cia2) - n_i[0] * Sia2, Cia2 + (n_i[2]**2) * (1 - Cia2)]]), (_Ps[7] - center_pos)/LA.norm(_Ps[7] - center_pos))\n else:\n e_i = np.dot(np.array([[Cia2 + (n_i[0]**2) * (1 - Cia2), n_i[0] * n_i[1] * (1 - Cia2) - n_i[2] * Sia2, n_i[0] * n_i[2] * (1 - Cia2) + n_i[1] * Sia2],\\\n [n_i[1] * n_i[0] * (1 - Cia2) + n_i[2] * Sia2, Cia2 + (n_i[1]**2) * (1 - Cia2), n_i[1] * n_i[2] * (1 - Cia2) - n_i[0] * Sia2],\\\n [n_i[2] * n_i[0] * (1 - Cia2) - n_i[1] * Sia2, n_i[2] * n_i[1] * (1 - Cia2) + n_i[0] * Sia2, Cia2 + (n_i[2]**2) * (1 - Cia2)]]), (_Ps[5] - center_pos)/LA.norm(_Ps[5] - center_pos))\n d_etha_i = (2 * sin_ialfa / LA.norm(x07 - x03)) - (2 * math.sqrt(1 - np.dot(x043,x045)**2/(LA.norm(x043)*LA.norm(x045))**2)/(LA.norm(x043 - x045)))\n\n\n l_J = (Lj20 + Lj06 + Lj68 + Lj82) / 4\n h = (h_iminus + h_iplus + h_Jminus + h_Jplus) / 4\n I = (l_J * h**3) / 12\n M_i = (young_modulus * I * (d_etha_i + poisson * d_etha_J)/(1 - poisson**2))\n M_J = (young_modulus * I * (d_etha_J + poisson * d_etha_i)/(1 - poisson**2))\n #曲げ力\n F_Bi = M_i / LA.norm(x03) + M_i / LA.norm(x07) * e_i\n F_BJ = M_J / LA.norm(x01) + M_J / LA.norm(x05) * e_j\n #空気力\n # S = (S_iminus + S_iplus + S_Jminus + S_Jplus) / 4\n # F_A = p * S\n F_A = np.array([0.0, 0.0, -0.1]) * _a\n\n # 運動方程式（支配方程式）\n S_0 = (S_iminus0 + S_iplus0 + S_Jminus0 + S_Jplus0) / 4\n F_T = F_T41 + F_T43 + F_T45 + F_T47\n F_S = F_S41 + F_S43 + F_S45 + F_S47\n F_B = F_Bi + F_BJ\n return (F_T + F_S + F_B + F_A) / (rho * h_0 * S_0) - c * _vs","def pi_fixed(prec, verbose=False, verbose_base=None):\n # The Chudnovsky series gives 14.18 digits per term\n N = int(prec/3.3219280948/14.181647462 + 2)\n if verbose:\n print(\"binary splitting with N =\", N)\n g, p, q = bs_chudnovsky(0, N, 0, verbose)\n sqrtC = isqrt_fast(CHUD_C<<(2*prec))\n v = p*CHUD_C*sqrtC//((q+CHUD_A*p)*CHUD_D)\n return v","def fourPtFiniteDiff(x,y):\n dydx = np.zeros(y.shape,float)\n for i in range(2,len(y)-2):\n a = y[i-2]\n b = y[i-1]\n c = y[i+1]\n d = y[i+2]\n dydx[i] = (a-8*b+8*c-d)/(12*(x[1]-x[0]))\n dydx[-1] = (y[-1]-y[-2])/(x[-1]-x[-2])\n dydx[-2] = (y[-2]-y[-3])/(x[-2]-x[-3])\n dydx[0] = (y[1]-y[0])/(x[1]-x[0])\n dydx[1] = (y[2]-y[1])/(x[2]-x[1])\n return dydx","def fdr_correction(pvals):\r\n tmp = array(pvals).astype(float) # this converts Nones to nans\r\n return tmp * tmp.size / (1. + argsort(argsort(tmp)).astype(float))","def pinpoint(f, J0, g0, x0, mu1, mu2, \\\r\n alow, Jalow, galow, ahigh, Jahigh, gahigh, p):\r\n j = 0\r\n Jprime0 = g0.T@p\r\n Jprimealow = galow.T@p\r\n amin = (2*alow*(Jahigh-Jalow)+Jprimealow*(alow**2-ahigh**2))/\\\r\n (2*(Jahigh-Jalow+Jprimealow*(alow-ahigh)))\r\n Jamin, gamin = f(x0+amin*p)\r\n while True:\r\n Jprimeamin = gamin.T@p\r\n if (Jamin > J0+mu1*amin*Jprime0) or (Jamin > Jalow):\r\n ahigh = amin\r\n Jahigh = Jamin\r\n amin = (2*alow*(Jahigh-Jalow)+Jprimealow*(alow**2-ahigh**2))/\\\r\n (2*(Jahigh-Jalow+Jprimealow*(alow-ahigh)))\r\n Jamin, gamin = f(x0+amin*p)\r\n else:\r\n if (np.abs(Jprimeamin) <= np.abs(mu2*Jprime0)): \r\n astar = amin\r\n return Jamin, gamin, astar\r\n elif (Jprimeamin*(ahigh-alow) >= 0):\r\n ahigh = alow\r\n alow = amin\r\n Jalow = Jamin\r\n galow = gamin\r\n Jprimealow = galow.T@p\r\n amin = (2*alow*(Jahigh-Jalow)+Jprimealow*(alow**2-ahigh**2))/\\\r\n (2*(Jahigh-Jalow+Jprimealow*(alow-ahigh)))\r\n Jamin, gamin = f(x0+amin*p)\r\n j += 1","def assign_fixedpoints(\n adata: anndata.AnnData,\n basis: str = \"pca\",\n cores: int = 1,\n copy: bool = False,\n) -> Union[None, anndata.AnnData]:\n logger = LoggerManager.gen_logger(\"dynamo-assign_fixedpoints\")\n logger.info(\"assign_fixedpoints begins...\", indent_level=1)\n logger.log_time()\n adata = copy_adata(adata) if copy else adata\n\n VecFld, func = vecfld_from_adata(adata, basis=basis)\n\n vecfld_class = base_vectorfield(\n X=VecFld[\"X\"],\n V=VecFld[\"Y\"],\n func=func,\n )\n\n (\n X,\n valid_fps_type_assignment,\n assignment_id,\n ) = vecfld_class.assign_fixed_points(cores=cores)\n assignment_id = [str(int(i)) if np.isfinite(i) else None for i in assignment_id]\n adata.obs[\"fps_assignment\"] = assignment_id\n adata.uns[\"fps_assignment_\" + basis] = {\n \"X\": X,\n \"valid_fps_type_assignment\": valid_fps_type_assignment,\n \"assignment_id\": assignment_id,\n }\n\n logger.finish_progress(\"assign_fixedpoints\")\n if copy:\n return adata\n return None","def fD(self, vpd):\n\t if vpd < 0.1:\n\t return 1.\n\t else:\n\t return 3/13./sqrt(vpd/1000.)","def test_fdr_correction(self):\r\n pvals = array([.1, .7, .5, .3, .9])\r\n exp = array([.5, .7 * 5 / 4., .5 * 5 / 3., .3 * 5 / 2., .9])\r\n obs = fdr_correction(pvals)\r\n self.assertFloatEqual(obs, exp)","def cal_pt(self):\n\n if not self.check_def(['E','px','py','pz']):\n sys.exit('Particle error: Quadri impulsion not define (error for pt routine)')\n\n self.pt =math.sqrt(self.px**2+self.py**2)","def Fw(X, p0, back):\n Eac, g = X\n return p0 * Eac * g + back","def ppf(self,x):\n # TODO speed this up by doing it in Crow, not in python\n if hasattr(x,'__len__'):\n returnPpf = np.array([self.ppf(i) for i in x])\n else:\n returnPpf = self._distribution.inverseCdf(x)\n return returnPpf","def rewofz_nonvector(x,y):\n ncut=27\n xy=x*y\n xyp=xy/jnp.pi\n exx=jnp.exp(-x*x)\n f=exx*erfcx(y)*jnp.cos(2.0*xy)+x*jnp.sin(xy)/jnp.pi*exx*jnp.sinc(xyp)\n n=jnp.arange(1,ncut+1)\n n2=n*n\n vec0=1.0/(0.25*n2+ y*y)\n vec1=jnp.exp(-(0.25*n2+x*x))\n vec2=jnp.exp(-(0.5*n+x)*(0.5*n+x))\n vec3=jnp.exp(-(0.5*n-x)*(0.5*n-x))\n Sigma1=jnp.dot(vec0,vec1)\n Sigma2=jnp.dot(vec0,vec2)\n Sigma3=jnp.dot(vec0,vec3)\n f = f + 1.0/jnp.pi*(-y*jnp.cos(2.0*xy)*Sigma1 + 0.5*y*Sigma2 + 0.5*y*Sigma3)\n return f","def calc_diff(f, dx):\n \n df = (np.roll(f,-3)/60.-np.roll(f,-2)*3./20.+np.roll(f,-1)*3./4.-np.roll(f,1)*3./4.+np.roll(f,2)*3./20.-np.roll(f,3)/60.)/dx\n df[0] = (-21600./13649.*f[0]+81763./40947.*f[1]+131./27298.*f[2]-9143./13649.*f[3]+20539./81894.*f[4])/dx\n df[1] = (-81763./180195.*f[0]+7357./36039.*f[2]+30637./72078.*f[3]-2328./12013.*f[4]+6611./360390.*f[5])/dx\n df[2] = (-131./54220.*f[0]-7357./16266.*f[1]+645./2711.*f[3]+11237./32532.*f[4]-3487./27110.*f[5])/dx\n df[3] = (9143./53590.*f[0]-30637./64308.*f[1]-645./5359.*f[2]+13733./32154.*f[4]-67./4660.*f[5]+72./5359.*f[6])/dx\n df[4] = (-20539./236310.*f[0]+2328./7877.*f[1]-11237./47262.*f[2]-13733./23631.*f[3]+89387./118155.*f[5]-1296./7877.*f[6]+144./7877.*f[7])/dx\n df[5] = (-6611./262806.*f[1]+3487./43801.*f[2]+1541./87602.*f[3]-89387./131403.*f[4]+32400./43801.*f[6]-6480./43801.*f[7]+720./43801.*f[8])/dx\n df[-1] = -(-21600./13649.*f[-1]+81763./40947.*f[-2]+131./27298.*f[-3]-9143./13649.*f[-4]+20539./81894.*f[-5])/dx\n df[-2] = -(-81763./180195.*f[-1]+7357./36039.*f[-3]+30637./72078.*f[-4]-2328./12013.*f[-5]+6611./360390.*f[-6])/dx\n df[-3] = -(-131./54220.*f[-1]-7357./16266.*f[-2]+645./2711.*f[-4]+11237./32532.*f[-5]-3487./27110.*f[-6])/dx\n df[-4] = -(9143./53590.*f[-1]-30637./64308.*f[-2]-645./5359.*f[-3]+13733./32154.*f[-5]-67./4660.*f[-6]+72./5359.*f[-7])/dx\n df[-5] = -(-20539./236310.*f[-1]+2328./7877.*f[-2]-11237./47262.*f[-3]-13733./23631.*f[-4]+89387./118155.*f[-6]-1296./7877.*f[-7]+144./7877.*f[-8])/dx\n df[-6] = -(-6611./262806.*f[-2]+3487./43801.*f[-3]+1541./87602.*f[-4]-89387./131403.*f[-5]+32400./43801.*f[-7]-6480./43801.*f[-8]+720./43801.*f[-9])/dx\n\n return df","def f(self, X):\n\n return (X[0])**3 - (X[1])**2 + 1","def NR(ip, fp):\n x = fp[0] - ip[0]\n y = fp[1] - ip[1]\n r = sqrt(x ** 2 + y ** 2)\n return array([-y / r, x / r])","def flipy(self, p):\n return int(p.x), int(-p.y+self.h)","def FMScore(x,p,d):\n \n if x <= d[p][0.20]:\n return 1\n elif x <= d[p][0.4]:\n return 2\n elif x <= d[p][0.6]: \n return 3\n elif x <= d[p][0.8]:\n return 4\n else:\n return 5","def FMScore(x,p,d):\n \n if x <= d[p][0.20]:\n return 1\n elif x <= d[p][0.4]:\n return 2\n elif x <= d[p][0.6]: \n return 3\n elif x <= d[p][0.8]:\n return 4\n else:\n return 5","def optimizeposition(areas, omegas, x0, x1, z0, z1):\n\n # initial position of each quadpoint is at the center\n # of the edge connecting the midpoint and a corner point\n rhos = 0.5 * ones(4)\n a = 1 / sqrt(3)\n deltarhos = 0.25 * ones(4) # delta for finite differences\n\n while True: # while method has not converged\n # print(\"################## new iteration #############\")\n rhs = f(rhos, omegas, a, x0, x1, z0, z1, areas)\n print(\"##\")\n print(rhs)\n print(rhos)\n if norm(rhs) < 1e-5:\n break\n mat = df(rhos, omegas, a, x0, x1, z0, z1, areas, deltarhos)\n update = solve(mat, rhs)\n\n rhos += update\n # for i in range(4):\n # rhos[i] = max(0,min(1,rhos[i]))\n \"\"\"\n print(\"the norm of the rhs is \")\n print(norm(rhs))\n print(mat)\n print(\"rhs\")\n print(rhs)\n print(update)\n print(\"rhos\")\n print(rhos)\n \"\"\"\n # print(alpha)\n return rhos","def find_root(function, point_a, point_b, step, tol, max_iterations, \n show_process = False):\n left_point , right_point = search_interval_3d(function, point_a, point_b, \n step, tol, max_iterations,\n show_process)\n \n point_where_zero = bisection_3d(function, left_point, right_point, tol, \n max_iterations, show_process)\n \n return point_where_zero","def downhill(F, xStart, args=None, side=0.1, ftol=1.0e-6, xtol=1.0e-6, maxiter=1000, maxfunc=1000, maxiternochange=10):\n # TODO: check the types of the input ???\n\n # print \"Entering downhill\"\n n = len(xStart)\n x = np.zeros((n+1, n), dtype=float) #point null matrix, n+1 rows, n columns\n f = np.zeros(n+1, dtype=float) # null vector, n+1 columns\n p_count = 0 # counter for detecting a plateau\n f_count = 0 # counter for the number of function call\n f_best_count = 0 # counter for the number of iterations in which the best solution does not change\n f_best_prev = 0.0 # holds the best value from the previous iteration\n epsilon = 0.001 # tolerance for considering two values as equal\n # max_iter_no_change = 10 # maximum number of accepted iterations with no change in the optimal solution\n precision = 2\n round_map = partial(round, ndigits=precision) # partial function for rounding purposes\n\n # initial simplex\n x[0] = xStart\n for i in xrange(1, n+1):\n x[i] = xStart\n x[i,i-1] = xStart[i-1] + side\n\n # print \"Evaluate the starting points\"\n # compute the value of F at the vertices of the simplex\n for i in xrange(n+1):\n f[i] = F(x[i], args)\n # p_count += 1\n\n # main loop\n # print \"Start iterating\"\n for k in xrange(maxiter):\n\n # check the number of function calls\n if f_count > maxfunc:\n print \"Stopping criteria: maximum number of function calls\"\n print \"Best solution so far: \", x[iLo], \" value: \", f[iLo], \" at iteration:\", k\n # return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': (args['Q1'], args['Q2'], args['Q3']), 'stopping': 'MAXFUNCALL'}\n return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': [args['Q{}'.format(h)] for h in xrange(1, args['retailers']+1)], 'stopping': 'MAXFUNCALL'}\n\n # find the best and worst vertex (consider a minimization problem)\n iLo = np.argmin(f) # best vertex\n iHi = np.argmax(f) # worst vertex\n\n # print k,\" \", f[iLo]\n #\n # if f[iLo] < -0.310000:\n # print f[iLo]\n # print x[iLo]\n # print x\n # sys.exit(1)\n # print \"k: \", k, \" f_best_prev: \", f_best_prev, \" f[iLo]: \", f[iLo], \" f_best_count: \", f_best_count\n # print \"Beginning of iteration: %4d | Best x: %4f %4f %4f | Best value: %f\" % (k, x[iLo][0], x[iLo][1], x[iLo][2], f[iLo])\n # print \"x: \", x, \" f: \", f\n # print \"=========================================================================================\"\n # check if the solution has changed from the previous iterations\n if f[iLo] < f_best_prev:\n f_best_prev = f[iLo]\n f_best_count = 0\n else:\n f_best_count += 1\n\n if f_best_count > maxiternochange:\n print \"Stopping criteria: maximum number of iterations with no improvement in the best solution\"\n print \"Best solution so far: \", x[iLo], \" value: \", f[iLo], \" at iteration:\", k\n # return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': (args['Q1'], args['Q2'], args['Q3']), 'stopping': 'NOIMPROVEMENT'}\n return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': [args['Q{}'.format(h)] for h in xrange(1, args['retailers']+1)], 'stopping': 'NOIMPROVEMENT'}\n\n if abs(f[iLo] - f[iHi]) < ftol: # If difference between highest and lowest is smaller than ftol, return\n print \"Stopping criteria: difference between highest and lowest points is smaller than tolerance\"\n print \"Best solution so far: \", x[iLo], \" value: \", f[iLo], \" at iteration:\", k\n # return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': (args['Q1'], args['Q2'], args['Q3']), 'stopping': 'MAXTOLERANCE'}\n return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': [args['Q{}'.format(h)] for h in xrange(1, args['retailers']+1)], 'stopping': 'MAXTOLERANCE'}\n # compute the move vector d\n d = (-(n+1) * x[iHi] + np.sum(x, axis=0)) / n\n # print \"d: \", d\n\n # check for convergence\n if sqrt(np.dot(d, d)/n) < xtol: # length of the vector d\n print \"Stopping criteria: length of step d smaller than tolerance\"\n print \"Best solution so far: \", x[iLo], \" value: \", f[iLo], \" at iteration:\", k\n # return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': (args['Q1'], args['Q2'], args['Q3']), 'stopping': 'SMALLSTEP'}\n return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': [args['Q{}'.format(h)] for h in xrange(1, args['retailers']+1)], 'stopping': 'SMALLSTEP'}\n # try reflection\n xNew = np.array(map(round_map, x[iHi] + 2 * d))\n fNew = F(xNew, args)\n f_count += 1\n # print \"Reflected point: \", xNew, \" value: \", fNew\n\n # check for no improvement over the worst point\n # and for plateau condition\n if f[iHi] - epsilon <= fNew <= f[iHi] + epsilon:\n p_count += 1\n # print \"No improvement here\"\n\n if p_count == n+2: # we reflected all vertices with no improvement\n print \"Stopping criteria: Probably we landed on a plateau... exiting\" # TODO: restart instead of exiting\n print \"Best solution so far: \", x[iLo], \" value: \", f[iLo], \" at iteration:\", k\n # return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': (args['Q1'], args['Q2'], args['Q3']), 'stopping': 'PLATEAU'}\n return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': [args['Q{}'.format(h)] for h in xrange(1, args['retailers']+1)], 'stopping': 'PLATEAU'}\n\n\n else:\n p_count = 0\n\n\n if fNew <= f[iLo]: # if the new value is better than the best so far,\n x[iHi] = xNew # substitute the worst vertex with the new one\n f[iHi] = fNew\n\n # try to expand the reflection\n xNew = np.array(map(round_map, x[iHi] + d))\n fNew = F(xNew, args)\n f_count += 1\n # print \"Expanded point: \", xNew, \" value: \", fNew\n\n if fNew <= f[iHi]: # in the original source version it is f[iLo] (?)\n x[iHi] = xNew\n f[iHi] = fNew\n else:\n # try reflection again\n if fNew <= f[iHi]:\n x[iHi] = xNew\n f[iHi] = fNew\n else:\n # try contraction\n xNew = np.array(map(round_map, x[iHi] + 0.5 * d))\n fNew = F(xNew, args)\n f_count += 1\n # print \"Contracted point: \", xNew, \" value: \", fNew\n\n if fNew <= f[iHi]: # accept contraction\n x[iHi] = xNew\n f[iHi] = fNew\n else:\n # shrink\n for i in xrange(len(x)):\n if i != iLo:\n x[i] = np.array(map(round_map, x[i] - x[iLo] * 0.5))\n f[i] = F(x[i], args)\n f_count += 1\n\n # print \"End of iteration: %4d | Best x: %4f %4f %4f | Best value: %f\" % (k, x[iLo][0], x[iLo][1], x[iLo][2], f[iLo])\n # print \"x: \", x, \" f: \", f\n # print \"*\"*50\n # print \"\"\n\n\n\n print \"Stopping criteria: maximum number of iterations\"\n print \"Best solution so far: \", x[iLo], \" value: \", f[iLo], \" at iteration:\", k\n # return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': (args['Q1'], args['Q2'], args['Q3']), 'stopping': 'MAXITERATION'}\n return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': [args['Q{}'.format(h)] for h in xrange(1, args['retailers']+1)], 'stopping': 'MAXITERATION'}","def fpart(x):\n return x - np.floor(x)","def f1(x):\n return x**3 - 2*x + 2","def fcp(self, var='x'):\n return self.charpoly(var).factor()","def eval_is_fixed(leaf, eval_from_search):\n check_val = nn_evaluate.evaluate(leaf)\n if leaf.side_to_move() == Side.B:\n check_val *= -1\n check_val = min(max(check_val/1000, -1), 1)\n if abs(check_val - eval_from_search) > .0008:\n if abs(eval_from_search) != 0 and abs(eval_from_search) != 1:\n print(\"fixed.. searchval:\", eval_from_search, \"nnval:\", check_val, \"fen\", leaf.fen())\n return True\n return False","def friction_factor(v1: \"int\", v2: \"int\") -> \"int\":","def F(self, x):\n F = np.zeros((1, x.shape[-1]))\n # Column indices of state vectors that fulfill the condition z<z0\n contact = x[1, :]<self.z0\n F[0, ~contact] = -self.H*self.R/(6*x[1, ~contact]**2)\n F[0, contact] = (4/3)*self.E*np.sqrt(self.R)*(self.z0 - x[1, contact])**1.5 - self.H*self.R/(6*self.z0**2)\n\n return F"],"string":"[\n \"def fixed_point(is_zero, plus, minus, f, x):\\n\\n @memo_Y\\n def _fixed_point(fixed_point_fun):\\n def __fixed_point(collected, new):\\n diff = minus(new, collected)\\n if is_zero(diff):\\n return collected\\n return fixed_point_fun(plus(collected, diff), f(diff))\\n return __fixed_point\\n\\n return _fixed_point(x, f(x))\",\n \"def fixed_point(x, int_bits, frac_bits):\\n if int_bits == None and frac_bits == None: return x\\n _frac = x - np.floor(x) #if x >= 0 else x - np.ceil(x)\\n _int = np.floor(x) #if x>= 0 else np.ceil(x)\\n _frac = np.round(_frac*2**frac_bits)/2**frac_bits\\n _x = _int + _frac\\n # if _x > 2**(int_bits-1)-1: _x = 2**(int_bits-1)-1\\n # elif _x < -2**(int_bits-1): _x = -2**(int_bits-1)\\n if _x > 2**(int_bits)-2**(-frac_bits): _x = 2**(int_bits)-2**(-frac_bits)\\n elif _x < -2**(int_bits): _x = -2**(int_bits)\\n return _x\",\n \"def fixed(self):\\n return self.f_fixed().m_fixed()\",\n \"def test_fixed_point_system(testFunctions, tol, printFlag): \\n pass\",\n \"def test_fixed_point(testFunctions, tol, printFlag): \\n pass\",\n \"def fixed_point(func, init, **kwargs):\\n\\n def fixed_func(mix):\\n \\\"\\\"\\\"Labeling function for a fixed point\\\"\\\"\\\"\\n return np.argmin((mix == 0) - mix + func(mix))\\n\\n return labeled_subsimplex(fixed_func, init, **kwargs)\",\n \"def fppp(x):\\n return (-2000.00*math.cos(10.0.x+1))\",\n \"def fix_point_arithmetic(self):\\n\\n return self._fixpntar\",\n \"def f(x0: float, x1: float) -> float:\\n return 8 - (x0 - 2) ** 2 - (x1 - 2) ** 2\",\n \"def calculate_prp(self, ref_point: np.ndarray, f_current: np.ndarray) -> np.ndarray:\\n\\n # distance\\n d = np.linalg.norm(np.atleast_2d(ref_point - f_current))\\n\\n # unit vectors\\n ei = np.array([np.zeros(len(ref_point))])\\n es = np.repeat(ei, len(ref_point), axis=0)\\n\\n for i, j in enumerate(es):\\n for ind, _ in enumerate(j):\\n if ind == i:\\n j[ind] = 1\\n\\n return ref_point + (d * es)\",\n \"def def_mpf_constant(fixed):\\n def f(prec, rnd=round_fast):\\n wp = prec + 20\\n v = fixed(wp)\\n if rnd in (round_up, round_ceiling):\\n v += 1\\n return normalize(0, v, -wp, bitcount(v), prec, rnd)\\n f.__doc__ = fixed.__doc__\\n return f\",\n \"def ppf(self,x):\\n ppfValue = self.invCDF(x)\\n return ppfValue\",\n \"def fpp(x):\\n return (-200.0*math.sin(10.0*x+1.0))\",\n \"def _correct_p(self, f0, f1):\\n return self.p * np.exp(self.dbeta * (f0 + f1) / 2)\",\n \"def return_zeropoint():\\n return 22.5\",\n \"def classify_fixedpoints(fps, scale):\\n\\n x_directions = []\\n scale = scale\\n for fp in fps:\\n\\n trace = np.matrix.trace(fp['jac'])\\n det = np.linalg.det(fp['jac'])\\n if det > 0 and trace == 0:\\n print('center has been found. Watch out for limit cycles')\\n elif trace**2 - 4 * det == 0:\\n print(\\\"star nodes has been found.\\\")\\n elif trace**2 - 4 * det < 0:\\n print(\\\"spiral has been found\\\")\\n e_val, e_vecs = np.linalg.eig(fp['jac'])\\n ids = np.argwhere(np.real(e_val) > 0)\\n countgreaterzero = np.sum(e_val > 0)\\n if countgreaterzero == 0:\\n print('stable fixed point was found.')\\n fp['fp_stability'] = 'stable fixed point'\\n elif countgreaterzero > 0:\\n print('saddle point was found.')\\n fp['fp_stability'] = 'saddle point'\\n for id in ids:\\n x_plus = fp['x'] + scale * e_val[id] * np.real(e_vecs[:, id].transpose())\\n x_minus = fp['x'] - scale * e_val[id] * np.real(e_vecs[:, id].transpose())\\n x_direction = np.vstack((x_plus, fp['x'], x_minus))\\n x_directions.append(np.real(x_direction))\\n\\n return fps, x_directions\",\n \"def PointMilieu(x,f):\\n\\tNx = f.shape[0]\\n\\tS=0.0\\n\\tfor i in range(0,Nx-1):\\n\\t\\tS=S+f[i]*(x[i+1]-x[i]) \\n\\treturn S\",\n \"def ppf(self,x):\\n if self.base == 'natural':\\n ppfValue = math.exp((self.upperBound-self.lowerBound)*x + self.lowerBound)\\n else:\\n ppfValue = 10.**((self.upperBound-self.lowerBound)*x + self.lowerBound)\\n return ppfValue\",\n \"def find_zero(f, df):\\n def near_zero(x):\\n return approx_eq(f(x), 0)\\n return improve(newton_update(f, df), near_zero)\",\n \"def _compute_f(self, p, dh, dv):\\n return dh / (self.beta * p * dv)\",\n \"def p2f (p):\\n #return 11000**((p+1)/2)\\n #return (p+1)*11000\\n return (p+1)*5500\",\n \"def p() -> float:\\n return 0.9\",\n \"def jacobian(kernel: Kern, variable_points: ndarray, fixed_points: ndarray) -> ndarray:\\n if isinstance(kernel, RBF):\\n lengthscale = kernel.lengthscale.values[0]\\n k = kernel.K(variable_points, fixed_points)\\n\\n # The (i, j, k)-th element of this is the k-th component of X_i - D_j.\\n differences = variable_points[:, newaxis, :] - fixed_points[newaxis, :, :]\\n\\n return -k[:, :, newaxis] * differences / (lengthscale ** 2)\\n else:\\n raise NotImplementedError\",\n \"def fixed_points(self, epsilon = 0.000001):\\n # (a b) (z) = (Lz)\\n # (c d) (1) ( L) \\n\\n # az + b = c z^2 + d z\\n # 0 = c z^2 + (d-a)z - b\\n # z = ((a-d) \\\\pm sqrt( (a-d)^2 + 4 bc )) / 2c\\n\\n a, b, c, d = self\\n\\n assert abs(c) > epsilon\\n zp = ((a - d) + sqrt( (a - d)**2 + 4*b*c)) / 2*c\\n zm = ((a - d) - sqrt( (a - d)**2 + 4*b*c)) / 2*c\\n Lp = c*zp + d\\n Lm = c*zm + d\\n if abs(Lp) < abs(Lm):\\n Ls = [Lp, Lm]\\n out = [zp, zm]\\n else:\\n Ls = [Lm, Lp]\\n out = [zm, zp] \\n assert abs(Ls[0]) < 1 - epsilon and 1 + epsilon < abs(Ls[1])\\n return [CP1((z,1)) for z in out]\",\n \"def fpr(self):\\n return float(self.fp) / (self.fp + self.tn) if self.tn != 0 else 1\",\n \"def phi_fixed(prec):\\n prec += 10\\n a = isqrt_fast(MPZ_FIVE<<(2*prec)) + (MPZ_ONE << prec)\\n return a >> 11\",\n \"def apoint(rpoint):\\r\\n tempy = gv[\\\"fixedLL\\\"][1] + gv[\\\"globalscale\\\"]*rpoint[1]*(gv[\\\"fixedUR\\\"][1]-gv[\\\"fixedLL\\\"][1])\\r\\n if gv[\\\"localxscale\\\"] != -1:\\r\\n tempx = gv[\\\"fixedLL\\\"][0] + gv[\\\"localxscale\\\"]*gv[\\\"globalscale\\\"]*rpoint[0]*(gv[\\\"fixedUR\\\"][0]-gv[\\\"fixedLL\\\"][0])\\r\\n else:\\r\\n tempx = gv[\\\"fixedLL\\\"][0] + gv[\\\"globalscale\\\"]*rpoint[0]*(gv[\\\"fixedUR\\\"][0]-gv[\\\"fixedLL\\\"][0])\\r\\n if tempx - gv[\\\"fixedUR\\\"][0] > 0 and tempx - gv[\\\"fixedUR\\\"][0] < 1e-7:\\r\\n tempx = gv[\\\"fixedUR\\\"][0]\\r\\n if tempx > gv[\\\"fixedUR\\\"][0]:\\r\\n print ( \\\"problem x value : \\\",tempx, \\\" max x allowed : \\\",gv[\\\"fixedUR\\\"][0])\\r\\n return [tempx,tempy]\",\n \"def fCalc(self):\\n # A dictionary composed of all internal and boundary points\\n allPoints = dict(self.internalPoints.items() + self.boundaryPoints.items())\\n\\n for pointLabel in allPoints.keys():\\n # Compute fE, fW, fN and fW only for internal mesh points\\n if allPoints[pointLabel].type.lower() == 'internal':\\n xLabel = pointLabel[0]\\n yLabel = pointLabel[1]\\n x = self.internalPoints[(xLabel,yLabel)].x\\n y = self.internalPoints[(xLabel,yLabel)].y\\n xE = allPoints[(xLabel + 1,yLabel)].x\\n xW = allPoints[(xLabel - 1,yLabel)].x\\n yN = allPoints[(xLabel,yLabel + 1)].y\\n yS = allPoints[(xLabel,yLabel - 1)].y\\n \\n if (xE - x)/self.h < -0.000001 or (xE - x)/self.h > 1.000001:\\n errorMessage = '**Error! (xE - x)/h for the point with label ('+str(xLabel) + ',' + str(yLabel) + ') and coordinate (' + str(x) + ',' + str(y) + ') is not between zero and one: (xE - x)/h = ' + str((xE - x)/self.h)\\n raise customError(errorMessage)\\n else:\\n self.internalPoints[(xLabel,yLabel)].fE = (xE - x)/self.h\\n\\n # Note that in the following we use -0.000001 and 1.000001 \\n # instead of 0 and 1, respectively, to avoid problems with\\n # with very small fractions. For example if the fractions is\\n # greater than one by 2.22e-16 the condition (x - xW)/self.h > 1\\n # will be false and the code returns an error\\n if (x - xW)/self.h < -0.000001 or (x - xW)/self.h > 1.000001:\\n errorMessage = '**Error! (x - xW)/h for the point with label ('+str(xLabel) + ',' + str(yLabel) + ') and coordinate (' + str(x) + ',' + str(y) + ') is not between zero and one: (x - xW)/h = ' + str((x - xW)/self.h)\\n raise customError(errorMessage)\\n else:\\n self.internalPoints[(xLabel,yLabel)].fW = (x - xW)/self.h\\n \\n if (yN - y)/self.h < -0.000001 or (yN - y)/self.h > 1.000001:\\n errorMessage = '**Error! (yN - y)/h for the point with label ('+str(xLabel) + ',' + str(yLabel) + ') and coordinate (' + str(x) + ',' + str(y) + ') is not between zero and one: (yN - y)/h = ' + str((yN - y)/self.h)\\n raise customError(errorMessage)\\n else:\\n self.internalPoints[(xLabel,yLabel)].fN = (yN - y)/self.h\\n \\n if (y - yS)/self.h < -0.000001 or (y - yS)/self.h > 1.000001:\\n errorMessage = '**Error! (y - yS)/h for the point with label ('+str(xLabel) + ',' + str(yLabel) + ') and coordinate (' + str(x) + ',' + str(y) + ') is not between zero and one: (y - yS)/h = ' + str((y - yS)/self.h)\\n raise customError(errorMessage)\\n else:\\n self.internalPoints[(xLabel,yLabel)].fS = (y - yS)/self.h\\n \\n # Calculate the coeeficients requried to compute the Laplacian \\n self.internalPoints[(xLabel,yLabel)].LapCoeffCalc()\",\n \"def ppf(self,x):\\n if self.method == 'spline':\\n ppfValue = self._distribution.inverseCdf(x,random())\\n else:\\n self.raiseAnError(NotImplementedError,'ppf is not yet implemented for ' + self.method + ' method')\\n return ppfValue\",\n \"def fixed_point_multiply(data, multiplier, shift):\\n return _make.fixed_point_multiply(data, multiplier, shift)\",\n \"def solve(self, f: sym.Function, start: float):\\n if self.__doVisual:\\n self.__visualisiere(f, style='r', description='f(' + str(self.__symbol) + ')=' + str(f))\\n\\n self.__ableitung = f.diff(self.__symbol)\\n self.__funktion = f\\n self.__tries = 0\\n current_point = start\\n current_div = abs(f.evalf(subs={self.__symbol: current_point}))\\n # wiederholen bis genauigkeit erreicht oder das Maximum der Versuche erreicht ist\\n while current_div > self.__precision and self.__tries < self.__max_tries:\\n current_point = self.__do_newton(f, current_point)\\n result = self.__evaluate(current_point)\\n current_div = abs(result)\\n self.__tries = self.__tries + 1\\n\\n if self.__doVisual:\\n self.__visual_result()\\n return current_point, current_div\",\n \"def f_fixed(self):\\n self.fx_free = self.fy_free = self.fz_free = False\\n return self\",\n \"def fd_center(f, h, x0):\\n return (f(x0 + h) - 2*f(x0) + f(x0 - h))/(h**2)\",\n \"def _fv(self):\\n return self.beta * (self.x ** self.c)\",\n \"def diff_1st_central(fp, fm, eps):\\n \\n return (fp - fm)/(2.0*eps)\",\n \"def ppf(self,x):\\n ppfValue = self._distribution.inverseCdf(x,random())\\n return ppfValue\",\n \"def ppf(self,x):\\n ppfValue = self._distribution.inverseCdf(x,random())\\n return ppfValue\",\n \"def _centred_first_derivs(self, f):\\n return ((f[2:, 1:-1] - f[0:-2, 1:-1]) / (2 * self._dx),\\n (f[1:-1, 2:] - f[1:-1, 0:-2]) / (2 * self._dy))\",\n \"def convergent_point_guarded(x0, x1, y, f):\\n d0 = distance(x0, y, f)\\n d1 = distance(x1, y, f)\\n if d0 < d1:\\n x1 = power_unary(x1, d1 - d0, f)\\n elif d1 < d0:\\n x0 = power_unary(x0, d0 - d1, f)\\n return convergent_point(x0, x1, f)\",\n \"def FindClosestPointWithinRadius(self, p_float, , p_float_4):\\n ...\",\n \"def compute_fpa_welfare(bidders, anonymous_reserve, points=1000):\\r\\n wel = 0.0\\r\\n for i in range(len(bidders[0].strategy.F_jump_points) - 1):\\r\\n bid_range_start = bidders[0].strategy.F_jump_points[i][0]\\r\\n bid_range_end = bidders[0].strategy.F_jump_points[i + 1][0]\\r\\n if bid_range_start < bid_range_end:\\r\\n num_points = max(100, int(points / (\\r\\n bidders[0].strategy.F_jump_points[-1][0] - bidders[0].strategy.F_jump_points[0][0]) *\\r\\n (bidders[0].strategy.F_jump_points[i + 1][0] - bidders[0].strategy.F_jump_points[i][0])))\\r\\n bid_range = np.linspace(bidders[0].strategy.F_jump_points[i][0],\\r\\n bidders[0].strategy.F_jump_points[i + 1][0],\\r\\n num=num_points)\\r\\n bid_range = bid_range[1:]\\r\\n\\r\\n wel_b = [0.0] * len(bid_range)\\r\\n for j in range(len(bid_range)):\\r\\n cdf, _, active_values = prob_dist(bidders, bid_range[j])\\r\\n if len(active_values) <= 1:\\r\\n wel_b[j] = 0.0\\r\\n else:\\r\\n wel_b[j] = np.prod(cdf) * (sum(active_values) / (len(active_values) - 1.0) *\\r\\n sum(1.0 / (np.array(active_values) - bid_range[j])) -\\r\\n sum(np.array(active_values) / (np.array(active_values) - bid_range[j])))\\r\\n wel += integrate.simps(wel_b, bid_range)\\r\\n\\r\\n # point mass at min winning bid\\r\\n min_winning_bid = max(compute_min_winning_bid(bidders), anonymous_reserve)\\r\\n values = [[-1.0] for _ in range(len(bidders))]\\r\\n probs = [[0.0] for _ in range(len(bidders))]\\r\\n for i in range(len(bidders)):\\r\\n bidder = bidders[i]\\r\\n F_min_winning_bid = bidder.strategy.F_jump_points[0][1]\\r\\n for j in range(len(bidder.prob)):\\r\\n if bidder.values[j] < min_winning_bid:\\r\\n probs[i][0] += bidder.prob[j]\\r\\n elif sum(bidder.prob[:j]) < F_min_winning_bid:\\r\\n values[i].append(bidder.values[j])\\r\\n probs[i].append(min(bidder.prob[j], F_min_winning_bid - sum(bidder.prob[:j])))\\r\\n else:\\r\\n break\\r\\n\\r\\n for i in range(len(bidders)):\\r\\n for i_value_idx in range(1, len(values[i])):\\r\\n i_value = values[i][i_value_idx]\\r\\n if i_value == 0.0:\\r\\n continue\\r\\n winning_prob = probs[i][i_value_idx]\\r\\n for j in range(len(bidders)):\\r\\n if j == i:\\r\\n continue\\r\\n j_losing_prob = 0.0\\r\\n for j_value_idx in range(len(values[j])):\\r\\n j_value = values[j][j_value_idx]\\r\\n if j_value < i_value or (j_value == i_value and j < i):\\r\\n j_losing_prob += probs[j][j_value_idx]\\r\\n winning_prob *= j_losing_prob\\r\\n wel += winning_prob * i_value\\r\\n return wel\",\n \"def set_starting_point(f, x_input):\\n\\n k = 2\\n bnd1_fda = FloatDPApproximation(x_input)\\n bnd2_fda = bnd1_fda - k * (f(bnd1_fda) / derivative(f, bnd1_fda))\\n bnd1_float = float(str(bnd1_fda))\\n bnd2_float = float(str(bnd2_fda))\\n if bnd1_float < bnd2_float:\\n ix = UpperInterval({cast_exact(bnd1_float): cast_exact(bnd2_float)})\\n else:\\n ix = UpperInterval({cast_exact(bnd2_float): cast_exact(bnd1_float)})\\n\\n x = cast_singleton(ix)\\n x_end = FloatDPApproximation(x)\\n return x_end\",\n \"def compute_fk(self, sigma, sigma_des, C, offset):\\n if sigma >= sigma_des:\\n # push robot away\\n f = -((sigma - sigma_des) ** 2)/C + offset\\n elif sigma < sigma_des:\\n # pull robot in\\n f = ((sigma - sigma_des) ** 2)/C + offset\\n else:\\n f = 0\\n return f\",\n \"def F(x):\\n soln = x - (1.0/5.0)*math.cos(10.0*x+1.0) \\n return soln\",\n \"def fix_point(h, lower, upper):\\n return brentq(lambda x: x - h(x), lower, upper)\",\n \"def parabolic(self, f, x):\\n\\t # Requires real division. Insert float() somewhere to force it?\\n\\t xv = 1 / 2 * (f[x - 1] - f[x + 1]) / (f[x - 1] - 2 * f[x] + f[x + 1]) + x\\n\\t yv = f[x] - 1 / 4 * (f[x - 1] - f[x + 1]) * (xv - x)\\n\\t return (xv, yv)\",\n \"def my_Newton( fct, df_dx, x0):\\r\\n xn = float(x0)\\r\\n eps = 1e-5\\r\\n N = 20\\r\\n i = 0\\r\\n while abs( fct( xn**(i + 1)) - fct( xn**i)) > eps and i < N:\\r\\n x_next = xn - fct(xn)/df_dx(xn)\\r\\n print( i, 'fct value', abs( fct(xn)), x_next)\\r\\n xn = x_next\\r\\n i += 1\\r\\n if abs( fct( xn)) < eps:\\r\\n return x_next\\r\\n else: #solution did not converge\\r\\n return np.nan\",\n \"def convergent_point(x0, x1, f):\\n while x0 != x1:\\n x0, x1 = f(x0), f(x1)\\n return x0\",\n \"def pofd(self):\\n return self.table[0, 1] / (self.table[0, 1] + self.table[1, 1])\",\n \"def pointlength(x):\\n return 0.0\",\n \"def my_Newton(fct, df_dx, x0):\\r\\n xn = float(x0)\\r\\n eps = 1e-5\\r\\n N = 20\\r\\n i = 0\\r\\n while abs(fct (xn)) > eps and i < N:\\r\\n x_next = xn - fct(xn)/df_dx(xn)\\r\\n print(i , 'fct_value', abs(fct(xn)), x_next)\\r\\n xn = x_next\\r\\n i += 1\\r\\n if abs(fct(xn)) < eps:\\r\\n return x_next\\r\\n else: #solution did not converge\\r\\n return np.nan\",\n \"def FrictionF(self,eta):\\n return -3*3.14*eta*self.par.d*self.par.vel\",\n \"def fpppp(x):\\n return (20000.0*math.sin(10.0*x+1.0))\",\n \"def F(self, points):\\n\\n # Perform calculation in the frame parallel to the ellipse\\n # and then rotate it back\\n rotatedP = self.rotatePoint(points)\\n\\n surface_pot = np.sqrt((rotatedP[..., 0]/self.axisA[:, None])**2 + (rotatedP[..., 1]/self.axisB[:, None])**2)\\n\\n # Force = -grad potential\\n # swapaxes is necesary to make the created\\n # force array of shape [N_samples, N-particles, 2]\\n\\n surface_force = - 1/surface_pot[..., None]*np.array([\\n rotatedP[..., 0]/self.axisA[:, None]**2, \\n rotatedP[..., 1]/self.axisB[:, None]**2\\n ]).swapaxes(0, 2).swapaxes(0, 1) \\n\\n # Rotate back to the original frame\\n surface_force = self.rotatePoint(surface_force, -1)\\n\\n # Force is scaled with A_conf and applied only if the particle is outside\\n return self.A_conf*surface_force*self.isOutside(points)[:, :, None]\",\n \"def ppf(self,x):\\n if x > 1.0 or x < 0:\\n self.raiseAnError(IOError,'Categorical distribution cannot calculate ppf for', str(x), '! Valid value should within [0,1]!')\\n sortedMapping = sorted(self.mapping.items(), key=operator.itemgetter(0))\\n if x == 1.0:\\n return float(sortedMapping[-1][0]) if self.isFloat else sortedMapping[-1][0]\\n else:\\n cumulative=0.0\\n for element in sortedMapping:\\n cumulative += element[1]\\n if cumulative >= x:\\n return float(element[0]) if self.isFloat else element[0]\",\n \"def p2f(self):\\n\\n stale = self.m_f\\n self.m_f = self.v.b / self.m_v\",\n \"def e_fixed(prec):\\n # Slight overestimate of N needed for 1/N! < 2**(-prec)\\n # This could be tightened for large N.\\n N = int(1.1*prec/math.log(prec) + 20)\\n p, q = bspe(0,N)\\n return ((p+q)<<prec)//q\",\n \"def calibrate_nopp(fundamental):\\n thresh = 0.09682\\n m1 = -0.1014\\n b1 = 0.2839\\n m2 = -0.065\\n b2 = 0.21\\n state1 = (fundamental < thresh)\\n\\n cal_fun = copy.copy(fundamental)\\n cal_fun[state1] = 10**((fundamental[state1] - b1) / m1)\\n cal_fun[~state1] = 10**((fundamental[~state1] - b2) / m2)\\n return cal_fun\",\n \"def erfc(x):\\n return 0.0\",\n \"def __v(pk: float, pna: float, pcl: float, pca: float) -> float:\\n ex_ion = pk * ex_k + pna * ex_na + pcl * in_cl + pca * ex_ca\\n in_ion = pk * in_k + pna * in_na + pcl * ex_cl + pca * in_ca\\n v = r * t / f * np.log(ex_ion/in_ion) * 1000\\n return v\",\n \"def cal_frost_point(dew_point):\\n\\n nalts = dew_point.shape[0]\\n frost_point = np.NaN * np.zeros_like(dew_point)\\n log_es = -0.58002206e4 / dew_point + 1.3914993 - 0.48640239e-1 \\\\\\n * dew_point + 0.41764768e-4 * dew_point ** 2 - 0.14452093e-7 \\\\\\n * dew_point ** 3 + 0.65459673e1 * np.log(dew_point)\\n\\n for j in range(nalts):\\n if dew_point[j] < 273.15 and np.isfinite(dew_point[ j]):\\n try:\\n frost_point[ j] = brentq(delta_es, 100, 273, args=log_es[j])\\n except ValueError: \\n frost_point[ j] = np.NaN\\n else:\\n frost_point[ j] = np.NaN\\n return frost_point\",\n \"def diff_1st_fwrdbwrd(fp, fm, eps):\\n \\n return (fp - fm)/eps\",\n \"def fpb(x, y):\\n if y == 0:\\n return x\\n else:\\n return fpb(y, (x % y))\",\n \"def aptd_ln_pl0_pl1_id_f0_f1__iea(aptd,ln,pl0,pl1,id,f0,f1):\\n dsl = aptd['id__nu']\\n f0ind = dsl_d_f__inda(dsl,id,f0)\\n f1ind = dsl_d_f__inda(dsl,id,f1)\\n pc0 = aptd[ln][pl__pstring(pl0)] # point cloud 0\\n pc1 = aptd[ln][pl__pstring(pl1)] # point cloud 1\\n return (pc0[f0ind]-pc0[f1ind])-(pc1[f0ind]-pc1[f1ind])\",\n \"def f2p (f):\\n #return 2*math.log(f, 11000) - 1\\n #return f/11000 - 1\\n return f/5500 - 1\",\n \"def find_zero(f,p1,d):\\n if p1 > 10:\\n p1 = 0.5\\n c = p1 - f(p1)*d/(f(p1+d)-f(p1)) # simple\\n \\n # we can do this in case derivative diverges because our function is symmetric\\n if c < 0:\\n c = -c\\n \\n global n_of_zeros\\n \\n if n_of_zeros > 8:\\n print('Go linear')\\n return find_zero_linear(f,d,c,d)\\n \\n n_of_zeros += 1\\n print('#',n_of_zeros,' current zero: ',c)\\n \\n # if p1 and c are close together\\n if np.abs(c-p1)<d or f(c)==0:\\n return c\\n else:\\n return find_zero(f,c,d)\",\n \"def neighbour_force(self, point):\\n left_vector = np.array([\\n self.neighbour1.x - point[0],\\n self.neighbour1.y - point[1],\\n ])\\n right_vector = np.array([\\n self.neighbour2.x - point[0],\\n self.neighbour2.y - point[1],\\n ])\\n return 0.1 * (left_vector + right_vector)\",\n \"def TestFunc2(x):\\r\\n return 10*(-0.02*x[0] + 0.5*x[0]*x[0] + x[1])**2 \\\\\\r\\n + 128*(-0.02*x[0] + 0.5*x[0]*x[0] - x[1]/4) \\\\\\r\\n - (8e-5)*x[0]\",\n \"def f(z):\\n a=1./(1.+z)\\n #da=0.01\\n da=0.01*a\\n #da=1e-7\\n gp,g,gm=[D(1./ia-1.) for ia in [a+da,a,a-da]]\\n f=a*(gp-gm)/(2*g*da)\\n #dz=0.01\\n #gp,g,gm=[D(zi) for zi in [z+dz,z,z-dz]]\\n #f=(z)*(gp-gm)/(2.*g*dz)\\n return f\",\n \"def _check_approx_fixed_point(V_current, V_previous, tol):\\n\\n # Compute the sup norm between `V_current` and `V_previous`\\n sup_norm = np.max(np.abs(V_current - V_previous))\\n\\n # Algorithm termination condition\\n fp = sup_norm <= tol\\n\\n return fp, sup_norm\",\n \"def farenheit(ctemp):\\n return round(9.0/5.0 * ctemp + 32)\",\n \"def psi(x, y):\\n return x\",\n \"def f1(x, a, b):\\n #return x**43 - b*x**42 + x**7 - x**6 * a + 84*x - 42 * b - 42 * a\\n return (x**42 + 42)/(x-a) + (x**6 + 42)/(x-b)\",\n \"def f_v(_a, _vs, _Ps, _Ps0): # _aはスカラ, _vsはベクトル, _Ps, _Ps0は３行2列の行列\\n center_pos = _Ps[0]\\n center_pos_0 = _Ps0[0]\\n idx_iter = Index_iterator(1, 8)\\n #中心点から各点へのベクトル\\n x = []\\n x0 = []\\n for p in (_Ps):\\n x.append(p - center_pos)\\n for p in _Ps(_Ps0):\\n x0.append(p - center_pos_0)\\n\\n x01 = (_Ps[1]-center_pos) \\n x02 = (_Ps[2]-center_pos) \\n x03 = (_Ps[3]-center_pos) \\n x04 = (_Ps[4]-center_pos) \\n x05 = (_Ps[5]-center_pos) \\n x06 = (_Ps[6]-center_pos) \\n x07 = (_Ps[7]-center_pos) \\n x08 = (_Ps[8]-center_pos)\\n print('p_id', center_pos, end='\\\\t')\\n print('x01:', x01, end=\\\"\\\\t\\\")\\n print('x03:', x03, end=\\\"\\\\t\\\")\\n print('x05:', x05, end=\\\"\\\\t\\\")\\n print('x07:', x07)\\n x001 = (_Ps0[1]-_Ps0[0]) \\n x002 = (_Ps0[2]-_Ps0[0]) \\n x003 = (_Ps0[3]-_Ps0[0]) \\n x004 = (_Ps0[4]-_Ps0[0]) \\n x005 = (_Ps0[5]-_Ps0[0]) \\n x006 = (_Ps0[6]-_Ps0[0]) \\n x007 = (_Ps0[7]-_Ps0[0]) \\n x008 = (_Ps0[8]-_Ps0[0]) \\n \\n #中心点周りの面の面積\\n def calc_area(j,k,l):\\n s = LA.norm(np.cross(x[j],x[k]))/2 \\\\\\n + LA.norm(np.cross(x[k],x[l]))/2\\n return s\\n\\n s = []\\n s0 = []\\n hen = [1,3,5,7]\\n for i in range(4):\\n j,k,l = [n for n in idx_iter.get_indexes(start_idx=hen[i], 3)]\\n s[i] = calc_area(j,k,l)\\n s0[i] = calc_area(j,k,l)\\n\\n # s0123 = LA.norm(np.cross(x[1],x[2]))/2\\\\\\n # +LA.norm(np.cross(x[2],x[3]))/2\\n # s4367 = LA.norm(np.cross(x[3],x[4]))/2\\\\\\n # +LA.norm(np.cross(x[4],x[5]))/2\\n # s4785 = LA.norm(np.cross(x[5],x[6]))/2\\\\\\n # +LA.norm(np.cross(x[6],x[7]))/2\\n # s4521 = LA.norm(np.cross(x[7],x[8]))/2\\\\\\n # +LA.norm(np.cross(x[8],x[1]))/2\\n # s04103 = LA.norm(np.cross(x0[1],x0[2]))/2\\\\\\n # +LA.norm(np.cross(x0[2],x0[3]))/2\\n # s04367 = LA.norm(np.cross(x0[3],x0[4]))/2\\\\\\n # +LA.norm(np.cross(x0[4],x0[7]))/2\\n # s04785 = LA.norm(np.cross(x0[7],x0[8]))/2\\\\\\n # +LA.norm(np.cross(x0[8],x0[5]))/2\\n # s04521 = LA.norm(np.cross(x0[5],x0[2]))/2\\\\\\n # +LA.norm(np.cross(x0[2],x0[1]))/2\\n \\n #各方向への平均面積(ここだけ反時計回り順で設定してる)\\n S_iminus = (s[1] + s[2]) / 2 #43方向\\n S_Jminus = (s[1] + s[4]) / 2 #41方向\\n S_iplus = (s[3] + s[4]) / 2 #45方向\\n S_Jplus = (s[3] + s[2]) / 2 #47方向\\n S_iminus0 = (s0[1] + s0[2]) / 2 #43方向\\n S_Jminus0 = (s0[1] + s0[4]) / 2 #41方向\\n S_iplus0 = (s0[3] + s0[4]) / 2 #45方向\\n S_Jplus0 = (s0[3] + s0[2]) / 2 #47方向\\n # 各方向への厚み\\n h_iminus = h_0 / ((poisson/(1-poisson) * (S_iminus - S_iminus0) / S_iminus0) + 1) #43方向\\n h_Jminus = h_0 / ((poisson/(1-poisson) * (S_Jminus - S_Jminus0) / S_Jminus0) + 1) #41方向\\n h_iplus = h_0 / ((poisson/(1-poisson) * (S_iplus - S_iplus0) / S_iplus0) + 1) #45方向\\n h_Jplus = h_0 / ((poisson/(1-poisson) * (S_Jplus - S_Jplus0) / S_Jplus0) + 1) #47方向\\n # 各断片の重心\\n g = []\\n kado = [2,4,6,8]\\n hen = [1,3,5,7]\\n for i in range(len(kado)):\\n _kado = kado[i]\\n _hen1, _ = [idx for idx in idx_iter.get_indexes_reverse(_kado, 2)]\\n _hen2, _ = [idx for idx in idx_iter.get_indexes(_kado, 2)]\\n _hen = [_hen1, _hen2]\\n _g1 = (center_pos + _Ps[_kado] + _Ps[_hen1])/3\\n _g2 = (center_pos + _Ps[_kado] + _Ps[_hen2])/3\\n g.append([_g1, _g2])\\n\\n g401 = (center_pos + _Ps[0] + _Ps[1]) / 3\\n g430 = (center_pos + _Ps[3] + _Ps[0]) / 3\\n g436 = (center_pos + _Ps[3] + _Ps[6]) / 3\\n g467 = (center_pos + _Ps[6] + _Ps[7]) / 3\\n g478 = (center_pos + _Ps[7] + _Ps[8]) / 3\\n g485 = (center_pos + _Ps[8] + _Ps[5]) / 3\\n g452 = (center_pos + _Ps[5] + _Ps[2]) / 3\\n g421 = (center_pos + _Ps[2] + _Ps[1]) / 3\\n g0401 = (_Ps0[4] + _Ps0[0] + _Ps0[1]) / 3\\n g0430 = (_Ps0[4] + _Ps0[3] + _Ps0[0]) / 3\\n g0436 = (_Ps0[4] + _Ps0[3] + _Ps0[6]) / 3\\n g0467 = (_Ps0[4] + _Ps0[6] + _Ps0[7]) / 3\\n g0478 = (_Ps0[4] + _Ps0[7] + _Ps0[8]) / 3\\n g0485 = (_Ps0[4] + _Ps0[8] + _Ps0[5]) / 3\\n g0452 = (_Ps0[4] + _Ps0[5] + _Ps0[2]) / 3\\n g0421 = (_Ps0[4] + _Ps0[2] + _Ps0[1]) / 3\\n \\n # 各断片面積\\n triangle_area = []\\n kado = [2,4,6,8]\\n for i in range(len(kado)):\\n j, k = [idx for idx in idx_iter.get_indexes_reverse(kado[i], 1)]\\n _s1 = LA.norm(np.cross(x[j],x[k]))/2\\n j, k = [idx for idx in idx_iter.get_indexes(kado[i], 1)]\\n _s2 = LA.norm(np.cross(x[j],x[k]))/2\\n triangle_area.append([_s1, _s2])\\n\\n s410 = LA.norm(np.cross(x[1],x[2]))/2\\n s403 = LA.norm(np.cross(x[2],x[3]))/2\\n s436 = LA.norm(np.cross(x[3],x[4]))/2\\n s467 = LA.norm(np.cross(x[4],x[5]))/2\\n s478 = LA.norm(np.cross(x[5],x[6]))/2\\n s485 = LA.norm(np.cross(x[6],x[7]))/2\\n s452 = LA.norm(np.cross(x[7],x[8]))/2\\n s421 = LA.norm(np.cross(x[8],x[1]))/2\\n s0410 = LA.norm(np.cross(x0[1],x0[2]))/2\\n s0403 = LA.norm(np.cross(x0[2],x0[3]))/2\\n s0436 = LA.norm(np.cross(x0[3],x0[4]))/2\\n s0467 = LA.norm(np.cross(x0[4],x0[5]))/2\\n s0478 = LA.norm(np.cross(x0[5],x0[6]))/2\\n s0485 = LA.norm(np.cross(x0[6],x0[7]))/2\\n s0452 = LA.norm(np.cross(x0[7],x0[8]))/2\\n s0421 = LA.norm(np.cross(x0[8],x0[1]))/2\\n # 四角の重心\\n\\n center_g_square = []\\n for i in range(len(g)):\\n _g = (triangle_area[i][0]*g[i][0] + triangle_area[i][1]*g[i][1])/(triangle_area[i][0] + triangle_area[i][1])\\n center_g.append(_g)\\n g4103 = (s410*g401 + s403*g430) / (s410 + s403)\\n g4367 = (s436*g436 + s467*g467) / (s436 + s467)\\n g4785 = (s478*g478 + s485*g485) / (s478 + s485)\\n g4521 = (s452*g452 + s421*g421) / (s452 + s421)\\n g04103 = (s0410*g0401 + s0403*g0430) / (s0410 + s0403)\\n g04367 = (s0436*g0436 + s0467*g0467) / (s0436 + s0467)\\n g04785 = (s0478*g0478 + s0485*g0485) / (s0478 + s0485)\\n g04521 = (s0452*g0452 + s0421*g0421) / (s0452 + s0421)\\n # 各重心間の距離\\n Lj82 = LA.norm(g4521 - g4103)\\n Lj24 = LA.norm(g4103 - g4367)\\n Lj46 = LA.norm(g4367 - g4785)\\n Lj68 = LA.norm(g4785 - g4521)\\n \\n # ひずみ\\n eps_i41 = (LA.norm(x01) - LA.norm(x041)) / LA.norm(x041)\\n eps_J41 = (LA.norm(g4521 - g4103) - LA.norm(g04521 - g04103)) / LA.norm(g04521 - g04103)\\n eps_i43 = (LA.norm(x03) - LA.norm(x043)) / LA.norm(x043)\\n eps_J43 = (LA.norm(g4103 - g4367) - LA.norm(g04103 - g04367)) / LA.norm(g04103 - g04367)\\n eps_i47 = (LA.norm(x01) - LA.norm(x041)) / LA.norm(x041)\\n eps_J47 = (LA.norm(g4367 - g4785) - LA.norm(g04367 - g04785)) / LA.norm(g04367 - g04785)\\n eps_i45 = (LA.norm(x01) - LA.norm(x041)) / LA.norm(x041)\\n eps_J45 = (LA.norm(g4785 - g4521) - LA.norm(g04785 - g04521)) / LA.norm(g04785 - g04521)\\n # 張力\\n F_T1 = (young_modulus * h_Jminus * Lj82 * (eps_i41 + poisson * eps_J41) / (1 - poisson**2))*x01/LA.norm(x01)\\n F_T3 = (young_modulus * h_iminus * Lj24 * (eps_i43 + poisson * eps_J43) / (1 - poisson**2))*x03/LA.norm(x03)\\n F_T5 = (young_modulus * h_Jplus * Lj46 * (eps_i47 + poisson * eps_J47) / (1 - poisson**2))*x05/LA.norm(x05)\\n F_T7 = (young_modulus * h_iplus * Lj68 * (eps_i45 + poisson * eps_J45) / (1 - poisson**2))*x07/LA.norm(x07)\\n # せん断ひずみ\\n gamma513 = (math.acos((np.dot(x07,x01))/(LA.norm(x07)*LA.norm(x01))) - math.acos((np.dot(x045,x041))/(LA.norm(x045)*LA.norm(x041)))\\\\\\n + math.acos((np.dot(x03,x01))/(LA.norm(x03)*LA.norm(x01))) - math.acos((np.dot(x043,x041))/(LA.norm(x043)*LA.norm(x041))))/2\\n gamma137 = (math.acos((np.dot(x01,x03))/(LA.norm(x01)*LA.norm(x03))) - math.acos((np.dot(x041,x043))/(LA.norm(x041)*LA.norm(x043)))\\\\\\n + math.acos((np.dot(x03,x05))/(LA.norm(x03)*LA.norm(x05))) - math.acos((np.dot(x043,x047))/(LA.norm(x043)*LA.norm(x047))))/2\\n gamma375 = (math.acos((np.dot(x05,x03))/(LA.norm(x05)*LA.norm(x03))) - math.acos((np.dot(x047,x043))/(LA.norm(x047)*LA.norm(x043)))\\\\\\n + math.acos((np.dot(x07,x05))/(LA.norm(x07)*LA.norm(x05))) - math.acos((np.dot(x045,x047))/(LA.norm(x045)*LA.norm(x047))))/2\\n gamma751 = (math.acos((np.dot(x05,x07))/(LA.norm(x05)*LA.norm(x07))) - math.acos((np.dot(x047,x045))/(LA.norm(x047)*LA.norm(x045)))\\\\\\n + math.acos((np.dot(x07,x01))/(LA.norm(x07)*LA.norm(x01))) - math.acos((np.dot(x045,x041))/(LA.norm(x045)*LA.norm(x041))))/2\\n # せん断力\\n F_S41 = ((young_modulus * h_Jminus * LA.norm(x01) * gamma513)/(2 * (1 + poisson)))*x01/LA.norm(x01)\\n F_S43 = ((young_modulus * h_Jminus * LA.norm(x03) * gamma137)/(2 * (1 + poisson)))*x03/LA.norm(x03)\\n F_S47 = ((young_modulus * h_Jminus * LA.norm(x05) * gamma375)/(2 * (1 + poisson)))*x05/LA.norm(x05)\\n F_S45 = ((young_modulus * h_Jminus * LA.norm(x07) * gamma751)/(2 * (1 + poisson)))*x07/LA.norm(x07)\\n \\n # J方向の曲げ力\\n n_j_cross = np.cross(x05, x01)\\n if any(n_j_cross):\\n n_J = n_j_cross/LA.norm(n_j_cross)\\n else: \\n\\n l_Jalfa = LA.norm(_Ps[1] - _Ps[7])\\n cos_Jalfa = (LA.norm(x01)**2 + LA.norm(x05)**2 - l_Jalfa**2) / (2 * LA.norm(x01) * LA.norm(x05))\\n if cos_Jalfa > 1.0:\\n cos_Jalfa = 1.0\\n elif cos_Jalfa < -1.0:\\n cos_Jalfa = -1.0\\n sin_Jalfa = math.sqrt(1 - cos_Jalfa**2)\\n CJa2 = math.sqrt((cos_Jalfa + 1)/2)\\n SJa2 = math.sqrt((1 - cos_Jalfa)/2)\\n zJC = (_Ps[7][2]-_Ps[1][2])/(_Ps[7][0]-_Ps[1][0]) * (center_pos[0]-_Ps[1][0]) + _Ps[1][2] #曲げ力の方向の場合わけに必要\\n if center_pos[2] > zJC:\\n e_j = np.dot(np.array([[CJa2 + (n_J[0]**2) * (1 - CJa2), n_J[0] * n_J[1] * (1 - CJa2) + n_J[2] * SJa2, n_J[0] * n_J[2] * (1 - CJa2) - n_J[1] * SJa2],\\\\\\n [n_J[1] * n_J[0] * (1 - CJa2) - n_J[2] * SJa2, CJa2 + (n_J[1]**2) * (1 - CJa2), n_J[1] * n_J[2] * (1 - CJa2) + n_J[0] * SJa2],\\\\\\n [n_J[2] * n_J[0] * (1 - CJa2) + n_J[1] * SJa2, n_J[2] * n_J[1] * (1 - CJa2) - n_J[0] * SJa2, CJa2 + (n_J[2]**2) * (1 - CJa2)]]), (_Ps[7] - center_pos)/LA.norm(_Ps[7] - center_pos))\\n else:\\n e_j = np.dot(np.array([[CJa2 + (n_J[0]**2) * (1 - CJa2), n_J[0] * n_J[1] * (1 - CJa2) - n_J[2] * SJa2, n_J[0] * n_J[2] * (1 - CJa2) + n_J[1] * SJa2],\\\\\\n [n_J[1] * n_J[0] * (1 - CJa2) + n_J[2] * SJa2, CJa2 + (n_J[1]**2) * (1 - CJa2), n_J[1] * n_J[2] * (1 - CJa2) - n_J[0] * SJa2],\\\\\\n [n_J[2] * n_J[0] * (1 - CJa2) - n_J[1] * SJa2, n_J[2] * n_J[1] * (1 - CJa2) + n_J[0] * SJa2, CJa2 + (n_J[2]**2) * (1 - CJa2)]]), (_Ps[7] - center_pos)/LA.norm(_Ps[7] - center_pos))\\n d_etha_J = (2 * sin_Jalfa / l_Jalfa) - (2 * math.sqrt(1 - np.dot(x041,x047)**2/(LA.norm(x041)*LA.norm(x047))**2)/(LA.norm(x041 - x047)))\\n\\n n_i = np.cross(x07,x03)/LA.norm(np.cross(x03,x07)) \\n cos_ialfa = np.dot(x03,x07) / (LA.norm(x03) * LA.norm(x07))\\n sin_ialfa = math.sqrt(1 - cos_ialfa**2)\\n Cia2 = math.sqrt((cos_ialfa + 1)/2)\\n Sia2 = math.sqrt((1 - cos_ialfa)/2)\\n ziC = (_Ps[5][2]-_Ps[3][2])/(_Ps[5][0]-_Ps[3][0]) * (center_pos[0]-_Ps[3][0]) + _Ps[3][2]\\n if center_pos[2] > ziC:\\n e_i = np.dot(np.array([[Cia2 + (n_i[0]**2) * (1 - Cia2), n_i[0] * n_i[1] * (1 - Cia2) + n_i[2] * Sia2, n_i[0] * n_i[2] * (1 - Cia2) - n_i[1] * Sia2],\\\\\\n [n_i[1] * n_i[0] * (1 - Cia2) - n_i[2] * Sia2, Cia2 + (n_i[1]**2) * (1 - Cia2), n_i[1] * n_i[2] * (1 - Cia2) + n_i[0] * Sia2],\\\\\\n [n_i[2] * n_i[0] * (1 - Cia2) + n_i[1] * Sia2, n_i[2] * n_i[1] * (1 - Cia2) - n_i[0] * Sia2, Cia2 + (n_i[2]**2) * (1 - Cia2)]]), (_Ps[7] - center_pos)/LA.norm(_Ps[7] - center_pos))\\n else:\\n e_i = np.dot(np.array([[Cia2 + (n_i[0]**2) * (1 - Cia2), n_i[0] * n_i[1] * (1 - Cia2) - n_i[2] * Sia2, n_i[0] * n_i[2] * (1 - Cia2) + n_i[1] * Sia2],\\\\\\n [n_i[1] * n_i[0] * (1 - Cia2) + n_i[2] * Sia2, Cia2 + (n_i[1]**2) * (1 - Cia2), n_i[1] * n_i[2] * (1 - Cia2) - n_i[0] * Sia2],\\\\\\n [n_i[2] * n_i[0] * (1 - Cia2) - n_i[1] * Sia2, n_i[2] * n_i[1] * (1 - Cia2) + n_i[0] * Sia2, Cia2 + (n_i[2]**2) * (1 - Cia2)]]), (_Ps[5] - center_pos)/LA.norm(_Ps[5] - center_pos))\\n d_etha_i = (2 * sin_ialfa / LA.norm(x07 - x03)) - (2 * math.sqrt(1 - np.dot(x043,x045)**2/(LA.norm(x043)*LA.norm(x045))**2)/(LA.norm(x043 - x045)))\\n\\n\\n l_J = (Lj20 + Lj06 + Lj68 + Lj82) / 4\\n h = (h_iminus + h_iplus + h_Jminus + h_Jplus) / 4\\n I = (l_J * h**3) / 12\\n M_i = (young_modulus * I * (d_etha_i + poisson * d_etha_J)/(1 - poisson**2))\\n M_J = (young_modulus * I * (d_etha_J + poisson * d_etha_i)/(1 - poisson**2))\\n #曲げ力\\n F_Bi = M_i / LA.norm(x03) + M_i / LA.norm(x07) * e_i\\n F_BJ = M_J / LA.norm(x01) + M_J / LA.norm(x05) * e_j\\n #空気力\\n # S = (S_iminus + S_iplus + S_Jminus + S_Jplus) / 4\\n # F_A = p * S\\n F_A = np.array([0.0, 0.0, -0.1]) * _a\\n\\n # 運動方程式（支配方程式）\\n S_0 = (S_iminus0 + S_iplus0 + S_Jminus0 + S_Jplus0) / 4\\n F_T = F_T41 + F_T43 + F_T45 + F_T47\\n F_S = F_S41 + F_S43 + F_S45 + F_S47\\n F_B = F_Bi + F_BJ\\n return (F_T + F_S + F_B + F_A) / (rho * h_0 * S_0) - c * _vs\",\n \"def pi_fixed(prec, verbose=False, verbose_base=None):\\n # The Chudnovsky series gives 14.18 digits per term\\n N = int(prec/3.3219280948/14.181647462 + 2)\\n if verbose:\\n print(\\\"binary splitting with N =\\\", N)\\n g, p, q = bs_chudnovsky(0, N, 0, verbose)\\n sqrtC = isqrt_fast(CHUD_C<<(2*prec))\\n v = p*CHUD_C*sqrtC//((q+CHUD_A*p)*CHUD_D)\\n return v\",\n \"def fourPtFiniteDiff(x,y):\\n dydx = np.zeros(y.shape,float)\\n for i in range(2,len(y)-2):\\n a = y[i-2]\\n b = y[i-1]\\n c = y[i+1]\\n d = y[i+2]\\n dydx[i] = (a-8*b+8*c-d)/(12*(x[1]-x[0]))\\n dydx[-1] = (y[-1]-y[-2])/(x[-1]-x[-2])\\n dydx[-2] = (y[-2]-y[-3])/(x[-2]-x[-3])\\n dydx[0] = (y[1]-y[0])/(x[1]-x[0])\\n dydx[1] = (y[2]-y[1])/(x[2]-x[1])\\n return dydx\",\n \"def fdr_correction(pvals):\\r\\n tmp = array(pvals).astype(float) # this converts Nones to nans\\r\\n return tmp * tmp.size / (1. + argsort(argsort(tmp)).astype(float))\",\n \"def pinpoint(f, J0, g0, x0, mu1, mu2, \\\\\\r\\n alow, Jalow, galow, ahigh, Jahigh, gahigh, p):\\r\\n j = 0\\r\\n Jprime0 = g0.T@p\\r\\n Jprimealow = galow.T@p\\r\\n amin = (2*alow*(Jahigh-Jalow)+Jprimealow*(alow**2-ahigh**2))/\\\\\\r\\n (2*(Jahigh-Jalow+Jprimealow*(alow-ahigh)))\\r\\n Jamin, gamin = f(x0+amin*p)\\r\\n while True:\\r\\n Jprimeamin = gamin.T@p\\r\\n if (Jamin > J0+mu1*amin*Jprime0) or (Jamin > Jalow):\\r\\n ahigh = amin\\r\\n Jahigh = Jamin\\r\\n amin = (2*alow*(Jahigh-Jalow)+Jprimealow*(alow**2-ahigh**2))/\\\\\\r\\n (2*(Jahigh-Jalow+Jprimealow*(alow-ahigh)))\\r\\n Jamin, gamin = f(x0+amin*p)\\r\\n else:\\r\\n if (np.abs(Jprimeamin) <= np.abs(mu2*Jprime0)): \\r\\n astar = amin\\r\\n return Jamin, gamin, astar\\r\\n elif (Jprimeamin*(ahigh-alow) >= 0):\\r\\n ahigh = alow\\r\\n alow = amin\\r\\n Jalow = Jamin\\r\\n galow = gamin\\r\\n Jprimealow = galow.T@p\\r\\n amin = (2*alow*(Jahigh-Jalow)+Jprimealow*(alow**2-ahigh**2))/\\\\\\r\\n (2*(Jahigh-Jalow+Jprimealow*(alow-ahigh)))\\r\\n Jamin, gamin = f(x0+amin*p)\\r\\n j += 1\",\n \"def assign_fixedpoints(\\n adata: anndata.AnnData,\\n basis: str = \\\"pca\\\",\\n cores: int = 1,\\n copy: bool = False,\\n) -> Union[None, anndata.AnnData]:\\n logger = LoggerManager.gen_logger(\\\"dynamo-assign_fixedpoints\\\")\\n logger.info(\\\"assign_fixedpoints begins...\\\", indent_level=1)\\n logger.log_time()\\n adata = copy_adata(adata) if copy else adata\\n\\n VecFld, func = vecfld_from_adata(adata, basis=basis)\\n\\n vecfld_class = base_vectorfield(\\n X=VecFld[\\\"X\\\"],\\n V=VecFld[\\\"Y\\\"],\\n func=func,\\n )\\n\\n (\\n X,\\n valid_fps_type_assignment,\\n assignment_id,\\n ) = vecfld_class.assign_fixed_points(cores=cores)\\n assignment_id = [str(int(i)) if np.isfinite(i) else None for i in assignment_id]\\n adata.obs[\\\"fps_assignment\\\"] = assignment_id\\n adata.uns[\\\"fps_assignment_\\\" + basis] = {\\n \\\"X\\\": X,\\n \\\"valid_fps_type_assignment\\\": valid_fps_type_assignment,\\n \\\"assignment_id\\\": assignment_id,\\n }\\n\\n logger.finish_progress(\\\"assign_fixedpoints\\\")\\n if copy:\\n return adata\\n return None\",\n \"def fD(self, vpd):\\n\\t if vpd < 0.1:\\n\\t return 1.\\n\\t else:\\n\\t return 3/13./sqrt(vpd/1000.)\",\n \"def test_fdr_correction(self):\\r\\n pvals = array([.1, .7, .5, .3, .9])\\r\\n exp = array([.5, .7 * 5 / 4., .5 * 5 / 3., .3 * 5 / 2., .9])\\r\\n obs = fdr_correction(pvals)\\r\\n self.assertFloatEqual(obs, exp)\",\n \"def cal_pt(self):\\n\\n if not self.check_def(['E','px','py','pz']):\\n sys.exit('Particle error: Quadri impulsion not define (error for pt routine)')\\n\\n self.pt =math.sqrt(self.px**2+self.py**2)\",\n \"def Fw(X, p0, back):\\n Eac, g = X\\n return p0 * Eac * g + back\",\n \"def ppf(self,x):\\n # TODO speed this up by doing it in Crow, not in python\\n if hasattr(x,'__len__'):\\n returnPpf = np.array([self.ppf(i) for i in x])\\n else:\\n returnPpf = self._distribution.inverseCdf(x)\\n return returnPpf\",\n \"def rewofz_nonvector(x,y):\\n ncut=27\\n xy=x*y\\n xyp=xy/jnp.pi\\n exx=jnp.exp(-x*x)\\n f=exx*erfcx(y)*jnp.cos(2.0*xy)+x*jnp.sin(xy)/jnp.pi*exx*jnp.sinc(xyp)\\n n=jnp.arange(1,ncut+1)\\n n2=n*n\\n vec0=1.0/(0.25*n2+ y*y)\\n vec1=jnp.exp(-(0.25*n2+x*x))\\n vec2=jnp.exp(-(0.5*n+x)*(0.5*n+x))\\n vec3=jnp.exp(-(0.5*n-x)*(0.5*n-x))\\n Sigma1=jnp.dot(vec0,vec1)\\n Sigma2=jnp.dot(vec0,vec2)\\n Sigma3=jnp.dot(vec0,vec3)\\n f = f + 1.0/jnp.pi*(-y*jnp.cos(2.0*xy)*Sigma1 + 0.5*y*Sigma2 + 0.5*y*Sigma3)\\n return f\",\n \"def calc_diff(f, dx):\\n \\n df = (np.roll(f,-3)/60.-np.roll(f,-2)*3./20.+np.roll(f,-1)*3./4.-np.roll(f,1)*3./4.+np.roll(f,2)*3./20.-np.roll(f,3)/60.)/dx\\n df[0] = (-21600./13649.*f[0]+81763./40947.*f[1]+131./27298.*f[2]-9143./13649.*f[3]+20539./81894.*f[4])/dx\\n df[1] = (-81763./180195.*f[0]+7357./36039.*f[2]+30637./72078.*f[3]-2328./12013.*f[4]+6611./360390.*f[5])/dx\\n df[2] = (-131./54220.*f[0]-7357./16266.*f[1]+645./2711.*f[3]+11237./32532.*f[4]-3487./27110.*f[5])/dx\\n df[3] = (9143./53590.*f[0]-30637./64308.*f[1]-645./5359.*f[2]+13733./32154.*f[4]-67./4660.*f[5]+72./5359.*f[6])/dx\\n df[4] = (-20539./236310.*f[0]+2328./7877.*f[1]-11237./47262.*f[2]-13733./23631.*f[3]+89387./118155.*f[5]-1296./7877.*f[6]+144./7877.*f[7])/dx\\n df[5] = (-6611./262806.*f[1]+3487./43801.*f[2]+1541./87602.*f[3]-89387./131403.*f[4]+32400./43801.*f[6]-6480./43801.*f[7]+720./43801.*f[8])/dx\\n df[-1] = -(-21600./13649.*f[-1]+81763./40947.*f[-2]+131./27298.*f[-3]-9143./13649.*f[-4]+20539./81894.*f[-5])/dx\\n df[-2] = -(-81763./180195.*f[-1]+7357./36039.*f[-3]+30637./72078.*f[-4]-2328./12013.*f[-5]+6611./360390.*f[-6])/dx\\n df[-3] = -(-131./54220.*f[-1]-7357./16266.*f[-2]+645./2711.*f[-4]+11237./32532.*f[-5]-3487./27110.*f[-6])/dx\\n df[-4] = -(9143./53590.*f[-1]-30637./64308.*f[-2]-645./5359.*f[-3]+13733./32154.*f[-5]-67./4660.*f[-6]+72./5359.*f[-7])/dx\\n df[-5] = -(-20539./236310.*f[-1]+2328./7877.*f[-2]-11237./47262.*f[-3]-13733./23631.*f[-4]+89387./118155.*f[-6]-1296./7877.*f[-7]+144./7877.*f[-8])/dx\\n df[-6] = -(-6611./262806.*f[-2]+3487./43801.*f[-3]+1541./87602.*f[-4]-89387./131403.*f[-5]+32400./43801.*f[-7]-6480./43801.*f[-8]+720./43801.*f[-9])/dx\\n\\n return df\",\n \"def f(self, X):\\n\\n return (X[0])**3 - (X[1])**2 + 1\",\n \"def NR(ip, fp):\\n x = fp[0] - ip[0]\\n y = fp[1] - ip[1]\\n r = sqrt(x ** 2 + y ** 2)\\n return array([-y / r, x / r])\",\n \"def flipy(self, p):\\n return int(p.x), int(-p.y+self.h)\",\n \"def FMScore(x,p,d):\\n \\n if x <= d[p][0.20]:\\n return 1\\n elif x <= d[p][0.4]:\\n return 2\\n elif x <= d[p][0.6]: \\n return 3\\n elif x <= d[p][0.8]:\\n return 4\\n else:\\n return 5\",\n \"def FMScore(x,p,d):\\n \\n if x <= d[p][0.20]:\\n return 1\\n elif x <= d[p][0.4]:\\n return 2\\n elif x <= d[p][0.6]: \\n return 3\\n elif x <= d[p][0.8]:\\n return 4\\n else:\\n return 5\",\n \"def optimizeposition(areas, omegas, x0, x1, z0, z1):\\n\\n # initial position of each quadpoint is at the center\\n # of the edge connecting the midpoint and a corner point\\n rhos = 0.5 * ones(4)\\n a = 1 / sqrt(3)\\n deltarhos = 0.25 * ones(4) # delta for finite differences\\n\\n while True: # while method has not converged\\n # print(\\\"################## new iteration #############\\\")\\n rhs = f(rhos, omegas, a, x0, x1, z0, z1, areas)\\n print(\\\"##\\\")\\n print(rhs)\\n print(rhos)\\n if norm(rhs) < 1e-5:\\n break\\n mat = df(rhos, omegas, a, x0, x1, z0, z1, areas, deltarhos)\\n update = solve(mat, rhs)\\n\\n rhos += update\\n # for i in range(4):\\n # rhos[i] = max(0,min(1,rhos[i]))\\n \\\"\\\"\\\"\\n print(\\\"the norm of the rhs is \\\")\\n print(norm(rhs))\\n print(mat)\\n print(\\\"rhs\\\")\\n print(rhs)\\n print(update)\\n print(\\\"rhos\\\")\\n print(rhos)\\n \\\"\\\"\\\"\\n # print(alpha)\\n return rhos\",\n \"def find_root(function, point_a, point_b, step, tol, max_iterations, \\n show_process = False):\\n left_point , right_point = search_interval_3d(function, point_a, point_b, \\n step, tol, max_iterations,\\n show_process)\\n \\n point_where_zero = bisection_3d(function, left_point, right_point, tol, \\n max_iterations, show_process)\\n \\n return point_where_zero\",\n \"def downhill(F, xStart, args=None, side=0.1, ftol=1.0e-6, xtol=1.0e-6, maxiter=1000, maxfunc=1000, maxiternochange=10):\\n # TODO: check the types of the input ???\\n\\n # print \\\"Entering downhill\\\"\\n n = len(xStart)\\n x = np.zeros((n+1, n), dtype=float) #point null matrix, n+1 rows, n columns\\n f = np.zeros(n+1, dtype=float) # null vector, n+1 columns\\n p_count = 0 # counter for detecting a plateau\\n f_count = 0 # counter for the number of function call\\n f_best_count = 0 # counter for the number of iterations in which the best solution does not change\\n f_best_prev = 0.0 # holds the best value from the previous iteration\\n epsilon = 0.001 # tolerance for considering two values as equal\\n # max_iter_no_change = 10 # maximum number of accepted iterations with no change in the optimal solution\\n precision = 2\\n round_map = partial(round, ndigits=precision) # partial function for rounding purposes\\n\\n # initial simplex\\n x[0] = xStart\\n for i in xrange(1, n+1):\\n x[i] = xStart\\n x[i,i-1] = xStart[i-1] + side\\n\\n # print \\\"Evaluate the starting points\\\"\\n # compute the value of F at the vertices of the simplex\\n for i in xrange(n+1):\\n f[i] = F(x[i], args)\\n # p_count += 1\\n\\n # main loop\\n # print \\\"Start iterating\\\"\\n for k in xrange(maxiter):\\n\\n # check the number of function calls\\n if f_count > maxfunc:\\n print \\\"Stopping criteria: maximum number of function calls\\\"\\n print \\\"Best solution so far: \\\", x[iLo], \\\" value: \\\", f[iLo], \\\" at iteration:\\\", k\\n # return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': (args['Q1'], args['Q2'], args['Q3']), 'stopping': 'MAXFUNCALL'}\\n return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': [args['Q{}'.format(h)] for h in xrange(1, args['retailers']+1)], 'stopping': 'MAXFUNCALL'}\\n\\n # find the best and worst vertex (consider a minimization problem)\\n iLo = np.argmin(f) # best vertex\\n iHi = np.argmax(f) # worst vertex\\n\\n # print k,\\\" \\\", f[iLo]\\n #\\n # if f[iLo] < -0.310000:\\n # print f[iLo]\\n # print x[iLo]\\n # print x\\n # sys.exit(1)\\n # print \\\"k: \\\", k, \\\" f_best_prev: \\\", f_best_prev, \\\" f[iLo]: \\\", f[iLo], \\\" f_best_count: \\\", f_best_count\\n # print \\\"Beginning of iteration: %4d | Best x: %4f %4f %4f | Best value: %f\\\" % (k, x[iLo][0], x[iLo][1], x[iLo][2], f[iLo])\\n # print \\\"x: \\\", x, \\\" f: \\\", f\\n # print \\\"=========================================================================================\\\"\\n # check if the solution has changed from the previous iterations\\n if f[iLo] < f_best_prev:\\n f_best_prev = f[iLo]\\n f_best_count = 0\\n else:\\n f_best_count += 1\\n\\n if f_best_count > maxiternochange:\\n print \\\"Stopping criteria: maximum number of iterations with no improvement in the best solution\\\"\\n print \\\"Best solution so far: \\\", x[iLo], \\\" value: \\\", f[iLo], \\\" at iteration:\\\", k\\n # return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': (args['Q1'], args['Q2'], args['Q3']), 'stopping': 'NOIMPROVEMENT'}\\n return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': [args['Q{}'.format(h)] for h in xrange(1, args['retailers']+1)], 'stopping': 'NOIMPROVEMENT'}\\n\\n if abs(f[iLo] - f[iHi]) < ftol: # If difference between highest and lowest is smaller than ftol, return\\n print \\\"Stopping criteria: difference between highest and lowest points is smaller than tolerance\\\"\\n print \\\"Best solution so far: \\\", x[iLo], \\\" value: \\\", f[iLo], \\\" at iteration:\\\", k\\n # return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': (args['Q1'], args['Q2'], args['Q3']), 'stopping': 'MAXTOLERANCE'}\\n return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': [args['Q{}'.format(h)] for h in xrange(1, args['retailers']+1)], 'stopping': 'MAXTOLERANCE'}\\n # compute the move vector d\\n d = (-(n+1) * x[iHi] + np.sum(x, axis=0)) / n\\n # print \\\"d: \\\", d\\n\\n # check for convergence\\n if sqrt(np.dot(d, d)/n) < xtol: # length of the vector d\\n print \\\"Stopping criteria: length of step d smaller than tolerance\\\"\\n print \\\"Best solution so far: \\\", x[iLo], \\\" value: \\\", f[iLo], \\\" at iteration:\\\", k\\n # return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': (args['Q1'], args['Q2'], args['Q3']), 'stopping': 'SMALLSTEP'}\\n return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': [args['Q{}'.format(h)] for h in xrange(1, args['retailers']+1)], 'stopping': 'SMALLSTEP'}\\n # try reflection\\n xNew = np.array(map(round_map, x[iHi] + 2 * d))\\n fNew = F(xNew, args)\\n f_count += 1\\n # print \\\"Reflected point: \\\", xNew, \\\" value: \\\", fNew\\n\\n # check for no improvement over the worst point\\n # and for plateau condition\\n if f[iHi] - epsilon <= fNew <= f[iHi] + epsilon:\\n p_count += 1\\n # print \\\"No improvement here\\\"\\n\\n if p_count == n+2: # we reflected all vertices with no improvement\\n print \\\"Stopping criteria: Probably we landed on a plateau... exiting\\\" # TODO: restart instead of exiting\\n print \\\"Best solution so far: \\\", x[iLo], \\\" value: \\\", f[iLo], \\\" at iteration:\\\", k\\n # return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': (args['Q1'], args['Q2'], args['Q3']), 'stopping': 'PLATEAU'}\\n return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': [args['Q{}'.format(h)] for h in xrange(1, args['retailers']+1)], 'stopping': 'PLATEAU'}\\n\\n\\n else:\\n p_count = 0\\n\\n\\n if fNew <= f[iLo]: # if the new value is better than the best so far,\\n x[iHi] = xNew # substitute the worst vertex with the new one\\n f[iHi] = fNew\\n\\n # try to expand the reflection\\n xNew = np.array(map(round_map, x[iHi] + d))\\n fNew = F(xNew, args)\\n f_count += 1\\n # print \\\"Expanded point: \\\", xNew, \\\" value: \\\", fNew\\n\\n if fNew <= f[iHi]: # in the original source version it is f[iLo] (?)\\n x[iHi] = xNew\\n f[iHi] = fNew\\n else:\\n # try reflection again\\n if fNew <= f[iHi]:\\n x[iHi] = xNew\\n f[iHi] = fNew\\n else:\\n # try contraction\\n xNew = np.array(map(round_map, x[iHi] + 0.5 * d))\\n fNew = F(xNew, args)\\n f_count += 1\\n # print \\\"Contracted point: \\\", xNew, \\\" value: \\\", fNew\\n\\n if fNew <= f[iHi]: # accept contraction\\n x[iHi] = xNew\\n f[iHi] = fNew\\n else:\\n # shrink\\n for i in xrange(len(x)):\\n if i != iLo:\\n x[i] = np.array(map(round_map, x[i] - x[iLo] * 0.5))\\n f[i] = F(x[i], args)\\n f_count += 1\\n\\n # print \\\"End of iteration: %4d | Best x: %4f %4f %4f | Best value: %f\\\" % (k, x[iLo][0], x[iLo][1], x[iLo][2], f[iLo])\\n # print \\\"x: \\\", x, \\\" f: \\\", f\\n # print \\\"*\\\"*50\\n # print \\\"\\\"\\n\\n\\n\\n print \\\"Stopping criteria: maximum number of iterations\\\"\\n print \\\"Best solution so far: \\\", x[iLo], \\\" value: \\\", f[iLo], \\\" at iteration:\\\", k\\n # return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': (args['Q1'], args['Q2'], args['Q3']), 'stopping': 'MAXITERATION'}\\n return {'point' : x[iLo], 'value': f[iLo], 'iteration': k, 'funcalls': f_count, 'allocation': [args['Q{}'.format(h)] for h in xrange(1, args['retailers']+1)], 'stopping': 'MAXITERATION'}\",\n \"def fpart(x):\\n return x - np.floor(x)\",\n \"def f1(x):\\n return x**3 - 2*x + 2\",\n \"def fcp(self, var='x'):\\n return self.charpoly(var).factor()\",\n \"def eval_is_fixed(leaf, eval_from_search):\\n check_val = nn_evaluate.evaluate(leaf)\\n if leaf.side_to_move() == Side.B:\\n check_val *= -1\\n check_val = min(max(check_val/1000, -1), 1)\\n if abs(check_val - eval_from_search) > .0008:\\n if abs(eval_from_search) != 0 and abs(eval_from_search) != 1:\\n print(\\\"fixed.. searchval:\\\", eval_from_search, \\\"nnval:\\\", check_val, \\\"fen\\\", leaf.fen())\\n return True\\n return False\",\n \"def friction_factor(v1: \\\"int\\\", v2: \\\"int\\\") -> \\\"int\\\":\",\n \"def F(self, x):\\n F = np.zeros((1, x.shape[-1]))\\n # Column indices of state vectors that fulfill the condition z<z0\\n contact = x[1, :]<self.z0\\n F[0, ~contact] = -self.H*self.R/(6*x[1, ~contact]**2)\\n F[0, contact] = (4/3)*self.E*np.sqrt(self.R)*(self.z0 - x[1, contact])**1.5 - self.H*self.R/(6*self.z0**2)\\n\\n return F\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7288447","0.63831216","0.6331708","0.6310987","0.62785643","0.6213673","0.6211178","0.61968625","0.6118697","0.6110409","0.6091076","0.6086669","0.59297514","0.5889126","0.5873738","0.58619815","0.5842633","0.5819706","0.5756298","0.5717596","0.5702371","0.56871235","0.56865853","0.5680593","0.5676993","0.566645","0.56639826","0.566245","0.56530577","0.5648185","0.56419605","0.5611461","0.5609422","0.56033117","0.5578811","0.5577539","0.5577539","0.5552904","0.5552585","0.5549406","0.55491614","0.55426466","0.5541167","0.5540621","0.5538121","0.55239505","0.55168","0.5500648","0.5496273","0.5478506","0.54723","0.546178","0.54566514","0.54466873","0.54440826","0.5441023","0.5435519","0.5431213","0.5430237","0.54258645","0.54060835","0.5404798","0.54033375","0.5399399","0.5398221","0.53972906","0.5388948","0.5387406","0.5383953","0.53742844","0.53718865","0.53718644","0.5361465","0.5346656","0.53390753","0.5334807","0.53315145","0.53132725","0.53018683","0.52979463","0.52944785","0.5293627","0.5289361","0.52872753","0.5279518","0.52735573","0.526983","0.5265044","0.526278","0.5259002","0.5259002","0.5257658","0.5256842","0.5253013","0.5252052","0.5251072","0.5245951","0.5244442","0.52434886","0.5240773"],"string":"[\n \"0.7288447\",\n \"0.63831216\",\n \"0.6331708\",\n \"0.6310987\",\n \"0.62785643\",\n \"0.6213673\",\n \"0.6211178\",\n \"0.61968625\",\n \"0.6118697\",\n \"0.6110409\",\n \"0.6091076\",\n \"0.6086669\",\n \"0.59297514\",\n \"0.5889126\",\n \"0.5873738\",\n \"0.58619815\",\n \"0.5842633\",\n \"0.5819706\",\n \"0.5756298\",\n \"0.5717596\",\n \"0.5702371\",\n \"0.56871235\",\n \"0.56865853\",\n \"0.5680593\",\n \"0.5676993\",\n \"0.566645\",\n \"0.56639826\",\n \"0.566245\",\n \"0.56530577\",\n \"0.5648185\",\n \"0.56419605\",\n \"0.5611461\",\n \"0.5609422\",\n \"0.56033117\",\n \"0.5578811\",\n \"0.5577539\",\n \"0.5577539\",\n \"0.5552904\",\n \"0.5552585\",\n \"0.5549406\",\n \"0.55491614\",\n \"0.55426466\",\n \"0.5541167\",\n \"0.5540621\",\n \"0.5538121\",\n \"0.55239505\",\n \"0.55168\",\n \"0.5500648\",\n \"0.5496273\",\n \"0.5478506\",\n \"0.54723\",\n \"0.546178\",\n \"0.54566514\",\n \"0.54466873\",\n \"0.54440826\",\n \"0.5441023\",\n \"0.5435519\",\n \"0.5431213\",\n \"0.5430237\",\n \"0.54258645\",\n \"0.54060835\",\n \"0.5404798\",\n \"0.54033375\",\n \"0.5399399\",\n \"0.5398221\",\n \"0.53972906\",\n \"0.5388948\",\n \"0.5387406\",\n \"0.5383953\",\n \"0.53742844\",\n \"0.53718865\",\n \"0.53718644\",\n \"0.5361465\",\n \"0.5346656\",\n \"0.53390753\",\n \"0.5334807\",\n \"0.53315145\",\n \"0.53132725\",\n \"0.53018683\",\n \"0.52979463\",\n \"0.52944785\",\n \"0.5293627\",\n \"0.5289361\",\n \"0.52872753\",\n \"0.5279518\",\n \"0.52735573\",\n \"0.526983\",\n \"0.5265044\",\n \"0.526278\",\n \"0.5259002\",\n \"0.5259002\",\n \"0.5257658\",\n \"0.5256842\",\n \"0.5253013\",\n \"0.5252052\",\n \"0.5251072\",\n \"0.5245951\",\n \"0.5244442\",\n \"0.52434886\",\n \"0.5240773\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.56695026"},"document_rank":{"kind":"string","value":"25"}}},{"rowIdx":88568,"cells":{"query":{"kind":"string","value":"Root finding algorithm. Based on MATLAB implementation by Botev et al. >>> From the matlab code >>> ints = np.arange(1, 51) >>> ans = _root(_fixed_point, N=50, args=(50, ints, ints)) >>> np.allclose(ans, 9.237610787616029e05) True"},"document":{"kind":"string","value":"def _find_root(function, N, squared_integers, grid_data_dct2):\n\n # From the implementation by Botev, the original paper author\n # Rule of thumb of obtaining a feasible solution\n N2 = tf.math.maximum(\n tf.math.minimum(tf.constant(1050, ztypes.float), N),\n tf.constant(50, ztypes.float),\n )\n tol = 10e-12 + 0.01 * (N2 - 50) / 1000\n left_bracket = tf.constant(0.0, dtype=ztypes.float)\n right_bracket = tf.constant(10e-12, ztypes.float) + tf.constant(\n 0.01, ztypes.float\n ) * (N2 - tf.constant(50, ztypes.float)) / tf.constant(1000, ztypes.float)\n\n converged = tf.constant(False)\n t_star = tf.constant(0.0, dtype=ztypes.float)\n\n def fixed_point_function(t):\n return _fixed_point(t, N, squared_integers, grid_data_dct2)\n\n def condition(right_bracket, converged, t_star):\n return tf.math.logical_not(converged)\n\n def body(right_bracket, converged, t_star):\n t_star, value_at_t_star, num_iterations, converged = root_search.brentq(\n fixed_point_function, left_bracket, right_bracket, None, None, 2e-12\n )\n\n t_star = t_star - value_at_t_star\n\n right_bracket = right_bracket * tf.constant(2.0, ztypes.float)\n\n return right_bracket, converged, t_star\n\n # While a solution is not found, increase the tolerance and try again\n right_bracket, converged, t_star = tf.while_loop(\n condition, body, [right_bracket, converged, t_star]\n )\n\n return t_star"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def find_root(function, point_a, point_b, step, tol, max_iterations, \n show_process = False):\n left_point , right_point = search_interval_3d(function, point_a, point_b, \n step, tol, max_iterations,\n show_process)\n \n point_where_zero = bisection_3d(function, left_point, right_point, tol, \n max_iterations, show_process)\n \n return point_where_zero","def find_root_1(x, n, p=0.001):\n step = p / 10\n guess = step\n while abs(guess ** n - x) > p:\n guess += step\n return round(guess, 3)","def findroot(self,x0,method='fmin',**kwargs):\n return self._optimize(x0,'root',method,**kwargs)","def nthRoot(x,n):\n return op.pow(x,1/n)","def test_find_root_in_interval(self):\n\n print(\"\\nFalse Position Method: Root in Interval\")\n\n # input\n xi = 0 # initial value\n xf = 1 # final value\n et = 1e-6 # relative error threshold\n\n # function\n root, ic, msg = FalsePosition.find_root_in_interval(self.fn, xi, xf, et)\n\n # output\n if root != None:\n print(\"\\tInterval: [{xi}, {xf}]\\n\\t{msg}: {x}\\n\\tFunction Value: {fx}\\n\\tIterations: {ic}\".format(xi=xi, xf=xf, msg=msg, x=root, fx=self.fn(root), ic=ic))\n else:\n print(\"\\t{msg}.\".format(msg=msg))","def actual_root(x):\n root = x ** (1/n)\n\tprint(x)\n return root","def find_root(f, df, ddf, initial_guess = 0.0, limit = 0.00001, max_iterations = 1000):\n xn_1 = initial_guess\n i = 0\n while i < max_iterations:\n fx = f(xn_1)\n dfx = df(xn_1)\n ddfx = ddf(xn_1)\n xn = xn_1 - 2 * fx * dfx / (2 * dfx ** 2 - fx * ddfx)\n if abs(xn - xn_1) < limit:\n return xn\n xn_1 = xn\n i += 1\n return None","def sroot(n):\n\n return int(n ** 0.5) == n ** 0.5","def find_root_2(x, n, p=0.001):\n step = p / 10\n left, right = 0, x\n while True:\n guess = (left + right) / 2\n result = guess ** n\n if abs(result - x) <= p:\n break\n elif result > x + p:\n right = guess - step\n else:\n left = guess + step\n\n if round(guess) ** n == x:\n return round(guess)\n return round(guess, 3)","def nth_root(n):\n def actual_root(x):\n \"\"\"Returns the nth root of x\"\"\"\n root = x ** (1/n)\n\tprint(x)\n return root\n return actual_root","def integer_root(n,k):\n # from https://stackoverflow.com/questions/15978781/how-to-find-integer-nth-roots/15979957:\n # Newton's method to find kth root of n\n u, s = n, n+1\n while u < s:\n s = u\n t = (k-1) * s + n // pow(s, k-1)\n u = t // k\n return s","def rootfind_newton(func, x0, a, b, maxiter=50, tol=1.0e-11):\n\n for iter in xrange(maxiter):\n\n fval, fpval, args = func(x0)\n # print \"x0=%.4f fval=%.2e fpval=%.2e [%.4f, %.4f]\" % (x0, fval, fpval, a, b)\n\n if fval < 0:\n a = x0\n else:\n b = x0\n\n x = x0 - fval/fpval\n if not (a < x < b):\n # Once we have bracketed the root, we don't allow the\n # iterations to leave the bracket.\n x = 0.5*(a+b)\n\n if np.abs(x-x0) < tol or np.abs(fval) < tol:\n break\n\n x0 = x\n\n return x, fval, iter, args","def root_0(a):\n return 0","def n_root_of_x(n, x):\n if n==0:\n return 1\n \n return 1 if n==0 else x**(1.0/n)","def getRoot(self, xa,xb, *args):\n \n count = 0\n\n while np.abs(xa-xb) > self.precision:\n x = (xa + xb)/2\n count += 1\n if self.f(x, *args)*self.f(xa, *args) > 0:\n xa = x\n else:\n xb = x\n return [x, count]","def test_newton_root_finder(self):\n\n # Set up the problem of finding the square roots of three numbers.\n constants = np.array([4.0, 9.0, 16.0])\n initial_values = np.ones(len(constants))\n\n def objective_and_gradient(values):\n objective = values**2 - constants\n gradient = 2.0 * values\n return objective, gradient\n\n # Obtain and evaluate a tensor containing the roots.\n roots = newton_root_finder(objective_and_gradient, initial_values)\n root_values, converged, failed = self.evaluate(roots)\n\n # Reference values.\n roots_bench = np.array([2.0, 3.0, 4.0])\n converged_bench = np.array([True, True, True])\n failed_bench = np.array([False, False, False])\n\n # Assert that the values we obtained are close to the true values.\n np.testing.assert_array_equal(converged, converged_bench)\n np.testing.assert_array_equal(failed, failed_bench)\n np.testing.assert_almost_equal(root_values, roots_bench, decimal=7)","def simple_root(self, i):","def test_roots_slow():\n a, b, c, d, x = symbols(\"a,b,c,d,x\")\n\n f1 = x ** 2 * c + (a / b) + x * c * d - a\n f2 = x ** 2 * (a + b * (c - d) * a) + x * a * b * c / (b * d - d) + (a * d - c / d)\n\n assert list(roots(f1, x).values()) == [1, 1]\n assert list(roots(f2, x).values()) == [1, 1]\n\n (zz, yy, xx, zy, zx, yx, k) = symbols(\"zz,yy,xx,zy,zx,yx,k\")\n\n e1 = (zz - k) * (yy - k) * (xx - k) + zy * yx * zx + zx - zy - yx\n e2 = (zz - k) * yx * yx + zx * (yy - k) * zx + zy * zy * (xx - k)\n\n assert list(roots(e1 - e2, k).values()) == [1, 1, 1]\n\n f = x ** 3 + 2 * x ** 2 + 8\n R = list(roots(f).keys())\n\n assert not any(i for i in [f.subs(x, ri).n(chop=True) for ri in R])","def _rootsFinder(self, fun, jac, bounds, npoints, method):\n if method == \"regular\":\n step = (bounds[1] - bounds[0]) / (npoints + 1)\n try:\n X0 = np.arange(bounds[0] + step, bounds[1], step)\n except:\n X0 = np.random.uniform(bounds[0], bounds[1], npoints)\n elif method == \"random\":\n X0 = np.random.uniform(bounds[0], bounds[1], npoints)\n\n def objFun(X, f, jac):\n g = 0\n j = np.zeros(X.shape)\n i = 0\n for x in X:\n fx = f(x)\n g = g + fx**2\n j[i] = 2 * fx * jac(x)\n i = i + 1\n return g, j\n\n opt = minimize(\n lambda X: objFun(X, fun, jac),\n X0,\n method=\"L-BFGS-B\",\n jac=True,\n bounds=[bounds] * len(X0),\n )\n\n X = opt.x\n np.round(X, decimals=5)\n return np.unique(X)","def newton_sqrt(n, threshold):\n\tx = n\n\twhile True:\n\t\troot = 0.5 * (x + n/x)\n\n\t\tif abs(root - x) < threshold:\n\t\t\treturn root\n\n\t\tx = root","def nth_root_of_a(n, a):\n return find_zero(lambda x: pow(x, n) - a, lambda x: n * pow(x, n-1))","def _nth_root(value, n_root) -> float:\r\n\r\n root_value = 1 / float(n_root)\r\n return Decimal(value) ** Decimal(root_value)","def findRoot(x, power, epsilon):\n\n if x < 0 and power % 2 == 0:\n return None\n\n low = min(-1.0, x)\n high = max(1.0, x)\n ans = (high + low) / 2.0\n while abs(ans**power - x) >= epsilon:\n if ans ** power < x:\n low = ans\n else:\n high = ans\n ans = (high + low) / 2.0\n return ans","def newton(f, xinit, tol, N):\n if f(xinit) < tol:\n return xinit\n else:\n n = 1\n while n < N:\n xnew = xinit - (f(xinit) / derivative(f, xinit))\n if abs(f(xnew)) < tol:\n print('Root found. Number of iterations: ', n)\n return xnew\n break\n else:\n xinit = xnew\n n = n + 1\n else:\n return 'Max iterations reached. No root found within chosen tolerance.'","def test_find_all_roots(self):\n\n print(\"\\nFalse Position Method: All Roots\")\n\n # input\n xmin = -1e2 # minimum x-value\n xmax = 1e2 # maximum x-value\n step = 1e0 # step-size of interval\n et = 1e-6 # relative error threshold\n\n # function\n roots, ic = FalsePosition.find_all_roots(self.fn, xmin, xmax, step, et)\n\n if len(roots) != 0:\n print(\"\\tAll Roots: {X}\\n\\tIterations: {ic}\".format(X=roots, ic=ic))\n else:\n print(\"\\tNo root found with given initial values.\")","def _nth_root(value, n_root):\n return value ** (1 / n_root)","def findRoot3(x,power,epsilon):\n if x<0 and power%2 ==0:\n return None\n # when x is fractional,root is between 0 and 1\n low = min(-1,x)\n high = max(1,x)\n ans = (high+low)/2.0\n while abs(ans**power -x) > epsilon:\n print ans\n if ans**power <x:\n low = ans \n else:\n high = ans\n ans = (high+low)/2.0\n return ans","def root_1(a, b):\n return -b / a","def root(x, y, precision=20):\n if type(x) is complex:\n return x ** (1.0 / y)\n if type(y) is complex:\n return x ** (1.0 / y)\n\n try:\n x = float(x)\n except:\n raise TypeError(\"{0} is not a number\".format(x))\n try:\n y = float(y)\n except:\n raise TypeError(\"{0} is not a number\".format(y))\n if x < 0 and y % 2 == 0:\n return root(abs(x), y) * 1j\n elif x < 0:\n return -root(abs(x), y)\n elif y < 0:\n return x ** (1.0 / y)\n\n if int(x) == x:\n x = int(x)\n if int(y) == y:\n y = int(y)\n # return x ** (1.0 / y)\n\n f = lambda n: n ** y - x\n fprime = lambda n: y * n ** (y - 1)\n\n guess = 10\n change = 1\n\n while change > 10 ** -precision:\n guess2 = guess - f(guess) / fprime(guess)\n change = abs(guess2 - guess)\n guess = guess2\n\n return guess","def custom_sqrt(n, p):\n\tstart = 0\n\tend = n\n\twhile start <= end:\n\t\tmid = start + (end - start) // 2\n\t\tif mid*mid == n:\n\t\t\treturn mid\n\t\tif mid * mid > n:\n\t\t\tend = mid - 1\n\t\tif mid * mid < n:\n\t\t\tstart = mid + 1\n\n\troot = end\n\tincr = 0.1\n\tfor i in range(p):\n\t\twhile (root*root <= n):\n\t\t\troot += incr\n\n\t\troot -= incr\n\t\tincr /= 10\n\n\treturn root","def find_poly_root(poly, initial_guess = 0.0, limit = 0.00001, max_iterations = 1000):\n # Calculate the polynomial derivatives\n dpoly = polynomial.derivative(poly)\n ddpoly = polynomial.derivative(dpoly)\n # Closures !!!\n f = lambda x: polynomial.eval(poly, x)\n df = lambda x: polynomial.eval(dpoly, x)\n ddf = lambda x: polynomial.eval(ddpoly, x)\n # Call the generic root finder\n return find_root(f, df, ddf, initial_guess, limit, max_iterations)","def _root():\n return 0","def sp_solve ( fun , xmin , xmax , C = 0 , args = () ) :\n ##\n if iszero ( C ) :\n return findroot ( fun , xmin , xmax , args = args )\n ##\n func = lambda x , *a : fun(x,*a)-C\n return findroot ( func , xmin , xmax , args = args )","def Stochastic_RootFinder(F, x0, a=.5, alpha=0.5, max_iter=20, xtol=.01, ValidInterval=[0.00001,100]):\n\n xp,n= ValidInterval[1]*2,1\n n0 = int(max_iter/20)+1\n xn = x0\n displacement = 10 * xtol\n\n while displacement > xtol and n<max_iter:\n an = a/ ( (n+n0)** alpha)\n Fn=F(xn)\n print('SRF step '+ str(n))\n print('--------------------------')\n print('current value of x is '+ str(xn))\n print('current value of F is '+ str(Fn))\n xnext = xn-an*np.asscalar(Fn)\n \n if xnext>ValidInterval[1]:\n xnext = ValidInterval[1]\n elif xnext<ValidInterval[0]:\n xnext = ValidInterval[0]\n \n print('new x is ' + str(xnext))\n\n\n\n # shift and compute total displacement in the last 2 steps\n displacement = np.ptp(np.array([xp,xn,xnext]))\n print('displacement in the last 3 steps is ' + str(displacement))\n xp=xn\n xn=xnext\n \n\n n=n+1\n\n return xnext,Fn","def root_midpoint(self):\n node1, node2, distance = self.find_middle_point()\n self.root_nodes(node1, node2, distance)","def compute_root(poly, x_0, epsilon):\n guess = 0\n while True:\n poly_value = evaluate_poly(poly, x_0)\n if -epsilon < poly_value < epsilon:\n guess += 1\n return x_0, guess\n else:\n poly_derivative = compute_deriv(poly)\n deriv_value = evaluate_poly(poly_derivative, x_0)\n x_0 = x_0 - poly_value / deriv_value\n guess += 1","def mpf_nthroot(s, n, prec, rnd=round_fast):\n sign, man, exp, bc = s\n if sign:\n raise ComplexResult(\"nth root of a negative number\")\n if not man:\n if s == fnan:\n return fnan\n if s == fzero:\n if n > 0:\n return fzero\n if n == 0:\n return fone\n return finf\n # Infinity\n if not n:\n return fnan\n if n < 0:\n return fzero\n return finf\n flag_inverse = False\n if n < 2:\n if n == 0:\n return fone\n if n == 1:\n return mpf_pos(s, prec, rnd)\n if n == -1:\n return mpf_div(fone, s, prec, rnd)\n # n < 0\n rnd = reciprocal_rnd[rnd]\n flag_inverse = True\n extra_inverse = 5\n prec += extra_inverse\n n = -n\n if n > 20 and (n >= 20000 or prec < int(233 + 28.3 * n**0.62)):\n prec2 = prec + 10\n fn = from_int(n)\n nth = mpf_rdiv_int(1, fn, prec2)\n r = mpf_pow(s, nth, prec2, rnd)\n s = normalize(r[0], r[1], r[2], r[3], prec, rnd)\n if flag_inverse:\n return mpf_div(fone, s, prec-extra_inverse, rnd)\n else:\n return s\n # Convert to a fixed-point number with prec2 bits.\n prec2 = prec + 2*n - (prec%n)\n # a few tests indicate that\n # for 10 < n < 10**4 a bit more precision is needed\n if n > 10:\n prec2 += prec2//10\n prec2 = prec2 - prec2%n\n # Mantissa may have more bits than we need. Trim it down.\n shift = bc - prec2\n # Adjust exponents to make prec2 and exp+shift multiples of n.\n sign1 = 0\n es = exp+shift\n if es < 0:\n sign1 = 1\n es = -es\n if sign1:\n shift += es%n\n else:\n shift -= es%n\n man = rshift(man, shift)\n extra = 10\n exp1 = ((exp+shift-(n-1)*prec2)//n) - extra\n rnd_shift = 0\n if flag_inverse:\n if rnd == 'u' or rnd == 'c':\n rnd_shift = 1\n else:\n if rnd == 'd' or rnd == 'f':\n rnd_shift = 1\n man = nthroot_fixed(man+rnd_shift, n, prec2, exp1)\n s = from_man_exp(man, exp1, prec, rnd)\n if flag_inverse:\n return mpf_div(fone, s, prec-extra_inverse, rnd)\n else:\n return s","def primitive_root(n):\n if n == 2:\n return 1\n phi = euler_phi(n)\n phi_divisors = factorize(phi)\n for g in range(2, n + 1):\n if gcd(g, n) != 1:\n continue\n for d, _ in phi_divisors:\n if powmod(g, phi // d, n) == 1:\n # g can not be a generator\n break\n else:\n return g\n\n # generator not found\n # Gauss theorem conditions did not met\n return None","def root(self, x):\n assert ((x < self.n) & (x >= 0)), 'array index is out of bounds'\n\n while x != self.array[x]:\n self.array[x] = self.array[self.array[x]]\n x = self.array[x]\n return x","def find_roots(func, a, b, step=1e-3, roots=None):\n if roots is None:\n roots = []\n if len(roots) > 100:\n return roots\n if func(a) == 0:\n roots.append(a)\n find_roots(func, a+1e-3, b, roots)\n if func(b) == 0:\n roots.append(b)\n find_roots(func, a, b-1e-3, roots)\n # n_steps = 1000\n # step = 1./n_steps\n n_steps = int(1./step)\n win_size = b - a\n for s in np.linspace(a+step, b-step, n_steps):\n if func(s) * func(s+step*win_size) >= 0:\n continue\n r = brentq(func, s, s+step*win_size)\n roots.append(r)\n\n return roots","def square_root(value):\n # Init\n root = 1.0 # Provisional square root\n difference = (root * root) - value # How far off is our provisional root\n\n ##--- Loop until the provisional root is close enough to the actual root ----###\n while difference > 0.00000001 or difference < -0.00000001:\n root = (root + (value / root)) / 2 # Compute new provisional root\n difference = (root * root) - value # # How far off is our current approximation?\n \n return root","def rootsearch(self, f, a, b, dx):\n x1 = a \n f1 = f(a)\n x2 = a + dx\n f2 = f(x2)\n while f1*f2 > 0.0:\n if x1 >= b: \n return None,None\n x1 = x2\n f1 = f2\n x2 = x1 + dx\n f2 = f(x2)\n else:\n return x1,x2","def bisect_root(V, y0, rng, Eleft, E0left, Eright, E0right, delta):\n\n E0mid = (E0left + E0right) / 2.0\n func = schroed_system(E0mid, V)\n [Emid, _] = one_step(func, y0, rng)\n\n # If we try to bisect too much, we can reach the machine's limit\n # and one of the sides will be equal to the middle\n if E0mid == E0left or E0mid == E0right:\n return (E0mid, Emid)\n\n if abs(Emid) < delta:\n return (E0mid, Emid)\n\n if sign_change(Eleft, Emid):\n return bisect_root(V, y0, rng, Eleft, E0left, Emid, E0mid, delta)\n elif sign_change(Emid, Eright):\n return bisect_root(V, y0, rng, Emid, E0mid, Eright, E0right, delta)\n else:\n assert ValueError, \"there is no sign change in the values given\"","def root_scalar(func, *args, **kwargs):\n bracket = kwargs.get('bracket', None)\n if bracket is None or len(bracket) != 2:\n msg = (\"To run root_scalar, you have to provide a \"\n \"`bracket` keyword argument with a sequence \"\n \"of length 2.\")\n raise ValueError(msg)\n\n try:\n func(bracket[0], *args)\n except Exception as e:\n msg = (\"Before running scipy.integrate.root_scalar \"\n \"I tried running the function you provided \"\n \"with `bracket[0]`, \"\n \"and I got the following error:\")\n logger.error(msg)\n raise (e)\n\n underride(kwargs, rtol=1e-4)\n\n res = spo.root_scalar(func, *args, **kwargs)\n\n if not res.converged:\n msg = (\"scipy.optimize.root_scalar did not converge. \"\n \"The message it returned is:\\n\" + res.flag)\n raise ValueError(msg)\n\n return res","def int_root(y, n):\r\n if y < 0: raise ValueError, \"y must not be negative\"\r\n if n < 1: raise ValueError, \"n must be positive\"\r\n if y in (0, 1): return y, True\r\n if n == 1: return y, True\r\n if n > y: return 1, False\r\n # Get initial estimate for Newton's method. Care must be taken to\r\n # avoid overflow\r\n try:\r\n guess = int(y ** (1./n)+0.5)\r\n except OverflowError:\r\n try:\r\n guess = int(math.exp(math.log(y)/n)+0.5)\r\n except OverflowError:\r\n guess = 1 << int(math.log(y, 2)/n)\r\n # Newton iteration\r\n xprev, x = -1, guess\r\n while 1:\r\n t = x**(n-1)\r\n xprev, x = x, x - (t*x-y)//(n*t)\r\n if abs(x - xprev) < 1:\r\n break\r\n # Compensate\r\n t = x**n\r\n while t > y:\r\n x -= 1\r\n t = x**n\r\n return x, t == y","def sqrt(x):\n return 0.0","def test_inv_sphere_v3_root_find(self):\n import itertools\n\n for k in (0, -1, 1, 1.75, 0.325, 1/7, -1.75, -0.325, -1/7):\n s = space(fake_curvature=k) \n for m in itertools.chain(\n range(30),\n range(31,3000,100),\n map((1).__truediv__, range(3, 30, 2)),\n ):\n r = s.inv_sphere_v3(m)\n self.assertTrue(r >= 0)\n v = s.sphere_v3(r)\n self.assertTrue(isclose(\n m,\n v\n ))","def find_roots(a: int, b: int, c: int):\n if a == 0:\n x = -c / b\n print(f\"Solution is {x}\")\n return x\n\n d = b ** 2 - (4 * a * c)\n\n if d < 0:\n print(\"No solutions\")\n return None\n elif d == 0:\n x = (-b + sqrt(d)) / (2 * a)\n print(f\"Solution is {x}\")\n return x\n\n x1 = (-b + sqrt(d)) / (2 * a)\n x2 = (-b - sqrt(d)) / (2 * a)\n\n print(f\"Solutions are {x1} and {x2}\")\n return x1, x2","def root_finding_newton(fun, J, x, eps, max_iter, args):\n F_value = fun(x, *args)\n F_value_ = F_value.reshape((-1,1))\n F_norm = np.linalg.norm(F_value, 2) # l2 norm of vector\n iteration_counter = 0\n while abs(F_norm) > eps and iteration_counter < max_iter:\n delta = np.linalg.solve(J(x, args), -F_value_)\n\n for i in range(x.size): #wtf numba!?!?!\n x[i] += delta[i,0]\n\n F_value = fun(x, *args)\n F_value_ = F_value.reshape((-1,1))\n F_norm = np.linalg.norm(F_value, 2)\n iteration_counter += 1\n\n # Here, either a solution is found, or too many iterations\n if abs(F_norm) > eps:\n iteration_counter = -1\n raise ValueError('Maximum iteration reached in newton root finding!')\n return x, iteration_counter","def compute_root(poly, x_0, epsilon):\n # TO DO ...\n diff = evaluate_poly(poly, x_0)\n count = 0\n\n if abs(diff) > epsilon:\n #Newton's Method Formula\n x_1 = x_0 - (evaluate_poly(poly, x_0) / evaluate_poly(compute_deriv(poly), x_0))\n #Recursion!\n x_0 , count = compute_root(poly, x_1, epsilon)\n else:\n pass\n\n return x_0, count + 1","def binary_search_find_root(number, min, max, accuracy, n):\n if max <= min: # Can't find\n return -1\n\n mid_val = (max + min)/2 # Returns a float.\n if round(mid_val ** n, accuracy) == number:\n return mid_val\n elif mid_val ** n > number: # Need to make mid_val**2 less so it matches number.\n return binary_search_find_root(number, min, mid_val, accuracy, n) # Look at values between min and mid, discard > mid point.\n elif mid_val ** n < number:\n return binary_search_find_root(number, mid_val, max, accuracy, n) # Discard values lower than mid to make number bigger.","def test_j0_root():\n import time\n t1 = time.time()\n\n # Our version uses tabulated values up to 40, so a useful test of the extrapolation\n # requires this to have more than 40 items.\n vals1 = [ galsim.bessel.j0_root(s) for s in range(1,51) ]\n print 'vals1 = ',vals1\n\n try:\n import scipy.special\n vals2 = scipy.special.jn_zeros(0,50)\n print 'vals2 = ',vals2\n np.testing.assert_almost_equal(\n vals1, vals2, 8, \"bessel.j0_root disagrees with scipy.special.jn_zeros\")\n except ImportError:\n print 'Unable to import scipy. Skipping scipy tests of j0_root.'\n\n # These values are what scipy returns. Check against these, so not require scipy.\n vals2 = [ 2.40482556, 5.52007811, 8.65372791, 11.79153444,\n 14.93091771, 18.07106397, 21.21163663, 24.35247153,\n 27.49347913, 30.63460647, 33.77582021, 36.91709835,\n 40.05842576, 43.19979171, 46.34118837, 49.4826099 ,\n 52.62405184, 55.76551076, 58.90698393, 62.04846919,\n 65.1899648 , 68.33146933, 71.4729816 , 74.61450064,\n 77.75602563, 80.89755587, 84.03909078, 87.18062984,\n 90.32217264, 93.46371878, 96.60526795, 99.74681986,\n 102.88837425, 106.02993092, 109.17148965, 112.31305028,\n 115.45461265, 118.59617663, 121.73774209, 124.87930891,\n 128.02087701, 131.16244628, 134.30401664, 137.44558802,\n 140.58716035, 143.72873357, 146.87030763, 150.01188246,\n 153.15345802, 156.29503427\n ]\n np.testing.assert_almost_equal(\n vals1, vals2, 8, \"bessel.j0_root disagrees with reference values\")\n\n t2 = time.time()\n print 'time for %s = %.2f'%(funcname(),t2-t1)","def positiveRoot(a,b,c):\n # The discriminant\n disc = np.sqrt(b**2 - 4*a*c)\n root1 = (-b + disc) / (2*a)\n # This tells python to return the root1 value when the positive_root function is called\n return root1","def scale_root(self) -> int:\r\n ...","def newton(f, x0, dx, eps=1e-10):\n # Initialization\n globvar.ncalls = 0\n x = np.copy(x0)\n n = len(x)\n J = np.zeros((n, n), dtype='float64')\n fx = f(x)\n\n # Begin root search\n while True:\n globvar.ncalls += 1\n\n # Fill the Jacobian matrix\n for j in range(n):\n x[j] += dx[j]\n df = f(x) - fx\n\n for i in range(n):\n J[i, j] = df[i] / dx[j]\n\n x[j] -= dx[j]\n\n # Decompose and solve using Given's rotations\n decomp(J)\n Dx = -fx\n solve(J, Dx)\n\n # Begin backtracking linesearch\n lamb = 2.0\n while True: \n lamb /= 2\n y = x + Dx * lamb\n fy = f(y)\n\n fynorm = np.linalg.norm(fy)\n fxnorm = np.linalg.norm(fx)\n\n if (fynorm < (1 - lamb / 2) * fxnorm) or (lamb < (1 / 128.0)):\n break\n\n # Save latest approximation\n x = y\n fx = fy\n\n Dxnorm = np.linalg.norm(Dx)\n fxnorm = np.linalg.norm(fx)\n dxnorm = np.linalg.norm(dx)\n if Dxnorm < dxnorm or fxnorm < eps:\n break\n\n return x","def sqrt(n, one):\n # Use floating point arithmetic to make an initial guess\n floating_point_precision = 10**16\n n_float = float((n * floating_point_precision) // one) / floating_point_precision\n x = (int(floating_point_precision * math.sqrt(n_float)) * one) // floating_point_precision\n n_one = n * one\n while 1:\n x_old = x\n x = (x + n_one // x) // 2\n if x == x_old:\n break\n return x","def _square_rooted(x):\n return sqrt(sum([(a * a) for a in x]))","def test_find_root_multi(self):\n\n print(\"\\nNewton-Raphson Method: Multivariate\")\n\n # input\n xi = 1 # initial value of first variable\n yi = 1 # initial value of second variable\n em = 1e-6 # error margin\n imax = 1e3 # maximum number of iterations to consider\n\n # function\n root, ic, msg = NewtonRaphson.find_root_multi([self.f, self.g], [[self.dfdx, self.dfdy],[self.dgdx, self.dgdy]], [xi, yi], em, imax)\n\n # output\n if root != None:\n print(\"\\tInitial value: {xi}\\n\\tRoot: {X}\\n\\tFirst function Value: {f}\\n\\tSecond function Value: {g}\\n\\tIterations: {ic}\".format(xi=xi, X=root, f=self.f(root), g=self.g(root), ic=ic))\n else:\n print(\"\\t{msg}.\".format(msg=msg))","def test_cases():\r\n quadratic_roots(1,3,-21)\r\n quadratic_roots(2,-4,-6)\r\n quadratic_roots(1,4,-12)\r\n quadratic_roots(4,12,9)\r\n quadratic_roots(-2,-11,-21)\r\n quadratic_roots(4,1,4)\r\n quadratic_roots(1,1,0)\r\n quadratic_roots(1,0,-16)\r\n quadratic_roots(1,-14,-49)\r\n quadratic_roots(1,10,25)","def test_find_root_uni(self):\n\n print(\"\\nNewton-Raphson Method: Univariate\")\n\n # input\n xi = 1 # initial value\n et = 1e-6 # relative error threshold\n imax = 1e6 # maximum number of iterations to consider\n\n # function\n root, ic, msg = NewtonRaphson.find_root_uni(self.fn, self.df, xi, et, imax)\n\n # output\n if root != None:\n print(\"\\tInitial value: {xi}\\n\\tRoot: {x}\\n\\tFunction Value: {fx}\\n\\tIterations: {ic}\".format(xi=xi, x=root, fx=self.fn(root), ic=ic))\n else:\n print(\"\\t{msg}.\".format(msg=msg))","def findPrimitiveNthRoot(M, N):\n roots = nthroot_mod(1, N, M, True)[1:] # find Nth root of unity\n for root in roots: # find primitive Nth root of unity\n is_primitive = True\n for k in range(1, N):\n if pow(root, k, M) == 1:\n is_primitive = False\n if is_primitive:\n return root\n return None","def call_by_root(f, root=0):\n MPI = is_running_mpi()\n if MPI:\n comm = MPI.COMM_WORLD\n rank = comm.Get_rank()\n if rank == root:\n return f()\n else:\n return f()","def solve(n=5000,C=-6*10**11,a=900,b=3):\n coeffs = np.zeros(n+2)\n coeffs[0] = a-b*n\n coeffs[1] = b*(n+1) - a\n coeffs[-3] = -C\n coeffs[-2] = 2*C - a\n coeffs[-1] = a+b-C\n mp.dps = 27\n roots = polyroots(coeffs)\n for root in roots:\n print root","def root_3(a, b, c, d):\n abc = a * b * c\n bbb = b * b * b\n aad = a * a * d\n\n dd = (18. * abc * d - 4. * bbb * d\n + b * b * c * c - 4. * a * c * c * c\n - 27. * aad * d)\n d0 = b * b - 3. * a * c\n\n # second and third cubic unity roots (first is just 1)\n cu2 = -0.5 + 0.86602540378443864676j\n cu3 = -0.5 - 0.86602540378443864676j\n\n if not dd and not d0: # all real roots\n x1 = x2 = x3 = -b / (3. * a)\n elif not dd and d0: # double root, simple root\n x1 = x2 = ((9. * a * d - b * c) / (2. * d0))\n x3 = (4. * abc - 9. * aad - bbb) / (a * d0)\n else:\n d1 = 2. * bbb - 9. * abc\n d1 = d1 + 27. * aad\n\n if not d0: cin = d1 + 0j # inner terms cancel\n else: cin = (d1 - sqrt(-27.0 * a * a * dd)) / 2.\n\n cc = cin ** (1. / 3.)\n p = (-1. / (3. * a))\n\n x1 = p * (b + cc + d0 / cc)\n x2 = p * (b + cu2 * cc + d0 / (cu2 * cc))\n x3 = p * (b + cu3 * cc + d0 / (cu3 * cc))\n\n return x1, x2, x3","def root_finding_newton_previously(fun, J, x, eps, max_iter, args):\n F_value = fun(x, args)\n F_value_ = F_value.reshape((-1,1))\n F_norm = np.linalg.norm(F_value, 2) # l2 norm of vector\n iteration_counter = 0\n while abs(F_norm) > eps and iteration_counter < max_iter:\n delta = np.linalg.solve(J(x, args), -F_value)\n x = x + delta\n F_value = fun(x, args)\n F_value_ = F_value.reshape((-1,1))\n F_norm = np.linalg.norm(F_value, 2)\n iteration_counter += 1\n\n # Here, either a solution is found, or too many iterations\n if abs(F_norm) > eps:\n iteration_counter = -1\n raise ValueError('Maximum iteration reached in newton root finding!')\n return x, iteration_counter","def Newton(f, x0, tol, kmax, c=0.5, tao=1e-6, reg_const=1e-7):\r\n\r\n k = 1\r\n\r\n xk = x0.copy() # We don't want to change x0 from the outside scope\r\n\r\n # Cache for f(xk) in case the calculation is expensive\r\n # - Should save 2-3 function evaluations per outside loop iteration\r\n f_xk = f(xk)\r\n\r\n s = LA.norm(f_xk)**2\r\n\r\n while np.sqrt(s) > tol and k < kmax:\r\n # Build the Jacobian matrix approximation using Central Differences\r\n H = _CentralDifferencesJacobian(f, xk, tao)\r\n\r\n try:\r\n # Uses LAPACK _gesv to solve H*dk = -f(xk)\r\n dk = LA.solve(H, -f_xk)\r\n except LA.LinAlgError:\r\n # Most likely here because the above H is singular\r\n # Therefore we regularize by adding a small (1e-7) multiple of I:\r\n dk = LA.solve(H + reg_const*np.eye(xk.shape[0]), -f_xk)\r\n\r\n z = c*LA.norm(np.matmul(f_xk.T, H))*LA.norm(dk)\r\n\r\n # Solve the step size using the method by Stoer and Bulirsch\r\n j = 0\r\n L = LA.norm(f(xk + dk))**2\r\n R = s-z\r\n Lmin = L\r\n index = 0\r\n while L > R:\r\n j += 1\r\n L = LA.norm(f(xk + 2**(-j)*dk))**2\r\n R = s - 2**(-j)*z\r\n if L < Lmin:\r\n Lmin = L\r\n index = j\r\n\r\n # Update xk\r\n xk = xk + 2**(-index)*dk\r\n\r\n k += 1\r\n\r\n # Cache the new f(xk)\r\n f_xk = f(xk)\r\n\r\n s = LA.norm(f_xk)**2\r\n\r\n # If kmax gets exceeded, we can't trust the answer so issue a warning\r\n if k >= kmax:\r\n # For debugging purposes\r\n # print(\"k exceeded kmax, can't trust answer\")\r\n # return xk\r\n warnings.warn(\"kmax exceeded, consider raising it\", NonConvergenceWarning)\r\n\r\n # Otherwise, we stopped the above loop because we're within tolerance so the answer is good\r\n return xk, k","def getRoots(self):\n a, b, c = self.getCoefficients()[2], self.getCoefficients()[1], self.getCoefficients()[0]\n delta = b**2 - 4*a*c\n if delta >= 0:\n roots = sorted([(-b - math.sqrt(delta))/(2*a), (-b + math.sqrt(delta))/(2*a)])\n else:\n roots = sorted([(-b - math.sqrt(-delta)*1j)/(2*a), (-b + math.sqrt(-delta)*1j)/(2*a)], key=lambda x: (x.real, x.imag))\n return roots","def root_finding_newton_previously(fun, J, x, eps, max_iter, args):\n F_value = fun(x, args)\n # F_value_ = F_value.reshape((-1, 1))\n F_norm = np.linalg.norm(F_value, 2) # l2 norm of vector\n iteration_counter = 0\n while abs(F_norm) > eps and iteration_counter < max_iter:\n delta = np.linalg.solve(J(x, args), -F_value)\n x = x + delta\n F_value = fun(x, args)\n # F_value_ = F_value.reshape((-1, 1))\n F_norm = np.linalg.norm(F_value, 2)\n iteration_counter += 1\n\n # Here, either a solution is found, or too many iterations\n if abs(F_norm) > eps:\n iteration_counter = -1\n raise ValueError(\"Maximum iteration reached in newton root finding!\")\n return x, iteration_counter","def test_cubic_roots(roots, a0, a1, a2, a3=None, tol=1.0e-12):\n\n N = len(a0)\n for n in range(N):\n c0 = a0[n]\n c1 = a1[n]\n c2 = a2[n]\n c3 = a3[n]\n\n print(f\"Polynomial {n}: a = {(c0,c1,c2,c3)}\")\n\n rts = np.unique(roots[n])\n rts = rts[~np.isnan(rts)]\n\n for x in rts:\n f = c0 + c1 * x + c2 * x**2 + c3 * x**3\n ok = np.abs(f) <= tol\n\n print(f\" root x = {x}: f(x) = {f} {'OK' if ok else 'FAILED'}\")\n\n if not ok:\n raise Exception(\"NOT OK!\")\n\n if len(rts) == 0:\n print(\" no real roots.\")","def cube_root(val):\n return val ** (1 / 3)","def roots_binomial(f):\n n = f.degree()\n\n a, b = f.nth(n), f.nth(0)\n base = -cancel(b/a)\n alpha = root(base, n)\n\n if alpha.is_number:\n alpha = alpha.expand(complex=True)\n\n # define some parameters that will allow us to order the roots.\n # If the domain is ZZ this is guaranteed to return roots sorted\n # with reals before non-real roots and non-real sorted according\n # to real part and imaginary part, e.g. -1, 1, -1 + I, 2 - I\n neg = base.is_negative\n even = n % 2 == 0\n if neg:\n if even == True and (base + 1).is_positive:\n big = True\n else:\n big = False\n\n # get the indices in the right order so the computed\n # roots will be sorted when the domain is ZZ\n ks = []\n imax = n//2\n if even:\n ks.append(imax)\n imax -= 1\n if not neg:\n ks.append(0)\n for i in range(imax, 0, -1):\n if neg:\n ks.extend([i, -i])\n else:\n ks.extend([-i, i])\n if neg:\n ks.append(0)\n if big:\n for i in range(0, len(ks), 2):\n pair = ks[i: i + 2]\n pair = list(reversed(pair))\n\n # compute the roots\n roots, d = [], 2*I*pi/n\n for k in ks:\n zeta = exp(k*d).expand(complex=True)\n roots.append((alpha*zeta).expand(power_base=False))\n\n return roots","def refine_real_root(f, s, t, eps=None, steps=None, fast=False):\n return dmp_refine_real_root(f.rep, s, t, f.lev, f.dom, eps=eps, steps=steps, fast=fast)","def isPrimitiveNthRoot(M, N, beta):\n return pow(beta, N, M) == 1 # modular(M).modExponent(beta, N) == 1","def root_finding_newton(fun, J, x, eps, max_iter, args):\n F_value = fun(x, args)\n F_value_ = F_value.reshape((-1, 1))\n F_norm = np.linalg.norm(F_value, 2) # l2 norm of vector\n iteration_counter = 0\n while abs(F_norm) > eps and iteration_counter < max_iter:\n delta = np.linalg.solve(J(x, args), -F_value_)\n\n for i in range(x.size): # wtf numba!?!?!\n x[i] += delta[i, 0]\n\n F_value = fun(x, args)\n F_value_ = F_value.reshape((-1, 1))\n F_norm = np.linalg.norm(F_value, 2)\n iteration_counter += 1\n\n # Here, either a solution is found, or too many iterations\n if abs(F_norm) > eps:\n iteration_counter = -1\n raise ValueError(\"Maximum iteration reached in newton root finding!\")\n return x, iteration_counter","def root_v0(self, v):\n from scipy.integrate import quad\n from scipy.special import erfc, erfcx\n def integrand(u):\n \"\"\"Integrand of self-consistency equation\"\"\"\n return erfcx(-u)\n #if u < -4.0:\n #return -1. / np.sqrt(np.pi) * (1.0 / u - 1.0 / (2.0 * u**3) + \n ##3.0 / (4.0 * u**5) - \n ##15.0 / (8.0 * u**7))\n #else:\n #return np.exp(u**2) * (1. + erf(u))\n\n\n mu_v = self.mu(v)\n sd_v = self.sd(v)\n low = (self.V_r - mu_v) / sd_v\n up = (self.theta - mu_v) / sd_v\n bounds = np.array([low, up]).T\n\n integral = np.array([quad(integrand, lower, upper)[0] for lower, upper in bounds])\n root = - 1. / v + self.t_ref * 1e-3 \\\n + np.sqrt(np.pi) * self.tau_m * 1e-3 * integral\n return root","def get_positive_roots(roots, A):\n return roots[[np.any(utils.round(to_simple_root_basis(root, A)) > 0) for root in roots]]","def sqrt(n):\n pass","def my_sqrt(x):\n square_root = x**(0.5)\n return square_root","def mySqrt(self, x: int) -> int:\n if x == 0:\n return 0\n d = 0.1\n y = x / 2\n z = (y + x/y) / 2\n e = abs(z-y)\n while e > d:\n y = z\n z = (y + x/y) / 2\n e = abs(z - y)\n return int(z)","def __find_root(self, x):\n index = x\n while self.data[index] != index:\n self.data[index] = self.data[self.data[index]]\n index = self.data[index]\n\n return index","def sqrt(number):\n # return number if its 0 or 1 since 0*0=0 and 1*1=1\n if number == 0 or number ==1:\n return number\n #square root negative number is not real number\n if number < 0:\n return None\n\n #using binary search, if s is square root of y that means 0<=s<=y. That is\n #s*s = y. if for a given number x, x*x > y that means square root s should lie\n #between 0<=s<x. if for a given number x, x*x < y that means square root s should lie\n #between x<s<=y\n start = 1\n end = number\n floor_sqrt = 0\n iterate=0\n while(start <= end):\n iterate+=1\n #start with middle elemment\n mid = (start + end )//2\n #check if mid * mid = number, then mid is answer\n if mid * mid == number:\n return mid\n #if mid * mid < number, check between range (mid,end]\n #also maintain mid value since, we have to return floor value\n if mid * mid < number:\n start = mid + 1\n floor_sqrt = mid\n #if mid * mid > number, check between range [start,end)\n else:\n end = mid - 1\n return floor_sqrt","def sqrt(a):","def sqrt(x):\n def good_enough(guess):\n precision = 0.001\n f = abs(guess ** 2 - x)\n return (f < precision)\n \n def improve(guess):\n return (guess + x/guess) / 2.0\n \n counter = 1\n guess = 1\n while not good_enough(guess) and counter <= 100:\n guess = improve(guess)\n counter += 1\n assert counter <= 100,'100 iterations done and no good answer' \n return int(guess)","def newton_method(f, x, Ep, step):\n\n while True:\n step = step + 1\n # print(\"bnd1:=\",bnd1)\n h = f(x) / derivative(f, x)\n x = x - h\n if (decide(abs(h) <= Ep)):\n break\n # print(\"Root in Approximation: \",bnd1)\n return step","def bisectionSqrt(x, epsilon = 0.01, low = None, high = None):\n\n\tif low == None:\n\t\tlow = 0.0\n\tif high == None:\n\t\thigh = x\n\n\tmidPoint = (high + low)/2.0\n\t# If the difference of the midpoint squared and x is\n\t# within the epsilon tolerance, OR is the midpoint is\n\t# greater than X, we stop and give answer\n\tif abs(midPoint**2 - x) < epsilon or midPoint > x:\n\t\treturn midPoint\n\telse:\n\t\t# Otherwise check if the midPoint is too big or small\n\t\tif midPoint ** 2 < x:\n\t\t\t# If too small, recurse on the upper half\n\t\t\treturn bisectionSqrt(x,epsilon,midPoint,high)\n\t\telse :\n\t\t\t# If too big, recurse on the lower half\n\t\t\treturn bisectionSqrt(x,epsilon,low,midPoint)","def brents(f, x0, x1, max_iter=50, tolerance=1e-5):\n \n fx0 = f(x0)\n fx1 = f(x1)\n \n assert (fx0 * fx1) <= 0, \"Root not bracketed\" \n \n if abs(fx0) < abs(fx1):\n x0, x1 = x1, x0\n fx0, fx1 = fx1, fx0\n \n x2, fx2 = x0, fx0\n \n d = np.nan\n mflag = True\n steps_taken = 0\n \n while steps_taken < max_iter and abs(x1-x0) > tolerance:\n fx0 = f(x0)\n fx1 = f(x1)\n fx2 = f(x2)\n \n if fx0 != fx2 and fx1 != fx2:\n L0 = (x0 * fx1 * fx2) / ((fx0 - fx1) * (fx0 - fx2))\n L1 = (x1 * fx0 * fx2) / ((fx1 - fx0) * (fx1 - fx2))\n L2 = (x2 * fx1 * fx0) / ((fx2 - fx0) * (fx2 - fx1))\n new = L0 + L1 + L2\n \n else:\n new = x1 - ( (fx1 * (x1 - x0)) / (fx1 - fx0) )\n \n tt1 = (new < ((3 * x0 + x1) / 4) or new > x1)\n tt2 = (mflag == True and (abs(new - x1)) >= (abs(x1 - x2) / 2))\n tt3 = (mflag == False and (abs(new - x1)) >= (abs(x2 - d) / 2))\n tt4 = (mflag == True and (abs(x1 - x2)) < tolerance)\n tt5 = (mflag == False and (abs(x2 - d)) < tolerance)\n if (tt1 or\n tt2 or\n tt3 or\n tt4 or\n tt5):\n new = (x0 + x1) / 2\n mflag = True\n \n else:\n mflag = False\n \n fnew = f(new)\n d, x2 = x2, x1\n \n if (fx0 * fnew) < 0:\n x1 = new\n else:\n x0 = new\n \n if abs(fx0) < abs(fx1):\n x0, x1 = x1, x0\n \n steps_taken += 1\n \n return x1, steps_taken","def root_2(a, b, c):\n p1 = sqrt(b * b - 4. * a * c)\n p2 = -2. * a\n\n x1 = (b - p1) / p2\n x2 = (b + p1) / p2\n\n return x1, x2","def test_fixed_point(testFunctions, tol, printFlag): \n pass","def test_fixed_point_system(testFunctions, tol, printFlag): \n pass","def test_root():\n gnroot = 's51001'\n root = germanet_data.get_synset_by_id(gnroot)\n np.testing.assert_equal(root.is_root(), True)\n np.testing.assert_equal(root.is_leaf(), False)","def iroots(a, b, c):\n discriminant = b*b-4*a*c\n if discriminant == 0:\n return -b/(2*a), None\n else:\n return (-b+isqrt(discriminant))/(2*a), (-b-isqrt(discriminant))/(2*a)","def kth_root_modulo(a, k, n):\n # x = g^y => x^k = (g^k)^y = a\n # => y = log_{g^k} a (mod n)\n g = primitive_root(n)\n gk = powmod(g, k, n)\n y = log_modulo(gk, a, n)\n return powmod(g, y, n)","def squareRootExhaustive(x, epsilon):\n step = espilon**2\n ans = 0.0\n while abs(ans**2 - x) >= epsilon and ans*ans <= x: \n # The ans*ans <= is there because of floating point arithmetic I think.\n ans += step \n if ans*ans > x:\n raise ValueError\n return ans","def sqrt_newton(a):\n\tdef sqrt_update(x):\n\t\treturn 0.5 * (x + a / x)\n\tdef sqrt_close(x):\n\t\treturn approx_eq(x * x, a)\n\treturn improve(sqrt_update, sqrt_close)","def bisect(f, x1, x2, tol=1.0e-9):\n assert callable(f), \"User-supplied function must be callable.\"\n assert x1 != x2, \"Bad initial range given to bracket.\"\n f1 = f(x1)\n f2 = f(x2)\n assert f1 * f2 < 0.0, \"Range does not clearly bracket a root.\"\n while abs(x2 - x1) > tol:\n x_mid = 0.5*(x1+x2)\n f_mid = f(x_mid)\n if f_mid == 0.0:\n return x_mid # found it\n if f_mid * f1 < 0.0:\n x2 = x_mid\n f2 = f_mid\n else:\n x1 = x_mid\n f1 = f_mid\n return x_mid","def square_root_with_newton_method(number, iterations):\n # Inital value of g.\n # Cycle based on the iterations number.\n # Formula in the cycle.\n # Return the rounded final result.\n\n if number <= 0 or iterations < 0:\n return None\n g = number * 0.5\n for i in range(int(iterations)):\n g2 = (g + number / g) * 0.5\n g = g2\n return round(g, 3)","def arr_1(A):\n copy = np.copy(A)\n indices = np.array(range(copy.size)) #array of indices\n roots = np.sqrt(indices)\n return copy + roots","def squareRootBi(x, epsilon):\n low = 0.0\n high = max(1.0, x)\n ans = (high + low)/2.0\n while abs(ans**2 - x) >= epsilon:\n # Where as here the ans*ans <= x isn't required because every value in\n # the bisection search is by nature some factor of 2. Clever. \n if ans**2 < x:\n low = ans\n else:\n high = ans\n ans = (high + low) / 2.0\n return ans","def _realroots_quadratic(a1, a0):\n D = a1*a1 - 4*a0\n if D < 0:\n return []\n SD = math.sqrt(D)\n return [0.5 * (-a1 + SD), 0.5 * (-a1 - SD)]","def is_root(self, n):\n return n == self._root"],"string":"[\n \"def find_root(function, point_a, point_b, step, tol, max_iterations, \\n show_process = False):\\n left_point , right_point = search_interval_3d(function, point_a, point_b, \\n step, tol, max_iterations,\\n show_process)\\n \\n point_where_zero = bisection_3d(function, left_point, right_point, tol, \\n max_iterations, show_process)\\n \\n return point_where_zero\",\n \"def find_root_1(x, n, p=0.001):\\n step = p / 10\\n guess = step\\n while abs(guess ** n - x) > p:\\n guess += step\\n return round(guess, 3)\",\n \"def findroot(self,x0,method='fmin',**kwargs):\\n return self._optimize(x0,'root',method,**kwargs)\",\n \"def nthRoot(x,n):\\n return op.pow(x,1/n)\",\n \"def test_find_root_in_interval(self):\\n\\n print(\\\"\\\\nFalse Position Method: Root in Interval\\\")\\n\\n # input\\n xi = 0 # initial value\\n xf = 1 # final value\\n et = 1e-6 # relative error threshold\\n\\n # function\\n root, ic, msg = FalsePosition.find_root_in_interval(self.fn, xi, xf, et)\\n\\n # output\\n if root != None:\\n print(\\\"\\\\tInterval: [{xi}, {xf}]\\\\n\\\\t{msg}: {x}\\\\n\\\\tFunction Value: {fx}\\\\n\\\\tIterations: {ic}\\\".format(xi=xi, xf=xf, msg=msg, x=root, fx=self.fn(root), ic=ic))\\n else:\\n print(\\\"\\\\t{msg}.\\\".format(msg=msg))\",\n \"def actual_root(x):\\n root = x ** (1/n)\\n\\tprint(x)\\n return root\",\n \"def find_root(f, df, ddf, initial_guess = 0.0, limit = 0.00001, max_iterations = 1000):\\n xn_1 = initial_guess\\n i = 0\\n while i < max_iterations:\\n fx = f(xn_1)\\n dfx = df(xn_1)\\n ddfx = ddf(xn_1)\\n xn = xn_1 - 2 * fx * dfx / (2 * dfx ** 2 - fx * ddfx)\\n if abs(xn - xn_1) < limit:\\n return xn\\n xn_1 = xn\\n i += 1\\n return None\",\n \"def sroot(n):\\n\\n return int(n ** 0.5) == n ** 0.5\",\n \"def find_root_2(x, n, p=0.001):\\n step = p / 10\\n left, right = 0, x\\n while True:\\n guess = (left + right) / 2\\n result = guess ** n\\n if abs(result - x) <= p:\\n break\\n elif result > x + p:\\n right = guess - step\\n else:\\n left = guess + step\\n\\n if round(guess) ** n == x:\\n return round(guess)\\n return round(guess, 3)\",\n \"def nth_root(n):\\n def actual_root(x):\\n \\\"\\\"\\\"Returns the nth root of x\\\"\\\"\\\"\\n root = x ** (1/n)\\n\\tprint(x)\\n return root\\n return actual_root\",\n \"def integer_root(n,k):\\n # from https://stackoverflow.com/questions/15978781/how-to-find-integer-nth-roots/15979957:\\n # Newton's method to find kth root of n\\n u, s = n, n+1\\n while u < s:\\n s = u\\n t = (k-1) * s + n // pow(s, k-1)\\n u = t // k\\n return s\",\n \"def rootfind_newton(func, x0, a, b, maxiter=50, tol=1.0e-11):\\n\\n for iter in xrange(maxiter):\\n\\n fval, fpval, args = func(x0)\\n # print \\\"x0=%.4f fval=%.2e fpval=%.2e [%.4f, %.4f]\\\" % (x0, fval, fpval, a, b)\\n\\n if fval < 0:\\n a = x0\\n else:\\n b = x0\\n\\n x = x0 - fval/fpval\\n if not (a < x < b):\\n # Once we have bracketed the root, we don't allow the\\n # iterations to leave the bracket.\\n x = 0.5*(a+b)\\n\\n if np.abs(x-x0) < tol or np.abs(fval) < tol:\\n break\\n\\n x0 = x\\n\\n return x, fval, iter, args\",\n \"def root_0(a):\\n return 0\",\n \"def n_root_of_x(n, x):\\n if n==0:\\n return 1\\n \\n return 1 if n==0 else x**(1.0/n)\",\n \"def getRoot(self, xa,xb, *args):\\n \\n count = 0\\n\\n while np.abs(xa-xb) > self.precision:\\n x = (xa + xb)/2\\n count += 1\\n if self.f(x, *args)*self.f(xa, *args) > 0:\\n xa = x\\n else:\\n xb = x\\n return [x, count]\",\n \"def test_newton_root_finder(self):\\n\\n # Set up the problem of finding the square roots of three numbers.\\n constants = np.array([4.0, 9.0, 16.0])\\n initial_values = np.ones(len(constants))\\n\\n def objective_and_gradient(values):\\n objective = values**2 - constants\\n gradient = 2.0 * values\\n return objective, gradient\\n\\n # Obtain and evaluate a tensor containing the roots.\\n roots = newton_root_finder(objective_and_gradient, initial_values)\\n root_values, converged, failed = self.evaluate(roots)\\n\\n # Reference values.\\n roots_bench = np.array([2.0, 3.0, 4.0])\\n converged_bench = np.array([True, True, True])\\n failed_bench = np.array([False, False, False])\\n\\n # Assert that the values we obtained are close to the true values.\\n np.testing.assert_array_equal(converged, converged_bench)\\n np.testing.assert_array_equal(failed, failed_bench)\\n np.testing.assert_almost_equal(root_values, roots_bench, decimal=7)\",\n \"def simple_root(self, i):\",\n \"def test_roots_slow():\\n a, b, c, d, x = symbols(\\\"a,b,c,d,x\\\")\\n\\n f1 = x ** 2 * c + (a / b) + x * c * d - a\\n f2 = x ** 2 * (a + b * (c - d) * a) + x * a * b * c / (b * d - d) + (a * d - c / d)\\n\\n assert list(roots(f1, x).values()) == [1, 1]\\n assert list(roots(f2, x).values()) == [1, 1]\\n\\n (zz, yy, xx, zy, zx, yx, k) = symbols(\\\"zz,yy,xx,zy,zx,yx,k\\\")\\n\\n e1 = (zz - k) * (yy - k) * (xx - k) + zy * yx * zx + zx - zy - yx\\n e2 = (zz - k) * yx * yx + zx * (yy - k) * zx + zy * zy * (xx - k)\\n\\n assert list(roots(e1 - e2, k).values()) == [1, 1, 1]\\n\\n f = x ** 3 + 2 * x ** 2 + 8\\n R = list(roots(f).keys())\\n\\n assert not any(i for i in [f.subs(x, ri).n(chop=True) for ri in R])\",\n \"def _rootsFinder(self, fun, jac, bounds, npoints, method):\\n if method == \\\"regular\\\":\\n step = (bounds[1] - bounds[0]) / (npoints + 1)\\n try:\\n X0 = np.arange(bounds[0] + step, bounds[1], step)\\n except:\\n X0 = np.random.uniform(bounds[0], bounds[1], npoints)\\n elif method == \\\"random\\\":\\n X0 = np.random.uniform(bounds[0], bounds[1], npoints)\\n\\n def objFun(X, f, jac):\\n g = 0\\n j = np.zeros(X.shape)\\n i = 0\\n for x in X:\\n fx = f(x)\\n g = g + fx**2\\n j[i] = 2 * fx * jac(x)\\n i = i + 1\\n return g, j\\n\\n opt = minimize(\\n lambda X: objFun(X, fun, jac),\\n X0,\\n method=\\\"L-BFGS-B\\\",\\n jac=True,\\n bounds=[bounds] * len(X0),\\n )\\n\\n X = opt.x\\n np.round(X, decimals=5)\\n return np.unique(X)\",\n \"def newton_sqrt(n, threshold):\\n\\tx = n\\n\\twhile True:\\n\\t\\troot = 0.5 * (x + n/x)\\n\\n\\t\\tif abs(root - x) < threshold:\\n\\t\\t\\treturn root\\n\\n\\t\\tx = root\",\n \"def nth_root_of_a(n, a):\\n return find_zero(lambda x: pow(x, n) - a, lambda x: n * pow(x, n-1))\",\n \"def _nth_root(value, n_root) -> float:\\r\\n\\r\\n root_value = 1 / float(n_root)\\r\\n return Decimal(value) ** Decimal(root_value)\",\n \"def findRoot(x, power, epsilon):\\n\\n if x < 0 and power % 2 == 0:\\n return None\\n\\n low = min(-1.0, x)\\n high = max(1.0, x)\\n ans = (high + low) / 2.0\\n while abs(ans**power - x) >= epsilon:\\n if ans ** power < x:\\n low = ans\\n else:\\n high = ans\\n ans = (high + low) / 2.0\\n return ans\",\n \"def newton(f, xinit, tol, N):\\n if f(xinit) < tol:\\n return xinit\\n else:\\n n = 1\\n while n < N:\\n xnew = xinit - (f(xinit) / derivative(f, xinit))\\n if abs(f(xnew)) < tol:\\n print('Root found. Number of iterations: ', n)\\n return xnew\\n break\\n else:\\n xinit = xnew\\n n = n + 1\\n else:\\n return 'Max iterations reached. No root found within chosen tolerance.'\",\n \"def test_find_all_roots(self):\\n\\n print(\\\"\\\\nFalse Position Method: All Roots\\\")\\n\\n # input\\n xmin = -1e2 # minimum x-value\\n xmax = 1e2 # maximum x-value\\n step = 1e0 # step-size of interval\\n et = 1e-6 # relative error threshold\\n\\n # function\\n roots, ic = FalsePosition.find_all_roots(self.fn, xmin, xmax, step, et)\\n\\n if len(roots) != 0:\\n print(\\\"\\\\tAll Roots: {X}\\\\n\\\\tIterations: {ic}\\\".format(X=roots, ic=ic))\\n else:\\n print(\\\"\\\\tNo root found with given initial values.\\\")\",\n \"def _nth_root(value, n_root):\\n return value ** (1 / n_root)\",\n \"def findRoot3(x,power,epsilon):\\n if x<0 and power%2 ==0:\\n return None\\n # when x is fractional,root is between 0 and 1\\n low = min(-1,x)\\n high = max(1,x)\\n ans = (high+low)/2.0\\n while abs(ans**power -x) > epsilon:\\n print ans\\n if ans**power <x:\\n low = ans \\n else:\\n high = ans\\n ans = (high+low)/2.0\\n return ans\",\n \"def root_1(a, b):\\n return -b / a\",\n \"def root(x, y, precision=20):\\n if type(x) is complex:\\n return x ** (1.0 / y)\\n if type(y) is complex:\\n return x ** (1.0 / y)\\n\\n try:\\n x = float(x)\\n except:\\n raise TypeError(\\\"{0} is not a number\\\".format(x))\\n try:\\n y = float(y)\\n except:\\n raise TypeError(\\\"{0} is not a number\\\".format(y))\\n if x < 0 and y % 2 == 0:\\n return root(abs(x), y) * 1j\\n elif x < 0:\\n return -root(abs(x), y)\\n elif y < 0:\\n return x ** (1.0 / y)\\n\\n if int(x) == x:\\n x = int(x)\\n if int(y) == y:\\n y = int(y)\\n # return x ** (1.0 / y)\\n\\n f = lambda n: n ** y - x\\n fprime = lambda n: y * n ** (y - 1)\\n\\n guess = 10\\n change = 1\\n\\n while change > 10 ** -precision:\\n guess2 = guess - f(guess) / fprime(guess)\\n change = abs(guess2 - guess)\\n guess = guess2\\n\\n return guess\",\n \"def custom_sqrt(n, p):\\n\\tstart = 0\\n\\tend = n\\n\\twhile start <= end:\\n\\t\\tmid = start + (end - start) // 2\\n\\t\\tif mid*mid == n:\\n\\t\\t\\treturn mid\\n\\t\\tif mid * mid > n:\\n\\t\\t\\tend = mid - 1\\n\\t\\tif mid * mid < n:\\n\\t\\t\\tstart = mid + 1\\n\\n\\troot = end\\n\\tincr = 0.1\\n\\tfor i in range(p):\\n\\t\\twhile (root*root <= n):\\n\\t\\t\\troot += incr\\n\\n\\t\\troot -= incr\\n\\t\\tincr /= 10\\n\\n\\treturn root\",\n \"def find_poly_root(poly, initial_guess = 0.0, limit = 0.00001, max_iterations = 1000):\\n # Calculate the polynomial derivatives\\n dpoly = polynomial.derivative(poly)\\n ddpoly = polynomial.derivative(dpoly)\\n # Closures !!!\\n f = lambda x: polynomial.eval(poly, x)\\n df = lambda x: polynomial.eval(dpoly, x)\\n ddf = lambda x: polynomial.eval(ddpoly, x)\\n # Call the generic root finder\\n return find_root(f, df, ddf, initial_guess, limit, max_iterations)\",\n \"def _root():\\n return 0\",\n \"def sp_solve ( fun , xmin , xmax , C = 0 , args = () ) :\\n ##\\n if iszero ( C ) :\\n return findroot ( fun , xmin , xmax , args = args )\\n ##\\n func = lambda x , *a : fun(x,*a)-C\\n return findroot ( func , xmin , xmax , args = args )\",\n \"def Stochastic_RootFinder(F, x0, a=.5, alpha=0.5, max_iter=20, xtol=.01, ValidInterval=[0.00001,100]):\\n\\n xp,n= ValidInterval[1]*2,1\\n n0 = int(max_iter/20)+1\\n xn = x0\\n displacement = 10 * xtol\\n\\n while displacement > xtol and n<max_iter:\\n an = a/ ( (n+n0)** alpha)\\n Fn=F(xn)\\n print('SRF step '+ str(n))\\n print('--------------------------')\\n print('current value of x is '+ str(xn))\\n print('current value of F is '+ str(Fn))\\n xnext = xn-an*np.asscalar(Fn)\\n \\n if xnext>ValidInterval[1]:\\n xnext = ValidInterval[1]\\n elif xnext<ValidInterval[0]:\\n xnext = ValidInterval[0]\\n \\n print('new x is ' + str(xnext))\\n\\n\\n\\n # shift and compute total displacement in the last 2 steps\\n displacement = np.ptp(np.array([xp,xn,xnext]))\\n print('displacement in the last 3 steps is ' + str(displacement))\\n xp=xn\\n xn=xnext\\n \\n\\n n=n+1\\n\\n return xnext,Fn\",\n \"def root_midpoint(self):\\n node1, node2, distance = self.find_middle_point()\\n self.root_nodes(node1, node2, distance)\",\n \"def compute_root(poly, x_0, epsilon):\\n guess = 0\\n while True:\\n poly_value = evaluate_poly(poly, x_0)\\n if -epsilon < poly_value < epsilon:\\n guess += 1\\n return x_0, guess\\n else:\\n poly_derivative = compute_deriv(poly)\\n deriv_value = evaluate_poly(poly_derivative, x_0)\\n x_0 = x_0 - poly_value / deriv_value\\n guess += 1\",\n \"def mpf_nthroot(s, n, prec, rnd=round_fast):\\n sign, man, exp, bc = s\\n if sign:\\n raise ComplexResult(\\\"nth root of a negative number\\\")\\n if not man:\\n if s == fnan:\\n return fnan\\n if s == fzero:\\n if n > 0:\\n return fzero\\n if n == 0:\\n return fone\\n return finf\\n # Infinity\\n if not n:\\n return fnan\\n if n < 0:\\n return fzero\\n return finf\\n flag_inverse = False\\n if n < 2:\\n if n == 0:\\n return fone\\n if n == 1:\\n return mpf_pos(s, prec, rnd)\\n if n == -1:\\n return mpf_div(fone, s, prec, rnd)\\n # n < 0\\n rnd = reciprocal_rnd[rnd]\\n flag_inverse = True\\n extra_inverse = 5\\n prec += extra_inverse\\n n = -n\\n if n > 20 and (n >= 20000 or prec < int(233 + 28.3 * n**0.62)):\\n prec2 = prec + 10\\n fn = from_int(n)\\n nth = mpf_rdiv_int(1, fn, prec2)\\n r = mpf_pow(s, nth, prec2, rnd)\\n s = normalize(r[0], r[1], r[2], r[3], prec, rnd)\\n if flag_inverse:\\n return mpf_div(fone, s, prec-extra_inverse, rnd)\\n else:\\n return s\\n # Convert to a fixed-point number with prec2 bits.\\n prec2 = prec + 2*n - (prec%n)\\n # a few tests indicate that\\n # for 10 < n < 10**4 a bit more precision is needed\\n if n > 10:\\n prec2 += prec2//10\\n prec2 = prec2 - prec2%n\\n # Mantissa may have more bits than we need. Trim it down.\\n shift = bc - prec2\\n # Adjust exponents to make prec2 and exp+shift multiples of n.\\n sign1 = 0\\n es = exp+shift\\n if es < 0:\\n sign1 = 1\\n es = -es\\n if sign1:\\n shift += es%n\\n else:\\n shift -= es%n\\n man = rshift(man, shift)\\n extra = 10\\n exp1 = ((exp+shift-(n-1)*prec2)//n) - extra\\n rnd_shift = 0\\n if flag_inverse:\\n if rnd == 'u' or rnd == 'c':\\n rnd_shift = 1\\n else:\\n if rnd == 'd' or rnd == 'f':\\n rnd_shift = 1\\n man = nthroot_fixed(man+rnd_shift, n, prec2, exp1)\\n s = from_man_exp(man, exp1, prec, rnd)\\n if flag_inverse:\\n return mpf_div(fone, s, prec-extra_inverse, rnd)\\n else:\\n return s\",\n \"def primitive_root(n):\\n if n == 2:\\n return 1\\n phi = euler_phi(n)\\n phi_divisors = factorize(phi)\\n for g in range(2, n + 1):\\n if gcd(g, n) != 1:\\n continue\\n for d, _ in phi_divisors:\\n if powmod(g, phi // d, n) == 1:\\n # g can not be a generator\\n break\\n else:\\n return g\\n\\n # generator not found\\n # Gauss theorem conditions did not met\\n return None\",\n \"def root(self, x):\\n assert ((x < self.n) & (x >= 0)), 'array index is out of bounds'\\n\\n while x != self.array[x]:\\n self.array[x] = self.array[self.array[x]]\\n x = self.array[x]\\n return x\",\n \"def find_roots(func, a, b, step=1e-3, roots=None):\\n if roots is None:\\n roots = []\\n if len(roots) > 100:\\n return roots\\n if func(a) == 0:\\n roots.append(a)\\n find_roots(func, a+1e-3, b, roots)\\n if func(b) == 0:\\n roots.append(b)\\n find_roots(func, a, b-1e-3, roots)\\n # n_steps = 1000\\n # step = 1./n_steps\\n n_steps = int(1./step)\\n win_size = b - a\\n for s in np.linspace(a+step, b-step, n_steps):\\n if func(s) * func(s+step*win_size) >= 0:\\n continue\\n r = brentq(func, s, s+step*win_size)\\n roots.append(r)\\n\\n return roots\",\n \"def square_root(value):\\n # Init\\n root = 1.0 # Provisional square root\\n difference = (root * root) - value # How far off is our provisional root\\n\\n ##--- Loop until the provisional root is close enough to the actual root ----###\\n while difference > 0.00000001 or difference < -0.00000001:\\n root = (root + (value / root)) / 2 # Compute new provisional root\\n difference = (root * root) - value # # How far off is our current approximation?\\n \\n return root\",\n \"def rootsearch(self, f, a, b, dx):\\n x1 = a \\n f1 = f(a)\\n x2 = a + dx\\n f2 = f(x2)\\n while f1*f2 > 0.0:\\n if x1 >= b: \\n return None,None\\n x1 = x2\\n f1 = f2\\n x2 = x1 + dx\\n f2 = f(x2)\\n else:\\n return x1,x2\",\n \"def bisect_root(V, y0, rng, Eleft, E0left, Eright, E0right, delta):\\n\\n E0mid = (E0left + E0right) / 2.0\\n func = schroed_system(E0mid, V)\\n [Emid, _] = one_step(func, y0, rng)\\n\\n # If we try to bisect too much, we can reach the machine's limit\\n # and one of the sides will be equal to the middle\\n if E0mid == E0left or E0mid == E0right:\\n return (E0mid, Emid)\\n\\n if abs(Emid) < delta:\\n return (E0mid, Emid)\\n\\n if sign_change(Eleft, Emid):\\n return bisect_root(V, y0, rng, Eleft, E0left, Emid, E0mid, delta)\\n elif sign_change(Emid, Eright):\\n return bisect_root(V, y0, rng, Emid, E0mid, Eright, E0right, delta)\\n else:\\n assert ValueError, \\\"there is no sign change in the values given\\\"\",\n \"def root_scalar(func, *args, **kwargs):\\n bracket = kwargs.get('bracket', None)\\n if bracket is None or len(bracket) != 2:\\n msg = (\\\"To run root_scalar, you have to provide a \\\"\\n \\\"`bracket` keyword argument with a sequence \\\"\\n \\\"of length 2.\\\")\\n raise ValueError(msg)\\n\\n try:\\n func(bracket[0], *args)\\n except Exception as e:\\n msg = (\\\"Before running scipy.integrate.root_scalar \\\"\\n \\\"I tried running the function you provided \\\"\\n \\\"with `bracket[0]`, \\\"\\n \\\"and I got the following error:\\\")\\n logger.error(msg)\\n raise (e)\\n\\n underride(kwargs, rtol=1e-4)\\n\\n res = spo.root_scalar(func, *args, **kwargs)\\n\\n if not res.converged:\\n msg = (\\\"scipy.optimize.root_scalar did not converge. \\\"\\n \\\"The message it returned is:\\\\n\\\" + res.flag)\\n raise ValueError(msg)\\n\\n return res\",\n \"def int_root(y, n):\\r\\n if y < 0: raise ValueError, \\\"y must not be negative\\\"\\r\\n if n < 1: raise ValueError, \\\"n must be positive\\\"\\r\\n if y in (0, 1): return y, True\\r\\n if n == 1: return y, True\\r\\n if n > y: return 1, False\\r\\n # Get initial estimate for Newton's method. Care must be taken to\\r\\n # avoid overflow\\r\\n try:\\r\\n guess = int(y ** (1./n)+0.5)\\r\\n except OverflowError:\\r\\n try:\\r\\n guess = int(math.exp(math.log(y)/n)+0.5)\\r\\n except OverflowError:\\r\\n guess = 1 << int(math.log(y, 2)/n)\\r\\n # Newton iteration\\r\\n xprev, x = -1, guess\\r\\n while 1:\\r\\n t = x**(n-1)\\r\\n xprev, x = x, x - (t*x-y)//(n*t)\\r\\n if abs(x - xprev) < 1:\\r\\n break\\r\\n # Compensate\\r\\n t = x**n\\r\\n while t > y:\\r\\n x -= 1\\r\\n t = x**n\\r\\n return x, t == y\",\n \"def sqrt(x):\\n return 0.0\",\n \"def test_inv_sphere_v3_root_find(self):\\n import itertools\\n\\n for k in (0, -1, 1, 1.75, 0.325, 1/7, -1.75, -0.325, -1/7):\\n s = space(fake_curvature=k) \\n for m in itertools.chain(\\n range(30),\\n range(31,3000,100),\\n map((1).__truediv__, range(3, 30, 2)),\\n ):\\n r = s.inv_sphere_v3(m)\\n self.assertTrue(r >= 0)\\n v = s.sphere_v3(r)\\n self.assertTrue(isclose(\\n m,\\n v\\n ))\",\n \"def find_roots(a: int, b: int, c: int):\\n if a == 0:\\n x = -c / b\\n print(f\\\"Solution is {x}\\\")\\n return x\\n\\n d = b ** 2 - (4 * a * c)\\n\\n if d < 0:\\n print(\\\"No solutions\\\")\\n return None\\n elif d == 0:\\n x = (-b + sqrt(d)) / (2 * a)\\n print(f\\\"Solution is {x}\\\")\\n return x\\n\\n x1 = (-b + sqrt(d)) / (2 * a)\\n x2 = (-b - sqrt(d)) / (2 * a)\\n\\n print(f\\\"Solutions are {x1} and {x2}\\\")\\n return x1, x2\",\n \"def root_finding_newton(fun, J, x, eps, max_iter, args):\\n F_value = fun(x, *args)\\n F_value_ = F_value.reshape((-1,1))\\n F_norm = np.linalg.norm(F_value, 2) # l2 norm of vector\\n iteration_counter = 0\\n while abs(F_norm) > eps and iteration_counter < max_iter:\\n delta = np.linalg.solve(J(x, args), -F_value_)\\n\\n for i in range(x.size): #wtf numba!?!?!\\n x[i] += delta[i,0]\\n\\n F_value = fun(x, *args)\\n F_value_ = F_value.reshape((-1,1))\\n F_norm = np.linalg.norm(F_value, 2)\\n iteration_counter += 1\\n\\n # Here, either a solution is found, or too many iterations\\n if abs(F_norm) > eps:\\n iteration_counter = -1\\n raise ValueError('Maximum iteration reached in newton root finding!')\\n return x, iteration_counter\",\n \"def compute_root(poly, x_0, epsilon):\\n # TO DO ...\\n diff = evaluate_poly(poly, x_0)\\n count = 0\\n\\n if abs(diff) > epsilon:\\n #Newton's Method Formula\\n x_1 = x_0 - (evaluate_poly(poly, x_0) / evaluate_poly(compute_deriv(poly), x_0))\\n #Recursion!\\n x_0 , count = compute_root(poly, x_1, epsilon)\\n else:\\n pass\\n\\n return x_0, count + 1\",\n \"def binary_search_find_root(number, min, max, accuracy, n):\\n if max <= min: # Can't find\\n return -1\\n\\n mid_val = (max + min)/2 # Returns a float.\\n if round(mid_val ** n, accuracy) == number:\\n return mid_val\\n elif mid_val ** n > number: # Need to make mid_val**2 less so it matches number.\\n return binary_search_find_root(number, min, mid_val, accuracy, n) # Look at values between min and mid, discard > mid point.\\n elif mid_val ** n < number:\\n return binary_search_find_root(number, mid_val, max, accuracy, n) # Discard values lower than mid to make number bigger.\",\n \"def test_j0_root():\\n import time\\n t1 = time.time()\\n\\n # Our version uses tabulated values up to 40, so a useful test of the extrapolation\\n # requires this to have more than 40 items.\\n vals1 = [ galsim.bessel.j0_root(s) for s in range(1,51) ]\\n print 'vals1 = ',vals1\\n\\n try:\\n import scipy.special\\n vals2 = scipy.special.jn_zeros(0,50)\\n print 'vals2 = ',vals2\\n np.testing.assert_almost_equal(\\n vals1, vals2, 8, \\\"bessel.j0_root disagrees with scipy.special.jn_zeros\\\")\\n except ImportError:\\n print 'Unable to import scipy. Skipping scipy tests of j0_root.'\\n\\n # These values are what scipy returns. Check against these, so not require scipy.\\n vals2 = [ 2.40482556, 5.52007811, 8.65372791, 11.79153444,\\n 14.93091771, 18.07106397, 21.21163663, 24.35247153,\\n 27.49347913, 30.63460647, 33.77582021, 36.91709835,\\n 40.05842576, 43.19979171, 46.34118837, 49.4826099 ,\\n 52.62405184, 55.76551076, 58.90698393, 62.04846919,\\n 65.1899648 , 68.33146933, 71.4729816 , 74.61450064,\\n 77.75602563, 80.89755587, 84.03909078, 87.18062984,\\n 90.32217264, 93.46371878, 96.60526795, 99.74681986,\\n 102.88837425, 106.02993092, 109.17148965, 112.31305028,\\n 115.45461265, 118.59617663, 121.73774209, 124.87930891,\\n 128.02087701, 131.16244628, 134.30401664, 137.44558802,\\n 140.58716035, 143.72873357, 146.87030763, 150.01188246,\\n 153.15345802, 156.29503427\\n ]\\n np.testing.assert_almost_equal(\\n vals1, vals2, 8, \\\"bessel.j0_root disagrees with reference values\\\")\\n\\n t2 = time.time()\\n print 'time for %s = %.2f'%(funcname(),t2-t1)\",\n \"def positiveRoot(a,b,c):\\n # The discriminant\\n disc = np.sqrt(b**2 - 4*a*c)\\n root1 = (-b + disc) / (2*a)\\n # This tells python to return the root1 value when the positive_root function is called\\n return root1\",\n \"def scale_root(self) -> int:\\r\\n ...\",\n \"def newton(f, x0, dx, eps=1e-10):\\n # Initialization\\n globvar.ncalls = 0\\n x = np.copy(x0)\\n n = len(x)\\n J = np.zeros((n, n), dtype='float64')\\n fx = f(x)\\n\\n # Begin root search\\n while True:\\n globvar.ncalls += 1\\n\\n # Fill the Jacobian matrix\\n for j in range(n):\\n x[j] += dx[j]\\n df = f(x) - fx\\n\\n for i in range(n):\\n J[i, j] = df[i] / dx[j]\\n\\n x[j] -= dx[j]\\n\\n # Decompose and solve using Given's rotations\\n decomp(J)\\n Dx = -fx\\n solve(J, Dx)\\n\\n # Begin backtracking linesearch\\n lamb = 2.0\\n while True: \\n lamb /= 2\\n y = x + Dx * lamb\\n fy = f(y)\\n\\n fynorm = np.linalg.norm(fy)\\n fxnorm = np.linalg.norm(fx)\\n\\n if (fynorm < (1 - lamb / 2) * fxnorm) or (lamb < (1 / 128.0)):\\n break\\n\\n # Save latest approximation\\n x = y\\n fx = fy\\n\\n Dxnorm = np.linalg.norm(Dx)\\n fxnorm = np.linalg.norm(fx)\\n dxnorm = np.linalg.norm(dx)\\n if Dxnorm < dxnorm or fxnorm < eps:\\n break\\n\\n return x\",\n \"def sqrt(n, one):\\n # Use floating point arithmetic to make an initial guess\\n floating_point_precision = 10**16\\n n_float = float((n * floating_point_precision) // one) / floating_point_precision\\n x = (int(floating_point_precision * math.sqrt(n_float)) * one) // floating_point_precision\\n n_one = n * one\\n while 1:\\n x_old = x\\n x = (x + n_one // x) // 2\\n if x == x_old:\\n break\\n return x\",\n \"def _square_rooted(x):\\n return sqrt(sum([(a * a) for a in x]))\",\n \"def test_find_root_multi(self):\\n\\n print(\\\"\\\\nNewton-Raphson Method: Multivariate\\\")\\n\\n # input\\n xi = 1 # initial value of first variable\\n yi = 1 # initial value of second variable\\n em = 1e-6 # error margin\\n imax = 1e3 # maximum number of iterations to consider\\n\\n # function\\n root, ic, msg = NewtonRaphson.find_root_multi([self.f, self.g], [[self.dfdx, self.dfdy],[self.dgdx, self.dgdy]], [xi, yi], em, imax)\\n\\n # output\\n if root != None:\\n print(\\\"\\\\tInitial value: {xi}\\\\n\\\\tRoot: {X}\\\\n\\\\tFirst function Value: {f}\\\\n\\\\tSecond function Value: {g}\\\\n\\\\tIterations: {ic}\\\".format(xi=xi, X=root, f=self.f(root), g=self.g(root), ic=ic))\\n else:\\n print(\\\"\\\\t{msg}.\\\".format(msg=msg))\",\n \"def test_cases():\\r\\n quadratic_roots(1,3,-21)\\r\\n quadratic_roots(2,-4,-6)\\r\\n quadratic_roots(1,4,-12)\\r\\n quadratic_roots(4,12,9)\\r\\n quadratic_roots(-2,-11,-21)\\r\\n quadratic_roots(4,1,4)\\r\\n quadratic_roots(1,1,0)\\r\\n quadratic_roots(1,0,-16)\\r\\n quadratic_roots(1,-14,-49)\\r\\n quadratic_roots(1,10,25)\",\n \"def test_find_root_uni(self):\\n\\n print(\\\"\\\\nNewton-Raphson Method: Univariate\\\")\\n\\n # input\\n xi = 1 # initial value\\n et = 1e-6 # relative error threshold\\n imax = 1e6 # maximum number of iterations to consider\\n\\n # function\\n root, ic, msg = NewtonRaphson.find_root_uni(self.fn, self.df, xi, et, imax)\\n\\n # output\\n if root != None:\\n print(\\\"\\\\tInitial value: {xi}\\\\n\\\\tRoot: {x}\\\\n\\\\tFunction Value: {fx}\\\\n\\\\tIterations: {ic}\\\".format(xi=xi, x=root, fx=self.fn(root), ic=ic))\\n else:\\n print(\\\"\\\\t{msg}.\\\".format(msg=msg))\",\n \"def findPrimitiveNthRoot(M, N):\\n roots = nthroot_mod(1, N, M, True)[1:] # find Nth root of unity\\n for root in roots: # find primitive Nth root of unity\\n is_primitive = True\\n for k in range(1, N):\\n if pow(root, k, M) == 1:\\n is_primitive = False\\n if is_primitive:\\n return root\\n return None\",\n \"def call_by_root(f, root=0):\\n MPI = is_running_mpi()\\n if MPI:\\n comm = MPI.COMM_WORLD\\n rank = comm.Get_rank()\\n if rank == root:\\n return f()\\n else:\\n return f()\",\n \"def solve(n=5000,C=-6*10**11,a=900,b=3):\\n coeffs = np.zeros(n+2)\\n coeffs[0] = a-b*n\\n coeffs[1] = b*(n+1) - a\\n coeffs[-3] = -C\\n coeffs[-2] = 2*C - a\\n coeffs[-1] = a+b-C\\n mp.dps = 27\\n roots = polyroots(coeffs)\\n for root in roots:\\n print root\",\n \"def root_3(a, b, c, d):\\n abc = a * b * c\\n bbb = b * b * b\\n aad = a * a * d\\n\\n dd = (18. * abc * d - 4. * bbb * d\\n + b * b * c * c - 4. * a * c * c * c\\n - 27. * aad * d)\\n d0 = b * b - 3. * a * c\\n\\n # second and third cubic unity roots (first is just 1)\\n cu2 = -0.5 + 0.86602540378443864676j\\n cu3 = -0.5 - 0.86602540378443864676j\\n\\n if not dd and not d0: # all real roots\\n x1 = x2 = x3 = -b / (3. * a)\\n elif not dd and d0: # double root, simple root\\n x1 = x2 = ((9. * a * d - b * c) / (2. * d0))\\n x3 = (4. * abc - 9. * aad - bbb) / (a * d0)\\n else:\\n d1 = 2. * bbb - 9. * abc\\n d1 = d1 + 27. * aad\\n\\n if not d0: cin = d1 + 0j # inner terms cancel\\n else: cin = (d1 - sqrt(-27.0 * a * a * dd)) / 2.\\n\\n cc = cin ** (1. / 3.)\\n p = (-1. / (3. * a))\\n\\n x1 = p * (b + cc + d0 / cc)\\n x2 = p * (b + cu2 * cc + d0 / (cu2 * cc))\\n x3 = p * (b + cu3 * cc + d0 / (cu3 * cc))\\n\\n return x1, x2, x3\",\n \"def root_finding_newton_previously(fun, J, x, eps, max_iter, args):\\n F_value = fun(x, args)\\n F_value_ = F_value.reshape((-1,1))\\n F_norm = np.linalg.norm(F_value, 2) # l2 norm of vector\\n iteration_counter = 0\\n while abs(F_norm) > eps and iteration_counter < max_iter:\\n delta = np.linalg.solve(J(x, args), -F_value)\\n x = x + delta\\n F_value = fun(x, args)\\n F_value_ = F_value.reshape((-1,1))\\n F_norm = np.linalg.norm(F_value, 2)\\n iteration_counter += 1\\n\\n # Here, either a solution is found, or too many iterations\\n if abs(F_norm) > eps:\\n iteration_counter = -1\\n raise ValueError('Maximum iteration reached in newton root finding!')\\n return x, iteration_counter\",\n \"def Newton(f, x0, tol, kmax, c=0.5, tao=1e-6, reg_const=1e-7):\\r\\n\\r\\n k = 1\\r\\n\\r\\n xk = x0.copy() # We don't want to change x0 from the outside scope\\r\\n\\r\\n # Cache for f(xk) in case the calculation is expensive\\r\\n # - Should save 2-3 function evaluations per outside loop iteration\\r\\n f_xk = f(xk)\\r\\n\\r\\n s = LA.norm(f_xk)**2\\r\\n\\r\\n while np.sqrt(s) > tol and k < kmax:\\r\\n # Build the Jacobian matrix approximation using Central Differences\\r\\n H = _CentralDifferencesJacobian(f, xk, tao)\\r\\n\\r\\n try:\\r\\n # Uses LAPACK _gesv to solve H*dk = -f(xk)\\r\\n dk = LA.solve(H, -f_xk)\\r\\n except LA.LinAlgError:\\r\\n # Most likely here because the above H is singular\\r\\n # Therefore we regularize by adding a small (1e-7) multiple of I:\\r\\n dk = LA.solve(H + reg_const*np.eye(xk.shape[0]), -f_xk)\\r\\n\\r\\n z = c*LA.norm(np.matmul(f_xk.T, H))*LA.norm(dk)\\r\\n\\r\\n # Solve the step size using the method by Stoer and Bulirsch\\r\\n j = 0\\r\\n L = LA.norm(f(xk + dk))**2\\r\\n R = s-z\\r\\n Lmin = L\\r\\n index = 0\\r\\n while L > R:\\r\\n j += 1\\r\\n L = LA.norm(f(xk + 2**(-j)*dk))**2\\r\\n R = s - 2**(-j)*z\\r\\n if L < Lmin:\\r\\n Lmin = L\\r\\n index = j\\r\\n\\r\\n # Update xk\\r\\n xk = xk + 2**(-index)*dk\\r\\n\\r\\n k += 1\\r\\n\\r\\n # Cache the new f(xk)\\r\\n f_xk = f(xk)\\r\\n\\r\\n s = LA.norm(f_xk)**2\\r\\n\\r\\n # If kmax gets exceeded, we can't trust the answer so issue a warning\\r\\n if k >= kmax:\\r\\n # For debugging purposes\\r\\n # print(\\\"k exceeded kmax, can't trust answer\\\")\\r\\n # return xk\\r\\n warnings.warn(\\\"kmax exceeded, consider raising it\\\", NonConvergenceWarning)\\r\\n\\r\\n # Otherwise, we stopped the above loop because we're within tolerance so the answer is good\\r\\n return xk, k\",\n \"def getRoots(self):\\n a, b, c = self.getCoefficients()[2], self.getCoefficients()[1], self.getCoefficients()[0]\\n delta = b**2 - 4*a*c\\n if delta >= 0:\\n roots = sorted([(-b - math.sqrt(delta))/(2*a), (-b + math.sqrt(delta))/(2*a)])\\n else:\\n roots = sorted([(-b - math.sqrt(-delta)*1j)/(2*a), (-b + math.sqrt(-delta)*1j)/(2*a)], key=lambda x: (x.real, x.imag))\\n return roots\",\n \"def root_finding_newton_previously(fun, J, x, eps, max_iter, args):\\n F_value = fun(x, args)\\n # F_value_ = F_value.reshape((-1, 1))\\n F_norm = np.linalg.norm(F_value, 2) # l2 norm of vector\\n iteration_counter = 0\\n while abs(F_norm) > eps and iteration_counter < max_iter:\\n delta = np.linalg.solve(J(x, args), -F_value)\\n x = x + delta\\n F_value = fun(x, args)\\n # F_value_ = F_value.reshape((-1, 1))\\n F_norm = np.linalg.norm(F_value, 2)\\n iteration_counter += 1\\n\\n # Here, either a solution is found, or too many iterations\\n if abs(F_norm) > eps:\\n iteration_counter = -1\\n raise ValueError(\\\"Maximum iteration reached in newton root finding!\\\")\\n return x, iteration_counter\",\n \"def test_cubic_roots(roots, a0, a1, a2, a3=None, tol=1.0e-12):\\n\\n N = len(a0)\\n for n in range(N):\\n c0 = a0[n]\\n c1 = a1[n]\\n c2 = a2[n]\\n c3 = a3[n]\\n\\n print(f\\\"Polynomial {n}: a = {(c0,c1,c2,c3)}\\\")\\n\\n rts = np.unique(roots[n])\\n rts = rts[~np.isnan(rts)]\\n\\n for x in rts:\\n f = c0 + c1 * x + c2 * x**2 + c3 * x**3\\n ok = np.abs(f) <= tol\\n\\n print(f\\\" root x = {x}: f(x) = {f} {'OK' if ok else 'FAILED'}\\\")\\n\\n if not ok:\\n raise Exception(\\\"NOT OK!\\\")\\n\\n if len(rts) == 0:\\n print(\\\" no real roots.\\\")\",\n \"def cube_root(val):\\n return val ** (1 / 3)\",\n \"def roots_binomial(f):\\n n = f.degree()\\n\\n a, b = f.nth(n), f.nth(0)\\n base = -cancel(b/a)\\n alpha = root(base, n)\\n\\n if alpha.is_number:\\n alpha = alpha.expand(complex=True)\\n\\n # define some parameters that will allow us to order the roots.\\n # If the domain is ZZ this is guaranteed to return roots sorted\\n # with reals before non-real roots and non-real sorted according\\n # to real part and imaginary part, e.g. -1, 1, -1 + I, 2 - I\\n neg = base.is_negative\\n even = n % 2 == 0\\n if neg:\\n if even == True and (base + 1).is_positive:\\n big = True\\n else:\\n big = False\\n\\n # get the indices in the right order so the computed\\n # roots will be sorted when the domain is ZZ\\n ks = []\\n imax = n//2\\n if even:\\n ks.append(imax)\\n imax -= 1\\n if not neg:\\n ks.append(0)\\n for i in range(imax, 0, -1):\\n if neg:\\n ks.extend([i, -i])\\n else:\\n ks.extend([-i, i])\\n if neg:\\n ks.append(0)\\n if big:\\n for i in range(0, len(ks), 2):\\n pair = ks[i: i + 2]\\n pair = list(reversed(pair))\\n\\n # compute the roots\\n roots, d = [], 2*I*pi/n\\n for k in ks:\\n zeta = exp(k*d).expand(complex=True)\\n roots.append((alpha*zeta).expand(power_base=False))\\n\\n return roots\",\n \"def refine_real_root(f, s, t, eps=None, steps=None, fast=False):\\n return dmp_refine_real_root(f.rep, s, t, f.lev, f.dom, eps=eps, steps=steps, fast=fast)\",\n \"def isPrimitiveNthRoot(M, N, beta):\\n return pow(beta, N, M) == 1 # modular(M).modExponent(beta, N) == 1\",\n \"def root_finding_newton(fun, J, x, eps, max_iter, args):\\n F_value = fun(x, args)\\n F_value_ = F_value.reshape((-1, 1))\\n F_norm = np.linalg.norm(F_value, 2) # l2 norm of vector\\n iteration_counter = 0\\n while abs(F_norm) > eps and iteration_counter < max_iter:\\n delta = np.linalg.solve(J(x, args), -F_value_)\\n\\n for i in range(x.size): # wtf numba!?!?!\\n x[i] += delta[i, 0]\\n\\n F_value = fun(x, args)\\n F_value_ = F_value.reshape((-1, 1))\\n F_norm = np.linalg.norm(F_value, 2)\\n iteration_counter += 1\\n\\n # Here, either a solution is found, or too many iterations\\n if abs(F_norm) > eps:\\n iteration_counter = -1\\n raise ValueError(\\\"Maximum iteration reached in newton root finding!\\\")\\n return x, iteration_counter\",\n \"def root_v0(self, v):\\n from scipy.integrate import quad\\n from scipy.special import erfc, erfcx\\n def integrand(u):\\n \\\"\\\"\\\"Integrand of self-consistency equation\\\"\\\"\\\"\\n return erfcx(-u)\\n #if u < -4.0:\\n #return -1. / np.sqrt(np.pi) * (1.0 / u - 1.0 / (2.0 * u**3) + \\n ##3.0 / (4.0 * u**5) - \\n ##15.0 / (8.0 * u**7))\\n #else:\\n #return np.exp(u**2) * (1. + erf(u))\\n\\n\\n mu_v = self.mu(v)\\n sd_v = self.sd(v)\\n low = (self.V_r - mu_v) / sd_v\\n up = (self.theta - mu_v) / sd_v\\n bounds = np.array([low, up]).T\\n\\n integral = np.array([quad(integrand, lower, upper)[0] for lower, upper in bounds])\\n root = - 1. / v + self.t_ref * 1e-3 \\\\\\n + np.sqrt(np.pi) * self.tau_m * 1e-3 * integral\\n return root\",\n \"def get_positive_roots(roots, A):\\n return roots[[np.any(utils.round(to_simple_root_basis(root, A)) > 0) for root in roots]]\",\n \"def sqrt(n):\\n pass\",\n \"def my_sqrt(x):\\n square_root = x**(0.5)\\n return square_root\",\n \"def mySqrt(self, x: int) -> int:\\n if x == 0:\\n return 0\\n d = 0.1\\n y = x / 2\\n z = (y + x/y) / 2\\n e = abs(z-y)\\n while e > d:\\n y = z\\n z = (y + x/y) / 2\\n e = abs(z - y)\\n return int(z)\",\n \"def __find_root(self, x):\\n index = x\\n while self.data[index] != index:\\n self.data[index] = self.data[self.data[index]]\\n index = self.data[index]\\n\\n return index\",\n \"def sqrt(number):\\n # return number if its 0 or 1 since 0*0=0 and 1*1=1\\n if number == 0 or number ==1:\\n return number\\n #square root negative number is not real number\\n if number < 0:\\n return None\\n\\n #using binary search, if s is square root of y that means 0<=s<=y. That is\\n #s*s = y. if for a given number x, x*x > y that means square root s should lie\\n #between 0<=s<x. if for a given number x, x*x < y that means square root s should lie\\n #between x<s<=y\\n start = 1\\n end = number\\n floor_sqrt = 0\\n iterate=0\\n while(start <= end):\\n iterate+=1\\n #start with middle elemment\\n mid = (start + end )//2\\n #check if mid * mid = number, then mid is answer\\n if mid * mid == number:\\n return mid\\n #if mid * mid < number, check between range (mid,end]\\n #also maintain mid value since, we have to return floor value\\n if mid * mid < number:\\n start = mid + 1\\n floor_sqrt = mid\\n #if mid * mid > number, check between range [start,end)\\n else:\\n end = mid - 1\\n return floor_sqrt\",\n \"def sqrt(a):\",\n \"def sqrt(x):\\n def good_enough(guess):\\n precision = 0.001\\n f = abs(guess ** 2 - x)\\n return (f < precision)\\n \\n def improve(guess):\\n return (guess + x/guess) / 2.0\\n \\n counter = 1\\n guess = 1\\n while not good_enough(guess) and counter <= 100:\\n guess = improve(guess)\\n counter += 1\\n assert counter <= 100,'100 iterations done and no good answer' \\n return int(guess)\",\n \"def newton_method(f, x, Ep, step):\\n\\n while True:\\n step = step + 1\\n # print(\\\"bnd1:=\\\",bnd1)\\n h = f(x) / derivative(f, x)\\n x = x - h\\n if (decide(abs(h) <= Ep)):\\n break\\n # print(\\\"Root in Approximation: \\\",bnd1)\\n return step\",\n \"def bisectionSqrt(x, epsilon = 0.01, low = None, high = None):\\n\\n\\tif low == None:\\n\\t\\tlow = 0.0\\n\\tif high == None:\\n\\t\\thigh = x\\n\\n\\tmidPoint = (high + low)/2.0\\n\\t# If the difference of the midpoint squared and x is\\n\\t# within the epsilon tolerance, OR is the midpoint is\\n\\t# greater than X, we stop and give answer\\n\\tif abs(midPoint**2 - x) < epsilon or midPoint > x:\\n\\t\\treturn midPoint\\n\\telse:\\n\\t\\t# Otherwise check if the midPoint is too big or small\\n\\t\\tif midPoint ** 2 < x:\\n\\t\\t\\t# If too small, recurse on the upper half\\n\\t\\t\\treturn bisectionSqrt(x,epsilon,midPoint,high)\\n\\t\\telse :\\n\\t\\t\\t# If too big, recurse on the lower half\\n\\t\\t\\treturn bisectionSqrt(x,epsilon,low,midPoint)\",\n \"def brents(f, x0, x1, max_iter=50, tolerance=1e-5):\\n \\n fx0 = f(x0)\\n fx1 = f(x1)\\n \\n assert (fx0 * fx1) <= 0, \\\"Root not bracketed\\\" \\n \\n if abs(fx0) < abs(fx1):\\n x0, x1 = x1, x0\\n fx0, fx1 = fx1, fx0\\n \\n x2, fx2 = x0, fx0\\n \\n d = np.nan\\n mflag = True\\n steps_taken = 0\\n \\n while steps_taken < max_iter and abs(x1-x0) > tolerance:\\n fx0 = f(x0)\\n fx1 = f(x1)\\n fx2 = f(x2)\\n \\n if fx0 != fx2 and fx1 != fx2:\\n L0 = (x0 * fx1 * fx2) / ((fx0 - fx1) * (fx0 - fx2))\\n L1 = (x1 * fx0 * fx2) / ((fx1 - fx0) * (fx1 - fx2))\\n L2 = (x2 * fx1 * fx0) / ((fx2 - fx0) * (fx2 - fx1))\\n new = L0 + L1 + L2\\n \\n else:\\n new = x1 - ( (fx1 * (x1 - x0)) / (fx1 - fx0) )\\n \\n tt1 = (new < ((3 * x0 + x1) / 4) or new > x1)\\n tt2 = (mflag == True and (abs(new - x1)) >= (abs(x1 - x2) / 2))\\n tt3 = (mflag == False and (abs(new - x1)) >= (abs(x2 - d) / 2))\\n tt4 = (mflag == True and (abs(x1 - x2)) < tolerance)\\n tt5 = (mflag == False and (abs(x2 - d)) < tolerance)\\n if (tt1 or\\n tt2 or\\n tt3 or\\n tt4 or\\n tt5):\\n new = (x0 + x1) / 2\\n mflag = True\\n \\n else:\\n mflag = False\\n \\n fnew = f(new)\\n d, x2 = x2, x1\\n \\n if (fx0 * fnew) < 0:\\n x1 = new\\n else:\\n x0 = new\\n \\n if abs(fx0) < abs(fx1):\\n x0, x1 = x1, x0\\n \\n steps_taken += 1\\n \\n return x1, steps_taken\",\n \"def root_2(a, b, c):\\n p1 = sqrt(b * b - 4. * a * c)\\n p2 = -2. * a\\n\\n x1 = (b - p1) / p2\\n x2 = (b + p1) / p2\\n\\n return x1, x2\",\n \"def test_fixed_point(testFunctions, tol, printFlag): \\n pass\",\n \"def test_fixed_point_system(testFunctions, tol, printFlag): \\n pass\",\n \"def test_root():\\n gnroot = 's51001'\\n root = germanet_data.get_synset_by_id(gnroot)\\n np.testing.assert_equal(root.is_root(), True)\\n np.testing.assert_equal(root.is_leaf(), False)\",\n \"def iroots(a, b, c):\\n discriminant = b*b-4*a*c\\n if discriminant == 0:\\n return -b/(2*a), None\\n else:\\n return (-b+isqrt(discriminant))/(2*a), (-b-isqrt(discriminant))/(2*a)\",\n \"def kth_root_modulo(a, k, n):\\n # x = g^y => x^k = (g^k)^y = a\\n # => y = log_{g^k} a (mod n)\\n g = primitive_root(n)\\n gk = powmod(g, k, n)\\n y = log_modulo(gk, a, n)\\n return powmod(g, y, n)\",\n \"def squareRootExhaustive(x, epsilon):\\n step = espilon**2\\n ans = 0.0\\n while abs(ans**2 - x) >= epsilon and ans*ans <= x: \\n # The ans*ans <= is there because of floating point arithmetic I think.\\n ans += step \\n if ans*ans > x:\\n raise ValueError\\n return ans\",\n \"def sqrt_newton(a):\\n\\tdef sqrt_update(x):\\n\\t\\treturn 0.5 * (x + a / x)\\n\\tdef sqrt_close(x):\\n\\t\\treturn approx_eq(x * x, a)\\n\\treturn improve(sqrt_update, sqrt_close)\",\n \"def bisect(f, x1, x2, tol=1.0e-9):\\n assert callable(f), \\\"User-supplied function must be callable.\\\"\\n assert x1 != x2, \\\"Bad initial range given to bracket.\\\"\\n f1 = f(x1)\\n f2 = f(x2)\\n assert f1 * f2 < 0.0, \\\"Range does not clearly bracket a root.\\\"\\n while abs(x2 - x1) > tol:\\n x_mid = 0.5*(x1+x2)\\n f_mid = f(x_mid)\\n if f_mid == 0.0:\\n return x_mid # found it\\n if f_mid * f1 < 0.0:\\n x2 = x_mid\\n f2 = f_mid\\n else:\\n x1 = x_mid\\n f1 = f_mid\\n return x_mid\",\n \"def square_root_with_newton_method(number, iterations):\\n # Inital value of g.\\n # Cycle based on the iterations number.\\n # Formula in the cycle.\\n # Return the rounded final result.\\n\\n if number <= 0 or iterations < 0:\\n return None\\n g = number * 0.5\\n for i in range(int(iterations)):\\n g2 = (g + number / g) * 0.5\\n g = g2\\n return round(g, 3)\",\n \"def arr_1(A):\\n copy = np.copy(A)\\n indices = np.array(range(copy.size)) #array of indices\\n roots = np.sqrt(indices)\\n return copy + roots\",\n \"def squareRootBi(x, epsilon):\\n low = 0.0\\n high = max(1.0, x)\\n ans = (high + low)/2.0\\n while abs(ans**2 - x) >= epsilon:\\n # Where as here the ans*ans <= x isn't required because every value in\\n # the bisection search is by nature some factor of 2. Clever. \\n if ans**2 < x:\\n low = ans\\n else:\\n high = ans\\n ans = (high + low) / 2.0\\n return ans\",\n \"def _realroots_quadratic(a1, a0):\\n D = a1*a1 - 4*a0\\n if D < 0:\\n return []\\n SD = math.sqrt(D)\\n return [0.5 * (-a1 + SD), 0.5 * (-a1 - SD)]\",\n \"def is_root(self, n):\\n return n == self._root\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.73860395","0.70872056","0.6967801","0.69340694","0.69075763","0.68714964","0.6838874","0.6783198","0.67171526","0.6622454","0.6563255","0.65425867","0.64857024","0.64850307","0.64433384","0.64288294","0.6416696","0.64105165","0.64094615","0.6380394","0.63778025","0.63749564","0.63456887","0.6343153","0.6338011","0.63364714","0.6325611","0.6322467","0.62838185","0.62001604","0.6172485","0.61551714","0.61448133","0.6140084","0.6096052","0.6067267","0.60344744","0.5994176","0.5986016","0.5973045","0.59706247","0.5970439","0.5961545","0.5911555","0.59090376","0.58946604","0.5871458","0.58610547","0.5824892","0.58239466","0.5814648","0.5809791","0.5805601","0.5798754","0.5795465","0.5740271","0.5734714","0.57247216","0.5722637","0.5719849","0.5716117","0.56945264","0.56699353","0.5665134","0.563869","0.5624454","0.5622325","0.5614928","0.5592093","0.5587911","0.55821896","0.5577653","0.55544853","0.55493796","0.5541214","0.5537602","0.55374455","0.55338484","0.5505303","0.5492837","0.54810244","0.5480696","0.5462466","0.54592866","0.54498506","0.543565","0.54104364","0.5409058","0.5400818","0.5394801","0.53863305","0.5376449","0.5371044","0.5356991","0.535395","0.53471804","0.5332003","0.533167","0.53277767","0.5325562"],"string":"[\n \"0.73860395\",\n \"0.70872056\",\n \"0.6967801\",\n \"0.69340694\",\n \"0.69075763\",\n \"0.68714964\",\n \"0.6838874\",\n \"0.6783198\",\n \"0.67171526\",\n \"0.6622454\",\n \"0.6563255\",\n \"0.65425867\",\n \"0.64857024\",\n \"0.64850307\",\n \"0.64433384\",\n \"0.64288294\",\n \"0.6416696\",\n \"0.64105165\",\n \"0.64094615\",\n \"0.6380394\",\n \"0.63778025\",\n \"0.63749564\",\n \"0.63456887\",\n \"0.6343153\",\n \"0.6338011\",\n \"0.63364714\",\n \"0.6325611\",\n \"0.6322467\",\n \"0.62838185\",\n \"0.62001604\",\n \"0.6172485\",\n \"0.61551714\",\n \"0.61448133\",\n \"0.6140084\",\n \"0.6096052\",\n \"0.6067267\",\n \"0.60344744\",\n \"0.5994176\",\n \"0.5986016\",\n \"0.5973045\",\n \"0.59706247\",\n \"0.5970439\",\n \"0.5961545\",\n \"0.5911555\",\n \"0.59090376\",\n \"0.58946604\",\n \"0.5871458\",\n \"0.58610547\",\n \"0.5824892\",\n \"0.58239466\",\n \"0.5814648\",\n \"0.5809791\",\n \"0.5805601\",\n \"0.5798754\",\n \"0.5795465\",\n \"0.5740271\",\n \"0.5734714\",\n \"0.57247216\",\n \"0.5722637\",\n \"0.5719849\",\n \"0.5716117\",\n \"0.56945264\",\n \"0.56699353\",\n \"0.5665134\",\n \"0.563869\",\n \"0.5624454\",\n \"0.5622325\",\n \"0.5614928\",\n \"0.5592093\",\n \"0.5587911\",\n \"0.55821896\",\n \"0.5577653\",\n \"0.55544853\",\n \"0.55493796\",\n \"0.5541214\",\n \"0.5537602\",\n \"0.55374455\",\n \"0.55338484\",\n \"0.5505303\",\n \"0.5492837\",\n \"0.54810244\",\n \"0.5480696\",\n \"0.5462466\",\n \"0.54592866\",\n \"0.54498506\",\n \"0.543565\",\n \"0.54104364\",\n \"0.5409058\",\n \"0.5400818\",\n \"0.5394801\",\n \"0.53863305\",\n \"0.5376449\",\n \"0.5371044\",\n \"0.5356991\",\n \"0.535395\",\n \"0.53471804\",\n \"0.5332003\",\n \"0.533167\",\n \"0.53277767\",\n \"0.5325562\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.65467143"},"document_rank":{"kind":"string","value":"11"}}},{"rowIdx":88569,"cells":{"query":{"kind":"string","value":"Generate the save path for an image. If a modifier string is provided, this is added between the existing name and the extension. e.g. fname=\"moon.jpeg\" modstirng=\"cropped\" > \"moon_cropped.jpeg\". This is then joined with the output directory. If no modiifer, just returns joined path of outdir and fname."},"document":{"kind":"string","value":"def genSavePath(outdir, fname, modstring=None):\n\n if modstring:\n base,ext = os.path.splitext(fname)\n fname = f\"{base}_{modstring}.{ext}\"\n \n writepath = os.path.join(outdir, fname)\n return writepath"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def output_filename(self, modifier):\n fs = self._filesystem\n output_filename = fs.join(self._root_output_dir, self._test_name)\n return fs.splitext(output_filename)[0] + modifier","def name_final_path(out_img_folder):\n if out_img_folder == None:\n return \"./.out_hidden_images\"\n else:\n return out_img_folder","def get_save_path(op: Save, calculation: \"FileCalculation\") -> str:\n from PartSegCore.analysis.save_functions import save_dict\n\n extension = save_dict[op.algorithm].get_default_extension()\n rel_path = os.path.relpath(calculation.file_path, calculation.base_prefix)\n rel_path = os.path.splitext(rel_path)[0]\n if op.directory:\n file_name = os.path.basename(rel_path)\n base_rel_path = os.path.dirname(rel_path)\n return os.path.join(calculation.result_prefix, base_rel_path, op.directory, file_name + op.suffix + extension)\n return os.path.join(calculation.result_prefix, rel_path + op.suffix + extension)","def get_out_file_path(self):\n dir_path = self._get_output_dir()\n self._check_make_dirs(dir_path)\n return join(dir_path, self.FOCUSED_IMAGE_NAME)","def path_to_name(img):\n\n return os.path.dirname(img) + '_' + os.path.basename(img)","def get_path(dir_name, file_format, args):\n fname = \"{exp}-excl-{excl}\".format(exp=args.exp,\n excl=args.feature_set)\n path = os.path.join(SAVE_ROOT, dir_name, args.rbp,\n fname + file_format)\n\n # make the directory if it doesn't exist_ok\n os.makedirs(os.path.dirname(path), exist_ok=True)\n\n return path","def construct_image_savepath(self, date_string, coords_string, image_type=\"RGB\"):\n\n if \"SUB\" in image_type:\n output_location = os.path.join(self.output_location, date_string, \"SPLIT\")\n else:\n output_location = os.path.join(self.output_location, date_string, \"PROCESSED\")\n # filename is the date, coordinates, and image type\n filename = f'{date_string}_{coords_string}_{image_type}.png'\n\n # full path is dir + filename\n full_path = os.path.join(output_location, filename)\n\n return full_path","def _output_path(name):\n output = Path(\"../Analysis Results/\").joinpath(str(date.today()))\n output.mkdir(parents=True, exist_ok=True)\n return output.joinpath(f\"{name}.png\")","def get_file_full_path(self):\n return self.save_dir + os.sep + self.save_file_without_ext + self.save_file_ext","def img_save(self):\n file_name, extension = return_folder_file_extension(self.img_name)[1:]\n image_name_save = \"%s_D=%s_Rs=%s_size=%s_offset=%i%s\" % (file_name, self.D, self.Rs, self.axe_X, self.offset_X+self.offset_X2, extension)\n\n if self.img2 is not None:\n self.img2.save(image_name_save)\n print(\"Saved \"+image_name_save)\n else:\n print(\"No image to save\")","def name_to_path(img, origin):\n\n orig_file_parts = img.split('_')[1:]\n\n category = orig_file_parts[-3]\n filename = orig_file_parts[-2]+'_'+orig_file_parts[-1]\n\n orig_file = os.path.sep.join([origin, category])\n orig_file = os.path.sep.join([orig_file, filename])\n\n return orig_file","def output_file_name_maker(args):\n log.debug(\"Entering output_file_name_maker()\")\n path = os.getcwd() + '/out_files/'\n if not os.path.isdir(path):\n os.mkdir(path)\n\n if args.output is None:\n out_file_name = path + args.input[:-4] + '_' + args.type + '_' + args.layer\n else:\n out_file_name = path + args.output\n\n log.debug(\"Exiting output_file_name_maker()\")\n return out_file_name","def _out(self, *args):\n suffix = '_'.join(map(str, args))\n return os.path.join(self._out_folder, suffix )","def build_output_file_path(dir, role, id):\n clean_dir = dir.rstrip(\"/\")\n punct = string.punctuation\n junk = punct + \" \"\n trantab = string.maketrans(junk, \"_________________________________\")\n clean_role = role.encode(\"ascii\", \"replace\").strip(junk).translate(trantab)\n path = (clean_dir + \"/\" + clean_version + \"-\" + clean_role + \"-\" +\n str(id) + \".json\")\n return re.sub(r'(_)\\1+', r'\\1', path)","def getImgPath(outputDir, cameraID, timestamp, cropCoords=None, diffMinutes=0):\n timeStr = datetime.datetime.fromtimestamp(timestamp).isoformat()\n timeStr = timeStr.replace(':', ';') # make windows happy\n imgName = '__'.join([cameraID, timeStr])\n if diffMinutes:\n imgName += ('_Diff%d' % diffMinutes)\n if cropCoords:\n imgName += '_Crop_' + 'x'.join(list(map(lambda x: str(x), cropCoords)))\n imgPath = os.path.join(outputDir, imgName + '.jpg')\n return imgPath","def out_filename(self, filetype, dir, format='old'):\n filename = self.filename(filetype=filetype, format=format)\n return Path(dir) / filename","def __diff_filename(self):\n diff_dir = os.path.join(self.__folder, Reference.DIFF_OUT)\n if not os.path.exists(diff_dir):\n os.makedirs(diff_dir)\n return os.path.join(diff_dir, self.__name +'.jpg')","def imgOutputPath(self, newpath):\n newimg = self.imagePath().replace(self.home, newpath)\n return newimg","def generate_filename(\n self, directory=os.getcwd(), prefix=\"tile\", format=\"png\", path=True\n ):\n filename = prefix + \"_{col:02d}_{row:02d}.{ext}\".format(\n col=self.column, row=self.row, ext=format.lower().replace(\"jpeg\", \"jpg\")\n )\n if not path:\n return filename\n return os.path.join(directory, filename)","def saveImage(self, fileName=\"mandelbrot.frac\"):\n # Save the image as a PNG\n if fileName == \"\":\n fileName = \"mandelbrot.frac\"\n directories = fileName.split(\"/\")\n for n in directories:\n if \".frac\" in n:\n name = n.rsplit(\".\", 1)[0]\n self.img.write(f\"{name}.png\")\n print(f\"Wrote image {name}.png\")","def create_filename (self):\n\t\tassert self.__patient_name and self.__location_name, \"New filename could not be determined, one or more needed arguments is empty!\"\n\t\t_patient_name = self.__patient_name.split(' ')\n\t\t_patient_name.reverse()\n\t\t\n\t\treturn os.path.join(os.path.dirname(self.file._path), \"%s MR %s%s\" % (self.__location_name, ', '.join(_patient_name).upper(), self._file.extension))","def photo_directory_path(instance, filename):\n return 'gallery/photos/{0}/{1}'.format(instance.photo_name, filename)","def write(self, name=None, ext=None, directory=None):\n delim = \"_\"\n if name is None:\n # extra delimeter added to separate edits from the extension\n name = delim.join(self.edits) + delim\n if directory is not None:\n name = os.path.join(directory, name)\n if ext is None:\n ext = self.ext\n\n return cv2.imwrite(name + ext, self.img)","def _make_path(self) -> str:\r\n path_ = Path(path.join(conf.instance.output_path, self.path_prefix, self.name))\r\n if self.is_identifier_in_paths:\r\n path_ = path_ / self.identifier\r\n return path_","def get_filepath(image):\r\n extension = (len(image.split('/')[-1:][0]))\r\n return image[:-extension]","def student_image_file_path(instance, filename):\n ext = filename.split('.')[-1] # [-1] returns the last item from a list\n filename = f'{uuid.uuid4()}.{ext}'\n\n return os.path.join('uploads/students/', filename)","def outputPath():\n scenePath = bpy.data.filepath\n # If the scene hasn't been saved yet the path is empty.\n # Returning an empty path prompts the user for saving the scene.\n if not scenePath:\n return\n renderPath = os.path.join(os.path.dirname(scenePath), \"{}_thumbs\".format(NAME))\n return renderPath","def set_image_out_path(self, image_path):\n i = image_path.rfind('/')\n self.image_out_path = image_path[:i+1] + \"out/\" + image_path[i+1:]","def get_savename(outdir, plot_name, extension):\n save_name = '.'.join([plot_name, extension])\n save_name = '/'.join([outdir, save_name])\n return save_name","def recipe_image_file_path(instance, filename):\n # Return the extention of the file name\n ext = filename.split('.')[-1]\n # Create a new name using the uuid\n filename = f'{uuid.uuid4()}.{ext}'\n\n # A relable method that allowed us to join 2 strings into a vaild path\n return os.path.join('uploads/recipe/', filename)","def get_image_filename(self, filename):\n path = 'images/{folder}/{filename}'.format(\n folder=self.folder,\n filename=filename\n )\n return path","def process_image(self, decorator):\r\n savefig_dir = self.savefig_dir\r\n source_dir = self.source_dir\r\n saveargs = decorator.split(' ')\r\n filename = saveargs[1]\r\n # insert relative path to image file in source\r\n outfile = os.path.relpath(os.path.join(savefig_dir,filename),\r\n source_dir)\r\n\r\n imagerows = ['.. image:: %s'%outfile]\r\n\r\n for kwarg in saveargs[2:]:\r\n arg, val = kwarg.split('=')\r\n arg = arg.strip()\r\n val = val.strip()\r\n imagerows.append(' :%s: %s'%(arg, val))\r\n\r\n image_file = os.path.basename(outfile) # only return file name\r\n image_directive = '\\n'.join(imagerows)\r\n return image_file, image_directive","def _make_output_path(self, filename):\n return os.path.join(self._output_directory, filename)","def makefilename(self):\n fp= (pathlib.Path(self.vr_folder).expanduser()/(time.strftime(self.vr_filename))).with_suffix('')\n fp.parent.mkdir(parents=True, exist_ok=True)\n print('files setup', str(fp))\n return fp","def generate_file_filename(instance, filename):\n return _generate_filename(instance, filename, 'photos')","def get_photo_path(self, filename):\n univ = \"abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890\"\n name = \"\".join([random.choice(univ) for i in xrange(20)])\n root, ext = os.path.splitext(filename)\n\n return u'photos/%s' % (name + ext)","def imagefile(self):\n if self.__filetype==\"flatWarp\" :\n ext = \".fw\"\n elif self.__filetype==\"camWarp\" :\n ext = \".camWarp\"\n elif self.__filetype==\"raw\" :\n ext = \".Data.dat\"\n else :\n raise ValueError(f\"requested file type {self.__filetype} not recognized\")\n\n return self.__imagefolder/self.file.replace(\".im3\", ext)","def opath ( dir_name, file_name = None ):\n if file_name:\n return os.path.join(output_path, dir_name, file_name)\n return os.path.join(output_path, dir_name)","def _app_outfile_path(path, app_name, extension):\n filename = '%s.%s' % (app_name, extension)\n return os.path.join(path, filename)","def _make_save_path(self, save_path, save_name):\n if save_name.endswith('.txt'):\n path = os.path.join(save_path, save_name)\n else:\n self.save_name = save_name+'.txt'\n path = os.path.join(save_path, save_name)\n return path","def _gen_image_filename(instance, filename):\n # First, store the original filename in the model\n instance.original_filename = filename\n\n return _unique_path(instance.owner.pk, filename)","def make_path(self, basename):\n return os.path.join(self.output_folder, basename.format(self.sample_name))","def build_out_path(d):\n assert \"output_dir\" in d, \"Dictionary must have output dir\"\n\n path = d.pop(\"output_dir\")\n\n weights_path = path + \"weights_\"\n log_path = path + \"log_\"\n train_data_path = path + \"train_data_\"\n\n # Sort dictionary for consistency\n odict = OrderedDict(sorted(d.items(), key=lambda t: t[0]))\n\n for key, val in zip(odict.keys(), odict.values()):\n if key not in (\"input_dir\", \"loss_type\", \"typical_epochs\", \"num_epochs\"):\n text = str(key) + \"_\" + str(val) + \"_\"\n weights_path += text\n log_path += text\n train_data_path += text\n\n weights_path += \".pth\"\n log_path += \".log\"\n train_data_path += \".pkl\"\n\n return weights_path, log_path, train_data_path","def make_img_name(file_ext='.png'):\r\n fn = []\r\n # format seqs and write out to temp file\r\n for i in range(0, 30):\r\n fn.append(choice(ALPHABET))\r\n return ''.join(fn) + file_ext","def save_image(image: FileStorage):\n base_path = Path(current_app.config[\"USER_DIR\"]) / \"images\"\n fileparts = image.filename.rsplit(\".\", 1)\n sanitized_filename = secure_filename(fileparts[0])\n dest_path = base_path / f\"{sanitized_filename}.{fileparts[1]}\"\n i = 1\n while dest_path.exists():\n dest_path = base_path / f\"{sanitized_filename}-{i}.{fileparts[1]}\"\n i += 1\n image.save(str(dest_path))\n return dest_path.parts[-1]","def _get_filepath(self, name=None, use_timestamp=True):\n current_time = str(int(time.time()))\n if not name and not use_timestamp:\n raise Exception(\"Name or timestamp is required\")\n if name:\n self.fname = \"%s\" % name\n current_time = \"_%s\" % current_time\n if use_timestamp:\n self.fname = \"%s%s\" % (self.fname, current_time)\n if len(self.fname) > 0:\n self.fname = \"%s/%s.jpg\" % (self.picture_directory, self.fname)\n return self.fname","def doctor_image_upload_path(instance, file_path):\n file_name, file_ext = get_file_name_ext(file_path)\n random_file_name = generate_random_text(file_name)\n final_file_name = f\"profile_photos/{random_file_name}\"\n return final_file_name","def get_full_path(file_extension=True) -> str:\n return get_directory() + \"/\" + get_filename(file_extension=file_extension)","def savestring(self , name , filenum , samedir = False , prefix = True):\n if prefix == True:\n if samedir:\n \"\"\"\n Making use of some implementation detail of savefig, if we read in files from all different directory's, the prefixes contain the path of those files relative to the rootdirectory. So if you save the file we save it with first the prefix and then the name , so the figures end up in the same directory as the files. If you don't want this behaviour we need to remove the / in the prefixs so fig.savefig will not recognize it as a path so all the figures end up in the current working directory. Remark we only remove the / because if all the figures end up in same dir we need the path information to distinguish them.\n \"\"\"\n self.prefix = [pre.translate(None , '/.') for pre in self.prefix]\n return '%s%s%d.png' %(self.prefix[filenum], name, filenum )\n #return '%s%s.png' %(self.prefix[filenum], name)\n else:\n return '%s%d.png' %(name, filenum )","def get_path(\n layer: LayerType,\n batch_size: int,\n num_runs: int,\n num_repeats: int,\n gsm_mode: str,\n random_seed: Optional[int] = None,\n forward_only: bool = False,\n root: str = \"./results/raw/\",\n suffix: str = \"\",\n) -> str:\n pickle_name = f\"{layer}_mode_{gsm_mode}_bs_{batch_size}_runs_{num_runs}_repeats_{num_repeats}_seed_{random_seed}\"\n if forward_only:\n pickle_name += \"_forward_only\"\n\n if len(suffix) and not suffix.startswith(\"_\"):\n suffix = f\"_{suffix}\"\n\n return f\"{root}{pickle_name}{suffix}.pkl\"","def make_image_path(raw_img, input_base, base_path):\n path = os.path.dirname(raw_img)\n relpath = os.path.relpath(path, input_base)\n if relpath == '.':\n dest_folder = base_path\n else:\n dest_folder = os.path.join(base_path, relpath)\n return os.path.normpath(dest_folder)\n # return dest_folder","def gen_folder(base, e, f, a, k):\n \n return base + 'eps_' + str(e) + '_fp_' + str(f) + \\\n '_areak_' + str(a) + '_kappa_' + str(k)","def buildPath(dir, file_name, ext, description = None):\n\tpath = os.path.join(dir, file_name)\n\tbase, _ = os.path.splitext(path)\n\tif not description == None:\n\t\tbase = base + '.' + description\n\treturn base + ext","def build_portrait_filename(self, key):\n\t\tname = self.source.get_name()\n\t\tif name == None:\n\t\t\treturn None\n\t\treturn \"portrait_\" + name + \"_\" + key + \".bmp\"","def create_savename(self):\n \n savename = self.config.get('grid', 'dir') + self.fname.split('/')[-1]\n newsuffix = '_gridded_%ix%ix%i.nc' % (self.nx, self.ny, self.nz)\n savename = savename.replace('.nc', newsuffix)\n \n return savename","def save_photo():\n save_name = filedialog.asksaveasfilename(initialdir=\"10.APOD Viewer/\", title=\"Save Image\", filetype=((\"JPEG\", \"*.jpg\"), (\"All Files\", \"*.*\")))\n img.save(save_name + \".jpg\")","def get_output_filename(self, gzip=False):\n if self.mode == 'light':\n suffix = '-light'\n else:\n suffix = ''\n\n destination = self.destination\n extension = 'fits'\n if gzip:\n destination += '-compressed'\n extension += '.gz'\n return os.path.join(destination,\n 'iphas-dr2-{0}{1}.{2}'.format(\n self.get_partname(),\n suffix,\n extension))","def build_file_path(dir_name, file_name, ext):\n return os.path.join(dir_name, os.path.extsep.join((file_name, ext)))","def _getSavePath(self):\n path, filename = os.path.split(self.path)\n savePath = os.path.join(path, os.path.splitext(filename)[0])\n return savePath","def make_path(self):\n folders = [\n f\"{self.save_path}{self.name}/json/\",\n f\"{self.save_path}{self.name}/images/\",\n ]\n if hasattr(self, \"masks\"):\n folders.append(f\"{self.save_path}{self.name}/masks/\")\n for folder in folders:\n if not os.path.exists(folder):\n os.makedirs(folder)","def generate_filename(extension, with_path=True, base_folder=None):\n name = get_md5(str(uuid4()))\n # if not extension:\n # extension = get_file_extension()\n if base_folder is not None:\n base_folder = \"%s/\" % base_folder.rstrip(\"/\")\n else:\n base_folder = \"\"\n\n if with_path:\n return \"%s%s/%s/%s/%s.%s\" % (base_folder, name[0], name[1], name[2], name, extension)\n else:\n return \"%s%s.%s\" % (base_folder, name, extension)","def get_outfolder():\n \n valid = False\n while not valid:\n fname = raw_input(\"Please enter directory to save images. \")\n if not os.path.exists(fname):\n os.makedirs(fname)\n #Check to see if the file is there.\n if os.path.exists(fname): \n valid = True\n #File is not there, check to see if write privileges can be given\n #to created file.\n elif os.access(os.path.dirname(fname), os.W_OK):\n valid = True\n else:\n print \"Invalid local path, please try again.\"\n return fname","def roompost_image_file_path(instance, filename):\n ext = filename.split('.')[-1]\n filename = f'{uuid.uuid4()}.{ext}'\n\n return os.path.join('uploads/post/', filename)","def GetOutputFilename(fname):\n return os.path.join(outdir, fname)","def recipe_image_file_path(instance, filename):\n\n ext = filename.split('.')[-1]\n filename = f'{uuid.uuid4()}.{ext}'\n\n return os.path.join('uploads/recipe/', filename)","def get_filename(\n self,\n name,\n ext=\".npz\",\n map_tag=None,\n iter_index=None,\n extra_tag=None,\n bp_opts=False,\n ):\n if self.output_root is None:\n return None\n\n if bp_opts:\n if self.ensemble_mean:\n name = \"{}_mean\".format(name)\n elif self.ensemble_median:\n name = \"{}_median\".format(name)\n elif self.sim_index is not None:\n name = \"{}_sim{:04d}\".format(name, self.sim_index)\n if self.signal_type_sim:\n name = \"{}_{}\".format(name, self.signal_type_sim)\n if self.noise_type_sim:\n name = \"{}_{}\".format(name, self.noise_type_sim)\n else:\n if self.data_type != \"raw\":\n name = \"{}_{}\".format(name, self.data_type)\n if getattr(self, \"template_cleaned\", False):\n name = \"{}_clean_{}\".format(name, self.template_type)\n if getattr(self, \"planck_sub\", False):\n name = \"{}_planck_sub\".format(name)\n if self.weighted_bins:\n name = \"{}_wbins\".format(name)\n if getattr(self, \"return_cls\", False):\n name = \"{}_cl\".format(name)\n\n if map_tag is not None:\n name = \"{}_map_{}\".format(name, map_tag)\n if iter_index is not None:\n name = \"{}_iter{:03d}\".format(name, iter_index)\n if extra_tag is not None:\n name = \"{}_{}\".format(name, extra_tag)\n\n tag = \"_{}\".format(self.output_tag) if self.output_tag else \"\"\n if not ext.startswith(\".\"):\n ext = \".{}\".format(ext)\n return os.path.join(self.output_root, \"{}{}{}\".format(name, tag, ext))","def return_folder_file_extension(img_name):\n *folder, file = img_name.replace(\"\\\\\", \"/\").split(\"/\")\n\n if len(folder) != 0:\n folder = folder[0]\n\n file, extension = file.split(\".\")\n\n return folder, file, \".\"+extension","def save_step_2(imgs, match_list, output_path=\"./output/step2\"):\n # ... your code here ...\n for i in range(len(imgs)):\n name1,tail1 = str.split(filenames[match_list[i][0]],\".\")\n name2,tail2 = str.split(filenames[match_list[i][2]],\".\")\n cv2.imwrite(output_path+\"/\"+name1+\"_\"+str(match_list[i][1])+\"_\"+name2+\"_\"+str(match_list[i][3])+\"_\"+str(match_list[i][4])+\".jpg\", imgs[i])","def file_path(instance, filename):\n hashcode = hash(filename)\n mask = 255 # bitmask\n # use the first and second bytes of the hash code represented as\n # zero-padded hex numbers as directory names\n # provides 256 * 256 = 65536 of possible directory combinations\n dir1 = \"{:0>2x}\".format(hashcode & mask)\n dir2 = \"{:0>2x}\".format((hashcode >> 8) & mask)\n # Galaxy doesn't process names with parentheses in them\n filename = re.sub('[()]', '_', filename)\n return os.path.join(dir1, dir2, filename)","def get_path_to_image():\n file_types = [\n (\"JPEG Image\", '*.jpeg; *jpg'),\n (\"PNG Image\", '*.png'),\n (\"BPM Image\", '*.bmp'),\n (\"Netpbm Image\", '*.ppm; *.pgm; *.pbm; *pnm')\n ]\n\n GlobalVar.file_path = filedialog.askopenfilename(filetypes=file_types)\n GlobalVar.name_original = GlobalVar.file_path.split('/')[-1]\n GlobalVar.is_open_image = True\n\n read_image(GlobalVar.file_path)","def makeSavePaths(title, *fileFormats, outputdir=\"outputPlots\"):\n if not os.path.exists(outputdir):\n os.makedirs(outputdir)\n return [outputdir + \"/\" + title + fileFormat for fileFormat in fileFormats]","def construct_filename(output_dir,\n file_descriptor,\n extension,\n *args,\n **kwargs):\n if len(args) == 0 and len(kwargs) == 0:\n return Path(output_dir,\n '{}{}'.format(file_descriptor, extension))\n elif len(args) == 0:\n return Path(output_dir,\n '{}_{}{}'.format('_'.join([f'{k}{v}' for k, v in kwargs.items()\n if v is not None]),\n file_descriptor,\n extension))\n elif len(kwargs) == 0:\n return Path(output_dir,\n '{}_{}{}'.format('_'.join([ar for ar in args if ar is not None]),\n file_descriptor,\n extension))\n else:\n return Path(output_dir,\n '{}_{}_{}{}'.format('_'.join([ar for ar in args if ar is not None]),\n '_'.join([f'{k}{v}' for k, v in kwargs.items()\n if v is not None]),\n file_descriptor,\n extension))","def get_output_dir(imdb, net):\n path = os.path.abspath(os.path.join(__C.ROOT_DIR, 'output', __C.EXP_DIR, imdb.name))\n if net is None:\n return path\n else:\n return os.path.join(path, net.name)","def image_name(name):\n \n # Gets the '.' position\n dot = name.find('.')\n # Slice the name from beginning and before '.'\n img = name[:dot]\n # return string with jpg format\n return \"{}.jpg\".format(img)","def build_path(self, section: str, scr_name: str) -> str:\n base = self.root.joinpath(section).joinpath(f\"{scr_name}.png\")\n os_ver = env.version[1] if env.version < (11, 0) else env.version[0]\n os_specific = self.root.joinpath(section).joinpath(f\"{scr_name}_{os_ver}.png\")\n return (os_specific if os_specific.exists() else base).as_posix()","def get_file_save_path(self):\n return self.out","def save(img, path, file_name):\n\n name = os.path.join(path,file_name).replace('/', os.sep)\n\n io.imsave(name,img)","def save_output_image_to_directory(self):\n curr_directory = os.path.dirname(os.path.abspath(__file__))\n images_dir = curr_directory + \"/images/\"\n if not os.path.exists(images_dir):\n os.makedirs(images_dir)\n self.output_image_name = md5(str(uuid4()).encode()).hexdigest() + \".png\"\n image_file_name = images_dir + self.output_image_name\n self.output_image.save(image_file_name)\n logger.info(\"Image file saved locally : %s\", image_file_name)","def get_filename(self, workspace, make_dirs=True, check_overwrite=True):\n\n measurements = workspace.measurements\n file_name_feature = self.source_file_name_feature\n filename = measurements.get_current_measurement(\"Image\", file_name_feature)\n filename = os.path.splitext(filename)[0]\n if self.wants_file_name_suffix:\n suffix = self.file_name_suffix.value\n suffix = workspace.measurements.apply_metadata(suffix)\n filename += suffix\n\n filename = \"%s.%s\" % (filename, self.get_file_format())\n pathname = self.pathname.get_absolute_path(measurements)\n if self.create_subdirectories:\n image_path = self.source_path(workspace)\n subdir = os.path.relpath(image_path, self.root_dir.get_absolute_path())\n pathname = os.path.join(pathname, subdir)\n if len(pathname) and not os.path.isdir(pathname) and make_dirs:\n try:\n os.makedirs(pathname)\n except:\n #\n # On cluster, this can fail if the path was created by\n # another process after this process found it did not exist.\n #\n if not os.path.isdir(pathname):\n raise\n result = os.path.join(pathname, filename)\n if check_overwrite and not self.check_overwrite(result, workspace):\n return\n\n if check_overwrite and os.path.isfile(result):\n try:\n os.remove(result)\n except:\n import bioformats\n\n bioformats.clear_image_reader_cache()\n os.remove(result)\n return result","def filename(self):\n # Just the name of the file\n filename = self.use_name\n if self.extension:\n filename = \"{0}.{1}\".format(self.use_name, self.extension)\n # Architecture sub-folder\n arch_folder_conf = spack.config.get(\"modules:%s:arch_folder\" % self.conf.name, True)\n if arch_folder_conf:\n # include an arch specific folder between root and filename\n arch_folder = str(self.spec.architecture)\n filename = os.path.join(arch_folder, filename)\n # Return the absolute path\n return os.path.join(self.dirname(), filename)","def write_image(fname, data):\n # Get the file extension for this file, assuming it is the last continuous string after the last period\n fmt = fname.split(\".\")[-1]\n return writers[fmt](fname, data)","def make_file_name(name):\n expanded_path = os.path.expandvars(make_fp_rel(name))\n return expanded_path","def __make_path(self, filename):\n return self.__path() + os.sep + filename","def get_write_path(*args) -> str:\n\n return str(Path(WRITE_PATH, *args))","def imagePath(self):\n if self.use_dic:\n if self.imlist:\n paths = []\n for img in self.allimgs:\n paths.append(join(self.home, 'data'+str(self.data), self.activity, self.imsize, str(img)+'.jpg'))\n return paths\n else:\n path = join(self.home, 'data'+str(self.data), self.activity, self.imsize, str(self.img)+'.jpg')\n else:\n path = self.img\n return path","def generateFilename(folder, prefix, ext):\n filename = os.path.basename(os.path.normpath(folder))\n if prefix:\n filename = \"{0}-{1}\".format(prefix, filename)\n path = getIncrementedFilename(os.path.join(folder, filename), ext)\n return path","def out_filename(self, filetype, format='old', dir=Location.OUT_DIR):\n filename = self.filename(filetype=filetype, format=format)\n # return Path(dir) / filename\n return filename","def out_filename(self, filetype, format='old', dir=Location.OUT_DIR):\n filename = self.filename(filetype=filetype, format=format)\n #return Path(dir) / filename\n return filename","def outputFilepath(self, filename):\n return os.path.expanduser('~') + '/' + filename","def eval(self):\n if self.magic:\n return self.magic\n if not self.filename:\n return file_pattern.format(self.alias)\n return self.path","def get_image_path(instance, filename):\n filename, file_extension = path.splitext(filename)\n return path.join(str(uuid4()) + file_extension)","def _make_fname(song, ext=None, av=None, subdir=None):\n # pylint: disable=E1103\n # Instance of 'bool' has no 'extension' member (some types not inferable)\n ddir = os.path.join(Config.DDIR.get, subdir) if subdir else Config.DDIR.get\n if not os.path.exists(ddir):\n os.makedirs(ddir)\n\n if ext:\n extension = ext\n\n else:\n stream = streams.select(streams.get(song),\n audio=av == \"audio\", m4a_ok=True)\n extension = stream['ext']\n\n # filename = song.title[:59] + \".\" + extension\n filename = song.title + \".\" + extension\n filename = os.path.join(ddir, mswinfn(filename.replace(\"/\", \"-\")))\n filename = filename.replace('\"', '')\n return filename","def get_img_path(self, inp=None, aux=None):\n img_path = \"\".join([\n self._report_generator.config.img_dir,\n os.sep,\n self.get_tag(inp, aux),\n \".png\"])\n return img_path","def name_to_path(name):\n words = name.split()\n return \"_\".join(words) + \".world\"","def _dir_out(self):\n ens_label = utils.io.ens_label(self.ens_mem)\n return os.path.join(self.proj.direc_out, self.proj.name,\n self.model.name, self.run.name,\n ens_label, self.name)","def getFilePath( source, paper, month, day, year ):\r\n attributes = { SOURCE : source,\r\n PAPER : paper,\r\n MONTH : month,\r\n DAY : day,\r\n YEAR : year \r\n }\r\n return \"\\\\\".join( [ settings.CLEAN_STORE ] + [ attributes[ key ] for key in STORE_ORDER ] )","def make_new_path(path, postfix = \"\", ext = \"\"):\n dir = os.path.split(path)[0]\n old_basename, old_ext = os.path.splitext(path)\n new_basename = old_basename + \"_\" + postfix\n new_path = os.path.join(dir, new_basename + \".\" + ext)\n return new_path","def path(self, args):\n dir_path = self.dir_path_(*args)\n return os.path.join(dir_path, self.file_name)","def save(self, prefix='./', name=None, include_space=False):\n name = name or 'unnamed'\n filename = f'{name}.pth'\n prefix = join(prefix, 'architect')\n if not exists(prefix): make_dirs(prefix)\n path = join(prefix, filename)\n\n space = self.search_space\n if not include_space:\n self.search_space = None\n torch.save(self, path)\n self.search_space = space\n return path","def get_filename(self, path, prefix, suffix, date, period):\n return os.path.join(path,\n '%s%s%s' % (\n prefix,\n self.get_filename_date(date,\n params=dict(period=period)),\n suffix))"],"string":"[\n \"def output_filename(self, modifier):\\n fs = self._filesystem\\n output_filename = fs.join(self._root_output_dir, self._test_name)\\n return fs.splitext(output_filename)[0] + modifier\",\n \"def name_final_path(out_img_folder):\\n if out_img_folder == None:\\n return \\\"./.out_hidden_images\\\"\\n else:\\n return out_img_folder\",\n \"def get_save_path(op: Save, calculation: \\\"FileCalculation\\\") -> str:\\n from PartSegCore.analysis.save_functions import save_dict\\n\\n extension = save_dict[op.algorithm].get_default_extension()\\n rel_path = os.path.relpath(calculation.file_path, calculation.base_prefix)\\n rel_path = os.path.splitext(rel_path)[0]\\n if op.directory:\\n file_name = os.path.basename(rel_path)\\n base_rel_path = os.path.dirname(rel_path)\\n return os.path.join(calculation.result_prefix, base_rel_path, op.directory, file_name + op.suffix + extension)\\n return os.path.join(calculation.result_prefix, rel_path + op.suffix + extension)\",\n \"def get_out_file_path(self):\\n dir_path = self._get_output_dir()\\n self._check_make_dirs(dir_path)\\n return join(dir_path, self.FOCUSED_IMAGE_NAME)\",\n \"def path_to_name(img):\\n\\n return os.path.dirname(img) + '_' + os.path.basename(img)\",\n \"def get_path(dir_name, file_format, args):\\n fname = \\\"{exp}-excl-{excl}\\\".format(exp=args.exp,\\n excl=args.feature_set)\\n path = os.path.join(SAVE_ROOT, dir_name, args.rbp,\\n fname + file_format)\\n\\n # make the directory if it doesn't exist_ok\\n os.makedirs(os.path.dirname(path), exist_ok=True)\\n\\n return path\",\n \"def construct_image_savepath(self, date_string, coords_string, image_type=\\\"RGB\\\"):\\n\\n if \\\"SUB\\\" in image_type:\\n output_location = os.path.join(self.output_location, date_string, \\\"SPLIT\\\")\\n else:\\n output_location = os.path.join(self.output_location, date_string, \\\"PROCESSED\\\")\\n # filename is the date, coordinates, and image type\\n filename = f'{date_string}_{coords_string}_{image_type}.png'\\n\\n # full path is dir + filename\\n full_path = os.path.join(output_location, filename)\\n\\n return full_path\",\n \"def _output_path(name):\\n output = Path(\\\"../Analysis Results/\\\").joinpath(str(date.today()))\\n output.mkdir(parents=True, exist_ok=True)\\n return output.joinpath(f\\\"{name}.png\\\")\",\n \"def get_file_full_path(self):\\n return self.save_dir + os.sep + self.save_file_without_ext + self.save_file_ext\",\n \"def img_save(self):\\n file_name, extension = return_folder_file_extension(self.img_name)[1:]\\n image_name_save = \\\"%s_D=%s_Rs=%s_size=%s_offset=%i%s\\\" % (file_name, self.D, self.Rs, self.axe_X, self.offset_X+self.offset_X2, extension)\\n\\n if self.img2 is not None:\\n self.img2.save(image_name_save)\\n print(\\\"Saved \\\"+image_name_save)\\n else:\\n print(\\\"No image to save\\\")\",\n \"def name_to_path(img, origin):\\n\\n orig_file_parts = img.split('_')[1:]\\n\\n category = orig_file_parts[-3]\\n filename = orig_file_parts[-2]+'_'+orig_file_parts[-1]\\n\\n orig_file = os.path.sep.join([origin, category])\\n orig_file = os.path.sep.join([orig_file, filename])\\n\\n return orig_file\",\n \"def output_file_name_maker(args):\\n log.debug(\\\"Entering output_file_name_maker()\\\")\\n path = os.getcwd() + '/out_files/'\\n if not os.path.isdir(path):\\n os.mkdir(path)\\n\\n if args.output is None:\\n out_file_name = path + args.input[:-4] + '_' + args.type + '_' + args.layer\\n else:\\n out_file_name = path + args.output\\n\\n log.debug(\\\"Exiting output_file_name_maker()\\\")\\n return out_file_name\",\n \"def _out(self, *args):\\n suffix = '_'.join(map(str, args))\\n return os.path.join(self._out_folder, suffix )\",\n \"def build_output_file_path(dir, role, id):\\n clean_dir = dir.rstrip(\\\"/\\\")\\n punct = string.punctuation\\n junk = punct + \\\" \\\"\\n trantab = string.maketrans(junk, \\\"_________________________________\\\")\\n clean_role = role.encode(\\\"ascii\\\", \\\"replace\\\").strip(junk).translate(trantab)\\n path = (clean_dir + \\\"/\\\" + clean_version + \\\"-\\\" + clean_role + \\\"-\\\" +\\n str(id) + \\\".json\\\")\\n return re.sub(r'(_)\\\\1+', r'\\\\1', path)\",\n \"def getImgPath(outputDir, cameraID, timestamp, cropCoords=None, diffMinutes=0):\\n timeStr = datetime.datetime.fromtimestamp(timestamp).isoformat()\\n timeStr = timeStr.replace(':', ';') # make windows happy\\n imgName = '__'.join([cameraID, timeStr])\\n if diffMinutes:\\n imgName += ('_Diff%d' % diffMinutes)\\n if cropCoords:\\n imgName += '_Crop_' + 'x'.join(list(map(lambda x: str(x), cropCoords)))\\n imgPath = os.path.join(outputDir, imgName + '.jpg')\\n return imgPath\",\n \"def out_filename(self, filetype, dir, format='old'):\\n filename = self.filename(filetype=filetype, format=format)\\n return Path(dir) / filename\",\n \"def __diff_filename(self):\\n diff_dir = os.path.join(self.__folder, Reference.DIFF_OUT)\\n if not os.path.exists(diff_dir):\\n os.makedirs(diff_dir)\\n return os.path.join(diff_dir, self.__name +'.jpg')\",\n \"def imgOutputPath(self, newpath):\\n newimg = self.imagePath().replace(self.home, newpath)\\n return newimg\",\n \"def generate_filename(\\n self, directory=os.getcwd(), prefix=\\\"tile\\\", format=\\\"png\\\", path=True\\n ):\\n filename = prefix + \\\"_{col:02d}_{row:02d}.{ext}\\\".format(\\n col=self.column, row=self.row, ext=format.lower().replace(\\\"jpeg\\\", \\\"jpg\\\")\\n )\\n if not path:\\n return filename\\n return os.path.join(directory, filename)\",\n \"def saveImage(self, fileName=\\\"mandelbrot.frac\\\"):\\n # Save the image as a PNG\\n if fileName == \\\"\\\":\\n fileName = \\\"mandelbrot.frac\\\"\\n directories = fileName.split(\\\"/\\\")\\n for n in directories:\\n if \\\".frac\\\" in n:\\n name = n.rsplit(\\\".\\\", 1)[0]\\n self.img.write(f\\\"{name}.png\\\")\\n print(f\\\"Wrote image {name}.png\\\")\",\n \"def create_filename (self):\\n\\t\\tassert self.__patient_name and self.__location_name, \\\"New filename could not be determined, one or more needed arguments is empty!\\\"\\n\\t\\t_patient_name = self.__patient_name.split(' ')\\n\\t\\t_patient_name.reverse()\\n\\t\\t\\n\\t\\treturn os.path.join(os.path.dirname(self.file._path), \\\"%s MR %s%s\\\" % (self.__location_name, ', '.join(_patient_name).upper(), self._file.extension))\",\n \"def photo_directory_path(instance, filename):\\n return 'gallery/photos/{0}/{1}'.format(instance.photo_name, filename)\",\n \"def write(self, name=None, ext=None, directory=None):\\n delim = \\\"_\\\"\\n if name is None:\\n # extra delimeter added to separate edits from the extension\\n name = delim.join(self.edits) + delim\\n if directory is not None:\\n name = os.path.join(directory, name)\\n if ext is None:\\n ext = self.ext\\n\\n return cv2.imwrite(name + ext, self.img)\",\n \"def _make_path(self) -> str:\\r\\n path_ = Path(path.join(conf.instance.output_path, self.path_prefix, self.name))\\r\\n if self.is_identifier_in_paths:\\r\\n path_ = path_ / self.identifier\\r\\n return path_\",\n \"def get_filepath(image):\\r\\n extension = (len(image.split('/')[-1:][0]))\\r\\n return image[:-extension]\",\n \"def student_image_file_path(instance, filename):\\n ext = filename.split('.')[-1] # [-1] returns the last item from a list\\n filename = f'{uuid.uuid4()}.{ext}'\\n\\n return os.path.join('uploads/students/', filename)\",\n \"def outputPath():\\n scenePath = bpy.data.filepath\\n # If the scene hasn't been saved yet the path is empty.\\n # Returning an empty path prompts the user for saving the scene.\\n if not scenePath:\\n return\\n renderPath = os.path.join(os.path.dirname(scenePath), \\\"{}_thumbs\\\".format(NAME))\\n return renderPath\",\n \"def set_image_out_path(self, image_path):\\n i = image_path.rfind('/')\\n self.image_out_path = image_path[:i+1] + \\\"out/\\\" + image_path[i+1:]\",\n \"def get_savename(outdir, plot_name, extension):\\n save_name = '.'.join([plot_name, extension])\\n save_name = '/'.join([outdir, save_name])\\n return save_name\",\n \"def recipe_image_file_path(instance, filename):\\n # Return the extention of the file name\\n ext = filename.split('.')[-1]\\n # Create a new name using the uuid\\n filename = f'{uuid.uuid4()}.{ext}'\\n\\n # A relable method that allowed us to join 2 strings into a vaild path\\n return os.path.join('uploads/recipe/', filename)\",\n \"def get_image_filename(self, filename):\\n path = 'images/{folder}/{filename}'.format(\\n folder=self.folder,\\n filename=filename\\n )\\n return path\",\n \"def process_image(self, decorator):\\r\\n savefig_dir = self.savefig_dir\\r\\n source_dir = self.source_dir\\r\\n saveargs = decorator.split(' ')\\r\\n filename = saveargs[1]\\r\\n # insert relative path to image file in source\\r\\n outfile = os.path.relpath(os.path.join(savefig_dir,filename),\\r\\n source_dir)\\r\\n\\r\\n imagerows = ['.. image:: %s'%outfile]\\r\\n\\r\\n for kwarg in saveargs[2:]:\\r\\n arg, val = kwarg.split('=')\\r\\n arg = arg.strip()\\r\\n val = val.strip()\\r\\n imagerows.append(' :%s: %s'%(arg, val))\\r\\n\\r\\n image_file = os.path.basename(outfile) # only return file name\\r\\n image_directive = '\\\\n'.join(imagerows)\\r\\n return image_file, image_directive\",\n \"def _make_output_path(self, filename):\\n return os.path.join(self._output_directory, filename)\",\n \"def makefilename(self):\\n fp= (pathlib.Path(self.vr_folder).expanduser()/(time.strftime(self.vr_filename))).with_suffix('')\\n fp.parent.mkdir(parents=True, exist_ok=True)\\n print('files setup', str(fp))\\n return fp\",\n \"def generate_file_filename(instance, filename):\\n return _generate_filename(instance, filename, 'photos')\",\n \"def get_photo_path(self, filename):\\n univ = \\\"abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890\\\"\\n name = \\\"\\\".join([random.choice(univ) for i in xrange(20)])\\n root, ext = os.path.splitext(filename)\\n\\n return u'photos/%s' % (name + ext)\",\n \"def imagefile(self):\\n if self.__filetype==\\\"flatWarp\\\" :\\n ext = \\\".fw\\\"\\n elif self.__filetype==\\\"camWarp\\\" :\\n ext = \\\".camWarp\\\"\\n elif self.__filetype==\\\"raw\\\" :\\n ext = \\\".Data.dat\\\"\\n else :\\n raise ValueError(f\\\"requested file type {self.__filetype} not recognized\\\")\\n\\n return self.__imagefolder/self.file.replace(\\\".im3\\\", ext)\",\n \"def opath ( dir_name, file_name = None ):\\n if file_name:\\n return os.path.join(output_path, dir_name, file_name)\\n return os.path.join(output_path, dir_name)\",\n \"def _app_outfile_path(path, app_name, extension):\\n filename = '%s.%s' % (app_name, extension)\\n return os.path.join(path, filename)\",\n \"def _make_save_path(self, save_path, save_name):\\n if save_name.endswith('.txt'):\\n path = os.path.join(save_path, save_name)\\n else:\\n self.save_name = save_name+'.txt'\\n path = os.path.join(save_path, save_name)\\n return path\",\n \"def _gen_image_filename(instance, filename):\\n # First, store the original filename in the model\\n instance.original_filename = filename\\n\\n return _unique_path(instance.owner.pk, filename)\",\n \"def make_path(self, basename):\\n return os.path.join(self.output_folder, basename.format(self.sample_name))\",\n \"def build_out_path(d):\\n assert \\\"output_dir\\\" in d, \\\"Dictionary must have output dir\\\"\\n\\n path = d.pop(\\\"output_dir\\\")\\n\\n weights_path = path + \\\"weights_\\\"\\n log_path = path + \\\"log_\\\"\\n train_data_path = path + \\\"train_data_\\\"\\n\\n # Sort dictionary for consistency\\n odict = OrderedDict(sorted(d.items(), key=lambda t: t[0]))\\n\\n for key, val in zip(odict.keys(), odict.values()):\\n if key not in (\\\"input_dir\\\", \\\"loss_type\\\", \\\"typical_epochs\\\", \\\"num_epochs\\\"):\\n text = str(key) + \\\"_\\\" + str(val) + \\\"_\\\"\\n weights_path += text\\n log_path += text\\n train_data_path += text\\n\\n weights_path += \\\".pth\\\"\\n log_path += \\\".log\\\"\\n train_data_path += \\\".pkl\\\"\\n\\n return weights_path, log_path, train_data_path\",\n \"def make_img_name(file_ext='.png'):\\r\\n fn = []\\r\\n # format seqs and write out to temp file\\r\\n for i in range(0, 30):\\r\\n fn.append(choice(ALPHABET))\\r\\n return ''.join(fn) + file_ext\",\n \"def save_image(image: FileStorage):\\n base_path = Path(current_app.config[\\\"USER_DIR\\\"]) / \\\"images\\\"\\n fileparts = image.filename.rsplit(\\\".\\\", 1)\\n sanitized_filename = secure_filename(fileparts[0])\\n dest_path = base_path / f\\\"{sanitized_filename}.{fileparts[1]}\\\"\\n i = 1\\n while dest_path.exists():\\n dest_path = base_path / f\\\"{sanitized_filename}-{i}.{fileparts[1]}\\\"\\n i += 1\\n image.save(str(dest_path))\\n return dest_path.parts[-1]\",\n \"def _get_filepath(self, name=None, use_timestamp=True):\\n current_time = str(int(time.time()))\\n if not name and not use_timestamp:\\n raise Exception(\\\"Name or timestamp is required\\\")\\n if name:\\n self.fname = \\\"%s\\\" % name\\n current_time = \\\"_%s\\\" % current_time\\n if use_timestamp:\\n self.fname = \\\"%s%s\\\" % (self.fname, current_time)\\n if len(self.fname) > 0:\\n self.fname = \\\"%s/%s.jpg\\\" % (self.picture_directory, self.fname)\\n return self.fname\",\n \"def doctor_image_upload_path(instance, file_path):\\n file_name, file_ext = get_file_name_ext(file_path)\\n random_file_name = generate_random_text(file_name)\\n final_file_name = f\\\"profile_photos/{random_file_name}\\\"\\n return final_file_name\",\n \"def get_full_path(file_extension=True) -> str:\\n return get_directory() + \\\"/\\\" + get_filename(file_extension=file_extension)\",\n \"def savestring(self , name , filenum , samedir = False , prefix = True):\\n if prefix == True:\\n if samedir:\\n \\\"\\\"\\\"\\n Making use of some implementation detail of savefig, if we read in files from all different directory's, the prefixes contain the path of those files relative to the rootdirectory. So if you save the file we save it with first the prefix and then the name , so the figures end up in the same directory as the files. If you don't want this behaviour we need to remove the / in the prefixs so fig.savefig will not recognize it as a path so all the figures end up in the current working directory. Remark we only remove the / because if all the figures end up in same dir we need the path information to distinguish them.\\n \\\"\\\"\\\"\\n self.prefix = [pre.translate(None , '/.') for pre in self.prefix]\\n return '%s%s%d.png' %(self.prefix[filenum], name, filenum )\\n #return '%s%s.png' %(self.prefix[filenum], name)\\n else:\\n return '%s%d.png' %(name, filenum )\",\n \"def get_path(\\n layer: LayerType,\\n batch_size: int,\\n num_runs: int,\\n num_repeats: int,\\n gsm_mode: str,\\n random_seed: Optional[int] = None,\\n forward_only: bool = False,\\n root: str = \\\"./results/raw/\\\",\\n suffix: str = \\\"\\\",\\n) -> str:\\n pickle_name = f\\\"{layer}_mode_{gsm_mode}_bs_{batch_size}_runs_{num_runs}_repeats_{num_repeats}_seed_{random_seed}\\\"\\n if forward_only:\\n pickle_name += \\\"_forward_only\\\"\\n\\n if len(suffix) and not suffix.startswith(\\\"_\\\"):\\n suffix = f\\\"_{suffix}\\\"\\n\\n return f\\\"{root}{pickle_name}{suffix}.pkl\\\"\",\n \"def make_image_path(raw_img, input_base, base_path):\\n path = os.path.dirname(raw_img)\\n relpath = os.path.relpath(path, input_base)\\n if relpath == '.':\\n dest_folder = base_path\\n else:\\n dest_folder = os.path.join(base_path, relpath)\\n return os.path.normpath(dest_folder)\\n # return dest_folder\",\n \"def gen_folder(base, e, f, a, k):\\n \\n return base + 'eps_' + str(e) + '_fp_' + str(f) + \\\\\\n '_areak_' + str(a) + '_kappa_' + str(k)\",\n \"def buildPath(dir, file_name, ext, description = None):\\n\\tpath = os.path.join(dir, file_name)\\n\\tbase, _ = os.path.splitext(path)\\n\\tif not description == None:\\n\\t\\tbase = base + '.' + description\\n\\treturn base + ext\",\n \"def build_portrait_filename(self, key):\\n\\t\\tname = self.source.get_name()\\n\\t\\tif name == None:\\n\\t\\t\\treturn None\\n\\t\\treturn \\\"portrait_\\\" + name + \\\"_\\\" + key + \\\".bmp\\\"\",\n \"def create_savename(self):\\n \\n savename = self.config.get('grid', 'dir') + self.fname.split('/')[-1]\\n newsuffix = '_gridded_%ix%ix%i.nc' % (self.nx, self.ny, self.nz)\\n savename = savename.replace('.nc', newsuffix)\\n \\n return savename\",\n \"def save_photo():\\n save_name = filedialog.asksaveasfilename(initialdir=\\\"10.APOD Viewer/\\\", title=\\\"Save Image\\\", filetype=((\\\"JPEG\\\", \\\"*.jpg\\\"), (\\\"All Files\\\", \\\"*.*\\\")))\\n img.save(save_name + \\\".jpg\\\")\",\n \"def get_output_filename(self, gzip=False):\\n if self.mode == 'light':\\n suffix = '-light'\\n else:\\n suffix = ''\\n\\n destination = self.destination\\n extension = 'fits'\\n if gzip:\\n destination += '-compressed'\\n extension += '.gz'\\n return os.path.join(destination,\\n 'iphas-dr2-{0}{1}.{2}'.format(\\n self.get_partname(),\\n suffix,\\n extension))\",\n \"def build_file_path(dir_name, file_name, ext):\\n return os.path.join(dir_name, os.path.extsep.join((file_name, ext)))\",\n \"def _getSavePath(self):\\n path, filename = os.path.split(self.path)\\n savePath = os.path.join(path, os.path.splitext(filename)[0])\\n return savePath\",\n \"def make_path(self):\\n folders = [\\n f\\\"{self.save_path}{self.name}/json/\\\",\\n f\\\"{self.save_path}{self.name}/images/\\\",\\n ]\\n if hasattr(self, \\\"masks\\\"):\\n folders.append(f\\\"{self.save_path}{self.name}/masks/\\\")\\n for folder in folders:\\n if not os.path.exists(folder):\\n os.makedirs(folder)\",\n \"def generate_filename(extension, with_path=True, base_folder=None):\\n name = get_md5(str(uuid4()))\\n # if not extension:\\n # extension = get_file_extension()\\n if base_folder is not None:\\n base_folder = \\\"%s/\\\" % base_folder.rstrip(\\\"/\\\")\\n else:\\n base_folder = \\\"\\\"\\n\\n if with_path:\\n return \\\"%s%s/%s/%s/%s.%s\\\" % (base_folder, name[0], name[1], name[2], name, extension)\\n else:\\n return \\\"%s%s.%s\\\" % (base_folder, name, extension)\",\n \"def get_outfolder():\\n \\n valid = False\\n while not valid:\\n fname = raw_input(\\\"Please enter directory to save images. \\\")\\n if not os.path.exists(fname):\\n os.makedirs(fname)\\n #Check to see if the file is there.\\n if os.path.exists(fname): \\n valid = True\\n #File is not there, check to see if write privileges can be given\\n #to created file.\\n elif os.access(os.path.dirname(fname), os.W_OK):\\n valid = True\\n else:\\n print \\\"Invalid local path, please try again.\\\"\\n return fname\",\n \"def roompost_image_file_path(instance, filename):\\n ext = filename.split('.')[-1]\\n filename = f'{uuid.uuid4()}.{ext}'\\n\\n return os.path.join('uploads/post/', filename)\",\n \"def GetOutputFilename(fname):\\n return os.path.join(outdir, fname)\",\n \"def recipe_image_file_path(instance, filename):\\n\\n ext = filename.split('.')[-1]\\n filename = f'{uuid.uuid4()}.{ext}'\\n\\n return os.path.join('uploads/recipe/', filename)\",\n \"def get_filename(\\n self,\\n name,\\n ext=\\\".npz\\\",\\n map_tag=None,\\n iter_index=None,\\n extra_tag=None,\\n bp_opts=False,\\n ):\\n if self.output_root is None:\\n return None\\n\\n if bp_opts:\\n if self.ensemble_mean:\\n name = \\\"{}_mean\\\".format(name)\\n elif self.ensemble_median:\\n name = \\\"{}_median\\\".format(name)\\n elif self.sim_index is not None:\\n name = \\\"{}_sim{:04d}\\\".format(name, self.sim_index)\\n if self.signal_type_sim:\\n name = \\\"{}_{}\\\".format(name, self.signal_type_sim)\\n if self.noise_type_sim:\\n name = \\\"{}_{}\\\".format(name, self.noise_type_sim)\\n else:\\n if self.data_type != \\\"raw\\\":\\n name = \\\"{}_{}\\\".format(name, self.data_type)\\n if getattr(self, \\\"template_cleaned\\\", False):\\n name = \\\"{}_clean_{}\\\".format(name, self.template_type)\\n if getattr(self, \\\"planck_sub\\\", False):\\n name = \\\"{}_planck_sub\\\".format(name)\\n if self.weighted_bins:\\n name = \\\"{}_wbins\\\".format(name)\\n if getattr(self, \\\"return_cls\\\", False):\\n name = \\\"{}_cl\\\".format(name)\\n\\n if map_tag is not None:\\n name = \\\"{}_map_{}\\\".format(name, map_tag)\\n if iter_index is not None:\\n name = \\\"{}_iter{:03d}\\\".format(name, iter_index)\\n if extra_tag is not None:\\n name = \\\"{}_{}\\\".format(name, extra_tag)\\n\\n tag = \\\"_{}\\\".format(self.output_tag) if self.output_tag else \\\"\\\"\\n if not ext.startswith(\\\".\\\"):\\n ext = \\\".{}\\\".format(ext)\\n return os.path.join(self.output_root, \\\"{}{}{}\\\".format(name, tag, ext))\",\n \"def return_folder_file_extension(img_name):\\n *folder, file = img_name.replace(\\\"\\\\\\\\\\\", \\\"/\\\").split(\\\"/\\\")\\n\\n if len(folder) != 0:\\n folder = folder[0]\\n\\n file, extension = file.split(\\\".\\\")\\n\\n return folder, file, \\\".\\\"+extension\",\n \"def save_step_2(imgs, match_list, output_path=\\\"./output/step2\\\"):\\n # ... your code here ...\\n for i in range(len(imgs)):\\n name1,tail1 = str.split(filenames[match_list[i][0]],\\\".\\\")\\n name2,tail2 = str.split(filenames[match_list[i][2]],\\\".\\\")\\n cv2.imwrite(output_path+\\\"/\\\"+name1+\\\"_\\\"+str(match_list[i][1])+\\\"_\\\"+name2+\\\"_\\\"+str(match_list[i][3])+\\\"_\\\"+str(match_list[i][4])+\\\".jpg\\\", imgs[i])\",\n \"def file_path(instance, filename):\\n hashcode = hash(filename)\\n mask = 255 # bitmask\\n # use the first and second bytes of the hash code represented as\\n # zero-padded hex numbers as directory names\\n # provides 256 * 256 = 65536 of possible directory combinations\\n dir1 = \\\"{:0>2x}\\\".format(hashcode & mask)\\n dir2 = \\\"{:0>2x}\\\".format((hashcode >> 8) & mask)\\n # Galaxy doesn't process names with parentheses in them\\n filename = re.sub('[()]', '_', filename)\\n return os.path.join(dir1, dir2, filename)\",\n \"def get_path_to_image():\\n file_types = [\\n (\\\"JPEG Image\\\", '*.jpeg; *jpg'),\\n (\\\"PNG Image\\\", '*.png'),\\n (\\\"BPM Image\\\", '*.bmp'),\\n (\\\"Netpbm Image\\\", '*.ppm; *.pgm; *.pbm; *pnm')\\n ]\\n\\n GlobalVar.file_path = filedialog.askopenfilename(filetypes=file_types)\\n GlobalVar.name_original = GlobalVar.file_path.split('/')[-1]\\n GlobalVar.is_open_image = True\\n\\n read_image(GlobalVar.file_path)\",\n \"def makeSavePaths(title, *fileFormats, outputdir=\\\"outputPlots\\\"):\\n if not os.path.exists(outputdir):\\n os.makedirs(outputdir)\\n return [outputdir + \\\"/\\\" + title + fileFormat for fileFormat in fileFormats]\",\n \"def construct_filename(output_dir,\\n file_descriptor,\\n extension,\\n *args,\\n **kwargs):\\n if len(args) == 0 and len(kwargs) == 0:\\n return Path(output_dir,\\n '{}{}'.format(file_descriptor, extension))\\n elif len(args) == 0:\\n return Path(output_dir,\\n '{}_{}{}'.format('_'.join([f'{k}{v}' for k, v in kwargs.items()\\n if v is not None]),\\n file_descriptor,\\n extension))\\n elif len(kwargs) == 0:\\n return Path(output_dir,\\n '{}_{}{}'.format('_'.join([ar for ar in args if ar is not None]),\\n file_descriptor,\\n extension))\\n else:\\n return Path(output_dir,\\n '{}_{}_{}{}'.format('_'.join([ar for ar in args if ar is not None]),\\n '_'.join([f'{k}{v}' for k, v in kwargs.items()\\n if v is not None]),\\n file_descriptor,\\n extension))\",\n \"def get_output_dir(imdb, net):\\n path = os.path.abspath(os.path.join(__C.ROOT_DIR, 'output', __C.EXP_DIR, imdb.name))\\n if net is None:\\n return path\\n else:\\n return os.path.join(path, net.name)\",\n \"def image_name(name):\\n \\n # Gets the '.' position\\n dot = name.find('.')\\n # Slice the name from beginning and before '.'\\n img = name[:dot]\\n # return string with jpg format\\n return \\\"{}.jpg\\\".format(img)\",\n \"def build_path(self, section: str, scr_name: str) -> str:\\n base = self.root.joinpath(section).joinpath(f\\\"{scr_name}.png\\\")\\n os_ver = env.version[1] if env.version < (11, 0) else env.version[0]\\n os_specific = self.root.joinpath(section).joinpath(f\\\"{scr_name}_{os_ver}.png\\\")\\n return (os_specific if os_specific.exists() else base).as_posix()\",\n \"def get_file_save_path(self):\\n return self.out\",\n \"def save(img, path, file_name):\\n\\n name = os.path.join(path,file_name).replace('/', os.sep)\\n\\n io.imsave(name,img)\",\n \"def save_output_image_to_directory(self):\\n curr_directory = os.path.dirname(os.path.abspath(__file__))\\n images_dir = curr_directory + \\\"/images/\\\"\\n if not os.path.exists(images_dir):\\n os.makedirs(images_dir)\\n self.output_image_name = md5(str(uuid4()).encode()).hexdigest() + \\\".png\\\"\\n image_file_name = images_dir + self.output_image_name\\n self.output_image.save(image_file_name)\\n logger.info(\\\"Image file saved locally : %s\\\", image_file_name)\",\n \"def get_filename(self, workspace, make_dirs=True, check_overwrite=True):\\n\\n measurements = workspace.measurements\\n file_name_feature = self.source_file_name_feature\\n filename = measurements.get_current_measurement(\\\"Image\\\", file_name_feature)\\n filename = os.path.splitext(filename)[0]\\n if self.wants_file_name_suffix:\\n suffix = self.file_name_suffix.value\\n suffix = workspace.measurements.apply_metadata(suffix)\\n filename += suffix\\n\\n filename = \\\"%s.%s\\\" % (filename, self.get_file_format())\\n pathname = self.pathname.get_absolute_path(measurements)\\n if self.create_subdirectories:\\n image_path = self.source_path(workspace)\\n subdir = os.path.relpath(image_path, self.root_dir.get_absolute_path())\\n pathname = os.path.join(pathname, subdir)\\n if len(pathname) and not os.path.isdir(pathname) and make_dirs:\\n try:\\n os.makedirs(pathname)\\n except:\\n #\\n # On cluster, this can fail if the path was created by\\n # another process after this process found it did not exist.\\n #\\n if not os.path.isdir(pathname):\\n raise\\n result = os.path.join(pathname, filename)\\n if check_overwrite and not self.check_overwrite(result, workspace):\\n return\\n\\n if check_overwrite and os.path.isfile(result):\\n try:\\n os.remove(result)\\n except:\\n import bioformats\\n\\n bioformats.clear_image_reader_cache()\\n os.remove(result)\\n return result\",\n \"def filename(self):\\n # Just the name of the file\\n filename = self.use_name\\n if self.extension:\\n filename = \\\"{0}.{1}\\\".format(self.use_name, self.extension)\\n # Architecture sub-folder\\n arch_folder_conf = spack.config.get(\\\"modules:%s:arch_folder\\\" % self.conf.name, True)\\n if arch_folder_conf:\\n # include an arch specific folder between root and filename\\n arch_folder = str(self.spec.architecture)\\n filename = os.path.join(arch_folder, filename)\\n # Return the absolute path\\n return os.path.join(self.dirname(), filename)\",\n \"def write_image(fname, data):\\n # Get the file extension for this file, assuming it is the last continuous string after the last period\\n fmt = fname.split(\\\".\\\")[-1]\\n return writers[fmt](fname, data)\",\n \"def make_file_name(name):\\n expanded_path = os.path.expandvars(make_fp_rel(name))\\n return expanded_path\",\n \"def __make_path(self, filename):\\n return self.__path() + os.sep + filename\",\n \"def get_write_path(*args) -> str:\\n\\n return str(Path(WRITE_PATH, *args))\",\n \"def imagePath(self):\\n if self.use_dic:\\n if self.imlist:\\n paths = []\\n for img in self.allimgs:\\n paths.append(join(self.home, 'data'+str(self.data), self.activity, self.imsize, str(img)+'.jpg'))\\n return paths\\n else:\\n path = join(self.home, 'data'+str(self.data), self.activity, self.imsize, str(self.img)+'.jpg')\\n else:\\n path = self.img\\n return path\",\n \"def generateFilename(folder, prefix, ext):\\n filename = os.path.basename(os.path.normpath(folder))\\n if prefix:\\n filename = \\\"{0}-{1}\\\".format(prefix, filename)\\n path = getIncrementedFilename(os.path.join(folder, filename), ext)\\n return path\",\n \"def out_filename(self, filetype, format='old', dir=Location.OUT_DIR):\\n filename = self.filename(filetype=filetype, format=format)\\n # return Path(dir) / filename\\n return filename\",\n \"def out_filename(self, filetype, format='old', dir=Location.OUT_DIR):\\n filename = self.filename(filetype=filetype, format=format)\\n #return Path(dir) / filename\\n return filename\",\n \"def outputFilepath(self, filename):\\n return os.path.expanduser('~') + '/' + filename\",\n \"def eval(self):\\n if self.magic:\\n return self.magic\\n if not self.filename:\\n return file_pattern.format(self.alias)\\n return self.path\",\n \"def get_image_path(instance, filename):\\n filename, file_extension = path.splitext(filename)\\n return path.join(str(uuid4()) + file_extension)\",\n \"def _make_fname(song, ext=None, av=None, subdir=None):\\n # pylint: disable=E1103\\n # Instance of 'bool' has no 'extension' member (some types not inferable)\\n ddir = os.path.join(Config.DDIR.get, subdir) if subdir else Config.DDIR.get\\n if not os.path.exists(ddir):\\n os.makedirs(ddir)\\n\\n if ext:\\n extension = ext\\n\\n else:\\n stream = streams.select(streams.get(song),\\n audio=av == \\\"audio\\\", m4a_ok=True)\\n extension = stream['ext']\\n\\n # filename = song.title[:59] + \\\".\\\" + extension\\n filename = song.title + \\\".\\\" + extension\\n filename = os.path.join(ddir, mswinfn(filename.replace(\\\"/\\\", \\\"-\\\")))\\n filename = filename.replace('\\\"', '')\\n return filename\",\n \"def get_img_path(self, inp=None, aux=None):\\n img_path = \\\"\\\".join([\\n self._report_generator.config.img_dir,\\n os.sep,\\n self.get_tag(inp, aux),\\n \\\".png\\\"])\\n return img_path\",\n \"def name_to_path(name):\\n words = name.split()\\n return \\\"_\\\".join(words) + \\\".world\\\"\",\n \"def _dir_out(self):\\n ens_label = utils.io.ens_label(self.ens_mem)\\n return os.path.join(self.proj.direc_out, self.proj.name,\\n self.model.name, self.run.name,\\n ens_label, self.name)\",\n \"def getFilePath( source, paper, month, day, year ):\\r\\n attributes = { SOURCE : source,\\r\\n PAPER : paper,\\r\\n MONTH : month,\\r\\n DAY : day,\\r\\n YEAR : year \\r\\n }\\r\\n return \\\"\\\\\\\\\\\".join( [ settings.CLEAN_STORE ] + [ attributes[ key ] for key in STORE_ORDER ] )\",\n \"def make_new_path(path, postfix = \\\"\\\", ext = \\\"\\\"):\\n dir = os.path.split(path)[0]\\n old_basename, old_ext = os.path.splitext(path)\\n new_basename = old_basename + \\\"_\\\" + postfix\\n new_path = os.path.join(dir, new_basename + \\\".\\\" + ext)\\n return new_path\",\n \"def path(self, args):\\n dir_path = self.dir_path_(*args)\\n return os.path.join(dir_path, self.file_name)\",\n \"def save(self, prefix='./', name=None, include_space=False):\\n name = name or 'unnamed'\\n filename = f'{name}.pth'\\n prefix = join(prefix, 'architect')\\n if not exists(prefix): make_dirs(prefix)\\n path = join(prefix, filename)\\n\\n space = self.search_space\\n if not include_space:\\n self.search_space = None\\n torch.save(self, path)\\n self.search_space = space\\n return path\",\n \"def get_filename(self, path, prefix, suffix, date, period):\\n return os.path.join(path,\\n '%s%s%s' % (\\n prefix,\\n self.get_filename_date(date,\\n params=dict(period=period)),\\n suffix))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6506808","0.61701065","0.5883275","0.5868304","0.5847001","0.5811345","0.5766814","0.5759355","0.57464373","0.57153183","0.5675875","0.5666476","0.5665445","0.5655566","0.56509286","0.5640137","0.562522","0.55997884","0.55983824","0.5587275","0.55767787","0.55177546","0.5506417","0.55056167","0.5497194","0.54952997","0.54930097","0.54881585","0.5464366","0.5445688","0.5437197","0.5428549","0.54240566","0.54209733","0.5409543","0.54089975","0.53991085","0.5396603","0.5378559","0.537736","0.5373157","0.5369715","0.53614086","0.5360275","0.5355144","0.53540593","0.5351328","0.53484917","0.5346974","0.5331137","0.5319083","0.5311761","0.5308886","0.53062016","0.530084","0.5285454","0.5273808","0.52725655","0.5271354","0.5264117","0.52640307","0.5261622","0.5259683","0.52549505","0.5248501","0.5239688","0.5235066","0.52278847","0.52254385","0.5208832","0.5208785","0.5207803","0.52075136","0.5201536","0.5196644","0.51965135","0.51930946","0.518888","0.51850665","0.5182842","0.5182706","0.5180105","0.51786715","0.5168127","0.51681185","0.51584184","0.5157714","0.5144969","0.51379406","0.5130109","0.51255697","0.512173","0.51195973","0.51123023","0.511222","0.5098237","0.50978875","0.50975454","0.5096332","0.5090923"],"string":"[\n \"0.6506808\",\n \"0.61701065\",\n \"0.5883275\",\n \"0.5868304\",\n \"0.5847001\",\n \"0.5811345\",\n \"0.5766814\",\n \"0.5759355\",\n \"0.57464373\",\n \"0.57153183\",\n \"0.5675875\",\n \"0.5666476\",\n \"0.5665445\",\n \"0.5655566\",\n \"0.56509286\",\n \"0.5640137\",\n \"0.562522\",\n \"0.55997884\",\n \"0.55983824\",\n \"0.5587275\",\n \"0.55767787\",\n \"0.55177546\",\n \"0.5506417\",\n \"0.55056167\",\n \"0.5497194\",\n \"0.54952997\",\n \"0.54930097\",\n \"0.54881585\",\n \"0.5464366\",\n \"0.5445688\",\n \"0.5437197\",\n \"0.5428549\",\n \"0.54240566\",\n \"0.54209733\",\n \"0.5409543\",\n \"0.54089975\",\n \"0.53991085\",\n \"0.5396603\",\n \"0.5378559\",\n \"0.537736\",\n \"0.5373157\",\n \"0.5369715\",\n \"0.53614086\",\n \"0.5360275\",\n \"0.5355144\",\n \"0.53540593\",\n \"0.5351328\",\n \"0.53484917\",\n \"0.5346974\",\n \"0.5331137\",\n \"0.5319083\",\n \"0.5311761\",\n \"0.5308886\",\n \"0.53062016\",\n \"0.530084\",\n \"0.5285454\",\n \"0.5273808\",\n \"0.52725655\",\n \"0.5271354\",\n \"0.5264117\",\n \"0.52640307\",\n \"0.5261622\",\n \"0.5259683\",\n \"0.52549505\",\n \"0.5248501\",\n \"0.5239688\",\n \"0.5235066\",\n \"0.52278847\",\n \"0.52254385\",\n \"0.5208832\",\n \"0.5208785\",\n \"0.5207803\",\n \"0.52075136\",\n \"0.5201536\",\n \"0.5196644\",\n \"0.51965135\",\n \"0.51930946\",\n \"0.518888\",\n \"0.51850665\",\n \"0.5182842\",\n \"0.5182706\",\n \"0.5180105\",\n \"0.51786715\",\n \"0.5168127\",\n \"0.51681185\",\n \"0.51584184\",\n \"0.5157714\",\n \"0.5144969\",\n \"0.51379406\",\n \"0.5130109\",\n \"0.51255697\",\n \"0.512173\",\n \"0.51195973\",\n \"0.51123023\",\n \"0.511222\",\n \"0.5098237\",\n \"0.50978875\",\n \"0.50975454\",\n \"0.5096332\",\n \"0.5090923\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.731317"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88570,"cells":{"query":{"kind":"string","value":"Convert image to a regular baseline JPEG. Quality option is ignored if useexistingqtables=True."},"document":{"kind":"string","value":"def savebaselineJPEG(image, fname, outpath, optimize=True, quality=75, recompressed=False, useexistingqtables=False, preserve_name=False):\n\n if not preserve_name:\n if recompressed:\n fpath = genSavePath(outpath, fname, modstring=f\"recompressed_q{quality}\")\n else:\n fpath = genSavePath(outpath, fname, modstring=f\"q{quality}\")\n else:\n fpath = genSavePath(outpath, fname)\n\n try:\n if useexistingqtables:\n image.save(fpath, subsample=\"keep\", optimize=optimize, qtables=image.quantization)\n else:\n image.save(fpath, subsample=\"keep\", optimize=optimize, quality=quality)\n\n except IOError as m:\n print(\"Baseline JPEG creation failed for: {}. \\nReason:{}\".format(fname, m))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def convert_to_jpeg(image, quality=90):\n\n\t# Load the image into a new BytesIO\n\tsImg = BytesIO(image)\n\n\t# Create an empty BytesIO for the new image\n\tsNewImg = BytesIO(b'')\n\n\t# Create a new Pillow instance from the raw data\n\toImg = Pillow.open(sImg)\n\n\t# If the mode is not valid\n\tif oImg.mode not in ('1','L','RGB','RGBA'):\n\t\toImg = oImg.convert('RGB');\n\n\t# Save the new image as a JPEG\n\toImg.save(sNewImg, 'JPEG', quality=quality, subsampling=0)\n\n\t# Pull out the raw string\n\tsRet = sNewImg.getvalue()\n\n\t# Close the image\n\toImg.close()\n\n\t# Return the new image\n\treturn sRet","def exportImg(self):\n if self.superSampling:\n print(\"Exporting with size adjusted\")\n self.img = self.img.resize((int(self.width/2),int(self.height/2)),Image.NEAREST)\n self.img.save(self.fileName,\"PNG\")","def preprocess(img_name, quality=None):\n img = plt.imread(img_name)\n Y, X, C = img.shape\n img = img[:Y-Y%2, :X-X%2, :3]\n if quality is not None:\n img = jpeg_compress(img, quality)\n img = img_to_tensor(img).cuda().type(torch.float)\n return img","def convert_image(\n png_image: str, jpeg_image_quality: int = IMAGE_QUALITY_JPEG\n) -> str:\n img_rgb: Image.Image = Image.open(\n BytesIO(base64.b64decode(png_image))\n ).convert(\"RGB\")\n buffered: BytesIO = BytesIO()\n img_rgb.save(buffered, format=\"JPEG\", quality=jpeg_image_quality)\n jpeg_image_base64: str = base64.b64encode(buffered.getvalue()).decode(\n \"utf-8\"\n )\n\n return jpeg_image_base64","def img_recolor(self, args, input_image_path):\n \n ec = encoder.Encoder(output_path=args.intermediate_representation, method=args.method,\n size=args.size, p=args.p, grid_size=args.grid_size, plot=args.plot, quantize=args.quantize)\n dc = decoder.Decoder(output_path=args.output_path, method=args.method, size=args.size, p=args.p, gpu_id=args.gpu_id, plot=args.plot)\n\n ec.encode(input_image_path)\n img_gray_name = ar_utils.gen_new_gray_filename(input_image_path)\n img_gray_path = os.path.join(args.intermediate_representation, img_gray_name)\n dc.decode(img_gray_path)\n\n if args.delete_gray and os.path.exists(img_gray_path):\n os.remove(img_gray_path)","def PIL_to_bytes(img, ext: str = 'png', quality: int = None):\n bytes_io = io.BytesIO()\n if quality is not None:\n img.save(bytes_io, format=ext, quality=quality)\n else:\n subsampling = -1 if ext.lower() in ['jpg', 'jpeg'] else 0\n img.save(bytes_io, format=ext, quality=100, subsampling=subsampling)\n bytes_io.seek(0)\n return bytes_io","def convert_img(self):\r\n self.img = self.img.convert('RGB')","def jpeg_quantize(block: np.ndarray, option: model.QTables):\n t = table[option]\n return deadzone_quantize(block, t)","def convertImageToGrey(self):\n self.cnvImgTest.convertToGreyscale()","def extend_image(self):\n IJ.run(self.image, 'Select All', '')\n IJ.run(self.image, 'Copy', '')\n width = self.image.getWidth()\n height = int(self.image.getHeight() + self.extend_full)\n new_image = IJ.createImage(\n IMP.getTitle(), '32-bit black', width, height, 1)\n new_image.setRoi(0, 0, self.image.getWidth(), self.image.getHeight())\n IJ.run(new_image, 'Paste', '')\n IJ.run(new_image, 'Enhance Contrast', 'saturated=0.35')\n IJ.run(new_image, 'Select None', '')\n cal = Calibration(self.image)\n cal.pixelWidth = self.dispersion\n cal.xOrigin = self.offset\n new_image.setCalibration(cal)\n self.image = new_image\n return new_image","def convertImage(self):\n saveAs = config.get(\"saveFormat\")\n saveLocation = config.get(\"saveLocation\")\n image = Image.open(self.folderLocation.text())\n fileName = Path(image.filename).stem\n if saveAs == 'ico':\n size = 256, 256\n destPath = saveLocation+fileName+\".\"+saveAs\n im = Image.open(self.folderLocation.text())\n im.thumbnail(size)\n im.save(destPath, 'jpeg')\n else:\n image.save(saveLocation+fileName+\".\"+saveAs, saveAs)","def prepare_image(im):\n width, height = im.size\n if width > 256 or height > 256:\n factor = 256.0 / max(width, height)\n im = im.resize((int(factor * width), int(factor * height)),\n Image.BILINEAR)\n return im","def convert_to_jpg_then_compress(self):\n\t\tself._compressed_file_name = 'c_' + self.file_name\n\t\tself._compressed_save_path = self.full_path.replace(self.file_name, self._compressed_file_name).replace('.png', '.jpg')\n\n\t\timage = Image.open(self.full_path)\n\t\timage.save(self._compressed_save_path)\n\n\t\timage = Image.open(self._compressed_save_path)\n\t\timage.save(self._compressed_save_path, quality=85, progressive=False)\n\n\t\tself._compressed_file_size = ufo.get_file_size_in_bytes(self._compressed_save_path)\n\n\t\ttransfer_path = self._compressed_save_path.replace('c_' + self.file_name, self.file_name).replace('/configuration_files/', '/quasar_site_django/')\n\t\tufo.copy_file_to_path(self._compressed_save_path, transfer_path)","def convert(dir_path, table, dataset, quality, test_case):\n final_path = dir_path.joinpath(\"images\")\n if test_case:\n size = 20\n else:\n size = len(table)\n for i in tqdm(range(size)):\n img = Image.fromarray(table[i])\n if dataset == 1:\n img = img.convert(\"L\")\n nom = final_path.joinpath(str(i) + \".jpg\")\n img.save(nom, quality=quality)","def convert_to_image(self, frame, base64_encode=False):\n #NOTE: tuple (85010, 1) ndarray --> data reduction\n img_buf_arr = cv2.imencode(\".jpeg\", frame)[1]\n if base64_encode:\n img_buf_arr = b\"data:image/jpeg;base64,\" + base64.b64encode(img_buf_arr)\n return img_buf_arr\n return bytes(img_buf_arr)","def save_barcode_to_pillow(self, scale_x=1, scale_y=1):\n\n # creating a black and while 1-BIT image\n # note: if you have problems with 1-BIT images\n # select image type \"L\" and set color=255 for a greyscale image\n\n im = Image.new('1',\n (int(self.barcode_array['num_cols']),\n int(self.barcode_array['num_rows'])),\n color=1)\n\n # note: the generated barcode array is inverse, \"1\" is black, \"0\" is white.\n\n pixels = im.load()\n for r in xrange(int(self.barcode_array['num_rows'])):\n for c in xrange(int(self.barcode_array['num_cols'])):\n if self.barcode_array['bcode'][r][c] == \"1\":\n pixels[c, r] = 0\n\n if scale_x != 1 or scale_y != 1:\n im = im.resize(\n (scale_x * int(self.barcode_array['num_cols']),\n scale_y * int(self.barcode_array['num_rows'])))\n\n return im","def imageprepare(self,argv):\r\n\t\tim = Image.open(argv).convert('L')\r\n\t\twidth = float(im.size[0])\r\n\t\theight = float(im.size[1])\r\n\t\tnewImage = Image.new('L', (28, 28), (255)) # creates white canvas of 28x28 pixels\r\n\r\n\t\tif width > height: # check which dimension is bigger\r\n\t\t\t# Width is bigger. Width becomes 20 pixels.\r\n\t\t\tnheight = int(round((20.0 / width * height), 0)) # resize height according to ratio width\r\n\t\t\tif nheight == 0: # rare case but minimum is 1 pixel\r\n\t\t\t\tnheight = 1\r\n\t\t\t\t# resize and sharpen\r\n\t\t\timg = im.resize((20, nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\r\n\t\t\twtop = int(round(((28 - nheight) / 2), 0)) # caculate horizontal pozition\r\n\t\t\tnewImage.paste(img, (4, wtop)) # paste resized image on white canvas\r\n\t\telse:\r\n\t\t\t# Height is bigger. Heigth becomes 20 pixels.\r\n\t\t\tnwidth = int(round((20.0 / height * width), 0)) # resize width according to ratio height\r\n\t\t\tif (nwidth == 0): # rare case but minimum is 1 pixel\r\n\t\t\t\tnwidth = 1\r\n\t\t\t\t# resize and sharpen\r\n\t\t\timg = im.resize((nwidth, 20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\r\n\t\t\twleft = int(round(((28 - nwidth) / 2), 0)) # caculate vertical pozition\r\n\t\t\tnewImage.paste(img, (wleft, 4)) # paste resized image on white canvas\r\n\r\n\t\t# newImage.save(\"sample.png\")\r\n\r\n\t\ttv = list(newImage.getdata()) # get pixel values\r\n\r\n\t\t# normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\r\n\t\ttva = [(255 - x) * 1.0 / 255.0 for x in tv]\r\n\t\treturn tva","def imageprepare(argv):\n im = Image.open(argv).convert('L')\n width = float(im.size[0])\n height = float(im.size[1])\n newImage = Image.new('L', (28, 28), (255)) # creates white canvas of 28x28 pixels\n\n if width > height: # check which dimension is bigger\n # Width is bigger. Width becomes 20 pixels.\n nheight = int(round((20.0 / width * height), 0)) # resize height according to ratio width\n if (nheight == 0): # rare case but minimum is 1 pixel\n nheight = 1\n # resize and sharpen\n img = im.resize((20, nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\n wtop = int(round(((28 - nheight) / 2), 0)) # calculate horizontal position\n newImage.paste(img, (4, wtop)) # paste resized image on white canvas\n else:\n # Height is bigger. Heigth becomes 20 pixels.\n nwidth = int(round((20.0 / height * width), 0)) # resize width according to ratio height\n if (nwidth == 0): # rare case but minimum is 1 pixel\n nwidth = 1\n # resize and sharpen\n img = im.resize((nwidth, 20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\n wleft = int(round(((28 - nwidth) / 2), 0)) # caculate vertical pozition\n newImage.paste(img, (wleft, 4)) # paste resized image on white canvas\n\n # newImage.save(\"sample.png\n\n tv = list(newImage.getdata()) # get pixel values\n\n # normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\n tva = [(255 - x) * 1.0 / 255.0 for x in tv]\n print(tva)\n return tva","def downsample(self, hr_img):\r\n lr_img = hr_img.resize((int(hr_img.width / self.scaling_factor), int(hr_img.height / self.scaling_factor)),\r\n Image.BICUBIC)\r\n # Convert the LR and HR image to the required type\r\n lr_img = convert_image(lr_img, source='pil', target=self.lr_img_type)\r\n hr_img = convert_image(hr_img, source='pil', target=self.hr_img_type)\r\n return lr_img, hr_img","def img_prep(img, shape=(128, 128)):\n # Resize\n img = resize_volume(img, (shape[0], shape[1]))\n\n img = numpy.multiply(255, _normalize(img)).astype(numpy.uint8)\n\n return img","def new(self, fmt='JPEG', quality=70):\n canvas = Image.new(\n self._mode,\n (self._width,\n self._height),\n self._bg_color)\n drawer = ImageDraw.Draw(canvas)\n verify_code = self.drawtext(drawer)\n self.noisy(drawer)\n self.blur(canvas)\n self.line(drawer, canvas)\n buf = StringIO.StringIO()\n canvas.save(buf, fmt, quality=quality)\n return buf, verify_code","def image_to_scratch(im, scratch_image_name):\n\tim.save(scratch_image_name, dpi=(200,200))","def convert_frames(frame, img_format: str, scale=None) -> bytes:\n\n path = frame.filename\n\n with open(path, \"rb\") as image_file:\n im = Image.open(image_file)\n converted_img = BytesIO()\n if scale:\n _LOGGER.debug(\"Scaling the image\")\n (width, height) = (int(im.width * scale), int(im.height * scale))\n _LOGGER.debug(\"Original size is {}wx{}h, new size is {}wx{}h\".format(im.width, im.height, width, height))\n im = im.resize([width, height])\n im.save(converted_img, img_format)\n return converted_img.getvalue()","def _build_final_image(self, image):\n raise NotImplementedError","def convert_png_image_to_webp(png, out, quality=80):\n command = [CWEBP, '-q', str(quality), png, '-o', out]\n run_subprocess(command)","def save_to_image_file(self, filename, image_format='png', scale_x=1, scale_y=1):\n\n self.save_barcode_to_pillow(scale_x=scale_x, scale_y=scale_y).save(filename,\n format=image_format)","def image_quality(self, image_quality):\n\n self._image_quality = image_quality","def convertFrame(self):\r\n try:\r\n height, width = self.currentFrame.shape[:2]\r\n img = QtGui.QImage(self.currentFrame,\r\n width,\r\n height,\r\n QtGui.QImage.Format_RGB888)\r\n img = QtGui.QPixmap.fromImage(img)\r\n self.previousFrame = self.currentFrame\r\n return img\r\n except:\r\n return None","def imageprepare(argv):\r\n im = Image.open(argv).convert('L')\r\n width = float(im.size[0])\r\n height = float(im.size[1])\r\n newImage = Image.new('L', (28, 28), (255)) #creates white canvas of 28x28 pixels\r\n \r\n if width > height: #check which dimension is bigger\r\n #Width is bigger. Width becomes 20 pixels.\r\n nheight = int(round((20.0/width*height),0)) #resize height according to ratio width\r\n if (nheight == 0): #rare case but minimum is 1 pixel\r\n nheight = 1 \r\n # resize and sharpen\r\n img = im.resize((20,nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\r\n wtop = int(round(((28 - nheight)/2),0)) #caculate horizontal pozition\r\n newImage.paste(img, (4, wtop)) #paste resized image on white canvas\r\n else:\r\n #Height is bigger. Heigth becomes 20 pixels. \r\n nwidth = int(round((20.0/height*width),0)) #resize width according to ratio height\r\n if (nwidth == 0): #rare case but minimum is 1 pixel\r\n nwidth = 1\r\n # resize and sharpen\r\n img = im.resize((nwidth,20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\r\n wleft = int(round(((28 - nwidth)/2),0)) #caculate vertical pozition\r\n newImage.paste(img, (wleft, 4)) #paste resized image on white canvas\r\n \r\n #newImage.save(\"sample.png\")\r\n\r\n tv = list(newImage.getdata()) #get pixel values\r\n \r\n #normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\r\n tva = [ (255-x)*1.0/255.0 for x in tv] \r\n #print(tva)\r\n return tva","def quant_image(self, image=None, dst=None, ndeep=None, ndigits=None, override=True, delete=True):\n # Check Whether Pngquant Exist\n if not self.file_exists(self.quant_file):\n raise ValueError(self.err_pngquant)\n\n # Check Whether Image Exist\n if not self.file_exists(image):\n raise ValueError(self.err_image)\n\n # Compress Image By Call Function quant_data\n # Dst Should Pass Image When Override Origin Image\n return self.quant_data(self.open_file(image), dst=dst or (override and image), ndeep=ndeep, ndigits=ndigits, delete=delete)","def nn_resample_image(image_path, pxl_box_width, pxl_box_height):\n image = Image.open(image_path)\n if image.format == \"JPEG\" or image.format == \"PNG\":\n __nn_resample_png_jpeg_image(image, pxl_box_width, pxl_box_height)\n elif image.format == \"GIF\":\n __nn_resample_gif_image(image, pxl_box_width, pxl_box_height)\n\n return image","def generate_fit_image(self):\n if self.fit_mode == \"stretch\":\n return self.im.resize((self.width, self.height))\n else:\n raise NotImplementedError(\"%s: This fit mode doesn't exist\" % self.fit_mode)","def downsample_image(img, output_path, ratio=2):\n assert ratio>=1, ratio\n if ratio == 1:\n return True\n old_im = Image.open(img)\n old_size = old_im.size\n new_size = (int(old_size[0]/ratio), int(old_size[1]/ratio))\n\n new_im = old_im.resize(new_size, PIL.Image.LANCZOS)\n new_im.save(output_path)\n return True","def convertFrame(self):\n try:\n height,width=self.currentFrame.shape[:2]\n img=QtGui.QImage(self.currentFrame,\n width,\n height,\n QtGui.QImage.Format_RGB888)\n img=QtGui.QPixmap.fromImage(img)\n self.previousFrame = self.currentFrame\n return img\n except:\n return None","def prepare(img,\n resize=False, new_size=(64, 64),\n apply_contrast=False, contrast_channels=(0, 1, 2)\n ):\n new_img = crop(img)\n\n if resize:\n new_img = cv2.resize(new_img, new_size)\n\n if apply_contrast:\n new_img = increase_contrast(new_img, channels=contrast_channels)\n\n return new_img","def prepare_image(img):\n img = img.filter(ImageFilter.SMOOTH_MORE)\n img = img.filter(ImageFilter.SMOOTH_MORE)\n if 'L' != img.mode:\n img = img.convert('L')\n return img","def imageprepare(filename):\n img = Image.open(filename).convert('L')\n rect = img.getbbox()\n im = img.crop(rect)\n im.save(filename + '_pressprocessed.png')\n\n width = float(im.size[0])\n height = float(im.size[1])\n newImage = Image.new('L', (28, 28), (0)) #creates white canvas of 28x28 pixels\n if width > height: #check which dimension is bigger\n #Width is bigger. Width becomes 20 pixels.\n nheight = int(round((20.0/width*height),0)) #resize height according to ratio width\n if (nheight == 0): #rare case but minimum is 1 pixel\n nheight = 1\n # resize and sharpen\n img = im.resize((20,nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\n wtop = int(round(((28 - nheight)/2),0)) #caculate horizontal pozition\n newImage.paste(img, (4, wtop)) #paste resized image on white canvas\n newImage.save(filename + '_final.png')\n else:\n #Height is bigger. Heigth becomes 20 pixels. \n nwidth = int(round((20.0/height*width),0)) #resize width according to ratio height\n if (nwidth == 0): #rare case but minimum is 1 pixel\n nwidth = 1\n # resize and sharpen\n img = im.resize((nwidth,20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\n wleft = int(round(((28 - nwidth)/2),0)) #caculate vertical pozition\n newImage.paste(img, (wleft, 4)) #paste resized image on white canvas\n newImage.save(filename + '_final.png')\n tv = list(newImage.getdata()) #get pixel values\n #normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\n tva = [ (x)*1.0/255.0 for x in tv] \n return tva","def process_image(image):\n image = resize(image)\n return image","def __make_png(self, abspath_img_rgb):\n if not os.path.exists(DIR_PNG):\n os.makedirs(DIR_PNG)\n\n outsize = '{}%'.format(OUTSIZE_RGB)\n img_name_rgb = os.path.basename(abspath_img_rgb)\n suffix_extension_tif = Utils.get_suffix_tif(img_name_rgb)\n img_png = img_name_rgb.replace(suffix_extension_tif, '.png')\n path_img_png = os.path.join(DIR_PNG, img_png)\n\n command = \"gdal_translate -ot byte -of PNG -outsize {} {} \" \\\n \"-a_nodata 0 -q {} {}\".format(\n outsize, outsize, abspath_img_rgb, path_img_png\n )\n os.system(command)\n return os.path.join(DIR_PNG_TO_DB, img_png)","def upscale_pre(user_select):\n global result_img\n global pixel_buff\n print('=======================================')\n print('Starting upscale...')\n input_img_x, input_img_y = working_img.size\n working_img_mode = working_img.mode\n output_img = Image.new(working_img_mode, (input_img_x*2, input_img_y*2))\n outputx, outputy = output_img.size\n print(f'outputx set:{outputx} outputy set:{outputy}')\n if working_img_mode == \"RBGA\":\n pixel_buff = (0, 0, 0, 0)\n else:\n pixel_buff = (0, 0, 0)\n print('Making space...')\n #Inserting input image pixel and black pixel\n ix = iy = 0\n for oy in range(0, outputy, 2):\n for ox in range(0, outputx):\n if ox % 2 != 1:\n output_img.putpixel((ox, oy), working_img.getpixel((ix,iy)))\n ix += 1\n else:\n output_img.putpixel((ox, oy), pixel_buff)\n if ix == input_img_x:\n ix = 0\n #print(f'pixel:{ix, iy} input:{working_img.getpixel((ix,iy))} / pixel:{ox, oy} output:{output_img.getpixel((ox,oy))}')\n iy += 1\n #Inserting Black line\n ix = iy = 0\n for oy in range(1, outputy, 2):\n for ox in range(0, outputx):\n output_img.putpixel((ox, oy), pixel_buff)\n #print(f'pixel:{ix, iy} input:{working_img.getpixel((ix,iy))} / pixel:{ox, oy} output:{output_img.getpixel((ox,oy))}')\n return output_img","def img_to_pixmap(img, scale=1.0, code=\"rgb\"):\n if code.lower() == \"rgb\":\n img_format = QImage.Format_RGB888\n bytes_per_pixel = 3 # For RGB\n elif code.lower() == \"bgr\":\n img_format = QImage.Format_BGR888\n bytes_per_pixel = 3 # for bgr\n elif code.lower() == \"rgba\":\n img_format = QImage.Format_RGBA8888\n bytes_per_pixel = 4\n else:\n img_format = QImage.Format_Grayscale8\n bytes_per_pixel = 1\n # Need to fix the problem with background\n qimg = QImage(img, img.shape[1], img.shape[0],\n img.shape[1] * bytes_per_pixel,\n img_format)\n width = img.shape[1]\n height = img.shape[0]\n w_ = int(width * scale)\n h_ = int(height * scale)\n if w_ > h_:\n pix = QPixmap.fromImage(qimg).scaledToWidth(\n w_, mode=Qt.SmoothTransformation)\n else:\n pix = QPixmap.fromImage(qimg).scaledToHeight(\n h_, mode=Qt.SmoothTransformation)\n return pix, (w_, h_)","def _test_img_resize(self, backend):\n # Check quality setting unaffected by new parameter\n im_95_qual = backend.resize(\n 225,\n self.IMG_225x225,\n quality=95,\n max_filesize=0,\n )\n # check valid path returned - max_filesize hasn't broken resize command\n self.assertExists(im_95_qual)\n\n # Attempt a lower filesize with same quality\n im_a = backend.resize(\n 225,\n self.IMG_225x225,\n quality=95,\n max_filesize=0.9 * os.stat(syspath(im_95_qual)).st_size,\n )\n self.assertExists(im_a)\n # target size was achieved\n self.assertLess(os.stat(syspath(im_a)).st_size,\n os.stat(syspath(im_95_qual)).st_size)\n\n # Attempt with lower initial quality\n im_75_qual = backend.resize(\n 225,\n self.IMG_225x225,\n quality=75,\n max_filesize=0,\n )\n self.assertExists(im_75_qual)\n\n im_b = backend.resize(\n 225,\n self.IMG_225x225,\n quality=95,\n max_filesize=0.9 * os.stat(syspath(im_75_qual)).st_size,\n )\n self.assertExists(im_b)\n # Check high (initial) quality still gives a smaller filesize\n self.assertLess(os.stat(syspath(im_b)).st_size,\n os.stat(syspath(im_75_qual)).st_size)","def grocepre(img):\n img_prepro = pre.get_grayscale(img)\n img_prepro = pre.remove_noise(img_prepro)\n img_prepro = pre.dilate(img_prepro)\n img_prepro = pre.erode(img_prepro)\n img_prepro = pre.opening(img_prepro)\n img_prepro = pre.thresholding(img_prepro)\n\n return img_prepro","def handle_image(name):\n from_path = args.from_dir + name\n to_path = args.to_dir + name\n\n if width != args.width:\n subprocess.call('jpegtran -rotate 90 -grayscale ' + from_path + ' > ' \\\n + to_path, shell=True)\n else:\n subprocess.call('jpegtran -grayscale ' + from_path + ' > ' + to_path,\\\n shell=True)","def _create_image(self):\n if hasattr(self, '_image') and self._image:\n return self._image\n try:\n command = \"tex2im -b transparent -t cyan\"\n subprocess.run([*command.split(), self._formula])\n except Exception as e:\n import traceback\n print(traceback.format_exc())\n return None\n # tex2im converts to out.png by default\n img = Image.open('out.png').convert('RGBA')\n # create a new rgba image to blend the latex with the alpha\n subprocess.run([\"rm\", \"out.png\"])\n return img","def generateScaled(img):\n\n if not img._scaledfn:\n return\n\n aimgfn = join(opts.root, img._filename)\n if not opts.fast:\n img._size = imageSize(aimgfn)\n\n ascaledfn = join(opts.root, img._scaledfn)\n\n if opts.scaled_force:\n if opts.quiet: print \"forced regeneration of '%s'\" % img._scaledfn\n elif not exists(ascaledfn):\n if opts.quiet: print \"thumbnail absent '%s'\" % img._scaledfn\n else:\n # Check if scaledsize has changed\n if not opts.fast:\n img._scaledsize = imageSize(ascaledfn)\n if not checkThumbSize(img._size, \\\n img._scaledsize, \\\n opts.scaled_size):\n if opts.quiet: print \"thumbnail '%s size has changed\" % img._scaledfn\n try:\n # Clear cache for thumbnail size.\n del imageSizeCache[ ascaledfn ]\n except:\n pass\n else:\n if opts.quiet: print \"thumbnail '%s' already generated (size ok)\" \\\n % img._scaledfn\n return\n else:\n if opts.quiet: print \"thumbnail '%s' already generated\" % img._scaledfn\n return\n\n if opts.no_magick:\n if opts.quiet: print \"ImageMagick tools disabled, can't create thumbnail\"\n return\n\n # create necessary directories\n d = dirname(ascaledfn)\n if not exists(d):\n os.makedirs(d)\n\n if opts.pil:\n\n try:\n im = PilImage.open(aimgfn)\n im.thumbnail((opts.scaled_size, opts.scaled_size), config.ScaledImages[\"Interpolation\"])\n im.save(ascaledfn)\n\n img._scaledsize = im.size\n except IOError, e:\n raise SystemExit(\\\n \"Error: identifying file '%s'\" % aimgfn + str(e))\n\n else:\n\n cmd = getMagickProg('convert') + ' -border 2x2 '\n # FIXME check if this is a problem if not specified\n #cmd += '-interlace NONE '\n\n cmd += '-geometry %dx%d ' % (opts.scaled_size, opts.scaled_size)\n\n if opts.scaled_quality:\n cmd += '-quality %d ' % opts.scaled_quality\n\n # This doesn't add text into the picture itself, just the comment in\n # the header.\n if opts.copyright:\n cmd += '-comment \\\"%s\\\" ' % opts.copyright\n\n # We use [1] to extract the thumbnail when there is one.\n # It is harmless otherwise.\n subimg = \"\"\n if img._ext.lower() in [ \".jpg\", \".tif\", \".tiff\" ]:\n subimg = \"[1]\"\n\n cmd += '\"%s%s\" \"%s\"' % (aimgfn, subimg, ascaledfn)\n\n if opts.quiet: print \"generating thumbnail '%s'\" % img._scaledfn\n\n (chin, chout, cherr) = os.popen3(cmd)\n errs = cherr.readlines()\n chout.close()\n cherr.close()\n if errs:\n print >> sys.stderr, \\\n \"Error: running convert program on %s:\" % aimgfn\n errs = string.join(errs, '\\n')\n print errs\n\n if subimg and \\\n re.compile('Unable to read subimage').search(errs):\n if opts.quiet: print \"retrying without subimage\"\n cmd = string.replace(cmd, subimg, \"\")\n\n (chin, chout, cherr) = os.popen3(cmd)\n errs = cherr.readlines()\n chout.close()\n cherr.close()\n if errs:\n print >> sys.stderr, \\\n \"Error: running convert program on %s:\" % aimgfn\n print string.join(errs, '\\n')\n\n else:\n img._scaledsize = imageSize(ascaledfn)","def convert_image_to_QTformat(self, image):\n image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n convertToQtFormat = QImage(image.data, image.shape[1], image.shape[0], QImage.Format_RGB888)\n qt_image = convertToQtFormat.scaled(500, 375, Qt.KeepAspectRatio)\n return qt_image","def encode_png(track_metadata):\n\tprint(\"---- Encoding\", track_metadata.file_name, \"to PNG...\")\n\n\t# First step: OptiPNG.\n\tnew_file_name = track_metadata.file_name + \".png\"\n\toptipng_command = [\"optipng\", \"-o7\", \"-strip\", \"all\", \"-snip\", \"-out\", new_file_name, track_metadata.file_name]\n\tprint(optipng_command)\n\tprocess = subprocess.Popen(optipng_command, stdout=subprocess.PIPE)\n\t(cout, cerr) = process.communicate()\n\texit_code = process.wait()\n\tif exit_code != 0: #0 is success.\n\t\traise Exception(\"OptiPNG failed with exit code {exit_code}. CERR: {cerr}\".format(exit_code=exit_code, cerr=cerr))\n\n\tect_command = [\"/home/ruben/encoding/Efficient-Compression-Tool/build/ect\", \"-9\", \"-strip\", \"--allfilters-b\", \"--mt-deflate\", new_file_name]\n\tprint(ect_command)\n\tprocess = subprocess.Popen(ect_command, stdout=subprocess.PIPE)\n\t(cout, cerr) = process.communicate()\n\texit_code = process.wait()\n\tif exit_code != 0: #0 is success.\n\t\traise Exception(\"ECT failed with exit code {exit_code}. CERR: {cerr}\".format(exit_code=exit_code, cerr=cerr))\n\n\t#Delete old file.\n\tif os.path.exists(track_metadata.file_name):\n\t\tos.remove(track_metadata.file_name)\n\n\ttrack_metadata.file_name = new_file_name\n\ttrack_metadata.codec = \"png\"","def quantize(im_orig, n_quant, n_iter):\n if im_orig.ndim == RGB_DIM:\n # Quantize only Y channel.\n im_yiq = rgb2yiq(im_orig)\n result = __gray_quantize(im_yiq[:, :, Y_CHANNEL], n_quant, n_iter)\n im_yiq[:, :, Y_CHANNEL] = result[IMAGE_LOCATION]\n\n # Convert back to RGB space.\n result[IMAGE_LOCATION] = yiq2rgb(im_yiq)\n return result\n # Otherwise, just quantize.\n return __gray_quantize(im_orig, n_quant, n_iter)","def compression_jpeg(img: np.ndarray, quality=20):\n \n imgtype = img.dtype\n if img.ndim >= 3:\n img_channels = img.shape[2]\n elif img.ndim == 2:\n img_channels = 1\n\n #encoding parameters\n encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), quality]\n # encode\n is_success, encimg = cv2.imencode('.jpg', img, encode_param) \n \n # decode\n jpeg_img = cv2.imdecode(encimg, 1)\n \n # fix for grayscale images\n if jpeg_img.ndim == 3 and jpeg_img.shape[2] != img_channels:\n jpeg_img = jpeg_img[:,:,1]\n\n if jpeg_img.ndim != 3:\n jpeg_img = jpeg_img[..., np.newaxis]\n \n return jpeg_img.astype(imgtype)","def mozjpeg(ext_args, root=None):\n args = copy.copy(_MOZJPEG_ARGS)\n if Settings.destroy_metadata:\n args += [\"-copy\", \"none\"]\n else:\n args += [\"-copy\", \"all\"]\n if Settings.jpegtran_prog:\n args += [\"-progressive\"]\n\n args += ['-outfile']\n args += [ext_args.new_filename, ext_args.old_filename]\n if test:\n print(\"mozjpeg: \", args)\n return 0\n\n extern.run_ext(args, root)\n return _JPEG_FORMAT","def to_qt_pixmap(self, scale=None):\n bytes_per_line = 3 * self.width\n img = self.to_color().img\n rgb = opencv.cvtColor(img, opencv.COLOR_BGR2RGB)\n q_img = QImage(rgb.data, self.width, self.height, bytes_per_line, QImage.Format_RGB888)\n pixmap = QPixmap.fromImage(q_img)\n\n if scale is not None:\n pixmap = pixmap.scaled(scale, QtCore.Qt.KeepAspectRatio, QtCore.Qt.SmoothTransformation)\n\n return pixmap","def __create_base_shap_img(self):\n\n self.img = 255 * np.ones([1680, 1680, 3], dtype=np.uint8)\n self.baseline_scale_img = cv2.imread(self.scale_img_dict[\"baseline_scale\"])\n self.baseline_scale_top_left = (100, 800)\n baseline_scale_bottom_right = (\n self.baseline_scale_top_left[0] + self.baseline_scale_img.shape[0],\n self.baseline_scale_top_left[1] + self.baseline_scale_img.shape[1],\n )\n baseline_scale_middle = ((int(700 + self.baseline_scale_img.shape[1] / 2)), 85)\n self.img[\n self.baseline_scale_top_left[0] : baseline_scale_bottom_right[0],\n self.baseline_scale_top_left[1] : baseline_scale_bottom_right[1],\n ] = self.baseline_scale_img\n cv2.putText(\n self.img,\n \"BASELINE SHAP\",\n baseline_scale_middle,\n cv2.FONT_HERSHEY_COMPLEX,\n 1,\n (0, 0, 0),\n 2,\n )\n\n self.small_arrow_img = cv2.imread(self.scale_img_dict[\"small_arrow\"])\n small_arrow_top_left = (\n baseline_scale_bottom_right[0],\n int(\n self.baseline_scale_top_left[1]\n + (self.baseline_scale_img.shape[1] / 100) * (self.shap_baseline_value)\n ),\n )\n small_arrow_bottom_right = (\n small_arrow_top_left[0] + self.small_arrow_img.shape[0],\n small_arrow_top_left[1] + self.small_arrow_img.shape[1],\n )\n self.img[\n small_arrow_top_left[0] : small_arrow_bottom_right[0],\n small_arrow_top_left[1] : small_arrow_bottom_right[1],\n ] = self.small_arrow_img\n\n self.color_bar_img = cv2.imread(self.scale_img_dict[\"color_bar\"])\n\n side_scale_img = cv2.imread(self.scale_img_dict[\"side_scale\"])\n side_scale_top_left = (\n small_arrow_bottom_right[0] + 50,\n self.baseline_scale_top_left[1] - 50,\n )\n self.side_scale_y_tick_cords = [\n (side_scale_top_left[0], side_scale_top_left[1] - 75)\n ]\n for i in range(1, 7):\n self.side_scale_y_tick_cords.append(\n (\n int(side_scale_top_left[0] + (side_scale_img.shape[0] / 4) * i),\n int(side_scale_top_left[1] - 75),\n )\n )\n self.arrow_start = (\n int(small_arrow_top_left[1] + (self.small_arrow_img.shape[1] / 2)),\n side_scale_top_left[0],\n )\n\n for img_cnt, (img_name, img_data) in enumerate(self.category_img_dict.items()):\n icon_img = cv2.resize(\n cv2.imread(img_data[\"icon\"]),\n None,\n fx=1.5,\n fy=1.5,\n interpolation=cv2.INTER_CUBIC,\n )\n icon_top_left = (\n self.side_scale_y_tick_cords[img_cnt][0] - int(icon_img.shape[0] / 2),\n self.side_scale_y_tick_cords[img_cnt][1] - 100,\n )\n icon_bottom_right = (\n icon_top_left[0] + icon_img.shape[0],\n self.side_scale_y_tick_cords[img_cnt][1] + icon_img.shape[1] - 100,\n )\n text_location = (\n int(\n icon_bottom_right[0]\n - (icon_bottom_right[0] - icon_top_left[0])\n + 100\n ),\n int(icon_bottom_right[1] - (icon_bottom_right[1] - icon_top_left[1]))\n - 380,\n )\n cv2.putText(\n self.img,\n str(img_name),\n (text_location[1], text_location[0]),\n cv2.FONT_HERSHEY_COMPLEX,\n 0.75,\n (0, 0, 0),\n 1,\n )\n self.img[\n icon_top_left[0] : icon_bottom_right[0],\n icon_top_left[1] : icon_bottom_right[1],\n ] = icon_img","def rescale_image_0255(image):\n # scale image to from [0.0, 1.0] to [0, 255]\n image *= 255\n return image.astype(np.uint8)","def prepare_test_img(self, idx):\n img_info = self.img_infos[idx]\n img_path = osp.join(self.img_prefix, img_info['filename'])\n\n if self.proposals is not None:\n proposal = self.proposals[idx][:self.num_max_proposals]\n if not proposal.shape[1] == 4 or proposal.shape[1] == 5:\n raise AssertionError(\n 'proposals should have shapes (n, 4) or (n, 5), '\n 'but found {}'.format(proposal.shape))\n else:\n proposal = None\n\n if self.with_background_erasing:\n ann = self.get_ann_info(idx)\n gt_bboxes = ann['bboxes']\n else:\n gt_bboxes = None\n\n def prepare_single_scale(img_path, expected_size, flip_ratio=0,\n proposal=None, bbox=None):\n _img, img_shape, pad_shape, scale_factor, \\\n flipped_flag, flipped_direction = self.img_transforms(\n img_path, expected_size, flip_ratio=flip_ratio)\n if bbox is not None:\n if not len(bbox) == 0:\n _gt_bboxes = self.bbox_transforms(bbox,\n img_shape,\n scale_factor,\n flipped_flag,\n flipped_direction)\n else:\n _gt_bboxes = bbox\n _img = self.background_erasing(\n _img, img_shape, _gt_bboxes,\n cell_size=self.be_cell_size,\n random_ratio=self.be_random_ratio)\n _img = to_tensor(_img)\n _img_meta = dict(\n filename=img_info['filename'],\n ori_shape=(img_info['height'], img_info['width'], 3),\n img_shape=img_shape,\n pad_shape=pad_shape,\n scale_factor=scale_factor,\n flipped_flag=flipped_flag,\n flipped_direction=flipped_direction\n )\n if proposal is not None:\n if proposal.shape[1] == 5:\n score = proposal[:, 4, None]\n proposal = proposal[:, :4]\n else:\n score = None\n _proposal = self.bbox_transforms(proposal,\n img_shape,\n scale_factor,\n flipped_flag,\n flipped_direction)\n _proposal = np.hstack([_proposal, score]) \\\n if score is not None else _proposal\n _proposal = to_tensor(_proposal)\n else:\n _proposal = None\n return _img, _img_meta, _proposal\n\n imgs = []\n img_metas = []\n proposals = []\n for expected_size in self.img_expected_sizes:\n # at first, we do not flip the image\n _img, _img_meta, _proposal = prepare_single_scale(\n img_path, expected_size, flip_ratio=0,\n proposal=proposal, bbox=gt_bboxes)\n imgs.append(_img)\n img_metas.append(DataContainer(_img_meta, cpu_only=True))\n proposals.append(_proposal)\n if self.flip_ratio > 0:\n _img, _img_meta, _proposal = prepare_single_scale(\n img_path, expected_size, flip_ratio=1,\n proposal=proposal, bbox=gt_bboxes)\n imgs.append(_img)\n img_metas.append(DataContainer(_img_meta, cpu_only=True))\n proposals.append(_proposal)\n data = dict(img=imgs, img_meta=img_metas)\n if self.proposals is not None:\n data['proposals'] = proposals\n return data","def save_subpix_png(path, img, scale_factor=256.0):\n Path(path).parent.mkdir(parents=True, exist_ok=True)\n img = img.astype(np.float32) * scale_factor\n if np.amax(img) > (2**16)-1:\n warnings.warn(\"image out of range(\" + str(np.amax(img)/scale_factor) +\n \"), try with a smaller scale factor. loading this file \" +\n \"will results in invalid values, file: \"+str(path))\n img[img > (2**16)-1] = 0\n img = img.astype(np.uint16)\n cv2.imwrite(str(path), img)","def convert_image(image_path):\n with Image.open(image_path) as img:\n new_image = img.convert(\"RGBA\" if img.format == \"PNG\" else \"RGB\")\n new_image.save(image_path)","def turn_into_image(self):\n if self.title_colours:\n self.table_to_image = TableToImage(self.table.get_string(), self.colour, self.rows, self.titles,\n self.title_colours)\n else:\n self.table_to_image = TableToImage(self.table.get_string(), self.colour, self.rows)","def scale(input_img, size):\n width, height = size\n old_height, old_width = input_img.shape\n x_scale = float(height) / old_height\n y_scale = float(width) / old_width\n\n output_img = np.zeros((height, width), dtype=np.uint8)\n for xidx in xrange(height):\n old_x = float(xidx) / x_scale\n for yidx in xrange(width):\n old_y = float(yidx) / y_scale\n if old_x.is_integer() or old_y.is_integer():\n output_img[xidx, yidx] = input_img[int(old_x), int(old_y)]\n else: # use bilinear interpolation\n x1 = int(np.floor(old_x))\n x2 = int(np.ceil(old_x)) if int(np.ceil(old_x)) < old_height else old_height - 1\n y1 = int(np.floor(old_y))\n y2 = int(np.ceil(old_y)) if int(np.ceil(old_y)) < old_width else old_width - 1\n\n q11 = input_img[x1, y1]\n q12 = input_img[x1, y2]\n q21 = input_img[x2, y1]\n q22 = input_img[x2, y2]\n\n output_img[xidx, yidx] = (q11 * (x2 - old_x) * (y2 - old_y)\n + q21 * (old_x - x1) * (y2 - old_y)\n + q12 * (x2 - old_x) * (old_y - y1)\n + q22 * (old_x - x1) * (old_y - y1)) \\\n / ((x2 - x1) * (y2 - y1) + 1e-10)\n\n return output_img","def get_qpimage_raw(self, idx=0):\n # Load experimental data\n with h5py.File(self.path) as h5:\n holo = h5[\"0\"][:]\n qpi = qpimage.QPImage(data=holo,\n which_data=\"raw-oah\",\n meta_data=self.get_metadata(idx),\n qpretrieve_kw=self.qpretrieve_kw,\n h5dtype=self.as_type)\n return qpi","def create_jpg (filename):\n\n try:\n\n image_jpg = '{}.jpg'.format(filename.split('.fits')[0])\n\n if not isfile(image_jpg):\n\n log.info ('saving {} to {}'.format(filename, image_jpg))\n\n # read input image\n data, header = read_hdulist(filename, get_header=True)\n\n imgtype = header['IMAGETYP'].lower()\n file_str = image_jpg.split('/')[-1].split('.jpg')[0]\n if imgtype == 'object':\n title = ('file:{} object:{} filter:{} exptime:{:.1f}s '\n 'QC flag:{}'.format(file_str, header['OBJECT'],\n header['FILTER'], header['EXPTIME'],\n header['QC-FLAG']))\n else:\n title = ('file:{} imgtype:{} filter:{} QC flag:{}'\n .format(file_str, header['IMAGETYP'], header['FILTER'],\n header['QC-FLAG']))\n\n pixelcoords = True\n if pixelcoords:\n f = aplpy.FITSFigure(data)\n else:\n f = aplpy.FITSFigure(filename)\n\n vmin, vmax = zscale().get_limits(data)\n f.show_colorscale(cmap='gray', vmin=vmin, vmax=vmax)\n f.add_colorbar()\n f.set_title(title)\n #f.add_grid()\n #f.set_theme('pretty')\n f.save(image_jpg, adjust_bbox=False)\n f.close()\n\n\n except Exception as e:\n #log.exception (traceback.format_exc())\n log.exception ('exception was raised in creating jpg of image {}: {}'\n .format(filename,e))\n\n\n return image_jpg","def ff_correct_image(image):\n pass","def ff_correct_image(image):\n pass","def drawImage(self, QRectF, QImage, QRectF_1, Qt_ImageConversionFlags_flags=None): # real signature unknown; restored from __doc__\r\n pass","def pre_processing_image(img):\n\n #print(img.shape)\n # apply gamma correction and show the images\n #adjusted = adjust_gamma(img, gamma=0.65)\n\n adjusted = exposure.adjust_gamma(img, gamma=1.65)\n #print(adjusted.shape)\n\n # log transform of image\n\n logarithmic_corrected = exposure.adjust_log(adjusted, 1)\n #print(logarithmic_corrected.shape)\n\n # denoising\n #dst2 = cv2.fastNlMeansDenoisingColored(logarithmic_corrected, None, 10, 10, 7, 21)\n #print(dst2.shape)\n dst2 = logarithmic_corrected\n return dst2","def imageprepare(image_data):\n im = Image.open(io.BytesIO(image_data))\n im = remove_transparency(im)\n im = im.resize((28,28))\n width = float(im.size[0])\n height = float(im.size[1])\n new_image = Image.new('L', (28, 28), 255) # creates white canvas of 28x28 pixels\n\n if width > height: # check which dimension is bigger\n # Width is bigger. Width becomes 20 pixels.\n nheight = int(round((20.0 / width * height), 0)) # resize height according to ratio width\n if nheight == 0: # rare case but minimum is 1 pixel\n nheight = 1\n # resize and sharpen\n img = im.resize((20, nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\n wtop = int(round(((28 - nheight) / 2), 0)) # calculate horizontal position\n new_image.paste(img, (4, wtop)) # paste resized image on white canvas\n else:\n # Height is bigger. Heigth becomes 20 pixels.\n nwidth = int(round((20.0 / height * width), 0)) # resize width according to ratio height\n if nwidth == 0: # rare case but minimum is 1 pixel\n nwidth = 1\n # resize and sharpen\n img = im.resize((nwidth, 20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\n wleft = int(round(((28 - nwidth) / 2), 0)) # caculate vertical pozition\n new_image.paste(img, (wleft, 4)) # paste resized image on white canvas\n\n # new_image = ImageOps.invert(new_image)\n\n tv = list(new_image.getdata()) # get pixel values\n\n # normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\n tva = [(255 - x) * 1.0 / 255.0 for x in tv]\n return tva, new_image","def convert_cv_qt(self, cv_img):\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\n h, w, ch = rgb_image.shape\n bytes_per_line = ch * w\n convert_to_Qt_format = QtGui.QImage(\n rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\n display_width = 960\n display_height = 540\n p = convert_to_Qt_format.scaled(\n display_width, display_height, Qt.KeepAspectRatio)\n return QPixmap.fromImage(p)","def resize_img(self,scale=1):\n reduced = self.image.reduce((scale,scale))\n reduced.save(\"../edited/{}\".format(self.image.filename))\n\n reduced = Image.open(\"../edited/{}\".format(self.image.filename))\n return reduced","def pildumps(image, format=\"PNG\"):\n result = StringIO.StringIO()\n if image.dtype in [np.dtype('f'), np.dtype('d')]:\n assert np.amin(image) > -0.001 and np.amax(image) < 1.001\n image = np.clip(image, 0.0, 1.0)\n image = np.array(image * 255.0, 'uint8')\n PIL.Image.fromarray(image).save(result, format=format)\n return result.getvalue()","def convert_image(source, dest, out_format, run_as_root=False):\n cmd = ('qemu-img', 'convert', '-O', out_format, source, dest)\n utils.execute(*cmd, run_as_root=run_as_root)","def convert_cv_qt(self, cv_img):\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\n h, w, ch = rgb_image.shape\n bytes_per_line = ch * w\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\n p = convert_to_Qt_format.scaled(self.disply_width, self.display_height, ) #Qt.KeepAspectRatio\n return QPixmap.fromImage(p)","def convert_cv_qt(self, cv_img):\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\n h, w, ch = rgb_image.shape\n bytes_per_line = ch * w\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\n p = convert_to_Qt_format.scaled(self.disply_width, self.display_height, ) #Qt.KeepAspectRatio\n return QPixmap.fromImage(p)","def convert_cv_qt(self, cv_img):\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\n h, w, ch = rgb_image.shape\n bytes_per_line = ch * w\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\n p = convert_to_Qt_format.scaled(self.disply_width, self.display_height, ) #Qt.KeepAspectRatio\n return QPixmap.fromImage(p)","def embed_image_pred(image):\n image_pil2 = Image.fromarray((255 * image).astype('uint8'))\n #image_pil2 = image_pil.resize((256, 256))\n string_buf2 = StringIO.StringIO()\n image_pil2.save(string_buf2, format='png')\n data = string_buf2.getvalue().encode('base64').replace('\\n', '')\n return 'data:image/png;base64,' + data","def q_1(input_file, output_file):\n img = cv2.imread(input_file, cv2.IMREAD_COLOR)\n\n # Convert image to gray channel\n np_img = np.array(img)\n b = np_img[:,:,0]\n g = np_img[:,:,1]\n r = np_img[:,:,2]\n img_gray = 0.21 * b + 0.72 * g + 0.07 * r\n img_gray = np.array(img_gray, dtype='uint8')\n cv2.imwrite(output_file, img_gray)\n print(np_img)","def img_optimizer(image, s3bucket):\n try:\n s3client = boto3.client('s3', region_name=AWS_REGION)\n\n temp_ifile = '/tmp/tmp_ifile.jpg'\n\n with open(temp_ifile, 'wb') as data:\n s3client.download_fileobj(s3bucket, image, data)\n\n file_src = temp_ifile\n file_dst = file_src.split('.')[0] + '_.' + file_src.split('.')[1]\n\n img = Image.open(file_src)\n\n \"\"\"\n Applying downsampling antialias algorithm without actual resize gives 30-40% lower file size. \n Downsize with 0.97 aspect ratio gives up to 50% decrease. \n \"\"\"\n aspect = 0.97\n new_size = (int(float(img.size[0]) * float(aspect)), int(float(img.size[1]) * float(aspect)))\n\n new_img = img.resize(new_size, Image.ANTIALIAS)\n new_img.save(file_dst)\n piexif.transplant(file_src, file_dst)\n\n return 'SUCCESS', file_dst\n\n except Exception as err:\n print('Image optimization failed:', err)\n return 'FAILED', file_src","def jpeg_to_png(img: bytes) -> bytes:\n im = Image.open(BytesIO(img))\n width = 240\n height = int(im.size[1] * (240 / im.size[0]))\n im = im.convert(\"RGB\").resize((width, height))\n stream = BytesIO()\n im.save(stream, format=\"PNG\")\n return stream.getvalue()","def resize_img(img, STANDARD_SIZE, verbose=False):\n if verbose:\n print \"changing size from %s to %s\" % (str(img.size), str(STANDARD_SIZE))\n img = img.resize(STANDARD_SIZE)\n return img","def transform_image(self, image):\n\n image = self.image_processor.postprocess(image, output_type='pil')\n return image","def convertFrame(self):\n try:\n img = QImage(self.currentVideoFrame,\n self.currentVideoFrame.shape[1],\n self.currentVideoFrame.shape[0],\n QImage.Format_RGB888\n )\n return img\n except:\n return None","def convertFrame(self):\n try:\n img = QImage(self.currentVideoFrame,\n self.currentVideoFrame.shape[1],\n self.currentVideoFrame.shape[0],\n QImage.Format_RGB888\n )\n return img\n except:\n return None","def convert_cv_qt(self, cv_img):\n\t\trgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\n\t\th, w, ch = rgb_image.shape\n\t\tbytes_per_line = ch * w\n\t\tconvert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\n\n\t\tif w > 1000:\n\t\t\trat = w / 1000\n\t\t\tw = 1000\n\t\t\th = h / rat\n\n\t\tp = convert_to_Qt_format.scaled(int(w), int(h), Qt.KeepAspectRatio)\n\t\treturn QPixmap.fromImage(p)","def create_artificial_image(self):\n background = self.BGI.create_background_image()\n star_PSF = self.PSF.create_star_PSF()\n header = self.HDR.create_header()\n\n fits.writeto(self.image_dir + self.image_name + '.fits',\n background + star_PSF, overwrite=True, header=header)","def transform(self, previousimage):","def smaller(self):\n w1, h1 = float(self.imwidth), float(self.imheight)\n w2, h2 = float(self.__huge_size), float(self.__huge_size)\n aspect_ratio1 = w1 / h1\n aspect_ratio2 = w2 / h2 # it equals to 1.0\n if aspect_ratio1 == aspect_ratio2:\n image = Image.new('RGB', (int(w2), int(h2)))\n k = h2 / h1 # compression ratio\n w = int(w2) # band length\n elif aspect_ratio1 > aspect_ratio2:\n image = Image.new('RGB', (int(w2), int(w2 / aspect_ratio1)))\n k = h2 / w1 # compression ratio\n w = int(w2) # band length\n else: # aspect_ratio1 < aspect_ration2\n image = Image.new('RGB', (int(h2 * aspect_ratio1), int(h2)))\n k = h2 / h1 # compression ratio\n w = int(h2 * aspect_ratio1) # band length\n i, j, n = 0, 1, round(0.5 + self.imheight / self.__band_width)\n while i < self.imheight:\n print('\\rOpening image: {j} from {n}'.format(j=j, n=n), end='')\n band = min(self.__band_width, self.imheight - i) # width of the tile band\n self.__tile[1][3] = band # set band width\n self.__tile[2] = self.__offset + self.imwidth * i * 3 # tile offset (3 bytes per pixel)\n self.__image.close()\n self.__image = Image.open(self.path) # reopen / reset image\n self.__image.size = (self.imwidth, band) # set size of the tile band\n self.__image.tile = [self.__tile] # set tile\n cropped = self.__image.crop((0, 0, self.imwidth, band)) # crop tile band\n image.paste(cropped.resize((w, int(band * k) + 1), self.__filter), (0, int(i * k)))\n i += band\n j += 1\n print('\\r' + 30 * ' ' + '\\r', end='') # hide printed string\n return image","def preprocess(exam, data_folder, save_path, image_format):\n for v in ['L-CC', 'L-MLO', 'R-CC', 'R-MLO']:\n if len(exam[v]) == 0:\n continue\n else:\n for image in exam[v]:\n image_path = data_folder + '/' + image + '.' + image_format\n # Extract subdirectories\n subdirs = \"/\".join(image.split('/')[:-1])\n save_dirs = os.path.join(save_path, subdirs)\n # Extract image id\n image_id = image.split('/')[-1]\n # Create save directories\n os.makedirs(save_dirs, exist_ok=True)\n png_save_path = os.path.join(save_dirs, image_id + '.png')\n with Image(filename=image_path, format=image_format) as img:\n with img.clone() as i:\n i.auto_level()\n with i.convert('png') as png_image:\n png_image.transform(resize='896x1152!')\n png_image.save(filename=png_save_path)","def to_image(self, width=800, height=600, outline=20, background=\"white\", **kwargs):\n img = _rodframe_image(\n parameters=self.parameters,\n width=width,\n height=height,\n outline=outline,\n background=background,\n **kwargs\n )\n return img","def frame_to_pixmap(color_image): \r\n height, width, channel = color_image.shape\r\n bytes_per_line = channel * width\r\n\r\n q_img = QImage(color_image.data, width, height, bytes_per_line, QImage.Format_BGR888)\r\n return QPixmap.fromImage(q_img)","def convert_cv_qt(self, cv_img):\r\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\r\n h, w, ch = rgb_image.shape\r\n bytes_per_line = ch * w\r\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\r\n p = convert_to_Qt_format.scaled(self.disply_width, self.display_height, Qt.KeepAspectRatio)\r\n return QPixmap.fromImage(p)","def convert_cv_qt(self, cv_img):\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\n h, w, ch = rgb_image.shape\n bytes_per_line = ch * w\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\n p = convert_to_Qt_format.scaled(225, 220) # , Qt.KeepAspectRatio)\n return QPixmap.fromImage(p)","def jpegoptim(filename, quality=None, root=None):\n # jpegoptim - s - f - o - -all - progressive . / test.png\n args = copy.copy(_JPEGOPTIM_ARGS)\n if Settings.destroy_metadata:\n args += [\"-s\"]\n if Settings.force:\n args += [\"-f\"]\n if Settings.verbose:\n args += [\"-v\"]\n if quality:\n args += [\"-m {}\".format(quality)]\n if Settings.jpegtran_prog:\n args += [\"--all-progressive\"]\n\n args += [filename]\n if test:\n print(\"jpegoptim: \", args)\n return 0\n\n extern.run_ext(args, root)\n return _JPEG_FORMAT","def adjust(self, image):\n ...","def encode_scaled(data, size, version=0, level=QR_ECLEVEL_L, hint=QR_MODE_8,\n case_sensitive=True):\n version, src_size, im = encode(data, version, level, hint, case_sensitive)\n if size < src_size:\n size = src_size\n qr_size = (size / src_size) * src_size\n im = im.resize((qr_size, qr_size), Image.NEAREST)\n pad = (size - qr_size) / 2\n ret = Image.new(\"L\", (size, size), 255)\n ret.paste(im, (pad, pad))\n\n return (version, size, ret)","def saverescale(image, fname, outpath, scalefactor=0.5, preserve_name=False):\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"resize_{scalefactor}\")\n else:\n fpath = genSavePath(outpath, fname)\n newsize = (int(image.width * scalefactor), int(image.height * scalefactor))\n im = copy(image)\n im = im.resize(newsize)\n try:\n im.save(fpath, subsample=\"keep\", qtables=image.quantization, optimize=True)\n\n except IOError as m:\n print( \"Resize({}) image creation failed for: {}. \\nReason:{}\".format(scalefactor,fname,m))","def capture_image(self):\n ext = self.image_save_type.lower()\n\n if self.calibrating:\n print('calibrating')\n\n if ext == 'fits':\n self.save_fits()\n self._image_counter += 1\n else:\n img = self.original_image\n path = os.path.join(self.home, 'data')\n name = \"camtrak_frame_{}.png\".format(self._image_counter) \n fn = os.path.join(path, name)\n cv2.imwrite(fn, img)\n\n QtWidgets.QApplication.beep()\n self.statusBar().showMessage(f'Saved image to {fn}')\n self._image_counter += 1","def thumbnail(self, fnameIn, fnameOut):\n cmd = \"convert -define jpeg:size=500x150 \"\n cmd += '\"%s\" ' % os.path.join(self.downloadFolder, fnameIn)\n cmd += \"-auto-orient -thumbnail 250x150 \"\n cmd += '\"%s\" ' % os.path.join(self.thumbnailFolder, fnameOut)\n self.log(\"creating thumbnail ...\")\n self.log(cmd)\n process = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE)\n process.wait()","def image(self):\n # TODO: make sure this method works for png, gif, tiff\n if self.has_metadata:\n self.extract_metadata()\n tempdir_path = self.make_tempdir()\n tempfile_path = os.path.join(tempdir_path, self.filename)\n warnings.simplefilter('error', Image.DecompressionBombWarning)\n try: # Do image conversions\n img_in = Image.open(self.src_path)\n img_out = Image.frombytes(img_in.mode, img_in.size, img_in.tobytes())\n img_out.save(tempfile_path)\n self.src_path = tempfile_path\n except Exception as e: # Catch decompression bombs\n # TODO: change this from all Exceptions to specific DecompressionBombWarning\n self.add_error(e, \"Caught exception (possible decompression bomb?) while translating file {}.\".format(self.src_path))\n self.make_dangerous()\n self.add_file_string('Image file')\n self.set_property('processing_type', 'image')","def convert_cv_qt(self, cv_img):\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\n h, w, ch = rgb_image.shape\n bytes_per_line = ch * w\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\n p = convert_to_Qt_format.scaled(self.display_width, self.display_height, Qt.KeepAspectRatio)\n return QPixmap.fromImage(p)","def convert_cv_qt(self, cv_img):\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\n h, w, ch = rgb_image.shape\n bytes_per_line = ch * w\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\n p = convert_to_Qt_format.scaled(self.display_width, self.display_height, Qt.KeepAspectRatio)\n return QPixmap.fromImage(p)","def image(self):\r\n\r\n if sys.version < '3':\r\n imageio = StringIO.StringIO(self._image_data)\r\n else:\r\n imageio = StringIO.BytesIO(self._image_data)\r\n\r\n try:\r\n source_image = PILImage.open(imageio)\r\n img = PILImage.new('RGBA', source_image.size, (0, 0, 0, 0))\r\n\r\n if source_image.mode == 'L':\r\n alpha = source_image.split()[0]\r\n transparency = source_image.info.get('transparency')\r\n mask = PILImage.eval(alpha, lambda a: 0 if a == transparency else 255)\r\n img.paste(source_image, (0, 0), mask=mask)\r\n else:\r\n img.paste(source_image, (0, 0))\r\n except IOError, e:\r\n raise PILUnavailableError(e.args[0].split()[1])\r\n finally:\r\n imageio.close()\r\n\r\n self.original_width, self.original_height = img.size\r\n\r\n # Crop the image searching for the smallest possible bounding box\r\n # without losing any non-transparent pixel.\r\n # This crop is only used if the crop flag is set in the config.\r\n if self.config['crop']:\r\n img = img.crop(img.split()[-1].getbbox())\r\n return img"],"string":"[\n \"def convert_to_jpeg(image, quality=90):\\n\\n\\t# Load the image into a new BytesIO\\n\\tsImg = BytesIO(image)\\n\\n\\t# Create an empty BytesIO for the new image\\n\\tsNewImg = BytesIO(b'')\\n\\n\\t# Create a new Pillow instance from the raw data\\n\\toImg = Pillow.open(sImg)\\n\\n\\t# If the mode is not valid\\n\\tif oImg.mode not in ('1','L','RGB','RGBA'):\\n\\t\\toImg = oImg.convert('RGB');\\n\\n\\t# Save the new image as a JPEG\\n\\toImg.save(sNewImg, 'JPEG', quality=quality, subsampling=0)\\n\\n\\t# Pull out the raw string\\n\\tsRet = sNewImg.getvalue()\\n\\n\\t# Close the image\\n\\toImg.close()\\n\\n\\t# Return the new image\\n\\treturn sRet\",\n \"def exportImg(self):\\n if self.superSampling:\\n print(\\\"Exporting with size adjusted\\\")\\n self.img = self.img.resize((int(self.width/2),int(self.height/2)),Image.NEAREST)\\n self.img.save(self.fileName,\\\"PNG\\\")\",\n \"def preprocess(img_name, quality=None):\\n img = plt.imread(img_name)\\n Y, X, C = img.shape\\n img = img[:Y-Y%2, :X-X%2, :3]\\n if quality is not None:\\n img = jpeg_compress(img, quality)\\n img = img_to_tensor(img).cuda().type(torch.float)\\n return img\",\n \"def convert_image(\\n png_image: str, jpeg_image_quality: int = IMAGE_QUALITY_JPEG\\n) -> str:\\n img_rgb: Image.Image = Image.open(\\n BytesIO(base64.b64decode(png_image))\\n ).convert(\\\"RGB\\\")\\n buffered: BytesIO = BytesIO()\\n img_rgb.save(buffered, format=\\\"JPEG\\\", quality=jpeg_image_quality)\\n jpeg_image_base64: str = base64.b64encode(buffered.getvalue()).decode(\\n \\\"utf-8\\\"\\n )\\n\\n return jpeg_image_base64\",\n \"def img_recolor(self, args, input_image_path):\\n \\n ec = encoder.Encoder(output_path=args.intermediate_representation, method=args.method,\\n size=args.size, p=args.p, grid_size=args.grid_size, plot=args.plot, quantize=args.quantize)\\n dc = decoder.Decoder(output_path=args.output_path, method=args.method, size=args.size, p=args.p, gpu_id=args.gpu_id, plot=args.plot)\\n\\n ec.encode(input_image_path)\\n img_gray_name = ar_utils.gen_new_gray_filename(input_image_path)\\n img_gray_path = os.path.join(args.intermediate_representation, img_gray_name)\\n dc.decode(img_gray_path)\\n\\n if args.delete_gray and os.path.exists(img_gray_path):\\n os.remove(img_gray_path)\",\n \"def PIL_to_bytes(img, ext: str = 'png', quality: int = None):\\n bytes_io = io.BytesIO()\\n if quality is not None:\\n img.save(bytes_io, format=ext, quality=quality)\\n else:\\n subsampling = -1 if ext.lower() in ['jpg', 'jpeg'] else 0\\n img.save(bytes_io, format=ext, quality=100, subsampling=subsampling)\\n bytes_io.seek(0)\\n return bytes_io\",\n \"def convert_img(self):\\r\\n self.img = self.img.convert('RGB')\",\n \"def jpeg_quantize(block: np.ndarray, option: model.QTables):\\n t = table[option]\\n return deadzone_quantize(block, t)\",\n \"def convertImageToGrey(self):\\n self.cnvImgTest.convertToGreyscale()\",\n \"def extend_image(self):\\n IJ.run(self.image, 'Select All', '')\\n IJ.run(self.image, 'Copy', '')\\n width = self.image.getWidth()\\n height = int(self.image.getHeight() + self.extend_full)\\n new_image = IJ.createImage(\\n IMP.getTitle(), '32-bit black', width, height, 1)\\n new_image.setRoi(0, 0, self.image.getWidth(), self.image.getHeight())\\n IJ.run(new_image, 'Paste', '')\\n IJ.run(new_image, 'Enhance Contrast', 'saturated=0.35')\\n IJ.run(new_image, 'Select None', '')\\n cal = Calibration(self.image)\\n cal.pixelWidth = self.dispersion\\n cal.xOrigin = self.offset\\n new_image.setCalibration(cal)\\n self.image = new_image\\n return new_image\",\n \"def convertImage(self):\\n saveAs = config.get(\\\"saveFormat\\\")\\n saveLocation = config.get(\\\"saveLocation\\\")\\n image = Image.open(self.folderLocation.text())\\n fileName = Path(image.filename).stem\\n if saveAs == 'ico':\\n size = 256, 256\\n destPath = saveLocation+fileName+\\\".\\\"+saveAs\\n im = Image.open(self.folderLocation.text())\\n im.thumbnail(size)\\n im.save(destPath, 'jpeg')\\n else:\\n image.save(saveLocation+fileName+\\\".\\\"+saveAs, saveAs)\",\n \"def prepare_image(im):\\n width, height = im.size\\n if width > 256 or height > 256:\\n factor = 256.0 / max(width, height)\\n im = im.resize((int(factor * width), int(factor * height)),\\n Image.BILINEAR)\\n return im\",\n \"def convert_to_jpg_then_compress(self):\\n\\t\\tself._compressed_file_name = 'c_' + self.file_name\\n\\t\\tself._compressed_save_path = self.full_path.replace(self.file_name, self._compressed_file_name).replace('.png', '.jpg')\\n\\n\\t\\timage = Image.open(self.full_path)\\n\\t\\timage.save(self._compressed_save_path)\\n\\n\\t\\timage = Image.open(self._compressed_save_path)\\n\\t\\timage.save(self._compressed_save_path, quality=85, progressive=False)\\n\\n\\t\\tself._compressed_file_size = ufo.get_file_size_in_bytes(self._compressed_save_path)\\n\\n\\t\\ttransfer_path = self._compressed_save_path.replace('c_' + self.file_name, self.file_name).replace('/configuration_files/', '/quasar_site_django/')\\n\\t\\tufo.copy_file_to_path(self._compressed_save_path, transfer_path)\",\n \"def convert(dir_path, table, dataset, quality, test_case):\\n final_path = dir_path.joinpath(\\\"images\\\")\\n if test_case:\\n size = 20\\n else:\\n size = len(table)\\n for i in tqdm(range(size)):\\n img = Image.fromarray(table[i])\\n if dataset == 1:\\n img = img.convert(\\\"L\\\")\\n nom = final_path.joinpath(str(i) + \\\".jpg\\\")\\n img.save(nom, quality=quality)\",\n \"def convert_to_image(self, frame, base64_encode=False):\\n #NOTE: tuple (85010, 1) ndarray --> data reduction\\n img_buf_arr = cv2.imencode(\\\".jpeg\\\", frame)[1]\\n if base64_encode:\\n img_buf_arr = b\\\"data:image/jpeg;base64,\\\" + base64.b64encode(img_buf_arr)\\n return img_buf_arr\\n return bytes(img_buf_arr)\",\n \"def save_barcode_to_pillow(self, scale_x=1, scale_y=1):\\n\\n # creating a black and while 1-BIT image\\n # note: if you have problems with 1-BIT images\\n # select image type \\\"L\\\" and set color=255 for a greyscale image\\n\\n im = Image.new('1',\\n (int(self.barcode_array['num_cols']),\\n int(self.barcode_array['num_rows'])),\\n color=1)\\n\\n # note: the generated barcode array is inverse, \\\"1\\\" is black, \\\"0\\\" is white.\\n\\n pixels = im.load()\\n for r in xrange(int(self.barcode_array['num_rows'])):\\n for c in xrange(int(self.barcode_array['num_cols'])):\\n if self.barcode_array['bcode'][r][c] == \\\"1\\\":\\n pixels[c, r] = 0\\n\\n if scale_x != 1 or scale_y != 1:\\n im = im.resize(\\n (scale_x * int(self.barcode_array['num_cols']),\\n scale_y * int(self.barcode_array['num_rows'])))\\n\\n return im\",\n \"def imageprepare(self,argv):\\r\\n\\t\\tim = Image.open(argv).convert('L')\\r\\n\\t\\twidth = float(im.size[0])\\r\\n\\t\\theight = float(im.size[1])\\r\\n\\t\\tnewImage = Image.new('L', (28, 28), (255)) # creates white canvas of 28x28 pixels\\r\\n\\r\\n\\t\\tif width > height: # check which dimension is bigger\\r\\n\\t\\t\\t# Width is bigger. Width becomes 20 pixels.\\r\\n\\t\\t\\tnheight = int(round((20.0 / width * height), 0)) # resize height according to ratio width\\r\\n\\t\\t\\tif nheight == 0: # rare case but minimum is 1 pixel\\r\\n\\t\\t\\t\\tnheight = 1\\r\\n\\t\\t\\t\\t# resize and sharpen\\r\\n\\t\\t\\timg = im.resize((20, nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\r\\n\\t\\t\\twtop = int(round(((28 - nheight) / 2), 0)) # caculate horizontal pozition\\r\\n\\t\\t\\tnewImage.paste(img, (4, wtop)) # paste resized image on white canvas\\r\\n\\t\\telse:\\r\\n\\t\\t\\t# Height is bigger. Heigth becomes 20 pixels.\\r\\n\\t\\t\\tnwidth = int(round((20.0 / height * width), 0)) # resize width according to ratio height\\r\\n\\t\\t\\tif (nwidth == 0): # rare case but minimum is 1 pixel\\r\\n\\t\\t\\t\\tnwidth = 1\\r\\n\\t\\t\\t\\t# resize and sharpen\\r\\n\\t\\t\\timg = im.resize((nwidth, 20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\r\\n\\t\\t\\twleft = int(round(((28 - nwidth) / 2), 0)) # caculate vertical pozition\\r\\n\\t\\t\\tnewImage.paste(img, (wleft, 4)) # paste resized image on white canvas\\r\\n\\r\\n\\t\\t# newImage.save(\\\"sample.png\\\")\\r\\n\\r\\n\\t\\ttv = list(newImage.getdata()) # get pixel values\\r\\n\\r\\n\\t\\t# normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\\r\\n\\t\\ttva = [(255 - x) * 1.0 / 255.0 for x in tv]\\r\\n\\t\\treturn tva\",\n \"def imageprepare(argv):\\n im = Image.open(argv).convert('L')\\n width = float(im.size[0])\\n height = float(im.size[1])\\n newImage = Image.new('L', (28, 28), (255)) # creates white canvas of 28x28 pixels\\n\\n if width > height: # check which dimension is bigger\\n # Width is bigger. Width becomes 20 pixels.\\n nheight = int(round((20.0 / width * height), 0)) # resize height according to ratio width\\n if (nheight == 0): # rare case but minimum is 1 pixel\\n nheight = 1\\n # resize and sharpen\\n img = im.resize((20, nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\n wtop = int(round(((28 - nheight) / 2), 0)) # calculate horizontal position\\n newImage.paste(img, (4, wtop)) # paste resized image on white canvas\\n else:\\n # Height is bigger. Heigth becomes 20 pixels.\\n nwidth = int(round((20.0 / height * width), 0)) # resize width according to ratio height\\n if (nwidth == 0): # rare case but minimum is 1 pixel\\n nwidth = 1\\n # resize and sharpen\\n img = im.resize((nwidth, 20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\n wleft = int(round(((28 - nwidth) / 2), 0)) # caculate vertical pozition\\n newImage.paste(img, (wleft, 4)) # paste resized image on white canvas\\n\\n # newImage.save(\\\"sample.png\\n\\n tv = list(newImage.getdata()) # get pixel values\\n\\n # normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\\n tva = [(255 - x) * 1.0 / 255.0 for x in tv]\\n print(tva)\\n return tva\",\n \"def downsample(self, hr_img):\\r\\n lr_img = hr_img.resize((int(hr_img.width / self.scaling_factor), int(hr_img.height / self.scaling_factor)),\\r\\n Image.BICUBIC)\\r\\n # Convert the LR and HR image to the required type\\r\\n lr_img = convert_image(lr_img, source='pil', target=self.lr_img_type)\\r\\n hr_img = convert_image(hr_img, source='pil', target=self.hr_img_type)\\r\\n return lr_img, hr_img\",\n \"def img_prep(img, shape=(128, 128)):\\n # Resize\\n img = resize_volume(img, (shape[0], shape[1]))\\n\\n img = numpy.multiply(255, _normalize(img)).astype(numpy.uint8)\\n\\n return img\",\n \"def new(self, fmt='JPEG', quality=70):\\n canvas = Image.new(\\n self._mode,\\n (self._width,\\n self._height),\\n self._bg_color)\\n drawer = ImageDraw.Draw(canvas)\\n verify_code = self.drawtext(drawer)\\n self.noisy(drawer)\\n self.blur(canvas)\\n self.line(drawer, canvas)\\n buf = StringIO.StringIO()\\n canvas.save(buf, fmt, quality=quality)\\n return buf, verify_code\",\n \"def image_to_scratch(im, scratch_image_name):\\n\\tim.save(scratch_image_name, dpi=(200,200))\",\n \"def convert_frames(frame, img_format: str, scale=None) -> bytes:\\n\\n path = frame.filename\\n\\n with open(path, \\\"rb\\\") as image_file:\\n im = Image.open(image_file)\\n converted_img = BytesIO()\\n if scale:\\n _LOGGER.debug(\\\"Scaling the image\\\")\\n (width, height) = (int(im.width * scale), int(im.height * scale))\\n _LOGGER.debug(\\\"Original size is {}wx{}h, new size is {}wx{}h\\\".format(im.width, im.height, width, height))\\n im = im.resize([width, height])\\n im.save(converted_img, img_format)\\n return converted_img.getvalue()\",\n \"def _build_final_image(self, image):\\n raise NotImplementedError\",\n \"def convert_png_image_to_webp(png, out, quality=80):\\n command = [CWEBP, '-q', str(quality), png, '-o', out]\\n run_subprocess(command)\",\n \"def save_to_image_file(self, filename, image_format='png', scale_x=1, scale_y=1):\\n\\n self.save_barcode_to_pillow(scale_x=scale_x, scale_y=scale_y).save(filename,\\n format=image_format)\",\n \"def image_quality(self, image_quality):\\n\\n self._image_quality = image_quality\",\n \"def convertFrame(self):\\r\\n try:\\r\\n height, width = self.currentFrame.shape[:2]\\r\\n img = QtGui.QImage(self.currentFrame,\\r\\n width,\\r\\n height,\\r\\n QtGui.QImage.Format_RGB888)\\r\\n img = QtGui.QPixmap.fromImage(img)\\r\\n self.previousFrame = self.currentFrame\\r\\n return img\\r\\n except:\\r\\n return None\",\n \"def imageprepare(argv):\\r\\n im = Image.open(argv).convert('L')\\r\\n width = float(im.size[0])\\r\\n height = float(im.size[1])\\r\\n newImage = Image.new('L', (28, 28), (255)) #creates white canvas of 28x28 pixels\\r\\n \\r\\n if width > height: #check which dimension is bigger\\r\\n #Width is bigger. Width becomes 20 pixels.\\r\\n nheight = int(round((20.0/width*height),0)) #resize height according to ratio width\\r\\n if (nheight == 0): #rare case but minimum is 1 pixel\\r\\n nheight = 1 \\r\\n # resize and sharpen\\r\\n img = im.resize((20,nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\r\\n wtop = int(round(((28 - nheight)/2),0)) #caculate horizontal pozition\\r\\n newImage.paste(img, (4, wtop)) #paste resized image on white canvas\\r\\n else:\\r\\n #Height is bigger. Heigth becomes 20 pixels. \\r\\n nwidth = int(round((20.0/height*width),0)) #resize width according to ratio height\\r\\n if (nwidth == 0): #rare case but minimum is 1 pixel\\r\\n nwidth = 1\\r\\n # resize and sharpen\\r\\n img = im.resize((nwidth,20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\r\\n wleft = int(round(((28 - nwidth)/2),0)) #caculate vertical pozition\\r\\n newImage.paste(img, (wleft, 4)) #paste resized image on white canvas\\r\\n \\r\\n #newImage.save(\\\"sample.png\\\")\\r\\n\\r\\n tv = list(newImage.getdata()) #get pixel values\\r\\n \\r\\n #normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\\r\\n tva = [ (255-x)*1.0/255.0 for x in tv] \\r\\n #print(tva)\\r\\n return tva\",\n \"def quant_image(self, image=None, dst=None, ndeep=None, ndigits=None, override=True, delete=True):\\n # Check Whether Pngquant Exist\\n if not self.file_exists(self.quant_file):\\n raise ValueError(self.err_pngquant)\\n\\n # Check Whether Image Exist\\n if not self.file_exists(image):\\n raise ValueError(self.err_image)\\n\\n # Compress Image By Call Function quant_data\\n # Dst Should Pass Image When Override Origin Image\\n return self.quant_data(self.open_file(image), dst=dst or (override and image), ndeep=ndeep, ndigits=ndigits, delete=delete)\",\n \"def nn_resample_image(image_path, pxl_box_width, pxl_box_height):\\n image = Image.open(image_path)\\n if image.format == \\\"JPEG\\\" or image.format == \\\"PNG\\\":\\n __nn_resample_png_jpeg_image(image, pxl_box_width, pxl_box_height)\\n elif image.format == \\\"GIF\\\":\\n __nn_resample_gif_image(image, pxl_box_width, pxl_box_height)\\n\\n return image\",\n \"def generate_fit_image(self):\\n if self.fit_mode == \\\"stretch\\\":\\n return self.im.resize((self.width, self.height))\\n else:\\n raise NotImplementedError(\\\"%s: This fit mode doesn't exist\\\" % self.fit_mode)\",\n \"def downsample_image(img, output_path, ratio=2):\\n assert ratio>=1, ratio\\n if ratio == 1:\\n return True\\n old_im = Image.open(img)\\n old_size = old_im.size\\n new_size = (int(old_size[0]/ratio), int(old_size[1]/ratio))\\n\\n new_im = old_im.resize(new_size, PIL.Image.LANCZOS)\\n new_im.save(output_path)\\n return True\",\n \"def convertFrame(self):\\n try:\\n height,width=self.currentFrame.shape[:2]\\n img=QtGui.QImage(self.currentFrame,\\n width,\\n height,\\n QtGui.QImage.Format_RGB888)\\n img=QtGui.QPixmap.fromImage(img)\\n self.previousFrame = self.currentFrame\\n return img\\n except:\\n return None\",\n \"def prepare(img,\\n resize=False, new_size=(64, 64),\\n apply_contrast=False, contrast_channels=(0, 1, 2)\\n ):\\n new_img = crop(img)\\n\\n if resize:\\n new_img = cv2.resize(new_img, new_size)\\n\\n if apply_contrast:\\n new_img = increase_contrast(new_img, channels=contrast_channels)\\n\\n return new_img\",\n \"def prepare_image(img):\\n img = img.filter(ImageFilter.SMOOTH_MORE)\\n img = img.filter(ImageFilter.SMOOTH_MORE)\\n if 'L' != img.mode:\\n img = img.convert('L')\\n return img\",\n \"def imageprepare(filename):\\n img = Image.open(filename).convert('L')\\n rect = img.getbbox()\\n im = img.crop(rect)\\n im.save(filename + '_pressprocessed.png')\\n\\n width = float(im.size[0])\\n height = float(im.size[1])\\n newImage = Image.new('L', (28, 28), (0)) #creates white canvas of 28x28 pixels\\n if width > height: #check which dimension is bigger\\n #Width is bigger. Width becomes 20 pixels.\\n nheight = int(round((20.0/width*height),0)) #resize height according to ratio width\\n if (nheight == 0): #rare case but minimum is 1 pixel\\n nheight = 1\\n # resize and sharpen\\n img = im.resize((20,nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\n wtop = int(round(((28 - nheight)/2),0)) #caculate horizontal pozition\\n newImage.paste(img, (4, wtop)) #paste resized image on white canvas\\n newImage.save(filename + '_final.png')\\n else:\\n #Height is bigger. Heigth becomes 20 pixels. \\n nwidth = int(round((20.0/height*width),0)) #resize width according to ratio height\\n if (nwidth == 0): #rare case but minimum is 1 pixel\\n nwidth = 1\\n # resize and sharpen\\n img = im.resize((nwidth,20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\n wleft = int(round(((28 - nwidth)/2),0)) #caculate vertical pozition\\n newImage.paste(img, (wleft, 4)) #paste resized image on white canvas\\n newImage.save(filename + '_final.png')\\n tv = list(newImage.getdata()) #get pixel values\\n #normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\\n tva = [ (x)*1.0/255.0 for x in tv] \\n return tva\",\n \"def process_image(image):\\n image = resize(image)\\n return image\",\n \"def __make_png(self, abspath_img_rgb):\\n if not os.path.exists(DIR_PNG):\\n os.makedirs(DIR_PNG)\\n\\n outsize = '{}%'.format(OUTSIZE_RGB)\\n img_name_rgb = os.path.basename(abspath_img_rgb)\\n suffix_extension_tif = Utils.get_suffix_tif(img_name_rgb)\\n img_png = img_name_rgb.replace(suffix_extension_tif, '.png')\\n path_img_png = os.path.join(DIR_PNG, img_png)\\n\\n command = \\\"gdal_translate -ot byte -of PNG -outsize {} {} \\\" \\\\\\n \\\"-a_nodata 0 -q {} {}\\\".format(\\n outsize, outsize, abspath_img_rgb, path_img_png\\n )\\n os.system(command)\\n return os.path.join(DIR_PNG_TO_DB, img_png)\",\n \"def upscale_pre(user_select):\\n global result_img\\n global pixel_buff\\n print('=======================================')\\n print('Starting upscale...')\\n input_img_x, input_img_y = working_img.size\\n working_img_mode = working_img.mode\\n output_img = Image.new(working_img_mode, (input_img_x*2, input_img_y*2))\\n outputx, outputy = output_img.size\\n print(f'outputx set:{outputx} outputy set:{outputy}')\\n if working_img_mode == \\\"RBGA\\\":\\n pixel_buff = (0, 0, 0, 0)\\n else:\\n pixel_buff = (0, 0, 0)\\n print('Making space...')\\n #Inserting input image pixel and black pixel\\n ix = iy = 0\\n for oy in range(0, outputy, 2):\\n for ox in range(0, outputx):\\n if ox % 2 != 1:\\n output_img.putpixel((ox, oy), working_img.getpixel((ix,iy)))\\n ix += 1\\n else:\\n output_img.putpixel((ox, oy), pixel_buff)\\n if ix == input_img_x:\\n ix = 0\\n #print(f'pixel:{ix, iy} input:{working_img.getpixel((ix,iy))} / pixel:{ox, oy} output:{output_img.getpixel((ox,oy))}')\\n iy += 1\\n #Inserting Black line\\n ix = iy = 0\\n for oy in range(1, outputy, 2):\\n for ox in range(0, outputx):\\n output_img.putpixel((ox, oy), pixel_buff)\\n #print(f'pixel:{ix, iy} input:{working_img.getpixel((ix,iy))} / pixel:{ox, oy} output:{output_img.getpixel((ox,oy))}')\\n return output_img\",\n \"def img_to_pixmap(img, scale=1.0, code=\\\"rgb\\\"):\\n if code.lower() == \\\"rgb\\\":\\n img_format = QImage.Format_RGB888\\n bytes_per_pixel = 3 # For RGB\\n elif code.lower() == \\\"bgr\\\":\\n img_format = QImage.Format_BGR888\\n bytes_per_pixel = 3 # for bgr\\n elif code.lower() == \\\"rgba\\\":\\n img_format = QImage.Format_RGBA8888\\n bytes_per_pixel = 4\\n else:\\n img_format = QImage.Format_Grayscale8\\n bytes_per_pixel = 1\\n # Need to fix the problem with background\\n qimg = QImage(img, img.shape[1], img.shape[0],\\n img.shape[1] * bytes_per_pixel,\\n img_format)\\n width = img.shape[1]\\n height = img.shape[0]\\n w_ = int(width * scale)\\n h_ = int(height * scale)\\n if w_ > h_:\\n pix = QPixmap.fromImage(qimg).scaledToWidth(\\n w_, mode=Qt.SmoothTransformation)\\n else:\\n pix = QPixmap.fromImage(qimg).scaledToHeight(\\n h_, mode=Qt.SmoothTransformation)\\n return pix, (w_, h_)\",\n \"def _test_img_resize(self, backend):\\n # Check quality setting unaffected by new parameter\\n im_95_qual = backend.resize(\\n 225,\\n self.IMG_225x225,\\n quality=95,\\n max_filesize=0,\\n )\\n # check valid path returned - max_filesize hasn't broken resize command\\n self.assertExists(im_95_qual)\\n\\n # Attempt a lower filesize with same quality\\n im_a = backend.resize(\\n 225,\\n self.IMG_225x225,\\n quality=95,\\n max_filesize=0.9 * os.stat(syspath(im_95_qual)).st_size,\\n )\\n self.assertExists(im_a)\\n # target size was achieved\\n self.assertLess(os.stat(syspath(im_a)).st_size,\\n os.stat(syspath(im_95_qual)).st_size)\\n\\n # Attempt with lower initial quality\\n im_75_qual = backend.resize(\\n 225,\\n self.IMG_225x225,\\n quality=75,\\n max_filesize=0,\\n )\\n self.assertExists(im_75_qual)\\n\\n im_b = backend.resize(\\n 225,\\n self.IMG_225x225,\\n quality=95,\\n max_filesize=0.9 * os.stat(syspath(im_75_qual)).st_size,\\n )\\n self.assertExists(im_b)\\n # Check high (initial) quality still gives a smaller filesize\\n self.assertLess(os.stat(syspath(im_b)).st_size,\\n os.stat(syspath(im_75_qual)).st_size)\",\n \"def grocepre(img):\\n img_prepro = pre.get_grayscale(img)\\n img_prepro = pre.remove_noise(img_prepro)\\n img_prepro = pre.dilate(img_prepro)\\n img_prepro = pre.erode(img_prepro)\\n img_prepro = pre.opening(img_prepro)\\n img_prepro = pre.thresholding(img_prepro)\\n\\n return img_prepro\",\n \"def handle_image(name):\\n from_path = args.from_dir + name\\n to_path = args.to_dir + name\\n\\n if width != args.width:\\n subprocess.call('jpegtran -rotate 90 -grayscale ' + from_path + ' > ' \\\\\\n + to_path, shell=True)\\n else:\\n subprocess.call('jpegtran -grayscale ' + from_path + ' > ' + to_path,\\\\\\n shell=True)\",\n \"def _create_image(self):\\n if hasattr(self, '_image') and self._image:\\n return self._image\\n try:\\n command = \\\"tex2im -b transparent -t cyan\\\"\\n subprocess.run([*command.split(), self._formula])\\n except Exception as e:\\n import traceback\\n print(traceback.format_exc())\\n return None\\n # tex2im converts to out.png by default\\n img = Image.open('out.png').convert('RGBA')\\n # create a new rgba image to blend the latex with the alpha\\n subprocess.run([\\\"rm\\\", \\\"out.png\\\"])\\n return img\",\n \"def generateScaled(img):\\n\\n if not img._scaledfn:\\n return\\n\\n aimgfn = join(opts.root, img._filename)\\n if not opts.fast:\\n img._size = imageSize(aimgfn)\\n\\n ascaledfn = join(opts.root, img._scaledfn)\\n\\n if opts.scaled_force:\\n if opts.quiet: print \\\"forced regeneration of '%s'\\\" % img._scaledfn\\n elif not exists(ascaledfn):\\n if opts.quiet: print \\\"thumbnail absent '%s'\\\" % img._scaledfn\\n else:\\n # Check if scaledsize has changed\\n if not opts.fast:\\n img._scaledsize = imageSize(ascaledfn)\\n if not checkThumbSize(img._size, \\\\\\n img._scaledsize, \\\\\\n opts.scaled_size):\\n if opts.quiet: print \\\"thumbnail '%s size has changed\\\" % img._scaledfn\\n try:\\n # Clear cache for thumbnail size.\\n del imageSizeCache[ ascaledfn ]\\n except:\\n pass\\n else:\\n if opts.quiet: print \\\"thumbnail '%s' already generated (size ok)\\\" \\\\\\n % img._scaledfn\\n return\\n else:\\n if opts.quiet: print \\\"thumbnail '%s' already generated\\\" % img._scaledfn\\n return\\n\\n if opts.no_magick:\\n if opts.quiet: print \\\"ImageMagick tools disabled, can't create thumbnail\\\"\\n return\\n\\n # create necessary directories\\n d = dirname(ascaledfn)\\n if not exists(d):\\n os.makedirs(d)\\n\\n if opts.pil:\\n\\n try:\\n im = PilImage.open(aimgfn)\\n im.thumbnail((opts.scaled_size, opts.scaled_size), config.ScaledImages[\\\"Interpolation\\\"])\\n im.save(ascaledfn)\\n\\n img._scaledsize = im.size\\n except IOError, e:\\n raise SystemExit(\\\\\\n \\\"Error: identifying file '%s'\\\" % aimgfn + str(e))\\n\\n else:\\n\\n cmd = getMagickProg('convert') + ' -border 2x2 '\\n # FIXME check if this is a problem if not specified\\n #cmd += '-interlace NONE '\\n\\n cmd += '-geometry %dx%d ' % (opts.scaled_size, opts.scaled_size)\\n\\n if opts.scaled_quality:\\n cmd += '-quality %d ' % opts.scaled_quality\\n\\n # This doesn't add text into the picture itself, just the comment in\\n # the header.\\n if opts.copyright:\\n cmd += '-comment \\\\\\\"%s\\\\\\\" ' % opts.copyright\\n\\n # We use [1] to extract the thumbnail when there is one.\\n # It is harmless otherwise.\\n subimg = \\\"\\\"\\n if img._ext.lower() in [ \\\".jpg\\\", \\\".tif\\\", \\\".tiff\\\" ]:\\n subimg = \\\"[1]\\\"\\n\\n cmd += '\\\"%s%s\\\" \\\"%s\\\"' % (aimgfn, subimg, ascaledfn)\\n\\n if opts.quiet: print \\\"generating thumbnail '%s'\\\" % img._scaledfn\\n\\n (chin, chout, cherr) = os.popen3(cmd)\\n errs = cherr.readlines()\\n chout.close()\\n cherr.close()\\n if errs:\\n print >> sys.stderr, \\\\\\n \\\"Error: running convert program on %s:\\\" % aimgfn\\n errs = string.join(errs, '\\\\n')\\n print errs\\n\\n if subimg and \\\\\\n re.compile('Unable to read subimage').search(errs):\\n if opts.quiet: print \\\"retrying without subimage\\\"\\n cmd = string.replace(cmd, subimg, \\\"\\\")\\n\\n (chin, chout, cherr) = os.popen3(cmd)\\n errs = cherr.readlines()\\n chout.close()\\n cherr.close()\\n if errs:\\n print >> sys.stderr, \\\\\\n \\\"Error: running convert program on %s:\\\" % aimgfn\\n print string.join(errs, '\\\\n')\\n\\n else:\\n img._scaledsize = imageSize(ascaledfn)\",\n \"def convert_image_to_QTformat(self, image):\\n image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\\n convertToQtFormat = QImage(image.data, image.shape[1], image.shape[0], QImage.Format_RGB888)\\n qt_image = convertToQtFormat.scaled(500, 375, Qt.KeepAspectRatio)\\n return qt_image\",\n \"def encode_png(track_metadata):\\n\\tprint(\\\"---- Encoding\\\", track_metadata.file_name, \\\"to PNG...\\\")\\n\\n\\t# First step: OptiPNG.\\n\\tnew_file_name = track_metadata.file_name + \\\".png\\\"\\n\\toptipng_command = [\\\"optipng\\\", \\\"-o7\\\", \\\"-strip\\\", \\\"all\\\", \\\"-snip\\\", \\\"-out\\\", new_file_name, track_metadata.file_name]\\n\\tprint(optipng_command)\\n\\tprocess = subprocess.Popen(optipng_command, stdout=subprocess.PIPE)\\n\\t(cout, cerr) = process.communicate()\\n\\texit_code = process.wait()\\n\\tif exit_code != 0: #0 is success.\\n\\t\\traise Exception(\\\"OptiPNG failed with exit code {exit_code}. CERR: {cerr}\\\".format(exit_code=exit_code, cerr=cerr))\\n\\n\\tect_command = [\\\"/home/ruben/encoding/Efficient-Compression-Tool/build/ect\\\", \\\"-9\\\", \\\"-strip\\\", \\\"--allfilters-b\\\", \\\"--mt-deflate\\\", new_file_name]\\n\\tprint(ect_command)\\n\\tprocess = subprocess.Popen(ect_command, stdout=subprocess.PIPE)\\n\\t(cout, cerr) = process.communicate()\\n\\texit_code = process.wait()\\n\\tif exit_code != 0: #0 is success.\\n\\t\\traise Exception(\\\"ECT failed with exit code {exit_code}. CERR: {cerr}\\\".format(exit_code=exit_code, cerr=cerr))\\n\\n\\t#Delete old file.\\n\\tif os.path.exists(track_metadata.file_name):\\n\\t\\tos.remove(track_metadata.file_name)\\n\\n\\ttrack_metadata.file_name = new_file_name\\n\\ttrack_metadata.codec = \\\"png\\\"\",\n \"def quantize(im_orig, n_quant, n_iter):\\n if im_orig.ndim == RGB_DIM:\\n # Quantize only Y channel.\\n im_yiq = rgb2yiq(im_orig)\\n result = __gray_quantize(im_yiq[:, :, Y_CHANNEL], n_quant, n_iter)\\n im_yiq[:, :, Y_CHANNEL] = result[IMAGE_LOCATION]\\n\\n # Convert back to RGB space.\\n result[IMAGE_LOCATION] = yiq2rgb(im_yiq)\\n return result\\n # Otherwise, just quantize.\\n return __gray_quantize(im_orig, n_quant, n_iter)\",\n \"def compression_jpeg(img: np.ndarray, quality=20):\\n \\n imgtype = img.dtype\\n if img.ndim >= 3:\\n img_channels = img.shape[2]\\n elif img.ndim == 2:\\n img_channels = 1\\n\\n #encoding parameters\\n encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), quality]\\n # encode\\n is_success, encimg = cv2.imencode('.jpg', img, encode_param) \\n \\n # decode\\n jpeg_img = cv2.imdecode(encimg, 1)\\n \\n # fix for grayscale images\\n if jpeg_img.ndim == 3 and jpeg_img.shape[2] != img_channels:\\n jpeg_img = jpeg_img[:,:,1]\\n\\n if jpeg_img.ndim != 3:\\n jpeg_img = jpeg_img[..., np.newaxis]\\n \\n return jpeg_img.astype(imgtype)\",\n \"def mozjpeg(ext_args, root=None):\\n args = copy.copy(_MOZJPEG_ARGS)\\n if Settings.destroy_metadata:\\n args += [\\\"-copy\\\", \\\"none\\\"]\\n else:\\n args += [\\\"-copy\\\", \\\"all\\\"]\\n if Settings.jpegtran_prog:\\n args += [\\\"-progressive\\\"]\\n\\n args += ['-outfile']\\n args += [ext_args.new_filename, ext_args.old_filename]\\n if test:\\n print(\\\"mozjpeg: \\\", args)\\n return 0\\n\\n extern.run_ext(args, root)\\n return _JPEG_FORMAT\",\n \"def to_qt_pixmap(self, scale=None):\\n bytes_per_line = 3 * self.width\\n img = self.to_color().img\\n rgb = opencv.cvtColor(img, opencv.COLOR_BGR2RGB)\\n q_img = QImage(rgb.data, self.width, self.height, bytes_per_line, QImage.Format_RGB888)\\n pixmap = QPixmap.fromImage(q_img)\\n\\n if scale is not None:\\n pixmap = pixmap.scaled(scale, QtCore.Qt.KeepAspectRatio, QtCore.Qt.SmoothTransformation)\\n\\n return pixmap\",\n \"def __create_base_shap_img(self):\\n\\n self.img = 255 * np.ones([1680, 1680, 3], dtype=np.uint8)\\n self.baseline_scale_img = cv2.imread(self.scale_img_dict[\\\"baseline_scale\\\"])\\n self.baseline_scale_top_left = (100, 800)\\n baseline_scale_bottom_right = (\\n self.baseline_scale_top_left[0] + self.baseline_scale_img.shape[0],\\n self.baseline_scale_top_left[1] + self.baseline_scale_img.shape[1],\\n )\\n baseline_scale_middle = ((int(700 + self.baseline_scale_img.shape[1] / 2)), 85)\\n self.img[\\n self.baseline_scale_top_left[0] : baseline_scale_bottom_right[0],\\n self.baseline_scale_top_left[1] : baseline_scale_bottom_right[1],\\n ] = self.baseline_scale_img\\n cv2.putText(\\n self.img,\\n \\\"BASELINE SHAP\\\",\\n baseline_scale_middle,\\n cv2.FONT_HERSHEY_COMPLEX,\\n 1,\\n (0, 0, 0),\\n 2,\\n )\\n\\n self.small_arrow_img = cv2.imread(self.scale_img_dict[\\\"small_arrow\\\"])\\n small_arrow_top_left = (\\n baseline_scale_bottom_right[0],\\n int(\\n self.baseline_scale_top_left[1]\\n + (self.baseline_scale_img.shape[1] / 100) * (self.shap_baseline_value)\\n ),\\n )\\n small_arrow_bottom_right = (\\n small_arrow_top_left[0] + self.small_arrow_img.shape[0],\\n small_arrow_top_left[1] + self.small_arrow_img.shape[1],\\n )\\n self.img[\\n small_arrow_top_left[0] : small_arrow_bottom_right[0],\\n small_arrow_top_left[1] : small_arrow_bottom_right[1],\\n ] = self.small_arrow_img\\n\\n self.color_bar_img = cv2.imread(self.scale_img_dict[\\\"color_bar\\\"])\\n\\n side_scale_img = cv2.imread(self.scale_img_dict[\\\"side_scale\\\"])\\n side_scale_top_left = (\\n small_arrow_bottom_right[0] + 50,\\n self.baseline_scale_top_left[1] - 50,\\n )\\n self.side_scale_y_tick_cords = [\\n (side_scale_top_left[0], side_scale_top_left[1] - 75)\\n ]\\n for i in range(1, 7):\\n self.side_scale_y_tick_cords.append(\\n (\\n int(side_scale_top_left[0] + (side_scale_img.shape[0] / 4) * i),\\n int(side_scale_top_left[1] - 75),\\n )\\n )\\n self.arrow_start = (\\n int(small_arrow_top_left[1] + (self.small_arrow_img.shape[1] / 2)),\\n side_scale_top_left[0],\\n )\\n\\n for img_cnt, (img_name, img_data) in enumerate(self.category_img_dict.items()):\\n icon_img = cv2.resize(\\n cv2.imread(img_data[\\\"icon\\\"]),\\n None,\\n fx=1.5,\\n fy=1.5,\\n interpolation=cv2.INTER_CUBIC,\\n )\\n icon_top_left = (\\n self.side_scale_y_tick_cords[img_cnt][0] - int(icon_img.shape[0] / 2),\\n self.side_scale_y_tick_cords[img_cnt][1] - 100,\\n )\\n icon_bottom_right = (\\n icon_top_left[0] + icon_img.shape[0],\\n self.side_scale_y_tick_cords[img_cnt][1] + icon_img.shape[1] - 100,\\n )\\n text_location = (\\n int(\\n icon_bottom_right[0]\\n - (icon_bottom_right[0] - icon_top_left[0])\\n + 100\\n ),\\n int(icon_bottom_right[1] - (icon_bottom_right[1] - icon_top_left[1]))\\n - 380,\\n )\\n cv2.putText(\\n self.img,\\n str(img_name),\\n (text_location[1], text_location[0]),\\n cv2.FONT_HERSHEY_COMPLEX,\\n 0.75,\\n (0, 0, 0),\\n 1,\\n )\\n self.img[\\n icon_top_left[0] : icon_bottom_right[0],\\n icon_top_left[1] : icon_bottom_right[1],\\n ] = icon_img\",\n \"def rescale_image_0255(image):\\n # scale image to from [0.0, 1.0] to [0, 255]\\n image *= 255\\n return image.astype(np.uint8)\",\n \"def prepare_test_img(self, idx):\\n img_info = self.img_infos[idx]\\n img_path = osp.join(self.img_prefix, img_info['filename'])\\n\\n if self.proposals is not None:\\n proposal = self.proposals[idx][:self.num_max_proposals]\\n if not proposal.shape[1] == 4 or proposal.shape[1] == 5:\\n raise AssertionError(\\n 'proposals should have shapes (n, 4) or (n, 5), '\\n 'but found {}'.format(proposal.shape))\\n else:\\n proposal = None\\n\\n if self.with_background_erasing:\\n ann = self.get_ann_info(idx)\\n gt_bboxes = ann['bboxes']\\n else:\\n gt_bboxes = None\\n\\n def prepare_single_scale(img_path, expected_size, flip_ratio=0,\\n proposal=None, bbox=None):\\n _img, img_shape, pad_shape, scale_factor, \\\\\\n flipped_flag, flipped_direction = self.img_transforms(\\n img_path, expected_size, flip_ratio=flip_ratio)\\n if bbox is not None:\\n if not len(bbox) == 0:\\n _gt_bboxes = self.bbox_transforms(bbox,\\n img_shape,\\n scale_factor,\\n flipped_flag,\\n flipped_direction)\\n else:\\n _gt_bboxes = bbox\\n _img = self.background_erasing(\\n _img, img_shape, _gt_bboxes,\\n cell_size=self.be_cell_size,\\n random_ratio=self.be_random_ratio)\\n _img = to_tensor(_img)\\n _img_meta = dict(\\n filename=img_info['filename'],\\n ori_shape=(img_info['height'], img_info['width'], 3),\\n img_shape=img_shape,\\n pad_shape=pad_shape,\\n scale_factor=scale_factor,\\n flipped_flag=flipped_flag,\\n flipped_direction=flipped_direction\\n )\\n if proposal is not None:\\n if proposal.shape[1] == 5:\\n score = proposal[:, 4, None]\\n proposal = proposal[:, :4]\\n else:\\n score = None\\n _proposal = self.bbox_transforms(proposal,\\n img_shape,\\n scale_factor,\\n flipped_flag,\\n flipped_direction)\\n _proposal = np.hstack([_proposal, score]) \\\\\\n if score is not None else _proposal\\n _proposal = to_tensor(_proposal)\\n else:\\n _proposal = None\\n return _img, _img_meta, _proposal\\n\\n imgs = []\\n img_metas = []\\n proposals = []\\n for expected_size in self.img_expected_sizes:\\n # at first, we do not flip the image\\n _img, _img_meta, _proposal = prepare_single_scale(\\n img_path, expected_size, flip_ratio=0,\\n proposal=proposal, bbox=gt_bboxes)\\n imgs.append(_img)\\n img_metas.append(DataContainer(_img_meta, cpu_only=True))\\n proposals.append(_proposal)\\n if self.flip_ratio > 0:\\n _img, _img_meta, _proposal = prepare_single_scale(\\n img_path, expected_size, flip_ratio=1,\\n proposal=proposal, bbox=gt_bboxes)\\n imgs.append(_img)\\n img_metas.append(DataContainer(_img_meta, cpu_only=True))\\n proposals.append(_proposal)\\n data = dict(img=imgs, img_meta=img_metas)\\n if self.proposals is not None:\\n data['proposals'] = proposals\\n return data\",\n \"def save_subpix_png(path, img, scale_factor=256.0):\\n Path(path).parent.mkdir(parents=True, exist_ok=True)\\n img = img.astype(np.float32) * scale_factor\\n if np.amax(img) > (2**16)-1:\\n warnings.warn(\\\"image out of range(\\\" + str(np.amax(img)/scale_factor) +\\n \\\"), try with a smaller scale factor. loading this file \\\" +\\n \\\"will results in invalid values, file: \\\"+str(path))\\n img[img > (2**16)-1] = 0\\n img = img.astype(np.uint16)\\n cv2.imwrite(str(path), img)\",\n \"def convert_image(image_path):\\n with Image.open(image_path) as img:\\n new_image = img.convert(\\\"RGBA\\\" if img.format == \\\"PNG\\\" else \\\"RGB\\\")\\n new_image.save(image_path)\",\n \"def turn_into_image(self):\\n if self.title_colours:\\n self.table_to_image = TableToImage(self.table.get_string(), self.colour, self.rows, self.titles,\\n self.title_colours)\\n else:\\n self.table_to_image = TableToImage(self.table.get_string(), self.colour, self.rows)\",\n \"def scale(input_img, size):\\n width, height = size\\n old_height, old_width = input_img.shape\\n x_scale = float(height) / old_height\\n y_scale = float(width) / old_width\\n\\n output_img = np.zeros((height, width), dtype=np.uint8)\\n for xidx in xrange(height):\\n old_x = float(xidx) / x_scale\\n for yidx in xrange(width):\\n old_y = float(yidx) / y_scale\\n if old_x.is_integer() or old_y.is_integer():\\n output_img[xidx, yidx] = input_img[int(old_x), int(old_y)]\\n else: # use bilinear interpolation\\n x1 = int(np.floor(old_x))\\n x2 = int(np.ceil(old_x)) if int(np.ceil(old_x)) < old_height else old_height - 1\\n y1 = int(np.floor(old_y))\\n y2 = int(np.ceil(old_y)) if int(np.ceil(old_y)) < old_width else old_width - 1\\n\\n q11 = input_img[x1, y1]\\n q12 = input_img[x1, y2]\\n q21 = input_img[x2, y1]\\n q22 = input_img[x2, y2]\\n\\n output_img[xidx, yidx] = (q11 * (x2 - old_x) * (y2 - old_y)\\n + q21 * (old_x - x1) * (y2 - old_y)\\n + q12 * (x2 - old_x) * (old_y - y1)\\n + q22 * (old_x - x1) * (old_y - y1)) \\\\\\n / ((x2 - x1) * (y2 - y1) + 1e-10)\\n\\n return output_img\",\n \"def get_qpimage_raw(self, idx=0):\\n # Load experimental data\\n with h5py.File(self.path) as h5:\\n holo = h5[\\\"0\\\"][:]\\n qpi = qpimage.QPImage(data=holo,\\n which_data=\\\"raw-oah\\\",\\n meta_data=self.get_metadata(idx),\\n qpretrieve_kw=self.qpretrieve_kw,\\n h5dtype=self.as_type)\\n return qpi\",\n \"def create_jpg (filename):\\n\\n try:\\n\\n image_jpg = '{}.jpg'.format(filename.split('.fits')[0])\\n\\n if not isfile(image_jpg):\\n\\n log.info ('saving {} to {}'.format(filename, image_jpg))\\n\\n # read input image\\n data, header = read_hdulist(filename, get_header=True)\\n\\n imgtype = header['IMAGETYP'].lower()\\n file_str = image_jpg.split('/')[-1].split('.jpg')[0]\\n if imgtype == 'object':\\n title = ('file:{} object:{} filter:{} exptime:{:.1f}s '\\n 'QC flag:{}'.format(file_str, header['OBJECT'],\\n header['FILTER'], header['EXPTIME'],\\n header['QC-FLAG']))\\n else:\\n title = ('file:{} imgtype:{} filter:{} QC flag:{}'\\n .format(file_str, header['IMAGETYP'], header['FILTER'],\\n header['QC-FLAG']))\\n\\n pixelcoords = True\\n if pixelcoords:\\n f = aplpy.FITSFigure(data)\\n else:\\n f = aplpy.FITSFigure(filename)\\n\\n vmin, vmax = zscale().get_limits(data)\\n f.show_colorscale(cmap='gray', vmin=vmin, vmax=vmax)\\n f.add_colorbar()\\n f.set_title(title)\\n #f.add_grid()\\n #f.set_theme('pretty')\\n f.save(image_jpg, adjust_bbox=False)\\n f.close()\\n\\n\\n except Exception as e:\\n #log.exception (traceback.format_exc())\\n log.exception ('exception was raised in creating jpg of image {}: {}'\\n .format(filename,e))\\n\\n\\n return image_jpg\",\n \"def ff_correct_image(image):\\n pass\",\n \"def ff_correct_image(image):\\n pass\",\n \"def drawImage(self, QRectF, QImage, QRectF_1, Qt_ImageConversionFlags_flags=None): # real signature unknown; restored from __doc__\\r\\n pass\",\n \"def pre_processing_image(img):\\n\\n #print(img.shape)\\n # apply gamma correction and show the images\\n #adjusted = adjust_gamma(img, gamma=0.65)\\n\\n adjusted = exposure.adjust_gamma(img, gamma=1.65)\\n #print(adjusted.shape)\\n\\n # log transform of image\\n\\n logarithmic_corrected = exposure.adjust_log(adjusted, 1)\\n #print(logarithmic_corrected.shape)\\n\\n # denoising\\n #dst2 = cv2.fastNlMeansDenoisingColored(logarithmic_corrected, None, 10, 10, 7, 21)\\n #print(dst2.shape)\\n dst2 = logarithmic_corrected\\n return dst2\",\n \"def imageprepare(image_data):\\n im = Image.open(io.BytesIO(image_data))\\n im = remove_transparency(im)\\n im = im.resize((28,28))\\n width = float(im.size[0])\\n height = float(im.size[1])\\n new_image = Image.new('L', (28, 28), 255) # creates white canvas of 28x28 pixels\\n\\n if width > height: # check which dimension is bigger\\n # Width is bigger. Width becomes 20 pixels.\\n nheight = int(round((20.0 / width * height), 0)) # resize height according to ratio width\\n if nheight == 0: # rare case but minimum is 1 pixel\\n nheight = 1\\n # resize and sharpen\\n img = im.resize((20, nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\n wtop = int(round(((28 - nheight) / 2), 0)) # calculate horizontal position\\n new_image.paste(img, (4, wtop)) # paste resized image on white canvas\\n else:\\n # Height is bigger. Heigth becomes 20 pixels.\\n nwidth = int(round((20.0 / height * width), 0)) # resize width according to ratio height\\n if nwidth == 0: # rare case but minimum is 1 pixel\\n nwidth = 1\\n # resize and sharpen\\n img = im.resize((nwidth, 20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\n wleft = int(round(((28 - nwidth) / 2), 0)) # caculate vertical pozition\\n new_image.paste(img, (wleft, 4)) # paste resized image on white canvas\\n\\n # new_image = ImageOps.invert(new_image)\\n\\n tv = list(new_image.getdata()) # get pixel values\\n\\n # normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\\n tva = [(255 - x) * 1.0 / 255.0 for x in tv]\\n return tva, new_image\",\n \"def convert_cv_qt(self, cv_img):\\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\\n h, w, ch = rgb_image.shape\\n bytes_per_line = ch * w\\n convert_to_Qt_format = QtGui.QImage(\\n rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\\n display_width = 960\\n display_height = 540\\n p = convert_to_Qt_format.scaled(\\n display_width, display_height, Qt.KeepAspectRatio)\\n return QPixmap.fromImage(p)\",\n \"def resize_img(self,scale=1):\\n reduced = self.image.reduce((scale,scale))\\n reduced.save(\\\"../edited/{}\\\".format(self.image.filename))\\n\\n reduced = Image.open(\\\"../edited/{}\\\".format(self.image.filename))\\n return reduced\",\n \"def pildumps(image, format=\\\"PNG\\\"):\\n result = StringIO.StringIO()\\n if image.dtype in [np.dtype('f'), np.dtype('d')]:\\n assert np.amin(image) > -0.001 and np.amax(image) < 1.001\\n image = np.clip(image, 0.0, 1.0)\\n image = np.array(image * 255.0, 'uint8')\\n PIL.Image.fromarray(image).save(result, format=format)\\n return result.getvalue()\",\n \"def convert_image(source, dest, out_format, run_as_root=False):\\n cmd = ('qemu-img', 'convert', '-O', out_format, source, dest)\\n utils.execute(*cmd, run_as_root=run_as_root)\",\n \"def convert_cv_qt(self, cv_img):\\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\\n h, w, ch = rgb_image.shape\\n bytes_per_line = ch * w\\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\\n p = convert_to_Qt_format.scaled(self.disply_width, self.display_height, ) #Qt.KeepAspectRatio\\n return QPixmap.fromImage(p)\",\n \"def convert_cv_qt(self, cv_img):\\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\\n h, w, ch = rgb_image.shape\\n bytes_per_line = ch * w\\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\\n p = convert_to_Qt_format.scaled(self.disply_width, self.display_height, ) #Qt.KeepAspectRatio\\n return QPixmap.fromImage(p)\",\n \"def convert_cv_qt(self, cv_img):\\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\\n h, w, ch = rgb_image.shape\\n bytes_per_line = ch * w\\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\\n p = convert_to_Qt_format.scaled(self.disply_width, self.display_height, ) #Qt.KeepAspectRatio\\n return QPixmap.fromImage(p)\",\n \"def embed_image_pred(image):\\n image_pil2 = Image.fromarray((255 * image).astype('uint8'))\\n #image_pil2 = image_pil.resize((256, 256))\\n string_buf2 = StringIO.StringIO()\\n image_pil2.save(string_buf2, format='png')\\n data = string_buf2.getvalue().encode('base64').replace('\\\\n', '')\\n return 'data:image/png;base64,' + data\",\n \"def q_1(input_file, output_file):\\n img = cv2.imread(input_file, cv2.IMREAD_COLOR)\\n\\n # Convert image to gray channel\\n np_img = np.array(img)\\n b = np_img[:,:,0]\\n g = np_img[:,:,1]\\n r = np_img[:,:,2]\\n img_gray = 0.21 * b + 0.72 * g + 0.07 * r\\n img_gray = np.array(img_gray, dtype='uint8')\\n cv2.imwrite(output_file, img_gray)\\n print(np_img)\",\n \"def img_optimizer(image, s3bucket):\\n try:\\n s3client = boto3.client('s3', region_name=AWS_REGION)\\n\\n temp_ifile = '/tmp/tmp_ifile.jpg'\\n\\n with open(temp_ifile, 'wb') as data:\\n s3client.download_fileobj(s3bucket, image, data)\\n\\n file_src = temp_ifile\\n file_dst = file_src.split('.')[0] + '_.' + file_src.split('.')[1]\\n\\n img = Image.open(file_src)\\n\\n \\\"\\\"\\\"\\n Applying downsampling antialias algorithm without actual resize gives 30-40% lower file size. \\n Downsize with 0.97 aspect ratio gives up to 50% decrease. \\n \\\"\\\"\\\"\\n aspect = 0.97\\n new_size = (int(float(img.size[0]) * float(aspect)), int(float(img.size[1]) * float(aspect)))\\n\\n new_img = img.resize(new_size, Image.ANTIALIAS)\\n new_img.save(file_dst)\\n piexif.transplant(file_src, file_dst)\\n\\n return 'SUCCESS', file_dst\\n\\n except Exception as err:\\n print('Image optimization failed:', err)\\n return 'FAILED', file_src\",\n \"def jpeg_to_png(img: bytes) -> bytes:\\n im = Image.open(BytesIO(img))\\n width = 240\\n height = int(im.size[1] * (240 / im.size[0]))\\n im = im.convert(\\\"RGB\\\").resize((width, height))\\n stream = BytesIO()\\n im.save(stream, format=\\\"PNG\\\")\\n return stream.getvalue()\",\n \"def resize_img(img, STANDARD_SIZE, verbose=False):\\n if verbose:\\n print \\\"changing size from %s to %s\\\" % (str(img.size), str(STANDARD_SIZE))\\n img = img.resize(STANDARD_SIZE)\\n return img\",\n \"def transform_image(self, image):\\n\\n image = self.image_processor.postprocess(image, output_type='pil')\\n return image\",\n \"def convertFrame(self):\\n try:\\n img = QImage(self.currentVideoFrame,\\n self.currentVideoFrame.shape[1],\\n self.currentVideoFrame.shape[0],\\n QImage.Format_RGB888\\n )\\n return img\\n except:\\n return None\",\n \"def convertFrame(self):\\n try:\\n img = QImage(self.currentVideoFrame,\\n self.currentVideoFrame.shape[1],\\n self.currentVideoFrame.shape[0],\\n QImage.Format_RGB888\\n )\\n return img\\n except:\\n return None\",\n \"def convert_cv_qt(self, cv_img):\\n\\t\\trgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\\n\\t\\th, w, ch = rgb_image.shape\\n\\t\\tbytes_per_line = ch * w\\n\\t\\tconvert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\\n\\n\\t\\tif w > 1000:\\n\\t\\t\\trat = w / 1000\\n\\t\\t\\tw = 1000\\n\\t\\t\\th = h / rat\\n\\n\\t\\tp = convert_to_Qt_format.scaled(int(w), int(h), Qt.KeepAspectRatio)\\n\\t\\treturn QPixmap.fromImage(p)\",\n \"def create_artificial_image(self):\\n background = self.BGI.create_background_image()\\n star_PSF = self.PSF.create_star_PSF()\\n header = self.HDR.create_header()\\n\\n fits.writeto(self.image_dir + self.image_name + '.fits',\\n background + star_PSF, overwrite=True, header=header)\",\n \"def transform(self, previousimage):\",\n \"def smaller(self):\\n w1, h1 = float(self.imwidth), float(self.imheight)\\n w2, h2 = float(self.__huge_size), float(self.__huge_size)\\n aspect_ratio1 = w1 / h1\\n aspect_ratio2 = w2 / h2 # it equals to 1.0\\n if aspect_ratio1 == aspect_ratio2:\\n image = Image.new('RGB', (int(w2), int(h2)))\\n k = h2 / h1 # compression ratio\\n w = int(w2) # band length\\n elif aspect_ratio1 > aspect_ratio2:\\n image = Image.new('RGB', (int(w2), int(w2 / aspect_ratio1)))\\n k = h2 / w1 # compression ratio\\n w = int(w2) # band length\\n else: # aspect_ratio1 < aspect_ration2\\n image = Image.new('RGB', (int(h2 * aspect_ratio1), int(h2)))\\n k = h2 / h1 # compression ratio\\n w = int(h2 * aspect_ratio1) # band length\\n i, j, n = 0, 1, round(0.5 + self.imheight / self.__band_width)\\n while i < self.imheight:\\n print('\\\\rOpening image: {j} from {n}'.format(j=j, n=n), end='')\\n band = min(self.__band_width, self.imheight - i) # width of the tile band\\n self.__tile[1][3] = band # set band width\\n self.__tile[2] = self.__offset + self.imwidth * i * 3 # tile offset (3 bytes per pixel)\\n self.__image.close()\\n self.__image = Image.open(self.path) # reopen / reset image\\n self.__image.size = (self.imwidth, band) # set size of the tile band\\n self.__image.tile = [self.__tile] # set tile\\n cropped = self.__image.crop((0, 0, self.imwidth, band)) # crop tile band\\n image.paste(cropped.resize((w, int(band * k) + 1), self.__filter), (0, int(i * k)))\\n i += band\\n j += 1\\n print('\\\\r' + 30 * ' ' + '\\\\r', end='') # hide printed string\\n return image\",\n \"def preprocess(exam, data_folder, save_path, image_format):\\n for v in ['L-CC', 'L-MLO', 'R-CC', 'R-MLO']:\\n if len(exam[v]) == 0:\\n continue\\n else:\\n for image in exam[v]:\\n image_path = data_folder + '/' + image + '.' + image_format\\n # Extract subdirectories\\n subdirs = \\\"/\\\".join(image.split('/')[:-1])\\n save_dirs = os.path.join(save_path, subdirs)\\n # Extract image id\\n image_id = image.split('/')[-1]\\n # Create save directories\\n os.makedirs(save_dirs, exist_ok=True)\\n png_save_path = os.path.join(save_dirs, image_id + '.png')\\n with Image(filename=image_path, format=image_format) as img:\\n with img.clone() as i:\\n i.auto_level()\\n with i.convert('png') as png_image:\\n png_image.transform(resize='896x1152!')\\n png_image.save(filename=png_save_path)\",\n \"def to_image(self, width=800, height=600, outline=20, background=\\\"white\\\", **kwargs):\\n img = _rodframe_image(\\n parameters=self.parameters,\\n width=width,\\n height=height,\\n outline=outline,\\n background=background,\\n **kwargs\\n )\\n return img\",\n \"def frame_to_pixmap(color_image): \\r\\n height, width, channel = color_image.shape\\r\\n bytes_per_line = channel * width\\r\\n\\r\\n q_img = QImage(color_image.data, width, height, bytes_per_line, QImage.Format_BGR888)\\r\\n return QPixmap.fromImage(q_img)\",\n \"def convert_cv_qt(self, cv_img):\\r\\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\\r\\n h, w, ch = rgb_image.shape\\r\\n bytes_per_line = ch * w\\r\\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\\r\\n p = convert_to_Qt_format.scaled(self.disply_width, self.display_height, Qt.KeepAspectRatio)\\r\\n return QPixmap.fromImage(p)\",\n \"def convert_cv_qt(self, cv_img):\\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\\n h, w, ch = rgb_image.shape\\n bytes_per_line = ch * w\\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\\n p = convert_to_Qt_format.scaled(225, 220) # , Qt.KeepAspectRatio)\\n return QPixmap.fromImage(p)\",\n \"def jpegoptim(filename, quality=None, root=None):\\n # jpegoptim - s - f - o - -all - progressive . / test.png\\n args = copy.copy(_JPEGOPTIM_ARGS)\\n if Settings.destroy_metadata:\\n args += [\\\"-s\\\"]\\n if Settings.force:\\n args += [\\\"-f\\\"]\\n if Settings.verbose:\\n args += [\\\"-v\\\"]\\n if quality:\\n args += [\\\"-m {}\\\".format(quality)]\\n if Settings.jpegtran_prog:\\n args += [\\\"--all-progressive\\\"]\\n\\n args += [filename]\\n if test:\\n print(\\\"jpegoptim: \\\", args)\\n return 0\\n\\n extern.run_ext(args, root)\\n return _JPEG_FORMAT\",\n \"def adjust(self, image):\\n ...\",\n \"def encode_scaled(data, size, version=0, level=QR_ECLEVEL_L, hint=QR_MODE_8,\\n case_sensitive=True):\\n version, src_size, im = encode(data, version, level, hint, case_sensitive)\\n if size < src_size:\\n size = src_size\\n qr_size = (size / src_size) * src_size\\n im = im.resize((qr_size, qr_size), Image.NEAREST)\\n pad = (size - qr_size) / 2\\n ret = Image.new(\\\"L\\\", (size, size), 255)\\n ret.paste(im, (pad, pad))\\n\\n return (version, size, ret)\",\n \"def saverescale(image, fname, outpath, scalefactor=0.5, preserve_name=False):\\n if not preserve_name:\\n fpath = genSavePath(outpath, fname, modstring=f\\\"resize_{scalefactor}\\\")\\n else:\\n fpath = genSavePath(outpath, fname)\\n newsize = (int(image.width * scalefactor), int(image.height * scalefactor))\\n im = copy(image)\\n im = im.resize(newsize)\\n try:\\n im.save(fpath, subsample=\\\"keep\\\", qtables=image.quantization, optimize=True)\\n\\n except IOError as m:\\n print( \\\"Resize({}) image creation failed for: {}. \\\\nReason:{}\\\".format(scalefactor,fname,m))\",\n \"def capture_image(self):\\n ext = self.image_save_type.lower()\\n\\n if self.calibrating:\\n print('calibrating')\\n\\n if ext == 'fits':\\n self.save_fits()\\n self._image_counter += 1\\n else:\\n img = self.original_image\\n path = os.path.join(self.home, 'data')\\n name = \\\"camtrak_frame_{}.png\\\".format(self._image_counter) \\n fn = os.path.join(path, name)\\n cv2.imwrite(fn, img)\\n\\n QtWidgets.QApplication.beep()\\n self.statusBar().showMessage(f'Saved image to {fn}')\\n self._image_counter += 1\",\n \"def thumbnail(self, fnameIn, fnameOut):\\n cmd = \\\"convert -define jpeg:size=500x150 \\\"\\n cmd += '\\\"%s\\\" ' % os.path.join(self.downloadFolder, fnameIn)\\n cmd += \\\"-auto-orient -thumbnail 250x150 \\\"\\n cmd += '\\\"%s\\\" ' % os.path.join(self.thumbnailFolder, fnameOut)\\n self.log(\\\"creating thumbnail ...\\\")\\n self.log(cmd)\\n process = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE)\\n process.wait()\",\n \"def image(self):\\n # TODO: make sure this method works for png, gif, tiff\\n if self.has_metadata:\\n self.extract_metadata()\\n tempdir_path = self.make_tempdir()\\n tempfile_path = os.path.join(tempdir_path, self.filename)\\n warnings.simplefilter('error', Image.DecompressionBombWarning)\\n try: # Do image conversions\\n img_in = Image.open(self.src_path)\\n img_out = Image.frombytes(img_in.mode, img_in.size, img_in.tobytes())\\n img_out.save(tempfile_path)\\n self.src_path = tempfile_path\\n except Exception as e: # Catch decompression bombs\\n # TODO: change this from all Exceptions to specific DecompressionBombWarning\\n self.add_error(e, \\\"Caught exception (possible decompression bomb?) while translating file {}.\\\".format(self.src_path))\\n self.make_dangerous()\\n self.add_file_string('Image file')\\n self.set_property('processing_type', 'image')\",\n \"def convert_cv_qt(self, cv_img):\\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\\n h, w, ch = rgb_image.shape\\n bytes_per_line = ch * w\\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\\n p = convert_to_Qt_format.scaled(self.display_width, self.display_height, Qt.KeepAspectRatio)\\n return QPixmap.fromImage(p)\",\n \"def convert_cv_qt(self, cv_img):\\n rgb_image = cv2.cvtColor(cv_img, cv2.COLOR_BGR2RGB)\\n h, w, ch = rgb_image.shape\\n bytes_per_line = ch * w\\n convert_to_Qt_format = QtGui.QImage(rgb_image.data, w, h, bytes_per_line, QtGui.QImage.Format_RGB888)\\n p = convert_to_Qt_format.scaled(self.display_width, self.display_height, Qt.KeepAspectRatio)\\n return QPixmap.fromImage(p)\",\n \"def image(self):\\r\\n\\r\\n if sys.version < '3':\\r\\n imageio = StringIO.StringIO(self._image_data)\\r\\n else:\\r\\n imageio = StringIO.BytesIO(self._image_data)\\r\\n\\r\\n try:\\r\\n source_image = PILImage.open(imageio)\\r\\n img = PILImage.new('RGBA', source_image.size, (0, 0, 0, 0))\\r\\n\\r\\n if source_image.mode == 'L':\\r\\n alpha = source_image.split()[0]\\r\\n transparency = source_image.info.get('transparency')\\r\\n mask = PILImage.eval(alpha, lambda a: 0 if a == transparency else 255)\\r\\n img.paste(source_image, (0, 0), mask=mask)\\r\\n else:\\r\\n img.paste(source_image, (0, 0))\\r\\n except IOError, e:\\r\\n raise PILUnavailableError(e.args[0].split()[1])\\r\\n finally:\\r\\n imageio.close()\\r\\n\\r\\n self.original_width, self.original_height = img.size\\r\\n\\r\\n # Crop the image searching for the smallest possible bounding box\\r\\n # without losing any non-transparent pixel.\\r\\n # This crop is only used if the crop flag is set in the config.\\r\\n if self.config['crop']:\\r\\n img = img.crop(img.split()[-1].getbbox())\\r\\n return img\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.54743165","0.54736084","0.5438891","0.54282427","0.541862","0.53912777","0.53576815","0.52602875","0.5242374","0.52363783","0.52289176","0.521572","0.5162085","0.51128095","0.51099354","0.5074247","0.50239307","0.5019632","0.5016915","0.5016185","0.49931777","0.49894148","0.49856457","0.49802148","0.49646667","0.49628535","0.4961163","0.4956524","0.49511573","0.49481258","0.49408063","0.49374783","0.4937359","0.49338785","0.4928059","0.4909096","0.4907542","0.4907439","0.49066687","0.49054083","0.48961937","0.48933542","0.48848376","0.48765782","0.48723835","0.48644525","0.48552758","0.4855209","0.48377427","0.48256147","0.48205557","0.48154747","0.48041075","0.47946286","0.479306","0.4791679","0.4789318","0.4788567","0.47861075","0.47796822","0.4775482","0.4772207","0.4772207","0.4766746","0.47611696","0.47600627","0.47594115","0.47557583","0.47455627","0.47452113","0.47381136","0.47381136","0.47381136","0.47354722","0.47307014","0.4730243","0.4726761","0.47245908","0.47236532","0.47232917","0.47232917","0.47141743","0.47128418","0.47112545","0.47066623","0.4697329","0.46949983","0.4685063","0.46791118","0.46766034","0.46611887","0.46573657","0.4651459","0.46471035","0.46469334","0.46463656","0.4642929","0.46427217","0.46427217","0.46391776"],"string":"[\n \"0.54743165\",\n \"0.54736084\",\n \"0.5438891\",\n \"0.54282427\",\n \"0.541862\",\n \"0.53912777\",\n \"0.53576815\",\n \"0.52602875\",\n \"0.5242374\",\n \"0.52363783\",\n \"0.52289176\",\n \"0.521572\",\n \"0.5162085\",\n \"0.51128095\",\n \"0.51099354\",\n \"0.5074247\",\n \"0.50239307\",\n \"0.5019632\",\n \"0.5016915\",\n \"0.5016185\",\n \"0.49931777\",\n \"0.49894148\",\n \"0.49856457\",\n \"0.49802148\",\n \"0.49646667\",\n \"0.49628535\",\n \"0.4961163\",\n \"0.4956524\",\n \"0.49511573\",\n \"0.49481258\",\n \"0.49408063\",\n \"0.49374783\",\n \"0.4937359\",\n \"0.49338785\",\n \"0.4928059\",\n \"0.4909096\",\n \"0.4907542\",\n \"0.4907439\",\n \"0.49066687\",\n \"0.49054083\",\n \"0.48961937\",\n \"0.48933542\",\n \"0.48848376\",\n \"0.48765782\",\n \"0.48723835\",\n \"0.48644525\",\n \"0.48552758\",\n \"0.4855209\",\n \"0.48377427\",\n \"0.48256147\",\n \"0.48205557\",\n \"0.48154747\",\n \"0.48041075\",\n \"0.47946286\",\n \"0.479306\",\n \"0.4791679\",\n \"0.4789318\",\n \"0.4788567\",\n \"0.47861075\",\n \"0.47796822\",\n \"0.4775482\",\n \"0.4772207\",\n \"0.4772207\",\n \"0.4766746\",\n \"0.47611696\",\n \"0.47600627\",\n \"0.47594115\",\n \"0.47557583\",\n \"0.47455627\",\n \"0.47452113\",\n \"0.47381136\",\n \"0.47381136\",\n \"0.47381136\",\n \"0.47354722\",\n \"0.47307014\",\n \"0.4730243\",\n \"0.4726761\",\n \"0.47245908\",\n \"0.47236532\",\n \"0.47232917\",\n \"0.47232917\",\n \"0.47141743\",\n \"0.47128418\",\n \"0.47112545\",\n \"0.47066623\",\n \"0.4697329\",\n \"0.46949983\",\n \"0.4685063\",\n \"0.46791118\",\n \"0.46766034\",\n \"0.46611887\",\n \"0.46573657\",\n \"0.4651459\",\n \"0.46471035\",\n \"0.46469334\",\n \"0.46463656\",\n \"0.4642929\",\n \"0.46427217\",\n \"0.46427217\",\n \"0.46391776\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7245555"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88571,"cells":{"query":{"kind":"string","value":"Save a rotated version of theimage."},"document":{"kind":"string","value":"def saverotation(image, fname, outpath, degreescounterlockwise=90, preserve_name=False):\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"rotated_{degreescounterlockwise}\")\n else:\n fpath = genSavePath(outpath, fname)\n im = copy(image)\n im = im.rotate(degreescounterlockwise)\n try:\n im.save(fpath, subsample=\"keep\", qtables=image.quantization, optimize=True)\n\n except IOError as m:\n print(( \"Rotated({}) image creation failed for: {}. \\nReason:{}\".format(degreescounterlockwise,fname,m)))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def rotate(image_path):\n try:\n with Image.open(image_path) as img:\n img = ImageOps.exif_transpose(img)\n img.save(image_path, format=img.format, quality=95)\n except Exception as e:\n log.warn(f'Cannot rotate input image: [{e}]')","def apply_rotation(image):\n\n\t# Load the image into a new BytesIO\n\tsImg = BytesIO(image)\n\tsNewImg = BytesIO(b'')\n\n\t# Create a new Pillow instance from the raw data\n\toImg = Pillow.open(sImg)\n\n\t# Store the image format\n\tsFormat = oImg.format\n\n\t# Get the proper sequence\n\ttry:\n\t\tlSeq = SEQUENCES[oImg._getexif()[ORIENTATION_TAG] - 1]\n\n\t\t# Transpose the image\n\t\tfor i in lSeq:\n\t\t\toImg = oImg.transpose(i)\n\n\t\t# Save the image using the same format as we got it in\n\t\toImg.save(sNewImg, sFormat)\n\n\t\t# Get the raw bytes\n\t\tsRet = sNewImg.getvalue()\n\n\t# If there's no sequence, return the image as is\n\texcept Exception as e:\n\t\tsRet = image\n\n\t# Cleanup\n\toImg.close()\n\tsImg.close()\n\tsNewImg.close()\n\n\t# Return\n\treturn sRet","def rotated_image(image):\n orientation = parameter('Orientation',90) # in degrees counter-clockwise\n if orientation == None: orienation = 0\n return image.rotate(orientation)","def flip_image(image_path, saved_location):\n image_obj = Image.open(image_path)\n rotated_image = image_obj.transpose(Image.FLIP_LEFT_RIGHT)\n rotated_image.save(saved_location)","def rotate(img_path):\r\n\timg = cv2.imread(img_path)\r\n\timgcorrect = ImgCorrect(img)\r\n\tlines_img = imgcorrect.img_lines()\r\n\tif lines_img is None:\r\n\t rotated = imgcorrect.rotate_image(0)\r\n\telse:\r\n\t degree = imgcorrect.search_lines()\r\n\t rotated = imgcorrect.rotate_image(degree)\r\n\tcv2.imwrite(img_path, rotated)","def rotate(path, degrees=-90):\n im = orientate(Image.open(path))\n rotated_im = im.rotate(degrees, expand=True)\n rotated_im.save(path)","def img_resize_rotate(file):\n orig_file = source_dir + file \n new_file = output_dir + file\n #print(\"source {} output {}\".format(orig_file, new_file))\n \n # Image.open('newauctionsheet.jpg').convert(mode=\"L\").show()\n img = Image.open( orig_file).resize((128,128)).rotate(90)\n new_img = img.convert('RGB').resize((128,128))\n new_img.save(output_dir + \"/\" + file, format=\"JPEG\")","def rotate(self):\n val = None\n try:\n \"\"\"Get rotation tags\"\"\"\n f = open(self._name, 'rb')\n tags = exifread.process_file(f)\n f.close()\n orientation = tags[\"Image Orientation\"]\n val = orientation.values\n\n except:\n return True\n\n if 3 in val:\n rotation = 180\n\n elif 6 in val:\n rotation = 270\n\n elif 8 in val:\n rotation = 90\n\n else:\n rotation = 0\n\n self._image = pygame.transform.rotate(self._image, rotation)","def rotate_right_90(img):\r\n #reading image\r\n im = Image.open(\"filename\")\r\n \r\n #flipping image 90 degrees\r\n newimg = im.transpose(PIL.Image.ROTATE_90)\r\n \r\n return img","def rotateImage(self):\n self.cnvImgOrig.rotate(\"./images/origPic.tiff\")\n self.cnvImgTest.rotate(\"./images/testPic.tiff\")","def save_image(self):\n self.compressed_image_id = str(uuid.uuid4().hex)\n plot.imsave(\n str(\n self.compressed_image_id + \"{}\").format(\n \".png\"), self.compressed_image)\n\n if self.verbose:\n print(\n \"Compressed image saved at \" + (\n str(self.compressed_image_id + \"{}\").format(\".png\")))","def rotate_image(self, file_name, num_rotations=3):\n image = cv2.imread(file_name, cv2.IMREAD_ANYDEPTH)\n destination_filename = self.parent_folder + os.path.basename(file_name)\n cv2.imwrite(destination_filename, np.rot90(image, num_rotations), [cv2.IMWRITE_PNG_COMPRESSION, 0])","def rotate(self, *args, **kwargs):\n return _image.image_rotate(self, *args, **kwargs)","def rotate_image(image):\n return tf.image.rot90(image)","def fix_orientation(self, pImg):\n path = pImg\n lImg = Image.open(pImg)\n lExif = lImg._getexif()\n if lExif != None:\n for tag, value in lExif.items():\n decoded = TAGS.get(tag, tag)\n if decoded == 'Orientation':\n if value == 3: lImg = lImg.rotate(180)\n if value == 6: lImg = lImg.rotate(270)\n if value == 8: lImg = lImg.rotate(90)\n break\n\n lImg.save(path, quality = 95)","def apply_image_rotation_by_exif(image, exif_orientation):\n if exif_orientation == 3:\n result_image = image.rotate(180, expand=True)\n elif exif_orientation == 6:\n result_image = image.rotate(270, expand=True)\n elif exif_orientation == 8:\n result_image = image.rotate(90, expand=True)\n else:\n result_image = image\n return result_image","def save_as(self, filename):\n opencv.imwrite(filename, self.img)","def rotate(self):\n pass","def rotate(self, cwise):\n try:\n self._is_transformable()\n cwise = get_int(cwise, allow_sign=True)\n except NotTransformable as e:\n self._app[\"statusbar\"].message(str(e) + \" rotate\", \"error\")\n return\n except StringConversionError as e:\n self._app[\"statusbar\"].message(str(e), \"error\")\n return\n images = self.get_images(\"Rotated\")\n cwise = cwise % 4\n # Update properties\n for fil in images:\n if fil in self._changes:\n self._changes[fil][0] = \\\n (self._changes[fil][0] + cwise) % 4\n else:\n self._changes[fil] = [cwise, 0, 0]\n # Rotate the image shown\n if self._app.get_path() in images:\n self.emit(\"changed\", \"rotate\", cwise)\n # Reload thumbnails of rotated images immediately\n if self._app[\"thumbnail\"].toggled:\n self.apply()","def rotate(img, angle, resample=False, expand=False, center=None):\r\n \r\n return img.rotate(angle, resample, expand, center)","def rotate(self, degrees):\n self.drawer.flush()\n self.img = self.img.rotate(degrees, PIL.Image.BICUBIC)\n self.update_drawer_img()\n return self","def rotate(self):\n tmp = self.width\n self.width = self.height\n self.height = tmp\n self.rotated = not self.rotated","def rotate(self):\n\n last_center = self.rect.center\n self.image = pg.transform.rotate(self.image_copy,self.angle)\n self.rect = self.image.get_rect()\n self.rect.center = last_center\n self.angle +=self.rotate_by","def archive_image(self, img):\n \n try:\n imgname = \"roboimg\" + str(int(time.time())) + \".png\"\n imgpath = os.path.join(self.imgdir, imgname)\n # print(\"Pic name \" + imgpath)\n\n cv2.imwrite(imgpath, img)\n except:\n self.logger.error(\"archive_image failed %s\" % (imgpath))","def store_image(self):\n cv2.imwrite(self.__diff_filename(), self.__diff_image())","def save_image(self):\n self.save()","def rotate90(self):","def rotate(file_path, angle):\n\n folder, file_name, ext = parse_file_path(file_path)\n url = addr + 'img/rotate'\n\n img = cv2.imread(file_path)\n _, img_encoded = cv2.imencode('.jpg', img)\n payload = img_encoded.tostring()\n response = requests.post(url, data = payload, params = {'agnle': angle})\n if response.status_code != 200:\n print(json.loads(response.content))\n return None\n \n img_array = uncompress_nparr(response.content)\n file_path = os.path.join(folder, file_name + '-' + random_string() + 'rotate' + ext)\n cv2.imwrite(file_path, img_array)\n return file_path","def visualize_rotated_image(image_uint8, rows_columns_top_left, width_crop, is_rotated, paths):\n if is_rotated:\n image_possible_rotation_uint8 = numpy.rot90(image_uint8,\n k=3)\n else:\n image_possible_rotation_uint8 = image_uint8\n \n # `visualize_crops` checks that `image_possible_rotation_uint8.dtype`\n # is equal to `numpy.uint8` and `image_possible_rotation_uint8.ndim`\n # is equal to 3.\n visualize_crops(image_possible_rotation_uint8,\n rows_columns_top_left,\n width_crop,\n paths[1:])\n for i in range(image_possible_rotation_uint8.shape[2]):\n save_image(paths[0][i],\n image_possible_rotation_uint8[:, :, i])","def savePhoto(self, path):\n if self.original_image and path:\n cv2.imwrite(path, self.original_image)","def _reorient_image(image, orientation='RAS'):\n\n orig_ornt = nib.io_orientation(image.affine)\n targ_ornt = nib.orientations.axcodes2ornt(orientation)\n transform = nib.orientations.ornt_transform(orig_ornt, targ_ornt)\n image = image.as_reoriented(transform)\n\n return image","def save(self, filepath):\n self.drawer.flush()\n self.img.save(filepath)","def Rotate(angle):\n def rotate_img(img, angle=angle):\n img = Ft.rotate(img, angle, resample=BILINEAR)\n return img\n return rotate_img","def load_image():\n if display_histogram == 1:\n image = cv2.imread(filename, cv2.IMREAD_GRAYSCALE)\n else:\n image = cv2.imread(filename, cv2.IMREAD_COLOR)\n\n image_resized = cv2.resize(image, None, fx=scale, fy=scale, interpolation=cv2.INTER_CUBIC)\n rows, cols = image_resized.shape[0:2] # get height and width \n\n rotation_matrix = cv2.getRotationMatrix2D((cols/2, rows/2), rotation, 1)\n image_rotated = cv2.warpAffine(image_resized, rotation_matrix, (cols, rows))\n\n return image_rotated","def _rotate_image_90(self, img: ndarray, k: int) -> ndarray:\n if img.shape[0] < img.shape[1]:\n self.y = np.rot90(img, k)\n return self.y\n else:\n return img","def save_grtrans_image(grt_obj):\n I_im = grt_obj.ivals[:,0,0].reshape(npix,npix).flatten()\n Q_im = grt_obj.ivals[:,1,0].reshape(npix,npix).flatten()\n U_im = grt_obj.ivals[:,2,0].reshape(npix,npix).flatten()\n V_im = grt_obj.ivals[:,3,0].reshape(npix,npix).flatten()\n\n # convert to Tb\n factor = 3.254e13/(RF**2 * psize_rad**2)\n I_im *= factor\n Q_im *= factor\n U_im *= factor\n V_im *= factor\n\n x = np.array([[i for i in range(npix)] for j in range(npix)]).flatten()\n y = np.array([[j for i in range(npix)] for j in range(npix)]).flatten()\n\n x -= npix/2\n y -= npix/2\n x = x*psize_uas\n y = y*psize_uas\n\n outdat = np.vstack((x.T,y.T,I_im.T,Q_im.T,U_im.T,V_im.T)).T\n np.savetxt('../rrjet_and_riaf/'+FNAME,outdat)\n #np.savetxt('../rrjet_and_riaf/grtrans_jet_compare_positron_noconv.txt',outdat)\n return","def rotate_no_clip(self, angle):\n # Calculate the size the expanded image needs to be to contain rotated image\n x, y = self.width, self.height\n w = abs(x*math.cos(angle)) + abs(y*math.sin(angle))\n h = abs(x*math.sin(angle)) + abs(y*math.cos(angle))\n\n # Paste the image into a larger frame and rotate\n img = Image.blank(w, h, 4, 0)\n img.paste(self, w/2-x/2, h/2-y/2)\n rotated = img.rotate(angle, (w/2, h/2))\n\n return rotated","def write_image(self, filename):\n cv2.imwrite(filename, self.image)","def rotate_pillow_image(pillow_image, orientation):\n image_format = pillow_image.format\n if orientation == 'from-image':\n if 'exif' in pillow_image.info:\n pillow_image = ImageOps.exif_transpose(pillow_image)\n elif orientation != 'none':\n angle, flip = orientation\n if angle > 0:\n rotation = getattr(Image.Transpose, f'ROTATE_{angle}')\n pillow_image = pillow_image.transpose(rotation)\n if flip:\n pillow_image = pillow_image.transpose(\n Image.Transpose.FLIP_LEFT_RIGHT)\n\n # Keep image format as it is discarded by transposition\n pillow_image.format = image_format\n return pillow_image","def rotate(self, image, angle):\n tmpImage = pygame.transform.rotate(image ,angle)\n imageCentreX = tmpImage.get_rect()[0] + tmpImage.get_rect()[2]/2\n imageCentreY = tmpImage.get_rect()[1] + tmpImage.get_rect()[3]/2\n\n targetWidth = tmpImage.get_rect()[2]\n targetHeight = tmpImage.get_rect()[3]\n\n imageOut = pygame.Surface((targetWidth, targetHeight))\n imageOut.fill((255,255,0))\n imageOut.set_colorkey((255,255,0))\n imageOut.blit(tmpImage,(0,0), pygame.Rect( imageCentreX-targetWidth/2,imageCentreY-targetHeight/2, targetWidth, targetHeight ) )\n return imageOut","def rotate90(input_file, rotations=[1,0,0],\n use_matrix=True, use_header=True):\n import os\n import numpy as np\n import nibabel as nb\n\n from mindboggle.utils.utils import execute\n\n # Load image volume\n img = nb.load(input_file)\n dat = img.get_data()\n if use_matrix:\n mat = img.get_affine()\n if use_header:\n hdr = img.get_header()\n pixdims = hdr.get_zooms()\n if pixdims[0] != pixdims[1] or \\\n pixdims[0] != pixdims[2] or \\\n pixdims[1] != pixdims[2]:\n os.error('This function assumes isometric voxels.')\n else:\n pixdims = [1,1,1]\n dims = img.get_shape()\n if dims[0] != dims[1] or \\\n dims[0] != dims[2] or \\\n dims[1] != dims[2]:\n os.error('This function assumes same dimensions along each axis.')\n\n dat_new = np.zeros(dims)\n lenx = dims[0]\n\n # Rotate about x-axis\n if rotations[0] != 0:\n print('Rotate about x-axis')\n pixdims = '{0} {1} {2}'.format(pixdims[0], pixdims[2], pixdims[1])\n for y in range(lenx):\n if rotations[0]==1:\n dat_new[:, :, y] = dat[:, y, :]\n #elif rotations[0]==-1:\n # dat_new[:, :, lenx-1-y] = dat[:, y, :]\n\n # Rotate about y-axis\n elif rotations[1] != 0:\n print('Rotate about y-axis')\n pixdims = '{0} {1} {2}'.format(pixdims[2], pixdims[1], pixdims[0])\n for z in range(lenx):\n if rotations[1]==1:\n dat_new[z, :, :] = dat[:, :, z]\n #elif rotations[1]==-1:\n # dat_new[lenx-1-z, :, :] = dat[:, :, z]\n\n # Rotate about z-axis\n elif rotations[2] != 0:\n print('Rotate about z-axis')\n pixdims = '{0} {1} {2}'.format(pixdims[1], pixdims[0], pixdims[2])\n for x in range(lenx):\n if rotations[2]==1:\n dat_new[:, x, :] = dat[x, :, :]\n #elif rotations[2]==-1:\n # dat_new[:, lenx-1-x, :] = dat[x, :, :]\n\n # Save output\n out_file = 'rot'+''.join([str(x) for x in rotations])\\\n + '_' + os.path.basename(input_file)\n if use_matrix:\n if use_header:\n img = nb.Nifti1Image(dat_new, mat, hdr)\n else:\n img = nb.Nifti1Image(dat_new, mat)\n elif use_header:\n img = nb.Nifti1Image(dat_new, np.eye(4,4), hdr)\n else:\n img = nb.Nifti1Image(dat_new, np.eye(4,4))\n\n img.to_filename(out_file)\n\n # Swap pixel dimensions\n print('Swap pixel dimensions')\n cmd = ['fslchpixdim', out_file, pixdims]\n execute(cmd)\n\n return out_file","def save_image(image, file_name):\n io.imsave(file_name,image)","def preprocess(self, image):\n if self.rotate == 0:\n return image\n\n angle = self.rotate * -90\n return image.rotate(angle, expand=True).crop((0, 0, self._w, self._h))","def save(self, filename):\n self.image.save(filename, self.options.img_format)","def _reorient_numpy_image(self, image, orientation):\n if len(image.shape) == 2:\n image = np.resize(image, (image.shape[0], image.shape[1], 1))\n if orientation in {\n tifftools.constants.Orientation.LeftTop.value,\n tifftools.constants.Orientation.RightTop.value,\n tifftools.constants.Orientation.LeftBottom.value,\n tifftools.constants.Orientation.RightBottom.value}:\n image = image.transpose(1, 0, 2)\n if orientation in {\n tifftools.constants.Orientation.BottomLeft.value,\n tifftools.constants.Orientation.BottomRight.value,\n tifftools.constants.Orientation.LeftBottom.value,\n tifftools.constants.Orientation.RightBottom.value}:\n image = image[::-1, ::, ::]\n if orientation in {\n tifftools.constants.Orientation.TopRight.value,\n tifftools.constants.Orientation.BottomRight.value,\n tifftools.constants.Orientation.RightTop.value,\n tifftools.constants.Orientation.RightBottom.value}:\n image = image[::, ::-1, ::]\n return image","def save_calibration(self):\n\n path = './{}/'.format(self.controller)\n # Check if path exist, if not, creates it.\n if not os.path.exists(os.path.dirname(path)):\n try:\n os.makedirs(os.path.dirname(path))\n except OSError as exc:\n # Guard against race condition\n if exc.errno != errno.EEXIST:\n raise\n\n # Save Jacobian matrix (self.mat)\n with open(\"./{i}/mat.txt\".format(i=self.controller), 'wt') as f:\n for i in range(3):\n f.write('{a},{b},{c}\\n'.format(a=self.mat[i, 0], b=self.mat[i, 1], c=self.mat[i, 2]))\n\n # Save rotational matrix\n with open(\"./{i}/rotmat.txt\".format(i=self.controller), 'wt') as f:\n for i in range(3):\n f.write('{a},{b},{c}\\n'.format(a=self.rot[i, 0], b=self.rot[i, 1], c=self.rot[i, 2]))\n\n # Save other data\n with open('./{i}/data.txt'.format(i=self.controller), 'wt') as f:\n f.write('{d}\\n'.format(d=self.um_px))\n f.write('{d}\\n'.format(d=self.x_init))\n f.write('{d}\\n'.format(d=self.y_init))\n f.write('{d}\\n'.format(d=self.template_loc[0]))\n f.write('{d}\\n'.format(d=self.template_loc[1]))","def rotate_img(image, degrees):\n if degrees == 90:\n return cv2.rotate(image, cv2.ROTATE_90_CLOCKWISE)\n elif degrees == 180:\n return cv2.rotate(image, cv2.ROTATE_180)\n elif degrees == 270:\n return cv2.rotate(image, cv2.ROTATE_90_COUNTERCLOCKWISE)\n elif degrees == 0:\n return image\n else:\n print(\"DEGREE = \", degrees)","def reorient_img(img, namer):\n from ndmg.utils.reg_utils import normalize_xform\n\n # Load image, orient as RAS\n orig_img = nib.load(img)\n reoriented = nib.as_closest_canonical(orig_img)\n normalized = normalize_xform(reoriented)\n\n # Image may be reoriented\n if normalized is not orig_img:\n print(\"%s%s%s\" % (\"Reorienting \", img, \" to RAS+...\"))\n out_name = \"%s%s%s%s\" % (\n namer.dirs[\"output\"][\"prep_anat\"],\n \"/\",\n img.split(\"/\")[-1].split(\".nii.gz\")[0],\n \"_reor_RAS.nii.gz\",\n )\n else:\n out_name = \"%s%s%s%s\" % (\n namer.dirs[\"output\"][\"prep_anat\"],\n \"/\",\n img.split(\"/\")[-1].split(\".nii.gz\")[0],\n \"_RAS.nii.gz\",\n )\n\n normalized.to_filename(out_name)\n\n return out_name","def save_image(self, filename):\n raster.save_image(filename, self.image, self.metadata)","def rot_image(original_image, angle):\n # Tämä copypastettu jostain netistä. Vaatii että kuva on neliö.\n assert original_image.get_width() == original_image.get_height(), \\\n \"Can't rotate image - not square. %r\" % original_image\n orig_rect = original_image.get_rect()\n rot_image = pygame.transform.rotate(original_image, angle)\n rot_rect = orig_rect.copy()\n rot_rect.center = rot_image.get_rect().center\n rot_image = rot_image.subsurface(rot_rect).copy()\n return rot_image","def rotateImage(self, img, angle=90):\n if (angle == 90) :\n return(cv2.flip(cv2.transpose(img),flipCode=0))\n elif (angle == -90) :\n return(cv2.flip(cv2.transpose(img),flipCode=1))\n else :\n center = (img.shape[1]/2.0,img.shape[0]/2.0)\n rotate = cv2.getRotationMatrix2D(center, angle, 1.0)\n return cv2.warpAffine(img, rotate, (img.shape[1], img.shape[0]))","def rotate(img, angle, resample=False, expand=False, center=None):\n\n #if not _is_pil_image(img):\n # raise TypeError('img should be PIL Image. Got {}'.format(type(img)))\n\n return img.rotate(angle, resample, expand, center)","def im_rotate(im_path, rotate_angle):\n image = cv.imread(str(im_path))\n image_r = cv.rotate(image, rotate_angle)\n\n return image_r","def reverse_transformation(self, rot90, flip_lr=False):\n\n transformed_ROI = copy.deepcopy(self) #Make a copy of itself to transform and return\n\n # Undo the left-right flip\n if flip_lr:\n transformed_ROI.center = (transformed_ROI.center[0], self.img_shape[1] - transformed_ROI.center[1])\n\n #Undo the rotation of the image\n cent = transformed_ROI.center\n if rot90 == 1:\n transformed_ROI.center = (cent[1], self.img_shape[0] - cent[0])\n transformed_ROI.size = (transformed_ROI.size[1], transformed_ROI.size[0])\n elif rot90 == 2:\n transformed_ROI.center = (self.img_shape[0] - cent[0], self.img_shape[1] - cent[1])\n elif rot90 == 3:\n transformed_ROI.center = (self.img_shape[1] - cent[1], cent[0])\n transformed_ROI.size = (transformed_ROI.size[1], transformed_ROI.size[0])\n\n return transformed_ROI","def rotate((x,y)):\n orientation = parameter('Orientation',90) # in degrees counter-clockwise\n if orientation == None: orienation = 0\n w,h = image_size()\n if orientation == 0: return (x,y)\n if orientation == -90: return (h-y,x)\n if orientation == 90: return (y,w-x)\n if orientation == 180: return (w-x,h-y)\n return (x,y)","def _save(filename, img):\n if not os.path.exists(OUTPUT_DIR):\n os.makedirs(OUTPUT_DIR)\n # filename = filename+'.png'\n filename = os.path.join(OUTPUT_DIR, filename)\n # print(filename, img.shape)\n cv.imwrite(filename, img)","def save_image(self, filename):\n if filename[-4:] != '.pkl':\n filename + '.pkl'\n with open(filename, 'wb') as output: # Overwrites any existing file.\n pickle.dump(self, output, pickle.HIGHEST_PROTOCOL)","def save(self, fn):\n plt.imsave(fn, self.image)","def imwrite(image, path):\n return scipy.misc.imsave(path, to_range(image, 0, 255, np.uint8))","def write(self, image):\n raise NotImplementedError()","def img_save(self):\n file_name, extension = return_folder_file_extension(self.img_name)[1:]\n image_name_save = \"%s_D=%s_Rs=%s_size=%s_offset=%i%s\" % (file_name, self.D, self.Rs, self.axe_X, self.offset_X+self.offset_X2, extension)\n\n if self.img2 is not None:\n self.img2.save(image_name_save)\n print(\"Saved \"+image_name_save)\n else:\n print(\"No image to save\")","def save_image(img, path):\n cv2.imwrite(path, img)","def rotate_image_set(self, folder_name, num_rotations=3):\n print(\"Rotating images in folder: \"+str(folder_name))\n photo_list = self.get_photo_list(folder_name, '*.png')\n destination_folder = folder_name+\"_rotated90\"\n\n try:\n print(\"Making dir \" + str(destination_folder) + \" for rotation\")\n os.mkdir(destination_folder)\n except OSError as e:\n print(e)\n print(\"Folder likely exists, have you already done this rotation??\")\n return\n\n for i, name in enumerate(photo_list):\n print(\"Rotating \" +str(i) + \" of \" + str(len(photo_list)))\n file_name = folder_name + '/' + name\n destination_filename = destination_folder + '/' + name[:-4] + '.png'\n image = cv2.imread(file_name, cv2.IMREAD_ANYDEPTH)\n cv2.imwrite(destination_filename, np.rot90(image, num_rotations), [cv2.IMWRITE_PNG_COMPRESSION, 0])","def img_save(name,img):\n cv2.imwrite(name,img)","def rotate(img, angle):\n if not _is_numpy(img):\n raise TypeError('img should be Numpy Image. Got {}'.format(type(img)))\n\n aug = iaa.Affine(rotate=angle)\n return aug.augment_image(img)","def save_image(filename, image):\n im = cv2.resize(image, None, fx=SCALE_DOWN, fy=SCALE_DOWN)\n cv2.imwrite(os.path.join(OUT_DIR, filename), im)","def imwrite(image, path):\n\n if image.ndim == 3 and image.shape[2] == 1: # for gray image\n image = np.array(image, copy=True)\n image.shape = image.shape[0:2]\n\n imgarray=((image+1.0)*127.5).astype(np.uint8)\n img=Image.fromarray(imgarray)\n img.save(path)","def _rotate_img(self, results):\n angle = self.angle\n height, width = results['img_shape'][:2]\n center = ((width - 1) * 0.5, (height - 1) * 0.5)\n\n # Compute rotation matrix\n mat_rotation = cv2.getRotationMatrix2D(center, -angle, 1)\n\n # Compute height and width of new image after rotation\n cos = np.abs(mat_rotation[0, 0])\n sin = np.abs(mat_rotation[0, 1])\n width_new = height * sin + width * cos\n height_new = height * cos + width * sin\n mat_rotation[0, 2] += (width_new - width) * 0.5\n mat_rotation[1, 2] += (height_new - height) * 0.5\n width_new = int(np.round(width_new))\n height_new = int(np.round(height_new))\n \n # Rotate image\n img_rotation = cv2.warpAffine(results['img'], mat_rotation, (width_new, height_new),\n borderValue=self.borderValue)\n results['img'] = img_rotation\n results['img_shape'] = results['img'].shape\n\n # Rotate corresponding annotations: all boxes in bbox_fields\n for key in results.get('bbox_fields', []):\n gt_boxes_ret = []\n for poly in results[key]:\n rot_array = []\n poly_length = len(poly)\n\n if poly_length == 4:\n poly = [poly[0], poly[1], poly[2], poly[1], poly[2], poly[3], poly[0], poly[3]]\n\n # Convert to np.array of shape (:, 2)\n for i in range(0, len(poly), 2):\n rot_array.append(np.array([poly[i], poly[i + 1]]))\n\n # Rotate corresponding annotations\n rot_array = np.array([rot_array])\n rot_array = cv2.transform(rot_array, mat_rotation).squeeze().reshape(len(poly))\n\n if poly_length == 4:\n x_coords = rot_array[0::2]\n y_coords = rot_array[1::2]\n rot_array = np.array([\n np.min(x_coords),\n np.min(y_coords),\n np.max(x_coords),\n np.max(y_coords)\n ])\n\n gt_boxes_ret.append(rot_array)\n if len(results[key]) > 0:\n results[key] = gt_boxes_ret\n\n # Rotate gt_bboxes according to gt_poly_bboxes\n if 'gt_bboxes' in results and 'gt_poly_bboxes' in results:\n gt_bboxes = []\n gt_bboxes_ignore = []\n\n for poly in results['gt_poly_bboxes']:\n poly = np.array(poly, dtype=np.double)\n x_coords = poly[0::2]\n y_coords = poly[1::2]\n aligned_poly = [\n np.min(x_coords),\n np.min(y_coords),\n np.max(x_coords),\n np.max(y_coords)\n ]\n gt_bboxes.append(aligned_poly)\n\n for poly in results['gt_poly_bboxes_ignore']:\n poly = np.array(poly, dtype=np.double)\n x_coords = poly[0::2]\n y_coords = poly[1::2]\n aligned_poly = [\n np.min(x_coords),\n np.min(y_coords),\n np.max(x_coords),\n np.max(y_coords)\n ]\n gt_bboxes_ignore.append(aligned_poly)\n\n if len(gt_bboxes) == 0:\n gt_bboxes = np.zeros((0, 4), dtype=np.float32)\n else:\n gt_bboxes = np.array(gt_bboxes, dtype=np.float32)\n\n if len(gt_bboxes_ignore) == 0:\n gt_bboxes_ignore = np.zeros((0, 4), dtype=np.float32)\n else:\n gt_bboxes_ignore = np.array(gt_bboxes_ignore, dtype=np.float32)\n\n results['gt_bboxes'] = gt_bboxes\n results['gt_bboxes_ignore'] = gt_bboxes_ignore\n\n # Rotate corresponding annotations: all boxes in cbbox_fields\n for key in results.get('cbbox_fields', []):\n gt_cboxes_ret = []\n for instance in results[key]:\n tmp_cboxes = []\n for poly in instance:\n rot_array = []\n # Convert to np.array of shape (:, 2)\n for i in range(0, len(poly), 2):\n rot_array.append(np.array([poly[i], poly[i + 1]]))\n rot_array = np.array([rot_array])\n # Rotate corresponding annotations\n rot_array = cv2.transform(rot_array, mat_rotation).squeeze().reshape(len(poly))\n tmp_cboxes.append(rot_array)\n gt_cboxes_ret.append(tmp_cboxes)\n results[key] = gt_cboxes_ret\n\n # Rotate corresponding annotations: all masks in mask_fields\n for key in results.get('mask_fields', []):\n mask = results[key].masks.transpose((1, 2, 0))\n if len(results[key].masks) == 0:\n results[key] = results[key].resize((height_new, width_new))\n else:\n # Rotate mask\n mask_rotation = cv2.warpAffine(mask, mat_rotation, (width_new, height_new),\n borderValue=self.borderValue)\n if mask_rotation.ndim == 2:\n # case when only one mask, (h, w)\n mask_rotation = mask_rotation[:, :, None] # (h, w, 1)\n mask_rotation = mask_rotation.transpose((2, 0, 1))\n results[key].masks = mask_rotation\n results[key].height = height_new\n results[key].width = width_new","def saveflip(image, fname, outpath, axis='x', preserve_name=False):\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"mirror_{axis}\")\n else:\n fpath = genSavePath(outpath, fname)\n im = copy(image)\n if axis == 'x':\n im = im.transpose(Image.FLIP_LEFT_RIGHT)\n elif axis == 'y':\n im = im.transpose(Image.FLIP_TOP_BOTTOM)\n else:\n raise Exception('No valid axis procvided for flipping: {} - received value: {}'.format(fname, axis))\n try:\n im.save(fpath, subsample=\"keep\", qtables=image.quantization, optimize=True)\n\n except IOError as m:\n print( \"Flipped({}) image creation failed for: {}. \\nReason:{}\".format(axis,fname,m))","def save(self):\n\n self.image.save(\"./output/\" + self.name + \" pg\" + str(self._page) + \".png\")","def detect_orientation(image):\n custom_oem_psm_config = r'--oem 1--psm 7'\n newdata = pytesseract.image_to_osd(image,config= custom_oem_psm_config)\n rotation = int(re.search('(?<=Rotate: )\\\\d+', newdata).group(0))\n # print(\"Rotation degrees : \", rotation)\n return rotate_img(image, rotation)","def save(\n self,\n output_path: str,\n show_confidence: bool = True,\n ) -> None:\n image = self.draw(show_confidence=show_confidence)\n save_image(image=image, path=output_path)","def rotate_and_wrap_image(self, image, degree_of_rotation):\n\n image_center = tuple(np.array(image.shape[1::-1]) / 2)\n rot_mat = cv2.getRotationMatrix2D(image_center, degree_of_rotation, 1.0)\n # borderMode (constant) and borderValue are important for maintaiing consistency \n ri = cv2.warpAffine(image, rot_mat, image.shape[1::-1], flags=cv2.INTER_LINEAR, borderMode = cv2.BORDER_CONSTANT,borderValue = (255,255,255))\n return ri","def rotate_augmentation():\n rand_rotate = np.random.randint(180)\n return lambda image: rotate_with_extension(image, rand_rotate)","def save_calibration(filename):\n pass","def rotateIMG(self):\n self.blit_image = pygame.transform.rotate(self.blit_image, self.blitHeading - 45)\n self.rect = self.blit_image.get_rect()\n self.rect.center = (int(self.pos.x), int(self.pos.y))","def rotate(self, angle, reshape=False):\n return IntensityMap.rotate(self, angle, reshape=reshape)","def save(self, filename):\n print(\"Saving...\", end=\"\\r\")\n canvas = self.canvas[self.N:self.S,self.W:self.E]\n cv2.imwrite(\"./Output/\"+filename, canvas)\n print(\"Saved:\",filename)","def rotate(self):\r\n self.rot = (self.vel.y * -3)\r\n if self.rot < -90:\r\n self.rot = -90\r\n \r\n new_image = pg.transform.rotate(self.bird_sprites[self.sprite_frame], self.rot)\r\n old_center = self.rect.center\r\n self.image = new_image\r\n self.rect = self.image.get_rect()\r\n self.rect.center = old_center\r\n # self.animate()\r","def rotate(im: Image) -> Image:\n return im.rotate(random.randint(0, 360))","def rotate(self, image, angle):\n # Get the image size\n # No that's not an error - NumPy stores image matricies backwards\n image_size = (image.shape[1], image.shape[0])\n image_center = tuple(np.array(image_size) / 2)\n\n # Convert the OpenCV 3x2 rotation matrix to 3x3\n rot_mat = np.vstack(\n [cv2.getRotationMatrix2D(image_center, angle, 1.0), [0, 0, 1]]\n )\n\n rot_mat_notranslate = np.matrix(rot_mat[0:2, 0:2])\n\n # Shorthand for below calcs\n image_w2 = image_size[0] * 0.5\n image_h2 = image_size[1] * 0.5\n\n # Obtain the rotated coordinates of the image corners\n rotated_coords = [\n (np.array([-image_w2, image_h2]) * rot_mat_notranslate).A[0],\n (np.array([image_w2, image_h2]) * rot_mat_notranslate).A[0],\n (np.array([-image_w2, -image_h2]) * rot_mat_notranslate).A[0],\n (np.array([image_w2, -image_h2]) * rot_mat_notranslate).A[0]\n ]\n\n # Find the size of the new image\n x_coords = [pt[0] for pt in rotated_coords]\n x_pos = [x for x in x_coords if x > 0]\n x_neg = [x for x in x_coords if x < 0]\n\n y_coords = [pt[1] for pt in rotated_coords]\n y_pos = [y for y in y_coords if y > 0]\n y_neg = [y for y in y_coords if y < 0]\n\n right_bound = max(x_pos)\n left_bound = min(x_neg)\n top_bound = max(y_pos)\n bot_bound = min(y_neg)\n\n new_w = int(abs(right_bound - left_bound))\n new_h = int(abs(top_bound - bot_bound))\n\n # We require a translation matrix to keep the image centred\n trans_mat = np.matrix([\n [1, 0, int(new_w * 0.5 - image_w2)],\n [0, 1, int(new_h * 0.5 - image_h2)],\n [0, 0, 1]\n ])\n\n # Compute the tranform for the combined rotation and translation\n affine_mat = (np.matrix(trans_mat) * np.matrix(rot_mat))[0:2, :]\n\n # Apply the transform\n result = cv2.warpAffine(\n image,\n affine_mat,\n (new_w, new_h),\n flags=cv2.INTER_LINEAR\n )\n\n return result","def __cv2_rotate(image, deg):\n num_rows, num_cols = image.shape[:2]\n\n rotation_matrix = cv.getRotationMatrix2D((num_cols / 2, num_rows / 2), deg, 1)\n image = cv.warpAffine(np.float32(image), rotation_matrix, (num_cols, num_rows))\n # In case of only one channel, warpAffine removes channel dimension.\"\"\"\n return image","def convert_to_jpg(filepath):\n\n f, e = os.path.splitext(filepath)\n outfile = f + \".jpg\"\n # We don't want to delete .JPG or .JPEG so we lower the extension\n filepath_lowered = f + e.lower()\n if outfile != filepath_lowered:\n try:\n image = Image.open(filepath)\n\n # Rotate image: https://stackoverflow.com/a/6218425\n # for orientation in ExifTags.TAGS.keys() :\n # if ExifTags.TAGS[orientation] == 'Orientation' : break\n orientation = 274 # get 274 through upper loop\n try:\n exif=dict(image._getexif().items())\n print(exif[orientation])\n if exif[orientation] == 3 :\n image=image.rotate(180, expand=True)\n elif exif[orientation] == 6 :\n image=image.rotate(270, expand=True)\n elif exif[orientation] == 8 :\n image=image.rotate(90, expand=True)\n except (AttributeError, KeyError): # image has no meta data\n pass\n\n image.convert('RGB').save(outfile)\n except IOError:\n print(\"cannot convert\", filepath)\n exit(1)\n os.remove(filepath)\n return outfile\n return filepath","def transform(self, previousimage):","def orient(self,Y):\r\n self.orientation[Y]+=1\r\n if self.orientation[Y]>3:\r\n self.orientation[Y]=0\r\n if self.orientation[Y]<0:\r\n self.orientation[Y]=3\r\n self.can.delete(self.image_bateau[Y])\r\n self.image_bateau[Y]=self.create_image(self.img[self.orientation[Y]][Y],0,0)\r\n self.affichage(Y)","def rotate_with_extension(image, alpha):\n # Determine if alpha is larger than 90 degrees and rotate accordingly\n # Number of 90 degree turns\n quarter = int(alpha / 90)\n # turn the image 90 deg quarter times\n image = image.rotate(quarter * 90)\n # Get the angle of the rest of the rotation\n alpha = alpha % 90\n\n # Size of image\n size = image.size[0]\n # Get radians\n alpha_rad = alpha/180 * np.pi\n\n # Compute the size of the extended image needed to keep an image of the\n # right size after cropping\n cos = np.cos(alpha_rad)\n sin = np.sin(alpha_rad)\n L = int(size * (sin + cos))\n\n # Extend the image then rotate it\n extend = mirror_extend(int((L-size)/2), image)\n rotate = extend.rotate(alpha, expand=1)\n # Get the current side length of the rotated image and compute the\n # difference with the original image to obtain the number of pixels to remove\n # from each border\n side = rotate.size[0]\n pixel_to_remove = (side - size)/2\n # Crop the image\n return rotate.crop((pixel_to_remove, pixel_to_remove, pixel_to_remove + size, pixel_to_remove+size))","def write(self, filename):\n\n self.__image.save(filename)","def saveImageAs(self, name):\n\t\tself.image.save(name)","def save(self, **kwargs):\n self.remove_file()\n if not self.image:\n self.generate(save=False)\n else:\n self.image.name = self.file()\n super(FormatedPhoto, self).save(**kwargs)","def save_image(filename, matrix):\n im = Image.new('L', list(reversed(matrix.shape)))\n data = np.floor(np.ravel(matrix) * 256)\n im.putdata(data)\n im.save(filename)","def data(self):\n image = transform.warp(self._raw_image_data, self._corrective_transform)\n image_data = transform.rotate(image, self._rotation_offset)\n return image_data","def image_preview(img_path):\r\n img = Image.open(img_path)\r\n t_size = 256, 256\r\n\r\n try:\r\n if \"exif\" in img.info:\r\n exif_dict = piexif.load(img.info[\"exif\"])\r\n if piexif.ImageIFD.Orientation in exif_dict[\"0th\"]:\r\n orientation = exif_dict[\"0th\"].pop(piexif.ImageIFD.Orientation)\r\n #exif_bytes = piexif.dump(exif_dict)\r\n if orientation == 2:\r\n img = img.transpose(Image.FLIP_LEFT_RIGHT)\r\n elif orientation == 3:\r\n img = img.rotate(180)\r\n elif orientation == 4:\r\n img = img.rotate(180).transpose(Image.FLIP_LEFT_RIGHT)\r\n elif orientation == 5:\r\n img = img.rotate(-90, expand=True).transpose(Image.FLIP_LEFT_RIGHT)\r\n elif orientation == 6:\r\n img = img.rotate(-90, expand=True)\r\n elif orientation == 7:\r\n img = img.rotate(90, expand=True).transpose(Image.FLIP_LEFT_RIGHT)\r\n elif orientation == 8:\r\n img = img.rotate(90, expand=True)\r\n except:\r\n print('exif data problem in', img_path)\r\n\r\n new_image = Image.new(img.mode, t_size, color=(255,255,255))\r\n img.thumbnail(t_size, Image.ANTIALIAS) # in-place\r\n x_offset= (new_image.size[0] - img.size[0]) // 2\r\n y_offset= (new_image.size[1] - img.size[1]) // 2\r\n new_image.paste(img, (x_offset, y_offset))\r\n img = new_image\r\n\r\n # in memory image -> bytes -> base64_string\r\n buffered = BytesIO()\r\n img.save(buffered, format=\"JPEG\")\r\n img_preview = base64.b64encode(buffered.getvalue()).decode('utf-8')\r\n\r\n return img_preview","def rotate(self, angle):\n rotmat = rotation_matrix_2d(angle)\n rotated = np.dot(rotmat.T, [self.pix_x.value, self.pix_y.value])\n self.pix_x = rotated[0] * self.pix_x.unit\n self.pix_y = rotated[1] * self.pix_x.unit\n self.pix_rotation -= angle","def rotation(self):\n\t\treturn self.piv.a.rotate.v","def save(image, name):\n from matplotlib import pyplot\n import matplotlib as mpl\n fig = pyplot.figure()\n ax = fig.add_subplot(1,1,1)\n imgplot = ax.imshow(image, cmap=mpl.cm.Greys)\n imgplot.set_interpolation('nearest')\n ax.xaxis.set_ticks_position('top')\n ax.yaxis.set_ticks_position('left')\n pyplot.savefig(name)","def save_img(img: np.ndarray, path: str) -> None:\n\n img_obj = Image.fromarray(img)\n img_obj.save(path)","def save(self, file: Union[str, Path, BinaryIO]):\n np.savez_compressed(\n file, avg_img=self.avg_img, corr_img=self.corr_img,\n fit_result=_fit_result_to_list(self.fit_result),\n fit_amplitude=self.fit_amplitude, bg=self.bg)","def save_image(nom, image, _geo_trans):\n cols = image.shape[2]\n rows = image.shape[1]\n bands = image.shape[0]\n print(bands, cols, rows)\n driver = gdal.GetDriverByName(\"GTiff\")\n out_raster = driver.Create(nom, cols, rows, bands, gdal.GDT_Byte)\n # if (geo_trans):\n # outRaster.SetGeoTransform(geo_trans)\n band = out_raster.GetRasterBand(1)\n band.WriteArray(np.round(image[0]))\n band = out_raster.GetRasterBand(2)\n band.WriteArray(np.round(image[1]))\n band = out_raster.GetRasterBand(3)\n band.WriteArray(np.round(image[2]))","def save(img, path, file_name):\n\n name = os.path.join(path,file_name).replace('/', os.sep)\n\n io.imsave(name,img)","def rotate(image, degrees):\n # Convert from degrees to radians.\n degrees_to_radians = math.pi / 180.0\n radians = degrees * degrees_to_radians\n return tfa.image.rotate(tf.convert_to_tensor(image), tf.constant(radians))"],"string":"[\n \"def rotate(image_path):\\n try:\\n with Image.open(image_path) as img:\\n img = ImageOps.exif_transpose(img)\\n img.save(image_path, format=img.format, quality=95)\\n except Exception as e:\\n log.warn(f'Cannot rotate input image: [{e}]')\",\n \"def apply_rotation(image):\\n\\n\\t# Load the image into a new BytesIO\\n\\tsImg = BytesIO(image)\\n\\tsNewImg = BytesIO(b'')\\n\\n\\t# Create a new Pillow instance from the raw data\\n\\toImg = Pillow.open(sImg)\\n\\n\\t# Store the image format\\n\\tsFormat = oImg.format\\n\\n\\t# Get the proper sequence\\n\\ttry:\\n\\t\\tlSeq = SEQUENCES[oImg._getexif()[ORIENTATION_TAG] - 1]\\n\\n\\t\\t# Transpose the image\\n\\t\\tfor i in lSeq:\\n\\t\\t\\toImg = oImg.transpose(i)\\n\\n\\t\\t# Save the image using the same format as we got it in\\n\\t\\toImg.save(sNewImg, sFormat)\\n\\n\\t\\t# Get the raw bytes\\n\\t\\tsRet = sNewImg.getvalue()\\n\\n\\t# If there's no sequence, return the image as is\\n\\texcept Exception as e:\\n\\t\\tsRet = image\\n\\n\\t# Cleanup\\n\\toImg.close()\\n\\tsImg.close()\\n\\tsNewImg.close()\\n\\n\\t# Return\\n\\treturn sRet\",\n \"def rotated_image(image):\\n orientation = parameter('Orientation',90) # in degrees counter-clockwise\\n if orientation == None: orienation = 0\\n return image.rotate(orientation)\",\n \"def flip_image(image_path, saved_location):\\n image_obj = Image.open(image_path)\\n rotated_image = image_obj.transpose(Image.FLIP_LEFT_RIGHT)\\n rotated_image.save(saved_location)\",\n \"def rotate(img_path):\\r\\n\\timg = cv2.imread(img_path)\\r\\n\\timgcorrect = ImgCorrect(img)\\r\\n\\tlines_img = imgcorrect.img_lines()\\r\\n\\tif lines_img is None:\\r\\n\\t rotated = imgcorrect.rotate_image(0)\\r\\n\\telse:\\r\\n\\t degree = imgcorrect.search_lines()\\r\\n\\t rotated = imgcorrect.rotate_image(degree)\\r\\n\\tcv2.imwrite(img_path, rotated)\",\n \"def rotate(path, degrees=-90):\\n im = orientate(Image.open(path))\\n rotated_im = im.rotate(degrees, expand=True)\\n rotated_im.save(path)\",\n \"def img_resize_rotate(file):\\n orig_file = source_dir + file \\n new_file = output_dir + file\\n #print(\\\"source {} output {}\\\".format(orig_file, new_file))\\n \\n # Image.open('newauctionsheet.jpg').convert(mode=\\\"L\\\").show()\\n img = Image.open( orig_file).resize((128,128)).rotate(90)\\n new_img = img.convert('RGB').resize((128,128))\\n new_img.save(output_dir + \\\"/\\\" + file, format=\\\"JPEG\\\")\",\n \"def rotate(self):\\n val = None\\n try:\\n \\\"\\\"\\\"Get rotation tags\\\"\\\"\\\"\\n f = open(self._name, 'rb')\\n tags = exifread.process_file(f)\\n f.close()\\n orientation = tags[\\\"Image Orientation\\\"]\\n val = orientation.values\\n\\n except:\\n return True\\n\\n if 3 in val:\\n rotation = 180\\n\\n elif 6 in val:\\n rotation = 270\\n\\n elif 8 in val:\\n rotation = 90\\n\\n else:\\n rotation = 0\\n\\n self._image = pygame.transform.rotate(self._image, rotation)\",\n \"def rotate_right_90(img):\\r\\n #reading image\\r\\n im = Image.open(\\\"filename\\\")\\r\\n \\r\\n #flipping image 90 degrees\\r\\n newimg = im.transpose(PIL.Image.ROTATE_90)\\r\\n \\r\\n return img\",\n \"def rotateImage(self):\\n self.cnvImgOrig.rotate(\\\"./images/origPic.tiff\\\")\\n self.cnvImgTest.rotate(\\\"./images/testPic.tiff\\\")\",\n \"def save_image(self):\\n self.compressed_image_id = str(uuid.uuid4().hex)\\n plot.imsave(\\n str(\\n self.compressed_image_id + \\\"{}\\\").format(\\n \\\".png\\\"), self.compressed_image)\\n\\n if self.verbose:\\n print(\\n \\\"Compressed image saved at \\\" + (\\n str(self.compressed_image_id + \\\"{}\\\").format(\\\".png\\\")))\",\n \"def rotate_image(self, file_name, num_rotations=3):\\n image = cv2.imread(file_name, cv2.IMREAD_ANYDEPTH)\\n destination_filename = self.parent_folder + os.path.basename(file_name)\\n cv2.imwrite(destination_filename, np.rot90(image, num_rotations), [cv2.IMWRITE_PNG_COMPRESSION, 0])\",\n \"def rotate(self, *args, **kwargs):\\n return _image.image_rotate(self, *args, **kwargs)\",\n \"def rotate_image(image):\\n return tf.image.rot90(image)\",\n \"def fix_orientation(self, pImg):\\n path = pImg\\n lImg = Image.open(pImg)\\n lExif = lImg._getexif()\\n if lExif != None:\\n for tag, value in lExif.items():\\n decoded = TAGS.get(tag, tag)\\n if decoded == 'Orientation':\\n if value == 3: lImg = lImg.rotate(180)\\n if value == 6: lImg = lImg.rotate(270)\\n if value == 8: lImg = lImg.rotate(90)\\n break\\n\\n lImg.save(path, quality = 95)\",\n \"def apply_image_rotation_by_exif(image, exif_orientation):\\n if exif_orientation == 3:\\n result_image = image.rotate(180, expand=True)\\n elif exif_orientation == 6:\\n result_image = image.rotate(270, expand=True)\\n elif exif_orientation == 8:\\n result_image = image.rotate(90, expand=True)\\n else:\\n result_image = image\\n return result_image\",\n \"def save_as(self, filename):\\n opencv.imwrite(filename, self.img)\",\n \"def rotate(self):\\n pass\",\n \"def rotate(self, cwise):\\n try:\\n self._is_transformable()\\n cwise = get_int(cwise, allow_sign=True)\\n except NotTransformable as e:\\n self._app[\\\"statusbar\\\"].message(str(e) + \\\" rotate\\\", \\\"error\\\")\\n return\\n except StringConversionError as e:\\n self._app[\\\"statusbar\\\"].message(str(e), \\\"error\\\")\\n return\\n images = self.get_images(\\\"Rotated\\\")\\n cwise = cwise % 4\\n # Update properties\\n for fil in images:\\n if fil in self._changes:\\n self._changes[fil][0] = \\\\\\n (self._changes[fil][0] + cwise) % 4\\n else:\\n self._changes[fil] = [cwise, 0, 0]\\n # Rotate the image shown\\n if self._app.get_path() in images:\\n self.emit(\\\"changed\\\", \\\"rotate\\\", cwise)\\n # Reload thumbnails of rotated images immediately\\n if self._app[\\\"thumbnail\\\"].toggled:\\n self.apply()\",\n \"def rotate(img, angle, resample=False, expand=False, center=None):\\r\\n \\r\\n return img.rotate(angle, resample, expand, center)\",\n \"def rotate(self, degrees):\\n self.drawer.flush()\\n self.img = self.img.rotate(degrees, PIL.Image.BICUBIC)\\n self.update_drawer_img()\\n return self\",\n \"def rotate(self):\\n tmp = self.width\\n self.width = self.height\\n self.height = tmp\\n self.rotated = not self.rotated\",\n \"def rotate(self):\\n\\n last_center = self.rect.center\\n self.image = pg.transform.rotate(self.image_copy,self.angle)\\n self.rect = self.image.get_rect()\\n self.rect.center = last_center\\n self.angle +=self.rotate_by\",\n \"def archive_image(self, img):\\n \\n try:\\n imgname = \\\"roboimg\\\" + str(int(time.time())) + \\\".png\\\"\\n imgpath = os.path.join(self.imgdir, imgname)\\n # print(\\\"Pic name \\\" + imgpath)\\n\\n cv2.imwrite(imgpath, img)\\n except:\\n self.logger.error(\\\"archive_image failed %s\\\" % (imgpath))\",\n \"def store_image(self):\\n cv2.imwrite(self.__diff_filename(), self.__diff_image())\",\n \"def save_image(self):\\n self.save()\",\n \"def rotate90(self):\",\n \"def rotate(file_path, angle):\\n\\n folder, file_name, ext = parse_file_path(file_path)\\n url = addr + 'img/rotate'\\n\\n img = cv2.imread(file_path)\\n _, img_encoded = cv2.imencode('.jpg', img)\\n payload = img_encoded.tostring()\\n response = requests.post(url, data = payload, params = {'agnle': angle})\\n if response.status_code != 200:\\n print(json.loads(response.content))\\n return None\\n \\n img_array = uncompress_nparr(response.content)\\n file_path = os.path.join(folder, file_name + '-' + random_string() + 'rotate' + ext)\\n cv2.imwrite(file_path, img_array)\\n return file_path\",\n \"def visualize_rotated_image(image_uint8, rows_columns_top_left, width_crop, is_rotated, paths):\\n if is_rotated:\\n image_possible_rotation_uint8 = numpy.rot90(image_uint8,\\n k=3)\\n else:\\n image_possible_rotation_uint8 = image_uint8\\n \\n # `visualize_crops` checks that `image_possible_rotation_uint8.dtype`\\n # is equal to `numpy.uint8` and `image_possible_rotation_uint8.ndim`\\n # is equal to 3.\\n visualize_crops(image_possible_rotation_uint8,\\n rows_columns_top_left,\\n width_crop,\\n paths[1:])\\n for i in range(image_possible_rotation_uint8.shape[2]):\\n save_image(paths[0][i],\\n image_possible_rotation_uint8[:, :, i])\",\n \"def savePhoto(self, path):\\n if self.original_image and path:\\n cv2.imwrite(path, self.original_image)\",\n \"def _reorient_image(image, orientation='RAS'):\\n\\n orig_ornt = nib.io_orientation(image.affine)\\n targ_ornt = nib.orientations.axcodes2ornt(orientation)\\n transform = nib.orientations.ornt_transform(orig_ornt, targ_ornt)\\n image = image.as_reoriented(transform)\\n\\n return image\",\n \"def save(self, filepath):\\n self.drawer.flush()\\n self.img.save(filepath)\",\n \"def Rotate(angle):\\n def rotate_img(img, angle=angle):\\n img = Ft.rotate(img, angle, resample=BILINEAR)\\n return img\\n return rotate_img\",\n \"def load_image():\\n if display_histogram == 1:\\n image = cv2.imread(filename, cv2.IMREAD_GRAYSCALE)\\n else:\\n image = cv2.imread(filename, cv2.IMREAD_COLOR)\\n\\n image_resized = cv2.resize(image, None, fx=scale, fy=scale, interpolation=cv2.INTER_CUBIC)\\n rows, cols = image_resized.shape[0:2] # get height and width \\n\\n rotation_matrix = cv2.getRotationMatrix2D((cols/2, rows/2), rotation, 1)\\n image_rotated = cv2.warpAffine(image_resized, rotation_matrix, (cols, rows))\\n\\n return image_rotated\",\n \"def _rotate_image_90(self, img: ndarray, k: int) -> ndarray:\\n if img.shape[0] < img.shape[1]:\\n self.y = np.rot90(img, k)\\n return self.y\\n else:\\n return img\",\n \"def save_grtrans_image(grt_obj):\\n I_im = grt_obj.ivals[:,0,0].reshape(npix,npix).flatten()\\n Q_im = grt_obj.ivals[:,1,0].reshape(npix,npix).flatten()\\n U_im = grt_obj.ivals[:,2,0].reshape(npix,npix).flatten()\\n V_im = grt_obj.ivals[:,3,0].reshape(npix,npix).flatten()\\n\\n # convert to Tb\\n factor = 3.254e13/(RF**2 * psize_rad**2)\\n I_im *= factor\\n Q_im *= factor\\n U_im *= factor\\n V_im *= factor\\n\\n x = np.array([[i for i in range(npix)] for j in range(npix)]).flatten()\\n y = np.array([[j for i in range(npix)] for j in range(npix)]).flatten()\\n\\n x -= npix/2\\n y -= npix/2\\n x = x*psize_uas\\n y = y*psize_uas\\n\\n outdat = np.vstack((x.T,y.T,I_im.T,Q_im.T,U_im.T,V_im.T)).T\\n np.savetxt('../rrjet_and_riaf/'+FNAME,outdat)\\n #np.savetxt('../rrjet_and_riaf/grtrans_jet_compare_positron_noconv.txt',outdat)\\n return\",\n \"def rotate_no_clip(self, angle):\\n # Calculate the size the expanded image needs to be to contain rotated image\\n x, y = self.width, self.height\\n w = abs(x*math.cos(angle)) + abs(y*math.sin(angle))\\n h = abs(x*math.sin(angle)) + abs(y*math.cos(angle))\\n\\n # Paste the image into a larger frame and rotate\\n img = Image.blank(w, h, 4, 0)\\n img.paste(self, w/2-x/2, h/2-y/2)\\n rotated = img.rotate(angle, (w/2, h/2))\\n\\n return rotated\",\n \"def write_image(self, filename):\\n cv2.imwrite(filename, self.image)\",\n \"def rotate_pillow_image(pillow_image, orientation):\\n image_format = pillow_image.format\\n if orientation == 'from-image':\\n if 'exif' in pillow_image.info:\\n pillow_image = ImageOps.exif_transpose(pillow_image)\\n elif orientation != 'none':\\n angle, flip = orientation\\n if angle > 0:\\n rotation = getattr(Image.Transpose, f'ROTATE_{angle}')\\n pillow_image = pillow_image.transpose(rotation)\\n if flip:\\n pillow_image = pillow_image.transpose(\\n Image.Transpose.FLIP_LEFT_RIGHT)\\n\\n # Keep image format as it is discarded by transposition\\n pillow_image.format = image_format\\n return pillow_image\",\n \"def rotate(self, image, angle):\\n tmpImage = pygame.transform.rotate(image ,angle)\\n imageCentreX = tmpImage.get_rect()[0] + tmpImage.get_rect()[2]/2\\n imageCentreY = tmpImage.get_rect()[1] + tmpImage.get_rect()[3]/2\\n\\n targetWidth = tmpImage.get_rect()[2]\\n targetHeight = tmpImage.get_rect()[3]\\n\\n imageOut = pygame.Surface((targetWidth, targetHeight))\\n imageOut.fill((255,255,0))\\n imageOut.set_colorkey((255,255,0))\\n imageOut.blit(tmpImage,(0,0), pygame.Rect( imageCentreX-targetWidth/2,imageCentreY-targetHeight/2, targetWidth, targetHeight ) )\\n return imageOut\",\n \"def rotate90(input_file, rotations=[1,0,0],\\n use_matrix=True, use_header=True):\\n import os\\n import numpy as np\\n import nibabel as nb\\n\\n from mindboggle.utils.utils import execute\\n\\n # Load image volume\\n img = nb.load(input_file)\\n dat = img.get_data()\\n if use_matrix:\\n mat = img.get_affine()\\n if use_header:\\n hdr = img.get_header()\\n pixdims = hdr.get_zooms()\\n if pixdims[0] != pixdims[1] or \\\\\\n pixdims[0] != pixdims[2] or \\\\\\n pixdims[1] != pixdims[2]:\\n os.error('This function assumes isometric voxels.')\\n else:\\n pixdims = [1,1,1]\\n dims = img.get_shape()\\n if dims[0] != dims[1] or \\\\\\n dims[0] != dims[2] or \\\\\\n dims[1] != dims[2]:\\n os.error('This function assumes same dimensions along each axis.')\\n\\n dat_new = np.zeros(dims)\\n lenx = dims[0]\\n\\n # Rotate about x-axis\\n if rotations[0] != 0:\\n print('Rotate about x-axis')\\n pixdims = '{0} {1} {2}'.format(pixdims[0], pixdims[2], pixdims[1])\\n for y in range(lenx):\\n if rotations[0]==1:\\n dat_new[:, :, y] = dat[:, y, :]\\n #elif rotations[0]==-1:\\n # dat_new[:, :, lenx-1-y] = dat[:, y, :]\\n\\n # Rotate about y-axis\\n elif rotations[1] != 0:\\n print('Rotate about y-axis')\\n pixdims = '{0} {1} {2}'.format(pixdims[2], pixdims[1], pixdims[0])\\n for z in range(lenx):\\n if rotations[1]==1:\\n dat_new[z, :, :] = dat[:, :, z]\\n #elif rotations[1]==-1:\\n # dat_new[lenx-1-z, :, :] = dat[:, :, z]\\n\\n # Rotate about z-axis\\n elif rotations[2] != 0:\\n print('Rotate about z-axis')\\n pixdims = '{0} {1} {2}'.format(pixdims[1], pixdims[0], pixdims[2])\\n for x in range(lenx):\\n if rotations[2]==1:\\n dat_new[:, x, :] = dat[x, :, :]\\n #elif rotations[2]==-1:\\n # dat_new[:, lenx-1-x, :] = dat[x, :, :]\\n\\n # Save output\\n out_file = 'rot'+''.join([str(x) for x in rotations])\\\\\\n + '_' + os.path.basename(input_file)\\n if use_matrix:\\n if use_header:\\n img = nb.Nifti1Image(dat_new, mat, hdr)\\n else:\\n img = nb.Nifti1Image(dat_new, mat)\\n elif use_header:\\n img = nb.Nifti1Image(dat_new, np.eye(4,4), hdr)\\n else:\\n img = nb.Nifti1Image(dat_new, np.eye(4,4))\\n\\n img.to_filename(out_file)\\n\\n # Swap pixel dimensions\\n print('Swap pixel dimensions')\\n cmd = ['fslchpixdim', out_file, pixdims]\\n execute(cmd)\\n\\n return out_file\",\n \"def save_image(image, file_name):\\n io.imsave(file_name,image)\",\n \"def preprocess(self, image):\\n if self.rotate == 0:\\n return image\\n\\n angle = self.rotate * -90\\n return image.rotate(angle, expand=True).crop((0, 0, self._w, self._h))\",\n \"def save(self, filename):\\n self.image.save(filename, self.options.img_format)\",\n \"def _reorient_numpy_image(self, image, orientation):\\n if len(image.shape) == 2:\\n image = np.resize(image, (image.shape[0], image.shape[1], 1))\\n if orientation in {\\n tifftools.constants.Orientation.LeftTop.value,\\n tifftools.constants.Orientation.RightTop.value,\\n tifftools.constants.Orientation.LeftBottom.value,\\n tifftools.constants.Orientation.RightBottom.value}:\\n image = image.transpose(1, 0, 2)\\n if orientation in {\\n tifftools.constants.Orientation.BottomLeft.value,\\n tifftools.constants.Orientation.BottomRight.value,\\n tifftools.constants.Orientation.LeftBottom.value,\\n tifftools.constants.Orientation.RightBottom.value}:\\n image = image[::-1, ::, ::]\\n if orientation in {\\n tifftools.constants.Orientation.TopRight.value,\\n tifftools.constants.Orientation.BottomRight.value,\\n tifftools.constants.Orientation.RightTop.value,\\n tifftools.constants.Orientation.RightBottom.value}:\\n image = image[::, ::-1, ::]\\n return image\",\n \"def save_calibration(self):\\n\\n path = './{}/'.format(self.controller)\\n # Check if path exist, if not, creates it.\\n if not os.path.exists(os.path.dirname(path)):\\n try:\\n os.makedirs(os.path.dirname(path))\\n except OSError as exc:\\n # Guard against race condition\\n if exc.errno != errno.EEXIST:\\n raise\\n\\n # Save Jacobian matrix (self.mat)\\n with open(\\\"./{i}/mat.txt\\\".format(i=self.controller), 'wt') as f:\\n for i in range(3):\\n f.write('{a},{b},{c}\\\\n'.format(a=self.mat[i, 0], b=self.mat[i, 1], c=self.mat[i, 2]))\\n\\n # Save rotational matrix\\n with open(\\\"./{i}/rotmat.txt\\\".format(i=self.controller), 'wt') as f:\\n for i in range(3):\\n f.write('{a},{b},{c}\\\\n'.format(a=self.rot[i, 0], b=self.rot[i, 1], c=self.rot[i, 2]))\\n\\n # Save other data\\n with open('./{i}/data.txt'.format(i=self.controller), 'wt') as f:\\n f.write('{d}\\\\n'.format(d=self.um_px))\\n f.write('{d}\\\\n'.format(d=self.x_init))\\n f.write('{d}\\\\n'.format(d=self.y_init))\\n f.write('{d}\\\\n'.format(d=self.template_loc[0]))\\n f.write('{d}\\\\n'.format(d=self.template_loc[1]))\",\n \"def rotate_img(image, degrees):\\n if degrees == 90:\\n return cv2.rotate(image, cv2.ROTATE_90_CLOCKWISE)\\n elif degrees == 180:\\n return cv2.rotate(image, cv2.ROTATE_180)\\n elif degrees == 270:\\n return cv2.rotate(image, cv2.ROTATE_90_COUNTERCLOCKWISE)\\n elif degrees == 0:\\n return image\\n else:\\n print(\\\"DEGREE = \\\", degrees)\",\n \"def reorient_img(img, namer):\\n from ndmg.utils.reg_utils import normalize_xform\\n\\n # Load image, orient as RAS\\n orig_img = nib.load(img)\\n reoriented = nib.as_closest_canonical(orig_img)\\n normalized = normalize_xform(reoriented)\\n\\n # Image may be reoriented\\n if normalized is not orig_img:\\n print(\\\"%s%s%s\\\" % (\\\"Reorienting \\\", img, \\\" to RAS+...\\\"))\\n out_name = \\\"%s%s%s%s\\\" % (\\n namer.dirs[\\\"output\\\"][\\\"prep_anat\\\"],\\n \\\"/\\\",\\n img.split(\\\"/\\\")[-1].split(\\\".nii.gz\\\")[0],\\n \\\"_reor_RAS.nii.gz\\\",\\n )\\n else:\\n out_name = \\\"%s%s%s%s\\\" % (\\n namer.dirs[\\\"output\\\"][\\\"prep_anat\\\"],\\n \\\"/\\\",\\n img.split(\\\"/\\\")[-1].split(\\\".nii.gz\\\")[0],\\n \\\"_RAS.nii.gz\\\",\\n )\\n\\n normalized.to_filename(out_name)\\n\\n return out_name\",\n \"def save_image(self, filename):\\n raster.save_image(filename, self.image, self.metadata)\",\n \"def rot_image(original_image, angle):\\n # Tämä copypastettu jostain netistä. Vaatii että kuva on neliö.\\n assert original_image.get_width() == original_image.get_height(), \\\\\\n \\\"Can't rotate image - not square. %r\\\" % original_image\\n orig_rect = original_image.get_rect()\\n rot_image = pygame.transform.rotate(original_image, angle)\\n rot_rect = orig_rect.copy()\\n rot_rect.center = rot_image.get_rect().center\\n rot_image = rot_image.subsurface(rot_rect).copy()\\n return rot_image\",\n \"def rotateImage(self, img, angle=90):\\n if (angle == 90) :\\n return(cv2.flip(cv2.transpose(img),flipCode=0))\\n elif (angle == -90) :\\n return(cv2.flip(cv2.transpose(img),flipCode=1))\\n else :\\n center = (img.shape[1]/2.0,img.shape[0]/2.0)\\n rotate = cv2.getRotationMatrix2D(center, angle, 1.0)\\n return cv2.warpAffine(img, rotate, (img.shape[1], img.shape[0]))\",\n \"def rotate(img, angle, resample=False, expand=False, center=None):\\n\\n #if not _is_pil_image(img):\\n # raise TypeError('img should be PIL Image. Got {}'.format(type(img)))\\n\\n return img.rotate(angle, resample, expand, center)\",\n \"def im_rotate(im_path, rotate_angle):\\n image = cv.imread(str(im_path))\\n image_r = cv.rotate(image, rotate_angle)\\n\\n return image_r\",\n \"def reverse_transformation(self, rot90, flip_lr=False):\\n\\n transformed_ROI = copy.deepcopy(self) #Make a copy of itself to transform and return\\n\\n # Undo the left-right flip\\n if flip_lr:\\n transformed_ROI.center = (transformed_ROI.center[0], self.img_shape[1] - transformed_ROI.center[1])\\n\\n #Undo the rotation of the image\\n cent = transformed_ROI.center\\n if rot90 == 1:\\n transformed_ROI.center = (cent[1], self.img_shape[0] - cent[0])\\n transformed_ROI.size = (transformed_ROI.size[1], transformed_ROI.size[0])\\n elif rot90 == 2:\\n transformed_ROI.center = (self.img_shape[0] - cent[0], self.img_shape[1] - cent[1])\\n elif rot90 == 3:\\n transformed_ROI.center = (self.img_shape[1] - cent[1], cent[0])\\n transformed_ROI.size = (transformed_ROI.size[1], transformed_ROI.size[0])\\n\\n return transformed_ROI\",\n \"def rotate((x,y)):\\n orientation = parameter('Orientation',90) # in degrees counter-clockwise\\n if orientation == None: orienation = 0\\n w,h = image_size()\\n if orientation == 0: return (x,y)\\n if orientation == -90: return (h-y,x)\\n if orientation == 90: return (y,w-x)\\n if orientation == 180: return (w-x,h-y)\\n return (x,y)\",\n \"def _save(filename, img):\\n if not os.path.exists(OUTPUT_DIR):\\n os.makedirs(OUTPUT_DIR)\\n # filename = filename+'.png'\\n filename = os.path.join(OUTPUT_DIR, filename)\\n # print(filename, img.shape)\\n cv.imwrite(filename, img)\",\n \"def save_image(self, filename):\\n if filename[-4:] != '.pkl':\\n filename + '.pkl'\\n with open(filename, 'wb') as output: # Overwrites any existing file.\\n pickle.dump(self, output, pickle.HIGHEST_PROTOCOL)\",\n \"def save(self, fn):\\n plt.imsave(fn, self.image)\",\n \"def imwrite(image, path):\\n return scipy.misc.imsave(path, to_range(image, 0, 255, np.uint8))\",\n \"def write(self, image):\\n raise NotImplementedError()\",\n \"def img_save(self):\\n file_name, extension = return_folder_file_extension(self.img_name)[1:]\\n image_name_save = \\\"%s_D=%s_Rs=%s_size=%s_offset=%i%s\\\" % (file_name, self.D, self.Rs, self.axe_X, self.offset_X+self.offset_X2, extension)\\n\\n if self.img2 is not None:\\n self.img2.save(image_name_save)\\n print(\\\"Saved \\\"+image_name_save)\\n else:\\n print(\\\"No image to save\\\")\",\n \"def save_image(img, path):\\n cv2.imwrite(path, img)\",\n \"def rotate_image_set(self, folder_name, num_rotations=3):\\n print(\\\"Rotating images in folder: \\\"+str(folder_name))\\n photo_list = self.get_photo_list(folder_name, '*.png')\\n destination_folder = folder_name+\\\"_rotated90\\\"\\n\\n try:\\n print(\\\"Making dir \\\" + str(destination_folder) + \\\" for rotation\\\")\\n os.mkdir(destination_folder)\\n except OSError as e:\\n print(e)\\n print(\\\"Folder likely exists, have you already done this rotation??\\\")\\n return\\n\\n for i, name in enumerate(photo_list):\\n print(\\\"Rotating \\\" +str(i) + \\\" of \\\" + str(len(photo_list)))\\n file_name = folder_name + '/' + name\\n destination_filename = destination_folder + '/' + name[:-4] + '.png'\\n image = cv2.imread(file_name, cv2.IMREAD_ANYDEPTH)\\n cv2.imwrite(destination_filename, np.rot90(image, num_rotations), [cv2.IMWRITE_PNG_COMPRESSION, 0])\",\n \"def img_save(name,img):\\n cv2.imwrite(name,img)\",\n \"def rotate(img, angle):\\n if not _is_numpy(img):\\n raise TypeError('img should be Numpy Image. Got {}'.format(type(img)))\\n\\n aug = iaa.Affine(rotate=angle)\\n return aug.augment_image(img)\",\n \"def save_image(filename, image):\\n im = cv2.resize(image, None, fx=SCALE_DOWN, fy=SCALE_DOWN)\\n cv2.imwrite(os.path.join(OUT_DIR, filename), im)\",\n \"def imwrite(image, path):\\n\\n if image.ndim == 3 and image.shape[2] == 1: # for gray image\\n image = np.array(image, copy=True)\\n image.shape = image.shape[0:2]\\n\\n imgarray=((image+1.0)*127.5).astype(np.uint8)\\n img=Image.fromarray(imgarray)\\n img.save(path)\",\n \"def _rotate_img(self, results):\\n angle = self.angle\\n height, width = results['img_shape'][:2]\\n center = ((width - 1) * 0.5, (height - 1) * 0.5)\\n\\n # Compute rotation matrix\\n mat_rotation = cv2.getRotationMatrix2D(center, -angle, 1)\\n\\n # Compute height and width of new image after rotation\\n cos = np.abs(mat_rotation[0, 0])\\n sin = np.abs(mat_rotation[0, 1])\\n width_new = height * sin + width * cos\\n height_new = height * cos + width * sin\\n mat_rotation[0, 2] += (width_new - width) * 0.5\\n mat_rotation[1, 2] += (height_new - height) * 0.5\\n width_new = int(np.round(width_new))\\n height_new = int(np.round(height_new))\\n \\n # Rotate image\\n img_rotation = cv2.warpAffine(results['img'], mat_rotation, (width_new, height_new),\\n borderValue=self.borderValue)\\n results['img'] = img_rotation\\n results['img_shape'] = results['img'].shape\\n\\n # Rotate corresponding annotations: all boxes in bbox_fields\\n for key in results.get('bbox_fields', []):\\n gt_boxes_ret = []\\n for poly in results[key]:\\n rot_array = []\\n poly_length = len(poly)\\n\\n if poly_length == 4:\\n poly = [poly[0], poly[1], poly[2], poly[1], poly[2], poly[3], poly[0], poly[3]]\\n\\n # Convert to np.array of shape (:, 2)\\n for i in range(0, len(poly), 2):\\n rot_array.append(np.array([poly[i], poly[i + 1]]))\\n\\n # Rotate corresponding annotations\\n rot_array = np.array([rot_array])\\n rot_array = cv2.transform(rot_array, mat_rotation).squeeze().reshape(len(poly))\\n\\n if poly_length == 4:\\n x_coords = rot_array[0::2]\\n y_coords = rot_array[1::2]\\n rot_array = np.array([\\n np.min(x_coords),\\n np.min(y_coords),\\n np.max(x_coords),\\n np.max(y_coords)\\n ])\\n\\n gt_boxes_ret.append(rot_array)\\n if len(results[key]) > 0:\\n results[key] = gt_boxes_ret\\n\\n # Rotate gt_bboxes according to gt_poly_bboxes\\n if 'gt_bboxes' in results and 'gt_poly_bboxes' in results:\\n gt_bboxes = []\\n gt_bboxes_ignore = []\\n\\n for poly in results['gt_poly_bboxes']:\\n poly = np.array(poly, dtype=np.double)\\n x_coords = poly[0::2]\\n y_coords = poly[1::2]\\n aligned_poly = [\\n np.min(x_coords),\\n np.min(y_coords),\\n np.max(x_coords),\\n np.max(y_coords)\\n ]\\n gt_bboxes.append(aligned_poly)\\n\\n for poly in results['gt_poly_bboxes_ignore']:\\n poly = np.array(poly, dtype=np.double)\\n x_coords = poly[0::2]\\n y_coords = poly[1::2]\\n aligned_poly = [\\n np.min(x_coords),\\n np.min(y_coords),\\n np.max(x_coords),\\n np.max(y_coords)\\n ]\\n gt_bboxes_ignore.append(aligned_poly)\\n\\n if len(gt_bboxes) == 0:\\n gt_bboxes = np.zeros((0, 4), dtype=np.float32)\\n else:\\n gt_bboxes = np.array(gt_bboxes, dtype=np.float32)\\n\\n if len(gt_bboxes_ignore) == 0:\\n gt_bboxes_ignore = np.zeros((0, 4), dtype=np.float32)\\n else:\\n gt_bboxes_ignore = np.array(gt_bboxes_ignore, dtype=np.float32)\\n\\n results['gt_bboxes'] = gt_bboxes\\n results['gt_bboxes_ignore'] = gt_bboxes_ignore\\n\\n # Rotate corresponding annotations: all boxes in cbbox_fields\\n for key in results.get('cbbox_fields', []):\\n gt_cboxes_ret = []\\n for instance in results[key]:\\n tmp_cboxes = []\\n for poly in instance:\\n rot_array = []\\n # Convert to np.array of shape (:, 2)\\n for i in range(0, len(poly), 2):\\n rot_array.append(np.array([poly[i], poly[i + 1]]))\\n rot_array = np.array([rot_array])\\n # Rotate corresponding annotations\\n rot_array = cv2.transform(rot_array, mat_rotation).squeeze().reshape(len(poly))\\n tmp_cboxes.append(rot_array)\\n gt_cboxes_ret.append(tmp_cboxes)\\n results[key] = gt_cboxes_ret\\n\\n # Rotate corresponding annotations: all masks in mask_fields\\n for key in results.get('mask_fields', []):\\n mask = results[key].masks.transpose((1, 2, 0))\\n if len(results[key].masks) == 0:\\n results[key] = results[key].resize((height_new, width_new))\\n else:\\n # Rotate mask\\n mask_rotation = cv2.warpAffine(mask, mat_rotation, (width_new, height_new),\\n borderValue=self.borderValue)\\n if mask_rotation.ndim == 2:\\n # case when only one mask, (h, w)\\n mask_rotation = mask_rotation[:, :, None] # (h, w, 1)\\n mask_rotation = mask_rotation.transpose((2, 0, 1))\\n results[key].masks = mask_rotation\\n results[key].height = height_new\\n results[key].width = width_new\",\n \"def saveflip(image, fname, outpath, axis='x', preserve_name=False):\\n if not preserve_name:\\n fpath = genSavePath(outpath, fname, modstring=f\\\"mirror_{axis}\\\")\\n else:\\n fpath = genSavePath(outpath, fname)\\n im = copy(image)\\n if axis == 'x':\\n im = im.transpose(Image.FLIP_LEFT_RIGHT)\\n elif axis == 'y':\\n im = im.transpose(Image.FLIP_TOP_BOTTOM)\\n else:\\n raise Exception('No valid axis procvided for flipping: {} - received value: {}'.format(fname, axis))\\n try:\\n im.save(fpath, subsample=\\\"keep\\\", qtables=image.quantization, optimize=True)\\n\\n except IOError as m:\\n print( \\\"Flipped({}) image creation failed for: {}. \\\\nReason:{}\\\".format(axis,fname,m))\",\n \"def save(self):\\n\\n self.image.save(\\\"./output/\\\" + self.name + \\\" pg\\\" + str(self._page) + \\\".png\\\")\",\n \"def detect_orientation(image):\\n custom_oem_psm_config = r'--oem 1--psm 7'\\n newdata = pytesseract.image_to_osd(image,config= custom_oem_psm_config)\\n rotation = int(re.search('(?<=Rotate: )\\\\\\\\d+', newdata).group(0))\\n # print(\\\"Rotation degrees : \\\", rotation)\\n return rotate_img(image, rotation)\",\n \"def save(\\n self,\\n output_path: str,\\n show_confidence: bool = True,\\n ) -> None:\\n image = self.draw(show_confidence=show_confidence)\\n save_image(image=image, path=output_path)\",\n \"def rotate_and_wrap_image(self, image, degree_of_rotation):\\n\\n image_center = tuple(np.array(image.shape[1::-1]) / 2)\\n rot_mat = cv2.getRotationMatrix2D(image_center, degree_of_rotation, 1.0)\\n # borderMode (constant) and borderValue are important for maintaiing consistency \\n ri = cv2.warpAffine(image, rot_mat, image.shape[1::-1], flags=cv2.INTER_LINEAR, borderMode = cv2.BORDER_CONSTANT,borderValue = (255,255,255))\\n return ri\",\n \"def rotate_augmentation():\\n rand_rotate = np.random.randint(180)\\n return lambda image: rotate_with_extension(image, rand_rotate)\",\n \"def save_calibration(filename):\\n pass\",\n \"def rotateIMG(self):\\n self.blit_image = pygame.transform.rotate(self.blit_image, self.blitHeading - 45)\\n self.rect = self.blit_image.get_rect()\\n self.rect.center = (int(self.pos.x), int(self.pos.y))\",\n \"def rotate(self, angle, reshape=False):\\n return IntensityMap.rotate(self, angle, reshape=reshape)\",\n \"def save(self, filename):\\n print(\\\"Saving...\\\", end=\\\"\\\\r\\\")\\n canvas = self.canvas[self.N:self.S,self.W:self.E]\\n cv2.imwrite(\\\"./Output/\\\"+filename, canvas)\\n print(\\\"Saved:\\\",filename)\",\n \"def rotate(self):\\r\\n self.rot = (self.vel.y * -3)\\r\\n if self.rot < -90:\\r\\n self.rot = -90\\r\\n \\r\\n new_image = pg.transform.rotate(self.bird_sprites[self.sprite_frame], self.rot)\\r\\n old_center = self.rect.center\\r\\n self.image = new_image\\r\\n self.rect = self.image.get_rect()\\r\\n self.rect.center = old_center\\r\\n # self.animate()\\r\",\n \"def rotate(im: Image) -> Image:\\n return im.rotate(random.randint(0, 360))\",\n \"def rotate(self, image, angle):\\n # Get the image size\\n # No that's not an error - NumPy stores image matricies backwards\\n image_size = (image.shape[1], image.shape[0])\\n image_center = tuple(np.array(image_size) / 2)\\n\\n # Convert the OpenCV 3x2 rotation matrix to 3x3\\n rot_mat = np.vstack(\\n [cv2.getRotationMatrix2D(image_center, angle, 1.0), [0, 0, 1]]\\n )\\n\\n rot_mat_notranslate = np.matrix(rot_mat[0:2, 0:2])\\n\\n # Shorthand for below calcs\\n image_w2 = image_size[0] * 0.5\\n image_h2 = image_size[1] * 0.5\\n\\n # Obtain the rotated coordinates of the image corners\\n rotated_coords = [\\n (np.array([-image_w2, image_h2]) * rot_mat_notranslate).A[0],\\n (np.array([image_w2, image_h2]) * rot_mat_notranslate).A[0],\\n (np.array([-image_w2, -image_h2]) * rot_mat_notranslate).A[0],\\n (np.array([image_w2, -image_h2]) * rot_mat_notranslate).A[0]\\n ]\\n\\n # Find the size of the new image\\n x_coords = [pt[0] for pt in rotated_coords]\\n x_pos = [x for x in x_coords if x > 0]\\n x_neg = [x for x in x_coords if x < 0]\\n\\n y_coords = [pt[1] for pt in rotated_coords]\\n y_pos = [y for y in y_coords if y > 0]\\n y_neg = [y for y in y_coords if y < 0]\\n\\n right_bound = max(x_pos)\\n left_bound = min(x_neg)\\n top_bound = max(y_pos)\\n bot_bound = min(y_neg)\\n\\n new_w = int(abs(right_bound - left_bound))\\n new_h = int(abs(top_bound - bot_bound))\\n\\n # We require a translation matrix to keep the image centred\\n trans_mat = np.matrix([\\n [1, 0, int(new_w * 0.5 - image_w2)],\\n [0, 1, int(new_h * 0.5 - image_h2)],\\n [0, 0, 1]\\n ])\\n\\n # Compute the tranform for the combined rotation and translation\\n affine_mat = (np.matrix(trans_mat) * np.matrix(rot_mat))[0:2, :]\\n\\n # Apply the transform\\n result = cv2.warpAffine(\\n image,\\n affine_mat,\\n (new_w, new_h),\\n flags=cv2.INTER_LINEAR\\n )\\n\\n return result\",\n \"def __cv2_rotate(image, deg):\\n num_rows, num_cols = image.shape[:2]\\n\\n rotation_matrix = cv.getRotationMatrix2D((num_cols / 2, num_rows / 2), deg, 1)\\n image = cv.warpAffine(np.float32(image), rotation_matrix, (num_cols, num_rows))\\n # In case of only one channel, warpAffine removes channel dimension.\\\"\\\"\\\"\\n return image\",\n \"def convert_to_jpg(filepath):\\n\\n f, e = os.path.splitext(filepath)\\n outfile = f + \\\".jpg\\\"\\n # We don't want to delete .JPG or .JPEG so we lower the extension\\n filepath_lowered = f + e.lower()\\n if outfile != filepath_lowered:\\n try:\\n image = Image.open(filepath)\\n\\n # Rotate image: https://stackoverflow.com/a/6218425\\n # for orientation in ExifTags.TAGS.keys() :\\n # if ExifTags.TAGS[orientation] == 'Orientation' : break\\n orientation = 274 # get 274 through upper loop\\n try:\\n exif=dict(image._getexif().items())\\n print(exif[orientation])\\n if exif[orientation] == 3 :\\n image=image.rotate(180, expand=True)\\n elif exif[orientation] == 6 :\\n image=image.rotate(270, expand=True)\\n elif exif[orientation] == 8 :\\n image=image.rotate(90, expand=True)\\n except (AttributeError, KeyError): # image has no meta data\\n pass\\n\\n image.convert('RGB').save(outfile)\\n except IOError:\\n print(\\\"cannot convert\\\", filepath)\\n exit(1)\\n os.remove(filepath)\\n return outfile\\n return filepath\",\n \"def transform(self, previousimage):\",\n \"def orient(self,Y):\\r\\n self.orientation[Y]+=1\\r\\n if self.orientation[Y]>3:\\r\\n self.orientation[Y]=0\\r\\n if self.orientation[Y]<0:\\r\\n self.orientation[Y]=3\\r\\n self.can.delete(self.image_bateau[Y])\\r\\n self.image_bateau[Y]=self.create_image(self.img[self.orientation[Y]][Y],0,0)\\r\\n self.affichage(Y)\",\n \"def rotate_with_extension(image, alpha):\\n # Determine if alpha is larger than 90 degrees and rotate accordingly\\n # Number of 90 degree turns\\n quarter = int(alpha / 90)\\n # turn the image 90 deg quarter times\\n image = image.rotate(quarter * 90)\\n # Get the angle of the rest of the rotation\\n alpha = alpha % 90\\n\\n # Size of image\\n size = image.size[0]\\n # Get radians\\n alpha_rad = alpha/180 * np.pi\\n\\n # Compute the size of the extended image needed to keep an image of the\\n # right size after cropping\\n cos = np.cos(alpha_rad)\\n sin = np.sin(alpha_rad)\\n L = int(size * (sin + cos))\\n\\n # Extend the image then rotate it\\n extend = mirror_extend(int((L-size)/2), image)\\n rotate = extend.rotate(alpha, expand=1)\\n # Get the current side length of the rotated image and compute the\\n # difference with the original image to obtain the number of pixels to remove\\n # from each border\\n side = rotate.size[0]\\n pixel_to_remove = (side - size)/2\\n # Crop the image\\n return rotate.crop((pixel_to_remove, pixel_to_remove, pixel_to_remove + size, pixel_to_remove+size))\",\n \"def write(self, filename):\\n\\n self.__image.save(filename)\",\n \"def saveImageAs(self, name):\\n\\t\\tself.image.save(name)\",\n \"def save(self, **kwargs):\\n self.remove_file()\\n if not self.image:\\n self.generate(save=False)\\n else:\\n self.image.name = self.file()\\n super(FormatedPhoto, self).save(**kwargs)\",\n \"def save_image(filename, matrix):\\n im = Image.new('L', list(reversed(matrix.shape)))\\n data = np.floor(np.ravel(matrix) * 256)\\n im.putdata(data)\\n im.save(filename)\",\n \"def data(self):\\n image = transform.warp(self._raw_image_data, self._corrective_transform)\\n image_data = transform.rotate(image, self._rotation_offset)\\n return image_data\",\n \"def image_preview(img_path):\\r\\n img = Image.open(img_path)\\r\\n t_size = 256, 256\\r\\n\\r\\n try:\\r\\n if \\\"exif\\\" in img.info:\\r\\n exif_dict = piexif.load(img.info[\\\"exif\\\"])\\r\\n if piexif.ImageIFD.Orientation in exif_dict[\\\"0th\\\"]:\\r\\n orientation = exif_dict[\\\"0th\\\"].pop(piexif.ImageIFD.Orientation)\\r\\n #exif_bytes = piexif.dump(exif_dict)\\r\\n if orientation == 2:\\r\\n img = img.transpose(Image.FLIP_LEFT_RIGHT)\\r\\n elif orientation == 3:\\r\\n img = img.rotate(180)\\r\\n elif orientation == 4:\\r\\n img = img.rotate(180).transpose(Image.FLIP_LEFT_RIGHT)\\r\\n elif orientation == 5:\\r\\n img = img.rotate(-90, expand=True).transpose(Image.FLIP_LEFT_RIGHT)\\r\\n elif orientation == 6:\\r\\n img = img.rotate(-90, expand=True)\\r\\n elif orientation == 7:\\r\\n img = img.rotate(90, expand=True).transpose(Image.FLIP_LEFT_RIGHT)\\r\\n elif orientation == 8:\\r\\n img = img.rotate(90, expand=True)\\r\\n except:\\r\\n print('exif data problem in', img_path)\\r\\n\\r\\n new_image = Image.new(img.mode, t_size, color=(255,255,255))\\r\\n img.thumbnail(t_size, Image.ANTIALIAS) # in-place\\r\\n x_offset= (new_image.size[0] - img.size[0]) // 2\\r\\n y_offset= (new_image.size[1] - img.size[1]) // 2\\r\\n new_image.paste(img, (x_offset, y_offset))\\r\\n img = new_image\\r\\n\\r\\n # in memory image -> bytes -> base64_string\\r\\n buffered = BytesIO()\\r\\n img.save(buffered, format=\\\"JPEG\\\")\\r\\n img_preview = base64.b64encode(buffered.getvalue()).decode('utf-8')\\r\\n\\r\\n return img_preview\",\n \"def rotate(self, angle):\\n rotmat = rotation_matrix_2d(angle)\\n rotated = np.dot(rotmat.T, [self.pix_x.value, self.pix_y.value])\\n self.pix_x = rotated[0] * self.pix_x.unit\\n self.pix_y = rotated[1] * self.pix_x.unit\\n self.pix_rotation -= angle\",\n \"def rotation(self):\\n\\t\\treturn self.piv.a.rotate.v\",\n \"def save(image, name):\\n from matplotlib import pyplot\\n import matplotlib as mpl\\n fig = pyplot.figure()\\n ax = fig.add_subplot(1,1,1)\\n imgplot = ax.imshow(image, cmap=mpl.cm.Greys)\\n imgplot.set_interpolation('nearest')\\n ax.xaxis.set_ticks_position('top')\\n ax.yaxis.set_ticks_position('left')\\n pyplot.savefig(name)\",\n \"def save_img(img: np.ndarray, path: str) -> None:\\n\\n img_obj = Image.fromarray(img)\\n img_obj.save(path)\",\n \"def save(self, file: Union[str, Path, BinaryIO]):\\n np.savez_compressed(\\n file, avg_img=self.avg_img, corr_img=self.corr_img,\\n fit_result=_fit_result_to_list(self.fit_result),\\n fit_amplitude=self.fit_amplitude, bg=self.bg)\",\n \"def save_image(nom, image, _geo_trans):\\n cols = image.shape[2]\\n rows = image.shape[1]\\n bands = image.shape[0]\\n print(bands, cols, rows)\\n driver = gdal.GetDriverByName(\\\"GTiff\\\")\\n out_raster = driver.Create(nom, cols, rows, bands, gdal.GDT_Byte)\\n # if (geo_trans):\\n # outRaster.SetGeoTransform(geo_trans)\\n band = out_raster.GetRasterBand(1)\\n band.WriteArray(np.round(image[0]))\\n band = out_raster.GetRasterBand(2)\\n band.WriteArray(np.round(image[1]))\\n band = out_raster.GetRasterBand(3)\\n band.WriteArray(np.round(image[2]))\",\n \"def save(img, path, file_name):\\n\\n name = os.path.join(path,file_name).replace('/', os.sep)\\n\\n io.imsave(name,img)\",\n \"def rotate(image, degrees):\\n # Convert from degrees to radians.\\n degrees_to_radians = math.pi / 180.0\\n radians = degrees * degrees_to_radians\\n return tfa.image.rotate(tf.convert_to_tensor(image), tf.constant(radians))\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.70346487","0.68889385","0.682253","0.6747778","0.6635483","0.6627623","0.6563121","0.6496392","0.6405352","0.63929117","0.63382024","0.6252712","0.61955154","0.61868703","0.61305135","0.6124323","0.61061513","0.60409236","0.60030663","0.5996765","0.5981615","0.59649175","0.5938406","0.59283155","0.5907406","0.58840513","0.58698326","0.58264184","0.5821145","0.58167994","0.5800452","0.5789977","0.5787863","0.5782785","0.5728513","0.5710594","0.5690795","0.5682947","0.5663356","0.56608284","0.56515104","0.56441796","0.5641938","0.5619743","0.5615921","0.560209","0.55982834","0.5597409","0.55886513","0.55802137","0.556189","0.55598605","0.55566776","0.55495024","0.55483025","0.55331975","0.5527856","0.55273587","0.5523111","0.55132073","0.5482614","0.5469644","0.54589367","0.54524755","0.54511625","0.54510087","0.5443444","0.54362893","0.542437","0.5418539","0.54039985","0.54023385","0.5393368","0.53834176","0.53765756","0.5374581","0.5364491","0.5357385","0.5352411","0.53461504","0.5339839","0.53373516","0.53332716","0.5332161","0.53239745","0.53214717","0.5313657","0.5313412","0.5312776","0.5311284","0.53105605","0.5304704","0.530403","0.52997917","0.5295069","0.52888983","0.5283813","0.52837825","0.5282571","0.5279015"],"string":"[\n \"0.70346487\",\n \"0.68889385\",\n \"0.682253\",\n \"0.6747778\",\n \"0.6635483\",\n \"0.6627623\",\n \"0.6563121\",\n \"0.6496392\",\n \"0.6405352\",\n \"0.63929117\",\n \"0.63382024\",\n \"0.6252712\",\n \"0.61955154\",\n \"0.61868703\",\n \"0.61305135\",\n \"0.6124323\",\n \"0.61061513\",\n \"0.60409236\",\n \"0.60030663\",\n \"0.5996765\",\n \"0.5981615\",\n \"0.59649175\",\n \"0.5938406\",\n \"0.59283155\",\n \"0.5907406\",\n \"0.58840513\",\n \"0.58698326\",\n \"0.58264184\",\n \"0.5821145\",\n \"0.58167994\",\n \"0.5800452\",\n \"0.5789977\",\n \"0.5787863\",\n \"0.5782785\",\n \"0.5728513\",\n \"0.5710594\",\n \"0.5690795\",\n \"0.5682947\",\n \"0.5663356\",\n \"0.56608284\",\n \"0.56515104\",\n \"0.56441796\",\n \"0.5641938\",\n \"0.5619743\",\n \"0.5615921\",\n \"0.560209\",\n \"0.55982834\",\n \"0.5597409\",\n \"0.55886513\",\n \"0.55802137\",\n \"0.556189\",\n \"0.55598605\",\n \"0.55566776\",\n \"0.55495024\",\n \"0.55483025\",\n \"0.55331975\",\n \"0.5527856\",\n \"0.55273587\",\n \"0.5523111\",\n \"0.55132073\",\n \"0.5482614\",\n \"0.5469644\",\n \"0.54589367\",\n \"0.54524755\",\n \"0.54511625\",\n \"0.54510087\",\n \"0.5443444\",\n \"0.54362893\",\n \"0.542437\",\n \"0.5418539\",\n \"0.54039985\",\n \"0.54023385\",\n \"0.5393368\",\n \"0.53834176\",\n \"0.53765756\",\n \"0.5374581\",\n \"0.5364491\",\n \"0.5357385\",\n \"0.5352411\",\n \"0.53461504\",\n \"0.5339839\",\n \"0.53373516\",\n \"0.53332716\",\n \"0.5332161\",\n \"0.53239745\",\n \"0.53214717\",\n \"0.5313657\",\n \"0.5313412\",\n \"0.5312776\",\n \"0.5311284\",\n \"0.53105605\",\n \"0.5304704\",\n \"0.530403\",\n \"0.52997917\",\n \"0.5295069\",\n \"0.52888983\",\n \"0.5283813\",\n \"0.52837825\",\n \"0.5282571\",\n \"0.5279015\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7409973"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88572,"cells":{"query":{"kind":"string","value":"Save a scaled copy of the image, uses a single scale factor for both x,y axes to maintain aspect ratio"},"document":{"kind":"string","value":"def saverescale(image, fname, outpath, scalefactor=0.5, preserve_name=False):\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"resize_{scalefactor}\")\n else:\n fpath = genSavePath(outpath, fname)\n newsize = (int(image.width * scalefactor), int(image.height * scalefactor))\n im = copy(image)\n im = im.resize(newsize)\n try:\n im.save(fpath, subsample=\"keep\", qtables=image.quantization, optimize=True)\n\n except IOError as m:\n print( \"Resize({}) image creation failed for: {}. \\nReason:{}\".format(scalefactor,fname,m))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def exportImg(self):\n if self.superSampling:\n print(\"Exporting with size adjusted\")\n self.img = self.img.resize((int(self.width/2),int(self.height/2)),Image.NEAREST)\n self.img.save(self.fileName,\"PNG\")","def save_image_with_scale(path, variable):\n\n arr = variable.cpu().data.numpy()\n arr = np.clip(arr, -1., 1.)\n arr = (arr+1.)/2 * 255.\n arr = arr.astype(np.uint8)\n skimage.io.imsave(path, arr)","def scale(img, scale):\n return resize(img, x_scale=scale, y_scale=scale)","def Rescale(self):\r\n picWidth,picHeight = self.oldSize = self.GetSizeTuple()\r\n bitmap = self.scaled = self.bitmap\r\n if not bitmap: return\r\n imgWidth,imgHeight = bitmap.GetWidth(),bitmap.GetHeight()\r\n if self.scaling == 2 or (self.scaling == 1 and (imgWidth > picWidth or imgHeight > picHeight)):\r\n image = bitmap.ConvertToImage()\r\n factor = min(1.0*picWidth/imgWidth,1.0*picHeight/imgHeight)\r\n newWidth,newHeight = int(factor*imgWidth),int(factor*imgHeight)\r\n self.scaled = image.Scale(newWidth,newHeight).ConvertToBitmap()\r\n #self.scaled = image.Scale(newWidth,newHeight,wx.IMAGE_QUALITY_HIGH ).ConvertToBitmap()\r","def _scale(self, image):\n\n if image.GetWidth() != self._width or image.GetHeight()!= self._height:\n image.Rescale(self._width, self._height)\n \n return image","def scale(self, infile: str, outfile: str):\n\n with Image(filename=infile) as src:\n width, height = self.new_dimensions(src)\n with src.clone() as dest:\n dest.resize(width=width,height=height)\n logging.debug(\n f'Converted \"{infile}\" ({src.width}x{src.height})'\n f' -> \"{outfile}\" ({dest.width}x{dest.height})')\n dest.save(filename=outfile)","def save_subpix_png(path, img, scale_factor=256.0):\n Path(path).parent.mkdir(parents=True, exist_ok=True)\n img = img.astype(np.float32) * scale_factor\n if np.amax(img) > (2**16)-1:\n warnings.warn(\"image out of range(\" + str(np.amax(img)/scale_factor) +\n \"), try with a smaller scale factor. loading this file \" +\n \"will results in invalid values, file: \"+str(path))\n img[img > (2**16)-1] = 0\n img = img.astype(np.uint16)\n cv2.imwrite(str(path), img)","def resize_img(self,scale=1):\n reduced = self.image.reduce((scale,scale))\n reduced.save(\"../edited/{}\".format(self.image.filename))\n\n reduced = Image.open(\"../edited/{}\".format(self.image.filename))\n return reduced","def SaveOneImg(x, filename):\r\n # 6.1 Min and Max values in this data\r\n lower = np.min(x[0,:])\r\n upper = np.max(x[0,:])\r\n # 6.2 Range of values\r\n range = upper - lower\r\n # 6.3 Normalize now\r\n trans = (x[0,:] - lower)/range # Normalize image to values [0,1]\r\n imsave(filename, trans.reshape(75,75)) # Reshape image and save it to disk\r\n return os.path.getsize(filename) # Return img size on disk\r","def scale_image(img_path, ratio):\n img = cv2.imread(img_path)\n (h, w) = img.shape[:2]\n h = int(h * ratio)\n w = int(w * ratio)\n img = cv2.resize(img, (w, h))\n cv2.imwrite(img_path, img)","def set_scale_factors_to_output_size(self):\n # Compute the scale_factor using rounded scaled image size.\n height = tf.shape(self._image)[0]\n width = tf.shape(self._image)[1]\n max_image_size = tf.to_float(tf.maximum(height, width))\n image_scale = tf.to_float(self._output_size) / max_image_size\n scaled_height = tf.to_int32(tf.to_float(height) * image_scale)\n scaled_width = tf.to_int32(tf.to_float(width) * image_scale)\n self._image_scale = image_scale\n self._scaled_height = scaled_height\n self._scaled_width = scaled_width","def rescale(self, img):\n\n if self.scale != 1:\n return imutils.resize(img, width=int(img.shape[1] * self.scale))\n else:\n return img","def aspect_scale(img, rescale_tuple):\n bx, by = rescale_tuple\n ix,iy = img.get_size()\n\n if ix > iy:\n scale_factor = bx/float(ix)\n sy = scale_factor * iy\n if sy > by:\n scale_factor = by/float(iy)\n sx = scale_factor * ix\n sy = by\n else:\n sx = bx\n else:\n scale_factor = by/float(iy)\n sx = scale_factor * ix\n if sx > bx:\n scale_factor = bx/float(ix)\n sx = bx\n sy = scale_factor * iy\n else:\n sy = by\n\n return int(sx), int(sy)","def save_image(image_numpy, image_path, aspect_ratio=1.0):\n\n image_pil = Image.fromarray(image_numpy)\n h, w, _ = image_numpy.shape\n\n if aspect_ratio > 1.0:\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\n if aspect_ratio < 1.0:\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\n image_pil.save(image_path)","def save_image(image_numpy, image_path, aspect_ratio=1.0):\n\n image_pil = Image.fromarray(image_numpy)\n h, w, _ = image_numpy.shape\n\n if aspect_ratio > 1.0:\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\n if aspect_ratio < 1.0:\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\n image_pil.save(image_path)","def save(image, name):\n from matplotlib import pyplot\n import matplotlib as mpl\n fig = pyplot.figure()\n ax = fig.add_subplot(1,1,1)\n imgplot = ax.imshow(image, cmap=mpl.cm.Greys)\n imgplot.set_interpolation('nearest')\n ax.xaxis.set_ticks_position('top')\n ax.yaxis.set_ticks_position('left')\n pyplot.savefig(name)","def imageScale(scale):\n\t\treturn max(1, int(scale * (InterfaceTools.getCanvasSize()[0] / height)))","def save_image(filename, image):\n im = cv2.resize(image, None, fx=SCALE_DOWN, fy=SCALE_DOWN)\n cv2.imwrite(os.path.join(OUT_DIR, filename), im)","def save_image(image_numpy, image_path, aspect_ratio=1.0):\n\n image_pil = Image.fromarray(image_numpy)\n h, w, _ = image_numpy.shape\n\n if aspect_ratio is None:\n pass\n elif aspect_ratio > 1.0:\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\n elif aspect_ratio < 1.0:\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\n image_pil.save(image_path)","def create_image(pixels, out_path, scaled=False):\n if scaled:\n # e.g. flirIrCamera\n Gmin = pixels[pixels>0].min()\n Gmax = pixels.max()\n scaled_px = (pixels-Gmin)/(Gmax - Gmin)\n plt.imsave(out_path, cm.get_cmap('jet')(scaled_px))\n else:\n # e.g. PSII\n # TODO: Can we make these use same library?\n # TODO: plt.imsave(out_path, pixels)\n Image.fromarray(pixels).save(out_path)","def scale(input_img, size):\n width, height = size\n old_height, old_width = input_img.shape\n x_scale = float(height) / old_height\n y_scale = float(width) / old_width\n\n output_img = np.zeros((height, width), dtype=np.uint8)\n for xidx in xrange(height):\n old_x = float(xidx) / x_scale\n for yidx in xrange(width):\n old_y = float(yidx) / y_scale\n if old_x.is_integer() or old_y.is_integer():\n output_img[xidx, yidx] = input_img[int(old_x), int(old_y)]\n else: # use bilinear interpolation\n x1 = int(np.floor(old_x))\n x2 = int(np.ceil(old_x)) if int(np.ceil(old_x)) < old_height else old_height - 1\n y1 = int(np.floor(old_y))\n y2 = int(np.ceil(old_y)) if int(np.ceil(old_y)) < old_width else old_width - 1\n\n q11 = input_img[x1, y1]\n q12 = input_img[x1, y2]\n q21 = input_img[x2, y1]\n q22 = input_img[x2, y2]\n\n output_img[xidx, yidx] = (q11 * (x2 - old_x) * (y2 - old_y)\n + q21 * (old_x - x1) * (y2 - old_y)\n + q12 * (x2 - old_x) * (old_y - y1)\n + q22 * (old_x - x1) * (old_y - y1)) \\\n / ((x2 - x1) * (y2 - y1) + 1e-10)\n\n return output_img","def rescale_image(image, scale=0.50):\r\n \r\n wi = int(image.shape[1]*scale)\r\n hei = int(image.shape[0]*scale)\r\n dimension = (wi, hei)\r\n return cv.resize(image, dimension, interpolation = cv.INTER_AREA)","def scale_image(image: Image, scale: float) -> Image:\n width = round(image.width * scale)\n height = round(image.height * scale)\n image.thumbnail((width, height))\n return image","def save_image(image, output_path, limits=None):\n\n # Generate a figure with no axes, border, etc.\n fig = plt.figure()\n fig.set_size_inches(1, 1)\n ax = plt.Axes(fig, [0, 0, 1, 1])\n ax.set_axis_off()\n fig.add_axes(ax)\n\n # If the image is complex, warn the user and discard the imaginary part.\n if np.iscomplexobj(image):\n warnings.warn('Image is complex; only saving real part')\n image = np.real(image)\n\n # Plot the image, scaled according to the limits if they are provided.\n if limits is None:\n ax.imshow(image, cmap='gray', aspect='auto', interpolation='none')\n else:\n vmin = limits[0]\n vmax = limits[1]\n ax.imshow(image, cmap='gray', vmin=vmin, vmax=vmax, aspect='auto', interpolation='none')\n\n # Save the figure with a high resolution, and close it.\n plt.savefig(output_path, dpi=800)\n plt.close()","def rescale_and_resize_image(img_name, img_size, save_img):\n \n try:\n \n # Open image\n img = Image.open(img_name)\n \n # Resize image\n img = img.resize((int(img_size), int(img_size)), Image.ANTIALIAS) \n \n # Get data from image\n img_list = list(img.getdata())\n \n # Find minimum and maximum value pixels in the image\n img_max = max(img_list)\n img_min = min(img_list)\n \n # Determine factor to scale to a 8-bit image\n scale_factor = 255.0/(img_max - img_min)\n \n img_list_new = [0] * img_size * img_size\n \n # Rescale all pixels to the range 0 to 255 (in line with unit8 values)\n for i in range(0,img_size):\n for j in range(0,img_size):\n img_list_new[i*img_size + j] = int((img_list[i*img_size + j]-img_min)*scale_factor)\n if (img_list_new[i*img_size + j] > 255) or (img_list_new[i*img_size + j] < 0) or (img_list_new[i*img_size + j]-int(img_list_new[i*img_size + j]) != 0):\n print(\"img_list_new[%d][%d] = %r\" % (i,j,img_list_new[i*img_size + j]))\n \n img.putdata(img_list_new)\n \n # Convert to uint8 greyscale image\n img = img.convert('L')\n \n # Save image\n if save_img:\n img.save(img_name)\n else:\n ph = ImageTk.PhotoImage(img)\n return ph\n \n finally:\n \n # Close image\n img.close()","def Save_Image_Crop(img, x, y, width, height, filename = None, path = 'Predictions'):\n img = img[y:y+height, x:x+width,:]\n\n if filename is not None:\n try: \n os.mkdir(path)\n except OSError as error: \n print('') \n fig, ax = plt.subplots(figsize=(18, 20))\n ax.imshow(img)\n plt.tight_layout()\n plt.savefig(path + '/' + filename + '_Crop.png')","def scale(self):","def save(self, fn):\n plt.imsave(fn, self.image)","def export_to_scale(\n paper_size: tuple[float, float] = (8.5, 11),\n origin: tuple[float, float] = (0, 0),\n scale: float = 1,\n dpi: int = 300,\n):\n doc = make_doc(offset=(1, 2), size=(6.5, 8))\n msp = doc.modelspace()\n msp.add_mtext(\n f\"scale = 1:{scale}\\n\"\n f\"paper size = {paper_size[0]:.1f} inch x {paper_size[1]:.1f} inch \",\n dxfattribs={\"style\": \"OpenSans\", \"char_height\": 0.25},\n ).set_location(\n (0.2, 0.2), attachment_point=MTextEntityAlignment.BOTTOM_LEFT\n )\n\n ctx = RenderContext(doc)\n fig: plt.Figure = plt.figure(dpi=dpi)\n ax: plt.Axes = fig.add_axes([0, 0, 1, 1])\n\n # disable all margins\n ax.margins(0)\n\n # get the final render limits in drawing units:\n min_x, min_y, max_x, max_y = render_limits(\n origin, paper_size, scale\n )\n\n ax.set_xlim(min_x, max_x)\n ax.set_ylim(min_y, max_y)\n\n out = MatplotlibBackend(ax)\n # finalizing invokes auto-scaling by default!\n Frontend(ctx, out).draw_layout(msp, finalize=False)\n\n # set output size in inches:\n fig.set_size_inches(paper_size[0], paper_size[1], forward=True)\n\n fig.savefig(CWD / f\"image_scale_1_{scale}.pdf\", dpi=dpi)\n plt.close(fig)","def scale_image(self, pixels, size):\n x_min, x_max = np.amin(pixels[:,0]), np.amax(pixels[:,0])\n y_min, y_max = np.amin(pixels[:,1]), np.amax(pixels[:,1])\n z_min, z_max = np.amin(pixels[:,2]), np.amax(pixels[:,2])\n \n pixels[:,0] -= x_min \n pixels[:,1] -= y_min\n pixels[:,2] -= z_min\n \n x_max -= x_min\n y_max -= y_min\n z_max -= z_min\n \n scale_factor = size / max(x_max, y_max, z_max) \n # All points are now between [0..max]\n\n pixels *= scale_factor\n return pixels","def __scale_image(image, scale: float):\r\n height, width, _ = image.shape\r\n\r\n width_scaled = int(np.ceil(width * scale))\r\n height_scaled = int(np.ceil(height * scale))\r\n\r\n im_data = cv2.resize(image, (width_scaled, height_scaled), interpolation=cv2.INTER_AREA)\r\n\r\n # Normalize the image's pixels\r\n im_data_normalized = (im_data - 127.5) * 0.0078125\r\n\r\n return im_data_normalized","def draw_image(self):\n self.PDF.saveState()\n self.PDF.scale(1, -1)\n # self.PDF.drawImage(\n # LOGO, 490, -78, width=80, preserveAspectRatio=True, mask=\"auto\"\n # )\n self.PDF.restoreState()","def scale_img(img, scale=1.0):\n dim = (int(img.shape[1]*scale), int(img.shape[0]*scale))\n return cv2.resize(img.copy(), dim, interpolation=cv2.INTER_AREA)","def upscale_main_side(output_img):\n #Fixing pixel which y % 2 != 1\n outputx, outputy = output_img.size\n for oy in range(0, outputy-1, 2):\n for ox in range(1, outputx, 2):\n pixel1 = output_img.getpixel((ox-1, oy))\n p1 = pixel1[0]\n p2 = pixel1[1]\n p3 = pixel1[2]\n if ox == outputx-1 :\n output_img.putpixel((ox, oy), (p1, p2, p3))\n else:\n pixel2 = output_img.getpixel((ox+1, oy))\n P1 = pixel2[0]\n P2 = pixel2[1]\n P3 = pixel2[2]\n output_img.putpixel((ox, oy), (int((p1+P1)/2), int((p2+P2)/2), int((p3+P3)/2)))\n #print(f'pixel:{ox, oy} output:{output_img.getpixel((ox,oy))}')\n #Fixing pixel which y % 2 == 1\n for oy in range(1, outputy-1, 2):\n for ox in range(0, outputx):\n pixel1 = output_img.getpixel((ox, oy-1))\n p1 = pixel1[0]\n p2 = pixel1[1]\n p3 = pixel1[2]\n if oy == outputx:\n output_img.putpixel((ox, oy), (p1, p2, p3))\n break\n else:\n pixel2 = output_img.getpixel((ox, oy+1))\n P1 = pixel2[0]\n P2 = pixel2[1]\n P3 = pixel2[2]\n output_img.putpixel((ox, oy), (int((p1+P1)/2), int((p2+P2)/2), int((p3+P3)/2)))\n #print(f'pixel:{ox, oy} output:{output_img.getpixel((ox,oy))}')\n #Save image \n result_img = output_path+'/output.'+working_img.format.lower()\n output_img.save(result_img)\n print('Upscale finished..!')\n output_img.show()","def save_image(path, image): \n if len(image.shape) == 4:\n image = image.reshape((image.shape[1], image.shape[2], image.shape[3]))\n image = np.clip(image * 255.0, 0, 255).astype(np.uint8)\n skimage.io.imsave(path, image)","def clickAutoscale(self, event):\n self.axes.autoscale_view()","def generateScaled(img):\n\n if not img._scaledfn:\n return\n\n aimgfn = join(opts.root, img._filename)\n if not opts.fast:\n img._size = imageSize(aimgfn)\n\n ascaledfn = join(opts.root, img._scaledfn)\n\n if opts.scaled_force:\n if opts.quiet: print \"forced regeneration of '%s'\" % img._scaledfn\n elif not exists(ascaledfn):\n if opts.quiet: print \"thumbnail absent '%s'\" % img._scaledfn\n else:\n # Check if scaledsize has changed\n if not opts.fast:\n img._scaledsize = imageSize(ascaledfn)\n if not checkThumbSize(img._size, \\\n img._scaledsize, \\\n opts.scaled_size):\n if opts.quiet: print \"thumbnail '%s size has changed\" % img._scaledfn\n try:\n # Clear cache for thumbnail size.\n del imageSizeCache[ ascaledfn ]\n except:\n pass\n else:\n if opts.quiet: print \"thumbnail '%s' already generated (size ok)\" \\\n % img._scaledfn\n return\n else:\n if opts.quiet: print \"thumbnail '%s' already generated\" % img._scaledfn\n return\n\n if opts.no_magick:\n if opts.quiet: print \"ImageMagick tools disabled, can't create thumbnail\"\n return\n\n # create necessary directories\n d = dirname(ascaledfn)\n if not exists(d):\n os.makedirs(d)\n\n if opts.pil:\n\n try:\n im = PilImage.open(aimgfn)\n im.thumbnail((opts.scaled_size, opts.scaled_size), config.ScaledImages[\"Interpolation\"])\n im.save(ascaledfn)\n\n img._scaledsize = im.size\n except IOError, e:\n raise SystemExit(\\\n \"Error: identifying file '%s'\" % aimgfn + str(e))\n\n else:\n\n cmd = getMagickProg('convert') + ' -border 2x2 '\n # FIXME check if this is a problem if not specified\n #cmd += '-interlace NONE '\n\n cmd += '-geometry %dx%d ' % (opts.scaled_size, opts.scaled_size)\n\n if opts.scaled_quality:\n cmd += '-quality %d ' % opts.scaled_quality\n\n # This doesn't add text into the picture itself, just the comment in\n # the header.\n if opts.copyright:\n cmd += '-comment \\\"%s\\\" ' % opts.copyright\n\n # We use [1] to extract the thumbnail when there is one.\n # It is harmless otherwise.\n subimg = \"\"\n if img._ext.lower() in [ \".jpg\", \".tif\", \".tiff\" ]:\n subimg = \"[1]\"\n\n cmd += '\"%s%s\" \"%s\"' % (aimgfn, subimg, ascaledfn)\n\n if opts.quiet: print \"generating thumbnail '%s'\" % img._scaledfn\n\n (chin, chout, cherr) = os.popen3(cmd)\n errs = cherr.readlines()\n chout.close()\n cherr.close()\n if errs:\n print >> sys.stderr, \\\n \"Error: running convert program on %s:\" % aimgfn\n errs = string.join(errs, '\\n')\n print errs\n\n if subimg and \\\n re.compile('Unable to read subimage').search(errs):\n if opts.quiet: print \"retrying without subimage\"\n cmd = string.replace(cmd, subimg, \"\")\n\n (chin, chout, cherr) = os.popen3(cmd)\n errs = cherr.readlines()\n chout.close()\n cherr.close()\n if errs:\n print >> sys.stderr, \\\n \"Error: running convert program on %s:\" % aimgfn\n print string.join(errs, '\\n')\n\n else:\n img._scaledsize = imageSize(ascaledfn)","def autoScale(self):\n\t\tif self.autoscaleToggle:\n\t\t\tif not self.fullscreenToggle:\n\t\t\t\tmaxSize = (self.get_screen().get_width() - 100, self.get_screen().get_height() - 100)\n\t\t\telse:\n\t\t\t\tmaxSize = (self.get_screen().get_width(), self.get_screen().get_height())\n\t\t\timgSize = [self.currentPixbuf.get_width(), self.currentPixbuf.get_height()]\n\n\t\t\tif imgSize[0] > maxSize[0] or imgSize[1] > maxSize[1]:\n\t\t\t\tscaleFactor = 1.0 * maxSize[0] / imgSize[0]\n\t\t\t\tif imgSize[1] * scaleFactor > maxSize[1]:\n\t\t\t\t\tscaleFactor = 1.0 * maxSize[1] / imgSize[1]\n\t\t\t\tself.scaleFactor = scaleFactor\n\t\t\t\timgSize[0] = int(imgSize[0] * scaleFactor)\n\t\t\t\timgSize[1] = int(imgSize[1] * scaleFactor)","def scale_down(image:np.array)->np.array:\n src = image\n scale_percent = 25\n width = int(src.shape[1] * scale_percent / 100)\n height = int(src.shape[0] * scale_percent / 100)\n dsize = (width, height)\n output = cv2.resize(src, dsize)\n return output","def draw_scale(img,scale,width=2,head_enlarge_rate=1,fix_head_size=0):\n scale_img = copy.deepcopy(img)\n for i in range(scale.shape[0]):\n if fix_head_size > 0:\n head_size = fix_head_size\n else:\n head_size = scale[i][2] * head_enlarge_rate\n p1 = (int(round(scale[i][0] - head_size / 2)),\n int(round(scale[i][1] - head_size / 2)))\n p2 = (int(round(scale[i][0] + head_size / 2)),\n int(round(scale[i][1] + head_size / 2)))\n cv2.rectangle(scale_img, p1, p2, (0, 0, 255), width)\n\n return scale_img","def convertImage(self):\n saveAs = config.get(\"saveFormat\")\n saveLocation = config.get(\"saveLocation\")\n image = Image.open(self.folderLocation.text())\n fileName = Path(image.filename).stem\n if saveAs == 'ico':\n size = 256, 256\n destPath = saveLocation+fileName+\".\"+saveAs\n im = Image.open(self.folderLocation.text())\n im.thumbnail(size)\n im.save(destPath, 'jpeg')\n else:\n image.save(saveLocation+fileName+\".\"+saveAs, saveAs)","def scale_image(image=np.zeros((100,100)), \n new_width=100,\n ascii_block_size=(2,3)):\n \n original_width, original_height = image.shape\n aspect_ratio = original_height / float(original_width)\n w,h = ascii_block_size\n new_height = int(h/w * aspect_ratio * new_width)\n\n return skimage.transform.resize(image, (new_width, new_height))","def scaleZoomed(self, bx, by):\n ix, iy = self._image.get_size()\n if ix > iy:\n # fit to width\n scale = bx/float(iy)\n sy = scale * ix\n if sy > by:\n scale = by/float(iy)\n sx = scale * ix\n sy = by\n else:\n sx = bx\n else:\n # fit to height\n scale = by/float(ix)\n sx = scale * iy\n if sx > bx:\n scale = bx/float(ix)\n sx = bx\n sy = scale * iy\n else:\n sy = by\n\n self._image = pygame.transform.scale(self._image, (int(sx), int(sy)))","def scale4x(self) -> 'BaseImage':\n return self.scale2x().scale2x()","def fit_image(self, img, width, height):\n if img.get_height()/height > img.get_width()/width:\n # scale is determined by width\n w = width\n h = int(math.ceil(img.get_height() * (w/img.get_width())))\n else:\n # scale is determined by height\n h = height\n w = int(math.ceil(img.get_width() * (h/img.get_height())))\n img = pygame.transform.smoothscale(img, (w,h))\n rect = img.get_rect()\n rect = rect.move((width-w)//2, (height-h)//2)\n img2 = pygame.Surface((width, height))\n img2.blit(img, rect)\n return img2","def saveImage(np_img, output_path, mode=None, scale=255.0):\n\n if mode is not None:\n if mode == 'dist_norm':\n np_img *= scale/np_img.max()\n np_out = Image.fromarray((np_img).astype('uint8'))\n elif mode == 'blob_labels':\n np_out = Image.fromarray((np_img*255).astype(np.uint8))\n else:\n return (mode, \" is not a supported mode.\")\n else:\n np_out = Image.fromarray(np_img)\n np_out.save(output_path)\n\n if os.path.exists(output_path):\n return 0\n else:\n return 1","def save_resized_image(image, resolution: float, image_name: str):\n\tfilename: str = join(join(base_directory, str(resolution) + 'x'),\n\t image_name)\n\tprint(image_name)\n\tprint(join(base_directory, str(resolution)))\n\tprint(filename)\n\tcv.imwrite(filename, image)","def save(self, grid, output_dir, output_name):\n save_grayscale(grid, output_dir, output_name)","def rescale_image(image: np.ndarray, scale: float) -> np.ndarray:\n (height, width) = image.shape[:2]\n new_dims = (int(width * scale), int(height * scale))\n return cv2.resize(image, new_dims, interpolation=cv2.INTER_CUBIC)","def resize(im, new_size, preserve_aspect_ratio=True, prefilter=True):\n factors = [new_size[i] / im.shape[i] for i in range(2)]\n\n #assert factors[0] == factors[1], \"Must have same factor for now\"\n f = factors[0] \n \n if f < 1:\n im2 = pyramid_reduce(im, downscale=1/f)\n elif f > 1:\n im2 = pyramid_expand(im, upscale=f)\n else:\n im2 = im\n\n assert im2.shape[:2] == tuple(new_size), \"{0} != {1} (original size: {2})\".format(im2.shape, new_size, im.shape)\n \n return im2","def compress_image(filename = \"hubble.jpg\", s = 2):\n \n image = imread(filename)/255\n \n toShow = plt.subplot(121)\n \n #Color\n if len(np.shape(image)) == 3:\n #Set up original RGB values\n R = np.array(image[:,:,0])\n G = np.array(image[:,:,1])\n B = np.array(image[:,:,2])\n \n R, errR = svd_approx(R,s)\n G, errG = svd_approx(G,s)\n B, errB = svd_approx(B,s)\n imageF = np.dstack((R,G,B))\n err = errR + errG + errB\n toShow.imshow(imageF)\n toShow.set_title(\"New \" + str(err) + \", so \" + str((image.size-err)) + \" \\\"saved\\\"\")\n toShow.axis(\"off\")\n \n toShow = plt.subplot(122)\n toShow.set_title(\"Original \" + str(image.size))\n toShow = plt.imshow(image)\n #Gray\n else:\n imageF, err = svd_approx(image, s)\n# print(np.shape(imageF))\n toShow.imshow(imageF, cmap = \"gray\")\n toShow.set_title(\"New \" + str(err) + \", so \" + str((image.size-err)) + \" \\\"saved\\\"\")\n toShow.axis(\"off\")\n toShow = plt.subplot(122)\n toShow.set_title(\"Original \" + str(image.size))\n toShow = plt.imshow(image, cmap = \"gray\")\n \n plt.suptitle(\"MY PLOTS: \" + str((image.size-err)) + \" \\\"saved\\\" :p\")\n \n return\n raise NotImplementedError(\"Problem 5 Incomplete\")","def scale(self, scale):\n \n scale_matrix = wf.scaleMatrix(scale, self.width/2, self.height/2, 0)\n self.transform(scale_matrix)","def resize_preserving_aspect_then_crop(self, image, new_shape):\n orig_shape = image.shape\n orig_height = orig_shape[0]\n orig_width = orig_shape[1]\n orig_chans = orig_shape[2]\n if orig_height > orig_width:\n scale = new_shape[0]/orig_width\n else:\n scale = new_shape[1]/orig_height\n new_height = int(orig_height * scale)\n new_width = int(orig_width * scale)\n # resize preserving aspect ratio\n image = transform.resize(image, [new_height, new_width, orig_chans], anti_aliasing=True,\n mode=\"reflect\")\n # crop to square\n image = self.crop_to_size(image, new_shape)\n # in case original image dim was less than new dim, expand\n image = transform.resize(image, new_shape, anti_aliasing=True,\n mode=\"reflect\")\n return image","def rescale_image(self, img_file, new_width, new_height, model_path, file_description):\n cwd = os.getcwd()\n self.new_width = new_width\n self.new_height = new_height\n self.extract_file_name(img_file)\n shutil.copy(img_file, os.path.join('utils_dfn/temp', self.file_name_with_ext))\n self.run_padding()\n self.run_dfn(model_path)\n self.restore_to_correct_size(file_description)\n clean()","def resize_img(input_img, scale=1.1):\n if scale == 1.0:\n return input_img\n rows, cols, ch = input_img.shape\n d = rows * (scale - 1) # overall image size change from rows, cols, to rows - 2d, cols - 2d\n pts1 = np.float32([[d, d], [rows - 1 - d, d], [d, cols - 1 - d], [rows - 1 - d, cols - 1 - d]])\n pts2 = np.float32([[0, 0], [rows - 1, 0], [0, cols - 1], [rows - 1, cols - 1]])\n M = cv2.getPerspectiveTransform(pts1, pts2)\n dst = cv2.warpPerspective(input_img, M, (cols, rows), borderMode=1)\n return dst","def save_normalized_image(path, data):\n image_parser = ImageFile.Parser()\n try:\n image_parser.feed(data)\n image = image_parser.close()\n except IOError:\n return False\n image.thumbnail(MAX_IMAGE_SIZE, Image.ANTIALIAS)\n if image.mode != 'RGB':\n image = image.convert('RGB')\n image.save(path)\n return True","def ConvertToScaledBitmap(self, size, window=None):\n size = wx.Size(*size)\n if window:\n size.width = int(size.width * window.GetContentScaleFactor())\n size.height = int(size.height * window.GetContentScaleFactor())\n\n # We can only have one overall scale factor for both dimensions with\n # this rasterization method, so chose either the minimum of width or\n # height to help ensure it fits both ways within the specified size.\n sx = size.width / self.width\n sy = size.height / self.height\n scale = min(sx, sy)\n return self.ConvertToBitmap(scale=scale, width=size.width, height=size.height)","def set_scales(self):\r\n self.canvas.update()\r\n self.dxmin = self.dmargin\r\n self.dymin = self.dmargin\r\n self.dxmax = self.canvas.winfo_width() - self.dmargin - 1\r\n self.dymax = self.canvas.winfo_height() - self.dmargin - 1\r\n\r\n # Flip the Y coordinates to invert the result.\r\n if self.y_is_flipped:\r\n self.dymin, self.dymax = self.dymax, self.dymin\r\n\r\n self.xscale = (self.dxmax - self.dxmin) / (self.wxmax - self.wxmin)\r\n self.yscale = (self.dymax - self.dymin) / (self.wymax - self.wymin)\r\n\r\n # Calculate 1 pixel in world coordinates.\r\n self.xpix = 1 / self.xscale\r\n self.ypix = 1 / self.yscale","def save_to_image_file(self, filename, image_format='png', scale_x=1, scale_y=1):\n\n self.save_barcode_to_pillow(scale_x=scale_x, scale_y=scale_y).save(filename,\n format=image_format)","def save_image(image, figsize, save_path, ticks=False, grey=True):\n fig = plt.figure(figsize=figsize)\n if grey:\n plt.imshow(image, cmap=plt.get_cmap('gray'))\n else:\n plt.imshow(image)\n if not ticks:\n plt.xticks([]), plt.yticks([])\n plt.tight_layout()\n fig.savefig(save_path)\n plt.close(fig)\n return","def downscale_image(img, bottom, x, y):\n width, height = tuple(img.shape[1::-1])\n img = img[int(round((1 - bottom) * (height - 1))):(height - 1), 1:(width - 1)]\n img = cv2.resize(img, (x, y))\n #img = cv2.Canny(img, 100, 200)\n ret, img = cv2.threshold(img, img.mean(), 255, cv2.THRESH_BINARY)\n return img","def save_image(self):\r\n filename = filedialog.asksaveasfilename(title='Save Image As...',\r\n filetypes=((\"Portable Network Graphics (.png)\", \"*.png\"), (\"Portable Document Format(.pdf)\", \"*.pdf\")))\r\n self.graph.savefig(filename, dpi=self.graph.dpi)","def cb_save(event):\n fig.savefig('sample.univariate_discrete.py.png', dpi=300, format='png', transparent=True)","def scale_invert(self):","def save_image(self):\n self.save()","def _point_scale2img(points, _H, _W):\n # with tf.variable_scope(\"_point_scale2img\", reuse=False):\n points = points * tf.constant([_H - 1, _W - 1], \"float32\")\n return points","def imsave(file_name, img):\n assert(type(img) == torch.FloatTensor,\n 'img must be a torch.FloatTensor')\n ndim = len(img.size())\n assert(ndim == 2 or ndim == 3,\n 'img must be a 2 or 3 dimensional tensor')\n\n img = img.numpy()\n\n if ndim == 3:\n plt.imsave(file_name, np.transpose(img, (1, 2, 0)))\n else:\n plt.imsave(file_name, img, cmap='gray')","def save_plot_as_image(self):\r\n plt.savefig(ROOT_DIR + '/presentation/images/' + self.folder + '/' + self.generated_image_name + '.png',\r\n bbox_inches='tight')","def scale_img(img):\r\n # Scale values of img between 0 and 255.\r\n img -= np.amin(img)\r\n img /= np.amax(img)\r\n img *= 255\r\n return img","def test_scale_image_gray_identity(self):\n scaled = scale_image(self.gray_image, 1)\n self.assertEqual(self.gray_image.shape, scaled.shape)","def convert(fn):\n assert fn[-4:] == \".npy\", \"%s: File extension should match '.npy'\" % fn\n\n print \"Converting file '%s' to .png\" % fn\n numpy_img = np.load(fn)\n\n #Rescale to 0-255 and convert to uint8\n rescaled = (255.0 / numpy_img.max() * (numpy_img - numpy_img.min())).astype(np.uint8)\n\n im = Image.fromarray(rescaled)\n im.save(fn[:-4] + \".png\")","def scale(self,id,x,y,s):\n if id not in self.elements.keys():\n print(\"Id input not registered! Please check your process\")\n return False\n element=self.elements[id]\n state=element.scale(self.h-1-y,x,s,self.w,self.h)\n if state==True:\n self.canvas=np.ones((self.h,self.w,3),dtype=np.uint8)*255\n self.sync=False\n return state","def save_image(path, image, cmap='gist_earth_r'):\n n_cols = n_rows = 1\n n_pixels = 256\n dpi_of_monitor = 96 # HARDCODED DPI VALUE FROM MY OLD DELL LAPTOP...\n figsize = (n_pixels * n_cols / dpi_of_monitor,\n n_pixels * n_rows / dpi_of_monitor)\n f, ax = plt.subplots(n_rows, n_cols, figsize=figsize)\n f.subplots_adjust(wspace=0, hspace=0, left=0, right=1, bottom=0, top=1)\n ax.axis('off')\n ax.imshow(image, cmap=cmap, vmin=0, vmax=None)\n f.savefig(path, dpi=dpi_of_monitor)\n plt.close(f)","def scale(self, scale=1):\n self.x *= scale\n self.y *= scale\n self.width *= scale\n self.height *= scale\n\n # Always update the corners after operation\n self.update_corners()\n return","def _rescale(x, xlim, ylim):\n m = (ylim[1] - ylim[0]) / (xlim[1] - xlim[0])\n c = ylim[1] - m * xlim[1]\n y = m * x + c\n return y","def autoscale(self, img: Image, max_height: int, max_width: int):\n height = img.bgr.shape[0]\n width = img.bgr.shape[1]\n\n diff_height = max_height / height\n diff_width = max_width / width\n\n diff = min(diff_height, diff_width)\n\n height = int(height * diff)\n width = int(width * diff)\n\n return img.rescale_image(height, width)","def scaleImageToEqualSize(sourceImg, targetImg):\n return cv2.resize(sourceImg,\n None, # no specific out dim\n fx=targetImg.shape[1] / sourceImg.shape[1], # scale factor Y\n fy=targetImg.shape[0] / sourceImg.shape[0], # scale factor X\n interpolation=cv2.INTER_AREA)","def save(self, filename):\n self.image.save(filename, self.options.img_format)","def downsample_image(img, output_path, ratio=2):\n assert ratio>=1, ratio\n if ratio == 1:\n return True\n old_im = Image.open(img)\n old_size = old_im.size\n new_size = (int(old_size[0]/ratio), int(old_size[1]/ratio))\n\n new_im = old_im.resize(new_size, PIL.Image.LANCZOS)\n new_im.save(output_path)\n return True","def make_square_axes(ax):\n ax.set_aspect(1 / ax.get_data_ratio())","def numpyEnlarge(self,img,scale):\n if scale==1:\n # don't need alpha on output\n self.frameBuffer=img[:ALPHA]\n return\n if scale<1:\n raise InvalidScale(\"numpyEnlarge can only be used to enlarge. Got scale factor \"+str(scale))\n\n h,w=img.shape[:2]\n for x in xrange(w):\n for y in xrange(h):\n pixel = img[y, x]\n y1=y*scale\n y2=y1+scale\n x1=x*scale\n x2=x1+scale\n self.frameBuffer[y1:y2, x1:x2] = pixel[:ALPHA]","def save_image(lt_image, out_dir, filename, max_width=None):\n if not lt_image.stream:\n return\n\n filedata = lt_image.stream.get_data()\n out_file_name = join(out_dir, filename)\n\n bits_per_component = lt_image.stream.attrs['BitsPerComponent']\n if bits_per_component == 8:\n # カラーとグレー画像はそのまま保存\n with open(out_file_name, 'wb') as fp:\n fp.write(filedata)\n elif bits_per_component == 1:\n # モノクロ画像はfiledataから作成\n w, h = lt_image.stream.attrs['Width'], lt_image.stream.attrs['Height']\n img = Image.frombytes('1', (w, h), filedata)\n # グレー化、リサイズ、invertを行って保存\n img = img.convert('L').resize((w // 2, h // 2), Image.ANTIALIAS)\n img = ImageOps.invert(img)\n img.save(out_file_name)\n\n if max_width:\n print('max_width:', max_width)\n img = Image.open(out_file_name)\n w, h = img.size[:2]\n img_resize = img.resize((max_width, h * max_width // w), Image.ANTIALIAS)\n img_resize.save(out_file_name)","def save(self):\n img = Image.new(\"1\", (self.container.width, self.container.height))\n draw = ImageDraw.Draw(img)\n for item in self.items:\n draw.ellipse(item.box_coordinates(), fill=1)\n del draw\n img.save(\"plot.bmp\", \"bmp\")","def zoom(cls, img, zoom):\n w, h = img.size\n x = h / 2\n y = w / 2\n zoom2 = zoom * 2\n img = img.crop((x - w / zoom2, y - h / zoom2,\n x + w / zoom2, y + h / zoom2))\n return img.resize((w, h), Image.LANCZOS)","def compress_image(filename, s):\r\n image = imread(filename) / 255\r\n size = image.shape\r\n orig_entries = image.size\r\n #colored\r\n if len(size) == 3:\r\n #plot original\r\n orig = plt.subplot(121)\r\n orig.imshow(image)\r\n orig.axis(\"off\")\r\n #red in image\r\n R = image[:,:,0]\r\n #green in image\r\n G = image[:,:,1]\r\n #blue in image\r\n B = image[:,:,2]\r\n #approximate red, green and blue in range\r\n new_R, entries_R = svd_approx(R,s)\r\n new_R = np.clip(new_R,0,1)\r\n new_G, entries_G = svd_approx(G,s)\r\n new_G = np.clip(new_G,0,1)\r\n new_B, entries_B = svd_approx(B,s)\r\n new_B = np.clip(new_B,0,1)\r\n #stack all in one array\r\n new_image = np.dstack((new_R,new_G,new_B))\r\n #plot image\r\n new = plt.subplot(122)\r\n new.imshow(new_image)\r\n new.axis(\"off\")\r\n #title image with saved number of entries\r\n plt.suptitle(str(orig_entries - (entries_R+entries_G+entries_B)) + \" Entries\")\r\n\r\n\r\n #grayscale\r\n else:\r\n #plot original\r\n orig = plt.subplot(121)\r\n orig.imshow(image, cmap=\"gray\")\r\n orig.axis(\"off\")\r\n #approximate the image\r\n new_A, entries = svd_approx(image,s)\r\n #plot it\r\n new = plt.subplot(122)\r\n new.imshow(new_A, cmap=\"gray\")\r\n new.axis(\"off\")\r\n #title image with saved number of entries\r\n plt.suptitle(str(orig_entries - entries) + \" Entries\")\r\n\r\n plt.show()","def resize(img):\n size = (500, 500)\n img.thumbnail(size)\n return img","def test_scale_image_rgb_identity(self):\n scaled = scale_image(self.rgb_image, 1)\n self.assertEqual(self.rgb_image.shape, scaled.shape)","def scale_image(img, factor=1):\n return cv2.resize(img, (int(img.shape[1] * factor), int(img.shape[0] * factor)))","def preserveAspectRatio(self):\n return self._preserve_aspect_ratio","def tofits(self, *args, **kwargs):\n return _image.image_tofits(self, *args, **kwargs)","def save_image(image_numpy, image_path, aspect_ratio=1.0, color_map=False):\n if color_map:\n import matplotlib.pyplot as plt\n cm = plt.get_cmap('jet')\n colored_image = cm(image_numpy[:,:,0])[:,:,:3]\n# print_numpy(colored_image, val=True, shp=True) # max 1.0 min 0.0 shape (256,256,3)\n \n image_pil = Image.fromarray((colored_image*255.).astype(np.uint8))\n else:\n# print_numpy(image_numpy, val=True, shp=True)\n image_pil = Image.fromarray(image_numpy)\n h, w, _ = image_numpy.shape\n\n if aspect_ratio > 1.0:\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\n if aspect_ratio < 1.0:\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\n image_pil.save(image_path)","def save_figure(self, data):\n\n\t\tsizes = np.shape(data)\n\t\tfig = plt.figure()\n\t\tfig.set_size_inches(1, 1. * sizes[0]/sizes[1], forward = False)\n\t\tax = plt.Axes(fig, [0., 0., 1., 1.])\n\t\tax.set_axis_off()\n\t\tfig.add_axes(ax)\n\t\tax.imshow(data, \"gray\")\n\n\t\t#plt.show()\n\t\tself.plotfile = os.path.join('static', 'Figure' + '.png')\n\t\tplt.savefig(self.plotfile, dpi = sizes[1])","def save_image(self):\n self.compressed_image_id = str(uuid.uuid4().hex)\n plot.imsave(\n str(\n self.compressed_image_id + \"{}\").format(\n \".png\"), self.compressed_image)\n\n if self.verbose:\n print(\n \"Compressed image saved at \" + (\n str(self.compressed_image_id + \"{}\").format(\".png\")))","def get_scaled_image(self, min_width=1024):\n self.dispersion = self.image.getCalibration().pixelWidth\n self.offset = self.image.getCalibration().xOrigin\n binning = 1\n while binning * min_width < self.image.getWidth():\n binning *= 2\n if binning > 1:\n binning /= 2\n IJ.run(self.image, 'Select None', '')\n new_image = self.image.crop()\n IJ.run(new_image, 'Bin...', 'x=%d y=%d binning=Average' %\n (binning, binning))\n self.dispersion *= binning\n self.offset /= binning\n self.image = new_image\n return new_image","def adjust(self, image):\n ...","def resize_image(self, width=200):\n self.new_width = width\n aspect_ratio = self.original_height/float(self.original_width)\n self.new_height = int(aspect_ratio * self.new_width)\n\n resized_image = self.image.resize((self.new_width, self.new_height), Image.BILINEAR)\n return resized_image","def resize_image(image_path):\n image = Image.open(image_path)\n\n imagefit = ImageOps.fit(image, (612, 612), Image.ANTIALIAS)\n imagefit.save(image_path, 'JPEG', quality=100)","def _save(filename, img):\n if not os.path.exists(OUTPUT_DIR):\n os.makedirs(OUTPUT_DIR)\n # filename = filename+'.png'\n filename = os.path.join(OUTPUT_DIR, filename)\n # print(filename, img.shape)\n cv.imwrite(filename, img)","def dat_imshow(x):\n plt.imshow(x,interpolation='nearest',aspect='auto')","def scale_widget_to_image_size(self):\n if self._image is not None:\n im = self._image.make_image()\n self.width = im.shape[1]\n self.height = im.shape[0]"],"string":"[\n \"def exportImg(self):\\n if self.superSampling:\\n print(\\\"Exporting with size adjusted\\\")\\n self.img = self.img.resize((int(self.width/2),int(self.height/2)),Image.NEAREST)\\n self.img.save(self.fileName,\\\"PNG\\\")\",\n \"def save_image_with_scale(path, variable):\\n\\n arr = variable.cpu().data.numpy()\\n arr = np.clip(arr, -1., 1.)\\n arr = (arr+1.)/2 * 255.\\n arr = arr.astype(np.uint8)\\n skimage.io.imsave(path, arr)\",\n \"def scale(img, scale):\\n return resize(img, x_scale=scale, y_scale=scale)\",\n \"def Rescale(self):\\r\\n picWidth,picHeight = self.oldSize = self.GetSizeTuple()\\r\\n bitmap = self.scaled = self.bitmap\\r\\n if not bitmap: return\\r\\n imgWidth,imgHeight = bitmap.GetWidth(),bitmap.GetHeight()\\r\\n if self.scaling == 2 or (self.scaling == 1 and (imgWidth > picWidth or imgHeight > picHeight)):\\r\\n image = bitmap.ConvertToImage()\\r\\n factor = min(1.0*picWidth/imgWidth,1.0*picHeight/imgHeight)\\r\\n newWidth,newHeight = int(factor*imgWidth),int(factor*imgHeight)\\r\\n self.scaled = image.Scale(newWidth,newHeight).ConvertToBitmap()\\r\\n #self.scaled = image.Scale(newWidth,newHeight,wx.IMAGE_QUALITY_HIGH ).ConvertToBitmap()\\r\",\n \"def _scale(self, image):\\n\\n if image.GetWidth() != self._width or image.GetHeight()!= self._height:\\n image.Rescale(self._width, self._height)\\n \\n return image\",\n \"def scale(self, infile: str, outfile: str):\\n\\n with Image(filename=infile) as src:\\n width, height = self.new_dimensions(src)\\n with src.clone() as dest:\\n dest.resize(width=width,height=height)\\n logging.debug(\\n f'Converted \\\"{infile}\\\" ({src.width}x{src.height})'\\n f' -> \\\"{outfile}\\\" ({dest.width}x{dest.height})')\\n dest.save(filename=outfile)\",\n \"def save_subpix_png(path, img, scale_factor=256.0):\\n Path(path).parent.mkdir(parents=True, exist_ok=True)\\n img = img.astype(np.float32) * scale_factor\\n if np.amax(img) > (2**16)-1:\\n warnings.warn(\\\"image out of range(\\\" + str(np.amax(img)/scale_factor) +\\n \\\"), try with a smaller scale factor. loading this file \\\" +\\n \\\"will results in invalid values, file: \\\"+str(path))\\n img[img > (2**16)-1] = 0\\n img = img.astype(np.uint16)\\n cv2.imwrite(str(path), img)\",\n \"def resize_img(self,scale=1):\\n reduced = self.image.reduce((scale,scale))\\n reduced.save(\\\"../edited/{}\\\".format(self.image.filename))\\n\\n reduced = Image.open(\\\"../edited/{}\\\".format(self.image.filename))\\n return reduced\",\n \"def SaveOneImg(x, filename):\\r\\n # 6.1 Min and Max values in this data\\r\\n lower = np.min(x[0,:])\\r\\n upper = np.max(x[0,:])\\r\\n # 6.2 Range of values\\r\\n range = upper - lower\\r\\n # 6.3 Normalize now\\r\\n trans = (x[0,:] - lower)/range # Normalize image to values [0,1]\\r\\n imsave(filename, trans.reshape(75,75)) # Reshape image and save it to disk\\r\\n return os.path.getsize(filename) # Return img size on disk\\r\",\n \"def scale_image(img_path, ratio):\\n img = cv2.imread(img_path)\\n (h, w) = img.shape[:2]\\n h = int(h * ratio)\\n w = int(w * ratio)\\n img = cv2.resize(img, (w, h))\\n cv2.imwrite(img_path, img)\",\n \"def set_scale_factors_to_output_size(self):\\n # Compute the scale_factor using rounded scaled image size.\\n height = tf.shape(self._image)[0]\\n width = tf.shape(self._image)[1]\\n max_image_size = tf.to_float(tf.maximum(height, width))\\n image_scale = tf.to_float(self._output_size) / max_image_size\\n scaled_height = tf.to_int32(tf.to_float(height) * image_scale)\\n scaled_width = tf.to_int32(tf.to_float(width) * image_scale)\\n self._image_scale = image_scale\\n self._scaled_height = scaled_height\\n self._scaled_width = scaled_width\",\n \"def rescale(self, img):\\n\\n if self.scale != 1:\\n return imutils.resize(img, width=int(img.shape[1] * self.scale))\\n else:\\n return img\",\n \"def aspect_scale(img, rescale_tuple):\\n bx, by = rescale_tuple\\n ix,iy = img.get_size()\\n\\n if ix > iy:\\n scale_factor = bx/float(ix)\\n sy = scale_factor * iy\\n if sy > by:\\n scale_factor = by/float(iy)\\n sx = scale_factor * ix\\n sy = by\\n else:\\n sx = bx\\n else:\\n scale_factor = by/float(iy)\\n sx = scale_factor * ix\\n if sx > bx:\\n scale_factor = bx/float(ix)\\n sx = bx\\n sy = scale_factor * iy\\n else:\\n sy = by\\n\\n return int(sx), int(sy)\",\n \"def save_image(image_numpy, image_path, aspect_ratio=1.0):\\n\\n image_pil = Image.fromarray(image_numpy)\\n h, w, _ = image_numpy.shape\\n\\n if aspect_ratio > 1.0:\\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\\n if aspect_ratio < 1.0:\\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\\n image_pil.save(image_path)\",\n \"def save_image(image_numpy, image_path, aspect_ratio=1.0):\\n\\n image_pil = Image.fromarray(image_numpy)\\n h, w, _ = image_numpy.shape\\n\\n if aspect_ratio > 1.0:\\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\\n if aspect_ratio < 1.0:\\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\\n image_pil.save(image_path)\",\n \"def save(image, name):\\n from matplotlib import pyplot\\n import matplotlib as mpl\\n fig = pyplot.figure()\\n ax = fig.add_subplot(1,1,1)\\n imgplot = ax.imshow(image, cmap=mpl.cm.Greys)\\n imgplot.set_interpolation('nearest')\\n ax.xaxis.set_ticks_position('top')\\n ax.yaxis.set_ticks_position('left')\\n pyplot.savefig(name)\",\n \"def imageScale(scale):\\n\\t\\treturn max(1, int(scale * (InterfaceTools.getCanvasSize()[0] / height)))\",\n \"def save_image(filename, image):\\n im = cv2.resize(image, None, fx=SCALE_DOWN, fy=SCALE_DOWN)\\n cv2.imwrite(os.path.join(OUT_DIR, filename), im)\",\n \"def save_image(image_numpy, image_path, aspect_ratio=1.0):\\n\\n image_pil = Image.fromarray(image_numpy)\\n h, w, _ = image_numpy.shape\\n\\n if aspect_ratio is None:\\n pass\\n elif aspect_ratio > 1.0:\\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\\n elif aspect_ratio < 1.0:\\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\\n image_pil.save(image_path)\",\n \"def create_image(pixels, out_path, scaled=False):\\n if scaled:\\n # e.g. flirIrCamera\\n Gmin = pixels[pixels>0].min()\\n Gmax = pixels.max()\\n scaled_px = (pixels-Gmin)/(Gmax - Gmin)\\n plt.imsave(out_path, cm.get_cmap('jet')(scaled_px))\\n else:\\n # e.g. PSII\\n # TODO: Can we make these use same library?\\n # TODO: plt.imsave(out_path, pixels)\\n Image.fromarray(pixels).save(out_path)\",\n \"def scale(input_img, size):\\n width, height = size\\n old_height, old_width = input_img.shape\\n x_scale = float(height) / old_height\\n y_scale = float(width) / old_width\\n\\n output_img = np.zeros((height, width), dtype=np.uint8)\\n for xidx in xrange(height):\\n old_x = float(xidx) / x_scale\\n for yidx in xrange(width):\\n old_y = float(yidx) / y_scale\\n if old_x.is_integer() or old_y.is_integer():\\n output_img[xidx, yidx] = input_img[int(old_x), int(old_y)]\\n else: # use bilinear interpolation\\n x1 = int(np.floor(old_x))\\n x2 = int(np.ceil(old_x)) if int(np.ceil(old_x)) < old_height else old_height - 1\\n y1 = int(np.floor(old_y))\\n y2 = int(np.ceil(old_y)) if int(np.ceil(old_y)) < old_width else old_width - 1\\n\\n q11 = input_img[x1, y1]\\n q12 = input_img[x1, y2]\\n q21 = input_img[x2, y1]\\n q22 = input_img[x2, y2]\\n\\n output_img[xidx, yidx] = (q11 * (x2 - old_x) * (y2 - old_y)\\n + q21 * (old_x - x1) * (y2 - old_y)\\n + q12 * (x2 - old_x) * (old_y - y1)\\n + q22 * (old_x - x1) * (old_y - y1)) \\\\\\n / ((x2 - x1) * (y2 - y1) + 1e-10)\\n\\n return output_img\",\n \"def rescale_image(image, scale=0.50):\\r\\n \\r\\n wi = int(image.shape[1]*scale)\\r\\n hei = int(image.shape[0]*scale)\\r\\n dimension = (wi, hei)\\r\\n return cv.resize(image, dimension, interpolation = cv.INTER_AREA)\",\n \"def scale_image(image: Image, scale: float) -> Image:\\n width = round(image.width * scale)\\n height = round(image.height * scale)\\n image.thumbnail((width, height))\\n return image\",\n \"def save_image(image, output_path, limits=None):\\n\\n # Generate a figure with no axes, border, etc.\\n fig = plt.figure()\\n fig.set_size_inches(1, 1)\\n ax = plt.Axes(fig, [0, 0, 1, 1])\\n ax.set_axis_off()\\n fig.add_axes(ax)\\n\\n # If the image is complex, warn the user and discard the imaginary part.\\n if np.iscomplexobj(image):\\n warnings.warn('Image is complex; only saving real part')\\n image = np.real(image)\\n\\n # Plot the image, scaled according to the limits if they are provided.\\n if limits is None:\\n ax.imshow(image, cmap='gray', aspect='auto', interpolation='none')\\n else:\\n vmin = limits[0]\\n vmax = limits[1]\\n ax.imshow(image, cmap='gray', vmin=vmin, vmax=vmax, aspect='auto', interpolation='none')\\n\\n # Save the figure with a high resolution, and close it.\\n plt.savefig(output_path, dpi=800)\\n plt.close()\",\n \"def rescale_and_resize_image(img_name, img_size, save_img):\\n \\n try:\\n \\n # Open image\\n img = Image.open(img_name)\\n \\n # Resize image\\n img = img.resize((int(img_size), int(img_size)), Image.ANTIALIAS) \\n \\n # Get data from image\\n img_list = list(img.getdata())\\n \\n # Find minimum and maximum value pixels in the image\\n img_max = max(img_list)\\n img_min = min(img_list)\\n \\n # Determine factor to scale to a 8-bit image\\n scale_factor = 255.0/(img_max - img_min)\\n \\n img_list_new = [0] * img_size * img_size\\n \\n # Rescale all pixels to the range 0 to 255 (in line with unit8 values)\\n for i in range(0,img_size):\\n for j in range(0,img_size):\\n img_list_new[i*img_size + j] = int((img_list[i*img_size + j]-img_min)*scale_factor)\\n if (img_list_new[i*img_size + j] > 255) or (img_list_new[i*img_size + j] < 0) or (img_list_new[i*img_size + j]-int(img_list_new[i*img_size + j]) != 0):\\n print(\\\"img_list_new[%d][%d] = %r\\\" % (i,j,img_list_new[i*img_size + j]))\\n \\n img.putdata(img_list_new)\\n \\n # Convert to uint8 greyscale image\\n img = img.convert('L')\\n \\n # Save image\\n if save_img:\\n img.save(img_name)\\n else:\\n ph = ImageTk.PhotoImage(img)\\n return ph\\n \\n finally:\\n \\n # Close image\\n img.close()\",\n \"def Save_Image_Crop(img, x, y, width, height, filename = None, path = 'Predictions'):\\n img = img[y:y+height, x:x+width,:]\\n\\n if filename is not None:\\n try: \\n os.mkdir(path)\\n except OSError as error: \\n print('') \\n fig, ax = plt.subplots(figsize=(18, 20))\\n ax.imshow(img)\\n plt.tight_layout()\\n plt.savefig(path + '/' + filename + '_Crop.png')\",\n \"def scale(self):\",\n \"def save(self, fn):\\n plt.imsave(fn, self.image)\",\n \"def export_to_scale(\\n paper_size: tuple[float, float] = (8.5, 11),\\n origin: tuple[float, float] = (0, 0),\\n scale: float = 1,\\n dpi: int = 300,\\n):\\n doc = make_doc(offset=(1, 2), size=(6.5, 8))\\n msp = doc.modelspace()\\n msp.add_mtext(\\n f\\\"scale = 1:{scale}\\\\n\\\"\\n f\\\"paper size = {paper_size[0]:.1f} inch x {paper_size[1]:.1f} inch \\\",\\n dxfattribs={\\\"style\\\": \\\"OpenSans\\\", \\\"char_height\\\": 0.25},\\n ).set_location(\\n (0.2, 0.2), attachment_point=MTextEntityAlignment.BOTTOM_LEFT\\n )\\n\\n ctx = RenderContext(doc)\\n fig: plt.Figure = plt.figure(dpi=dpi)\\n ax: plt.Axes = fig.add_axes([0, 0, 1, 1])\\n\\n # disable all margins\\n ax.margins(0)\\n\\n # get the final render limits in drawing units:\\n min_x, min_y, max_x, max_y = render_limits(\\n origin, paper_size, scale\\n )\\n\\n ax.set_xlim(min_x, max_x)\\n ax.set_ylim(min_y, max_y)\\n\\n out = MatplotlibBackend(ax)\\n # finalizing invokes auto-scaling by default!\\n Frontend(ctx, out).draw_layout(msp, finalize=False)\\n\\n # set output size in inches:\\n fig.set_size_inches(paper_size[0], paper_size[1], forward=True)\\n\\n fig.savefig(CWD / f\\\"image_scale_1_{scale}.pdf\\\", dpi=dpi)\\n plt.close(fig)\",\n \"def scale_image(self, pixels, size):\\n x_min, x_max = np.amin(pixels[:,0]), np.amax(pixels[:,0])\\n y_min, y_max = np.amin(pixels[:,1]), np.amax(pixels[:,1])\\n z_min, z_max = np.amin(pixels[:,2]), np.amax(pixels[:,2])\\n \\n pixels[:,0] -= x_min \\n pixels[:,1] -= y_min\\n pixels[:,2] -= z_min\\n \\n x_max -= x_min\\n y_max -= y_min\\n z_max -= z_min\\n \\n scale_factor = size / max(x_max, y_max, z_max) \\n # All points are now between [0..max]\\n\\n pixels *= scale_factor\\n return pixels\",\n \"def __scale_image(image, scale: float):\\r\\n height, width, _ = image.shape\\r\\n\\r\\n width_scaled = int(np.ceil(width * scale))\\r\\n height_scaled = int(np.ceil(height * scale))\\r\\n\\r\\n im_data = cv2.resize(image, (width_scaled, height_scaled), interpolation=cv2.INTER_AREA)\\r\\n\\r\\n # Normalize the image's pixels\\r\\n im_data_normalized = (im_data - 127.5) * 0.0078125\\r\\n\\r\\n return im_data_normalized\",\n \"def draw_image(self):\\n self.PDF.saveState()\\n self.PDF.scale(1, -1)\\n # self.PDF.drawImage(\\n # LOGO, 490, -78, width=80, preserveAspectRatio=True, mask=\\\"auto\\\"\\n # )\\n self.PDF.restoreState()\",\n \"def scale_img(img, scale=1.0):\\n dim = (int(img.shape[1]*scale), int(img.shape[0]*scale))\\n return cv2.resize(img.copy(), dim, interpolation=cv2.INTER_AREA)\",\n \"def upscale_main_side(output_img):\\n #Fixing pixel which y % 2 != 1\\n outputx, outputy = output_img.size\\n for oy in range(0, outputy-1, 2):\\n for ox in range(1, outputx, 2):\\n pixel1 = output_img.getpixel((ox-1, oy))\\n p1 = pixel1[0]\\n p2 = pixel1[1]\\n p3 = pixel1[2]\\n if ox == outputx-1 :\\n output_img.putpixel((ox, oy), (p1, p2, p3))\\n else:\\n pixel2 = output_img.getpixel((ox+1, oy))\\n P1 = pixel2[0]\\n P2 = pixel2[1]\\n P3 = pixel2[2]\\n output_img.putpixel((ox, oy), (int((p1+P1)/2), int((p2+P2)/2), int((p3+P3)/2)))\\n #print(f'pixel:{ox, oy} output:{output_img.getpixel((ox,oy))}')\\n #Fixing pixel which y % 2 == 1\\n for oy in range(1, outputy-1, 2):\\n for ox in range(0, outputx):\\n pixel1 = output_img.getpixel((ox, oy-1))\\n p1 = pixel1[0]\\n p2 = pixel1[1]\\n p3 = pixel1[2]\\n if oy == outputx:\\n output_img.putpixel((ox, oy), (p1, p2, p3))\\n break\\n else:\\n pixel2 = output_img.getpixel((ox, oy+1))\\n P1 = pixel2[0]\\n P2 = pixel2[1]\\n P3 = pixel2[2]\\n output_img.putpixel((ox, oy), (int((p1+P1)/2), int((p2+P2)/2), int((p3+P3)/2)))\\n #print(f'pixel:{ox, oy} output:{output_img.getpixel((ox,oy))}')\\n #Save image \\n result_img = output_path+'/output.'+working_img.format.lower()\\n output_img.save(result_img)\\n print('Upscale finished..!')\\n output_img.show()\",\n \"def save_image(path, image): \\n if len(image.shape) == 4:\\n image = image.reshape((image.shape[1], image.shape[2], image.shape[3]))\\n image = np.clip(image * 255.0, 0, 255).astype(np.uint8)\\n skimage.io.imsave(path, image)\",\n \"def clickAutoscale(self, event):\\n self.axes.autoscale_view()\",\n \"def generateScaled(img):\\n\\n if not img._scaledfn:\\n return\\n\\n aimgfn = join(opts.root, img._filename)\\n if not opts.fast:\\n img._size = imageSize(aimgfn)\\n\\n ascaledfn = join(opts.root, img._scaledfn)\\n\\n if opts.scaled_force:\\n if opts.quiet: print \\\"forced regeneration of '%s'\\\" % img._scaledfn\\n elif not exists(ascaledfn):\\n if opts.quiet: print \\\"thumbnail absent '%s'\\\" % img._scaledfn\\n else:\\n # Check if scaledsize has changed\\n if not opts.fast:\\n img._scaledsize = imageSize(ascaledfn)\\n if not checkThumbSize(img._size, \\\\\\n img._scaledsize, \\\\\\n opts.scaled_size):\\n if opts.quiet: print \\\"thumbnail '%s size has changed\\\" % img._scaledfn\\n try:\\n # Clear cache for thumbnail size.\\n del imageSizeCache[ ascaledfn ]\\n except:\\n pass\\n else:\\n if opts.quiet: print \\\"thumbnail '%s' already generated (size ok)\\\" \\\\\\n % img._scaledfn\\n return\\n else:\\n if opts.quiet: print \\\"thumbnail '%s' already generated\\\" % img._scaledfn\\n return\\n\\n if opts.no_magick:\\n if opts.quiet: print \\\"ImageMagick tools disabled, can't create thumbnail\\\"\\n return\\n\\n # create necessary directories\\n d = dirname(ascaledfn)\\n if not exists(d):\\n os.makedirs(d)\\n\\n if opts.pil:\\n\\n try:\\n im = PilImage.open(aimgfn)\\n im.thumbnail((opts.scaled_size, opts.scaled_size), config.ScaledImages[\\\"Interpolation\\\"])\\n im.save(ascaledfn)\\n\\n img._scaledsize = im.size\\n except IOError, e:\\n raise SystemExit(\\\\\\n \\\"Error: identifying file '%s'\\\" % aimgfn + str(e))\\n\\n else:\\n\\n cmd = getMagickProg('convert') + ' -border 2x2 '\\n # FIXME check if this is a problem if not specified\\n #cmd += '-interlace NONE '\\n\\n cmd += '-geometry %dx%d ' % (opts.scaled_size, opts.scaled_size)\\n\\n if opts.scaled_quality:\\n cmd += '-quality %d ' % opts.scaled_quality\\n\\n # This doesn't add text into the picture itself, just the comment in\\n # the header.\\n if opts.copyright:\\n cmd += '-comment \\\\\\\"%s\\\\\\\" ' % opts.copyright\\n\\n # We use [1] to extract the thumbnail when there is one.\\n # It is harmless otherwise.\\n subimg = \\\"\\\"\\n if img._ext.lower() in [ \\\".jpg\\\", \\\".tif\\\", \\\".tiff\\\" ]:\\n subimg = \\\"[1]\\\"\\n\\n cmd += '\\\"%s%s\\\" \\\"%s\\\"' % (aimgfn, subimg, ascaledfn)\\n\\n if opts.quiet: print \\\"generating thumbnail '%s'\\\" % img._scaledfn\\n\\n (chin, chout, cherr) = os.popen3(cmd)\\n errs = cherr.readlines()\\n chout.close()\\n cherr.close()\\n if errs:\\n print >> sys.stderr, \\\\\\n \\\"Error: running convert program on %s:\\\" % aimgfn\\n errs = string.join(errs, '\\\\n')\\n print errs\\n\\n if subimg and \\\\\\n re.compile('Unable to read subimage').search(errs):\\n if opts.quiet: print \\\"retrying without subimage\\\"\\n cmd = string.replace(cmd, subimg, \\\"\\\")\\n\\n (chin, chout, cherr) = os.popen3(cmd)\\n errs = cherr.readlines()\\n chout.close()\\n cherr.close()\\n if errs:\\n print >> sys.stderr, \\\\\\n \\\"Error: running convert program on %s:\\\" % aimgfn\\n print string.join(errs, '\\\\n')\\n\\n else:\\n img._scaledsize = imageSize(ascaledfn)\",\n \"def autoScale(self):\\n\\t\\tif self.autoscaleToggle:\\n\\t\\t\\tif not self.fullscreenToggle:\\n\\t\\t\\t\\tmaxSize = (self.get_screen().get_width() - 100, self.get_screen().get_height() - 100)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tmaxSize = (self.get_screen().get_width(), self.get_screen().get_height())\\n\\t\\t\\timgSize = [self.currentPixbuf.get_width(), self.currentPixbuf.get_height()]\\n\\n\\t\\t\\tif imgSize[0] > maxSize[0] or imgSize[1] > maxSize[1]:\\n\\t\\t\\t\\tscaleFactor = 1.0 * maxSize[0] / imgSize[0]\\n\\t\\t\\t\\tif imgSize[1] * scaleFactor > maxSize[1]:\\n\\t\\t\\t\\t\\tscaleFactor = 1.0 * maxSize[1] / imgSize[1]\\n\\t\\t\\t\\tself.scaleFactor = scaleFactor\\n\\t\\t\\t\\timgSize[0] = int(imgSize[0] * scaleFactor)\\n\\t\\t\\t\\timgSize[1] = int(imgSize[1] * scaleFactor)\",\n \"def scale_down(image:np.array)->np.array:\\n src = image\\n scale_percent = 25\\n width = int(src.shape[1] * scale_percent / 100)\\n height = int(src.shape[0] * scale_percent / 100)\\n dsize = (width, height)\\n output = cv2.resize(src, dsize)\\n return output\",\n \"def draw_scale(img,scale,width=2,head_enlarge_rate=1,fix_head_size=0):\\n scale_img = copy.deepcopy(img)\\n for i in range(scale.shape[0]):\\n if fix_head_size > 0:\\n head_size = fix_head_size\\n else:\\n head_size = scale[i][2] * head_enlarge_rate\\n p1 = (int(round(scale[i][0] - head_size / 2)),\\n int(round(scale[i][1] - head_size / 2)))\\n p2 = (int(round(scale[i][0] + head_size / 2)),\\n int(round(scale[i][1] + head_size / 2)))\\n cv2.rectangle(scale_img, p1, p2, (0, 0, 255), width)\\n\\n return scale_img\",\n \"def convertImage(self):\\n saveAs = config.get(\\\"saveFormat\\\")\\n saveLocation = config.get(\\\"saveLocation\\\")\\n image = Image.open(self.folderLocation.text())\\n fileName = Path(image.filename).stem\\n if saveAs == 'ico':\\n size = 256, 256\\n destPath = saveLocation+fileName+\\\".\\\"+saveAs\\n im = Image.open(self.folderLocation.text())\\n im.thumbnail(size)\\n im.save(destPath, 'jpeg')\\n else:\\n image.save(saveLocation+fileName+\\\".\\\"+saveAs, saveAs)\",\n \"def scale_image(image=np.zeros((100,100)), \\n new_width=100,\\n ascii_block_size=(2,3)):\\n \\n original_width, original_height = image.shape\\n aspect_ratio = original_height / float(original_width)\\n w,h = ascii_block_size\\n new_height = int(h/w * aspect_ratio * new_width)\\n\\n return skimage.transform.resize(image, (new_width, new_height))\",\n \"def scaleZoomed(self, bx, by):\\n ix, iy = self._image.get_size()\\n if ix > iy:\\n # fit to width\\n scale = bx/float(iy)\\n sy = scale * ix\\n if sy > by:\\n scale = by/float(iy)\\n sx = scale * ix\\n sy = by\\n else:\\n sx = bx\\n else:\\n # fit to height\\n scale = by/float(ix)\\n sx = scale * iy\\n if sx > bx:\\n scale = bx/float(ix)\\n sx = bx\\n sy = scale * iy\\n else:\\n sy = by\\n\\n self._image = pygame.transform.scale(self._image, (int(sx), int(sy)))\",\n \"def scale4x(self) -> 'BaseImage':\\n return self.scale2x().scale2x()\",\n \"def fit_image(self, img, width, height):\\n if img.get_height()/height > img.get_width()/width:\\n # scale is determined by width\\n w = width\\n h = int(math.ceil(img.get_height() * (w/img.get_width())))\\n else:\\n # scale is determined by height\\n h = height\\n w = int(math.ceil(img.get_width() * (h/img.get_height())))\\n img = pygame.transform.smoothscale(img, (w,h))\\n rect = img.get_rect()\\n rect = rect.move((width-w)//2, (height-h)//2)\\n img2 = pygame.Surface((width, height))\\n img2.blit(img, rect)\\n return img2\",\n \"def saveImage(np_img, output_path, mode=None, scale=255.0):\\n\\n if mode is not None:\\n if mode == 'dist_norm':\\n np_img *= scale/np_img.max()\\n np_out = Image.fromarray((np_img).astype('uint8'))\\n elif mode == 'blob_labels':\\n np_out = Image.fromarray((np_img*255).astype(np.uint8))\\n else:\\n return (mode, \\\" is not a supported mode.\\\")\\n else:\\n np_out = Image.fromarray(np_img)\\n np_out.save(output_path)\\n\\n if os.path.exists(output_path):\\n return 0\\n else:\\n return 1\",\n \"def save_resized_image(image, resolution: float, image_name: str):\\n\\tfilename: str = join(join(base_directory, str(resolution) + 'x'),\\n\\t image_name)\\n\\tprint(image_name)\\n\\tprint(join(base_directory, str(resolution)))\\n\\tprint(filename)\\n\\tcv.imwrite(filename, image)\",\n \"def save(self, grid, output_dir, output_name):\\n save_grayscale(grid, output_dir, output_name)\",\n \"def rescale_image(image: np.ndarray, scale: float) -> np.ndarray:\\n (height, width) = image.shape[:2]\\n new_dims = (int(width * scale), int(height * scale))\\n return cv2.resize(image, new_dims, interpolation=cv2.INTER_CUBIC)\",\n \"def resize(im, new_size, preserve_aspect_ratio=True, prefilter=True):\\n factors = [new_size[i] / im.shape[i] for i in range(2)]\\n\\n #assert factors[0] == factors[1], \\\"Must have same factor for now\\\"\\n f = factors[0] \\n \\n if f < 1:\\n im2 = pyramid_reduce(im, downscale=1/f)\\n elif f > 1:\\n im2 = pyramid_expand(im, upscale=f)\\n else:\\n im2 = im\\n\\n assert im2.shape[:2] == tuple(new_size), \\\"{0} != {1} (original size: {2})\\\".format(im2.shape, new_size, im.shape)\\n \\n return im2\",\n \"def compress_image(filename = \\\"hubble.jpg\\\", s = 2):\\n \\n image = imread(filename)/255\\n \\n toShow = plt.subplot(121)\\n \\n #Color\\n if len(np.shape(image)) == 3:\\n #Set up original RGB values\\n R = np.array(image[:,:,0])\\n G = np.array(image[:,:,1])\\n B = np.array(image[:,:,2])\\n \\n R, errR = svd_approx(R,s)\\n G, errG = svd_approx(G,s)\\n B, errB = svd_approx(B,s)\\n imageF = np.dstack((R,G,B))\\n err = errR + errG + errB\\n toShow.imshow(imageF)\\n toShow.set_title(\\\"New \\\" + str(err) + \\\", so \\\" + str((image.size-err)) + \\\" \\\\\\\"saved\\\\\\\"\\\")\\n toShow.axis(\\\"off\\\")\\n \\n toShow = plt.subplot(122)\\n toShow.set_title(\\\"Original \\\" + str(image.size))\\n toShow = plt.imshow(image)\\n #Gray\\n else:\\n imageF, err = svd_approx(image, s)\\n# print(np.shape(imageF))\\n toShow.imshow(imageF, cmap = \\\"gray\\\")\\n toShow.set_title(\\\"New \\\" + str(err) + \\\", so \\\" + str((image.size-err)) + \\\" \\\\\\\"saved\\\\\\\"\\\")\\n toShow.axis(\\\"off\\\")\\n toShow = plt.subplot(122)\\n toShow.set_title(\\\"Original \\\" + str(image.size))\\n toShow = plt.imshow(image, cmap = \\\"gray\\\")\\n \\n plt.suptitle(\\\"MY PLOTS: \\\" + str((image.size-err)) + \\\" \\\\\\\"saved\\\\\\\" :p\\\")\\n \\n return\\n raise NotImplementedError(\\\"Problem 5 Incomplete\\\")\",\n \"def scale(self, scale):\\n \\n scale_matrix = wf.scaleMatrix(scale, self.width/2, self.height/2, 0)\\n self.transform(scale_matrix)\",\n \"def resize_preserving_aspect_then_crop(self, image, new_shape):\\n orig_shape = image.shape\\n orig_height = orig_shape[0]\\n orig_width = orig_shape[1]\\n orig_chans = orig_shape[2]\\n if orig_height > orig_width:\\n scale = new_shape[0]/orig_width\\n else:\\n scale = new_shape[1]/orig_height\\n new_height = int(orig_height * scale)\\n new_width = int(orig_width * scale)\\n # resize preserving aspect ratio\\n image = transform.resize(image, [new_height, new_width, orig_chans], anti_aliasing=True,\\n mode=\\\"reflect\\\")\\n # crop to square\\n image = self.crop_to_size(image, new_shape)\\n # in case original image dim was less than new dim, expand\\n image = transform.resize(image, new_shape, anti_aliasing=True,\\n mode=\\\"reflect\\\")\\n return image\",\n \"def rescale_image(self, img_file, new_width, new_height, model_path, file_description):\\n cwd = os.getcwd()\\n self.new_width = new_width\\n self.new_height = new_height\\n self.extract_file_name(img_file)\\n shutil.copy(img_file, os.path.join('utils_dfn/temp', self.file_name_with_ext))\\n self.run_padding()\\n self.run_dfn(model_path)\\n self.restore_to_correct_size(file_description)\\n clean()\",\n \"def resize_img(input_img, scale=1.1):\\n if scale == 1.0:\\n return input_img\\n rows, cols, ch = input_img.shape\\n d = rows * (scale - 1) # overall image size change from rows, cols, to rows - 2d, cols - 2d\\n pts1 = np.float32([[d, d], [rows - 1 - d, d], [d, cols - 1 - d], [rows - 1 - d, cols - 1 - d]])\\n pts2 = np.float32([[0, 0], [rows - 1, 0], [0, cols - 1], [rows - 1, cols - 1]])\\n M = cv2.getPerspectiveTransform(pts1, pts2)\\n dst = cv2.warpPerspective(input_img, M, (cols, rows), borderMode=1)\\n return dst\",\n \"def save_normalized_image(path, data):\\n image_parser = ImageFile.Parser()\\n try:\\n image_parser.feed(data)\\n image = image_parser.close()\\n except IOError:\\n return False\\n image.thumbnail(MAX_IMAGE_SIZE, Image.ANTIALIAS)\\n if image.mode != 'RGB':\\n image = image.convert('RGB')\\n image.save(path)\\n return True\",\n \"def ConvertToScaledBitmap(self, size, window=None):\\n size = wx.Size(*size)\\n if window:\\n size.width = int(size.width * window.GetContentScaleFactor())\\n size.height = int(size.height * window.GetContentScaleFactor())\\n\\n # We can only have one overall scale factor for both dimensions with\\n # this rasterization method, so chose either the minimum of width or\\n # height to help ensure it fits both ways within the specified size.\\n sx = size.width / self.width\\n sy = size.height / self.height\\n scale = min(sx, sy)\\n return self.ConvertToBitmap(scale=scale, width=size.width, height=size.height)\",\n \"def set_scales(self):\\r\\n self.canvas.update()\\r\\n self.dxmin = self.dmargin\\r\\n self.dymin = self.dmargin\\r\\n self.dxmax = self.canvas.winfo_width() - self.dmargin - 1\\r\\n self.dymax = self.canvas.winfo_height() - self.dmargin - 1\\r\\n\\r\\n # Flip the Y coordinates to invert the result.\\r\\n if self.y_is_flipped:\\r\\n self.dymin, self.dymax = self.dymax, self.dymin\\r\\n\\r\\n self.xscale = (self.dxmax - self.dxmin) / (self.wxmax - self.wxmin)\\r\\n self.yscale = (self.dymax - self.dymin) / (self.wymax - self.wymin)\\r\\n\\r\\n # Calculate 1 pixel in world coordinates.\\r\\n self.xpix = 1 / self.xscale\\r\\n self.ypix = 1 / self.yscale\",\n \"def save_to_image_file(self, filename, image_format='png', scale_x=1, scale_y=1):\\n\\n self.save_barcode_to_pillow(scale_x=scale_x, scale_y=scale_y).save(filename,\\n format=image_format)\",\n \"def save_image(image, figsize, save_path, ticks=False, grey=True):\\n fig = plt.figure(figsize=figsize)\\n if grey:\\n plt.imshow(image, cmap=plt.get_cmap('gray'))\\n else:\\n plt.imshow(image)\\n if not ticks:\\n plt.xticks([]), plt.yticks([])\\n plt.tight_layout()\\n fig.savefig(save_path)\\n plt.close(fig)\\n return\",\n \"def downscale_image(img, bottom, x, y):\\n width, height = tuple(img.shape[1::-1])\\n img = img[int(round((1 - bottom) * (height - 1))):(height - 1), 1:(width - 1)]\\n img = cv2.resize(img, (x, y))\\n #img = cv2.Canny(img, 100, 200)\\n ret, img = cv2.threshold(img, img.mean(), 255, cv2.THRESH_BINARY)\\n return img\",\n \"def save_image(self):\\r\\n filename = filedialog.asksaveasfilename(title='Save Image As...',\\r\\n filetypes=((\\\"Portable Network Graphics (.png)\\\", \\\"*.png\\\"), (\\\"Portable Document Format(.pdf)\\\", \\\"*.pdf\\\")))\\r\\n self.graph.savefig(filename, dpi=self.graph.dpi)\",\n \"def cb_save(event):\\n fig.savefig('sample.univariate_discrete.py.png', dpi=300, format='png', transparent=True)\",\n \"def scale_invert(self):\",\n \"def save_image(self):\\n self.save()\",\n \"def _point_scale2img(points, _H, _W):\\n # with tf.variable_scope(\\\"_point_scale2img\\\", reuse=False):\\n points = points * tf.constant([_H - 1, _W - 1], \\\"float32\\\")\\n return points\",\n \"def imsave(file_name, img):\\n assert(type(img) == torch.FloatTensor,\\n 'img must be a torch.FloatTensor')\\n ndim = len(img.size())\\n assert(ndim == 2 or ndim == 3,\\n 'img must be a 2 or 3 dimensional tensor')\\n\\n img = img.numpy()\\n\\n if ndim == 3:\\n plt.imsave(file_name, np.transpose(img, (1, 2, 0)))\\n else:\\n plt.imsave(file_name, img, cmap='gray')\",\n \"def save_plot_as_image(self):\\r\\n plt.savefig(ROOT_DIR + '/presentation/images/' + self.folder + '/' + self.generated_image_name + '.png',\\r\\n bbox_inches='tight')\",\n \"def scale_img(img):\\r\\n # Scale values of img between 0 and 255.\\r\\n img -= np.amin(img)\\r\\n img /= np.amax(img)\\r\\n img *= 255\\r\\n return img\",\n \"def test_scale_image_gray_identity(self):\\n scaled = scale_image(self.gray_image, 1)\\n self.assertEqual(self.gray_image.shape, scaled.shape)\",\n \"def convert(fn):\\n assert fn[-4:] == \\\".npy\\\", \\\"%s: File extension should match '.npy'\\\" % fn\\n\\n print \\\"Converting file '%s' to .png\\\" % fn\\n numpy_img = np.load(fn)\\n\\n #Rescale to 0-255 and convert to uint8\\n rescaled = (255.0 / numpy_img.max() * (numpy_img - numpy_img.min())).astype(np.uint8)\\n\\n im = Image.fromarray(rescaled)\\n im.save(fn[:-4] + \\\".png\\\")\",\n \"def scale(self,id,x,y,s):\\n if id not in self.elements.keys():\\n print(\\\"Id input not registered! Please check your process\\\")\\n return False\\n element=self.elements[id]\\n state=element.scale(self.h-1-y,x,s,self.w,self.h)\\n if state==True:\\n self.canvas=np.ones((self.h,self.w,3),dtype=np.uint8)*255\\n self.sync=False\\n return state\",\n \"def save_image(path, image, cmap='gist_earth_r'):\\n n_cols = n_rows = 1\\n n_pixels = 256\\n dpi_of_monitor = 96 # HARDCODED DPI VALUE FROM MY OLD DELL LAPTOP...\\n figsize = (n_pixels * n_cols / dpi_of_monitor,\\n n_pixels * n_rows / dpi_of_monitor)\\n f, ax = plt.subplots(n_rows, n_cols, figsize=figsize)\\n f.subplots_adjust(wspace=0, hspace=0, left=0, right=1, bottom=0, top=1)\\n ax.axis('off')\\n ax.imshow(image, cmap=cmap, vmin=0, vmax=None)\\n f.savefig(path, dpi=dpi_of_monitor)\\n plt.close(f)\",\n \"def scale(self, scale=1):\\n self.x *= scale\\n self.y *= scale\\n self.width *= scale\\n self.height *= scale\\n\\n # Always update the corners after operation\\n self.update_corners()\\n return\",\n \"def _rescale(x, xlim, ylim):\\n m = (ylim[1] - ylim[0]) / (xlim[1] - xlim[0])\\n c = ylim[1] - m * xlim[1]\\n y = m * x + c\\n return y\",\n \"def autoscale(self, img: Image, max_height: int, max_width: int):\\n height = img.bgr.shape[0]\\n width = img.bgr.shape[1]\\n\\n diff_height = max_height / height\\n diff_width = max_width / width\\n\\n diff = min(diff_height, diff_width)\\n\\n height = int(height * diff)\\n width = int(width * diff)\\n\\n return img.rescale_image(height, width)\",\n \"def scaleImageToEqualSize(sourceImg, targetImg):\\n return cv2.resize(sourceImg,\\n None, # no specific out dim\\n fx=targetImg.shape[1] / sourceImg.shape[1], # scale factor Y\\n fy=targetImg.shape[0] / sourceImg.shape[0], # scale factor X\\n interpolation=cv2.INTER_AREA)\",\n \"def save(self, filename):\\n self.image.save(filename, self.options.img_format)\",\n \"def downsample_image(img, output_path, ratio=2):\\n assert ratio>=1, ratio\\n if ratio == 1:\\n return True\\n old_im = Image.open(img)\\n old_size = old_im.size\\n new_size = (int(old_size[0]/ratio), int(old_size[1]/ratio))\\n\\n new_im = old_im.resize(new_size, PIL.Image.LANCZOS)\\n new_im.save(output_path)\\n return True\",\n \"def make_square_axes(ax):\\n ax.set_aspect(1 / ax.get_data_ratio())\",\n \"def numpyEnlarge(self,img,scale):\\n if scale==1:\\n # don't need alpha on output\\n self.frameBuffer=img[:ALPHA]\\n return\\n if scale<1:\\n raise InvalidScale(\\\"numpyEnlarge can only be used to enlarge. Got scale factor \\\"+str(scale))\\n\\n h,w=img.shape[:2]\\n for x in xrange(w):\\n for y in xrange(h):\\n pixel = img[y, x]\\n y1=y*scale\\n y2=y1+scale\\n x1=x*scale\\n x2=x1+scale\\n self.frameBuffer[y1:y2, x1:x2] = pixel[:ALPHA]\",\n \"def save_image(lt_image, out_dir, filename, max_width=None):\\n if not lt_image.stream:\\n return\\n\\n filedata = lt_image.stream.get_data()\\n out_file_name = join(out_dir, filename)\\n\\n bits_per_component = lt_image.stream.attrs['BitsPerComponent']\\n if bits_per_component == 8:\\n # カラーとグレー画像はそのまま保存\\n with open(out_file_name, 'wb') as fp:\\n fp.write(filedata)\\n elif bits_per_component == 1:\\n # モノクロ画像はfiledataから作成\\n w, h = lt_image.stream.attrs['Width'], lt_image.stream.attrs['Height']\\n img = Image.frombytes('1', (w, h), filedata)\\n # グレー化、リサイズ、invertを行って保存\\n img = img.convert('L').resize((w // 2, h // 2), Image.ANTIALIAS)\\n img = ImageOps.invert(img)\\n img.save(out_file_name)\\n\\n if max_width:\\n print('max_width:', max_width)\\n img = Image.open(out_file_name)\\n w, h = img.size[:2]\\n img_resize = img.resize((max_width, h * max_width // w), Image.ANTIALIAS)\\n img_resize.save(out_file_name)\",\n \"def save(self):\\n img = Image.new(\\\"1\\\", (self.container.width, self.container.height))\\n draw = ImageDraw.Draw(img)\\n for item in self.items:\\n draw.ellipse(item.box_coordinates(), fill=1)\\n del draw\\n img.save(\\\"plot.bmp\\\", \\\"bmp\\\")\",\n \"def zoom(cls, img, zoom):\\n w, h = img.size\\n x = h / 2\\n y = w / 2\\n zoom2 = zoom * 2\\n img = img.crop((x - w / zoom2, y - h / zoom2,\\n x + w / zoom2, y + h / zoom2))\\n return img.resize((w, h), Image.LANCZOS)\",\n \"def compress_image(filename, s):\\r\\n image = imread(filename) / 255\\r\\n size = image.shape\\r\\n orig_entries = image.size\\r\\n #colored\\r\\n if len(size) == 3:\\r\\n #plot original\\r\\n orig = plt.subplot(121)\\r\\n orig.imshow(image)\\r\\n orig.axis(\\\"off\\\")\\r\\n #red in image\\r\\n R = image[:,:,0]\\r\\n #green in image\\r\\n G = image[:,:,1]\\r\\n #blue in image\\r\\n B = image[:,:,2]\\r\\n #approximate red, green and blue in range\\r\\n new_R, entries_R = svd_approx(R,s)\\r\\n new_R = np.clip(new_R,0,1)\\r\\n new_G, entries_G = svd_approx(G,s)\\r\\n new_G = np.clip(new_G,0,1)\\r\\n new_B, entries_B = svd_approx(B,s)\\r\\n new_B = np.clip(new_B,0,1)\\r\\n #stack all in one array\\r\\n new_image = np.dstack((new_R,new_G,new_B))\\r\\n #plot image\\r\\n new = plt.subplot(122)\\r\\n new.imshow(new_image)\\r\\n new.axis(\\\"off\\\")\\r\\n #title image with saved number of entries\\r\\n plt.suptitle(str(orig_entries - (entries_R+entries_G+entries_B)) + \\\" Entries\\\")\\r\\n\\r\\n\\r\\n #grayscale\\r\\n else:\\r\\n #plot original\\r\\n orig = plt.subplot(121)\\r\\n orig.imshow(image, cmap=\\\"gray\\\")\\r\\n orig.axis(\\\"off\\\")\\r\\n #approximate the image\\r\\n new_A, entries = svd_approx(image,s)\\r\\n #plot it\\r\\n new = plt.subplot(122)\\r\\n new.imshow(new_A, cmap=\\\"gray\\\")\\r\\n new.axis(\\\"off\\\")\\r\\n #title image with saved number of entries\\r\\n plt.suptitle(str(orig_entries - entries) + \\\" Entries\\\")\\r\\n\\r\\n plt.show()\",\n \"def resize(img):\\n size = (500, 500)\\n img.thumbnail(size)\\n return img\",\n \"def test_scale_image_rgb_identity(self):\\n scaled = scale_image(self.rgb_image, 1)\\n self.assertEqual(self.rgb_image.shape, scaled.shape)\",\n \"def scale_image(img, factor=1):\\n return cv2.resize(img, (int(img.shape[1] * factor), int(img.shape[0] * factor)))\",\n \"def preserveAspectRatio(self):\\n return self._preserve_aspect_ratio\",\n \"def tofits(self, *args, **kwargs):\\n return _image.image_tofits(self, *args, **kwargs)\",\n \"def save_image(image_numpy, image_path, aspect_ratio=1.0, color_map=False):\\n if color_map:\\n import matplotlib.pyplot as plt\\n cm = plt.get_cmap('jet')\\n colored_image = cm(image_numpy[:,:,0])[:,:,:3]\\n# print_numpy(colored_image, val=True, shp=True) # max 1.0 min 0.0 shape (256,256,3)\\n \\n image_pil = Image.fromarray((colored_image*255.).astype(np.uint8))\\n else:\\n# print_numpy(image_numpy, val=True, shp=True)\\n image_pil = Image.fromarray(image_numpy)\\n h, w, _ = image_numpy.shape\\n\\n if aspect_ratio > 1.0:\\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\\n if aspect_ratio < 1.0:\\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\\n image_pil.save(image_path)\",\n \"def save_figure(self, data):\\n\\n\\t\\tsizes = np.shape(data)\\n\\t\\tfig = plt.figure()\\n\\t\\tfig.set_size_inches(1, 1. * sizes[0]/sizes[1], forward = False)\\n\\t\\tax = plt.Axes(fig, [0., 0., 1., 1.])\\n\\t\\tax.set_axis_off()\\n\\t\\tfig.add_axes(ax)\\n\\t\\tax.imshow(data, \\\"gray\\\")\\n\\n\\t\\t#plt.show()\\n\\t\\tself.plotfile = os.path.join('static', 'Figure' + '.png')\\n\\t\\tplt.savefig(self.plotfile, dpi = sizes[1])\",\n \"def save_image(self):\\n self.compressed_image_id = str(uuid.uuid4().hex)\\n plot.imsave(\\n str(\\n self.compressed_image_id + \\\"{}\\\").format(\\n \\\".png\\\"), self.compressed_image)\\n\\n if self.verbose:\\n print(\\n \\\"Compressed image saved at \\\" + (\\n str(self.compressed_image_id + \\\"{}\\\").format(\\\".png\\\")))\",\n \"def get_scaled_image(self, min_width=1024):\\n self.dispersion = self.image.getCalibration().pixelWidth\\n self.offset = self.image.getCalibration().xOrigin\\n binning = 1\\n while binning * min_width < self.image.getWidth():\\n binning *= 2\\n if binning > 1:\\n binning /= 2\\n IJ.run(self.image, 'Select None', '')\\n new_image = self.image.crop()\\n IJ.run(new_image, 'Bin...', 'x=%d y=%d binning=Average' %\\n (binning, binning))\\n self.dispersion *= binning\\n self.offset /= binning\\n self.image = new_image\\n return new_image\",\n \"def adjust(self, image):\\n ...\",\n \"def resize_image(self, width=200):\\n self.new_width = width\\n aspect_ratio = self.original_height/float(self.original_width)\\n self.new_height = int(aspect_ratio * self.new_width)\\n\\n resized_image = self.image.resize((self.new_width, self.new_height), Image.BILINEAR)\\n return resized_image\",\n \"def resize_image(image_path):\\n image = Image.open(image_path)\\n\\n imagefit = ImageOps.fit(image, (612, 612), Image.ANTIALIAS)\\n imagefit.save(image_path, 'JPEG', quality=100)\",\n \"def _save(filename, img):\\n if not os.path.exists(OUTPUT_DIR):\\n os.makedirs(OUTPUT_DIR)\\n # filename = filename+'.png'\\n filename = os.path.join(OUTPUT_DIR, filename)\\n # print(filename, img.shape)\\n cv.imwrite(filename, img)\",\n \"def dat_imshow(x):\\n plt.imshow(x,interpolation='nearest',aspect='auto')\",\n \"def scale_widget_to_image_size(self):\\n if self._image is not None:\\n im = self._image.make_image()\\n self.width = im.shape[1]\\n self.height = im.shape[0]\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7007898","0.69334567","0.6804052","0.6749671","0.6498489","0.64127666","0.63798004","0.6349806","0.6243057","0.62239367","0.61422914","0.6138981","0.61325663","0.61003655","0.61003655","0.6086245","0.60752183","0.6060752","0.6048594","0.60214186","0.60083693","0.5973957","0.596449","0.595399","0.5948689","0.59373","0.5924159","0.5919978","0.591995","0.5874858","0.5871491","0.58676964","0.5818037","0.5800698","0.58000773","0.57730675","0.57662284","0.5758693","0.57552063","0.5748286","0.57431704","0.5723492","0.5715193","0.5693649","0.56925213","0.5690499","0.56900585","0.56828064","0.56826544","0.56618375","0.5661027","0.5643159","0.56382936","0.5631379","0.56266195","0.56251484","0.5618284","0.5616727","0.5615862","0.56025636","0.5589054","0.55810666","0.5577366","0.557699","0.55709493","0.55695796","0.55693513","0.5559391","0.55492556","0.554492","0.5540143","0.5535228","0.552444","0.5523014","0.5519092","0.5516752","0.55159324","0.5511094","0.5501392","0.5500178","0.5499025","0.5498141","0.5495086","0.54828584","0.5472138","0.5465304","0.54612386","0.54603326","0.54587924","0.5444538","0.5440001","0.5435924","0.5424342","0.5420404","0.5418121","0.54093206","0.54090405","0.54088986","0.54069537","0.54063773"],"string":"[\n \"0.7007898\",\n \"0.69334567\",\n \"0.6804052\",\n \"0.6749671\",\n \"0.6498489\",\n \"0.64127666\",\n \"0.63798004\",\n \"0.6349806\",\n \"0.6243057\",\n \"0.62239367\",\n \"0.61422914\",\n \"0.6138981\",\n \"0.61325663\",\n \"0.61003655\",\n \"0.61003655\",\n \"0.6086245\",\n \"0.60752183\",\n \"0.6060752\",\n \"0.6048594\",\n \"0.60214186\",\n \"0.60083693\",\n \"0.5973957\",\n \"0.596449\",\n \"0.595399\",\n \"0.5948689\",\n \"0.59373\",\n \"0.5924159\",\n \"0.5919978\",\n \"0.591995\",\n \"0.5874858\",\n \"0.5871491\",\n \"0.58676964\",\n \"0.5818037\",\n \"0.5800698\",\n \"0.58000773\",\n \"0.57730675\",\n \"0.57662284\",\n \"0.5758693\",\n \"0.57552063\",\n \"0.5748286\",\n \"0.57431704\",\n \"0.5723492\",\n \"0.5715193\",\n \"0.5693649\",\n \"0.56925213\",\n \"0.5690499\",\n \"0.56900585\",\n \"0.56828064\",\n \"0.56826544\",\n \"0.56618375\",\n \"0.5661027\",\n \"0.5643159\",\n \"0.56382936\",\n \"0.5631379\",\n \"0.56266195\",\n \"0.56251484\",\n \"0.5618284\",\n \"0.5616727\",\n \"0.5615862\",\n \"0.56025636\",\n \"0.5589054\",\n \"0.55810666\",\n \"0.5577366\",\n \"0.557699\",\n \"0.55709493\",\n \"0.55695796\",\n \"0.55693513\",\n \"0.5559391\",\n \"0.55492556\",\n \"0.554492\",\n \"0.5540143\",\n \"0.5535228\",\n \"0.552444\",\n \"0.5523014\",\n \"0.5519092\",\n \"0.5516752\",\n \"0.55159324\",\n \"0.5511094\",\n \"0.5501392\",\n \"0.5500178\",\n \"0.5499025\",\n \"0.5498141\",\n \"0.5495086\",\n \"0.54828584\",\n \"0.5472138\",\n \"0.5465304\",\n \"0.54612386\",\n \"0.54603326\",\n \"0.54587924\",\n \"0.5444538\",\n \"0.5440001\",\n \"0.5435924\",\n \"0.5424342\",\n \"0.5420404\",\n \"0.5418121\",\n \"0.54093206\",\n \"0.54090405\",\n \"0.54088986\",\n \"0.54069537\",\n \"0.54063773\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6704548"},"document_rank":{"kind":"string","value":"4"}}},{"rowIdx":88573,"cells":{"query":{"kind":"string","value":"Save a thumbnail of the image, preserves aspect ratio, so longest side will be of size[max(x,y)]"},"document":{"kind":"string","value":"def savethumb(image, fname, outpath, size=(128,128), preserve_name=False):\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"thumbnail_{size[0]}_{size[1]}\")\n else:\n fpath = genSavePath(outpath, fname)\n im = copy(image)\n im.thumbnail(size)\n try:\n im.save(fpath, subsample=\"keep\", qtables=image.quantization, optimize=True)\n\n except IOError as m:\n print( \"Thumbnail({}) image creation failed for: {}. \\nReason:{}\".format(size,fname,m))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def make_thumbnail(filepath):\n img = Image.open(filepath)\n thumb = None\n w, h = img.size\n\n # if it is exactly 128x128, do nothing\n if w == 128 and h == 128:\n return True\n\n # if the width and height are equal, scale down\n if w == h:\n thumb = img.resize((128, 128), Image.BICUBIC)\n thumb.save(filepath)\n return True\n\n # when the image's width is smaller than the height\n if w < h:\n # scale so that the width is 128\n ratio = w / 128.\n w_new, h_new = 128, int(h / ratio)\n thumb = img.resize((w_new, h_new), Image.BICUBIC)\n\n # crop the excess\n top, bottom = 0, 0\n margin = h_new - 128\n top, bottom = margin // 2, 128 + margin // 2\n box = (0, top, 128, bottom)\n cropped = thumb.crop(box)\n cropped.save(filepath)\n return True\n\n # when the image's height is smaller than the width\n if h < w:\n # scale so that the height is 128\n ratio = h / 128.\n w_new, h_new = int(w / ratio), 128\n thumb = img.resize((w_new, h_new), Image.BICUBIC)\n\n # crop the excess\n left, right = 0, 0\n margin = w_new - 128\n left, right = margin // 2, 128 + margin // 2\n box = (left, 0, right, 128)\n cropped = thumb.crop(box)\n cropped.save(filepath)\n return True\n return False","def make_thumbnail(image, size=(100, 100)):\n logging.debug(image)\n\n im = create_colorblind_image(image)\n\n thumb_io = BytesIO() # create a BytesIO object\n\n im.save(thumb_io, 'PNG', quality=85) # save image to BytesIO object\n\n thumbnail = File(thumb_io, name=image.name) # create a django friendly File object\n\n return thumbnail","def resize_image(image, size=(926, 617)):\n\n im = Image.open(image)\n im.convert('RGB')\n im.thumbnail(size)\n thumb_io = BytesIO()\n im.save(thumb_io, 'JPEG', quality=85)\n thumbnail = File(thumb_io, name=image.name)\n return thumbnail","def write_thumbnail(image_name, size):\n # TODO : use something else instead of image.thumbnail\n sizes = {\n 'small' : [30,40],\n 'medium' : [70,70],\n 'large' : [120,120]\n }\n image = Image.open(f'{WRITE_FOLDER}/{USER_NAME}/original/{image_name}')\n image.thumbnail((sizes[size][0], sizes[size][1]))\n image.save(f'{WRITE_FOLDER}/{USER_NAME}/{size}/{image_name}')","def resize(img):\n size = (500, 500)\n img.thumbnail(size)\n return img","def create_thumb(source_fame, target_fame, target_w = 260, target_h=205):\r\n size = target_w, target_h\r\n im = Image.open(source_fame)\r\n width = im.size[0]\r\n height = im.size[1]\r\n newwidth = int(size[0])\r\n newheight = int(height*(newwidth/float(width)))\r\n if newheight > int(size[1]):\r\n newheight = int(size[1])\r\n newwidth = int(width*(newheight/float(height)))\r\n size = newwidth, newheight\r\n # Resize and save the image\r\n im.thumbnail(size, Image.ANTIALIAS)\r\n im.save(target_fame)","def create_thumb(dirpath, imgname):\n with open(join(dirpath, imgname), 'r+b') as f:\n with Image.open(f) as image:\n thumb = resizeimage.resize_width(image, 50)\n thumbpath = join(outdir, thumbdir, imgname)\n print(\"saving thumbnail to\", thumbpath)\n thumb.save(thumbpath, image.format)","def thumbnail(self, fnameIn, fnameOut):\n cmd = \"convert -define jpeg:size=500x150 \"\n cmd += '\"%s\" ' % os.path.join(self.downloadFolder, fnameIn)\n cmd += \"-auto-orient -thumbnail 250x150 \"\n cmd += '\"%s\" ' % os.path.join(self.thumbnailFolder, fnameOut)\n self.log(\"creating thumbnail ...\")\n self.log(cmd)\n process = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE)\n process.wait()","def generate_thumbnail(self, img_path):\n\n thumb_path = self.thumbnail_path(img_path)\n dirpath = os.path.dirname(thumb_path)\n try:\n os.makedirs(dirpath)\n except OSError: # path exists\n pass\n\n cmd = [\n '/usr/local/bin/gm',\n 'convert',\n '-thumbnail', '256x256>',\n '-background', 'transparent',\n '-gravity', 'center',\n '-extent', '256x256',\n img_path, thumb_path\n ]\n\n retcode = subprocess.call(cmd)\n\n if retcode:\n log.error('convert exited with %d : %s', retcode, img_path)\n return False\n\n log.debug('Wrote thumbnail for `%s` to `%s`.', img_path, thumb_path)\n\n return True","def thumbnail_image(filename, size=(64, 64), format='.png'):\n\n try:\n im = Image.open(filename)\n im.thumbnail(size, Image.ANTIALIAS)\n\n basename = os.path.basename(filename)\n thumb_filename = os.path.join('thumbs', f'{basename.rsplit(\".\")[0]}_thumb.png')\n im.save(thumb_filename)\n print('Saved', thumb_filename)\n return True\n\n except Exception as e:\n print('Error converting file', filename)\n raise","def resize_profile_pic(sender, instance, **kwargs):\n profile_pic = instance.profile_picture\n if profile_pic.name != \"default.png\":\n img = Image.open(profile_pic.path)\n if img.height > 300 or img.width > 300:\n output_size = (300, 300)\n img.thumbnail(output_size)\n img.save(profile_pic.path)","def resize_image(filename, out=None, thumbnail=False):\n\n if thumbnail:\n image_size = frappe.db.get_value(\n 'eBay Manager Settings', filters=None,\n fieldname='ebay_thumbnail_size')\n else:\n image_size = frappe.db.get_value(\n 'eBay Manager Settings', filters=None,\n fieldname='ebay_image_size')\n image_size = int(image_size)\n\n if image_size < 1:\n frappe.throw('Invalid image size: ' + str(image_size))\n\n size_string = '{}x{}>'.format(image_size, image_size)\n if out is not None:\n subprocess.call(\n ['convert', '-auto-orient', '-resize', size_string,\n filename, out])\n else:\n subprocess.call(\n ['mogrify', '-auto-orient', '-resize', size_string, filename])","def create_thumbnail(self, target, format=None):","def save_image(lt_image, out_dir, filename, max_width=None):\n if not lt_image.stream:\n return\n\n filedata = lt_image.stream.get_data()\n out_file_name = join(out_dir, filename)\n\n bits_per_component = lt_image.stream.attrs['BitsPerComponent']\n if bits_per_component == 8:\n # カラーとグレー画像はそのまま保存\n with open(out_file_name, 'wb') as fp:\n fp.write(filedata)\n elif bits_per_component == 1:\n # モノクロ画像はfiledataから作成\n w, h = lt_image.stream.attrs['Width'], lt_image.stream.attrs['Height']\n img = Image.frombytes('1', (w, h), filedata)\n # グレー化、リサイズ、invertを行って保存\n img = img.convert('L').resize((w // 2, h // 2), Image.ANTIALIAS)\n img = ImageOps.invert(img)\n img.save(out_file_name)\n\n if max_width:\n print('max_width:', max_width)\n img = Image.open(out_file_name)\n w, h = img.size[:2]\n img_resize = img.resize((max_width, h * max_width // w), Image.ANTIALIAS)\n img_resize.save(out_file_name)","def Save_Image_Crop(img, x, y, width, height, filename = None, path = 'Predictions'):\n img = img[y:y+height, x:x+width,:]\n\n if filename is not None:\n try: \n os.mkdir(path)\n except OSError as error: \n print('') \n fig, ax = plt.subplots(figsize=(18, 20))\n ax.imshow(img)\n plt.tight_layout()\n plt.savefig(path + '/' + filename + '_Crop.png')","def generate_thumbnail(image_data, min_source_height, max_source_height, min_source_width, max_source_width, content_type, width, height, overlay_path, valign, top_crop_pct=None, bottom_crop_pct=None, left_crop_pct=None, right_crop_pct=None, crop_x=None, crop_y=None, post_crop_uniform_scale_pct=None):\n # figure out the width/height of the image from the datastore\n \n# img = images.Image(image_data=image_data)\n# img.crop(left_x=0.25, top_y=0.25, right_x=0.25, bottom_y=0.25)\n# img.resize(width=width, height=height)\n# logging.info('(b) w=%i, h=%i' % (img.width, img.height))\n# output = img.execute_transforms(output_encoding=img.format)\n \n image = images.Image(image_data)\n \n if min_source_height is not None and image.height < min_source_height:\n return None\n if max_source_height is not None and image.height > max_source_height:\n return None\n \n if min_source_width is not None and image.width < min_source_width:\n return None\n if max_source_width is not None and image.width > max_source_width:\n return None\n \n \n if content_type == 'image/png':\n output_encoding = images.PNG\n else:\n output_encoding = images.JPEG\n if crop_x is not None and crop_y is not None and valign is None and top_crop_pct is None and bottom_crop_pct is None and (image.width >= crop_x + width) and (image.height >= crop_y + height):\n fw = float(image.width)\n fh = float(image.height)\n try:\n output = images.crop(image_data, float(crop_x) / fw, float(crop_y) / fh, float(crop_x + width) / fw, float(crop_y + height) / fh, output_encoding=output_encoding)\n except:\n output = image_data\n else:\n if width > image.width and height > image.height:\n output = image_data\n# # this would result in scaling the image UP, that's no good\n# if image.width > image.height:\n# width = image.width\n# else:\n# height = image.height\n# \n# output = images.resize(image_data, width, height, output_encoding)\n else:\n output = rescale(image, width, height, halign='middle', valign=valign, top_crop_pct=top_crop_pct, bottom_crop_pct=bottom_crop_pct, left_crop_pct=left_crop_pct, right_crop_pct=right_crop_pct)\n \n if post_crop_uniform_scale_pct is not None:\n output = images.resize(output, width=int(width * post_crop_uniform_scale_pct), output_encoding=output_encoding)\n \n if overlay_path is not None:\n # read the overlay into memory\n overlay_data = open(overlay_path,'r').read()\n # composite the overlay onto the rescaled output\n if content_type == 'image/png':\n output_encoding = images.PNG\n else:\n output_encoding = images.JPEG\n output = images.composite(\n inputs=[\n (output,0,0,1.0,images.CENTER_CENTER),\n (overlay_data,0,0,1.0,images.CENTER_CENTER),\n ],\n width=width,\n height=height,\n output_encoding=output_encoding\n )\n return output","def generate_thumb(origin, size, fn):\n assert isinstance(size, int), 'Integers are expected'\n img = Image.open(origin)\n path = os.path.dirname(origin)\n\n new_img = img.resize((size, size), Image.ANTIALIAS)\n thumb_path = os.path.join(path, fn)\n new_img.save(thumb_path)\n return thumb_path","def create_thumbnail(image_name):\n try:\n # SMALL\n write_thumbnail(image_name, 'small')\n # MEDIUM\n write_thumbnail(image_name, 'medium')\n # LARGE\n write_thumbnail(image_name, 'large')\n\n except IOError:\n print('create thumbnail error')\n pass","def write_thumbnails(self, appstruct):\n slugser = slugify(appstruct[\"serial\"])\n pdf_filename = \"thumbnails/%s/uploaded.pdf\" % slugser\n top_file = \"thumbnails/%s/top.png\" % slugser\n mos_file = \"thumbnails/%s/mosaic.png\" % slugser\n \n thumg = ThumbnailGenerator(pdf_filename)\n self.save_blob(thumg.top_thumbnail(), top_file)\n self.save_blob(thumg.mosaic_thumbnail(), mos_file)","def thumbnail(self, size, resample=BICUBIC):\r\n # preserve aspect ratio\r\n x, y = self.size\r\n if x > size[0]:\r\n y = int(max(y * size[0] / x, 1))\r\n x = int(size[0])\r\n if y > size[1]:\r\n x = int(max(x * size[1] / y, 1))\r\n y = int(size[1])\r\n size = x, y\r\n if size == self.size:\r\n return\r\n self.draft(None, size)\r\n self._instance = self.resize(size, resample, image=self._instance)\r\n self.readonly = 0\r\n self.pyaccess = None","def thumbnail(im, config):\n\n im.thumbnail(\n (config['width'], config['height']),\n ANTIALIAS,\n )\n\n return im","def resize_image(image, max_dimension):\n max_size = (max_dimension, max_dimension)\n return image.thumbnail(max_size, Image.ANTIALIAS)","def bigThumbnail(self):\n\t\tfileCount = len(self.fileList)\n\t\tthumbSize = (200, 200)\n\t\timgHoriz = int(self.get_screen().get_width() / (thumbSize[1] + 20))\n\t\timgSize = (self.get_screen().get_width(), (thumbSize[1] + 20) * (int(fileCount / imgHoriz) + 2))\n\n\t\tpixbuf = gtk.gdk.Pixbuf(gtk.gdk.COLORSPACE_RGB, True, 8, imgSize[0], imgSize[1])\n\t\tfor file in range(len(self.fileList)):\n\t\t\ttry:\n\t\t\t\ttimg = gtk.gdk.pixbuf_new_from_file(self.fileList[file])\n\t\t\texcept:\n\t\t\t\tprint >> sys.stderr, \"Failed to load image %s\" % self.fileList[file]\n\t\t\t\tcontinue\n\t\t\ttimgSize = [timg.get_width(), timg.get_height()]\n\t\t\tif timgSize[0] > thumbSize[0] or timgSize[1] > thumbSize[1]:\n\t\t\t\tscaleFactor = 1.0 * thumbSize[0] / timgSize[0]\n\t\t\t\tif timgSize[1] * scaleFactor > thumbSize[1]:\n\t\t\t\t\tscaleFactor = 1.0 * thumbSize[1] / timgSize[1]\n\t\t\t\tself.scaleFactor = scaleFactor\n\t\t\t\ttimgSize[0] = int(timgSize[0] * scaleFactor)\n\t\t\t\ttimgSize[1] = int(timgSize[1] * scaleFactor)\n\t\t\t\ttimg = timg.scale_simple(timgSize[0], timgSize[1], gtk.gdk.INTERP_BILINEAR)\n\t\t\tpos = ( (file % imgHoriz) * (thumbSize[0] + 20) + 10 + (thumbSize[0] - timgSize[0]) / 2,\n\t\t\t\tint(file / imgHoriz) * (thumbSize[1] + 20) + 10)\n\n\t\t\tprint \" Rendering thumbnails; %d of %d\\r\" % (file, len(self.fileList)),\n\t\t\tsys.stdout.flush()\n\n\t\t\ttimg.copy_area(0, 0, timgSize[0], timgSize[1], pixbuf, pos[0], pos[1])\n\t\t\tdel timg\n\t\t\tgc.collect()\n\t\tprint\n\t\tself.currentPixbuf = pixbuf\n\t\tself.fileList = [ \"#\" ]\n\t\tself.fileName = \"#\"\n\t\tself.autoScale()\n\t\tself.display()","def save(self):\n im = Image.open(self.picture)\n output = BytesIO()\n im.thumbnail((350, 350))\n im.save(output, format='JPEG', quality=100)\n output.seek(0)\n self.picture = InMemoryUploadedFile(output, 'ImageField', \"%s.jpg\" % self.picture.name.split('.')[0],\n 'image/jpeg', sys.getsizeof(output), None)\n super(Tire, self).save()","def img_resize(infile, size):\n try:\n infile.thumbnail(size, Image.ANTIALIAS)\n except:\n print(\"cannot create thumbnail for '%s'\" % infile)\n return infile","def resize_and_save(local_file,new_file,maxsize=None,maxh=None,maxw=None,crop=None):\n logging.debug(\"maxw = %s, maxsize=%s, crop=%s\" % (maxw,maxsize,crop))\n img = Image.open(local_file)\n width,height = img.size\n width,height = float(width), float(height)\n ratio = float(1)\n if crop is not None:\n size = float(maxsize)\n if width <= height and width > size:\n ratio = size/width\n elif height < width and height > size:\n ratio = size/height\n else: \n ratio = 1 # too small\n elif maxsize:\n size = float(maxsize)\n if width >= height and width > size:\n ratio = size/width\n elif height > width and height > size:\n ratio = size/height\n else: \n ratio = 1 # too small\n elif maxh:\n size = maxh\n if height > size:\n ratio = size/height\n else:\n # too small\n ratio = 1\n elif maxw:\n size = maxw\n if width > size:\n ratio = size/width\n else:\n # too small\n ratio = 1\n else:\n raise Exception(\"must specify max width, OR max size\")\n \n print(\"old: ratio = %s: size(x,y) = %s,%s\" % (ratio,width,height))\n height = int(height*ratio)\n width = int(width*ratio)\n print(\"new ratio = %s: size(x,y) = %s,%s\" % (ratio,width,height))\n img = img.resize((width, height),Image.ANTIALIAS)\n if crop is not None:\n log.debug(\"in crop %s\" % crop)\n crop = int(crop)\n if width > crop:\n amt = int((int(width) - crop)/2)\n img = img.crop((amt,0,amt + crop, crop))\n elif height > crop:\n amt = int((int(height) - crop)/2)\n img = img.crop((0,amt,crop,amt+crop))\n \n log.debug(\"saving new file %s\" % new_file)\n if img.mode != \"RGB\":\n img = img.convert(\"RGB\")\n img.save(new_file)","def image_to_thumbs(img):\r\n\theight, width, channels = img.shape\r\n\tthumbs = {\"original\": img}\r\n\t#sizes = [640, 320, 160]\r\n\tsizes = [200]\r\n\tfor size in sizes:\r\n\t\tif (width >= size):\r\n\t\t\tr = (size + 0.0) / width\r\n\t\t\tmax_size = (size, int(height * r))\r\n\t\t\tthumbs[str(size)] = cv2.resize(img, max_size, interpolation=cv2.INTER_AREA)\r\n\r\n\treturn thumbs","def generate_thumbnail():\n import tempfile\n import glob\n from anima.env import mayaEnv\n m_env = mayaEnv.Maya()\n v = m_env.get_current_version()\n\n if not v:\n return\n\n # do not generate a thumbnail from a Repr\n if '@' in v.take_name:\n return\n\n task = v.task\n project = task.project\n # repo = project.repository\n imf = project.image_format\n width = int(imf.width * 0.5)\n height = int(imf.height * 0.5)\n\n temp_output = tempfile.mktemp()\n\n current_frame = pm.currentTime(q=1)\n output_file = pm.playblast(\n fmt='image',\n startTime=current_frame,\n endTime=current_frame,\n sequenceTime=1,\n forceOverwrite=1,\n filename=temp_output,\n clearCache=1,\n showOrnaments=1,\n percent=100,\n wh=(width, height),\n offScreen=1,\n viewer=0,\n compression='PNG',\n quality=70,\n framePadding=0\n )\n pm.currentTime(current_frame)\n\n output_file = output_file.replace('####', '*')\n found_output_file = glob.glob(output_file)\n if found_output_file:\n output_file = found_output_file[0]\n\n from anima.ui import utils\n utils.upload_thumbnail(task, output_file)\n\n return found_output_file","def generateThumbnail(img):\n\n if not img._thumbfn:\n return\n\n aimgfn = join(opts.root, img._filename)\n if not opts.fast:\n img._size = imageSize(aimgfn)\n\n athumbfn = join(opts.root, img._thumbfn)\n\n if opts.thumb_force:\n if opts.quiet: print \"forced regeneration of '%s'\" % img._thumbfn\n elif not exists(athumbfn):\n if opts.quiet: print \"thumbnail absent '%s'\" % img._thumbfn\n else:\n # Check if thumbsize has changed\n if not opts.fast:\n img._thumbsize = imageSize(athumbfn)\n if not checkThumbSize(img._size, \\\n img._thumbsize, \\\n opts.thumb_size):\n if opts.quiet: print \"thumbnail '%s size has changed\" % img._thumbfn\n try:\n # Clear cache for thumbnail size.\n del imageSizeCache[ athumbfn ]\n except:\n pass\n else:\n# pass\n# if opts.quiet: print \"thumbnail '%s' already generated (size ok)\" \\\n# % img._thumbfn\n return\n else:\n if opts.quiet: print \"thumbnail '%s' already generated\" % img._thumbfn\n return\n\n if opts.no_magick:\n if opts.quiet: print \"ImageMagick tools disabled, can't create thumbnail\"\n return\n\n # create necessary directories\n d = dirname(athumbfn)\n if not exists(d):\n os.makedirs(d)\n\n if opts.pil:\n\n try:\n im = PilImage.open(aimgfn)\n im.thumbnail((opts.thumb_size, opts.thumb_size), config.Thumbnails[\"Interpolation\"])\n im.save(athumbfn)\n\n img._thumbsize = im.size\n except IOError, e:\n raise SystemExit(\\\n \"Error: identifying file '%s'\" % aimgfn + str(e))\n\n else:\n\n cmd = getMagickProg('convert') + ' -border 2x2 '\n # FIXME check if this is a problem if not specified\n #cmd += '-interlace NONE '\n\n cmd += '-geometry %dx%d ' % (opts.thumb_size, opts.thumb_size)\n\n if opts.thumb_quality:\n cmd += '-quality %d ' % opts.thumb_quality\n\n # This doesn't add text into the picture itself, just the comment in\n # the header.\n if opts.copyright:\n cmd += '-comment \\\"%s\\\" ' % opts.copyright\n\n # We use [1] to extract the thumbnail when there is one.\n # It is harmless otherwise.\n subimg = \"\"\n if img._ext.lower() in [ \".jpg\", \".tif\", \".tiff\" ]:\n subimg = \"[1]\"\n\n cmd += '\"%s%s\" \"%s\"' % (aimgfn, subimg, athumbfn)\n\n if opts.quiet: print \"generating thumbnail '%s'\" % img._thumbfn\n\n (chin, chout, cherr) = os.popen3(cmd)\n errs = cherr.readlines()\n chout.close()\n cherr.close()\n if errs:\n print >> sys.stderr, \\\n \"Error: running convert program on %s:\" % aimgfn\n errs = string.join(errs, '\\n')\n print errs\n\n if subimg and \\\n re.compile('Unable to read subimage').search(errs):\n if opts.quiet: print \"retrying without subimage\"\n cmd = string.replace(cmd, subimg, \"\")\n\n (chin, chout, cherr) = os.popen3(cmd)\n errs = cherr.readlines()\n chout.close()\n cherr.close()\n if errs:\n print >> sys.stderr, \\\n \"Error: running convert program on %s:\" % aimgfn\n print string.join(errs, '\\n')\n\n else:\n img._thumbsize = imageSize(athumbfn)","def save(self, *args, **kwargs):\n if not self.pk: # on create\n image = Image.open(self.file)\n image.thumbnail((400, 400), Image.ANTIALIAS)\n\n thumb = io.BytesIO()\n image.save(\n thumb, format=\"jpeg\", quality=80, optimize=True, progressive=True\n )\n self.thumbnail = InMemoryUploadedFile(\n thumb, None, self.file.name, 'image/jpeg', thumb.tell(), None\n )\n\n super(File, self).save(*args, **kwargs)","def thumb_profil(log):\n\tpath = get_plato_path()\n\tfrom PIL import Image\n\tsize = 100,200\n\tim = Image.open('/%s/plato_users/%s/profil_BIG.jpg'%(path,log))\n\tim.thumbnail(size, Image.ANTIALIAS)\n\tim.save('/%s/plato_users/%s/profil.jpg'%(path,log),\"JPEG\")","def thumbnail(self, width, height, path, **kwargs):\n return self.get('fileops/thumbnail', api='CONV', params={\n 'root': self.root,\n 'path': path,\n 'width': width,\n 'height': height,\n }, **kwargs)","def convertImage(self):\n saveAs = config.get(\"saveFormat\")\n saveLocation = config.get(\"saveLocation\")\n image = Image.open(self.folderLocation.text())\n fileName = Path(image.filename).stem\n if saveAs == 'ico':\n size = 256, 256\n destPath = saveLocation+fileName+\".\"+saveAs\n im = Image.open(self.folderLocation.text())\n im.thumbnail(size)\n im.save(destPath, 'jpeg')\n else:\n image.save(saveLocation+fileName+\".\"+saveAs, saveAs)","def save_thumbnail(self, save=True):\n modified = False\n if self.thumbnail:\n self.thumbnail.delete(save=False)\n modified = True\n\n result = self._thumbnail_save()\n if result:\n bytes, extension = result\n filename = '%s.%s' % (uuid.uuid4(), extension)\n self.thumbnail.save(name=filename, content=ContentFile(bytes))\n modified = True\n\n if modified and save:\n self.save()","def downsize_img(img: Image.Image,\n max_width: int,\n max_height: int) -> Tuple[Image.Image, bool]:\n width, height = img.size\n # Assume 0 as current size\n if not max_width:\n max_width = width\n if not max_height:\n max_height = height\n\n if (max_width, max_height) == (width, height): # If no changes, do nothing\n return img, False\n\n img.thumbnail((max_width, max_height), resample=Image.LANCZOS)\n return img, True","def get_thumbnail(img_path):\n thumb = JPEGImage(unicode(img_path)).exif_thumbnail.as_blob()\n if thumb:\n logger.debug(\"Using EXIF thumbnail for {0}\".format(img_path))\n return thumb\n else:\n logger.debug(\"Generating thumbnail for {0}\".format(img_path))\n return scale_image(unicode(img_path), width=160)","def GetThumbnail(self, type, maxsize): # real signature unknown; restored from __doc__\n pass","def save_image(filename, image):\n im = cv2.resize(image, None, fx=SCALE_DOWN, fy=SCALE_DOWN)\n cv2.imwrite(os.path.join(OUT_DIR, filename), im)","def make_thumbnail(self):\n # https://gist.github.com/valberg/2429288\n\n # make sure image data is set\n if not self.image_data:\n return False\n\n if self.proxy_data:\n return True\n\n # Create a resized version of the image\n image = Image.open(self.image_data)\n image.thumbnail(THUMBNAIL_SIZE, Image.BICUBIC)\n\n # Save the thumbnail to in-memory 'file'\n temp_thumb = BytesIO()\n image.save(temp_thumb, 'jpeg')\n temp_thumb.seek(0) # rewinds the file\n\n # Save image to a SimpleUploadFile which can be saved\n # into ImageField\n # TODO figure out how to pass base image's UUID before\n # image is committed to DB\n basename = os.path.basename(self.image_data.name)\n uuidname = os.path.splitext(basename)[0]\n suf = SimpleUploadedFile(uuidname,\n temp_thumb.read(), content_type='image/jpeg')\n thumb_filename = '{}_thumb.jpeg'.format(suf.name)\n\n # set save=False, or else it will infinite loop\n self.proxy_data.save(thumb_filename,\n suf,\n save=False)\n\n # Also store the real dimensions for the Pillow thumbnail\n self.proxy_width, self.proxy_height = image.size\n\n temp_thumb.close()\n\n return True","def image_thumb(www_path:Path, fname, width:int, height:int, itype=\"jpg\", quality:int=50):\n if fname is None:\n return None\n\n shots_path = www_path / 'shots'\n thumb_path = www_path / 'thumb'\n image = shots_path / fname\n if '..' in fname:\n raise ValueError('wat')\n\n try:\n filesize = os.path.getsize(image)\n except FileNotFoundError:\n return\n\n the_string = f'thumb {fname} {width} {height} {filesize}'.encode('utf-8')\n hash_fname = md5(the_string).hexdigest() + '.' + itype\n dest = str(thumb_path / hash_fname)\n\n if not os.path.exists(dest):\n cmd = ['convert', '-quality', '50', str(image), '-resize', f'{width}x{height}', '+profile', '\"*\"', dest]\n subprocess.check_call(cmd)\n\n return f'/thumb/{hash_fname}'","def image_optimize(file, width, height, force=False, resize=False):\n import Image as pil\n \n max_width = width\n max_height = height\n\n img = pil.open(file)\n \n #Fixing problem with gif\n if img.mode != \"RGB\":\n img = img.convert(\"RGB\")\n\n src_width, src_height = img.size\n src_ratio = float(src_width) / float(src_height)\n dst_width, dst_height = max_width, max_height\n dst_ratio = float(dst_width) / float(dst_height)\n \n if not force:\n if src_height > src_width:\n max_width = dst_height\n max_height = dst_width\n img.thumbnail((max_width, max_height), pil.ANTIALIAS)\n else:\n if dst_ratio < src_ratio:\n crop_height = src_height \n crop_width = crop_height * dst_ratio \n x_offset = int((src_width - crop_width)/2) \n y_offset = 0 \n else: \n crop_width = src_width\n crop_height = crop_width / dst_ratio\n x_offset = 0\n y_offset = int((src_height - crop_height)/3)\n img = img.crop((x_offset, y_offset, x_offset+int(crop_width),\n y_offset+int(crop_height)))\n img = img.resize((dst_width, dst_height), pil.ANTIALIAS)\n \n return img","def save_resized_image(image, resolution: float, image_name: str):\n\tfilename: str = join(join(base_directory, str(resolution) + 'x'),\n\t image_name)\n\tprint(image_name)\n\tprint(join(base_directory, str(resolution)))\n\tprint(filename)\n\tcv.imwrite(filename, image)","def exportImg(self):\n if self.superSampling:\n print(\"Exporting with size adjusted\")\n self.img = self.img.resize((int(self.width/2),int(self.height/2)),Image.NEAREST)\n self.img.save(self.fileName,\"PNG\")","def save_image(image_numpy, image_path, aspect_ratio=1.0):\n\n image_pil = Image.fromarray(image_numpy)\n h, w, _ = image_numpy.shape\n\n if aspect_ratio > 1.0:\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\n if aspect_ratio < 1.0:\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\n image_pil.save(image_path)","def save_image(image_numpy, image_path, aspect_ratio=1.0):\n\n image_pil = Image.fromarray(image_numpy)\n h, w, _ = image_numpy.shape\n\n if aspect_ratio > 1.0:\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\n if aspect_ratio < 1.0:\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\n image_pil.save(image_path)","def setThumbnailImage(*args):","def save_image(image_numpy, image_path, aspect_ratio=1.0):\n\n image_pil = Image.fromarray(image_numpy)\n h, w, _ = image_numpy.shape\n\n if aspect_ratio is None:\n pass\n elif aspect_ratio > 1.0:\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\n elif aspect_ratio < 1.0:\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\n image_pil.save(image_path)","def resize_and_crop(img, savePath, size, crop_type='middle'):\n\t# If height is higher we resize vertically, if not we resize horizontally\n\n\t# Get current and desired ratio for the images\n\timg_ratio = img.size[0] / float(img.size[1])\n\tratio = size[0] / float(size[1])\n\tprint \"img_ratio = \" + str(img_ratio) + \". ratio = \" + str(ratio)\n\t#The image is scaled/cropped vertically or horizontally depending on the ratio\n\tif ratio > img_ratio:\n\t\timg = img.resize((size[0], int(round(size[0] * img.size[1] / img.size[0]))),\n\t\t Image.ANTIALIAS)\n\t\t# Crop in the top, middle or bottom\n\t\tif crop_type == 'top':\n\t\t\tbox = (0, 0, img.size[0], size[1])\n\t\telif crop_type == 'middle':\n\t\t\tbox = (0, int(round((img.size[1] - size[1]) / 2)), img.size[0],\n\t\t int(round((img.size[1] + size[1]) / 2)))\n\t\telif crop_type == 'bottom':\n\t\t\tbox = (0, img.size[1] - size[1], img.size[0], img.size[1])\n\t\telse :\n\t\t\traise ValueError('ERROR: invalid value for crop_type')\n\t\tprint \"ratio > img_ratio. Cropping box: \"\n\t\tprint box\n\t\timg = img.crop(box)\n\telif ratio < img_ratio:\n\t\timg = img.resize((int(round(size[1] * img.size[0] / img.size[1])), size[1]),\n\t\t Image.ANTIALIAS)\n\t\t# Crop in the top, middle or bottom\n\t\tif crop_type == 'top':\n\t\t\tbox = (0, 0, size[0], img.size[1])\n\t\telif crop_type == 'middle':\n\t\t\tbox = (int(round((img.size[0] - size[0]) / 2)), 0,\n\t\t int(round((img.size[0] + size[0]) / 2)), img.size[1])\n\t\telif crop_type == 'bottom':\n\t\t\tbox = (img.size[0] - size[0], 0, img.size[0], img.size[1])\n\t\telse :\n\t\t\traise ValueError('ERROR: invalid value for crop_type')\n\n\t\tprint \"ratio < img_ratio. Cropping box: \"\n\t\tprint box\n\t\timg = img.crop(box)\n\telse :\n\t\tprint \"so i guess the ratios are the same?\"\n\t\timg = img.resize((size[0], size[1]),\n\t Image.ANTIALIAS)\n\t # If the scale is the same, we do not need to crop\n\tprint \"Saving thumb to \" + savePath\n\timg.save(savePath, \"JPEG\", quality=thumbCompressQual)","def resize_png(width, height, source, destination):\n\n os.system('convert -resize %sx%s \"%s\" \"%s\"' % (width, height, source, destination))","def save_thumb(metadata_df):\n session = requests.Session()\n session.auth = (PLANET_API_KEY, '')\n auth = session.auth\n \n for index, row in metadata_df.iterrows():\n url = row.thumbnail\n date = row.date\n item_type = row.item_type\n cloud_cover = row.cloud_cover\n id_ = row.id\n sample_id = row.sample_id\n \n thumb_name = f'it{item_type}_cc{cloud_cover}_y{date.year}m{date.month}_{id_}.jpg'\n \n thumb_path = os.path.join(os.getcwd(),'thumbs', \n str(sample_id), \n str(date.year))\n \n Path(thumb_path).mkdir(parents=True, exist_ok=True)\n\n r = requests.get(url, auth=auth, stream=True)\n if r.status_code == 200:\n with open(os.path.join(thumb_path, thumb_name), 'wb') as f:\n r.raw.decode_content = True\n shutil.copyfileobj(r.raw, f)","def test_create_thumbnails(self):\n \n logging.info('create_thumbnail')\n \n for size in self.article.sizes.keys():\n assert not self.article.thumbnail_exists(size)\n\n self.article.image.save('avatar.png', ContentFile(self.image.read()))\n self.article.create_thumbnails()\n \n for size in self.article.sizes.keys():\n assert self.article.thumbnail_exists(size)","def thumbnail(self, options):\n params = {\n 'width': options['width'] if 'width' in options else 50,\n 'height': options['height'] if 'height' in options else 50,\n 'smartCropping': options['smartCropping'] if 'smartCropping' in options else False\n }\n\n return Base._postWithOptions(self, _thumbnailUrl, options, params)","def fileResizeObscure(new_filepath):\n # Resize\n img1 = Image.open(new_filepath)\n img2=image_reduce(img1)\n *** Stopped working here\n newpath=\"toupload\\\\%s\" % new_filepath\n # Block ID\n width=img2.size[0]\n height=img2.size[1]\n # Obscuring params were decided by trial and error using fraction of width and height\n x1=int(0.16*width)\n x2=int(0.28*width)\n y1=int(0.94*height)\n y2=int(0.98*height) \n # Faster but easier to snoop? should not be since it changes the pixels\n draw = ImageDraw.Draw(img2)\n draw.rectangle([(x1,y1),(x2,y2)],fill=\"white\")\n del draw\n \n img2.save(newpath,optimize=True,quality=95)","def _resize_image(filename, size):\n width, height = 0, 1\n\n try:\n import Image, ImageOps\n except ImportError:\n from PIL import Image, ImageOps\n\n if not size['resample']:\n resample = Image.ANTIALIAS\n\n img = Image.open(filename)\n if (img.size[width] > size['width'] or\n img.size[height] > size['height']):\n\n #If the image is big resize it with the cheapest resize algorithm\n factor = 1\n while (img.size[0] / factor > 2 * size['width'] and\n img.size[1] * 2 / factor > 2 * size['height']):\n factor *= 2\n if factor > 1:\n img.thumbnail((int(img.size[0] / factor),\n int(img.size[1] / factor)), resample=resample)\n\n if size['crop']:\n img = ImageOps.fit(img, (size['width'], size['height']), method=resample)\n else:\n img.thumbnail((size['width'], size['height']), resample=resample)\n\n try:\n img.save(filename, optimize=1)\n except IOError:\n img.save(filename)","def extract_thumbnail(img, joints):\n x_min, y_min = np.min(joints, axis=0)\n x_max, y_max = np.max(joints, axis=0)\n [h, w, _] = img.shape\n\n if x_min > 20:\n x_min -= 20\n if y_min > 20:\n y_min -= 20\n\n if x_max+20 < w:\n x_max += 20\n if y_max+20 < h:\n y_max += 20\n\n return img[y_min:y_max, x_min:x_max, :]","def RescaleScreenShot(bmp, thumbnail_size=200):\r\n\r\n bmpW, bmpH = bmp.GetWidth(), bmp.GetHeight()\r\n img = bmp.ConvertToImage()\r\n\r\n newW, newH = bmpW, bmpH\r\n \r\n if bmpW > bmpH:\r\n if bmpW > thumbnail_size:\r\n ratio = bmpW/float(thumbnail_size)\r\n newW, newH = int(bmpW/ratio), int(bmpH/ratio)\r\n img.Rescale(newW, newH, wx.IMAGE_QUALITY_HIGH)\r\n else:\r\n if bmpH > thumbnail_size:\r\n ratio = bmpH/float(thumbnail_size)\r\n newW, newH = int(bmpW/ratio), int(bmpH/ratio)\r\n img.Rescale(newW, newH, wx.IMAGE_QUALITY_HIGH)\r\n\r\n newBmp = img.ConvertToBitmap()\r\n otherBmp = wx.EmptyBitmap(newW+5, newH+5) \r\n\r\n memDC = wx.MemoryDC()\r\n memDC.SelectObject(otherBmp)\r\n memDC.SetBackground(wx.WHITE_BRUSH)\r\n memDC.Clear()\r\n \r\n memDC.SetPen(wx.TRANSPARENT_PEN)\r\n\r\n pos = 0\r\n for i in xrange(5, 0, -1):\r\n brush = wx.Brush(wx.Colour(50*i, 50*i, 50*i))\r\n memDC.SetBrush(brush)\r\n memDC.DrawRoundedRectangle(0, 0, newW+5-pos, newH+5-pos, 2)\r\n pos += 1\r\n\r\n memDC.DrawBitmap(newBmp, 0, 0, True)\r\n \r\n # Select the Bitmap out of the memory DC by selecting a new\r\n # uninitialized Bitmap\r\n memDC.SelectObject(wx.NullBitmap)\r\n\r\n return otherBmp","def save_image(image, output_path, limits=None):\n\n # Generate a figure with no axes, border, etc.\n fig = plt.figure()\n fig.set_size_inches(1, 1)\n ax = plt.Axes(fig, [0, 0, 1, 1])\n ax.set_axis_off()\n fig.add_axes(ax)\n\n # If the image is complex, warn the user and discard the imaginary part.\n if np.iscomplexobj(image):\n warnings.warn('Image is complex; only saving real part')\n image = np.real(image)\n\n # Plot the image, scaled according to the limits if they are provided.\n if limits is None:\n ax.imshow(image, cmap='gray', aspect='auto', interpolation='none')\n else:\n vmin = limits[0]\n vmax = limits[1]\n ax.imshow(image, cmap='gray', vmin=vmin, vmax=vmax, aspect='auto', interpolation='none')\n\n # Save the figure with a high resolution, and close it.\n plt.savefig(output_path, dpi=800)\n plt.close()","def FlyResize( image, log_mess, nimages, method = Image.ANTIALIAS ):\n oldw, oldh = image.size\n resl = [8, 10, 14, 16, 20, 22, 24, 32, 40, 48, 64, 96, 128, 256]\n \n if oldw > 256 or oldh > 256:\n newsiz = min(resl, key = lambda x:abs(x - max(oldw, oldh)))\n image.thumbnail((newsiz, newsiz), method)\n neww, newh = image.size\n log_mess += ' and new size scaled = %s x %s' %(neww, newh)\n elif nimages > 1:\n log_mess += ' and size = %s x %s' %(oldw, oldh)\n \n return oldw, oldh, image, log_mess","def resize_image(self, im, max_side_len=512):\n h, w, _ = im.shape\n\n resize_w = w\n resize_h = h\n\n # limit the max side\n if max(resize_h, resize_w) > max_side_len:\n ratio = float(max_side_len) / resize_h if resize_h > resize_w else float(max_side_len) / resize_w\n else:\n ratio = 1.\n resize_h = int(resize_h * ratio)\n resize_w = int(resize_w * ratio)\n\n resize_h = resize_h if resize_h % 32 == 0 else (resize_h // 32 - 1) * 32\n resize_w = resize_w if resize_w % 32 == 0 else (resize_w // 32 - 1) * 32\n im = cv2.resize(im, (int(resize_w), int(resize_h)))\n\n ratio_h = resize_h / float(h)\n ratio_w = resize_w / float(w)\n\n return im, (ratio_h, ratio_w)","def resize_img(img, max_side=1000):\n height, width = img.shape\n # if the image is small enough as is, return it unchanged\n if height <= 1000 and width <= 1000:\n return img\n dim = tuple()\n if height > width:\n scale_ratio = max_side / height\n dim = (int(width * scale_ratio), max_side)\n else:\n scale_ratio = max_side / width\n dim = (max_side, int(height * scale_ratio))\n return cv2.resize(img, dim, interpolation=cv2.INTER_AREA)","def generate_thumbnail(progress_controller=None):\n # TODO: For now skip if this is Maya2017\n import pymel\n\n if pymel.versions.current() >= 201700:\n return\n\n # skip this if maya is running in batch mode\n if pm.general.about(batch=1):\n return\n\n from anima.dcc.mayaEnv import auxiliary\n\n auxiliary.generate_thumbnail()","def resize_file_to(self, in_path, out_path, keep_filename=False):\n if keep_filename:\n filename = path.join(out_path, path.basename(in_path))\n else:\n filename = path.join(out_path, self.get_thumbnail_name(in_path))\n out_path = path.dirname(filename)\n if not path.exists(out_path):\n os.makedirs(out_path)\n if not path.exists(filename):\n try:\n image = Image.open(in_path)\n thumbnail = self.resize(image)\n thumbnail.save(filename)\n logger.info(\"Generated Thumbnail {0}\".format(path.basename(filename)))\n except IOError:\n logger.info(\n \"Generating Thumbnail for {0} skipped\".format(\n path.basename(filename)\n )\n )","def get_thumbnail_size(self, thumbnail_name, forced=False):","def resize_image(path, size=256):\n\n _portlate = 0,\n _landscape = 1,\n\n img = Image.open(path)\n if img.mode != 'RGB':\n img = img.convert('RGB')\n w, h = img.size\n if (w == size) and (h == size):\n return img\n shape = _landscape if w > h else _portlate\n shorter_side = w if w < h else h\n longer_side = w if w > h else h\n magnification = size / shorter_side\n longer_side *= magnification\n shorter_side *= magnification\n if shape == _landscape:\n resize = (round(longer_side), round(shorter_side))\n else:\n resize = (round(shorter_side), round(longer_side))\n assert round(shorter_side) == size, \"this function has bugs\"\n scaled_img = img.resize(resize, Image.LANCZOS)\n r_w, r_h = resize\n if (r_h == size) and (r_w == size):\n return scaled_img\n if shape == _landscape:\n left = (r_w - size) // 2\n top = 0\n else:\n left = 0\n top = (r_h - size) // 2\n bottom = top + size\n right = left + size\n box = (left, top, right, bottom)\n cropped_img = scaled_img.crop(box)\n assert (size, size) == cropped_img.size, \\\n \"this function has bugs\"\n return cropped_img","def _image_resize_keep_ratio(self, image, max_w, max_h, crop=False):\n raise NotImplementedError","def image_preview(img_path):\r\n img = Image.open(img_path)\r\n t_size = 256, 256\r\n\r\n try:\r\n if \"exif\" in img.info:\r\n exif_dict = piexif.load(img.info[\"exif\"])\r\n if piexif.ImageIFD.Orientation in exif_dict[\"0th\"]:\r\n orientation = exif_dict[\"0th\"].pop(piexif.ImageIFD.Orientation)\r\n #exif_bytes = piexif.dump(exif_dict)\r\n if orientation == 2:\r\n img = img.transpose(Image.FLIP_LEFT_RIGHT)\r\n elif orientation == 3:\r\n img = img.rotate(180)\r\n elif orientation == 4:\r\n img = img.rotate(180).transpose(Image.FLIP_LEFT_RIGHT)\r\n elif orientation == 5:\r\n img = img.rotate(-90, expand=True).transpose(Image.FLIP_LEFT_RIGHT)\r\n elif orientation == 6:\r\n img = img.rotate(-90, expand=True)\r\n elif orientation == 7:\r\n img = img.rotate(90, expand=True).transpose(Image.FLIP_LEFT_RIGHT)\r\n elif orientation == 8:\r\n img = img.rotate(90, expand=True)\r\n except:\r\n print('exif data problem in', img_path)\r\n\r\n new_image = Image.new(img.mode, t_size, color=(255,255,255))\r\n img.thumbnail(t_size, Image.ANTIALIAS) # in-place\r\n x_offset= (new_image.size[0] - img.size[0]) // 2\r\n y_offset= (new_image.size[1] - img.size[1]) // 2\r\n new_image.paste(img, (x_offset, y_offset))\r\n img = new_image\r\n\r\n # in memory image -> bytes -> base64_string\r\n buffered = BytesIO()\r\n img.save(buffered, format=\"JPEG\")\r\n img_preview = base64.b64encode(buffered.getvalue()).decode('utf-8')\r\n\r\n return img_preview","def get_thumbnail(format):","def get_thumbnail_size(context, image):\n if not image or not context['CONFIG']['THUMBNAIL_ENABLED']:\n return False\n if context['CONFIG']['THUMBNAIL_PRESERVE_RATIO']:\n if image.height > image.width:\n ret = '0x%s' % context['CONFIG']['THUMBNAIL_MAX_HEIGHT']\n else:\n ret = '%sx0' % context['CONFIG']['THUMBNAIL_MAX_WIDTH']\n else:\n ret = '%sx%s' % (\n context['CONFIG']['THUMBNAIL_MAX_WIDTH'],\n context['CONFIG']['THUMBNAIL_MAX_HEIGHT']\n )\n return ret","def resize(img, size):\n img = cv2.resize(img, tuple(size[::-1]))\n return img","def calc_thumbnail_size(img):\n width, length = img.size\n ratio = width / length\n\n # for some reason, if it's exactly 224, then thumnailed image is 223\n dim = 224 + 1 # output dim\n if ratio > 1:\n size = (dim * ratio, dim)\n else:\n size = (dim, dim / ratio)\n# print(size)\n return size","def resize(fname, width, height):\n image = cv2.imread(fname) # read priginal image\n cv2.imshow('Original Image', image) # show original image\n cv2.waitKey(0) # stop\n\n org_height, org_width = image.shape[0:2] # original width and height\n\n # print width and height\n print(\"width\", org_width)\n print(\"height\", org_height)\n\n # check image height and width and resize to new size\n if org_width >= org_height:\n new_image = cv2.resize(image, (width, height))\n else:\n new_image = cv2.resize(image, (height, width))\n\n return fname, new_image","def compress_image(image: BinaryIO, size: Tuple[int, int] = (512, 512)) -> File:\n im = Image.open(image)\n im_format = im.format\n im.thumbnail(size)\n if im.mode in (\"P\", \"RGBA\"):\n im = im.quantize()\n im_io = BytesIO()\n im.save(im_io, im_format)\n return File(im_io, image.name)","def generate_thumb_filename(instance, filename):\n return _generate_filename(instance, filename, 'thumbs')","def _take_snapshot(self, filename, frame):\n thumbnail_key = os.path.join(self._obj_key_prefix, \"{}.jpg\"\n .format(filename))\n drawn_image = im.draw_region(frame.image,\n self._detector.roi,\n EVENT_ALERT_COLOR_CODE,\n 0.4)\n shrunk_image = im.shrink_image(drawn_image)\n self._obj_store.save_image_obj(thumbnail_key, shrunk_image)\n return thumbnail_key","def _image_resize_keep_ratio(self, image, max_w, max_h, crop=False):\n if crop:\n width, height = sizing.new_size_keep_aspect_ratio(image.size, (max_w, max_h), 'outer')\n image = image.resize((width, height), Image.ANTIALIAS)\n image = image.crop(sizing.new_size_by_croping(image.size, (max_w, max_h)))\n else:\n width, height = sizing.new_size_keep_aspect_ratio(image.size, (max_w, max_h), 'inner')\n image = image.resize((width, height), Image.ANTIALIAS)\n return image, image.size[0], image.size[1]","def generate(self, save=True):\n stretched_photo, crop_box = self._generate_img()\n\n # set crop_box to (0,0,0,0) if photo not cropped\n if not crop_box:\n crop_box = 0, 0, 0, 0\n\n self.crop_left, self.crop_top, right, bottom = crop_box\n self.crop_width = right - self.crop_left\n self.crop_height = bottom - self.crop_top\n\n self.width, self.height = stretched_photo.size\n\n f = BytesIO()\n imgf = (self.photo._get_image().format or\n Image.EXTENSION[path.splitext(self.photo.image.name)[1]])\n\n stretched_photo.save(f, format=imgf, quality=self.format.resample_quality)\n f.seek(0)\n\n self.image.save(self.file(), ContentFile(f.read()), save)","def mosaic_thumbnail(self):\n serial = slugify(self.request.matchdict[\"serial\"])\n filename = \"thumbnails/%s/mosaic.png\" % serial\n return FileResponse(filename)","async def resize_photo(photo):\n image = Image.open(photo)\n maxsize = (512, 512)\n if (image.width and image.height) < 512:\n size1 = image.width\n size2 = image.height\n if image.width > image.height:\n scale = 512 / size1\n size1new = 512\n size2new = size2 * scale\n else:\n scale = 512 / size2\n size1new = size1 * scale\n size2new = 512\n size1new = math.floor(size1new)\n size2new = math.floor(size2new)\n sizenew = (size1new, size2new)\n image = image.resize(sizenew)\n else:\n image.thumbnail(maxsize)\n\n return image","def save_image(path, image): \n if len(image.shape) == 4:\n image = image.reshape((image.shape[1], image.shape[2], image.shape[3]))\n image = np.clip(image * 255.0, 0, 255).astype(np.uint8)\n skimage.io.imsave(path, image)","def save_image(image, figsize, save_path, ticks=False, grey=True):\n fig = plt.figure(figsize=figsize)\n if grey:\n plt.imshow(image, cmap=plt.get_cmap('gray'))\n else:\n plt.imshow(image)\n if not ticks:\n plt.xticks([]), plt.yticks([])\n plt.tight_layout()\n fig.savefig(save_path)\n plt.close(fig)\n return","def thumbnail(self, item):\n if self._has_image_field(item) and self._field_is_visible('image'):\n tile_conf = self.get_tile_configuration()\n image_conf = tile_conf.get('image', None)\n if image_conf:\n scaleconf = image_conf['imgsize']\n # Scale string is something like: 'mini 200:200'.\n # We need the name only: 'mini'.\n scale = scaleconf.split(' ')[0]\n scales = ploneapi.content.get(path='@@images')\n return scales.scale('image', scale)","def get_thumbnail_url():","def img_url_thumbnail(self):\n url = '%s=s%s-c' % (self.img_url, self.THUMBNAIL_SIZE_PX)\n if self.img_rot in Plaque.ALLOWED_ROTATIONS:\n url = \"%s-r%s\" % (url, self.img_rot)\n return url","def plot_thumb(self, data_fname):\n thumbnail = self.controller.plot_thumb(data_fname, self.bitmap_width, self.bitmap_height)\n if thumbnail is not None:\n self.figure_bmp.SetBitmap(thumbnail)\n else:\n self.plot_blank()","def resize_image(first_image, width, height):\n resizing_image = Image()\n temp_image = ((Pil_image.open(first_image.picture)).convert(\"RGB\")).resize((width, height), Pil_image.ANTIALIAS)\n filestream = BytesIO()\n temp_image.save(filestream, 'JPEG', quality=90)\n filestream.seek(0)\n name = f\"{str(first_image.picture).split('.')[0]}_{width}_{height}.{str(first_image.picture).split('.')[1]}\"\n image = InMemoryUploadedFile(filestream, 'picture', name, 'jpeg/image', sys.getsizeof(filestream), None)\n resizing_image.url = first_image.url\n resizing_image.width = width\n resizing_image.height = height\n resizing_image.parent = first_image.id\n resizing_image.picture = image\n resizing_image.save()\n return resizing_image","def createThumbnail(self, useCursorPosition=False, dbPath = None, versionInt = None):\n\n return \"\"\n # logger.debug(\"Func: createThumbnail\")\n # projectPath = self.projectDir\n # if useCursorPosition:\n # versionInt = self.currentVersionIndex\n # dbPath = self.currentDatabasePath\n # else:\n # if not dbPath or not versionInt:\n # msg = \"Both dbPath and version must be defined if useCursorPosition=False\"\n # raise Exception ([360, msg])\n #\n # versionStr = \"v%s\" % (str(versionInt).zfill(3))\n # dbDir, shotNameWithExt = os.path.split(dbPath)\n # shotName = os.path.splitext(shotNameWithExt)[0]\n #\n # thumbPath = \"{0}_{1}_thumb.jpg\".format(os.path.join(dbDir, shotName), versionStr)\n # relThumbPath = os.path.relpath(thumbPath, projectPath)\n #\n # # create a thumbnail using playblast\n # thumbDir = os.path.split(thumbPath)[0]\n # if os.path.exists(thumbDir):\n # # frame = pm.currentTime(query=True)\n # frame = cmds.currentTime(query=True)\n # # store = pm.getAttr(\"defaultRenderGlobals.imageFormat\")\n # store = cmds.getAttr(\"defaultRenderGlobals.imageFormat\")\n # # pm.setAttr(\"defaultRenderGlobals.imageFormat\", 8) # This is the value for jpeg\n # cmds.setAttr(\"defaultRenderGlobals.imageFormat\", 8) # This is the value for jpeg\n # # pm.playblast(completeFilename=thumbPath, forceOverwrite=True, format='image', width=221, height=124, showOrnaments=False, frame=[frame], viewer=False, percent=100)\n # cmds.playblast(completeFilename=thumbPath, forceOverwrite=True, format='image', width=221, height=124, showOrnaments=False, frame=[frame], viewer=False, percent=100)\n # # pm.setAttr(\"defaultRenderGlobals.imageFormat\", store) #take it back\n # cmds.setAttr(\"defaultRenderGlobals.imageFormat\", store) #take it back\n # else:\n # # pm.warning(\"something went wrong with thumbnail. Skipping thumbnail\")\n # cmds.warning(\"something went wrong with thumbnail. Skipping thumbnail\")\n # return \"\"\n # # return thumbPath\n # return relThumbPath","def thumbnail(self, item):\n if self._has_image_field(item) and self._field_is_visible(\"image\"):\n tile_conf = self.get_tile_configuration()\n image_conf = tile_conf.get(\"image\", None)\n if image_conf:\n scaleconf = image_conf[\"imgsize\"]\n # scale string is something like: 'mini 200:200' and\n # we need the name only: 'mini'\n if scaleconf == \"_original\":\n scale = None\n else:\n scale = scaleconf.split(\" \")[0]\n scales = item.restrictedTraverse(\"@@images\")\n return scales.scale(\"image\", scale)","def _create_placeholder(self, thumbnail_size):\n logger.debug(\"Creating placeholder. thumbnail_size: %s\", thumbnail_size)\n placeholder = Image.new(\"RGB\", (thumbnail_size, thumbnail_size))\n draw = ImageDraw.Draw(placeholder)\n draw.rectangle(((0, 0), (thumbnail_size, thumbnail_size)), outline=\"#E5E5E5\", width=1)\n placeholder = np.array(placeholder)\n self._previewcache[\"placeholder\"] = placeholder\n logger.debug(\"Created placeholder. shape: %s\", placeholder.shape)","def square_image(img):\r\n x,y = img.size\r\n while y > x:\r\n #slice 10px at a time until square\r\n slice_height = min(y - x, 10)\r\n\r\n bottom = img.crop((0, y - slice_height, x, y))\r\n top = img.crop((0, 0, x, slice_height))\r\n\r\n #remove the slice with the least entropy\r\n if image_entropy(bottom) < image_entropy(top):\r\n img = img.crop((0, 0, x, y - slice_height))\r\n else:\r\n img = img.crop((0, slice_height, x, y))\r\n\r\n x,y = img.size\r\n\r\n return img","def resize_img(self,scale=1):\n reduced = self.image.reduce((scale,scale))\n reduced.save(\"../edited/{}\".format(self.image.filename))\n\n reduced = Image.open(\"../edited/{}\".format(self.image.filename))\n return reduced","def get_thumbnail_magnification(slide):\n ratio = np.asarray(slide.dimensions) / np.asarray(slide.associated_images[\"thumbnail\"].size)\n # np.sqrt(np.prod(ratio))\n return ratio","def get_thumbnail_name(self, thumbnail_name, with_size=None):","def save_original_image(slide, heatmapPath):\n dims = slide.dims\n img = slide.image.read_region((0,0), len(dims)-1, dims[-1])\n img.save(os.path.join(heatmapPath, slide.id) + \".png\")","def get_thumbnail(self, size):\n\n thumb = self.associated_images[b'thumbnail']\n return thumb","def save_tile_img(tif, xyz, dataset, tile_size, region, zone, save_path, display=False):\n \n prefix = f'{region}{zone}{dataset}_'\n x,y,z = xyz\n tile, mask = rt_main.tile(tif, x,y,z, tilesize=tile_size)\n if display: \n plt.imshow(np.moveaxis(tile,0,2))\n plt.show()\n \n skimage.io.imsave(f'{save_path}/{prefix}{z}_{x}_{y}.png',np.moveaxis(tile,0,2), check_contrast=False)","def resize_img(self, filename: str, size: Tuple[int, int] = (299, 299)):\n img = Image.open(join(self.source_dir, filename))\n width, height = img.size\n orig_shape = np.array(img.size)\n wanted_shape = np.array(size)\n ratios = wanted_shape / orig_shape\n wanted_width, wanted_height = size\n ratio_w, ratio_h = wanted_width / width, wanted_height / height\n\n if np.alltrue(ratios > 1):\n # Both sides of the image are shorter than the desired dimension,\n # so take the side that's closer in size and enlarge the image\n # in both directions to make that one fit\n factor = min(ratio_h, ratio_w)\n img = img.resize((int(width * factor), int(height * factor)))\n\n # Now we have an image that's either larger than the desired shape\n # or at least one side matches the desired shape and we can resize\n # with contain\n cover = resizeimage.resize_contain(img, size)\n cover.save(join(self.dest_dir, filename), 'JPEG')","def top_thumbnail(self):\n serial = slugify(self.request.matchdict[\"serial\"])\n filename = \"thumbnails/%s/top.png\" % serial\n return FileResponse(filename)","def save_normalized_image(path, data):\n image_parser = ImageFile.Parser()\n try:\n image_parser.feed(data)\n image = image_parser.close()\n except IOError:\n return False\n image.thumbnail(MAX_IMAGE_SIZE, Image.ANTIALIAS)\n if image.mode != 'RGB':\n image = image.convert('RGB')\n image.save(path)\n return True","def save_image(image, filename, mode='PNG'):\n out = Image.new(mode='L', size=(image['width'], image['height']))\n out.putdata(image['pixels'])\n if isinstance(filename, str):\n out.save(filename)\n else:\n out.save(filename, mode)\n out.close()","def save_image(image, filename, mode='PNG'):\n out = Image.new(mode='L', size=(image['width'], image['height']))\n out.putdata(image['pixels'])\n if isinstance(filename, str):\n out.save(filename)\n else:\n out.save(filename, mode)\n out.close()"],"string":"[\n \"def make_thumbnail(filepath):\\n img = Image.open(filepath)\\n thumb = None\\n w, h = img.size\\n\\n # if it is exactly 128x128, do nothing\\n if w == 128 and h == 128:\\n return True\\n\\n # if the width and height are equal, scale down\\n if w == h:\\n thumb = img.resize((128, 128), Image.BICUBIC)\\n thumb.save(filepath)\\n return True\\n\\n # when the image's width is smaller than the height\\n if w < h:\\n # scale so that the width is 128\\n ratio = w / 128.\\n w_new, h_new = 128, int(h / ratio)\\n thumb = img.resize((w_new, h_new), Image.BICUBIC)\\n\\n # crop the excess\\n top, bottom = 0, 0\\n margin = h_new - 128\\n top, bottom = margin // 2, 128 + margin // 2\\n box = (0, top, 128, bottom)\\n cropped = thumb.crop(box)\\n cropped.save(filepath)\\n return True\\n\\n # when the image's height is smaller than the width\\n if h < w:\\n # scale so that the height is 128\\n ratio = h / 128.\\n w_new, h_new = int(w / ratio), 128\\n thumb = img.resize((w_new, h_new), Image.BICUBIC)\\n\\n # crop the excess\\n left, right = 0, 0\\n margin = w_new - 128\\n left, right = margin // 2, 128 + margin // 2\\n box = (left, 0, right, 128)\\n cropped = thumb.crop(box)\\n cropped.save(filepath)\\n return True\\n return False\",\n \"def make_thumbnail(image, size=(100, 100)):\\n logging.debug(image)\\n\\n im = create_colorblind_image(image)\\n\\n thumb_io = BytesIO() # create a BytesIO object\\n\\n im.save(thumb_io, 'PNG', quality=85) # save image to BytesIO object\\n\\n thumbnail = File(thumb_io, name=image.name) # create a django friendly File object\\n\\n return thumbnail\",\n \"def resize_image(image, size=(926, 617)):\\n\\n im = Image.open(image)\\n im.convert('RGB')\\n im.thumbnail(size)\\n thumb_io = BytesIO()\\n im.save(thumb_io, 'JPEG', quality=85)\\n thumbnail = File(thumb_io, name=image.name)\\n return thumbnail\",\n \"def write_thumbnail(image_name, size):\\n # TODO : use something else instead of image.thumbnail\\n sizes = {\\n 'small' : [30,40],\\n 'medium' : [70,70],\\n 'large' : [120,120]\\n }\\n image = Image.open(f'{WRITE_FOLDER}/{USER_NAME}/original/{image_name}')\\n image.thumbnail((sizes[size][0], sizes[size][1]))\\n image.save(f'{WRITE_FOLDER}/{USER_NAME}/{size}/{image_name}')\",\n \"def resize(img):\\n size = (500, 500)\\n img.thumbnail(size)\\n return img\",\n \"def create_thumb(source_fame, target_fame, target_w = 260, target_h=205):\\r\\n size = target_w, target_h\\r\\n im = Image.open(source_fame)\\r\\n width = im.size[0]\\r\\n height = im.size[1]\\r\\n newwidth = int(size[0])\\r\\n newheight = int(height*(newwidth/float(width)))\\r\\n if newheight > int(size[1]):\\r\\n newheight = int(size[1])\\r\\n newwidth = int(width*(newheight/float(height)))\\r\\n size = newwidth, newheight\\r\\n # Resize and save the image\\r\\n im.thumbnail(size, Image.ANTIALIAS)\\r\\n im.save(target_fame)\",\n \"def create_thumb(dirpath, imgname):\\n with open(join(dirpath, imgname), 'r+b') as f:\\n with Image.open(f) as image:\\n thumb = resizeimage.resize_width(image, 50)\\n thumbpath = join(outdir, thumbdir, imgname)\\n print(\\\"saving thumbnail to\\\", thumbpath)\\n thumb.save(thumbpath, image.format)\",\n \"def thumbnail(self, fnameIn, fnameOut):\\n cmd = \\\"convert -define jpeg:size=500x150 \\\"\\n cmd += '\\\"%s\\\" ' % os.path.join(self.downloadFolder, fnameIn)\\n cmd += \\\"-auto-orient -thumbnail 250x150 \\\"\\n cmd += '\\\"%s\\\" ' % os.path.join(self.thumbnailFolder, fnameOut)\\n self.log(\\\"creating thumbnail ...\\\")\\n self.log(cmd)\\n process = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE)\\n process.wait()\",\n \"def generate_thumbnail(self, img_path):\\n\\n thumb_path = self.thumbnail_path(img_path)\\n dirpath = os.path.dirname(thumb_path)\\n try:\\n os.makedirs(dirpath)\\n except OSError: # path exists\\n pass\\n\\n cmd = [\\n '/usr/local/bin/gm',\\n 'convert',\\n '-thumbnail', '256x256>',\\n '-background', 'transparent',\\n '-gravity', 'center',\\n '-extent', '256x256',\\n img_path, thumb_path\\n ]\\n\\n retcode = subprocess.call(cmd)\\n\\n if retcode:\\n log.error('convert exited with %d : %s', retcode, img_path)\\n return False\\n\\n log.debug('Wrote thumbnail for `%s` to `%s`.', img_path, thumb_path)\\n\\n return True\",\n \"def thumbnail_image(filename, size=(64, 64), format='.png'):\\n\\n try:\\n im = Image.open(filename)\\n im.thumbnail(size, Image.ANTIALIAS)\\n\\n basename = os.path.basename(filename)\\n thumb_filename = os.path.join('thumbs', f'{basename.rsplit(\\\".\\\")[0]}_thumb.png')\\n im.save(thumb_filename)\\n print('Saved', thumb_filename)\\n return True\\n\\n except Exception as e:\\n print('Error converting file', filename)\\n raise\",\n \"def resize_profile_pic(sender, instance, **kwargs):\\n profile_pic = instance.profile_picture\\n if profile_pic.name != \\\"default.png\\\":\\n img = Image.open(profile_pic.path)\\n if img.height > 300 or img.width > 300:\\n output_size = (300, 300)\\n img.thumbnail(output_size)\\n img.save(profile_pic.path)\",\n \"def resize_image(filename, out=None, thumbnail=False):\\n\\n if thumbnail:\\n image_size = frappe.db.get_value(\\n 'eBay Manager Settings', filters=None,\\n fieldname='ebay_thumbnail_size')\\n else:\\n image_size = frappe.db.get_value(\\n 'eBay Manager Settings', filters=None,\\n fieldname='ebay_image_size')\\n image_size = int(image_size)\\n\\n if image_size < 1:\\n frappe.throw('Invalid image size: ' + str(image_size))\\n\\n size_string = '{}x{}>'.format(image_size, image_size)\\n if out is not None:\\n subprocess.call(\\n ['convert', '-auto-orient', '-resize', size_string,\\n filename, out])\\n else:\\n subprocess.call(\\n ['mogrify', '-auto-orient', '-resize', size_string, filename])\",\n \"def create_thumbnail(self, target, format=None):\",\n \"def save_image(lt_image, out_dir, filename, max_width=None):\\n if not lt_image.stream:\\n return\\n\\n filedata = lt_image.stream.get_data()\\n out_file_name = join(out_dir, filename)\\n\\n bits_per_component = lt_image.stream.attrs['BitsPerComponent']\\n if bits_per_component == 8:\\n # カラーとグレー画像はそのまま保存\\n with open(out_file_name, 'wb') as fp:\\n fp.write(filedata)\\n elif bits_per_component == 1:\\n # モノクロ画像はfiledataから作成\\n w, h = lt_image.stream.attrs['Width'], lt_image.stream.attrs['Height']\\n img = Image.frombytes('1', (w, h), filedata)\\n # グレー化、リサイズ、invertを行って保存\\n img = img.convert('L').resize((w // 2, h // 2), Image.ANTIALIAS)\\n img = ImageOps.invert(img)\\n img.save(out_file_name)\\n\\n if max_width:\\n print('max_width:', max_width)\\n img = Image.open(out_file_name)\\n w, h = img.size[:2]\\n img_resize = img.resize((max_width, h * max_width // w), Image.ANTIALIAS)\\n img_resize.save(out_file_name)\",\n \"def Save_Image_Crop(img, x, y, width, height, filename = None, path = 'Predictions'):\\n img = img[y:y+height, x:x+width,:]\\n\\n if filename is not None:\\n try: \\n os.mkdir(path)\\n except OSError as error: \\n print('') \\n fig, ax = plt.subplots(figsize=(18, 20))\\n ax.imshow(img)\\n plt.tight_layout()\\n plt.savefig(path + '/' + filename + '_Crop.png')\",\n \"def generate_thumbnail(image_data, min_source_height, max_source_height, min_source_width, max_source_width, content_type, width, height, overlay_path, valign, top_crop_pct=None, bottom_crop_pct=None, left_crop_pct=None, right_crop_pct=None, crop_x=None, crop_y=None, post_crop_uniform_scale_pct=None):\\n # figure out the width/height of the image from the datastore\\n \\n# img = images.Image(image_data=image_data)\\n# img.crop(left_x=0.25, top_y=0.25, right_x=0.25, bottom_y=0.25)\\n# img.resize(width=width, height=height)\\n# logging.info('(b) w=%i, h=%i' % (img.width, img.height))\\n# output = img.execute_transforms(output_encoding=img.format)\\n \\n image = images.Image(image_data)\\n \\n if min_source_height is not None and image.height < min_source_height:\\n return None\\n if max_source_height is not None and image.height > max_source_height:\\n return None\\n \\n if min_source_width is not None and image.width < min_source_width:\\n return None\\n if max_source_width is not None and image.width > max_source_width:\\n return None\\n \\n \\n if content_type == 'image/png':\\n output_encoding = images.PNG\\n else:\\n output_encoding = images.JPEG\\n if crop_x is not None and crop_y is not None and valign is None and top_crop_pct is None and bottom_crop_pct is None and (image.width >= crop_x + width) and (image.height >= crop_y + height):\\n fw = float(image.width)\\n fh = float(image.height)\\n try:\\n output = images.crop(image_data, float(crop_x) / fw, float(crop_y) / fh, float(crop_x + width) / fw, float(crop_y + height) / fh, output_encoding=output_encoding)\\n except:\\n output = image_data\\n else:\\n if width > image.width and height > image.height:\\n output = image_data\\n# # this would result in scaling the image UP, that's no good\\n# if image.width > image.height:\\n# width = image.width\\n# else:\\n# height = image.height\\n# \\n# output = images.resize(image_data, width, height, output_encoding)\\n else:\\n output = rescale(image, width, height, halign='middle', valign=valign, top_crop_pct=top_crop_pct, bottom_crop_pct=bottom_crop_pct, left_crop_pct=left_crop_pct, right_crop_pct=right_crop_pct)\\n \\n if post_crop_uniform_scale_pct is not None:\\n output = images.resize(output, width=int(width * post_crop_uniform_scale_pct), output_encoding=output_encoding)\\n \\n if overlay_path is not None:\\n # read the overlay into memory\\n overlay_data = open(overlay_path,'r').read()\\n # composite the overlay onto the rescaled output\\n if content_type == 'image/png':\\n output_encoding = images.PNG\\n else:\\n output_encoding = images.JPEG\\n output = images.composite(\\n inputs=[\\n (output,0,0,1.0,images.CENTER_CENTER),\\n (overlay_data,0,0,1.0,images.CENTER_CENTER),\\n ],\\n width=width,\\n height=height,\\n output_encoding=output_encoding\\n )\\n return output\",\n \"def generate_thumb(origin, size, fn):\\n assert isinstance(size, int), 'Integers are expected'\\n img = Image.open(origin)\\n path = os.path.dirname(origin)\\n\\n new_img = img.resize((size, size), Image.ANTIALIAS)\\n thumb_path = os.path.join(path, fn)\\n new_img.save(thumb_path)\\n return thumb_path\",\n \"def create_thumbnail(image_name):\\n try:\\n # SMALL\\n write_thumbnail(image_name, 'small')\\n # MEDIUM\\n write_thumbnail(image_name, 'medium')\\n # LARGE\\n write_thumbnail(image_name, 'large')\\n\\n except IOError:\\n print('create thumbnail error')\\n pass\",\n \"def write_thumbnails(self, appstruct):\\n slugser = slugify(appstruct[\\\"serial\\\"])\\n pdf_filename = \\\"thumbnails/%s/uploaded.pdf\\\" % slugser\\n top_file = \\\"thumbnails/%s/top.png\\\" % slugser\\n mos_file = \\\"thumbnails/%s/mosaic.png\\\" % slugser\\n \\n thumg = ThumbnailGenerator(pdf_filename)\\n self.save_blob(thumg.top_thumbnail(), top_file)\\n self.save_blob(thumg.mosaic_thumbnail(), mos_file)\",\n \"def thumbnail(self, size, resample=BICUBIC):\\r\\n # preserve aspect ratio\\r\\n x, y = self.size\\r\\n if x > size[0]:\\r\\n y = int(max(y * size[0] / x, 1))\\r\\n x = int(size[0])\\r\\n if y > size[1]:\\r\\n x = int(max(x * size[1] / y, 1))\\r\\n y = int(size[1])\\r\\n size = x, y\\r\\n if size == self.size:\\r\\n return\\r\\n self.draft(None, size)\\r\\n self._instance = self.resize(size, resample, image=self._instance)\\r\\n self.readonly = 0\\r\\n self.pyaccess = None\",\n \"def thumbnail(im, config):\\n\\n im.thumbnail(\\n (config['width'], config['height']),\\n ANTIALIAS,\\n )\\n\\n return im\",\n \"def resize_image(image, max_dimension):\\n max_size = (max_dimension, max_dimension)\\n return image.thumbnail(max_size, Image.ANTIALIAS)\",\n \"def bigThumbnail(self):\\n\\t\\tfileCount = len(self.fileList)\\n\\t\\tthumbSize = (200, 200)\\n\\t\\timgHoriz = int(self.get_screen().get_width() / (thumbSize[1] + 20))\\n\\t\\timgSize = (self.get_screen().get_width(), (thumbSize[1] + 20) * (int(fileCount / imgHoriz) + 2))\\n\\n\\t\\tpixbuf = gtk.gdk.Pixbuf(gtk.gdk.COLORSPACE_RGB, True, 8, imgSize[0], imgSize[1])\\n\\t\\tfor file in range(len(self.fileList)):\\n\\t\\t\\ttry:\\n\\t\\t\\t\\ttimg = gtk.gdk.pixbuf_new_from_file(self.fileList[file])\\n\\t\\t\\texcept:\\n\\t\\t\\t\\tprint >> sys.stderr, \\\"Failed to load image %s\\\" % self.fileList[file]\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\ttimgSize = [timg.get_width(), timg.get_height()]\\n\\t\\t\\tif timgSize[0] > thumbSize[0] or timgSize[1] > thumbSize[1]:\\n\\t\\t\\t\\tscaleFactor = 1.0 * thumbSize[0] / timgSize[0]\\n\\t\\t\\t\\tif timgSize[1] * scaleFactor > thumbSize[1]:\\n\\t\\t\\t\\t\\tscaleFactor = 1.0 * thumbSize[1] / timgSize[1]\\n\\t\\t\\t\\tself.scaleFactor = scaleFactor\\n\\t\\t\\t\\ttimgSize[0] = int(timgSize[0] * scaleFactor)\\n\\t\\t\\t\\ttimgSize[1] = int(timgSize[1] * scaleFactor)\\n\\t\\t\\t\\ttimg = timg.scale_simple(timgSize[0], timgSize[1], gtk.gdk.INTERP_BILINEAR)\\n\\t\\t\\tpos = ( (file % imgHoriz) * (thumbSize[0] + 20) + 10 + (thumbSize[0] - timgSize[0]) / 2,\\n\\t\\t\\t\\tint(file / imgHoriz) * (thumbSize[1] + 20) + 10)\\n\\n\\t\\t\\tprint \\\" Rendering thumbnails; %d of %d\\\\r\\\" % (file, len(self.fileList)),\\n\\t\\t\\tsys.stdout.flush()\\n\\n\\t\\t\\ttimg.copy_area(0, 0, timgSize[0], timgSize[1], pixbuf, pos[0], pos[1])\\n\\t\\t\\tdel timg\\n\\t\\t\\tgc.collect()\\n\\t\\tprint\\n\\t\\tself.currentPixbuf = pixbuf\\n\\t\\tself.fileList = [ \\\"#\\\" ]\\n\\t\\tself.fileName = \\\"#\\\"\\n\\t\\tself.autoScale()\\n\\t\\tself.display()\",\n \"def save(self):\\n im = Image.open(self.picture)\\n output = BytesIO()\\n im.thumbnail((350, 350))\\n im.save(output, format='JPEG', quality=100)\\n output.seek(0)\\n self.picture = InMemoryUploadedFile(output, 'ImageField', \\\"%s.jpg\\\" % self.picture.name.split('.')[0],\\n 'image/jpeg', sys.getsizeof(output), None)\\n super(Tire, self).save()\",\n \"def img_resize(infile, size):\\n try:\\n infile.thumbnail(size, Image.ANTIALIAS)\\n except:\\n print(\\\"cannot create thumbnail for '%s'\\\" % infile)\\n return infile\",\n \"def resize_and_save(local_file,new_file,maxsize=None,maxh=None,maxw=None,crop=None):\\n logging.debug(\\\"maxw = %s, maxsize=%s, crop=%s\\\" % (maxw,maxsize,crop))\\n img = Image.open(local_file)\\n width,height = img.size\\n width,height = float(width), float(height)\\n ratio = float(1)\\n if crop is not None:\\n size = float(maxsize)\\n if width <= height and width > size:\\n ratio = size/width\\n elif height < width and height > size:\\n ratio = size/height\\n else: \\n ratio = 1 # too small\\n elif maxsize:\\n size = float(maxsize)\\n if width >= height and width > size:\\n ratio = size/width\\n elif height > width and height > size:\\n ratio = size/height\\n else: \\n ratio = 1 # too small\\n elif maxh:\\n size = maxh\\n if height > size:\\n ratio = size/height\\n else:\\n # too small\\n ratio = 1\\n elif maxw:\\n size = maxw\\n if width > size:\\n ratio = size/width\\n else:\\n # too small\\n ratio = 1\\n else:\\n raise Exception(\\\"must specify max width, OR max size\\\")\\n \\n print(\\\"old: ratio = %s: size(x,y) = %s,%s\\\" % (ratio,width,height))\\n height = int(height*ratio)\\n width = int(width*ratio)\\n print(\\\"new ratio = %s: size(x,y) = %s,%s\\\" % (ratio,width,height))\\n img = img.resize((width, height),Image.ANTIALIAS)\\n if crop is not None:\\n log.debug(\\\"in crop %s\\\" % crop)\\n crop = int(crop)\\n if width > crop:\\n amt = int((int(width) - crop)/2)\\n img = img.crop((amt,0,amt + crop, crop))\\n elif height > crop:\\n amt = int((int(height) - crop)/2)\\n img = img.crop((0,amt,crop,amt+crop))\\n \\n log.debug(\\\"saving new file %s\\\" % new_file)\\n if img.mode != \\\"RGB\\\":\\n img = img.convert(\\\"RGB\\\")\\n img.save(new_file)\",\n \"def image_to_thumbs(img):\\r\\n\\theight, width, channels = img.shape\\r\\n\\tthumbs = {\\\"original\\\": img}\\r\\n\\t#sizes = [640, 320, 160]\\r\\n\\tsizes = [200]\\r\\n\\tfor size in sizes:\\r\\n\\t\\tif (width >= size):\\r\\n\\t\\t\\tr = (size + 0.0) / width\\r\\n\\t\\t\\tmax_size = (size, int(height * r))\\r\\n\\t\\t\\tthumbs[str(size)] = cv2.resize(img, max_size, interpolation=cv2.INTER_AREA)\\r\\n\\r\\n\\treturn thumbs\",\n \"def generate_thumbnail():\\n import tempfile\\n import glob\\n from anima.env import mayaEnv\\n m_env = mayaEnv.Maya()\\n v = m_env.get_current_version()\\n\\n if not v:\\n return\\n\\n # do not generate a thumbnail from a Repr\\n if '@' in v.take_name:\\n return\\n\\n task = v.task\\n project = task.project\\n # repo = project.repository\\n imf = project.image_format\\n width = int(imf.width * 0.5)\\n height = int(imf.height * 0.5)\\n\\n temp_output = tempfile.mktemp()\\n\\n current_frame = pm.currentTime(q=1)\\n output_file = pm.playblast(\\n fmt='image',\\n startTime=current_frame,\\n endTime=current_frame,\\n sequenceTime=1,\\n forceOverwrite=1,\\n filename=temp_output,\\n clearCache=1,\\n showOrnaments=1,\\n percent=100,\\n wh=(width, height),\\n offScreen=1,\\n viewer=0,\\n compression='PNG',\\n quality=70,\\n framePadding=0\\n )\\n pm.currentTime(current_frame)\\n\\n output_file = output_file.replace('####', '*')\\n found_output_file = glob.glob(output_file)\\n if found_output_file:\\n output_file = found_output_file[0]\\n\\n from anima.ui import utils\\n utils.upload_thumbnail(task, output_file)\\n\\n return found_output_file\",\n \"def generateThumbnail(img):\\n\\n if not img._thumbfn:\\n return\\n\\n aimgfn = join(opts.root, img._filename)\\n if not opts.fast:\\n img._size = imageSize(aimgfn)\\n\\n athumbfn = join(opts.root, img._thumbfn)\\n\\n if opts.thumb_force:\\n if opts.quiet: print \\\"forced regeneration of '%s'\\\" % img._thumbfn\\n elif not exists(athumbfn):\\n if opts.quiet: print \\\"thumbnail absent '%s'\\\" % img._thumbfn\\n else:\\n # Check if thumbsize has changed\\n if not opts.fast:\\n img._thumbsize = imageSize(athumbfn)\\n if not checkThumbSize(img._size, \\\\\\n img._thumbsize, \\\\\\n opts.thumb_size):\\n if opts.quiet: print \\\"thumbnail '%s size has changed\\\" % img._thumbfn\\n try:\\n # Clear cache for thumbnail size.\\n del imageSizeCache[ athumbfn ]\\n except:\\n pass\\n else:\\n# pass\\n# if opts.quiet: print \\\"thumbnail '%s' already generated (size ok)\\\" \\\\\\n# % img._thumbfn\\n return\\n else:\\n if opts.quiet: print \\\"thumbnail '%s' already generated\\\" % img._thumbfn\\n return\\n\\n if opts.no_magick:\\n if opts.quiet: print \\\"ImageMagick tools disabled, can't create thumbnail\\\"\\n return\\n\\n # create necessary directories\\n d = dirname(athumbfn)\\n if not exists(d):\\n os.makedirs(d)\\n\\n if opts.pil:\\n\\n try:\\n im = PilImage.open(aimgfn)\\n im.thumbnail((opts.thumb_size, opts.thumb_size), config.Thumbnails[\\\"Interpolation\\\"])\\n im.save(athumbfn)\\n\\n img._thumbsize = im.size\\n except IOError, e:\\n raise SystemExit(\\\\\\n \\\"Error: identifying file '%s'\\\" % aimgfn + str(e))\\n\\n else:\\n\\n cmd = getMagickProg('convert') + ' -border 2x2 '\\n # FIXME check if this is a problem if not specified\\n #cmd += '-interlace NONE '\\n\\n cmd += '-geometry %dx%d ' % (opts.thumb_size, opts.thumb_size)\\n\\n if opts.thumb_quality:\\n cmd += '-quality %d ' % opts.thumb_quality\\n\\n # This doesn't add text into the picture itself, just the comment in\\n # the header.\\n if opts.copyright:\\n cmd += '-comment \\\\\\\"%s\\\\\\\" ' % opts.copyright\\n\\n # We use [1] to extract the thumbnail when there is one.\\n # It is harmless otherwise.\\n subimg = \\\"\\\"\\n if img._ext.lower() in [ \\\".jpg\\\", \\\".tif\\\", \\\".tiff\\\" ]:\\n subimg = \\\"[1]\\\"\\n\\n cmd += '\\\"%s%s\\\" \\\"%s\\\"' % (aimgfn, subimg, athumbfn)\\n\\n if opts.quiet: print \\\"generating thumbnail '%s'\\\" % img._thumbfn\\n\\n (chin, chout, cherr) = os.popen3(cmd)\\n errs = cherr.readlines()\\n chout.close()\\n cherr.close()\\n if errs:\\n print >> sys.stderr, \\\\\\n \\\"Error: running convert program on %s:\\\" % aimgfn\\n errs = string.join(errs, '\\\\n')\\n print errs\\n\\n if subimg and \\\\\\n re.compile('Unable to read subimage').search(errs):\\n if opts.quiet: print \\\"retrying without subimage\\\"\\n cmd = string.replace(cmd, subimg, \\\"\\\")\\n\\n (chin, chout, cherr) = os.popen3(cmd)\\n errs = cherr.readlines()\\n chout.close()\\n cherr.close()\\n if errs:\\n print >> sys.stderr, \\\\\\n \\\"Error: running convert program on %s:\\\" % aimgfn\\n print string.join(errs, '\\\\n')\\n\\n else:\\n img._thumbsize = imageSize(athumbfn)\",\n \"def save(self, *args, **kwargs):\\n if not self.pk: # on create\\n image = Image.open(self.file)\\n image.thumbnail((400, 400), Image.ANTIALIAS)\\n\\n thumb = io.BytesIO()\\n image.save(\\n thumb, format=\\\"jpeg\\\", quality=80, optimize=True, progressive=True\\n )\\n self.thumbnail = InMemoryUploadedFile(\\n thumb, None, self.file.name, 'image/jpeg', thumb.tell(), None\\n )\\n\\n super(File, self).save(*args, **kwargs)\",\n \"def thumb_profil(log):\\n\\tpath = get_plato_path()\\n\\tfrom PIL import Image\\n\\tsize = 100,200\\n\\tim = Image.open('/%s/plato_users/%s/profil_BIG.jpg'%(path,log))\\n\\tim.thumbnail(size, Image.ANTIALIAS)\\n\\tim.save('/%s/plato_users/%s/profil.jpg'%(path,log),\\\"JPEG\\\")\",\n \"def thumbnail(self, width, height, path, **kwargs):\\n return self.get('fileops/thumbnail', api='CONV', params={\\n 'root': self.root,\\n 'path': path,\\n 'width': width,\\n 'height': height,\\n }, **kwargs)\",\n \"def convertImage(self):\\n saveAs = config.get(\\\"saveFormat\\\")\\n saveLocation = config.get(\\\"saveLocation\\\")\\n image = Image.open(self.folderLocation.text())\\n fileName = Path(image.filename).stem\\n if saveAs == 'ico':\\n size = 256, 256\\n destPath = saveLocation+fileName+\\\".\\\"+saveAs\\n im = Image.open(self.folderLocation.text())\\n im.thumbnail(size)\\n im.save(destPath, 'jpeg')\\n else:\\n image.save(saveLocation+fileName+\\\".\\\"+saveAs, saveAs)\",\n \"def save_thumbnail(self, save=True):\\n modified = False\\n if self.thumbnail:\\n self.thumbnail.delete(save=False)\\n modified = True\\n\\n result = self._thumbnail_save()\\n if result:\\n bytes, extension = result\\n filename = '%s.%s' % (uuid.uuid4(), extension)\\n self.thumbnail.save(name=filename, content=ContentFile(bytes))\\n modified = True\\n\\n if modified and save:\\n self.save()\",\n \"def downsize_img(img: Image.Image,\\n max_width: int,\\n max_height: int) -> Tuple[Image.Image, bool]:\\n width, height = img.size\\n # Assume 0 as current size\\n if not max_width:\\n max_width = width\\n if not max_height:\\n max_height = height\\n\\n if (max_width, max_height) == (width, height): # If no changes, do nothing\\n return img, False\\n\\n img.thumbnail((max_width, max_height), resample=Image.LANCZOS)\\n return img, True\",\n \"def get_thumbnail(img_path):\\n thumb = JPEGImage(unicode(img_path)).exif_thumbnail.as_blob()\\n if thumb:\\n logger.debug(\\\"Using EXIF thumbnail for {0}\\\".format(img_path))\\n return thumb\\n else:\\n logger.debug(\\\"Generating thumbnail for {0}\\\".format(img_path))\\n return scale_image(unicode(img_path), width=160)\",\n \"def GetThumbnail(self, type, maxsize): # real signature unknown; restored from __doc__\\n pass\",\n \"def save_image(filename, image):\\n im = cv2.resize(image, None, fx=SCALE_DOWN, fy=SCALE_DOWN)\\n cv2.imwrite(os.path.join(OUT_DIR, filename), im)\",\n \"def make_thumbnail(self):\\n # https://gist.github.com/valberg/2429288\\n\\n # make sure image data is set\\n if not self.image_data:\\n return False\\n\\n if self.proxy_data:\\n return True\\n\\n # Create a resized version of the image\\n image = Image.open(self.image_data)\\n image.thumbnail(THUMBNAIL_SIZE, Image.BICUBIC)\\n\\n # Save the thumbnail to in-memory 'file'\\n temp_thumb = BytesIO()\\n image.save(temp_thumb, 'jpeg')\\n temp_thumb.seek(0) # rewinds the file\\n\\n # Save image to a SimpleUploadFile which can be saved\\n # into ImageField\\n # TODO figure out how to pass base image's UUID before\\n # image is committed to DB\\n basename = os.path.basename(self.image_data.name)\\n uuidname = os.path.splitext(basename)[0]\\n suf = SimpleUploadedFile(uuidname,\\n temp_thumb.read(), content_type='image/jpeg')\\n thumb_filename = '{}_thumb.jpeg'.format(suf.name)\\n\\n # set save=False, or else it will infinite loop\\n self.proxy_data.save(thumb_filename,\\n suf,\\n save=False)\\n\\n # Also store the real dimensions for the Pillow thumbnail\\n self.proxy_width, self.proxy_height = image.size\\n\\n temp_thumb.close()\\n\\n return True\",\n \"def image_thumb(www_path:Path, fname, width:int, height:int, itype=\\\"jpg\\\", quality:int=50):\\n if fname is None:\\n return None\\n\\n shots_path = www_path / 'shots'\\n thumb_path = www_path / 'thumb'\\n image = shots_path / fname\\n if '..' in fname:\\n raise ValueError('wat')\\n\\n try:\\n filesize = os.path.getsize(image)\\n except FileNotFoundError:\\n return\\n\\n the_string = f'thumb {fname} {width} {height} {filesize}'.encode('utf-8')\\n hash_fname = md5(the_string).hexdigest() + '.' + itype\\n dest = str(thumb_path / hash_fname)\\n\\n if not os.path.exists(dest):\\n cmd = ['convert', '-quality', '50', str(image), '-resize', f'{width}x{height}', '+profile', '\\\"*\\\"', dest]\\n subprocess.check_call(cmd)\\n\\n return f'/thumb/{hash_fname}'\",\n \"def image_optimize(file, width, height, force=False, resize=False):\\n import Image as pil\\n \\n max_width = width\\n max_height = height\\n\\n img = pil.open(file)\\n \\n #Fixing problem with gif\\n if img.mode != \\\"RGB\\\":\\n img = img.convert(\\\"RGB\\\")\\n\\n src_width, src_height = img.size\\n src_ratio = float(src_width) / float(src_height)\\n dst_width, dst_height = max_width, max_height\\n dst_ratio = float(dst_width) / float(dst_height)\\n \\n if not force:\\n if src_height > src_width:\\n max_width = dst_height\\n max_height = dst_width\\n img.thumbnail((max_width, max_height), pil.ANTIALIAS)\\n else:\\n if dst_ratio < src_ratio:\\n crop_height = src_height \\n crop_width = crop_height * dst_ratio \\n x_offset = int((src_width - crop_width)/2) \\n y_offset = 0 \\n else: \\n crop_width = src_width\\n crop_height = crop_width / dst_ratio\\n x_offset = 0\\n y_offset = int((src_height - crop_height)/3)\\n img = img.crop((x_offset, y_offset, x_offset+int(crop_width),\\n y_offset+int(crop_height)))\\n img = img.resize((dst_width, dst_height), pil.ANTIALIAS)\\n \\n return img\",\n \"def save_resized_image(image, resolution: float, image_name: str):\\n\\tfilename: str = join(join(base_directory, str(resolution) + 'x'),\\n\\t image_name)\\n\\tprint(image_name)\\n\\tprint(join(base_directory, str(resolution)))\\n\\tprint(filename)\\n\\tcv.imwrite(filename, image)\",\n \"def exportImg(self):\\n if self.superSampling:\\n print(\\\"Exporting with size adjusted\\\")\\n self.img = self.img.resize((int(self.width/2),int(self.height/2)),Image.NEAREST)\\n self.img.save(self.fileName,\\\"PNG\\\")\",\n \"def save_image(image_numpy, image_path, aspect_ratio=1.0):\\n\\n image_pil = Image.fromarray(image_numpy)\\n h, w, _ = image_numpy.shape\\n\\n if aspect_ratio > 1.0:\\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\\n if aspect_ratio < 1.0:\\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\\n image_pil.save(image_path)\",\n \"def save_image(image_numpy, image_path, aspect_ratio=1.0):\\n\\n image_pil = Image.fromarray(image_numpy)\\n h, w, _ = image_numpy.shape\\n\\n if aspect_ratio > 1.0:\\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\\n if aspect_ratio < 1.0:\\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\\n image_pil.save(image_path)\",\n \"def setThumbnailImage(*args):\",\n \"def save_image(image_numpy, image_path, aspect_ratio=1.0):\\n\\n image_pil = Image.fromarray(image_numpy)\\n h, w, _ = image_numpy.shape\\n\\n if aspect_ratio is None:\\n pass\\n elif aspect_ratio > 1.0:\\n image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)\\n elif aspect_ratio < 1.0:\\n image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)\\n image_pil.save(image_path)\",\n \"def resize_and_crop(img, savePath, size, crop_type='middle'):\\n\\t# If height is higher we resize vertically, if not we resize horizontally\\n\\n\\t# Get current and desired ratio for the images\\n\\timg_ratio = img.size[0] / float(img.size[1])\\n\\tratio = size[0] / float(size[1])\\n\\tprint \\\"img_ratio = \\\" + str(img_ratio) + \\\". ratio = \\\" + str(ratio)\\n\\t#The image is scaled/cropped vertically or horizontally depending on the ratio\\n\\tif ratio > img_ratio:\\n\\t\\timg = img.resize((size[0], int(round(size[0] * img.size[1] / img.size[0]))),\\n\\t\\t Image.ANTIALIAS)\\n\\t\\t# Crop in the top, middle or bottom\\n\\t\\tif crop_type == 'top':\\n\\t\\t\\tbox = (0, 0, img.size[0], size[1])\\n\\t\\telif crop_type == 'middle':\\n\\t\\t\\tbox = (0, int(round((img.size[1] - size[1]) / 2)), img.size[0],\\n\\t\\t int(round((img.size[1] + size[1]) / 2)))\\n\\t\\telif crop_type == 'bottom':\\n\\t\\t\\tbox = (0, img.size[1] - size[1], img.size[0], img.size[1])\\n\\t\\telse :\\n\\t\\t\\traise ValueError('ERROR: invalid value for crop_type')\\n\\t\\tprint \\\"ratio > img_ratio. Cropping box: \\\"\\n\\t\\tprint box\\n\\t\\timg = img.crop(box)\\n\\telif ratio < img_ratio:\\n\\t\\timg = img.resize((int(round(size[1] * img.size[0] / img.size[1])), size[1]),\\n\\t\\t Image.ANTIALIAS)\\n\\t\\t# Crop in the top, middle or bottom\\n\\t\\tif crop_type == 'top':\\n\\t\\t\\tbox = (0, 0, size[0], img.size[1])\\n\\t\\telif crop_type == 'middle':\\n\\t\\t\\tbox = (int(round((img.size[0] - size[0]) / 2)), 0,\\n\\t\\t int(round((img.size[0] + size[0]) / 2)), img.size[1])\\n\\t\\telif crop_type == 'bottom':\\n\\t\\t\\tbox = (img.size[0] - size[0], 0, img.size[0], img.size[1])\\n\\t\\telse :\\n\\t\\t\\traise ValueError('ERROR: invalid value for crop_type')\\n\\n\\t\\tprint \\\"ratio < img_ratio. Cropping box: \\\"\\n\\t\\tprint box\\n\\t\\timg = img.crop(box)\\n\\telse :\\n\\t\\tprint \\\"so i guess the ratios are the same?\\\"\\n\\t\\timg = img.resize((size[0], size[1]),\\n\\t Image.ANTIALIAS)\\n\\t # If the scale is the same, we do not need to crop\\n\\tprint \\\"Saving thumb to \\\" + savePath\\n\\timg.save(savePath, \\\"JPEG\\\", quality=thumbCompressQual)\",\n \"def resize_png(width, height, source, destination):\\n\\n os.system('convert -resize %sx%s \\\"%s\\\" \\\"%s\\\"' % (width, height, source, destination))\",\n \"def save_thumb(metadata_df):\\n session = requests.Session()\\n session.auth = (PLANET_API_KEY, '')\\n auth = session.auth\\n \\n for index, row in metadata_df.iterrows():\\n url = row.thumbnail\\n date = row.date\\n item_type = row.item_type\\n cloud_cover = row.cloud_cover\\n id_ = row.id\\n sample_id = row.sample_id\\n \\n thumb_name = f'it{item_type}_cc{cloud_cover}_y{date.year}m{date.month}_{id_}.jpg'\\n \\n thumb_path = os.path.join(os.getcwd(),'thumbs', \\n str(sample_id), \\n str(date.year))\\n \\n Path(thumb_path).mkdir(parents=True, exist_ok=True)\\n\\n r = requests.get(url, auth=auth, stream=True)\\n if r.status_code == 200:\\n with open(os.path.join(thumb_path, thumb_name), 'wb') as f:\\n r.raw.decode_content = True\\n shutil.copyfileobj(r.raw, f)\",\n \"def test_create_thumbnails(self):\\n \\n logging.info('create_thumbnail')\\n \\n for size in self.article.sizes.keys():\\n assert not self.article.thumbnail_exists(size)\\n\\n self.article.image.save('avatar.png', ContentFile(self.image.read()))\\n self.article.create_thumbnails()\\n \\n for size in self.article.sizes.keys():\\n assert self.article.thumbnail_exists(size)\",\n \"def thumbnail(self, options):\\n params = {\\n 'width': options['width'] if 'width' in options else 50,\\n 'height': options['height'] if 'height' in options else 50,\\n 'smartCropping': options['smartCropping'] if 'smartCropping' in options else False\\n }\\n\\n return Base._postWithOptions(self, _thumbnailUrl, options, params)\",\n \"def fileResizeObscure(new_filepath):\\n # Resize\\n img1 = Image.open(new_filepath)\\n img2=image_reduce(img1)\\n *** Stopped working here\\n newpath=\\\"toupload\\\\\\\\%s\\\" % new_filepath\\n # Block ID\\n width=img2.size[0]\\n height=img2.size[1]\\n # Obscuring params were decided by trial and error using fraction of width and height\\n x1=int(0.16*width)\\n x2=int(0.28*width)\\n y1=int(0.94*height)\\n y2=int(0.98*height) \\n # Faster but easier to snoop? should not be since it changes the pixels\\n draw = ImageDraw.Draw(img2)\\n draw.rectangle([(x1,y1),(x2,y2)],fill=\\\"white\\\")\\n del draw\\n \\n img2.save(newpath,optimize=True,quality=95)\",\n \"def _resize_image(filename, size):\\n width, height = 0, 1\\n\\n try:\\n import Image, ImageOps\\n except ImportError:\\n from PIL import Image, ImageOps\\n\\n if not size['resample']:\\n resample = Image.ANTIALIAS\\n\\n img = Image.open(filename)\\n if (img.size[width] > size['width'] or\\n img.size[height] > size['height']):\\n\\n #If the image is big resize it with the cheapest resize algorithm\\n factor = 1\\n while (img.size[0] / factor > 2 * size['width'] and\\n img.size[1] * 2 / factor > 2 * size['height']):\\n factor *= 2\\n if factor > 1:\\n img.thumbnail((int(img.size[0] / factor),\\n int(img.size[1] / factor)), resample=resample)\\n\\n if size['crop']:\\n img = ImageOps.fit(img, (size['width'], size['height']), method=resample)\\n else:\\n img.thumbnail((size['width'], size['height']), resample=resample)\\n\\n try:\\n img.save(filename, optimize=1)\\n except IOError:\\n img.save(filename)\",\n \"def extract_thumbnail(img, joints):\\n x_min, y_min = np.min(joints, axis=0)\\n x_max, y_max = np.max(joints, axis=0)\\n [h, w, _] = img.shape\\n\\n if x_min > 20:\\n x_min -= 20\\n if y_min > 20:\\n y_min -= 20\\n\\n if x_max+20 < w:\\n x_max += 20\\n if y_max+20 < h:\\n y_max += 20\\n\\n return img[y_min:y_max, x_min:x_max, :]\",\n \"def RescaleScreenShot(bmp, thumbnail_size=200):\\r\\n\\r\\n bmpW, bmpH = bmp.GetWidth(), bmp.GetHeight()\\r\\n img = bmp.ConvertToImage()\\r\\n\\r\\n newW, newH = bmpW, bmpH\\r\\n \\r\\n if bmpW > bmpH:\\r\\n if bmpW > thumbnail_size:\\r\\n ratio = bmpW/float(thumbnail_size)\\r\\n newW, newH = int(bmpW/ratio), int(bmpH/ratio)\\r\\n img.Rescale(newW, newH, wx.IMAGE_QUALITY_HIGH)\\r\\n else:\\r\\n if bmpH > thumbnail_size:\\r\\n ratio = bmpH/float(thumbnail_size)\\r\\n newW, newH = int(bmpW/ratio), int(bmpH/ratio)\\r\\n img.Rescale(newW, newH, wx.IMAGE_QUALITY_HIGH)\\r\\n\\r\\n newBmp = img.ConvertToBitmap()\\r\\n otherBmp = wx.EmptyBitmap(newW+5, newH+5) \\r\\n\\r\\n memDC = wx.MemoryDC()\\r\\n memDC.SelectObject(otherBmp)\\r\\n memDC.SetBackground(wx.WHITE_BRUSH)\\r\\n memDC.Clear()\\r\\n \\r\\n memDC.SetPen(wx.TRANSPARENT_PEN)\\r\\n\\r\\n pos = 0\\r\\n for i in xrange(5, 0, -1):\\r\\n brush = wx.Brush(wx.Colour(50*i, 50*i, 50*i))\\r\\n memDC.SetBrush(brush)\\r\\n memDC.DrawRoundedRectangle(0, 0, newW+5-pos, newH+5-pos, 2)\\r\\n pos += 1\\r\\n\\r\\n memDC.DrawBitmap(newBmp, 0, 0, True)\\r\\n \\r\\n # Select the Bitmap out of the memory DC by selecting a new\\r\\n # uninitialized Bitmap\\r\\n memDC.SelectObject(wx.NullBitmap)\\r\\n\\r\\n return otherBmp\",\n \"def save_image(image, output_path, limits=None):\\n\\n # Generate a figure with no axes, border, etc.\\n fig = plt.figure()\\n fig.set_size_inches(1, 1)\\n ax = plt.Axes(fig, [0, 0, 1, 1])\\n ax.set_axis_off()\\n fig.add_axes(ax)\\n\\n # If the image is complex, warn the user and discard the imaginary part.\\n if np.iscomplexobj(image):\\n warnings.warn('Image is complex; only saving real part')\\n image = np.real(image)\\n\\n # Plot the image, scaled according to the limits if they are provided.\\n if limits is None:\\n ax.imshow(image, cmap='gray', aspect='auto', interpolation='none')\\n else:\\n vmin = limits[0]\\n vmax = limits[1]\\n ax.imshow(image, cmap='gray', vmin=vmin, vmax=vmax, aspect='auto', interpolation='none')\\n\\n # Save the figure with a high resolution, and close it.\\n plt.savefig(output_path, dpi=800)\\n plt.close()\",\n \"def FlyResize( image, log_mess, nimages, method = Image.ANTIALIAS ):\\n oldw, oldh = image.size\\n resl = [8, 10, 14, 16, 20, 22, 24, 32, 40, 48, 64, 96, 128, 256]\\n \\n if oldw > 256 or oldh > 256:\\n newsiz = min(resl, key = lambda x:abs(x - max(oldw, oldh)))\\n image.thumbnail((newsiz, newsiz), method)\\n neww, newh = image.size\\n log_mess += ' and new size scaled = %s x %s' %(neww, newh)\\n elif nimages > 1:\\n log_mess += ' and size = %s x %s' %(oldw, oldh)\\n \\n return oldw, oldh, image, log_mess\",\n \"def resize_image(self, im, max_side_len=512):\\n h, w, _ = im.shape\\n\\n resize_w = w\\n resize_h = h\\n\\n # limit the max side\\n if max(resize_h, resize_w) > max_side_len:\\n ratio = float(max_side_len) / resize_h if resize_h > resize_w else float(max_side_len) / resize_w\\n else:\\n ratio = 1.\\n resize_h = int(resize_h * ratio)\\n resize_w = int(resize_w * ratio)\\n\\n resize_h = resize_h if resize_h % 32 == 0 else (resize_h // 32 - 1) * 32\\n resize_w = resize_w if resize_w % 32 == 0 else (resize_w // 32 - 1) * 32\\n im = cv2.resize(im, (int(resize_w), int(resize_h)))\\n\\n ratio_h = resize_h / float(h)\\n ratio_w = resize_w / float(w)\\n\\n return im, (ratio_h, ratio_w)\",\n \"def resize_img(img, max_side=1000):\\n height, width = img.shape\\n # if the image is small enough as is, return it unchanged\\n if height <= 1000 and width <= 1000:\\n return img\\n dim = tuple()\\n if height > width:\\n scale_ratio = max_side / height\\n dim = (int(width * scale_ratio), max_side)\\n else:\\n scale_ratio = max_side / width\\n dim = (max_side, int(height * scale_ratio))\\n return cv2.resize(img, dim, interpolation=cv2.INTER_AREA)\",\n \"def generate_thumbnail(progress_controller=None):\\n # TODO: For now skip if this is Maya2017\\n import pymel\\n\\n if pymel.versions.current() >= 201700:\\n return\\n\\n # skip this if maya is running in batch mode\\n if pm.general.about(batch=1):\\n return\\n\\n from anima.dcc.mayaEnv import auxiliary\\n\\n auxiliary.generate_thumbnail()\",\n \"def resize_file_to(self, in_path, out_path, keep_filename=False):\\n if keep_filename:\\n filename = path.join(out_path, path.basename(in_path))\\n else:\\n filename = path.join(out_path, self.get_thumbnail_name(in_path))\\n out_path = path.dirname(filename)\\n if not path.exists(out_path):\\n os.makedirs(out_path)\\n if not path.exists(filename):\\n try:\\n image = Image.open(in_path)\\n thumbnail = self.resize(image)\\n thumbnail.save(filename)\\n logger.info(\\\"Generated Thumbnail {0}\\\".format(path.basename(filename)))\\n except IOError:\\n logger.info(\\n \\\"Generating Thumbnail for {0} skipped\\\".format(\\n path.basename(filename)\\n )\\n )\",\n \"def get_thumbnail_size(self, thumbnail_name, forced=False):\",\n \"def resize_image(path, size=256):\\n\\n _portlate = 0,\\n _landscape = 1,\\n\\n img = Image.open(path)\\n if img.mode != 'RGB':\\n img = img.convert('RGB')\\n w, h = img.size\\n if (w == size) and (h == size):\\n return img\\n shape = _landscape if w > h else _portlate\\n shorter_side = w if w < h else h\\n longer_side = w if w > h else h\\n magnification = size / shorter_side\\n longer_side *= magnification\\n shorter_side *= magnification\\n if shape == _landscape:\\n resize = (round(longer_side), round(shorter_side))\\n else:\\n resize = (round(shorter_side), round(longer_side))\\n assert round(shorter_side) == size, \\\"this function has bugs\\\"\\n scaled_img = img.resize(resize, Image.LANCZOS)\\n r_w, r_h = resize\\n if (r_h == size) and (r_w == size):\\n return scaled_img\\n if shape == _landscape:\\n left = (r_w - size) // 2\\n top = 0\\n else:\\n left = 0\\n top = (r_h - size) // 2\\n bottom = top + size\\n right = left + size\\n box = (left, top, right, bottom)\\n cropped_img = scaled_img.crop(box)\\n assert (size, size) == cropped_img.size, \\\\\\n \\\"this function has bugs\\\"\\n return cropped_img\",\n \"def _image_resize_keep_ratio(self, image, max_w, max_h, crop=False):\\n raise NotImplementedError\",\n \"def image_preview(img_path):\\r\\n img = Image.open(img_path)\\r\\n t_size = 256, 256\\r\\n\\r\\n try:\\r\\n if \\\"exif\\\" in img.info:\\r\\n exif_dict = piexif.load(img.info[\\\"exif\\\"])\\r\\n if piexif.ImageIFD.Orientation in exif_dict[\\\"0th\\\"]:\\r\\n orientation = exif_dict[\\\"0th\\\"].pop(piexif.ImageIFD.Orientation)\\r\\n #exif_bytes = piexif.dump(exif_dict)\\r\\n if orientation == 2:\\r\\n img = img.transpose(Image.FLIP_LEFT_RIGHT)\\r\\n elif orientation == 3:\\r\\n img = img.rotate(180)\\r\\n elif orientation == 4:\\r\\n img = img.rotate(180).transpose(Image.FLIP_LEFT_RIGHT)\\r\\n elif orientation == 5:\\r\\n img = img.rotate(-90, expand=True).transpose(Image.FLIP_LEFT_RIGHT)\\r\\n elif orientation == 6:\\r\\n img = img.rotate(-90, expand=True)\\r\\n elif orientation == 7:\\r\\n img = img.rotate(90, expand=True).transpose(Image.FLIP_LEFT_RIGHT)\\r\\n elif orientation == 8:\\r\\n img = img.rotate(90, expand=True)\\r\\n except:\\r\\n print('exif data problem in', img_path)\\r\\n\\r\\n new_image = Image.new(img.mode, t_size, color=(255,255,255))\\r\\n img.thumbnail(t_size, Image.ANTIALIAS) # in-place\\r\\n x_offset= (new_image.size[0] - img.size[0]) // 2\\r\\n y_offset= (new_image.size[1] - img.size[1]) // 2\\r\\n new_image.paste(img, (x_offset, y_offset))\\r\\n img = new_image\\r\\n\\r\\n # in memory image -> bytes -> base64_string\\r\\n buffered = BytesIO()\\r\\n img.save(buffered, format=\\\"JPEG\\\")\\r\\n img_preview = base64.b64encode(buffered.getvalue()).decode('utf-8')\\r\\n\\r\\n return img_preview\",\n \"def get_thumbnail(format):\",\n \"def get_thumbnail_size(context, image):\\n if not image or not context['CONFIG']['THUMBNAIL_ENABLED']:\\n return False\\n if context['CONFIG']['THUMBNAIL_PRESERVE_RATIO']:\\n if image.height > image.width:\\n ret = '0x%s' % context['CONFIG']['THUMBNAIL_MAX_HEIGHT']\\n else:\\n ret = '%sx0' % context['CONFIG']['THUMBNAIL_MAX_WIDTH']\\n else:\\n ret = '%sx%s' % (\\n context['CONFIG']['THUMBNAIL_MAX_WIDTH'],\\n context['CONFIG']['THUMBNAIL_MAX_HEIGHT']\\n )\\n return ret\",\n \"def resize(img, size):\\n img = cv2.resize(img, tuple(size[::-1]))\\n return img\",\n \"def calc_thumbnail_size(img):\\n width, length = img.size\\n ratio = width / length\\n\\n # for some reason, if it's exactly 224, then thumnailed image is 223\\n dim = 224 + 1 # output dim\\n if ratio > 1:\\n size = (dim * ratio, dim)\\n else:\\n size = (dim, dim / ratio)\\n# print(size)\\n return size\",\n \"def resize(fname, width, height):\\n image = cv2.imread(fname) # read priginal image\\n cv2.imshow('Original Image', image) # show original image\\n cv2.waitKey(0) # stop\\n\\n org_height, org_width = image.shape[0:2] # original width and height\\n\\n # print width and height\\n print(\\\"width\\\", org_width)\\n print(\\\"height\\\", org_height)\\n\\n # check image height and width and resize to new size\\n if org_width >= org_height:\\n new_image = cv2.resize(image, (width, height))\\n else:\\n new_image = cv2.resize(image, (height, width))\\n\\n return fname, new_image\",\n \"def compress_image(image: BinaryIO, size: Tuple[int, int] = (512, 512)) -> File:\\n im = Image.open(image)\\n im_format = im.format\\n im.thumbnail(size)\\n if im.mode in (\\\"P\\\", \\\"RGBA\\\"):\\n im = im.quantize()\\n im_io = BytesIO()\\n im.save(im_io, im_format)\\n return File(im_io, image.name)\",\n \"def generate_thumb_filename(instance, filename):\\n return _generate_filename(instance, filename, 'thumbs')\",\n \"def _take_snapshot(self, filename, frame):\\n thumbnail_key = os.path.join(self._obj_key_prefix, \\\"{}.jpg\\\"\\n .format(filename))\\n drawn_image = im.draw_region(frame.image,\\n self._detector.roi,\\n EVENT_ALERT_COLOR_CODE,\\n 0.4)\\n shrunk_image = im.shrink_image(drawn_image)\\n self._obj_store.save_image_obj(thumbnail_key, shrunk_image)\\n return thumbnail_key\",\n \"def _image_resize_keep_ratio(self, image, max_w, max_h, crop=False):\\n if crop:\\n width, height = sizing.new_size_keep_aspect_ratio(image.size, (max_w, max_h), 'outer')\\n image = image.resize((width, height), Image.ANTIALIAS)\\n image = image.crop(sizing.new_size_by_croping(image.size, (max_w, max_h)))\\n else:\\n width, height = sizing.new_size_keep_aspect_ratio(image.size, (max_w, max_h), 'inner')\\n image = image.resize((width, height), Image.ANTIALIAS)\\n return image, image.size[0], image.size[1]\",\n \"def generate(self, save=True):\\n stretched_photo, crop_box = self._generate_img()\\n\\n # set crop_box to (0,0,0,0) if photo not cropped\\n if not crop_box:\\n crop_box = 0, 0, 0, 0\\n\\n self.crop_left, self.crop_top, right, bottom = crop_box\\n self.crop_width = right - self.crop_left\\n self.crop_height = bottom - self.crop_top\\n\\n self.width, self.height = stretched_photo.size\\n\\n f = BytesIO()\\n imgf = (self.photo._get_image().format or\\n Image.EXTENSION[path.splitext(self.photo.image.name)[1]])\\n\\n stretched_photo.save(f, format=imgf, quality=self.format.resample_quality)\\n f.seek(0)\\n\\n self.image.save(self.file(), ContentFile(f.read()), save)\",\n \"def mosaic_thumbnail(self):\\n serial = slugify(self.request.matchdict[\\\"serial\\\"])\\n filename = \\\"thumbnails/%s/mosaic.png\\\" % serial\\n return FileResponse(filename)\",\n \"async def resize_photo(photo):\\n image = Image.open(photo)\\n maxsize = (512, 512)\\n if (image.width and image.height) < 512:\\n size1 = image.width\\n size2 = image.height\\n if image.width > image.height:\\n scale = 512 / size1\\n size1new = 512\\n size2new = size2 * scale\\n else:\\n scale = 512 / size2\\n size1new = size1 * scale\\n size2new = 512\\n size1new = math.floor(size1new)\\n size2new = math.floor(size2new)\\n sizenew = (size1new, size2new)\\n image = image.resize(sizenew)\\n else:\\n image.thumbnail(maxsize)\\n\\n return image\",\n \"def save_image(path, image): \\n if len(image.shape) == 4:\\n image = image.reshape((image.shape[1], image.shape[2], image.shape[3]))\\n image = np.clip(image * 255.0, 0, 255).astype(np.uint8)\\n skimage.io.imsave(path, image)\",\n \"def save_image(image, figsize, save_path, ticks=False, grey=True):\\n fig = plt.figure(figsize=figsize)\\n if grey:\\n plt.imshow(image, cmap=plt.get_cmap('gray'))\\n else:\\n plt.imshow(image)\\n if not ticks:\\n plt.xticks([]), plt.yticks([])\\n plt.tight_layout()\\n fig.savefig(save_path)\\n plt.close(fig)\\n return\",\n \"def thumbnail(self, item):\\n if self._has_image_field(item) and self._field_is_visible('image'):\\n tile_conf = self.get_tile_configuration()\\n image_conf = tile_conf.get('image', None)\\n if image_conf:\\n scaleconf = image_conf['imgsize']\\n # Scale string is something like: 'mini 200:200'.\\n # We need the name only: 'mini'.\\n scale = scaleconf.split(' ')[0]\\n scales = ploneapi.content.get(path='@@images')\\n return scales.scale('image', scale)\",\n \"def get_thumbnail_url():\",\n \"def img_url_thumbnail(self):\\n url = '%s=s%s-c' % (self.img_url, self.THUMBNAIL_SIZE_PX)\\n if self.img_rot in Plaque.ALLOWED_ROTATIONS:\\n url = \\\"%s-r%s\\\" % (url, self.img_rot)\\n return url\",\n \"def plot_thumb(self, data_fname):\\n thumbnail = self.controller.plot_thumb(data_fname, self.bitmap_width, self.bitmap_height)\\n if thumbnail is not None:\\n self.figure_bmp.SetBitmap(thumbnail)\\n else:\\n self.plot_blank()\",\n \"def resize_image(first_image, width, height):\\n resizing_image = Image()\\n temp_image = ((Pil_image.open(first_image.picture)).convert(\\\"RGB\\\")).resize((width, height), Pil_image.ANTIALIAS)\\n filestream = BytesIO()\\n temp_image.save(filestream, 'JPEG', quality=90)\\n filestream.seek(0)\\n name = f\\\"{str(first_image.picture).split('.')[0]}_{width}_{height}.{str(first_image.picture).split('.')[1]}\\\"\\n image = InMemoryUploadedFile(filestream, 'picture', name, 'jpeg/image', sys.getsizeof(filestream), None)\\n resizing_image.url = first_image.url\\n resizing_image.width = width\\n resizing_image.height = height\\n resizing_image.parent = first_image.id\\n resizing_image.picture = image\\n resizing_image.save()\\n return resizing_image\",\n \"def createThumbnail(self, useCursorPosition=False, dbPath = None, versionInt = None):\\n\\n return \\\"\\\"\\n # logger.debug(\\\"Func: createThumbnail\\\")\\n # projectPath = self.projectDir\\n # if useCursorPosition:\\n # versionInt = self.currentVersionIndex\\n # dbPath = self.currentDatabasePath\\n # else:\\n # if not dbPath or not versionInt:\\n # msg = \\\"Both dbPath and version must be defined if useCursorPosition=False\\\"\\n # raise Exception ([360, msg])\\n #\\n # versionStr = \\\"v%s\\\" % (str(versionInt).zfill(3))\\n # dbDir, shotNameWithExt = os.path.split(dbPath)\\n # shotName = os.path.splitext(shotNameWithExt)[0]\\n #\\n # thumbPath = \\\"{0}_{1}_thumb.jpg\\\".format(os.path.join(dbDir, shotName), versionStr)\\n # relThumbPath = os.path.relpath(thumbPath, projectPath)\\n #\\n # # create a thumbnail using playblast\\n # thumbDir = os.path.split(thumbPath)[0]\\n # if os.path.exists(thumbDir):\\n # # frame = pm.currentTime(query=True)\\n # frame = cmds.currentTime(query=True)\\n # # store = pm.getAttr(\\\"defaultRenderGlobals.imageFormat\\\")\\n # store = cmds.getAttr(\\\"defaultRenderGlobals.imageFormat\\\")\\n # # pm.setAttr(\\\"defaultRenderGlobals.imageFormat\\\", 8) # This is the value for jpeg\\n # cmds.setAttr(\\\"defaultRenderGlobals.imageFormat\\\", 8) # This is the value for jpeg\\n # # pm.playblast(completeFilename=thumbPath, forceOverwrite=True, format='image', width=221, height=124, showOrnaments=False, frame=[frame], viewer=False, percent=100)\\n # cmds.playblast(completeFilename=thumbPath, forceOverwrite=True, format='image', width=221, height=124, showOrnaments=False, frame=[frame], viewer=False, percent=100)\\n # # pm.setAttr(\\\"defaultRenderGlobals.imageFormat\\\", store) #take it back\\n # cmds.setAttr(\\\"defaultRenderGlobals.imageFormat\\\", store) #take it back\\n # else:\\n # # pm.warning(\\\"something went wrong with thumbnail. Skipping thumbnail\\\")\\n # cmds.warning(\\\"something went wrong with thumbnail. Skipping thumbnail\\\")\\n # return \\\"\\\"\\n # # return thumbPath\\n # return relThumbPath\",\n \"def thumbnail(self, item):\\n if self._has_image_field(item) and self._field_is_visible(\\\"image\\\"):\\n tile_conf = self.get_tile_configuration()\\n image_conf = tile_conf.get(\\\"image\\\", None)\\n if image_conf:\\n scaleconf = image_conf[\\\"imgsize\\\"]\\n # scale string is something like: 'mini 200:200' and\\n # we need the name only: 'mini'\\n if scaleconf == \\\"_original\\\":\\n scale = None\\n else:\\n scale = scaleconf.split(\\\" \\\")[0]\\n scales = item.restrictedTraverse(\\\"@@images\\\")\\n return scales.scale(\\\"image\\\", scale)\",\n \"def _create_placeholder(self, thumbnail_size):\\n logger.debug(\\\"Creating placeholder. thumbnail_size: %s\\\", thumbnail_size)\\n placeholder = Image.new(\\\"RGB\\\", (thumbnail_size, thumbnail_size))\\n draw = ImageDraw.Draw(placeholder)\\n draw.rectangle(((0, 0), (thumbnail_size, thumbnail_size)), outline=\\\"#E5E5E5\\\", width=1)\\n placeholder = np.array(placeholder)\\n self._previewcache[\\\"placeholder\\\"] = placeholder\\n logger.debug(\\\"Created placeholder. shape: %s\\\", placeholder.shape)\",\n \"def square_image(img):\\r\\n x,y = img.size\\r\\n while y > x:\\r\\n #slice 10px at a time until square\\r\\n slice_height = min(y - x, 10)\\r\\n\\r\\n bottom = img.crop((0, y - slice_height, x, y))\\r\\n top = img.crop((0, 0, x, slice_height))\\r\\n\\r\\n #remove the slice with the least entropy\\r\\n if image_entropy(bottom) < image_entropy(top):\\r\\n img = img.crop((0, 0, x, y - slice_height))\\r\\n else:\\r\\n img = img.crop((0, slice_height, x, y))\\r\\n\\r\\n x,y = img.size\\r\\n\\r\\n return img\",\n \"def resize_img(self,scale=1):\\n reduced = self.image.reduce((scale,scale))\\n reduced.save(\\\"../edited/{}\\\".format(self.image.filename))\\n\\n reduced = Image.open(\\\"../edited/{}\\\".format(self.image.filename))\\n return reduced\",\n \"def get_thumbnail_magnification(slide):\\n ratio = np.asarray(slide.dimensions) / np.asarray(slide.associated_images[\\\"thumbnail\\\"].size)\\n # np.sqrt(np.prod(ratio))\\n return ratio\",\n \"def get_thumbnail_name(self, thumbnail_name, with_size=None):\",\n \"def save_original_image(slide, heatmapPath):\\n dims = slide.dims\\n img = slide.image.read_region((0,0), len(dims)-1, dims[-1])\\n img.save(os.path.join(heatmapPath, slide.id) + \\\".png\\\")\",\n \"def get_thumbnail(self, size):\\n\\n thumb = self.associated_images[b'thumbnail']\\n return thumb\",\n \"def save_tile_img(tif, xyz, dataset, tile_size, region, zone, save_path, display=False):\\n \\n prefix = f'{region}{zone}{dataset}_'\\n x,y,z = xyz\\n tile, mask = rt_main.tile(tif, x,y,z, tilesize=tile_size)\\n if display: \\n plt.imshow(np.moveaxis(tile,0,2))\\n plt.show()\\n \\n skimage.io.imsave(f'{save_path}/{prefix}{z}_{x}_{y}.png',np.moveaxis(tile,0,2), check_contrast=False)\",\n \"def resize_img(self, filename: str, size: Tuple[int, int] = (299, 299)):\\n img = Image.open(join(self.source_dir, filename))\\n width, height = img.size\\n orig_shape = np.array(img.size)\\n wanted_shape = np.array(size)\\n ratios = wanted_shape / orig_shape\\n wanted_width, wanted_height = size\\n ratio_w, ratio_h = wanted_width / width, wanted_height / height\\n\\n if np.alltrue(ratios > 1):\\n # Both sides of the image are shorter than the desired dimension,\\n # so take the side that's closer in size and enlarge the image\\n # in both directions to make that one fit\\n factor = min(ratio_h, ratio_w)\\n img = img.resize((int(width * factor), int(height * factor)))\\n\\n # Now we have an image that's either larger than the desired shape\\n # or at least one side matches the desired shape and we can resize\\n # with contain\\n cover = resizeimage.resize_contain(img, size)\\n cover.save(join(self.dest_dir, filename), 'JPEG')\",\n \"def top_thumbnail(self):\\n serial = slugify(self.request.matchdict[\\\"serial\\\"])\\n filename = \\\"thumbnails/%s/top.png\\\" % serial\\n return FileResponse(filename)\",\n \"def save_normalized_image(path, data):\\n image_parser = ImageFile.Parser()\\n try:\\n image_parser.feed(data)\\n image = image_parser.close()\\n except IOError:\\n return False\\n image.thumbnail(MAX_IMAGE_SIZE, Image.ANTIALIAS)\\n if image.mode != 'RGB':\\n image = image.convert('RGB')\\n image.save(path)\\n return True\",\n \"def save_image(image, filename, mode='PNG'):\\n out = Image.new(mode='L', size=(image['width'], image['height']))\\n out.putdata(image['pixels'])\\n if isinstance(filename, str):\\n out.save(filename)\\n else:\\n out.save(filename, mode)\\n out.close()\",\n \"def save_image(image, filename, mode='PNG'):\\n out = Image.new(mode='L', size=(image['width'], image['height']))\\n out.putdata(image['pixels'])\\n if isinstance(filename, str):\\n out.save(filename)\\n else:\\n out.save(filename, mode)\\n out.close()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6931515","0.68739617","0.68509567","0.68389434","0.6793269","0.6591011","0.6537345","0.6449486","0.6414779","0.6377539","0.6353064","0.63198406","0.6311073","0.6295751","0.6291895","0.6244799","0.6227591","0.6221736","0.6218256","0.62178695","0.6205242","0.614075","0.6133338","0.6115921","0.61114675","0.61104786","0.6087212","0.6075646","0.6053927","0.604407","0.6043874","0.60386133","0.601983","0.6008455","0.60030925","0.5970516","0.5949743","0.59447354","0.59325963","0.5929201","0.5915176","0.58811194","0.5879404","0.5873414","0.5873414","0.5871622","0.5854899","0.58080405","0.5791255","0.57759464","0.57564527","0.5752586","0.57363343","0.5735664","0.57330346","0.5712254","0.570385","0.56848097","0.5677779","0.56718445","0.56668526","0.5664646","0.56614566","0.5661132","0.5645779","0.56301117","0.5625926","0.56174165","0.5601872","0.557818","0.5575695","0.55638134","0.55588216","0.5548876","0.55210346","0.5516589","0.551537","0.55054253","0.549772","0.54887986","0.54809946","0.5480354","0.5471207","0.5468815","0.54629487","0.5456285","0.5453852","0.542297","0.54160434","0.54105055","0.54104435","0.54084957","0.5408294","0.5398282","0.53966385","0.53937685","0.53860205","0.5382951","0.5382702","0.5382702"],"string":"[\n \"0.6931515\",\n \"0.68739617\",\n \"0.68509567\",\n \"0.68389434\",\n \"0.6793269\",\n \"0.6591011\",\n \"0.6537345\",\n \"0.6449486\",\n \"0.6414779\",\n \"0.6377539\",\n \"0.6353064\",\n \"0.63198406\",\n \"0.6311073\",\n \"0.6295751\",\n \"0.6291895\",\n \"0.6244799\",\n \"0.6227591\",\n \"0.6221736\",\n \"0.6218256\",\n \"0.62178695\",\n \"0.6205242\",\n \"0.614075\",\n \"0.6133338\",\n \"0.6115921\",\n \"0.61114675\",\n \"0.61104786\",\n \"0.6087212\",\n \"0.6075646\",\n \"0.6053927\",\n \"0.604407\",\n \"0.6043874\",\n \"0.60386133\",\n \"0.601983\",\n \"0.6008455\",\n \"0.60030925\",\n \"0.5970516\",\n \"0.5949743\",\n \"0.59447354\",\n \"0.59325963\",\n \"0.5929201\",\n \"0.5915176\",\n \"0.58811194\",\n \"0.5879404\",\n \"0.5873414\",\n \"0.5873414\",\n \"0.5871622\",\n \"0.5854899\",\n \"0.58080405\",\n \"0.5791255\",\n \"0.57759464\",\n \"0.57564527\",\n \"0.5752586\",\n \"0.57363343\",\n \"0.5735664\",\n \"0.57330346\",\n \"0.5712254\",\n \"0.570385\",\n \"0.56848097\",\n \"0.5677779\",\n \"0.56718445\",\n \"0.56668526\",\n \"0.5664646\",\n \"0.56614566\",\n \"0.5661132\",\n \"0.5645779\",\n \"0.56301117\",\n \"0.5625926\",\n \"0.56174165\",\n \"0.5601872\",\n \"0.557818\",\n \"0.5575695\",\n \"0.55638134\",\n \"0.55588216\",\n \"0.5548876\",\n \"0.55210346\",\n \"0.5516589\",\n \"0.551537\",\n \"0.55054253\",\n \"0.549772\",\n \"0.54887986\",\n \"0.54809946\",\n \"0.5480354\",\n \"0.5471207\",\n \"0.5468815\",\n \"0.54629487\",\n \"0.5456285\",\n \"0.5453852\",\n \"0.542297\",\n \"0.54160434\",\n \"0.54105055\",\n \"0.54104435\",\n \"0.54084957\",\n \"0.5408294\",\n \"0.5398282\",\n \"0.53966385\",\n \"0.53937685\",\n \"0.53860205\",\n \"0.5382951\",\n \"0.5382702\",\n \"0.5382702\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7045417"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88574,"cells":{"query":{"kind":"string","value":"Save a cropped version of the image."},"document":{"kind":"string","value":"def savecrop(image, fname, outpath, cropabsolute=None, cropfactors=[0.2, 0.2, 0.2, 0.2], preserve_name=False):\n if cropabsolute:\n if type(cropabsolute) != list:\n raise Exception(\"cropabsolute must be a list of length 4.\")\n else:\n if len(cropabsolute) !=4:\n raise Exception(\"Please provide 4 values corresponsindg to [left, upper, right, lower]\")\n cropbox = (int(cropabsolute[0]),\n int(cropabsolute[1]),\n int(image.width - cropabsolute[2]),\n int(image.height - cropabsolute[3])\n )\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"cropped{cropabsolute}\")\n else:\n fpath = genSavePath(outpath, fname)\n else:\n if type(cropfactors) != list:\n raise Exception(\"cropfactors must be a list of length 4.\")\n else:\n if len(cropfactors) !=4:\n raise Exception(\"Please provide 4 values corresponsindg to [left, upper, right, lower]\")\n cropbox = (int(image.width * cropfactors[0]),\n int(image.height * cropfactors[1]),\n int(image.width * (1-cropfactors[2])),\n int(image.height * (1-cropfactors[3]))\n )\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"cropped{cropfactors}\")\n else:\n fpath = genSavePath(outpath, fname)\n im = copy(image)\n im = im.crop(cropbox)\n try:\n im.save(fpath, subsample=\"keep\", qtables=image.quantization, optimize=True)\n\n except IOError as m:\n print( \"Crop({}) image creation failed for: {}. \\nReason:{}\".format(cropabsolute,cropfactors,fname,m))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def Save_Image_Crop(img, x, y, width, height, filename = None, path = 'Predictions'):\n img = img[y:y+height, x:x+width,:]\n\n if filename is not None:\n try: \n os.mkdir(path)\n except OSError as error: \n print('') \n fig, ax = plt.subplots(figsize=(18, 20))\n ax.imshow(img)\n plt.tight_layout()\n plt.savefig(path + '/' + filename + '_Crop.png')","def crop_image(self, image, top_left, bottom_right):\n # Crop image to include ROI using slicing. The first entry is the length and the second entry is the height.\n image_cropped = image[top_left[1]:bottom_right[1], top_left[0]:bottom_right[0]]\n \n # Save the cropped image\n cv2.imwrite(os.path.join(self.output_dir, f\"{self.input_image}_cropped.jpg\"), image_cropped)\n \n return image_cropped","def crop_image(self):\n\n image_data = Image.open(self.img_path)\n return image_data.crop(self.data_type)","def crop_and_save_single(img,crop_height,crop_width,image_save_dir,name,with_label=False):\n\n assert np.mod(img.shape[0], crop_height) == 0\n assert np.mod(img.shape[1], crop_width) == 0\n\n num_row = img.shape[0] #// crop_height\n num_col = img.shape[1] #// crop_width\n crop_img = np.zeros((crop_height, crop_width, 4))\n\n for row in range(0,num_row,crop_height):\n for col in range(0,num_col,crop_width):\n # print(\"row:{}, row+crop height:{}, j: {}, row+cropwidth:{}\".format(row,row+crop_height,col,col+crop_width))\n crop_img = img[row:row+crop_height, col:col+crop_width, :]\n\n # out_name = img_name[:-4] + '_' + \\\n out_name = name + '_' + \\\n str(num_col) + '_' + str(row).zfill(2) + \\\n '_' + str(col).zfill(2)+'.png'\n\n # if with_label:\n # label_name = \"/\"+str(index) + \"_\" + date_time + \"_label\"\n # crop_3_ch = crop_img[:,:,:3] # if cropping a labeled image\n # crop_label = crop_img[:,:,-1] # if cropping a labeled image\n # PIL_crop_label = Image.fromarray(crop_label.astype(np.uint8))\n # # PIL_crop_label.save(save_dir[1]+\"_label_\"+out_name) # if cropping a labeled image\n\n PIL_crop = Image.fromarray(crop_img[:,:,:3].astype(np.uint8))\n # if with_label:\n # # return PIL_crop,PIL_crop_label\n # # return PIL_crop\n PIL_crop.save(image_save_dir+\"/\"+out_name)","def crop_image(input_image, output_image, start_x, start_y, width, height):\n box = (start_x, start_y, start_x + width, start_y + height)\n output_img = img.crop(box)\n output_img.save(output_image +\".png\")","def crop_object_from_image(saving_folder,root_folder_path,root_folder_name,row_info):\n class_name=row_info['class']\n file_id=row_info['file_id']\n img_type=row_info['type']\n xmin=row_info['x_min']\n xmax=row_info['x_max']\n ymin=row_info['y_min']\n ymax=row_info['y_max']\n\n\n origin_img_path=os.path.join(root_folder_path,root_folder_name,img_type,file_id+\".png\")\n crop_img_path=os.path.join(saving_folder,file_id+\"_\"+class_name+\".png\")\n\n origin_img=cv2.imread(origin_img_path)\n crop_img=origin_img[ymin:ymax-1,xmin:xmax-1]\n\n # If width or height only contain 1 pixel, do not crop.\n if xmax-xmin<=2 or ymax-ymin<=2:\n print(\"Only one pixel, pass!\")\n return 0\n # print(origin_img.shape)\n # print(xmin,xmax,ymin,ymax)\n # print(crop_img.shape)\n # print(crop_img_path)\n cv2.imwrite(crop_img_path,crop_img)","def _crop(self, fieldname, scale, box):\n croputils = IImageCroppingUtils(self.context)\n data = croputils.get_image_data(fieldname)\n\n original_file = StringIO(data)\n image = PIL.Image.open(original_file)\n image_format = image.format or self.DEFAULT_FORMAT\n\n cropped_image = image.crop(box)\n cropped_image_file = StringIO()\n cropped_image.save(cropped_image_file, image_format, quality=100)\n cropped_image_file.seek(0)\n\n croputils.save_cropped(fieldname, scale, cropped_image_file)\n\n # store crop information in annotations\n self._store(fieldname, scale, box)\n\n # Purge caches if needed\n notify(Purge(self.context))","def crop_image(inputimage, folder, newimgname, xtop=0, ytop=64, xbottom=512, ybottom=448):\n\timg = Image.open(folder + os.sep + inputimage)\n\timg = img.crop((xtop, ytop, xbottom, ybottom))\n\timg.save(folder + os.sep + newimgname, 'PNG')","def crop_image(image_to_crop, year):\r\n\timg = Image.open(image_to_crop)\r\n\t#The dimensions of just the US in the image\r\n\timg = img.crop((80, 240, 800, 615))\r\n\r\n\tfile_destination = \"images/cropped_images/\" + str(year) + \".png\"\r\n\r\n\timage_file = open(file_destination, 'wb')\r\n\timg.save(image_file, 'png')\r\n\timage_file.close()","def crop_image(img, output_path):\n old_im = Image.open(img).convert('L')\n img_data = np.asarray(old_im, dtype=np.uint8) # height, width\n nnz_inds = np.where(img_data!=255)\n if len(nnz_inds[0]) == 0:\n old_im.save(output_path)\n return False\n\n y_min = np.min(nnz_inds[0])\n y_max = np.max(nnz_inds[0])\n x_min = np.min(nnz_inds[1])\n x_max = np.max(nnz_inds[1])\n old_im = old_im.crop((x_min, y_min, x_max+1, y_max+1))\n old_im.save(output_path)\n return True","def generate(self, save=True):\n stretched_photo, crop_box = self._generate_img()\n\n # set crop_box to (0,0,0,0) if photo not cropped\n if not crop_box:\n crop_box = 0, 0, 0, 0\n\n self.crop_left, self.crop_top, right, bottom = crop_box\n self.crop_width = right - self.crop_left\n self.crop_height = bottom - self.crop_top\n\n self.width, self.height = stretched_photo.size\n\n f = BytesIO()\n imgf = (self.photo._get_image().format or\n Image.EXTENSION[path.splitext(self.photo.image.name)[1]])\n\n stretched_photo.save(f, format=imgf, quality=self.format.resample_quality)\n f.seek(0)\n\n self.image.save(self.file(), ContentFile(f.read()), save)","def corp_image(self):\n try:\n # Open image\n image_to_crop = Image.open(self.captcha_image_filename, 'r')\n # Crop image\n image = image_to_crop.crop((-1, 8, 65, 22))\n # Save image\n image.save(self.cropped_captcha_filename)\n except UnidentifiedImageError as error:\n raise(error)","def create_clipping(request):\n if request.method == 'POST':\n image = request.POST.get('image')\n\n # check if the blanked image should be saved to the backend\n if request.POST.get('save_clipping') in ['false', False]:\n save = False\n else:\n save = True\n\n selection = {\n 'id': int(request.POST.get('selection[id]')),\n 'x': int(round(float(request.POST.get('selection[x]')))),\n 'y': int(round(float(request.POST.get('selection[y]')))),\n 'width': int(round(float(request.POST.get('selection[width]')))),\n 'height': int(round(float(request.POST.get('selection[height]')))),\n 'full_width': int(round(float(request.POST.get('selection[full_width]')))),\n 'full_height': int(round(float(request.POST.get('selection[full_height]'))))\n }\n\n # get the image id, the model object and the selection from the model\n edit_url = request.POST.get('edit_url')\n image_id = int(edit_url.split(\"/\")[-2])\n image_object = CustomImage.objects.get(id=image_id)\n original_selection = image_object.selections\n\n reseized_image = image_object.resize_url\n\n if selection['id'] == -1: # no selection -> use the whole image\n cropped_image = reseized_image\n else: # a specific selecion is used -> get the cropped image and selecion attributes\n image_object = CroppedImage.objects.get(id=selection['id'])\n cropped_image = original_selection[unicode(request.POST.get('selection[id]'))][\"url\"]\n\n # calculate the new blanking mask\n mask = get_mask_from_image(image, selection, cropped_image, save, image_object)\n\n # stream the new mask to the output\n stream = BytesIO()\n flat_mask = []\n for line in mask:\n flat_mask.extend(line)\n np.savetxt(stream, flat_mask, fmt=\"%u\", delimiter=', ', newline=', ')\n stream.seek(0)\n return HttpResponse(stream.read())\n\n return HttpResponse(\n json.dumps({\"nothing to see\": \"this isn't happening\"}),\n content_type=\"application/json\"\n )","def savePhoto(self, path):\n if self.original_image and path:\n cv2.imwrite(path, self.original_image)","def crop_image (filename):\n from PIL import Image\n image = Image.open(filename)\n for edge in 'NSWE':\n image = _crop(image, edge)\n image.save(filename)","def crop(self, *args, **kwargs):\n return _image.image_crop(self, *args, **kwargs)","def crop(original_img, coordinates, destination):\n image = cv2.imread(original_img)\n cropped = image.copy()\n if coordinates is None or len(coordinates) == 0:\n cv2.imwrite(destination, cropped)\n else:\n cnt = np.array(coordinates)\n cropped = four_point_transform(image, cnt)\n cv2.imwrite(destination, cropped)","def crop(self, coords):\n pass","def crop(self):\n\n return self.image.crop(self.x, self.y, self.width(), self.height(), centered = True)","def save(self, filename):\n print(\"Saving...\", end=\"\\r\")\n canvas = self.canvas[self.N:self.S,self.W:self.E]\n cv2.imwrite(\"./Output/\"+filename, canvas)\n print(\"Saved:\",filename)","def set_cropping(self, crop=True):\n self._crop = crop\n self._final = None # Force rebuild","def test_crop(self):\r\n u = Uploader()\r\n size = (100, 100)\r\n im = Image.new('RGB', size)\r\n folder = tempfile.mkdtemp()\r\n u.upload_folder = folder\r\n im.save(os.path.join(folder, 'image.png'))\r\n coordinates = (0, 0, 50, 50)\r\n file = FileStorage(filename=os.path.join(folder, 'image.png'))\r\n with patch('pybossa.uploader.Image', return_value=True):\r\n err_msg = \"It should crop the image\"\r\n assert u.crop(file, coordinates) is True, err_msg\r\n\r\n with patch('pybossa.uploader.Image.open', side_effect=IOError):\r\n err_msg = \"It should return false\"\r\n assert u.crop(file, coordinates) is False, err_msg","def save(\n self,\n output_path: str,\n show_confidence: bool = True,\n ) -> None:\n image = self.draw(show_confidence=show_confidence)\n save_image(image=image, path=output_path)","def _generate_crop(self):\n if self.box_drawn == True:\n if (self.cd_pic_num != -1) & (self.cd_crop_num == 1):\n self.communicator.generate_crop(picture_num=self.cd_pic_num, \\\n xa=self.xa, ya=self.ya, xb=self.xb, yb=self.yb)\n else:\n print \"ERROR: can only generate a new crop from a thumbnail\"\n else:\n print \"ERROR: please select an area to generate a crop from\"","def save_image(path, image): \n if len(image.shape) == 4:\n image = image.reshape((image.shape[1], image.shape[2], image.shape[3]))\n image = np.clip(image * 255.0, 0, 255).astype(np.uint8)\n skimage.io.imsave(path, image)","def crop(img, x, y, w, h):\n check_type(img)\n return img.crop((x, y, x + w, y + h))","def save_as(self, filename):\n opencv.imwrite(filename, self.img)","def crop_image(img):\n gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)\n _, threshed = cv.threshold(gray, 240, 255, cv.THRESH_BINARY_INV)\n\n kernel = cv.getStructuringElement(cv.MORPH_ELLIPSE, (11, 11))\n morphed = cv.morphologyEx(threshed, cv.MORPH_CLOSE, kernel)\n\n cnts = cv.findContours(morphed, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)[-2]\n cnt = sorted(cnts, key=cv.contourArea)[-1]\n\n x, y, w, h = cv.boundingRect(cnt)\n dst = img[y:y+h, x:x+w]\n cv.imwrite(\"001.png\", dst)\n return dst","def save_crops(self, workspace):\n objects_name = self.objects_name.value\n objects = workspace.object_set.get_objects(objects_name)\n bit_depth = self.bit_depth.value\n if self.input_type == IF_IMAGE:\n image_name = self.image_name.value\n image = workspace.image_set.get_image(image_name)\n pixels = image.pixel_data\n elif self.input_type == IF_OBJECTS:\n obj_name = self.input_object_name.value\n inp_obj = workspace.object_set.get_objects(obj_name)\n pixels = inp_obj.get_segmented()\n else:\n raise (\"invalid choice of input\")\n\n filename = self.get_filename(workspace)\n object_extension = self.object_extension.value\n if filename is None: # failed overwrite check\n return\n\n slices = ndi.find_objects(objects.segmented)\n slices, labels = zip(\n *[(s, label) for label, s in enumerate(slices) if s is not None]\n )\n\n ext_slices = [\n self._extend_slice_touple(\n sl, object_extension, [pixels.shape[0], pixels.shape[1]]\n )\n for sl in slices\n ]\n out_folder = os.path.dirname(filename)\n basename = os.path.splitext(os.path.basename(filename))[0]\n # the stack for imctools needs to be cxy, while it is xyc in cp\n if len(pixels.shape) == 2:\n stack = pixels.reshape([1] + list(pixels.shape))\n else:\n stack = np.rollaxis(pixels, 2, 0)\n\n # fix the dtype\n if bit_depth == BIT_DEPTH_8:\n stack = skimage.util.img_as_ubyte(stack)\n elif bit_depth == BIT_DEPTH_16:\n stack = skimage.util.img_as_uint(stack)\n elif bit_depth == BIT_DEPTH_FLOAT:\n stack = skimage.util.img_as_float(stack).astype(np.float32)\n\n self._save_object_stack(out_folder, basename, stack, ext_slices, labels)\n self.save_filename_measurements(workspace)\n if self.show_window:\n workspace.display_data.wrote_image = True","def crop_image(self, img):\n img.crop_image(self._center, 1.1 * self._radius)","def crop(image, dimX, dimY):\n # TODO\n return image","def save_and_return_cropped(image_as_array, imagefolder_new, imagetype_new, imagename):\n\n # Check if there is a section of the row that is 90% non-white\n def half_row_nonwhite(row, verbose=False):\n nonwhite_in_a_row_ratio = 0\n white_in_a_row_ratio = 0\n for pixel in row:\n if np.sum(pixel) < 255 * row.shape[1]:\n nonwhite_in_a_row_ratio += 1 / row.shape[0]\n elif white_in_a_row_ratio < 0.05:\n nonwhite_in_a_row_ratio += 1 / row.shape[0]\n white_in_a_row_ratio += 1 / row.shape[0]\n else:\n nonwhite_in_a_row_ratio = 0\n white_in_a_row_ratio = 0\n if nonwhite_in_a_row_ratio > 0.5:\n return True\n return False\n\n # Calculate start and end row (or col)\n def start_and_end(image_as_array):\n start, end = 0, 0\n for r in range(image_as_array.shape[0]):\n sufficient_contrast = (\n np.abs(\n int(np.sum(image_as_array[r])) - int(np.sum(image_as_array[r + 1]))\n )\n > 0.3 * 255 * image_as_array.shape[1] * image_as_array.shape[2]\n )\n if sufficient_contrast:\n if start == 0 and half_row_nonwhite(image_as_array[r + 1]):\n start = r + 1\n continue\n if start > 0 and half_row_nonwhite(image_as_array[r]):\n end = r + 1\n break\n return start, end\n\n y1, y2 = start_and_end(image_as_array)\n x1, x2 = start_and_end(np.swapaxes(image_as_array, 0, 1))\n cropped_image_as_array = image_as_array[y1:y2, x1:x2, :]\n\n # Save cropped image\n FILEPATH_cropped = imagefolder_new + imagename.split(\".\")[0] + imagetype_new\n Image.fromarray(cropped_image_as_array).save(FILEPATH_cropped)\n return cropped_image_as_array","def slide_crop(img, img_meta, model_cfg, save_dir):\r\n ori_shape = img_meta[0]['ori_shape']\r\n stem = Path(img_meta[0]['ori_filename']).stem\r\n save_dir = Path(save_dir)\r\n save_dir.mkdir(parents=True, exist_ok=True)\r\n\r\n h_stride, w_stride = model_cfg.test_cfg.stride\r\n h_crop, w_crop = model_cfg.test_cfg.crop_size\r\n batch_size, _, h_img, w_img = img.size()\r\n h_grids = max(h_img - h_crop + h_stride - 1, 0) // h_stride + 1\r\n w_grids = max(w_img - w_crop + w_stride - 1, 0) // w_stride + 1\r\n\r\n cnt = 0\r\n for h_idx in range(h_grids):\r\n for w_idx in range(w_grids):\r\n y1 = h_idx * h_stride\r\n x1 = w_idx * w_stride\r\n y2 = min(y1 + h_crop, h_img)\r\n x2 = min(x1 + w_crop, w_img)\r\n y1 = max(y2 - h_crop, 0)\r\n x1 = max(x2 - w_crop, 0)\r\n crop_img = img[:, :, y1:y2, x1:x2]\r\n \r\n cnt += 1\r\n msg1 = f'{x1},{y1},{x2},{y2}'\r\n msg2 = f'{ori_shape[0]},{ori_shape[1]},{ori_shape[2]}'\r\n msg3 = f'{batch_size},{h_img},{w_img}'\r\n bin_path = save_dir/f'{stem}-{\"-\".join([msg1, msg2, msg3])}.bin'\r\n crop_img.numpy().astype(np.float32).tofile(bin_path)\r\n\r\n return cnt","def crop (*args, **kwargs):\n return compute('crop', inputs=list(args), args=kwargs)","def crop(image, size):\n size = size.split('x')\n (root, name, ext) = split_filepath(image.path)\n filename = scale_image(image.path, (int(size[0]), int(size[1])), 'crop')\n return '/%s/%s' % (os.path.abspath(root).replace('%s/' % os.path.abspath(settings.BASE_PATH), ''), filename)","def crop(img, i, j, h, w):\n return img.crop((j, i, j + w, i + h))","def crop(img, i, j, h, w):\n return img.crop((j, i, j + w, i + h))","def __call__(self, img):\n image_width, image_height = img.size\n image_short = min(image_width, image_height)\n\n crop_size = float(self.imgsize) / (self.imgsize + 32) * image_short\n\n crop_height, crop_width = crop_size, crop_size\n crop_top = int(round((image_height - crop_height) / 2.))\n crop_left = int(round((image_width - crop_width) / 2.))\n return img.crop((crop_left, crop_top, crop_left + crop_width, crop_top + crop_height))","def __call__(self, img):\n image_width, image_height = img.size\n image_short = min(image_width, image_height)\n\n crop_size = float(self.imgsize) / (self.imgsize + 32) * image_short\n\n crop_height, crop_width = crop_size, crop_size\n crop_top = int(round((image_height - crop_height) / 2.))\n crop_left = int(round((image_width - crop_width) / 2.))\n return img.crop((crop_left, crop_top, crop_left + crop_width, crop_top + crop_height))","def crop_save( img_path_filename, lines_boxes, lines_texts, lines_probs, filename, basename, output_dir_name ):\n\t# Read the image\n\timage = Image.open( img_path_filename )\n\t# Get image's size\n\twidth, height = image.size\n\n\ti = 0\n\ttext_local = \"\"\n\ttext_global = \"\"\n\twhile i < len(lines_boxes):\n\t\t##################################################################################################\n\t\t# Left Upper Corner\n\t\tx1 = lines_boxes[i][0]\n\t\tx1 = x1 - 8\n\t\tif x1 < 0:\n\t\t\tx1 = 0\n\n\t\ty1 = lines_boxes[i][1]\n\t\ty1 = y1 - 1\n\t\tif y1 < 0:\n\t\t\ty1 = 0\n\n\t\t# Right Lower Corner\n\t\tx2 = lines_boxes[i][2]\n\t\tx2 = x2 + 10\n\t\tif x2 > (width - 1):\n\t\t\tx2 = width - 1\n\n\t\ty2 = lines_boxes[i][3]\n\t\ty2 = y2 + 1\n\t\tif y2 > (height - 1):\n\t\t\ty2 = height - 1\n\n\t\t# Crop the block and save it\n\t\tn_line = \"%03d\" % (i+1)\n\t\tline_filename = output_dir_name + \"/\" + basename + \"_\" + n_line + \".jpg\"\t\t\n\n\t\timg_cropped = image.crop( (x1, y1, x2, y2) )\n\t\timg_cropped.save( line_filename, 'JPEG', quality = 100 )\n\n\t\t##################################################################################################\n\t\t# Create the information about the cropped line for the local and global text files\n\t\ttext_line = basename + \"_\" + n_line + \".jpg\\t\" + str(x1) + \"\\t\" + str(y1) + \"\\t\" + str(x2) + \"\\t\" + str(y2) + \"\\t\" + ''.join(lines_texts[i]) + \"\\n\"\n\t\ttext_local += text_line\n\t\ttext_global += filename + \"\\t\" + text_line\n\n\t\t##################################################################################################\n\t\t# Creation of the text and probability file for each line\n\t\tj = 0\n\t\tcontent_text_file = \"\"\n\t\tcontent_prob_file = \"\"\n\t\twhile j<len(lines_texts[i]):\n\t\t\tcontent_text_file += lines_texts[i][j]\n\t\t\tcontent_prob_file += lines_texts[i][j] + '\\t' + str(lines_probs[i][j]) + '\\n'\n\t\t\tj = j + 1\n\t\t# Write to disk the text file\n\t\ttext_filename = output_dir_name + \"/\" + basename + \"_\" + n_line + \".txt\"\n\t\twith open( text_filename, \"w+\" ) as f_text:\n\t\t\tf_text.write( content_text_file )\n\t\t# Write to disk the probabilities file\n\t\tprob_filename = output_dir_name + \"/\" + basename + \"_\" + n_line + \".prob\"\n\t\twith open( prob_filename, \"w+\" ) as f_prob:\n\t\t\tf_prob.write( content_prob_file )\n\n\t\ti = i + 1\n\n\treturn( text_local, text_global )","def save_detection(self, image):\n\t\timg = self.visualize_detection(image)\n\t\timg = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)\n\t\tcv2.imwrite(f'{SAVE_PATH}{self.clip}{self.num_save}.jpg', img)","def basic_crop(data):\n return data['crop'];","def save_image(self):\n self.save()","def crop_image(image):\r\n return image[40:-20, :]","def display_cropped_img(i):\n image = PIL.Image.open(testing_img_paths[i])\n image = image.crop(box=(313,99,825,611))\n image = image.resize((256,256))\n display(image)","def save(self, filepath):\n self.drawer.flush()\n self.img.save(filepath)","def __crop(img, pos, size):\n ow, oh = img.size\n x1, y1 = pos\n tw = th = size\n if (ow > tw or oh > th):\n return img.crop((x1, y1, x1 + tw, y1 + th))\n return img","def crop(img, top, left, width, height):\n if not all([isinstance(x, int) for x in (top, left, width, height)]):\n raise ValueError(\"params should be integer!\")\n if (width > img.shape[0] or height > img.shape[1]):\n raise ValueError(\"the output imgage size should be small than input image!!!\")\n\n if len(img.shape) == 2:\n img_height, img_width = img.shape\n else:\n img_height, img_width, _ = img.shape\n right = img_width - (left + width)\n bottom = img_height - (top + height)\n if len(img.shape) == 2:\n img_croped = util.crop(img,((top,bottom),(left,right)))\n else:\n img_croped = util.crop(img,((top,bottom),(left,right),(0,0)))\n\n return img_croped","def _save(filename, img):\n if not os.path.exists(OUTPUT_DIR):\n os.makedirs(OUTPUT_DIR)\n # filename = filename+'.png'\n filename = os.path.join(OUTPUT_DIR, filename)\n # print(filename, img.shape)\n cv.imwrite(filename, img)","def save(self, path):\n (folder, filename) = os.path.split(path)\n if not filename:\n filename = _clean_filename(self.name)\n path = os.path.join(folder, filename)\n return self.image.save(path)","def saveView(self, filename):\n\n pixmap = self.grab();\n ok = pixmap.save(filename)\n if not ok:\n raise IOError('Unable to save image ' + filename)","def save_Image(self, path, name, array):\n # Resize into a 2D array\n shaped_arr = np.reshape((array * 255).astype('uint8'),\n (self.im_size, self.im_size))\n cv.imwrite(\"%s/missed_img%s.jpg\" % (path, name),shaped_arr)","def save_overlay(self, path):\n if self.im is None:\n raise ValueError('You didnt call the MaskOverlay, therefore there is no image in memory')\n im_masked = img_as_ubyte(self.im_masked)\n imsave(path, im_masked)","def save_image(filename, image):\n im = cv2.resize(image, None, fx=SCALE_DOWN, fy=SCALE_DOWN)\n cv2.imwrite(os.path.join(OUT_DIR, filename), im)","def run_crops(self, workspace):\n #\n # First, check to see if we should save this image\n #\n self.save_crops(workspace)\n return True","def set_crop(self, crop):\n self.crop = crop","def crop(src_path, out_path, bbox_geometry, bbox_crs):\n\n # validate area of interest\n\n\n # load imagery\n satdata = rasterio.open(src_path)\n\n # grab crs\n crs = satdata.meta['crs']\n crs = str(crs).split(':')[-1]\n\n # check crs\n if(crs != bbox_crs):\n raise Exception(f'Imagery & bounding box crs mismatch ({crs}, {bbox_crs})')\n\n # apply mask with crop=True to crop the resulting raster to the AOI's bounding box\n clipped, transform = mask(satdata, aoi, crop=True)\n\n # Using a copy of the metadata from our original raster dataset, we can write a new geoTIFF\n # containing the new, clipped raster data:\n meta = satdata.meta.copy()\n\n # update metadata with new, clipped mosaic's boundaries\n meta.update(\n {\n \"transform\": transform,\n \"height\":clipped.shape[1],\n \"width\":clipped.shape[2]\n }\n )\n\n # write the clipped-and-cropped dataset to a new GeoTIFF\n with rasterio.open(out_path, 'w', **meta) as dst:\n dst.write(clipped)","def save(self, filename):\n self.image.save(filename, self.options.img_format)","def crop_img(image, bound):\n scale = 1.01 # 1%\n return image.crop((bound.vertices[0].x // scale, bound.vertices[0].y // scale,\n int(bound.vertices[2].x * scale), int(bound.vertices[2].y) * scale))","def crop_images(row, crop_path):\n def crop(im, box, square=True):\n \"\"\" box: list, [x_left, y_bottom, x_l + w, y_b + h]\n \"\"\"\n def pad_square(box):\n \"\"\" If box is a rectangle, expand it to a square.\n \"\"\"\n x, y, xw, yh = box\n w = xw-x\n h = yh-y\n if w < h:\n w = h\n elif h < w:\n h = w\n return [x, y, x+w, y+h]\n if square:\n box = pad_square(box)\n x, y, xw, yh = box\n return im[y:yh, x:xw]\n im = tiffread(row['Image'])\n im_crop = crop(im, row['Cropbox'], square=True)\n crop_file = os.path.join(crop_path, row['Name'], row['UID'])\n tiffwrite(crop_file, im_crop)","def img_save(self):\n file_name, extension = return_folder_file_extension(self.img_name)[1:]\n image_name_save = \"%s_D=%s_Rs=%s_size=%s_offset=%i%s\" % (file_name, self.D, self.Rs, self.axe_X, self.offset_X+self.offset_X2, extension)\n\n if self.img2 is not None:\n self.img2.save(image_name_save)\n print(\"Saved \"+image_name_save)\n else:\n print(\"No image to save\")","def save_processed_image(self, filename=None):\n if filename is None:\n tag = self.get_alert_objects_list(\"_\")\n filename = os.path.join(\n config.IMAGE_SAVE_PATH, \"%s_%s_%s_%s.jpg\" %\n (time.strftime(\"%Y-%m-%d_%H.%M.%S\", time.localtime(self.timestamp)),\n self.camera_name, self.detection_model, tag))\n # print(\"Using filename %s\" % filename)\n ret = cv2.imwrite(filename, self.processed_image)\n self.processed_file = filename\n return ret","def uncrop( self ):\n \n if self._cropped:\n self._reset_bounds()\n self._cropped = False\n else:\n print(\"This data cube was not cropped\")","def crop(self, image):\n\t\treturn image.copy()[self.ymin:self.ymax,self.xmin:self.xmax]","def save_pca(self, filepath):\n mean_beam, principal_components, variances = self.pca()\n image_shape = np.array(self.image_shape)\n with open(filepath, 'wb') as f:\n np.save(f, image_shape)\n np.save(f, mean_beam)\n np.save(f, principal_components)\n np.save(f, variances)\n np.save(f, self.mask)","def save_image(self, filename):\n raster.save_image(filename, self.image, self.metadata)","def imsave_clip(outfile,img):\n img = img_as_float(img).clip(0.,1.)\n io.imsave(outfile,img)","def save_original_image(slide, heatmapPath):\n dims = slide.dims\n img = slide.image.read_region((0,0), len(dims)-1, dims[-1])\n img.save(os.path.join(heatmapPath, slide.id) + \".png\")","def _crop_write_image(self, inroot, images, outroot):\n for image in images:\n inimage_path = osp.join(inroot, image)\n cvimg = cv2.imread(inimage_path)\n cvimg = cvimg[60:-30, 25:-25]\n h, w, _ = cvimg.shape\n assert h == w == 128\n outimage_path = osp.join(outroot, image)\n cv2.imwrite(outimage_path, cvimg)\n print(outimage_path)","def crop(self, bbox):\n if self.__huge: # image is huge and not totally in RAM\n band = bbox[3] - bbox[1] # width of the tile band\n self.__tile[1][3] = band # set the tile height\n self.__tile[2] = self.__offset + self.imwidth * bbox[1] * 3 # set offset of the band\n self.__image.close()\n self.__image = Image.open(self.path) # reopen / reset image\n self.__image.size = (self.imwidth, band) # set size of the tile band\n self.__image.tile = [self.__tile]\n return self.__image.crop((bbox[0], 0, bbox[2], band))\n else: # image is totally in RAM\n return self.__pyramid[0].crop(bbox)","def Crop_Image(img, mask, x, y, width, height):\n img = img[y:y+height, x:x+width,:]\n mask = mask[y:y+height, x:x+width,:]\n return img, mask","def get_crop(self):\n if self.cropping_method == self.CROP_NONE:\n self.autocrop()\n return '{h}% {v}%'.format(h=self.from_left, v=self.from_top)","def crop_img(img_path, tile_x, tile_y , save_path):\n # make directory to save tiles\n im = Image.open(img_path)\n try:\n os.mkdir(img_path)\n except OSError:\n print(\"Creation of the directory %s failed\" % img_path)\n else:\n print(\"Successfully created the directory %s \" % img_path)\n \n # conver image to numpyarray and extract image height and width\n img_arr = np.array(im)\n shape = img_arr.shape\n img_y = shape[0]\n img_x = shape[1]\n\n #calculate point to crop\n xy_points = calcul_xy_array(img_x, img_y, tile_x, tile_y)\n\n for x, y in xy_points:\n \n #extract pixels fro array\n A = img_arr[y: y + tile_y, x: x + tile_x, :]\n \n #convert array back to img\n im = Image.fromarray(A)\n\n\n #saving the image in formate:\n #Original_img_name + \"__\" + tile_x_cor \"_\" + tile_y_cor \"__\"+\n #Original_img_height + \"_\" + Original_img_width\n name = (img_path.split('\\\\'))[-1]\n file_name = str(name) + \"__\" + str(x) + \"_\" + str(y) + \"__\" + str(\n img_x) + \"_\" + str(img_y) + \".tif\"\n\n path = save_path + '\\\\' + file_name\n im.save(path)","def crop(im, config):\n\n src_width, src_height = im.size\n\n src_ratio = float(src_width) / float(src_height)\n dst_ratio = float(config['width']) / float(config['height'])\n\n if dst_ratio < src_ratio:\n crop_height = src_height\n crop_width = crop_height * dst_ratio\n x_offset = int(float(src_width - crop_width) / 2)\n y_offset = 0\n else:\n crop_width = src_width\n crop_height = crop_width / dst_ratio\n x_offset = 0\n y_offset = int(float(src_height - crop_height) / 3)\n\n im = im.crop((\n x_offset,\n y_offset,\n x_offset + int(crop_width),\n y_offset + int(crop_height),\n ))\n\n return im.resize(\n (config['width'], config['height']),\n ANTIALIAS,\n )","def doCrop(image, x, y, w, h):\n\tcrop_height = int((config.FACE_HEIGHT / float(config.FACE_WIDTH)) * w)\n\tmidy = y + h/2\n\ty1 = max(0, midy-crop_height/2)\n\ty2 = min(image.shape[0]-1, midy+crop_height/2)\n\treturn image[y1:y2, x:x+w]","def savePicture(self):\n self.file_name = QtGui.QFileDialog.getSaveFileName(self, \n \"Save as... (specify extension)\", \"\")\n cv2.imwrite(self.file_name, self.frame)","def avatar_crop(request, id=None):\n if id:\n avatar = get_object_or_404(Avatar, id=id, user=request.user)\n else:\n avatar = get_object_or_404(Avatar, user=request.user, primary=True)\n\n if (avatar.avatar.width<=avatar.avatar.height):\n result = \"width\"\n else:\n result = \"height\"\n\n if not request.method == \"POST\":\n form = AvatarCropForm()\n else:\n try:\n orig = avatar.avatar.storage.open(avatar.avatar.name, 'rb').read()\n image = Image.open(StringIO(orig))\n except IOError:\n return\n form = AvatarCropForm(image, request.POST)\n\n if form.is_valid():\n top = int(form.cleaned_data.get('top'))\n left = int(form.cleaned_data.get('left'))\n right = int(form.cleaned_data.get('right'))\n bottom = int(form.cleaned_data.get('bottom'))\n\n box = [ left, top, right, bottom ]\n (w, h) = image.size\n if result==\"width\":\n box = map(lambda x: x*h/AVATAR_CROP_MAX_SIZE, box)\n else:\n box = map(lambda x: x*w/AVATAR_CROP_MAX_SIZE, box)\n\n image = image.crop(box)\n if image.mode != 'RGB':\n image = image.convert('RGB')\n\n thumb = StringIO()\n image.save(thumb, AVATAR_THUMB_FORMAT, quality=AVATAR_THUMB_QUALITY)\n thumb_file = ContentFile(thumb.getvalue())\n\n base_name, ext = os.path.splitext(avatar.avatar.name)\n thumb = avatar.avatar.storage.save(\"%s_cropped%s\" % (base_name, ext), thumb_file)\n Avatar.objects.filter(id=avatar.id).update(primary=False)\n new_avatar = Avatar(user=request.user, primary=True, avatar=thumb)\n new_avatar.save()\n messages.add_message(request, messages.INFO, _(\"Your new avatar has been saved successfully.\"))\n return HttpResponseRedirect(reverse(\"avatar_change\"))\n\n return render_to_response(\"avatar_crop/crop.html\", {\n 'AVATAR_CROP_MAX_SIZE': AVATAR_CROP_MAX_SIZE,\n 'dim': result,\n 'avatar': avatar,\n 'form': form\n }, context_instance=RequestContext(request))","def save_image(img, path):\n cv2.imwrite(path, img)","def save(self):\n img = Image.new(\"1\", (self.container.width, self.container.height))\n draw = ImageDraw.Draw(img)\n for item in self.items:\n draw.ellipse(item.box_coordinates(), fill=1)\n del draw\n img.save(\"plot.bmp\", \"bmp\")","def save_image(self):\n self.compressed_image_id = str(uuid.uuid4().hex)\n plot.imsave(\n str(\n self.compressed_image_id + \"{}\").format(\n \".png\"), self.compressed_image)\n\n if self.verbose:\n print(\n \"Compressed image saved at \" + (\n str(self.compressed_image_id + \"{}\").format(\".png\")))","def save(self, path):\n dirname = osp.dirname(osp.abspath(path))\n if not osp.isdir(dirname):\n os.mkdir(dirname)\n image = self.build()\n LOGGER.info(\"Save image '%s'\", path)\n image.save(path)\n return image","def save(self, path, filename=None, overwrite=False):\n \n if filename is None and self.metadata is None:\n raise ValueError(\"If the image has no 'metadata', you must specify a filename\")\n elif filename is not None:\n pass\n elif filename is None and self.metadata is not None:\n filename = os.path.basename(self.metadata[\"pfilename\"])\n \n full_image_path = os.path.join(path, filename)\n \n if overwrite and os.path.exists(full_image_path):\n os.remove(full_image_path)\n \n self.fits.writeto(full_image_path)","def resize_img(self,scale=1):\n reduced = self.image.reduce((scale,scale))\n reduced.save(\"../edited/{}\".format(self.image.filename))\n\n reduced = Image.open(\"../edited/{}\".format(self.image.filename))\n return reduced","def crop( self, remove_bad=True, check_coverage=True ):\n \n if not self._cropped:\n cropper = image_cube_cropper( check_coverage=check_coverage ).fit( self )\n\n # remove corrupt images if desired \n if remove_bad:\n self._remove_steps( cropper.get_null_images() )\n self._remove_steps( cropper.get_corrupt_images() )\n\n # set new bounds and cropped cube indicator\n self._set_bounds( cropper.get_bounds() )\n self._cropped = True\n \n else:\n if ir.config.verbosity_level >= 1:\n print(\"This data cube has already been cropped\")","def observation(self, frame):\r\n if self.grayscale:\r\n frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)\r\n frame = cv2.resize(frame, (self.width, self.height), interpolation=cv2.INTER_AREA)\r\n crop_frame = frame[self.crop:, :]\r\n if self.grayscale:\r\n crop_frame = crop_frame[:,:, None]\r\n return crop_frame","def capture_image(self):\n ext = self.image_save_type.lower()\n\n if self.calibrating:\n print('calibrating')\n\n if ext == 'fits':\n self.save_fits()\n self._image_counter += 1\n else:\n img = self.original_image\n path = os.path.join(self.home, 'data')\n name = \"camtrak_frame_{}.png\".format(self._image_counter) \n fn = os.path.join(path, name)\n cv2.imwrite(fn, img)\n\n QtWidgets.QApplication.beep()\n self.statusBar().showMessage(f'Saved image to {fn}')\n self._image_counter += 1","def crop(image, countours, num_img, path_des):\n i = 0\n if len(countours) == 0: # we d'ont fine a contour save the all image\n path = path_des\n cv2.imwrite(os.path.join(path, 'Barcod') + '_' + 'num' + str(i) + '_' + 'img' + num_img, image)\n i = i + 1\n for cntr in countours:\n # creates an approximate rectangle around contour\n x, y, w, h = cv2.boundingRect(cntr)\n of = 50\n # pulls crop out of the image based on dimensions\n # new_img = image[y-of:y + h+of, x-of:x + w+of]\n new_img = offset(image, y - of, y + h + of, x - of, x + w + of)\n\n path = path_des\n cv2.imwrite(os.path.join(path, 'Barcod') + '_' + 'num' + str(i) + '_' + 'img' + num_img, new_img)\n\n i = i + 1","def crop(img, top, left, height, width):\n if not _is_numpy(img):\n raise TypeError('img should be Numpy Image. Got {}'.format(type(img)))\n\n return img[top:top + height, left:left + width]","def Crop(self, path):\n global img, crop\n self.window_created = True\n self.path = path\n self.crop = tk.Toplevel(None)\n self.crop.protocol(\"WM_DELETE_WINDOW\", self.CloseCropWindow)\n \n# tk.Label(crop, text=self.path).grid()\n self.crop.title(\"Crop Window\")\n #load image specified in path var\n img = Image.open(self.path)\n img = ImageTk.PhotoImage(img)\n #print img.height()\n #create canvas to show image\n global crop_canvas \n crop_canvas = tk.Canvas(master=self.crop, bg='#000',\n width=img.width(), height=img.height())\n \n crop_canvas.bind('<Button-1>', self.Btn1Pressed)\n crop_canvas.bind('<ButtonRelease-1>', self.Btn1Released)\n crop_canvas.bind('<B1-Motion>', self.Btn1Motion)\n \n \n crop_canvas.create_image(0,0,anchor=tk.NW, image=img)\n crop_canvas.image = img #keep image reference\n crop_canvas.grid(sticky=tk.NW)\n self.crop.focus_set()\n \n #btns for zoom functionality\n \"\"\"\n zoom_in = tk.Button(master=self.crop_canvas,text='+', anchor=tk.NE,\n command=self.ZoomIn)\n zoom_out = tk.Button(master=self.crop_canvas,text='-',anchor=tk.NE, \n command=self.ZoomOut)\n \"\"\"\n #zoom_in.place(x=img.width()-14,y=0)\n #zoom_out.place(x=img.width()-14,y=30)","def img_save(name,img):\n cv2.imwrite(name,img)","def save(self, **kwargs):\n self.remove_file()\n if not self.image:\n self.generate(save=False)\n else:\n self.image.name = self.file()\n super(FormatedPhoto, self).save(**kwargs)","def saveimage(self):\n if self.saveimageButton.isChecked():\n self.save = True\n self.channelsOpen()\n self.movetoStart()\n self.saveimageButton.setText('Abort')\n self.guarda = np.zeros((self.numberofPixels, self.numberofPixels))\n self.liveviewStart()\n\n else:\n self.save = False\n print(\"Abort\")\n self.saveimageButton.setText('reintentar Scan and Stop')\n self.liveviewStop()","def crop_img(img_path, lbl_path, output_path):\n img_file_list = os.listdir(img_path)\n lbl_file_list = os.listdir(lbl_path)\n\n img_endswith = img_file_list[0].split(\".\")[-1]\n cnt = 1\n for lbl_file in lbl_file_list:\n coords = get_coords_from_label(os.path.join(lbl_path, lbl_file))\n for coord in coords:\n xmin, ymin, xmax, ymax = coord\n\n img = cv2.imread(os.path.join(img_path, lbl_file.replace(\"xml\", img_endswith)))\n cropped = img[ymin:ymax, xmin:xmax]\n\n output_file = os.path.join(output_path, \"{}.{}\".format(cnt, img_endswith))\n cv2.imwrite(output_file, cropped)\n cnt += 1","def _crop_image(image: Image, w: int, h: int, area_to_crop: Tuple[int]) -> Image:\n expected_w = 480\n expected_h = 360\n if w != expected_w:\n print(\"Warning, image width:\", w, \"differs from expected width:\", expected_w)\n if h != expected_h:\n print(\"Warning, image height:\", h, \"differs from expected height:\", expected_h)\n\n cropped_image = image.crop(area_to_crop)\n w_cropped, h_cropped = cropped_image.size\n return cropped_image.resize((w_cropped, h_cropped))","def saveImage(self, event):\r\n fileWritten = self.image.writeFile()\r\n self.statusBar.SetStatusText(\"Saved {}\".format(fileWritten))","def save_file(camera, frame):\n save = input(\"Would you like to save your drawing? Enter yes or no \")\n if save == \"yes\" or save == \"y\" or save == \"ye\" or save == \"yes \": # accounting for typos\n name = input(\"What would you like to name your masterpiece? \")\n filename = 'images/' + name + '.png'\n cv2.imwrite(filename, cv2.flip(frame,1)) # saves the image as the last frame\n camera.release()\n pygame.quit()\n\n # reopen saved picture to display for user\n img = cv2.imread(filename, 1)\n b,g,r = cv2.split(img) # get b,g,r\n rgb_img = cv2.merge([r,g,b]) # convert from bgr colorspace to rgb\n crop_img = rgb_img[36:450, 0:600] # crop out the colorbar\n cv2.imshow(filename, crop_img)\n cv2.imwrite(filename, crop_img)\n cv2.waitKey(10000)\n cv2.destroyAllWindows()\n camera.release()\n pygame.quit() # cleanup the camera and close any open windows\n else:\n print(\"Thank you for trying CVPaint!\")\n pygame.quit()\n camera.release()\n cv2.destroyAllWindows()","def save_image(image, file_name):\n io.imsave(file_name,image)","def save_photo():\n save_name = filedialog.asksaveasfilename(initialdir=\"10.APOD Viewer/\", title=\"Save Image\", filetype=((\"JPEG\", \"*.jpg\"), (\"All Files\", \"*.*\")))\n img.save(save_name + \".jpg\")","def resize_and_crop(img, savePath, size, crop_type='middle'):\n\t# If height is higher we resize vertically, if not we resize horizontally\n\n\t# Get current and desired ratio for the images\n\timg_ratio = img.size[0] / float(img.size[1])\n\tratio = size[0] / float(size[1])\n\tprint \"img_ratio = \" + str(img_ratio) + \". ratio = \" + str(ratio)\n\t#The image is scaled/cropped vertically or horizontally depending on the ratio\n\tif ratio > img_ratio:\n\t\timg = img.resize((size[0], int(round(size[0] * img.size[1] / img.size[0]))),\n\t\t Image.ANTIALIAS)\n\t\t# Crop in the top, middle or bottom\n\t\tif crop_type == 'top':\n\t\t\tbox = (0, 0, img.size[0], size[1])\n\t\telif crop_type == 'middle':\n\t\t\tbox = (0, int(round((img.size[1] - size[1]) / 2)), img.size[0],\n\t\t int(round((img.size[1] + size[1]) / 2)))\n\t\telif crop_type == 'bottom':\n\t\t\tbox = (0, img.size[1] - size[1], img.size[0], img.size[1])\n\t\telse :\n\t\t\traise ValueError('ERROR: invalid value for crop_type')\n\t\tprint \"ratio > img_ratio. Cropping box: \"\n\t\tprint box\n\t\timg = img.crop(box)\n\telif ratio < img_ratio:\n\t\timg = img.resize((int(round(size[1] * img.size[0] / img.size[1])), size[1]),\n\t\t Image.ANTIALIAS)\n\t\t# Crop in the top, middle or bottom\n\t\tif crop_type == 'top':\n\t\t\tbox = (0, 0, size[0], img.size[1])\n\t\telif crop_type == 'middle':\n\t\t\tbox = (int(round((img.size[0] - size[0]) / 2)), 0,\n\t\t int(round((img.size[0] + size[0]) / 2)), img.size[1])\n\t\telif crop_type == 'bottom':\n\t\t\tbox = (img.size[0] - size[0], 0, img.size[0], img.size[1])\n\t\telse :\n\t\t\traise ValueError('ERROR: invalid value for crop_type')\n\n\t\tprint \"ratio < img_ratio. Cropping box: \"\n\t\tprint box\n\t\timg = img.crop(box)\n\telse :\n\t\tprint \"so i guess the ratios are the same?\"\n\t\timg = img.resize((size[0], size[1]),\n\t Image.ANTIALIAS)\n\t # If the scale is the same, we do not need to crop\n\tprint \"Saving thumb to \" + savePath\n\timg.save(savePath, \"JPEG\", quality=thumbCompressQual)","def resize_and_save(local_file,new_file,maxsize=None,maxh=None,maxw=None,crop=None):\n logging.debug(\"maxw = %s, maxsize=%s, crop=%s\" % (maxw,maxsize,crop))\n img = Image.open(local_file)\n width,height = img.size\n width,height = float(width), float(height)\n ratio = float(1)\n if crop is not None:\n size = float(maxsize)\n if width <= height and width > size:\n ratio = size/width\n elif height < width and height > size:\n ratio = size/height\n else: \n ratio = 1 # too small\n elif maxsize:\n size = float(maxsize)\n if width >= height and width > size:\n ratio = size/width\n elif height > width and height > size:\n ratio = size/height\n else: \n ratio = 1 # too small\n elif maxh:\n size = maxh\n if height > size:\n ratio = size/height\n else:\n # too small\n ratio = 1\n elif maxw:\n size = maxw\n if width > size:\n ratio = size/width\n else:\n # too small\n ratio = 1\n else:\n raise Exception(\"must specify max width, OR max size\")\n \n print(\"old: ratio = %s: size(x,y) = %s,%s\" % (ratio,width,height))\n height = int(height*ratio)\n width = int(width*ratio)\n print(\"new ratio = %s: size(x,y) = %s,%s\" % (ratio,width,height))\n img = img.resize((width, height),Image.ANTIALIAS)\n if crop is not None:\n log.debug(\"in crop %s\" % crop)\n crop = int(crop)\n if width > crop:\n amt = int((int(width) - crop)/2)\n img = img.crop((amt,0,amt + crop, crop))\n elif height > crop:\n amt = int((int(height) - crop)/2)\n img = img.crop((0,amt,crop,amt+crop))\n \n log.debug(\"saving new file %s\" % new_file)\n if img.mode != \"RGB\":\n img = img.convert(\"RGB\")\n img.save(new_file)"],"string":"[\n \"def Save_Image_Crop(img, x, y, width, height, filename = None, path = 'Predictions'):\\n img = img[y:y+height, x:x+width,:]\\n\\n if filename is not None:\\n try: \\n os.mkdir(path)\\n except OSError as error: \\n print('') \\n fig, ax = plt.subplots(figsize=(18, 20))\\n ax.imshow(img)\\n plt.tight_layout()\\n plt.savefig(path + '/' + filename + '_Crop.png')\",\n \"def crop_image(self, image, top_left, bottom_right):\\n # Crop image to include ROI using slicing. The first entry is the length and the second entry is the height.\\n image_cropped = image[top_left[1]:bottom_right[1], top_left[0]:bottom_right[0]]\\n \\n # Save the cropped image\\n cv2.imwrite(os.path.join(self.output_dir, f\\\"{self.input_image}_cropped.jpg\\\"), image_cropped)\\n \\n return image_cropped\",\n \"def crop_image(self):\\n\\n image_data = Image.open(self.img_path)\\n return image_data.crop(self.data_type)\",\n \"def crop_and_save_single(img,crop_height,crop_width,image_save_dir,name,with_label=False):\\n\\n assert np.mod(img.shape[0], crop_height) == 0\\n assert np.mod(img.shape[1], crop_width) == 0\\n\\n num_row = img.shape[0] #// crop_height\\n num_col = img.shape[1] #// crop_width\\n crop_img = np.zeros((crop_height, crop_width, 4))\\n\\n for row in range(0,num_row,crop_height):\\n for col in range(0,num_col,crop_width):\\n # print(\\\"row:{}, row+crop height:{}, j: {}, row+cropwidth:{}\\\".format(row,row+crop_height,col,col+crop_width))\\n crop_img = img[row:row+crop_height, col:col+crop_width, :]\\n\\n # out_name = img_name[:-4] + '_' + \\\\\\n out_name = name + '_' + \\\\\\n str(num_col) + '_' + str(row).zfill(2) + \\\\\\n '_' + str(col).zfill(2)+'.png'\\n\\n # if with_label:\\n # label_name = \\\"/\\\"+str(index) + \\\"_\\\" + date_time + \\\"_label\\\"\\n # crop_3_ch = crop_img[:,:,:3] # if cropping a labeled image\\n # crop_label = crop_img[:,:,-1] # if cropping a labeled image\\n # PIL_crop_label = Image.fromarray(crop_label.astype(np.uint8))\\n # # PIL_crop_label.save(save_dir[1]+\\\"_label_\\\"+out_name) # if cropping a labeled image\\n\\n PIL_crop = Image.fromarray(crop_img[:,:,:3].astype(np.uint8))\\n # if with_label:\\n # # return PIL_crop,PIL_crop_label\\n # # return PIL_crop\\n PIL_crop.save(image_save_dir+\\\"/\\\"+out_name)\",\n \"def crop_image(input_image, output_image, start_x, start_y, width, height):\\n box = (start_x, start_y, start_x + width, start_y + height)\\n output_img = img.crop(box)\\n output_img.save(output_image +\\\".png\\\")\",\n \"def crop_object_from_image(saving_folder,root_folder_path,root_folder_name,row_info):\\n class_name=row_info['class']\\n file_id=row_info['file_id']\\n img_type=row_info['type']\\n xmin=row_info['x_min']\\n xmax=row_info['x_max']\\n ymin=row_info['y_min']\\n ymax=row_info['y_max']\\n\\n\\n origin_img_path=os.path.join(root_folder_path,root_folder_name,img_type,file_id+\\\".png\\\")\\n crop_img_path=os.path.join(saving_folder,file_id+\\\"_\\\"+class_name+\\\".png\\\")\\n\\n origin_img=cv2.imread(origin_img_path)\\n crop_img=origin_img[ymin:ymax-1,xmin:xmax-1]\\n\\n # If width or height only contain 1 pixel, do not crop.\\n if xmax-xmin<=2 or ymax-ymin<=2:\\n print(\\\"Only one pixel, pass!\\\")\\n return 0\\n # print(origin_img.shape)\\n # print(xmin,xmax,ymin,ymax)\\n # print(crop_img.shape)\\n # print(crop_img_path)\\n cv2.imwrite(crop_img_path,crop_img)\",\n \"def _crop(self, fieldname, scale, box):\\n croputils = IImageCroppingUtils(self.context)\\n data = croputils.get_image_data(fieldname)\\n\\n original_file = StringIO(data)\\n image = PIL.Image.open(original_file)\\n image_format = image.format or self.DEFAULT_FORMAT\\n\\n cropped_image = image.crop(box)\\n cropped_image_file = StringIO()\\n cropped_image.save(cropped_image_file, image_format, quality=100)\\n cropped_image_file.seek(0)\\n\\n croputils.save_cropped(fieldname, scale, cropped_image_file)\\n\\n # store crop information in annotations\\n self._store(fieldname, scale, box)\\n\\n # Purge caches if needed\\n notify(Purge(self.context))\",\n \"def crop_image(inputimage, folder, newimgname, xtop=0, ytop=64, xbottom=512, ybottom=448):\\n\\timg = Image.open(folder + os.sep + inputimage)\\n\\timg = img.crop((xtop, ytop, xbottom, ybottom))\\n\\timg.save(folder + os.sep + newimgname, 'PNG')\",\n \"def crop_image(image_to_crop, year):\\r\\n\\timg = Image.open(image_to_crop)\\r\\n\\t#The dimensions of just the US in the image\\r\\n\\timg = img.crop((80, 240, 800, 615))\\r\\n\\r\\n\\tfile_destination = \\\"images/cropped_images/\\\" + str(year) + \\\".png\\\"\\r\\n\\r\\n\\timage_file = open(file_destination, 'wb')\\r\\n\\timg.save(image_file, 'png')\\r\\n\\timage_file.close()\",\n \"def crop_image(img, output_path):\\n old_im = Image.open(img).convert('L')\\n img_data = np.asarray(old_im, dtype=np.uint8) # height, width\\n nnz_inds = np.where(img_data!=255)\\n if len(nnz_inds[0]) == 0:\\n old_im.save(output_path)\\n return False\\n\\n y_min = np.min(nnz_inds[0])\\n y_max = np.max(nnz_inds[0])\\n x_min = np.min(nnz_inds[1])\\n x_max = np.max(nnz_inds[1])\\n old_im = old_im.crop((x_min, y_min, x_max+1, y_max+1))\\n old_im.save(output_path)\\n return True\",\n \"def generate(self, save=True):\\n stretched_photo, crop_box = self._generate_img()\\n\\n # set crop_box to (0,0,0,0) if photo not cropped\\n if not crop_box:\\n crop_box = 0, 0, 0, 0\\n\\n self.crop_left, self.crop_top, right, bottom = crop_box\\n self.crop_width = right - self.crop_left\\n self.crop_height = bottom - self.crop_top\\n\\n self.width, self.height = stretched_photo.size\\n\\n f = BytesIO()\\n imgf = (self.photo._get_image().format or\\n Image.EXTENSION[path.splitext(self.photo.image.name)[1]])\\n\\n stretched_photo.save(f, format=imgf, quality=self.format.resample_quality)\\n f.seek(0)\\n\\n self.image.save(self.file(), ContentFile(f.read()), save)\",\n \"def corp_image(self):\\n try:\\n # Open image\\n image_to_crop = Image.open(self.captcha_image_filename, 'r')\\n # Crop image\\n image = image_to_crop.crop((-1, 8, 65, 22))\\n # Save image\\n image.save(self.cropped_captcha_filename)\\n except UnidentifiedImageError as error:\\n raise(error)\",\n \"def create_clipping(request):\\n if request.method == 'POST':\\n image = request.POST.get('image')\\n\\n # check if the blanked image should be saved to the backend\\n if request.POST.get('save_clipping') in ['false', False]:\\n save = False\\n else:\\n save = True\\n\\n selection = {\\n 'id': int(request.POST.get('selection[id]')),\\n 'x': int(round(float(request.POST.get('selection[x]')))),\\n 'y': int(round(float(request.POST.get('selection[y]')))),\\n 'width': int(round(float(request.POST.get('selection[width]')))),\\n 'height': int(round(float(request.POST.get('selection[height]')))),\\n 'full_width': int(round(float(request.POST.get('selection[full_width]')))),\\n 'full_height': int(round(float(request.POST.get('selection[full_height]'))))\\n }\\n\\n # get the image id, the model object and the selection from the model\\n edit_url = request.POST.get('edit_url')\\n image_id = int(edit_url.split(\\\"/\\\")[-2])\\n image_object = CustomImage.objects.get(id=image_id)\\n original_selection = image_object.selections\\n\\n reseized_image = image_object.resize_url\\n\\n if selection['id'] == -1: # no selection -> use the whole image\\n cropped_image = reseized_image\\n else: # a specific selecion is used -> get the cropped image and selecion attributes\\n image_object = CroppedImage.objects.get(id=selection['id'])\\n cropped_image = original_selection[unicode(request.POST.get('selection[id]'))][\\\"url\\\"]\\n\\n # calculate the new blanking mask\\n mask = get_mask_from_image(image, selection, cropped_image, save, image_object)\\n\\n # stream the new mask to the output\\n stream = BytesIO()\\n flat_mask = []\\n for line in mask:\\n flat_mask.extend(line)\\n np.savetxt(stream, flat_mask, fmt=\\\"%u\\\", delimiter=', ', newline=', ')\\n stream.seek(0)\\n return HttpResponse(stream.read())\\n\\n return HttpResponse(\\n json.dumps({\\\"nothing to see\\\": \\\"this isn't happening\\\"}),\\n content_type=\\\"application/json\\\"\\n )\",\n \"def savePhoto(self, path):\\n if self.original_image and path:\\n cv2.imwrite(path, self.original_image)\",\n \"def crop_image (filename):\\n from PIL import Image\\n image = Image.open(filename)\\n for edge in 'NSWE':\\n image = _crop(image, edge)\\n image.save(filename)\",\n \"def crop(self, *args, **kwargs):\\n return _image.image_crop(self, *args, **kwargs)\",\n \"def crop(original_img, coordinates, destination):\\n image = cv2.imread(original_img)\\n cropped = image.copy()\\n if coordinates is None or len(coordinates) == 0:\\n cv2.imwrite(destination, cropped)\\n else:\\n cnt = np.array(coordinates)\\n cropped = four_point_transform(image, cnt)\\n cv2.imwrite(destination, cropped)\",\n \"def crop(self, coords):\\n pass\",\n \"def crop(self):\\n\\n return self.image.crop(self.x, self.y, self.width(), self.height(), centered = True)\",\n \"def save(self, filename):\\n print(\\\"Saving...\\\", end=\\\"\\\\r\\\")\\n canvas = self.canvas[self.N:self.S,self.W:self.E]\\n cv2.imwrite(\\\"./Output/\\\"+filename, canvas)\\n print(\\\"Saved:\\\",filename)\",\n \"def set_cropping(self, crop=True):\\n self._crop = crop\\n self._final = None # Force rebuild\",\n \"def test_crop(self):\\r\\n u = Uploader()\\r\\n size = (100, 100)\\r\\n im = Image.new('RGB', size)\\r\\n folder = tempfile.mkdtemp()\\r\\n u.upload_folder = folder\\r\\n im.save(os.path.join(folder, 'image.png'))\\r\\n coordinates = (0, 0, 50, 50)\\r\\n file = FileStorage(filename=os.path.join(folder, 'image.png'))\\r\\n with patch('pybossa.uploader.Image', return_value=True):\\r\\n err_msg = \\\"It should crop the image\\\"\\r\\n assert u.crop(file, coordinates) is True, err_msg\\r\\n\\r\\n with patch('pybossa.uploader.Image.open', side_effect=IOError):\\r\\n err_msg = \\\"It should return false\\\"\\r\\n assert u.crop(file, coordinates) is False, err_msg\",\n \"def save(\\n self,\\n output_path: str,\\n show_confidence: bool = True,\\n ) -> None:\\n image = self.draw(show_confidence=show_confidence)\\n save_image(image=image, path=output_path)\",\n \"def _generate_crop(self):\\n if self.box_drawn == True:\\n if (self.cd_pic_num != -1) & (self.cd_crop_num == 1):\\n self.communicator.generate_crop(picture_num=self.cd_pic_num, \\\\\\n xa=self.xa, ya=self.ya, xb=self.xb, yb=self.yb)\\n else:\\n print \\\"ERROR: can only generate a new crop from a thumbnail\\\"\\n else:\\n print \\\"ERROR: please select an area to generate a crop from\\\"\",\n \"def save_image(path, image): \\n if len(image.shape) == 4:\\n image = image.reshape((image.shape[1], image.shape[2], image.shape[3]))\\n image = np.clip(image * 255.0, 0, 255).astype(np.uint8)\\n skimage.io.imsave(path, image)\",\n \"def crop(img, x, y, w, h):\\n check_type(img)\\n return img.crop((x, y, x + w, y + h))\",\n \"def save_as(self, filename):\\n opencv.imwrite(filename, self.img)\",\n \"def crop_image(img):\\n gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)\\n _, threshed = cv.threshold(gray, 240, 255, cv.THRESH_BINARY_INV)\\n\\n kernel = cv.getStructuringElement(cv.MORPH_ELLIPSE, (11, 11))\\n morphed = cv.morphologyEx(threshed, cv.MORPH_CLOSE, kernel)\\n\\n cnts = cv.findContours(morphed, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)[-2]\\n cnt = sorted(cnts, key=cv.contourArea)[-1]\\n\\n x, y, w, h = cv.boundingRect(cnt)\\n dst = img[y:y+h, x:x+w]\\n cv.imwrite(\\\"001.png\\\", dst)\\n return dst\",\n \"def save_crops(self, workspace):\\n objects_name = self.objects_name.value\\n objects = workspace.object_set.get_objects(objects_name)\\n bit_depth = self.bit_depth.value\\n if self.input_type == IF_IMAGE:\\n image_name = self.image_name.value\\n image = workspace.image_set.get_image(image_name)\\n pixels = image.pixel_data\\n elif self.input_type == IF_OBJECTS:\\n obj_name = self.input_object_name.value\\n inp_obj = workspace.object_set.get_objects(obj_name)\\n pixels = inp_obj.get_segmented()\\n else:\\n raise (\\\"invalid choice of input\\\")\\n\\n filename = self.get_filename(workspace)\\n object_extension = self.object_extension.value\\n if filename is None: # failed overwrite check\\n return\\n\\n slices = ndi.find_objects(objects.segmented)\\n slices, labels = zip(\\n *[(s, label) for label, s in enumerate(slices) if s is not None]\\n )\\n\\n ext_slices = [\\n self._extend_slice_touple(\\n sl, object_extension, [pixels.shape[0], pixels.shape[1]]\\n )\\n for sl in slices\\n ]\\n out_folder = os.path.dirname(filename)\\n basename = os.path.splitext(os.path.basename(filename))[0]\\n # the stack for imctools needs to be cxy, while it is xyc in cp\\n if len(pixels.shape) == 2:\\n stack = pixels.reshape([1] + list(pixels.shape))\\n else:\\n stack = np.rollaxis(pixels, 2, 0)\\n\\n # fix the dtype\\n if bit_depth == BIT_DEPTH_8:\\n stack = skimage.util.img_as_ubyte(stack)\\n elif bit_depth == BIT_DEPTH_16:\\n stack = skimage.util.img_as_uint(stack)\\n elif bit_depth == BIT_DEPTH_FLOAT:\\n stack = skimage.util.img_as_float(stack).astype(np.float32)\\n\\n self._save_object_stack(out_folder, basename, stack, ext_slices, labels)\\n self.save_filename_measurements(workspace)\\n if self.show_window:\\n workspace.display_data.wrote_image = True\",\n \"def crop_image(self, img):\\n img.crop_image(self._center, 1.1 * self._radius)\",\n \"def crop(image, dimX, dimY):\\n # TODO\\n return image\",\n \"def save_and_return_cropped(image_as_array, imagefolder_new, imagetype_new, imagename):\\n\\n # Check if there is a section of the row that is 90% non-white\\n def half_row_nonwhite(row, verbose=False):\\n nonwhite_in_a_row_ratio = 0\\n white_in_a_row_ratio = 0\\n for pixel in row:\\n if np.sum(pixel) < 255 * row.shape[1]:\\n nonwhite_in_a_row_ratio += 1 / row.shape[0]\\n elif white_in_a_row_ratio < 0.05:\\n nonwhite_in_a_row_ratio += 1 / row.shape[0]\\n white_in_a_row_ratio += 1 / row.shape[0]\\n else:\\n nonwhite_in_a_row_ratio = 0\\n white_in_a_row_ratio = 0\\n if nonwhite_in_a_row_ratio > 0.5:\\n return True\\n return False\\n\\n # Calculate start and end row (or col)\\n def start_and_end(image_as_array):\\n start, end = 0, 0\\n for r in range(image_as_array.shape[0]):\\n sufficient_contrast = (\\n np.abs(\\n int(np.sum(image_as_array[r])) - int(np.sum(image_as_array[r + 1]))\\n )\\n > 0.3 * 255 * image_as_array.shape[1] * image_as_array.shape[2]\\n )\\n if sufficient_contrast:\\n if start == 0 and half_row_nonwhite(image_as_array[r + 1]):\\n start = r + 1\\n continue\\n if start > 0 and half_row_nonwhite(image_as_array[r]):\\n end = r + 1\\n break\\n return start, end\\n\\n y1, y2 = start_and_end(image_as_array)\\n x1, x2 = start_and_end(np.swapaxes(image_as_array, 0, 1))\\n cropped_image_as_array = image_as_array[y1:y2, x1:x2, :]\\n\\n # Save cropped image\\n FILEPATH_cropped = imagefolder_new + imagename.split(\\\".\\\")[0] + imagetype_new\\n Image.fromarray(cropped_image_as_array).save(FILEPATH_cropped)\\n return cropped_image_as_array\",\n \"def slide_crop(img, img_meta, model_cfg, save_dir):\\r\\n ori_shape = img_meta[0]['ori_shape']\\r\\n stem = Path(img_meta[0]['ori_filename']).stem\\r\\n save_dir = Path(save_dir)\\r\\n save_dir.mkdir(parents=True, exist_ok=True)\\r\\n\\r\\n h_stride, w_stride = model_cfg.test_cfg.stride\\r\\n h_crop, w_crop = model_cfg.test_cfg.crop_size\\r\\n batch_size, _, h_img, w_img = img.size()\\r\\n h_grids = max(h_img - h_crop + h_stride - 1, 0) // h_stride + 1\\r\\n w_grids = max(w_img - w_crop + w_stride - 1, 0) // w_stride + 1\\r\\n\\r\\n cnt = 0\\r\\n for h_idx in range(h_grids):\\r\\n for w_idx in range(w_grids):\\r\\n y1 = h_idx * h_stride\\r\\n x1 = w_idx * w_stride\\r\\n y2 = min(y1 + h_crop, h_img)\\r\\n x2 = min(x1 + w_crop, w_img)\\r\\n y1 = max(y2 - h_crop, 0)\\r\\n x1 = max(x2 - w_crop, 0)\\r\\n crop_img = img[:, :, y1:y2, x1:x2]\\r\\n \\r\\n cnt += 1\\r\\n msg1 = f'{x1},{y1},{x2},{y2}'\\r\\n msg2 = f'{ori_shape[0]},{ori_shape[1]},{ori_shape[2]}'\\r\\n msg3 = f'{batch_size},{h_img},{w_img}'\\r\\n bin_path = save_dir/f'{stem}-{\\\"-\\\".join([msg1, msg2, msg3])}.bin'\\r\\n crop_img.numpy().astype(np.float32).tofile(bin_path)\\r\\n\\r\\n return cnt\",\n \"def crop (*args, **kwargs):\\n return compute('crop', inputs=list(args), args=kwargs)\",\n \"def crop(image, size):\\n size = size.split('x')\\n (root, name, ext) = split_filepath(image.path)\\n filename = scale_image(image.path, (int(size[0]), int(size[1])), 'crop')\\n return '/%s/%s' % (os.path.abspath(root).replace('%s/' % os.path.abspath(settings.BASE_PATH), ''), filename)\",\n \"def crop(img, i, j, h, w):\\n return img.crop((j, i, j + w, i + h))\",\n \"def crop(img, i, j, h, w):\\n return img.crop((j, i, j + w, i + h))\",\n \"def __call__(self, img):\\n image_width, image_height = img.size\\n image_short = min(image_width, image_height)\\n\\n crop_size = float(self.imgsize) / (self.imgsize + 32) * image_short\\n\\n crop_height, crop_width = crop_size, crop_size\\n crop_top = int(round((image_height - crop_height) / 2.))\\n crop_left = int(round((image_width - crop_width) / 2.))\\n return img.crop((crop_left, crop_top, crop_left + crop_width, crop_top + crop_height))\",\n \"def __call__(self, img):\\n image_width, image_height = img.size\\n image_short = min(image_width, image_height)\\n\\n crop_size = float(self.imgsize) / (self.imgsize + 32) * image_short\\n\\n crop_height, crop_width = crop_size, crop_size\\n crop_top = int(round((image_height - crop_height) / 2.))\\n crop_left = int(round((image_width - crop_width) / 2.))\\n return img.crop((crop_left, crop_top, crop_left + crop_width, crop_top + crop_height))\",\n \"def crop_save( img_path_filename, lines_boxes, lines_texts, lines_probs, filename, basename, output_dir_name ):\\n\\t# Read the image\\n\\timage = Image.open( img_path_filename )\\n\\t# Get image's size\\n\\twidth, height = image.size\\n\\n\\ti = 0\\n\\ttext_local = \\\"\\\"\\n\\ttext_global = \\\"\\\"\\n\\twhile i < len(lines_boxes):\\n\\t\\t##################################################################################################\\n\\t\\t# Left Upper Corner\\n\\t\\tx1 = lines_boxes[i][0]\\n\\t\\tx1 = x1 - 8\\n\\t\\tif x1 < 0:\\n\\t\\t\\tx1 = 0\\n\\n\\t\\ty1 = lines_boxes[i][1]\\n\\t\\ty1 = y1 - 1\\n\\t\\tif y1 < 0:\\n\\t\\t\\ty1 = 0\\n\\n\\t\\t# Right Lower Corner\\n\\t\\tx2 = lines_boxes[i][2]\\n\\t\\tx2 = x2 + 10\\n\\t\\tif x2 > (width - 1):\\n\\t\\t\\tx2 = width - 1\\n\\n\\t\\ty2 = lines_boxes[i][3]\\n\\t\\ty2 = y2 + 1\\n\\t\\tif y2 > (height - 1):\\n\\t\\t\\ty2 = height - 1\\n\\n\\t\\t# Crop the block and save it\\n\\t\\tn_line = \\\"%03d\\\" % (i+1)\\n\\t\\tline_filename = output_dir_name + \\\"/\\\" + basename + \\\"_\\\" + n_line + \\\".jpg\\\"\\t\\t\\n\\n\\t\\timg_cropped = image.crop( (x1, y1, x2, y2) )\\n\\t\\timg_cropped.save( line_filename, 'JPEG', quality = 100 )\\n\\n\\t\\t##################################################################################################\\n\\t\\t# Create the information about the cropped line for the local and global text files\\n\\t\\ttext_line = basename + \\\"_\\\" + n_line + \\\".jpg\\\\t\\\" + str(x1) + \\\"\\\\t\\\" + str(y1) + \\\"\\\\t\\\" + str(x2) + \\\"\\\\t\\\" + str(y2) + \\\"\\\\t\\\" + ''.join(lines_texts[i]) + \\\"\\\\n\\\"\\n\\t\\ttext_local += text_line\\n\\t\\ttext_global += filename + \\\"\\\\t\\\" + text_line\\n\\n\\t\\t##################################################################################################\\n\\t\\t# Creation of the text and probability file for each line\\n\\t\\tj = 0\\n\\t\\tcontent_text_file = \\\"\\\"\\n\\t\\tcontent_prob_file = \\\"\\\"\\n\\t\\twhile j<len(lines_texts[i]):\\n\\t\\t\\tcontent_text_file += lines_texts[i][j]\\n\\t\\t\\tcontent_prob_file += lines_texts[i][j] + '\\\\t' + str(lines_probs[i][j]) + '\\\\n'\\n\\t\\t\\tj = j + 1\\n\\t\\t# Write to disk the text file\\n\\t\\ttext_filename = output_dir_name + \\\"/\\\" + basename + \\\"_\\\" + n_line + \\\".txt\\\"\\n\\t\\twith open( text_filename, \\\"w+\\\" ) as f_text:\\n\\t\\t\\tf_text.write( content_text_file )\\n\\t\\t# Write to disk the probabilities file\\n\\t\\tprob_filename = output_dir_name + \\\"/\\\" + basename + \\\"_\\\" + n_line + \\\".prob\\\"\\n\\t\\twith open( prob_filename, \\\"w+\\\" ) as f_prob:\\n\\t\\t\\tf_prob.write( content_prob_file )\\n\\n\\t\\ti = i + 1\\n\\n\\treturn( text_local, text_global )\",\n \"def save_detection(self, image):\\n\\t\\timg = self.visualize_detection(image)\\n\\t\\timg = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)\\n\\t\\tcv2.imwrite(f'{SAVE_PATH}{self.clip}{self.num_save}.jpg', img)\",\n \"def basic_crop(data):\\n return data['crop'];\",\n \"def save_image(self):\\n self.save()\",\n \"def crop_image(image):\\r\\n return image[40:-20, :]\",\n \"def display_cropped_img(i):\\n image = PIL.Image.open(testing_img_paths[i])\\n image = image.crop(box=(313,99,825,611))\\n image = image.resize((256,256))\\n display(image)\",\n \"def save(self, filepath):\\n self.drawer.flush()\\n self.img.save(filepath)\",\n \"def __crop(img, pos, size):\\n ow, oh = img.size\\n x1, y1 = pos\\n tw = th = size\\n if (ow > tw or oh > th):\\n return img.crop((x1, y1, x1 + tw, y1 + th))\\n return img\",\n \"def crop(img, top, left, width, height):\\n if not all([isinstance(x, int) for x in (top, left, width, height)]):\\n raise ValueError(\\\"params should be integer!\\\")\\n if (width > img.shape[0] or height > img.shape[1]):\\n raise ValueError(\\\"the output imgage size should be small than input image!!!\\\")\\n\\n if len(img.shape) == 2:\\n img_height, img_width = img.shape\\n else:\\n img_height, img_width, _ = img.shape\\n right = img_width - (left + width)\\n bottom = img_height - (top + height)\\n if len(img.shape) == 2:\\n img_croped = util.crop(img,((top,bottom),(left,right)))\\n else:\\n img_croped = util.crop(img,((top,bottom),(left,right),(0,0)))\\n\\n return img_croped\",\n \"def _save(filename, img):\\n if not os.path.exists(OUTPUT_DIR):\\n os.makedirs(OUTPUT_DIR)\\n # filename = filename+'.png'\\n filename = os.path.join(OUTPUT_DIR, filename)\\n # print(filename, img.shape)\\n cv.imwrite(filename, img)\",\n \"def save(self, path):\\n (folder, filename) = os.path.split(path)\\n if not filename:\\n filename = _clean_filename(self.name)\\n path = os.path.join(folder, filename)\\n return self.image.save(path)\",\n \"def saveView(self, filename):\\n\\n pixmap = self.grab();\\n ok = pixmap.save(filename)\\n if not ok:\\n raise IOError('Unable to save image ' + filename)\",\n \"def save_Image(self, path, name, array):\\n # Resize into a 2D array\\n shaped_arr = np.reshape((array * 255).astype('uint8'),\\n (self.im_size, self.im_size))\\n cv.imwrite(\\\"%s/missed_img%s.jpg\\\" % (path, name),shaped_arr)\",\n \"def save_overlay(self, path):\\n if self.im is None:\\n raise ValueError('You didnt call the MaskOverlay, therefore there is no image in memory')\\n im_masked = img_as_ubyte(self.im_masked)\\n imsave(path, im_masked)\",\n \"def save_image(filename, image):\\n im = cv2.resize(image, None, fx=SCALE_DOWN, fy=SCALE_DOWN)\\n cv2.imwrite(os.path.join(OUT_DIR, filename), im)\",\n \"def run_crops(self, workspace):\\n #\\n # First, check to see if we should save this image\\n #\\n self.save_crops(workspace)\\n return True\",\n \"def set_crop(self, crop):\\n self.crop = crop\",\n \"def crop(src_path, out_path, bbox_geometry, bbox_crs):\\n\\n # validate area of interest\\n\\n\\n # load imagery\\n satdata = rasterio.open(src_path)\\n\\n # grab crs\\n crs = satdata.meta['crs']\\n crs = str(crs).split(':')[-1]\\n\\n # check crs\\n if(crs != bbox_crs):\\n raise Exception(f'Imagery & bounding box crs mismatch ({crs}, {bbox_crs})')\\n\\n # apply mask with crop=True to crop the resulting raster to the AOI's bounding box\\n clipped, transform = mask(satdata, aoi, crop=True)\\n\\n # Using a copy of the metadata from our original raster dataset, we can write a new geoTIFF\\n # containing the new, clipped raster data:\\n meta = satdata.meta.copy()\\n\\n # update metadata with new, clipped mosaic's boundaries\\n meta.update(\\n {\\n \\\"transform\\\": transform,\\n \\\"height\\\":clipped.shape[1],\\n \\\"width\\\":clipped.shape[2]\\n }\\n )\\n\\n # write the clipped-and-cropped dataset to a new GeoTIFF\\n with rasterio.open(out_path, 'w', **meta) as dst:\\n dst.write(clipped)\",\n \"def save(self, filename):\\n self.image.save(filename, self.options.img_format)\",\n \"def crop_img(image, bound):\\n scale = 1.01 # 1%\\n return image.crop((bound.vertices[0].x // scale, bound.vertices[0].y // scale,\\n int(bound.vertices[2].x * scale), int(bound.vertices[2].y) * scale))\",\n \"def crop_images(row, crop_path):\\n def crop(im, box, square=True):\\n \\\"\\\"\\\" box: list, [x_left, y_bottom, x_l + w, y_b + h]\\n \\\"\\\"\\\"\\n def pad_square(box):\\n \\\"\\\"\\\" If box is a rectangle, expand it to a square.\\n \\\"\\\"\\\"\\n x, y, xw, yh = box\\n w = xw-x\\n h = yh-y\\n if w < h:\\n w = h\\n elif h < w:\\n h = w\\n return [x, y, x+w, y+h]\\n if square:\\n box = pad_square(box)\\n x, y, xw, yh = box\\n return im[y:yh, x:xw]\\n im = tiffread(row['Image'])\\n im_crop = crop(im, row['Cropbox'], square=True)\\n crop_file = os.path.join(crop_path, row['Name'], row['UID'])\\n tiffwrite(crop_file, im_crop)\",\n \"def img_save(self):\\n file_name, extension = return_folder_file_extension(self.img_name)[1:]\\n image_name_save = \\\"%s_D=%s_Rs=%s_size=%s_offset=%i%s\\\" % (file_name, self.D, self.Rs, self.axe_X, self.offset_X+self.offset_X2, extension)\\n\\n if self.img2 is not None:\\n self.img2.save(image_name_save)\\n print(\\\"Saved \\\"+image_name_save)\\n else:\\n print(\\\"No image to save\\\")\",\n \"def save_processed_image(self, filename=None):\\n if filename is None:\\n tag = self.get_alert_objects_list(\\\"_\\\")\\n filename = os.path.join(\\n config.IMAGE_SAVE_PATH, \\\"%s_%s_%s_%s.jpg\\\" %\\n (time.strftime(\\\"%Y-%m-%d_%H.%M.%S\\\", time.localtime(self.timestamp)),\\n self.camera_name, self.detection_model, tag))\\n # print(\\\"Using filename %s\\\" % filename)\\n ret = cv2.imwrite(filename, self.processed_image)\\n self.processed_file = filename\\n return ret\",\n \"def uncrop( self ):\\n \\n if self._cropped:\\n self._reset_bounds()\\n self._cropped = False\\n else:\\n print(\\\"This data cube was not cropped\\\")\",\n \"def crop(self, image):\\n\\t\\treturn image.copy()[self.ymin:self.ymax,self.xmin:self.xmax]\",\n \"def save_pca(self, filepath):\\n mean_beam, principal_components, variances = self.pca()\\n image_shape = np.array(self.image_shape)\\n with open(filepath, 'wb') as f:\\n np.save(f, image_shape)\\n np.save(f, mean_beam)\\n np.save(f, principal_components)\\n np.save(f, variances)\\n np.save(f, self.mask)\",\n \"def save_image(self, filename):\\n raster.save_image(filename, self.image, self.metadata)\",\n \"def imsave_clip(outfile,img):\\n img = img_as_float(img).clip(0.,1.)\\n io.imsave(outfile,img)\",\n \"def save_original_image(slide, heatmapPath):\\n dims = slide.dims\\n img = slide.image.read_region((0,0), len(dims)-1, dims[-1])\\n img.save(os.path.join(heatmapPath, slide.id) + \\\".png\\\")\",\n \"def _crop_write_image(self, inroot, images, outroot):\\n for image in images:\\n inimage_path = osp.join(inroot, image)\\n cvimg = cv2.imread(inimage_path)\\n cvimg = cvimg[60:-30, 25:-25]\\n h, w, _ = cvimg.shape\\n assert h == w == 128\\n outimage_path = osp.join(outroot, image)\\n cv2.imwrite(outimage_path, cvimg)\\n print(outimage_path)\",\n \"def crop(self, bbox):\\n if self.__huge: # image is huge and not totally in RAM\\n band = bbox[3] - bbox[1] # width of the tile band\\n self.__tile[1][3] = band # set the tile height\\n self.__tile[2] = self.__offset + self.imwidth * bbox[1] * 3 # set offset of the band\\n self.__image.close()\\n self.__image = Image.open(self.path) # reopen / reset image\\n self.__image.size = (self.imwidth, band) # set size of the tile band\\n self.__image.tile = [self.__tile]\\n return self.__image.crop((bbox[0], 0, bbox[2], band))\\n else: # image is totally in RAM\\n return self.__pyramid[0].crop(bbox)\",\n \"def Crop_Image(img, mask, x, y, width, height):\\n img = img[y:y+height, x:x+width,:]\\n mask = mask[y:y+height, x:x+width,:]\\n return img, mask\",\n \"def get_crop(self):\\n if self.cropping_method == self.CROP_NONE:\\n self.autocrop()\\n return '{h}% {v}%'.format(h=self.from_left, v=self.from_top)\",\n \"def crop_img(img_path, tile_x, tile_y , save_path):\\n # make directory to save tiles\\n im = Image.open(img_path)\\n try:\\n os.mkdir(img_path)\\n except OSError:\\n print(\\\"Creation of the directory %s failed\\\" % img_path)\\n else:\\n print(\\\"Successfully created the directory %s \\\" % img_path)\\n \\n # conver image to numpyarray and extract image height and width\\n img_arr = np.array(im)\\n shape = img_arr.shape\\n img_y = shape[0]\\n img_x = shape[1]\\n\\n #calculate point to crop\\n xy_points = calcul_xy_array(img_x, img_y, tile_x, tile_y)\\n\\n for x, y in xy_points:\\n \\n #extract pixels fro array\\n A = img_arr[y: y + tile_y, x: x + tile_x, :]\\n \\n #convert array back to img\\n im = Image.fromarray(A)\\n\\n\\n #saving the image in formate:\\n #Original_img_name + \\\"__\\\" + tile_x_cor \\\"_\\\" + tile_y_cor \\\"__\\\"+\\n #Original_img_height + \\\"_\\\" + Original_img_width\\n name = (img_path.split('\\\\\\\\'))[-1]\\n file_name = str(name) + \\\"__\\\" + str(x) + \\\"_\\\" + str(y) + \\\"__\\\" + str(\\n img_x) + \\\"_\\\" + str(img_y) + \\\".tif\\\"\\n\\n path = save_path + '\\\\\\\\' + file_name\\n im.save(path)\",\n \"def crop(im, config):\\n\\n src_width, src_height = im.size\\n\\n src_ratio = float(src_width) / float(src_height)\\n dst_ratio = float(config['width']) / float(config['height'])\\n\\n if dst_ratio < src_ratio:\\n crop_height = src_height\\n crop_width = crop_height * dst_ratio\\n x_offset = int(float(src_width - crop_width) / 2)\\n y_offset = 0\\n else:\\n crop_width = src_width\\n crop_height = crop_width / dst_ratio\\n x_offset = 0\\n y_offset = int(float(src_height - crop_height) / 3)\\n\\n im = im.crop((\\n x_offset,\\n y_offset,\\n x_offset + int(crop_width),\\n y_offset + int(crop_height),\\n ))\\n\\n return im.resize(\\n (config['width'], config['height']),\\n ANTIALIAS,\\n )\",\n \"def doCrop(image, x, y, w, h):\\n\\tcrop_height = int((config.FACE_HEIGHT / float(config.FACE_WIDTH)) * w)\\n\\tmidy = y + h/2\\n\\ty1 = max(0, midy-crop_height/2)\\n\\ty2 = min(image.shape[0]-1, midy+crop_height/2)\\n\\treturn image[y1:y2, x:x+w]\",\n \"def savePicture(self):\\n self.file_name = QtGui.QFileDialog.getSaveFileName(self, \\n \\\"Save as... (specify extension)\\\", \\\"\\\")\\n cv2.imwrite(self.file_name, self.frame)\",\n \"def avatar_crop(request, id=None):\\n if id:\\n avatar = get_object_or_404(Avatar, id=id, user=request.user)\\n else:\\n avatar = get_object_or_404(Avatar, user=request.user, primary=True)\\n\\n if (avatar.avatar.width<=avatar.avatar.height):\\n result = \\\"width\\\"\\n else:\\n result = \\\"height\\\"\\n\\n if not request.method == \\\"POST\\\":\\n form = AvatarCropForm()\\n else:\\n try:\\n orig = avatar.avatar.storage.open(avatar.avatar.name, 'rb').read()\\n image = Image.open(StringIO(orig))\\n except IOError:\\n return\\n form = AvatarCropForm(image, request.POST)\\n\\n if form.is_valid():\\n top = int(form.cleaned_data.get('top'))\\n left = int(form.cleaned_data.get('left'))\\n right = int(form.cleaned_data.get('right'))\\n bottom = int(form.cleaned_data.get('bottom'))\\n\\n box = [ left, top, right, bottom ]\\n (w, h) = image.size\\n if result==\\\"width\\\":\\n box = map(lambda x: x*h/AVATAR_CROP_MAX_SIZE, box)\\n else:\\n box = map(lambda x: x*w/AVATAR_CROP_MAX_SIZE, box)\\n\\n image = image.crop(box)\\n if image.mode != 'RGB':\\n image = image.convert('RGB')\\n\\n thumb = StringIO()\\n image.save(thumb, AVATAR_THUMB_FORMAT, quality=AVATAR_THUMB_QUALITY)\\n thumb_file = ContentFile(thumb.getvalue())\\n\\n base_name, ext = os.path.splitext(avatar.avatar.name)\\n thumb = avatar.avatar.storage.save(\\\"%s_cropped%s\\\" % (base_name, ext), thumb_file)\\n Avatar.objects.filter(id=avatar.id).update(primary=False)\\n new_avatar = Avatar(user=request.user, primary=True, avatar=thumb)\\n new_avatar.save()\\n messages.add_message(request, messages.INFO, _(\\\"Your new avatar has been saved successfully.\\\"))\\n return HttpResponseRedirect(reverse(\\\"avatar_change\\\"))\\n\\n return render_to_response(\\\"avatar_crop/crop.html\\\", {\\n 'AVATAR_CROP_MAX_SIZE': AVATAR_CROP_MAX_SIZE,\\n 'dim': result,\\n 'avatar': avatar,\\n 'form': form\\n }, context_instance=RequestContext(request))\",\n \"def save_image(img, path):\\n cv2.imwrite(path, img)\",\n \"def save(self):\\n img = Image.new(\\\"1\\\", (self.container.width, self.container.height))\\n draw = ImageDraw.Draw(img)\\n for item in self.items:\\n draw.ellipse(item.box_coordinates(), fill=1)\\n del draw\\n img.save(\\\"plot.bmp\\\", \\\"bmp\\\")\",\n \"def save_image(self):\\n self.compressed_image_id = str(uuid.uuid4().hex)\\n plot.imsave(\\n str(\\n self.compressed_image_id + \\\"{}\\\").format(\\n \\\".png\\\"), self.compressed_image)\\n\\n if self.verbose:\\n print(\\n \\\"Compressed image saved at \\\" + (\\n str(self.compressed_image_id + \\\"{}\\\").format(\\\".png\\\")))\",\n \"def save(self, path):\\n dirname = osp.dirname(osp.abspath(path))\\n if not osp.isdir(dirname):\\n os.mkdir(dirname)\\n image = self.build()\\n LOGGER.info(\\\"Save image '%s'\\\", path)\\n image.save(path)\\n return image\",\n \"def save(self, path, filename=None, overwrite=False):\\n \\n if filename is None and self.metadata is None:\\n raise ValueError(\\\"If the image has no 'metadata', you must specify a filename\\\")\\n elif filename is not None:\\n pass\\n elif filename is None and self.metadata is not None:\\n filename = os.path.basename(self.metadata[\\\"pfilename\\\"])\\n \\n full_image_path = os.path.join(path, filename)\\n \\n if overwrite and os.path.exists(full_image_path):\\n os.remove(full_image_path)\\n \\n self.fits.writeto(full_image_path)\",\n \"def resize_img(self,scale=1):\\n reduced = self.image.reduce((scale,scale))\\n reduced.save(\\\"../edited/{}\\\".format(self.image.filename))\\n\\n reduced = Image.open(\\\"../edited/{}\\\".format(self.image.filename))\\n return reduced\",\n \"def crop( self, remove_bad=True, check_coverage=True ):\\n \\n if not self._cropped:\\n cropper = image_cube_cropper( check_coverage=check_coverage ).fit( self )\\n\\n # remove corrupt images if desired \\n if remove_bad:\\n self._remove_steps( cropper.get_null_images() )\\n self._remove_steps( cropper.get_corrupt_images() )\\n\\n # set new bounds and cropped cube indicator\\n self._set_bounds( cropper.get_bounds() )\\n self._cropped = True\\n \\n else:\\n if ir.config.verbosity_level >= 1:\\n print(\\\"This data cube has already been cropped\\\")\",\n \"def observation(self, frame):\\r\\n if self.grayscale:\\r\\n frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)\\r\\n frame = cv2.resize(frame, (self.width, self.height), interpolation=cv2.INTER_AREA)\\r\\n crop_frame = frame[self.crop:, :]\\r\\n if self.grayscale:\\r\\n crop_frame = crop_frame[:,:, None]\\r\\n return crop_frame\",\n \"def capture_image(self):\\n ext = self.image_save_type.lower()\\n\\n if self.calibrating:\\n print('calibrating')\\n\\n if ext == 'fits':\\n self.save_fits()\\n self._image_counter += 1\\n else:\\n img = self.original_image\\n path = os.path.join(self.home, 'data')\\n name = \\\"camtrak_frame_{}.png\\\".format(self._image_counter) \\n fn = os.path.join(path, name)\\n cv2.imwrite(fn, img)\\n\\n QtWidgets.QApplication.beep()\\n self.statusBar().showMessage(f'Saved image to {fn}')\\n self._image_counter += 1\",\n \"def crop(image, countours, num_img, path_des):\\n i = 0\\n if len(countours) == 0: # we d'ont fine a contour save the all image\\n path = path_des\\n cv2.imwrite(os.path.join(path, 'Barcod') + '_' + 'num' + str(i) + '_' + 'img' + num_img, image)\\n i = i + 1\\n for cntr in countours:\\n # creates an approximate rectangle around contour\\n x, y, w, h = cv2.boundingRect(cntr)\\n of = 50\\n # pulls crop out of the image based on dimensions\\n # new_img = image[y-of:y + h+of, x-of:x + w+of]\\n new_img = offset(image, y - of, y + h + of, x - of, x + w + of)\\n\\n path = path_des\\n cv2.imwrite(os.path.join(path, 'Barcod') + '_' + 'num' + str(i) + '_' + 'img' + num_img, new_img)\\n\\n i = i + 1\",\n \"def crop(img, top, left, height, width):\\n if not _is_numpy(img):\\n raise TypeError('img should be Numpy Image. Got {}'.format(type(img)))\\n\\n return img[top:top + height, left:left + width]\",\n \"def Crop(self, path):\\n global img, crop\\n self.window_created = True\\n self.path = path\\n self.crop = tk.Toplevel(None)\\n self.crop.protocol(\\\"WM_DELETE_WINDOW\\\", self.CloseCropWindow)\\n \\n# tk.Label(crop, text=self.path).grid()\\n self.crop.title(\\\"Crop Window\\\")\\n #load image specified in path var\\n img = Image.open(self.path)\\n img = ImageTk.PhotoImage(img)\\n #print img.height()\\n #create canvas to show image\\n global crop_canvas \\n crop_canvas = tk.Canvas(master=self.crop, bg='#000',\\n width=img.width(), height=img.height())\\n \\n crop_canvas.bind('<Button-1>', self.Btn1Pressed)\\n crop_canvas.bind('<ButtonRelease-1>', self.Btn1Released)\\n crop_canvas.bind('<B1-Motion>', self.Btn1Motion)\\n \\n \\n crop_canvas.create_image(0,0,anchor=tk.NW, image=img)\\n crop_canvas.image = img #keep image reference\\n crop_canvas.grid(sticky=tk.NW)\\n self.crop.focus_set()\\n \\n #btns for zoom functionality\\n \\\"\\\"\\\"\\n zoom_in = tk.Button(master=self.crop_canvas,text='+', anchor=tk.NE,\\n command=self.ZoomIn)\\n zoom_out = tk.Button(master=self.crop_canvas,text='-',anchor=tk.NE, \\n command=self.ZoomOut)\\n \\\"\\\"\\\"\\n #zoom_in.place(x=img.width()-14,y=0)\\n #zoom_out.place(x=img.width()-14,y=30)\",\n \"def img_save(name,img):\\n cv2.imwrite(name,img)\",\n \"def save(self, **kwargs):\\n self.remove_file()\\n if not self.image:\\n self.generate(save=False)\\n else:\\n self.image.name = self.file()\\n super(FormatedPhoto, self).save(**kwargs)\",\n \"def saveimage(self):\\n if self.saveimageButton.isChecked():\\n self.save = True\\n self.channelsOpen()\\n self.movetoStart()\\n self.saveimageButton.setText('Abort')\\n self.guarda = np.zeros((self.numberofPixels, self.numberofPixels))\\n self.liveviewStart()\\n\\n else:\\n self.save = False\\n print(\\\"Abort\\\")\\n self.saveimageButton.setText('reintentar Scan and Stop')\\n self.liveviewStop()\",\n \"def crop_img(img_path, lbl_path, output_path):\\n img_file_list = os.listdir(img_path)\\n lbl_file_list = os.listdir(lbl_path)\\n\\n img_endswith = img_file_list[0].split(\\\".\\\")[-1]\\n cnt = 1\\n for lbl_file in lbl_file_list:\\n coords = get_coords_from_label(os.path.join(lbl_path, lbl_file))\\n for coord in coords:\\n xmin, ymin, xmax, ymax = coord\\n\\n img = cv2.imread(os.path.join(img_path, lbl_file.replace(\\\"xml\\\", img_endswith)))\\n cropped = img[ymin:ymax, xmin:xmax]\\n\\n output_file = os.path.join(output_path, \\\"{}.{}\\\".format(cnt, img_endswith))\\n cv2.imwrite(output_file, cropped)\\n cnt += 1\",\n \"def _crop_image(image: Image, w: int, h: int, area_to_crop: Tuple[int]) -> Image:\\n expected_w = 480\\n expected_h = 360\\n if w != expected_w:\\n print(\\\"Warning, image width:\\\", w, \\\"differs from expected width:\\\", expected_w)\\n if h != expected_h:\\n print(\\\"Warning, image height:\\\", h, \\\"differs from expected height:\\\", expected_h)\\n\\n cropped_image = image.crop(area_to_crop)\\n w_cropped, h_cropped = cropped_image.size\\n return cropped_image.resize((w_cropped, h_cropped))\",\n \"def saveImage(self, event):\\r\\n fileWritten = self.image.writeFile()\\r\\n self.statusBar.SetStatusText(\\\"Saved {}\\\".format(fileWritten))\",\n \"def save_file(camera, frame):\\n save = input(\\\"Would you like to save your drawing? Enter yes or no \\\")\\n if save == \\\"yes\\\" or save == \\\"y\\\" or save == \\\"ye\\\" or save == \\\"yes \\\": # accounting for typos\\n name = input(\\\"What would you like to name your masterpiece? \\\")\\n filename = 'images/' + name + '.png'\\n cv2.imwrite(filename, cv2.flip(frame,1)) # saves the image as the last frame\\n camera.release()\\n pygame.quit()\\n\\n # reopen saved picture to display for user\\n img = cv2.imread(filename, 1)\\n b,g,r = cv2.split(img) # get b,g,r\\n rgb_img = cv2.merge([r,g,b]) # convert from bgr colorspace to rgb\\n crop_img = rgb_img[36:450, 0:600] # crop out the colorbar\\n cv2.imshow(filename, crop_img)\\n cv2.imwrite(filename, crop_img)\\n cv2.waitKey(10000)\\n cv2.destroyAllWindows()\\n camera.release()\\n pygame.quit() # cleanup the camera and close any open windows\\n else:\\n print(\\\"Thank you for trying CVPaint!\\\")\\n pygame.quit()\\n camera.release()\\n cv2.destroyAllWindows()\",\n \"def save_image(image, file_name):\\n io.imsave(file_name,image)\",\n \"def save_photo():\\n save_name = filedialog.asksaveasfilename(initialdir=\\\"10.APOD Viewer/\\\", title=\\\"Save Image\\\", filetype=((\\\"JPEG\\\", \\\"*.jpg\\\"), (\\\"All Files\\\", \\\"*.*\\\")))\\n img.save(save_name + \\\".jpg\\\")\",\n \"def resize_and_crop(img, savePath, size, crop_type='middle'):\\n\\t# If height is higher we resize vertically, if not we resize horizontally\\n\\n\\t# Get current and desired ratio for the images\\n\\timg_ratio = img.size[0] / float(img.size[1])\\n\\tratio = size[0] / float(size[1])\\n\\tprint \\\"img_ratio = \\\" + str(img_ratio) + \\\". ratio = \\\" + str(ratio)\\n\\t#The image is scaled/cropped vertically or horizontally depending on the ratio\\n\\tif ratio > img_ratio:\\n\\t\\timg = img.resize((size[0], int(round(size[0] * img.size[1] / img.size[0]))),\\n\\t\\t Image.ANTIALIAS)\\n\\t\\t# Crop in the top, middle or bottom\\n\\t\\tif crop_type == 'top':\\n\\t\\t\\tbox = (0, 0, img.size[0], size[1])\\n\\t\\telif crop_type == 'middle':\\n\\t\\t\\tbox = (0, int(round((img.size[1] - size[1]) / 2)), img.size[0],\\n\\t\\t int(round((img.size[1] + size[1]) / 2)))\\n\\t\\telif crop_type == 'bottom':\\n\\t\\t\\tbox = (0, img.size[1] - size[1], img.size[0], img.size[1])\\n\\t\\telse :\\n\\t\\t\\traise ValueError('ERROR: invalid value for crop_type')\\n\\t\\tprint \\\"ratio > img_ratio. Cropping box: \\\"\\n\\t\\tprint box\\n\\t\\timg = img.crop(box)\\n\\telif ratio < img_ratio:\\n\\t\\timg = img.resize((int(round(size[1] * img.size[0] / img.size[1])), size[1]),\\n\\t\\t Image.ANTIALIAS)\\n\\t\\t# Crop in the top, middle or bottom\\n\\t\\tif crop_type == 'top':\\n\\t\\t\\tbox = (0, 0, size[0], img.size[1])\\n\\t\\telif crop_type == 'middle':\\n\\t\\t\\tbox = (int(round((img.size[0] - size[0]) / 2)), 0,\\n\\t\\t int(round((img.size[0] + size[0]) / 2)), img.size[1])\\n\\t\\telif crop_type == 'bottom':\\n\\t\\t\\tbox = (img.size[0] - size[0], 0, img.size[0], img.size[1])\\n\\t\\telse :\\n\\t\\t\\traise ValueError('ERROR: invalid value for crop_type')\\n\\n\\t\\tprint \\\"ratio < img_ratio. Cropping box: \\\"\\n\\t\\tprint box\\n\\t\\timg = img.crop(box)\\n\\telse :\\n\\t\\tprint \\\"so i guess the ratios are the same?\\\"\\n\\t\\timg = img.resize((size[0], size[1]),\\n\\t Image.ANTIALIAS)\\n\\t # If the scale is the same, we do not need to crop\\n\\tprint \\\"Saving thumb to \\\" + savePath\\n\\timg.save(savePath, \\\"JPEG\\\", quality=thumbCompressQual)\",\n \"def resize_and_save(local_file,new_file,maxsize=None,maxh=None,maxw=None,crop=None):\\n logging.debug(\\\"maxw = %s, maxsize=%s, crop=%s\\\" % (maxw,maxsize,crop))\\n img = Image.open(local_file)\\n width,height = img.size\\n width,height = float(width), float(height)\\n ratio = float(1)\\n if crop is not None:\\n size = float(maxsize)\\n if width <= height and width > size:\\n ratio = size/width\\n elif height < width and height > size:\\n ratio = size/height\\n else: \\n ratio = 1 # too small\\n elif maxsize:\\n size = float(maxsize)\\n if width >= height and width > size:\\n ratio = size/width\\n elif height > width and height > size:\\n ratio = size/height\\n else: \\n ratio = 1 # too small\\n elif maxh:\\n size = maxh\\n if height > size:\\n ratio = size/height\\n else:\\n # too small\\n ratio = 1\\n elif maxw:\\n size = maxw\\n if width > size:\\n ratio = size/width\\n else:\\n # too small\\n ratio = 1\\n else:\\n raise Exception(\\\"must specify max width, OR max size\\\")\\n \\n print(\\\"old: ratio = %s: size(x,y) = %s,%s\\\" % (ratio,width,height))\\n height = int(height*ratio)\\n width = int(width*ratio)\\n print(\\\"new ratio = %s: size(x,y) = %s,%s\\\" % (ratio,width,height))\\n img = img.resize((width, height),Image.ANTIALIAS)\\n if crop is not None:\\n log.debug(\\\"in crop %s\\\" % crop)\\n crop = int(crop)\\n if width > crop:\\n amt = int((int(width) - crop)/2)\\n img = img.crop((amt,0,amt + crop, crop))\\n elif height > crop:\\n amt = int((int(height) - crop)/2)\\n img = img.crop((0,amt,crop,amt+crop))\\n \\n log.debug(\\\"saving new file %s\\\" % new_file)\\n if img.mode != \\\"RGB\\\":\\n img = img.convert(\\\"RGB\\\")\\n img.save(new_file)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7306745","0.69884664","0.6980087","0.6949157","0.687741","0.6825131","0.6791875","0.66822034","0.66574806","0.66544116","0.66482884","0.66326034","0.65988314","0.6507213","0.6493506","0.6481142","0.6444658","0.63948953","0.6392374","0.63720816","0.63054436","0.63051605","0.6289981","0.62451404","0.6231402","0.62217045","0.6195159","0.61853844","0.61714345","0.61642516","0.6161903","0.6150007","0.6149161","0.61152095","0.61042523","0.61030036","0.61030036","0.6071148","0.6071148","0.6061958","0.6057172","0.6023021","0.60130525","0.59988093","0.5993894","0.5942661","0.59309256","0.59150463","0.58944094","0.5886841","0.5876215","0.586022","0.58544636","0.58527863","0.5851378","0.5850987","0.5847187","0.5831815","0.5830178","0.58215463","0.58094895","0.5806554","0.5789316","0.57762265","0.5768055","0.57569146","0.57560855","0.5733904","0.5727988","0.5720832","0.571351","0.5713194","0.5702762","0.56914425","0.56910384","0.5690435","0.56880677","0.568659","0.56801504","0.56794703","0.5663242","0.5658396","0.56574106","0.565603","0.5652596","0.5643002","0.5638774","0.5636214","0.56310004","0.56086963","0.5606049","0.5601165","0.55935293","0.5593118","0.5592296","0.55840707","0.55808586","0.5574353","0.5567536","0.5561707"],"string":"[\n \"0.7306745\",\n \"0.69884664\",\n \"0.6980087\",\n \"0.6949157\",\n \"0.687741\",\n \"0.6825131\",\n \"0.6791875\",\n \"0.66822034\",\n \"0.66574806\",\n \"0.66544116\",\n \"0.66482884\",\n \"0.66326034\",\n \"0.65988314\",\n \"0.6507213\",\n \"0.6493506\",\n \"0.6481142\",\n \"0.6444658\",\n \"0.63948953\",\n \"0.6392374\",\n \"0.63720816\",\n \"0.63054436\",\n \"0.63051605\",\n \"0.6289981\",\n \"0.62451404\",\n \"0.6231402\",\n \"0.62217045\",\n \"0.6195159\",\n \"0.61853844\",\n \"0.61714345\",\n \"0.61642516\",\n \"0.6161903\",\n \"0.6150007\",\n \"0.6149161\",\n \"0.61152095\",\n \"0.61042523\",\n \"0.61030036\",\n \"0.61030036\",\n \"0.6071148\",\n \"0.6071148\",\n \"0.6061958\",\n \"0.6057172\",\n \"0.6023021\",\n \"0.60130525\",\n \"0.59988093\",\n \"0.5993894\",\n \"0.5942661\",\n \"0.59309256\",\n \"0.59150463\",\n \"0.58944094\",\n \"0.5886841\",\n \"0.5876215\",\n \"0.586022\",\n \"0.58544636\",\n \"0.58527863\",\n \"0.5851378\",\n \"0.5850987\",\n \"0.5847187\",\n \"0.5831815\",\n \"0.5830178\",\n \"0.58215463\",\n \"0.58094895\",\n \"0.5806554\",\n \"0.5789316\",\n \"0.57762265\",\n \"0.5768055\",\n \"0.57569146\",\n \"0.57560855\",\n \"0.5733904\",\n \"0.5727988\",\n \"0.5720832\",\n \"0.571351\",\n \"0.5713194\",\n \"0.5702762\",\n \"0.56914425\",\n \"0.56910384\",\n \"0.5690435\",\n \"0.56880677\",\n \"0.568659\",\n \"0.56801504\",\n \"0.56794703\",\n \"0.5663242\",\n \"0.5658396\",\n \"0.56574106\",\n \"0.565603\",\n \"0.5652596\",\n \"0.5643002\",\n \"0.5638774\",\n \"0.5636214\",\n \"0.56310004\",\n \"0.56086963\",\n \"0.5606049\",\n \"0.5601165\",\n \"0.55935293\",\n \"0.5593118\",\n \"0.5592296\",\n \"0.55840707\",\n \"0.55808586\",\n \"0.5574353\",\n \"0.5567536\",\n \"0.5561707\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.70799524"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":88575,"cells":{"query":{"kind":"string","value":"Flip the image on the x or y axis"},"document":{"kind":"string","value":"def saveflip(image, fname, outpath, axis='x', preserve_name=False):\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"mirror_{axis}\")\n else:\n fpath = genSavePath(outpath, fname)\n im = copy(image)\n if axis == 'x':\n im = im.transpose(Image.FLIP_LEFT_RIGHT)\n elif axis == 'y':\n im = im.transpose(Image.FLIP_TOP_BOTTOM)\n else:\n raise Exception('No valid axis procvided for flipping: {} - received value: {}'.format(fname, axis))\n try:\n im.save(fpath, subsample=\"keep\", qtables=image.quantization, optimize=True)\n\n except IOError as m:\n print( \"Flipped({}) image creation failed for: {}. \\nReason:{}\".format(axis,fname,m))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def flip_image(img, vert=True):\n if vert:\n return img.transpose(Image.FLIP_TOP_BOTTOM)\n else:\n return img.transpose(Image.FLIP_LEFT_RIGHT)","def vflip(img):\n #if not _is_pil_image(img):\n # raise TypeError('img should be PIL Image. Got {}'.format(type(img)))\n\n return img.transpose(Image.FLIP_TOP_BOTTOM)","def __flip(img, flip, flip_type=Image.FLIP_LEFT_RIGHT):\n if flip:\n return img.transpose(flip_type)\n return img","def flip_horizontal(img):\r\n #reading image\r\n im = Image.open(\"filename\")\r\n\r\n #flipping image horizontally\r\n newimg = im.transpose(PIL.Image.FLIP_LEFT_RIGHT)\r\n \r\n return img","def flip_vertical(img):\r\n #reading image\r\n im = Image.open(\"filename\")\r\n\r\n #flipping image vertically\r\n newimg = im.transpose(PIL.Image.FLIP_TOP_BOTTOM)\r\n return img","def flip(self, horizontal):\n try:\n self._is_transformable()\n horizontal = get_int(horizontal)\n except NotTransformable as e:\n self._app[\"statusbar\"].message(str(e) + \" flip\", \"error\")\n return\n except StringConversionError as e:\n self._app[\"statusbar\"].message(str(e), \"error\")\n return\n images = self.get_images(\"Flipped\")\n # Apply changes\n for fil in images:\n if fil not in self._changes:\n self._changes[fil] = [0, 0, 0]\n if horizontal:\n self._changes[fil][1] = \\\n (self._changes[fil][1] + 1) % 2\n else:\n self._changes[fil][2] = \\\n (self._changes[fil][2] + 1) % 2\n # Flip the image shown\n if self._app.get_path() in images:\n self.emit(\"changed\", \"flip\", horizontal)\n # Reload thumbnails of flipped images immediately\n if self._app[\"thumbnail\"].toggled:\n self.apply()","def flip(self, mode='h'):\n # TODO: Implement the flip function. Remember to record the boolean values is_horizontal_flip and\n # is_vertical_flip.\n if mode == 'h':\n self.is_horizontal_flip = True\n self.x = np.flipud(self.x)\n elif mode == 'v':\n self.is_vertical_flip = True\n self.x = np.fliplr(self.x)\n else:\n self.is_vertical_flip = True\n self.is_horizontal_flip = True\n self.x = np.fliplr(self.x)\n self.x = np.flipud(self.x)\n # raise NotImplementedError\n #######################################################################\n # #\n # #\n # TODO: YOUR CODE HERE #\n # #\n # #\n #######################################################################","def flip(self, xflip=True, yflip=False):\n self.drawer.flush()\n img = self.img\n if xflip: img = img.transpose(PIL.Image.FLIP_LEFT_RIGHT)\n if yflip: img = img.transpose(PIL.Image.FLIP_TOP_BOTTOM)\n self.img = img\n self.update_drawer_img()\n return self","def flip(self, horizontally):\n\t\tself.currentPixbuf = self.currentPixbuf.flip(horizontally)\n\t\tself.scaleCache[1] = 0\n\t\tgc.collect()","def flip_image(image):\n return cv2.flip(image, flipCode=1)","def flip_image(image):\n\n return cv2.flip(image, 1)","def mirrorImage(self):\n\n im = Image.open(self.ActivePhoto)\n out = im.transpose(PIL.Image.FLIP_LEFT_RIGHT)\n out.save(self.ActivePhoto)\n self.photo.setPixmap(QtGui.QPixmap(self.ActivePhoto))\n print (\"Flipped image\")","def flip(self, x, y):\n self.pieces[x + (y * self.width)].flip()","def flip(self):","def flip(img, boolean=True):\n return pg.transform.flip(img, boolean, False)","def flip_image_vertical(image):\n return cv.flip(image, 1)","def flip_image_horizontal(image):\n return cv.flip(image, 0)","def flip(self):\n self.width, self.height = self.height, self.width","def flip_image(image, direction):\n prevShape = image.shape\n image, reshaped = reshape_to_cv_format(image, False)\n image = cv.flip(image, direction)\n if reshaped: \n image = image.reshape(prevShape)\n return image","def flip(img, code=0):\n\treturn cv2.flip(img, flipCode=code)","def flip_image(image, label):\n # Flip the image\n cv2.flip(image, 1, image)\n\n # Flip the label\n label[1] = image.shape[1] - label[1]","def set_flipped(self, x, y):\n self.pieces[x + (y * self.width)].set_flipped()","def flip_augmentation():\n return lambda image: ImageOps.flip(image)","def vflip(img, data_format='CHW'):\n _assert_image_tensor(img, data_format)\n\n h_axis = _get_image_h_axis(data_format)\n\n return img.flip(axis=[h_axis])","def flip_vertical(original_image: Image) -> Image :\r\n \r\n new_image = copy(original_image)\r\n \r\n pixel_width = get_width(original_image)\r\n pixel_height = get_height(original_image) \r\n\r\n \r\n for x in range(pixel_width) :\r\n for y in range(pixel_height) :\r\n original_vertical_pixel = get_color(original_image, x, y)\r\n opposite_vertical_pixel = pixel_height - 1 - y\r\n set_color(new_image, x, opposite_vertical_pixel, original_vertical_pixel)\r\n \r\n return new_image","def flip(self, x: bool, y: bool) -> 'BaseImage':\n assert isinstance(x, bool)\n assert isinstance(y, bool)\n assert (x or y), 'at least one axis should be True'\n self._surface = pygame.transform.flip(self._surface, x, y)\n return self","def flip_image(image_path, saved_location):\n image_obj = Image.open(image_path)\n rotated_image = image_obj.transpose(Image.FLIP_LEFT_RIGHT)\n rotated_image.save(saved_location)","def mirror(image):\n\n return cv2.flip(image, 1)","def flip(self, xbool, ybool):\n self._surf = pygame.transform.flip(self._surf, xbool, ybool).convert_alpha()","def td_flip(self):\n self.cw_rotate()\n self.cw_rotate()\n self.lr_flip()\n self.find_edges()","def flip_image(image, rects, axis = 1):\n\n if axis not in [-1,0,1]:\n return image, rects\n\n height = image.shape[0]\n widht = image.shape[1]\n \n image = cv2.flip(image,axis)\n\n if axis == 1:\n rects[:,1] = widht - rects[:,1]\n rects[:,3] = widht - rects[:,3]\n rects[:,3], rects[:,1] = rects[:,1].copy(),rects[:,3].copy()\n elif axis == 0:\n rects[:,2] = height - rects[:,2]\n rects[:,4] = height - rects[:,4]\n rects[:,4], rects[:,2] = rects[:,2].copy(),rects[:,4].copy()\n elif axis == -1:\n rects[:,1] = widht - rects[:,1]\n rects[:,3] = widht - rects[:,3]\n rects[:,3], rects[:,1] = rects[:,1].copy(),rects[:,3].copy()\n rects[:,2] = height - rects[:,2]\n rects[:,4] = height - rects[:,4]\n rects[:,4], rects[:,2] = rects[:,2].copy(),rects[:,4].copy()\n\n return image, rects","def _augment(img):\r\n return flip(img, axis=2)","def flip_vertical(image: Image) -> Image:\r\n flipped_image = copy(image)\r\n middle_pixel = get_width(flipped_image) // 2\r\n width = get_width(flipped_image)\r\n height = get_height(flipped_image)\r\n \r\n for x in range(middle_pixel):\r\n for y in range(height):\r\n r,g,b = get_color(image,x,y)\r\n new_r, new_g, new_b = get_color(image, abs(width-x) - 1, y)\r\n set_color(flipped_image,x,y,create_color(new_r,new_g,new_b))\r\n set_color(flipped_image,width-x-1,y,create_color(r,g,b))\r\n \r\n return flipped_image","def flip_images(x, y):\n flip_i = random.sample(range(x.shape[0]), int(x.shape[0] / 2))\n x[flip_i] = x[flip_i, :, ::-1, :]\n y[flip_i] = -y[flip_i]\n\n return x, y","def fliplr(img):\n inv_idx = torch.arange(img.size(3) - 1, -1, -1).long() # N x C x H x W\n img_flip = img.index_select(3, inv_idx)\n\n return img_flip","def vflip(img):\n if not _is_numpy_image(img):\n raise TypeError('img should be nparray Image. Got {}'.format(type(img)))\n\n return cv2.flip(img, 0)","def flip(tensor, axis=None):\n raise NotImplementedError","def _augment(img):\n return flip(img, axis=2)","def convert_flip(g, op, block):\n\n x = g.get_node(op.input(\"X\")[0])\n axis = op.attr(\"axis\")\n\n for i, ax in enumerate(axis):\n if i == 0:\n out = _op.reverse(x, ax)\n else:\n out = _op.reverse(out, ax)\n\n g.add_node(op.output(\"Out\")[0], out)","def flip_vertical(image: Image) -> Image:\r\n flipped_image = copy(image)\r\n middle_pixel = get_width(flipped_image) // 2\r\n width = get_width(flipped_image)\r\n height = get_height(flipped_image)\r\n\r\n for x in range(middle_pixel):\r\n for y in range(height):\r\n r, g, b = get_color(image, x, y)\r\n new_r, new_g, new_b = get_color(image, abs(width - x) - 1, y)\r\n set_color(flipped_image, x, y, create_color(new_r, new_g, new_b))\r\n set_color(flipped_image, width - x - 1, y, create_color(r, g, b))\r\n\r\n return flipped_image","def flip(flip_x=False, flip_y=False): \r\n x, y = 1, 1\r\n if flip_x:\r\n x = np.random.choice((-1,1))\r\n if flip_y:\r\n y = np.random.choice((-1,1))\r\n return np.array(((x, 0, 0),\r\n (0, y, 0),\r\n (0, 0, 1)), dtype=np.float)","def flip_axes(input_file, flipx=True, flipy=True, flipz=False,\n use_matrix=False, use_header=True):\n import os\n import numpy as np\n import nibabel as nb\n\n # Load image volume\n img = nb.load(input_file)\n dat = img.get_data()\n if use_matrix:\n mat = img.get_affine()\n if use_header:\n hdr = img.get_header()\n lenx, leny, lenz = np.shape(dat)\n dat_new = np.zeros((lenx, leny, lenz))\n\n # Flip x\n if flipx:\n for x in range(lenx):\n dat_new[lenx-1-x,:,:] = dat[x,:,:]\n\n # Flip y\n if flipy:\n for y in range(leny):\n dat_new[:,leny-1-y,:] = dat[:,y,:]\n\n # Flip z\n if flipz:\n for z in range(lenz):\n dat_new[:,:,lenz-1-z] = dat[:,:,z]\n\n # Save output\n out_file = 'reorient_' + os.path.basename(input_file)\n if use_matrix:\n if use_header:\n img = nb.Nifti1Image(dat_new, mat, hdr)\n else:\n img = nb.Nifti1Image(dat_new, mat)\n elif use_header:\n img = nb.Nifti1Image(dat_new, np.eye(4,4), hdr)\n else:\n img = nb.Nifti1Image(dat_new, np.eye(4,4))\n\n img.to_filename(out_file)\n\n return out_file","def vflip(img):\n if not _is_numpy(img):\n raise TypeError('img should be Numpy Image. Got {}'.format(type(img)))\n\n return np.flipud(img)","def transform(x: np.array, params: TransformParams) -> np.array:\n if params.do_hor_flip:\n x = flip_axis(x, 1)\n\n if params.do_vert_flip:\n x = flip_axis(x, 0)\n\n return x","def flip(self):\n \n if self.faceup:\n self.faceup = False\n else:\n self.faceup = True","def hflip(img):\n #if not _is_pil_image(img):\n # raise TypeError('img should be PIL Image. Got {}'.format(type(img)))\n\n return img.transpose(Image.FLIP_LEFT_RIGHT)","def mirror(img):\n return img[:, ::-1]","def flip_horizontal(picture: Image) -> Image:\r\n \r\n hflip = copy(picture)\r\n width = get_width(picture)\r\n height = get_height(picture)\r\n \r\n for x in range(width):\r\n for y in range(height):\r\n original_hpixel = get_color(picture, x, y)\r\n hflip_pixel = (width - 1) - x\r\n set_color(hflip, hflip_pixel, y, original_hpixel)\r\n \r\n return hflip","def flip(imgs):\n x = random.choice([-1, 0, 1, 2])\n if x == 2:\n return imgs\n else:\n return [cv2.flip(img, x) for img in imgs]","def flip(self, bev_direction: str = 'horizontal') -> None:\n pass","def flip_h(image, gt):\n result_im = cv2.flip(image, 1)\n result_gt = cv2.flip(gt, 1)\n\n return result_im, result_gt","def img_add_flip(arr, flip_horiz = True, flip_vert = False):\r\n assert len(arr.shape) == 3, \"'arr' input array must be three dimensional\"\r\n arr_copy = arr.copy()\r\n if flip_horiz:\r\n arr_copy = np.fliplr(arr_copy)\r\n if flip_vert:\r\n arr_copy = np.flipud(arr_copy)\r\n return arr_copy","def image_flip(image, direction):\n im_size = image.get_shape().as_list()\n if direction == 'left_right':\n flip_function = tf.image.random_flip_left_right\n elif direction == 'up_down':\n flip_function = tf.image.random_flip_up_down\n else:\n raise NotImplementedError\n\n if len(im_size) == 3:\n return flip_function(image)\n elif len(im_size) == 4:\n if im_size[-1] > 1:\n raise NotImplementedError\n trans_image = tf.transpose(tf.squeeze(image), [1, 2, 0])\n flip_image = tf.expand_dims(\n tf.transpose(flip_function(trans_image), [2, 0, 1]), axis=-1)\n return flip_image\n else:\n raise NotImplementedError","def flip_x(self):\n self.x_lim_helper.flip_limits()","def flip_x(self):\n self.x_lim_helper.flip_limits()","def flip_frame(frame, flip_code):\n return cv.flip(frame, flip_code)","def flip_horizontally(img, gt_boxes):\n flipped_img = tf.image.flip_left_right(img)\n flipped_gt_boxes = tf.stack([gt_boxes[..., 0],\n 1.0 - gt_boxes[..., 3],\n gt_boxes[..., 2],\n 1.0 - gt_boxes[..., 1]], -1)\n return flipped_img, flipped_gt_boxes","def flip(self, flip_x=True, flip_y=True):\n self._version += 1\n self._surf = pygame.transform.flip(self._surf,\n flip_x, flip_y).convert_alpha()\n return self","def fotoXO(self):\n\t\ttry:\n\t\t\timageP = self.cam.get_image()\n\t\t\tself.image = pygame.transform.flip(imageP, True, False)\n\t\texcept:\n\t\t\tpass\n\t\treturn self.image","def flipAndInvertImage(A: List[List[int]]) -> List[List[int]]:\n # 1'st pass: reverse every row\n for r in range(len(A)):\n reverse_row(r, A)\n # 2'nd pass: flip every row\n for r in range(len(A)):\n flip_row(r, A)\n return A","def flipAndInvertImage2(self, A: List[List[int]]) -> List[List[int]]:\n def invert(x):\n if x:\n return 0\n else:\n return 1\n\n for row in A:\n left, right = 0, len(row)-1\n while left <= right:\n row[left], row[right] = invert(row[right]), invert(row[left])\n left += 1\n right -= 1\n\n return A","def flip(self):\n if self.is_face_up:\n arcade.load_texture(self.back_file)\n self.is_face_up = False\n else:\n arcade.load_texture(self.face_file)\n self.is_face_up = True","def flip(a, axis):\n a_ndim = a.ndim\n if a_ndim < 1:\n raise core.core._AxisError('Input must be >= 1-d')\n\n axis = int(axis)\n if not -a_ndim <= axis < a_ndim:\n raise core.core._AxisError(\n 'axis must be >= %d and < %d' % (-a_ndim, a_ndim))\n\n return _flip(a, axis)","def random_flip(self, image, label, horizontal=False):\n\n flip = 1\n rand_float = uniform(0, 1)\n\n if horizontal:\n # 1 == vertical flip\n # 0 == horizontal flip\n flip = randint(0, 1)\n\n if rand_float > 0.5:\n image = cv2.flip(image, flip)\n label = cv2.flip(label, flip)\n\n return image, label","def flipAndInvertImage(self, A: List[List[int]]) -> List[List[int]]:\n return [[1- x for x in reversed(row)] for row in A]","def flip(self, axes=None):\n axes = self._make_axes_as_num(axes)\n vals = self.values\n if 0 in axes:\n vals = vals[::-1, :]\n if 1 in axes:\n vals = vals[:, ::-1]\n return Signal2D(vals, index=self.index, columns=self.columns)","def horizontal_flip(img, steering_angle):\n flipped = cv2.flip(img, 1) # positive (>0) flip code means flipping about y-axis\n steering_angle = steering_angle * -1 # change sign of steering angle to account for flip\n return flipped, steering_angle","def image_augmentation(img):\n return np.fliplr(img)","def hflip(img):\n if not _is_numpy_image(img):\n raise TypeError('img should be nparray Image. Got {}'.format(type(img)))\n\n return cv2.flip(img, 1)","def setHorizontalFlip(self, flag):\n\t\tself.flipHorizontally = flag","def inverse_transform(data, flip, rotate):\n if flip == 'FLIP_LEFT_RIGHT':\n data = np.fliplr(data)\n\n if rotate == 'ROTATE_90':\n data = np.rot90(data, 3)\n\n if rotate == 'ROTATE_180':\n data = np.rot90(data, 2)\n\n if rotate == 'ROTATE_270':\n data = np.rot90(data, 1)\n\n return data","def horizontal_flip() -> Callable:\n return lambda img: TF.hflip(img)","def collate_fn_flip(self, batch):\n FT = torch.FloatTensor\n img, uvd_gt = zip(*batch)\n flip = random.randint(1, 10000)%2\n # Do flipping\n # 0 = left, 1 = right\n hand_side = 1\n if flip:\n hand_side = 0 \n\n new_img = []\n new_uvd = []\n for i, u in batch:\n if flip:\n i = i.transpose(Image.FLIP_LEFT_RIGHT)\n u[:, 0] = 0.999 - u[:, 0]\n i = np.asarray(i)\n i = i/255.0\n i = IMG.imgshape2torch(i)\n new_img.append(i)\n new_uvd.append(u)\n \n new_img = FT(new_img)\n new_uvd = FT(new_uvd)\n return new_img, new_uvd, hand_side","def flip_2d_image_and_label(image, label):\n image_flipped = cv2.flip(image, 1)\n\n # Flip the label\n width = image.shape[1]\n half_width = width / 2\n\n flipped_label = np.copy(label)\n\n x1 = label[0]\n x2 = label[2]\n\n diff = x1 - half_width\n # width of bounding box\n width_bb = x2 - x1\n assert(x2 > x1)\n\n if x1 < half_width:\n new_x2 = half_width + abs(diff)\n else:\n new_x2 = half_width - abs(diff)\n new_x = new_x2 - width_bb\n\n # since we are doing mirror flip,\n # the y's remain unchanged\n flipped_label[0] = int(new_x)\n flipped_label[2] = int(new_x2)\n\n return image_flipped, flipped_label","def lr_flip(self):\n for g in self.grid:\n g.reverse()","def flip_rotate(img):\r\n\r\n choice = int(8*np.random.rand())\r\n \r\n if choice == 0:\r\n return img\r\n if choice == 1:\r\n return np.rot90(img, 1)\r\n if choice == 2:\r\n return np.rot90(img, 2)\r\n if choice == 3:\r\n return np.rot90(img, 3)\r\n if choice == 4:\r\n return np.flip(img, 0)\r\n if choice == 5:\r\n return np.flip(img, 1)\r\n if choice == 6:\r\n return np.flip(np.rot90(img, 1), 0)\r\n if choice == 7:\r\n return np.flip(np.rot90(img, 1), 1)","def flipMat(image):\n retImage = cv.CreateMat(image.rows, image.cols, image.type)\n height = image.rows\n transMatrix = cv.CreateMatHeader(2, 3, cv.CV_32FC1)\n narr = numpy.array([[1, 0, 0], [0, -1, height]], numpy.float32)\n cv.SetData(transMatrix, narr, cv.CV_AUTOSTEP)\n cv.WarpAffine(image, retImage, transMatrix)\n return retImage","def flip(self, x, y, /, *args, **kwargs):\n return self._func(y, x, *args, **kwargs)","def hflip(img):\n if not _is_numpy(img):\n raise TypeError('img should be Numpy Image. Got {}'.format(type(img)))\n\n return np.fliplr(img)","def flip(self, index):\n head, tail = self.get_extreme_points(index)\n centroid = self.get_position(index)\n\n if tail is not None and centroid is not None:\n self.set_angle(index, points_angle(centroid, tail) )","def flip(self):\n self._start, self._end = self._end, self._start","def problem1():\n\n img = load_image(\"data/a1p1.png\")\n display_image(img)\n\n save_as_npy(\"a1p1.npy\", img)\n\n img1 = load_npy(\"a1p1.npy\")\n display_image(img1)\n\n img2 = mirror_horizontal(img1)\n display_image(img2)\n\n display_images(img1, img2)","def flip(h):\n return np.flip(h)","def flip(h):\n return np.flip(h)","def flipAndInvertImage(self, A: List[List[int]]) -> List[List[int]]:\n return [list(map(lambda x: 0 if x else 1, row[::-1])) for row in A]","def rotate_right_90(img):\r\n #reading image\r\n im = Image.open(\"filename\")\r\n \r\n #flipping image 90 degrees\r\n newimg = im.transpose(PIL.Image.ROTATE_90)\r\n \r\n return img","def setVerticalFlip(self, flag):\n\t\tif self.ext.lower() in [\"png\", \"jpg\", \"jpeg\"]:\n\t\t\tself.flipVertically = not flag\n\t\telse:\n\t\t\tself.flipVertically = flag","def flip(self, p):\n return -p","def flip(x, dim):\n dim = x.dim() + dim if dim < 0 else dim\n inds = tuple(slice(None, None) if i != dim\n else x.new(torch.arange(x.size(i) - 1, -1, -1).tolist()).long()\n for i in range(x.dim()))\n return x[inds]","def random_flip(image ):\n if random.randint(0,1):\n image = flipud(image) # vertical flip\n if random.randint(0,1):\n image = fliplr(image) # horizontal flip\n return image","def invert(self, img):\n return self.inverse()(img)","def flip(self, axes=None, inplace=False, i=False):\n d = _inplace_enabled_define_and_cleanup(self)\n super(DimensionCoordinate, d).flip(axes=axes, inplace=True)\n\n direction = d._custom.get(\"direction\")\n if direction is not None:\n d._custom[\"direction\"] = not direction\n\n return d","def sym_right_img(img):\n img = img.transpose(Image.FLIP_LEFT_RIGHT)\n return sym_left_img(img)","def vflip(source: np.ndarray) -> np.ndarray:\n assert len(source.shape) == 3, 'Shape is not rows x cols x channels'\n assert source.dtype == np.float, 'Images must be doubles.'\n h, w, c = source.shape\n result = np.empty([h, w, c])\n jit_vflip(result, source)\n return result","def flip_image(image, bboxes=None, left_right=True, up_down=False):\n image_shape = tf.shape(image)\n height = image_shape[0]\n width = image_shape[1]\n\n if bboxes is not None:\n # bboxes usually come from dataset as ints, but just in case we are\n # using flip for preprocessing, where bboxes usually are represented as\n # floats, we cast them.\n bboxes = tf.to_int32(bboxes)\n\n if left_right:\n image = tf.image.flip_left_right(image)\n if bboxes is not None:\n x_min, y_min, x_max, y_max, label = tf.unstack(bboxes, axis=1)\n new_x_min = width - x_max - 1\n new_y_min = y_min\n new_x_max = new_x_min + (x_max - x_min)\n new_y_max = y_max\n bboxes = tf.stack(\n [new_x_min, new_y_min, new_x_max, new_y_max, label], axis=1\n )\n\n if up_down:\n image = tf.image.flip_up_down(image)\n if bboxes is not None:\n x_min, y_min, x_max, y_max, label = tf.unstack(bboxes, axis=1)\n new_x_min = x_min\n new_y_min = height - y_max - 1\n new_x_max = x_max\n new_y_max = new_y_min + (y_max - y_min)\n bboxes = tf.stack(\n [new_x_min, new_y_min, new_x_max, new_y_max, label], axis=1\n )\n\n return_dict = {'image': image}\n if bboxes is not None:\n return_dict['bboxes'] = bboxes\n\n return return_dict","def flip_points(a):\n a = np.array(a)\n return np.flip(a, 1)","def flip(file_path, flip_dir):\n\n if flip_dir != 'v' and flip_dir != 'h':\n print('wrong parameter')\n return None\n \n folder, file_name, ext = parse_file_path(file_path)\n\n url = addr + '/img/flip'\n\n img = cv2.imread(file_path)\n\n _, img_encoded = cv2.imencode('.jpg', img)\n payload = img_encoded.tostring()\n response = requests.post(url, data = payload, params= {'dir': (0 if flip_dir == 'v' else 1})\n\n if response.status_code != 200:\n print(json.loads(response.content))\n return None\n \n img_array = uncompress_nparr(response.content)\n file_path = os.path.join(folder, file_name + '-' + random_string() + '-flip' + ext)\n cv2.imwrite(file_path, img_array)\n return file_path","def hflip(img, data_format='CHW'):\n _assert_image_tensor(img, data_format)\n\n w_axis = _get_image_w_axis(data_format)\n\n return img.flip(axis=[w_axis])","def transform(self, previousimage):","def vflip(self):\n for y in range(0, self.height // 2):\n for x in range(0, self.width):\n self._chars[x][y], self._chars[x][self.height - 1 - y] = self._chars[x][self.height - 1 - y], self._chars[x][y]\n self._fginfo[x][y], self._fginfo[x][self.height - 1 - y] = self._fginfo[x][self.height - 1 - y], self._fginfo[x][y]\n self._bginfo[x][y], self._bginfo[x][self.height - 1 - y] = self._bginfo[x][self.height - 1 - y], self._bginfo[x][y]\n self._strDirty = True"],"string":"[\n \"def flip_image(img, vert=True):\\n if vert:\\n return img.transpose(Image.FLIP_TOP_BOTTOM)\\n else:\\n return img.transpose(Image.FLIP_LEFT_RIGHT)\",\n \"def vflip(img):\\n #if not _is_pil_image(img):\\n # raise TypeError('img should be PIL Image. Got {}'.format(type(img)))\\n\\n return img.transpose(Image.FLIP_TOP_BOTTOM)\",\n \"def __flip(img, flip, flip_type=Image.FLIP_LEFT_RIGHT):\\n if flip:\\n return img.transpose(flip_type)\\n return img\",\n \"def flip_horizontal(img):\\r\\n #reading image\\r\\n im = Image.open(\\\"filename\\\")\\r\\n\\r\\n #flipping image horizontally\\r\\n newimg = im.transpose(PIL.Image.FLIP_LEFT_RIGHT)\\r\\n \\r\\n return img\",\n \"def flip_vertical(img):\\r\\n #reading image\\r\\n im = Image.open(\\\"filename\\\")\\r\\n\\r\\n #flipping image vertically\\r\\n newimg = im.transpose(PIL.Image.FLIP_TOP_BOTTOM)\\r\\n return img\",\n \"def flip(self, horizontal):\\n try:\\n self._is_transformable()\\n horizontal = get_int(horizontal)\\n except NotTransformable as e:\\n self._app[\\\"statusbar\\\"].message(str(e) + \\\" flip\\\", \\\"error\\\")\\n return\\n except StringConversionError as e:\\n self._app[\\\"statusbar\\\"].message(str(e), \\\"error\\\")\\n return\\n images = self.get_images(\\\"Flipped\\\")\\n # Apply changes\\n for fil in images:\\n if fil not in self._changes:\\n self._changes[fil] = [0, 0, 0]\\n if horizontal:\\n self._changes[fil][1] = \\\\\\n (self._changes[fil][1] + 1) % 2\\n else:\\n self._changes[fil][2] = \\\\\\n (self._changes[fil][2] + 1) % 2\\n # Flip the image shown\\n if self._app.get_path() in images:\\n self.emit(\\\"changed\\\", \\\"flip\\\", horizontal)\\n # Reload thumbnails of flipped images immediately\\n if self._app[\\\"thumbnail\\\"].toggled:\\n self.apply()\",\n \"def flip(self, mode='h'):\\n # TODO: Implement the flip function. Remember to record the boolean values is_horizontal_flip and\\n # is_vertical_flip.\\n if mode == 'h':\\n self.is_horizontal_flip = True\\n self.x = np.flipud(self.x)\\n elif mode == 'v':\\n self.is_vertical_flip = True\\n self.x = np.fliplr(self.x)\\n else:\\n self.is_vertical_flip = True\\n self.is_horizontal_flip = True\\n self.x = np.fliplr(self.x)\\n self.x = np.flipud(self.x)\\n # raise NotImplementedError\\n #######################################################################\\n # #\\n # #\\n # TODO: YOUR CODE HERE #\\n # #\\n # #\\n #######################################################################\",\n \"def flip(self, xflip=True, yflip=False):\\n self.drawer.flush()\\n img = self.img\\n if xflip: img = img.transpose(PIL.Image.FLIP_LEFT_RIGHT)\\n if yflip: img = img.transpose(PIL.Image.FLIP_TOP_BOTTOM)\\n self.img = img\\n self.update_drawer_img()\\n return self\",\n \"def flip(self, horizontally):\\n\\t\\tself.currentPixbuf = self.currentPixbuf.flip(horizontally)\\n\\t\\tself.scaleCache[1] = 0\\n\\t\\tgc.collect()\",\n \"def flip_image(image):\\n return cv2.flip(image, flipCode=1)\",\n \"def flip_image(image):\\n\\n return cv2.flip(image, 1)\",\n \"def mirrorImage(self):\\n\\n im = Image.open(self.ActivePhoto)\\n out = im.transpose(PIL.Image.FLIP_LEFT_RIGHT)\\n out.save(self.ActivePhoto)\\n self.photo.setPixmap(QtGui.QPixmap(self.ActivePhoto))\\n print (\\\"Flipped image\\\")\",\n \"def flip(self, x, y):\\n self.pieces[x + (y * self.width)].flip()\",\n \"def flip(self):\",\n \"def flip(img, boolean=True):\\n return pg.transform.flip(img, boolean, False)\",\n \"def flip_image_vertical(image):\\n return cv.flip(image, 1)\",\n \"def flip_image_horizontal(image):\\n return cv.flip(image, 0)\",\n \"def flip(self):\\n self.width, self.height = self.height, self.width\",\n \"def flip_image(image, direction):\\n prevShape = image.shape\\n image, reshaped = reshape_to_cv_format(image, False)\\n image = cv.flip(image, direction)\\n if reshaped: \\n image = image.reshape(prevShape)\\n return image\",\n \"def flip(img, code=0):\\n\\treturn cv2.flip(img, flipCode=code)\",\n \"def flip_image(image, label):\\n # Flip the image\\n cv2.flip(image, 1, image)\\n\\n # Flip the label\\n label[1] = image.shape[1] - label[1]\",\n \"def set_flipped(self, x, y):\\n self.pieces[x + (y * self.width)].set_flipped()\",\n \"def flip_augmentation():\\n return lambda image: ImageOps.flip(image)\",\n \"def vflip(img, data_format='CHW'):\\n _assert_image_tensor(img, data_format)\\n\\n h_axis = _get_image_h_axis(data_format)\\n\\n return img.flip(axis=[h_axis])\",\n \"def flip_vertical(original_image: Image) -> Image :\\r\\n \\r\\n new_image = copy(original_image)\\r\\n \\r\\n pixel_width = get_width(original_image)\\r\\n pixel_height = get_height(original_image) \\r\\n\\r\\n \\r\\n for x in range(pixel_width) :\\r\\n for y in range(pixel_height) :\\r\\n original_vertical_pixel = get_color(original_image, x, y)\\r\\n opposite_vertical_pixel = pixel_height - 1 - y\\r\\n set_color(new_image, x, opposite_vertical_pixel, original_vertical_pixel)\\r\\n \\r\\n return new_image\",\n \"def flip(self, x: bool, y: bool) -> 'BaseImage':\\n assert isinstance(x, bool)\\n assert isinstance(y, bool)\\n assert (x or y), 'at least one axis should be True'\\n self._surface = pygame.transform.flip(self._surface, x, y)\\n return self\",\n \"def flip_image(image_path, saved_location):\\n image_obj = Image.open(image_path)\\n rotated_image = image_obj.transpose(Image.FLIP_LEFT_RIGHT)\\n rotated_image.save(saved_location)\",\n \"def mirror(image):\\n\\n return cv2.flip(image, 1)\",\n \"def flip(self, xbool, ybool):\\n self._surf = pygame.transform.flip(self._surf, xbool, ybool).convert_alpha()\",\n \"def td_flip(self):\\n self.cw_rotate()\\n self.cw_rotate()\\n self.lr_flip()\\n self.find_edges()\",\n \"def flip_image(image, rects, axis = 1):\\n\\n if axis not in [-1,0,1]:\\n return image, rects\\n\\n height = image.shape[0]\\n widht = image.shape[1]\\n \\n image = cv2.flip(image,axis)\\n\\n if axis == 1:\\n rects[:,1] = widht - rects[:,1]\\n rects[:,3] = widht - rects[:,3]\\n rects[:,3], rects[:,1] = rects[:,1].copy(),rects[:,3].copy()\\n elif axis == 0:\\n rects[:,2] = height - rects[:,2]\\n rects[:,4] = height - rects[:,4]\\n rects[:,4], rects[:,2] = rects[:,2].copy(),rects[:,4].copy()\\n elif axis == -1:\\n rects[:,1] = widht - rects[:,1]\\n rects[:,3] = widht - rects[:,3]\\n rects[:,3], rects[:,1] = rects[:,1].copy(),rects[:,3].copy()\\n rects[:,2] = height - rects[:,2]\\n rects[:,4] = height - rects[:,4]\\n rects[:,4], rects[:,2] = rects[:,2].copy(),rects[:,4].copy()\\n\\n return image, rects\",\n \"def _augment(img):\\r\\n return flip(img, axis=2)\",\n \"def flip_vertical(image: Image) -> Image:\\r\\n flipped_image = copy(image)\\r\\n middle_pixel = get_width(flipped_image) // 2\\r\\n width = get_width(flipped_image)\\r\\n height = get_height(flipped_image)\\r\\n \\r\\n for x in range(middle_pixel):\\r\\n for y in range(height):\\r\\n r,g,b = get_color(image,x,y)\\r\\n new_r, new_g, new_b = get_color(image, abs(width-x) - 1, y)\\r\\n set_color(flipped_image,x,y,create_color(new_r,new_g,new_b))\\r\\n set_color(flipped_image,width-x-1,y,create_color(r,g,b))\\r\\n \\r\\n return flipped_image\",\n \"def flip_images(x, y):\\n flip_i = random.sample(range(x.shape[0]), int(x.shape[0] / 2))\\n x[flip_i] = x[flip_i, :, ::-1, :]\\n y[flip_i] = -y[flip_i]\\n\\n return x, y\",\n \"def fliplr(img):\\n inv_idx = torch.arange(img.size(3) - 1, -1, -1).long() # N x C x H x W\\n img_flip = img.index_select(3, inv_idx)\\n\\n return img_flip\",\n \"def vflip(img):\\n if not _is_numpy_image(img):\\n raise TypeError('img should be nparray Image. Got {}'.format(type(img)))\\n\\n return cv2.flip(img, 0)\",\n \"def flip(tensor, axis=None):\\n raise NotImplementedError\",\n \"def _augment(img):\\n return flip(img, axis=2)\",\n \"def convert_flip(g, op, block):\\n\\n x = g.get_node(op.input(\\\"X\\\")[0])\\n axis = op.attr(\\\"axis\\\")\\n\\n for i, ax in enumerate(axis):\\n if i == 0:\\n out = _op.reverse(x, ax)\\n else:\\n out = _op.reverse(out, ax)\\n\\n g.add_node(op.output(\\\"Out\\\")[0], out)\",\n \"def flip_vertical(image: Image) -> Image:\\r\\n flipped_image = copy(image)\\r\\n middle_pixel = get_width(flipped_image) // 2\\r\\n width = get_width(flipped_image)\\r\\n height = get_height(flipped_image)\\r\\n\\r\\n for x in range(middle_pixel):\\r\\n for y in range(height):\\r\\n r, g, b = get_color(image, x, y)\\r\\n new_r, new_g, new_b = get_color(image, abs(width - x) - 1, y)\\r\\n set_color(flipped_image, x, y, create_color(new_r, new_g, new_b))\\r\\n set_color(flipped_image, width - x - 1, y, create_color(r, g, b))\\r\\n\\r\\n return flipped_image\",\n \"def flip(flip_x=False, flip_y=False): \\r\\n x, y = 1, 1\\r\\n if flip_x:\\r\\n x = np.random.choice((-1,1))\\r\\n if flip_y:\\r\\n y = np.random.choice((-1,1))\\r\\n return np.array(((x, 0, 0),\\r\\n (0, y, 0),\\r\\n (0, 0, 1)), dtype=np.float)\",\n \"def flip_axes(input_file, flipx=True, flipy=True, flipz=False,\\n use_matrix=False, use_header=True):\\n import os\\n import numpy as np\\n import nibabel as nb\\n\\n # Load image volume\\n img = nb.load(input_file)\\n dat = img.get_data()\\n if use_matrix:\\n mat = img.get_affine()\\n if use_header:\\n hdr = img.get_header()\\n lenx, leny, lenz = np.shape(dat)\\n dat_new = np.zeros((lenx, leny, lenz))\\n\\n # Flip x\\n if flipx:\\n for x in range(lenx):\\n dat_new[lenx-1-x,:,:] = dat[x,:,:]\\n\\n # Flip y\\n if flipy:\\n for y in range(leny):\\n dat_new[:,leny-1-y,:] = dat[:,y,:]\\n\\n # Flip z\\n if flipz:\\n for z in range(lenz):\\n dat_new[:,:,lenz-1-z] = dat[:,:,z]\\n\\n # Save output\\n out_file = 'reorient_' + os.path.basename(input_file)\\n if use_matrix:\\n if use_header:\\n img = nb.Nifti1Image(dat_new, mat, hdr)\\n else:\\n img = nb.Nifti1Image(dat_new, mat)\\n elif use_header:\\n img = nb.Nifti1Image(dat_new, np.eye(4,4), hdr)\\n else:\\n img = nb.Nifti1Image(dat_new, np.eye(4,4))\\n\\n img.to_filename(out_file)\\n\\n return out_file\",\n \"def vflip(img):\\n if not _is_numpy(img):\\n raise TypeError('img should be Numpy Image. Got {}'.format(type(img)))\\n\\n return np.flipud(img)\",\n \"def transform(x: np.array, params: TransformParams) -> np.array:\\n if params.do_hor_flip:\\n x = flip_axis(x, 1)\\n\\n if params.do_vert_flip:\\n x = flip_axis(x, 0)\\n\\n return x\",\n \"def flip(self):\\n \\n if self.faceup:\\n self.faceup = False\\n else:\\n self.faceup = True\",\n \"def hflip(img):\\n #if not _is_pil_image(img):\\n # raise TypeError('img should be PIL Image. Got {}'.format(type(img)))\\n\\n return img.transpose(Image.FLIP_LEFT_RIGHT)\",\n \"def mirror(img):\\n return img[:, ::-1]\",\n \"def flip_horizontal(picture: Image) -> Image:\\r\\n \\r\\n hflip = copy(picture)\\r\\n width = get_width(picture)\\r\\n height = get_height(picture)\\r\\n \\r\\n for x in range(width):\\r\\n for y in range(height):\\r\\n original_hpixel = get_color(picture, x, y)\\r\\n hflip_pixel = (width - 1) - x\\r\\n set_color(hflip, hflip_pixel, y, original_hpixel)\\r\\n \\r\\n return hflip\",\n \"def flip(imgs):\\n x = random.choice([-1, 0, 1, 2])\\n if x == 2:\\n return imgs\\n else:\\n return [cv2.flip(img, x) for img in imgs]\",\n \"def flip(self, bev_direction: str = 'horizontal') -> None:\\n pass\",\n \"def flip_h(image, gt):\\n result_im = cv2.flip(image, 1)\\n result_gt = cv2.flip(gt, 1)\\n\\n return result_im, result_gt\",\n \"def img_add_flip(arr, flip_horiz = True, flip_vert = False):\\r\\n assert len(arr.shape) == 3, \\\"'arr' input array must be three dimensional\\\"\\r\\n arr_copy = arr.copy()\\r\\n if flip_horiz:\\r\\n arr_copy = np.fliplr(arr_copy)\\r\\n if flip_vert:\\r\\n arr_copy = np.flipud(arr_copy)\\r\\n return arr_copy\",\n \"def image_flip(image, direction):\\n im_size = image.get_shape().as_list()\\n if direction == 'left_right':\\n flip_function = tf.image.random_flip_left_right\\n elif direction == 'up_down':\\n flip_function = tf.image.random_flip_up_down\\n else:\\n raise NotImplementedError\\n\\n if len(im_size) == 3:\\n return flip_function(image)\\n elif len(im_size) == 4:\\n if im_size[-1] > 1:\\n raise NotImplementedError\\n trans_image = tf.transpose(tf.squeeze(image), [1, 2, 0])\\n flip_image = tf.expand_dims(\\n tf.transpose(flip_function(trans_image), [2, 0, 1]), axis=-1)\\n return flip_image\\n else:\\n raise NotImplementedError\",\n \"def flip_x(self):\\n self.x_lim_helper.flip_limits()\",\n \"def flip_x(self):\\n self.x_lim_helper.flip_limits()\",\n \"def flip_frame(frame, flip_code):\\n return cv.flip(frame, flip_code)\",\n \"def flip_horizontally(img, gt_boxes):\\n flipped_img = tf.image.flip_left_right(img)\\n flipped_gt_boxes = tf.stack([gt_boxes[..., 0],\\n 1.0 - gt_boxes[..., 3],\\n gt_boxes[..., 2],\\n 1.0 - gt_boxes[..., 1]], -1)\\n return flipped_img, flipped_gt_boxes\",\n \"def flip(self, flip_x=True, flip_y=True):\\n self._version += 1\\n self._surf = pygame.transform.flip(self._surf,\\n flip_x, flip_y).convert_alpha()\\n return self\",\n \"def fotoXO(self):\\n\\t\\ttry:\\n\\t\\t\\timageP = self.cam.get_image()\\n\\t\\t\\tself.image = pygame.transform.flip(imageP, True, False)\\n\\t\\texcept:\\n\\t\\t\\tpass\\n\\t\\treturn self.image\",\n \"def flipAndInvertImage(A: List[List[int]]) -> List[List[int]]:\\n # 1'st pass: reverse every row\\n for r in range(len(A)):\\n reverse_row(r, A)\\n # 2'nd pass: flip every row\\n for r in range(len(A)):\\n flip_row(r, A)\\n return A\",\n \"def flipAndInvertImage2(self, A: List[List[int]]) -> List[List[int]]:\\n def invert(x):\\n if x:\\n return 0\\n else:\\n return 1\\n\\n for row in A:\\n left, right = 0, len(row)-1\\n while left <= right:\\n row[left], row[right] = invert(row[right]), invert(row[left])\\n left += 1\\n right -= 1\\n\\n return A\",\n \"def flip(self):\\n if self.is_face_up:\\n arcade.load_texture(self.back_file)\\n self.is_face_up = False\\n else:\\n arcade.load_texture(self.face_file)\\n self.is_face_up = True\",\n \"def flip(a, axis):\\n a_ndim = a.ndim\\n if a_ndim < 1:\\n raise core.core._AxisError('Input must be >= 1-d')\\n\\n axis = int(axis)\\n if not -a_ndim <= axis < a_ndim:\\n raise core.core._AxisError(\\n 'axis must be >= %d and < %d' % (-a_ndim, a_ndim))\\n\\n return _flip(a, axis)\",\n \"def random_flip(self, image, label, horizontal=False):\\n\\n flip = 1\\n rand_float = uniform(0, 1)\\n\\n if horizontal:\\n # 1 == vertical flip\\n # 0 == horizontal flip\\n flip = randint(0, 1)\\n\\n if rand_float > 0.5:\\n image = cv2.flip(image, flip)\\n label = cv2.flip(label, flip)\\n\\n return image, label\",\n \"def flipAndInvertImage(self, A: List[List[int]]) -> List[List[int]]:\\n return [[1- x for x in reversed(row)] for row in A]\",\n \"def flip(self, axes=None):\\n axes = self._make_axes_as_num(axes)\\n vals = self.values\\n if 0 in axes:\\n vals = vals[::-1, :]\\n if 1 in axes:\\n vals = vals[:, ::-1]\\n return Signal2D(vals, index=self.index, columns=self.columns)\",\n \"def horizontal_flip(img, steering_angle):\\n flipped = cv2.flip(img, 1) # positive (>0) flip code means flipping about y-axis\\n steering_angle = steering_angle * -1 # change sign of steering angle to account for flip\\n return flipped, steering_angle\",\n \"def image_augmentation(img):\\n return np.fliplr(img)\",\n \"def hflip(img):\\n if not _is_numpy_image(img):\\n raise TypeError('img should be nparray Image. Got {}'.format(type(img)))\\n\\n return cv2.flip(img, 1)\",\n \"def setHorizontalFlip(self, flag):\\n\\t\\tself.flipHorizontally = flag\",\n \"def inverse_transform(data, flip, rotate):\\n if flip == 'FLIP_LEFT_RIGHT':\\n data = np.fliplr(data)\\n\\n if rotate == 'ROTATE_90':\\n data = np.rot90(data, 3)\\n\\n if rotate == 'ROTATE_180':\\n data = np.rot90(data, 2)\\n\\n if rotate == 'ROTATE_270':\\n data = np.rot90(data, 1)\\n\\n return data\",\n \"def horizontal_flip() -> Callable:\\n return lambda img: TF.hflip(img)\",\n \"def collate_fn_flip(self, batch):\\n FT = torch.FloatTensor\\n img, uvd_gt = zip(*batch)\\n flip = random.randint(1, 10000)%2\\n # Do flipping\\n # 0 = left, 1 = right\\n hand_side = 1\\n if flip:\\n hand_side = 0 \\n\\n new_img = []\\n new_uvd = []\\n for i, u in batch:\\n if flip:\\n i = i.transpose(Image.FLIP_LEFT_RIGHT)\\n u[:, 0] = 0.999 - u[:, 0]\\n i = np.asarray(i)\\n i = i/255.0\\n i = IMG.imgshape2torch(i)\\n new_img.append(i)\\n new_uvd.append(u)\\n \\n new_img = FT(new_img)\\n new_uvd = FT(new_uvd)\\n return new_img, new_uvd, hand_side\",\n \"def flip_2d_image_and_label(image, label):\\n image_flipped = cv2.flip(image, 1)\\n\\n # Flip the label\\n width = image.shape[1]\\n half_width = width / 2\\n\\n flipped_label = np.copy(label)\\n\\n x1 = label[0]\\n x2 = label[2]\\n\\n diff = x1 - half_width\\n # width of bounding box\\n width_bb = x2 - x1\\n assert(x2 > x1)\\n\\n if x1 < half_width:\\n new_x2 = half_width + abs(diff)\\n else:\\n new_x2 = half_width - abs(diff)\\n new_x = new_x2 - width_bb\\n\\n # since we are doing mirror flip,\\n # the y's remain unchanged\\n flipped_label[0] = int(new_x)\\n flipped_label[2] = int(new_x2)\\n\\n return image_flipped, flipped_label\",\n \"def lr_flip(self):\\n for g in self.grid:\\n g.reverse()\",\n \"def flip_rotate(img):\\r\\n\\r\\n choice = int(8*np.random.rand())\\r\\n \\r\\n if choice == 0:\\r\\n return img\\r\\n if choice == 1:\\r\\n return np.rot90(img, 1)\\r\\n if choice == 2:\\r\\n return np.rot90(img, 2)\\r\\n if choice == 3:\\r\\n return np.rot90(img, 3)\\r\\n if choice == 4:\\r\\n return np.flip(img, 0)\\r\\n if choice == 5:\\r\\n return np.flip(img, 1)\\r\\n if choice == 6:\\r\\n return np.flip(np.rot90(img, 1), 0)\\r\\n if choice == 7:\\r\\n return np.flip(np.rot90(img, 1), 1)\",\n \"def flipMat(image):\\n retImage = cv.CreateMat(image.rows, image.cols, image.type)\\n height = image.rows\\n transMatrix = cv.CreateMatHeader(2, 3, cv.CV_32FC1)\\n narr = numpy.array([[1, 0, 0], [0, -1, height]], numpy.float32)\\n cv.SetData(transMatrix, narr, cv.CV_AUTOSTEP)\\n cv.WarpAffine(image, retImage, transMatrix)\\n return retImage\",\n \"def flip(self, x, y, /, *args, **kwargs):\\n return self._func(y, x, *args, **kwargs)\",\n \"def hflip(img):\\n if not _is_numpy(img):\\n raise TypeError('img should be Numpy Image. Got {}'.format(type(img)))\\n\\n return np.fliplr(img)\",\n \"def flip(self, index):\\n head, tail = self.get_extreme_points(index)\\n centroid = self.get_position(index)\\n\\n if tail is not None and centroid is not None:\\n self.set_angle(index, points_angle(centroid, tail) )\",\n \"def flip(self):\\n self._start, self._end = self._end, self._start\",\n \"def problem1():\\n\\n img = load_image(\\\"data/a1p1.png\\\")\\n display_image(img)\\n\\n save_as_npy(\\\"a1p1.npy\\\", img)\\n\\n img1 = load_npy(\\\"a1p1.npy\\\")\\n display_image(img1)\\n\\n img2 = mirror_horizontal(img1)\\n display_image(img2)\\n\\n display_images(img1, img2)\",\n \"def flip(h):\\n return np.flip(h)\",\n \"def flip(h):\\n return np.flip(h)\",\n \"def flipAndInvertImage(self, A: List[List[int]]) -> List[List[int]]:\\n return [list(map(lambda x: 0 if x else 1, row[::-1])) for row in A]\",\n \"def rotate_right_90(img):\\r\\n #reading image\\r\\n im = Image.open(\\\"filename\\\")\\r\\n \\r\\n #flipping image 90 degrees\\r\\n newimg = im.transpose(PIL.Image.ROTATE_90)\\r\\n \\r\\n return img\",\n \"def setVerticalFlip(self, flag):\\n\\t\\tif self.ext.lower() in [\\\"png\\\", \\\"jpg\\\", \\\"jpeg\\\"]:\\n\\t\\t\\tself.flipVertically = not flag\\n\\t\\telse:\\n\\t\\t\\tself.flipVertically = flag\",\n \"def flip(self, p):\\n return -p\",\n \"def flip(x, dim):\\n dim = x.dim() + dim if dim < 0 else dim\\n inds = tuple(slice(None, None) if i != dim\\n else x.new(torch.arange(x.size(i) - 1, -1, -1).tolist()).long()\\n for i in range(x.dim()))\\n return x[inds]\",\n \"def random_flip(image ):\\n if random.randint(0,1):\\n image = flipud(image) # vertical flip\\n if random.randint(0,1):\\n image = fliplr(image) # horizontal flip\\n return image\",\n \"def invert(self, img):\\n return self.inverse()(img)\",\n \"def flip(self, axes=None, inplace=False, i=False):\\n d = _inplace_enabled_define_and_cleanup(self)\\n super(DimensionCoordinate, d).flip(axes=axes, inplace=True)\\n\\n direction = d._custom.get(\\\"direction\\\")\\n if direction is not None:\\n d._custom[\\\"direction\\\"] = not direction\\n\\n return d\",\n \"def sym_right_img(img):\\n img = img.transpose(Image.FLIP_LEFT_RIGHT)\\n return sym_left_img(img)\",\n \"def vflip(source: np.ndarray) -> np.ndarray:\\n assert len(source.shape) == 3, 'Shape is not rows x cols x channels'\\n assert source.dtype == np.float, 'Images must be doubles.'\\n h, w, c = source.shape\\n result = np.empty([h, w, c])\\n jit_vflip(result, source)\\n return result\",\n \"def flip_image(image, bboxes=None, left_right=True, up_down=False):\\n image_shape = tf.shape(image)\\n height = image_shape[0]\\n width = image_shape[1]\\n\\n if bboxes is not None:\\n # bboxes usually come from dataset as ints, but just in case we are\\n # using flip for preprocessing, where bboxes usually are represented as\\n # floats, we cast them.\\n bboxes = tf.to_int32(bboxes)\\n\\n if left_right:\\n image = tf.image.flip_left_right(image)\\n if bboxes is not None:\\n x_min, y_min, x_max, y_max, label = tf.unstack(bboxes, axis=1)\\n new_x_min = width - x_max - 1\\n new_y_min = y_min\\n new_x_max = new_x_min + (x_max - x_min)\\n new_y_max = y_max\\n bboxes = tf.stack(\\n [new_x_min, new_y_min, new_x_max, new_y_max, label], axis=1\\n )\\n\\n if up_down:\\n image = tf.image.flip_up_down(image)\\n if bboxes is not None:\\n x_min, y_min, x_max, y_max, label = tf.unstack(bboxes, axis=1)\\n new_x_min = x_min\\n new_y_min = height - y_max - 1\\n new_x_max = x_max\\n new_y_max = new_y_min + (y_max - y_min)\\n bboxes = tf.stack(\\n [new_x_min, new_y_min, new_x_max, new_y_max, label], axis=1\\n )\\n\\n return_dict = {'image': image}\\n if bboxes is not None:\\n return_dict['bboxes'] = bboxes\\n\\n return return_dict\",\n \"def flip_points(a):\\n a = np.array(a)\\n return np.flip(a, 1)\",\n \"def flip(file_path, flip_dir):\\n\\n if flip_dir != 'v' and flip_dir != 'h':\\n print('wrong parameter')\\n return None\\n \\n folder, file_name, ext = parse_file_path(file_path)\\n\\n url = addr + '/img/flip'\\n\\n img = cv2.imread(file_path)\\n\\n _, img_encoded = cv2.imencode('.jpg', img)\\n payload = img_encoded.tostring()\\n response = requests.post(url, data = payload, params= {'dir': (0 if flip_dir == 'v' else 1})\\n\\n if response.status_code != 200:\\n print(json.loads(response.content))\\n return None\\n \\n img_array = uncompress_nparr(response.content)\\n file_path = os.path.join(folder, file_name + '-' + random_string() + '-flip' + ext)\\n cv2.imwrite(file_path, img_array)\\n return file_path\",\n \"def hflip(img, data_format='CHW'):\\n _assert_image_tensor(img, data_format)\\n\\n w_axis = _get_image_w_axis(data_format)\\n\\n return img.flip(axis=[w_axis])\",\n \"def transform(self, previousimage):\",\n \"def vflip(self):\\n for y in range(0, self.height // 2):\\n for x in range(0, self.width):\\n self._chars[x][y], self._chars[x][self.height - 1 - y] = self._chars[x][self.height - 1 - y], self._chars[x][y]\\n self._fginfo[x][y], self._fginfo[x][self.height - 1 - y] = self._fginfo[x][self.height - 1 - y], self._fginfo[x][y]\\n self._bginfo[x][y], self._bginfo[x][self.height - 1 - y] = self._bginfo[x][self.height - 1 - y], self._bginfo[x][y]\\n self._strDirty = True\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.76031363","0.75496536","0.75196064","0.751224","0.7474454","0.7395922","0.7393975","0.73869336","0.7386315","0.7383523","0.7346391","0.73111284","0.72888714","0.7244896","0.72281134","0.7200845","0.7131485","0.7130178","0.7129639","0.71281487","0.71267927","0.7076869","0.70291156","0.7017386","0.70040727","0.6985608","0.6976754","0.6972783","0.6934945","0.6932188","0.69072706","0.6874737","0.6839652","0.6831815","0.68313104","0.68082154","0.67924917","0.6772184","0.67619616","0.672864","0.67202556","0.6658504","0.66551405","0.6648333","0.6628675","0.6624895","0.6580533","0.65790486","0.65344024","0.6483125","0.6482498","0.64530563","0.6440093","0.6438284","0.6438284","0.63944685","0.6389543","0.63858646","0.63769037","0.6369205","0.6324363","0.63183033","0.63155663","0.63151455","0.6307069","0.6291241","0.6291099","0.62910134","0.62907976","0.6288502","0.62847227","0.62846607","0.62834895","0.62738913","0.6261449","0.6254417","0.62527454","0.62452084","0.62401706","0.6236087","0.62220645","0.62210536","0.62064946","0.62064946","0.62014997","0.6197647","0.616647","0.6151079","0.6146002","0.61264795","0.6083568","0.6056612","0.6047492","0.6044332","0.6032763","0.60247797","0.60136276","0.60042906","0.6002687","0.6001162"],"string":"[\n \"0.76031363\",\n \"0.75496536\",\n \"0.75196064\",\n \"0.751224\",\n \"0.7474454\",\n \"0.7395922\",\n \"0.7393975\",\n \"0.73869336\",\n \"0.7386315\",\n \"0.7383523\",\n \"0.7346391\",\n \"0.73111284\",\n \"0.72888714\",\n \"0.7244896\",\n \"0.72281134\",\n \"0.7200845\",\n \"0.7131485\",\n \"0.7130178\",\n \"0.7129639\",\n \"0.71281487\",\n \"0.71267927\",\n \"0.7076869\",\n \"0.70291156\",\n \"0.7017386\",\n \"0.70040727\",\n \"0.6985608\",\n \"0.6976754\",\n \"0.6972783\",\n \"0.6934945\",\n \"0.6932188\",\n \"0.69072706\",\n \"0.6874737\",\n \"0.6839652\",\n \"0.6831815\",\n \"0.68313104\",\n \"0.68082154\",\n \"0.67924917\",\n \"0.6772184\",\n \"0.67619616\",\n \"0.672864\",\n \"0.67202556\",\n \"0.6658504\",\n \"0.66551405\",\n \"0.6648333\",\n \"0.6628675\",\n \"0.6624895\",\n \"0.6580533\",\n \"0.65790486\",\n \"0.65344024\",\n \"0.6483125\",\n \"0.6482498\",\n \"0.64530563\",\n \"0.6440093\",\n \"0.6438284\",\n \"0.6438284\",\n \"0.63944685\",\n \"0.6389543\",\n \"0.63858646\",\n \"0.63769037\",\n \"0.6369205\",\n \"0.6324363\",\n \"0.63183033\",\n \"0.63155663\",\n \"0.63151455\",\n \"0.6307069\",\n \"0.6291241\",\n \"0.6291099\",\n \"0.62910134\",\n \"0.62907976\",\n \"0.6288502\",\n \"0.62847227\",\n \"0.62846607\",\n \"0.62834895\",\n \"0.62738913\",\n \"0.6261449\",\n \"0.6254417\",\n \"0.62527454\",\n \"0.62452084\",\n \"0.62401706\",\n \"0.6236087\",\n \"0.62220645\",\n \"0.62210536\",\n \"0.62064946\",\n \"0.62064946\",\n \"0.62014997\",\n \"0.6197647\",\n \"0.616647\",\n \"0.6151079\",\n \"0.6146002\",\n \"0.61264795\",\n \"0.6083568\",\n \"0.6056612\",\n \"0.6047492\",\n \"0.6044332\",\n \"0.6032763\",\n \"0.60247797\",\n \"0.60136276\",\n \"0.60042906\",\n \"0.6002687\",\n \"0.6001162\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.71528536"},"document_rank":{"kind":"string","value":"16"}}},{"rowIdx":88576,"cells":{"query":{"kind":"string","value":"Save a watermarked version of the image. resize watermark to 10% of the image height, with a minimum height of 40"},"document":{"kind":"string","value":"def savewatermarked(image, fname, outpath, watermark, preserve_name=False):\n im = image.copy()\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"watermarked\")\n else:\n fpath = genSavePath(outpath, fname)\n \n targetheight = int(image.height / 10)\n waterwidthscaler = watermark.width / watermark.height\n targetwidth = int(targetheight * waterwidthscaler)\n # Enforce minimum size\n if targetheight < 40:\n targetheight = 40\n targetwidth = int(targetheight * waterwidthscaler)\n # It's too wide, skew it to fit.\n if targetwidth > image.width:\n targetwidth = int(mage.width)\n # Scale the watermark\n scaledwatermark = watermark.resize((targetwidth, targetheight))\n # Add it to the image\n im.paste(scaledwatermark, (im.width - targetwidth, im.height - targetheight))\n try:\n im.save(fpath, subsample=\"keep\", qtables=image.quantization, optimize=True)\n\n except IOError as m:\n print( \"Watermarked image creation failed for: {}. \\nReason:{}\".format(fname,m))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def add_watermark(self, image, watermark, position='scale', opacity=1, format=None):","def watermark(im, credits, opacity=1):\n # First resize mark to make it appropriate size\n logoURL = 'https://s3.amazonaws.com/static.thecrimson.com' + \\\n '/images/feature/thc-logo-large.png'\n imfile = StringIO.StringIO(urllib.urlopen(logoURL).read())\n mark = PIL.Image.open(imfile)\n mark = mark.resize((100, 10), PIL.Image.ANTIALIAS)\n if opacity < 1:\n mark = reduce_opacity(mark, opacity)\n if im.mode != 'RGBA':\n im = im.convert('RGBA')\n # create a transparent layer the size of the image and draw the\n # watermark in that layer.\n # font = imfont.truetype(font='/static/fonts/ColabLig-webfont.ttf',\n # size=15, index=0, encoding='')\n layer = PIL.Image.new('RGBA', im.size, (0, 0, 0, 0))\n draw = imdraw.Draw(im)\n position = (im.size[0] - mark.size[0] - 10, 10)\n layer.paste(mark, position)\n # draw.text((x, y),\"Sample Text\",(r,g,b),font)\n draw.text((10, im.size[1] - 20), credits, (255, 255, 255))\n # composite the watermark with the layer\n watermarkedImage = PIL.Image.composite(layer, im, layer)\n response = HttpResponse(content_type='image/png')\n watermarkedImage.save(response, 'PNG')\n return response","def watermark_image(self, watermark_path, pos_name):\n image = Image.open(self.path)\n watermark = Image.open(watermark_path)\n self.watermark_width, self.watermark_height = watermark.size\n pos = self.watermark_position(pos_name)\n\n parent_dir = os.path.dirname(self.output_path)\n if not os.path.exists(parent_dir):\n os.makedirs(parent_dir)\n\n watermark_ext = os.path.splitext(watermark_path)[-1]\n if watermark_ext in (\".png\", \".PNG\"):\n transparent = Image.new('RGBA', (self.width, self.height), (0, 0, 0, 0))\n transparent.paste(image, (0, 0))\n transparent.paste(watermark, pos, mask=watermark)\n self.output_path = \".\".join([os.path.splitext(self.output_path)[0], \"png\"])\n transparent.save(self.output_path)\n elif watermark_ext in (\".jpg\", \".JPG\", \".jpeg\", \".JPEG\"):\n image.paste(watermark, pos)\n image.save(self.output_path)\n\n return os.path.exists(self.output_path)","def waterMarkImages(imageFile,\n imageOutputPath,\n text,\n fontName=\"Bangers\",\n size=\"M\",\n opacity=255,\n position=\"BR\"):\n # TODO : Try to have color as an argument as well\n fileName = imageFile.split(os.path.sep)[-1]\n try:\n photo = Image.open(imageFile).convert(\"RGBA\")\n except IOError:\n raise WatermarkException(4, val=imageFile)\n\n width, height = photo.size\n\n COLOR = (255, 255, 255)\n\n textImage = Image.new('RGBA', (width, height), COLOR + (0, ))\n\n fontsize = _setSize(width, height, size)\n\n drawing = ImageDraw.Draw(textImage)\n\n if fontName in FONT_MAP:\n # * fontPath = \"PyWaterMark\\\\fonts\\\\\" + FONT_MAP[fontName] - ONLY DEVS\n fontPath = pkg_resources.resource_filename(\n 'PyWatermark', 'fonts/' + FONT_MAP[fontName])\n if not os.path.isfile(fontPath):\n raise WatermarkException(2, val=fontName)\n else:\n if not os.path.isfile(fontName):\n raise WatermarkException(3, val=fontName)\n\n font = ImageFont.truetype(fontPath, fontsize)\n\n textWidth, textHeight = drawing.textsize(text, font)\n\n pos = _setPosition(width, height, textWidth, textHeight, position)\n\n drawing.text(pos, text, fill=COLOR + (opacity, ), font=font)\n\n combined = Image.alpha_composite(photo, textImage)\n\n filenameSave = fileName.split('.')\n filenameSave[1] = 'wm.png'\n filenameSave = ''.join(filenameSave)\n # * Why you can't store JPEG images with transparency\n # * https://stackoverflow.com/questions/41413956/pil-unable-to-change-the-transparency-level-for-jpeg-image\n combined.save(imageOutputPath + '\\\\' + filenameSave)\n\n return filenameSave","def watermark(im, mark, position=None, adjust='tile', alpha=1):\n # Check input\n assert alpha >= 0 and alpha <= 1\n\n # Set watermark alpha\n if alpha < 1:\n mark = opacity(mark, alpha)\n if im.mode != 'RGBA':\n im = im.convert('RGBA')\n # Draw watermark in a transparent layer\n layer = Image.new('RGBA', im.size, (0,0,0,0))\n if adjust == 'tile':\n for y in range(0, im.size[1], mark.size[1]):\n for x in range(0, im.size[0], mark.size[0]):\n layer.paste(mark, (x, y))\n elif adjust == 'scale':\n # Scale preserving the aspect ratio\n ratio = min(\n float(im.size[0]) / mark.size[0], float(im.size[1]) / mark.size[1])\n w = int(mark.size[0] * ratio)\n h = int(mark.size[1] * ratio)\n mark = mark.resize((w, h))\n layer.paste(mark, ((im.size[0] - w) / 2, (im.size[1] - h) / 2))\n else:\n layer.paste(mark, position)\n # Composite watermark with layer\n return Image.composite(layer, im, layer)","def custom_watermark(self, canvas, doc):\n canvas.saveState()\n canvas.setFont('Helvetica', 45)\n canvas.setFillGray(0.80)\n canvas.rotate(self.watermark_rotation)\n canvas.drawCentredString(\n self.watermark_position_x,\n self.watermark_position_y,\n self.watermark_string\n )\n canvas.restoreState()","def watermark(self, image, transparency=0.0, left=0, top=0):\n with image.clone() as watermark_image:\n watermark_image.transparentize(transparency)\n self.composite(watermark_image, left, top)\n self.raise_exception()","def exportImg(self):\n if self.superSampling:\n print(\"Exporting with size adjusted\")\n self.img = self.img.resize((int(self.width/2),int(self.height/2)),Image.NEAREST)\n self.img.save(self.fileName,\"PNG\")","def __draw_watermark(self):\n if self.watermark_text is not None:\n self.fig.text(0.5, 0.5, self.watermark_text,\n fontsize=self.settings.otherParams[\"watermark.fontsize\"], color='gray',\n ha='center', va='center', alpha=0.3, rotation=65, transform=self.ax.transAxes)","def image_to_scratch(im, scratch_image_name):\n\tim.save(scratch_image_name, dpi=(200,200))","def WarpSave(fn, w=500,h=500, msg=True):\n MSG(\"WarpSave\")\n img = WarpImage(w,h)\n cv2.imwrite(fn,img)\n if msg:\n print \"Image written: \", fn\n return","def add_watermark(image, text, font=watermark_font) -> Image:\n rgba_image = image.convert('RGBA')\n text_overlay = Image.new('RGBA', rgba_image.size, (255, 255, 255, 0))\n image_draw = ImageDraw.Draw(text_overlay)\n\n text_size_x, text_size_y = image_draw.textsize(text, font=font)\n\n # Set text position.\n text_xy = (rgba_image.size[0] - text_size_x, rgba_image.size[1] - text_size_y)\n\n # Set text color and transparency.\n image_draw.text(text_xy, text, font=font, fill=(128, 128, 128, 180))\n image_with_watermark = Image.alpha_composite(rgba_image, text_overlay)\n return image_with_watermark","def imageprepare(filename):\n img = Image.open(filename).convert('L')\n rect = img.getbbox()\n im = img.crop(rect)\n im.save(filename + '_pressprocessed.png')\n\n width = float(im.size[0])\n height = float(im.size[1])\n newImage = Image.new('L', (28, 28), (0)) #creates white canvas of 28x28 pixels\n if width > height: #check which dimension is bigger\n #Width is bigger. Width becomes 20 pixels.\n nheight = int(round((20.0/width*height),0)) #resize height according to ratio width\n if (nheight == 0): #rare case but minimum is 1 pixel\n nheight = 1\n # resize and sharpen\n img = im.resize((20,nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\n wtop = int(round(((28 - nheight)/2),0)) #caculate horizontal pozition\n newImage.paste(img, (4, wtop)) #paste resized image on white canvas\n newImage.save(filename + '_final.png')\n else:\n #Height is bigger. Heigth becomes 20 pixels. \n nwidth = int(round((20.0/height*width),0)) #resize width according to ratio height\n if (nwidth == 0): #rare case but minimum is 1 pixel\n nwidth = 1\n # resize and sharpen\n img = im.resize((nwidth,20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\n wleft = int(round(((28 - nwidth)/2),0)) #caculate vertical pozition\n newImage.paste(img, (wleft, 4)) #paste resized image on white canvas\n newImage.save(filename + '_final.png')\n tv = list(newImage.getdata()) #get pixel values\n #normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\n tva = [ (x)*1.0/255.0 for x in tv] \n return tva","def Save_Image_Crop(img, x, y, width, height, filename = None, path = 'Predictions'):\n img = img[y:y+height, x:x+width,:]\n\n if filename is not None:\n try: \n os.mkdir(path)\n except OSError as error: \n print('') \n fig, ax = plt.subplots(figsize=(18, 20))\n ax.imshow(img)\n plt.tight_layout()\n plt.savefig(path + '/' + filename + '_Crop.png')","def compress_image(filename,k):","def write_jpeg(filename,band,skypos,tranges,skyrange,width=False,height=False,\n\t\t\t stepsz=1.,clobber=False,verbose=0,tscale=1000.,retries=20):\n\tscipy.misc.imsave(filename,countmap(band,skypos,tranges,skyrange,\n\t\t\t\t\t width=width,height=height,verbose=verbose,tscale=tscale,\n\t\t\t\t\t retries=retries))\n\treturn","def save_annotated_image(self, file: Path) -> None:\n pass","def saveImage(*args, annotation: Union[AnyStr, bool]=\"\", backgroundColor: Union[List[float,\n float, float], bool]=None, currentView: bool=True, defineTemplate: AnyStr=\"\",\n docTag: Union[AnyStr, bool]=\"\", dragCallback: Script=None, dropCallback:\n Script=None, enable: bool=True, enableBackground: bool=True, enableKeyboardFocus:\n bool=True, exists: bool=True, fullPathName: bool=True, height: Union[int, bool]=0,\n highlightColor: Union[List[float, float, float], bool]=None, image: Union[AnyStr,\n bool]=\"\", isObscured: bool=True, manage: bool=True, noBackground: bool=True,\n numberOfPopupMenus: bool=True, objectThumbnail: AnyStr=\"\", parent: Union[AnyStr,\n bool]=\"\", popupMenuArray: bool=True, preventOverride: bool=True, sceneFile:\n AnyStr=\"\", statusBarMessage: AnyStr=\"\", useTemplate: AnyStr=\"\", visible:\n bool=True, visibleChangeCommand: Union[Script, bool]=None, width: Union[int,\n bool]=0, q=True, query=True, e=True, edit=True, **kwargs)->Union[AnyStr, Any]:\n pass","def save_png(self, filename):\n post_script = self.canvas.postscript().encode()\n img = Image.open(io.BytesIO(post_script))\n img.save(filename, format=\"PNG\")","def add_watermark(self, text):\n self.watermark_text = text","def write_stitched_image(self):\r\n\r\n self.write_debug(\"End of train detected. Writing stitched image.\")\r\n cv2.imwrite(os.path.join(self.output_dir_stitched, 'stitched.jpg'), self.stitched_image)","def watermark_text(self, text, color, font_type, font_size, pos_name):\n image = Image.open(self.path)\n drawing = ImageDraw.Draw(image)\n text = text\n font = ImageFont.truetype(font_type, font_size)\n self.watermark_width, self.watermark_height = drawing.textsize(text, font)\n pos = self.watermark_position(pos_name)\n\n drawing.text(pos, text, fill=color, font=font)\n parent_dir = os.path.dirname(self.output_path)\n\n if not os.path.exists(parent_dir):\n os.makedirs(parent_dir)\n\n image.save(self.output_path)\n return os.path.exists(self.output_path)","def write_png(buffer, width, height, fileobj, dpi=None): # real signature unknown; restored from __doc__\n pass","def imageprepare(self,argv):\r\n\t\tim = Image.open(argv).convert('L')\r\n\t\twidth = float(im.size[0])\r\n\t\theight = float(im.size[1])\r\n\t\tnewImage = Image.new('L', (28, 28), (255)) # creates white canvas of 28x28 pixels\r\n\r\n\t\tif width > height: # check which dimension is bigger\r\n\t\t\t# Width is bigger. Width becomes 20 pixels.\r\n\t\t\tnheight = int(round((20.0 / width * height), 0)) # resize height according to ratio width\r\n\t\t\tif nheight == 0: # rare case but minimum is 1 pixel\r\n\t\t\t\tnheight = 1\r\n\t\t\t\t# resize and sharpen\r\n\t\t\timg = im.resize((20, nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\r\n\t\t\twtop = int(round(((28 - nheight) / 2), 0)) # caculate horizontal pozition\r\n\t\t\tnewImage.paste(img, (4, wtop)) # paste resized image on white canvas\r\n\t\telse:\r\n\t\t\t# Height is bigger. Heigth becomes 20 pixels.\r\n\t\t\tnwidth = int(round((20.0 / height * width), 0)) # resize width according to ratio height\r\n\t\t\tif (nwidth == 0): # rare case but minimum is 1 pixel\r\n\t\t\t\tnwidth = 1\r\n\t\t\t\t# resize and sharpen\r\n\t\t\timg = im.resize((nwidth, 20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\r\n\t\t\twleft = int(round(((28 - nwidth) / 2), 0)) # caculate vertical pozition\r\n\t\t\tnewImage.paste(img, (wleft, 4)) # paste resized image on white canvas\r\n\r\n\t\t# newImage.save(\"sample.png\")\r\n\r\n\t\ttv = list(newImage.getdata()) # get pixel values\r\n\r\n\t\t# normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\r\n\t\ttva = [(255 - x) * 1.0 / 255.0 for x in tv]\r\n\t\treturn tva","def _save_annotation(annotation, filename):\n\n pil_image = Image.fromarray(annotation.astype(dtype=np.uint8))\n '''\n with tf.io.gfile.GFile(filename, mode='w') as f:\n #with open(filename, mode='w') as f:\n print(f)\n pil_image.save(f, 'PNG')\n '''\n pil_image.save(filename)","def advance_watermark_to(self, new_watermark):\n self._add(WatermarkEvent(new_watermark))\n return self","def write_thumbnail(image_name, size):\n # TODO : use something else instead of image.thumbnail\n sizes = {\n 'small' : [30,40],\n 'medium' : [70,70],\n 'large' : [120,120]\n }\n image = Image.open(f'{WRITE_FOLDER}/{USER_NAME}/original/{image_name}')\n image.thumbnail((sizes[size][0], sizes[size][1]))\n image.save(f'{WRITE_FOLDER}/{USER_NAME}/{size}/{image_name}')","def save_image(lt_image, out_dir, filename, max_width=None):\n if not lt_image.stream:\n return\n\n filedata = lt_image.stream.get_data()\n out_file_name = join(out_dir, filename)\n\n bits_per_component = lt_image.stream.attrs['BitsPerComponent']\n if bits_per_component == 8:\n # カラーとグレー画像はそのまま保存\n with open(out_file_name, 'wb') as fp:\n fp.write(filedata)\n elif bits_per_component == 1:\n # モノクロ画像はfiledataから作成\n w, h = lt_image.stream.attrs['Width'], lt_image.stream.attrs['Height']\n img = Image.frombytes('1', (w, h), filedata)\n # グレー化、リサイズ、invertを行って保存\n img = img.convert('L').resize((w // 2, h // 2), Image.ANTIALIAS)\n img = ImageOps.invert(img)\n img.save(out_file_name)\n\n if max_width:\n print('max_width:', max_width)\n img = Image.open(out_file_name)\n w, h = img.size[:2]\n img_resize = img.resize((max_width, h * max_width // w), Image.ANTIALIAS)\n img_resize.save(out_file_name)","def imwrite(image, path):\n return scipy.misc.imsave(path, to_range(image, 0, 255, np.uint8))","def compress_image(filename = \"hubble.jpg\", s = 2):\n \n image = imread(filename)/255\n \n toShow = plt.subplot(121)\n \n #Color\n if len(np.shape(image)) == 3:\n #Set up original RGB values\n R = np.array(image[:,:,0])\n G = np.array(image[:,:,1])\n B = np.array(image[:,:,2])\n \n R, errR = svd_approx(R,s)\n G, errG = svd_approx(G,s)\n B, errB = svd_approx(B,s)\n imageF = np.dstack((R,G,B))\n err = errR + errG + errB\n toShow.imshow(imageF)\n toShow.set_title(\"New \" + str(err) + \", so \" + str((image.size-err)) + \" \\\"saved\\\"\")\n toShow.axis(\"off\")\n \n toShow = plt.subplot(122)\n toShow.set_title(\"Original \" + str(image.size))\n toShow = plt.imshow(image)\n #Gray\n else:\n imageF, err = svd_approx(image, s)\n# print(np.shape(imageF))\n toShow.imshow(imageF, cmap = \"gray\")\n toShow.set_title(\"New \" + str(err) + \", so \" + str((image.size-err)) + \" \\\"saved\\\"\")\n toShow.axis(\"off\")\n toShow = plt.subplot(122)\n toShow.set_title(\"Original \" + str(image.size))\n toShow = plt.imshow(image, cmap = \"gray\")\n \n plt.suptitle(\"MY PLOTS: \" + str((image.size-err)) + \" \\\"saved\\\" :p\")\n \n return\n raise NotImplementedError(\"Problem 5 Incomplete\")","def save_as_fits(self, filename):","def imageprepare(argv):\r\n im = Image.open(argv).convert('L')\r\n width = float(im.size[0])\r\n height = float(im.size[1])\r\n newImage = Image.new('L', (28, 28), (255)) #creates white canvas of 28x28 pixels\r\n \r\n if width > height: #check which dimension is bigger\r\n #Width is bigger. Width becomes 20 pixels.\r\n nheight = int(round((20.0/width*height),0)) #resize height according to ratio width\r\n if (nheight == 0): #rare case but minimum is 1 pixel\r\n nheight = 1 \r\n # resize and sharpen\r\n img = im.resize((20,nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\r\n wtop = int(round(((28 - nheight)/2),0)) #caculate horizontal pozition\r\n newImage.paste(img, (4, wtop)) #paste resized image on white canvas\r\n else:\r\n #Height is bigger. Heigth becomes 20 pixels. \r\n nwidth = int(round((20.0/height*width),0)) #resize width according to ratio height\r\n if (nwidth == 0): #rare case but minimum is 1 pixel\r\n nwidth = 1\r\n # resize and sharpen\r\n img = im.resize((nwidth,20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\r\n wleft = int(round(((28 - nwidth)/2),0)) #caculate vertical pozition\r\n newImage.paste(img, (wleft, 4)) #paste resized image on white canvas\r\n \r\n #newImage.save(\"sample.png\")\r\n\r\n tv = list(newImage.getdata()) #get pixel values\r\n \r\n #normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\r\n tva = [ (255-x)*1.0/255.0 for x in tv] \r\n #print(tva)\r\n return tva","def save(image, name):\n from matplotlib import pyplot\n import matplotlib as mpl\n fig = pyplot.figure()\n ax = fig.add_subplot(1,1,1)\n imgplot = ax.imshow(image, cmap=mpl.cm.Greys)\n imgplot.set_interpolation('nearest')\n ax.xaxis.set_ticks_position('top')\n ax.yaxis.set_ticks_position('left')\n pyplot.savefig(name)","def save_image(self, filename):\n raster.save_image(filename, self.image, self.metadata)","def save_image(path, image): \n if len(image.shape) == 4:\n image = image.reshape((image.shape[1], image.shape[2], image.shape[3]))\n image = np.clip(image * 255.0, 0, 255).astype(np.uint8)\n skimage.io.imsave(path, image)","def save_image(self):\n self.compressed_image_id = str(uuid.uuid4().hex)\n plot.imsave(\n str(\n self.compressed_image_id + \"{}\").format(\n \".png\"), self.compressed_image)\n\n if self.verbose:\n print(\n \"Compressed image saved at \" + (\n str(self.compressed_image_id + \"{}\").format(\".png\")))","def identify_watermark(exam, image):\n img = cv2.imread(image)\n img = cv2.copyMakeBorder(img, 100, 100, 100, 100, cv2.BORDER_CONSTANT)\n\n corners = []\n bits = []\n\n def handle_click(event, x, y, flags, params):\n if event == cv2.EVENT_LBUTTONDOWN:\n bits.append(Point(x, y))\n cv2.circle(img, (x, y), 5, (255, 0, 0), -1)\n if event == cv2.EVENT_RBUTTONDOWN:\n corners.append(Point(x, y))\n cv2.circle(img, (x, y), 5, (0, 255, 0), -1)\n\n cv2.namedWindow(\"image\")\n cv2.setMouseCallback(\"image\", handle_click)\n while True:\n cv2.imshow(\"image\", img)\n if cv2.waitKey(20) & 0xFF == 13:\n break\n\n print(decode_watermark(get_exam(exam=exam), get_roster(exam=exam), corners, bits))","def create_artificial_image(self):\n background = self.BGI.create_background_image()\n star_PSF = self.PSF.create_star_PSF()\n header = self.HDR.create_header()\n\n fits.writeto(self.image_dir + self.image_name + '.fits',\n background + star_PSF, overwrite=True, header=header)","def saveborder(image, fname, outpath, width=20, colour=\"black\", preserve_name=False):\n im = image.copy()\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"border{width}{colour}\")\n else:\n fpath = genSavePath(outpath, fname)\n\n im = ImageOps.expand(im, border=width, fill=colour)\n try:\n im.save(fpath, subsample=\"keep\", qtables=image.quantization, optimize=True)\n\n except IOError as m:\n print(\"Border image creation failed for: {}. \\nReason:{}\".format(fname,m))","def writeImage(image, filename):\n Sky = [128,128,128]\n Building = [128,0,0]\n Pole = [192,192,128]\n Road_marking = [255,69,0]\n Road = [128,64,128]\n Pavement = [60,40,222]\n Tree = [128,128,0]\n SignSymbol = [192,128,128]\n Fence = [64,64,128]\n Car = [64,0,128]\n Pedestrian = [64,64,0]\n Bicyclist = [0,128,192]\n Unlabelled = [0,0,0]\n r = image.copy()\n g = image.copy()\n b = image.copy()\n label_colours = np.array([Sky, Building, Pole, Road_marking, Road, Pavement, Tree, SignSymbol, Fence, Car, Pedestrian, Bicyclist, Unlabelled])\n for l in range(0,12):\n r[image==l] = label_colours[l,0]\n g[image==l] = label_colours[l,1]\n b[image==l] = label_colours[l,2]\n rgb = np.zeros((image.shape[0], image.shape[1], 3))\n rgb[:,:,0] = r/1.0\n rgb[:,:,1] = g/1.0\n rgb[:,:,2] = b/1.0\n im = Image.fromarray(np.uint8(rgb))\n # im.save('/Users/koheiyamamoto/Desktop/SegNet/out/' + filename)\n im.save('./out/' + filename)","def save_image(img: Image, filename: str) -> None:\r\n img.save(filename)","def save_image(self):\n self.save()","def save_image(image, file_name):\n io.imsave(file_name,image)","def augment_img(img):\n img = random_hflip_img(img)\n img = cutout_img(img, size=12)\n img = zero_pad_and_crop_img(img)\n return img","def write(img, path):\n create_directories_for_file_name(path)\n writer = sitk.ImageFileWriter()\n writer.Execute(img, path, True)","def add_transparent_watermark(base_image, overlay_image):\n # Split out the transparency mask from the color info\n watermark_img = overlay_image[:, :, :3]\n watermark_mask = overlay_image[:, :, 3:]\n\n # Calculate the inverse mask\n background_mask = 255 - watermark_mask\n\n # Turn background_mask into three channel, so we can use weight\n background_mask = cv2.cvtColor(background_mask, cv2.COLOR_GRAY2BGR)\n\n # Create a masked out base image, and masked out watermark\n # Convert the images to floating point in range 0.0 - 1.0\n base_part = (base_image * (1 / 255.0)) * (background_mask * (1 / 255.0))\n watermark_part = (watermark_img * (1 / 255.0)) * (background_mask * (1 / 255.0))\n\n # Add them together, rescale back to an 8bit integer image\n return np.uint8(cv2.addWeighted(base_part, 255.0, watermark_part, 255.0, 0.0))","def adjust(self, image):\n ...","def overlay_image(image_to_show, image_to_add, directory=None):\n \n direcx = \"/Documents/1.4.5 Images/\"#put a condition pls\n if directory == None:\n directory = os.getcwd()\n print directory\n new_image = PIL.Image.open(directory + direcx + image_to_show)\n new_imager = PIL.Image.open(directory + direcx + image_to_show)\n new_imager.show()\n new_image2 = PIL.Image.open(directory + direcx + image_to_add)\n new_image2.show()\n \n width, height = new_imager.size\n print str(width) + \" \" + str(height)\n \n new_image22 = new_image2.resize((width,height), PIL.Image.ANTIALIAS)\n new_image22.show()\n\n new_imager.paste(new_image22, (0,0), new_image22)\n new_imager.show()\n #cohrt = PIL.Image.blend(new_imager, new_image22, alpha=0.5)\n #cohrt.show() #broked","def tiffwrite(filename, im):\n tf.imwrite(filename, im)","def export_image(self, bbox, zoomlevel, imagepath):\n assert has_pil, _(\"Cannot export image without python PIL\")\n grid,tile_bounds = self.grid_tiles(bbox, zoomlevel)\n width = len(grid[0])\n height = len(grid)\n widthpix = width * self.tile_size\n heightpix = height * self.tile_size\n result = Image.new(\"RGBA\", (widthpix, heightpix))\n offset = (0, 0)\n for i, row in enumerate(grid):\n for j, (x, y) in enumerate(row):\n offset = (j * self.tile_size, i * self.tile_size)\n img = self._tile_image(self.tile((zoomlevel, x, y)))\n result.paste(img, offset)\n if imagepath.endswith(\".tif\") or imagepath.endswith(\".tiff\"):\n # http://effbot.org/imagingbook/pil-index.htm#appendixes\n # Packbits, LZW, or JPEG\n # In the current version, PIL always writes uncompressed TIFF files.\n image_gdal=\"gdal_input.tif\"\n result.save(image_gdal, format=\"TIFF\", compression=\"JPEG\")\n self.geotif_image(tile_bounds,(widthpix,heightpix),imagepath,image_gdal)\n else:\n if imagepath.endswith(\".jpg\") or imagepath.endswith(\".jpeg\"):\n # IOError: encoder error -2 when writing image file\n result.save(imagepath, format=\"JPEG\", quality=int(self.jpg_quality), optimize=True, progressive=False)\n elif imagepath.endswith(\".png\") :\n result.save(imagepath, format=\"PNG\",optimize=True)\n else:\n result.save(imagepath)\n logger.info(_(\"-I-> export_image: Save resulting image to '%s' - bounds[%s]\") % (imagepath,tile_bounds))","def create_output_image(building_footprint, parcel_footprint, file_path):\n fig, ax = plt.subplots(figsize=(10, 10))\n gpd.overlay(building_footprint, parcel_footprint, how=\"symmetric_difference\").plot(\n ax=ax, color=\"lightgray\"\n )\n parcel_footprint.geometry.exterior.buffer(0.25).plot(ax=ax, color=\"black\")\n building_footprint.plot(ax=ax, color=\"black\")\n\n ax.patch.set_facecolor(\"white\")\n ax.patch.set_edgecolor(\"white\")\n fig.patch.set_visible(False)\n ax.axis(\"off\")\n fig.savefig(\n file_path,\n bbox_inches=\"tight\",\n pad_inches=0,\n facecolor=\"white\",\n edgecolor=\"white\",\n quality=IMG_QUALITY,\n )\n plt.close()","def generate_thumbnail(image_data, min_source_height, max_source_height, min_source_width, max_source_width, content_type, width, height, overlay_path, valign, top_crop_pct=None, bottom_crop_pct=None, left_crop_pct=None, right_crop_pct=None, crop_x=None, crop_y=None, post_crop_uniform_scale_pct=None):\n # figure out the width/height of the image from the datastore\n \n# img = images.Image(image_data=image_data)\n# img.crop(left_x=0.25, top_y=0.25, right_x=0.25, bottom_y=0.25)\n# img.resize(width=width, height=height)\n# logging.info('(b) w=%i, h=%i' % (img.width, img.height))\n# output = img.execute_transforms(output_encoding=img.format)\n \n image = images.Image(image_data)\n \n if min_source_height is not None and image.height < min_source_height:\n return None\n if max_source_height is not None and image.height > max_source_height:\n return None\n \n if min_source_width is not None and image.width < min_source_width:\n return None\n if max_source_width is not None and image.width > max_source_width:\n return None\n \n \n if content_type == 'image/png':\n output_encoding = images.PNG\n else:\n output_encoding = images.JPEG\n if crop_x is not None and crop_y is not None and valign is None and top_crop_pct is None and bottom_crop_pct is None and (image.width >= crop_x + width) and (image.height >= crop_y + height):\n fw = float(image.width)\n fh = float(image.height)\n try:\n output = images.crop(image_data, float(crop_x) / fw, float(crop_y) / fh, float(crop_x + width) / fw, float(crop_y + height) / fh, output_encoding=output_encoding)\n except:\n output = image_data\n else:\n if width > image.width and height > image.height:\n output = image_data\n# # this would result in scaling the image UP, that's no good\n# if image.width > image.height:\n# width = image.width\n# else:\n# height = image.height\n# \n# output = images.resize(image_data, width, height, output_encoding)\n else:\n output = rescale(image, width, height, halign='middle', valign=valign, top_crop_pct=top_crop_pct, bottom_crop_pct=bottom_crop_pct, left_crop_pct=left_crop_pct, right_crop_pct=right_crop_pct)\n \n if post_crop_uniform_scale_pct is not None:\n output = images.resize(output, width=int(width * post_crop_uniform_scale_pct), output_encoding=output_encoding)\n \n if overlay_path is not None:\n # read the overlay into memory\n overlay_data = open(overlay_path,'r').read()\n # composite the overlay onto the rescaled output\n if content_type == 'image/png':\n output_encoding = images.PNG\n else:\n output_encoding = images.JPEG\n output = images.composite(\n inputs=[\n (output,0,0,1.0,images.CENTER_CENTER),\n (overlay_data,0,0,1.0,images.CENTER_CENTER),\n ],\n width=width,\n height=height,\n output_encoding=output_encoding\n )\n return output","def imwrite(image, path):\n\n if image.ndim == 3 and image.shape[2] == 1: # for gray image\n image = np.array(image, copy=True)\n image.shape = image.shape[0:2]\n\n imgarray=((image+1.0)*127.5).astype(np.uint8)\n img=Image.fromarray(imgarray)\n img.save(path)","def stipple(img):\n\n\timg = threshold(img, 25)\n\n\treturn img","def weight_paste(pixSrc, pixPng, src_id, logo_id):\n weight = pixPng[:, :, 3] / 255\n weight = weight[:, :, np.newaxis]\n alpha = weight[logo_id]\n beta = 1 - alpha\n pixSrc[src_id] = pixSrc[src_id] * beta + pixPng[logo_id] * alpha\n return pixSrc","def write_image(path, image):\n image = tf.image.encode_jpeg(image, quality=100)\n return tf.io.write_file(path, image)","def imageprepare(argv):\n im = Image.open(argv).convert('L')\n width = float(im.size[0])\n height = float(im.size[1])\n newImage = Image.new('L', (28, 28), (255)) # creates white canvas of 28x28 pixels\n\n if width > height: # check which dimension is bigger\n # Width is bigger. Width becomes 20 pixels.\n nheight = int(round((20.0 / width * height), 0)) # resize height according to ratio width\n if (nheight == 0): # rare case but minimum is 1 pixel\n nheight = 1\n # resize and sharpen\n img = im.resize((20, nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\n wtop = int(round(((28 - nheight) / 2), 0)) # calculate horizontal position\n newImage.paste(img, (4, wtop)) # paste resized image on white canvas\n else:\n # Height is bigger. Heigth becomes 20 pixels.\n nwidth = int(round((20.0 / height * width), 0)) # resize width according to ratio height\n if (nwidth == 0): # rare case but minimum is 1 pixel\n nwidth = 1\n # resize and sharpen\n img = im.resize((nwidth, 20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\n wleft = int(round(((28 - nwidth) / 2), 0)) # caculate vertical pozition\n newImage.paste(img, (wleft, 4)) # paste resized image on white canvas\n\n # newImage.save(\"sample.png\n\n tv = list(newImage.getdata()) # get pixel values\n\n # normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\n tva = [(255 - x) * 1.0 / 255.0 for x in tv]\n print(tva)\n return tva","def advance_watermark_to_infinity(self):\n self.advance_watermark_to(timestamp.MAX_TIMESTAMP)\n return self","def embed_image_pred(image):\n image_pil2 = Image.fromarray((255 * image).astype('uint8'))\n #image_pil2 = image_pil.resize((256, 256))\n string_buf2 = StringIO.StringIO()\n image_pil2.save(string_buf2, format='png')\n data = string_buf2.getvalue().encode('base64').replace('\\n', '')\n return 'data:image/png;base64,' + data","def save_image(image):\n if config['save_images']['enabled']:\n directory = config['save_images']['destination']\n filename = datetime.datetime.now().strftime(\"%Y%m%d-%H%M%S%f\") + '.jpg'\n destination = os.path.join(directory, filename)\n logging.debug('saving image to %s', destination)\n f = open(destination, 'wb')\n f.write(image)\n f.close","def create_png(image, label):\n sv = \"/home/avojtekova/Desktop/final_results/star_det/generated_images/\" \n \n for i in range(len(image)):\n data = fits.getdata(image[i][0], ext = 0)\n norm = ImageNormalize(data,interval = ZScaleInterval(), stretch = LinearStretch())\n \n print(image[i][0])\n plt.imshow(data, cmap='Greys_r', origin='lower', norm=norm)#[1250:1750, 2000:2500] add this when you want just part of image \n plt.title(label[i])\n plt.axis('off')\n plt.tight_layout()\n plt.legend\n if i<2:\n if not os.path.isdir(sv + image[i][0][-33:-25] + \"/\") :\n os.makedirs(sv + image[i][0][-33:-25] + \"/\")\n plt.savefig(sv + image[i][0][-33:-25] + \"/\" + label[i]+ \"_\" + image[i][0][-33:-25] + \"_big.png\", dpi = 1000)#,bbox_inches='tight', pad_inches = 0) \n else:\n if not os.path.isdir(sv + image[i][0][-40:-32] + \"/\") :\n os.makedirs(sv + image[i][0][-40:-32] + \"/\")\n plt.savefig(sv + image[i][0][-40:-32] + \"/\" + label[i]+image[i][0][-40:-32] + \"_big.png\", dpi = 1000)#,bbox_inches='tight', pad_inches = 0)\n plt.close()","def save_image(self, filename):\n if filename[-4:] != '.pkl':\n filename + '.pkl'\n with open(filename, 'wb') as output: # Overwrites any existing file.\n pickle.dump(self, output, pickle.HIGHEST_PROTOCOL)","def save_image(filename, image):\n im = cv2.resize(image, None, fx=SCALE_DOWN, fy=SCALE_DOWN)\n cv2.imwrite(os.path.join(OUT_DIR, filename), im)","def update_PDF(pdf_file,new_name,path,watermark_text):\n \n # use reportlab to create a PDF that will be used \n # as a watermark on another PDF.\n c= canvas.Canvas(\"watermark.pdf\") # the watermark pdf\n c.setFont(\"Courier\", 70) # watermark font/size\n c.setFillGray(0.3,0.3) # watermark color/transparency\n c.saveState() # save current canvas state\n c.translate(500,100) # position the canvas\n c.rotate(45) # rotate the canvas\n #c.drawCentredString(0, 0, watermark_text) # write text\n c.drawCentredString(0, 300, watermark_text) # write text\n #c.drawCentredString(0, 600, watermark_text) # write text\n c.restoreState() # restore canvas state\n c.save()\n\n # initialize an output stream for the new, watermarked PDF\n output = PdfFileWriter()\n\n # read in the given PDF to memory that will have the watermark applied to it\n input1 = PdfFileReader(open(pdf_file, \"rb\")) \n page_count = input1.getNumPages()\n \n # loop through every page of the given PDF file and watermark it\n for i in range(page_count):\n # skip the first page if keep_grade_report==0\n if(keep_grade_report==0):\n if(i==0):\n i=1\n page_i = input1.getPage(i) # open up the current page\n watermark = PdfFileReader(open(\"watermark.pdf\", \"rb\")) # read in the watermark pdf to memory\n page_i.mergePage(watermark.getPage(0))# merge watermark pdf with page_i\n output.addPage(page_i) # add watermarked page_i to the output pdf\n\n # write the output of our new, watermarked PDF to the given given file name\n if not os.path.exists(path):\n os.makedirs(path)\n outputStream = open(path+new_name+\".pdf\", \"wb\") \n output.write(outputStream) \n outputStream.close()","def main():\r\n original = SimpleImage(\"images/poppy.png\")\r\n original.show()\r\n # shrink function\r\n after_shrink = shrink('images/poppy.png')\r\n after_shrink.show()","def write(self, file_name, width=1500.0, height=1000.0):\n with open(file_name, 'wb+') as fh:\n fh.write(self.make(width, height))","def extend_image(self):\n IJ.run(self.image, 'Select All', '')\n IJ.run(self.image, 'Copy', '')\n width = self.image.getWidth()\n height = int(self.image.getHeight() + self.extend_full)\n new_image = IJ.createImage(\n IMP.getTitle(), '32-bit black', width, height, 1)\n new_image.setRoi(0, 0, self.image.getWidth(), self.image.getHeight())\n IJ.run(new_image, 'Paste', '')\n IJ.run(new_image, 'Enhance Contrast', 'saturated=0.35')\n IJ.run(new_image, 'Select None', '')\n cal = Calibration(self.image)\n cal.pixelWidth = self.dispersion\n cal.xOrigin = self.offset\n new_image.setCalibration(cal)\n self.image = new_image\n return new_image","def save_image(image, filename, mode='PNG'):\n out = Image.new(mode='L', size=(image['width'], image['height']))\n out.putdata(image['pixels'])\n if isinstance(filename, str):\n out.save(filename)\n else:\n out.save(filename, mode)\n out.close()","def save_image(image, filename, mode='PNG'):\n out = Image.new(mode='L', size=(image['width'], image['height']))\n out.putdata(image['pixels'])\n if isinstance(filename, str):\n out.save(filename)\n else:\n out.save(filename, mode)\n out.close()","def save(self, filename):\n try:\n import PIL\n except ImportError:\n raise RuntimeError('Could not import PIL. PIL (pillow) is required to save fresnel images.')\n else:\n if self._output is None:\n self.render()\n image = PIL.Image.fromarray(self._output[:], mode='RGBA')\n image.save(filename)","def compress_image(image: BinaryIO, size: Tuple[int, int] = (512, 512)) -> File:\n im = Image.open(image)\n im_format = im.format\n im.thumbnail(size)\n if im.mode in (\"P\", \"RGBA\"):\n im = im.quantize()\n im_io = BytesIO()\n im.save(im_io, im_format)\n return File(im_io, image.name)","def saveImage(turtle, filename):\n ts = turtle.getscreen()\n tc = ts.getcanvas()\n tc.postscript(file=filename)","def save(self, fn):\n plt.imsave(fn, self.image)","def build_filler_images(self):","def write(self, image):\n raise NotImplementedError()","def make_montage(infile):\n\n #create a blank image\n blank = Image.new(\"RGB\", OUTPIC_SIZE ,(25,23,24,255))\n\n #paste the background\n bg = Image.open(BACKGROUND_FILENAME)\n blank.paste(bg,(0,0))\n \n #paste the raw picture\n im = Image.open(infile)\n \n # past on background\n blank.paste(im,OUTPIC_PHOTO_OFFSET)\n\n #paste the stickers layer on the pic (a transparent png)\n stickers = Image.open(STICKERS_FILENAME)\n blank.paste(stickers,(0,0),stickers)\n\n return blank","def write_greyscale(filename,pixels):\n height=len(pixels)\n width=len(pixels[0])\n with open(filename,'wb') as f:\n # BMP Header\n f.write(b'BM')\n size_bookmark=f.tell()\n f.write(b'\\x00\\x00\\x00\\x00')\n f.write(b'\\x00\\x00')\n f.write(b'\\x00\\x00')\n pixel_offset_bookmark=f.tell()\n f.write(b'\\x00\\x00\\x00\\x00')\n # PIXEL HEADER 40 BYTES\n f.write(b'\\x28\\x00\\x00\\x00')\n f.write(_int_to_bytes(width))\n f.write(_int_to_bytes(height))\n f.write(b'\\x01\\x00') #01 number of image planes, 08 bits per pixel\n f.write(b'\\x08\\x00') #01 number of image planes, 08 bits per pixel\n f.write(b'\\x00\\x00\\x00\\x00') # Internal bmp\n f.write(b'\\x00\\x00\\x00\\x00') # Internal bmp\n f.write(b'\\x00\\x00\\x00\\x00') # Internal bmp\n f.write(b'\\x00\\x00\\x00\\x00') # Internal bmp\n f.write(b'\\x00\\x00\\x00\\x00') # Internal bmp\n f.write(b'\\x00\\x00\\x00\\x00') # Internal bmp\n \n # Color palatte - linear greyscale\n for c in range(256):\n f.write(bytes((c,c,c,0))) #Blue,green,red,zero\n \n pixel_data_bookmark = f.tell()\n for row in reversed(pixels):\n row_data=bytes(row)\n f.write(row_data)\n padding=b'\\x00' * ( 4 - (len(row)%4))\n f.write(padding)\n \n #EOF\n eof_bookmark = f.tell()\n\n # Fill size placeholder\n f.seek(size_bookmark)\n f.write(_int_to_bytes(eof_bookmark))\n f.seek(pixel_offset_bookmark)\n f.write(_int_to_bytes(pixel_data_bookmark))","def testImage():\n width = 200\n height = 200\n image = BitMap( width, height )\n \n # create a loop in order to draw some pixels\n \n for col in range(width):\n if col % 10 == 0: print 'col is', col\n for row in range(height):\n if col % 10 == 0 or row % 10 == 0:\n image.plotPoint( col, row ) \n \n # we have now looped through every image pixel\n # next, we write it out to a file\n \n image.saveFile( \"test.bmp\" )\n #changing the col and row number determines how big the grid is for the picture or how zoomed in it is. Changing the and to or just makes the grid go from dotted grid to lines.","def write_text(text_to_write, image_size):\n image_text = Image.new(\"RGB\", image_size)\n font = ImageFont.load_default().font\n drawer = ImageDraw.Draw(image_text)\n\n #Text wrapping. Change parameters for different text formatting\n margin = offset = 10\n for line in textwrap.wrap(text_to_write, width=60):\n drawer.text((margin,offset), line, font=font)\n offset += 10\n return image_text","def saveImage(self, event):\r\n fileWritten = self.image.writeFile()\r\n self.statusBar.SetStatusText(\"Saved {}\".format(fileWritten))","def write_image(path, tokens, weights):\n\n f = render_attn_inner(tokens, weights)\n f.savefig(path, bbox_inches=\"tight\", frameon=False)\n plt.close(f)","def save_image(image, output_folder, output_name):\n\n\tfolder_path = compute_path(output_folder, 'dataset')\n\tos.makedirs(folder_path, exist_ok=True)\n\n\tfile_path = os.path.join(folder_path, output_name + '.png')\n\timage.save(file_path)","def save_tile_img(tif, xyz, dataset, tile_size, region, zone, save_path, display=False):\n \n prefix = f'{region}{zone}{dataset}_'\n x,y,z = xyz\n tile, mask = rt_main.tile(tif, x,y,z, tilesize=tile_size)\n if display: \n plt.imshow(np.moveaxis(tile,0,2))\n plt.show()\n \n skimage.io.imsave(f'{save_path}/{prefix}{z}_{x}_{y}.png',np.moveaxis(tile,0,2), check_contrast=False)","def dem_jpeg(dem_file):\n out_file = dem_file+'.jpeg'\n rsc_file = out_file+'.rsc'\n shutil.copy2(dem_file+'.rsc', rsc_file)\n # read data\n dem = readfile.read(dem_file)[0]\n print('dem.shape:',dem.shape)\n # figure size\n ds_shape = tuple(reversed(dem.shape))\n fig_dpi = 300\n fig_size = [i / fig_dpi for i in ds_shape]\n print('fig_size:',fig_size)\n # color range\n disp_min = np.nanmin(dem) - 4000\n disp_max = np.nanmax(dem) + 2000\n # prepare shaded relief\n ls = LightSource(azdeg=315, altdeg=45)\n dem_shade = ls.shade(dem, vert_exag=0.3, cmap=plt.get_cmap('gray'), vmin=disp_min, vmax=disp_max)\n dem_shade[np.isnan(dem_shade[:, :, 0])] = np.nan\n print('dem_shade.shape:',dem_shade.shape)\n # plot\n fig, ax = plt.subplots(figsize=fig_size)\n ax.imshow(dem_shade, interpolation='spline16', origin='upper')\n # get rid of whitespace on the side\n ax.axis('off')\n ax.get_xaxis().set_ticks([])\n ax.get_yaxis().set_ticks([])\n fig.subplots_adjust(left=0,right=1,bottom=0,top=1)\n # output\n print('save figure to file {}'.format(out_file))\n plt.savefig(out_file, transparent=True, dpi=300, pad_inches=0.0)\n \n #resize to desired size(FA 8/19, unclear why size is wrong)\n im = Image.open(out_file)\n im_out = im.resize(dem.shape, Image.NEAREST)\n im_out.save(out_file)\n \n #plt.show()","def save(\n self,\n output_path: str,\n show_confidence: bool = True,\n ) -> None:\n image = self.draw(show_confidence=show_confidence)\n save_image(image=image, path=output_path)","def image_optimize(file, width, height, force=False, resize=False):\n import Image as pil\n \n max_width = width\n max_height = height\n\n img = pil.open(file)\n \n #Fixing problem with gif\n if img.mode != \"RGB\":\n img = img.convert(\"RGB\")\n\n src_width, src_height = img.size\n src_ratio = float(src_width) / float(src_height)\n dst_width, dst_height = max_width, max_height\n dst_ratio = float(dst_width) / float(dst_height)\n \n if not force:\n if src_height > src_width:\n max_width = dst_height\n max_height = dst_width\n img.thumbnail((max_width, max_height), pil.ANTIALIAS)\n else:\n if dst_ratio < src_ratio:\n crop_height = src_height \n crop_width = crop_height * dst_ratio \n x_offset = int((src_width - crop_width)/2) \n y_offset = 0 \n else: \n crop_width = src_width\n crop_height = crop_width / dst_ratio\n x_offset = 0\n y_offset = int((src_height - crop_height)/3)\n img = img.crop((x_offset, y_offset, x_offset+int(crop_width),\n y_offset+int(crop_height)))\n img = img.resize((dst_width, dst_height), pil.ANTIALIAS)\n \n return img","def fileResizeObscure(new_filepath):\n # Resize\n img1 = Image.open(new_filepath)\n img2=image_reduce(img1)\n *** Stopped working here\n newpath=\"toupload\\\\%s\" % new_filepath\n # Block ID\n width=img2.size[0]\n height=img2.size[1]\n # Obscuring params were decided by trial and error using fraction of width and height\n x1=int(0.16*width)\n x2=int(0.28*width)\n y1=int(0.94*height)\n y2=int(0.98*height) \n # Faster but easier to snoop? should not be since it changes the pixels\n draw = ImageDraw.Draw(img2)\n draw.rectangle([(x1,y1),(x2,y2)],fill=\"white\")\n del draw\n \n img2.save(newpath,optimize=True,quality=95)","def save_PPM(self, fileName, imageComment = \"\"):\n file = open(add_ext_if_needed(fileName, \"ppm\"), \"w\")\n file.write(\"P3\\n\"); \n file.write(\"# \" + imageComment + \"\\n\")\n file.write(str(self._image.width()) + \" \" + str(self._image.height()) + \"\\n\")\n file.write(\"255\\n\")\n for y in range(self._image.height()):\n for x in range(self._image.width()):\n r,g,b = self.getPixel(x,y);\n file.write(str(r) + \" \" + str(g) + \" \" + str(b) + \"\\n\")\n file.close()","def save(self, filename):\n self.image.save(filename, self.options.img_format)","def save(self):\n\n self.image.save(\"./output/\" + self.name + \" pg\" + str(self._page) + \".png\")","def create_input_image(parcel_footprint, file_path):\n fig, ax = plt.subplots(figsize=(10, 10))\n parcel_footprint.plot(ax=ax, color=\"lightgray\")\n parcel_footprint.geometry.exterior.buffer(0.25).plot(ax=ax, color=\"black\")\n\n ax.patch.set_facecolor(\"white\")\n ax.patch.set_edgecolor(\"white\")\n fig.patch.set_visible(False)\n ax.axis(\"off\")\n fig.savefig(\n file_path,\n bbox_inches=\"tight\",\n pad_inches=0,\n facecolor=\"white\",\n edgecolor=\"white\",\n quality=IMG_QUALITY,\n )\n plt.close()","def overlay_image(image_to_show, image_to_add, directory=None):\n \n direcx = \"/Documents/1.4.5 Images/\"#put a condition pls\n if directory == None:\n directory = os.getcwd()\n print directory\n new_image = PIL.Image.open(directory + direcx + image_to_show)\n new_imager = PIL.Image.open(directory + direcx + image_to_show)\n new_imager.show()\n new_image2 = PIL.Image.open(directory + direcx + image_to_add)\n new_image2.show()\n width, height = new_imager.size\n print str(width) + \" \" + str(height)\n #print new_image\n #print new_image2\n #if image_to_show == \"\":\n # print_directory_list2()\n # return \"Use one of these\"\n new_image22 = new_image2.resize((width,height), PIL.Image.ANTIALIAS)\n new_image22.show()\n\n new_imager.paste(new_image22, (width, height), new_image22)\n new_imager.show()\n #cohrt = PIL.Image.blend(new_imager, new_image22, alpha=0.5)\n #cohrt.show()","def brandify_img(img, img_name, border_width_percentage=0.10, \\\nborder_width_cap=150, inner_border_width=7, \\\ninner_border_color=(50, 255, 50, 0), outer_border_color=(50, 50, 50, 0)):\n if img_name.startswith(\"Modified-\"):\n return\n width = img.size[0]\n height = img.size[1]\n # A new image that will be embiggened to fit the border\n border_width = int(float(width + height) / 2 * border_width_percentage)\n if border_width > border_width_cap:\n border_width = border_width_cap\n total_width = width + border_width * 2\n total_height = height + border_width * 2\n img.convert(mode=\"RGBA\")\n bordered_img = PIL.Image.new(\"RGBA\", img.size)\n bordered_img = PIL.ImageOps.expand(img, border=border_width)\n draw = PIL.ImageDraw.Draw(bordered_img)\n \n # Fill in the border for the image\n # The inner part of the border will be later covered up by the image itself\n draw_border_gradient(bordered_img, center_color=inner_border_color, \\\n outer_color=outer_border_color, excluding_region=(border_width, \\\n width + border_width, border_width, height + border_width))\n \n # Inner border\n # \"bb\" stands for border for border\n bb_color = (255 - 50, 255 - 50, 255 - 50, 255)\n draw.rectangle((border_width - inner_border_width, border_width - \\\n inner_border_width, width + border_width + inner_border_width, height + \\\n border_width + inner_border_width), fill=bb_color)\n \n # Add the original image\n bordered_img.paste(img, (border_width, border_width, width + border_width, \\\n height + border_width))\n \n # Add some basic design to the border\n # Add lines on each corner\n # Order is top left, top right, bottom left, bottom right\n draw.line((0, 0, border_width, border_width), fill=bb_color, width=3)\n draw.line((total_width, 0, total_width - border_width, border_width), \\\n fill=bb_color, width=3)\n draw.line((0, total_height, border_width, total_height - border_width), \\\n fill=bb_color, width=3)\n draw.line((total_width, total_height, total_width - border_width, \\\n total_height - border_width), fill=bb_color, width=3)\n \n # Apply the brand image\n new_width = int((float(brand_image.size[0]) / brand_image.size[1]) * \\\n border_width)\n new_height = border_width - inner_border_width\n resized_img = brand_image.resize((new_width, new_height))\n bordered_img.paste(resized_img, box=((width - resized_img.size[0] / 2) \\\n / 2, 0), mask=resized_img)\n \n bordered_img.save(image_directory + os.sep + \"Modified-\" + img_name)","def save(self):\n im = Image.open(self.picture)\n output = BytesIO()\n im.thumbnail((350, 350))\n im.save(output, format='JPEG', quality=100)\n output.seek(0)\n self.picture = InMemoryUploadedFile(output, 'ImageField', \"%s.jpg\" % self.picture.name.split('.')[0],\n 'image/jpeg', sys.getsizeof(output), None)\n super(Tire, self).save()","def img_save(self):\n file_name, extension = return_folder_file_extension(self.img_name)[1:]\n image_name_save = \"%s_D=%s_Rs=%s_size=%s_offset=%i%s\" % (file_name, self.D, self.Rs, self.axe_X, self.offset_X+self.offset_X2, extension)\n\n if self.img2 is not None:\n self.img2.save(image_name_save)\n print(\"Saved \"+image_name_save)\n else:\n print(\"No image to save\")","def marksimilar(image, clust, size):\n global opt\n blocks = []\n if clust:\n draw = ImageDraw.Draw(image)\n mask = Image.new('RGB', (size,size), 'cyan')\n for cl in clust:\n for x,y in cl:\n \tim = image.crop((x,y,x+size,y+size))\n \tim = Image.blend(im,mask,0.5)\n \tblocks.append((x,y,im))\n for bl in blocks:\n \tx,y,im = bl\n \timage.paste(im,(x,y,x+size,y+size))\n if int(opt.imauto):\n for cl in clust:\n cx1 = min([cx for cx,cy in cl])\n cy1 = min([cy for cx,cy in cl])\n cx2 = max([cx for cx,cy in cl]) + block_len\n cy2 = max([cy for cx,cy in cl]) + block_len\n draw.rectangle([cx1,cy1,cx2,cy2],outline=\"magenta\")\n return image","def sharpen(image_path, factor=3):\n BasicTransform.convert_image(image_path)\n\n with Image.open(image_path) as img:\n filter = ImageEnhance.Sharpness(img)\n new_image = filter.enhance(factor)\n new_image.save(image_path)","def write(self, file_name, width=1500.0, height=1000.0):\n with open(file_name, 'w+') as fh:\n fh.write(self.make(width, height))","def boundary(self,image,i,j):\r\n if((j >=25- self.padding) and (j <=175+ self.padding ) and (i >= 425- self.padding) and (i <= 575+ self.padding)):\r\n image[self.maximum_size-i,j,:]=0,0,0\r\n self.image_p[i,j,:]=2\r\n #print(2)\r","def imgWrite(img, path):\n dirMake(os.path.dirname(path))\n sitk.WriteImage(img, path)\n\n # Reformat files to be compatible with CIS Software\n #ext = os.path.splitext(path)[1].lower()\n #if ext == \".vtk\": vtkReformat(path, path)"],"string":"[\n \"def add_watermark(self, image, watermark, position='scale', opacity=1, format=None):\",\n \"def watermark(im, credits, opacity=1):\\n # First resize mark to make it appropriate size\\n logoURL = 'https://s3.amazonaws.com/static.thecrimson.com' + \\\\\\n '/images/feature/thc-logo-large.png'\\n imfile = StringIO.StringIO(urllib.urlopen(logoURL).read())\\n mark = PIL.Image.open(imfile)\\n mark = mark.resize((100, 10), PIL.Image.ANTIALIAS)\\n if opacity < 1:\\n mark = reduce_opacity(mark, opacity)\\n if im.mode != 'RGBA':\\n im = im.convert('RGBA')\\n # create a transparent layer the size of the image and draw the\\n # watermark in that layer.\\n # font = imfont.truetype(font='/static/fonts/ColabLig-webfont.ttf',\\n # size=15, index=0, encoding='')\\n layer = PIL.Image.new('RGBA', im.size, (0, 0, 0, 0))\\n draw = imdraw.Draw(im)\\n position = (im.size[0] - mark.size[0] - 10, 10)\\n layer.paste(mark, position)\\n # draw.text((x, y),\\\"Sample Text\\\",(r,g,b),font)\\n draw.text((10, im.size[1] - 20), credits, (255, 255, 255))\\n # composite the watermark with the layer\\n watermarkedImage = PIL.Image.composite(layer, im, layer)\\n response = HttpResponse(content_type='image/png')\\n watermarkedImage.save(response, 'PNG')\\n return response\",\n \"def watermark_image(self, watermark_path, pos_name):\\n image = Image.open(self.path)\\n watermark = Image.open(watermark_path)\\n self.watermark_width, self.watermark_height = watermark.size\\n pos = self.watermark_position(pos_name)\\n\\n parent_dir = os.path.dirname(self.output_path)\\n if not os.path.exists(parent_dir):\\n os.makedirs(parent_dir)\\n\\n watermark_ext = os.path.splitext(watermark_path)[-1]\\n if watermark_ext in (\\\".png\\\", \\\".PNG\\\"):\\n transparent = Image.new('RGBA', (self.width, self.height), (0, 0, 0, 0))\\n transparent.paste(image, (0, 0))\\n transparent.paste(watermark, pos, mask=watermark)\\n self.output_path = \\\".\\\".join([os.path.splitext(self.output_path)[0], \\\"png\\\"])\\n transparent.save(self.output_path)\\n elif watermark_ext in (\\\".jpg\\\", \\\".JPG\\\", \\\".jpeg\\\", \\\".JPEG\\\"):\\n image.paste(watermark, pos)\\n image.save(self.output_path)\\n\\n return os.path.exists(self.output_path)\",\n \"def waterMarkImages(imageFile,\\n imageOutputPath,\\n text,\\n fontName=\\\"Bangers\\\",\\n size=\\\"M\\\",\\n opacity=255,\\n position=\\\"BR\\\"):\\n # TODO : Try to have color as an argument as well\\n fileName = imageFile.split(os.path.sep)[-1]\\n try:\\n photo = Image.open(imageFile).convert(\\\"RGBA\\\")\\n except IOError:\\n raise WatermarkException(4, val=imageFile)\\n\\n width, height = photo.size\\n\\n COLOR = (255, 255, 255)\\n\\n textImage = Image.new('RGBA', (width, height), COLOR + (0, ))\\n\\n fontsize = _setSize(width, height, size)\\n\\n drawing = ImageDraw.Draw(textImage)\\n\\n if fontName in FONT_MAP:\\n # * fontPath = \\\"PyWaterMark\\\\\\\\fonts\\\\\\\\\\\" + FONT_MAP[fontName] - ONLY DEVS\\n fontPath = pkg_resources.resource_filename(\\n 'PyWatermark', 'fonts/' + FONT_MAP[fontName])\\n if not os.path.isfile(fontPath):\\n raise WatermarkException(2, val=fontName)\\n else:\\n if not os.path.isfile(fontName):\\n raise WatermarkException(3, val=fontName)\\n\\n font = ImageFont.truetype(fontPath, fontsize)\\n\\n textWidth, textHeight = drawing.textsize(text, font)\\n\\n pos = _setPosition(width, height, textWidth, textHeight, position)\\n\\n drawing.text(pos, text, fill=COLOR + (opacity, ), font=font)\\n\\n combined = Image.alpha_composite(photo, textImage)\\n\\n filenameSave = fileName.split('.')\\n filenameSave[1] = 'wm.png'\\n filenameSave = ''.join(filenameSave)\\n # * Why you can't store JPEG images with transparency\\n # * https://stackoverflow.com/questions/41413956/pil-unable-to-change-the-transparency-level-for-jpeg-image\\n combined.save(imageOutputPath + '\\\\\\\\' + filenameSave)\\n\\n return filenameSave\",\n \"def watermark(im, mark, position=None, adjust='tile', alpha=1):\\n # Check input\\n assert alpha >= 0 and alpha <= 1\\n\\n # Set watermark alpha\\n if alpha < 1:\\n mark = opacity(mark, alpha)\\n if im.mode != 'RGBA':\\n im = im.convert('RGBA')\\n # Draw watermark in a transparent layer\\n layer = Image.new('RGBA', im.size, (0,0,0,0))\\n if adjust == 'tile':\\n for y in range(0, im.size[1], mark.size[1]):\\n for x in range(0, im.size[0], mark.size[0]):\\n layer.paste(mark, (x, y))\\n elif adjust == 'scale':\\n # Scale preserving the aspect ratio\\n ratio = min(\\n float(im.size[0]) / mark.size[0], float(im.size[1]) / mark.size[1])\\n w = int(mark.size[0] * ratio)\\n h = int(mark.size[1] * ratio)\\n mark = mark.resize((w, h))\\n layer.paste(mark, ((im.size[0] - w) / 2, (im.size[1] - h) / 2))\\n else:\\n layer.paste(mark, position)\\n # Composite watermark with layer\\n return Image.composite(layer, im, layer)\",\n \"def custom_watermark(self, canvas, doc):\\n canvas.saveState()\\n canvas.setFont('Helvetica', 45)\\n canvas.setFillGray(0.80)\\n canvas.rotate(self.watermark_rotation)\\n canvas.drawCentredString(\\n self.watermark_position_x,\\n self.watermark_position_y,\\n self.watermark_string\\n )\\n canvas.restoreState()\",\n \"def watermark(self, image, transparency=0.0, left=0, top=0):\\n with image.clone() as watermark_image:\\n watermark_image.transparentize(transparency)\\n self.composite(watermark_image, left, top)\\n self.raise_exception()\",\n \"def exportImg(self):\\n if self.superSampling:\\n print(\\\"Exporting with size adjusted\\\")\\n self.img = self.img.resize((int(self.width/2),int(self.height/2)),Image.NEAREST)\\n self.img.save(self.fileName,\\\"PNG\\\")\",\n \"def __draw_watermark(self):\\n if self.watermark_text is not None:\\n self.fig.text(0.5, 0.5, self.watermark_text,\\n fontsize=self.settings.otherParams[\\\"watermark.fontsize\\\"], color='gray',\\n ha='center', va='center', alpha=0.3, rotation=65, transform=self.ax.transAxes)\",\n \"def image_to_scratch(im, scratch_image_name):\\n\\tim.save(scratch_image_name, dpi=(200,200))\",\n \"def WarpSave(fn, w=500,h=500, msg=True):\\n MSG(\\\"WarpSave\\\")\\n img = WarpImage(w,h)\\n cv2.imwrite(fn,img)\\n if msg:\\n print \\\"Image written: \\\", fn\\n return\",\n \"def add_watermark(image, text, font=watermark_font) -> Image:\\n rgba_image = image.convert('RGBA')\\n text_overlay = Image.new('RGBA', rgba_image.size, (255, 255, 255, 0))\\n image_draw = ImageDraw.Draw(text_overlay)\\n\\n text_size_x, text_size_y = image_draw.textsize(text, font=font)\\n\\n # Set text position.\\n text_xy = (rgba_image.size[0] - text_size_x, rgba_image.size[1] - text_size_y)\\n\\n # Set text color and transparency.\\n image_draw.text(text_xy, text, font=font, fill=(128, 128, 128, 180))\\n image_with_watermark = Image.alpha_composite(rgba_image, text_overlay)\\n return image_with_watermark\",\n \"def imageprepare(filename):\\n img = Image.open(filename).convert('L')\\n rect = img.getbbox()\\n im = img.crop(rect)\\n im.save(filename + '_pressprocessed.png')\\n\\n width = float(im.size[0])\\n height = float(im.size[1])\\n newImage = Image.new('L', (28, 28), (0)) #creates white canvas of 28x28 pixels\\n if width > height: #check which dimension is bigger\\n #Width is bigger. Width becomes 20 pixels.\\n nheight = int(round((20.0/width*height),0)) #resize height according to ratio width\\n if (nheight == 0): #rare case but minimum is 1 pixel\\n nheight = 1\\n # resize and sharpen\\n img = im.resize((20,nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\n wtop = int(round(((28 - nheight)/2),0)) #caculate horizontal pozition\\n newImage.paste(img, (4, wtop)) #paste resized image on white canvas\\n newImage.save(filename + '_final.png')\\n else:\\n #Height is bigger. Heigth becomes 20 pixels. \\n nwidth = int(round((20.0/height*width),0)) #resize width according to ratio height\\n if (nwidth == 0): #rare case but minimum is 1 pixel\\n nwidth = 1\\n # resize and sharpen\\n img = im.resize((nwidth,20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\n wleft = int(round(((28 - nwidth)/2),0)) #caculate vertical pozition\\n newImage.paste(img, (wleft, 4)) #paste resized image on white canvas\\n newImage.save(filename + '_final.png')\\n tv = list(newImage.getdata()) #get pixel values\\n #normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\\n tva = [ (x)*1.0/255.0 for x in tv] \\n return tva\",\n \"def Save_Image_Crop(img, x, y, width, height, filename = None, path = 'Predictions'):\\n img = img[y:y+height, x:x+width,:]\\n\\n if filename is not None:\\n try: \\n os.mkdir(path)\\n except OSError as error: \\n print('') \\n fig, ax = plt.subplots(figsize=(18, 20))\\n ax.imshow(img)\\n plt.tight_layout()\\n plt.savefig(path + '/' + filename + '_Crop.png')\",\n \"def compress_image(filename,k):\",\n \"def write_jpeg(filename,band,skypos,tranges,skyrange,width=False,height=False,\\n\\t\\t\\t stepsz=1.,clobber=False,verbose=0,tscale=1000.,retries=20):\\n\\tscipy.misc.imsave(filename,countmap(band,skypos,tranges,skyrange,\\n\\t\\t\\t\\t\\t width=width,height=height,verbose=verbose,tscale=tscale,\\n\\t\\t\\t\\t\\t retries=retries))\\n\\treturn\",\n \"def save_annotated_image(self, file: Path) -> None:\\n pass\",\n \"def saveImage(*args, annotation: Union[AnyStr, bool]=\\\"\\\", backgroundColor: Union[List[float,\\n float, float], bool]=None, currentView: bool=True, defineTemplate: AnyStr=\\\"\\\",\\n docTag: Union[AnyStr, bool]=\\\"\\\", dragCallback: Script=None, dropCallback:\\n Script=None, enable: bool=True, enableBackground: bool=True, enableKeyboardFocus:\\n bool=True, exists: bool=True, fullPathName: bool=True, height: Union[int, bool]=0,\\n highlightColor: Union[List[float, float, float], bool]=None, image: Union[AnyStr,\\n bool]=\\\"\\\", isObscured: bool=True, manage: bool=True, noBackground: bool=True,\\n numberOfPopupMenus: bool=True, objectThumbnail: AnyStr=\\\"\\\", parent: Union[AnyStr,\\n bool]=\\\"\\\", popupMenuArray: bool=True, preventOverride: bool=True, sceneFile:\\n AnyStr=\\\"\\\", statusBarMessage: AnyStr=\\\"\\\", useTemplate: AnyStr=\\\"\\\", visible:\\n bool=True, visibleChangeCommand: Union[Script, bool]=None, width: Union[int,\\n bool]=0, q=True, query=True, e=True, edit=True, **kwargs)->Union[AnyStr, Any]:\\n pass\",\n \"def save_png(self, filename):\\n post_script = self.canvas.postscript().encode()\\n img = Image.open(io.BytesIO(post_script))\\n img.save(filename, format=\\\"PNG\\\")\",\n \"def add_watermark(self, text):\\n self.watermark_text = text\",\n \"def write_stitched_image(self):\\r\\n\\r\\n self.write_debug(\\\"End of train detected. Writing stitched image.\\\")\\r\\n cv2.imwrite(os.path.join(self.output_dir_stitched, 'stitched.jpg'), self.stitched_image)\",\n \"def watermark_text(self, text, color, font_type, font_size, pos_name):\\n image = Image.open(self.path)\\n drawing = ImageDraw.Draw(image)\\n text = text\\n font = ImageFont.truetype(font_type, font_size)\\n self.watermark_width, self.watermark_height = drawing.textsize(text, font)\\n pos = self.watermark_position(pos_name)\\n\\n drawing.text(pos, text, fill=color, font=font)\\n parent_dir = os.path.dirname(self.output_path)\\n\\n if not os.path.exists(parent_dir):\\n os.makedirs(parent_dir)\\n\\n image.save(self.output_path)\\n return os.path.exists(self.output_path)\",\n \"def write_png(buffer, width, height, fileobj, dpi=None): # real signature unknown; restored from __doc__\\n pass\",\n \"def imageprepare(self,argv):\\r\\n\\t\\tim = Image.open(argv).convert('L')\\r\\n\\t\\twidth = float(im.size[0])\\r\\n\\t\\theight = float(im.size[1])\\r\\n\\t\\tnewImage = Image.new('L', (28, 28), (255)) # creates white canvas of 28x28 pixels\\r\\n\\r\\n\\t\\tif width > height: # check which dimension is bigger\\r\\n\\t\\t\\t# Width is bigger. Width becomes 20 pixels.\\r\\n\\t\\t\\tnheight = int(round((20.0 / width * height), 0)) # resize height according to ratio width\\r\\n\\t\\t\\tif nheight == 0: # rare case but minimum is 1 pixel\\r\\n\\t\\t\\t\\tnheight = 1\\r\\n\\t\\t\\t\\t# resize and sharpen\\r\\n\\t\\t\\timg = im.resize((20, nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\r\\n\\t\\t\\twtop = int(round(((28 - nheight) / 2), 0)) # caculate horizontal pozition\\r\\n\\t\\t\\tnewImage.paste(img, (4, wtop)) # paste resized image on white canvas\\r\\n\\t\\telse:\\r\\n\\t\\t\\t# Height is bigger. Heigth becomes 20 pixels.\\r\\n\\t\\t\\tnwidth = int(round((20.0 / height * width), 0)) # resize width according to ratio height\\r\\n\\t\\t\\tif (nwidth == 0): # rare case but minimum is 1 pixel\\r\\n\\t\\t\\t\\tnwidth = 1\\r\\n\\t\\t\\t\\t# resize and sharpen\\r\\n\\t\\t\\timg = im.resize((nwidth, 20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\r\\n\\t\\t\\twleft = int(round(((28 - nwidth) / 2), 0)) # caculate vertical pozition\\r\\n\\t\\t\\tnewImage.paste(img, (wleft, 4)) # paste resized image on white canvas\\r\\n\\r\\n\\t\\t# newImage.save(\\\"sample.png\\\")\\r\\n\\r\\n\\t\\ttv = list(newImage.getdata()) # get pixel values\\r\\n\\r\\n\\t\\t# normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\\r\\n\\t\\ttva = [(255 - x) * 1.0 / 255.0 for x in tv]\\r\\n\\t\\treturn tva\",\n \"def _save_annotation(annotation, filename):\\n\\n pil_image = Image.fromarray(annotation.astype(dtype=np.uint8))\\n '''\\n with tf.io.gfile.GFile(filename, mode='w') as f:\\n #with open(filename, mode='w') as f:\\n print(f)\\n pil_image.save(f, 'PNG')\\n '''\\n pil_image.save(filename)\",\n \"def advance_watermark_to(self, new_watermark):\\n self._add(WatermarkEvent(new_watermark))\\n return self\",\n \"def write_thumbnail(image_name, size):\\n # TODO : use something else instead of image.thumbnail\\n sizes = {\\n 'small' : [30,40],\\n 'medium' : [70,70],\\n 'large' : [120,120]\\n }\\n image = Image.open(f'{WRITE_FOLDER}/{USER_NAME}/original/{image_name}')\\n image.thumbnail((sizes[size][0], sizes[size][1]))\\n image.save(f'{WRITE_FOLDER}/{USER_NAME}/{size}/{image_name}')\",\n \"def save_image(lt_image, out_dir, filename, max_width=None):\\n if not lt_image.stream:\\n return\\n\\n filedata = lt_image.stream.get_data()\\n out_file_name = join(out_dir, filename)\\n\\n bits_per_component = lt_image.stream.attrs['BitsPerComponent']\\n if bits_per_component == 8:\\n # カラーとグレー画像はそのまま保存\\n with open(out_file_name, 'wb') as fp:\\n fp.write(filedata)\\n elif bits_per_component == 1:\\n # モノクロ画像はfiledataから作成\\n w, h = lt_image.stream.attrs['Width'], lt_image.stream.attrs['Height']\\n img = Image.frombytes('1', (w, h), filedata)\\n # グレー化、リサイズ、invertを行って保存\\n img = img.convert('L').resize((w // 2, h // 2), Image.ANTIALIAS)\\n img = ImageOps.invert(img)\\n img.save(out_file_name)\\n\\n if max_width:\\n print('max_width:', max_width)\\n img = Image.open(out_file_name)\\n w, h = img.size[:2]\\n img_resize = img.resize((max_width, h * max_width // w), Image.ANTIALIAS)\\n img_resize.save(out_file_name)\",\n \"def imwrite(image, path):\\n return scipy.misc.imsave(path, to_range(image, 0, 255, np.uint8))\",\n \"def compress_image(filename = \\\"hubble.jpg\\\", s = 2):\\n \\n image = imread(filename)/255\\n \\n toShow = plt.subplot(121)\\n \\n #Color\\n if len(np.shape(image)) == 3:\\n #Set up original RGB values\\n R = np.array(image[:,:,0])\\n G = np.array(image[:,:,1])\\n B = np.array(image[:,:,2])\\n \\n R, errR = svd_approx(R,s)\\n G, errG = svd_approx(G,s)\\n B, errB = svd_approx(B,s)\\n imageF = np.dstack((R,G,B))\\n err = errR + errG + errB\\n toShow.imshow(imageF)\\n toShow.set_title(\\\"New \\\" + str(err) + \\\", so \\\" + str((image.size-err)) + \\\" \\\\\\\"saved\\\\\\\"\\\")\\n toShow.axis(\\\"off\\\")\\n \\n toShow = plt.subplot(122)\\n toShow.set_title(\\\"Original \\\" + str(image.size))\\n toShow = plt.imshow(image)\\n #Gray\\n else:\\n imageF, err = svd_approx(image, s)\\n# print(np.shape(imageF))\\n toShow.imshow(imageF, cmap = \\\"gray\\\")\\n toShow.set_title(\\\"New \\\" + str(err) + \\\", so \\\" + str((image.size-err)) + \\\" \\\\\\\"saved\\\\\\\"\\\")\\n toShow.axis(\\\"off\\\")\\n toShow = plt.subplot(122)\\n toShow.set_title(\\\"Original \\\" + str(image.size))\\n toShow = plt.imshow(image, cmap = \\\"gray\\\")\\n \\n plt.suptitle(\\\"MY PLOTS: \\\" + str((image.size-err)) + \\\" \\\\\\\"saved\\\\\\\" :p\\\")\\n \\n return\\n raise NotImplementedError(\\\"Problem 5 Incomplete\\\")\",\n \"def save_as_fits(self, filename):\",\n \"def imageprepare(argv):\\r\\n im = Image.open(argv).convert('L')\\r\\n width = float(im.size[0])\\r\\n height = float(im.size[1])\\r\\n newImage = Image.new('L', (28, 28), (255)) #creates white canvas of 28x28 pixels\\r\\n \\r\\n if width > height: #check which dimension is bigger\\r\\n #Width is bigger. Width becomes 20 pixels.\\r\\n nheight = int(round((20.0/width*height),0)) #resize height according to ratio width\\r\\n if (nheight == 0): #rare case but minimum is 1 pixel\\r\\n nheight = 1 \\r\\n # resize and sharpen\\r\\n img = im.resize((20,nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\r\\n wtop = int(round(((28 - nheight)/2),0)) #caculate horizontal pozition\\r\\n newImage.paste(img, (4, wtop)) #paste resized image on white canvas\\r\\n else:\\r\\n #Height is bigger. Heigth becomes 20 pixels. \\r\\n nwidth = int(round((20.0/height*width),0)) #resize width according to ratio height\\r\\n if (nwidth == 0): #rare case but minimum is 1 pixel\\r\\n nwidth = 1\\r\\n # resize and sharpen\\r\\n img = im.resize((nwidth,20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\r\\n wleft = int(round(((28 - nwidth)/2),0)) #caculate vertical pozition\\r\\n newImage.paste(img, (wleft, 4)) #paste resized image on white canvas\\r\\n \\r\\n #newImage.save(\\\"sample.png\\\")\\r\\n\\r\\n tv = list(newImage.getdata()) #get pixel values\\r\\n \\r\\n #normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\\r\\n tva = [ (255-x)*1.0/255.0 for x in tv] \\r\\n #print(tva)\\r\\n return tva\",\n \"def save(image, name):\\n from matplotlib import pyplot\\n import matplotlib as mpl\\n fig = pyplot.figure()\\n ax = fig.add_subplot(1,1,1)\\n imgplot = ax.imshow(image, cmap=mpl.cm.Greys)\\n imgplot.set_interpolation('nearest')\\n ax.xaxis.set_ticks_position('top')\\n ax.yaxis.set_ticks_position('left')\\n pyplot.savefig(name)\",\n \"def save_image(self, filename):\\n raster.save_image(filename, self.image, self.metadata)\",\n \"def save_image(path, image): \\n if len(image.shape) == 4:\\n image = image.reshape((image.shape[1], image.shape[2], image.shape[3]))\\n image = np.clip(image * 255.0, 0, 255).astype(np.uint8)\\n skimage.io.imsave(path, image)\",\n \"def save_image(self):\\n self.compressed_image_id = str(uuid.uuid4().hex)\\n plot.imsave(\\n str(\\n self.compressed_image_id + \\\"{}\\\").format(\\n \\\".png\\\"), self.compressed_image)\\n\\n if self.verbose:\\n print(\\n \\\"Compressed image saved at \\\" + (\\n str(self.compressed_image_id + \\\"{}\\\").format(\\\".png\\\")))\",\n \"def identify_watermark(exam, image):\\n img = cv2.imread(image)\\n img = cv2.copyMakeBorder(img, 100, 100, 100, 100, cv2.BORDER_CONSTANT)\\n\\n corners = []\\n bits = []\\n\\n def handle_click(event, x, y, flags, params):\\n if event == cv2.EVENT_LBUTTONDOWN:\\n bits.append(Point(x, y))\\n cv2.circle(img, (x, y), 5, (255, 0, 0), -1)\\n if event == cv2.EVENT_RBUTTONDOWN:\\n corners.append(Point(x, y))\\n cv2.circle(img, (x, y), 5, (0, 255, 0), -1)\\n\\n cv2.namedWindow(\\\"image\\\")\\n cv2.setMouseCallback(\\\"image\\\", handle_click)\\n while True:\\n cv2.imshow(\\\"image\\\", img)\\n if cv2.waitKey(20) & 0xFF == 13:\\n break\\n\\n print(decode_watermark(get_exam(exam=exam), get_roster(exam=exam), corners, bits))\",\n \"def create_artificial_image(self):\\n background = self.BGI.create_background_image()\\n star_PSF = self.PSF.create_star_PSF()\\n header = self.HDR.create_header()\\n\\n fits.writeto(self.image_dir + self.image_name + '.fits',\\n background + star_PSF, overwrite=True, header=header)\",\n \"def saveborder(image, fname, outpath, width=20, colour=\\\"black\\\", preserve_name=False):\\n im = image.copy()\\n if not preserve_name:\\n fpath = genSavePath(outpath, fname, modstring=f\\\"border{width}{colour}\\\")\\n else:\\n fpath = genSavePath(outpath, fname)\\n\\n im = ImageOps.expand(im, border=width, fill=colour)\\n try:\\n im.save(fpath, subsample=\\\"keep\\\", qtables=image.quantization, optimize=True)\\n\\n except IOError as m:\\n print(\\\"Border image creation failed for: {}. \\\\nReason:{}\\\".format(fname,m))\",\n \"def writeImage(image, filename):\\n Sky = [128,128,128]\\n Building = [128,0,0]\\n Pole = [192,192,128]\\n Road_marking = [255,69,0]\\n Road = [128,64,128]\\n Pavement = [60,40,222]\\n Tree = [128,128,0]\\n SignSymbol = [192,128,128]\\n Fence = [64,64,128]\\n Car = [64,0,128]\\n Pedestrian = [64,64,0]\\n Bicyclist = [0,128,192]\\n Unlabelled = [0,0,0]\\n r = image.copy()\\n g = image.copy()\\n b = image.copy()\\n label_colours = np.array([Sky, Building, Pole, Road_marking, Road, Pavement, Tree, SignSymbol, Fence, Car, Pedestrian, Bicyclist, Unlabelled])\\n for l in range(0,12):\\n r[image==l] = label_colours[l,0]\\n g[image==l] = label_colours[l,1]\\n b[image==l] = label_colours[l,2]\\n rgb = np.zeros((image.shape[0], image.shape[1], 3))\\n rgb[:,:,0] = r/1.0\\n rgb[:,:,1] = g/1.0\\n rgb[:,:,2] = b/1.0\\n im = Image.fromarray(np.uint8(rgb))\\n # im.save('/Users/koheiyamamoto/Desktop/SegNet/out/' + filename)\\n im.save('./out/' + filename)\",\n \"def save_image(img: Image, filename: str) -> None:\\r\\n img.save(filename)\",\n \"def save_image(self):\\n self.save()\",\n \"def save_image(image, file_name):\\n io.imsave(file_name,image)\",\n \"def augment_img(img):\\n img = random_hflip_img(img)\\n img = cutout_img(img, size=12)\\n img = zero_pad_and_crop_img(img)\\n return img\",\n \"def write(img, path):\\n create_directories_for_file_name(path)\\n writer = sitk.ImageFileWriter()\\n writer.Execute(img, path, True)\",\n \"def add_transparent_watermark(base_image, overlay_image):\\n # Split out the transparency mask from the color info\\n watermark_img = overlay_image[:, :, :3]\\n watermark_mask = overlay_image[:, :, 3:]\\n\\n # Calculate the inverse mask\\n background_mask = 255 - watermark_mask\\n\\n # Turn background_mask into three channel, so we can use weight\\n background_mask = cv2.cvtColor(background_mask, cv2.COLOR_GRAY2BGR)\\n\\n # Create a masked out base image, and masked out watermark\\n # Convert the images to floating point in range 0.0 - 1.0\\n base_part = (base_image * (1 / 255.0)) * (background_mask * (1 / 255.0))\\n watermark_part = (watermark_img * (1 / 255.0)) * (background_mask * (1 / 255.0))\\n\\n # Add them together, rescale back to an 8bit integer image\\n return np.uint8(cv2.addWeighted(base_part, 255.0, watermark_part, 255.0, 0.0))\",\n \"def adjust(self, image):\\n ...\",\n \"def overlay_image(image_to_show, image_to_add, directory=None):\\n \\n direcx = \\\"/Documents/1.4.5 Images/\\\"#put a condition pls\\n if directory == None:\\n directory = os.getcwd()\\n print directory\\n new_image = PIL.Image.open(directory + direcx + image_to_show)\\n new_imager = PIL.Image.open(directory + direcx + image_to_show)\\n new_imager.show()\\n new_image2 = PIL.Image.open(directory + direcx + image_to_add)\\n new_image2.show()\\n \\n width, height = new_imager.size\\n print str(width) + \\\" \\\" + str(height)\\n \\n new_image22 = new_image2.resize((width,height), PIL.Image.ANTIALIAS)\\n new_image22.show()\\n\\n new_imager.paste(new_image22, (0,0), new_image22)\\n new_imager.show()\\n #cohrt = PIL.Image.blend(new_imager, new_image22, alpha=0.5)\\n #cohrt.show() #broked\",\n \"def tiffwrite(filename, im):\\n tf.imwrite(filename, im)\",\n \"def export_image(self, bbox, zoomlevel, imagepath):\\n assert has_pil, _(\\\"Cannot export image without python PIL\\\")\\n grid,tile_bounds = self.grid_tiles(bbox, zoomlevel)\\n width = len(grid[0])\\n height = len(grid)\\n widthpix = width * self.tile_size\\n heightpix = height * self.tile_size\\n result = Image.new(\\\"RGBA\\\", (widthpix, heightpix))\\n offset = (0, 0)\\n for i, row in enumerate(grid):\\n for j, (x, y) in enumerate(row):\\n offset = (j * self.tile_size, i * self.tile_size)\\n img = self._tile_image(self.tile((zoomlevel, x, y)))\\n result.paste(img, offset)\\n if imagepath.endswith(\\\".tif\\\") or imagepath.endswith(\\\".tiff\\\"):\\n # http://effbot.org/imagingbook/pil-index.htm#appendixes\\n # Packbits, LZW, or JPEG\\n # In the current version, PIL always writes uncompressed TIFF files.\\n image_gdal=\\\"gdal_input.tif\\\"\\n result.save(image_gdal, format=\\\"TIFF\\\", compression=\\\"JPEG\\\")\\n self.geotif_image(tile_bounds,(widthpix,heightpix),imagepath,image_gdal)\\n else:\\n if imagepath.endswith(\\\".jpg\\\") or imagepath.endswith(\\\".jpeg\\\"):\\n # IOError: encoder error -2 when writing image file\\n result.save(imagepath, format=\\\"JPEG\\\", quality=int(self.jpg_quality), optimize=True, progressive=False)\\n elif imagepath.endswith(\\\".png\\\") :\\n result.save(imagepath, format=\\\"PNG\\\",optimize=True)\\n else:\\n result.save(imagepath)\\n logger.info(_(\\\"-I-> export_image: Save resulting image to '%s' - bounds[%s]\\\") % (imagepath,tile_bounds))\",\n \"def create_output_image(building_footprint, parcel_footprint, file_path):\\n fig, ax = plt.subplots(figsize=(10, 10))\\n gpd.overlay(building_footprint, parcel_footprint, how=\\\"symmetric_difference\\\").plot(\\n ax=ax, color=\\\"lightgray\\\"\\n )\\n parcel_footprint.geometry.exterior.buffer(0.25).plot(ax=ax, color=\\\"black\\\")\\n building_footprint.plot(ax=ax, color=\\\"black\\\")\\n\\n ax.patch.set_facecolor(\\\"white\\\")\\n ax.patch.set_edgecolor(\\\"white\\\")\\n fig.patch.set_visible(False)\\n ax.axis(\\\"off\\\")\\n fig.savefig(\\n file_path,\\n bbox_inches=\\\"tight\\\",\\n pad_inches=0,\\n facecolor=\\\"white\\\",\\n edgecolor=\\\"white\\\",\\n quality=IMG_QUALITY,\\n )\\n plt.close()\",\n \"def generate_thumbnail(image_data, min_source_height, max_source_height, min_source_width, max_source_width, content_type, width, height, overlay_path, valign, top_crop_pct=None, bottom_crop_pct=None, left_crop_pct=None, right_crop_pct=None, crop_x=None, crop_y=None, post_crop_uniform_scale_pct=None):\\n # figure out the width/height of the image from the datastore\\n \\n# img = images.Image(image_data=image_data)\\n# img.crop(left_x=0.25, top_y=0.25, right_x=0.25, bottom_y=0.25)\\n# img.resize(width=width, height=height)\\n# logging.info('(b) w=%i, h=%i' % (img.width, img.height))\\n# output = img.execute_transforms(output_encoding=img.format)\\n \\n image = images.Image(image_data)\\n \\n if min_source_height is not None and image.height < min_source_height:\\n return None\\n if max_source_height is not None and image.height > max_source_height:\\n return None\\n \\n if min_source_width is not None and image.width < min_source_width:\\n return None\\n if max_source_width is not None and image.width > max_source_width:\\n return None\\n \\n \\n if content_type == 'image/png':\\n output_encoding = images.PNG\\n else:\\n output_encoding = images.JPEG\\n if crop_x is not None and crop_y is not None and valign is None and top_crop_pct is None and bottom_crop_pct is None and (image.width >= crop_x + width) and (image.height >= crop_y + height):\\n fw = float(image.width)\\n fh = float(image.height)\\n try:\\n output = images.crop(image_data, float(crop_x) / fw, float(crop_y) / fh, float(crop_x + width) / fw, float(crop_y + height) / fh, output_encoding=output_encoding)\\n except:\\n output = image_data\\n else:\\n if width > image.width and height > image.height:\\n output = image_data\\n# # this would result in scaling the image UP, that's no good\\n# if image.width > image.height:\\n# width = image.width\\n# else:\\n# height = image.height\\n# \\n# output = images.resize(image_data, width, height, output_encoding)\\n else:\\n output = rescale(image, width, height, halign='middle', valign=valign, top_crop_pct=top_crop_pct, bottom_crop_pct=bottom_crop_pct, left_crop_pct=left_crop_pct, right_crop_pct=right_crop_pct)\\n \\n if post_crop_uniform_scale_pct is not None:\\n output = images.resize(output, width=int(width * post_crop_uniform_scale_pct), output_encoding=output_encoding)\\n \\n if overlay_path is not None:\\n # read the overlay into memory\\n overlay_data = open(overlay_path,'r').read()\\n # composite the overlay onto the rescaled output\\n if content_type == 'image/png':\\n output_encoding = images.PNG\\n else:\\n output_encoding = images.JPEG\\n output = images.composite(\\n inputs=[\\n (output,0,0,1.0,images.CENTER_CENTER),\\n (overlay_data,0,0,1.0,images.CENTER_CENTER),\\n ],\\n width=width,\\n height=height,\\n output_encoding=output_encoding\\n )\\n return output\",\n \"def imwrite(image, path):\\n\\n if image.ndim == 3 and image.shape[2] == 1: # for gray image\\n image = np.array(image, copy=True)\\n image.shape = image.shape[0:2]\\n\\n imgarray=((image+1.0)*127.5).astype(np.uint8)\\n img=Image.fromarray(imgarray)\\n img.save(path)\",\n \"def stipple(img):\\n\\n\\timg = threshold(img, 25)\\n\\n\\treturn img\",\n \"def weight_paste(pixSrc, pixPng, src_id, logo_id):\\n weight = pixPng[:, :, 3] / 255\\n weight = weight[:, :, np.newaxis]\\n alpha = weight[logo_id]\\n beta = 1 - alpha\\n pixSrc[src_id] = pixSrc[src_id] * beta + pixPng[logo_id] * alpha\\n return pixSrc\",\n \"def write_image(path, image):\\n image = tf.image.encode_jpeg(image, quality=100)\\n return tf.io.write_file(path, image)\",\n \"def imageprepare(argv):\\n im = Image.open(argv).convert('L')\\n width = float(im.size[0])\\n height = float(im.size[1])\\n newImage = Image.new('L', (28, 28), (255)) # creates white canvas of 28x28 pixels\\n\\n if width > height: # check which dimension is bigger\\n # Width is bigger. Width becomes 20 pixels.\\n nheight = int(round((20.0 / width * height), 0)) # resize height according to ratio width\\n if (nheight == 0): # rare case but minimum is 1 pixel\\n nheight = 1\\n # resize and sharpen\\n img = im.resize((20, nheight), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\n wtop = int(round(((28 - nheight) / 2), 0)) # calculate horizontal position\\n newImage.paste(img, (4, wtop)) # paste resized image on white canvas\\n else:\\n # Height is bigger. Heigth becomes 20 pixels.\\n nwidth = int(round((20.0 / height * width), 0)) # resize width according to ratio height\\n if (nwidth == 0): # rare case but minimum is 1 pixel\\n nwidth = 1\\n # resize and sharpen\\n img = im.resize((nwidth, 20), Image.ANTIALIAS).filter(ImageFilter.SHARPEN)\\n wleft = int(round(((28 - nwidth) / 2), 0)) # caculate vertical pozition\\n newImage.paste(img, (wleft, 4)) # paste resized image on white canvas\\n\\n # newImage.save(\\\"sample.png\\n\\n tv = list(newImage.getdata()) # get pixel values\\n\\n # normalize pixels to 0 and 1. 0 is pure white, 1 is pure black.\\n tva = [(255 - x) * 1.0 / 255.0 for x in tv]\\n print(tva)\\n return tva\",\n \"def advance_watermark_to_infinity(self):\\n self.advance_watermark_to(timestamp.MAX_TIMESTAMP)\\n return self\",\n \"def embed_image_pred(image):\\n image_pil2 = Image.fromarray((255 * image).astype('uint8'))\\n #image_pil2 = image_pil.resize((256, 256))\\n string_buf2 = StringIO.StringIO()\\n image_pil2.save(string_buf2, format='png')\\n data = string_buf2.getvalue().encode('base64').replace('\\\\n', '')\\n return 'data:image/png;base64,' + data\",\n \"def save_image(image):\\n if config['save_images']['enabled']:\\n directory = config['save_images']['destination']\\n filename = datetime.datetime.now().strftime(\\\"%Y%m%d-%H%M%S%f\\\") + '.jpg'\\n destination = os.path.join(directory, filename)\\n logging.debug('saving image to %s', destination)\\n f = open(destination, 'wb')\\n f.write(image)\\n f.close\",\n \"def create_png(image, label):\\n sv = \\\"/home/avojtekova/Desktop/final_results/star_det/generated_images/\\\" \\n \\n for i in range(len(image)):\\n data = fits.getdata(image[i][0], ext = 0)\\n norm = ImageNormalize(data,interval = ZScaleInterval(), stretch = LinearStretch())\\n \\n print(image[i][0])\\n plt.imshow(data, cmap='Greys_r', origin='lower', norm=norm)#[1250:1750, 2000:2500] add this when you want just part of image \\n plt.title(label[i])\\n plt.axis('off')\\n plt.tight_layout()\\n plt.legend\\n if i<2:\\n if not os.path.isdir(sv + image[i][0][-33:-25] + \\\"/\\\") :\\n os.makedirs(sv + image[i][0][-33:-25] + \\\"/\\\")\\n plt.savefig(sv + image[i][0][-33:-25] + \\\"/\\\" + label[i]+ \\\"_\\\" + image[i][0][-33:-25] + \\\"_big.png\\\", dpi = 1000)#,bbox_inches='tight', pad_inches = 0) \\n else:\\n if not os.path.isdir(sv + image[i][0][-40:-32] + \\\"/\\\") :\\n os.makedirs(sv + image[i][0][-40:-32] + \\\"/\\\")\\n plt.savefig(sv + image[i][0][-40:-32] + \\\"/\\\" + label[i]+image[i][0][-40:-32] + \\\"_big.png\\\", dpi = 1000)#,bbox_inches='tight', pad_inches = 0)\\n plt.close()\",\n \"def save_image(self, filename):\\n if filename[-4:] != '.pkl':\\n filename + '.pkl'\\n with open(filename, 'wb') as output: # Overwrites any existing file.\\n pickle.dump(self, output, pickle.HIGHEST_PROTOCOL)\",\n \"def save_image(filename, image):\\n im = cv2.resize(image, None, fx=SCALE_DOWN, fy=SCALE_DOWN)\\n cv2.imwrite(os.path.join(OUT_DIR, filename), im)\",\n \"def update_PDF(pdf_file,new_name,path,watermark_text):\\n \\n # use reportlab to create a PDF that will be used \\n # as a watermark on another PDF.\\n c= canvas.Canvas(\\\"watermark.pdf\\\") # the watermark pdf\\n c.setFont(\\\"Courier\\\", 70) # watermark font/size\\n c.setFillGray(0.3,0.3) # watermark color/transparency\\n c.saveState() # save current canvas state\\n c.translate(500,100) # position the canvas\\n c.rotate(45) # rotate the canvas\\n #c.drawCentredString(0, 0, watermark_text) # write text\\n c.drawCentredString(0, 300, watermark_text) # write text\\n #c.drawCentredString(0, 600, watermark_text) # write text\\n c.restoreState() # restore canvas state\\n c.save()\\n\\n # initialize an output stream for the new, watermarked PDF\\n output = PdfFileWriter()\\n\\n # read in the given PDF to memory that will have the watermark applied to it\\n input1 = PdfFileReader(open(pdf_file, \\\"rb\\\")) \\n page_count = input1.getNumPages()\\n \\n # loop through every page of the given PDF file and watermark it\\n for i in range(page_count):\\n # skip the first page if keep_grade_report==0\\n if(keep_grade_report==0):\\n if(i==0):\\n i=1\\n page_i = input1.getPage(i) # open up the current page\\n watermark = PdfFileReader(open(\\\"watermark.pdf\\\", \\\"rb\\\")) # read in the watermark pdf to memory\\n page_i.mergePage(watermark.getPage(0))# merge watermark pdf with page_i\\n output.addPage(page_i) # add watermarked page_i to the output pdf\\n\\n # write the output of our new, watermarked PDF to the given given file name\\n if not os.path.exists(path):\\n os.makedirs(path)\\n outputStream = open(path+new_name+\\\".pdf\\\", \\\"wb\\\") \\n output.write(outputStream) \\n outputStream.close()\",\n \"def main():\\r\\n original = SimpleImage(\\\"images/poppy.png\\\")\\r\\n original.show()\\r\\n # shrink function\\r\\n after_shrink = shrink('images/poppy.png')\\r\\n after_shrink.show()\",\n \"def write(self, file_name, width=1500.0, height=1000.0):\\n with open(file_name, 'wb+') as fh:\\n fh.write(self.make(width, height))\",\n \"def extend_image(self):\\n IJ.run(self.image, 'Select All', '')\\n IJ.run(self.image, 'Copy', '')\\n width = self.image.getWidth()\\n height = int(self.image.getHeight() + self.extend_full)\\n new_image = IJ.createImage(\\n IMP.getTitle(), '32-bit black', width, height, 1)\\n new_image.setRoi(0, 0, self.image.getWidth(), self.image.getHeight())\\n IJ.run(new_image, 'Paste', '')\\n IJ.run(new_image, 'Enhance Contrast', 'saturated=0.35')\\n IJ.run(new_image, 'Select None', '')\\n cal = Calibration(self.image)\\n cal.pixelWidth = self.dispersion\\n cal.xOrigin = self.offset\\n new_image.setCalibration(cal)\\n self.image = new_image\\n return new_image\",\n \"def save_image(image, filename, mode='PNG'):\\n out = Image.new(mode='L', size=(image['width'], image['height']))\\n out.putdata(image['pixels'])\\n if isinstance(filename, str):\\n out.save(filename)\\n else:\\n out.save(filename, mode)\\n out.close()\",\n \"def save_image(image, filename, mode='PNG'):\\n out = Image.new(mode='L', size=(image['width'], image['height']))\\n out.putdata(image['pixels'])\\n if isinstance(filename, str):\\n out.save(filename)\\n else:\\n out.save(filename, mode)\\n out.close()\",\n \"def save(self, filename):\\n try:\\n import PIL\\n except ImportError:\\n raise RuntimeError('Could not import PIL. PIL (pillow) is required to save fresnel images.')\\n else:\\n if self._output is None:\\n self.render()\\n image = PIL.Image.fromarray(self._output[:], mode='RGBA')\\n image.save(filename)\",\n \"def compress_image(image: BinaryIO, size: Tuple[int, int] = (512, 512)) -> File:\\n im = Image.open(image)\\n im_format = im.format\\n im.thumbnail(size)\\n if im.mode in (\\\"P\\\", \\\"RGBA\\\"):\\n im = im.quantize()\\n im_io = BytesIO()\\n im.save(im_io, im_format)\\n return File(im_io, image.name)\",\n \"def saveImage(turtle, filename):\\n ts = turtle.getscreen()\\n tc = ts.getcanvas()\\n tc.postscript(file=filename)\",\n \"def save(self, fn):\\n plt.imsave(fn, self.image)\",\n \"def build_filler_images(self):\",\n \"def write(self, image):\\n raise NotImplementedError()\",\n \"def make_montage(infile):\\n\\n #create a blank image\\n blank = Image.new(\\\"RGB\\\", OUTPIC_SIZE ,(25,23,24,255))\\n\\n #paste the background\\n bg = Image.open(BACKGROUND_FILENAME)\\n blank.paste(bg,(0,0))\\n \\n #paste the raw picture\\n im = Image.open(infile)\\n \\n # past on background\\n blank.paste(im,OUTPIC_PHOTO_OFFSET)\\n\\n #paste the stickers layer on the pic (a transparent png)\\n stickers = Image.open(STICKERS_FILENAME)\\n blank.paste(stickers,(0,0),stickers)\\n\\n return blank\",\n \"def write_greyscale(filename,pixels):\\n height=len(pixels)\\n width=len(pixels[0])\\n with open(filename,'wb') as f:\\n # BMP Header\\n f.write(b'BM')\\n size_bookmark=f.tell()\\n f.write(b'\\\\x00\\\\x00\\\\x00\\\\x00')\\n f.write(b'\\\\x00\\\\x00')\\n f.write(b'\\\\x00\\\\x00')\\n pixel_offset_bookmark=f.tell()\\n f.write(b'\\\\x00\\\\x00\\\\x00\\\\x00')\\n # PIXEL HEADER 40 BYTES\\n f.write(b'\\\\x28\\\\x00\\\\x00\\\\x00')\\n f.write(_int_to_bytes(width))\\n f.write(_int_to_bytes(height))\\n f.write(b'\\\\x01\\\\x00') #01 number of image planes, 08 bits per pixel\\n f.write(b'\\\\x08\\\\x00') #01 number of image planes, 08 bits per pixel\\n f.write(b'\\\\x00\\\\x00\\\\x00\\\\x00') # Internal bmp\\n f.write(b'\\\\x00\\\\x00\\\\x00\\\\x00') # Internal bmp\\n f.write(b'\\\\x00\\\\x00\\\\x00\\\\x00') # Internal bmp\\n f.write(b'\\\\x00\\\\x00\\\\x00\\\\x00') # Internal bmp\\n f.write(b'\\\\x00\\\\x00\\\\x00\\\\x00') # Internal bmp\\n f.write(b'\\\\x00\\\\x00\\\\x00\\\\x00') # Internal bmp\\n \\n # Color palatte - linear greyscale\\n for c in range(256):\\n f.write(bytes((c,c,c,0))) #Blue,green,red,zero\\n \\n pixel_data_bookmark = f.tell()\\n for row in reversed(pixels):\\n row_data=bytes(row)\\n f.write(row_data)\\n padding=b'\\\\x00' * ( 4 - (len(row)%4))\\n f.write(padding)\\n \\n #EOF\\n eof_bookmark = f.tell()\\n\\n # Fill size placeholder\\n f.seek(size_bookmark)\\n f.write(_int_to_bytes(eof_bookmark))\\n f.seek(pixel_offset_bookmark)\\n f.write(_int_to_bytes(pixel_data_bookmark))\",\n \"def testImage():\\n width = 200\\n height = 200\\n image = BitMap( width, height )\\n \\n # create a loop in order to draw some pixels\\n \\n for col in range(width):\\n if col % 10 == 0: print 'col is', col\\n for row in range(height):\\n if col % 10 == 0 or row % 10 == 0:\\n image.plotPoint( col, row ) \\n \\n # we have now looped through every image pixel\\n # next, we write it out to a file\\n \\n image.saveFile( \\\"test.bmp\\\" )\\n #changing the col and row number determines how big the grid is for the picture or how zoomed in it is. Changing the and to or just makes the grid go from dotted grid to lines.\",\n \"def write_text(text_to_write, image_size):\\n image_text = Image.new(\\\"RGB\\\", image_size)\\n font = ImageFont.load_default().font\\n drawer = ImageDraw.Draw(image_text)\\n\\n #Text wrapping. Change parameters for different text formatting\\n margin = offset = 10\\n for line in textwrap.wrap(text_to_write, width=60):\\n drawer.text((margin,offset), line, font=font)\\n offset += 10\\n return image_text\",\n \"def saveImage(self, event):\\r\\n fileWritten = self.image.writeFile()\\r\\n self.statusBar.SetStatusText(\\\"Saved {}\\\".format(fileWritten))\",\n \"def write_image(path, tokens, weights):\\n\\n f = render_attn_inner(tokens, weights)\\n f.savefig(path, bbox_inches=\\\"tight\\\", frameon=False)\\n plt.close(f)\",\n \"def save_image(image, output_folder, output_name):\\n\\n\\tfolder_path = compute_path(output_folder, 'dataset')\\n\\tos.makedirs(folder_path, exist_ok=True)\\n\\n\\tfile_path = os.path.join(folder_path, output_name + '.png')\\n\\timage.save(file_path)\",\n \"def save_tile_img(tif, xyz, dataset, tile_size, region, zone, save_path, display=False):\\n \\n prefix = f'{region}{zone}{dataset}_'\\n x,y,z = xyz\\n tile, mask = rt_main.tile(tif, x,y,z, tilesize=tile_size)\\n if display: \\n plt.imshow(np.moveaxis(tile,0,2))\\n plt.show()\\n \\n skimage.io.imsave(f'{save_path}/{prefix}{z}_{x}_{y}.png',np.moveaxis(tile,0,2), check_contrast=False)\",\n \"def dem_jpeg(dem_file):\\n out_file = dem_file+'.jpeg'\\n rsc_file = out_file+'.rsc'\\n shutil.copy2(dem_file+'.rsc', rsc_file)\\n # read data\\n dem = readfile.read(dem_file)[0]\\n print('dem.shape:',dem.shape)\\n # figure size\\n ds_shape = tuple(reversed(dem.shape))\\n fig_dpi = 300\\n fig_size = [i / fig_dpi for i in ds_shape]\\n print('fig_size:',fig_size)\\n # color range\\n disp_min = np.nanmin(dem) - 4000\\n disp_max = np.nanmax(dem) + 2000\\n # prepare shaded relief\\n ls = LightSource(azdeg=315, altdeg=45)\\n dem_shade = ls.shade(dem, vert_exag=0.3, cmap=plt.get_cmap('gray'), vmin=disp_min, vmax=disp_max)\\n dem_shade[np.isnan(dem_shade[:, :, 0])] = np.nan\\n print('dem_shade.shape:',dem_shade.shape)\\n # plot\\n fig, ax = plt.subplots(figsize=fig_size)\\n ax.imshow(dem_shade, interpolation='spline16', origin='upper')\\n # get rid of whitespace on the side\\n ax.axis('off')\\n ax.get_xaxis().set_ticks([])\\n ax.get_yaxis().set_ticks([])\\n fig.subplots_adjust(left=0,right=1,bottom=0,top=1)\\n # output\\n print('save figure to file {}'.format(out_file))\\n plt.savefig(out_file, transparent=True, dpi=300, pad_inches=0.0)\\n \\n #resize to desired size(FA 8/19, unclear why size is wrong)\\n im = Image.open(out_file)\\n im_out = im.resize(dem.shape, Image.NEAREST)\\n im_out.save(out_file)\\n \\n #plt.show()\",\n \"def save(\\n self,\\n output_path: str,\\n show_confidence: bool = True,\\n ) -> None:\\n image = self.draw(show_confidence=show_confidence)\\n save_image(image=image, path=output_path)\",\n \"def image_optimize(file, width, height, force=False, resize=False):\\n import Image as pil\\n \\n max_width = width\\n max_height = height\\n\\n img = pil.open(file)\\n \\n #Fixing problem with gif\\n if img.mode != \\\"RGB\\\":\\n img = img.convert(\\\"RGB\\\")\\n\\n src_width, src_height = img.size\\n src_ratio = float(src_width) / float(src_height)\\n dst_width, dst_height = max_width, max_height\\n dst_ratio = float(dst_width) / float(dst_height)\\n \\n if not force:\\n if src_height > src_width:\\n max_width = dst_height\\n max_height = dst_width\\n img.thumbnail((max_width, max_height), pil.ANTIALIAS)\\n else:\\n if dst_ratio < src_ratio:\\n crop_height = src_height \\n crop_width = crop_height * dst_ratio \\n x_offset = int((src_width - crop_width)/2) \\n y_offset = 0 \\n else: \\n crop_width = src_width\\n crop_height = crop_width / dst_ratio\\n x_offset = 0\\n y_offset = int((src_height - crop_height)/3)\\n img = img.crop((x_offset, y_offset, x_offset+int(crop_width),\\n y_offset+int(crop_height)))\\n img = img.resize((dst_width, dst_height), pil.ANTIALIAS)\\n \\n return img\",\n \"def fileResizeObscure(new_filepath):\\n # Resize\\n img1 = Image.open(new_filepath)\\n img2=image_reduce(img1)\\n *** Stopped working here\\n newpath=\\\"toupload\\\\\\\\%s\\\" % new_filepath\\n # Block ID\\n width=img2.size[0]\\n height=img2.size[1]\\n # Obscuring params were decided by trial and error using fraction of width and height\\n x1=int(0.16*width)\\n x2=int(0.28*width)\\n y1=int(0.94*height)\\n y2=int(0.98*height) \\n # Faster but easier to snoop? should not be since it changes the pixels\\n draw = ImageDraw.Draw(img2)\\n draw.rectangle([(x1,y1),(x2,y2)],fill=\\\"white\\\")\\n del draw\\n \\n img2.save(newpath,optimize=True,quality=95)\",\n \"def save_PPM(self, fileName, imageComment = \\\"\\\"):\\n file = open(add_ext_if_needed(fileName, \\\"ppm\\\"), \\\"w\\\")\\n file.write(\\\"P3\\\\n\\\"); \\n file.write(\\\"# \\\" + imageComment + \\\"\\\\n\\\")\\n file.write(str(self._image.width()) + \\\" \\\" + str(self._image.height()) + \\\"\\\\n\\\")\\n file.write(\\\"255\\\\n\\\")\\n for y in range(self._image.height()):\\n for x in range(self._image.width()):\\n r,g,b = self.getPixel(x,y);\\n file.write(str(r) + \\\" \\\" + str(g) + \\\" \\\" + str(b) + \\\"\\\\n\\\")\\n file.close()\",\n \"def save(self, filename):\\n self.image.save(filename, self.options.img_format)\",\n \"def save(self):\\n\\n self.image.save(\\\"./output/\\\" + self.name + \\\" pg\\\" + str(self._page) + \\\".png\\\")\",\n \"def create_input_image(parcel_footprint, file_path):\\n fig, ax = plt.subplots(figsize=(10, 10))\\n parcel_footprint.plot(ax=ax, color=\\\"lightgray\\\")\\n parcel_footprint.geometry.exterior.buffer(0.25).plot(ax=ax, color=\\\"black\\\")\\n\\n ax.patch.set_facecolor(\\\"white\\\")\\n ax.patch.set_edgecolor(\\\"white\\\")\\n fig.patch.set_visible(False)\\n ax.axis(\\\"off\\\")\\n fig.savefig(\\n file_path,\\n bbox_inches=\\\"tight\\\",\\n pad_inches=0,\\n facecolor=\\\"white\\\",\\n edgecolor=\\\"white\\\",\\n quality=IMG_QUALITY,\\n )\\n plt.close()\",\n \"def overlay_image(image_to_show, image_to_add, directory=None):\\n \\n direcx = \\\"/Documents/1.4.5 Images/\\\"#put a condition pls\\n if directory == None:\\n directory = os.getcwd()\\n print directory\\n new_image = PIL.Image.open(directory + direcx + image_to_show)\\n new_imager = PIL.Image.open(directory + direcx + image_to_show)\\n new_imager.show()\\n new_image2 = PIL.Image.open(directory + direcx + image_to_add)\\n new_image2.show()\\n width, height = new_imager.size\\n print str(width) + \\\" \\\" + str(height)\\n #print new_image\\n #print new_image2\\n #if image_to_show == \\\"\\\":\\n # print_directory_list2()\\n # return \\\"Use one of these\\\"\\n new_image22 = new_image2.resize((width,height), PIL.Image.ANTIALIAS)\\n new_image22.show()\\n\\n new_imager.paste(new_image22, (width, height), new_image22)\\n new_imager.show()\\n #cohrt = PIL.Image.blend(new_imager, new_image22, alpha=0.5)\\n #cohrt.show()\",\n \"def brandify_img(img, img_name, border_width_percentage=0.10, \\\\\\nborder_width_cap=150, inner_border_width=7, \\\\\\ninner_border_color=(50, 255, 50, 0), outer_border_color=(50, 50, 50, 0)):\\n if img_name.startswith(\\\"Modified-\\\"):\\n return\\n width = img.size[0]\\n height = img.size[1]\\n # A new image that will be embiggened to fit the border\\n border_width = int(float(width + height) / 2 * border_width_percentage)\\n if border_width > border_width_cap:\\n border_width = border_width_cap\\n total_width = width + border_width * 2\\n total_height = height + border_width * 2\\n img.convert(mode=\\\"RGBA\\\")\\n bordered_img = PIL.Image.new(\\\"RGBA\\\", img.size)\\n bordered_img = PIL.ImageOps.expand(img, border=border_width)\\n draw = PIL.ImageDraw.Draw(bordered_img)\\n \\n # Fill in the border for the image\\n # The inner part of the border will be later covered up by the image itself\\n draw_border_gradient(bordered_img, center_color=inner_border_color, \\\\\\n outer_color=outer_border_color, excluding_region=(border_width, \\\\\\n width + border_width, border_width, height + border_width))\\n \\n # Inner border\\n # \\\"bb\\\" stands for border for border\\n bb_color = (255 - 50, 255 - 50, 255 - 50, 255)\\n draw.rectangle((border_width - inner_border_width, border_width - \\\\\\n inner_border_width, width + border_width + inner_border_width, height + \\\\\\n border_width + inner_border_width), fill=bb_color)\\n \\n # Add the original image\\n bordered_img.paste(img, (border_width, border_width, width + border_width, \\\\\\n height + border_width))\\n \\n # Add some basic design to the border\\n # Add lines on each corner\\n # Order is top left, top right, bottom left, bottom right\\n draw.line((0, 0, border_width, border_width), fill=bb_color, width=3)\\n draw.line((total_width, 0, total_width - border_width, border_width), \\\\\\n fill=bb_color, width=3)\\n draw.line((0, total_height, border_width, total_height - border_width), \\\\\\n fill=bb_color, width=3)\\n draw.line((total_width, total_height, total_width - border_width, \\\\\\n total_height - border_width), fill=bb_color, width=3)\\n \\n # Apply the brand image\\n new_width = int((float(brand_image.size[0]) / brand_image.size[1]) * \\\\\\n border_width)\\n new_height = border_width - inner_border_width\\n resized_img = brand_image.resize((new_width, new_height))\\n bordered_img.paste(resized_img, box=((width - resized_img.size[0] / 2) \\\\\\n / 2, 0), mask=resized_img)\\n \\n bordered_img.save(image_directory + os.sep + \\\"Modified-\\\" + img_name)\",\n \"def save(self):\\n im = Image.open(self.picture)\\n output = BytesIO()\\n im.thumbnail((350, 350))\\n im.save(output, format='JPEG', quality=100)\\n output.seek(0)\\n self.picture = InMemoryUploadedFile(output, 'ImageField', \\\"%s.jpg\\\" % self.picture.name.split('.')[0],\\n 'image/jpeg', sys.getsizeof(output), None)\\n super(Tire, self).save()\",\n \"def img_save(self):\\n file_name, extension = return_folder_file_extension(self.img_name)[1:]\\n image_name_save = \\\"%s_D=%s_Rs=%s_size=%s_offset=%i%s\\\" % (file_name, self.D, self.Rs, self.axe_X, self.offset_X+self.offset_X2, extension)\\n\\n if self.img2 is not None:\\n self.img2.save(image_name_save)\\n print(\\\"Saved \\\"+image_name_save)\\n else:\\n print(\\\"No image to save\\\")\",\n \"def marksimilar(image, clust, size):\\n global opt\\n blocks = []\\n if clust:\\n draw = ImageDraw.Draw(image)\\n mask = Image.new('RGB', (size,size), 'cyan')\\n for cl in clust:\\n for x,y in cl:\\n \\tim = image.crop((x,y,x+size,y+size))\\n \\tim = Image.blend(im,mask,0.5)\\n \\tblocks.append((x,y,im))\\n for bl in blocks:\\n \\tx,y,im = bl\\n \\timage.paste(im,(x,y,x+size,y+size))\\n if int(opt.imauto):\\n for cl in clust:\\n cx1 = min([cx for cx,cy in cl])\\n cy1 = min([cy for cx,cy in cl])\\n cx2 = max([cx for cx,cy in cl]) + block_len\\n cy2 = max([cy for cx,cy in cl]) + block_len\\n draw.rectangle([cx1,cy1,cx2,cy2],outline=\\\"magenta\\\")\\n return image\",\n \"def sharpen(image_path, factor=3):\\n BasicTransform.convert_image(image_path)\\n\\n with Image.open(image_path) as img:\\n filter = ImageEnhance.Sharpness(img)\\n new_image = filter.enhance(factor)\\n new_image.save(image_path)\",\n \"def write(self, file_name, width=1500.0, height=1000.0):\\n with open(file_name, 'w+') as fh:\\n fh.write(self.make(width, height))\",\n \"def boundary(self,image,i,j):\\r\\n if((j >=25- self.padding) and (j <=175+ self.padding ) and (i >= 425- self.padding) and (i <= 575+ self.padding)):\\r\\n image[self.maximum_size-i,j,:]=0,0,0\\r\\n self.image_p[i,j,:]=2\\r\\n #print(2)\\r\",\n \"def imgWrite(img, path):\\n dirMake(os.path.dirname(path))\\n sitk.WriteImage(img, path)\\n\\n # Reformat files to be compatible with CIS Software\\n #ext = os.path.splitext(path)[1].lower()\\n #if ext == \\\".vtk\\\": vtkReformat(path, path)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7318583","0.6755734","0.66474384","0.6608156","0.6311425","0.5929534","0.5910654","0.58472747","0.58287114","0.58228457","0.5805072","0.56639534","0.5578972","0.55572283","0.5513554","0.5510311","0.55005735","0.5479865","0.5456375","0.5421586","0.54154515","0.5401148","0.5373784","0.5372007","0.53625435","0.5339748","0.5296579","0.5284281","0.52733433","0.5263293","0.52604055","0.52518874","0.5243926","0.52399135","0.52127874","0.520608","0.5196467","0.51907814","0.5181694","0.5180175","0.5172935","0.5153717","0.5132572","0.51321054","0.51315165","0.5131227","0.5129543","0.5124015","0.51104087","0.5102805","0.5101115","0.50898695","0.5064524","0.5064184","0.5064167","0.50574076","0.50492495","0.50428045","0.50402045","0.5038588","0.5031682","0.5029365","0.50273883","0.50265354","0.50109696","0.4991059","0.49858665","0.49824673","0.49824673","0.4972699","0.497052","0.49662152","0.49658617","0.4958894","0.4956187","0.49559855","0.49447146","0.49427298","0.49415156","0.49375442","0.49375176","0.49310374","0.49301586","0.4918782","0.4911001","0.49064964","0.49050993","0.48917365","0.48882222","0.48868474","0.48850077","0.48844644","0.48842072","0.48831207","0.488127","0.48724648","0.48720783","0.48686868","0.48635238","0.48588967"],"string":"[\n \"0.7318583\",\n \"0.6755734\",\n \"0.66474384\",\n \"0.6608156\",\n \"0.6311425\",\n \"0.5929534\",\n \"0.5910654\",\n \"0.58472747\",\n \"0.58287114\",\n \"0.58228457\",\n \"0.5805072\",\n \"0.56639534\",\n \"0.5578972\",\n \"0.55572283\",\n \"0.5513554\",\n \"0.5510311\",\n \"0.55005735\",\n \"0.5479865\",\n \"0.5456375\",\n \"0.5421586\",\n \"0.54154515\",\n \"0.5401148\",\n \"0.5373784\",\n \"0.5372007\",\n \"0.53625435\",\n \"0.5339748\",\n \"0.5296579\",\n \"0.5284281\",\n \"0.52733433\",\n \"0.5263293\",\n \"0.52604055\",\n \"0.52518874\",\n \"0.5243926\",\n \"0.52399135\",\n \"0.52127874\",\n \"0.520608\",\n \"0.5196467\",\n \"0.51907814\",\n \"0.5181694\",\n \"0.5180175\",\n \"0.5172935\",\n \"0.5153717\",\n \"0.5132572\",\n \"0.51321054\",\n \"0.51315165\",\n \"0.5131227\",\n \"0.5129543\",\n \"0.5124015\",\n \"0.51104087\",\n \"0.5102805\",\n \"0.5101115\",\n \"0.50898695\",\n \"0.5064524\",\n \"0.5064184\",\n \"0.5064167\",\n \"0.50574076\",\n \"0.50492495\",\n \"0.50428045\",\n \"0.50402045\",\n \"0.5038588\",\n \"0.5031682\",\n \"0.5029365\",\n \"0.50273883\",\n \"0.50265354\",\n \"0.50109696\",\n \"0.4991059\",\n \"0.49858665\",\n \"0.49824673\",\n \"0.49824673\",\n \"0.4972699\",\n \"0.497052\",\n \"0.49662152\",\n \"0.49658617\",\n \"0.4958894\",\n \"0.4956187\",\n \"0.49559855\",\n \"0.49447146\",\n \"0.49427298\",\n \"0.49415156\",\n \"0.49375442\",\n \"0.49375176\",\n \"0.49310374\",\n \"0.49301586\",\n \"0.4918782\",\n \"0.4911001\",\n \"0.49064964\",\n \"0.49050993\",\n \"0.48917365\",\n \"0.48882222\",\n \"0.48868474\",\n \"0.48850077\",\n \"0.48844644\",\n \"0.48842072\",\n \"0.48831207\",\n \"0.488127\",\n \"0.48724648\",\n \"0.48720783\",\n \"0.48686868\",\n \"0.48635238\",\n \"0.48588967\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.78452754"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88577,"cells":{"query":{"kind":"string","value":"Perform colour enhancements to the image."},"document":{"kind":"string","value":"def saveenhanced(image, fname, outpath, colourfactor=1, brightnessfactor=1, contrastfactor=1, sharpnessfactor=1, preserve_name=False):\n estring = \"col{}br{}con{}sh{}\".format(colourfactor, brightnessfactor, contrastfactor, sharpnessfactor)\n\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"enhanced_{estring}\")\n else:\n fpath = genSavePath(outpath, fname)\n\n im = copy(image)\n if colourfactor != 1:\n en = ImageEnhance.Color(im)\n im = en.enhance(colourfactor)\n if brightnessfactor != 1:\n en = ImageEnhance.Contrast(im)\n im = en.enhance(contrastfactor)\n if contrastfactor != 1:\n en = ImageEnhance.Brightness(im)\n im = en.enhance(brightnessfactor)\n if sharpnessfactor != 1:\n en = ImageEnhance.Sharpness(im)\n im = en.enhance(sharpnessfactor)\n\n try:\n im.save(fpath, subsample=\"keep\",qtables=image.quantization, optimize=True)\n\n except IOError as m:\n print( \"Enhanced({}) image creation failed for: {}. \\nReason:{}\".format(estring,fname,m))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def __enhance_image(self, img):\n\n blue = self.g.clahe.apply(img[:,:,0])\n green = self.g.clahe.apply(img[:,:,1])\n red = self.g.clahe.apply(img[:,:,2])\n img[:,:,0] = blue\n img[:,:,1] = green\n img[:,:,2] = red\n return img","def _adjust_color_img(self, results, factor=1.0):\n for key in results.get('img_fields', ['image']):\n # NOTE defaultly the image should be BGR format\n img = results[key]\n results[key] = mmcv.adjust_color(img, factor).astype(img.dtype)","def enhance_contrast(img):\n for y in range(frame_height):\n for x in range(frame_width):\n if img[y, x, 1] > 100:\n # range of blues to limit of puppet motion 255/(frame_width - 150)\n img[y][x][0] = x*0.4\n if img[y, x, 1] <= 100:\n img[y][x][2] = img[y][x][2]*0.5\n cv2.imwrite(\"contrasted.png\", img)","def colorize(image, newColor):\n image = image.copy()\n\n # zero out RGB values\n image.fill((0, 0, 0, 255), None, pg.BLEND_RGBA_MULT)\n # add in new RGB values\n image.fill(newColor[0:3] + (0,), None, pg.BLEND_RGBA_ADD)\n\n return image","def set_color(self):\n self.image[self.x, self.y] = self.color\n if self.diffusion:\n r = g = b = 0\n for i in range(self.convolution_matrix.shape[0]):\n for j in range(self.convolution_matrix.shape[1]):\n r = g = b = 0\n for k in range(self.convolution_matrix.shape[0]):\n for l in range(self.convolution_matrix.shape[1]):\n m = (self.x + i + k - 2 + self.image.shape[0]) % self.image.shape[0]\n n = (self.y + j + l - 2 + self.image.shape[1]) % self.image.shape[1]\n r += self.convolution_matrix[k][l] * self.image[m, n][2]\n g += self.convolution_matrix[k][l] * self.image[m, n][1]\n b += self.convolution_matrix[k][l] * self.image[m, n][0]\n self.image[self.x, self.y] = (b, g, r)","def colorize(image, newColor):\n image = image.copy()\n\n # zero out RGB values\n image.fill((0, 0, 0, 255), None, pygame.BLEND_RGBA_MULT)\n # add in new RGB values\n image.fill(newColor[0:3] + [0,], None, pygame.BLEND_RGBA_ADD)\n\n return image","def grayscale(img):\n for pixel in img:\n x, y, col = pixel\n r, g, b = col\n \n r = (r + g + b)/3\n r = g = b\n \n new_color = create_color(r, g, b)\n set_color(img, x, y, new_color)","def applyJET(img):\n\treturn applyColorMap(img, \"jet\")","def solarize(img, threshold):\n \n for x, y, col in img:\n\n # Invert the values of all RGB components less than 128,\n # leaving components with higher values unchanged.\n\n red, green, blue = col\n\n if red < threshold:\n red = 255 - red\n\n if green < threshold:\n green = 255 - green\n\n if blue < threshold:\n blue = 255 - blue\n\n col = create_color(red, green, blue)\n set_color(img, x, y, col)","def reduce_color(image):\n\n # http://stackoverflow.com/questions/5906693/how-to-reduce-the-number-of-colors-in-an-image-with-opencv-in-python\n w, h, _ = image.shape\n for row in xrange(h-1):\n for col in xrange(w-1):\n #pi = row * w * 3 + col * 3\n pixel = image[col][row]\n pixel[0] = __reduceColorValue(pixel[0])\n pixel[1] = __reduceColorValue(pixel[1])\n pixel[2] = __reduceColorValue(pixel[2])\n return image","def intensity_enhance(self, im):\n\n color_factor = self.intensity * self.random.uniform(-0.4, 0.4) + 1\n contrast_factor = self.intensity * self.random.uniform(-0.5, 0.5) + 1\n sharpess_factor = self.intensity * self.random.uniform(-0.8, 0.8) + 1\n bright_factor = self.intensity * self.random.uniform(-0.5, 0.5) + 1\n self.last_factors = [color_factor, contrast_factor, sharpess_factor, bright_factor]\n\n image = Image.fromarray(np.uint8(im * 255))\n enhancer = ImageEnhance.Color(image)\n image = enhancer.enhance(color_factor)\n enhancer = ImageEnhance.Contrast(image)\n image = enhancer.enhance(contrast_factor)\n enhancer = ImageEnhance.Sharpness(image)\n image = enhancer.enhance(sharpess_factor)\n enhancer = ImageEnhance.Brightness(image)\n image = enhancer.enhance(bright_factor)\n\n return np.asarray(image) / 255.","def saturate(image_path, factor=4):\n BasicTransform.convert_image(image_path)\n\n with Image.open(image_path) as img:\n filter = ImageEnhance.Color(img)\n new_image = filter.enhance(factor)\n new_image.save(image_path)","def colour_image(self):\n for row_cnt, colour_row in enumerate(self.table_colour):\n self.processed = []\n for column_cnt, colour in enumerate(colour_row):\n self.row_cnt = row_cnt + 3\n self.column_cnt = column_cnt\n self.colour = colour\n self.word = self.original_rows[self.row_cnt - 3][self.column_cnt]\n self.colour_specific_word()","def enhance_contrast(img):\n # CLAHE (Contrast Limited Adaptive Histogram Equalization)\n clahe = cv2.createCLAHE(clipLimit=3., tileGridSize=(8, 8))\n\n lab = cv2.cvtColor(img, cv2.COLOR_BGR2LAB) # convert from BGR to LAB color space\n l, a, b = cv2.split(lab) # split on 3 different channels\n\n l2 = clahe.apply(l) # apply CLAHE to the L-channel\n\n lab = cv2.merge((l2, a, b)) # merge channels\n img2 = cv2.cvtColor(lab, cv2.COLOR_LAB2BGR) # convert from LAB to BGR\n\n return img2","def red_filter(img):\r\n #with Image.open(filename) as img:\r\n w = img.width\r\n h = img.height\r\n\r\n newimg = Image.new('RGB', (w,h))\r\n for y in range(h):\r\n for x in range(w):\r\n r, g, b = img.getpixel((x,y))\r\n \r\n newimg.putpixel((x, y), (r, 0, 0))\r\n \r\n return newimg","def img_recolor(self, args, input_image_path):\n \n ec = encoder.Encoder(output_path=args.intermediate_representation, method=args.method,\n size=args.size, p=args.p, grid_size=args.grid_size, plot=args.plot, quantize=args.quantize)\n dc = decoder.Decoder(output_path=args.output_path, method=args.method, size=args.size, p=args.p, gpu_id=args.gpu_id, plot=args.plot)\n\n ec.encode(input_image_path)\n img_gray_name = ar_utils.gen_new_gray_filename(input_image_path)\n img_gray_path = os.path.join(args.intermediate_representation, img_gray_name)\n dc.decode(img_gray_path)\n\n if args.delete_gray and os.path.exists(img_gray_path):\n os.remove(img_gray_path)","def check_image_color(image):\n\n def check_color(i, j, k):\n \"\"\" Function used only for DEBUGGING\"\"\"\n img.show()\n image = Image.new(\"RGB\", (200, 200), (int(Y), int(Y), int(Y)))\n image.show()\n image = Image.new(\"RGB\", (200, 200), (int(i), int(j), int(k)))\n image.show()\n\n if not os.path.isfile(image):\n return \"Image not found\"\n\n def calculate_bgr(data):\n average_color_per_row = numpy.average(data, axis=0)\n average_color = numpy.average(average_color_per_row, axis=0)\n return tuple(average_color)\n\n def calculate_y(r, g, b):\n alpha = 0.299\n betta = 0.587\n gamma = 0.114\n return alpha * r + betta * g + gamma * b\n\n # split the image for four squares calucate averate pixel for them and take higest value\n # blure image and save to /Library/Caches as com.apple.desktop.admin.png\n # in case using blur tool --> blur = cv2.blur(img,(5,5))\n try:\n img_cv_data = cv2.imread(image)\n B, G, R = calculate_bgr(img_cv_data)\n Y = calculate_y(B, G, R)\n height, width = img_cv_data.shape[:2]\n except Exception as err:\n print(f\"[ERROR] {err} with image: {image}\")\n return \"Error parsing image\"\n\n # image detection\n if Y < 72.0:\n _type = \"dark\"\n elif Y >= 73.0 and Y <= 108.0:\n _type = \"evening\"\n else:\n _type = \"light\"\n\n return _type","def brighten(image_path, factor=1.5):\n BasicTransform.darken(image_path, factor)","def _apply(self, real=False):\n pixbuf = self._pixbuf if real else self._pixbuf.copy()\n # Apply brightness, contrast and saturation\n pixbuf = image_enhance.enhance_bc(pixbuf, self._manipulations[\"bri\"],\n self._manipulations[\"con\"])\n pixbuf.saturate_and_pixelate(pixbuf, self._manipulations[\"sat\"] + 1,\n False)\n # Show the edited pixbuf\n self._app[\"image\"].set_pixbuf(pixbuf)\n # Save file if needed\n if real:\n save_pixbuf(pixbuf, self._app.get_path())","def colorImgPreProcess(self, image):\n #do processing on the image while it's still in color\n image = cv2.medianBlur(image, 7) #kernal size must be odd\n #image = cv2.bilateralFilter(image, 9, 75, 75) #TODO: uncomment when it won't cause C++ errors with ROS\n #self.closeImages() #uncomment if showing output image\n return image","def one_color(image,color=[0,0,255]):\r\n output = image.copy()\r\n for line in range(len(image)):\r\n for column in range(len(image[0])):\r\n distance = calc_distance(color,image[line][column])\r\n if distance <=150:\r\n output[line][column]=[255,255,255]\r\n else:\r\n output[line][column]=[0,0,0]\r\n return output","def color_callback(self, data):\n cv_image = self.bridge.imgmsg_to_cv2(data, desired_encoding=\"passthrough\")\n self.color_mutex.acquire()\n self.color_image = cv_image\n self.color_mutex.release()","def color_pixels(self, image, color):\r\n\r\n image[self.ally, self.allx] = color\r\n return image","def adjust_saturation(img, saturation_factor):\n check_type(img)\n\n enhancer = ImageEnhance.Color(img)\n img = enhancer.enhance(saturation_factor)\n return img","def __smoothen_color(self, outer, inner):\n outer_curve = zip(outer[0], outer[1])\n inner_curve = zip(inner[0], inner[1])\n x_points = []\n y_points = []\n for point in outer_curve:\n x_points.append(point[0])\n y_points.append(point[1])\n for point in inner_curve:\n x_points.append(point[0])\n y_points.append(point[1])\n img_base = np.zeros((self.height, self.width))\n cv2.fillConvexPoly(img_base, np.array(np.c_[x_points, y_points], dtype='int32'), 1)\n img_mask = cv2.GaussianBlur(img_base, (81, 81), 0) #51,51\n img_blur_3d = np.ndarray([self.height, self.width, 3], dtype='float')\n img_blur_3d[:, :, 0] = img_mask\n img_blur_3d[:, :, 1] = img_mask\n img_blur_3d[:, :, 2] = img_mask\n self.im_copy = (img_blur_3d * self.image * 0.7 + (1 - img_blur_3d * 0.7) * self.im_copy).astype('uint8')","def falso_color(img):\n rows,cols = img.shape\n img_red = np.copy(img)\n img_green = np.copy(img)\n img_blue = np.copy(img)\n img_false = np.zeros((rows, cols, 3), dtype=np.uint8)\n\n for i in range(0,rows):\n for j in range(0,cols):\n\n if (0 <= img[i, j] <= 43):\n img_red[i, j] = 255\n img_green[i, j] = img[i, j] * (255 / 43)\n img_blue[i, j] = 0\n\n elif(43 < img[i, j] <= 86):\n img_red[i, j] = (255 - (img[i, j] - 43) * (255 / 43))\n img_green[i, j] = 255\n img_blue[i,j] = 0\n\n elif(86 < img[i, j] <= 128):\n img_red[i, j] = 0\n img_green[i, j] = 255\n img_blue[i, j] = ((img[i, j] - 86) * (255 / 42))\n\n elif(128<img[i, j]<=171):\n img_red[i, j] = 0\n img_green[i, j] = ((171 - img[i, j]) * (255 / 43))\n img_blue[i, j] = 255\n\n elif(171 < img[i, j] <= 214):\n img_red[i, j] = (img[i, j] - 171) * (255 / 43)\n img_green[i, j] = 0\n img_blue[i, j] = 255\n\n elif(214 < img[i, j]):\n img_red[i, j] = 255\n img_green[i, j] = 0\n img_blue[i, j] = ((255 - img[i, j]) * (255 / 41))\n\n img_false[:, :, 0] = img_red\n img_false[:, :, 1] = img_green\n img_false[:, :, 2] = img_blue\n\n return img_false","def darker(image):\r\n # Demonstrate looping over all the pixels of an image,\r\n # changing each pixel to be half its original intensity.\r\n for pixel in image:\r\n pixel.red = pixel.red // 2\r\n pixel.green = pixel.green // 2\r\n pixel.blue = pixel.blue // 2","def augment_brightness(image):\n rand_brightness = .25 + np.random.uniform()\n image = cv2.cvtColor(image, cv2.COLOR_RGB2HSV)\n image[:, :, 2] = image[:, :, 2] * rand_brightness\n image = cv2.cvtColor(image, cv2.COLOR_HSV2RGB)\n return image","def __add_color(self, intensity):\n val = color.rgb2lab(\n (self.image[self.lip_y, self.lip_x] / 255.)\n .reshape(len(self.lip_y), 1, 3)\n ).reshape(len(self.lip_y), 3)\n l_val, a_val, b_val = np.mean(val[:, 0]), np.mean(val[:, 1]), np.mean(val[:, 2])\n l1_val, a1_val, b1_val = color.rgb2lab(\n np.array(\n (self.red_l / 255., self.green_l / 255., self.blue_l / 255.)\n ).reshape(1, 1, 3)\n ).reshape(3,)\n l_final, a_final, b_final = (l1_val - l_val) * \\\n intensity, (a1_val - a_val) * \\\n intensity, (b1_val - b_val) * intensity\n val[:, 0] = np.clip(val[:, 0] + l_final, 0, 100)\n val[:, 1] = np.clip(val[:, 1] + a_final, -127, 128)\n val[:, 2] = np.clip(val[:, 2] + b_final, -127, 128)\n self.image[self.lip_y, self.lip_x] = color.lab2rgb(val.reshape(\n len(self.lip_y), 1, 3)).reshape(len(self.lip_y), 3) * 255","def negative(img): \n for pixel in img:\n x, y, col = pixel \n r, g, b = col\n \n new_color = create_color(255 - r, 255 - g, 255 - b)\n set_color(img, x, y, new_color)","def grayscale(image: Image) -> Image:\r\n new_image = copy(image)\r\n for x,y,(r,g,b) in image:\r\n pix_bright = (r+g+b)//3\r\n Gray = create_color(pix_bright,pix_bright,pix_bright)\r\n set_color(new_image,x,y,Gray) \r\n return new_image","def colorize_images(self, img):\n self.load_model()\n self.mdn.eval()\n self.vae.eval()\n n, _, _ = img.shape\n img = img.astype(np.float32) / 255\n img = torch.tensor(img, dtype=torch.float, device=self.device).unsqueeze(1)\n with torch.no_grad():\n z = self.mdn(img)\n ab_out = self.vae.decode(z)\n lab_out = torch.cat((img, ab_out), dim=1)\n lab_out = self.unnormalize(lab_out).cpu().numpy()\n lab_out = np.transpose(lab_out, (0, 2, 3, 1)).astype(np.uint8)\n for i in range(n):\n color_out = cv2.cvtColor(lab_out[i], cv2.COLOR_LAB2BGR)\n color_out = cv2.resize(color_out, (96, 96), interpolation=cv2.INTER_AREA)\n cv2.imwrite(\"../datasets/stl10/divcolor/{}.png\".format(str(i)), color_out)\n return","def add_alpha(image_data):\n\n # get hsv image\n hsv = rgb_to_hsv(image_data[:, :, :3].astype(float) / 255)\n\n # create new image and set alpha channel\n new_image_data = np.zeros(image_data.shape)\n new_image_data[:, :, 3] = hsv[:, :, 2]\n\n # set value of hsv image to either 0 or 1.\n hsv[:, :, 2] = np.where(hsv[:, :, 2] > 0, 1, 0)\n\n # combine alpha and new rgb\n new_image_data[:, :, :3] = hsv_to_rgb(hsv)\n return new_image_data","def apply_color_processing(imgdata, cpopt, flat=False):\r\n\r\n if cpopt == ColorProcessingOptions.cpColor:\r\n if flat:\r\n raise ValueError(\"Color images can not be represented as a flat image array without color information\")\r\n return imgdata\r\n\r\n if cpopt == ColorProcessingOptions.cpRed:\r\n flat_imgdata = imgdata[:, :, 0]\r\n elif cpopt == ColorProcessingOptions.cpGreen:\r\n flat_imgdata = imgdata[:, :, 1]\r\n elif cpopt == ColorProcessingOptions.cpBlue:\r\n flat_imgdata = imgdata[:, :, 2]\r\n elif cpopt == ColorProcessingOptions.cpMonochrome:\r\n flat_imgdata = np.array(Image.fromarray(imgdata).convert(\"L\"))\r\n\r\n if flat:\r\n return flat_imgdata\r\n\r\n color_index = {\r\n ColorProcessingOptions.cpRed: [0],\r\n ColorProcessingOptions.cpGreen: [1],\r\n ColorProcessingOptions.cpBlue: [2],\r\n ColorProcessingOptions.cpMonochrome: [0, 1, 2]\r\n }\r\n\r\n converted_imgdata = np.zeros_like(imgdata)\r\n for ci in color_index[cpopt]:\r\n converted_imgdata[:, :, ci] = flat_imgdata\r\n\r\n return converted_imgdata","def colors(im=None):\n if im is None:\n path = \"C:\\\\Users\\\\2053_HSUF\\\\PycharmProjects\\\\dialtones\\\\pics\\\\76aa16c9_playstore.png\"\n im = cv2.imread(path, cv2.IMREAD_GRAYSCALE)\n for shade in range(13):\n colorized = cv2.applyColorMap(im, shade)\n cv2.imshow(\"yo\", colorized)\n cv2.waitKey(0)\n cv2.destroyAllWindows()","def __call__(self, img, target):\n if random.random() < 0.5:\n img = ImageEnhance.Brightness(img).enhance(0.5 + random.random())\n if random.random() < 0.5:\n img = ImageEnhance.Color(img).enhance(0.5 + random.random())\n if random.random() < 0.5:\n img = ImageEnhance.Contrast(img).enhance(0.5 + random.random())\n return img, target","def setColors255(self):\r\n # productive\r\n profprint()\r\n self.color255 = [[0, 0, 0] for i in range(MAXCOL)]\r\n self.color255[0] = [221, 108, 158]\r\n self.color255[1] = [128, 174, 128]\r\n self.color255[2] = [241, 214, 145]\r\n self.color255[3] = [177, 122, 101]\r\n self.color255[4] = [111, 184, 210]\r\n self.color255[5] = [216, 101, 79]\r\n self.color255[6] = [221, 130, 101]\r\n self.color255[7] = [144, 238, 144]\r\n self.color255[8] = [192, 104, 88]\r\n self.color255[9] = [220, 245, 20]\r\n self.color255[10] = [78, 63, 0]\r\n self.color255[11] = [255, 250, 220]\r\n self.color255[12] = [230, 220, 70]\r\n self.color255[13] = [200, 200, 235]\r\n self.color255[14] = [250, 250, 210]\r\n self.color255[15] = [244, 214, 49]\r\n self.color255[16] = [0, 151, 206]\r\n self.color255[17] = [183, 156, 220]\r\n self.color255[18] = [183, 214, 211]\r\n self.color255[19] = [152, 189, 207]\r\n self.color255[20] = [178, 212, 242]\r\n self.color255[21] = [68, 172, 100]\r\n self.color255[22] = [111, 197, 131]\r\n self.color255[23] = [85, 188, 255]\r\n self.color255[24] = [0, 145, 30]\r\n self.color255[25] = [214, 230, 130]\r\n self.color255[26] = [218, 255, 255]\r\n self.color255[27] = [170, 250, 250]\r\n self.color255[28] = [140, 224, 228]\r\n self.color255[29] = [188, 65, 28]\r\n self.color255[30] = [216, 191, 216]\r\n self.color255[31] = [145, 60, 66]\r\n self.color255[32] = [150, 98, 83]\r\n self.color255[33] = [250, 250, 225]\r\n self.color255[34] = [200, 200, 215]\r\n self.color255[35] = [68, 131, 98]\r\n self.color255[36] = [83, 146, 164]\r\n self.color255[37] = [162, 115, 105]\r\n self.color255[38] = [141, 93, 137]\r\n self.color255[39] = [182, 166, 110]\r\n self.color255[40] = [188, 135, 166]\r\n self.color255[41] = [154, 150, 201]\r\n self.color255[42] = [177, 140, 190]\r\n self.color255[43] = [30, 111, 85]\r\n self.color255[44] = [210, 157, 166]\r\n self.color255[45] = [48, 129, 126]\r\n self.color255[46] = [98, 153, 112]\r\n self.color255[47] = [69, 110, 53]\r\n self.color255[48] = [166, 113, 137]\r\n self.color255[49] = [122, 101, 38]\r\n self.color255[50] = [253, 135, 192]\r\n self.color255[51] = [145, 92, 109]\r\n self.color255[52] = [46, 101, 131]\r\n self.color255[53] = [0, 108, 112]\r\n self.color255[54] = [127, 150, 88]\r\n self.color255[55] = [159, 116, 163]\r\n self.color255[56] = [125, 102, 154]\r\n self.color255[57] = [106, 174, 155]\r\n self.color255[58] = [154, 146, 83]\r\n self.color255[59] = [126, 126, 55]\r\n self.color255[60] = [201, 160, 133]\r\n self.color255[61] = [78, 152, 141]\r\n self.color255[62] = [174, 140, 103]\r\n self.color255[63] = [139, 126, 177]\r\n self.color255[64] = [148, 120, 72]\r\n self.color255[65] = [186, 135, 135]\r\n self.color255[66] = [99, 106, 24]\r\n self.color255[67] = [156, 171, 108]\r\n self.color255[68] = [64, 123, 147]\r\n self.color255[69] = [138, 95, 74]\r\n self.color255[70] = [97, 113, 158]\r\n self.color255[71] = [126, 161, 197]\r\n self.color255[72] = [194, 195, 164]\r\n self.color255[73] = [88, 106, 215]\r\n self.color255[74] = [82, 174, 128]\r\n self.color255[75] = [57, 157, 110]\r\n self.color255[76] = [60, 143, 83]\r\n self.color255[77] = [92, 162, 109]\r\n self.color255[78] = [255, 244, 209]\r\n self.color255[79] = [201, 121, 77]\r\n self.color255[80] = [70, 163, 117]\r\n self.color255[81] = [188, 91, 95]\r\n self.color255[82] = [166, 84, 94]\r\n self.color255[83] = [182, 105, 107]\r\n self.color255[84] = [229, 147, 118]\r\n self.color255[85] = [174, 122, 90]\r\n self.color255[86] = [201, 112, 73]\r\n self.color255[87] = [194, 142, 0]\r\n self.color255[88] = [241, 213, 144]\r\n self.color255[89] = [203, 179, 77]\r\n self.color255[90] = [229, 204, 109]\r\n self.color255[91] = [255, 243, 152]\r\n self.color255[92] = [209, 185, 85]\r\n self.color255[93] = [248, 223, 131]\r\n self.color255[94] = [255, 230, 138]\r\n self.color255[95] = [196, 172, 68]\r\n self.color255[96] = [255, 255, 167]\r\n self.color255[97] = [255, 250, 160]\r\n self.color255[98] = [255, 237, 145]\r\n self.color255[99] = [242, 217, 123]\r\n self.color255[100] = [222, 198, 101]\r\n self.color255[101] = [213, 124, 109]\r\n self.color255[102] = [184, 105, 108]\r\n self.color255[103] = [150, 208, 243]\r\n self.color255[104] = [62, 162, 114]\r\n self.color255[105] = [242, 206, 142]\r\n self.color255[106] = [250, 210, 139]\r\n self.color255[107] = [255, 255, 207]\r\n self.color255[108] = [182, 228, 255]\r\n self.color255[109] = [175, 216, 244]\r\n self.color255[110] = [197, 165, 145]\r\n self.color255[111] = [172, 138, 115]\r\n self.color255[112] = [202, 164, 140]\r\n self.color255[113] = [224, 186, 162]\r\n self.color255[114] = [255, 245, 217]\r\n self.color255[115] = [206, 110, 84]\r\n self.color255[116] = [210, 115, 89]\r\n self.color255[117] = [203, 108, 81]\r\n self.color255[118] = [233, 138, 112]\r\n self.color255[119] = [195, 100, 73]\r\n self.color255[120] = [181, 85, 57]\r\n self.color255[121] = [152, 55, 13]\r\n self.color255[122] = [159, 63, 27]\r\n self.color255[123] = [166, 70, 38]\r\n self.color255[124] = [218, 123, 97]\r\n self.color255[125] = [225, 130, 104]\r\n self.color255[126] = [224, 97, 76]\r\n self.color255[127] = [184, 122, 154]\r\n self.color255[128] = [211, 171, 143]\r\n self.color255[129] = [47, 150, 103]\r\n self.color255[130] = [173, 121, 88]\r\n self.color255[131] = [188, 95, 76]\r\n self.color255[132] = [255, 239, 172]\r\n self.color255[133] = [226, 202, 134]\r\n self.color255[134] = [253, 232, 158]\r\n self.color255[135] = [244, 217, 154]\r\n self.color255[136] = [205, 179, 108]\r\n self.color255[137] = [186, 124, 161]\r\n self.color255[138] = [255, 255, 220]\r\n self.color255[139] = [234, 234, 194]\r\n self.color255[140] = [204, 142, 178]\r\n self.color255[141] = [180, 119, 153]\r\n self.color255[142] = [216, 132, 105]\r\n self.color255[143] = [255, 253, 229]\r\n self.color255[144] = [205, 167, 142]\r\n self.color255[145] = [204, 168, 143]\r\n self.color255[146] = [255, 224, 199]\r\n self.color255[147] = [139, 150, 98]\r\n self.color255[148] = [249, 180, 111]\r\n self.color255[149] = [157, 108, 162]\r\n self.color255[150] = [203, 136, 116]\r\n self.color255[151] = [185, 102, 83]\r\n self.color255[152] = [247, 182, 164]\r\n self.color255[153] = [222, 154, 132]\r\n self.color255[154] = [124, 186, 223]\r\n self.color255[155] = [249, 186, 150]\r\n self.color255[156] = [244, 170, 147]\r\n self.color255[157] = [255, 181, 158]\r\n self.color255[158] = [255, 190, 165]\r\n self.color255[159] = [227, 153, 130]\r\n self.color255[160] = [213, 141, 113]\r\n self.color255[161] = [193, 123, 103]\r\n self.color255[162] = [216, 146, 127]\r\n self.color255[163] = [230, 158, 140]\r\n self.color255[164] = [245, 172, 147]\r\n self.color255[165] = [241, 172, 151]\r\n self.color255[166] = [177, 124, 92]\r\n self.color255[167] = [171, 85, 68]\r\n self.color255[168] = [217, 198, 131]\r\n self.color255[169] = [212, 188, 102]\r\n self.color255[170] = [185, 135, 134]\r\n self.color255[171] = [198, 175, 125]\r\n self.color255[172] = [194, 98, 79]\r\n self.color255[173] = [255, 238, 170]\r\n self.color255[174] = [206, 111, 93]\r\n self.color255[175] = [216, 186, 0]\r\n self.color255[176] = [255, 226, 77]\r\n self.color255[177] = [255, 243, 106]\r\n self.color255[178] = [255, 234, 92]\r\n self.color255[179] = [240, 210, 35]\r\n self.color255[180] = [224, 194, 0]\r\n self.color255[181] = [213, 99, 79]\r\n self.color255[182] = [217, 102, 81]\r\n self.color255[183] = [0, 147, 202]\r\n self.color255[184] = [0, 122, 171]\r\n self.color255[185] = [186, 77, 64]\r\n self.color255[186] = [240, 255, 30]\r\n self.color255[187] = [185, 232, 61]\r\n self.color255[188] = [0, 226, 255]\r\n self.color255[189] = [251, 159, 255]\r\n self.color255[190] = [230, 169, 29]\r\n self.color255[191] = [0, 194, 113]\r\n self.color255[192] = [104, 160, 249]\r\n self.color255[193] = [221, 108, 158]\r\n self.color255[194] = [137, 142, 0]\r\n self.color255[195] = [230, 70, 0]\r\n self.color255[196] = [0, 147, 0]\r\n self.color255[197] = [0, 147, 248]\r\n self.color255[198] = [231, 0, 206]\r\n self.color255[199] = [129, 78, 0]\r\n self.color255[200] = [0, 116, 0]\r\n self.color255[201] = [0, 0, 255]\r\n self.color255[202] = [157, 0, 0]\r\n self.color255[203] = [100, 100, 130]\r\n self.color255[204] = [205, 205, 100]\r\n self.color255[205] = [255, 255, 0]\r\n\r\n return self.color255","def ColorJitterAug(img, brightness, contrast, saturation):\n coef = np.array([[[0.299, 0.587, 0.114]]])\n if brightness > 0:\n \"\"\"Augumenter body\"\"\"\n alpha = 1.0 + random.uniform(-brightness, brightness) * 0.7\n img *= alpha\n img = np.clip(img, 0.,255.)\n\n if contrast > 0:\n \"\"\"Augumenter body\"\"\"\n alpha = 1.0 + random.uniform(-contrast, contrast) * 0.7\n gray = img*coef\n gray = (3.0*(1.0-alpha)/gray.size)*np.sum(gray)\n img *= alpha\n img += gray\n img = np.clip(img, 0.,255.)\n\n if saturation > 0:\n \"\"\"Augumenter body\"\"\"\n alpha = 1.0 + random.uniform(-saturation, saturation) * 0.7\n gray = img*coef\n gray = np.sum(gray, axis=2, keepdims=True)\n gray *= (1.0-alpha)\n img *= alpha\n img += gray\n img = np.clip(img, 0.,255.)\n return img","def recolorRC(src,dst):\n b,g,r=cv2.split(src)\n cv2.addWeighted(b,0.5,g,0.5,0,b) #arguements(in order):first src array,a weight applied\n # to array, scnd src array, a weight applied to array\n # a constant added to the result and a destination array\n cv2.merge((b,b,r),dest) #replace b and g with modified b(which has both and g)","def enhance_edges(image):\n working_image = image.copy()\n working_image = cv2.cvtColor(working_image, cv2.COLOR_BGR2GRAY)\n # Blur away fine details.\n working_image = cv2.GaussianBlur(working_image, (5, 5), 0)\n return working_image","def intensityPSF_Blues(N=1000):\n col_seq = [( 0/255., 20/255., 80/255.), ( 8/255., 48/255., 107/255.),\n ( 8/255., 81/255., 156/255.), ( 33/255., 113/255., 181/255.),\n ( 66/255., 146/255., 198/255.), (107/255., 174/255., 214/255.),\n (158/255., 202/255., 225/255.), (198/255., 219/255., 239/255.),\n (222/255., 235/255., 247/255.), (247/255., 251/255., 255/255.)]\n\n cdict = {'red': ((0.00, col_seq[0][0], col_seq[0][0]),\n (0.02, col_seq[1][0], col_seq[1][0]),\n (0.06, col_seq[2][0], col_seq[2][0]),\n (0.10, col_seq[3][0], col_seq[3][0]),\n (0.20, col_seq[4][0], col_seq[4][0]),\n (0.30, col_seq[5][0], col_seq[5][0]),\n (0.50, col_seq[6][0], col_seq[6][0]),\n (0.75, col_seq[7][0], col_seq[7][0]),\n (0.90, col_seq[8][0], col_seq[8][0]),\n (1.00, col_seq[9][0], col_seq[9][0])),\n 'green': ((0.00, col_seq[0][1], col_seq[0][1]),\n (0.02, col_seq[1][1], col_seq[1][1]),\n (0.06, col_seq[2][1], col_seq[2][1]),\n (0.10, col_seq[3][1], col_seq[3][1]),\n (0.20, col_seq[4][1], col_seq[4][1]),\n (0.30, col_seq[5][1], col_seq[5][1]),\n (0.50, col_seq[6][1], col_seq[6][1]),\n (0.75, col_seq[7][1], col_seq[7][1]),\n (0.90, col_seq[8][1], col_seq[8][1]),\n (1.00, col_seq[9][1], col_seq[9][1])),\n 'blue': ((0.00, col_seq[0][2], col_seq[0][2]),\n (0.02, col_seq[1][2], col_seq[1][2]),\n (0.06, col_seq[2][2], col_seq[2][2]),\n (0.10, col_seq[3][2], col_seq[3][2]),\n (0.20, col_seq[4][2], col_seq[4][2]),\n (0.30, col_seq[5][2], col_seq[5][2]),\n (0.50, col_seq[6][2], col_seq[6][2]),\n (0.75, col_seq[7][2], col_seq[7][2]),\n (0.90, col_seq[8][2], col_seq[8][2]),\n (1.00, col_seq[9][2], col_seq[9][2]))}\n\n psfblues = _mplb.colors.LinearSegmentedColormap('psfblues', cdict, N)\n return psfblues","def darken(image_path, factor=0.5):\n BasicTransform.convert_image(image_path)\n\n with Image.open(image_path) as img:\n filter = ImageEnhance.Brightness(img)\n new_image = filter.enhance(factor)\n new_image.save(image_path)","def applyHSV(img):\n\treturn applyColorMap(img, \"hsv\")","def calibrate_image(image, tl = 0.5):\n for y in range(len(image)):\n for x in range(len(image[y])):\n # Convert the exiting pixel color to HLS model.\n h, l, s = rgb_to_hls(image[y, x])\n\n # We convert the HLS model back to RGB, but using our target \n # brightness value `tl`.\n r, g, b = colorsys.hls_to_rgb(h, tl, s)\n \n # Set the new pixel color.\n image[y][x] = [r * 255, g * 255, b * 255]\n\n return image","def change_Shield_Color (im, newcolor, GRAPHICSMODE=\"PIL\"):\r\n DEBUG = 0\r\n #DEBUG = 1\r\n\r\n if DEBUG == 1:\r\n print \"newcolor:\", newcolor\r\n print \"im:\", im\r\n \r\n THRESHOLD = 225 # Doesn't rely on colour being exactly 255,255,255\r\n\r\n if GRAPHICSMODE == \"PIL\":\r\n im.convert(\"RGBA\")\r\n newimdata = []\r\n for color in im.getdata():\r\n if color[0] > THRESHOLD:\r\n if color[1] > THRESHOLD:\r\n if color[2] > THRESHOLD:\r\n if color[3] > THRESHOLD:\r\n newimdata.append(newcolor)\r\n else:\r\n newimdata.append(color)\r\n else:\r\n newimdata.append(color)\r\n else:\r\n newimdata.append(color)\r\n else:\r\n newimdata.append(color)\r\n #print\r\n newim = PilImage.new(\"RGBA\",im.size)\r\n newim.putdata(newimdata)\r\n\r\n elif GRAPHICSMODE == \"PyGame\":\r\n im.convert()\r\n if DEBUG == 1:\r\n print \"newcolor:\", newcolor\r\n newcolor = pygame.Color(newcolor[0], newcolor[1], newcolor[2], 255) # why the HELL does pygame reverse RBG -> GBR???\r\n\r\n if DEBUG == 1:\r\n print \"newcolor(converted):\", newcolor\r\n newim = pygame.Surface((im.get_width(),im.get_height()), pygame.SRCALPHA, 32) #change its background color \r\n\r\n tochange = pygame.Color(THRESHOLD, THRESHOLD, THRESHOLD,255) # or whatever yellow color you want\r\n\r\n thresh = (20, 20, 20, 20) # or whatever threshold works\r\n\r\n if DEBUG == 1:\r\n print \"newim:\",newim \r\n print \"type(newim):\",type(newim)\r\n print \"im:\",im\r\n print \"type(im):\",type(im)\r\n print \"tochange:\",tochange\r\n print \"thresh:\",thresh\r\n print \"newcolor:\",newcolor\r\n\r\n pygame.Surface.lock(im)\r\n\r\n for imx in range(0, im.get_width()):\r\n for imy in range(0, im.get_height()):\r\n color = im.get_at((imx,imy))\r\n if color[0] > THRESHOLD:\r\n if color[1] > THRESHOLD:\r\n if color[2] > THRESHOLD:\r\n if color[3] > THRESHOLD:\r\n newim.set_at((imx,imy), newcolor)\r\n else:\r\n newim.set_at((imx,imy), color)\r\n else:\r\n newim.set_at((imx,imy), color)\r\n else:\r\n newim.set_at((imx,imy), color)\r\n else:\r\n newim.set_at((imx,imy), color)\r\n\r\n if DEBUG == 1:\r\n if os.path.isfile(\"E:\\\\Projects\\\\NEW RENPY GAME\\\\TEMP\\\\TESTFILE_OLD.png\"):\r\n os.remove(\"E:\\\\Projects\\\\NEW RENPY GAME\\\\TEMP\\\\TESTFILE_OLD.png\")\r\n if os.path.isfile(\"E:\\\\Projects\\\\NEW RENPY GAME\\\\TEMP\\\\TESTFILE.png\"):\r\n os.rename(\"E:\\\\Projects\\\\NEW RENPY GAME\\\\TEMP\\\\TESTFILE.png\", \"E:\\\\Projects\\\\NEW RENPY GAME\\\\TEMP\\\\TESTFILE_OLD.png\")\r\n pygame.image.save(newim, \"E:\\\\Projects\\\\NEW RENPY GAME\\\\TEMP\\\\TESTFILE.png\")\r\n print \"wrote file 'E:\\\\Projects\\\\NEW RENPY GAME\\\\TEMP\\\\TESTFILE.png'\"\r\n print\r\n\r\n pygame.Surface.unlock(im)\r\n\r\n return newim","def adjust(im, col, startcol=None):\n\tif startcol is None:\n\t\tstartcol = meancol(im)\n\trband, gband, bband = im.split()\n\trbri, gbri, bbri = ImageEnhance.Brightness(rband), ImageEnhance.Brightness(gband), ImageEnhance.Brightness(bband)\n\trband = rbri.enhance((float(col[0]) / float(startcol[0])))\n\tgband = gbri.enhance((float(col[1]) / float(startcol[1])))\n\tbband = bbri.enhance((float(col[2]) / float(startcol[2])))\n\tim = Image.merge(\"RGB\",(rband, gband, bband))\n\treturn im","def do_reduce_colors(img: Image.Image,\n max_colors: int) -> Tuple[Image.Image, int, int]:\n orig_mode = img.mode\n\n if orig_mode == \"1\":\n return img, 2, 2\n\n colors = img.getcolors()\n if colors:\n orig_colors = len(colors)\n else:\n orig_colors = 0\n\n # Intermediate conversion steps when needed\n if orig_mode in [\"CMYK\", \"YCbCr\", \"LAB\", \"HSV\"]:\n img = img.convert(\"RGB\")\n elif orig_mode == \"LA\":\n img = img.convert(\"RGBA\")\n\n # Actual color reduction happening here\n if orig_mode in [\"RGB\", \"L\"]:\n palette = Image.ADAPTIVE\n elif orig_mode == \"RGBA\":\n palette = Image.ADAPTIVE\n transparent = Image.new(\"RGBA\", img.size, (0, 0, 0, 0))\n # blend with transparent image using own alpha\n img = Image.composite(img, transparent, img)\n elif orig_mode == \"P\":\n palette = img.getpalette()\n img = img.convert(\"RGBA\")\n width, height = img.size\n alpha_layer = Image.new(\"L\", img.size)\n for x in range(width):\n for y in range(height):\n _, _, _, alpha = img.getpixel((x, y))\n alpha_layer.putpixel((x, y), alpha)\n img.putalpha(alpha_layer)\n else:\n return img, 0, 0\n\n img = img.convert(\"P\", palette=palette, colors=max_colors)\n return img, orig_colors, len(img.getcolors())","def posterize(picture: Image) -> Image:\r\n new_pic = copy(picture)\r\n red = 0\r\n green = 0\r\n blue = 0\r\n for x, y, (r, g, b) in picture:\r\n red = _adjust_component(r)\r\n green = _adjust_component(g)\r\n blue = _adjust_component(b)\r\n new_colour = Color(red,green,blue)\r\n set_color(new_pic, x, y, new_colour)\r\n return new_pic","def Contrast(img):\r\n factor = 2 * (np.random.rand() - 0.5) * 128\r\n assert (factor <= 128 and factor >= -128), 'contract factor value wrong'\r\n fvalue = 259.0/255.0 * (factor + 255.0)/(259.0-factor)\r\n img = np.round((img - 128.0)*fvalue + 128.0)\r\n img = np.where(img > 255, 255, img)\r\n img = np.where(img < 0, 0, img)\r\n img = np.uint8(img)\r\n return img","def stain_image(image, num_stains, color):","def IncreaseContrast(self, image, percentage):\n # copyImage = [ [0...0][0...0][0...0][0...0]]\n # copyImage = np.zeros(image.shape, image.dtype) # dtype is the data type ex:int\n # newImg = loop x,y,c (old_image) * a + b\n\n a = 1.5 # [1.0..3.0] Responsible for Contrast #TODO GET PARAMS\n b = 35 # [0.. 100] Responsible for Brightness #TODO GET PARAMS\n newImg = cv2.convertScaleAbs(image, alpha=a, beta=b)\n return newImg","def exercise2a(self):\n colors = [\n [253, 253, 150],\n [255, 125, 125],\n [150, 111, 214],\n [119, 158, 203],\n [255, 105, 97],\n [ 3, 192, 60]\n ]\n # This takes some time …\n #self.b1 = mandelbrot(1200, 600, colors, [0, 0, 0], 0.02, 0.73, 0.21)\n # Load the pregenerated image ;)\n self.b1 = misc.imread(\"B1.png\")\n plt.axis('off')\n plt.imshow(self.b1)\n plt.show()\n misc.imsave(\"B1.png\", self.b1)\n misc.imsave(\"B1_Brightness.png\", print_brightness(self.b1))","def augment(self, image):\n\n contrast = ImageEnhance.Contrast(image)\n return contrast.enhance(self._contrast)","def colourise_image(self, folder_name):\n colourised_folder_name = folder_name + '_colourised'\n\n try:\n print(\"Making dir \" + str(colourised_folder_name) + \" for colourisation\")\n os.mkdir(colourised_folder_name)\n except OSError:\n print(\"Folder exists, have you already done this colourisation??\")\n return\n\n print(\"Writing to folder +\" + str(colourised_folder_name))\n photo_list = self.get_photo_list(folder_name)\n for i, name in enumerate(photo_list):\n file_name = folder_name + '/' + name\n colourised_image_name = colourised_folder_name + '/' + name\n image = cv2.imread(file_name, cv2.IMREAD_GRAYSCALE)\n image_8bit = image.astype(np.uint8)\n colour_image = cv2.applyColorMap(image_8bit, cv2.COLORMAP_JET)\n cv2.imwrite(colourised_image_name, colour_image)","def Color(img: Image, magnitude: float) -> Image:\n return PIL.ImageEnhance.Color(img).enhance(1 + magnitude * random.choice([-1, 1]))","def _process_img_rgb(self, sensor_data):\n img = np.array(sensor_data.raw_data).reshape((self.img_y, self.img_x, 4))\n img = img[:, :, :3] # sensor is actualy rgba, we dont need alpha values\n self.rgb = img # need to scale rgb values to be {0,1}","def change_color(icon, color):\n img = icon.convert(\"LA\")\n img = img.convert(\"RGBA\")\n image_np = np.array(icon)\n _, _, _, alpha = image_np.T\n mask = alpha > 0\n image_np[..., :-1][mask.T] = ImageColor.getcolor(color, \"RGB\")\n edited_image = Image.fromarray(image_np)\n return edited_image","def setColors255(self):\n #productive\n profprint()\n self.color255= [[0,0,0] for i in range(205)]\n self.color255[0]=[221,108,158]\n self.color255[1]=[128,174,128]\n self.color255[2]=[241,214,145]\n self.color255[3]=[177,122,101]\n self.color255[4]=[111,184,210]\n self.color255[5]=[216,101,79]\n self.color255[6]=[221,130,101]\n self.color255[7]=[144,238,144]\n self.color255[8]=[192,104,88]\n self.color255[9]=[220,245,20]\n self.color255[10]=[78,63,0]\n self.color255[11]=[255,250,220]\n self.color255[12]=[230,220,70]\n self.color255[13]=[200,200,235]\n self.color255[14]=[250,250,210]\n self.color255[15]=[244,214,49]\n self.color255[16]=[0,151,206]\n self.color255[17]=[183,156,220]\n self.color255[18]=[183,214,211]\n self.color255[19]=[152,189,207]\n self.color255[20]=[178,212,242]\n self.color255[21]=[68,172,100]\n self.color255[22]=[111,197,131]\n self.color255[23]=[85,188,255]\n self.color255[24]=[0,145,30]\n self.color255[25]=[214,230,130]\n self.color255[26]=[218,255,255]\n self.color255[27]=[170,250,250]\n self.color255[28]=[140,224,228]\n self.color255[29]=[188,65,28]\n self.color255[30]=[216,191,216]\n self.color255[31]=[145,60,66]\n self.color255[32]=[150,98,83]\n self.color255[33]=[250,250,225]\n self.color255[34]=[200,200,215]\n self.color255[35]=[68,131,98]\n self.color255[36]=[83,146,164]\n self.color255[37]=[162,115,105]\n self.color255[38]=[141,93,137]\n self.color255[39]=[182,166,110]\n self.color255[40]=[188,135,166]\n self.color255[41]=[154,150,201]\n self.color255[42]=[177,140,190]\n self.color255[43]=[30,111,85]\n self.color255[44]=[210,157,166]\n self.color255[45]=[48,129,126]\n self.color255[46]=[98,153,112]\n self.color255[47]=[69,110,53]\n self.color255[48]=[166,113,137]\n self.color255[49]=[122,101,38]\n self.color255[50]=[253,135,192]\n self.color255[51]=[145,92,109]\n self.color255[52]=[46,101,131]\n self.color255[53]=[0,108,112]\n self.color255[54]=[127,150,88]\n self.color255[55]=[159,116,163]\n self.color255[56]=[125,102,154]\n self.color255[57]=[106,174,155]\n self.color255[58]=[154,146,83]\n self.color255[59]=[126,126,55]\n self.color255[60]=[201,160,133]\n self.color255[61]=[78,152,141]\n self.color255[62]=[174,140,103]\n self.color255[63]=[139,126,177]\n self.color255[64]=[148,120,72]\n self.color255[65]=[186,135,135]\n self.color255[66]=[99,106,24]\n self.color255[67]=[156,171,108]\n self.color255[68]=[64,123,147]\n self.color255[69]=[138,95,74]\n self.color255[70]=[97,113,158]\n self.color255[71]=[126,161,197]\n self.color255[72]=[194,195,164]\n self.color255[73]=[88,106,215]\n self.color255[74]=[82,174,128]\n self.color255[75]=[57,157,110]\n self.color255[76]=[60,143,83]\n self.color255[77]=[92,162,109]\n self.color255[78]=[255,244,209]\n self.color255[79]=[201,121,77]\n self.color255[80]=[70,163,117]\n self.color255[81]=[188,91,95]\n self.color255[82]=[166,84,94]\n self.color255[83]=[182,105,107]\n self.color255[84]=[229,147,118]\n self.color255[85]=[174,122,90]\n self.color255[86]=[201,112,73]\n self.color255[87]=[194,142,0]\n self.color255[88]=[241,213,144]\n self.color255[89]=[203,179,77]\n self.color255[90]=[229,204,109]\n self.color255[91]=[255,243,152]\n self.color255[92]=[209,185,85]\n self.color255[93]=[248,223,131]\n self.color255[94]=[255,230,138]\n self.color255[95]=[196,172,68]\n self.color255[96]=[255,255,167]\n self.color255[97]=[255,250,160]\n self.color255[98]=[255,237,145]\n self.color255[99]=[242,217,123]\n self.color255[100]=[222,198,101]\n self.color255[101]=[213,124,109]\n self.color255[102]=[184,105,108]\n self.color255[103]=[150,208,243]\n self.color255[104]=[62,162,114]\n self.color255[105]=[242,206,142]\n self.color255[106]=[250,210,139]\n self.color255[107]=[255,255,207]\n self.color255[108]=[182,228,255]\n self.color255[109]=[175,216,244]\n self.color255[110]=[197,165,145]\n self.color255[111]=[172,138,115]\n self.color255[112]=[202,164,140]\n self.color255[113]=[224,186,162]\n self.color255[114]=[255,245,217]\n self.color255[115]=[206,110,84]\n self.color255[116]=[210,115,89]\n self.color255[117]=[203,108,81]\n self.color255[118]=[233,138,112]\n self.color255[119]=[195,100,73]\n self.color255[120]=[181,85,57]\n self.color255[121]=[152,55,13]\n self.color255[122]=[159,63,27]\n self.color255[123]=[166,70,38]\n self.color255[124]=[218,123,97]\n self.color255[125]=[225,130,104]\n self.color255[126]=[224,97,76]\n self.color255[127]=[184,122,154]\n self.color255[128]=[211,171,143]\n self.color255[129]=[47,150,103]\n self.color255[130]=[173,121,88]\n self.color255[131]=[188,95,76]\n self.color255[132]=[255,239,172]\n self.color255[133]=[226,202,134]\n self.color255[134]=[253,232,158]\n self.color255[135]=[244,217,154]\n self.color255[136]=[205,179,108]\n self.color255[137]=[186,124,161]\n self.color255[138]=[255,255,220]\n self.color255[139]=[234,234,194]\n self.color255[140]=[204,142,178]\n self.color255[141]=[180,119,153]\n self.color255[142]=[216,132,105]\n self.color255[143]=[255,253,229]\n self.color255[144]=[205,167,142]\n self.color255[145]=[204,168,143]\n self.color255[146]=[255,224,199]\n self.color255[147]=[139,150,98]\n self.color255[148]=[249,180,111]\n self.color255[149]=[157,108,162]\n self.color255[150]=[203,136,116]\n self.color255[151]=[185,102,83]\n self.color255[152]=[247,182,164]\n self.color255[153]=[222,154,132]\n self.color255[154]=[124,186,223]\n self.color255[155]=[249,186,150]\n self.color255[156]=[244,170,147]\n self.color255[157]=[255,181,158]\n self.color255[158]=[255,190,165]\n self.color255[159]=[227,153,130]\n self.color255[160]=[213,141,113]\n self.color255[161]=[193,123,103]\n self.color255[162]=[216,146,127]\n self.color255[163]=[230,158,140]\n self.color255[164]=[245,172,147]\n self.color255[165]=[241,172,151]\n self.color255[166]=[177,124,92]\n self.color255[167]=[171,85,68]\n self.color255[168]=[217,198,131]\n self.color255[169]=[212,188,102]\n self.color255[170]=[185,135,134]\n self.color255[171]=[198,175,125]\n self.color255[172]=[194,98,79]\n self.color255[173]=[255,238,170]\n self.color255[174]=[206,111,93]\n self.color255[175]=[216,186,0]\n self.color255[176]=[255,226,77]\n self.color255[177]=[255,243,106]\n self.color255[178]=[255,234,92]\n self.color255[179]=[240,210,35]\n self.color255[180]=[224,194,0]\n self.color255[181]=[213,99,79]\n self.color255[182]=[217,102,81]\n self.color255[183]=[0,147,202]\n self.color255[184]=[0,122,171]\n self.color255[185]=[186,77,64]\n self.color255[186]=[240,255,30]\n self.color255[187]=[185,232,61]\n self.color255[188]=[0,226,255]\n self.color255[189]=[251,159,255]\n self.color255[190]=[230,169,29]\n self.color255[191]=[0,194,113]\n self.color255[192]=[104,160,249]\n self.color255[193]=[221,108,158]\n self.color255[194]=[137,142,0]\n self.color255[195]=[230,70,0]\n self.color255[196]=[0,147,0]\n self.color255[197]=[0,147,248]\n self.color255[198]=[231,0,206]\n self.color255[199]=[129,78,0]\n self.color255[200]=[0,116,0]\n self.color255[201]=[0,0,255]\n self.color255[202]=[157,0,0]\n self.color255[203]=[100,100,130]\n self.color255[204]=[205,205,100]\n \n return self.color255","def changeColor(self):\n self.layer.new_colormap()","def color_filter(self, image):\n converted = hls_scale(image)\n\n # white color mask\n white_lower_bnd, white_upper_bnd = self.color_filter_params[\"white_bounds\"]\n white_mask = cv2.inRange(converted, white_lower_bnd, white_upper_bnd)\n\n # yellow color mask\n yellow_lower_bnd, yellow_upper_bnd = self.color_filter_params[\"yellow_bounds\"]\n yellow_mask = cv2.inRange(converted, yellow_lower_bnd, yellow_upper_bnd)\n\n # combine the mask\n mask = cv2.bitwise_or(white_mask, yellow_mask)\n\n return cv2.bitwise_and(image, image, mask=mask)","def apply_image_function(\n self,\n image_function: Callable[[int, int, int, int], Tuple4IntType]\n ) -> 'BaseImage':\n w, h = self._surface.get_size()\n for x in range(w):\n for y in range(h):\n r, g, b, a = self._surface.get_at((x, y))\n r, g, b, a = image_function(r, g, b, a)\n r = int(max(0, min(r, 255)))\n g = int(max(0, min(g, 255)))\n b = int(max(0, min(b, 255)))\n a = int(max(0, min(a, 255)))\n # noinspection PyArgumentList\n self.set_at((x, y), pygame.Color(r, g, b, a))\n return self","def smooth_image(img_file=\"cy_double.png\"):\n \n oldimg, newimg, width, height, win = setup_image(img_file)\n\n for col in range(newimg.getWidth()):\n for row in range(newimg.getHeight()):\n p = newimg.getPixel(col, row)\n neighbors = []\n # Put the 8 surrounding pixels into neighbors\n for i in range(col-1, col+2):\n for j in range(row-1, row+2):\n try:\n neighbor = newimg.getPixel(i, j)\n neighbors.append(neighbor)\n except:\n continue\n nlen = len(neighbors)\n # Average out the RBG values\n if nlen:\n # Uncommented, the following line would leave most of the white \n # untouched which works a little better for real photographs, imo.\n #~ if nlen and p[0]+p[1]+p[2] < 690:\n p.red = sum([neighbors[i][0] for i in range(nlen)])/nlen\n p.green = sum([neighbors[i][1] for i in range(nlen)])/nlen\n p.blue = sum([neighbors[i][2] for i in range(nlen)])/nlen\n newimg.setPixel(col,row,p)\n\n write_image(img_file, newimg, win, \"_smooth\")","def apply_mask(image, mask, color, alpha=0.5):\n for c in range(3):\n image[:, :, c] = np.where(mask == 1,\n image[:, :, c] *\n (1 - alpha) + alpha * color[c] * 255,\n image[:, :, c])\n # cv2.imshow(\"TEST\",image.astype(np.uint8))\n # print(color)\n return image","def image_local_enhance_contrast(image: np.ndarray):\n \n # Resize image to a shape of (48, 48)\n image = image_as_square(image)\n\n image = filters.rank.enhance_contrast(image, morphology.disk(2))\n\n # Resize the iamge back to a shape of (2304, )\n return image_as_array(image)","def adjustContrast(img, fac):\n img2 = np.float32(img)\n mean = round(cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY).mean())\n img2 = (1 - fac) * mean + fac * img2\n img2 = np.uint8(img2.clip(min=0, max=255))\n return img2","def enhance_brightness(self, delta, p=None):\n if self._max_aug_nums>0:\n if self._nums>self._max_aug_nums:\n return self\n self._nums += 1\n if p is None:\n p = self._p\n self.image = enhance_brightness(self.image, delta, p)\n return self","def enhance(self, image):\n\n if self.random.uniform(0, 1) < self.p:\n return self.intensity_enhance(image)\n else:\n return image","def preprocess_image(img):\r\n\r\n hsvImg = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)\r\n\r\n hsvImg[...,1] = hsvImg[...,1]*1.75 #increase saturation by 175%\r\n\r\n image_f =cv2.cvtColor(hsvImg,cv2.COLOR_HSV2BGR)\r\n\r\n return image_f","def enhanceContrast(image, mask, target_path, name, save=False):\n \n\n \n # Contrast stretching\n p2, p98 = np.percentile(image, (2, 98))\n image_rescale = exposure.rescale_intensity(image, in_range=(p2, p98))\n \n # Equalization\n image_eq = exposure.equalize_hist(image)\n \n # Adaptive Equalization\n image_adapteq = exposure.equalize_adapthist(image, clip_limit=0.03)\n \n # Display results\n fig = plt.figure(figsize=(19, 13))\n axes = np.zeros((2, 4), dtype=np.object)\n axes[0, 0] = fig.add_subplot(2, 4, 1)\n for i in range(1, 4):\n axes[0, i] = fig.add_subplot(2, 4, 1+i, sharex=axes[0,0], sharey=axes[0,0])\n for i in range(0, 4):\n axes[1, i] = fig.add_subplot(2, 4, 5+i)\n \n ax_image, ax_hist, ax_cdf = plot_image_and_hist(image, mask, mask_cmap, img_cmap,\n axes[:, 0])\n ax_image.set_title('Low contrast image')\n \n y_min, y_max = ax_hist.get_ylim()\n ax_hist.set_ylabel('Number of pixels')\n ax_hist.set_yticks(np.linspace(0, y_max, 5))\n \n ax_image, ax_hist, ax_cdf = plot_image_and_hist(image_rescale, mask, mask_cmap, img_cmap,\n axes[:, 1])\n ax_image.set_title('Contrast stretching')\n \n ax_image, ax_hist, ax_cdf = plot_image_and_hist(image_eq, mask, mask_cmap, img_cmap,\n axes[:, 2])\n ax_image.set_title('Histogram equalization')\n \n ax_image, ax_hist, ax_cdf = plot_image_and_hist(image_adapteq,mask, mask_cmap, img_cmap,\n axes[:, 3])\n ax_image.set_title('Adaptive equalization')\n \n ax_cdf.set_ylabel('Fraction of total intensity')\n ax_cdf.set_yticks(np.linspace(0, 1, 5))\n \n # prevent overlap of y-axis labels\n fig.tight_layout()\n if save:\n plt.savefig(os.path.join(target_path, name))\n else:\n plt.show()\n plt.close()\n return image_adapteq","def process(self):\n self.output_image = cv.cvtColor(self.input_image, cv.COLOR_BGR2GRAY)\n cv.COLOR_BAYER_BG2GRAY\n return self.output_image","def _color(self, x, factor):\r\n factor = (factor/MAX_LEVEL) * 1.8 + .1\r\n degenerate = tf.image.grayscale_to_rgb(tf.image.rgb_to_grayscale(x))\r\n x = tfa.image.blend(degenerate, tf.cast(x, tf.float32), factor)\r\n return tf.saturate_cast(x, tf.uint8)","def enhance_hue(self, delta, p=None):\n if self._max_aug_nums>0:\n if self._nums>self._max_aug_nums:\n return self\n self._nums += 1\n if p is None:\n p = self._p\n self.image = enhance_hue(self.image, delta, p)\n return self","def change_color(image, from_color, to_color):\n\n\twidth, height = image.get_size()\n\tfor x in range(width):\n\t\tfor y in range(height):\n\t\t\tif image.get_at((x, y)) == from_color:\n\t\t\t\timage.set_at((x, y), to_color)\n\treturn image","def augment_brightness_camera_images(image):\n\n # The HSV - Hue Saturation Value representation converts the image from RGB space to HSV space\n # where the Value(brightness) represents the brightness that is randomly increased\n\n image1 = cv2.cvtColor(image,cv2.COLOR_RGB2HSV)\n random_bright = .25+np.random.uniform()\n #print(random_bright)\n image1[:,:,2] = image1[:,:,2]*random_bright\n image1 = cv2.cvtColor(image1,cv2.COLOR_HSV2RGB)\n return image1","def blur(img, start_x, start_y, radius, blur_w, blur_h):\n def around(img : Image, x, y, val_x, val_y):\n \"\"\"Gets the rgb values averages for all px in radius X around the given px\"\"\"\n colors = []\n r_color = []\n max_x, max_y = img.height, img.width \n for i, j in zip(range(val_x), range(val_y)): # Get the rgb values of all the pixels around\n try:\n colors.append(img.getpixel((x + i, y + j)))\n colors.append(img.getpixel((x - i, y - j)))\n colors.append(img.getpixel((x - i, y + j)))\n colors.append(img.getpixel((x + i, y - j)))\n except IndexError:\n if x + i > max_x:\n x = max_x\n if y + j > max_y:\n y = max_y\n print(\"IndexError handled ! X & Y are now \" , x, y, \" as the permitted max image value\") \n colors.append(img.getpixel((x, y)))\n for i in range(3): # Compute the average for each rbg value\n t_color = [x[i] for x in colors]\n r_color.append(sum(t_color)//len(colors))\n return r_color\n for x in range(blur_w):\n act_x = start_x + x\n # print(\"[act x]\", act_x)\n # if act_x > img.height: # SECURITY : If a digit superior than the height/width is input, it will automaticly use the height/width\n # # b = b + 1\n # act_x = img.height\n for y in range(blur_h): \n act_y = start_y + y\n # if act_y > img.width: # SECURITY : If a digit superior than the height/width is input, it will automaticly use the height/width\n # act_y = img.width\n px_c = around(img, act_x, act_y, radius, radius)\n img.putpixel((start_x + x, start_y + y), tuple(px_c))\n return img","def color_transfert():\n\n\n\tn_target = input(\"Tell me which picture wants a new make up.\\n\\n\")\n\tn_source = input(\"And now tell me which one she wanna look like \\n\\n\")\n\n\ttarget = cv.imread(n_target, 1)\n\tsource = cv.imread(n_source, 1)\n\n\t### So basically, target will get new colors from source\n\n\t## First let's convert them into the l alpha beta color space\n\n\tt_alpha = rgb2alpha(target)\n\ts_alpha = rgb2alpha(source)\n\n\n\t## Now let's make up our target thanks to some statistical operations\n\n\tm_target = make_up(t_alpha, s_alpha)\n\n\n\t## Finally we gonna convert target back to rgb space\n\n\tm_target = alpha2rgb(m_target)\n\n\t## And save it, so let's name it, you don't have to give the format, we'll add it here\n\n\tname = input(\"What's the name of the new picture ? \\n\")\n\n\tname += \".png\"\n\n\tcv.imwrite(name, m_target)\t\t# You can now post your new picture to instagramm and let\n\t\t\t\t\t\t# your followers believe that you are a skilled photograph.\t\n\t\t\t\t\t\t# I personally don't use this shit so fuck it.\n\n\tprint(\"{} saved.\".format(name))","def process_image(image):\r\n image = random_brightness(image)\r\n image = crop_image(image)\r\n image = resize(image)\r\n return image","def equalize_color(img):\n imgeq = numpy.zeros_like(img, dtype='float')\n for i in xrange(img.shape[2]):\n imgeq[:,:,i] = exposure.equalize_hist(img[:,:,i])\n return imgeq","def _adjust_contrast_img(self, results, factor=1.0):\n for key in results.get('img_fields', ['image']):\n img = results[key]\n results[key] = mmcv.adjust_contrast(img, factor).astype(img.dtype)","def colorize(self):\n return","def recompute_final_image(self):\n if self._image is None:\n self.final_image = None\n return\n if isinstance(self._image, np.ndarray):\n if self._image.dtype == np.float and np.any(self._image > 1):\n im = self._image / 255\n else:\n im = self._image\n if self.cmap is not None:\n im = cm.get_cmap(self.cmap)(im)\n im = PIL.Image.fromarray((im * 255).astype(np.uint8))\n else: # we hope it is a PIL image or equivalent\n im = self._image\n im = im.convert('RGBA')\n if self.make_square:\n new_size = max(im.width, im.height)\n im = im.resize((new_size, new_size), PIL.Image.NEAREST)\n if self.resolution is not None:\n if self.resolution.size == 1:\n im = im.resize((self.resolution, self.resolution),\n PIL.Image.NEAREST)\n else:\n im = im.resize(self.resolution,\n PIL.Image.NEAREST)\n if self.circ_cut is not None:\n middle = np.array(im.size) / 2\n x = np.arange(im.size[0]) - middle[0] + 0.5\n x = x / np.max(np.abs(x))\n y = np.arange(im.size[1]) - middle[1] + 0.5\n y = y / np.max(np.abs(y))\n yy, xx = np.meshgrid(y, x)\n r = np.sqrt(xx ** 2 + yy ** 2)\n alpha = np.empty(r.shape)\n alpha[r > 1] = 0\n alpha[r <= self.circ_cut] = 1\n val = (r > self.circ_cut) & (r <= 1)\n alpha[val] = (\n 0.5 + 0.5 * np.cos(\n np.pi * (r[val] - self.circ_cut)\n / (1 - self.circ_cut)))\n alpha = alpha.T * np.array(im.getchannel('A'))\n alpha = PIL.Image.fromarray(np.uint8(alpha))\n im.putalpha(alpha)\n if self.col is not None:\n if self.border_type is None:\n pass\n elif self.border_type == 'alpha':\n bg_alpha = np.array(im.getchannel('A'))\n bg_alpha = bg_alpha > 0\n bg_alpha = PIL.Image.fromarray(255 * np.uint8(bg_alpha))\n bg = PIL.Image.new('RGBA', im.size, color=self.col)\n bg.putalpha(bg_alpha)\n im = PIL.Image.alpha_composite(bg, im)\n elif self.border_type == 'pad':\n im = PIL.ImageOps.expand(\n im,\n border=self.border_width,\n fill=self.col)\n elif self.border_type == 'conv':\n im = PIL.ImageOps.expand(\n im,\n border=self.border_width,\n fill=(0, 0, 0, 0))\n bg_alpha = im.getchannel('A')\n bg_alpha = bg_alpha.filter(PIL.ImageFilter.BoxBlur(\n self.border_width))\n bg_alpha = np.array(bg_alpha)\n bg_alpha = 255 * np.uint8(bg_alpha > 0)\n bg_alpha = PIL.Image.fromarray(bg_alpha)\n bg = PIL.Image.new('RGBA', im.size, color=self.col)\n bg.putalpha(bg_alpha)\n im = PIL.Image.alpha_composite(bg, im)\n self.final_image = im","def recolorPixels(x,y,px, newColorArray):\r\n for i in range(0+coeff1*x,coeff1+coeff1*x):\r\n for j in range(0+coeff1*y,coeff1+coeff1*y):\r\n px[i,j]=newColorArray[x][y]","def apply(self):\n \n i = 0\n for LEDStrip in self._LEDStrips:\n LEDStrip.applyColor(self._colors[i][0], self._colors[i][1], self._colors[i][2])\n i += 1","def emphasis(self, img, scale=2, fraction=0.5) :\n return cv2.subtract(cv2.multiply(img[:,:,self.color],scale),\n cv2.multiply(cv2.add( img[:,:,(self.color+1)%3],\n img[:,:,(self.color+2)%3]),fraction))","def shade_grey(img):\n b,g,r = cv2.split(img)\n illumination_est = np.mean([shade_grey_est(x) for x in [b,g,r]])\n b_corrected = illumination_est/np.mean(b)*b\n b_corrected = b_corrected.clip(max=240)\n g_corrected = illumination_est/np.mean(g)*g\n g_corrected = g_corrected.clip(max=240)\n r_corrected = illumination_est/np.mean(r)*r\n r_corrected = r_corrected.clip(max=240)\n return cv2.merge((np.uint8(b_corrected),np.uint8(g_corrected),np.uint8(r_corrected)))","def manage_color(self,test=0):\n\t\thls = cv2.cvtColor(self.img, cv2.COLOR_RGB2HLS)\n\t\ts_t150_255 = ch_threshold(hls, 2, (150,255))\n\t\th_t25_180 = ch_threshold(hls, 0, (25,180))\n\t\tl_t200_255 = ch_threshold(hls,1, (200,255))\n\t\tyellow = self.manage_yellow()\n\t\t \n\t\ts_yellow = binary_or(s_t150_255, yellow)\n\t\ts_y_h = binary_substr(s_yellow,h_t25_180)\n\t\ts_y_h_l = binary_or(s_y_h, l_t200_255)\n\t\treturn s_y_h_l","async def update_image(new_value: str) -> None:\n img.apply(swatch, img.Handle.color(parse_color(new_value), size, size))","def paint_fill(image, col, row, color, orig_color):\n\n if image[row][col] != orig_color:\n return\n if row < 0 or row >= len(image) or col < 0 or col >= len(image[0]):\n return\n\n image[row][col] = color\n\n paint_fill(image, col - 1, row, color, orig_color)\n paint_fill(image, col + 1, row, color, orig_color)\n paint_fill(image, col, row - 1, color, orig_color)\n paint_fill(image, col, row + 1, color, orig_color)\n\n return","def contrast_brightness_demo(img, ctr, bri): # 亮度b 对比度c\n blank = np.zeros(img.shape, img.dtype)\n out = cv.addWeighted(img, ctr, blank, 1 - ctr, bri)\n\n return out","def add_color(self, markers):\n self.img[markers == -1] = [255, 255, 255]\n self.img[markers == 1] = [255, 0, 0]\n self.img[markers == 2] = [0, 50, 0]\n self.img[markers == 3] = [0, 0, 255]\n self.img[markers == 4] = [255, 255, 0]\n self.img[markers == 5] = [0, 255, 255]\n self.img[markers == 6] = [255, 0, 255]\n\n self.img[markers == 7] = [125, 0, 0]\n self.img[markers == 8] = [0, 125, 0]\n self.img[markers == 9] = [0, 0, 125]\n self.img[markers == 10] = [125, 125, 0]\n self.img[markers == 11] = [0, 125, 125]\n self.img[markers == 12] = [125, 0, 125]\n\n self.img[markers == 13] = [255, 255, 255]\n self.img[markers == 14] = [255, 0, 0]\n self.img[markers == 15] = [0, 255, 0]\n self.img[markers == 16] = [0, 0, 255]\n self.img[markers == 17] = [255, 255, 0]\n self.img[markers == 18] = [0, 255, 255]\n self.img[markers == 19] = [255, 0, 255]","def adjustSaturation(img, fac):\n img2 = np.float32(img)\n tmp = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n tmp = cv2.cvtColor(tmp, cv2.COLOR_GRAY2BGR)\n\n img2 = (1 - fac) * tmp + fac * img2\n img2 = np.uint8(img2.clip(0, 255))\n return img2","def apply_filter(self, image):\n pass","def changeColor( self ):\n\t\t\n\t\tx, y = self.position.xy\n\t\tself.color = ( int((x / WINDOW_X) * 128), int((x / WINDOW_X) * 128) + int((y / WINDOW_Y) * 128 ), int((y / WINDOW_Y) * 128))","def grayscale(image):\n for y in range(image.getHeight() ):\n for x in range (image.getWidth() ):\n (r, g, b) = image.getPixel(x,y)\n r = int(r * 0.299)\n g = int(g * 0.587)\n b = int(b * 0.114)\n gray = r + g + b\n image.setPixel (x, y, (gray, gray, gray))","def contrast_adjust(image, alpha=1.3, beta=20):\n newimage = image.astype(np.float32) * alpha + beta\n\n if type(image[0, 0, 0]) == np.uint8:\n newimage[newimage < 0] = 0\n newimage[newimage > 255] = 255\n return np.uint8(newimage)\n else:\n newimage[newimage < 0] = 0\n newimage[newimage > 1] = 1.\n return newimage","def adjust_contrast(img, contrast_factor):\n check_type(img)\n\n enhancer = ImageEnhance.Contrast(img)\n img = enhancer.enhance(contrast_factor)\n return img","def post_process_image(self, image):\r\n A = np.min(image)\r\n B = np.max(image)\r\n k = 255\r\n R, C = image.shape\r\n for i in range(R):\r\n for j in range(C):\r\n image[i][j] = (k / (B-A)) * (image[i][j] - A)\r\n average_image = np.average(image)\r\n if average_image > 50:\r\n return image.astype(dtype='uint8')\r\n else:\r\n return (255-image).astype(dtype='uint8')","def AutoContrast(img: Image, _: float) -> Image:\n return PIL.ImageOps.autocontrast(img)","def create_colorful_test_image(self):\n ch255 = np.full([100, 200, 1], 255, dtype=np.uint8)\n ch128 = np.full([100, 200, 1], 128, dtype=np.uint8)\n ch0 = np.full([100, 200, 1], 0, dtype=np.uint8)\n imr = np.concatenate((ch255, ch128, ch128), axis=2)\n img = np.concatenate((ch255, ch255, ch0), axis=2)\n imb = np.concatenate((ch255, ch0, ch255), axis=2)\n imw = np.concatenate((ch128, ch128, ch128), axis=2)\n imu = np.concatenate((imr, img), axis=1)\n imd = np.concatenate((imb, imw), axis=1)\n image = np.concatenate((imu, imd), axis=0)\n return image","def perform(self, image, mode):\n random.seed(self.seed.get(mode))\n if mode == 'binary':\n return image\n\n # gets random number between -0.5 and 0.5 from normal distribution\n change_in_saturation = max(-0.5, min(0.5, random.normalvariate(0, 0.167)))\n change_in_saturation = 0.35\n hsv_image = cv2.cvtColor(image.astype(np.float32), cv2.COLOR_BGR2HSV)\n max_change_per_pixel = (np.full((len(image[:, 0, 0]), len(image[0, :, 0])), 1) - hsv_image[:, :, 1])\n min_change_per_pixel = hsv_image[:, :, 1]\n change_per_pixel = np.minimum(min_change_per_pixel, max_change_per_pixel) * change_in_saturation\n\n hsv_image[:, :, 1] = hsv_image[:, :, 1] + change_per_pixel\n\n image = np.round(cv2.cvtColor(hsv_image, cv2.COLOR_HSV2BGR)).astype(np.uint8)\n return image","def weighted_grayscale(img):\n for pixel in img:\n x, y, col = pixel\n r, g, b = col\n \n r = (r * 0.299 + g * 0.587 + b * 0.114)\n r = g = b\n \n new_color = create_color(r, g, b)\n set_color(img, x, y, new_color)"],"string":"[\n \"def __enhance_image(self, img):\\n\\n blue = self.g.clahe.apply(img[:,:,0])\\n green = self.g.clahe.apply(img[:,:,1])\\n red = self.g.clahe.apply(img[:,:,2])\\n img[:,:,0] = blue\\n img[:,:,1] = green\\n img[:,:,2] = red\\n return img\",\n \"def _adjust_color_img(self, results, factor=1.0):\\n for key in results.get('img_fields', ['image']):\\n # NOTE defaultly the image should be BGR format\\n img = results[key]\\n results[key] = mmcv.adjust_color(img, factor).astype(img.dtype)\",\n \"def enhance_contrast(img):\\n for y in range(frame_height):\\n for x in range(frame_width):\\n if img[y, x, 1] > 100:\\n # range of blues to limit of puppet motion 255/(frame_width - 150)\\n img[y][x][0] = x*0.4\\n if img[y, x, 1] <= 100:\\n img[y][x][2] = img[y][x][2]*0.5\\n cv2.imwrite(\\\"contrasted.png\\\", img)\",\n \"def colorize(image, newColor):\\n image = image.copy()\\n\\n # zero out RGB values\\n image.fill((0, 0, 0, 255), None, pg.BLEND_RGBA_MULT)\\n # add in new RGB values\\n image.fill(newColor[0:3] + (0,), None, pg.BLEND_RGBA_ADD)\\n\\n return image\",\n \"def set_color(self):\\n self.image[self.x, self.y] = self.color\\n if self.diffusion:\\n r = g = b = 0\\n for i in range(self.convolution_matrix.shape[0]):\\n for j in range(self.convolution_matrix.shape[1]):\\n r = g = b = 0\\n for k in range(self.convolution_matrix.shape[0]):\\n for l in range(self.convolution_matrix.shape[1]):\\n m = (self.x + i + k - 2 + self.image.shape[0]) % self.image.shape[0]\\n n = (self.y + j + l - 2 + self.image.shape[1]) % self.image.shape[1]\\n r += self.convolution_matrix[k][l] * self.image[m, n][2]\\n g += self.convolution_matrix[k][l] * self.image[m, n][1]\\n b += self.convolution_matrix[k][l] * self.image[m, n][0]\\n self.image[self.x, self.y] = (b, g, r)\",\n \"def colorize(image, newColor):\\n image = image.copy()\\n\\n # zero out RGB values\\n image.fill((0, 0, 0, 255), None, pygame.BLEND_RGBA_MULT)\\n # add in new RGB values\\n image.fill(newColor[0:3] + [0,], None, pygame.BLEND_RGBA_ADD)\\n\\n return image\",\n \"def grayscale(img):\\n for pixel in img:\\n x, y, col = pixel\\n r, g, b = col\\n \\n r = (r + g + b)/3\\n r = g = b\\n \\n new_color = create_color(r, g, b)\\n set_color(img, x, y, new_color)\",\n \"def applyJET(img):\\n\\treturn applyColorMap(img, \\\"jet\\\")\",\n \"def solarize(img, threshold):\\n \\n for x, y, col in img:\\n\\n # Invert the values of all RGB components less than 128,\\n # leaving components with higher values unchanged.\\n\\n red, green, blue = col\\n\\n if red < threshold:\\n red = 255 - red\\n\\n if green < threshold:\\n green = 255 - green\\n\\n if blue < threshold:\\n blue = 255 - blue\\n\\n col = create_color(red, green, blue)\\n set_color(img, x, y, col)\",\n \"def reduce_color(image):\\n\\n # http://stackoverflow.com/questions/5906693/how-to-reduce-the-number-of-colors-in-an-image-with-opencv-in-python\\n w, h, _ = image.shape\\n for row in xrange(h-1):\\n for col in xrange(w-1):\\n #pi = row * w * 3 + col * 3\\n pixel = image[col][row]\\n pixel[0] = __reduceColorValue(pixel[0])\\n pixel[1] = __reduceColorValue(pixel[1])\\n pixel[2] = __reduceColorValue(pixel[2])\\n return image\",\n \"def intensity_enhance(self, im):\\n\\n color_factor = self.intensity * self.random.uniform(-0.4, 0.4) + 1\\n contrast_factor = self.intensity * self.random.uniform(-0.5, 0.5) + 1\\n sharpess_factor = self.intensity * self.random.uniform(-0.8, 0.8) + 1\\n bright_factor = self.intensity * self.random.uniform(-0.5, 0.5) + 1\\n self.last_factors = [color_factor, contrast_factor, sharpess_factor, bright_factor]\\n\\n image = Image.fromarray(np.uint8(im * 255))\\n enhancer = ImageEnhance.Color(image)\\n image = enhancer.enhance(color_factor)\\n enhancer = ImageEnhance.Contrast(image)\\n image = enhancer.enhance(contrast_factor)\\n enhancer = ImageEnhance.Sharpness(image)\\n image = enhancer.enhance(sharpess_factor)\\n enhancer = ImageEnhance.Brightness(image)\\n image = enhancer.enhance(bright_factor)\\n\\n return np.asarray(image) / 255.\",\n \"def saturate(image_path, factor=4):\\n BasicTransform.convert_image(image_path)\\n\\n with Image.open(image_path) as img:\\n filter = ImageEnhance.Color(img)\\n new_image = filter.enhance(factor)\\n new_image.save(image_path)\",\n \"def colour_image(self):\\n for row_cnt, colour_row in enumerate(self.table_colour):\\n self.processed = []\\n for column_cnt, colour in enumerate(colour_row):\\n self.row_cnt = row_cnt + 3\\n self.column_cnt = column_cnt\\n self.colour = colour\\n self.word = self.original_rows[self.row_cnt - 3][self.column_cnt]\\n self.colour_specific_word()\",\n \"def enhance_contrast(img):\\n # CLAHE (Contrast Limited Adaptive Histogram Equalization)\\n clahe = cv2.createCLAHE(clipLimit=3., tileGridSize=(8, 8))\\n\\n lab = cv2.cvtColor(img, cv2.COLOR_BGR2LAB) # convert from BGR to LAB color space\\n l, a, b = cv2.split(lab) # split on 3 different channels\\n\\n l2 = clahe.apply(l) # apply CLAHE to the L-channel\\n\\n lab = cv2.merge((l2, a, b)) # merge channels\\n img2 = cv2.cvtColor(lab, cv2.COLOR_LAB2BGR) # convert from LAB to BGR\\n\\n return img2\",\n \"def red_filter(img):\\r\\n #with Image.open(filename) as img:\\r\\n w = img.width\\r\\n h = img.height\\r\\n\\r\\n newimg = Image.new('RGB', (w,h))\\r\\n for y in range(h):\\r\\n for x in range(w):\\r\\n r, g, b = img.getpixel((x,y))\\r\\n \\r\\n newimg.putpixel((x, y), (r, 0, 0))\\r\\n \\r\\n return newimg\",\n \"def img_recolor(self, args, input_image_path):\\n \\n ec = encoder.Encoder(output_path=args.intermediate_representation, method=args.method,\\n size=args.size, p=args.p, grid_size=args.grid_size, plot=args.plot, quantize=args.quantize)\\n dc = decoder.Decoder(output_path=args.output_path, method=args.method, size=args.size, p=args.p, gpu_id=args.gpu_id, plot=args.plot)\\n\\n ec.encode(input_image_path)\\n img_gray_name = ar_utils.gen_new_gray_filename(input_image_path)\\n img_gray_path = os.path.join(args.intermediate_representation, img_gray_name)\\n dc.decode(img_gray_path)\\n\\n if args.delete_gray and os.path.exists(img_gray_path):\\n os.remove(img_gray_path)\",\n \"def check_image_color(image):\\n\\n def check_color(i, j, k):\\n \\\"\\\"\\\" Function used only for DEBUGGING\\\"\\\"\\\"\\n img.show()\\n image = Image.new(\\\"RGB\\\", (200, 200), (int(Y), int(Y), int(Y)))\\n image.show()\\n image = Image.new(\\\"RGB\\\", (200, 200), (int(i), int(j), int(k)))\\n image.show()\\n\\n if not os.path.isfile(image):\\n return \\\"Image not found\\\"\\n\\n def calculate_bgr(data):\\n average_color_per_row = numpy.average(data, axis=0)\\n average_color = numpy.average(average_color_per_row, axis=0)\\n return tuple(average_color)\\n\\n def calculate_y(r, g, b):\\n alpha = 0.299\\n betta = 0.587\\n gamma = 0.114\\n return alpha * r + betta * g + gamma * b\\n\\n # split the image for four squares calucate averate pixel for them and take higest value\\n # blure image and save to /Library/Caches as com.apple.desktop.admin.png\\n # in case using blur tool --> blur = cv2.blur(img,(5,5))\\n try:\\n img_cv_data = cv2.imread(image)\\n B, G, R = calculate_bgr(img_cv_data)\\n Y = calculate_y(B, G, R)\\n height, width = img_cv_data.shape[:2]\\n except Exception as err:\\n print(f\\\"[ERROR] {err} with image: {image}\\\")\\n return \\\"Error parsing image\\\"\\n\\n # image detection\\n if Y < 72.0:\\n _type = \\\"dark\\\"\\n elif Y >= 73.0 and Y <= 108.0:\\n _type = \\\"evening\\\"\\n else:\\n _type = \\\"light\\\"\\n\\n return _type\",\n \"def brighten(image_path, factor=1.5):\\n BasicTransform.darken(image_path, factor)\",\n \"def _apply(self, real=False):\\n pixbuf = self._pixbuf if real else self._pixbuf.copy()\\n # Apply brightness, contrast and saturation\\n pixbuf = image_enhance.enhance_bc(pixbuf, self._manipulations[\\\"bri\\\"],\\n self._manipulations[\\\"con\\\"])\\n pixbuf.saturate_and_pixelate(pixbuf, self._manipulations[\\\"sat\\\"] + 1,\\n False)\\n # Show the edited pixbuf\\n self._app[\\\"image\\\"].set_pixbuf(pixbuf)\\n # Save file if needed\\n if real:\\n save_pixbuf(pixbuf, self._app.get_path())\",\n \"def colorImgPreProcess(self, image):\\n #do processing on the image while it's still in color\\n image = cv2.medianBlur(image, 7) #kernal size must be odd\\n #image = cv2.bilateralFilter(image, 9, 75, 75) #TODO: uncomment when it won't cause C++ errors with ROS\\n #self.closeImages() #uncomment if showing output image\\n return image\",\n \"def one_color(image,color=[0,0,255]):\\r\\n output = image.copy()\\r\\n for line in range(len(image)):\\r\\n for column in range(len(image[0])):\\r\\n distance = calc_distance(color,image[line][column])\\r\\n if distance <=150:\\r\\n output[line][column]=[255,255,255]\\r\\n else:\\r\\n output[line][column]=[0,0,0]\\r\\n return output\",\n \"def color_callback(self, data):\\n cv_image = self.bridge.imgmsg_to_cv2(data, desired_encoding=\\\"passthrough\\\")\\n self.color_mutex.acquire()\\n self.color_image = cv_image\\n self.color_mutex.release()\",\n \"def color_pixels(self, image, color):\\r\\n\\r\\n image[self.ally, self.allx] = color\\r\\n return image\",\n \"def adjust_saturation(img, saturation_factor):\\n check_type(img)\\n\\n enhancer = ImageEnhance.Color(img)\\n img = enhancer.enhance(saturation_factor)\\n return img\",\n \"def __smoothen_color(self, outer, inner):\\n outer_curve = zip(outer[0], outer[1])\\n inner_curve = zip(inner[0], inner[1])\\n x_points = []\\n y_points = []\\n for point in outer_curve:\\n x_points.append(point[0])\\n y_points.append(point[1])\\n for point in inner_curve:\\n x_points.append(point[0])\\n y_points.append(point[1])\\n img_base = np.zeros((self.height, self.width))\\n cv2.fillConvexPoly(img_base, np.array(np.c_[x_points, y_points], dtype='int32'), 1)\\n img_mask = cv2.GaussianBlur(img_base, (81, 81), 0) #51,51\\n img_blur_3d = np.ndarray([self.height, self.width, 3], dtype='float')\\n img_blur_3d[:, :, 0] = img_mask\\n img_blur_3d[:, :, 1] = img_mask\\n img_blur_3d[:, :, 2] = img_mask\\n self.im_copy = (img_blur_3d * self.image * 0.7 + (1 - img_blur_3d * 0.7) * self.im_copy).astype('uint8')\",\n \"def falso_color(img):\\n rows,cols = img.shape\\n img_red = np.copy(img)\\n img_green = np.copy(img)\\n img_blue = np.copy(img)\\n img_false = np.zeros((rows, cols, 3), dtype=np.uint8)\\n\\n for i in range(0,rows):\\n for j in range(0,cols):\\n\\n if (0 <= img[i, j] <= 43):\\n img_red[i, j] = 255\\n img_green[i, j] = img[i, j] * (255 / 43)\\n img_blue[i, j] = 0\\n\\n elif(43 < img[i, j] <= 86):\\n img_red[i, j] = (255 - (img[i, j] - 43) * (255 / 43))\\n img_green[i, j] = 255\\n img_blue[i,j] = 0\\n\\n elif(86 < img[i, j] <= 128):\\n img_red[i, j] = 0\\n img_green[i, j] = 255\\n img_blue[i, j] = ((img[i, j] - 86) * (255 / 42))\\n\\n elif(128<img[i, j]<=171):\\n img_red[i, j] = 0\\n img_green[i, j] = ((171 - img[i, j]) * (255 / 43))\\n img_blue[i, j] = 255\\n\\n elif(171 < img[i, j] <= 214):\\n img_red[i, j] = (img[i, j] - 171) * (255 / 43)\\n img_green[i, j] = 0\\n img_blue[i, j] = 255\\n\\n elif(214 < img[i, j]):\\n img_red[i, j] = 255\\n img_green[i, j] = 0\\n img_blue[i, j] = ((255 - img[i, j]) * (255 / 41))\\n\\n img_false[:, :, 0] = img_red\\n img_false[:, :, 1] = img_green\\n img_false[:, :, 2] = img_blue\\n\\n return img_false\",\n \"def darker(image):\\r\\n # Demonstrate looping over all the pixels of an image,\\r\\n # changing each pixel to be half its original intensity.\\r\\n for pixel in image:\\r\\n pixel.red = pixel.red // 2\\r\\n pixel.green = pixel.green // 2\\r\\n pixel.blue = pixel.blue // 2\",\n \"def augment_brightness(image):\\n rand_brightness = .25 + np.random.uniform()\\n image = cv2.cvtColor(image, cv2.COLOR_RGB2HSV)\\n image[:, :, 2] = image[:, :, 2] * rand_brightness\\n image = cv2.cvtColor(image, cv2.COLOR_HSV2RGB)\\n return image\",\n \"def __add_color(self, intensity):\\n val = color.rgb2lab(\\n (self.image[self.lip_y, self.lip_x] / 255.)\\n .reshape(len(self.lip_y), 1, 3)\\n ).reshape(len(self.lip_y), 3)\\n l_val, a_val, b_val = np.mean(val[:, 0]), np.mean(val[:, 1]), np.mean(val[:, 2])\\n l1_val, a1_val, b1_val = color.rgb2lab(\\n np.array(\\n (self.red_l / 255., self.green_l / 255., self.blue_l / 255.)\\n ).reshape(1, 1, 3)\\n ).reshape(3,)\\n l_final, a_final, b_final = (l1_val - l_val) * \\\\\\n intensity, (a1_val - a_val) * \\\\\\n intensity, (b1_val - b_val) * intensity\\n val[:, 0] = np.clip(val[:, 0] + l_final, 0, 100)\\n val[:, 1] = np.clip(val[:, 1] + a_final, -127, 128)\\n val[:, 2] = np.clip(val[:, 2] + b_final, -127, 128)\\n self.image[self.lip_y, self.lip_x] = color.lab2rgb(val.reshape(\\n len(self.lip_y), 1, 3)).reshape(len(self.lip_y), 3) * 255\",\n \"def negative(img): \\n for pixel in img:\\n x, y, col = pixel \\n r, g, b = col\\n \\n new_color = create_color(255 - r, 255 - g, 255 - b)\\n set_color(img, x, y, new_color)\",\n \"def grayscale(image: Image) -> Image:\\r\\n new_image = copy(image)\\r\\n for x,y,(r,g,b) in image:\\r\\n pix_bright = (r+g+b)//3\\r\\n Gray = create_color(pix_bright,pix_bright,pix_bright)\\r\\n set_color(new_image,x,y,Gray) \\r\\n return new_image\",\n \"def colorize_images(self, img):\\n self.load_model()\\n self.mdn.eval()\\n self.vae.eval()\\n n, _, _ = img.shape\\n img = img.astype(np.float32) / 255\\n img = torch.tensor(img, dtype=torch.float, device=self.device).unsqueeze(1)\\n with torch.no_grad():\\n z = self.mdn(img)\\n ab_out = self.vae.decode(z)\\n lab_out = torch.cat((img, ab_out), dim=1)\\n lab_out = self.unnormalize(lab_out).cpu().numpy()\\n lab_out = np.transpose(lab_out, (0, 2, 3, 1)).astype(np.uint8)\\n for i in range(n):\\n color_out = cv2.cvtColor(lab_out[i], cv2.COLOR_LAB2BGR)\\n color_out = cv2.resize(color_out, (96, 96), interpolation=cv2.INTER_AREA)\\n cv2.imwrite(\\\"../datasets/stl10/divcolor/{}.png\\\".format(str(i)), color_out)\\n return\",\n \"def add_alpha(image_data):\\n\\n # get hsv image\\n hsv = rgb_to_hsv(image_data[:, :, :3].astype(float) / 255)\\n\\n # create new image and set alpha channel\\n new_image_data = np.zeros(image_data.shape)\\n new_image_data[:, :, 3] = hsv[:, :, 2]\\n\\n # set value of hsv image to either 0 or 1.\\n hsv[:, :, 2] = np.where(hsv[:, :, 2] > 0, 1, 0)\\n\\n # combine alpha and new rgb\\n new_image_data[:, :, :3] = hsv_to_rgb(hsv)\\n return new_image_data\",\n \"def apply_color_processing(imgdata, cpopt, flat=False):\\r\\n\\r\\n if cpopt == ColorProcessingOptions.cpColor:\\r\\n if flat:\\r\\n raise ValueError(\\\"Color images can not be represented as a flat image array without color information\\\")\\r\\n return imgdata\\r\\n\\r\\n if cpopt == ColorProcessingOptions.cpRed:\\r\\n flat_imgdata = imgdata[:, :, 0]\\r\\n elif cpopt == ColorProcessingOptions.cpGreen:\\r\\n flat_imgdata = imgdata[:, :, 1]\\r\\n elif cpopt == ColorProcessingOptions.cpBlue:\\r\\n flat_imgdata = imgdata[:, :, 2]\\r\\n elif cpopt == ColorProcessingOptions.cpMonochrome:\\r\\n flat_imgdata = np.array(Image.fromarray(imgdata).convert(\\\"L\\\"))\\r\\n\\r\\n if flat:\\r\\n return flat_imgdata\\r\\n\\r\\n color_index = {\\r\\n ColorProcessingOptions.cpRed: [0],\\r\\n ColorProcessingOptions.cpGreen: [1],\\r\\n ColorProcessingOptions.cpBlue: [2],\\r\\n ColorProcessingOptions.cpMonochrome: [0, 1, 2]\\r\\n }\\r\\n\\r\\n converted_imgdata = np.zeros_like(imgdata)\\r\\n for ci in color_index[cpopt]:\\r\\n converted_imgdata[:, :, ci] = flat_imgdata\\r\\n\\r\\n return converted_imgdata\",\n \"def colors(im=None):\\n if im is None:\\n path = \\\"C:\\\\\\\\Users\\\\\\\\2053_HSUF\\\\\\\\PycharmProjects\\\\\\\\dialtones\\\\\\\\pics\\\\\\\\76aa16c9_playstore.png\\\"\\n im = cv2.imread(path, cv2.IMREAD_GRAYSCALE)\\n for shade in range(13):\\n colorized = cv2.applyColorMap(im, shade)\\n cv2.imshow(\\\"yo\\\", colorized)\\n cv2.waitKey(0)\\n cv2.destroyAllWindows()\",\n \"def __call__(self, img, target):\\n if random.random() < 0.5:\\n img = ImageEnhance.Brightness(img).enhance(0.5 + random.random())\\n if random.random() < 0.5:\\n img = ImageEnhance.Color(img).enhance(0.5 + random.random())\\n if random.random() < 0.5:\\n img = ImageEnhance.Contrast(img).enhance(0.5 + random.random())\\n return img, target\",\n \"def setColors255(self):\\r\\n # productive\\r\\n profprint()\\r\\n self.color255 = [[0, 0, 0] for i in range(MAXCOL)]\\r\\n self.color255[0] = [221, 108, 158]\\r\\n self.color255[1] = [128, 174, 128]\\r\\n self.color255[2] = [241, 214, 145]\\r\\n self.color255[3] = [177, 122, 101]\\r\\n self.color255[4] = [111, 184, 210]\\r\\n self.color255[5] = [216, 101, 79]\\r\\n self.color255[6] = [221, 130, 101]\\r\\n self.color255[7] = [144, 238, 144]\\r\\n self.color255[8] = [192, 104, 88]\\r\\n self.color255[9] = [220, 245, 20]\\r\\n self.color255[10] = [78, 63, 0]\\r\\n self.color255[11] = [255, 250, 220]\\r\\n self.color255[12] = [230, 220, 70]\\r\\n self.color255[13] = [200, 200, 235]\\r\\n self.color255[14] = [250, 250, 210]\\r\\n self.color255[15] = [244, 214, 49]\\r\\n self.color255[16] = [0, 151, 206]\\r\\n self.color255[17] = [183, 156, 220]\\r\\n self.color255[18] = [183, 214, 211]\\r\\n self.color255[19] = [152, 189, 207]\\r\\n self.color255[20] = [178, 212, 242]\\r\\n self.color255[21] = [68, 172, 100]\\r\\n self.color255[22] = [111, 197, 131]\\r\\n self.color255[23] = [85, 188, 255]\\r\\n self.color255[24] = [0, 145, 30]\\r\\n self.color255[25] = [214, 230, 130]\\r\\n self.color255[26] = [218, 255, 255]\\r\\n self.color255[27] = [170, 250, 250]\\r\\n self.color255[28] = [140, 224, 228]\\r\\n self.color255[29] = [188, 65, 28]\\r\\n self.color255[30] = [216, 191, 216]\\r\\n self.color255[31] = [145, 60, 66]\\r\\n self.color255[32] = [150, 98, 83]\\r\\n self.color255[33] = [250, 250, 225]\\r\\n self.color255[34] = [200, 200, 215]\\r\\n self.color255[35] = [68, 131, 98]\\r\\n self.color255[36] = [83, 146, 164]\\r\\n self.color255[37] = [162, 115, 105]\\r\\n self.color255[38] = [141, 93, 137]\\r\\n self.color255[39] = [182, 166, 110]\\r\\n self.color255[40] = [188, 135, 166]\\r\\n self.color255[41] = [154, 150, 201]\\r\\n self.color255[42] = [177, 140, 190]\\r\\n self.color255[43] = [30, 111, 85]\\r\\n self.color255[44] = [210, 157, 166]\\r\\n self.color255[45] = [48, 129, 126]\\r\\n self.color255[46] = [98, 153, 112]\\r\\n self.color255[47] = [69, 110, 53]\\r\\n self.color255[48] = [166, 113, 137]\\r\\n self.color255[49] = [122, 101, 38]\\r\\n self.color255[50] = [253, 135, 192]\\r\\n self.color255[51] = [145, 92, 109]\\r\\n self.color255[52] = [46, 101, 131]\\r\\n self.color255[53] = [0, 108, 112]\\r\\n self.color255[54] = [127, 150, 88]\\r\\n self.color255[55] = [159, 116, 163]\\r\\n self.color255[56] = [125, 102, 154]\\r\\n self.color255[57] = [106, 174, 155]\\r\\n self.color255[58] = [154, 146, 83]\\r\\n self.color255[59] = [126, 126, 55]\\r\\n self.color255[60] = [201, 160, 133]\\r\\n self.color255[61] = [78, 152, 141]\\r\\n self.color255[62] = [174, 140, 103]\\r\\n self.color255[63] = [139, 126, 177]\\r\\n self.color255[64] = [148, 120, 72]\\r\\n self.color255[65] = [186, 135, 135]\\r\\n self.color255[66] = [99, 106, 24]\\r\\n self.color255[67] = [156, 171, 108]\\r\\n self.color255[68] = [64, 123, 147]\\r\\n self.color255[69] = [138, 95, 74]\\r\\n self.color255[70] = [97, 113, 158]\\r\\n self.color255[71] = [126, 161, 197]\\r\\n self.color255[72] = [194, 195, 164]\\r\\n self.color255[73] = [88, 106, 215]\\r\\n self.color255[74] = [82, 174, 128]\\r\\n self.color255[75] = [57, 157, 110]\\r\\n self.color255[76] = [60, 143, 83]\\r\\n self.color255[77] = [92, 162, 109]\\r\\n self.color255[78] = [255, 244, 209]\\r\\n self.color255[79] = [201, 121, 77]\\r\\n self.color255[80] = [70, 163, 117]\\r\\n self.color255[81] = [188, 91, 95]\\r\\n self.color255[82] = [166, 84, 94]\\r\\n self.color255[83] = [182, 105, 107]\\r\\n self.color255[84] = [229, 147, 118]\\r\\n self.color255[85] = [174, 122, 90]\\r\\n self.color255[86] = [201, 112, 73]\\r\\n self.color255[87] = [194, 142, 0]\\r\\n self.color255[88] = [241, 213, 144]\\r\\n self.color255[89] = [203, 179, 77]\\r\\n self.color255[90] = [229, 204, 109]\\r\\n self.color255[91] = [255, 243, 152]\\r\\n self.color255[92] = [209, 185, 85]\\r\\n self.color255[93] = [248, 223, 131]\\r\\n self.color255[94] = [255, 230, 138]\\r\\n self.color255[95] = [196, 172, 68]\\r\\n self.color255[96] = [255, 255, 167]\\r\\n self.color255[97] = [255, 250, 160]\\r\\n self.color255[98] = [255, 237, 145]\\r\\n self.color255[99] = [242, 217, 123]\\r\\n self.color255[100] = [222, 198, 101]\\r\\n self.color255[101] = [213, 124, 109]\\r\\n self.color255[102] = [184, 105, 108]\\r\\n self.color255[103] = [150, 208, 243]\\r\\n self.color255[104] = [62, 162, 114]\\r\\n self.color255[105] = [242, 206, 142]\\r\\n self.color255[106] = [250, 210, 139]\\r\\n self.color255[107] = [255, 255, 207]\\r\\n self.color255[108] = [182, 228, 255]\\r\\n self.color255[109] = [175, 216, 244]\\r\\n self.color255[110] = [197, 165, 145]\\r\\n self.color255[111] = [172, 138, 115]\\r\\n self.color255[112] = [202, 164, 140]\\r\\n self.color255[113] = [224, 186, 162]\\r\\n self.color255[114] = [255, 245, 217]\\r\\n self.color255[115] = [206, 110, 84]\\r\\n self.color255[116] = [210, 115, 89]\\r\\n self.color255[117] = [203, 108, 81]\\r\\n self.color255[118] = [233, 138, 112]\\r\\n self.color255[119] = [195, 100, 73]\\r\\n self.color255[120] = [181, 85, 57]\\r\\n self.color255[121] = [152, 55, 13]\\r\\n self.color255[122] = [159, 63, 27]\\r\\n self.color255[123] = [166, 70, 38]\\r\\n self.color255[124] = [218, 123, 97]\\r\\n self.color255[125] = [225, 130, 104]\\r\\n self.color255[126] = [224, 97, 76]\\r\\n self.color255[127] = [184, 122, 154]\\r\\n self.color255[128] = [211, 171, 143]\\r\\n self.color255[129] = [47, 150, 103]\\r\\n self.color255[130] = [173, 121, 88]\\r\\n self.color255[131] = [188, 95, 76]\\r\\n self.color255[132] = [255, 239, 172]\\r\\n self.color255[133] = [226, 202, 134]\\r\\n self.color255[134] = [253, 232, 158]\\r\\n self.color255[135] = [244, 217, 154]\\r\\n self.color255[136] = [205, 179, 108]\\r\\n self.color255[137] = [186, 124, 161]\\r\\n self.color255[138] = [255, 255, 220]\\r\\n self.color255[139] = [234, 234, 194]\\r\\n self.color255[140] = [204, 142, 178]\\r\\n self.color255[141] = [180, 119, 153]\\r\\n self.color255[142] = [216, 132, 105]\\r\\n self.color255[143] = [255, 253, 229]\\r\\n self.color255[144] = [205, 167, 142]\\r\\n self.color255[145] = [204, 168, 143]\\r\\n self.color255[146] = [255, 224, 199]\\r\\n self.color255[147] = [139, 150, 98]\\r\\n self.color255[148] = [249, 180, 111]\\r\\n self.color255[149] = [157, 108, 162]\\r\\n self.color255[150] = [203, 136, 116]\\r\\n self.color255[151] = [185, 102, 83]\\r\\n self.color255[152] = [247, 182, 164]\\r\\n self.color255[153] = [222, 154, 132]\\r\\n self.color255[154] = [124, 186, 223]\\r\\n self.color255[155] = [249, 186, 150]\\r\\n self.color255[156] = [244, 170, 147]\\r\\n self.color255[157] = [255, 181, 158]\\r\\n self.color255[158] = [255, 190, 165]\\r\\n self.color255[159] = [227, 153, 130]\\r\\n self.color255[160] = [213, 141, 113]\\r\\n self.color255[161] = [193, 123, 103]\\r\\n self.color255[162] = [216, 146, 127]\\r\\n self.color255[163] = [230, 158, 140]\\r\\n self.color255[164] = [245, 172, 147]\\r\\n self.color255[165] = [241, 172, 151]\\r\\n self.color255[166] = [177, 124, 92]\\r\\n self.color255[167] = [171, 85, 68]\\r\\n self.color255[168] = [217, 198, 131]\\r\\n self.color255[169] = [212, 188, 102]\\r\\n self.color255[170] = [185, 135, 134]\\r\\n self.color255[171] = [198, 175, 125]\\r\\n self.color255[172] = [194, 98, 79]\\r\\n self.color255[173] = [255, 238, 170]\\r\\n self.color255[174] = [206, 111, 93]\\r\\n self.color255[175] = [216, 186, 0]\\r\\n self.color255[176] = [255, 226, 77]\\r\\n self.color255[177] = [255, 243, 106]\\r\\n self.color255[178] = [255, 234, 92]\\r\\n self.color255[179] = [240, 210, 35]\\r\\n self.color255[180] = [224, 194, 0]\\r\\n self.color255[181] = [213, 99, 79]\\r\\n self.color255[182] = [217, 102, 81]\\r\\n self.color255[183] = [0, 147, 202]\\r\\n self.color255[184] = [0, 122, 171]\\r\\n self.color255[185] = [186, 77, 64]\\r\\n self.color255[186] = [240, 255, 30]\\r\\n self.color255[187] = [185, 232, 61]\\r\\n self.color255[188] = [0, 226, 255]\\r\\n self.color255[189] = [251, 159, 255]\\r\\n self.color255[190] = [230, 169, 29]\\r\\n self.color255[191] = [0, 194, 113]\\r\\n self.color255[192] = [104, 160, 249]\\r\\n self.color255[193] = [221, 108, 158]\\r\\n self.color255[194] = [137, 142, 0]\\r\\n self.color255[195] = [230, 70, 0]\\r\\n self.color255[196] = [0, 147, 0]\\r\\n self.color255[197] = [0, 147, 248]\\r\\n self.color255[198] = [231, 0, 206]\\r\\n self.color255[199] = [129, 78, 0]\\r\\n self.color255[200] = [0, 116, 0]\\r\\n self.color255[201] = [0, 0, 255]\\r\\n self.color255[202] = [157, 0, 0]\\r\\n self.color255[203] = [100, 100, 130]\\r\\n self.color255[204] = [205, 205, 100]\\r\\n self.color255[205] = [255, 255, 0]\\r\\n\\r\\n return self.color255\",\n \"def ColorJitterAug(img, brightness, contrast, saturation):\\n coef = np.array([[[0.299, 0.587, 0.114]]])\\n if brightness > 0:\\n \\\"\\\"\\\"Augumenter body\\\"\\\"\\\"\\n alpha = 1.0 + random.uniform(-brightness, brightness) * 0.7\\n img *= alpha\\n img = np.clip(img, 0.,255.)\\n\\n if contrast > 0:\\n \\\"\\\"\\\"Augumenter body\\\"\\\"\\\"\\n alpha = 1.0 + random.uniform(-contrast, contrast) * 0.7\\n gray = img*coef\\n gray = (3.0*(1.0-alpha)/gray.size)*np.sum(gray)\\n img *= alpha\\n img += gray\\n img = np.clip(img, 0.,255.)\\n\\n if saturation > 0:\\n \\\"\\\"\\\"Augumenter body\\\"\\\"\\\"\\n alpha = 1.0 + random.uniform(-saturation, saturation) * 0.7\\n gray = img*coef\\n gray = np.sum(gray, axis=2, keepdims=True)\\n gray *= (1.0-alpha)\\n img *= alpha\\n img += gray\\n img = np.clip(img, 0.,255.)\\n return img\",\n \"def recolorRC(src,dst):\\n b,g,r=cv2.split(src)\\n cv2.addWeighted(b,0.5,g,0.5,0,b) #arguements(in order):first src array,a weight applied\\n # to array, scnd src array, a weight applied to array\\n # a constant added to the result and a destination array\\n cv2.merge((b,b,r),dest) #replace b and g with modified b(which has both and g)\",\n \"def enhance_edges(image):\\n working_image = image.copy()\\n working_image = cv2.cvtColor(working_image, cv2.COLOR_BGR2GRAY)\\n # Blur away fine details.\\n working_image = cv2.GaussianBlur(working_image, (5, 5), 0)\\n return working_image\",\n \"def intensityPSF_Blues(N=1000):\\n col_seq = [( 0/255., 20/255., 80/255.), ( 8/255., 48/255., 107/255.),\\n ( 8/255., 81/255., 156/255.), ( 33/255., 113/255., 181/255.),\\n ( 66/255., 146/255., 198/255.), (107/255., 174/255., 214/255.),\\n (158/255., 202/255., 225/255.), (198/255., 219/255., 239/255.),\\n (222/255., 235/255., 247/255.), (247/255., 251/255., 255/255.)]\\n\\n cdict = {'red': ((0.00, col_seq[0][0], col_seq[0][0]),\\n (0.02, col_seq[1][0], col_seq[1][0]),\\n (0.06, col_seq[2][0], col_seq[2][0]),\\n (0.10, col_seq[3][0], col_seq[3][0]),\\n (0.20, col_seq[4][0], col_seq[4][0]),\\n (0.30, col_seq[5][0], col_seq[5][0]),\\n (0.50, col_seq[6][0], col_seq[6][0]),\\n (0.75, col_seq[7][0], col_seq[7][0]),\\n (0.90, col_seq[8][0], col_seq[8][0]),\\n (1.00, col_seq[9][0], col_seq[9][0])),\\n 'green': ((0.00, col_seq[0][1], col_seq[0][1]),\\n (0.02, col_seq[1][1], col_seq[1][1]),\\n (0.06, col_seq[2][1], col_seq[2][1]),\\n (0.10, col_seq[3][1], col_seq[3][1]),\\n (0.20, col_seq[4][1], col_seq[4][1]),\\n (0.30, col_seq[5][1], col_seq[5][1]),\\n (0.50, col_seq[6][1], col_seq[6][1]),\\n (0.75, col_seq[7][1], col_seq[7][1]),\\n (0.90, col_seq[8][1], col_seq[8][1]),\\n (1.00, col_seq[9][1], col_seq[9][1])),\\n 'blue': ((0.00, col_seq[0][2], col_seq[0][2]),\\n (0.02, col_seq[1][2], col_seq[1][2]),\\n (0.06, col_seq[2][2], col_seq[2][2]),\\n (0.10, col_seq[3][2], col_seq[3][2]),\\n (0.20, col_seq[4][2], col_seq[4][2]),\\n (0.30, col_seq[5][2], col_seq[5][2]),\\n (0.50, col_seq[6][2], col_seq[6][2]),\\n (0.75, col_seq[7][2], col_seq[7][2]),\\n (0.90, col_seq[8][2], col_seq[8][2]),\\n (1.00, col_seq[9][2], col_seq[9][2]))}\\n\\n psfblues = _mplb.colors.LinearSegmentedColormap('psfblues', cdict, N)\\n return psfblues\",\n \"def darken(image_path, factor=0.5):\\n BasicTransform.convert_image(image_path)\\n\\n with Image.open(image_path) as img:\\n filter = ImageEnhance.Brightness(img)\\n new_image = filter.enhance(factor)\\n new_image.save(image_path)\",\n \"def applyHSV(img):\\n\\treturn applyColorMap(img, \\\"hsv\\\")\",\n \"def calibrate_image(image, tl = 0.5):\\n for y in range(len(image)):\\n for x in range(len(image[y])):\\n # Convert the exiting pixel color to HLS model.\\n h, l, s = rgb_to_hls(image[y, x])\\n\\n # We convert the HLS model back to RGB, but using our target \\n # brightness value `tl`.\\n r, g, b = colorsys.hls_to_rgb(h, tl, s)\\n \\n # Set the new pixel color.\\n image[y][x] = [r * 255, g * 255, b * 255]\\n\\n return image\",\n \"def change_Shield_Color (im, newcolor, GRAPHICSMODE=\\\"PIL\\\"):\\r\\n DEBUG = 0\\r\\n #DEBUG = 1\\r\\n\\r\\n if DEBUG == 1:\\r\\n print \\\"newcolor:\\\", newcolor\\r\\n print \\\"im:\\\", im\\r\\n \\r\\n THRESHOLD = 225 # Doesn't rely on colour being exactly 255,255,255\\r\\n\\r\\n if GRAPHICSMODE == \\\"PIL\\\":\\r\\n im.convert(\\\"RGBA\\\")\\r\\n newimdata = []\\r\\n for color in im.getdata():\\r\\n if color[0] > THRESHOLD:\\r\\n if color[1] > THRESHOLD:\\r\\n if color[2] > THRESHOLD:\\r\\n if color[3] > THRESHOLD:\\r\\n newimdata.append(newcolor)\\r\\n else:\\r\\n newimdata.append(color)\\r\\n else:\\r\\n newimdata.append(color)\\r\\n else:\\r\\n newimdata.append(color)\\r\\n else:\\r\\n newimdata.append(color)\\r\\n #print\\r\\n newim = PilImage.new(\\\"RGBA\\\",im.size)\\r\\n newim.putdata(newimdata)\\r\\n\\r\\n elif GRAPHICSMODE == \\\"PyGame\\\":\\r\\n im.convert()\\r\\n if DEBUG == 1:\\r\\n print \\\"newcolor:\\\", newcolor\\r\\n newcolor = pygame.Color(newcolor[0], newcolor[1], newcolor[2], 255) # why the HELL does pygame reverse RBG -> GBR???\\r\\n\\r\\n if DEBUG == 1:\\r\\n print \\\"newcolor(converted):\\\", newcolor\\r\\n newim = pygame.Surface((im.get_width(),im.get_height()), pygame.SRCALPHA, 32) #change its background color \\r\\n\\r\\n tochange = pygame.Color(THRESHOLD, THRESHOLD, THRESHOLD,255) # or whatever yellow color you want\\r\\n\\r\\n thresh = (20, 20, 20, 20) # or whatever threshold works\\r\\n\\r\\n if DEBUG == 1:\\r\\n print \\\"newim:\\\",newim \\r\\n print \\\"type(newim):\\\",type(newim)\\r\\n print \\\"im:\\\",im\\r\\n print \\\"type(im):\\\",type(im)\\r\\n print \\\"tochange:\\\",tochange\\r\\n print \\\"thresh:\\\",thresh\\r\\n print \\\"newcolor:\\\",newcolor\\r\\n\\r\\n pygame.Surface.lock(im)\\r\\n\\r\\n for imx in range(0, im.get_width()):\\r\\n for imy in range(0, im.get_height()):\\r\\n color = im.get_at((imx,imy))\\r\\n if color[0] > THRESHOLD:\\r\\n if color[1] > THRESHOLD:\\r\\n if color[2] > THRESHOLD:\\r\\n if color[3] > THRESHOLD:\\r\\n newim.set_at((imx,imy), newcolor)\\r\\n else:\\r\\n newim.set_at((imx,imy), color)\\r\\n else:\\r\\n newim.set_at((imx,imy), color)\\r\\n else:\\r\\n newim.set_at((imx,imy), color)\\r\\n else:\\r\\n newim.set_at((imx,imy), color)\\r\\n\\r\\n if DEBUG == 1:\\r\\n if os.path.isfile(\\\"E:\\\\\\\\Projects\\\\\\\\NEW RENPY GAME\\\\\\\\TEMP\\\\\\\\TESTFILE_OLD.png\\\"):\\r\\n os.remove(\\\"E:\\\\\\\\Projects\\\\\\\\NEW RENPY GAME\\\\\\\\TEMP\\\\\\\\TESTFILE_OLD.png\\\")\\r\\n if os.path.isfile(\\\"E:\\\\\\\\Projects\\\\\\\\NEW RENPY GAME\\\\\\\\TEMP\\\\\\\\TESTFILE.png\\\"):\\r\\n os.rename(\\\"E:\\\\\\\\Projects\\\\\\\\NEW RENPY GAME\\\\\\\\TEMP\\\\\\\\TESTFILE.png\\\", \\\"E:\\\\\\\\Projects\\\\\\\\NEW RENPY GAME\\\\\\\\TEMP\\\\\\\\TESTFILE_OLD.png\\\")\\r\\n pygame.image.save(newim, \\\"E:\\\\\\\\Projects\\\\\\\\NEW RENPY GAME\\\\\\\\TEMP\\\\\\\\TESTFILE.png\\\")\\r\\n print \\\"wrote file 'E:\\\\\\\\Projects\\\\\\\\NEW RENPY GAME\\\\\\\\TEMP\\\\\\\\TESTFILE.png'\\\"\\r\\n print\\r\\n\\r\\n pygame.Surface.unlock(im)\\r\\n\\r\\n return newim\",\n \"def adjust(im, col, startcol=None):\\n\\tif startcol is None:\\n\\t\\tstartcol = meancol(im)\\n\\trband, gband, bband = im.split()\\n\\trbri, gbri, bbri = ImageEnhance.Brightness(rband), ImageEnhance.Brightness(gband), ImageEnhance.Brightness(bband)\\n\\trband = rbri.enhance((float(col[0]) / float(startcol[0])))\\n\\tgband = gbri.enhance((float(col[1]) / float(startcol[1])))\\n\\tbband = bbri.enhance((float(col[2]) / float(startcol[2])))\\n\\tim = Image.merge(\\\"RGB\\\",(rband, gband, bband))\\n\\treturn im\",\n \"def do_reduce_colors(img: Image.Image,\\n max_colors: int) -> Tuple[Image.Image, int, int]:\\n orig_mode = img.mode\\n\\n if orig_mode == \\\"1\\\":\\n return img, 2, 2\\n\\n colors = img.getcolors()\\n if colors:\\n orig_colors = len(colors)\\n else:\\n orig_colors = 0\\n\\n # Intermediate conversion steps when needed\\n if orig_mode in [\\\"CMYK\\\", \\\"YCbCr\\\", \\\"LAB\\\", \\\"HSV\\\"]:\\n img = img.convert(\\\"RGB\\\")\\n elif orig_mode == \\\"LA\\\":\\n img = img.convert(\\\"RGBA\\\")\\n\\n # Actual color reduction happening here\\n if orig_mode in [\\\"RGB\\\", \\\"L\\\"]:\\n palette = Image.ADAPTIVE\\n elif orig_mode == \\\"RGBA\\\":\\n palette = Image.ADAPTIVE\\n transparent = Image.new(\\\"RGBA\\\", img.size, (0, 0, 0, 0))\\n # blend with transparent image using own alpha\\n img = Image.composite(img, transparent, img)\\n elif orig_mode == \\\"P\\\":\\n palette = img.getpalette()\\n img = img.convert(\\\"RGBA\\\")\\n width, height = img.size\\n alpha_layer = Image.new(\\\"L\\\", img.size)\\n for x in range(width):\\n for y in range(height):\\n _, _, _, alpha = img.getpixel((x, y))\\n alpha_layer.putpixel((x, y), alpha)\\n img.putalpha(alpha_layer)\\n else:\\n return img, 0, 0\\n\\n img = img.convert(\\\"P\\\", palette=palette, colors=max_colors)\\n return img, orig_colors, len(img.getcolors())\",\n \"def posterize(picture: Image) -> Image:\\r\\n new_pic = copy(picture)\\r\\n red = 0\\r\\n green = 0\\r\\n blue = 0\\r\\n for x, y, (r, g, b) in picture:\\r\\n red = _adjust_component(r)\\r\\n green = _adjust_component(g)\\r\\n blue = _adjust_component(b)\\r\\n new_colour = Color(red,green,blue)\\r\\n set_color(new_pic, x, y, new_colour)\\r\\n return new_pic\",\n \"def Contrast(img):\\r\\n factor = 2 * (np.random.rand() - 0.5) * 128\\r\\n assert (factor <= 128 and factor >= -128), 'contract factor value wrong'\\r\\n fvalue = 259.0/255.0 * (factor + 255.0)/(259.0-factor)\\r\\n img = np.round((img - 128.0)*fvalue + 128.0)\\r\\n img = np.where(img > 255, 255, img)\\r\\n img = np.where(img < 0, 0, img)\\r\\n img = np.uint8(img)\\r\\n return img\",\n \"def stain_image(image, num_stains, color):\",\n \"def IncreaseContrast(self, image, percentage):\\n # copyImage = [ [0...0][0...0][0...0][0...0]]\\n # copyImage = np.zeros(image.shape, image.dtype) # dtype is the data type ex:int\\n # newImg = loop x,y,c (old_image) * a + b\\n\\n a = 1.5 # [1.0..3.0] Responsible for Contrast #TODO GET PARAMS\\n b = 35 # [0.. 100] Responsible for Brightness #TODO GET PARAMS\\n newImg = cv2.convertScaleAbs(image, alpha=a, beta=b)\\n return newImg\",\n \"def exercise2a(self):\\n colors = [\\n [253, 253, 150],\\n [255, 125, 125],\\n [150, 111, 214],\\n [119, 158, 203],\\n [255, 105, 97],\\n [ 3, 192, 60]\\n ]\\n # This takes some time …\\n #self.b1 = mandelbrot(1200, 600, colors, [0, 0, 0], 0.02, 0.73, 0.21)\\n # Load the pregenerated image ;)\\n self.b1 = misc.imread(\\\"B1.png\\\")\\n plt.axis('off')\\n plt.imshow(self.b1)\\n plt.show()\\n misc.imsave(\\\"B1.png\\\", self.b1)\\n misc.imsave(\\\"B1_Brightness.png\\\", print_brightness(self.b1))\",\n \"def augment(self, image):\\n\\n contrast = ImageEnhance.Contrast(image)\\n return contrast.enhance(self._contrast)\",\n \"def colourise_image(self, folder_name):\\n colourised_folder_name = folder_name + '_colourised'\\n\\n try:\\n print(\\\"Making dir \\\" + str(colourised_folder_name) + \\\" for colourisation\\\")\\n os.mkdir(colourised_folder_name)\\n except OSError:\\n print(\\\"Folder exists, have you already done this colourisation??\\\")\\n return\\n\\n print(\\\"Writing to folder +\\\" + str(colourised_folder_name))\\n photo_list = self.get_photo_list(folder_name)\\n for i, name in enumerate(photo_list):\\n file_name = folder_name + '/' + name\\n colourised_image_name = colourised_folder_name + '/' + name\\n image = cv2.imread(file_name, cv2.IMREAD_GRAYSCALE)\\n image_8bit = image.astype(np.uint8)\\n colour_image = cv2.applyColorMap(image_8bit, cv2.COLORMAP_JET)\\n cv2.imwrite(colourised_image_name, colour_image)\",\n \"def Color(img: Image, magnitude: float) -> Image:\\n return PIL.ImageEnhance.Color(img).enhance(1 + magnitude * random.choice([-1, 1]))\",\n \"def _process_img_rgb(self, sensor_data):\\n img = np.array(sensor_data.raw_data).reshape((self.img_y, self.img_x, 4))\\n img = img[:, :, :3] # sensor is actualy rgba, we dont need alpha values\\n self.rgb = img # need to scale rgb values to be {0,1}\",\n \"def change_color(icon, color):\\n img = icon.convert(\\\"LA\\\")\\n img = img.convert(\\\"RGBA\\\")\\n image_np = np.array(icon)\\n _, _, _, alpha = image_np.T\\n mask = alpha > 0\\n image_np[..., :-1][mask.T] = ImageColor.getcolor(color, \\\"RGB\\\")\\n edited_image = Image.fromarray(image_np)\\n return edited_image\",\n \"def setColors255(self):\\n #productive\\n profprint()\\n self.color255= [[0,0,0] for i in range(205)]\\n self.color255[0]=[221,108,158]\\n self.color255[1]=[128,174,128]\\n self.color255[2]=[241,214,145]\\n self.color255[3]=[177,122,101]\\n self.color255[4]=[111,184,210]\\n self.color255[5]=[216,101,79]\\n self.color255[6]=[221,130,101]\\n self.color255[7]=[144,238,144]\\n self.color255[8]=[192,104,88]\\n self.color255[9]=[220,245,20]\\n self.color255[10]=[78,63,0]\\n self.color255[11]=[255,250,220]\\n self.color255[12]=[230,220,70]\\n self.color255[13]=[200,200,235]\\n self.color255[14]=[250,250,210]\\n self.color255[15]=[244,214,49]\\n self.color255[16]=[0,151,206]\\n self.color255[17]=[183,156,220]\\n self.color255[18]=[183,214,211]\\n self.color255[19]=[152,189,207]\\n self.color255[20]=[178,212,242]\\n self.color255[21]=[68,172,100]\\n self.color255[22]=[111,197,131]\\n self.color255[23]=[85,188,255]\\n self.color255[24]=[0,145,30]\\n self.color255[25]=[214,230,130]\\n self.color255[26]=[218,255,255]\\n self.color255[27]=[170,250,250]\\n self.color255[28]=[140,224,228]\\n self.color255[29]=[188,65,28]\\n self.color255[30]=[216,191,216]\\n self.color255[31]=[145,60,66]\\n self.color255[32]=[150,98,83]\\n self.color255[33]=[250,250,225]\\n self.color255[34]=[200,200,215]\\n self.color255[35]=[68,131,98]\\n self.color255[36]=[83,146,164]\\n self.color255[37]=[162,115,105]\\n self.color255[38]=[141,93,137]\\n self.color255[39]=[182,166,110]\\n self.color255[40]=[188,135,166]\\n self.color255[41]=[154,150,201]\\n self.color255[42]=[177,140,190]\\n self.color255[43]=[30,111,85]\\n self.color255[44]=[210,157,166]\\n self.color255[45]=[48,129,126]\\n self.color255[46]=[98,153,112]\\n self.color255[47]=[69,110,53]\\n self.color255[48]=[166,113,137]\\n self.color255[49]=[122,101,38]\\n self.color255[50]=[253,135,192]\\n self.color255[51]=[145,92,109]\\n self.color255[52]=[46,101,131]\\n self.color255[53]=[0,108,112]\\n self.color255[54]=[127,150,88]\\n self.color255[55]=[159,116,163]\\n self.color255[56]=[125,102,154]\\n self.color255[57]=[106,174,155]\\n self.color255[58]=[154,146,83]\\n self.color255[59]=[126,126,55]\\n self.color255[60]=[201,160,133]\\n self.color255[61]=[78,152,141]\\n self.color255[62]=[174,140,103]\\n self.color255[63]=[139,126,177]\\n self.color255[64]=[148,120,72]\\n self.color255[65]=[186,135,135]\\n self.color255[66]=[99,106,24]\\n self.color255[67]=[156,171,108]\\n self.color255[68]=[64,123,147]\\n self.color255[69]=[138,95,74]\\n self.color255[70]=[97,113,158]\\n self.color255[71]=[126,161,197]\\n self.color255[72]=[194,195,164]\\n self.color255[73]=[88,106,215]\\n self.color255[74]=[82,174,128]\\n self.color255[75]=[57,157,110]\\n self.color255[76]=[60,143,83]\\n self.color255[77]=[92,162,109]\\n self.color255[78]=[255,244,209]\\n self.color255[79]=[201,121,77]\\n self.color255[80]=[70,163,117]\\n self.color255[81]=[188,91,95]\\n self.color255[82]=[166,84,94]\\n self.color255[83]=[182,105,107]\\n self.color255[84]=[229,147,118]\\n self.color255[85]=[174,122,90]\\n self.color255[86]=[201,112,73]\\n self.color255[87]=[194,142,0]\\n self.color255[88]=[241,213,144]\\n self.color255[89]=[203,179,77]\\n self.color255[90]=[229,204,109]\\n self.color255[91]=[255,243,152]\\n self.color255[92]=[209,185,85]\\n self.color255[93]=[248,223,131]\\n self.color255[94]=[255,230,138]\\n self.color255[95]=[196,172,68]\\n self.color255[96]=[255,255,167]\\n self.color255[97]=[255,250,160]\\n self.color255[98]=[255,237,145]\\n self.color255[99]=[242,217,123]\\n self.color255[100]=[222,198,101]\\n self.color255[101]=[213,124,109]\\n self.color255[102]=[184,105,108]\\n self.color255[103]=[150,208,243]\\n self.color255[104]=[62,162,114]\\n self.color255[105]=[242,206,142]\\n self.color255[106]=[250,210,139]\\n self.color255[107]=[255,255,207]\\n self.color255[108]=[182,228,255]\\n self.color255[109]=[175,216,244]\\n self.color255[110]=[197,165,145]\\n self.color255[111]=[172,138,115]\\n self.color255[112]=[202,164,140]\\n self.color255[113]=[224,186,162]\\n self.color255[114]=[255,245,217]\\n self.color255[115]=[206,110,84]\\n self.color255[116]=[210,115,89]\\n self.color255[117]=[203,108,81]\\n self.color255[118]=[233,138,112]\\n self.color255[119]=[195,100,73]\\n self.color255[120]=[181,85,57]\\n self.color255[121]=[152,55,13]\\n self.color255[122]=[159,63,27]\\n self.color255[123]=[166,70,38]\\n self.color255[124]=[218,123,97]\\n self.color255[125]=[225,130,104]\\n self.color255[126]=[224,97,76]\\n self.color255[127]=[184,122,154]\\n self.color255[128]=[211,171,143]\\n self.color255[129]=[47,150,103]\\n self.color255[130]=[173,121,88]\\n self.color255[131]=[188,95,76]\\n self.color255[132]=[255,239,172]\\n self.color255[133]=[226,202,134]\\n self.color255[134]=[253,232,158]\\n self.color255[135]=[244,217,154]\\n self.color255[136]=[205,179,108]\\n self.color255[137]=[186,124,161]\\n self.color255[138]=[255,255,220]\\n self.color255[139]=[234,234,194]\\n self.color255[140]=[204,142,178]\\n self.color255[141]=[180,119,153]\\n self.color255[142]=[216,132,105]\\n self.color255[143]=[255,253,229]\\n self.color255[144]=[205,167,142]\\n self.color255[145]=[204,168,143]\\n self.color255[146]=[255,224,199]\\n self.color255[147]=[139,150,98]\\n self.color255[148]=[249,180,111]\\n self.color255[149]=[157,108,162]\\n self.color255[150]=[203,136,116]\\n self.color255[151]=[185,102,83]\\n self.color255[152]=[247,182,164]\\n self.color255[153]=[222,154,132]\\n self.color255[154]=[124,186,223]\\n self.color255[155]=[249,186,150]\\n self.color255[156]=[244,170,147]\\n self.color255[157]=[255,181,158]\\n self.color255[158]=[255,190,165]\\n self.color255[159]=[227,153,130]\\n self.color255[160]=[213,141,113]\\n self.color255[161]=[193,123,103]\\n self.color255[162]=[216,146,127]\\n self.color255[163]=[230,158,140]\\n self.color255[164]=[245,172,147]\\n self.color255[165]=[241,172,151]\\n self.color255[166]=[177,124,92]\\n self.color255[167]=[171,85,68]\\n self.color255[168]=[217,198,131]\\n self.color255[169]=[212,188,102]\\n self.color255[170]=[185,135,134]\\n self.color255[171]=[198,175,125]\\n self.color255[172]=[194,98,79]\\n self.color255[173]=[255,238,170]\\n self.color255[174]=[206,111,93]\\n self.color255[175]=[216,186,0]\\n self.color255[176]=[255,226,77]\\n self.color255[177]=[255,243,106]\\n self.color255[178]=[255,234,92]\\n self.color255[179]=[240,210,35]\\n self.color255[180]=[224,194,0]\\n self.color255[181]=[213,99,79]\\n self.color255[182]=[217,102,81]\\n self.color255[183]=[0,147,202]\\n self.color255[184]=[0,122,171]\\n self.color255[185]=[186,77,64]\\n self.color255[186]=[240,255,30]\\n self.color255[187]=[185,232,61]\\n self.color255[188]=[0,226,255]\\n self.color255[189]=[251,159,255]\\n self.color255[190]=[230,169,29]\\n self.color255[191]=[0,194,113]\\n self.color255[192]=[104,160,249]\\n self.color255[193]=[221,108,158]\\n self.color255[194]=[137,142,0]\\n self.color255[195]=[230,70,0]\\n self.color255[196]=[0,147,0]\\n self.color255[197]=[0,147,248]\\n self.color255[198]=[231,0,206]\\n self.color255[199]=[129,78,0]\\n self.color255[200]=[0,116,0]\\n self.color255[201]=[0,0,255]\\n self.color255[202]=[157,0,0]\\n self.color255[203]=[100,100,130]\\n self.color255[204]=[205,205,100]\\n \\n return self.color255\",\n \"def changeColor(self):\\n self.layer.new_colormap()\",\n \"def color_filter(self, image):\\n converted = hls_scale(image)\\n\\n # white color mask\\n white_lower_bnd, white_upper_bnd = self.color_filter_params[\\\"white_bounds\\\"]\\n white_mask = cv2.inRange(converted, white_lower_bnd, white_upper_bnd)\\n\\n # yellow color mask\\n yellow_lower_bnd, yellow_upper_bnd = self.color_filter_params[\\\"yellow_bounds\\\"]\\n yellow_mask = cv2.inRange(converted, yellow_lower_bnd, yellow_upper_bnd)\\n\\n # combine the mask\\n mask = cv2.bitwise_or(white_mask, yellow_mask)\\n\\n return cv2.bitwise_and(image, image, mask=mask)\",\n \"def apply_image_function(\\n self,\\n image_function: Callable[[int, int, int, int], Tuple4IntType]\\n ) -> 'BaseImage':\\n w, h = self._surface.get_size()\\n for x in range(w):\\n for y in range(h):\\n r, g, b, a = self._surface.get_at((x, y))\\n r, g, b, a = image_function(r, g, b, a)\\n r = int(max(0, min(r, 255)))\\n g = int(max(0, min(g, 255)))\\n b = int(max(0, min(b, 255)))\\n a = int(max(0, min(a, 255)))\\n # noinspection PyArgumentList\\n self.set_at((x, y), pygame.Color(r, g, b, a))\\n return self\",\n \"def smooth_image(img_file=\\\"cy_double.png\\\"):\\n \\n oldimg, newimg, width, height, win = setup_image(img_file)\\n\\n for col in range(newimg.getWidth()):\\n for row in range(newimg.getHeight()):\\n p = newimg.getPixel(col, row)\\n neighbors = []\\n # Put the 8 surrounding pixels into neighbors\\n for i in range(col-1, col+2):\\n for j in range(row-1, row+2):\\n try:\\n neighbor = newimg.getPixel(i, j)\\n neighbors.append(neighbor)\\n except:\\n continue\\n nlen = len(neighbors)\\n # Average out the RBG values\\n if nlen:\\n # Uncommented, the following line would leave most of the white \\n # untouched which works a little better for real photographs, imo.\\n #~ if nlen and p[0]+p[1]+p[2] < 690:\\n p.red = sum([neighbors[i][0] for i in range(nlen)])/nlen\\n p.green = sum([neighbors[i][1] for i in range(nlen)])/nlen\\n p.blue = sum([neighbors[i][2] for i in range(nlen)])/nlen\\n newimg.setPixel(col,row,p)\\n\\n write_image(img_file, newimg, win, \\\"_smooth\\\")\",\n \"def apply_mask(image, mask, color, alpha=0.5):\\n for c in range(3):\\n image[:, :, c] = np.where(mask == 1,\\n image[:, :, c] *\\n (1 - alpha) + alpha * color[c] * 255,\\n image[:, :, c])\\n # cv2.imshow(\\\"TEST\\\",image.astype(np.uint8))\\n # print(color)\\n return image\",\n \"def image_local_enhance_contrast(image: np.ndarray):\\n \\n # Resize image to a shape of (48, 48)\\n image = image_as_square(image)\\n\\n image = filters.rank.enhance_contrast(image, morphology.disk(2))\\n\\n # Resize the iamge back to a shape of (2304, )\\n return image_as_array(image)\",\n \"def adjustContrast(img, fac):\\n img2 = np.float32(img)\\n mean = round(cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY).mean())\\n img2 = (1 - fac) * mean + fac * img2\\n img2 = np.uint8(img2.clip(min=0, max=255))\\n return img2\",\n \"def enhance_brightness(self, delta, p=None):\\n if self._max_aug_nums>0:\\n if self._nums>self._max_aug_nums:\\n return self\\n self._nums += 1\\n if p is None:\\n p = self._p\\n self.image = enhance_brightness(self.image, delta, p)\\n return self\",\n \"def enhance(self, image):\\n\\n if self.random.uniform(0, 1) < self.p:\\n return self.intensity_enhance(image)\\n else:\\n return image\",\n \"def preprocess_image(img):\\r\\n\\r\\n hsvImg = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)\\r\\n\\r\\n hsvImg[...,1] = hsvImg[...,1]*1.75 #increase saturation by 175%\\r\\n\\r\\n image_f =cv2.cvtColor(hsvImg,cv2.COLOR_HSV2BGR)\\r\\n\\r\\n return image_f\",\n \"def enhanceContrast(image, mask, target_path, name, save=False):\\n \\n\\n \\n # Contrast stretching\\n p2, p98 = np.percentile(image, (2, 98))\\n image_rescale = exposure.rescale_intensity(image, in_range=(p2, p98))\\n \\n # Equalization\\n image_eq = exposure.equalize_hist(image)\\n \\n # Adaptive Equalization\\n image_adapteq = exposure.equalize_adapthist(image, clip_limit=0.03)\\n \\n # Display results\\n fig = plt.figure(figsize=(19, 13))\\n axes = np.zeros((2, 4), dtype=np.object)\\n axes[0, 0] = fig.add_subplot(2, 4, 1)\\n for i in range(1, 4):\\n axes[0, i] = fig.add_subplot(2, 4, 1+i, sharex=axes[0,0], sharey=axes[0,0])\\n for i in range(0, 4):\\n axes[1, i] = fig.add_subplot(2, 4, 5+i)\\n \\n ax_image, ax_hist, ax_cdf = plot_image_and_hist(image, mask, mask_cmap, img_cmap,\\n axes[:, 0])\\n ax_image.set_title('Low contrast image')\\n \\n y_min, y_max = ax_hist.get_ylim()\\n ax_hist.set_ylabel('Number of pixels')\\n ax_hist.set_yticks(np.linspace(0, y_max, 5))\\n \\n ax_image, ax_hist, ax_cdf = plot_image_and_hist(image_rescale, mask, mask_cmap, img_cmap,\\n axes[:, 1])\\n ax_image.set_title('Contrast stretching')\\n \\n ax_image, ax_hist, ax_cdf = plot_image_and_hist(image_eq, mask, mask_cmap, img_cmap,\\n axes[:, 2])\\n ax_image.set_title('Histogram equalization')\\n \\n ax_image, ax_hist, ax_cdf = plot_image_and_hist(image_adapteq,mask, mask_cmap, img_cmap,\\n axes[:, 3])\\n ax_image.set_title('Adaptive equalization')\\n \\n ax_cdf.set_ylabel('Fraction of total intensity')\\n ax_cdf.set_yticks(np.linspace(0, 1, 5))\\n \\n # prevent overlap of y-axis labels\\n fig.tight_layout()\\n if save:\\n plt.savefig(os.path.join(target_path, name))\\n else:\\n plt.show()\\n plt.close()\\n return image_adapteq\",\n \"def process(self):\\n self.output_image = cv.cvtColor(self.input_image, cv.COLOR_BGR2GRAY)\\n cv.COLOR_BAYER_BG2GRAY\\n return self.output_image\",\n \"def _color(self, x, factor):\\r\\n factor = (factor/MAX_LEVEL) * 1.8 + .1\\r\\n degenerate = tf.image.grayscale_to_rgb(tf.image.rgb_to_grayscale(x))\\r\\n x = tfa.image.blend(degenerate, tf.cast(x, tf.float32), factor)\\r\\n return tf.saturate_cast(x, tf.uint8)\",\n \"def enhance_hue(self, delta, p=None):\\n if self._max_aug_nums>0:\\n if self._nums>self._max_aug_nums:\\n return self\\n self._nums += 1\\n if p is None:\\n p = self._p\\n self.image = enhance_hue(self.image, delta, p)\\n return self\",\n \"def change_color(image, from_color, to_color):\\n\\n\\twidth, height = image.get_size()\\n\\tfor x in range(width):\\n\\t\\tfor y in range(height):\\n\\t\\t\\tif image.get_at((x, y)) == from_color:\\n\\t\\t\\t\\timage.set_at((x, y), to_color)\\n\\treturn image\",\n \"def augment_brightness_camera_images(image):\\n\\n # The HSV - Hue Saturation Value representation converts the image from RGB space to HSV space\\n # where the Value(brightness) represents the brightness that is randomly increased\\n\\n image1 = cv2.cvtColor(image,cv2.COLOR_RGB2HSV)\\n random_bright = .25+np.random.uniform()\\n #print(random_bright)\\n image1[:,:,2] = image1[:,:,2]*random_bright\\n image1 = cv2.cvtColor(image1,cv2.COLOR_HSV2RGB)\\n return image1\",\n \"def blur(img, start_x, start_y, radius, blur_w, blur_h):\\n def around(img : Image, x, y, val_x, val_y):\\n \\\"\\\"\\\"Gets the rgb values averages for all px in radius X around the given px\\\"\\\"\\\"\\n colors = []\\n r_color = []\\n max_x, max_y = img.height, img.width \\n for i, j in zip(range(val_x), range(val_y)): # Get the rgb values of all the pixels around\\n try:\\n colors.append(img.getpixel((x + i, y + j)))\\n colors.append(img.getpixel((x - i, y - j)))\\n colors.append(img.getpixel((x - i, y + j)))\\n colors.append(img.getpixel((x + i, y - j)))\\n except IndexError:\\n if x + i > max_x:\\n x = max_x\\n if y + j > max_y:\\n y = max_y\\n print(\\\"IndexError handled ! X & Y are now \\\" , x, y, \\\" as the permitted max image value\\\") \\n colors.append(img.getpixel((x, y)))\\n for i in range(3): # Compute the average for each rbg value\\n t_color = [x[i] for x in colors]\\n r_color.append(sum(t_color)//len(colors))\\n return r_color\\n for x in range(blur_w):\\n act_x = start_x + x\\n # print(\\\"[act x]\\\", act_x)\\n # if act_x > img.height: # SECURITY : If a digit superior than the height/width is input, it will automaticly use the height/width\\n # # b = b + 1\\n # act_x = img.height\\n for y in range(blur_h): \\n act_y = start_y + y\\n # if act_y > img.width: # SECURITY : If a digit superior than the height/width is input, it will automaticly use the height/width\\n # act_y = img.width\\n px_c = around(img, act_x, act_y, radius, radius)\\n img.putpixel((start_x + x, start_y + y), tuple(px_c))\\n return img\",\n \"def color_transfert():\\n\\n\\n\\tn_target = input(\\\"Tell me which picture wants a new make up.\\\\n\\\\n\\\")\\n\\tn_source = input(\\\"And now tell me which one she wanna look like \\\\n\\\\n\\\")\\n\\n\\ttarget = cv.imread(n_target, 1)\\n\\tsource = cv.imread(n_source, 1)\\n\\n\\t### So basically, target will get new colors from source\\n\\n\\t## First let's convert them into the l alpha beta color space\\n\\n\\tt_alpha = rgb2alpha(target)\\n\\ts_alpha = rgb2alpha(source)\\n\\n\\n\\t## Now let's make up our target thanks to some statistical operations\\n\\n\\tm_target = make_up(t_alpha, s_alpha)\\n\\n\\n\\t## Finally we gonna convert target back to rgb space\\n\\n\\tm_target = alpha2rgb(m_target)\\n\\n\\t## And save it, so let's name it, you don't have to give the format, we'll add it here\\n\\n\\tname = input(\\\"What's the name of the new picture ? \\\\n\\\")\\n\\n\\tname += \\\".png\\\"\\n\\n\\tcv.imwrite(name, m_target)\\t\\t# You can now post your new picture to instagramm and let\\n\\t\\t\\t\\t\\t\\t# your followers believe that you are a skilled photograph.\\t\\n\\t\\t\\t\\t\\t\\t# I personally don't use this shit so fuck it.\\n\\n\\tprint(\\\"{} saved.\\\".format(name))\",\n \"def process_image(image):\\r\\n image = random_brightness(image)\\r\\n image = crop_image(image)\\r\\n image = resize(image)\\r\\n return image\",\n \"def equalize_color(img):\\n imgeq = numpy.zeros_like(img, dtype='float')\\n for i in xrange(img.shape[2]):\\n imgeq[:,:,i] = exposure.equalize_hist(img[:,:,i])\\n return imgeq\",\n \"def _adjust_contrast_img(self, results, factor=1.0):\\n for key in results.get('img_fields', ['image']):\\n img = results[key]\\n results[key] = mmcv.adjust_contrast(img, factor).astype(img.dtype)\",\n \"def colorize(self):\\n return\",\n \"def recompute_final_image(self):\\n if self._image is None:\\n self.final_image = None\\n return\\n if isinstance(self._image, np.ndarray):\\n if self._image.dtype == np.float and np.any(self._image > 1):\\n im = self._image / 255\\n else:\\n im = self._image\\n if self.cmap is not None:\\n im = cm.get_cmap(self.cmap)(im)\\n im = PIL.Image.fromarray((im * 255).astype(np.uint8))\\n else: # we hope it is a PIL image or equivalent\\n im = self._image\\n im = im.convert('RGBA')\\n if self.make_square:\\n new_size = max(im.width, im.height)\\n im = im.resize((new_size, new_size), PIL.Image.NEAREST)\\n if self.resolution is not None:\\n if self.resolution.size == 1:\\n im = im.resize((self.resolution, self.resolution),\\n PIL.Image.NEAREST)\\n else:\\n im = im.resize(self.resolution,\\n PIL.Image.NEAREST)\\n if self.circ_cut is not None:\\n middle = np.array(im.size) / 2\\n x = np.arange(im.size[0]) - middle[0] + 0.5\\n x = x / np.max(np.abs(x))\\n y = np.arange(im.size[1]) - middle[1] + 0.5\\n y = y / np.max(np.abs(y))\\n yy, xx = np.meshgrid(y, x)\\n r = np.sqrt(xx ** 2 + yy ** 2)\\n alpha = np.empty(r.shape)\\n alpha[r > 1] = 0\\n alpha[r <= self.circ_cut] = 1\\n val = (r > self.circ_cut) & (r <= 1)\\n alpha[val] = (\\n 0.5 + 0.5 * np.cos(\\n np.pi * (r[val] - self.circ_cut)\\n / (1 - self.circ_cut)))\\n alpha = alpha.T * np.array(im.getchannel('A'))\\n alpha = PIL.Image.fromarray(np.uint8(alpha))\\n im.putalpha(alpha)\\n if self.col is not None:\\n if self.border_type is None:\\n pass\\n elif self.border_type == 'alpha':\\n bg_alpha = np.array(im.getchannel('A'))\\n bg_alpha = bg_alpha > 0\\n bg_alpha = PIL.Image.fromarray(255 * np.uint8(bg_alpha))\\n bg = PIL.Image.new('RGBA', im.size, color=self.col)\\n bg.putalpha(bg_alpha)\\n im = PIL.Image.alpha_composite(bg, im)\\n elif self.border_type == 'pad':\\n im = PIL.ImageOps.expand(\\n im,\\n border=self.border_width,\\n fill=self.col)\\n elif self.border_type == 'conv':\\n im = PIL.ImageOps.expand(\\n im,\\n border=self.border_width,\\n fill=(0, 0, 0, 0))\\n bg_alpha = im.getchannel('A')\\n bg_alpha = bg_alpha.filter(PIL.ImageFilter.BoxBlur(\\n self.border_width))\\n bg_alpha = np.array(bg_alpha)\\n bg_alpha = 255 * np.uint8(bg_alpha > 0)\\n bg_alpha = PIL.Image.fromarray(bg_alpha)\\n bg = PIL.Image.new('RGBA', im.size, color=self.col)\\n bg.putalpha(bg_alpha)\\n im = PIL.Image.alpha_composite(bg, im)\\n self.final_image = im\",\n \"def recolorPixels(x,y,px, newColorArray):\\r\\n for i in range(0+coeff1*x,coeff1+coeff1*x):\\r\\n for j in range(0+coeff1*y,coeff1+coeff1*y):\\r\\n px[i,j]=newColorArray[x][y]\",\n \"def apply(self):\\n \\n i = 0\\n for LEDStrip in self._LEDStrips:\\n LEDStrip.applyColor(self._colors[i][0], self._colors[i][1], self._colors[i][2])\\n i += 1\",\n \"def emphasis(self, img, scale=2, fraction=0.5) :\\n return cv2.subtract(cv2.multiply(img[:,:,self.color],scale),\\n cv2.multiply(cv2.add( img[:,:,(self.color+1)%3],\\n img[:,:,(self.color+2)%3]),fraction))\",\n \"def shade_grey(img):\\n b,g,r = cv2.split(img)\\n illumination_est = np.mean([shade_grey_est(x) for x in [b,g,r]])\\n b_corrected = illumination_est/np.mean(b)*b\\n b_corrected = b_corrected.clip(max=240)\\n g_corrected = illumination_est/np.mean(g)*g\\n g_corrected = g_corrected.clip(max=240)\\n r_corrected = illumination_est/np.mean(r)*r\\n r_corrected = r_corrected.clip(max=240)\\n return cv2.merge((np.uint8(b_corrected),np.uint8(g_corrected),np.uint8(r_corrected)))\",\n \"def manage_color(self,test=0):\\n\\t\\thls = cv2.cvtColor(self.img, cv2.COLOR_RGB2HLS)\\n\\t\\ts_t150_255 = ch_threshold(hls, 2, (150,255))\\n\\t\\th_t25_180 = ch_threshold(hls, 0, (25,180))\\n\\t\\tl_t200_255 = ch_threshold(hls,1, (200,255))\\n\\t\\tyellow = self.manage_yellow()\\n\\t\\t \\n\\t\\ts_yellow = binary_or(s_t150_255, yellow)\\n\\t\\ts_y_h = binary_substr(s_yellow,h_t25_180)\\n\\t\\ts_y_h_l = binary_or(s_y_h, l_t200_255)\\n\\t\\treturn s_y_h_l\",\n \"async def update_image(new_value: str) -> None:\\n img.apply(swatch, img.Handle.color(parse_color(new_value), size, size))\",\n \"def paint_fill(image, col, row, color, orig_color):\\n\\n if image[row][col] != orig_color:\\n return\\n if row < 0 or row >= len(image) or col < 0 or col >= len(image[0]):\\n return\\n\\n image[row][col] = color\\n\\n paint_fill(image, col - 1, row, color, orig_color)\\n paint_fill(image, col + 1, row, color, orig_color)\\n paint_fill(image, col, row - 1, color, orig_color)\\n paint_fill(image, col, row + 1, color, orig_color)\\n\\n return\",\n \"def contrast_brightness_demo(img, ctr, bri): # 亮度b 对比度c\\n blank = np.zeros(img.shape, img.dtype)\\n out = cv.addWeighted(img, ctr, blank, 1 - ctr, bri)\\n\\n return out\",\n \"def add_color(self, markers):\\n self.img[markers == -1] = [255, 255, 255]\\n self.img[markers == 1] = [255, 0, 0]\\n self.img[markers == 2] = [0, 50, 0]\\n self.img[markers == 3] = [0, 0, 255]\\n self.img[markers == 4] = [255, 255, 0]\\n self.img[markers == 5] = [0, 255, 255]\\n self.img[markers == 6] = [255, 0, 255]\\n\\n self.img[markers == 7] = [125, 0, 0]\\n self.img[markers == 8] = [0, 125, 0]\\n self.img[markers == 9] = [0, 0, 125]\\n self.img[markers == 10] = [125, 125, 0]\\n self.img[markers == 11] = [0, 125, 125]\\n self.img[markers == 12] = [125, 0, 125]\\n\\n self.img[markers == 13] = [255, 255, 255]\\n self.img[markers == 14] = [255, 0, 0]\\n self.img[markers == 15] = [0, 255, 0]\\n self.img[markers == 16] = [0, 0, 255]\\n self.img[markers == 17] = [255, 255, 0]\\n self.img[markers == 18] = [0, 255, 255]\\n self.img[markers == 19] = [255, 0, 255]\",\n \"def adjustSaturation(img, fac):\\n img2 = np.float32(img)\\n tmp = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\\n tmp = cv2.cvtColor(tmp, cv2.COLOR_GRAY2BGR)\\n\\n img2 = (1 - fac) * tmp + fac * img2\\n img2 = np.uint8(img2.clip(0, 255))\\n return img2\",\n \"def apply_filter(self, image):\\n pass\",\n \"def changeColor( self ):\\n\\t\\t\\n\\t\\tx, y = self.position.xy\\n\\t\\tself.color = ( int((x / WINDOW_X) * 128), int((x / WINDOW_X) * 128) + int((y / WINDOW_Y) * 128 ), int((y / WINDOW_Y) * 128))\",\n \"def grayscale(image):\\n for y in range(image.getHeight() ):\\n for x in range (image.getWidth() ):\\n (r, g, b) = image.getPixel(x,y)\\n r = int(r * 0.299)\\n g = int(g * 0.587)\\n b = int(b * 0.114)\\n gray = r + g + b\\n image.setPixel (x, y, (gray, gray, gray))\",\n \"def contrast_adjust(image, alpha=1.3, beta=20):\\n newimage = image.astype(np.float32) * alpha + beta\\n\\n if type(image[0, 0, 0]) == np.uint8:\\n newimage[newimage < 0] = 0\\n newimage[newimage > 255] = 255\\n return np.uint8(newimage)\\n else:\\n newimage[newimage < 0] = 0\\n newimage[newimage > 1] = 1.\\n return newimage\",\n \"def adjust_contrast(img, contrast_factor):\\n check_type(img)\\n\\n enhancer = ImageEnhance.Contrast(img)\\n img = enhancer.enhance(contrast_factor)\\n return img\",\n \"def post_process_image(self, image):\\r\\n A = np.min(image)\\r\\n B = np.max(image)\\r\\n k = 255\\r\\n R, C = image.shape\\r\\n for i in range(R):\\r\\n for j in range(C):\\r\\n image[i][j] = (k / (B-A)) * (image[i][j] - A)\\r\\n average_image = np.average(image)\\r\\n if average_image > 50:\\r\\n return image.astype(dtype='uint8')\\r\\n else:\\r\\n return (255-image).astype(dtype='uint8')\",\n \"def AutoContrast(img: Image, _: float) -> Image:\\n return PIL.ImageOps.autocontrast(img)\",\n \"def create_colorful_test_image(self):\\n ch255 = np.full([100, 200, 1], 255, dtype=np.uint8)\\n ch128 = np.full([100, 200, 1], 128, dtype=np.uint8)\\n ch0 = np.full([100, 200, 1], 0, dtype=np.uint8)\\n imr = np.concatenate((ch255, ch128, ch128), axis=2)\\n img = np.concatenate((ch255, ch255, ch0), axis=2)\\n imb = np.concatenate((ch255, ch0, ch255), axis=2)\\n imw = np.concatenate((ch128, ch128, ch128), axis=2)\\n imu = np.concatenate((imr, img), axis=1)\\n imd = np.concatenate((imb, imw), axis=1)\\n image = np.concatenate((imu, imd), axis=0)\\n return image\",\n \"def perform(self, image, mode):\\n random.seed(self.seed.get(mode))\\n if mode == 'binary':\\n return image\\n\\n # gets random number between -0.5 and 0.5 from normal distribution\\n change_in_saturation = max(-0.5, min(0.5, random.normalvariate(0, 0.167)))\\n change_in_saturation = 0.35\\n hsv_image = cv2.cvtColor(image.astype(np.float32), cv2.COLOR_BGR2HSV)\\n max_change_per_pixel = (np.full((len(image[:, 0, 0]), len(image[0, :, 0])), 1) - hsv_image[:, :, 1])\\n min_change_per_pixel = hsv_image[:, :, 1]\\n change_per_pixel = np.minimum(min_change_per_pixel, max_change_per_pixel) * change_in_saturation\\n\\n hsv_image[:, :, 1] = hsv_image[:, :, 1] + change_per_pixel\\n\\n image = np.round(cv2.cvtColor(hsv_image, cv2.COLOR_HSV2BGR)).astype(np.uint8)\\n return image\",\n \"def weighted_grayscale(img):\\n for pixel in img:\\n x, y, col = pixel\\n r, g, b = col\\n \\n r = (r * 0.299 + g * 0.587 + b * 0.114)\\n r = g = b\\n \\n new_color = create_color(r, g, b)\\n set_color(img, x, y, new_color)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.79571605","0.67238367","0.6699741","0.66279745","0.66164297","0.6579595","0.65684307","0.64621973","0.63937193","0.63469017","0.63373184","0.63109785","0.6228176","0.61978406","0.61928","0.61690545","0.61679554","0.6136985","0.6136281","0.6107434","0.60941255","0.6086365","0.6038167","0.60252744","0.6015981","0.6012086","0.6001512","0.5977713","0.5974887","0.59482986","0.5935672","0.5926012","0.59259415","0.5924252","0.5919418","0.5914649","0.59122974","0.5898526","0.5875008","0.5867007","0.5865372","0.584743","0.58444464","0.58435214","0.58402556","0.5839648","0.58319485","0.58231705","0.58152467","0.58084536","0.57936317","0.57930195","0.57843035","0.578344","0.5775897","0.5757926","0.5744925","0.5744838","0.5740711","0.5721808","0.5718428","0.5714149","0.57133085","0.57114154","0.5707776","0.57067704","0.57060486","0.5697055","0.56954587","0.5689637","0.56813264","0.5673566","0.56667763","0.56604487","0.5655013","0.56454647","0.56436175","0.56364036","0.56304306","0.5628488","0.5614512","0.56124806","0.5611764","0.56046295","0.5601101","0.559974","0.55906135","0.5589257","0.55868894","0.55814713","0.5577143","0.55727565","0.5570864","0.55671626","0.5566088","0.55601996","0.5560033","0.55543625","0.5553764","0.554665","0.55464613"],"string":"[\n \"0.79571605\",\n \"0.67238367\",\n \"0.6699741\",\n \"0.66279745\",\n \"0.66164297\",\n \"0.6579595\",\n \"0.65684307\",\n \"0.64621973\",\n \"0.63937193\",\n \"0.63469017\",\n \"0.63373184\",\n \"0.63109785\",\n \"0.6228176\",\n \"0.61978406\",\n \"0.61928\",\n \"0.61690545\",\n \"0.61679554\",\n \"0.6136985\",\n \"0.6136281\",\n \"0.6107434\",\n \"0.60941255\",\n \"0.6086365\",\n \"0.6038167\",\n \"0.60252744\",\n \"0.6015981\",\n \"0.6012086\",\n \"0.6001512\",\n \"0.5977713\",\n \"0.5974887\",\n \"0.59482986\",\n \"0.5935672\",\n \"0.5926012\",\n \"0.59259415\",\n \"0.5924252\",\n \"0.5919418\",\n \"0.5914649\",\n \"0.59122974\",\n \"0.5898526\",\n \"0.5875008\",\n \"0.5867007\",\n \"0.5865372\",\n \"0.584743\",\n \"0.58444464\",\n \"0.58435214\",\n \"0.58402556\",\n \"0.5839648\",\n \"0.58319485\",\n \"0.58231705\",\n \"0.58152467\",\n \"0.58084536\",\n \"0.57936317\",\n \"0.57930195\",\n \"0.57843035\",\n \"0.578344\",\n \"0.5775897\",\n \"0.5757926\",\n \"0.5744925\",\n \"0.5744838\",\n \"0.5740711\",\n \"0.5721808\",\n \"0.5718428\",\n \"0.5714149\",\n \"0.57133085\",\n \"0.57114154\",\n \"0.5707776\",\n \"0.57067704\",\n \"0.57060486\",\n \"0.5697055\",\n \"0.56954587\",\n \"0.5689637\",\n \"0.56813264\",\n \"0.5673566\",\n \"0.56667763\",\n \"0.56604487\",\n \"0.5655013\",\n \"0.56454647\",\n \"0.56436175\",\n \"0.56364036\",\n \"0.56304306\",\n \"0.5628488\",\n \"0.5614512\",\n \"0.56124806\",\n \"0.5611764\",\n \"0.56046295\",\n \"0.5601101\",\n \"0.559974\",\n \"0.55906135\",\n \"0.5589257\",\n \"0.55868894\",\n \"0.55814713\",\n \"0.5577143\",\n \"0.55727565\",\n \"0.5570864\",\n \"0.55671626\",\n \"0.5566088\",\n \"0.55601996\",\n \"0.5560033\",\n \"0.55543625\",\n \"0.5553764\",\n \"0.554665\",\n \"0.55464613\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":88578,"cells":{"query":{"kind":"string","value":"Save a version of the file with an added border, controlled by the colour and width parameters."},"document":{"kind":"string","value":"def saveborder(image, fname, outpath, width=20, colour=\"black\", preserve_name=False):\n im = image.copy()\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"border{width}{colour}\")\n else:\n fpath = genSavePath(outpath, fname)\n\n im = ImageOps.expand(im, border=width, fill=colour)\n try:\n im.save(fpath, subsample=\"keep\", qtables=image.quantization, optimize=True)\n\n except IOError as m:\n print(\"Border image creation failed for: {}. \\nReason:{}\".format(fname,m))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def save_visualization_to_file(self, file_name, length = 90):\n session = self.capture_last(length)\n visualizer.animate(session , 0, length, name = file_name, min_x = -1, max_x = 1, min_y = -1, max_y = 1, show = False )","def write(self, file_name, width=1500.0, height=1000.0):\n with open(file_name, 'wb+') as fh:\n fh.write(self.make(width, height))","def write(self, file_name, width=1500.0, height=1000.0):\n with open(file_name, 'w+') as fh:\n fh.write(self.make(width, height))","def saveOutlined(self, filepath: str):\n\n if self.outlined is None:\n print('No intermidiary image, try run find first')\n return\n self.save(filepath, self.outlined)","def write(self, fileW):\n fileW.wByte(self.b)\n fileW.wByte(self.g)\n fileW.wByte(self.r)\n fileW.wByte(self.a)","def save(self, output_path: str, box_thickness: int = 2, show_confidence: bool = True, color_mapping: Optional[List[Tuple[int, int, int]]] = None) -> None:\n frames = self.draw(box_thickness=box_thickness, show_confidence=show_confidence, color_mapping=color_mapping)\n save_video(output_path=output_path, frames=frames, fps=self.fps)","def saveLightcurve(self, filename):\n lfile = open(filename, 'w')\n lfile.write(\"# time \\t counts \\t countrate \\n\")\n for t,c,cr in zip(self.time, self.counts, self.countrate):\n lfile.write(str(t) + \"\\t\" + str(c) + \"\\t\" + str(cr) + \"\\n\")\n lfile.close()","def write(self, fileW):\n fileW.wShort(self.x)\n fileW.wShort(self.y)","def on_save_style_clicked(self, obj):\n name = cuni(self.top.get_object(\"style_name\").get_text())\n\n self.save_paragraph()\n self.style.set_name(name)\n self.parent.sheetlist.set_style_sheet(name, self.style)\n self.parent.redraw()\n self.window.destroy()","def Save(self, app, pad):\n data = pad.get('1.0', GUI.END)[:-1]\n try:\n f = open(File.path, 'w')\n f.write(data)\n f.close()\n except IOError:\n f = open('untitled.cpp', 'w')\n f.write(data)\n f.close()\n return -1","def printfile(self, event=None):\n filename = self.en.get()\n bbox = self.canvas.bbox(ALL)\n width=bbox.right*self.unit\n height=bbox.bottom*self.unit\n self.canvas.config(width=width, height=height)\n self.canvas.dump(filename)\n self.canvas.config(width=self.ca_width, height=self.ca_height)\n self.la.config(text='Wrote file ' + filename)","def save_file(self, _filename):\n imgsize = (self.__resolution[0], self.__resolution[1])\n print imgsize\n\n if(self.__resolution[2] == 1):\n # grayscale -> convert to RGB\n bg_white = (255, 255, 255)\n img = Image.new(\"RGB\", imgsize, bg_white)\n\n for x in xrange(0, self.__resolution[0], 1):\n for y in xrange(0, self.__resolution[1], 1):\n col = self.get_color(_pos)\n # duplicate the channels\n ucharcol = (255 * col[0], 255 * col[0], 255 * col[0])\n img.putpixel((x, self.__resolution[1] - y - 1), ucharcol)\n\n elif(self.__resolution[2] == 3):\n # RGB\n bg_white = (255, 255, 255)\n img = Image.new(\"RGB\", imgsize, bg_white)\n\n for x in xrange(0, self.__resolution[0], 1):\n for y in xrange(0, self.__resolution[1], 1):\n col = self.get_color(_pos)\n ucharcol = (255 * col[0], 255 * col[1], 255 * col[2])\n img.putpixel((x, self.__resolution[1] - y - 1), ucharcol)\n\n elif(self.__resolution[2] == 4):\n # RGBA\n bg_white = (255, 255, 255, 255)\n img = Image.new(\"RGBA\", imgsize, bg_white)\n\n for x in xrange(0, self.__resolution[0], 1):\n for y in xrange(0, self.__resolution[1], 1):\n col = 255 * self.get_color((x, y))\n ucharcol = (int(col[0]), int(col[1]), int(col[2]), int(col[3]))\n img.putpixel((x, self.__resolution[1] - y - 1), ucharcol)\n else:\n raise StandardError, ('supported number of channels are 1, 3, and 4, only.')\n\n img.save(_filename)","def accept(self):\n global fileName, origheight, origwidth\n border=size=style=alt=title=\"\"\n\n alt=str(self.le_alt.text())\n\n if self.le_title.text():\n title='title=\"'+str(self.le_title.text())+'\"'\n\n #If size has changed, put it\n if not str(origheight)==str(self.le_height.text()) or not str(origwidth)==str(self.le_width.text()):\n size=' width=\"'+str(self.le_width.text())+'\" height=\"'+str(self.le_height.text())+'\"'\n #Put to code Border options if has selected\n if self.ch_border.isChecked():\n global bordercolor\n #TODO: LINE EDIT DOES NOT HAVE SUPPORT TO BORDERCOLOR ON IMAGES\n border=' border=\"'+str(self.sb_border_width.value())+'\"'\n style=style+\" border-style: \"+self.cb_style.currentText().toLower()+\" ; border: \"+str(self.sb_border_width.value())+\"px \"+bordercolor.name()+\"; \"\n #If any has style parameters, define it\n if style<>\"\":\n style=' style=\"'+style+'\"'\n\n camino,fichero=os.path.split(str(fileName))\n imgcode=\"<img \"+title+' src=\"img'+os.sep+fichero+'\" '+size+border+style+\" >\"+alt+\"</img>\"\n self.emit(SIGNAL(\"imgcode\"), imgcode,fileName)\n self.close()","def write(self, filename):\n f = open(filename, 'bw')\n\n # file header (14)\n f.write(char('B'))\n f.write(char('M'))\n f.write(dword(14 + 40 + self.width * self.height * 3))\n f.write(dword(0))\n f.write(dword(14 + 40))\n\n # image header (40)\n f.write(dword(40))\n f.write(dword(self.width))\n f.write(dword(self.height))\n f.write(word(1))\n f.write(word(24))\n f.write(dword(0))\n f.write(dword(0))\n f.write(dword(self.width * self.height * 3))\n f.write(dword(0))\n f.write(dword(0))\n f.write(dword(0))\n f.write(dword(0))\n\n # pixel data\n for x in range(self.height):\n for y in range(self.width):\n f.write(self.pixels[x][y])\n f.close()","def save(self, filename):\n print(\"Saving...\", end=\"\\r\")\n canvas = self.canvas[self.N:self.S,self.W:self.E]\n cv2.imwrite(\"./Output/\"+filename, canvas)\n print(\"Saved:\",filename)","def set_border(self, color: tuple = (0, 0, 0, 255), width: int = 1):\n self.border_color = color\n self.border = width","def save(\n self,\n output_path: str,\n box_thickness: int = 2,\n show_confidence: bool = True,\n color_mapping: Optional[List[Tuple[int, int, int]]] = None,\n target_bboxes: Optional[np.ndarray] = None,\n target_bboxes_format: Optional[str] = None,\n target_class_ids: Optional[np.ndarray] = None,\n ) -> None:\n image = self.draw(\n box_thickness=box_thickness,\n show_confidence=show_confidence,\n color_mapping=color_mapping,\n target_bboxes=target_bboxes,\n target_bboxes_format=target_bboxes_format,\n target_class_ids=target_class_ids,\n )\n save_image(image=image, path=output_path)","def update_border(self):\n # side borders\n for row_position in range(NUM_ROWS+BORDER_WIDTH*2):\n self.stdscr.addstr(row_position, 0, '|', curses.color_pair(7))\n self.stdscr.addstr(row_position, NUM_COLUMNS*BLOCK_WIDTH+1, '|', curses.color_pair(7))\n # top and bottom borders\n for column_position in range(NUM_COLUMNS*BLOCK_WIDTH+BORDER_WIDTH*2):\n self.stdscr.addstr(0, column_position, '-', curses.color_pair(7))\n self.stdscr.addstr(NUM_ROWS+1, column_position, '-', curses.color_pair(7))","def save_screenshot(self, file_name, width=3840, height=2160, first=True, last=True):\n if first and self.assigned_opengl_context is not None:\n self.assigned_opengl_context.makeCurrent()\n gr3.export(file_name, width, height)\n if last and self.assigned_opengl_context is not None:\n self.assigned_opengl_context.doneCurrent()","def save(self, filename: str, transparent: bool = False) -> None:\n if transparent:\n for fig in self._figures:\n fig.background_fill_color = None # type: ignore[assignment]\n fig.border_fill_color = None # type: ignore[assignment]\n\n if self._want_svg:\n export_svg(self._layout, filename=filename)\n else:\n export_png(self._layout, filename=filename)","def save(self, filename, overwrite=False, verbose=True, msg=''):\n if msg:\n msg = ' \"%s\"' % msg\n save_to_file(\n filename, self, overwrite=overwrite, verbose=verbose,\n showname='curve%s' % msg\n )","def save_babble(self):\n save_file = filedialog.asksaveasfile(mode='w', defaultextension='.txt')\n if save_file is None:\n return\n save_file.write(self.display.get('1.0', tk.END))\n save_file.close()","def _save_version_file(cls, hivemind_version, git_revision, git_date):\n with open(\"hive/version.py\", 'w') as version_file:\n version_file.write(\"# generated by setup.py\\n\")\n version_file.write(\"# contents will be overwritten\\n\")\n version_file.write(\"VERSION = '{}'\\n\".format(hivemind_version))\n version_file.write(\"GIT_REVISION = '{}'\\n\".format(git_revision))\n version_file.write(\"GIT_DATE = '{}'\\n\".format(git_date))","def format_box(box, box_style, border_visible, border_color, border_style,\n border_width, border_radius, padding, margin):\n box.box_style = box_style\n box.padding = padding\n box.margin = margin\n if border_visible:\n box.border_color = border_color\n box.border_style = border_style\n box.border_width = border_width\n box.border_radius = border_radius\n else:\n box.border_width = 0","def save(self, fname):\n fmt = \" %7.1f %7.1f %8.2f %8.2f %8.2f %8.3f %8.3f %8.3f %8.3f %6.1f\"\n with open(fname, 'wb') as fid:\n fid.write('# CoordinateSystem \"Head\"\\n'.encode('utf-8'))\n fid.write('# begin end X (mm) Y (mm) Z (mm)'\n ' Q(nAm) Qx(nAm) Qy(nAm) Qz(nAm) g/%\\n'\n .encode('utf-8'))\n t = self.times[:, np.newaxis] * 1000.\n gof = self.gof[:, np.newaxis]\n amp = 1e9 * self.amplitude[:, np.newaxis]\n out = np.concatenate((t, t, self.pos / 1e-3, amp,\n self.ori * amp, gof), axis=-1)\n np.savetxt(fid, out, fmt=fmt)\n if self.name is not None:\n fid.write(('## Name \"%s dipoles\" Style \"Dipoles\"'\n % self.name).encode('utf-8'))","def savefig(plt, path, show_message= True, tight_flag= True, newline= True):\n if show_message:\n print(\"Saving to {}\".format(path))\n if tight_flag:\n plt.savefig(path, bbox_inches='tight', pad_inches=0)\n else:\n plt.savefig(path)\n if newline:\n print(\"\")","def _get_thickness(self,filename, maxLen=3):\n filename = os.path.splitext(filename)[0] \n filename = os.path.split(filename)[1] \n filename = filename.split(\"_t\")[-1] \n filename = filename.split(\"_\")[0]\n if \"v\" in filename:\n part1=filename.split(\"v\",1)[0]\n part2=filename.split(\"v\",1)[1]\n filename = ''.join((filename.split(\"v\",1)[0],'.',filename.split(\"v\",1)[1]))#['%s.%s' %(filename.split(\"v\",1)[0],filename.split(\"v\",1)[1])]\n print(filename)\n thickness = filename\n return thickness","def save(self, filepath):\n self.drawer.flush()\n self.img.save(filepath)","def save(self, filename):\n if len(self.interpolated_points) > 0:\n red, green, blue = zip(*self.interpolated_points)\n red = [np.asscalar(x) for x in red]\n green = [np.asscalar(x) for x in green]\n blue = [np.asscalar(x) for x in blue]\n output_type = \"interpolated\"\n print(\"Exporting interpolated points\")\n elif len(self.main_cluster) > 0:\n red, green, blue = self.get_color_lookup_table_points(self.main_cluster)\n output_type = \"clustered\"\n print(\"Exporting cluster points\")\n else:\n red = self.color_lookup_table_points[0]\n green = self.color_lookup_table_points[1]\n blue = self.color_lookup_table_points[2]\n output_type = \"resized\"\n print(\"Exporting resized points\")\n\n data = dict(\n red=red,\n green=green,\n blue=blue\n )\n\n filename = f'{filename}_{output_type}.pickle'\n with open(filename, 'wb') as outfile:\n pickle.dump(data, outfile, protocol=2)\n # stores data of color lookup table in file as pickle for efficient loading (yaml is too slow)\n\n print(f\"Output saved to '{filename}'.\")","def write(self, file_name, style=None):\n write_elongation(self, file_name, style=style)","def save_GRID( self , filename ):\n self._fwrite_GRID( filename )","def save(self, filename):\n pass","def style(self, box_style=None, border_visible=False, border_colour='black',\n border_style='solid', border_width=1, border_radius=0, padding=0,\n margin=0, font_family='', font_size=None, font_style='',\n font_weight=''):\n format_box(self, box_style, border_visible, border_colour, border_style,\n border_width, border_radius, padding, margin)\n format_font(self, font_family, font_size, font_style, font_weight)\n format_font(self.file_format_select, font_family, font_size, font_style,\n font_weight)\n format_font(self.dpi_text, font_family, font_size, font_style,\n font_weight)\n format_font(self.orientation_dropdown, font_family, font_size,\n font_style, font_weight)\n format_font(self.papertype_select, font_family, font_size, font_style,\n font_weight)\n format_font(self.transparent_checkbox, font_family, font_size,\n font_style, font_weight)\n format_font(self.pad_inches_text, font_family, font_size, font_style,\n font_weight)\n format_font(self.filename_text, font_family, font_size, font_style,\n font_weight)\n format_font(self.overwrite_checkbox, font_family, font_size, font_style,\n font_weight)\n format_font(self.save_button, font_family, font_size, font_style,\n font_weight)\n self.facecolour_widget.style(\n box_style=None, border_visible=False, font_family=font_family,\n font_size=font_size, font_weight=font_weight, font_style=font_style)\n self.edgecolour_widget.style(\n box_style=None, border_visible=False, font_family=font_family,\n font_size=font_size, font_weight=font_weight, font_style=font_style)","def save_poly(self,ikfile,boresight,x,y,z): \n with open(ikfile, \"w\") as f:\n f.write(\"KPL/IK \\nComments. \\nMore comments. \\nMore comments.\\n\\\\begindata\\n\")\n f.write(\"INS-99999_FOV_SHAPE = 'POLYGON'\\n\")\n f.write(\"INS-99999_FOV_FRAME = 'CAMERA_FRAME'\\n\")\n f.write(\"INS-99999_BORESIGHT = (%15.10f %15.10f %15.10f)\\n\" %(boresight[0],boresight[1],boresight[2]))\n f.write(\"INS-99999_FOV_BOUNDARY_CORNERS = (%15.10f %15.10f %15.10f \\n\" %(x[0],y[0],z[0]))\n for i in range(1,len(x)-1):\n f.write(\"%34s %15.10f %15.10f %15.10f \\n\" %(\" \",x[i],y[i],z[i]))\n f.write(\"%34s %15.10f %15.10f %15.10f) \\n\" %(\" \",x[len(x)-1],y[len(y)-1],z[len(z)-1]))\n f.close()","def write(self, fileW):\n fileW.wFloat(self.x)\n fileW.wFloat(self.y)\n fileW.wFloat(self.z)","def write_grid(self, file_path, fmt='%0.16g'):\n with open(file_path, 'w') as outfile:\n if self.grid.size == 3:\n outfile.write('{}\\t{}\\t{}\\n'.format(self.grid[0].size - 1,\n self.grid[1].size - 1,\n self.grid[2].size - 1))\n else:\n outfile.write('{}\\t{}\\n'.format(self.grid[0].size - 1,\n self.grid[1].size - 1))\n with open(file_path, 'ab') as outfile:\n numpy.savetxt(outfile, numpy.c_[self.grid[0]], fmt=fmt)\n numpy.savetxt(outfile, numpy.c_[self.grid[1]], fmt=fmt)\n if self.grid.size == 3:\n numpy.savetxt(outfile, numpy.c_[self.grid[2]], fmt=fmt)","def write(self, outfile, style='xyz', xyzlabel=True):\n out = ''\n if style == 'xyz':\n if xyzlabel:\n out += f'{len(self)}\\n\\n'\n out += str(self)\n elif style == 'latex':\n header = f'{len(self)}\\\\\\\\\\n'\n line_form = '{:<2}' + ' {:> 13.6f}' * 3 + ' {:>7.4f}'\n atoms = [line_form.format(atom, *pos, charge) for atom, xyz, charge in self]\n atoms = '\\n'.join(atoms)\n out = '\\\\begin{verbatim}\\n' + atoms + '\\n\\\\end{verbatim}'\n else:\n raise SyntaxError('Invalid style')\n with open(outfile, 'w') as f:\n f.write(out)","def style(self, box_style=None, border_visible=False, border_color='black',\n border_style='solid', border_width=1, border_radius=0, padding=0,\n margin=0, font_family='', font_size=None, font_style='',\n font_weight=''):\n _format_box(self, box_style, border_visible, border_color, border_style,\n border_width, border_radius, padding, margin)\n _format_font(self, font_family, font_size, font_style, font_weight)\n _format_font(self.file_format_select, font_family, font_size,\n font_style, font_weight)\n _format_font(self.dpi_text, font_family, font_size, font_style,\n font_weight)\n _format_font(self.orientation_dropdown, font_family, font_size,\n font_style, font_weight)\n _format_font(self.papertype_select, font_family, font_size,\n font_style, font_weight)\n _format_font(self.transparent_checkbox, font_family, font_size,\n font_style, font_weight)\n _format_font(self.pad_inches_text, font_family, font_size, font_style,\n font_weight)\n _format_font(self.filename_text, font_family, font_size, font_style,\n font_weight)\n _format_font(self.overwrite_checkbox, font_family, font_size,\n font_style, font_weight)\n _format_font(self.save_button, font_family, font_size, font_style,\n font_weight)\n self.facecolour_widget.style(\n box_style=None, border_visible=False, font_family=font_family,\n font_size=font_size, font_weight=font_weight, font_style=font_style)\n self.edgecolour_widget.style(\n box_style=None, border_visible=False, font_family=font_family,\n font_size=font_size, font_weight=font_weight, font_style=font_style)","def create_file(destfile, size):\n fulllines = int(math.floor(size / 100.0))\n nwd = int(math.floor(math.log(fulllines+1))) + 1\n fmt = \"%{0}d \".format(nwd)\n\n with open(destfile, 'w') as fd:\n for i in range(fulllines):\n fd.write(fmt % i)\n fd.write('x' * (98-nwd))\n fd.write('\\n')\n\n left = size - (fulllines * 100)\n if left > nwd:\n fd.write(fmt % (fulllines))\n left -= nwd + 1\n if left > 1:\n fd.write('x' * (left-1))\n left = 1\n if left > 0:\n fd.write('\\n')\n\n return os.stat(destfile).st_size","def export_wells(self, w, title):\r\n self._check_out(title)\r\n np.savez_compressed(os.path.join(self.out_dir, title, title), w)","def write_file(self, filename):\n with open(filename, \"w\") as fo:\n # vertices\n\n for x, y, z in self.vertices:\n fo.write(\"v {} {} {}\\n\".format(x, y, z))\n logging.info(\"Wrote {} vertices\".format(len(self.vertices)))\n\n # faces\n faces = 0\n width, height = self.size\n for y in range(0, height-1):\n for x in range(0, width-1):\n tl = self.vertex_num(x,y)\n tr = tl + 1\n bl = tl + width\n br = bl + 1\n fo.write(\"f {} {} {}\\n\".format(tl, tr, bl))\n fo.write(\"f {} {} {}\\n\".format(tr, br, bl))\n faces += 2\n logging.info(\"Wrote {} tris\".format(faces))","def save_bmp(filename, data, width, height):\r\n\r\n hdr = struct.pack(\"<BBLHHLLLLHHLLLLLL\",\r\n 0x42, 0x4D,\r\n width * height * 3 + 54,\r\n 0, 0,\r\n 54, # offset\r\n 40, # header length\r\n width, height,\r\n 0, # colorplanes\r\n 24, # colordepth\r\n 0, # compression\r\n width * height * 3, # imagesize: calcular\r\n 0, 0, # resolution hor,vert\r\n 0, # palette\r\n 0) # importantcolors\r\n\r\n bmpfile = open(filename, \"wb\")\r\n bmpfile.write(hdr)\r\n bmpfile.write(data)\r\n bmpfile.close()","def finish(self):\n self._fout.add_size()\n self._fout.add_padding()\n self._fout.close()","def save(\n self,\n output_path: str,\n show_confidence: bool = True,\n ) -> None:\n image = self.draw(show_confidence=show_confidence)\n save_image(image=image, path=output_path)","def save(self, assignment, filename):\n from PIL import Image, ImageDraw, ImageFont\n cell_size = 100\n cell_border = 2\n interior_size = cell_size - 2 * cell_border\n letters = self.letter_grid(assignment)\n\n # Create a blank canvas\n img = Image.new(\n \"RGBA\",\n (self.crossword.width * cell_size,\n self.crossword.height * cell_size),\n \"black\"\n )\n font = ImageFont.truetype(\"assets/fonts/OpenSans-Regular.ttf\", 80)\n draw = ImageDraw.Draw(img)\n\n for i in range(self.crossword.height):\n for j in range(self.crossword.width):\n\n rect = [\n (j * cell_size + cell_border,\n i * cell_size + cell_border),\n ((j + 1) * cell_size - cell_border,\n (i + 1) * cell_size - cell_border)\n ]\n if self.crossword.structure[i][j]:\n draw.rectangle(rect, fill=\"white\")\n if letters[i][j]:\n w, h = draw.textsize(letters[i][j], font=font)\n draw.text(\n (rect[0][0] + ((interior_size - w) / 2),\n rect[0][1] + ((interior_size - h) / 2) - 10),\n letters[i][j], fill=\"black\", font=font\n )\n\n img.save(filename)","def save(self, assignment, filename):\n from PIL import Image, ImageDraw, ImageFont\n cell_size = 100\n cell_border = 2\n interior_size = cell_size - 2 * cell_border\n letters = self.letter_grid(assignment)\n\n # Create a blank canvas\n img = Image.new(\n \"RGBA\",\n (self.crossword.width * cell_size,\n self.crossword.height * cell_size),\n \"black\"\n )\n font = ImageFont.truetype(\"assets/fonts/OpenSans-Regular.ttf\", 80)\n draw = ImageDraw.Draw(img)\n\n for i in range(self.crossword.height):\n for j in range(self.crossword.width):\n\n rect = [\n (j * cell_size + cell_border,\n i * cell_size + cell_border),\n ((j + 1) * cell_size - cell_border,\n (i + 1) * cell_size - cell_border)\n ]\n if self.crossword.structure[i][j]:\n draw.rectangle(rect, fill=\"white\")\n if letters[i][j]:\n w, h = draw.textsize(letters[i][j], font=font)\n draw.text(\n (rect[0][0] + ((interior_size - w) / 2),\n rect[0][1] + ((interior_size - h) / 2) - 10),\n letters[i][j], fill=\"black\", font=font\n )\n\n img.save(filename)","def save(self, assignment, filename):\n from PIL import Image, ImageDraw, ImageFont\n cell_size = 100\n cell_border = 2\n interior_size = cell_size - 2 * cell_border\n letters = self.letter_grid(assignment)\n\n # Create a blank canvas\n img = Image.new(\n \"RGBA\",\n (self.crossword.width * cell_size,\n self.crossword.height * cell_size),\n \"black\"\n )\n font = ImageFont.truetype(\"assets/fonts/OpenSans-Regular.ttf\", 80)\n draw = ImageDraw.Draw(img)\n\n for i in range(self.crossword.height):\n for j in range(self.crossword.width):\n\n rect = [\n (j * cell_size + cell_border,\n i * cell_size + cell_border),\n ((j + 1) * cell_size - cell_border,\n (i + 1) * cell_size - cell_border)\n ]\n if self.crossword.structure[i][j]:\n draw.rectangle(rect, fill=\"white\")\n if letters[i][j]:\n w, h = draw.textsize(letters[i][j], font=font)\n draw.text(\n (rect[0][0] + ((interior_size - w) / 2),\n rect[0][1] + ((interior_size - h) / 2) - 10),\n letters[i][j], fill=\"black\", font=font\n )\n\n img.save(filename)","def create_half_pic(self):\n number_of_line = 0\n for i in range(*self.horizontal_pic_border):\n number_of_column = self.parameter//2\n for j in range(*self.vertical_pic_border):\n if number_of_column > (number_of_line + 1):\n self.flag[i][j] = ' '\n elif number_of_column == (number_of_line + 1):\n self.flag[i][j] = CIRCLE_BORDER\n else:\n self.flag[i][j] = CIRCLE_INNER\n number_of_column -= 1\n mirror_update(self.flag[i])\n number_of_line += 1","def bgsave(self):\r\n return self.format_inline('BGSAVE')","def draw(self, item, filename, style, thumb=False):\n valid_styles = {\n #'dudedb': self.__draw_ubl_style, # need revision\n #'ptp': self.__draw_ubl_style, # need revision\n 'episcan': self.__draw_gen_style,\n }\n\n assert style in valid_styles, '{0} style not in valid_styles ({1})'.format(style, valid_styles)\n\n if thumb:\n p = {\"pad1\": item[\"len\"] * 0.02,\n \"pad2\": item[\"len\"] * 0.003,\n \"figsize\": (1.5, 0.3),\n \"lpad\": 0.16,\n \"evpad\": 0.5,\n \"nvpad\": 0.4}\n else:\n if not self.fixed:\n p = {\"pad1\": self.max_len * 0.035, # pad out 1% of the figure left and right\n \"pad2\": self.max_len * 0.003,\n \"figsize\": (25, 1),\n \"lpad\": 0.02, # vertical size of the central line\n \"evpad\": 0.25, # vertical size of the 'normal' rectangle domain boxes.\n \"nvpad\": 0.2,\n \"titlepos\": \"left\",\n \"titlesize\": 13} # vertical size of the 'enhanced' rectangle domain boxes.\n else: # ie fixed\n p = {\"pad1\": item[\"len\"] * 0.03, # pad out 1% of the figure left and right\n \"pad2\": item[\"len\"] * 0.003,\n \"figsize\": (7, 1),\n \"lpad\": 0.02, # vertical size of the central line\n \"evpad\": 0.20, # vertical size of the 'normal' rectangle domain boxes.\n \"nvpad\": 0.2,\n \"titlesize\": 13\n } # vertical size of the 'enhanced' rectangle domain boxes.\n\n\n fig = plt.figure(figsize=p[\"figsize\"])\n\n ax = fig.add_subplot(211)\n axlab = fig.add_subplot(212)\n\n ax.set_position([0, 0.5, 1.0, 0.5])\n axlab.set_position([0, 0.0, 1.0, 0.60])\n\n ax.add_patch(Rectangle((0,-p[\"lpad\"]), item[\"len\"]-1, p[\"lpad\"]*2, ec=\"none\", fc=\"black\", color=\"black\")) # The line for the protein\n\n if self.fixed:\n ax.set_xlim([-p[\"pad1\"], item[\"len\"]+p[\"pad1\"]])\n axlab.set_xlim([-p[\"pad1\"], item[\"len\"]+p[\"pad1\"]])\n else:\n ax.set_xlim([-p[\"pad1\"], self.max_len+p[\"pad1\"]])\n axlab.set_xlim([-p[\"pad1\"], item[\"len\"]+p[\"pad1\"]])\n\n ax.set_ylim([-1, 1])\n\n axlab.set_ylim([0, 10])\n axlab.set_facecolor('none')\n\n if len(item[\"domains\"]) > 0:\n valid_styles[style](ax, axlab, item, p, thumb)\n\n if not thumb: # numbers showing the aa position of peptide\n tpad = p['pad1']/10\n ax.text(-tpad, 0, str(0), ha=\"right\", va=\"center\", fontsize=5, color=\"black\", zorder=100001)\n ax.text(item[\"len\"]+tpad, 0, item['len'], ha=\"left\", va=\"center\", fontsize=5, color=\"black\", zorder=100001)\n\n ax.set_xticklabels(\"\")\n ax.set_yticklabels(\"\")\n ax.set_ylabel(\"\")\n ax.set_xlabel(\"\")\n ax.tick_params(left=None, top=None, bottom=None, right=None)\n ax.set_frame_on(False)\n\n axlab.set_xticklabels(\"\")\n axlab.set_yticklabels(\"\")\n axlab.set_ylabel(\"\")\n axlab.set_xlabel(\"\")\n axlab.tick_params(left=None, top=None, bottom=None, right=None)\n axlab.set_frame_on(False)\n\n fig.savefig(filename)\n plt.close(fig) # Free up the memory","def write_file(self):\n if self.it_num % 5 == 0:\n #plt.imshow(self.grid)\n #plt.savefig(\"output%.4d.png\" % self.it_num, bbox_inches='tight')\n io.savemat(\"MLOutput%.4d\" % self.it_num, { \"Grid\":self.grid})","def hsep(self, width = 1, fg=None, bg=None, double=False):\n\n self.savepos()\n\n self.out.write(self._colorize((\"═\" if double else \"─\") * width, fg, bg))\n\n self.restorepos()","def saveImage(self, file_name='./out.jpg'):\n frame = self.camera.get_frame()\n color = frame.color_image[0]\n cv2.imwrite(file_name, color)\n cv2.imshow('frame', color)\n cv2.waitKey()\n cv2.destroyAllWindows()","def write2file(self, save_to):\n headerstyle = xlwt.easyxf(self.header_style.get_style_string())\n missing_val_style = xlwt.easyxf(\n self.missing_value_style.get_style_string())\n row_styles = [xlwt.easyxf(self.first_style.get_style_string()),\n xlwt.easyxf(self.second_style.get_style_string())]\n\n properties, sections, table = self._build_table()\n\n workbook = xlwt.Workbook()\n sheet = workbook.add_sheet(self.sheet_name)\n\n if os.path.splitext(save_to)[-1] == '':\n save_to += '.xls'\n\n max_col_len = []\n\n if (self.switch):\n\n for i, prop in enumerate([''] + properties):\n sheet.write(0, i, prop, headerstyle)\n max_col_len.append(len(str(prop)))\n\n for row_num, sec in enumerate(sections):\n sheet.write(row_num + 1, 0, sec, headerstyle)\n if len(str(sec)) > max_col_len[0]:\n max_col_len[0] = len(str(sec))\n\n for row_num, row in enumerate(table):\n for col_num, elem in enumerate(row):\n\n if elem is None:\n style = missing_val_style\n cell_content = \"\"\n else:\n style = row_styles[row_num % 2]\n cell_content = elem\n\n if isinstance(cell_content, datetime.datetime):\n style.num_format_str = \"DD-MM-YYYY HH:MM:SS\"\n elif isinstance(cell_content, datetime.date):\n style.num_format_str = \"DD-MM-YYYY\"\n elif isinstance(cell_content, datetime.time):\n style.num_format_str = \"HH:MM:SS\"\n else:\n style.num_format_str = \"\"\n\n sheet.write(row_num + 1, col_num + 1, cell_content, style)\n if len(str(cell_content)) > max_col_len[col_num+1]:\n max_col_len[col_num+1] = len(str(cell_content))\n\n else:\n\n for i, sec in enumerate([''] + sections):\n sheet.write(0, i, sec, headerstyle)\n max_col_len.append(len(str(sec)))\n\n for row_num, prop in enumerate(properties):\n sheet.write(row_num + 1, 0, prop, headerstyle)\n if len(str(prop)) > max_col_len[0]:\n max_col_len[0] = len(str(prop))\n\n for col_num, col in enumerate(table):\n for row_num, elem in enumerate(col):\n\n if elem is None:\n style = missing_val_style\n cell_content = \"\"\n else:\n style = row_styles[row_num % 2]\n cell_content = elem\n\n if isinstance(cell_content, datetime.datetime):\n style.num_format_str = \"DD-MM-YYYY HH:MM:SS\"\n elif isinstance(cell_content, datetime.date):\n style.num_format_str = \"DD-MM-YYYY\"\n elif isinstance(cell_content, datetime.time):\n style.num_format_str = \"HH:MM:SS\"\n else:\n style.num_format_str = \"\"\n\n sheet.write(row_num + 1, col_num + 1, cell_content, style)\n if len(str(cell_content)) > max_col_len[col_num+1]:\n max_col_len[col_num+1] = len(str(cell_content))\n\n # adjust width of he columns\n for col_id, col_len in enumerate(max_col_len):\n sheet.col(col_id).width = (256 * (col_len+1))\n\n workbook.save(save_to)","def save(self, filename, precision='%15.07e', encoding='utf-8'):\n\n # when creating empty st object, cols is not set yet\n if not hasattr(self, 'cols'):\n if self.main_data_sets[1][1].shape[1]==19:\n self.cols = stc.split()\n elif self.main_data_sets[1][1].shape[1]==30:\n self.cols = fpm.split()\n else:\n c = self.main_data_sets[1][1].shape[1]\n raise TypeError(f'St input needs 19 (iso) or 30 (aniso/fpm) cols, not {c}')\n\n colwidth = len(precision % 1)\n sep = '=' * colwidth * len(self.cols) + '\\n'\n colhead = ''.join([k.center(colwidth) for k in self.cols]) + '\\n'\n\n nsets = len(self.main_data_sets)\n # fails if dirname is empty string\n if len(os.path.dirname(filename)) > 0:\n os.makedirs(os.path.dirname(filename), exist_ok=True)\n with open(filename, 'w', encoding=encoding) as fid:\n fid.write('%i ; number of sets, Nset\\n' % nsets)\n for mset, set_data_dict in self.main_data_sets.items():\n fid.write('#%i ; set number\\n' % mset)\n for set, set_array in set_data_dict.items():\n dstr = self.to_str(mset=mset, set=set, precision=precision)\n npoints = self.main_data_sets[mset][set].shape[0]\n fid.write(sep + colhead + sep)\n fid.write('$%i %i\\n' % (set, npoints))\n fid.write(dstr + '\\n')","def new_file(name, style):\n with open(CSV_DIR / name, \"w\") as f:\n writer = csv.writer(f)\n if style:\n writer.writerow(cols_style)\n else:\n writer.writerow(cols)","def SaveHeight(self,val=0):\n if self.height_first_save:\n self.height_file = self.params.Save(self.height,\"height\",subfolder=\"functions/\",val=val)\n self.depth_file = self.params.Save(self.depth,\"depth\",subfolder=\"functions/\",val=val)\n self.height_first_save = False\n else:\n self.params.Save(self.height,\"height\",subfolder=\"functions/\",val=val,file=self.height_file)\n self.params.Save(self.depth,\"depth\",subfolder=\"functions/\",val=val,file=self.depth_file)","def save(self, filename):\n self.image.save(filename, self.options.img_format)","def border(self):\n ...","def saveWorld(self, filename):\n worldFile = open( filename, 'w' );\n worldFile.write( \"WIDTH {0}\\nHEIGHT {1}\\n\".format( self.mWidth, self.mHeight ) );\n\n for space in self.mSpaces:\n if isinstance(space, Circle):\n worldFile.write( \"SPACE circle {0} {1} {2}\\n\".format( space.X, space.Y, space.Radius ) );\n elif isinstance(space, Rect):\n worldFile.write( \"SPACE rect {0} {1} {2} {3}\\n\".format( space.X,space.Y,space.Width,space.Height ) );\n\n for obst in self.mObstMgr.mObstacles:\n if isinstance(obst,Circle):\n worldFile.write( \"OBSTACLE circle {0} {1} {2}\\n\".format( obst.X, obst.Y, obst.Radius ) );\n elif isinstance(obst,Rect):\n worldFile.write( \"OBSTACLE rect {0} {1} {2} {3}\\n\".format( obst.X,obst.Y,obst.Width,obst.Height ) );\n worldFile.close();\n pass;","def add_border(original_img,border_size):\r\n new_image=SimpleImage.blank(2 * border_size + original_img.width ,2 * border_size + original_img.height )\r\n\r\n \"\"\"\r\n Task 2: Creating black border\r\n \r\n \"\"\"\r\n for y in range(new_image.height):\r\n for x in range(new_image.width):\r\n\r\n # converting all the border pixels to black\r\n\r\n if x <= border_size or x >= border_size + original_img.height or y <= border_size or y >= border_size + original_img.width:\r\n\r\n px=new_image.get_pixel(x,y)\r\n px.red=0\r\n px.green=0\r\n px.blue=0\r\n\r\n # replacing the pixels other than the border with inage\r\n\r\n else:\r\n\r\n new_image.get_pixel(x,y).red=original_img.get_pixel(x-border_size, y-border_size).red\r\n new_image.get_pixel(x,y).blue = original_img.get_pixel(x - border_size, y - border_size).blue\r\n new_image.get_pixel(x,y).green = original_img.get_pixel(x - border_size, y - border_size).green\r\n\r\n\r\n return new_image","def OnSave(self, e):\n\t\tconvert_to = None\n\t\tif e.Id == 201:\n\t\t\tconvert_to = \"photoabsorption\"\n\t\telif e.Id == 202:\n\t\t\tconvert_to = \"refractive_index\"\n\t\tlogger.info(\"Save\")\n\t\tfd = wx.FileDialog(self, style=wx.FD_SAVE|wx.FD_OVERWRITE_PROMPT)\n\t\tif fd.ShowModal()==wx.ID_OK:\n\t\t\tmetadata = {\"Density\": float(self.DensityText.GetValue()), \"Molecular Formula\":self.StoichiometryText.GetValue(),\"Formula Mass\":data.calculate_FormulaMass(self.Stoichiometry)}\n\t\t\tdata.export_data(fd.GetPath(), numpy.transpose(numpy.vstack((self.Full_E,self.KK_Real_Spectrum,data.coeffs_to_ASF(self.Full_E,self.Imaginary_Spectrum)))), header_info=metadata, convert_to=convert_to)","def save(self, file):\n boulders = []\n elephants = []\n rhinos = []\n for i in range(5):\n for j in range(5):\n if self[i][j]!= 0:\n piece = self[i][j]\n L = []\n if not isinstance(self[i][j], Boulder):\n L.append(self[i][j].direction[0])\n L.append(self[i][j].direction[1])\n if piece.species == \"Elephant\":\n elephants.append(\"(\" + str(i) + \",\" + str(j)+ \") : np.array([\"+str(L[0])+ \",\" + str(L[1])+\"])\")\n elif piece.species == \"Rhinoceros\":\n rhinos.append(\"(\"+str(i)+\",\" +str(j)+ \") : np.array([\"+str(L[0]) + \",\" + str(L[1])+\"])\")\n elif isinstance(piece, Boulder):\n boulders.append(\"(\" + str(i) + \",\" + str(j) + \")\")\n file.write(\"# King of Siam GameFile \\n\\nplayer_turn {\\n \" + self.playerTurn + \"\\n}\\n\\n\")\n file.write(\"Boulder {\")\n for k in range(len(boulders)):\n file.write(\"\\n \" + boulders[k] + \";\")\n file.write(\"\\n}\\n\\nElephant {\")\n for elt in elephants:\n file.write(\"\\n \" + elt + \";\")\n file.write(\"\\n}\\n\\nRhinoceros {\")\n for elt in rhinos:\n file.write(\"\\n \" + elt + \";\")\n file.write(\"\\n}\")\n\n file.close()","def write_flow(flow, filename):\n f = open(filename, 'wb')\n magic = numpy.array([202021.25], dtype=numpy.float32)\n (height, width) = flow.shape[0:2]\n w = numpy.array([width], dtype=numpy.int32)\n h = numpy.array([height], dtype=numpy.int32)\n magic.tofile(f)\n w.tofile(f)\n h.tofile(f)\n flow.tofile(f)\n f.close()","def __init__(self, width, height):\r\n super().__init__(width, height)\r\n \r\n self.file = open(\"drawing.c\", \"w\")\r\n self.held_keys = set()\r\n arcade.set_background_color(arcade.color.WHITE)\r\n self.cursor = [Cursor()]\r\n self.record = []","def save(self):\n Preferences.setVCS(\n \"AutoClose\",\n self.vcsAutoCloseCheckBox.isChecked())\n Preferences.setVCS(\n \"AutoSaveFiles\",\n self.vcsAutoSaveCheckBox.isChecked())\n Preferences.setVCS(\n \"AutoSaveProject\",\n self.vcsAutoSaveProjectCheckBox.isChecked())\n Preferences.setVCS(\n \"StatusMonitorInterval\",\n self.vcsStatusMonitorIntervalSpinBox.value())\n Preferences.setVCS(\n \"MonitorLocalStatus\",\n self.vcsMonitorLocalStatusCheckBox.isChecked())\n Preferences.setVCS(\n \"AutoUpdate\",\n self.autoUpdateCheckBox.isChecked())\n \n self.saveColours(Preferences.setProjectBrowserColour)","def brandify_img(img, img_name, border_width_percentage=0.10, \\\nborder_width_cap=150, inner_border_width=7, \\\ninner_border_color=(50, 255, 50, 0), outer_border_color=(50, 50, 50, 0)):\n if img_name.startswith(\"Modified-\"):\n return\n width = img.size[0]\n height = img.size[1]\n # A new image that will be embiggened to fit the border\n border_width = int(float(width + height) / 2 * border_width_percentage)\n if border_width > border_width_cap:\n border_width = border_width_cap\n total_width = width + border_width * 2\n total_height = height + border_width * 2\n img.convert(mode=\"RGBA\")\n bordered_img = PIL.Image.new(\"RGBA\", img.size)\n bordered_img = PIL.ImageOps.expand(img, border=border_width)\n draw = PIL.ImageDraw.Draw(bordered_img)\n \n # Fill in the border for the image\n # The inner part of the border will be later covered up by the image itself\n draw_border_gradient(bordered_img, center_color=inner_border_color, \\\n outer_color=outer_border_color, excluding_region=(border_width, \\\n width + border_width, border_width, height + border_width))\n \n # Inner border\n # \"bb\" stands for border for border\n bb_color = (255 - 50, 255 - 50, 255 - 50, 255)\n draw.rectangle((border_width - inner_border_width, border_width - \\\n inner_border_width, width + border_width + inner_border_width, height + \\\n border_width + inner_border_width), fill=bb_color)\n \n # Add the original image\n bordered_img.paste(img, (border_width, border_width, width + border_width, \\\n height + border_width))\n \n # Add some basic design to the border\n # Add lines on each corner\n # Order is top left, top right, bottom left, bottom right\n draw.line((0, 0, border_width, border_width), fill=bb_color, width=3)\n draw.line((total_width, 0, total_width - border_width, border_width), \\\n fill=bb_color, width=3)\n draw.line((0, total_height, border_width, total_height - border_width), \\\n fill=bb_color, width=3)\n draw.line((total_width, total_height, total_width - border_width, \\\n total_height - border_width), fill=bb_color, width=3)\n \n # Apply the brand image\n new_width = int((float(brand_image.size[0]) / brand_image.size[1]) * \\\n border_width)\n new_height = border_width - inner_border_width\n resized_img = brand_image.resize((new_width, new_height))\n bordered_img.paste(resized_img, box=((width - resized_img.size[0] / 2) \\\n / 2, 0), mask=resized_img)\n \n bordered_img.save(image_directory + os.sep + \"Modified-\" + img_name)","def save(self, filename, path = False,\n squash = False, verbose = True, *args, **kwargs):\n\n if hasattr(self, \"wavelength\") and hasattr(self, \"throughput\"): ## enables resampling and wavelength conversion to be easily saved\n if verbose: print(\"has data\")\n if not path:\n if verbose: print(\"No directory specified, assuming \" + defaults._default_filter_dir_path)\n path = defaults._default_filter_dir_path\n else:\n errors.StringWarning(path)\n\n outpath = os.path.join(path, filename)\n\n utils.check_dir_path(path)\n\n if os.path.isfile(outpath):\n warnings.warn(\"Found existing file matching \" + path + \". Run with squash = True to overwrite\")\n if squash:\n print(\"Overwriting \" + outpath)\n outtable = Table([self.wavelength, self.throughput], names = [\"wavelength\", \"throughput\"])\n outtable.write(outpath, format = \"ascii.fast_commented_header\", overwrite = True)\n self._format_for_save = outtable\n\n\n else:\n print(\"Writing \" + outpath)\n outtable = Table([self.wavelength, self.throughput], names = [\"wavelength\", \"throughput\"])\n\n outtable.write(outpath, format = \"ascii.fast_commented_header\")\n self._format_for_save = outtable\n\n else:\n warnings.warn(\"Doesn't seem to be any data here (empty self.data)\")\n pass","def write_flow(flow, filename):\n f = open(filename, 'wb')\n magic = np.array([202021.25], dtype=np.float32)\n (height, width) = flow.shape[0:2]\n w = np.array([width], dtype=np.int32)\n h = np.array([height], dtype=np.int32)\n magic.tofile(f)\n w.tofile(f)\n h.tofile(f)\n flow.tofile(f)\n f.close()","def save_bbox(tensor, box, filename, nrow=8, padding=0,\n normalize=False, scale_each=False, pad_value=0, draw_line=False, save=True):\n from PIL import Image\n \n # print(box)\n # assert False\n\n grid = make_grid_bbox(tensor, box, nrow=nrow, padding=padding, pad_value=pad_value,\n normalize=normalize, scale_each=scale_each, draw_line=draw_line)\n\n # Add 0.5 after unnormalizing to [0, 255] to round to nearest integer\n # ndarr = grid.mul_(255).add_(0.5).clamp_(0, 255).permute(1, 2, 0).to('cpu', torch.uint8).numpy()\n ndarr = grid.mul_(13).add_(0.5).clamp_(0, 13).permute(1, 2, 0).to('cpu', torch.uint8).numpy()\n\n # colorize the gray images\n # ndarr = cv2.applyColorMap(cv2.convertScaleAbs(ndarr, alpha=20.0), cv2.COLORMAP_JET)\n palette = []\n for i in range(256):\n palette.extend((255, 255, 255))\n palette[:3*14] = np.array([[84, 139, 84],\n [0, 100, 0],\n [0, 0, 128],\n [85, 26, 139],\n [255, 0, 255],\n [165, 42, 42],\n [139, 134, 130],\n [205, 198, 115],\n [139, 58, 58],\n [255, 255, 255],\n [0, 0, 0],\n [30, 144, 255],\n [135, 206, 235],\n [255, 255, 0]], dtype='uint8').flatten()\n\n # # draw box\n # ndarr = draw_box(ndarr, box, palette)\n\n im = Image.fromarray(ndarr).convert('L')\n # colorize\n im.putpalette(palette)\n if save:\n im.save(filename)\n else:\n return im","def create_regfile(userinput, x, y, filename, color='blue', width=2):\n target_dir = userinput['OUTDIR']\n outputfile = target_dir + '/s_extraction/{}'.format(filename)\n\n logging.info('Writing region file {}'.format(filename))\n\n with open(outputfile, 'w') as file:\n file.write('global color={} width={} font=\"helvetica 15 normal roman\" highlite=1 \\n'\\\n .format(color,width))\n file.write('image\\n')\n\n for i in range(len(x)):\n newline = 'circle(' + str(x[i]) + ',' + str(y[i]) + ',7) \\n'\n file.write(newline)","def save_as_fits(self, filename):","def savefig(filename, leg=None, format='.eps', *args, **kwargs):\n if leg:\n art=[leg]\n plt.savefig(filename + format, additional_artists=art, bbox_inches=\"tight\", *args, **kwargs)\n else:\n plt.savefig(filename + format, bbox_inches=\"tight\", *args, **kwargs)\n plt.close()","def write_version_file(version):\n try:\n git_log = subprocess.check_output(\n ['git', 'log', '-1', '--pretty=%h %ai']).decode('utf-8')\n git_diff = (subprocess.check_output(['git', 'diff', '.']) +\n subprocess.check_output(\n ['git', 'diff', '--cached', '.'])).decode('utf-8')\n if git_diff == '':\n git_status = '(CLEAN) ' + git_log\n else:\n git_status = '(UNCLEAN) ' + git_log\n except Exception as e:\n print(\"Unable to obtain git version information, exception: {}\"\n .format(e))\n git_status = ''\n\n version_file = '.version'\n if os.path.isfile(version_file) is False:\n with open('bilby/' + version_file, 'w+') as f:\n f.write('{}: {}'.format(version, git_status))\n\n return version_file","def reset(self) -> None:\n self.file.write(\"\\b\" * (len(self.current_frame) + self.current_padding))","def predefined_style(self, style):\n if style == 'minimal':\n self.style(box_style='', border_visible=True, border_colour='black',\n border_style='solid', border_width=1, border_radius=0,\n padding='0.2cm', margin='0.3cm', font_family='',\n font_size=None, font_style='', font_weight='')\n self.save_button.button_style = ''\n self.save_button.font_weight = 'normal'\n elif (style == 'info' or style == 'success' or style == 'danger' or\n style == 'warning'):\n self.style(box_style=style, border_visible=True,\n border_colour= map_styles_to_hex_colours(style),\n border_style='solid', border_width=1, border_radius=10,\n padding='0.2cm', margin='0.3cm', font_family='',\n font_size=None, font_style='', font_weight='')\n self.save_button.button_style = 'primary'\n self.save_button.font_weight = 'bold'\n else:\n raise ValueError('style must be minimal or info or success or '\n 'danger or warning')","def close(self, event, data):\n try:\n with open(self.save_file, \"w+\") as save_file:\n try:\n data = json.load(save_file)\n except ValueError:\n data = dict()\n data[\"color\"] = rgb_to_hex(self.rgb_color)\n json.dump(data, save_file)\n except (OSError, json.JSONDecodeError):\n print(\"Error when trying to set save file.\")\n Gtk.main_quit()","def write( self, NewFilename='', Integer=True ):\n try:\n if NewFilename != '':\n self.name=NewFilename\n Output = open( self.name, 'w' )\n Output.write( 'ncols\\t\\t %d\\n' % self.ncols )\n Output.write( 'nrows\\t\\t %d\\n' % self.nrows )\n Output.write( 'xllcorner\\t\\t %f\\n' % self.xllcorner)\n Output.write( 'yllcorner\\t\\t %f\\n' % self.yllcorner)\n Output.write( 'cellsize\\t\\t %f\\n' % self.cellsize)\n if Integer:\n Output.write( 'NODATA_value\\t\\t %d\\n' % int(self.nodata) )\n else:\n Output.write( 'NODATA_value\\t\\t %f\\n' % self.nodata )\n for row in range( self.nrows-1,-1,-1 ):\n record = []\n for col in range( self.ncols ):\n if Integer:\n record.append( str( int( round( self.data[row,col]) ) ) )\n else:\n record.append( str(self.data[row,col]) )\n Output.write( string.join(record, ' ')+'\\n' )\n Output.close()\n except:\n print \"Error writing grid ::\", self.name","def LHCbStyle_alt ( name = \"LHCbStyle\" ,\n desc = \"Standard LHCb plots style\" ,\n lineWidth = lhcbWidth ,\n font = lhcbFont ,\n makeNew = False ,\n force = True ) :\n obj = ROOT.gROOT.FindObject ( name )\n if obj and issubclass ( type( obj ) , ROOT.TStyle ) and not makeNew : \n logger.info ('The style %s is reused' % obj.GetName() )\n if force : \n logger.info ('The style %s is forced' % obj.GetName() )\n ROOT.gROOT.SetStyle ( obj.GetName() )\n ROOT.gROOT.ForceStyle ( )\n return obj\n \n nam = name\n i = 1\n while obj :\n nam = name + '_%d' % i\n obj = ROOT.gROOT.FindObject ( nam )\n i += 1\n \n style = ROOT.TStyle ( nam , desc )\n logger.info ('New style %s is created' % style.GetName() )\n \n ## use plain black on white colors\n style . SetFrameBorderMode ( 0 )\n style . SetCanvasBorderMode ( 0 )\n style . SetPadBorderMode ( 0 )\n style . SetPadColor ( 0 )\n style . SetCanvasColor ( 0 )\n style . SetStatColor ( 0 )\n # style . SetPalette ( 1 )\n # style . SetTitleStyle ( 0 )\n ## set the paper & margin sizes\n style . SetPaperSize ( 20 , 26 )\n style . SetPadTopMargin ( 0.05 )\n style . SetPadRightMargin ( 0.05 ) ## increase for colz plots\n style . SetPadBottomMargin ( 0.16 )\n style . SetPadLeftMargin ( 0.14 )\n \n ## use large fonts\n style . SetTextFont ( font )\n style . SetTextSize ( 0.08 )\n style . SetLabelFont ( font , \"x\" ) \n style . SetLabelFont ( font , \"y\" ) \n style . SetLabelFont ( font , \"z\" ) \n style . SetLabelSize ( 0.05 , \"x\" )\n style . SetLabelSize ( 0.05 , \"y\" )\n style . SetLabelSize ( 0.05 , \"z\" )\n style . SetTitleFont ( font )\n style . SetTitleSize ( 0.06 , \"x\" )\n style . SetTitleSize ( 0.06 , \"y\" )\n style . SetTitleSize ( 0.06 , \"z\" ) \n \n \n ## use bold lines and markers\n style . SetLineWidth ( lineWidth )\n style . SetFrameLineWidth ( lineWidth )\n style . SetHistLineWidth ( lineWidth )\n style . SetFuncWidth ( lineWidth )\n style . SetGridWidth ( lineWidth )\n style . SetLineStyleString ( 2 , \"[12 12]\" ) ## postscript dashes\n #style . SetMarkerStyle ( 20 )\n style . SetMarkerSize ( 1.2 )\n \n ## label offsets\n style . SetLabelOffset(0.015);\n \n ## by default, do not display histogram decorations:\n style . SetOptStat ( 0 ) \n ## lhcbStyle->SetOptStat(\"emr\"); ## show only nent -e , mean - m , rms -r\n ## full opts at http://root.cern.ch/root/html/TStyle.html#TStyle:SetOptStat\n style . SetStatFormat (\"6.3g\") ## specified as c printf options\n # style . SetOptTitle ( 1 )\n style . SetOptFit ( 0 )\n ## lhcbStyle . SetOptFit(1011); // order is probability, Chi2, errors, parameters\n \n\n ## look of the statistics box:\n style . SetStatBorderSize ( 0 )\n style . SetStatFont ( font )\n # style . SetStatFontSize ( 0.05 )\n # style . SetStatX ( 0.9 )\n # style . SetStatY ( 0.9 )\n # style . SetStatW ( 0.25 )\n # style . SetStatH ( 0.15 )\n ## put tick marks on top and RHS of plots\n style . SetPadTickX ( 1 )\n style . SetPadTickY ( 1 )\n \n## histogram divisions: only 5 in x to avoid label overlaps\n style . SetNdivisions ( 505 , \"x\" )\n style . SetNdivisions ( 510 , \"y\" )\n \n if force : \n logger.info ('The style %s is forced' % style.GetName() )\n ROOT.gROOT.SetStyle ( style.GetName() )\n ROOT.gROOT.ForceStyle ()\n \n return style","def _write(self, stream):\n\n self._img.append(self.make_path())\n self._img.append(self.make_border())\n self._img.append(self.make_text())\n\n ET.ElementTree(self._img).write(stream, encoding=\"UTF-8\", xml_declaration=True)","def add_border(self, color='white', width=2.0):\n points = np.array([[1.0, 1.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 0.0], [1.0, 0.0, 0.0]])\n\n lines = np.array([[2, 0, 1], [2, 1, 2], [2, 2, 3], [2, 3, 0]]).ravel()\n\n poly = pyvista.PolyData()\n poly.points = points\n poly.lines = lines\n\n coordinate = _vtk.vtkCoordinate()\n coordinate.SetCoordinateSystemToNormalizedViewport()\n\n mapper = _vtk.vtkPolyDataMapper2D()\n mapper.SetInputData(poly)\n mapper.SetTransformCoordinate(coordinate)\n\n actor = _vtk.vtkActor2D()\n actor.SetMapper(mapper)\n actor.GetProperty().SetColor(Color(color).float_rgb)\n actor.GetProperty().SetLineWidth(width)\n\n self.AddViewProp(actor)\n self.Modified()\n\n self._border_actor = actor\n return actor","def save_image(self):\n # open the dialog and get the selected file\n file_one = QtGui.QFileDialog.getSaveFileName(\n self,\n QtGui.QApplication.translate(\n \"MainWindow\", \n \"Supported formats:\", \n None, \n QtGui.QApplication.UnicodeUTF8)+\n \" emf, eps, pdf, png, ps, raw, rgba, svg, svgz\", \n \"\",\n \"Enhanced MetaFile \\t.emf (*.emf);; \"+\n \"Encapsulated PostScript \\t.eps (*.eps);; \"+\n \"Portable Document Format \\t.pdf (*.pdf);; \"+\n \"Portable Network Graphics \\t.png (*.png);;\"+\n \"PostScript \\t.ps (*.ps);; \"+\n \"RAW image file \\t.raw (*.raw);; \"+\n \"Red Green Blue Alpha \\t.rgba (*.rgba);; \"+\n \"Scalable Vector Graphics \\t.svg (*.svg);; \"+\n \"Scalable Vector Graphics compressed \\t.svgz (*.svgz)\")\n # if a file is selected\n if file_one:\n # update the lineEdit text with the selected filename\n self.textBrowser.append(\n QtGui.QApplication.translate(\n \"MainWindow\", \n \"Saving to \", \n None, \n QtGui.QApplication.UnicodeUTF8\n )+file_one)\n\n plt.clf()\n # adding different plots if required\n if self.checkBox_R.isChecked():\n lines = plt.plot(self.graf_t, self.graf_r)\n plt.setp(lines[0], \n lw=1, \n label=str(\n QtGui.QApplication.translate(\n \"MainWindow\", \n \"Reference\", \n None, \n QtGui.QApplication.UnicodeUTF8)), \n color = 'blue')\n \n if self.checkBox_U.isChecked():\n lines = plt.plot(self.graf_t, self.graf_u)\n plt.setp(lines[0], \n lw=2, \n label=str(\n QtGui.QApplication.translate(\n \"MainWindow\", \n \"Input\", \n None, \n QtGui.QApplication.UnicodeUTF8)), \n color='red')\n \n if self.checkBox_x1.isChecked():\n lines = plt.plot(self.graf_t, self.graf_x1)\n plt.setp(lines[0], \n lw=1, \n label=str(\n QtGui.QApplication.translate(\n \"MainWindow\", \n \"First Int.\", \n None, \n QtGui.QApplication.UnicodeUTF8)), \n color='grey')\n \n if self.checkBox_x0.isChecked():\n lines = plt.plot(self.graf_t, self.graf_x0)\n plt.setp(lines[0], \n lw=2, \n label=str(\n QtGui.QApplication.translate(\n \"MainWindow\", \n \"Second Int.\", \n None, \n QtGui.QApplication.UnicodeUTF8)), \n color='orange')\n\n plt.axis([self.graf_t[0], self.graf_t[-1], -3, 3])\n \n plt.title(str(\n QtGui.QApplication.translate(\n \"MainWindow\", \n \"Double Integrator\", \n None, \n QtGui.QApplication.UnicodeUTF8)))\n \n plt.suptitle(str(\n QtGui.QApplication.translate(\n \"MainWindow\", \n \"Networked and Embedded Control Systems:\", \n None, \n QtGui.QApplication.UnicodeUTF8)))\n \n plt.xlabel(str(\n QtGui.QApplication.translate(\n \"MainWindow\", \n \"t (s)\", \n None, \n QtGui.QApplication.UnicodeUTF8)))\n \n plt.ylabel(str(\n QtGui.QApplication.translate(\n \"MainWindow\", \n \"Voltage (V)\", \n None, \n QtGui.QApplication.UnicodeUTF8)))\n \n plt.legend(bbox_to_anchor=(0, 1, 1, 0), loc=1, ncol=6, mode=\"expand\", borderaxespad=0.)\n \n filename = str(file_one)# + '.svg'\n try:\n plt.savefig(filename, dpi=300)\n except ValueError as e:\n print(e)\n self.textBrowser.append(str(e))\n self.textBrowser.append(\n QtGui.QApplication.translate(\n \"MainWindow\", \n \"Trying to save as .svg\", \n None, \n QtGui.QApplication.UnicodeUTF8))\n \n filename = str(file_one) + '.svg'\n plt.savefig(filename, dpi=300)\n pass\n except ImportError as e:\n print(e)\n self.textBrowser.append(str(e))\n self.textBrowser.append(\n QtGui.QApplication.translate(\n \"MainWindow\", \n \"Trying to save as .svg\", \n None, \n QtGui.QApplication.UnicodeUTF8))\n \n filename = str(file_one) + '.svg'\n plt.savefig(filename, dpi=300)\n pass\n except:\n self.textBrowser.append(\"Error al guardar la imatge\")\n \n plt.clf()","def save(self):\n filename = os.path.expanduser(\"~/\" + self.name)\n print(filename)\n np.savetxt(filename + \"_left.txt\", self.central)\n np.savetxt(filename + \"_right.txt\", self.boundaries)","def write_bgf(self, filename):\n body = [\"BIOGRF{0:>5s}\\n\".format(self.biogrf)]\n if self.descrp:\n body.append(\"DESCRP {0}\\n\".format(self.descrp))\n else:\n body.append(\"DESCRP {0}\\n\".format(filename))\n body.append(\"FORCEFIELD {0}\\n\".format(self.ff))\n body.append(\"FORMAT ATOM (a6,1x,i5,1x,a5,1x,a3,1x,a1,1x,a5,3f10.5\"\n \",1x,a5,i3,i2,1x,f8.5,i2,i4,f10.5)\\n\")\n atoms = []\n hetatms = []\n conect = []\n for atom in self.atoms:\n a, c = atom.writeline()\n if atom.record == 'ATOM':\n atoms.append(a)\n elif atom.record == 'HETATM':\n hetatms.append(a)\n conect.append(c)\n body.extend(atoms)\n body.extend(hetatms)\n body.append(\"FORMAT CONECT (a6,14i6)\\nFORMAT ORDER (a6,i6,13f6.3)\\n\")\n body.extend(conect)\n body.append(\"END\\n\")\n with open(filename, 'w') as f:\n f.writelines(body)","def save_image(self, file_obj):\n manager = pyglet.image.get_buffer_manager()\n colorbuffer = manager.get_color_buffer()\n\n # if passed a string save by name\n if hasattr(file_obj, 'write'):\n colorbuffer.save(file=file_obj)\n else:\n colorbuffer.save(filename=file_obj)","def save(self, fileName, *args):\n if self._renderRequired:\n self.render()\n self.qimage.save(fileName, *args)","def on_save(self, event):\n file_choices = \"PNG (*.png)|*.png\"\n \n dlg = wx.FileDialog(\n self, \n message=\"Save plot as...\",\n defaultDir=os.getcwd(),\n defaultFile=\"plot.png\",\n wildcard=file_choices,\n style=wx.SAVE)\n \n if dlg.ShowModal() == wx.ID_OK:\n path = dlg.GetPath()\n self.canvas.print_figure(path, dpi=self.dpi)\n self.flash_status_message(\"Saved to %s\" % path)","def save_as(\n cls, figure_or_data, filename, format=None, width=None, height=None, scale=None\n ):\n # todo: format shadows built-in name\n (base, ext) = os.path.splitext(filename)\n if not ext and not format:\n filename += \".png\"\n elif ext and not format:\n format = ext[1:]\n elif not ext and format:\n filename += \".\" + format\n\n img = cls.get(figure_or_data, format, width, height, scale)\n\n f = open(filename, \"wb\")\n f.write(img)\n f.close()","def saveView(self, filename):\n\n pixmap = self.grab();\n ok = pixmap.save(filename)\n if not ok:\n raise IOError('Unable to save image ' + filename)","def write (self, file):\n\t\tfile.write (self.pack ())","def shape_writer(f):\n\n # extract the file extension\n _, ext = os.path.splitext(f)\n\n # if the file is a dxf then parse it otherwise\n # loads it as a pickle\n if ext.lower() == \".dxf\":\n dxf = dxfParser.parse(f)\n shapes = []\n rects = []\n for s in dxf:\n bounding_rect = s.cutPolyline.getBoundsRectanglePolyline()\n rects.append(bounding_rect)\n bounds = s.cutPolyline.getBounds()\n tx = -bounds[\"left\"]\n ty = -bounds[\"bottom\"]\n s.cutPolyline.translatePoly(tx, ty)\n shapes.append(s.cutPolyline.polylineToTuple())\n\n else: # if it's a pickle file\n with open(f, \"rb\") as file:\n dxf = pkl.load(file)\n dxf = dxf[0]\n shapes = []\n rects = []\n for s in dxf:\n # same flow but shapes has no cutPolyline()\n bounding_rect = s.getBoundsRectanglePolyline()\n rects.append(bounding_rect)\n bounds = s.getBounds()\n tx = -bounds[\"left\"]\n ty = -bounds[\"bottom\"]\n s.translatePoly(tx, ty)\n shapes.append(s.polylineToTuple())\n\n for i, shape in enumerate(shapes):\n h = int(rects[i].coords[3][1] - rects[i].coords[1][1])\n w = int(rects[i].coords[2][0] - rects[i].coords[0][0])\n # create a blank image\n img = np.zeros((h + 10, w + 10), dtype=np.uint8)\n img.fill(255)\n\n polyx = []\n polyy = []\n\n for coords in shape:\n polyx.append(coords[0] + 5)\n polyy.append(coords[1] + 5)\n\n pts = np.vstack((polyx, polyy)).astype(np.int32).T\n\n cv2.polylines(img, [pts], 0, 0, thickness=1)\n if ext.lower() == \".dxf\":\n cv2.imwrite(f\"{SOURCE_PATH}shape_{i}.png\", img)\n else:\n cv2.imwrite(f\"{PROD_PATH}\\\\shape_{i}.png\", img)","def part1(width, height, size, color):\n pass","def save(self, filename):\n o = open(filename, 'w')\n o.write(self.write())\n o.close()","def fileResizeObscure(new_filepath):\n # Resize\n img1 = Image.open(new_filepath)\n img2=image_reduce(img1)\n *** Stopped working here\n newpath=\"toupload\\\\%s\" % new_filepath\n # Block ID\n width=img2.size[0]\n height=img2.size[1]\n # Obscuring params were decided by trial and error using fraction of width and height\n x1=int(0.16*width)\n x2=int(0.28*width)\n y1=int(0.94*height)\n y2=int(0.98*height) \n # Faster but easier to snoop? should not be since it changes the pixels\n draw = ImageDraw.Draw(img2)\n draw.rectangle([(x1,y1),(x2,y2)],fill=\"white\")\n del draw\n \n img2.save(newpath,optimize=True,quality=95)","def save(self, filename):\n result = self.render()\n\n with open(filename, 'w') as f:\n f.write(result)","def save_frame(self, save_path_filename):\n raise NotImplementedError","def write_file(self,filename):\n \n with open(filename, 'w') as f:\n tab_width = np.max([len(k) for k in self.header.keys()])\n for k,v in self.header.items():\n f.write(u'{0}:\\t{1}\\n'.format(k, v).encode('utf8').expandtabs(tab_width+2))\n np.savetxt(f, self.data, fmt ='%f %f %f %d')","def on_export(self):\n path = os.path.dirname(os.path.realpath(__file__))\n\n filters = ('Portable Network Graphics (*.png);;'\n 'Portable Document Format (*.pdf);;'\n 'Postscript (*.ps);;'\n 'Encapsulated Postscript (*.eps);;'\n 'Scalable Vector Graphics (*.svg)')\n\n filename = QtGui.QFileDialog.getSaveFileName(self,\n caption='Export figure',\n directory=path,\n filter=filters)\n filename = str(filename)\n\n if filename != '':\n previous_size = self.fig.get_size_inches()\n self.fig.set_size_inches(float(self.le_width.text()),\n float(self.le_height.text()))\n\n dpi = int(self.le_dpi.text())\n\n self.fig.savefig(filename, dpi=dpi, bbox_inches='tight')\n self.fig.set_size_inches(previous_size)\n\n self.canvas.draw()","def predefined_style(self, style):\n if style == 'minimal':\n self.style(box_style='', border_visible=True, border_color='black',\n border_style='solid', border_width=1, border_radius=0,\n padding='0.2cm', margin='0.3cm', font_family='',\n font_size=None, font_style='', font_weight='')\n self.save_button.button_style = ''\n self.save_button.font_weight = 'normal'\n elif (style == 'info' or style == 'success' or style == 'danger' or\n style == 'warning'):\n self.style(box_style=style, border_visible=True,\n border_color= _map_styles_to_hex_colours(style),\n border_style='solid', border_width=1, border_radius=10,\n padding='0.2cm', margin='0.3cm', font_family='',\n font_size=None, font_style='', font_weight='')\n self.save_button.button_style = 'primary'\n self.save_button.font_weight = 'bold'\n else:\n raise ValueError('style must be minimal or info or success or '\n 'danger or warning')","def save_as(self, filename):\n opencv.imwrite(filename, self.img)"],"string":"[\n \"def save_visualization_to_file(self, file_name, length = 90):\\n session = self.capture_last(length)\\n visualizer.animate(session , 0, length, name = file_name, min_x = -1, max_x = 1, min_y = -1, max_y = 1, show = False )\",\n \"def write(self, file_name, width=1500.0, height=1000.0):\\n with open(file_name, 'wb+') as fh:\\n fh.write(self.make(width, height))\",\n \"def write(self, file_name, width=1500.0, height=1000.0):\\n with open(file_name, 'w+') as fh:\\n fh.write(self.make(width, height))\",\n \"def saveOutlined(self, filepath: str):\\n\\n if self.outlined is None:\\n print('No intermidiary image, try run find first')\\n return\\n self.save(filepath, self.outlined)\",\n \"def write(self, fileW):\\n fileW.wByte(self.b)\\n fileW.wByte(self.g)\\n fileW.wByte(self.r)\\n fileW.wByte(self.a)\",\n \"def save(self, output_path: str, box_thickness: int = 2, show_confidence: bool = True, color_mapping: Optional[List[Tuple[int, int, int]]] = None) -> None:\\n frames = self.draw(box_thickness=box_thickness, show_confidence=show_confidence, color_mapping=color_mapping)\\n save_video(output_path=output_path, frames=frames, fps=self.fps)\",\n \"def saveLightcurve(self, filename):\\n lfile = open(filename, 'w')\\n lfile.write(\\\"# time \\\\t counts \\\\t countrate \\\\n\\\")\\n for t,c,cr in zip(self.time, self.counts, self.countrate):\\n lfile.write(str(t) + \\\"\\\\t\\\" + str(c) + \\\"\\\\t\\\" + str(cr) + \\\"\\\\n\\\")\\n lfile.close()\",\n \"def write(self, fileW):\\n fileW.wShort(self.x)\\n fileW.wShort(self.y)\",\n \"def on_save_style_clicked(self, obj):\\n name = cuni(self.top.get_object(\\\"style_name\\\").get_text())\\n\\n self.save_paragraph()\\n self.style.set_name(name)\\n self.parent.sheetlist.set_style_sheet(name, self.style)\\n self.parent.redraw()\\n self.window.destroy()\",\n \"def Save(self, app, pad):\\n data = pad.get('1.0', GUI.END)[:-1]\\n try:\\n f = open(File.path, 'w')\\n f.write(data)\\n f.close()\\n except IOError:\\n f = open('untitled.cpp', 'w')\\n f.write(data)\\n f.close()\\n return -1\",\n \"def printfile(self, event=None):\\n filename = self.en.get()\\n bbox = self.canvas.bbox(ALL)\\n width=bbox.right*self.unit\\n height=bbox.bottom*self.unit\\n self.canvas.config(width=width, height=height)\\n self.canvas.dump(filename)\\n self.canvas.config(width=self.ca_width, height=self.ca_height)\\n self.la.config(text='Wrote file ' + filename)\",\n \"def save_file(self, _filename):\\n imgsize = (self.__resolution[0], self.__resolution[1])\\n print imgsize\\n\\n if(self.__resolution[2] == 1):\\n # grayscale -> convert to RGB\\n bg_white = (255, 255, 255)\\n img = Image.new(\\\"RGB\\\", imgsize, bg_white)\\n\\n for x in xrange(0, self.__resolution[0], 1):\\n for y in xrange(0, self.__resolution[1], 1):\\n col = self.get_color(_pos)\\n # duplicate the channels\\n ucharcol = (255 * col[0], 255 * col[0], 255 * col[0])\\n img.putpixel((x, self.__resolution[1] - y - 1), ucharcol)\\n\\n elif(self.__resolution[2] == 3):\\n # RGB\\n bg_white = (255, 255, 255)\\n img = Image.new(\\\"RGB\\\", imgsize, bg_white)\\n\\n for x in xrange(0, self.__resolution[0], 1):\\n for y in xrange(0, self.__resolution[1], 1):\\n col = self.get_color(_pos)\\n ucharcol = (255 * col[0], 255 * col[1], 255 * col[2])\\n img.putpixel((x, self.__resolution[1] - y - 1), ucharcol)\\n\\n elif(self.__resolution[2] == 4):\\n # RGBA\\n bg_white = (255, 255, 255, 255)\\n img = Image.new(\\\"RGBA\\\", imgsize, bg_white)\\n\\n for x in xrange(0, self.__resolution[0], 1):\\n for y in xrange(0, self.__resolution[1], 1):\\n col = 255 * self.get_color((x, y))\\n ucharcol = (int(col[0]), int(col[1]), int(col[2]), int(col[3]))\\n img.putpixel((x, self.__resolution[1] - y - 1), ucharcol)\\n else:\\n raise StandardError, ('supported number of channels are 1, 3, and 4, only.')\\n\\n img.save(_filename)\",\n \"def accept(self):\\n global fileName, origheight, origwidth\\n border=size=style=alt=title=\\\"\\\"\\n\\n alt=str(self.le_alt.text())\\n\\n if self.le_title.text():\\n title='title=\\\"'+str(self.le_title.text())+'\\\"'\\n\\n #If size has changed, put it\\n if not str(origheight)==str(self.le_height.text()) or not str(origwidth)==str(self.le_width.text()):\\n size=' width=\\\"'+str(self.le_width.text())+'\\\" height=\\\"'+str(self.le_height.text())+'\\\"'\\n #Put to code Border options if has selected\\n if self.ch_border.isChecked():\\n global bordercolor\\n #TODO: LINE EDIT DOES NOT HAVE SUPPORT TO BORDERCOLOR ON IMAGES\\n border=' border=\\\"'+str(self.sb_border_width.value())+'\\\"'\\n style=style+\\\" border-style: \\\"+self.cb_style.currentText().toLower()+\\\" ; border: \\\"+str(self.sb_border_width.value())+\\\"px \\\"+bordercolor.name()+\\\"; \\\"\\n #If any has style parameters, define it\\n if style<>\\\"\\\":\\n style=' style=\\\"'+style+'\\\"'\\n\\n camino,fichero=os.path.split(str(fileName))\\n imgcode=\\\"<img \\\"+title+' src=\\\"img'+os.sep+fichero+'\\\" '+size+border+style+\\\" >\\\"+alt+\\\"</img>\\\"\\n self.emit(SIGNAL(\\\"imgcode\\\"), imgcode,fileName)\\n self.close()\",\n \"def write(self, filename):\\n f = open(filename, 'bw')\\n\\n # file header (14)\\n f.write(char('B'))\\n f.write(char('M'))\\n f.write(dword(14 + 40 + self.width * self.height * 3))\\n f.write(dword(0))\\n f.write(dword(14 + 40))\\n\\n # image header (40)\\n f.write(dword(40))\\n f.write(dword(self.width))\\n f.write(dword(self.height))\\n f.write(word(1))\\n f.write(word(24))\\n f.write(dword(0))\\n f.write(dword(0))\\n f.write(dword(self.width * self.height * 3))\\n f.write(dword(0))\\n f.write(dword(0))\\n f.write(dword(0))\\n f.write(dword(0))\\n\\n # pixel data\\n for x in range(self.height):\\n for y in range(self.width):\\n f.write(self.pixels[x][y])\\n f.close()\",\n \"def save(self, filename):\\n print(\\\"Saving...\\\", end=\\\"\\\\r\\\")\\n canvas = self.canvas[self.N:self.S,self.W:self.E]\\n cv2.imwrite(\\\"./Output/\\\"+filename, canvas)\\n print(\\\"Saved:\\\",filename)\",\n \"def set_border(self, color: tuple = (0, 0, 0, 255), width: int = 1):\\n self.border_color = color\\n self.border = width\",\n \"def save(\\n self,\\n output_path: str,\\n box_thickness: int = 2,\\n show_confidence: bool = True,\\n color_mapping: Optional[List[Tuple[int, int, int]]] = None,\\n target_bboxes: Optional[np.ndarray] = None,\\n target_bboxes_format: Optional[str] = None,\\n target_class_ids: Optional[np.ndarray] = None,\\n ) -> None:\\n image = self.draw(\\n box_thickness=box_thickness,\\n show_confidence=show_confidence,\\n color_mapping=color_mapping,\\n target_bboxes=target_bboxes,\\n target_bboxes_format=target_bboxes_format,\\n target_class_ids=target_class_ids,\\n )\\n save_image(image=image, path=output_path)\",\n \"def update_border(self):\\n # side borders\\n for row_position in range(NUM_ROWS+BORDER_WIDTH*2):\\n self.stdscr.addstr(row_position, 0, '|', curses.color_pair(7))\\n self.stdscr.addstr(row_position, NUM_COLUMNS*BLOCK_WIDTH+1, '|', curses.color_pair(7))\\n # top and bottom borders\\n for column_position in range(NUM_COLUMNS*BLOCK_WIDTH+BORDER_WIDTH*2):\\n self.stdscr.addstr(0, column_position, '-', curses.color_pair(7))\\n self.stdscr.addstr(NUM_ROWS+1, column_position, '-', curses.color_pair(7))\",\n \"def save_screenshot(self, file_name, width=3840, height=2160, first=True, last=True):\\n if first and self.assigned_opengl_context is not None:\\n self.assigned_opengl_context.makeCurrent()\\n gr3.export(file_name, width, height)\\n if last and self.assigned_opengl_context is not None:\\n self.assigned_opengl_context.doneCurrent()\",\n \"def save(self, filename: str, transparent: bool = False) -> None:\\n if transparent:\\n for fig in self._figures:\\n fig.background_fill_color = None # type: ignore[assignment]\\n fig.border_fill_color = None # type: ignore[assignment]\\n\\n if self._want_svg:\\n export_svg(self._layout, filename=filename)\\n else:\\n export_png(self._layout, filename=filename)\",\n \"def save(self, filename, overwrite=False, verbose=True, msg=''):\\n if msg:\\n msg = ' \\\"%s\\\"' % msg\\n save_to_file(\\n filename, self, overwrite=overwrite, verbose=verbose,\\n showname='curve%s' % msg\\n )\",\n \"def save_babble(self):\\n save_file = filedialog.asksaveasfile(mode='w', defaultextension='.txt')\\n if save_file is None:\\n return\\n save_file.write(self.display.get('1.0', tk.END))\\n save_file.close()\",\n \"def _save_version_file(cls, hivemind_version, git_revision, git_date):\\n with open(\\\"hive/version.py\\\", 'w') as version_file:\\n version_file.write(\\\"# generated by setup.py\\\\n\\\")\\n version_file.write(\\\"# contents will be overwritten\\\\n\\\")\\n version_file.write(\\\"VERSION = '{}'\\\\n\\\".format(hivemind_version))\\n version_file.write(\\\"GIT_REVISION = '{}'\\\\n\\\".format(git_revision))\\n version_file.write(\\\"GIT_DATE = '{}'\\\\n\\\".format(git_date))\",\n \"def format_box(box, box_style, border_visible, border_color, border_style,\\n border_width, border_radius, padding, margin):\\n box.box_style = box_style\\n box.padding = padding\\n box.margin = margin\\n if border_visible:\\n box.border_color = border_color\\n box.border_style = border_style\\n box.border_width = border_width\\n box.border_radius = border_radius\\n else:\\n box.border_width = 0\",\n \"def save(self, fname):\\n fmt = \\\" %7.1f %7.1f %8.2f %8.2f %8.2f %8.3f %8.3f %8.3f %8.3f %6.1f\\\"\\n with open(fname, 'wb') as fid:\\n fid.write('# CoordinateSystem \\\"Head\\\"\\\\n'.encode('utf-8'))\\n fid.write('# begin end X (mm) Y (mm) Z (mm)'\\n ' Q(nAm) Qx(nAm) Qy(nAm) Qz(nAm) g/%\\\\n'\\n .encode('utf-8'))\\n t = self.times[:, np.newaxis] * 1000.\\n gof = self.gof[:, np.newaxis]\\n amp = 1e9 * self.amplitude[:, np.newaxis]\\n out = np.concatenate((t, t, self.pos / 1e-3, amp,\\n self.ori * amp, gof), axis=-1)\\n np.savetxt(fid, out, fmt=fmt)\\n if self.name is not None:\\n fid.write(('## Name \\\"%s dipoles\\\" Style \\\"Dipoles\\\"'\\n % self.name).encode('utf-8'))\",\n \"def savefig(plt, path, show_message= True, tight_flag= True, newline= True):\\n if show_message:\\n print(\\\"Saving to {}\\\".format(path))\\n if tight_flag:\\n plt.savefig(path, bbox_inches='tight', pad_inches=0)\\n else:\\n plt.savefig(path)\\n if newline:\\n print(\\\"\\\")\",\n \"def _get_thickness(self,filename, maxLen=3):\\n filename = os.path.splitext(filename)[0] \\n filename = os.path.split(filename)[1] \\n filename = filename.split(\\\"_t\\\")[-1] \\n filename = filename.split(\\\"_\\\")[0]\\n if \\\"v\\\" in filename:\\n part1=filename.split(\\\"v\\\",1)[0]\\n part2=filename.split(\\\"v\\\",1)[1]\\n filename = ''.join((filename.split(\\\"v\\\",1)[0],'.',filename.split(\\\"v\\\",1)[1]))#['%s.%s' %(filename.split(\\\"v\\\",1)[0],filename.split(\\\"v\\\",1)[1])]\\n print(filename)\\n thickness = filename\\n return thickness\",\n \"def save(self, filepath):\\n self.drawer.flush()\\n self.img.save(filepath)\",\n \"def save(self, filename):\\n if len(self.interpolated_points) > 0:\\n red, green, blue = zip(*self.interpolated_points)\\n red = [np.asscalar(x) for x in red]\\n green = [np.asscalar(x) for x in green]\\n blue = [np.asscalar(x) for x in blue]\\n output_type = \\\"interpolated\\\"\\n print(\\\"Exporting interpolated points\\\")\\n elif len(self.main_cluster) > 0:\\n red, green, blue = self.get_color_lookup_table_points(self.main_cluster)\\n output_type = \\\"clustered\\\"\\n print(\\\"Exporting cluster points\\\")\\n else:\\n red = self.color_lookup_table_points[0]\\n green = self.color_lookup_table_points[1]\\n blue = self.color_lookup_table_points[2]\\n output_type = \\\"resized\\\"\\n print(\\\"Exporting resized points\\\")\\n\\n data = dict(\\n red=red,\\n green=green,\\n blue=blue\\n )\\n\\n filename = f'{filename}_{output_type}.pickle'\\n with open(filename, 'wb') as outfile:\\n pickle.dump(data, outfile, protocol=2)\\n # stores data of color lookup table in file as pickle for efficient loading (yaml is too slow)\\n\\n print(f\\\"Output saved to '{filename}'.\\\")\",\n \"def write(self, file_name, style=None):\\n write_elongation(self, file_name, style=style)\",\n \"def save_GRID( self , filename ):\\n self._fwrite_GRID( filename )\",\n \"def save(self, filename):\\n pass\",\n \"def style(self, box_style=None, border_visible=False, border_colour='black',\\n border_style='solid', border_width=1, border_radius=0, padding=0,\\n margin=0, font_family='', font_size=None, font_style='',\\n font_weight=''):\\n format_box(self, box_style, border_visible, border_colour, border_style,\\n border_width, border_radius, padding, margin)\\n format_font(self, font_family, font_size, font_style, font_weight)\\n format_font(self.file_format_select, font_family, font_size, font_style,\\n font_weight)\\n format_font(self.dpi_text, font_family, font_size, font_style,\\n font_weight)\\n format_font(self.orientation_dropdown, font_family, font_size,\\n font_style, font_weight)\\n format_font(self.papertype_select, font_family, font_size, font_style,\\n font_weight)\\n format_font(self.transparent_checkbox, font_family, font_size,\\n font_style, font_weight)\\n format_font(self.pad_inches_text, font_family, font_size, font_style,\\n font_weight)\\n format_font(self.filename_text, font_family, font_size, font_style,\\n font_weight)\\n format_font(self.overwrite_checkbox, font_family, font_size, font_style,\\n font_weight)\\n format_font(self.save_button, font_family, font_size, font_style,\\n font_weight)\\n self.facecolour_widget.style(\\n box_style=None, border_visible=False, font_family=font_family,\\n font_size=font_size, font_weight=font_weight, font_style=font_style)\\n self.edgecolour_widget.style(\\n box_style=None, border_visible=False, font_family=font_family,\\n font_size=font_size, font_weight=font_weight, font_style=font_style)\",\n \"def save_poly(self,ikfile,boresight,x,y,z): \\n with open(ikfile, \\\"w\\\") as f:\\n f.write(\\\"KPL/IK \\\\nComments. \\\\nMore comments. \\\\nMore comments.\\\\n\\\\\\\\begindata\\\\n\\\")\\n f.write(\\\"INS-99999_FOV_SHAPE = 'POLYGON'\\\\n\\\")\\n f.write(\\\"INS-99999_FOV_FRAME = 'CAMERA_FRAME'\\\\n\\\")\\n f.write(\\\"INS-99999_BORESIGHT = (%15.10f %15.10f %15.10f)\\\\n\\\" %(boresight[0],boresight[1],boresight[2]))\\n f.write(\\\"INS-99999_FOV_BOUNDARY_CORNERS = (%15.10f %15.10f %15.10f \\\\n\\\" %(x[0],y[0],z[0]))\\n for i in range(1,len(x)-1):\\n f.write(\\\"%34s %15.10f %15.10f %15.10f \\\\n\\\" %(\\\" \\\",x[i],y[i],z[i]))\\n f.write(\\\"%34s %15.10f %15.10f %15.10f) \\\\n\\\" %(\\\" \\\",x[len(x)-1],y[len(y)-1],z[len(z)-1]))\\n f.close()\",\n \"def write(self, fileW):\\n fileW.wFloat(self.x)\\n fileW.wFloat(self.y)\\n fileW.wFloat(self.z)\",\n \"def write_grid(self, file_path, fmt='%0.16g'):\\n with open(file_path, 'w') as outfile:\\n if self.grid.size == 3:\\n outfile.write('{}\\\\t{}\\\\t{}\\\\n'.format(self.grid[0].size - 1,\\n self.grid[1].size - 1,\\n self.grid[2].size - 1))\\n else:\\n outfile.write('{}\\\\t{}\\\\n'.format(self.grid[0].size - 1,\\n self.grid[1].size - 1))\\n with open(file_path, 'ab') as outfile:\\n numpy.savetxt(outfile, numpy.c_[self.grid[0]], fmt=fmt)\\n numpy.savetxt(outfile, numpy.c_[self.grid[1]], fmt=fmt)\\n if self.grid.size == 3:\\n numpy.savetxt(outfile, numpy.c_[self.grid[2]], fmt=fmt)\",\n \"def write(self, outfile, style='xyz', xyzlabel=True):\\n out = ''\\n if style == 'xyz':\\n if xyzlabel:\\n out += f'{len(self)}\\\\n\\\\n'\\n out += str(self)\\n elif style == 'latex':\\n header = f'{len(self)}\\\\\\\\\\\\\\\\\\\\n'\\n line_form = '{:<2}' + ' {:> 13.6f}' * 3 + ' {:>7.4f}'\\n atoms = [line_form.format(atom, *pos, charge) for atom, xyz, charge in self]\\n atoms = '\\\\n'.join(atoms)\\n out = '\\\\\\\\begin{verbatim}\\\\n' + atoms + '\\\\n\\\\\\\\end{verbatim}'\\n else:\\n raise SyntaxError('Invalid style')\\n with open(outfile, 'w') as f:\\n f.write(out)\",\n \"def style(self, box_style=None, border_visible=False, border_color='black',\\n border_style='solid', border_width=1, border_radius=0, padding=0,\\n margin=0, font_family='', font_size=None, font_style='',\\n font_weight=''):\\n _format_box(self, box_style, border_visible, border_color, border_style,\\n border_width, border_radius, padding, margin)\\n _format_font(self, font_family, font_size, font_style, font_weight)\\n _format_font(self.file_format_select, font_family, font_size,\\n font_style, font_weight)\\n _format_font(self.dpi_text, font_family, font_size, font_style,\\n font_weight)\\n _format_font(self.orientation_dropdown, font_family, font_size,\\n font_style, font_weight)\\n _format_font(self.papertype_select, font_family, font_size,\\n font_style, font_weight)\\n _format_font(self.transparent_checkbox, font_family, font_size,\\n font_style, font_weight)\\n _format_font(self.pad_inches_text, font_family, font_size, font_style,\\n font_weight)\\n _format_font(self.filename_text, font_family, font_size, font_style,\\n font_weight)\\n _format_font(self.overwrite_checkbox, font_family, font_size,\\n font_style, font_weight)\\n _format_font(self.save_button, font_family, font_size, font_style,\\n font_weight)\\n self.facecolour_widget.style(\\n box_style=None, border_visible=False, font_family=font_family,\\n font_size=font_size, font_weight=font_weight, font_style=font_style)\\n self.edgecolour_widget.style(\\n box_style=None, border_visible=False, font_family=font_family,\\n font_size=font_size, font_weight=font_weight, font_style=font_style)\",\n \"def create_file(destfile, size):\\n fulllines = int(math.floor(size / 100.0))\\n nwd = int(math.floor(math.log(fulllines+1))) + 1\\n fmt = \\\"%{0}d \\\".format(nwd)\\n\\n with open(destfile, 'w') as fd:\\n for i in range(fulllines):\\n fd.write(fmt % i)\\n fd.write('x' * (98-nwd))\\n fd.write('\\\\n')\\n\\n left = size - (fulllines * 100)\\n if left > nwd:\\n fd.write(fmt % (fulllines))\\n left -= nwd + 1\\n if left > 1:\\n fd.write('x' * (left-1))\\n left = 1\\n if left > 0:\\n fd.write('\\\\n')\\n\\n return os.stat(destfile).st_size\",\n \"def export_wells(self, w, title):\\r\\n self._check_out(title)\\r\\n np.savez_compressed(os.path.join(self.out_dir, title, title), w)\",\n \"def write_file(self, filename):\\n with open(filename, \\\"w\\\") as fo:\\n # vertices\\n\\n for x, y, z in self.vertices:\\n fo.write(\\\"v {} {} {}\\\\n\\\".format(x, y, z))\\n logging.info(\\\"Wrote {} vertices\\\".format(len(self.vertices)))\\n\\n # faces\\n faces = 0\\n width, height = self.size\\n for y in range(0, height-1):\\n for x in range(0, width-1):\\n tl = self.vertex_num(x,y)\\n tr = tl + 1\\n bl = tl + width\\n br = bl + 1\\n fo.write(\\\"f {} {} {}\\\\n\\\".format(tl, tr, bl))\\n fo.write(\\\"f {} {} {}\\\\n\\\".format(tr, br, bl))\\n faces += 2\\n logging.info(\\\"Wrote {} tris\\\".format(faces))\",\n \"def save_bmp(filename, data, width, height):\\r\\n\\r\\n hdr = struct.pack(\\\"<BBLHHLLLLHHLLLLLL\\\",\\r\\n 0x42, 0x4D,\\r\\n width * height * 3 + 54,\\r\\n 0, 0,\\r\\n 54, # offset\\r\\n 40, # header length\\r\\n width, height,\\r\\n 0, # colorplanes\\r\\n 24, # colordepth\\r\\n 0, # compression\\r\\n width * height * 3, # imagesize: calcular\\r\\n 0, 0, # resolution hor,vert\\r\\n 0, # palette\\r\\n 0) # importantcolors\\r\\n\\r\\n bmpfile = open(filename, \\\"wb\\\")\\r\\n bmpfile.write(hdr)\\r\\n bmpfile.write(data)\\r\\n bmpfile.close()\",\n \"def finish(self):\\n self._fout.add_size()\\n self._fout.add_padding()\\n self._fout.close()\",\n \"def save(\\n self,\\n output_path: str,\\n show_confidence: bool = True,\\n ) -> None:\\n image = self.draw(show_confidence=show_confidence)\\n save_image(image=image, path=output_path)\",\n \"def save(self, assignment, filename):\\n from PIL import Image, ImageDraw, ImageFont\\n cell_size = 100\\n cell_border = 2\\n interior_size = cell_size - 2 * cell_border\\n letters = self.letter_grid(assignment)\\n\\n # Create a blank canvas\\n img = Image.new(\\n \\\"RGBA\\\",\\n (self.crossword.width * cell_size,\\n self.crossword.height * cell_size),\\n \\\"black\\\"\\n )\\n font = ImageFont.truetype(\\\"assets/fonts/OpenSans-Regular.ttf\\\", 80)\\n draw = ImageDraw.Draw(img)\\n\\n for i in range(self.crossword.height):\\n for j in range(self.crossword.width):\\n\\n rect = [\\n (j * cell_size + cell_border,\\n i * cell_size + cell_border),\\n ((j + 1) * cell_size - cell_border,\\n (i + 1) * cell_size - cell_border)\\n ]\\n if self.crossword.structure[i][j]:\\n draw.rectangle(rect, fill=\\\"white\\\")\\n if letters[i][j]:\\n w, h = draw.textsize(letters[i][j], font=font)\\n draw.text(\\n (rect[0][0] + ((interior_size - w) / 2),\\n rect[0][1] + ((interior_size - h) / 2) - 10),\\n letters[i][j], fill=\\\"black\\\", font=font\\n )\\n\\n img.save(filename)\",\n \"def save(self, assignment, filename):\\n from PIL import Image, ImageDraw, ImageFont\\n cell_size = 100\\n cell_border = 2\\n interior_size = cell_size - 2 * cell_border\\n letters = self.letter_grid(assignment)\\n\\n # Create a blank canvas\\n img = Image.new(\\n \\\"RGBA\\\",\\n (self.crossword.width * cell_size,\\n self.crossword.height * cell_size),\\n \\\"black\\\"\\n )\\n font = ImageFont.truetype(\\\"assets/fonts/OpenSans-Regular.ttf\\\", 80)\\n draw = ImageDraw.Draw(img)\\n\\n for i in range(self.crossword.height):\\n for j in range(self.crossword.width):\\n\\n rect = [\\n (j * cell_size + cell_border,\\n i * cell_size + cell_border),\\n ((j + 1) * cell_size - cell_border,\\n (i + 1) * cell_size - cell_border)\\n ]\\n if self.crossword.structure[i][j]:\\n draw.rectangle(rect, fill=\\\"white\\\")\\n if letters[i][j]:\\n w, h = draw.textsize(letters[i][j], font=font)\\n draw.text(\\n (rect[0][0] + ((interior_size - w) / 2),\\n rect[0][1] + ((interior_size - h) / 2) - 10),\\n letters[i][j], fill=\\\"black\\\", font=font\\n )\\n\\n img.save(filename)\",\n \"def save(self, assignment, filename):\\n from PIL import Image, ImageDraw, ImageFont\\n cell_size = 100\\n cell_border = 2\\n interior_size = cell_size - 2 * cell_border\\n letters = self.letter_grid(assignment)\\n\\n # Create a blank canvas\\n img = Image.new(\\n \\\"RGBA\\\",\\n (self.crossword.width * cell_size,\\n self.crossword.height * cell_size),\\n \\\"black\\\"\\n )\\n font = ImageFont.truetype(\\\"assets/fonts/OpenSans-Regular.ttf\\\", 80)\\n draw = ImageDraw.Draw(img)\\n\\n for i in range(self.crossword.height):\\n for j in range(self.crossword.width):\\n\\n rect = [\\n (j * cell_size + cell_border,\\n i * cell_size + cell_border),\\n ((j + 1) * cell_size - cell_border,\\n (i + 1) * cell_size - cell_border)\\n ]\\n if self.crossword.structure[i][j]:\\n draw.rectangle(rect, fill=\\\"white\\\")\\n if letters[i][j]:\\n w, h = draw.textsize(letters[i][j], font=font)\\n draw.text(\\n (rect[0][0] + ((interior_size - w) / 2),\\n rect[0][1] + ((interior_size - h) / 2) - 10),\\n letters[i][j], fill=\\\"black\\\", font=font\\n )\\n\\n img.save(filename)\",\n \"def create_half_pic(self):\\n number_of_line = 0\\n for i in range(*self.horizontal_pic_border):\\n number_of_column = self.parameter//2\\n for j in range(*self.vertical_pic_border):\\n if number_of_column > (number_of_line + 1):\\n self.flag[i][j] = ' '\\n elif number_of_column == (number_of_line + 1):\\n self.flag[i][j] = CIRCLE_BORDER\\n else:\\n self.flag[i][j] = CIRCLE_INNER\\n number_of_column -= 1\\n mirror_update(self.flag[i])\\n number_of_line += 1\",\n \"def bgsave(self):\\r\\n return self.format_inline('BGSAVE')\",\n \"def draw(self, item, filename, style, thumb=False):\\n valid_styles = {\\n #'dudedb': self.__draw_ubl_style, # need revision\\n #'ptp': self.__draw_ubl_style, # need revision\\n 'episcan': self.__draw_gen_style,\\n }\\n\\n assert style in valid_styles, '{0} style not in valid_styles ({1})'.format(style, valid_styles)\\n\\n if thumb:\\n p = {\\\"pad1\\\": item[\\\"len\\\"] * 0.02,\\n \\\"pad2\\\": item[\\\"len\\\"] * 0.003,\\n \\\"figsize\\\": (1.5, 0.3),\\n \\\"lpad\\\": 0.16,\\n \\\"evpad\\\": 0.5,\\n \\\"nvpad\\\": 0.4}\\n else:\\n if not self.fixed:\\n p = {\\\"pad1\\\": self.max_len * 0.035, # pad out 1% of the figure left and right\\n \\\"pad2\\\": self.max_len * 0.003,\\n \\\"figsize\\\": (25, 1),\\n \\\"lpad\\\": 0.02, # vertical size of the central line\\n \\\"evpad\\\": 0.25, # vertical size of the 'normal' rectangle domain boxes.\\n \\\"nvpad\\\": 0.2,\\n \\\"titlepos\\\": \\\"left\\\",\\n \\\"titlesize\\\": 13} # vertical size of the 'enhanced' rectangle domain boxes.\\n else: # ie fixed\\n p = {\\\"pad1\\\": item[\\\"len\\\"] * 0.03, # pad out 1% of the figure left and right\\n \\\"pad2\\\": item[\\\"len\\\"] * 0.003,\\n \\\"figsize\\\": (7, 1),\\n \\\"lpad\\\": 0.02, # vertical size of the central line\\n \\\"evpad\\\": 0.20, # vertical size of the 'normal' rectangle domain boxes.\\n \\\"nvpad\\\": 0.2,\\n \\\"titlesize\\\": 13\\n } # vertical size of the 'enhanced' rectangle domain boxes.\\n\\n\\n fig = plt.figure(figsize=p[\\\"figsize\\\"])\\n\\n ax = fig.add_subplot(211)\\n axlab = fig.add_subplot(212)\\n\\n ax.set_position([0, 0.5, 1.0, 0.5])\\n axlab.set_position([0, 0.0, 1.0, 0.60])\\n\\n ax.add_patch(Rectangle((0,-p[\\\"lpad\\\"]), item[\\\"len\\\"]-1, p[\\\"lpad\\\"]*2, ec=\\\"none\\\", fc=\\\"black\\\", color=\\\"black\\\")) # The line for the protein\\n\\n if self.fixed:\\n ax.set_xlim([-p[\\\"pad1\\\"], item[\\\"len\\\"]+p[\\\"pad1\\\"]])\\n axlab.set_xlim([-p[\\\"pad1\\\"], item[\\\"len\\\"]+p[\\\"pad1\\\"]])\\n else:\\n ax.set_xlim([-p[\\\"pad1\\\"], self.max_len+p[\\\"pad1\\\"]])\\n axlab.set_xlim([-p[\\\"pad1\\\"], item[\\\"len\\\"]+p[\\\"pad1\\\"]])\\n\\n ax.set_ylim([-1, 1])\\n\\n axlab.set_ylim([0, 10])\\n axlab.set_facecolor('none')\\n\\n if len(item[\\\"domains\\\"]) > 0:\\n valid_styles[style](ax, axlab, item, p, thumb)\\n\\n if not thumb: # numbers showing the aa position of peptide\\n tpad = p['pad1']/10\\n ax.text(-tpad, 0, str(0), ha=\\\"right\\\", va=\\\"center\\\", fontsize=5, color=\\\"black\\\", zorder=100001)\\n ax.text(item[\\\"len\\\"]+tpad, 0, item['len'], ha=\\\"left\\\", va=\\\"center\\\", fontsize=5, color=\\\"black\\\", zorder=100001)\\n\\n ax.set_xticklabels(\\\"\\\")\\n ax.set_yticklabels(\\\"\\\")\\n ax.set_ylabel(\\\"\\\")\\n ax.set_xlabel(\\\"\\\")\\n ax.tick_params(left=None, top=None, bottom=None, right=None)\\n ax.set_frame_on(False)\\n\\n axlab.set_xticklabels(\\\"\\\")\\n axlab.set_yticklabels(\\\"\\\")\\n axlab.set_ylabel(\\\"\\\")\\n axlab.set_xlabel(\\\"\\\")\\n axlab.tick_params(left=None, top=None, bottom=None, right=None)\\n axlab.set_frame_on(False)\\n\\n fig.savefig(filename)\\n plt.close(fig) # Free up the memory\",\n \"def write_file(self):\\n if self.it_num % 5 == 0:\\n #plt.imshow(self.grid)\\n #plt.savefig(\\\"output%.4d.png\\\" % self.it_num, bbox_inches='tight')\\n io.savemat(\\\"MLOutput%.4d\\\" % self.it_num, { \\\"Grid\\\":self.grid})\",\n \"def hsep(self, width = 1, fg=None, bg=None, double=False):\\n\\n self.savepos()\\n\\n self.out.write(self._colorize((\\\"═\\\" if double else \\\"─\\\") * width, fg, bg))\\n\\n self.restorepos()\",\n \"def saveImage(self, file_name='./out.jpg'):\\n frame = self.camera.get_frame()\\n color = frame.color_image[0]\\n cv2.imwrite(file_name, color)\\n cv2.imshow('frame', color)\\n cv2.waitKey()\\n cv2.destroyAllWindows()\",\n \"def write2file(self, save_to):\\n headerstyle = xlwt.easyxf(self.header_style.get_style_string())\\n missing_val_style = xlwt.easyxf(\\n self.missing_value_style.get_style_string())\\n row_styles = [xlwt.easyxf(self.first_style.get_style_string()),\\n xlwt.easyxf(self.second_style.get_style_string())]\\n\\n properties, sections, table = self._build_table()\\n\\n workbook = xlwt.Workbook()\\n sheet = workbook.add_sheet(self.sheet_name)\\n\\n if os.path.splitext(save_to)[-1] == '':\\n save_to += '.xls'\\n\\n max_col_len = []\\n\\n if (self.switch):\\n\\n for i, prop in enumerate([''] + properties):\\n sheet.write(0, i, prop, headerstyle)\\n max_col_len.append(len(str(prop)))\\n\\n for row_num, sec in enumerate(sections):\\n sheet.write(row_num + 1, 0, sec, headerstyle)\\n if len(str(sec)) > max_col_len[0]:\\n max_col_len[0] = len(str(sec))\\n\\n for row_num, row in enumerate(table):\\n for col_num, elem in enumerate(row):\\n\\n if elem is None:\\n style = missing_val_style\\n cell_content = \\\"\\\"\\n else:\\n style = row_styles[row_num % 2]\\n cell_content = elem\\n\\n if isinstance(cell_content, datetime.datetime):\\n style.num_format_str = \\\"DD-MM-YYYY HH:MM:SS\\\"\\n elif isinstance(cell_content, datetime.date):\\n style.num_format_str = \\\"DD-MM-YYYY\\\"\\n elif isinstance(cell_content, datetime.time):\\n style.num_format_str = \\\"HH:MM:SS\\\"\\n else:\\n style.num_format_str = \\\"\\\"\\n\\n sheet.write(row_num + 1, col_num + 1, cell_content, style)\\n if len(str(cell_content)) > max_col_len[col_num+1]:\\n max_col_len[col_num+1] = len(str(cell_content))\\n\\n else:\\n\\n for i, sec in enumerate([''] + sections):\\n sheet.write(0, i, sec, headerstyle)\\n max_col_len.append(len(str(sec)))\\n\\n for row_num, prop in enumerate(properties):\\n sheet.write(row_num + 1, 0, prop, headerstyle)\\n if len(str(prop)) > max_col_len[0]:\\n max_col_len[0] = len(str(prop))\\n\\n for col_num, col in enumerate(table):\\n for row_num, elem in enumerate(col):\\n\\n if elem is None:\\n style = missing_val_style\\n cell_content = \\\"\\\"\\n else:\\n style = row_styles[row_num % 2]\\n cell_content = elem\\n\\n if isinstance(cell_content, datetime.datetime):\\n style.num_format_str = \\\"DD-MM-YYYY HH:MM:SS\\\"\\n elif isinstance(cell_content, datetime.date):\\n style.num_format_str = \\\"DD-MM-YYYY\\\"\\n elif isinstance(cell_content, datetime.time):\\n style.num_format_str = \\\"HH:MM:SS\\\"\\n else:\\n style.num_format_str = \\\"\\\"\\n\\n sheet.write(row_num + 1, col_num + 1, cell_content, style)\\n if len(str(cell_content)) > max_col_len[col_num+1]:\\n max_col_len[col_num+1] = len(str(cell_content))\\n\\n # adjust width of he columns\\n for col_id, col_len in enumerate(max_col_len):\\n sheet.col(col_id).width = (256 * (col_len+1))\\n\\n workbook.save(save_to)\",\n \"def save(self, filename, precision='%15.07e', encoding='utf-8'):\\n\\n # when creating empty st object, cols is not set yet\\n if not hasattr(self, 'cols'):\\n if self.main_data_sets[1][1].shape[1]==19:\\n self.cols = stc.split()\\n elif self.main_data_sets[1][1].shape[1]==30:\\n self.cols = fpm.split()\\n else:\\n c = self.main_data_sets[1][1].shape[1]\\n raise TypeError(f'St input needs 19 (iso) or 30 (aniso/fpm) cols, not {c}')\\n\\n colwidth = len(precision % 1)\\n sep = '=' * colwidth * len(self.cols) + '\\\\n'\\n colhead = ''.join([k.center(colwidth) for k in self.cols]) + '\\\\n'\\n\\n nsets = len(self.main_data_sets)\\n # fails if dirname is empty string\\n if len(os.path.dirname(filename)) > 0:\\n os.makedirs(os.path.dirname(filename), exist_ok=True)\\n with open(filename, 'w', encoding=encoding) as fid:\\n fid.write('%i ; number of sets, Nset\\\\n' % nsets)\\n for mset, set_data_dict in self.main_data_sets.items():\\n fid.write('#%i ; set number\\\\n' % mset)\\n for set, set_array in set_data_dict.items():\\n dstr = self.to_str(mset=mset, set=set, precision=precision)\\n npoints = self.main_data_sets[mset][set].shape[0]\\n fid.write(sep + colhead + sep)\\n fid.write('$%i %i\\\\n' % (set, npoints))\\n fid.write(dstr + '\\\\n')\",\n \"def new_file(name, style):\\n with open(CSV_DIR / name, \\\"w\\\") as f:\\n writer = csv.writer(f)\\n if style:\\n writer.writerow(cols_style)\\n else:\\n writer.writerow(cols)\",\n \"def SaveHeight(self,val=0):\\n if self.height_first_save:\\n self.height_file = self.params.Save(self.height,\\\"height\\\",subfolder=\\\"functions/\\\",val=val)\\n self.depth_file = self.params.Save(self.depth,\\\"depth\\\",subfolder=\\\"functions/\\\",val=val)\\n self.height_first_save = False\\n else:\\n self.params.Save(self.height,\\\"height\\\",subfolder=\\\"functions/\\\",val=val,file=self.height_file)\\n self.params.Save(self.depth,\\\"depth\\\",subfolder=\\\"functions/\\\",val=val,file=self.depth_file)\",\n \"def save(self, filename):\\n self.image.save(filename, self.options.img_format)\",\n \"def border(self):\\n ...\",\n \"def saveWorld(self, filename):\\n worldFile = open( filename, 'w' );\\n worldFile.write( \\\"WIDTH {0}\\\\nHEIGHT {1}\\\\n\\\".format( self.mWidth, self.mHeight ) );\\n\\n for space in self.mSpaces:\\n if isinstance(space, Circle):\\n worldFile.write( \\\"SPACE circle {0} {1} {2}\\\\n\\\".format( space.X, space.Y, space.Radius ) );\\n elif isinstance(space, Rect):\\n worldFile.write( \\\"SPACE rect {0} {1} {2} {3}\\\\n\\\".format( space.X,space.Y,space.Width,space.Height ) );\\n\\n for obst in self.mObstMgr.mObstacles:\\n if isinstance(obst,Circle):\\n worldFile.write( \\\"OBSTACLE circle {0} {1} {2}\\\\n\\\".format( obst.X, obst.Y, obst.Radius ) );\\n elif isinstance(obst,Rect):\\n worldFile.write( \\\"OBSTACLE rect {0} {1} {2} {3}\\\\n\\\".format( obst.X,obst.Y,obst.Width,obst.Height ) );\\n worldFile.close();\\n pass;\",\n \"def add_border(original_img,border_size):\\r\\n new_image=SimpleImage.blank(2 * border_size + original_img.width ,2 * border_size + original_img.height )\\r\\n\\r\\n \\\"\\\"\\\"\\r\\n Task 2: Creating black border\\r\\n \\r\\n \\\"\\\"\\\"\\r\\n for y in range(new_image.height):\\r\\n for x in range(new_image.width):\\r\\n\\r\\n # converting all the border pixels to black\\r\\n\\r\\n if x <= border_size or x >= border_size + original_img.height or y <= border_size or y >= border_size + original_img.width:\\r\\n\\r\\n px=new_image.get_pixel(x,y)\\r\\n px.red=0\\r\\n px.green=0\\r\\n px.blue=0\\r\\n\\r\\n # replacing the pixels other than the border with inage\\r\\n\\r\\n else:\\r\\n\\r\\n new_image.get_pixel(x,y).red=original_img.get_pixel(x-border_size, y-border_size).red\\r\\n new_image.get_pixel(x,y).blue = original_img.get_pixel(x - border_size, y - border_size).blue\\r\\n new_image.get_pixel(x,y).green = original_img.get_pixel(x - border_size, y - border_size).green\\r\\n\\r\\n\\r\\n return new_image\",\n \"def OnSave(self, e):\\n\\t\\tconvert_to = None\\n\\t\\tif e.Id == 201:\\n\\t\\t\\tconvert_to = \\\"photoabsorption\\\"\\n\\t\\telif e.Id == 202:\\n\\t\\t\\tconvert_to = \\\"refractive_index\\\"\\n\\t\\tlogger.info(\\\"Save\\\")\\n\\t\\tfd = wx.FileDialog(self, style=wx.FD_SAVE|wx.FD_OVERWRITE_PROMPT)\\n\\t\\tif fd.ShowModal()==wx.ID_OK:\\n\\t\\t\\tmetadata = {\\\"Density\\\": float(self.DensityText.GetValue()), \\\"Molecular Formula\\\":self.StoichiometryText.GetValue(),\\\"Formula Mass\\\":data.calculate_FormulaMass(self.Stoichiometry)}\\n\\t\\t\\tdata.export_data(fd.GetPath(), numpy.transpose(numpy.vstack((self.Full_E,self.KK_Real_Spectrum,data.coeffs_to_ASF(self.Full_E,self.Imaginary_Spectrum)))), header_info=metadata, convert_to=convert_to)\",\n \"def save(self, file):\\n boulders = []\\n elephants = []\\n rhinos = []\\n for i in range(5):\\n for j in range(5):\\n if self[i][j]!= 0:\\n piece = self[i][j]\\n L = []\\n if not isinstance(self[i][j], Boulder):\\n L.append(self[i][j].direction[0])\\n L.append(self[i][j].direction[1])\\n if piece.species == \\\"Elephant\\\":\\n elephants.append(\\\"(\\\" + str(i) + \\\",\\\" + str(j)+ \\\") : np.array([\\\"+str(L[0])+ \\\",\\\" + str(L[1])+\\\"])\\\")\\n elif piece.species == \\\"Rhinoceros\\\":\\n rhinos.append(\\\"(\\\"+str(i)+\\\",\\\" +str(j)+ \\\") : np.array([\\\"+str(L[0]) + \\\",\\\" + str(L[1])+\\\"])\\\")\\n elif isinstance(piece, Boulder):\\n boulders.append(\\\"(\\\" + str(i) + \\\",\\\" + str(j) + \\\")\\\")\\n file.write(\\\"# King of Siam GameFile \\\\n\\\\nplayer_turn {\\\\n \\\" + self.playerTurn + \\\"\\\\n}\\\\n\\\\n\\\")\\n file.write(\\\"Boulder {\\\")\\n for k in range(len(boulders)):\\n file.write(\\\"\\\\n \\\" + boulders[k] + \\\";\\\")\\n file.write(\\\"\\\\n}\\\\n\\\\nElephant {\\\")\\n for elt in elephants:\\n file.write(\\\"\\\\n \\\" + elt + \\\";\\\")\\n file.write(\\\"\\\\n}\\\\n\\\\nRhinoceros {\\\")\\n for elt in rhinos:\\n file.write(\\\"\\\\n \\\" + elt + \\\";\\\")\\n file.write(\\\"\\\\n}\\\")\\n\\n file.close()\",\n \"def write_flow(flow, filename):\\n f = open(filename, 'wb')\\n magic = numpy.array([202021.25], dtype=numpy.float32)\\n (height, width) = flow.shape[0:2]\\n w = numpy.array([width], dtype=numpy.int32)\\n h = numpy.array([height], dtype=numpy.int32)\\n magic.tofile(f)\\n w.tofile(f)\\n h.tofile(f)\\n flow.tofile(f)\\n f.close()\",\n \"def __init__(self, width, height):\\r\\n super().__init__(width, height)\\r\\n \\r\\n self.file = open(\\\"drawing.c\\\", \\\"w\\\")\\r\\n self.held_keys = set()\\r\\n arcade.set_background_color(arcade.color.WHITE)\\r\\n self.cursor = [Cursor()]\\r\\n self.record = []\",\n \"def save(self):\\n Preferences.setVCS(\\n \\\"AutoClose\\\",\\n self.vcsAutoCloseCheckBox.isChecked())\\n Preferences.setVCS(\\n \\\"AutoSaveFiles\\\",\\n self.vcsAutoSaveCheckBox.isChecked())\\n Preferences.setVCS(\\n \\\"AutoSaveProject\\\",\\n self.vcsAutoSaveProjectCheckBox.isChecked())\\n Preferences.setVCS(\\n \\\"StatusMonitorInterval\\\",\\n self.vcsStatusMonitorIntervalSpinBox.value())\\n Preferences.setVCS(\\n \\\"MonitorLocalStatus\\\",\\n self.vcsMonitorLocalStatusCheckBox.isChecked())\\n Preferences.setVCS(\\n \\\"AutoUpdate\\\",\\n self.autoUpdateCheckBox.isChecked())\\n \\n self.saveColours(Preferences.setProjectBrowserColour)\",\n \"def brandify_img(img, img_name, border_width_percentage=0.10, \\\\\\nborder_width_cap=150, inner_border_width=7, \\\\\\ninner_border_color=(50, 255, 50, 0), outer_border_color=(50, 50, 50, 0)):\\n if img_name.startswith(\\\"Modified-\\\"):\\n return\\n width = img.size[0]\\n height = img.size[1]\\n # A new image that will be embiggened to fit the border\\n border_width = int(float(width + height) / 2 * border_width_percentage)\\n if border_width > border_width_cap:\\n border_width = border_width_cap\\n total_width = width + border_width * 2\\n total_height = height + border_width * 2\\n img.convert(mode=\\\"RGBA\\\")\\n bordered_img = PIL.Image.new(\\\"RGBA\\\", img.size)\\n bordered_img = PIL.ImageOps.expand(img, border=border_width)\\n draw = PIL.ImageDraw.Draw(bordered_img)\\n \\n # Fill in the border for the image\\n # The inner part of the border will be later covered up by the image itself\\n draw_border_gradient(bordered_img, center_color=inner_border_color, \\\\\\n outer_color=outer_border_color, excluding_region=(border_width, \\\\\\n width + border_width, border_width, height + border_width))\\n \\n # Inner border\\n # \\\"bb\\\" stands for border for border\\n bb_color = (255 - 50, 255 - 50, 255 - 50, 255)\\n draw.rectangle((border_width - inner_border_width, border_width - \\\\\\n inner_border_width, width + border_width + inner_border_width, height + \\\\\\n border_width + inner_border_width), fill=bb_color)\\n \\n # Add the original image\\n bordered_img.paste(img, (border_width, border_width, width + border_width, \\\\\\n height + border_width))\\n \\n # Add some basic design to the border\\n # Add lines on each corner\\n # Order is top left, top right, bottom left, bottom right\\n draw.line((0, 0, border_width, border_width), fill=bb_color, width=3)\\n draw.line((total_width, 0, total_width - border_width, border_width), \\\\\\n fill=bb_color, width=3)\\n draw.line((0, total_height, border_width, total_height - border_width), \\\\\\n fill=bb_color, width=3)\\n draw.line((total_width, total_height, total_width - border_width, \\\\\\n total_height - border_width), fill=bb_color, width=3)\\n \\n # Apply the brand image\\n new_width = int((float(brand_image.size[0]) / brand_image.size[1]) * \\\\\\n border_width)\\n new_height = border_width - inner_border_width\\n resized_img = brand_image.resize((new_width, new_height))\\n bordered_img.paste(resized_img, box=((width - resized_img.size[0] / 2) \\\\\\n / 2, 0), mask=resized_img)\\n \\n bordered_img.save(image_directory + os.sep + \\\"Modified-\\\" + img_name)\",\n \"def save(self, filename, path = False,\\n squash = False, verbose = True, *args, **kwargs):\\n\\n if hasattr(self, \\\"wavelength\\\") and hasattr(self, \\\"throughput\\\"): ## enables resampling and wavelength conversion to be easily saved\\n if verbose: print(\\\"has data\\\")\\n if not path:\\n if verbose: print(\\\"No directory specified, assuming \\\" + defaults._default_filter_dir_path)\\n path = defaults._default_filter_dir_path\\n else:\\n errors.StringWarning(path)\\n\\n outpath = os.path.join(path, filename)\\n\\n utils.check_dir_path(path)\\n\\n if os.path.isfile(outpath):\\n warnings.warn(\\\"Found existing file matching \\\" + path + \\\". Run with squash = True to overwrite\\\")\\n if squash:\\n print(\\\"Overwriting \\\" + outpath)\\n outtable = Table([self.wavelength, self.throughput], names = [\\\"wavelength\\\", \\\"throughput\\\"])\\n outtable.write(outpath, format = \\\"ascii.fast_commented_header\\\", overwrite = True)\\n self._format_for_save = outtable\\n\\n\\n else:\\n print(\\\"Writing \\\" + outpath)\\n outtable = Table([self.wavelength, self.throughput], names = [\\\"wavelength\\\", \\\"throughput\\\"])\\n\\n outtable.write(outpath, format = \\\"ascii.fast_commented_header\\\")\\n self._format_for_save = outtable\\n\\n else:\\n warnings.warn(\\\"Doesn't seem to be any data here (empty self.data)\\\")\\n pass\",\n \"def write_flow(flow, filename):\\n f = open(filename, 'wb')\\n magic = np.array([202021.25], dtype=np.float32)\\n (height, width) = flow.shape[0:2]\\n w = np.array([width], dtype=np.int32)\\n h = np.array([height], dtype=np.int32)\\n magic.tofile(f)\\n w.tofile(f)\\n h.tofile(f)\\n flow.tofile(f)\\n f.close()\",\n \"def save_bbox(tensor, box, filename, nrow=8, padding=0,\\n normalize=False, scale_each=False, pad_value=0, draw_line=False, save=True):\\n from PIL import Image\\n \\n # print(box)\\n # assert False\\n\\n grid = make_grid_bbox(tensor, box, nrow=nrow, padding=padding, pad_value=pad_value,\\n normalize=normalize, scale_each=scale_each, draw_line=draw_line)\\n\\n # Add 0.5 after unnormalizing to [0, 255] to round to nearest integer\\n # ndarr = grid.mul_(255).add_(0.5).clamp_(0, 255).permute(1, 2, 0).to('cpu', torch.uint8).numpy()\\n ndarr = grid.mul_(13).add_(0.5).clamp_(0, 13).permute(1, 2, 0).to('cpu', torch.uint8).numpy()\\n\\n # colorize the gray images\\n # ndarr = cv2.applyColorMap(cv2.convertScaleAbs(ndarr, alpha=20.0), cv2.COLORMAP_JET)\\n palette = []\\n for i in range(256):\\n palette.extend((255, 255, 255))\\n palette[:3*14] = np.array([[84, 139, 84],\\n [0, 100, 0],\\n [0, 0, 128],\\n [85, 26, 139],\\n [255, 0, 255],\\n [165, 42, 42],\\n [139, 134, 130],\\n [205, 198, 115],\\n [139, 58, 58],\\n [255, 255, 255],\\n [0, 0, 0],\\n [30, 144, 255],\\n [135, 206, 235],\\n [255, 255, 0]], dtype='uint8').flatten()\\n\\n # # draw box\\n # ndarr = draw_box(ndarr, box, palette)\\n\\n im = Image.fromarray(ndarr).convert('L')\\n # colorize\\n im.putpalette(palette)\\n if save:\\n im.save(filename)\\n else:\\n return im\",\n \"def create_regfile(userinput, x, y, filename, color='blue', width=2):\\n target_dir = userinput['OUTDIR']\\n outputfile = target_dir + '/s_extraction/{}'.format(filename)\\n\\n logging.info('Writing region file {}'.format(filename))\\n\\n with open(outputfile, 'w') as file:\\n file.write('global color={} width={} font=\\\"helvetica 15 normal roman\\\" highlite=1 \\\\n'\\\\\\n .format(color,width))\\n file.write('image\\\\n')\\n\\n for i in range(len(x)):\\n newline = 'circle(' + str(x[i]) + ',' + str(y[i]) + ',7) \\\\n'\\n file.write(newline)\",\n \"def save_as_fits(self, filename):\",\n \"def savefig(filename, leg=None, format='.eps', *args, **kwargs):\\n if leg:\\n art=[leg]\\n plt.savefig(filename + format, additional_artists=art, bbox_inches=\\\"tight\\\", *args, **kwargs)\\n else:\\n plt.savefig(filename + format, bbox_inches=\\\"tight\\\", *args, **kwargs)\\n plt.close()\",\n \"def write_version_file(version):\\n try:\\n git_log = subprocess.check_output(\\n ['git', 'log', '-1', '--pretty=%h %ai']).decode('utf-8')\\n git_diff = (subprocess.check_output(['git', 'diff', '.']) +\\n subprocess.check_output(\\n ['git', 'diff', '--cached', '.'])).decode('utf-8')\\n if git_diff == '':\\n git_status = '(CLEAN) ' + git_log\\n else:\\n git_status = '(UNCLEAN) ' + git_log\\n except Exception as e:\\n print(\\\"Unable to obtain git version information, exception: {}\\\"\\n .format(e))\\n git_status = ''\\n\\n version_file = '.version'\\n if os.path.isfile(version_file) is False:\\n with open('bilby/' + version_file, 'w+') as f:\\n f.write('{}: {}'.format(version, git_status))\\n\\n return version_file\",\n \"def reset(self) -> None:\\n self.file.write(\\\"\\\\b\\\" * (len(self.current_frame) + self.current_padding))\",\n \"def predefined_style(self, style):\\n if style == 'minimal':\\n self.style(box_style='', border_visible=True, border_colour='black',\\n border_style='solid', border_width=1, border_radius=0,\\n padding='0.2cm', margin='0.3cm', font_family='',\\n font_size=None, font_style='', font_weight='')\\n self.save_button.button_style = ''\\n self.save_button.font_weight = 'normal'\\n elif (style == 'info' or style == 'success' or style == 'danger' or\\n style == 'warning'):\\n self.style(box_style=style, border_visible=True,\\n border_colour= map_styles_to_hex_colours(style),\\n border_style='solid', border_width=1, border_radius=10,\\n padding='0.2cm', margin='0.3cm', font_family='',\\n font_size=None, font_style='', font_weight='')\\n self.save_button.button_style = 'primary'\\n self.save_button.font_weight = 'bold'\\n else:\\n raise ValueError('style must be minimal or info or success or '\\n 'danger or warning')\",\n \"def close(self, event, data):\\n try:\\n with open(self.save_file, \\\"w+\\\") as save_file:\\n try:\\n data = json.load(save_file)\\n except ValueError:\\n data = dict()\\n data[\\\"color\\\"] = rgb_to_hex(self.rgb_color)\\n json.dump(data, save_file)\\n except (OSError, json.JSONDecodeError):\\n print(\\\"Error when trying to set save file.\\\")\\n Gtk.main_quit()\",\n \"def write( self, NewFilename='', Integer=True ):\\n try:\\n if NewFilename != '':\\n self.name=NewFilename\\n Output = open( self.name, 'w' )\\n Output.write( 'ncols\\\\t\\\\t %d\\\\n' % self.ncols )\\n Output.write( 'nrows\\\\t\\\\t %d\\\\n' % self.nrows )\\n Output.write( 'xllcorner\\\\t\\\\t %f\\\\n' % self.xllcorner)\\n Output.write( 'yllcorner\\\\t\\\\t %f\\\\n' % self.yllcorner)\\n Output.write( 'cellsize\\\\t\\\\t %f\\\\n' % self.cellsize)\\n if Integer:\\n Output.write( 'NODATA_value\\\\t\\\\t %d\\\\n' % int(self.nodata) )\\n else:\\n Output.write( 'NODATA_value\\\\t\\\\t %f\\\\n' % self.nodata )\\n for row in range( self.nrows-1,-1,-1 ):\\n record = []\\n for col in range( self.ncols ):\\n if Integer:\\n record.append( str( int( round( self.data[row,col]) ) ) )\\n else:\\n record.append( str(self.data[row,col]) )\\n Output.write( string.join(record, ' ')+'\\\\n' )\\n Output.close()\\n except:\\n print \\\"Error writing grid ::\\\", self.name\",\n \"def LHCbStyle_alt ( name = \\\"LHCbStyle\\\" ,\\n desc = \\\"Standard LHCb plots style\\\" ,\\n lineWidth = lhcbWidth ,\\n font = lhcbFont ,\\n makeNew = False ,\\n force = True ) :\\n obj = ROOT.gROOT.FindObject ( name )\\n if obj and issubclass ( type( obj ) , ROOT.TStyle ) and not makeNew : \\n logger.info ('The style %s is reused' % obj.GetName() )\\n if force : \\n logger.info ('The style %s is forced' % obj.GetName() )\\n ROOT.gROOT.SetStyle ( obj.GetName() )\\n ROOT.gROOT.ForceStyle ( )\\n return obj\\n \\n nam = name\\n i = 1\\n while obj :\\n nam = name + '_%d' % i\\n obj = ROOT.gROOT.FindObject ( nam )\\n i += 1\\n \\n style = ROOT.TStyle ( nam , desc )\\n logger.info ('New style %s is created' % style.GetName() )\\n \\n ## use plain black on white colors\\n style . SetFrameBorderMode ( 0 )\\n style . SetCanvasBorderMode ( 0 )\\n style . SetPadBorderMode ( 0 )\\n style . SetPadColor ( 0 )\\n style . SetCanvasColor ( 0 )\\n style . SetStatColor ( 0 )\\n # style . SetPalette ( 1 )\\n # style . SetTitleStyle ( 0 )\\n ## set the paper & margin sizes\\n style . SetPaperSize ( 20 , 26 )\\n style . SetPadTopMargin ( 0.05 )\\n style . SetPadRightMargin ( 0.05 ) ## increase for colz plots\\n style . SetPadBottomMargin ( 0.16 )\\n style . SetPadLeftMargin ( 0.14 )\\n \\n ## use large fonts\\n style . SetTextFont ( font )\\n style . SetTextSize ( 0.08 )\\n style . SetLabelFont ( font , \\\"x\\\" ) \\n style . SetLabelFont ( font , \\\"y\\\" ) \\n style . SetLabelFont ( font , \\\"z\\\" ) \\n style . SetLabelSize ( 0.05 , \\\"x\\\" )\\n style . SetLabelSize ( 0.05 , \\\"y\\\" )\\n style . SetLabelSize ( 0.05 , \\\"z\\\" )\\n style . SetTitleFont ( font )\\n style . SetTitleSize ( 0.06 , \\\"x\\\" )\\n style . SetTitleSize ( 0.06 , \\\"y\\\" )\\n style . SetTitleSize ( 0.06 , \\\"z\\\" ) \\n \\n \\n ## use bold lines and markers\\n style . SetLineWidth ( lineWidth )\\n style . SetFrameLineWidth ( lineWidth )\\n style . SetHistLineWidth ( lineWidth )\\n style . SetFuncWidth ( lineWidth )\\n style . SetGridWidth ( lineWidth )\\n style . SetLineStyleString ( 2 , \\\"[12 12]\\\" ) ## postscript dashes\\n #style . SetMarkerStyle ( 20 )\\n style . SetMarkerSize ( 1.2 )\\n \\n ## label offsets\\n style . SetLabelOffset(0.015);\\n \\n ## by default, do not display histogram decorations:\\n style . SetOptStat ( 0 ) \\n ## lhcbStyle->SetOptStat(\\\"emr\\\"); ## show only nent -e , mean - m , rms -r\\n ## full opts at http://root.cern.ch/root/html/TStyle.html#TStyle:SetOptStat\\n style . SetStatFormat (\\\"6.3g\\\") ## specified as c printf options\\n # style . SetOptTitle ( 1 )\\n style . SetOptFit ( 0 )\\n ## lhcbStyle . SetOptFit(1011); // order is probability, Chi2, errors, parameters\\n \\n\\n ## look of the statistics box:\\n style . SetStatBorderSize ( 0 )\\n style . SetStatFont ( font )\\n # style . SetStatFontSize ( 0.05 )\\n # style . SetStatX ( 0.9 )\\n # style . SetStatY ( 0.9 )\\n # style . SetStatW ( 0.25 )\\n # style . SetStatH ( 0.15 )\\n ## put tick marks on top and RHS of plots\\n style . SetPadTickX ( 1 )\\n style . SetPadTickY ( 1 )\\n \\n## histogram divisions: only 5 in x to avoid label overlaps\\n style . SetNdivisions ( 505 , \\\"x\\\" )\\n style . SetNdivisions ( 510 , \\\"y\\\" )\\n \\n if force : \\n logger.info ('The style %s is forced' % style.GetName() )\\n ROOT.gROOT.SetStyle ( style.GetName() )\\n ROOT.gROOT.ForceStyle ()\\n \\n return style\",\n \"def _write(self, stream):\\n\\n self._img.append(self.make_path())\\n self._img.append(self.make_border())\\n self._img.append(self.make_text())\\n\\n ET.ElementTree(self._img).write(stream, encoding=\\\"UTF-8\\\", xml_declaration=True)\",\n \"def add_border(self, color='white', width=2.0):\\n points = np.array([[1.0, 1.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 0.0], [1.0, 0.0, 0.0]])\\n\\n lines = np.array([[2, 0, 1], [2, 1, 2], [2, 2, 3], [2, 3, 0]]).ravel()\\n\\n poly = pyvista.PolyData()\\n poly.points = points\\n poly.lines = lines\\n\\n coordinate = _vtk.vtkCoordinate()\\n coordinate.SetCoordinateSystemToNormalizedViewport()\\n\\n mapper = _vtk.vtkPolyDataMapper2D()\\n mapper.SetInputData(poly)\\n mapper.SetTransformCoordinate(coordinate)\\n\\n actor = _vtk.vtkActor2D()\\n actor.SetMapper(mapper)\\n actor.GetProperty().SetColor(Color(color).float_rgb)\\n actor.GetProperty().SetLineWidth(width)\\n\\n self.AddViewProp(actor)\\n self.Modified()\\n\\n self._border_actor = actor\\n return actor\",\n \"def save_image(self):\\n # open the dialog and get the selected file\\n file_one = QtGui.QFileDialog.getSaveFileName(\\n self,\\n QtGui.QApplication.translate(\\n \\\"MainWindow\\\", \\n \\\"Supported formats:\\\", \\n None, \\n QtGui.QApplication.UnicodeUTF8)+\\n \\\" emf, eps, pdf, png, ps, raw, rgba, svg, svgz\\\", \\n \\\"\\\",\\n \\\"Enhanced MetaFile \\\\t.emf (*.emf);; \\\"+\\n \\\"Encapsulated PostScript \\\\t.eps (*.eps);; \\\"+\\n \\\"Portable Document Format \\\\t.pdf (*.pdf);; \\\"+\\n \\\"Portable Network Graphics \\\\t.png (*.png);;\\\"+\\n \\\"PostScript \\\\t.ps (*.ps);; \\\"+\\n \\\"RAW image file \\\\t.raw (*.raw);; \\\"+\\n \\\"Red Green Blue Alpha \\\\t.rgba (*.rgba);; \\\"+\\n \\\"Scalable Vector Graphics \\\\t.svg (*.svg);; \\\"+\\n \\\"Scalable Vector Graphics compressed \\\\t.svgz (*.svgz)\\\")\\n # if a file is selected\\n if file_one:\\n # update the lineEdit text with the selected filename\\n self.textBrowser.append(\\n QtGui.QApplication.translate(\\n \\\"MainWindow\\\", \\n \\\"Saving to \\\", \\n None, \\n QtGui.QApplication.UnicodeUTF8\\n )+file_one)\\n\\n plt.clf()\\n # adding different plots if required\\n if self.checkBox_R.isChecked():\\n lines = plt.plot(self.graf_t, self.graf_r)\\n plt.setp(lines[0], \\n lw=1, \\n label=str(\\n QtGui.QApplication.translate(\\n \\\"MainWindow\\\", \\n \\\"Reference\\\", \\n None, \\n QtGui.QApplication.UnicodeUTF8)), \\n color = 'blue')\\n \\n if self.checkBox_U.isChecked():\\n lines = plt.plot(self.graf_t, self.graf_u)\\n plt.setp(lines[0], \\n lw=2, \\n label=str(\\n QtGui.QApplication.translate(\\n \\\"MainWindow\\\", \\n \\\"Input\\\", \\n None, \\n QtGui.QApplication.UnicodeUTF8)), \\n color='red')\\n \\n if self.checkBox_x1.isChecked():\\n lines = plt.plot(self.graf_t, self.graf_x1)\\n plt.setp(lines[0], \\n lw=1, \\n label=str(\\n QtGui.QApplication.translate(\\n \\\"MainWindow\\\", \\n \\\"First Int.\\\", \\n None, \\n QtGui.QApplication.UnicodeUTF8)), \\n color='grey')\\n \\n if self.checkBox_x0.isChecked():\\n lines = plt.plot(self.graf_t, self.graf_x0)\\n plt.setp(lines[0], \\n lw=2, \\n label=str(\\n QtGui.QApplication.translate(\\n \\\"MainWindow\\\", \\n \\\"Second Int.\\\", \\n None, \\n QtGui.QApplication.UnicodeUTF8)), \\n color='orange')\\n\\n plt.axis([self.graf_t[0], self.graf_t[-1], -3, 3])\\n \\n plt.title(str(\\n QtGui.QApplication.translate(\\n \\\"MainWindow\\\", \\n \\\"Double Integrator\\\", \\n None, \\n QtGui.QApplication.UnicodeUTF8)))\\n \\n plt.suptitle(str(\\n QtGui.QApplication.translate(\\n \\\"MainWindow\\\", \\n \\\"Networked and Embedded Control Systems:\\\", \\n None, \\n QtGui.QApplication.UnicodeUTF8)))\\n \\n plt.xlabel(str(\\n QtGui.QApplication.translate(\\n \\\"MainWindow\\\", \\n \\\"t (s)\\\", \\n None, \\n QtGui.QApplication.UnicodeUTF8)))\\n \\n plt.ylabel(str(\\n QtGui.QApplication.translate(\\n \\\"MainWindow\\\", \\n \\\"Voltage (V)\\\", \\n None, \\n QtGui.QApplication.UnicodeUTF8)))\\n \\n plt.legend(bbox_to_anchor=(0, 1, 1, 0), loc=1, ncol=6, mode=\\\"expand\\\", borderaxespad=0.)\\n \\n filename = str(file_one)# + '.svg'\\n try:\\n plt.savefig(filename, dpi=300)\\n except ValueError as e:\\n print(e)\\n self.textBrowser.append(str(e))\\n self.textBrowser.append(\\n QtGui.QApplication.translate(\\n \\\"MainWindow\\\", \\n \\\"Trying to save as .svg\\\", \\n None, \\n QtGui.QApplication.UnicodeUTF8))\\n \\n filename = str(file_one) + '.svg'\\n plt.savefig(filename, dpi=300)\\n pass\\n except ImportError as e:\\n print(e)\\n self.textBrowser.append(str(e))\\n self.textBrowser.append(\\n QtGui.QApplication.translate(\\n \\\"MainWindow\\\", \\n \\\"Trying to save as .svg\\\", \\n None, \\n QtGui.QApplication.UnicodeUTF8))\\n \\n filename = str(file_one) + '.svg'\\n plt.savefig(filename, dpi=300)\\n pass\\n except:\\n self.textBrowser.append(\\\"Error al guardar la imatge\\\")\\n \\n plt.clf()\",\n \"def save(self):\\n filename = os.path.expanduser(\\\"~/\\\" + self.name)\\n print(filename)\\n np.savetxt(filename + \\\"_left.txt\\\", self.central)\\n np.savetxt(filename + \\\"_right.txt\\\", self.boundaries)\",\n \"def write_bgf(self, filename):\\n body = [\\\"BIOGRF{0:>5s}\\\\n\\\".format(self.biogrf)]\\n if self.descrp:\\n body.append(\\\"DESCRP {0}\\\\n\\\".format(self.descrp))\\n else:\\n body.append(\\\"DESCRP {0}\\\\n\\\".format(filename))\\n body.append(\\\"FORCEFIELD {0}\\\\n\\\".format(self.ff))\\n body.append(\\\"FORMAT ATOM (a6,1x,i5,1x,a5,1x,a3,1x,a1,1x,a5,3f10.5\\\"\\n \\\",1x,a5,i3,i2,1x,f8.5,i2,i4,f10.5)\\\\n\\\")\\n atoms = []\\n hetatms = []\\n conect = []\\n for atom in self.atoms:\\n a, c = atom.writeline()\\n if atom.record == 'ATOM':\\n atoms.append(a)\\n elif atom.record == 'HETATM':\\n hetatms.append(a)\\n conect.append(c)\\n body.extend(atoms)\\n body.extend(hetatms)\\n body.append(\\\"FORMAT CONECT (a6,14i6)\\\\nFORMAT ORDER (a6,i6,13f6.3)\\\\n\\\")\\n body.extend(conect)\\n body.append(\\\"END\\\\n\\\")\\n with open(filename, 'w') as f:\\n f.writelines(body)\",\n \"def save_image(self, file_obj):\\n manager = pyglet.image.get_buffer_manager()\\n colorbuffer = manager.get_color_buffer()\\n\\n # if passed a string save by name\\n if hasattr(file_obj, 'write'):\\n colorbuffer.save(file=file_obj)\\n else:\\n colorbuffer.save(filename=file_obj)\",\n \"def save(self, fileName, *args):\\n if self._renderRequired:\\n self.render()\\n self.qimage.save(fileName, *args)\",\n \"def on_save(self, event):\\n file_choices = \\\"PNG (*.png)|*.png\\\"\\n \\n dlg = wx.FileDialog(\\n self, \\n message=\\\"Save plot as...\\\",\\n defaultDir=os.getcwd(),\\n defaultFile=\\\"plot.png\\\",\\n wildcard=file_choices,\\n style=wx.SAVE)\\n \\n if dlg.ShowModal() == wx.ID_OK:\\n path = dlg.GetPath()\\n self.canvas.print_figure(path, dpi=self.dpi)\\n self.flash_status_message(\\\"Saved to %s\\\" % path)\",\n \"def save_as(\\n cls, figure_or_data, filename, format=None, width=None, height=None, scale=None\\n ):\\n # todo: format shadows built-in name\\n (base, ext) = os.path.splitext(filename)\\n if not ext and not format:\\n filename += \\\".png\\\"\\n elif ext and not format:\\n format = ext[1:]\\n elif not ext and format:\\n filename += \\\".\\\" + format\\n\\n img = cls.get(figure_or_data, format, width, height, scale)\\n\\n f = open(filename, \\\"wb\\\")\\n f.write(img)\\n f.close()\",\n \"def saveView(self, filename):\\n\\n pixmap = self.grab();\\n ok = pixmap.save(filename)\\n if not ok:\\n raise IOError('Unable to save image ' + filename)\",\n \"def write (self, file):\\n\\t\\tfile.write (self.pack ())\",\n \"def shape_writer(f):\\n\\n # extract the file extension\\n _, ext = os.path.splitext(f)\\n\\n # if the file is a dxf then parse it otherwise\\n # loads it as a pickle\\n if ext.lower() == \\\".dxf\\\":\\n dxf = dxfParser.parse(f)\\n shapes = []\\n rects = []\\n for s in dxf:\\n bounding_rect = s.cutPolyline.getBoundsRectanglePolyline()\\n rects.append(bounding_rect)\\n bounds = s.cutPolyline.getBounds()\\n tx = -bounds[\\\"left\\\"]\\n ty = -bounds[\\\"bottom\\\"]\\n s.cutPolyline.translatePoly(tx, ty)\\n shapes.append(s.cutPolyline.polylineToTuple())\\n\\n else: # if it's a pickle file\\n with open(f, \\\"rb\\\") as file:\\n dxf = pkl.load(file)\\n dxf = dxf[0]\\n shapes = []\\n rects = []\\n for s in dxf:\\n # same flow but shapes has no cutPolyline()\\n bounding_rect = s.getBoundsRectanglePolyline()\\n rects.append(bounding_rect)\\n bounds = s.getBounds()\\n tx = -bounds[\\\"left\\\"]\\n ty = -bounds[\\\"bottom\\\"]\\n s.translatePoly(tx, ty)\\n shapes.append(s.polylineToTuple())\\n\\n for i, shape in enumerate(shapes):\\n h = int(rects[i].coords[3][1] - rects[i].coords[1][1])\\n w = int(rects[i].coords[2][0] - rects[i].coords[0][0])\\n # create a blank image\\n img = np.zeros((h + 10, w + 10), dtype=np.uint8)\\n img.fill(255)\\n\\n polyx = []\\n polyy = []\\n\\n for coords in shape:\\n polyx.append(coords[0] + 5)\\n polyy.append(coords[1] + 5)\\n\\n pts = np.vstack((polyx, polyy)).astype(np.int32).T\\n\\n cv2.polylines(img, [pts], 0, 0, thickness=1)\\n if ext.lower() == \\\".dxf\\\":\\n cv2.imwrite(f\\\"{SOURCE_PATH}shape_{i}.png\\\", img)\\n else:\\n cv2.imwrite(f\\\"{PROD_PATH}\\\\\\\\shape_{i}.png\\\", img)\",\n \"def part1(width, height, size, color):\\n pass\",\n \"def save(self, filename):\\n o = open(filename, 'w')\\n o.write(self.write())\\n o.close()\",\n \"def fileResizeObscure(new_filepath):\\n # Resize\\n img1 = Image.open(new_filepath)\\n img2=image_reduce(img1)\\n *** Stopped working here\\n newpath=\\\"toupload\\\\\\\\%s\\\" % new_filepath\\n # Block ID\\n width=img2.size[0]\\n height=img2.size[1]\\n # Obscuring params were decided by trial and error using fraction of width and height\\n x1=int(0.16*width)\\n x2=int(0.28*width)\\n y1=int(0.94*height)\\n y2=int(0.98*height) \\n # Faster but easier to snoop? should not be since it changes the pixels\\n draw = ImageDraw.Draw(img2)\\n draw.rectangle([(x1,y1),(x2,y2)],fill=\\\"white\\\")\\n del draw\\n \\n img2.save(newpath,optimize=True,quality=95)\",\n \"def save(self, filename):\\n result = self.render()\\n\\n with open(filename, 'w') as f:\\n f.write(result)\",\n \"def save_frame(self, save_path_filename):\\n raise NotImplementedError\",\n \"def write_file(self,filename):\\n \\n with open(filename, 'w') as f:\\n tab_width = np.max([len(k) for k in self.header.keys()])\\n for k,v in self.header.items():\\n f.write(u'{0}:\\\\t{1}\\\\n'.format(k, v).encode('utf8').expandtabs(tab_width+2))\\n np.savetxt(f, self.data, fmt ='%f %f %f %d')\",\n \"def on_export(self):\\n path = os.path.dirname(os.path.realpath(__file__))\\n\\n filters = ('Portable Network Graphics (*.png);;'\\n 'Portable Document Format (*.pdf);;'\\n 'Postscript (*.ps);;'\\n 'Encapsulated Postscript (*.eps);;'\\n 'Scalable Vector Graphics (*.svg)')\\n\\n filename = QtGui.QFileDialog.getSaveFileName(self,\\n caption='Export figure',\\n directory=path,\\n filter=filters)\\n filename = str(filename)\\n\\n if filename != '':\\n previous_size = self.fig.get_size_inches()\\n self.fig.set_size_inches(float(self.le_width.text()),\\n float(self.le_height.text()))\\n\\n dpi = int(self.le_dpi.text())\\n\\n self.fig.savefig(filename, dpi=dpi, bbox_inches='tight')\\n self.fig.set_size_inches(previous_size)\\n\\n self.canvas.draw()\",\n \"def predefined_style(self, style):\\n if style == 'minimal':\\n self.style(box_style='', border_visible=True, border_color='black',\\n border_style='solid', border_width=1, border_radius=0,\\n padding='0.2cm', margin='0.3cm', font_family='',\\n font_size=None, font_style='', font_weight='')\\n self.save_button.button_style = ''\\n self.save_button.font_weight = 'normal'\\n elif (style == 'info' or style == 'success' or style == 'danger' or\\n style == 'warning'):\\n self.style(box_style=style, border_visible=True,\\n border_color= _map_styles_to_hex_colours(style),\\n border_style='solid', border_width=1, border_radius=10,\\n padding='0.2cm', margin='0.3cm', font_family='',\\n font_size=None, font_style='', font_weight='')\\n self.save_button.button_style = 'primary'\\n self.save_button.font_weight = 'bold'\\n else:\\n raise ValueError('style must be minimal or info or success or '\\n 'danger or warning')\",\n \"def save_as(self, filename):\\n opencv.imwrite(filename, self.img)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5784574","0.56733894","0.5626295","0.5541043","0.5428487","0.5386171","0.5383418","0.53502595","0.5343739","0.5342087","0.5294229","0.5275449","0.52629405","0.5256234","0.5255994","0.52103263","0.5183001","0.5153634","0.51445657","0.5137024","0.51188093","0.5094579","0.5079907","0.50793195","0.5068237","0.50477463","0.50238585","0.501057","0.4991059","0.49856266","0.49652815","0.49550298","0.49532488","0.49371842","0.49360657","0.49293527","0.49127555","0.49104375","0.4910173","0.4895891","0.4893277","0.48783234","0.48770747","0.48767325","0.48765728","0.48765728","0.48765728","0.4874011","0.487186","0.4871012","0.48680216","0.48564658","0.4844824","0.48298603","0.4827856","0.48245674","0.48205292","0.48182368","0.48181477","0.4813228","0.48089987","0.48025548","0.48020944","0.4797668","0.47969592","0.47939938","0.47888032","0.47874758","0.4784543","0.4776115","0.47753158","0.4764611","0.47636843","0.4762132","0.47615153","0.47607166","0.4759804","0.47589475","0.4750551","0.4736841","0.47367302","0.47328925","0.47299135","0.4729489","0.47282702","0.47249156","0.47193646","0.47184342","0.47181174","0.47172758","0.47165653","0.47149974","0.47117692","0.47114944","0.47102177","0.47030404","0.47025356","0.47025356","0.47022885","0.46995786"],"string":"[\n \"0.5784574\",\n \"0.56733894\",\n \"0.5626295\",\n \"0.5541043\",\n \"0.5428487\",\n \"0.5386171\",\n \"0.5383418\",\n \"0.53502595\",\n \"0.5343739\",\n \"0.5342087\",\n \"0.5294229\",\n \"0.5275449\",\n \"0.52629405\",\n \"0.5256234\",\n \"0.5255994\",\n \"0.52103263\",\n \"0.5183001\",\n \"0.5153634\",\n \"0.51445657\",\n \"0.5137024\",\n \"0.51188093\",\n \"0.5094579\",\n \"0.5079907\",\n \"0.50793195\",\n \"0.5068237\",\n \"0.50477463\",\n \"0.50238585\",\n \"0.501057\",\n \"0.4991059\",\n \"0.49856266\",\n \"0.49652815\",\n \"0.49550298\",\n \"0.49532488\",\n \"0.49371842\",\n \"0.49360657\",\n \"0.49293527\",\n \"0.49127555\",\n \"0.49104375\",\n \"0.4910173\",\n \"0.4895891\",\n \"0.4893277\",\n \"0.48783234\",\n \"0.48770747\",\n \"0.48767325\",\n \"0.48765728\",\n \"0.48765728\",\n \"0.48765728\",\n \"0.4874011\",\n \"0.487186\",\n \"0.4871012\",\n \"0.48680216\",\n \"0.48564658\",\n \"0.4844824\",\n \"0.48298603\",\n \"0.4827856\",\n \"0.48245674\",\n \"0.48205292\",\n \"0.48182368\",\n \"0.48181477\",\n \"0.4813228\",\n \"0.48089987\",\n \"0.48025548\",\n \"0.48020944\",\n \"0.4797668\",\n \"0.47969592\",\n \"0.47939938\",\n \"0.47888032\",\n \"0.47874758\",\n \"0.4784543\",\n \"0.4776115\",\n \"0.47753158\",\n \"0.4764611\",\n \"0.47636843\",\n \"0.4762132\",\n \"0.47615153\",\n \"0.47607166\",\n \"0.4759804\",\n \"0.47589475\",\n \"0.4750551\",\n \"0.4736841\",\n \"0.47367302\",\n \"0.47328925\",\n \"0.47299135\",\n \"0.4729489\",\n \"0.47282702\",\n \"0.47249156\",\n \"0.47193646\",\n \"0.47184342\",\n \"0.47181174\",\n \"0.47172758\",\n \"0.47165653\",\n \"0.47149974\",\n \"0.47117692\",\n \"0.47114944\",\n \"0.47102177\",\n \"0.47030404\",\n \"0.47025356\",\n \"0.47025356\",\n \"0.47022885\",\n \"0.46995786\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.72179383"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88579,"cells":{"query":{"kind":"string","value":"Save a simulated fragmented file version of the file. Trunfactor specifies how much of the data, sequentially from the start of file, should be written to the new file."},"document":{"kind":"string","value":"def savefragment(filepath, fname, outpath, truncfactor=0.5, preserve_name=False):\n\n # Read data\n infile = open(filepath, 'rb')\n data = infile.read()\n infile.close()\n\n # Write truncated filepath\n if not preserve_name:\n fpath = genSavePath(outpath, fname, modstring=f\"truncated{truncfactor}\")\n else:\n fpath = genSavePath(outpath, fname)\n\n \n\n ofile = open(fpath, 'wb')\n writelength = int(len(data) * truncfactor)\n ofile.write(data[:writelength])\n ofile.close()\n print( \"Saved {}\".format(fpath))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def write_data(infbfile,begin_N,dur_N,outfbfile):\n infbfile.seek_to_sample(begin_N)\n for i in range(begin_N,(begin_N+dur_N)):\n data = infbfile.read_sample()\n data.tofile(outfbfile)","def save(self, fname):\n lh_data = self.data[:len(self.lh_vertno)]\n rh_data = self.data[-len(self.rh_vertno):]\n\n print 'Writing STC to disk...',\n write_stc(fname + '-lh.stc', tmin=self.tmin, tstep=self.tstep,\n vertices=self.lh_vertno, data=lh_data)\n write_stc(fname + '-rh.stc', tmin=self.tmin, tstep=self.tstep,\n vertices=self.rh_vertno, data=rh_data)\n print '[done]'","def write_file(self):\r\n # -open file for writing\r\n f_fbob = open(self.fn_path, 'w')\r\n\r\n # -write header\r\n f_fbob.write('%s\\n' % (self.heading))\r\n\r\n # -write sections 1 & 2 : NOTE- what about NOPRINT?\r\n f_fbob.write('%10i%10i%10i%10i\\n' % (self.nqfb, self.nqcfb,\r\n self.nqtfb, self.iufbobsv))\r\n f_fbob.write('%10e\\n' % (self.tomultfb)) # check format\r\n\r\n # -write sections 3-5 looping through observations groups\r\n c = 0\r\n for i in range(self.nqfb):\r\n # while (i < self.nqfb):\r\n # write section 3\r\n f_fbob.write('{:10d}{:10d}\\n'.format(self.nqobfb[i],\r\n self.nqclfb[i]))\r\n\r\n # Loop through observation times for the groups\r\n for j in range(self.nqobfb[i]):\r\n # -write section 4\r\n f_fbob.write(\r\n '{}{:10d}{:10.4g}{}{:10.4g}\\n'.format(self.obsnam[c],\r\n self.irefsp[c],\r\n self.toffset[c], ' ',\r\n self.flwobs[c]))\r\n c += 1 # index variable\r\n\r\n # -write section 5 - NOTE- need to adjust factor for muliple obs same cell\r\n for j in range(abs(self.nqclfb[i])):\r\n if self.nqclfb[\r\n i] < 0: # set factor to 1.0 for all cells in group\r\n self.factor[i, :] = 1.0\r\n f_fbob.write('{:10d}{:10d}{:10d}{}{:10f}\\n'\r\n .format(self.layer[i, j], (self.row[i, j]),\r\n self.column[i, j],\r\n ' ', self.factor[\r\n i, j])) # note- is 10f good enough here?\r\n\r\n f_fbob.close()\r\n #\r\n # swm: BEGIN hack for writing standard file\r\n sfname = self.fn_path # swm:hack\r\n sfname += '_ins' # swm: hack\r\n # write header\r\n f_ins = open(sfname, 'w') # swm: hack for standard file\r\n f_ins.write('jif @\\n') # swm: hack for standard file\r\n f_ins.write('StandardFile 0 1 %s\\n' % (\r\n self.nqtfb)) # swm: hack for standard file\r\n for i in range(0, self.nqtfb):\r\n f_ins.write(\r\n '{}\\n'.format(self.obsnam[i])) # swm: hack for standard file\r\n\r\n f_ins.close()\r\n # swm: END hack for writing standard file\r\n\r\n return","def write_file(f_name, size, best, best_tour):\n new_file = open(\"Checking Tours/Genetic/TourfileA/tourNEW\"+f_name+\".txt\", 'w+')\n new_file.write(\"NAME = \" + f_name + \",\")\n new_file.write(\"\\nTOURSIZE = \" + str(size) + \",\")\n new_file.write(\"\\nLENGTH = \" + str(best) + \",\\n\")\n for i in range(size):\n new_file.write(str(best_tour[i]+1)+\",\")\n new_file.close()","def saveFullMouvement(filename, nbSteps, delay, Servos):\n\ttabPositions = [] # Cree un tableau vide\n\ti = 0 # Index de boucle\n\n\twhile i <= nbSteps: # Fait toutes les etapes\n\t\t# Sauvegarde l'etape dans le tableau\n\t\ttabPositions.append(getMouvementSteps(Servos))\n\t\ttime.sleep(delay) # Delai entre chaque etape\n\t\ti += 1 # Incremente l'index\n\n\t# Ecrit toutes les etapes dans le fichier\n\taxFiles.writeFile(tabPositions, filename)","def save(self, f):\n self.f = f\n for region in self.regions:\n ext = region.address & 0xFFFF0000\n self.write_hex_line(\n HexLine(0, EXTLINADR, struct.pack(\">H\", ext >> 16))\n )\n address = region.address - ext\n for chunk in chunks(region.data):\n if address >= 0x10000:\n ext += 0x10000\n self.write_hex_line(\n HexLine(0, EXTLINADR, struct.pack(\">H\", ext >> 16))\n )\n address -= 0x10000\n self.write_hex_line(HexLine(address, DATA, chunk))\n address += len(chunk)\n self.write_hex_line(HexLine(0, EOF))","def change_input(filename, frac_l=0.019994, force=25.0, time=200_000, seed=None):\r\n\r\n frac_sl = round(1.5 /(32**3 *3), 6)\r\n frac_l = round(frac_l -frac_sl, 6)\r\n frac_w = round(1 -frac_l -frac_sl, 6)\r\n \r\n params = {'Box': \"32 32 32\\t1 1 1\", 'RNGSeed': seed if seed is not None else -4073, 'Step': 0.02, 'Time': time, \r\n 'SamplePeriod': 100, 'AnalysisPeriod': 1000, 'DensityPeriod': time, 'DisplayPeriod': time //10, 'RestartPeriod': time,\r\n }\r\n\r\n with open(filename, 'rt') as rf:\r\n with open(filename+'_sim', 'wt') as wf:\r\n\r\n for line in rf:\r\n \r\n if line.startswith('Polymer\\tWater') or line.startswith('Polymer Water'):\r\n line = line.strip().split()\r\n line[2] = f\"{frac_w:.6f}\"\r\n \r\n # Converts list to list[str]\r\n line = list(map(str, line))\r\n wf.write('\\t'.join(line) + '\\n')\r\n\r\n elif line.startswith('Polymer\\tLipid') or line.startswith('Polymer Lipid'):\r\n line = line.strip().split()\r\n line[2] = f\"{frac_l:.6f}\"\r\n\r\n # Converts list to list[str]\r\n line = list(map(str, line))\r\n wf.write('\\t'.join(line) + '\\n')\r\n \r\n elif line.startswith('Polymer\\tSingleLipid') or line.startswith('Polymer SingleLipid'):\r\n line = line.strip().split()\r\n line[2] = f\"{frac_sl:.6f}\"\r\n\r\n # Converts list to list[str]\r\n line = list(map(str, line))\r\n wf.write('\\t'.join(line) + '\\n')\r\n\r\n elif line.startswith('Command\\tConstantForceOnTarget') or line.startswith('Command ConstantForceOnTarget'):\r\n line = line.strip().split()\r\n\r\n if line[3] == \"singleLipidHead\":\r\n line[-1] = f\"{force /3:.6f}\" \r\n\r\n elif line[3] == \"lowerHeads\":\r\n line[-1] = f\"{force /3 /(1636):.6f}\"\r\n\r\n # Converts list to list[str]\r\n line = list(map(str, line))\r\n wf.write('\\t'.join(line) + '\\n')\r\n \r\n # if line.startswith('\tTimes\t0 1000'):\r\n # line = line.strip().split()\r\n # line[2] = f\"{time}\"\r\n \r\n # # Converts list to list[str]\r\n # line = list(map(str, line))\r\n # wf.write('\\t'.join(line) + '\\n') \r\n # line = next(rf) \r\n \r\n # if line.strip().split() and line.strip().split()[0] in params.keys():\r\n # key = line.strip().split()[0]\r\n # wf.write(f\"{key:<12}\\t{str(params[key])}\\n\")\r\n\r\n else:\r\n wf.write(line)","def save(self, filename):\n target = open(filename, 'w')\n target.write(\"\\\\data\\\\\\n\")\n target.write(\"ngram 1=\" + str(len(self.f1)) + \"\\n\\n\")\n target.write(\"\\\\1-grams:\\n\")\n for w,p in sorted(self.f1.items()): \n target.write(str(p) + \" \" + w + \"\\n\")\n target.write(\"\\\\end\\\\\\n\")\n target.close()","def save_file(self, sub):\n fileout = os.path.join(self.saving_dir, 'output_skeleton_' + str(sub) + '.nii.gz')\n print('writing altered skeleton to', fileout)\n aims.write(self.skel, fileout)","def write(self, fname):\n pass","def setFastFile(self,fname):\n self.fst_file = fname","def to_file(self, file_path, smirnoff_data):\n pass","def write_sum(self):\n with open('{}_Simulation_Fst.dat'.format(self.simulation_window), 'w+') as output:\n for line in self.fst_data:\n output.write(line)","def save_fits(data, fname):\n\tcols = fits.ColDefs(np.copy(data)) # This is somehow necessary.\n\ttbhdu = fits.BinTableHDU.from_columns(cols)\n\ttbhdu.writeto(fname, clobber=True)\n\t\n\treturn","def finish(self):\n self._fout.add_size()\n self._fout.add_padding()\n self._fout.close()","def tempfile(self,calcMD5=False,calcSHA1=False):\n import tempfile,hashlib\n tf = tempfile.NamedTemporaryFile()\n if calcMD5: tf.md5 = hashlib.md5()\n if calcSHA1: tf.sha1 = hashlib.sha1()\n for run in self.byteruns():\n self.imagefile.seek(run.img_start)\n count = run.bytes\n while count>0:\n xfer_bytes = min(count,1024*1024) # transfer up to a megabyte at a time\n buf = self.imagefile.read(xfer_bytes)\n tf.write(buf)\n if calcMD5: tf.md5.update(buf)\n if calcSHA1: tf.sha1.update(buf)\n count -= xfer_bytes\n tf.flush()\n return tf","def generate_file(self, filename, amount):\n with open(filename, \"w\", encoding=\"utf-8\") as fi:\n count = 0\n space = \"\" if self.token is Tokenization.byte or self.token is Tokenization.character else \" \"\n for generate_token in self.generate():\n count += 1\n outputStr = str(generate_token)\n outputStr += space\n fi.write(outputStr)\n if count >= amount:\n break","def moveNewFragmentsToTmpDir(options,nextTaskNum):\n for i in range(1,nextTaskNum):\n frag = getFragmentPath(options.tmpDir, options.fragBase, i)\n newfrag = getFragmentPath(\"%s%stmp\" % (options.tmpDir, os.sep), options.fragBase, i)\n os.rename(newfrag,frag)\n os.rmdir(\"%s%stmp\" % (options.tmpDir, os.sep))","def write_stc(filename, tmin, tstep, vertices, data):\n fid = open(filename, 'wb')\n\n # write start time in ms\n fid.write(np.array(1000 * tmin, dtype='>f4').tostring())\n # write sampling rate in ms\n fid.write(np.array(1000 * tstep, dtype='>f4').tostring())\n # write number of vertices\n fid.write(np.array(vertices.shape[0], dtype='>I4').tostring())\n # write the vertex indices\n fid.write(np.array(vertices, dtype='>I4').tostring())\n\n # write the number of timepts\n fid.write(np.array(data.shape[1], dtype='>I4').tostring())\n #\n # write the data\n #\n fid.write(np.array(data.T, dtype='>f4').tostring())\n\n # close the file\n fid.close()","def make_fet(self):\n fet_filename = self.filename + \".fet.\" + str(self.tet_num)\n with open(fet_filename, \"w\") as f:\n f.write(str(self.feature_array.shape[1]))\n f.write(\"\\n\")\n np.savetxt(f, self.feature_array, fmt=\"%1.5f\")","def write_chunk(chunk, token):\n dest = rem_dir('grab')\n # input(dest)\n file_name = '{}_{}'.format('cpf_temp', token)\n dest_file_name = os.path.join(os.path.abspath(dest), file_name)\n # input(dest_file_name)\n WRITE_STREAM = open(dest_file_name, 'wb')\n WRITE_STREAM.write(chunk)\n WRITE_STREAM.close()\n\n return True","def writeTmpFastq(self, fw_reads_path, rev_reads_path):\n try:\n fq1 = open(fw_reads_path, \"w+\")\n fq1.write(reads1_string)\n fq1.close()\n fq2 = open(rev_reads_path, \"w+\")\n fq2.write(reads2_string)\n fq2.close()\n except OSError:\n pass","def writeTmpFastq(self, fw_reads_path, rev_reads_path):\n try:\n fq1 = open(fw_reads_path, \"w+\")\n fq1.write(reads1_string)\n fq1.close()\n fq2 = open(rev_reads_path, \"w+\")\n fq2.write(reads2_string)\n fq2.close()\n except OSError:\n pass","def to_file(self, filename):\n self.header['n'] = self.n\n save_gyre(filename, self.header, self.data)","def writefragment(oldfrag,newfrag,verb=0):\n print(f\">>> writefragment: Writing fragment for job: {oldfrag} -> {newfrag}\")\n head = \"\"\"#! /usr/bin/env cmsRun\n# Generated with submit_fragment.py\"\"\"\n opts = \"\"\"# USER OPTIONS\nfrom FWCore.ParameterSet.VarParsing import VarParsing\noptions = VarParsing('analysis')\n#options.register('tag', \"\",mytype=VarParsing.varType.string)\noptions.register('index', -1,mytype=VarParsing.varType.int)\noptions.register('outdir', \".\",mytype=VarParsing.varType.string)\noptions.register('maxevts',100,mytype=VarParsing.varType.int)\noptions.register('seed', -1,mytype=VarParsing.varType.int)\noptions.parseArguments()\ntag = options.tag\nindex = options.index\noutdir = options.outdir\nseed = options.seed\nmaxevts = options.maxevts\nif index>=0:\n tag += \"_%04d\"%(index)\noutfile_RAW = \"file:%s/GENSIM%s.root\"%(outdir,tag)\noutfile_LHE = \"file:%s/LHE%s.root\"%(outdir,tag)\nprint(\">>> %-11s = %r\"%('index',index))\nprint(\">>> %-11s = %r\"%('seed',seed))\nprint(\">>> %-11s = %r\"%('maxevts',maxevts))\nprint(\">>> %-11s = %r\"%('outfile_RAW',outfile_RAW))\nprint(\">>> %-11s = %r\"%('outfile_LHE',outfile_LHE))\n\"\"\"\n seed = \"\"\"\n# RANDOM SEED\nif seed>0:\n process.RandomNumberGeneratorService.externalLHEProducer.initialSeed = int(seed)\nelse:\n from IOMC.RandomEngine.RandomServiceHelper import RandomNumberServiceHelper\n randSvc = RandomNumberServiceHelper(process.RandomNumberGeneratorService)\n randSvc.populate() # set random number each cmsRun\n\"\"\"\n \n # READ OLD FRAGMENT\n hasopts = False\n hasrand = False\n oldlines = [ ]\n if verb>=1:\n print(f\">>> writefragment: Opening {oldfrag}...\")\n with open(oldfrag,'r') as oldfile:\n for line in oldfile.readlines():\n if 'VarParsing' in line:\n hasopts = True\n warning(f\"Fragment {oldfrag} already has VarParsing...\",pre=\"writefragment: \")\n if 'process.RandomNumberGeneratorService' in line:\n hasrand = True\n oldlines.append(line)\n \n # WRITE NEW FRAGMENT\n flag = None\n if verb>=1:\n print(f\">>> writefragment: Writing {newfrag}...\")\n if os.path.isfile(newfrag):\n warning(f\"{newfrag} already exists!\",pre=\"writefragment: \")\n with open(newfrag,'w') as newfile:\n for line in head.split('\\n'):\n writeline(newfile,line,verb=verb)\n for line in oldlines:\n vline = line.rstrip('\\n')\n if 'cms.Process' in line: # insert user options\n for optline in opts.split('\\n'):\n writeline(newfile,optline,verb=verb)\n elif 'process.maxEvents' in line or 'process.externalLHEProducer' in line:\n flag = 'maxevts'\n elif 'process.LHEoutput' in line:\n flag = 'LHE'\n elif 'process.RAWSIMoutput' in line:\n flag = 'RAW'\n elif flag=='maxevts' and ('input' in line or 'nEvents' in line):\n line = rexp_nevts.sub(fr\"\\1(maxevts)\",line)\n vline = rexp_nevts.sub(fr\"\\1({green('maxevts')})\",vline)\n flag = None\n elif flag=='RAW' and 'fileName' in line:\n line = rexp_fname.sub(r\"\\1(outfile_RAW),\",line)\n vline = rexp_fname.sub(fr\"\\1({green('outfile_RAW')}),\",vline)\n flag = None\n elif flag=='LHE' and 'fileName' in line:\n line = rexp_fname.sub(fr\"\\1(outfile_LHE),\",line)\n vline = rexp_fname.sub(fr\"\\1({green('outfile_LHE')}),\",vline)\n flag = None\n if verb>=3:\n print(f\">>> writefragment: {vline}\")\n newfile.write(line)\n for line in seed.split('\\n'):\n writeline(newfile,line,verb=verb)\n \n return oldfrag","def save(self, save_path, step):\n \n p = Path(save_path) / \"{:04d}\".format(step)\n p.mkdir(parents=True, exist_ok=True)\n fname = str(p / \"data.npz\")\n np.savez_compressed(fname,\n n_bins=self.n_bins,\n ranges=self.ranges,\n V=self.V,\n next_state=self.next_state,\n next_reward=self.next_reward\n )","def resize_file(self,fobj, diff, BUFFER_SIZE=2 ** 16):\n\n fobj.seek(0, 2)\n filesize = fobj.tell()\n\n if diff < 0:\n if filesize + diff < 0:\n raise ValueError\n # truncate flushes internally\n fobj.truncate(filesize + diff)\n elif diff > 0:\n try:\n while diff:\n addsize = min(BUFFER_SIZE, diff)\n fobj.write(b\"\\x00\" * addsize)\n diff -= addsize\n fobj.flush()\n except IOError as e:\n if e.errno == errno.ENOSPC:\n # To reduce the chance of corrupt files in case of missing\n # space try to revert the file expansion back. Of course\n # in reality every in-file-write can also fail due to COW etc.\n # Note: IOError gets also raised in flush() due to buffering\n fobj.truncate(filesize)\n raise","def saveseed(self, seed):\n savefile = gettempdir() + '/last_test_seed_fate.tmp'\n if args.verbose:\n print('Saving run into ' + savefile)\n with open(savefile, 'w') as f:\n f.write(str(seed))","def writeRawFCD():\n global vehId, vehIdDict\n vehIdDict = {}\n vehId = 0\n day = 0\n\n def getVehId(orgId):\n \"\"\"creates new vehicle id's which consists only numerics\"\"\"\n global vehId, vehIdDict\n value = vehIdDict.get(orgId, vehId)\n if value is vehId:\n vehIdDict[orgId] = vehId\n vehId = (vehId + 1) % 65500\n return value\n\n outputFile = open(path.FQrawFCD, 'w')\n\n for period, quota, vtypeDictR, taxiSum in generatePeriodQuotaSets():\n day += 86400\n # reset dict so that every taxi (even if the vehicle is chosen several\n # times) gets its own id\n vehIdDict = {}\n # dataset=0\n sortedKeys = vtypeDictR.keys()\n sortedKeys.sort()\n for timestep in sortedKeys:\n taxiList = vtypeDictR[timestep]\n for tup in taxiList: # all elements in this timestep\n # calc timestep ->for every period /quota set a new day\n time = timestep + day\n time = calcTime.getDateFromDepart(time)\n # dataset+=1\n # print ouptut\n # veh_id date (time to simDate+time) x (remove and\n # set comma new)\n outputFile.write(str(getVehId(tup[0])) + '\\t' + time + '\\t' + tup[3][0:2] + '.' + tup[3][2:7] + tup[3][8:] +\n # y (remove and set comma new)\n # status speed form m/s in km/h\n '\\t' + tup[4][0:2] + '.' + tup[4][2:7] + tup[4][8:] + '\\t' + \"90\" + '\\t' + str(int(round(tup[2] * 3.6))) + '\\n')\n # print dataset, time\n print(vehId)\n outputFile.close()","def reMake(self, final_path, map_, chunk_path, delete_residuals=False):\n map_ = {int(k): v for k, v in map_.items()}\n print(\"[+] Remake started...\")\n try:\n file_content_string = \"\"\n for i in range(0, len(map_)):\n file_content_string += open(chunk_path + map_[i], \"r\").read()\n if delete_residuals == True: remove(chunk_path + map_[i])\n file_content = b64.b64decode(file_content_string)\n with open(final_path, \"wb\") as f:\n f.write(file_content)\n print(\"[+] Remake done.\")\n except Exception as e:\n print(e)\n print(\"[+] Remake went wrong.\")","def save_trans(self, fname):\n if not self.can_save:\n raise RuntimeError(\"Not enough information for saving transform\")\n trans_matrix = self.head_mri_trans\n trans = {'to': FIFF.FIFFV_COORD_MRI, 'from': FIFF.FIFFV_COORD_HEAD,\n 'trans': trans_matrix}\n write_trans(fname, trans)","def write(self, f):\n if self.best_mhc_align:\n mhc_align_str = self.best_mhc_align.subject_str()\n mhc_score_str = str(self.best_mhc_align.bit_score)\n else:\n mhc_align_str = \".\"\n mhc_score_str = \"0\"\n\n if self.best_non_mhc_align:\n non_mhc_align_str = self.best_non_mhc_align.subject_str()\n non_mhc_score_str = str(self.best_non_mhc_align.bit_score)\n else:\n non_mhc_align_str = \".\"\n non_mhc_score_str = \"0\"\n \n f.write(\"\\t\".join([self.locus, self.short_samp_id, self.name,\n str(self.length), mhc_align_str, non_mhc_align_str,\n mhc_score_str, non_mhc_score_str,\n str(self.n_mhc_align), str(self.n_non_mhc_align)]) + \"\\n\")","def write_file(self):\n file = open(self.__file_path, 'w+')\n file.truncate(0)\n file.write(self.__content)\n file.close()","def save_tmp_file(self, data):\n with open(self.tmp_file, 'wb') as f:\n f.write(data)","def dump_current_chunk(self, use_where):\n log.info(\"Dumping raw data onto local disk for further investigation\")\n log.info(\"Columns will be dumped in following order: \")\n log.info(\", \".join(self._pk_for_filter + self.checksum_column_list))\n for table_name in [self.table_name, self.new_table_name]:\n if table_name == self.new_table_name:\n # index for new schema can be any indexes that provides\n # uniqueness and covering old PK lookup\n idx_for_checksum = self.find_coverage_index()\n outfile = self._outfile_name(\n suffix=\".new\",\n chunk_id=0,\n # MySQL does create the file with the extension itself\n skip_compressed_extension=True,\n )\n else:\n # index for old schema should always be PK\n idx_for_checksum = \"PRIMARY\"\n outfile = self._outfile_name(\n suffix=\".old\",\n chunk_id=0,\n # MySQL does create the file with the extension itself\n skip_compressed_extension=True,\n )\n log.info(\"Dump offending chunk from {} into {}\".format(table_name, outfile))\n self.execute_sql(\n sql.dump_current_chunk(\n table_name,\n self.checksum_column_list,\n self._pk_for_filter,\n self.range_start_vars_array,\n self.select_chunk_size,\n idx_for_checksum,\n use_where,\n enable_outfile_compression=self.enable_outfile_compression,\n ),\n (outfile,),\n )","def Seperate(f_read, f_write_name):\n lines = f_read.readlines()\n line_s = [line.split() for line in lines]\n\n for i in range(6, 13):\n nbytes = pow(2,i)\n f_write = f_write_name + str(nbytes) + \"b.txt\"\n f = open(f_write, \"w+\")\n\n for line in line_s:\n if line[3] == str(nbytes):\n f.write(\" \".join(line))\n f.write(\"\\n\")\n f.close()","def store(self, filename):","def __create_test_file(self):\n self.test_file = os.path.join(os.path.dirname(self.server_path), \"data\")\n with open(self.test_file, \"ab+\") as f:\n n_blocks = int(self.args.size) // self.max_block_size\n for i in range(n_blocks):\n f.write(bytearray(os.urandom(self.max_block_size)))\n remaining = int(self.args.size) % self.max_block_size\n if remaining > 0:\n f.write(bytearray(os.urandom(remaining)))\n self.assertEqual(int(self.args.size), os.path.getsize(self.test_file))","def write_srf(self, to, quantity=\"frequency\", factor: numbers.Number=1.0):\n #tools.validate(Channel.write_srf, locals())\n try:\n to.write\n except AttributeError: # not an open file\n try:\n to = open(to, 'wb')\n except IsADirectoryError:\n to = open(os.path.join(to, \"specresp_\" +\n self.get_chanstr(full=True) +\n \".dat\"),\n 'wb')\n\n (x, y) = self.srf()\n if quantity == \"frequency\":\n pass\n elif quantity == \"wavelength\":\n x = physics.frequency2wavelength(x)\n elif quantity == \"wavenumber\":\n x = physics.frequency2wavenumber(x)\n else:\n raise ValueError(\"Unknown quantity: {}\".format(quantity))\n\n print(now(), \"Writing to\", to.name)\n numpy.savetxt(to, numpy.c_[x*factor, y])","def write(self, filename):\n assert filename[-3:]=='.fz','name must end in .fz'\n\n files.makedir_fromfile(filename)\n\n ucfilename=filename[0:-3]\n bname = os.path.basename(ucfilename)\n\n tmp_path = os.path.join(\n files.get_temp_dir(),\n bname,\n )\n files.makedir_fromfile(tmp_path)\n\n with TempFile(tmp_path) as tfile:\n super(CosmosMEDSMaker,self).write(tfile.path)\n self._compress_meds_file(tfile.path, filename)","def to_file(self, fn):\n store.store_dict(fn, 'trainalgorithm', self.to_dict())","def write_to_file_z(path):\n path1 = path + \"/z_Macros\"\n if not os.path.exists(path1):\n os.mkdir(path1)\n for e in range(int(e_steps)+1):\n filename = \"x0y0z%ske%s.mac\" %(dz*z + z_min, e*de + e_min)\n path = path1\n fullpath = os.path.join(path, filename)\n f = open(fullpath, \"w\")\n f.write('/rat/physics_list/OmitMuonicProcesses true\\n')\n f.write(\"/rat/physics_list/OmitHadronicProcesses true \\n\")\n f.write(\"\\n\")\n f.write(\"\\n\")\n f.write('/rat/db/set DETECTOR geo_file \"geo/snoplus.geo\"\\n')\n f.write('/rat/db/set GEO[scint] material \"labppo_scintillator\"\\n')\n f.write('/rat/db/set DAQ dqxx_info 0 \\n')\n f.write(\"/run/initialize \\n\")\n f.write(\"\\n\")\n f.write(\"\\n\")\n f.write(\"/rat/proc frontend\\n\")\n f.write(\"/rat/proc trigger\\n\")\n f.write(\"/rat/proc eventbuilder\\n\")\n f.write(\"/rat/proc count\\n\")\n f.write(\"/rat/procset update 100\\n\")\n f.write(\"/rat/proc calibratePMT\\n\")\n f.write(\"/rat/proc scintFitter\\n\")\n f.write(\"/rat/proclast outroot\\n\")\n f.write('/rat/procset file \"x0y0z%ske%s.root\"\\n' %(dz*z + z_min, e*de + e_min))\n f.write(\"\\n\")\n f.write(\"\\n\")\n f.write(\"/generator/add combo gun:point:poisson\\n\")\n f.write(\"# want random, isotropic momentum distribution; energy given in MeV\\n\")\n f.write(\"/generator/vtx/set e- 0 0 0 %s\\n\" %(e*de + e_min))\n f.write(\"# position given in Cartesians, relative to detector center, in mm\\n\")\n f.write(\"/generator/pos/set 0 0 %s\\n\" % (dz*z + z_min))\n f.write(\"/generator/rate/set 1\\n\")\n f.write(\"\\n\")\n f.write(\"\\n\")\n f.write(\"/rat/run/start %s\\n\" %(n))\n f.write(\"exit\")","def saveFile(self,newfile=None):\n if newfile == None:\n shutil.move(self.filename,self.filename+'~')\n self.handler = open(self.filename,'w')\n else:\n self.handler = open(newfile,'w')\n self.handler.writelines(self.content)\n self.handler.close()","def save(self, fname, snver=None):\n self._io.save(fname)","def save_data(self, f): \n if not self.sampling:\n self.convert_to_array()\n np.save(f, self.reads)","def backup_int_in_fname(num: int, file_name: str) -> None:\n with open(file_name, 'w') as fname:\n fname.write(str(num))","def _prepare_input_file(self, filename, numlines, maxvalue):\n with open(filename, 'a') as f:\n for _ in range(numlines):\n f.write(str(randrange(maxvalue)) + '\\n')\n self.filepath = f.name","def save_model(self, step):\n\n # file_name = params['name']\n # pickle.dump(self, gzip.open(file_name, 'wb'))","def _write_raw_fif(raw, bids_fname):\n raw.save(\n bids_fname,\n fmt=raw.orig_format,\n split_size=_FIFF_SPLIT_SIZE,\n split_naming=\"bids\",\n overwrite=True,\n )","def save_tsv_file(parsed_data):\n result_file.write('\\t'.join(parsed_data) + '\\n')","def write(self, file):\n pos = file.tell()\n pickle.dump((self.index, self.meta, self.info), file)\n file.seek(0)\n\n # update the header with the position of the content index.\n file.write(struct.pack('<Q', pos))","def create_file(tmpdir, flowcell, lane, read, file_content):\n\n file_name = f\"S1_FC000{flowcell}_L00{lane}_R_{read}.fastq.gz\"\n file_path = tmpdir / file_name\n file_path.write(file_content)\n return file_path","def writeFST(self,ofname,fstDict):\n try:\n ofh = open(ofname,'w')\n except:\n sys.stdout.write (\"Error opening %s\\n\" % ofname)\n return 0\n\n\n # writing FAST input: If the second field in the line is present in the dictionary,\n # write the new value. Otherwise\n # write the original line. special case for the file name fields \"\"\"\n for iln in range(len(self.lines_fast)):\n line = self.lines_fast[iln]\n flds = line.strip().split()\n if (len(flds) >1 and flds[1] in ['PtfmFile','TwrFile','BldFile(1)','BldFile(2)','BldFile(3)', 'ADfile','NoiseFile']):\n # substituting possibly modified file names for subfiles\n if (flds[1] == 'PtfmFile'):\n flds[0] = self.ptfm_file\n if (flds[1] == 'TwrFile'):\n flds[0] = self.twr_file\n if (flds[1] == 'ADAMSFile'):\n flds[0] = self.adams_file\n if (flds[1] == 'BldFile(1)'):\n flds[0] = self.blade1_file\n if (flds[1] == 'BldFile(2)'):\n flds[0] = self.blade2_file \n if (flds[1] == 'BldFile(3)'):\n flds[0] = self.blade3_file \n if (flds[1] == 'ADfile'):\n flds[0] = self.ad_file \n if (flds[1] == 'NoiseFile'):\n flds[0] = self.noise_file \n flds[0] = \"\\\"%s\\\"\" % flds[0] ## put the quote back on\n oline = ' '.join(flds)\n ofh.write(oline)\n ofh.write('\\n')\n\n elif (len(flds)>1 and flds[1] in fstDict):\n # replacing this entry with something from fstDict\n f0 = '{:.2f} '.format(fstDict[flds[1]])\n oline = ' '.join([f0] + flds[1:])\n ofh.write(oline)\n ofh.write('\\n')\n\n elif (len(flds)>1 and flds[1] == \"SumPrint\"):\n # special case to deal with either V7.1 OR v7.2\n ofh.write(line)\n nextln = self.lines_fast[iln+1].split()\n if (self.fst_file_type == 0 and self.fst_exe_type == 1):\n if nextln[1] != \"OutFileFmt\": ## this check should not be necessary if fst_xxx_type are correct\n ofh.write(\"1 OutFileFmt - Format for tabular (time-marching) output file(s) (1: text file [<RootName>.out], 2: binary\\n\") \n elif (self.fst_file_type == 1 and self.fst_exe_type == 0):\n if nextln[1] != \"OutFileFmt\": ## this check should not be necessary if fst_xxx_type are correct\n # skip line \n iln += 1\n elif (len(flds) > 0 and flds[0] == \"END\"):\n # uh oh, better back up and write the outputs!\n if self.output_list != None:\n for out in self.output_list:\n ofh.write(\"\\\"%s\\\"\\n\" % out)\n ofh.write(line)\n else:\n # just write the line unmodified\n ofh.write(line)\n\n ofh.close()\n\n return 1","def create_file(toy_data, filename):\n root_file = ROOT.TFile.Open(filename, \"RECREATE\")\n \n bin_edges = toy_data[\"bin_edges\"]\n sig = create_th1f(bin_edges, toy_data[\"sig\"], toy_data[\"sig_stat\"])\n sig.SetName(\"signal\")\n\n data = create_th1f(bin_edges, toy_data[\"data\"], toy_data[\"data_stat\"])\n data.SetName(\"data\")\n\n bkg = create_th1f(bin_edges, toy_data[\"bkg\"], toy_data[\"bkg_stat\"])\n bkg.SetName(\"bkg\")\n\n root_file.Write()\n root_file.Close()","def StoreAntirollback(now, ar_filename, kern_f):\n print 'antirollback time now ' + str(now)\n sys.stdout.flush()\n kern_f.write(str(now))\n kern_f.flush()\n tmpdir = os.path.dirname(ar_filename)\n with tempfile.NamedTemporaryFile(mode='w', dir=tmpdir, delete=False) as f:\n f.write(str(now) + '\\n')\n f.flush()\n os.fsync(f.fileno())\n os.rename(f.name, ar_filename)","def reload_tailed_file(self):\n try:\n self.file_ = open(self.tailed_file, \"r\")\n self.size = os.path.getsize(self.tailed_file)\n\n # Go to the head of file\n self.file_.seek(0, 1)\n\n return True\n except:\n return False","def split_file(in_file, num_splits, split_dir, mut_file):\n\n # create the output directory if it does\n # not exist\n if not os.path.exists(split_dir):\n os.mkdir(split_dir)\n\n # open the info file\n f = open(in_file)\n pdb_header = f.readline()\n\n # open the mutation file\n m = open(mut_file)\n mut_header = m.readline()\n\n # read into a dictionary containing\n # structure ids as keys and lines pertaining\n # to it as values\n pdb_dict = read_file(f)\n mut_dict = read_file(m)\n\n # determine total num of ids in file\n total_ids = len(list(pdb_dict.keys()))\n print(total_ids)\n # determine num of ids to put in each split\n num_ids = int(total_ids/num_splits)\n\n # counters\n count_file = 0\n count_id = num_ids\n\n # randomize order of insertions\n keys = list(pdb_dict.keys())\n random.shuffle(keys)\n\n # iterate through dict and write to files\n #for key in sorted(pdb_dict):\n for key in keys:\n\n # check if we need a new file\n if (count_id == num_ids and count_file < num_splits):\n count_id = 0\n pdb_out = open(split_dir + \"/pdb_info_split_\" + str(count_file) + \".txt\", 'w')\n pdb_out.write(pdb_header)\n mut_out = open(split_dir + \"/mut_info_split_\" + str(count_file) + \".txt\", 'w')\n mut_out.write(mut_header)\n count_file += 1\n\n # write all lines pertaining to the structure id\n for line in pdb_dict[key]:\n pdb_out.write(line)\n if key in mut_dict:\n for line in mut_dict[key]:\n mut_out.write(line)\n\n count_id += 1","def writeFile(self, f, fname):\n with open(self.PATH + fname, 'wb') as handle:\n pickle.dump(f, handle, protocol = pickle.HIGHEST_PROTOCOL)","def write_flow(flow, filename):\n f = open(filename, 'wb')\n magic = numpy.array([202021.25], dtype=numpy.float32)\n (height, width) = flow.shape[0:2]\n w = numpy.array([width], dtype=numpy.int32)\n h = numpy.array([height], dtype=numpy.int32)\n magic.tofile(f)\n w.tofile(f)\n h.tofile(f)\n flow.tofile(f)\n f.close()","def processfile(file, out, me):\n if out.endswith('.npz'):\n out = out[:-4]\n out = out + ('-%03d' % me) + '.npz'\n if os.path.exists(out):\n return\n f = QPM.QPMSubsampleFile(file)\n xis = []\n mybf = QPM.LogWindowBiasFunction(edges[me], edges[me + 1])\n mymock = QPM.halomock(f, 1e6, mybf, continuous=False)\n for i in range(me + 1):\n bf = QPM.LogWindowBiasFunction(edges[i], edges[i + 1])\n mock = QPM.halomock(f, 1e6, bf, continuous=False)\n # the error is nonsense since we have just one sample\n # deal with it in combine\n xi = QPM.xi([mock], mocks2=[mymock])\n r = xi[0]\n xis.append(xi[1])\n print edges[i], edges[i + 1], len(mock[0]), mock[1].sum()\n numpy.savez(out, r=r, xi=xis, edges=edges, N=1e6, me=me)","def write_flow(flow, filename):\n f = open(filename, 'wb')\n magic = np.array([202021.25], dtype=np.float32)\n (height, width) = flow.shape[0:2]\n w = np.array([width], dtype=np.int32)\n h = np.array([height], dtype=np.int32)\n magic.tofile(f)\n w.tofile(f)\n h.tofile(f)\n flow.tofile(f)\n f.close()","def save(self, fname):\n pass","def WriteCurrentHists( filename='hist.root') :\n\n file = ROOT.TFile.Open( filename, 'RECREATE')\n\n for hist, samp in samples.samples.iteritems() :\n newhist = samp.hist.Clone(hist)\n file.cd()\n newhist.Write()\n\n file.Close()","def _create_sparsed_file(self, nms, path, size):\n nms.appliance.execute(\n 'truncate --size %(size)dG %(path)s' % {\n 'path': path,\n 'size': size\n }\n )","def saveUploadedRecipe(self, file):\r\n filename = str(file)\r\n with open(os.path.join(main.settings.RECIPE_DIR, filename), 'wb+') as destination:\r\n for chunk in file.chunks():\r\n destination.write(chunk)","def write_dftb_in(self, filename):\n\n outfile = open(filename, 'w')\n outfile.write('Geometry = GenFormat { \\n')\n #outfile.write(' <<< \"geo_end.gen\" \\n')\n outfile.write(' <<< %s \\n' %self.geo_fname)\n outfile.write('} \\n')\n outfile.write(' \\n')\n\n params = self.parameters.copy()\n\n s = 'Hamiltonian_MaxAngularMomentum_'\n for key in params:\n if key.startswith(s) and len(key) > len(s):\n break\n else:\n # User didn't specify max angular mometa. Get them from\n # the .skf files:\n symbols = set(self.atoms.get_chemical_symbols())\n for symbol in symbols:\n path = os.path.join(self.slako_dir,\n '{0}-{0}.skf'.format(symbol))\n l = read_max_angular_momentum(path)\n params[s + symbol] = '\"{}\"'.format('spdf'[l])\n\n # --------MAIN KEYWORDS-------\n previous_key = 'dummy_'\n myspace = ' '\n for key, value in sorted(params.items()):\n current_depth = key.rstrip('_').count('_')\n previous_depth = previous_key.rstrip('_').count('_')\n for my_backsclash in reversed(\n range(previous_depth - current_depth)):\n outfile.write(3 * (1 + my_backsclash) * myspace + '} \\n')\n outfile.write(3 * current_depth * myspace)\n if key.endswith('_') and len(value) > 0:\n outfile.write(key.rstrip('_').rsplit('_')[-1] +\n ' = ' + str(value) + '{ \\n')\n elif (key.endswith('_') and (len(value) == 0) \n and current_depth == 0): # E.g. 'Options {'\n outfile.write(key.rstrip('_').rsplit('_')[-1] +\n ' ' + str(value) + '{ \\n')\n elif (key.endswith('_') and (len(value) == 0) \n and current_depth > 0): # E.g. 'Hamiltonian_Max... = {'\n outfile.write(key.rstrip('_').rsplit('_')[-1] +\n ' = ' + str(value) + '{ \\n')\n elif key.count('_empty') == 1:\n outfile.write(str(value) + ' \\n')\n elif ((key == 'Hamiltonian_ReadInitialCharges') and \n (str(value).upper() == 'YES')):\n f1 = os.path.isfile(self.directory + os.sep + 'charges.dat')\n f2 = os.path.isfile(self.directory + os.sep + 'charges.bin')\n if not (f1 or f2):\n print('charges.dat or .bin not found, switching off guess')\n value = 'No'\n outfile.write(key.rsplit('_')[-1] + ' = ' + str(value) + ' \\n')\n else:\n outfile.write(key.rsplit('_')[-1] + ' = ' + str(value) + ' \\n')\n # point\n if self.pcpot is not None and ('DFTB' in str(value)):\n outfile.write(' ElectricField = { \\n')\n outfile.write(' PointCharges = { \\n')\n outfile.write(\n ' CoordsAndCharges [Angstrom] = DirectRead { \\n')\n outfile.write(' Records = ' +\n str(len(self.pcpot.mmcharges)) + ' \\n')\n outfile.write(\n ' File = \"dftb_external_charges.dat\" \\n')\n outfile.write(' } \\n')\n outfile.write(' } \\n')\n outfile.write(' } \\n')\n previous_key = key\n\n current_depth = key.rstrip('_').count('_')\n for my_backsclash in reversed(range(current_depth)):\n outfile.write(3 * my_backsclash * myspace + '} \\n')\n #outfile.write('ParserOptions { \\n')\n #outfile.write(' IgnoreUnprocessedNodes = Yes \\n')\n #outfile.write('} \\n')\n #if self.do_forces:\n # outfile.write('Analysis { \\n')\n # outfile.write(' CalculateForces = Yes \\n')\n # outfile.write('} \\n')\n\n outfile.close()","def save_as_fits(self, filename):","def save_to(self, f: BinaryIO):\n raise NotImplementedError","def write(self):\n # # Sometimes file is not written properly. So delete and rewrite it\n # os.system('rm {}'.format(snip_dir + '/' + self.name))\n # if 'NUM_TIME_STEPS' not in self.define.keys():\n # warnings.warn('NUM_TIME_STEPS missing in header. Execution may hang!')\n with open(snip_dir + '/' + self.name, 'w') as f:\n f.write('/* Temporary generated file for snip process definitions before compilation */\\n')\n f.write(self.__str__())\n\n # os.system('ls {}'.format(snip_dir + '/' + self.name))","def write_to_fits(self, filename=None, gain=GAIN):\n\n hdu_new = self.hdu_ideal\n hdu_new[1].data = (self.data/gain).astype('uint16') # Convert to ADU in 16 bit integers.\n\n if filename is None:\n filename = self.ima_path[:-5] + self.modif_str + '.fits'\n hdu_new.writeto(filename, overwrite=True)\n\n print('Writing to file: ' + filename)","def downsample(self, tfactor=1, ffactor=1, gulp=512, filename=None,\n back_compatible=True, **kwargs):\n if filename is None:\n filename = f\"{self.header.basename}_f{ffactor:d}_t{tfactor:d}.fil\"\n if self.header.nchans % ffactor != 0:\n raise ValueError(\"Bad frequency factor given\")\n\n # Gulp must be a multiple of tfactor\n gulp = int(np.ceil(gulp / tfactor) * tfactor)\n\n out_file = self.header.prepOutfile(\n filename,\n {\n \"tsamp\": self.header.tsamp * tfactor,\n \"nchans\": self.header.nchans // ffactor,\n \"foff\": self.header.foff * ffactor,\n },\n back_compatible=back_compatible\n )\n\n write_ar = np.zeros(\n gulp * self.header.nchans // ffactor // tfactor, dtype=self.header.dtype,\n )\n for nsamps, _ii, data in self.readPlan(gulp, **kwargs):\n lib.downsample(data, write_ar, tfactor, ffactor, self.header.nchans, nsamps)\n out_file.cwrite(\n write_ar[:nsamps * self.header.nchans // ffactor // tfactor]\n )\n return out_file.name","def write(self, file):\n #write header\n self.ID.write(file)\n if (self.write_size): \n self.size.write(file)\n for variable in self.variables:\n variable.write(file)\n for subchunk in self.subchunks:\n subchunk.write(file)","def write_uem(uemf, uem, n_digits=3):\n with open(uemf, 'wb') as f:\n for file_id in sorted(iterkeys(uem)):\n for onset, offset in sorted(uem[file_id]):\n line = ' '.join([file_id,\n '1',\n format_float(onset, n_digits),\n format_float(offset, n_digits)\n ])\n f.write(line.encode('utf-8'))\n f.write(b'\\n')","def write_to_file_x(path):\n path1 = path + \"/x_Macros\"\n if not os.path.exists(path1):\n os.mkdir(path1)\n for e in range(int(e_steps)+1):\n filename = \"x%sy0z0ke%s.mac\" %(dx*x + x_min, e*de + e_min)\n path = path1\n fullpath = os.path.join(path, filename)\n f = open(fullpath, \"w\")\n f.write('/rat/physics_list/OmitMuonicProcesses true\\n')\n f.write(\"/rat/physics_list/OmitHadronicProcesses true \\n\")\n f.write(\"\\n\")\n f.write(\"\\n\")\n f.write('/rat/db/set DETECTOR geo_file \"geo/snoplus.geo\"\\n')\n f.write('/rat/db/set GEO[scint] material \"labppo_scintillator\"\\n')\n f.write('/rat/db/set DAQ dqxx_info 0\\n')\n f.write(\"/run/initialize \\n\")\n f.write(\"\\n\")\n f.write(\"\\n\")\n f.write(\"/rat/proc frontend\\n\")\n f.write(\"/rat/proc trigger\\n\")\n f.write(\"/rat/proc eventbuilder\\n\")\n f.write(\"/rat/proc count\\n\")\n f.write(\"/rat/procset update 100\\n\")\n f.write(\"/rat/proc calibratePMT\\n\")\n f.write(\"/rat/proc scintFitter\\n\")\n f.write(\"/rat/proclast outroot\\n\")\n f.write('/rat/procset file \"x%sy0z0ke%s.root\"\\n' %(dx*x + x_min, e*de + e_min))\n f.write(\"\\n\")\n f.write(\"\\n\")\n f.write(\"/generator/add combo gun:point:poisson\\n\")\n f.write(\"# want random, isotropic momentum distribution; energy given in MeV\\n\")\n f.write(\"/generator/vtx/set e- 0 0 0 %s\\n\" %(e*de + e_min))\n f.write(\"# position given in Cartesians, relative to detector center, in mm\\n\")\n f.write(\"/generator/pos/set %s 0 0\\n\" % (dx*x + x_min))\n f.write(\"/generator/rate/set 1\\n\")\n f.write(\"\\n\")\n f.write(\"\\n\")\n f.write(\"/rat/run/start %s\\n\" %(n))\n f.write(\"exit\")","def save(self,outPath=None):\n if (not self.canSave): raise StateError(_(\"Insufficient data to write file.\"))\n if not outPath:\n fileInfo = self.fileInfo\n outPath = os.path.join(fileInfo.dir,fileInfo.name)\n out = file(outPath,'wb')\n #--Tes3 Record\n self.tes3.setChanged()\n self.tes3.hedr.setChanged()\n self.tes3.hedr.numRecords = len(self.records) #--numRecords AFTER TES3 record\n self.tes3.getSize()\n self.tes3.dump(out)\n #--Other Records\n for record in self.records:\n record.getSize()\n record.dump(out)\n out.close()","def init_flowgram_file(filename=None, n=0, l=400, prefix=\"/tmp/\"):\r\n\r\n if (filename is None):\r\n fd, filename = mkstemp (dir=prefix, suffix=\".dat\")\r\n close(fd)\r\n\r\n fh = open(filename, \"w\")\r\n fh.write(\"%d %d\\n\" % (n, l))\r\n return (fh, filename)","def __write_measurement(self, measurement):\n with self.__filename.open(mode='a') as history_file:\n history_file.write(measurement + '\\n')","def to_file(self, fname, delimiter=\"\\t\", encoding=\"utf-8\"):\n with open(fname, \"wb\") as fh:\n for key, score in self.ranked_items():\n fh.write(self.to_record(key, score, delimiter).encode(encoding))","def write_towhee_restart(self, filename, pbc=(0, 0, 0)):\n seeds = [5054388, 14604618, 6176650, 7526479, 6525, 10097385, 9059353,\n 14349506, 535, 7287374, 12195841, 7272997, 5692437, 11292972,\n 1589479, 16351161, 14342867, 3500530, 14385737, 2924396,\n 11857489, 6765405, 12074244, 5940539, 3050519]\n version = 6\n numcycles = 0\n numboxes = 1\n nummoltypes = 1\n maxtranssingle = 0.5\n maxtranscom = 0.15305334\n maxrot = 0.672082\n maxvoldis = [[1.0, 1.0, 1.0], [1.0, 1.0, 1.0], [1.0, 1.0, 1.0]]\n if type(pbc) is list or type(pbc) is tuple:\n pbc = np.asarray(pbc)\n length = np.asarray(self.length) + pbc\n hmatrix = np.diag(length)\n maxvoldis.extend(list(hmatrix))\n with open(filename, 'w') as f:\n f.write(f\"\\t\\t{version}\\n\")\n f.write(\"\\t\" + \"\\t \".join(map(str, seeds)) + \"\\n\")\n f.write(f\"\\t{numcycles} \\t\\t{numboxes} \\t\\t{nummoltypes}\\n\")\n f.write(f\"\\t{maxtranssingle:20.15f}\\n\")\n f.write(f\"\\t{maxtranscom:20.15f}\\n\")\n f.write(f\"\\t{maxrot:20.15f}\\n\\n\")\n for row in maxvoldis:\n f.write(f\"\\t{row[0]:20.15f} \\t{row[1]:20.15f} \\t{row[2]:20.15f}\\n\")\n f.write(f\"\\t{self.numatom // self.molsize}\\n\")\n f.write(f\"\\t{self.molsize}\\n\")\n f.write(\"\\t \".join(map(str, list(self.contents['Mol_type'].astype(int)))) + \"\\n\")\n f.write(\"\\t \".join(map(str, list(self.contents['Box_ID'].astype(int)))) + \"\\n\")\n df = self.contents[['X', 'Y', 'Z']].copy()\n np.savetxt(f, df.values, fmt=\" %20.15f\"*3)","def write_file(self):\n print 'Writing '+self.name+' binary...'\n if self.vals is not None:\n if len(self.vals) == self.size:\n stream = self.pack_mem()\n with open(self.name+'.bin','wb') as f:\n f.write(stream)\n print 'File written: '+self.name+'.bin'\n else:\n print 'Error: input array for '+self.name+'is not the right '+\\\n 'size (should be '+str(self.size)+'). Skipping.'\n else:\n print 'No array provided, skipping.'","def resize_file(fobj, diff, BUFFER_SIZE=2 ** 16):\n\n fobj.seek(0, 2)\n filesize = fobj.tell()\n\n if diff < 0:\n if filesize + diff < 0:\n raise ValueError\n # truncate flushes internally\n fobj.truncate(filesize + diff)\n elif diff > 0:\n try:\n while diff:\n addsize = min(BUFFER_SIZE, diff)\n fobj.write(b\"\\x00\" * addsize)\n diff -= addsize\n fobj.flush()\n except IOError as e:\n if e.errno == errno.ENOSPC:\n # To reduce the chance of corrupt files in case of missing\n # space try to revert the file expansion back. Of course\n # in reality every in-file-write can also fail due to COW etc.\n # Note: IOError gets also raised in flush() due to buffering\n fobj.truncate(filesize)\n raise","def __appendToFile(self, st):\n fh = open(self.__fileName, \"a\")\n line = st.get_id_student() + \" \" + st.get_nume_student()\n fh.write(\"\\n\")\n fh.write(line)\n fh.close()","def writeHedr(self):\n path = os.path.join(self.dir,self.name)\n out = file(path,'r+b')\n out.seek(16) #--Skip to Hedr record data\n self.tes3.hedr.getSize()\n self.tes3.hedr.dump(out)\n out.close()\n #--Done\n self.getHeader()\n self.setMTime()","def write_file_simple(self,filename):\n\n output = open(filename,\"w\")\n # write header\n output.write(\"# %1s %3s %22s %6s %22s\\n\"%(\"l\",\"n\",\"nu_theo (muHz)\",\"unused\",\"Inertia\"))\n for i in range(self.modes.shape[0]):\n output.write(\" %1d %3d %22.15e 0.0 %22.15e\\n\"%( \\\n self.modes[\"l\"][i], \\\n self.modes[\"n\"][i], \\\n self.modes[\"freq\"][i]*self.glb[ifreq_ref], \\\n self.modes[\"inertia\"][i]))\n output.close()","def newfile(self) :\n\n\t\tfrom tempfile import mkstemp\n\t\timport os\n\t\tglobal configurer\n\n\t\tfd,name = mkstemp(suffix='.blend')\n\t\tos.close(fd)\n\t\tself.name = name\n\t\tfd = open(name,'wb', configurer.get('ServerBufferSize'))\n\t\tself.fd = fd\n\t\tprint name\n\t\treturn 1","def dump(self, step=None):\n if self._compressed:\n np.savez_compressed(self._file_path, **self._data)\n else:\n np.savez(self._file_path, **self._data)","def random_split_tf_record(file, filenames, ratios=(0.5, 0.5)):\n assert (len(filenames) == len(ratios)) and (len(filenames) == 2), 'Support two parts only'\n\n if tf.gfile.Exists(filenames[0]) or tf.gfile.Exists(filenames[1]):\n raise FileExistsError('File exists. Continuing will overwrite it. Abort!')\n\n ratio = ratios[0] / sum(ratios)\n\n with TFRecordWriter(filenames[0]) as tfwriter1, TFRecordWriter(filenames[1]) as tfwriter2:\n for example in tf.python_io.tf_record_iterator(file):\n if np.random.rand(1) <= ratio:\n tfwriter1.write(example)\n else:\n tfwriter2.write(example)\n\n tfwriter1.flush()\n tfwriter2.flush()","def write_flt_file(filename, data, dsize):\n binfile = open(filename,'wb')\n\n dsize = numpy.array(dsize)\n dsize[-1] = data.shape[0]\n\n header = [len(dsize)] # dimension\n header.extend(list(dsize)) # size\n header.append(4) # data type: float\n header.append(dsize.prod()) # total length of data\n\n a = array.array('i')\n a.fromlist(header)\n if is_little_endian():\n a.byteswap()\n\n a.tofile(binfile)\n\n a = array.array('f')\n for o in data:\n a.fromlist(list(o))\n if is_little_endian():\n a.byteswap()\n a.tofile(binfile)\n binfile.close()","def write_checkpoint(self):\n self.file_checkpoint_data = open(self.path_checkpoint, \"a+\")\n array_to_write = [str(self.radious), self.type_feature, self.type_filtering, self.h_filterig]\n self.file_checkpoint_data.write(','.join(array_to_write) + \"\\n\")\n self.file_checkpoint_data.flush()","def save_whiten_mat(W):\n w_id = open('data/W.bin','w')\n W.tofile(w_id)\n w_id.close()","def write_file(self,f=None):\n nrow, ncol, nlay, nper = self.parent.nrow_ncol_nlay_nper\n # Open file for writing\n if f is None:\n f = open(self.fn_path, 'w')\n # First line: heading\n f.write('{}\\n'.format(self.heading))\n # write dataset 1\n f.write('{} {} {} {} {} {} {}\\n'.format(self.ipakcb, self.iswtoc,\n self.nsystm, self.ithk,\n self.ivoid, self.istpcs,\n self.icrcc))\n # write dataset 2\n t = self.lnwt.array\n for tt in t:\n f.write('{} '.format(tt + 1))\n f.write('\\n')\n\n # write dataset 3\n f.write(\n '{} {} {} {} {} {} {} {} {} {}\\n'.format(self.izcfl, self.izcfm,\n self.iglfl, self.iglfm,\n self.iestfl, self.iestfm,\n self.ipcsfl, self.ipcsfm,\n self.istfl, self.istfm))\n\n # write dataset 4\n f.write(self.gl0.get_file_entry())\n\n # write dataset 5\n f.write(self.sgm.get_file_entry())\n\n # write dataset 6\n f.write(self.sgs.get_file_entry())\n\n # write datasets 7 to 13\n for k in range(self.nsystm):\n f.write(self.thick[k].get_file_entry())\n if self.icrcc != 0:\n f.write(self.sse[k].get_file_entry())\n f.write(self.ssv[k].get_file_entry())\n else:\n f.write(self.cr[k].get_file_entry())\n f.write(self.cc[k].get_file_entry())\n f.write(self.void[k].get_file_entry())\n f.write(self.sub[k].get_file_entry())\n\n # write datasets 14 and 15\n for k in range(nlay):\n if self.istpcs != 0:\n f.write(self.pcsoff[k].get_file_entry())\n else:\n f.write(self.pcs[k].get_file_entry())\n\n # write dataset 16 and 17\n if self.iswtoc > 0:\n # dataset 16\n for i in self.ids16:\n f.write('{} '.format(i))\n f.write(' #dataset 16\\n')\n\n # dataset 17\n for k in range(self.iswtoc):\n t = self.ids17[k, :].copy()\n t[0:4] += 1\n for i in t:\n f.write('{} '.format(i))\n f.write(' #dataset 17 iswtoc {}\\n'.format(k + 1))\n\n # close swt file\n f.close()","def write (self, file):\n\t\tfile.write (self.pack ())","def save_final_config(self, configuration):\n filename = (\n \"transpose-\" + str(max(self.args.begin, 1)) +\n \"_\" + str(max(self.args.end, 1)) +\n \"_\" + str(max(self.args.nruns, 1)) +\n time.strftime(\"-%Y%m%d-%H%M%S\") + \".json\")\n print(\"Optimal block size written to \" + filename +\n \": \", configuration.data)\n self.manipulator().save_to_file(configuration.data, filename)","def test_append_to_flowgram_file(self):\r\n\r\n fh, tmp_filename = init_flowgram_file(n=100, l=400)\r\n self.assert_(exists(tmp_filename))\r\n self.tmp_filename = tmp_filename\r\n\r\n flow1 = Flowgram(\"0 1.2 2.1 3.4 0.02 0.01 1.02 0.08\")\r\n append_to_flowgram_file(\"test_id\", flow1, fh)\r\n\r\n flow2 = Flowgram('0.5 1.0 4.1 0.0 0.0 1.23 0.0 3.1',\r\n Name='a', floworder=\"TACG\",\r\n header_info={\r\n 'Bases': 'TACCCCAGGG', 'Clip Qual Right': 7,\r\n 'Flow Indexes': \"1\\t2\\t3\\t3\\t3\\t3\\t6\\t8\\t8\\t8\"})\r\n append_to_flowgram_file(\"test_id2\", flow2, fh, trim=True)\r\n # close and re-open to read from start, seek might work as well here...\r\n fh.close()\r\n fh = open(tmp_filename)\r\n result_file_content = list(fh)\r\n self.assertEqual(result_file_content, [\"100 400\\n\",\r\n \"test_id 8 0.0 1.2 2.1 3.4 0.02 0.01 1.02 0.08\\n\",\r\n \"test_id2 6 0.5 1.0 4.1 0.0 0.0 1.23\\n\"])","def savemat(self, file_name):\n d = {'dG0_prime': self.dG0_prime,\n 'dG0': self.dG0,\n 'T': self.T,\n 'I': self.I,\n 'pH': self.pH,\n 'pMg': self.pMg,\n 'weight': self.weight,\n 'cids': self.cids,\n 'S': self.S.values}\n savemat(file_name, d, oned_as='row')","def run_ptmcmc_save(\n sampler, startPos, nSteps, file, progress=True, col_names=\"\", **kwargs\n):\n if file:\n with open(file, \"w\") as f:\n f.write(col_names)\n if col_names:\n f.write(\"\\n\")\n\n iStep = 0\n if progress:\n bar = tqdm(total=nSteps)\n\n ## TODO: Impliment this with kwrgs manipulation, currently it is dumb.\n try:\n for pos, prob, like in sampler.sample(\n startPos, iterations=nSteps, store=False, **kwargs\n ):\n iStep += 1\n if progress:\n bar.update()\n # pos is shape (ntemps, nwalkers, npars)\n # prob is shape (ntemps, nwalkers)\n # loop over all walkers for first temp and append to file\n zpos = pos[0, ...]\n zprob = prob[0, ...]\n\n for k in range(zpos.shape[0]):\n thisPos = zpos[k]\n thisProb = zprob[k]\n\n with open(file, \"a\") as f:\n f.write(\n \"{0:4d} {1:s} {2:f}\\n\".format(\n k, \" \".join(map(str, thisPos)), thisProb\n )\n )\n\n except TypeError:\n for pos, prob, like in sampler.sample(\n startPos, iterations=nSteps, storechain=True, **kwargs\n ):\n iStep += 1\n if progress:\n bar.update()\n # pos is shape (ntemps, nwalkers, npars)\n # prob is shape (ntemps, nwalkers)\n # loop over all walkers for first temp and append to file\n zpos = pos[0, ...]\n zprob = prob[0, ...]\n\n for k in range(zpos.shape[0]):\n thisPos = zpos[k]\n thisProb = zprob[k]\n\n with open(file, \"a\") as f:\n f.write(\n \"{0:4d} {1:s} {2:f}\\n\".format(\n k, \" \".join(map(str, thisPos)), thisProb\n )\n )\n\n if progress:\n bar.close()\n return sampler","def tofile(self, f):\n raise NotImplementedError(\"ScalableRedisLocalBloomFilter not support tofile\")","def to_file(self, fid, precision=16, comment_lines=[], foldmaskinfo=True):\n # Open the file object.\n newfile = False\n if not hasattr(fid, 'write'):\n newfile = True\n fid = open(fid, 'w')\n\n # Write comments\n for line in comment_lines:\n fid.write('# ')\n fid.write(line.strip())\n fid.write(os.linesep)\n\n # Write out the shape of the fs\n fid.write('{0} '.format(self.sample_size))\n\n if foldmaskinfo:\n if not self.folded:\n fid.write('unfolded ')\n else:\n fid.write('folded ')\n \n fid.write(os.linesep)\n\n # Write the data to the file\n self.data.tofile(fid, ' ', '%%.%ig' % precision)\n fid.write(os.linesep)\n\n if foldmaskinfo:\n # Write the mask to the file\n np.asarray(self.mask,int).tofile(fid, ' ')\n fid.write(os.linesep)\n\n # Close file\n if newfile:\n fid.close()","def save_h5(self, filename):\n try:\n shutil.copyfile(filename, '{0}_bak'.format(filename))\n except IOError:\n print 'could not make backup of trainer param file (which is \\\n normal if we haven\\'t saved one until now)'\n paramfile = tables.openFile(filename, 'w')\n paramfile.createArray(paramfile.root, 'learningrate',\n self.learningrate)\n paramfile.createArray(paramfile.root, 'verbose', self.verbose)\n paramfile.createArray(paramfile.root, 'loadsize', self.loadsize)\n paramfile.createArray(paramfile.root, 'batchsize', self.batchsize)\n paramfile.createArray(paramfile.root, 'momentum',\n self.momentum)\n paramfile.createArray(paramfile.root, 'epochcount',\n self.epochcount)\n paramfile.createArray(paramfile.root, 'momentum_batchcounter',\n self.momentum_batchcounter)\n incsgrp = paramfile.createGroup(paramfile.root, 'incs', 'increments')\n for p in self._params:\n paramfile.createArray(incsgrp, p.name, self._incs[p].get_value())\n if self.rmsprop is not None:\n avg_grad_sqrs_grp = paramfile.createGroup(paramfile.root, 'avg_grad_sqrs')\n for p in self._params:\n paramfile.createArray(avg_grad_sqrs_grp, p.name, self._avg_grad_sqrs[p].get_value())\n paramfile.close()","def dump_gain_file(filename,raw=None,gain=None,model=None,chisq=[],name_prefix=\"\"):\n import os\n dirname,basename = os.path.split(filename)\n full_filename = os.path.join(dirname,name_prefix+basename)\n outfile = open(full_filename,\"w\")\n d = raw\n print 'Dumping gains to %s' % full_filename\n stepsize = d.shape[1]\n # Header\n outfile.write(\"#Tubes Sectors Steps\\n\")\n outfile.write(\"%d %d %d\\n\" % (d.shape[-1],d.shape[0],d.shape[1]))\n # raw data\n for tube_no in range(d.shape[-1]):\n for sector_no in range(d.shape[0]):\n for step_no in range(stepsize):\n outfile.write(\"%8.3f %7.3f\\n\" % (d.storage[sector_no,step_no,tube_no],d.var[sector_no,step_no,tube_no]))\n outfile.write(\"#intensities\\n\")\n for intensity in model:\n outfile.write(\"%8.3f\\n\" % intensity)\n outfile.write(\"#gains\\n\")\n for g in gain:\n outfile.write(\"%8.3f\\n\" % g)\n outfile.write(\"#chisq\\n\")\n for c in chisq:\n outfile.write(\"%8.3f\\n\" % c)\n outfile.close()"],"string":"[\n \"def write_data(infbfile,begin_N,dur_N,outfbfile):\\n infbfile.seek_to_sample(begin_N)\\n for i in range(begin_N,(begin_N+dur_N)):\\n data = infbfile.read_sample()\\n data.tofile(outfbfile)\",\n \"def save(self, fname):\\n lh_data = self.data[:len(self.lh_vertno)]\\n rh_data = self.data[-len(self.rh_vertno):]\\n\\n print 'Writing STC to disk...',\\n write_stc(fname + '-lh.stc', tmin=self.tmin, tstep=self.tstep,\\n vertices=self.lh_vertno, data=lh_data)\\n write_stc(fname + '-rh.stc', tmin=self.tmin, tstep=self.tstep,\\n vertices=self.rh_vertno, data=rh_data)\\n print '[done]'\",\n \"def write_file(self):\\r\\n # -open file for writing\\r\\n f_fbob = open(self.fn_path, 'w')\\r\\n\\r\\n # -write header\\r\\n f_fbob.write('%s\\\\n' % (self.heading))\\r\\n\\r\\n # -write sections 1 & 2 : NOTE- what about NOPRINT?\\r\\n f_fbob.write('%10i%10i%10i%10i\\\\n' % (self.nqfb, self.nqcfb,\\r\\n self.nqtfb, self.iufbobsv))\\r\\n f_fbob.write('%10e\\\\n' % (self.tomultfb)) # check format\\r\\n\\r\\n # -write sections 3-5 looping through observations groups\\r\\n c = 0\\r\\n for i in range(self.nqfb):\\r\\n # while (i < self.nqfb):\\r\\n # write section 3\\r\\n f_fbob.write('{:10d}{:10d}\\\\n'.format(self.nqobfb[i],\\r\\n self.nqclfb[i]))\\r\\n\\r\\n # Loop through observation times for the groups\\r\\n for j in range(self.nqobfb[i]):\\r\\n # -write section 4\\r\\n f_fbob.write(\\r\\n '{}{:10d}{:10.4g}{}{:10.4g}\\\\n'.format(self.obsnam[c],\\r\\n self.irefsp[c],\\r\\n self.toffset[c], ' ',\\r\\n self.flwobs[c]))\\r\\n c += 1 # index variable\\r\\n\\r\\n # -write section 5 - NOTE- need to adjust factor for muliple obs same cell\\r\\n for j in range(abs(self.nqclfb[i])):\\r\\n if self.nqclfb[\\r\\n i] < 0: # set factor to 1.0 for all cells in group\\r\\n self.factor[i, :] = 1.0\\r\\n f_fbob.write('{:10d}{:10d}{:10d}{}{:10f}\\\\n'\\r\\n .format(self.layer[i, j], (self.row[i, j]),\\r\\n self.column[i, j],\\r\\n ' ', self.factor[\\r\\n i, j])) # note- is 10f good enough here?\\r\\n\\r\\n f_fbob.close()\\r\\n #\\r\\n # swm: BEGIN hack for writing standard file\\r\\n sfname = self.fn_path # swm:hack\\r\\n sfname += '_ins' # swm: hack\\r\\n # write header\\r\\n f_ins = open(sfname, 'w') # swm: hack for standard file\\r\\n f_ins.write('jif @\\\\n') # swm: hack for standard file\\r\\n f_ins.write('StandardFile 0 1 %s\\\\n' % (\\r\\n self.nqtfb)) # swm: hack for standard file\\r\\n for i in range(0, self.nqtfb):\\r\\n f_ins.write(\\r\\n '{}\\\\n'.format(self.obsnam[i])) # swm: hack for standard file\\r\\n\\r\\n f_ins.close()\\r\\n # swm: END hack for writing standard file\\r\\n\\r\\n return\",\n \"def write_file(f_name, size, best, best_tour):\\n new_file = open(\\\"Checking Tours/Genetic/TourfileA/tourNEW\\\"+f_name+\\\".txt\\\", 'w+')\\n new_file.write(\\\"NAME = \\\" + f_name + \\\",\\\")\\n new_file.write(\\\"\\\\nTOURSIZE = \\\" + str(size) + \\\",\\\")\\n new_file.write(\\\"\\\\nLENGTH = \\\" + str(best) + \\\",\\\\n\\\")\\n for i in range(size):\\n new_file.write(str(best_tour[i]+1)+\\\",\\\")\\n new_file.close()\",\n \"def saveFullMouvement(filename, nbSteps, delay, Servos):\\n\\ttabPositions = [] # Cree un tableau vide\\n\\ti = 0 # Index de boucle\\n\\n\\twhile i <= nbSteps: # Fait toutes les etapes\\n\\t\\t# Sauvegarde l'etape dans le tableau\\n\\t\\ttabPositions.append(getMouvementSteps(Servos))\\n\\t\\ttime.sleep(delay) # Delai entre chaque etape\\n\\t\\ti += 1 # Incremente l'index\\n\\n\\t# Ecrit toutes les etapes dans le fichier\\n\\taxFiles.writeFile(tabPositions, filename)\",\n \"def save(self, f):\\n self.f = f\\n for region in self.regions:\\n ext = region.address & 0xFFFF0000\\n self.write_hex_line(\\n HexLine(0, EXTLINADR, struct.pack(\\\">H\\\", ext >> 16))\\n )\\n address = region.address - ext\\n for chunk in chunks(region.data):\\n if address >= 0x10000:\\n ext += 0x10000\\n self.write_hex_line(\\n HexLine(0, EXTLINADR, struct.pack(\\\">H\\\", ext >> 16))\\n )\\n address -= 0x10000\\n self.write_hex_line(HexLine(address, DATA, chunk))\\n address += len(chunk)\\n self.write_hex_line(HexLine(0, EOF))\",\n \"def change_input(filename, frac_l=0.019994, force=25.0, time=200_000, seed=None):\\r\\n\\r\\n frac_sl = round(1.5 /(32**3 *3), 6)\\r\\n frac_l = round(frac_l -frac_sl, 6)\\r\\n frac_w = round(1 -frac_l -frac_sl, 6)\\r\\n \\r\\n params = {'Box': \\\"32 32 32\\\\t1 1 1\\\", 'RNGSeed': seed if seed is not None else -4073, 'Step': 0.02, 'Time': time, \\r\\n 'SamplePeriod': 100, 'AnalysisPeriod': 1000, 'DensityPeriod': time, 'DisplayPeriod': time //10, 'RestartPeriod': time,\\r\\n }\\r\\n\\r\\n with open(filename, 'rt') as rf:\\r\\n with open(filename+'_sim', 'wt') as wf:\\r\\n\\r\\n for line in rf:\\r\\n \\r\\n if line.startswith('Polymer\\\\tWater') or line.startswith('Polymer Water'):\\r\\n line = line.strip().split()\\r\\n line[2] = f\\\"{frac_w:.6f}\\\"\\r\\n \\r\\n # Converts list to list[str]\\r\\n line = list(map(str, line))\\r\\n wf.write('\\\\t'.join(line) + '\\\\n')\\r\\n\\r\\n elif line.startswith('Polymer\\\\tLipid') or line.startswith('Polymer Lipid'):\\r\\n line = line.strip().split()\\r\\n line[2] = f\\\"{frac_l:.6f}\\\"\\r\\n\\r\\n # Converts list to list[str]\\r\\n line = list(map(str, line))\\r\\n wf.write('\\\\t'.join(line) + '\\\\n')\\r\\n \\r\\n elif line.startswith('Polymer\\\\tSingleLipid') or line.startswith('Polymer SingleLipid'):\\r\\n line = line.strip().split()\\r\\n line[2] = f\\\"{frac_sl:.6f}\\\"\\r\\n\\r\\n # Converts list to list[str]\\r\\n line = list(map(str, line))\\r\\n wf.write('\\\\t'.join(line) + '\\\\n')\\r\\n\\r\\n elif line.startswith('Command\\\\tConstantForceOnTarget') or line.startswith('Command ConstantForceOnTarget'):\\r\\n line = line.strip().split()\\r\\n\\r\\n if line[3] == \\\"singleLipidHead\\\":\\r\\n line[-1] = f\\\"{force /3:.6f}\\\" \\r\\n\\r\\n elif line[3] == \\\"lowerHeads\\\":\\r\\n line[-1] = f\\\"{force /3 /(1636):.6f}\\\"\\r\\n\\r\\n # Converts list to list[str]\\r\\n line = list(map(str, line))\\r\\n wf.write('\\\\t'.join(line) + '\\\\n')\\r\\n \\r\\n # if line.startswith('\\tTimes\\t0 1000'):\\r\\n # line = line.strip().split()\\r\\n # line[2] = f\\\"{time}\\\"\\r\\n \\r\\n # # Converts list to list[str]\\r\\n # line = list(map(str, line))\\r\\n # wf.write('\\\\t'.join(line) + '\\\\n') \\r\\n # line = next(rf) \\r\\n \\r\\n # if line.strip().split() and line.strip().split()[0] in params.keys():\\r\\n # key = line.strip().split()[0]\\r\\n # wf.write(f\\\"{key:<12}\\\\t{str(params[key])}\\\\n\\\")\\r\\n\\r\\n else:\\r\\n wf.write(line)\",\n \"def save(self, filename):\\n target = open(filename, 'w')\\n target.write(\\\"\\\\\\\\data\\\\\\\\\\\\n\\\")\\n target.write(\\\"ngram 1=\\\" + str(len(self.f1)) + \\\"\\\\n\\\\n\\\")\\n target.write(\\\"\\\\\\\\1-grams:\\\\n\\\")\\n for w,p in sorted(self.f1.items()): \\n target.write(str(p) + \\\" \\\" + w + \\\"\\\\n\\\")\\n target.write(\\\"\\\\\\\\end\\\\\\\\\\\\n\\\")\\n target.close()\",\n \"def save_file(self, sub):\\n fileout = os.path.join(self.saving_dir, 'output_skeleton_' + str(sub) + '.nii.gz')\\n print('writing altered skeleton to', fileout)\\n aims.write(self.skel, fileout)\",\n \"def write(self, fname):\\n pass\",\n \"def setFastFile(self,fname):\\n self.fst_file = fname\",\n \"def to_file(self, file_path, smirnoff_data):\\n pass\",\n \"def write_sum(self):\\n with open('{}_Simulation_Fst.dat'.format(self.simulation_window), 'w+') as output:\\n for line in self.fst_data:\\n output.write(line)\",\n \"def save_fits(data, fname):\\n\\tcols = fits.ColDefs(np.copy(data)) # This is somehow necessary.\\n\\ttbhdu = fits.BinTableHDU.from_columns(cols)\\n\\ttbhdu.writeto(fname, clobber=True)\\n\\t\\n\\treturn\",\n \"def finish(self):\\n self._fout.add_size()\\n self._fout.add_padding()\\n self._fout.close()\",\n \"def tempfile(self,calcMD5=False,calcSHA1=False):\\n import tempfile,hashlib\\n tf = tempfile.NamedTemporaryFile()\\n if calcMD5: tf.md5 = hashlib.md5()\\n if calcSHA1: tf.sha1 = hashlib.sha1()\\n for run in self.byteruns():\\n self.imagefile.seek(run.img_start)\\n count = run.bytes\\n while count>0:\\n xfer_bytes = min(count,1024*1024) # transfer up to a megabyte at a time\\n buf = self.imagefile.read(xfer_bytes)\\n tf.write(buf)\\n if calcMD5: tf.md5.update(buf)\\n if calcSHA1: tf.sha1.update(buf)\\n count -= xfer_bytes\\n tf.flush()\\n return tf\",\n \"def generate_file(self, filename, amount):\\n with open(filename, \\\"w\\\", encoding=\\\"utf-8\\\") as fi:\\n count = 0\\n space = \\\"\\\" if self.token is Tokenization.byte or self.token is Tokenization.character else \\\" \\\"\\n for generate_token in self.generate():\\n count += 1\\n outputStr = str(generate_token)\\n outputStr += space\\n fi.write(outputStr)\\n if count >= amount:\\n break\",\n \"def moveNewFragmentsToTmpDir(options,nextTaskNum):\\n for i in range(1,nextTaskNum):\\n frag = getFragmentPath(options.tmpDir, options.fragBase, i)\\n newfrag = getFragmentPath(\\\"%s%stmp\\\" % (options.tmpDir, os.sep), options.fragBase, i)\\n os.rename(newfrag,frag)\\n os.rmdir(\\\"%s%stmp\\\" % (options.tmpDir, os.sep))\",\n \"def write_stc(filename, tmin, tstep, vertices, data):\\n fid = open(filename, 'wb')\\n\\n # write start time in ms\\n fid.write(np.array(1000 * tmin, dtype='>f4').tostring())\\n # write sampling rate in ms\\n fid.write(np.array(1000 * tstep, dtype='>f4').tostring())\\n # write number of vertices\\n fid.write(np.array(vertices.shape[0], dtype='>I4').tostring())\\n # write the vertex indices\\n fid.write(np.array(vertices, dtype='>I4').tostring())\\n\\n # write the number of timepts\\n fid.write(np.array(data.shape[1], dtype='>I4').tostring())\\n #\\n # write the data\\n #\\n fid.write(np.array(data.T, dtype='>f4').tostring())\\n\\n # close the file\\n fid.close()\",\n \"def make_fet(self):\\n fet_filename = self.filename + \\\".fet.\\\" + str(self.tet_num)\\n with open(fet_filename, \\\"w\\\") as f:\\n f.write(str(self.feature_array.shape[1]))\\n f.write(\\\"\\\\n\\\")\\n np.savetxt(f, self.feature_array, fmt=\\\"%1.5f\\\")\",\n \"def write_chunk(chunk, token):\\n dest = rem_dir('grab')\\n # input(dest)\\n file_name = '{}_{}'.format('cpf_temp', token)\\n dest_file_name = os.path.join(os.path.abspath(dest), file_name)\\n # input(dest_file_name)\\n WRITE_STREAM = open(dest_file_name, 'wb')\\n WRITE_STREAM.write(chunk)\\n WRITE_STREAM.close()\\n\\n return True\",\n \"def writeTmpFastq(self, fw_reads_path, rev_reads_path):\\n try:\\n fq1 = open(fw_reads_path, \\\"w+\\\")\\n fq1.write(reads1_string)\\n fq1.close()\\n fq2 = open(rev_reads_path, \\\"w+\\\")\\n fq2.write(reads2_string)\\n fq2.close()\\n except OSError:\\n pass\",\n \"def writeTmpFastq(self, fw_reads_path, rev_reads_path):\\n try:\\n fq1 = open(fw_reads_path, \\\"w+\\\")\\n fq1.write(reads1_string)\\n fq1.close()\\n fq2 = open(rev_reads_path, \\\"w+\\\")\\n fq2.write(reads2_string)\\n fq2.close()\\n except OSError:\\n pass\",\n \"def to_file(self, filename):\\n self.header['n'] = self.n\\n save_gyre(filename, self.header, self.data)\",\n \"def writefragment(oldfrag,newfrag,verb=0):\\n print(f\\\">>> writefragment: Writing fragment for job: {oldfrag} -> {newfrag}\\\")\\n head = \\\"\\\"\\\"#! /usr/bin/env cmsRun\\n# Generated with submit_fragment.py\\\"\\\"\\\"\\n opts = \\\"\\\"\\\"# USER OPTIONS\\nfrom FWCore.ParameterSet.VarParsing import VarParsing\\noptions = VarParsing('analysis')\\n#options.register('tag', \\\"\\\",mytype=VarParsing.varType.string)\\noptions.register('index', -1,mytype=VarParsing.varType.int)\\noptions.register('outdir', \\\".\\\",mytype=VarParsing.varType.string)\\noptions.register('maxevts',100,mytype=VarParsing.varType.int)\\noptions.register('seed', -1,mytype=VarParsing.varType.int)\\noptions.parseArguments()\\ntag = options.tag\\nindex = options.index\\noutdir = options.outdir\\nseed = options.seed\\nmaxevts = options.maxevts\\nif index>=0:\\n tag += \\\"_%04d\\\"%(index)\\noutfile_RAW = \\\"file:%s/GENSIM%s.root\\\"%(outdir,tag)\\noutfile_LHE = \\\"file:%s/LHE%s.root\\\"%(outdir,tag)\\nprint(\\\">>> %-11s = %r\\\"%('index',index))\\nprint(\\\">>> %-11s = %r\\\"%('seed',seed))\\nprint(\\\">>> %-11s = %r\\\"%('maxevts',maxevts))\\nprint(\\\">>> %-11s = %r\\\"%('outfile_RAW',outfile_RAW))\\nprint(\\\">>> %-11s = %r\\\"%('outfile_LHE',outfile_LHE))\\n\\\"\\\"\\\"\\n seed = \\\"\\\"\\\"\\n# RANDOM SEED\\nif seed>0:\\n process.RandomNumberGeneratorService.externalLHEProducer.initialSeed = int(seed)\\nelse:\\n from IOMC.RandomEngine.RandomServiceHelper import RandomNumberServiceHelper\\n randSvc = RandomNumberServiceHelper(process.RandomNumberGeneratorService)\\n randSvc.populate() # set random number each cmsRun\\n\\\"\\\"\\\"\\n \\n # READ OLD FRAGMENT\\n hasopts = False\\n hasrand = False\\n oldlines = [ ]\\n if verb>=1:\\n print(f\\\">>> writefragment: Opening {oldfrag}...\\\")\\n with open(oldfrag,'r') as oldfile:\\n for line in oldfile.readlines():\\n if 'VarParsing' in line:\\n hasopts = True\\n warning(f\\\"Fragment {oldfrag} already has VarParsing...\\\",pre=\\\"writefragment: \\\")\\n if 'process.RandomNumberGeneratorService' in line:\\n hasrand = True\\n oldlines.append(line)\\n \\n # WRITE NEW FRAGMENT\\n flag = None\\n if verb>=1:\\n print(f\\\">>> writefragment: Writing {newfrag}...\\\")\\n if os.path.isfile(newfrag):\\n warning(f\\\"{newfrag} already exists!\\\",pre=\\\"writefragment: \\\")\\n with open(newfrag,'w') as newfile:\\n for line in head.split('\\\\n'):\\n writeline(newfile,line,verb=verb)\\n for line in oldlines:\\n vline = line.rstrip('\\\\n')\\n if 'cms.Process' in line: # insert user options\\n for optline in opts.split('\\\\n'):\\n writeline(newfile,optline,verb=verb)\\n elif 'process.maxEvents' in line or 'process.externalLHEProducer' in line:\\n flag = 'maxevts'\\n elif 'process.LHEoutput' in line:\\n flag = 'LHE'\\n elif 'process.RAWSIMoutput' in line:\\n flag = 'RAW'\\n elif flag=='maxevts' and ('input' in line or 'nEvents' in line):\\n line = rexp_nevts.sub(fr\\\"\\\\1(maxevts)\\\",line)\\n vline = rexp_nevts.sub(fr\\\"\\\\1({green('maxevts')})\\\",vline)\\n flag = None\\n elif flag=='RAW' and 'fileName' in line:\\n line = rexp_fname.sub(r\\\"\\\\1(outfile_RAW),\\\",line)\\n vline = rexp_fname.sub(fr\\\"\\\\1({green('outfile_RAW')}),\\\",vline)\\n flag = None\\n elif flag=='LHE' and 'fileName' in line:\\n line = rexp_fname.sub(fr\\\"\\\\1(outfile_LHE),\\\",line)\\n vline = rexp_fname.sub(fr\\\"\\\\1({green('outfile_LHE')}),\\\",vline)\\n flag = None\\n if verb>=3:\\n print(f\\\">>> writefragment: {vline}\\\")\\n newfile.write(line)\\n for line in seed.split('\\\\n'):\\n writeline(newfile,line,verb=verb)\\n \\n return oldfrag\",\n \"def save(self, save_path, step):\\n \\n p = Path(save_path) / \\\"{:04d}\\\".format(step)\\n p.mkdir(parents=True, exist_ok=True)\\n fname = str(p / \\\"data.npz\\\")\\n np.savez_compressed(fname,\\n n_bins=self.n_bins,\\n ranges=self.ranges,\\n V=self.V,\\n next_state=self.next_state,\\n next_reward=self.next_reward\\n )\",\n \"def resize_file(self,fobj, diff, BUFFER_SIZE=2 ** 16):\\n\\n fobj.seek(0, 2)\\n filesize = fobj.tell()\\n\\n if diff < 0:\\n if filesize + diff < 0:\\n raise ValueError\\n # truncate flushes internally\\n fobj.truncate(filesize + diff)\\n elif diff > 0:\\n try:\\n while diff:\\n addsize = min(BUFFER_SIZE, diff)\\n fobj.write(b\\\"\\\\x00\\\" * addsize)\\n diff -= addsize\\n fobj.flush()\\n except IOError as e:\\n if e.errno == errno.ENOSPC:\\n # To reduce the chance of corrupt files in case of missing\\n # space try to revert the file expansion back. Of course\\n # in reality every in-file-write can also fail due to COW etc.\\n # Note: IOError gets also raised in flush() due to buffering\\n fobj.truncate(filesize)\\n raise\",\n \"def saveseed(self, seed):\\n savefile = gettempdir() + '/last_test_seed_fate.tmp'\\n if args.verbose:\\n print('Saving run into ' + savefile)\\n with open(savefile, 'w') as f:\\n f.write(str(seed))\",\n \"def writeRawFCD():\\n global vehId, vehIdDict\\n vehIdDict = {}\\n vehId = 0\\n day = 0\\n\\n def getVehId(orgId):\\n \\\"\\\"\\\"creates new vehicle id's which consists only numerics\\\"\\\"\\\"\\n global vehId, vehIdDict\\n value = vehIdDict.get(orgId, vehId)\\n if value is vehId:\\n vehIdDict[orgId] = vehId\\n vehId = (vehId + 1) % 65500\\n return value\\n\\n outputFile = open(path.FQrawFCD, 'w')\\n\\n for period, quota, vtypeDictR, taxiSum in generatePeriodQuotaSets():\\n day += 86400\\n # reset dict so that every taxi (even if the vehicle is chosen several\\n # times) gets its own id\\n vehIdDict = {}\\n # dataset=0\\n sortedKeys = vtypeDictR.keys()\\n sortedKeys.sort()\\n for timestep in sortedKeys:\\n taxiList = vtypeDictR[timestep]\\n for tup in taxiList: # all elements in this timestep\\n # calc timestep ->for every period /quota set a new day\\n time = timestep + day\\n time = calcTime.getDateFromDepart(time)\\n # dataset+=1\\n # print ouptut\\n # veh_id date (time to simDate+time) x (remove and\\n # set comma new)\\n outputFile.write(str(getVehId(tup[0])) + '\\\\t' + time + '\\\\t' + tup[3][0:2] + '.' + tup[3][2:7] + tup[3][8:] +\\n # y (remove and set comma new)\\n # status speed form m/s in km/h\\n '\\\\t' + tup[4][0:2] + '.' + tup[4][2:7] + tup[4][8:] + '\\\\t' + \\\"90\\\" + '\\\\t' + str(int(round(tup[2] * 3.6))) + '\\\\n')\\n # print dataset, time\\n print(vehId)\\n outputFile.close()\",\n \"def reMake(self, final_path, map_, chunk_path, delete_residuals=False):\\n map_ = {int(k): v for k, v in map_.items()}\\n print(\\\"[+] Remake started...\\\")\\n try:\\n file_content_string = \\\"\\\"\\n for i in range(0, len(map_)):\\n file_content_string += open(chunk_path + map_[i], \\\"r\\\").read()\\n if delete_residuals == True: remove(chunk_path + map_[i])\\n file_content = b64.b64decode(file_content_string)\\n with open(final_path, \\\"wb\\\") as f:\\n f.write(file_content)\\n print(\\\"[+] Remake done.\\\")\\n except Exception as e:\\n print(e)\\n print(\\\"[+] Remake went wrong.\\\")\",\n \"def save_trans(self, fname):\\n if not self.can_save:\\n raise RuntimeError(\\\"Not enough information for saving transform\\\")\\n trans_matrix = self.head_mri_trans\\n trans = {'to': FIFF.FIFFV_COORD_MRI, 'from': FIFF.FIFFV_COORD_HEAD,\\n 'trans': trans_matrix}\\n write_trans(fname, trans)\",\n \"def write(self, f):\\n if self.best_mhc_align:\\n mhc_align_str = self.best_mhc_align.subject_str()\\n mhc_score_str = str(self.best_mhc_align.bit_score)\\n else:\\n mhc_align_str = \\\".\\\"\\n mhc_score_str = \\\"0\\\"\\n\\n if self.best_non_mhc_align:\\n non_mhc_align_str = self.best_non_mhc_align.subject_str()\\n non_mhc_score_str = str(self.best_non_mhc_align.bit_score)\\n else:\\n non_mhc_align_str = \\\".\\\"\\n non_mhc_score_str = \\\"0\\\"\\n \\n f.write(\\\"\\\\t\\\".join([self.locus, self.short_samp_id, self.name,\\n str(self.length), mhc_align_str, non_mhc_align_str,\\n mhc_score_str, non_mhc_score_str,\\n str(self.n_mhc_align), str(self.n_non_mhc_align)]) + \\\"\\\\n\\\")\",\n \"def write_file(self):\\n file = open(self.__file_path, 'w+')\\n file.truncate(0)\\n file.write(self.__content)\\n file.close()\",\n \"def save_tmp_file(self, data):\\n with open(self.tmp_file, 'wb') as f:\\n f.write(data)\",\n \"def dump_current_chunk(self, use_where):\\n log.info(\\\"Dumping raw data onto local disk for further investigation\\\")\\n log.info(\\\"Columns will be dumped in following order: \\\")\\n log.info(\\\", \\\".join(self._pk_for_filter + self.checksum_column_list))\\n for table_name in [self.table_name, self.new_table_name]:\\n if table_name == self.new_table_name:\\n # index for new schema can be any indexes that provides\\n # uniqueness and covering old PK lookup\\n idx_for_checksum = self.find_coverage_index()\\n outfile = self._outfile_name(\\n suffix=\\\".new\\\",\\n chunk_id=0,\\n # MySQL does create the file with the extension itself\\n skip_compressed_extension=True,\\n )\\n else:\\n # index for old schema should always be PK\\n idx_for_checksum = \\\"PRIMARY\\\"\\n outfile = self._outfile_name(\\n suffix=\\\".old\\\",\\n chunk_id=0,\\n # MySQL does create the file with the extension itself\\n skip_compressed_extension=True,\\n )\\n log.info(\\\"Dump offending chunk from {} into {}\\\".format(table_name, outfile))\\n self.execute_sql(\\n sql.dump_current_chunk(\\n table_name,\\n self.checksum_column_list,\\n self._pk_for_filter,\\n self.range_start_vars_array,\\n self.select_chunk_size,\\n idx_for_checksum,\\n use_where,\\n enable_outfile_compression=self.enable_outfile_compression,\\n ),\\n (outfile,),\\n )\",\n \"def Seperate(f_read, f_write_name):\\n lines = f_read.readlines()\\n line_s = [line.split() for line in lines]\\n\\n for i in range(6, 13):\\n nbytes = pow(2,i)\\n f_write = f_write_name + str(nbytes) + \\\"b.txt\\\"\\n f = open(f_write, \\\"w+\\\")\\n\\n for line in line_s:\\n if line[3] == str(nbytes):\\n f.write(\\\" \\\".join(line))\\n f.write(\\\"\\\\n\\\")\\n f.close()\",\n \"def store(self, filename):\",\n \"def __create_test_file(self):\\n self.test_file = os.path.join(os.path.dirname(self.server_path), \\\"data\\\")\\n with open(self.test_file, \\\"ab+\\\") as f:\\n n_blocks = int(self.args.size) // self.max_block_size\\n for i in range(n_blocks):\\n f.write(bytearray(os.urandom(self.max_block_size)))\\n remaining = int(self.args.size) % self.max_block_size\\n if remaining > 0:\\n f.write(bytearray(os.urandom(remaining)))\\n self.assertEqual(int(self.args.size), os.path.getsize(self.test_file))\",\n \"def write_srf(self, to, quantity=\\\"frequency\\\", factor: numbers.Number=1.0):\\n #tools.validate(Channel.write_srf, locals())\\n try:\\n to.write\\n except AttributeError: # not an open file\\n try:\\n to = open(to, 'wb')\\n except IsADirectoryError:\\n to = open(os.path.join(to, \\\"specresp_\\\" +\\n self.get_chanstr(full=True) +\\n \\\".dat\\\"),\\n 'wb')\\n\\n (x, y) = self.srf()\\n if quantity == \\\"frequency\\\":\\n pass\\n elif quantity == \\\"wavelength\\\":\\n x = physics.frequency2wavelength(x)\\n elif quantity == \\\"wavenumber\\\":\\n x = physics.frequency2wavenumber(x)\\n else:\\n raise ValueError(\\\"Unknown quantity: {}\\\".format(quantity))\\n\\n print(now(), \\\"Writing to\\\", to.name)\\n numpy.savetxt(to, numpy.c_[x*factor, y])\",\n \"def write(self, filename):\\n assert filename[-3:]=='.fz','name must end in .fz'\\n\\n files.makedir_fromfile(filename)\\n\\n ucfilename=filename[0:-3]\\n bname = os.path.basename(ucfilename)\\n\\n tmp_path = os.path.join(\\n files.get_temp_dir(),\\n bname,\\n )\\n files.makedir_fromfile(tmp_path)\\n\\n with TempFile(tmp_path) as tfile:\\n super(CosmosMEDSMaker,self).write(tfile.path)\\n self._compress_meds_file(tfile.path, filename)\",\n \"def to_file(self, fn):\\n store.store_dict(fn, 'trainalgorithm', self.to_dict())\",\n \"def write_to_file_z(path):\\n path1 = path + \\\"/z_Macros\\\"\\n if not os.path.exists(path1):\\n os.mkdir(path1)\\n for e in range(int(e_steps)+1):\\n filename = \\\"x0y0z%ske%s.mac\\\" %(dz*z + z_min, e*de + e_min)\\n path = path1\\n fullpath = os.path.join(path, filename)\\n f = open(fullpath, \\\"w\\\")\\n f.write('/rat/physics_list/OmitMuonicProcesses true\\\\n')\\n f.write(\\\"/rat/physics_list/OmitHadronicProcesses true \\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write('/rat/db/set DETECTOR geo_file \\\"geo/snoplus.geo\\\"\\\\n')\\n f.write('/rat/db/set GEO[scint] material \\\"labppo_scintillator\\\"\\\\n')\\n f.write('/rat/db/set DAQ dqxx_info 0 \\\\n')\\n f.write(\\\"/run/initialize \\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"/rat/proc frontend\\\\n\\\")\\n f.write(\\\"/rat/proc trigger\\\\n\\\")\\n f.write(\\\"/rat/proc eventbuilder\\\\n\\\")\\n f.write(\\\"/rat/proc count\\\\n\\\")\\n f.write(\\\"/rat/procset update 100\\\\n\\\")\\n f.write(\\\"/rat/proc calibratePMT\\\\n\\\")\\n f.write(\\\"/rat/proc scintFitter\\\\n\\\")\\n f.write(\\\"/rat/proclast outroot\\\\n\\\")\\n f.write('/rat/procset file \\\"x0y0z%ske%s.root\\\"\\\\n' %(dz*z + z_min, e*de + e_min))\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"/generator/add combo gun:point:poisson\\\\n\\\")\\n f.write(\\\"# want random, isotropic momentum distribution; energy given in MeV\\\\n\\\")\\n f.write(\\\"/generator/vtx/set e- 0 0 0 %s\\\\n\\\" %(e*de + e_min))\\n f.write(\\\"# position given in Cartesians, relative to detector center, in mm\\\\n\\\")\\n f.write(\\\"/generator/pos/set 0 0 %s\\\\n\\\" % (dz*z + z_min))\\n f.write(\\\"/generator/rate/set 1\\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"/rat/run/start %s\\\\n\\\" %(n))\\n f.write(\\\"exit\\\")\",\n \"def saveFile(self,newfile=None):\\n if newfile == None:\\n shutil.move(self.filename,self.filename+'~')\\n self.handler = open(self.filename,'w')\\n else:\\n self.handler = open(newfile,'w')\\n self.handler.writelines(self.content)\\n self.handler.close()\",\n \"def save(self, fname, snver=None):\\n self._io.save(fname)\",\n \"def save_data(self, f): \\n if not self.sampling:\\n self.convert_to_array()\\n np.save(f, self.reads)\",\n \"def backup_int_in_fname(num: int, file_name: str) -> None:\\n with open(file_name, 'w') as fname:\\n fname.write(str(num))\",\n \"def _prepare_input_file(self, filename, numlines, maxvalue):\\n with open(filename, 'a') as f:\\n for _ in range(numlines):\\n f.write(str(randrange(maxvalue)) + '\\\\n')\\n self.filepath = f.name\",\n \"def save_model(self, step):\\n\\n # file_name = params['name']\\n # pickle.dump(self, gzip.open(file_name, 'wb'))\",\n \"def _write_raw_fif(raw, bids_fname):\\n raw.save(\\n bids_fname,\\n fmt=raw.orig_format,\\n split_size=_FIFF_SPLIT_SIZE,\\n split_naming=\\\"bids\\\",\\n overwrite=True,\\n )\",\n \"def save_tsv_file(parsed_data):\\n result_file.write('\\\\t'.join(parsed_data) + '\\\\n')\",\n \"def write(self, file):\\n pos = file.tell()\\n pickle.dump((self.index, self.meta, self.info), file)\\n file.seek(0)\\n\\n # update the header with the position of the content index.\\n file.write(struct.pack('<Q', pos))\",\n \"def create_file(tmpdir, flowcell, lane, read, file_content):\\n\\n file_name = f\\\"S1_FC000{flowcell}_L00{lane}_R_{read}.fastq.gz\\\"\\n file_path = tmpdir / file_name\\n file_path.write(file_content)\\n return file_path\",\n \"def writeFST(self,ofname,fstDict):\\n try:\\n ofh = open(ofname,'w')\\n except:\\n sys.stdout.write (\\\"Error opening %s\\\\n\\\" % ofname)\\n return 0\\n\\n\\n # writing FAST input: If the second field in the line is present in the dictionary,\\n # write the new value. Otherwise\\n # write the original line. special case for the file name fields \\\"\\\"\\\"\\n for iln in range(len(self.lines_fast)):\\n line = self.lines_fast[iln]\\n flds = line.strip().split()\\n if (len(flds) >1 and flds[1] in ['PtfmFile','TwrFile','BldFile(1)','BldFile(2)','BldFile(3)', 'ADfile','NoiseFile']):\\n # substituting possibly modified file names for subfiles\\n if (flds[1] == 'PtfmFile'):\\n flds[0] = self.ptfm_file\\n if (flds[1] == 'TwrFile'):\\n flds[0] = self.twr_file\\n if (flds[1] == 'ADAMSFile'):\\n flds[0] = self.adams_file\\n if (flds[1] == 'BldFile(1)'):\\n flds[0] = self.blade1_file\\n if (flds[1] == 'BldFile(2)'):\\n flds[0] = self.blade2_file \\n if (flds[1] == 'BldFile(3)'):\\n flds[0] = self.blade3_file \\n if (flds[1] == 'ADfile'):\\n flds[0] = self.ad_file \\n if (flds[1] == 'NoiseFile'):\\n flds[0] = self.noise_file \\n flds[0] = \\\"\\\\\\\"%s\\\\\\\"\\\" % flds[0] ## put the quote back on\\n oline = ' '.join(flds)\\n ofh.write(oline)\\n ofh.write('\\\\n')\\n\\n elif (len(flds)>1 and flds[1] in fstDict):\\n # replacing this entry with something from fstDict\\n f0 = '{:.2f} '.format(fstDict[flds[1]])\\n oline = ' '.join([f0] + flds[1:])\\n ofh.write(oline)\\n ofh.write('\\\\n')\\n\\n elif (len(flds)>1 and flds[1] == \\\"SumPrint\\\"):\\n # special case to deal with either V7.1 OR v7.2\\n ofh.write(line)\\n nextln = self.lines_fast[iln+1].split()\\n if (self.fst_file_type == 0 and self.fst_exe_type == 1):\\n if nextln[1] != \\\"OutFileFmt\\\": ## this check should not be necessary if fst_xxx_type are correct\\n ofh.write(\\\"1 OutFileFmt - Format for tabular (time-marching) output file(s) (1: text file [<RootName>.out], 2: binary\\\\n\\\") \\n elif (self.fst_file_type == 1 and self.fst_exe_type == 0):\\n if nextln[1] != \\\"OutFileFmt\\\": ## this check should not be necessary if fst_xxx_type are correct\\n # skip line \\n iln += 1\\n elif (len(flds) > 0 and flds[0] == \\\"END\\\"):\\n # uh oh, better back up and write the outputs!\\n if self.output_list != None:\\n for out in self.output_list:\\n ofh.write(\\\"\\\\\\\"%s\\\\\\\"\\\\n\\\" % out)\\n ofh.write(line)\\n else:\\n # just write the line unmodified\\n ofh.write(line)\\n\\n ofh.close()\\n\\n return 1\",\n \"def create_file(toy_data, filename):\\n root_file = ROOT.TFile.Open(filename, \\\"RECREATE\\\")\\n \\n bin_edges = toy_data[\\\"bin_edges\\\"]\\n sig = create_th1f(bin_edges, toy_data[\\\"sig\\\"], toy_data[\\\"sig_stat\\\"])\\n sig.SetName(\\\"signal\\\")\\n\\n data = create_th1f(bin_edges, toy_data[\\\"data\\\"], toy_data[\\\"data_stat\\\"])\\n data.SetName(\\\"data\\\")\\n\\n bkg = create_th1f(bin_edges, toy_data[\\\"bkg\\\"], toy_data[\\\"bkg_stat\\\"])\\n bkg.SetName(\\\"bkg\\\")\\n\\n root_file.Write()\\n root_file.Close()\",\n \"def StoreAntirollback(now, ar_filename, kern_f):\\n print 'antirollback time now ' + str(now)\\n sys.stdout.flush()\\n kern_f.write(str(now))\\n kern_f.flush()\\n tmpdir = os.path.dirname(ar_filename)\\n with tempfile.NamedTemporaryFile(mode='w', dir=tmpdir, delete=False) as f:\\n f.write(str(now) + '\\\\n')\\n f.flush()\\n os.fsync(f.fileno())\\n os.rename(f.name, ar_filename)\",\n \"def reload_tailed_file(self):\\n try:\\n self.file_ = open(self.tailed_file, \\\"r\\\")\\n self.size = os.path.getsize(self.tailed_file)\\n\\n # Go to the head of file\\n self.file_.seek(0, 1)\\n\\n return True\\n except:\\n return False\",\n \"def split_file(in_file, num_splits, split_dir, mut_file):\\n\\n # create the output directory if it does\\n # not exist\\n if not os.path.exists(split_dir):\\n os.mkdir(split_dir)\\n\\n # open the info file\\n f = open(in_file)\\n pdb_header = f.readline()\\n\\n # open the mutation file\\n m = open(mut_file)\\n mut_header = m.readline()\\n\\n # read into a dictionary containing\\n # structure ids as keys and lines pertaining\\n # to it as values\\n pdb_dict = read_file(f)\\n mut_dict = read_file(m)\\n\\n # determine total num of ids in file\\n total_ids = len(list(pdb_dict.keys()))\\n print(total_ids)\\n # determine num of ids to put in each split\\n num_ids = int(total_ids/num_splits)\\n\\n # counters\\n count_file = 0\\n count_id = num_ids\\n\\n # randomize order of insertions\\n keys = list(pdb_dict.keys())\\n random.shuffle(keys)\\n\\n # iterate through dict and write to files\\n #for key in sorted(pdb_dict):\\n for key in keys:\\n\\n # check if we need a new file\\n if (count_id == num_ids and count_file < num_splits):\\n count_id = 0\\n pdb_out = open(split_dir + \\\"/pdb_info_split_\\\" + str(count_file) + \\\".txt\\\", 'w')\\n pdb_out.write(pdb_header)\\n mut_out = open(split_dir + \\\"/mut_info_split_\\\" + str(count_file) + \\\".txt\\\", 'w')\\n mut_out.write(mut_header)\\n count_file += 1\\n\\n # write all lines pertaining to the structure id\\n for line in pdb_dict[key]:\\n pdb_out.write(line)\\n if key in mut_dict:\\n for line in mut_dict[key]:\\n mut_out.write(line)\\n\\n count_id += 1\",\n \"def writeFile(self, f, fname):\\n with open(self.PATH + fname, 'wb') as handle:\\n pickle.dump(f, handle, protocol = pickle.HIGHEST_PROTOCOL)\",\n \"def write_flow(flow, filename):\\n f = open(filename, 'wb')\\n magic = numpy.array([202021.25], dtype=numpy.float32)\\n (height, width) = flow.shape[0:2]\\n w = numpy.array([width], dtype=numpy.int32)\\n h = numpy.array([height], dtype=numpy.int32)\\n magic.tofile(f)\\n w.tofile(f)\\n h.tofile(f)\\n flow.tofile(f)\\n f.close()\",\n \"def processfile(file, out, me):\\n if out.endswith('.npz'):\\n out = out[:-4]\\n out = out + ('-%03d' % me) + '.npz'\\n if os.path.exists(out):\\n return\\n f = QPM.QPMSubsampleFile(file)\\n xis = []\\n mybf = QPM.LogWindowBiasFunction(edges[me], edges[me + 1])\\n mymock = QPM.halomock(f, 1e6, mybf, continuous=False)\\n for i in range(me + 1):\\n bf = QPM.LogWindowBiasFunction(edges[i], edges[i + 1])\\n mock = QPM.halomock(f, 1e6, bf, continuous=False)\\n # the error is nonsense since we have just one sample\\n # deal with it in combine\\n xi = QPM.xi([mock], mocks2=[mymock])\\n r = xi[0]\\n xis.append(xi[1])\\n print edges[i], edges[i + 1], len(mock[0]), mock[1].sum()\\n numpy.savez(out, r=r, xi=xis, edges=edges, N=1e6, me=me)\",\n \"def write_flow(flow, filename):\\n f = open(filename, 'wb')\\n magic = np.array([202021.25], dtype=np.float32)\\n (height, width) = flow.shape[0:2]\\n w = np.array([width], dtype=np.int32)\\n h = np.array([height], dtype=np.int32)\\n magic.tofile(f)\\n w.tofile(f)\\n h.tofile(f)\\n flow.tofile(f)\\n f.close()\",\n \"def save(self, fname):\\n pass\",\n \"def WriteCurrentHists( filename='hist.root') :\\n\\n file = ROOT.TFile.Open( filename, 'RECREATE')\\n\\n for hist, samp in samples.samples.iteritems() :\\n newhist = samp.hist.Clone(hist)\\n file.cd()\\n newhist.Write()\\n\\n file.Close()\",\n \"def _create_sparsed_file(self, nms, path, size):\\n nms.appliance.execute(\\n 'truncate --size %(size)dG %(path)s' % {\\n 'path': path,\\n 'size': size\\n }\\n )\",\n \"def saveUploadedRecipe(self, file):\\r\\n filename = str(file)\\r\\n with open(os.path.join(main.settings.RECIPE_DIR, filename), 'wb+') as destination:\\r\\n for chunk in file.chunks():\\r\\n destination.write(chunk)\",\n \"def write_dftb_in(self, filename):\\n\\n outfile = open(filename, 'w')\\n outfile.write('Geometry = GenFormat { \\\\n')\\n #outfile.write(' <<< \\\"geo_end.gen\\\" \\\\n')\\n outfile.write(' <<< %s \\\\n' %self.geo_fname)\\n outfile.write('} \\\\n')\\n outfile.write(' \\\\n')\\n\\n params = self.parameters.copy()\\n\\n s = 'Hamiltonian_MaxAngularMomentum_'\\n for key in params:\\n if key.startswith(s) and len(key) > len(s):\\n break\\n else:\\n # User didn't specify max angular mometa. Get them from\\n # the .skf files:\\n symbols = set(self.atoms.get_chemical_symbols())\\n for symbol in symbols:\\n path = os.path.join(self.slako_dir,\\n '{0}-{0}.skf'.format(symbol))\\n l = read_max_angular_momentum(path)\\n params[s + symbol] = '\\\"{}\\\"'.format('spdf'[l])\\n\\n # --------MAIN KEYWORDS-------\\n previous_key = 'dummy_'\\n myspace = ' '\\n for key, value in sorted(params.items()):\\n current_depth = key.rstrip('_').count('_')\\n previous_depth = previous_key.rstrip('_').count('_')\\n for my_backsclash in reversed(\\n range(previous_depth - current_depth)):\\n outfile.write(3 * (1 + my_backsclash) * myspace + '} \\\\n')\\n outfile.write(3 * current_depth * myspace)\\n if key.endswith('_') and len(value) > 0:\\n outfile.write(key.rstrip('_').rsplit('_')[-1] +\\n ' = ' + str(value) + '{ \\\\n')\\n elif (key.endswith('_') and (len(value) == 0) \\n and current_depth == 0): # E.g. 'Options {'\\n outfile.write(key.rstrip('_').rsplit('_')[-1] +\\n ' ' + str(value) + '{ \\\\n')\\n elif (key.endswith('_') and (len(value) == 0) \\n and current_depth > 0): # E.g. 'Hamiltonian_Max... = {'\\n outfile.write(key.rstrip('_').rsplit('_')[-1] +\\n ' = ' + str(value) + '{ \\\\n')\\n elif key.count('_empty') == 1:\\n outfile.write(str(value) + ' \\\\n')\\n elif ((key == 'Hamiltonian_ReadInitialCharges') and \\n (str(value).upper() == 'YES')):\\n f1 = os.path.isfile(self.directory + os.sep + 'charges.dat')\\n f2 = os.path.isfile(self.directory + os.sep + 'charges.bin')\\n if not (f1 or f2):\\n print('charges.dat or .bin not found, switching off guess')\\n value = 'No'\\n outfile.write(key.rsplit('_')[-1] + ' = ' + str(value) + ' \\\\n')\\n else:\\n outfile.write(key.rsplit('_')[-1] + ' = ' + str(value) + ' \\\\n')\\n # point\\n if self.pcpot is not None and ('DFTB' in str(value)):\\n outfile.write(' ElectricField = { \\\\n')\\n outfile.write(' PointCharges = { \\\\n')\\n outfile.write(\\n ' CoordsAndCharges [Angstrom] = DirectRead { \\\\n')\\n outfile.write(' Records = ' +\\n str(len(self.pcpot.mmcharges)) + ' \\\\n')\\n outfile.write(\\n ' File = \\\"dftb_external_charges.dat\\\" \\\\n')\\n outfile.write(' } \\\\n')\\n outfile.write(' } \\\\n')\\n outfile.write(' } \\\\n')\\n previous_key = key\\n\\n current_depth = key.rstrip('_').count('_')\\n for my_backsclash in reversed(range(current_depth)):\\n outfile.write(3 * my_backsclash * myspace + '} \\\\n')\\n #outfile.write('ParserOptions { \\\\n')\\n #outfile.write(' IgnoreUnprocessedNodes = Yes \\\\n')\\n #outfile.write('} \\\\n')\\n #if self.do_forces:\\n # outfile.write('Analysis { \\\\n')\\n # outfile.write(' CalculateForces = Yes \\\\n')\\n # outfile.write('} \\\\n')\\n\\n outfile.close()\",\n \"def save_as_fits(self, filename):\",\n \"def save_to(self, f: BinaryIO):\\n raise NotImplementedError\",\n \"def write(self):\\n # # Sometimes file is not written properly. So delete and rewrite it\\n # os.system('rm {}'.format(snip_dir + '/' + self.name))\\n # if 'NUM_TIME_STEPS' not in self.define.keys():\\n # warnings.warn('NUM_TIME_STEPS missing in header. Execution may hang!')\\n with open(snip_dir + '/' + self.name, 'w') as f:\\n f.write('/* Temporary generated file for snip process definitions before compilation */\\\\n')\\n f.write(self.__str__())\\n\\n # os.system('ls {}'.format(snip_dir + '/' + self.name))\",\n \"def write_to_fits(self, filename=None, gain=GAIN):\\n\\n hdu_new = self.hdu_ideal\\n hdu_new[1].data = (self.data/gain).astype('uint16') # Convert to ADU in 16 bit integers.\\n\\n if filename is None:\\n filename = self.ima_path[:-5] + self.modif_str + '.fits'\\n hdu_new.writeto(filename, overwrite=True)\\n\\n print('Writing to file: ' + filename)\",\n \"def downsample(self, tfactor=1, ffactor=1, gulp=512, filename=None,\\n back_compatible=True, **kwargs):\\n if filename is None:\\n filename = f\\\"{self.header.basename}_f{ffactor:d}_t{tfactor:d}.fil\\\"\\n if self.header.nchans % ffactor != 0:\\n raise ValueError(\\\"Bad frequency factor given\\\")\\n\\n # Gulp must be a multiple of tfactor\\n gulp = int(np.ceil(gulp / tfactor) * tfactor)\\n\\n out_file = self.header.prepOutfile(\\n filename,\\n {\\n \\\"tsamp\\\": self.header.tsamp * tfactor,\\n \\\"nchans\\\": self.header.nchans // ffactor,\\n \\\"foff\\\": self.header.foff * ffactor,\\n },\\n back_compatible=back_compatible\\n )\\n\\n write_ar = np.zeros(\\n gulp * self.header.nchans // ffactor // tfactor, dtype=self.header.dtype,\\n )\\n for nsamps, _ii, data in self.readPlan(gulp, **kwargs):\\n lib.downsample(data, write_ar, tfactor, ffactor, self.header.nchans, nsamps)\\n out_file.cwrite(\\n write_ar[:nsamps * self.header.nchans // ffactor // tfactor]\\n )\\n return out_file.name\",\n \"def write(self, file):\\n #write header\\n self.ID.write(file)\\n if (self.write_size): \\n self.size.write(file)\\n for variable in self.variables:\\n variable.write(file)\\n for subchunk in self.subchunks:\\n subchunk.write(file)\",\n \"def write_uem(uemf, uem, n_digits=3):\\n with open(uemf, 'wb') as f:\\n for file_id in sorted(iterkeys(uem)):\\n for onset, offset in sorted(uem[file_id]):\\n line = ' '.join([file_id,\\n '1',\\n format_float(onset, n_digits),\\n format_float(offset, n_digits)\\n ])\\n f.write(line.encode('utf-8'))\\n f.write(b'\\\\n')\",\n \"def write_to_file_x(path):\\n path1 = path + \\\"/x_Macros\\\"\\n if not os.path.exists(path1):\\n os.mkdir(path1)\\n for e in range(int(e_steps)+1):\\n filename = \\\"x%sy0z0ke%s.mac\\\" %(dx*x + x_min, e*de + e_min)\\n path = path1\\n fullpath = os.path.join(path, filename)\\n f = open(fullpath, \\\"w\\\")\\n f.write('/rat/physics_list/OmitMuonicProcesses true\\\\n')\\n f.write(\\\"/rat/physics_list/OmitHadronicProcesses true \\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write('/rat/db/set DETECTOR geo_file \\\"geo/snoplus.geo\\\"\\\\n')\\n f.write('/rat/db/set GEO[scint] material \\\"labppo_scintillator\\\"\\\\n')\\n f.write('/rat/db/set DAQ dqxx_info 0\\\\n')\\n f.write(\\\"/run/initialize \\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"/rat/proc frontend\\\\n\\\")\\n f.write(\\\"/rat/proc trigger\\\\n\\\")\\n f.write(\\\"/rat/proc eventbuilder\\\\n\\\")\\n f.write(\\\"/rat/proc count\\\\n\\\")\\n f.write(\\\"/rat/procset update 100\\\\n\\\")\\n f.write(\\\"/rat/proc calibratePMT\\\\n\\\")\\n f.write(\\\"/rat/proc scintFitter\\\\n\\\")\\n f.write(\\\"/rat/proclast outroot\\\\n\\\")\\n f.write('/rat/procset file \\\"x%sy0z0ke%s.root\\\"\\\\n' %(dx*x + x_min, e*de + e_min))\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"/generator/add combo gun:point:poisson\\\\n\\\")\\n f.write(\\\"# want random, isotropic momentum distribution; energy given in MeV\\\\n\\\")\\n f.write(\\\"/generator/vtx/set e- 0 0 0 %s\\\\n\\\" %(e*de + e_min))\\n f.write(\\\"# position given in Cartesians, relative to detector center, in mm\\\\n\\\")\\n f.write(\\\"/generator/pos/set %s 0 0\\\\n\\\" % (dx*x + x_min))\\n f.write(\\\"/generator/rate/set 1\\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"\\\\n\\\")\\n f.write(\\\"/rat/run/start %s\\\\n\\\" %(n))\\n f.write(\\\"exit\\\")\",\n \"def save(self,outPath=None):\\n if (not self.canSave): raise StateError(_(\\\"Insufficient data to write file.\\\"))\\n if not outPath:\\n fileInfo = self.fileInfo\\n outPath = os.path.join(fileInfo.dir,fileInfo.name)\\n out = file(outPath,'wb')\\n #--Tes3 Record\\n self.tes3.setChanged()\\n self.tes3.hedr.setChanged()\\n self.tes3.hedr.numRecords = len(self.records) #--numRecords AFTER TES3 record\\n self.tes3.getSize()\\n self.tes3.dump(out)\\n #--Other Records\\n for record in self.records:\\n record.getSize()\\n record.dump(out)\\n out.close()\",\n \"def init_flowgram_file(filename=None, n=0, l=400, prefix=\\\"/tmp/\\\"):\\r\\n\\r\\n if (filename is None):\\r\\n fd, filename = mkstemp (dir=prefix, suffix=\\\".dat\\\")\\r\\n close(fd)\\r\\n\\r\\n fh = open(filename, \\\"w\\\")\\r\\n fh.write(\\\"%d %d\\\\n\\\" % (n, l))\\r\\n return (fh, filename)\",\n \"def __write_measurement(self, measurement):\\n with self.__filename.open(mode='a') as history_file:\\n history_file.write(measurement + '\\\\n')\",\n \"def to_file(self, fname, delimiter=\\\"\\\\t\\\", encoding=\\\"utf-8\\\"):\\n with open(fname, \\\"wb\\\") as fh:\\n for key, score in self.ranked_items():\\n fh.write(self.to_record(key, score, delimiter).encode(encoding))\",\n \"def write_towhee_restart(self, filename, pbc=(0, 0, 0)):\\n seeds = [5054388, 14604618, 6176650, 7526479, 6525, 10097385, 9059353,\\n 14349506, 535, 7287374, 12195841, 7272997, 5692437, 11292972,\\n 1589479, 16351161, 14342867, 3500530, 14385737, 2924396,\\n 11857489, 6765405, 12074244, 5940539, 3050519]\\n version = 6\\n numcycles = 0\\n numboxes = 1\\n nummoltypes = 1\\n maxtranssingle = 0.5\\n maxtranscom = 0.15305334\\n maxrot = 0.672082\\n maxvoldis = [[1.0, 1.0, 1.0], [1.0, 1.0, 1.0], [1.0, 1.0, 1.0]]\\n if type(pbc) is list or type(pbc) is tuple:\\n pbc = np.asarray(pbc)\\n length = np.asarray(self.length) + pbc\\n hmatrix = np.diag(length)\\n maxvoldis.extend(list(hmatrix))\\n with open(filename, 'w') as f:\\n f.write(f\\\"\\\\t\\\\t{version}\\\\n\\\")\\n f.write(\\\"\\\\t\\\" + \\\"\\\\t \\\".join(map(str, seeds)) + \\\"\\\\n\\\")\\n f.write(f\\\"\\\\t{numcycles} \\\\t\\\\t{numboxes} \\\\t\\\\t{nummoltypes}\\\\n\\\")\\n f.write(f\\\"\\\\t{maxtranssingle:20.15f}\\\\n\\\")\\n f.write(f\\\"\\\\t{maxtranscom:20.15f}\\\\n\\\")\\n f.write(f\\\"\\\\t{maxrot:20.15f}\\\\n\\\\n\\\")\\n for row in maxvoldis:\\n f.write(f\\\"\\\\t{row[0]:20.15f} \\\\t{row[1]:20.15f} \\\\t{row[2]:20.15f}\\\\n\\\")\\n f.write(f\\\"\\\\t{self.numatom // self.molsize}\\\\n\\\")\\n f.write(f\\\"\\\\t{self.molsize}\\\\n\\\")\\n f.write(\\\"\\\\t \\\".join(map(str, list(self.contents['Mol_type'].astype(int)))) + \\\"\\\\n\\\")\\n f.write(\\\"\\\\t \\\".join(map(str, list(self.contents['Box_ID'].astype(int)))) + \\\"\\\\n\\\")\\n df = self.contents[['X', 'Y', 'Z']].copy()\\n np.savetxt(f, df.values, fmt=\\\" %20.15f\\\"*3)\",\n \"def write_file(self):\\n print 'Writing '+self.name+' binary...'\\n if self.vals is not None:\\n if len(self.vals) == self.size:\\n stream = self.pack_mem()\\n with open(self.name+'.bin','wb') as f:\\n f.write(stream)\\n print 'File written: '+self.name+'.bin'\\n else:\\n print 'Error: input array for '+self.name+'is not the right '+\\\\\\n 'size (should be '+str(self.size)+'). Skipping.'\\n else:\\n print 'No array provided, skipping.'\",\n \"def resize_file(fobj, diff, BUFFER_SIZE=2 ** 16):\\n\\n fobj.seek(0, 2)\\n filesize = fobj.tell()\\n\\n if diff < 0:\\n if filesize + diff < 0:\\n raise ValueError\\n # truncate flushes internally\\n fobj.truncate(filesize + diff)\\n elif diff > 0:\\n try:\\n while diff:\\n addsize = min(BUFFER_SIZE, diff)\\n fobj.write(b\\\"\\\\x00\\\" * addsize)\\n diff -= addsize\\n fobj.flush()\\n except IOError as e:\\n if e.errno == errno.ENOSPC:\\n # To reduce the chance of corrupt files in case of missing\\n # space try to revert the file expansion back. Of course\\n # in reality every in-file-write can also fail due to COW etc.\\n # Note: IOError gets also raised in flush() due to buffering\\n fobj.truncate(filesize)\\n raise\",\n \"def __appendToFile(self, st):\\n fh = open(self.__fileName, \\\"a\\\")\\n line = st.get_id_student() + \\\" \\\" + st.get_nume_student()\\n fh.write(\\\"\\\\n\\\")\\n fh.write(line)\\n fh.close()\",\n \"def writeHedr(self):\\n path = os.path.join(self.dir,self.name)\\n out = file(path,'r+b')\\n out.seek(16) #--Skip to Hedr record data\\n self.tes3.hedr.getSize()\\n self.tes3.hedr.dump(out)\\n out.close()\\n #--Done\\n self.getHeader()\\n self.setMTime()\",\n \"def write_file_simple(self,filename):\\n\\n output = open(filename,\\\"w\\\")\\n # write header\\n output.write(\\\"# %1s %3s %22s %6s %22s\\\\n\\\"%(\\\"l\\\",\\\"n\\\",\\\"nu_theo (muHz)\\\",\\\"unused\\\",\\\"Inertia\\\"))\\n for i in range(self.modes.shape[0]):\\n output.write(\\\" %1d %3d %22.15e 0.0 %22.15e\\\\n\\\"%( \\\\\\n self.modes[\\\"l\\\"][i], \\\\\\n self.modes[\\\"n\\\"][i], \\\\\\n self.modes[\\\"freq\\\"][i]*self.glb[ifreq_ref], \\\\\\n self.modes[\\\"inertia\\\"][i]))\\n output.close()\",\n \"def newfile(self) :\\n\\n\\t\\tfrom tempfile import mkstemp\\n\\t\\timport os\\n\\t\\tglobal configurer\\n\\n\\t\\tfd,name = mkstemp(suffix='.blend')\\n\\t\\tos.close(fd)\\n\\t\\tself.name = name\\n\\t\\tfd = open(name,'wb', configurer.get('ServerBufferSize'))\\n\\t\\tself.fd = fd\\n\\t\\tprint name\\n\\t\\treturn 1\",\n \"def dump(self, step=None):\\n if self._compressed:\\n np.savez_compressed(self._file_path, **self._data)\\n else:\\n np.savez(self._file_path, **self._data)\",\n \"def random_split_tf_record(file, filenames, ratios=(0.5, 0.5)):\\n assert (len(filenames) == len(ratios)) and (len(filenames) == 2), 'Support two parts only'\\n\\n if tf.gfile.Exists(filenames[0]) or tf.gfile.Exists(filenames[1]):\\n raise FileExistsError('File exists. Continuing will overwrite it. Abort!')\\n\\n ratio = ratios[0] / sum(ratios)\\n\\n with TFRecordWriter(filenames[0]) as tfwriter1, TFRecordWriter(filenames[1]) as tfwriter2:\\n for example in tf.python_io.tf_record_iterator(file):\\n if np.random.rand(1) <= ratio:\\n tfwriter1.write(example)\\n else:\\n tfwriter2.write(example)\\n\\n tfwriter1.flush()\\n tfwriter2.flush()\",\n \"def write_flt_file(filename, data, dsize):\\n binfile = open(filename,'wb')\\n\\n dsize = numpy.array(dsize)\\n dsize[-1] = data.shape[0]\\n\\n header = [len(dsize)] # dimension\\n header.extend(list(dsize)) # size\\n header.append(4) # data type: float\\n header.append(dsize.prod()) # total length of data\\n\\n a = array.array('i')\\n a.fromlist(header)\\n if is_little_endian():\\n a.byteswap()\\n\\n a.tofile(binfile)\\n\\n a = array.array('f')\\n for o in data:\\n a.fromlist(list(o))\\n if is_little_endian():\\n a.byteswap()\\n a.tofile(binfile)\\n binfile.close()\",\n \"def write_checkpoint(self):\\n self.file_checkpoint_data = open(self.path_checkpoint, \\\"a+\\\")\\n array_to_write = [str(self.radious), self.type_feature, self.type_filtering, self.h_filterig]\\n self.file_checkpoint_data.write(','.join(array_to_write) + \\\"\\\\n\\\")\\n self.file_checkpoint_data.flush()\",\n \"def save_whiten_mat(W):\\n w_id = open('data/W.bin','w')\\n W.tofile(w_id)\\n w_id.close()\",\n \"def write_file(self,f=None):\\n nrow, ncol, nlay, nper = self.parent.nrow_ncol_nlay_nper\\n # Open file for writing\\n if f is None:\\n f = open(self.fn_path, 'w')\\n # First line: heading\\n f.write('{}\\\\n'.format(self.heading))\\n # write dataset 1\\n f.write('{} {} {} {} {} {} {}\\\\n'.format(self.ipakcb, self.iswtoc,\\n self.nsystm, self.ithk,\\n self.ivoid, self.istpcs,\\n self.icrcc))\\n # write dataset 2\\n t = self.lnwt.array\\n for tt in t:\\n f.write('{} '.format(tt + 1))\\n f.write('\\\\n')\\n\\n # write dataset 3\\n f.write(\\n '{} {} {} {} {} {} {} {} {} {}\\\\n'.format(self.izcfl, self.izcfm,\\n self.iglfl, self.iglfm,\\n self.iestfl, self.iestfm,\\n self.ipcsfl, self.ipcsfm,\\n self.istfl, self.istfm))\\n\\n # write dataset 4\\n f.write(self.gl0.get_file_entry())\\n\\n # write dataset 5\\n f.write(self.sgm.get_file_entry())\\n\\n # write dataset 6\\n f.write(self.sgs.get_file_entry())\\n\\n # write datasets 7 to 13\\n for k in range(self.nsystm):\\n f.write(self.thick[k].get_file_entry())\\n if self.icrcc != 0:\\n f.write(self.sse[k].get_file_entry())\\n f.write(self.ssv[k].get_file_entry())\\n else:\\n f.write(self.cr[k].get_file_entry())\\n f.write(self.cc[k].get_file_entry())\\n f.write(self.void[k].get_file_entry())\\n f.write(self.sub[k].get_file_entry())\\n\\n # write datasets 14 and 15\\n for k in range(nlay):\\n if self.istpcs != 0:\\n f.write(self.pcsoff[k].get_file_entry())\\n else:\\n f.write(self.pcs[k].get_file_entry())\\n\\n # write dataset 16 and 17\\n if self.iswtoc > 0:\\n # dataset 16\\n for i in self.ids16:\\n f.write('{} '.format(i))\\n f.write(' #dataset 16\\\\n')\\n\\n # dataset 17\\n for k in range(self.iswtoc):\\n t = self.ids17[k, :].copy()\\n t[0:4] += 1\\n for i in t:\\n f.write('{} '.format(i))\\n f.write(' #dataset 17 iswtoc {}\\\\n'.format(k + 1))\\n\\n # close swt file\\n f.close()\",\n \"def write (self, file):\\n\\t\\tfile.write (self.pack ())\",\n \"def save_final_config(self, configuration):\\n filename = (\\n \\\"transpose-\\\" + str(max(self.args.begin, 1)) +\\n \\\"_\\\" + str(max(self.args.end, 1)) +\\n \\\"_\\\" + str(max(self.args.nruns, 1)) +\\n time.strftime(\\\"-%Y%m%d-%H%M%S\\\") + \\\".json\\\")\\n print(\\\"Optimal block size written to \\\" + filename +\\n \\\": \\\", configuration.data)\\n self.manipulator().save_to_file(configuration.data, filename)\",\n \"def test_append_to_flowgram_file(self):\\r\\n\\r\\n fh, tmp_filename = init_flowgram_file(n=100, l=400)\\r\\n self.assert_(exists(tmp_filename))\\r\\n self.tmp_filename = tmp_filename\\r\\n\\r\\n flow1 = Flowgram(\\\"0 1.2 2.1 3.4 0.02 0.01 1.02 0.08\\\")\\r\\n append_to_flowgram_file(\\\"test_id\\\", flow1, fh)\\r\\n\\r\\n flow2 = Flowgram('0.5 1.0 4.1 0.0 0.0 1.23 0.0 3.1',\\r\\n Name='a', floworder=\\\"TACG\\\",\\r\\n header_info={\\r\\n 'Bases': 'TACCCCAGGG', 'Clip Qual Right': 7,\\r\\n 'Flow Indexes': \\\"1\\\\t2\\\\t3\\\\t3\\\\t3\\\\t3\\\\t6\\\\t8\\\\t8\\\\t8\\\"})\\r\\n append_to_flowgram_file(\\\"test_id2\\\", flow2, fh, trim=True)\\r\\n # close and re-open to read from start, seek might work as well here...\\r\\n fh.close()\\r\\n fh = open(tmp_filename)\\r\\n result_file_content = list(fh)\\r\\n self.assertEqual(result_file_content, [\\\"100 400\\\\n\\\",\\r\\n \\\"test_id 8 0.0 1.2 2.1 3.4 0.02 0.01 1.02 0.08\\\\n\\\",\\r\\n \\\"test_id2 6 0.5 1.0 4.1 0.0 0.0 1.23\\\\n\\\"])\",\n \"def savemat(self, file_name):\\n d = {'dG0_prime': self.dG0_prime,\\n 'dG0': self.dG0,\\n 'T': self.T,\\n 'I': self.I,\\n 'pH': self.pH,\\n 'pMg': self.pMg,\\n 'weight': self.weight,\\n 'cids': self.cids,\\n 'S': self.S.values}\\n savemat(file_name, d, oned_as='row')\",\n \"def run_ptmcmc_save(\\n sampler, startPos, nSteps, file, progress=True, col_names=\\\"\\\", **kwargs\\n):\\n if file:\\n with open(file, \\\"w\\\") as f:\\n f.write(col_names)\\n if col_names:\\n f.write(\\\"\\\\n\\\")\\n\\n iStep = 0\\n if progress:\\n bar = tqdm(total=nSteps)\\n\\n ## TODO: Impliment this with kwrgs manipulation, currently it is dumb.\\n try:\\n for pos, prob, like in sampler.sample(\\n startPos, iterations=nSteps, store=False, **kwargs\\n ):\\n iStep += 1\\n if progress:\\n bar.update()\\n # pos is shape (ntemps, nwalkers, npars)\\n # prob is shape (ntemps, nwalkers)\\n # loop over all walkers for first temp and append to file\\n zpos = pos[0, ...]\\n zprob = prob[0, ...]\\n\\n for k in range(zpos.shape[0]):\\n thisPos = zpos[k]\\n thisProb = zprob[k]\\n\\n with open(file, \\\"a\\\") as f:\\n f.write(\\n \\\"{0:4d} {1:s} {2:f}\\\\n\\\".format(\\n k, \\\" \\\".join(map(str, thisPos)), thisProb\\n )\\n )\\n\\n except TypeError:\\n for pos, prob, like in sampler.sample(\\n startPos, iterations=nSteps, storechain=True, **kwargs\\n ):\\n iStep += 1\\n if progress:\\n bar.update()\\n # pos is shape (ntemps, nwalkers, npars)\\n # prob is shape (ntemps, nwalkers)\\n # loop over all walkers for first temp and append to file\\n zpos = pos[0, ...]\\n zprob = prob[0, ...]\\n\\n for k in range(zpos.shape[0]):\\n thisPos = zpos[k]\\n thisProb = zprob[k]\\n\\n with open(file, \\\"a\\\") as f:\\n f.write(\\n \\\"{0:4d} {1:s} {2:f}\\\\n\\\".format(\\n k, \\\" \\\".join(map(str, thisPos)), thisProb\\n )\\n )\\n\\n if progress:\\n bar.close()\\n return sampler\",\n \"def tofile(self, f):\\n raise NotImplementedError(\\\"ScalableRedisLocalBloomFilter not support tofile\\\")\",\n \"def to_file(self, fid, precision=16, comment_lines=[], foldmaskinfo=True):\\n # Open the file object.\\n newfile = False\\n if not hasattr(fid, 'write'):\\n newfile = True\\n fid = open(fid, 'w')\\n\\n # Write comments\\n for line in comment_lines:\\n fid.write('# ')\\n fid.write(line.strip())\\n fid.write(os.linesep)\\n\\n # Write out the shape of the fs\\n fid.write('{0} '.format(self.sample_size))\\n\\n if foldmaskinfo:\\n if not self.folded:\\n fid.write('unfolded ')\\n else:\\n fid.write('folded ')\\n \\n fid.write(os.linesep)\\n\\n # Write the data to the file\\n self.data.tofile(fid, ' ', '%%.%ig' % precision)\\n fid.write(os.linesep)\\n\\n if foldmaskinfo:\\n # Write the mask to the file\\n np.asarray(self.mask,int).tofile(fid, ' ')\\n fid.write(os.linesep)\\n\\n # Close file\\n if newfile:\\n fid.close()\",\n \"def save_h5(self, filename):\\n try:\\n shutil.copyfile(filename, '{0}_bak'.format(filename))\\n except IOError:\\n print 'could not make backup of trainer param file (which is \\\\\\n normal if we haven\\\\'t saved one until now)'\\n paramfile = tables.openFile(filename, 'w')\\n paramfile.createArray(paramfile.root, 'learningrate',\\n self.learningrate)\\n paramfile.createArray(paramfile.root, 'verbose', self.verbose)\\n paramfile.createArray(paramfile.root, 'loadsize', self.loadsize)\\n paramfile.createArray(paramfile.root, 'batchsize', self.batchsize)\\n paramfile.createArray(paramfile.root, 'momentum',\\n self.momentum)\\n paramfile.createArray(paramfile.root, 'epochcount',\\n self.epochcount)\\n paramfile.createArray(paramfile.root, 'momentum_batchcounter',\\n self.momentum_batchcounter)\\n incsgrp = paramfile.createGroup(paramfile.root, 'incs', 'increments')\\n for p in self._params:\\n paramfile.createArray(incsgrp, p.name, self._incs[p].get_value())\\n if self.rmsprop is not None:\\n avg_grad_sqrs_grp = paramfile.createGroup(paramfile.root, 'avg_grad_sqrs')\\n for p in self._params:\\n paramfile.createArray(avg_grad_sqrs_grp, p.name, self._avg_grad_sqrs[p].get_value())\\n paramfile.close()\",\n \"def dump_gain_file(filename,raw=None,gain=None,model=None,chisq=[],name_prefix=\\\"\\\"):\\n import os\\n dirname,basename = os.path.split(filename)\\n full_filename = os.path.join(dirname,name_prefix+basename)\\n outfile = open(full_filename,\\\"w\\\")\\n d = raw\\n print 'Dumping gains to %s' % full_filename\\n stepsize = d.shape[1]\\n # Header\\n outfile.write(\\\"#Tubes Sectors Steps\\\\n\\\")\\n outfile.write(\\\"%d %d %d\\\\n\\\" % (d.shape[-1],d.shape[0],d.shape[1]))\\n # raw data\\n for tube_no in range(d.shape[-1]):\\n for sector_no in range(d.shape[0]):\\n for step_no in range(stepsize):\\n outfile.write(\\\"%8.3f %7.3f\\\\n\\\" % (d.storage[sector_no,step_no,tube_no],d.var[sector_no,step_no,tube_no]))\\n outfile.write(\\\"#intensities\\\\n\\\")\\n for intensity in model:\\n outfile.write(\\\"%8.3f\\\\n\\\" % intensity)\\n outfile.write(\\\"#gains\\\\n\\\")\\n for g in gain:\\n outfile.write(\\\"%8.3f\\\\n\\\" % g)\\n outfile.write(\\\"#chisq\\\\n\\\")\\n for c in chisq:\\n outfile.write(\\\"%8.3f\\\\n\\\" % c)\\n outfile.close()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.53168994","0.52053297","0.50609237","0.5041503","0.5023959","0.49947497","0.49635452","0.495652","0.49504188","0.49476227","0.494738","0.49422064","0.49133167","0.4913253","0.49015784","0.48993456","0.48802665","0.48687673","0.4865208","0.48493338","0.48483008","0.48411688","0.48411688","0.48292923","0.4820725","0.48182422","0.48146063","0.48059195","0.48008552","0.4798425","0.4791038","0.4785083","0.47848228","0.47810966","0.4771805","0.47674382","0.47661558","0.47650748","0.47609174","0.47602922","0.47599083","0.47548285","0.47500372","0.4742242","0.4738615","0.47331083","0.47325346","0.47307602","0.4724912","0.47224358","0.47204024","0.4715254","0.47075725","0.46940583","0.46907112","0.46849802","0.46831205","0.46741942","0.4668082","0.46671665","0.46654204","0.46509245","0.46470276","0.46446297","0.46377134","0.46304256","0.4626727","0.4620425","0.4615402","0.46146324","0.4613788","0.4611493","0.46103948","0.46093687","0.46078885","0.46061006","0.46039736","0.46026155","0.46019238","0.45962435","0.4594668","0.45935556","0.45911208","0.45818764","0.4578097","0.4577635","0.45700577","0.45680684","0.4565439","0.45647058","0.45635396","0.4561961","0.45530865","0.45525205","0.4550309","0.45476085","0.45453435","0.45446137","0.45429087","0.4539477"],"string":"[\n \"0.53168994\",\n \"0.52053297\",\n \"0.50609237\",\n \"0.5041503\",\n \"0.5023959\",\n \"0.49947497\",\n \"0.49635452\",\n \"0.495652\",\n \"0.49504188\",\n \"0.49476227\",\n \"0.494738\",\n \"0.49422064\",\n \"0.49133167\",\n \"0.4913253\",\n \"0.49015784\",\n \"0.48993456\",\n \"0.48802665\",\n \"0.48687673\",\n \"0.4865208\",\n \"0.48493338\",\n \"0.48483008\",\n \"0.48411688\",\n \"0.48411688\",\n \"0.48292923\",\n \"0.4820725\",\n \"0.48182422\",\n \"0.48146063\",\n \"0.48059195\",\n \"0.48008552\",\n \"0.4798425\",\n \"0.4791038\",\n \"0.4785083\",\n \"0.47848228\",\n \"0.47810966\",\n \"0.4771805\",\n \"0.47674382\",\n \"0.47661558\",\n \"0.47650748\",\n \"0.47609174\",\n \"0.47602922\",\n \"0.47599083\",\n \"0.47548285\",\n \"0.47500372\",\n \"0.4742242\",\n \"0.4738615\",\n \"0.47331083\",\n \"0.47325346\",\n \"0.47307602\",\n \"0.4724912\",\n \"0.47224358\",\n \"0.47204024\",\n \"0.4715254\",\n \"0.47075725\",\n \"0.46940583\",\n \"0.46907112\",\n \"0.46849802\",\n \"0.46831205\",\n \"0.46741942\",\n \"0.4668082\",\n \"0.46671665\",\n \"0.46654204\",\n \"0.46509245\",\n \"0.46470276\",\n \"0.46446297\",\n \"0.46377134\",\n \"0.46304256\",\n \"0.4626727\",\n \"0.4620425\",\n \"0.4615402\",\n \"0.46146324\",\n \"0.4613788\",\n \"0.4611493\",\n \"0.46103948\",\n \"0.46093687\",\n \"0.46078885\",\n \"0.46061006\",\n \"0.46039736\",\n \"0.46026155\",\n \"0.46019238\",\n \"0.45962435\",\n \"0.4594668\",\n \"0.45935556\",\n \"0.45911208\",\n \"0.45818764\",\n \"0.4578097\",\n \"0.4577635\",\n \"0.45700577\",\n \"0.45680684\",\n \"0.4565439\",\n \"0.45647058\",\n \"0.45635396\",\n \"0.4561961\",\n \"0.45530865\",\n \"0.45525205\",\n \"0.4550309\",\n \"0.45476085\",\n \"0.45453435\",\n \"0.45446137\",\n \"0.45429087\",\n \"0.4539477\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.62867725"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88580,"cells":{"query":{"kind":"string","value":"Detects Xepr instances which are waiting for connections from XeprAPI clients. For this to work, the API has to be enabled in Xepr (menu \"Processing\" > submenu \"XeprAPI\" > menu item \"Enable Xepr API\"). Xepr instances which already are connected to an XeprAPI client are not listed."},"document":{"kind":"string","value":"def getXeprInstances():\n apilib = _loadapilib()\n instances = _findInst(apilib)\n return dict([(p, t) for p, t in instances])"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _wait_active(client, request_id, max_num):\n logging.info('Waiting for instances to be active')\n while True:\n res = client.describe_spot_fleet_instances(SpotFleetRequestId=request_id)\n if len(res['ActiveInstances']) == max_num:\n logging.info('Instances are active now.')\n instance_id_list = [ i['InstanceId'] for i in res['ActiveInstances'] ]\n return instance_id_list\n time.sleep(10)","def wait_for_instances(self) -> pulumi.Output[Optional[bool]]:\n return pulumi.get(self, \"wait_for_instances\")","async def _check_api(self) -> None:\n await self._api_request(\"devices\")","def detect_instances(self):\n lh.subsection(\"Instance Detection for {0.name}\".format(self))\n jwt = self.get_jwt_header()\n self.all_instances = []\n logging.debug(\"waiting for frontend\")\n logfiles = set() # logfiles that can be used for debugging\n\n # the more instances we expect to spawn the more patient:\n tries = 10 * self.expect_instance_count\n\n # Wait for forntend to become alive.\n all_instances_up = False\n while not all_instances_up and tries:\n self.all_instances = []\n detected_instances = []\n sys.stdout.write(\".\")\n sys.stdout.flush()\n\n for root, dirs, files in os.walk(self.basedir):\n for onefile in files:\n # logging.debug(\"f: \" + root + os.path.sep + onefile)\n if onefile.endswith(\"log\"):\n logfiles.add(str(Path(root) / onefile))\n\n for name in dirs:\n # logging.debug(\"d: \" + root + os.path.sep + name)\n match = None\n instance_class = None\n if name.startswith(\"sync\"):\n match = re.match(r\"(syncmaster|syncworker)(\\d*)\", name)\n instance_class = SyncInstance\n else:\n match = re.match(\n r\"(agent|coordinator|dbserver|resilientsingle|single)(\\d*)\",\n name,\n )\n instance_class = ArangodInstance\n # directory = self.basedir / name\n if match and len(match.group(2)) > 0:\n # we may see a `local-slave-*` directory inbetween,\n # hence we need to choose the current directory not\n # the starter toplevel dir for this:\n instance = instance_class(\n match.group(1),\n match.group(2),\n self.cfg.localhost,\n self.cfg.publicip,\n Path(root) / name,\n self.passvoid,\n self.cfg.ssl,\n self.cfg.version,\n self.enterprise,\n jwt=jwt,\n )\n instance.wait_for_logfile(tries)\n instance.detect_pid(\n ppid=self.instance.pid,\n full_binary_path=self.cfg.real_sbin_dir,\n offset=0,\n )\n detected_instances.append(instance.instance_type)\n self.all_instances.append(instance)\n\n print(self.expect_instances)\n detected_instances.sort()\n print(detected_instances)\n attach(str(self.expect_instances), \"Expected instances\")\n attach(str(detected_instances), \"Detected instances\")\n if (self.expect_instances != detected_instances) or (not self.get_frontends()):\n tries -= 1\n time.sleep(5)\n else:\n all_instances_up = True\n\n if not self.get_frontends():\n print()\n logging.error(\"STARTER FAILED TO SPAWN ARANGOD\")\n self.show_all_instances()\n logging.error(\"can not continue without frontend instance\")\n logging.error(\"please check logs in\" + str(self.basedir))\n for logf in logfiles:\n logging.debug(logf)\n message = \"if that does not help try to delete: \" + str(self.basedir)\n logging.error(message)\n raise Exception(message)\n self.show_all_instances()","def _check_awaiting(self):\r\n # TODO: check for wait loops\r\n for w in list(self._awaiting.values()):\r\n self._try_register_platform(w[\"instance\"], w[\"kind\"], w[\"parent\"], w[\"wait\"], awaiting=True)","def detect_instance_pids_still_alive(self):\n missing_instances = []\n running_pids = psutil.pids()\n for instance in self.all_instances:\n if instance.pid not in running_pids:\n missing_instances.append(instance)\n\n if len(missing_instances) > 0:\n logging.error(\n \"Not all instances are alive. The following are not running: %s\",\n str(missing_instances),\n )\n logging.error(get_process_tree())\n raise Exception(\"instances missing: \" + str(missing_instances))\n instances_table = get_instances_table(self.get_instance_essentials())\n logging.info(\"All arangod instances still running: \\n%s\", str(instances_table))\n attach_table(instances_table, \"Instances table\")","def _get_instances_pending_events(self):\n\n conn = connect_to_region(REGION, aws_access_key_id=KEY_ID, aws_secret_access_key=ACCESS_KEY)\n stats = conn.get_all_instance_status()\n next_token = stats.next_token\n while next_token != None:\n next_stats = conn.get_all_instance_status(next_token=next_token)\n stats.extend(next_stats)\n next_token = next_stats.next_token\n ret = []\n for stat in stats:\n if stat.events:\n for event in stat.events:\n if re.match('^\\[Completed\\]', event.description):\n continue\n ret.append([stat.id, event.code, event.not_before])\n if len(ret) > 0:\n instances = get_instances([stat[0] for stat in ret])\n for stat in ret:\n stat.insert(1, instances[stat[0]])\n return ret","def wait_for_container():\n for i in xrange(30):\n print(\"Waiting for service to come up\")\n try:\n requests.get(URL).raise_for_status()\n return True\n except Exception as e:\n print e\n sleep(1)\n\n return False","def get_polling_service_instances_11(self):\n poll_instances = []\n poll_services = PollService.objects.filter(data_collections=self, enabled=True)\n for poll_service in poll_services:\n message_bindings = [mb.binding_id for mb in poll_service.supported_message_bindings.all()]\n for supported_protocol_binding in poll_service.supported_protocol_bindings.all():\n poll_instance = tm11.PollingServiceInstance(supported_protocol_binding.binding_id,\n poll_service.build_service_address(supported_protocol_binding.binding_id),\n message_bindings)\n poll_instances.append(poll_instance)\n\n return poll_instances","async def async_discovery(hass: HomeAssistant) -> list[dict[str, Any]]:\n LOGGER.debug(\"Starting ONVIF discovery\")\n services = await hass.async_add_executor_job(wsdiscovery)\n\n devices = []\n for service in services:\n url = urlparse(service.getXAddrs()[0])\n device = {\n CONF_DEVICE_ID: None,\n CONF_NAME: service.getEPR(),\n CONF_HOST: url.hostname,\n CONF_PORT: url.port or 80,\n CONF_HARDWARE: None,\n }\n for scope in service.getScopes():\n scope_str = scope.getValue()\n if scope_str.lower().startswith(\"onvif://www.onvif.org/name\"):\n device[CONF_NAME] = scope_str.split(\"/\")[-1]\n if scope_str.lower().startswith(\"onvif://www.onvif.org/hardware\"):\n device[CONF_HARDWARE] = scope_str.split(\"/\")[-1]\n if scope_str.lower().startswith(\"onvif://www.onvif.org/mac\"):\n device[CONF_DEVICE_ID] = scope_str.split(\"/\")[-1]\n devices.append(device)\n\n return devices","def find_connections():\n # print \"External\"\n # print findservices('00:0D:93:19:C8:68')\n # print findservices('bc:f5:ac:84:81:0c')\n # print finddevices()\n # print findservices(gethostaddr())\n # print gethostclass()\n print \"Your address: \", lb.gethostaddr()\n print lb.finddevicename(lb.gethostaddr())\n s = lb.socket()\n #s.bind((\"\", 0)) # RFCOMM port\n #s.bind((\"\", 1)) # RFCOMM port\n s.bind((\"\", 2)) # RFCOMM port\n print \"About to listen\"\n s.listen(1)\n print \"About to advertise\"\n lb.advertise(\"LightBlueService\", s, lb.RFCOMM)\n print \"Advertised at {} and listening on channel {}...\".format(s.getsockname()[0], s.getsockname()[1])\n print \"Waiting to accept\"\n # s.setblocking(1)\n try:\n conn, addr = s.accept()\n except KeyboardInterrupt:\n print \"Closing connection due to keyboard intterupt\"\n s.close()\n raise KeyboardInterrupt\n # Set timeout for 1 second\n # s.settimeout(1.0)\n print \"Connected by\", addr\n return conn, addr, s","def wait_for_open_ports(self, instance_name=\"\"):\n ports = None\n if instance_name in wellknownports:\n ports = wellknownports[instance_name]\n else:\n elements = self.systemd_name.split(\"@\")\n if elements[0] in wellknownports:\n ports = wellknownports[elements[0]]\n if ports:\n ipautil.wait_for_open_ports('localhost', ports,\n self.api.env.startup_timeout)","def ensure_discovery_jobs(self):\n if self.is_managed and self.object_profile.enable_box_discovery:\n Job.submit(\n \"discovery\",\n self.BOX_DISCOVERY_JOB,\n key=self.id,\n pool=self.pool.name,\n delta=self.pool.get_delta(),\n keep_ts=True,\n )\n else:\n Job.remove(\"discovery\", self.BOX_DISCOVERY_JOB, key=self.id, pool=self.pool.name)\n if self.is_managed and self.object_profile.enable_periodic_discovery:\n Job.submit(\n \"discovery\",\n self.PERIODIC_DISCOVERY_JOB,\n key=self.id,\n pool=self.pool.name,\n delta=self.pool.get_delta(),\n keep_ts=True,\n )\n else:\n Job.remove(\"discovery\", self.PERIODIC_DISCOVERY_JOB, key=self.id, pool=self.pool.name)","def _wait_initialized(client, instance_id_list):\n logging.info('Waiting for instances to be initialized.')\n while True:\n res = client.describe_instance_status(InstanceIds=instance_id_list)\n if len(res['InstanceStatuses']) == 0:\n time.sleep(10)\n continue\n if all([ s['InstanceStatus']['Status'] == 'ok' for s in res['InstanceStatuses'] ]):\n logging.info('Instances are initialized now.')\n return\n time.sleep(10)","def test_connection(cls, instances):\n try:\n instance, = instances\n except ValueError:\n cls.raise_user_error('multiple_instances')\n\n try:\n with magento.API(\n instance.url, instance.api_user, instance.api_key\n ):\n return\n except (\n xmlrpclib.Fault, IOError, xmlrpclib.ProtocolError, socket.timeout\n ):\n cls.raise_user_error(\"connection_error\")","def keep_vifs_bound():\n global EVT_TIMEOUT, NETSRS\n\n while bEndless:\n with xenapi_session() as x:\n try:\n vms = x.VM.get_all_records() # Get a list of VMs for multiple uses\n\n # If the host is in maintenance mode end it and auto start VMs\n host_ref = x.host.get_by_uuid(get_host_ref())\n if not x.host.get_enabled(host_ref):\n x.host.enable(host_ref) # End maintenance mode\n\n # Get a list of suitable VMs to start, ordered by ha restart priority\n autostart_list = [(vms[k]['order'], k, float(vms[k]['start_delay'])) for k in vms.keys() if (\n (not vms[k]['is_a_snapshot']) and\n (not vms[k]['is_a_template']) and\n (not vms[k]['is_control_domain']) and\n (('auto_poweron' in vms[k]['other_config']) and (vms[k]['other_config']['auto_poweron'])) and\n ('Halted' == vms[k]['power_state'])\n )]\n # We avoid .sort with a lambda to be able to delete the vms list\n from operator import itemgetter\n autostart_list.sort(key=itemgetter(0))\n\n # Attempt to start the VMs, while respecting the delays\n for i in range(len(autostart_list)):\n vm_ref = autostart_list[i][1]\n try:\n x.VM.start(vm_ref, False, False)\n except:\n pass\n finally:\n from time import sleep\n if i < (len(autostart_list) - 1):\n sleep(autostart_list[i][2])\n\n del autostart_list # Clean up\n\n # Find the ObscureRef of the target VM\n try:\n vmref = [k for k in vms.keys() if vms[k]['name_label'] == VMNAME][0]\n except:\n print('Unable to find a VM named \"{}\"'.format(VMNAME))\n exit(4)\n vifs = x.VM.get_VIFs(vmref)\n bNetworkFound = False\n for vif in vifs:\n if SSPNNAME == x.network.get_record(x.VIF.get_network(vif))['name_label']:\n bNetworkFound = True\n break\n if not bNetworkFound:\n print('Unable to find a network named \"{}\" attached to the \"{}\" VM'.format(SSPNNAME, VMNAME))\n exit(5)\n\n # Clean up\n del vifs\n del vms\n\n # Non-blocking listen for VM events\n token = '' # Initial token\n while bEndless:\n output = x.event_from(['VM'], token, EVT_TIMEOUT)\n token = output['token'] # Current token\n\n for event in output['events']:\n # Check the IP assigned to the VIFs of the target VM, if it's running\n if (('add' == event['operation']) or\n ('mod' == event['operation'])) and \\\n (vmref == event['ref']) and \\\n ('Running' == x.VM.get_power_state(vmref)):\n if 'snapshot' not in event:\n continue\n vifs = event['snapshot']['VIFs'] # Virtual interfaces list\n for vif in vifs:\n net = x.VIF.get_network(vif) # Network ref\n netrec = x.network.get_record(net) # Network record\n if SSPNNAME != netrec['name_label']:\n continue\n if rebind_ip_address(netrec['bridge']) and NETSRS:\n for sr in NETSRS:\n # Check if the destination is live for a maximum of 2 minutes and a half,\n # and if it goes live replug the target SRs\n (sr_uuid, pingTarget), = sr.items()\n p = Ping(pingTarget, 5000)\n if p.live(30):\n plug_pbds(x, sr_uuid)\n\n except (socket.error, XmlRPCFault):\n # Toolstack restarted/unavailable or SIGTERM'd\n pass","def tcp_ping_nodes(self, timeout=20.0):\n for node in self.all_instances:\n if node.instance_type in [\n InstanceType.RESILIENT_SINGLE,\n InstanceType.SINGLE,\n InstanceType.DBSERVER,\n ]:\n node.check_version_request(timeout)","def available(self):\n from pyhs3 import STATE_LISTENING\n return self._connection.api.state == STATE_LISTENING","def wait_for_exec_to_start():\n node_instances = self.client.node_instances.list()\n for ni in node_instances:\n # this will keyerror out (and be retried) if the operation\n # didn't run yet\n pids[ni.node_id] = ni.runtime_properties['pid']","def check_avalaible_proxys(proxys):\n socket.setdefaulttimeout(30)\n\n print(bcolors.WARNING + \"[-] Testing Proxy List...\\n\" + bcolors.ENDC)\n\n max_thread = THREAD\n\n queue = Queue.Queue()\n queuelock = threading.Lock()\n threads = []\n\n for proxy in proxys:\n queue.put(proxy)\n\n while not queue.empty():\n queuelock.acquire()\n for workers in range(max_thread):\n t = threading.Thread(target=check_proxy, args=(queue,))\n t.setDaemon(True)\n t.start()\n threads.append(t)\n for t in threads:\n t.join()\n queuelock.release()\n\n print(bcolors.OKGREEN + \"[+] Online Proxy: \" + bcolors.BOLD + str(len(proxys_working_list)) + bcolors.ENDC + \"\\n\")\n\n if len(proxys_working_list) == 0:\n print (\"No proxies loaded! Check your proxy file. Exiting...\")\n sys.exit(1)","def running(self):\n\n return can_connect_to(APIConsumer.host, APIConsumer.port)","def waiting_clients(self):\n return self.storage.iterkeys()","def check(self):\n if self.backend.poll():\n raise RuntimeError('Backend process died.')\n\n if self.esp.poll():\n raise RuntimeError('ESP process died.')","def _check_publishers_connection(self):\n \n rate = rospy.Rate(10) # 10hz; HOW DOES THIS WORK FOR CATVEHICLE/\n \n self._check_cmd_vel_pub()\n\n rospy.logdebug(\"All Publishers READY\")","def _detect(self):\n if (monasca_setup.detection.find_process_name('nova-api') is not None and\n os.path.isfile(nova_conf)):\n self.available = True","def available(self) -> bool:\n return self.thermostat[\"runtime\"][\"connected\"]","async def check_status(self):\n while True:\n async with self._loop_lock:\n new_monitor_processes = {}\n for class_name in self.monitor_processes:\n monitor = self.monitor_processes[class_name][\"process\"]\n if monitor.poll() is not None:\n log = f\"Monitor {class_name} has stopped with code: {monitor.returncode}\"\n if monitor.returncode:\n self.general_logger.warning(log)\n if self.config[\"WebhookConfig\"][\"crash_webhook\"]:\n embed = get_mm_crash_embed(\n \"Monitor \" + class_name,\n monitor.returncode,\n monitor.pid,\n )\n ts = datetime.now().strftime(\n self.config[\"WebhookConfig\"][\"timestamp_format\"]\n )\n\n embed.set_footer(\n text=f\"{self.config['WebhookConfig']['provider']} | {ts}\",\n icon_url=self.config[\"WebhookConfig\"][\n \"provider_icon\"\n ],\n )\n data = json.dumps(\n {\n \"embeds\": [embed.to_dict()],\n \"username\": \"MonitorManager process watcher\",\n \"avatar_url\": self.config[\"WebhookConfig\"][\n \"provider_icon\"\n ],\n }\n )\n r = await self.client.fetch(\n self.config[\"WebhookConfig\"][\"crash_webhook\"],\n method=\"POST\",\n body=data,\n headers={\"content-type\": \"application/json\"},\n raise_error=False,\n )\n else:\n self.general_logger.info(log)\n else:\n new_monitor_processes[class_name] = self.monitor_processes[\n class_name\n ]\n self.monitor_processes = new_monitor_processes\n\n new_scraper_processes = {}\n for class_name in self.scraper_processes:\n scraper = self.scraper_processes[class_name][\"process\"]\n if scraper.poll() is not None:\n log = f\"Scraper {class_name} has stopped with code: {scraper.returncode}\"\n if scraper.returncode:\n self.general_logger.warning(log)\n if self.config[\"WebhookConfig\"][\"crash_webhook\"]:\n embed = get_mm_crash_embed(\n \"Scraper \" + class_name,\n scraper.returncode,\n scraper.pid,\n )\n ts = datetime.now().strftime(\n self.config[\"WebhookConfig\"][\"timestamp_format\"]\n )\n\n embed.set_footer(\n text=f\"{self.config['WebhookConfig']['provider']} | {ts}\",\n icon_url=self.config[\"WebhookConfig\"][\n \"provider_icon\"\n ],\n )\n data = json.dumps(\n {\n \"embeds\": [embed.to_dict()],\n \"username\": \"MonitorManager process watcher\",\n \"avatar_url\": self.config[\"WebhookConfig\"][\n \"provider_icon\"\n ],\n }\n )\n r = await self.client.fetch(\n self.config[\"WebhookConfig\"][\"crash_webhook\"],\n method=\"POST\",\n body=data,\n headers={\"content-type\": \"application/json\"},\n raise_error=False,\n )\n else:\n self.general_logger.info(log)\n else:\n new_scraper_processes[class_name] = self.scraper_processes[\n class_name\n ]\n self.scraper_processes = new_scraper_processes\n await asyncio.sleep(1)","def _check_publishers_connection(self):\n rate = rospy.Rate(10) # 1hz\n while self._vel_pub.get_num_connections() == 0 and not rospy.is_shutdown():\n rospy.logdebug(\"No susbribers to _vel_pub yet so we wait and try again\")\n try:\n rate.sleep()\n except rospy.ROSInterruptException:\n # This is to avoid error when world is rested, time when backwards.\n pass\n rospy.logdebug(\"_vel_pub Publisher Connected\")\n\n rospy.logdebug(\"All Publishers READY\")","def wsdiscovery() -> list[Service]:\n discovery = WSDiscovery(ttl=4)\n try:\n discovery.start()\n return discovery.searchServices(\n scopes=[Scope(\"onvif://www.onvif.org/Profile/Streaming\")]\n )\n finally:\n discovery.stop()\n # Stop the threads started by WSDiscovery since otherwise there is a leak.\n discovery._stopThreads() # pylint: disable=protected-access","def get_subscribers():\n # TODO: make calls to each device asynchronous so we don't block\n # trying to read from an unresponsive device on start up.\n PortList = serial.tools.list_ports.comports()\n manager.executor = ThreadPoolExecutor(max_workers=len(PortList))\n for port in PortList:\n if port.device in IGNORE_LIST:\n continue\n log.info('Found {}'.format(port.device))\n ser = serial.Serial(port.device, baudrate=115200)\n looping = True\n while looping:\n b = pyvesc.encode(pyvesc.ReqSubscription('t'))\n ser.reset_input_buffer()\n ser.write(b)\n l = ser.read()\n if l == b'\\x02' or l == b'\\x03':\n # It's a VESC message!\n looping = not init_vesc_driver(port, ser, l)\n else:\n # It's a JSON message!\n looping = not init_json_driver(port, ser, l)","def is_available():","def __some_alive(self):\n for service in self.__services.values():\n if service.is_alive():\n return True\n return False","def get_polling_service_instances_10(self):\n poll_instances = []\n poll_services = PollService.objects.filter(data_collections=self, enabled=True)\n for poll_service in poll_services:\n message_bindings = [mb.binding_id for mb in poll_service.supported_message_bindings.all()]\n for supported_protocol_binding in poll_service.supported_protocol_bindings.all():\n poll_instance = tm10.PollingServiceInstance(supported_protocol_binding.binding_id,\n poll_service.build_service_address(supported_protocol_binding.binding_id),\n message_bindings)\n poll_instances.append(poll_instance)\n\n return poll_instances","def checkonly(self):\n OTHER_WSREP.append(socket.gethostbyname(socket.gethostname()))\n for hostitem in ALL_NODES:\n checkhost(hostitem)\n if OTHER_WSREP:\n for wsrepitem in OTHER_WSREP:\n REMAINING_NODES.append(wsrepitem)\n if REMAINING_NODES:\n for wsrephost in OTHER_WSREP:\n checkwsrep(wsrephost)\n print ''","def _check_coms(self):\n self.com._check_rep()","def _update_info(self):\n with self.lock:\n _LOGGER.info('Checking wireless clients')\n\n self.last_results = []\n\n active_clients = self.get_ddwrt_data()\n\n if not active_clients:\n return False\n\n self.last_results.extend(active_clients)\n\n return True","def __check_image_handlers(self):\n active_workers = []\n for w in self.__image_handlers:\n if w.is_alive():\n active_workers.append(w)\n self.__image_handlers = active_workers\n\n if len(self.__video_modules) > len(self.__image_handlers):\n new_t = threading.Thread(target=self.__image_request_handler)\n new_t.start()\n self.__image_handlers.append(new_t)","def check_publishers_connection(self):\n rate = rospy.Rate(10) # 10hz\n while (self._cart_velocity_publisher.get_num_connections() == 0 and not rospy.is_shutdown()):\n rospy.logdebug(\"No susbribers to _cart_velocity_publisher yet so we wait and try again\")\n try:\n rate.sleep()\n except rospy.ROSInterruptException:\n # This is to avoid error when world is rested, time when backwards.\n pass\n rospy.logdebug(\"_base_pub Publisher Connected\")\n\n rospy.logdebug(\"All Publishers READY\")","def check_server(self, timeout=1):\n ans = None\n end_time = time.time() + timeout\n while time.time() <= end_time:\n try:\n ans = self.xmlproxy.ping()\n except socket_error:\n time.sleep(1)\n except Exception as err:\n self.class_logger.warning(\"Unexpected type of error while checking xmlrpc server - {0} - {1}\".format(type(err), err))\n time.sleep(1)\n else:\n if ans == \"XMLReportingServer\":\n return True\n else:\n message = \"Unknown xmlrpc server is running on localhost:18080\"\n self.class_logger.error(message)\n raise Exception(message)\n return False","def clients(self):\n items = []\n for elem in self.query('/clients'):\n baseurl = 'http://%s:%s' % (elem.attrib['address'],\n elem.attrib['port'])\n items.append(PlexClient(baseurl, server=self, data=elem))\n return items","def check_guest_applications(self):\n apps = None\n testflow.step(\"Check if guest agent is reporting applications\")\n for sample in TimeoutingSampler(\n config.SAMPLER_TIMEOUT, config.SAMPLER_SLEEP,\n ll_vms.get_vm, self.vm_name\n ):\n apps = ll_vms.get_vm_applications(sample.get_name())\n if len(apps) > 0:\n break\n logger.info(\"Windows '%s' apps are: %s\", self.disk_name, apps)\n for app in apps:\n testflow.step(\"Check if app %s is reporting version\", app)\n try:\n re.search(\"[ -]\\d+.*\", app).group(0)[1:]\n except AttributeError:\n logger.error(\"App %s is not reporting version\", app)","def get_pending_instances(self):\n return [instance for instance in self.instances.itervalues()\n if InstanceState.REQUESTED <= instance.state < InstanceState.RUNNING]","def detect_instance_pids(self):\n for instance in self.all_instances:\n instance.detect_pid(\n ppid=self.instance.pid,\n full_binary_path=self.cfg.real_sbin_dir,\n offset=0,\n )\n\n self.show_all_instances()\n self.detect_arangosh_instances(self.cfg, self.cfg.version)","def detect_used_ports():\n MAX_PORT = 1025\n DEFAULT_HOST = '127.0.0.1'\n open_ports = []\n socket.setdefaulttimeout(1)\n for port in range(0, MAX_PORT):\n res = port_scan(DEFAULT_HOST, port)\n if res:\n open_ports.append(port)\n # debugging purpose to see if program is running\n if port % 5000 == 0 and port != 0:\n sys.stderr.write('.')\n return open_ports","def _check_sources(self):\n avail_sources = []\n for source in self.__video_sources:\n avail_sources.append(source)\n\n # Try to start each video source known. Naovideo is not in this list,\n # because without an explicit request, no IP and port is known so no\n # connection can be made.\n for source in [\"webcam\", \"kinect\"]:\n if source in avail_sources:\n continue\n\n # Status unknown, try to start and stop\n self.__logger.info(\"Trying to see if source %s is available\" % source)\n try:\n if self._start_video_source(source):\n avail_sources.append(source)\n self._stop_video_source(source)\n except Exception, e:\n self.__logger.info(\"Error starting source %s, (error: %s) must not be available\" % (source, str(e)))\n \n return avail_sources","def known_nodes(self) -> List[Client]:\n return list(self.in_memory_client_registry.values())","def get_active_clients():\n global drivers\n\n if not drivers:\n return jsonify([])\n\n result = {client: get_client_info(client) for client in drivers}\n return jsonify(result)","def getActiveProcesses():\n active = []\n\n for p in PROCESSRUNNER_PROCESSES:\n if p.is_alive():\n active.append(p)\n\n return active","def instances_used(self):\n return None","def get_running_pris(self):\n try:\n running_pris_list = []\n output = self.ssh.exec_command(self.check_running_kombu_dialer_command)\n for line in output[1].readlines():\n line = line.split()\n if self.server in line and \"-g\" in line:\n running_pris_list.append(\n int(\n line[line.index(\"-g\")+1][2:]\n )\n )\n return running_pris_list\n except Exception as err:\n self.error_logger.error(err.message + \" PRITester::get_running_pris\")\n return None","def wait_for_cadvisor_up(self):\n ping = None\n while ping is None:\n ping = requests.get(self._url_prefix, timeout=CONNECTION_TIMEOUT)\n if ping is None:\n logger.debug(\"Unable to connect to cadvisor %s. Will sleep for %s sec\",\n self._url_prefix, CHECK_LIVELINESS_INTERVAL)\n time.sleep(CHECK_LIVELINESS_INTERVAL)\n logger.info(\"cAdvisor client is up for endpoint %s\", self._url_prefix)","def _check_endpoints_last_communication(self):\n while self._thread_running:\n endpoints = EndpointService.get_all_endpoints()\n for endpoint in endpoints:\n if datetime.now() - endpoint.lastCommunication > timedelta(minutes=TOKEN_EXPIRE_TIME):\n EventService.add_event(Event(\"0\", \"Lost Endpoint At \" +\n str(endpoint[EndpointKeys.LAST_COMMUNICATION_KEY]),\n \"Report\", \"IDLE\", endpoint[EndpointKeys.HOSTNAME_KEY],\n endpoint[EndpointKeys.IP_ADDRESS_KEY]))\n EndpointService.delete_endpoint(endpoint.id)\n sleep(SLEEP_TIME)","async def async_scan_devices(self):\n await self.async_update_info()\n return list(self.last_results.keys())","def test_all_workers_are_active_processes(self):\n WORKERS_COUNT = 10\n\n # Testing only ProcessPool since only it has the mechanism that waits for all workers to come online before\n # start finishes\n pool = ProcessPool(WORKERS_COUNT)\n\n pool.start(WorkerIdGeneratingWorker)\n for _ in range(100):\n pool.ventilate()\n\n active_worker_ids = [pool.get_results() for _ in range(100)]\n self.assertEqual(set(range(WORKERS_COUNT)), set(active_worker_ids))\n\n pool.stop()\n pool.join()","def check_pool(self):\n if self.conn.queue_len() < MAX_PROXIES:\n return True\n return False","def basic_overcloud_processes_running(self):\n for attempt_number in range(600):\n\n try:\n\n for process_name in self.processes_to_check:\n # osp16/python3 process is \"neutron-server:\"\n if process_name == 'neutron-server' and \\\n self.oc_procs_df.query('PROCESS==\"{}\"'.format(\n process_name)).empty:\n process_name = 'neutron-server:'\n # osp17 mysqld process name is mysqld_safe\n if process_name == 'mysqld' and \\\n self.oc_procs_df.query('PROCESS==\"{}\"'.format(\n process_name)).empty:\n process_name = 'mysqld_safe'\n # redis not deployed on osp17 by default, only if some\n # other services such as designate and octavia are deployed\n if (process_name == 'redis-server' and\n not overcloud.is_redis_expected()):\n redis_message = (\"redis-server not expected on OSP 17 \"\n \"and later releases by default\")\n if self.oc_procs_df.query(\n f'PROCESS==\"{process_name}\"').empty:\n LOG.info(redis_message)\n continue\n else:\n raise OvercloudProcessesException(\n process_error=redis_message)\n\n if not self.oc_procs_df.query('PROCESS==\"{}\"'.format(\n process_name)).empty:\n LOG.info(\"overcloud processes status checks: \"\n \"process {} is \"\n \"in running state\".format(process_name))\n continue\n else:\n LOG.info(\"Failure : overcloud processes status checks:\"\n \"process {} is not running \".format(\n process_name))\n raise OvercloudProcessesException(\n process_error=\"process {} is not running \".format(\n process_name))\n # if all procs are running we can return true\n return True\n except OvercloudProcessesException:\n LOG.info('Retrying overcloud processes checks attempt '\n '{} of 360'.format(attempt_number))\n time.sleep(1)\n self.oc_procs_df = overcloud.get_overcloud_nodes_dataframe(\n get_overcloud_node_processes_table)\n # exhausted all retries\n tobiko.fail('Not all overcloud processes are running !\\n')","def owserver_running():\n for proc in psutil.process_iter():\n if 'owserver' in proc.name():\n return True\n return False","def get_instances() -> dict:\n url = f\"{app.config['COMPUTE_SERVERS_REF']}/detail\"\n instances_rq = request(\n method=\"GET\", url=url, headers=build_header(), params={\"vm_state\": \"active\"},\n )\n\n if not instances_rq.ok:\n HTTPError(instances_rq.status_code)\n\n answer = {\"servers\": list()}\n for instance in instances_rq.json()[\"servers\"]:\n instance_info = dict(name=instance[\"name\"])\n instance_info[\"ip_addresses\"] = list()\n for network, info in instance[\"addresses\"].items():\n instance_info[\"ip_addresses\"].extend(entry[\"addr\"] for entry in info)\n answer[\"servers\"].append(instance_info)\n\n return answer","def available(self):\n if self._available is None:\n try:\n global xpress\n import xpress\n\n # Always disable the global output. We only want output if\n # we install callbacks explicitly\n xpress.setOutputEnabled(False)\n self._available = True\n except:\n self._available = False\n return self._available","def get_vrps(self):\n self.info(\"Trying to get new VRP data from agent\")\n for i in range(3):\n time.sleep(1)\n if self.conn.poll():\n self.vrps = self.conn.recv()\n self.info(\"Got data on try {}\".format(i))\n return True\n self.info(\"Nothing to receive on try {}\".format(i))\n self.warning(\"No data received from agent\")\n return False","def startListening(self):\n mgr = self.cxn.manager\n # example of Signal processing:\n # server = self.cxn[self.selectedADR]\n # update_state = lambda c, payload: self.updateInterface()\n # yield server.signal_state_changed(self.ID)\n # yield server.addListener(listener = update_state, source=None,ID=self.ID)\n\n # state update (only if the message is from the correct ADR server)\n update_state = lambda c, (s,payload): self.updateInterface() \\\n if self.correctServer(s) else -1\n self.cxn._cxn.addListener(update_state, source=mgr.ID, ID=101)\n yield mgr.subscribe_to_named_message('State Changed', 101, True)\n # log update\n update_log = lambda c, (s,(t,m,a)): self.updateLog(t,m,a) \\\n if self.correctServer(s) else -1\n self.cxn._cxn.addListener(update_log, source=mgr.ID, ID=102)\n yield mgr.subscribe_to_named_message('Log Changed', 102, True)\n # magging up stopped\n mag_stop = lambda c, (s,payload): self.magUpStopped() \\\n if self.correctServer(s) else -1\n self.cxn._cxn.addListener(mag_stop, source=mgr.ID, ID=103)\n yield mgr.subscribe_to_named_message('MagUp Stopped', 103, True)\n # regulation stopped\n reg_stop = lambda c, (s,payload): self.regulationStopped() \\\n if self.correctServer(s) else -1\n self.cxn._cxn.addListener(reg_stop, source=mgr.ID, ID=104)\n yield mgr.subscribe_to_named_message('Regulation Stopped', 104, True)\n # magging up started\n mag_start = lambda c, (s,payload): self.magUpStarted() \\\n if self.correctServer(s) else -1\n self.cxn._cxn.addListener(mag_start, source=mgr.ID, ID=105)\n yield mgr.subscribe_to_named_message('MagUp Started', 105, True)\n # regulation started\n reg_start = lambda c, (s,payload): self.regulationStarted() \\\n if self.correctServer(s) else -1\n self.cxn._cxn.addListener(reg_start, source=mgr.ID, ID=106)\n yield mgr.subscribe_to_named_message('Regulation Started', 106, True)\n # servers starting and stopping\n serv_conn_func = lambda c, (sID, sName): self.serverChanged(sName)\n serv_disconn_func = lambda c, (sID, sName): self.serverChanged(sName)\n self.cxn._cxn.addListener(serv_conn_func, source=mgr.ID, ID=107)\n self.cxn._cxn.addListener(serv_disconn_func, source=mgr.ID, ID=108)\n yield mgr.subscribe_to_named_message('Server Connect', 107, True)\n yield mgr.subscribe_to_named_message('Server Disconnect', 108, True)","def create_clients():\n clients = {}\n\n rospy.loginfo(\"Waiting for rubble detector\")\n clients['rubble_detect'] = actionlib.SimpleActionClient('rubble_detect',\n RubbleDetectAction)\n\n rospy.loginfo(\"Waiting for rubble checker\")\n clients['rubble_check'] = actionlib.SimpleActionClient('rubble_check',\n RubbleCheckAction)\n clients['rubble_check'].wait_for_server()\n rospy.loginfo(\"rubble_check connected\")\n\n rospy.loginfo(\"Waiting for room searcher\")\n clients['search_room'] = actionlib.SimpleActionClient('search_room',\n SearchRoomAction)\n clients['search_room'].wait_for_server()\n rospy.loginfo(\"search_room connected\")\n\n rospy.loginfo(\"Waiting for navigator\")\n clients['navigation'] = actionlib.SimpleActionClient('navigation',\n NavigateAction)\n clients['navigation'].wait_for_server()\n rospy.loginfo(\"navigation connected\")\n\n rospy.loginfo(\"Waiting for door clearer\")\n clients['rubble_clear'] = actionlib.SimpleActionClient('rubble_clear',\n RubbleClearAction)\n clients['rubble_clear'].wait_for_server()\n rospy.loginfo(\"rubble clear connected\")\n\n rospy.loginfo(\"All clients for policy executor set up\")\n\n return clients","def run(self):\n for req, resp in self.servings:\n resp.check_timeout()","def active_failover_detect_hosts(self):\n self.check_that_instance_is_alive()\n # this is the way to detect the master starter...\n lfs = self.get_log_file()\n if lfs.find(\"Just became master\") >= 0:\n self.is_master = True\n else:\n self.is_master = False\n regx = re.compile(r\"Starting resilientsingle on port (\\d*) .*\")\n match = regx.search(lfs)\n if match is None:\n raise Exception(timestamp() + \"Unable to get my host state! \" + self.basedir + \" - \" + lfs)\n\n self.frontend_port = match.groups()[0]","def urlvoid_check(name, api_key):\n if not is_fqdn(name):\n return None\n\n url = 'http://api.urlvoid.com/api1000/{key}/host/{name}'.format(key=api_key, name=name)\n response = requests.get(url)\n tree = ET.fromstring(response.text)\n if tree.find('./detections/engines'):\n return [e.text for e in tree.find('./detections/engines')]\n else:\n return None","def issuer_liveness_check():\n global app_config\n\n if app_config[\"running\"]:\n # return True until we get a shutdown request\n return True\n\n # return True until the work queue is cleared\n return tob_connection_active()","def _wait(self):\n conn = None\n try:\n conn = libvirt.open(\"qemu:///system\")\n while True:\n time.sleep(10)\n try:\n state = conn.lookupByName(self.domain).info()[0]\n except (libvirt.libvirtError, TypeError, IndexError):\n break\n if state in [4, 5, 6]: # crashed or shutdown\n break\n finally:\n if conn is not None:\n conn.close()","def wait_proc(self, proc_pattern, max_retry=3):\n check_cmd = \"pgrep -f '%s'\" % proc_pattern\n fip_lst = self._get_ins_fips()\n ssh_clt = paramiko.SSHClient()\n ssh_clt.set_missing_host_key_policy(paramiko.AutoAddPolicy())\n\n for srv_grp, fip_grp in zip(self.srv_grp_lst, fip_lst):\n for srv, fip in zip(srv_grp, fip_grp):\n retry = 0\n while retry <= max_retry:\n try:\n ssh_clt.connect(fip, 22, srv['ssh']['user_name'],\n key_filename=srv['ssh']['pvt_key_file'])\n except Exception:\n logger.warn(\n '[FIP:%s] Can not connect to instance, try again after 3 seconds'\n % fip\n )\n time.sleep(3)\n retry += 1\n else:\n break\n else:\n ssh_clt.close()\n raise ServerChainError(\n '[FIP:%s] Can not connect to instance via SSH' % fip)\n\n trans = ssh_clt.get_transport()\n retry = 0\n while retry <= max_retry:\n channel = trans.open_session()\n channel.exec_command(check_cmd)\n status = channel.recv_exit_status()\n if status == 0:\n break\n else:\n logger.warn(\n '[FIP:%s] Process is not running, recheck after 10 seconds.'\n % fip\n )\n time.sleep(10)\n retry += 1\n else:\n ssh_clt.close()\n raise ServerChainError(\n '[FIP:%s] SF Process is not running' % fip)\n\n ssh_clt.close()","def verify_services(self):\n services = [\"metric_collector\", \"log_collector\"]\n service_version_9 = [\"lma_collector\"]\n pids = {}\n processes_count = {\n \"collectd \": 1,\n \"collectdmon \": 1\n }\n\n if self.settings.version.startswith(\"0.9\"):\n processes_count[\n \"hekad -config[= ]/etc/{}\".format(service_version_9)] = 1\n else:\n # Starting with 0.10, there are one collector for logs and one for\n # metrics\n for service in services:\n processes_count[\"hekad -config[= ]/etc/{}\".format(service)] = 1\n online_nodes = [node for node in self.helpers.get_all_ready_nodes()\n if node[\"online\"]]\n for node in online_nodes:\n pids[node[\"name\"]] = {}\n with self.env.d_env.get_ssh_to_remote(node[\"ip\"]) as remote:\n for process, count in processes_count.items():\n logger.info(\"Checking process {0} on node {1}\".format(\n process, node[\"name\"]\n ))\n pids[node[\"name\"]][process] = (\n self.checkers.check_process_count(\n remote, process, count))\n return pids","def isListening(self):\n if not self.proxy:\n self.proxy = self.session.service(\"ALExpressiveListening\")\n return self.proxy.isListening()","def kafka_consumer_check_instances(self) -> Optional[pulumi.Input[int]]:\n return pulumi.get(self, \"kafka_consumer_check_instances\")","def check_firefox_processes(self):\n mm = MicroManager(self.hostname)\n ff_procs = mm.find_processes_by_name(\"firefox\")\n if len(ff_procs) > 2:\n return [CheckStatus(self, CheckStatus.CHECK_FIREFOX_PROCESS_COUNT, CheckStatus.STATUS_FAIL, \"There are {} firefox processes running\".format(len(ff_procs))), ]\n else:\n return [CheckStatus(self, CheckStatus.CHECK_FIREFOX_PROCESS_COUNT, CheckStatus.STATUS_PASS), ]","def poll():\n try:\n self.connect(VAULT_TOKEN).sys.list_enabled_audit_devices()\n return True\n except hvac.exceptions.InternalServerError as ex:\n if str(ex).startswith('local node not active but active cluster node not found'):\n return False\n raise","def check_availability(self):\n pass","async def _async_has_devices(opp: OpenPeerPower) -> bool:\n # TODO Check if there are any devices that can be discovered in the network.\n devices = await opp.async_add_executor_job(my_pypi_dependency.discover)\n return len(devices) > 0","async def test_web_access(registered_devices: List[Device], max_parallel_connections:int = 30) -> List[Device]:\n\n session = aiohttp.ClientSession()\n registered_devices_after_checks = []\n\n test_connection_tasks = (is_web_enabled(session, device) for device in registered_devices)\n\n while True:\n parallel_tasks = list(islice(test_connection_tasks, max_parallel_connections))\n if not parallel_tasks:\n break\n\n done, pending = await asyncio.wait(parallel_tasks, loop=loop)\n\n for task in done:\n registered_devices_after_checks.append(task.result())\n\n session.close()\n\n return registered_devices_after_checks","def _detect(self):\n if monasca_setup.detection.find_process_cmdline('rabbitmq-server') is not None:\n self.available = True","def proxy_scrape(self):\n print(\"Getting new live proxies\")\n url = 'https://free-proxy-list.net/'\n response = requests.get(url)\n parser = fromstring(response.text)\n proxies = set()\n for i in parser.xpath('//tbody/tr')[:20]:\n # if i.xpath('.//td[7][contains(text(),\"yes\")]'):\n proxy = \":\".join([i.xpath('.//td[1]/text()')\n [0], i.xpath('.//td[2]/text()')[0]])\n proxies.add(proxy)\n # return proxies\n # proxies=[]\n print(\"Obtained proxied are as : \", proxies)\n proxy_pool = cycle(proxies)\n proxy_list = [proxy for proxy in proxies]\n return proxy_pool, proxy_list","def gotConnectionWithServices(timeout):\n\n try:\n rospy.wait_for_service('fluid/take_off', timeout=timeout)\n rospy.wait_for_service('fluid/explore', timeout=timeout)\n rospy.wait_for_service('fluid/travel', timeout=timeout)\n rospy.wait_for_service('fluid/land', timeout=timeout)\n rospy.wait_for_service('fluid/interact', timeout=timeout)\n return True\n except rospy.ROSException:\n return False","def disable_discovery(self):","def instances(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['BrokerInstanceArgs']]]]:\n return pulumi.get(self, \"instances\")","def wait_for_ready(self, instance_id, limit, delay=1, pending=False):\r\n for count, new_instance in enumerate(repeat(instance_id), start=1):\r\n instance = self.get_instance(new_instance)\r\n last_reload = lookup(instance, 'lastOperatingSystemReload', 'id')\r\n active_transaction = lookup(instance, 'activeTransaction', 'id')\r\n\r\n reloading = all((\r\n active_transaction,\r\n last_reload,\r\n last_reload == active_transaction\r\n ))\r\n\r\n # only check for outstanding transactions if requested\r\n outstanding = False\r\n if pending:\r\n outstanding = active_transaction\r\n\r\n # return True if the instance has only if the instance has\r\n # finished provisioning and isn't currently reloading the OS.\r\n if instance.get('provisionDate') \\\r\n and not reloading and not outstanding:\r\n return True\r\n\r\n if count >= limit:\r\n return False\r\n\r\n sleep(delay)","def get_registered_clients(self):\n return self.hub.get_registered_clients(self.get_private_key())","def check_eapi(self, eapi):\n\t\treturn True","def poll(cls, context):\r\n return hasattr(bpy.types.Object, \"BlenderNEURON_node\") and \\\r\n bpy.types.Object.BlenderNEURON_node is not None and \\\r\n bpy.types.Object.BlenderNEURON_node.client is not None","def poll(cls, context):\r\n return hasattr(bpy.types.Object, \"BlenderNEURON_node\") and \\\r\n bpy.types.Object.BlenderNEURON_node is not None and \\\r\n bpy.types.Object.BlenderNEURON_node.client is not None","def is_call_waiting(self) -> bool:","def wait_on_elb_instance ( elb_conn, elb_name, elb_instance_id, elb_state = 'InService', sleep_time = 10, max_wait = 300 ) :\n instance_states = elb_conn.describe_instance_health( load_balancer_name = elb_name,\n instances = [ elb_instance_id ] )\n instance_state = instance_states[ 0 ].state\n while instance_state != elb_state :\n if max_wait <= 0 :\n break\n time.sleep( sleep_time )\n max_wait -= sleep_time\n instance_states = elb_conn.describe_instance_health( load_balancer_name = elb_name,\n instances = [ elb_instance_id ] )\n instance_state = instance_states[ 0 ].state\n\n return instance_state == elb_state","async def request(self) -> set[LcnAddr]:\n await self.addr_conn.conn.segment_scan_completed_event.wait()\n self.groups_known.clear()\n self.trh.activate()\n await self.groups_known.wait()\n return self.groups","async def request(self) -> set[LcnAddr]:\n await self.addr_conn.conn.segment_scan_completed_event.wait()\n self.groups_known.clear()\n self.trh.activate()\n await self.groups_known.wait()\n return self.groups","def run(self):\n run = True\n while run:\n statuses = self.check_status()\n unhealthy = [ups for ups in statuses.keys() if not statuses[ups]]\n drivers_to_bounce = set()\n for ups in unhealthy:\n driver = self.ups_confs[ups].get('driver', 'usbhid-ups')\n drivers_to_bounce.add(driver)\n if drivers_to_bounce:\n self.bounce_drivers(drivers_to_bounce)\n time.sleep(self.monitor_cycle/1000)","def wait_for_version_reply(self):\n frontends = self.get_frontends()\n for frontend in frontends:\n # we abuse this function:\n while frontend.get_afo_state() != AfoServerState.LEADER:\n progress(\".\")\n time.sleep(0.1)","def _find_xinput(self):\n for dll in XINPUT_DLL_NAMES:\n try:\n self.xinput = getattr(ctypes.windll, dll)\n except OSError:\n pass\n else:\n # We found an xinput driver\n self.xinput_dll = dll\n break\n else:\n # We didn't find an xinput library\n warn(\n \"No xinput driver dll found, gamepads not supported.\",\n RuntimeWarning)","def instances_created(self):\n with _MonitorEnv._lock:\n return self._instances_created","def test_evrpnl_instances(self) -> bool:\n\n for rte_info in self.results.values():\n frvcp_solver = solver.Solver(\n self.ref_instance, rte_info['route'], self.q_init)\n obj, _ = frvcp_solver.solve()\n self.assertAlmostEqual(obj, rte_info['obj'], 3)","def _get_dependencies():\n return config.check_driver_dependencies(__virtualname__, {\"XenAPI\": HAS_XEN_API})","def isThereApiCalls(report):\n with open(report, \"rb\") as r:\n data = json.load(r)\n for i in range(numProcs(report)):\n if len(data[\"behavior\"][\"processes\"][i][\"calls\"]) > 0:\n return True\n else:\n continue\n return False","def instances(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['InstanceStatusArgs']]]]:\n return pulumi.get(self, \"instances\")","def _loadchildren():\n return [\n [PingAPI, {}, None],\n ]","def get_candidates(self, cloud_name, jobs, count, return_only_all_idle=False):\n\n asg_info = self.phantom_client.get_autoscale_groups_info(self.phantom_client.asg.name)\n all_instances_info = asg_info[self.phantom_client.asg.name]['instances']\n instances = self.phantom_client.get_alive_instnaces(all_instances_info)\n\n localjobs = copy.copy(jobs)\n\n idle_list = []\n nonidle_list = []\n for instance in instances:\n if instances[instance]['cloud_name'] != cloud_name:\n continue\n job_matching_found = False\n for job in localjobs.list:\n if instances[instance]['public_dns'] == job.node:\n #nonidle_list.append( (instance, job.running, instances[instance]) )\n nonidle_list.append( (instance, job.progress, instances[instance]) )\n\n localjobs.list.remove(job)\n job_matching_found = True\n break\n if not job_matching_found:\n idle_list.append( (instance, instances[instance]) )\n\n # Truncate idle list if needed (in case there are more idle instances than count)\n # Does not do anything if count >= len(idle_list)\n\n if return_only_all_idle:\n # DONE if this flag is set\n return idle_list\n\n idle_list = idle_list[:count]\n\n if idle_list:\n idle_list_str = \"\"\n for instance in idle_list:\n idle_list_str += \"%s:%s,\" % (instance[0], instance[1]['public_dns'])\n LOG.info(\"OO found idle candidates for termination in %s: %s\" % (cloud_name, idle_list_str))\n\n # Sort by the run time in the decreasing order\n sorted_nonidle_list = sorted(nonidle_list, key=operator.itemgetter(1), reverse=True)\n\n remaining_count = count - len(idle_list)\n # Truncate sorted non-idle list if needed (in case remaining_count < len(sorted_nonidle_list))\n sorted_nonidle_list = sorted_nonidle_list[:remaining_count]\n\n sorted_nonidle_list_instances_only = []\n if sorted_nonidle_list:\n nonidle_list_str = \"\"\n for atuple in sorted_nonidle_list:\n nonidle_list_str += \"%s:%s:%s,\" % (atuple[0], atuple[2]['public_dns'], atuple[1])\n sorted_nonidle_list_instances_only.append((atuple[0], atuple[2] ))\n LOG.info(\"OO found non-idle candidates for termination in %s: %s\" % (cloud_name, nonidle_list_str))\n\n total_found = len(idle_list)+len(sorted_nonidle_list_instances_only)\n if not total_found == count:\n LOG.info(\"OO can't supply enough (%d) instances for termination. Found only %d\", count, total_found)\n\n return idle_list, sorted_nonidle_list_instances_only"],"string":"[\n \"def _wait_active(client, request_id, max_num):\\n logging.info('Waiting for instances to be active')\\n while True:\\n res = client.describe_spot_fleet_instances(SpotFleetRequestId=request_id)\\n if len(res['ActiveInstances']) == max_num:\\n logging.info('Instances are active now.')\\n instance_id_list = [ i['InstanceId'] for i in res['ActiveInstances'] ]\\n return instance_id_list\\n time.sleep(10)\",\n \"def wait_for_instances(self) -> pulumi.Output[Optional[bool]]:\\n return pulumi.get(self, \\\"wait_for_instances\\\")\",\n \"async def _check_api(self) -> None:\\n await self._api_request(\\\"devices\\\")\",\n \"def detect_instances(self):\\n lh.subsection(\\\"Instance Detection for {0.name}\\\".format(self))\\n jwt = self.get_jwt_header()\\n self.all_instances = []\\n logging.debug(\\\"waiting for frontend\\\")\\n logfiles = set() # logfiles that can be used for debugging\\n\\n # the more instances we expect to spawn the more patient:\\n tries = 10 * self.expect_instance_count\\n\\n # Wait for forntend to become alive.\\n all_instances_up = False\\n while not all_instances_up and tries:\\n self.all_instances = []\\n detected_instances = []\\n sys.stdout.write(\\\".\\\")\\n sys.stdout.flush()\\n\\n for root, dirs, files in os.walk(self.basedir):\\n for onefile in files:\\n # logging.debug(\\\"f: \\\" + root + os.path.sep + onefile)\\n if onefile.endswith(\\\"log\\\"):\\n logfiles.add(str(Path(root) / onefile))\\n\\n for name in dirs:\\n # logging.debug(\\\"d: \\\" + root + os.path.sep + name)\\n match = None\\n instance_class = None\\n if name.startswith(\\\"sync\\\"):\\n match = re.match(r\\\"(syncmaster|syncworker)(\\\\d*)\\\", name)\\n instance_class = SyncInstance\\n else:\\n match = re.match(\\n r\\\"(agent|coordinator|dbserver|resilientsingle|single)(\\\\d*)\\\",\\n name,\\n )\\n instance_class = ArangodInstance\\n # directory = self.basedir / name\\n if match and len(match.group(2)) > 0:\\n # we may see a `local-slave-*` directory inbetween,\\n # hence we need to choose the current directory not\\n # the starter toplevel dir for this:\\n instance = instance_class(\\n match.group(1),\\n match.group(2),\\n self.cfg.localhost,\\n self.cfg.publicip,\\n Path(root) / name,\\n self.passvoid,\\n self.cfg.ssl,\\n self.cfg.version,\\n self.enterprise,\\n jwt=jwt,\\n )\\n instance.wait_for_logfile(tries)\\n instance.detect_pid(\\n ppid=self.instance.pid,\\n full_binary_path=self.cfg.real_sbin_dir,\\n offset=0,\\n )\\n detected_instances.append(instance.instance_type)\\n self.all_instances.append(instance)\\n\\n print(self.expect_instances)\\n detected_instances.sort()\\n print(detected_instances)\\n attach(str(self.expect_instances), \\\"Expected instances\\\")\\n attach(str(detected_instances), \\\"Detected instances\\\")\\n if (self.expect_instances != detected_instances) or (not self.get_frontends()):\\n tries -= 1\\n time.sleep(5)\\n else:\\n all_instances_up = True\\n\\n if not self.get_frontends():\\n print()\\n logging.error(\\\"STARTER FAILED TO SPAWN ARANGOD\\\")\\n self.show_all_instances()\\n logging.error(\\\"can not continue without frontend instance\\\")\\n logging.error(\\\"please check logs in\\\" + str(self.basedir))\\n for logf in logfiles:\\n logging.debug(logf)\\n message = \\\"if that does not help try to delete: \\\" + str(self.basedir)\\n logging.error(message)\\n raise Exception(message)\\n self.show_all_instances()\",\n \"def _check_awaiting(self):\\r\\n # TODO: check for wait loops\\r\\n for w in list(self._awaiting.values()):\\r\\n self._try_register_platform(w[\\\"instance\\\"], w[\\\"kind\\\"], w[\\\"parent\\\"], w[\\\"wait\\\"], awaiting=True)\",\n \"def detect_instance_pids_still_alive(self):\\n missing_instances = []\\n running_pids = psutil.pids()\\n for instance in self.all_instances:\\n if instance.pid not in running_pids:\\n missing_instances.append(instance)\\n\\n if len(missing_instances) > 0:\\n logging.error(\\n \\\"Not all instances are alive. The following are not running: %s\\\",\\n str(missing_instances),\\n )\\n logging.error(get_process_tree())\\n raise Exception(\\\"instances missing: \\\" + str(missing_instances))\\n instances_table = get_instances_table(self.get_instance_essentials())\\n logging.info(\\\"All arangod instances still running: \\\\n%s\\\", str(instances_table))\\n attach_table(instances_table, \\\"Instances table\\\")\",\n \"def _get_instances_pending_events(self):\\n\\n conn = connect_to_region(REGION, aws_access_key_id=KEY_ID, aws_secret_access_key=ACCESS_KEY)\\n stats = conn.get_all_instance_status()\\n next_token = stats.next_token\\n while next_token != None:\\n next_stats = conn.get_all_instance_status(next_token=next_token)\\n stats.extend(next_stats)\\n next_token = next_stats.next_token\\n ret = []\\n for stat in stats:\\n if stat.events:\\n for event in stat.events:\\n if re.match('^\\\\[Completed\\\\]', event.description):\\n continue\\n ret.append([stat.id, event.code, event.not_before])\\n if len(ret) > 0:\\n instances = get_instances([stat[0] for stat in ret])\\n for stat in ret:\\n stat.insert(1, instances[stat[0]])\\n return ret\",\n \"def wait_for_container():\\n for i in xrange(30):\\n print(\\\"Waiting for service to come up\\\")\\n try:\\n requests.get(URL).raise_for_status()\\n return True\\n except Exception as e:\\n print e\\n sleep(1)\\n\\n return False\",\n \"def get_polling_service_instances_11(self):\\n poll_instances = []\\n poll_services = PollService.objects.filter(data_collections=self, enabled=True)\\n for poll_service in poll_services:\\n message_bindings = [mb.binding_id for mb in poll_service.supported_message_bindings.all()]\\n for supported_protocol_binding in poll_service.supported_protocol_bindings.all():\\n poll_instance = tm11.PollingServiceInstance(supported_protocol_binding.binding_id,\\n poll_service.build_service_address(supported_protocol_binding.binding_id),\\n message_bindings)\\n poll_instances.append(poll_instance)\\n\\n return poll_instances\",\n \"async def async_discovery(hass: HomeAssistant) -> list[dict[str, Any]]:\\n LOGGER.debug(\\\"Starting ONVIF discovery\\\")\\n services = await hass.async_add_executor_job(wsdiscovery)\\n\\n devices = []\\n for service in services:\\n url = urlparse(service.getXAddrs()[0])\\n device = {\\n CONF_DEVICE_ID: None,\\n CONF_NAME: service.getEPR(),\\n CONF_HOST: url.hostname,\\n CONF_PORT: url.port or 80,\\n CONF_HARDWARE: None,\\n }\\n for scope in service.getScopes():\\n scope_str = scope.getValue()\\n if scope_str.lower().startswith(\\\"onvif://www.onvif.org/name\\\"):\\n device[CONF_NAME] = scope_str.split(\\\"/\\\")[-1]\\n if scope_str.lower().startswith(\\\"onvif://www.onvif.org/hardware\\\"):\\n device[CONF_HARDWARE] = scope_str.split(\\\"/\\\")[-1]\\n if scope_str.lower().startswith(\\\"onvif://www.onvif.org/mac\\\"):\\n device[CONF_DEVICE_ID] = scope_str.split(\\\"/\\\")[-1]\\n devices.append(device)\\n\\n return devices\",\n \"def find_connections():\\n # print \\\"External\\\"\\n # print findservices('00:0D:93:19:C8:68')\\n # print findservices('bc:f5:ac:84:81:0c')\\n # print finddevices()\\n # print findservices(gethostaddr())\\n # print gethostclass()\\n print \\\"Your address: \\\", lb.gethostaddr()\\n print lb.finddevicename(lb.gethostaddr())\\n s = lb.socket()\\n #s.bind((\\\"\\\", 0)) # RFCOMM port\\n #s.bind((\\\"\\\", 1)) # RFCOMM port\\n s.bind((\\\"\\\", 2)) # RFCOMM port\\n print \\\"About to listen\\\"\\n s.listen(1)\\n print \\\"About to advertise\\\"\\n lb.advertise(\\\"LightBlueService\\\", s, lb.RFCOMM)\\n print \\\"Advertised at {} and listening on channel {}...\\\".format(s.getsockname()[0], s.getsockname()[1])\\n print \\\"Waiting to accept\\\"\\n # s.setblocking(1)\\n try:\\n conn, addr = s.accept()\\n except KeyboardInterrupt:\\n print \\\"Closing connection due to keyboard intterupt\\\"\\n s.close()\\n raise KeyboardInterrupt\\n # Set timeout for 1 second\\n # s.settimeout(1.0)\\n print \\\"Connected by\\\", addr\\n return conn, addr, s\",\n \"def wait_for_open_ports(self, instance_name=\\\"\\\"):\\n ports = None\\n if instance_name in wellknownports:\\n ports = wellknownports[instance_name]\\n else:\\n elements = self.systemd_name.split(\\\"@\\\")\\n if elements[0] in wellknownports:\\n ports = wellknownports[elements[0]]\\n if ports:\\n ipautil.wait_for_open_ports('localhost', ports,\\n self.api.env.startup_timeout)\",\n \"def ensure_discovery_jobs(self):\\n if self.is_managed and self.object_profile.enable_box_discovery:\\n Job.submit(\\n \\\"discovery\\\",\\n self.BOX_DISCOVERY_JOB,\\n key=self.id,\\n pool=self.pool.name,\\n delta=self.pool.get_delta(),\\n keep_ts=True,\\n )\\n else:\\n Job.remove(\\\"discovery\\\", self.BOX_DISCOVERY_JOB, key=self.id, pool=self.pool.name)\\n if self.is_managed and self.object_profile.enable_periodic_discovery:\\n Job.submit(\\n \\\"discovery\\\",\\n self.PERIODIC_DISCOVERY_JOB,\\n key=self.id,\\n pool=self.pool.name,\\n delta=self.pool.get_delta(),\\n keep_ts=True,\\n )\\n else:\\n Job.remove(\\\"discovery\\\", self.PERIODIC_DISCOVERY_JOB, key=self.id, pool=self.pool.name)\",\n \"def _wait_initialized(client, instance_id_list):\\n logging.info('Waiting for instances to be initialized.')\\n while True:\\n res = client.describe_instance_status(InstanceIds=instance_id_list)\\n if len(res['InstanceStatuses']) == 0:\\n time.sleep(10)\\n continue\\n if all([ s['InstanceStatus']['Status'] == 'ok' for s in res['InstanceStatuses'] ]):\\n logging.info('Instances are initialized now.')\\n return\\n time.sleep(10)\",\n \"def test_connection(cls, instances):\\n try:\\n instance, = instances\\n except ValueError:\\n cls.raise_user_error('multiple_instances')\\n\\n try:\\n with magento.API(\\n instance.url, instance.api_user, instance.api_key\\n ):\\n return\\n except (\\n xmlrpclib.Fault, IOError, xmlrpclib.ProtocolError, socket.timeout\\n ):\\n cls.raise_user_error(\\\"connection_error\\\")\",\n \"def keep_vifs_bound():\\n global EVT_TIMEOUT, NETSRS\\n\\n while bEndless:\\n with xenapi_session() as x:\\n try:\\n vms = x.VM.get_all_records() # Get a list of VMs for multiple uses\\n\\n # If the host is in maintenance mode end it and auto start VMs\\n host_ref = x.host.get_by_uuid(get_host_ref())\\n if not x.host.get_enabled(host_ref):\\n x.host.enable(host_ref) # End maintenance mode\\n\\n # Get a list of suitable VMs to start, ordered by ha restart priority\\n autostart_list = [(vms[k]['order'], k, float(vms[k]['start_delay'])) for k in vms.keys() if (\\n (not vms[k]['is_a_snapshot']) and\\n (not vms[k]['is_a_template']) and\\n (not vms[k]['is_control_domain']) and\\n (('auto_poweron' in vms[k]['other_config']) and (vms[k]['other_config']['auto_poweron'])) and\\n ('Halted' == vms[k]['power_state'])\\n )]\\n # We avoid .sort with a lambda to be able to delete the vms list\\n from operator import itemgetter\\n autostart_list.sort(key=itemgetter(0))\\n\\n # Attempt to start the VMs, while respecting the delays\\n for i in range(len(autostart_list)):\\n vm_ref = autostart_list[i][1]\\n try:\\n x.VM.start(vm_ref, False, False)\\n except:\\n pass\\n finally:\\n from time import sleep\\n if i < (len(autostart_list) - 1):\\n sleep(autostart_list[i][2])\\n\\n del autostart_list # Clean up\\n\\n # Find the ObscureRef of the target VM\\n try:\\n vmref = [k for k in vms.keys() if vms[k]['name_label'] == VMNAME][0]\\n except:\\n print('Unable to find a VM named \\\"{}\\\"'.format(VMNAME))\\n exit(4)\\n vifs = x.VM.get_VIFs(vmref)\\n bNetworkFound = False\\n for vif in vifs:\\n if SSPNNAME == x.network.get_record(x.VIF.get_network(vif))['name_label']:\\n bNetworkFound = True\\n break\\n if not bNetworkFound:\\n print('Unable to find a network named \\\"{}\\\" attached to the \\\"{}\\\" VM'.format(SSPNNAME, VMNAME))\\n exit(5)\\n\\n # Clean up\\n del vifs\\n del vms\\n\\n # Non-blocking listen for VM events\\n token = '' # Initial token\\n while bEndless:\\n output = x.event_from(['VM'], token, EVT_TIMEOUT)\\n token = output['token'] # Current token\\n\\n for event in output['events']:\\n # Check the IP assigned to the VIFs of the target VM, if it's running\\n if (('add' == event['operation']) or\\n ('mod' == event['operation'])) and \\\\\\n (vmref == event['ref']) and \\\\\\n ('Running' == x.VM.get_power_state(vmref)):\\n if 'snapshot' not in event:\\n continue\\n vifs = event['snapshot']['VIFs'] # Virtual interfaces list\\n for vif in vifs:\\n net = x.VIF.get_network(vif) # Network ref\\n netrec = x.network.get_record(net) # Network record\\n if SSPNNAME != netrec['name_label']:\\n continue\\n if rebind_ip_address(netrec['bridge']) and NETSRS:\\n for sr in NETSRS:\\n # Check if the destination is live for a maximum of 2 minutes and a half,\\n # and if it goes live replug the target SRs\\n (sr_uuid, pingTarget), = sr.items()\\n p = Ping(pingTarget, 5000)\\n if p.live(30):\\n plug_pbds(x, sr_uuid)\\n\\n except (socket.error, XmlRPCFault):\\n # Toolstack restarted/unavailable or SIGTERM'd\\n pass\",\n \"def tcp_ping_nodes(self, timeout=20.0):\\n for node in self.all_instances:\\n if node.instance_type in [\\n InstanceType.RESILIENT_SINGLE,\\n InstanceType.SINGLE,\\n InstanceType.DBSERVER,\\n ]:\\n node.check_version_request(timeout)\",\n \"def available(self):\\n from pyhs3 import STATE_LISTENING\\n return self._connection.api.state == STATE_LISTENING\",\n \"def wait_for_exec_to_start():\\n node_instances = self.client.node_instances.list()\\n for ni in node_instances:\\n # this will keyerror out (and be retried) if the operation\\n # didn't run yet\\n pids[ni.node_id] = ni.runtime_properties['pid']\",\n \"def check_avalaible_proxys(proxys):\\n socket.setdefaulttimeout(30)\\n\\n print(bcolors.WARNING + \\\"[-] Testing Proxy List...\\\\n\\\" + bcolors.ENDC)\\n\\n max_thread = THREAD\\n\\n queue = Queue.Queue()\\n queuelock = threading.Lock()\\n threads = []\\n\\n for proxy in proxys:\\n queue.put(proxy)\\n\\n while not queue.empty():\\n queuelock.acquire()\\n for workers in range(max_thread):\\n t = threading.Thread(target=check_proxy, args=(queue,))\\n t.setDaemon(True)\\n t.start()\\n threads.append(t)\\n for t in threads:\\n t.join()\\n queuelock.release()\\n\\n print(bcolors.OKGREEN + \\\"[+] Online Proxy: \\\" + bcolors.BOLD + str(len(proxys_working_list)) + bcolors.ENDC + \\\"\\\\n\\\")\\n\\n if len(proxys_working_list) == 0:\\n print (\\\"No proxies loaded! Check your proxy file. Exiting...\\\")\\n sys.exit(1)\",\n \"def running(self):\\n\\n return can_connect_to(APIConsumer.host, APIConsumer.port)\",\n \"def waiting_clients(self):\\n return self.storage.iterkeys()\",\n \"def check(self):\\n if self.backend.poll():\\n raise RuntimeError('Backend process died.')\\n\\n if self.esp.poll():\\n raise RuntimeError('ESP process died.')\",\n \"def _check_publishers_connection(self):\\n \\n rate = rospy.Rate(10) # 10hz; HOW DOES THIS WORK FOR CATVEHICLE/\\n \\n self._check_cmd_vel_pub()\\n\\n rospy.logdebug(\\\"All Publishers READY\\\")\",\n \"def _detect(self):\\n if (monasca_setup.detection.find_process_name('nova-api') is not None and\\n os.path.isfile(nova_conf)):\\n self.available = True\",\n \"def available(self) -> bool:\\n return self.thermostat[\\\"runtime\\\"][\\\"connected\\\"]\",\n \"async def check_status(self):\\n while True:\\n async with self._loop_lock:\\n new_monitor_processes = {}\\n for class_name in self.monitor_processes:\\n monitor = self.monitor_processes[class_name][\\\"process\\\"]\\n if monitor.poll() is not None:\\n log = f\\\"Monitor {class_name} has stopped with code: {monitor.returncode}\\\"\\n if monitor.returncode:\\n self.general_logger.warning(log)\\n if self.config[\\\"WebhookConfig\\\"][\\\"crash_webhook\\\"]:\\n embed = get_mm_crash_embed(\\n \\\"Monitor \\\" + class_name,\\n monitor.returncode,\\n monitor.pid,\\n )\\n ts = datetime.now().strftime(\\n self.config[\\\"WebhookConfig\\\"][\\\"timestamp_format\\\"]\\n )\\n\\n embed.set_footer(\\n text=f\\\"{self.config['WebhookConfig']['provider']} | {ts}\\\",\\n icon_url=self.config[\\\"WebhookConfig\\\"][\\n \\\"provider_icon\\\"\\n ],\\n )\\n data = json.dumps(\\n {\\n \\\"embeds\\\": [embed.to_dict()],\\n \\\"username\\\": \\\"MonitorManager process watcher\\\",\\n \\\"avatar_url\\\": self.config[\\\"WebhookConfig\\\"][\\n \\\"provider_icon\\\"\\n ],\\n }\\n )\\n r = await self.client.fetch(\\n self.config[\\\"WebhookConfig\\\"][\\\"crash_webhook\\\"],\\n method=\\\"POST\\\",\\n body=data,\\n headers={\\\"content-type\\\": \\\"application/json\\\"},\\n raise_error=False,\\n )\\n else:\\n self.general_logger.info(log)\\n else:\\n new_monitor_processes[class_name] = self.monitor_processes[\\n class_name\\n ]\\n self.monitor_processes = new_monitor_processes\\n\\n new_scraper_processes = {}\\n for class_name in self.scraper_processes:\\n scraper = self.scraper_processes[class_name][\\\"process\\\"]\\n if scraper.poll() is not None:\\n log = f\\\"Scraper {class_name} has stopped with code: {scraper.returncode}\\\"\\n if scraper.returncode:\\n self.general_logger.warning(log)\\n if self.config[\\\"WebhookConfig\\\"][\\\"crash_webhook\\\"]:\\n embed = get_mm_crash_embed(\\n \\\"Scraper \\\" + class_name,\\n scraper.returncode,\\n scraper.pid,\\n )\\n ts = datetime.now().strftime(\\n self.config[\\\"WebhookConfig\\\"][\\\"timestamp_format\\\"]\\n )\\n\\n embed.set_footer(\\n text=f\\\"{self.config['WebhookConfig']['provider']} | {ts}\\\",\\n icon_url=self.config[\\\"WebhookConfig\\\"][\\n \\\"provider_icon\\\"\\n ],\\n )\\n data = json.dumps(\\n {\\n \\\"embeds\\\": [embed.to_dict()],\\n \\\"username\\\": \\\"MonitorManager process watcher\\\",\\n \\\"avatar_url\\\": self.config[\\\"WebhookConfig\\\"][\\n \\\"provider_icon\\\"\\n ],\\n }\\n )\\n r = await self.client.fetch(\\n self.config[\\\"WebhookConfig\\\"][\\\"crash_webhook\\\"],\\n method=\\\"POST\\\",\\n body=data,\\n headers={\\\"content-type\\\": \\\"application/json\\\"},\\n raise_error=False,\\n )\\n else:\\n self.general_logger.info(log)\\n else:\\n new_scraper_processes[class_name] = self.scraper_processes[\\n class_name\\n ]\\n self.scraper_processes = new_scraper_processes\\n await asyncio.sleep(1)\",\n \"def _check_publishers_connection(self):\\n rate = rospy.Rate(10) # 1hz\\n while self._vel_pub.get_num_connections() == 0 and not rospy.is_shutdown():\\n rospy.logdebug(\\\"No susbribers to _vel_pub yet so we wait and try again\\\")\\n try:\\n rate.sleep()\\n except rospy.ROSInterruptException:\\n # This is to avoid error when world is rested, time when backwards.\\n pass\\n rospy.logdebug(\\\"_vel_pub Publisher Connected\\\")\\n\\n rospy.logdebug(\\\"All Publishers READY\\\")\",\n \"def wsdiscovery() -> list[Service]:\\n discovery = WSDiscovery(ttl=4)\\n try:\\n discovery.start()\\n return discovery.searchServices(\\n scopes=[Scope(\\\"onvif://www.onvif.org/Profile/Streaming\\\")]\\n )\\n finally:\\n discovery.stop()\\n # Stop the threads started by WSDiscovery since otherwise there is a leak.\\n discovery._stopThreads() # pylint: disable=protected-access\",\n \"def get_subscribers():\\n # TODO: make calls to each device asynchronous so we don't block\\n # trying to read from an unresponsive device on start up.\\n PortList = serial.tools.list_ports.comports()\\n manager.executor = ThreadPoolExecutor(max_workers=len(PortList))\\n for port in PortList:\\n if port.device in IGNORE_LIST:\\n continue\\n log.info('Found {}'.format(port.device))\\n ser = serial.Serial(port.device, baudrate=115200)\\n looping = True\\n while looping:\\n b = pyvesc.encode(pyvesc.ReqSubscription('t'))\\n ser.reset_input_buffer()\\n ser.write(b)\\n l = ser.read()\\n if l == b'\\\\x02' or l == b'\\\\x03':\\n # It's a VESC message!\\n looping = not init_vesc_driver(port, ser, l)\\n else:\\n # It's a JSON message!\\n looping = not init_json_driver(port, ser, l)\",\n \"def is_available():\",\n \"def __some_alive(self):\\n for service in self.__services.values():\\n if service.is_alive():\\n return True\\n return False\",\n \"def get_polling_service_instances_10(self):\\n poll_instances = []\\n poll_services = PollService.objects.filter(data_collections=self, enabled=True)\\n for poll_service in poll_services:\\n message_bindings = [mb.binding_id for mb in poll_service.supported_message_bindings.all()]\\n for supported_protocol_binding in poll_service.supported_protocol_bindings.all():\\n poll_instance = tm10.PollingServiceInstance(supported_protocol_binding.binding_id,\\n poll_service.build_service_address(supported_protocol_binding.binding_id),\\n message_bindings)\\n poll_instances.append(poll_instance)\\n\\n return poll_instances\",\n \"def checkonly(self):\\n OTHER_WSREP.append(socket.gethostbyname(socket.gethostname()))\\n for hostitem in ALL_NODES:\\n checkhost(hostitem)\\n if OTHER_WSREP:\\n for wsrepitem in OTHER_WSREP:\\n REMAINING_NODES.append(wsrepitem)\\n if REMAINING_NODES:\\n for wsrephost in OTHER_WSREP:\\n checkwsrep(wsrephost)\\n print ''\",\n \"def _check_coms(self):\\n self.com._check_rep()\",\n \"def _update_info(self):\\n with self.lock:\\n _LOGGER.info('Checking wireless clients')\\n\\n self.last_results = []\\n\\n active_clients = self.get_ddwrt_data()\\n\\n if not active_clients:\\n return False\\n\\n self.last_results.extend(active_clients)\\n\\n return True\",\n \"def __check_image_handlers(self):\\n active_workers = []\\n for w in self.__image_handlers:\\n if w.is_alive():\\n active_workers.append(w)\\n self.__image_handlers = active_workers\\n\\n if len(self.__video_modules) > len(self.__image_handlers):\\n new_t = threading.Thread(target=self.__image_request_handler)\\n new_t.start()\\n self.__image_handlers.append(new_t)\",\n \"def check_publishers_connection(self):\\n rate = rospy.Rate(10) # 10hz\\n while (self._cart_velocity_publisher.get_num_connections() == 0 and not rospy.is_shutdown()):\\n rospy.logdebug(\\\"No susbribers to _cart_velocity_publisher yet so we wait and try again\\\")\\n try:\\n rate.sleep()\\n except rospy.ROSInterruptException:\\n # This is to avoid error when world is rested, time when backwards.\\n pass\\n rospy.logdebug(\\\"_base_pub Publisher Connected\\\")\\n\\n rospy.logdebug(\\\"All Publishers READY\\\")\",\n \"def check_server(self, timeout=1):\\n ans = None\\n end_time = time.time() + timeout\\n while time.time() <= end_time:\\n try:\\n ans = self.xmlproxy.ping()\\n except socket_error:\\n time.sleep(1)\\n except Exception as err:\\n self.class_logger.warning(\\\"Unexpected type of error while checking xmlrpc server - {0} - {1}\\\".format(type(err), err))\\n time.sleep(1)\\n else:\\n if ans == \\\"XMLReportingServer\\\":\\n return True\\n else:\\n message = \\\"Unknown xmlrpc server is running on localhost:18080\\\"\\n self.class_logger.error(message)\\n raise Exception(message)\\n return False\",\n \"def clients(self):\\n items = []\\n for elem in self.query('/clients'):\\n baseurl = 'http://%s:%s' % (elem.attrib['address'],\\n elem.attrib['port'])\\n items.append(PlexClient(baseurl, server=self, data=elem))\\n return items\",\n \"def check_guest_applications(self):\\n apps = None\\n testflow.step(\\\"Check if guest agent is reporting applications\\\")\\n for sample in TimeoutingSampler(\\n config.SAMPLER_TIMEOUT, config.SAMPLER_SLEEP,\\n ll_vms.get_vm, self.vm_name\\n ):\\n apps = ll_vms.get_vm_applications(sample.get_name())\\n if len(apps) > 0:\\n break\\n logger.info(\\\"Windows '%s' apps are: %s\\\", self.disk_name, apps)\\n for app in apps:\\n testflow.step(\\\"Check if app %s is reporting version\\\", app)\\n try:\\n re.search(\\\"[ -]\\\\d+.*\\\", app).group(0)[1:]\\n except AttributeError:\\n logger.error(\\\"App %s is not reporting version\\\", app)\",\n \"def get_pending_instances(self):\\n return [instance for instance in self.instances.itervalues()\\n if InstanceState.REQUESTED <= instance.state < InstanceState.RUNNING]\",\n \"def detect_instance_pids(self):\\n for instance in self.all_instances:\\n instance.detect_pid(\\n ppid=self.instance.pid,\\n full_binary_path=self.cfg.real_sbin_dir,\\n offset=0,\\n )\\n\\n self.show_all_instances()\\n self.detect_arangosh_instances(self.cfg, self.cfg.version)\",\n \"def detect_used_ports():\\n MAX_PORT = 1025\\n DEFAULT_HOST = '127.0.0.1'\\n open_ports = []\\n socket.setdefaulttimeout(1)\\n for port in range(0, MAX_PORT):\\n res = port_scan(DEFAULT_HOST, port)\\n if res:\\n open_ports.append(port)\\n # debugging purpose to see if program is running\\n if port % 5000 == 0 and port != 0:\\n sys.stderr.write('.')\\n return open_ports\",\n \"def _check_sources(self):\\n avail_sources = []\\n for source in self.__video_sources:\\n avail_sources.append(source)\\n\\n # Try to start each video source known. Naovideo is not in this list,\\n # because without an explicit request, no IP and port is known so no\\n # connection can be made.\\n for source in [\\\"webcam\\\", \\\"kinect\\\"]:\\n if source in avail_sources:\\n continue\\n\\n # Status unknown, try to start and stop\\n self.__logger.info(\\\"Trying to see if source %s is available\\\" % source)\\n try:\\n if self._start_video_source(source):\\n avail_sources.append(source)\\n self._stop_video_source(source)\\n except Exception, e:\\n self.__logger.info(\\\"Error starting source %s, (error: %s) must not be available\\\" % (source, str(e)))\\n \\n return avail_sources\",\n \"def known_nodes(self) -> List[Client]:\\n return list(self.in_memory_client_registry.values())\",\n \"def get_active_clients():\\n global drivers\\n\\n if not drivers:\\n return jsonify([])\\n\\n result = {client: get_client_info(client) for client in drivers}\\n return jsonify(result)\",\n \"def getActiveProcesses():\\n active = []\\n\\n for p in PROCESSRUNNER_PROCESSES:\\n if p.is_alive():\\n active.append(p)\\n\\n return active\",\n \"def instances_used(self):\\n return None\",\n \"def get_running_pris(self):\\n try:\\n running_pris_list = []\\n output = self.ssh.exec_command(self.check_running_kombu_dialer_command)\\n for line in output[1].readlines():\\n line = line.split()\\n if self.server in line and \\\"-g\\\" in line:\\n running_pris_list.append(\\n int(\\n line[line.index(\\\"-g\\\")+1][2:]\\n )\\n )\\n return running_pris_list\\n except Exception as err:\\n self.error_logger.error(err.message + \\\" PRITester::get_running_pris\\\")\\n return None\",\n \"def wait_for_cadvisor_up(self):\\n ping = None\\n while ping is None:\\n ping = requests.get(self._url_prefix, timeout=CONNECTION_TIMEOUT)\\n if ping is None:\\n logger.debug(\\\"Unable to connect to cadvisor %s. Will sleep for %s sec\\\",\\n self._url_prefix, CHECK_LIVELINESS_INTERVAL)\\n time.sleep(CHECK_LIVELINESS_INTERVAL)\\n logger.info(\\\"cAdvisor client is up for endpoint %s\\\", self._url_prefix)\",\n \"def _check_endpoints_last_communication(self):\\n while self._thread_running:\\n endpoints = EndpointService.get_all_endpoints()\\n for endpoint in endpoints:\\n if datetime.now() - endpoint.lastCommunication > timedelta(minutes=TOKEN_EXPIRE_TIME):\\n EventService.add_event(Event(\\\"0\\\", \\\"Lost Endpoint At \\\" +\\n str(endpoint[EndpointKeys.LAST_COMMUNICATION_KEY]),\\n \\\"Report\\\", \\\"IDLE\\\", endpoint[EndpointKeys.HOSTNAME_KEY],\\n endpoint[EndpointKeys.IP_ADDRESS_KEY]))\\n EndpointService.delete_endpoint(endpoint.id)\\n sleep(SLEEP_TIME)\",\n \"async def async_scan_devices(self):\\n await self.async_update_info()\\n return list(self.last_results.keys())\",\n \"def test_all_workers_are_active_processes(self):\\n WORKERS_COUNT = 10\\n\\n # Testing only ProcessPool since only it has the mechanism that waits for all workers to come online before\\n # start finishes\\n pool = ProcessPool(WORKERS_COUNT)\\n\\n pool.start(WorkerIdGeneratingWorker)\\n for _ in range(100):\\n pool.ventilate()\\n\\n active_worker_ids = [pool.get_results() for _ in range(100)]\\n self.assertEqual(set(range(WORKERS_COUNT)), set(active_worker_ids))\\n\\n pool.stop()\\n pool.join()\",\n \"def check_pool(self):\\n if self.conn.queue_len() < MAX_PROXIES:\\n return True\\n return False\",\n \"def basic_overcloud_processes_running(self):\\n for attempt_number in range(600):\\n\\n try:\\n\\n for process_name in self.processes_to_check:\\n # osp16/python3 process is \\\"neutron-server:\\\"\\n if process_name == 'neutron-server' and \\\\\\n self.oc_procs_df.query('PROCESS==\\\"{}\\\"'.format(\\n process_name)).empty:\\n process_name = 'neutron-server:'\\n # osp17 mysqld process name is mysqld_safe\\n if process_name == 'mysqld' and \\\\\\n self.oc_procs_df.query('PROCESS==\\\"{}\\\"'.format(\\n process_name)).empty:\\n process_name = 'mysqld_safe'\\n # redis not deployed on osp17 by default, only if some\\n # other services such as designate and octavia are deployed\\n if (process_name == 'redis-server' and\\n not overcloud.is_redis_expected()):\\n redis_message = (\\\"redis-server not expected on OSP 17 \\\"\\n \\\"and later releases by default\\\")\\n if self.oc_procs_df.query(\\n f'PROCESS==\\\"{process_name}\\\"').empty:\\n LOG.info(redis_message)\\n continue\\n else:\\n raise OvercloudProcessesException(\\n process_error=redis_message)\\n\\n if not self.oc_procs_df.query('PROCESS==\\\"{}\\\"'.format(\\n process_name)).empty:\\n LOG.info(\\\"overcloud processes status checks: \\\"\\n \\\"process {} is \\\"\\n \\\"in running state\\\".format(process_name))\\n continue\\n else:\\n LOG.info(\\\"Failure : overcloud processes status checks:\\\"\\n \\\"process {} is not running \\\".format(\\n process_name))\\n raise OvercloudProcessesException(\\n process_error=\\\"process {} is not running \\\".format(\\n process_name))\\n # if all procs are running we can return true\\n return True\\n except OvercloudProcessesException:\\n LOG.info('Retrying overcloud processes checks attempt '\\n '{} of 360'.format(attempt_number))\\n time.sleep(1)\\n self.oc_procs_df = overcloud.get_overcloud_nodes_dataframe(\\n get_overcloud_node_processes_table)\\n # exhausted all retries\\n tobiko.fail('Not all overcloud processes are running !\\\\n')\",\n \"def owserver_running():\\n for proc in psutil.process_iter():\\n if 'owserver' in proc.name():\\n return True\\n return False\",\n \"def get_instances() -> dict:\\n url = f\\\"{app.config['COMPUTE_SERVERS_REF']}/detail\\\"\\n instances_rq = request(\\n method=\\\"GET\\\", url=url, headers=build_header(), params={\\\"vm_state\\\": \\\"active\\\"},\\n )\\n\\n if not instances_rq.ok:\\n HTTPError(instances_rq.status_code)\\n\\n answer = {\\\"servers\\\": list()}\\n for instance in instances_rq.json()[\\\"servers\\\"]:\\n instance_info = dict(name=instance[\\\"name\\\"])\\n instance_info[\\\"ip_addresses\\\"] = list()\\n for network, info in instance[\\\"addresses\\\"].items():\\n instance_info[\\\"ip_addresses\\\"].extend(entry[\\\"addr\\\"] for entry in info)\\n answer[\\\"servers\\\"].append(instance_info)\\n\\n return answer\",\n \"def available(self):\\n if self._available is None:\\n try:\\n global xpress\\n import xpress\\n\\n # Always disable the global output. We only want output if\\n # we install callbacks explicitly\\n xpress.setOutputEnabled(False)\\n self._available = True\\n except:\\n self._available = False\\n return self._available\",\n \"def get_vrps(self):\\n self.info(\\\"Trying to get new VRP data from agent\\\")\\n for i in range(3):\\n time.sleep(1)\\n if self.conn.poll():\\n self.vrps = self.conn.recv()\\n self.info(\\\"Got data on try {}\\\".format(i))\\n return True\\n self.info(\\\"Nothing to receive on try {}\\\".format(i))\\n self.warning(\\\"No data received from agent\\\")\\n return False\",\n \"def startListening(self):\\n mgr = self.cxn.manager\\n # example of Signal processing:\\n # server = self.cxn[self.selectedADR]\\n # update_state = lambda c, payload: self.updateInterface()\\n # yield server.signal_state_changed(self.ID)\\n # yield server.addListener(listener = update_state, source=None,ID=self.ID)\\n\\n # state update (only if the message is from the correct ADR server)\\n update_state = lambda c, (s,payload): self.updateInterface() \\\\\\n if self.correctServer(s) else -1\\n self.cxn._cxn.addListener(update_state, source=mgr.ID, ID=101)\\n yield mgr.subscribe_to_named_message('State Changed', 101, True)\\n # log update\\n update_log = lambda c, (s,(t,m,a)): self.updateLog(t,m,a) \\\\\\n if self.correctServer(s) else -1\\n self.cxn._cxn.addListener(update_log, source=mgr.ID, ID=102)\\n yield mgr.subscribe_to_named_message('Log Changed', 102, True)\\n # magging up stopped\\n mag_stop = lambda c, (s,payload): self.magUpStopped() \\\\\\n if self.correctServer(s) else -1\\n self.cxn._cxn.addListener(mag_stop, source=mgr.ID, ID=103)\\n yield mgr.subscribe_to_named_message('MagUp Stopped', 103, True)\\n # regulation stopped\\n reg_stop = lambda c, (s,payload): self.regulationStopped() \\\\\\n if self.correctServer(s) else -1\\n self.cxn._cxn.addListener(reg_stop, source=mgr.ID, ID=104)\\n yield mgr.subscribe_to_named_message('Regulation Stopped', 104, True)\\n # magging up started\\n mag_start = lambda c, (s,payload): self.magUpStarted() \\\\\\n if self.correctServer(s) else -1\\n self.cxn._cxn.addListener(mag_start, source=mgr.ID, ID=105)\\n yield mgr.subscribe_to_named_message('MagUp Started', 105, True)\\n # regulation started\\n reg_start = lambda c, (s,payload): self.regulationStarted() \\\\\\n if self.correctServer(s) else -1\\n self.cxn._cxn.addListener(reg_start, source=mgr.ID, ID=106)\\n yield mgr.subscribe_to_named_message('Regulation Started', 106, True)\\n # servers starting and stopping\\n serv_conn_func = lambda c, (sID, sName): self.serverChanged(sName)\\n serv_disconn_func = lambda c, (sID, sName): self.serverChanged(sName)\\n self.cxn._cxn.addListener(serv_conn_func, source=mgr.ID, ID=107)\\n self.cxn._cxn.addListener(serv_disconn_func, source=mgr.ID, ID=108)\\n yield mgr.subscribe_to_named_message('Server Connect', 107, True)\\n yield mgr.subscribe_to_named_message('Server Disconnect', 108, True)\",\n \"def create_clients():\\n clients = {}\\n\\n rospy.loginfo(\\\"Waiting for rubble detector\\\")\\n clients['rubble_detect'] = actionlib.SimpleActionClient('rubble_detect',\\n RubbleDetectAction)\\n\\n rospy.loginfo(\\\"Waiting for rubble checker\\\")\\n clients['rubble_check'] = actionlib.SimpleActionClient('rubble_check',\\n RubbleCheckAction)\\n clients['rubble_check'].wait_for_server()\\n rospy.loginfo(\\\"rubble_check connected\\\")\\n\\n rospy.loginfo(\\\"Waiting for room searcher\\\")\\n clients['search_room'] = actionlib.SimpleActionClient('search_room',\\n SearchRoomAction)\\n clients['search_room'].wait_for_server()\\n rospy.loginfo(\\\"search_room connected\\\")\\n\\n rospy.loginfo(\\\"Waiting for navigator\\\")\\n clients['navigation'] = actionlib.SimpleActionClient('navigation',\\n NavigateAction)\\n clients['navigation'].wait_for_server()\\n rospy.loginfo(\\\"navigation connected\\\")\\n\\n rospy.loginfo(\\\"Waiting for door clearer\\\")\\n clients['rubble_clear'] = actionlib.SimpleActionClient('rubble_clear',\\n RubbleClearAction)\\n clients['rubble_clear'].wait_for_server()\\n rospy.loginfo(\\\"rubble clear connected\\\")\\n\\n rospy.loginfo(\\\"All clients for policy executor set up\\\")\\n\\n return clients\",\n \"def run(self):\\n for req, resp in self.servings:\\n resp.check_timeout()\",\n \"def active_failover_detect_hosts(self):\\n self.check_that_instance_is_alive()\\n # this is the way to detect the master starter...\\n lfs = self.get_log_file()\\n if lfs.find(\\\"Just became master\\\") >= 0:\\n self.is_master = True\\n else:\\n self.is_master = False\\n regx = re.compile(r\\\"Starting resilientsingle on port (\\\\d*) .*\\\")\\n match = regx.search(lfs)\\n if match is None:\\n raise Exception(timestamp() + \\\"Unable to get my host state! \\\" + self.basedir + \\\" - \\\" + lfs)\\n\\n self.frontend_port = match.groups()[0]\",\n \"def urlvoid_check(name, api_key):\\n if not is_fqdn(name):\\n return None\\n\\n url = 'http://api.urlvoid.com/api1000/{key}/host/{name}'.format(key=api_key, name=name)\\n response = requests.get(url)\\n tree = ET.fromstring(response.text)\\n if tree.find('./detections/engines'):\\n return [e.text for e in tree.find('./detections/engines')]\\n else:\\n return None\",\n \"def issuer_liveness_check():\\n global app_config\\n\\n if app_config[\\\"running\\\"]:\\n # return True until we get a shutdown request\\n return True\\n\\n # return True until the work queue is cleared\\n return tob_connection_active()\",\n \"def _wait(self):\\n conn = None\\n try:\\n conn = libvirt.open(\\\"qemu:///system\\\")\\n while True:\\n time.sleep(10)\\n try:\\n state = conn.lookupByName(self.domain).info()[0]\\n except (libvirt.libvirtError, TypeError, IndexError):\\n break\\n if state in [4, 5, 6]: # crashed or shutdown\\n break\\n finally:\\n if conn is not None:\\n conn.close()\",\n \"def wait_proc(self, proc_pattern, max_retry=3):\\n check_cmd = \\\"pgrep -f '%s'\\\" % proc_pattern\\n fip_lst = self._get_ins_fips()\\n ssh_clt = paramiko.SSHClient()\\n ssh_clt.set_missing_host_key_policy(paramiko.AutoAddPolicy())\\n\\n for srv_grp, fip_grp in zip(self.srv_grp_lst, fip_lst):\\n for srv, fip in zip(srv_grp, fip_grp):\\n retry = 0\\n while retry <= max_retry:\\n try:\\n ssh_clt.connect(fip, 22, srv['ssh']['user_name'],\\n key_filename=srv['ssh']['pvt_key_file'])\\n except Exception:\\n logger.warn(\\n '[FIP:%s] Can not connect to instance, try again after 3 seconds'\\n % fip\\n )\\n time.sleep(3)\\n retry += 1\\n else:\\n break\\n else:\\n ssh_clt.close()\\n raise ServerChainError(\\n '[FIP:%s] Can not connect to instance via SSH' % fip)\\n\\n trans = ssh_clt.get_transport()\\n retry = 0\\n while retry <= max_retry:\\n channel = trans.open_session()\\n channel.exec_command(check_cmd)\\n status = channel.recv_exit_status()\\n if status == 0:\\n break\\n else:\\n logger.warn(\\n '[FIP:%s] Process is not running, recheck after 10 seconds.'\\n % fip\\n )\\n time.sleep(10)\\n retry += 1\\n else:\\n ssh_clt.close()\\n raise ServerChainError(\\n '[FIP:%s] SF Process is not running' % fip)\\n\\n ssh_clt.close()\",\n \"def verify_services(self):\\n services = [\\\"metric_collector\\\", \\\"log_collector\\\"]\\n service_version_9 = [\\\"lma_collector\\\"]\\n pids = {}\\n processes_count = {\\n \\\"collectd \\\": 1,\\n \\\"collectdmon \\\": 1\\n }\\n\\n if self.settings.version.startswith(\\\"0.9\\\"):\\n processes_count[\\n \\\"hekad -config[= ]/etc/{}\\\".format(service_version_9)] = 1\\n else:\\n # Starting with 0.10, there are one collector for logs and one for\\n # metrics\\n for service in services:\\n processes_count[\\\"hekad -config[= ]/etc/{}\\\".format(service)] = 1\\n online_nodes = [node for node in self.helpers.get_all_ready_nodes()\\n if node[\\\"online\\\"]]\\n for node in online_nodes:\\n pids[node[\\\"name\\\"]] = {}\\n with self.env.d_env.get_ssh_to_remote(node[\\\"ip\\\"]) as remote:\\n for process, count in processes_count.items():\\n logger.info(\\\"Checking process {0} on node {1}\\\".format(\\n process, node[\\\"name\\\"]\\n ))\\n pids[node[\\\"name\\\"]][process] = (\\n self.checkers.check_process_count(\\n remote, process, count))\\n return pids\",\n \"def isListening(self):\\n if not self.proxy:\\n self.proxy = self.session.service(\\\"ALExpressiveListening\\\")\\n return self.proxy.isListening()\",\n \"def kafka_consumer_check_instances(self) -> Optional[pulumi.Input[int]]:\\n return pulumi.get(self, \\\"kafka_consumer_check_instances\\\")\",\n \"def check_firefox_processes(self):\\n mm = MicroManager(self.hostname)\\n ff_procs = mm.find_processes_by_name(\\\"firefox\\\")\\n if len(ff_procs) > 2:\\n return [CheckStatus(self, CheckStatus.CHECK_FIREFOX_PROCESS_COUNT, CheckStatus.STATUS_FAIL, \\\"There are {} firefox processes running\\\".format(len(ff_procs))), ]\\n else:\\n return [CheckStatus(self, CheckStatus.CHECK_FIREFOX_PROCESS_COUNT, CheckStatus.STATUS_PASS), ]\",\n \"def poll():\\n try:\\n self.connect(VAULT_TOKEN).sys.list_enabled_audit_devices()\\n return True\\n except hvac.exceptions.InternalServerError as ex:\\n if str(ex).startswith('local node not active but active cluster node not found'):\\n return False\\n raise\",\n \"def check_availability(self):\\n pass\",\n \"async def _async_has_devices(opp: OpenPeerPower) -> bool:\\n # TODO Check if there are any devices that can be discovered in the network.\\n devices = await opp.async_add_executor_job(my_pypi_dependency.discover)\\n return len(devices) > 0\",\n \"async def test_web_access(registered_devices: List[Device], max_parallel_connections:int = 30) -> List[Device]:\\n\\n session = aiohttp.ClientSession()\\n registered_devices_after_checks = []\\n\\n test_connection_tasks = (is_web_enabled(session, device) for device in registered_devices)\\n\\n while True:\\n parallel_tasks = list(islice(test_connection_tasks, max_parallel_connections))\\n if not parallel_tasks:\\n break\\n\\n done, pending = await asyncio.wait(parallel_tasks, loop=loop)\\n\\n for task in done:\\n registered_devices_after_checks.append(task.result())\\n\\n session.close()\\n\\n return registered_devices_after_checks\",\n \"def _detect(self):\\n if monasca_setup.detection.find_process_cmdline('rabbitmq-server') is not None:\\n self.available = True\",\n \"def proxy_scrape(self):\\n print(\\\"Getting new live proxies\\\")\\n url = 'https://free-proxy-list.net/'\\n response = requests.get(url)\\n parser = fromstring(response.text)\\n proxies = set()\\n for i in parser.xpath('//tbody/tr')[:20]:\\n # if i.xpath('.//td[7][contains(text(),\\\"yes\\\")]'):\\n proxy = \\\":\\\".join([i.xpath('.//td[1]/text()')\\n [0], i.xpath('.//td[2]/text()')[0]])\\n proxies.add(proxy)\\n # return proxies\\n # proxies=[]\\n print(\\\"Obtained proxied are as : \\\", proxies)\\n proxy_pool = cycle(proxies)\\n proxy_list = [proxy for proxy in proxies]\\n return proxy_pool, proxy_list\",\n \"def gotConnectionWithServices(timeout):\\n\\n try:\\n rospy.wait_for_service('fluid/take_off', timeout=timeout)\\n rospy.wait_for_service('fluid/explore', timeout=timeout)\\n rospy.wait_for_service('fluid/travel', timeout=timeout)\\n rospy.wait_for_service('fluid/land', timeout=timeout)\\n rospy.wait_for_service('fluid/interact', timeout=timeout)\\n return True\\n except rospy.ROSException:\\n return False\",\n \"def disable_discovery(self):\",\n \"def instances(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['BrokerInstanceArgs']]]]:\\n return pulumi.get(self, \\\"instances\\\")\",\n \"def wait_for_ready(self, instance_id, limit, delay=1, pending=False):\\r\\n for count, new_instance in enumerate(repeat(instance_id), start=1):\\r\\n instance = self.get_instance(new_instance)\\r\\n last_reload = lookup(instance, 'lastOperatingSystemReload', 'id')\\r\\n active_transaction = lookup(instance, 'activeTransaction', 'id')\\r\\n\\r\\n reloading = all((\\r\\n active_transaction,\\r\\n last_reload,\\r\\n last_reload == active_transaction\\r\\n ))\\r\\n\\r\\n # only check for outstanding transactions if requested\\r\\n outstanding = False\\r\\n if pending:\\r\\n outstanding = active_transaction\\r\\n\\r\\n # return True if the instance has only if the instance has\\r\\n # finished provisioning and isn't currently reloading the OS.\\r\\n if instance.get('provisionDate') \\\\\\r\\n and not reloading and not outstanding:\\r\\n return True\\r\\n\\r\\n if count >= limit:\\r\\n return False\\r\\n\\r\\n sleep(delay)\",\n \"def get_registered_clients(self):\\n return self.hub.get_registered_clients(self.get_private_key())\",\n \"def check_eapi(self, eapi):\\n\\t\\treturn True\",\n \"def poll(cls, context):\\r\\n return hasattr(bpy.types.Object, \\\"BlenderNEURON_node\\\") and \\\\\\r\\n bpy.types.Object.BlenderNEURON_node is not None and \\\\\\r\\n bpy.types.Object.BlenderNEURON_node.client is not None\",\n \"def poll(cls, context):\\r\\n return hasattr(bpy.types.Object, \\\"BlenderNEURON_node\\\") and \\\\\\r\\n bpy.types.Object.BlenderNEURON_node is not None and \\\\\\r\\n bpy.types.Object.BlenderNEURON_node.client is not None\",\n \"def is_call_waiting(self) -> bool:\",\n \"def wait_on_elb_instance ( elb_conn, elb_name, elb_instance_id, elb_state = 'InService', sleep_time = 10, max_wait = 300 ) :\\n instance_states = elb_conn.describe_instance_health( load_balancer_name = elb_name,\\n instances = [ elb_instance_id ] )\\n instance_state = instance_states[ 0 ].state\\n while instance_state != elb_state :\\n if max_wait <= 0 :\\n break\\n time.sleep( sleep_time )\\n max_wait -= sleep_time\\n instance_states = elb_conn.describe_instance_health( load_balancer_name = elb_name,\\n instances = [ elb_instance_id ] )\\n instance_state = instance_states[ 0 ].state\\n\\n return instance_state == elb_state\",\n \"async def request(self) -> set[LcnAddr]:\\n await self.addr_conn.conn.segment_scan_completed_event.wait()\\n self.groups_known.clear()\\n self.trh.activate()\\n await self.groups_known.wait()\\n return self.groups\",\n \"async def request(self) -> set[LcnAddr]:\\n await self.addr_conn.conn.segment_scan_completed_event.wait()\\n self.groups_known.clear()\\n self.trh.activate()\\n await self.groups_known.wait()\\n return self.groups\",\n \"def run(self):\\n run = True\\n while run:\\n statuses = self.check_status()\\n unhealthy = [ups for ups in statuses.keys() if not statuses[ups]]\\n drivers_to_bounce = set()\\n for ups in unhealthy:\\n driver = self.ups_confs[ups].get('driver', 'usbhid-ups')\\n drivers_to_bounce.add(driver)\\n if drivers_to_bounce:\\n self.bounce_drivers(drivers_to_bounce)\\n time.sleep(self.monitor_cycle/1000)\",\n \"def wait_for_version_reply(self):\\n frontends = self.get_frontends()\\n for frontend in frontends:\\n # we abuse this function:\\n while frontend.get_afo_state() != AfoServerState.LEADER:\\n progress(\\\".\\\")\\n time.sleep(0.1)\",\n \"def _find_xinput(self):\\n for dll in XINPUT_DLL_NAMES:\\n try:\\n self.xinput = getattr(ctypes.windll, dll)\\n except OSError:\\n pass\\n else:\\n # We found an xinput driver\\n self.xinput_dll = dll\\n break\\n else:\\n # We didn't find an xinput library\\n warn(\\n \\\"No xinput driver dll found, gamepads not supported.\\\",\\n RuntimeWarning)\",\n \"def instances_created(self):\\n with _MonitorEnv._lock:\\n return self._instances_created\",\n \"def test_evrpnl_instances(self) -> bool:\\n\\n for rte_info in self.results.values():\\n frvcp_solver = solver.Solver(\\n self.ref_instance, rte_info['route'], self.q_init)\\n obj, _ = frvcp_solver.solve()\\n self.assertAlmostEqual(obj, rte_info['obj'], 3)\",\n \"def _get_dependencies():\\n return config.check_driver_dependencies(__virtualname__, {\\\"XenAPI\\\": HAS_XEN_API})\",\n \"def isThereApiCalls(report):\\n with open(report, \\\"rb\\\") as r:\\n data = json.load(r)\\n for i in range(numProcs(report)):\\n if len(data[\\\"behavior\\\"][\\\"processes\\\"][i][\\\"calls\\\"]) > 0:\\n return True\\n else:\\n continue\\n return False\",\n \"def instances(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['InstanceStatusArgs']]]]:\\n return pulumi.get(self, \\\"instances\\\")\",\n \"def _loadchildren():\\n return [\\n [PingAPI, {}, None],\\n ]\",\n \"def get_candidates(self, cloud_name, jobs, count, return_only_all_idle=False):\\n\\n asg_info = self.phantom_client.get_autoscale_groups_info(self.phantom_client.asg.name)\\n all_instances_info = asg_info[self.phantom_client.asg.name]['instances']\\n instances = self.phantom_client.get_alive_instnaces(all_instances_info)\\n\\n localjobs = copy.copy(jobs)\\n\\n idle_list = []\\n nonidle_list = []\\n for instance in instances:\\n if instances[instance]['cloud_name'] != cloud_name:\\n continue\\n job_matching_found = False\\n for job in localjobs.list:\\n if instances[instance]['public_dns'] == job.node:\\n #nonidle_list.append( (instance, job.running, instances[instance]) )\\n nonidle_list.append( (instance, job.progress, instances[instance]) )\\n\\n localjobs.list.remove(job)\\n job_matching_found = True\\n break\\n if not job_matching_found:\\n idle_list.append( (instance, instances[instance]) )\\n\\n # Truncate idle list if needed (in case there are more idle instances than count)\\n # Does not do anything if count >= len(idle_list)\\n\\n if return_only_all_idle:\\n # DONE if this flag is set\\n return idle_list\\n\\n idle_list = idle_list[:count]\\n\\n if idle_list:\\n idle_list_str = \\\"\\\"\\n for instance in idle_list:\\n idle_list_str += \\\"%s:%s,\\\" % (instance[0], instance[1]['public_dns'])\\n LOG.info(\\\"OO found idle candidates for termination in %s: %s\\\" % (cloud_name, idle_list_str))\\n\\n # Sort by the run time in the decreasing order\\n sorted_nonidle_list = sorted(nonidle_list, key=operator.itemgetter(1), reverse=True)\\n\\n remaining_count = count - len(idle_list)\\n # Truncate sorted non-idle list if needed (in case remaining_count < len(sorted_nonidle_list))\\n sorted_nonidle_list = sorted_nonidle_list[:remaining_count]\\n\\n sorted_nonidle_list_instances_only = []\\n if sorted_nonidle_list:\\n nonidle_list_str = \\\"\\\"\\n for atuple in sorted_nonidle_list:\\n nonidle_list_str += \\\"%s:%s:%s,\\\" % (atuple[0], atuple[2]['public_dns'], atuple[1])\\n sorted_nonidle_list_instances_only.append((atuple[0], atuple[2] ))\\n LOG.info(\\\"OO found non-idle candidates for termination in %s: %s\\\" % (cloud_name, nonidle_list_str))\\n\\n total_found = len(idle_list)+len(sorted_nonidle_list_instances_only)\\n if not total_found == count:\\n LOG.info(\\\"OO can't supply enough (%d) instances for termination. Found only %d\\\", count, total_found)\\n\\n return idle_list, sorted_nonidle_list_instances_only\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6325874","0.57466775","0.55821526","0.5577072","0.54760903","0.54682326","0.543734","0.5412187","0.5394259","0.53219014","0.5313654","0.52691233","0.5248033","0.5224936","0.52046394","0.5202071","0.52012694","0.5174187","0.51666844","0.51602364","0.5159468","0.51507205","0.51476645","0.51452607","0.5143909","0.5127485","0.5102608","0.508867","0.50865024","0.5082796","0.5077515","0.5073241","0.50683707","0.5066033","0.5060414","0.50584954","0.50486964","0.503617","0.50311244","0.502086","0.50184137","0.5012161","0.50016904","0.49907395","0.49885276","0.49878278","0.49793157","0.49652869","0.49592212","0.4957863","0.4946271","0.49411863","0.49365434","0.49299476","0.49271074","0.49268264","0.49253172","0.49252608","0.49212095","0.4918728","0.4911024","0.4905017","0.49022734","0.48956144","0.48916224","0.48909786","0.48901194","0.48897016","0.48865193","0.48824695","0.48810926","0.48743466","0.48727146","0.48726946","0.48607507","0.48566273","0.4847518","0.48470104","0.48441297","0.48326525","0.48124924","0.4811461","0.48023605","0.48021713","0.48006183","0.48006183","0.4794473","0.47918537","0.47882563","0.47882563","0.47861326","0.47839758","0.478215","0.47805944","0.4780535","0.4778418","0.4778376","0.47783655","0.47782582","0.477737"],"string":"[\n \"0.6325874\",\n \"0.57466775\",\n \"0.55821526\",\n \"0.5577072\",\n \"0.54760903\",\n \"0.54682326\",\n \"0.543734\",\n \"0.5412187\",\n \"0.5394259\",\n \"0.53219014\",\n \"0.5313654\",\n \"0.52691233\",\n \"0.5248033\",\n \"0.5224936\",\n \"0.52046394\",\n \"0.5202071\",\n \"0.52012694\",\n \"0.5174187\",\n \"0.51666844\",\n \"0.51602364\",\n \"0.5159468\",\n \"0.51507205\",\n \"0.51476645\",\n \"0.51452607\",\n \"0.5143909\",\n \"0.5127485\",\n \"0.5102608\",\n \"0.508867\",\n \"0.50865024\",\n \"0.5082796\",\n \"0.5077515\",\n \"0.5073241\",\n \"0.50683707\",\n \"0.5066033\",\n \"0.5060414\",\n \"0.50584954\",\n \"0.50486964\",\n \"0.503617\",\n \"0.50311244\",\n \"0.502086\",\n \"0.50184137\",\n \"0.5012161\",\n \"0.50016904\",\n \"0.49907395\",\n \"0.49885276\",\n \"0.49878278\",\n \"0.49793157\",\n \"0.49652869\",\n \"0.49592212\",\n \"0.4957863\",\n \"0.4946271\",\n \"0.49411863\",\n \"0.49365434\",\n \"0.49299476\",\n \"0.49271074\",\n \"0.49268264\",\n \"0.49253172\",\n \"0.49252608\",\n \"0.49212095\",\n \"0.4918728\",\n \"0.4911024\",\n \"0.4905017\",\n \"0.49022734\",\n \"0.48956144\",\n \"0.48916224\",\n \"0.48909786\",\n \"0.48901194\",\n \"0.48897016\",\n \"0.48865193\",\n \"0.48824695\",\n \"0.48810926\",\n \"0.48743466\",\n \"0.48727146\",\n \"0.48726946\",\n \"0.48607507\",\n \"0.48566273\",\n \"0.4847518\",\n \"0.48470104\",\n \"0.48441297\",\n \"0.48326525\",\n \"0.48124924\",\n \"0.4811461\",\n \"0.48023605\",\n \"0.48021713\",\n \"0.48006183\",\n \"0.48006183\",\n \"0.4794473\",\n \"0.47918537\",\n \"0.47882563\",\n \"0.47882563\",\n \"0.47861326\",\n \"0.47839758\",\n \"0.478215\",\n \"0.47805944\",\n \"0.4780535\",\n \"0.4778418\",\n \"0.4778376\",\n \"0.47783655\",\n \"0.47782582\",\n \"0.477737\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6125134"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":88581,"cells":{"query":{"kind":"string","value":"Creates Experiment object to create a new experiment or to access an experiment already set up by the operator of the Xepr application."},"document":{"kind":"string","value":"def XeprExperiment(self, *p, **k):\n # noinspection PyTypeChecker\n return Experiment(self, *p, **k)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_experiment_if_needed(tr):\n exp = tr.getExperiment(EXPERIMENT_ID)\n if None == exp:\n create_project_if_needed(tr)\n exp = tr.createNewExperiment(EXPERIMENT_ID, 'DEFAULT_EXPERIMENT')\n \n return exp","def create_experiment(self):\n experiment = wandb.init(\n name=self._name, dir=self._dir, project=self._project,\n anonymous=self._anonymous, reinit=True, id=self._id,\n resume='allow', tags=self._tags, entity=self._entity\n )\n wandb.run.save()\n return experiment","def _create_or_get_experiment(self) -> tensorboard_experiment.TensorboardExperiment:\n logger.info(\"Creating experiment\")\n\n tb_experiment = tensorboard_experiment.TensorboardExperiment(\n description=self._description, display_name=self._experiment_display_name\n )\n\n try:\n experiment = self._api.create_tensorboard_experiment(\n parent=self._tensorboard_resource_name,\n tensorboard_experiment=tb_experiment,\n tensorboard_experiment_id=self._experiment_name,\n )\n self._is_brand_new_experiment = True\n except exceptions.AlreadyExists:\n logger.info(\"Creating experiment failed. Retrieving experiment.\")\n experiment_name = os.path.join(\n self._tensorboard_resource_name, \"experiments\", self._experiment_name\n )\n experiment = self._api.get_tensorboard_experiment(name=experiment_name)\n return experiment","def create_experiment(name='exp', database=None):\n ex = Experiment(name)\n\n atlas_user = os.environ.get('MONGO_DB_USER')\n atlas_password = os.environ.get('MONGO_DB_PASS')\n atlas_host = os.environ.get('MONGO_DB_HOST')\n\n # Add remote MongoDB observer, only if environment variables are set\n if atlas_user and atlas_password and atlas_host:\n ex.observers.append(MongoObserver(\n url=f\"mongodb+srv://{atlas_user}:{atlas_password}@{atlas_host}\",\n db_name=database))\n return ex","def newExperiment(self):\n experiment = Experiment()\n newtitle = 'Untitled ' + self.getNextUntitled()\n experimentFrame = SequenceFrame(self, experiment, True, newtitle)\n experiment.setInteractionParameters(parentFrame=experimentFrame,\n graphManagerClass=StandardGraphManager)\n self.frames.append(experimentFrame)\n self.names.append(newtitle)\n log.info('Created experiment ' + newtitle)\n experimentFrame.Show()\n testFrame = tf.TestingFrame(experimentFrame, experiment)\n testFrame.Show()\n self.Show(False)","def experiment(self) -> Run:\n if self._experiment is None:\n self._experiment = self.create_experiment()\n return self._experiment","def create(self, request):\n serializer = ExperimentSerializer(data=request.data)\n if serializer.is_valid():\n serializer.save()\n\n return send_response(request.method, serializer)","def create_experiment(self):\n\n experiment = self._create_or_get_experiment()\n self._experiment = experiment\n self._one_platform_resource_manager = uploader_utils.OnePlatformResourceManager(\n self._experiment.name, self._api\n )\n\n self._request_sender = _BatchedRequestSender(\n self._experiment.name,\n self._api,\n allowed_plugins=self._allowed_plugins,\n upload_limits=self._upload_limits,\n rpc_rate_limiter=self._rpc_rate_limiter,\n tensor_rpc_rate_limiter=self._tensor_rpc_rate_limiter,\n blob_rpc_rate_limiter=self._blob_rpc_rate_limiter,\n blob_storage_bucket=self._blob_storage_bucket,\n blob_storage_folder=self._blob_storage_folder,\n one_platform_resource_manager=self._one_platform_resource_manager,\n tracker=self._tracker,\n )\n\n # Update partials with experiment name\n for sender in self._additional_senders.keys():\n self._additional_senders[sender] = self._additional_senders[sender](\n experiment_resource_name=self._experiment.name,\n )\n\n self._dispatcher = _Dispatcher(\n request_sender=self._request_sender,\n additional_senders=self._additional_senders,\n )","def create_experiment_v1(self, skill_id, create_experiment_request, **kwargs):\n # type: (str, CreateExperimentRequest_abced22d, **Any) -> Union[ApiResponse, object, StandardizedError_f5106a89, BadRequestError_f854b05]\n operation_name = \"create_experiment_v1\"\n params = locals()\n for key, val in six.iteritems(params['kwargs']):\n params[key] = val\n del params['kwargs']\n # verify the required parameter 'skill_id' is set\n if ('skill_id' not in params) or (params['skill_id'] is None):\n raise ValueError(\n \"Missing the required parameter `skill_id` when calling `\" + operation_name + \"`\")\n # verify the required parameter 'create_experiment_request' is set\n if ('create_experiment_request' not in params) or (params['create_experiment_request'] is None):\n raise ValueError(\n \"Missing the required parameter `create_experiment_request` when calling `\" + operation_name + \"`\")\n\n resource_path = '/v1/skills/{skillId}/experiments'\n resource_path = resource_path.replace('{format}', 'json')\n\n path_params = {} # type: Dict\n if 'skill_id' in params:\n path_params['skillId'] = params['skill_id']\n\n query_params = [] # type: List\n\n header_params = [] # type: List\n\n body_params = None\n if 'create_experiment_request' in params:\n body_params = params['create_experiment_request']\n header_params.append(('Content-type', 'application/json'))\n header_params.append(('User-Agent', self.user_agent))\n\n # Response Type\n full_response = False\n if 'full_response' in params:\n full_response = params['full_response']\n\n # Authentication setting\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\n authorization_value = \"Bearer \" + access_token\n header_params.append(('Authorization', authorization_value))\n\n error_definitions = [] # type: List\n error_definitions.append(ServiceClientResponse(response_type=None, status_code=201, message=\"Experiment created. Returns the generated experiment identifier in 'Location' header.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.bad_request_error.BadRequestError\", status_code=400, message=\"Server cannot process the request due to a client error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=401, message=\"The auth token is invalid/expired or doesn't have access to the resource.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.bad_request_error.BadRequestError\", status_code=403, message=\"The operation being requested is not allowed.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=404, message=\"The resource being requested is not found.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=429, message=\"Exceeds the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=500, message=\"Internal Server Error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=503, message=\"Service Unavailable.\"))\n\n api_response = self.invoke(\n method=\"POST\",\n endpoint=self._api_endpoint,\n path=resource_path,\n path_params=path_params,\n query_params=query_params,\n header_params=header_params,\n body=body_params,\n response_definitions=error_definitions,\n response_type=None)\n\n if full_response:\n return api_response\n \n return None","def create_experiment(\n self,\n name: str,\n description: str = None,\n namespace: str = None) -> kfp_server_api.V1Experiment:\n namespace = namespace or self.get_user_namespace()\n experiment = None\n try:\n experiment = self.get_experiment(\n experiment_name=name, namespace=namespace)\n except ValueError as error:\n # Ignore error if the experiment does not exist.\n if not str(error).startswith('No experiment is found with name'):\n raise error\n\n if not experiment:\n logging.info('Creating experiment {}.'.format(name))\n\n resource_references = []\n if namespace:\n key = kfp_server_api.models.V1ResourceKey(\n id=namespace,\n type=kfp_server_api.models.V1ResourceType.NAMESPACE)\n reference = kfp_server_api.models.V1ResourceReference(\n key=key,\n relationship=kfp_server_api.models.V1Relationship.OWNER)\n resource_references.append(reference)\n\n experiment = kfp_server_api.models.V1Experiment(\n name=name,\n description=description,\n resource_references=resource_references)\n experiment = self._experiment_api.create_experiment(body=experiment)\n\n if self._is_ipython():\n import IPython\n html = \\\n ('<a href=\"%s/#/experiments/details/%s\" target=\"_blank\" >Experiment details</a>.'\n % (self._get_url_prefix(), experiment.id))\n IPython.display.display(IPython.display.HTML(html))\n return experiment","def test_create_experiment_hit_no_config(self):\n with OrionState(experiments=[config]) as cfg:\n experiment = create_experiment(config[\"name\"], storage=cfg.storage_config)\n\n assert experiment.name == config[\"name\"]\n assert experiment.version == 1\n assert experiment.space.configuration == config[\"space\"]\n assert experiment.algorithm\n assert experiment.algorithm.configuration == config[\"algorithm\"]\n assert experiment.max_trials == config[\"max_trials\"]\n assert experiment.max_broken == config[\"max_broken\"]\n assert experiment.working_dir == config[\"working_dir\"]","def test_create_experiment_no_storage(self, monkeypatch):\n name = \"oopsie_forgot_a_storage\"\n host = orion.core.config.storage.database.host\n\n with OrionState(storage=orion.core.config.storage.to_dict()) as cfg:\n # Reset the Storage and drop instances so that setup_storage() would fail.\n cfg.cleanup()\n\n # Make sure storage must be instantiated during `create_experiment()`\n # with pytest.raises(SingletonNotInstantiatedError):\n # setup_storage()\n\n experiment = create_experiment(\n name=name, space={\"x\": \"uniform(0, 10)\"}, storage=cfg.storage_config\n )\n\n assert isinstance(experiment._experiment._storage, Legacy)\n assert isinstance(experiment._experiment._storage._db, PickledDB)\n assert experiment._experiment._storage._db.host == host","def test_create_experiment_new_no_space(self):\n with OrionState() as cfg:\n name = \"oopsie_forgot_a_space\"\n with pytest.raises(NoConfigurationError) as exc:\n create_experiment(name=name, storage=cfg.storage_config)\n\n assert f\"Experiment {name} does not exist in DB\" in str(exc.value)","def test_create_experiment_new_default(self):\n name = \"all_default\"\n space = {\"x\": \"uniform(0, 10)\"}\n with OrionState() as cfg:\n experiment = create_experiment(\n name=\"all_default\", space=space, storage=cfg.storage_config\n )\n\n assert experiment.name == name\n assert experiment.space.configuration == space\n\n assert experiment.max_trials == orion.core.config.experiment.max_trials\n assert experiment.max_broken == orion.core.config.experiment.max_broken\n assert experiment.working_dir == orion.core.config.experiment.working_dir\n assert experiment.algorithm\n assert experiment.algorithm.configuration == {\"random\": {\"seed\": None}}","def experiment_init(self):\n raise NotImplementedError(\"this needs to be implemented!\")","def main(_):\n description = xm.ExperimentDescription(\n FLAGS.exp_name, tags=[\n FLAGS.env_name,\n ])\n experiment = build_experiment()\n xm.launch_experiment(description, experiment)","def with_experiment_using_python_api(storage, monkeypatch, one_experiment):\n experiment = experiment_builder.build(\n name=\"from-python-api\", space={\"x\": \"uniform(0, 10)\"}, storage=storage\n )\n\n return experiment","def _populate_exp(self):\n self._exp = self.volume_provider.get_project(\n ExperimentResource(self._channel.exp_name, self._channel.coll_name)\n )","def __init__(self, exp_params, stamp_unique=True):\n self._main_thread = True\n self.params = copy.deepcopy(exp_params)\n self.params['class'] = self.__class__.__name__\n self._check_required_params()\n self.__check_exist_path()\n self.__create_folder(stamp_unique)\n set_experiment_logger(self.params['path_exp'], FILE_LOGS)\n # set stream logging to info level\n for lh in logging.getLogger().handlers:\n if isinstance(lh, logging.StreamHandler) and \\\n not isinstance(lh, logging.FileHandler):\n lh.setLevel(logging.INFO)\n logging.info('initialise experiment...')\n logging.info(string_dict(self.params, 'PARAMETERS:'))\n logging.info('COMPUTER: %r', computer_info())","def experiment_init(self):\n pass","def add_experiment(redis, name):\n\n if not ALLOWED_NAMES.match(name):\n raise ExperimentException(name, \"Illegal name\")\n if redis.exists(EXPERIMENT_REDIS_KEY_TEMPLATE % name):\n raise ExperimentException(name, \"Already exists\")\n\n json = dict(creation_date=util.unicode_type(datetime.datetime.now()))\n pipe = redis.pipeline(transaction=True)\n pipe.sadd(ACTIVE_EXPERIMENTS_REDIS_KEY, name)\n pipe.hset(EXPERIMENT_REDIS_KEY_TEMPLATE % name, \"metadata\", escape.json_encode(json))\n pipe.execute()\n return Experiment(redis, name)","def experiments_init(self):\n pass","def __init__(self, experiment, **kwargs):\n \n # retrieve which experiment to run\n experiment_function = getattr(self, experiment)\n\n if kwargs:\n kwargs['experiment']=experiment\n experiment_function(**kwargs)\n\n else:\n kwargs={'experiment':experiment}\n experiment_function(**kwargs)","def create_eval(self):\n self.ev_id = \"ev-\" + base64.b32encode(os.urandom(10)).decode(\"ascii\")\n self.ev_name = \"Evaluation: \" + self.ml_name\n self._ml.create_evaluation(\n EvaluationId=self.ev_id,\n EvaluationName=self.ev_name,\n MLModelId=self.ml_id,\n EvaluationDataSourceId=self.fold.eval_ds_id\n )\n logger.info(\"Created Evaluation \" + self.ev_id)","def test_load_experiment(self):\n exp = Experiment(self.epath,\n normalization='ch0',\n auto_alignment=False)\n self.assertTrue(isinstance(exp, Experiment))","def _onNew(self, event):\n self.newExperiment()","def run_new_session(self, experiment_id, epochs, log_base_path='logs',\n model_checkpoint_period=2,\n prediction_checkpoint_period=2):\n exp = ExperimentDB(\n self.dbclient, experiment_id=experiment_id,\n log_base_path=log_base_path\n ).run_experiment(\n model_checkpoint_period=model_checkpoint_period,\n prediction_checkpoint_period=prediction_checkpoint_period,\n save_origin_images=False, verbose=1, epochs=epochs)\n\n return exp","def create_experiment(output_dir, X, y, train_steps=1000, num_units=7, output_units=1, num_layers=1):\n\n config = {\n 'name': 'time_series',\n 'output_dir': output_dir,\n 'eval_every_n_steps': 100,\n 'train_steps_per_iteration': 100,\n 'train_steps': train_steps,\n 'run_config': {'save_checkpoints_steps': 100},\n 'train_input_data_config': {\n 'input_type': plx.configs.InputDataConfig.NUMPY,\n 'pipeline_config': {'name': 'train', 'batch_size': 64, 'num_epochs': None,\n 'shuffle': False},\n 'x': {'x': X['train']},\n 'y': y['train']\n },\n 'eval_input_data_config': {\n 'input_type': plx.configs.InputDataConfig.NUMPY,\n 'pipeline_config': {'name': 'eval', 'batch_size': 32, 'num_epochs': None,\n 'shuffle': False},\n 'x': {'x': X['val']},\n 'y': y['val']\n },\n 'estimator_config': {'output_dir': output_dir},\n 'model_config': {\n 'module': 'Regressor',\n 'loss_config': {'module': 'mean_squared_error'},\n 'eval_metrics_config': [{'module': 'streaming_root_mean_squared_error'},\n {'module': 'streaming_mean_absolute_error'}],\n 'optimizer_config': {'module': 'adagrad', 'learning_rate': 0.1},\n 'graph_config': {\n 'name': 'regressor',\n 'features': ['x'],\n 'definition': [\n (plx.layers.LSTM, {'num_units': num_units, 'num_layers': num_layers}),\n (plx.layers.FullyConnected, {'num_units': output_units}),\n ]\n }\n }\n }\n experiment_config = plx.configs.ExperimentConfig.read_configs(config)\n return plx.experiments.create_experiment(experiment_config)","def add_experiment(self, environment_name, environment_builder_params, agent_name, agent_builder_params):\n if environment_name in self.environment_list:\n if agent_name in self.experiment_structure[environment_name]:\n raise AttributeError('An experiment for environment {} and builders {} already exists.'.format(environment_name, agent_name))\n else:\n self.experiment_structure[environment_name][agent_name] = self._create_experiment(environment_name, environment_builder_params, agent_name, agent_builder_params)\n else:\n self.environment_list.append(environment_name)\n self.experiment_structure[environment_name] = {agent_name: self._create_experiment(environment_name, environment_builder_params, agent_name, agent_builder_params)}\n \n if agent_name not in self.agent_list:\n self.agent_list.append(agent_name)","def __init__(self, experiment_data):\n self._experiment_data = experiment_data","def openExperiment(self):\n ext = _EXTS_EXPERIMENT[0]\n wildcard = 'Transport experiment (*.%s)|*.%s' % (ext, ext)\n dialog = wx.FileDialog(self, \"Open Experiment\", c.getExperimentFolder(),\n '', wildcard, wx.FD_OPEN)\n if dialog.ShowModal() == wx.ID_OK:\n experimentPath = dialog.GetPath()\n experimentName = os.path.basename(experimentPath)\n if experimentName.endswith(ext):\n experimentName = experimentName[:-len(ext)-1]\n experiment = loader.loadExperiment(experimentPath)\n frame = SequenceFrame(self, experiment, False,\n title=experimentName,\n experimentPath=experimentPath)\n experiment.setInteractionParameters(parentFrame=frame,\n graphManagerClass=StandardGraphManager)\n self.frames.append(frame)\n self.names.append(experimentName)\n log.info('Opened experiment ' + experimentName)\n frame.Show()\n self.Show(False)","def Experiment(self, default=None):\n return self.data.get('experiment', default)","def get_config():\n return ExperimentConfig(base_path=os.getenv(\"AICROWD_OUTPUT_PATH\", \"./scratch/shared\"),\n experiment_name=os.getenv(\"AICROWD_EVALUATION_NAME\", \"experiment_name\"),\n dataset_name=os.getenv(\"AICROWD_DATASET_NAME\", \"cars3d\"))","def __init__(self, agent_id=\"default\", experiment_id=\"default\"):\n self.runtime = runtime()\n self.agent_id = agent_id\n self.experiment_id = experiment_id","def _create_new_experiment_dir(self):\n ls = os.listdir(self.experiment_dir)\n existing_exp_dirs = [d for d in ls if d.startswith('experiment')]\n if len(existing_exp_dirs) == 0:\n out = 'experiment1'\n else:\n inds = [int(d.lstrip('experiment')) for d in existing_exp_dirs]\n out = 'experiment'+str(max(inds)+1)\n\n self.new_experiment_dir = os.path.join(self.experiment_dir, out)\n os.mkdir(self.new_experiment_dir)\n return None","def start(self, config):\n self.config = config\n\n # create experiment folder, initialize config, exp_info\n print(\"creating new experiment folder...\")\n self._create_new_experiment_dir()\n self.config_path = os.path.join(self.new_experiment_dir, 'experiment.config')\n self.experiment_info_path = os.path.join(self.new_experiment_dir, 'info.txt')\n\n # save config\n print(\"saving experiment config...\")\n self._write_config(self.config_path)\n\n # save experiment info\n print(\"saving experiment info...\")\n self._write_experiment_info(self.experiment_info_path)\n\n return None","def start_experiment():\r\n check_parameters()\r\n try:\r\n EXP.start()\r\n except InputError as inst:\r\n tkMessageBox.showinfo(inst.expr, inst.msg)","def test_create_experiment_new_full_config(self, user_config):\n with OrionState() as cfg:\n experiment = create_experiment(**user_config, storage=cfg.storage_config)\n\n exp_config = experiment.configuration\n\n assert exp_config[\"space\"] == config[\"space\"]\n assert exp_config[\"max_trials\"] == config[\"max_trials\"]\n assert exp_config[\"max_broken\"] == config[\"max_broken\"]\n assert exp_config[\"working_dir\"] == config[\"working_dir\"]\n assert exp_config[\"algorithm\"] == config[\"algorithm\"]","def with_experiment_params(self, **params):\n self.experiment_params = params\n return self","def test_create_experiment_hit_no_branch(self, user_config):\n with OrionState(experiments=[config]) as cfg:\n experiment = create_experiment(**user_config, storage=cfg.storage_config)\n\n exp_config = experiment.configuration\n\n assert experiment.name == config[\"name\"]\n assert experiment.version == 1\n assert exp_config[\"space\"] == config[\"space\"]\n assert exp_config[\"max_trials\"] == config[\"max_trials\"]\n assert exp_config[\"max_broken\"] == config[\"max_broken\"]\n assert exp_config[\"working_dir\"] == config[\"working_dir\"]\n assert exp_config[\"algorithm\"] == config[\"algorithm\"]","def only_experiments_db(storage, exp_config):\n for exp in exp_config[0]:\n storage.create_experiment(exp)","def get_experiment_v1(self, skill_id, experiment_id, **kwargs):\n # type: (str, str, **Any) -> Union[ApiResponse, object, GetExperimentResponse_fcd92c35, StandardizedError_f5106a89, BadRequestError_f854b05]\n operation_name = \"get_experiment_v1\"\n params = locals()\n for key, val in six.iteritems(params['kwargs']):\n params[key] = val\n del params['kwargs']\n # verify the required parameter 'skill_id' is set\n if ('skill_id' not in params) or (params['skill_id'] is None):\n raise ValueError(\n \"Missing the required parameter `skill_id` when calling `\" + operation_name + \"`\")\n # verify the required parameter 'experiment_id' is set\n if ('experiment_id' not in params) or (params['experiment_id'] is None):\n raise ValueError(\n \"Missing the required parameter `experiment_id` when calling `\" + operation_name + \"`\")\n\n resource_path = '/v1/skills/{skillId}/experiments/{experimentId}'\n resource_path = resource_path.replace('{format}', 'json')\n\n path_params = {} # type: Dict\n if 'skill_id' in params:\n path_params['skillId'] = params['skill_id']\n if 'experiment_id' in params:\n path_params['experimentId'] = params['experiment_id']\n\n query_params = [] # type: List\n\n header_params = [] # type: List\n\n body_params = None\n header_params.append(('Content-type', 'application/json'))\n header_params.append(('User-Agent', self.user_agent))\n\n # Response Type\n full_response = False\n if 'full_response' in params:\n full_response = params['full_response']\n\n # Authentication setting\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\n authorization_value = \"Bearer \" + access_token\n header_params.append(('Authorization', authorization_value))\n\n error_definitions = [] # type: List\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.experiment.get_experiment_response.GetExperimentResponse\", status_code=200, message=\"Returned skill experiment.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=401, message=\"The auth token is invalid/expired or doesn't have access to the resource.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.bad_request_error.BadRequestError\", status_code=403, message=\"The operation being requested is not allowed.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=404, message=\"The resource being requested is not found.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=429, message=\"Exceeds the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=500, message=\"Internal Server Error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=503, message=\"Service Unavailable.\"))\n\n api_response = self.invoke(\n method=\"GET\",\n endpoint=self._api_endpoint,\n path=resource_path,\n path_params=path_params,\n query_params=query_params,\n header_params=header_params,\n body=body_params,\n response_definitions=error_definitions,\n response_type=\"ask_smapi_model.v1.skill.experiment.get_experiment_response.GetExperimentResponse\")\n\n if full_response:\n return api_response\n return api_response.body","def with_experiment_missing_conf_file(monkeypatch, one_experiment, storage, orionstate):\n exp = experiment_builder.build(name=\"test_single_exp\", version=1, storage=storage)\n conf_file = \"idontexist.yaml\"\n exp.metadata[\"user_config\"] = conf_file\n exp.metadata[\"user_args\"] += [\"--config\", conf_file]\n\n orionstate.database.write(\"experiments\", exp.configuration, query={\"_id\": exp.id})\n\n return exp","def test_create_experiment_debug_mode(self, tmp_path):\n\n conf_file = str(tmp_path / \"db.pkl\")\n\n experiment = create_experiment(\n config[\"name\"],\n space={\"x\": \"uniform(0, 10)\"},\n storage={\n \"type\": \"legacy\",\n \"database\": {\"type\": \"pickleddb\", \"host\": conf_file},\n },\n )\n\n storage = experiment._experiment._storage\n assert isinstance(storage, Legacy)\n assert isinstance(storage._db, PickledDB)\n\n experiment = create_experiment(\n config[\"name\"],\n space={\"x\": \"uniform(0, 10)\"},\n storage={\"type\": \"legacy\", \"database\": {\"type\": \"pickleddb\"}},\n debug=True,\n )\n\n storage = experiment._experiment._storage\n assert isinstance(storage, Legacy)\n assert isinstance(storage._db, EphemeralDB)","def test_create_experiment(client, users):\n login_experimenter(client)\n\n exp = ExperimentFactory()\n datetime_format = \"%Y-%m-%d %H:%M:%S\"\n\n response = client.post(\"/experiments/\", data=dict(\n name=exp.name,\n start=exp.start.strftime(datetime_format),\n stop=exp.stop.strftime(datetime_format),\n blurb=exp.blurb))\n assert response.status_code == 200\n assert json_success(response.data)\n\n response = client.get(\"/experiments/\")\n data = response.data.decode(response.charset)\n assert response.status_code == 200\n assert exp.name in data\n\n response = client.post(\"/experiments/\", data=dict(\n start=exp.start.strftime(datetime_format),\n stop=exp.stop.strftime(datetime_format),\n blurb=exp.blurb))\n data = response.data.decode(response.charset)\n json_data = json.loads(data)\n assert json_data[\"success\"] == 0\n assert json_data[\"errors\"]\n\n response = client.post(\"/experiments/\", data=dict(\n name=exp.name,\n start=exp.start.strftime(datetime_format),\n stop=exp.start.strftime(datetime_format),\n blurb=exp.blurb))\n data = response.data.decode(response.charset)\n json_data = json.loads(data)\n assert json_data[\"success\"] == 0\n assert json_data[\"errors\"]\n\n response = client.post(\"/experiments/\", data=dict(\n name=exp.name,\n start=(datetime.now() - timedelta(days=5)).strftime(datetime_format),\n stop=(datetime.now() - timedelta(days=1)).strftime(datetime_format),\n blurb=exp.blurb))\n data = response.data.decode(response.charset)\n json_data = json.loads(data)\n assert json_data[\"success\"] == 0\n assert json_data[\"errors\"]","def test_create_experiment_bad_storage(self):\n name = \"oopsie_bad_storage\"\n # Make sure there is no existing storage singleton\n\n with pytest.raises(NotImplementedError) as exc:\n create_experiment(\n name=name,\n storage={\"type\": \"legacy\", \"database\": {\"type\": \"idontexist\"}},\n )\n\n assert \"Could not find implementation of Database, type = 'idontexist'\" in str(\n exc.value\n )","def one_experiment(monkeypatch, storage):\n monkeypatch.chdir(os.path.dirname(os.path.abspath(__file__)))\n name = \"test_single_exp\"\n orion.core.cli.main(\n [\"hunt\", \"--init-only\", \"-n\", name, \"./black_box.py\", \"--x~uniform(0,1)\"]\n )\n ensure_deterministic_id(name, storage)\n return storage.fetch_experiments({\"name\": name})[0]","def run(self, *args, **kwargs):\n from klibs.KLGraphics.KLDraw import Ellipse\n \n if P.eye_tracking:\n RED = (255, 0, 0)\n WHITE = (255, 255, 255)\n self.tracker_dot = Ellipse(8, stroke=[2, WHITE], fill=RED).render()\n if not P.manual_eyelink_setup:\n self.el.setup()\n\n self.setup()\n try:\n self.__execute_experiment__(*args, **kwargs)\n except RuntimeError:\n print(full_trace())\n\n self.quit()","def test_expand_experiments():\n template_script = get_template_script()\n experiment_systems = utils.CombinatorialLeaf(['explicit-system', 'implicit-system', 'hydration-system'])\n template_script['experiments']['system'] = experiment_systems\n\n exp_builder = ExperimentBuilder(script=template_script, job_id=1, n_jobs=2)\n experiments = list(exp_builder._expand_experiments())\n assert len(experiments) == 2\n\n exp_builder = ExperimentBuilder(script=template_script, job_id=2, n_jobs=2)\n experiments = list(exp_builder._expand_experiments())\n assert len(experiments) == 1","def experiment_pb(\n hparam_infos,\n metric_infos,\n user=\"\",\n description=\"\",\n time_created_secs=None):\n if time_created_secs is None:\n time_created_secs = time.time()\n experiment = api_pb2.Experiment(\n description=description,\n user=user,\n time_created_secs=time_created_secs,\n hparam_infos=hparam_infos,\n metric_infos=metric_infos)\n return _summary(metadata.EXPERIMENT_TAG,\n plugin_data_pb2.HParamsPluginData(experiment=experiment))","def delete(ctx):\n user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'),\n ctx.obj.get('experiment'))\n if not click.confirm(\"Are sure you want to delete experiment `{}`\".format(_experiment)):\n click.echo('Existing without deleting experiment.')\n sys.exit(1)\n\n try:\n response = PolyaxonClient().experiment.delete_experiment(\n user, project_name, _experiment)\n # Purge caching\n ExperimentManager.purge()\n except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e:\n Printer.print_error('Could not delete experiment `{}`.'.format(_experiment))\n Printer.print_error('Error message `{}`.'.format(e))\n sys.exit(1)\n\n if response.status_code == 204:\n Printer.print_success(\"Experiment `{}` was delete successfully\".format(_experiment))","def create_mlflow_experiment(experiment_name: Text, mode: oct = 0o777) -> int:\n\n mlflow.set_experiment(experiment_name)\n experiment = mlflow.get_experiment_by_name(experiment_name)\n artifact_location = experiment.artifact_location.replace('file://', '')\n\n if not os.path.exists(artifact_location):\n os.mkdir(artifact_location)\n os.chmod(artifact_location, mode) # Change the access permissions\n\n return experiment.experiment_id","def test_init(self):\n ex = Experiment(note=\"Test\")\n self.assertEqual(ex.note, \"Test\")","def _load_experiment(\n experiment_name: str, decoder: Decoder, reduced_state: bool = False\n) -> Experiment:\n # Convert SQA to user-facing class outside of session scope to avoid timeouts\n return decoder.experiment_from_sqa(\n experiment_sqa=_get_experiment_sqa_reduced_state(\n experiment_name=experiment_name, decoder=decoder\n )\n if reduced_state\n else _get_experiment_sqa(experiment_name=experiment_name, decoder=decoder),\n reduced_state=reduced_state,\n )","def test_run_experiment_locally(self) -> None:\n\n experiment = Experiment(\n name=\"torchx_booth_sequential_demo\",\n search_space=SearchSpace(parameters=self._parameters),\n optimization_config=OptimizationConfig(objective=self._objective),\n runner=self._runner,\n is_test=True,\n properties={Keys.IMMUTABLE_SEARCH_SPACE_AND_OPT_CONF: True},\n )\n\n scheduler = Scheduler(\n experiment=experiment,\n generation_strategy=(\n choose_generation_strategy(\n search_space=experiment.search_space,\n )\n ),\n options=SchedulerOptions(),\n )\n\n try:\n for _ in range(3):\n scheduler.run_n_trials(max_trials=2)\n\n # TorchXMetric always returns trial index; hence the best experiment\n # for min objective will be the params for trial 0.\n scheduler.report_results()\n except FailureRateExceededError:\n pass # TODO(ehotaj): Figure out why this test fails in OSS.\n # Nothing to assert, just make sure experiment runs.","def _create_sample_episode(self) -> study_pb2.Episode:\n study_id, session_id = self.init_session()\n episode = sample_episode(study_id=study_id, session_id=session_id)\n self.storage.create_episode(episode)\n return episode","def test_run_experiment():\n with mmtools.utils.temporary_directory() as tmp_dir:\n yaml_content = \"\"\"\n ---\n options:\n resume_setup: no\n resume_simulation: no\n default_number_of_iterations: 0\n output_dir: {}\n setup_dir: ''\n experiments_dir: ''\n minimize: no\n annihilate_sterics: yes\n molecules:\n T4lysozyme:\n filepath: {}\n leap: {{parameters: oldff/leaprc.ff14SB}}\n select: 0\n p-xylene:\n filepath: {}\n antechamber: {{charge_method: bcc}}\n leap: {{parameters: leaprc.gaff}}\n solvents:\n vacuum:\n nonbonded_method: NoCutoff\n GBSA-OBC2:\n nonbonded_method: NoCutoff\n implicit_solvent: OBC2\n protocols:{}\n systems:\n system:\n receptor: T4lysozyme\n ligand: p-xylene\n solvent: !Combinatorial [vacuum, GBSA-OBC2]\n experiments:\n system: system\n protocol: absolute-binding\n restraint:\n type: FlatBottom\n spring_constant: 0.6*kilocalorie_per_mole/angstroms**2\n well_radius: 5.2*nanometers\n restrained_receptor_atoms: 1644\n restrained_ligand_atoms: 2609\n options:\n temperature: 302.0*kelvin\n \"\"\".format(tmp_dir, examples_paths()['lysozyme'], examples_paths()['p-xylene'],\n indent(standard_protocol))\n\n exp_builder = ExperimentBuilder(textwrap.dedent(yaml_content))\n\n # Now check_setup_resume should not raise exceptions\n exp_builder._check_resume()\n\n # We setup a molecule and with resume_setup: now we can't do the experiment\n err_msg = ''\n exp_builder._options['resume_setup'] = False\n exp_builder._db._setup_molecules('p-xylene')\n try:\n exp_builder.run_experiments()\n except YamlParseError as e:\n err_msg = str(e)\n assert 'molecule' in err_msg\n\n # Same thing with a system\n err_msg = ''\n system_dir = os.path.dirname(\n exp_builder._db.get_system('system_GBSAOBC2')[0].position_path)\n try:\n exp_builder.run_experiments()\n except YamlParseError as e:\n err_msg = str(e)\n assert 'system' in err_msg\n\n # Now we set resume_setup to True and things work\n exp_builder._options['resume_setup'] = True\n ligand_dir = exp_builder._db.get_molecule_dir('p-xylene')\n frcmod_file = os.path.join(ligand_dir, 'p-xylene.frcmod')\n prmtop_file = os.path.join(system_dir, 'complex.prmtop')\n molecule_last_touched = os.stat(frcmod_file).st_mtime\n system_last_touched = os.stat(prmtop_file).st_mtime\n exp_builder.run_experiments()\n\n # Neither the system nor the molecule has been processed again\n assert molecule_last_touched == os.stat(frcmod_file).st_mtime\n assert system_last_touched == os.stat(prmtop_file).st_mtime\n\n # The experiments folders are correctly named and positioned\n for exp_name in ['systemvacuum', 'systemGBSAOBC2']:\n # The output directory must be the one in the experiment section\n output_dir = os.path.join(tmp_dir, exp_name)\n assert os.path.isdir(output_dir)\n assert os.path.isfile(os.path.join(output_dir, 'complex.nc'))\n assert os.path.isfile(os.path.join(output_dir, 'solvent.nc'))\n assert os.path.isfile(os.path.join(output_dir, exp_name + '.yaml'))\n assert os.path.isfile(os.path.join(output_dir, exp_name + '.log'))\n\n # Analysis script is correct\n analysis_script_path = os.path.join(output_dir, 'analysis.yaml')\n with open(analysis_script_path, 'r') as f:\n assert yaml.load(f, Loader=yaml.FullLoader) == [['complex', 1], ['solvent', -1]]\n\n # Now we can't run the experiment again with resume_simulation: no\n exp_builder._options['resume_simulation'] = False\n try:\n exp_builder.run_experiments()\n except YamlParseError as e:\n err_msg = str(e)\n assert 'experiment' in err_msg\n\n # We set resume_simulation: yes and now things work\n exp_builder._options['resume_simulation'] = True\n exp_builder.run_experiments()","def main(_):\n description = xm.ExperimentDescription(\n 'HIS - trial=%d' % FLAGS.trial, tags=['his'])\n experiment = build_experiment()\n xm.launch_experiment(description, experiment)","def new_experiment_from_components(self, dataset_params, input_params,\n architecture, model_params,\n train_params=None,\n name='', description=''):\n exp_name = name or ''\n try:\n # find each component by id then create the full JSON\n dataset_params_obj = self.dbclient.find_by_id(\n ConfigRef.DATASET_PARAMS, dataset_params)\n dataset_params_cf = dataset_params_obj[RefAttr.CONFIG]\n\n input_params_obj = self.dbclient.find_by_id(\n ConfigRef.INPUT_PARAMS, input_params)\n input_params_cf = input_params_obj[RefAttr.CONFIG]\n\n architecture_obj = self.dbclient.find_by_id(\n ConfigRef.ARCHITECTURE, architecture)\n architecture_cf = architecture_obj[RefAttr.CONFIG]\n\n model_params_obj = self.dbclient.find_by_id(\n ConfigRef.MODEL_PARAMS, model_params)\n model_params_cf = model_params_obj[RefAttr.CONFIG]\n\n if train_params:\n train_params_obj = self.dbclient.find_by_id(\n ConfigRef.TRAIN_PARAMS, train_params)\n train_params_cf = train_params_obj[RefAttr.CONFIG]\n else:\n train_params_cf = '{ }'\n\n config = self._new_config_from_components(\n dataset_params_cf, input_params_cf, architecture_cf,\n model_params_cf, train_params_cf\n )\n\n if not name:\n exp_name = ' - '.join([\n dataset_params_obj[RefAttr.NAME],\n input_params_obj[RefAttr.NAME],\n architecture_obj[RefAttr.NAME],\n model_params_obj[RefAttr.NAME],\n train_params_obj[RefAttr.NAME] if train_params else '',\n ])\n return self.new_experiment_from_full_config(\n exp_name, config, description=description)\n except Exception:\n return None","def set_experiment(self, new_exp=False):\n self.id = str(self.Id_widget.text()).strip()\n if self.id == '' or self.working_dir is None:\n msg_window('id and working directory must be entered')\n return\n conf_map = {}\n\n self.scan = str(self.scan_widget.text()).replace(' ', '')\n if len(self.scan) > 0:\n scans = self.scan.split('-')\n if len(scans) > 2:\n msg_window('if entering scan or scan range, please enter numeric values, separated with \"-\" if range')\n return\n for sc in scans:\n try:\n numeric = int(sc)\n except:\n msg_window(\n 'if entering scan or scan range, please enter numeric values, separated with \"-\" if range')\n return\n conf_map['scan'] = '\"' + self.scan + '\"'\n self.exp_id = self.id + '_' + self.scan\n\n else:\n self.exp_id = self.id\n self.experiment_dir = os.path.join(self.working_dir, self.exp_id)\n self.assure_experiment_dir()\n\n if not new_exp:\n # read the configurations from GUI and write to experiment config files\n # save the main config\n conf_map['working_dir'] = '\"' + str(self.working_dir).strip() + '\"'\n conf_map['experiment_id'] = '\"' + self.id + '\"'\n if len(self.beamline_widget.text().strip()) > 0:\n conf_map['beamline'] = '\"' + str(self.beamline_widget.text().strip()) + '\"'\n self.beamline = self.beamline_widget.text().strip()\n if self.specfile is not None:\n conf_map['specfile'] = '\"' + str(self.specfile).strip() + '\"'\n write_conf(conf_map, os.path.join(self.experiment_dir, 'conf'), 'config')\n\n if self.t is None:\n try:\n self.t = Tabs(self)\n self.vbox.addWidget(self.t)\n except:\n pass\n\n if not new_exp:\n self.t.save_conf()","def main():\n ex = Experiment(SEED)\n ex.main()","def new(cls, etype, ecode, evalue, time=None):\n e = cls()\n e.set(etype, ecode, evalue, time)\n return e","def setExperiment(self, **kwargs):\n # If the dictionary robot value is 'tb1' then change the button Style\n global robot_Selected_Value\n if kwargs['robot'] =='1':\n robot_Selected_Value = 'TB1'\n elif kwargs['robot'] =='2':\n robot_Selected_Value = 'TB2'\n elif kwargs['robot'] =='3':\n robot_Selected_Value = 'TB3'\n elif kwargs['robot'] =='4':\n robot_Selected_Value = 'TB4'\n elif kwargs['set'] =='OK':\n # CONFIGURATION VARIABLES\n robot_Type_Value = self.robot_Selection_Type.currentText()\n robot_Role_Value = self.robot_Selection_Role.currentText()\n robot_Task_Value = self.robot_Selection_Task.currentText()\n robot_Behavior_Value = self.robot_Selection_Behavior.currentText()\n robot_Experiment_Value = self.robot_Selection_Experiment.currentText()\n # XML CREATION\n environmentXMLFile = et.Element('EXP_CONFIGURATIONS')\n comment = et.Comment(\"Experiment Configuration and Variables\")\n environmentXMLFile.append(comment)\n environmentConfig = et.SubElement(environmentXMLFile, 'ROBOT_SELECTED')\n environmentConfig.text = str(robot_Selected_Value)\n environmentConfig = et.SubElement(environmentXMLFile, 'ROBOT_TYPE')\n environmentConfig.text = str(robot_Type_Value)\n environmentConfig = et.SubElement(environmentXMLFile, 'ROBOT_ROLE')\n environmentConfig.text = str(robot_Role_Value)\n environmentConfig = et.SubElement(environmentXMLFile, 'ROBOT_TASK')\n environmentConfig.text = str(robot_Task_Value)\n environmentConfig = et.SubElement(environmentXMLFile, 'ROBOT_BEHAVIOR')\n environmentConfig.text = str(robot_Behavior_Value)\n environmentConfig = et.SubElement(environmentXMLFile, 'ROBOT_EXPERIMENT')\n environmentConfig.text = str(robot_Experiment_Value)\n try:\n tree = et.ElementTree(environmentXMLFile)\n tree.write('experimentConfig.xml', encoding='utf8')\n sendFiles.sshSendFiles()\n operationSucess()\n except Exception:\n operationError()","def test_experiments_authed_experimenter(client, users):\n login_experimenter(client)\n\n response = client.get(\"/\")\n data = response.data.decode(response.charset)\n assert \"Hello experimenter\" in data\n\n exp = ExperimentFactory()\n assignment_set = AssignmentSet()\n exp.assignment_sets.append(assignment_set)\n exp.save()\n\n exp_url = \"/experiments/\" + str(exp.id)\n\n response = client.get(\"/experiments/\")\n data = response.data.decode(response.charset)\n assert response.status_code == 200\n assert exp.name in data\n\n response = client.get(exp_url)\n data = response.data.decode(response.charset)\n assert response.status_code == 200\n assert exp.name in data\n assert \"Start\" not in data\n\n response = client.get(exp_url + \"/settings\")\n assert response.status_code == 200\n\n response = client.put(exp_url)\n assert response.status_code == 200\n\n response = client.delete(exp_url)\n assert response.status_code == 200\n assert json_success(response.data)","def _construct_new_expert(self):\n return self.WeightedExpert(\n cp.deepcopy(self.base_estimator), 1, self.labels)","def new_experiment_from_full_config(self, name, config, description=''):\n new_exp = {\n ExperimentAttr.NAME: name,\n ExperimentAttr.CONFIG: config,\n ExperimentAttr.DESC: description\n }\n\n return self.dbclient.insert(Tables.EXPERIMENTS, new_exp).inserted_id","def build_experiment():\n\n # ====== Argument creation ======\n model_dir = FLAGS.model_dir.format(\n cell=FLAGS.cell,\n user=getpass.getuser(),\n trial=FLAGS.trial,\n )\n\n # ====== Jobs and runtime creation ======\n\n # Job: worker\n requirements = xm.Requirements(gpu_types=[xm.GpuType.V100],)\n runtime_worker = xm.Borg(\n cell=FLAGS.cell,\n priority=FLAGS.priority,\n requirements=requirements,\n )\n exec_worker = xm.BuildTarget(\n '//experimental/users/gjt/his:mnist',\n name='worker',\n args=dict(\n gfs_user=FLAGS.gfs_user,\n logdir=model_dir,\n mode='train',\n ),\n platform=xm.Platform.GPU,\n runtime=runtime_worker,\n )\n\n # Job: eval\n runtime_eval = xm.Borg(\n cell=FLAGS.cell,\n priority=FLAGS.priority,\n )\n exec_eval = xm.BuildTarget(\n '//experimental/users/gjt/his:mnist',\n name='eval',\n args=dict(\n gfs_user=FLAGS.gfs_user,\n logdir=model_dir,\n mode='eval',\n split='train,valid,test',\n num_iwae_samples='1,1,1000',\n ),\n platform=xm.Platform.GPU, # Do we need GPU for eval?\n runtime=runtime_eval,\n )\n\n # ====== Executable experiment creation ======\n list_executables = []\n list_executables.append(xm_helper.build_single_job(exec_worker))\n list_executables.append(xm_helper.build_single_job(exec_eval))\n\n experiment = xm.ParallelExecutable(list_executables, name='his_service')\n\n # Build experiments\n hyper_parameters = {}\n\n # SNIS vs LARS\n hyper_parameters['snis_vs_lars'] = hyper.product([\n hyper.chainit([\n hyper.product([\n hyper.fixed('proposal', 'gaussian', length=1),\n hyper.fixed('model', 'bernoulli_vae', length=1),\n ]),\n hyper.product([\n hyper.fixed('proposal', 'bernoulli_vae', length=1),\n hyper.fixed('model', 'nis', length=1),\n ]),\n hyper.product([\n hyper.fixed('proposal', 'nis', length=1),\n hyper.fixed('model', 'bernoulli_vae', length=1),\n ]),\n ]),\n hyper.sweep('run', hyper.discrete([0])),\n hyper.fixed('dataset', 'static_mnist', length=1),\n hyper.fixed('reparameterize_proposal', False, length=1),\n hyper.fixed('anneal_kl_step', 100000, length=1),\n ])\n\n # Continuous comparisons: HIS, NIS, VAE\n hyper_parameters['continuous'] = hyper.product([\n hyper.chainit([\n hyper.product([\n hyper.fixed('proposal', 'gaussian', length=1),\n hyper.fixed('model', 'gaussian_vae', length=1),\n ]),\n hyper.product([\n hyper.fixed('proposal', 'gaussian_vae', length=1),\n hyper.fixed('model', 'nis', length=1),\n ]),\n hyper.product([\n hyper.fixed('proposal', 'gaussian', length=1),\n hyper.fixed('model', 'hisvae', length=1),\n hyper.sweep('his_T', hyper.discrete([5, 10, 15])),\n ]),\n ]),\n hyper.sweep('run', hyper.discrete([0])),\n hyper.fixed('dataset', 'jittered_mnist', length=1),\n hyper.fixed('reparameterize_proposal', True, length=1),\n hyper.fixed('squash', True, length=1),\n ])\n\n hyper_parameters['celeba'] = hyper.product([\n hyper.chainit([\n hyper.product([\n hyper.fixed('proposal', 'gaussian', length=1),\n hyper.fixed('model', 'conv_gaussian_vae', length=1),\n ]),\n ]),\n hyper.sweep('run', hyper.discrete([0])),\n hyper.fixed('dataset', 'jittered_celeba', length=1),\n hyper.fixed('reparameterize_proposal', True, length=1),\n hyper.fixed('squash', True, length=1),\n hyper.fixed('latent_dim', 16, length=1),\n hyper.fixed('batch_size', 36, length=1),\n ])\n\n experiment = xm.ParameterSweep(experiment, hyper_parameters[FLAGS.exp_type])\n experiment = xm.WithTensorBoard(experiment, model_dir)\n\n return experiment","def test_init_experiment(self):\n optimizer = \"RandomSearch\"\n name = \"test_init_experiment\"\n param_defs = {\n \"x\": MinMaxNumericParamDef(0, 1),\n \"name\": NominalParamDef([\"A\", \"B\", \"C\"])\n }\n minimization = True\n\n LAss = PrettyLabAssistant()\n LAss.init_experiment(name, optimizer, param_defs, minimization=minimization)\n\n exp_ass = LAss.exp_assistants[name]\n\n assert_equal(exp_ass.optimizer, optimizer)\n assert_is_none(exp_ass.optimizer_arguments, None)\n assert_equal(exp_ass.experiment.minimization_problem, minimization)\n with assert_raises(ValueError):\n LAss.init_experiment(name, optimizer, param_defs, minimization=minimization)","def new(self):\n uuid = uuid4().hex\n cur = self.conn.cursor()\n cur.execute(\n \"\"\"\n INSERT INTO experiments (uuid)\n VALUES(?)\n \"\"\", [uuid])\n cur.close()\n self.conn.commit()\n return uuid","def load_experiment(\n experiment_name: str,\n config: Optional[SQAConfig] = None,\n reduced_state: bool = False,\n) -> Experiment:\n config = config or SQAConfig()\n decoder = Decoder(config=config)\n return _load_experiment(\n experiment_name=experiment_name, decoder=decoder, reduced_state=reduced_state\n )","def make_experiment(\n path, experiment_name, experiment_info, verbosity, log_dir, output_path\n):\n experiment_dir = output_path / experiment_name\n if experiment_dir.is_dir():\n return\n experiment_dir.mkdir(parents=True)\n\n experiment_params = get_experiment_params(experiment_name, verbosity, log_dir)\n with (experiment_dir / \"experiment_params.json\").open(\"w\") as f:\n json.dump(experiment_params, f)\n\n for filename, filepath in experiment_info.items():\n filename += \".json\"\n new_path = experiment_dir / filename\n shutil.copy(filepath, new_path)","def experiments(self, key, value):\n experiments = self.get('experiments', [])\n\n name = value.get('e')\n recid = value.get('0')\n record = get_record_ref(recid, 'experiments')\n\n experiments.append({\n 'curated_relation': record is not None,\n 'name': name,\n 'record': record\n })\n\n return experiments","def __init__(self, exp_spec: ExperimentSpec, agent_root_dir: str = None):\n \n if agent_root_dir is not None:\n self.agent_root_dir = agent_root_dir\n else:\n self._use_hardcoded_agent_root_directory()\n \n self.exp_spec = exp_spec\n \n try:\n hec = exp_spec['harderEnvCoeficient']\n self.playground = GymPlayground(environment_name=exp_spec.prefered_environment, harderEnvCoeficient=hec)\n except KeyError:\n self.playground = GymPlayground(environment_name=exp_spec.prefered_environment)\n \n \"\"\" ---- Init computation graph ---- \"\"\"\n # required placeholder for Agent.play() methode\n self.obs_t_ph = None\n self.policy_pi = None\n \n self._build_computation_graph()\n \n not_implemented_msg = \"must be set by _build_computation_graph()\"\n assert self.obs_t_ph is not None, \"self.obs_t_ph {}\".format(not_implemented_msg)\n assert self.policy_pi is not None, \"self.policy_pi {}\".format(not_implemented_msg)\n \n \"\"\" ---- Setup parameters saving ---- \"\"\"\n self.saver = tf_cv1.train.Saver()\n self.writer = None\n self.this_run_dir = None","def experiment(\n self,\n dataset: Union[str, dict, pd.DataFrame] = None,\n training_set: Union[str, dict, pd.DataFrame] = None,\n validation_set: Union[str, dict, pd.DataFrame] = None,\n test_set: Union[str, dict, pd.DataFrame] = None,\n training_set_metadata: Union[str, dict] = None,\n data_format: str = None,\n experiment_name: str = \"experiment\",\n model_name: str = \"run\",\n model_load_path: str = None,\n model_resume_path: str = None,\n eval_split: str = TEST,\n skip_save_training_description: bool = False,\n skip_save_training_statistics: bool = False,\n skip_save_model: bool = False,\n skip_save_progress: bool = False,\n skip_save_log: bool = False,\n skip_save_processed_input: bool = False,\n skip_save_unprocessed_output: bool = False,\n skip_save_predictions: bool = False,\n skip_save_eval_stats: bool = False,\n skip_collect_predictions: bool = False,\n skip_collect_overall_stats: bool = False,\n output_directory: str = \"results\",\n random_seed: int = default_random_seed,\n **kwargs,\n ) -> Tuple[Optional[dict], TrainingStats, PreprocessedDataset, str]:\n if self._user_config.get(HYPEROPT):\n print_boxed(\"WARNING\")\n logger.warning(HYPEROPT_WARNING)\n\n (train_stats, preprocessed_data, output_directory) = self.train(\n dataset=dataset,\n training_set=training_set,\n validation_set=validation_set,\n test_set=test_set,\n training_set_metadata=training_set_metadata,\n data_format=data_format,\n experiment_name=experiment_name,\n model_name=model_name,\n model_load_path=model_load_path,\n model_resume_path=model_resume_path,\n skip_save_training_description=skip_save_training_description,\n skip_save_training_statistics=skip_save_training_statistics,\n skip_save_model=skip_save_model,\n skip_save_progress=skip_save_progress,\n skip_save_log=skip_save_log,\n skip_save_processed_input=skip_save_processed_input,\n skip_save_unprocessed_output=skip_save_unprocessed_output,\n output_directory=output_directory,\n random_seed=random_seed,\n )\n\n (training_set, validation_set, test_set, training_set_metadata) = preprocessed_data\n\n eval_set = validation_set\n if eval_split == TRAINING:\n eval_set = training_set\n elif eval_split == VALIDATION:\n eval_set = validation_set\n elif eval_split == TEST:\n eval_set = test_set\n else:\n logger.warning(f\"Eval split {eval_split} not supported. \" f\"Using validation set instead\")\n\n if eval_set is not None:\n trainer_dict = self.config_obj.trainer.to_dict()\n batch_size = trainer_dict.get(EVAL_BATCH_SIZE, trainer_dict.get(BATCH_SIZE, None))\n\n # predict\n try:\n eval_stats, _, _ = self.evaluate(\n eval_set,\n data_format=data_format,\n batch_size=batch_size,\n output_directory=output_directory,\n skip_save_unprocessed_output=skip_save_unprocessed_output,\n skip_save_predictions=skip_save_predictions,\n skip_save_eval_stats=skip_save_eval_stats,\n collect_predictions=not skip_collect_predictions,\n collect_overall_stats=not skip_collect_overall_stats,\n return_type=\"dict\",\n )\n except NotImplementedError:\n logger.warning(\n \"Skipping evaluation as the necessary methods are not \"\n \"supported. Full exception below:\\n\"\n f\"{traceback.format_exc()}\"\n )\n eval_stats = None\n else:\n logger.warning(f\"The evaluation set {eval_set} was not provided. \" f\"Skipping evaluation\")\n eval_stats = None\n\n return eval_stats, train_stats, preprocessed_data, output_directory","def _Run(args, version):\n validation.ValidateDisplayName(args.display_name)\n\n tensorboard_ref = args.CONCEPTS.tensorboard.Parse()\n region = tensorboard_ref.AsDict()['locationsId']\n with endpoint_util.AiplatformEndpointOverrides(version, region=region):\n tensorboard_experiments_client = client.TensorboardExperimentsClient(\n version=version)\n response = tensorboard_experiments_client.Create(tensorboard_ref, args)\n if response.name:\n log.status.Print(('Created Vertex AI Tensorboard experiment: {}.').format(\n response.name))\n return response","def __init__(\n self,\n config,\n experiment_id,\n training_workflow_metadata={},\n hosting_workflow_metadata={},\n joining_workflow_metadata={},\n evaluation_workflow_metadata={},\n ):\n self.boto_session = boto3.Session()\n self._region_name = self.boto_session.region_name\n self.account = self.boto_session.client(\"sts\").get_caller_identity()[\"Account\"]\n if self._region_name is None:\n raise ValueError(\"Must setup AWS configuration with a valid region\")\n\n # unique id common across all experiments in the account\n self.experiment_id = experiment_id\n\n # load configs\n self.config = config\n self.image = self.config.get(\"image\", None).replace(\"{AWS_REGION}\", self._region_name)\n self.algor_config = self.config.get(\"algor\", {})\n self.local_mode = self.config.get(\"local_mode\", True)\n if self.local_mode:\n self._update_instance_type_for_local_mode()\n self.sagemaker_session = LocalSession()\n else:\n self.sagemaker_session = sagemaker.session.Session(self.boto_session)\n\n self.soft_deployment = self.config.get(\"soft_deployment\", False)\n\n # load resource config and init shared resourced if not exists\n self.resource_manager = ResourceManager(\n self.config.get(\"resource\", {}), boto_session=self.boto_session\n )\n self.resource_manager.create_shared_resource_if_not_exist()\n\n # init clients\n self.exp_db_client = self.resource_manager.exp_db_client\n self.model_db_client = self.resource_manager.model_db_client\n self.join_db_client = self.resource_manager.join_db_client\n self.cw_logger = CloudWatchLogger(self.boto_session.client(\"cloudwatch\"), self._region_name)\n self.sagemaker_client = self.sagemaker_session.sagemaker_client\n\n # init s3 client for rewards upload\n self.s3_client = self.boto_session.client(\"s3\")\n\n # create a local JoinJobRecord object.\n self.experiment_record = ExperimentRecord(\n experiment_id,\n training_workflow_metadata,\n hosting_workflow_metadata,\n joining_workflow_metadata,\n evaluation_workflow_metadata,\n )\n self.next_model_to_train = None\n self.next_join_job = None\n self.next_model_to_evaluate = None\n\n # Try to save new ExperimentRecord to ExperimentDb. If it throws\n # RecordAlreadyExistsException, re-read the ExperimentRecord from ExperimentDb,\n # and use it as initial state\n try:\n self.exp_db_client.create_new_experiment_record(self.experiment_record.to_ddb_record())\n except RecordAlreadyExistsException:\n logger.warn(\n f\"Experiment with name {self.experiment_id} already exists. \"\n \"Reusing current state from ExperimentDb.\"\n )\n experiment_record = self.exp_db_client.get_experiment_record(experiment_id)\n self.experiment_record = ExperimentRecord.load_from_ddb_record(experiment_record)\n except Exception as e:\n logger.error(\"Unhandled Exception! \" + str(e))\n raise UnhandledWorkflowException(\"Something went wrong while creating a new experiment\")\n\n try:\n self.cw_logger.create_cloudwatch_dashboard_from_experiment_id(self.experiment_id)\n except Exception as e:\n logger.error(\"Unable to create CloudWatch Dashboard.\" + str(e))\n logger.error(\n \"To see metrics on CloudWatch, run bandit_experiment.\"\n \"cw_logger.create_cloudwatch_dashboard_from_experiment_id function again.\"\n )\n\n # start a daemon thread to sync ExperimentDb states to local states\n # the daemon thread will keep running till the session ends\n self.sync_thread = ExperimentManagerSyncThread(experiment_manager=self)\n\n # Run the thread in SageMaker mode only\n if not self.local_mode:\n self.sync_thread.setDaemon(True)\n self.sync_thread.start()","def create_experiment_from_api(self, experiment_accession_code: str) -> Tuple[Experiment, Dict]:\n\n try:\n experiment_data = self._get_experiment_data(accession_code=experiment_accession_code)\n except KeyError:\n logger.error(\n \"Could not collect data from remote experiment source!\",\n experiment_accession_code=experiment_accession_code,\n survey_job=self.survey_job.id,\n )\n raise\n\n array_designs = experiment_data[\"array_designs\"]\n # This experiment has no platform at all, and is therefore useless.\n if not array_designs:\n logger.warn(\n \"Remote experiment has no array design listed.\",\n experiment_accession_code=experiment_accession_code,\n survey_job=self.survey_job.id,\n )\n raise UnsupportedPlatformException\n\n platforms = {}\n # If there is more than one array design listed in the experiment\n # then there is no other way to determine which array was used\n # for which sample other than looking at the header of the CEL\n # file. That obviously cannot happen until the CEL file has been\n # downloaded so we can just mark it as UNKNOWN and let the\n # downloader inspect the downloaded file to determine the\n # array then.\n if len(array_designs) != 1:\n platforms[\"platform_accession_code\"] = UNKNOWN\n platforms[\"platform_accession_name\"] = UNKNOWN\n platforms[\"manufacturer\"] = UNKNOWN\n else:\n external_accession = array_designs[0]\n for platform in get_supported_microarray_platforms():\n if platform[\"external_accession\"] == external_accession:\n platforms[\"platform_accession_code\"] = get_normalized_platform(\n platform[\"platform_accession\"]\n )\n # Illumina appears in the accession codes for\n # platforms manufactured by Illumina\n if \"ILLUMINA\" in platforms[\"platform_accession_code\"].upper():\n platforms[\"manufacturer\"] = \"ILLUMINA\"\n platforms[\"platform_accession_name\"] = platform[\"platform_accession\"]\n # It's not Illumina, the only other supported Microarray platform is\n # Affy. As our list of supported platforms grows this logic will\n # need to get more sophisticated.\n else:\n platforms[\"manufacturer\"] = \"AFFYMETRIX\"\n platform_mapping = get_readable_affymetrix_names()\n platforms[\"platform_accession_name\"] = platform_mapping[\n platform[\"platform_accession\"]\n ]\n\n if \"platform_accession_code\" not in platforms:\n # We don't know what platform this accession corresponds to.\n platforms[\"platform_accession_code\"] = external_accession\n platforms[\"platform_accession_name\"] = UNKNOWN\n platforms[\"manufacturer\"] = UNKNOWN\n\n # Create the experiment.\n try:\n experiment = Experiment.objects.get(accession_code=experiment_accession_code)\n logger.debug(\n \"Experiment already exists, skipping object creation.\",\n experiment_accession_code=experiment_accession_code,\n survey_job=self.survey_job.id,\n )\n except Experiment.DoesNotExist:\n experiment = Experiment()\n experiment.accession_code = experiment_accession_code\n experiment.source_url = experiment_data[\"url\"]\n self._apply_metadata_to_experiment(experiment, experiment_data)\n experiment.save()\n\n json_xa = ExperimentAnnotation()\n json_xa.experiment = experiment\n json_xa.data = experiment_data\n json_xa.is_ccdl = False\n json_xa.save()\n\n # Fetch and parse the IDF/SDRF file for any other fields.\n idf_url = IDF_URL_TEMPLATE.format(code=experiment_accession_code)\n idf_text = utils.requests_retry_session().get(idf_url, timeout=60).text\n\n idf_data = {}\n for line in idf_text.split(\"\\n\"):\n key_val = line.strip().split(\"\\t\")\n if len(key_val) == 2:\n idf_data[key_val[0]] = key_val[1]\n elif len(key_val) > 2:\n idf_data[key_val[0]] = key_val[1:]\n\n idf_xa = ExperimentAnnotation()\n idf_xa.data = idf_data\n idf_xa.experiment = experiment\n idf_xa.is_ccdl = False\n idf_xa.save()\n\n if \"Investigation Title\" in idf_data and isinstance(\n idf_data[\"Investigation Title\"], str\n ):\n experiment.title = idf_data[\"Investigation Title\"]\n\n if \"Person Affiliation\" in idf_data:\n # This is very rare, ex: E-MEXP-32\n if isinstance(idf_data[\"Person Affiliation\"], list):\n unique_people = list(set(idf_data[\"Person Affiliation\"]))\n experiment.submitter_institution = \", \".join(unique_people)[:255]\n else:\n experiment.submitter_institution = idf_data[\"Person Affiliation\"]\n\n if \"Publication Title\" in idf_data:\n # This will happen for some superseries.\n # Ex: E-GEOD-29536\n # Assume most recent is \"best:, store the rest in experiment annotation.\n if isinstance(idf_data[\"Publication Title\"], list):\n experiment.publication_title = \"; \".join(idf_data[\"Publication Title\"])\n else:\n experiment.publication_title = idf_data[\"Publication Title\"]\n experiment.has_publication = True\n\n if \"Publication DOI\" in idf_data:\n experiment.has_publication = True\n if isinstance(idf_data[\"Publication DOI\"], list):\n experiment.publication_doi = \", \".join(idf_data[\"Publication DOI\"])\n else:\n experiment.publication_doi = idf_data[\"Publication DOI\"]\n\n if \"PubMed ID\" in idf_data:\n experiment.has_publication = True\n if isinstance(idf_data[\"PubMed ID\"], list):\n experiment.pubmed_id = \", \".join(idf_data[\"PubMed ID\"])\n else:\n experiment.pubmed_id = idf_data[\"PubMed ID\"]\n\n # Scrape publication title and authorship from Pubmed\n if experiment.pubmed_id:\n pubmed_metadata = utils.get_title_and_authors_for_pubmed_id(experiment.pubmed_id)\n experiment.publication_title = pubmed_metadata[0]\n experiment.publication_authors = pubmed_metadata[1]\n\n experiment.protocol_description = experiment_data[\"protocols\"]\n experiment.save()\n\n return experiment, platforms","def run_experiment():\n pass","def make_exp(exp_group, args):\n equalized_args = ['='.join(tup) for tup in args]\n stripped_args = [arg.lstrip('-') for arg in equalized_args]\n exp_name = [pvalue for (pname, pvalue) in args if pname == '-exp-id'][0]\n \n unrolled_args = [arg for arg_tup in args for arg in arg_tup]\n arg_str = ' '.join(unrolled_args) + ' -exp-group ' + exp_group\n\n get_ipython().system(u'mkdir -p ../store/output/$exp_group/$exp_name')\n get_ipython().system(u'mkdir -p ../store/weights/$exp_group/$exp_name')\n get_ipython().system(u'mkdir -p ../store/probas/$exp_group')\n get_ipython().system(u'mkdir -p ../store/train/$exp_group/$exp_name')\n get_ipython().system(u'mkdir -p ../store/hyperparams/$exp_group')\n get_ipython().system(u'mkdir -p ../store/models/$exp_group')\n\n get_ipython().system(u'mkdir -p exps/$exp_group')\n get_ipython().system(u\"sed 's/ARGUMENTS/$arg_str/g' job_template | sed 's/EXP_GROUP/$exp_group/g' | sed 's/EXPERIMENT/$exp_name/g' > exps/$exp_group/$exp_name\")","def create_epic():\n client = RequestManager()\n client.set_method(\"POST\")\n client.set_endpoint(\"/projects/{0}/epics\".format(STORED_ID['project_id']))\n name = \"\".join(choices(string.ascii_letters, k=6))\n body = {\"name\": name}\n client.set_body(json.dumps(body))\n response = client.execute_request()\n STORED_ID['epic_id'] = response.json()['id']","def exp_main(self, use_remote_data=True, test=False):\n test = str_to_bool(test)\n use_remote_data = str_to_bool(use_remote_data)\n root_uri = get_root_uri(use_remote_data)\n root_uri = os.path.join(root_uri, rv_output_dir)\n spacenet_config = VegasBuildings(use_remote_data)\n experiments = []\n runs = [0]\n\n noise_modes = [\n NoiseMode(NoiseMode.SHIFT, 0),\n NoiseMode(NoiseMode.SHIFT, 10),\n NoiseMode(NoiseMode.SHIFT, 20),\n NoiseMode(NoiseMode.SHIFT, 30),\n NoiseMode(NoiseMode.SHIFT, 40),\n NoiseMode(NoiseMode.SHIFT, 50),\n NoiseMode(NoiseMode.DROP, 0.0),\n NoiseMode(NoiseMode.DROP, 0.1),\n NoiseMode(NoiseMode.DROP, 0.2),\n NoiseMode(NoiseMode.DROP, 0.3),\n NoiseMode(NoiseMode.DROP, 0.4),\n NoiseMode(NoiseMode.DROP, 0.5)\n ]\n\n for nm in noise_modes:\n for run in runs:\n exp_id = get_exp_id(nm, run)\n task = build_task(spacenet_config.get_class_map())\n backend = build_fastai_backend(task, test)\n analyzer = rv.AnalyzerConfig.builder(rv.STATS_ANALYZER) \\\n .build()\n dataset = build_dataset(task, spacenet_config, test, nm)\n\n experiment = rv.ExperimentConfig.builder() \\\n .with_id(exp_id) \\\n .with_analyze_key('shift-0-0') \\\n .with_task(task) \\\n .with_backend(backend) \\\n .with_analyzer(analyzer) \\\n .with_dataset(dataset) \\\n .with_root_uri(root_uri) \\\n .build()\n experiments.append(experiment)\n\n return experiments","def _create_dataset(source=''):\n return ExperimentalDataset()","def update_experiment_v1(self, skill_id, experiment_id, update_experiment_request, **kwargs):\n # type: (str, str, UpdateExperimentRequest_d8449813, **Any) -> Union[ApiResponse, object, StandardizedError_f5106a89, BadRequestError_f854b05]\n operation_name = \"update_experiment_v1\"\n params = locals()\n for key, val in six.iteritems(params['kwargs']):\n params[key] = val\n del params['kwargs']\n # verify the required parameter 'skill_id' is set\n if ('skill_id' not in params) or (params['skill_id'] is None):\n raise ValueError(\n \"Missing the required parameter `skill_id` when calling `\" + operation_name + \"`\")\n # verify the required parameter 'experiment_id' is set\n if ('experiment_id' not in params) or (params['experiment_id'] is None):\n raise ValueError(\n \"Missing the required parameter `experiment_id` when calling `\" + operation_name + \"`\")\n # verify the required parameter 'update_experiment_request' is set\n if ('update_experiment_request' not in params) or (params['update_experiment_request'] is None):\n raise ValueError(\n \"Missing the required parameter `update_experiment_request` when calling `\" + operation_name + \"`\")\n\n resource_path = '/v1/skills/{skillId}/experiments/{experimentId}/properties'\n resource_path = resource_path.replace('{format}', 'json')\n\n path_params = {} # type: Dict\n if 'skill_id' in params:\n path_params['skillId'] = params['skill_id']\n if 'experiment_id' in params:\n path_params['experimentId'] = params['experiment_id']\n\n query_params = [] # type: List\n\n header_params = [] # type: List\n\n body_params = None\n if 'update_experiment_request' in params:\n body_params = params['update_experiment_request']\n header_params.append(('Content-type', 'application/json'))\n header_params.append(('User-Agent', self.user_agent))\n\n # Response Type\n full_response = False\n if 'full_response' in params:\n full_response = params['full_response']\n\n # Authentication setting\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\n authorization_value = \"Bearer \" + access_token\n header_params.append(('Authorization', authorization_value))\n\n error_definitions = [] # type: List\n error_definitions.append(ServiceClientResponse(response_type=None, status_code=204, message=\"Success. No content.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.bad_request_error.BadRequestError\", status_code=400, message=\"Server cannot process the request due to a client error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=401, message=\"The auth token is invalid/expired or doesn't have access to the resource.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.bad_request_error.BadRequestError\", status_code=403, message=\"The operation being requested is not allowed.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=404, message=\"The resource being requested is not found.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=409, message=\"The request could not be completed due to a conflict with the current state of the target resource.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=429, message=\"Exceeds the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=500, message=\"Internal Server Error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=503, message=\"Service Unavailable.\"))\n\n api_response = self.invoke(\n method=\"POST\",\n endpoint=self._api_endpoint,\n path=resource_path,\n path_params=path_params,\n query_params=query_params,\n header_params=header_params,\n body=body_params,\n response_definitions=error_definitions,\n response_type=None)\n\n if full_response:\n return api_response\n \n return None","def create_experiment_path(self, experiment):\n # get communications object as link to microscope hardware\n communicatons_object = self._get_control_software().connection\n experiment_path = communicatons_object.create_experiment_path(\n experiment, self.experiment_folder\n )\n return experiment_path","def _problem_run_experiments_initialise(self):\n pass","def __init__(self):\n\n #: Dict[str, Any]: Experiment metadata\n self.__experiment_metadata = None\n\n #: List[CurveData]: Processed experiment data set.\n self.__processed_data_set = list()\n\n #: Backend: backend object used for experimentation\n self.__backend = None\n\n # Add expected options to instance variable so that every method can access to.\n for key in self._default_options().__dict__:\n setattr(self, f\"__{key}\", None)\n\n # Add fixed parameters to instance variable so that every method can access to.\n for key in self.__fixed_parameters__:\n setattr(self, f\"__{key}\", None)","def _get_equipment(self):\r\n eq = self._pvsr.getEquipmentByName(self._meas[\"equipment\"])\r\n if eq is None:\r\n site = self._pvsr.getSiteByName(self._default_site)\r\n if site is None:\r\n logging.info(\"Creating new default site {0}\".format(self._default_site))\r\n site = self._pvsr.create_pvsr_object(\"Site\")\r\n site.ParentId = 1\r\n site.Name = self._default_site\r\n site=self._pvsr.addSite(site)\r\n else:\r\n logging.debug(\"Default site ID is {0}\".format(site.Id))\r\n \r\n logging.info(\"Creating new equipment: {0}\".format(self._meas[\"equipment\"]))\r\n if self._meas[\"collector_type\"] == 'J':\r\n eq = self._pvsr.create_pvsr_object(\"JagaEquipment\")\r\n eq.ASCII_0000_EQ_COLL_KEY = self._meas[\"equipment\"] + \"key\"\r\n elif self._meas[\"collector_type\"] == 'Y':\r\n eq = self._pvsr.create_pvsr_object(\"SynthTransEquipment\")\r\n else:\r\n raise ValueError(\"The equipment does not exist in PVSR\") \r\n eq.Name = self._meas[\"equipment\"]\r\n eq.ParentId = site.Id\r\n eq.CollectorType = self._meas[\"collector_type\"]\r\n eq.IntervalInSec = 300\r\n eq.RetainRawData = 365\r\n eq.CollectData = \"Yes\"\r\n \r\n eq = self._pvsr.addEquipment(eq)\r\n logging.info(\"Added equipment {0}, id: {1}\".format(self._meas[\"equipment\"],eq.Id))\r\n else:\r\n logging.debug(\"Found equipment: {0}, id: {1}\".format(self._meas[\"equipment\"],eq.Id))\r\n return eq","def create_experience(cls, state, action, reward, done, next_state) -> 'Experience':\n return cls(\n state=state,\n action=action,\n reward=reward,\n done=done,\n next_state=next_state,\n )","def _make(dataset, model):\n def wrapper(args):\n return SlimExperiment(dataset, model, args)\n return wrapper","def add_experiment(self, experiment):\n nra_ = c.c_int(experiment.z)\n klm_ = c.c_int(experiment.line)\n hv_ = c.c_double(experiment.energy_eV / 1e3)\n ielt_ = c.c_int()\n iline_ = c.c_int()\n iexpk_ = c.c_int()\n logger.debug('StEdAddNrAtomLineHV(key, %i, %i)', experiment.z, experiment.line)\n if not self._lib.StEdAddNrAtomLineHV(self._key, nra_, klm_, hv_,\n c.byref(ielt_), c.byref(iline_), c.byref(iexpk_)):\n self._raise_error(\"Cannot add atomic number and line\")\n\n standard = experiment.standard\n if isinstance(standard, Sample):\n standard = self._create_standard(standard)\n standard_ = c.create_string_buffer(standard.encode('ascii'))\n logger.debug('StEdSetLine(key, %i, %i, %i, %s)', ielt_.value, iline_.value, klm_.value, standard)\n if not self._lib.StEdSetLine(self._key, ielt_, iline_, klm_, standard_):\n self._raise_error(\"Cannot set standard\")\n\n analyzed = experiment.is_analyzed()\n analyzed_ = c.c_bool(analyzed)\n logger.debug(\"StEdSetAnalyzedFlag(key, %i, %r)\", ielt_.value, analyzed)\n if not self._lib.StEdSetAnalyzedFlag(self._key, ielt_, analyzed_):\n self._raise_error(\"Cannot add experiment analyzed flag\")\n\n kratio_ = c.c_double(experiment.kratio)\n logger.debug(\"StEdSetExpK(key, %i, %i, %i, %f, %f, %f, 0.0, 2)\",\n ielt_.value, iline_.value, iexpk_.value,\n experiment.energy_eV / 1e3, experiment.energy_eV / 1e3,\n experiment.kratio)\n if not self._lib.StEdSetExpK(self._key, ielt_, iline_, iexpk_,\n hv_, hv_, kratio_, c.c_double(0.0),\n c.c_int(2)):\n self._raise_error(\"Cannot set experiment k-ratio\")\n\n if experiment.is_analyzed():\n indexes = (ielt_.value, iline_.value, iexpk_.value)\n self._experiments.setdefault(experiment, indexes)","def experiment(self) -> Any:","def experiment_params():\n exp = {\n 'lr': [1e-3],\n 'loss_function': ['cce'],\n 'optimizer': ['nadam'],\n 'dataset': [\n # 'curv_contour_length_9',\n 'cluttered_nist_ix1',\n # 'curv_baseline',\n ]\n }\n exp['data_augmentations'] = [\n [\n 'grayscale',\n 'center_crop',\n # 'left_right',\n # 'up_down',\n 'uint8_rescale',\n 'singleton',\n 'zero_one'\n ]]\n exp['val_augmentations'] = [\n [\n 'grayscale',\n 'center_crop',\n # 'left_right',\n # 'up_down',\n 'uint8_rescale',\n 'singleton',\n 'zero_one'\n ]]\n exp['batch_size'] = 32 # Train/val batch size.\n exp['epochs'] = 4\n exp['model_name'] = 'unet'\n exp['exp_name'] = exp['model_name'] + '_' + exp['dataset'][0]\n exp['save_weights'] = True\n exp['validation_iters'] = 1000\n exp['num_validation_evals'] = 200\n exp['shuffle_val'] = True # Shuffle val data.\n exp['shuffle_train'] = True\n return exp","def test_experiment_do_not_exist(self):\n with pytest.raises(NoConfigurationError) as exception:\n get_experiment(\"a\")\n assert (\n \"No experiment with given name 'a' and version '*' inside database, \"\n \"no view can be created.\" == str(exception.value)\n )","def add_agent(self, environment_name, agent_name, agent_params):\n assert environment_name in self._environment_dict\n assert self._is_sweep is False or self._is_sweep is None\n self._is_sweep = False\n if agent_name in self._experiment_structure[environment_name]:\n raise AttributeError(\n f'An experiment for environment {environment_name} and builders {agent_name} already exists.'\n )\n\n environment_builder_params = self._environment_dict[environment_name]['build_params']\n\n try:\n exp = self._create_experiment(environment_name, environment_builder_params, agent_name, agent_params)\n self._experiment_structure[environment_name][agent_name] = exp\n except AttributeError as e:\n self.logger.error(\n f'Unable to create experiment for the environment {environment_name} and agent {agent_name}'\n )\n self.logger.exception(e)","def get_experiment(self,\n experiment_id=None,\n experiment_name=None,\n namespace=None) -> kfp_server_api.V1Experiment:\n namespace = namespace or self.get_user_namespace()\n if experiment_id is None and experiment_name is None:\n raise ValueError(\n 'Either experiment_id or experiment_name is required')\n if experiment_id is not None:\n return self._experiment_api.get_experiment(id=experiment_id)\n experiment_filter = json.dumps({\n 'predicates': [{\n 'op': _FILTER_OPERATIONS['EQUALS'],\n 'key': 'name',\n 'stringValue': experiment_name,\n }]\n })\n if namespace:\n result = self._experiment_api.list_experiment(\n filter=experiment_filter,\n resource_reference_key_type=kfp_server_api.models\n .v1_resource_type.V1ResourceType.NAMESPACE,\n resource_reference_key_id=namespace)\n else:\n result = self._experiment_api.list_experiment(\n filter=experiment_filter)\n if not result.experiments:\n raise ValueError(\n 'No experiment is found with name {}.'.format(experiment_name))\n if len(result.experiments) > 1:\n raise ValueError(\n 'Multiple experiments is found with name {}.'.format(\n experiment_name))\n return result.experiments[0]","def __init__(self, name, ingredients=()):\n caller_globals = inspect.stack()[1][0].f_globals\n super(Experiment, self).__init__(path=name,\n ingredients=ingredients,\n _generate_seed=True,\n _caller_globals=caller_globals)\n self.name = name\n self.default_command = \"\"\n self.logger = None\n self.observers = []\n self.command(print_config)\n self.command(print_dependencies)","def setUpClass(cls):\n with patch('builtins.input', side_effect=['yes', 12]):\n experiment = Experiment(cls.experiment_path)\n cls.experiment = experiment","def make_exps(exp_group, args, num_exps=32, grid_search=False, baseline_exp_groups=[]):\n args_list = list(args_generator(args, num_exps, grid_search))\n\n # Remove exp_group directories!\n get_ipython().system(u'rm -rf exps/$exp_group')\n get_ipython().system(u'rm -rf ../store/output/$exp_group')\n get_ipython().system(u'rm -rf ../store/weights/$exp_group')\n get_ipython().system(u'rm -rf ../store/probas/$exp_group')\n get_ipython().system(u'rm -rf ../store/train/$exp_group')\n get_ipython().system(u'rm -rf ../store/hyperparams/$exp_group')\n get_ipython().system(u'rm -rf ../store/models/$exp_group')\n\n for i, args_setting in enumerate(args_list):\n make_exp(exp_group, args_setting)\n\n # Copy in existing experiments - for learning curve visualizations\n for baseline_exp_group in baseline_exp_groups:\n get_ipython().system(u'cp -r ../output/$baseline_exp_group/* ../output/$exp_group')","def experiment(self):\n return self._experiment","def _find_or_add_artifact(self, i):\n\n console = i.get('out','')=='con'\n\n # Try to find experiment artifact by alias and/or tags\n ii = utils.sub_input(i, self.cmind.cfg['artifact_keys'] + ['tags'])\n ii['action']='find'\n\n ii_copy = copy.deepcopy(ii)\n\n # If artifact is specified, remove tags\n artifact = ii.get('artifact','').strip()\n if artifact!='' and not artifact.endswith(':') \\\n and '*' not in artifact and '?' not in artifact:\n if 'tags' in ii: del(ii['tags'])\n\n r = self.cmind.access(ii)\n if r['return']>0: return r\n\n lst = r['list']\n\n if len(lst)>1:\n print ('More than 1 experiment artifact found:')\n\n lst = sorted(lst, key=lambda x: x.path)\n \n num = 0\n print ('')\n for e in lst:\n print ('{}) {}'.format(num, e.path))\n print (' Tags: {}'.format(','.join(e.meta.get('tags',[]))))\n num += 1\n\n if not console:\n return {'return':1, 'error':'more than 1 experiment artifact found.\\nPlease use \"cm run experiment {name}\" or \"cm run experiment --tags={tags separated by comma}\"'}\n \n print ('')\n x=input('Make your selection or press Enter for 0: ')\n\n x=x.strip()\n if x=='': x='0'\n\n selection = int(x)\n\n if selection < 0 or selection >= num:\n selection = 0\n\n experiment = lst[selection]\n\n elif len(lst)==1:\n experiment = lst[0]\n else:\n # Create new entry\n if i.get('fail_if_not_found',False):\n return {'return':1, 'error':'experiment not found'}\n \n ii = copy.deepcopy(ii_copy)\n ii['action']='add'\n r = self.cmind.access(ii)\n if r['return']>0: return r\n\n experiment_uid = r['meta']['uid']\n\n r = self.cmind.access({'action':'find',\n 'automation':'experiment,a0a2d123ef064bcb',\n 'artifact':experiment_uid})\n if r['return']>0: return r\n\n lst = r['list']\n if len(lst)==0 or len(lst)>1:\n return {'return':1, 'error':'created experiment artifact with UID {} but can\\'t find it - weird'.format(experiment_uid)}\n\n experiment = lst[0]\n \n return {'return':0, 'experiment':experiment}"],"string":"[\n \"def create_experiment_if_needed(tr):\\n exp = tr.getExperiment(EXPERIMENT_ID)\\n if None == exp:\\n create_project_if_needed(tr)\\n exp = tr.createNewExperiment(EXPERIMENT_ID, 'DEFAULT_EXPERIMENT')\\n \\n return exp\",\n \"def create_experiment(self):\\n experiment = wandb.init(\\n name=self._name, dir=self._dir, project=self._project,\\n anonymous=self._anonymous, reinit=True, id=self._id,\\n resume='allow', tags=self._tags, entity=self._entity\\n )\\n wandb.run.save()\\n return experiment\",\n \"def _create_or_get_experiment(self) -> tensorboard_experiment.TensorboardExperiment:\\n logger.info(\\\"Creating experiment\\\")\\n\\n tb_experiment = tensorboard_experiment.TensorboardExperiment(\\n description=self._description, display_name=self._experiment_display_name\\n )\\n\\n try:\\n experiment = self._api.create_tensorboard_experiment(\\n parent=self._tensorboard_resource_name,\\n tensorboard_experiment=tb_experiment,\\n tensorboard_experiment_id=self._experiment_name,\\n )\\n self._is_brand_new_experiment = True\\n except exceptions.AlreadyExists:\\n logger.info(\\\"Creating experiment failed. Retrieving experiment.\\\")\\n experiment_name = os.path.join(\\n self._tensorboard_resource_name, \\\"experiments\\\", self._experiment_name\\n )\\n experiment = self._api.get_tensorboard_experiment(name=experiment_name)\\n return experiment\",\n \"def create_experiment(name='exp', database=None):\\n ex = Experiment(name)\\n\\n atlas_user = os.environ.get('MONGO_DB_USER')\\n atlas_password = os.environ.get('MONGO_DB_PASS')\\n atlas_host = os.environ.get('MONGO_DB_HOST')\\n\\n # Add remote MongoDB observer, only if environment variables are set\\n if atlas_user and atlas_password and atlas_host:\\n ex.observers.append(MongoObserver(\\n url=f\\\"mongodb+srv://{atlas_user}:{atlas_password}@{atlas_host}\\\",\\n db_name=database))\\n return ex\",\n \"def newExperiment(self):\\n experiment = Experiment()\\n newtitle = 'Untitled ' + self.getNextUntitled()\\n experimentFrame = SequenceFrame(self, experiment, True, newtitle)\\n experiment.setInteractionParameters(parentFrame=experimentFrame,\\n graphManagerClass=StandardGraphManager)\\n self.frames.append(experimentFrame)\\n self.names.append(newtitle)\\n log.info('Created experiment ' + newtitle)\\n experimentFrame.Show()\\n testFrame = tf.TestingFrame(experimentFrame, experiment)\\n testFrame.Show()\\n self.Show(False)\",\n \"def experiment(self) -> Run:\\n if self._experiment is None:\\n self._experiment = self.create_experiment()\\n return self._experiment\",\n \"def create(self, request):\\n serializer = ExperimentSerializer(data=request.data)\\n if serializer.is_valid():\\n serializer.save()\\n\\n return send_response(request.method, serializer)\",\n \"def create_experiment(self):\\n\\n experiment = self._create_or_get_experiment()\\n self._experiment = experiment\\n self._one_platform_resource_manager = uploader_utils.OnePlatformResourceManager(\\n self._experiment.name, self._api\\n )\\n\\n self._request_sender = _BatchedRequestSender(\\n self._experiment.name,\\n self._api,\\n allowed_plugins=self._allowed_plugins,\\n upload_limits=self._upload_limits,\\n rpc_rate_limiter=self._rpc_rate_limiter,\\n tensor_rpc_rate_limiter=self._tensor_rpc_rate_limiter,\\n blob_rpc_rate_limiter=self._blob_rpc_rate_limiter,\\n blob_storage_bucket=self._blob_storage_bucket,\\n blob_storage_folder=self._blob_storage_folder,\\n one_platform_resource_manager=self._one_platform_resource_manager,\\n tracker=self._tracker,\\n )\\n\\n # Update partials with experiment name\\n for sender in self._additional_senders.keys():\\n self._additional_senders[sender] = self._additional_senders[sender](\\n experiment_resource_name=self._experiment.name,\\n )\\n\\n self._dispatcher = _Dispatcher(\\n request_sender=self._request_sender,\\n additional_senders=self._additional_senders,\\n )\",\n \"def create_experiment_v1(self, skill_id, create_experiment_request, **kwargs):\\n # type: (str, CreateExperimentRequest_abced22d, **Any) -> Union[ApiResponse, object, StandardizedError_f5106a89, BadRequestError_f854b05]\\n operation_name = \\\"create_experiment_v1\\\"\\n params = locals()\\n for key, val in six.iteritems(params['kwargs']):\\n params[key] = val\\n del params['kwargs']\\n # verify the required parameter 'skill_id' is set\\n if ('skill_id' not in params) or (params['skill_id'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `skill_id` when calling `\\\" + operation_name + \\\"`\\\")\\n # verify the required parameter 'create_experiment_request' is set\\n if ('create_experiment_request' not in params) or (params['create_experiment_request'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `create_experiment_request` when calling `\\\" + operation_name + \\\"`\\\")\\n\\n resource_path = '/v1/skills/{skillId}/experiments'\\n resource_path = resource_path.replace('{format}', 'json')\\n\\n path_params = {} # type: Dict\\n if 'skill_id' in params:\\n path_params['skillId'] = params['skill_id']\\n\\n query_params = [] # type: List\\n\\n header_params = [] # type: List\\n\\n body_params = None\\n if 'create_experiment_request' in params:\\n body_params = params['create_experiment_request']\\n header_params.append(('Content-type', 'application/json'))\\n header_params.append(('User-Agent', self.user_agent))\\n\\n # Response Type\\n full_response = False\\n if 'full_response' in params:\\n full_response = params['full_response']\\n\\n # Authentication setting\\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\\n authorization_value = \\\"Bearer \\\" + access_token\\n header_params.append(('Authorization', authorization_value))\\n\\n error_definitions = [] # type: List\\n error_definitions.append(ServiceClientResponse(response_type=None, status_code=201, message=\\\"Experiment created. Returns the generated experiment identifier in 'Location' header.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.bad_request_error.BadRequestError\\\", status_code=400, message=\\\"Server cannot process the request due to a client error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=401, message=\\\"The auth token is invalid/expired or doesn't have access to the resource.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.bad_request_error.BadRequestError\\\", status_code=403, message=\\\"The operation being requested is not allowed.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=404, message=\\\"The resource being requested is not found.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=429, message=\\\"Exceeds the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=500, message=\\\"Internal Server Error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=503, message=\\\"Service Unavailable.\\\"))\\n\\n api_response = self.invoke(\\n method=\\\"POST\\\",\\n endpoint=self._api_endpoint,\\n path=resource_path,\\n path_params=path_params,\\n query_params=query_params,\\n header_params=header_params,\\n body=body_params,\\n response_definitions=error_definitions,\\n response_type=None)\\n\\n if full_response:\\n return api_response\\n \\n return None\",\n \"def create_experiment(\\n self,\\n name: str,\\n description: str = None,\\n namespace: str = None) -> kfp_server_api.V1Experiment:\\n namespace = namespace or self.get_user_namespace()\\n experiment = None\\n try:\\n experiment = self.get_experiment(\\n experiment_name=name, namespace=namespace)\\n except ValueError as error:\\n # Ignore error if the experiment does not exist.\\n if not str(error).startswith('No experiment is found with name'):\\n raise error\\n\\n if not experiment:\\n logging.info('Creating experiment {}.'.format(name))\\n\\n resource_references = []\\n if namespace:\\n key = kfp_server_api.models.V1ResourceKey(\\n id=namespace,\\n type=kfp_server_api.models.V1ResourceType.NAMESPACE)\\n reference = kfp_server_api.models.V1ResourceReference(\\n key=key,\\n relationship=kfp_server_api.models.V1Relationship.OWNER)\\n resource_references.append(reference)\\n\\n experiment = kfp_server_api.models.V1Experiment(\\n name=name,\\n description=description,\\n resource_references=resource_references)\\n experiment = self._experiment_api.create_experiment(body=experiment)\\n\\n if self._is_ipython():\\n import IPython\\n html = \\\\\\n ('<a href=\\\"%s/#/experiments/details/%s\\\" target=\\\"_blank\\\" >Experiment details</a>.'\\n % (self._get_url_prefix(), experiment.id))\\n IPython.display.display(IPython.display.HTML(html))\\n return experiment\",\n \"def test_create_experiment_hit_no_config(self):\\n with OrionState(experiments=[config]) as cfg:\\n experiment = create_experiment(config[\\\"name\\\"], storage=cfg.storage_config)\\n\\n assert experiment.name == config[\\\"name\\\"]\\n assert experiment.version == 1\\n assert experiment.space.configuration == config[\\\"space\\\"]\\n assert experiment.algorithm\\n assert experiment.algorithm.configuration == config[\\\"algorithm\\\"]\\n assert experiment.max_trials == config[\\\"max_trials\\\"]\\n assert experiment.max_broken == config[\\\"max_broken\\\"]\\n assert experiment.working_dir == config[\\\"working_dir\\\"]\",\n \"def test_create_experiment_no_storage(self, monkeypatch):\\n name = \\\"oopsie_forgot_a_storage\\\"\\n host = orion.core.config.storage.database.host\\n\\n with OrionState(storage=orion.core.config.storage.to_dict()) as cfg:\\n # Reset the Storage and drop instances so that setup_storage() would fail.\\n cfg.cleanup()\\n\\n # Make sure storage must be instantiated during `create_experiment()`\\n # with pytest.raises(SingletonNotInstantiatedError):\\n # setup_storage()\\n\\n experiment = create_experiment(\\n name=name, space={\\\"x\\\": \\\"uniform(0, 10)\\\"}, storage=cfg.storage_config\\n )\\n\\n assert isinstance(experiment._experiment._storage, Legacy)\\n assert isinstance(experiment._experiment._storage._db, PickledDB)\\n assert experiment._experiment._storage._db.host == host\",\n \"def test_create_experiment_new_no_space(self):\\n with OrionState() as cfg:\\n name = \\\"oopsie_forgot_a_space\\\"\\n with pytest.raises(NoConfigurationError) as exc:\\n create_experiment(name=name, storage=cfg.storage_config)\\n\\n assert f\\\"Experiment {name} does not exist in DB\\\" in str(exc.value)\",\n \"def test_create_experiment_new_default(self):\\n name = \\\"all_default\\\"\\n space = {\\\"x\\\": \\\"uniform(0, 10)\\\"}\\n with OrionState() as cfg:\\n experiment = create_experiment(\\n name=\\\"all_default\\\", space=space, storage=cfg.storage_config\\n )\\n\\n assert experiment.name == name\\n assert experiment.space.configuration == space\\n\\n assert experiment.max_trials == orion.core.config.experiment.max_trials\\n assert experiment.max_broken == orion.core.config.experiment.max_broken\\n assert experiment.working_dir == orion.core.config.experiment.working_dir\\n assert experiment.algorithm\\n assert experiment.algorithm.configuration == {\\\"random\\\": {\\\"seed\\\": None}}\",\n \"def experiment_init(self):\\n raise NotImplementedError(\\\"this needs to be implemented!\\\")\",\n \"def main(_):\\n description = xm.ExperimentDescription(\\n FLAGS.exp_name, tags=[\\n FLAGS.env_name,\\n ])\\n experiment = build_experiment()\\n xm.launch_experiment(description, experiment)\",\n \"def with_experiment_using_python_api(storage, monkeypatch, one_experiment):\\n experiment = experiment_builder.build(\\n name=\\\"from-python-api\\\", space={\\\"x\\\": \\\"uniform(0, 10)\\\"}, storage=storage\\n )\\n\\n return experiment\",\n \"def _populate_exp(self):\\n self._exp = self.volume_provider.get_project(\\n ExperimentResource(self._channel.exp_name, self._channel.coll_name)\\n )\",\n \"def __init__(self, exp_params, stamp_unique=True):\\n self._main_thread = True\\n self.params = copy.deepcopy(exp_params)\\n self.params['class'] = self.__class__.__name__\\n self._check_required_params()\\n self.__check_exist_path()\\n self.__create_folder(stamp_unique)\\n set_experiment_logger(self.params['path_exp'], FILE_LOGS)\\n # set stream logging to info level\\n for lh in logging.getLogger().handlers:\\n if isinstance(lh, logging.StreamHandler) and \\\\\\n not isinstance(lh, logging.FileHandler):\\n lh.setLevel(logging.INFO)\\n logging.info('initialise experiment...')\\n logging.info(string_dict(self.params, 'PARAMETERS:'))\\n logging.info('COMPUTER: %r', computer_info())\",\n \"def experiment_init(self):\\n pass\",\n \"def add_experiment(redis, name):\\n\\n if not ALLOWED_NAMES.match(name):\\n raise ExperimentException(name, \\\"Illegal name\\\")\\n if redis.exists(EXPERIMENT_REDIS_KEY_TEMPLATE % name):\\n raise ExperimentException(name, \\\"Already exists\\\")\\n\\n json = dict(creation_date=util.unicode_type(datetime.datetime.now()))\\n pipe = redis.pipeline(transaction=True)\\n pipe.sadd(ACTIVE_EXPERIMENTS_REDIS_KEY, name)\\n pipe.hset(EXPERIMENT_REDIS_KEY_TEMPLATE % name, \\\"metadata\\\", escape.json_encode(json))\\n pipe.execute()\\n return Experiment(redis, name)\",\n \"def experiments_init(self):\\n pass\",\n \"def __init__(self, experiment, **kwargs):\\n \\n # retrieve which experiment to run\\n experiment_function = getattr(self, experiment)\\n\\n if kwargs:\\n kwargs['experiment']=experiment\\n experiment_function(**kwargs)\\n\\n else:\\n kwargs={'experiment':experiment}\\n experiment_function(**kwargs)\",\n \"def create_eval(self):\\n self.ev_id = \\\"ev-\\\" + base64.b32encode(os.urandom(10)).decode(\\\"ascii\\\")\\n self.ev_name = \\\"Evaluation: \\\" + self.ml_name\\n self._ml.create_evaluation(\\n EvaluationId=self.ev_id,\\n EvaluationName=self.ev_name,\\n MLModelId=self.ml_id,\\n EvaluationDataSourceId=self.fold.eval_ds_id\\n )\\n logger.info(\\\"Created Evaluation \\\" + self.ev_id)\",\n \"def test_load_experiment(self):\\n exp = Experiment(self.epath,\\n normalization='ch0',\\n auto_alignment=False)\\n self.assertTrue(isinstance(exp, Experiment))\",\n \"def _onNew(self, event):\\n self.newExperiment()\",\n \"def run_new_session(self, experiment_id, epochs, log_base_path='logs',\\n model_checkpoint_period=2,\\n prediction_checkpoint_period=2):\\n exp = ExperimentDB(\\n self.dbclient, experiment_id=experiment_id,\\n log_base_path=log_base_path\\n ).run_experiment(\\n model_checkpoint_period=model_checkpoint_period,\\n prediction_checkpoint_period=prediction_checkpoint_period,\\n save_origin_images=False, verbose=1, epochs=epochs)\\n\\n return exp\",\n \"def create_experiment(output_dir, X, y, train_steps=1000, num_units=7, output_units=1, num_layers=1):\\n\\n config = {\\n 'name': 'time_series',\\n 'output_dir': output_dir,\\n 'eval_every_n_steps': 100,\\n 'train_steps_per_iteration': 100,\\n 'train_steps': train_steps,\\n 'run_config': {'save_checkpoints_steps': 100},\\n 'train_input_data_config': {\\n 'input_type': plx.configs.InputDataConfig.NUMPY,\\n 'pipeline_config': {'name': 'train', 'batch_size': 64, 'num_epochs': None,\\n 'shuffle': False},\\n 'x': {'x': X['train']},\\n 'y': y['train']\\n },\\n 'eval_input_data_config': {\\n 'input_type': plx.configs.InputDataConfig.NUMPY,\\n 'pipeline_config': {'name': 'eval', 'batch_size': 32, 'num_epochs': None,\\n 'shuffle': False},\\n 'x': {'x': X['val']},\\n 'y': y['val']\\n },\\n 'estimator_config': {'output_dir': output_dir},\\n 'model_config': {\\n 'module': 'Regressor',\\n 'loss_config': {'module': 'mean_squared_error'},\\n 'eval_metrics_config': [{'module': 'streaming_root_mean_squared_error'},\\n {'module': 'streaming_mean_absolute_error'}],\\n 'optimizer_config': {'module': 'adagrad', 'learning_rate': 0.1},\\n 'graph_config': {\\n 'name': 'regressor',\\n 'features': ['x'],\\n 'definition': [\\n (plx.layers.LSTM, {'num_units': num_units, 'num_layers': num_layers}),\\n (plx.layers.FullyConnected, {'num_units': output_units}),\\n ]\\n }\\n }\\n }\\n experiment_config = plx.configs.ExperimentConfig.read_configs(config)\\n return plx.experiments.create_experiment(experiment_config)\",\n \"def add_experiment(self, environment_name, environment_builder_params, agent_name, agent_builder_params):\\n if environment_name in self.environment_list:\\n if agent_name in self.experiment_structure[environment_name]:\\n raise AttributeError('An experiment for environment {} and builders {} already exists.'.format(environment_name, agent_name))\\n else:\\n self.experiment_structure[environment_name][agent_name] = self._create_experiment(environment_name, environment_builder_params, agent_name, agent_builder_params)\\n else:\\n self.environment_list.append(environment_name)\\n self.experiment_structure[environment_name] = {agent_name: self._create_experiment(environment_name, environment_builder_params, agent_name, agent_builder_params)}\\n \\n if agent_name not in self.agent_list:\\n self.agent_list.append(agent_name)\",\n \"def __init__(self, experiment_data):\\n self._experiment_data = experiment_data\",\n \"def openExperiment(self):\\n ext = _EXTS_EXPERIMENT[0]\\n wildcard = 'Transport experiment (*.%s)|*.%s' % (ext, ext)\\n dialog = wx.FileDialog(self, \\\"Open Experiment\\\", c.getExperimentFolder(),\\n '', wildcard, wx.FD_OPEN)\\n if dialog.ShowModal() == wx.ID_OK:\\n experimentPath = dialog.GetPath()\\n experimentName = os.path.basename(experimentPath)\\n if experimentName.endswith(ext):\\n experimentName = experimentName[:-len(ext)-1]\\n experiment = loader.loadExperiment(experimentPath)\\n frame = SequenceFrame(self, experiment, False,\\n title=experimentName,\\n experimentPath=experimentPath)\\n experiment.setInteractionParameters(parentFrame=frame,\\n graphManagerClass=StandardGraphManager)\\n self.frames.append(frame)\\n self.names.append(experimentName)\\n log.info('Opened experiment ' + experimentName)\\n frame.Show()\\n self.Show(False)\",\n \"def Experiment(self, default=None):\\n return self.data.get('experiment', default)\",\n \"def get_config():\\n return ExperimentConfig(base_path=os.getenv(\\\"AICROWD_OUTPUT_PATH\\\", \\\"./scratch/shared\\\"),\\n experiment_name=os.getenv(\\\"AICROWD_EVALUATION_NAME\\\", \\\"experiment_name\\\"),\\n dataset_name=os.getenv(\\\"AICROWD_DATASET_NAME\\\", \\\"cars3d\\\"))\",\n \"def __init__(self, agent_id=\\\"default\\\", experiment_id=\\\"default\\\"):\\n self.runtime = runtime()\\n self.agent_id = agent_id\\n self.experiment_id = experiment_id\",\n \"def _create_new_experiment_dir(self):\\n ls = os.listdir(self.experiment_dir)\\n existing_exp_dirs = [d for d in ls if d.startswith('experiment')]\\n if len(existing_exp_dirs) == 0:\\n out = 'experiment1'\\n else:\\n inds = [int(d.lstrip('experiment')) for d in existing_exp_dirs]\\n out = 'experiment'+str(max(inds)+1)\\n\\n self.new_experiment_dir = os.path.join(self.experiment_dir, out)\\n os.mkdir(self.new_experiment_dir)\\n return None\",\n \"def start(self, config):\\n self.config = config\\n\\n # create experiment folder, initialize config, exp_info\\n print(\\\"creating new experiment folder...\\\")\\n self._create_new_experiment_dir()\\n self.config_path = os.path.join(self.new_experiment_dir, 'experiment.config')\\n self.experiment_info_path = os.path.join(self.new_experiment_dir, 'info.txt')\\n\\n # save config\\n print(\\\"saving experiment config...\\\")\\n self._write_config(self.config_path)\\n\\n # save experiment info\\n print(\\\"saving experiment info...\\\")\\n self._write_experiment_info(self.experiment_info_path)\\n\\n return None\",\n \"def start_experiment():\\r\\n check_parameters()\\r\\n try:\\r\\n EXP.start()\\r\\n except InputError as inst:\\r\\n tkMessageBox.showinfo(inst.expr, inst.msg)\",\n \"def test_create_experiment_new_full_config(self, user_config):\\n with OrionState() as cfg:\\n experiment = create_experiment(**user_config, storage=cfg.storage_config)\\n\\n exp_config = experiment.configuration\\n\\n assert exp_config[\\\"space\\\"] == config[\\\"space\\\"]\\n assert exp_config[\\\"max_trials\\\"] == config[\\\"max_trials\\\"]\\n assert exp_config[\\\"max_broken\\\"] == config[\\\"max_broken\\\"]\\n assert exp_config[\\\"working_dir\\\"] == config[\\\"working_dir\\\"]\\n assert exp_config[\\\"algorithm\\\"] == config[\\\"algorithm\\\"]\",\n \"def with_experiment_params(self, **params):\\n self.experiment_params = params\\n return self\",\n \"def test_create_experiment_hit_no_branch(self, user_config):\\n with OrionState(experiments=[config]) as cfg:\\n experiment = create_experiment(**user_config, storage=cfg.storage_config)\\n\\n exp_config = experiment.configuration\\n\\n assert experiment.name == config[\\\"name\\\"]\\n assert experiment.version == 1\\n assert exp_config[\\\"space\\\"] == config[\\\"space\\\"]\\n assert exp_config[\\\"max_trials\\\"] == config[\\\"max_trials\\\"]\\n assert exp_config[\\\"max_broken\\\"] == config[\\\"max_broken\\\"]\\n assert exp_config[\\\"working_dir\\\"] == config[\\\"working_dir\\\"]\\n assert exp_config[\\\"algorithm\\\"] == config[\\\"algorithm\\\"]\",\n \"def only_experiments_db(storage, exp_config):\\n for exp in exp_config[0]:\\n storage.create_experiment(exp)\",\n \"def get_experiment_v1(self, skill_id, experiment_id, **kwargs):\\n # type: (str, str, **Any) -> Union[ApiResponse, object, GetExperimentResponse_fcd92c35, StandardizedError_f5106a89, BadRequestError_f854b05]\\n operation_name = \\\"get_experiment_v1\\\"\\n params = locals()\\n for key, val in six.iteritems(params['kwargs']):\\n params[key] = val\\n del params['kwargs']\\n # verify the required parameter 'skill_id' is set\\n if ('skill_id' not in params) or (params['skill_id'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `skill_id` when calling `\\\" + operation_name + \\\"`\\\")\\n # verify the required parameter 'experiment_id' is set\\n if ('experiment_id' not in params) or (params['experiment_id'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `experiment_id` when calling `\\\" + operation_name + \\\"`\\\")\\n\\n resource_path = '/v1/skills/{skillId}/experiments/{experimentId}'\\n resource_path = resource_path.replace('{format}', 'json')\\n\\n path_params = {} # type: Dict\\n if 'skill_id' in params:\\n path_params['skillId'] = params['skill_id']\\n if 'experiment_id' in params:\\n path_params['experimentId'] = params['experiment_id']\\n\\n query_params = [] # type: List\\n\\n header_params = [] # type: List\\n\\n body_params = None\\n header_params.append(('Content-type', 'application/json'))\\n header_params.append(('User-Agent', self.user_agent))\\n\\n # Response Type\\n full_response = False\\n if 'full_response' in params:\\n full_response = params['full_response']\\n\\n # Authentication setting\\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\\n authorization_value = \\\"Bearer \\\" + access_token\\n header_params.append(('Authorization', authorization_value))\\n\\n error_definitions = [] # type: List\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.experiment.get_experiment_response.GetExperimentResponse\\\", status_code=200, message=\\\"Returned skill experiment.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=401, message=\\\"The auth token is invalid/expired or doesn't have access to the resource.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.bad_request_error.BadRequestError\\\", status_code=403, message=\\\"The operation being requested is not allowed.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=404, message=\\\"The resource being requested is not found.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=429, message=\\\"Exceeds the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=500, message=\\\"Internal Server Error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=503, message=\\\"Service Unavailable.\\\"))\\n\\n api_response = self.invoke(\\n method=\\\"GET\\\",\\n endpoint=self._api_endpoint,\\n path=resource_path,\\n path_params=path_params,\\n query_params=query_params,\\n header_params=header_params,\\n body=body_params,\\n response_definitions=error_definitions,\\n response_type=\\\"ask_smapi_model.v1.skill.experiment.get_experiment_response.GetExperimentResponse\\\")\\n\\n if full_response:\\n return api_response\\n return api_response.body\",\n \"def with_experiment_missing_conf_file(monkeypatch, one_experiment, storage, orionstate):\\n exp = experiment_builder.build(name=\\\"test_single_exp\\\", version=1, storage=storage)\\n conf_file = \\\"idontexist.yaml\\\"\\n exp.metadata[\\\"user_config\\\"] = conf_file\\n exp.metadata[\\\"user_args\\\"] += [\\\"--config\\\", conf_file]\\n\\n orionstate.database.write(\\\"experiments\\\", exp.configuration, query={\\\"_id\\\": exp.id})\\n\\n return exp\",\n \"def test_create_experiment_debug_mode(self, tmp_path):\\n\\n conf_file = str(tmp_path / \\\"db.pkl\\\")\\n\\n experiment = create_experiment(\\n config[\\\"name\\\"],\\n space={\\\"x\\\": \\\"uniform(0, 10)\\\"},\\n storage={\\n \\\"type\\\": \\\"legacy\\\",\\n \\\"database\\\": {\\\"type\\\": \\\"pickleddb\\\", \\\"host\\\": conf_file},\\n },\\n )\\n\\n storage = experiment._experiment._storage\\n assert isinstance(storage, Legacy)\\n assert isinstance(storage._db, PickledDB)\\n\\n experiment = create_experiment(\\n config[\\\"name\\\"],\\n space={\\\"x\\\": \\\"uniform(0, 10)\\\"},\\n storage={\\\"type\\\": \\\"legacy\\\", \\\"database\\\": {\\\"type\\\": \\\"pickleddb\\\"}},\\n debug=True,\\n )\\n\\n storage = experiment._experiment._storage\\n assert isinstance(storage, Legacy)\\n assert isinstance(storage._db, EphemeralDB)\",\n \"def test_create_experiment(client, users):\\n login_experimenter(client)\\n\\n exp = ExperimentFactory()\\n datetime_format = \\\"%Y-%m-%d %H:%M:%S\\\"\\n\\n response = client.post(\\\"/experiments/\\\", data=dict(\\n name=exp.name,\\n start=exp.start.strftime(datetime_format),\\n stop=exp.stop.strftime(datetime_format),\\n blurb=exp.blurb))\\n assert response.status_code == 200\\n assert json_success(response.data)\\n\\n response = client.get(\\\"/experiments/\\\")\\n data = response.data.decode(response.charset)\\n assert response.status_code == 200\\n assert exp.name in data\\n\\n response = client.post(\\\"/experiments/\\\", data=dict(\\n start=exp.start.strftime(datetime_format),\\n stop=exp.stop.strftime(datetime_format),\\n blurb=exp.blurb))\\n data = response.data.decode(response.charset)\\n json_data = json.loads(data)\\n assert json_data[\\\"success\\\"] == 0\\n assert json_data[\\\"errors\\\"]\\n\\n response = client.post(\\\"/experiments/\\\", data=dict(\\n name=exp.name,\\n start=exp.start.strftime(datetime_format),\\n stop=exp.start.strftime(datetime_format),\\n blurb=exp.blurb))\\n data = response.data.decode(response.charset)\\n json_data = json.loads(data)\\n assert json_data[\\\"success\\\"] == 0\\n assert json_data[\\\"errors\\\"]\\n\\n response = client.post(\\\"/experiments/\\\", data=dict(\\n name=exp.name,\\n start=(datetime.now() - timedelta(days=5)).strftime(datetime_format),\\n stop=(datetime.now() - timedelta(days=1)).strftime(datetime_format),\\n blurb=exp.blurb))\\n data = response.data.decode(response.charset)\\n json_data = json.loads(data)\\n assert json_data[\\\"success\\\"] == 0\\n assert json_data[\\\"errors\\\"]\",\n \"def test_create_experiment_bad_storage(self):\\n name = \\\"oopsie_bad_storage\\\"\\n # Make sure there is no existing storage singleton\\n\\n with pytest.raises(NotImplementedError) as exc:\\n create_experiment(\\n name=name,\\n storage={\\\"type\\\": \\\"legacy\\\", \\\"database\\\": {\\\"type\\\": \\\"idontexist\\\"}},\\n )\\n\\n assert \\\"Could not find implementation of Database, type = 'idontexist'\\\" in str(\\n exc.value\\n )\",\n \"def one_experiment(monkeypatch, storage):\\n monkeypatch.chdir(os.path.dirname(os.path.abspath(__file__)))\\n name = \\\"test_single_exp\\\"\\n orion.core.cli.main(\\n [\\\"hunt\\\", \\\"--init-only\\\", \\\"-n\\\", name, \\\"./black_box.py\\\", \\\"--x~uniform(0,1)\\\"]\\n )\\n ensure_deterministic_id(name, storage)\\n return storage.fetch_experiments({\\\"name\\\": name})[0]\",\n \"def run(self, *args, **kwargs):\\n from klibs.KLGraphics.KLDraw import Ellipse\\n \\n if P.eye_tracking:\\n RED = (255, 0, 0)\\n WHITE = (255, 255, 255)\\n self.tracker_dot = Ellipse(8, stroke=[2, WHITE], fill=RED).render()\\n if not P.manual_eyelink_setup:\\n self.el.setup()\\n\\n self.setup()\\n try:\\n self.__execute_experiment__(*args, **kwargs)\\n except RuntimeError:\\n print(full_trace())\\n\\n self.quit()\",\n \"def test_expand_experiments():\\n template_script = get_template_script()\\n experiment_systems = utils.CombinatorialLeaf(['explicit-system', 'implicit-system', 'hydration-system'])\\n template_script['experiments']['system'] = experiment_systems\\n\\n exp_builder = ExperimentBuilder(script=template_script, job_id=1, n_jobs=2)\\n experiments = list(exp_builder._expand_experiments())\\n assert len(experiments) == 2\\n\\n exp_builder = ExperimentBuilder(script=template_script, job_id=2, n_jobs=2)\\n experiments = list(exp_builder._expand_experiments())\\n assert len(experiments) == 1\",\n \"def experiment_pb(\\n hparam_infos,\\n metric_infos,\\n user=\\\"\\\",\\n description=\\\"\\\",\\n time_created_secs=None):\\n if time_created_secs is None:\\n time_created_secs = time.time()\\n experiment = api_pb2.Experiment(\\n description=description,\\n user=user,\\n time_created_secs=time_created_secs,\\n hparam_infos=hparam_infos,\\n metric_infos=metric_infos)\\n return _summary(metadata.EXPERIMENT_TAG,\\n plugin_data_pb2.HParamsPluginData(experiment=experiment))\",\n \"def delete(ctx):\\n user, project_name, _experiment = get_project_experiment_or_local(ctx.obj.get('project'),\\n ctx.obj.get('experiment'))\\n if not click.confirm(\\\"Are sure you want to delete experiment `{}`\\\".format(_experiment)):\\n click.echo('Existing without deleting experiment.')\\n sys.exit(1)\\n\\n try:\\n response = PolyaxonClient().experiment.delete_experiment(\\n user, project_name, _experiment)\\n # Purge caching\\n ExperimentManager.purge()\\n except (PolyaxonHTTPError, PolyaxonShouldExitError, PolyaxonClientException) as e:\\n Printer.print_error('Could not delete experiment `{}`.'.format(_experiment))\\n Printer.print_error('Error message `{}`.'.format(e))\\n sys.exit(1)\\n\\n if response.status_code == 204:\\n Printer.print_success(\\\"Experiment `{}` was delete successfully\\\".format(_experiment))\",\n \"def create_mlflow_experiment(experiment_name: Text, mode: oct = 0o777) -> int:\\n\\n mlflow.set_experiment(experiment_name)\\n experiment = mlflow.get_experiment_by_name(experiment_name)\\n artifact_location = experiment.artifact_location.replace('file://', '')\\n\\n if not os.path.exists(artifact_location):\\n os.mkdir(artifact_location)\\n os.chmod(artifact_location, mode) # Change the access permissions\\n\\n return experiment.experiment_id\",\n \"def test_init(self):\\n ex = Experiment(note=\\\"Test\\\")\\n self.assertEqual(ex.note, \\\"Test\\\")\",\n \"def _load_experiment(\\n experiment_name: str, decoder: Decoder, reduced_state: bool = False\\n) -> Experiment:\\n # Convert SQA to user-facing class outside of session scope to avoid timeouts\\n return decoder.experiment_from_sqa(\\n experiment_sqa=_get_experiment_sqa_reduced_state(\\n experiment_name=experiment_name, decoder=decoder\\n )\\n if reduced_state\\n else _get_experiment_sqa(experiment_name=experiment_name, decoder=decoder),\\n reduced_state=reduced_state,\\n )\",\n \"def test_run_experiment_locally(self) -> None:\\n\\n experiment = Experiment(\\n name=\\\"torchx_booth_sequential_demo\\\",\\n search_space=SearchSpace(parameters=self._parameters),\\n optimization_config=OptimizationConfig(objective=self._objective),\\n runner=self._runner,\\n is_test=True,\\n properties={Keys.IMMUTABLE_SEARCH_SPACE_AND_OPT_CONF: True},\\n )\\n\\n scheduler = Scheduler(\\n experiment=experiment,\\n generation_strategy=(\\n choose_generation_strategy(\\n search_space=experiment.search_space,\\n )\\n ),\\n options=SchedulerOptions(),\\n )\\n\\n try:\\n for _ in range(3):\\n scheduler.run_n_trials(max_trials=2)\\n\\n # TorchXMetric always returns trial index; hence the best experiment\\n # for min objective will be the params for trial 0.\\n scheduler.report_results()\\n except FailureRateExceededError:\\n pass # TODO(ehotaj): Figure out why this test fails in OSS.\\n # Nothing to assert, just make sure experiment runs.\",\n \"def _create_sample_episode(self) -> study_pb2.Episode:\\n study_id, session_id = self.init_session()\\n episode = sample_episode(study_id=study_id, session_id=session_id)\\n self.storage.create_episode(episode)\\n return episode\",\n \"def test_run_experiment():\\n with mmtools.utils.temporary_directory() as tmp_dir:\\n yaml_content = \\\"\\\"\\\"\\n ---\\n options:\\n resume_setup: no\\n resume_simulation: no\\n default_number_of_iterations: 0\\n output_dir: {}\\n setup_dir: ''\\n experiments_dir: ''\\n minimize: no\\n annihilate_sterics: yes\\n molecules:\\n T4lysozyme:\\n filepath: {}\\n leap: {{parameters: oldff/leaprc.ff14SB}}\\n select: 0\\n p-xylene:\\n filepath: {}\\n antechamber: {{charge_method: bcc}}\\n leap: {{parameters: leaprc.gaff}}\\n solvents:\\n vacuum:\\n nonbonded_method: NoCutoff\\n GBSA-OBC2:\\n nonbonded_method: NoCutoff\\n implicit_solvent: OBC2\\n protocols:{}\\n systems:\\n system:\\n receptor: T4lysozyme\\n ligand: p-xylene\\n solvent: !Combinatorial [vacuum, GBSA-OBC2]\\n experiments:\\n system: system\\n protocol: absolute-binding\\n restraint:\\n type: FlatBottom\\n spring_constant: 0.6*kilocalorie_per_mole/angstroms**2\\n well_radius: 5.2*nanometers\\n restrained_receptor_atoms: 1644\\n restrained_ligand_atoms: 2609\\n options:\\n temperature: 302.0*kelvin\\n \\\"\\\"\\\".format(tmp_dir, examples_paths()['lysozyme'], examples_paths()['p-xylene'],\\n indent(standard_protocol))\\n\\n exp_builder = ExperimentBuilder(textwrap.dedent(yaml_content))\\n\\n # Now check_setup_resume should not raise exceptions\\n exp_builder._check_resume()\\n\\n # We setup a molecule and with resume_setup: now we can't do the experiment\\n err_msg = ''\\n exp_builder._options['resume_setup'] = False\\n exp_builder._db._setup_molecules('p-xylene')\\n try:\\n exp_builder.run_experiments()\\n except YamlParseError as e:\\n err_msg = str(e)\\n assert 'molecule' in err_msg\\n\\n # Same thing with a system\\n err_msg = ''\\n system_dir = os.path.dirname(\\n exp_builder._db.get_system('system_GBSAOBC2')[0].position_path)\\n try:\\n exp_builder.run_experiments()\\n except YamlParseError as e:\\n err_msg = str(e)\\n assert 'system' in err_msg\\n\\n # Now we set resume_setup to True and things work\\n exp_builder._options['resume_setup'] = True\\n ligand_dir = exp_builder._db.get_molecule_dir('p-xylene')\\n frcmod_file = os.path.join(ligand_dir, 'p-xylene.frcmod')\\n prmtop_file = os.path.join(system_dir, 'complex.prmtop')\\n molecule_last_touched = os.stat(frcmod_file).st_mtime\\n system_last_touched = os.stat(prmtop_file).st_mtime\\n exp_builder.run_experiments()\\n\\n # Neither the system nor the molecule has been processed again\\n assert molecule_last_touched == os.stat(frcmod_file).st_mtime\\n assert system_last_touched == os.stat(prmtop_file).st_mtime\\n\\n # The experiments folders are correctly named and positioned\\n for exp_name in ['systemvacuum', 'systemGBSAOBC2']:\\n # The output directory must be the one in the experiment section\\n output_dir = os.path.join(tmp_dir, exp_name)\\n assert os.path.isdir(output_dir)\\n assert os.path.isfile(os.path.join(output_dir, 'complex.nc'))\\n assert os.path.isfile(os.path.join(output_dir, 'solvent.nc'))\\n assert os.path.isfile(os.path.join(output_dir, exp_name + '.yaml'))\\n assert os.path.isfile(os.path.join(output_dir, exp_name + '.log'))\\n\\n # Analysis script is correct\\n analysis_script_path = os.path.join(output_dir, 'analysis.yaml')\\n with open(analysis_script_path, 'r') as f:\\n assert yaml.load(f, Loader=yaml.FullLoader) == [['complex', 1], ['solvent', -1]]\\n\\n # Now we can't run the experiment again with resume_simulation: no\\n exp_builder._options['resume_simulation'] = False\\n try:\\n exp_builder.run_experiments()\\n except YamlParseError as e:\\n err_msg = str(e)\\n assert 'experiment' in err_msg\\n\\n # We set resume_simulation: yes and now things work\\n exp_builder._options['resume_simulation'] = True\\n exp_builder.run_experiments()\",\n \"def main(_):\\n description = xm.ExperimentDescription(\\n 'HIS - trial=%d' % FLAGS.trial, tags=['his'])\\n experiment = build_experiment()\\n xm.launch_experiment(description, experiment)\",\n \"def new_experiment_from_components(self, dataset_params, input_params,\\n architecture, model_params,\\n train_params=None,\\n name='', description=''):\\n exp_name = name or ''\\n try:\\n # find each component by id then create the full JSON\\n dataset_params_obj = self.dbclient.find_by_id(\\n ConfigRef.DATASET_PARAMS, dataset_params)\\n dataset_params_cf = dataset_params_obj[RefAttr.CONFIG]\\n\\n input_params_obj = self.dbclient.find_by_id(\\n ConfigRef.INPUT_PARAMS, input_params)\\n input_params_cf = input_params_obj[RefAttr.CONFIG]\\n\\n architecture_obj = self.dbclient.find_by_id(\\n ConfigRef.ARCHITECTURE, architecture)\\n architecture_cf = architecture_obj[RefAttr.CONFIG]\\n\\n model_params_obj = self.dbclient.find_by_id(\\n ConfigRef.MODEL_PARAMS, model_params)\\n model_params_cf = model_params_obj[RefAttr.CONFIG]\\n\\n if train_params:\\n train_params_obj = self.dbclient.find_by_id(\\n ConfigRef.TRAIN_PARAMS, train_params)\\n train_params_cf = train_params_obj[RefAttr.CONFIG]\\n else:\\n train_params_cf = '{ }'\\n\\n config = self._new_config_from_components(\\n dataset_params_cf, input_params_cf, architecture_cf,\\n model_params_cf, train_params_cf\\n )\\n\\n if not name:\\n exp_name = ' - '.join([\\n dataset_params_obj[RefAttr.NAME],\\n input_params_obj[RefAttr.NAME],\\n architecture_obj[RefAttr.NAME],\\n model_params_obj[RefAttr.NAME],\\n train_params_obj[RefAttr.NAME] if train_params else '',\\n ])\\n return self.new_experiment_from_full_config(\\n exp_name, config, description=description)\\n except Exception:\\n return None\",\n \"def set_experiment(self, new_exp=False):\\n self.id = str(self.Id_widget.text()).strip()\\n if self.id == '' or self.working_dir is None:\\n msg_window('id and working directory must be entered')\\n return\\n conf_map = {}\\n\\n self.scan = str(self.scan_widget.text()).replace(' ', '')\\n if len(self.scan) > 0:\\n scans = self.scan.split('-')\\n if len(scans) > 2:\\n msg_window('if entering scan or scan range, please enter numeric values, separated with \\\"-\\\" if range')\\n return\\n for sc in scans:\\n try:\\n numeric = int(sc)\\n except:\\n msg_window(\\n 'if entering scan or scan range, please enter numeric values, separated with \\\"-\\\" if range')\\n return\\n conf_map['scan'] = '\\\"' + self.scan + '\\\"'\\n self.exp_id = self.id + '_' + self.scan\\n\\n else:\\n self.exp_id = self.id\\n self.experiment_dir = os.path.join(self.working_dir, self.exp_id)\\n self.assure_experiment_dir()\\n\\n if not new_exp:\\n # read the configurations from GUI and write to experiment config files\\n # save the main config\\n conf_map['working_dir'] = '\\\"' + str(self.working_dir).strip() + '\\\"'\\n conf_map['experiment_id'] = '\\\"' + self.id + '\\\"'\\n if len(self.beamline_widget.text().strip()) > 0:\\n conf_map['beamline'] = '\\\"' + str(self.beamline_widget.text().strip()) + '\\\"'\\n self.beamline = self.beamline_widget.text().strip()\\n if self.specfile is not None:\\n conf_map['specfile'] = '\\\"' + str(self.specfile).strip() + '\\\"'\\n write_conf(conf_map, os.path.join(self.experiment_dir, 'conf'), 'config')\\n\\n if self.t is None:\\n try:\\n self.t = Tabs(self)\\n self.vbox.addWidget(self.t)\\n except:\\n pass\\n\\n if not new_exp:\\n self.t.save_conf()\",\n \"def main():\\n ex = Experiment(SEED)\\n ex.main()\",\n \"def new(cls, etype, ecode, evalue, time=None):\\n e = cls()\\n e.set(etype, ecode, evalue, time)\\n return e\",\n \"def setExperiment(self, **kwargs):\\n # If the dictionary robot value is 'tb1' then change the button Style\\n global robot_Selected_Value\\n if kwargs['robot'] =='1':\\n robot_Selected_Value = 'TB1'\\n elif kwargs['robot'] =='2':\\n robot_Selected_Value = 'TB2'\\n elif kwargs['robot'] =='3':\\n robot_Selected_Value = 'TB3'\\n elif kwargs['robot'] =='4':\\n robot_Selected_Value = 'TB4'\\n elif kwargs['set'] =='OK':\\n # CONFIGURATION VARIABLES\\n robot_Type_Value = self.robot_Selection_Type.currentText()\\n robot_Role_Value = self.robot_Selection_Role.currentText()\\n robot_Task_Value = self.robot_Selection_Task.currentText()\\n robot_Behavior_Value = self.robot_Selection_Behavior.currentText()\\n robot_Experiment_Value = self.robot_Selection_Experiment.currentText()\\n # XML CREATION\\n environmentXMLFile = et.Element('EXP_CONFIGURATIONS')\\n comment = et.Comment(\\\"Experiment Configuration and Variables\\\")\\n environmentXMLFile.append(comment)\\n environmentConfig = et.SubElement(environmentXMLFile, 'ROBOT_SELECTED')\\n environmentConfig.text = str(robot_Selected_Value)\\n environmentConfig = et.SubElement(environmentXMLFile, 'ROBOT_TYPE')\\n environmentConfig.text = str(robot_Type_Value)\\n environmentConfig = et.SubElement(environmentXMLFile, 'ROBOT_ROLE')\\n environmentConfig.text = str(robot_Role_Value)\\n environmentConfig = et.SubElement(environmentXMLFile, 'ROBOT_TASK')\\n environmentConfig.text = str(robot_Task_Value)\\n environmentConfig = et.SubElement(environmentXMLFile, 'ROBOT_BEHAVIOR')\\n environmentConfig.text = str(robot_Behavior_Value)\\n environmentConfig = et.SubElement(environmentXMLFile, 'ROBOT_EXPERIMENT')\\n environmentConfig.text = str(robot_Experiment_Value)\\n try:\\n tree = et.ElementTree(environmentXMLFile)\\n tree.write('experimentConfig.xml', encoding='utf8')\\n sendFiles.sshSendFiles()\\n operationSucess()\\n except Exception:\\n operationError()\",\n \"def test_experiments_authed_experimenter(client, users):\\n login_experimenter(client)\\n\\n response = client.get(\\\"/\\\")\\n data = response.data.decode(response.charset)\\n assert \\\"Hello experimenter\\\" in data\\n\\n exp = ExperimentFactory()\\n assignment_set = AssignmentSet()\\n exp.assignment_sets.append(assignment_set)\\n exp.save()\\n\\n exp_url = \\\"/experiments/\\\" + str(exp.id)\\n\\n response = client.get(\\\"/experiments/\\\")\\n data = response.data.decode(response.charset)\\n assert response.status_code == 200\\n assert exp.name in data\\n\\n response = client.get(exp_url)\\n data = response.data.decode(response.charset)\\n assert response.status_code == 200\\n assert exp.name in data\\n assert \\\"Start\\\" not in data\\n\\n response = client.get(exp_url + \\\"/settings\\\")\\n assert response.status_code == 200\\n\\n response = client.put(exp_url)\\n assert response.status_code == 200\\n\\n response = client.delete(exp_url)\\n assert response.status_code == 200\\n assert json_success(response.data)\",\n \"def _construct_new_expert(self):\\n return self.WeightedExpert(\\n cp.deepcopy(self.base_estimator), 1, self.labels)\",\n \"def new_experiment_from_full_config(self, name, config, description=''):\\n new_exp = {\\n ExperimentAttr.NAME: name,\\n ExperimentAttr.CONFIG: config,\\n ExperimentAttr.DESC: description\\n }\\n\\n return self.dbclient.insert(Tables.EXPERIMENTS, new_exp).inserted_id\",\n \"def build_experiment():\\n\\n # ====== Argument creation ======\\n model_dir = FLAGS.model_dir.format(\\n cell=FLAGS.cell,\\n user=getpass.getuser(),\\n trial=FLAGS.trial,\\n )\\n\\n # ====== Jobs and runtime creation ======\\n\\n # Job: worker\\n requirements = xm.Requirements(gpu_types=[xm.GpuType.V100],)\\n runtime_worker = xm.Borg(\\n cell=FLAGS.cell,\\n priority=FLAGS.priority,\\n requirements=requirements,\\n )\\n exec_worker = xm.BuildTarget(\\n '//experimental/users/gjt/his:mnist',\\n name='worker',\\n args=dict(\\n gfs_user=FLAGS.gfs_user,\\n logdir=model_dir,\\n mode='train',\\n ),\\n platform=xm.Platform.GPU,\\n runtime=runtime_worker,\\n )\\n\\n # Job: eval\\n runtime_eval = xm.Borg(\\n cell=FLAGS.cell,\\n priority=FLAGS.priority,\\n )\\n exec_eval = xm.BuildTarget(\\n '//experimental/users/gjt/his:mnist',\\n name='eval',\\n args=dict(\\n gfs_user=FLAGS.gfs_user,\\n logdir=model_dir,\\n mode='eval',\\n split='train,valid,test',\\n num_iwae_samples='1,1,1000',\\n ),\\n platform=xm.Platform.GPU, # Do we need GPU for eval?\\n runtime=runtime_eval,\\n )\\n\\n # ====== Executable experiment creation ======\\n list_executables = []\\n list_executables.append(xm_helper.build_single_job(exec_worker))\\n list_executables.append(xm_helper.build_single_job(exec_eval))\\n\\n experiment = xm.ParallelExecutable(list_executables, name='his_service')\\n\\n # Build experiments\\n hyper_parameters = {}\\n\\n # SNIS vs LARS\\n hyper_parameters['snis_vs_lars'] = hyper.product([\\n hyper.chainit([\\n hyper.product([\\n hyper.fixed('proposal', 'gaussian', length=1),\\n hyper.fixed('model', 'bernoulli_vae', length=1),\\n ]),\\n hyper.product([\\n hyper.fixed('proposal', 'bernoulli_vae', length=1),\\n hyper.fixed('model', 'nis', length=1),\\n ]),\\n hyper.product([\\n hyper.fixed('proposal', 'nis', length=1),\\n hyper.fixed('model', 'bernoulli_vae', length=1),\\n ]),\\n ]),\\n hyper.sweep('run', hyper.discrete([0])),\\n hyper.fixed('dataset', 'static_mnist', length=1),\\n hyper.fixed('reparameterize_proposal', False, length=1),\\n hyper.fixed('anneal_kl_step', 100000, length=1),\\n ])\\n\\n # Continuous comparisons: HIS, NIS, VAE\\n hyper_parameters['continuous'] = hyper.product([\\n hyper.chainit([\\n hyper.product([\\n hyper.fixed('proposal', 'gaussian', length=1),\\n hyper.fixed('model', 'gaussian_vae', length=1),\\n ]),\\n hyper.product([\\n hyper.fixed('proposal', 'gaussian_vae', length=1),\\n hyper.fixed('model', 'nis', length=1),\\n ]),\\n hyper.product([\\n hyper.fixed('proposal', 'gaussian', length=1),\\n hyper.fixed('model', 'hisvae', length=1),\\n hyper.sweep('his_T', hyper.discrete([5, 10, 15])),\\n ]),\\n ]),\\n hyper.sweep('run', hyper.discrete([0])),\\n hyper.fixed('dataset', 'jittered_mnist', length=1),\\n hyper.fixed('reparameterize_proposal', True, length=1),\\n hyper.fixed('squash', True, length=1),\\n ])\\n\\n hyper_parameters['celeba'] = hyper.product([\\n hyper.chainit([\\n hyper.product([\\n hyper.fixed('proposal', 'gaussian', length=1),\\n hyper.fixed('model', 'conv_gaussian_vae', length=1),\\n ]),\\n ]),\\n hyper.sweep('run', hyper.discrete([0])),\\n hyper.fixed('dataset', 'jittered_celeba', length=1),\\n hyper.fixed('reparameterize_proposal', True, length=1),\\n hyper.fixed('squash', True, length=1),\\n hyper.fixed('latent_dim', 16, length=1),\\n hyper.fixed('batch_size', 36, length=1),\\n ])\\n\\n experiment = xm.ParameterSweep(experiment, hyper_parameters[FLAGS.exp_type])\\n experiment = xm.WithTensorBoard(experiment, model_dir)\\n\\n return experiment\",\n \"def test_init_experiment(self):\\n optimizer = \\\"RandomSearch\\\"\\n name = \\\"test_init_experiment\\\"\\n param_defs = {\\n \\\"x\\\": MinMaxNumericParamDef(0, 1),\\n \\\"name\\\": NominalParamDef([\\\"A\\\", \\\"B\\\", \\\"C\\\"])\\n }\\n minimization = True\\n\\n LAss = PrettyLabAssistant()\\n LAss.init_experiment(name, optimizer, param_defs, minimization=minimization)\\n\\n exp_ass = LAss.exp_assistants[name]\\n\\n assert_equal(exp_ass.optimizer, optimizer)\\n assert_is_none(exp_ass.optimizer_arguments, None)\\n assert_equal(exp_ass.experiment.minimization_problem, minimization)\\n with assert_raises(ValueError):\\n LAss.init_experiment(name, optimizer, param_defs, minimization=minimization)\",\n \"def new(self):\\n uuid = uuid4().hex\\n cur = self.conn.cursor()\\n cur.execute(\\n \\\"\\\"\\\"\\n INSERT INTO experiments (uuid)\\n VALUES(?)\\n \\\"\\\"\\\", [uuid])\\n cur.close()\\n self.conn.commit()\\n return uuid\",\n \"def load_experiment(\\n experiment_name: str,\\n config: Optional[SQAConfig] = None,\\n reduced_state: bool = False,\\n) -> Experiment:\\n config = config or SQAConfig()\\n decoder = Decoder(config=config)\\n return _load_experiment(\\n experiment_name=experiment_name, decoder=decoder, reduced_state=reduced_state\\n )\",\n \"def make_experiment(\\n path, experiment_name, experiment_info, verbosity, log_dir, output_path\\n):\\n experiment_dir = output_path / experiment_name\\n if experiment_dir.is_dir():\\n return\\n experiment_dir.mkdir(parents=True)\\n\\n experiment_params = get_experiment_params(experiment_name, verbosity, log_dir)\\n with (experiment_dir / \\\"experiment_params.json\\\").open(\\\"w\\\") as f:\\n json.dump(experiment_params, f)\\n\\n for filename, filepath in experiment_info.items():\\n filename += \\\".json\\\"\\n new_path = experiment_dir / filename\\n shutil.copy(filepath, new_path)\",\n \"def experiments(self, key, value):\\n experiments = self.get('experiments', [])\\n\\n name = value.get('e')\\n recid = value.get('0')\\n record = get_record_ref(recid, 'experiments')\\n\\n experiments.append({\\n 'curated_relation': record is not None,\\n 'name': name,\\n 'record': record\\n })\\n\\n return experiments\",\n \"def __init__(self, exp_spec: ExperimentSpec, agent_root_dir: str = None):\\n \\n if agent_root_dir is not None:\\n self.agent_root_dir = agent_root_dir\\n else:\\n self._use_hardcoded_agent_root_directory()\\n \\n self.exp_spec = exp_spec\\n \\n try:\\n hec = exp_spec['harderEnvCoeficient']\\n self.playground = GymPlayground(environment_name=exp_spec.prefered_environment, harderEnvCoeficient=hec)\\n except KeyError:\\n self.playground = GymPlayground(environment_name=exp_spec.prefered_environment)\\n \\n \\\"\\\"\\\" ---- Init computation graph ---- \\\"\\\"\\\"\\n # required placeholder for Agent.play() methode\\n self.obs_t_ph = None\\n self.policy_pi = None\\n \\n self._build_computation_graph()\\n \\n not_implemented_msg = \\\"must be set by _build_computation_graph()\\\"\\n assert self.obs_t_ph is not None, \\\"self.obs_t_ph {}\\\".format(not_implemented_msg)\\n assert self.policy_pi is not None, \\\"self.policy_pi {}\\\".format(not_implemented_msg)\\n \\n \\\"\\\"\\\" ---- Setup parameters saving ---- \\\"\\\"\\\"\\n self.saver = tf_cv1.train.Saver()\\n self.writer = None\\n self.this_run_dir = None\",\n \"def experiment(\\n self,\\n dataset: Union[str, dict, pd.DataFrame] = None,\\n training_set: Union[str, dict, pd.DataFrame] = None,\\n validation_set: Union[str, dict, pd.DataFrame] = None,\\n test_set: Union[str, dict, pd.DataFrame] = None,\\n training_set_metadata: Union[str, dict] = None,\\n data_format: str = None,\\n experiment_name: str = \\\"experiment\\\",\\n model_name: str = \\\"run\\\",\\n model_load_path: str = None,\\n model_resume_path: str = None,\\n eval_split: str = TEST,\\n skip_save_training_description: bool = False,\\n skip_save_training_statistics: bool = False,\\n skip_save_model: bool = False,\\n skip_save_progress: bool = False,\\n skip_save_log: bool = False,\\n skip_save_processed_input: bool = False,\\n skip_save_unprocessed_output: bool = False,\\n skip_save_predictions: bool = False,\\n skip_save_eval_stats: bool = False,\\n skip_collect_predictions: bool = False,\\n skip_collect_overall_stats: bool = False,\\n output_directory: str = \\\"results\\\",\\n random_seed: int = default_random_seed,\\n **kwargs,\\n ) -> Tuple[Optional[dict], TrainingStats, PreprocessedDataset, str]:\\n if self._user_config.get(HYPEROPT):\\n print_boxed(\\\"WARNING\\\")\\n logger.warning(HYPEROPT_WARNING)\\n\\n (train_stats, preprocessed_data, output_directory) = self.train(\\n dataset=dataset,\\n training_set=training_set,\\n validation_set=validation_set,\\n test_set=test_set,\\n training_set_metadata=training_set_metadata,\\n data_format=data_format,\\n experiment_name=experiment_name,\\n model_name=model_name,\\n model_load_path=model_load_path,\\n model_resume_path=model_resume_path,\\n skip_save_training_description=skip_save_training_description,\\n skip_save_training_statistics=skip_save_training_statistics,\\n skip_save_model=skip_save_model,\\n skip_save_progress=skip_save_progress,\\n skip_save_log=skip_save_log,\\n skip_save_processed_input=skip_save_processed_input,\\n skip_save_unprocessed_output=skip_save_unprocessed_output,\\n output_directory=output_directory,\\n random_seed=random_seed,\\n )\\n\\n (training_set, validation_set, test_set, training_set_metadata) = preprocessed_data\\n\\n eval_set = validation_set\\n if eval_split == TRAINING:\\n eval_set = training_set\\n elif eval_split == VALIDATION:\\n eval_set = validation_set\\n elif eval_split == TEST:\\n eval_set = test_set\\n else:\\n logger.warning(f\\\"Eval split {eval_split} not supported. \\\" f\\\"Using validation set instead\\\")\\n\\n if eval_set is not None:\\n trainer_dict = self.config_obj.trainer.to_dict()\\n batch_size = trainer_dict.get(EVAL_BATCH_SIZE, trainer_dict.get(BATCH_SIZE, None))\\n\\n # predict\\n try:\\n eval_stats, _, _ = self.evaluate(\\n eval_set,\\n data_format=data_format,\\n batch_size=batch_size,\\n output_directory=output_directory,\\n skip_save_unprocessed_output=skip_save_unprocessed_output,\\n skip_save_predictions=skip_save_predictions,\\n skip_save_eval_stats=skip_save_eval_stats,\\n collect_predictions=not skip_collect_predictions,\\n collect_overall_stats=not skip_collect_overall_stats,\\n return_type=\\\"dict\\\",\\n )\\n except NotImplementedError:\\n logger.warning(\\n \\\"Skipping evaluation as the necessary methods are not \\\"\\n \\\"supported. Full exception below:\\\\n\\\"\\n f\\\"{traceback.format_exc()}\\\"\\n )\\n eval_stats = None\\n else:\\n logger.warning(f\\\"The evaluation set {eval_set} was not provided. \\\" f\\\"Skipping evaluation\\\")\\n eval_stats = None\\n\\n return eval_stats, train_stats, preprocessed_data, output_directory\",\n \"def _Run(args, version):\\n validation.ValidateDisplayName(args.display_name)\\n\\n tensorboard_ref = args.CONCEPTS.tensorboard.Parse()\\n region = tensorboard_ref.AsDict()['locationsId']\\n with endpoint_util.AiplatformEndpointOverrides(version, region=region):\\n tensorboard_experiments_client = client.TensorboardExperimentsClient(\\n version=version)\\n response = tensorboard_experiments_client.Create(tensorboard_ref, args)\\n if response.name:\\n log.status.Print(('Created Vertex AI Tensorboard experiment: {}.').format(\\n response.name))\\n return response\",\n \"def __init__(\\n self,\\n config,\\n experiment_id,\\n training_workflow_metadata={},\\n hosting_workflow_metadata={},\\n joining_workflow_metadata={},\\n evaluation_workflow_metadata={},\\n ):\\n self.boto_session = boto3.Session()\\n self._region_name = self.boto_session.region_name\\n self.account = self.boto_session.client(\\\"sts\\\").get_caller_identity()[\\\"Account\\\"]\\n if self._region_name is None:\\n raise ValueError(\\\"Must setup AWS configuration with a valid region\\\")\\n\\n # unique id common across all experiments in the account\\n self.experiment_id = experiment_id\\n\\n # load configs\\n self.config = config\\n self.image = self.config.get(\\\"image\\\", None).replace(\\\"{AWS_REGION}\\\", self._region_name)\\n self.algor_config = self.config.get(\\\"algor\\\", {})\\n self.local_mode = self.config.get(\\\"local_mode\\\", True)\\n if self.local_mode:\\n self._update_instance_type_for_local_mode()\\n self.sagemaker_session = LocalSession()\\n else:\\n self.sagemaker_session = sagemaker.session.Session(self.boto_session)\\n\\n self.soft_deployment = self.config.get(\\\"soft_deployment\\\", False)\\n\\n # load resource config and init shared resourced if not exists\\n self.resource_manager = ResourceManager(\\n self.config.get(\\\"resource\\\", {}), boto_session=self.boto_session\\n )\\n self.resource_manager.create_shared_resource_if_not_exist()\\n\\n # init clients\\n self.exp_db_client = self.resource_manager.exp_db_client\\n self.model_db_client = self.resource_manager.model_db_client\\n self.join_db_client = self.resource_manager.join_db_client\\n self.cw_logger = CloudWatchLogger(self.boto_session.client(\\\"cloudwatch\\\"), self._region_name)\\n self.sagemaker_client = self.sagemaker_session.sagemaker_client\\n\\n # init s3 client for rewards upload\\n self.s3_client = self.boto_session.client(\\\"s3\\\")\\n\\n # create a local JoinJobRecord object.\\n self.experiment_record = ExperimentRecord(\\n experiment_id,\\n training_workflow_metadata,\\n hosting_workflow_metadata,\\n joining_workflow_metadata,\\n evaluation_workflow_metadata,\\n )\\n self.next_model_to_train = None\\n self.next_join_job = None\\n self.next_model_to_evaluate = None\\n\\n # Try to save new ExperimentRecord to ExperimentDb. If it throws\\n # RecordAlreadyExistsException, re-read the ExperimentRecord from ExperimentDb,\\n # and use it as initial state\\n try:\\n self.exp_db_client.create_new_experiment_record(self.experiment_record.to_ddb_record())\\n except RecordAlreadyExistsException:\\n logger.warn(\\n f\\\"Experiment with name {self.experiment_id} already exists. \\\"\\n \\\"Reusing current state from ExperimentDb.\\\"\\n )\\n experiment_record = self.exp_db_client.get_experiment_record(experiment_id)\\n self.experiment_record = ExperimentRecord.load_from_ddb_record(experiment_record)\\n except Exception as e:\\n logger.error(\\\"Unhandled Exception! \\\" + str(e))\\n raise UnhandledWorkflowException(\\\"Something went wrong while creating a new experiment\\\")\\n\\n try:\\n self.cw_logger.create_cloudwatch_dashboard_from_experiment_id(self.experiment_id)\\n except Exception as e:\\n logger.error(\\\"Unable to create CloudWatch Dashboard.\\\" + str(e))\\n logger.error(\\n \\\"To see metrics on CloudWatch, run bandit_experiment.\\\"\\n \\\"cw_logger.create_cloudwatch_dashboard_from_experiment_id function again.\\\"\\n )\\n\\n # start a daemon thread to sync ExperimentDb states to local states\\n # the daemon thread will keep running till the session ends\\n self.sync_thread = ExperimentManagerSyncThread(experiment_manager=self)\\n\\n # Run the thread in SageMaker mode only\\n if not self.local_mode:\\n self.sync_thread.setDaemon(True)\\n self.sync_thread.start()\",\n \"def create_experiment_from_api(self, experiment_accession_code: str) -> Tuple[Experiment, Dict]:\\n\\n try:\\n experiment_data = self._get_experiment_data(accession_code=experiment_accession_code)\\n except KeyError:\\n logger.error(\\n \\\"Could not collect data from remote experiment source!\\\",\\n experiment_accession_code=experiment_accession_code,\\n survey_job=self.survey_job.id,\\n )\\n raise\\n\\n array_designs = experiment_data[\\\"array_designs\\\"]\\n # This experiment has no platform at all, and is therefore useless.\\n if not array_designs:\\n logger.warn(\\n \\\"Remote experiment has no array design listed.\\\",\\n experiment_accession_code=experiment_accession_code,\\n survey_job=self.survey_job.id,\\n )\\n raise UnsupportedPlatformException\\n\\n platforms = {}\\n # If there is more than one array design listed in the experiment\\n # then there is no other way to determine which array was used\\n # for which sample other than looking at the header of the CEL\\n # file. That obviously cannot happen until the CEL file has been\\n # downloaded so we can just mark it as UNKNOWN and let the\\n # downloader inspect the downloaded file to determine the\\n # array then.\\n if len(array_designs) != 1:\\n platforms[\\\"platform_accession_code\\\"] = UNKNOWN\\n platforms[\\\"platform_accession_name\\\"] = UNKNOWN\\n platforms[\\\"manufacturer\\\"] = UNKNOWN\\n else:\\n external_accession = array_designs[0]\\n for platform in get_supported_microarray_platforms():\\n if platform[\\\"external_accession\\\"] == external_accession:\\n platforms[\\\"platform_accession_code\\\"] = get_normalized_platform(\\n platform[\\\"platform_accession\\\"]\\n )\\n # Illumina appears in the accession codes for\\n # platforms manufactured by Illumina\\n if \\\"ILLUMINA\\\" in platforms[\\\"platform_accession_code\\\"].upper():\\n platforms[\\\"manufacturer\\\"] = \\\"ILLUMINA\\\"\\n platforms[\\\"platform_accession_name\\\"] = platform[\\\"platform_accession\\\"]\\n # It's not Illumina, the only other supported Microarray platform is\\n # Affy. As our list of supported platforms grows this logic will\\n # need to get more sophisticated.\\n else:\\n platforms[\\\"manufacturer\\\"] = \\\"AFFYMETRIX\\\"\\n platform_mapping = get_readable_affymetrix_names()\\n platforms[\\\"platform_accession_name\\\"] = platform_mapping[\\n platform[\\\"platform_accession\\\"]\\n ]\\n\\n if \\\"platform_accession_code\\\" not in platforms:\\n # We don't know what platform this accession corresponds to.\\n platforms[\\\"platform_accession_code\\\"] = external_accession\\n platforms[\\\"platform_accession_name\\\"] = UNKNOWN\\n platforms[\\\"manufacturer\\\"] = UNKNOWN\\n\\n # Create the experiment.\\n try:\\n experiment = Experiment.objects.get(accession_code=experiment_accession_code)\\n logger.debug(\\n \\\"Experiment already exists, skipping object creation.\\\",\\n experiment_accession_code=experiment_accession_code,\\n survey_job=self.survey_job.id,\\n )\\n except Experiment.DoesNotExist:\\n experiment = Experiment()\\n experiment.accession_code = experiment_accession_code\\n experiment.source_url = experiment_data[\\\"url\\\"]\\n self._apply_metadata_to_experiment(experiment, experiment_data)\\n experiment.save()\\n\\n json_xa = ExperimentAnnotation()\\n json_xa.experiment = experiment\\n json_xa.data = experiment_data\\n json_xa.is_ccdl = False\\n json_xa.save()\\n\\n # Fetch and parse the IDF/SDRF file for any other fields.\\n idf_url = IDF_URL_TEMPLATE.format(code=experiment_accession_code)\\n idf_text = utils.requests_retry_session().get(idf_url, timeout=60).text\\n\\n idf_data = {}\\n for line in idf_text.split(\\\"\\\\n\\\"):\\n key_val = line.strip().split(\\\"\\\\t\\\")\\n if len(key_val) == 2:\\n idf_data[key_val[0]] = key_val[1]\\n elif len(key_val) > 2:\\n idf_data[key_val[0]] = key_val[1:]\\n\\n idf_xa = ExperimentAnnotation()\\n idf_xa.data = idf_data\\n idf_xa.experiment = experiment\\n idf_xa.is_ccdl = False\\n idf_xa.save()\\n\\n if \\\"Investigation Title\\\" in idf_data and isinstance(\\n idf_data[\\\"Investigation Title\\\"], str\\n ):\\n experiment.title = idf_data[\\\"Investigation Title\\\"]\\n\\n if \\\"Person Affiliation\\\" in idf_data:\\n # This is very rare, ex: E-MEXP-32\\n if isinstance(idf_data[\\\"Person Affiliation\\\"], list):\\n unique_people = list(set(idf_data[\\\"Person Affiliation\\\"]))\\n experiment.submitter_institution = \\\", \\\".join(unique_people)[:255]\\n else:\\n experiment.submitter_institution = idf_data[\\\"Person Affiliation\\\"]\\n\\n if \\\"Publication Title\\\" in idf_data:\\n # This will happen for some superseries.\\n # Ex: E-GEOD-29536\\n # Assume most recent is \\\"best:, store the rest in experiment annotation.\\n if isinstance(idf_data[\\\"Publication Title\\\"], list):\\n experiment.publication_title = \\\"; \\\".join(idf_data[\\\"Publication Title\\\"])\\n else:\\n experiment.publication_title = idf_data[\\\"Publication Title\\\"]\\n experiment.has_publication = True\\n\\n if \\\"Publication DOI\\\" in idf_data:\\n experiment.has_publication = True\\n if isinstance(idf_data[\\\"Publication DOI\\\"], list):\\n experiment.publication_doi = \\\", \\\".join(idf_data[\\\"Publication DOI\\\"])\\n else:\\n experiment.publication_doi = idf_data[\\\"Publication DOI\\\"]\\n\\n if \\\"PubMed ID\\\" in idf_data:\\n experiment.has_publication = True\\n if isinstance(idf_data[\\\"PubMed ID\\\"], list):\\n experiment.pubmed_id = \\\", \\\".join(idf_data[\\\"PubMed ID\\\"])\\n else:\\n experiment.pubmed_id = idf_data[\\\"PubMed ID\\\"]\\n\\n # Scrape publication title and authorship from Pubmed\\n if experiment.pubmed_id:\\n pubmed_metadata = utils.get_title_and_authors_for_pubmed_id(experiment.pubmed_id)\\n experiment.publication_title = pubmed_metadata[0]\\n experiment.publication_authors = pubmed_metadata[1]\\n\\n experiment.protocol_description = experiment_data[\\\"protocols\\\"]\\n experiment.save()\\n\\n return experiment, platforms\",\n \"def run_experiment():\\n pass\",\n \"def make_exp(exp_group, args):\\n equalized_args = ['='.join(tup) for tup in args]\\n stripped_args = [arg.lstrip('-') for arg in equalized_args]\\n exp_name = [pvalue for (pname, pvalue) in args if pname == '-exp-id'][0]\\n \\n unrolled_args = [arg for arg_tup in args for arg in arg_tup]\\n arg_str = ' '.join(unrolled_args) + ' -exp-group ' + exp_group\\n\\n get_ipython().system(u'mkdir -p ../store/output/$exp_group/$exp_name')\\n get_ipython().system(u'mkdir -p ../store/weights/$exp_group/$exp_name')\\n get_ipython().system(u'mkdir -p ../store/probas/$exp_group')\\n get_ipython().system(u'mkdir -p ../store/train/$exp_group/$exp_name')\\n get_ipython().system(u'mkdir -p ../store/hyperparams/$exp_group')\\n get_ipython().system(u'mkdir -p ../store/models/$exp_group')\\n\\n get_ipython().system(u'mkdir -p exps/$exp_group')\\n get_ipython().system(u\\\"sed 's/ARGUMENTS/$arg_str/g' job_template | sed 's/EXP_GROUP/$exp_group/g' | sed 's/EXPERIMENT/$exp_name/g' > exps/$exp_group/$exp_name\\\")\",\n \"def create_epic():\\n client = RequestManager()\\n client.set_method(\\\"POST\\\")\\n client.set_endpoint(\\\"/projects/{0}/epics\\\".format(STORED_ID['project_id']))\\n name = \\\"\\\".join(choices(string.ascii_letters, k=6))\\n body = {\\\"name\\\": name}\\n client.set_body(json.dumps(body))\\n response = client.execute_request()\\n STORED_ID['epic_id'] = response.json()['id']\",\n \"def exp_main(self, use_remote_data=True, test=False):\\n test = str_to_bool(test)\\n use_remote_data = str_to_bool(use_remote_data)\\n root_uri = get_root_uri(use_remote_data)\\n root_uri = os.path.join(root_uri, rv_output_dir)\\n spacenet_config = VegasBuildings(use_remote_data)\\n experiments = []\\n runs = [0]\\n\\n noise_modes = [\\n NoiseMode(NoiseMode.SHIFT, 0),\\n NoiseMode(NoiseMode.SHIFT, 10),\\n NoiseMode(NoiseMode.SHIFT, 20),\\n NoiseMode(NoiseMode.SHIFT, 30),\\n NoiseMode(NoiseMode.SHIFT, 40),\\n NoiseMode(NoiseMode.SHIFT, 50),\\n NoiseMode(NoiseMode.DROP, 0.0),\\n NoiseMode(NoiseMode.DROP, 0.1),\\n NoiseMode(NoiseMode.DROP, 0.2),\\n NoiseMode(NoiseMode.DROP, 0.3),\\n NoiseMode(NoiseMode.DROP, 0.4),\\n NoiseMode(NoiseMode.DROP, 0.5)\\n ]\\n\\n for nm in noise_modes:\\n for run in runs:\\n exp_id = get_exp_id(nm, run)\\n task = build_task(spacenet_config.get_class_map())\\n backend = build_fastai_backend(task, test)\\n analyzer = rv.AnalyzerConfig.builder(rv.STATS_ANALYZER) \\\\\\n .build()\\n dataset = build_dataset(task, spacenet_config, test, nm)\\n\\n experiment = rv.ExperimentConfig.builder() \\\\\\n .with_id(exp_id) \\\\\\n .with_analyze_key('shift-0-0') \\\\\\n .with_task(task) \\\\\\n .with_backend(backend) \\\\\\n .with_analyzer(analyzer) \\\\\\n .with_dataset(dataset) \\\\\\n .with_root_uri(root_uri) \\\\\\n .build()\\n experiments.append(experiment)\\n\\n return experiments\",\n \"def _create_dataset(source=''):\\n return ExperimentalDataset()\",\n \"def update_experiment_v1(self, skill_id, experiment_id, update_experiment_request, **kwargs):\\n # type: (str, str, UpdateExperimentRequest_d8449813, **Any) -> Union[ApiResponse, object, StandardizedError_f5106a89, BadRequestError_f854b05]\\n operation_name = \\\"update_experiment_v1\\\"\\n params = locals()\\n for key, val in six.iteritems(params['kwargs']):\\n params[key] = val\\n del params['kwargs']\\n # verify the required parameter 'skill_id' is set\\n if ('skill_id' not in params) or (params['skill_id'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `skill_id` when calling `\\\" + operation_name + \\\"`\\\")\\n # verify the required parameter 'experiment_id' is set\\n if ('experiment_id' not in params) or (params['experiment_id'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `experiment_id` when calling `\\\" + operation_name + \\\"`\\\")\\n # verify the required parameter 'update_experiment_request' is set\\n if ('update_experiment_request' not in params) or (params['update_experiment_request'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `update_experiment_request` when calling `\\\" + operation_name + \\\"`\\\")\\n\\n resource_path = '/v1/skills/{skillId}/experiments/{experimentId}/properties'\\n resource_path = resource_path.replace('{format}', 'json')\\n\\n path_params = {} # type: Dict\\n if 'skill_id' in params:\\n path_params['skillId'] = params['skill_id']\\n if 'experiment_id' in params:\\n path_params['experimentId'] = params['experiment_id']\\n\\n query_params = [] # type: List\\n\\n header_params = [] # type: List\\n\\n body_params = None\\n if 'update_experiment_request' in params:\\n body_params = params['update_experiment_request']\\n header_params.append(('Content-type', 'application/json'))\\n header_params.append(('User-Agent', self.user_agent))\\n\\n # Response Type\\n full_response = False\\n if 'full_response' in params:\\n full_response = params['full_response']\\n\\n # Authentication setting\\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\\n authorization_value = \\\"Bearer \\\" + access_token\\n header_params.append(('Authorization', authorization_value))\\n\\n error_definitions = [] # type: List\\n error_definitions.append(ServiceClientResponse(response_type=None, status_code=204, message=\\\"Success. No content.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.bad_request_error.BadRequestError\\\", status_code=400, message=\\\"Server cannot process the request due to a client error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=401, message=\\\"The auth token is invalid/expired or doesn't have access to the resource.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.bad_request_error.BadRequestError\\\", status_code=403, message=\\\"The operation being requested is not allowed.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=404, message=\\\"The resource being requested is not found.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=409, message=\\\"The request could not be completed due to a conflict with the current state of the target resource.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=429, message=\\\"Exceeds the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=500, message=\\\"Internal Server Error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=503, message=\\\"Service Unavailable.\\\"))\\n\\n api_response = self.invoke(\\n method=\\\"POST\\\",\\n endpoint=self._api_endpoint,\\n path=resource_path,\\n path_params=path_params,\\n query_params=query_params,\\n header_params=header_params,\\n body=body_params,\\n response_definitions=error_definitions,\\n response_type=None)\\n\\n if full_response:\\n return api_response\\n \\n return None\",\n \"def create_experiment_path(self, experiment):\\n # get communications object as link to microscope hardware\\n communicatons_object = self._get_control_software().connection\\n experiment_path = communicatons_object.create_experiment_path(\\n experiment, self.experiment_folder\\n )\\n return experiment_path\",\n \"def _problem_run_experiments_initialise(self):\\n pass\",\n \"def __init__(self):\\n\\n #: Dict[str, Any]: Experiment metadata\\n self.__experiment_metadata = None\\n\\n #: List[CurveData]: Processed experiment data set.\\n self.__processed_data_set = list()\\n\\n #: Backend: backend object used for experimentation\\n self.__backend = None\\n\\n # Add expected options to instance variable so that every method can access to.\\n for key in self._default_options().__dict__:\\n setattr(self, f\\\"__{key}\\\", None)\\n\\n # Add fixed parameters to instance variable so that every method can access to.\\n for key in self.__fixed_parameters__:\\n setattr(self, f\\\"__{key}\\\", None)\",\n \"def _get_equipment(self):\\r\\n eq = self._pvsr.getEquipmentByName(self._meas[\\\"equipment\\\"])\\r\\n if eq is None:\\r\\n site = self._pvsr.getSiteByName(self._default_site)\\r\\n if site is None:\\r\\n logging.info(\\\"Creating new default site {0}\\\".format(self._default_site))\\r\\n site = self._pvsr.create_pvsr_object(\\\"Site\\\")\\r\\n site.ParentId = 1\\r\\n site.Name = self._default_site\\r\\n site=self._pvsr.addSite(site)\\r\\n else:\\r\\n logging.debug(\\\"Default site ID is {0}\\\".format(site.Id))\\r\\n \\r\\n logging.info(\\\"Creating new equipment: {0}\\\".format(self._meas[\\\"equipment\\\"]))\\r\\n if self._meas[\\\"collector_type\\\"] == 'J':\\r\\n eq = self._pvsr.create_pvsr_object(\\\"JagaEquipment\\\")\\r\\n eq.ASCII_0000_EQ_COLL_KEY = self._meas[\\\"equipment\\\"] + \\\"key\\\"\\r\\n elif self._meas[\\\"collector_type\\\"] == 'Y':\\r\\n eq = self._pvsr.create_pvsr_object(\\\"SynthTransEquipment\\\")\\r\\n else:\\r\\n raise ValueError(\\\"The equipment does not exist in PVSR\\\") \\r\\n eq.Name = self._meas[\\\"equipment\\\"]\\r\\n eq.ParentId = site.Id\\r\\n eq.CollectorType = self._meas[\\\"collector_type\\\"]\\r\\n eq.IntervalInSec = 300\\r\\n eq.RetainRawData = 365\\r\\n eq.CollectData = \\\"Yes\\\"\\r\\n \\r\\n eq = self._pvsr.addEquipment(eq)\\r\\n logging.info(\\\"Added equipment {0}, id: {1}\\\".format(self._meas[\\\"equipment\\\"],eq.Id))\\r\\n else:\\r\\n logging.debug(\\\"Found equipment: {0}, id: {1}\\\".format(self._meas[\\\"equipment\\\"],eq.Id))\\r\\n return eq\",\n \"def create_experience(cls, state, action, reward, done, next_state) -> 'Experience':\\n return cls(\\n state=state,\\n action=action,\\n reward=reward,\\n done=done,\\n next_state=next_state,\\n )\",\n \"def _make(dataset, model):\\n def wrapper(args):\\n return SlimExperiment(dataset, model, args)\\n return wrapper\",\n \"def add_experiment(self, experiment):\\n nra_ = c.c_int(experiment.z)\\n klm_ = c.c_int(experiment.line)\\n hv_ = c.c_double(experiment.energy_eV / 1e3)\\n ielt_ = c.c_int()\\n iline_ = c.c_int()\\n iexpk_ = c.c_int()\\n logger.debug('StEdAddNrAtomLineHV(key, %i, %i)', experiment.z, experiment.line)\\n if not self._lib.StEdAddNrAtomLineHV(self._key, nra_, klm_, hv_,\\n c.byref(ielt_), c.byref(iline_), c.byref(iexpk_)):\\n self._raise_error(\\\"Cannot add atomic number and line\\\")\\n\\n standard = experiment.standard\\n if isinstance(standard, Sample):\\n standard = self._create_standard(standard)\\n standard_ = c.create_string_buffer(standard.encode('ascii'))\\n logger.debug('StEdSetLine(key, %i, %i, %i, %s)', ielt_.value, iline_.value, klm_.value, standard)\\n if not self._lib.StEdSetLine(self._key, ielt_, iline_, klm_, standard_):\\n self._raise_error(\\\"Cannot set standard\\\")\\n\\n analyzed = experiment.is_analyzed()\\n analyzed_ = c.c_bool(analyzed)\\n logger.debug(\\\"StEdSetAnalyzedFlag(key, %i, %r)\\\", ielt_.value, analyzed)\\n if not self._lib.StEdSetAnalyzedFlag(self._key, ielt_, analyzed_):\\n self._raise_error(\\\"Cannot add experiment analyzed flag\\\")\\n\\n kratio_ = c.c_double(experiment.kratio)\\n logger.debug(\\\"StEdSetExpK(key, %i, %i, %i, %f, %f, %f, 0.0, 2)\\\",\\n ielt_.value, iline_.value, iexpk_.value,\\n experiment.energy_eV / 1e3, experiment.energy_eV / 1e3,\\n experiment.kratio)\\n if not self._lib.StEdSetExpK(self._key, ielt_, iline_, iexpk_,\\n hv_, hv_, kratio_, c.c_double(0.0),\\n c.c_int(2)):\\n self._raise_error(\\\"Cannot set experiment k-ratio\\\")\\n\\n if experiment.is_analyzed():\\n indexes = (ielt_.value, iline_.value, iexpk_.value)\\n self._experiments.setdefault(experiment, indexes)\",\n \"def experiment(self) -> Any:\",\n \"def experiment_params():\\n exp = {\\n 'lr': [1e-3],\\n 'loss_function': ['cce'],\\n 'optimizer': ['nadam'],\\n 'dataset': [\\n # 'curv_contour_length_9',\\n 'cluttered_nist_ix1',\\n # 'curv_baseline',\\n ]\\n }\\n exp['data_augmentations'] = [\\n [\\n 'grayscale',\\n 'center_crop',\\n # 'left_right',\\n # 'up_down',\\n 'uint8_rescale',\\n 'singleton',\\n 'zero_one'\\n ]]\\n exp['val_augmentations'] = [\\n [\\n 'grayscale',\\n 'center_crop',\\n # 'left_right',\\n # 'up_down',\\n 'uint8_rescale',\\n 'singleton',\\n 'zero_one'\\n ]]\\n exp['batch_size'] = 32 # Train/val batch size.\\n exp['epochs'] = 4\\n exp['model_name'] = 'unet'\\n exp['exp_name'] = exp['model_name'] + '_' + exp['dataset'][0]\\n exp['save_weights'] = True\\n exp['validation_iters'] = 1000\\n exp['num_validation_evals'] = 200\\n exp['shuffle_val'] = True # Shuffle val data.\\n exp['shuffle_train'] = True\\n return exp\",\n \"def test_experiment_do_not_exist(self):\\n with pytest.raises(NoConfigurationError) as exception:\\n get_experiment(\\\"a\\\")\\n assert (\\n \\\"No experiment with given name 'a' and version '*' inside database, \\\"\\n \\\"no view can be created.\\\" == str(exception.value)\\n )\",\n \"def add_agent(self, environment_name, agent_name, agent_params):\\n assert environment_name in self._environment_dict\\n assert self._is_sweep is False or self._is_sweep is None\\n self._is_sweep = False\\n if agent_name in self._experiment_structure[environment_name]:\\n raise AttributeError(\\n f'An experiment for environment {environment_name} and builders {agent_name} already exists.'\\n )\\n\\n environment_builder_params = self._environment_dict[environment_name]['build_params']\\n\\n try:\\n exp = self._create_experiment(environment_name, environment_builder_params, agent_name, agent_params)\\n self._experiment_structure[environment_name][agent_name] = exp\\n except AttributeError as e:\\n self.logger.error(\\n f'Unable to create experiment for the environment {environment_name} and agent {agent_name}'\\n )\\n self.logger.exception(e)\",\n \"def get_experiment(self,\\n experiment_id=None,\\n experiment_name=None,\\n namespace=None) -> kfp_server_api.V1Experiment:\\n namespace = namespace or self.get_user_namespace()\\n if experiment_id is None and experiment_name is None:\\n raise ValueError(\\n 'Either experiment_id or experiment_name is required')\\n if experiment_id is not None:\\n return self._experiment_api.get_experiment(id=experiment_id)\\n experiment_filter = json.dumps({\\n 'predicates': [{\\n 'op': _FILTER_OPERATIONS['EQUALS'],\\n 'key': 'name',\\n 'stringValue': experiment_name,\\n }]\\n })\\n if namespace:\\n result = self._experiment_api.list_experiment(\\n filter=experiment_filter,\\n resource_reference_key_type=kfp_server_api.models\\n .v1_resource_type.V1ResourceType.NAMESPACE,\\n resource_reference_key_id=namespace)\\n else:\\n result = self._experiment_api.list_experiment(\\n filter=experiment_filter)\\n if not result.experiments:\\n raise ValueError(\\n 'No experiment is found with name {}.'.format(experiment_name))\\n if len(result.experiments) > 1:\\n raise ValueError(\\n 'Multiple experiments is found with name {}.'.format(\\n experiment_name))\\n return result.experiments[0]\",\n \"def __init__(self, name, ingredients=()):\\n caller_globals = inspect.stack()[1][0].f_globals\\n super(Experiment, self).__init__(path=name,\\n ingredients=ingredients,\\n _generate_seed=True,\\n _caller_globals=caller_globals)\\n self.name = name\\n self.default_command = \\\"\\\"\\n self.logger = None\\n self.observers = []\\n self.command(print_config)\\n self.command(print_dependencies)\",\n \"def setUpClass(cls):\\n with patch('builtins.input', side_effect=['yes', 12]):\\n experiment = Experiment(cls.experiment_path)\\n cls.experiment = experiment\",\n \"def make_exps(exp_group, args, num_exps=32, grid_search=False, baseline_exp_groups=[]):\\n args_list = list(args_generator(args, num_exps, grid_search))\\n\\n # Remove exp_group directories!\\n get_ipython().system(u'rm -rf exps/$exp_group')\\n get_ipython().system(u'rm -rf ../store/output/$exp_group')\\n get_ipython().system(u'rm -rf ../store/weights/$exp_group')\\n get_ipython().system(u'rm -rf ../store/probas/$exp_group')\\n get_ipython().system(u'rm -rf ../store/train/$exp_group')\\n get_ipython().system(u'rm -rf ../store/hyperparams/$exp_group')\\n get_ipython().system(u'rm -rf ../store/models/$exp_group')\\n\\n for i, args_setting in enumerate(args_list):\\n make_exp(exp_group, args_setting)\\n\\n # Copy in existing experiments - for learning curve visualizations\\n for baseline_exp_group in baseline_exp_groups:\\n get_ipython().system(u'cp -r ../output/$baseline_exp_group/* ../output/$exp_group')\",\n \"def experiment(self):\\n return self._experiment\",\n \"def _find_or_add_artifact(self, i):\\n\\n console = i.get('out','')=='con'\\n\\n # Try to find experiment artifact by alias and/or tags\\n ii = utils.sub_input(i, self.cmind.cfg['artifact_keys'] + ['tags'])\\n ii['action']='find'\\n\\n ii_copy = copy.deepcopy(ii)\\n\\n # If artifact is specified, remove tags\\n artifact = ii.get('artifact','').strip()\\n if artifact!='' and not artifact.endswith(':') \\\\\\n and '*' not in artifact and '?' not in artifact:\\n if 'tags' in ii: del(ii['tags'])\\n\\n r = self.cmind.access(ii)\\n if r['return']>0: return r\\n\\n lst = r['list']\\n\\n if len(lst)>1:\\n print ('More than 1 experiment artifact found:')\\n\\n lst = sorted(lst, key=lambda x: x.path)\\n \\n num = 0\\n print ('')\\n for e in lst:\\n print ('{}) {}'.format(num, e.path))\\n print (' Tags: {}'.format(','.join(e.meta.get('tags',[]))))\\n num += 1\\n\\n if not console:\\n return {'return':1, 'error':'more than 1 experiment artifact found.\\\\nPlease use \\\"cm run experiment {name}\\\" or \\\"cm run experiment --tags={tags separated by comma}\\\"'}\\n \\n print ('')\\n x=input('Make your selection or press Enter for 0: ')\\n\\n x=x.strip()\\n if x=='': x='0'\\n\\n selection = int(x)\\n\\n if selection < 0 or selection >= num:\\n selection = 0\\n\\n experiment = lst[selection]\\n\\n elif len(lst)==1:\\n experiment = lst[0]\\n else:\\n # Create new entry\\n if i.get('fail_if_not_found',False):\\n return {'return':1, 'error':'experiment not found'}\\n \\n ii = copy.deepcopy(ii_copy)\\n ii['action']='add'\\n r = self.cmind.access(ii)\\n if r['return']>0: return r\\n\\n experiment_uid = r['meta']['uid']\\n\\n r = self.cmind.access({'action':'find',\\n 'automation':'experiment,a0a2d123ef064bcb',\\n 'artifact':experiment_uid})\\n if r['return']>0: return r\\n\\n lst = r['list']\\n if len(lst)==0 or len(lst)>1:\\n return {'return':1, 'error':'created experiment artifact with UID {} but can\\\\'t find it - weird'.format(experiment_uid)}\\n\\n experiment = lst[0]\\n \\n return {'return':0, 'experiment':experiment}\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7578074","0.7373269","0.72146213","0.7015423","0.69071597","0.6736371","0.65408194","0.64728445","0.64639014","0.6389977","0.63315874","0.62304384","0.622714","0.61377406","0.6132721","0.6109624","0.6044673","0.59917486","0.5942433","0.5940935","0.59142244","0.585526","0.57360315","0.57147515","0.5708123","0.5673326","0.56729805","0.560397","0.5570058","0.5540097","0.5532693","0.5517302","0.5515169","0.5473909","0.5459366","0.5452456","0.5415712","0.5398745","0.53956205","0.5393008","0.5391678","0.5362999","0.5343556","0.5340552","0.5329331","0.5326165","0.5314897","0.53096056","0.52868724","0.526926","0.5269127","0.52651685","0.5264327","0.526391","0.52638614","0.5261583","0.5259481","0.5253889","0.5252329","0.5246835","0.524642","0.5243269","0.5242266","0.5232498","0.5229177","0.52286166","0.52251035","0.5223081","0.52198315","0.5203888","0.5198233","0.51978654","0.5170707","0.5165808","0.51633495","0.51601267","0.5159166","0.5157604","0.5156767","0.5155901","0.515459","0.51545477","0.5151119","0.5148139","0.5119621","0.5108954","0.5085702","0.5073671","0.5061773","0.50612444","0.50523543","0.5051934","0.5051759","0.505003","0.5049509","0.50490135","0.50380456","0.5036836","0.5035102","0.5030311"],"string":"[\n \"0.7578074\",\n \"0.7373269\",\n \"0.72146213\",\n \"0.7015423\",\n \"0.69071597\",\n \"0.6736371\",\n \"0.65408194\",\n \"0.64728445\",\n \"0.64639014\",\n \"0.6389977\",\n \"0.63315874\",\n \"0.62304384\",\n \"0.622714\",\n \"0.61377406\",\n \"0.6132721\",\n \"0.6109624\",\n \"0.6044673\",\n \"0.59917486\",\n \"0.5942433\",\n \"0.5940935\",\n \"0.59142244\",\n \"0.585526\",\n \"0.57360315\",\n \"0.57147515\",\n \"0.5708123\",\n \"0.5673326\",\n \"0.56729805\",\n \"0.560397\",\n \"0.5570058\",\n \"0.5540097\",\n \"0.5532693\",\n \"0.5517302\",\n \"0.5515169\",\n \"0.5473909\",\n \"0.5459366\",\n \"0.5452456\",\n \"0.5415712\",\n \"0.5398745\",\n \"0.53956205\",\n \"0.5393008\",\n \"0.5391678\",\n \"0.5362999\",\n \"0.5343556\",\n \"0.5340552\",\n \"0.5329331\",\n \"0.5326165\",\n \"0.5314897\",\n \"0.53096056\",\n \"0.52868724\",\n \"0.526926\",\n \"0.5269127\",\n \"0.52651685\",\n \"0.5264327\",\n \"0.526391\",\n \"0.52638614\",\n \"0.5261583\",\n \"0.5259481\",\n \"0.5253889\",\n \"0.5252329\",\n \"0.5246835\",\n \"0.524642\",\n \"0.5243269\",\n \"0.5242266\",\n \"0.5232498\",\n \"0.5229177\",\n \"0.52286166\",\n \"0.52251035\",\n \"0.5223081\",\n \"0.52198315\",\n \"0.5203888\",\n \"0.5198233\",\n \"0.51978654\",\n \"0.5170707\",\n \"0.5165808\",\n \"0.51633495\",\n \"0.51601267\",\n \"0.5159166\",\n \"0.5157604\",\n \"0.5156767\",\n \"0.5155901\",\n \"0.515459\",\n \"0.51545477\",\n \"0.5151119\",\n \"0.5148139\",\n \"0.5119621\",\n \"0.5108954\",\n \"0.5085702\",\n \"0.5073671\",\n \"0.5061773\",\n \"0.50612444\",\n \"0.50523543\",\n \"0.5051934\",\n \"0.5051759\",\n \"0.505003\",\n \"0.5049509\",\n \"0.50490135\",\n \"0.50380456\",\n \"0.5036836\",\n \"0.5035102\",\n \"0.5030311\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7045335"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":88582,"cells":{"query":{"kind":"string","value":"Closes the API and tells Xepr to shut down its API support as well. After that, the API support of Xepr has to be re enabled manually by the Xepr operator (menu \"Processing\" > submenu \"XeprAPI\" > menu item \"Enable Xepr API\") to be able to establish the Xepr API again."},"document":{"kind":"string","value":"def XeprClose(self):\n\n with self._lock:\n for func in self._dynamicmethods:\n delattr(self, func)\n\n self._dynamicmethods = []\n self._printmsg('Closing API...', newline=False)\n if self._API.XeprDisableAPI(1) == SUCCESS:\n self._printmsg('done.', prefix='')\n self._APIopen = False\n else:\n self._printmsg('done.', prefix='')\n raise IOError('%sCould not close API' % _msgprefix)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def close(self):\n self.__aceQLHttpApi.close()","def _close(self):\n log.Debug('dpbx.close():')","def close(self):\n self.controller.DisableDevice()\n self.controller.StopPolling()\n self.controller.Disconnect(False)","def close(self):\n if self.dev_open:\n try:\n self.lib().close()\n except CygnetExc:\n pass\n self.dev_open = False","def __del__(self):\n try:\n self.api.transport.session.close()\n except Exception as e:\n log.debug(f\"Failed to close VSO API connection with: {e}\")","def Close(self):","def close_ws(self):\n self.cmd_gw_ws_api.close()","def closeConfiguration(self):\n self.parent.closeDresser()","def close(self): # from gym/core.py\n pass","def close(self):\n closeI1Display()","def close(self) -> None:\n lib.Fapi_Finalize(self._ctx_pp)","def close(self):\n try:\n self.check_state('close')\n except Exception:\n pass\n try: # copy from reboot function\n self.newportxps.ftpconn.close()\n self.newportxps._xps.CloseAllOtherSockets(self.newportxps._sid)\n except Exception:\n pass","def on_close_control_com_btn_clicked(self):\n self.control1.device.close_port()\n # self.sensor1.sensor.close_port()\n self.control1.pause()\n self.open_control_com_btn.setEnabled(True)\n self.close_control_com_btn.setEnabled(False)\n self.set_rcr_btns_bool(False)\n self.set_status_txt(\"closing control board \")","def close(self):\n self.stop_updating_loop()\n if self._rpc is not None:\n self._rpc.close()\n self._rpc = None","def close(self):\n\n #Kill all zombie PIDs and exit gracefully\n try:\n self.webdriver.quit()\n except:\n pass\n if 'p' not in sys.argv:\n self.kill()\n sys.exit()","def close(self):\n pass","def close(self):\n pass","def cleanup_revpi(self):\n self.rpi.core.a1green.value = False\n self.rpi.core.a1red.value = False\n self.rpi.io.main_relay.value = False\n self.rpi.io.relay_1.value = False\n self.rpi.io.relay_2.value = False\n self.rpi = revpimodio2.RevPiModIO(autorefresh=False)\n self.opc_server.stop()\n print(\"exit\")\n # self.master.destroy()\n exit(1)","def close(self):\r\n pass","def close(self):\r\n pass","def close(self):\r\n pass","def close(self):\n self.exit()","def close(self):\n self.call('close')","def close(self):\n self.closing = True","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):\n pass","def close(self):","def close(self):","def close(self):","def close(self):","def close(self):","def close(self):","def close(self):","def close(self):","def close(self):","def close(self):","def stop(self):\n self._report(registry=self.registry, flush_current_hist=True)\n if self._sdk_metrics_registry:\n self._sdk_metrics_registry.close(timeout_secs=1)\n super().stop()\n self.wavefront_client.close()","def Close(self):\n return","def Close(self):\n return","def close(self):\n print 'close'","def close_acesso(self):\n self.acesso.quit()","def close():\n sys.exit()","def close(self):\n self._close = True","def close_driver( self ):\r\n self.com_driver.close()\r\n self.gui.set_open( \"Closed\" )\r\n msg = \"Closed Comm Port\"\r\n self.gui.print_info_string( msg )\r\n return","def close(self):\n self.stop()\n GPIO.cleanup()","def close(self):\r\n pass","def _close_http_session(self):\n if self._api_http_session:\n try:\n self._api_http_session.close()\n except RequestException:\n pass","def close(self) -> None:","def close(self) -> None:","def close(self) -> None:","def close(self) -> None:","def close(self) -> None:","def close(self) -> None:","def close(self) -> None:","def close(self) -> None:","def handle_close(self):\n self.active = False\n self.close()","def close(self):\n\n\t\tself._interface.close()","def close(self):\n\n\t\tself._interface.close()","def close (self):\n pass","def close(self):\n ...","def close(self):\n ...","def close(self): \n\t\tself.env.close()","def close(self) -> None:\n ...","def close(self) -> None:\n ...","def close(self):\n self.is_open = False","def close(self):\n closeI1ProDevice()","def close(self):\n GPIO.cleanup(self.gpio_pin)","def close(self):\n self.gym.close()","def close(self):\n self._core.close()","def _doCloseTool(self):\n self._cmdCloseTool()","def _close(self):\n if self.snmpProxy:\n self.snmpProxy.close()\n self.snmpProxy = None","def close(self):\n self._isOpen = False","def close(self) -> None:\r\n pass","def close(self):\n self.destroy()"],"string":"[\n \"def close(self):\\n self.__aceQLHttpApi.close()\",\n \"def _close(self):\\n log.Debug('dpbx.close():')\",\n \"def close(self):\\n self.controller.DisableDevice()\\n self.controller.StopPolling()\\n self.controller.Disconnect(False)\",\n \"def close(self):\\n if self.dev_open:\\n try:\\n self.lib().close()\\n except CygnetExc:\\n pass\\n self.dev_open = False\",\n \"def __del__(self):\\n try:\\n self.api.transport.session.close()\\n except Exception as e:\\n log.debug(f\\\"Failed to close VSO API connection with: {e}\\\")\",\n \"def Close(self):\",\n \"def close_ws(self):\\n self.cmd_gw_ws_api.close()\",\n \"def closeConfiguration(self):\\n self.parent.closeDresser()\",\n \"def close(self): # from gym/core.py\\n pass\",\n \"def close(self):\\n closeI1Display()\",\n \"def close(self) -> None:\\n lib.Fapi_Finalize(self._ctx_pp)\",\n \"def close(self):\\n try:\\n self.check_state('close')\\n except Exception:\\n pass\\n try: # copy from reboot function\\n self.newportxps.ftpconn.close()\\n self.newportxps._xps.CloseAllOtherSockets(self.newportxps._sid)\\n except Exception:\\n pass\",\n \"def on_close_control_com_btn_clicked(self):\\n self.control1.device.close_port()\\n # self.sensor1.sensor.close_port()\\n self.control1.pause()\\n self.open_control_com_btn.setEnabled(True)\\n self.close_control_com_btn.setEnabled(False)\\n self.set_rcr_btns_bool(False)\\n self.set_status_txt(\\\"closing control board \\\")\",\n \"def close(self):\\n self.stop_updating_loop()\\n if self._rpc is not None:\\n self._rpc.close()\\n self._rpc = None\",\n \"def close(self):\\n\\n #Kill all zombie PIDs and exit gracefully\\n try:\\n self.webdriver.quit()\\n except:\\n pass\\n if 'p' not in sys.argv:\\n self.kill()\\n sys.exit()\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def cleanup_revpi(self):\\n self.rpi.core.a1green.value = False\\n self.rpi.core.a1red.value = False\\n self.rpi.io.main_relay.value = False\\n self.rpi.io.relay_1.value = False\\n self.rpi.io.relay_2.value = False\\n self.rpi = revpimodio2.RevPiModIO(autorefresh=False)\\n self.opc_server.stop()\\n print(\\\"exit\\\")\\n # self.master.destroy()\\n exit(1)\",\n \"def close(self):\\r\\n pass\",\n \"def close(self):\\r\\n pass\",\n \"def close(self):\\r\\n pass\",\n \"def close(self):\\n self.exit()\",\n \"def close(self):\\n self.call('close')\",\n \"def close(self):\\n self.closing = True\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\\n pass\",\n \"def close(self):\",\n \"def close(self):\",\n \"def close(self):\",\n \"def close(self):\",\n \"def close(self):\",\n \"def close(self):\",\n \"def close(self):\",\n \"def close(self):\",\n \"def close(self):\",\n \"def close(self):\",\n \"def stop(self):\\n self._report(registry=self.registry, flush_current_hist=True)\\n if self._sdk_metrics_registry:\\n self._sdk_metrics_registry.close(timeout_secs=1)\\n super().stop()\\n self.wavefront_client.close()\",\n \"def Close(self):\\n return\",\n \"def Close(self):\\n return\",\n \"def close(self):\\n print 'close'\",\n \"def close_acesso(self):\\n self.acesso.quit()\",\n \"def close():\\n sys.exit()\",\n \"def close(self):\\n self._close = True\",\n \"def close_driver( self ):\\r\\n self.com_driver.close()\\r\\n self.gui.set_open( \\\"Closed\\\" )\\r\\n msg = \\\"Closed Comm Port\\\"\\r\\n self.gui.print_info_string( msg )\\r\\n return\",\n \"def close(self):\\n self.stop()\\n GPIO.cleanup()\",\n \"def close(self):\\r\\n pass\",\n \"def _close_http_session(self):\\n if self._api_http_session:\\n try:\\n self._api_http_session.close()\\n except RequestException:\\n pass\",\n \"def close(self) -> None:\",\n \"def close(self) -> None:\",\n \"def close(self) -> None:\",\n \"def close(self) -> None:\",\n \"def close(self) -> None:\",\n \"def close(self) -> None:\",\n \"def close(self) -> None:\",\n \"def close(self) -> None:\",\n \"def handle_close(self):\\n self.active = False\\n self.close()\",\n \"def close(self):\\n\\n\\t\\tself._interface.close()\",\n \"def close(self):\\n\\n\\t\\tself._interface.close()\",\n \"def close (self):\\n pass\",\n \"def close(self):\\n ...\",\n \"def close(self):\\n ...\",\n \"def close(self): \\n\\t\\tself.env.close()\",\n \"def close(self) -> None:\\n ...\",\n \"def close(self) -> None:\\n ...\",\n \"def close(self):\\n self.is_open = False\",\n \"def close(self):\\n closeI1ProDevice()\",\n \"def close(self):\\n GPIO.cleanup(self.gpio_pin)\",\n \"def close(self):\\n self.gym.close()\",\n \"def close(self):\\n self._core.close()\",\n \"def _doCloseTool(self):\\n self._cmdCloseTool()\",\n \"def _close(self):\\n if self.snmpProxy:\\n self.snmpProxy.close()\\n self.snmpProxy = None\",\n \"def close(self):\\n self._isOpen = False\",\n \"def close(self) -> None:\\r\\n pass\",\n \"def close(self):\\n self.destroy()\"\n]","isConversational":false},"negative_scores":{"kind":"list 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\"0.6518419\",\n \"0.6297029\",\n \"0.6261232\",\n \"0.6248867\",\n \"0.61627144\",\n \"0.6101848\",\n \"0.6072765\",\n \"0.60054755\",\n \"0.6004206\",\n \"0.6000544\",\n \"0.5971086\",\n \"0.5967516\",\n \"0.59390146\",\n \"0.593771\",\n \"0.5916162\",\n \"0.59158105\",\n \"0.59158105\",\n \"0.590212\",\n \"0.5895577\",\n \"0.5895577\",\n \"0.5895577\",\n \"0.589408\",\n \"0.5885616\",\n \"0.5878102\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.58703464\",\n \"0.5869492\",\n \"0.5869492\",\n \"0.5869492\",\n \"0.5869492\",\n \"0.5869492\",\n \"0.5869492\",\n \"0.5869492\",\n \"0.5869492\",\n \"0.5869492\",\n \"0.5869492\",\n \"0.58659446\",\n \"0.5864144\",\n \"0.5864144\",\n \"0.58510274\",\n \"0.5849111\",\n \"0.58490175\",\n \"0.58478355\",\n \"0.5846133\",\n \"0.58443797\",\n \"0.5843127\",\n \"0.58406436\",\n \"0.5830005\",\n \"0.5830005\",\n \"0.5830005\",\n \"0.5830005\",\n \"0.5830005\",\n \"0.5830005\",\n \"0.5830005\",\n \"0.5830005\",\n \"0.5826045\",\n \"0.5820227\",\n \"0.5820227\",\n \"0.58198714\",\n \"0.5813592\",\n \"0.5813592\",\n \"0.5788281\",\n \"0.5786486\",\n \"0.5786486\",\n \"0.5769065\",\n \"0.5766898\",\n \"0.57644415\",\n \"0.57540107\",\n \"0.5731556\",\n \"0.5729212\",\n \"0.5728694\",\n \"0.5724412\",\n \"0.57225966\",\n \"0.5720209\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.83324784"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88583,"cells":{"query":{"kind":"string","value":"Refreshes the Xepr GUI."},"document":{"kind":"string","value":"def XeprGUIrefresh(self):\n with self._lock:\n self._API.XeprRefreshGUI()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def refresh(self):\n\t\tself.win.refresh()\n\t\tfor c in self.components:\n\t\t\tc.refresh()","def refresh_dialog(self):\n self._client.update_elements()","def refresh(self):\n self.Refresh()","def Refresh(self):\n pass","def refresh(self):\n self.__refresh()","def refresh(self) -> None:\n self.screen.refresh()","def _refresh(self):\n self._need_display_update = True\n self._update()","def refresh(self):\n self.log_info(f\"Browser.refresh: Refreshing the page\")\n self.CORE.refresh()\n return","def reload():\n xd = display.XKCDDisplayService()\n if xd.is_running():\n click.echo(\"gracefully reloading changes\")\n xd.send_signal(signal.SIGHUP)\n else:\n click.echo(\"xkcd service not running\")","def refresh_screen(self):","def refresh(self):\n\n if self.eventBox.window != None:\n self.eventBox.window.set_cursor(None)\n self.enable_controls(False)\n threading.Thread(target=self.thread_refresh).start()","def refresh(self):\n\t\tself.driver.refresh()","def refresh(self):\n pass","def refresh(self):\n pass","def refresh_screen(self):\n stdscr = self.stdscr\n stdscr.refresh()","def refresh(self):\n\n for w in self.windows.values():\n w.refresh()","def refresh(self) -> None:\n pass","def refresh(self) -> None:\n pass","def refresh(self) -> None:\n pass","def _refresh_screen(self):\n self.myscreen.refresh()\n self.box1.refresh()\n self.box2.refresh()","def refresh():\n curve_editor.refresh()","def on_refreshButton_clicked(self):\n self.buttonBox.button(QDialogButtonBox.Close).setEnabled(False)\n \n self.buttonBox.button(QDialogButtonBox.Save).setEnabled(False)\n self.refreshButton.setEnabled(False)\n \n self.start(self.__filename, diffMode=self.__diffMode, refreshable=True)","def refresh_all(self):\n self.stdscr.noutrefresh()\n self.chat_container.noutrefresh()\n self.chat_win.noutrefresh()\n self.prompt_win.noutrefresh()\n curses.doupdate()","def refresh(self):\n self.getWindow().getDecorView().postInvalidate()","def refresh(self):\n\n # Set Graphics scene\n self.setScene(QtGui.QGraphicsScene())\n self._connections = set()\n self._nodes = {}\n self._selection = set()\n self._manipulation_mode = 0\n self._selection_rect = None","def updateWidget(self):\n pass","def UpdateUI(self):\n # colors & font\n self.SetBackgroundColour(wx.GetApp().settings.bg_color)\n self.SetForegroundColour(wx.GetApp().settings.fg_color)\n self.SetFont(wx.GetApp().settings.text_font)\n\n # apply new (or not) 'wx' values to content.\n p = self.FindWindow(\"content\")\n if p is not None:\n p.SetBackgroundColour(wx.GetApp().settings.bg_color)\n p.SetForegroundColour(wx.GetApp().settings.fg_color)\n p.SetFont(wx.GetApp().settings.text_font)\n\n # apply new (or not) 'wx' values to header.\n p = self.FindWindow(\"header\")\n if p is not None:\n p.SetBackgroundColour(wx.GetApp().settings.header_bg_color)\n p.SetForegroundColour(wx.GetApp().settings.header_fg_color)\n p.SetFont(wx.GetApp().settings.header_text_font)\n\n # apply new (or not) 'wx' values to actions.\n p = self.FindWindow(\"actions\")\n if p is not None:\n p.SetBackgroundColour(wx.GetApp().settings.action_bg_color)\n p.SetForegroundColour(wx.GetApp().settings.action_fg_color)\n p.SetFont(wx.GetApp().settings.action_text_font)\n\n self.Refresh()","def Refresh(self, erase=True, rect=None):\r\n\r\n self._main_win.Refresh(erase, rect)\r\n self._header_win.Refresh(erase, rect)","def refreshContents(self):\n self.ivGeneralButton1.hide()\n self.ivGeneralButton2.hide()\n self.ovGeneralButton1.hide()\n self.ovGeneralButton2.hide()\n self.dataBrowser.refreshContents()\n inputNames = self.dat.flowsheet.input.compoundNames()\n self.dat.flowsheet.markConnectedInputs()\n delList = []\n for i in range(len(inputNames)):\n if self.dat.flowsheet.input.get(inputNames[i]).con == True:\n delList.append(inputNames[i])\n for n in delList:\n inputNames.remove(n)\n outputNames = self.dat.flowsheet.output.compoundNames()\n if self.dat.surrogateCurrent is not None:\n i = self.toolSelectBox.findText(self.dat.surrogateCurrent)\n if i >= 0:\n self.blockapply = True\n self.toolSelectBox.setCurrentIndex(i)\n self.blockapply = False\n tool = self.toolSelectBox.currentText()\n if tool == \"\":\n return\n pg = self.dat.surrogateMethods.plugins[tool].surrogateMethod(self.dat)\n pg.loadFromSession()\n pg.updateOptions()\n\n for i, btn in enumerate(pg.inputVarButtons):\n # this is because I am beeing lazy there are two\n # preexisting buttons\n if i == 0:\n self.ivGeneralButton1.setText(btn[0])\n self.ivGeneralButton1.show()\n elif i == 1:\n self.ivGeneralButton2.setText(btn[0])\n self.ivGeneralButton2.show()\n\n for i, btn in enumerate(pg.outputVarButtons):\n if i == 0:\n self.ovGeneralButton1.setText(btn[0])\n self.ovGeneralButton1.show()\n elif i == 1:\n self.ovGeneralButton2.setText(btn[0])\n self.ovGeneralButton2.show()\n\n for i in range(self.optTable[tool].rowCount()):\n oname = gh.getCellText(self.optTable[tool], i, 0)\n if oname in pg.options:\n if pg.options[oname].dtype == bool:\n gh.setCellChecked(\n self.optTable[tool], i, 1, pg.options[oname].value\n )\n elif len(pg.options[oname].validValues) > 0:\n gh.cellPulldownSetItemsJSON(\n self.optTable[tool], i, 1, pg.options[oname].validValues\n )\n gh.cellPulldownSetJSON(\n self.optTable[tool], i, 1, pg.options[oname].value\n )\n else:\n gh.setCellJSON(self.optTable[tool], i, 1, pg.options[oname].value)\n self.inputTable.setRowCount(0)\n self.inputTable.setColumnCount(3 + len(pg.inputCols))\n for i, item in enumerate(pg.inputCols):\n gh.setColHeaderIntem(self.inputTable, i + 3, item[0])\n self.outputTable.setRowCount(0)\n self.outputTable.setColumnCount(1 + len(pg.outputCols))\n for i, item in enumerate(pg.outputCols):\n gh.setColHeaderIntem(self.outputTable, i + 1, item[0])\n self.inputTable.setRowCount(len(inputNames))\n self.outputTable.setRowCount(len(outputNames))\n self.inputCols = gh.colIndexes(self.inputTable)\n self.outputCols = gh.colIndexes(self.outputTable)\n for i in range(len(inputNames)):\n var = self.dat.flowsheet.input.get(inputNames[i])\n gh.setTableItem(\n self.inputTable,\n row=i,\n col=self.inputCols[\"Name\"],\n text=inputNames[i],\n check=inputNames[i] in pg.input,\n editable=False,\n )\n gh.setTableItem(\n self.inputTable,\n row=i,\n col=self.inputCols[\"Max\"],\n text=var.max,\n jsonEnc=True,\n )\n gh.setTableItem(\n self.inputTable,\n row=i,\n col=self.inputCols[\"Min\"],\n text=var.min,\n jsonEnc=True,\n )\n for item in pg.inputCols:\n val = pg.getInputVarOption(item[0], inputNames[i])\n gh.setTableItem(\n self.inputTable,\n row=i,\n col=self.inputCols[item[0]],\n text=val,\n jsonEnc=True,\n )\n for i in range(len(outputNames)):\n var = self.dat.flowsheet.output.get(outputNames[i])\n gh.setTableItem(\n self.outputTable,\n row=i,\n col=self.outputCols[\"Name\"],\n text=outputNames[i],\n check=outputNames[i] in pg.output,\n editable=False,\n )\n for item in pg.outputCols:\n val = pg.getOutputVarOption(item[0], outputNames[i])\n gh.setTableItem(\n self.outputTable,\n row=i,\n col=self.outputCols[item[0]],\n text=val,\n jsonEnc=True,\n )\n self.inputTable.resizeColumnsToContents()\n self.outputTable.resizeColumnsToContents()","def show(self):\n self.root.update()\n self.root.deiconify()","def refresh(self):\n\n self.driver.implicitly_wait(5)\n self.driver.refresh()","def refresh_all(self):\n\t\t\n\t\tself.symbolsList.set_datasource(self.source)\n\t\tself.symbolsList.refresh()\n\t\t\n\t\tself.plotFrame.set_datasource(self.source)\n\t\tself.plotFrame.refresh()","def refresh(self) :\n if not self.running:\n self.running = True\n self.strip.show()\n self.running = False\n self.refreshTimer.expired = True\n self.refreshTimer.isrunning = False","def repaint(self):\n pass","def reload(self):","def reload(self):","def refresh_window():\n global lineno\n lineno = 0\n curses.endwin()\n win.erase()\n print_header()\n win.refresh()","def _update_gui(self):\r\n \r\n # Update the RF button.\r\n rf_on = self.api.get_output()\r\n if rf_on == None: rf_on = True\r\n self.button_rf.set_checked(rf_on, block_events=True).enable()\r\n \r\n # Update the combo; we block first just in case the value doesn't \"change\"\r\n if self.api == None: self.label_instrument_name.set_text('Simulation')\r\n else:\r\n if self.api.get_mode() == 'Fixed': self.combo_mode.set_value(0, block_events=True).enable()\r\n else: self.combo_mode.set_value(1, block_events=True).enable()\r\n self._combo_mode_changed()\r\n \r\n # Update the list plot\r\n self.query_list()","def reload(self):\n\n pass","def refresh_plugin(self):\n pass","def refresh_view(self):\n # self.view_model.query_str = \"\"\n self.query_header.content.text = query_title_bar_text(self.shared_state)\n # self.view_model.update_results()\n self.layout.focus(self.query_window)","def Reload(self):\n self._inspector_backend.Navigate(self.url, None, 10)","def RefreshButton(self, part):\r\n \r\n rect = wx.Rect(*part.rect)\r\n rect.Inflate(2, 2)\r\n self._frame.Refresh(True, rect)\r\n self._frame.Update()","def refresh_chat(self):\n self.chat_container.noutrefresh()\n self.chat_win.noutrefresh()\n curses.doupdate()","def refresh(self):\n self._refresh_method()","def _sync_gui(self):\n self._update_buttons()\n\n self.turn_value_label.config(text=self.turn_value_text)\n self.selected_piece_value_label.config(text=self.selected_piece_value_text)\n\n self.update()","def redraw(self):\n self._create()","def on_reload_button_cicked_(self):\n self.pause_subscriber = True\n\n self._load_robot_description()\n controllers = self.get_current_controllers()\n\n self.joints = self._create_joints(controllers)\n\n self.synergy = self._create_synergy(controllers)\n\n self.delete_old_sliders_()\n\n # self._widget.sliderReleaseCheckBox.setCheckState(Qt.Unchecked)\n\n self.load_new_synergy_sliders_()\n\n # self.load_new_sliders_()\n\n self._update_synergy_viewer()\n\n self.pause_subscriber = False","def exec(self):\n self._root.after(100, self.change_state, States.INITIAL) # enter the state once gui is setup\n super().exec()","def updateGraphics():\n _root.update_idletasks()","def _refreshActionTriggeredSlot(self):\r\n \r\n self._controller.model.refresh(self._controller.model.activeIndex)","def refresh_prompt(self):\n self.prompt_win.noutrefresh()\n curses.doupdate()","def on_refresh_button_cicked_(self):\n for slider in self.sliders:\n slider.refresh()","def update(self):\n self.wc.update()","def restart(self):\n self.points_arr.append(self.click_count)\n self.grid.destroy()\n self.click_count = 0\n self.ranking_label.destroy()\n self.ranking_box.destroy()\n self.ranking_box = Gtk.Grid()\n self.vbox.add(self.ranking_box)\n self.ranking_panel()\n self.point_label_score.set_markup(\"<b>0</b>\")\n self.point_label_score.show_all()\n self.grid = BallsGrid(self.rows, self.cols)\n self.create_grid()\n self.grid.show()","def restart(self):\n self.gui_block.set()","def win32_refresh_window(cls) -> None:\n # Get console handle\n handle = HANDLE(windll.kernel32.GetConsoleWindow())\n\n RDW_INVALIDATE = 0x0001\n windll.user32.RedrawWindow(handle, None, None, c_uint(RDW_INVALIDATE))","def update_gui(self):\n for where, updates in self.gui_updates.items():\n self.window[where].update(**updates)\n self.gui_updates = {}","def refresh_UI(self):\r\n\t\tself.source_img_entry.setText(self.filestate.get_source_img_filename())\r\n\t\tself.sink_dir_entry.setText(self.filestate.get_sink_dir_name())\r\n\t\tself.sink_db_name_entry.setText(self.filestate.get_sink_db_filename())\r\n\t\tif self.existing_case: self.source_db_entry.setText(self.filestate.get_source_db_filename())","def updateWidget(self):\n\n if self.frame1.state() == 'normal':\n self.frame2.deiconify()\n self.frame1.withdraw()\n else:\n self.frame2.withdraw()\n self.frame2.update()\n self.frame2.deiconify()\n self.frame1.title(\"%s's turn\" % self.usernames[1])\n self.frame2.title(\"%s's turn\" % self.usernames[0])\n showDialogBox(\"%s's turn first!\" % self.usernames[0])\n self.frame1.update()\n self.frame2.update()","def naredi_refresh_zs_panela(self):\r\n self.emit(QtCore.SIGNAL('refresh_zs_panela'))","def refresh(self):\n raise NotImplementedError","def refresh(self):\n raise NotImplementedError","def refresh(self):\n raise NotImplementedError(\"To be implemented\")","def redraw(self):\r\n self.c.update()","def update(self):\n self.redraw()\n self._changed = False","def update(self):\n self.redraw()\n self._changed = False","def update(self):\n self.backbone_module.update()\n mx.nd.waitall()","def flush(self):\n #self.update_idletasks()\n self.__checkOpen()\n _tkCall(self.update_idletasks)","def reload_processgraph_view(self):\n #widget = self.processgraphWidget\n #self.load_dict_into_widget(widget, self.processgraph.graph)\n self.processgraphEdit.setText(json.dumps(self.processgraph.graph, indent=2, sort_keys=True))\n #widget.show()","def refreshTree(self):\n\n # Gets default rows\n rows = getsAllClients()\n\n # Puts and displays rows in tree\n self.displayTreeRows(rows)","def redraw_menu(self, event):\n self.appInit()\n self.redraw()","def relayout(self): \n\t\t#self.urmaswin.Layout()\n\t\t#wx.CallAfter(self.urmaswin.Layout)\n\t\t#wx.CallAfter(self.visualizer.OnSize)","def refresh(self, btn=None):\n\n if self.visible and self.filename:\n self.load_file(self.filename, self.title)","def refresh_self(self) -> None:\n self._logger.debug(\"running\")\n try:\n self.figure.canvas.draw()\n except Exception as e:\n self._logger.exception(\"issue with drawing canvas.\")\n self._logger.debug(\"done\")","def UpdateDisplay(self):\n ##Jconf\n self.chJconf.Clear()\n for name in self.state.GetSurface(\"JconfDict\").GetNames():\n self.chJconf.Append(name)\n self.chJconf.SetStringSelection(self.state.GetSurface(\"JconfSelection\"))\n self.chJconf.Enable(self.state.IsEnabled(\"JconfDict\") == True and\n self.state.IsEnabled(\"JconfSelection\") == True and\n self.state.GetSurface(\"Xplorer\") == True)\n self.bEditJconf.Enable(self.state.IsEnabled(\"JconfDict\") and\n self.state.GetSurface(\"Xplorer\") == True)\n ##Name Server\n self.cbNameServer.SetValue(self.state.GetSurface(\"NameServer\"))\n self.cbNameServer.Enable(self.state.IsEnabled(\"NameServer\"))\n ##Conductor\n self.cbConductor.SetValue(self.state.GetSurface(\"Conductor\"))\n self.cbConductor.Enable(self.state.IsEnabled(\"Conductor\"))\n ##Xplorer\n self.cbXplorer.SetValue(self.state.GetSurface(\"Xplorer\"))\n self.cbXplorer.Enable(self.state.IsEnabled(\"Xplorer\"))\n ##Desktop Mode\n self.cbDesktop.SetValue(self.state.GetSurface(\"DesktopMode\"))\n self.cbDesktop.Enable(self.state.IsEnabled(\"DesktopMode\"))\n ##Xplorer Type\n if self.state.GetSurface(\"DesktopMode\"):\n self.rbXplorer.SetSelection(0)\n else:\n if (self.state.GetSurface(\"XplorerType\") == \"OSG-VEP\"):\n self.rbXplorer.SetSelection(0)\n else:\n self.rbXplorer.SetSelection(1)\n self.rbXplorer.Enable(self.state.IsEnabled(\"XplorerType\") == True and\n self.state.GetSurface(\"DesktopMode\") == False and\n self.state.GetSurface(\"Xplorer\") == True)\n ##Cluster Node button\n self.bCluster.Enable(CLUSTER_ENABLED and\n self.state.GetSurface(\"Xplorer\") == True and\n self.state.GetSurface(\"DesktopMode\") == False and\n self.state.GetSurface(\"XplorerType\") == \"OSG-VEPC\")\n return","def reload_widget(self, worker_name):\n self.worker_config = self.main_ctrl.get_worker_config(worker_name)\n self.setup_ui_data(self.worker_config)\n self._pause_worker()","def cmd_refresh():\r\n if game_on:\r\n global wrd_lst, head_lst\r\n letters = refresh()\r\n generate_button(letters)\r\n wrd_lst = []\r\n head_lst = [1]\r\n for button in button_lst:\r\n button['bg'] = 'white'\r\n word_display['text'] = \"\"","def draw(self):\n\n # Use update instead of update_idletasks because it works better\n # on some Windows machines.\n self.root.update()","def unload(self): \n self.mainOperator.LabelInputs.resize(0)\n self._dirty = False","def redraw(self):\n self.vispy_widget.canvas.update()","def exec_(self):\n self.app.exec_()","def redraw(self):\n self.vispy_viewer.canvas.update()","def refresh_HDV(self):\n self.canvas.draw()\n self.dicom_navigation.parent.dicom_right_window.top_info.canvas_HDV.draw()","def onReload(self, event):\n\n\t\tself.wv.Reload()","def on_NodeServiceRefresh_clicked(self):\n # TODO: not implemented yet\n #raise NotImplementedError\n output=\"Refresh Finished ! Press button to Get more text!\"\n if self.NodeServer!=\"\" :\n try:\n output=self.NodeServer.readcmdResult(1000)\n print(f\"cmd execute result:\\n{output}\")\n\n except:\n print(\"No More Result!\")\n\n self.NodeServiceText.append(output)\n print(output)\n\n self.NodeServiceText.reload()\n ## should add some code here for server and client","def reload(self):\n self.rpc.call(MsfRpcMethod.CoreReloadModules)","def refresh(self, event):\n self.updatetext(self.textfunc, self.textargs)","def reset(self, event):\n #Resets the current puzzle\n self.w.delete('all') #Deletes all widgets/components \n self.resetnums() #Call restnums() to reset self.movelist\n\n #Destroys all buttons on GUI\n #self.buttonlist.append(self.lbl)\n for i in range(len(self.buttonlist)):\n self.buttonlist[i].destroy()\n\n self.create_widgets(self.counter) #Calls the create_widgets() to redisplay all widgets and buttons\n self.lbl2[\"text\"] = \"\" #Clears any text (e.g. instructions or check) if there is any.","def refresh_display(self):\n for widget in self.button_frame.children.values():\n widget.grid_forget() \n\n for (i, rd) in enumerate(self.row_detail_list):\n rd.frame.grid(row=i)","def updateSettingsUI(self):\n\n pass","def run(self):\n self.root.title(\"Etymology relations\")\n self.root.geometry(\"1080x600\")\n self.root.deiconify()\n self.root.mainloop()","def menu_redraw_blender_window(self, event=None):\n if self.app.children:\n self.app.childActive.refresh()","def reload_and_trigger_output(self):\n self.browser.refresh()\n self.wait_for_js() # pylint: disable=no-member\n self.q(css='div#fixture button').first.click()","def flush(self):\n self.__checkOpen()\n _root.update()","def refreshCredit(self):\n self.mainmenu.updateCR()","def redraw(self) -> None:\n self.canvas.draw_idle()\n self.Refresh()","def refreshActiveFrames(self, event=None):\n self.unloadAllFrames()\n self.checkFramesHaveData()\n\n try:\n self.contentFrame.currFrame.built = False\n except AttributeError:\n pass\n\n try:\n if self.contentFrame.currFrame.hasRequiredData():\n self.contentFrame.currFrame.enter()\n else:\n self.frameBtnCmds[0](self)\n except AttributeError:\n self.frameBtnCmds[0](self)","def updateGui(self, msg):\n TRIES = 10\n for i in range(1, TRIES+1):\n try: # attempt up to 10 times if socket error\n #self.__gui_app.sendUpdate(msg)\n # LJR - Fixed Python 2.7 bug by reconnecting to server locally on each request\n g= xmlrpclib.ServerProxy('http://localhost:%d' % self.__xmlrpc_port)\n g.sendUpdate(msg)\n break\n except socket.error, info: # most likely 'connection refused'\n if i == TRIES:\n print \"ERROR: XML-RPC call failed all %d tries! %s\" % (i,info)\n sys.exit(-1)\n time.sleep(0.1)","def update_(self):\n self.update_listbox()\n self.update_infobox()\n self.update_statusbar()\n self.listbox.select_set(0)\n self.listbox.focus_set()"],"string":"[\n \"def refresh(self):\\n\\t\\tself.win.refresh()\\n\\t\\tfor c in self.components:\\n\\t\\t\\tc.refresh()\",\n \"def refresh_dialog(self):\\n self._client.update_elements()\",\n \"def refresh(self):\\n self.Refresh()\",\n \"def Refresh(self):\\n pass\",\n \"def refresh(self):\\n self.__refresh()\",\n \"def refresh(self) -> None:\\n self.screen.refresh()\",\n \"def _refresh(self):\\n self._need_display_update = True\\n self._update()\",\n \"def refresh(self):\\n self.log_info(f\\\"Browser.refresh: Refreshing the page\\\")\\n self.CORE.refresh()\\n return\",\n \"def reload():\\n xd = display.XKCDDisplayService()\\n if xd.is_running():\\n click.echo(\\\"gracefully reloading changes\\\")\\n xd.send_signal(signal.SIGHUP)\\n else:\\n click.echo(\\\"xkcd service not running\\\")\",\n \"def refresh_screen(self):\",\n \"def refresh(self):\\n\\n if self.eventBox.window != None:\\n self.eventBox.window.set_cursor(None)\\n self.enable_controls(False)\\n threading.Thread(target=self.thread_refresh).start()\",\n \"def refresh(self):\\n\\t\\tself.driver.refresh()\",\n \"def refresh(self):\\n pass\",\n \"def refresh(self):\\n pass\",\n \"def refresh_screen(self):\\n stdscr = self.stdscr\\n stdscr.refresh()\",\n \"def refresh(self):\\n\\n for w in self.windows.values():\\n w.refresh()\",\n \"def refresh(self) -> None:\\n pass\",\n \"def refresh(self) -> None:\\n pass\",\n \"def refresh(self) -> None:\\n pass\",\n \"def _refresh_screen(self):\\n self.myscreen.refresh()\\n self.box1.refresh()\\n self.box2.refresh()\",\n \"def refresh():\\n curve_editor.refresh()\",\n \"def on_refreshButton_clicked(self):\\n self.buttonBox.button(QDialogButtonBox.Close).setEnabled(False)\\n \\n self.buttonBox.button(QDialogButtonBox.Save).setEnabled(False)\\n self.refreshButton.setEnabled(False)\\n \\n self.start(self.__filename, diffMode=self.__diffMode, refreshable=True)\",\n \"def refresh_all(self):\\n self.stdscr.noutrefresh()\\n self.chat_container.noutrefresh()\\n self.chat_win.noutrefresh()\\n self.prompt_win.noutrefresh()\\n curses.doupdate()\",\n \"def refresh(self):\\n self.getWindow().getDecorView().postInvalidate()\",\n \"def refresh(self):\\n\\n # Set Graphics scene\\n self.setScene(QtGui.QGraphicsScene())\\n self._connections = set()\\n self._nodes = {}\\n self._selection = set()\\n self._manipulation_mode = 0\\n self._selection_rect = None\",\n \"def updateWidget(self):\\n pass\",\n \"def UpdateUI(self):\\n # colors & font\\n self.SetBackgroundColour(wx.GetApp().settings.bg_color)\\n self.SetForegroundColour(wx.GetApp().settings.fg_color)\\n self.SetFont(wx.GetApp().settings.text_font)\\n\\n # apply new (or not) 'wx' values to content.\\n p = self.FindWindow(\\\"content\\\")\\n if p is not None:\\n p.SetBackgroundColour(wx.GetApp().settings.bg_color)\\n p.SetForegroundColour(wx.GetApp().settings.fg_color)\\n p.SetFont(wx.GetApp().settings.text_font)\\n\\n # apply new (or not) 'wx' values to header.\\n p = self.FindWindow(\\\"header\\\")\\n if p is not None:\\n p.SetBackgroundColour(wx.GetApp().settings.header_bg_color)\\n p.SetForegroundColour(wx.GetApp().settings.header_fg_color)\\n p.SetFont(wx.GetApp().settings.header_text_font)\\n\\n # apply new (or not) 'wx' values to actions.\\n p = self.FindWindow(\\\"actions\\\")\\n if p is not None:\\n p.SetBackgroundColour(wx.GetApp().settings.action_bg_color)\\n p.SetForegroundColour(wx.GetApp().settings.action_fg_color)\\n p.SetFont(wx.GetApp().settings.action_text_font)\\n\\n self.Refresh()\",\n \"def Refresh(self, erase=True, rect=None):\\r\\n\\r\\n self._main_win.Refresh(erase, rect)\\r\\n self._header_win.Refresh(erase, rect)\",\n \"def refreshContents(self):\\n self.ivGeneralButton1.hide()\\n self.ivGeneralButton2.hide()\\n self.ovGeneralButton1.hide()\\n self.ovGeneralButton2.hide()\\n self.dataBrowser.refreshContents()\\n inputNames = self.dat.flowsheet.input.compoundNames()\\n self.dat.flowsheet.markConnectedInputs()\\n delList = []\\n for i in range(len(inputNames)):\\n if self.dat.flowsheet.input.get(inputNames[i]).con == True:\\n delList.append(inputNames[i])\\n for n in delList:\\n inputNames.remove(n)\\n outputNames = self.dat.flowsheet.output.compoundNames()\\n if self.dat.surrogateCurrent is not None:\\n i = self.toolSelectBox.findText(self.dat.surrogateCurrent)\\n if i >= 0:\\n self.blockapply = True\\n self.toolSelectBox.setCurrentIndex(i)\\n self.blockapply = False\\n tool = self.toolSelectBox.currentText()\\n if tool == \\\"\\\":\\n return\\n pg = self.dat.surrogateMethods.plugins[tool].surrogateMethod(self.dat)\\n pg.loadFromSession()\\n pg.updateOptions()\\n\\n for i, btn in enumerate(pg.inputVarButtons):\\n # this is because I am beeing lazy there are two\\n # preexisting buttons\\n if i == 0:\\n self.ivGeneralButton1.setText(btn[0])\\n self.ivGeneralButton1.show()\\n elif i == 1:\\n self.ivGeneralButton2.setText(btn[0])\\n self.ivGeneralButton2.show()\\n\\n for i, btn in enumerate(pg.outputVarButtons):\\n if i == 0:\\n self.ovGeneralButton1.setText(btn[0])\\n self.ovGeneralButton1.show()\\n elif i == 1:\\n self.ovGeneralButton2.setText(btn[0])\\n self.ovGeneralButton2.show()\\n\\n for i in range(self.optTable[tool].rowCount()):\\n oname = gh.getCellText(self.optTable[tool], i, 0)\\n if oname in pg.options:\\n if pg.options[oname].dtype == bool:\\n gh.setCellChecked(\\n self.optTable[tool], i, 1, pg.options[oname].value\\n )\\n elif len(pg.options[oname].validValues) > 0:\\n gh.cellPulldownSetItemsJSON(\\n self.optTable[tool], i, 1, pg.options[oname].validValues\\n )\\n gh.cellPulldownSetJSON(\\n self.optTable[tool], i, 1, pg.options[oname].value\\n )\\n else:\\n gh.setCellJSON(self.optTable[tool], i, 1, pg.options[oname].value)\\n self.inputTable.setRowCount(0)\\n self.inputTable.setColumnCount(3 + len(pg.inputCols))\\n for i, item in enumerate(pg.inputCols):\\n gh.setColHeaderIntem(self.inputTable, i + 3, item[0])\\n self.outputTable.setRowCount(0)\\n self.outputTable.setColumnCount(1 + len(pg.outputCols))\\n for i, item in enumerate(pg.outputCols):\\n gh.setColHeaderIntem(self.outputTable, i + 1, item[0])\\n self.inputTable.setRowCount(len(inputNames))\\n self.outputTable.setRowCount(len(outputNames))\\n self.inputCols = gh.colIndexes(self.inputTable)\\n self.outputCols = gh.colIndexes(self.outputTable)\\n for i in range(len(inputNames)):\\n var = self.dat.flowsheet.input.get(inputNames[i])\\n gh.setTableItem(\\n self.inputTable,\\n row=i,\\n col=self.inputCols[\\\"Name\\\"],\\n text=inputNames[i],\\n check=inputNames[i] in pg.input,\\n editable=False,\\n )\\n gh.setTableItem(\\n self.inputTable,\\n row=i,\\n col=self.inputCols[\\\"Max\\\"],\\n text=var.max,\\n jsonEnc=True,\\n )\\n gh.setTableItem(\\n self.inputTable,\\n row=i,\\n col=self.inputCols[\\\"Min\\\"],\\n text=var.min,\\n jsonEnc=True,\\n )\\n for item in pg.inputCols:\\n val = pg.getInputVarOption(item[0], inputNames[i])\\n gh.setTableItem(\\n self.inputTable,\\n row=i,\\n col=self.inputCols[item[0]],\\n text=val,\\n jsonEnc=True,\\n )\\n for i in range(len(outputNames)):\\n var = self.dat.flowsheet.output.get(outputNames[i])\\n gh.setTableItem(\\n self.outputTable,\\n row=i,\\n col=self.outputCols[\\\"Name\\\"],\\n text=outputNames[i],\\n check=outputNames[i] in pg.output,\\n editable=False,\\n )\\n for item in pg.outputCols:\\n val = pg.getOutputVarOption(item[0], outputNames[i])\\n gh.setTableItem(\\n self.outputTable,\\n row=i,\\n col=self.outputCols[item[0]],\\n text=val,\\n jsonEnc=True,\\n )\\n self.inputTable.resizeColumnsToContents()\\n self.outputTable.resizeColumnsToContents()\",\n \"def show(self):\\n self.root.update()\\n self.root.deiconify()\",\n \"def refresh(self):\\n\\n self.driver.implicitly_wait(5)\\n self.driver.refresh()\",\n \"def refresh_all(self):\\n\\t\\t\\n\\t\\tself.symbolsList.set_datasource(self.source)\\n\\t\\tself.symbolsList.refresh()\\n\\t\\t\\n\\t\\tself.plotFrame.set_datasource(self.source)\\n\\t\\tself.plotFrame.refresh()\",\n \"def refresh(self) :\\n if not self.running:\\n self.running = True\\n self.strip.show()\\n self.running = False\\n self.refreshTimer.expired = True\\n self.refreshTimer.isrunning = False\",\n \"def repaint(self):\\n pass\",\n \"def reload(self):\",\n \"def reload(self):\",\n \"def refresh_window():\\n global lineno\\n lineno = 0\\n curses.endwin()\\n win.erase()\\n print_header()\\n win.refresh()\",\n \"def _update_gui(self):\\r\\n \\r\\n # Update the RF button.\\r\\n rf_on = self.api.get_output()\\r\\n if rf_on == None: rf_on = True\\r\\n self.button_rf.set_checked(rf_on, block_events=True).enable()\\r\\n \\r\\n # Update the combo; we block first just in case the value doesn't \\\"change\\\"\\r\\n if self.api == None: self.label_instrument_name.set_text('Simulation')\\r\\n else:\\r\\n if self.api.get_mode() == 'Fixed': self.combo_mode.set_value(0, block_events=True).enable()\\r\\n else: self.combo_mode.set_value(1, block_events=True).enable()\\r\\n self._combo_mode_changed()\\r\\n \\r\\n # Update the list plot\\r\\n self.query_list()\",\n \"def reload(self):\\n\\n pass\",\n \"def refresh_plugin(self):\\n pass\",\n \"def refresh_view(self):\\n # self.view_model.query_str = \\\"\\\"\\n self.query_header.content.text = query_title_bar_text(self.shared_state)\\n # self.view_model.update_results()\\n self.layout.focus(self.query_window)\",\n \"def Reload(self):\\n self._inspector_backend.Navigate(self.url, None, 10)\",\n \"def RefreshButton(self, part):\\r\\n \\r\\n rect = wx.Rect(*part.rect)\\r\\n rect.Inflate(2, 2)\\r\\n self._frame.Refresh(True, rect)\\r\\n self._frame.Update()\",\n \"def refresh_chat(self):\\n self.chat_container.noutrefresh()\\n self.chat_win.noutrefresh()\\n curses.doupdate()\",\n \"def refresh(self):\\n self._refresh_method()\",\n \"def _sync_gui(self):\\n self._update_buttons()\\n\\n self.turn_value_label.config(text=self.turn_value_text)\\n self.selected_piece_value_label.config(text=self.selected_piece_value_text)\\n\\n self.update()\",\n \"def redraw(self):\\n self._create()\",\n \"def on_reload_button_cicked_(self):\\n self.pause_subscriber = True\\n\\n self._load_robot_description()\\n controllers = self.get_current_controllers()\\n\\n self.joints = self._create_joints(controllers)\\n\\n self.synergy = self._create_synergy(controllers)\\n\\n self.delete_old_sliders_()\\n\\n # self._widget.sliderReleaseCheckBox.setCheckState(Qt.Unchecked)\\n\\n self.load_new_synergy_sliders_()\\n\\n # self.load_new_sliders_()\\n\\n self._update_synergy_viewer()\\n\\n self.pause_subscriber = False\",\n \"def exec(self):\\n self._root.after(100, self.change_state, States.INITIAL) # enter the state once gui is setup\\n super().exec()\",\n \"def updateGraphics():\\n _root.update_idletasks()\",\n \"def _refreshActionTriggeredSlot(self):\\r\\n \\r\\n self._controller.model.refresh(self._controller.model.activeIndex)\",\n \"def refresh_prompt(self):\\n self.prompt_win.noutrefresh()\\n curses.doupdate()\",\n \"def on_refresh_button_cicked_(self):\\n for slider in self.sliders:\\n slider.refresh()\",\n \"def update(self):\\n self.wc.update()\",\n \"def restart(self):\\n self.points_arr.append(self.click_count)\\n self.grid.destroy()\\n self.click_count = 0\\n self.ranking_label.destroy()\\n self.ranking_box.destroy()\\n self.ranking_box = Gtk.Grid()\\n self.vbox.add(self.ranking_box)\\n self.ranking_panel()\\n self.point_label_score.set_markup(\\\"<b>0</b>\\\")\\n self.point_label_score.show_all()\\n self.grid = BallsGrid(self.rows, self.cols)\\n self.create_grid()\\n self.grid.show()\",\n \"def restart(self):\\n self.gui_block.set()\",\n \"def win32_refresh_window(cls) -> None:\\n # Get console handle\\n handle = HANDLE(windll.kernel32.GetConsoleWindow())\\n\\n RDW_INVALIDATE = 0x0001\\n windll.user32.RedrawWindow(handle, None, None, c_uint(RDW_INVALIDATE))\",\n \"def update_gui(self):\\n for where, updates in self.gui_updates.items():\\n self.window[where].update(**updates)\\n self.gui_updates = {}\",\n \"def refresh_UI(self):\\r\\n\\t\\tself.source_img_entry.setText(self.filestate.get_source_img_filename())\\r\\n\\t\\tself.sink_dir_entry.setText(self.filestate.get_sink_dir_name())\\r\\n\\t\\tself.sink_db_name_entry.setText(self.filestate.get_sink_db_filename())\\r\\n\\t\\tif self.existing_case: self.source_db_entry.setText(self.filestate.get_source_db_filename())\",\n \"def updateWidget(self):\\n\\n if self.frame1.state() == 'normal':\\n self.frame2.deiconify()\\n self.frame1.withdraw()\\n else:\\n self.frame2.withdraw()\\n self.frame2.update()\\n self.frame2.deiconify()\\n self.frame1.title(\\\"%s's turn\\\" % self.usernames[1])\\n self.frame2.title(\\\"%s's turn\\\" % self.usernames[0])\\n showDialogBox(\\\"%s's turn first!\\\" % self.usernames[0])\\n self.frame1.update()\\n self.frame2.update()\",\n \"def naredi_refresh_zs_panela(self):\\r\\n self.emit(QtCore.SIGNAL('refresh_zs_panela'))\",\n \"def refresh(self):\\n raise NotImplementedError\",\n \"def refresh(self):\\n raise NotImplementedError\",\n \"def refresh(self):\\n raise NotImplementedError(\\\"To be implemented\\\")\",\n \"def redraw(self):\\r\\n self.c.update()\",\n \"def update(self):\\n self.redraw()\\n self._changed = False\",\n \"def update(self):\\n self.redraw()\\n self._changed = False\",\n \"def update(self):\\n self.backbone_module.update()\\n mx.nd.waitall()\",\n \"def flush(self):\\n #self.update_idletasks()\\n self.__checkOpen()\\n _tkCall(self.update_idletasks)\",\n \"def reload_processgraph_view(self):\\n #widget = self.processgraphWidget\\n #self.load_dict_into_widget(widget, self.processgraph.graph)\\n self.processgraphEdit.setText(json.dumps(self.processgraph.graph, indent=2, sort_keys=True))\\n #widget.show()\",\n \"def refreshTree(self):\\n\\n # Gets default rows\\n rows = getsAllClients()\\n\\n # Puts and displays rows in tree\\n self.displayTreeRows(rows)\",\n \"def redraw_menu(self, event):\\n self.appInit()\\n self.redraw()\",\n \"def relayout(self): \\n\\t\\t#self.urmaswin.Layout()\\n\\t\\t#wx.CallAfter(self.urmaswin.Layout)\\n\\t\\t#wx.CallAfter(self.visualizer.OnSize)\",\n \"def refresh(self, btn=None):\\n\\n if self.visible and self.filename:\\n self.load_file(self.filename, self.title)\",\n \"def refresh_self(self) -> None:\\n self._logger.debug(\\\"running\\\")\\n try:\\n self.figure.canvas.draw()\\n except Exception as e:\\n self._logger.exception(\\\"issue with drawing canvas.\\\")\\n self._logger.debug(\\\"done\\\")\",\n \"def UpdateDisplay(self):\\n ##Jconf\\n self.chJconf.Clear()\\n for name in self.state.GetSurface(\\\"JconfDict\\\").GetNames():\\n self.chJconf.Append(name)\\n self.chJconf.SetStringSelection(self.state.GetSurface(\\\"JconfSelection\\\"))\\n self.chJconf.Enable(self.state.IsEnabled(\\\"JconfDict\\\") == True and\\n self.state.IsEnabled(\\\"JconfSelection\\\") == True and\\n self.state.GetSurface(\\\"Xplorer\\\") == True)\\n self.bEditJconf.Enable(self.state.IsEnabled(\\\"JconfDict\\\") and\\n self.state.GetSurface(\\\"Xplorer\\\") == True)\\n ##Name Server\\n self.cbNameServer.SetValue(self.state.GetSurface(\\\"NameServer\\\"))\\n self.cbNameServer.Enable(self.state.IsEnabled(\\\"NameServer\\\"))\\n ##Conductor\\n self.cbConductor.SetValue(self.state.GetSurface(\\\"Conductor\\\"))\\n self.cbConductor.Enable(self.state.IsEnabled(\\\"Conductor\\\"))\\n ##Xplorer\\n self.cbXplorer.SetValue(self.state.GetSurface(\\\"Xplorer\\\"))\\n self.cbXplorer.Enable(self.state.IsEnabled(\\\"Xplorer\\\"))\\n ##Desktop Mode\\n self.cbDesktop.SetValue(self.state.GetSurface(\\\"DesktopMode\\\"))\\n self.cbDesktop.Enable(self.state.IsEnabled(\\\"DesktopMode\\\"))\\n ##Xplorer Type\\n if self.state.GetSurface(\\\"DesktopMode\\\"):\\n self.rbXplorer.SetSelection(0)\\n else:\\n if (self.state.GetSurface(\\\"XplorerType\\\") == \\\"OSG-VEP\\\"):\\n self.rbXplorer.SetSelection(0)\\n else:\\n self.rbXplorer.SetSelection(1)\\n self.rbXplorer.Enable(self.state.IsEnabled(\\\"XplorerType\\\") == True and\\n self.state.GetSurface(\\\"DesktopMode\\\") == False and\\n self.state.GetSurface(\\\"Xplorer\\\") == True)\\n ##Cluster Node button\\n self.bCluster.Enable(CLUSTER_ENABLED and\\n self.state.GetSurface(\\\"Xplorer\\\") == True and\\n self.state.GetSurface(\\\"DesktopMode\\\") == False and\\n self.state.GetSurface(\\\"XplorerType\\\") == \\\"OSG-VEPC\\\")\\n return\",\n \"def reload_widget(self, worker_name):\\n self.worker_config = self.main_ctrl.get_worker_config(worker_name)\\n self.setup_ui_data(self.worker_config)\\n self._pause_worker()\",\n \"def cmd_refresh():\\r\\n if game_on:\\r\\n global wrd_lst, head_lst\\r\\n letters = refresh()\\r\\n generate_button(letters)\\r\\n wrd_lst = []\\r\\n head_lst = [1]\\r\\n for button in button_lst:\\r\\n button['bg'] = 'white'\\r\\n word_display['text'] = \\\"\\\"\",\n \"def draw(self):\\n\\n # Use update instead of update_idletasks because it works better\\n # on some Windows machines.\\n self.root.update()\",\n \"def unload(self): \\n self.mainOperator.LabelInputs.resize(0)\\n self._dirty = False\",\n \"def redraw(self):\\n self.vispy_widget.canvas.update()\",\n \"def exec_(self):\\n self.app.exec_()\",\n \"def redraw(self):\\n self.vispy_viewer.canvas.update()\",\n \"def refresh_HDV(self):\\n self.canvas.draw()\\n self.dicom_navigation.parent.dicom_right_window.top_info.canvas_HDV.draw()\",\n \"def onReload(self, event):\\n\\n\\t\\tself.wv.Reload()\",\n \"def on_NodeServiceRefresh_clicked(self):\\n # TODO: not implemented yet\\n #raise NotImplementedError\\n output=\\\"Refresh Finished ! Press button to Get more text!\\\"\\n if self.NodeServer!=\\\"\\\" :\\n try:\\n output=self.NodeServer.readcmdResult(1000)\\n print(f\\\"cmd execute result:\\\\n{output}\\\")\\n\\n except:\\n print(\\\"No More Result!\\\")\\n\\n self.NodeServiceText.append(output)\\n print(output)\\n\\n self.NodeServiceText.reload()\\n ## should add some code here for server and client\",\n \"def reload(self):\\n self.rpc.call(MsfRpcMethod.CoreReloadModules)\",\n \"def refresh(self, event):\\n self.updatetext(self.textfunc, self.textargs)\",\n \"def reset(self, event):\\n #Resets the current puzzle\\n self.w.delete('all') #Deletes all widgets/components \\n self.resetnums() #Call restnums() to reset self.movelist\\n\\n #Destroys all buttons on GUI\\n #self.buttonlist.append(self.lbl)\\n for i in range(len(self.buttonlist)):\\n self.buttonlist[i].destroy()\\n\\n self.create_widgets(self.counter) #Calls the create_widgets() to redisplay all widgets and buttons\\n self.lbl2[\\\"text\\\"] = \\\"\\\" #Clears any text (e.g. instructions or check) if there is any.\",\n \"def refresh_display(self):\\n for widget in self.button_frame.children.values():\\n widget.grid_forget() \\n\\n for (i, rd) in enumerate(self.row_detail_list):\\n rd.frame.grid(row=i)\",\n \"def updateSettingsUI(self):\\n\\n pass\",\n \"def run(self):\\n self.root.title(\\\"Etymology relations\\\")\\n self.root.geometry(\\\"1080x600\\\")\\n self.root.deiconify()\\n self.root.mainloop()\",\n \"def menu_redraw_blender_window(self, event=None):\\n if self.app.children:\\n self.app.childActive.refresh()\",\n \"def reload_and_trigger_output(self):\\n self.browser.refresh()\\n self.wait_for_js() # pylint: disable=no-member\\n self.q(css='div#fixture button').first.click()\",\n \"def flush(self):\\n self.__checkOpen()\\n _root.update()\",\n \"def refreshCredit(self):\\n self.mainmenu.updateCR()\",\n \"def redraw(self) -> None:\\n self.canvas.draw_idle()\\n self.Refresh()\",\n \"def refreshActiveFrames(self, event=None):\\n self.unloadAllFrames()\\n self.checkFramesHaveData()\\n\\n try:\\n self.contentFrame.currFrame.built = False\\n except AttributeError:\\n pass\\n\\n try:\\n if self.contentFrame.currFrame.hasRequiredData():\\n self.contentFrame.currFrame.enter()\\n else:\\n self.frameBtnCmds[0](self)\\n except AttributeError:\\n self.frameBtnCmds[0](self)\",\n \"def updateGui(self, msg):\\n TRIES = 10\\n for i in range(1, TRIES+1):\\n try: # attempt up to 10 times if socket error\\n #self.__gui_app.sendUpdate(msg)\\n # LJR - Fixed Python 2.7 bug by reconnecting to server locally on each request\\n g= xmlrpclib.ServerProxy('http://localhost:%d' % self.__xmlrpc_port)\\n g.sendUpdate(msg)\\n break\\n except socket.error, info: # most likely 'connection refused'\\n if i == TRIES:\\n print \\\"ERROR: XML-RPC call failed all %d tries! %s\\\" % (i,info)\\n sys.exit(-1)\\n time.sleep(0.1)\",\n \"def update_(self):\\n self.update_listbox()\\n self.update_infobox()\\n self.update_statusbar()\\n self.listbox.select_set(0)\\n self.listbox.focus_set()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7118413","0.6885529","0.6867989","0.66451275","0.65044814","0.6423347","0.6417798","0.6398829","0.63724816","0.6371857","0.63682497","0.6328148","0.63234603","0.63234603","0.6223904","0.62109405","0.6206273","0.6206273","0.6206273","0.6157153","0.60916936","0.6085941","0.6057907","0.60544246","0.60501224","0.60323954","0.60251707","0.6015356","0.6007564","0.60028046","0.5997792","0.5991072","0.59269166","0.5910002","0.59070915","0.59070915","0.5900439","0.58852845","0.5884753","0.58838975","0.58783025","0.5863434","0.5856141","0.5833551","0.58271545","0.5789529","0.5787836","0.5768445","0.5767469","0.57642037","0.5742768","0.57362854","0.5710715","0.5704518","0.5697073","0.56899273","0.56792927","0.567352","0.5672819","0.56593966","0.56586266","0.56573504","0.56573504","0.5653056","0.5636545","0.56355983","0.56355983","0.56309074","0.56287163","0.5608343","0.56060326","0.55857676","0.5580585","0.55771023","0.55763704","0.5572605","0.5568853","0.55686796","0.55664104","0.5565459","0.55612564","0.55597776","0.55510813","0.55399275","0.5536942","0.5533604","0.55329555","0.55198336","0.55152845","0.55152535","0.5512832","0.5510667","0.55096006","0.54924834","0.5490281","0.54791355","0.5472308","0.5471428","0.54713976","0.5450764"],"string":"[\n \"0.7118413\",\n \"0.6885529\",\n \"0.6867989\",\n \"0.66451275\",\n \"0.65044814\",\n \"0.6423347\",\n \"0.6417798\",\n \"0.6398829\",\n \"0.63724816\",\n \"0.6371857\",\n \"0.63682497\",\n \"0.6328148\",\n \"0.63234603\",\n \"0.63234603\",\n \"0.6223904\",\n \"0.62109405\",\n \"0.6206273\",\n \"0.6206273\",\n \"0.6206273\",\n \"0.6157153\",\n \"0.60916936\",\n \"0.6085941\",\n \"0.6057907\",\n \"0.60544246\",\n \"0.60501224\",\n \"0.60323954\",\n \"0.60251707\",\n \"0.6015356\",\n \"0.6007564\",\n \"0.60028046\",\n \"0.5997792\",\n \"0.5991072\",\n \"0.59269166\",\n \"0.5910002\",\n \"0.59070915\",\n \"0.59070915\",\n \"0.5900439\",\n \"0.58852845\",\n \"0.5884753\",\n \"0.58838975\",\n \"0.58783025\",\n \"0.5863434\",\n \"0.5856141\",\n \"0.5833551\",\n \"0.58271545\",\n \"0.5789529\",\n \"0.5787836\",\n \"0.5768445\",\n \"0.5767469\",\n \"0.57642037\",\n \"0.5742768\",\n \"0.57362854\",\n \"0.5710715\",\n \"0.5704518\",\n \"0.5697073\",\n \"0.56899273\",\n \"0.56792927\",\n \"0.567352\",\n \"0.5672819\",\n \"0.56593966\",\n \"0.56586266\",\n \"0.56573504\",\n \"0.56573504\",\n \"0.5653056\",\n \"0.5636545\",\n \"0.56355983\",\n \"0.56355983\",\n \"0.56309074\",\n \"0.56287163\",\n \"0.5608343\",\n \"0.56060326\",\n \"0.55857676\",\n \"0.5580585\",\n \"0.55771023\",\n \"0.55763704\",\n \"0.5572605\",\n \"0.5568853\",\n \"0.55686796\",\n \"0.55664104\",\n \"0.5565459\",\n \"0.55612564\",\n \"0.55597776\",\n \"0.55510813\",\n \"0.55399275\",\n \"0.5536942\",\n \"0.5533604\",\n \"0.55329555\",\n \"0.55198336\",\n \"0.55152845\",\n \"0.55152535\",\n \"0.5512832\",\n \"0.5510667\",\n \"0.55096006\",\n \"0.54924834\",\n \"0.5490281\",\n \"0.54791355\",\n \"0.5472308\",\n \"0.5471428\",\n \"0.54713976\",\n \"0.5450764\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.85330975"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88584,"cells":{"query":{"kind":"string","value":"Check whether dataset is available."},"document":{"kind":"string","value":"def datasetAvailable(self):\n dset = None\n try:\n dset = self._getcopy()\n except Exception:\n pass\n\n if dset is not None:\n self._parent.destroyDset(dset)\n return True\n return False"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def data_available(dataset_name=None):\r\n for file_list in data_resources[dataset_name]['files']:\r\n for file in file_list:\r\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\r\n return False\r\n return True","def check_dataset_exists(dataset):\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\n return result == 0","def DataAvailable(self) -> bool:","def get_is_data_available(self):\n return self._data_available","def check_for_data():\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\n return False\n return True","def is_dataset(self):\n return self._dataset is not None","def dataset_exists(es_url, id, es_index=\"grq\"):\n\n total, id = check_dataset(es_url, id, es_index)\n if total > 0:\n return True\n return False","def exists_dataset(self, dataset):\n assert dataset, \"Must input a valid dataset name.\"\n return any(self.get_by_dataset(dataset))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))","def dataset_exists(dataset_reference, client):\n from google.cloud.exceptions import NotFound\n\n try:\n client.get_dataset(dataset_reference)\n return True\n except NotFound:\n return False","def has_datamask(self):\n return self.datamask is not None","def data_loaded_check(self):\n return True","def is_empty(self):\n for key, dataset in self.datasets.items():\n try:\n has_data = dataset.has_data()\n except MFDataException as mfde:\n raise MFDataException(\n mfdata_except=mfde,\n model=self._container_package.model_name,\n package=self._container_package._get_pname(),\n message=\"Error occurred while verifying\"\n ' data of dataset \"{}\" in block '\n '\"{}\"'.format(dataset.structure.name, self.structure.name),\n )\n\n if has_data is not None and has_data:\n return False\n return True","def data_ready(self) -> bool:\n data_ready = ctypes.c_uint8()\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\n return data_ready.value != 0","def _check_before_run(self):\r\n if not os.path.exists(self.dataset_dir):\r\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))","def available(self) -> bool:\n return super().available and bool(self.data)","def _DatasetExists(dataset_id, project_id):\n client = GetApiClient()\n service = client.datasets\n get_request_type = GetApiMessage('BigqueryDatasetsGetRequest')\n get_request = get_request_type(datasetId=dataset_id, projectId=project_id)\n try:\n service.Get(get_request)\n return True\n except apitools_exceptions.HttpNotFoundError:\n log.info('Dataset with id [{}:{}] not found.'.format(\n project_id, dataset_id))\n\n return False","def available(self):\n #return not self.anonymous and len(self._data())\n return True","def _loaded_data(self):\n try:\n dsize = [int(d) for d\n in self.run('fits size', via='get').split()]\n except (ValueError, TypeError, AttributeError) as err:\n log.debug(f' FITS size error: {err}')\n return False\n else:\n if 0 in dsize:\n return False\n else:\n return True","def has_data(self):\n return len(self.data) > 0","def check_dataset(self):\n url = self.metadata.metadata_url\n document = Document.objects.get(\n metadata=self.metadata,\n document_type=DocumentEnum.METADATA.value,\n is_original=True,\n )\n original_document = document.content\n self.check_document(url, original_document)","def available(self) -> bool:\n return (\n super().available\n and self.coordinator.data is not None\n and self.module_id in self.coordinator.data\n and self.data_id in self.coordinator.data[self.module_id]\n )","def check_availability(self):\n pass","def exists(self, name):\n assert name, \"Must input a valid dataset name.\"\n return name in self.manager.data[\"dataset\"]","def available(self):\n\t\t\treturn False","def available(self):\n\t\t\treturn False","def available(self):\n\t\t\treturn False","def validate_dataset(self):\n pass","def is_valid(self, dataset):\n pass","def check_data(dataframe):\n if dataframe.iloc[0, 0] == 'No data available':\n return False\n else:\n return True","def available(self) -> bool:\n raise NotImplementedError","def _exists(self) -> bool:\n client = MlflowClient()\n all_metrics = client._tracking_client.store.get_all_metrics(\n run_uuid=self.run_id\n )\n return any(self._is_dataset_metric(x) for x in all_metrics)","def is_available():","def has_data(self) -> bool:\n raise NotImplementedError","def _check_before_run(self):\r\n if not osp.exists(self.dataset_dir):\r\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\r\n if not osp.exists(self.train_dir):\r\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))","def available(self) -> bool:\n return True","def available(self) -> bool:\n return True","def CheckForExistence(requested_data, available_data):\n if requested_data is not None:\n return 1 # The requested data exists.\n elif available_data:\n return -1 # The requested data does not exist.\n else:\n return 0 # No data exists at all.","def available(self) -> bool:\n return super().available and (\n self.coordinator.data.get(self.entity_description.key) is not None\n )","def data_available(self):\n return (self.status & 0x08) != 0","def exists(dtype, name, rootdir=None):\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)","def is_available() -> bool:\n # This function never throws and returns 0 if driver is missing or can't\n # be initialized\n return device_count() > 0","def is_available(**kwargs: Any) -> bool:\n try:\n _check_available()\n except Unavailable as e:\n logger.info('Database not available: %s', e)\n return False\n return True","def available(self):\n\t\t\treturn True","def available(self):\n\t\t\treturn True","def available(self):\n\t\t\treturn True","def available(self):\n return True","def available(self):\n return True","def data_ready(self):\n data_ready = len(self.barcode) > 0\n data_ready &= self.price > 0\n data_ready &= len(self.description) > 0\n return data_ready","def load_dataset(self) -> bool:\n\n if self.write_path is None:\n raise Exception(\"Error: Attempted to load results dataset without ever specifiying a path to write it to\")\n\n try:\n if self.format == \"arrow\":\n self.res_dataset = Dataset.load_from_disk(self.write_path)\n elif self.format == \"csv\":\n self.res_dataset = pd.read_csv(self.write_path)\n return True\n except:\n return False","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.data_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.data_dir))\n if not osp.exists(self.split_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.split_dir))","def wait_for_data_ready(self):\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_WaitMeasurementDataReady(self.dev))","def is_available(self) -> bool:\n raise NotImplementedError","def ensure_dataset_loaded(self, name):\n if name not in self.datasets:\n print(f'Loading dataset \"{name}\"')\n pd_data = pd.read_excel(self.datafiles[name])\n data = pd.DataFrame.to_dict(pd_data, 'records')\n self.datasets[name] = data","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.test_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.test_dir))","def has_data(self):\n if len(self.channels) > 0:\n return True\n return False","def has_data(self, *args, **kwargs):\n return False","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.list_query_path):\n raise RuntimeError(\"'{}' is not available\".format(self.list_query_path))\n if not osp.exists(self.list_gallery_path):\n raise RuntimeError(\"'{}' is not available\".format(self.list_gallery_path))","def check(self):\n self._parse_config()\n if self.name == \"\":\n self.name = \"local\"\n self.chart_name += \"_\" + self.name\n data = self._get_data()\n if data is None:\n return False\n\n return True","def nltk_dataset_resource_exists(self, name):\n\n try:\n if (name + \".zip\") in listdir(nltk.data.find(\"corpora\")):\n return True\n except:\n warning(\"Unable to probe nltk corpora at path {}\".format(nltk.data.path))\n return False","def check_Data(self):\r\n \r\n if self._target_data is None:\r\n self.processData()","def validate_dataset(self, path: str = None) -> bool:\n checked = {} # type: Dict[str, Any]\n # Check path exists\n path = path if path is not None else self.path\n if not os.path.exists(path):\n raise ValueError('The path to the dataset does not exists! ({:s})'.format(path))\n # Check readme\n checked['readme'] = os.path.exists(os.path.join(path, 'Readme.md'))\n # Check the different file formats\n file_formats = {\n 'simple-zip': 'single_oscillation_{:04d}.zip',\n 'advanced-gz': 'single_oscillation_0-2_{:04d}.gz',\n 'big2-gz': 'single_oscillation_01-2_{:04d}.gz',\n }\n for file_key, file_format in file_formats.items():\n file_count = 0\n while os.path.exists(os.path.join(path, file_format.format(file_count))):\n file_count += 1\n checked[file_key] = file_count\n # Test for valid dataset\n if checked['readme'] and checked['simple-zip'] == 64:\n self.dataset = 'simple'\n self._file_format = 'single_oscillation_{:04d}.zip'\n self._max_file_count = 64\n return True\n elif checked['advanced-gz'] == 1024:\n self.dataset = 'big'\n self._file_format = 'single_oscillation_0-2_{:04d}.gz'\n self._max_file_count = 1024\n return True\n elif checked['big2-gz'] == 1024:\n self.dataset = 'big2'\n self._file_format = 'single_oscillation_01-2_{:04d}.gz'\n self._max_file_count = 1024\n return True\n return False","def is_available(self):\n raise NotImplementedError","def _check_availability(self, names: Iterable) -> None:\n unavailable = [x for x in names if x not in self.__by_name.keys()]\n if unavailable:\n raise ValueError(f'datasets: {unavailable} not available in the {self.region} region.')","def test_no_updated_datasets(self):\n response = self.client.get(self.get_url(self.study.pk))\n context = response.context\n table = context['source_dataset_table']\n for dataset in self.datasets_v3:\n self.assertNotIn(dataset, table.data)","def has_data(self):\n return self._data is not None","def _check_data_valid(self):\n\n is_valid = (sum(~np.isnan(self.data).flatten()) > 0 and self.data.flatten().sum() != 0)\n if not is_valid:\n raise FITSException(f\"No data in {self.survey}\")","def wait_until_dataset_version_ready(self, version_id):\n ready = False\n attempt = 0\n\n while not ready:\n Mixpanel.LOGGER.debug('Waiting...')\n time.sleep(60)\n version = self.list_dataset_version(version_id)\n attempt = attempt + 1\n if 'state' in version:\n ready = version['state']['ready']\n Mixpanel.LOGGER.debug('Attempt #' + str(attempt) + ': ready = ' + str(ready))\n else:\n Mixpanel.LOGGER.warning('Failed to get dataset version object for version_id ' + str(\n version_id) + 'of dataset ' + self.dataset_id)\n return False\n\n return True","def isDataSourceReadable(self):\r\n\r\n readable = True\r\n start, stop = self.getReadParameters(\\\r\n numpy.array(0, dtype=numpy.int64), self.chunk_size)\r\n try:\r\n self.data_source.read(start, stop)\r\n except tables.HDF5ExtError:\r\n readable = False\r\n print(translate('Buffer',\r\n \"\"\"\\nError: problems reading records. The dataset seems \"\"\"\r\n \"\"\"to be compressed with the {0} library. Check that it \"\"\"\r\n \"\"\"is installed in your system, please.\"\"\",\r\n 'A dataset readability error').\\\r\n format(self.data_source.filters.complib))\r\n\r\n return readable","def is_available(self) -> bool:\n raise NotImplementedError() # pragma: nocover","def downloaded(self) -> bool:\n return not (self.data is None)","def has_data(self) -> bool:\n return bool(self.data)","def has_data(self):\n\n return self._data is not None","def has_data(self):\n\n return self._data is not None","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_name_path):\n raise RuntimeError(\"'{}' is not available\".format(self.train_name_path))\n if not osp.exists(self.test_name_path):\n raise RuntimeError(\"'{}' is not available\".format(self.test_name_path))\n if not osp.exists(self.track_train_info_path):\n raise RuntimeError(\"'{}' is not available\".format(self.track_train_info_path))\n if not osp.exists(self.track_test_info_path):\n raise RuntimeError(\"'{}' is not available\".format(self.track_test_info_path))\n if not osp.exists(self.query_IDX_path):\n raise RuntimeError(\"'{}' is not available\".format(self.query_IDX_path))","def available(self) -> bool:\n if self._coordinator and not self._coordinator.last_update_success:\n return False\n return self.rest.data is not None","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.probe_gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.probe_gallery_dir))","def has(self, id_):\n with self._db_connection() as connection:\n return connection.contains_dataset(id_)","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def _check_before_run(self):\n if not osp.exists(self.dataset_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.dataset_dir))\n if not osp.exists(self.train_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.train_dir))\n if not osp.exists(self.query_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.query_dir))\n if not osp.exists(self.gallery_dir):\n raise RuntimeError(\"'{}' is not available\".format(self.gallery_dir))","def state_data_available(self):\n _LOGGER.debug(\"State data available for device %s\", self._serial)\n self._state_data_available.put_nowait(True)","def _verify(self) -> None:\n # Check if the extracted files already exist\n pathname = os.path.join(self.root, self.data_dir)\n if os.path.exists(pathname):\n return\n\n # Check if the zip files have already been downloaded\n pathname = os.path.join(self.root, self.data_dir) + \".zip\"\n if os.path.exists(pathname):\n self._extract()\n return\n\n # Check if the user requested to download the dataset\n if not self.download:\n raise RuntimeError(\n f\"Dataset not found in `root={self.root}` and `download=False`, \"\n \"either specify a different `root` directory or use `download=True` \"\n \"to automatically download the dataset.\"\n )\n\n # Download the dataset\n self._download()\n self._extract()","def _warn_for_missing_datasets(self, datasets: set[str]):\n any_missing = False\n for ds in datasets:\n if not self.frames.has_dataset(ds):\n any_missing = True\n logger.warn(f'dataset \"{ds}\" is not in the database')\n if any_missing:\n logger.warn(f\"datasets in the databse: {self.all_datasets()}\")","def available(self) -> bool:\n is_avail = True\n if self.entity_description.available_fn is not None:\n is_avail = self.entity_description.available_fn(self._wrap_device)\n return self._api.available and is_avail","def is_version_data_existed(self):\n # if exists, skip\n # return \n\n return True","def storage_available(self):\n logger.debug('Function storage_available start')\n \n # 2.9 GB\n max_size = 2.9*10**9\n \n if self.total_image_data_size >= max_size:\n logger.info(\"Storage not available\")\n return False\n else:\n logger.info(\"Storage available\")\n return True\n\n logger.debug('Function storage_available end')","def checkIfThereIsData(self, i):\n _, amountOfThings = self.weaviate.Get(\"/\" + i)\n if len(amountOfThings[i]) == 0:\n return False\n else:\n return True","def requiresData():\n return True","def _check_for_input_data(self):\n wrapper = BigQueryWrapper()\n try:\n wrapper.get_table(self.project_id, self.input_dataset, self.input_table)\n except HttpError as exn:\n if exn.status_code == 404:\n self._create_input_data()","def is_dataset(X, require_attrs=None):\n\n if require_attrs is None:\n require_attrs = [\"data_vars\", \"coords\", \"dims\", \"to_array\"]\n\n return all([hasattr(X, name) for name in require_attrs])","def is_available(self, cmd):\n num_qubits = 0\n for qureg in cmd.all_qubits:\n num_qubits += len(qureg)\n return num_qubits <= 2","def is_dataset_created(path, suffix=\"\"):\n dataset_id = None\n try:\n with open(\"%s%sdataset%s\" % (path, os.sep, suffix)) as dataset_file:\n dataset_id = dataset_file.readline().strip()\n try:\n dataset_id = bigml.api.get_dataset_id(dataset_id)\n return True, dataset_id\n except ValueError:\n return False, None\n except IOError:\n return False, None","def _IsReady(self):\n if self.ip_address is None:\n self._GetIpAddress()\n if self.ip_address is not None:\n url = 'http://%s' % (self.ip_address)\n r = requests.get(url)\n if r.status_code == 200:\n return True\n return False","def is_ready(self):\n try:\n self._data\n except ValidationError as ve:\n log.error(f\"{self.endpoint} relation data not yet valid. ({ve}\")\n return False\n if self._data is None:\n log.error(f\"{self.endpoint} relation data not yet available.\")\n return False\n return all(\n field is not None\n for field in [\n self._data.auth_url,\n self._data.username,\n self._data.password,\n self._data.user_domain_name,\n self._data.project_domain_name,\n self._data.project_name,\n ]\n )","def check_existing_dataset(path: str):\n x_path = os.path.join(path, IMG_DIR)\n y_path = os.path.join(path, MSK_DIR)\n\n if os.path.isdir(x_path) and os.path.isdir(y_path):\n _, _, x_files = next(os.walk(x_path))\n _, _, y_files = next(os.walk(y_path))\n x = len(x_files)\n y = len(y_files)\n\n if x != y:\n logger.warning(\n \"Found un-even numbers of x-y for dataset. x = %i, y = %i.\", x, y\n )\n\n return -1\n\n if x == 0:\n logger.info(\"Found 0 existing sets.\")\n\n return 0\n logger.info(\"Found %s sets in existing dataset.\", x)\n\n return x\n logger.error(\"Could not locate x and y folder.\")\n sys.exit()"],"string":"[\n \"def data_available(dataset_name=None):\\r\\n for file_list in data_resources[dataset_name]['files']:\\r\\n for file in file_list:\\r\\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\\r\\n return False\\r\\n return True\",\n \"def check_dataset_exists(dataset):\\n result = subprocess.call(['das_client.py', '--query', 'dataset dataset=%s' % dataset])\\n return result == 0\",\n \"def DataAvailable(self) -> bool:\",\n \"def get_is_data_available(self):\\n return self._data_available\",\n \"def check_for_data():\\n if not (os.path.exists(ep.get_test_data_path()) or os.path.exists(ep.get_dbn_weight_path())):\\n return False\\n return True\",\n \"def is_dataset(self):\\n return self._dataset is not None\",\n \"def dataset_exists(es_url, id, es_index=\\\"grq\\\"):\\n\\n total, id = check_dataset(es_url, id, es_index)\\n if total > 0:\\n return True\\n return False\",\n \"def exists_dataset(self, dataset):\\n assert dataset, \\\"Must input a valid dataset name.\\\"\\n return any(self.get_by_dataset(dataset))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\",\n \"def dataset_exists(dataset_reference, client):\\n from google.cloud.exceptions import NotFound\\n\\n try:\\n client.get_dataset(dataset_reference)\\n return True\\n except NotFound:\\n return False\",\n \"def has_datamask(self):\\n return self.datamask is not None\",\n \"def data_loaded_check(self):\\n return True\",\n \"def is_empty(self):\\n for key, dataset in self.datasets.items():\\n try:\\n has_data = dataset.has_data()\\n except MFDataException as mfde:\\n raise MFDataException(\\n mfdata_except=mfde,\\n model=self._container_package.model_name,\\n package=self._container_package._get_pname(),\\n message=\\\"Error occurred while verifying\\\"\\n ' data of dataset \\\"{}\\\" in block '\\n '\\\"{}\\\"'.format(dataset.structure.name, self.structure.name),\\n )\\n\\n if has_data is not None and has_data:\\n return False\\n return True\",\n \"def data_ready(self) -> bool:\\n data_ready = ctypes.c_uint8()\\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_GetMeasurementDataReady(self.dev, byref(data_ready)))\\n return data_ready.value != 0\",\n \"def _check_before_run(self):\\r\\n if not os.path.exists(self.dataset_dir):\\r\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\",\n \"def available(self) -> bool:\\n return super().available and bool(self.data)\",\n \"def _DatasetExists(dataset_id, project_id):\\n client = GetApiClient()\\n service = client.datasets\\n get_request_type = GetApiMessage('BigqueryDatasetsGetRequest')\\n get_request = get_request_type(datasetId=dataset_id, projectId=project_id)\\n try:\\n service.Get(get_request)\\n return True\\n except apitools_exceptions.HttpNotFoundError:\\n log.info('Dataset with id [{}:{}] not found.'.format(\\n project_id, dataset_id))\\n\\n return False\",\n \"def available(self):\\n #return not self.anonymous and len(self._data())\\n return True\",\n \"def _loaded_data(self):\\n try:\\n dsize = [int(d) for d\\n in self.run('fits size', via='get').split()]\\n except (ValueError, TypeError, AttributeError) as err:\\n log.debug(f' FITS size error: {err}')\\n return False\\n else:\\n if 0 in dsize:\\n return False\\n else:\\n return True\",\n \"def has_data(self):\\n return len(self.data) > 0\",\n \"def check_dataset(self):\\n url = self.metadata.metadata_url\\n document = Document.objects.get(\\n metadata=self.metadata,\\n document_type=DocumentEnum.METADATA.value,\\n is_original=True,\\n )\\n original_document = document.content\\n self.check_document(url, original_document)\",\n \"def available(self) -> bool:\\n return (\\n super().available\\n and self.coordinator.data is not None\\n and self.module_id in self.coordinator.data\\n and self.data_id in self.coordinator.data[self.module_id]\\n )\",\n \"def check_availability(self):\\n pass\",\n \"def exists(self, name):\\n assert name, \\\"Must input a valid dataset name.\\\"\\n return name in self.manager.data[\\\"dataset\\\"]\",\n \"def available(self):\\n\\t\\t\\treturn False\",\n \"def available(self):\\n\\t\\t\\treturn False\",\n \"def available(self):\\n\\t\\t\\treturn False\",\n \"def validate_dataset(self):\\n pass\",\n \"def is_valid(self, dataset):\\n pass\",\n \"def check_data(dataframe):\\n if dataframe.iloc[0, 0] == 'No data available':\\n return False\\n else:\\n return True\",\n \"def available(self) -> bool:\\n raise NotImplementedError\",\n \"def _exists(self) -> bool:\\n client = MlflowClient()\\n all_metrics = client._tracking_client.store.get_all_metrics(\\n run_uuid=self.run_id\\n )\\n return any(self._is_dataset_metric(x) for x in all_metrics)\",\n \"def is_available():\",\n \"def has_data(self) -> bool:\\n raise NotImplementedError\",\n \"def _check_before_run(self):\\r\\n if not osp.exists(self.dataset_dir):\\r\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\r\\n if not osp.exists(self.train_dir):\\r\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\",\n \"def available(self) -> bool:\\n return True\",\n \"def available(self) -> bool:\\n return True\",\n \"def CheckForExistence(requested_data, available_data):\\n if requested_data is not None:\\n return 1 # The requested data exists.\\n elif available_data:\\n return -1 # The requested data does not exist.\\n else:\\n return 0 # No data exists at all.\",\n \"def available(self) -> bool:\\n return super().available and (\\n self.coordinator.data.get(self.entity_description.key) is not None\\n )\",\n \"def data_available(self):\\n return (self.status & 0x08) != 0\",\n \"def exists(dtype, name, rootdir=None):\\n return FreezableAPI.to_slug(dtype,name) in FreezableAPI.datasets(rootdir=rootdir)\",\n \"def is_available() -> bool:\\n # This function never throws and returns 0 if driver is missing or can't\\n # be initialized\\n return device_count() > 0\",\n \"def is_available(**kwargs: Any) -> bool:\\n try:\\n _check_available()\\n except Unavailable as e:\\n logger.info('Database not available: %s', e)\\n return False\\n return True\",\n \"def available(self):\\n\\t\\t\\treturn True\",\n \"def available(self):\\n\\t\\t\\treturn True\",\n \"def available(self):\\n\\t\\t\\treturn True\",\n \"def available(self):\\n return True\",\n \"def available(self):\\n return True\",\n \"def data_ready(self):\\n data_ready = len(self.barcode) > 0\\n data_ready &= self.price > 0\\n data_ready &= len(self.description) > 0\\n return data_ready\",\n \"def load_dataset(self) -> bool:\\n\\n if self.write_path is None:\\n raise Exception(\\\"Error: Attempted to load results dataset without ever specifiying a path to write it to\\\")\\n\\n try:\\n if self.format == \\\"arrow\\\":\\n self.res_dataset = Dataset.load_from_disk(self.write_path)\\n elif self.format == \\\"csv\\\":\\n self.res_dataset = pd.read_csv(self.write_path)\\n return True\\n except:\\n return False\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.data_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.data_dir))\\n if not osp.exists(self.split_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.split_dir))\",\n \"def wait_for_data_ready(self):\\n Utils.check(VL53L1X_C_LIBRARY.VL53L1_WaitMeasurementDataReady(self.dev))\",\n \"def is_available(self) -> bool:\\n raise NotImplementedError\",\n \"def ensure_dataset_loaded(self, name):\\n if name not in self.datasets:\\n print(f'Loading dataset \\\"{name}\\\"')\\n pd_data = pd.read_excel(self.datafiles[name])\\n data = pd.DataFrame.to_dict(pd_data, 'records')\\n self.datasets[name] = data\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.test_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.test_dir))\",\n \"def has_data(self):\\n if len(self.channels) > 0:\\n return True\\n return False\",\n \"def has_data(self, *args, **kwargs):\\n return False\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.list_query_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.list_query_path))\\n if not osp.exists(self.list_gallery_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.list_gallery_path))\",\n \"def check(self):\\n self._parse_config()\\n if self.name == \\\"\\\":\\n self.name = \\\"local\\\"\\n self.chart_name += \\\"_\\\" + self.name\\n data = self._get_data()\\n if data is None:\\n return False\\n\\n return True\",\n \"def nltk_dataset_resource_exists(self, name):\\n\\n try:\\n if (name + \\\".zip\\\") in listdir(nltk.data.find(\\\"corpora\\\")):\\n return True\\n except:\\n warning(\\\"Unable to probe nltk corpora at path {}\\\".format(nltk.data.path))\\n return False\",\n \"def check_Data(self):\\r\\n \\r\\n if self._target_data is None:\\r\\n self.processData()\",\n \"def validate_dataset(self, path: str = None) -> bool:\\n checked = {} # type: Dict[str, Any]\\n # Check path exists\\n path = path if path is not None else self.path\\n if not os.path.exists(path):\\n raise ValueError('The path to the dataset does not exists! ({:s})'.format(path))\\n # Check readme\\n checked['readme'] = os.path.exists(os.path.join(path, 'Readme.md'))\\n # Check the different file formats\\n file_formats = {\\n 'simple-zip': 'single_oscillation_{:04d}.zip',\\n 'advanced-gz': 'single_oscillation_0-2_{:04d}.gz',\\n 'big2-gz': 'single_oscillation_01-2_{:04d}.gz',\\n }\\n for file_key, file_format in file_formats.items():\\n file_count = 0\\n while os.path.exists(os.path.join(path, file_format.format(file_count))):\\n file_count += 1\\n checked[file_key] = file_count\\n # Test for valid dataset\\n if checked['readme'] and checked['simple-zip'] == 64:\\n self.dataset = 'simple'\\n self._file_format = 'single_oscillation_{:04d}.zip'\\n self._max_file_count = 64\\n return True\\n elif checked['advanced-gz'] == 1024:\\n self.dataset = 'big'\\n self._file_format = 'single_oscillation_0-2_{:04d}.gz'\\n self._max_file_count = 1024\\n return True\\n elif checked['big2-gz'] == 1024:\\n self.dataset = 'big2'\\n self._file_format = 'single_oscillation_01-2_{:04d}.gz'\\n self._max_file_count = 1024\\n return True\\n return False\",\n \"def is_available(self):\\n raise NotImplementedError\",\n \"def _check_availability(self, names: Iterable) -> None:\\n unavailable = [x for x in names if x not in self.__by_name.keys()]\\n if unavailable:\\n raise ValueError(f'datasets: {unavailable} not available in the {self.region} region.')\",\n \"def test_no_updated_datasets(self):\\n response = self.client.get(self.get_url(self.study.pk))\\n context = response.context\\n table = context['source_dataset_table']\\n for dataset in self.datasets_v3:\\n self.assertNotIn(dataset, table.data)\",\n \"def has_data(self):\\n return self._data is not None\",\n \"def _check_data_valid(self):\\n\\n is_valid = (sum(~np.isnan(self.data).flatten()) > 0 and self.data.flatten().sum() != 0)\\n if not is_valid:\\n raise FITSException(f\\\"No data in {self.survey}\\\")\",\n \"def wait_until_dataset_version_ready(self, version_id):\\n ready = False\\n attempt = 0\\n\\n while not ready:\\n Mixpanel.LOGGER.debug('Waiting...')\\n time.sleep(60)\\n version = self.list_dataset_version(version_id)\\n attempt = attempt + 1\\n if 'state' in version:\\n ready = version['state']['ready']\\n Mixpanel.LOGGER.debug('Attempt #' + str(attempt) + ': ready = ' + str(ready))\\n else:\\n Mixpanel.LOGGER.warning('Failed to get dataset version object for version_id ' + str(\\n version_id) + 'of dataset ' + self.dataset_id)\\n return False\\n\\n return True\",\n \"def isDataSourceReadable(self):\\r\\n\\r\\n readable = True\\r\\n start, stop = self.getReadParameters(\\\\\\r\\n numpy.array(0, dtype=numpy.int64), self.chunk_size)\\r\\n try:\\r\\n self.data_source.read(start, stop)\\r\\n except tables.HDF5ExtError:\\r\\n readable = False\\r\\n print(translate('Buffer',\\r\\n \\\"\\\"\\\"\\\\nError: problems reading records. The dataset seems \\\"\\\"\\\"\\r\\n \\\"\\\"\\\"to be compressed with the {0} library. Check that it \\\"\\\"\\\"\\r\\n \\\"\\\"\\\"is installed in your system, please.\\\"\\\"\\\",\\r\\n 'A dataset readability error').\\\\\\r\\n format(self.data_source.filters.complib))\\r\\n\\r\\n return readable\",\n \"def is_available(self) -> bool:\\n raise NotImplementedError() # pragma: nocover\",\n \"def downloaded(self) -> bool:\\n return not (self.data is None)\",\n \"def has_data(self) -> bool:\\n return bool(self.data)\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def has_data(self):\\n\\n return self._data is not None\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_name_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_name_path))\\n if not osp.exists(self.test_name_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.test_name_path))\\n if not osp.exists(self.track_train_info_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.track_train_info_path))\\n if not osp.exists(self.track_test_info_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.track_test_info_path))\\n if not osp.exists(self.query_IDX_path):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_IDX_path))\",\n \"def available(self) -> bool:\\n if self._coordinator and not self._coordinator.last_update_success:\\n return False\\n return self.rest.data is not None\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.probe_gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.probe_gallery_dir))\",\n \"def has(self, id_):\\n with self._db_connection() as connection:\\n return connection.contains_dataset(id_)\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def _check_before_run(self):\\n if not osp.exists(self.dataset_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.dataset_dir))\\n if not osp.exists(self.train_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.train_dir))\\n if not osp.exists(self.query_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.query_dir))\\n if not osp.exists(self.gallery_dir):\\n raise RuntimeError(\\\"'{}' is not available\\\".format(self.gallery_dir))\",\n \"def state_data_available(self):\\n _LOGGER.debug(\\\"State data available for device %s\\\", self._serial)\\n self._state_data_available.put_nowait(True)\",\n \"def _verify(self) -> None:\\n # Check if the extracted files already exist\\n pathname = os.path.join(self.root, self.data_dir)\\n if os.path.exists(pathname):\\n return\\n\\n # Check if the zip files have already been downloaded\\n pathname = os.path.join(self.root, self.data_dir) + \\\".zip\\\"\\n if os.path.exists(pathname):\\n self._extract()\\n return\\n\\n # Check if the user requested to download the dataset\\n if not self.download:\\n raise RuntimeError(\\n f\\\"Dataset not found in `root={self.root}` and `download=False`, \\\"\\n \\\"either specify a different `root` directory or use `download=True` \\\"\\n \\\"to automatically download the dataset.\\\"\\n )\\n\\n # Download the dataset\\n self._download()\\n self._extract()\",\n \"def _warn_for_missing_datasets(self, datasets: set[str]):\\n any_missing = False\\n for ds in datasets:\\n if not self.frames.has_dataset(ds):\\n any_missing = True\\n logger.warn(f'dataset \\\"{ds}\\\" is not in the database')\\n if any_missing:\\n logger.warn(f\\\"datasets in the databse: {self.all_datasets()}\\\")\",\n \"def available(self) -> bool:\\n is_avail = True\\n if self.entity_description.available_fn is not None:\\n is_avail = self.entity_description.available_fn(self._wrap_device)\\n return self._api.available and is_avail\",\n \"def is_version_data_existed(self):\\n # if exists, skip\\n # return \\n\\n return True\",\n \"def storage_available(self):\\n logger.debug('Function storage_available start')\\n \\n # 2.9 GB\\n max_size = 2.9*10**9\\n \\n if self.total_image_data_size >= max_size:\\n logger.info(\\\"Storage not available\\\")\\n return False\\n else:\\n logger.info(\\\"Storage available\\\")\\n return True\\n\\n logger.debug('Function storage_available end')\",\n \"def checkIfThereIsData(self, i):\\n _, amountOfThings = self.weaviate.Get(\\\"/\\\" + i)\\n if len(amountOfThings[i]) == 0:\\n return False\\n else:\\n return True\",\n \"def requiresData():\\n return True\",\n \"def _check_for_input_data(self):\\n wrapper = BigQueryWrapper()\\n try:\\n wrapper.get_table(self.project_id, self.input_dataset, self.input_table)\\n except HttpError as exn:\\n if exn.status_code == 404:\\n self._create_input_data()\",\n \"def is_dataset(X, require_attrs=None):\\n\\n if require_attrs is None:\\n require_attrs = [\\\"data_vars\\\", \\\"coords\\\", \\\"dims\\\", \\\"to_array\\\"]\\n\\n return all([hasattr(X, name) for name in require_attrs])\",\n \"def is_available(self, cmd):\\n num_qubits = 0\\n for qureg in cmd.all_qubits:\\n num_qubits += len(qureg)\\n return num_qubits <= 2\",\n \"def is_dataset_created(path, suffix=\\\"\\\"):\\n dataset_id = None\\n try:\\n with open(\\\"%s%sdataset%s\\\" % (path, os.sep, suffix)) as dataset_file:\\n dataset_id = dataset_file.readline().strip()\\n try:\\n dataset_id = bigml.api.get_dataset_id(dataset_id)\\n return True, dataset_id\\n except ValueError:\\n return False, None\\n except IOError:\\n return False, None\",\n \"def _IsReady(self):\\n if self.ip_address is None:\\n self._GetIpAddress()\\n if self.ip_address is not None:\\n url = 'http://%s' % (self.ip_address)\\n r = requests.get(url)\\n if r.status_code == 200:\\n return True\\n return False\",\n \"def is_ready(self):\\n try:\\n self._data\\n except ValidationError as ve:\\n log.error(f\\\"{self.endpoint} relation data not yet valid. ({ve}\\\")\\n return False\\n if self._data is None:\\n log.error(f\\\"{self.endpoint} relation data not yet available.\\\")\\n return False\\n return all(\\n field is not None\\n for field in [\\n self._data.auth_url,\\n self._data.username,\\n self._data.password,\\n self._data.user_domain_name,\\n self._data.project_domain_name,\\n self._data.project_name,\\n ]\\n )\",\n \"def check_existing_dataset(path: str):\\n x_path = os.path.join(path, IMG_DIR)\\n y_path = os.path.join(path, MSK_DIR)\\n\\n if os.path.isdir(x_path) and os.path.isdir(y_path):\\n _, _, x_files = next(os.walk(x_path))\\n _, _, y_files = next(os.walk(y_path))\\n x = len(x_files)\\n y = len(y_files)\\n\\n if x != y:\\n logger.warning(\\n \\\"Found un-even numbers of x-y for dataset. x = %i, y = %i.\\\", x, y\\n )\\n\\n return -1\\n\\n if x == 0:\\n logger.info(\\\"Found 0 existing sets.\\\")\\n\\n return 0\\n logger.info(\\\"Found %s sets in existing dataset.\\\", x)\\n\\n return x\\n logger.error(\\\"Could not locate x and y folder.\\\")\\n sys.exit()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7826292","0.7441684","0.72973037","0.7230916","0.7226951","0.70393974","0.7030351","0.70008165","0.6950723","0.6928618","0.6912717","0.69047856","0.683975","0.6828007","0.67924714","0.667985","0.6654125","0.6600955","0.6577739","0.6553427","0.6533301","0.65295076","0.64898944","0.6486349","0.6481533","0.6481533","0.6481533","0.6463391","0.6454404","0.6435176","0.64198554","0.6415891","0.6414071","0.6413826","0.6401759","0.638504","0.638504","0.63720256","0.6364796","0.63308376","0.6321156","0.630879","0.63072073","0.6302297","0.6302297","0.6302297","0.6300031","0.6300031","0.6284197","0.6280347","0.62741244","0.62659353","0.6263866","0.62574404","0.6252234","0.6247585","0.6233882","0.6183179","0.6163347","0.61514914","0.61492413","0.613164","0.6131079","0.61096907","0.60986644","0.60906905","0.6083831","0.6080587","0.6077791","0.6073253","0.607311","0.60526687","0.6048941","0.6048941","0.604608","0.6046034","0.60371405","0.60280496","0.60235983","0.60235983","0.60235983","0.60235983","0.60235983","0.60235983","0.60235983","0.6006697","0.60021555","0.5999896","0.5977669","0.59706074","0.59575206","0.5955495","0.5955331","0.59350806","0.5934438","0.5914415","0.59116656","0.5908889","0.58976376","0.5886445"],"string":"[\n \"0.7826292\",\n \"0.7441684\",\n \"0.72973037\",\n \"0.7230916\",\n \"0.7226951\",\n \"0.70393974\",\n \"0.7030351\",\n \"0.70008165\",\n \"0.6950723\",\n \"0.6928618\",\n \"0.6912717\",\n \"0.69047856\",\n \"0.683975\",\n \"0.6828007\",\n \"0.67924714\",\n \"0.667985\",\n \"0.6654125\",\n \"0.6600955\",\n \"0.6577739\",\n \"0.6553427\",\n \"0.6533301\",\n \"0.65295076\",\n \"0.64898944\",\n \"0.6486349\",\n \"0.6481533\",\n \"0.6481533\",\n \"0.6481533\",\n \"0.6463391\",\n \"0.6454404\",\n \"0.6435176\",\n \"0.64198554\",\n \"0.6415891\",\n \"0.6414071\",\n \"0.6413826\",\n \"0.6401759\",\n \"0.638504\",\n \"0.638504\",\n \"0.63720256\",\n \"0.6364796\",\n \"0.63308376\",\n \"0.6321156\",\n \"0.630879\",\n \"0.63072073\",\n \"0.6302297\",\n \"0.6302297\",\n \"0.6302297\",\n \"0.6300031\",\n \"0.6300031\",\n \"0.6284197\",\n \"0.6280347\",\n \"0.62741244\",\n \"0.62659353\",\n \"0.6263866\",\n \"0.62574404\",\n \"0.6252234\",\n \"0.6247585\",\n \"0.6233882\",\n \"0.6183179\",\n \"0.6163347\",\n \"0.61514914\",\n \"0.61492413\",\n \"0.613164\",\n \"0.6131079\",\n \"0.61096907\",\n \"0.60986644\",\n \"0.60906905\",\n \"0.6083831\",\n \"0.6080587\",\n \"0.6077791\",\n \"0.6073253\",\n \"0.607311\",\n \"0.60526687\",\n \"0.6048941\",\n \"0.6048941\",\n \"0.604608\",\n \"0.6046034\",\n \"0.60371405\",\n \"0.60280496\",\n \"0.60235983\",\n \"0.60235983\",\n \"0.60235983\",\n \"0.60235983\",\n \"0.60235983\",\n \"0.60235983\",\n \"0.60235983\",\n \"0.6006697\",\n \"0.60021555\",\n \"0.5999896\",\n \"0.5977669\",\n \"0.59706074\",\n \"0.59575206\",\n \"0.5955495\",\n \"0.5955331\",\n \"0.59350806\",\n \"0.5934438\",\n \"0.5914415\",\n \"0.59116656\",\n \"0.5908889\",\n \"0.58976376\",\n \"0.5886445\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.78361577"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88585,"cells":{"query":{"kind":"string","value":"Get the list of functional units for the experiment."},"document":{"kind":"string","value":"def getFuList(self):\n if self._fupardict:\n return self._fupardict.keys()\n buf = self._parent.Xeprbuf(10000)\n self.aqGetExpFuList(buf, 10000)\n return buf.get_unicode_str().split(',')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_units(self) -> List[str]:\n result = []\n for elements in self._get_results_list():\n result.append(elements[3])\n return result","def getListOfUnits(self, *args):\n return _libsbml.UnitDefinition_getListOfUnits(self, *args)","def client_units(self) -> List[FlyingUnit]:\n return [u for u in self.units if u.is_human()]","def list_data_units(self):\n return self.data_units.items()","def get_units(self, obj: Dimension) -> [Unit]:\n try:\n return obj.units()\n except KeyError as e:\n logging.error(str(e))\n return []","def getUnits(self):\n return _libsbml.Species_getUnits(self)","def get(self, *args):\n return _libsbml.ListOfUnits_get(self, *args)","def units(inventory):\n return inventory.reduce(convert.get_units)","def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetFunnelUnitArgs']]]]:\n return pulumi.get(self, \"units\")","def get_unit_names(status, application_name):\n return [name for name, unit in get_units(status, application_name)]","def enumerateUnits(self):\n return self._lowLevelEnumerateUnits()","async def get_all_units():\n all_devices = []\n if network is None:\n import netifaces\n\n gateway = netifaces.gateways().get(\"default\", {})\n subnet = gateway.get(netifaces.AF_INET, ())[0][:-1] + \"0/24\"\n else:\n subnet = network\n async with gdh_session() as session:\n googledevices = NetworkScan(loop, session)\n result = await googledevices.scan_for_units(subnet)\n if feature:\n for unit in result:\n if unit[feature]:\n all_devices.append(unit)\n else:\n all_devices = result\n print(format_json(all_devices))","async def get_all_units():\n all_devices = []\n if network is None:\n import netifaces\n\n gateway = netifaces.gateways().get(\"default\", {})\n subnet = gateway.get(netifaces.AF_INET, ())[0][:-1] + \"0/24\"\n else:\n subnet = network\n async with gdh_session() as session:\n googledevices = NetworkScan(loop, session)\n result = await googledevices.scan_for_units(subnet)\n if feature:\n for unit in result:\n if unit[feature]:\n all_devices.append(unit)\n else:\n all_devices = result\n print(format_json(all_devices))","def get_units(status, application_name):\n units = []\n for unit_name, unit in iter_units(status):\n if unit_name.startswith('{}/'.format(application_name)):\n units.append((unit_name, unit,))\n return units","def get_functions(self):\n\n functions = []\n for scenario in self.scenarios:\n functions.extend(scenario.functions)\n\n return functions","def get_units(**kwargs):\n\n instance = Ceic._get_instance()\n\n get_dictionaries_method = instance._dictionary_facade.get_units\n result = instance._make_request(get_dictionaries_method, **kwargs)\n\n return result","def get(self, *args):\n return _libsbml.ListOfUnitDefinitions_get(self, *args)","def get_units(self):\n return str(self._modeler.GetModelUnits())","def unit_system(self):\n val = self._stub.List(self._message).unit_system\n return map_unit_system[val]","def units(self):\n return self._units","def units(self):\n return self._units","def get_alive_units(self):\n alive_units = []\n for unit in self.units:\n if not unit.is_alive():\n continue\n alive_units.append(unit)\n return alive_units","def getListOfUnitDefinitions(self, *args):\n return _libsbml.Model_getListOfUnitDefinitions(self, *args)","def getUnits(self):\n return _libsbml.Parameter_getUnits(self)","def enumerate_units():\n count = c_int16()\n size = c_int16(1023)\n serials = (c_int8 * size.value)()\n libtype = 'windll' if IS_WINDOWS else 'cdll'\n sdk = LoadLibrary('ps5000a', libtype)\n result = sdk.lib.ps5000aEnumerateUnits(byref(count), byref(serials), byref(size))\n if result != PICO_OK:\n if result == PICO_NOT_FOUND:\n err_name, err_msg = 'PICO_NOT_FOUND', 'Are you sure that a PicoScope is connected to the computer?'\n else:\n err_name, err_msg = ERROR_CODES_API.get(result, ('UnhandledError', 'Error code 0x{:x}'.format(result)))\n raise PicoTechError('Cannot enumerate units.\\n{}: {}'.format(err_name, err_msg))\n return string_at(addressof(serials)).decode('utf-8').split(',')","def list_power_supply_units(self):\n\n doc = self.client.enumerate(uris.CIM_PowerSupply)\n\n psus = doc.find('.//s:Body/wsen:EnumerateResponse/wsman:Items',\n wsman.NS_MAP)\n\n return [self._parse_psus(psu) for psu in psus]","def getUnits(self):\n return _libsbml.Compartment_getUnits(self)","def unit_classes(self):\n return self._unit_classes","def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetPyUnitArgs']]]]:\n return pulumi.get(self, \"units\")","def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetTableUnitArgs']]]]:\n return pulumi.get(self, \"units\")","def get_active_units(self):\n alive_units = self.get_alive_units()\n active_units = []\n for alive_unit in alive_units:\n if not alive_unit.ready_to_attack():\n continue\n active_units.append(alive_unit)\n return active_units","def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetHeatmapUnitArgs']]]]:\n return pulumi.get(self, \"units\")","def test_get_var_units(flopy_dis_mf6):\n mf6 = flopy_dis_mf6[1]\n mf6.initialize()\n\n with pytest.raises(NotImplementedError):\n mf6.get_var_units(\"\")","def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetLogTableUnitArgs']]]]:\n return pulumi.get(self, \"units\")","def getSubstanceUnits(self):\n return _libsbml.Species_getSubstanceUnits(self)","def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetJsonUnitArgs']]]]:\n return pulumi.get(self, \"units\")","def units(self):\n return self.children()","def buildUnits(self, obs, UnitName, Quantity):\n \n \"\"\"drones, overlords, zerglings, roaches, hydralisks, corrupters, queen(may need own function)\"\"\" \n actions.FUNCTIONS.select_larva(\"select\")\n if (UnitName == \"drone\"):\n if self.can_do(obs, actions.FUNCTIONS.Train_Zergling_quick.id):\n return actions.FUNCTIONS.Train_Drone_quick(\"now\")\n if (UnitName == \"overlord\"):\n if self.can_do(obs, actions.FUNCTIONS.Train_Zergling_quick.id):\n return actions.FUNCTIONS.Train_Overlord_quick(\"now\")\n if (UnitName == \"zergling\"):\n if self.can_do(obs, actions.FUNCTIONS.Train_Zergling_quick.id):\n return actions.FUNCTIONS.Train_Zergling_quick(\"now\")\n if (UnitName == \"Roach\"):\n if self.can_do(obs, actions.FUNCTIONS.Train_Zergling_quick.id):\n return actions.FUNCTIONS.Train_Roach_quick(\"now\")\n if (UnitName == \"hydralisks\"):\n if self.can_do(obs, actions.FUNCTIONS.Train_Zergling_quick.id):\n return actions.FUNCTIONS.Train_Hydralisk_quick(\"now\")\n if (UnitName == \"corruptor\"):\n if self.can_do(obs, actions.FUNCTIONS.Train_Zergling_quick.id):\n return actions.FUNCTIONS.Train_Corruptor_quick(\"now\")\n \"\"\"UnitsForControlGroup: [#drone, #zergling, #roaches, #hydralisks]\"\"\"","def get_list_powers(self):\r\n return self._api.get_list_powers()","def unit_display_names(self) -> localedata.LocaleDataDict:\n return self._data['unit_display_names']","def lutList():\n sessionLuts = nuke.Root()[\"luts\"]\n luts = re.findall('[a-zA-Z0-9.*]+', sessionLuts.toScript())\n return luts","def get_devices(self):\n data = {\n \"device_id\": self.uuid,\n \"cmd\": \"get_account_units\",\n \"account_token\": self.api_token\n }\n headers = {\n \"Content-Type\": \"application/json\"\n }\n\n response = requests.post(\"{}/box_pin\".format(self.BASE_URL),\n data=json.dumps(data),\n headers=headers)\n response_json = response.json()\n if not response_json.get(\"success\"):\n raise ValueError(response_json.get(\"error_message\"))\n\n units_json = response_json.get(\"units\")\n devices = []\n for unit in units_json:\n device = Charger(unit, self)\n device.update_state()\n devices.append(device)\n\n return devices","def heat_exchanger_utilities_from_units(units):\n heat_utilities = sum([i.heat_utilities for i in units], ())\n return [i for i in heat_utilities if i.heat_exchanger]","def list_feature_tests(self):\n\t\treturn self.test_names","def get_units(self, names):\n # Make sure names is a list\n if isinstance(names, str) or isinstance(names, unicode):\n names = [names]\n \n # Return the list of units\n ans = []\n for name in names:\n if name in self.interp_ds:\n ans.append(self.interp_ds[name].attrs['units'])\n else:\n ans.append('Not Available in Dataset')\n \n return ans","def getAllMeasurement(self): \n return self.measurement","def _get_representation_component_units(args, kwargs):\n if \"unit\" not in kwargs:\n units = [None, None, None]\n\n else:\n units = kwargs.pop(\"unit\")\n\n if isinstance(units, str):\n units = [x.strip() for x in units.split(\",\")]\n # Allow for input like unit='deg' or unit='m'\n if len(units) == 1:\n units = [units[0], units[0], units[0]]\n elif isinstance(units, (Unit, IrreducibleUnit)):\n units = [units, units, units]\n\n try:\n units = [(Unit(x) if x else None) for x in units]\n units.extend(None for x in range(3 - len(units)))\n if len(units) > 3:\n raise ValueError()\n except Exception as err:\n raise ValueError(\n \"Unit keyword must have one to three unit values as \"\n \"tuple or comma-separated string.\"\n ) from err\n\n return units","def uw(self):\n return sm.unitvec(self.w)","def populateListFormulaUnitsData(self):\n return _libsbml.Model_populateListFormulaUnitsData(self)","def getUnits(self):\n return _libsbml.ASTNode_getUnits(self)","def get_measures(self) -> List[str]:\n result = []\n for elements in self._get_results_list():\n result.append(elements[2])\n return result","def unitsofmeasure(self):\n return self._unitsofmeasure","def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetBulletUnitArgs']]]]:\n return pulumi.get(self, \"units\")","def get_temperatures(self, units):\n sensor_value = self.get_temperature(self.DEGREES_C)\n return [self._get_unit_factor(unit)(sensor_value) for unit in units]","def get_cpu_units(self):\n\t\treturn call_sdk_function('PrlVmCfg_GetCpuUnits', self.handle)","def unit_of_measurement(self):\n return self._units","def getSubstanceUnits(self):\n return _libsbml.Model_getSubstanceUnits(self)","def _getunits(x):\n if pb.units.has_units(x):\n \n units = x.units\n \n else:\n \n units = None\n \n return units","def get_units(cls, wkt):\n if HAS_GDAL:\n return SpatialReference(wkt).units\n else:\n m = cls.units_regex.match(wkt)\n return m.group('unit'), m.group('unit_name')","def getUnits(self):\n return _libsbml.Rule_getUnits(self)","def units(self):\n return self.__class__.get_setting_units(self.key, **self.get_kwargs())","def getVolumeUnits(self):\n return _libsbml.Model_getVolumeUnits(self)","def get_units(self, variable):\n try:\n units = self.dataset[variable].units\n return units\n except:\n return None","def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetBillboardUnitArgs']]]]:\n return pulumi.get(self, \"units\")","def getListOfSpecies(self):\n return self.model.getListOfSpecies()","def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetLineUnitArgs']]]]:\n return pulumi.get(self, \"units\")","def units(self):\n pass","def get_units(self, output_name: str):\n return self._output_units[output_name]","def subunits(self):\n\n return [get_target_by_id(id_) for id_ in self._subunit_ids]","def unit_array(self):\n return self._data_array.values * units(self._units)","def measurements(self):\n exp_type = 'Q_MS_MEASUREMENT'\n path = \"/%s/%s\" % (space, project)\n search = self.transaction.getSearchService()\n exps = search.listExperiments(path)\n return [exp for exp in exps if exp.getExperimentType() == exp_type]","def _get_units(self):\n #assert self.ser.isOpen()\n\n self.serial_connection.write('UNI' + self.CR + self.LF)\n acknowledgement = self.serial_connection.readline()\n self._check_acknowledgement(acknowledgement)\n\n self.serial_connection.write(self.ENQ)\n unit = self.MEASUREMENT_UNITS[self.serial_connection.readline().rstrip(self.LF).rstrip(self.CR)]\n\n self.serial_connection.write(self.CR + self.LF)\n\n return unit","def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetStackedBarUnitArgs']]]]:\n return pulumi.get(self, \"units\")","def get_list_powers(self):\r\n _debug('simq03b_api.get_list_powers')\r\n \r\n s = self.query('SOUR:LIST:POW?')\r\n if s == None: return None\r\n a = []\r\n n = 0\r\n for x in s.split(','):\r\n try:\r\n a.append(float(x.strip()))\r\n except:\r\n print('ERROR get_list_powers(): non-float in list ', n, x)\r\n n += 1\r\n return a","def get_idle_units(self, n):\n status = self.get_status() \n unitindices = []\n for i in xrange(len(status)):\n if status[i] == 'idle':\n unitindices.append(i)\n if len(unitindices) == n:\n break\n return unitindices","def totalUnits(self):\n\t\treturn self.units","def getUnits(self):\n\n return len(self.units)","def get_names(self):\n\n return self.mod_suites.keys()","def get_all_items(unit) -> list:\n items = []\n for item in unit.items:\n if item.multi_item:\n for subitem in item.subitems:\n items.append(subitem)\n else:\n items.append(item)\n return items","def getElementName(self):\n return _libsbml.ListOfUnits_getElementName(self)","def get_metric_list(self) -> List[str]:\n ...","def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetBarUnitArgs']]]]:\n return pulumi.get(self, \"units\")","def _get_units(self, name):\n meta = self._abs2meta\n\n if name in meta:\n return meta[name]['units']\n\n proms = self._prom2abs\n\n if name in proms['output']:\n abs_name = proms['output'][name][0]\n return meta[abs_name]['units']\n\n elif name in proms['input']:\n if len(proms['input'][name]) > 1:\n # The promoted name maps to multiple absolute names, require absolute name.\n msg = \"Can't get units for the promoted name '%s' because it refers to \" + \\\n \"multiple inputs: %s. Access the units using an absolute path name.\"\n raise RuntimeError(msg % (name, str(proms['input'][name])))\n\n abs_name = proms['input'][name][0]\n return meta[abs_name]['units']\n\n raise KeyError('Variable name \"{}\" not found.'.format(name))","def getAllSpectrumMeasurements(self): \n return self.spectrum","def raw_units(self) -> str:\n if self._node.uom == 'F':\n return TEMP_FAHRENHEIT\n if self._node.uom == 'C':\n return TEMP_CELSIUS\n return self._node.uom","def get_meters(api):\n devices = api.device_list()\n return [Meter(api, device.hardware_address) for device in devices if device.model_id == 'electric_meter']","def getDistanceUnits(self) -> Unit:\n ...","def fluid_func(self):\n residual = []\n for fluid, x in self.inl[0].fluid.val.items():\n res = x * self.inl[0].m.val_SI\n for o in self.outl:\n res -= o.fluid.val[fluid] * o.m.val_SI\n residual += [res]\n return residual","def test_get_bios_unit_list(self):\n pass","def _get_fitness(self, mol):\n\n property_vector = []\n for property_fn in self._property_fns:\n logger.info(\n f'Using {property_fn.__name__} on \"{mol}\".'\n )\n property_vector.append(property_fn(mol))\n return property_vector","def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetAreaUnitArgs']]]]:\n return pulumi.get(self, \"units\")","def time_units(self) -> str:\n return self._ll_tree_sequence.get_time_units()","def getSubstanceUnits(self):\n return _libsbml.KineticLaw_getSubstanceUnits(self)","def _get_units(self, q) -> unyt.Unit:\n try:\n units = q.units\n except AttributeError:\n units = unyt.dimensionless\n return unyt.Unit(units, registry=self.registry)","def fluid_func(self):\n residual = []\n for i in range(self.num_i):\n for fluid, x in self.inl[0].fluid.val.items():\n residual += [x - self.outl[0].fluid.val[fluid]]\n return residual","def GenerateUnitList(self):\n # Verify platform specific terms. Skip whole term if platform does not\n # match.\n if self.term.platform:\n if 'silverpeak' not in self.term.platform:\n return []\n if self.term.platform_exclude:\n if 'silverpeak' in self.term.platform_exclude:\n return []\n\n ret_str = []\n if 'established' in self.term.option:\n dst_ports = ['any']\n else:\n dst_ports = self._NormalizePortRanges(\n self._FixLongList(self.term.destination_port, 10)\n )\n source_all_ipv6, source_address = self._FixIPv6Address(\n self.term.source_address\n )\n if source_all_ipv6:\n return ret_str\n destination_all_ipv6, destination_address = self._FixIPv6Address(\n self.term.destination_address\n )\n if destination_all_ipv6:\n return ret_str\n src_ips = self._NormalizeNetblocks(self._FixLongList(source_address, 50))\n src_ports = self._NormalizePortRanges(\n self._FixLongList(self.term.source_port, 10)\n )\n dst_ips = self._NormalizeNetblocks(\n self._FixLongList(destination_address, 50)\n )\n for src_ip in src_ips:\n for src_port in src_ports:\n for dst_ip in dst_ips:\n for dst_port in dst_ports:\n ret_str.append((src_ip, src_port, dst_ip, dst_port))\n return ret_str","def unit_of_measurement(self):\n return self.var_units","def measurements(self):\n # get available measurement types for this node\n measurement_types = self.measurement_types()\n\n # retrieve measurement for each type\n return list(self.measurement(t) for t in measurement_types)","def get_units(self):\r\n msg = struct.pack('>2B', 56, 14)\r\n response = self.query(msg)\r\n\r\n if response[1] == 2:\r\n units = 'A'\r\n to_nm_multiplier = 1 / 10\r\n elif response[1] == 1:\r\n units = 'nm'\r\n to_nm_multiplier = 1\r\n elif response[1] == 0:\r\n units = 'um'\r\n to_nm_multiplier = 1000\r\n else:\r\n raise ValueError('Units not recognised.')\r\n\r\n # Save results locally too for quick re-use\r\n self._current_units = units\r\n self._current_to_nm_multiplier = to_nm_multiplier\r\n\r\n return units, to_nm_multiplier","def unit_of_measurement(self) -> str:\n raw_units = self.raw_units\n\n if raw_units in [TEMP_CELSIUS, TEMP_FAHRENHEIT]:\n return self.hass.config.units.temperature_unit\n return raw_units"],"string":"[\n \"def get_units(self) -> List[str]:\\n result = []\\n for elements in self._get_results_list():\\n result.append(elements[3])\\n return result\",\n \"def getListOfUnits(self, *args):\\n return _libsbml.UnitDefinition_getListOfUnits(self, *args)\",\n \"def client_units(self) -> List[FlyingUnit]:\\n return [u for u in self.units if u.is_human()]\",\n \"def list_data_units(self):\\n return self.data_units.items()\",\n \"def get_units(self, obj: Dimension) -> [Unit]:\\n try:\\n return obj.units()\\n except KeyError as e:\\n logging.error(str(e))\\n return []\",\n \"def getUnits(self):\\n return _libsbml.Species_getUnits(self)\",\n \"def get(self, *args):\\n return _libsbml.ListOfUnits_get(self, *args)\",\n \"def units(inventory):\\n return inventory.reduce(convert.get_units)\",\n \"def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetFunnelUnitArgs']]]]:\\n return pulumi.get(self, \\\"units\\\")\",\n \"def get_unit_names(status, application_name):\\n return [name for name, unit in get_units(status, application_name)]\",\n \"def enumerateUnits(self):\\n return self._lowLevelEnumerateUnits()\",\n \"async def get_all_units():\\n all_devices = []\\n if network is None:\\n import netifaces\\n\\n gateway = netifaces.gateways().get(\\\"default\\\", {})\\n subnet = gateway.get(netifaces.AF_INET, ())[0][:-1] + \\\"0/24\\\"\\n else:\\n subnet = network\\n async with gdh_session() as session:\\n googledevices = NetworkScan(loop, session)\\n result = await googledevices.scan_for_units(subnet)\\n if feature:\\n for unit in result:\\n if unit[feature]:\\n all_devices.append(unit)\\n else:\\n all_devices = result\\n print(format_json(all_devices))\",\n \"async def get_all_units():\\n all_devices = []\\n if network is None:\\n import netifaces\\n\\n gateway = netifaces.gateways().get(\\\"default\\\", {})\\n subnet = gateway.get(netifaces.AF_INET, ())[0][:-1] + \\\"0/24\\\"\\n else:\\n subnet = network\\n async with gdh_session() as session:\\n googledevices = NetworkScan(loop, session)\\n result = await googledevices.scan_for_units(subnet)\\n if feature:\\n for unit in result:\\n if unit[feature]:\\n all_devices.append(unit)\\n else:\\n all_devices = result\\n print(format_json(all_devices))\",\n \"def get_units(status, application_name):\\n units = []\\n for unit_name, unit in iter_units(status):\\n if unit_name.startswith('{}/'.format(application_name)):\\n units.append((unit_name, unit,))\\n return units\",\n \"def get_functions(self):\\n\\n functions = []\\n for scenario in self.scenarios:\\n functions.extend(scenario.functions)\\n\\n return functions\",\n \"def get_units(**kwargs):\\n\\n instance = Ceic._get_instance()\\n\\n get_dictionaries_method = instance._dictionary_facade.get_units\\n result = instance._make_request(get_dictionaries_method, **kwargs)\\n\\n return result\",\n \"def get(self, *args):\\n return _libsbml.ListOfUnitDefinitions_get(self, *args)\",\n \"def get_units(self):\\n return str(self._modeler.GetModelUnits())\",\n \"def unit_system(self):\\n val = self._stub.List(self._message).unit_system\\n return map_unit_system[val]\",\n \"def units(self):\\n return self._units\",\n \"def units(self):\\n return self._units\",\n \"def get_alive_units(self):\\n alive_units = []\\n for unit in self.units:\\n if not unit.is_alive():\\n continue\\n alive_units.append(unit)\\n return alive_units\",\n \"def getListOfUnitDefinitions(self, *args):\\n return _libsbml.Model_getListOfUnitDefinitions(self, *args)\",\n \"def getUnits(self):\\n return _libsbml.Parameter_getUnits(self)\",\n \"def enumerate_units():\\n count = c_int16()\\n size = c_int16(1023)\\n serials = (c_int8 * size.value)()\\n libtype = 'windll' if IS_WINDOWS else 'cdll'\\n sdk = LoadLibrary('ps5000a', libtype)\\n result = sdk.lib.ps5000aEnumerateUnits(byref(count), byref(serials), byref(size))\\n if result != PICO_OK:\\n if result == PICO_NOT_FOUND:\\n err_name, err_msg = 'PICO_NOT_FOUND', 'Are you sure that a PicoScope is connected to the computer?'\\n else:\\n err_name, err_msg = ERROR_CODES_API.get(result, ('UnhandledError', 'Error code 0x{:x}'.format(result)))\\n raise PicoTechError('Cannot enumerate units.\\\\n{}: {}'.format(err_name, err_msg))\\n return string_at(addressof(serials)).decode('utf-8').split(',')\",\n \"def list_power_supply_units(self):\\n\\n doc = self.client.enumerate(uris.CIM_PowerSupply)\\n\\n psus = doc.find('.//s:Body/wsen:EnumerateResponse/wsman:Items',\\n wsman.NS_MAP)\\n\\n return [self._parse_psus(psu) for psu in psus]\",\n \"def getUnits(self):\\n return _libsbml.Compartment_getUnits(self)\",\n \"def unit_classes(self):\\n return self._unit_classes\",\n \"def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetPyUnitArgs']]]]:\\n return pulumi.get(self, \\\"units\\\")\",\n \"def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetTableUnitArgs']]]]:\\n return pulumi.get(self, \\\"units\\\")\",\n \"def get_active_units(self):\\n alive_units = self.get_alive_units()\\n active_units = []\\n for alive_unit in alive_units:\\n if not alive_unit.ready_to_attack():\\n continue\\n active_units.append(alive_unit)\\n return active_units\",\n \"def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetHeatmapUnitArgs']]]]:\\n return pulumi.get(self, \\\"units\\\")\",\n \"def test_get_var_units(flopy_dis_mf6):\\n mf6 = flopy_dis_mf6[1]\\n mf6.initialize()\\n\\n with pytest.raises(NotImplementedError):\\n mf6.get_var_units(\\\"\\\")\",\n \"def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetLogTableUnitArgs']]]]:\\n return pulumi.get(self, \\\"units\\\")\",\n \"def getSubstanceUnits(self):\\n return _libsbml.Species_getSubstanceUnits(self)\",\n \"def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetJsonUnitArgs']]]]:\\n return pulumi.get(self, \\\"units\\\")\",\n \"def units(self):\\n return self.children()\",\n \"def buildUnits(self, obs, UnitName, Quantity):\\n \\n \\\"\\\"\\\"drones, overlords, zerglings, roaches, hydralisks, corrupters, queen(may need own function)\\\"\\\"\\\" \\n actions.FUNCTIONS.select_larva(\\\"select\\\")\\n if (UnitName == \\\"drone\\\"):\\n if self.can_do(obs, actions.FUNCTIONS.Train_Zergling_quick.id):\\n return actions.FUNCTIONS.Train_Drone_quick(\\\"now\\\")\\n if (UnitName == \\\"overlord\\\"):\\n if self.can_do(obs, actions.FUNCTIONS.Train_Zergling_quick.id):\\n return actions.FUNCTIONS.Train_Overlord_quick(\\\"now\\\")\\n if (UnitName == \\\"zergling\\\"):\\n if self.can_do(obs, actions.FUNCTIONS.Train_Zergling_quick.id):\\n return actions.FUNCTIONS.Train_Zergling_quick(\\\"now\\\")\\n if (UnitName == \\\"Roach\\\"):\\n if self.can_do(obs, actions.FUNCTIONS.Train_Zergling_quick.id):\\n return actions.FUNCTIONS.Train_Roach_quick(\\\"now\\\")\\n if (UnitName == \\\"hydralisks\\\"):\\n if self.can_do(obs, actions.FUNCTIONS.Train_Zergling_quick.id):\\n return actions.FUNCTIONS.Train_Hydralisk_quick(\\\"now\\\")\\n if (UnitName == \\\"corruptor\\\"):\\n if self.can_do(obs, actions.FUNCTIONS.Train_Zergling_quick.id):\\n return actions.FUNCTIONS.Train_Corruptor_quick(\\\"now\\\")\\n \\\"\\\"\\\"UnitsForControlGroup: [#drone, #zergling, #roaches, #hydralisks]\\\"\\\"\\\"\",\n \"def get_list_powers(self):\\r\\n return self._api.get_list_powers()\",\n \"def unit_display_names(self) -> localedata.LocaleDataDict:\\n return self._data['unit_display_names']\",\n \"def lutList():\\n sessionLuts = nuke.Root()[\\\"luts\\\"]\\n luts = re.findall('[a-zA-Z0-9.*]+', sessionLuts.toScript())\\n return luts\",\n \"def get_devices(self):\\n data = {\\n \\\"device_id\\\": self.uuid,\\n \\\"cmd\\\": \\\"get_account_units\\\",\\n \\\"account_token\\\": self.api_token\\n }\\n headers = {\\n \\\"Content-Type\\\": \\\"application/json\\\"\\n }\\n\\n response = requests.post(\\\"{}/box_pin\\\".format(self.BASE_URL),\\n data=json.dumps(data),\\n headers=headers)\\n response_json = response.json()\\n if not response_json.get(\\\"success\\\"):\\n raise ValueError(response_json.get(\\\"error_message\\\"))\\n\\n units_json = response_json.get(\\\"units\\\")\\n devices = []\\n for unit in units_json:\\n device = Charger(unit, self)\\n device.update_state()\\n devices.append(device)\\n\\n return devices\",\n \"def heat_exchanger_utilities_from_units(units):\\n heat_utilities = sum([i.heat_utilities for i in units], ())\\n return [i for i in heat_utilities if i.heat_exchanger]\",\n \"def list_feature_tests(self):\\n\\t\\treturn self.test_names\",\n \"def get_units(self, names):\\n # Make sure names is a list\\n if isinstance(names, str) or isinstance(names, unicode):\\n names = [names]\\n \\n # Return the list of units\\n ans = []\\n for name in names:\\n if name in self.interp_ds:\\n ans.append(self.interp_ds[name].attrs['units'])\\n else:\\n ans.append('Not Available in Dataset')\\n \\n return ans\",\n \"def getAllMeasurement(self): \\n return self.measurement\",\n \"def _get_representation_component_units(args, kwargs):\\n if \\\"unit\\\" not in kwargs:\\n units = [None, None, None]\\n\\n else:\\n units = kwargs.pop(\\\"unit\\\")\\n\\n if isinstance(units, str):\\n units = [x.strip() for x in units.split(\\\",\\\")]\\n # Allow for input like unit='deg' or unit='m'\\n if len(units) == 1:\\n units = [units[0], units[0], units[0]]\\n elif isinstance(units, (Unit, IrreducibleUnit)):\\n units = [units, units, units]\\n\\n try:\\n units = [(Unit(x) if x else None) for x in units]\\n units.extend(None for x in range(3 - len(units)))\\n if len(units) > 3:\\n raise ValueError()\\n except Exception as err:\\n raise ValueError(\\n \\\"Unit keyword must have one to three unit values as \\\"\\n \\\"tuple or comma-separated string.\\\"\\n ) from err\\n\\n return units\",\n \"def uw(self):\\n return sm.unitvec(self.w)\",\n \"def populateListFormulaUnitsData(self):\\n return _libsbml.Model_populateListFormulaUnitsData(self)\",\n \"def getUnits(self):\\n return _libsbml.ASTNode_getUnits(self)\",\n \"def get_measures(self) -> List[str]:\\n result = []\\n for elements in self._get_results_list():\\n result.append(elements[2])\\n return result\",\n \"def unitsofmeasure(self):\\n return self._unitsofmeasure\",\n \"def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetBulletUnitArgs']]]]:\\n return pulumi.get(self, \\\"units\\\")\",\n \"def get_temperatures(self, units):\\n sensor_value = self.get_temperature(self.DEGREES_C)\\n return [self._get_unit_factor(unit)(sensor_value) for unit in units]\",\n \"def get_cpu_units(self):\\n\\t\\treturn call_sdk_function('PrlVmCfg_GetCpuUnits', self.handle)\",\n \"def unit_of_measurement(self):\\n return self._units\",\n \"def getSubstanceUnits(self):\\n return _libsbml.Model_getSubstanceUnits(self)\",\n \"def _getunits(x):\\n if pb.units.has_units(x):\\n \\n units = x.units\\n \\n else:\\n \\n units = None\\n \\n return units\",\n \"def get_units(cls, wkt):\\n if HAS_GDAL:\\n return SpatialReference(wkt).units\\n else:\\n m = cls.units_regex.match(wkt)\\n return m.group('unit'), m.group('unit_name')\",\n \"def getUnits(self):\\n return _libsbml.Rule_getUnits(self)\",\n \"def units(self):\\n return self.__class__.get_setting_units(self.key, **self.get_kwargs())\",\n \"def getVolumeUnits(self):\\n return _libsbml.Model_getVolumeUnits(self)\",\n \"def get_units(self, variable):\\n try:\\n units = self.dataset[variable].units\\n return units\\n except:\\n return None\",\n \"def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetBillboardUnitArgs']]]]:\\n return pulumi.get(self, \\\"units\\\")\",\n \"def getListOfSpecies(self):\\n return self.model.getListOfSpecies()\",\n \"def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetLineUnitArgs']]]]:\\n return pulumi.get(self, \\\"units\\\")\",\n \"def units(self):\\n pass\",\n \"def get_units(self, output_name: str):\\n return self._output_units[output_name]\",\n \"def subunits(self):\\n\\n return [get_target_by_id(id_) for id_ in self._subunit_ids]\",\n \"def unit_array(self):\\n return self._data_array.values * units(self._units)\",\n \"def measurements(self):\\n exp_type = 'Q_MS_MEASUREMENT'\\n path = \\\"/%s/%s\\\" % (space, project)\\n search = self.transaction.getSearchService()\\n exps = search.listExperiments(path)\\n return [exp for exp in exps if exp.getExperimentType() == exp_type]\",\n \"def _get_units(self):\\n #assert self.ser.isOpen()\\n\\n self.serial_connection.write('UNI' + self.CR + self.LF)\\n acknowledgement = self.serial_connection.readline()\\n self._check_acknowledgement(acknowledgement)\\n\\n self.serial_connection.write(self.ENQ)\\n unit = self.MEASUREMENT_UNITS[self.serial_connection.readline().rstrip(self.LF).rstrip(self.CR)]\\n\\n self.serial_connection.write(self.CR + self.LF)\\n\\n return unit\",\n \"def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetStackedBarUnitArgs']]]]:\\n return pulumi.get(self, \\\"units\\\")\",\n \"def get_list_powers(self):\\r\\n _debug('simq03b_api.get_list_powers')\\r\\n \\r\\n s = self.query('SOUR:LIST:POW?')\\r\\n if s == None: return None\\r\\n a = []\\r\\n n = 0\\r\\n for x in s.split(','):\\r\\n try:\\r\\n a.append(float(x.strip()))\\r\\n except:\\r\\n print('ERROR get_list_powers(): non-float in list ', n, x)\\r\\n n += 1\\r\\n return a\",\n \"def get_idle_units(self, n):\\n status = self.get_status() \\n unitindices = []\\n for i in xrange(len(status)):\\n if status[i] == 'idle':\\n unitindices.append(i)\\n if len(unitindices) == n:\\n break\\n return unitindices\",\n \"def totalUnits(self):\\n\\t\\treturn self.units\",\n \"def getUnits(self):\\n\\n return len(self.units)\",\n \"def get_names(self):\\n\\n return self.mod_suites.keys()\",\n \"def get_all_items(unit) -> list:\\n items = []\\n for item in unit.items:\\n if item.multi_item:\\n for subitem in item.subitems:\\n items.append(subitem)\\n else:\\n items.append(item)\\n return items\",\n \"def getElementName(self):\\n return _libsbml.ListOfUnits_getElementName(self)\",\n \"def get_metric_list(self) -> List[str]:\\n ...\",\n \"def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetBarUnitArgs']]]]:\\n return pulumi.get(self, \\\"units\\\")\",\n \"def _get_units(self, name):\\n meta = self._abs2meta\\n\\n if name in meta:\\n return meta[name]['units']\\n\\n proms = self._prom2abs\\n\\n if name in proms['output']:\\n abs_name = proms['output'][name][0]\\n return meta[abs_name]['units']\\n\\n elif name in proms['input']:\\n if len(proms['input'][name]) > 1:\\n # The promoted name maps to multiple absolute names, require absolute name.\\n msg = \\\"Can't get units for the promoted name '%s' because it refers to \\\" + \\\\\\n \\\"multiple inputs: %s. Access the units using an absolute path name.\\\"\\n raise RuntimeError(msg % (name, str(proms['input'][name])))\\n\\n abs_name = proms['input'][name][0]\\n return meta[abs_name]['units']\\n\\n raise KeyError('Variable name \\\"{}\\\" not found.'.format(name))\",\n \"def getAllSpectrumMeasurements(self): \\n return self.spectrum\",\n \"def raw_units(self) -> str:\\n if self._node.uom == 'F':\\n return TEMP_FAHRENHEIT\\n if self._node.uom == 'C':\\n return TEMP_CELSIUS\\n return self._node.uom\",\n \"def get_meters(api):\\n devices = api.device_list()\\n return [Meter(api, device.hardware_address) for device in devices if device.model_id == 'electric_meter']\",\n \"def getDistanceUnits(self) -> Unit:\\n ...\",\n \"def fluid_func(self):\\n residual = []\\n for fluid, x in self.inl[0].fluid.val.items():\\n res = x * self.inl[0].m.val_SI\\n for o in self.outl:\\n res -= o.fluid.val[fluid] * o.m.val_SI\\n residual += [res]\\n return residual\",\n \"def test_get_bios_unit_list(self):\\n pass\",\n \"def _get_fitness(self, mol):\\n\\n property_vector = []\\n for property_fn in self._property_fns:\\n logger.info(\\n f'Using {property_fn.__name__} on \\\"{mol}\\\".'\\n )\\n property_vector.append(property_fn(mol))\\n return property_vector\",\n \"def units(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OneDashboardPageWidgetAreaUnitArgs']]]]:\\n return pulumi.get(self, \\\"units\\\")\",\n \"def time_units(self) -> str:\\n return self._ll_tree_sequence.get_time_units()\",\n \"def getSubstanceUnits(self):\\n return _libsbml.KineticLaw_getSubstanceUnits(self)\",\n \"def _get_units(self, q) -> unyt.Unit:\\n try:\\n units = q.units\\n except AttributeError:\\n units = unyt.dimensionless\\n return unyt.Unit(units, registry=self.registry)\",\n \"def fluid_func(self):\\n residual = []\\n for i in range(self.num_i):\\n for fluid, x in self.inl[0].fluid.val.items():\\n residual += [x - self.outl[0].fluid.val[fluid]]\\n return residual\",\n \"def GenerateUnitList(self):\\n # Verify platform specific terms. Skip whole term if platform does not\\n # match.\\n if self.term.platform:\\n if 'silverpeak' not in self.term.platform:\\n return []\\n if self.term.platform_exclude:\\n if 'silverpeak' in self.term.platform_exclude:\\n return []\\n\\n ret_str = []\\n if 'established' in self.term.option:\\n dst_ports = ['any']\\n else:\\n dst_ports = self._NormalizePortRanges(\\n self._FixLongList(self.term.destination_port, 10)\\n )\\n source_all_ipv6, source_address = self._FixIPv6Address(\\n self.term.source_address\\n )\\n if source_all_ipv6:\\n return ret_str\\n destination_all_ipv6, destination_address = self._FixIPv6Address(\\n self.term.destination_address\\n )\\n if destination_all_ipv6:\\n return ret_str\\n src_ips = self._NormalizeNetblocks(self._FixLongList(source_address, 50))\\n src_ports = self._NormalizePortRanges(\\n self._FixLongList(self.term.source_port, 10)\\n )\\n dst_ips = self._NormalizeNetblocks(\\n self._FixLongList(destination_address, 50)\\n )\\n for src_ip in src_ips:\\n for src_port in src_ports:\\n for dst_ip in dst_ips:\\n for dst_port in dst_ports:\\n ret_str.append((src_ip, src_port, dst_ip, dst_port))\\n return ret_str\",\n \"def unit_of_measurement(self):\\n return self.var_units\",\n \"def measurements(self):\\n # get available measurement types for this node\\n measurement_types = self.measurement_types()\\n\\n # retrieve measurement for each type\\n return list(self.measurement(t) for t in measurement_types)\",\n \"def get_units(self):\\r\\n msg = struct.pack('>2B', 56, 14)\\r\\n response = self.query(msg)\\r\\n\\r\\n if response[1] == 2:\\r\\n units = 'A'\\r\\n to_nm_multiplier = 1 / 10\\r\\n elif response[1] == 1:\\r\\n units = 'nm'\\r\\n to_nm_multiplier = 1\\r\\n elif response[1] == 0:\\r\\n units = 'um'\\r\\n to_nm_multiplier = 1000\\r\\n else:\\r\\n raise ValueError('Units not recognised.')\\r\\n\\r\\n # Save results locally too for quick re-use\\r\\n self._current_units = units\\r\\n self._current_to_nm_multiplier = to_nm_multiplier\\r\\n\\r\\n return units, to_nm_multiplier\",\n \"def unit_of_measurement(self) -> str:\\n raw_units = self.raw_units\\n\\n if raw_units in [TEMP_CELSIUS, TEMP_FAHRENHEIT]:\\n return self.hass.config.units.temperature_unit\\n return raw_units\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7093225","0.65067303","0.6453618","0.6437445","0.6428049","0.63517296","0.6145797","0.60083926","0.59385496","0.59025174","0.5840358","0.5831512","0.5831512","0.58269817","0.58130693","0.5776839","0.57549787","0.57283396","0.5718893","0.5671003","0.5671003","0.5651187","0.56393594","0.5627784","0.56052995","0.56038404","0.55969685","0.555957","0.5539501","0.553809","0.5534111","0.55260897","0.5519234","0.5511228","0.5485108","0.546993","0.54682016","0.54566634","0.54337335","0.542809","0.54237586","0.5420529","0.5408851","0.54064167","0.5397552","0.53966933","0.53961486","0.5379281","0.5373466","0.53672457","0.5362649","0.5355036","0.53519034","0.53504175","0.5346241","0.5343123","0.53292125","0.53221315","0.5316053","0.5315821","0.53030056","0.5285977","0.52851427","0.52592826","0.52581096","0.5251268","0.5233307","0.5228359","0.5218814","0.52124923","0.5193939","0.51895416","0.51880616","0.5186813","0.51864564","0.51742417","0.51720697","0.51524514","0.5141888","0.51404005","0.51251733","0.5122975","0.5120949","0.5118992","0.5112044","0.51108974","0.5108815","0.509645","0.5070263","0.50678307","0.5062044","0.50388515","0.50363857","0.50328445","0.5028698","0.5028563","0.50267476","0.5023462","0.50216866","0.50135976"],"string":"[\n \"0.7093225\",\n \"0.65067303\",\n \"0.6453618\",\n \"0.6437445\",\n \"0.6428049\",\n \"0.63517296\",\n \"0.6145797\",\n \"0.60083926\",\n \"0.59385496\",\n \"0.59025174\",\n \"0.5840358\",\n \"0.5831512\",\n \"0.5831512\",\n \"0.58269817\",\n \"0.58130693\",\n \"0.5776839\",\n \"0.57549787\",\n \"0.57283396\",\n \"0.5718893\",\n \"0.5671003\",\n \"0.5671003\",\n \"0.5651187\",\n \"0.56393594\",\n \"0.5627784\",\n \"0.56052995\",\n \"0.56038404\",\n \"0.55969685\",\n \"0.555957\",\n \"0.5539501\",\n \"0.553809\",\n \"0.5534111\",\n \"0.55260897\",\n \"0.5519234\",\n \"0.5511228\",\n \"0.5485108\",\n \"0.546993\",\n \"0.54682016\",\n \"0.54566634\",\n \"0.54337335\",\n \"0.542809\",\n \"0.54237586\",\n \"0.5420529\",\n \"0.5408851\",\n \"0.54064167\",\n \"0.5397552\",\n \"0.53966933\",\n \"0.53961486\",\n \"0.5379281\",\n \"0.5373466\",\n \"0.53672457\",\n \"0.5362649\",\n \"0.5355036\",\n \"0.53519034\",\n \"0.53504175\",\n \"0.5346241\",\n \"0.5343123\",\n \"0.53292125\",\n \"0.53221315\",\n \"0.5316053\",\n \"0.5315821\",\n \"0.53030056\",\n \"0.5285977\",\n \"0.52851427\",\n \"0.52592826\",\n \"0.52581096\",\n \"0.5251268\",\n \"0.5233307\",\n \"0.5228359\",\n \"0.5218814\",\n \"0.52124923\",\n \"0.5193939\",\n \"0.51895416\",\n \"0.51880616\",\n \"0.5186813\",\n \"0.51864564\",\n \"0.51742417\",\n \"0.51720697\",\n \"0.51524514\",\n \"0.5141888\",\n \"0.51404005\",\n \"0.51251733\",\n \"0.5122975\",\n \"0.5120949\",\n \"0.5118992\",\n \"0.5112044\",\n \"0.51108974\",\n \"0.5108815\",\n \"0.509645\",\n \"0.5070263\",\n \"0.50678307\",\n \"0.5062044\",\n \"0.50388515\",\n \"0.50363857\",\n \"0.50328445\",\n \"0.5028698\",\n \"0.5028563\",\n \"0.50267476\",\n \"0.5023462\",\n \"0.50216866\",\n \"0.50135976\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5055429"},"document_rank":{"kind":"string","value":"91"}}},{"rowIdx":88586,"cells":{"query":{"kind":"string","value":"Get the list of paramater names for the functional unit funame."},"document":{"kind":"string","value":"def getFuParList(self, funame):\n if not self._fupardict:\n buf = self._parent.Xeprbuf(10000)\n for fu in self.getFuList():\n self.aqGetExpFuParList(fu, buf, 10000)\n parlist = [x for x in buf.get_unicode_str().split(',') if self.aqGetParType('%s.%s' % (fu, x)) != self._parent.AQ_DT_UNKNOWN]\n self._fupardict[fu] = parlist\n\n if funame not in self._fupardict:\n for fu in self.getFuList():\n if fu.upper() == funame.upper():\n funame = fu\n break\n\n if funame not in self._fupardict:\n raise ParameterError(\"%sno such functional unit '%s' in experiment '%s'\" % (_msgprefix, funame, self.aqGetExpName()))\n return self._fupardict[funame]"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def parameter_names(self) -> List[str]:","def parameterNames(self, p_int): # real signature unknown; restored from __doc__\n return []","def get_param_names(hf):\n parameters = get_params(hf)\n return [p.name for p in parameters]","def get_str_param_names(self):\n # Exclude self.api and self.names from the command string\n return self.get_attribute_names(FormattedParameter)","def get_param_names(self):\n return list(self.params.keys())","def _get_param_names(self):\n temp_params = {'function': self.function, 'target': self.target}\n\n temp_params.update(self.kwargs)\n\n return temp_params","def get_hyperparameter_names():\n params = ['mu', 'nu', 'r', 's']\n return params","def _get_param_names(self):\r\n return sorted([p\r\n for p in self.__dict__\r\n if p != 'additional_args'])","def get_parameter_names(self):\n parNames = []\n # for par in self.variables: # TODO: LIKELY A BUG! DOES THE SAME AS get_variable_names()\n for par in self.parameters: # TRYING TO SOLVE THE ISSUE\n # EstimationVariable\n parNames.append(par.name)\n return parNames","def parameter_names(self):\n return [x for x in self.transformations.values() if isinstance(x, str)]","def get_model_parameter_names():\n params = ['mu', 'rho']\n return params","def parameter_names(self) -> list:\n parameters = []\n parameters.extend(self.properties.parameter_names)\n return parameters","def _f_in_parameters(self) -> List[Tuple[str, str]]:\n result = list() # type: List[Tuple[str, str]]\n for param in self.params:\n type_list = param.f_type()\n for type_name, postfix in type_list:\n result.append((type_name, param.name + postfix))\n return result","def _fc_in_parameters(self) -> List[str]:\n result = list() # type: List[str]\n\n for param in self.params:\n type_list = param.fc_type()\n for type_name, postfix in type_list:\n result.append('{} {}'.format(type_name, param.name + postfix))\n\n return result","def param_unc_names(self) -> List[str]:\n return self._param_unc_names(self.model).decode(\"utf-8\").split(\",\")","def param_names(\n self, *, include_tp: bool = False, include_gq: bool = False\n ) -> List[str]:\n return (\n self._param_names(self.model, int(include_tp), int(include_gq))\n .decode(\"utf-8\")\n .split(\",\")\n )","def get_ext_param_names(self):\n num_param = core.xc_func_info_get_n_ext_params(self.xc_func_info)\n\n ret = []\n for p in range(num_param):\n tmp = core.xc_func_info_get_ext_params_name(self.xc_func_info, p)\n ret.append(tmp.decode(\"UTF-8\"))\n\n return ret","def get_paramnames_list(self):\n # TODO include syselem?\n\n query = \"SELECT NAME FROM %s\" % self.__schema\n with self.__connection.cursor() as cursor:\n cursor.execute(query)\n result = cursor.fetchall()\n return [val['NAME'] for val in result]","def get_layer_var_names(self):\n return(self.params)","def get_param_names(self):\n # Sort the FIO parameter names to generate consistent fio commands\n all_param_names = super(FioCommand, self).get_param_names()\n # move the 'name' option as the first option of fio job\n all_param_names.remove(\"name\")\n all_param_names.insert(0, \"name\")\n\n return all_param_names","def _get_fitted_param_names(self):\n return self._fitted_param_names","def getParameterList(self):\n inputList = []\n for name, n in zip(self._names, self._inputs):\n inputList += ['%s.x%d' % (name, i) for i in range(n)]\n return inputList","def _formal_params(self, doclet):\n name, paren, params = self.arguments[0].partition('(')\n return ('(%s' % params) if params else '(%s)' % ', '.join(doclet['meta']['code']['paramnames'])","def return_parameter_names():\n return list(titles), list(labels)","def get_params_list():\n return common.QOL_PARAMS","def parameters_names(cls):\n return cls._Parameters._fields","def param(self):\r\n\r\n return []","def _fi_in_parameters(self) -> List[Tuple[str, str]]:\n result = list() # type: List[Tuple[str, str]]\n for param in self.params:\n type_list = param.fi_type()\n for type_name, postfix in type_list:\n result.append((type_name, param.name + postfix))\n return result","def param(self):\n return []","def param(self):\n return []","def parameters_list(self):\n return [getattr(self.parameters, p) for p in self.parameters_names()]","def _get_parameters(self):\n return (self.SYMBOL, self.parameterArray())","def param(self):\r\n return []","def get_params(node):\n if node.type == 'parameter':\n return [(self.descend(node.args[0]), types.translation[self.descend(node.args[1])])]\n else:\n l = []\n for p in node.args:\n l.extend(get_params(p))\n return l","def return_all_parameter_names():\n a = list(titles)\n a.append(r\"$\\chi^{2}$ per degree of freedom\")\n b = list(labels)\n b.append(\"chi2_per_dof\")\n return a, b","def variables_used (self) :\r\n\t\treturn [i[0] for i in self.parameters]","def parameters(self):\n return []","def parameter_names_from_model(model):\n variables = model.getVariables()\n itvar = variables.iterator()\n names = []\n for i in xrange(len(variables)):\n currentvar = itvar.Next()\n names.append(currentvar.GetName())\n return names","def parameter_names(self):\n raise NotImplementedError(\"the parameter_names property should \"\n \"be defined in the Estimator sub-class\")","def parameters(self):\n return [p for _, a in vars(self).items() for p in self._params(a)]","def function_name(parameters):","def get_params(self):\n return []","def list_params(ns):\n try:\n ns = make_global_ns(ns)\n names = get_param_server().getParamNames()\n names.sort()\n return [n for n in names if n.startswith(ns)]\n except socket.error:\n raise RosParamIOException(\"Unable to communicate with master!\")","def get_param_names(obj: Union[Type[_BaseTpcpObject], _BaseTpcpObject]) -> List[str]:\n cls = obj if isinstance(obj, type) else type(obj)\n parameters = list(_get_init_defaults(cls).values())\n for p in parameters:\n if p.kind == p.VAR_POSITIONAL:\n raise RuntimeError(\n \"tpcp algorithms and pipelines should always specify their parameters in the signature of their \"\n f\"__init__ (no varargs). {cls} doesn't follow this convention.\"\n )\n # Extract and sort argument names excluding 'self'\n return sorted([p.name for p in parameters])","def names(self):\n result = []\n result.extend(self.positional_arguments)\n if self.arbitary_positional_arguments is not None:\n result.append(self.arbitary_positional_arguments)\n if self.arbitary_keyword_arguments is not None:\n result.append(self.arbitary_keyword_arguments)\n result.extend(self.keyword_arguments)\n return result","def getGroupFuncs(self):\n\n funcs = []\n for p in self.Parameters:\n if p.arg_name[0:8] == \"Function\" and p.arg_value:\n fct, attr = p.arg_value.split(':')\n if fct and attr:\n funcs.append((fct, attr))\n if not funcs:\n funcs.append(('count', '*'))\n return funcs","def _get_param_names(self, direction: int, layer: int) -> List[str]:\n suffix = '_reverse' if direction == 1 else ''\n param_names = ['weight_ih_l{}{}', 'weight_hh_l{}{}']\n if self.bias:\n param_names += ['bias_ih_l{}{}', 'bias_hh_l{}{}']\n param_names = [x.format(layer, suffix) for x in param_names]\n return param_names","def def_paramt():\n Zeff = 1.0\n amu = 2.0\n mf = mp*amu\n return Zeff, amu,mf","def param(self):\r\n paramlist = []\r\n gradlist = []\r\n\r\n for layer in self.layers:\r\n try:\r\n layer_param, layer_grad = layer.param()\r\n paramlist = paramlist + layer_param\r\n gradlist = gradlist + layer_grad\r\n except ValueError:\r\n continue\r\n return paramlist, gradlist","def GetFunctionParametersAndValues():\n frame = inspect.currentframe().f_back\n args, _, _, values = inspect.getargvalues(frame)\n return ([(i, values[i]) for i in args])","def parameters(self):\n return [term.parameter for term in self.terms]","def named_trainable_parameters(self) -> List[str]:\n return [name for name, p in self._model.named_parameters() if p.requires_grad]","def _get_parameters(self) -> list:\n return self.parameters","def get_params(self):","def get_required_parameters(self) -> list:\n results = []\n if self.no_params or self.params_optional:\n return []\n else:\n for parameter, parameter_details in self.parameters.items():\n # Fixing issue #92\n # if parameter == \"effect\":\n # continue\n if not parameter_details.default_value:\n results.append(parameter_details.name)\n return results","def get_parameter_names(self, exclude_pop_model=False):\n if (self._population_model is None) or exclude_pop_model:\n names = self._mechanistic_model.parameters()\n for error_model in self._error_models:\n names += error_model.get_parameter_names()\n return names\n\n return self._population_model.get_parameter_names()","def parameter_names(self, add_self=False, adjust_for_printing=False, recursive=True):\n if adjust_for_printing: adjust = lambda x: adjust_name_for_printing(x)\n else: adjust = lambda x: x\n if recursive: names = [xi for x in self.parameters for xi in x.parameter_names(add_self=True, adjust_for_printing=adjust_for_printing)]\n else: names = [adjust(x.name) for x in self.parameters]\n if add_self: names = map(lambda x: adjust(self.name) + \".\" + x, names)\n return names","def get_mandatory_param_names(self):\n all_names = self.params.keys()\n return [name for name in all_names \n if not self.params[name].is_optional]","def get_resource_params():\n return Parameter.list()","def fixture_sorted_param_names(allparams):\n return sorted(list(allparams.keys()))","def param_strs(self):\n name_len = max(len(p.name) for p in self)\n value_len = max(len(p.value_str) for p in self.params.values())\n units_len = max(len(p.units) for p in self.params.values())\n return [(p.name.ljust(name_len), p.value_str.ljust(value_len),\n p.units.ljust(units_len), p.__doc__)\n for p in self.params.values() if p]","def source_parameter_names(self):\n return [x for x, y in self.transformations.items() if isinstance(y, str)]","def getParameters(self):\n params = []\n for m in [self.ix, self.ih, self.fx, self.fh, self.ox, self.oh, self.ux, self.uh]:\n # we do not get param of output module\n l = list(m.parameters())\n params.extend(l)\n\n one_dim = [p.view(p.numel()) for p in params]\n params = F.torch.cat(one_dim)\n return params","def getParameters(self):\n params = []\n for m in [self.ix, self.ih, self.fx, self.fh, self.ox, self.oh, self.ux, self.uh]:\n # we do not get param of output module\n l = list(m.parameters())\n params.extend(l)\n\n one_dim = [p.view(p.numel()) for p in params]\n params = F.torch.cat(one_dim)\n return params","def load_params(self, func, index):\n inputs = inspect.getfullargspec(func).args\n params = []\n for iname in inputs:\n params.append(self.load(f\"{func.__name__}.{iname}_{index}\"))\n return params","def get_params(self):\n return list(self.params.values())","def sensor_parameters_list(self):\n return list(self.params_f.keys()) + list(self.params_i.keys())","def potential_parameters(cls):\n return [\"k\", \"periodicity\", \"phase\", \"idivf\"]","def potential_parameters(cls):\n return [\"k\", \"periodicity\", \"phase\", \"idivf\"]","def func_var_names(func):\n names = func.__code__.co_varnames[:func.__code__.co_argcount]\n return names","def print_param_names(model):\n for (param_name, param) in model.get_parameters().items():\n print(param_name, param.shape)","def _get_param_names(cls):\n # fetch the constructor or the original constructor before\n # deprecation wrapping if any\n init = getattr(cls.__init__, 'deprecated_original', cls.__init__)\n if init is object.__init__:\n # No explicit constructor to introspect\n return []\n\n # introspect the constructor arguments to find the model parameters\n # to represent\n init_signature = signature(init)\n # Consider the constructor parameters excluding 'self'\n parameters = [\n p for p in init_signature.parameters.values()\n if p.name != 'self' and p.kind != p.VAR_KEYWORD\n ]\n for p in parameters:\n if p.kind == p.VAR_POSITIONAL:\n raise EstimatorParameterError(\n 'scikit-learn estimators should always '\n 'specify their parameters in the signature'\n ' of their __init__ (no varargs).'\n \" %s with constructor %s doesn't \"\n ' follow this convention.' % (cls, init_signature))\n # Extract and sort argument names excluding 'self'\n return sorted([p.name for p in parameters])","def argument_list(self):\n answer = self._call('argument_list')\n return answer.names","def getListOfParameters(self):\n return self.model.getListOfParameters()","def get_suffstat_names():\n params = ['sum_x', 'sum_x_squared']\n return params","def params(self):\n return [cq.Symbol('theta_0')]","def argnames(method):\n return [arg for arg in method.__code__.co_varnames if arg != \"self\"]","def getListOfParameters(self, *args):\n return _libsbml.KineticLaw_getListOfParameters(self, *args)","def getElementName(self):\n return _libsbml.ListOfParameters_getElementName(self)","def _getargs(fn_sig):\n params = fn_sig.parameters\n args = []\n for k, v in params.items():\n if (v.kind & v.POSITIONAL_OR_KEYWORD) == v.POSITIONAL_OR_KEYWORD:\n args.append(k)\n else:\n msg = \"%s argument type unsupported in jitclass\" % v.kind\n raise errors.UnsupportedError(msg)\n return args","def paramDetails(cls):\n return {\n 'dim': (10, 20, 2, 20),\n 'nIter': (1, 10, 2, 5),\n 'lamb': (.1, 1., .1, .05),\n 'alph': (30, 50, 5, 40)\n }","def potential_parameters(cls):\n return [\"k\", \"angle\"]","def getParameters(self): #$NON-NLS-1$\r","def getListOfLocalParameters(self, *args):\n return _libsbml.KineticLaw_getListOfLocalParameters(self, *args)","def _get_param_names_transformed(self):\r\n n = self._get_param_names()\r\n\r\n # remove/concatenate the tied parameter names\r\n if len(self.tied_indices):\r\n for t in self.tied_indices:\r\n n[t[0]] = \"<tie>\".join([n[tt] for tt in t])\r\n remove = np.hstack([t[1:] for t in self.tied_indices])\r\n else:\r\n remove = np.empty(shape=(0,), dtype=np.int)\r\n\r\n # also remove the fixed params\r\n if len(self.fixed_indices):\r\n remove = np.hstack((remove, np.hstack(self.fixed_indices)))\r\n\r\n # add markers to show that some variables are constrained\r\n for i, t in zip(self.constrained_indices, self.constraints):\r\n for ii in i:\r\n n[ii] = n[ii] + t.__str__()\r\n\r\n n = [nn for i, nn in enumerate(n) if not i in remove]\r\n return n","def parameters(self):\n return self.vars","def potential_parameters(cls):\n return [\"k\", \"length\"]","def parameters(self):\n return [i for i in self.variables if has_roles(i, Parameter)]","def _create_parameter_names(self):\n self._parameter_names = [key for key in self.parameter_schema.keys() if key != 'num_simulations']","def get_params(self):\n pass","def get_parameters_list(self):\n return self.description[\"config\"][\"values\"].keys()","def getElementName(self):\n return _libsbml.ListOfLocalParameters_getElementName(self)","def get_ext_param_descriptions(self):\n num_param = core.xc_func_info_get_n_ext_params(self.xc_func_info)\n\n ret = []\n for p in range(num_param):\n tmp = core.xc_func_info_get_ext_params_description(self.xc_func_info, p)\n ret.append(tmp.decode(\"UTF-8\"))\n\n return ret","def get_params(self) -> torch.Tensor:\n params = []\n for pp in list(self.net.parameters()):\n params.append(pp.view(-1))\n return torch.cat(params)","def get_params(self, pnames=None):\n l = []\n if pnames is None:\n pnames = self._params.keys()\n for pname in pnames:\n p = self._params[pname]\n if isinstance(p, Parameter):\n l.append(p)\n return l","def parameter_values(self) -> List[Tuple[str, Any]]:\n pvs = [(param, getattr(self, variable))\n for variable, param in self.variable_name_to_query_param.items()]\n return [(p, v) for p, v in pvs if v is not None]","def get_params(self):\n raise NotImplementedError","def params():\n raise NotImplementedError","def compile_parameter_list(self):\r\n if self.__tokenizer.token_type() != TYPES_DIC[\"SYMBOL\"]:\r\n type = self.__get_type()\r\n self.__advance()\r\n name = self.__tokenizer.identifier()\r\n self.__subroutine_symbols.define(name, type, \"argument\")\r\n self.__advance()\r\n while self.__tokenizer.symbol() != ')':\r\n self.__advance()\r\n type = self.__get_type()\r\n self.__advance()\r\n name = self.__tokenizer.identifier()\r\n self.__subroutine_symbols.define(name, type, \"argument\")\r\n self.__advance()","def getdefflags(config_nm):\n if config_nm is 'train':\n user_params = user_params_train\n elif config_nm is 'eval':\n user_params = user_params_eval\n elif config_nm is 'tfrecorder':\n user_params = user_params_recorder\n else:\n print('Unrecognized configuration name : %s, exiting ....' % config_nm)\n exit(-1)\n\n\n return mandatory_params+user_params"],"string":"[\n \"def parameter_names(self) -> List[str]:\",\n \"def parameterNames(self, p_int): # real signature unknown; restored from __doc__\\n return []\",\n \"def get_param_names(hf):\\n parameters = get_params(hf)\\n return [p.name for p in parameters]\",\n \"def get_str_param_names(self):\\n # Exclude self.api and self.names from the command string\\n return self.get_attribute_names(FormattedParameter)\",\n \"def get_param_names(self):\\n return list(self.params.keys())\",\n \"def _get_param_names(self):\\n temp_params = {'function': self.function, 'target': self.target}\\n\\n temp_params.update(self.kwargs)\\n\\n return temp_params\",\n \"def get_hyperparameter_names():\\n params = ['mu', 'nu', 'r', 's']\\n return params\",\n \"def _get_param_names(self):\\r\\n return sorted([p\\r\\n for p in self.__dict__\\r\\n if p != 'additional_args'])\",\n \"def get_parameter_names(self):\\n parNames = []\\n # for par in self.variables: # TODO: LIKELY A BUG! DOES THE SAME AS get_variable_names()\\n for par in self.parameters: # TRYING TO SOLVE THE ISSUE\\n # EstimationVariable\\n parNames.append(par.name)\\n return parNames\",\n \"def parameter_names(self):\\n return [x for x in self.transformations.values() if isinstance(x, str)]\",\n \"def get_model_parameter_names():\\n params = ['mu', 'rho']\\n return params\",\n \"def parameter_names(self) -> list:\\n parameters = []\\n parameters.extend(self.properties.parameter_names)\\n return parameters\",\n \"def _f_in_parameters(self) -> List[Tuple[str, str]]:\\n result = list() # type: List[Tuple[str, str]]\\n for param in self.params:\\n type_list = param.f_type()\\n for type_name, postfix in type_list:\\n result.append((type_name, param.name + postfix))\\n return result\",\n \"def _fc_in_parameters(self) -> List[str]:\\n result = list() # type: List[str]\\n\\n for param in self.params:\\n type_list = param.fc_type()\\n for type_name, postfix in type_list:\\n result.append('{} {}'.format(type_name, param.name + postfix))\\n\\n return result\",\n \"def param_unc_names(self) -> List[str]:\\n return self._param_unc_names(self.model).decode(\\\"utf-8\\\").split(\\\",\\\")\",\n \"def param_names(\\n self, *, include_tp: bool = False, include_gq: bool = False\\n ) -> List[str]:\\n return (\\n self._param_names(self.model, int(include_tp), int(include_gq))\\n .decode(\\\"utf-8\\\")\\n .split(\\\",\\\")\\n )\",\n \"def get_ext_param_names(self):\\n num_param = core.xc_func_info_get_n_ext_params(self.xc_func_info)\\n\\n ret = []\\n for p in range(num_param):\\n tmp = core.xc_func_info_get_ext_params_name(self.xc_func_info, p)\\n ret.append(tmp.decode(\\\"UTF-8\\\"))\\n\\n return ret\",\n \"def get_paramnames_list(self):\\n # TODO include syselem?\\n\\n query = \\\"SELECT NAME FROM %s\\\" % self.__schema\\n with self.__connection.cursor() as cursor:\\n cursor.execute(query)\\n result = cursor.fetchall()\\n return [val['NAME'] for val in result]\",\n \"def get_layer_var_names(self):\\n return(self.params)\",\n \"def get_param_names(self):\\n # Sort the FIO parameter names to generate consistent fio commands\\n all_param_names = super(FioCommand, self).get_param_names()\\n # move the 'name' option as the first option of fio job\\n all_param_names.remove(\\\"name\\\")\\n all_param_names.insert(0, \\\"name\\\")\\n\\n return all_param_names\",\n \"def _get_fitted_param_names(self):\\n return self._fitted_param_names\",\n \"def getParameterList(self):\\n inputList = []\\n for name, n in zip(self._names, self._inputs):\\n inputList += ['%s.x%d' % (name, i) for i in range(n)]\\n return inputList\",\n \"def _formal_params(self, doclet):\\n name, paren, params = self.arguments[0].partition('(')\\n return ('(%s' % params) if params else '(%s)' % ', '.join(doclet['meta']['code']['paramnames'])\",\n \"def return_parameter_names():\\n return list(titles), list(labels)\",\n \"def get_params_list():\\n return common.QOL_PARAMS\",\n \"def parameters_names(cls):\\n return cls._Parameters._fields\",\n \"def param(self):\\r\\n\\r\\n return []\",\n \"def _fi_in_parameters(self) -> List[Tuple[str, str]]:\\n result = list() # type: List[Tuple[str, str]]\\n for param in self.params:\\n type_list = param.fi_type()\\n for type_name, postfix in type_list:\\n result.append((type_name, param.name + postfix))\\n return result\",\n \"def param(self):\\n return []\",\n \"def param(self):\\n return []\",\n \"def parameters_list(self):\\n return [getattr(self.parameters, p) for p in self.parameters_names()]\",\n \"def _get_parameters(self):\\n return (self.SYMBOL, self.parameterArray())\",\n \"def param(self):\\r\\n return []\",\n \"def get_params(node):\\n if node.type == 'parameter':\\n return [(self.descend(node.args[0]), types.translation[self.descend(node.args[1])])]\\n else:\\n l = []\\n for p in node.args:\\n l.extend(get_params(p))\\n return l\",\n \"def return_all_parameter_names():\\n a = list(titles)\\n a.append(r\\\"$\\\\chi^{2}$ per degree of freedom\\\")\\n b = list(labels)\\n b.append(\\\"chi2_per_dof\\\")\\n return a, b\",\n \"def variables_used (self) :\\r\\n\\t\\treturn [i[0] for i in self.parameters]\",\n \"def parameters(self):\\n return []\",\n \"def parameter_names_from_model(model):\\n variables = model.getVariables()\\n itvar = variables.iterator()\\n names = []\\n for i in xrange(len(variables)):\\n currentvar = itvar.Next()\\n names.append(currentvar.GetName())\\n return names\",\n \"def parameter_names(self):\\n raise NotImplementedError(\\\"the parameter_names property should \\\"\\n \\\"be defined in the Estimator sub-class\\\")\",\n \"def parameters(self):\\n return [p for _, a in vars(self).items() for p in self._params(a)]\",\n \"def function_name(parameters):\",\n \"def get_params(self):\\n return []\",\n \"def list_params(ns):\\n try:\\n ns = make_global_ns(ns)\\n names = get_param_server().getParamNames()\\n names.sort()\\n return [n for n in names if n.startswith(ns)]\\n except socket.error:\\n raise RosParamIOException(\\\"Unable to communicate with master!\\\")\",\n \"def get_param_names(obj: Union[Type[_BaseTpcpObject], _BaseTpcpObject]) -> List[str]:\\n cls = obj if isinstance(obj, type) else type(obj)\\n parameters = list(_get_init_defaults(cls).values())\\n for p in parameters:\\n if p.kind == p.VAR_POSITIONAL:\\n raise RuntimeError(\\n \\\"tpcp algorithms and pipelines should always specify their parameters in the signature of their \\\"\\n f\\\"__init__ (no varargs). {cls} doesn't follow this convention.\\\"\\n )\\n # Extract and sort argument names excluding 'self'\\n return sorted([p.name for p in parameters])\",\n \"def names(self):\\n result = []\\n result.extend(self.positional_arguments)\\n if self.arbitary_positional_arguments is not None:\\n result.append(self.arbitary_positional_arguments)\\n if self.arbitary_keyword_arguments is not None:\\n result.append(self.arbitary_keyword_arguments)\\n result.extend(self.keyword_arguments)\\n return result\",\n \"def getGroupFuncs(self):\\n\\n funcs = []\\n for p in self.Parameters:\\n if p.arg_name[0:8] == \\\"Function\\\" and p.arg_value:\\n fct, attr = p.arg_value.split(':')\\n if fct and attr:\\n funcs.append((fct, attr))\\n if not funcs:\\n funcs.append(('count', '*'))\\n return funcs\",\n \"def _get_param_names(self, direction: int, layer: int) -> List[str]:\\n suffix = '_reverse' if direction == 1 else ''\\n param_names = ['weight_ih_l{}{}', 'weight_hh_l{}{}']\\n if self.bias:\\n param_names += ['bias_ih_l{}{}', 'bias_hh_l{}{}']\\n param_names = [x.format(layer, suffix) for x in param_names]\\n return param_names\",\n \"def def_paramt():\\n Zeff = 1.0\\n amu = 2.0\\n mf = mp*amu\\n return Zeff, amu,mf\",\n \"def param(self):\\r\\n paramlist = []\\r\\n gradlist = []\\r\\n\\r\\n for layer in self.layers:\\r\\n try:\\r\\n layer_param, layer_grad = layer.param()\\r\\n paramlist = paramlist + layer_param\\r\\n gradlist = gradlist + layer_grad\\r\\n except ValueError:\\r\\n continue\\r\\n return paramlist, gradlist\",\n \"def GetFunctionParametersAndValues():\\n frame = inspect.currentframe().f_back\\n args, _, _, values = inspect.getargvalues(frame)\\n return ([(i, values[i]) for i in args])\",\n \"def parameters(self):\\n return [term.parameter for term in self.terms]\",\n \"def named_trainable_parameters(self) -> List[str]:\\n return [name for name, p in self._model.named_parameters() if p.requires_grad]\",\n \"def _get_parameters(self) -> list:\\n return self.parameters\",\n \"def get_params(self):\",\n \"def get_required_parameters(self) -> list:\\n results = []\\n if self.no_params or self.params_optional:\\n return []\\n else:\\n for parameter, parameter_details in self.parameters.items():\\n # Fixing issue #92\\n # if parameter == \\\"effect\\\":\\n # continue\\n if not parameter_details.default_value:\\n results.append(parameter_details.name)\\n return results\",\n \"def get_parameter_names(self, exclude_pop_model=False):\\n if (self._population_model is None) or exclude_pop_model:\\n names = self._mechanistic_model.parameters()\\n for error_model in self._error_models:\\n names += error_model.get_parameter_names()\\n return names\\n\\n return self._population_model.get_parameter_names()\",\n \"def parameter_names(self, add_self=False, adjust_for_printing=False, recursive=True):\\n if adjust_for_printing: adjust = lambda x: adjust_name_for_printing(x)\\n else: adjust = lambda x: x\\n if recursive: names = [xi for x in self.parameters for xi in x.parameter_names(add_self=True, adjust_for_printing=adjust_for_printing)]\\n else: names = [adjust(x.name) for x in self.parameters]\\n if add_self: names = map(lambda x: adjust(self.name) + \\\".\\\" + x, names)\\n return names\",\n \"def get_mandatory_param_names(self):\\n all_names = self.params.keys()\\n return [name for name in all_names \\n if not self.params[name].is_optional]\",\n \"def get_resource_params():\\n return Parameter.list()\",\n \"def fixture_sorted_param_names(allparams):\\n return sorted(list(allparams.keys()))\",\n \"def param_strs(self):\\n name_len = max(len(p.name) for p in self)\\n value_len = max(len(p.value_str) for p in self.params.values())\\n units_len = max(len(p.units) for p in self.params.values())\\n return [(p.name.ljust(name_len), p.value_str.ljust(value_len),\\n p.units.ljust(units_len), p.__doc__)\\n for p in self.params.values() if p]\",\n \"def source_parameter_names(self):\\n return [x for x, y in self.transformations.items() if isinstance(y, str)]\",\n \"def getParameters(self):\\n params = []\\n for m in [self.ix, self.ih, self.fx, self.fh, self.ox, self.oh, self.ux, self.uh]:\\n # we do not get param of output module\\n l = list(m.parameters())\\n params.extend(l)\\n\\n one_dim = [p.view(p.numel()) for p in params]\\n params = F.torch.cat(one_dim)\\n return params\",\n \"def getParameters(self):\\n params = []\\n for m in [self.ix, self.ih, self.fx, self.fh, self.ox, self.oh, self.ux, self.uh]:\\n # we do not get param of output module\\n l = list(m.parameters())\\n params.extend(l)\\n\\n one_dim = [p.view(p.numel()) for p in params]\\n params = F.torch.cat(one_dim)\\n return params\",\n \"def load_params(self, func, index):\\n inputs = inspect.getfullargspec(func).args\\n params = []\\n for iname in inputs:\\n params.append(self.load(f\\\"{func.__name__}.{iname}_{index}\\\"))\\n return params\",\n \"def get_params(self):\\n return list(self.params.values())\",\n \"def sensor_parameters_list(self):\\n return list(self.params_f.keys()) + list(self.params_i.keys())\",\n \"def potential_parameters(cls):\\n return [\\\"k\\\", \\\"periodicity\\\", \\\"phase\\\", \\\"idivf\\\"]\",\n \"def potential_parameters(cls):\\n return [\\\"k\\\", \\\"periodicity\\\", \\\"phase\\\", \\\"idivf\\\"]\",\n \"def func_var_names(func):\\n names = func.__code__.co_varnames[:func.__code__.co_argcount]\\n return names\",\n \"def print_param_names(model):\\n for (param_name, param) in model.get_parameters().items():\\n print(param_name, param.shape)\",\n \"def _get_param_names(cls):\\n # fetch the constructor or the original constructor before\\n # deprecation wrapping if any\\n init = getattr(cls.__init__, 'deprecated_original', cls.__init__)\\n if init is object.__init__:\\n # No explicit constructor to introspect\\n return []\\n\\n # introspect the constructor arguments to find the model parameters\\n # to represent\\n init_signature = signature(init)\\n # Consider the constructor parameters excluding 'self'\\n parameters = [\\n p for p in init_signature.parameters.values()\\n if p.name != 'self' and p.kind != p.VAR_KEYWORD\\n ]\\n for p in parameters:\\n if p.kind == p.VAR_POSITIONAL:\\n raise EstimatorParameterError(\\n 'scikit-learn estimators should always '\\n 'specify their parameters in the signature'\\n ' of their __init__ (no varargs).'\\n \\\" %s with constructor %s doesn't \\\"\\n ' follow this convention.' % (cls, init_signature))\\n # Extract and sort argument names excluding 'self'\\n return sorted([p.name for p in parameters])\",\n \"def argument_list(self):\\n answer = self._call('argument_list')\\n return answer.names\",\n \"def getListOfParameters(self):\\n return self.model.getListOfParameters()\",\n \"def get_suffstat_names():\\n params = ['sum_x', 'sum_x_squared']\\n return params\",\n \"def params(self):\\n return [cq.Symbol('theta_0')]\",\n \"def argnames(method):\\n return [arg for arg in method.__code__.co_varnames if arg != \\\"self\\\"]\",\n \"def getListOfParameters(self, *args):\\n return _libsbml.KineticLaw_getListOfParameters(self, *args)\",\n \"def getElementName(self):\\n return _libsbml.ListOfParameters_getElementName(self)\",\n \"def _getargs(fn_sig):\\n params = fn_sig.parameters\\n args = []\\n for k, v in params.items():\\n if (v.kind & v.POSITIONAL_OR_KEYWORD) == v.POSITIONAL_OR_KEYWORD:\\n args.append(k)\\n else:\\n msg = \\\"%s argument type unsupported in jitclass\\\" % v.kind\\n raise errors.UnsupportedError(msg)\\n return args\",\n \"def paramDetails(cls):\\n return {\\n 'dim': (10, 20, 2, 20),\\n 'nIter': (1, 10, 2, 5),\\n 'lamb': (.1, 1., .1, .05),\\n 'alph': (30, 50, 5, 40)\\n }\",\n \"def potential_parameters(cls):\\n return [\\\"k\\\", \\\"angle\\\"]\",\n \"def getParameters(self): #$NON-NLS-1$\\r\",\n \"def getListOfLocalParameters(self, *args):\\n return _libsbml.KineticLaw_getListOfLocalParameters(self, *args)\",\n \"def _get_param_names_transformed(self):\\r\\n n = self._get_param_names()\\r\\n\\r\\n # remove/concatenate the tied parameter names\\r\\n if len(self.tied_indices):\\r\\n for t in self.tied_indices:\\r\\n n[t[0]] = \\\"<tie>\\\".join([n[tt] for tt in t])\\r\\n remove = np.hstack([t[1:] for t in self.tied_indices])\\r\\n else:\\r\\n remove = np.empty(shape=(0,), dtype=np.int)\\r\\n\\r\\n # also remove the fixed params\\r\\n if len(self.fixed_indices):\\r\\n remove = np.hstack((remove, np.hstack(self.fixed_indices)))\\r\\n\\r\\n # add markers to show that some variables are constrained\\r\\n for i, t in zip(self.constrained_indices, self.constraints):\\r\\n for ii in i:\\r\\n n[ii] = n[ii] + t.__str__()\\r\\n\\r\\n n = [nn for i, nn in enumerate(n) if not i in remove]\\r\\n return n\",\n \"def parameters(self):\\n return self.vars\",\n \"def potential_parameters(cls):\\n return [\\\"k\\\", \\\"length\\\"]\",\n \"def parameters(self):\\n return [i for i in self.variables if has_roles(i, Parameter)]\",\n \"def _create_parameter_names(self):\\n self._parameter_names = [key for key in self.parameter_schema.keys() if key != 'num_simulations']\",\n \"def get_params(self):\\n pass\",\n \"def get_parameters_list(self):\\n return self.description[\\\"config\\\"][\\\"values\\\"].keys()\",\n \"def getElementName(self):\\n return _libsbml.ListOfLocalParameters_getElementName(self)\",\n \"def get_ext_param_descriptions(self):\\n num_param = core.xc_func_info_get_n_ext_params(self.xc_func_info)\\n\\n ret = []\\n for p in range(num_param):\\n tmp = core.xc_func_info_get_ext_params_description(self.xc_func_info, p)\\n ret.append(tmp.decode(\\\"UTF-8\\\"))\\n\\n return ret\",\n \"def get_params(self) -> torch.Tensor:\\n params = []\\n for pp in list(self.net.parameters()):\\n params.append(pp.view(-1))\\n return torch.cat(params)\",\n \"def get_params(self, pnames=None):\\n l = []\\n if pnames is None:\\n pnames = self._params.keys()\\n for pname in pnames:\\n p = self._params[pname]\\n if isinstance(p, Parameter):\\n l.append(p)\\n return l\",\n \"def parameter_values(self) -> List[Tuple[str, Any]]:\\n pvs = [(param, getattr(self, variable))\\n for variable, param in self.variable_name_to_query_param.items()]\\n return [(p, v) for p, v in pvs if v is not None]\",\n \"def get_params(self):\\n raise NotImplementedError\",\n \"def params():\\n raise NotImplementedError\",\n \"def compile_parameter_list(self):\\r\\n if self.__tokenizer.token_type() != TYPES_DIC[\\\"SYMBOL\\\"]:\\r\\n type = self.__get_type()\\r\\n self.__advance()\\r\\n name = self.__tokenizer.identifier()\\r\\n self.__subroutine_symbols.define(name, type, \\\"argument\\\")\\r\\n self.__advance()\\r\\n while self.__tokenizer.symbol() != ')':\\r\\n self.__advance()\\r\\n type = self.__get_type()\\r\\n self.__advance()\\r\\n name = self.__tokenizer.identifier()\\r\\n self.__subroutine_symbols.define(name, type, \\\"argument\\\")\\r\\n self.__advance()\",\n \"def getdefflags(config_nm):\\n if config_nm is 'train':\\n user_params = user_params_train\\n elif config_nm is 'eval':\\n user_params = user_params_eval\\n elif config_nm is 'tfrecorder':\\n user_params = user_params_recorder\\n else:\\n print('Unrecognized configuration name : %s, exiting ....' % config_nm)\\n exit(-1)\\n\\n\\n return mandatory_params+user_params\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7988936","0.74989027","0.7314254","0.7287591","0.72515583","0.7218516","0.71054345","0.70339245","0.7012955","0.6996692","0.6981282","0.6979131","0.69392234","0.68479455","0.68444264","0.6826156","0.6822841","0.6799787","0.67326","0.6730319","0.6724998","0.6699051","0.6652106","0.6650752","0.66370994","0.6635843","0.6581524","0.6579941","0.6564477","0.6564477","0.65341514","0.6504907","0.6499476","0.64166737","0.64159924","0.6415853","0.6413363","0.6409981","0.64073926","0.64051133","0.63949585","0.6385912","0.6316737","0.6310994","0.6306765","0.6289181","0.62744194","0.62741125","0.6269139","0.6265924","0.62619495","0.6256635","0.6242426","0.6238863","0.62318146","0.6216613","0.6211803","0.62084424","0.6189837","0.6168737","0.6160903","0.61533123","0.6147536","0.6147536","0.61365825","0.6132048","0.61200714","0.6119378","0.6119378","0.61187613","0.6108518","0.6091053","0.60908747","0.607988","0.6048925","0.604111","0.6040503","0.602842","0.6028142","0.6022022","0.60192996","0.60110176","0.59981614","0.5994884","0.5993239","0.5987149","0.597894","0.5976208","0.5971746","0.59715027","0.5966833","0.5965733","0.59590274","0.5945239","0.5943772","0.5937218","0.5930109","0.59291315","0.59285045","0.5927728"],"string":"[\n \"0.7988936\",\n \"0.74989027\",\n \"0.7314254\",\n \"0.7287591\",\n \"0.72515583\",\n \"0.7218516\",\n \"0.71054345\",\n \"0.70339245\",\n \"0.7012955\",\n \"0.6996692\",\n \"0.6981282\",\n \"0.6979131\",\n \"0.69392234\",\n \"0.68479455\",\n \"0.68444264\",\n \"0.6826156\",\n \"0.6822841\",\n \"0.6799787\",\n \"0.67326\",\n \"0.6730319\",\n \"0.6724998\",\n \"0.6699051\",\n \"0.6652106\",\n \"0.6650752\",\n \"0.66370994\",\n \"0.6635843\",\n \"0.6581524\",\n \"0.6579941\",\n \"0.6564477\",\n \"0.6564477\",\n \"0.65341514\",\n \"0.6504907\",\n \"0.6499476\",\n \"0.64166737\",\n \"0.64159924\",\n \"0.6415853\",\n \"0.6413363\",\n \"0.6409981\",\n \"0.64073926\",\n \"0.64051133\",\n \"0.63949585\",\n \"0.6385912\",\n \"0.6316737\",\n \"0.6310994\",\n \"0.6306765\",\n \"0.6289181\",\n \"0.62744194\",\n \"0.62741125\",\n \"0.6269139\",\n \"0.6265924\",\n \"0.62619495\",\n \"0.6256635\",\n \"0.6242426\",\n \"0.6238863\",\n \"0.62318146\",\n \"0.6216613\",\n \"0.6211803\",\n \"0.62084424\",\n \"0.6189837\",\n \"0.6168737\",\n \"0.6160903\",\n \"0.61533123\",\n \"0.6147536\",\n \"0.6147536\",\n \"0.61365825\",\n \"0.6132048\",\n \"0.61200714\",\n \"0.6119378\",\n \"0.6119378\",\n \"0.61187613\",\n \"0.6108518\",\n \"0.6091053\",\n \"0.60908747\",\n \"0.607988\",\n \"0.6048925\",\n \"0.604111\",\n \"0.6040503\",\n \"0.602842\",\n \"0.6028142\",\n \"0.6022022\",\n \"0.60192996\",\n \"0.60110176\",\n \"0.59981614\",\n \"0.5994884\",\n \"0.5993239\",\n \"0.5987149\",\n \"0.597894\",\n \"0.5976208\",\n \"0.5971746\",\n \"0.59715027\",\n \"0.5966833\",\n \"0.5965733\",\n \"0.59590274\",\n \"0.5945239\",\n \"0.5943772\",\n \"0.5937218\",\n \"0.5930109\",\n \"0.59291315\",\n \"0.59285045\",\n \"0.5927728\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.61655676"},"document_rank":{"kind":"string","value":"60"}}},{"rowIdx":88587,"cells":{"query":{"kind":"string","value":"Finds the fully qualified parameter name for the name given by param"},"document":{"kind":"string","value":"def findParam(self, param, findall=False):\n param = param.replace('*', '').strip()\n if not param:\n if not findall:\n return\n return []\n if param in self._fuparhist and not findall:\n return self._fuparhist[param]\n p = param.split('.')\n if len(p) not in (1, 2):\n if not findall:\n return\n return []\n if len(p) == 1 or not p[0]:\n fulist = self.getFuList()\n else:\n fulist = [fu for fu in self.getFuList() if fu.upper() == p[0].upper()]\n parlist = []\n for fu in fulist:\n for par in self.getFuParList(fu):\n if p[-1].upper() == par.upper():\n parlist.append('%s.%s' % (fu, par))\n if not findall:\n break\n\n if not findall and parlist:\n break\n\n if parlist:\n if len(parlist) == 1:\n self._fuparhist[param] = '%s' % parlist[0]\n if findall:\n return parlist\n return parlist[0]\n if findall:\n return []\n return"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def param_name(p):\n prefix = ['limit_', 'error_', 'fix_']\n for prf in prefix:\n if p.startswith(prf):\n return p[len(prf):]\n return p","def get_param_name(self, param_id, syselem):\n\n with self.__connection.cursor() as cursor:\n query = \"SELECT NAME FROM %s WHERE PID= '%s' AND SYSTEM_ELEMENT= '%s'\" % (self.__schema, param_id, syselem)\n cursor.execute(query)\n result = cursor.fetchone()\n return result['NAME']","def get_param_filter_name(cls, param, rel=None):\n # check for empty param\n if not param:\n return param\n\n # strip the rel prefix from the param name.\n prefix = '%s%s' % (rel or '', LOOKUP_SEP)\n if rel and param.startswith(prefix):\n param = param[len(prefix):]\n\n # Attempt to match against filters with lookups first. (username__endswith)\n if param in cls.base_filters:\n return param\n\n # Attempt to match against exclusion filters\n if param[-1] == '!' and param[:-1] in cls.base_filters:\n return param[:-1]\n\n # Match against relationships. (author__username__endswith).\n # Preference more specific filters. eg, `note__author` over `note`.\n for name in reversed(sorted(cls.related_filters)):\n # we need to match against '__' to prevent eager matching against\n # like names. eg, note vs note2. Exact matches are handled above.\n if param.startswith(\"%s%s\" % (name, LOOKUP_SEP)):\n return name","def _get_variable_name(param_name):\n m = re.match(\"^(.*):\\\\d+$\", param_name)\n if m is not None:\n param_name = m.group(1)\n return param_name","def _get_variable_name(self, param_name):\n m = re.match(\"^(.*):\\\\d+$\", param_name)\n if m is not None:\n param_name = m.group(1)\n return param_name","def _get_variable_name(self, param_name):\n m = re.match(\"^(.*):\\\\d+$\", param_name)\n if m is not None:\n param_name = m.group(1)\n return param_name","def _get_variable_name(self, param_name):\n m = re.match(\"^(.*):\\\\d+$\", param_name)\n if m is not None:\n param_name = m.group(1)\n return param_name","def _get_variable_name(self, param_name):\n m = re.match(\"^(.*):\\\\d+$\", param_name)\n if m is not None:\n param_name = m.group(1)\n return param_name","def _get_variable_name(self, param_name):\n m = re.match(\"^(.*):\\\\d+$\", param_name)\n if m is not None:\n param_name = m.group(1)\n return param_name","def get_param(self, name: str, depth: int = 0) -> \"Param\":\n parts: List[str] = name.split(\".\")\n if depth < len(parts) - 1:\n part = parts[depth + 1]\n if part not in self._stack:\n return None\n if not isinstance(\n self._stack[part], # type: ignore\n ParamNamespace,\n ):\n return self._stack[part] # type: ignore\n return self._stack[part].get_param(name, depth + 1) # type: ignore\n if name in self.names:\n return self\n return None","def _get_variable_name(self, param_name):\n m = re.match(\"^(.*):\\\\d+$\", six.ensure_str(param_name))\n if m is not None:\n param_name = m.group(1)\n return param_name","def _get_variable_name(self, param_name):\n m = re.match(\"^(.*):\\\\d+$\", six.ensure_str(param_name))\n if m is not None:\n param_name = m.group(1)\n return param_name","def _get_variable_name(self, param_name):\n m = re.match(\"^(.*):\\\\d+$\", param_name)\n if m is not None:\n param_name = m.group(1)\n return param_name","def _get_variable_name(self, param_name):\n m = re.match(\"^(.*):\\\\d+$\", param_name)\n if m is not None:\n param_name = m.group(1)\n return param_name","def _get_variable_name(self, param_name):\n m = re.match(\"^(.*):\\\\d+$\", param_name)\n if m is not None:\n param_name = m.group(1)\n return param_name","def get_param_with_name(self, param_name):\n return self.params[param_name]","def _get_param_doc(self, param_name: str) -> Optional[DocstringParam]:\n for param in self._doc.params:\n if param.arg_name == param_name:\n return param\n\n return None","def AttributeName(self, param_name):\n for attribute_name, p in six.iteritems(self.attribute_to_params_map):\n if p == param_name:\n return attribute_name","def _get_one_param(self, param_name):\n return getattr(self, '__' + param_name)","def get_parameter(request, param):\n if param == \"Params\":\n return request.split(\"\\r\\n\\r\\n\")[1]\n if isinstance(param, type([])):\n return [request.split(\"\\r\\n\\r\\n\")[1] if x == \"Param\" else request.split(x + \": \")[1].split(\"\\r\\n\")[0] for x in param]\n if isinstance(param, type(\"\")):\n return request.split(param + \": \")[1].split(\"\\r\\n\")[0]","def getParam(self,param):\n if param in self.params.keys():\n return self.params[param]\n else:\n return None","def get_param(self, param_name, memo=None):\n # Cast param_name to str once, for convenience:\n # (This is needed because Parameter members are Enum objects,\n # which can't be used in place of string-valued indexes)\n param_name = str(param_name)\n explicit_attr = getattr(self, param_name)\n if explicit_attr is not None:\n return explicit_attr\n else:\n return self.build_param(param_name, memo=memo)","def _get_param_to_param_name(\n model: torch.nn.Module,\n) -> Dict[torch.nn.Parameter, str]:\n param_to_param_names = _get_param_to_unflat_param_names(model)\n for param_names in param_to_param_names.values():\n assert len(param_names) > 0, \"`_get_param_to_unflat_param_names()` \" \\\n \"should not construct empty lists\"\n if len(param_names) > 1:\n raise RuntimeError(\n \"Each parameter should only map to one parameter name but got \"\n f\"{len(param_names)}: {param_names}\"\n )\n param_to_param_name = {\n param: param_names[0]\n for param, param_names in param_to_param_names.items()\n }\n return param_to_param_name","def get_parameter_value_by_fully_qualified_parameter_name(\n fully_qualified_parameter_name: str,\n domain: Optional[Domain] = None,\n variables: Optional[ParameterContainer] = None,\n parameters: Optional[Dict[str, ParameterContainer]] = None,\n) -> Optional[Union[Any, ParameterNode]]:\n validate_fully_qualified_parameter_name(\n fully_qualified_parameter_name=fully_qualified_parameter_name\n )\n\n # Using \"__getitem__\" (bracket) notation instead of \"__getattr__\" (dot) notation in order to insure the\n # compatibility of field names (e.g., \"domain_kwargs\") with user-facing syntax (as governed by the value of the\n # DOMAIN_KWARGS_PARAMETER_NAME constant, which may change, requiring the same change to the field name).\n if fully_qualified_parameter_name == DOMAIN_KWARGS_PARAMETER_FULLY_QUALIFIED_NAME:\n if domain:\n # Supports the \"$domain.domain_kwargs\" style syntax.\n return domain[DOMAIN_KWARGS_PARAMETER_NAME]\n return None\n\n if fully_qualified_parameter_name.startswith(\n DOMAIN_KWARGS_PARAMETER_FULLY_QUALIFIED_NAME\n ):\n if domain and domain[DOMAIN_KWARGS_PARAMETER_NAME]:\n # Supports the \"$domain.domain_kwargs.column\" style syntax.\n return domain[DOMAIN_KWARGS_PARAMETER_NAME].get(\n fully_qualified_parameter_name[\n (len(DOMAIN_KWARGS_PARAMETER_FULLY_QUALIFIED_NAME) + 1) :\n ]\n )\n return None\n\n parameter_container: ParameterContainer\n\n if fully_qualified_parameter_name.startswith(VARIABLES_KEY):\n fully_qualified_parameter_name = fully_qualified_parameter_name[1:]\n parameter_container = variables\n else:\n fully_qualified_parameter_name = fully_qualified_parameter_name[1:]\n parameter_container = parameters[domain.id]\n\n fully_qualified_parameter_name_as_list: List[\n str\n ] = fully_qualified_parameter_name.split(\n FULLY_QUALIFIED_PARAMETER_NAME_SEPARATOR_CHARACTER\n )\n\n if len(fully_qualified_parameter_name_as_list) == 0:\n return None\n\n return _get_parameter_value_from_parameter_container(\n fully_qualified_parameter_name=fully_qualified_parameter_name,\n fully_qualified_parameter_name_as_list=fully_qualified_parameter_name_as_list,\n parameter_container=parameter_container,\n )","def get_param(self, param_name):\n if hasattr(self, param_name):\n return getattr(self, param_name)\n else:\n return None","def param_name(self):\n return self._param_name","def get_param(self, param):\n return self.params.get(param, None)","def _get_arg_name(self, arg, variable_name):","def get_parameter(self, param):\n try:\n result = self._data[\"queryResult\"][\"parameters\"][param]\n except KeyError:\n result = None\n\n return result","def check_param(param):\n return PREPEND_STR+param if keyword.iskeyword(param) else param","def get_param(query, config):\n keys = query.split('.')\n if len(keys) == 1:\n key = keys[0]\n if not config.has_key(key):\n return None\n return config[key]\n else:\n return Config.get_nested_param(keys, config)","def find_param(self, ptype, name):\n param_to_find = PBRTParam(ptype, name)\n for p in self._data:\n if p == param_to_find:\n return p\n return None","def _search_param_in_docstr(docstr, param_str):\n # look at #40 to see definitions of those params\n patterns = [re.compile(p % re.escape(param_str))\n for p in DOCSTRING_PARAM_PATTERNS]\n for pattern in patterns:\n match = pattern.search(docstr)\n if match:\n return _strip_rest_role(match.group(1))\n\n return None","def get_parameter(self, name: str) -> any:\r\n if name in self.kwargs:\r\n return self.kwargs[name]\r\n for x in self.args:\r\n if isinstance(x, dict) and name in x:\r\n return x[name]\r\n else:\r\n return None","def getParam(self, params, name):\n return params.get(name)","def _get_param_from_request(self, nombreParametro):\n\t\treturn request.args.get(nombreParametro)","def _AttributeName(self, param_name, attribute_config, anchor=False):\n if attribute_config.attribute_name:\n return attribute_config.attribute_name\n if anchor:\n return 'name'\n return param_name.replace('Id', '_id').lower()","def id_func(param):\n if isinstance(param, dict) and \":name:\" in param:\n return param[\":name:\"]\n\n retval = str(param)\n if len(retval) > 25:\n retval = retval[:20] + \"...\" + retval[-2:]\n return retval","def id_func(param):\n if isinstance(param, dict) and \":name:\" in param:\n return param[\":name:\"]\n\n retval = str(param)\n if len(retval) > 25:\n retval = retval[:20] + \"...\" + retval[-2:]\n return retval","def get_param_re_names(self, param_name_re, syselem):\n\n with self.__connection.cursor() as cursor:\n query = \"SELECT PID FROM %s WHERE NAME LIKE '%s' AND SYSTEM_ELEMENT= '%s'\" % (self.__schema, param_name_re, syselem)\n cursor.execute(query)\n result = cursor.fetchone()\n return result['PID']","def lookup_name(self, name, default=None):\n for frames in reversed(self._arg_transformer):\n if name in frames:\n return frames[name]\n return name if default is None else default","def get_param_from_container(param, container):\n if param in container.params:\n param = container.params[param]\n if param in container:\n param = container.get(param)\n elif param in container:\n param = container.get(param)\n else:\n if isinstance(param, FunctionType):\n param = param(container)\n return param","def get_rule_param_type(\n self, rule_name: str, rule_param_name: str\n ) -> objects.BaseObject:\n rule_param_list = self.get_rule_param_list(rule_name)\n\n for param_name, param_type in rule_param_list:\n if param_name == rule_param_name:\n return param_type\n raise Exception(\n 'Rule %s has no param called %s' % (rule_name, rule_param_name))","def _parse_module_name(program_param):\n if program_param and program_param.endswith(\".py\"):\n return program_param[:-3]\n return program_param","def getParam(self, paramName):\n for pname, pvalue in self.neededParamsNames.items():\n if pvalue[0] == paramName:\n if paramName in self.neededParams:\n return self.neededParams[paramName]\n for pname, pvalue in self.optionalParamsNames.items():\n if pvalue[0] == paramName:\n if paramName in self.optionalParams:\n return self.optionalParams[paramName]\n else:\n return pvalue[2]\n print >> sys.stderr, \"Coding error: param\", paramName,\"is not\",\\\n \"among the available options\"\n sys.exit(1)","def get_parameter_by_label(self, label):\n \n for attr in self.parm_list:\n if attr.label == label:\n return attr\n\n self.logging.error(\"Can't find topic: \"+label)\n return None","def get_underlying_parameter(self, rel_name):\n return self._declaration[rel_name].underlying_parameter # pytype: disable=bad-return-type","def get_parameter(par_name):\r\n config_file = open('./config.txt', 'r')\r\n lines = config_file.readlines()\r\n for line in lines:\r\n line = line.rstrip('\\n\\r')\r\n if line.startswith(par_name):\r\n return line.split('=')[1]","def checkreplaceparam(stdpardict, functypepardict, parsuffix):\n try:\n ftpara = next(v for k, v in functypepardict.items() if k.endswith(parsuffix))\n return ftpara\n except StopIteration:\n try:\n return next(v for k, v in stdpardict.items() if k.endswith(parsuffix))\n except StopIteration:\n #return 'Parameter not defined or not passed to class'\n raise Exception('Parameter {} is not found in Parameters passed to SV class'.format(parsuffix))","def get_param(self, name):\n for param in self._parameters:\n if name == param._name:\n return param\n pass\n new_param = self._add_param(name)\n return new_param","def get_parameter(key):\n if key in param_dict:\n # was a supplied parameter\n param = param_dict.get(key)\n elif module and hasattr(module, key):\n param = getattr(module, key)\n if hasattr(param, \"__call__\"):\n # we don't allow module methods\n raise Exception()\n elif attr_getter:\n # get value from attr_getter function\n try:\n param = attr_getter(key)\n except: # noqa e722\n raise Exception()\n else:\n raise Exception()\n if isinstance(param, Composite):\n if param.text():\n param = param.copy()\n else:\n param = \"\"\n return param","def parameterName(self):\n return self.name()","def extract_name_description(self, param):\n name = None\n description = None\n if getattr(param, 'description', None):\n description = param.description\n\n if getattr(param, 'primary_name', None):\n name = param.primary_name\n elif getattr(param, 'param_type', None):\n if getattr(param.param_type, 'name', None):\n name = param.param_type.name\n if not description and getattr(param.param_type, 'description', None):\n description = param.param_type.description\n elif getattr(param.param_type, 'element_type', None) and \\\n getattr(param.param_type.element_type, 'name', None):\n name = param.param_type.element_type.name\n if not description and getattr(param.param_type.element_type, 'description', None):\n description = param.param_type.element_type.description\n\n return self.replace_sync(name), self.extract_description(description)","def get_parameter(cur, par):\n cur.execute(\"SELECT value FROM parameters WHERE par='%s';\" % par)\n return cur.fetchone()[0]","def GetUniqueParam(self, name):\n if not hasattr(self, '_params'):\n self._params = cgi.parse_qs(self.path[self.path.find('?') + 1:])\n\n param_list = self._params.get(name, [])\n if len(param_list) == 1:\n return param_list[0]\n return None","def extractparam(pardict, parsuffix):\n return next(v for k, v in pardict.items() if k.endswith(parsuffix))","def fix_default_param(defparam, classname):\n if (classname + '::') == defparam[0:len(classname)+2:]:\n return defparam[len(classname)+2::]\n #if defparam[len(defparam)-1] == \"f\":\n # return defparam[0:len(defparam)-1]\n return defparam","def get_name(internal: str):\n if '__' in internal:\n return ': '.join(get_name(s) for s in internal.split('__'))\n *path, name = internal.split('::')\n current = config.utils.names\n look_in = [current]\n try:\n for k in path:\n current = current[k]\n look_in.append(current)\n except KeyError:\n # noinspection PyUnboundLocalVariable\n logging.warning('invalid namespace {!r} of {!r}'.format(k, internal))\n look_in.reverse()\n for ns in look_in:\n try:\n val = ns[name]\n if isinstance(val, str):\n return val\n elif isinstance(val, dict):\n return val['*this*']\n else:\n raise TypeError('{!r} is neither dict nor str'.format(val))\n except KeyError:\n pass\n logging.warning('Name \"{}\" was not found in the namefile'.format('::'.join(path+[name])))\n return '::'.join(path+[name])","def findParam(posName, startIndex, endIndex):\r\n for i in range(startIndex, endIndex):\r\n if allParamNodes[i].getAttribute('position') == posName:\r\n return manager.parameters[i]\r\n \r\n raise Exception('Problem resolving parameter to J Matrix from xml file')","def get_qname(uri, name):\n if not uri or not name or name[0] in ('{', '.', '/', '['):\n return name\n else:\n return '{%s}%s' % (uri, name)","def _name(self):\n return self.arguments[0].split('(')[0]","def get_name(self) -> str:\n # read the original value passed by the command\n name = self.raw_param.get(\"name\")\n\n # this parameter does not need dynamic completion\n # this parameter does not need validation\n return name","def _detect_source_param_class(self, param):\n if self.config[\"source\"][\"parameter\"][\"name\"] == param:\n return self.config[\"source\"][\"parameter\"][\"class\"]\n else:\n return None","def _name(self):\n return self._arguments[0].split('(')[0]","def getparam(name, default=None, stash=None, params=None):\n v = getparamlist(name, stash=stash, params=params)\n if len(v) > 0: return v[0]\n return default","def get_param(name, dictionary):\n if (\"templates_dict\" in dictionary):\n dictionary = dictionary[\"templates_dict\"]\n if (name in dictionary):\n return dictionary[name]\n raise KeyError(\"'{}' was not found in context.\".format(name))","def _resolve_name(self, cls, name):\n attrs = name.split('.')\n part = cls\n while attrs:\n attr = attrs.pop(0)\n part = getattr(part, attr, UNSET)\n if part is UNSET:\n return name\n if not isinstance(part, basestring):\n raise TypeError(\"Invalid key: {!r}\".format(part))\n return part","def _find_by_name(details: CallableDetails, name: str):\n arg = details.arg_by_name(name)\n if not arg:\n raise IncompatibleHandlerFactoryError(\n f\"Callable {details.obj!r} has no argument named {name}\"\n )\n return arg","def build_path_to_parameter(\n parameter_set: DwdObservationDataset,\n resolution: Resolution,\n period: Period,\n) -> str:\n if parameter_set == DwdObservationDataset.SOLAR and resolution in (\n Resolution.HOURLY,\n Resolution.DAILY,\n ):\n return f\"{resolution.value}/{parameter_set.value}/\"\n\n return f\"{resolution.value}/{parameter_set.value}/{period.value}/\"","def _get_name(name):\n if \"::\" in name:\n return name.split(\"::\")[1]\n return name","def _get_name(name):\n if \"::\" in name:\n return name.split(\"::\")[1]\n return name","def function_name(parameters):","def get_param_id(self, param_name, syselem):\n\n with self.__connection.cursor() as cursor:\n query = \"SELECT PID FROM %s WHERE NAME= '%s' AND SYSTEM_ELEMENT= '%s'\" % (self.__schema, param_name, syselem)\n cursor.execute(query)\n result = cursor.fetchone()\n return result['PID']","def get_parameter_type(self, name):\n phil_scope = phil.parse(\n \"\"\"include scope dials.command_line.scale.phil_scope\"\"\",\n process_includes=True,\n )\n obj = phil.find_scope(phil_scope, name)\n if not obj:\n raise ValueError(\n \"\"\"Unable to resolve %s in the phil scope, make sure full phil path\nis provided. For example, physical.decay_correction rather than decay_correction\"\"\"\n % name\n )\n return obj.type.phil_type # a str: \"int\", \"bool\" etc","def get_name_query_cond(column: str, val: str, query_params: dict):\n if val is not None and column is not None:\n query_params[column] = '%' + val + '%'\n return 'AHJ.' + column + ' LIKE %(' + column + ')s AND '\n return ''","def local_defect_name(global_name):\n return global_name.split(':')[-1]","def _get_ssm_param(self, parameter_name):\n response = self.ssm_client.get_parameter(Name=parameter_name)\n res = response.get(\"Parameter\", {})\n cwa_parameter = res.get(\"Value\", {})\n return cwa_parameter","def getParameter(self, name):","def _get_unique_param_name(self, name, mode):\n _name = name\n inc = 1\n \n if mode == NodeParam.INPUT:\n existing_params = self._input_params\n else:\n existing_params = self._output_params\n \n while _name in existing_params:\n _name = \"%s%i\" % (name, inc) \n inc += 1 \n return _name","def getName(self):\n return _libsbml.Parameter_getName(self)","def retrieve_name(var):\n for fi in reversed(inspect.stack()):\n names = [var_name for var_name, var_val in fi.frame.f_locals.items() if var_val is var]\n if len(names) > 0:\n return names[0]","def get_parameter(self, topic):\n \n for attr in self.parm_list:\n if attr.topic == topic:\n return attr\n\n self.logging.error(\"Can't find topic: \"+topic)\n return None","def find_qualified_name(filename, max_iterations=5):\n filename = os.path.abspath(filename)\n vc_root = find_vc_root(filename, max_iterations)\n _, name = filename.split(f\"{vc_root}/\")\n if name.endswith(\".py\"):\n name = name[:-3]\n return name.replace(\"/\", \".\")","def normalize_parameter(parameter: str, expression: str) -> Tuple[Optional[str], str, str]:\n try:\n # The parameter name is prefixed with its location. Example: `path.id`\n location, name = tuple(parameter.split(\".\"))\n return location, name, expression\n except ValueError:\n return None, parameter, expression","def get_parameter_domain(self, parameter_name):\n pgraph = self.solver_binary.solver.parameter_graph[0].serializedGraph\n if pgraph is None: return None\n tree = etree.parse(StringIO(pgraph))\n if tree is None: return None\n root = tree.getroot()\n for node in root:\n if node.tag == \"parameters\" and node[1].text == parameter_name:\n return node[0].attrib.values()[0]","def _name_from_args(func, _, params):\n return \"{}_{}\".format(func.__name__, \"_\".join(str(arg) for arg in params.args))","def register_param(param: Type[Param]) -> None:\n for alias in param.type_aliases + [param.type]:\n if alias in TYPE_NAMES:\n raise PyParamNameError(\n \"Type name has already been \" f\"registered: {alias}\"\n )\n TYPE_NAMES[alias] = param.type\n\n PARAM_MAPPINGS[param.type] = param\n param.on_register()","def _formal_params(self, doclet):\n name, paren, params = self.arguments[0].partition('(')\n return ('(%s' % params) if params else '(%s)' % ', '.join(doclet['meta']['code']['paramnames'])","def get_query_parameter(self,original_name: Optional[str] = None) -> str:\n if not original_name:\n raise TypeError(\"original_name cannot be null.\")\n if original_name == \"count\":\n return \"%24count\"\n if original_name == \"expand\":\n return \"%24expand\"\n if original_name == \"filter\":\n return \"%24filter\"\n if original_name == \"orderby\":\n return \"%24orderby\"\n if original_name == \"search\":\n return \"%24search\"\n if original_name == \"select\":\n return \"%24select\"\n if original_name == \"skip\":\n return \"%24skip\"\n if original_name == \"top\":\n return \"%24top\"\n return original_name","def get_query_parameter(self,original_name: Optional[str] = None) -> str:\n if not original_name:\n raise TypeError(\"original_name cannot be null.\")\n if original_name == \"count\":\n return \"%24count\"\n if original_name == \"expand\":\n return \"%24expand\"\n if original_name == \"filter\":\n return \"%24filter\"\n if original_name == \"orderby\":\n return \"%24orderby\"\n if original_name == \"search\":\n return \"%24search\"\n if original_name == \"select\":\n return \"%24select\"\n if original_name == \"skip\":\n return \"%24skip\"\n if original_name == \"top\":\n return \"%24top\"\n return original_name","def gui_get_param(self,param_name):\n return self._tkvars[param_name].get()","def lookup(name):","def lookup(name):","def retrieve_name(self, var):\r\n\t\tfor fi in reversed(inspect.stack()):\r\n\t\t\tnames = [var_name for var_name, var_val in fi.frame.f_locals.items() if var_val is var]\r\n\t\t\tif len(names) > 0:\r\n\t\t\t\treturn names[0]\r\n\t\treturn \"<unknown>\"","def ParamName(self, attribute_name):\n if attribute_name not in self.attribute_to_params_map:\n raise ValueError(\n 'No param name found for attribute [{}]. Existing attributes are '\n '[{}]'.format(attribute_name,\n ', '.join(sorted(self.attribute_to_params_map.keys()))))\n return self.attribute_to_params_map[attribute_name]","def rename_param(self, param, name):\n old_name = param.name\n new_name = self._get_unique_param_name(name, param.mode)\n \n param._name = new_name\n \n if param.mode == NodeParam.INPUT:\n self._input_params.pop(old_name)\n self._input_params[new_name] = param\n else:\n self._output_params.pop(old_name)\n self._output_params[new_name] = param\n \n return new_name","def namedModelParameter(self, s):\n try:\n idx = self.parameterNames.index(s)\n except ValueError:\n return None\n \n if idx >= len(self.stateVector):\n idx -= len(self.stateVector)\n val = self.otherModelParameters[idx]\n else:\n val = self.stateVector[idx]\n \n return val","def fully_qualified_name(self) -> str:\n return pulumi.get(self, \"fully_qualified_name\")","def param_lookup(param_fpath, param_name, version=-999):\n\n # save the column names and read the last line of parameters in a params.csv file\n params_csv_object = open(param_fpath, 'rU')\n lines = csv.reader(params_csv_object)\n keys = lines.next() # save column names as keys\n for line in lines:\n if line[3]: # check that data is present, any extra blank lines saved at end of file won't override real data\n params = line\n read_version = int(params[0])\n # break out of the loop once the target parameter version have been read, if specified\n if read_version == version:\n break\n params_csv_object.close()\n print \"Updating .100 files based on parameter version %i...\" % read_version\n\n # propagate parameter data into dictionary\n dictionary = {}\n for i, key in enumerate(keys):\n dictionary[key] = params[i]\n\n return dictionary[param_name]","def get_parameter(name, parameter, path=None):\n _ensure_exists(name, path=path)\n cmd = \"lxc-cgroup\"\n if path:\n cmd += f\" -P {shlex.quote(path)}\"\n cmd += f\" -n {name} {parameter}\"\n ret = __salt__[\"cmd.run_all\"](cmd, python_shell=False)\n if ret[\"retcode\"] != 0:\n raise CommandExecutionError(f\"Unable to retrieve value for '{parameter}'\")\n return ret[\"stdout\"].strip()"],"string":"[\n \"def param_name(p):\\n prefix = ['limit_', 'error_', 'fix_']\\n for prf in prefix:\\n if p.startswith(prf):\\n return p[len(prf):]\\n return p\",\n \"def get_param_name(self, param_id, syselem):\\n\\n with self.__connection.cursor() as cursor:\\n query = \\\"SELECT NAME FROM %s WHERE PID= '%s' AND SYSTEM_ELEMENT= '%s'\\\" % (self.__schema, param_id, syselem)\\n cursor.execute(query)\\n result = cursor.fetchone()\\n return result['NAME']\",\n \"def get_param_filter_name(cls, param, rel=None):\\n # check for empty param\\n if not param:\\n return param\\n\\n # strip the rel prefix from the param name.\\n prefix = '%s%s' % (rel or '', LOOKUP_SEP)\\n if rel and param.startswith(prefix):\\n param = param[len(prefix):]\\n\\n # Attempt to match against filters with lookups first. (username__endswith)\\n if param in cls.base_filters:\\n return param\\n\\n # Attempt to match against exclusion filters\\n if param[-1] == '!' and param[:-1] in cls.base_filters:\\n return param[:-1]\\n\\n # Match against relationships. (author__username__endswith).\\n # Preference more specific filters. eg, `note__author` over `note`.\\n for name in reversed(sorted(cls.related_filters)):\\n # we need to match against '__' to prevent eager matching against\\n # like names. eg, note vs note2. Exact matches are handled above.\\n if param.startswith(\\\"%s%s\\\" % (name, LOOKUP_SEP)):\\n return name\",\n \"def _get_variable_name(param_name):\\n m = re.match(\\\"^(.*):\\\\\\\\d+$\\\", param_name)\\n if m is not None:\\n param_name = m.group(1)\\n return param_name\",\n \"def _get_variable_name(self, param_name):\\n m = re.match(\\\"^(.*):\\\\\\\\d+$\\\", param_name)\\n if m is not None:\\n param_name = m.group(1)\\n return param_name\",\n \"def _get_variable_name(self, param_name):\\n m = re.match(\\\"^(.*):\\\\\\\\d+$\\\", param_name)\\n if m is not None:\\n param_name = m.group(1)\\n return param_name\",\n \"def _get_variable_name(self, param_name):\\n m = re.match(\\\"^(.*):\\\\\\\\d+$\\\", param_name)\\n if m is not None:\\n param_name = m.group(1)\\n return param_name\",\n \"def _get_variable_name(self, param_name):\\n m = re.match(\\\"^(.*):\\\\\\\\d+$\\\", param_name)\\n if m is not None:\\n param_name = m.group(1)\\n return param_name\",\n \"def _get_variable_name(self, param_name):\\n m = re.match(\\\"^(.*):\\\\\\\\d+$\\\", param_name)\\n if m is not None:\\n param_name = m.group(1)\\n return param_name\",\n \"def get_param(self, name: str, depth: int = 0) -> \\\"Param\\\":\\n parts: List[str] = name.split(\\\".\\\")\\n if depth < len(parts) - 1:\\n part = parts[depth + 1]\\n if part not in self._stack:\\n return None\\n if not isinstance(\\n self._stack[part], # type: ignore\\n ParamNamespace,\\n ):\\n return self._stack[part] # type: ignore\\n return self._stack[part].get_param(name, depth + 1) # type: ignore\\n if name in self.names:\\n return self\\n return None\",\n \"def _get_variable_name(self, param_name):\\n m = re.match(\\\"^(.*):\\\\\\\\d+$\\\", six.ensure_str(param_name))\\n if m is not None:\\n param_name = m.group(1)\\n return param_name\",\n \"def _get_variable_name(self, param_name):\\n m = re.match(\\\"^(.*):\\\\\\\\d+$\\\", six.ensure_str(param_name))\\n if m is not None:\\n param_name = m.group(1)\\n return param_name\",\n \"def _get_variable_name(self, param_name):\\n m = re.match(\\\"^(.*):\\\\\\\\d+$\\\", param_name)\\n if m is not None:\\n param_name = m.group(1)\\n return param_name\",\n \"def _get_variable_name(self, param_name):\\n m = re.match(\\\"^(.*):\\\\\\\\d+$\\\", param_name)\\n if m is not None:\\n param_name = m.group(1)\\n return param_name\",\n \"def _get_variable_name(self, param_name):\\n m = re.match(\\\"^(.*):\\\\\\\\d+$\\\", param_name)\\n if m is not None:\\n param_name = m.group(1)\\n return param_name\",\n \"def get_param_with_name(self, param_name):\\n return self.params[param_name]\",\n \"def _get_param_doc(self, param_name: str) -> Optional[DocstringParam]:\\n for param in self._doc.params:\\n if param.arg_name == param_name:\\n return param\\n\\n return None\",\n \"def AttributeName(self, param_name):\\n for attribute_name, p in six.iteritems(self.attribute_to_params_map):\\n if p == param_name:\\n return attribute_name\",\n \"def _get_one_param(self, param_name):\\n return getattr(self, '__' + param_name)\",\n \"def get_parameter(request, param):\\n if param == \\\"Params\\\":\\n return request.split(\\\"\\\\r\\\\n\\\\r\\\\n\\\")[1]\\n if isinstance(param, type([])):\\n return [request.split(\\\"\\\\r\\\\n\\\\r\\\\n\\\")[1] if x == \\\"Param\\\" else request.split(x + \\\": \\\")[1].split(\\\"\\\\r\\\\n\\\")[0] for x in param]\\n if isinstance(param, type(\\\"\\\")):\\n return request.split(param + \\\": \\\")[1].split(\\\"\\\\r\\\\n\\\")[0]\",\n \"def getParam(self,param):\\n if param in self.params.keys():\\n return self.params[param]\\n else:\\n return None\",\n \"def get_param(self, param_name, memo=None):\\n # Cast param_name to str once, for convenience:\\n # (This is needed because Parameter members are Enum objects,\\n # which can't be used in place of string-valued indexes)\\n param_name = str(param_name)\\n explicit_attr = getattr(self, param_name)\\n if explicit_attr is not None:\\n return explicit_attr\\n else:\\n return self.build_param(param_name, memo=memo)\",\n \"def _get_param_to_param_name(\\n model: torch.nn.Module,\\n) -> Dict[torch.nn.Parameter, str]:\\n param_to_param_names = _get_param_to_unflat_param_names(model)\\n for param_names in param_to_param_names.values():\\n assert len(param_names) > 0, \\\"`_get_param_to_unflat_param_names()` \\\" \\\\\\n \\\"should not construct empty lists\\\"\\n if len(param_names) > 1:\\n raise RuntimeError(\\n \\\"Each parameter should only map to one parameter name but got \\\"\\n f\\\"{len(param_names)}: {param_names}\\\"\\n )\\n param_to_param_name = {\\n param: param_names[0]\\n for param, param_names in param_to_param_names.items()\\n }\\n return param_to_param_name\",\n \"def get_parameter_value_by_fully_qualified_parameter_name(\\n fully_qualified_parameter_name: str,\\n domain: Optional[Domain] = None,\\n variables: Optional[ParameterContainer] = None,\\n parameters: Optional[Dict[str, ParameterContainer]] = None,\\n) -> Optional[Union[Any, ParameterNode]]:\\n validate_fully_qualified_parameter_name(\\n fully_qualified_parameter_name=fully_qualified_parameter_name\\n )\\n\\n # Using \\\"__getitem__\\\" (bracket) notation instead of \\\"__getattr__\\\" (dot) notation in order to insure the\\n # compatibility of field names (e.g., \\\"domain_kwargs\\\") with user-facing syntax (as governed by the value of the\\n # DOMAIN_KWARGS_PARAMETER_NAME constant, which may change, requiring the same change to the field name).\\n if fully_qualified_parameter_name == DOMAIN_KWARGS_PARAMETER_FULLY_QUALIFIED_NAME:\\n if domain:\\n # Supports the \\\"$domain.domain_kwargs\\\" style syntax.\\n return domain[DOMAIN_KWARGS_PARAMETER_NAME]\\n return None\\n\\n if fully_qualified_parameter_name.startswith(\\n DOMAIN_KWARGS_PARAMETER_FULLY_QUALIFIED_NAME\\n ):\\n if domain and domain[DOMAIN_KWARGS_PARAMETER_NAME]:\\n # Supports the \\\"$domain.domain_kwargs.column\\\" style syntax.\\n return domain[DOMAIN_KWARGS_PARAMETER_NAME].get(\\n fully_qualified_parameter_name[\\n (len(DOMAIN_KWARGS_PARAMETER_FULLY_QUALIFIED_NAME) + 1) :\\n ]\\n )\\n return None\\n\\n parameter_container: ParameterContainer\\n\\n if fully_qualified_parameter_name.startswith(VARIABLES_KEY):\\n fully_qualified_parameter_name = fully_qualified_parameter_name[1:]\\n parameter_container = variables\\n else:\\n fully_qualified_parameter_name = fully_qualified_parameter_name[1:]\\n parameter_container = parameters[domain.id]\\n\\n fully_qualified_parameter_name_as_list: List[\\n str\\n ] = fully_qualified_parameter_name.split(\\n FULLY_QUALIFIED_PARAMETER_NAME_SEPARATOR_CHARACTER\\n )\\n\\n if len(fully_qualified_parameter_name_as_list) == 0:\\n return None\\n\\n return _get_parameter_value_from_parameter_container(\\n fully_qualified_parameter_name=fully_qualified_parameter_name,\\n fully_qualified_parameter_name_as_list=fully_qualified_parameter_name_as_list,\\n parameter_container=parameter_container,\\n )\",\n \"def get_param(self, param_name):\\n if hasattr(self, param_name):\\n return getattr(self, param_name)\\n else:\\n return None\",\n \"def param_name(self):\\n return self._param_name\",\n \"def get_param(self, param):\\n return self.params.get(param, None)\",\n \"def _get_arg_name(self, arg, variable_name):\",\n \"def get_parameter(self, param):\\n try:\\n result = self._data[\\\"queryResult\\\"][\\\"parameters\\\"][param]\\n except KeyError:\\n result = None\\n\\n return result\",\n \"def check_param(param):\\n return PREPEND_STR+param if keyword.iskeyword(param) else param\",\n \"def get_param(query, config):\\n keys = query.split('.')\\n if len(keys) == 1:\\n key = keys[0]\\n if not config.has_key(key):\\n return None\\n return config[key]\\n else:\\n return Config.get_nested_param(keys, config)\",\n \"def find_param(self, ptype, name):\\n param_to_find = PBRTParam(ptype, name)\\n for p in self._data:\\n if p == param_to_find:\\n return p\\n return None\",\n \"def _search_param_in_docstr(docstr, param_str):\\n # look at #40 to see definitions of those params\\n patterns = [re.compile(p % re.escape(param_str))\\n for p in DOCSTRING_PARAM_PATTERNS]\\n for pattern in patterns:\\n match = pattern.search(docstr)\\n if match:\\n return _strip_rest_role(match.group(1))\\n\\n return None\",\n \"def get_parameter(self, name: str) -> any:\\r\\n if name in self.kwargs:\\r\\n return self.kwargs[name]\\r\\n for x in self.args:\\r\\n if isinstance(x, dict) and name in x:\\r\\n return x[name]\\r\\n else:\\r\\n return None\",\n \"def getParam(self, params, name):\\n return params.get(name)\",\n \"def _get_param_from_request(self, nombreParametro):\\n\\t\\treturn request.args.get(nombreParametro)\",\n \"def _AttributeName(self, param_name, attribute_config, anchor=False):\\n if attribute_config.attribute_name:\\n return attribute_config.attribute_name\\n if anchor:\\n return 'name'\\n return param_name.replace('Id', '_id').lower()\",\n \"def id_func(param):\\n if isinstance(param, dict) and \\\":name:\\\" in param:\\n return param[\\\":name:\\\"]\\n\\n retval = str(param)\\n if len(retval) > 25:\\n retval = retval[:20] + \\\"...\\\" + retval[-2:]\\n return retval\",\n \"def id_func(param):\\n if isinstance(param, dict) and \\\":name:\\\" in param:\\n return param[\\\":name:\\\"]\\n\\n retval = str(param)\\n if len(retval) > 25:\\n retval = retval[:20] + \\\"...\\\" + retval[-2:]\\n return retval\",\n \"def get_param_re_names(self, param_name_re, syselem):\\n\\n with self.__connection.cursor() as cursor:\\n query = \\\"SELECT PID FROM %s WHERE NAME LIKE '%s' AND SYSTEM_ELEMENT= '%s'\\\" % (self.__schema, param_name_re, syselem)\\n cursor.execute(query)\\n result = cursor.fetchone()\\n return result['PID']\",\n \"def lookup_name(self, name, default=None):\\n for frames in reversed(self._arg_transformer):\\n if name in frames:\\n return frames[name]\\n return name if default is None else default\",\n \"def get_param_from_container(param, container):\\n if param in container.params:\\n param = container.params[param]\\n if param in container:\\n param = container.get(param)\\n elif param in container:\\n param = container.get(param)\\n else:\\n if isinstance(param, FunctionType):\\n param = param(container)\\n return param\",\n \"def get_rule_param_type(\\n self, rule_name: str, rule_param_name: str\\n ) -> objects.BaseObject:\\n rule_param_list = self.get_rule_param_list(rule_name)\\n\\n for param_name, param_type in rule_param_list:\\n if param_name == rule_param_name:\\n return param_type\\n raise Exception(\\n 'Rule %s has no param called %s' % (rule_name, rule_param_name))\",\n \"def _parse_module_name(program_param):\\n if program_param and program_param.endswith(\\\".py\\\"):\\n return program_param[:-3]\\n return program_param\",\n \"def getParam(self, paramName):\\n for pname, pvalue in self.neededParamsNames.items():\\n if pvalue[0] == paramName:\\n if paramName in self.neededParams:\\n return self.neededParams[paramName]\\n for pname, pvalue in self.optionalParamsNames.items():\\n if pvalue[0] == paramName:\\n if paramName in self.optionalParams:\\n return self.optionalParams[paramName]\\n else:\\n return pvalue[2]\\n print >> sys.stderr, \\\"Coding error: param\\\", paramName,\\\"is not\\\",\\\\\\n \\\"among the available options\\\"\\n sys.exit(1)\",\n \"def get_parameter_by_label(self, label):\\n \\n for attr in self.parm_list:\\n if attr.label == label:\\n return attr\\n\\n self.logging.error(\\\"Can't find topic: \\\"+label)\\n return None\",\n \"def get_underlying_parameter(self, rel_name):\\n return self._declaration[rel_name].underlying_parameter # pytype: disable=bad-return-type\",\n \"def get_parameter(par_name):\\r\\n config_file = open('./config.txt', 'r')\\r\\n lines = config_file.readlines()\\r\\n for line in lines:\\r\\n line = line.rstrip('\\\\n\\\\r')\\r\\n if line.startswith(par_name):\\r\\n return line.split('=')[1]\",\n \"def checkreplaceparam(stdpardict, functypepardict, parsuffix):\\n try:\\n ftpara = next(v for k, v in functypepardict.items() if k.endswith(parsuffix))\\n return ftpara\\n except StopIteration:\\n try:\\n return next(v for k, v in stdpardict.items() if k.endswith(parsuffix))\\n except StopIteration:\\n #return 'Parameter not defined or not passed to class'\\n raise Exception('Parameter {} is not found in Parameters passed to SV class'.format(parsuffix))\",\n \"def get_param(self, name):\\n for param in self._parameters:\\n if name == param._name:\\n return param\\n pass\\n new_param = self._add_param(name)\\n return new_param\",\n \"def get_parameter(key):\\n if key in param_dict:\\n # was a supplied parameter\\n param = param_dict.get(key)\\n elif module and hasattr(module, key):\\n param = getattr(module, key)\\n if hasattr(param, \\\"__call__\\\"):\\n # we don't allow module methods\\n raise Exception()\\n elif attr_getter:\\n # get value from attr_getter function\\n try:\\n param = attr_getter(key)\\n except: # noqa e722\\n raise Exception()\\n else:\\n raise Exception()\\n if isinstance(param, Composite):\\n if param.text():\\n param = param.copy()\\n else:\\n param = \\\"\\\"\\n return param\",\n \"def parameterName(self):\\n return self.name()\",\n \"def extract_name_description(self, param):\\n name = None\\n description = None\\n if getattr(param, 'description', None):\\n description = param.description\\n\\n if getattr(param, 'primary_name', None):\\n name = param.primary_name\\n elif getattr(param, 'param_type', None):\\n if getattr(param.param_type, 'name', None):\\n name = param.param_type.name\\n if not description and getattr(param.param_type, 'description', None):\\n description = param.param_type.description\\n elif getattr(param.param_type, 'element_type', None) and \\\\\\n getattr(param.param_type.element_type, 'name', None):\\n name = param.param_type.element_type.name\\n if not description and getattr(param.param_type.element_type, 'description', None):\\n description = param.param_type.element_type.description\\n\\n return self.replace_sync(name), self.extract_description(description)\",\n \"def get_parameter(cur, par):\\n cur.execute(\\\"SELECT value FROM parameters WHERE par='%s';\\\" % par)\\n return cur.fetchone()[0]\",\n \"def GetUniqueParam(self, name):\\n if not hasattr(self, '_params'):\\n self._params = cgi.parse_qs(self.path[self.path.find('?') + 1:])\\n\\n param_list = self._params.get(name, [])\\n if len(param_list) == 1:\\n return param_list[0]\\n return None\",\n \"def extractparam(pardict, parsuffix):\\n return next(v for k, v in pardict.items() if k.endswith(parsuffix))\",\n \"def fix_default_param(defparam, classname):\\n if (classname + '::') == defparam[0:len(classname)+2:]:\\n return defparam[len(classname)+2::]\\n #if defparam[len(defparam)-1] == \\\"f\\\":\\n # return defparam[0:len(defparam)-1]\\n return defparam\",\n \"def get_name(internal: str):\\n if '__' in internal:\\n return ': '.join(get_name(s) for s in internal.split('__'))\\n *path, name = internal.split('::')\\n current = config.utils.names\\n look_in = [current]\\n try:\\n for k in path:\\n current = current[k]\\n look_in.append(current)\\n except KeyError:\\n # noinspection PyUnboundLocalVariable\\n logging.warning('invalid namespace {!r} of {!r}'.format(k, internal))\\n look_in.reverse()\\n for ns in look_in:\\n try:\\n val = ns[name]\\n if isinstance(val, str):\\n return val\\n elif isinstance(val, dict):\\n return val['*this*']\\n else:\\n raise TypeError('{!r} is neither dict nor str'.format(val))\\n except KeyError:\\n pass\\n logging.warning('Name \\\"{}\\\" was not found in the namefile'.format('::'.join(path+[name])))\\n return '::'.join(path+[name])\",\n \"def findParam(posName, startIndex, endIndex):\\r\\n for i in range(startIndex, endIndex):\\r\\n if allParamNodes[i].getAttribute('position') == posName:\\r\\n return manager.parameters[i]\\r\\n \\r\\n raise Exception('Problem resolving parameter to J Matrix from xml file')\",\n \"def get_qname(uri, name):\\n if not uri or not name or name[0] in ('{', '.', '/', '['):\\n return name\\n else:\\n return '{%s}%s' % (uri, name)\",\n \"def _name(self):\\n return self.arguments[0].split('(')[0]\",\n \"def get_name(self) -> str:\\n # read the original value passed by the command\\n name = self.raw_param.get(\\\"name\\\")\\n\\n # this parameter does not need dynamic completion\\n # this parameter does not need validation\\n return name\",\n \"def _detect_source_param_class(self, param):\\n if self.config[\\\"source\\\"][\\\"parameter\\\"][\\\"name\\\"] == param:\\n return self.config[\\\"source\\\"][\\\"parameter\\\"][\\\"class\\\"]\\n else:\\n return None\",\n \"def _name(self):\\n return self._arguments[0].split('(')[0]\",\n \"def getparam(name, default=None, stash=None, params=None):\\n v = getparamlist(name, stash=stash, params=params)\\n if len(v) > 0: return v[0]\\n return default\",\n \"def get_param(name, dictionary):\\n if (\\\"templates_dict\\\" in dictionary):\\n dictionary = dictionary[\\\"templates_dict\\\"]\\n if (name in dictionary):\\n return dictionary[name]\\n raise KeyError(\\\"'{}' was not found in context.\\\".format(name))\",\n \"def _resolve_name(self, cls, name):\\n attrs = name.split('.')\\n part = cls\\n while attrs:\\n attr = attrs.pop(0)\\n part = getattr(part, attr, UNSET)\\n if part is UNSET:\\n return name\\n if not isinstance(part, basestring):\\n raise TypeError(\\\"Invalid key: {!r}\\\".format(part))\\n return part\",\n \"def _find_by_name(details: CallableDetails, name: str):\\n arg = details.arg_by_name(name)\\n if not arg:\\n raise IncompatibleHandlerFactoryError(\\n f\\\"Callable {details.obj!r} has no argument named {name}\\\"\\n )\\n return arg\",\n \"def build_path_to_parameter(\\n parameter_set: DwdObservationDataset,\\n resolution: Resolution,\\n period: Period,\\n) -> str:\\n if parameter_set == DwdObservationDataset.SOLAR and resolution in (\\n Resolution.HOURLY,\\n Resolution.DAILY,\\n ):\\n return f\\\"{resolution.value}/{parameter_set.value}/\\\"\\n\\n return f\\\"{resolution.value}/{parameter_set.value}/{period.value}/\\\"\",\n \"def _get_name(name):\\n if \\\"::\\\" in name:\\n return name.split(\\\"::\\\")[1]\\n return name\",\n \"def _get_name(name):\\n if \\\"::\\\" in name:\\n return name.split(\\\"::\\\")[1]\\n return name\",\n \"def function_name(parameters):\",\n \"def get_param_id(self, param_name, syselem):\\n\\n with self.__connection.cursor() as cursor:\\n query = \\\"SELECT PID FROM %s WHERE NAME= '%s' AND SYSTEM_ELEMENT= '%s'\\\" % (self.__schema, param_name, syselem)\\n cursor.execute(query)\\n result = cursor.fetchone()\\n return result['PID']\",\n \"def get_parameter_type(self, name):\\n phil_scope = phil.parse(\\n \\\"\\\"\\\"include scope dials.command_line.scale.phil_scope\\\"\\\"\\\",\\n process_includes=True,\\n )\\n obj = phil.find_scope(phil_scope, name)\\n if not obj:\\n raise ValueError(\\n \\\"\\\"\\\"Unable to resolve %s in the phil scope, make sure full phil path\\nis provided. For example, physical.decay_correction rather than decay_correction\\\"\\\"\\\"\\n % name\\n )\\n return obj.type.phil_type # a str: \\\"int\\\", \\\"bool\\\" etc\",\n \"def get_name_query_cond(column: str, val: str, query_params: dict):\\n if val is not None and column is not None:\\n query_params[column] = '%' + val + '%'\\n return 'AHJ.' + column + ' LIKE %(' + column + ')s AND '\\n return ''\",\n \"def local_defect_name(global_name):\\n return global_name.split(':')[-1]\",\n \"def _get_ssm_param(self, parameter_name):\\n response = self.ssm_client.get_parameter(Name=parameter_name)\\n res = response.get(\\\"Parameter\\\", {})\\n cwa_parameter = res.get(\\\"Value\\\", {})\\n return cwa_parameter\",\n \"def getParameter(self, name):\",\n \"def _get_unique_param_name(self, name, mode):\\n _name = name\\n inc = 1\\n \\n if mode == NodeParam.INPUT:\\n existing_params = self._input_params\\n else:\\n existing_params = self._output_params\\n \\n while _name in existing_params:\\n _name = \\\"%s%i\\\" % (name, inc) \\n inc += 1 \\n return _name\",\n \"def getName(self):\\n return _libsbml.Parameter_getName(self)\",\n \"def retrieve_name(var):\\n for fi in reversed(inspect.stack()):\\n names = [var_name for var_name, var_val in fi.frame.f_locals.items() if var_val is var]\\n if len(names) > 0:\\n return names[0]\",\n \"def get_parameter(self, topic):\\n \\n for attr in self.parm_list:\\n if attr.topic == topic:\\n return attr\\n\\n self.logging.error(\\\"Can't find topic: \\\"+topic)\\n return None\",\n \"def find_qualified_name(filename, max_iterations=5):\\n filename = os.path.abspath(filename)\\n vc_root = find_vc_root(filename, max_iterations)\\n _, name = filename.split(f\\\"{vc_root}/\\\")\\n if name.endswith(\\\".py\\\"):\\n name = name[:-3]\\n return name.replace(\\\"/\\\", \\\".\\\")\",\n \"def normalize_parameter(parameter: str, expression: str) -> Tuple[Optional[str], str, str]:\\n try:\\n # The parameter name is prefixed with its location. Example: `path.id`\\n location, name = tuple(parameter.split(\\\".\\\"))\\n return location, name, expression\\n except ValueError:\\n return None, parameter, expression\",\n \"def get_parameter_domain(self, parameter_name):\\n pgraph = self.solver_binary.solver.parameter_graph[0].serializedGraph\\n if pgraph is None: return None\\n tree = etree.parse(StringIO(pgraph))\\n if tree is None: return None\\n root = tree.getroot()\\n for node in root:\\n if node.tag == \\\"parameters\\\" and node[1].text == parameter_name:\\n return node[0].attrib.values()[0]\",\n \"def _name_from_args(func, _, params):\\n return \\\"{}_{}\\\".format(func.__name__, \\\"_\\\".join(str(arg) for arg in params.args))\",\n \"def register_param(param: Type[Param]) -> None:\\n for alias in param.type_aliases + [param.type]:\\n if alias in TYPE_NAMES:\\n raise PyParamNameError(\\n \\\"Type name has already been \\\" f\\\"registered: {alias}\\\"\\n )\\n TYPE_NAMES[alias] = param.type\\n\\n PARAM_MAPPINGS[param.type] = param\\n param.on_register()\",\n \"def _formal_params(self, doclet):\\n name, paren, params = self.arguments[0].partition('(')\\n return ('(%s' % params) if params else '(%s)' % ', '.join(doclet['meta']['code']['paramnames'])\",\n \"def get_query_parameter(self,original_name: Optional[str] = None) -> str:\\n if not original_name:\\n raise TypeError(\\\"original_name cannot be null.\\\")\\n if original_name == \\\"count\\\":\\n return \\\"%24count\\\"\\n if original_name == \\\"expand\\\":\\n return \\\"%24expand\\\"\\n if original_name == \\\"filter\\\":\\n return \\\"%24filter\\\"\\n if original_name == \\\"orderby\\\":\\n return \\\"%24orderby\\\"\\n if original_name == \\\"search\\\":\\n return \\\"%24search\\\"\\n if original_name == \\\"select\\\":\\n return \\\"%24select\\\"\\n if original_name == \\\"skip\\\":\\n return \\\"%24skip\\\"\\n if original_name == \\\"top\\\":\\n return \\\"%24top\\\"\\n return original_name\",\n \"def get_query_parameter(self,original_name: Optional[str] = None) -> str:\\n if not original_name:\\n raise TypeError(\\\"original_name cannot be null.\\\")\\n if original_name == \\\"count\\\":\\n return \\\"%24count\\\"\\n if original_name == \\\"expand\\\":\\n return \\\"%24expand\\\"\\n if original_name == \\\"filter\\\":\\n return \\\"%24filter\\\"\\n if original_name == \\\"orderby\\\":\\n return \\\"%24orderby\\\"\\n if original_name == \\\"search\\\":\\n return \\\"%24search\\\"\\n if original_name == \\\"select\\\":\\n return \\\"%24select\\\"\\n if original_name == \\\"skip\\\":\\n return \\\"%24skip\\\"\\n if original_name == \\\"top\\\":\\n return \\\"%24top\\\"\\n return original_name\",\n \"def gui_get_param(self,param_name):\\n return self._tkvars[param_name].get()\",\n \"def lookup(name):\",\n \"def lookup(name):\",\n \"def retrieve_name(self, var):\\r\\n\\t\\tfor fi in reversed(inspect.stack()):\\r\\n\\t\\t\\tnames = [var_name for var_name, var_val in fi.frame.f_locals.items() if var_val is var]\\r\\n\\t\\t\\tif len(names) > 0:\\r\\n\\t\\t\\t\\treturn names[0]\\r\\n\\t\\treturn \\\"<unknown>\\\"\",\n \"def ParamName(self, attribute_name):\\n if attribute_name not in self.attribute_to_params_map:\\n raise ValueError(\\n 'No param name found for attribute [{}]. Existing attributes are '\\n '[{}]'.format(attribute_name,\\n ', '.join(sorted(self.attribute_to_params_map.keys()))))\\n return self.attribute_to_params_map[attribute_name]\",\n \"def rename_param(self, param, name):\\n old_name = param.name\\n new_name = self._get_unique_param_name(name, param.mode)\\n \\n param._name = new_name\\n \\n if param.mode == NodeParam.INPUT:\\n self._input_params.pop(old_name)\\n self._input_params[new_name] = param\\n else:\\n self._output_params.pop(old_name)\\n self._output_params[new_name] = param\\n \\n return new_name\",\n \"def namedModelParameter(self, s):\\n try:\\n idx = self.parameterNames.index(s)\\n except ValueError:\\n return None\\n \\n if idx >= len(self.stateVector):\\n idx -= len(self.stateVector)\\n val = self.otherModelParameters[idx]\\n else:\\n val = self.stateVector[idx]\\n \\n return val\",\n \"def fully_qualified_name(self) -> str:\\n return pulumi.get(self, \\\"fully_qualified_name\\\")\",\n \"def param_lookup(param_fpath, param_name, version=-999):\\n\\n # save the column names and read the last line of parameters in a params.csv file\\n params_csv_object = open(param_fpath, 'rU')\\n lines = csv.reader(params_csv_object)\\n keys = lines.next() # save column names as keys\\n for line in lines:\\n if line[3]: # check that data is present, any extra blank lines saved at end of file won't override real data\\n params = line\\n read_version = int(params[0])\\n # break out of the loop once the target parameter version have been read, if specified\\n if read_version == version:\\n break\\n params_csv_object.close()\\n print \\\"Updating .100 files based on parameter version %i...\\\" % read_version\\n\\n # propagate parameter data into dictionary\\n dictionary = {}\\n for i, key in enumerate(keys):\\n dictionary[key] = params[i]\\n\\n return dictionary[param_name]\",\n \"def get_parameter(name, parameter, path=None):\\n _ensure_exists(name, path=path)\\n cmd = \\\"lxc-cgroup\\\"\\n if path:\\n cmd += f\\\" -P {shlex.quote(path)}\\\"\\n cmd += f\\\" -n {name} {parameter}\\\"\\n ret = __salt__[\\\"cmd.run_all\\\"](cmd, python_shell=False)\\n if ret[\\\"retcode\\\"] != 0:\\n raise CommandExecutionError(f\\\"Unable to retrieve value for '{parameter}'\\\")\\n return ret[\\\"stdout\\\"].strip()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7109423","0.6902756","0.6839676","0.68305796","0.68224156","0.68224156","0.68224156","0.68224156","0.68224156","0.6680651","0.6656476","0.6656476","0.66398823","0.66398823","0.66398823","0.6597125","0.6567056","0.65526336","0.65026873","0.6357738","0.62984914","0.6290804","0.624869","0.624822","0.6233775","0.6205049","0.619289","0.61517066","0.614021","0.6113876","0.60750407","0.6057846","0.602133","0.601546","0.6004808","0.59585816","0.59271026","0.59158134","0.59158134","0.5905368","0.58958775","0.58695644","0.58575195","0.5849262","0.5832025","0.5822178","0.58138525","0.5810932","0.5801885","0.5798093","0.57971144","0.5770674","0.5766226","0.5758765","0.5737122","0.5715498","0.5709848","0.5696743","0.56965786","0.567623","0.56704307","0.56391174","0.5633548","0.56333405","0.56123924","0.56016165","0.55877984","0.5572703","0.5534293","0.55197585","0.55197585","0.55166674","0.55041933","0.54945165","0.5489787","0.5482341","0.54814917","0.5474184","0.54603434","0.54596406","0.5459505","0.54558825","0.54437315","0.5442182","0.5435266","0.54334354","0.5414311","0.54136187","0.54039174","0.54039174","0.53987724","0.5397721","0.5397721","0.5396501","0.53879714","0.5368327","0.53668207","0.53650814","0.53577596","0.53517014"],"string":"[\n \"0.7109423\",\n \"0.6902756\",\n \"0.6839676\",\n \"0.68305796\",\n \"0.68224156\",\n \"0.68224156\",\n \"0.68224156\",\n \"0.68224156\",\n \"0.68224156\",\n \"0.6680651\",\n \"0.6656476\",\n \"0.6656476\",\n \"0.66398823\",\n \"0.66398823\",\n \"0.66398823\",\n \"0.6597125\",\n \"0.6567056\",\n \"0.65526336\",\n \"0.65026873\",\n \"0.6357738\",\n \"0.62984914\",\n \"0.6290804\",\n \"0.624869\",\n \"0.624822\",\n \"0.6233775\",\n \"0.6205049\",\n \"0.619289\",\n \"0.61517066\",\n \"0.614021\",\n \"0.6113876\",\n \"0.60750407\",\n \"0.6057846\",\n \"0.602133\",\n \"0.601546\",\n \"0.6004808\",\n \"0.59585816\",\n \"0.59271026\",\n \"0.59158134\",\n \"0.59158134\",\n \"0.5905368\",\n \"0.58958775\",\n \"0.58695644\",\n \"0.58575195\",\n \"0.5849262\",\n \"0.5832025\",\n \"0.5822178\",\n \"0.58138525\",\n \"0.5810932\",\n \"0.5801885\",\n \"0.5798093\",\n \"0.57971144\",\n \"0.5770674\",\n \"0.5766226\",\n \"0.5758765\",\n \"0.5737122\",\n \"0.5715498\",\n \"0.5709848\",\n \"0.5696743\",\n \"0.56965786\",\n \"0.567623\",\n \"0.56704307\",\n \"0.56391174\",\n \"0.5633548\",\n \"0.56333405\",\n \"0.56123924\",\n \"0.56016165\",\n \"0.55877984\",\n \"0.5572703\",\n \"0.5534293\",\n \"0.55197585\",\n \"0.55197585\",\n \"0.55166674\",\n \"0.55041933\",\n \"0.54945165\",\n \"0.5489787\",\n \"0.5482341\",\n \"0.54814917\",\n \"0.5474184\",\n \"0.54603434\",\n \"0.54596406\",\n \"0.5459505\",\n \"0.54558825\",\n \"0.54437315\",\n \"0.5442182\",\n \"0.5435266\",\n \"0.54334354\",\n \"0.5414311\",\n \"0.54136187\",\n \"0.54039174\",\n \"0.54039174\",\n \"0.53987724\",\n \"0.5397721\",\n \"0.5397721\",\n \"0.5396501\",\n \"0.53879714\",\n \"0.5368327\",\n \"0.53668207\",\n \"0.53650814\",\n \"0.53577596\",\n \"0.53517014\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.66429484"},"document_rank":{"kind":"string","value":"12"}}},{"rowIdx":88588,"cells":{"query":{"kind":"string","value":"Get the name of the experiment."},"document":{"kind":"string","value":"def aqGetExpName(self):\n return self._expname"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def experiment_name(self):\n # type: () -> string_types\n return self._experiment_name","def get_name() -> str:\n pass","def get_name() -> str:","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")","def get_name(self) -> str:\n pass","def name(self) -> str:\n return pulumi.get(self, \"name\")","def name(self) -> str:\n return pulumi.get(self, \"name\")","def name(self) -> str:\n return pulumi.get(self, \"name\")","def name(self) -> str:\n return pulumi.get(self, \"name\")","def name(self) -> str:\n return pulumi.get(self, \"name\")","def name(self) -> str:\n return pulumi.get(self, \"name\")","def name(self) -> str:\n return pulumi.get(self, \"name\")","def name(self) -> str:\n return pulumi.get(self, \"name\")"],"string":"[\n \"def experiment_name(self):\\n # type: () -> string_types\\n return self._experiment_name\",\n \"def get_name() -> str:\\n pass\",\n \"def get_name() -> str:\",\n \"def 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parameter."},"document":{"kind":"string","value":"def getParam(self, name, enum=None):\n return Parameter(self, name, enum)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_additional_properties_with_array_of_enums(self):\n pass","def convertToEnumItemArray(byte: int, enumType: cern.japc.value.EnumType) -> typing.List[cern.japc.value.EnumItem]:\n ...","def convertToEnumItemSetArray(byte: int, enumType: cern.japc.value.EnumType) -> typing.List[cern.japc.value.EnumItemSet]:\n ...","def convertToEnumItemArray(boolean: bool) -> typing.List[cern.japc.value.EnumItem]:\n ...","def getlist(self, key, type=None):\n if key not in self:\n return []\n values = super().__getitem__(key)\n if type is not None:\n values = [type(value) for value in values]\n return values","def convertToEnumItemSetArray(boolean: bool) -> typing.List[cern.japc.value.EnumItemSet]:\n ...","def type_array():\n return []","def __getitem__(self, idx):\n return self.GetArray(idx)","def __getitem__(self, idx):\n return self.GetArray(idx)","def __getattr__(self, name):\n try:\n return self[self.argpos(name)]\n except:\n pass\n return list.__getattr__(self, name)","def __getitem__(self, index):\n return self.to_list()[index]","def enum(self):\n return plist(enumerate(self), root=self.__root__)","def test_array_of_enums(self):\n from petstore_api.model import array_of_enums, string_enum\n endpoint = self.api.array_of_enums\n assert endpoint.openapi_types['array_of_enums'] == (array_of_enums.ArrayOfEnums,)\n assert endpoint.settings['response_type'] == (array_of_enums.ArrayOfEnums,)\n\n # serialization + deserialization works\n with patch.object(RESTClientObject, 'request') as mock_method:\n value = [string_enum.StringEnum(\"placed\")]\n body = array_of_enums.ArrayOfEnums(value)\n value_simple = [\"placed\"]\n mock_method.return_value = self.mock_response(value_simple)\n\n response = endpoint(array_of_enums=body)\n self.assert_request_called_with(mock_method, 'http://petstore.swagger.io:80/v2/fake/refs/array-of-enums', value_simple)\n\n assert isinstance(response, array_of_enums.ArrayOfEnums)\n assert response.value == value","def asArray( cls, value, typeCode=None ):\n if value is None:\n return value\n else:\n return cls.contiguous( value, typeCode )","def enum(**enums):\n return type('Enum',(),enums)","def get_possible_array_value(args, key):\n if not args:\n return []\n if key in args:\n return [args.get(key)]\n return args.getlist(key + '[]')","def getStatusValues(self):\n return []","def get_list(self, key: str, default=[]) -> list:\n try:\n return self[key]\n except KeyError:\n return default","def _listarr(self, func):\n return [func(self.ptr, i) for i in range(len(self))]","def toArray(self, *args):\n pass","def __getitem__(self, pos):\n\t\t# Handle if a slice of positions are passed in by grabbing all the values\n\t\t# and returning them in a list.\n\t\t#pprint(pos)\n\t\tif isinstance(pos, slice):\n\t\t\treturn self.leds[pos]\n\t\t# Else assume the passed in value is a number to the position.\n\t\telse:\n\t\t\treturn self.leds","def enum(self):\r\n raise NotImplementedError","def oper_array(fct, arr, init):\n result = []\n for i, item in enumerate(arr):\n result.append(fct(result[i-1] if result else init, item))\n return result","def array_form(self):\n return tuple(self)","def getlist(self, key):\n try:\n return dict.__getitem__(self, key)\n except KeyError:\n return []","def handle_enum(enum_annotations: Any) -> list:\n result = []\n for attribute in list(enum_annotations):\n result.append(attribute.value)\n return result","def iflatten(self):\n return _((e for es in self.array for e in es))","def __iter__(self):\n return iter(self._enums)","def enum(**enums):\n return type('Enum', (), enums)","def __noop_list(self, *args, **kwargs):\n return []","def __getitem__(self, index):\n return index, super().__getitem__(index)","def flag(self, arr):\n return arr","def __getitem__(self, *args):\n return self.data.__getitem__(*args)","def lookup_array(self, *args, **kwargs): # real signature unknown\n pass","def lookup_array(self, *args, **kwargs): # real signature unknown\n pass","def getlist(self, k, default=_MISSING):\n try:\n return super(OrderedMultiDict, self).__getitem__(k)[:]\n except KeyError:\n if default is _MISSING:\n return []\n return default","def __getitem__(self, key):\n if not self.ordinal:\n i = self.names().index('(%s==%s)' % (self.termname, str(key)))\n return self()[i]\n else:\n v = self.namespace[self._name]\n return np.array([(vv == key) for vv in v]).astype(np.float)","def array_of(element: Type) -> ArrayType:\n return ArrayType(element)","def default_array(self, count: int) -> List[Any]:\n return [self.default() for _ in range(count)]","def Array(*args):\n array = VBArray(len(args) - 1, Variant)\n for idx in range(len(args)):\n array[idx] = args[idx]\n return array","def enum(*sequential, **named):\n enums = dict(zip(sequential, range(len(sequential))), **named)\n return type('Enum', (), enums)","def enum(*sequential, **named):\n enums = dict(zip(sequential, range(len(sequential))), **named)\n return type('Enum', (), enums)","def enum(*sequential, **named):\n enums = dict(zip(sequential, range(len(sequential))), **named)\n return type('Enum', (), enums)","def enum(*sequential, **named):\n enums = dict(zip(sequential, range(len(sequential))), **named)\n return type('Enum', (), enums)","def __getitem__(self, index):\n # type: (int) -> Any\n items = list.__getitem__(self, index)\n return type(self)(self._values(items)) if isinstance(index, slice) else self.value(items)","def list_value(self) -> global___Expression.RepeatedValue:","def array(self):","def test_cast_list(self):\n dim = Real(\"yolo\", \"uniform\", -3, 4)\n assert dim.cast([\"1\", \"2\"]) == [1.0, 2.0]","def __getitem__(self, item):\n return self.getList()","def test_cast_list(self):\n dim = Integer(\"yolo\", \"uniform\", -3, 5)\n assert dim.cast([\"1\", \"2\"]) == [1, 2]","def __sub__(self, vs):\n return [v for v in self.__elements if tuple(v) not in map(tuple, vs)]","def _value(self) -> List[Any]:\n ret = [\n cast_to(val, self.subtype)\n for sublist in self._stack\n for val in sublist\n ]\n\n if self.required and not ret:\n raise PyParamValueError(ARGUMENT_REQUIRED)\n self._stack = []\n return ret","def get_enumerations_from_bit_mask(enumeration, mask):\n return [x for x in enumeration if (x.value & mask) == x.value]","def __getitem__(self, pos):\n if isinstance(pos, list): # pos is containing multiple indices as a list\n return [self.__getitem__(pos=p) for p in pos]\n elif pos is None:\n return None\n elif np.all(np.array([isinstance(p, (int, np.integer)) for p in pos])):\n # pos is mapped to a single element (pos is composed of integer indices).\n # just do rounding.\n idx = []\n for p, s in zip(pos, self.shape):\n idx.append(p % s)\n return self.elements[tuple(idx)]\n else:\n # pos is mapped to multiple indices. (possible examples include ([0:5, 3], [[1,2,3], 3], ...).\n # Create a list containing the indices to iterate over, and return a numpy.ndarray containing items\n # corresponding to the indices in the list.\n # When the indices don't specify the lower boundary (e.g., [:5]), it iterates from 0.\n # When the indices don't specify the upper boundary (e.g., [3:]), it iterates to the maximum index defined.\n idx = None\n for i, p in enumerate(pos):\n idx = _extend_index_dim(idx, p, self.shape[i])\n idx = np.asarray(idx)\n # iterate and generate the list to return\n item = np.empty(idx.shape[:-1], dtype=self.dtype) # -1 because the tuples in idx are flatten.\n for i, _null in np.ndenumerate(item):\n item[i] = self.__getitem__(pos=tuple(idx[i]))\n return np.asarray(item)","def optional(cls):\n return []","def __getitem__(self):\n pass","def __getitem__(self, index: slice) -> List:\n\n return self.data[index]","def __call__(self, tokens: Union[Hashable, List[Hashable], Tuple[Hashable]])\\\n -> Union[int, np.ndarray]:\n return self[tokens]","def __getitem__(self, *args):\n return _ida_hexrays.fnum_array___getitem__(self, *args)","def all(cls):\n return []","def unary_op(self):\n return plist([op(x) for x in self], root=self.__root__)","def slice(self, field):\n return [getattr(r, field) for r in self.__elements__]","def _always_array(value: str | list | None) -> list:\n if value is None:\n value = []\n elif not isinstance(value, list):\n value = [value]\n return value","def get_value(self) -> Union[Iterable[T], List[T]]:\n return self.array","def values(self) -> List:\n pass","def _init_as_list(arg):\n if arg is None:\n return []\n elif isinstance(arg, str):\n return [arg]\n else:\n return arg","def getall(l, idx):\n return [l[i] for i in idx]","def __getitem__(self, keys):\n if isinstance(keys, int):\n return super().__getitem__(keys)\n elif isinstance(keys, list):\n return self.vectors(keys)\n elif isinstance(keys, str):\n return self.find(keys)\n elif isinstance(keys, tuple):\n return self.item(keys[0], keys[1])\n elif isinstance(keys, slice):\n return super().__getitem__(keys)","def __get__(self,obj,objtype):\n if not obj:\n return [getattr(objtype,a) for a in self.attribs]\n else:\n return [getattr(obj,a) for a in self.attribs]","def _get_list(self, key, operation, create=False, decode=False):\n return self._get_by_type(key, operation, create, b'list', [], decode=decode)","def getArrayList(self, arrayType):\n if arrayType in self.arrayLists:\n return self.arrayLists[arrayType]","def c_array(ctype, values):\n\n arr = (ctype*len(values))()\n arr[:] = values\n return arr","def _process_vals(self, param_name, vals):\n if(not(ut.is_iter(vals))):\n vals = [vals]\n return array(vals)","def _process_vals(self, param_name, vals):\n if(not(ut.is_iter(vals))):\n vals = [vals]\n return array(vals)","def __getitem__(self, idx):\n return self.getitem(idx)","def __getitem__(self, key):\n return self.__values.__getitem__(key)","def as_array(value):\n\tif not isinstance(value, list):\n\t\treturn [value]\n\treturn value","def values(self, *keys: _K) -> t.List[t.Any]: # type: ignore[override]\n if keys:\n d: t.List[t.Any] = []\n for key in keys:\n try:\n i = self.index(key)\n except KeyError:\n d.append(None)\n else:\n d.append(self[i])\n return d\n return list(self)","def getlist(self, key):\n \n value = self.get(key, [])\n if value is None or isinstance(value, (list, tuple)):\n return value\n else:\n return [value]","def Array( *args ):\n tArray = ()\n for arg in args:\n tArray += (arg,)\n return tArray","def Array( *args ):\n tArray = ()\n for arg in args:\n tArray += (arg,)\n return tArray","def get_all(cls, exclude_values: Iterator['CommonBucksType'] = None) -> Tuple['CommonBucksType']:\n if exclude_values is None:\n exclude_values = (cls.INVALID,)\n # noinspection PyTypeChecker\n value_list: Tuple[CommonBucksType, ...] = tuple([value for value in cls.values if value not in exclude_values])\n return value_list","def get_many(self, keys, default=None):\n raise NotImplementedError()","def __getitem__(self, index):\n if isinstance(index, types.SliceType):\n return [self._main[key] for key in self._main._sequence[index]]\n else:\n return self._main[self._main._sequence[index]]","def __getitem__(self, key: K) -> List[V]:\n return self._table.get(key)","def _build_iterable(self):","def new_array(cls):\n return cls.for_value({})","def __getitem__(self, idx):\n pass","def __getitem__(self, idx):\n pass","def __array__(self):\n return self.to_array()","def __getitem__(self, index):\n raise NotImplementedError","def as_name_list(cls, lower=True, **kwargs):\n return cls.enum_class.as_name_list(lower=lower, **kwargs)","def __array__(self, dtype=None) -> np.ndarray:\n return self.values","def __getitem__(self, key):\n try:\n if utils.is_str(key):\n key = utils.force_name_case(key)\n return next(enum for enum in self if enum.name == key)\n else:\n return self._enums[key]\n except (StopIteration, TypeError, KeyError, IndexError):\n raise KeyError(\"There is no enum with the name/index '%s' in the '%s' bitfield!\" % (key, self.name))","def __getitem__(self, *args, **kwargs): # real signature unknown; restored from __doc__\n pass","def _as_list(arr):\n if not isinstance(arr, (list, tuple)):\n return [arr]\n return arr","def __getitem__(self, _):\n raise NotImplementedError()","def sequential_enum(*sequential, **named):\n enums = dict(zip(sequential, range(len(sequential))), **named)\n return type('Enum', (), enums)","def native_type(value):\n return getattr(value, 'tolist', lambda: value)()","def __getitem__(self, index):\n pass","def __getitem__(self, index):\n pass"],"string":"[\n \"def test_additional_properties_with_array_of_enums(self):\\n pass\",\n \"def convertToEnumItemArray(byte: int, enumType: cern.japc.value.EnumType) -> typing.List[cern.japc.value.EnumItem]:\\n ...\",\n \"def convertToEnumItemSetArray(byte: int, enumType: cern.japc.value.EnumType) -> typing.List[cern.japc.value.EnumItemSet]:\\n ...\",\n \"def convertToEnumItemArray(boolean: bool) -> typing.List[cern.japc.value.EnumItem]:\\n ...\",\n \"def getlist(self, key, type=None):\\n if key not in self:\\n return []\\n values = super().__getitem__(key)\\n if type is not None:\\n values = [type(value) for value in values]\\n return values\",\n \"def convertToEnumItemSetArray(boolean: bool) -> typing.List[cern.japc.value.EnumItemSet]:\\n ...\",\n \"def type_array():\\n return []\",\n \"def __getitem__(self, idx):\\n return self.GetArray(idx)\",\n \"def __getitem__(self, idx):\\n return self.GetArray(idx)\",\n \"def __getattr__(self, name):\\n try:\\n return self[self.argpos(name)]\\n except:\\n pass\\n return list.__getattr__(self, name)\",\n \"def __getitem__(self, index):\\n return self.to_list()[index]\",\n \"def enum(self):\\n return plist(enumerate(self), root=self.__root__)\",\n \"def test_array_of_enums(self):\\n from petstore_api.model import array_of_enums, string_enum\\n endpoint = self.api.array_of_enums\\n assert endpoint.openapi_types['array_of_enums'] == (array_of_enums.ArrayOfEnums,)\\n assert endpoint.settings['response_type'] == (array_of_enums.ArrayOfEnums,)\\n\\n # serialization + deserialization works\\n with patch.object(RESTClientObject, 'request') as mock_method:\\n value = [string_enum.StringEnum(\\\"placed\\\")]\\n body = array_of_enums.ArrayOfEnums(value)\\n value_simple = [\\\"placed\\\"]\\n mock_method.return_value = self.mock_response(value_simple)\\n\\n response = endpoint(array_of_enums=body)\\n self.assert_request_called_with(mock_method, 'http://petstore.swagger.io:80/v2/fake/refs/array-of-enums', value_simple)\\n\\n assert isinstance(response, array_of_enums.ArrayOfEnums)\\n assert response.value == value\",\n \"def asArray( cls, value, typeCode=None ):\\n if value is None:\\n return value\\n else:\\n return cls.contiguous( value, typeCode )\",\n \"def enum(**enums):\\n return type('Enum',(),enums)\",\n \"def get_possible_array_value(args, key):\\n if not args:\\n return []\\n if key in args:\\n return [args.get(key)]\\n return args.getlist(key + '[]')\",\n \"def getStatusValues(self):\\n return []\",\n \"def get_list(self, key: str, default=[]) -> list:\\n try:\\n return self[key]\\n except KeyError:\\n return default\",\n \"def _listarr(self, func):\\n return [func(self.ptr, i) for i in range(len(self))]\",\n \"def toArray(self, *args):\\n pass\",\n \"def __getitem__(self, pos):\\n\\t\\t# Handle if a slice of positions are passed in by grabbing all the values\\n\\t\\t# and returning them in a list.\\n\\t\\t#pprint(pos)\\n\\t\\tif isinstance(pos, slice):\\n\\t\\t\\treturn self.leds[pos]\\n\\t\\t# Else assume the passed in value is a number to the position.\\n\\t\\telse:\\n\\t\\t\\treturn self.leds\",\n \"def enum(self):\\r\\n raise NotImplementedError\",\n \"def oper_array(fct, arr, init):\\n result = []\\n for i, item in enumerate(arr):\\n result.append(fct(result[i-1] if result else init, item))\\n return result\",\n \"def array_form(self):\\n return tuple(self)\",\n \"def getlist(self, key):\\n try:\\n return dict.__getitem__(self, key)\\n except KeyError:\\n return []\",\n \"def handle_enum(enum_annotations: Any) -> list:\\n result = []\\n for attribute in list(enum_annotations):\\n result.append(attribute.value)\\n return result\",\n \"def iflatten(self):\\n return _((e for es in self.array for e in es))\",\n \"def __iter__(self):\\n return iter(self._enums)\",\n \"def enum(**enums):\\n return type('Enum', (), enums)\",\n \"def __noop_list(self, *args, **kwargs):\\n return []\",\n \"def __getitem__(self, index):\\n return index, super().__getitem__(index)\",\n \"def flag(self, arr):\\n return arr\",\n \"def __getitem__(self, *args):\\n return self.data.__getitem__(*args)\",\n \"def lookup_array(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def lookup_array(self, *args, **kwargs): # real signature unknown\\n pass\",\n \"def getlist(self, k, default=_MISSING):\\n try:\\n return super(OrderedMultiDict, self).__getitem__(k)[:]\\n except KeyError:\\n if default is _MISSING:\\n return []\\n return default\",\n \"def __getitem__(self, key):\\n if not self.ordinal:\\n i = self.names().index('(%s==%s)' % (self.termname, str(key)))\\n return self()[i]\\n else:\\n v = self.namespace[self._name]\\n return np.array([(vv == key) for vv in v]).astype(np.float)\",\n \"def array_of(element: Type) -> ArrayType:\\n return ArrayType(element)\",\n \"def default_array(self, count: int) -> List[Any]:\\n return [self.default() for _ in range(count)]\",\n \"def Array(*args):\\n array = VBArray(len(args) - 1, Variant)\\n for idx in range(len(args)):\\n array[idx] = args[idx]\\n return array\",\n \"def enum(*sequential, **named):\\n enums = dict(zip(sequential, range(len(sequential))), **named)\\n return type('Enum', (), enums)\",\n \"def enum(*sequential, **named):\\n enums = dict(zip(sequential, range(len(sequential))), **named)\\n return type('Enum', (), enums)\",\n \"def enum(*sequential, **named):\\n enums = dict(zip(sequential, range(len(sequential))), **named)\\n return type('Enum', (), enums)\",\n \"def enum(*sequential, **named):\\n enums = dict(zip(sequential, range(len(sequential))), **named)\\n return type('Enum', (), enums)\",\n \"def __getitem__(self, index):\\n # type: (int) -> Any\\n items = list.__getitem__(self, index)\\n return type(self)(self._values(items)) if isinstance(index, slice) else self.value(items)\",\n \"def list_value(self) -> global___Expression.RepeatedValue:\",\n \"def array(self):\",\n \"def test_cast_list(self):\\n dim = Real(\\\"yolo\\\", \\\"uniform\\\", -3, 4)\\n assert dim.cast([\\\"1\\\", \\\"2\\\"]) == [1.0, 2.0]\",\n \"def __getitem__(self, item):\\n return self.getList()\",\n \"def test_cast_list(self):\\n dim = Integer(\\\"yolo\\\", \\\"uniform\\\", -3, 5)\\n assert dim.cast([\\\"1\\\", \\\"2\\\"]) == [1, 2]\",\n \"def __sub__(self, vs):\\n return [v for v in self.__elements if tuple(v) not in map(tuple, vs)]\",\n \"def _value(self) -> List[Any]:\\n ret = [\\n cast_to(val, self.subtype)\\n for sublist in self._stack\\n for val in sublist\\n ]\\n\\n if self.required and not ret:\\n raise PyParamValueError(ARGUMENT_REQUIRED)\\n self._stack = []\\n return ret\",\n \"def get_enumerations_from_bit_mask(enumeration, mask):\\n return [x for x in enumeration if (x.value & mask) == x.value]\",\n \"def __getitem__(self, pos):\\n if isinstance(pos, list): # pos is containing multiple indices as a list\\n return [self.__getitem__(pos=p) for p in pos]\\n elif pos is None:\\n return None\\n elif np.all(np.array([isinstance(p, (int, np.integer)) for p in pos])):\\n # pos is mapped to a single element (pos is composed of integer indices).\\n # just do rounding.\\n idx = []\\n for p, s in zip(pos, self.shape):\\n idx.append(p % s)\\n return self.elements[tuple(idx)]\\n else:\\n # pos is mapped to multiple indices. (possible examples include ([0:5, 3], [[1,2,3], 3], ...).\\n # Create a list containing the indices to iterate over, and return a numpy.ndarray containing items\\n # corresponding to the indices in the list.\\n # When the indices don't specify the lower boundary (e.g., [:5]), it iterates from 0.\\n # When the indices don't specify the upper boundary (e.g., [3:]), it iterates to the maximum index defined.\\n idx = None\\n for i, p in enumerate(pos):\\n idx = _extend_index_dim(idx, p, self.shape[i])\\n idx = np.asarray(idx)\\n # iterate and generate the list to return\\n item = np.empty(idx.shape[:-1], dtype=self.dtype) # -1 because the tuples in idx are flatten.\\n for i, _null in np.ndenumerate(item):\\n item[i] = self.__getitem__(pos=tuple(idx[i]))\\n return np.asarray(item)\",\n \"def optional(cls):\\n return []\",\n \"def __getitem__(self):\\n pass\",\n \"def __getitem__(self, index: slice) -> List:\\n\\n return self.data[index]\",\n \"def __call__(self, tokens: Union[Hashable, List[Hashable], Tuple[Hashable]])\\\\\\n -> Union[int, np.ndarray]:\\n return self[tokens]\",\n \"def __getitem__(self, *args):\\n return _ida_hexrays.fnum_array___getitem__(self, *args)\",\n \"def all(cls):\\n return []\",\n \"def unary_op(self):\\n return plist([op(x) for x in self], root=self.__root__)\",\n \"def slice(self, field):\\n return [getattr(r, field) for r in self.__elements__]\",\n \"def _always_array(value: str | list | None) -> list:\\n if value is None:\\n value = []\\n elif not isinstance(value, list):\\n value = [value]\\n return value\",\n \"def get_value(self) -> Union[Iterable[T], List[T]]:\\n return self.array\",\n \"def values(self) -> List:\\n pass\",\n \"def _init_as_list(arg):\\n if arg is None:\\n return []\\n elif isinstance(arg, str):\\n return [arg]\\n else:\\n return arg\",\n \"def getall(l, idx):\\n return [l[i] for i in idx]\",\n \"def __getitem__(self, keys):\\n if isinstance(keys, int):\\n return super().__getitem__(keys)\\n elif isinstance(keys, list):\\n return self.vectors(keys)\\n elif isinstance(keys, str):\\n return self.find(keys)\\n elif isinstance(keys, tuple):\\n return self.item(keys[0], keys[1])\\n elif isinstance(keys, slice):\\n return super().__getitem__(keys)\",\n \"def __get__(self,obj,objtype):\\n if not obj:\\n return [getattr(objtype,a) for a in self.attribs]\\n else:\\n return [getattr(obj,a) for a in self.attribs]\",\n \"def _get_list(self, key, operation, create=False, decode=False):\\n return self._get_by_type(key, operation, create, b'list', [], decode=decode)\",\n \"def getArrayList(self, arrayType):\\n if arrayType in self.arrayLists:\\n return self.arrayLists[arrayType]\",\n \"def c_array(ctype, values):\\n\\n arr = (ctype*len(values))()\\n arr[:] = values\\n return arr\",\n \"def _process_vals(self, param_name, vals):\\n if(not(ut.is_iter(vals))):\\n vals = [vals]\\n return array(vals)\",\n \"def _process_vals(self, param_name, vals):\\n if(not(ut.is_iter(vals))):\\n vals = [vals]\\n return array(vals)\",\n \"def __getitem__(self, idx):\\n return self.getitem(idx)\",\n \"def __getitem__(self, key):\\n return self.__values.__getitem__(key)\",\n \"def as_array(value):\\n\\tif not isinstance(value, list):\\n\\t\\treturn [value]\\n\\treturn value\",\n \"def values(self, *keys: _K) -> t.List[t.Any]: # type: ignore[override]\\n if keys:\\n d: t.List[t.Any] = []\\n for key in keys:\\n try:\\n i = self.index(key)\\n except KeyError:\\n d.append(None)\\n else:\\n d.append(self[i])\\n return d\\n return list(self)\",\n \"def getlist(self, key):\\n \\n value = self.get(key, [])\\n if value is None or isinstance(value, (list, tuple)):\\n return value\\n else:\\n return [value]\",\n \"def Array( *args ):\\n tArray = ()\\n for arg in args:\\n tArray += (arg,)\\n return tArray\",\n \"def Array( *args ):\\n tArray = ()\\n for arg in args:\\n tArray += (arg,)\\n return tArray\",\n \"def get_all(cls, exclude_values: Iterator['CommonBucksType'] = None) -> Tuple['CommonBucksType']:\\n if exclude_values is None:\\n exclude_values = (cls.INVALID,)\\n # noinspection PyTypeChecker\\n value_list: Tuple[CommonBucksType, ...] = tuple([value for value in cls.values if value not in exclude_values])\\n return value_list\",\n \"def get_many(self, keys, default=None):\\n raise NotImplementedError()\",\n \"def __getitem__(self, index):\\n if isinstance(index, types.SliceType):\\n return [self._main[key] for key in self._main._sequence[index]]\\n else:\\n return self._main[self._main._sequence[index]]\",\n \"def __getitem__(self, key: K) -> List[V]:\\n return self._table.get(key)\",\n \"def _build_iterable(self):\",\n \"def new_array(cls):\\n return cls.for_value({})\",\n \"def __getitem__(self, idx):\\n pass\",\n \"def __getitem__(self, idx):\\n pass\",\n \"def __array__(self):\\n return self.to_array()\",\n \"def __getitem__(self, index):\\n raise NotImplementedError\",\n \"def as_name_list(cls, lower=True, **kwargs):\\n return cls.enum_class.as_name_list(lower=lower, **kwargs)\",\n \"def __array__(self, dtype=None) -> np.ndarray:\\n return self.values\",\n \"def __getitem__(self, key):\\n try:\\n if utils.is_str(key):\\n key = utils.force_name_case(key)\\n return next(enum for enum in self if enum.name == key)\\n else:\\n return self._enums[key]\\n except (StopIteration, TypeError, KeyError, IndexError):\\n raise KeyError(\\\"There is no enum with the name/index '%s' in the '%s' bitfield!\\\" % (key, self.name))\",\n \"def __getitem__(self, *args, **kwargs): # real signature unknown; restored from __doc__\\n pass\",\n \"def _as_list(arr):\\n if not isinstance(arr, (list, tuple)):\\n return [arr]\\n return arr\",\n \"def __getitem__(self, _):\\n raise NotImplementedError()\",\n \"def sequential_enum(*sequential, **named):\\n enums = dict(zip(sequential, range(len(sequential))), **named)\\n return type('Enum', (), enums)\",\n \"def native_type(value):\\n return getattr(value, 'tolist', lambda: value)()\",\n \"def __getitem__(self, index):\\n pass\",\n \"def __getitem__(self, index):\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5966134","0.586653","0.57834995","0.5671007","0.5469387","0.5347836","0.51718843","0.5109061","0.5109061","0.51058966","0.50422406","0.5024083","0.49625045","0.4904923","0.49036974","0.48679268","0.48582023","0.48460153","0.48249942","0.48193696","0.481613","0.4814986","0.48136583","0.48053566","0.48036107","0.47792184","0.47655365","0.47609043","0.4757647","0.47515917","0.47495478","0.4747147","0.47444627","0.47341266","0.47341266","0.47138545","0.4713471","0.47102037","0.47043788","0.46971315","0.4687132","0.4687132","0.4687132","0.4687132","0.46817052","0.4676296","0.46752295","0.4672186","0.466093","0.46583557","0.46520212","0.46470496","0.464646","0.4640953","0.4640568","0.46397528","0.462892","0.4625517","0.46210793","0.46166712","0.46095538","0.460417","0.46041107","0.46009013","0.45890263","0.4588586","0.45847234","0.45812312","0.4574054","0.45714492","0.4569636","0.45673466","0.45629406","0.45629406","0.45598316","0.45551926","0.45533046","0.4550612","0.4548368","0.45458877","0.45458877","0.45446134","0.45403972","0.45382905","0.4535502","0.45342577","0.452729","0.45237994","0.45237994","0.45112887","0.45090997","0.4506496","0.4506352","0.45011044","0.44961894","0.44942915","0.4491923","0.44914183","0.44894692","0.44879633","0.44879633"],"string":"[\n \"0.5966134\",\n \"0.586653\",\n \"0.57834995\",\n \"0.5671007\",\n \"0.5469387\",\n \"0.5347836\",\n \"0.51718843\",\n \"0.5109061\",\n \"0.5109061\",\n \"0.51058966\",\n \"0.50422406\",\n \"0.5024083\",\n \"0.49625045\",\n \"0.4904923\",\n \"0.49036974\",\n \"0.48679268\",\n \"0.48582023\",\n \"0.48460153\",\n \"0.48249942\",\n \"0.48193696\",\n \"0.481613\",\n \"0.4814986\",\n \"0.48136583\",\n \"0.48053566\",\n \"0.48036107\",\n \"0.47792184\",\n \"0.47655365\",\n \"0.47609043\",\n \"0.4757647\",\n \"0.47515917\",\n \"0.47495478\",\n \"0.4747147\",\n \"0.47444627\",\n \"0.47341266\",\n \"0.47341266\",\n \"0.47138545\",\n \"0.4713471\",\n \"0.47102037\",\n \"0.47043788\",\n \"0.46971315\",\n \"0.4687132\",\n \"0.4687132\",\n \"0.4687132\",\n \"0.4687132\",\n \"0.46817052\",\n \"0.4676296\",\n \"0.46752295\",\n \"0.4672186\",\n \"0.466093\",\n \"0.46583557\",\n \"0.46520212\",\n \"0.46470496\",\n \"0.464646\",\n \"0.4640953\",\n \"0.4640568\",\n \"0.46397528\",\n \"0.462892\",\n \"0.4625517\",\n \"0.46210793\",\n \"0.46166712\",\n \"0.46095538\",\n \"0.460417\",\n \"0.46041107\",\n \"0.46009013\",\n \"0.45890263\",\n \"0.4588586\",\n \"0.45847234\",\n \"0.45812312\",\n \"0.4574054\",\n \"0.45714492\",\n \"0.4569636\",\n \"0.45673466\",\n \"0.45629406\",\n \"0.45629406\",\n \"0.45598316\",\n \"0.45551926\",\n \"0.45533046\",\n \"0.4550612\",\n \"0.4548368\",\n \"0.45458877\",\n \"0.45458877\",\n \"0.45446134\",\n \"0.45403972\",\n \"0.45382905\",\n \"0.4535502\",\n \"0.45342577\",\n \"0.452729\",\n \"0.45237994\",\n \"0.45237994\",\n \"0.45112887\",\n \"0.45090997\",\n \"0.4506496\",\n \"0.4506352\",\n \"0.45011044\",\n \"0.44961894\",\n \"0.44942915\",\n \"0.4491923\",\n \"0.44914183\",\n \"0.44894692\",\n \"0.44879633\",\n \"0.44879633\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":88590,"cells":{"query":{"kind":"string","value":"Decrypt this guardian's share of one or more ballots"},"document":{"kind":"string","value":"def decrypt_ballot_shares(\n request: DecryptBallotSharesRequest = Body(...),\n scheduler: Scheduler = Depends(get_scheduler),\n) -> Any:\n ballots = [\n CiphertextAcceptedBallot.from_json_object(ballot)\n for ballot in request.encrypted_ballots\n ]\n context = CiphertextElectionContext.from_json_object(request.context)\n guardian = convert_guardian(request.guardian)\n\n shares = [\n compute_decryption_share_for_ballot(guardian, ballot, context, scheduler)\n for ballot in ballots\n ]\n\n response = DecryptBallotSharesResponse(\n shares=[write_json_object(share) for share in shares]\n )\n\n return response"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_pam_secret(self, key):\n\n\n privateKeyA=self.rand() \n privateKeyB=self.rand() \n publicKeyA = int(pow(genrated,privateKeyA,prime))\n publicKeyB = int(pow(genrated,privateKeyB,prime))\n\n resp = self.process(\n requests.get(f\"{self.api_url}/secretman/GetSecretV2/{key}\" ,\n headers=self.headers(self.api_key,publicKeyA,publicKeyB )\n )\n ).text\n \n sharedKeyA = int(pow(int(json.loads(resp)['keyA']),privateKeyA,prime))\n sharedKeyB = int(pow(int(json.loads(resp)['keyB']),privateKeyB,prime))\n finalSec = sharedKeyA ** sharedKeyB\n return aes256.decrypt(json.loads(resp)['value'], str(finalSec)).decode(\"utf-8\")","def main():\n\n prime = 0xffffffffffffffffc90fdaa22168c234c4c6628b80dc1cd129024e088a67cc74020bbea63b139b22514a08798e3404ddef9519b3cd3a431b302b0a6df25f14374fe1356d6d51c245e485b576625e7ec6f44c42e9a637ed6b0bff5cb6f406b7edee386bfb5a899fa5ae9f24117c4b1fe649286651ece45b3dc2007cb8a163bf0598da48361c55d39a69163fa8fd24cf5f83655d23dca3ad961c62f356208552bb9ed529077096966d670c354e4abc9804f1746c08ca237327ffffffffffffffff\n base = 2\n \n connection = diffiehellman_mitm_sim(prime, base)\n\n # intercept alices public key\n prime, base , _ = next(connection)\n\n # send prime instead of alices public key to bob. Recieve Bobs public key, \n # which we forget as it is not needs. The shared kill will be 0.\n\n connection.send((prime, base, prime))\n\n #Send prime as bob's public key to alice. We have ensured that the shared\n #hared secret key is 0. Recieve Alice's ciphertext for bob\n ciphertext_a2b = connection.send(prime)\n\n # decrypt\n malcolm = AES_CBC(SHA1(bso.int_to_bytes(0)).digest()[:16], b'0'*16)\n messages = []\n messages.append(bso.remove_padding_pkcs7(malcolm.decrypt(ciphertext_a2b[:-16], ciphertext_a2b[-16:])))\n\n #Send the ciphertext to bob. Recieve his response\n ciphertext_b2a = connection.send(ciphertext_a2b)\n\n messages.append(bso.remove_padding_pkcs7(malcolm.decrypt(ciphertext_b2a[:-16], ciphertext_b2a[-16:])))\n\n assert messages[0] == b'Message to Bob'\n assert messages[1] == b'Message to Alice'\n\n \n return","def _ready_to_decrypt(self, shares: Dict[GuardianId, DecryptionShare]) -> bool:\n # If all guardian shares are represented including if necessary\n # the missing guardians reconstructed shares, the decryption can be made\n return len(shares) == self._context.number_of_guardians","def shared_decryption(sk_shares, ciphertext):\n if len(sk_shares) < 1:\n raise('No shares given')\n used_shares = get_correct_num_of_shares(sk_shares)\n plaintext_shares = [sk_share.compute_plaintext_share(\n ciphertext) for sk_share in used_shares]\n lambdas = [calc_lambda(plaintext_shares, share[0], sk_shares[0].precomputed_fac) for i, share in enumerate(plaintext_shares)]\n return sk_shares[0].reconstruct_plaintext(plaintext_shares), plaintext_shares, lambdas","def keygen(cls, bits, num_shares, threshold):\n if threshold < 2:\n raise('Threshold should be at least 2, but is {}'.format(threshold))\n primes = PrimeStorage()\n ((p, p_), (q, q_)) = primes.getRandomSafePrimes(bits // 2)\n\n n = p * q\n m = p_ * q_\n\n # find secret\n d = ext_euclid(n, m)\n\n pk = PublicPaillierKey(n)\n\n # Shamir secret sharing: determine polynomial\n coeffs = [d] + [randint(0, n*m) for _ in range(threshold-1)]\n # determine shares\n shares = [eval_polynomial(coeffs, i, n*m)\n for i in range(1, num_shares + 1)]\n key_shares = [PrivateKeyShare(\n shares[i-1], i, len(shares), threshold, pk) for i in range(1, num_shares + 1)]\n\n # - v, a generator of Z^*_(n^2)\n # - verification key for each decryption party\n\n return pk, key_shares","def diffiehellman_mitm_sim(prime, base):\n alice = {}\n\n #Alice generates their public key an sends to 'bob'\n alice['dh'] = DiffieHellman(prime, base, secret_key=secrets.randbelow(prime))\n alice_pub = alice['dh'].gen_public_key()\n\n (prime, base, key_for_bob) = yield (prime, base, alice_pub)\n\n \n\n #bob recieves 'alice's' public key, generates their own public key and\n #the shared key. Sends their public key ot 'alice'\n bob = {'dh':DiffieHellman(prime, base, secret_key=secrets.randbelow(prime))}\n bob_pup = bob['dh'].gen_public_key()\n bob['dh'].gen_shared_key(key_for_bob)\n\n key_for_alice = yield bob_pup\n\n ### Alice recieves Bob's public key, generates the shared key and encrypts\n ### message for bob\n\n alice['dh'].gen_shared_key(key_for_alice)\n \n alice['sha1'] = SHA1(bso.int_to_bytes(alice['dh'].shared_key))\n alice['cipher'] = AES_CBC(alice['sha1'].digest()[:16], secrets.token_bytes(16))\n alice_ciphertext = alice['cipher'].encrypt(b'Message to Bob')\n alice_ciphertext += alice['cipher'].IV\n\n ciphertext_for_bob = yield alice_ciphertext\n \n #Bob recieves the ciphertext, decrypts it and send a reply.\n\n bob['sha1'] = SHA1(bso.int_to_bytes(bob['dh'].shared_key))\n bob['cipher'] = AES_CBC(bob['sha1'].digest()[:16], secrets.token_bytes(16))\n bob_ciphertext = bob['cipher'].encrypt(b'Message to Alice')\n bob_ciphertext += bob['cipher'].IV\n\n ciphertext_for_alice = yield bob_ciphertext\n\n ### Finally alice decrypts bobs reply\n\n alice['cipher'].decrypt(ciphertext_for_alice[:-16], ciphertext_for_alice[-16:])","def dh_decrypt(priv, ciphertext):\n Group1,private, public = dh_get_key()#generate new DH pair for Bob\n iv=ciphertext[0]\n cipher=ciphertext[1]\n tag=ciphertext[2]\n pubA=ciphertext[3]\n \n #Bob derives shared secret key by multiplying his public key with Alice's private key\n shared2 = pubA.pt_mul(priv)#qA * dB\n print \"key from dec is\", shared2\n\n hashedKey=sha256(shared2.export()).digest()\n \n aes = Cipher(\"aes-128-gcm\")\n plain = aes.quick_gcm_dec(hashedKey[:16], iv, cipher, tag)#where to get IV and tag from ???\n \n return plain.encode(\"utf8\")","def decrypt(self, data):","def encrypt_ballot(request, election):\n answers = utils.from_json(request.POST['answers_json'])\n ev = homomorphic.EncryptedVote.fromElectionAndAnswers(election, answers)\n return ev.ld_object.includeRandomness().toJSONDict()","def _save_ballot_shares(\n self,\n guardian_id: GuardianId,\n guardians_ballot_shares: Dict[BallotId, Optional[DecryptionShare]],\n ) -> None:\n for ballot_id, guardian_ballot_share in guardians_ballot_shares.items():\n shares = self._ballot_shares.get(ballot_id)\n if shares is None:\n shares = {}\n if guardian_ballot_share is not None:\n shares[guardian_id] = guardian_ballot_share\n self._ballot_shares[ballot_id] = shares","def _decrypt_secret(\n self, \n encryption_key: str,\n secret_list: List,\n secret_name: str\n ):\n f = Fernet(\n bytes(encryption_key, \"utf-8\")\n )\n secret=None\n if 'secrets' in secret_list:\n if secret_name in secret_list['secrets']:\n secret = f.decrypt(\n bytes(secret_list['secrets'][secret_name], \"utf-8\")\n ).decode('UTF-8')\n #self.log.log_success(\n # f'{secret_name} : {secret}'\n #)\n return secret","def cast(box,I,choice='White Ballot'):\n smallringsize = __smallringsize__\n IKey = Crypto.PublicKey.RSA.importKey(open('keys/%s.pem'%I).read())\n fullring,index,i,crypted,d2s,found,cands = [],0,0,None,[],False,{}\n for l in open(box).readlines():\n if re.match(r'\\(',l):\n name,h,num,d1,d2,url = eval(l)\n tsprk = urllib.urlopen(url).read()\n d2s = eval(urllib.urlopen(url+'?d='+d2).read())\n elif re.match(r'\\{',l):\n cands = eval(l)\n cands['White Ballot'] = 'ok'\n elif reg(re.match(r'\\.([\\w\\-]{10})\\s(\\d{0,10})\\s([\\w\\-]{10,200})\\s([\\w\\-]{10,200})$',l)):\n if reg.v.group(3) == itob64(IKey.n):\n index,found = i,True\n fullring.append(IKey)\n else:\n fullring.append(myKey(b64toi(reg.v.group(3))))\n i += 1\n if not found:\n return '\\'%s\\' is not registered!'%I\n if not cands.has_key(choice):\n return '\\'%s\\' choice is not one of selectable'%choice\n crypted = rsa(myKey(b64toi(d2s[0]))).encrypt(b64toi(base64.urlsafe_b64encode(choice)))\n pos,lind = setsample(len(fullring),index,smallringsize)\n smallring = getsample(fullring,lind,smallringsize) if lind else fullring\n open(box,'a').write('!%s %s %s\\n'%(lind,crypted,ringBL(smallring).sign(crypted,pos)))","def decryption_process(name, modulus, passed, secret, key):\n\tprint('\\n', name, 'uses the public number they were sent--', str(passed), \n\t'and raises it to the power of their original secret key number--', str(secret))\n\tprint('Then', name, 'uses the original public modulus--', str(modulus), 'and takes the modulus to find the shared secret key',\n\t\tstr(key) + '.')\n\tprint(\"This process's equation is as follows:\", str(passed) + '^' + str(secret), 'mod', \n\t\tstr(modulus), '=', str(key))","def __decrypt_secrets(self, secrets):\n assert self.decrypter != None\n return [self.decrypter.decrypt(secret) for secret in secrets]","def decrypt(crypto, priv):\r\n string = rsa.encrypt(crypto, priv)\r\n string = livingDead.utfE(crypto)\r\n return crypto","def test_secretbox_enc_dec(self):\n # Encrypt with sk\n encrypted_data = nacl.secretbox_encrypt(data=self.unencrypted_data, sk=self.sk)\n\n # Decrypt with sk\n decrypted_data = nacl.secretbox_decrypt(data=encrypted_data, sk=self.sk)\n\n self.assertEqual(self.unencrypted_data, decrypted_data)","def decrypt(self, secret):\n return self._transform(secret, self._decoder)","def decrypt(self, secret):\n return self._transform(secret, self._decoder)","def _des_crypt(self, block, crypt_type):\n block = self._permutate(self.__ip, block)\n num_bits = 8 * self.block_size\n self.L = block[:num_bits // 2]\n self.R = block[num_bits // 2:]\n\n if crypt_type == self.ENCRYPT:\n key_iter = 0\n key_delt = 1\n else:\n key_iter = 15\n key_delt = -1\n\n for i in range(0, 16):\n temp_R = self.R\n # expand 32-bit R into 48-bit R\n self.R = self._permutate(self.__expansion_table, self.R)\n self.R = list(map(lambda x, y: x ^ y, self.R, self.Kn[key_iter]))\n B = [self.R[:6], self.R[6:12], self.R[12:18], self.R[18:24],\n self.R[24:30], self.R[30:36], self.R[36:42], self.R[42:]]\n\n # permute B[1] to B[8] using the S-boxes\n pos = 0\n Bn = [0] * 32\n for j in range(0, 8):\n # offsets\n m = (B[j][0] << 1) + (B[j][5])\n n = (B[j][1] << 3) + (B[j][2] << 2) + (B[j][3] << 1) + (B[j][4])\n\n # find the permutation value\n v = self.__sbox[j][(m << 4) + n]\n\n # turn value into bits\n Bn[pos] = (v & 8) >> 3\n Bn[pos+1] = (v & 4) >> 2\n Bn[pos+2] = (v & 2) >> 1\n Bn[pos+3] = v & 1\n\n pos += 4\n\n self.R = self._permutate(self.__p, Bn)\n\n self.R = list(map(lambda x, y: x ^ y, self.R, self.L))\n\n self.L = temp_R\n\n key_iter += key_delt\n\n self.final = self._permutate(self.__fp, self.R + self.L)\n return self.final","def deal(self):\n hands = sample(self.deck, 13) #random sample so no need to shuffle\n hand1, hand2, flip = hands[:6], hands[6:-1], hands[-1]\n return hand1, hand2, flip","def generateShares(self,secret,n,k):\n # generate a random polynomial\n a = np.zeros((k,),dtype=self.stype)\n for i in range(0,k-1): # select random coefficients\n a[i] = self.F.GetRandomElement()\n a[k-1] = secret # secret is the last element\n\n # evaluate the polynomial at 1,2,...,n.\n D = {} # shares\n for i in range(0,n):\n D[i+1] = self._evalPoly(a,i+1)\n return D","def _key_share(self, grease):\n ext = b\"\\x00\\x33\"\n\n # Add grease value if necessary.\n if grease:\n share_ext = self._choose_grease()\n share_ext += b\"\\x00\\x01\\x00\"\n else:\n share_ext = b\"\"\n\n group = b\"\\x00\\x1d\"\n share_ext += group\n key_exchange_length = b\"\\x00\\x20\"\n share_ext += key_exchange_length\n share_ext += os.urandom(32)\n second_length = len(share_ext)\n first_length = second_length+2\n ext += struct.pack(\">H\", first_length)\n ext += struct.pack(\">H\", second_length)\n ext += share_ext\n\n return ext","def decrypt_pass(self, cont):\r\n try:\r\n iv = cont[3:15]\r\n data = cont[15:]\r\n ciph = AES.new(self.chrome_key(), AES.MODE_GCM, iv)\r\n decrypted = ciph.decrypt(data)\r\n decrypted = decrypted[:-16].decode()\r\n return decrypted\r\n except:\r\n decrypted = win32crypt.CryptUnprotectData(buff, None, None, None, 0)\r\n return decrypted[1]","def obfuscate(self):\n r = self.public_key.get_random_lt_n()\n r_pow_n = powmod(r, self.public_key.n, self.public_key.nsquare)\n self.__ciphertext = self.__ciphertext * r_pow_n % self.public_key.nsquare\n self.__is_obfuscated = True","def get_secret(self):\n return Buffer.from_mpz(self._secret_key)","def decode(self, crypto):","def Obfuscate(self,passphrase=None,public_attributes=[]):\n\t\t\n\t\tnew_me = self.Secure(passphrase,['ID','status'])\n\n\t\treturn new_me","def mulligan(self):\n self.deck.extend(self.hand) # Put hand back in deck\n self.hand.clear() # Clear hand\n random.shuffle(self.deck) # Shuffle deck\n self.draw() # Redraw cards","def decrypt(self, secret):\n return str.translate(secret, self._decoder)","def main():\n # key = random(1024)\n # ciphertexts = [encrypt(key, msg) for msg in MSGS]\n\n # Get key and secret message\n knownPlain2 = \"The nice thing about Keeyloq is now we cryptographers can drive a lot of fancy cars - Dan Boneh\"\n key = strxor(ciphertexts[2], knownPlain2)\n secret = strxor(target, key)\n\n print \"Key: \" + key\n print \"Key (Hex): \" + key.encode(\"hex\")\n print \"Secret: \" + secret","def generate_sharedsecret_bytes(self):\n return number_to_string(\n self.generate_sharedsecret(),\n self.private_key.curve.order)","def combine_shares(share_list: List[bytes]) -> bytes:\n unpickled_share_list: List[List[Tuple[int, bytes]]] = [\n cast(List[Tuple[int, bytes]], pickle.loads(share)) for share in share_list\n ]\n\n chunk_num = len(unpickled_share_list[0])\n secret_padded = bytearray(0)\n chunk_shares_list: List[List[Tuple[int, bytes]]] = []\n for i in range(chunk_num):\n chunk_shares: List[Tuple[int, bytes]] = []\n for share in unpickled_share_list:\n chunk_shares.append(share[i])\n chunk_shares_list.append(chunk_shares)\n\n with ThreadPoolExecutor(max_workers=10) as executor:\n for chunk in executor.map(_shamir_combine, chunk_shares_list):\n secret_padded += chunk\n\n secret = unpad(secret_padded, 16)\n return bytes(secret)","def decrypt(self, password):\r\n\r\n key = self.config.get_string(\"gox\", \"secret_key\")\r\n sec = self.config.get_string(\"gox\", \"secret_secret\")\r\n if sec == \"\" or key == \"\":\r\n return self.S_NO_SECRET\r\n\r\n # pylint: disable=E1101\r\n hashed_pass = hashlib.sha512(password.encode(\"utf-8\")).digest()\r\n crypt_key = hashed_pass[:32]\r\n crypt_ini = hashed_pass[-16:]\r\n aes = AES.new(crypt_key, AES.MODE_OFB, crypt_ini)\r\n try:\r\n encrypted_secret = base64.b64decode(sec.strip().encode(\"ascii\"))\r\n self.secret = aes.decrypt(encrypted_secret).strip()\r\n self.key = key.strip()\r\n except ValueError:\r\n return self.S_FAIL\r\n\r\n # now test if we now have something plausible\r\n try:\r\n print(\"testing secret...\")\r\n # is it plain ascii? (if not this will raise exception)\r\n dummy = self.secret.decode(\"ascii\")\r\n # can it be decoded? correct size afterwards?\r\n if len(base64.b64decode(self.secret)) != 64:\r\n raise Exception(\"decrypted secret has wrong size\")\r\n\r\n print(\"testing key...\")\r\n # key must be only hex digits and have the right size\r\n hex_key = self.key.replace(\"-\", \"\").encode(\"ascii\")\r\n if len(binascii.unhexlify(hex_key)) != 16:\r\n raise Exception(\"key has wrong size\")\r\n\r\n print(\"ok :-)\")\r\n return self.S_OK\r\n\r\n except Exception as exc:\r\n # this key and secret do not work :-(\r\n self.secret = \"\"\r\n self.key = \"\"\r\n print(\"### Error occurred while testing the decrypted secret:\")\r\n print(\" '%s'\" % exc)\r\n print(\" This does not seem to be a valid MtGox API secret\")\r\n return self.S_FAIL","def sym_dec(self, ciph, passphrase):\n (rfd, wfd) = xpipe()\n os.write(wfd, passphrase + '\\n')\n plain = xsystem([self.sslname, self.symmetric, '-d', '-pass',\n 'fd:' + str(rfd)], ciph)\n xclose(wfd)\n xclose(rfd)\n if not plain:\n warning('keymanagement: Unable to decrypt because %s does not exist\\n' %(self.sslname))\n return None\n\n return plain","def genKey(self, otherKey):\n self.sharedSecret = self.genSecret(self.privateKey, otherKey)\n #print(\"Shared secret:\")\n #print(self.sharedSecret)\n s = hashlib.sha256()\n s.update(bytes(str(self.sharedSecret).encode()))\n self.key = s.digest()","def generate_sharedsecret(self):\n return self._get_shared_secret(self.public_key)","def session_key(self, public_B):\n raw_secret = gmp.powmod(\n public_B.to_mpz(),\n self._secret_key,\n self._dh_p\n )\n\n # Hash the secret to create a key\n h_256 = SHA256.new()\n h_256.update(raw_secret.digits(10))\n raw_key = h_256.digest()\n\n return Buffer(raw_key)","def decrypt(self, buffer):\n try:\n ct = base64.b64decode(buffer)\n except:\n print('f a i l')\n return bytes('fail')\n\n cipher = AES.new(self.psk, AES.MODE_GCM, FIXED_IV)\n pt = unpad(cipher.decrypt(ct), AES.block_size)\n return pt","def prompt_encrypt(self):\r\n print(\"Please copy/paste key and secret from MtGox and\")\r\n print(\"then provide a password to encrypt them.\")\r\n print(\"\")\r\n\r\n\r\n key = input(\" key: \").strip()\r\n secret = input(\" secret: \").strip()\r\n while True:\r\n password1 = getpass.getpass(\" password: \").strip()\r\n if password1 == \"\":\r\n print(\"aborting\")\r\n return\r\n password2 = getpass.getpass(\"password (again): \").strip()\r\n if password1 != password2:\r\n print(\"you had a typo in the password. try again...\")\r\n else:\r\n break\r\n\r\n # pylint: disable=E1101\r\n hashed_pass = hashlib.sha512(password1.encode(\"utf-8\")).digest()\r\n crypt_key = hashed_pass[:32]\r\n crypt_ini = hashed_pass[-16:]\r\n aes = AES.new(crypt_key, AES.MODE_OFB, crypt_ini)\r\n\r\n # since the secret is a base64 string we can just just pad it with\r\n # spaces which can easily be stripped again after decryping\r\n print(len(secret))\r\n secret += \" \" * (16 - len(secret) % 16)\r\n print(len(secret))\r\n secret = base64.b64encode(aes.encrypt(secret)).decode(\"ascii\")\r\n\r\n self.config.set(\"gox\", \"secret_key\", key)\r\n self.config.set(\"gox\", \"secret_secret\", secret)\r\n self.config.save()\r\n\r\n print(\"encrypted secret has been saved in %s\" % self.config.filename)","def decipher(self):\n plaintext = \"\"\n for ct, key_char in zip(self.text, self.key):\n char_index = self.char_block.rows[key_char].index(ct)\n plaintext += self.char_block.alphabet[char_index]\n print(plaintext)","def splitImage(image, shareFile1=\"share1.tif\", shareFile2=\"share2.tif\"):\n\n _, expandedPad = makePad(Image.open(image).size, shareFile1)\n expandedCiphertext = makeCryptograph(str(image), shareFile2)\n print(expandedPad,expandedCiphertext)\n return expandedPad, expandedCiphertext","def prompt_decrypt(self):\r\n if self.know_secret():\r\n return self.S_OK\r\n\r\n key = self.config.get_string(\"gox\", \"secret_key\")\r\n sec = self.config.get_string(\"gox\", \"secret_secret\")\r\n if sec == \"\" or key == \"\":\r\n return self.S_NO_SECRET\r\n\r\n if self.password_from_commandline_option:\r\n password = self.password_from_commandline_option\r\n else:\r\n password = getpass.getpass(\"enter passphrase for secret: \")\r\n\r\n result = self.decrypt(password)\r\n if result != self.S_OK:\r\n print(\"\")\r\n print(\"secret could not be decrypted\")\r\n answer = input(\"press any key to continue anyways \" \\\r\n + \"(trading disabled) or 'q' to quit: \")\r\n if answer == \"q\":\r\n result = self.S_FAIL_FATAL\r\n else:\r\n result = self.S_NO_SECRET\r\n return result","def decrypt(cls, ciphertext_and_tag, aad, key, iv):","def decrypt(self, sentence, pad):\r\n sentence = list(sentence)\r\n decrypted_sentence = []\r\n x = list(\"abcdefghijklmnopqrstuvwxyz\")\r\n l = len(x)\r\n y = pad \r\n z = list(zip(x, y))\r\n z.append((\" \", \" \"))\r\n for i in sentence:\r\n if i.lower() not in x:\r\n decrypted_sentence.append(i)\r\n continue \r\n for a in z:\r\n if i.lower() == a[1]:\r\n if i.isupper():\r\n decrypted_sentence.append(a[0].upper())\r\n else:\r\n decrypted_sentence.append(a[0])\r\n decrypted_sentence = \"\".join(decrypted_sentence)\r\n return decrypted_sentence","def Private(self):\n self.Send(self.EncryptString('private\\n'))\n print self.DecryptString(self.Recv(4096))\n print self.DecryptString(self.Recv(4096))","def shared_key(private_key,public_key):\n\treturn private_key.exchange(public_key)","def brute_force_decrypt(text):\n for n in range(26):\n print(f\"Using a shift value of {n}\")\n print(decrypt(text, n))\n print(\"\\n***\\n\")","def calcSecret(self,D):\n idxs = list(D.keys())\n k = len(idxs) # number of shares given\n\n # evaluate terms of Lagrange polynomial at zero\n # see https://en.wikipedia.org/wiki/Lagrange_polynomial\n for i in range(0,k):\n for j in range(0,k):\n if i == j:\n pass\n else:\n D[idxs[i]] = self.F.Divide(self.F.Multiply(D[idxs[i]],idxs[j]),self.F.Subtract(idxs[i],idxs[j]))\n \n # sum terms to recover secret\n y = D[idxs[0]]\n for i in range(1,k):\n y = self.F.Add(y,D[idxs[i]]) \n return y","def link(self, secret=None, secondSecret=None):\r\n if hasattr(dposlib, \"core\"):\r\n if secret:\r\n keys = dposlib.core.crypto.getKeys(secret)\r\n self.senderPublicKey = keys[\"publicKey\"]\r\n self._privateKey = keys[\"privateKey\"]\r\n if secondSecret:\r\n keys = dposlib.core.crypto.getKeys(secondSecret)\r\n self._secondPrivateKey = keys[\"privateKey\"]","def decrypt(priv, pub, cipher):\n x = myExp(cipher, priv.lamb, pub.n_sq) - 1\n plain = ((x // pub.n) * priv.mu) % pub.n\n return plain","def break_cipher( self, ciphertexts ):\n\n\t\ttruncated = self.__truncate(ciphertexts)\n\t\tciphertexstring = b''.join( truncated )\n\n\t\tkeystream_size = len( truncated[0] )\n\n\t\ttransposed = self.__transpose( ciphertexstring, keystream_size )\n\n\t\txor_key = b''\n\t\tfor block in transposed:\n\t\t\thex_block = hexlify( block )\n\t\t\txor_key += bytes( [ ord( break_xor_single_byte_by_freq(hex_block) ) ] )\n\n\t\treturn xor_key","def getBalancedAssetComposition(self):\n composition = dict()\n composition['bull'] = 50\n composition['bear'] = 100 - composition['bull']\n return composition","def decrypt():\n plaintext = \"\"\n i = 0\n while i < len(ciphertext):\n if i%2==1:\n try:\n plaintext += key[ ciphertext[i-1]+ciphertext[i] ]\n except KeyError:\n plaintext += ciphertext[i-1]+ciphertext[i]\n i += 1\n return plaintext","def decrypt(self, message):\n # message = message.upper().split()\n # message = \"\".join(message)\n # desalting the message to remove 5 characters blocks\n padding = input(\"Have you used 5 characters blocks? y/n \")\n if padding == \"y\":\n message = message.replace(\" \", \"\")\n message = self.desalt_random(message)\n message = \"\".join(message)\n\n message = message.upper()\n message_list = []\n for ch in message:\n message_list.append(self.main_dict[ch][0])\n\n # OTP Encryption / process the message with OTP\n otp = input(\"What is the OTP that was generated for you during \"\n \"encryption process?: \")\n otp = otp.upper()\n random_otp = []\n for ch in otp:\n random_otp.append(self.main_dict[ch][0])\n\n # If OTP is correct, decrypt the message with mod27\n if len(message_list) != len(random_otp):\n print(\"You typed a wrong OTP.\")\n return None\n else:\n math_list = []\n for i, item in enumerate(message_list):\n if message_list[i] >= random_otp[i]:\n x = message_list[i] - random_otp[i]\n for key, value in self.main_dict.items():\n if value[0] == x:\n math_list.append(key)\n else:\n for key, value in self.main_dict.items():\n if item == value[0]:\n x = value[1] - random_otp[i]\n for key, value in self.main_dict.items():\n if value[0] == x:\n math_list.append(key)\n return \"\".join(math_list)","def _save_tally_share(\n self, guardian_id: GuardianId, guardians_tally_share: DecryptionShare\n ) -> None:\n self._tally_shares[guardian_id] = guardians_tally_share","def crack(self, iterable: Iterable[str]):\n self.pool.map_async(self.unsign, iterable, error_callback=logger.error)\n self.pool.close()\n self.pool.join()\n return self.secret","def _decrypt_block(self, v, k):\n DEBUG = GLOBAL_DEBUG and True\n if DEBUG: print \"_decrypt_block()\"\n\n v0 = struct.unpack(\"<L\", v[0:4])[0]\n v1 = struct.unpack(\"<L\", v[4:8])[0]\n delta = CRYPTO_DETLA; _sum = CRYPTO_SUM\n k0 = struct.unpack(\"<L\", k[ 0: 4])[0]\n k1 = struct.unpack(\"<L\", k[ 4: 8])[0]\n k2 = struct.unpack(\"<L\", k[ 8:12])[0]\n k3 = struct.unpack(\"<L\", k[12:16])[0]\n\n for i in range(CRYPTO_ROUNDS):\n tmp0 = uint32_t(uint32_t(v0 << 6) + k2)\n tmp1 = uint32_t(v0 + _sum)\n tmp2 = uint32_t(uint32_t(v0 >> 7) + k3)\n v1 = uint32_t(v1 - uint32_t(tmp0 ^ tmp1 ^ tmp2))\n\n tmp0 = uint32_t(uint32_t(v1 << 6) + k0)\n tmp1 = uint32_t(v1 + _sum)\n tmp2 = uint32_t(uint32_t(v1 >> 7) + k1)\n v0 = uint32_t(v0 - uint32_t(tmp0 ^ tmp1 ^ tmp2))\n\n _sum = uint32_t(_sum - delta)\n\n return struct.pack(\"<LL\", v0, v1)","def find(cls, name, pass_phrase=None):\n\n secret = cls.get_instance(name)\n secret_data = secret.data[0] # using backref\n\n if not pass_phrase:\n pass_phrase = secret_data.pass_phrase\n else:\n pass_phrase = pass_phrase.encode()\n\n enc_msg = secret_data.generate_enc_msg()\n LOG.debug(\"Decrypting data\")\n secret_val = Crypto.decrypt_AES_GCM(enc_msg, pass_phrase)\n\n return secret_val","def de_cryptate(self):\r\n\r\n intab1 = \"abcdefghijklomnopqrstuvwxyz !,.\"\r\n outtab1 = \"?2p=o)7i(u9/y&t3%r¤5e#w1q!>*'^;)\"\r\n# Fetching from written in textbox\r\n s = self.textbox.toPlainText()\r\n a = s.lower()\r\n# Changing out the letters/numbers/etc\r\n crypted = (a.translate({ord(x): y for (y, x) in zip(intab1, outtab1)}))\r\n# Clear the textbox\r\n self.textbox.clear()\r\n# Write the Decrypted text\r\n self.textbox.setPlainText(crypted)","def derive_keys(self, master_salt, master_secret):\n\n self.sender_key = self._kdf(master_salt, master_secret, self.sender_id, 'Key')\n self.recipient_key = self._kdf(master_salt, master_secret, self.recipient_id, 'Key')\n\n self.common_iv = self._kdf(master_salt, master_secret, b\"\", 'IV')","def genSecret(self, privateKey, otherKey):\n\n\t\tsharedSecret = pow(otherKey, privateKey, self.prime_p)\n\t\treturn sharedSecret","def decrypt(self, phrase):\n keyword = input(\"What keyword is it encrypted with? \")\n plaintext = \"ABCDEFGHIJKLMNOPQRSTUVWXYZ\"\n ciphertext = []\n decrypted = []\n for i in keyword.upper():\n if i not in ciphertext:\n ciphertext.append(i)\n for i in plaintext:\n if i not in ciphertext:\n ciphertext.append(i)\n\n key_dict = dict(zip(plaintext, ciphertext))\n\n for i in phrase.upper():\n if i == \" \":\n decrypted.append(\" \")\n else:\n for key, value in key_dict.items():\n if i == value:\n decrypted.append(key)\n\n return \"\".join(decrypted)","def _reset(self) -> None:\n\n self.done_bidding = False\n self.done_playing = False\n\n self.contract.reset()\n\n # resetting bidding history\n # 1C 1D 1H 1S 1N ... 7N (PASS - not considered)\n self.history_bid = np.zeros(36, dtype=np.uint8)\n\n self.history_play = np.full((NUM_PLAYERS, NUM_PLAYS), np.nan)\n\n # generating vulnerabilities\n self.vulnerability = (np.random.rand(NUM_PAIRS) > 0.5).astype(np.uint8)\n self.vulnerabilities = self.vulnerability[[0, 1, 0, 1]]\n\n # resetting auction_history\n self.auction_history = np.zeros(self.auction_history_shape, dtype=np.uint8)\n\n # resetting bidding elimination signal - doubles and redoubles are not allowed at the start\n self.elim_sig_bid = np.ones(AUCTION_SPACE_SIZE, dtype=np.uint8)\n self.elim_sig_bid[REDOUBLE_RANGE] = 0\n\n # resetting the players' hands (aka one_hot_deal)\n self.one_hot_deal = np.zeros((NUM_PLAYERS, NUM_CARDS), dtype=np.uint8)\n self.one_hot_known_deal = np.ones((NUM_PLAYERS, NUM_CARDS), dtype=np.uint8)\n\n # resetting playing elimination signal: without\n self.elim_sig_play = np.ones((NUM_PLAYERS, NUM_CARDS), dtype=np.uint8)\n\n # resetting various counts\n self.max_bid = -1\n\n self.n_pass = 0\n self.n_double = 0\n self.n_redouble = 0\n\n # index of the first bidder; start from the smallest one by default\n # TODO[ス: should I care that the player in the 1st bidding seat always starts bidding?\n # I don't see how this could cause any problems\n self.turn_bid = self.bidding_seats[0]\n self.turn_play = None\n\n self.n_play_actions = 0\n self.n_play_turns = 0\n self.tricks = np.zeros(NUM_PLAYERS, dtype=np.uint8)\n self.score_play = np.zeros((NUM_PLAYS + 1, NUM_PLAYERS))","def computeSecretKey(g, p):\r\n \"\"\"You will need to implement this function.\"\"\"\r\n return random.randint(1, p-1)","def dh_encrypt(pub, message):\n \n Group, private, public = dh_get_key()#generate new DH pair for Alice\n #private key is an integer/scalar and public key is a point on the curve \n \n #check whether public key of Bob is valid and on curve \n assert Group.check_point(pub)\n \n #Alice obtains shared secret by multiplying her private key with bob's forwarded public key\n key = pub.pt_mul(private)#dA* qB\n print \"key from enc is\", key\n \n hashedKey=sha256(key.export()).digest()\n\n \n plaintext = message.encode(\"utf8\")#encode message\n aes = Cipher(\"aes-128-gcm\")#select cipher\n iv = urandom(16)#generate initialization vector \n cipher, tag = aes.quick_gcm_enc(hashedKey[:16], iv, plaintext)#encrypt using shared key \n ciphertext = [iv,cipher,tag,public]\n\n return ciphertext","def secret():\n pass","def decrypt(self, C, D):\n M = D + (ORDER-self.x)*C\n\n print(\"M =\", M)\n\n D2 = D + (ORDER - 1)*M\n\n r = random_order()\n\n B0 = r*G\n B1 = r*C\n\n h = SHA256.new()\n h.update(str(self.Y).encode())\n h.update(str(C).encode())\n h.update(str(D2).encode())\n h.update(str(B0).encode())\n h.update(str(B1).encode())\n\n c = int(h.hexdigest(), 16)\n\n z = (r + c*self.x) % ORDER\n\n return (M, c, z)","def generate(nof_shares, min_shares, clipboard, qr_code, long):\n w = int(math.log10(nof_shares)) + 1\n\n print(f\"Generating random shared secrets using '{min_shares} of {nof_shares}' config...\")\n mnemonic_secret, secret_bits, mnemonic_shares = make_random_mnemonic_shares(\n minimum_shares=min_shares,\n nof_shares=nof_shares,\n prime=PRIME_13TH_MERSENNE if long else PRIME_12TH_MERSENNE,\n )\n\n if qr_code:\n generate_qrcode(mnemonic_secret, \"master\")\n\n mnemonic_secret_wrapped = \"\\n\\t\".join(textwrap.wrap(mnemonic_secret))\n msg = f\"\"\"Generated secret ( equivalent of {secret_bits} bits ):\n\\t{mnemonic_secret_wrapped}\nUse at least {min_shares} of the following {nof_shares} shared secrets to recover secret:\"\"\"\n for i, ms in enumerate(mnemonic_shares):\n ms_wrapped = \"\\n\\t\".join(textwrap.wrap(ms))\n msg += f\"\\n{i + 1:{w}d}:\\n\\t{ms_wrapped}\"\n if qr_code:\n generate_qrcode(ms, f\"{i+1:0{w}d}\")\n\n if clipboard:\n copy_to_clipboard_and_clear(\"Generated secret and shared secret\", msg)\n else:\n print(msg)\n\n # test recovering the secret\n for _ in range(nof_shares * 10):\n k = random.randint(min_shares, nof_shares)\n test_mnemonic_shares = random.sample(mnemonic_shares, k=k)\n test_mnemonic_secret = number_to_mnemonic(recover_mnemonic_secret(test_mnemonic_shares))\n assert test_mnemonic_secret == mnemonic_secret\n print(\"Done.\")","def decrypt_chunk(self, chunk):\n L, R = chunk\n # Run the feistel rounds as in encryption, but with keys going from n..1\n for i in range(self.number_of_rounds, 0, -1):\n L, R = self.feistel_round(L, R, i)\n return R, L","def symcipher_from_secret(\n cls,\n secret,\n algorithm=TPM2_ALG.AES,\n mode=TPM2_ALG.CFB,\n nameAlg=TPM2_ALG.SHA256,\n objectAttributes=(\n TPMA_OBJECT.DECRYPT | TPMA_OBJECT.SIGN_ENCRYPT | TPMA_OBJECT.USERWITHAUTH\n ),\n seed=None,\n ):\n sa, pa = TPMT_SENSITIVE.symcipher_from_secret(\n secret, algorithm, mode, nameAlg, objectAttributes, seed\n )\n priv = TPM2B_SENSITIVE(sensitiveArea=sa)\n pub = TPM2B_PUBLIC(publicArea=pa)\n return (priv, pub)","def test_share_distributor(self):\n\n # =================================================================\n # test: complete test, share distribution int\n # =================================================================\n\n sell_list = [StockOrderWrapper(self.order_2)]\n sell = sell_list[0]\n buy_orders = [StockOrderWrapper(self.order_3), StockOrderWrapper(self.order_4), StockOrderWrapper(self.order_7),\n StockOrderWrapper(self.order_8), StockOrderWrapper(self.order_11),\n StockOrderWrapper(self.order_12)]\n\n result = self.bidding_round_manager.share_distributor(sell_orders=sell_list, buy_orders=buy_orders)\n\n order_real_3 = result[0]\n order_real_4 = result[1]\n order_real_7 = result[2]\n order_real_8 = result[3]\n order_real_11 = result[4]\n order_real_12 = result[5]\n\n sell_order_dict_1 = {sell: 1}\n sell_order_dict_2 = {sell: 2}\n\n order_exp_3 = StockOrderWrapper(self.order_3)\n order_exp_4 = StockOrderWrapper(self.order_4)\n order_exp_7 = StockOrderWrapper(self.order_7)\n order_exp_8 = StockOrderWrapper(self.order_8)\n order_exp_11 = StockOrderWrapper(self.order_11)\n order_exp_12 = StockOrderWrapper(self.order_12)\n\n order_exp_3.transaction_dict = sell_order_dict_1\n order_exp_4.transaction_dict = sell_order_dict_2\n order_exp_7.transaction_dict = sell_order_dict_2\n order_exp_8.transaction_dict = sell_order_dict_2\n order_exp_11.transaction_dict = sell_order_dict_2\n order_exp_12.transaction_dict = sell_order_dict_1\n\n order_exp_3.shares_left = 4\n order_exp_4.shares_left = 8\n order_exp_7.shares_left = 8\n order_exp_8.shares_left = 8\n order_exp_11.shares_left = 8\n order_exp_12.shares_left = 4\n\n self.is_equal_order_wrapper(order_real_3, order_exp_3)\n self.is_equal_order_wrapper(order_real_4, order_exp_4)\n self.is_equal_order_wrapper(order_real_7, order_exp_7)\n self.is_equal_order_wrapper(order_real_8, order_exp_8)\n self.is_equal_order_wrapper(order_real_11, order_exp_11)\n self.is_equal_order_wrapper(order_real_12, order_exp_12)\n\n # =================================================================\n # test: share distribution float easy\n # =================================================================\n\n sell_list = [StockOrderWrapper(self.order_2)]\n sell = sell_list[0]\n\n buy_order_3 = StockOrderWrapper(self.order_3)\n buy_order_4 = StockOrderWrapper(self.order_4)\n buy_order_7 = StockOrderWrapper(self.order_7)\n buy_order_8 = StockOrderWrapper(self.order_8)\n buy_order_11 = StockOrderWrapper(self.order_11)\n buy_order_12 = StockOrderWrapper(self.order_12)\n\n sell.shares_left = 6\n buy_order_3.shares_left = 8 # 2.4 -> 3\n buy_order_4.shares_left = 4 # 1.2 -> 1\n buy_order_7.shares_left = 4 # 1.2 -> 1\n buy_order_8.shares_left = 4 # 1.2 -> 1\n buy_order_11.shares_left = 0 # 0.0 -> 0\n buy_order_12.shares_left = 0 # 0.0 -> 0\n\n buy_orders = [buy_order_3, buy_order_4, buy_order_7, buy_order_8, buy_order_11, buy_order_12]\n\n result = self.bidding_round_manager.share_distributor(sell_orders=sell_list, buy_orders=buy_orders)\n\n result_dict = {}\n\n for res in result:\n result_dict[res.stock_order.order_id] = res\n\n try:\n # noinspection PyUnusedLocal\n dummy = result[4]\n raise AssertionError(\"IndexError exception expected\")\n except IndexError:\n pass\n\n sell_order_dict_1 = {sell: 1}\n sell_order_dict_3 = {sell: 3}\n\n order_exp_3.transaction_dict = sell_order_dict_3\n order_exp_4.transaction_dict = sell_order_dict_1\n order_exp_7.transaction_dict = sell_order_dict_1\n order_exp_8.transaction_dict = sell_order_dict_1\n\n order_exp_3.shares_left = 5\n order_exp_4.shares_left = 3\n order_exp_7.shares_left = 3\n order_exp_8.shares_left = 3\n\n self.is_equal_order_wrapper(result_dict.get(3), order_exp_3)\n self.is_equal_order_wrapper(result_dict.get(4), order_exp_4)\n self.is_equal_order_wrapper(result_dict.get(7), order_exp_7)\n self.is_equal_order_wrapper(result_dict.get(8), order_exp_8)\n\n # =================================================================\n # test: share distribution float complex (multiple float iterations)\n # =================================================================\n\n sell_list = [StockOrderWrapper(self.order_2)]\n sell = sell_list[0]\n\n buy_order_3 = StockOrderWrapper(self.order_3)\n buy_order_4 = StockOrderWrapper(self.order_4)\n buy_order_7 = StockOrderWrapper(self.order_7)\n buy_order_8 = StockOrderWrapper(self.order_8)\n buy_order_11 = StockOrderWrapper(self.order_11)\n buy_order_12 = StockOrderWrapper(self.order_12)\n\n sell.shares_left = 18\n sell.stock_order.order_status = DEFINITIVE\n\n self.order_3.order_status = DEFINITIVE\n self.order_4.order_status = DEFINITIVE\n self.order_7.order_status = DEFINITIVE\n self.order_8.order_status = DEFINITIVE\n self.order_11.order_status = DEFINITIVE\n self.order_12.order_status = DEFINITIVE\n\n buy_order_3.shares_left = 6 # 3.6 -> 4\n buy_order_4.shares_left = 4 # 2.4 -> 2\n buy_order_7.shares_left = 2 # 1.2 -> 1\n buy_order_8.shares_left = 2 # 1.2 -> 1\n buy_order_11.shares_left = 8 # 4.8 -> 5\n buy_order_12.shares_left = 8 # 4.8 -> 5\n\n buy_orders = [buy_order_3, buy_order_4, buy_order_7, buy_order_8, buy_order_11, buy_order_12]\n\n result = self.bidding_round_manager.share_distributor(sell_orders=sell_list, buy_orders=buy_orders)\n\n result_dict = {}\n\n for res in result:\n result_dict[res.stock_order.order_id] = res\n\n try:\n # noinspection PyUnusedLocal\n dummy = result[6]\n raise AssertionError(\"IndexError exception expected\")\n except IndexError:\n pass\n\n sell_order_dict_1 = {sell: 1}\n sell_order_dict_2 = {sell: 2}\n sell_order_dict_4 = {sell: 4}\n sell_order_dict_5 = {sell: 5}\n\n order_exp_3.transaction_dict = sell_order_dict_4\n order_exp_4.transaction_dict = sell_order_dict_2\n order_exp_7.transaction_dict = sell_order_dict_1\n order_exp_8.transaction_dict = sell_order_dict_1\n order_exp_11.transaction_dict = sell_order_dict_5\n order_exp_12.transaction_dict = sell_order_dict_5\n\n order_exp_3.shares_left = 2\n order_exp_4.shares_left = 2\n order_exp_7.shares_left = 1\n order_exp_8.shares_left = 1\n order_exp_11.shares_left = 3\n order_exp_12.shares_left = 3\n\n self.is_equal_order_wrapper(result_dict.get(3), order_exp_3)\n self.is_equal_order_wrapper(result_dict.get(4), order_exp_4)\n self.is_equal_order_wrapper(result_dict.get(7), order_exp_7)\n self.is_equal_order_wrapper(result_dict.get(8), order_exp_8)\n self.is_equal_order_wrapper(result_dict.get(11), order_exp_11)\n self.is_equal_order_wrapper(result_dict.get(12), order_exp_12)\n\n # =================================================================\n # test: share distribution date (two stocks left after one float iteration)\n # =================================================================\n\n sell_list = [StockOrderWrapper(self.order_2)]\n sell = sell_list[0]\n\n buy_order_3 = StockOrderWrapper(self.order_3)\n buy_order_4 = StockOrderWrapper(self.order_4)\n buy_order_7 = StockOrderWrapper(self.order_7)\n buy_order_8 = StockOrderWrapper(self.order_8)\n buy_order_11 = StockOrderWrapper(self.order_11)\n buy_order_12 = StockOrderWrapper(self.order_12)\n\n sell.shares_left = 19\n\n buy_order_3.shares_left = 4 # 2.4 -> 2 -> 3\n buy_order_4.shares_left = 4 # 2.4 -> 2 -> 3\n buy_order_7.shares_left = 4 # 2.4 -> 2 -> 2\n buy_order_8.shares_left = 2 # 1.2 -> 1 -> 1\n buy_order_11.shares_left = 8 # 4.8 -> 5 -> 5\n buy_order_12.shares_left = 8 # 4.8 -> 5 -> 5\n\n buy_orders = [buy_order_3, buy_order_4, buy_order_7, buy_order_8, buy_order_11, buy_order_12]\n\n result = self.bidding_round_manager.share_distributor(sell_orders=sell_list, buy_orders=buy_orders)\n\n result_dict = {}\n\n for res in result:\n result_dict[res.stock_order.order_id] = res\n\n try:\n # noinspection PyUnusedLocal\n dummy = result[6]\n raise AssertionError(\"IndexError exception expected\")\n except IndexError:\n pass\n\n sell_order_dict_1 = {sell: 1}\n sell_order_dict_2 = {sell: 2}\n sell_order_dict_3 = {sell: 3}\n sell_order_dict_5 = {sell: 5}\n\n order_exp_3.transaction_dict = sell_order_dict_3\n order_exp_4.transaction_dict = sell_order_dict_3\n order_exp_7.transaction_dict = sell_order_dict_2\n order_exp_8.transaction_dict = sell_order_dict_1\n order_exp_11.transaction_dict = sell_order_dict_5\n order_exp_12.transaction_dict = sell_order_dict_5\n\n order_exp_3.shares_left = 1\n order_exp_4.shares_left = 1\n order_exp_7.shares_left = 2\n order_exp_8.shares_left = 1\n order_exp_11.shares_left = 3\n order_exp_12.shares_left = 3\n\n order_exp_11.order_status = DEFINITIVE\n order_exp_12.order_status = DEFINITIVE\n\n self.is_equal_order_wrapper(result_dict.get(3), order_exp_3)\n self.is_equal_order_wrapper(result_dict.get(4), order_exp_4)\n self.is_equal_order_wrapper(result_dict.get(7), order_exp_7)\n self.is_equal_order_wrapper(result_dict.get(8), order_exp_8)\n self.is_equal_order_wrapper(result_dict.get(11), order_exp_11)\n self.is_equal_order_wrapper(result_dict.get(12), order_exp_12)\n\n # =================================================================\n # test: share distribution int sell shares left\n # =================================================================\n\n sell_list = [StockOrderWrapper(self.order_2)]\n sell = sell_list[0]\n\n sell.shares_left = 100\n\n buy_order_3 = StockOrderWrapper(self.order_3)\n buy_order_4 = StockOrderWrapper(self.order_4)\n buy_order_7 = StockOrderWrapper(self.order_7)\n buy_order_8 = StockOrderWrapper(self.order_8)\n buy_order_11 = StockOrderWrapper(self.order_11)\n buy_order_12 = StockOrderWrapper(self.order_12)\n\n buy_order_3.shares_left = 4\n buy_order_4.shares_left = 7\n buy_order_7.shares_left = 9\n buy_order_8.shares_left = 4\n buy_order_11.shares_left = 8\n buy_order_12.shares_left = 3\n\n buy_orders = [buy_order_3, buy_order_4, buy_order_7, buy_order_8, buy_order_11, buy_order_12]\n\n result = self.bidding_round_manager.share_distributor(sell_orders=sell_list, buy_orders=buy_orders)\n\n order_exp_2 = StockOrderWrapper(self.order_2)\n order_exp_2.shares_left = 65\n\n self.is_equal_order_wrapper(result[0], order_exp_2)\n\n sell_order_dict_3 = {sell: 3}\n sell_order_dict_4 = {sell: 4}\n sell_order_dict_7 = {sell: 7}\n sell_order_dict_8 = {sell: 8}\n sell_order_dict_9 = {sell: 9}\n\n order_exp_3.transaction_dict = sell_order_dict_4\n order_exp_4.transaction_dict = sell_order_dict_7\n order_exp_7.transaction_dict = sell_order_dict_9\n order_exp_8.transaction_dict = sell_order_dict_4\n order_exp_11.transaction_dict = sell_order_dict_8\n order_exp_12.transaction_dict = sell_order_dict_3\n\n order_exp_3.shares_left = 0\n order_exp_4.shares_left = 0\n order_exp_7.shares_left = 0\n order_exp_8.shares_left = 0\n order_exp_11.shares_left = 0\n order_exp_12.shares_left = 0\n\n order_exp_3.order_status = PROCESSED\n order_exp_4.order_status = PROCESSED\n order_exp_7.order_status = PROCESSED\n order_exp_8.order_status = PROCESSED\n order_exp_11.order_status = PROCESSED\n order_exp_12.order_status = PROCESSED\n\n self.is_equal_order_wrapper(buy_order_3, order_exp_3)\n self.is_equal_order_wrapper(buy_order_4, order_exp_4)\n self.is_equal_order_wrapper(buy_order_7, order_exp_7)\n self.is_equal_order_wrapper(buy_order_8, order_exp_8)\n self.is_equal_order_wrapper(buy_order_11, order_exp_11)\n self.is_equal_order_wrapper(buy_order_12, order_exp_12)","def operate_cipher(self):","def decrypt(self, key, value):\n key = hashlib.sha256(key).digest()[:self.BLOCK_SIZE]\n iv = value[:16]\n crypted = value[16:]\n cipher = AES.new(key,AES.MODE_CBC,iv)\n return self.pkcs5_unpad(cipher.decrypt(crypted))","def decrypt(self, ciphertext):\n text = []\n # ciphertext = ciphertext.upper()\n for char in ciphertext:\n try:\n key = math_utils.mult_mod_inv(self.a, len(self.characters)) * (self.characters.index(char) - self.b) % len(self.characters)\n # If character is not in set for cipher,\n # directly append it without transformation\n except ValueError:\n text.append(char)\n else:\n text.append(self.characters[key])\n return ''.join(text)","def can_be_unlocked(self, keycard):\n pass","def get_plaintext_ballots(\n self, ciphertext_ballots: List[SubmittedBallot], manifest: Manifest\n ) -> Optional[Dict[BallotId, PlaintextTally]]:\n\n if not self.announcement_complete():\n return None\n\n ballots = {}\n\n for ciphertext_ballot in ciphertext_ballots:\n ballot_shares = self._ballot_shares.get(ciphertext_ballot.object_id)\n if not ballot_shares or not self._ready_to_decrypt(ballot_shares):\n # Skip ballot if not ready to decrypt\n continue\n ballot = decrypt_ballot(\n ciphertext_ballot,\n ballot_shares,\n self._context.crypto_extended_base_hash,\n manifest,\n )\n\n if ballot:\n ballots[ballot.object_id] = ballot\n\n return ballots","def set_values_from_bob(F_in, Y_in, d_in, ciphertexts):\n global F, d, e_x, e_y, e_xor\n F, d = F_in, d_in\n e_y, e_xor = Y_in\n e_x = decrypt(ciphertexts)","def decrypt(cypher, priv_key):\n\n if not isinstance(priv_key, key.PrivateKey):\n raise TypeError(\"You must use the private key with decrypt\")\n\n return gluechops(cypher, priv_key.d, priv_key.n, decrypt_int)","async def get_secret(app: Sanic, secret_key: str, passphrase: str) -> str:\n\n data = await app.db.secrets.find_one({'secret_key': secret_key})\n await app.db.secrets.find_one({'secret_key': secret_key})\n if not data:\n raise exceptions.InvalidSecretKeyException()\n\n key = get_fernet_key(app, passphrase)\n\n sign = hmac.digest(key=key, msg=passphrase.encode(), digest='sha512').hex()\n if sign != data['signature']:\n raise exceptions.InvalidPassphraseException()\n\n await app.db.secrets.delete_one({'secret_key': secret_key})\n\n encrypted = data['secret'].encode()\n cipher = fernet.Fernet(key)\n if data.get('ttl'):\n try:\n secret = cipher.decrypt(encrypted, ttl=data['ttl']).decode()\n except fernet.InvalidToken:\n raise exceptions.InvalidSecretKeyException()\n else:\n secret = cipher.decrypt(encrypted).decode()\n\n return secret","def decrypt_slice_secret( observer_pkey_pem, sealed_slice_secret_b64 ):\n \n # get the public key\n try:\n observer_pubkey_pem = CryptoKey.importKey( observer_pkey_pem ).publickey().exportKey()\n except Exception, e:\n logger.exception(e)\n logger.error(\"Failed to derive public key from private key\")\n return None \n \n sealed_slice_secret = base64.b64decode( sealed_slice_secret_b64 )\n \n # decrypt it \n rc, slice_secret = c_syndicate.decrypt_data( observer_pubkey_pem, observer_pkey_pem, sealed_slice_secret )\n \n if rc != 0:\n logger.error(\"Failed to decrypt '%s', rc = %d\" % (sealed_slice_secret_b64, rc))\n return None\n \n return slice_secret","def ecb_decrypt(ct_bin_list, keys, rounds):\n dec_result = \"\"\n\n with multiprocessing.Pool() as p:\n dec_result = p.starmap(feistel_decrypt, zip(ct_bin_list, keys, repeat(rounds)))\n return dec_result","def decrypt_file(open_name:str, write_name:str, key:str):\n\n\n with open(write_name, \"wb\") as f:\n key = key.encode()\n for (i, part_of_picture) in enumerate(PictureSlices(open_name)):\n round_key = b\"%d%s randominfix %d\" % (i, key, i)\n decrypted_part = xor(part_of_picture, sha512(round_key).digest())\n f.write(decrypted_part)","def decrypt(self, key):\n super(MACDataUplinkMessage, self).decrypt(key, dir=0)","def as_encrypted(self):\n\n # Interpret as one word (pid), followed by a bunch of shorts\n struct_def = \"I\" + \"H\" * ((len(self.blob) - 4) / 2)\n words = list( struct.unpack(struct_def, self.blob) )\n\n # Apply the block shuffle and standard Pokémon encryption\n shuffled = self.shuffle_chunks(words)\n self.reciprocal_crypt(shuffled)\n\n # Stuff back into a string, and done\n return struct.pack(struct_def, *shuffled)","def keyedhash_from_secret(\n cls,\n secret,\n nameAlg=TPM2_ALG.SHA256,\n objectAttributes=(\n TPMA_OBJECT.DECRYPT | TPMA_OBJECT.SIGN_ENCRYPT | TPMA_OBJECT.USERWITHAUTH\n ),\n scheme=None,\n seed=None,\n ):\n sa, pa = TPMT_SENSITIVE.keyedhash_from_secret(\n secret, nameAlg, objectAttributes, scheme, seed\n )\n priv = TPM2B_SENSITIVE(sensitiveArea=sa)\n pub = TPM2B_PUBLIC(publicArea=pa)\n return (priv, pub)","def secret() -> None:\n pass","def decryptor(iv = os.urandom(16), key = os.urandom(32), bc = backend):\n\tcipher = Cipher(algorithms.AES(key), modes.CBC(iv), backend = bc)\n\treturn iv, key, cipher.decryptor()","def deal(self):\n\n if self.dealer: # Has cards in hand\n self.dealer.reset()\n\n if self.player: # Has cards in hand\n self.player.reset()\n\n dealer_first = self.deck.draw()\n dealer_second = self.deck.draw()\n dealer_second.flip()\n self.dealer.take_card(dealer_first)\n self.dealer.take_card(dealer_second)\n\n player_first = self.deck.draw()\n player_second = self.deck.draw()\n player_first.flip()\n player_second.flip()\n self.player.take_card(player_first)\n self.player.take_card(player_second)\n\n if self.verbose:\n print('Player bets:', self.player_bet)\n for player in (self.player, self.dealer):\n print(player, 'dealt:')\n for card in player:\n if card.face():\n print(' '*3, str(card)+':', 'face up')\n else:\n print(' '*3, str(card)+':', 'face down')","def cbc_decrypt(ct_bin_list, keys, rounds):\n ivector = ct_bin_list.pop(0)\n dec_result = []\n msg = ct_bin_list\n\n with multiprocessing.Pool() as p:\n x = p.starmap(feistel_decrypt, zip(msg, keys, repeat(rounds)))\n\n dec_result.append(xor_compare(x[0],ivector))\n if len(x) > 1:\n for i in range(1, len(x)):\n dec_result.append(xor_compare(x[i],msg[i-1]))\n\n return dec_result","def generate_keys(g, o):\n priv = o.random()\n pub = priv * g\n\n return (priv, pub)","def randomize_herbs(self):\n random.shuffle(self.herbivores)","def rsa_decrypt(self, thing):\n return self.true_private_key.decrypt(\n thing,\n cryptography.hazmat.primitives.asymmetric.padding.OAEP(\n mgf=cryptography.hazmat.primitives.asymmetric.padding.MGF1(\n algorithm=hashes.SHA256()),\n algorithm=hashes.SHA256(),\n label=None\n )\n )","def assess_hand(self, r):\n bidIndex = -1\n while bool(random.getrandbits(1)): # Coin flip\n bidIndex += 1\n if bidIndex == -1:\n self.maxBid = LEGAL_BIDS[0] - 1 # Pass immediately.\n else:\n self.maxBid = LEGAL_BIDS[bidIndex]","def switcher_secret(self):\n return self._switcher_secret","def passphrase():\n a = []\n for i in range(1,6):\n a.append(password())\n # join words into phrase\n p = \" \".join(a)\n # split phrase into a list\n p = list(p)\n # substitute a random character\n rc = \"\"\"1~!#$%^2&*()-=3+[]\\{}4:;\"'<>5?/01236456789\"\"\"\n p[secrets.choice(range(0,len(p)))] = rc[secrets.choice(range(0,len(rc)))]\n # put phrase back together\n p = \"\".join(p)\n return p","def test_kyc_get_legal_share_holders(self):\n pass","def encrypt(self, message):\n # message = message.upper().split()\n # message = \"\".join(message)\n message = message.upper()\n message_list = []\n for ch in message:\n message_list.append(self.main_dict[ch][0])\n\n # Generate a random key\n random_otp = [random.choice(self.alphabet_list) for _ in range(len(message))]\n print(\"Your OTP is: \" + str(\"\".join(random_otp)))\n print(\"Use the OTP to unlock the message.\")\n\n # Convert Random key to integers\n for i, item in enumerate(random_otp):\n random_otp[i] = self.main_dict[item][0]\n\n # Do the math with Random Key and the message\n math_list = []\n for i, item in enumerate(message_list):\n try:\n result = message_list[i] + random_otp[i]\n math_list.append(result)\n except:\n print(\"The message and OTP does not have the same length\")\n continue\n\n # Logic to do mod27\n for i, item in enumerate(math_list):\n for key, value in self.main_dict.items():\n if item > 26:\n if value[1] == item:\n math_list[i] = key\n else:\n if value[0] == item:\n math_list[i] = key\n\n # Algorithm for 5 block characters\n padding = input(\"Would you like to use block 5 characters? y/n \")\n if padding == \"y\":\n math_list = self.salt_with_random(math_list)\n return \" \".join(math_list)\n else:\n math_list = \"\".join(math_list)\n return math_list","def encrypt(self, sentence):\r\n sentence = list(sentence)\r\n encrypted_sentence = []\r\n x = list(\"abcdefghijklmnopqrstuvwxyz\")\r\n l = len(x)\r\n y = random.sample(x, l)\r\n z = list(zip(x, y))\r\n z.append((\" \", \" \"))\r\n for i in sentence:\r\n if i.lower() not in x:\r\n encrypted_sentence.append(i)\r\n continue \r\n for a in z:\r\n if i.lower() == a[0]:\r\n if i.isupper():\r\n encrypted_sentence.append(a[1].upper())\r\n else:\r\n encrypted_sentence.append(a[1])\r\n encrypted_sentence = \"\".join(encrypted_sentence)\r\n y = \"\".join(y)\r\n cls()\r\n print(\"Your one time use pad is: {}\".format(y))\r\n print(\"\")\r\n return encrypted_sentence","def Secure(self,passphrase=None,public_attributes=[]):\n\n\t\tif passphrase == None:\n\t\t\treturn self.Dictify()\n\t\telse:\n\t\t\tself.data = Encrypting.Symmetric.Encrypt(json.dumps(self.Dictify()).encode('utf-8'),passphrase).decode('utf-8')\n\t\t\t\n\t\t#secure data and dictify\n\t\tmy_secure_dict = self.Dictify()\n\n\t\t#new obfuscated obj\n\t\tnew_me = {'data':my_secure_dict['data']}\n\n\t\tfor pub_att in public_attributes:\n\t\t\tnew_me[pub_att] = my_secure_dict[pub_att]\n\n\t\treturn new_me","def manage_removeSharedSecret(self, REQUEST):\n self._shared_secret = None\n response = REQUEST.response\n response.redirect(\n '%s/manage_secret?manage_tabs_message=%s' %\n (self.absolute_url(), 'Shared+secret+removed.')\n )"],"string":"[\n \"def get_pam_secret(self, key):\\n\\n\\n privateKeyA=self.rand() \\n privateKeyB=self.rand() \\n publicKeyA = int(pow(genrated,privateKeyA,prime))\\n publicKeyB = int(pow(genrated,privateKeyB,prime))\\n\\n resp = self.process(\\n requests.get(f\\\"{self.api_url}/secretman/GetSecretV2/{key}\\\" ,\\n headers=self.headers(self.api_key,publicKeyA,publicKeyB )\\n )\\n ).text\\n \\n sharedKeyA = int(pow(int(json.loads(resp)['keyA']),privateKeyA,prime))\\n sharedKeyB = int(pow(int(json.loads(resp)['keyB']),privateKeyB,prime))\\n finalSec = sharedKeyA ** sharedKeyB\\n return aes256.decrypt(json.loads(resp)['value'], str(finalSec)).decode(\\\"utf-8\\\")\",\n \"def main():\\n\\n prime = 0xffffffffffffffffc90fdaa22168c234c4c6628b80dc1cd129024e088a67cc74020bbea63b139b22514a08798e3404ddef9519b3cd3a431b302b0a6df25f14374fe1356d6d51c245e485b576625e7ec6f44c42e9a637ed6b0bff5cb6f406b7edee386bfb5a899fa5ae9f24117c4b1fe649286651ece45b3dc2007cb8a163bf0598da48361c55d39a69163fa8fd24cf5f83655d23dca3ad961c62f356208552bb9ed529077096966d670c354e4abc9804f1746c08ca237327ffffffffffffffff\\n base = 2\\n \\n connection = diffiehellman_mitm_sim(prime, base)\\n\\n # intercept alices public key\\n prime, base , _ = next(connection)\\n\\n # send prime instead of alices public key to bob. Recieve Bobs public key, \\n # which we forget as it is not needs. The shared kill will be 0.\\n\\n connection.send((prime, base, prime))\\n\\n #Send prime as bob's public key to alice. We have ensured that the shared\\n #hared secret key is 0. Recieve Alice's ciphertext for bob\\n ciphertext_a2b = connection.send(prime)\\n\\n # decrypt\\n malcolm = AES_CBC(SHA1(bso.int_to_bytes(0)).digest()[:16], b'0'*16)\\n messages = []\\n messages.append(bso.remove_padding_pkcs7(malcolm.decrypt(ciphertext_a2b[:-16], ciphertext_a2b[-16:])))\\n\\n #Send the ciphertext to bob. Recieve his response\\n ciphertext_b2a = connection.send(ciphertext_a2b)\\n\\n messages.append(bso.remove_padding_pkcs7(malcolm.decrypt(ciphertext_b2a[:-16], ciphertext_b2a[-16:])))\\n\\n assert messages[0] == b'Message to Bob'\\n assert messages[1] == b'Message to Alice'\\n\\n \\n return\",\n \"def _ready_to_decrypt(self, shares: Dict[GuardianId, DecryptionShare]) -> bool:\\n # If all guardian shares are represented including if necessary\\n # the missing guardians reconstructed shares, the decryption can be made\\n return len(shares) == self._context.number_of_guardians\",\n \"def shared_decryption(sk_shares, ciphertext):\\n if len(sk_shares) < 1:\\n raise('No shares given')\\n used_shares = get_correct_num_of_shares(sk_shares)\\n plaintext_shares = [sk_share.compute_plaintext_share(\\n ciphertext) for sk_share in used_shares]\\n lambdas = [calc_lambda(plaintext_shares, share[0], sk_shares[0].precomputed_fac) for i, share in enumerate(plaintext_shares)]\\n return sk_shares[0].reconstruct_plaintext(plaintext_shares), plaintext_shares, lambdas\",\n \"def keygen(cls, bits, num_shares, threshold):\\n if threshold < 2:\\n raise('Threshold should be at least 2, but is {}'.format(threshold))\\n primes = PrimeStorage()\\n ((p, p_), (q, q_)) = primes.getRandomSafePrimes(bits // 2)\\n\\n n = p * q\\n m = p_ * q_\\n\\n # find secret\\n d = ext_euclid(n, m)\\n\\n pk = PublicPaillierKey(n)\\n\\n # Shamir secret sharing: determine polynomial\\n coeffs = [d] + [randint(0, n*m) for _ in range(threshold-1)]\\n # determine shares\\n shares = [eval_polynomial(coeffs, i, n*m)\\n for i in range(1, num_shares + 1)]\\n key_shares = [PrivateKeyShare(\\n shares[i-1], i, len(shares), threshold, pk) for i in range(1, num_shares + 1)]\\n\\n # - v, a generator of Z^*_(n^2)\\n # - verification key for each decryption party\\n\\n return pk, key_shares\",\n \"def diffiehellman_mitm_sim(prime, base):\\n alice = {}\\n\\n #Alice generates their public key an sends to 'bob'\\n alice['dh'] = DiffieHellman(prime, base, secret_key=secrets.randbelow(prime))\\n alice_pub = alice['dh'].gen_public_key()\\n\\n (prime, base, key_for_bob) = yield (prime, base, alice_pub)\\n\\n \\n\\n #bob recieves 'alice's' public key, generates their own public key and\\n #the shared key. Sends their public key ot 'alice'\\n bob = {'dh':DiffieHellman(prime, base, secret_key=secrets.randbelow(prime))}\\n bob_pup = bob['dh'].gen_public_key()\\n bob['dh'].gen_shared_key(key_for_bob)\\n\\n key_for_alice = yield bob_pup\\n\\n ### Alice recieves Bob's public key, generates the shared key and encrypts\\n ### message for bob\\n\\n alice['dh'].gen_shared_key(key_for_alice)\\n \\n alice['sha1'] = SHA1(bso.int_to_bytes(alice['dh'].shared_key))\\n alice['cipher'] = AES_CBC(alice['sha1'].digest()[:16], secrets.token_bytes(16))\\n alice_ciphertext = alice['cipher'].encrypt(b'Message to Bob')\\n alice_ciphertext += alice['cipher'].IV\\n\\n ciphertext_for_bob = yield alice_ciphertext\\n \\n #Bob recieves the ciphertext, decrypts it and send a reply.\\n\\n bob['sha1'] = SHA1(bso.int_to_bytes(bob['dh'].shared_key))\\n bob['cipher'] = AES_CBC(bob['sha1'].digest()[:16], secrets.token_bytes(16))\\n bob_ciphertext = bob['cipher'].encrypt(b'Message to Alice')\\n bob_ciphertext += bob['cipher'].IV\\n\\n ciphertext_for_alice = yield bob_ciphertext\\n\\n ### Finally alice decrypts bobs reply\\n\\n alice['cipher'].decrypt(ciphertext_for_alice[:-16], ciphertext_for_alice[-16:])\",\n \"def dh_decrypt(priv, ciphertext):\\n Group1,private, public = dh_get_key()#generate new DH pair for Bob\\n iv=ciphertext[0]\\n cipher=ciphertext[1]\\n tag=ciphertext[2]\\n pubA=ciphertext[3]\\n \\n #Bob derives shared secret key by multiplying his public key with Alice's private key\\n shared2 = pubA.pt_mul(priv)#qA * dB\\n print \\\"key from dec is\\\", shared2\\n\\n hashedKey=sha256(shared2.export()).digest()\\n \\n aes = Cipher(\\\"aes-128-gcm\\\")\\n plain = aes.quick_gcm_dec(hashedKey[:16], iv, cipher, tag)#where to get IV and tag from ???\\n \\n return plain.encode(\\\"utf8\\\")\",\n \"def decrypt(self, data):\",\n \"def encrypt_ballot(request, election):\\n answers = utils.from_json(request.POST['answers_json'])\\n ev = homomorphic.EncryptedVote.fromElectionAndAnswers(election, answers)\\n return ev.ld_object.includeRandomness().toJSONDict()\",\n \"def _save_ballot_shares(\\n self,\\n guardian_id: GuardianId,\\n guardians_ballot_shares: Dict[BallotId, Optional[DecryptionShare]],\\n ) -> None:\\n for ballot_id, guardian_ballot_share in guardians_ballot_shares.items():\\n shares = self._ballot_shares.get(ballot_id)\\n if shares is None:\\n shares = {}\\n if guardian_ballot_share is not None:\\n shares[guardian_id] = guardian_ballot_share\\n self._ballot_shares[ballot_id] = shares\",\n \"def _decrypt_secret(\\n self, \\n encryption_key: str,\\n secret_list: List,\\n secret_name: str\\n ):\\n f = Fernet(\\n bytes(encryption_key, \\\"utf-8\\\")\\n )\\n secret=None\\n if 'secrets' in secret_list:\\n if secret_name in secret_list['secrets']:\\n secret = f.decrypt(\\n bytes(secret_list['secrets'][secret_name], \\\"utf-8\\\")\\n ).decode('UTF-8')\\n #self.log.log_success(\\n # f'{secret_name} : {secret}'\\n #)\\n return secret\",\n \"def cast(box,I,choice='White Ballot'):\\n smallringsize = __smallringsize__\\n IKey = Crypto.PublicKey.RSA.importKey(open('keys/%s.pem'%I).read())\\n fullring,index,i,crypted,d2s,found,cands = [],0,0,None,[],False,{}\\n for l in open(box).readlines():\\n if re.match(r'\\\\(',l):\\n name,h,num,d1,d2,url = eval(l)\\n tsprk = urllib.urlopen(url).read()\\n d2s = eval(urllib.urlopen(url+'?d='+d2).read())\\n elif re.match(r'\\\\{',l):\\n cands = eval(l)\\n cands['White Ballot'] = 'ok'\\n elif reg(re.match(r'\\\\.([\\\\w\\\\-]{10})\\\\s(\\\\d{0,10})\\\\s([\\\\w\\\\-]{10,200})\\\\s([\\\\w\\\\-]{10,200})$',l)):\\n if reg.v.group(3) == itob64(IKey.n):\\n index,found = i,True\\n fullring.append(IKey)\\n else:\\n fullring.append(myKey(b64toi(reg.v.group(3))))\\n i += 1\\n if not found:\\n return '\\\\'%s\\\\' is not registered!'%I\\n if not cands.has_key(choice):\\n return '\\\\'%s\\\\' choice is not one of selectable'%choice\\n crypted = rsa(myKey(b64toi(d2s[0]))).encrypt(b64toi(base64.urlsafe_b64encode(choice)))\\n pos,lind = setsample(len(fullring),index,smallringsize)\\n smallring = getsample(fullring,lind,smallringsize) if lind else fullring\\n open(box,'a').write('!%s %s %s\\\\n'%(lind,crypted,ringBL(smallring).sign(crypted,pos)))\",\n \"def decryption_process(name, modulus, passed, secret, key):\\n\\tprint('\\\\n', name, 'uses the public number they were sent--', str(passed), \\n\\t'and raises it to the power of their original secret key number--', str(secret))\\n\\tprint('Then', name, 'uses the original public modulus--', str(modulus), 'and takes the modulus to find the shared secret key',\\n\\t\\tstr(key) + '.')\\n\\tprint(\\\"This process's equation is as follows:\\\", str(passed) + '^' + str(secret), 'mod', \\n\\t\\tstr(modulus), '=', str(key))\",\n \"def __decrypt_secrets(self, secrets):\\n assert self.decrypter != None\\n return [self.decrypter.decrypt(secret) for secret in secrets]\",\n \"def decrypt(crypto, priv):\\r\\n string = rsa.encrypt(crypto, priv)\\r\\n string = livingDead.utfE(crypto)\\r\\n return crypto\",\n \"def test_secretbox_enc_dec(self):\\n # Encrypt with sk\\n encrypted_data = nacl.secretbox_encrypt(data=self.unencrypted_data, sk=self.sk)\\n\\n # Decrypt with sk\\n decrypted_data = nacl.secretbox_decrypt(data=encrypted_data, sk=self.sk)\\n\\n self.assertEqual(self.unencrypted_data, decrypted_data)\",\n \"def decrypt(self, secret):\\n return self._transform(secret, self._decoder)\",\n \"def decrypt(self, secret):\\n return self._transform(secret, self._decoder)\",\n \"def _des_crypt(self, block, crypt_type):\\n block = self._permutate(self.__ip, block)\\n num_bits = 8 * self.block_size\\n self.L = block[:num_bits // 2]\\n self.R = block[num_bits // 2:]\\n\\n if crypt_type == self.ENCRYPT:\\n key_iter = 0\\n key_delt = 1\\n else:\\n key_iter = 15\\n key_delt = -1\\n\\n for i in range(0, 16):\\n temp_R = self.R\\n # expand 32-bit R into 48-bit R\\n self.R = self._permutate(self.__expansion_table, self.R)\\n self.R = list(map(lambda x, y: x ^ y, self.R, self.Kn[key_iter]))\\n B = [self.R[:6], self.R[6:12], self.R[12:18], self.R[18:24],\\n self.R[24:30], self.R[30:36], self.R[36:42], self.R[42:]]\\n\\n # permute B[1] to B[8] using the S-boxes\\n pos = 0\\n Bn = [0] * 32\\n for j in range(0, 8):\\n # offsets\\n m = (B[j][0] << 1) + (B[j][5])\\n n = (B[j][1] << 3) + (B[j][2] << 2) + (B[j][3] << 1) + (B[j][4])\\n\\n # find the permutation value\\n v = self.__sbox[j][(m << 4) + n]\\n\\n # turn value into bits\\n Bn[pos] = (v & 8) >> 3\\n Bn[pos+1] = (v & 4) >> 2\\n Bn[pos+2] = (v & 2) >> 1\\n Bn[pos+3] = v & 1\\n\\n pos += 4\\n\\n self.R = self._permutate(self.__p, Bn)\\n\\n self.R = list(map(lambda x, y: x ^ y, self.R, self.L))\\n\\n self.L = temp_R\\n\\n key_iter += key_delt\\n\\n self.final = self._permutate(self.__fp, self.R + self.L)\\n return self.final\",\n \"def deal(self):\\n hands = sample(self.deck, 13) #random sample so no need to shuffle\\n hand1, hand2, flip = hands[:6], hands[6:-1], hands[-1]\\n return hand1, hand2, flip\",\n \"def generateShares(self,secret,n,k):\\n # generate a random polynomial\\n a = np.zeros((k,),dtype=self.stype)\\n for i in range(0,k-1): # select random coefficients\\n a[i] = self.F.GetRandomElement()\\n a[k-1] = secret # secret is the last element\\n\\n # evaluate the polynomial at 1,2,...,n.\\n D = {} # shares\\n for i in range(0,n):\\n D[i+1] = self._evalPoly(a,i+1)\\n return D\",\n \"def _key_share(self, grease):\\n ext = b\\\"\\\\x00\\\\x33\\\"\\n\\n # Add grease value if necessary.\\n if grease:\\n share_ext = self._choose_grease()\\n share_ext += b\\\"\\\\x00\\\\x01\\\\x00\\\"\\n else:\\n share_ext = b\\\"\\\"\\n\\n group = b\\\"\\\\x00\\\\x1d\\\"\\n share_ext += group\\n key_exchange_length = b\\\"\\\\x00\\\\x20\\\"\\n share_ext += key_exchange_length\\n share_ext += os.urandom(32)\\n second_length = len(share_ext)\\n first_length = second_length+2\\n ext += struct.pack(\\\">H\\\", first_length)\\n ext += struct.pack(\\\">H\\\", second_length)\\n ext += share_ext\\n\\n return ext\",\n \"def decrypt_pass(self, cont):\\r\\n try:\\r\\n iv = cont[3:15]\\r\\n data = cont[15:]\\r\\n ciph = AES.new(self.chrome_key(), AES.MODE_GCM, iv)\\r\\n decrypted = ciph.decrypt(data)\\r\\n decrypted = decrypted[:-16].decode()\\r\\n return decrypted\\r\\n except:\\r\\n decrypted = win32crypt.CryptUnprotectData(buff, None, None, None, 0)\\r\\n return decrypted[1]\",\n \"def obfuscate(self):\\n r = self.public_key.get_random_lt_n()\\n r_pow_n = powmod(r, self.public_key.n, self.public_key.nsquare)\\n self.__ciphertext = self.__ciphertext * r_pow_n % self.public_key.nsquare\\n self.__is_obfuscated = True\",\n \"def get_secret(self):\\n return Buffer.from_mpz(self._secret_key)\",\n \"def decode(self, crypto):\",\n \"def Obfuscate(self,passphrase=None,public_attributes=[]):\\n\\t\\t\\n\\t\\tnew_me = self.Secure(passphrase,['ID','status'])\\n\\n\\t\\treturn new_me\",\n \"def mulligan(self):\\n self.deck.extend(self.hand) # Put hand back in deck\\n self.hand.clear() # Clear hand\\n random.shuffle(self.deck) # Shuffle deck\\n self.draw() # Redraw cards\",\n \"def decrypt(self, secret):\\n return str.translate(secret, self._decoder)\",\n \"def main():\\n # key = random(1024)\\n # ciphertexts = [encrypt(key, msg) for msg in MSGS]\\n\\n # Get key and secret message\\n knownPlain2 = \\\"The nice thing about Keeyloq is now we cryptographers can drive a lot of fancy cars - Dan Boneh\\\"\\n key = strxor(ciphertexts[2], knownPlain2)\\n secret = strxor(target, key)\\n\\n print \\\"Key: \\\" + key\\n print \\\"Key (Hex): \\\" + key.encode(\\\"hex\\\")\\n print \\\"Secret: \\\" + secret\",\n \"def generate_sharedsecret_bytes(self):\\n return number_to_string(\\n self.generate_sharedsecret(),\\n self.private_key.curve.order)\",\n \"def combine_shares(share_list: List[bytes]) -> bytes:\\n unpickled_share_list: List[List[Tuple[int, bytes]]] = [\\n cast(List[Tuple[int, bytes]], pickle.loads(share)) for share in share_list\\n ]\\n\\n chunk_num = len(unpickled_share_list[0])\\n secret_padded = bytearray(0)\\n chunk_shares_list: List[List[Tuple[int, bytes]]] = []\\n for i in range(chunk_num):\\n chunk_shares: List[Tuple[int, bytes]] = []\\n for share in unpickled_share_list:\\n chunk_shares.append(share[i])\\n chunk_shares_list.append(chunk_shares)\\n\\n with ThreadPoolExecutor(max_workers=10) as executor:\\n for chunk in executor.map(_shamir_combine, chunk_shares_list):\\n secret_padded += chunk\\n\\n secret = unpad(secret_padded, 16)\\n return bytes(secret)\",\n \"def decrypt(self, password):\\r\\n\\r\\n key = self.config.get_string(\\\"gox\\\", \\\"secret_key\\\")\\r\\n sec = self.config.get_string(\\\"gox\\\", \\\"secret_secret\\\")\\r\\n if sec == \\\"\\\" or key == \\\"\\\":\\r\\n return self.S_NO_SECRET\\r\\n\\r\\n # pylint: disable=E1101\\r\\n hashed_pass = hashlib.sha512(password.encode(\\\"utf-8\\\")).digest()\\r\\n crypt_key = hashed_pass[:32]\\r\\n crypt_ini = hashed_pass[-16:]\\r\\n aes = AES.new(crypt_key, AES.MODE_OFB, crypt_ini)\\r\\n try:\\r\\n encrypted_secret = base64.b64decode(sec.strip().encode(\\\"ascii\\\"))\\r\\n self.secret = aes.decrypt(encrypted_secret).strip()\\r\\n self.key = key.strip()\\r\\n except ValueError:\\r\\n return self.S_FAIL\\r\\n\\r\\n # now test if we now have something plausible\\r\\n try:\\r\\n print(\\\"testing secret...\\\")\\r\\n # is it plain ascii? (if not this will raise exception)\\r\\n dummy = self.secret.decode(\\\"ascii\\\")\\r\\n # can it be decoded? correct size afterwards?\\r\\n if len(base64.b64decode(self.secret)) != 64:\\r\\n raise Exception(\\\"decrypted secret has wrong size\\\")\\r\\n\\r\\n print(\\\"testing key...\\\")\\r\\n # key must be only hex digits and have the right size\\r\\n hex_key = self.key.replace(\\\"-\\\", \\\"\\\").encode(\\\"ascii\\\")\\r\\n if len(binascii.unhexlify(hex_key)) != 16:\\r\\n raise Exception(\\\"key has wrong size\\\")\\r\\n\\r\\n print(\\\"ok :-)\\\")\\r\\n return self.S_OK\\r\\n\\r\\n except Exception as exc:\\r\\n # this key and secret do not work :-(\\r\\n self.secret = \\\"\\\"\\r\\n self.key = \\\"\\\"\\r\\n print(\\\"### Error occurred while testing the decrypted secret:\\\")\\r\\n print(\\\" '%s'\\\" % exc)\\r\\n print(\\\" This does not seem to be a valid MtGox API secret\\\")\\r\\n return self.S_FAIL\",\n \"def sym_dec(self, ciph, passphrase):\\n (rfd, wfd) = xpipe()\\n os.write(wfd, passphrase + '\\\\n')\\n plain = xsystem([self.sslname, self.symmetric, '-d', '-pass',\\n 'fd:' + str(rfd)], ciph)\\n xclose(wfd)\\n xclose(rfd)\\n if not plain:\\n warning('keymanagement: Unable to decrypt because %s does not exist\\\\n' %(self.sslname))\\n return None\\n\\n return plain\",\n \"def genKey(self, otherKey):\\n self.sharedSecret = self.genSecret(self.privateKey, otherKey)\\n #print(\\\"Shared secret:\\\")\\n #print(self.sharedSecret)\\n s = hashlib.sha256()\\n s.update(bytes(str(self.sharedSecret).encode()))\\n self.key = s.digest()\",\n \"def generate_sharedsecret(self):\\n return self._get_shared_secret(self.public_key)\",\n \"def session_key(self, public_B):\\n raw_secret = gmp.powmod(\\n public_B.to_mpz(),\\n self._secret_key,\\n self._dh_p\\n )\\n\\n # Hash the secret to create a key\\n h_256 = SHA256.new()\\n h_256.update(raw_secret.digits(10))\\n raw_key = h_256.digest()\\n\\n return Buffer(raw_key)\",\n \"def decrypt(self, buffer):\\n try:\\n ct = base64.b64decode(buffer)\\n except:\\n print('f a i l')\\n return bytes('fail')\\n\\n cipher = AES.new(self.psk, AES.MODE_GCM, FIXED_IV)\\n pt = unpad(cipher.decrypt(ct), AES.block_size)\\n return pt\",\n \"def prompt_encrypt(self):\\r\\n print(\\\"Please copy/paste key and secret from MtGox and\\\")\\r\\n print(\\\"then provide a password to encrypt them.\\\")\\r\\n print(\\\"\\\")\\r\\n\\r\\n\\r\\n key = input(\\\" key: \\\").strip()\\r\\n secret = input(\\\" secret: \\\").strip()\\r\\n while True:\\r\\n password1 = getpass.getpass(\\\" password: \\\").strip()\\r\\n if password1 == \\\"\\\":\\r\\n print(\\\"aborting\\\")\\r\\n return\\r\\n password2 = getpass.getpass(\\\"password (again): \\\").strip()\\r\\n if password1 != password2:\\r\\n print(\\\"you had a typo in the password. try again...\\\")\\r\\n else:\\r\\n break\\r\\n\\r\\n # pylint: disable=E1101\\r\\n hashed_pass = hashlib.sha512(password1.encode(\\\"utf-8\\\")).digest()\\r\\n crypt_key = hashed_pass[:32]\\r\\n crypt_ini = hashed_pass[-16:]\\r\\n aes = AES.new(crypt_key, AES.MODE_OFB, crypt_ini)\\r\\n\\r\\n # since the secret is a base64 string we can just just pad it with\\r\\n # spaces which can easily be stripped again after decryping\\r\\n print(len(secret))\\r\\n secret += \\\" \\\" * (16 - len(secret) % 16)\\r\\n print(len(secret))\\r\\n secret = base64.b64encode(aes.encrypt(secret)).decode(\\\"ascii\\\")\\r\\n\\r\\n self.config.set(\\\"gox\\\", \\\"secret_key\\\", key)\\r\\n self.config.set(\\\"gox\\\", \\\"secret_secret\\\", secret)\\r\\n self.config.save()\\r\\n\\r\\n print(\\\"encrypted secret has been saved in %s\\\" % self.config.filename)\",\n \"def decipher(self):\\n plaintext = \\\"\\\"\\n for ct, key_char in zip(self.text, self.key):\\n char_index = self.char_block.rows[key_char].index(ct)\\n plaintext += self.char_block.alphabet[char_index]\\n print(plaintext)\",\n \"def splitImage(image, shareFile1=\\\"share1.tif\\\", shareFile2=\\\"share2.tif\\\"):\\n\\n _, expandedPad = makePad(Image.open(image).size, shareFile1)\\n expandedCiphertext = makeCryptograph(str(image), shareFile2)\\n print(expandedPad,expandedCiphertext)\\n return expandedPad, expandedCiphertext\",\n \"def prompt_decrypt(self):\\r\\n if self.know_secret():\\r\\n return self.S_OK\\r\\n\\r\\n key = self.config.get_string(\\\"gox\\\", \\\"secret_key\\\")\\r\\n sec = self.config.get_string(\\\"gox\\\", \\\"secret_secret\\\")\\r\\n if sec == \\\"\\\" or key == \\\"\\\":\\r\\n return self.S_NO_SECRET\\r\\n\\r\\n if self.password_from_commandline_option:\\r\\n password = self.password_from_commandline_option\\r\\n else:\\r\\n password = getpass.getpass(\\\"enter passphrase for secret: \\\")\\r\\n\\r\\n result = self.decrypt(password)\\r\\n if result != self.S_OK:\\r\\n print(\\\"\\\")\\r\\n print(\\\"secret could not be decrypted\\\")\\r\\n answer = input(\\\"press any key to continue anyways \\\" \\\\\\r\\n + \\\"(trading disabled) or 'q' to quit: \\\")\\r\\n if answer == \\\"q\\\":\\r\\n result = self.S_FAIL_FATAL\\r\\n else:\\r\\n result = self.S_NO_SECRET\\r\\n return result\",\n \"def decrypt(cls, ciphertext_and_tag, aad, key, iv):\",\n \"def decrypt(self, sentence, pad):\\r\\n sentence = list(sentence)\\r\\n decrypted_sentence = []\\r\\n x = list(\\\"abcdefghijklmnopqrstuvwxyz\\\")\\r\\n l = len(x)\\r\\n y = pad \\r\\n z = list(zip(x, y))\\r\\n z.append((\\\" \\\", \\\" \\\"))\\r\\n for i in sentence:\\r\\n if i.lower() not in x:\\r\\n decrypted_sentence.append(i)\\r\\n continue \\r\\n for a in z:\\r\\n if i.lower() == a[1]:\\r\\n if i.isupper():\\r\\n decrypted_sentence.append(a[0].upper())\\r\\n else:\\r\\n decrypted_sentence.append(a[0])\\r\\n decrypted_sentence = \\\"\\\".join(decrypted_sentence)\\r\\n return decrypted_sentence\",\n \"def Private(self):\\n self.Send(self.EncryptString('private\\\\n'))\\n print self.DecryptString(self.Recv(4096))\\n print self.DecryptString(self.Recv(4096))\",\n \"def shared_key(private_key,public_key):\\n\\treturn private_key.exchange(public_key)\",\n \"def brute_force_decrypt(text):\\n for n in range(26):\\n print(f\\\"Using a shift value of {n}\\\")\\n print(decrypt(text, n))\\n print(\\\"\\\\n***\\\\n\\\")\",\n \"def calcSecret(self,D):\\n idxs = list(D.keys())\\n k = len(idxs) # number of shares given\\n\\n # evaluate terms of Lagrange polynomial at zero\\n # see https://en.wikipedia.org/wiki/Lagrange_polynomial\\n for i in range(0,k):\\n for j in range(0,k):\\n if i == j:\\n pass\\n else:\\n D[idxs[i]] = self.F.Divide(self.F.Multiply(D[idxs[i]],idxs[j]),self.F.Subtract(idxs[i],idxs[j]))\\n \\n # sum terms to recover secret\\n y = D[idxs[0]]\\n for i in range(1,k):\\n y = self.F.Add(y,D[idxs[i]]) \\n return y\",\n \"def link(self, secret=None, secondSecret=None):\\r\\n if hasattr(dposlib, \\\"core\\\"):\\r\\n if secret:\\r\\n keys = dposlib.core.crypto.getKeys(secret)\\r\\n self.senderPublicKey = keys[\\\"publicKey\\\"]\\r\\n self._privateKey = keys[\\\"privateKey\\\"]\\r\\n if secondSecret:\\r\\n keys = dposlib.core.crypto.getKeys(secondSecret)\\r\\n self._secondPrivateKey = keys[\\\"privateKey\\\"]\",\n \"def decrypt(priv, pub, cipher):\\n x = myExp(cipher, priv.lamb, pub.n_sq) - 1\\n plain = ((x // pub.n) * priv.mu) % pub.n\\n return plain\",\n \"def break_cipher( self, ciphertexts ):\\n\\n\\t\\ttruncated = self.__truncate(ciphertexts)\\n\\t\\tciphertexstring = b''.join( truncated )\\n\\n\\t\\tkeystream_size = len( truncated[0] )\\n\\n\\t\\ttransposed = self.__transpose( ciphertexstring, keystream_size )\\n\\n\\t\\txor_key = b''\\n\\t\\tfor block in transposed:\\n\\t\\t\\thex_block = hexlify( block )\\n\\t\\t\\txor_key += bytes( [ ord( break_xor_single_byte_by_freq(hex_block) ) ] )\\n\\n\\t\\treturn xor_key\",\n \"def getBalancedAssetComposition(self):\\n composition = dict()\\n composition['bull'] = 50\\n composition['bear'] = 100 - composition['bull']\\n return composition\",\n \"def decrypt():\\n plaintext = \\\"\\\"\\n i = 0\\n while i < len(ciphertext):\\n if i%2==1:\\n try:\\n plaintext += key[ ciphertext[i-1]+ciphertext[i] ]\\n except KeyError:\\n plaintext += ciphertext[i-1]+ciphertext[i]\\n i += 1\\n return plaintext\",\n \"def decrypt(self, message):\\n # message = message.upper().split()\\n # message = \\\"\\\".join(message)\\n # desalting the message to remove 5 characters blocks\\n padding = input(\\\"Have you used 5 characters blocks? y/n \\\")\\n if padding == \\\"y\\\":\\n message = message.replace(\\\" \\\", \\\"\\\")\\n message = self.desalt_random(message)\\n message = \\\"\\\".join(message)\\n\\n message = message.upper()\\n message_list = []\\n for ch in message:\\n message_list.append(self.main_dict[ch][0])\\n\\n # OTP Encryption / process the message with OTP\\n otp = input(\\\"What is the OTP that was generated for you during \\\"\\n \\\"encryption process?: \\\")\\n otp = otp.upper()\\n random_otp = []\\n for ch in otp:\\n random_otp.append(self.main_dict[ch][0])\\n\\n # If OTP is correct, decrypt the message with mod27\\n if len(message_list) != len(random_otp):\\n print(\\\"You typed a wrong OTP.\\\")\\n return None\\n else:\\n math_list = []\\n for i, item in enumerate(message_list):\\n if message_list[i] >= random_otp[i]:\\n x = message_list[i] - random_otp[i]\\n for key, value in self.main_dict.items():\\n if value[0] == x:\\n math_list.append(key)\\n else:\\n for key, value in self.main_dict.items():\\n if item == value[0]:\\n x = value[1] - random_otp[i]\\n for key, value in self.main_dict.items():\\n if value[0] == x:\\n math_list.append(key)\\n return \\\"\\\".join(math_list)\",\n \"def _save_tally_share(\\n self, guardian_id: GuardianId, guardians_tally_share: DecryptionShare\\n ) -> None:\\n self._tally_shares[guardian_id] = guardians_tally_share\",\n \"def crack(self, iterable: Iterable[str]):\\n self.pool.map_async(self.unsign, iterable, error_callback=logger.error)\\n self.pool.close()\\n self.pool.join()\\n return self.secret\",\n \"def _decrypt_block(self, v, k):\\n DEBUG = GLOBAL_DEBUG and True\\n if DEBUG: print \\\"_decrypt_block()\\\"\\n\\n v0 = struct.unpack(\\\"<L\\\", v[0:4])[0]\\n v1 = struct.unpack(\\\"<L\\\", v[4:8])[0]\\n delta = CRYPTO_DETLA; _sum = CRYPTO_SUM\\n k0 = struct.unpack(\\\"<L\\\", k[ 0: 4])[0]\\n k1 = struct.unpack(\\\"<L\\\", k[ 4: 8])[0]\\n k2 = struct.unpack(\\\"<L\\\", k[ 8:12])[0]\\n k3 = struct.unpack(\\\"<L\\\", k[12:16])[0]\\n\\n for i in range(CRYPTO_ROUNDS):\\n tmp0 = uint32_t(uint32_t(v0 << 6) + k2)\\n tmp1 = uint32_t(v0 + _sum)\\n tmp2 = uint32_t(uint32_t(v0 >> 7) + k3)\\n v1 = uint32_t(v1 - uint32_t(tmp0 ^ tmp1 ^ tmp2))\\n\\n tmp0 = uint32_t(uint32_t(v1 << 6) + k0)\\n tmp1 = uint32_t(v1 + _sum)\\n tmp2 = uint32_t(uint32_t(v1 >> 7) + k1)\\n v0 = uint32_t(v0 - uint32_t(tmp0 ^ tmp1 ^ tmp2))\\n\\n _sum = uint32_t(_sum - delta)\\n\\n return struct.pack(\\\"<LL\\\", v0, v1)\",\n \"def find(cls, name, pass_phrase=None):\\n\\n secret = cls.get_instance(name)\\n secret_data = secret.data[0] # using backref\\n\\n if not pass_phrase:\\n pass_phrase = secret_data.pass_phrase\\n else:\\n pass_phrase = pass_phrase.encode()\\n\\n enc_msg = secret_data.generate_enc_msg()\\n LOG.debug(\\\"Decrypting data\\\")\\n secret_val = Crypto.decrypt_AES_GCM(enc_msg, pass_phrase)\\n\\n return secret_val\",\n \"def de_cryptate(self):\\r\\n\\r\\n intab1 = \\\"abcdefghijklomnopqrstuvwxyz !,.\\\"\\r\\n outtab1 = \\\"?2p=o)7i(u9/y&t3%r¤5e#w1q!>*'^;)\\\"\\r\\n# Fetching from written in textbox\\r\\n s = self.textbox.toPlainText()\\r\\n a = s.lower()\\r\\n# Changing out the letters/numbers/etc\\r\\n crypted = (a.translate({ord(x): y for (y, x) in zip(intab1, outtab1)}))\\r\\n# Clear the textbox\\r\\n self.textbox.clear()\\r\\n# Write the Decrypted text\\r\\n self.textbox.setPlainText(crypted)\",\n \"def derive_keys(self, master_salt, master_secret):\\n\\n self.sender_key = self._kdf(master_salt, master_secret, self.sender_id, 'Key')\\n self.recipient_key = self._kdf(master_salt, master_secret, self.recipient_id, 'Key')\\n\\n self.common_iv = self._kdf(master_salt, master_secret, b\\\"\\\", 'IV')\",\n \"def genSecret(self, privateKey, otherKey):\\n\\n\\t\\tsharedSecret = pow(otherKey, privateKey, self.prime_p)\\n\\t\\treturn sharedSecret\",\n \"def decrypt(self, phrase):\\n keyword = input(\\\"What keyword is it encrypted with? \\\")\\n plaintext = \\\"ABCDEFGHIJKLMNOPQRSTUVWXYZ\\\"\\n ciphertext = []\\n decrypted = []\\n for i in keyword.upper():\\n if i not in ciphertext:\\n ciphertext.append(i)\\n for i in plaintext:\\n if i not in ciphertext:\\n ciphertext.append(i)\\n\\n key_dict = dict(zip(plaintext, ciphertext))\\n\\n for i in phrase.upper():\\n if i == \\\" \\\":\\n decrypted.append(\\\" \\\")\\n else:\\n for key, value in key_dict.items():\\n if i == value:\\n decrypted.append(key)\\n\\n return \\\"\\\".join(decrypted)\",\n \"def _reset(self) -> None:\\n\\n self.done_bidding = False\\n self.done_playing = False\\n\\n self.contract.reset()\\n\\n # resetting bidding history\\n # 1C 1D 1H 1S 1N ... 7N (PASS - not considered)\\n self.history_bid = np.zeros(36, dtype=np.uint8)\\n\\n self.history_play = np.full((NUM_PLAYERS, NUM_PLAYS), np.nan)\\n\\n # generating vulnerabilities\\n self.vulnerability = (np.random.rand(NUM_PAIRS) > 0.5).astype(np.uint8)\\n self.vulnerabilities = self.vulnerability[[0, 1, 0, 1]]\\n\\n # resetting auction_history\\n self.auction_history = np.zeros(self.auction_history_shape, dtype=np.uint8)\\n\\n # resetting bidding elimination signal - doubles and redoubles are not allowed at the start\\n self.elim_sig_bid = np.ones(AUCTION_SPACE_SIZE, dtype=np.uint8)\\n self.elim_sig_bid[REDOUBLE_RANGE] = 0\\n\\n # resetting the players' hands (aka one_hot_deal)\\n self.one_hot_deal = np.zeros((NUM_PLAYERS, NUM_CARDS), dtype=np.uint8)\\n self.one_hot_known_deal = np.ones((NUM_PLAYERS, NUM_CARDS), dtype=np.uint8)\\n\\n # resetting playing elimination signal: without\\n self.elim_sig_play = np.ones((NUM_PLAYERS, NUM_CARDS), dtype=np.uint8)\\n\\n # resetting various counts\\n self.max_bid = -1\\n\\n self.n_pass = 0\\n self.n_double = 0\\n self.n_redouble = 0\\n\\n # index of the first bidder; start from the smallest one by default\\n # TODO[ス: should I care that the player in the 1st bidding seat always starts bidding?\\n # I don't see how this could cause any problems\\n self.turn_bid = self.bidding_seats[0]\\n self.turn_play = None\\n\\n self.n_play_actions = 0\\n self.n_play_turns = 0\\n self.tricks = np.zeros(NUM_PLAYERS, dtype=np.uint8)\\n self.score_play = np.zeros((NUM_PLAYS + 1, NUM_PLAYERS))\",\n \"def computeSecretKey(g, p):\\r\\n \\\"\\\"\\\"You will need to implement this function.\\\"\\\"\\\"\\r\\n return random.randint(1, p-1)\",\n \"def dh_encrypt(pub, message):\\n \\n Group, private, public = dh_get_key()#generate new DH pair for Alice\\n #private key is an integer/scalar and public key is a point on the curve \\n \\n #check whether public key of Bob is valid and on curve \\n assert Group.check_point(pub)\\n \\n #Alice obtains shared secret by multiplying her private key with bob's forwarded public key\\n key = pub.pt_mul(private)#dA* qB\\n print \\\"key from enc is\\\", key\\n \\n hashedKey=sha256(key.export()).digest()\\n\\n \\n plaintext = message.encode(\\\"utf8\\\")#encode message\\n aes = Cipher(\\\"aes-128-gcm\\\")#select cipher\\n iv = urandom(16)#generate initialization vector \\n cipher, tag = aes.quick_gcm_enc(hashedKey[:16], iv, plaintext)#encrypt using shared key \\n ciphertext = [iv,cipher,tag,public]\\n\\n return ciphertext\",\n \"def secret():\\n pass\",\n \"def decrypt(self, C, D):\\n M = D + (ORDER-self.x)*C\\n\\n print(\\\"M =\\\", M)\\n\\n D2 = D + (ORDER - 1)*M\\n\\n r = random_order()\\n\\n B0 = r*G\\n B1 = r*C\\n\\n h = SHA256.new()\\n h.update(str(self.Y).encode())\\n h.update(str(C).encode())\\n h.update(str(D2).encode())\\n h.update(str(B0).encode())\\n h.update(str(B1).encode())\\n\\n c = int(h.hexdigest(), 16)\\n\\n z = (r + c*self.x) % ORDER\\n\\n return (M, c, z)\",\n \"def generate(nof_shares, min_shares, clipboard, qr_code, long):\\n w = int(math.log10(nof_shares)) + 1\\n\\n print(f\\\"Generating random shared secrets using '{min_shares} of {nof_shares}' config...\\\")\\n mnemonic_secret, secret_bits, mnemonic_shares = make_random_mnemonic_shares(\\n minimum_shares=min_shares,\\n nof_shares=nof_shares,\\n prime=PRIME_13TH_MERSENNE if long else PRIME_12TH_MERSENNE,\\n )\\n\\n if qr_code:\\n generate_qrcode(mnemonic_secret, \\\"master\\\")\\n\\n mnemonic_secret_wrapped = \\\"\\\\n\\\\t\\\".join(textwrap.wrap(mnemonic_secret))\\n msg = f\\\"\\\"\\\"Generated secret ( equivalent of {secret_bits} bits ):\\n\\\\t{mnemonic_secret_wrapped}\\nUse at least {min_shares} of the following {nof_shares} shared secrets to recover secret:\\\"\\\"\\\"\\n for i, ms in enumerate(mnemonic_shares):\\n ms_wrapped = \\\"\\\\n\\\\t\\\".join(textwrap.wrap(ms))\\n msg += f\\\"\\\\n{i + 1:{w}d}:\\\\n\\\\t{ms_wrapped}\\\"\\n if qr_code:\\n generate_qrcode(ms, f\\\"{i+1:0{w}d}\\\")\\n\\n if clipboard:\\n copy_to_clipboard_and_clear(\\\"Generated secret and shared secret\\\", msg)\\n else:\\n print(msg)\\n\\n # test recovering the secret\\n for _ in range(nof_shares * 10):\\n k = random.randint(min_shares, nof_shares)\\n test_mnemonic_shares = random.sample(mnemonic_shares, k=k)\\n test_mnemonic_secret = number_to_mnemonic(recover_mnemonic_secret(test_mnemonic_shares))\\n assert test_mnemonic_secret == mnemonic_secret\\n print(\\\"Done.\\\")\",\n \"def decrypt_chunk(self, chunk):\\n L, R = chunk\\n # Run the feistel rounds as in encryption, but with keys going from n..1\\n for i in range(self.number_of_rounds, 0, -1):\\n L, R = self.feistel_round(L, R, i)\\n return R, L\",\n \"def symcipher_from_secret(\\n cls,\\n secret,\\n algorithm=TPM2_ALG.AES,\\n mode=TPM2_ALG.CFB,\\n nameAlg=TPM2_ALG.SHA256,\\n objectAttributes=(\\n TPMA_OBJECT.DECRYPT | TPMA_OBJECT.SIGN_ENCRYPT | TPMA_OBJECT.USERWITHAUTH\\n ),\\n seed=None,\\n ):\\n sa, pa = TPMT_SENSITIVE.symcipher_from_secret(\\n secret, algorithm, mode, nameAlg, objectAttributes, seed\\n )\\n priv = TPM2B_SENSITIVE(sensitiveArea=sa)\\n pub = TPM2B_PUBLIC(publicArea=pa)\\n return (priv, pub)\",\n \"def test_share_distributor(self):\\n\\n # =================================================================\\n # test: complete test, share distribution int\\n # =================================================================\\n\\n sell_list = [StockOrderWrapper(self.order_2)]\\n sell = sell_list[0]\\n buy_orders = [StockOrderWrapper(self.order_3), StockOrderWrapper(self.order_4), StockOrderWrapper(self.order_7),\\n StockOrderWrapper(self.order_8), StockOrderWrapper(self.order_11),\\n StockOrderWrapper(self.order_12)]\\n\\n result = self.bidding_round_manager.share_distributor(sell_orders=sell_list, buy_orders=buy_orders)\\n\\n order_real_3 = result[0]\\n order_real_4 = result[1]\\n order_real_7 = result[2]\\n order_real_8 = result[3]\\n order_real_11 = result[4]\\n order_real_12 = result[5]\\n\\n sell_order_dict_1 = {sell: 1}\\n sell_order_dict_2 = {sell: 2}\\n\\n order_exp_3 = StockOrderWrapper(self.order_3)\\n order_exp_4 = StockOrderWrapper(self.order_4)\\n order_exp_7 = StockOrderWrapper(self.order_7)\\n order_exp_8 = StockOrderWrapper(self.order_8)\\n order_exp_11 = StockOrderWrapper(self.order_11)\\n order_exp_12 = StockOrderWrapper(self.order_12)\\n\\n order_exp_3.transaction_dict = sell_order_dict_1\\n order_exp_4.transaction_dict = sell_order_dict_2\\n order_exp_7.transaction_dict = sell_order_dict_2\\n order_exp_8.transaction_dict = sell_order_dict_2\\n order_exp_11.transaction_dict = sell_order_dict_2\\n order_exp_12.transaction_dict = sell_order_dict_1\\n\\n order_exp_3.shares_left = 4\\n order_exp_4.shares_left = 8\\n order_exp_7.shares_left = 8\\n order_exp_8.shares_left = 8\\n order_exp_11.shares_left = 8\\n order_exp_12.shares_left = 4\\n\\n self.is_equal_order_wrapper(order_real_3, order_exp_3)\\n self.is_equal_order_wrapper(order_real_4, order_exp_4)\\n self.is_equal_order_wrapper(order_real_7, order_exp_7)\\n self.is_equal_order_wrapper(order_real_8, order_exp_8)\\n self.is_equal_order_wrapper(order_real_11, order_exp_11)\\n self.is_equal_order_wrapper(order_real_12, order_exp_12)\\n\\n # =================================================================\\n # test: share distribution float easy\\n # =================================================================\\n\\n sell_list = [StockOrderWrapper(self.order_2)]\\n sell = sell_list[0]\\n\\n buy_order_3 = StockOrderWrapper(self.order_3)\\n buy_order_4 = StockOrderWrapper(self.order_4)\\n buy_order_7 = StockOrderWrapper(self.order_7)\\n buy_order_8 = StockOrderWrapper(self.order_8)\\n buy_order_11 = StockOrderWrapper(self.order_11)\\n buy_order_12 = StockOrderWrapper(self.order_12)\\n\\n sell.shares_left = 6\\n buy_order_3.shares_left = 8 # 2.4 -> 3\\n buy_order_4.shares_left = 4 # 1.2 -> 1\\n buy_order_7.shares_left = 4 # 1.2 -> 1\\n buy_order_8.shares_left = 4 # 1.2 -> 1\\n buy_order_11.shares_left = 0 # 0.0 -> 0\\n buy_order_12.shares_left = 0 # 0.0 -> 0\\n\\n buy_orders = [buy_order_3, buy_order_4, buy_order_7, buy_order_8, buy_order_11, buy_order_12]\\n\\n result = self.bidding_round_manager.share_distributor(sell_orders=sell_list, buy_orders=buy_orders)\\n\\n result_dict = {}\\n\\n for res in result:\\n result_dict[res.stock_order.order_id] = res\\n\\n try:\\n # noinspection PyUnusedLocal\\n dummy = result[4]\\n raise AssertionError(\\\"IndexError exception expected\\\")\\n except IndexError:\\n pass\\n\\n sell_order_dict_1 = {sell: 1}\\n sell_order_dict_3 = {sell: 3}\\n\\n order_exp_3.transaction_dict = sell_order_dict_3\\n order_exp_4.transaction_dict = sell_order_dict_1\\n order_exp_7.transaction_dict = sell_order_dict_1\\n order_exp_8.transaction_dict = sell_order_dict_1\\n\\n order_exp_3.shares_left = 5\\n order_exp_4.shares_left = 3\\n order_exp_7.shares_left = 3\\n order_exp_8.shares_left = 3\\n\\n self.is_equal_order_wrapper(result_dict.get(3), order_exp_3)\\n self.is_equal_order_wrapper(result_dict.get(4), order_exp_4)\\n self.is_equal_order_wrapper(result_dict.get(7), order_exp_7)\\n self.is_equal_order_wrapper(result_dict.get(8), order_exp_8)\\n\\n # =================================================================\\n # test: share distribution float complex (multiple float iterations)\\n # =================================================================\\n\\n sell_list = [StockOrderWrapper(self.order_2)]\\n sell = sell_list[0]\\n\\n buy_order_3 = StockOrderWrapper(self.order_3)\\n buy_order_4 = StockOrderWrapper(self.order_4)\\n buy_order_7 = StockOrderWrapper(self.order_7)\\n buy_order_8 = StockOrderWrapper(self.order_8)\\n buy_order_11 = StockOrderWrapper(self.order_11)\\n buy_order_12 = StockOrderWrapper(self.order_12)\\n\\n sell.shares_left = 18\\n sell.stock_order.order_status = DEFINITIVE\\n\\n self.order_3.order_status = DEFINITIVE\\n self.order_4.order_status = DEFINITIVE\\n self.order_7.order_status = DEFINITIVE\\n self.order_8.order_status = DEFINITIVE\\n self.order_11.order_status = DEFINITIVE\\n self.order_12.order_status = DEFINITIVE\\n\\n buy_order_3.shares_left = 6 # 3.6 -> 4\\n buy_order_4.shares_left = 4 # 2.4 -> 2\\n buy_order_7.shares_left = 2 # 1.2 -> 1\\n buy_order_8.shares_left = 2 # 1.2 -> 1\\n buy_order_11.shares_left = 8 # 4.8 -> 5\\n buy_order_12.shares_left = 8 # 4.8 -> 5\\n\\n buy_orders = [buy_order_3, buy_order_4, buy_order_7, buy_order_8, buy_order_11, buy_order_12]\\n\\n result = self.bidding_round_manager.share_distributor(sell_orders=sell_list, buy_orders=buy_orders)\\n\\n result_dict = {}\\n\\n for res in result:\\n result_dict[res.stock_order.order_id] = res\\n\\n try:\\n # noinspection PyUnusedLocal\\n dummy = result[6]\\n raise AssertionError(\\\"IndexError exception expected\\\")\\n except IndexError:\\n pass\\n\\n sell_order_dict_1 = {sell: 1}\\n sell_order_dict_2 = {sell: 2}\\n sell_order_dict_4 = {sell: 4}\\n sell_order_dict_5 = {sell: 5}\\n\\n order_exp_3.transaction_dict = sell_order_dict_4\\n order_exp_4.transaction_dict = sell_order_dict_2\\n order_exp_7.transaction_dict = sell_order_dict_1\\n order_exp_8.transaction_dict = sell_order_dict_1\\n order_exp_11.transaction_dict = sell_order_dict_5\\n order_exp_12.transaction_dict = sell_order_dict_5\\n\\n order_exp_3.shares_left = 2\\n order_exp_4.shares_left = 2\\n order_exp_7.shares_left = 1\\n order_exp_8.shares_left = 1\\n order_exp_11.shares_left = 3\\n order_exp_12.shares_left = 3\\n\\n self.is_equal_order_wrapper(result_dict.get(3), order_exp_3)\\n self.is_equal_order_wrapper(result_dict.get(4), order_exp_4)\\n self.is_equal_order_wrapper(result_dict.get(7), order_exp_7)\\n self.is_equal_order_wrapper(result_dict.get(8), order_exp_8)\\n self.is_equal_order_wrapper(result_dict.get(11), order_exp_11)\\n self.is_equal_order_wrapper(result_dict.get(12), order_exp_12)\\n\\n # =================================================================\\n # test: share distribution date (two stocks left after one float iteration)\\n # =================================================================\\n\\n sell_list = [StockOrderWrapper(self.order_2)]\\n sell = sell_list[0]\\n\\n buy_order_3 = StockOrderWrapper(self.order_3)\\n buy_order_4 = StockOrderWrapper(self.order_4)\\n buy_order_7 = StockOrderWrapper(self.order_7)\\n buy_order_8 = StockOrderWrapper(self.order_8)\\n buy_order_11 = StockOrderWrapper(self.order_11)\\n buy_order_12 = StockOrderWrapper(self.order_12)\\n\\n sell.shares_left = 19\\n\\n buy_order_3.shares_left = 4 # 2.4 -> 2 -> 3\\n buy_order_4.shares_left = 4 # 2.4 -> 2 -> 3\\n buy_order_7.shares_left = 4 # 2.4 -> 2 -> 2\\n buy_order_8.shares_left = 2 # 1.2 -> 1 -> 1\\n buy_order_11.shares_left = 8 # 4.8 -> 5 -> 5\\n buy_order_12.shares_left = 8 # 4.8 -> 5 -> 5\\n\\n buy_orders = [buy_order_3, buy_order_4, buy_order_7, buy_order_8, buy_order_11, buy_order_12]\\n\\n result = self.bidding_round_manager.share_distributor(sell_orders=sell_list, buy_orders=buy_orders)\\n\\n result_dict = {}\\n\\n for res in result:\\n result_dict[res.stock_order.order_id] = res\\n\\n try:\\n # noinspection PyUnusedLocal\\n dummy = result[6]\\n raise AssertionError(\\\"IndexError exception expected\\\")\\n except IndexError:\\n pass\\n\\n sell_order_dict_1 = {sell: 1}\\n sell_order_dict_2 = {sell: 2}\\n sell_order_dict_3 = {sell: 3}\\n sell_order_dict_5 = {sell: 5}\\n\\n order_exp_3.transaction_dict = sell_order_dict_3\\n order_exp_4.transaction_dict = sell_order_dict_3\\n order_exp_7.transaction_dict = sell_order_dict_2\\n order_exp_8.transaction_dict = sell_order_dict_1\\n order_exp_11.transaction_dict = sell_order_dict_5\\n order_exp_12.transaction_dict = sell_order_dict_5\\n\\n order_exp_3.shares_left = 1\\n order_exp_4.shares_left = 1\\n order_exp_7.shares_left = 2\\n order_exp_8.shares_left = 1\\n order_exp_11.shares_left = 3\\n order_exp_12.shares_left = 3\\n\\n order_exp_11.order_status = DEFINITIVE\\n order_exp_12.order_status = DEFINITIVE\\n\\n self.is_equal_order_wrapper(result_dict.get(3), order_exp_3)\\n self.is_equal_order_wrapper(result_dict.get(4), order_exp_4)\\n self.is_equal_order_wrapper(result_dict.get(7), order_exp_7)\\n self.is_equal_order_wrapper(result_dict.get(8), order_exp_8)\\n self.is_equal_order_wrapper(result_dict.get(11), order_exp_11)\\n self.is_equal_order_wrapper(result_dict.get(12), order_exp_12)\\n\\n # =================================================================\\n # test: share distribution int sell shares left\\n # =================================================================\\n\\n sell_list = [StockOrderWrapper(self.order_2)]\\n sell = sell_list[0]\\n\\n sell.shares_left = 100\\n\\n buy_order_3 = StockOrderWrapper(self.order_3)\\n buy_order_4 = StockOrderWrapper(self.order_4)\\n buy_order_7 = StockOrderWrapper(self.order_7)\\n buy_order_8 = StockOrderWrapper(self.order_8)\\n buy_order_11 = StockOrderWrapper(self.order_11)\\n buy_order_12 = StockOrderWrapper(self.order_12)\\n\\n buy_order_3.shares_left = 4\\n buy_order_4.shares_left = 7\\n buy_order_7.shares_left = 9\\n buy_order_8.shares_left = 4\\n buy_order_11.shares_left = 8\\n buy_order_12.shares_left = 3\\n\\n buy_orders = [buy_order_3, buy_order_4, buy_order_7, buy_order_8, buy_order_11, buy_order_12]\\n\\n result = self.bidding_round_manager.share_distributor(sell_orders=sell_list, buy_orders=buy_orders)\\n\\n order_exp_2 = StockOrderWrapper(self.order_2)\\n order_exp_2.shares_left = 65\\n\\n self.is_equal_order_wrapper(result[0], order_exp_2)\\n\\n sell_order_dict_3 = {sell: 3}\\n sell_order_dict_4 = {sell: 4}\\n sell_order_dict_7 = {sell: 7}\\n sell_order_dict_8 = {sell: 8}\\n sell_order_dict_9 = {sell: 9}\\n\\n order_exp_3.transaction_dict = sell_order_dict_4\\n order_exp_4.transaction_dict = sell_order_dict_7\\n order_exp_7.transaction_dict = sell_order_dict_9\\n order_exp_8.transaction_dict = sell_order_dict_4\\n order_exp_11.transaction_dict = sell_order_dict_8\\n order_exp_12.transaction_dict = sell_order_dict_3\\n\\n order_exp_3.shares_left = 0\\n order_exp_4.shares_left = 0\\n order_exp_7.shares_left = 0\\n order_exp_8.shares_left = 0\\n order_exp_11.shares_left = 0\\n order_exp_12.shares_left = 0\\n\\n order_exp_3.order_status = PROCESSED\\n order_exp_4.order_status = PROCESSED\\n order_exp_7.order_status = PROCESSED\\n order_exp_8.order_status = PROCESSED\\n order_exp_11.order_status = PROCESSED\\n order_exp_12.order_status = PROCESSED\\n\\n self.is_equal_order_wrapper(buy_order_3, order_exp_3)\\n self.is_equal_order_wrapper(buy_order_4, order_exp_4)\\n self.is_equal_order_wrapper(buy_order_7, order_exp_7)\\n self.is_equal_order_wrapper(buy_order_8, order_exp_8)\\n self.is_equal_order_wrapper(buy_order_11, order_exp_11)\\n self.is_equal_order_wrapper(buy_order_12, order_exp_12)\",\n \"def operate_cipher(self):\",\n \"def decrypt(self, key, value):\\n key = hashlib.sha256(key).digest()[:self.BLOCK_SIZE]\\n iv = value[:16]\\n crypted = value[16:]\\n cipher = AES.new(key,AES.MODE_CBC,iv)\\n return self.pkcs5_unpad(cipher.decrypt(crypted))\",\n \"def decrypt(self, ciphertext):\\n text = []\\n # ciphertext = ciphertext.upper()\\n for char in ciphertext:\\n try:\\n key = math_utils.mult_mod_inv(self.a, len(self.characters)) * (self.characters.index(char) - self.b) % len(self.characters)\\n # If character is not in set for cipher,\\n # directly append it without transformation\\n except ValueError:\\n text.append(char)\\n else:\\n text.append(self.characters[key])\\n return ''.join(text)\",\n \"def can_be_unlocked(self, keycard):\\n pass\",\n \"def get_plaintext_ballots(\\n self, ciphertext_ballots: List[SubmittedBallot], manifest: Manifest\\n ) -> Optional[Dict[BallotId, PlaintextTally]]:\\n\\n if not self.announcement_complete():\\n return None\\n\\n ballots = {}\\n\\n for ciphertext_ballot in ciphertext_ballots:\\n ballot_shares = self._ballot_shares.get(ciphertext_ballot.object_id)\\n if not ballot_shares or not self._ready_to_decrypt(ballot_shares):\\n # Skip ballot if not ready to decrypt\\n continue\\n ballot = decrypt_ballot(\\n ciphertext_ballot,\\n ballot_shares,\\n self._context.crypto_extended_base_hash,\\n manifest,\\n )\\n\\n if ballot:\\n ballots[ballot.object_id] = ballot\\n\\n return ballots\",\n \"def set_values_from_bob(F_in, Y_in, d_in, ciphertexts):\\n global F, d, e_x, e_y, e_xor\\n F, d = F_in, d_in\\n e_y, e_xor = Y_in\\n e_x = decrypt(ciphertexts)\",\n \"def decrypt(cypher, priv_key):\\n\\n if not isinstance(priv_key, key.PrivateKey):\\n raise TypeError(\\\"You must use the private key with decrypt\\\")\\n\\n return gluechops(cypher, priv_key.d, priv_key.n, decrypt_int)\",\n \"async def get_secret(app: Sanic, secret_key: str, passphrase: str) -> str:\\n\\n data = await app.db.secrets.find_one({'secret_key': secret_key})\\n await app.db.secrets.find_one({'secret_key': secret_key})\\n if not data:\\n raise exceptions.InvalidSecretKeyException()\\n\\n key = get_fernet_key(app, passphrase)\\n\\n sign = hmac.digest(key=key, msg=passphrase.encode(), digest='sha512').hex()\\n if sign != data['signature']:\\n raise exceptions.InvalidPassphraseException()\\n\\n await app.db.secrets.delete_one({'secret_key': secret_key})\\n\\n encrypted = data['secret'].encode()\\n cipher = fernet.Fernet(key)\\n if data.get('ttl'):\\n try:\\n secret = cipher.decrypt(encrypted, ttl=data['ttl']).decode()\\n except fernet.InvalidToken:\\n raise exceptions.InvalidSecretKeyException()\\n else:\\n secret = cipher.decrypt(encrypted).decode()\\n\\n return secret\",\n \"def decrypt_slice_secret( observer_pkey_pem, sealed_slice_secret_b64 ):\\n \\n # get the public key\\n try:\\n observer_pubkey_pem = CryptoKey.importKey( observer_pkey_pem ).publickey().exportKey()\\n except Exception, e:\\n logger.exception(e)\\n logger.error(\\\"Failed to derive public key from private key\\\")\\n return None \\n \\n sealed_slice_secret = base64.b64decode( sealed_slice_secret_b64 )\\n \\n # decrypt it \\n rc, slice_secret = c_syndicate.decrypt_data( observer_pubkey_pem, observer_pkey_pem, sealed_slice_secret )\\n \\n if rc != 0:\\n logger.error(\\\"Failed to decrypt '%s', rc = %d\\\" % (sealed_slice_secret_b64, rc))\\n return None\\n \\n return slice_secret\",\n \"def ecb_decrypt(ct_bin_list, keys, rounds):\\n dec_result = \\\"\\\"\\n\\n with multiprocessing.Pool() as p:\\n dec_result = p.starmap(feistel_decrypt, zip(ct_bin_list, keys, repeat(rounds)))\\n return dec_result\",\n \"def decrypt_file(open_name:str, write_name:str, key:str):\\n\\n\\n with open(write_name, \\\"wb\\\") as f:\\n key = key.encode()\\n for (i, part_of_picture) in enumerate(PictureSlices(open_name)):\\n round_key = b\\\"%d%s randominfix %d\\\" % (i, key, i)\\n decrypted_part = xor(part_of_picture, sha512(round_key).digest())\\n f.write(decrypted_part)\",\n \"def decrypt(self, key):\\n super(MACDataUplinkMessage, self).decrypt(key, dir=0)\",\n \"def as_encrypted(self):\\n\\n # Interpret as one word (pid), followed by a bunch of shorts\\n struct_def = \\\"I\\\" + \\\"H\\\" * ((len(self.blob) - 4) / 2)\\n words = list( struct.unpack(struct_def, self.blob) )\\n\\n # Apply the block shuffle and standard Pokémon encryption\\n shuffled = self.shuffle_chunks(words)\\n self.reciprocal_crypt(shuffled)\\n\\n # Stuff back into a string, and done\\n return struct.pack(struct_def, *shuffled)\",\n \"def keyedhash_from_secret(\\n cls,\\n secret,\\n nameAlg=TPM2_ALG.SHA256,\\n objectAttributes=(\\n TPMA_OBJECT.DECRYPT | TPMA_OBJECT.SIGN_ENCRYPT | TPMA_OBJECT.USERWITHAUTH\\n ),\\n scheme=None,\\n seed=None,\\n ):\\n sa, pa = TPMT_SENSITIVE.keyedhash_from_secret(\\n secret, nameAlg, objectAttributes, scheme, seed\\n )\\n priv = TPM2B_SENSITIVE(sensitiveArea=sa)\\n pub = TPM2B_PUBLIC(publicArea=pa)\\n return (priv, pub)\",\n \"def secret() -> None:\\n pass\",\n \"def decryptor(iv = os.urandom(16), key = os.urandom(32), bc = backend):\\n\\tcipher = Cipher(algorithms.AES(key), modes.CBC(iv), backend = bc)\\n\\treturn iv, key, cipher.decryptor()\",\n \"def deal(self):\\n\\n if self.dealer: # Has cards in hand\\n self.dealer.reset()\\n\\n if self.player: # Has cards in hand\\n self.player.reset()\\n\\n dealer_first = self.deck.draw()\\n dealer_second = self.deck.draw()\\n dealer_second.flip()\\n self.dealer.take_card(dealer_first)\\n self.dealer.take_card(dealer_second)\\n\\n player_first = self.deck.draw()\\n player_second = self.deck.draw()\\n player_first.flip()\\n player_second.flip()\\n self.player.take_card(player_first)\\n self.player.take_card(player_second)\\n\\n if self.verbose:\\n print('Player bets:', self.player_bet)\\n for player in (self.player, self.dealer):\\n print(player, 'dealt:')\\n for card in player:\\n if card.face():\\n print(' '*3, str(card)+':', 'face up')\\n else:\\n print(' '*3, str(card)+':', 'face down')\",\n \"def cbc_decrypt(ct_bin_list, keys, rounds):\\n ivector = ct_bin_list.pop(0)\\n dec_result = []\\n msg = ct_bin_list\\n\\n with multiprocessing.Pool() as p:\\n x = p.starmap(feistel_decrypt, zip(msg, keys, repeat(rounds)))\\n\\n dec_result.append(xor_compare(x[0],ivector))\\n if len(x) > 1:\\n for i in range(1, len(x)):\\n dec_result.append(xor_compare(x[i],msg[i-1]))\\n\\n return dec_result\",\n \"def generate_keys(g, o):\\n priv = o.random()\\n pub = priv * g\\n\\n return (priv, pub)\",\n \"def randomize_herbs(self):\\n random.shuffle(self.herbivores)\",\n \"def rsa_decrypt(self, thing):\\n return self.true_private_key.decrypt(\\n thing,\\n cryptography.hazmat.primitives.asymmetric.padding.OAEP(\\n mgf=cryptography.hazmat.primitives.asymmetric.padding.MGF1(\\n algorithm=hashes.SHA256()),\\n algorithm=hashes.SHA256(),\\n label=None\\n )\\n )\",\n \"def assess_hand(self, r):\\n bidIndex = -1\\n while bool(random.getrandbits(1)): # Coin flip\\n bidIndex += 1\\n if bidIndex == -1:\\n self.maxBid = LEGAL_BIDS[0] - 1 # Pass immediately.\\n else:\\n self.maxBid = LEGAL_BIDS[bidIndex]\",\n \"def switcher_secret(self):\\n return self._switcher_secret\",\n \"def passphrase():\\n a = []\\n for i in range(1,6):\\n a.append(password())\\n # join words into phrase\\n p = \\\" \\\".join(a)\\n # split phrase into a list\\n p = list(p)\\n # substitute a random character\\n rc = \\\"\\\"\\\"1~!#$%^2&*()-=3+[]\\\\{}4:;\\\"'<>5?/01236456789\\\"\\\"\\\"\\n p[secrets.choice(range(0,len(p)))] = rc[secrets.choice(range(0,len(rc)))]\\n # put phrase back together\\n p = \\\"\\\".join(p)\\n return p\",\n \"def test_kyc_get_legal_share_holders(self):\\n pass\",\n \"def encrypt(self, message):\\n # message = message.upper().split()\\n # message = \\\"\\\".join(message)\\n message = message.upper()\\n message_list = []\\n for ch in message:\\n message_list.append(self.main_dict[ch][0])\\n\\n # Generate a random key\\n random_otp = [random.choice(self.alphabet_list) for _ in range(len(message))]\\n print(\\\"Your OTP is: \\\" + str(\\\"\\\".join(random_otp)))\\n print(\\\"Use the OTP to unlock the message.\\\")\\n\\n # Convert Random key to integers\\n for i, item in enumerate(random_otp):\\n random_otp[i] = self.main_dict[item][0]\\n\\n # Do the math with Random Key and the message\\n math_list = []\\n for i, item in enumerate(message_list):\\n try:\\n result = message_list[i] + random_otp[i]\\n math_list.append(result)\\n except:\\n print(\\\"The message and OTP does not have the same length\\\")\\n continue\\n\\n # Logic to do mod27\\n for i, item in enumerate(math_list):\\n for key, value in self.main_dict.items():\\n if item > 26:\\n if value[1] == item:\\n math_list[i] = key\\n else:\\n if value[0] == item:\\n math_list[i] = key\\n\\n # Algorithm for 5 block characters\\n padding = input(\\\"Would you like to use block 5 characters? y/n \\\")\\n if padding == \\\"y\\\":\\n math_list = self.salt_with_random(math_list)\\n return \\\" \\\".join(math_list)\\n else:\\n math_list = \\\"\\\".join(math_list)\\n return math_list\",\n \"def encrypt(self, sentence):\\r\\n sentence = list(sentence)\\r\\n encrypted_sentence = []\\r\\n x = list(\\\"abcdefghijklmnopqrstuvwxyz\\\")\\r\\n l = len(x)\\r\\n y = random.sample(x, l)\\r\\n z = list(zip(x, y))\\r\\n z.append((\\\" \\\", \\\" \\\"))\\r\\n for i in sentence:\\r\\n if i.lower() not in x:\\r\\n encrypted_sentence.append(i)\\r\\n continue \\r\\n for a in z:\\r\\n if i.lower() == a[0]:\\r\\n if i.isupper():\\r\\n encrypted_sentence.append(a[1].upper())\\r\\n else:\\r\\n encrypted_sentence.append(a[1])\\r\\n encrypted_sentence = \\\"\\\".join(encrypted_sentence)\\r\\n y = \\\"\\\".join(y)\\r\\n cls()\\r\\n print(\\\"Your one time use pad is: {}\\\".format(y))\\r\\n print(\\\"\\\")\\r\\n return encrypted_sentence\",\n \"def Secure(self,passphrase=None,public_attributes=[]):\\n\\n\\t\\tif passphrase == None:\\n\\t\\t\\treturn self.Dictify()\\n\\t\\telse:\\n\\t\\t\\tself.data = Encrypting.Symmetric.Encrypt(json.dumps(self.Dictify()).encode('utf-8'),passphrase).decode('utf-8')\\n\\t\\t\\t\\n\\t\\t#secure data and dictify\\n\\t\\tmy_secure_dict = self.Dictify()\\n\\n\\t\\t#new obfuscated obj\\n\\t\\tnew_me = {'data':my_secure_dict['data']}\\n\\n\\t\\tfor pub_att in public_attributes:\\n\\t\\t\\tnew_me[pub_att] = my_secure_dict[pub_att]\\n\\n\\t\\treturn new_me\",\n \"def manage_removeSharedSecret(self, REQUEST):\\n self._shared_secret = None\\n response = REQUEST.response\\n response.redirect(\\n '%s/manage_secret?manage_tabs_message=%s' %\\n (self.absolute_url(), 'Shared+secret+removed.')\\n )\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.629344","0.5591807","0.5542672","0.54974806","0.54797286","0.54184014","0.540358","0.53940344","0.5366817","0.5345882","0.5340164","0.522527","0.51924723","0.5167279","0.51538104","0.5105933","0.5103906","0.5103906","0.5098788","0.50672245","0.5058073","0.5024589","0.50155383","0.5010108","0.49981487","0.49917495","0.49795553","0.4972225","0.49666363","0.49659494","0.49564028","0.4949791","0.49392784","0.49359024","0.48987246","0.48870072","0.48654258","0.48510996","0.48467994","0.48464668","0.4835154","0.4825739","0.4824474","0.48230955","0.4817349","0.480885","0.48073792","0.47859755","0.4784464","0.4781502","0.47712153","0.4768848","0.47637516","0.47535905","0.47524202","0.4740882","0.47399747","0.47307175","0.47271606","0.47268134","0.46955305","0.46931317","0.4691702","0.4688453","0.46819815","0.46766734","0.46758378","0.4661908","0.46553084","0.46471936","0.46460003","0.46449944","0.46416214","0.4635985","0.46228677","0.4620332","0.46162298","0.46154493","0.45992702","0.45982656","0.4596868","0.45918974","0.4591328","0.45885843","0.45863023","0.45850664","0.45786744","0.45778698","0.45764455","0.4573698","0.4571244","0.4570406","0.45687234","0.45673734","0.45658025","0.45630905","0.45624024","0.4559558","0.45562893","0.45534766"],"string":"[\n \"0.629344\",\n \"0.5591807\",\n \"0.5542672\",\n \"0.54974806\",\n \"0.54797286\",\n \"0.54184014\",\n \"0.540358\",\n \"0.53940344\",\n \"0.5366817\",\n \"0.5345882\",\n \"0.5340164\",\n \"0.522527\",\n \"0.51924723\",\n \"0.5167279\",\n \"0.51538104\",\n \"0.5105933\",\n \"0.5103906\",\n \"0.5103906\",\n \"0.5098788\",\n \"0.50672245\",\n \"0.5058073\",\n \"0.5024589\",\n \"0.50155383\",\n \"0.5010108\",\n \"0.49981487\",\n \"0.49917495\",\n \"0.49795553\",\n \"0.4972225\",\n \"0.49666363\",\n \"0.49659494\",\n \"0.49564028\",\n \"0.4949791\",\n \"0.49392784\",\n \"0.49359024\",\n \"0.48987246\",\n \"0.48870072\",\n \"0.48654258\",\n \"0.48510996\",\n \"0.48467994\",\n \"0.48464668\",\n \"0.4835154\",\n \"0.4825739\",\n \"0.4824474\",\n \"0.48230955\",\n \"0.4817349\",\n \"0.480885\",\n \"0.48073792\",\n \"0.47859755\",\n \"0.4784464\",\n \"0.4781502\",\n \"0.47712153\",\n \"0.4768848\",\n \"0.47637516\",\n \"0.47535905\",\n \"0.47524202\",\n \"0.4740882\",\n \"0.47399747\",\n \"0.47307175\",\n \"0.47271606\",\n \"0.47268134\",\n \"0.46955305\",\n \"0.46931317\",\n \"0.4691702\",\n \"0.4688453\",\n \"0.46819815\",\n \"0.46766734\",\n \"0.46758378\",\n \"0.4661908\",\n \"0.46553084\",\n \"0.46471936\",\n \"0.46460003\",\n \"0.46449944\",\n \"0.46416214\",\n \"0.4635985\",\n \"0.46228677\",\n \"0.4620332\",\n \"0.46162298\",\n \"0.46154493\",\n \"0.45992702\",\n \"0.45982656\",\n \"0.4596868\",\n \"0.45918974\",\n \"0.4591328\",\n \"0.45885843\",\n \"0.45863023\",\n \"0.45850664\",\n \"0.45786744\",\n \"0.45778698\",\n \"0.45764455\",\n \"0.4573698\",\n \"0.4571244\",\n \"0.4570406\",\n \"0.45687234\",\n \"0.45673734\",\n \"0.45658025\",\n \"0.45630905\",\n \"0.45624024\",\n \"0.4559558\",\n \"0.45562893\",\n \"0.45534766\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6520781"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88591,"cells":{"query":{"kind":"string","value":"Check the value for limits according to topic. If out of limit, notify over telegram"},"document":{"kind":"string","value":"def limitsExsess(topic, value):\n\n if isNotifyTime(topic):\n if \"temperature\" in topic:\n val = float(value)\n if val < MIN_TEMPERATURE or val > MAX_TEMPERATURE:\n notifyTelegram(\"Temperature out of bounds: \"+value+\"degC\")\n return True\n if \"CO\" in topic:\n val = float(value)\n if warmedUp and val > CARBON_MONOXIDE_ADC_THRESH:\n notifyTelegram(\"Carbon Monoxide level above threshold: \"+value)\n return True\n if \"All_Gas\" in topic:\n val = float(value)\n if warmedUp and val > GAS_ALL_ADC_THRESH:\n notifyTelegram(\"Poison gas level above threshold: \"+value)\n return True\n if \"alarm\" in topic:\n val = float(value)\n if int(val) == 1:\n notifyTelegram(\"ALARM in Living room is On!\")\n return True\n if \"MotionHUE\" in topic:\n val = float(value)\n if int(val) == 1:\n notifyTelegram(\"HUE Motion sensor detected movement!\")\n return True\n return False"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def allowedLimit(self, number, msg=None):\n return allowed_limit(number, msg)","async def max(self, ctx, limit: int):\n self.data_check(ctx)\n server = ctx.message.server\n\n self.riceCog2[server.id][\"max\"] = limit\n dataIO.save_json(self.warning_settings,\n self.riceCog2)\n await self.bot.say(\"Warn limit is now: \\n{}\".format(limit))","async def cclimit(self, ctx, limit_amount: int = None):\n if limit_amount is None:\n return await ctx.send_help()\n if limit_amount < 0:\n return await ctx.send(\"You need to use a number larger than 0.\")\n await self.config.limit.set(limit_amount)\n await ctx.send(f\"Chatchart is now limited to {limit_amount} messages.\")","def test_messenger_limit():\n all_messages_resp = requests.get(BASE_URL)\n all_messages = all_messages_resp.json()\n total_message_count = len(all_messages)\n message_limit = total_message_count // 2\n\n query_params = {\"limit\": message_limit}\n limit_resp = requests.get(BASE_URL, params=query_params)\n limited_messages = limit_resp.json()\n assert limit_resp.status_code == 200\n assert len(limited_messages) == message_limit","def on_limit(self, track):\n print \"!!! Limitation notice received: %s\" % str(track)\n return","def on_limit(self, track):\n print ('Got Rate limit Message', str(track))\n return True # Don't kill the stream","def check_limit(limit):\n if limit:\n limit = int(limit)\n if limit > settings.MAX_LISTING_LIMIT or \\\n limit < settings.MIN_LISTING_LIMIT:\n # SuspiciousOperation raises 400 bad request in Django 1.11.\n # https://docs.djangoproject.com/en/1.11/ref/views/#the-400-bad-request-view\n raise SuspiciousOperation()\n return limit\n return settings.DEFAULT_LISTING_LIMIT","def on_limit(self, track):\n log.debug(\"Received limit notice: %d\", track)","def ge(value, limit):\n return value >= limit","def gt(value, limit):\n return value > limit","def test_limit(self) -> None:\n\n channel = self.make_request(\n \"GET\",\n self.url + \"?limit=5\",\n access_token=self.admin_user_tok,\n )\n\n self.assertEqual(200, channel.code, msg=channel.json_body)\n self.assertEqual(channel.json_body[\"total\"], 20)\n self.assertEqual(len(channel.json_body[\"event_reports\"]), 5)\n self.assertEqual(channel.json_body[\"next_token\"], 5)\n self._check_fields(channel.json_body[\"event_reports\"])","def validate_correct_hint(self):\n is_response_hint_valid = False\n while is_response_hint_valid is False:\n hint_value = self.ask_user_input(\"Enter maximum hint threshold\")\n if not hint_value.isdigit():\n print(\"Not a number, please try again\")\n elif 0 <= int(hint_value) <= 81:\n is_response_hint_valid = True\n self.current_response = hint_value\n else:\n print(\"Number is out of the valid range, please try again\")\n return is_response_hint_valid","def test_limits_boundary_values(self):\n\n def check_error_msg(status, output, storagelimit=False):\n import json\n if status == False:\n content = json.loads(output)[\"errors\"]\n if storagelimit:\n actual_error = content[\"dataStorageLimit\"]\n expected_error = '\"dataStorageLimit\" must be an integer between -1 and 100000'\n else:\n actual_error = content[\"dataThrottleLimit\"]\n expected_error = '\"dataThrottleLimit\" must be an integer between -1 and 2147483647'\n self.assertEqual(actual_error, expected_error)\n else:\n self.fail(\"expected to fail but passsed\")\n\n bucket = self.cluster.buckets[0]\n server = random.choice(bucket.servers)\n bucket_helper = BucketHelper(server)\n status, content = bucket_helper.set_throttle_n_storage_limit(bucket.name,\n throttle_limit=-2)\n check_error_msg(status, content)\n status, content = bucket_helper.set_throttle_n_storage_limit(bucket.name,\n throttle_limit=2147483648)\n check_error_msg(status, content)\n\n status, content = bucket_helper.set_throttle_n_storage_limit(bucket.name,\n storage_limit=-2)\n check_error_msg(status, content, True)\n status, content = bucket_helper.set_throttle_n_storage_limit(bucket.name,\n storage_limit=2147483648)\n check_error_msg(status, content, True)\n\n status, content = bucket_helper.set_throttle_n_storage_limit(bucket.name,\n throttle_limit=-2,\n storage_limit=-2)\n check_error_msg(status, content)\n check_error_msg(status, content, True)\n status, content = bucket_helper.set_throttle_n_storage_limit(bucket.name,\n throttle_limit=2147483648,\n storage_limit=2147483648)\n check_error_msg(status, content)\n check_error_msg(status, content, True)","def check_limit(limit_value):\n try:\n limit = int(limit_value)\n except ValueError:\n raise SystemExit('The argument \"limit\" should be a positive number')\n else:\n if limit < 1:\n raise SystemExit('The argument \"limit\" should be greater than 0')\n else:\n return limit","def check(self):\n self.__check_request_limit()","def if_value_higher_3000():\n res = requests.get(\"https://www.nasdaq.com/\")\n SnP500_value = extractor.findall(res.text)[0]\n # You can see this result from the log\n print(SnP500_value)\n if float(SnP500_value) > 3000:\n return 'send_email'\n else:\n return 'do_nothing'","async def rate_limit(self, ctx):\n await ctx.send(\"We have found that the approximate rate limit is 30-40 requests per second. Staying \"\n \"below this should be safe.\")","def check_msg(self, msg, log, topic):\n topics = self.cfg_logs[log]['topics']\n\n if topic in topics.keys():\n for attribute in topics[topic]:\n if not attribute.startswith('_'):\n val = getattr(msg, attribute)\n\n if 'min' in topics[topic][attribute].keys():\n if val < topics[topic][attribute]['min']:\n self.errors.append(\n '{} {} {} {}: violating minimium value {}: {}'.format(log, msg.header.stamp.to_sec(),\n topic, attribute,\n topics[topic][attribute]['min'],\n val))\n if 'max' in topics[topic][attribute].keys():\n if val > topics[topic][attribute]['max']:\n self.errors.append(\n '{} {} {} {}: violating maximum value {}: {}'.format(log, msg.header.stamp.to_sec(),\n topic, attribute,\n topics[topic][attribute]['max'],\n val))\n if 'val' in topics[topic][attribute].keys():\n if val != topics[topic][attribute]['val']:\n self.errors.append(\n '{} {} {} {}: violating value {}: {}'.format(log, msg.header.stamp.to_sec(), topic,\n attribute, topics[topic][attribute]['val'],\n val))","def check_limits(self):\n\n too_hi = False\n too_lo = False\n if is_empty(self.value):\n return None\n\n # Check for limit violations.\n if is_valid(self.limit_lower):\n too_lo = (self.value < self.limit_lower)\n if is_valid(self.limit_upper):\n too_hi = (self.value > self.limit_upper)\n\n # If a limit is violated, return the designated limit action.\n if too_hi or too_lo:\n return self.limit_action\n else:\n return None","def test_limit_and_from(self) -> None:\n\n channel = self.make_request(\n \"GET\",\n self.url + \"?from=5&limit=10\",\n access_token=self.admin_user_tok,\n )\n\n self.assertEqual(200, channel.code, msg=channel.json_body)\n self.assertEqual(channel.json_body[\"total\"], 20)\n self.assertEqual(channel.json_body[\"next_token\"], 15)\n self.assertEqual(len(channel.json_body[\"event_reports\"]), 10)\n self._check_fields(channel.json_body[\"event_reports\"])","def limitValue(self, value, lowerLimit, upperLimit):\n if value > upperLimit:\n return upperLimit\n elif value < lowerLimit:\n return lowerLimit\n else:\n return value","def test_limit_is_negative(self) -> None:\n\n channel = self.make_request(\n \"GET\",\n self.url + \"?limit=-5\",\n access_token=self.admin_user_tok,\n )\n\n self.assertEqual(400, channel.code, msg=channel.json_body)\n self.assertEqual(Codes.INVALID_PARAM, channel.json_body[\"errcode\"])","def limit(self, limit):\n raise NotImplementedError(\"This should have been implemented.\")","def checkLimit(device, checkStatus):\n d = device.read(1)\n if d:\n print(d)\n status = d[0]\n\n printStatus(status)\n if (checkStatus & status):\n return False\n return True","def check_constrained(self, limit=None):\n\n # Set the 'well-constrained' limit at 10% (arbitrary) if not provided.\n limit = (Decimal(0.1) if not limit else Decimal(limit))\n\n if is_empty(self.value) or is_empty(self.uncertainty):\n return False\n elif self.uncertainty > (Decimal(self.value) * Decimal(limit)):\n self.well_constrained = False\n else:\n self.well_constrained = True","def _is_limited(request, rate, rl):\n def inner(*args, **kwargs):\n is_limited = rl.is_limited(*args, **kwargs)\n\n if is_limited:\n messages.error(\n request,\n _(\"Too many submissions, wait %(time)s.\") % {\n 'time': rate.split('/')[1]})\n\n return is_limited\n\n return inner","def set_throttle_callback(self, msg):\n\t\t\n\t\tthrottle_val = msg.data\n\n\t\tprint(\"Setting throttle to {}\".format(throttle_val))\n\t\tprint(\"Publishing single value, {}, to /driver/throttle topic\".format(self.throttle_low))\n\n\t\tif throttle_val < self.throttle_high or throttle_val > self.throttle_low:\n\t\t\tprint(\"!!! Must provide a throttle value between {} (full throttle) and {} (low throttle) !!!\".format(self.throttle_high, self.throttle_low))\n\t\t\treturn\n\n\t\tif not throttle_val:\n\t\t\tthrottle_val = self.throttle_home\n\n\t\tself.throttle_pub.publish(throttle_val)","def check_engine_limits(current_rqmt, task):\n current_rqmt['time'] = min(168, current_rqmt.get('time', 1))\n return current_rqmt","def test_exceeded_limit(self):\n msg=self.sample_data(\"error_exceeded_limit.xml\")\n error = ErrorParser().process_all(msg)\n assert isinstance(error, PatronLoanLimitReached)\n eq_(u'Patron cannot loan more than 12 documents', error.message)","def _limit(value, min_value, max_value):\n\n if value < min_value:\n return min_value\n if value > max_value:\n return max_value\n return value","def test_api_requests_limited(self):\n\n did_reach_rate_limit = False\n for _ in range(110):\n response = self.send_get('Participant', expected_status=None)\n if response.status_code == TooManyRequests.code:\n did_reach_rate_limit = True\n break\n\n self.assertTrue(did_reach_rate_limit)","def _validate_clear_args(limit):\n min_limit = 1\n max_limit = 20\n default_error = f\"[Limit] The `limit` argument must be a number between {min_limit} and {max_limit}\"\n try:\n limit = int(limit)\n except (ValueError, TypeError):\n return default_error\n if not (min_limit <= limit <= max_limit):\n return default_error\n return None","def _safe_limit_check(self):\n if self.rem == 40:\n self.time_start = time.time()\n elif time.time() - self.time_start >= 11:\n self.rem = 40\n self.time_start = time.time()\n elif self.rem <= 0:\n t = 11 - (time.time() - self.time_start)\n\n if t <= 0:\n self.rem = 40\n self.time_start = time.time()\n else:\n if self.policy == Limit.Sleep:\n time.sleep(t)\n elif self.policy == Limit.Ignore:\n return False\n\n self.rem -= 1\n return True","def _check_amount_with_priority(self):\n\t\tfor slc in self:\n\t\t\tif slc.max_amount and self.search([('priority', '<', slc.priority), ('max_amount', '>=', slc.max_amount)]):\n\t\t\t\traise Warning(_(\"There are below slides [Priority less than %s] with bigger amount from [%s]\"\n\t\t\t\t \" which against the logic!!!\\n You can increase amount or handel priority\")\n\t\t\t\t % (slc.priority, slc.max_amount))","def validate(c_name, val):\n n = 80\n threshold = 4\n while (threshold >= 0):\n if ((len(channels[c_name]) > n) and (val <= threshold)):\n return True\n else:\n n -= 20\n threshold -= 1\n\n return False","def _check_items_limit(self):\n if self.items_limit and self.items_limit == self.get_metadata('items_count'):\n raise ItemsLimitReached('Finishing job after items_limit reached:'\n ' {} items written.'.format(self.get_metadata('items_count')))","def chkLimits(name, value, Min, Max, unit = 'V', Hex = False):\n\n #global Log\n if not Min < value < Max:\n if Hex:\n line = \"%s:0x%X OUT OF LIMITS (0x%X, 0x%X). Test Failed !\" %(name, value, Min, Max)\n else:\n line = \"%s:%F %s OUT OF LIMITS (%F, %f). Test Failed !\" %(name, value, unit, Min, Max)\n Log.logError(line)\n Err.bumpError()\n return False\n if Hex:\n Log.logText(' '+'%s:0x%X expected range from:0x%X To: 0x%X. Test PASS !'% (name, value, Min, Max))\n else:\n Log.logText(' '+'%s:%F %s expected range From:%F %s To: %F %s. Test PASS !'% (name, value, unit, Min,unit, Max, unit))\n return True","def check_min_value(self, tracked_price):\n if tracked_price < self.min_value and self.warning_calls <= 2:\n print(f'Warning! Price dropeed under {self.min_value} pln {tracked_price}')\n self.make_phone_call()\n self.warning_calls += 1\n elif tracked_price < self.min_value and self.warning_calls == 3:\n self.send_a_message(\n f'This is a warning message. Price of EUR/PLN dropped under critical value!'\n f' {self.min_value} pln')\n print(f'Called 3 times! Price dropeed under {self.min_value} pln {tracked_price}')\n self.warning_calls = 0\n else:\n print(f\"Current price for Euro in PLN is {tracked_price}\")","def pwm_limit(self, value):\n self._write(MX_PWM_LIMIT, value)","def check_limit(redis_client):\n if redis_client.llen('query_counter') >= API_RATE_LIMIT:\n left_val = redis_client.lpop('query_counter')\n parsed_left_val = float(left_val.decode('utf-8'))\n current_api_window = (datetime.utcnow() - timedelta(minutes=API_WINDOW_PERIOD)).timestamp()\n if parsed_left_val > current_api_window:\n redis_client.lpush('query_counter', left_val)\n return False\n return True","def le(value, limit):\n return value <= limit","def limit():\n bwc = BandwidthConfigurator()\n bwc.limit()","def _check(self):\n try:\n num = int(self.ids.res_lim.text)\n # reset negative numbers to zero\n if num <= 0:\n self.ids.res_lim.text = str(0)\n except ValueError:\n self.ids.res_lim.text = str(self.limit)\n\n return int(self.ids.res_lim.text)","def _send_maximum(self):\n content = {'maximum': self.maximum.isoformat()}\n self.send_action('set_maximum', content)","def _thresholdAlarm(self, project_usage, proj_name, old_used_space_perc):\n\n message = \"\"\n threshold_soft = 95\n threshold_hard = 100\n if (proj_name in self.conf.mirrored_projects):\n threshold_soft = 95*2\n threshold_hard = 100*2\n if ((project_usage['used_space_perc'] > threshold_soft) and \n (project_usage['used_space_perc'] > old_used_space_perc)):\n message = \"project \" + proj_name + \" is reaching its quota limit \" \\\n + \"(used space > 95%): \" + str(project_usage['used_space'])\\\n + \" \" + self.conf.storage_space_unity\n if (project_usage['used_space_perc'] >= threshold_hard):\n message = \"project \" + proj_name + \" reached its quota limit \" \\\n + \"(used space > 100%): \" + str(project_usage['used_space'])\\\n + \" \" + self.conf.storage_space_unity\n if (len(message) > 0):\n mailsnd = MailSender()\n mailsnd.send(message, self.conf.notification_sender, \n self.conf.notification_receiver)\n logger.debug(\"sent alert for quota over limit related to project: \"\n + proj_name)","def test_device_readings_max(self):\n request = self.client().get('/devices/{}/readings/max/'.format(self.device_uuid))\n\n self.assertEqual(request.json.get('value', None), 100)","def charge_limit(self, limit=None):\n if limit is None:\n done, data = self._request('GH')\n if done:\n return int(data[0])\n else:\n if self._request('SH', str(int(limit)))[0]:\n return limit\n\n raise EvseError","def subscriptions_limit(self) -> pulumi.Output[Optional[int]]:\n return pulumi.get(self, \"subscriptions_limit\")","def _get_limit(self, req):\n try:\n limit = int(req.params.get('limit', CONF.limit_param_default))\n except ValueError:\n raise exc.HTTPBadRequest(_(\"limit param must be an integer\"))\n\n if limit < 0:\n raise exc.HTTPBadRequest(_(\"limit param must be positive\"))\n\n return min(CONF.api_limit_max, limit)","def limit(self, limit):\n\n # Return between 1 and 250 results, defaults to 10\n return max(1, min(250, int(limit) if limit else 10))","def send_it(self, func, limit, *args, **kwargs):\n counter = 0\n if counter > limit:\n return False\n counter += 1\n try:\n result = func(*args, **kwargs)\n time.sleep(1.1)\n return result\n except gspread.exceptions.APIError as e:\n if (e.response.json())['error']['code'] == 429:\n time.sleep(501)\n self.send_it(func, limit, *args, **kwargs)\n else:\n print(e)\n return False\n except Exception as e:\n print(e)\n return False","def constrain(inputVal, lower_limit, upper_limit):\n \n if (inputVal < lower_limit):\n return lower_limit\n elif (inputVal > upper_limit):\n return upper_limit\n else:\n return inputVal","def check_rate_limit(self):\n # Already received 429 from server\n if self.rate_limit_sleep:\n msg = f\"请求过于频繁，已被BitMEX限制，请等待{self.rate_limit_sleep}秒后再试\"\n self.gateway.write_log(msg)\n return False\n # Just local request limit is reached\n elif not self.rate_limit_remaining:\n msg = \"请求频率太高，有触发BitMEX流控的风险，请稍候再试\"\n self.gateway.write_log(msg)\n return False\n else:\n self.rate_limit_remaining -= 1\n return True","def check_value(self, name, min_int, max_int):\n while True:\n numb = input(f\"-- {name} : Entrez une valeur comprise \"\n f\"entre {min_int} et {max_int} : \")\n try:\n check = int(numb)\n if check == 99 or min_int <= check <= max_int:\n break\n except ValueError:\n pass\n return check","def get_limit(self):\r\n\r\n limit = self.request_data.get('limit', self.limit)\r\n if limit is None:\r\n limit = getattr(settings, 'API_LIMIT_PER_PAGE', 20)\r\n\r\n try:\r\n limit = int(limit)\r\n except ValueError:\r\n raise BadRequest(\r\n \"Invalid limit '%s' provided. Please provide a positive integer.\" % limit)\r\n\r\n if limit < 0:\r\n raise BadRequest(\"Invalid limit '%s' provided. Please provide a positive integer >= 0.\" % limit)\r\n\r\n if self.max_limit and (not limit or limit > self.max_limit):\r\n # If it's more than the max, we're only going to return the max.\r\n # This is to prevent excessive DB (or other) load.\r\n return self.max_limit\r\n\r\n return limit","def test_limit(self):\n\t\tfor lim in [1, '234', -100, '-200']:\n\t\t\tself.filter.set_limit(lim)\n\t\t\tself.assertEqual(int(lim), self.filter.get_limit(), \"Limit mismatch: %s!=%s\" % (lim, self.filter.get_limit()))\n\t\tself.filter.set_limit('test')\n\t\tself.assertEqual('test', self.filter.get_limit(), \"String set failed for Filter limit.\")","def _determine_limit(self, limit):\n\n # Note: +1 is allowed here because it allows\n # the user to fetch one beyond to see if they\n # are at the end of the list\n if not limit:\n res = conf.api_configuration.max_returned_num + 1\n else:\n res = min(conf.api_configuration.max_returned_num + 1, limit)\n\n return res","def get_high_limit(self):\n debug(\"Getting high limit...\")\n value = self.get_value(7)/10.\n if not isnan(value): info(\"High limit %r C\" % value)\n else: warn(\"High limit unreadable (old firmware?)\")\n return value","def test_get_remain_limit(self):\n finder = FinderInsidePro(self.test_key)\n limit = finder.get_remain_limit()\n assert isinstance(limit, int)\n assert limit > 0","def on_over_limit(limit):\n return (jsonify({'data': 'You hit the rate limit', 'error': '429'}), 429)","def limit(self) -> pulumi.Input[float]:\n return pulumi.get(self, \"limit\")","def set_limit(self, errors):\n self.limit = errors","def updateMessages(self, parameters):\n l = 0;\n \n if parameters[1].value == True:\n #parameters[4].setErrorMessage(\"Random percentage value required!\")\n l = l + 1;\n if parameters[2].value == '' or parameters[2].value is None:\n parameters[2].setErrorMessage(\"Thinning value required!\")\n \n if parameters[3].value == True:\n l = l + 1; \n #parameters[4].setErrorMessage(\"Random percentage value required!\")\n if parameters[4].value == '' or parameters[4].value is None:\n parameters[4].setErrorMessage(\"Random percentage value required!\")\n elif parameters[4].value > 100 or parameters[4].value < 1:\n parameters[4].setErrorMessage(\"Value has to between 1-100 %!\")\n \n if (l < 1):\n parameters[1].setErrorMessage(\"You have to select either one!\")\n parameters[3].setErrorMessage(\"You have to select either one!\")\n \n return","async def threshold(self, ctx, threshold: int):\n if threshold > 0:\n self.bot.db.execute(\"UPDATE starboards SET threshold = ? WHERE channel_id = ?\", (threshold, ctx.channel.id))\n await ctx.say(\"star.threshold\", threshold)\n await self.set_topic(ctx.channel.id)\n else:\n await ctx.say(\"star.unsigned\", threshold)","def __motorLimitHit(self, channelValue, channelName):\n if channelValue:\n if channelName.endswith('low_lim_hit'):\n self.limit = self.limit | LOWLIMIT\n self.__changeMotorState(ONLIMIT)\n else:\n self.limit = self.limit | HIGHLIMIT\n self.__changeMotorState(ONLIMIT)","def limit_reached(service, ip):\n\n timestamp = format_time(get_time())\n coordinates = get_coordinates(ip)\n\n values = defaultdict(lambda: PLACEHOLDER_STRING,\n {'event_type': 'limit_reached',\n '@timestamp': timestamp,\n 'service': service,\n 'ip': ip,\n 'honeypotID': ID})\n \n if coordinates:\n values['coordinates'] = '{:.4f},{:.4f}'.format(coordinates[0], coordinates[1])\n\n if Config.use_broker:\n BrokerEndpoint.BrokerEndpoint.sendLogs(json.dumps(values))\n\n if coordinates:\n values['lat'] = '{:.4f}'.format(coordinates[0])\n values['lon'] = '{:.4f}'.format(coordinates[1])\n\n message = '{@timestamp} - [LIMIT REACHED] - {service}, {ip}, Lat: {lat}, Lon: {lon}'.format_map(values)\n _log_alert(message)","def check_value(self, pos):\n if self.limits is not None:\n low, high = self.limits\n if low != high and not (low <= pos <= high):\n raise ValueError(\"{} outside of user-specified limits\" \"\".format(pos))\n else:\n self.setpoint.check_value(pos)","def check(self):\n logging.info(\"rate limit remaining %s\" % self.remaining)\n while self.remaining <= 1:\n now = time.time()\n logging.debug(\"rate limit < 1, now=%s and reset=%s\", now,\n self.reset)\n if self.reset and now < self.reset:\n # padded with 5 seconds just to be on the safe side\n secs = self.reset - now + 5\n logging.info(\"sleeping %s seconds for rate limiting\" % secs)\n time.sleep(secs)\n else:\n # sleep a second before checking again for new rate limit\n time.sleep(1)\n # get the latest limit\n self.ping()\n self.remaining -= 1","def test_recv_nolimit(self):\n self.driver.send_nolimit(self.msg_long)\n msg_flag, msg_recv = self.instance.recv_nolimit(self.timeout)\n assert(msg_flag)\n nt.assert_equal(msg_recv, self.msg_long)","def check_rate_limit(session, provided_iocs):\n rate_limit = session.rate_limit_status()[\"resources\"][\"search\"][\"/search/tweets\"]\n\n if rate_limit[\"remaining\"] == 0:\n reset_time = rate_limit[\"reset\"]\n rate_limit[\"reset\"] = time.strftime('%Y-%m-%d %H:%M:%S',\n time.localtime(reset_time))\n return rate_limit\n\n if len(provided_iocs) > rate_limit[\"remaining\"]:\n rate_limit = {\"Search term limit\": rate_limit[\"remaining\"],\n \"Total Search Terms Provided\": len(provided_iocs)}\n return rate_limit\n return","def get_limit(self):\n return self.limit","def bounds_check(session):\n\n max_ = session.field.opts.max\n min_ = session.field.opts.min\n\n if max_ is not None and len(session.data) > max_:\n raise session.field.invalid(error_type='out_of_bounds')\n if min_ is not None and len(session.data) < min_:\n raise session.field.invalid(error_type='out_of_bounds')\n\n return session.data","def temperature_limit(self, value):\n self._write(MX_TEMPERATURE_LIMIT, value)","def _check_amount_with_priority(self):\n\t\tfor line in self:\n\t\t\tif line.tax_slide_id and (line.amount_from > line.tax_slide_id.max_amount\n\t\t\t or line.amount_to > line.tax_slide_id.max_amount):\n\t\t\t\traise Warning(_(\"Line Amount couldn't exceed te slide max amount [%s]\" % line.tax_slide_id.max_amount))","def count_changed_handler(count: int):\n # Chat should have at least two active members\n global can_speak\n can_speak = count >= 2\n if not can_speak:\n safe_print(print_mutex, \"Too few members. Waiting another member...\")","def __limit_value(self, value, v_range):\n if np.isnan(value):\n print('Warning: trying to limit nan value in range {0}'.format(v_range))\n return value\n\n return np.min([v_range[1], np.max([value, v_range[0]])])","def LimitedInput(message, limit, isNumber=False):\n keepAsking = True\n while keepAsking:\n answer = input(message)\n if len(answer) > limit:\n print(\"The input must be\", limit, \"characters or less.\")\n else:\n keepAsking = False\n if isNumber is True and CheckNumber(answer) is False:\n print(\"The input must be a number.\")\n keepAsking = True\n return answer","def test_default_limit(self):\n telem = self.create_logs(self.user1, num=200)\n\n response = self.client.get(telemetry_url)\n self.assertEqual(200, response.status_code)\n\n data = json.loads(response.content)\n\n self.assertEqual(100, len(data))","async def _msgvote_threshold(self, ctx, threshold: int):\n\n if threshold < 0:\n await self.bot.say(\"Invalid threshold. Must be a positive \"\n \"integer, or 0 to disable.\")\n elif threshold == 0:\n self.settings[\"threshold\"] = threshold\n dataIO.save_json(self.settings_path, self.settings)\n await self.bot.say(\"Message deletion disabled.\")\n else:\n self.settings[\"threshold\"] = threshold\n dataIO.save_json(self.settings_path, self.settings)\n await self.bot.say(\"Messages will be deleted if [downvotes - \"\n \"upvotes] reaches {}.\".format(threshold))","def _check_fit_limits(self,t,em,limits):\n\n if limits[0] < t[0] or limits[1] > t[-1]:\n self.logger.warning(\"Fit limits outside of temperature range. %.2f < %.2f MK or %.2f > %.2f MK. Returning None.\"%(limits[0]/1e+6,t[0]/1e+6,limits[1]/1e+6,t[-1]/1e+6))\n return None\n\n emnew = np.interp(np.array([limits[0],limits[1]]),t,em)\n if emnew[0] < self.em_cutoff or emnew[1] < self.em_cutoff:\n self.logger.warning(\"Fit limits below EM threshold, logEM_thresh=%.2f. logEM0,logEM1 = (%.2f,%.2f). Returning None.\"%(np.log10(self.em_cutoff),np.log10(emnew[0]),np.log10(emnew[1])))\n return None\n\n return limits","def set_Limit(self, value):\n super(DescribeEvaluationsInputSet, self)._set_input('Limit', value)","def test_send_nolimit(self):\n msg_flag = self.instance.send_nolimit(self.msg_long)\n assert(msg_flag)\n msg_flag, msg_recv = self.driver.recv_nolimit(self.timeout)\n assert(msg_flag)\n nt.assert_equal(msg_recv, self.msg_long)","def limited(self) -> pulumi.Output[bool]:\n return pulumi.get(self, \"limited\")","def set_limit_max():\n limit_max = request.params.get(\"limit_max\", 0, type=float)\n output = request.params.get(\"output\", 1, type=int)\n retval = RP_LIB.rp_LimitMax(output, ctypes.c_float(limit_max))\n if retval != 0:\n LOG.error(\"Failed to set maximum output voltage. Error code: %s\", ERROR_CODES[retval])","def _get_limit(self, req):\n try:\n limit = int(req.str_params.get('limit', MAX_ITEM_LIMIT))\n except ValueError:\n raise exc.HTTPBadRequest(\"limit param must be an integer\")\n\n if limit < 0:\n raise exc.HTTPBadRequest(\"limit param must be positive\")\n\n return min(MAX_ITEM_LIMIT, limit)","def limited(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"limited\")","def _single_value_max(data, threshold):\r\n amin = np.min(data)\r\n amax = np.max(data)\r\n limit = amax - (amax - amin) * threshold\r\n return data > limit","def calculate(self, limit):\r\n pass","def on_limit(self, track):\n print(track)","def _checked_maximum(self):\n self._block_signals()\n if self._maximum_length_checkbox.isChecked():\n # Maximum length enabled\n self._level_gen.maximum_length = MAXIMUM_LENGTH\n else:\n # Maximum length disabled\n self._level_gen.maximum_length = None\n self._refresh_view()\n self._unblock_signals()","def _check_rate_limit(self, res, amt, balance, meta, raven_vars, dispatch, t):\n # TODO distinct up/down rates\n # check limiting rate for resource flow in/out, if any\n if self._rate:\n request = {res: None}\n inputs = {'request': request,\n 'meta': meta,\n 'raven_vars': raven_vars,\n 'dispatch': dispatch,\n 't': t}\n max_rate = self._rate.evaluate(inputs, target_var=res)[0][res]\n delta = np.sign(amt) * min(max_rate, abs(amt))\n print('max_rate in _check_rate_limit',max_rate, 'delta (min of maxrate and abs(amt)',delta)\n return {res: delta}, meta\n return {res: amt}, meta","def _validate_value(self, value):\n if self.limits[0] <= value <= self.limits[1]:\n return True\n else:\n return False","def _validate_value(self, value):\n return (self.maximum_value is None) or (value <= self.maximum_value)","def test_maxttl_possible_values(self):\n # default\n rest = RestConnection(self.master)\n default_maxttl = rest.get_bucket_maxTTL()\n if default_maxttl != 0:\n self.fail(\"FAIL: default maxTTL if left unset must be 0 but is {0}\".format(default_maxttl))\n self.log.info(\"Verified: default maxTTL if left unset is {0}\".format(default_maxttl))\n\n # max value\n try:\n self._update_bucket_maxTTL(maxttl=2147483648)\n except Exception as e:\n self.log.info(\"Expected exception : {0}\".format(e))\n try:\n self._update_bucket_maxTTL(maxttl=2147483647)\n except Exception as e:\n self.fail(\"Unable to set maxTTL=2147483647, the max permitted value\")\n else:\n self.log.info(\"Verified: Max value permitted is 2147483647\")\n else:\n self.fail(\"Able to set maxTTL greater than 2147483647\")\n\n # min value\n try:\n self._update_bucket_maxTTL(maxttl=0)\n except Exception as e:\n self.fail(\"Unable to set maxTTL=0, the min permitted value\")\n else:\n self.log.info(\"Verified: Min value permitted is 0\")\n\n # negative value\n try:\n self._update_bucket_maxTTL(maxttl=-60)\n except Exception as e:\n self.log.info(\"Verified: negative values not permitted, exception : {0}\".format(e))\n else:\n self.fail(\"FAIL: Able to set a negative maxTTL\")\n\n # date/string\n try:\n self._update_bucket_maxTTL(maxttl=\"12/23/2016\")\n except Exception as e:\n self.log.info(\"Verified: string not permitted, exception : {0}\".format(e))\n else:\n self.fail(\"FAIL: Able to set a date string maxTTL\")","def maximum():\n if len(a_variable.get()) > MAX_CHARACTERS:\n messagebox.showwarning(title=\"Max Characters Exceeded!\",\n message=\"Please enter no more than 25\\n\"\n \"characters, thanks.\")\n clear_box() # Clears the entry field","def test_set_maximum(self):\n self.server_widget.maximum = 1000\n assert self.client_widget.maximum == self.server_widget.maximum","def rate_limit_check():\n\n data = api.rate_limit_status()\n\n user_timeline_remaining = data['resources']['statuses'] \\\n ['/statuses/user_timeline'] \\\n ['remaining']\n\n followers_list_remaining = data['resources']['followers'] \\\n ['/followers/list']['remaining']\n\n rate_limit_remaining = data['resources']['application'] \\\n ['/application/rate_limit_status']['remaining']\n\n verify_credentials_remaining = data['resources']['account'] \\\n ['/account/verify_credentials'] \\\n ['remaining']\n\n user_timeline_reset = data['resources']['statuses'] \\\n ['/statuses/user_timeline'] \\\n ['reset']\n\n followers_list_reset = data['resources']['followers'] \\\n ['/followers/list']['reset']\n\n rate_limit_reset = data['resources']['application'] \\\n ['/application/rate_limit_status']['reset']\n\n verify_credentials_reset = data['resources']['account'] \\\n ['/account/verify_credentials'] \\\n ['reset']\n\n return {'utrem': user_timeline_remaining,\n 'ftrem': followers_list_remaining,\n 'rlrem': rate_limit_remaining,\n 'vcrem': verify_credentials_remaining,\n 'utres': user_timeline_reset,\n 'ftres': followers_list_reset,\n 'rlres': rate_limit_reset,\n 'vcres': verify_credentials_reset}","def check_sample(temp, alert_settings):\n\n # If no range settings, we default to true\n ret = Alert.ALERT_TYPE_TEMP_GOOD;\n \n # Check against upper limit only if one exists\n if alert_settings[HIGH_LIMIT] and temp > Decimal(alert_settings[HIGH_LIMIT]):\n ret = Alert.ALERT_TYPE_TEMP_HIGH\n # Check against lower limit only if one exists\n elif alert_settings[LOW_LIMIT] and temp < Decimal(alert_settings[LOW_LIMIT]):\n ret = Alert.ALERT_TYPE_TEMP_LOW \n #logger.debug(\" Temp %s between %s and %s: %s\" % (temp, alert_settings[LOW_LIMIT], alert_settings[HIGH_LIMIT], ret))\n\n return ret","def limit(self, limit):\n self._evaluated = False\n self._limit = limit\n return self","async def is_max(self, member, guild: discord.Guild) -> bool:\n if hasattr(member, 'id'):\n cursor = await self.bot.db.execute(\n 'SELECT warns FROM users WHERE user_id = ? AND guild_id = ?', (member.id, guild.id)\n )\n results = await cursor.fetchone()\n if results[0] == 3:\n return True\n return False"],"string":"[\n \"def allowedLimit(self, number, msg=None):\\n return allowed_limit(number, msg)\",\n \"async def max(self, ctx, limit: int):\\n self.data_check(ctx)\\n server = ctx.message.server\\n\\n self.riceCog2[server.id][\\\"max\\\"] = limit\\n dataIO.save_json(self.warning_settings,\\n self.riceCog2)\\n await self.bot.say(\\\"Warn limit is now: \\\\n{}\\\".format(limit))\",\n \"async def cclimit(self, ctx, limit_amount: int = None):\\n if limit_amount is None:\\n return await ctx.send_help()\\n if limit_amount < 0:\\n return await ctx.send(\\\"You need to use a number larger than 0.\\\")\\n await self.config.limit.set(limit_amount)\\n await ctx.send(f\\\"Chatchart is now limited to {limit_amount} messages.\\\")\",\n \"def test_messenger_limit():\\n all_messages_resp = requests.get(BASE_URL)\\n all_messages = all_messages_resp.json()\\n total_message_count = len(all_messages)\\n message_limit = total_message_count // 2\\n\\n query_params = {\\\"limit\\\": message_limit}\\n limit_resp = requests.get(BASE_URL, params=query_params)\\n limited_messages = limit_resp.json()\\n assert limit_resp.status_code == 200\\n assert len(limited_messages) == message_limit\",\n \"def on_limit(self, track):\\n print \\\"!!! Limitation notice received: %s\\\" % str(track)\\n return\",\n \"def on_limit(self, track):\\n print ('Got Rate limit Message', str(track))\\n return True # Don't kill the stream\",\n \"def check_limit(limit):\\n if limit:\\n limit = int(limit)\\n if limit > settings.MAX_LISTING_LIMIT or \\\\\\n limit < settings.MIN_LISTING_LIMIT:\\n # SuspiciousOperation raises 400 bad request in Django 1.11.\\n # https://docs.djangoproject.com/en/1.11/ref/views/#the-400-bad-request-view\\n raise SuspiciousOperation()\\n return limit\\n return settings.DEFAULT_LISTING_LIMIT\",\n \"def on_limit(self, track):\\n log.debug(\\\"Received limit notice: %d\\\", track)\",\n \"def ge(value, limit):\\n return value >= limit\",\n \"def gt(value, limit):\\n return value > limit\",\n \"def test_limit(self) -> None:\\n\\n channel = self.make_request(\\n \\\"GET\\\",\\n self.url + \\\"?limit=5\\\",\\n access_token=self.admin_user_tok,\\n )\\n\\n self.assertEqual(200, channel.code, msg=channel.json_body)\\n self.assertEqual(channel.json_body[\\\"total\\\"], 20)\\n self.assertEqual(len(channel.json_body[\\\"event_reports\\\"]), 5)\\n self.assertEqual(channel.json_body[\\\"next_token\\\"], 5)\\n self._check_fields(channel.json_body[\\\"event_reports\\\"])\",\n \"def validate_correct_hint(self):\\n is_response_hint_valid = False\\n while is_response_hint_valid is False:\\n hint_value = self.ask_user_input(\\\"Enter maximum hint threshold\\\")\\n if not hint_value.isdigit():\\n print(\\\"Not a number, please try again\\\")\\n elif 0 <= int(hint_value) <= 81:\\n is_response_hint_valid = True\\n self.current_response = hint_value\\n else:\\n print(\\\"Number is out of the valid range, please try again\\\")\\n return is_response_hint_valid\",\n \"def test_limits_boundary_values(self):\\n\\n def check_error_msg(status, output, storagelimit=False):\\n import json\\n if status == False:\\n content = json.loads(output)[\\\"errors\\\"]\\n if storagelimit:\\n actual_error = content[\\\"dataStorageLimit\\\"]\\n expected_error = '\\\"dataStorageLimit\\\" must be an integer between -1 and 100000'\\n else:\\n actual_error = content[\\\"dataThrottleLimit\\\"]\\n expected_error = '\\\"dataThrottleLimit\\\" must be an integer between -1 and 2147483647'\\n self.assertEqual(actual_error, expected_error)\\n else:\\n self.fail(\\\"expected to fail but passsed\\\")\\n\\n bucket = self.cluster.buckets[0]\\n server = random.choice(bucket.servers)\\n bucket_helper = BucketHelper(server)\\n status, content = bucket_helper.set_throttle_n_storage_limit(bucket.name,\\n throttle_limit=-2)\\n check_error_msg(status, content)\\n status, content = bucket_helper.set_throttle_n_storage_limit(bucket.name,\\n throttle_limit=2147483648)\\n check_error_msg(status, content)\\n\\n status, content = bucket_helper.set_throttle_n_storage_limit(bucket.name,\\n storage_limit=-2)\\n check_error_msg(status, content, True)\\n status, content = bucket_helper.set_throttle_n_storage_limit(bucket.name,\\n storage_limit=2147483648)\\n check_error_msg(status, content, True)\\n\\n status, content = bucket_helper.set_throttle_n_storage_limit(bucket.name,\\n throttle_limit=-2,\\n storage_limit=-2)\\n check_error_msg(status, content)\\n check_error_msg(status, content, True)\\n status, content = bucket_helper.set_throttle_n_storage_limit(bucket.name,\\n throttle_limit=2147483648,\\n storage_limit=2147483648)\\n check_error_msg(status, content)\\n check_error_msg(status, content, True)\",\n \"def check_limit(limit_value):\\n try:\\n limit = int(limit_value)\\n except ValueError:\\n raise SystemExit('The argument \\\"limit\\\" should be a positive number')\\n else:\\n if limit < 1:\\n raise SystemExit('The argument \\\"limit\\\" should be greater than 0')\\n else:\\n return limit\",\n \"def check(self):\\n self.__check_request_limit()\",\n \"def if_value_higher_3000():\\n res = requests.get(\\\"https://www.nasdaq.com/\\\")\\n SnP500_value = extractor.findall(res.text)[0]\\n # You can see this result from the log\\n print(SnP500_value)\\n if float(SnP500_value) > 3000:\\n return 'send_email'\\n else:\\n return 'do_nothing'\",\n \"async def rate_limit(self, ctx):\\n await ctx.send(\\\"We have found that the approximate rate limit is 30-40 requests per second. Staying \\\"\\n \\\"below this should be safe.\\\")\",\n \"def check_msg(self, msg, log, topic):\\n topics = self.cfg_logs[log]['topics']\\n\\n if topic in topics.keys():\\n for attribute in topics[topic]:\\n if not attribute.startswith('_'):\\n val = getattr(msg, attribute)\\n\\n if 'min' in topics[topic][attribute].keys():\\n if val < topics[topic][attribute]['min']:\\n self.errors.append(\\n '{} {} {} {}: violating minimium value {}: {}'.format(log, msg.header.stamp.to_sec(),\\n topic, attribute,\\n topics[topic][attribute]['min'],\\n val))\\n if 'max' in topics[topic][attribute].keys():\\n if val > topics[topic][attribute]['max']:\\n self.errors.append(\\n '{} {} {} {}: violating maximum value {}: {}'.format(log, msg.header.stamp.to_sec(),\\n topic, attribute,\\n topics[topic][attribute]['max'],\\n val))\\n if 'val' in topics[topic][attribute].keys():\\n if val != topics[topic][attribute]['val']:\\n self.errors.append(\\n '{} {} {} {}: violating value {}: {}'.format(log, msg.header.stamp.to_sec(), topic,\\n attribute, topics[topic][attribute]['val'],\\n val))\",\n \"def check_limits(self):\\n\\n too_hi = False\\n too_lo = False\\n if is_empty(self.value):\\n return None\\n\\n # Check for limit violations.\\n if is_valid(self.limit_lower):\\n too_lo = (self.value < self.limit_lower)\\n if is_valid(self.limit_upper):\\n too_hi = (self.value > self.limit_upper)\\n\\n # If a limit is violated, return the designated limit action.\\n if too_hi or too_lo:\\n return self.limit_action\\n else:\\n return None\",\n \"def test_limit_and_from(self) -> None:\\n\\n channel = self.make_request(\\n \\\"GET\\\",\\n self.url + \\\"?from=5&limit=10\\\",\\n access_token=self.admin_user_tok,\\n )\\n\\n self.assertEqual(200, channel.code, msg=channel.json_body)\\n self.assertEqual(channel.json_body[\\\"total\\\"], 20)\\n self.assertEqual(channel.json_body[\\\"next_token\\\"], 15)\\n self.assertEqual(len(channel.json_body[\\\"event_reports\\\"]), 10)\\n self._check_fields(channel.json_body[\\\"event_reports\\\"])\",\n \"def limitValue(self, value, lowerLimit, upperLimit):\\n if value > upperLimit:\\n return upperLimit\\n elif value < lowerLimit:\\n return lowerLimit\\n else:\\n return value\",\n \"def test_limit_is_negative(self) -> None:\\n\\n channel = self.make_request(\\n \\\"GET\\\",\\n self.url + \\\"?limit=-5\\\",\\n access_token=self.admin_user_tok,\\n )\\n\\n self.assertEqual(400, channel.code, msg=channel.json_body)\\n self.assertEqual(Codes.INVALID_PARAM, channel.json_body[\\\"errcode\\\"])\",\n \"def limit(self, limit):\\n raise NotImplementedError(\\\"This should have been implemented.\\\")\",\n \"def checkLimit(device, checkStatus):\\n d = device.read(1)\\n if d:\\n print(d)\\n status = d[0]\\n\\n printStatus(status)\\n if (checkStatus & status):\\n return False\\n return True\",\n \"def check_constrained(self, limit=None):\\n\\n # Set the 'well-constrained' limit at 10% (arbitrary) if not provided.\\n limit = (Decimal(0.1) if not limit else Decimal(limit))\\n\\n if is_empty(self.value) or is_empty(self.uncertainty):\\n return False\\n elif self.uncertainty > (Decimal(self.value) * Decimal(limit)):\\n self.well_constrained = False\\n else:\\n self.well_constrained = True\",\n \"def _is_limited(request, rate, rl):\\n def inner(*args, **kwargs):\\n is_limited = rl.is_limited(*args, **kwargs)\\n\\n if is_limited:\\n messages.error(\\n request,\\n _(\\\"Too many submissions, wait %(time)s.\\\") % {\\n 'time': rate.split('/')[1]})\\n\\n return is_limited\\n\\n return inner\",\n \"def set_throttle_callback(self, msg):\\n\\t\\t\\n\\t\\tthrottle_val = msg.data\\n\\n\\t\\tprint(\\\"Setting throttle to {}\\\".format(throttle_val))\\n\\t\\tprint(\\\"Publishing single value, {}, to /driver/throttle topic\\\".format(self.throttle_low))\\n\\n\\t\\tif throttle_val < self.throttle_high or throttle_val > self.throttle_low:\\n\\t\\t\\tprint(\\\"!!! Must provide a throttle value between {} (full throttle) and {} (low throttle) !!!\\\".format(self.throttle_high, self.throttle_low))\\n\\t\\t\\treturn\\n\\n\\t\\tif not throttle_val:\\n\\t\\t\\tthrottle_val = self.throttle_home\\n\\n\\t\\tself.throttle_pub.publish(throttle_val)\",\n \"def check_engine_limits(current_rqmt, task):\\n current_rqmt['time'] = min(168, current_rqmt.get('time', 1))\\n return current_rqmt\",\n \"def test_exceeded_limit(self):\\n msg=self.sample_data(\\\"error_exceeded_limit.xml\\\")\\n error = ErrorParser().process_all(msg)\\n assert isinstance(error, PatronLoanLimitReached)\\n eq_(u'Patron cannot loan more than 12 documents', error.message)\",\n \"def _limit(value, min_value, max_value):\\n\\n if value < min_value:\\n return min_value\\n if value > max_value:\\n return max_value\\n return value\",\n \"def test_api_requests_limited(self):\\n\\n did_reach_rate_limit = False\\n for _ in range(110):\\n response = self.send_get('Participant', expected_status=None)\\n if response.status_code == TooManyRequests.code:\\n did_reach_rate_limit = True\\n break\\n\\n self.assertTrue(did_reach_rate_limit)\",\n \"def _validate_clear_args(limit):\\n min_limit = 1\\n max_limit = 20\\n default_error = f\\\"[Limit] The `limit` argument must be a number between {min_limit} and {max_limit}\\\"\\n try:\\n limit = int(limit)\\n except (ValueError, TypeError):\\n return default_error\\n if not (min_limit <= limit <= max_limit):\\n return default_error\\n return None\",\n \"def _safe_limit_check(self):\\n if self.rem == 40:\\n self.time_start = time.time()\\n elif time.time() - self.time_start >= 11:\\n self.rem = 40\\n self.time_start = time.time()\\n elif self.rem <= 0:\\n t = 11 - (time.time() - self.time_start)\\n\\n if t <= 0:\\n self.rem = 40\\n self.time_start = time.time()\\n else:\\n if self.policy == Limit.Sleep:\\n time.sleep(t)\\n elif self.policy == Limit.Ignore:\\n return False\\n\\n self.rem -= 1\\n return True\",\n \"def _check_amount_with_priority(self):\\n\\t\\tfor slc in self:\\n\\t\\t\\tif slc.max_amount and self.search([('priority', '<', slc.priority), ('max_amount', '>=', slc.max_amount)]):\\n\\t\\t\\t\\traise Warning(_(\\\"There are below slides [Priority less than %s] with bigger amount from [%s]\\\"\\n\\t\\t\\t\\t \\\" which against the logic!!!\\\\n You can increase amount or handel priority\\\")\\n\\t\\t\\t\\t % (slc.priority, slc.max_amount))\",\n \"def validate(c_name, val):\\n n = 80\\n threshold = 4\\n while (threshold >= 0):\\n if ((len(channels[c_name]) > n) and (val <= threshold)):\\n return True\\n else:\\n n -= 20\\n threshold -= 1\\n\\n return False\",\n \"def _check_items_limit(self):\\n if self.items_limit and self.items_limit == self.get_metadata('items_count'):\\n raise ItemsLimitReached('Finishing job after items_limit reached:'\\n ' {} items written.'.format(self.get_metadata('items_count')))\",\n \"def chkLimits(name, value, Min, Max, unit = 'V', Hex = False):\\n\\n #global Log\\n if not Min < value < Max:\\n if Hex:\\n line = \\\"%s:0x%X OUT OF LIMITS (0x%X, 0x%X). Test Failed !\\\" %(name, value, Min, Max)\\n else:\\n line = \\\"%s:%F %s OUT OF LIMITS (%F, %f). Test Failed !\\\" %(name, value, unit, Min, Max)\\n Log.logError(line)\\n Err.bumpError()\\n return False\\n if Hex:\\n Log.logText(' '+'%s:0x%X expected range from:0x%X To: 0x%X. Test PASS !'% (name, value, Min, Max))\\n else:\\n Log.logText(' '+'%s:%F %s expected range From:%F %s To: %F %s. Test PASS !'% (name, value, unit, Min,unit, Max, unit))\\n return True\",\n \"def check_min_value(self, tracked_price):\\n if tracked_price < self.min_value and self.warning_calls <= 2:\\n print(f'Warning! Price dropeed under {self.min_value} pln {tracked_price}')\\n self.make_phone_call()\\n self.warning_calls += 1\\n elif tracked_price < self.min_value and self.warning_calls == 3:\\n self.send_a_message(\\n f'This is a warning message. Price of EUR/PLN dropped under critical value!'\\n f' {self.min_value} pln')\\n print(f'Called 3 times! Price dropeed under {self.min_value} pln {tracked_price}')\\n self.warning_calls = 0\\n else:\\n print(f\\\"Current price for Euro in PLN is {tracked_price}\\\")\",\n \"def pwm_limit(self, value):\\n self._write(MX_PWM_LIMIT, value)\",\n \"def check_limit(redis_client):\\n if redis_client.llen('query_counter') >= API_RATE_LIMIT:\\n left_val = redis_client.lpop('query_counter')\\n parsed_left_val = float(left_val.decode('utf-8'))\\n current_api_window = (datetime.utcnow() - timedelta(minutes=API_WINDOW_PERIOD)).timestamp()\\n if parsed_left_val > current_api_window:\\n redis_client.lpush('query_counter', left_val)\\n return False\\n return True\",\n \"def le(value, limit):\\n return value <= limit\",\n \"def limit():\\n bwc = BandwidthConfigurator()\\n bwc.limit()\",\n \"def _check(self):\\n try:\\n num = int(self.ids.res_lim.text)\\n # reset negative numbers to zero\\n if num <= 0:\\n self.ids.res_lim.text = str(0)\\n except ValueError:\\n self.ids.res_lim.text = str(self.limit)\\n\\n return int(self.ids.res_lim.text)\",\n \"def _send_maximum(self):\\n content = {'maximum': self.maximum.isoformat()}\\n self.send_action('set_maximum', content)\",\n \"def _thresholdAlarm(self, project_usage, proj_name, old_used_space_perc):\\n\\n message = \\\"\\\"\\n threshold_soft = 95\\n threshold_hard = 100\\n if (proj_name in self.conf.mirrored_projects):\\n threshold_soft = 95*2\\n threshold_hard = 100*2\\n if ((project_usage['used_space_perc'] > threshold_soft) and \\n (project_usage['used_space_perc'] > old_used_space_perc)):\\n message = \\\"project \\\" + proj_name + \\\" is reaching its quota limit \\\" \\\\\\n + \\\"(used space > 95%): \\\" + str(project_usage['used_space'])\\\\\\n + \\\" \\\" + self.conf.storage_space_unity\\n if (project_usage['used_space_perc'] >= threshold_hard):\\n message = \\\"project \\\" + proj_name + \\\" reached its quota limit \\\" \\\\\\n + \\\"(used space > 100%): \\\" + str(project_usage['used_space'])\\\\\\n + \\\" \\\" + self.conf.storage_space_unity\\n if (len(message) > 0):\\n mailsnd = MailSender()\\n mailsnd.send(message, self.conf.notification_sender, \\n self.conf.notification_receiver)\\n logger.debug(\\\"sent alert for quota over limit related to project: \\\"\\n + proj_name)\",\n \"def test_device_readings_max(self):\\n request = self.client().get('/devices/{}/readings/max/'.format(self.device_uuid))\\n\\n self.assertEqual(request.json.get('value', None), 100)\",\n \"def charge_limit(self, limit=None):\\n if limit is None:\\n done, data = self._request('GH')\\n if done:\\n return int(data[0])\\n else:\\n if self._request('SH', str(int(limit)))[0]:\\n return limit\\n\\n raise EvseError\",\n \"def subscriptions_limit(self) -> pulumi.Output[Optional[int]]:\\n return pulumi.get(self, \\\"subscriptions_limit\\\")\",\n \"def _get_limit(self, req):\\n try:\\n limit = int(req.params.get('limit', CONF.limit_param_default))\\n except ValueError:\\n raise exc.HTTPBadRequest(_(\\\"limit param must be an integer\\\"))\\n\\n if limit < 0:\\n raise exc.HTTPBadRequest(_(\\\"limit param must be positive\\\"))\\n\\n return min(CONF.api_limit_max, limit)\",\n \"def limit(self, limit):\\n\\n # Return between 1 and 250 results, defaults to 10\\n return max(1, min(250, int(limit) if limit else 10))\",\n \"def send_it(self, func, limit, *args, **kwargs):\\n counter = 0\\n if counter > limit:\\n return False\\n counter += 1\\n try:\\n result = func(*args, **kwargs)\\n time.sleep(1.1)\\n return result\\n except gspread.exceptions.APIError as e:\\n if (e.response.json())['error']['code'] == 429:\\n time.sleep(501)\\n self.send_it(func, limit, *args, **kwargs)\\n else:\\n print(e)\\n return False\\n except Exception as e:\\n print(e)\\n return False\",\n \"def constrain(inputVal, lower_limit, upper_limit):\\n \\n if (inputVal < lower_limit):\\n return lower_limit\\n elif (inputVal > upper_limit):\\n return upper_limit\\n else:\\n return inputVal\",\n \"def check_rate_limit(self):\\n # Already received 429 from server\\n if self.rate_limit_sleep:\\n msg = f\\\"请求过于频繁，已被BitMEX限制，请等待{self.rate_limit_sleep}秒后再试\\\"\\n self.gateway.write_log(msg)\\n return False\\n # Just local request limit is reached\\n elif not self.rate_limit_remaining:\\n msg = \\\"请求频率太高，有触发BitMEX流控的风险，请稍候再试\\\"\\n self.gateway.write_log(msg)\\n return False\\n else:\\n self.rate_limit_remaining -= 1\\n return True\",\n \"def check_value(self, name, min_int, max_int):\\n while True:\\n numb = input(f\\\"-- {name} : Entrez une valeur comprise \\\"\\n f\\\"entre {min_int} et {max_int} : \\\")\\n try:\\n check = int(numb)\\n if check == 99 or min_int <= check <= max_int:\\n break\\n except ValueError:\\n pass\\n return check\",\n \"def get_limit(self):\\r\\n\\r\\n limit = self.request_data.get('limit', self.limit)\\r\\n if limit is None:\\r\\n limit = getattr(settings, 'API_LIMIT_PER_PAGE', 20)\\r\\n\\r\\n try:\\r\\n limit = int(limit)\\r\\n except ValueError:\\r\\n raise BadRequest(\\r\\n \\\"Invalid limit '%s' provided. Please provide a positive integer.\\\" % limit)\\r\\n\\r\\n if limit < 0:\\r\\n raise BadRequest(\\\"Invalid limit '%s' provided. Please provide a positive integer >= 0.\\\" % limit)\\r\\n\\r\\n if self.max_limit and (not limit or limit > self.max_limit):\\r\\n # If it's more than the max, we're only going to return the max.\\r\\n # This is to prevent excessive DB (or other) load.\\r\\n return self.max_limit\\r\\n\\r\\n return limit\",\n \"def test_limit(self):\\n\\t\\tfor lim in [1, '234', -100, '-200']:\\n\\t\\t\\tself.filter.set_limit(lim)\\n\\t\\t\\tself.assertEqual(int(lim), self.filter.get_limit(), \\\"Limit mismatch: %s!=%s\\\" % (lim, self.filter.get_limit()))\\n\\t\\tself.filter.set_limit('test')\\n\\t\\tself.assertEqual('test', self.filter.get_limit(), \\\"String set failed for Filter limit.\\\")\",\n \"def _determine_limit(self, limit):\\n\\n # Note: +1 is allowed here because it allows\\n # the user to fetch one beyond to see if they\\n # are at the end of the list\\n if not limit:\\n res = conf.api_configuration.max_returned_num + 1\\n else:\\n res = min(conf.api_configuration.max_returned_num + 1, limit)\\n\\n return res\",\n \"def get_high_limit(self):\\n debug(\\\"Getting high limit...\\\")\\n value = self.get_value(7)/10.\\n if not isnan(value): info(\\\"High limit %r C\\\" % value)\\n else: warn(\\\"High limit unreadable (old firmware?)\\\")\\n return value\",\n \"def test_get_remain_limit(self):\\n finder = FinderInsidePro(self.test_key)\\n limit = finder.get_remain_limit()\\n assert isinstance(limit, int)\\n assert limit > 0\",\n \"def on_over_limit(limit):\\n return (jsonify({'data': 'You hit the rate limit', 'error': '429'}), 429)\",\n \"def limit(self) -> pulumi.Input[float]:\\n return pulumi.get(self, \\\"limit\\\")\",\n \"def set_limit(self, errors):\\n self.limit = errors\",\n \"def updateMessages(self, parameters):\\n l = 0;\\n \\n if parameters[1].value == True:\\n #parameters[4].setErrorMessage(\\\"Random percentage value required!\\\")\\n l = l + 1;\\n if parameters[2].value == '' or parameters[2].value is None:\\n parameters[2].setErrorMessage(\\\"Thinning value required!\\\")\\n \\n if parameters[3].value == True:\\n l = l + 1; \\n #parameters[4].setErrorMessage(\\\"Random percentage value required!\\\")\\n if parameters[4].value == '' or parameters[4].value is None:\\n parameters[4].setErrorMessage(\\\"Random percentage value required!\\\")\\n elif parameters[4].value > 100 or parameters[4].value < 1:\\n parameters[4].setErrorMessage(\\\"Value has to between 1-100 %!\\\")\\n \\n if (l < 1):\\n parameters[1].setErrorMessage(\\\"You have to select either one!\\\")\\n parameters[3].setErrorMessage(\\\"You have to select either one!\\\")\\n \\n return\",\n \"async def threshold(self, ctx, threshold: int):\\n if threshold > 0:\\n self.bot.db.execute(\\\"UPDATE starboards SET threshold = ? WHERE channel_id = ?\\\", (threshold, ctx.channel.id))\\n await ctx.say(\\\"star.threshold\\\", threshold)\\n await self.set_topic(ctx.channel.id)\\n else:\\n await ctx.say(\\\"star.unsigned\\\", threshold)\",\n \"def __motorLimitHit(self, channelValue, channelName):\\n if channelValue:\\n if channelName.endswith('low_lim_hit'):\\n self.limit = self.limit | LOWLIMIT\\n self.__changeMotorState(ONLIMIT)\\n else:\\n self.limit = self.limit | HIGHLIMIT\\n self.__changeMotorState(ONLIMIT)\",\n \"def limit_reached(service, ip):\\n\\n timestamp = format_time(get_time())\\n coordinates = get_coordinates(ip)\\n\\n values = defaultdict(lambda: PLACEHOLDER_STRING,\\n {'event_type': 'limit_reached',\\n '@timestamp': timestamp,\\n 'service': service,\\n 'ip': ip,\\n 'honeypotID': ID})\\n \\n if coordinates:\\n values['coordinates'] = '{:.4f},{:.4f}'.format(coordinates[0], coordinates[1])\\n\\n if Config.use_broker:\\n BrokerEndpoint.BrokerEndpoint.sendLogs(json.dumps(values))\\n\\n if coordinates:\\n values['lat'] = '{:.4f}'.format(coordinates[0])\\n values['lon'] = '{:.4f}'.format(coordinates[1])\\n\\n message = '{@timestamp} - [LIMIT REACHED] - {service}, {ip}, Lat: {lat}, Lon: {lon}'.format_map(values)\\n _log_alert(message)\",\n \"def check_value(self, pos):\\n if self.limits is not None:\\n low, high = self.limits\\n if low != high and not (low <= pos <= high):\\n raise ValueError(\\\"{} outside of user-specified limits\\\" \\\"\\\".format(pos))\\n else:\\n self.setpoint.check_value(pos)\",\n \"def check(self):\\n logging.info(\\\"rate limit remaining %s\\\" % self.remaining)\\n while self.remaining <= 1:\\n now = time.time()\\n logging.debug(\\\"rate limit < 1, now=%s and reset=%s\\\", now,\\n self.reset)\\n if self.reset and now < self.reset:\\n # padded with 5 seconds just to be on the safe side\\n secs = self.reset - now + 5\\n logging.info(\\\"sleeping %s seconds for rate limiting\\\" % secs)\\n time.sleep(secs)\\n else:\\n # sleep a second before checking again for new rate limit\\n time.sleep(1)\\n # get the latest limit\\n self.ping()\\n self.remaining -= 1\",\n \"def test_recv_nolimit(self):\\n self.driver.send_nolimit(self.msg_long)\\n msg_flag, msg_recv = self.instance.recv_nolimit(self.timeout)\\n assert(msg_flag)\\n nt.assert_equal(msg_recv, self.msg_long)\",\n \"def check_rate_limit(session, provided_iocs):\\n rate_limit = session.rate_limit_status()[\\\"resources\\\"][\\\"search\\\"][\\\"/search/tweets\\\"]\\n\\n if rate_limit[\\\"remaining\\\"] == 0:\\n reset_time = rate_limit[\\\"reset\\\"]\\n rate_limit[\\\"reset\\\"] = time.strftime('%Y-%m-%d %H:%M:%S',\\n time.localtime(reset_time))\\n return rate_limit\\n\\n if len(provided_iocs) > rate_limit[\\\"remaining\\\"]:\\n rate_limit = {\\\"Search term limit\\\": rate_limit[\\\"remaining\\\"],\\n \\\"Total Search Terms Provided\\\": len(provided_iocs)}\\n return rate_limit\\n return\",\n \"def get_limit(self):\\n return self.limit\",\n \"def bounds_check(session):\\n\\n max_ = session.field.opts.max\\n min_ = session.field.opts.min\\n\\n if max_ is not None and len(session.data) > max_:\\n raise session.field.invalid(error_type='out_of_bounds')\\n if min_ is not None and len(session.data) < min_:\\n raise session.field.invalid(error_type='out_of_bounds')\\n\\n return session.data\",\n \"def temperature_limit(self, value):\\n self._write(MX_TEMPERATURE_LIMIT, value)\",\n \"def _check_amount_with_priority(self):\\n\\t\\tfor line in self:\\n\\t\\t\\tif line.tax_slide_id and (line.amount_from > line.tax_slide_id.max_amount\\n\\t\\t\\t or line.amount_to > line.tax_slide_id.max_amount):\\n\\t\\t\\t\\traise Warning(_(\\\"Line Amount couldn't exceed te slide max amount [%s]\\\" % line.tax_slide_id.max_amount))\",\n \"def count_changed_handler(count: int):\\n # Chat should have at least two active members\\n global can_speak\\n can_speak = count >= 2\\n if not can_speak:\\n safe_print(print_mutex, \\\"Too few members. Waiting another member...\\\")\",\n \"def __limit_value(self, value, v_range):\\n if np.isnan(value):\\n print('Warning: trying to limit nan value in range {0}'.format(v_range))\\n return value\\n\\n return np.min([v_range[1], np.max([value, v_range[0]])])\",\n \"def LimitedInput(message, limit, isNumber=False):\\n keepAsking = True\\n while keepAsking:\\n answer = input(message)\\n if len(answer) > limit:\\n print(\\\"The input must be\\\", limit, \\\"characters or less.\\\")\\n else:\\n keepAsking = False\\n if isNumber is True and CheckNumber(answer) is False:\\n print(\\\"The input must be a number.\\\")\\n keepAsking = True\\n return answer\",\n \"def test_default_limit(self):\\n telem = self.create_logs(self.user1, num=200)\\n\\n response = self.client.get(telemetry_url)\\n self.assertEqual(200, response.status_code)\\n\\n data = json.loads(response.content)\\n\\n self.assertEqual(100, len(data))\",\n \"async def _msgvote_threshold(self, ctx, threshold: int):\\n\\n if threshold < 0:\\n await self.bot.say(\\\"Invalid threshold. Must be a positive \\\"\\n \\\"integer, or 0 to disable.\\\")\\n elif threshold == 0:\\n self.settings[\\\"threshold\\\"] = threshold\\n dataIO.save_json(self.settings_path, self.settings)\\n await self.bot.say(\\\"Message deletion disabled.\\\")\\n else:\\n self.settings[\\\"threshold\\\"] = threshold\\n dataIO.save_json(self.settings_path, self.settings)\\n await self.bot.say(\\\"Messages will be deleted if [downvotes - \\\"\\n \\\"upvotes] reaches {}.\\\".format(threshold))\",\n \"def _check_fit_limits(self,t,em,limits):\\n\\n if limits[0] < t[0] or limits[1] > t[-1]:\\n self.logger.warning(\\\"Fit limits outside of temperature range. %.2f < %.2f MK or %.2f > %.2f MK. Returning None.\\\"%(limits[0]/1e+6,t[0]/1e+6,limits[1]/1e+6,t[-1]/1e+6))\\n return None\\n\\n emnew = np.interp(np.array([limits[0],limits[1]]),t,em)\\n if emnew[0] < self.em_cutoff or emnew[1] < self.em_cutoff:\\n self.logger.warning(\\\"Fit limits below EM threshold, logEM_thresh=%.2f. logEM0,logEM1 = (%.2f,%.2f). Returning None.\\\"%(np.log10(self.em_cutoff),np.log10(emnew[0]),np.log10(emnew[1])))\\n return None\\n\\n return limits\",\n \"def set_Limit(self, value):\\n super(DescribeEvaluationsInputSet, self)._set_input('Limit', value)\",\n \"def test_send_nolimit(self):\\n msg_flag = self.instance.send_nolimit(self.msg_long)\\n assert(msg_flag)\\n msg_flag, msg_recv = self.driver.recv_nolimit(self.timeout)\\n assert(msg_flag)\\n nt.assert_equal(msg_recv, self.msg_long)\",\n \"def limited(self) -> pulumi.Output[bool]:\\n return pulumi.get(self, \\\"limited\\\")\",\n \"def set_limit_max():\\n limit_max = request.params.get(\\\"limit_max\\\", 0, type=float)\\n output = request.params.get(\\\"output\\\", 1, type=int)\\n retval = RP_LIB.rp_LimitMax(output, ctypes.c_float(limit_max))\\n if retval != 0:\\n LOG.error(\\\"Failed to set maximum output voltage. Error code: %s\\\", ERROR_CODES[retval])\",\n \"def _get_limit(self, req):\\n try:\\n limit = int(req.str_params.get('limit', MAX_ITEM_LIMIT))\\n except ValueError:\\n raise exc.HTTPBadRequest(\\\"limit param must be an integer\\\")\\n\\n if limit < 0:\\n raise exc.HTTPBadRequest(\\\"limit param must be positive\\\")\\n\\n return min(MAX_ITEM_LIMIT, limit)\",\n \"def limited(self) -> Optional[pulumi.Input[bool]]:\\n return pulumi.get(self, \\\"limited\\\")\",\n \"def _single_value_max(data, threshold):\\r\\n amin = np.min(data)\\r\\n amax = np.max(data)\\r\\n limit = amax - (amax - amin) * threshold\\r\\n return data > limit\",\n \"def calculate(self, limit):\\r\\n pass\",\n \"def on_limit(self, track):\\n print(track)\",\n \"def _checked_maximum(self):\\n self._block_signals()\\n if self._maximum_length_checkbox.isChecked():\\n # Maximum length enabled\\n self._level_gen.maximum_length = MAXIMUM_LENGTH\\n else:\\n # Maximum length disabled\\n self._level_gen.maximum_length = None\\n self._refresh_view()\\n self._unblock_signals()\",\n \"def _check_rate_limit(self, res, amt, balance, meta, raven_vars, dispatch, t):\\n # TODO distinct up/down rates\\n # check limiting rate for resource flow in/out, if any\\n if self._rate:\\n request = {res: None}\\n inputs = {'request': request,\\n 'meta': meta,\\n 'raven_vars': raven_vars,\\n 'dispatch': dispatch,\\n 't': t}\\n max_rate = self._rate.evaluate(inputs, target_var=res)[0][res]\\n delta = np.sign(amt) * min(max_rate, abs(amt))\\n print('max_rate in _check_rate_limit',max_rate, 'delta (min of maxrate and abs(amt)',delta)\\n return {res: delta}, meta\\n return {res: amt}, meta\",\n \"def _validate_value(self, value):\\n if self.limits[0] <= value <= self.limits[1]:\\n return True\\n else:\\n return False\",\n \"def _validate_value(self, value):\\n return (self.maximum_value is None) or (value <= self.maximum_value)\",\n \"def test_maxttl_possible_values(self):\\n # default\\n rest = RestConnection(self.master)\\n default_maxttl = rest.get_bucket_maxTTL()\\n if default_maxttl != 0:\\n self.fail(\\\"FAIL: default maxTTL if left unset must be 0 but is {0}\\\".format(default_maxttl))\\n self.log.info(\\\"Verified: default maxTTL if left unset is {0}\\\".format(default_maxttl))\\n\\n # max value\\n try:\\n self._update_bucket_maxTTL(maxttl=2147483648)\\n except Exception as e:\\n self.log.info(\\\"Expected exception : {0}\\\".format(e))\\n try:\\n self._update_bucket_maxTTL(maxttl=2147483647)\\n except Exception as e:\\n self.fail(\\\"Unable to set maxTTL=2147483647, the max permitted value\\\")\\n else:\\n self.log.info(\\\"Verified: Max value permitted is 2147483647\\\")\\n else:\\n self.fail(\\\"Able to set maxTTL greater than 2147483647\\\")\\n\\n # min value\\n try:\\n self._update_bucket_maxTTL(maxttl=0)\\n except Exception as e:\\n self.fail(\\\"Unable to set maxTTL=0, the min permitted value\\\")\\n else:\\n self.log.info(\\\"Verified: Min value permitted is 0\\\")\\n\\n # negative value\\n try:\\n self._update_bucket_maxTTL(maxttl=-60)\\n except Exception as e:\\n self.log.info(\\\"Verified: negative values not permitted, exception : {0}\\\".format(e))\\n else:\\n self.fail(\\\"FAIL: Able to set a negative maxTTL\\\")\\n\\n # date/string\\n try:\\n self._update_bucket_maxTTL(maxttl=\\\"12/23/2016\\\")\\n except Exception as e:\\n self.log.info(\\\"Verified: string not permitted, exception : {0}\\\".format(e))\\n else:\\n self.fail(\\\"FAIL: Able to set a date string maxTTL\\\")\",\n \"def maximum():\\n if len(a_variable.get()) > MAX_CHARACTERS:\\n messagebox.showwarning(title=\\\"Max Characters Exceeded!\\\",\\n message=\\\"Please enter no more than 25\\\\n\\\"\\n \\\"characters, thanks.\\\")\\n clear_box() # Clears the entry field\",\n \"def test_set_maximum(self):\\n self.server_widget.maximum = 1000\\n assert self.client_widget.maximum == self.server_widget.maximum\",\n \"def rate_limit_check():\\n\\n data = api.rate_limit_status()\\n\\n user_timeline_remaining = data['resources']['statuses'] \\\\\\n ['/statuses/user_timeline'] \\\\\\n ['remaining']\\n\\n followers_list_remaining = data['resources']['followers'] \\\\\\n ['/followers/list']['remaining']\\n\\n rate_limit_remaining = data['resources']['application'] \\\\\\n ['/application/rate_limit_status']['remaining']\\n\\n verify_credentials_remaining = data['resources']['account'] \\\\\\n ['/account/verify_credentials'] \\\\\\n ['remaining']\\n\\n user_timeline_reset = data['resources']['statuses'] \\\\\\n ['/statuses/user_timeline'] \\\\\\n ['reset']\\n\\n followers_list_reset = data['resources']['followers'] \\\\\\n ['/followers/list']['reset']\\n\\n rate_limit_reset = data['resources']['application'] \\\\\\n ['/application/rate_limit_status']['reset']\\n\\n verify_credentials_reset = data['resources']['account'] \\\\\\n ['/account/verify_credentials'] \\\\\\n ['reset']\\n\\n return {'utrem': user_timeline_remaining,\\n 'ftrem': followers_list_remaining,\\n 'rlrem': rate_limit_remaining,\\n 'vcrem': verify_credentials_remaining,\\n 'utres': user_timeline_reset,\\n 'ftres': followers_list_reset,\\n 'rlres': rate_limit_reset,\\n 'vcres': verify_credentials_reset}\",\n \"def check_sample(temp, alert_settings):\\n\\n # If no range settings, we default to true\\n ret = Alert.ALERT_TYPE_TEMP_GOOD;\\n \\n # Check against upper limit only if one exists\\n if alert_settings[HIGH_LIMIT] and temp > Decimal(alert_settings[HIGH_LIMIT]):\\n ret = Alert.ALERT_TYPE_TEMP_HIGH\\n # Check against lower limit only if one exists\\n elif alert_settings[LOW_LIMIT] and temp < Decimal(alert_settings[LOW_LIMIT]):\\n ret = Alert.ALERT_TYPE_TEMP_LOW \\n #logger.debug(\\\" Temp %s between %s and %s: %s\\\" % (temp, alert_settings[LOW_LIMIT], alert_settings[HIGH_LIMIT], ret))\\n\\n return ret\",\n \"def limit(self, limit):\\n self._evaluated = False\\n self._limit = limit\\n return self\",\n \"async def is_max(self, member, guild: discord.Guild) -> bool:\\n if hasattr(member, 'id'):\\n cursor = await self.bot.db.execute(\\n 'SELECT warns FROM users WHERE user_id = ? AND guild_id = ?', (member.id, guild.id)\\n )\\n results = await cursor.fetchone()\\n if results[0] == 3:\\n return True\\n return False\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6885966","0.6692245","0.66228366","0.6284632","0.627446","0.6245816","0.62092686","0.61613834","0.613513","0.609418","0.6056963","0.6042189","0.60258657","0.5984116","0.59698874","0.59312063","0.59092206","0.5906563","0.58542055","0.5850616","0.5809356","0.579957","0.5784076","0.57744926","0.57643306","0.57595515","0.575187","0.5748009","0.57465714","0.57419276","0.5713134","0.57118696","0.57016546","0.5695353","0.56905687","0.5682232","0.567557","0.5675286","0.5660535","0.5654064","0.56452006","0.563603","0.5626845","0.56190723","0.5597789","0.5594812","0.55931795","0.557884","0.55638456","0.55636525","0.55563897","0.5551577","0.5549967","0.5543087","0.55370647","0.551717","0.551461","0.55087155","0.54946136","0.54904735","0.5486161","0.54826933","0.5462265","0.5458333","0.5453898","0.54497916","0.544909","0.54335934","0.5421797","0.5416789","0.54164654","0.5415503","0.5411164","0.5409926","0.54059136","0.54037154","0.5401504","0.5393127","0.53926516","0.53923285","0.53921115","0.53863126","0.5380237","0.53800696","0.5366113","0.5364917","0.5364386","0.53635585","0.535769","0.5350568","0.5349918","0.53477895","0.5347465","0.53452","0.53451306","0.53440803","0.53431845","0.534307","0.5340166","0.5338023"],"string":"[\n \"0.6885966\",\n \"0.6692245\",\n \"0.66228366\",\n \"0.6284632\",\n \"0.627446\",\n \"0.6245816\",\n \"0.62092686\",\n \"0.61613834\",\n \"0.613513\",\n \"0.609418\",\n \"0.6056963\",\n \"0.6042189\",\n \"0.60258657\",\n \"0.5984116\",\n \"0.59698874\",\n \"0.59312063\",\n \"0.59092206\",\n \"0.5906563\",\n \"0.58542055\",\n \"0.5850616\",\n \"0.5809356\",\n \"0.579957\",\n \"0.5784076\",\n \"0.57744926\",\n \"0.57643306\",\n \"0.57595515\",\n \"0.575187\",\n \"0.5748009\",\n \"0.57465714\",\n \"0.57419276\",\n \"0.5713134\",\n \"0.57118696\",\n \"0.57016546\",\n \"0.5695353\",\n \"0.56905687\",\n \"0.5682232\",\n \"0.567557\",\n \"0.5675286\",\n \"0.5660535\",\n \"0.5654064\",\n \"0.56452006\",\n \"0.563603\",\n \"0.5626845\",\n \"0.56190723\",\n \"0.5597789\",\n \"0.5594812\",\n \"0.55931795\",\n \"0.557884\",\n \"0.55638456\",\n \"0.55636525\",\n \"0.55563897\",\n \"0.5551577\",\n \"0.5549967\",\n \"0.5543087\",\n \"0.55370647\",\n \"0.551717\",\n \"0.551461\",\n \"0.55087155\",\n \"0.54946136\",\n \"0.54904735\",\n \"0.5486161\",\n \"0.54826933\",\n \"0.5462265\",\n \"0.5458333\",\n \"0.5453898\",\n \"0.54497916\",\n \"0.544909\",\n \"0.54335934\",\n \"0.5421797\",\n \"0.5416789\",\n \"0.54164654\",\n \"0.5415503\",\n \"0.5411164\",\n \"0.5409926\",\n \"0.54059136\",\n \"0.54037154\",\n \"0.5401504\",\n \"0.5393127\",\n \"0.53926516\",\n \"0.53923285\",\n \"0.53921115\",\n \"0.53863126\",\n \"0.5380237\",\n \"0.53800696\",\n \"0.5366113\",\n \"0.5364917\",\n \"0.5364386\",\n \"0.53635585\",\n \"0.535769\",\n \"0.5350568\",\n \"0.5349918\",\n \"0.53477895\",\n \"0.5347465\",\n \"0.53452\",\n \"0.53451306\",\n \"0.53440803\",\n \"0.53431845\",\n \"0.534307\",\n \"0.5340166\",\n \"0.5338023\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.78263"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88592,"cells":{"query":{"kind":"string","value":"Gets valid user credentials from storage. If nothing has been stored, or if the stored credentials are invalid, the OAuth2 flow is completed to obtain the new credentials."},"document":{"kind":"string","value":"def get_credentials():\n #home_dir = os.path.expanduser('~')\n home_dir = (HOME_DIR)\n credential_dir = os.path.join(home_dir, '.credentials')\n print(\"Credentials folder: \",credential_dir)\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'sheets.googleapis.com-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _load_user_credentials(self, storage):\n # Set up a Flow object to be used if we need to authenticate.\n flow = client.flow_from_clientsecrets(\n self.client_secrets,\n scope=self.api_scopes,\n message=tools.message_if_missing(self.client_secrets))\n\n # Retrieve credentials from storage.\n # If the credentials don't exist or are invalid run through the installed\n # client flow. The storage object will ensure that if successful the good\n # credentials will get written back to file.\n\n credentials = storage.get()\n if credentials is None or credentials.invalid:\n credentials = tools.run_flow(flow, storage)\n\n return credentials","def get_credentials(self, **kwargs):\n creds_file = os.path.join(kwargs['user_dir'], 'credentials.json')\n\n # Getting credentials from Storage\n store = file.Storage(creds_file)\n creds = store.get()\n\n # Validating or refreshing credentials, if necessary\n if creds is None or creds.invalid:\n flow = client.flow_from_clientsecrets(self.client_secret_file,\n self.scopes)\n creds = tools.run_flow(flow, store)\n elif creds.access_token_expired:\n creds.refresh(httplib2.Http())\n else:\n pass\n\n return creds","def get_credentials():\n store = Storage(CREDENTIAL_PATH)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n credentials = tools.run_flow(flow, store, None)\n return credentials","def authorize_credentials():\n credentials = STORAGE.get()\n # If the credentials doesn't exist in the storage location then run the flow\n if credentials is None or credentials.invalid:\n flow = flow_from_clientsecrets(CREDENTIAL_JSON, scope=SCOPE)\n http = httplib2.Http()\n credentials = run_flow(flow, STORAGE, http=http)\n return credentials","def get_credentials(self):\n home_dir = os.path.expanduser(\"~\")\n credential_dir = os.path.join(home_dir, \".credentials\")\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir, \"autoto.json\")\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n credentials = tools.run_flow(flow, store, self.auth_flags)\n print(\"Storing credentials to \" + credential_path)\n return credentials","def get_credentials():\n credentials_path = os.path.join(CREDENTIALS_DIR, CREDENTIALS_FILE)\n store = oauth2client.file.Storage(credentials_path)\n credentials = store.locked_get()\n\n if not credentials or credentials.invalid:\n client_secret_path = os.path.join(CREDENTIAL_DIR, CLIENT_SECRET_FILE)\n flow = client.flow_from_clientsecrets(client_secret_path, \n scope='https://www.googleapis.com/auth/admin.directory.resource.calendar',\n redirect_uri='urn:ietf:wg:oauth:2.0:oob')\n\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n\n print(\"Storing credentials to: \" + credentials_path)\n\n\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'clockwise.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatability with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\r\n home_dir = os.path.expanduser('~')\r\n credential_dir = os.path.join(home_dir, '.credentials')\r\n if not os.path.exists(credential_dir):\r\n os.makedirs(credential_dir)\r\n credential_path = os.path.join(credential_dir,\r\n 'bis-python-quickstart.json')\r\n\r\n store = oauth2client.file.Storage(credential_path)\r\n credentials = store.get()\r\n if not credentials or credentials.invalid:\r\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\r\n flow.user_agent = APPLICATION_NAME\r\n if flags:\r\n credentials = tools.run_flow(flow, store, flags)\r\n else: # Needed only for compatibility with Python 2.6\r\n credentials = tools.run(flow, store)\r\n print('Storing credentials to ' + credential_path)\r\n return credentials","def get_creds():\n\tcredentials = None\n\tif os.path.exists('token.pickle'):\n\t\twith open('token.pickle', 'rb') as token:\n\t\t\tcredentials = pickle.load(token)\n\t# If there are no (valid) credentials available, let the user log in.\n\tif not credentials or not credentials.valid:\n\t\tif credentials and credentials.expired and credentials.refresh_token:\n\t\t\tcredentials.refresh(Request())\n\t\telse:\n\t\t\tflow = InstalledAppFlow.from_client_secrets_file('config/sa.json', SCOPES)\n\t\t\tcredentials = flow.run_local_server(port=0)\n\t\t# Save the credentials for the next run\n\t\twith open('token.pickle', 'wb') as token:\n\t\t\tpickle.dump(credentials, token)\n\treturn credentials","def get_credentials() -> client.Credentials:\n\n credential_path = os.path.join(HOME_DIR, \"google-credentials.json\")\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(os.path.join(HOME_DIR, CLIENT_SECRET_FILE), SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n # This attempts to open an authorization page in the default web browser, and asks the user\n # to grant the bot access to their data. If the user grants permission, the run_flow()\n # function returns new credentials.\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print(\"Storing credentials to \" + credential_path)","def get_credentials():\n store = Storage(CLIENT_CREDENTIALS_FILE)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + CLIENT_CREDENTIALS_FILE)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'credentialv_modify.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials(self):\r\n home_dir = os.path.expanduser('~')\r\n credential_dir = os.path.join(home_dir, '.credentials')\r\n if not os.path.exists(credential_dir):\r\n os.makedirs(credential_dir)\r\n credential_path = os.path.join(credential_dir, self.CRED_FILENAME)\r\n \r\n store = Storage(credential_path)\r\n credentials = store.get()\r\n if not credentials or credentials.invalid:\r\n flow = client.flow_from_clientsecrets(self.CLIENT_SECRET_FILE, self.SCOPES)\r\n flow.user_agent = self.APPLICATION_NAME\r\n if flags:\r\n credentials = tools.run_flow(flow, store, flags)\r\n else: # Needed only for compatibility with Python 2.6\r\n credentials = tools.run(flow, store)\r\n print('Storing credentials to ' + credential_path)\r\n return credentials","def get_credentials():\n credential_dir = os.path.realpath('.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'calendar-python-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path) # stores the users credentials --> TODO: put in database\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n\n credentials = tools.run_flow(flow, store, flags)\n\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir, 'fb-drive.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_creds():\n creds = None\n # The file token.pickle stores the user's access and refresh tokens, and is\n # created automatically when the authorization flow completes for the first\n # time.\n if os.path.exists('inputs/token.pickle'):\n with open('inputs/token.pickle', 'rb') as token:\n creds = pickle.load(token)\n # If there are no (valid) credentials available, let the user log in.\n if not creds or not creds.valid:\n if creds and creds.expired and creds.refresh_token:\n creds.refresh(Request())\n else:\n flow = InstalledAppFlow.from_client_secrets_file(\n 'inputs/credentials.json', SCOPES)\n creds = flow.run_local_server(port=0)\n # Save the credentials for the next run\n with open('inputs/token.pickle', 'wb') as token:\n pickle.dump(creds, token)\n return creds","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'reseller-python-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_stored_credentials(user_id):\n #\n # To instantiate an OAuth2Credentials instance from a Json\n # representation, use the oauth2client.client.Credentials.new_from_json\n # class method.\n user = engine.query(User).filter(userId=user_id).first()\n if user:\n user_dict = user.__dict__\n if user_dict['credentials']:\n # credentials = Credentials.new_from_json(user['credentials'])\n credentials = json.loads(user_dict['credentials'])\n token_expiry = credentials['token_expiry']\n dexp = parser.parse(str(token_expiry))\n dexp = dexp.replace(tzinfo=None)\n dnow = datetime.now()\n\n if dexp > dnow:\n return Credentials.new_from_json(user_dict['credentials'])\n else:\n status_code, data = renew_access_token(client_id=credentials['client_id'],\n client_secret=credentials['client_secret'],\n refresh_token=credentials['refresh_token'],\n )\n if status_code == INT_OK:\n credentials['access_token'] = data['access_token']\n credentials['token_expiry'] = datetime_util(datetime.now() + timedelta(seconds=float(str(data['expires_in']))))\n credentials = Credentials.new_from_json(json_encode(credentials))\n user.update_credentials(credentials.to_json())\n user.sync()\n return credentials\n else:\n return None\n else:\n return None\n return None","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'calendar-python-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'calendar-python-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'calendar-python-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'calendar-python-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'calendar-python-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\r\n home_dir = os.path.expanduser('~')\r\n credential_dir = os.path.join(home_dir, '.credentials')\r\n if not os.path.exists(credential_dir):\r\n os.makedirs(credential_dir)\r\n credential_path = os.path.join(credential_dir,\r\n 'calendar-python-quickstart.json')\r\n\r\n store = oauth2client.file.Storage(credential_path)\r\n credentials = store.get()\r\n if not credentials or credentials.invalid:\r\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\r\n flow.user_agent = APPLICATION_NAME\r\n if flags:\r\n credentials = tools.run_flow(flow, store, flags)\r\n else: # Needed only for compatibility with Python 2.6\r\n credentials = tools.run(flow, store)\r\n print('Storing credentials to ' + credential_path)\r\n return credentials","def get_credentials():\r\n home_dir = os.path.expanduser('~')\r\n credential_dir = os.path.join(home_dir, '.credentials')\r\n if not os.path.exists(credential_dir):\r\n os.makedirs(credential_dir)\r\n credential_path = os.path.join(credential_dir,'drive-python-quickstart.json')\r\n\r\n store = Storage(credential_path)\r\n credentials = store.get()\r\n if not credentials or credentials.invalid:\r\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\r\n flow.user_agent = APPLICATION_NAME\r\n if flags:\r\n credentials = tools.run_flow(flow, store, flags)\r\n else: # Needed only for compatibility with Python 2.6\r\n credentials = tools.run(flow, store)\r\n print('Storing credentials to ' + credential_path)\r\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'drive-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'drive-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n\thome_dir = os.path.expanduser('~')\n\tcredential_dir = os.path.join(home_dir, '.credentials')\n\tif not os.path.exists(credential_dir):\n\t\tos.makedirs(credential_dir)\n\tcredential_path = os.path.join(credential_dir, \n\t\t\t\t\t\t\t\t\t'facebook_updater.json')\n\t\t\t\t\t\t\t\t\t\n\tstore = oauth2client.file.Storage(credential_path)\n\tcredentials = store.get()\n\tif not credentials or credentials.invalid:\n\t\tflow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n\t\tflow.user_agent = APPLICATION_NAME\n\t\tif flags:\n\t\t\tcredentials = tools.run_flow(flow, store, flags)\n\t\tprint ('Storing credentials to ' + credential_path)\n\treturn credentials","def get_credentials():\n credential_dir = os.getcwd()\n credential_path = os.path.join(credential_dir,\n 'smarking_error_check.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'client_secret_OCR.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n print(\"Current folder: \" + os.getcwd())\n flow = client.flow_from_clientsecrets(\n \"../../\" + CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'gmail-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatability with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'grader.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n credentials = tools.run_flow(flow, store, tools.argparser.parse_args(args=[]))\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'gmail-python-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir, 'google-photos-stats.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n credentials = tools.run_flow(flow, store, flags)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'appsactivity-python-showtime.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n print('Storing credentials to ' + credential_path)\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'admin-directory_v1-NestedGroupSync.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatability with Python 2.6\n credentials = tools.run(flow, store)\n print 'Storing credentials to' + credential_path\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'thejam_calendar.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'calendar-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(config['client secret file'], SCOPES)\n flow.user_agent = APPLICATION_NAME\n if args:\n credentials = tools.run_flow(flow, store, args)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'sally.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'calendar-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'calendar-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'calendar-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n #home_dir = os.path.expanduser('~')\n home_dir = os.path.expanduser('/home/pi/')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir, 'gmail-python-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'sheets.googleapis.com-python-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'sheets.googleapis.com-python-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\r\n home_dir = os.path.expanduser('~')\r\n credential_dir = os.path.join(home_dir, '.credentials')\r\n if not os.path.exists(credential_dir):\r\n os.makedirs(credential_dir)\r\n credential_path = os.path.join(credential_dir,\r\n 'gmail-python-spam-filter.json')\r\n\r\n store = Storage(credential_path)\r\n credentials = store.get()\r\n if not credentials or credentials.invalid:\r\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\r\n flow.user_agent = APPLICATION_NAME\r\n if flags:\r\n credentials = tools.run_flow(flow, store, flags)\r\n else: # Needed only for compatibility with Python 2.6\r\n credentials = tools.run(flow, store)\r\n print('Storing credentials to ' + credential_path)\r\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'gmail-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_auth_token(self):\n creds = None\n # The file token.pickle stores the user's access and refresh tokens,\n # and is created automatically when the authorization flow completes\n # for the first time.\n if os.path.exists(self.token_path):\n with open(self.token_path, 'rb') as token:\n creds = pickle.load(token)\n # If there are no (valid) credentials available, let the user log in.\n if not creds or not creds.valid:\n if creds and creds.expired and creds.refresh_token:\n creds.refresh(Request())\n else:\n flow = InstalledAppFlow.from_client_secrets_file(\n self.credentials_path, self.scopes)\n creds = flow.run_local_server(port=0)\n # Save the credentials for the next run\n with open(self.token_path, 'wb') as token:\n pickle.dump(creds, token)\n return creds","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'gmail-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'gmail-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'gmail-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'gmail-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'gmail-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(args.clientSecretFile, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if args:\n credentials = tools.run_flow(flow, store, args)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def _get_credentials(self):\n\n scopes = 'https://www.googleapis.com/auth/drive'\n client_secret_file = '%s/config/client_secret.json' % PROJECT_DIR\n application_name = 'Drive API Quickstart'\n\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n\n credential_path = os.path.join(credential_dir, 'drive-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(client_secret_file, scopes)\n flow.user_agent = application_name\n\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatability with Python 2.6\n credentials = tools.run(flow, store)\n\n return credentials","def get_credentials(self):\n #\n # Why is this not read from the yaml file?\n path = Path(path_expand(self.credential_file)).resolve()\n if not os.path.exists(path):\n os.makedirs(path)\n\n credentials_path = (path / 'google-drive-credentials.json').resolve()\n print(credentials_path)\n\n store = Storage(credentials_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(self.client_secret_file,\n self.scopes)\n flow.user_agent = self.application_name\n #\n # SHOUDL THE FLAGS NOT BE SET IN THE YAML FILE OR DOCOPTS OFTHE COMMAND?\n #\n if self.flags:\n credentials = tools.run_flow(flow, store, self.flags)\n\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'sheets.googleapis.com-python.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = './ignore' #os.path.expanduser('./')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'gmail-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = './ignore' #os.path.expanduser('./')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'gmail-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials(self):\n home_dir = os.path.expanduser('~')\n # credential_dir = os.path.join(home_dir, '.credentials')\n credential_dir = '.credentials'\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir, 'drive-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(GoogleDocsConverter.CLIENT_SECRET_FILE, GoogleDocsConverter.SCOPES)\n flow.user_agent = GoogleDocsConverter.APPLICATION_NAME\n if self.flags:\n credentials = tools.run_flow(flow, store, self.flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir, 'sheets.googleapis.com-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n credentials = tools.run_flow(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser(os.getcwd())\n credential_dir = os.path.join(home_dir, '.credentials')\n print(credential_dir)\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'calendar-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_creds():\n # If modifying these scopes, delete the file token.pickle.\n SCOPES = ['https://www.googleapis.com/auth/gmail.readonly']\n creds = None\n dir_pre = '../secrets'\n # The file token.pickle stores the user's access and refresh tokens, and is\n # created automatically when the authorization flow completes for the first\n # time.\n logging.debug(f\"searching for creds in path: {os.getcwd()}\")\n if os.path.exists(os.path.join(dir_pre, 'token.pickle')):\n with open(os.path.join(dir_pre, 'token.pickle'), 'rb') as token:\n creds = pickle.load(token)\n logging.info('opening token.pickle')\n # If there are no (valid) credentials available, let the user log in.\n if not creds or not creds.valid:\n if creds and creds.expired and creds.refresh_token:\n logging.info('token expired, refreshing token')\n creds.refresh(Request())\n else:\n logging.info('token not found, re authenticating ')\n flow = InstalledAppFlow.from_client_secrets_file(os.path.join(dir_pre, 'credentials.json'), SCOPES)\n creds = flow.run_local_server(port=0)\n # Save the credentials for the next run\n with open(os.path.join(dir_pre, 'token.pickle'), 'wb') as token:\n pickle.dump(creds, token)\n\n return creds","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'sheets.googleapis.com-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'sheets.googleapis.com-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'sheets.googleapis.com-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'sheets.googleapis.com-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(\n credential_dir, 'sheets.googleapis.com-python-quickstart.json'\n )\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'sheets.googleapis.com-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(resource_path(CLIENT_SECRET_FILE), SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials(self):\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'homework_logger-gmail-api.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(self.CLIENT_SECRET_FILE, self.SCOPES)\n flow.user_agent = self.APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def getCredentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir, 'gmail-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def getCredentials(scopes):\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,'admin-directory_v1-python-quickstart.json')\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, scopes)\n flow.user_agent = APPLICATION_NAME\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials(self):\r\n \r\n try:\r\n import argparse\r\n #flags = argparse.ArgumentParser(parents=[tools.argparser]).parse_args()\r\n if self.noauth == True:\r\n flags = tools.argparser.parse_args(args=['--noauth_local_webserver'])\r\n else:\r\n flags = tools.argparser.parse_args(args=[])\r\n except ImportError:\r\n flags = None \r\n \r\n home_dir = os.path.expanduser('~')\r\n credential_dir = os.path.join(home_dir, '.credentials')\r\n if not os.path.exists(credential_dir):\r\n os.makedirs(credential_dir)\r\n credential_path = os.path.join(credential_dir,'sheets.googleapis.com-allstarbot.json')\r\n\r\n store = Storage(credential_path)\r\n credentials = store.get()\r\n if not credentials or credentials.invalid:\r\n secret = Path(self.CLIENT_SECRET_FILE)\r\n if secret.exists():\r\n flow = client.flow_from_clientsecrets(self.CLIENT_SECRET_FILE, self.SCOPES)\r\n else:\r\n print(\"client_secret.json not found, using env vars\")\r\n if not os.environ.get('client_id') or not os.environ.get('client_secret'): \r\n print(\"env vars client_id and client_secret not found. canceling\")\r\n raise Exception(\"client secret error\")\r\n else:\r\n flow = OAuth2WebServerFlow(\r\n os.environ.get('client_id'),\r\n os.environ.get('client_secret'),\r\n self.SCOPES) \r\n \r\n flow.params['access_type'] = 'offline'\r\n flow.user_agent = self.APPLICATION_NAME\r\n if flags:\r\n credentials = tools.run_flow(flow, store, flags)\r\n else: # Needed only for compatibility with Python 2.6\r\n credentials = tools.run(flow, store)\r\n print('Storing credentials to ' + credential_path)\r\n return credentials","def get_credentials(credentials_filename, application_name, client_secret_file, scopes):\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n credentials_filename)\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(client_secret_file, scopes)\n flow.user_agent = application_name\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n# else: # Needed only for compatibility with Python 2.6\n# credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def valid_credentials():\n if 'credentials' not in flask.session:\n return None\n\n credentials = client.OAuth2Credentials.from_json(\n flask.session['credentials'])\n\n if (credentials.invalid or\n credentials.access_token_expired):\n return None\n return credentials","def valid_credentials():\n if 'credentials' not in flask.session:\n return None\n\n credentials = client.OAuth2Credentials.from_json(\n flask.session['credentials'])\n\n if (credentials.invalid or\n credentials.access_token_expired):\n return None\n return credentials","def __create_credentials(self, scopes):\n creds = None\n\n # The File token.pickle stores the user's access and refresh tokens,\n # and is created automatically whne the flow compleates for the first time.\n if os.path.exists('token.pickle'):\n with open('token.pickle', 'rb') as token:\n creds = pickle.load(token)\n # if there are no valid credentials available, let the user log in\n if not creds or not creds.valid:\n if creds and creds.expired and creds.refresh_token:\n creds.refresh(Request())\n else:\n flow = InstalledAppFlow.from_client_secrets_file(\n 'credentials.json', scopes)\n creds = flow.run_local_server(port=0)\n # save the creds for the next run\n with open('token.pickle', 'wb') as token:\n pickle.dump(creds, token)\n\n return creds","def get_credentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'sheets.googleapis.logSheets.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n print('Storing credentials to ' + credential_path)\n return credentials","def authenticate():\n creds = None\n # The file token.pickle stores the user's access and refresh tokens, and is\n # created automatically when the authorization flow completes for the first\n # time.\n if os.path.exists('token.pickle'):\n with open('token.pickle', 'rb') as token:\n creds = pickle.load(token)\n # If there are no (valid) credentials available, let the user log in.\n if not creds or not creds.valid:\n if creds and creds.expired and creds.refresh_token:\n creds.refresh(Request())\n else:\n flow = InstalledAppFlow.from_client_secrets_file(\n 'google-drive-credentials.json', SCOPES)\n creds = flow.run_local_server(port=0)\n # Save the credentials for the next run\n with open('token.pickle', 'wb') as token:\n pickle.dump(creds, token)\n\n return creds","def getUsrCreds(self):\n import pickle\n import os.path\n from google_auth_oauthlib.flow import InstalledAppFlow\n from google.auth.transport.requests import Request\n\n # If modifying these scopes, delete the file token.pickle.\n SCOPES = ['https://www.googleapis.com/auth/calendar']\n\n self.creds = None\n # The file token.pickle stores the user's access and refresh tokens, and is\n # created automatically when the authorization flow completes for the first\n # time.\n if os.path.exists('token.pickle'):\n with open('token.pickle', 'rb') as self.token:\n self.creds = pickle.load(self.token)\n # If there are no (valid) credentials available, let the user log in.\n if not self.creds or not self.creds.valid:\n if self.creds and self.creds.expired and self.creds.refresh_token:\n self.creds.refresh(Request())\n else:\n self.flow = InstalledAppFlow.from_client_secrets_file(\n 'client_secret.json', scopes = SCOPES)\n self.creds = self.flow.run_local_server(port=0)\n # Save the credentials for the next run\n with open('token.pickle', 'wb') as self.token:\n pickle.dump(self.creds, self.token)\n\n return self.creds","def get_credentials(self):\n if getattr(self, 'credentials', None):\n return self.credentials\n\n scopes = settings.SCOPES\n client_secret_file = settings.CLIENT_SECRET_FILE\n application_name = 'Google Sheets API Python Quickstart'\n\n home_dir = os.path.expanduser(settings.CREDENTIALS_DIRECTORY)\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir, 'sheets.googleapis.com-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(client_secret_file, scopes)\n flow.user_agent = application_name\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n # print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n try:\n import argparse\n flags = argparse.ArgumentParser(parents=[tools.argparser]).parse_args()\n except ImportError:\n flags = None\n\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'appsactivity-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(GoogleGsuiteAPI.CLIENT_SECRET_FILE, GoogleGsuiteAPI.SCOPES)\n flow.user_agent = GoogleGsuiteAPI.APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def create_credentials():\r\n creds = None\r\n # The file token.pickle stores the user's access and refresh tokens, and is\r\n # created automatically when the authorization flow completes for the first\r\n # time.\r\n if os.path.exists('token.pickle'):\r\n with open('token.pickle', 'rb') as token:\r\n creds = pickle.load(token)\r\n # If there are no (valid) credentials available, let the user log in.\r\n if not creds or not creds.valid:\r\n if creds and creds.expired and creds.refresh_token:\r\n creds.refresh(Request())\r\n else:\r\n flow = InstalledAppFlow.from_client_secrets_file(\r\n 'client_secret.json', SCOPES)\r\n creds = flow.run_local_server()\r\n # Save the credentials for the next run\r\n with open('token.pickle', 'wb') as token:\r\n pickle.dump(creds, token)\r\n return creds","def get_stored_credentials(user):\n with open(\"access.json\", \"r\") as f:\n credentials = json.load(f)\n user_creds = credentials[user]\n return user_creds[\"access_token\"], user_creds[\"access_secret\"]","def get_credentials(scopes=None, secrets=None, storage=None, *,\n no_webserver=False):\n scopes = Scopes.get(scopes)\n\n if secrets is None:\n secrets = SECRETS\n if storage is None:\n storage = STORAGE\n\n secrets, storage = map(os.path.expanduser, (secrets, storage))\n\n store = file.Storage(storage)\n creds = store.get()\n\n if creds is None or creds.invalid:\n flow = client.flow_from_clientsecrets(secrets, scopes)\n args = ['--noauth_local_webserver'] if no_webserver else []\n flags = tools.argparser.parse_args(args)\n creds = tools.run_flow(flow, store, flags)\n\n return creds","def valid_credentials():\n if 'credentials' not in flask.session:\n return None\n\n credentials = client.OAuth2Credentials.from_json(\n flask.session['credentials'])\n\n if (credentials.invalid or credentials.access_token_expired):\n return None\n return credentials","def get_credentials(client_secrets='client_secrets.json',\n scope_='https://www.googleapis.com/auth/drive',\n redirect_uri_='http://localhost:8080'):\n flow = client.flow_from_clientsecrets(client_secrets,\n scope=scope_,\n redirect_uri=redirect_uri_)\n credentials = tools.run_flow(flow, Store(), None)\n return credentials","def get_credentials(account):\n credential_dir = os.path.join(HOME_DIR, META_DIR, account, \"credentials\")\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir, 'pyDrive.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_creds(\n user=\"default\", config=None, scope=default_scope, creds_dir=None, save=True\n):\n config = config or get_config()\n try:\n if \"private_key_id\" in config:\n return SACredentials.from_service_account_info(config, scopes=scope)\n\n if not isinstance(user, str):\n raise ConfigException(\n \"Need to provide a user key as a string if not using a service account\"\n )\n\n if creds_dir is None:\n creds_dir = get_config_dir() / \"creds\"\n\n creds_file = Path(creds_dir) / user\n\n if creds_file.exists():\n # need to convert Path to string for python 2.7\n return OAuthCredentials.from_authorized_user_file(str(creds_file))\n\n flow = InstalledAppFlow.from_client_config(config, scope)\n creds = flow.run_local_server(\n host=\"localhost\",\n port=8182,\n authorization_prompt_message=\"Please visit this URL: {url}\",\n success_message=\"The auth flow is complete; you may close this window.\",\n open_browser=False,\n )\n\n if save:\n creds_data = {\n \"refresh_token\": creds.refresh_token,\n \"token_uri\": creds.token_uri,\n \"client_id\": creds.client_id,\n \"client_secret\": creds.client_secret,\n \"scopes\": creds.scopes,\n }\n\n ensure_path(creds_dir)\n creds_file.write_text(decode(json.dumps(creds_data)))\n\n return creds\n except Exception:\n exc_info = sys.exc_info()\n raise ConfigException(*exc_info[1:])","def GetCredentials(self, credentials_path: str,\n client_secrets_path: str) -> Optional[Any]:\n scopes = ['openid', 'https://www.googleapis.com/auth/userinfo.email']\n credentials = None\n\n # Load credentials file if it exists\n if os.path.exists(credentials_path):\n try:\n credentials = Credentials.from_authorized_user_file(\n credentials_path, scopes)\n except ValueError as exception:\n msg = f'Error loading credentials: {exception!s}'\n self.ModuleError(msg, critical=True)\n # Refresh credentials using existing refresh_token\n if credentials and credentials.refresh_token:\n self.logger.debug('Found a refresh token. Requesting new id_token...')\n try:\n credentials.refresh(Request())\n except google_exceptions.RefreshError as exception:\n self.logger.debug(f'Error refreshing credentials: {exception!s}')\n else:\n # No credentials file, acquire new credentials from secrets file.\n self.logger.debug(\n 'Could not find existing credentials. Requesting new tokens.')\n try:\n appflow = flow.InstalledAppFlow.from_client_secrets_file(\n client_secrets_path, scopes)\n except FileNotFoundError as exception:\n msg = f'Client secrets file not found: {exception!s}'\n self.ModuleError(msg, critical=True)\n\n self.logger.info(\n 'Starting local HTTP server on localhost:8888 for OAUTH flow. '\n 'If running dftimewolf remotely over SSH you will need to tunnel '\n 'port 8888.')\n appflow.run_local_server(host='localhost', port=8888, open_browser=False)\n credentials = appflow.credentials\n\n # Save credentials\n if credentials:\n with open(credentials_path, 'w', encoding='utf-8') as token:\n token.write(credentials.to_json())\n\n return credentials","def get_credentials(commandline_flags=None):\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'drive-python-quickstart.json')\n\n store = oauth2client.file.Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if commandline_flags:\n credentials = tools.run_flow(flow, store, commandline_flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials():\n credential_dir = os.path.dirname(os.path.realpath(CLIENT_SECRET_FILE))\n credential_path = os.path.join(\n credential_dir, 'sheets.googleapis.com-endosys-events.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n credentials = tools.run_flow(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def acquire_oauth2_credentials():\n if os.path.isfile(\"%s/cre.json\" % file_path):\n f = open(\"%s/cre.json\" % file_path, \"r\")\n credentials = client.OAuth2Credentials.from_json(f.read())\n f.close()\n else: \n flow = client.flow_from_clientsecrets(\n \"%s/client_secrets.json\" % file_path,\n scope='https://www.googleapis.com/auth/analytics.readonly',\n redirect_uri='urn:ietf:wg:oauth:2.0:oob')\n auth_uri = flow.step1_get_authorize_url()\n webbrowser.open(auth_uri)\n auth_code = input('Enter the authentication code: ')\n credentials = flow.step2_exchange(auth_code)\n write_credentials(\"%s/cre.json\" % file_path, credentials)\n return credentials","def google_creds() -> object:\n # If modifying these scopes, delete the file token.pickle.\n SCOPES = ['https://www.googleapis.com/auth/drive.file',\n 'https://www.googleapis.com/auth/drive',\n 'https://www.googleapis.com/auth/drive.activity',\n 'https://www.googleapis.com/auth/spreadsheets'\n ]\n\n creds = None\n # The file token.pickle stores the user's access and refresh tokens, and is\n # created automatically when the authorization flow completes for the first\n # time.\n if os.path.exists('token.pickle'):\n with open('token.pickle', 'rb') as token:\n creds = pickle.load(token)\n # If there are no (valid) credentials available, let the user log in.\n if not creds or not creds.valid:\n if creds and creds.expired and creds.refresh_token:\n creds.refresh(Request())\n else:\n flow = InstalledAppFlow.from_client_secrets_file(\n 'credentials.json', SCOPES)\n creds = flow.run_local_server(port=0)\n # Save the credentials for the next run\n with open('token.pickle', 'wb') as token:\n pickle.dump(creds, token)\n\n return creds","def get_credentials(args, my_dirname):\n\n credential_dir = os.path.join(my_dirname, '.credentials')\n if not os.path.exists(credential_dir):\n os.mkdir(credential_dir)\n credential_path = os.path.join(credential_dir, 'sheets.googleapis.com-cotus-checker.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n try:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n credentials = tools.run_flow(flow, store, args)\n print('Storing credentials to ' + credential_path)\n except (oauth2client.clientsecrets.InvalidClientSecretsError, json.decoder.JSONDecodeError):\n pass\n return credentials","def get_GoogleCredentials():\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'calendar-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials(data_dir_path, client_secret_file_path, scopes, application_name):\n #home_dir = os.path.expanduser('~')\n #credential_dir = os.path.join(home_dir, '.credentials')\n credential_dir = os.path.join(data_dir_path, \".credentials\")\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'gmail-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(client_secret_file_path, scopes)\n flow.user_agent = application_name\n\n try:\n import argparse\n flags = argparse.ArgumentParser(parents=[tools.argparser]).parse_args()\n except ImportError:\n flags = None\n\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def get_credentials( flags=None ):\n home_dir = os.path.expanduser('~')\n credential_dir = os.path.join(home_dir, '.credentials')\n if not os.path.exists(credential_dir):\n os.makedirs(credential_dir)\n credential_path = os.path.join(credential_dir,\n 'drive-python-quickstart.json')\n\n store = Storage(credential_path)\n credentials = store.get()\n if not credentials or credentials.invalid:\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\n flow.user_agent = APPLICATION_NAME\n if flags:\n credentials = tools.run_flow(flow, store, flags)\n else: # Needed only for compatibility with Python 2.6\n credentials = tools.run(flow, store)\n print('Storing credentials to ' + credential_path)\n return credentials","def _get_credential(self):\n creds = None\n\n if os.path.exists('token.pickle'):\n with open('token.pickle', 'rb') as token:\n creds = pickle.load(token)\n\n if not creds or not creds.valid:\n if creds and creds.expired and creds.refresh_token:\n creds.refresh(Request())\n else:\n flow = InstalledAppFlow.from_client_secrets_file(\n 'credentials.json', self.config['SCOPES'])\n creds = flow.run_local_server(port=0)\n # Save the credentials for the next run\n with open('token.pickle', 'wb') as token:\n pickle.dump(creds, token)\n\n self.service = build('drive', 'v3', credentials=creds)","def get(self):\n self._lock.acquire()\n try:\n f = open(self._filename, 'r')\n credentials = pickle.loads(f.read())\n f.close()\n credentials.set_store(self.put)\n except:\n credentials = None\n self._lock.release()\n\n return credentials","def get_creds(\n config: Config=default):\n config_path = config.credential_path\n scopes = config.scopes\n\n logger.info('loading token')\n logger.debug(f'config_path: {config_path}')\n config_path = Path(config_path).expanduser()\n store = file.Storage(config_path/'token.json')\n creds = store.get()\n\n if not creds or creds.invalid:\n # Ask the user to give the correct permissions.\n logger.info('loading credentials')\n flow = client.flow_from_clientsecrets(\n config_path/'client_id.json',\n scopes)\n\n arguments = sys.argv\n sys.argv = sys.argv[0:1]\n # This line is why we need to remove the arguments from sys.argv\n # If you find a better way to get it to work, i'm buying it\n creds = tools.run_flow(flow, store)\n sys.argv = arguments\n\n return creds"],"string":"[\n \"def _load_user_credentials(self, storage):\\n # Set up a Flow object to be used if we need to authenticate.\\n flow = client.flow_from_clientsecrets(\\n self.client_secrets,\\n scope=self.api_scopes,\\n message=tools.message_if_missing(self.client_secrets))\\n\\n # Retrieve credentials from storage.\\n # If the credentials don't exist or are invalid run through the installed\\n # client flow. The storage object will ensure that if successful the good\\n # credentials will get written back to file.\\n\\n credentials = storage.get()\\n if credentials is None or credentials.invalid:\\n credentials = tools.run_flow(flow, storage)\\n\\n return credentials\",\n \"def get_credentials(self, **kwargs):\\n creds_file = os.path.join(kwargs['user_dir'], 'credentials.json')\\n\\n # Getting credentials from Storage\\n store = file.Storage(creds_file)\\n creds = store.get()\\n\\n # Validating or refreshing credentials, if necessary\\n if creds is None or creds.invalid:\\n flow = client.flow_from_clientsecrets(self.client_secret_file,\\n self.scopes)\\n creds = tools.run_flow(flow, store)\\n elif creds.access_token_expired:\\n creds.refresh(httplib2.Http())\\n else:\\n pass\\n\\n return creds\",\n \"def get_credentials():\\n store = Storage(CREDENTIAL_PATH)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n credentials = tools.run_flow(flow, store, None)\\n return credentials\",\n \"def authorize_credentials():\\n credentials = STORAGE.get()\\n # If the credentials doesn't exist in the storage location then run the flow\\n if credentials is None or credentials.invalid:\\n flow = flow_from_clientsecrets(CREDENTIAL_JSON, scope=SCOPE)\\n http = httplib2.Http()\\n credentials = run_flow(flow, STORAGE, http=http)\\n return credentials\",\n \"def get_credentials(self):\\n home_dir = os.path.expanduser(\\\"~\\\")\\n credential_dir = os.path.join(home_dir, \\\".credentials\\\")\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir, \\\"autoto.json\\\")\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n credentials = tools.run_flow(flow, store, self.auth_flags)\\n print(\\\"Storing credentials to \\\" + credential_path)\\n return credentials\",\n \"def get_credentials():\\n credentials_path = os.path.join(CREDENTIALS_DIR, CREDENTIALS_FILE)\\n store = oauth2client.file.Storage(credentials_path)\\n credentials = store.locked_get()\\n\\n if not credentials or credentials.invalid:\\n client_secret_path = os.path.join(CREDENTIAL_DIR, CLIENT_SECRET_FILE)\\n flow = client.flow_from_clientsecrets(client_secret_path, \\n scope='https://www.googleapis.com/auth/admin.directory.resource.calendar',\\n redirect_uri='urn:ietf:wg:oauth:2.0:oob')\\n\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n\\n print(\\\"Storing credentials to: \\\" + credentials_path)\\n\\n\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'clockwise.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatability with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\r\\n home_dir = os.path.expanduser('~')\\r\\n credential_dir = os.path.join(home_dir, '.credentials')\\r\\n if not os.path.exists(credential_dir):\\r\\n os.makedirs(credential_dir)\\r\\n credential_path = os.path.join(credential_dir,\\r\\n 'bis-python-quickstart.json')\\r\\n\\r\\n store = oauth2client.file.Storage(credential_path)\\r\\n credentials = store.get()\\r\\n if not credentials or credentials.invalid:\\r\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\r\\n flow.user_agent = APPLICATION_NAME\\r\\n if flags:\\r\\n credentials = tools.run_flow(flow, store, flags)\\r\\n else: # Needed only for compatibility with Python 2.6\\r\\n credentials = tools.run(flow, store)\\r\\n print('Storing credentials to ' + credential_path)\\r\\n return credentials\",\n \"def get_creds():\\n\\tcredentials = None\\n\\tif os.path.exists('token.pickle'):\\n\\t\\twith open('token.pickle', 'rb') as token:\\n\\t\\t\\tcredentials = pickle.load(token)\\n\\t# If there are no (valid) credentials available, let the user log in.\\n\\tif not credentials or not credentials.valid:\\n\\t\\tif credentials and credentials.expired and credentials.refresh_token:\\n\\t\\t\\tcredentials.refresh(Request())\\n\\t\\telse:\\n\\t\\t\\tflow = InstalledAppFlow.from_client_secrets_file('config/sa.json', SCOPES)\\n\\t\\t\\tcredentials = flow.run_local_server(port=0)\\n\\t\\t# Save the credentials for the next run\\n\\t\\twith open('token.pickle', 'wb') as token:\\n\\t\\t\\tpickle.dump(credentials, token)\\n\\treturn credentials\",\n \"def get_credentials() -> client.Credentials:\\n\\n credential_path = os.path.join(HOME_DIR, \\\"google-credentials.json\\\")\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(os.path.join(HOME_DIR, CLIENT_SECRET_FILE), SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n # This attempts to open an authorization page in the default web browser, and asks the user\\n # to grant the bot access to their data. If the user grants permission, the run_flow()\\n # function returns new credentials.\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print(\\\"Storing credentials to \\\" + credential_path)\",\n \"def get_credentials():\\n store = Storage(CLIENT_CREDENTIALS_FILE)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + CLIENT_CREDENTIALS_FILE)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'credentialv_modify.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials(self):\\r\\n home_dir = os.path.expanduser('~')\\r\\n credential_dir = os.path.join(home_dir, '.credentials')\\r\\n if not os.path.exists(credential_dir):\\r\\n os.makedirs(credential_dir)\\r\\n credential_path = os.path.join(credential_dir, self.CRED_FILENAME)\\r\\n \\r\\n store = Storage(credential_path)\\r\\n credentials = store.get()\\r\\n if not credentials or credentials.invalid:\\r\\n flow = client.flow_from_clientsecrets(self.CLIENT_SECRET_FILE, self.SCOPES)\\r\\n flow.user_agent = self.APPLICATION_NAME\\r\\n if flags:\\r\\n credentials = tools.run_flow(flow, store, flags)\\r\\n else: # Needed only for compatibility with Python 2.6\\r\\n credentials = tools.run(flow, store)\\r\\n print('Storing credentials to ' + credential_path)\\r\\n return credentials\",\n \"def get_credentials():\\n credential_dir = os.path.realpath('.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'calendar-python-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path) # stores the users credentials --> TODO: put in database\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n\\n credentials = tools.run_flow(flow, store, flags)\\n\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir, 'fb-drive.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_creds():\\n creds = None\\n # The file token.pickle stores the user's access and refresh tokens, and is\\n # created automatically when the authorization flow completes for the first\\n # time.\\n if os.path.exists('inputs/token.pickle'):\\n with open('inputs/token.pickle', 'rb') as token:\\n creds = pickle.load(token)\\n # If there are no (valid) credentials available, let the user log in.\\n if not creds or not creds.valid:\\n if creds and creds.expired and creds.refresh_token:\\n creds.refresh(Request())\\n else:\\n flow = InstalledAppFlow.from_client_secrets_file(\\n 'inputs/credentials.json', SCOPES)\\n creds = flow.run_local_server(port=0)\\n # Save the credentials for the next run\\n with open('inputs/token.pickle', 'wb') as token:\\n pickle.dump(creds, token)\\n return creds\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'reseller-python-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_stored_credentials(user_id):\\n #\\n # To instantiate an OAuth2Credentials instance from a Json\\n # representation, use the oauth2client.client.Credentials.new_from_json\\n # class method.\\n user = engine.query(User).filter(userId=user_id).first()\\n if user:\\n user_dict = user.__dict__\\n if user_dict['credentials']:\\n # credentials = Credentials.new_from_json(user['credentials'])\\n credentials = json.loads(user_dict['credentials'])\\n token_expiry = credentials['token_expiry']\\n dexp = parser.parse(str(token_expiry))\\n dexp = dexp.replace(tzinfo=None)\\n dnow = datetime.now()\\n\\n if dexp > dnow:\\n return Credentials.new_from_json(user_dict['credentials'])\\n else:\\n status_code, data = renew_access_token(client_id=credentials['client_id'],\\n client_secret=credentials['client_secret'],\\n refresh_token=credentials['refresh_token'],\\n )\\n if status_code == INT_OK:\\n credentials['access_token'] = data['access_token']\\n credentials['token_expiry'] = datetime_util(datetime.now() + timedelta(seconds=float(str(data['expires_in']))))\\n credentials = Credentials.new_from_json(json_encode(credentials))\\n user.update_credentials(credentials.to_json())\\n user.sync()\\n return credentials\\n else:\\n return None\\n else:\\n return None\\n return None\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'calendar-python-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'calendar-python-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'calendar-python-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'calendar-python-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'calendar-python-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\r\\n home_dir = os.path.expanduser('~')\\r\\n credential_dir = os.path.join(home_dir, '.credentials')\\r\\n if not os.path.exists(credential_dir):\\r\\n os.makedirs(credential_dir)\\r\\n credential_path = os.path.join(credential_dir,\\r\\n 'calendar-python-quickstart.json')\\r\\n\\r\\n store = oauth2client.file.Storage(credential_path)\\r\\n credentials = store.get()\\r\\n if not credentials or credentials.invalid:\\r\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\r\\n flow.user_agent = APPLICATION_NAME\\r\\n if flags:\\r\\n credentials = tools.run_flow(flow, store, flags)\\r\\n else: # Needed only for compatibility with Python 2.6\\r\\n credentials = tools.run(flow, store)\\r\\n print('Storing credentials to ' + credential_path)\\r\\n return credentials\",\n \"def get_credentials():\\r\\n home_dir = os.path.expanduser('~')\\r\\n credential_dir = os.path.join(home_dir, '.credentials')\\r\\n if not os.path.exists(credential_dir):\\r\\n os.makedirs(credential_dir)\\r\\n credential_path = os.path.join(credential_dir,'drive-python-quickstart.json')\\r\\n\\r\\n store = Storage(credential_path)\\r\\n credentials = store.get()\\r\\n if not credentials or credentials.invalid:\\r\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\r\\n flow.user_agent = APPLICATION_NAME\\r\\n if flags:\\r\\n credentials = tools.run_flow(flow, store, flags)\\r\\n else: # Needed only for compatibility with Python 2.6\\r\\n credentials = tools.run(flow, store)\\r\\n print('Storing credentials to ' + credential_path)\\r\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'drive-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'drive-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n\\thome_dir = os.path.expanduser('~')\\n\\tcredential_dir = os.path.join(home_dir, '.credentials')\\n\\tif not os.path.exists(credential_dir):\\n\\t\\tos.makedirs(credential_dir)\\n\\tcredential_path = os.path.join(credential_dir, \\n\\t\\t\\t\\t\\t\\t\\t\\t\\t'facebook_updater.json')\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\n\\tstore = oauth2client.file.Storage(credential_path)\\n\\tcredentials = store.get()\\n\\tif not credentials or credentials.invalid:\\n\\t\\tflow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n\\t\\tflow.user_agent = APPLICATION_NAME\\n\\t\\tif flags:\\n\\t\\t\\tcredentials = tools.run_flow(flow, store, flags)\\n\\t\\tprint ('Storing credentials to ' + credential_path)\\n\\treturn credentials\",\n \"def get_credentials():\\n credential_dir = os.getcwd()\\n credential_path = os.path.join(credential_dir,\\n 'smarking_error_check.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'client_secret_OCR.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n print(\\\"Current folder: \\\" + os.getcwd())\\n flow = client.flow_from_clientsecrets(\\n \\\"../../\\\" + CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'gmail-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatability with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'grader.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n credentials = tools.run_flow(flow, store, tools.argparser.parse_args(args=[]))\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'gmail-python-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir, 'google-photos-stats.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n credentials = tools.run_flow(flow, store, flags)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'appsactivity-python-showtime.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n print('Storing credentials to ' + credential_path)\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'admin-directory_v1-NestedGroupSync.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatability with Python 2.6\\n credentials = tools.run(flow, store)\\n print 'Storing credentials to' + credential_path\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'thejam_calendar.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'calendar-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(config['client secret file'], SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if args:\\n credentials = tools.run_flow(flow, store, args)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'sally.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'calendar-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'calendar-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'calendar-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n #home_dir = os.path.expanduser('~')\\n home_dir = os.path.expanduser('/home/pi/')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir, 'gmail-python-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'sheets.googleapis.com-python-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'sheets.googleapis.com-python-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\r\\n home_dir = os.path.expanduser('~')\\r\\n credential_dir = os.path.join(home_dir, '.credentials')\\r\\n if not os.path.exists(credential_dir):\\r\\n os.makedirs(credential_dir)\\r\\n credential_path = os.path.join(credential_dir,\\r\\n 'gmail-python-spam-filter.json')\\r\\n\\r\\n store = Storage(credential_path)\\r\\n credentials = store.get()\\r\\n if not credentials or credentials.invalid:\\r\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\r\\n flow.user_agent = APPLICATION_NAME\\r\\n if flags:\\r\\n credentials = tools.run_flow(flow, store, flags)\\r\\n else: # Needed only for compatibility with Python 2.6\\r\\n credentials = tools.run(flow, store)\\r\\n print('Storing credentials to ' + credential_path)\\r\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'gmail-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_auth_token(self):\\n creds = None\\n # The file token.pickle stores the user's access and refresh tokens,\\n # and is created automatically when the authorization flow completes\\n # for the first time.\\n if os.path.exists(self.token_path):\\n with open(self.token_path, 'rb') as token:\\n creds = pickle.load(token)\\n # If there are no (valid) credentials available, let the user log in.\\n if not creds or not creds.valid:\\n if creds and creds.expired and creds.refresh_token:\\n creds.refresh(Request())\\n else:\\n flow = InstalledAppFlow.from_client_secrets_file(\\n self.credentials_path, self.scopes)\\n creds = flow.run_local_server(port=0)\\n # Save the credentials for the next run\\n with open(self.token_path, 'wb') as token:\\n pickle.dump(creds, token)\\n return creds\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'gmail-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'gmail-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'gmail-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'gmail-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'gmail-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(args.clientSecretFile, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if args:\\n credentials = tools.run_flow(flow, store, args)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def _get_credentials(self):\\n\\n scopes = 'https://www.googleapis.com/auth/drive'\\n client_secret_file = '%s/config/client_secret.json' % PROJECT_DIR\\n application_name = 'Drive API Quickstart'\\n\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n\\n credential_path = os.path.join(credential_dir, 'drive-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(client_secret_file, scopes)\\n flow.user_agent = application_name\\n\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatability with Python 2.6\\n credentials = tools.run(flow, store)\\n\\n return credentials\",\n \"def get_credentials(self):\\n #\\n # Why is this not read from the yaml file?\\n path = Path(path_expand(self.credential_file)).resolve()\\n if not os.path.exists(path):\\n os.makedirs(path)\\n\\n credentials_path = (path / 'google-drive-credentials.json').resolve()\\n print(credentials_path)\\n\\n store = Storage(credentials_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(self.client_secret_file,\\n self.scopes)\\n flow.user_agent = self.application_name\\n #\\n # SHOUDL THE FLAGS NOT BE SET IN THE YAML FILE OR DOCOPTS OFTHE COMMAND?\\n #\\n if self.flags:\\n credentials = tools.run_flow(flow, store, self.flags)\\n\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'sheets.googleapis.com-python.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = './ignore' #os.path.expanduser('./')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'gmail-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = './ignore' #os.path.expanduser('./')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'gmail-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials(self):\\n home_dir = os.path.expanduser('~')\\n # credential_dir = os.path.join(home_dir, '.credentials')\\n credential_dir = '.credentials'\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir, 'drive-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(GoogleDocsConverter.CLIENT_SECRET_FILE, GoogleDocsConverter.SCOPES)\\n flow.user_agent = GoogleDocsConverter.APPLICATION_NAME\\n if self.flags:\\n credentials = tools.run_flow(flow, store, self.flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir, 'sheets.googleapis.com-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n credentials = tools.run_flow(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser(os.getcwd())\\n credential_dir = os.path.join(home_dir, '.credentials')\\n print(credential_dir)\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'calendar-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_creds():\\n # If modifying these scopes, delete the file token.pickle.\\n SCOPES = ['https://www.googleapis.com/auth/gmail.readonly']\\n creds = None\\n dir_pre = '../secrets'\\n # The file token.pickle stores the user's access and refresh tokens, and is\\n # created automatically when the authorization flow completes for the first\\n # time.\\n logging.debug(f\\\"searching for creds in path: {os.getcwd()}\\\")\\n if os.path.exists(os.path.join(dir_pre, 'token.pickle')):\\n with open(os.path.join(dir_pre, 'token.pickle'), 'rb') as token:\\n creds = pickle.load(token)\\n logging.info('opening token.pickle')\\n # If there are no (valid) credentials available, let the user log in.\\n if not creds or not creds.valid:\\n if creds and creds.expired and creds.refresh_token:\\n logging.info('token expired, refreshing token')\\n creds.refresh(Request())\\n else:\\n logging.info('token not found, re authenticating ')\\n flow = InstalledAppFlow.from_client_secrets_file(os.path.join(dir_pre, 'credentials.json'), SCOPES)\\n creds = flow.run_local_server(port=0)\\n # Save the credentials for the next run\\n with open(os.path.join(dir_pre, 'token.pickle'), 'wb') as token:\\n pickle.dump(creds, token)\\n\\n return creds\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'sheets.googleapis.com-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'sheets.googleapis.com-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'sheets.googleapis.com-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'sheets.googleapis.com-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(\\n credential_dir, 'sheets.googleapis.com-python-quickstart.json'\\n )\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'sheets.googleapis.com-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(resource_path(CLIENT_SECRET_FILE), SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials(self):\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'homework_logger-gmail-api.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(self.CLIENT_SECRET_FILE, self.SCOPES)\\n flow.user_agent = self.APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def getCredentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir, 'gmail-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def getCredentials(scopes):\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,'admin-directory_v1-python-quickstart.json')\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, scopes)\\n flow.user_agent = APPLICATION_NAME\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials(self):\\r\\n \\r\\n try:\\r\\n import argparse\\r\\n #flags = argparse.ArgumentParser(parents=[tools.argparser]).parse_args()\\r\\n if self.noauth == True:\\r\\n flags = tools.argparser.parse_args(args=['--noauth_local_webserver'])\\r\\n else:\\r\\n flags = tools.argparser.parse_args(args=[])\\r\\n except ImportError:\\r\\n flags = None \\r\\n \\r\\n home_dir = os.path.expanduser('~')\\r\\n credential_dir = os.path.join(home_dir, '.credentials')\\r\\n if not os.path.exists(credential_dir):\\r\\n os.makedirs(credential_dir)\\r\\n credential_path = os.path.join(credential_dir,'sheets.googleapis.com-allstarbot.json')\\r\\n\\r\\n store = Storage(credential_path)\\r\\n credentials = store.get()\\r\\n if not credentials or credentials.invalid:\\r\\n secret = Path(self.CLIENT_SECRET_FILE)\\r\\n if secret.exists():\\r\\n flow = client.flow_from_clientsecrets(self.CLIENT_SECRET_FILE, self.SCOPES)\\r\\n else:\\r\\n print(\\\"client_secret.json not found, using env vars\\\")\\r\\n if not os.environ.get('client_id') or not os.environ.get('client_secret'): \\r\\n print(\\\"env vars client_id and client_secret not found. canceling\\\")\\r\\n raise Exception(\\\"client secret error\\\")\\r\\n else:\\r\\n flow = OAuth2WebServerFlow(\\r\\n os.environ.get('client_id'),\\r\\n os.environ.get('client_secret'),\\r\\n self.SCOPES) \\r\\n \\r\\n flow.params['access_type'] = 'offline'\\r\\n flow.user_agent = self.APPLICATION_NAME\\r\\n if flags:\\r\\n credentials = tools.run_flow(flow, store, flags)\\r\\n else: # Needed only for compatibility with Python 2.6\\r\\n credentials = tools.run(flow, store)\\r\\n print('Storing credentials to ' + credential_path)\\r\\n return credentials\",\n \"def get_credentials(credentials_filename, application_name, client_secret_file, scopes):\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n credentials_filename)\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(client_secret_file, scopes)\\n flow.user_agent = application_name\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n# else: # Needed only for compatibility with Python 2.6\\n# credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def valid_credentials():\\n if 'credentials' not in flask.session:\\n return None\\n\\n credentials = client.OAuth2Credentials.from_json(\\n flask.session['credentials'])\\n\\n if (credentials.invalid or\\n credentials.access_token_expired):\\n return None\\n return credentials\",\n \"def valid_credentials():\\n if 'credentials' not in flask.session:\\n return None\\n\\n credentials = client.OAuth2Credentials.from_json(\\n flask.session['credentials'])\\n\\n if (credentials.invalid or\\n credentials.access_token_expired):\\n return None\\n return credentials\",\n \"def __create_credentials(self, scopes):\\n creds = None\\n\\n # The File token.pickle stores the user's access and refresh tokens,\\n # and is created automatically whne the flow compleates for the first time.\\n if os.path.exists('token.pickle'):\\n with open('token.pickle', 'rb') as token:\\n creds = pickle.load(token)\\n # if there are no valid credentials available, let the user log in\\n if not creds or not creds.valid:\\n if creds and creds.expired and creds.refresh_token:\\n creds.refresh(Request())\\n else:\\n flow = InstalledAppFlow.from_client_secrets_file(\\n 'credentials.json', scopes)\\n creds = flow.run_local_server(port=0)\\n # save the creds for the next run\\n with open('token.pickle', 'wb') as token:\\n pickle.dump(creds, token)\\n\\n return creds\",\n \"def get_credentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'sheets.googleapis.logSheets.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def authenticate():\\n creds = None\\n # The file token.pickle stores the user's access and refresh tokens, and is\\n # created automatically when the authorization flow completes for the first\\n # time.\\n if os.path.exists('token.pickle'):\\n with open('token.pickle', 'rb') as token:\\n creds = pickle.load(token)\\n # If there are no (valid) credentials available, let the user log in.\\n if not creds or not creds.valid:\\n if creds and creds.expired and creds.refresh_token:\\n creds.refresh(Request())\\n else:\\n flow = InstalledAppFlow.from_client_secrets_file(\\n 'google-drive-credentials.json', SCOPES)\\n creds = flow.run_local_server(port=0)\\n # Save the credentials for the next run\\n with open('token.pickle', 'wb') as token:\\n pickle.dump(creds, token)\\n\\n return creds\",\n \"def getUsrCreds(self):\\n import pickle\\n import os.path\\n from google_auth_oauthlib.flow import InstalledAppFlow\\n from google.auth.transport.requests import Request\\n\\n # If modifying these scopes, delete the file token.pickle.\\n SCOPES = ['https://www.googleapis.com/auth/calendar']\\n\\n self.creds = None\\n # The file token.pickle stores the user's access and refresh tokens, and is\\n # created automatically when the authorization flow completes for the first\\n # time.\\n if os.path.exists('token.pickle'):\\n with open('token.pickle', 'rb') as self.token:\\n self.creds = pickle.load(self.token)\\n # If there are no (valid) credentials available, let the user log in.\\n if not self.creds or not self.creds.valid:\\n if self.creds and self.creds.expired and self.creds.refresh_token:\\n self.creds.refresh(Request())\\n else:\\n self.flow = InstalledAppFlow.from_client_secrets_file(\\n 'client_secret.json', scopes = SCOPES)\\n self.creds = self.flow.run_local_server(port=0)\\n # Save the credentials for the next run\\n with open('token.pickle', 'wb') as self.token:\\n pickle.dump(self.creds, self.token)\\n\\n return self.creds\",\n \"def get_credentials(self):\\n if getattr(self, 'credentials', None):\\n return self.credentials\\n\\n scopes = settings.SCOPES\\n client_secret_file = settings.CLIENT_SECRET_FILE\\n application_name = 'Google Sheets API Python Quickstart'\\n\\n home_dir = os.path.expanduser(settings.CREDENTIALS_DIRECTORY)\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir, 'sheets.googleapis.com-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(client_secret_file, scopes)\\n flow.user_agent = application_name\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n # print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n try:\\n import argparse\\n flags = argparse.ArgumentParser(parents=[tools.argparser]).parse_args()\\n except ImportError:\\n flags = None\\n\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'appsactivity-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(GoogleGsuiteAPI.CLIENT_SECRET_FILE, GoogleGsuiteAPI.SCOPES)\\n flow.user_agent = GoogleGsuiteAPI.APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def create_credentials():\\r\\n creds = None\\r\\n # The file token.pickle stores the user's access and refresh tokens, and is\\r\\n # created automatically when the authorization flow completes for the first\\r\\n # time.\\r\\n if os.path.exists('token.pickle'):\\r\\n with open('token.pickle', 'rb') as token:\\r\\n creds = pickle.load(token)\\r\\n # If there are no (valid) credentials available, let the user log in.\\r\\n if not creds or not creds.valid:\\r\\n if creds and creds.expired and creds.refresh_token:\\r\\n creds.refresh(Request())\\r\\n else:\\r\\n flow = InstalledAppFlow.from_client_secrets_file(\\r\\n 'client_secret.json', SCOPES)\\r\\n creds = flow.run_local_server()\\r\\n # Save the credentials for the next run\\r\\n with open('token.pickle', 'wb') as token:\\r\\n pickle.dump(creds, token)\\r\\n return creds\",\n \"def get_stored_credentials(user):\\n with open(\\\"access.json\\\", \\\"r\\\") as f:\\n credentials = json.load(f)\\n user_creds = credentials[user]\\n return user_creds[\\\"access_token\\\"], user_creds[\\\"access_secret\\\"]\",\n \"def get_credentials(scopes=None, secrets=None, storage=None, *,\\n no_webserver=False):\\n scopes = Scopes.get(scopes)\\n\\n if secrets is None:\\n secrets = SECRETS\\n if storage is None:\\n storage = STORAGE\\n\\n secrets, storage = map(os.path.expanduser, (secrets, storage))\\n\\n store = file.Storage(storage)\\n creds = store.get()\\n\\n if creds is None or creds.invalid:\\n flow = client.flow_from_clientsecrets(secrets, scopes)\\n args = ['--noauth_local_webserver'] if no_webserver else []\\n flags = tools.argparser.parse_args(args)\\n creds = tools.run_flow(flow, store, flags)\\n\\n return creds\",\n \"def valid_credentials():\\n if 'credentials' not in flask.session:\\n return None\\n\\n credentials = client.OAuth2Credentials.from_json(\\n flask.session['credentials'])\\n\\n if (credentials.invalid or credentials.access_token_expired):\\n return None\\n return credentials\",\n \"def get_credentials(client_secrets='client_secrets.json',\\n scope_='https://www.googleapis.com/auth/drive',\\n redirect_uri_='http://localhost:8080'):\\n flow = client.flow_from_clientsecrets(client_secrets,\\n scope=scope_,\\n redirect_uri=redirect_uri_)\\n credentials = tools.run_flow(flow, Store(), None)\\n return credentials\",\n \"def get_credentials(account):\\n credential_dir = os.path.join(HOME_DIR, META_DIR, account, \\\"credentials\\\")\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir, 'pyDrive.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_creds(\\n user=\\\"default\\\", config=None, scope=default_scope, creds_dir=None, save=True\\n):\\n config = config or get_config()\\n try:\\n if \\\"private_key_id\\\" in config:\\n return SACredentials.from_service_account_info(config, scopes=scope)\\n\\n if not isinstance(user, str):\\n raise ConfigException(\\n \\\"Need to provide a user key as a string if not using a service account\\\"\\n )\\n\\n if creds_dir is None:\\n creds_dir = get_config_dir() / \\\"creds\\\"\\n\\n creds_file = Path(creds_dir) / user\\n\\n if creds_file.exists():\\n # need to convert Path to string for python 2.7\\n return OAuthCredentials.from_authorized_user_file(str(creds_file))\\n\\n flow = InstalledAppFlow.from_client_config(config, scope)\\n creds = flow.run_local_server(\\n host=\\\"localhost\\\",\\n port=8182,\\n authorization_prompt_message=\\\"Please visit this URL: {url}\\\",\\n success_message=\\\"The auth flow is complete; you may close this window.\\\",\\n open_browser=False,\\n )\\n\\n if save:\\n creds_data = {\\n \\\"refresh_token\\\": creds.refresh_token,\\n \\\"token_uri\\\": creds.token_uri,\\n \\\"client_id\\\": creds.client_id,\\n \\\"client_secret\\\": creds.client_secret,\\n \\\"scopes\\\": creds.scopes,\\n }\\n\\n ensure_path(creds_dir)\\n creds_file.write_text(decode(json.dumps(creds_data)))\\n\\n return creds\\n except Exception:\\n exc_info = sys.exc_info()\\n raise ConfigException(*exc_info[1:])\",\n \"def GetCredentials(self, credentials_path: str,\\n client_secrets_path: str) -> Optional[Any]:\\n scopes = ['openid', 'https://www.googleapis.com/auth/userinfo.email']\\n credentials = None\\n\\n # Load credentials file if it exists\\n if os.path.exists(credentials_path):\\n try:\\n credentials = Credentials.from_authorized_user_file(\\n credentials_path, scopes)\\n except ValueError as exception:\\n msg = f'Error loading credentials: {exception!s}'\\n self.ModuleError(msg, critical=True)\\n # Refresh credentials using existing refresh_token\\n if credentials and credentials.refresh_token:\\n self.logger.debug('Found a refresh token. Requesting new id_token...')\\n try:\\n credentials.refresh(Request())\\n except google_exceptions.RefreshError as exception:\\n self.logger.debug(f'Error refreshing credentials: {exception!s}')\\n else:\\n # No credentials file, acquire new credentials from secrets file.\\n self.logger.debug(\\n 'Could not find existing credentials. Requesting new tokens.')\\n try:\\n appflow = flow.InstalledAppFlow.from_client_secrets_file(\\n client_secrets_path, scopes)\\n except FileNotFoundError as exception:\\n msg = f'Client secrets file not found: {exception!s}'\\n self.ModuleError(msg, critical=True)\\n\\n self.logger.info(\\n 'Starting local HTTP server on localhost:8888 for OAUTH flow. '\\n 'If running dftimewolf remotely over SSH you will need to tunnel '\\n 'port 8888.')\\n appflow.run_local_server(host='localhost', port=8888, open_browser=False)\\n credentials = appflow.credentials\\n\\n # Save credentials\\n if credentials:\\n with open(credentials_path, 'w', encoding='utf-8') as token:\\n token.write(credentials.to_json())\\n\\n return credentials\",\n \"def get_credentials(commandline_flags=None):\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'drive-python-quickstart.json')\\n\\n store = oauth2client.file.Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if commandline_flags:\\n credentials = tools.run_flow(flow, store, commandline_flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials():\\n credential_dir = os.path.dirname(os.path.realpath(CLIENT_SECRET_FILE))\\n credential_path = os.path.join(\\n credential_dir, 'sheets.googleapis.com-endosys-events.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n credentials = tools.run_flow(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def acquire_oauth2_credentials():\\n if os.path.isfile(\\\"%s/cre.json\\\" % file_path):\\n f = open(\\\"%s/cre.json\\\" % file_path, \\\"r\\\")\\n credentials = client.OAuth2Credentials.from_json(f.read())\\n f.close()\\n else: \\n flow = client.flow_from_clientsecrets(\\n \\\"%s/client_secrets.json\\\" % file_path,\\n scope='https://www.googleapis.com/auth/analytics.readonly',\\n redirect_uri='urn:ietf:wg:oauth:2.0:oob')\\n auth_uri = flow.step1_get_authorize_url()\\n webbrowser.open(auth_uri)\\n auth_code = input('Enter the authentication code: ')\\n credentials = flow.step2_exchange(auth_code)\\n write_credentials(\\\"%s/cre.json\\\" % file_path, credentials)\\n return credentials\",\n \"def google_creds() -> object:\\n # If modifying these scopes, delete the file token.pickle.\\n SCOPES = ['https://www.googleapis.com/auth/drive.file',\\n 'https://www.googleapis.com/auth/drive',\\n 'https://www.googleapis.com/auth/drive.activity',\\n 'https://www.googleapis.com/auth/spreadsheets'\\n ]\\n\\n creds = None\\n # The file token.pickle stores the user's access and refresh tokens, and is\\n # created automatically when the authorization flow completes for the first\\n # time.\\n if os.path.exists('token.pickle'):\\n with open('token.pickle', 'rb') as token:\\n creds = pickle.load(token)\\n # If there are no (valid) credentials available, let the user log in.\\n if not creds or not creds.valid:\\n if creds and creds.expired and creds.refresh_token:\\n creds.refresh(Request())\\n else:\\n flow = InstalledAppFlow.from_client_secrets_file(\\n 'credentials.json', SCOPES)\\n creds = flow.run_local_server(port=0)\\n # Save the credentials for the next run\\n with open('token.pickle', 'wb') as token:\\n pickle.dump(creds, token)\\n\\n return creds\",\n \"def get_credentials(args, my_dirname):\\n\\n credential_dir = os.path.join(my_dirname, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.mkdir(credential_dir)\\n credential_path = os.path.join(credential_dir, 'sheets.googleapis.com-cotus-checker.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n try:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n credentials = tools.run_flow(flow, store, args)\\n print('Storing credentials to ' + credential_path)\\n except (oauth2client.clientsecrets.InvalidClientSecretsError, json.decoder.JSONDecodeError):\\n pass\\n return credentials\",\n \"def get_GoogleCredentials():\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'calendar-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials(data_dir_path, client_secret_file_path, scopes, application_name):\\n #home_dir = os.path.expanduser('~')\\n #credential_dir = os.path.join(home_dir, '.credentials')\\n credential_dir = os.path.join(data_dir_path, \\\".credentials\\\")\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'gmail-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(client_secret_file_path, scopes)\\n flow.user_agent = application_name\\n\\n try:\\n import argparse\\n flags = argparse.ArgumentParser(parents=[tools.argparser]).parse_args()\\n except ImportError:\\n flags = None\\n\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def get_credentials( flags=None ):\\n home_dir = os.path.expanduser('~')\\n credential_dir = os.path.join(home_dir, '.credentials')\\n if not os.path.exists(credential_dir):\\n os.makedirs(credential_dir)\\n credential_path = os.path.join(credential_dir,\\n 'drive-python-quickstart.json')\\n\\n store = Storage(credential_path)\\n credentials = store.get()\\n if not credentials or credentials.invalid:\\n flow = client.flow_from_clientsecrets(CLIENT_SECRET_FILE, SCOPES)\\n flow.user_agent = APPLICATION_NAME\\n if flags:\\n credentials = tools.run_flow(flow, store, flags)\\n else: # Needed only for compatibility with Python 2.6\\n credentials = tools.run(flow, store)\\n print('Storing credentials to ' + credential_path)\\n return credentials\",\n \"def _get_credential(self):\\n creds = None\\n\\n if os.path.exists('token.pickle'):\\n with open('token.pickle', 'rb') as token:\\n creds = pickle.load(token)\\n\\n if not creds or not creds.valid:\\n if creds and creds.expired and creds.refresh_token:\\n creds.refresh(Request())\\n else:\\n flow = InstalledAppFlow.from_client_secrets_file(\\n 'credentials.json', self.config['SCOPES'])\\n creds = flow.run_local_server(port=0)\\n # Save the credentials for the next run\\n with open('token.pickle', 'wb') as token:\\n pickle.dump(creds, token)\\n\\n self.service = build('drive', 'v3', credentials=creds)\",\n \"def get(self):\\n self._lock.acquire()\\n try:\\n f = open(self._filename, 'r')\\n credentials = pickle.loads(f.read())\\n f.close()\\n credentials.set_store(self.put)\\n except:\\n credentials = None\\n self._lock.release()\\n\\n return credentials\",\n \"def get_creds(\\n config: Config=default):\\n config_path = config.credential_path\\n scopes = config.scopes\\n\\n logger.info('loading token')\\n logger.debug(f'config_path: {config_path}')\\n config_path = Path(config_path).expanduser()\\n store = file.Storage(config_path/'token.json')\\n creds = store.get()\\n\\n if not creds or creds.invalid:\\n # Ask the user to give the correct permissions.\\n logger.info('loading credentials')\\n flow = client.flow_from_clientsecrets(\\n config_path/'client_id.json',\\n scopes)\\n\\n arguments = sys.argv\\n sys.argv = sys.argv[0:1]\\n # This line is why we need to remove the arguments from sys.argv\\n # If you find a better way to get it to work, i'm buying it\\n creds = tools.run_flow(flow, store)\\n sys.argv = arguments\\n\\n return creds\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7571305","0.7356556","0.71548086","0.711909","0.70713574","0.7026156","0.6991323","0.6962775","0.69490343","0.6940299","0.6935988","0.6906218","0.6900573","0.68998826","0.6857519","0.68309605","0.6792369","0.6785002","0.67753786","0.67753786","0.67753786","0.67753786","0.67753786","0.6775053","0.6754867","0.6751576","0.6751576","0.67427343","0.67382884","0.67332715","0.6701791","0.6699462","0.6689531","0.66893166","0.66652244","0.6659061","0.66449726","0.663316","0.66093534","0.65981686","0.65936434","0.65936434","0.6572427","0.65689546","0.65689546","0.65643436","0.65598214","0.6557007","0.65536606","0.65536606","0.65536606","0.65536606","0.6546328","0.6537979","0.6518682","0.6517348","0.6512031","0.6512031","0.6488877","0.64835495","0.64744055","0.64728","0.6470099","0.6470099","0.6470099","0.6470099","0.6454543","0.64482","0.6436911","0.64348835","0.64145434","0.6409216","0.6384664","0.63658065","0.63658065","0.6360874","0.6359657","0.63502645","0.63451743","0.6317901","0.63168526","0.6290881","0.6287336","0.628644","0.6278486","0.6274914","0.62706","0.6250182","0.6206144","0.6167895","0.6146476","0.6083926","0.60826224","0.60581505","0.6050213","0.6046963","0.60349125","0.60343176","0.6006201","0.594635"],"string":"[\n \"0.7571305\",\n \"0.7356556\",\n \"0.71548086\",\n \"0.711909\",\n \"0.70713574\",\n \"0.7026156\",\n \"0.6991323\",\n \"0.6962775\",\n \"0.69490343\",\n \"0.6940299\",\n \"0.6935988\",\n \"0.6906218\",\n \"0.6900573\",\n \"0.68998826\",\n \"0.6857519\",\n \"0.68309605\",\n \"0.6792369\",\n \"0.6785002\",\n \"0.67753786\",\n \"0.67753786\",\n \"0.67753786\",\n \"0.67753786\",\n \"0.67753786\",\n \"0.6775053\",\n \"0.6754867\",\n \"0.6751576\",\n \"0.6751576\",\n \"0.67427343\",\n \"0.67382884\",\n \"0.67332715\",\n \"0.6701791\",\n \"0.6699462\",\n \"0.6689531\",\n \"0.66893166\",\n \"0.66652244\",\n \"0.6659061\",\n \"0.66449726\",\n \"0.663316\",\n \"0.66093534\",\n \"0.65981686\",\n \"0.65936434\",\n \"0.65936434\",\n \"0.6572427\",\n \"0.65689546\",\n \"0.65689546\",\n \"0.65643436\",\n \"0.65598214\",\n \"0.6557007\",\n \"0.65536606\",\n \"0.65536606\",\n \"0.65536606\",\n \"0.65536606\",\n \"0.6546328\",\n \"0.6537979\",\n \"0.6518682\",\n \"0.6517348\",\n \"0.6512031\",\n \"0.6512031\",\n \"0.6488877\",\n \"0.64835495\",\n \"0.64744055\",\n \"0.64728\",\n \"0.6470099\",\n \"0.6470099\",\n \"0.6470099\",\n \"0.6470099\",\n \"0.6454543\",\n \"0.64482\",\n \"0.6436911\",\n \"0.64348835\",\n \"0.64145434\",\n \"0.6409216\",\n \"0.6384664\",\n \"0.63658065\",\n \"0.63658065\",\n \"0.6360874\",\n \"0.6359657\",\n \"0.63502645\",\n \"0.63451743\",\n \"0.6317901\",\n \"0.63168526\",\n \"0.6290881\",\n \"0.6287336\",\n \"0.628644\",\n \"0.6278486\",\n \"0.6274914\",\n \"0.62706\",\n \"0.6250182\",\n \"0.6206144\",\n \"0.6167895\",\n \"0.6146476\",\n \"0.6083926\",\n \"0.60826224\",\n \"0.60581505\",\n \"0.6050213\",\n \"0.6046963\",\n \"0.60349125\",\n \"0.60343176\",\n \"0.6006201\",\n \"0.594635\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6240862"},"document_rank":{"kind":"string","value":"88"}}},{"rowIdx":88593,"cells":{"query":{"kind":"string","value":"Converts encoded sequences into an array with sequence strings"},"document":{"kind":"string","value":"def decode_one_hot(encoded_sequences):\n if len(encoded_sequences.shape) == 3:\n s = encoded_sequences.shape\n encoded_sequences = encoded_sequences.reshape(1, s[0], s[1], s[2])\n\n #num_samples, _, _, seq_length = np.shape(encoded_sequences)\n _, num_samples, _, seq_length = np.shape(encoded_sequences)\n\n sequence_characters = np.chararray((num_samples, seq_length))\n sequence_characters[:] = 'N'\n for i, letter in enumerate(['A', 'C', 'G', 'T']):\n letter_indxs = (encoded_sequences[:, :, i, :] == 1).squeeze()\n try:\n sequence_characters[letter_indxs] = letter\n # in case there is only one sequence, letter_indxs will be a row vector\n except IndexError:\n sequence_characters[:, letter_indxs] = letter\n # return 1D view of sequence characters\n return sequence_characters.view('S%s' % (seq_length)).ravel()"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def decode_sequence(self, sequence=list) -> str:\n try:\n out = []\n for word in sequence:\n out.append(self.decode(word))\n return(out)\n except Exception as error:\n print(f\"Error: self.decode_sequence({sequence}) -> {error}\")","def seq_to_array_seq(seq, array_len=60):\n if len(seq) > array_len:\n raise Error('Sequence is too long for the array. Max of %d but %s is %d.' %\n (array_len, seq, len(seq)))\n return '%s%s' % (seq, 'T' * (array_len - len(seq)))","def encode(self, seq):","def _seq2vec(seq):\n vec = np.zeros(len(seq), dtype=int)\n for aai, aa in enumerate(seq):\n vec[aai] = AA2CODE[aa]\n return vec","def code_to_sequences( self, ucode ):\n\t\t\n\t\tassert isinstance( ucode, unicode ), 'ucode must be unicode string!' \n\t\t\n\t\tfor uchar in ucode:\n\t\t\tif not( uchar in self._char39 ):\n\t\t\t\traise Barcode39Error( '%s char is not listed in Barcode39 characters [0..9,A..Z,space,9,-,.,$,/,+,%]' )\n\n\t\tresult = []\n\t\tfor uchar in ucode:\n\t\t\tresult = result + self.char_to_seq(uchar) \n\t\t\t\n\t\treturn result","def decode(self, seq):\n return [ self.rev_vocab[int(el)] for el in seq ]","def encoded(self):\n text, chars = self.chars()\n int2char = dict(enumerate(chars))\n char2int = {ch: ii for ii, ch in int2char.items()}\n encoded = np.array([char2int[ch] for ch in text])\n return encoded","def seqs_to_strs(self,id_array,remove_pads=True):\n l = self.seqs_to_toks(id_array,remove_pads)\n return [' '.join(i) for i in l]","def binary_to_seq():\n bin_seq, dico_binary, comp_seq, file_comp = utf8_to_binary()\n \n #for each binary value associate the corresponding letter (key) \n #according to the dictionnary \n dna_seq = \"\"\n reading_binary = \"\"\n for value in bin_seq:\n reading_binary += value\n for letter, code in dico_binary.items():\n if code == reading_binary:\n dna_seq += letter\n reading_binary = \"\"\n break\n \n #print(dna_seq, bin_seq, comp_seq, file_comp)\n return dna_seq, bin_seq, comp_seq, file_comp","def split_sequence(self, sequence):\n\t\treturn [char for char in sequence]","def decode_sequence(sequence, encoding_to_item):\n return_sequence = []\n\n for i, itemset in enumerate(sequence):\n decoded_itemset = set()\n for item in itemset:\n decoded_itemset.add(encoding_to_item[item])\n return_sequence.append(decoded_itemset)\n return return_sequence","def array(self):\n return list(self.sequence)","def _rc_seq(self):\n logger.debug(\"Extracting sequences on the reverse strand\")\n sequences_rc = []\n table = str.maketrans({'a': 't', 'c': 'g', 'g': 'c', 't': 'a',\n 'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'})\n for sequence in self.sequences:\n sequences_rc.append(sequence.translate(table)[::-1])\n self.sequences_rc = sequences_rc","def _seq2vec(seq):\n seq=_substitute_opening_gap_char(seq)\n mapper = dict([(r, i) for i, r in enumerate(aalist)])\n naa = len(seq)\n naa_types = len(aalist)\n vec = np.zeros((naa, naa_types))\n for i, res in enumerate(list(seq)):\n ind = mapper[res]\n vec[i, ind] = 1.\n return vec","def to_seq (value):\n if not value:\n return []\n\n if isinstance (value, str):\n return [value]\n\n else:\n return value","def sequence_encoding(sequence, str_to_idx):\n sequence_of_indexes = [str_to_idx[element] for element in sequence]\n return torch.tensor(sequence_of_indexes, dtype=torch.long)","def smiles_to_seq(self, smiles):\n smiles_len = len(smiles)\n seq = [0]\n keys = self.char_dict.keys()\n i = 0\n while i < smiles_len:\n # Skip all spaces\n if smiles[i:i + 1] == ' ':\n i = i + 1\n # For 'Cl', 'Br', etc.\n elif smiles[i:i + 2] in keys:\n seq.append(self.char_dict[smiles[i:i + 2]])\n i = i + 2\n elif smiles[i:i + 1] in keys:\n seq.append(self.char_dict[smiles[i:i + 1]])\n i = i + 1\n else:\n raise ValueError('character not found in dict')\n for i in range(self.seq_length - len(seq)):\n # Padding with '_'\n seq.append(self.char_dict['_'])\n return np.array(seq)","def ascii_to_numpy(ascii_diagram, as_bytes=True):\n ascii_diagram = [list(i) for i in ascii_diagram]\n ascii_diagram = np.array(ascii_diagram)\n v_to_bytes = np.vectorize(to_bytes)\n return v_to_bytes(ascii_diagram) if as_bytes else ascii_diagram","def convert2seq(self,seq_int):\n\t\treturn [self.aminoacids[i] for i in seq_int]","def decode_python(self, encoded_chunks: np.ndarray) -> np.ndarray:\n encoded_chunks_reshaped = encoded_chunks.reshape((-1, 1))\n encoded_chunks_tiles = np.tile(\n encoded_chunks_reshaped, [1, self._dtype_size_bytes]\n )\n encoded_chunks_bytes_shifted = np.right_shift(\n encoded_chunks_tiles, self._bit_lengths\n )\n encoded_chunks_bytes = encoded_chunks_bytes_shifted % 2 ** (\n self._utf8_size_bits\n )\n int_to_char_fn = lambda x: (dict(enumerate(self._int_to_byte_map)).get(x))\n\n # Added `otypes=(np.string_,)` as an additional arg to np.vectorize to avoid\n # numpy crashes with empty strings (not able to identify the type).\n decoded_chars = np.vectorize(int_to_char_fn, otypes=(np.string_,))(\n encoded_chunks_bytes\n )\n decoded_chars_reshaped = decoded_chars.reshape(-1, self._max_length)\n decoded_strings = np.apply_along_axis(\n lambda r: r.tobytes(), arr=decoded_chars_reshaped, axis=1\n )\n\n return decoded_strings","def stringToUtf8Array(input):\n if _haveTypeUnicode:\n # Assume this is Python 2.\n if type(input) is str:\n # Convert the raw string to an int array.\n return map(ord, input)\n elif type(input) is unicode:\n # In Python 2, the result of encode is a str, so convert to int array.\n return map(ord, input.encode('utf-8'))\n else:\n return input\n else:\n if type(input) is str:\n return input.encode('utf-8')\n else:\n return input","def get_str_arrays(self):\n return self._fin.readline().strip('\\n').strip(' ').split(' ')","def char_to_seq( self, uchar ):\n\t\t\n\t\tlstParts = self._char39[ uchar ].split( '+' ) # [ 'nb', 'ns', 'nb', ... ]\n\t\t# Force evaluation with globals definition and local object definition (say on self.x)\n\t\treturn [ eval( '_'+code, globals(), self.__dict__ ) for code in lstParts ]","def read_fasta_sequences_to_str(filename):\n with open(filename) as f:\n lines = [line.strip() for line in f.readlines()]\n sequences = []\n text = ''\n\n for line in lines:\n if line[0] == '>':\n if len(text) > 0:\n sequences.append(text)\n text = ''\n else:\n if len(line):\n text += line\n if len(text) > 0:\n sequences.append(text)\n\n return sequences","def s2a(s):\n return np.array(list(s))","def bytes2matrix(text):\n return [list(text[i:i+4]) for i in range(0, len(text), 4)]","def encode(data, code_book):\n return np.array([int(chunk, 2).to_bytes(-(-len(chunk) // 8), byteorder='big') for chunk in\n map(lambda tup: ''.join(tup), (lambda iterable: zip_longest(*[iter(iterable)] * 8, fillvalue=''))(\n ''.join(map(lambda x: code_book[x], data))))])","def encode(self, sequence):\n fwd_states, bwd_states = self.encode_fwd_bwd(sequence)\n bwd_states = bwd_states[::-1]\n return [dy.concatenate([fwd_states[i], bwd_states[i]]) for i in range(len(fwd_states))]","def bs_to_array(bs):\n return np.array([int(x) for x in bs], dtype=\"int8\")","def encode_sequences(letter_sequences, symbol_to_idx, sequence_len, pad_symbol=None, go_symbol=None,\n pad_beginning=True, reverse=False, ):\n\n pad_idx = symbol_to_idx[pad_symbol]\n\n if go_symbol is None:\n go_idx = None\n else:\n go_idx = symbol_to_idx[go_symbol]\n\n assert sequence_len >= len(max(letter_sequences, key=len)) + 0 if go_idx is None else 1\n\n encoded_sequences = np.full((len(letter_sequences), sequence_len),\n fill_value=pad_idx,\n dtype=np.int32)\n\n for i, sequence in enumerate(letter_sequences):\n\n idxs = [symbol_to_idx[symbol] for symbol in sequence]\n\n if reverse:\n idxs = idxs[::-1]\n\n # Insert the idx of the GO symbol to the end of the sequence.\n if go_idx is not None:\n idxs.append(go_idx)\n\n if pad_beginning:\n encoded_sequences[i, -len(idxs):] = idxs\n else:\n encoded_sequences[i, :len(idxs)] = idxs\n\n return encoded_sequences","def decode_chain_list(in_bytes):\n bstrings = numpy.frombuffer(in_bytes, numpy.dtype('S' + str(mmtf.utils.constants.CHAIN_LEN)))\n return [s.decode(\"ascii\").strip(mmtf.utils.constants.NULL_BYTE) for s in bstrings]","def transform(self, y):\n encode_y = []\n for l in y:\n encode_y.append(self.encode_dict[l])\n\n return np.array(encode_y)","def decode(self, encoded):\n decoded = []\n for codes in encoded:\n tmp = []\n for code in codes:\n try:\n word = self.vocab[code]\n tmp.append(word)\n except:\n tmp.append(self.unk_token)\n decoded.append(tmp)\n return decoded","def kmer_seq_to_filters(kmers):\n\treturn np.concatenate([dna_string_to_array(s) for s in kmers])","def prune_decoded_seqs(seqs):\r\n out = []\r\n for s in seqs:\r\n if EOS in s:\r\n idx = s.index(EOS)\r\n out += [s[:idx]]\r\n else:\r\n out += [s]\r\n return out","def sents_to_seqs(sentences):\r\n list_of_sent = []\r\n list_of_seq = []\r\n list_of_labels = []\r\n for i in range(len(sentences)):\r\n for j in range(len(sentences[i])):\r\n if j + 4 < len(sentences[i]):\r\n list_of_sent.append(sentences[i][j])\r\n list_of_sent.append(sentences[i][j + 1])\r\n list_of_sent.append(sentences[i][j + 2])\r\n list_of_sent.append(sentences[i][j + 3])\r\n label = sentences[i][j + 4]\r\n list_of_labels.append(label)\r\n list_of_seq.append(list_of_sent)\r\n list_of_sent = []\r\n\r\n return list_of_seq, list_of_labels","def parse_sequences(sequences, max_order):\n return [get_transition_matrix(sequences, order) for order in xrange(max_order + 1)]","def transform_seq(seq):\n # TODO add character checking based on ASCII code\n return \"\".join(\"\" if aa in msa_characters else aa for aa in seq)","def back_translate(seq):\n\n base_nucleotide_list = []\n for i in seq:\n res = __get_key(i,CodonTable)\n base_nucleotide_list.append(res)\n return ''.join(base_nucleotide_list)","def _text_array(text):\n text = \"<mxit/>\" + text\n \n ar = map(ord, text)\n pads = 16 - (len(ar) % 16)\n ar += [0] * (pads-1)\n ar.append(pads)\n \n return ar","def binary_to_utf8():\n added, binary_seq, seq, file = binary_conversion()\n \n comp_seq = \"\"\n for bit in range(0, len(binary_seq), 8):\n #cut the sequence each 8 bits\n byte = binary_seq[bit:bit+8]\n code = int(byte, 2)\n #transforms 8 bits into a single character coded in utf-8\n comp_seq += chr(code)\n\n return added, comp_seq, binary_seq, seq, file","def array_encode(s):\n return np.frombuffer(s.encode('utf32'), dtype=np.int32, offset=4)","def convert_to_strings(self, sequences, sizes=None, remove_repetitions=False, return_offsets=False):\n strings = []\n offsets = [] if return_offsets else None\n for x in xrange(len(sequences)):\n seq_len = sizes[x] if sizes is not None else len(sequences[x])\n string, string_offsets = self.process_string(sequences[x], seq_len, remove_repetitions)\n strings.append([string]) # We only return one path\n if return_offsets:\n offsets.append([string_offsets])\n if return_offsets:\n return strings, offsets\n else:\n return strings","def get_sequence_list(files):\n sequence_list = []\n for i in range(0,len(files)):\n with open(files[i], \"r\") as fasta_file:\n fasta_seq_all = fasta_file.read()\n \n\n fasta_seq_all = fasta_seq_all.split(\">\")\n\n for j in range(0, len(fasta_seq_all)):\n fasta_seq = fasta_seq_all[j]\n if len(fasta_seq) > 2:\n \n fasta_seq = fasta_seq.splitlines()\n label = _format_label(files[i], fasta_seq.pop(0))\n format_fasta_seq = []\n for k in range(0,len(fasta_seq)):\n try:\n if fasta_seq[k][0] == \"\\n\":\n break\n \n format_fasta_seq.append(fasta_seq[k])\n except:\n break\n format_fasta_seq = \"\".join(format_fasta_seq)\n format_fasta_seq.strip()\n if len(format_fasta_seq) > 2:\n sequence_list.append(Sequence(format_fasta_seq, label))\n \n return sequence_list","def convert_to_strings(self, sequences, sizes=None, remove_repetitions=False, return_offsets=False):\n strings = []\n offsets = [] if return_offsets else None\n for x in range(len(sequences)):\n seq_len = sizes[x] if sizes is not None else len(sequences[x])\n string, string_offsets = self.process_string(sequences[x], seq_len, remove_repetitions)\n strings.append([string]) # We only return one path\n if return_offsets:\n offsets.append([string_offsets])\n if return_offsets:\n return strings, offsets\n else:\n return strings","def texts_to_sequences(self, targets=list) -> list:\n try:\n out = []\n for target in targets:\n out.append(self.encode_sentence(target))\n return(out)\n except Exception as error:\n print(f\"Error: self.texts_to_sequences([...]) -> {error}\")","def sequence(self):\n\n\t\tseq = \"\"\n\t\tfor chain in self.chain:\n\t\t\tfor res in chain.residue:\n\t\t\t\tseq += res.aa1()\n\n\t\treturn seq","def construct_sequence_list(self):\n return list(self.iter_sequence())","def fasta_seqs(file_name):\n list = []\n with open('../test_files/' + file_name, 'r') as infile:\n text = infile.read()\n seqs = text.split('>')\n for seq in seqs:\n try:\n x = seq.split('\\n', 1)\n # sequence will be stored in x[1], and i am removing nextline '\\n' characters that comes with it.\n list.append(x[1].replace('\\n', ''))\n except:\n pass\n return list","def sequence_to_list_ids(sequence, vocab):\n pass","def fasta_path_to_seqs(fasta_path, codon_table=False, codon_alphabet=False):\n seqs = []\n for record in SeqIO.parse(fasta_path, \"fasta\"):\n seqs.append(record)\n return seqs","def seq2Vec(sequences):\r\n global dict_words_n_vectors\r\n for sent in sequences:\r\n for i in range(len(sent)):\r\n if sent[i] in dict_words_n_vectors:\r\n sent[i] = dict_words_n_vectors[sent[i]]\r\n else:\r\n sent[i] = np.zeros(300)\r\n return np.array(sequences, dtype=\"float32\")","def test_ModelRnaCodonSequence(self):\n r = ArrayRnaCodonSequence(\"UUUCGU\")\n self.assertEqual(str(r), \"UUUCGU\")\n self.assertEqual(r._data, array([0, 28]))\n self.assertEqual(str(r.to_rna()), \"UUUCGU\")\n self.assertEqual(str(r.to_dna()), \"TTTCGT\")","def all_unambiguous(sequence_str):\n result = [[]]\n for c in sequence_str:\n result = [i + [a] for i in result\n for a in _AMBIGUOUS_MAP.get(c, c)]\n return [''.join(i) for i in result]","def prune_decoded_seqs(seqs):\n out = []\n for s in seqs:\n if constant.EOS in s:\n idx = s.index(constant.EOS_TOKEN)\n out += [s[:idx]]\n else:\n out += [s]\n return out","def convert_to_sequence(texts, tokenizer, max_length):\n fitted_tokenizer = tokenizer\n vectorized_text = fitted_tokenizer.texts_to_sequences(texts)\n\n # pad sequences\n vectorized_text = sequence.pad_sequences(vectorized_text, maxlen=max_length)\n\n return vectorized_text","def create_seqeunce_helper(i, text, dsl, char_count, char_to_n, extra, length = seq_length):\n\n seq_int = [] # Sequence mapped to integers\n output_seq = np.zeros((length, char_count)) # Output sequence which will become one item in input array \n\n # Get the next sequence and map its characters to integers\n for v in text[i * length + extra : (i + 1) * length + extra]:\n # If the seed_text is missing a character we append 0\n if v in char_to_n:\n seq_int.append(char_to_n[v])\n else:\n seq_int.append(0)\n\n # For character in sequence\n for j in range(length):\n # Set column corrpsonding to that character to 1\n output_seq[j][seq_int[j]] = 1.0 \n\n return output_seq","def arrays_to_sequences(token_list_iterable, sequence_length=2049):\n accum = []\n for l in token_list_iterable:\n accum.extend(l)\n\n if len(accum) > sequence_length:\n chunks = split_list(accum, sequence_length)\n yield from chunks[:-1]\n accum = chunks[-1]\n\n if len(accum) > 0:\n yield accum","def decode(e):\n return sum([length * [item] for length,item in e],[])","def readSequences(lines):\n seqs = []\n label = None\n seq_lines = []\n for line in lines:\n line = line.strip() # strip off white space\n if not line: # skip empty lines\n continue\n if line.startswith(';'): # ignore comment lines\n continue\n # check for start of next sequence:\n if line.startswith('>'): # label line\n # first, store the previous sequence if we had one:\n if seq_lines:\n seqs.append(Sequence(label, ''.join(seq_lines)))\n seq_lines = []\n # get the label (name) for the next sequence\n label = line[1:].strip()\n else:\n # collect all lines with sequence information for this sequence:\n seq_lines.append(line)\n # take care of the last sequence in the file\n seqs.append(Sequence(label, ''.join(seq_lines)))\n return seqs","def decode(self, s):\n i = 0\n strs = []\n while i < len(s):\n l = int(s[i:i+8], 16)\n strs.append(s[i+8:i+8+l])\n i += 8+l\n return strs","def seqs_to_ids(seqs, char_to_id, max_len=20):\n all_seqs = []\n\n # Turn a list of names into a 2d padded array of token ids\n for text in seqs:\n if len(text) != 0:\n all_text = []\n for word in text:\n all_text.append(char_to_id.get(word))\n\n all_seqs.append(all_text)\n final_all_seqs = np.zeros((len(all_seqs), max_len))\n\n for idx, row in enumerate(all_seqs):\n if len(row) >= max_len:\n final_all_seqs[idx, :max_len] += row[:max_len]\n else:\n final_all_seqs[idx, :len(row)] += row\n print('Shape of data tensor:', final_all_seqs.shape)\n\n return final_all_seqs","def build_sequence(data: Any):\n if isinstance(data, (bytearray, bytes)):\n data = data.decode()\n if isinstance(data, str):\n data = data.split(',')\n literals = []\n numeric = []\n for item in filter(None, data):\n if str(item).isdigit():\n numeric.append(int(item))\n continue\n if ':' in item:\n literals.append(item)\n elif isinstance(item, (tuple, set, list)):\n return build_sequence(item)\n else:\n raise Exception(item)\n return ','.join(literals + build_numeric_sequence(numeric))","def string_to_array(self):\n temp_map = copy.deepcopy(self.map.replace(\" \", \"\"))\n map_list = [[a for a in row] for row in temp_map.splitlines()]\n\n # Checks that all lines are of equal length\n for line in map_list:\n for index in range(len(map_list)):\n if len(map_list[index]) == len(line):\n continue\n else:\n raise SyntaxError(\"Island geography multi-line string \"\n \"must have lines of same length.\")\n map_arr = np.array(map_list)\n\n # Checks that there are only 'O's at the edges.\n edge = []\n edge += list(map_arr[0, :])\n edge += list(map_arr[-1, :])\n edge += list(map_arr[1:-1, 0])\n edge += list(map_arr[1:-1, -1])\n if set(edge) == {'O'}:\n pass\n else:\n raise SyntaxError(\"Island geography multi-line string \"\n \"must have 'O' around the edges. \")\n\n return map_arr","def encodings(self) -> list[int]:\n pass","def get_seq(self): # -> list[Unknown]:\n ...","def build_seq2seq(self, corpus):\n self.dataset = [[self.encode(message), self.encode(reply)] for message, reply in corpus]","def from_ascii(s):\n\treturn numpy.array(\n\t\t[\n\t\t\tord(c)\n\t\t\tfor c in s\n\t\t],\n\t\tdtype=numpy.uint8\n\t)","def string_encoder(string: str) -> List[bytes]:\n return [w.encode(\"utf-8\") for w in string.split()]","def decode(lst, typecode ):\n a = array.array( typecode )\n for n,c in lst: \n a.extend( array.array( typecode, (c,) * n ) )\n return a","def create_sequences(text, sequence_length, step):\n sequences = []\n labels = []\n for i in range(0, len(text) - sequence_length, step):\n sequences.append(text[i: i + sequence_length])\n labels.append(text[i + sequence_length])\n return sequences, labels","def tokenize(self, sequence: str) -> List[str]:\n raise NotImplementedError","def create_sequences(data, seq_length):\r\n xs = []\r\n ys = []\r\n for i in range(len(data) - seq_length - 1):\r\n # Create a sequence of features\r\n x = data[i:(i + seq_length)]\r\n # Take the next value as a target\r\n y = data[i + seq_length]\r\n # Append to lists\r\n xs.append(x)\r\n ys.append(y)\r\n # Convert to ndarrays and return\r\n return np.array(xs), np.array(ys)","def encode_sequence(text: List[str], vocab: Dict) -> Sequence[int]:\n return [vocab[ngram] if ngram in vocab else vocab[\"<UNK>\"] for ngram in text]","def get_sequence_coder(specs):\n\n def not_sequence(v):\n return v == tf.string or isinstance(v, tf.io.FixedLenFeature)\n\n sequence_keys = [k for k, v in specs.items() if not not_sequence(v)]\n return serialization.SequenceCoder(specs=specs, sequence_keys=sequence_keys)","def text_to_sequence(text, cmudict):\n text_seq = parse_text(text, cmudict)\n id_seq = [symbol_to_id[s] if s in symbol_to_id else symbol_to_id[_unk] for s in text_seq]\n\n return id_seq","def EncodeAndPad(srcs: typing.List[str], padded_length: int,\n atomizer) -> np.array:\n seqs = [atomizer.AtomizeString(src) for src in srcs]\n assert max(len(seq) for seq in seqs) <= padded_length\n pad_val = atomizer.vocab_size\n encoded = np.array(\n sequence.pad_sequences(seqs, maxlen=padded_length, value=pad_val))\n return np.vstack([np.expand_dims(x, axis=0) for x in encoded])","def sequence(self, field):\n if self._writer._buffer == deque([]):\n raise RuntimeError(\"Writer buffer is empty.\")\n if not isinstance(field, str):\n raise TypeError(\"<field> has to be string.\")\n loc = field.split(\".\")\n N = len(self._writer._buffer)\n ret = []\n for i in range(N):\n A = np.array(_getvaluefrombuffer(self._writer._buffer[i], loc))\n if A.shape == (1,):\n ret.append(A[0])\n else:\n ret.append(A)\n return np.array(ret)","def decode(self, labels):\n if len(labels.shape) == 1:\n return self.sp.DecodeIds([int(l) for l in labels])\n\n sentences = list()\n for batch in labels:\n sentence = str()\n for label in batch:\n sentence = self.sp.DecodeIds([int(l) for l in label])\n sentences.append(sentence)\n return sentences","def process(self, example: str) -> List[torch.Tensor]:\n return torch.tensor(self._tokenizer.encode(example, max_length=self.max_seq_len))","def format_seq_content(seq_str, out_format):\n sequences = []\n with tempfile.TemporaryFile(mode='w+') as fp:\n fp.write(seq_str)\n fp.seek(0)\n for record in SeqIO.parse(fp, out_format):\n sequences.append(record)\n return sequences","def get_seqs(in_fpath):\n f = open(in_fpath, 'r')\n csvread = csv.reader(f)\n seqs = [str(row) for row in csvread]\n seq1 = re.sub('[^A-Z]+', \"\", seqs[0])\n seq2 = re.sub('[^A-Z]+', \"\", seqs[1])\n return seq1, seq2","def encoding_ids(self):\n # type: () -> list[string_types]\n return self._encoding_ids","def test_regular_to_model(self):\n r = RNA.make_seq(\"AAA\", name=\"x\")\n s = RNA.make_array_seq(r)\n self.assertEqual(str(s), \"AAA\")\n self.assertEqual(s.moltype, RNA)\n self.assertEqual(s.name, \"x\")","def _sequences_to_new_records(sequences):\n if isinstance(sequences, dict):\n sequences = list(sequences.items())\n records = []\n for seq in sequences:\n if hasattr(seq, \"id\"):\n records.append(deepcopy(seq))\n else:\n name, seq = seq\n records.append(\n sequence_to_biopython_record(seq, id=name, name=name)\n )\n return records","def string_to_array(arg):\n\n res = arg.replace('[', '').replace(']', '').replace(',', '')\n return np.array(res.split(' '), dtype=np.int8)","def buildTrainingSequences(voc, maxlen=50, step=3):\n \n text, sym_indices, _ = voc\n sentences = []\n next_syms = []\n \n syms = set(text) # unique symbols (chars or words)\n \n for i in range(0, len(text) - maxlen, step):\n sentences.append(text[i: i + maxlen])\n next_syms.append(text[i + maxlen])\n print('nb sequences:', len(sentences))\n \n X = np.zeros((len(sentences), maxlen), dtype=np.int)\n y = np.zeros((len(sentences), len(syms)), dtype=np.bool)\n\n for i, sentence in enumerate(sentences):\n for j, sym in enumerate(sentence):\n X[i,j] = sym_indices[sym] \n \n y[i, sym_indices[next_syms[i]]] = 1 # one-hot enconding\n\n return (X,y)","def getSequence(resnames):\n\n get = AAMAP.get\n return ''.join([get(rn, 'X') for rn in resnames])","def decodeUtf8(self, arrayBuffer):","def decodeUtf8(self, arrayBuffer):","def bipa(sequence):\n return [_token2clts(segment)[0] for segment in sequence]","def _batch_encode(self, text: List[str]) -> List[List[str]]:\n token_ids: List[List[int]] = self.bert_model.batch_encode([t.strip() for t in text])\n tokens_ids_str: List[List[str]] = [[str(t) for t in token_id] for token_id in token_ids]\n return tokens_ids_str","def translate(self, sequences):\n return [self.vocab.translate(t) for t in sequences]","def decode (self, s):\n if s == \"null\": return []\n return s.split(chr(257))","def to_char_array(s):\n if type(s) != bytes:\n raise ValueError('Input to to_char_array function should be in bytes')\n char_array = []\n tokens = s.split(b' ')\n for token in tokens:\n char_array.append(ord(' '))\n if isemoji(token):\n char_array.append(token)\n continue\n if token in [b'!url', b'@user']:\n char_array.append(token)\n continue\n for c in token:\n char_array.append(c)\n print(char_array)\n return char_array[1:]","def FormatSeq(X):\n return [v.split(\"-\")[0] for v in X[\"Sequence\"]]","def i(self):\n return np.array(self._sequence)","def convert_one_hot_encoded_cards_to_str_encoded_list(cards: np.ndarray) -> List[str]:\n return [card_strings[i] for i in np.flatnonzero(cards)]","def generate_sequence_data_for_LSTM(complete_text_enumerated):\n pattern_sequence = []\n pattern_targets = []\n for i in range(0, len(complete_text_enumerated)-WINDOW_LENGTH):\n temp_pattern = complete_text_enumerated[i:i+WINDOW_LENGTH]\n temp_pattern_target = complete_text_enumerated[i+WINDOW_LENGTH]\n pattern_sequence.append(temp_pattern)\n pattern_targets.append(temp_pattern_target)\n num_patterns = len(pattern_sequence)\n X = np.reshape(pattern_sequence, (num_patterns, WINDOW_LENGTH, 1))\n y = np_utils.to_categorical(pattern_targets)\n return [X, y]","def to_sequence(self):\n queue = [self.root]\n seq_k = []\n seq_v = []\n\n while queue:\n res = queue.pop(0)\n seq_k.append(res.key)\n seq_v.append(res.payload)\n if res.hasLeftChild():\n queue.append(res.leftChild)\n if res.hasRightChild():\n queue.append(res.rightChild)\n\n return seq_k, seq_v"],"string":"[\n \"def decode_sequence(self, sequence=list) -> str:\\n try:\\n out = []\\n for word in sequence:\\n out.append(self.decode(word))\\n return(out)\\n except Exception as error:\\n print(f\\\"Error: self.decode_sequence({sequence}) -> {error}\\\")\",\n \"def seq_to_array_seq(seq, array_len=60):\\n if len(seq) > array_len:\\n raise Error('Sequence is too long for the array. Max of %d but %s is %d.' %\\n (array_len, seq, len(seq)))\\n return '%s%s' % (seq, 'T' * (array_len - len(seq)))\",\n \"def encode(self, seq):\",\n \"def _seq2vec(seq):\\n vec = np.zeros(len(seq), dtype=int)\\n for aai, aa in enumerate(seq):\\n vec[aai] = AA2CODE[aa]\\n return vec\",\n \"def code_to_sequences( self, ucode ):\\n\\t\\t\\n\\t\\tassert isinstance( ucode, unicode ), 'ucode must be unicode string!' \\n\\t\\t\\n\\t\\tfor uchar in ucode:\\n\\t\\t\\tif not( uchar in self._char39 ):\\n\\t\\t\\t\\traise Barcode39Error( '%s char is not listed in Barcode39 characters [0..9,A..Z,space,9,-,.,$,/,+,%]' )\\n\\n\\t\\tresult = []\\n\\t\\tfor uchar in ucode:\\n\\t\\t\\tresult = result + self.char_to_seq(uchar) \\n\\t\\t\\t\\n\\t\\treturn result\",\n \"def decode(self, seq):\\n return [ self.rev_vocab[int(el)] for el in seq ]\",\n \"def encoded(self):\\n text, chars = self.chars()\\n int2char = dict(enumerate(chars))\\n char2int = {ch: ii for ii, ch in int2char.items()}\\n encoded = np.array([char2int[ch] for ch in text])\\n return encoded\",\n \"def seqs_to_strs(self,id_array,remove_pads=True):\\n l = self.seqs_to_toks(id_array,remove_pads)\\n return [' '.join(i) for i in l]\",\n \"def binary_to_seq():\\n bin_seq, dico_binary, comp_seq, file_comp = utf8_to_binary()\\n \\n #for each binary value associate the corresponding letter (key) \\n #according to the dictionnary \\n dna_seq = \\\"\\\"\\n reading_binary = \\\"\\\"\\n for value in bin_seq:\\n reading_binary += value\\n for letter, code in dico_binary.items():\\n if code == reading_binary:\\n dna_seq += letter\\n reading_binary = \\\"\\\"\\n break\\n \\n #print(dna_seq, bin_seq, comp_seq, file_comp)\\n return dna_seq, bin_seq, comp_seq, file_comp\",\n \"def split_sequence(self, sequence):\\n\\t\\treturn [char for char in sequence]\",\n \"def decode_sequence(sequence, encoding_to_item):\\n return_sequence = []\\n\\n for i, itemset in enumerate(sequence):\\n decoded_itemset = set()\\n for item in itemset:\\n decoded_itemset.add(encoding_to_item[item])\\n return_sequence.append(decoded_itemset)\\n return return_sequence\",\n \"def array(self):\\n return list(self.sequence)\",\n \"def _rc_seq(self):\\n logger.debug(\\\"Extracting sequences on the reverse strand\\\")\\n sequences_rc = []\\n table = str.maketrans({'a': 't', 'c': 'g', 'g': 'c', 't': 'a',\\n 'A': 'T', 'C': 'G', 'G': 'C', 'T': 'A'})\\n for sequence in self.sequences:\\n sequences_rc.append(sequence.translate(table)[::-1])\\n self.sequences_rc = sequences_rc\",\n \"def _seq2vec(seq):\\n seq=_substitute_opening_gap_char(seq)\\n mapper = dict([(r, i) for i, r in enumerate(aalist)])\\n naa = len(seq)\\n naa_types = len(aalist)\\n vec = np.zeros((naa, naa_types))\\n for i, res in enumerate(list(seq)):\\n ind = mapper[res]\\n vec[i, ind] = 1.\\n return vec\",\n \"def to_seq (value):\\n if not value:\\n return []\\n\\n if isinstance (value, str):\\n return [value]\\n\\n else:\\n return value\",\n \"def sequence_encoding(sequence, str_to_idx):\\n sequence_of_indexes = [str_to_idx[element] for element in sequence]\\n return torch.tensor(sequence_of_indexes, dtype=torch.long)\",\n \"def smiles_to_seq(self, smiles):\\n smiles_len = len(smiles)\\n seq = [0]\\n keys = self.char_dict.keys()\\n i = 0\\n while i < smiles_len:\\n # Skip all spaces\\n if smiles[i:i + 1] == ' ':\\n i = i + 1\\n # For 'Cl', 'Br', etc.\\n elif smiles[i:i + 2] in keys:\\n seq.append(self.char_dict[smiles[i:i + 2]])\\n i = i + 2\\n elif smiles[i:i + 1] in keys:\\n seq.append(self.char_dict[smiles[i:i + 1]])\\n i = i + 1\\n else:\\n raise ValueError('character not found in dict')\\n for i in range(self.seq_length - len(seq)):\\n # Padding with '_'\\n seq.append(self.char_dict['_'])\\n return np.array(seq)\",\n \"def ascii_to_numpy(ascii_diagram, as_bytes=True):\\n ascii_diagram = [list(i) for i in ascii_diagram]\\n ascii_diagram = np.array(ascii_diagram)\\n v_to_bytes = np.vectorize(to_bytes)\\n return v_to_bytes(ascii_diagram) if as_bytes else ascii_diagram\",\n \"def convert2seq(self,seq_int):\\n\\t\\treturn [self.aminoacids[i] for i in seq_int]\",\n \"def decode_python(self, encoded_chunks: np.ndarray) -> np.ndarray:\\n encoded_chunks_reshaped = encoded_chunks.reshape((-1, 1))\\n encoded_chunks_tiles = np.tile(\\n encoded_chunks_reshaped, [1, self._dtype_size_bytes]\\n )\\n encoded_chunks_bytes_shifted = np.right_shift(\\n encoded_chunks_tiles, self._bit_lengths\\n )\\n encoded_chunks_bytes = encoded_chunks_bytes_shifted % 2 ** (\\n self._utf8_size_bits\\n )\\n int_to_char_fn = lambda x: (dict(enumerate(self._int_to_byte_map)).get(x))\\n\\n # Added `otypes=(np.string_,)` as an additional arg to np.vectorize to avoid\\n # numpy crashes with empty strings (not able to identify the type).\\n decoded_chars = np.vectorize(int_to_char_fn, otypes=(np.string_,))(\\n encoded_chunks_bytes\\n )\\n decoded_chars_reshaped = decoded_chars.reshape(-1, self._max_length)\\n decoded_strings = np.apply_along_axis(\\n lambda r: r.tobytes(), arr=decoded_chars_reshaped, axis=1\\n )\\n\\n return decoded_strings\",\n \"def stringToUtf8Array(input):\\n if _haveTypeUnicode:\\n # Assume this is Python 2.\\n if type(input) is str:\\n # Convert the raw string to an int array.\\n return map(ord, input)\\n elif type(input) is unicode:\\n # In Python 2, the result of encode is a str, so convert to int array.\\n return map(ord, input.encode('utf-8'))\\n else:\\n return input\\n else:\\n if type(input) is str:\\n return input.encode('utf-8')\\n else:\\n return input\",\n \"def get_str_arrays(self):\\n return self._fin.readline().strip('\\\\n').strip(' ').split(' ')\",\n \"def char_to_seq( self, uchar ):\\n\\t\\t\\n\\t\\tlstParts = self._char39[ uchar ].split( '+' ) # [ 'nb', 'ns', 'nb', ... ]\\n\\t\\t# Force evaluation with globals definition and local object definition (say on self.x)\\n\\t\\treturn [ eval( '_'+code, globals(), self.__dict__ ) for code in lstParts ]\",\n \"def read_fasta_sequences_to_str(filename):\\n with open(filename) as f:\\n lines = [line.strip() for line in f.readlines()]\\n sequences = []\\n text = ''\\n\\n for line in lines:\\n if line[0] == '>':\\n if len(text) > 0:\\n sequences.append(text)\\n text = ''\\n else:\\n if len(line):\\n text += line\\n if len(text) > 0:\\n sequences.append(text)\\n\\n return sequences\",\n \"def s2a(s):\\n return np.array(list(s))\",\n \"def bytes2matrix(text):\\n return [list(text[i:i+4]) for i in range(0, len(text), 4)]\",\n \"def encode(data, code_book):\\n return np.array([int(chunk, 2).to_bytes(-(-len(chunk) // 8), byteorder='big') for chunk in\\n map(lambda tup: ''.join(tup), (lambda iterable: zip_longest(*[iter(iterable)] * 8, fillvalue=''))(\\n ''.join(map(lambda x: code_book[x], data))))])\",\n \"def encode(self, sequence):\\n fwd_states, bwd_states = self.encode_fwd_bwd(sequence)\\n bwd_states = bwd_states[::-1]\\n return [dy.concatenate([fwd_states[i], bwd_states[i]]) for i in range(len(fwd_states))]\",\n \"def bs_to_array(bs):\\n return np.array([int(x) for x in bs], dtype=\\\"int8\\\")\",\n \"def encode_sequences(letter_sequences, symbol_to_idx, sequence_len, pad_symbol=None, go_symbol=None,\\n pad_beginning=True, reverse=False, ):\\n\\n pad_idx = symbol_to_idx[pad_symbol]\\n\\n if go_symbol is None:\\n go_idx = None\\n else:\\n go_idx = symbol_to_idx[go_symbol]\\n\\n assert sequence_len >= len(max(letter_sequences, key=len)) + 0 if go_idx is None else 1\\n\\n encoded_sequences = np.full((len(letter_sequences), sequence_len),\\n fill_value=pad_idx,\\n dtype=np.int32)\\n\\n for i, sequence in enumerate(letter_sequences):\\n\\n idxs = [symbol_to_idx[symbol] for symbol in sequence]\\n\\n if reverse:\\n idxs = idxs[::-1]\\n\\n # Insert the idx of the GO symbol to the end of the sequence.\\n if go_idx is not None:\\n idxs.append(go_idx)\\n\\n if pad_beginning:\\n encoded_sequences[i, -len(idxs):] = idxs\\n else:\\n encoded_sequences[i, :len(idxs)] = idxs\\n\\n return encoded_sequences\",\n \"def decode_chain_list(in_bytes):\\n bstrings = numpy.frombuffer(in_bytes, numpy.dtype('S' + str(mmtf.utils.constants.CHAIN_LEN)))\\n return [s.decode(\\\"ascii\\\").strip(mmtf.utils.constants.NULL_BYTE) for s in bstrings]\",\n \"def transform(self, y):\\n encode_y = []\\n for l in y:\\n encode_y.append(self.encode_dict[l])\\n\\n return np.array(encode_y)\",\n \"def decode(self, encoded):\\n decoded = []\\n for codes in encoded:\\n tmp = []\\n for code in codes:\\n try:\\n word = self.vocab[code]\\n tmp.append(word)\\n except:\\n tmp.append(self.unk_token)\\n decoded.append(tmp)\\n return decoded\",\n \"def kmer_seq_to_filters(kmers):\\n\\treturn np.concatenate([dna_string_to_array(s) for s in kmers])\",\n \"def prune_decoded_seqs(seqs):\\r\\n out = []\\r\\n for s in seqs:\\r\\n if EOS in s:\\r\\n idx = s.index(EOS)\\r\\n out += [s[:idx]]\\r\\n else:\\r\\n out += [s]\\r\\n return out\",\n \"def sents_to_seqs(sentences):\\r\\n list_of_sent = []\\r\\n list_of_seq = []\\r\\n list_of_labels = []\\r\\n for i in range(len(sentences)):\\r\\n for j in range(len(sentences[i])):\\r\\n if j + 4 < len(sentences[i]):\\r\\n list_of_sent.append(sentences[i][j])\\r\\n list_of_sent.append(sentences[i][j + 1])\\r\\n list_of_sent.append(sentences[i][j + 2])\\r\\n list_of_sent.append(sentences[i][j + 3])\\r\\n label = sentences[i][j + 4]\\r\\n list_of_labels.append(label)\\r\\n list_of_seq.append(list_of_sent)\\r\\n list_of_sent = []\\r\\n\\r\\n return list_of_seq, list_of_labels\",\n \"def parse_sequences(sequences, max_order):\\n return [get_transition_matrix(sequences, order) for order in xrange(max_order + 1)]\",\n \"def transform_seq(seq):\\n # TODO add character checking based on ASCII code\\n return \\\"\\\".join(\\\"\\\" if aa in msa_characters else aa for aa in seq)\",\n \"def back_translate(seq):\\n\\n base_nucleotide_list = []\\n for i in seq:\\n res = __get_key(i,CodonTable)\\n base_nucleotide_list.append(res)\\n return ''.join(base_nucleotide_list)\",\n \"def _text_array(text):\\n text = \\\"<mxit/>\\\" + text\\n \\n ar = map(ord, text)\\n pads = 16 - (len(ar) % 16)\\n ar += [0] * (pads-1)\\n ar.append(pads)\\n \\n return ar\",\n \"def binary_to_utf8():\\n added, binary_seq, seq, file = binary_conversion()\\n \\n comp_seq = \\\"\\\"\\n for bit in range(0, len(binary_seq), 8):\\n #cut the sequence each 8 bits\\n byte = binary_seq[bit:bit+8]\\n code = int(byte, 2)\\n #transforms 8 bits into a single character coded in utf-8\\n comp_seq += chr(code)\\n\\n return added, comp_seq, binary_seq, seq, file\",\n \"def array_encode(s):\\n return np.frombuffer(s.encode('utf32'), dtype=np.int32, offset=4)\",\n \"def convert_to_strings(self, sequences, sizes=None, remove_repetitions=False, return_offsets=False):\\n strings = []\\n offsets = [] if return_offsets else None\\n for x in xrange(len(sequences)):\\n seq_len = sizes[x] if sizes is not None else len(sequences[x])\\n string, string_offsets = self.process_string(sequences[x], seq_len, remove_repetitions)\\n strings.append([string]) # We only return one path\\n if return_offsets:\\n offsets.append([string_offsets])\\n if return_offsets:\\n return strings, offsets\\n else:\\n return strings\",\n \"def get_sequence_list(files):\\n sequence_list = []\\n for i in range(0,len(files)):\\n with open(files[i], \\\"r\\\") as fasta_file:\\n fasta_seq_all = fasta_file.read()\\n \\n\\n fasta_seq_all = fasta_seq_all.split(\\\">\\\")\\n\\n for j in range(0, len(fasta_seq_all)):\\n fasta_seq = fasta_seq_all[j]\\n if len(fasta_seq) > 2:\\n \\n fasta_seq = fasta_seq.splitlines()\\n label = _format_label(files[i], fasta_seq.pop(0))\\n format_fasta_seq = []\\n for k in range(0,len(fasta_seq)):\\n try:\\n if fasta_seq[k][0] == \\\"\\\\n\\\":\\n break\\n \\n format_fasta_seq.append(fasta_seq[k])\\n except:\\n break\\n format_fasta_seq = \\\"\\\".join(format_fasta_seq)\\n format_fasta_seq.strip()\\n if len(format_fasta_seq) > 2:\\n sequence_list.append(Sequence(format_fasta_seq, label))\\n \\n return sequence_list\",\n \"def convert_to_strings(self, sequences, sizes=None, remove_repetitions=False, return_offsets=False):\\n strings = []\\n offsets = [] if return_offsets else None\\n for x in range(len(sequences)):\\n seq_len = sizes[x] if sizes is not None else len(sequences[x])\\n string, string_offsets = self.process_string(sequences[x], seq_len, remove_repetitions)\\n strings.append([string]) # We only return one path\\n if return_offsets:\\n offsets.append([string_offsets])\\n if return_offsets:\\n return strings, offsets\\n else:\\n return strings\",\n \"def texts_to_sequences(self, targets=list) -> list:\\n try:\\n out = []\\n for target in targets:\\n out.append(self.encode_sentence(target))\\n return(out)\\n except Exception as error:\\n print(f\\\"Error: self.texts_to_sequences([...]) -> {error}\\\")\",\n \"def sequence(self):\\n\\n\\t\\tseq = \\\"\\\"\\n\\t\\tfor chain in self.chain:\\n\\t\\t\\tfor res in chain.residue:\\n\\t\\t\\t\\tseq += res.aa1()\\n\\n\\t\\treturn seq\",\n \"def construct_sequence_list(self):\\n return list(self.iter_sequence())\",\n \"def fasta_seqs(file_name):\\n list = []\\n with open('../test_files/' + file_name, 'r') as infile:\\n text = infile.read()\\n seqs = text.split('>')\\n for seq in seqs:\\n try:\\n x = seq.split('\\\\n', 1)\\n # sequence will be stored in x[1], and i am removing nextline '\\\\n' characters that comes with it.\\n list.append(x[1].replace('\\\\n', ''))\\n except:\\n pass\\n return list\",\n \"def sequence_to_list_ids(sequence, vocab):\\n pass\",\n \"def fasta_path_to_seqs(fasta_path, codon_table=False, codon_alphabet=False):\\n seqs = []\\n for record in SeqIO.parse(fasta_path, \\\"fasta\\\"):\\n seqs.append(record)\\n return seqs\",\n \"def seq2Vec(sequences):\\r\\n global dict_words_n_vectors\\r\\n for sent in sequences:\\r\\n for i in range(len(sent)):\\r\\n if sent[i] in dict_words_n_vectors:\\r\\n sent[i] = dict_words_n_vectors[sent[i]]\\r\\n else:\\r\\n sent[i] = np.zeros(300)\\r\\n return np.array(sequences, dtype=\\\"float32\\\")\",\n \"def test_ModelRnaCodonSequence(self):\\n r = ArrayRnaCodonSequence(\\\"UUUCGU\\\")\\n self.assertEqual(str(r), \\\"UUUCGU\\\")\\n self.assertEqual(r._data, array([0, 28]))\\n self.assertEqual(str(r.to_rna()), \\\"UUUCGU\\\")\\n self.assertEqual(str(r.to_dna()), \\\"TTTCGT\\\")\",\n \"def all_unambiguous(sequence_str):\\n result = [[]]\\n for c in sequence_str:\\n result = [i + [a] for i in result\\n for a in _AMBIGUOUS_MAP.get(c, c)]\\n return [''.join(i) for i in result]\",\n \"def prune_decoded_seqs(seqs):\\n out = []\\n for s in seqs:\\n if constant.EOS in s:\\n idx = s.index(constant.EOS_TOKEN)\\n out += [s[:idx]]\\n else:\\n out += [s]\\n return out\",\n \"def convert_to_sequence(texts, tokenizer, max_length):\\n fitted_tokenizer = tokenizer\\n vectorized_text = fitted_tokenizer.texts_to_sequences(texts)\\n\\n # pad sequences\\n vectorized_text = sequence.pad_sequences(vectorized_text, maxlen=max_length)\\n\\n return vectorized_text\",\n \"def create_seqeunce_helper(i, text, dsl, char_count, char_to_n, extra, length = seq_length):\\n\\n seq_int = [] # Sequence mapped to integers\\n output_seq = np.zeros((length, char_count)) # Output sequence which will become one item in input array \\n\\n # Get the next sequence and map its characters to integers\\n for v in text[i * length + extra : (i + 1) * length + extra]:\\n # If the seed_text is missing a character we append 0\\n if v in char_to_n:\\n seq_int.append(char_to_n[v])\\n else:\\n seq_int.append(0)\\n\\n # For character in sequence\\n for j in range(length):\\n # Set column corrpsonding to that character to 1\\n output_seq[j][seq_int[j]] = 1.0 \\n\\n return output_seq\",\n \"def arrays_to_sequences(token_list_iterable, sequence_length=2049):\\n accum = []\\n for l in token_list_iterable:\\n accum.extend(l)\\n\\n if len(accum) > sequence_length:\\n chunks = split_list(accum, sequence_length)\\n yield from chunks[:-1]\\n accum = chunks[-1]\\n\\n if len(accum) > 0:\\n yield accum\",\n \"def decode(e):\\n return sum([length * [item] for length,item in e],[])\",\n \"def readSequences(lines):\\n seqs = []\\n label = None\\n seq_lines = []\\n for line in lines:\\n line = line.strip() # strip off white space\\n if not line: # skip empty lines\\n continue\\n if line.startswith(';'): # ignore comment lines\\n continue\\n # check for start of next sequence:\\n if line.startswith('>'): # label line\\n # first, store the previous sequence if we had one:\\n if seq_lines:\\n seqs.append(Sequence(label, ''.join(seq_lines)))\\n seq_lines = []\\n # get the label (name) for the next sequence\\n label = line[1:].strip()\\n else:\\n # collect all lines with sequence information for this sequence:\\n seq_lines.append(line)\\n # take care of the last sequence in the file\\n seqs.append(Sequence(label, ''.join(seq_lines)))\\n return seqs\",\n \"def decode(self, s):\\n i = 0\\n strs = []\\n while i < len(s):\\n l = int(s[i:i+8], 16)\\n strs.append(s[i+8:i+8+l])\\n i += 8+l\\n return strs\",\n \"def seqs_to_ids(seqs, char_to_id, max_len=20):\\n all_seqs = []\\n\\n # Turn a list of names into a 2d padded array of token ids\\n for text in seqs:\\n if len(text) != 0:\\n all_text = []\\n for word in text:\\n all_text.append(char_to_id.get(word))\\n\\n all_seqs.append(all_text)\\n final_all_seqs = np.zeros((len(all_seqs), max_len))\\n\\n for idx, row in enumerate(all_seqs):\\n if len(row) >= max_len:\\n final_all_seqs[idx, :max_len] += row[:max_len]\\n else:\\n final_all_seqs[idx, :len(row)] += row\\n print('Shape of data tensor:', final_all_seqs.shape)\\n\\n return final_all_seqs\",\n \"def build_sequence(data: Any):\\n if isinstance(data, (bytearray, bytes)):\\n data = data.decode()\\n if isinstance(data, str):\\n data = data.split(',')\\n literals = []\\n numeric = []\\n for item in filter(None, data):\\n if str(item).isdigit():\\n numeric.append(int(item))\\n continue\\n if ':' in item:\\n literals.append(item)\\n elif isinstance(item, (tuple, set, list)):\\n return build_sequence(item)\\n else:\\n raise Exception(item)\\n return ','.join(literals + build_numeric_sequence(numeric))\",\n \"def string_to_array(self):\\n temp_map = copy.deepcopy(self.map.replace(\\\" \\\", \\\"\\\"))\\n map_list = [[a for a in row] for row in temp_map.splitlines()]\\n\\n # Checks that all lines are of equal length\\n for line in map_list:\\n for index in range(len(map_list)):\\n if len(map_list[index]) == len(line):\\n continue\\n else:\\n raise SyntaxError(\\\"Island geography multi-line string \\\"\\n \\\"must have lines of same length.\\\")\\n map_arr = np.array(map_list)\\n\\n # Checks that there are only 'O's at the edges.\\n edge = []\\n edge += list(map_arr[0, :])\\n edge += list(map_arr[-1, :])\\n edge += list(map_arr[1:-1, 0])\\n edge += list(map_arr[1:-1, -1])\\n if set(edge) == {'O'}:\\n pass\\n else:\\n raise SyntaxError(\\\"Island geography multi-line string \\\"\\n \\\"must have 'O' around the edges. \\\")\\n\\n return map_arr\",\n \"def encodings(self) -> list[int]:\\n pass\",\n \"def get_seq(self): # -> list[Unknown]:\\n ...\",\n \"def build_seq2seq(self, corpus):\\n self.dataset = [[self.encode(message), self.encode(reply)] for message, reply in corpus]\",\n \"def from_ascii(s):\\n\\treturn numpy.array(\\n\\t\\t[\\n\\t\\t\\tord(c)\\n\\t\\t\\tfor c in s\\n\\t\\t],\\n\\t\\tdtype=numpy.uint8\\n\\t)\",\n \"def string_encoder(string: str) -> List[bytes]:\\n return [w.encode(\\\"utf-8\\\") for w in string.split()]\",\n \"def decode(lst, typecode ):\\n a = array.array( typecode )\\n for n,c in lst: \\n a.extend( array.array( typecode, (c,) * n ) )\\n return a\",\n \"def create_sequences(text, sequence_length, step):\\n sequences = []\\n labels = []\\n for i in range(0, len(text) - sequence_length, step):\\n sequences.append(text[i: i + sequence_length])\\n labels.append(text[i + sequence_length])\\n return sequences, labels\",\n \"def tokenize(self, sequence: str) -> List[str]:\\n raise NotImplementedError\",\n \"def create_sequences(data, seq_length):\\r\\n xs = []\\r\\n ys = []\\r\\n for i in range(len(data) - seq_length - 1):\\r\\n # Create a sequence of features\\r\\n x = data[i:(i + seq_length)]\\r\\n # Take the next value as a target\\r\\n y = data[i + seq_length]\\r\\n # Append to lists\\r\\n xs.append(x)\\r\\n ys.append(y)\\r\\n # Convert to ndarrays and return\\r\\n return np.array(xs), np.array(ys)\",\n \"def encode_sequence(text: List[str], vocab: Dict) -> Sequence[int]:\\n return [vocab[ngram] if ngram in vocab else vocab[\\\"<UNK>\\\"] for ngram in text]\",\n \"def get_sequence_coder(specs):\\n\\n def not_sequence(v):\\n return v == tf.string or isinstance(v, tf.io.FixedLenFeature)\\n\\n sequence_keys = [k for k, v in specs.items() if not not_sequence(v)]\\n return serialization.SequenceCoder(specs=specs, sequence_keys=sequence_keys)\",\n \"def text_to_sequence(text, cmudict):\\n text_seq = parse_text(text, cmudict)\\n id_seq = [symbol_to_id[s] if s in symbol_to_id else symbol_to_id[_unk] for s in text_seq]\\n\\n return id_seq\",\n \"def EncodeAndPad(srcs: typing.List[str], padded_length: int,\\n atomizer) -> np.array:\\n seqs = [atomizer.AtomizeString(src) for src in srcs]\\n assert max(len(seq) for seq in seqs) <= padded_length\\n pad_val = atomizer.vocab_size\\n encoded = np.array(\\n sequence.pad_sequences(seqs, maxlen=padded_length, value=pad_val))\\n return np.vstack([np.expand_dims(x, axis=0) for x in encoded])\",\n \"def sequence(self, field):\\n if self._writer._buffer == deque([]):\\n raise RuntimeError(\\\"Writer buffer is empty.\\\")\\n if not isinstance(field, str):\\n raise TypeError(\\\"<field> has to be string.\\\")\\n loc = field.split(\\\".\\\")\\n N = len(self._writer._buffer)\\n ret = []\\n for i in range(N):\\n A = np.array(_getvaluefrombuffer(self._writer._buffer[i], loc))\\n if A.shape == (1,):\\n ret.append(A[0])\\n else:\\n ret.append(A)\\n return np.array(ret)\",\n \"def decode(self, labels):\\n if len(labels.shape) == 1:\\n return self.sp.DecodeIds([int(l) for l in labels])\\n\\n sentences = list()\\n for batch in labels:\\n sentence = str()\\n for label in batch:\\n sentence = self.sp.DecodeIds([int(l) for l in label])\\n sentences.append(sentence)\\n return sentences\",\n \"def process(self, example: str) -> List[torch.Tensor]:\\n return torch.tensor(self._tokenizer.encode(example, max_length=self.max_seq_len))\",\n \"def format_seq_content(seq_str, out_format):\\n sequences = []\\n with tempfile.TemporaryFile(mode='w+') as fp:\\n fp.write(seq_str)\\n fp.seek(0)\\n for record in SeqIO.parse(fp, out_format):\\n sequences.append(record)\\n return sequences\",\n \"def get_seqs(in_fpath):\\n f = open(in_fpath, 'r')\\n csvread = csv.reader(f)\\n seqs = [str(row) for row in csvread]\\n seq1 = re.sub('[^A-Z]+', \\\"\\\", seqs[0])\\n seq2 = re.sub('[^A-Z]+', \\\"\\\", seqs[1])\\n return seq1, seq2\",\n \"def encoding_ids(self):\\n # type: () -> list[string_types]\\n return self._encoding_ids\",\n \"def test_regular_to_model(self):\\n r = RNA.make_seq(\\\"AAA\\\", name=\\\"x\\\")\\n s = RNA.make_array_seq(r)\\n self.assertEqual(str(s), \\\"AAA\\\")\\n self.assertEqual(s.moltype, RNA)\\n self.assertEqual(s.name, \\\"x\\\")\",\n \"def _sequences_to_new_records(sequences):\\n if isinstance(sequences, dict):\\n sequences = list(sequences.items())\\n records = []\\n for seq in sequences:\\n if hasattr(seq, \\\"id\\\"):\\n records.append(deepcopy(seq))\\n else:\\n name, seq = seq\\n records.append(\\n sequence_to_biopython_record(seq, id=name, name=name)\\n )\\n return records\",\n \"def string_to_array(arg):\\n\\n res = arg.replace('[', '').replace(']', '').replace(',', '')\\n return np.array(res.split(' '), dtype=np.int8)\",\n \"def buildTrainingSequences(voc, maxlen=50, step=3):\\n \\n text, sym_indices, _ = voc\\n sentences = []\\n next_syms = []\\n \\n syms = set(text) # unique symbols (chars or words)\\n \\n for i in range(0, len(text) - maxlen, step):\\n sentences.append(text[i: i + maxlen])\\n next_syms.append(text[i + maxlen])\\n print('nb sequences:', len(sentences))\\n \\n X = np.zeros((len(sentences), maxlen), dtype=np.int)\\n y = np.zeros((len(sentences), len(syms)), dtype=np.bool)\\n\\n for i, sentence in enumerate(sentences):\\n for j, sym in enumerate(sentence):\\n X[i,j] = sym_indices[sym] \\n \\n y[i, sym_indices[next_syms[i]]] = 1 # one-hot enconding\\n\\n return (X,y)\",\n \"def getSequence(resnames):\\n\\n get = AAMAP.get\\n return ''.join([get(rn, 'X') for rn in resnames])\",\n \"def decodeUtf8(self, arrayBuffer):\",\n \"def decodeUtf8(self, arrayBuffer):\",\n \"def bipa(sequence):\\n return [_token2clts(segment)[0] for segment in sequence]\",\n \"def _batch_encode(self, text: List[str]) -> List[List[str]]:\\n token_ids: List[List[int]] = self.bert_model.batch_encode([t.strip() for t in text])\\n tokens_ids_str: List[List[str]] = [[str(t) for t in token_id] for token_id in token_ids]\\n return tokens_ids_str\",\n \"def translate(self, sequences):\\n return [self.vocab.translate(t) for t in sequences]\",\n \"def decode (self, s):\\n if s == \\\"null\\\": return []\\n return s.split(chr(257))\",\n \"def to_char_array(s):\\n if type(s) != bytes:\\n raise ValueError('Input to to_char_array function should be in bytes')\\n char_array = []\\n tokens = s.split(b' ')\\n for token in tokens:\\n char_array.append(ord(' '))\\n if isemoji(token):\\n char_array.append(token)\\n continue\\n if token in [b'!url', b'@user']:\\n char_array.append(token)\\n continue\\n for c in token:\\n char_array.append(c)\\n print(char_array)\\n return char_array[1:]\",\n \"def FormatSeq(X):\\n return [v.split(\\\"-\\\")[0] for v in X[\\\"Sequence\\\"]]\",\n \"def i(self):\\n return np.array(self._sequence)\",\n \"def convert_one_hot_encoded_cards_to_str_encoded_list(cards: np.ndarray) -> List[str]:\\n return [card_strings[i] for i in np.flatnonzero(cards)]\",\n \"def generate_sequence_data_for_LSTM(complete_text_enumerated):\\n pattern_sequence = []\\n pattern_targets = []\\n for i in range(0, len(complete_text_enumerated)-WINDOW_LENGTH):\\n temp_pattern = complete_text_enumerated[i:i+WINDOW_LENGTH]\\n temp_pattern_target = complete_text_enumerated[i+WINDOW_LENGTH]\\n pattern_sequence.append(temp_pattern)\\n pattern_targets.append(temp_pattern_target)\\n num_patterns = len(pattern_sequence)\\n X = np.reshape(pattern_sequence, (num_patterns, WINDOW_LENGTH, 1))\\n y = np_utils.to_categorical(pattern_targets)\\n return [X, y]\",\n \"def to_sequence(self):\\n queue = [self.root]\\n seq_k = []\\n seq_v = []\\n\\n while queue:\\n res = queue.pop(0)\\n seq_k.append(res.key)\\n seq_v.append(res.payload)\\n if res.hasLeftChild():\\n queue.append(res.leftChild)\\n if res.hasRightChild():\\n queue.append(res.rightChild)\\n\\n return seq_k, seq_v\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.69954103","0.68113625","0.65563","0.6483455","0.64378685","0.6263874","0.6176669","0.61550325","0.61276937","0.61096597","0.6037147","0.6029054","0.5999388","0.59981567","0.59195274","0.59060395","0.5906004","0.58647674","0.5854323","0.58464247","0.58129746","0.58010364","0.57766646","0.5752788","0.5741127","0.57285976","0.5717394","0.5681698","0.56607425","0.5656242","0.5650677","0.5647011","0.5638159","0.5633792","0.5633117","0.56300145","0.5629749","0.5627119","0.5608613","0.5597842","0.5584855","0.5580654","0.5563272","0.5538742","0.5527107","0.5521874","0.5519176","0.5517291","0.5516202","0.55121684","0.55076826","0.5506416","0.55014086","0.5494255","0.5490477","0.54790956","0.54709905","0.5469001","0.54683524","0.5465331","0.5461575","0.54547566","0.54317075","0.5421374","0.5412746","0.5411731","0.5398794","0.53812975","0.53779316","0.5374126","0.5367841","0.53677887","0.53672427","0.5364004","0.536327","0.5360667","0.535852","0.53517467","0.5321269","0.5318435","0.5315055","0.5311631","0.5304461","0.5296198","0.52907723","0.5289988","0.5289538","0.52849895","0.52611023","0.52611023","0.5260154","0.52591324","0.5254621","0.5251379","0.52441496","0.5231859","0.5229703","0.5225727","0.5223866","0.52224016"],"string":"[\n \"0.69954103\",\n \"0.68113625\",\n \"0.65563\",\n \"0.6483455\",\n \"0.64378685\",\n \"0.6263874\",\n \"0.6176669\",\n \"0.61550325\",\n \"0.61276937\",\n \"0.61096597\",\n \"0.6037147\",\n \"0.6029054\",\n \"0.5999388\",\n \"0.59981567\",\n \"0.59195274\",\n \"0.59060395\",\n \"0.5906004\",\n \"0.58647674\",\n \"0.5854323\",\n \"0.58464247\",\n \"0.58129746\",\n \"0.58010364\",\n \"0.57766646\",\n \"0.5752788\",\n \"0.5741127\",\n \"0.57285976\",\n \"0.5717394\",\n \"0.5681698\",\n \"0.56607425\",\n \"0.5656242\",\n \"0.5650677\",\n \"0.5647011\",\n \"0.5638159\",\n \"0.5633792\",\n \"0.5633117\",\n \"0.56300145\",\n \"0.5629749\",\n \"0.5627119\",\n \"0.5608613\",\n \"0.5597842\",\n \"0.5584855\",\n \"0.5580654\",\n \"0.5563272\",\n \"0.5538742\",\n \"0.5527107\",\n \"0.5521874\",\n \"0.5519176\",\n \"0.5517291\",\n \"0.5516202\",\n \"0.55121684\",\n \"0.55076826\",\n \"0.5506416\",\n \"0.55014086\",\n \"0.5494255\",\n \"0.5490477\",\n \"0.54790956\",\n \"0.54709905\",\n \"0.5469001\",\n \"0.54683524\",\n \"0.5465331\",\n \"0.5461575\",\n \"0.54547566\",\n \"0.54317075\",\n \"0.5421374\",\n \"0.5412746\",\n \"0.5411731\",\n \"0.5398794\",\n \"0.53812975\",\n \"0.53779316\",\n \"0.5374126\",\n \"0.5367841\",\n \"0.53677887\",\n \"0.53672427\",\n \"0.5364004\",\n \"0.536327\",\n \"0.5360667\",\n \"0.535852\",\n \"0.53517467\",\n \"0.5321269\",\n \"0.5318435\",\n \"0.5315055\",\n \"0.5311631\",\n \"0.5304461\",\n \"0.5296198\",\n \"0.52907723\",\n \"0.5289988\",\n \"0.5289538\",\n \"0.52849895\",\n \"0.52611023\",\n \"0.52611023\",\n \"0.5260154\",\n \"0.52591324\",\n \"0.5254621\",\n \"0.5251379\",\n \"0.52441496\",\n \"0.5231859\",\n \"0.5229703\",\n \"0.5225727\",\n \"0.5223866\",\n \"0.52224016\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.5643979"},"document_rank":{"kind":"string","value":"32"}}},{"rowIdx":88594,"cells":{"query":{"kind":"string","value":"Get a string that describes the target (for e.g. metadata)."},"document":{"kind":"string","value":"def data_name(self):\n return \"Bispectrum\""},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def getInfo(self):\n return self.name + \" [\" + self.target_type + \"]\"","def target(self) -> Optional[str]:\n return pulumi.get(self, \"target\")","def target_name(self):\n return self._target_name","def name(self) -> str:\n return self.inst['targetname']","def get_target_str(self) -> Optional[str]:\n if self._target_href:\n return self._target_href\n elif self._target_object:\n return self._target_object.get_self_href()\n else:\n return None","def get_target(self):\n task = self.task.get_task(self.task_id)\n if 'name' in task:\n return str(task['name'])\n return str(task)","def get_target(self, ):\n return self.get_parameter('target')","def str_targetting(self):\n if not self.targetting: # set to none etc.\n return \"doing nothing\"\n if self.targetting[0] == \"marching\":\n return \"marching -> \" + self.targetting[1].color_name()\n if self.targetting[0] == \"defending\":\n return \"staying put\"\n assert self.targetting[0] == \"sneaking\"\n return \"sneaking -> \" + self.targetting[1].color_name()","def get_target_simple(self):\n task = self.task.get_task(self.task_id)\n return str(task['name'])","def target_naming(ty,target):\n de = ty.description(target)\n de = de[0].upper() + de[1:] + \".\"\n return de","def process_target(self):\n assert isinstance(self.target, str)\n return f\"%{super().process_target()}%\"","def target_label(self):\n return self._target_label","def target(self):\n return self._properties.get('target')","def target(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"target\")","def target(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"target\")","def target(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"target\")","def target(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"target\")","def target(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"target\")","def target(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"target\")","def target(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"target\")","def target(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"target\")","def target_text_name(self):\n name = dsutils._connect_name(\n self._data_spec.name_prefix[1],\n self._tgt_decoder.text_tensor_name)\n return name","def target_type(self) -> str:\n return pulumi.get(self, \"target_type\")","def _get_details(target):\r\n assert target is not None and issubclass(target, Target)\r\n\r\n arg_spec = inspect.getargspec(target.__init__)\r\n arg_help = TargetsHelp._get_arg_help(target.__init__.__doc__)\r\n\r\n min_default_idx = 0\r\n if arg_spec.defaults is None:\r\n min_default_idx = len(arg_spec.args)\r\n elif len(arg_spec.args) > len(arg_spec.defaults):\r\n min_default_idx = len(arg_spec.args) - len(arg_spec.defaults)\r\n\r\n lines = [TargetsHelp.DETAILS_HEADER.substitute(\r\n name=TargetsHelp.TARGET_TO_ALIAS[target.__name__], desc=target.__doc__)]\r\n\r\n max_width = 0\r\n for arg in arg_spec.args:\r\n max_width = max(max_width, len(arg))\r\n\r\n wrapper = textwrap.TextWrapper(subsequent_indent=' '*(max_width+4))\r\n\r\n for idx, val in enumerate(arg_spec.args):\r\n has_default = False\r\n default_val = None\r\n\r\n if idx >= min_default_idx:\r\n has_default = True\r\n default_val = arg_spec.defaults[idx-min_default_idx]\r\n\r\n if val == 'self':\r\n continue\r\n help_str = 'No help available for this argument.'\r\n try:\r\n help_str = arg_help[val]\r\n except KeyError:\r\n pass\r\n if has_default:\r\n help_str += ' (default: %s) ' % str(default_val)\r\n lines.append(' %s: %s' % (val.rjust(max_width), '\\n'.join(wrapper.wrap(help_str))))\r\n return lines","def identifyTargetType(self, target):\n ipAddress = re.compile('\\d{1,3}\\.\\d{1,3}\\.\\d{1,3}\\.\\d{1,3}')\n ipFind = re.findall(ipAddress, target)\n if ipFind is not None and len(ipFind) > 0:\n return \"ip\"\n\n md5 = re.compile('[a-fA-F0-9]{32}', re.IGNORECASE)\n md5Find = re.findall(md5,target)\n if md5Find is not None and len(md5Find) > 0:\n return \"md5\"\n\n return \"hostname\"","def get_target_name(self):\n if self.preferred_name is None:\n target_name = self.original_name\n elif len(self.preferred_name) > 4:\n target_name = self.preferred_name\n else:\n target_name = self.original_name\n logger.debug('Source Document target file name: {}'.format(target_name))\n return target_name","def target(self) -> list[str]:\n if self._target is None:\n print(self.__class__.target.__doc__)\n raise SilSubProblemError(\n \"The *target* property has not been set (see above).\"\n )\n return self._target","def __str__(self):\n return 'Target with value ' + str(self.attributes[AT.VALUE])","def str_nfc_target(pnt, verbose):\n return _nfc.str_nfc_target(pnt, verbose)","def target_id(self) -> str:\n return self._target_id","def target_entity_type_name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"target_entity_type_name\")","def show_target(self, target):\n print \" \" + repr(target.subject) \\\n + \" \" + target.meaning \\\n + \" \" + target.verb \\\n + \" \" + repr(target.object)","def time_to_target(self) -> str:\r\n # TODO: Figure out how to implement this.\r\n self._logger.debug(log_message_formatter(\r\n \"get\", f\"{self}\", \"time_to_target\"))\r\n return self._time_to_target_options[0]","def simplified_target(target):\n if '_prod_' in target:\n return 'Production', 'prod'\n elif 'test' in target:\n return 'Test', 'test'\n elif 'nonprod' in target:\n return 'Non-Production', 'nonprod'\n elif 'all' in target:\n return 'All', 'all'\n else:\n return 'Target not found!', None","def get_target_info():\n target_binary = get_target_binary()\n target_platform, target_architecture = get_target_platform(target_binary)\n target_type = get_target_type()\n return target_binary, target_platform, target_architecture, target_type","def get_target(self):\n return self._target","def target_arn(self) -> str:\n return self._values.get('target_arn')","def target_id(self) -> Optional[str]:\n return pulumi.get(self, \"target_id\")","def target_type(self) -> Optional[str]:\n return pulumi.get(self, \"target_type\")","def target(self):\n return self.data.target","def getTargets(targets) -> str:\n return\"\"\"## Target\n| |Category| |Task| Estimated Time | Actual Time |\n| - | -: | - | - | - | - |\n{previousTargets}\"\"\".format(previousTargets=targets)","def __str__(self):\n if len(self.label) > 0:\n descr = [\"'%s', target='%s' [%s]\" % (self.label, self.target.name, self.target.body_type)]\n else:\n descr = [\"target='%s' [%s]\" % (self.target.name, self.target.body_type)]\n if self.baseline:\n descr[0] += ', initial baseline offset=%f' % (self.baseline.poly[-1],)\n if self.beam:\n descr[0] += ', beam height=%f' % (self.beam.height,)\n for scan_ind, scan in enumerate(self.scans):\n descr.append('%4d: %s' % (scan_ind, str(scan)))\n return '\\n'.join(descr)","def target_loc(self) -> str:\n return self._target_loc","def getTarget(self):\n return self.Target","def getTarget(self):\n return self._target","def target(self):\n return self._target","def target(self):\n return self._target","def target(self):\n return self._target","def target(self):\n return self._target","def _get_env_target(self, target='default'):\n return '{target}{env_postfix}'.format(\n target=target,\n env_postfix=self._env_postfix)","def target_entity_type(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"target_entity_type\")","def use(target, name):\n return \"The \" + name + \" takes effect on \" + target.name","def target_text_id_name(self):\n name = dsutils._connect_name(\n self._data_spec.name_prefix[1],\n self._tgt_decoder.text_id_tensor_name)\n return name","def target(self) :\n\t\ttry :\n\t\t\treturn self._target\n\t\texcept Exception as e:\n\t\t\traise e","def target(self) :\n\t\ttry :\n\t\t\treturn self._target\n\t\texcept Exception as e:\n\t\t\traise e","def target(self):\n return self.__target","def target(self):\n return self.__target","def target(self):\n return self.problem.target","def getTarget(self):\n\n return self._target","def process_target(self):\n if isinstance(self.target, UUID):\n self.target = str(self.target)\n\n return self.target","def _target(self):\n return self.__target","def get_target_info(\n targetId: Optional[TargetID] = None,\n) -> Generator[dict, dict, TargetInfo]:\n response = yield {\n \"method\": \"Target.getTargetInfo\",\n \"params\": filter_none({\"targetId\": str(targetId) if targetId else None}),\n }\n return TargetInfo.from_json(response[\"targetInfo\"])","def target_resource_id(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"target_resource_id\")","def target_resource_id(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"target_resource_id\")","def Target(self):\n return self._target","def get_target(self, agent, collective, topciprefix=None):","def get_name(self):\n\t\treturn self.source.get_name()","def get_target_reg( self ):\r\n\t\tif len( self.lines ) > 0:\r\n\t\t\tif self.reg == \"eax\" and self.lines[-1][1] == \"call\":\r\n\t\t# We have a call that overwrites EAX\r\n\t\t\t\treturn \"END\"\r\n\t\t\tif self.lines[-1][2] == self.reg and self.lines[-1][1] not in neutral_mnem:\r\n\t\t# We have a non-neutral instruction that writes to the register we're tracking\r\n\t\t\t\treturn \"END\"\r\n\t\t\telif self.lines[-1][2].find( self.reg ) != -1:\r\n\t\t# We have memory access to the location this register is pointing to or an operation on itself\r\n\t\t\t\treturn \"\"\r\n\t\t\telse:\r\n\t\t# If the target is a register, return this register\r\n\t\t\t\tif self.lines[-1][2] in x86_registers:\r\n\t\t\t\t\treturn self.lines[-1][2]\r\n\t\t\t\telse:\r\n\t\t\t\t\treturn \"\"\r\n\t\telse:\r\n\t\t\treturn \"\"","def get_target_name(f):\n name = os.path.basename(f)\n\n target_number = get_target_number(name)\n if target_number != 14:\n target_name = str(target_number)\n else:\n # We keep bound and free denotation if puzzle 14.\n target_name = str(target_number) + \\\n ('b' if 'bound' in name else 'f')\n return target_name","def target(self):\n return self._definition","def get_description(self):\n return self['command_name']","def describe(self) -> str:","def target(self, example):\n return example[self.target_index]","def parse_event_target(target: Any) -> Tuple[str, str]:\n if not target:\n return \"\", \"\"\n\n target_type = type(target).__name__\n\n if hasattr(target, \"uuid\"):\n return target_type, target.uuid\n\n if hasattr(target, \"id\"):\n return target_type, target.id\n\n return target_type, \"\"","def target_resource_guid(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"target_resource_guid\")","def use(target, name):\n return \"You use the \" + name + \" to pay \" + target.name","def target( self ) :\n\n return( self.__target )","def target(self):\n return bytes(self[8:16])","def target(self) -> Optional[int]:\n return pulumi.get(self, \"target\")","def target(self) -> Union[str, \"STACObject_Type\"]:\n if self._target_object:\n return self._target_object\n elif self._target_href:\n return self._target_href\n else:\n raise ValueError(\"No target defined for link.\")","def info(target):\n co = target.__code__\n return (co.co_name, co.co_filename, co.co_firstlineno)","def getMnemonicForTarget(targetId, table):\n request = \"SELECT textstring FROM %s WHERE role=\\\"MNEMONIC\\\" and target=\\\"%s\\\"\" % (table, targetId)\n execute(request)\n row = cursor.fetchone()\n if row == None:\n warn(\"mnemonic not found for target %s in table %s\" % (targetId, table) )\n else:\n return row[0]","def info():\n return r\"\"\"Lin-Yu Tseng and Chun Chen, \"Multiple trajectory search for Large Scale Global Optimization,\" 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), Hong Kong, 2008, pp. 3052-3059. doi: 10.1109/CEC.2008.4631210\"\"\"","def _get_description(actor, commit, run_id):\n return (\"Requested by @%s on commit %s\\n\" % (actor, commit) +\n \"Last updated: %s \\n\" % _get_datetime() +\n \"**[View integration test log & download artifacts](https://github.com/firebase/firebase-cpp-sdk/actions/runs/%s)**\\n\" % run_id)","def get_target_uri(self, docname: str, type: str = None) -> str:\n\n uri = docname + \".ipynb\"\n\n logger.debug(f\"[nbtutorial]: Target URI: {uri}\")\n\n return uri","def co_filename(self):\n assert (\n self.filename is not None\n ), \"co_filename requires Target created from filename\"\n return self.filename.strpath","def get_name(self):\n return \"make\"","def target_option(s):\n return s","def shortDescription(self):\n if self._current_test_descr is not None:\n return self._current_test_descr\n return super(TestCase, self).shortDescription()","def target_to_url(target):\n if is_wc(target):\n info = get_svninfo(target)\n return info[\"URL\"]\n return target","def getTargetType(self):\n return self.target_type","def __str__(self):\n return '{trait_name} ({phv}): dataset {pht}'.format(trait_name=self.i_trait_name,\n phv=self.full_accession,\n pht=self.source_dataset.full_accession)","def display_current_target():\n marker = 0\n target = \"\"\n with open(vars_file) as f:\n for line in f:\n if marker == 1 and '<<:' in line:\n line_list = line.split(':')\n target = line_list[1].strip()\n marker = 0\n if 'target_arrays:' in line:\n marker = 1\n simple_target, current_selection = simplified_target(target)\n print(f'Current target setting: {simple_target}')\n return simple_target, current_selection","def get_info(self) -> str:\n raise NotImplementedError()","def target(self):\n return self._task_target","def target_group(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"target_group\")","def _get__target(self):\n if self._saved_target is None:\n self._saved_target = self._metadata.get_callable()()\n \n return self._saved_target","def target_length_name(self):\n name = dsutils._connect_name(\n self._data_spec.name_prefix[1],\n self._tgt_decoder.length_tensor_name)\n return name","def __str__(self):\n struct_repr = \", \".join([\n \"group: \" + str(self.group),\n \"controls: \" + str(self.controls)\n ])\n\n return f\"ActuatorControlTarget: [{struct_repr}]\"","def get_info_string(self) -> str:\n return \"Not implemented\"","def target_id(self):\n\n return self._target_id"],"string":"[\n \"def getInfo(self):\\n return self.name + \\\" [\\\" + self.target_type + \\\"]\\\"\",\n \"def target(self) -> Optional[str]:\\n return pulumi.get(self, \\\"target\\\")\",\n \"def target_name(self):\\n return self._target_name\",\n \"def name(self) -> str:\\n return self.inst['targetname']\",\n \"def get_target_str(self) -> Optional[str]:\\n if self._target_href:\\n return self._target_href\\n elif self._target_object:\\n return self._target_object.get_self_href()\\n else:\\n return None\",\n \"def get_target(self):\\n task = self.task.get_task(self.task_id)\\n if 'name' in task:\\n return str(task['name'])\\n return str(task)\",\n \"def get_target(self, ):\\n return self.get_parameter('target')\",\n \"def str_targetting(self):\\n if not self.targetting: # set to none etc.\\n return \\\"doing nothing\\\"\\n if self.targetting[0] == \\\"marching\\\":\\n return \\\"marching -> \\\" + self.targetting[1].color_name()\\n if self.targetting[0] == \\\"defending\\\":\\n return \\\"staying put\\\"\\n assert self.targetting[0] == \\\"sneaking\\\"\\n return \\\"sneaking -> \\\" + self.targetting[1].color_name()\",\n \"def get_target_simple(self):\\n task = self.task.get_task(self.task_id)\\n return str(task['name'])\",\n \"def target_naming(ty,target):\\n de = ty.description(target)\\n de = de[0].upper() + de[1:] + \\\".\\\"\\n return de\",\n \"def process_target(self):\\n assert isinstance(self.target, str)\\n return f\\\"%{super().process_target()}%\\\"\",\n \"def target_label(self):\\n return self._target_label\",\n \"def target(self):\\n return self._properties.get('target')\",\n \"def target(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"target\\\")\",\n \"def target(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"target\\\")\",\n \"def target(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"target\\\")\",\n \"def target(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"target\\\")\",\n \"def target(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"target\\\")\",\n \"def target(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"target\\\")\",\n \"def target(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"target\\\")\",\n \"def target(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"target\\\")\",\n \"def target_text_name(self):\\n name = dsutils._connect_name(\\n self._data_spec.name_prefix[1],\\n self._tgt_decoder.text_tensor_name)\\n return name\",\n \"def target_type(self) -> str:\\n return pulumi.get(self, \\\"target_type\\\")\",\n \"def _get_details(target):\\r\\n assert target is not None and issubclass(target, Target)\\r\\n\\r\\n arg_spec = inspect.getargspec(target.__init__)\\r\\n arg_help = TargetsHelp._get_arg_help(target.__init__.__doc__)\\r\\n\\r\\n min_default_idx = 0\\r\\n if arg_spec.defaults is None:\\r\\n min_default_idx = len(arg_spec.args)\\r\\n elif len(arg_spec.args) > len(arg_spec.defaults):\\r\\n min_default_idx = len(arg_spec.args) - len(arg_spec.defaults)\\r\\n\\r\\n lines = [TargetsHelp.DETAILS_HEADER.substitute(\\r\\n name=TargetsHelp.TARGET_TO_ALIAS[target.__name__], desc=target.__doc__)]\\r\\n\\r\\n max_width = 0\\r\\n for arg in arg_spec.args:\\r\\n max_width = max(max_width, len(arg))\\r\\n\\r\\n wrapper = textwrap.TextWrapper(subsequent_indent=' '*(max_width+4))\\r\\n\\r\\n for idx, val in enumerate(arg_spec.args):\\r\\n has_default = False\\r\\n default_val = None\\r\\n\\r\\n if idx >= min_default_idx:\\r\\n has_default = True\\r\\n default_val = arg_spec.defaults[idx-min_default_idx]\\r\\n\\r\\n if val == 'self':\\r\\n continue\\r\\n help_str = 'No help available for this argument.'\\r\\n try:\\r\\n help_str = arg_help[val]\\r\\n except KeyError:\\r\\n pass\\r\\n if has_default:\\r\\n help_str += ' (default: %s) ' % str(default_val)\\r\\n lines.append(' %s: %s' % (val.rjust(max_width), '\\\\n'.join(wrapper.wrap(help_str))))\\r\\n return lines\",\n \"def identifyTargetType(self, target):\\n ipAddress = re.compile('\\\\d{1,3}\\\\.\\\\d{1,3}\\\\.\\\\d{1,3}\\\\.\\\\d{1,3}')\\n ipFind = re.findall(ipAddress, target)\\n if ipFind is not None and len(ipFind) > 0:\\n return \\\"ip\\\"\\n\\n md5 = re.compile('[a-fA-F0-9]{32}', re.IGNORECASE)\\n md5Find = re.findall(md5,target)\\n if md5Find is not None and len(md5Find) > 0:\\n return \\\"md5\\\"\\n\\n return \\\"hostname\\\"\",\n \"def get_target_name(self):\\n if self.preferred_name is None:\\n target_name = self.original_name\\n elif len(self.preferred_name) > 4:\\n target_name = self.preferred_name\\n else:\\n target_name = self.original_name\\n logger.debug('Source Document target file name: {}'.format(target_name))\\n return target_name\",\n \"def target(self) -> list[str]:\\n if self._target is None:\\n print(self.__class__.target.__doc__)\\n raise SilSubProblemError(\\n \\\"The *target* property has not been set (see above).\\\"\\n )\\n return self._target\",\n \"def __str__(self):\\n return 'Target with value ' + str(self.attributes[AT.VALUE])\",\n \"def str_nfc_target(pnt, verbose):\\n return _nfc.str_nfc_target(pnt, verbose)\",\n \"def target_id(self) -> str:\\n return self._target_id\",\n \"def target_entity_type_name(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"target_entity_type_name\\\")\",\n \"def show_target(self, target):\\n print \\\" \\\" + repr(target.subject) \\\\\\n + \\\" \\\" + target.meaning \\\\\\n + \\\" \\\" + target.verb \\\\\\n + \\\" \\\" + repr(target.object)\",\n \"def time_to_target(self) -> str:\\r\\n # TODO: Figure out how to implement this.\\r\\n self._logger.debug(log_message_formatter(\\r\\n \\\"get\\\", f\\\"{self}\\\", \\\"time_to_target\\\"))\\r\\n return self._time_to_target_options[0]\",\n \"def simplified_target(target):\\n if '_prod_' in target:\\n return 'Production', 'prod'\\n elif 'test' in target:\\n return 'Test', 'test'\\n elif 'nonprod' in target:\\n return 'Non-Production', 'nonprod'\\n elif 'all' in target:\\n return 'All', 'all'\\n else:\\n return 'Target not found!', None\",\n \"def get_target_info():\\n target_binary = get_target_binary()\\n target_platform, target_architecture = get_target_platform(target_binary)\\n target_type = get_target_type()\\n return target_binary, target_platform, target_architecture, target_type\",\n \"def get_target(self):\\n return self._target\",\n \"def target_arn(self) -> str:\\n return self._values.get('target_arn')\",\n \"def target_id(self) -> Optional[str]:\\n return pulumi.get(self, \\\"target_id\\\")\",\n \"def target_type(self) -> Optional[str]:\\n return pulumi.get(self, \\\"target_type\\\")\",\n \"def target(self):\\n return self.data.target\",\n \"def getTargets(targets) -> str:\\n return\\\"\\\"\\\"## Target\\n| |Category| |Task| Estimated Time | Actual Time |\\n| - | -: | - | - | - | - |\\n{previousTargets}\\\"\\\"\\\".format(previousTargets=targets)\",\n \"def __str__(self):\\n if len(self.label) > 0:\\n descr = [\\\"'%s', target='%s' [%s]\\\" % (self.label, self.target.name, self.target.body_type)]\\n else:\\n descr = [\\\"target='%s' [%s]\\\" % (self.target.name, self.target.body_type)]\\n if self.baseline:\\n descr[0] += ', initial baseline offset=%f' % (self.baseline.poly[-1],)\\n if self.beam:\\n descr[0] += ', beam height=%f' % (self.beam.height,)\\n for scan_ind, scan in enumerate(self.scans):\\n descr.append('%4d: %s' % (scan_ind, str(scan)))\\n return '\\\\n'.join(descr)\",\n \"def target_loc(self) -> str:\\n return self._target_loc\",\n \"def getTarget(self):\\n return self.Target\",\n \"def getTarget(self):\\n return self._target\",\n \"def target(self):\\n return self._target\",\n \"def target(self):\\n return self._target\",\n \"def target(self):\\n return self._target\",\n \"def target(self):\\n return self._target\",\n \"def _get_env_target(self, target='default'):\\n return '{target}{env_postfix}'.format(\\n target=target,\\n env_postfix=self._env_postfix)\",\n \"def target_entity_type(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"target_entity_type\\\")\",\n \"def use(target, name):\\n return \\\"The \\\" + name + \\\" takes effect on \\\" + target.name\",\n \"def target_text_id_name(self):\\n name = dsutils._connect_name(\\n self._data_spec.name_prefix[1],\\n self._tgt_decoder.text_id_tensor_name)\\n return name\",\n \"def target(self) :\\n\\t\\ttry :\\n\\t\\t\\treturn self._target\\n\\t\\texcept Exception as e:\\n\\t\\t\\traise e\",\n \"def target(self) :\\n\\t\\ttry :\\n\\t\\t\\treturn self._target\\n\\t\\texcept Exception as e:\\n\\t\\t\\traise e\",\n \"def target(self):\\n return self.__target\",\n \"def target(self):\\n return self.__target\",\n \"def target(self):\\n return self.problem.target\",\n \"def getTarget(self):\\n\\n return self._target\",\n \"def process_target(self):\\n if isinstance(self.target, UUID):\\n self.target = str(self.target)\\n\\n return self.target\",\n \"def _target(self):\\n return self.__target\",\n \"def get_target_info(\\n targetId: Optional[TargetID] = None,\\n) -> Generator[dict, dict, TargetInfo]:\\n response = yield {\\n \\\"method\\\": \\\"Target.getTargetInfo\\\",\\n \\\"params\\\": filter_none({\\\"targetId\\\": str(targetId) if targetId else None}),\\n }\\n return TargetInfo.from_json(response[\\\"targetInfo\\\"])\",\n \"def target_resource_id(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"target_resource_id\\\")\",\n \"def target_resource_id(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"target_resource_id\\\")\",\n \"def Target(self):\\n return self._target\",\n \"def get_target(self, agent, collective, topciprefix=None):\",\n \"def get_name(self):\\n\\t\\treturn self.source.get_name()\",\n \"def get_target_reg( self ):\\r\\n\\t\\tif len( self.lines ) > 0:\\r\\n\\t\\t\\tif self.reg == \\\"eax\\\" and self.lines[-1][1] == \\\"call\\\":\\r\\n\\t\\t# We have a call that overwrites EAX\\r\\n\\t\\t\\t\\treturn \\\"END\\\"\\r\\n\\t\\t\\tif self.lines[-1][2] == self.reg and self.lines[-1][1] not in neutral_mnem:\\r\\n\\t\\t# We have a non-neutral instruction that writes to the register we're tracking\\r\\n\\t\\t\\t\\treturn \\\"END\\\"\\r\\n\\t\\t\\telif self.lines[-1][2].find( self.reg ) != -1:\\r\\n\\t\\t# We have memory access to the location this register is pointing to or an operation on itself\\r\\n\\t\\t\\t\\treturn \\\"\\\"\\r\\n\\t\\t\\telse:\\r\\n\\t\\t# If the target is a register, return this register\\r\\n\\t\\t\\t\\tif self.lines[-1][2] in x86_registers:\\r\\n\\t\\t\\t\\t\\treturn self.lines[-1][2]\\r\\n\\t\\t\\t\\telse:\\r\\n\\t\\t\\t\\t\\treturn \\\"\\\"\\r\\n\\t\\telse:\\r\\n\\t\\t\\treturn \\\"\\\"\",\n \"def get_target_name(f):\\n name = os.path.basename(f)\\n\\n target_number = get_target_number(name)\\n if target_number != 14:\\n target_name = str(target_number)\\n else:\\n # We keep bound and free denotation if puzzle 14.\\n target_name = str(target_number) + \\\\\\n ('b' if 'bound' in name else 'f')\\n return target_name\",\n \"def target(self):\\n return self._definition\",\n \"def get_description(self):\\n return self['command_name']\",\n \"def describe(self) -> str:\",\n \"def target(self, example):\\n return example[self.target_index]\",\n \"def parse_event_target(target: Any) -> Tuple[str, str]:\\n if not target:\\n return \\\"\\\", \\\"\\\"\\n\\n target_type = type(target).__name__\\n\\n if hasattr(target, \\\"uuid\\\"):\\n return target_type, target.uuid\\n\\n if hasattr(target, \\\"id\\\"):\\n return target_type, target.id\\n\\n return target_type, \\\"\\\"\",\n \"def target_resource_guid(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"target_resource_guid\\\")\",\n \"def use(target, name):\\n return \\\"You use the \\\" + name + \\\" to pay \\\" + target.name\",\n \"def target( self ) :\\n\\n return( self.__target )\",\n \"def target(self):\\n return bytes(self[8:16])\",\n \"def target(self) -> Optional[int]:\\n return pulumi.get(self, \\\"target\\\")\",\n \"def target(self) -> Union[str, \\\"STACObject_Type\\\"]:\\n if self._target_object:\\n return self._target_object\\n elif self._target_href:\\n return self._target_href\\n else:\\n raise ValueError(\\\"No target defined for link.\\\")\",\n \"def info(target):\\n co = target.__code__\\n return (co.co_name, co.co_filename, co.co_firstlineno)\",\n \"def getMnemonicForTarget(targetId, table):\\n request = \\\"SELECT textstring FROM %s WHERE role=\\\\\\\"MNEMONIC\\\\\\\" and target=\\\\\\\"%s\\\\\\\"\\\" % (table, targetId)\\n execute(request)\\n row = cursor.fetchone()\\n if row == None:\\n warn(\\\"mnemonic not found for target %s in table %s\\\" % (targetId, table) )\\n else:\\n return row[0]\",\n \"def info():\\n return r\\\"\\\"\\\"Lin-Yu Tseng and Chun Chen, \\\"Multiple trajectory search for Large Scale Global Optimization,\\\" 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), Hong Kong, 2008, pp. 3052-3059. doi: 10.1109/CEC.2008.4631210\\\"\\\"\\\"\",\n \"def _get_description(actor, commit, run_id):\\n return (\\\"Requested by @%s on commit %s\\\\n\\\" % (actor, commit) +\\n \\\"Last updated: %s \\\\n\\\" % _get_datetime() +\\n \\\"**[View integration test log & download artifacts](https://github.com/firebase/firebase-cpp-sdk/actions/runs/%s)**\\\\n\\\" % run_id)\",\n \"def get_target_uri(self, docname: str, type: str = None) -> str:\\n\\n uri = docname + \\\".ipynb\\\"\\n\\n logger.debug(f\\\"[nbtutorial]: Target URI: {uri}\\\")\\n\\n return uri\",\n \"def co_filename(self):\\n assert (\\n self.filename is not None\\n ), \\\"co_filename requires Target created from filename\\\"\\n return self.filename.strpath\",\n \"def get_name(self):\\n return \\\"make\\\"\",\n \"def target_option(s):\\n return s\",\n \"def shortDescription(self):\\n if self._current_test_descr is not None:\\n return self._current_test_descr\\n return super(TestCase, self).shortDescription()\",\n \"def target_to_url(target):\\n if is_wc(target):\\n info = get_svninfo(target)\\n return info[\\\"URL\\\"]\\n return target\",\n \"def getTargetType(self):\\n return self.target_type\",\n \"def __str__(self):\\n return '{trait_name} ({phv}): dataset {pht}'.format(trait_name=self.i_trait_name,\\n phv=self.full_accession,\\n pht=self.source_dataset.full_accession)\",\n \"def display_current_target():\\n marker = 0\\n target = \\\"\\\"\\n with open(vars_file) as f:\\n for line in f:\\n if marker == 1 and '<<:' in line:\\n line_list = line.split(':')\\n target = line_list[1].strip()\\n marker = 0\\n if 'target_arrays:' in line:\\n marker = 1\\n simple_target, current_selection = simplified_target(target)\\n print(f'Current target setting: {simple_target}')\\n return simple_target, current_selection\",\n \"def get_info(self) -> str:\\n raise NotImplementedError()\",\n \"def target(self):\\n return self._task_target\",\n \"def target_group(self) -> pulumi.Output[str]:\\n return pulumi.get(self, \\\"target_group\\\")\",\n \"def _get__target(self):\\n if self._saved_target is None:\\n self._saved_target = self._metadata.get_callable()()\\n \\n return self._saved_target\",\n \"def target_length_name(self):\\n name = dsutils._connect_name(\\n self._data_spec.name_prefix[1],\\n self._tgt_decoder.length_tensor_name)\\n return name\",\n \"def __str__(self):\\n struct_repr = \\\", \\\".join([\\n \\\"group: \\\" + str(self.group),\\n \\\"controls: \\\" + str(self.controls)\\n ])\\n\\n return f\\\"ActuatorControlTarget: [{struct_repr}]\\\"\",\n \"def get_info_string(self) -> str:\\n return \\\"Not implemented\\\"\",\n \"def target_id(self):\\n\\n return self._target_id\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.73063004","0.72933376","0.7276515","0.7202048","0.71281767","0.696577","0.6881676","0.68652797","0.6742786","0.67377156","0.6706205","0.66736144","0.6576408","0.6562085","0.6562085","0.6562085","0.6562085","0.6562085","0.6562085","0.6562085","0.6562085","0.6555541","0.65542495","0.6551583","0.65413034","0.6507178","0.6495755","0.64857465","0.6434137","0.6432839","0.64117914","0.639408","0.6374682","0.6344693","0.63375705","0.6335527","0.63177204","0.6268114","0.62674206","0.6266736","0.6241796","0.6221497","0.619679","0.616202","0.61288804","0.6125816","0.6125816","0.6125816","0.6125816","0.61186975","0.60745054","0.6065403","0.6042345","0.6004059","0.6004059","0.6001576","0.6001576","0.5992967","0.592735","0.59091115","0.5881796","0.58705586","0.58642906","0.58642906","0.58627653","0.5859185","0.5854678","0.58502144","0.5838173","0.58328575","0.58070153","0.58036834","0.5801716","0.5795406","0.5790628","0.5781412","0.5745908","0.57446456","0.57332075","0.57045305","0.56919944","0.5678286","0.5651472","0.5646914","0.5642728","0.5633605","0.5604475","0.56040114","0.55989736","0.5595338","0.5592731","0.55804473","0.5579592","0.5577079","0.5567572","0.5567304","0.5565543","0.5562627","0.55535364","0.5552582","0.55501825"],"string":"[\n \"0.73063004\",\n \"0.72933376\",\n \"0.7276515\",\n \"0.7202048\",\n \"0.71281767\",\n \"0.696577\",\n \"0.6881676\",\n \"0.68652797\",\n \"0.6742786\",\n \"0.67377156\",\n \"0.6706205\",\n \"0.66736144\",\n \"0.6576408\",\n \"0.6562085\",\n \"0.6562085\",\n \"0.6562085\",\n \"0.6562085\",\n \"0.6562085\",\n \"0.6562085\",\n \"0.6562085\",\n \"0.6562085\",\n \"0.6555541\",\n \"0.65542495\",\n \"0.6551583\",\n \"0.65413034\",\n \"0.6507178\",\n \"0.6495755\",\n \"0.64857465\",\n \"0.6434137\",\n \"0.6432839\",\n \"0.64117914\",\n \"0.639408\",\n \"0.6374682\",\n \"0.6344693\",\n \"0.63375705\",\n \"0.6335527\",\n \"0.63177204\",\n \"0.6268114\",\n \"0.62674206\",\n \"0.6266736\",\n \"0.6241796\",\n \"0.6221497\",\n \"0.619679\",\n \"0.616202\",\n \"0.61288804\",\n \"0.6125816\",\n \"0.6125816\",\n \"0.6125816\",\n \"0.6125816\",\n \"0.61186975\",\n \"0.60745054\",\n \"0.6065403\",\n \"0.6042345\",\n \"0.6004059\",\n \"0.6004059\",\n \"0.6001576\",\n \"0.6001576\",\n \"0.5992967\",\n \"0.592735\",\n \"0.59091115\",\n \"0.5881796\",\n \"0.58705586\",\n \"0.58642906\",\n \"0.58642906\",\n \"0.58627653\",\n \"0.5859185\",\n \"0.5854678\",\n \"0.58502144\",\n \"0.5838173\",\n \"0.58328575\",\n \"0.58070153\",\n \"0.58036834\",\n \"0.5801716\",\n \"0.5795406\",\n \"0.5790628\",\n \"0.5781412\",\n \"0.5745908\",\n \"0.57446456\",\n \"0.57332075\",\n \"0.57045305\",\n \"0.56919944\",\n \"0.5678286\",\n \"0.5651472\",\n \"0.5646914\",\n \"0.5642728\",\n \"0.5633605\",\n \"0.5604475\",\n \"0.56040114\",\n \"0.55989736\",\n \"0.5595338\",\n \"0.5592731\",\n \"0.55804473\",\n \"0.5579592\",\n \"0.5577079\",\n \"0.5567572\",\n \"0.5567304\",\n \"0.5565543\",\n \"0.5562627\",\n \"0.55535364\",\n \"0.5552582\",\n \"0.55501825\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":88595,"cells":{"query":{"kind":"string","value":"Get the feature dimension of this data."},"document":{"kind":"string","value":"def feature_size(self):\n return self.fingerprint_length"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def feature_dimension(self) -> int:\n return self._feature_dimension","def feature_dim(self):\n return feature_dim_from_test_system(self)","def features_dim(self):\n if not self.exposes_features:\n return None\n\n dim = self._features_op.outputs[0].get_shape().as_list()[-1]\n if dim is None:\n logger.warning(\n \"Unable to statically get feature dimension; returning None\"\n )\n\n return dim","def feature_dim(self):\n raise NotImplementedError","def dim(self):\n if self._classifier is None:\n with self:\n return self._classifier.features_dim\n\n return self._classifier.features_dim","def get_data_dim(self):\n return self.data_dim","def dimension(self):\n return self._dim","def get_dimension(self):\n return self._dimension","def dimension(self):\n return self._dimension","def dimension(self):\n return self._dimension","def dimension(self):\n return self._dimension","def dimension(self):\n return self._dimension","def dimension_count(self):\n return self._dimensionCount","def get_dim(self):\n return self._dim","def get_dim(self):\n return self.dim","def get_num_dimensions(self):\n dimensions = self.data.shape\n return dimensions[1]","def _get_feature_dim(schema: schema_pb2.Schema, feature_name: str) -> int:\n\n for feature in schema.feature:\n if feature.name == feature_name:\n return feature.shape.dim[0].size\n raise ValueError('Feature not found: {}'.format(feature_name))","def dimension(self) -> float:\n return self._dimensions","def dimension_size(self):\n return self._dim","def dimension(self) -> int:\n return self.options.dimension","def get_feature_space_dimensionality(self):\n return self.nextIdPruned","def get_dimension(self) -> int:\n return self.embedder.get_dimension()","def dimension(self):\n\t\treturn self.d","def get_dimension(self):\n return","def getDimension(self):\n dim = len(self.__axis_labels__)\n if dim == 0:\n # Labels weren't set, so how about the data\n dim = self[0].dim()\n return dim","def dimensionality(self):\n return int(self.nDims)","def get_dimension_length(self):\n pass","def dimension(self):\n return self.__N","def dim(self):\n return self._dim","def get_dimensionality(self) -> int:\n return self.dimensionality","def get_input_dimension(self):\n return self.layers[0].get_input_dimension()","def feature_len(self):\n return len(self.coord)","def get_dimension_number(self) -> int:\n return np.squeeze(self._channel_arrays[0]).ndim","def get_num_features(self):\r\n \r\n return len(self[0]['x'])","def n_dim(self):\n return self._n_dim","def num_dim(self):\n return len(self._dimensions)","def num_dim(self):\n return len(self._dimensions)","def dim(self):\n return self.__dim__","def get_dim(self, name):\n return len(self.root_group.dimensions[name])","def _get_observation_dimension(self):\n return len(self._get_observation_np())","def dim(self) -> int:\n return self._n_dim","def dim(self):\n return self._d","def getDimensionality(self):\n dimensionality = self._distribution.returnDimensionality()\n return dimensionality","def spatial_dimension(self):\r\n return self.multi_index.spatial_dimension","def getDimension(self):\n return len(self.components)","def ndim(self):\n return self.X.ndim","def get_input_dimension(self):\n return self.in_dim","def ndim(self):\n return self.data.ndim","def get_num_points(self):\n dimensions = self.data.shape\n return dimensions[0]","def get_in_dim(self) -> int:\n return self.in_dim","def dim(self):\n return len(self.shape)","def dim(self):\n return len(self.shape)","def get_dimension_width(self):\n pass","def dimensions(self) -> int:\n return pulumi.get(self, \"dimensions\")","def dimension(self):\n return 3*self.genus - 3 + self.n","def spatial_dimension(self):\r\n pass","def dim(self):\n\t\treturn self.D","def num_features(self):\n if self.x is None:\n return 0\n return 1 if self.x.dim() == 1 else self.x.size(1)","def n_features(self):\n return self.components.shape[-1]","def x_dim(self) -> str:\n if self.get_attrs(\"x_dim\") not in self._obj.dims:\n self.set_spatial_dims()\n return self.attrs[\"x_dim\"]","def ndim(self):\n if self._ndim is None:\n self._ndim = self.get_mesh_dimension()\n\n return self._ndim","def dimension(self):\r\n a = 0\r\n for x in self.faces():\r\n if (len(x) > a):\r\n a = len(x) \r\n return a-1","def features_size(self) -> int:\n return len(self.data[0].features) if len(self.data) > 0 and self.data[0].features is not None else None","def InferSpatialDimension(self):\n\n assert self.points is not None\n # if self.points.shape[1] == 3:\n # if self.element_type == \"tri\" or self.element_type == \"quad\":\n # print(\"3D surface mesh of \", self.element_type)\n\n return self.points.shape[1]","def getNumDimensions(self):\n return len(self.di.keys())","def num_node_features(self) -> int:\n data, _, _ = self[0]\n if hasattr(data, 'num_node_features'):\n return data.num_node_features\n raise AttributeError(f\"'{data.__class__.__name__}' object has no \"\n f\"attribute 'num_node_features'\")","def get_ndim(self):\n return self.ndim","def dim(self):\n return self._domain.dim","def ndim(self):\n return self.__value.ndim","def dim(self):\n return self._historical_data.dim","def num_feature(self):\n if self.handle is None:\n raise AttributeError('Model not loaded yet')\n out = ctypes.c_size_t()\n _check_call(_LIB.TreeliteQueryNumFeature(self.handle, ctypes.byref(out)))\n return out.value","def width(self) -> int:\n return self._obj[self.x_dim].size","def xdim(self):\n return len(self._x)","def ndim(self):\n return self._ndim","def dim(self):\n return self.raw_wires.get_dim();","def get_data_dimensions(self):\n return image_utils.convert_shape_indexing(self._get_data_dimensions_rc(),\"rc\",self.image_indexing)","def ndim(self):\n return len(self.point)","def getDepth(self):\n return _libsbml.Dimensions_getDepth(self)","def shape(self):\n return self.dataset.shape","def dims(self):\n return self[0].dims","def _getdim(x):\n \n if np.ndim(x) > 1:\n \n dim = x.shape[-1]\n \n else:\n \n dim = 0\n \n return dim","def depth(self):\n return _libsbml.Dimensions_depth(self)","def dim(self):\n if not self.is_indexed():\n return 0\n return getattr(self._index, 'dimen', 0)","def get_num_features(self, ndim: int) -> int:\n nb_features = 0\n for feature_group in self.features_group_list:\n nb_features += feature_group.num_features(ndim)\n return nb_features","def input_dim(self):\n if hasattr(self, \"_input_dim\"):\n return self._input_dim\n return self.__input_dim","def ndim(self) -> int:\n return self[0].ndim","def get_feature_dims(self):\n db_task = self.analyze_db_task(constants.TRAIN_DB)\n return [db_task.image_height, db_task.image_width, db_task.image_channels]","def get_dimensions(self, variable):\n try:\n var_dimension = self.dataset[variable].dims\n return var_dimension\n except:\n print(\"Error Occurred: No Dimensions detected... Exiting. \")\n exit()","def num_edge_features(self) -> int:\n data, _, _ = self[0]\n if hasattr(data, 'num_edge_features'):\n return data.num_edge_features\n raise AttributeError(f\"'{data.__class__.__name__}' object has no \"\n f\"attribute 'num_edge_features'\")","def N(self):\n return self._dimensions","def dimensionality(self):\n if self.vector.shape is ():\n return 0\n if len(self.vector.shape) is 1:\n return 1\n _, dim = self.vector.shape\n return dim","def dim(self):\n if '_dim' in self.__dict__:\n return self._dim\n\n if len(self._Vrepresentation)==0:\n self._dim = -1\n return self._dim\n\n origin = vector(self._Vrepresentation[0])\n v_list = [ vector(v)-origin for v in self._Vrepresentation ]\n self._dim = matrix(v_list).rank()\n return self._dim","def maxdim(self):\n return self._maxdim","def dimension(self):\n return np.prod(np.asarray(self.subsystem_dims))","def num_node_features(self):\n return self[0].num_node_features","def get_dimension(self) -> \"IDimension\":\n raise NotImplementedError","def _get_ndim(self):\n return len(self.level_shapes[0])","def ndim(self):\n return len(self.shape)","def ndim(self):\n return len(self.shape)","def ndim(self):\n return len(self.shape)","def ndim(self):\n return len(self.shape)"],"string":"[\n \"def feature_dimension(self) -> int:\\n return self._feature_dimension\",\n \"def feature_dim(self):\\n return feature_dim_from_test_system(self)\",\n \"def features_dim(self):\\n if not self.exposes_features:\\n return None\\n\\n dim = self._features_op.outputs[0].get_shape().as_list()[-1]\\n if dim is None:\\n logger.warning(\\n \\\"Unable to statically get feature dimension; returning None\\\"\\n )\\n\\n return dim\",\n \"def feature_dim(self):\\n raise NotImplementedError\",\n \"def dim(self):\\n if self._classifier is None:\\n with self:\\n return self._classifier.features_dim\\n\\n return self._classifier.features_dim\",\n \"def get_data_dim(self):\\n return self.data_dim\",\n \"def dimension(self):\\n return self._dim\",\n \"def get_dimension(self):\\n return self._dimension\",\n \"def dimension(self):\\n return self._dimension\",\n \"def dimension(self):\\n return self._dimension\",\n \"def dimension(self):\\n return self._dimension\",\n \"def dimension(self):\\n return self._dimension\",\n \"def dimension_count(self):\\n return self._dimensionCount\",\n \"def get_dim(self):\\n return self._dim\",\n \"def get_dim(self):\\n return self.dim\",\n \"def get_num_dimensions(self):\\n dimensions = self.data.shape\\n return dimensions[1]\",\n \"def _get_feature_dim(schema: schema_pb2.Schema, feature_name: str) -> int:\\n\\n for feature in schema.feature:\\n if feature.name == feature_name:\\n return feature.shape.dim[0].size\\n raise ValueError('Feature not found: {}'.format(feature_name))\",\n \"def dimension(self) -> float:\\n return self._dimensions\",\n \"def dimension_size(self):\\n return self._dim\",\n \"def dimension(self) -> int:\\n return self.options.dimension\",\n \"def get_feature_space_dimensionality(self):\\n return self.nextIdPruned\",\n \"def get_dimension(self) -> int:\\n return self.embedder.get_dimension()\",\n \"def dimension(self):\\n\\t\\treturn self.d\",\n \"def get_dimension(self):\\n return\",\n \"def getDimension(self):\\n dim = len(self.__axis_labels__)\\n if dim == 0:\\n # Labels weren't set, so how about the data\\n dim = self[0].dim()\\n return dim\",\n \"def dimensionality(self):\\n return int(self.nDims)\",\n \"def get_dimension_length(self):\\n pass\",\n \"def dimension(self):\\n return self.__N\",\n \"def dim(self):\\n return self._dim\",\n \"def get_dimensionality(self) -> int:\\n return self.dimensionality\",\n \"def get_input_dimension(self):\\n return self.layers[0].get_input_dimension()\",\n \"def feature_len(self):\\n return len(self.coord)\",\n \"def get_dimension_number(self) -> int:\\n return np.squeeze(self._channel_arrays[0]).ndim\",\n \"def get_num_features(self):\\r\\n \\r\\n return len(self[0]['x'])\",\n \"def n_dim(self):\\n return self._n_dim\",\n \"def num_dim(self):\\n return len(self._dimensions)\",\n \"def num_dim(self):\\n return len(self._dimensions)\",\n \"def dim(self):\\n return self.__dim__\",\n \"def get_dim(self, name):\\n return len(self.root_group.dimensions[name])\",\n \"def _get_observation_dimension(self):\\n return len(self._get_observation_np())\",\n \"def dim(self) -> int:\\n return self._n_dim\",\n \"def dim(self):\\n return self._d\",\n \"def getDimensionality(self):\\n dimensionality = self._distribution.returnDimensionality()\\n return dimensionality\",\n \"def spatial_dimension(self):\\r\\n return self.multi_index.spatial_dimension\",\n \"def getDimension(self):\\n return len(self.components)\",\n \"def ndim(self):\\n return self.X.ndim\",\n \"def get_input_dimension(self):\\n return self.in_dim\",\n \"def ndim(self):\\n return self.data.ndim\",\n \"def get_num_points(self):\\n dimensions = self.data.shape\\n return dimensions[0]\",\n \"def get_in_dim(self) -> int:\\n return self.in_dim\",\n \"def dim(self):\\n return len(self.shape)\",\n \"def dim(self):\\n return len(self.shape)\",\n \"def get_dimension_width(self):\\n pass\",\n \"def dimensions(self) -> int:\\n return pulumi.get(self, \\\"dimensions\\\")\",\n \"def dimension(self):\\n return 3*self.genus - 3 + self.n\",\n \"def spatial_dimension(self):\\r\\n pass\",\n \"def dim(self):\\n\\t\\treturn self.D\",\n \"def num_features(self):\\n if self.x is None:\\n return 0\\n return 1 if self.x.dim() == 1 else self.x.size(1)\",\n \"def n_features(self):\\n return self.components.shape[-1]\",\n \"def x_dim(self) -> str:\\n if self.get_attrs(\\\"x_dim\\\") not in self._obj.dims:\\n self.set_spatial_dims()\\n return self.attrs[\\\"x_dim\\\"]\",\n \"def ndim(self):\\n if self._ndim is None:\\n self._ndim = self.get_mesh_dimension()\\n\\n return self._ndim\",\n \"def dimension(self):\\r\\n a = 0\\r\\n for x in self.faces():\\r\\n if (len(x) > a):\\r\\n a = len(x) \\r\\n return a-1\",\n \"def features_size(self) -> int:\\n return len(self.data[0].features) if len(self.data) > 0 and self.data[0].features is not None else None\",\n \"def InferSpatialDimension(self):\\n\\n assert self.points is not None\\n # if self.points.shape[1] == 3:\\n # if self.element_type == \\\"tri\\\" or self.element_type == \\\"quad\\\":\\n # print(\\\"3D surface mesh of \\\", self.element_type)\\n\\n return self.points.shape[1]\",\n \"def getNumDimensions(self):\\n return len(self.di.keys())\",\n \"def num_node_features(self) -> int:\\n data, _, _ = self[0]\\n if hasattr(data, 'num_node_features'):\\n return data.num_node_features\\n raise AttributeError(f\\\"'{data.__class__.__name__}' object has no \\\"\\n f\\\"attribute 'num_node_features'\\\")\",\n \"def get_ndim(self):\\n return self.ndim\",\n \"def dim(self):\\n return self._domain.dim\",\n \"def ndim(self):\\n return self.__value.ndim\",\n \"def dim(self):\\n return self._historical_data.dim\",\n \"def num_feature(self):\\n if self.handle is None:\\n raise AttributeError('Model not loaded yet')\\n out = ctypes.c_size_t()\\n _check_call(_LIB.TreeliteQueryNumFeature(self.handle, ctypes.byref(out)))\\n return out.value\",\n \"def width(self) -> int:\\n return self._obj[self.x_dim].size\",\n \"def xdim(self):\\n return len(self._x)\",\n \"def ndim(self):\\n return self._ndim\",\n \"def dim(self):\\n return self.raw_wires.get_dim();\",\n \"def get_data_dimensions(self):\\n return image_utils.convert_shape_indexing(self._get_data_dimensions_rc(),\\\"rc\\\",self.image_indexing)\",\n \"def ndim(self):\\n return len(self.point)\",\n \"def getDepth(self):\\n return _libsbml.Dimensions_getDepth(self)\",\n \"def shape(self):\\n return self.dataset.shape\",\n \"def dims(self):\\n return self[0].dims\",\n \"def _getdim(x):\\n \\n if np.ndim(x) > 1:\\n \\n dim = x.shape[-1]\\n \\n else:\\n \\n dim = 0\\n \\n return dim\",\n \"def depth(self):\\n return _libsbml.Dimensions_depth(self)\",\n \"def dim(self):\\n if not self.is_indexed():\\n return 0\\n return getattr(self._index, 'dimen', 0)\",\n \"def get_num_features(self, ndim: int) -> int:\\n nb_features = 0\\n for feature_group in self.features_group_list:\\n nb_features += feature_group.num_features(ndim)\\n return nb_features\",\n \"def input_dim(self):\\n if hasattr(self, \\\"_input_dim\\\"):\\n return self._input_dim\\n return self.__input_dim\",\n \"def ndim(self) -> int:\\n return self[0].ndim\",\n \"def get_feature_dims(self):\\n db_task = self.analyze_db_task(constants.TRAIN_DB)\\n return [db_task.image_height, db_task.image_width, db_task.image_channels]\",\n \"def get_dimensions(self, variable):\\n try:\\n var_dimension = self.dataset[variable].dims\\n return var_dimension\\n except:\\n print(\\\"Error Occurred: No Dimensions detected... Exiting. \\\")\\n exit()\",\n \"def num_edge_features(self) -> int:\\n data, _, _ = self[0]\\n if hasattr(data, 'num_edge_features'):\\n return data.num_edge_features\\n raise AttributeError(f\\\"'{data.__class__.__name__}' object has no \\\"\\n f\\\"attribute 'num_edge_features'\\\")\",\n \"def N(self):\\n return self._dimensions\",\n \"def dimensionality(self):\\n if self.vector.shape is ():\\n return 0\\n if len(self.vector.shape) is 1:\\n return 1\\n _, dim = self.vector.shape\\n return dim\",\n \"def dim(self):\\n if '_dim' in self.__dict__:\\n return self._dim\\n\\n if len(self._Vrepresentation)==0:\\n self._dim = -1\\n return self._dim\\n\\n origin = vector(self._Vrepresentation[0])\\n v_list = [ vector(v)-origin for v in self._Vrepresentation ]\\n self._dim = matrix(v_list).rank()\\n return self._dim\",\n \"def maxdim(self):\\n return self._maxdim\",\n \"def dimension(self):\\n return np.prod(np.asarray(self.subsystem_dims))\",\n \"def num_node_features(self):\\n return self[0].num_node_features\",\n \"def get_dimension(self) -> \\\"IDimension\\\":\\n raise NotImplementedError\",\n \"def _get_ndim(self):\\n return len(self.level_shapes[0])\",\n \"def ndim(self):\\n return len(self.shape)\",\n \"def ndim(self):\\n return len(self.shape)\",\n \"def ndim(self):\\n return len(self.shape)\",\n \"def ndim(self):\\n return len(self.shape)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.89637285","0.86458623","0.8564586","0.83512133","0.8064637","0.7931219","0.78060144","0.7794164","0.77869695","0.77869695","0.77869695","0.77869695","0.7766574","0.7721604","0.7697934","0.7682128","0.7605907","0.75448817","0.75407034","0.75349915","0.7521258","0.75125605","0.7505486","0.74562395","0.74494237","0.7421294","0.7397774","0.7391386","0.73731583","0.73686844","0.72501504","0.72475934","0.7245842","0.7230839","0.7230666","0.72041976","0.72041976","0.719971","0.71906227","0.7160303","0.71540236","0.71539104","0.7144492","0.7112119","0.71049285","0.7084107","0.70770854","0.7070734","0.70566195","0.7036852","0.7032092","0.7032092","0.70265114","0.69989115","0.69977814","0.6982276","0.6979679","0.69594646","0.6945762","0.6939971","0.6918311","0.688296","0.6881607","0.6868143","0.6863835","0.68607086","0.68430203","0.68374753","0.68340236","0.6818847","0.6815556","0.67973113","0.67958057","0.67948765","0.67909795","0.6771583","0.6746991","0.67172605","0.6712526","0.671212","0.67072433","0.6706404","0.67003906","0.6695825","0.66836286","0.66767913","0.66536564","0.66519886","0.663929","0.66345197","0.6626914","0.6614353","0.66018546","0.6597531","0.6595745","0.6595205","0.65909094","0.65782976","0.65782976","0.65782976","0.65782976"],"string":"[\n \"0.89637285\",\n \"0.86458623\",\n \"0.8564586\",\n \"0.83512133\",\n \"0.8064637\",\n \"0.7931219\",\n \"0.78060144\",\n \"0.7794164\",\n \"0.77869695\",\n \"0.77869695\",\n \"0.77869695\",\n \"0.77869695\",\n \"0.7766574\",\n \"0.7721604\",\n \"0.7697934\",\n \"0.7682128\",\n \"0.7605907\",\n \"0.75448817\",\n \"0.75407034\",\n \"0.75349915\",\n \"0.7521258\",\n \"0.75125605\",\n \"0.7505486\",\n \"0.74562395\",\n \"0.74494237\",\n \"0.7421294\",\n \"0.7397774\",\n \"0.7391386\",\n \"0.73731583\",\n \"0.73686844\",\n \"0.72501504\",\n \"0.72475934\",\n \"0.7245842\",\n \"0.7230839\",\n \"0.7230666\",\n \"0.72041976\",\n \"0.72041976\",\n \"0.719971\",\n \"0.71906227\",\n \"0.7160303\",\n \"0.71540236\",\n \"0.71539104\",\n \"0.7144492\",\n \"0.7112119\",\n \"0.71049285\",\n \"0.7084107\",\n \"0.70770854\",\n \"0.7070734\",\n \"0.70566195\",\n \"0.7036852\",\n \"0.7032092\",\n \"0.7032092\",\n \"0.70265114\",\n \"0.69989115\",\n \"0.69977814\",\n \"0.6982276\",\n \"0.6979679\",\n \"0.69594646\",\n \"0.6945762\",\n \"0.6939971\",\n \"0.6918311\",\n \"0.688296\",\n \"0.6881607\",\n \"0.6868143\",\n \"0.6863835\",\n \"0.68607086\",\n \"0.68430203\",\n \"0.68374753\",\n \"0.68340236\",\n \"0.6818847\",\n \"0.6815556\",\n \"0.67973113\",\n \"0.67958057\",\n \"0.67948765\",\n \"0.67909795\",\n \"0.6771583\",\n \"0.6746991\",\n \"0.67172605\",\n \"0.6712526\",\n \"0.671212\",\n \"0.67072433\",\n \"0.6706404\",\n \"0.67003906\",\n \"0.6695825\",\n \"0.66836286\",\n \"0.66767913\",\n \"0.66536564\",\n \"0.66519886\",\n \"0.663929\",\n \"0.66345197\",\n \"0.6626914\",\n \"0.6614353\",\n \"0.66018546\",\n \"0.6597531\",\n \"0.6595745\",\n \"0.6595205\",\n \"0.65909094\",\n \"0.65782976\",\n \"0.65782976\",\n \"0.65782976\",\n \"0.65782976\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":88596,"cells":{"query":{"kind":"string","value":"Convert the units of a bispectrum descriptor. Since these do not really have units this function does nothing yet."},"document":{"kind":"string","value":"def convert_units(array, in_units=\"None\"):\n if in_units == \"None\" or in_units is None:\n return array\n else:\n raise Exception(\"Unsupported unit for bispectrum descriptors.\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def convert_units(self):\n for prod in (\"ier\", \"ier_inc_rain\"):\n self.data[prod].data[:] /= 1e6","def backconvert_units(array, out_units):\n if out_units == \"None\" or out_units is None:\n return array\n else:\n raise Exception(\"Unsupported unit for bispectrum descriptors.\")","def convert_units(self, units):\n self.unit_array = self.unit_array.to(units)","def convert_units(unt, origunits):\n if unt[0:3] == origunits[0:3] | unt[0:3] == 'ori':\n units = origunits\n convf = 1\n else:\n if 'fee' == unt[(((0:3 -1) -1) -1)]:\n if origunits[0:3] == 'met':\n units = 'feet'\n convf = 3.2808399\n else:\n units = origunits\n convf = 1\n else:\n if 'met' == unt[(((0:3 -1) -1) -1)]:\n if origunits[0:3] == 'fee':\n units = 'meters'\n convf = 0.3048\n else:\n units = origunits\n convf = 1\n else:\n if 'm/s' == unt[(((0:3 -1) -1) -1)]:\n if origunits[0:3] == 'kno':\n units = 'meters/sec'\n convf = 0.51444444\n else:\n units = origunits\n convf = 1\n else:\n if 'kno' == unt[(((0:3 -1) -1) -1)]:\n if origunits[0:3] == 'm/s':\n units = 'knots'\n convf = 1.9438445\n else:\n units = origunits\n convf = 1\n else:\n error('Unknown units')\n #\n return units, convf","def convert(self):\n return _libsbml.SBMLUnitsConverter_convert(self)","def convert(self):\n return _libsbml.SBMLInferUnitsConverter_convert(self)","def convert_units(data, hdr, conv_to = \"surf_br\"):\n \n data_unit = hdr[\"SIGUNIT\"]\n \n if \"Jy/pix\" in data_unit:\n # pixel size in rad\n px_x = abs(hdr[\"CDELT1\"])*2*np.pi/360\n px_y = abs(hdr[\"CDELT2\"])*2*np.pi/360\n \n #pixel size in arcsec\n \n px_x = abs(hdr[\"CDELT1\"])*3600\n px_y = abs(hdr[\"CDELT2\"])*3600\n conversion_factor = 1000/(px_x*px_y)\n \n unit_label = \"mJy/arcsec^2\"\n \n #in case we want to convert to units flux, we need to multiply by the size (in steradians) of a pixel.\n if conv_to == \"flux\":\n conversion_factor*=abs(hdr[\"CDELT1\"])*abs(hdr[\"CDELT2\"])*(2*np.pi/360)**2\n unit_label = \"mJy\"\n \n data *= conversion_factor\n hdr[\"SIGUNIT\"] = unit_label\n else:\n print(\"\\t[WARNING]\\t \"+data_unit+\" conversion not yet implemented. No conversion performed.\")\n \n return data, hdr","def convertUnits(self, varname, arr):\n if varname == \"SPDQ\" or varname == \"PHQ\":\n return arr*2.5e6/1000.\n return arr","def convert_to_unit(self, data, unit):\n\n res = OrderedDict()\n\n # Loop over data and overwrite\n for ch in data:\n _idx = self.channels.index(ch)\n # Get data, scale and type of channel\n val, scale, _type = data[ch], self.daq_setup['devices']['adc']['ro_scales'][_idx], self.daq_setup['devices']['adc']['types'][_idx]\n # Adjust scale in case we're looking at SEM's sum signal; in this case current is multiplied by factor of 4\n scale *= 1 if _type != 'sem_sum' else 4\n\n res[ch] = val / 5.0 * scale * 1e-9 if unit == 'A' else val * 5.0 / 1e-9 / scale\n\n return res","def resolve_units(obj, _):\n return obj.units.decode()","def units_to_fits(unit):\n if unit is None:\n unit = Unit('')\n return unit.to_string(\"fits\").upper()","def convert_units(data, units):\n # Build the dictionary of units conversions\n convert = {'m' : [1.0, 0., 'm'], \n 'meter' : [1.0, 0., 'm'], \n 'deg C' : [1.0, 273.15, 'K'], \n 'Celsius' : [1.0, 273.15, 'K'], \n 'K' : [1.0, 0., 'K'],\n 'db' : [1.e4, 101325., 'Pa'], \n 'Pa' : [1.0, 0., 'Pa'],\n 'mg/m^3': [1.e-6, 0., 'kg/m^3'], \n 'S/m': [1.0, 0., 'S/m'],\n 'mS/m' : [1.e-3, 0., 'S/m'],\n 'psu': [1.0, 0., 'psu'], \n 'salinity': [1.0, 0., 'psu'], \n 'kg/m^3': [1.0, 0., 'kg/m^3'], \n 'kilogram meter-3': [1.0, 0., 'kg/m^3'], \n 'm/s': [1.0, 0., 'm/s'], \n 'mg/l': [1.e-3, 0., 'kg/m^3'],\n 'meter second-1' : [1.0, 0., 'm/s'],\n 'm.s-1' : [1.0, 0., 'm/s'],\n 'pH units' : [1.0, 0., 'pH units'],\n 'MPa' : [1.e6, 0., 'Pa'],\n '--' : [1.0, 0., '--'],\n 'mD' : [9.869233e-16, 0., 'm^2'],\n 'um' : [1.e-6, 0., 'm'],\n 'm/s 1e-9' : [1.e-9, 0., 'm/s'],\n 'm/s 1e-7' : [1.e-7, 0., 'm/s'],\n 'wt.%' : [10., 0., 'psu'],\n '10^-15 m^2' : [1.e-15, 0., 'm^2'],\n 'm^2' : [1., 0., 'm^2'],\n 'kg/m^2/year' : [3.168808781402895e-08, 0., 'kg/m^2/s'] \n } \n \n # Make sure the data are a numpy array and the units are a list\n if isinstance(data, float) or isinstance(data, int):\n data = np.array([data])\n if isinstance(data, list):\n data = np.array(data)\n if isinstance(units, str) or isinstance(units, unicode):\n units = [units]\n if units == None:\n units = ['']\n \n # Make sure you can slice through the columns: must be two-dimensional\n sh = data.shape\n data = np.atleast_2d(data)\n \n # Allow conversion of a row of data if all of the same unit\n if len(units) == 1 and data.shape[1] > 1:\n data = data.transpose()\n \n # Create an emtpy array to hold the output\n out_data = np.zeros(data.shape)\n out_units = []\n \n # Convert the units\n for i in range(len(units)):\n try:\n out_data[:,i] = data[:,i] * convert[units[i]][0] + \\\n convert[units[i]][1]\n out_units += [convert[units[i]][2]]\n except KeyError:\n print('Do not know how to convert %s to mks units' % units[i])\n print('Continuing without converting these units...')\n out_data[:,i] = data[:,i]\n out_units += units[i]\n \n # Return the converted data in the original shape\n out_data = np.reshape(out_data, sh, 'C')\n return (out_data, out_units)","def get_units(self):\r\n msg = struct.pack('>2B', 56, 14)\r\n response = self.query(msg)\r\n\r\n if response[1] == 2:\r\n units = 'A'\r\n to_nm_multiplier = 1 / 10\r\n elif response[1] == 1:\r\n units = 'nm'\r\n to_nm_multiplier = 1\r\n elif response[1] == 0:\r\n units = 'um'\r\n to_nm_multiplier = 1000\r\n else:\r\n raise ValueError('Units not recognised.')\r\n\r\n # Save results locally too for quick re-use\r\n self._current_units = units\r\n self._current_to_nm_multiplier = to_nm_multiplier\r\n\r\n return units, to_nm_multiplier","def __convert_to_mm(self, value, in_devunit=True):\r\n if in_devunit:\r\n value /= self.DEVUNIT_RATIO\r\n return value","def _convert_value(self, value, unit, axis):\n if hasattr(value, 'units'):\n return value.to(unit).magnitude\n else:\n return self._reg.Quantity(value, axis.get_units()).to(unit).magnitude","def test_convert_compatible_units(self):\n result = convert_units(self.arr, 'degC')\n expected_data = np.array([[-273.15, -272.15], [-271.15, -270.15]])\n expected_units = cf_units.Unit('degC')\n self.assertEquals(result.units, expected_units)\n self.assertArrayEqual(result.data, expected_data)","def useUnits():","def to_unit(self, unit):\n unit = _find_unit(unit)\n self.value = _convert_value(self.value, self.unit, unit)\n self.unit = unit","def extract_specs(self):\n vDeflection_unit = \"lcd-info.{}.conversion-set.conversion.force.scaling.unit.unit\".format(\n self.channel_numbers[\"vDeflection\"])\n self.units[\"vDeflection\"] = self.general[vDeflection_unit]\n\n height_unit = \"lcd-info.{}.conversion-set.conversion.nominal.scaling.unit.unit\".format(\n self.channel_numbers[\"height\"])\n self.units[\"height\"] = self.general[height_unit]","def unit_converter(val, from_u, to_u):\n\tconverter = {'b':0, 'k':1, 'm':2, 'g':3, 't':4}\n\tif converter[from_u] < converter[to_u]:\n\t\tval = float(val)\n\t\tfor _ in range(converter[to_u] - converter[from_u]):\n\t\t\tval = val/1024\n\telse:\n\t\tfor _ in range(converter[from_u] - converter[to_u]):\n\t\t\tval = val * 1024\n\t\t\t\n\treturn val","def normalize_units(data):\n for obj in data:\n obj['unit'] = normalize_units_function(obj.get('unit', ''))\n # for param in ds.get('parameters', {}).values():\n # if 'unit' in param:\n # param['unit'] = normalize_units_function(param['unit'])\n return data","def _convert_unit(self, unit):\n if unit in self.units:\n return self.units[unit]\n elif unit in unit_map:\n return unit_map[unit]\n else:\n raise SBMLError('Unit not recognized: ' + str(unit))","def _get_units(self):\n #assert self.ser.isOpen()\n\n self.serial_connection.write('UNI' + self.CR + self.LF)\n acknowledgement = self.serial_connection.readline()\n self._check_acknowledgement(acknowledgement)\n\n self.serial_connection.write(self.ENQ)\n unit = self.MEASUREMENT_UNITS[self.serial_connection.readline().rstrip(self.LF).rstrip(self.CR)]\n\n self.serial_connection.write(self.CR + self.LF)\n\n return unit","def to_axis_units(self, label, vals):\n if label in ['Hmolar', 'Smolar', 'Umolar', 'Dmolar', 'P']:\n return vals / 1000\n elif label in ['T']:\n return vals\n else:\n raise ValueError(label)","def fits_to_units(unit_str):\n unit_lookup = {\n 'meters': 'm',\n 'meter': 'm',\n 'degrees': 'deg',\n 'degree': 'deg',\n 'hz': 'Hz',\n 'hertz': 'Hz',\n 'second': 's',\n 'sec': 's',\n 'secs': 's',\n 'days': 'd',\n 'day': 'd',\n 'steradians': 'sr',\n 'steradian': 'sr',\n 'radians': 'rad',\n 'radian': 'rad',\n 'jy': 'Jy',\n 'au': 'AU',\n }\n\n try:\n new_units = \"\"\n\n if unit_str is None:\n unit_str = ''\n unit_str = unit_str.lower()\n unit_list = unit_str.split(\"/\")\n\n for uu in unit_list:\n if uu.endswith(\"s\") and len(uu) > 1:\n uu = uu[:-1]\n corrected_unit = unit_lookup.get(uu, uu)\n new_units += corrected_unit\n new_units += \" / \"\n new_units = new_units[:-3]\n unit = Unit(new_units)\n return unit\n\n except ValueError:\n warnings.warn(\"Unknown unit: %s\" % new_units, UnitWarning)\n return UnrecognizedUnit(unit_str)","def SBMLUnitsConverter_init():\n return _libsbml.SBMLUnitsConverter_init()","def get_units(self,):\n self.UNITS = {'pressure':'Pa',}\n return","def _d_converter(self):\n units = {'um':1e-6, 'mm':1e-3, 'inch':2.54e-2, 'in':2.54e-2,\\\n 'micron':1e-6, 'mil':2.54e-5, 'm':1.0}\n for i in self.stack:\n i.thickness = i.thickness*units[i.units]\n return","def convertUnit(*args, fromUnit: AnyStr=\"\", toUnit: AnyStr=\"\", **kwargs)->float:\n pass","def convert(self, value, units, newunits):\n return value * self._units[units] / self._units[newunits]","def convertToSpectroGram(self):","def test_unit_conversion(self):\n self.cube_uv_down.convert_units(\"kW m-2\")\n scale_factor = 1.0\n expected = np.full_like(\n self.cube_uv_down.data, dtype=np.float32, fill_value=0.1\n )\n result = calculate_uv_index(self.cube_uv_down, scale_factor)\n self.assertArrayEqual(result.data, expected)","def to_units(number):\n unit = 0\n while number >= 1024.:\n unit += 1\n number = number / 1024.\n if unit == len(UNITS) - 1:\n break\n if unit:\n return '%.2f%s' % (number, UNITS[unit])\n return '%d' % number","def convert_units(celsius_value, units):\n if units == 0:\n return celsius_value\n if units == 1:\n return celsius_value * 1.8 + 32\n return celsius_value + 273.15","def convert(value, units: UnitLike, registry: unyt.UnitRegistry = None):\n return process_unit_input(value, units, convert=True, registry=registry).v","def _get_units(self, q) -> unyt.Unit:\n try:\n units = q.units\n except AttributeError:\n units = unyt.dimensionless\n return unyt.Unit(units, registry=self.registry)","def units(self):\n pass","def convert_units(self, time_units=None, len_units=None):\n in_time = self.time_units\n # Check new time units\n if time_units is None:\n time_units = in_time\n flag = _units.validate_units(time_units)\n if flag == -1:\n raise ValueError('Bad time units input {}'.format(time_units))\n # Check new length units\n in_len = self.len_units\n if len_units is None:\n len_units = in_len\n flag = _units.validate_units(len_units)\n if flag == -1:\n raise ValueError('Bad length units input {}'.format(len_units))\n # Convert parameters units\n for key, value in self.parameters.items():\n if type(value) in [int, float]:\n self.parameters[key] = _units.units_conversion(value, in_len, len_units)\n # Convert drawdown data\n self.drawdown.convert_units(time_units, len_units)\n # Convert associate data units\n for i in range(self.data_count()):\n if self.data[i].dtype == 1: # drawdown units\n data_units = len_units\n elif self.data[i].dtype == 2: # first derivative units\n data_units = len_units + \"/\" + time_units\n elif self.data[i].dtype == 3: # second derivative units\n data_units = len_units + \"/\" + time_units + \"2\"\n self.data[i].convert_units(time_units, data_units)\n self.len_units = len_units\n self.time_units = time_units\n # End Function","def convert_F_units(F, lbda, in_unit='cgs', out_unit='si'):\n\n if in_unit == 'cgs':\n new_F = (F*1e23*np.power(lbda,2))/(c.c.value*1e6) # convert to jy\n elif in_unit == 'cgsA':\n new_F = (F*1e27*np.power(lbda,2))/(c.c.value*1e6) # convert to jy\n elif in_unit == 'si':\n new_F = (F*1e26*np.power(lbda,2))/(c.c.value*1e6) # convert to jy\n elif in_unit == \"jy\":\n new_F=F\n else:\n msg = \"in_unit not recognized, try either 'cgs', 'si' or 'jy'.\"\n raise TypeError(msg) \n if out_unit == 'jy':\n return new_F\n elif out_unit == 'cgs':\n return new_F*1e-23*c.c.value*1e6/np.power(lbda,2)\n elif out_unit == 'si':\n return new_F*1e-26*c.c.value*1e6/np.power(lbda,2)\n else:\n msg = \"out_unit not recognized, try either 'cgs', 'si' or 'jy'.\"\n raise TypeError(msg)","def convert_wave_to_units(self, wave):\n return [self.convert_point_to_units(i) for i in wave]","def units_to_pixels(self,units_):\n if type(units_) == str and units_.lower() in [\"fwhm\",\"psf\"]:\n units_ = self.fwhm\n\n return super(Image, self).units_to_pixels(units_, target=self.target)","def convert_unit(size_in_bytes, unit):\n if unit == 'KB':\n return size_in_bytes/1024\n elif unit == 'MB':\n return size_in_bytes/(1024*1024)\n elif unit == 'GB':\n return size_in_bytes/(1024*1024*1024)\n else:\n return size_in_bytes","def units(self, x):\n u = ''.join([chr(d) for d in self[x]['units'][:]])\n if (u in ['n/a']) and (x in ['latitude', 'longitude']):\n u = 'radian' # assume radians\n return u","def native_unit_of_measurement(self) -> str:\n return f\"{CURRENCY_CENT}/{UnitOfVolume.LITERS}\"","def _fix_units(cube, definition):\n\n if cube.var_name != 'pr':\n cube.convert_units(definition.units)","def convert(obj, unit, axis):\r\n return obj","def infer_original_units(self, dimensions):\n dimensions = units.Unit(dimensions)\n d = dimensions.dimensional_project(\n self._file_units_system + [\"a\", \"h\"])\n new_unit = reduce(lambda x, y: x * y, [\n a ** b for a, b in zip(self._file_units_system, d)])\n return new_unit","def unicode_of_unit(quant):\n return quant.dimensionality.unicode","def unit_of_measurement(self):\n if self.values.primary.units == \"C\":\n return TEMP_CELSIUS\n if self.values.primary.units == \"F\":\n return TEMP_FAHRENHEIT\n\n return self.values.primary.units","def unit_of_measurement(self):\n set_req = self.gateway.const.SetReq\n unit_map = {\n set_req.V_TEMP: (TEMP_CELSIUS\n if self.gateway.metric else TEMP_FAHRENHEIT),\n set_req.V_HUM: '%',\n set_req.V_DIMMER: '%',\n set_req.V_LIGHT_LEVEL: '%',\n set_req.V_WEIGHT: 'kg',\n set_req.V_DISTANCE: 'm',\n set_req.V_IMPEDANCE: 'ohm',\n set_req.V_WATT: 'W',\n set_req.V_KWH: 'kWh',\n set_req.V_FLOW: 'm',\n set_req.V_VOLUME: 'm3',\n set_req.V_VOLTAGE: 'V',\n set_req.V_CURRENT: 'A',\n }\n if float(self.gateway.protocol_version) >= 1.5:\n if set_req.V_UNIT_PREFIX in self._values:\n return self._values[\n set_req.V_UNIT_PREFIX]\n unit_map.update({set_req.V_PERCENTAGE: '%'})\n if float(self.gateway.protocol_version) >= 2.0:\n unit_map.update({\n set_req.V_ORP: 'mV',\n set_req.V_EC: 'μS/cm',\n set_req.V_VAR: 'var',\n set_req.V_VA: 'VA',\n })\n return unit_map.get(self.value_type)","def _get_units(self, name):\n meta = self._abs2meta\n\n if name in meta:\n return meta[name]['units']\n\n proms = self._prom2abs\n\n if name in proms['output']:\n abs_name = proms['output'][name][0]\n return meta[abs_name]['units']\n\n elif name in proms['input']:\n if len(proms['input'][name]) > 1:\n # The promoted name maps to multiple absolute names, require absolute name.\n msg = \"Can't get units for the promoted name '%s' because it refers to \" + \\\n \"multiple inputs: %s. Access the units using an absolute path name.\"\n raise RuntimeError(msg % (name, str(proms['input'][name])))\n\n abs_name = proms['input'][name][0]\n return meta[abs_name]['units']\n\n raise KeyError('Variable name \"{}\" not found.'.format(name))","def get_unit(scale):\n scale2unit = { 1e-9: 'nm',\n 1e-6: u'\\N{MICRO SIGN}m', #or hex id (lookup): u'\\u00B5'\n 1e-3: 'mm',\n 0.01: 'cm',\n 0.1:'dm',\n 1:'m',\n 1000:'km',\n # time\n 8.6400e4:'day',\n 3.1536e7:'yr',\n 3.1536e10:'ka',\n 3.1536e13:'Ma',\n #Pressure\n 1e9: 'GPa',\n 1e6: 'MPa',\n }\n return scale2unit[scale]","def _getunits(x):\n if pb.units.has_units(x):\n \n units = x.units\n \n else:\n \n units = None\n \n return units","def init():\n return _libsbml.SBMLUnitsConverter_init()","def convert(value, unit, axis):\n converted_value = value\n if isinstance(unit, str) or isinstance(unit, Unit):\n unit = (unit,)\n if isinstance(value, (unyt_array, unyt_quantity)):\n converted_value = value.to(*unit)\n else:\n value_type = type(value)\n converted_value = []\n for obj in value:\n converted_value.append(obj.to(*unit))\n converted_value = value_type(converted_value)\n return converted_value","def unit_array(self):\n return self._data_array.values * units(self._units)","def convert_frequency_2_internal_u(self,val):\n return val*conversion_facs_frequency[self.current_units[\"frequency\"]]","def unitsDetector(self, num):\n try:\n num = int(num)\n except:\n sys.exit('Invalid input! Method only takes ints or floats.')\n \n digits = 0\n while num > 1:\n num /= 10\n digits += 1\n \n digits -= 1\n ind = digits // 3\n units = {3: 'B', 2: 'M', 1: 'K', 0: ''}[ind]\n \n return 10 ** (ind * 3), units","def _unyt_array_convert_to_units_no_em(self, units, equivalence=None, **kwargs):\n units = _sanitize_units_convert(units, self.units.registry)\n if equivalence is None:\n new_units = units\n (conv_factor,\n offset) = self.units.get_conversion_factor(new_units, self.dtype)\n\n self.units = new_units\n values = self.d\n # if our dtype is an integer do the following somewhat awkward\n # dance to change the dtype in-place. We can't use astype\n # directly because that will create a copy and not update self\n if self.dtype.kind in (\"u\", \"i\"):\n # create a copy of the original data in floating point\n # form, it's possible this may lose precision for very\n # large integers\n dsize = values.dtype.itemsize\n new_dtype = \"f\" + str(dsize)\n large = LARGE_INPUT.get(dsize, 0)\n if large and np.any(np.abs(values) > large):\n warnings.warn(\n \"Overflow encountered while converting to units '%s'\" %\n new_units,\n RuntimeWarning,\n stacklevel=2,\n )\n float_values = values.astype(new_dtype)\n # change the dtypes in-place, this does not change the\n # underlying memory buffer\n values.dtype = new_dtype\n self.dtype = new_dtype\n # actually fill in the new float values now that our\n # dtype is correct\n np.copyto(values, float_values)\n values *= conv_factor\n\n if offset:\n np.subtract(values, offset, values)\n else:\n self.convert_to_equivalent(units, equivalence, **kwargs)","def convert(self, value, unit, axis):\n scaled = getattr(value, self.scale)\n if self.format in YMDHMS_FORMATS:\n return scaled.mjd\n elif self.format == \"byear_str\":\n return scaled.byear\n elif self.format == \"jyear_str\":\n return scaled.jyear\n else:\n return getattr(scaled, self.format)","def remove_units(namespace):\n res = copy(namespace)\n for label, value in res.__dict__.items():\n if isinstance(value, pd.Series):\n value = remove_units_series(value)\n res.__dict__[label] = magnitude(value)\n return res","def unit_of_measurement(self) -> str:\n raw_units = self.raw_units\n\n if raw_units in [TEMP_CELSIUS, TEMP_FAHRENHEIT]:\n return self.hass.config.units.temperature_unit\n return raw_units","def get_converted_si_unit():\n units = request.args.get('units')\n response = ConvertUnit(units).convert()\n return jsonify(response)","def unitpicker(a, llim=0.1):\n udict = {0: 'mol/mol',\n 1: 'mmol/mol',\n 2: '$\\mu$mol/mol',\n 3: 'nmol/mol',\n 4: 'pmol/mol',\n 5: 'fmol/mol'}\n a = abs(a)\n n = 0\n if a < llim:\n while a < llim:\n a *= 1000\n n += 1\n return float(1000**n), udict[n]","def _get_unit_factor(self, unit: str) -> np.ndarray:\n\n unit_factors = {\n 'vx': np.array((1, 1, 1)),\n 'nm': np.array(self.parameters.scale),\n 'um': np.array(self.parameters.scale)/1000\n }\n assert unit in unit_factors.keys(), 'Invalid unit'\n unit_factor = unit_factors[unit]\n\n return unit_factor","def to(self, unit, equivalencies=[]):\n\n return super(BaseOneDSpectrum, self).to(unit, equivalencies, freq=None)","def convert_units(src_unit: Union[str, float], tgt_unit: Union[str, float]):\n return _parse_unit(src_unit) / _parse_unit(tgt_unit)","def _to(\n value: Union[\"Value\", \"ValueArray\"], units: Union[Unit, str], inplace: bool\n) -> Any:\n if value.units == units:\n return value\n\n if value.units is None:\n raise RuntimeError(\"Cannot convert with units=None\")\n\n try:\n units = next(\n imp_unit\n for imp_unit in value.implemented_units\n if units.lower() in imp_unit.aliases\n )\n\n except StopIteration:\n raise TypeError(\n f\"No viable unit conversion from {value.units} -> {units}\"\n )\n\n if not (isinstance(value, Value) or isinstance(value, ValueArray)):\n raise ValueError(\n f\"Cannot convert {value} to new units. Must be one of\"\n f\" Value of ValueArray\"\n )\n\n if isinstance(value, Value) and inplace:\n raise ValueError(\n \"Cannot modify a value inplace as floats are immutable\"\n )\n\n # Convert to the base unit, then to the new units\n c = float(units.conversion / value.units.conversion)\n\n new_value = value if inplace else value.copy()\n new_value *= c\n new_value.units = units\n\n return None if inplace else new_value","def convert_energy_2_internal_u(self,val):\n units = self.current_units[\"energy\"]\n cfact = conversion_facs_energy[self.current_units[\"energy\"]]\n \n # special handling for nano meters\n if units == \"nm\":\n # zero is interpretted as zero energy\n try:\n ret = numpy.zeros(val.shape, dtype=val.dtype)\n ret[val!=0.0] = 1.0/val[val!=0]\n return ret/cfact\n except: \n return (1.0/val)/cfact\n #if val == 0.0:\n # return 0.0\n #return (1.0/val)/cfact\n else:\n return val*cfact","def convert_path_units(self, path_to_conv):\n\n converted_path = copy.deepcopy(path_to_conv) # TODO: figure out if this is the right way to do this- I have not yet understood how data should be handled here\n\n for i, coord in enumerate(converted_path):\n converted_path[i][0] = coord[0] / self.units_in_meter\n converted_path[i][1] = coord[1] / self.units_in_meter\n converted_path[i][2] = coord[2] / self.units_in_meter\n\n return converted_path","def get_units(self):\n return str(self._modeler.GetModelUnits())","def units(inventory):\n return inventory.reduce(convert.get_units)","def unit_of_measurement(self):\n return self.values.primary.units","def units(self):\n return self._units","def units(self):\n return self._units","def unit(x,convert_to=\"px\",from_unit=\"px\"):\n assert convert_to in UNITS, \"Cannot convert to unknown unit: %s\" % convert_to\n assert from_unit in UNITS, \"Cannot from unknown unit: %s\" % from_unit\n return float(x)*UNITS[convert_to]/UNITS[from_unit]","def convert_energy_2_current_u(self,val):\n units = self.current_units[\"energy\"]\n cfact = conversion_facs_energy[units]\n \n # special handling for nanometers\n if units == \"nm\":\n # zero is interpretted as zero energy\n try:\n ret = numpy.zeros(val.shape, dtype=val.dtype)\n ret[val!=0.0] = 1.0/val[val!=0]\n return ret/cfact\n except: \n return (1.0/val)/cfact\n else:\n return val/cfact","def _parse_units(self, model, comp, node):\n node = dom_child(node, 'unitDefinition')\n while node:\n name = node.getAttribute('id')\n self.log('Parsing unit definition for \"' + name + '\".')\n unit = myokit.units.dimensionless\n node2 = dom_child(node, 'listOfUnits')\n node2 = dom_child(node2, 'unit')\n while node2:\n kind = str(node2.getAttribute('kind')).strip()\n u2 = self._convert_unit(kind)\n if node2.hasAttribute('multiplier'):\n m = float(node2.getAttribute('multiplier'))\n else:\n m = 1.0\n if node2.hasAttribute('scale'):\n m *= 10 ** float(node2.getAttribute('scale'))\n u2 *= m\n if node2.hasAttribute('exponent'):\n u2 **= float(node2.getAttribute('exponent'))\n unit *= u2\n node2 = dom_next(node2, 'unit')\n self.units[name] = unit\n node = dom_next(node, 'unitDefinition')","def extendedConvert(self):\r\n devId = str(self.deviceId)\r\n if(devId == '28' or devId == '29'):\r\n answers = []\r\n #just add the counter value\r\n answers.append(self.fields[1])\r\n #find the engineering units converter\r\n enum = self.fields[0] & 0x3F\r\n #look up the scale and offset for that eeu\r\n eeu = self._eeumaps[str(enum)]\r\n self.eeu1 = eeu\r\n print('eeu:' + str(eeu))\r\n #convert from twos complement and adjust by scale/offset\r\n val = (self.convertSigned16(self.fields[2]) * eeu[1]) + eeu[0]\r\n answers.append(val)\r\n #reset fields to hold the new answers\r\n self.fields = answers\r\n self.units = [self.UNITS_COUNT, eeu[2]]\r\n elif(devId == '53' or devId == '54'):\r\n #strip off the first part of the answer which is the last part of the\r\n #serial number\r\n answers = [self.fields[1]]\r\n self.fields = answers\r\n elif(devId == '75' or devId == '76'):\r\n answers = []\r\n #find out the number of I/O points\r\n pointCount = self.fields[0] & 3\r\n #find out engineering units for 1st I/O\r\n enum = self.fields[1] & 0x3F\r\n eeu = self._eeumaps[str(enum)]\r\n self.eeu1 = eeu\r\n #new value = old value * scale + offset\r\n val = (self.convertSigned16(self.fields[3]) * eeu[1]) + eeu[0]\r\n answers.append(val)\r\n self.units = [eeu[2]]\r\n #see if there's two\r\n if pointCount == 2:\r\n #find out engineering units for 2nd I/O\r\n #and off first two bits\r\n enum = self.fields[0] >> 2\r\n eeu = self._eeumaps[str(enum)]\r\n self.eeu2 = eeu\r\n val = (self.convertSigned16(self.fields[2]) * eeu[1]) + eeu[0]\r\n answers.append(val)\r\n self.units.append(eeu[2])\r\n else:\r\n self.eeu2 = []\r\n #reset fields to hold the new answers\r\n self.fields = answers\r\n\r\n return","def unit_of_measurement(self):\n\n if self._sensor_class == DEVICE_CLASS_TEMPERATURE:\n return TEMP_CELSIUS\n\n elif self._sensor_class == DEVICE_CLASS_HUMIDITY:\n return '%'","def unit_of_measurement(self):\n return self._units","def unit_of_measurement(self):\n return self._metadata[1]","def raw_units(self) -> str:\n if self._node.uom == 'F':\n return TEMP_FAHRENHEIT\n if self._node.uom == 'C':\n return TEMP_CELSIUS\n return self._node.uom","def parse_unit(self, unitelem) -> Unit:\n u = Unit()\n\n u.unitid = unitelem.attrib['id'].strip()\n div = unitelem.find('{*}divide')\n if div is not None:\n nom = div.find('{*}unitNumerator').find('{*}measure')\n denom = div.find('{*}unitDenominator').find('{*}measure')\n u.nom = re.sub('.*:', '', nom.text).lower()\n u.denom = re.sub('.*:', '', denom.text).lower()\n else:\n m = unitelem.find('{*}measure')\n u.nom = re.sub('.*:', '', m.text).lower()\n\n return u","def unit_of_measurement(self):\n return self.sensor_type[\"unit\"]","def to_inch(self):\r\n if self.units != 'inch':\r\n self.units = 'inch'\r\n for statement in self.statements:\r\n statement.to_inch()\r\n for tool in iter(self.tools.values()):\r\n tool.to_inch()\r\n for primitive in self.primitives:\r\n primitive.to_inch()\r\n for hit in self.hits:\r\n hit.to_inch()","def test_change_units(self):\n s = State(\"water\", T=Q_(100, \"degC\"), p=Q_(1.0, \"atm\"), units=\"EE\")\n assert s.units == \"EE\"\n s.units = \"SI\"\n assert s.units == \"SI\"\n assert s.cv.units == \"kilojoule / kelvin / kilogram\"\n assert s.cp.units == \"kilojoule / kelvin / kilogram\"\n assert s.s.units == \"kilojoule / kelvin / kilogram\"\n assert s.h.units == \"kilojoule / kilogram\"\n assert s.T.units == \"degree_Celsius\"\n assert s.u.units == \"kilojoule / kilogram\"\n assert s.v.units == \"meter ** 3 / kilogram\"\n assert s.p.units == \"bar\"","def convert_volume(self, event):\n try:\n #Compare other unit to one unit(cubic decimeters)\n current_value, current_unit = float(\"0\" + str(self.v.get())), self.dropdown.get()\n unit_comp = {\"acre foot\": 1233481.837548, \"barrels\": 158.987295, \"bushels(UK)\": 36.36872, \"bushels(US)\": 35.23907, \"centiliters\": 0.01, \"cubic centimeters\": 0.001, \"cubic decameters\": 1000000.0, \"cubic decimeters\": 1.0, \"cubic feet\": 28.316847, \"cubic inches\": 0.016387, \"cubic kilometers\": 1000000000000.0, \"cubic meters\": 1000.0, \"cubic mile\": 4168181825000.0, \"cubic millimeters\": 1e-06, \"cubic yards\": 764.554858, \"cups\": 0.236588, \"deciliters\": 0.1, \"dram\": 0.003697, \"dram(imperial)\": 0.003552, \"fluid ounces(US)\": 0.029574, \"fluid ounces(imperial)\": 0.028413, \"gallons(US,dry)\": 4.404884, \"gallons(US,liquid)\": 3.785412, \"gallons(imperial)\": 4.54609, \"gill(US)\": 0.118294, \"gill(imperial)\": 0.142065, \"liters\": 1.0, \"liters(1901-1964)\": 1.000028, \"microliters\": 1e-06, \"milliliters\": 0.001, \"nanoliters\": 1e-09, \"picoliters\": 1e-12, \"pints(US,dry)\": 0.55061, \"pints(US,liquid)\": 0.473176, \"pints(imperial)\": 0.568261, \"quarts(UK,dry)\": 1.101221, \"quarts(US,liquid)\": 0.946353, \"quarts(imperial)\": 1.136523, \"table spoons\": 0.014787, \"tea spoons\": 0.004929}\n value_comp, printer = current_value * unit_comp[current_unit], \"\"\n unit_list = sorted(unit_comp.keys())\n unit_list.remove(current_unit)\n for unit in unit_list:\n printer += \"To %s \" % unit + \" \" * (max([len(i) for i in unit_list]) - len(unit)) + str(value_comp / unit_comp[unit]) + [\"\", \"\\n\"][unit_list[-1] != unit]\n except ValueError: #In case user enter the other type of value, not Int or Float\n printer = \"Value is invalid.\"\n self.print_text(printer)","def units(self, key):\n \n # Strip any operators\n _, key = get_operator(key)\n \n # Fill out aliases \n if key in component_from_alias:\n key = component_from_alias[key]\n elif key == 'E':\n key = 'electricField'\n elif key == 'B':\n key = 'magneticField' \n \n return pg_units(key)","def unit_array(self, values):\n self._data_array.values = values\n self._units = self._data_array.attrs['units'] = str(values.units)","def _get_units_object(self, units):\n if isinstance(units, cellml_units):\n # We're done\n pass\n else:\n units = amara_parse_cellml(unicode(units))\n assert isinstance(units, cellml_units)\n return units","def get_units(self, obj: Dimension) -> [Unit]:\n try:\n return obj.units()\n except KeyError as e:\n logging.error(str(e))\n return []","def raw_unit_of_measurement(self) -> str:\n if len(self._node.uom) == 1:\n if self._node.uom[0] in UOM_FRIENDLY_NAME:\n friendly_name = UOM_FRIENDLY_NAME.get(self._node.uom[0])\n if friendly_name == TEMP_CELSIUS or \\\n friendly_name == TEMP_FAHRENHEIT:\n friendly_name = self.hass.config.units.temperature_unit\n return friendly_name\n else:\n return self._node.uom[0]\n else:\n return None","def convert_same_units(self):\n # Convert pumping rate data\n pump_units = \"%s3/%s\" % (self.len_units, self.time_units)\n flag = _units.validate_units(pump_units)\n if flag == 2:\n self.pumprate.convert_units(self.time_units, pump_units)\n self.pump_units = pump_units","def __convert_to_devunit(self, value, in_devunit=False):\r\n if not in_devunit:\r\n value *= self.DEVUNIT_RATIO\r\n elif not isinstance(value, int):\r\n self.print_msg((\"Warning: non-integer value ({}) is given \"\r\n + \"in device unit.\").format(value))\r\n return int(value)","def convert_unit(self, time_unit):\r\n\r\n self.time_unit = time_unit\r\n self._conversion_factor = time_unit_conversion[time_unit]","def SBMLInferUnitsConverter_init():\n return _libsbml.SBMLInferUnitsConverter_init()","def _get_wavelength_attrs_with_units(self, attrname, units='AA'):\n attr = self._lick[attrname]\n if self.wavelength_unit is not None:\n if units is None:\n return attr * Unit(self.wavelength_unit)\n else:\n return (attr * Unit(self.wavelength_unit)).to(units)\n else:\n return attr","def assign_unit(self):\n self.units = {}\n for unit in RADIAL_UNITS:\n if unit.REPR == \"2th_deg\":\n self.units[unit] = self.tth_deg\n elif unit.REPR == \"2th_rad\":\n self.units[unit] = self.tth_rad\n elif unit.REPR == \"q_nm^-1\":\n self.units[unit] = self.q_nm\n elif unit.REPR == \"q_A^-1\":\n self.units[unit] = self.q_A\n elif unit.REPR == \"r_mm\":\n self.units[unit] = self.r_mm\n else:\n logger.warning(\"Unit unknown to GUI %s\" % unit)","def to_base_unit(val: float, unit: str = \"\") -> float:\n unit_scalar = UNITS.get(unit, None)\n if not unit_scalar:\n raise UnknownUnitError(f\"Unit '{unit}' is not supported\")\n\n return val * unit_scalar"],"string":"[\n \"def convert_units(self):\\n for prod in (\\\"ier\\\", \\\"ier_inc_rain\\\"):\\n self.data[prod].data[:] /= 1e6\",\n \"def backconvert_units(array, out_units):\\n if out_units == \\\"None\\\" or out_units is None:\\n return array\\n else:\\n raise Exception(\\\"Unsupported unit for bispectrum descriptors.\\\")\",\n \"def convert_units(self, units):\\n self.unit_array = self.unit_array.to(units)\",\n \"def convert_units(unt, origunits):\\n if unt[0:3] == origunits[0:3] | unt[0:3] == 'ori':\\n units = origunits\\n convf = 1\\n else:\\n if 'fee' == unt[(((0:3 -1) -1) -1)]:\\n if origunits[0:3] == 'met':\\n units = 'feet'\\n convf = 3.2808399\\n else:\\n units = origunits\\n convf = 1\\n else:\\n if 'met' == unt[(((0:3 -1) -1) -1)]:\\n if origunits[0:3] == 'fee':\\n units = 'meters'\\n convf = 0.3048\\n else:\\n units = origunits\\n convf = 1\\n else:\\n if 'm/s' == unt[(((0:3 -1) -1) -1)]:\\n if origunits[0:3] == 'kno':\\n units = 'meters/sec'\\n convf = 0.51444444\\n else:\\n units = origunits\\n convf = 1\\n else:\\n if 'kno' == unt[(((0:3 -1) -1) -1)]:\\n if origunits[0:3] == 'm/s':\\n units = 'knots'\\n convf = 1.9438445\\n else:\\n units = origunits\\n convf = 1\\n else:\\n error('Unknown units')\\n #\\n return units, convf\",\n \"def convert(self):\\n return _libsbml.SBMLUnitsConverter_convert(self)\",\n \"def convert(self):\\n return _libsbml.SBMLInferUnitsConverter_convert(self)\",\n \"def convert_units(data, hdr, conv_to = \\\"surf_br\\\"):\\n \\n data_unit = hdr[\\\"SIGUNIT\\\"]\\n \\n if \\\"Jy/pix\\\" in data_unit:\\n # pixel size in rad\\n px_x = abs(hdr[\\\"CDELT1\\\"])*2*np.pi/360\\n px_y = abs(hdr[\\\"CDELT2\\\"])*2*np.pi/360\\n \\n #pixel size in arcsec\\n \\n px_x = abs(hdr[\\\"CDELT1\\\"])*3600\\n px_y = abs(hdr[\\\"CDELT2\\\"])*3600\\n conversion_factor = 1000/(px_x*px_y)\\n \\n unit_label = \\\"mJy/arcsec^2\\\"\\n \\n #in case we want to convert to units flux, we need to multiply by the size (in steradians) of a pixel.\\n if conv_to == \\\"flux\\\":\\n conversion_factor*=abs(hdr[\\\"CDELT1\\\"])*abs(hdr[\\\"CDELT2\\\"])*(2*np.pi/360)**2\\n unit_label = \\\"mJy\\\"\\n \\n data *= conversion_factor\\n hdr[\\\"SIGUNIT\\\"] = unit_label\\n else:\\n print(\\\"\\\\t[WARNING]\\\\t \\\"+data_unit+\\\" conversion not yet implemented. No conversion performed.\\\")\\n \\n return data, hdr\",\n \"def convertUnits(self, varname, arr):\\n if varname == \\\"SPDQ\\\" or varname == \\\"PHQ\\\":\\n return arr*2.5e6/1000.\\n return arr\",\n \"def convert_to_unit(self, data, unit):\\n\\n res = OrderedDict()\\n\\n # Loop over data and overwrite\\n for ch in data:\\n _idx = self.channels.index(ch)\\n # Get data, scale and type of channel\\n val, scale, _type = data[ch], self.daq_setup['devices']['adc']['ro_scales'][_idx], self.daq_setup['devices']['adc']['types'][_idx]\\n # Adjust scale in case we're looking at SEM's sum signal; in this case current is multiplied by factor of 4\\n scale *= 1 if _type != 'sem_sum' else 4\\n\\n res[ch] = val / 5.0 * scale * 1e-9 if unit == 'A' else val * 5.0 / 1e-9 / scale\\n\\n return res\",\n \"def resolve_units(obj, _):\\n return obj.units.decode()\",\n \"def units_to_fits(unit):\\n if unit is None:\\n unit = Unit('')\\n return unit.to_string(\\\"fits\\\").upper()\",\n \"def convert_units(data, units):\\n # Build the dictionary of units conversions\\n convert = {'m' : [1.0, 0., 'm'], \\n 'meter' : [1.0, 0., 'm'], \\n 'deg C' : [1.0, 273.15, 'K'], \\n 'Celsius' : [1.0, 273.15, 'K'], \\n 'K' : [1.0, 0., 'K'],\\n 'db' : [1.e4, 101325., 'Pa'], \\n 'Pa' : [1.0, 0., 'Pa'],\\n 'mg/m^3': [1.e-6, 0., 'kg/m^3'], \\n 'S/m': [1.0, 0., 'S/m'],\\n 'mS/m' : [1.e-3, 0., 'S/m'],\\n 'psu': [1.0, 0., 'psu'], \\n 'salinity': [1.0, 0., 'psu'], \\n 'kg/m^3': [1.0, 0., 'kg/m^3'], \\n 'kilogram meter-3': [1.0, 0., 'kg/m^3'], \\n 'm/s': [1.0, 0., 'm/s'], \\n 'mg/l': [1.e-3, 0., 'kg/m^3'],\\n 'meter second-1' : [1.0, 0., 'm/s'],\\n 'm.s-1' : [1.0, 0., 'm/s'],\\n 'pH units' : [1.0, 0., 'pH units'],\\n 'MPa' : [1.e6, 0., 'Pa'],\\n '--' : [1.0, 0., '--'],\\n 'mD' : [9.869233e-16, 0., 'm^2'],\\n 'um' : [1.e-6, 0., 'm'],\\n 'm/s 1e-9' : [1.e-9, 0., 'm/s'],\\n 'm/s 1e-7' : [1.e-7, 0., 'm/s'],\\n 'wt.%' : [10., 0., 'psu'],\\n '10^-15 m^2' : [1.e-15, 0., 'm^2'],\\n 'm^2' : [1., 0., 'm^2'],\\n 'kg/m^2/year' : [3.168808781402895e-08, 0., 'kg/m^2/s'] \\n } \\n \\n # Make sure the data are a numpy array and the units are a list\\n if isinstance(data, float) or isinstance(data, int):\\n data = np.array([data])\\n if isinstance(data, list):\\n data = np.array(data)\\n if isinstance(units, str) or isinstance(units, unicode):\\n units = [units]\\n if units == None:\\n units = ['']\\n \\n # Make sure you can slice through the columns: must be two-dimensional\\n sh = data.shape\\n data = np.atleast_2d(data)\\n \\n # Allow conversion of a row of data if all of the same unit\\n if len(units) == 1 and data.shape[1] > 1:\\n data = data.transpose()\\n \\n # Create an emtpy array to hold the output\\n out_data = np.zeros(data.shape)\\n out_units = []\\n \\n # Convert the units\\n for i in range(len(units)):\\n try:\\n out_data[:,i] = data[:,i] * convert[units[i]][0] + \\\\\\n convert[units[i]][1]\\n out_units += [convert[units[i]][2]]\\n except KeyError:\\n print('Do not know how to convert %s to mks units' % units[i])\\n print('Continuing without converting these units...')\\n out_data[:,i] = data[:,i]\\n out_units += units[i]\\n \\n # Return the converted data in the original shape\\n out_data = np.reshape(out_data, sh, 'C')\\n return (out_data, out_units)\",\n \"def get_units(self):\\r\\n msg = struct.pack('>2B', 56, 14)\\r\\n response = self.query(msg)\\r\\n\\r\\n if response[1] == 2:\\r\\n units = 'A'\\r\\n to_nm_multiplier = 1 / 10\\r\\n elif response[1] == 1:\\r\\n units = 'nm'\\r\\n to_nm_multiplier = 1\\r\\n elif response[1] == 0:\\r\\n units = 'um'\\r\\n to_nm_multiplier = 1000\\r\\n else:\\r\\n raise ValueError('Units not recognised.')\\r\\n\\r\\n # Save results locally too for quick re-use\\r\\n self._current_units = units\\r\\n self._current_to_nm_multiplier = to_nm_multiplier\\r\\n\\r\\n return units, to_nm_multiplier\",\n \"def __convert_to_mm(self, value, in_devunit=True):\\r\\n if in_devunit:\\r\\n value /= self.DEVUNIT_RATIO\\r\\n return value\",\n \"def _convert_value(self, value, unit, axis):\\n if hasattr(value, 'units'):\\n return value.to(unit).magnitude\\n else:\\n return self._reg.Quantity(value, axis.get_units()).to(unit).magnitude\",\n \"def test_convert_compatible_units(self):\\n result = convert_units(self.arr, 'degC')\\n expected_data = np.array([[-273.15, -272.15], [-271.15, -270.15]])\\n expected_units = cf_units.Unit('degC')\\n self.assertEquals(result.units, expected_units)\\n self.assertArrayEqual(result.data, expected_data)\",\n \"def useUnits():\",\n \"def to_unit(self, unit):\\n unit = _find_unit(unit)\\n self.value = _convert_value(self.value, self.unit, unit)\\n self.unit = unit\",\n \"def extract_specs(self):\\n vDeflection_unit = \\\"lcd-info.{}.conversion-set.conversion.force.scaling.unit.unit\\\".format(\\n self.channel_numbers[\\\"vDeflection\\\"])\\n self.units[\\\"vDeflection\\\"] = self.general[vDeflection_unit]\\n\\n height_unit = \\\"lcd-info.{}.conversion-set.conversion.nominal.scaling.unit.unit\\\".format(\\n self.channel_numbers[\\\"height\\\"])\\n self.units[\\\"height\\\"] = self.general[height_unit]\",\n \"def unit_converter(val, from_u, to_u):\\n\\tconverter = {'b':0, 'k':1, 'm':2, 'g':3, 't':4}\\n\\tif converter[from_u] < converter[to_u]:\\n\\t\\tval = float(val)\\n\\t\\tfor _ in range(converter[to_u] - converter[from_u]):\\n\\t\\t\\tval = val/1024\\n\\telse:\\n\\t\\tfor _ in range(converter[from_u] - converter[to_u]):\\n\\t\\t\\tval = val * 1024\\n\\t\\t\\t\\n\\treturn val\",\n \"def normalize_units(data):\\n for obj in data:\\n obj['unit'] = normalize_units_function(obj.get('unit', ''))\\n # for param in ds.get('parameters', {}).values():\\n # if 'unit' in param:\\n # param['unit'] = normalize_units_function(param['unit'])\\n return data\",\n \"def _convert_unit(self, unit):\\n if unit in self.units:\\n return self.units[unit]\\n elif unit in unit_map:\\n return unit_map[unit]\\n else:\\n raise SBMLError('Unit not recognized: ' + str(unit))\",\n \"def _get_units(self):\\n #assert self.ser.isOpen()\\n\\n self.serial_connection.write('UNI' + self.CR + self.LF)\\n acknowledgement = self.serial_connection.readline()\\n self._check_acknowledgement(acknowledgement)\\n\\n self.serial_connection.write(self.ENQ)\\n unit = self.MEASUREMENT_UNITS[self.serial_connection.readline().rstrip(self.LF).rstrip(self.CR)]\\n\\n self.serial_connection.write(self.CR + self.LF)\\n\\n return unit\",\n \"def to_axis_units(self, label, vals):\\n if label in ['Hmolar', 'Smolar', 'Umolar', 'Dmolar', 'P']:\\n return vals / 1000\\n elif label in ['T']:\\n return vals\\n else:\\n raise ValueError(label)\",\n \"def fits_to_units(unit_str):\\n unit_lookup = {\\n 'meters': 'm',\\n 'meter': 'm',\\n 'degrees': 'deg',\\n 'degree': 'deg',\\n 'hz': 'Hz',\\n 'hertz': 'Hz',\\n 'second': 's',\\n 'sec': 's',\\n 'secs': 's',\\n 'days': 'd',\\n 'day': 'd',\\n 'steradians': 'sr',\\n 'steradian': 'sr',\\n 'radians': 'rad',\\n 'radian': 'rad',\\n 'jy': 'Jy',\\n 'au': 'AU',\\n }\\n\\n try:\\n new_units = \\\"\\\"\\n\\n if unit_str is None:\\n unit_str = ''\\n unit_str = unit_str.lower()\\n unit_list = unit_str.split(\\\"/\\\")\\n\\n for uu in unit_list:\\n if uu.endswith(\\\"s\\\") and len(uu) > 1:\\n uu = uu[:-1]\\n corrected_unit = unit_lookup.get(uu, uu)\\n new_units += corrected_unit\\n new_units += \\\" / \\\"\\n new_units = new_units[:-3]\\n unit = Unit(new_units)\\n return unit\\n\\n except ValueError:\\n warnings.warn(\\\"Unknown unit: %s\\\" % new_units, UnitWarning)\\n return UnrecognizedUnit(unit_str)\",\n \"def SBMLUnitsConverter_init():\\n return _libsbml.SBMLUnitsConverter_init()\",\n \"def get_units(self,):\\n self.UNITS = {'pressure':'Pa',}\\n return\",\n \"def _d_converter(self):\\n units = {'um':1e-6, 'mm':1e-3, 'inch':2.54e-2, 'in':2.54e-2,\\\\\\n 'micron':1e-6, 'mil':2.54e-5, 'm':1.0}\\n for i in self.stack:\\n i.thickness = i.thickness*units[i.units]\\n return\",\n \"def convertUnit(*args, fromUnit: AnyStr=\\\"\\\", toUnit: AnyStr=\\\"\\\", **kwargs)->float:\\n pass\",\n \"def convert(self, value, units, newunits):\\n return value * self._units[units] / self._units[newunits]\",\n \"def convertToSpectroGram(self):\",\n \"def test_unit_conversion(self):\\n self.cube_uv_down.convert_units(\\\"kW m-2\\\")\\n scale_factor = 1.0\\n expected = np.full_like(\\n self.cube_uv_down.data, dtype=np.float32, fill_value=0.1\\n )\\n result = calculate_uv_index(self.cube_uv_down, scale_factor)\\n self.assertArrayEqual(result.data, expected)\",\n \"def to_units(number):\\n unit = 0\\n while number >= 1024.:\\n unit += 1\\n number = number / 1024.\\n if unit == len(UNITS) - 1:\\n break\\n if unit:\\n return '%.2f%s' % (number, UNITS[unit])\\n return '%d' % number\",\n \"def convert_units(celsius_value, units):\\n if units == 0:\\n return celsius_value\\n if units == 1:\\n return celsius_value * 1.8 + 32\\n return celsius_value + 273.15\",\n \"def convert(value, units: UnitLike, registry: unyt.UnitRegistry = None):\\n return process_unit_input(value, units, convert=True, registry=registry).v\",\n \"def _get_units(self, q) -> unyt.Unit:\\n try:\\n units = q.units\\n except AttributeError:\\n units = unyt.dimensionless\\n return unyt.Unit(units, registry=self.registry)\",\n \"def units(self):\\n pass\",\n \"def convert_units(self, time_units=None, len_units=None):\\n in_time = self.time_units\\n # Check new time units\\n if time_units is None:\\n time_units = in_time\\n flag = _units.validate_units(time_units)\\n if flag == -1:\\n raise ValueError('Bad time units input {}'.format(time_units))\\n # Check new length units\\n in_len = self.len_units\\n if len_units is None:\\n len_units = in_len\\n flag = _units.validate_units(len_units)\\n if flag == -1:\\n raise ValueError('Bad length units input {}'.format(len_units))\\n # Convert parameters units\\n for key, value in self.parameters.items():\\n if type(value) in [int, float]:\\n self.parameters[key] = _units.units_conversion(value, in_len, len_units)\\n # Convert drawdown data\\n self.drawdown.convert_units(time_units, len_units)\\n # Convert associate data units\\n for i in range(self.data_count()):\\n if self.data[i].dtype == 1: # drawdown units\\n data_units = len_units\\n elif self.data[i].dtype == 2: # first derivative units\\n data_units = len_units + \\\"/\\\" + time_units\\n elif self.data[i].dtype == 3: # second derivative units\\n data_units = len_units + \\\"/\\\" + time_units + \\\"2\\\"\\n self.data[i].convert_units(time_units, data_units)\\n self.len_units = len_units\\n self.time_units = time_units\\n # End Function\",\n \"def convert_F_units(F, lbda, in_unit='cgs', out_unit='si'):\\n\\n if in_unit == 'cgs':\\n new_F = (F*1e23*np.power(lbda,2))/(c.c.value*1e6) # convert to jy\\n elif in_unit == 'cgsA':\\n new_F = (F*1e27*np.power(lbda,2))/(c.c.value*1e6) # convert to jy\\n elif in_unit == 'si':\\n new_F = (F*1e26*np.power(lbda,2))/(c.c.value*1e6) # convert to jy\\n elif in_unit == \\\"jy\\\":\\n new_F=F\\n else:\\n msg = \\\"in_unit not recognized, try either 'cgs', 'si' or 'jy'.\\\"\\n raise TypeError(msg) \\n if out_unit == 'jy':\\n return new_F\\n elif out_unit == 'cgs':\\n return new_F*1e-23*c.c.value*1e6/np.power(lbda,2)\\n elif out_unit == 'si':\\n return new_F*1e-26*c.c.value*1e6/np.power(lbda,2)\\n else:\\n msg = \\\"out_unit not recognized, try either 'cgs', 'si' or 'jy'.\\\"\\n raise TypeError(msg)\",\n \"def convert_wave_to_units(self, wave):\\n return [self.convert_point_to_units(i) for i in wave]\",\n \"def units_to_pixels(self,units_):\\n if type(units_) == str and units_.lower() in [\\\"fwhm\\\",\\\"psf\\\"]:\\n units_ = self.fwhm\\n\\n return super(Image, self).units_to_pixels(units_, target=self.target)\",\n \"def convert_unit(size_in_bytes, unit):\\n if unit == 'KB':\\n return size_in_bytes/1024\\n elif unit == 'MB':\\n return size_in_bytes/(1024*1024)\\n elif unit == 'GB':\\n return size_in_bytes/(1024*1024*1024)\\n else:\\n return size_in_bytes\",\n \"def units(self, x):\\n u = ''.join([chr(d) for d in self[x]['units'][:]])\\n if (u in ['n/a']) and (x in ['latitude', 'longitude']):\\n u = 'radian' # assume radians\\n return u\",\n \"def native_unit_of_measurement(self) -> str:\\n return f\\\"{CURRENCY_CENT}/{UnitOfVolume.LITERS}\\\"\",\n \"def _fix_units(cube, definition):\\n\\n if cube.var_name != 'pr':\\n cube.convert_units(definition.units)\",\n \"def convert(obj, unit, axis):\\r\\n return obj\",\n \"def infer_original_units(self, dimensions):\\n dimensions = units.Unit(dimensions)\\n d = dimensions.dimensional_project(\\n self._file_units_system + [\\\"a\\\", \\\"h\\\"])\\n new_unit = reduce(lambda x, y: x * y, [\\n a ** b for a, b in zip(self._file_units_system, d)])\\n return new_unit\",\n \"def unicode_of_unit(quant):\\n return quant.dimensionality.unicode\",\n \"def unit_of_measurement(self):\\n if self.values.primary.units == \\\"C\\\":\\n return TEMP_CELSIUS\\n if self.values.primary.units == \\\"F\\\":\\n return TEMP_FAHRENHEIT\\n\\n return self.values.primary.units\",\n \"def unit_of_measurement(self):\\n set_req = self.gateway.const.SetReq\\n unit_map = {\\n set_req.V_TEMP: (TEMP_CELSIUS\\n if self.gateway.metric else TEMP_FAHRENHEIT),\\n set_req.V_HUM: '%',\\n set_req.V_DIMMER: '%',\\n set_req.V_LIGHT_LEVEL: '%',\\n set_req.V_WEIGHT: 'kg',\\n set_req.V_DISTANCE: 'm',\\n set_req.V_IMPEDANCE: 'ohm',\\n set_req.V_WATT: 'W',\\n set_req.V_KWH: 'kWh',\\n set_req.V_FLOW: 'm',\\n set_req.V_VOLUME: 'm3',\\n set_req.V_VOLTAGE: 'V',\\n set_req.V_CURRENT: 'A',\\n }\\n if float(self.gateway.protocol_version) >= 1.5:\\n if set_req.V_UNIT_PREFIX in self._values:\\n return self._values[\\n set_req.V_UNIT_PREFIX]\\n unit_map.update({set_req.V_PERCENTAGE: '%'})\\n if float(self.gateway.protocol_version) >= 2.0:\\n unit_map.update({\\n set_req.V_ORP: 'mV',\\n set_req.V_EC: 'μS/cm',\\n set_req.V_VAR: 'var',\\n set_req.V_VA: 'VA',\\n })\\n return unit_map.get(self.value_type)\",\n \"def _get_units(self, name):\\n meta = self._abs2meta\\n\\n if name in meta:\\n return meta[name]['units']\\n\\n proms = self._prom2abs\\n\\n if name in proms['output']:\\n abs_name = proms['output'][name][0]\\n return meta[abs_name]['units']\\n\\n elif name in proms['input']:\\n if len(proms['input'][name]) > 1:\\n # The promoted name maps to multiple absolute names, require absolute name.\\n msg = \\\"Can't get units for the promoted name '%s' because it refers to \\\" + \\\\\\n \\\"multiple inputs: %s. Access the units using an absolute path name.\\\"\\n raise RuntimeError(msg % (name, str(proms['input'][name])))\\n\\n abs_name = proms['input'][name][0]\\n return meta[abs_name]['units']\\n\\n raise KeyError('Variable name \\\"{}\\\" not found.'.format(name))\",\n \"def get_unit(scale):\\n scale2unit = { 1e-9: 'nm',\\n 1e-6: u'\\\\N{MICRO SIGN}m', #or hex id (lookup): u'\\\\u00B5'\\n 1e-3: 'mm',\\n 0.01: 'cm',\\n 0.1:'dm',\\n 1:'m',\\n 1000:'km',\\n # time\\n 8.6400e4:'day',\\n 3.1536e7:'yr',\\n 3.1536e10:'ka',\\n 3.1536e13:'Ma',\\n #Pressure\\n 1e9: 'GPa',\\n 1e6: 'MPa',\\n }\\n return scale2unit[scale]\",\n \"def _getunits(x):\\n if pb.units.has_units(x):\\n \\n units = x.units\\n \\n else:\\n \\n units = None\\n \\n return units\",\n \"def init():\\n return _libsbml.SBMLUnitsConverter_init()\",\n \"def convert(value, unit, axis):\\n converted_value = value\\n if isinstance(unit, str) or isinstance(unit, Unit):\\n unit = (unit,)\\n if isinstance(value, (unyt_array, unyt_quantity)):\\n converted_value = value.to(*unit)\\n else:\\n value_type = type(value)\\n converted_value = []\\n for obj in value:\\n converted_value.append(obj.to(*unit))\\n converted_value = value_type(converted_value)\\n return converted_value\",\n \"def unit_array(self):\\n return self._data_array.values * units(self._units)\",\n \"def convert_frequency_2_internal_u(self,val):\\n return val*conversion_facs_frequency[self.current_units[\\\"frequency\\\"]]\",\n \"def unitsDetector(self, num):\\n try:\\n num = int(num)\\n except:\\n sys.exit('Invalid input! Method only takes ints or floats.')\\n \\n digits = 0\\n while num > 1:\\n num /= 10\\n digits += 1\\n \\n digits -= 1\\n ind = digits // 3\\n units = {3: 'B', 2: 'M', 1: 'K', 0: ''}[ind]\\n \\n return 10 ** (ind * 3), units\",\n \"def _unyt_array_convert_to_units_no_em(self, units, equivalence=None, **kwargs):\\n units = _sanitize_units_convert(units, self.units.registry)\\n if equivalence is None:\\n new_units = units\\n (conv_factor,\\n offset) = self.units.get_conversion_factor(new_units, self.dtype)\\n\\n self.units = new_units\\n values = self.d\\n # if our dtype is an integer do the following somewhat awkward\\n # dance to change the dtype in-place. We can't use astype\\n # directly because that will create a copy and not update self\\n if self.dtype.kind in (\\\"u\\\", \\\"i\\\"):\\n # create a copy of the original data in floating point\\n # form, it's possible this may lose precision for very\\n # large integers\\n dsize = values.dtype.itemsize\\n new_dtype = \\\"f\\\" + str(dsize)\\n large = LARGE_INPUT.get(dsize, 0)\\n if large and np.any(np.abs(values) > large):\\n warnings.warn(\\n \\\"Overflow encountered while converting to units '%s'\\\" %\\n new_units,\\n RuntimeWarning,\\n stacklevel=2,\\n )\\n float_values = values.astype(new_dtype)\\n # change the dtypes in-place, this does not change the\\n # underlying memory buffer\\n values.dtype = new_dtype\\n self.dtype = new_dtype\\n # actually fill in the new float values now that our\\n # dtype is correct\\n np.copyto(values, float_values)\\n values *= conv_factor\\n\\n if offset:\\n np.subtract(values, offset, values)\\n else:\\n self.convert_to_equivalent(units, equivalence, **kwargs)\",\n \"def convert(self, value, unit, axis):\\n scaled = getattr(value, self.scale)\\n if self.format in YMDHMS_FORMATS:\\n return scaled.mjd\\n elif self.format == \\\"byear_str\\\":\\n return scaled.byear\\n elif self.format == \\\"jyear_str\\\":\\n return scaled.jyear\\n else:\\n return getattr(scaled, self.format)\",\n \"def remove_units(namespace):\\n res = copy(namespace)\\n for label, value in res.__dict__.items():\\n if isinstance(value, pd.Series):\\n value = remove_units_series(value)\\n res.__dict__[label] = magnitude(value)\\n return res\",\n \"def unit_of_measurement(self) -> str:\\n raw_units = self.raw_units\\n\\n if raw_units in [TEMP_CELSIUS, TEMP_FAHRENHEIT]:\\n return self.hass.config.units.temperature_unit\\n return raw_units\",\n \"def get_converted_si_unit():\\n units = request.args.get('units')\\n response = ConvertUnit(units).convert()\\n return jsonify(response)\",\n \"def unitpicker(a, llim=0.1):\\n udict = {0: 'mol/mol',\\n 1: 'mmol/mol',\\n 2: '$\\\\mu$mol/mol',\\n 3: 'nmol/mol',\\n 4: 'pmol/mol',\\n 5: 'fmol/mol'}\\n a = abs(a)\\n n = 0\\n if a < llim:\\n while a < llim:\\n a *= 1000\\n n += 1\\n return float(1000**n), udict[n]\",\n \"def _get_unit_factor(self, unit: str) -> np.ndarray:\\n\\n unit_factors = {\\n 'vx': np.array((1, 1, 1)),\\n 'nm': np.array(self.parameters.scale),\\n 'um': np.array(self.parameters.scale)/1000\\n }\\n assert unit in unit_factors.keys(), 'Invalid unit'\\n unit_factor = unit_factors[unit]\\n\\n return unit_factor\",\n \"def to(self, unit, equivalencies=[]):\\n\\n return super(BaseOneDSpectrum, self).to(unit, equivalencies, freq=None)\",\n \"def convert_units(src_unit: Union[str, float], tgt_unit: Union[str, float]):\\n return _parse_unit(src_unit) / _parse_unit(tgt_unit)\",\n \"def _to(\\n value: Union[\\\"Value\\\", \\\"ValueArray\\\"], units: Union[Unit, str], inplace: bool\\n) -> Any:\\n if value.units == units:\\n return value\\n\\n if value.units is None:\\n raise RuntimeError(\\\"Cannot convert with units=None\\\")\\n\\n try:\\n units = next(\\n imp_unit\\n for imp_unit in value.implemented_units\\n if units.lower() in imp_unit.aliases\\n )\\n\\n except StopIteration:\\n raise TypeError(\\n f\\\"No viable unit conversion from {value.units} -> {units}\\\"\\n )\\n\\n if not (isinstance(value, Value) or isinstance(value, ValueArray)):\\n raise ValueError(\\n f\\\"Cannot convert {value} to new units. Must be one of\\\"\\n f\\\" Value of ValueArray\\\"\\n )\\n\\n if isinstance(value, Value) and inplace:\\n raise ValueError(\\n \\\"Cannot modify a value inplace as floats are immutable\\\"\\n )\\n\\n # Convert to the base unit, then to the new units\\n c = float(units.conversion / value.units.conversion)\\n\\n new_value = value if inplace else value.copy()\\n new_value *= c\\n new_value.units = units\\n\\n return None if inplace else new_value\",\n \"def convert_energy_2_internal_u(self,val):\\n units = self.current_units[\\\"energy\\\"]\\n cfact = conversion_facs_energy[self.current_units[\\\"energy\\\"]]\\n \\n # special handling for nano meters\\n if units == \\\"nm\\\":\\n # zero is interpretted as zero energy\\n try:\\n ret = numpy.zeros(val.shape, dtype=val.dtype)\\n ret[val!=0.0] = 1.0/val[val!=0]\\n return ret/cfact\\n except: \\n return (1.0/val)/cfact\\n #if val == 0.0:\\n # return 0.0\\n #return (1.0/val)/cfact\\n else:\\n return val*cfact\",\n \"def convert_path_units(self, path_to_conv):\\n\\n converted_path = copy.deepcopy(path_to_conv) # TODO: figure out if this is the right way to do this- I have not yet understood how data should be handled here\\n\\n for i, coord in enumerate(converted_path):\\n converted_path[i][0] = coord[0] / self.units_in_meter\\n converted_path[i][1] = coord[1] / self.units_in_meter\\n converted_path[i][2] = coord[2] / self.units_in_meter\\n\\n return converted_path\",\n \"def get_units(self):\\n return str(self._modeler.GetModelUnits())\",\n \"def units(inventory):\\n return inventory.reduce(convert.get_units)\",\n \"def unit_of_measurement(self):\\n return self.values.primary.units\",\n \"def units(self):\\n return self._units\",\n \"def units(self):\\n return self._units\",\n \"def unit(x,convert_to=\\\"px\\\",from_unit=\\\"px\\\"):\\n assert convert_to in UNITS, \\\"Cannot convert to unknown unit: %s\\\" % convert_to\\n assert from_unit in UNITS, \\\"Cannot from unknown unit: %s\\\" % from_unit\\n return float(x)*UNITS[convert_to]/UNITS[from_unit]\",\n \"def convert_energy_2_current_u(self,val):\\n units = self.current_units[\\\"energy\\\"]\\n cfact = conversion_facs_energy[units]\\n \\n # special handling for nanometers\\n if units == \\\"nm\\\":\\n # zero is interpretted as zero energy\\n try:\\n ret = numpy.zeros(val.shape, dtype=val.dtype)\\n ret[val!=0.0] = 1.0/val[val!=0]\\n return ret/cfact\\n except: \\n return (1.0/val)/cfact\\n else:\\n return val/cfact\",\n \"def _parse_units(self, model, comp, node):\\n node = dom_child(node, 'unitDefinition')\\n while node:\\n name = node.getAttribute('id')\\n self.log('Parsing unit definition for \\\"' + name + '\\\".')\\n unit = myokit.units.dimensionless\\n node2 = dom_child(node, 'listOfUnits')\\n node2 = dom_child(node2, 'unit')\\n while node2:\\n kind = str(node2.getAttribute('kind')).strip()\\n u2 = self._convert_unit(kind)\\n if node2.hasAttribute('multiplier'):\\n m = float(node2.getAttribute('multiplier'))\\n else:\\n m = 1.0\\n if node2.hasAttribute('scale'):\\n m *= 10 ** float(node2.getAttribute('scale'))\\n u2 *= m\\n if node2.hasAttribute('exponent'):\\n u2 **= float(node2.getAttribute('exponent'))\\n unit *= u2\\n node2 = dom_next(node2, 'unit')\\n self.units[name] = unit\\n node = dom_next(node, 'unitDefinition')\",\n \"def extendedConvert(self):\\r\\n devId = str(self.deviceId)\\r\\n if(devId == '28' or devId == '29'):\\r\\n answers = []\\r\\n #just add the counter value\\r\\n answers.append(self.fields[1])\\r\\n #find the engineering units converter\\r\\n enum = self.fields[0] & 0x3F\\r\\n #look up the scale and offset for that eeu\\r\\n eeu = self._eeumaps[str(enum)]\\r\\n self.eeu1 = eeu\\r\\n print('eeu:' + str(eeu))\\r\\n #convert from twos complement and adjust by scale/offset\\r\\n val = (self.convertSigned16(self.fields[2]) * eeu[1]) + eeu[0]\\r\\n answers.append(val)\\r\\n #reset fields to hold the new answers\\r\\n self.fields = answers\\r\\n self.units = [self.UNITS_COUNT, eeu[2]]\\r\\n elif(devId == '53' or devId == '54'):\\r\\n #strip off the first part of the answer which is the last part of the\\r\\n #serial number\\r\\n answers = [self.fields[1]]\\r\\n self.fields = answers\\r\\n elif(devId == '75' or devId == '76'):\\r\\n answers = []\\r\\n #find out the number of I/O points\\r\\n pointCount = self.fields[0] & 3\\r\\n #find out engineering units for 1st I/O\\r\\n enum = self.fields[1] & 0x3F\\r\\n eeu = self._eeumaps[str(enum)]\\r\\n self.eeu1 = eeu\\r\\n #new value = old value * scale + offset\\r\\n val = (self.convertSigned16(self.fields[3]) * eeu[1]) + eeu[0]\\r\\n answers.append(val)\\r\\n self.units = [eeu[2]]\\r\\n #see if there's two\\r\\n if pointCount == 2:\\r\\n #find out engineering units for 2nd I/O\\r\\n #and off first two bits\\r\\n enum = self.fields[0] >> 2\\r\\n eeu = self._eeumaps[str(enum)]\\r\\n self.eeu2 = eeu\\r\\n val = (self.convertSigned16(self.fields[2]) * eeu[1]) + eeu[0]\\r\\n answers.append(val)\\r\\n self.units.append(eeu[2])\\r\\n else:\\r\\n self.eeu2 = []\\r\\n #reset fields to hold the new answers\\r\\n self.fields = answers\\r\\n\\r\\n return\",\n \"def unit_of_measurement(self):\\n\\n if self._sensor_class == DEVICE_CLASS_TEMPERATURE:\\n return TEMP_CELSIUS\\n\\n elif self._sensor_class == DEVICE_CLASS_HUMIDITY:\\n return '%'\",\n \"def unit_of_measurement(self):\\n return self._units\",\n \"def unit_of_measurement(self):\\n return self._metadata[1]\",\n \"def raw_units(self) -> str:\\n if self._node.uom == 'F':\\n return TEMP_FAHRENHEIT\\n if self._node.uom == 'C':\\n return TEMP_CELSIUS\\n return self._node.uom\",\n \"def parse_unit(self, unitelem) -> Unit:\\n u = Unit()\\n\\n u.unitid = unitelem.attrib['id'].strip()\\n div = unitelem.find('{*}divide')\\n if div is not None:\\n nom = div.find('{*}unitNumerator').find('{*}measure')\\n denom = div.find('{*}unitDenominator').find('{*}measure')\\n u.nom = re.sub('.*:', '', nom.text).lower()\\n u.denom = re.sub('.*:', '', denom.text).lower()\\n else:\\n m = unitelem.find('{*}measure')\\n u.nom = re.sub('.*:', '', m.text).lower()\\n\\n return u\",\n \"def unit_of_measurement(self):\\n return self.sensor_type[\\\"unit\\\"]\",\n \"def to_inch(self):\\r\\n if self.units != 'inch':\\r\\n self.units = 'inch'\\r\\n for statement in self.statements:\\r\\n statement.to_inch()\\r\\n for tool in iter(self.tools.values()):\\r\\n tool.to_inch()\\r\\n for primitive in self.primitives:\\r\\n primitive.to_inch()\\r\\n for hit in self.hits:\\r\\n hit.to_inch()\",\n \"def test_change_units(self):\\n s = State(\\\"water\\\", T=Q_(100, \\\"degC\\\"), p=Q_(1.0, \\\"atm\\\"), units=\\\"EE\\\")\\n assert s.units == \\\"EE\\\"\\n s.units = \\\"SI\\\"\\n assert s.units == \\\"SI\\\"\\n assert s.cv.units == \\\"kilojoule / kelvin / kilogram\\\"\\n assert s.cp.units == \\\"kilojoule / kelvin / kilogram\\\"\\n assert s.s.units == \\\"kilojoule / kelvin / kilogram\\\"\\n assert s.h.units == \\\"kilojoule / kilogram\\\"\\n assert s.T.units == \\\"degree_Celsius\\\"\\n assert s.u.units == \\\"kilojoule / kilogram\\\"\\n assert s.v.units == \\\"meter ** 3 / kilogram\\\"\\n assert s.p.units == \\\"bar\\\"\",\n \"def convert_volume(self, event):\\n try:\\n #Compare other unit to one unit(cubic decimeters)\\n current_value, current_unit = float(\\\"0\\\" + str(self.v.get())), self.dropdown.get()\\n unit_comp = {\\\"acre foot\\\": 1233481.837548, \\\"barrels\\\": 158.987295, \\\"bushels(UK)\\\": 36.36872, \\\"bushels(US)\\\": 35.23907, \\\"centiliters\\\": 0.01, \\\"cubic centimeters\\\": 0.001, \\\"cubic decameters\\\": 1000000.0, \\\"cubic decimeters\\\": 1.0, \\\"cubic feet\\\": 28.316847, \\\"cubic inches\\\": 0.016387, \\\"cubic kilometers\\\": 1000000000000.0, \\\"cubic meters\\\": 1000.0, \\\"cubic mile\\\": 4168181825000.0, \\\"cubic millimeters\\\": 1e-06, \\\"cubic yards\\\": 764.554858, \\\"cups\\\": 0.236588, \\\"deciliters\\\": 0.1, \\\"dram\\\": 0.003697, \\\"dram(imperial)\\\": 0.003552, \\\"fluid ounces(US)\\\": 0.029574, \\\"fluid ounces(imperial)\\\": 0.028413, \\\"gallons(US,dry)\\\": 4.404884, \\\"gallons(US,liquid)\\\": 3.785412, \\\"gallons(imperial)\\\": 4.54609, \\\"gill(US)\\\": 0.118294, \\\"gill(imperial)\\\": 0.142065, \\\"liters\\\": 1.0, \\\"liters(1901-1964)\\\": 1.000028, \\\"microliters\\\": 1e-06, \\\"milliliters\\\": 0.001, \\\"nanoliters\\\": 1e-09, \\\"picoliters\\\": 1e-12, \\\"pints(US,dry)\\\": 0.55061, \\\"pints(US,liquid)\\\": 0.473176, \\\"pints(imperial)\\\": 0.568261, \\\"quarts(UK,dry)\\\": 1.101221, \\\"quarts(US,liquid)\\\": 0.946353, \\\"quarts(imperial)\\\": 1.136523, \\\"table spoons\\\": 0.014787, \\\"tea spoons\\\": 0.004929}\\n value_comp, printer = current_value * unit_comp[current_unit], \\\"\\\"\\n unit_list = sorted(unit_comp.keys())\\n unit_list.remove(current_unit)\\n for unit in unit_list:\\n printer += \\\"To %s \\\" % unit + \\\" \\\" * (max([len(i) for i in unit_list]) - len(unit)) + str(value_comp / unit_comp[unit]) + [\\\"\\\", \\\"\\\\n\\\"][unit_list[-1] != unit]\\n except ValueError: #In case user enter the other type of value, not Int or Float\\n printer = \\\"Value is invalid.\\\"\\n self.print_text(printer)\",\n \"def units(self, key):\\n \\n # Strip any operators\\n _, key = get_operator(key)\\n \\n # Fill out aliases \\n if key in component_from_alias:\\n key = component_from_alias[key]\\n elif key == 'E':\\n key = 'electricField'\\n elif key == 'B':\\n key = 'magneticField' \\n \\n return pg_units(key)\",\n \"def unit_array(self, values):\\n self._data_array.values = values\\n self._units = self._data_array.attrs['units'] = str(values.units)\",\n \"def _get_units_object(self, units):\\n if isinstance(units, cellml_units):\\n # We're done\\n pass\\n else:\\n units = amara_parse_cellml(unicode(units))\\n assert isinstance(units, cellml_units)\\n return units\",\n \"def get_units(self, obj: Dimension) -> [Unit]:\\n try:\\n return obj.units()\\n except KeyError as e:\\n logging.error(str(e))\\n return []\",\n \"def raw_unit_of_measurement(self) -> str:\\n if len(self._node.uom) == 1:\\n if self._node.uom[0] in UOM_FRIENDLY_NAME:\\n friendly_name = UOM_FRIENDLY_NAME.get(self._node.uom[0])\\n if friendly_name == TEMP_CELSIUS or \\\\\\n friendly_name == TEMP_FAHRENHEIT:\\n friendly_name = self.hass.config.units.temperature_unit\\n return friendly_name\\n else:\\n return self._node.uom[0]\\n else:\\n return None\",\n \"def convert_same_units(self):\\n # Convert pumping rate data\\n pump_units = \\\"%s3/%s\\\" % (self.len_units, self.time_units)\\n flag = _units.validate_units(pump_units)\\n if flag == 2:\\n self.pumprate.convert_units(self.time_units, pump_units)\\n self.pump_units = pump_units\",\n \"def __convert_to_devunit(self, value, in_devunit=False):\\r\\n if not in_devunit:\\r\\n value *= self.DEVUNIT_RATIO\\r\\n elif not isinstance(value, int):\\r\\n self.print_msg((\\\"Warning: non-integer value ({}) is given \\\"\\r\\n + \\\"in device unit.\\\").format(value))\\r\\n return int(value)\",\n \"def convert_unit(self, time_unit):\\r\\n\\r\\n self.time_unit = time_unit\\r\\n self._conversion_factor = time_unit_conversion[time_unit]\",\n \"def SBMLInferUnitsConverter_init():\\n return _libsbml.SBMLInferUnitsConverter_init()\",\n \"def _get_wavelength_attrs_with_units(self, attrname, units='AA'):\\n attr = self._lick[attrname]\\n if self.wavelength_unit is not None:\\n if units is None:\\n return attr * Unit(self.wavelength_unit)\\n else:\\n return (attr * Unit(self.wavelength_unit)).to(units)\\n else:\\n return attr\",\n \"def assign_unit(self):\\n self.units = {}\\n for unit in RADIAL_UNITS:\\n if unit.REPR == \\\"2th_deg\\\":\\n self.units[unit] = self.tth_deg\\n elif unit.REPR == \\\"2th_rad\\\":\\n self.units[unit] = self.tth_rad\\n elif unit.REPR == \\\"q_nm^-1\\\":\\n self.units[unit] = self.q_nm\\n elif unit.REPR == \\\"q_A^-1\\\":\\n self.units[unit] = self.q_A\\n elif unit.REPR == \\\"r_mm\\\":\\n self.units[unit] = self.r_mm\\n else:\\n logger.warning(\\\"Unit unknown to GUI %s\\\" % unit)\",\n \"def to_base_unit(val: float, unit: str = \\\"\\\") -> float:\\n unit_scalar = UNITS.get(unit, None)\\n if not unit_scalar:\\n raise UnknownUnitError(f\\\"Unit '{unit}' is not supported\\\")\\n\\n return val * unit_scalar\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7362858","0.697799","0.68368673","0.6746229","0.67332226","0.6689847","0.6652228","0.6625354","0.6573514","0.6546448","0.65275437","0.64689595","0.6373749","0.63324165","0.6316742","0.6294838","0.6258834","0.62498343","0.6219283","0.62110245","0.6167998","0.6137672","0.6133157","0.6125503","0.6112528","0.6110727","0.6071122","0.60685724","0.606024","0.60133827","0.60061723","0.60002226","0.5996126","0.5989617","0.5983106","0.59775066","0.59765154","0.59739304","0.5956788","0.5951643","0.5949568","0.59125906","0.59040725","0.5879863","0.5868503","0.58579576","0.58541965","0.5826265","0.5822009","0.58170843","0.58169574","0.5816161","0.5803071","0.57918984","0.57713646","0.577034","0.5760419","0.57572776","0.57526916","0.5739368","0.5733606","0.5730924","0.573083","0.5721424","0.5704954","0.5704072","0.57021964","0.57005847","0.5699744","0.5697231","0.56910306","0.5687708","0.56850064","0.5683625","0.5683625","0.5683327","0.5668974","0.5665825","0.5665265","0.56531197","0.56528497","0.56511015","0.56442505","0.5644201","0.56434155","0.5642921","0.5642717","0.5634871","0.56291384","0.56268805","0.5613936","0.5611674","0.5609308","0.5604121","0.5600435","0.5599861","0.5599733","0.5593979","0.55897117","0.558881"],"string":"[\n \"0.7362858\",\n \"0.697799\",\n \"0.68368673\",\n \"0.6746229\",\n \"0.67332226\",\n \"0.6689847\",\n \"0.6652228\",\n \"0.6625354\",\n \"0.6573514\",\n \"0.6546448\",\n \"0.65275437\",\n \"0.64689595\",\n \"0.6373749\",\n \"0.63324165\",\n \"0.6316742\",\n \"0.6294838\",\n \"0.6258834\",\n \"0.62498343\",\n \"0.6219283\",\n \"0.62110245\",\n \"0.6167998\",\n \"0.6137672\",\n \"0.6133157\",\n \"0.6125503\",\n \"0.6112528\",\n \"0.6110727\",\n \"0.6071122\",\n \"0.60685724\",\n \"0.606024\",\n \"0.60133827\",\n \"0.60061723\",\n \"0.60002226\",\n \"0.5996126\",\n \"0.5989617\",\n \"0.5983106\",\n \"0.59775066\",\n \"0.59765154\",\n \"0.59739304\",\n \"0.5956788\",\n \"0.5951643\",\n \"0.5949568\",\n \"0.59125906\",\n \"0.59040725\",\n \"0.5879863\",\n \"0.5868503\",\n \"0.58579576\",\n \"0.58541965\",\n \"0.5826265\",\n \"0.5822009\",\n \"0.58170843\",\n \"0.58169574\",\n \"0.5816161\",\n \"0.5803071\",\n \"0.57918984\",\n \"0.57713646\",\n \"0.577034\",\n \"0.5760419\",\n \"0.57572776\",\n \"0.57526916\",\n \"0.5739368\",\n \"0.5733606\",\n \"0.5730924\",\n \"0.573083\",\n \"0.5721424\",\n \"0.5704954\",\n \"0.5704072\",\n \"0.57021964\",\n \"0.57005847\",\n \"0.5699744\",\n \"0.5697231\",\n \"0.56910306\",\n \"0.5687708\",\n \"0.56850064\",\n \"0.5683625\",\n \"0.5683625\",\n \"0.5683327\",\n \"0.5668974\",\n \"0.5665825\",\n \"0.5665265\",\n \"0.56531197\",\n \"0.56528497\",\n \"0.56511015\",\n \"0.56442505\",\n \"0.5644201\",\n \"0.56434155\",\n \"0.5642921\",\n \"0.5642717\",\n \"0.5634871\",\n \"0.56291384\",\n \"0.56268805\",\n \"0.5613936\",\n \"0.5611674\",\n \"0.5609308\",\n \"0.5604121\",\n \"0.5600435\",\n \"0.5599861\",\n \"0.5599733\",\n \"0.5593979\",\n \"0.55897117\",\n \"0.558881\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7536837"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":88597,"cells":{"query":{"kind":"string","value":"Convert the units of a bispectrum descriptor. Since these do not really have units this function does nothing yet."},"document":{"kind":"string","value":"def backconvert_units(array, out_units):\n if out_units == \"None\" or out_units is None:\n return array\n else:\n raise Exception(\"Unsupported unit for bispectrum descriptors.\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def convert_units(array, in_units=\"None\"):\n if in_units == \"None\" or in_units is None:\n return array\n else:\n raise Exception(\"Unsupported unit for bispectrum descriptors.\")","def convert_units(self):\n for prod in (\"ier\", \"ier_inc_rain\"):\n self.data[prod].data[:] /= 1e6","def convert_units(self, units):\n self.unit_array = self.unit_array.to(units)","def convert_units(unt, origunits):\n if unt[0:3] == origunits[0:3] | unt[0:3] == 'ori':\n units = origunits\n convf = 1\n else:\n if 'fee' == unt[(((0:3 -1) -1) -1)]:\n if origunits[0:3] == 'met':\n units = 'feet'\n convf = 3.2808399\n else:\n units = origunits\n convf = 1\n else:\n if 'met' == unt[(((0:3 -1) -1) -1)]:\n if origunits[0:3] == 'fee':\n units = 'meters'\n convf = 0.3048\n else:\n units = origunits\n convf = 1\n else:\n if 'm/s' == unt[(((0:3 -1) -1) -1)]:\n if origunits[0:3] == 'kno':\n units = 'meters/sec'\n convf = 0.51444444\n else:\n units = origunits\n convf = 1\n else:\n if 'kno' == unt[(((0:3 -1) -1) -1)]:\n if origunits[0:3] == 'm/s':\n units = 'knots'\n convf = 1.9438445\n else:\n units = origunits\n convf = 1\n else:\n error('Unknown units')\n #\n return units, convf","def convert(self):\n return _libsbml.SBMLUnitsConverter_convert(self)","def convert(self):\n return _libsbml.SBMLInferUnitsConverter_convert(self)","def convert_units(data, hdr, conv_to = \"surf_br\"):\n \n data_unit = hdr[\"SIGUNIT\"]\n \n if \"Jy/pix\" in data_unit:\n # pixel size in rad\n px_x = abs(hdr[\"CDELT1\"])*2*np.pi/360\n px_y = abs(hdr[\"CDELT2\"])*2*np.pi/360\n \n #pixel size in arcsec\n \n px_x = abs(hdr[\"CDELT1\"])*3600\n px_y = abs(hdr[\"CDELT2\"])*3600\n conversion_factor = 1000/(px_x*px_y)\n \n unit_label = \"mJy/arcsec^2\"\n \n #in case we want to convert to units flux, we need to multiply by the size (in steradians) of a pixel.\n if conv_to == \"flux\":\n conversion_factor*=abs(hdr[\"CDELT1\"])*abs(hdr[\"CDELT2\"])*(2*np.pi/360)**2\n unit_label = \"mJy\"\n \n data *= conversion_factor\n hdr[\"SIGUNIT\"] = unit_label\n else:\n print(\"\\t[WARNING]\\t \"+data_unit+\" conversion not yet implemented. No conversion performed.\")\n \n return data, hdr","def convertUnits(self, varname, arr):\n if varname == \"SPDQ\" or varname == \"PHQ\":\n return arr*2.5e6/1000.\n return arr","def convert_to_unit(self, data, unit):\n\n res = OrderedDict()\n\n # Loop over data and overwrite\n for ch in data:\n _idx = self.channels.index(ch)\n # Get data, scale and type of channel\n val, scale, _type = data[ch], self.daq_setup['devices']['adc']['ro_scales'][_idx], self.daq_setup['devices']['adc']['types'][_idx]\n # Adjust scale in case we're looking at SEM's sum signal; in this case current is multiplied by factor of 4\n scale *= 1 if _type != 'sem_sum' else 4\n\n res[ch] = val / 5.0 * scale * 1e-9 if unit == 'A' else val * 5.0 / 1e-9 / scale\n\n return res","def resolve_units(obj, _):\n return obj.units.decode()","def units_to_fits(unit):\n if unit is None:\n unit = Unit('')\n return unit.to_string(\"fits\").upper()","def convert_units(data, units):\n # Build the dictionary of units conversions\n convert = {'m' : [1.0, 0., 'm'], \n 'meter' : [1.0, 0., 'm'], \n 'deg C' : [1.0, 273.15, 'K'], \n 'Celsius' : [1.0, 273.15, 'K'], \n 'K' : [1.0, 0., 'K'],\n 'db' : [1.e4, 101325., 'Pa'], \n 'Pa' : [1.0, 0., 'Pa'],\n 'mg/m^3': [1.e-6, 0., 'kg/m^3'], \n 'S/m': [1.0, 0., 'S/m'],\n 'mS/m' : [1.e-3, 0., 'S/m'],\n 'psu': [1.0, 0., 'psu'], \n 'salinity': [1.0, 0., 'psu'], \n 'kg/m^3': [1.0, 0., 'kg/m^3'], \n 'kilogram meter-3': [1.0, 0., 'kg/m^3'], \n 'm/s': [1.0, 0., 'm/s'], \n 'mg/l': [1.e-3, 0., 'kg/m^3'],\n 'meter second-1' : [1.0, 0., 'm/s'],\n 'm.s-1' : [1.0, 0., 'm/s'],\n 'pH units' : [1.0, 0., 'pH units'],\n 'MPa' : [1.e6, 0., 'Pa'],\n '--' : [1.0, 0., '--'],\n 'mD' : [9.869233e-16, 0., 'm^2'],\n 'um' : [1.e-6, 0., 'm'],\n 'm/s 1e-9' : [1.e-9, 0., 'm/s'],\n 'm/s 1e-7' : [1.e-7, 0., 'm/s'],\n 'wt.%' : [10., 0., 'psu'],\n '10^-15 m^2' : [1.e-15, 0., 'm^2'],\n 'm^2' : [1., 0., 'm^2'],\n 'kg/m^2/year' : [3.168808781402895e-08, 0., 'kg/m^2/s'] \n } \n \n # Make sure the data are a numpy array and the units are a list\n if isinstance(data, float) or isinstance(data, int):\n data = np.array([data])\n if isinstance(data, list):\n data = np.array(data)\n if isinstance(units, str) or isinstance(units, unicode):\n units = [units]\n if units == None:\n units = ['']\n \n # Make sure you can slice through the columns: must be two-dimensional\n sh = data.shape\n data = np.atleast_2d(data)\n \n # Allow conversion of a row of data if all of the same unit\n if len(units) == 1 and data.shape[1] > 1:\n data = data.transpose()\n \n # Create an emtpy array to hold the output\n out_data = np.zeros(data.shape)\n out_units = []\n \n # Convert the units\n for i in range(len(units)):\n try:\n out_data[:,i] = data[:,i] * convert[units[i]][0] + \\\n convert[units[i]][1]\n out_units += [convert[units[i]][2]]\n except KeyError:\n print('Do not know how to convert %s to mks units' % units[i])\n print('Continuing without converting these units...')\n out_data[:,i] = data[:,i]\n out_units += units[i]\n \n # Return the converted data in the original shape\n out_data = np.reshape(out_data, sh, 'C')\n return (out_data, out_units)","def get_units(self):\r\n msg = struct.pack('>2B', 56, 14)\r\n response = self.query(msg)\r\n\r\n if response[1] == 2:\r\n units = 'A'\r\n to_nm_multiplier = 1 / 10\r\n elif response[1] == 1:\r\n units = 'nm'\r\n to_nm_multiplier = 1\r\n elif response[1] == 0:\r\n units = 'um'\r\n to_nm_multiplier = 1000\r\n else:\r\n raise ValueError('Units not recognised.')\r\n\r\n # Save results locally too for quick re-use\r\n self._current_units = units\r\n self._current_to_nm_multiplier = to_nm_multiplier\r\n\r\n return units, to_nm_multiplier","def __convert_to_mm(self, value, in_devunit=True):\r\n if in_devunit:\r\n value /= self.DEVUNIT_RATIO\r\n return value","def _convert_value(self, value, unit, axis):\n if hasattr(value, 'units'):\n return value.to(unit).magnitude\n else:\n return self._reg.Quantity(value, axis.get_units()).to(unit).magnitude","def test_convert_compatible_units(self):\n result = convert_units(self.arr, 'degC')\n expected_data = np.array([[-273.15, -272.15], [-271.15, -270.15]])\n expected_units = cf_units.Unit('degC')\n self.assertEquals(result.units, expected_units)\n self.assertArrayEqual(result.data, expected_data)","def useUnits():","def to_unit(self, unit):\n unit = _find_unit(unit)\n self.value = _convert_value(self.value, self.unit, unit)\n self.unit = unit","def extract_specs(self):\n vDeflection_unit = \"lcd-info.{}.conversion-set.conversion.force.scaling.unit.unit\".format(\n self.channel_numbers[\"vDeflection\"])\n self.units[\"vDeflection\"] = self.general[vDeflection_unit]\n\n height_unit = \"lcd-info.{}.conversion-set.conversion.nominal.scaling.unit.unit\".format(\n self.channel_numbers[\"height\"])\n self.units[\"height\"] = self.general[height_unit]","def unit_converter(val, from_u, to_u):\n\tconverter = {'b':0, 'k':1, 'm':2, 'g':3, 't':4}\n\tif converter[from_u] < converter[to_u]:\n\t\tval = float(val)\n\t\tfor _ in range(converter[to_u] - converter[from_u]):\n\t\t\tval = val/1024\n\telse:\n\t\tfor _ in range(converter[from_u] - converter[to_u]):\n\t\t\tval = val * 1024\n\t\t\t\n\treturn val","def normalize_units(data):\n for obj in data:\n obj['unit'] = normalize_units_function(obj.get('unit', ''))\n # for param in ds.get('parameters', {}).values():\n # if 'unit' in param:\n # param['unit'] = normalize_units_function(param['unit'])\n return data","def _convert_unit(self, unit):\n if unit in self.units:\n return self.units[unit]\n elif unit in unit_map:\n return unit_map[unit]\n else:\n raise SBMLError('Unit not recognized: ' + str(unit))","def _get_units(self):\n #assert self.ser.isOpen()\n\n self.serial_connection.write('UNI' + self.CR + self.LF)\n acknowledgement = self.serial_connection.readline()\n self._check_acknowledgement(acknowledgement)\n\n self.serial_connection.write(self.ENQ)\n unit = self.MEASUREMENT_UNITS[self.serial_connection.readline().rstrip(self.LF).rstrip(self.CR)]\n\n self.serial_connection.write(self.CR + self.LF)\n\n return unit","def to_axis_units(self, label, vals):\n if label in ['Hmolar', 'Smolar', 'Umolar', 'Dmolar', 'P']:\n return vals / 1000\n elif label in ['T']:\n return vals\n else:\n raise ValueError(label)","def fits_to_units(unit_str):\n unit_lookup = {\n 'meters': 'm',\n 'meter': 'm',\n 'degrees': 'deg',\n 'degree': 'deg',\n 'hz': 'Hz',\n 'hertz': 'Hz',\n 'second': 's',\n 'sec': 's',\n 'secs': 's',\n 'days': 'd',\n 'day': 'd',\n 'steradians': 'sr',\n 'steradian': 'sr',\n 'radians': 'rad',\n 'radian': 'rad',\n 'jy': 'Jy',\n 'au': 'AU',\n }\n\n try:\n new_units = \"\"\n\n if unit_str is None:\n unit_str = ''\n unit_str = unit_str.lower()\n unit_list = unit_str.split(\"/\")\n\n for uu in unit_list:\n if uu.endswith(\"s\") and len(uu) > 1:\n uu = uu[:-1]\n corrected_unit = unit_lookup.get(uu, uu)\n new_units += corrected_unit\n new_units += \" / \"\n new_units = new_units[:-3]\n unit = Unit(new_units)\n return unit\n\n except ValueError:\n warnings.warn(\"Unknown unit: %s\" % new_units, UnitWarning)\n return UnrecognizedUnit(unit_str)","def SBMLUnitsConverter_init():\n return _libsbml.SBMLUnitsConverter_init()","def get_units(self,):\n self.UNITS = {'pressure':'Pa',}\n return","def _d_converter(self):\n units = {'um':1e-6, 'mm':1e-3, 'inch':2.54e-2, 'in':2.54e-2,\\\n 'micron':1e-6, 'mil':2.54e-5, 'm':1.0}\n for i in self.stack:\n i.thickness = i.thickness*units[i.units]\n return","def convertUnit(*args, fromUnit: AnyStr=\"\", toUnit: AnyStr=\"\", **kwargs)->float:\n pass","def convert(self, value, units, newunits):\n return value * self._units[units] / self._units[newunits]","def convertToSpectroGram(self):","def test_unit_conversion(self):\n self.cube_uv_down.convert_units(\"kW m-2\")\n scale_factor = 1.0\n expected = np.full_like(\n self.cube_uv_down.data, dtype=np.float32, fill_value=0.1\n )\n result = calculate_uv_index(self.cube_uv_down, scale_factor)\n self.assertArrayEqual(result.data, expected)","def to_units(number):\n unit = 0\n while number >= 1024.:\n unit += 1\n number = number / 1024.\n if unit == len(UNITS) - 1:\n break\n if unit:\n return '%.2f%s' % (number, UNITS[unit])\n return '%d' % number","def convert_units(celsius_value, units):\n if units == 0:\n return celsius_value\n if units == 1:\n return celsius_value * 1.8 + 32\n return celsius_value + 273.15","def convert(value, units: UnitLike, registry: unyt.UnitRegistry = None):\n return process_unit_input(value, units, convert=True, registry=registry).v","def _get_units(self, q) -> unyt.Unit:\n try:\n units = q.units\n except AttributeError:\n units = unyt.dimensionless\n return unyt.Unit(units, registry=self.registry)","def units(self):\n pass","def convert_units(self, time_units=None, len_units=None):\n in_time = self.time_units\n # Check new time units\n if time_units is None:\n time_units = in_time\n flag = _units.validate_units(time_units)\n if flag == -1:\n raise ValueError('Bad time units input {}'.format(time_units))\n # Check new length units\n in_len = self.len_units\n if len_units is None:\n len_units = in_len\n flag = _units.validate_units(len_units)\n if flag == -1:\n raise ValueError('Bad length units input {}'.format(len_units))\n # Convert parameters units\n for key, value in self.parameters.items():\n if type(value) in [int, float]:\n self.parameters[key] = _units.units_conversion(value, in_len, len_units)\n # Convert drawdown data\n self.drawdown.convert_units(time_units, len_units)\n # Convert associate data units\n for i in range(self.data_count()):\n if self.data[i].dtype == 1: # drawdown units\n data_units = len_units\n elif self.data[i].dtype == 2: # first derivative units\n data_units = len_units + \"/\" + time_units\n elif self.data[i].dtype == 3: # second derivative units\n data_units = len_units + \"/\" + time_units + \"2\"\n self.data[i].convert_units(time_units, data_units)\n self.len_units = len_units\n self.time_units = time_units\n # End Function","def convert_F_units(F, lbda, in_unit='cgs', out_unit='si'):\n\n if in_unit == 'cgs':\n new_F = (F*1e23*np.power(lbda,2))/(c.c.value*1e6) # convert to jy\n elif in_unit == 'cgsA':\n new_F = (F*1e27*np.power(lbda,2))/(c.c.value*1e6) # convert to jy\n elif in_unit == 'si':\n new_F = (F*1e26*np.power(lbda,2))/(c.c.value*1e6) # convert to jy\n elif in_unit == \"jy\":\n new_F=F\n else:\n msg = \"in_unit not recognized, try either 'cgs', 'si' or 'jy'.\"\n raise TypeError(msg) \n if out_unit == 'jy':\n return new_F\n elif out_unit == 'cgs':\n return new_F*1e-23*c.c.value*1e6/np.power(lbda,2)\n elif out_unit == 'si':\n return new_F*1e-26*c.c.value*1e6/np.power(lbda,2)\n else:\n msg = \"out_unit not recognized, try either 'cgs', 'si' or 'jy'.\"\n raise TypeError(msg)","def convert_wave_to_units(self, wave):\n return [self.convert_point_to_units(i) for i in wave]","def units_to_pixels(self,units_):\n if type(units_) == str and units_.lower() in [\"fwhm\",\"psf\"]:\n units_ = self.fwhm\n\n return super(Image, self).units_to_pixels(units_, target=self.target)","def convert_unit(size_in_bytes, unit):\n if unit == 'KB':\n return size_in_bytes/1024\n elif unit == 'MB':\n return size_in_bytes/(1024*1024)\n elif unit == 'GB':\n return size_in_bytes/(1024*1024*1024)\n else:\n return size_in_bytes","def units(self, x):\n u = ''.join([chr(d) for d in self[x]['units'][:]])\n if (u in ['n/a']) and (x in ['latitude', 'longitude']):\n u = 'radian' # assume radians\n return u","def native_unit_of_measurement(self) -> str:\n return f\"{CURRENCY_CENT}/{UnitOfVolume.LITERS}\"","def _fix_units(cube, definition):\n\n if cube.var_name != 'pr':\n cube.convert_units(definition.units)","def convert(obj, unit, axis):\r\n return obj","def infer_original_units(self, dimensions):\n dimensions = units.Unit(dimensions)\n d = dimensions.dimensional_project(\n self._file_units_system + [\"a\", \"h\"])\n new_unit = reduce(lambda x, y: x * y, [\n a ** b for a, b in zip(self._file_units_system, d)])\n return new_unit","def unicode_of_unit(quant):\n return quant.dimensionality.unicode","def unit_of_measurement(self):\n if self.values.primary.units == \"C\":\n return TEMP_CELSIUS\n if self.values.primary.units == \"F\":\n return TEMP_FAHRENHEIT\n\n return self.values.primary.units","def _get_units(self, name):\n meta = self._abs2meta\n\n if name in meta:\n return meta[name]['units']\n\n proms = self._prom2abs\n\n if name in proms['output']:\n abs_name = proms['output'][name][0]\n return meta[abs_name]['units']\n\n elif name in proms['input']:\n if len(proms['input'][name]) > 1:\n # The promoted name maps to multiple absolute names, require absolute name.\n msg = \"Can't get units for the promoted name '%s' because it refers to \" + \\\n \"multiple inputs: %s. Access the units using an absolute path name.\"\n raise RuntimeError(msg % (name, str(proms['input'][name])))\n\n abs_name = proms['input'][name][0]\n return meta[abs_name]['units']\n\n raise KeyError('Variable name \"{}\" not found.'.format(name))","def unit_of_measurement(self):\n set_req = self.gateway.const.SetReq\n unit_map = {\n set_req.V_TEMP: (TEMP_CELSIUS\n if self.gateway.metric else TEMP_FAHRENHEIT),\n set_req.V_HUM: '%',\n set_req.V_DIMMER: '%',\n set_req.V_LIGHT_LEVEL: '%',\n set_req.V_WEIGHT: 'kg',\n set_req.V_DISTANCE: 'm',\n set_req.V_IMPEDANCE: 'ohm',\n set_req.V_WATT: 'W',\n set_req.V_KWH: 'kWh',\n set_req.V_FLOW: 'm',\n set_req.V_VOLUME: 'm3',\n set_req.V_VOLTAGE: 'V',\n set_req.V_CURRENT: 'A',\n }\n if float(self.gateway.protocol_version) >= 1.5:\n if set_req.V_UNIT_PREFIX in self._values:\n return self._values[\n set_req.V_UNIT_PREFIX]\n unit_map.update({set_req.V_PERCENTAGE: '%'})\n if float(self.gateway.protocol_version) >= 2.0:\n unit_map.update({\n set_req.V_ORP: 'mV',\n set_req.V_EC: 'μS/cm',\n set_req.V_VAR: 'var',\n set_req.V_VA: 'VA',\n })\n return unit_map.get(self.value_type)","def get_unit(scale):\n scale2unit = { 1e-9: 'nm',\n 1e-6: u'\\N{MICRO SIGN}m', #or hex id (lookup): u'\\u00B5'\n 1e-3: 'mm',\n 0.01: 'cm',\n 0.1:'dm',\n 1:'m',\n 1000:'km',\n # time\n 8.6400e4:'day',\n 3.1536e7:'yr',\n 3.1536e10:'ka',\n 3.1536e13:'Ma',\n #Pressure\n 1e9: 'GPa',\n 1e6: 'MPa',\n }\n return scale2unit[scale]","def _getunits(x):\n if pb.units.has_units(x):\n \n units = x.units\n \n else:\n \n units = None\n \n return units","def init():\n return _libsbml.SBMLUnitsConverter_init()","def unit_array(self):\n return self._data_array.values * units(self._units)","def convert(value, unit, axis):\n converted_value = value\n if isinstance(unit, str) or isinstance(unit, Unit):\n unit = (unit,)\n if isinstance(value, (unyt_array, unyt_quantity)):\n converted_value = value.to(*unit)\n else:\n value_type = type(value)\n converted_value = []\n for obj in value:\n converted_value.append(obj.to(*unit))\n converted_value = value_type(converted_value)\n return converted_value","def unitsDetector(self, num):\n try:\n num = int(num)\n except:\n sys.exit('Invalid input! Method only takes ints or floats.')\n \n digits = 0\n while num > 1:\n num /= 10\n digits += 1\n \n digits -= 1\n ind = digits // 3\n units = {3: 'B', 2: 'M', 1: 'K', 0: ''}[ind]\n \n return 10 ** (ind * 3), units","def convert_frequency_2_internal_u(self,val):\n return val*conversion_facs_frequency[self.current_units[\"frequency\"]]","def _unyt_array_convert_to_units_no_em(self, units, equivalence=None, **kwargs):\n units = _sanitize_units_convert(units, self.units.registry)\n if equivalence is None:\n new_units = units\n (conv_factor,\n offset) = self.units.get_conversion_factor(new_units, self.dtype)\n\n self.units = new_units\n values = self.d\n # if our dtype is an integer do the following somewhat awkward\n # dance to change the dtype in-place. We can't use astype\n # directly because that will create a copy and not update self\n if self.dtype.kind in (\"u\", \"i\"):\n # create a copy of the original data in floating point\n # form, it's possible this may lose precision for very\n # large integers\n dsize = values.dtype.itemsize\n new_dtype = \"f\" + str(dsize)\n large = LARGE_INPUT.get(dsize, 0)\n if large and np.any(np.abs(values) > large):\n warnings.warn(\n \"Overflow encountered while converting to units '%s'\" %\n new_units,\n RuntimeWarning,\n stacklevel=2,\n )\n float_values = values.astype(new_dtype)\n # change the dtypes in-place, this does not change the\n # underlying memory buffer\n values.dtype = new_dtype\n self.dtype = new_dtype\n # actually fill in the new float values now that our\n # dtype is correct\n np.copyto(values, float_values)\n values *= conv_factor\n\n if offset:\n np.subtract(values, offset, values)\n else:\n self.convert_to_equivalent(units, equivalence, **kwargs)","def convert(self, value, unit, axis):\n scaled = getattr(value, self.scale)\n if self.format in YMDHMS_FORMATS:\n return scaled.mjd\n elif self.format == \"byear_str\":\n return scaled.byear\n elif self.format == \"jyear_str\":\n return scaled.jyear\n else:\n return getattr(scaled, self.format)","def remove_units(namespace):\n res = copy(namespace)\n for label, value in res.__dict__.items():\n if isinstance(value, pd.Series):\n value = remove_units_series(value)\n res.__dict__[label] = magnitude(value)\n return res","def unit_of_measurement(self) -> str:\n raw_units = self.raw_units\n\n if raw_units in [TEMP_CELSIUS, TEMP_FAHRENHEIT]:\n return self.hass.config.units.temperature_unit\n return raw_units","def get_converted_si_unit():\n units = request.args.get('units')\n response = ConvertUnit(units).convert()\n return jsonify(response)","def unitpicker(a, llim=0.1):\n udict = {0: 'mol/mol',\n 1: 'mmol/mol',\n 2: '$\\mu$mol/mol',\n 3: 'nmol/mol',\n 4: 'pmol/mol',\n 5: 'fmol/mol'}\n a = abs(a)\n n = 0\n if a < llim:\n while a < llim:\n a *= 1000\n n += 1\n return float(1000**n), udict[n]","def _get_unit_factor(self, unit: str) -> np.ndarray:\n\n unit_factors = {\n 'vx': np.array((1, 1, 1)),\n 'nm': np.array(self.parameters.scale),\n 'um': np.array(self.parameters.scale)/1000\n }\n assert unit in unit_factors.keys(), 'Invalid unit'\n unit_factor = unit_factors[unit]\n\n return unit_factor","def to(self, unit, equivalencies=[]):\n\n return super(BaseOneDSpectrum, self).to(unit, equivalencies, freq=None)","def convert_units(src_unit: Union[str, float], tgt_unit: Union[str, float]):\n return _parse_unit(src_unit) / _parse_unit(tgt_unit)","def _to(\n value: Union[\"Value\", \"ValueArray\"], units: Union[Unit, str], inplace: bool\n) -> Any:\n if value.units == units:\n return value\n\n if value.units is None:\n raise RuntimeError(\"Cannot convert with units=None\")\n\n try:\n units = next(\n imp_unit\n for imp_unit in value.implemented_units\n if units.lower() in imp_unit.aliases\n )\n\n except StopIteration:\n raise TypeError(\n f\"No viable unit conversion from {value.units} -> {units}\"\n )\n\n if not (isinstance(value, Value) or isinstance(value, ValueArray)):\n raise ValueError(\n f\"Cannot convert {value} to new units. Must be one of\"\n f\" Value of ValueArray\"\n )\n\n if isinstance(value, Value) and inplace:\n raise ValueError(\n \"Cannot modify a value inplace as floats are immutable\"\n )\n\n # Convert to the base unit, then to the new units\n c = float(units.conversion / value.units.conversion)\n\n new_value = value if inplace else value.copy()\n new_value *= c\n new_value.units = units\n\n return None if inplace else new_value","def convert_energy_2_internal_u(self,val):\n units = self.current_units[\"energy\"]\n cfact = conversion_facs_energy[self.current_units[\"energy\"]]\n \n # special handling for nano meters\n if units == \"nm\":\n # zero is interpretted as zero energy\n try:\n ret = numpy.zeros(val.shape, dtype=val.dtype)\n ret[val!=0.0] = 1.0/val[val!=0]\n return ret/cfact\n except: \n return (1.0/val)/cfact\n #if val == 0.0:\n # return 0.0\n #return (1.0/val)/cfact\n else:\n return val*cfact","def convert_path_units(self, path_to_conv):\n\n converted_path = copy.deepcopy(path_to_conv) # TODO: figure out if this is the right way to do this- I have not yet understood how data should be handled here\n\n for i, coord in enumerate(converted_path):\n converted_path[i][0] = coord[0] / self.units_in_meter\n converted_path[i][1] = coord[1] / self.units_in_meter\n converted_path[i][2] = coord[2] / self.units_in_meter\n\n return converted_path","def get_units(self):\n return str(self._modeler.GetModelUnits())","def units(inventory):\n return inventory.reduce(convert.get_units)","def unit_of_measurement(self):\n return self.values.primary.units","def units(self):\n return self._units","def units(self):\n return self._units","def unit(x,convert_to=\"px\",from_unit=\"px\"):\n assert convert_to in UNITS, \"Cannot convert to unknown unit: %s\" % convert_to\n assert from_unit in UNITS, \"Cannot from unknown unit: %s\" % from_unit\n return float(x)*UNITS[convert_to]/UNITS[from_unit]","def _parse_units(self, model, comp, node):\n node = dom_child(node, 'unitDefinition')\n while node:\n name = node.getAttribute('id')\n self.log('Parsing unit definition for \"' + name + '\".')\n unit = myokit.units.dimensionless\n node2 = dom_child(node, 'listOfUnits')\n node2 = dom_child(node2, 'unit')\n while node2:\n kind = str(node2.getAttribute('kind')).strip()\n u2 = self._convert_unit(kind)\n if node2.hasAttribute('multiplier'):\n m = float(node2.getAttribute('multiplier'))\n else:\n m = 1.0\n if node2.hasAttribute('scale'):\n m *= 10 ** float(node2.getAttribute('scale'))\n u2 *= m\n if node2.hasAttribute('exponent'):\n u2 **= float(node2.getAttribute('exponent'))\n unit *= u2\n node2 = dom_next(node2, 'unit')\n self.units[name] = unit\n node = dom_next(node, 'unitDefinition')","def convert_energy_2_current_u(self,val):\n units = self.current_units[\"energy\"]\n cfact = conversion_facs_energy[units]\n \n # special handling for nanometers\n if units == \"nm\":\n # zero is interpretted as zero energy\n try:\n ret = numpy.zeros(val.shape, dtype=val.dtype)\n ret[val!=0.0] = 1.0/val[val!=0]\n return ret/cfact\n except: \n return (1.0/val)/cfact\n else:\n return val/cfact","def extendedConvert(self):\r\n devId = str(self.deviceId)\r\n if(devId == '28' or devId == '29'):\r\n answers = []\r\n #just add the counter value\r\n answers.append(self.fields[1])\r\n #find the engineering units converter\r\n enum = self.fields[0] & 0x3F\r\n #look up the scale and offset for that eeu\r\n eeu = self._eeumaps[str(enum)]\r\n self.eeu1 = eeu\r\n print('eeu:' + str(eeu))\r\n #convert from twos complement and adjust by scale/offset\r\n val = (self.convertSigned16(self.fields[2]) * eeu[1]) + eeu[0]\r\n answers.append(val)\r\n #reset fields to hold the new answers\r\n self.fields = answers\r\n self.units = [self.UNITS_COUNT, eeu[2]]\r\n elif(devId == '53' or devId == '54'):\r\n #strip off the first part of the answer which is the last part of the\r\n #serial number\r\n answers = [self.fields[1]]\r\n self.fields = answers\r\n elif(devId == '75' or devId == '76'):\r\n answers = []\r\n #find out the number of I/O points\r\n pointCount = self.fields[0] & 3\r\n #find out engineering units for 1st I/O\r\n enum = self.fields[1] & 0x3F\r\n eeu = self._eeumaps[str(enum)]\r\n self.eeu1 = eeu\r\n #new value = old value * scale + offset\r\n val = (self.convertSigned16(self.fields[3]) * eeu[1]) + eeu[0]\r\n answers.append(val)\r\n self.units = [eeu[2]]\r\n #see if there's two\r\n if pointCount == 2:\r\n #find out engineering units for 2nd I/O\r\n #and off first two bits\r\n enum = self.fields[0] >> 2\r\n eeu = self._eeumaps[str(enum)]\r\n self.eeu2 = eeu\r\n val = (self.convertSigned16(self.fields[2]) * eeu[1]) + eeu[0]\r\n answers.append(val)\r\n self.units.append(eeu[2])\r\n else:\r\n self.eeu2 = []\r\n #reset fields to hold the new answers\r\n self.fields = answers\r\n\r\n return","def unit_of_measurement(self):\n return self._units","def unit_of_measurement(self):\n\n if self._sensor_class == DEVICE_CLASS_TEMPERATURE:\n return TEMP_CELSIUS\n\n elif self._sensor_class == DEVICE_CLASS_HUMIDITY:\n return '%'","def unit_of_measurement(self):\n return self._metadata[1]","def raw_units(self) -> str:\n if self._node.uom == 'F':\n return TEMP_FAHRENHEIT\n if self._node.uom == 'C':\n return TEMP_CELSIUS\n return self._node.uom","def parse_unit(self, unitelem) -> Unit:\n u = Unit()\n\n u.unitid = unitelem.attrib['id'].strip()\n div = unitelem.find('{*}divide')\n if div is not None:\n nom = div.find('{*}unitNumerator').find('{*}measure')\n denom = div.find('{*}unitDenominator').find('{*}measure')\n u.nom = re.sub('.*:', '', nom.text).lower()\n u.denom = re.sub('.*:', '', denom.text).lower()\n else:\n m = unitelem.find('{*}measure')\n u.nom = re.sub('.*:', '', m.text).lower()\n\n return u","def test_change_units(self):\n s = State(\"water\", T=Q_(100, \"degC\"), p=Q_(1.0, \"atm\"), units=\"EE\")\n assert s.units == \"EE\"\n s.units = \"SI\"\n assert s.units == \"SI\"\n assert s.cv.units == \"kilojoule / kelvin / kilogram\"\n assert s.cp.units == \"kilojoule / kelvin / kilogram\"\n assert s.s.units == \"kilojoule / kelvin / kilogram\"\n assert s.h.units == \"kilojoule / kilogram\"\n assert s.T.units == \"degree_Celsius\"\n assert s.u.units == \"kilojoule / kilogram\"\n assert s.v.units == \"meter ** 3 / kilogram\"\n assert s.p.units == \"bar\"","def unit_of_measurement(self):\n return self.sensor_type[\"unit\"]","def to_inch(self):\r\n if self.units != 'inch':\r\n self.units = 'inch'\r\n for statement in self.statements:\r\n statement.to_inch()\r\n for tool in iter(self.tools.values()):\r\n tool.to_inch()\r\n for primitive in self.primitives:\r\n primitive.to_inch()\r\n for hit in self.hits:\r\n hit.to_inch()","def convert_volume(self, event):\n try:\n #Compare other unit to one unit(cubic decimeters)\n current_value, current_unit = float(\"0\" + str(self.v.get())), self.dropdown.get()\n unit_comp = {\"acre foot\": 1233481.837548, \"barrels\": 158.987295, \"bushels(UK)\": 36.36872, \"bushels(US)\": 35.23907, \"centiliters\": 0.01, \"cubic centimeters\": 0.001, \"cubic decameters\": 1000000.0, \"cubic decimeters\": 1.0, \"cubic feet\": 28.316847, \"cubic inches\": 0.016387, \"cubic kilometers\": 1000000000000.0, \"cubic meters\": 1000.0, \"cubic mile\": 4168181825000.0, \"cubic millimeters\": 1e-06, \"cubic yards\": 764.554858, \"cups\": 0.236588, \"deciliters\": 0.1, \"dram\": 0.003697, \"dram(imperial)\": 0.003552, \"fluid ounces(US)\": 0.029574, \"fluid ounces(imperial)\": 0.028413, \"gallons(US,dry)\": 4.404884, \"gallons(US,liquid)\": 3.785412, \"gallons(imperial)\": 4.54609, \"gill(US)\": 0.118294, \"gill(imperial)\": 0.142065, \"liters\": 1.0, \"liters(1901-1964)\": 1.000028, \"microliters\": 1e-06, \"milliliters\": 0.001, \"nanoliters\": 1e-09, \"picoliters\": 1e-12, \"pints(US,dry)\": 0.55061, \"pints(US,liquid)\": 0.473176, \"pints(imperial)\": 0.568261, \"quarts(UK,dry)\": 1.101221, \"quarts(US,liquid)\": 0.946353, \"quarts(imperial)\": 1.136523, \"table spoons\": 0.014787, \"tea spoons\": 0.004929}\n value_comp, printer = current_value * unit_comp[current_unit], \"\"\n unit_list = sorted(unit_comp.keys())\n unit_list.remove(current_unit)\n for unit in unit_list:\n printer += \"To %s \" % unit + \" \" * (max([len(i) for i in unit_list]) - len(unit)) + str(value_comp / unit_comp[unit]) + [\"\", \"\\n\"][unit_list[-1] != unit]\n except ValueError: #In case user enter the other type of value, not Int or Float\n printer = \"Value is invalid.\"\n self.print_text(printer)","def units(self, key):\n \n # Strip any operators\n _, key = get_operator(key)\n \n # Fill out aliases \n if key in component_from_alias:\n key = component_from_alias[key]\n elif key == 'E':\n key = 'electricField'\n elif key == 'B':\n key = 'magneticField' \n \n return pg_units(key)","def unit_array(self, values):\n self._data_array.values = values\n self._units = self._data_array.attrs['units'] = str(values.units)","def _get_units_object(self, units):\n if isinstance(units, cellml_units):\n # We're done\n pass\n else:\n units = amara_parse_cellml(unicode(units))\n assert isinstance(units, cellml_units)\n return units","def get_units(self, obj: Dimension) -> [Unit]:\n try:\n return obj.units()\n except KeyError as e:\n logging.error(str(e))\n return []","def raw_unit_of_measurement(self) -> str:\n if len(self._node.uom) == 1:\n if self._node.uom[0] in UOM_FRIENDLY_NAME:\n friendly_name = UOM_FRIENDLY_NAME.get(self._node.uom[0])\n if friendly_name == TEMP_CELSIUS or \\\n friendly_name == TEMP_FAHRENHEIT:\n friendly_name = self.hass.config.units.temperature_unit\n return friendly_name\n else:\n return self._node.uom[0]\n else:\n return None","def convert_same_units(self):\n # Convert pumping rate data\n pump_units = \"%s3/%s\" % (self.len_units, self.time_units)\n flag = _units.validate_units(pump_units)\n if flag == 2:\n self.pumprate.convert_units(self.time_units, pump_units)\n self.pump_units = pump_units","def __convert_to_devunit(self, value, in_devunit=False):\r\n if not in_devunit:\r\n value *= self.DEVUNIT_RATIO\r\n elif not isinstance(value, int):\r\n self.print_msg((\"Warning: non-integer value ({}) is given \"\r\n + \"in device unit.\").format(value))\r\n return int(value)","def SBMLInferUnitsConverter_init():\n return _libsbml.SBMLInferUnitsConverter_init()","def convert_unit(self, time_unit):\r\n\r\n self.time_unit = time_unit\r\n self._conversion_factor = time_unit_conversion[time_unit]","def _get_wavelength_attrs_with_units(self, attrname, units='AA'):\n attr = self._lick[attrname]\n if self.wavelength_unit is not None:\n if units is None:\n return attr * Unit(self.wavelength_unit)\n else:\n return (attr * Unit(self.wavelength_unit)).to(units)\n else:\n return attr","def assign_unit(self):\n self.units = {}\n for unit in RADIAL_UNITS:\n if unit.REPR == \"2th_deg\":\n self.units[unit] = self.tth_deg\n elif unit.REPR == \"2th_rad\":\n self.units[unit] = self.tth_rad\n elif unit.REPR == \"q_nm^-1\":\n self.units[unit] = self.q_nm\n elif unit.REPR == \"q_A^-1\":\n self.units[unit] = self.q_A\n elif unit.REPR == \"r_mm\":\n self.units[unit] = self.r_mm\n else:\n logger.warning(\"Unit unknown to GUI %s\" % unit)","def cbToEngUnits( BoardNum, Range, DataVal, EngUnits = 0.0 ):\n EngUnits = ctypes.c_float( EngUnits )\n CHK( cbw.cbToEngUnits( BoardNum, Range, DataVal, byref( EngUnits ) ) )\n return EngUnits.value"],"string":"[\n \"def convert_units(array, in_units=\\\"None\\\"):\\n if in_units == \\\"None\\\" or in_units is None:\\n return array\\n else:\\n raise Exception(\\\"Unsupported unit for bispectrum descriptors.\\\")\",\n \"def convert_units(self):\\n for prod in (\\\"ier\\\", \\\"ier_inc_rain\\\"):\\n self.data[prod].data[:] /= 1e6\",\n \"def convert_units(self, units):\\n self.unit_array = self.unit_array.to(units)\",\n \"def convert_units(unt, origunits):\\n if unt[0:3] == origunits[0:3] | unt[0:3] == 'ori':\\n units = origunits\\n convf = 1\\n else:\\n if 'fee' == unt[(((0:3 -1) -1) -1)]:\\n if origunits[0:3] == 'met':\\n units = 'feet'\\n convf = 3.2808399\\n else:\\n units = origunits\\n convf = 1\\n else:\\n if 'met' == unt[(((0:3 -1) -1) -1)]:\\n if origunits[0:3] == 'fee':\\n units = 'meters'\\n convf = 0.3048\\n else:\\n units = origunits\\n convf = 1\\n else:\\n if 'm/s' == unt[(((0:3 -1) -1) -1)]:\\n if origunits[0:3] == 'kno':\\n units = 'meters/sec'\\n convf = 0.51444444\\n else:\\n units = origunits\\n convf = 1\\n else:\\n if 'kno' == unt[(((0:3 -1) -1) -1)]:\\n if origunits[0:3] == 'm/s':\\n units = 'knots'\\n convf = 1.9438445\\n else:\\n units = origunits\\n convf = 1\\n else:\\n error('Unknown units')\\n #\\n return units, convf\",\n \"def convert(self):\\n return _libsbml.SBMLUnitsConverter_convert(self)\",\n \"def convert(self):\\n return _libsbml.SBMLInferUnitsConverter_convert(self)\",\n \"def convert_units(data, hdr, conv_to = \\\"surf_br\\\"):\\n \\n data_unit = hdr[\\\"SIGUNIT\\\"]\\n \\n if \\\"Jy/pix\\\" in data_unit:\\n # pixel size in rad\\n px_x = abs(hdr[\\\"CDELT1\\\"])*2*np.pi/360\\n px_y = abs(hdr[\\\"CDELT2\\\"])*2*np.pi/360\\n \\n #pixel size in arcsec\\n \\n px_x = abs(hdr[\\\"CDELT1\\\"])*3600\\n px_y = abs(hdr[\\\"CDELT2\\\"])*3600\\n conversion_factor = 1000/(px_x*px_y)\\n \\n unit_label = \\\"mJy/arcsec^2\\\"\\n \\n #in case we want to convert to units flux, we need to multiply by the size (in steradians) of a pixel.\\n if conv_to == \\\"flux\\\":\\n conversion_factor*=abs(hdr[\\\"CDELT1\\\"])*abs(hdr[\\\"CDELT2\\\"])*(2*np.pi/360)**2\\n unit_label = \\\"mJy\\\"\\n \\n data *= conversion_factor\\n hdr[\\\"SIGUNIT\\\"] = unit_label\\n else:\\n print(\\\"\\\\t[WARNING]\\\\t \\\"+data_unit+\\\" conversion not yet implemented. No conversion performed.\\\")\\n \\n return data, hdr\",\n \"def convertUnits(self, varname, arr):\\n if varname == \\\"SPDQ\\\" or varname == \\\"PHQ\\\":\\n return arr*2.5e6/1000.\\n return arr\",\n \"def convert_to_unit(self, data, unit):\\n\\n res = OrderedDict()\\n\\n # Loop over data and overwrite\\n for ch in data:\\n _idx = self.channels.index(ch)\\n # Get data, scale and type of channel\\n val, scale, _type = data[ch], self.daq_setup['devices']['adc']['ro_scales'][_idx], self.daq_setup['devices']['adc']['types'][_idx]\\n # Adjust scale in case we're looking at SEM's sum signal; in this case current is multiplied by factor of 4\\n scale *= 1 if _type != 'sem_sum' else 4\\n\\n res[ch] = val / 5.0 * scale * 1e-9 if unit == 'A' else val * 5.0 / 1e-9 / scale\\n\\n return res\",\n \"def resolve_units(obj, _):\\n return obj.units.decode()\",\n \"def units_to_fits(unit):\\n if unit is None:\\n unit = Unit('')\\n return unit.to_string(\\\"fits\\\").upper()\",\n \"def convert_units(data, units):\\n # Build the dictionary of units conversions\\n convert = {'m' : [1.0, 0., 'm'], \\n 'meter' : [1.0, 0., 'm'], \\n 'deg C' : [1.0, 273.15, 'K'], \\n 'Celsius' : [1.0, 273.15, 'K'], \\n 'K' : [1.0, 0., 'K'],\\n 'db' : [1.e4, 101325., 'Pa'], \\n 'Pa' : [1.0, 0., 'Pa'],\\n 'mg/m^3': [1.e-6, 0., 'kg/m^3'], \\n 'S/m': [1.0, 0., 'S/m'],\\n 'mS/m' : [1.e-3, 0., 'S/m'],\\n 'psu': [1.0, 0., 'psu'], \\n 'salinity': [1.0, 0., 'psu'], \\n 'kg/m^3': [1.0, 0., 'kg/m^3'], \\n 'kilogram meter-3': [1.0, 0., 'kg/m^3'], \\n 'm/s': [1.0, 0., 'm/s'], \\n 'mg/l': [1.e-3, 0., 'kg/m^3'],\\n 'meter second-1' : [1.0, 0., 'm/s'],\\n 'm.s-1' : [1.0, 0., 'm/s'],\\n 'pH units' : [1.0, 0., 'pH units'],\\n 'MPa' : [1.e6, 0., 'Pa'],\\n '--' : [1.0, 0., '--'],\\n 'mD' : [9.869233e-16, 0., 'm^2'],\\n 'um' : [1.e-6, 0., 'm'],\\n 'm/s 1e-9' : [1.e-9, 0., 'm/s'],\\n 'm/s 1e-7' : [1.e-7, 0., 'm/s'],\\n 'wt.%' : [10., 0., 'psu'],\\n '10^-15 m^2' : [1.e-15, 0., 'm^2'],\\n 'm^2' : [1., 0., 'm^2'],\\n 'kg/m^2/year' : [3.168808781402895e-08, 0., 'kg/m^2/s'] \\n } \\n \\n # Make sure the data are a numpy array and the units are a list\\n if isinstance(data, float) or isinstance(data, int):\\n data = np.array([data])\\n if isinstance(data, list):\\n data = np.array(data)\\n if isinstance(units, str) or isinstance(units, unicode):\\n units = [units]\\n if units == None:\\n units = ['']\\n \\n # Make sure you can slice through the columns: must be two-dimensional\\n sh = data.shape\\n data = np.atleast_2d(data)\\n \\n # Allow conversion of a row of data if all of the same unit\\n if len(units) == 1 and data.shape[1] > 1:\\n data = data.transpose()\\n \\n # Create an emtpy array to hold the output\\n out_data = np.zeros(data.shape)\\n out_units = []\\n \\n # Convert the units\\n for i in range(len(units)):\\n try:\\n out_data[:,i] = data[:,i] * convert[units[i]][0] + \\\\\\n convert[units[i]][1]\\n out_units += [convert[units[i]][2]]\\n except KeyError:\\n print('Do not know how to convert %s to mks units' % units[i])\\n print('Continuing without converting these units...')\\n out_data[:,i] = data[:,i]\\n out_units += units[i]\\n \\n # Return the converted data in the original shape\\n out_data = np.reshape(out_data, sh, 'C')\\n return (out_data, out_units)\",\n \"def get_units(self):\\r\\n msg = struct.pack('>2B', 56, 14)\\r\\n response = self.query(msg)\\r\\n\\r\\n if response[1] == 2:\\r\\n units = 'A'\\r\\n to_nm_multiplier = 1 / 10\\r\\n elif response[1] == 1:\\r\\n units = 'nm'\\r\\n to_nm_multiplier = 1\\r\\n elif response[1] == 0:\\r\\n units = 'um'\\r\\n to_nm_multiplier = 1000\\r\\n else:\\r\\n raise ValueError('Units not recognised.')\\r\\n\\r\\n # Save results locally too for quick re-use\\r\\n self._current_units = units\\r\\n self._current_to_nm_multiplier = to_nm_multiplier\\r\\n\\r\\n return units, to_nm_multiplier\",\n \"def __convert_to_mm(self, value, in_devunit=True):\\r\\n if in_devunit:\\r\\n value /= self.DEVUNIT_RATIO\\r\\n return value\",\n \"def _convert_value(self, value, unit, axis):\\n if hasattr(value, 'units'):\\n return value.to(unit).magnitude\\n else:\\n return self._reg.Quantity(value, axis.get_units()).to(unit).magnitude\",\n \"def test_convert_compatible_units(self):\\n result = convert_units(self.arr, 'degC')\\n expected_data = np.array([[-273.15, -272.15], [-271.15, -270.15]])\\n expected_units = cf_units.Unit('degC')\\n self.assertEquals(result.units, expected_units)\\n self.assertArrayEqual(result.data, expected_data)\",\n \"def useUnits():\",\n \"def to_unit(self, unit):\\n unit = _find_unit(unit)\\n self.value = _convert_value(self.value, self.unit, unit)\\n self.unit = unit\",\n \"def extract_specs(self):\\n vDeflection_unit = \\\"lcd-info.{}.conversion-set.conversion.force.scaling.unit.unit\\\".format(\\n self.channel_numbers[\\\"vDeflection\\\"])\\n self.units[\\\"vDeflection\\\"] = self.general[vDeflection_unit]\\n\\n height_unit = \\\"lcd-info.{}.conversion-set.conversion.nominal.scaling.unit.unit\\\".format(\\n self.channel_numbers[\\\"height\\\"])\\n self.units[\\\"height\\\"] = self.general[height_unit]\",\n \"def unit_converter(val, from_u, to_u):\\n\\tconverter = {'b':0, 'k':1, 'm':2, 'g':3, 't':4}\\n\\tif converter[from_u] < converter[to_u]:\\n\\t\\tval = float(val)\\n\\t\\tfor _ in range(converter[to_u] - converter[from_u]):\\n\\t\\t\\tval = val/1024\\n\\telse:\\n\\t\\tfor _ in range(converter[from_u] - converter[to_u]):\\n\\t\\t\\tval = val * 1024\\n\\t\\t\\t\\n\\treturn val\",\n \"def normalize_units(data):\\n for obj in data:\\n obj['unit'] = normalize_units_function(obj.get('unit', ''))\\n # for param in ds.get('parameters', {}).values():\\n # if 'unit' in param:\\n # param['unit'] = normalize_units_function(param['unit'])\\n return data\",\n \"def _convert_unit(self, unit):\\n if unit in self.units:\\n return self.units[unit]\\n elif unit in unit_map:\\n return unit_map[unit]\\n else:\\n raise SBMLError('Unit not recognized: ' + str(unit))\",\n \"def _get_units(self):\\n #assert self.ser.isOpen()\\n\\n self.serial_connection.write('UNI' + self.CR + self.LF)\\n acknowledgement = self.serial_connection.readline()\\n self._check_acknowledgement(acknowledgement)\\n\\n self.serial_connection.write(self.ENQ)\\n unit = self.MEASUREMENT_UNITS[self.serial_connection.readline().rstrip(self.LF).rstrip(self.CR)]\\n\\n self.serial_connection.write(self.CR + self.LF)\\n\\n return unit\",\n \"def to_axis_units(self, label, vals):\\n if label in ['Hmolar', 'Smolar', 'Umolar', 'Dmolar', 'P']:\\n return vals / 1000\\n elif label in ['T']:\\n return vals\\n else:\\n raise ValueError(label)\",\n \"def fits_to_units(unit_str):\\n unit_lookup = {\\n 'meters': 'm',\\n 'meter': 'm',\\n 'degrees': 'deg',\\n 'degree': 'deg',\\n 'hz': 'Hz',\\n 'hertz': 'Hz',\\n 'second': 's',\\n 'sec': 's',\\n 'secs': 's',\\n 'days': 'd',\\n 'day': 'd',\\n 'steradians': 'sr',\\n 'steradian': 'sr',\\n 'radians': 'rad',\\n 'radian': 'rad',\\n 'jy': 'Jy',\\n 'au': 'AU',\\n }\\n\\n try:\\n new_units = \\\"\\\"\\n\\n if unit_str is None:\\n unit_str = ''\\n unit_str = unit_str.lower()\\n unit_list = unit_str.split(\\\"/\\\")\\n\\n for uu in unit_list:\\n if uu.endswith(\\\"s\\\") and len(uu) > 1:\\n uu = uu[:-1]\\n corrected_unit = unit_lookup.get(uu, uu)\\n new_units += corrected_unit\\n new_units += \\\" / \\\"\\n new_units = new_units[:-3]\\n unit = Unit(new_units)\\n return unit\\n\\n except ValueError:\\n warnings.warn(\\\"Unknown unit: %s\\\" % new_units, UnitWarning)\\n return UnrecognizedUnit(unit_str)\",\n \"def SBMLUnitsConverter_init():\\n return _libsbml.SBMLUnitsConverter_init()\",\n \"def get_units(self,):\\n self.UNITS = {'pressure':'Pa',}\\n return\",\n \"def _d_converter(self):\\n units = {'um':1e-6, 'mm':1e-3, 'inch':2.54e-2, 'in':2.54e-2,\\\\\\n 'micron':1e-6, 'mil':2.54e-5, 'm':1.0}\\n for i in self.stack:\\n i.thickness = i.thickness*units[i.units]\\n return\",\n \"def convertUnit(*args, fromUnit: AnyStr=\\\"\\\", toUnit: AnyStr=\\\"\\\", **kwargs)->float:\\n pass\",\n \"def convert(self, value, units, newunits):\\n return value * self._units[units] / self._units[newunits]\",\n \"def convertToSpectroGram(self):\",\n \"def test_unit_conversion(self):\\n self.cube_uv_down.convert_units(\\\"kW m-2\\\")\\n scale_factor = 1.0\\n expected = np.full_like(\\n self.cube_uv_down.data, dtype=np.float32, fill_value=0.1\\n )\\n result = calculate_uv_index(self.cube_uv_down, scale_factor)\\n self.assertArrayEqual(result.data, expected)\",\n \"def to_units(number):\\n unit = 0\\n while number >= 1024.:\\n unit += 1\\n number = number / 1024.\\n if unit == len(UNITS) - 1:\\n break\\n if unit:\\n return '%.2f%s' % (number, UNITS[unit])\\n return '%d' % number\",\n \"def convert_units(celsius_value, units):\\n if units == 0:\\n return celsius_value\\n if units == 1:\\n return celsius_value * 1.8 + 32\\n return celsius_value + 273.15\",\n \"def convert(value, units: UnitLike, registry: unyt.UnitRegistry = None):\\n return process_unit_input(value, units, convert=True, registry=registry).v\",\n \"def _get_units(self, q) -> unyt.Unit:\\n try:\\n units = q.units\\n except AttributeError:\\n units = unyt.dimensionless\\n return unyt.Unit(units, registry=self.registry)\",\n \"def units(self):\\n pass\",\n \"def convert_units(self, time_units=None, len_units=None):\\n in_time = self.time_units\\n # Check new time units\\n if time_units is None:\\n time_units = in_time\\n flag = _units.validate_units(time_units)\\n if flag == -1:\\n raise ValueError('Bad time units input {}'.format(time_units))\\n # Check new length units\\n in_len = self.len_units\\n if len_units is None:\\n len_units = in_len\\n flag = _units.validate_units(len_units)\\n if flag == -1:\\n raise ValueError('Bad length units input {}'.format(len_units))\\n # Convert parameters units\\n for key, value in self.parameters.items():\\n if type(value) in [int, float]:\\n self.parameters[key] = _units.units_conversion(value, in_len, len_units)\\n # Convert drawdown data\\n self.drawdown.convert_units(time_units, len_units)\\n # Convert associate data units\\n for i in range(self.data_count()):\\n if self.data[i].dtype == 1: # drawdown units\\n data_units = len_units\\n elif self.data[i].dtype == 2: # first derivative units\\n data_units = len_units + \\\"/\\\" + time_units\\n elif self.data[i].dtype == 3: # second derivative units\\n data_units = len_units + \\\"/\\\" + time_units + \\\"2\\\"\\n self.data[i].convert_units(time_units, data_units)\\n self.len_units = len_units\\n self.time_units = time_units\\n # End Function\",\n \"def convert_F_units(F, lbda, in_unit='cgs', out_unit='si'):\\n\\n if in_unit == 'cgs':\\n new_F = (F*1e23*np.power(lbda,2))/(c.c.value*1e6) # convert to jy\\n elif in_unit == 'cgsA':\\n new_F = (F*1e27*np.power(lbda,2))/(c.c.value*1e6) # convert to jy\\n elif in_unit == 'si':\\n new_F = (F*1e26*np.power(lbda,2))/(c.c.value*1e6) # convert to jy\\n elif in_unit == \\\"jy\\\":\\n new_F=F\\n else:\\n msg = \\\"in_unit not recognized, try either 'cgs', 'si' or 'jy'.\\\"\\n raise TypeError(msg) \\n if out_unit == 'jy':\\n return new_F\\n elif out_unit == 'cgs':\\n return new_F*1e-23*c.c.value*1e6/np.power(lbda,2)\\n elif out_unit == 'si':\\n return new_F*1e-26*c.c.value*1e6/np.power(lbda,2)\\n else:\\n msg = \\\"out_unit not recognized, try either 'cgs', 'si' or 'jy'.\\\"\\n raise TypeError(msg)\",\n \"def convert_wave_to_units(self, wave):\\n return [self.convert_point_to_units(i) for i in wave]\",\n \"def units_to_pixels(self,units_):\\n if type(units_) == str and units_.lower() in [\\\"fwhm\\\",\\\"psf\\\"]:\\n units_ = self.fwhm\\n\\n return super(Image, self).units_to_pixels(units_, target=self.target)\",\n \"def convert_unit(size_in_bytes, unit):\\n if unit == 'KB':\\n return size_in_bytes/1024\\n elif unit == 'MB':\\n return size_in_bytes/(1024*1024)\\n elif unit == 'GB':\\n return size_in_bytes/(1024*1024*1024)\\n else:\\n return size_in_bytes\",\n \"def units(self, x):\\n u = ''.join([chr(d) for d in self[x]['units'][:]])\\n if (u in ['n/a']) and (x in ['latitude', 'longitude']):\\n u = 'radian' # assume radians\\n return u\",\n \"def native_unit_of_measurement(self) -> str:\\n return f\\\"{CURRENCY_CENT}/{UnitOfVolume.LITERS}\\\"\",\n \"def _fix_units(cube, definition):\\n\\n if cube.var_name != 'pr':\\n cube.convert_units(definition.units)\",\n \"def convert(obj, unit, axis):\\r\\n return obj\",\n \"def infer_original_units(self, dimensions):\\n dimensions = units.Unit(dimensions)\\n d = dimensions.dimensional_project(\\n self._file_units_system + [\\\"a\\\", \\\"h\\\"])\\n new_unit = reduce(lambda x, y: x * y, [\\n a ** b for a, b in zip(self._file_units_system, d)])\\n return new_unit\",\n \"def unicode_of_unit(quant):\\n return quant.dimensionality.unicode\",\n \"def unit_of_measurement(self):\\n if self.values.primary.units == \\\"C\\\":\\n return TEMP_CELSIUS\\n if self.values.primary.units == \\\"F\\\":\\n return TEMP_FAHRENHEIT\\n\\n return self.values.primary.units\",\n \"def _get_units(self, name):\\n meta = self._abs2meta\\n\\n if name in meta:\\n return meta[name]['units']\\n\\n proms = self._prom2abs\\n\\n if name in proms['output']:\\n abs_name = proms['output'][name][0]\\n return meta[abs_name]['units']\\n\\n elif name in proms['input']:\\n if len(proms['input'][name]) > 1:\\n # The promoted name maps to multiple absolute names, require absolute name.\\n msg = \\\"Can't get units for the promoted name '%s' because it refers to \\\" + \\\\\\n \\\"multiple inputs: %s. Access the units using an absolute path name.\\\"\\n raise RuntimeError(msg % (name, str(proms['input'][name])))\\n\\n abs_name = proms['input'][name][0]\\n return meta[abs_name]['units']\\n\\n raise KeyError('Variable name \\\"{}\\\" not found.'.format(name))\",\n \"def unit_of_measurement(self):\\n set_req = self.gateway.const.SetReq\\n unit_map = {\\n set_req.V_TEMP: (TEMP_CELSIUS\\n if self.gateway.metric else TEMP_FAHRENHEIT),\\n set_req.V_HUM: '%',\\n set_req.V_DIMMER: '%',\\n set_req.V_LIGHT_LEVEL: '%',\\n set_req.V_WEIGHT: 'kg',\\n set_req.V_DISTANCE: 'm',\\n set_req.V_IMPEDANCE: 'ohm',\\n set_req.V_WATT: 'W',\\n set_req.V_KWH: 'kWh',\\n set_req.V_FLOW: 'm',\\n set_req.V_VOLUME: 'm3',\\n set_req.V_VOLTAGE: 'V',\\n set_req.V_CURRENT: 'A',\\n }\\n if float(self.gateway.protocol_version) >= 1.5:\\n if set_req.V_UNIT_PREFIX in self._values:\\n return self._values[\\n set_req.V_UNIT_PREFIX]\\n unit_map.update({set_req.V_PERCENTAGE: '%'})\\n if float(self.gateway.protocol_version) >= 2.0:\\n unit_map.update({\\n set_req.V_ORP: 'mV',\\n set_req.V_EC: 'μS/cm',\\n set_req.V_VAR: 'var',\\n set_req.V_VA: 'VA',\\n })\\n return unit_map.get(self.value_type)\",\n \"def get_unit(scale):\\n scale2unit = { 1e-9: 'nm',\\n 1e-6: u'\\\\N{MICRO SIGN}m', #or hex id (lookup): u'\\\\u00B5'\\n 1e-3: 'mm',\\n 0.01: 'cm',\\n 0.1:'dm',\\n 1:'m',\\n 1000:'km',\\n # time\\n 8.6400e4:'day',\\n 3.1536e7:'yr',\\n 3.1536e10:'ka',\\n 3.1536e13:'Ma',\\n #Pressure\\n 1e9: 'GPa',\\n 1e6: 'MPa',\\n }\\n return scale2unit[scale]\",\n \"def _getunits(x):\\n if pb.units.has_units(x):\\n \\n units = x.units\\n \\n else:\\n \\n units = None\\n \\n return units\",\n \"def init():\\n return _libsbml.SBMLUnitsConverter_init()\",\n \"def unit_array(self):\\n return self._data_array.values * units(self._units)\",\n \"def convert(value, unit, axis):\\n converted_value = value\\n if isinstance(unit, str) or isinstance(unit, Unit):\\n unit = (unit,)\\n if isinstance(value, (unyt_array, unyt_quantity)):\\n converted_value = value.to(*unit)\\n else:\\n value_type = type(value)\\n converted_value = []\\n for obj in value:\\n converted_value.append(obj.to(*unit))\\n converted_value = value_type(converted_value)\\n return converted_value\",\n \"def unitsDetector(self, num):\\n try:\\n num = int(num)\\n except:\\n sys.exit('Invalid input! Method only takes ints or floats.')\\n \\n digits = 0\\n while num > 1:\\n num /= 10\\n digits += 1\\n \\n digits -= 1\\n ind = digits // 3\\n units = {3: 'B', 2: 'M', 1: 'K', 0: ''}[ind]\\n \\n return 10 ** (ind * 3), units\",\n \"def convert_frequency_2_internal_u(self,val):\\n return val*conversion_facs_frequency[self.current_units[\\\"frequency\\\"]]\",\n \"def _unyt_array_convert_to_units_no_em(self, units, equivalence=None, **kwargs):\\n units = _sanitize_units_convert(units, self.units.registry)\\n if equivalence is None:\\n new_units = units\\n (conv_factor,\\n offset) = self.units.get_conversion_factor(new_units, self.dtype)\\n\\n self.units = new_units\\n values = self.d\\n # if our dtype is an integer do the following somewhat awkward\\n # dance to change the dtype in-place. We can't use astype\\n # directly because that will create a copy and not update self\\n if self.dtype.kind in (\\\"u\\\", \\\"i\\\"):\\n # create a copy of the original data in floating point\\n # form, it's possible this may lose precision for very\\n # large integers\\n dsize = values.dtype.itemsize\\n new_dtype = \\\"f\\\" + str(dsize)\\n large = LARGE_INPUT.get(dsize, 0)\\n if large and np.any(np.abs(values) > large):\\n warnings.warn(\\n \\\"Overflow encountered while converting to units '%s'\\\" %\\n new_units,\\n RuntimeWarning,\\n stacklevel=2,\\n )\\n float_values = values.astype(new_dtype)\\n # change the dtypes in-place, this does not change the\\n # underlying memory buffer\\n values.dtype = new_dtype\\n self.dtype = new_dtype\\n # actually fill in the new float values now that our\\n # dtype is correct\\n np.copyto(values, float_values)\\n values *= conv_factor\\n\\n if offset:\\n np.subtract(values, offset, values)\\n else:\\n self.convert_to_equivalent(units, equivalence, **kwargs)\",\n \"def convert(self, value, unit, axis):\\n scaled = getattr(value, self.scale)\\n if self.format in YMDHMS_FORMATS:\\n return scaled.mjd\\n elif self.format == \\\"byear_str\\\":\\n return scaled.byear\\n elif self.format == \\\"jyear_str\\\":\\n return scaled.jyear\\n else:\\n return getattr(scaled, self.format)\",\n \"def remove_units(namespace):\\n res = copy(namespace)\\n for label, value in res.__dict__.items():\\n if isinstance(value, pd.Series):\\n value = remove_units_series(value)\\n res.__dict__[label] = magnitude(value)\\n return res\",\n \"def unit_of_measurement(self) -> str:\\n raw_units = self.raw_units\\n\\n if raw_units in [TEMP_CELSIUS, TEMP_FAHRENHEIT]:\\n return self.hass.config.units.temperature_unit\\n return raw_units\",\n \"def get_converted_si_unit():\\n units = request.args.get('units')\\n response = ConvertUnit(units).convert()\\n return jsonify(response)\",\n \"def unitpicker(a, llim=0.1):\\n udict = {0: 'mol/mol',\\n 1: 'mmol/mol',\\n 2: '$\\\\mu$mol/mol',\\n 3: 'nmol/mol',\\n 4: 'pmol/mol',\\n 5: 'fmol/mol'}\\n a = abs(a)\\n n = 0\\n if a < llim:\\n while a < llim:\\n a *= 1000\\n n += 1\\n return float(1000**n), udict[n]\",\n \"def _get_unit_factor(self, unit: str) -> np.ndarray:\\n\\n unit_factors = {\\n 'vx': np.array((1, 1, 1)),\\n 'nm': np.array(self.parameters.scale),\\n 'um': np.array(self.parameters.scale)/1000\\n }\\n assert unit in unit_factors.keys(), 'Invalid unit'\\n unit_factor = unit_factors[unit]\\n\\n return unit_factor\",\n \"def to(self, unit, equivalencies=[]):\\n\\n return super(BaseOneDSpectrum, self).to(unit, equivalencies, freq=None)\",\n \"def convert_units(src_unit: Union[str, float], tgt_unit: Union[str, float]):\\n return _parse_unit(src_unit) / _parse_unit(tgt_unit)\",\n \"def _to(\\n value: Union[\\\"Value\\\", \\\"ValueArray\\\"], units: Union[Unit, str], inplace: bool\\n) -> Any:\\n if value.units == units:\\n return value\\n\\n if value.units is None:\\n raise RuntimeError(\\\"Cannot convert with units=None\\\")\\n\\n try:\\n units = next(\\n imp_unit\\n for imp_unit in value.implemented_units\\n if units.lower() in imp_unit.aliases\\n )\\n\\n except StopIteration:\\n raise TypeError(\\n f\\\"No viable unit conversion from {value.units} -> {units}\\\"\\n )\\n\\n if not (isinstance(value, Value) or isinstance(value, ValueArray)):\\n raise ValueError(\\n f\\\"Cannot convert {value} to new units. Must be one of\\\"\\n f\\\" Value of ValueArray\\\"\\n )\\n\\n if isinstance(value, Value) and inplace:\\n raise ValueError(\\n \\\"Cannot modify a value inplace as floats are immutable\\\"\\n )\\n\\n # Convert to the base unit, then to the new units\\n c = float(units.conversion / value.units.conversion)\\n\\n new_value = value if inplace else value.copy()\\n new_value *= c\\n new_value.units = units\\n\\n return None if inplace else new_value\",\n \"def convert_energy_2_internal_u(self,val):\\n units = self.current_units[\\\"energy\\\"]\\n cfact = conversion_facs_energy[self.current_units[\\\"energy\\\"]]\\n \\n # special handling for nano meters\\n if units == \\\"nm\\\":\\n # zero is interpretted as zero energy\\n try:\\n ret = numpy.zeros(val.shape, dtype=val.dtype)\\n ret[val!=0.0] = 1.0/val[val!=0]\\n return ret/cfact\\n except: \\n return (1.0/val)/cfact\\n #if val == 0.0:\\n # return 0.0\\n #return (1.0/val)/cfact\\n else:\\n return val*cfact\",\n \"def convert_path_units(self, path_to_conv):\\n\\n converted_path = copy.deepcopy(path_to_conv) # TODO: figure out if this is the right way to do this- I have not yet understood how data should be handled here\\n\\n for i, coord in enumerate(converted_path):\\n converted_path[i][0] = coord[0] / self.units_in_meter\\n converted_path[i][1] = coord[1] / self.units_in_meter\\n converted_path[i][2] = coord[2] / self.units_in_meter\\n\\n return converted_path\",\n \"def get_units(self):\\n return str(self._modeler.GetModelUnits())\",\n \"def units(inventory):\\n return inventory.reduce(convert.get_units)\",\n \"def unit_of_measurement(self):\\n return self.values.primary.units\",\n \"def units(self):\\n return self._units\",\n \"def units(self):\\n return self._units\",\n \"def unit(x,convert_to=\\\"px\\\",from_unit=\\\"px\\\"):\\n assert convert_to in UNITS, \\\"Cannot convert to unknown unit: %s\\\" % convert_to\\n assert from_unit in UNITS, \\\"Cannot from unknown unit: %s\\\" % from_unit\\n return float(x)*UNITS[convert_to]/UNITS[from_unit]\",\n \"def _parse_units(self, model, comp, node):\\n node = dom_child(node, 'unitDefinition')\\n while node:\\n name = node.getAttribute('id')\\n self.log('Parsing unit definition for \\\"' + name + '\\\".')\\n unit = myokit.units.dimensionless\\n node2 = dom_child(node, 'listOfUnits')\\n node2 = dom_child(node2, 'unit')\\n while node2:\\n kind = str(node2.getAttribute('kind')).strip()\\n u2 = self._convert_unit(kind)\\n if node2.hasAttribute('multiplier'):\\n m = float(node2.getAttribute('multiplier'))\\n else:\\n m = 1.0\\n if node2.hasAttribute('scale'):\\n m *= 10 ** float(node2.getAttribute('scale'))\\n u2 *= m\\n if node2.hasAttribute('exponent'):\\n u2 **= float(node2.getAttribute('exponent'))\\n unit *= u2\\n node2 = dom_next(node2, 'unit')\\n self.units[name] = unit\\n node = dom_next(node, 'unitDefinition')\",\n \"def convert_energy_2_current_u(self,val):\\n units = self.current_units[\\\"energy\\\"]\\n cfact = conversion_facs_energy[units]\\n \\n # special handling for nanometers\\n if units == \\\"nm\\\":\\n # zero is interpretted as zero energy\\n try:\\n ret = numpy.zeros(val.shape, dtype=val.dtype)\\n ret[val!=0.0] = 1.0/val[val!=0]\\n return ret/cfact\\n except: \\n return (1.0/val)/cfact\\n else:\\n return val/cfact\",\n \"def extendedConvert(self):\\r\\n devId = str(self.deviceId)\\r\\n if(devId == '28' or devId == '29'):\\r\\n answers = []\\r\\n #just add the counter value\\r\\n answers.append(self.fields[1])\\r\\n #find the engineering units converter\\r\\n enum = self.fields[0] & 0x3F\\r\\n #look up the scale and offset for that eeu\\r\\n eeu = self._eeumaps[str(enum)]\\r\\n self.eeu1 = eeu\\r\\n print('eeu:' + str(eeu))\\r\\n #convert from twos complement and adjust by scale/offset\\r\\n val = (self.convertSigned16(self.fields[2]) * eeu[1]) + eeu[0]\\r\\n answers.append(val)\\r\\n #reset fields to hold the new answers\\r\\n self.fields = answers\\r\\n self.units = [self.UNITS_COUNT, eeu[2]]\\r\\n elif(devId == '53' or devId == '54'):\\r\\n #strip off the first part of the answer which is the last part of the\\r\\n #serial number\\r\\n answers = [self.fields[1]]\\r\\n self.fields = answers\\r\\n elif(devId == '75' or devId == '76'):\\r\\n answers = []\\r\\n #find out the number of I/O points\\r\\n pointCount = self.fields[0] & 3\\r\\n #find out engineering units for 1st I/O\\r\\n enum = self.fields[1] & 0x3F\\r\\n eeu = self._eeumaps[str(enum)]\\r\\n self.eeu1 = eeu\\r\\n #new value = old value * scale + offset\\r\\n val = (self.convertSigned16(self.fields[3]) * eeu[1]) + eeu[0]\\r\\n answers.append(val)\\r\\n self.units = [eeu[2]]\\r\\n #see if there's two\\r\\n if pointCount == 2:\\r\\n #find out engineering units for 2nd I/O\\r\\n #and off first two bits\\r\\n enum = self.fields[0] >> 2\\r\\n eeu = self._eeumaps[str(enum)]\\r\\n self.eeu2 = eeu\\r\\n val = (self.convertSigned16(self.fields[2]) * eeu[1]) + eeu[0]\\r\\n answers.append(val)\\r\\n self.units.append(eeu[2])\\r\\n else:\\r\\n self.eeu2 = []\\r\\n #reset fields to hold the new answers\\r\\n self.fields = answers\\r\\n\\r\\n return\",\n \"def unit_of_measurement(self):\\n return self._units\",\n \"def unit_of_measurement(self):\\n\\n if self._sensor_class == DEVICE_CLASS_TEMPERATURE:\\n return TEMP_CELSIUS\\n\\n elif self._sensor_class == DEVICE_CLASS_HUMIDITY:\\n return '%'\",\n \"def unit_of_measurement(self):\\n return self._metadata[1]\",\n \"def raw_units(self) -> str:\\n if self._node.uom == 'F':\\n return TEMP_FAHRENHEIT\\n if self._node.uom == 'C':\\n return TEMP_CELSIUS\\n return self._node.uom\",\n \"def parse_unit(self, unitelem) -> Unit:\\n u = Unit()\\n\\n u.unitid = unitelem.attrib['id'].strip()\\n div = unitelem.find('{*}divide')\\n if div is not None:\\n nom = div.find('{*}unitNumerator').find('{*}measure')\\n denom = div.find('{*}unitDenominator').find('{*}measure')\\n u.nom = re.sub('.*:', '', nom.text).lower()\\n u.denom = re.sub('.*:', '', denom.text).lower()\\n else:\\n m = unitelem.find('{*}measure')\\n u.nom = re.sub('.*:', '', m.text).lower()\\n\\n return u\",\n \"def test_change_units(self):\\n s = State(\\\"water\\\", T=Q_(100, \\\"degC\\\"), p=Q_(1.0, \\\"atm\\\"), units=\\\"EE\\\")\\n assert s.units == \\\"EE\\\"\\n s.units = \\\"SI\\\"\\n assert s.units == \\\"SI\\\"\\n assert s.cv.units == \\\"kilojoule / kelvin / kilogram\\\"\\n assert s.cp.units == \\\"kilojoule / kelvin / kilogram\\\"\\n assert s.s.units == \\\"kilojoule / kelvin / kilogram\\\"\\n assert s.h.units == \\\"kilojoule / kilogram\\\"\\n assert s.T.units == \\\"degree_Celsius\\\"\\n assert s.u.units == \\\"kilojoule / kilogram\\\"\\n assert s.v.units == \\\"meter ** 3 / kilogram\\\"\\n assert s.p.units == \\\"bar\\\"\",\n \"def unit_of_measurement(self):\\n return self.sensor_type[\\\"unit\\\"]\",\n \"def to_inch(self):\\r\\n if self.units != 'inch':\\r\\n self.units = 'inch'\\r\\n for statement in self.statements:\\r\\n statement.to_inch()\\r\\n for tool in iter(self.tools.values()):\\r\\n tool.to_inch()\\r\\n for primitive in self.primitives:\\r\\n primitive.to_inch()\\r\\n for hit in self.hits:\\r\\n hit.to_inch()\",\n \"def convert_volume(self, event):\\n try:\\n #Compare other unit to one unit(cubic decimeters)\\n current_value, current_unit = float(\\\"0\\\" + str(self.v.get())), self.dropdown.get()\\n unit_comp = {\\\"acre foot\\\": 1233481.837548, \\\"barrels\\\": 158.987295, \\\"bushels(UK)\\\": 36.36872, \\\"bushels(US)\\\": 35.23907, \\\"centiliters\\\": 0.01, \\\"cubic centimeters\\\": 0.001, \\\"cubic decameters\\\": 1000000.0, \\\"cubic decimeters\\\": 1.0, \\\"cubic feet\\\": 28.316847, \\\"cubic inches\\\": 0.016387, \\\"cubic kilometers\\\": 1000000000000.0, \\\"cubic meters\\\": 1000.0, \\\"cubic mile\\\": 4168181825000.0, \\\"cubic millimeters\\\": 1e-06, \\\"cubic yards\\\": 764.554858, \\\"cups\\\": 0.236588, \\\"deciliters\\\": 0.1, \\\"dram\\\": 0.003697, \\\"dram(imperial)\\\": 0.003552, \\\"fluid ounces(US)\\\": 0.029574, \\\"fluid ounces(imperial)\\\": 0.028413, \\\"gallons(US,dry)\\\": 4.404884, \\\"gallons(US,liquid)\\\": 3.785412, \\\"gallons(imperial)\\\": 4.54609, \\\"gill(US)\\\": 0.118294, \\\"gill(imperial)\\\": 0.142065, \\\"liters\\\": 1.0, \\\"liters(1901-1964)\\\": 1.000028, \\\"microliters\\\": 1e-06, \\\"milliliters\\\": 0.001, \\\"nanoliters\\\": 1e-09, \\\"picoliters\\\": 1e-12, \\\"pints(US,dry)\\\": 0.55061, \\\"pints(US,liquid)\\\": 0.473176, \\\"pints(imperial)\\\": 0.568261, \\\"quarts(UK,dry)\\\": 1.101221, \\\"quarts(US,liquid)\\\": 0.946353, \\\"quarts(imperial)\\\": 1.136523, \\\"table spoons\\\": 0.014787, \\\"tea spoons\\\": 0.004929}\\n value_comp, printer = current_value * unit_comp[current_unit], \\\"\\\"\\n unit_list = sorted(unit_comp.keys())\\n unit_list.remove(current_unit)\\n for unit in unit_list:\\n printer += \\\"To %s \\\" % unit + \\\" \\\" * (max([len(i) for i in unit_list]) - len(unit)) + str(value_comp / unit_comp[unit]) + [\\\"\\\", \\\"\\\\n\\\"][unit_list[-1] != unit]\\n except ValueError: #In case user enter the other type of value, not Int or Float\\n printer = \\\"Value is invalid.\\\"\\n self.print_text(printer)\",\n \"def units(self, key):\\n \\n # Strip any operators\\n _, key = get_operator(key)\\n \\n # Fill out aliases \\n if key in component_from_alias:\\n key = component_from_alias[key]\\n elif key == 'E':\\n key = 'electricField'\\n elif key == 'B':\\n key = 'magneticField' \\n \\n return pg_units(key)\",\n \"def unit_array(self, values):\\n self._data_array.values = values\\n self._units = self._data_array.attrs['units'] = str(values.units)\",\n \"def _get_units_object(self, units):\\n if isinstance(units, cellml_units):\\n # We're done\\n pass\\n else:\\n units = amara_parse_cellml(unicode(units))\\n assert isinstance(units, cellml_units)\\n return units\",\n \"def get_units(self, obj: Dimension) -> [Unit]:\\n try:\\n return obj.units()\\n except KeyError as e:\\n logging.error(str(e))\\n return []\",\n \"def raw_unit_of_measurement(self) -> str:\\n if len(self._node.uom) == 1:\\n if self._node.uom[0] in UOM_FRIENDLY_NAME:\\n friendly_name = UOM_FRIENDLY_NAME.get(self._node.uom[0])\\n if friendly_name == TEMP_CELSIUS or \\\\\\n friendly_name == TEMP_FAHRENHEIT:\\n friendly_name = self.hass.config.units.temperature_unit\\n return friendly_name\\n else:\\n return self._node.uom[0]\\n else:\\n return None\",\n \"def convert_same_units(self):\\n # Convert pumping rate data\\n pump_units = \\\"%s3/%s\\\" % (self.len_units, self.time_units)\\n flag = _units.validate_units(pump_units)\\n if flag == 2:\\n self.pumprate.convert_units(self.time_units, pump_units)\\n self.pump_units = pump_units\",\n \"def __convert_to_devunit(self, value, in_devunit=False):\\r\\n if not in_devunit:\\r\\n value *= self.DEVUNIT_RATIO\\r\\n elif not isinstance(value, int):\\r\\n self.print_msg((\\\"Warning: non-integer value ({}) is given \\\"\\r\\n + \\\"in device unit.\\\").format(value))\\r\\n return int(value)\",\n \"def SBMLInferUnitsConverter_init():\\n return _libsbml.SBMLInferUnitsConverter_init()\",\n \"def convert_unit(self, time_unit):\\r\\n\\r\\n self.time_unit = time_unit\\r\\n self._conversion_factor = time_unit_conversion[time_unit]\",\n \"def _get_wavelength_attrs_with_units(self, attrname, units='AA'):\\n attr = self._lick[attrname]\\n if self.wavelength_unit is not None:\\n if units is None:\\n return attr * Unit(self.wavelength_unit)\\n else:\\n return (attr * Unit(self.wavelength_unit)).to(units)\\n else:\\n return attr\",\n \"def assign_unit(self):\\n self.units = {}\\n for unit in RADIAL_UNITS:\\n if unit.REPR == \\\"2th_deg\\\":\\n self.units[unit] = self.tth_deg\\n elif unit.REPR == \\\"2th_rad\\\":\\n self.units[unit] = self.tth_rad\\n elif unit.REPR == \\\"q_nm^-1\\\":\\n self.units[unit] = self.q_nm\\n elif unit.REPR == \\\"q_A^-1\\\":\\n self.units[unit] = self.q_A\\n elif unit.REPR == \\\"r_mm\\\":\\n self.units[unit] = self.r_mm\\n else:\\n logger.warning(\\\"Unit unknown to GUI %s\\\" % unit)\",\n \"def cbToEngUnits( BoardNum, Range, DataVal, EngUnits = 0.0 ):\\n EngUnits = ctypes.c_float( EngUnits )\\n CHK( cbw.cbToEngUnits( BoardNum, Range, DataVal, byref( EngUnits ) ) )\\n return EngUnits.value\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7536962","0.7362253","0.68372786","0.674662","0.6732477","0.66885984","0.665177","0.6623838","0.6573811","0.65471977","0.65269375","0.64705104","0.6375094","0.6330455","0.6316037","0.62951684","0.6259092","0.6249572","0.6218803","0.6210326","0.6170082","0.6136573","0.613454","0.61257637","0.61145324","0.6110248","0.60719216","0.60673285","0.60599464","0.60132724","0.6003513","0.5999872","0.5996715","0.5990414","0.59838694","0.5978679","0.5977484","0.5975112","0.59552276","0.5952138","0.5948542","0.5911982","0.59049934","0.5880017","0.5867853","0.5856709","0.5854324","0.5825775","0.5822277","0.58186877","0.58177865","0.58163154","0.5804694","0.5791493","0.5771444","0.57714355","0.57582206","0.57578015","0.5753025","0.57371485","0.5734584","0.5732167","0.57305753","0.5721052","0.5705062","0.57033455","0.57017267","0.57010394","0.5697212","0.5696481","0.56921417","0.56902224","0.5685165","0.5685154","0.5685154","0.56828547","0.5668206","0.5667553","0.5664368","0.56534547","0.5652542","0.5650681","0.5645845","0.5644696","0.5643603","0.5643275","0.56418306","0.5634774","0.5631077","0.56280416","0.5615923","0.56142545","0.5610219","0.56045777","0.55986476","0.5598397","0.5598301","0.5594889","0.5590981","0.5589303"],"string":"[\n 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\"0.57578015\",\n \"0.5753025\",\n \"0.57371485\",\n \"0.5734584\",\n \"0.5732167\",\n \"0.57305753\",\n \"0.5721052\",\n \"0.5705062\",\n \"0.57033455\",\n \"0.57017267\",\n \"0.57010394\",\n \"0.5697212\",\n \"0.5696481\",\n \"0.56921417\",\n \"0.56902224\",\n \"0.5685165\",\n \"0.5685154\",\n \"0.5685154\",\n \"0.56828547\",\n \"0.5668206\",\n \"0.5667553\",\n \"0.5664368\",\n \"0.56534547\",\n \"0.5652542\",\n \"0.5650681\",\n \"0.5645845\",\n \"0.5644696\",\n \"0.5643603\",\n \"0.5643275\",\n \"0.56418306\",\n \"0.5634774\",\n \"0.5631077\",\n \"0.56280416\",\n \"0.5615923\",\n \"0.56142545\",\n \"0.5610219\",\n \"0.56045777\",\n \"0.55986476\",\n \"0.5598397\",\n \"0.5598301\",\n \"0.5594889\",\n \"0.5590981\",\n \"0.5589303\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.69773746"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":88598,"cells":{"query":{"kind":"string","value":"Perform actual bispectrum calculation."},"document":{"kind":"string","value":"def _calculate(self, atoms, outdir, grid_dimensions, **kwargs):\n use_fp64 = kwargs.get(\"use_fp64\", False)\n\n lammps_format = \"lammps-data\"\n ase_out_path = os.path.join(outdir, \"lammps_input.tmp\")\n ase.io.write(ase_out_path, atoms, format=lammps_format)\n\n nx = grid_dimensions[0]\n ny = grid_dimensions[1]\n nz = grid_dimensions[2]\n\n # Create LAMMPS instance.\n lammps_dict = {}\n lammps_dict[\"twojmax\"] = self.parameters.bispectrum_twojmax\n lammps_dict[\"rcutfac\"] = self.parameters.bispectrum_cutoff\n lammps_dict[\"atom_config_fname\"] = ase_out_path\n lmp = self._setup_lammps(nx, ny, nz, outdir, lammps_dict,\n log_file_name=\"lammps_bgrid_log.tmp\")\n\n # An empty string means that the user wants to use the standard input.\n # What that is differs depending on serial/parallel execution.\n if self.parameters.lammps_compute_file == \"\":\n filepath = __file__.split(\"bispectrum\")[0]\n if self.parameters._configuration[\"mpi\"]:\n if self.parameters.use_z_splitting:\n self.parameters.lammps_compute_file = \\\n os.path.join(filepath, \"in.bgridlocal.python\")\n else:\n self.parameters.lammps_compute_file = \\\n os.path.join(filepath,\n \"in.bgridlocal_defaultproc.python\")\n else:\n self.parameters.lammps_compute_file = \\\n os.path.join(filepath, \"in.bgrid.python\")\n\n # Do the LAMMPS calculation.\n lmp.file(self.parameters.lammps_compute_file)\n\n # Set things not accessible from LAMMPS\n # First 3 cols are x, y, z, coords\n ncols0 = 3\n\n # Analytical relation for fingerprint length\n ncoeff = (self.parameters.bispectrum_twojmax + 2) * \\\n (self.parameters.bispectrum_twojmax + 3) * (self.parameters.bispectrum_twojmax + 4)\n ncoeff = ncoeff // 24 # integer division\n self.fingerprint_length = ncols0+ncoeff\n\n # Extract data from LAMMPS calculation.\n # This is different for the parallel and the serial case.\n # In the serial case we can expect to have a full bispectrum array at\n # the end of this function.\n # This is not necessarily true for the parallel case.\n if self.parameters._configuration[\"mpi\"]:\n nrows_local = extract_compute_np(lmp, \"bgridlocal\",\n lammps_constants.LMP_STYLE_LOCAL,\n lammps_constants.LMP_SIZE_ROWS)\n ncols_local = extract_compute_np(lmp, \"bgridlocal\",\n lammps_constants.LMP_STYLE_LOCAL,\n lammps_constants.LMP_SIZE_COLS)\n if ncols_local != self.fingerprint_length + 3:\n raise Exception(\"Inconsistent number of features.\")\n\n snap_descriptors_np = \\\n extract_compute_np(lmp, \"bgridlocal\",\n lammps_constants.LMP_STYLE_LOCAL, 2,\n array_shape=(nrows_local, ncols_local),\n use_fp64=use_fp64)\n lmp.close()\n\n # Copy the grid dimensions only at the end.\n self.grid_dimensions = [nx, ny, nz]\n return snap_descriptors_np, nrows_local\n\n else:\n # Extract data from LAMMPS calculation.\n snap_descriptors_np = \\\n extract_compute_np(lmp, \"bgrid\", 0, 2,\n (nz, ny, nx, self.fingerprint_length),\n use_fp64=use_fp64)\n lmp.close()\n\n # switch from x-fastest to z-fastest order (swaps 0th and 2nd\n # dimension)\n snap_descriptors_np = snap_descriptors_np.transpose([2, 1, 0, 3])\n # Copy the grid dimensions only at the end.\n self.grid_dimensions = [nx, ny, nz]\n if self.parameters.descriptors_contain_xyz:\n return snap_descriptors_np, nx*ny*nz\n else:\n return snap_descriptors_np[:, :, :, 3:], nx*ny*nz"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def calculate_ft(self):\n \n # Create a function which is able to evaluate B**2\n ffunc = scipy.interpolate.interp1d(self.psigrid, self.e.getF()[self.tind])\n def b2_func(R, Z, psi):\n bt = ffunc(psi)/R\n br = -self.psifunc.ev(R, Z, dy=1)/R\n bz = self.psifunc.ev(R, Z, dx=1)/R\n \n return bt**2 + br**2 + bz**2\n \n\n def b_bmax2(R,Z,psi):\n b2 = b2_func(R,Z,psi)\n return b2 / np.max(b2)\n \n def b_bmax(R,Z,psi):\n return np.sqrt(b_bmax2(R,Z,psi))\n \n # Evaluate the flux-surface averaged h^2 and h, as required\n fsa_h2 = self.fs_average(b_bmax2)\n fsa_h = self.fs_average(b_bmax)\n \n # This is the function which gets flux-surface averaged in equation (7)\n def ftl_func(R,Z,psi):\n h = b_bmax(R,Z,psi)\n h2 = b_bmax2(R,Z,psi)\n \n return (1 - (np.sqrt(1 - h) * (1 + 0.5 * h)))/h2\n \n \n # Equation 6, 7 in Lin-Liu\n fs_ftu = 1 - fsa_h2 / fsa_h**2 * (1 - np.sqrt(1 - fsa_h) * (1 + 0.5 * fsa_h))\n fs_ftl = 1 - fsa_h2 * self.fs_average(ftl_func)\n # Equation 18, 19 \n om = 0.75\n self.fs_ft = om*fs_ftu + (1-om)*fs_ftl","def compute_f2a_f2b(self):\n try:\n self.Frac2a = self.data['AB Counts'].sum(\n ) / self.data['A Counts'].sum()\n self.Frac2b = self.data['AB Counts'].sum(\n ) / self.data['B Counts'].sum()\n except BaseException:\n print(\"Ran into error computing AB/A and AB/B. Continuing\")","def calculate(self, b):\n self.n_steps = self.n_steps + 1\n self.length = b.length\n self.natoms = b.natoms\n for i in range(0,self.natoms-1):\n for j in range(i+1,self.natoms):\n rij = (b.atoms[i].xyz - b.atoms[j].xyz)\n rij = rij - self.pbc_correction(rij)\n mag_rij = la.norm(rij)\n bin_no = int(round(mag_rij/self.dr))\n if bin_no <= self.n_max:\n self.gr[bin_no] = self.gr[bin_no] + 1","def test_get_spectra_bi():\r\n\r\n methods = (None,\r\n {\"this_method\": 'welch', \"NFFT\": 256, \"Fs\": 2 * np.pi},\r\n {\"this_method\": 'welch', \"NFFT\": 1024, \"Fs\": 2 * np.pi})\r\n\r\n for method in methods:\r\n arsig1, _, _ = utils.ar_generator(N=2 ** 16)\r\n arsig2, _, _ = utils.ar_generator(N=2 ** 16)\r\n\r\n avg_pwr1 = (arsig1 ** 2).mean()\r\n avg_pwr2 = (arsig2 ** 2).mean()\r\n avg_xpwr = (arsig1 * arsig2.conjugate()).mean()\r\n\r\n tseries = np.vstack([arsig1, arsig2])\r\n\r\n f, fxx, fyy, fxy = tsa.get_spectra_bi(arsig1, arsig2, method=method)\r\n\r\n # \\sum_{\\omega} PSD(\\omega) d\\omega:\r\n est_pwr1 = np.sum(fxx * (f[1] - f[0]))\r\n est_pwr2 = np.sum(fyy * (f[1] - f[0]))\r\n est_xpwr = np.sum(fxy * (f[1] - f[0])).real\r\n\r\n # Test that we have the right order of magnitude:\r\n npt.assert_array_almost_equal(est_pwr1, avg_pwr1, decimal=-1)\r\n npt.assert_array_almost_equal(est_pwr2, avg_pwr2, decimal=-1)\r\n npt.assert_array_almost_equal(np.mean(est_xpwr),\r\n np.mean(avg_xpwr),\r\n decimal=-1)","def calculate(self, fullFile):\r\n\r\n # Initialize variables\r\n pixelSize = 0\r\n areaFracBright = 0\r\n estSize= 0\r\n diameter_average_bright = 0\r\n diameter_SD_bright = 0\r\n diameter_num_bright = 0\r\n diameter_average_dark = 0\r\n diameter_SD_dark = 0\r\n diameter_num_dark = 0\r\n length_average_bright = 0\r\n length_SD_bright = 0\r\n length_num_bright = 0\r\n length_average_dark = 0\r\n length_SD_dark = 0\r\n length_num_dark = 0\r\n area_average_bright = 0\r\n area_SD_bright = 0\r\n area_num_bright = 0\r\n area_average_dark = 0\r\n area_SD_dark = 0\r\n area_num_dark = 0\r\n sumLength_average_bright = 0\r\n sumLength_SD_bright = 0\r\n sumLength_num_bright = 0\r\n sumLength_average_dark = 0\r\n sumLength_SD_dark = 0\r\n sumLength_num_dark = 0\r\n \r\n # Rename text boxes and tkinter variables for easier reference\r\n results = self.textResults\r\n status = self.textStatus\r\n showSteps = self.varShowSteps.get()\r\n outputExcel = self.varOutputExcel.get()\r\n savePDF = self.varSavePDF.get()\r\n\r\n # Handle strange GUI input.\r\n if self.varSegment.get() == \"binary\":\r\n self.varSaveBinary.set(False)\r\n\r\n # Select the image to operate on.\r\n if self.varSegment.get() == \"binary\":\r\n brightFile = selectFile(title=\"Select the bright phase mask\")\r\n darkFile = selectFile(title=\"Select the bright phase mask\")\r\n folder = '/'.join(brightFile.split('/')[:-1])\r\n fname = brightFile.split('/')[-1].split(' -')[:-1][0]\r\n ftype = brightFile.split('.')[-1]\r\n fnametype = fname + '.' + ftype\r\n pixelString = brightFile.split('--')[1] \r\n pixelSize = float(pixelString)\r\n fullFile = brightFile\r\n\r\n else:\r\n #fullFile = selectFile()\r\n # Figure out file name and type.\r\n folder = '/'.join(fullFile.split('/')[:-1])\r\n fname = fullFile.split('/')[-1].split('.')[:-1][0]\r\n ftype = fullFile.split('.')[-1]\r\n fnametype = fname + '.' + ftype\r\n\r\n # Status update.\r\n if self.varSegment.get() == \"binary\":\r\n self.write(status, \"Operating on\", fnametype, \"(binary)\")\r\n self.write(results, \"Operating on\", fnametype, \"(binary)\")\r\n else:\r\n self.write(status, \"Operating on\", fnametype)\r\n self.write(results, \"Operating on\", fnametype)\r\n\r\n # Load image.\r\n img_raw = inout.load(fullFile)\r\n\r\n # Prepare for output of data to excel\r\n if outputExcel:\r\n if self.outFold == None:\r\n excelPath = folder+'/'+fname+' - All Measurements.xlsx'\r\n writer = pd.ExcelWriter(excelPath)\r\n else:\r\n excelPath = self.outFold+'/'+fname+' - All Measurements.xlsx'\r\n writer = pd.ExcelWriter(excelPath)\r\n\r\n # Prepare PDF file.\r\n pdf = None\r\n if savePDF:\r\n if self.outFold == None:\r\n pdf = PdfPages(folder+'/'+fname+' - Steps.pdf')\r\n else:\r\n pdf = PdfPages(self.outFold+'/'+fname+' - Steps.pdf')\r\n\r\n # Show steps.\r\n if showSteps:\r\n display.showFull(img_raw, title=\"Raw Image.\")\r\n\r\n if savePDF:\r\n inout.pdfSaveImage(pdf, img_raw, title=\"Raw Image.\")\r\n\r\n # Select the image data and scale bar.\r\n if self.varSegment.get() != \"binary\":\r\n\r\n if self.varAutoParse.get():\r\n profile = self.varProfile.get()\r\n img, pixelSize = autoSelect.autoDetect(img_raw, profile=profile)\r\n else:\r\n img, scale = manualSelectImage(img_raw)\r\n \r\n # Ensure proper dtype.\r\n img = inout.uint8(img) \r\n scale = inout.uint8(scale)\r\n\r\n # Get the pixel size.\r\n pixelSize = measure.manualPixelSize(scale)\r\n self.write(results, \"The pixel size is %.3f nm\" %(pixelSize))\r\n \r\n # Get a rough estimated of the ligament diameter.\r\n bright, dark = segment.roughSegment(img)\r\n estSizeD = measure.estimateDiameter(dark)\r\n estSizeB = measure.estimateDiameter(bright)\r\n estSizeB_rough = copy.copy(estSizeB)\r\n estSizeD_rough = copy.copy(estSizeD)\r\n # Get the average estimated size with a weight towards the thinner\r\n estSize = (min(estSizeD, estSizeB) + estSizeD + estSizeB) / 3\r\n # Result update \r\n self.write(results, \"Weighted average estimated diameter: \",\r\n round(estSize,3),\" pixels (\", round(estSize*pixelSize,3),\r\n \" nm).\", sep='')\r\n if savePDF:\r\n inout.pdfSaveImage(pdf, img, title=\"Selected image data\",\r\n cmap=plt.cm.gray)\r\n else:\r\n img = img_raw.copy()\r\n img = inout.uint8(img)\r\n\r\n # Segment the image.\r\n # Status update.\r\n if self.varSegment.get() == \"accurate\":\r\n self.write(status, \"Segmenting image. This may take a while,\",\r\n \"especially at higher resolutions.\")\r\n else:\r\n self.write(status, \"Segmenting image.\")\r\n # Segment based on options. \r\n if self.varSegment.get() == \"fast\":\r\n #already did this when estimating size\r\n pass\r\n elif self.varSegment.get() == \"manual\":\r\n bright, dark = segment.manualSegment(img)\r\n elif self.varSegment.get() == \"accurate\":\r\n bright, dark = segment.segment(img, estSize)\r\n elif self.varSegment.get() == \"binary\":\r\n bright = imread(brightFile)\r\n dark = imread(darkFile)\r\n estSizeD = measure.estimateDiameter(dark)\r\n estSizeB = measure.estimateDiameter(bright)\r\n estSizeB_rough = copy.copy(estSizeB)\r\n estSizeD_rough = copy.copy(estSizeD)\r\n # Get the average estimated size with a weight towards the thinner\r\n estSize = (min(estSizeD, estSizeB) + estSizeD + estSizeB) / 3\r\n # Result update \r\n self.write(results, \"Weighted average estimated diameter: \",\r\n round(estSize,3),\" pixels (\", round(estSize*pixelSize,3),\r\n \" nm).\", sep='')\r\n bright = inout.uint8(bright)\r\n dark = inout.uint8(dark)\r\n\r\n if showSteps and self.varSegment.get() != \"binary\":\r\n display.overlayMask(img, bright, title=\"Bright phase mask.\",\r\n animate=True)\r\n display.overlayMask(img, dark, title=\"Dark phase mask.\",\r\n animate=True)\r\n\r\n if savePDF and self.varSegment.get() != \"binary\":\r\n inout.pdfSaveOverlay(pdf, img, bright, title=\"Bright phase mask.\")\r\n inout.pdfSaveOverlay(pdf, img, dark, title=\"Dark phase mask.\")\r\n\r\n if self.varSaveMovie.get():\r\n stack = []\r\n for i in range(5):\r\n stack.append(gray2rgb(img))\r\n stack.append(display.overlayMask(img,bright,\r\n return_overlay=True))\r\n inout.save_movie(stack, ''.join((folder, '//', fname,\r\n ' - segment movie.mp4')))\r\n\r\n if self.varSaveBinary.get():\r\n inout.saveBinary(bright,\r\n folder+'/'+fname+' - Bright Segment--'+str(pixelSize)+'--.tif')\r\n inout.saveBinary(dark,\r\n folder+'/'+fname+' - Dark Segment--'+str(pixelSize)+'--.tif')\r\n\r\n \r\n \r\n # Calculate area fraction.\r\n if self.varAreaFraction.get():\r\n # Status update.\r\n self.write(status, \"Calculating area fraction.\")\r\n areaFracBright = np.count_nonzero(bright) / \\\r\n (np.count_nonzero(bright) + np.count_nonzero(dark))\r\n # Results update.\r\n self.write(results, \"Bright phase area fraction: %.3f\" \\\r\n %(areaFracBright))\r\n\r\n # Refine the estimated diameters.\r\n estSizeB, _ = measure.diameter(bright, estSize)\r\n estSizeD, _ = measure.diameter(dark, estSize)\r\n\r\n \r\n # Calculate the diameter.\r\n if self.varDiameter.get():\r\n # Status update.\r\n self.write(status, \"Calculating ligament diameter.\")\r\n # Calculate.\r\n diameter_average_bright, diameter_SD_bright, diameter_all_bright =\\\r\n measure.diameter(bright, estSizeB,\r\n showSteps=showSteps,\r\n returnAll=True,\r\n pdf=pdf)\r\n diameter_num_bright = len(diameter_all_bright)\r\n diameter_average_dark, diameter_SD_dark, diameter_all_dark =\\\r\n measure.diameter(dark, estSizeD,\r\n showSteps=showSteps,\r\n returnAll=True,\r\n pdf=pdf)\r\n diameter_num_dark = len(diameter_all_dark)\r\n # Update estimated ligament sizes.\r\n estSizeB = diameter_average_bright\r\n estSizeD = diameter_average_dark\r\n # Results update.\r\n self.write(results, \"Bright phase diameter:\",\r\n round(diameter_average_bright,2), \"±\",\r\n round(diameter_SD_bright), \"pixels.\")\r\n self.write(results, \"Dark phase diameter:\",\r\n round(diameter_average_dark,2), \"±\",\r\n round(diameter_SD_dark), \"pixels.\")\r\n\r\n if outputExcel:\r\n df = pd.DataFrame(diameter_all_bright)\r\n df.to_excel(writer, sheet_name=\"Bright phase diameter data\")\r\n df = pd.DataFrame(diameter_all_dark)\r\n df.to_excel(writer, sheet_name=\"Dark phase diameter data\") \r\n \r\n # Fix estSizeB and estSizeD if there is a problem\r\n estSizeB = estSizeB_rough if np.isnan(estSizeB) else estSizeB \r\n estSizeD = estSizeD_rough if np.isnan(estSizeD) else estSizeD \r\n \r\n # Calculate the ligament length.\r\n if self.varLength.get():\r\n # Status update.\r\n self.write(status, \"Calculating ligament length.\")\r\n length_average_bright, length_SD_bright, length_all_bright = \\\r\n measure.length(bright, estSizeB,\r\n showSteps=showSteps,\r\n returnAll=True,\r\n pdf=pdf)\r\n try:\r\n length_num_bright = len(length_all_bright)\r\n except TypeError:\r\n length_num_bright = 0\r\n length_average_dark, length_SD_dark, length_all_dark = \\\r\n measure.length(dark, estSizeD,\r\n showSteps=showSteps,\r\n returnAll=True,\r\n pdf=pdf)\r\n try:\r\n length_num_dark = len(length_all_dark)\r\n except TypeError:\r\n length_num_dark = 0\r\n # Results update.\r\n if length_average_bright != 0:\r\n self.write(results, \"Bright phase ligament length:\",\r\n round(length_average_bright,2), \"±\",\r\n round(length_SD_bright), \"pixels.\")\r\n if length_average_dark != 0:\r\n self.write(results, \"Dark phase ligament length:\",\r\n round(length_average_dark,2), \"±\",\r\n round(length_SD_dark), \"pixels.\")\r\n\r\n if outputExcel:\r\n if length_average_bright != 0:\r\n df = pd.DataFrame(length_all_bright)\r\n df.to_excel(writer, sheet_name=\"Bright phase length data\")\r\n if length_average_dark != 0:\r\n df = pd.DataFrame(length_all_dark)\r\n df.to_excel(writer, sheet_name=\"Dark phase length data\") \r\n\r\n # Calculate average object area.\r\n if self.varArea.get():\r\n # Status update.\r\n self.write(status, \"Calculating average object area.\")\r\n area_average_bright, area_SD_bright, area_all_bright = \\\r\n measure.area(bright, estSizeB,\r\n showSteps=showSteps,\r\n returnAll=True)\r\n try:\r\n area_num_bright = len(area_all_bright)\r\n except TypeError:\r\n area_num_bright = 0\r\n area_average_dark, area_SD_dark, area_all_dark = \\\r\n measure.area(dark, estSizeD,\r\n showSteps=showSteps,\r\n returnAll=True)\r\n try:\r\n area_num_dark = len(area_all_dark)\r\n except TypeError:\r\n area_num_dark = 0\r\n # Results update.\r\n if area_average_bright != 0:\r\n self.write(results, \"Bright phase average object area:\",\r\n round(area_average_bright,2), \"±\",\r\n round(area_SD_bright), \"pixels^2.\")\r\n if area_average_dark != 0:\r\n self.write(results, \"Dark phase average object area:\",\r\n round(area_average_dark,2), \"±\",\r\n round(area_SD_dark), \"pixels^2.\")\r\n\r\n if outputExcel:\r\n if area_average_bright != 0:\r\n df = pd.DataFrame(area_all_bright)\r\n df.to_excel(writer, sheet_name=\"Bright phase area data\")\r\n if area_average_dark != 0:\r\n df = pd.DataFrame(area_all_dark)\r\n df.to_excel(writer, sheet_name=\"Dark phase area data\") \r\n\r\n # Calculate the sum connected length of each object.\r\n if self.varSumConnectedLength.get():\r\n # Status update.\r\n self.write(status, \"Calculating sum connected ligament length.\")\r\n sumLength_average_bright, sumLength_SD_bright, \\\r\n sumLength_all_bright = \\\r\n measure.connectedLength(bright, estSizeB,\r\n showSteps=showSteps,\r\n returnAll=True,\r\n pdf=pdf)\r\n try:\r\n sumLength_num_bright = len(sumLength_all_bright)\r\n except TypeError:\r\n sumLength_num_bright = 0\r\n sumLength_average_dark, sumLength_SD_dark, sumLength_all_dark = \\\r\n measure.connectedLength(dark, estSizeD,\r\n showSteps=showSteps,\r\n returnAll=True,\r\n pdf=pdf)\r\n try:\r\n sumLength_num_dark = len(sumLength_all_dark)\r\n except TypeError:\r\n sumLength_num_dark = 0\r\n # Results update.\r\n if sumLength_average_bright != 0:\r\n self.write(results, \"Bright phase sum connected length:\",\r\n round(sumLength_average_bright,2), \"±\",\r\n round(sumLength_SD_bright), \"pixels.\")\r\n if sumLength_average_dark != 0:\r\n self.write(results, \"Dark phase sum connected length:\",\r\n round(sumLength_average_dark,2), \"±\",\r\n round(sumLength_SD_dark), \"pixels.\")\r\n\r\n if outputExcel:\r\n if sumLength_average_bright != 0:\r\n df = pd.DataFrame(sumLength_all_bright)\r\n df.to_excel(writer,\r\n sheet_name=\"Bright phase sum length data\")\r\n if sumLength_average_dark != 0:\r\n df = pd.DataFrame(sumLength_all_dark)\r\n df.to_excel(writer,\r\n sheet_name=\"Dark phase sum length data\") \r\n\r\n # Save excel file\r\n if outputExcel:\r\n writer.save()\r\n\r\n # Save the pdf.\r\n if savePDF:\r\n plt.title('Summary')\r\n plt.axis('off')\r\n fs = 10\r\n yloc = 0.95\r\n xloc = 0.01\r\n space = 0.05\r\n out = 'Image: ' + fnametype\r\n plt.text(xloc, yloc, out, fontsize=fs)\r\n yloc -= space\r\n out = 'Pixel size: ' + str(pixelSize)\r\n plt.text(xloc, yloc, out, fontsize=fs)\r\n yloc -= space\r\n out = 'Bright phase area fraction: ' + str(round(areaFracBright,3))\r\n plt.text(xloc, yloc, out, fontsize=fs)\r\n yloc -= space\r\n out = 'Rough diameter estimate: ' + str(round(estSize,3))+' pixels.'\r\n plt.text(xloc, yloc, out, fontsize=fs)\r\n yloc -= space*2\r\n\r\n out = 'Bright phase:'\r\n plt.text(xloc, yloc, out, fontsize=fs, fontweight='bold')\r\n yloc -= space\r\n if diameter_average_bright != 0:\r\n out = ('Ligament diameter: ' +\r\n str(round(diameter_average_bright*pixelSize,3)) +\r\n ' ± ' + str(round(diameter_SD_bright*pixelSize,3)) +\r\n ' nm')\r\n plt.text(xloc, yloc, out, fontsize=fs)\r\n yloc -= space\r\n if length_average_bright != 0:\r\n out = ('Ligament length: ' +\r\n str(round(length_average_bright*pixelSize,3)) +\r\n ' ± ' + str(round(length_SD_bright*pixelSize,3)) +\r\n ' nm')\r\n plt.text(xloc, yloc, out, fontsize=fs)\r\n yloc -= space\r\n if area_average_bright != 0:\r\n out = ('Object area: ' +\r\n str(round(area_average_bright*pixelSize**2,3)) +\r\n ' ± ' + str(round(area_SD_bright*pixelSize**2,3)) +\r\n r' nm$^2$')\r\n plt.text(xloc, yloc, out, fontsize=fs)\r\n yloc -= space\r\n if sumLength_average_bright != 0:\r\n out = ('Sum connected length: ' +\r\n str(round(sumLength_average_bright*pixelSize,3)) +\r\n ' ± ' + str(round(sumLength_SD_bright*pixelSize,3)) +\r\n ' nm')\r\n plt.text(xloc, yloc, out, fontsize=fs)\r\n yloc -= space\r\n yloc -= space\r\n\r\n out = 'Dark phase:'\r\n plt.text(xloc, yloc, out, fontsize=fs, fontweight='bold')\r\n yloc -= space\r\n if diameter_average_dark != 0:\r\n out = ('Ligament diameter: ' +\r\n str(round(diameter_average_dark*pixelSize,3)) +\r\n ' ± ' + str(round(diameter_SD_dark*pixelSize,3)) +\r\n ' nm')\r\n plt.text(xloc, yloc, out, fontsize=fs)\r\n yloc -= space\r\n if length_average_dark != 0:\r\n out = ('Ligament length: ' +\r\n str(round(length_average_dark*pixelSize,3)) +\r\n ' ± ' + str(round(length_SD_dark*pixelSize,3)) +\r\n ' nm')\r\n plt.text(xloc, yloc, out, fontsize=fs)\r\n yloc -= space\r\n if area_average_dark != 0:\r\n out = ('Object area: ' +\r\n str(round(area_average_dark*pixelSize**2,3)) +\r\n ' ± ' + str(round(area_SD_dark*pixelSize**2,3)) +\r\n r' nm$^2$')\r\n plt.text(xloc, yloc, out, fontsize=fs)\r\n yloc -= space\r\n if sumLength_average_dark != 0:\r\n out = ('Sum connected length: ' +\r\n str(round(sumLength_average_dark*pixelSize,3)) +\r\n ' ± ' + str(round(sumLength_SD_dark*pixelSize,3)) +\r\n ' nm')\r\n plt.text(xloc, yloc, out, fontsize=fs)\r\n yloc -= space\r\n \r\n\r\n pdf.savefig()\r\n plt.close()\r\n pdf.close()\r\n\r\n # Append data to the saveAll\r\n newdata = np.array(\r\n [[fnametype,\r\n round(pixelSize,2),\r\n round(areaFracBright,3),\r\n round(estSize*pixelSize,3),\r\n round(diameter_average_bright*pixelSize,3),\r\n round(diameter_SD_bright*pixelSize,3),\r\n diameter_num_bright,\r\n round(diameter_average_dark*pixelSize,3),\r\n round(diameter_SD_dark*pixelSize,3),\r\n diameter_num_dark,\r\n round(length_average_bright*pixelSize,3),\r\n round(length_SD_bright*pixelSize,3),\r\n length_num_bright,\r\n round(length_average_dark*pixelSize,3),\r\n round(length_SD_dark*pixelSize,3),\r\n length_num_dark,\r\n round(area_average_bright*pixelSize**2,3),\r\n round(area_SD_bright*pixelSize**2,3),\r\n area_num_bright,\r\n round(area_average_dark*pixelSize**2,3),\r\n round(area_SD_dark*pixelSize**2,3),\r\n area_num_dark,\r\n round(sumLength_average_bright*pixelSize,3),\r\n round(sumLength_SD_bright*pixelSize,3),\r\n sumLength_num_bright,\r\n round(sumLength_average_dark*pixelSize,3),\r\n round(sumLength_SD_dark*pixelSize,3),\r\n sumLength_num_dark\r\n ]])\r\n \r\n\r\n \r\n self.saveAll = np.append(self.saveAll, newdata, axis=0)\r\n\r\n # Add new line to status and results\r\n self.write(results, '')\r\n self.write(status, '')","def calculate_bandwidth(self, complist):\n\n self.type = complist[0]\n self.spot = complist[2]\n self.value = complist[1]\n self.fail = False\n\n if self.spot == \"1\" or self.spot == \"2\":\n # print \"Calculation if Loop 1st filter\"\n if self.type == \"C\":\n if self.c1 == 0:\n self.c1 = self.value\n else:\n self.fail = True\n else:\n if self.r1 == 0:\n self.r1 = self.value\n else:\n self.fail = True\n\n if self.spot == \"3\" or self.spot == \"4\":\n # print \"Calculation if loop 2nd filter\"\n if self.type == \"C\":\n if self.c2 == 0:\n self.c2 = self.value\n else:\n self.fail = True\n else: #self.type == \"R\"\n if self.r2 == 0:\n self.r2 = self.value\n else:\n self.fail = True\n\n if self.c1 != 0 and self.c2 != 0 and self.r1 != 0 and self.r2 != 0:\n cf_low = int((1/(2*pi*(self.r1)*(self.c1))/1000))\n #print \"hello!\"\n cf_low = str(cf_low)\n self.cutoff_freql = cf_low\n self.cutoff_freql_text = cf_low + \"K\"\n print self.cutoff_freql_text\n cf_high = int((1/(2*pi*(self.r2)*(self.c2))/1000))\n cf_high = str(cf_high)\n self.cutoff_freqh = cf_high\n self.cutoff_freqh_text = cf_high + \"K\"\n print self.cutoff_freqh_text\n voltage_change = float((self.r2)/self.r1)\n voltage = 5 + voltage_change\n self.voltage = str(voltage)\n print self.voltage","def process(self, stream):\n\n # Extract data and weight arrays, averaging over beams\n data = np.mean(stream.hfb[:], axis=2)\n weight = np.mean(stream.weight[:], axis=2)\n\n # Number of samples per data point in the HFB data:\n # n_samp = delta_nu * delta_t * (1 - frac_lost), where\n # delta_nu is the frequency resolution (390.625 kHz / 128),\n # delta_t the integration time (~10.066 s), and\n # frac_lost is the fraction of integration that was lost upstream\n freq_width = stream._data[\"index_map/freq/width\"][0] * 1e6\n nsubfreq = len(stream._data[\"index_map/subfreq\"])\n delta_nu = freq_width / nsubfreq\n delta_t = np.median(np.diff(stream._data[\"index_map/time/ctime\"]))\n frac_lost = stream[\"flags/frac_lost\"][0]\n n_samp = delta_nu * delta_t * (1.0 - frac_lost)\n\n # Ideal radiometer equation\n radiometer = data**2 * tools.invert_no_zero(n_samp)\n\n # Radiometer noise test: the sensitivity metric would be unity for\n # an ideal radiometer, it would be higher for data with RFI\n sensitivity_metric = 2.0 * tools.invert_no_zero(radiometer * weight)\n\n # Boolean mask indicating data that are contaminated by RFI\n mask = sensitivity_metric > self.threshold\n\n # Create container to hold output\n out = HFBRFIMask(axes_from=stream, attrs_from=stream)\n\n if self.keep_sens:\n out.add_dataset(\"sens\")\n out.sens[:] = sensitivity_metric\n\n # Save mask to output container\n out.mask[:] = mask\n\n # Add beam selection to RFI mask attributes\n out.attrs[\"beam\"] = stream._data[\"index_map\"][\"beam\"][:]\n\n # Return output container\n return out","def calculate(self) -> float:","def calc_flux_array(self):\n \n # First determine the associated spectrum\n self.compute_template_spectrum()\n\n # Calculate baseline counts to normalise fluxes we scan over\n # Go from 10**(bin_min)*mean up to 10**(bin_max)*mean in nbins steps\n b = self.setup_b_instance(0,add_ps_mask=True)\n mean = np.sum(b.CTB_masked_compressed[0])/len(b.CTB_masked_compressed[0])\n A_array = mean*10**np.linspace(self.bin_min,self.bin_max,self.nbins)\n\n # Array to get LLs when no profile likelihood run\n norun = np.array([1.0, 1.0, 1.0, 1.0])\n\n # Now setup and compute the arrays\n LL_array = np.array([]) \n A_array_short = np.array([])\n spect_array = np.array([])\n\n for i in range(len(A_array)):\n print \"on i =\",i\n # Calculate LL\n if i == 0:\n b1 = self.setup_b_instance(A_array[i],add_ps_mask=True)\n else:\n for key in b1.fixed_template_dict_nested.keys():\n b1.fixed_template_dict_nested[key] = b1.fixed_template_dict_nested[key]*A_array[i]/A_array[i-1]\n ll_val = b1.ll(norun,4,4)\n # Make triangle\n\n # Append to arrays\n LL_array = np.append(LL_array,ll_val)\n A_array_short = np.append(A_array_short,A_array[i])\n spect_array = self.spectrum*np.array(A_array_short)\n\n # Save output\n np.save(work_dir+'ScanOutput/'+self.tag+'/En_array-'+str(self.flux_array_ebin)+'.npy',self.En_center)\n np.save(work_dir+'ScanOutput/'+self.tag+'/LL_array-'+str(self.flux_array_ebin)+'.npy',LL_array)\n np.save(work_dir+'ScanOutput/'+self.tag+'/Flux_array-'+str(self.flux_array_ebin)+'.npy',spect_array)","def make_bispectra(self, bgwindow=4):\n\n bisp = lambda d, ij, jk, ki: d[:,ij] * d[:,jk] * n.conj(d[:,ki]) # bispectrum for pol data\n\n self.triples = self.make_triples()\n self.bispectra = n.ma.zeros((len(self.data), len(self.triples)), dtype='complex')\n\n for i in xrange((bgwindow/2)+self.twidth, len(self.data)-( (bgwindow/2)+2*self.twidth )):\n# for i in xrange((bgwindow/2)+self.twidth, len(self.data)-( (bgwindow/2)+self.twidth ), max(1,self.twidth)): # leaves gaps in data\n diff = self.tracksub(i, bgwindow=bgwindow)\n\n if len(n.shape(diff)) == 1: # no track\n continue\n\n diffmean = n.mean(diff, axis=2) # if all zeros, just make mean # bit of a hack\n\n for trip in xrange(len(self.triples)):\n ij, jk, ki = self.triples[trip]\n self.bispectra[i, trip] = bisp(diffmean, ij, jk, ki).mean(axis=0) # Stokes I bispectrum. Note we are averaging after forming bispectrum, so not technically a Stokes I bispectrum.","def FIR_estimate(self):\r\n raise NotImplementedError","def fbank(signal,samplerate=16000,winlen=0.025,winstep=0.01,\n nfilt=26,nfft=512,lowfreq=0,highfreq=None,preemph=0.97): \n highfreq= highfreq or samplerate/2\n print \"preemph %s\"%(preemph)\n signal = sigproc.preemphasis(signal,preemph)\n frames = sigproc.framesig(signal, winlen*samplerate, winstep*samplerate)\n matchframes(frames[0], frames[1])\n pspec = sigproc.powspec(frames,nfft)\n energy = pylab.sum(pspec,1) # this stores the total energy in each frame\n energy = pylab.where(energy == 0, pylab.finfo(float).eps, energy) # if energy is zero, we get problems with log\n fb = get_filterbanks(nfilt, nfft, samplerate, lowfreq, highfreq)\n print \"len(fb) %s\"%(len(fb))\n colour = \"k-\"\n for i in range(len(fb)):\n if colour == \"k-\":\n colour = \"r-\"\n else:\n colour = \"k-\"\n startedplot = False\n midpoint = 0\n for j in range(len(fb[i])):\n if fb[i][j] > 0:\n if startedplot == False:\n startedplot = j\n if j > 0:\n pylab.plot([j-1, j], [fb[i][j-1], fb[i][j]], colour)\n if fb[i][j] == 1.0:\n midpoint = j\n else:\n if not startedplot == False:\n pylab.plot([j-1, j], [fb[i][j-1], 0], colour)\n try:\n print \"slope to midpoint %.3f, slope from midpoint %.3f\"%(1.0/float(midpoint-startedplot), 1.0/float(midpoint-j+1))\n except:\n pass\n break\n pylab.show()\n feat = pylab.dot(pspec, fb.T) # compute the filterbank energies\n feat = pylab.where(feat == 0, pylab.finfo(float).eps, feat) # if feat is zero, we get problems with log\n return feat, energy","def _get_f50_worker(self, ra, dec, wave, sncut, \n direct_sigmas = False, linewidth = None):\n\n logger = logging.getLogger(name=\"ShotSensitivity\")\n\n try:\n [x for x in ra]\n except TypeError:\n ra = array([ra]) \n dec = array([dec]) \n wave = array([wave]) \n\n coords = SkyCoord(ra=ra, dec=dec, unit=\"deg\")\n wave_rect = self.extractor.get_wave()\n pixsize_aa = wave_rect[1] - wave_rect[0]\n\n # This will give 999 once the noise is scaled suitably\n badval = 999*1e17/pixsize_aa\n\n # Size of window in wave elements\n filter_len = 2*self.wavenpix + 1\n\n if type(wave) != type(None):\n wave_passed = True\n else:\n wave_passed = False\n convolution_filter = ones(filter_len) \n mask = True*ones(len(coords), dtype=int)\n \n noise = []\n \n info_results = self.extractor.get_fiberinfo_for_coords(\n coords,\n radius=self.rad,\n ffsky=self.ffsky,\n return_fiber_info=True,\n fiber_lower_limit=2, \n verbose=False\n )\n\n id_, aseps, aifux, aifuy, axc, ayc, ara, adec, adata, aerror, afmask, afiberid, \\\n amultiframe = info_results\n \n \n I = None\n fac = None\n norm_all = []\n amp = [] \n nan_fib_mask = []\n\n for i, c in enumerate(coords):\n \n sel = (id_ == i)\n\n if type(wave) != type(None):\n logger.debug(\"Running on source {:f} {:f} {:f}\".format(ra[i], dec[i], wave[i]))\n else:\n logger.debug(\"Running on position {:f} {:f}\".format(ra[i], dec[i]))\n\n logger.debug(\"Found {:d} fibers\".format(sum(sel)))\n\n if sum(sel) > 0:\n \n # fiber properties \n xc = axc[sel][0]\n yc = ayc[sel][0]\n ifux = aifux[sel]\n ifuy = aifuy[sel]\n data = adata[sel]\n error = aerror[sel]\n fmask = afmask[sel]\n fiberid = afiberid[sel]\n multiframe = amultiframe[sel]\n seps = aseps[sel]\n\n # Flag the zero elements as bad\n fmask[(abs(data) < 1e-30) | (abs(error) < 1e-30)] = False\n\n iclosest = argmin(seps)\n\n amp.append(fiberid[iclosest])\n\n if len(self.bad_amps) > 0:\n amp_flag = amp_flag_from_fiberid(fiberid[iclosest], \n self.bad_amps)\n else:\n amp_flag = True\n \n # XXX Could be faster - reloads the file every run\n meteor_flag = meteor_flag_from_coords(c, self.shotid)\n\n if not (amp_flag and meteor_flag):\n logger.debug(\"The data here are bad, position is masked\")\n if wave_passed:\n noise.append(badval)\n norm_all.append(1.0)\n # value doesn't matter as in amp flag\n nan_fib_mask.append(True)\n continue\n else:\n mask[i] = False\n \n weights, I, fac = self.extractor.build_weights(xc, yc, ifux, ifuy, self.moffat, \n I=I, fac=fac, return_I_fac = True)\n \n # (See Greg Zeimann's Remedy code)\n # normalized in the fiber direction\n norm = sum(weights, axis=0) \n weights = weights/norm\n\n\n result = self.extractor.get_spectrum(data, error, fmask, weights,\n remove_low_weights = False,\n sclean_bad = self.sclean_bad,\n return_scleaned_mask = True)\n \n spectrum_aper, spectrum_aper_error, scleaned = [res for res in result] \n \n if wave_passed:\n \n index = where(wave_rect >= wave[i])[0][0]\n ilo = index - self.wavenpix\n ihi = index + self.wavenpix + 1\n\n # If lower index less than zero, truncate\n if ilo < 0:\n ilo = 0\n \n if ihi < 0:\n ihi = 0\n \n # Output lots of information for very detailed debugging\n if logger.getEffectiveLevel() == logging.DEBUG: \n logger.debug(\"Table of fibers:\")\n logger.debug(\"# fiberid wave_index ifux ifuy weight noise mask\")\n for fibidx, fid in enumerate(fiberid):\n for wi, (tw, tnoise, tmask) in enumerate(zip((weights*norm)[fibidx, ilo:ihi], \n error[fibidx, ilo:ihi], fmask[fibidx, ilo:ihi]), \n ilo): \n logger.debug(\"{:s} {:d} {:f} {:f} {:f} {:f} {:s}\".format(fid, wi, ifux[fibidx], \n ifuy[fibidx], tw, tnoise, \n str(tmask)))\n\n\n # Mask source if bad values within the central 3 wavebins\n nan_fib = bad_central_mask(weights*norm, logical_not(fmask), \n index) \n nan_fib_mask.append(nan_fib)\n\n # Account for NaN and masked spectral bins\n bad = isnan(spectrum_aper_error[ilo:ihi])\n goodfrac = 1.0 - sum(bad)/len(bad)\n\n\n if all(isnan(spectrum_aper_error[ilo:ihi])):\n sum_sq = badval\n else:\n sum_sq = \\\n sqrt(nansum(square(spectrum_aper_error[ilo:ihi])/goodfrac))\n\n norm_all.append(mean(norm[ilo:ihi]))\n noise.append(sum_sq)\n else:\n logger.debug(\"Convolving with window to get flux limits versus wave\")\n\n\n # Use astropy convolution so NaNs are ignored\n convolved_variance = convolve(square(spectrum_aper_error),\n convolution_filter, \n normalize_kernel=False)\n std = sqrt(convolved_variance)\n\n # Also need to convolve aperture corrections to get\n # a total apcor across the wavelength window\n convolved_norm = convolve(norm,\n convolution_filter, \n normalize_kernel=True)\n\n # To get mean account for the edges in\n # the convolution\n for iend in range(self.wavenpix):\n edge_fac = filter_len/(filter_len + iend - self.wavenpix)\n convolved_norm[iend] *= edge_fac\n convolved_norm[-iend - 1] *= edge_fac\n\n\n # Mask wavelengths with too many bad pixels\n # equivalent to nan_fib in the wave != None mode\n wunorm = weights*norm\n for index in range(len(convolved_variance)):\n if not bad_central_mask(wunorm, logical_not(fmask), index):\n std[index] = badval\n\n noise.append(std)\n norm_all.append(convolved_norm)\n \n else:\n if wave_passed:\n noise.append(badval)\n norm_all.append(1.0)\n amp.append(\"000\")\n nan_fib_mask.append(True)\n else:\n noise.append(badval*ones(len(wave_rect)))\n norm_all.append(ones(len(wave_rect)))\n amp.append(\"000\")\n mask[i] = False\n\n\n \n # Apply the galaxy mask \n gal_mask = ones(len(coords), dtype=int)\n for gal_region in self.gal_regions:\n dummy_wcs = create_dummy_wcs(gal_region.center,\n imsize=2*gal_region.height)\n # zero if near galaxy\n gal_mask = gal_mask & invert(gal_region.contains(coords, dummy_wcs))\n\n noise = array(noise)\n snoise = pixsize_aa*1e-17*noise\n\n if wave_passed:\n\n bad = (gal_mask < 0.5) | (snoise > 998) | isnan(snoise) | invert(nan_fib_mask)\n\n normnoise = snoise/norm_all\n\n if not direct_sigmas:\n normnoise = self.f50_from_noise(normnoise, wave, sncut,\n linewidth = linewidth)\n\n \n normnoise[bad] = 999.\n\n return normnoise, amp, norm_all\n\n else:\n mask[gal_mask < 0.5] = False\n \n if self.badshot:\n mask[:] = False\n\n bad = (snoise > 998) | logical_not(isfinite(snoise))\n normnoise = snoise/norm_all\n\n if not direct_sigmas:\n normnoise = self.f50_from_noise(normnoise, wave, sncut,\n linewidth = linewidth)\n\n normnoise[bad] = 999\n\n return normnoise, mask, amp, norm_all","def run(self):\n qubit = self.qubit\n\n routine = self.routine\n\n # Saving some typing for parameters that are only read ;)\n allowed_delta_f = self.get_param_value(\"allowed_delta_f\")\n f_unit = self.get_param_value(\"f_unit\")\n f_factor = self.get_param_value(\"f_factor\")\n delta_f_unit = self.get_param_value(\"delta_f_unit\")\n delta_f_factor = self.get_param_value(\"delta_f_factor\")\n max_iterations = self.get_param_value(\"max_iterations\")\n transition = self.get_param_value(\"transition_name\")\n\n # Finding the ramsey experiment in the pipulse calibration\n pipulse_calib = routine.routine_steps[-1]\n ramsey = pipulse_calib.routine_steps[-1]\n\n # Transition frequency from last Ramsey\n freq = qubit[f\"{transition}_freq\"]()\n\n # Retrieving the frequency difference\n max_waiting_seconds = self.get_param_value(\"max_waiting_seconds\")\n for i in range(max_waiting_seconds):\n try:\n routine.delta_f = (\n ramsey.analysis.proc_data_dict[\n \"analysis_params_dict\"][\n qubit.name][\"exp_decay\"][\"new_qb_freq\"] -\n ramsey.analysis.proc_data_dict[\n \"analysis_params_dict\"][\n qubit.name][\"exp_decay\"][\"old_qb_freq\"])\n break\n except KeyError:\n log.warning(\n \"Could not find frequency difference between current \"\n \"and last Ramsey measurement, delta_f not updated\")\n break\n except AttributeError:\n # FIXME: Unsure if this can also happen on real set-up\n log.warning(\n \"Analysis not yet run on last Ramsey measurement, \"\n \"frequency difference not updated\")\n time.sleep(1)\n\n # Progress update\n if self.get_param_value('verbose'):\n print(f\"Iteration {routine.iteration}, {transition}-freq \"\n f\"{freq / f_factor} {f_unit}, frequency \"\n f\"difference = {routine.delta_f / delta_f_factor} \"\n f\"{delta_f_unit}\")\n\n # Check if the absolute frequency difference is small enough\n if np.abs(routine.delta_f) < allowed_delta_f:\n # Success\n if self.get_param_value('verbose'):\n print(f\"{transition}-frequency found to be \"\n f\"{freq / f_factor} {f_unit} within \"\n f\"{allowed_delta_f / delta_f_factor} \"\n f\"{delta_f_unit} of previous value.\")\n\n elif routine.iteration < max_iterations:\n # No success yet, adding a new rabi-ramsey and decision step\n if self.get_param_value('verbose'):\n print(f\"Allowed error (\"\n f\"{allowed_delta_f / delta_f_factor} \"\n f\"{delta_f_unit}) not yet achieved, adding new\"\n \" round of PiPulse calibration...\")\n\n routine.add_next_pipulse_step()\n\n step_settings = {'qubits': self.qubits}\n routine.add_step(\n FindFrequency.Decision,\n 'decision',\n step_settings,\n )\n\n routine.iteration += 1\n return\n\n else:\n # No success yet, reached max iterations\n msg = (f\"{self.step_label} routine finished for {qubit.name}, \"\n \"desired precision not necessarily achieved within the \"\n f\"maximum number of iterations ({max_iterations}).\")\n log.warning(msg)\n\n if self.get_param_value('verbose'):\n print(msg)\n\n if self.get_param_value('verbose'):\n # Printing termination update\n print(f\"FindFrequency routine finished: \"\n f\"{transition}-frequencies for {qubit.name} \"\n f\"is {freq / f_factor} {f_unit}.\")","def spectrum(datapath, run, forcebins = False):\n runpath = datapath + '/' + run\n events = [evnt for evnt in listdir(runpath) if not isfile(join(runpath,evnt))]\n allTraces = []\n total_time = 0\n pulses = {'zero': [], 'one': [], 'two': [], 'three': [], 'other': []}\n times = {'zero': [], 'one': [], 'two': [], 'three': [], 'other': []}\n #camextratime = 25e-6\n for event in events:\n if int(event)> 3:\n break\n print(event)\n e = sbc.DataHandling.GetSBCEvent.GetEvent(runpath,event)\n if e[\"slowDAQ\"][\"loaded\"]:\n #print(e[\"fastDAQ\"].keys())\n cgate = e[\"fastDAQ\"][\"CAMgate\"]\n #dcam = np.diff(cgate)\n fdt = e['fastDAQ']['time']\n #camOffTimes = np.sort(np.array([fdt[i] for i in range(len(dcam)) if dcam[i] > 0.5]))\n \n #camOnTimes = np.sort(np.array([fdt[i] for i in range(len(dcam)) if dcam[i] < 0.5]))\n fddt = fdt[1]-fdt[0]\n tfast = fdt[-1]-fdt[0]\n LED_on = [fdt[i] for i in range(len(cgate)) if cgate[i]<-0.5]\n blockedFraction = ((len(LED_on)*fddt))/tfast\n print(blockedFraction)\n tr = e[\"PMTtraces\"]\n trac = tr[\"traces\"]\n dt = tr[\"dt\"]\n #event_time = (tr['t0_sec'][-1]+tr['t0_frac'][-1]-tr['t0_sec'][0] - tr['t0_frac'][0])[0]\n event_time = (((e[\"slowDAQ\"][\"elapsed_time\"][-1]-e[\"slowDAQ\"][\"elapsed_time\"][0]))*(1-blockedFraction))\n #print(event_time)\n total_time += event_time\n\n #f,axes = plt.subplots(1,5,sharey=True)\n #f.suptitle(runpath+\"/\"+str(event))\n #pmttracetime = e[\"PMTtraces\"][\"t0_sec\"][:,0]+e[\"PMTtraces\"][\"t0_frac\"][:,0]\n #d=sbc.AnalysisModules.PMTfastDAQalignment.PMTandFastDAQalignment(e)\n #pmtalign = d[\"PMT_trigt0_sec\"]+d[\"PMT_trigt0_frac\"]\n #tracetimes = pmttracetime - pmtalign\n #camoffindex = 0\n #camonindex = 0\n for i in range(len(trac)):\n #print(i)\n \"\"\"\n thistracetime = tracetimes[i]\n \n #nearestcamoff = min(camOffTimes, key=lambda x:abs(x-thistracetime))\n #nearestcamon = min(camOnTimes, key=lambda x:abs(x-thistracetime))\n print(camOffTimes[camoffindex])\n print(thistracetime)\n if thistracetime > camOffTimes[camoffindex]:\n camoffindex += 1\n if thistracetime > camOnTimes[camonindex]:\n camonindex += 1 \n if camoffindex<len(camOffTimes)-1:\n if abs(camOffTimes[camoffindex]-thistracetime)<camextratime:\n print('excluding a trace near a camera off')\n continue\n if camonindex<len(camOnTimes)-1:\n if abs(camOnTimes[camonindex]-thistracetime)<camextratime:\n print('excluding a trace near a camera on')\n continue\n \"\"\"\n trace = np.fabs(trac[i][0])\n if max(trace) == 128:\n trace = stitchTraces(trace,np.fabs(e[\"PMTtraces\"][\"traces\"][i][1]))\n dt_tr = dt[i][0]\n\n # populate dictionaries arrays based on how many pulses there were\n [a,n,totInt,pktimes] = SBC_pulse_integrator_bressler(trace,dt_tr)\n if n == 0:\n number = 'zero'\n allTraces.append(a)\n elif n == 1:\n number = 'one'\n allTraces.append(a)\n times['one'].append(pktimes[0])\n elif n == 2:\n number = 'two'\n allTraces.append(a)\n elif n == 3:\n number = 'three'\n allTraces.append(a)\n else:\n number = 'other'\n allTraces.append(a)\n \"\"\"\n #if a != None:\n if isZero:\n if j < 5:\n if isNegative:\n if random() >0:\n print(runpath+\"/\"+str(event)+\" pmt trace \"+str(i))\n tPMT = np.arange(len(trace))*dt_tr\n axes[j].plot(tPMT,trace,lw=3)\n axes[j].set_xlabel(\"time (s)\",fontsize=25)\n axes[j].set_ylabel(\"PMT response (ADC)\",fontsize=25)\n j+=1\n \n \n plt.show\n \"\"\"\n pulses[number].append(a)\n gc.collect()\n \n \n for k in pulses:\n pulses[k] = [x for x in pulses[k] if x != None]\n \n allTraces = [x for x in allTraces if x != None]\n \n plt.figure()\n\n Nbins = int(np.floor(np.sqrt(len(allTraces))))\n allvals, bins, _ = plt.hist(allTraces,Nbins,label='all traces')\n \n areaVals = {'zero': [], 'one': [], 'two': [], 'three': [], 'other': []}\n for k in pulses:\n if k != 'other':\n areaVals[k], _, _ = plt.hist(pulses[k],bins,histtype = 'step',\n linewidth = 3,label= k+' hits')\n plt.legend(fontsize=12)\n plt.show() \n #spe_spectrum = areaVals['one']\n \n #def gaussian(x,mu,sigma,amplitude):\n # return amplitude * np.exp(-((x - mu) /(np.sqrt(2)* sigma))**2 )\n \n #params_spe, params_cov_spe = scipy.optimize.curve_fit(gaussian,bins[:len(areaVals['one'])],\n # spe_spectrum,\n # p0=[0.4e8,1e7,40])\n #params_twohits, params_cov_twohits = scipy.optimize.curve_fit(gaussian,\n # bins[:len(areaVals['two'])],\n # areaVals['two'],\n # p0=[0.8e8,1e7,10])\n #mu_spe = params_spe[0]\n #mu_2 = params_twohits[0] - mu_spe\n #print(mu_spe)\n #print(mu_2)\n \n #mu_avg = (mu_spe + mu_2)*0.5\n #mu_avg = get_gain(datapath,run)\n mu_avg = 1e7\n print(mu_avg)\n\n \n plt.figure()\n plt.grid(True)\n if isinstance(forcebins,np.ndarray):\n bins=forcebins\n fullspect,_,_=plt.hist([t/mu_avg for t in allTraces],\n forcebins,label='all traces')\n \n else:\n fullspect,bins,_=plt.hist([t/mu_avg for t in allTraces],\n int(np.floor(np.sqrt(len(allTraces)))),label='all traces')\n \n #print(bins)\n plt.yscale('log')\n plt.xlabel('phe based on a gain of '+str(mu_avg)+' electrons per phe')\n plt.legend()\n plt.show\n print(sum(fullspect)/total_time)\n print(\"The Total Exposure Time of run \"+str(runpath)+ \" was \"+str(total_time)+\" Seconds\")\n print(\"The overall PMT trigger rate was \" + str(len(allTraces)/total_time)+ \"Hz\")\n return [fullspect,bins,total_time]","def bf_analysis():\r\n\r\n global params\r\n n = params['n']\r\n level = params['level']\r\n bfmin = params['bfmin']\r\n bfmax = params['bfmax']\r\n bfstep = params['bfstep']\r\n ns = params['ns']\r\n po = params['po']\r\n pe = params['pe']\r\n pf = params['pf']\r\n bf_dir = create_dir(TIMES_PATH + 'bf')\r\n filename = datetime.datetime.now().strftime(DATE_FORMAT) + '.csv'\r\n with open(bf_dir + filename, 'wb') as csvfile:\r\n fw = csv.writer(csvfile)\r\n fw.writerow(('lv', 'ns', 'bf', 'nt', 'no', 'ne', 'nf',\r\n 'method1', 'method2', 'method3_1', 'method3_2'))\r\n bf = bfmin\r\n while bf <= bfmax:\r\n nt = int(round(bf * ns))\r\n no = max(int(round(po * nt)), 1)\r\n ne = max(int(round(pe * no)), 1)\r\n nf = max(int(round(pf * nt)), 1)\r\n times = [0] * 4\r\n for i in range(n):\r\n times = map(sum, zip(times, get_times(level, ns, nt, no, ne, nf)))\r\n show_progress('bf', bf, bfmin, bfmax, bfstep, i, n)\r\n times = map(lambda x: float(x) / n, times)\r\n fw.writerow((level, ns, bf, nt, no, ne, nf) + tuple(times))\r\n bf += bfstep\r\n csvfile.close()","def bruno_mes(self):\n MI = -125\n MA = 125\n INCR = 19\n####################################################################\n ### CHANNEL 1\n self.write('CHN 1')\n self.write('CHN?')\n print 'Acting on channel:',self.read()\n self.write('WAVE ARB')\n self.write('ARBLOAD ARB1')\n self.write('FREQ 100')\n self.write('DCOFFS 0.05')\n self.write('AMPL 0.1')\n \n l =(125,-125,125)#arange(MI,MA,INCR) # the ramp\n# lll = copy(l)[::-1][1:-1]\n# l = concatenate((l,lll))\n self.write_array_to_byte(l,1)","def test_baseline_spect(self, b0, x0, a, fwhm):\n x = np.linspace(-1, 1, 100)\n sigma = fwhm / np.sqrt(8 * np.log(2))\n y = a * np.exp(-((x - x0) ** 2) / (2 * sigma**2)) + b0\n\n b0_guess = guess.constant_spectral_offset(y)\n\n self.assertAlmostEqual(b0, b0_guess, delta=0.1)","def calculate(self):","def calculate_fmin_Band(self):\n if self.F0 is None and self.Band is not None:\n raise ValueError(\"Band option can only be set if F0 is also given.\")\n elif self.F0 is not None and self.Band is not None:\n self.fmin = self.F0 - 0.5 * self.Band\n elif self.noiseSFTs and not self.mfd.endswith(\"v4\"):\n logger.info(\"Generating SFTs with full bandwidth from noiseSFTs.\")\n elif self.F0 is None:\n err_msg = \"Need F0 and Band,\"\n if not self.mfd.endswith(\"v4\"):\n err_msg += \" or noiseSFTs,\"\n err_msg += \" or at least F0 to auto-estimate bandwidth around it.\"\n if self.mfd.endswith(\"v4\"):\n err_msg += (\n f\" Since we are using {self.mfd}, we need this even with noiseSFTs.\"\n )\n raise ValueError(err_msg)\n else:\n extraBins = (\n # matching extraBinsFull in XLALCreateFstatInput():\n # https://lscsoft.docs.ligo.org/lalsuite/lalpulsar/_compute_fstat_8c_source.html#l00490\n lalpulsar.FstatOptionalArgsDefaults.Dterms\n + int(lalpulsar.FstatOptionalArgsDefaults.runningMedianWindow / 2)\n + 1\n )\n logger.info(\n \"Estimating required SFT frequency range from properties\"\n \" of signal to inject plus {:d} extra bins either side\"\n \" (corresponding to default F-statistic settings).\".format(extraBins)\n )\n minCoverFreq, maxCoverFreq = utils.get_covering_band(\n tref=self.tref,\n tstart=self.tstart,\n tend=self.tend,\n F0=self.F0,\n F1=self.F1,\n F2=self.F2,\n F0band=0.0,\n F1band=0.0,\n F2band=0.0,\n maxOrbitAsini=getattr(self, \"asini\", 0.0),\n minOrbitPeriod=getattr(self, \"period\", 0.0),\n maxOrbitEcc=getattr(self, \"ecc\", 0.0),\n )\n self.fmin = minCoverFreq - extraBins / self.Tsft\n self.Band = maxCoverFreq - minCoverFreq + 2 * extraBins / self.Tsft\n if hasattr(self, \"fmin\"):\n logger.info(\n \"Generating SFTs with fmin={}, Band={}\".format(self.fmin, self.Band)\n )","def spectral_check(self, ):\r\n a, b = self.dfa, self.dfm.copy()\r\n b['ts_a']=a.ts\r\n b['flux_a'] = a.flux\r\n b['dflux'] = (b.flux-b.flux_a)/b.flux_unc\r\n b['eflux100_a'] = a.eflux100\r\n b['deflux'] = (b.eflux100-b.eflux100_a)/b.eflux100_unc\r\n b['pindex_a'] = a.pindex\r\n b['gdelta'] = (b.pindex-b.pindex_a)/b.pindex_unc\r\n self.dfm = b # since copy\r\n\r\n fig,axx = plt.subplots(1,2, figsize=(10,5), sharey=True)\r\n hkw = dict(bins=np.linspace(-5,5,51), histtype='step', lw=2, density=True)\r\n\r\n cut = (b.ts>50) & ~pd.isnull(b.deflux) & ~pd.isnull(b.gdelta) &\\\r\n (b.modelname==\"LogParabola\") & (b.pindex<3) & (b.pindex>0.5) &\\\r\n (b.e0>500) &(b.eflux100_unc>0) &(b.pindex_unc>0)\r\n self.check_total = sum(cut)\r\n for ax, title, val in zip(axx.flatten(), ['Energy Flux', 'Spectral index'], [b.deflux, b.gdelta]): \r\n\r\n df=val[cut]\r\n ax.hist(df.clip(-5,5), label='mean {:5.2f}\\nstd {:5.2f}'.format(df.mean(),df.std()), **hkw);\r\n ax.grid(alpha=0.5); \r\n x=np.linspace(-4,4)\r\n ax.plot(x, stats.norm.pdf(x), '--g' );\r\n ax.set(xlabel='normalized fit deviation', title=title, )\r\n ax.legend(loc='upper left',prop=dict(family='monospace'))\r\n fig.suptitle('Normalized devations of fit from model', fontsize=16);\r\n\r\n return fig","def brate(self):\n try:\n return self.pos / self.runtime\n except ZeroDivisionError:\n return 0","def test_filt_abmag(self):\n sun = Sun.from_builtin('E490_2014')\n V = get_bandpass('johnson v')\n wave, fluxd = sun.filt(V, unit=u.ABmag)\n assert np.isclose(fluxd.value, -26.77, atol=0.007)","def detect_bispectra(self, sigma=5., tol=1.3, Q=0, show=0, save=0):\n try:\n ba = self.bispectra\n except AttributeError:\n print 'Need to make bispectra first.'\n return\n\n# ntr = lambda num: num*(num-1)*(num-2)/6 # theoretical number of triples\n ntr = lambda num: len(self.triples) # consider possibility of zeros in data and take mean number of good triples over all times\n\n # using s=S/Q\n# mu = lambda s: s/(1+s) # for independent bispectra, as in kulkarni 1989\n mu = lambda s: 1. # for bispectra at high S/N from visibilities?\n sigbQ3 = lambda s: n.sqrt((1 + 3*mu(s)**2) + 3*(1 + mu(s)**2)*s**2 + 3*s**4) # from kulkarni 1989, normalized by Q**3, also rogers et al 1995\n s = lambda basnr, nants: (2.*basnr/n.sqrt(ntr(nants)))**(1/3.)\n\n # measure SNR_bl==Q from sigma clipped times with normal mean and std of bispectra. put into time,dm order\n bamean = ba.real.mean(axis=1)\n bastd = ba.real.std(axis=1)\n\n (meanmin,meanmax) = sigma_clip(bamean) # remove rfi\n (stdmin,stdmax) = sigma_clip(bastd) # remove rfi\n clipped = n.where((bamean > meanmin) & (bamean < meanmax) & (bastd > stdmin) & (bastd < stdmax) & (bamean != 0.0))[0] # remove rf\n\n bameanstd = ba[clipped].real.mean(axis=1).std()\n basnr = bamean/bameanstd\n if Q:\n print 'Using given Q =', Q\n else:\n Q = ((bameanstd/2.)*n.sqrt(ntr(self.nants)))**(1/3.)\n # Q = n.median( bastd[clipped]**(1/3.) ) # alternate for Q\n print 'Estimating noise per baseline from data. Q =', Q\n self.Q = Q\n\n # detect\n cands = n.where( (bastd/Q**3 < tol*sigbQ3(s(basnr, self.nants))) & (basnr > sigma) )[0] # define compact sources with good snr\n print cands\n\n # plot snrb lc and expected snr vs. sigb relation\n if show or save:\n p.figure()\n ax = p.axes()\n p.subplot(211)\n p.title(str(self.nskip/self.nbl)+' nskip, ' + str(len(cands))+' candidates', transform = ax.transAxes)\n p.plot(basnr, 'b.')\n if len(cands) > 0:\n p.plot(cands, basnr[cands], 'r*')\n p.ylim(-2*basnr[cands].max(),2*basnr[cands].max())\n p.xlabel('Integration')\n p.ylabel('SNR$_{bisp}$')\n p.subplot(212)\n p.plot(bastd/Q**3, basnr, 'b.')\n\n # plot reference theory lines\n smax = s(basnr.max(), self.nants)\n sarr = smax*n.arange(0,51)/50.\n p.plot(sigbQ3(sarr), 1/2.*sarr**3*n.sqrt(ntr(self.nants)), 'k')\n p.plot(tol*sigbQ3(sarr), 1/2.*sarr**3*n.sqrt(ntr(self.nants)), 'k--')\n p.plot(bastd[cands]/Q**3, basnr[cands], 'r*')\n\n if len(cands) > 0:\n p.axis([0, tol*sigbQ3(s(basnr[cands].max(), self.nants)), -0.5*basnr[cands].max(), 1.1*basnr[cands].max()])\n\n # show spectral modulation next to each point\n for candint in cands:\n sm = n.single(round(self.specmod(candint),1))\n p.text(bastd[candint]/Q**3, basnr[candint], str(sm), horizontalalignment='right', verticalalignment='bottom')\n p.xlabel('$\\sigma_b/Q^3$')\n p.ylabel('SNR$_{bisp}$')\n if save:\n if save == 1:\n savename = self.file.split('.')[:-1]\n savename.append(str(self.nskip/self.nbl) + '_bisp.png')\n savename = string.join(savename,'.')\n elif isinstance(save, string):\n savename = save\n print 'Saving file as ', savename\n p.savefig(self.pathout+savename)\n\n return basnr[cands], bastd[cands], cands","def _calibrate_measurement(self):\n\n cold_blackbody = bb_radiance(self.cbb.header.cbb_temperature + 273.15,\n self.cbb.data.wavelength)\n warm_blackbody = bb_radiance(self.wbb.header.wbb_temperature + 273.15,\n self.wbb.data.wavelength)\n\n self.wbb.data.average_spectrum[0] = 1\n self.wbb.data.average_spectrum[2047] = 1\n\n calibration_slope = ((warm_blackbody - cold_blackbody) /\n (self.wbb.data.average_spectrum - self.cbb.data.average_spectrum))\n calibration_offset = warm_blackbody - (self.wbb.data.average_spectrum * \n calibration_slope)\n\n self.wbb.calibrate_file(calibration_slope, calibration_offset)\n self.cbb.calibrate_file(calibration_slope, calibration_offset)\n self.sam.calibrate_file(calibration_slope, calibration_offset)\n\n if not self.dwr is None:\n self.dwr.calibrate_file(calibration_slope, calibration_offset)\n\n plate_temperature = self.dwr.header.spare_f[0]\n if (self.plate == -1) :\n plate_emissivity = self.dwr.header.spare_f[1]\n\n plate_blackbody = bb_radiance(plate_temperature + 273.15,\n self.dwr.data.wavelength)\n plate_emission = plate_emissivity * plate_blackbody\n\n self.dwr.data.average_spectrum = ((self.dwr.data.average_spectrum - \n plate_emission) / (1 - plate_emissivity))","def query(self):\n self._measurements[self.KEY_FMIX].df = self.fetch_data_fmix()\n self._measurements[self.KEY_EMIS].df = self.co2_calc(self._measurements[self.KEY_FMIX].df)","def retarder(self):\n self.spectrum = self.spectrum","def calculate(self, raw=False):\n \n with energy_units(\"int\"):\n if self.system is not None:\n if isinstance(self.system,Molecule):\n #self._calculate_Molecule(rwa) \n spect = self._calculate_monomer(raw=raw)\n elif isinstance(self.system, Aggregate):\n spect = self._calculate_aggregate( \n relaxation_tensor=\n self._relaxation_tensor,\n rate_matrix=\n self._rate_matrix,\n relaxation_hamiltonian=\n self._relaxation_hamiltonian,\n raw=raw)\n else:\n raise Exception(\"System to calculate spectrum for not defined\")\n \n return spect","def make_bispectra(self, bgwindow=4):\n\n bisp = lambda d, ij, jk, ki: d[:,ij] * d[:,jk] * n.conj(d[:,ki]) # bispectrum for pol data\n# bisp = lambda d, ij, jk, ki: n.complex(d[ij] * d[jk] * n.conj(d[ki])) # without pol axis\n\n triples = self.make_triples()\n meanbl = self.data.mean(axis=2).mean(axis=0) # find bls with no zeros in either pol to ignore in triples\n self.triples = triples[n.all(meanbl[triples][:,0] != 0j, axis=1) & n.all(meanbl[triples][:,1] != 0j, axis=1) & n.all(meanbl[triples][:,2] != 0j, axis=1)] # only take triples if both pols are good. may be smaller than set for an individual pol\n\n # set up arrays for bispectrum and for weighting data (ignoring zeros)\n bispectra = n.zeros((len(self.dmarr), len(self.data), len(self.triples)), dtype='complex')\n truearr = n.ones( (self.npol, self.nbl, len(self.chans)))\n falsearr = n.zeros( (self.npol, self.nbl, len(self.chans)))\n\n # iterate over dm trials and integrations\n for d in xrange(len(self.dmarr)):\n twidth = n.round(self.twidths[d])\n dmwidth = int(n.round(n.max(self.dmtrack0[d][0]) - n.min(self.dmtrack0[d][0])))\n\n for i in xrange((bgwindow/2)+twidth, len(self.data)-( (bgwindow/2)+2*twidth+dmwidth )): # dmwidth avoided at end, others are split on front and back side of time iteration\n# for i in xrange((bgwindow/2)+twidth, len(self.data)-( (bgwindow/2)+twidth+dmwidth ), max(1,twidth/2)): # can step by twidth/2, but messes up data products\n diff = self.tracksub(d, i, bgwindow=bgwindow)\n\n if len(n.shape(diff)) == 1: # no track\n continue\n\n# **need to redo for self.flags**\n weightarr = n.where(diff != 0j, truearr, falsearr) # ignore zeros in mean across channels # bit of a hack\n try:\n diffmean = n.average(diff, axis=2, weights=weightarr)\n except ZeroDivisionError:\n diffmean = n.mean(diff, axis=2) # if all zeros, just make mean # bit of a hack\n\n for trip in xrange(len(self.triples)):\n ij, jk, ki = self.triples[trip]\n bispectra[d, i, trip] = bisp(diffmean, ij, jk, ki).mean(axis=0) # Stokes I bispectrum. Note we are averaging after forming bispectrum, so not technically a Stokes I bispectrum.\n print 'dedispersed for ', self.dmarr[d]\n self.bispectra = n.ma.masked_array(bispectra, bispectra == 0j)","def calculate(self):\n\n beta = 1 # or 0.5 or 2 can also calculate F2 or F0.5 measure\n\n beta_squared = beta * beta\n precision = Precision()\n precision.confusion_matrix = self.confusion_matrix\n precision = precision.calculate()\n recall = Recall()\n recall.confusion_matrix = self.confusion_matrix\n recall = recall.calculate()\n\n denominator = beta_squared * precision + recall\n\n if denominator != 0:\n return (1 + beta_squared) * ((precision * recall) / denominator)\n else:\n return 0","def Bo_Bosol_calc(self):\n self.Bosol = (self.g*self.alpha * self.srflx ) \n #ZEROS FOR T3W APPLICATION\n self.Bo = np.zeros([self.b.shape[0]])","def calc(self):\n\n # the following if query ensures that volume- and interaction-terms\n # are only calculated if tau > 0.\n # (to avoid nan-values from invalid function-evaluations)\n\n if self.V.tau.shape == (1,):\n Isurf = self.surface()\n # differentiation for non-existing canopy, as otherwise NAN values\n if self.V.tau > 0.:\n Ivol = self.volume()\n if self.int_Q is True:\n Iint = self.interaction()\n else:\n Iint = np.array([0.])\n else:\n Ivol = np.array([0.])\n Iint = np.array([0.])\n else:\n # calculate surface-term (valid for any tau-value)\n Isurf = self.surface()\n\n # store initial parameter-values\n old_t_0 = self.t_0\n old_p_0 = self.p_0\n old_t_ex = self.t_ex\n old_p_ex = self.p_ex\n\n old_tau = self.V._get_tau()\n old_omega = self.V._get_omega()\n old_NN = self.SRF._get_NormBRDF()\n\n # set mask for tau > 0.\n mask = old_tau > 0.\n valid_index = np.where(mask)\n inval_index = np.where(~mask)\n\n # set parameter-values to valid values for calculation\n self.t_0 = old_t_0[valid_index[0]]\n self.p_0 = old_p_0[valid_index[0]]\n self.t_ex = old_t_ex[valid_index[0]]\n self.p_ex = old_p_ex[valid_index[0]]\n\n # squeezing the arrays is necessary since the setter-function for\n # tau, omega and NormBRDF automatically adds an axis to the arrays!\n self.V.tau = np.squeeze(old_tau[valid_index[0]])\n if np.array(self.V.omega).size != 1:\n self.V.omega = np.squeeze(old_omega[valid_index[0]])\n if np.array(self.SRF.NormBRDF).size != 1:\n self.SRF.NormBRDF = np.squeeze(old_NN[valid_index[0]])\n\n # calculate volume and interaction term where tau-values are valid\n _Ivol = self.volume()\n if self.int_Q is True:\n _Iint = self.interaction()\n else:\n _Iint = np.full_like(self.t_0, 0.)\n\n # reset parameter values to old values\n self.t_0 = old_t_0\n self.p_0 = old_p_0\n self.t_ex = old_t_ex\n self.p_ex = old_p_ex\n\n # squeezing the arrays is necessary since the setter-function for\n # tau, omega and NormBRDF automatically add an axis to the arrays!\n self.V.tau = np.squeeze(old_tau)\n self.V.omega = np.squeeze(old_omega)\n self.SRF.NormBRDF = np.squeeze(old_NN)\n\n # combine calculated volume-contributions for valid tau-values\n # with zero-arrays for invalid tau-values\n Ivol = np.ones_like(self.t_0)\n Ivol[valid_index[0]] = _Ivol\n Ivol[inval_index[0]] = np.ones_like(Ivol[inval_index[0]]) * 0.\n\n # combine calculated interaction-contributions for valid tau-values\n # with zero-arrays for invalid tau-values\n if self.int_Q is True:\n Iint = np.ones_like(self.t_0)\n Iint[valid_index[0]] = _Iint\n Iint[inval_index[0]] = np.ones_like(Iint[inval_index[0]]) * 0.\n else:\n Iint = np.full_like(self.t_0, 0.)\n\n return Isurf + Ivol + Iint, Isurf, Ivol, Iint","def spectate(self):\n pass","def band_penalty(self):\n fc_ix = np.argmin(np.abs(self.f - self.fc)) # Index to frequency array closes to center frequency\n # Number of indexes on each side of center frequency, not extending outside, only up to 10 kHz\n n = min(fc_ix, self.ix10k - fc_ix)\n if n == 0:\n return 0.0\n return np.mean(np.square(self.fr[fc_ix - n:fc_ix] - self.fr[fc_ix + n - 1:fc_ix - 1:-1]))","def get_b(self):\n return ((self.b_plus_bstar / self.n_pos) + (self.b_minus_bstar / self.n_neg)) / 2","def run(self, freqs, b='disc', scale=False, get_alpha='calc', save_alpha='none',\n freqUnit='GHz', block=[1, 1], reuse_override='check'):\n get_alpha = self.alpha_options[get_alpha[0].lower()]\n save_alpha = self.alpha_options[save_alpha[0].lower()]\n freqs, freqUnit = self.set_freqs(freqs=freqs, freqUnit=freqUnit)\n reuse = self.check_reuse(freqs, scale, get_alpha, save_alpha,\n reuse_override=reuse_override.lower())\n C_timer = datetime.datetime.now()\n if not reuse:\n self.freqs = freqs\n self.freqUnit = utils.proc_unit(freqUnit)\n self.scale = scale\n self.get_alpha = get_alpha\n self.save_alpha = save_alpha\n if self.verbose:\n s = '{} at {} frequencies ({} - {} {})'.format(self.planet, len(freqs),\n freqs[0], freqs[-1],\n utils.proc_unit(freqUnit))\n else:\n s = '{} at {} {}'.format(self.planet, freqs[0], utils.proc_unit(freqUnit))\n self.log.add(s, self.verbose)\n self.alpha_layers(freqs=self.freqs, atmos=self.atmos,\n scale=scale, get_alpha=get_alpha, save_alpha=save_alpha)\n D_timer = datetime.datetime.now()\n if self.verbose:\n print(\"Absoprtion calc took {:.1f} s\".format(utils.timer(D_timer - C_timer)))\n self.set_b(b=b, block=block)\n brtplt, datplt = self.set_bright_plots()\n is_img = self.set_image()\n\n # Loop over b values\n self.init_run()\n runStart = datetime.datetime.now()\n self.log.add('Run start ' + str(runStart), False)\n for i, bv in enumerate(self.b):\n # Figure out which alpha to use for this b. For now only one.\n j = self.map_b_to_atm(bv)\n is_img.i = i\n if self.verbose == 'loud':\n print('{} of {} (view {}) '.format(i + 1, len(self.b), bv), end='')\n self.bright_run(b=bv, freqs=self.freqs, atm=self.atmos[j], alpha=self.alpha[j],\n is_img=is_img, brtplt=brtplt)\n runStop = datetime.datetime.now()\n missed_planet = self.rNorm is None\n self.set_header(missed_planet, runStart, runStop)\n self.log.add('Run stop ' + str(runStop), False)\n self.populate_data_return(runStart, runStop)\n if self.verbose:\n print(\"RT calc took {:.1f} s\".format(utils.timer(runStop - runStart)))\n\n # ##Write output files\n if self.config.write_output_files:\n output_file = '{}_{}{}{}.dat'.format(self.planet, self.data_type, is_img.block,\n runStart.strftime(\"%Y%m%d_%H%M%S\"))\n output_file = os.path.join(self.config.output_directory, output_file)\n if self.verbose == 'loud':\n print('\\nWriting {} data to {}'.format(self.data_type, output_file))\n self.fIO.write(output_file, self.data_return)\n\n if brtplt is not None:\n brtplt.alpha()\n if self.data_type == 'spectrum' or self.data_type == 'profile' and len(freqs) > 1:\n datplt.Tb()\n if self.data_type == 'profile':\n datplt.profile()\n datplt.show()\n\n return self.data_return","def exercise2b(self):\n self.b2 = calibrate_image(self.b1)\n plt.axis('off')\n plt.imshow(self.b2)\n plt.show()\n misc.imsave(\"B2.png\", self.b2)\n misc.imsave(\"B2_Brightness.png\", print_brightness(self.b2))","def do_fft(self):\n start = time.time()\n self.record_chunk()\n self.window()\n self.calculate_mags()\n end = time.time()","def integrate_spectrum(self):\n flux = sum(self.spectrum)\n return flux","def compute(self):\n Y = self.data[1]\n # Create an order 3 lowpass butterworth filter\n b, a = signal.butter(3, 0.05)\n # Apply the filter to Y. Use lfilter_zi to choose the initial condition of the filter\n zi = signal.lfilter_zi(b, a)\n z, _ = signal.lfilter(b, a, Y, zi=zi * Y[0])\n # Apply the filter again, to have a result filtered at an order the same as filtfilt\n z2, _ = signal.lfilter(b, a, z, zi=zi * z[0])\n # Use filtfilt to apply the filter\n self.data[2] = signal.filtfilt(b, a, Y)\n self.data[3] = self.data[2] - self.data[1] - self.dataSpan * 0.3\n self.updatePlot()","def compute_rate(self):\n bg_rate = self.counts.data / self.livetime.data\n\n bg_rate /= self.counts.bin_volume\n\n bg_rate = bg_rate.to('MeV-1 sr-1 s-1')\n\n self.bg_rate.data = bg_rate\n self.bg_rate.data_err = (np.sqrt(self.counts.data) / (self.counts.bin_volume * self.livetime.data)).to(\n 'MeV-1 sr-1 s-1')","def _calc(self):\r\n tot_sum: float = 0 # ? total sum of the noise values\r\n max_amp: float = 0 # ? keep the sum in [0,1]\r\n amp: float = 1.0 # ? amplitude of each noise value\r\n freq: float = 1.0 # ? frequency for getting the detailed noise\r\n\r\n # for each octave we twice the frequency and multiply the amplitude \r\n # by persistance to get the detailed noise value\r\n # to keep the final sum value in the range [0, 1] we keep track of the \r\n # max amplitude (sum of all the amplitudes)\r\n for octave in range(self.octaves):\r\n noise_obj = PerlinNoise(self.inp_x*freq, self.inp_y*freq, self.inp_z*freq)\r\n # ? multiply the noise value by the amplitude\r\n tot_sum += noise_obj.val() * amp\r\n max_amp += amp\r\n\r\n amp *= self.persist\r\n freq *= 2.0 # double the freq each iteration\r\n\r\n # value is in the range [0,1]\r\n self.value = tot_sum / max_amp","def band_penalty(self):\n fc_ix = np.argmin(np.abs(self.f - self.fc)) # Index to frequency array closes to center frequency\n # Number of indexes on each side of center frequency, not extending outside, only up to 10 kHz\n n = min(fc_ix, self.ix10k - fc_ix)\n if n == 0:\n return 0.0\n return np.mean(np.square(self.fr[fc_ix - n:fc_ix] - (self.gain - self.fr[fc_ix + n - 1:fc_ix - 1:-1])))","def inst_bp(instrument,array=\"2\"):\n\n if instrument == \"MUSTANG2\" or instrument == \"MUSTANG\":\n srms = (300*u.um).to(\"m\") # surface RMS (microns)\n ### Reference: https://science.nrao.edu/facilities/gbt/proposing/GBTpg.pdf\n EA90 = 0.36 # Aperture efficiency at 90 GHz\n ### The beam efficiencies should be taken as 1.37* Aperture Efficiency\n R90 = np.exp(-4.0*np.pi*(srms/(const.c/(9.0e10*u.s**-1))).value) #\n Gnot = EA90/R90 # Unphysical, but see documentation...\n if instrument == \"MUSTANG2\":\n flow = 75.0 # GHz\n fhig = 105.0 # GHz\n else:\n flow = 82.5 # GHz\n fhig = 97.5 # GHz\n \n farr = np.arange(flow,fhig,1.0) # frequency array.\n tran = farr*0.0 + 1.0 # Let the transmission be unity everywhere.\n Larr = const.c.value/(farr*1.0e9) # Keep calm and carry on.\n ### Old formula:\n #Ruze = Gnot * np.exp(-4.0*np.pi*(srms.value)/Larr)\n ### Correct formula: (10 April 2018)\n Ruze = Gnot * np.exp(-(4.0*np.pi*srms.value/Larr)**2)\n NRuz = Ruze / np.max(Ruze) # Normalize it\n band = tran * Ruze # Bandpass, with (unnormalized) Ruze efficiency\n \n if instrument == \"NIKA2\" or instrument == \"NIKA\":\n caldir='/home/romero/NIKA2/NIKA_SVN/Processing/Pipeline/Calibration/BP/'\n bpfile=caldir+'Transmission_2017_Jan_NIKA2_v1.fits'\n hdulist = fits.open(bpfile)\n\n if array == \"1H\": # 1mm (260 GHz) array, Horizontal Polarization\n tbdata = hdulist[1].data # 1H\n freq = tbdata.field(0)\n tran = tbdata.field(1)\n erro = tbdata.field(2)\n atmt = tbdata.field(3)\n cfreq1h = np.sum(freq*tran)/np.sum(tran)\n \n if array == \"1V\": # 1mm (260 GHz) array, Vertical Polarization\n tbdata = hdulist[2].data # 1V\n freq = tbdata.field(0)\n tran = tbdata.field(1)\n erro = tbdata.field(2)\n atmt = tbdata.field(3)\n cfreq1v = np.sum(freq*tran)/np.sum(tran)\n \n if array == \"2\": # 2mm (150 GHz) array\n tbdata = hdulist[3].data # 2\n freq = tbdata.field(0)\n tran = tbdata.field(1)\n erro = tbdata.field(2)\n atmt = tbdata.field(3)\n cfreq2 = np.sum(freq*tran)/np.sum(tran)\n\n ### Trim the zero-frequency listing, if any.\n gi=np.where(freq > 0)\n freq = freq[gi]\n tran = tran[gi]\n erro = erro[gi]\n atmt = atmt[gi]\n \n### Calculate Aperture efficiencies from information found at:\n### http://www.iram.es/IRAMES/mainwiki/Iram30mEfficiencies\n Beff = 0.630 # at 210 GHz\n Aeff = Beff/1.27 # See text on webpage\n srms = (66.0*u.um).to(\"m\") # surface RMS (microns)\n R210 = np.exp(-4.0*np.pi*(srms/(const.c/(2.1e11*u.s**-1))).value) #\n Gnot = Aeff/R210 # Unphysical, but see documentation...\n\n Larr = const.c.value/(freq*1.0e9) # Keep calm and carry on. \n Ruze = Gnot * np.exp(-4.0*np.pi*(srms.value)/Larr)\n NRuz = Ruze / np.max(Ruze) # Normalize it\n band = tran * Ruze # Bandpass, with (unnormalized) Ruze efficiency\n farr = freq\n \n#########################################################################\n\n if instrument == 'ACT90':\n srms = (27.0*u.um).to(\"m\") # surface RMS (microns)\n EA90 = 0.95 # I'm making this number up...\n R90 = np.exp(-4.0*np.pi*(srms/(const.c/(9.0e10*u.s**-1))).value) #\n Gnot = EA90/R90 # Unphysical, but see documentation...\n flow = 65.0 # GHz\n fhig = 125.0 # GHz\n farr = np.arange(flow,fhig,1.0) # frequency array.\n freq_ref = 90.0 # I took EA90 to be a fictitious aperature efficiency at 90 GHz\n band = ruze_eff(farr,freq_ref,EA90,srms)\n\n if instrument == 'ACT150':\n srms = (27.0*u.um).to(\"m\") # surface RMS (microns)\n EA90 = 0.95 # I'm making this number up...\n R90 = np.exp(-4.0*np.pi*(srms/(const.c/(9.0e10*u.s**-1))).value) #\n Gnot = EA90/R90 # Unphysical, but see documentation...\n flow = 120.0 # GHz\n fhig = 180.0 # GHz\n farr = np.arange(flow,fhig,1.0) # frequency array.\n freq_ref = 90.0 # I took EA90 to be a fictitious aperature efficiency at 90 GHz\n band = ruze_eff(farr,freq_ref,EA90,srms)\n\n\n return band, farr","def beam(xb,yb,zb,wx,wy,wavelen):\n\n zRx = np.pi * wx**2 / wavelen\n zRy = np.pi * wy**2 / wavelen \n \n sqrtX = np.sqrt( 1 + np.power(zb/zRx,2) ) \n sqrtY = np.sqrt( 1 + np.power(zb/zRy,2) ) \n intensity = np.exp( -2.*( np.power(xb/(wx*sqrtX ),2) \\\n + np.power(yb/(wy*sqrtY),2) )) / sqrtX / sqrtY\n return intensity","def _calc_fgs_cr_mag(self, to_compute, band_series, guider_throughput, guider_gain, return_dataframe=False):\n to_return = []\n\n # Create initial dataframe\n df = pd.DataFrame(GSC_BAND_WAVELENGTH, columns=['Wavelength'], index=GSC_BAND_NAMES)\n\n # Add magnitudes\n df = pd.concat([df, band_series], axis=1, sort=True)\n df = df.rename(columns={0: 'Mag'})\n\n # Sort to order of increasing wavelength\n df = df.sort_values(by=['Wavelength'])\n\n # Calculate and add ABMagnitudes\n def ab_mag(row):\n if row.name in self._present_calculated_mags:\n return utils.convert_to_abmag(row['Mag'], row.name)\n else:\n return -999\n\n df['ABMag'] = df.apply(lambda row: ab_mag(row), axis=1)\n\n # Convert AB mag to flux (photons/s/m**2/micron)\n def calc_flux(row):\n if row['ABMag'] != -999:\n return 10.0 ** (-(row['ABMag'] + 48.6) / 2.5) * (1.0e4 / (PLANCK * row['Wavelength']))\n else:\n return -999\n\n df['Flux'] = df.apply(lambda row: calc_flux(row), axis=1)\n\n # Add extended wavelengths and compute flux\n extended_waves = np.array([3.0, 4.0, 5.0, 5.5])\n mag = np.full(4, np.nan)\n abmag = np.full(4, np.nan)\n flux = df.at[df.index[-1], \"Flux\"] * 2.17**2 / extended_waves**2\n in_data = list(map(list, zip(extended_waves, mag, abmag, flux)))\n df2 = pd.DataFrame(in_data, columns=['Wavelength', 'Mag', 'ABMag', 'Flux'],\n index=['Extend1', 'Extend2', 'Extend3', 'Extend4'])\n df = pd.concat([df, df2], axis=0)\n\n # Add throughput data to dataframe\n df['Throughput'] = df['Wavelength'].map(guider_throughput)\n\n # Compute number of photons reaching the FGS-Guider detector per second per micron.\n def calc_signal(row):\n if row['Flux'] != -999:\n return row['Flux'] * row['Throughput'] * 25\n else:\n return -999\n\n df['Signal'] = df.apply(lambda row: calc_signal(row), axis=1)\n\n # Can't compute if we only have J, H, and K # TODO will be changed later\n if {'tmassJmag', 'tmassHmag', 'tmassKsMag'} == set(self._present_calculated_mags):\n raise ValueError('Cannot compute FGS countrate & magnitude for a guide star ({}) with only 2MASS '\n 'data'.format(self.id))\n\n # Reset the shortest/2nd shortest bands to 0 if they are missing\n if df.at['JpgMag', 'Signal'] == -999:\n df.at['JpgMag', 'Signal'] = 0\n if df.at['SDSSgMag', 'Signal'] == -999:\n df.at['SDSSgMag', 'Signal'] = 0\n\n # Throw out any bands for which you don't have data\n df_short = df[df['Signal'] != -999]\n\n # Integrate flux in photons per second per micron over the FGS-Guider wavelength range. Use trapezoid formula.\n trapezoid = np.zeros(len(df_short) - 1)\n for i in range(len(trapezoid)):\n trapezoid[i] = (df_short.at[df_short.index[i + 1], \"Wavelength\"] -\n df_short.at[df_short.index[i], \"Wavelength\"]) * \\\n (df_short.at[df_short.index[i], \"Signal\"] +\n df_short.at[df_short.index[i + 1], \"Signal\"]) / 2.0\n electrons = np.sum(trapezoid)\n\n # Compute FGS countrate using conversion of # electrons => 1 count\n fgs_countrate = electrons / guider_gain\n\n if to_compute.lower() == 'countrate' or to_compute.lower() == 'both':\n to_return.append(fgs_countrate)\n\n # Compute FGS magnitude\n length = len(df_short) - 1\n trap1 = np.zeros(length)\n trap2 = np.zeros(length)\n for i in range(length):\n trap1[i] = (df_short.at[df_short.index[i + 1], \"Wavelength\"] -\n df_short.at[df_short.index[i], \"Wavelength\"]) * \\\n (df_short.at[df_short.index[i], \"Signal\"] +\n df_short.at[df_short.index[i + 1], \"Signal\"]) / 2.0\n trap2[i] = (df_short.at[df_short.index[i + 1], \"Wavelength\"] -\n df_short.at[df_short.index[i], \"Wavelength\"]) * \\\n (df_short.at[df_short.index[i], \"Throughput\"] +\n df_short.at[df_short.index[i + 1], \"Throughput\"]) / 2.0\n\n sum_signal = np.sum(trap1)\n sum_throughput = np.sum(trap2)\n\n if self.guider == 1:\n mag_conversion = MAG_CONVERSION_G1\n elif self.guider == 2:\n mag_conversion = MAG_CONVERSION_G2\n else:\n raise ValueError(\"Guider value must be an integer either 1 or 2\")\n\n fgs_magnitude = -2.5 * np.log10(sum_signal / sum_throughput) + mag_conversion\n\n if to_compute.lower() == 'magnitude' or to_compute.lower() == 'both':\n to_return.append(fgs_magnitude)\n\n if return_dataframe is True:\n to_return.append(df)\n\n return to_return","def estimate(self, bases, freqs, **kwargs):\n \n # Make sure that frequencies are provided for every basis measured\n if len(bases) != len(freqs):\n print(\"Error, must provide frequency data for all bases measured.\")\n return\n\n # Go through the keyword arguments and set mu and eps if required.\n mu = 1e-4\n eps = 0.1 \n\n if \"mu\" in kwargs:\n mu = kwargs[\"mu\"]\n if \"eps\" in kwargs:\n eps = kwargs[\"eps\"]\n\n # Separate the bases out into measured and unmeasured\n meas_bs_idx = []\n unmeas_bs_idx = []\n\n for x in range(self.dim):\n if x in bases:\n meas_bs_idx.append(x)\n else:\n unmeas_bs_idx.append(x)\n\n # Handle the vertical slope separately\n if -1 in bases:\n meas_bs_idx.append(-1)\n else:\n unmeas_bs_idx.append(-1)\n\n # Begin with the initial state, the maximally mixed state\n rho_0 = (1.0 / self.dim) * np.eye(self.dim)\n rho_n = rho_0\n\n \"\"\"print(\"Measured bases are \", end = \"\")\n print(meas_bs_idx)\n print(\"Unmeasured bases are \", end = \"\")\n print(unmeas_bs_idx)\"\"\"\n \n n = 1\n\n # Iterate\n while (n):\n ########################################################\n # Compute W(rho)\n # I might eventually put this in a separate method, but\n # for now I'm going to leave it here to avoid having to\n # repeatedly pass the same (large chunk of) information \n # to some helper function.\n ########################################################\n term_1 = np.zeros((self.dim, self.dim))\n term_2 = np.zeros((self.dim, self.dim))\n\n # Compute the first sum, which contains the measurement \n # frequencies and the measured bases. Note that in theory\n # the bases may not be in ascending order, however the \n # frequencies will be generated in the same order as the \n # bases are placed in the list. So create a separate counter\n # for frequencies to just iterate through them one at a time\n # as we go through the bases by their slope index.\n freq_idx = 0 \n for basis_idx in meas_bs_idx:\n for proj_idx in range(self.dim):\n this_projector = self.projectors[basis_idx][proj_idx]\n\n p_num = freqs[freq_idx][proj_idx] \n p_denom = np.trace(np.dot(rho_n, this_projector))\n prefactor = p_num / p_denom\n\n term_1 = term_1 + (prefactor * this_projector)\n freq_idx += 1\n\n # If there are no unmeasured basis, do nothing\n if len(unmeas_bs_idx) != 0:\n # Compute the second sum, which is over all the unmeasured bases.\n for basis_idx in unmeas_bs_idx:\n for proj_idx in range(self.dim):\n this_projector = self.projectors[basis_idx][proj_idx]\n\n prefactor = log(np.trace(np.dot(rho_n, this_projector)))\n\n term_2 = term_2 + (prefactor * this_projector)\n \n \n # Finally, compute W(rho)\n W_rho_n = term_1 - mu * term_2\n ########################################################\n\n #print(\"n = \" + str(n))\n #print(rho_n) \n\n # Check if we've got a good estimate. If the desired accuracy \n # is satisfied by the most recent rho_n, then we're done. \n # Return the estimator and the number of steps.\n # If not, increment n and keep going.\n if self.check_accuracy(W_rho_n, rho_n):\n return rho_n, n \n else:\n n += 1\n\n # Compute the next term in the series. It's a big ugly expression,\n # so I've separated out a term 'clump', and also the num/denom\n clump = W_rho_n - np.trace(np.dot(W_rho_n, rho_n)) * np.eye(self.dim)\n \n numerator = np.dot(np.eye(self.dim) + eps * clump, \\\n np.dot(rho_n, np.eye(self.dim) + eps * clump))\n denominator = 1 + (eps ** 2) * np.trace(np.dot(np.dot(clump, clump), rho_n))\n\n rho_np1 = numerator / denominator\n rho_n = rho_np1","def test_bayes_updates_good_data(self):\r\n # result for first -> fourth calculated by hand\r\n for obs, exp in zip(bayes_updates(self.test), self.result):\r\n self.assertFloatEqualAbs(obs, exp, 1e-11)","def calculate_flux(self, band):\n\n if (self.wavelength[0] > band.wavelength[0] or\n self.wavelength[-1] < band.wavelength[-1]):\n\n warn('Spectrum does not cover the whole bandpass, '\n 'extrapolating...')\n dw = np.median(np.diff(self.wavelength.value))\n spec_wavelength = np.arange(\n band.wavelength.value[0],\n band.wavelength.value[-1] + dw, dw) * angstrom\n spec_flux = np.interp(spec_wavelength, self.wavelength,\n self.flux.value)\n\n else:\n spec_wavelength = self.wavelength\n spec_flux = self.flux.value\n\n i, j = spec_wavelength.searchsorted(\n Quantity([band.wavelength[0], band.wavelength[-1]]))\n wavelength = spec_wavelength[i:j]\n flux = spec_flux[i:j]\n\n dw_band = np.median(np.diff(band.wavelength))\n dw_spec = np.median(np.diff(wavelength))\n\n if dw_spec.value > dw_band.value > 20:\n\n warn('Spectrum wavelength sampling interval {0:.2f}, but bandpass'\n 'sampling interval {1:.2f}'.format(dw_spec, dw_band))\n\n # Interpolate the spectrum to the passband wavelengths:\n flux = np.interp(band.wavelength, wavelength, flux)\n band_transmission = band.transmission\n wavelength = band.wavelength\n\n else:\n # Interpolate the band transmission to the spectrum wavelengths:\n band_transmission = np.interp(\n wavelength, band.wavelength, band.transmission)\n\n # Weight by the response and wavelength, appropriate when we're\n # counting the number of photons within the band:\n flux = (np.trapz(band_transmission * flux * wavelength, wavelength) /\n np.trapz(band_transmission * wavelength, wavelength))\n flux *= erg / s / cm ** 2 / angstrom\n\n return flux","def getB(self):\n return ((self.bPlusbStar() / self.nPos) + (self.bMinusbStar / self.nNeg)) / 2","def calculate(self):\n if self.sampling_timer.IsRunning():\n return\n if self.daq.data0 == []:\n average = 0.0\n else:\n average = mean(self.daq.data0)\n res_string = '%.2f' %average\n self.control_box.result_box.SetLabel(res_string)","def calculate(self):\r\n\r\n pass","def calbands( band = 0, tmo = 30 ) :\n optimizeThresholds(band,tmo)\n flattenPhases(band,tmo)\n calibrateSpectra(band=band,tmo=tmo)","def b_minus_bstar(self):\n running_total = 0\n for i in range(self.prob.num):\n if self.alphas[i] > 1e-5 and self.prob.Y[i] == -1:\n ayxx = 0\n for j in range(self.prob.num):\n ayxx += (self.alphas[j] + self.etas[j]) * self.prob.Y[j] * self.prob.xkernel(self.prob.X[j],\n self.prob.X[i])\n abcxx = 0\n for j in range(self.prob.num):\n abcxx += (self.alphas[j] + self.deltas[j]) * self.prob.xkernel(self.prob.X[j], self.prob.X[i])\n abcxx *= (1 / self.prob.gamma)\n running_total += -1 + abcxx - ayxx\n return running_total","def bandpass(filename,f1,f2,Q,wout=True,plot=True):\n start=time.time()\n n, data, data_dB,sr,ch=inputwav(filename)\n b, a = butter(Q,Wn=(f1/sr,f2/sr),btype='bandpass')\n data_filtered=lfilter(b,a,data,axis=0)\n print('Applying FFT...')\n if wout==True:\n print('Exporting...')\n sf.write(filename[0:len(filename)-4]+'_BP.wav',data_filtered,sr,'PCM_16')\n if plot==True:\n print('Plotting...')\n py.close()\n w, h = freqz(b,a,worN=16384)\n fig, (ax1, ax2) = py.subplots(nrows=2)\n ax1.semilogx(0.5*sr*w/np.pi,abs(h),'k-')\n ax1.set_xlabel('Frequency (Hz)')\n ax1.set_ylabel('Rel. Amplitude')\n ax1.grid()\n ax1.set_ylim(0,1.1)\n ax1.set_xlim(1,20000)\n ax2.plot(data,'k-',label='Raw data')\n ax2.plot(data_filtered,'m-',lw=1,label='Filtered data')\n ax2.set_xlim(0,10000)\n ax2.set_ylim(-1,1)\n ax2.set_ylabel('Amplitude (Norm Bits)')\n ax2.set_xlabel('Samples')\n ax2.legend(loc=2,frameon=False,ncol=2)\n py.subplots_adjust(hspace=0.35) \n print('Done!')\n end=time.time()\n elapsed=int(1000*(end-start))\n print('...............................')\n print('Completed in '+str(elapsed)+' milliseconds.')\n return data_filtered","def b_plus_bstar(self):\n running_total = 0\n for i in range(self.prob.num):\n if self.alphas[i] > 1e-5 and self.prob.Y[i] == 1:\n ayxx = 0\n for j in range(self.prob.num):\n ayxx += (self.alphas[j] + self.etas[j]) * self.prob.Y[j] * self.prob.xkernel(self.prob.X[j],\n self.prob.X[i])\n abcxx = 0\n for j in range(self.prob.num):\n abcxx += (self.alphas[j] + self.deltas[j]) * self.prob.xkernel(self.prob.X[j], self.prob.X[i])\n abcxx *= (1 / self.prob.gamma)\n running_total += 1 - abcxx - ayxx\n return running_total","def calculate(self):\r\n pass","def _calculate_fuel(self):\n self._fuel = self._calculate_fuel_r(self._mass)","def bPlusbStar(self):\n running_total = 0\n for i in range(self.prob.num):\n if self.alphas[i] > 1e-5 and self.prob.Y[i] == 1:\n ayxx = 0\n for j in range(self.prob.num):\n ayxx += self.alphas[j] * self.prob.Y[j] * self.prob.xkernel(self.prob.X[i], self.prob.X[j])\n abcxx = 0\n for j in range(self.prob.num):\n abcxx += (self.alphas[j] + self.deltas[j]) * self.prob.xkernel(self.prob.X[i], self.prob.X[j])\n abcxx *= (1 / self.prob.gamma)\n running_total += 1 - abcxx - ayxx\n return running_total","def calc_fffb_inhibition(self) -> None:\n # Feedforward inhibition\n ffi = self.spec.ff * max(self.avg_net - self.spec.ff0, 0)\n # Feedback inhibition\n self.fbi = self.spec.fb_dt * (self.spec.fb * self.avg_act - self.fbi)\n # Global inhibition\n self.gc_i = self.spec.gi * (ffi * self.fbi)","def test_9(self):\n\n sq_qe = gen_step_qe(1.42, 0.9)\n test_ill = Illumination()\n # test_qef = qe_filter(sq_qe)\n\n filtered_ill = test_ill * sq_qe\n\n assert isinstance(filtered_ill, Illumination)\n\n #plt.plot(filtered_ill.get_spectrum('eV')[0, :], filtered_ill.get_spectrum('eV')[1, :], label=\"filtered\")\n #plt.plot(test_ill.get_spectrum('eV')[0, :], test_ill.get_spectrum('eV')[1, :], label=\"original\")\n\n #plt.xlabel('wavelength (eV)')\n #plt.ylabel('spectrum (W/eV/m^2)')\n\n #plt.legend()\n\n #plt.show()","def compute_bias(ics, vbc):\n import os, time\n from seren3.array import SimArray\n \n # Compute size of grid and boxsize (for this patch)\n N = vbc.shape[0]\n boxsize = ics.boxsize.in_units(\"Mpc a h**-1\") * (float(N) / float(ics.header.N))\n\n # Compute vbc @ z=1000\n z = ics.z\n rms = vbc_rms(vbc)\n rms_recom = rms * (1001./z)\n\n # Check for PS and run CICsASS if needed\n fname_vbc0 = vbc_ps_fname(0., z, boxsize)\n if not os.path.isfile(fname_vbc0):\n exit_code = run_cicsass(boxsize, z, 0., fname_vbc0)\n\n fname_vbcrecom = vbc_ps_fname(rms_recom, z, boxsize)\n if not os.path.isfile(fname_vbcrecom):\n exit_code = run_cicsass(boxsize, z, rms_recom, fname_vbcrecom)\n\n # Load power spectra and compute bias\n ps_vbc0 = np.loadtxt(fname_vbc0, unpack=True)\n ps_vbcrecom = np.loadtxt(fname_vbcrecom, unpack=True)\n\n # Should have same lenghts if finished writing\n count = 0\n while len(ps_vbcrecom[1]) != len(ps_vbc0[1]):\n count += 1\n if count > 10:\n raise Exception(\"Reached sleep limit. Filesizes still differ\")\n time.sleep(5)\n ps_vbc0 = np.loadtxt(fname_vbc0, unpack=True)\n ps_vbcrecom = np.loadtxt(fname_vbcrecom, unpack=True)\n\n #CDM bias\n b_cdm = ps_vbcrecom[1] / ps_vbc0[1]\n # Baryon bias\n b_b = ps_vbcrecom[2] / ps_vbc0[2]\n # Wavenumber\n k_bias = SimArray(ps_vbcrecom[0] / ics.cosmo[\"h\"], \"h Mpc**-1\")\n\n return k_bias, b_cdm, b_b","def diff_bmf(mass_arr, volume, cvar_err, sim_bool, h1_bool): \n if sim_bool:\n mass_arr = np.log10(mass_arr)\n \n if not h1_bool:\n # changing from h=0.7 to h=1\n mass_arr = np.log10((10**mass_arr) / 2.041)\n \n if survey == 'eco':\n bin_min = np.round(np.log10((10**9.4) / 2.041), 1)\n bin_max = np.round(np.log10((10**11.8) / 2.041), 1)\n bins = np.linspace(bin_min, bin_max, 7)\n \n if survey == 'resolvea':\n bin_min = np.round(np.log10((10**9.4) / 2.041), 1)\n bin_max = np.round(np.log10((10**11.5) / 2.041), 1)\n bins = np.linspace(bin_min, bin_max, 7) \n\n if survey == 'resolveb':\n bin_min = np.round(np.log10((10**9.1) / 2.041), 1)\n bin_max = np.round(np.log10((10**11.5) / 2.041), 1)\n bins = np.linspace(bin_min, bin_max, 7) \n \n\n # Unnormalized histogram and bin edges\n counts, edg = np.histogram(mass_arr, bins=bins) # paper used 17 bins\n dm = edg[1] - edg[0] # Bin width\n maxis = 0.5 * (edg[1:] + edg[:-1]) # Mass axis i.e. bin centers\n # Normalized to volume and bin width\n err_poiss = np.sqrt(counts) / (volume * dm)\n\n phi = counts / (volume * dm) # not a log quantity\n return maxis, phi, err_poiss, bins, counts","def runBrighterFatter():\n RunData([getFiles(mintime=(15, 12, 20), maxtime=(15, 24, 16), folder='data/31Jul/')[0],], out='I800nmlow',\n wavelength='l800l')\n RunData([getFiles(mintime=(15, 28, 40), maxtime=(15, 39, 21), folder='data/31Jul/')[2],], out='I800nmmed',\n wavelength='l800m')\n RunData([getFiles(mintime=(15, 40, 07), maxtime=(15, 45, 14), folder='data/29Jul/')[4],], out='I800nmhigh',\n wavelength='l800h')","def pre_process(self):\n t1_start = perf_counter()\n wav_arr_raw = np.array(self.raw_data['spectrum_0'].attrs['wavelengths'])\n self.wavelengths = wav_arr_raw\n self.back_spectra_arr = np.array(self.raw_data['spectrum_0'].attrs['background'])\n\n corr_data = []\n times_proc = []\n\n # extract reference point for 0 seconds\n time_ref = str(self.raw_data['spectrum_0'].attrs['creation_timestamp'])\n\n # spectrometer adds 'b' and quotation marks to timestamps that must be removed\n # some spectra are taken on X.000000s which does not have a .%f component - use try and except\n try:\n time_ref = datetime.strptime((time_ref.replace('b','')).replace('\\'',''),\"%Y-%m-%dT%H:%M:%S.%f\")\n except ValueError:\n time_ref = datetime.strptime((time_ref.replace('b','')).replace('\\'',''),\"%Y-%m-%dT%H:%M:%S\")\n\n print('Measurement was started at {}, \\n normalising times and applying a background correction \\n'.format(time_ref))\n\n # applies background correction\n for counter, spectra in enumerate(self.raw_data.keys()):\n corr_data.append(self.raw_data[spectra]-self.back_spectra_arr)\n time = str(self.raw_data[spectra].attrs['creation_timestamp'])\n try:\n time = datetime.strptime((time.replace('b','')).replace('\\'',''),\"%Y-%m-%dT%H:%M:%S.%f\")\n except ValueError:\n time = datetime.strptime((time.replace('b','')).replace('\\'',''),\"%Y-%m-%dT%H:%M:%S\")\n deltatime = time - time_ref\n times_proc.append(deltatime.total_seconds())\n\n self.times = np.array(times_proc)\n print('Measurement contains {} spectra with {} wavelengths \\n'.format(len(self.times),len(self.wavelengths)))\n\n # data is stored as a pd Dataframe with elapsed times as indices and wavelengths as columns\n pre_proc_data = pd.DataFrame(corr_data, index = self.times, columns = self.wavelengths)\n\n # data may be disordered in time when iterated through\n # sort the data by elapsed time\n self.pre_proc_data = pre_proc_data.sort_index(axis=0)\n self.times = np.sort(self.times)\n\n t1_stop = perf_counter()\n print(\"Elapsed time for pre-processing:\", t1_stop-t1_start)\n\n return self.pre_proc_data","def __call__(self, frame_num):\n quant_sys = self.quant_sys\n quant_sys.propagate(10)\n\n # propagate the wigner function\n self.img_clasical_rho.set_array(\n (quant_sys.D22 + quant_sys.D11).real\n #quant_sys.get_classical_rho()\n )\n\n self.img_Upsilon2.set_array(\n quant_sys.quantum_rho.real\n )\n\n return self.img_clasical_rho, self.img_Upsilon2","def compute_rate(self):\n bg_rate = self.counts_cube.data / self.livetime_cube.data\n\n bg_rate /= self.counts_cube.bin_volume\n # bg_rate.set_zero_level()\n\n # import IPython; IPython.embed()\n bg_rate = bg_rate.to('1 / (MeV sr s)')\n\n self.background_cube.data = bg_rate","def calculate_abs(self):\n ref_spectra_raw = np.array(self.raw_data['spectrum_0'].attrs['reference'])\n self.ref_spectra_arr = np.subtract(ref_spectra_raw,self.back_spectra_arr)\n abs=-np.log10(self.pre_proc_data.div(self.ref_spectra_arr))\n self.abs_data=abs\n return self.abs_data","def simulate_spectrum(file_name = \"bands_full.dat\", k0=0,kf= 0.576,Nk=200,E_max=0.5,E_min=-0.5,Ne=200,gamma_k=0.002,gamma=0.004,lambda_0=20,orbital=\"pz\",suffix=\"\"):\n\n #define energy and momentum domains\n dk = (kf-k0)/Nk\n momenta = np.linspace(k0, kf+dk, Nk)\n energies = np.linspace(E_min, E_max, Ne)\n\n #initialize spectral function A_final to zero\n A_final = []\n for i_k in range(len(momenta)):\n I_e = []\n for j_e in range(len(energies)):\n I_e.append(0)\n A_final.append(I_e)\n\n #compute all lorenztian functions\n all_lor = compute_functions(file_name,E_max,E_min,gamma,gamma_k)\n\n #evaluate all functions\n print \"Evaluating functions\"\n for func in all_lor:\n s = np.vectorize(func)\n A = s(momenta[:,None],energies[None,:])\n A_final += A\n\n #print output\n file_output = \"\"\"A_gammak_%(gamma_k)s_gammae_%(gamma)s_Nk_%(Nk)s_Ne_%(Ne)s_lambda_%(lambda_0)s_%(orbital)s%(suffix)s\"\"\"%locals()\n file = open(file_output,'w')\n for i in range(len(momenta)):\n for j in range(len(energies)):\n print >> file,momenta[i],energies[j],A_final[i][j]\n print >> file,\"\"\n file.close()\n\n return file_output","def f2b(self, fres, f):\n return f / fres","def calculate(self):\n pass","def _calculate_a_value(self, bval, nvalue, nyr, cmag, ref_mag):\n\n denominator = np.sum(nyr * np.exp(-bval * (cmag - ref_mag)))\n return nvalue / denominator","def compute(self):\n # get the values in widgets\n if self.first:\n self.first = False\n type = self.type\n nfilter = self.nfilter\n order = self.order\n npass = self.npass\n else:\n type = self.typeComboBox.currentIndex()\n nfilter = int(str(self.filterComboBox.currentText()))\n order = self.orderSpinBox.value()\n npass = self.nbpassSpinBox.value()\n self.data[2] = self.data[1] # Restore initial values\n for i in range(npass):\n if type == 0:\n self.data[2] = MovAver(self.data[2], nfilter)\n else:\n self.data[2] = signal.savgol_filter(self.data[2],\n window_length = nfilter,\n polyorder = order)\n self.data[3] = self.data[2] - self.data[1] - self.diffshift\n self.type = type\n self.nfilter = nfilter\n self.npass = npass\n if type == 1:\n self.order = order\n self.updatePlot()","def detect_bispectra(self, sigma=5., tol=1.3, Q=0, show=0, save=0):\n\n try:\n ba = self.bispectra\n except AttributeError:\n print 'Need to make bispectra first.'\n return\n\n# ntr = lambda num: num*(num-1)*(num-2)/6 # assuming all triples are present\n ntr = lambda num: len(self.triples) # consider possibility of zeros in data and take mean number of good triples over all times\n\n # using s=S/Q\n mu = lambda s: 1. # for bispectra formed from visibilities\n sigbQ3 = lambda s: n.sqrt((1 + 3*mu(s)**2) + 3*(1 + mu(s)**2)*s**2 + 3*s**4) # from kulkarni 1989, normalized by Q**3, also rogers et al 1995\n s = lambda basnr, nants: (2.*basnr/n.sqrt(ntr(nants)))**(1/3.) # see rogers et al. 1995 for factor of 2\n\n # measure SNR_bl==Q from sigma clipped times with normal mean and std of bispectra. put into time,dm order\n bamean = ba.real.mean(axis=2).transpose()\n bastd = ba.real.std(axis=2).transpose()\n\n bameanstd = []\n for dmind in xrange(len(self.dmarr)):\n (meanmin,meanmax) = sigma_clip(bamean[:, dmind]) # remove rfi to estimate noise-like parts\n (stdmin,stdmax) = sigma_clip(bastd[:, dmind])\n clipped = n.where((bamean[:, dmind] > meanmin) & (bamean[:, dmind] < meanmax) & (bastd[:, dmind] > stdmin) & (bastd[:, dmind] < stdmax) & (bamean[:, dmind] != 0.0))[0] # remove rfi and zeros\n bameanstd.append(ba[dmind][clipped].real.mean(axis=1).std())\n\n bameanstd = n.array(bameanstd)\n basnr = bamean/bameanstd # = S**3/(Q**3 / n.sqrt(n_tr)) = s**3 * n.sqrt(n_tr)\n if Q:\n print 'Using given Q =', Q\n else:\n Q = ((bameanstd/2.)*n.sqrt(ntr(self.nants)))**(1/3.)\n # Q = n.median( bastd[clipped]**(1/3.) ) # alternate for Q\n print 'Estimating noise per baseline from data. Q (per DM) =', Q\n self.Q = Q\n\n # detect\n cands = n.where( (bastd/Q**3 < tol*sigbQ3(s(basnr, self.nants))) & (basnr > sigma) ) # get compact sources with high snr\n\n # plot snrb lc and expected snr vs. sigb relation\n if show or save:\n for dmbin in xrange(len(self.dmarr)):\n cands_dm = cands[0][n.where(cands[1] == dmbin)[0]] # find candidates for this dmbin\n p.figure(range(len(self.dmarr)).index(dmbin)+1)\n ax = p.axes()\n p.subplot(211)\n p.title(str(self.nskip/self.nbl) + ' nskip, ' + str(dmbin) + ' dmbin, ' + str(len(cands_dm))+' candidates', transform = ax.transAxes)\n p.plot(basnr[:,dmbin], 'b.')\n if len(cands_dm) > 0:\n p.plot(cands_dm, basnr[cands_dm,dmbin], 'r*')\n p.ylim(-2*basnr[cands_dm,dmbin].max(),2*basnr[cands_dm,dmbin].max())\n p.xlabel('Integration',fontsize=12,fontweight=\"bold\")\n p.ylabel('SNR_b',fontsize=12,fontweight=\"bold\")\n ax.spines['top'].set_visible(False)\n ax.spines['right'].set_visible(False)\n ax.spines['bottom'].set_position(('outward', 20))\n ax.spines['left'].set_position(('outward', 30))\n ax.yaxis.set_ticks_position('left')\n ax.xaxis.set_ticks_position('bottom')\n p.subplot(212)\n p.plot(bastd[:,dmbin]/Q[dmbin]**3, basnr[:,dmbin], 'b.')\n\n # plot reference theory lines\n smax = s(basnr[:,dmbin].max(), self.nants)\n sarr = smax*n.arange(0,101)/100.\n p.plot(sigbQ3(sarr), 1/2.*sarr**3*n.sqrt(ntr(self.nants)), 'k')\n p.plot(tol*sigbQ3(sarr), 1/2.*sarr**3*n.sqrt(ntr(self.nants)), 'k--')\n p.plot(bastd[cands_dm,dmbin]/Q[dmbin]**3, basnr[cands_dm,dmbin], 'r*')\n ax.spines['top'].set_visible(False)\n ax.spines['right'].set_visible(False)\n ax.spines['bottom'].set_position(('outward', 20))\n ax.spines['left'].set_position(('outward', 30))\n ax.yaxis.set_ticks_position('left')\n ax.xaxis.set_ticks_position('bottom')\n\n if len(cands_dm) > 0:\n p.axis([0, tol*sigbQ3(s(basnr[cands_dm,dmbin].max(), self.nants)), -0.5*basnr[cands_dm,dmbin].max(), 1.1*basnr[cands_dm,dmbin].max()])\n\n # show spectral modulation next to each point\n for candint in cands_dm:\n sm = n.single(round(self.specmod(dmbin,candint),1))\n p.text(bastd[candint,dmbin]/Q[dmbin]**3, basnr[candint,dmbin], str(sm), horizontalalignment='right', verticalalignment='bottom')\n p.xlabel('sigma_b/Q^3',fontsize=12,fontweight=\"bold\")\n p.ylabel('SNR_b',fontsize=12,fontweight=\"bold\")\n if save:\n if save == 1:\n savename = self.file.split('.')[:-1]\n savename.append(str(self.nskip/self.nbl) + '_' + str(dmbin) + '_bisp.png')\n savename = string.join(savename,'.')\n elif isinstance(save, string):\n savename = save\n print 'Saving file as ', savename\n p.savefig(self.pathout+savename)\n\n return basnr[cands], bastd[cands], zip(cands[0],cands[1])","def test_bayes_updates_permuted(self):\r\n for obs, exp in zip(bayes_updates(self.permuted), self.result):\r\n self.assertFloatEqualAbs(obs, exp, 1e-11)","def compute(self):\n return self.elbo_component / self.get_intervals_recorded()","def calculate(self):\n\n return self._calculate_volume(self.ground_truth)","def proz(): \r\n print(\"processing: \",CURDATA()[0]) \r\n Check_180turn(left_boundary,right_boundary)\r\n EF() #exponential window multiplication + fourier\r\n APK0() #1. Phase correction 0th Ordnung\r\n APK1() #1. Phase correction 1st Ordnung\r\n ABS() #Baseline correction\r\n APK()\r\n ABS() #Baseline correction\r\n Check_180turn(left_boundary,right_boundary)","def calculate_output(self):","def binned_fft(self):\n self.fft()\n self.fft_bins_y = self.binn_fft()\n self.fft_bins_y = np.asarray(self.fft_bins_y) * UPDATE_FACTOR + self.last_fft_bins_y *(1 - UPDATE_FACTOR)\n self.last_fft_bins_y = self.fft_bins_y","def __dmr_analysis(self, debug=False):\n global hfAdcRange, adcCountRange\n if self.buffer is None or len(self.buffer) != self.bufsize:\n self.set_eval_error(f'Data length ({len(self.buffer)}) differs from expected ({self.bufsize})')\n return None\n\n It = self.buffer[:self.bufsize//2]\n Qt = self.buffer[self.bufsize//2:]\n\n self.results['ADC_I'] = hfAdcRange * (It * 2 / adcCountRange - 1)\n self.results['ADC_Q'] = hfAdcRange * (Qt * 2 / adcCountRange - 1)\n\n # subtract the DC component and convert to int32\n It = np.around(It-np.mean(It)).astype('int32')\n Qt = np.around(Qt-np.mean(Qt)).astype('int32')\n\n # find the bit error rate and constant symbol intervals\n maxlen = 20*200 # max length of returned Iref, Qref\n numerr, numbit, Iref, Qref, symlenref = get_ber(It, Qt, maxlen)\n\n if numerr is None or numbit is None:\n self.set_eval_error(f'Too small data length - {len(self.buffer)}')\n return None\n\n ber = numerr/numbit\n\n return ber","def idealOpAmp():","def y(self):\n #print(xdb.xray_lines(self.element)[self.line].energy/1000)\n #self.output_params={}\n #print(self.getBulkCon(self.element,self.botchem,self.botden))\n x = self.x + self.qoff\n if not self.__fit__:\n self.output_params['scaler_parameters']={}\n return self.fluCalFun(x)\n #return self.x","def eval_fis(self,fis):\n #res = 0.0\n #for cl_state in self.classes:\n # res += cl_state.eval_fis(fis)\n #print \"=>\",res\n #return 1.0/res\n try:\n correct,count = self.quality_fis(fis)\n except Exception as err:\n print err\n correct = 0\n return correct","def bispectrum(self,l_edges,ratio=0.5,configuration=\"equilateral\",scale=None):\n\n\t\tassert not self._masked,\"Bispectrum calculation for masked maps is not allowed yet!\"\n\t\tassert l_edges is not None\n\n\t\tif self.side_angle.unit.physical_type==\"length\":\n\t\t\traise NotImplementedError(\"Bispectrum measurement not implemented yet if side physical unit is length!\")\n\n\t\t#Check folding ratio\n\t\tif (configuration==\"folded\") and not(ratio>0 and ratio<1):\n\t\t\traise ValueError(\"Folding ratio should be between 0 and 1!\")\n\n\t\t#Multipole edges\n\t\tl = 0.5*(l_edges[:-1] + l_edges[1:])\n\n\t\t#Calculate FFT of the map via FFT\n\t\tft_map = fftengine.rfft2(self.data)\n\n\t\t#Scale pixels if scaling is provided\n\t\tif scale is not None:\n\t\t\tsc = scale(self.getEll())\n\t\t\tft_map *= np.cbrt(sc)\n\n\t\t#Calculate bispectrum\n\t\tif configuration in (\"equilateral\",\"folded\"):\n\t\t\tbispectrum = _topology.bispectrum(ft_map,ft_map,ft_map,self.side_angle.to(u.deg).value,l_edges,configuration,ratio)\n\t\telse:\n\t\t\traise NotImplementedError(\"Bispectrum configuration '{0}' not implemented!\".format(configuration))\n\n\t\t#Return\n\t\treturn l,bispectrum","def get_b(self):\n return ((self.s_pos / self.n_pos) + (self.s_neg / self.n_neg)) / 2","def bmi_calculate(self):\r\n try:\r\n manager_obj = BMI_Manager(self.data)\r\n manager_obj.bmi_calculation()\r\n except Exception as ex:\r\n print(\"Exception in bmi_calculate function\")","def _calculate_strehl(self):\n\n self.strehl = np.exp(-1*((2*np.pi/self.science_wavelength)*self.high_order_wfe)**2)","def start(self):\n lastbeat = time.time()\n averages = []\n for x in range(self.keep_amount):\n averages.append(1)\n while self.run:\n cur_amount = len(averages)\n if self.keep_amount != cur_amount:\n if self.keep_amount < cur_amount:\n while self.keep_amount != len(averages):\n averages.pop(0)\n elif self.keep_amount < cur_amount:\n avg = sum(averages)/cur_amount\n while self.keep_amount != len(averages):\n averages.append(avg)\n self.do_fft()\n mag = self.get_average(self.s_freq, self.e_freq)\n avg = sum(averages)/self.keep_amount\n averages.pop(0)\n if (mag/avg)-1 > self.percent:\n now = time.time()\n if ((now-lastbeat) > self.wait_time) and self.relative_range() > .009:\n lastbeat = now\n self.detect_func()\n averages.append(avg)\n else:\n averages.append(mag)\n else:\n averages.append(mag)","def bMinusbStar(self):\n running_total = 0\n for i in range(self.prob.num):\n if self.alphas[i] > 1e-5 and self.prob.Y[i] == -1:\n ayxx = 0\n for j in range(self.prob.num):\n ayxx += self.alphas[j] * self.prob.Y[j] * self.prob.xkernel(self.prob.X[i], self.prob.X[j])\n abcxx = 0\n for j in range(self.prob.num):\n abcxx += (self.alphas[j] + self.deltas[j]) * self.prob.xkernel(self.prob.X[i], self.prob.X[j])\n abcxx *= (1 / self.prob.gamma)\n running_total += -1 + abcxx - ayxx\n return running_total","def test_bayes_factor_b(self):\n model_1 = ufloat(2, 1)\n model_2 = ufloat(4, 1)\n expected_result = ufloat(-4, 2.82842712474619032)\n actual_result = utils.bayes_factor(model_1, model_2)\n assert_almost_equal(actual_result.n, expected_result.n)\n assert_almost_equal(actual_result.s, expected_result.s)","def test_intra_power_law_fit(self):\n\n\t\tprint(type(self.fc_layers[0:2]), self.fc_layers[0:2])\n\t\tdetails= self.watcher.analyze(layers=self.fc_layers[0:2], intra=True, randomize=False, vectors=False, pl_package=POWERLAW_PACKAGE, xmax=XMAX_FORCE)\n\t\tactual_alpha = details.alpha[0]\n\t\t#actual_best_fit = details.best_fit[0]\n\t\t#print(actual_alpha,actual_best_fit)\n\n\t\texpected_alpha = 2.654 # not very accurate because of the sparisify transform\n\t\t#expected_best_fit = LOG_NORMAL\n\t\tself.assertAlmostEqual(actual_alpha,expected_alpha, places=1)\n\t\t#self.assertEqual(actual_best_fit, expected_best_fit)","def vbmstep(self):\n for k in range(self.k):\n self.beta_k[k] = self.beta_0 + self.counts[k]\n self.m_k[k] = (1 / self.beta_k[k]) * (self.beta_0 * self.m_0 +\n self.counts[k] * self.means[k])\n\n tmp = (self.beta_0 * self.counts[k]) / (self.beta_0 + self.counts[k])\n tmp2 = (self.means[k] - self.m_0)\n tmp = np.linalg.inv(self.W_0) + self.counts[k] * self.covars[k] + tmp * tmp2 @ tmp2.T\n self.w_k[k] = np.linalg.inv(tmp)\n self.nu_k[k] = self.nu_0 + self.counts[k]\n self.alpha_k[k] = self.alpha_0[k] + self.counts[k]","def fractional_absorbtion(self, port='Substrate'):\n\n base = self.sims[0].conf['General']['results_dir']\n self.log.info('Computing fractional absorbtion for group at %s' % base)\n vals = np.zeros(self.num_sims)\n freqs = np.zeros(self.num_sims)\n wvlgths = np.zeros(self.num_sims)\n spectra = np.zeros(self.num_sims)\n path = self.sims[0].conf['Simulation']['input_power_wv']\n wv_vec, p_vec = np.loadtxt(path, usecols=(0, 2), unpack=True, delimiter=',')\n p_wv = interpolate.interp1d(wv_vec, p_vec, kind='linear',\n bounds_error=False, fill_value='extrapolate')\n # Assuming the sims have been grouped by frequency, sum over all of\n # them\n for i, sim in enumerate(self.sims):\n # Unpack data for the port we passed in as an argument\n ref, trans, absorb = sim.data['transmission_data'][port]\n freq = sim.conf['Simulation']['params']['frequency']\n wvlgth = consts.c / freq\n wvlgth_nm = wvlgth * 1e9\n freqs[i] = freq\n wvlgths[i] = wvlgth\n # Get solar power from chosen spectrum\n # Get p at wvlength by interpolation\n sun_pow = p_wv(wvlgth_nm)\n spectra[i] = sun_pow * wvlgth_nm\n vals[i] = absorb * sun_pow * wvlgth_nm\n sim.clear_data()\n # Use Trapezoid rule to perform the integration. Note all the\n # necessary factors of the wavelength have already been included\n # above\n wvlgths = wvlgths[::-1]\n vals = vals[::-1]\n spectra = spectra[::-1]\n integrated_absorbtion = intg.trapz(vals, x=wvlgths * 1e9)\n power = intg.trapz(spectra, x=wvlgths * 1e9)\n # factor of 1/10 to convert A*m^-2 to mA*cm^-2\n #wv_fact = consts.e/(consts.c*consts.h*10)\n #wv_fact = .1\n #Jsc = (Jsc*wv_fact)/power\n frac_absorb = integrated_absorbtion / power\n outf = os.path.join(base, 'fractional_absorbtion.dat')\n with open(outf, 'w') as out:\n out.write('%f\\n' % frac_absorb)\n self.log.info('Fractional Absorbtion = %f' % frac_absorb)\n return frac_absorb","def check(self, data_input, debug_flag):\n self.results = [ [], [], [], False, [] ]\n _result = {}\n _wave1_t = data_input[0][0]\n _wave2_t = data_input[0][1]\n _wave3_t = data_input[0][2] \n _wave1_p = data_input[1][0]\n _wave2_p = data_input[1][1]\n _wave3_p = data_input[1][2]\n\n #Step1: b vs a\n #Step1.1: time_analaysis\n _result = {} \n _result[str(\"b_a_t\")] = EW_fibonacci.check_fibratio(_wave2_t, _wave1_t)\n self.results[0].append(_result)\n\n #Step1.2: price_analaysis\n _result = {} \n _result[str(\"b_a_p\")] = EW_fibonacci.check_fibratio(_wave2_p, _wave1_p)\n self.results[0].append(_result)\n\n\n #Step2: c vs b\n #Step2.1: time_analaysis\n _result = {} \n _result[str(\"c_b_t\")] = EW_fibonacci.check_fibratio(_wave3_t, _wave2_t)\n self.results[1].append(_result)\n\n #Step2.2: price_analaysis\n _result = {} \n _result[str(\"c_b_p\")] = EW_fibonacci.check_fibratio(_wave3_p, _wave2_p)\n self.results[1].append(_result)\n\n \n #Step3: c vs a\n #Step3.1: time_analaysis\n _result = {} \n _result[str(\"c_a_t\")] = EW_fibonacci.check_fibratio(_wave3_t, _wave1_t)\n self.results[2].append(_result)\n\n #Step3.2: price_analaysis\n _result = {} \n _result[str(\"c_a_p\")] = EW_fibonacci.check_fibratio(_wave3_p, _wave1_p)\n self.results[2].append(_result)\n\n\n #Step4: Check if this a-b-c is valid or not and which pattern can be chosen\n self.results[3], self.results[4] = self.check_type(data_input, debug_flag)\n\n\n #Step5: return the results\n return self.results","def run_results(self):\n calculation_band = self.ctx.workchain_bands.get_outputs(link_type=LinkType.CALL)[0]\n\n self.report('workchain succesfully completed'.format())\n self.out('band_parameters', calculation_band.out.output_parameters)\n self.out('bandstructure', calculation_band.out.output_band)","def _calculate_fuel_simple(self):\n self._fuel_simple = (self.mass // 3) - 2","def chisq_bs_fft(vis_arr, A, bis, sigma, order=FFT_INTERP_DEFAULT):\n im_info, (uv1, uv2, uv3) = A \n \n bisamples = sampler(vis_arr, im_info, [uv1, uv2, uv3], order=order, sample_type=\"bs\")\n\n return np.sum(np.abs(((bis - bisamples)/sigma))**2)/(2.*len(bis))","def inactivation(self):\n\n def boltzmann(voltage, vhalf, k):\n\n voltage = list(map(lambda x: float(x), voltage))\n exponent = np.exp(np.divide(np.subtract(voltage, vhalf), k))\n return (1/ (exponent + 1))\n\n def find_v_half(current, voltage):\n \"\"\"\n current: array of normalized IV curve\n voltage: array of the test potentials\n \"\"\"\n for i in range(len(voltage)):\n if current.iloc[i] < 0.5:\n continue\n elif current.iloc[i] == 0.5:\n return voltage.iloc[i]\n else:\n volt1 = float(voltage.iloc[i-1])\n volt2 = float(voltage.iloc[i])\n curr1 = float(current.iloc[i-1])\n curr2 = float(current.iloc[i])\n V_half = volt1 + (volt1 - volt2)*(0.5 - curr1)/(curr1 - curr2)\n return V_half\n\n v_half = []\n for i in range(self.n_cols):\n current = self.screened_data.iloc[:,i]\n #print(current)\n v_half.append(find_v_half(current, self.xaxis))\n print('Median: ', np.median(v_half))\n print('Min: ', np.min(v_half))\n print('Max: ', np.max(v_half))\n return 0\n\n initial_guess = [-42, 7]\n popt, pcov = curve_fit(boltzmann, self.xaxis, self.averaged_data, p0= initial_guess)\n plt.plot(self.xaxis, self.averaged_data, label = 'Average of all models')\n plt.plot(boltzmann(self.xaxis, *initial_guess), label = 'Initial Guess')\n plt.plot(self.xaxis, boltzmann(self.xaxis, *popt), label = 'Best Fit')\n plt.xlabel('Voltage (mV)')\n plt.ylabel('Normalized Current')\n plt.title('Steady State Inactivation')\n plt.legend()\n plt.savefig('inactivation_boltzmann_fit.png')\n return popt[0]","def obtain_data(self):\n ##MODIFY THIS\n #ipdb.set_trace()\n print('obtain_data')\n print(self.enabler)\n print(self.index)\n helper = '>'+str(1+int(self.chann_span.get()))+'Q'\n print('helper='+helper)\n while(self.enabler):\n #print('size'+str(1+int(self.chann_span.get())))\n #print('offset'+str(self.index-self.index_offset))\n A2 = struct.unpack(helper, fpga.read('A2', (1+int(self.chann_span.get()))*8, ((self.index-self.index_offset)*8))) \n #print(A2)\n #print(str(10*np.log10(A2))+'dB')\n self.amp_a2[0] = np.mean(A2)\n self.amp_a2 = np.roll(self.amp_a2, -1)\n B2 = struct.unpack(helper, fpga.read('B2', (1+int(self.chann_span.get()))*8, ((self.index-self.index_offset)*8)))\n self.amp_b2[0] = np.mean(B2)\n self.amp_b2 = np.roll(self.amp_b2, -1)\n AB_re = struct.unpack(helper, fpga.read('AB_re', (1+int(self.chann_span.get()))*8, ((self.index-self.index_offset)*8)))\n self.ab_re[0] = np.mean(AB_re)\n self.ab_re = np.roll(self.ab_re, -1)\n AB_im = struct.unpack(helper, fpga.read('AB_im', (1+int(self.chann_span.get()))*8, ((self.index-self.index_offset)*8)))\n self.ab_im[0] = np.mean(AB_im)\n self.ab_im = np.roll(self.ab_im, -1) \n # print('RE:' + str(self.ab_re)+ '\\t IM:' +str(self.ab_im))\n log_a = 10*np.log10(np.mean(self.amp_a2)+1.0)\n log_b = 10*np.log10(np.mean(self.amp_b2)+1.0) \n ang = np.rad2deg(np.arctan2(np.mean(self.ab_im), np.mean(self.ab_re))) #review the way of avg this... i dont know if its the most correct way to do it...\n self.a2.set(log_a)\n self.b2.set(log_b)\n self.ang.set(ang)\n self.amp_rel.set(log_a-log_b)\n return 1","def calculate_dark_current(image, i, int_time):\n dark_data_dir = r'F:\\TEMPO\\Data\\GroundTest\\FPS\\Integration_Sweep\\Dark'\n data_path_name_split = image.split('_')\n #print(data_path_name_split)\n all_int_files = [each for each in os.listdir(dark_data_dir) \\\n if each.endswith('_'+data_path_name_split[-1])] \n print(all_int_files)\n \n dark_data_file = os.path.join(dark_data_dir, all_int_files[0])\n IDL_variable = readsav(dark_data_file) \n all_full_frame = IDL_variable.q \n quad = all_full_frame[:, i, :, :]\n active_quad = np.mean(quad[:, 4:1028, 10:1034], axis=0) \n tsoc = np.mean(quad[:, 4:1028, 1034:1056], axis=0)\n bias_subtracted_quad = perform_bias_subtraction_ave(active_quad, tsoc)\n smear_subtracted_quad, smear_signal = perform_smear_subtraction(bias_subtracted_quad[10:1000, :], int_time)\n return smear_subtracted_quad"],"string":"[\n \"def calculate_ft(self):\\n \\n # Create a function which is able to evaluate B**2\\n ffunc = scipy.interpolate.interp1d(self.psigrid, self.e.getF()[self.tind])\\n def b2_func(R, Z, psi):\\n bt = ffunc(psi)/R\\n br = -self.psifunc.ev(R, Z, dy=1)/R\\n bz = self.psifunc.ev(R, Z, dx=1)/R\\n \\n return bt**2 + br**2 + bz**2\\n \\n\\n def b_bmax2(R,Z,psi):\\n b2 = b2_func(R,Z,psi)\\n return b2 / np.max(b2)\\n \\n def b_bmax(R,Z,psi):\\n return np.sqrt(b_bmax2(R,Z,psi))\\n \\n # Evaluate the flux-surface averaged h^2 and h, as required\\n fsa_h2 = self.fs_average(b_bmax2)\\n fsa_h = self.fs_average(b_bmax)\\n \\n # This is the function which gets flux-surface averaged in equation (7)\\n def ftl_func(R,Z,psi):\\n h = b_bmax(R,Z,psi)\\n h2 = b_bmax2(R,Z,psi)\\n \\n return (1 - (np.sqrt(1 - h) * (1 + 0.5 * h)))/h2\\n \\n \\n # Equation 6, 7 in Lin-Liu\\n fs_ftu = 1 - fsa_h2 / fsa_h**2 * (1 - np.sqrt(1 - fsa_h) * (1 + 0.5 * fsa_h))\\n fs_ftl = 1 - fsa_h2 * self.fs_average(ftl_func)\\n # Equation 18, 19 \\n om = 0.75\\n self.fs_ft = om*fs_ftu + (1-om)*fs_ftl\",\n \"def compute_f2a_f2b(self):\\n try:\\n self.Frac2a = self.data['AB Counts'].sum(\\n ) / self.data['A Counts'].sum()\\n self.Frac2b = self.data['AB Counts'].sum(\\n ) / self.data['B Counts'].sum()\\n except BaseException:\\n print(\\\"Ran into error computing AB/A and AB/B. Continuing\\\")\",\n \"def calculate(self, b):\\n self.n_steps = self.n_steps + 1\\n self.length = b.length\\n self.natoms = b.natoms\\n for i in range(0,self.natoms-1):\\n for j in range(i+1,self.natoms):\\n rij = (b.atoms[i].xyz - b.atoms[j].xyz)\\n rij = rij - self.pbc_correction(rij)\\n mag_rij = la.norm(rij)\\n bin_no = int(round(mag_rij/self.dr))\\n if bin_no <= self.n_max:\\n self.gr[bin_no] = self.gr[bin_no] + 1\",\n \"def test_get_spectra_bi():\\r\\n\\r\\n methods = (None,\\r\\n {\\\"this_method\\\": 'welch', \\\"NFFT\\\": 256, \\\"Fs\\\": 2 * np.pi},\\r\\n {\\\"this_method\\\": 'welch', \\\"NFFT\\\": 1024, \\\"Fs\\\": 2 * np.pi})\\r\\n\\r\\n for method in methods:\\r\\n arsig1, _, _ = utils.ar_generator(N=2 ** 16)\\r\\n arsig2, _, _ = utils.ar_generator(N=2 ** 16)\\r\\n\\r\\n avg_pwr1 = (arsig1 ** 2).mean()\\r\\n avg_pwr2 = (arsig2 ** 2).mean()\\r\\n avg_xpwr = (arsig1 * arsig2.conjugate()).mean()\\r\\n\\r\\n tseries = np.vstack([arsig1, arsig2])\\r\\n\\r\\n f, fxx, fyy, fxy = tsa.get_spectra_bi(arsig1, arsig2, method=method)\\r\\n\\r\\n # \\\\sum_{\\\\omega} PSD(\\\\omega) d\\\\omega:\\r\\n est_pwr1 = np.sum(fxx * (f[1] - f[0]))\\r\\n est_pwr2 = np.sum(fyy * (f[1] - f[0]))\\r\\n est_xpwr = np.sum(fxy * (f[1] - f[0])).real\\r\\n\\r\\n # Test that we have the right order of magnitude:\\r\\n npt.assert_array_almost_equal(est_pwr1, avg_pwr1, decimal=-1)\\r\\n npt.assert_array_almost_equal(est_pwr2, avg_pwr2, decimal=-1)\\r\\n npt.assert_array_almost_equal(np.mean(est_xpwr),\\r\\n np.mean(avg_xpwr),\\r\\n decimal=-1)\",\n \"def calculate(self, fullFile):\\r\\n\\r\\n # Initialize variables\\r\\n pixelSize = 0\\r\\n areaFracBright = 0\\r\\n estSize= 0\\r\\n diameter_average_bright = 0\\r\\n diameter_SD_bright = 0\\r\\n diameter_num_bright = 0\\r\\n diameter_average_dark = 0\\r\\n diameter_SD_dark = 0\\r\\n diameter_num_dark = 0\\r\\n length_average_bright = 0\\r\\n length_SD_bright = 0\\r\\n length_num_bright = 0\\r\\n length_average_dark = 0\\r\\n length_SD_dark = 0\\r\\n length_num_dark = 0\\r\\n area_average_bright = 0\\r\\n area_SD_bright = 0\\r\\n area_num_bright = 0\\r\\n area_average_dark = 0\\r\\n area_SD_dark = 0\\r\\n area_num_dark = 0\\r\\n sumLength_average_bright = 0\\r\\n sumLength_SD_bright = 0\\r\\n sumLength_num_bright = 0\\r\\n sumLength_average_dark = 0\\r\\n sumLength_SD_dark = 0\\r\\n sumLength_num_dark = 0\\r\\n \\r\\n # Rename text boxes and tkinter variables for easier reference\\r\\n results = self.textResults\\r\\n status = self.textStatus\\r\\n showSteps = self.varShowSteps.get()\\r\\n outputExcel = self.varOutputExcel.get()\\r\\n savePDF = self.varSavePDF.get()\\r\\n\\r\\n # Handle strange GUI input.\\r\\n if self.varSegment.get() == \\\"binary\\\":\\r\\n self.varSaveBinary.set(False)\\r\\n\\r\\n # Select the image to operate on.\\r\\n if self.varSegment.get() == \\\"binary\\\":\\r\\n brightFile = selectFile(title=\\\"Select the bright phase mask\\\")\\r\\n darkFile = selectFile(title=\\\"Select the bright phase mask\\\")\\r\\n folder = '/'.join(brightFile.split('/')[:-1])\\r\\n fname = brightFile.split('/')[-1].split(' -')[:-1][0]\\r\\n ftype = brightFile.split('.')[-1]\\r\\n fnametype = fname + '.' + ftype\\r\\n pixelString = brightFile.split('--')[1] \\r\\n pixelSize = float(pixelString)\\r\\n fullFile = brightFile\\r\\n\\r\\n else:\\r\\n #fullFile = selectFile()\\r\\n # Figure out file name and type.\\r\\n folder = '/'.join(fullFile.split('/')[:-1])\\r\\n fname = fullFile.split('/')[-1].split('.')[:-1][0]\\r\\n ftype = fullFile.split('.')[-1]\\r\\n fnametype = fname + '.' + ftype\\r\\n\\r\\n # Status update.\\r\\n if self.varSegment.get() == \\\"binary\\\":\\r\\n self.write(status, \\\"Operating on\\\", fnametype, \\\"(binary)\\\")\\r\\n self.write(results, \\\"Operating on\\\", fnametype, \\\"(binary)\\\")\\r\\n else:\\r\\n self.write(status, \\\"Operating on\\\", fnametype)\\r\\n self.write(results, \\\"Operating on\\\", fnametype)\\r\\n\\r\\n # Load image.\\r\\n img_raw = inout.load(fullFile)\\r\\n\\r\\n # Prepare for output of data to excel\\r\\n if outputExcel:\\r\\n if self.outFold == None:\\r\\n excelPath = folder+'/'+fname+' - All Measurements.xlsx'\\r\\n writer = pd.ExcelWriter(excelPath)\\r\\n else:\\r\\n excelPath = self.outFold+'/'+fname+' - All Measurements.xlsx'\\r\\n writer = pd.ExcelWriter(excelPath)\\r\\n\\r\\n # Prepare PDF file.\\r\\n pdf = None\\r\\n if savePDF:\\r\\n if self.outFold == None:\\r\\n pdf = PdfPages(folder+'/'+fname+' - Steps.pdf')\\r\\n else:\\r\\n pdf = PdfPages(self.outFold+'/'+fname+' - Steps.pdf')\\r\\n\\r\\n # Show steps.\\r\\n if showSteps:\\r\\n display.showFull(img_raw, title=\\\"Raw Image.\\\")\\r\\n\\r\\n if savePDF:\\r\\n inout.pdfSaveImage(pdf, img_raw, title=\\\"Raw Image.\\\")\\r\\n\\r\\n # Select the image data and scale bar.\\r\\n if self.varSegment.get() != \\\"binary\\\":\\r\\n\\r\\n if self.varAutoParse.get():\\r\\n profile = self.varProfile.get()\\r\\n img, pixelSize = autoSelect.autoDetect(img_raw, profile=profile)\\r\\n else:\\r\\n img, scale = manualSelectImage(img_raw)\\r\\n \\r\\n # Ensure proper dtype.\\r\\n img = inout.uint8(img) \\r\\n scale = inout.uint8(scale)\\r\\n\\r\\n # Get the pixel size.\\r\\n pixelSize = measure.manualPixelSize(scale)\\r\\n self.write(results, \\\"The pixel size is %.3f nm\\\" %(pixelSize))\\r\\n \\r\\n # Get a rough estimated of the ligament diameter.\\r\\n bright, dark = segment.roughSegment(img)\\r\\n estSizeD = measure.estimateDiameter(dark)\\r\\n estSizeB = measure.estimateDiameter(bright)\\r\\n estSizeB_rough = copy.copy(estSizeB)\\r\\n estSizeD_rough = copy.copy(estSizeD)\\r\\n # Get the average estimated size with a weight towards the thinner\\r\\n estSize = (min(estSizeD, estSizeB) + estSizeD + estSizeB) / 3\\r\\n # Result update \\r\\n self.write(results, \\\"Weighted average estimated diameter: \\\",\\r\\n round(estSize,3),\\\" pixels (\\\", round(estSize*pixelSize,3),\\r\\n \\\" nm).\\\", sep='')\\r\\n if savePDF:\\r\\n inout.pdfSaveImage(pdf, img, title=\\\"Selected image data\\\",\\r\\n cmap=plt.cm.gray)\\r\\n else:\\r\\n img = img_raw.copy()\\r\\n img = inout.uint8(img)\\r\\n\\r\\n # Segment the image.\\r\\n # Status update.\\r\\n if self.varSegment.get() == \\\"accurate\\\":\\r\\n self.write(status, \\\"Segmenting image. This may take a while,\\\",\\r\\n \\\"especially at higher resolutions.\\\")\\r\\n else:\\r\\n self.write(status, \\\"Segmenting image.\\\")\\r\\n # Segment based on options. \\r\\n if self.varSegment.get() == \\\"fast\\\":\\r\\n #already did this when estimating size\\r\\n pass\\r\\n elif self.varSegment.get() == \\\"manual\\\":\\r\\n bright, dark = segment.manualSegment(img)\\r\\n elif self.varSegment.get() == \\\"accurate\\\":\\r\\n bright, dark = segment.segment(img, estSize)\\r\\n elif self.varSegment.get() == \\\"binary\\\":\\r\\n bright = imread(brightFile)\\r\\n dark = imread(darkFile)\\r\\n estSizeD = measure.estimateDiameter(dark)\\r\\n estSizeB = measure.estimateDiameter(bright)\\r\\n estSizeB_rough = copy.copy(estSizeB)\\r\\n estSizeD_rough = copy.copy(estSizeD)\\r\\n # Get the average estimated size with a weight towards the thinner\\r\\n estSize = (min(estSizeD, estSizeB) + estSizeD + estSizeB) / 3\\r\\n # Result update \\r\\n self.write(results, \\\"Weighted average estimated diameter: \\\",\\r\\n round(estSize,3),\\\" pixels (\\\", round(estSize*pixelSize,3),\\r\\n \\\" nm).\\\", sep='')\\r\\n bright = inout.uint8(bright)\\r\\n dark = inout.uint8(dark)\\r\\n\\r\\n if showSteps and self.varSegment.get() != \\\"binary\\\":\\r\\n display.overlayMask(img, bright, title=\\\"Bright phase mask.\\\",\\r\\n animate=True)\\r\\n display.overlayMask(img, dark, title=\\\"Dark phase mask.\\\",\\r\\n animate=True)\\r\\n\\r\\n if savePDF and self.varSegment.get() != \\\"binary\\\":\\r\\n inout.pdfSaveOverlay(pdf, img, bright, title=\\\"Bright phase mask.\\\")\\r\\n inout.pdfSaveOverlay(pdf, img, dark, title=\\\"Dark phase mask.\\\")\\r\\n\\r\\n if self.varSaveMovie.get():\\r\\n stack = []\\r\\n for i in range(5):\\r\\n stack.append(gray2rgb(img))\\r\\n stack.append(display.overlayMask(img,bright,\\r\\n return_overlay=True))\\r\\n inout.save_movie(stack, ''.join((folder, '//', fname,\\r\\n ' - segment movie.mp4')))\\r\\n\\r\\n if self.varSaveBinary.get():\\r\\n inout.saveBinary(bright,\\r\\n folder+'/'+fname+' - Bright Segment--'+str(pixelSize)+'--.tif')\\r\\n inout.saveBinary(dark,\\r\\n folder+'/'+fname+' - Dark Segment--'+str(pixelSize)+'--.tif')\\r\\n\\r\\n \\r\\n \\r\\n # Calculate area fraction.\\r\\n if self.varAreaFraction.get():\\r\\n # Status update.\\r\\n self.write(status, \\\"Calculating area fraction.\\\")\\r\\n areaFracBright = np.count_nonzero(bright) / \\\\\\r\\n (np.count_nonzero(bright) + np.count_nonzero(dark))\\r\\n # Results update.\\r\\n self.write(results, \\\"Bright phase area fraction: %.3f\\\" \\\\\\r\\n %(areaFracBright))\\r\\n\\r\\n # Refine the estimated diameters.\\r\\n estSizeB, _ = measure.diameter(bright, estSize)\\r\\n estSizeD, _ = measure.diameter(dark, estSize)\\r\\n\\r\\n \\r\\n # Calculate the diameter.\\r\\n if self.varDiameter.get():\\r\\n # Status update.\\r\\n self.write(status, \\\"Calculating ligament diameter.\\\")\\r\\n # Calculate.\\r\\n diameter_average_bright, diameter_SD_bright, diameter_all_bright =\\\\\\r\\n measure.diameter(bright, estSizeB,\\r\\n showSteps=showSteps,\\r\\n returnAll=True,\\r\\n pdf=pdf)\\r\\n diameter_num_bright = len(diameter_all_bright)\\r\\n diameter_average_dark, diameter_SD_dark, diameter_all_dark =\\\\\\r\\n measure.diameter(dark, estSizeD,\\r\\n showSteps=showSteps,\\r\\n returnAll=True,\\r\\n pdf=pdf)\\r\\n diameter_num_dark = len(diameter_all_dark)\\r\\n # Update estimated ligament sizes.\\r\\n estSizeB = diameter_average_bright\\r\\n estSizeD = diameter_average_dark\\r\\n # Results update.\\r\\n self.write(results, \\\"Bright phase diameter:\\\",\\r\\n round(diameter_average_bright,2), \\\"±\\\",\\r\\n round(diameter_SD_bright), \\\"pixels.\\\")\\r\\n self.write(results, \\\"Dark phase diameter:\\\",\\r\\n round(diameter_average_dark,2), \\\"±\\\",\\r\\n round(diameter_SD_dark), \\\"pixels.\\\")\\r\\n\\r\\n if outputExcel:\\r\\n df = pd.DataFrame(diameter_all_bright)\\r\\n df.to_excel(writer, sheet_name=\\\"Bright phase diameter data\\\")\\r\\n df = pd.DataFrame(diameter_all_dark)\\r\\n df.to_excel(writer, sheet_name=\\\"Dark phase diameter data\\\") \\r\\n \\r\\n # Fix estSizeB and estSizeD if there is a problem\\r\\n estSizeB = estSizeB_rough if np.isnan(estSizeB) else estSizeB \\r\\n estSizeD = estSizeD_rough if np.isnan(estSizeD) else estSizeD \\r\\n \\r\\n # Calculate the ligament length.\\r\\n if self.varLength.get():\\r\\n # Status update.\\r\\n self.write(status, \\\"Calculating ligament length.\\\")\\r\\n length_average_bright, length_SD_bright, length_all_bright = \\\\\\r\\n measure.length(bright, estSizeB,\\r\\n showSteps=showSteps,\\r\\n returnAll=True,\\r\\n pdf=pdf)\\r\\n try:\\r\\n length_num_bright = len(length_all_bright)\\r\\n except TypeError:\\r\\n length_num_bright = 0\\r\\n length_average_dark, length_SD_dark, length_all_dark = \\\\\\r\\n measure.length(dark, estSizeD,\\r\\n showSteps=showSteps,\\r\\n returnAll=True,\\r\\n pdf=pdf)\\r\\n try:\\r\\n length_num_dark = len(length_all_dark)\\r\\n except TypeError:\\r\\n length_num_dark = 0\\r\\n # Results update.\\r\\n if length_average_bright != 0:\\r\\n self.write(results, \\\"Bright phase ligament length:\\\",\\r\\n round(length_average_bright,2), \\\"±\\\",\\r\\n round(length_SD_bright), \\\"pixels.\\\")\\r\\n if length_average_dark != 0:\\r\\n self.write(results, \\\"Dark phase ligament length:\\\",\\r\\n round(length_average_dark,2), \\\"±\\\",\\r\\n round(length_SD_dark), \\\"pixels.\\\")\\r\\n\\r\\n if outputExcel:\\r\\n if length_average_bright != 0:\\r\\n df = pd.DataFrame(length_all_bright)\\r\\n df.to_excel(writer, sheet_name=\\\"Bright phase length data\\\")\\r\\n if length_average_dark != 0:\\r\\n df = pd.DataFrame(length_all_dark)\\r\\n df.to_excel(writer, sheet_name=\\\"Dark phase length data\\\") \\r\\n\\r\\n # Calculate average object area.\\r\\n if self.varArea.get():\\r\\n # Status update.\\r\\n self.write(status, \\\"Calculating average object area.\\\")\\r\\n area_average_bright, area_SD_bright, area_all_bright = \\\\\\r\\n measure.area(bright, estSizeB,\\r\\n showSteps=showSteps,\\r\\n returnAll=True)\\r\\n try:\\r\\n area_num_bright = len(area_all_bright)\\r\\n except TypeError:\\r\\n area_num_bright = 0\\r\\n area_average_dark, area_SD_dark, area_all_dark = \\\\\\r\\n measure.area(dark, estSizeD,\\r\\n showSteps=showSteps,\\r\\n returnAll=True)\\r\\n try:\\r\\n area_num_dark = len(area_all_dark)\\r\\n except TypeError:\\r\\n area_num_dark = 0\\r\\n # Results update.\\r\\n if area_average_bright != 0:\\r\\n self.write(results, \\\"Bright phase average object area:\\\",\\r\\n round(area_average_bright,2), \\\"±\\\",\\r\\n round(area_SD_bright), \\\"pixels^2.\\\")\\r\\n if area_average_dark != 0:\\r\\n self.write(results, \\\"Dark phase average object area:\\\",\\r\\n round(area_average_dark,2), \\\"±\\\",\\r\\n round(area_SD_dark), \\\"pixels^2.\\\")\\r\\n\\r\\n if outputExcel:\\r\\n if area_average_bright != 0:\\r\\n df = pd.DataFrame(area_all_bright)\\r\\n df.to_excel(writer, sheet_name=\\\"Bright phase area data\\\")\\r\\n if area_average_dark != 0:\\r\\n df = pd.DataFrame(area_all_dark)\\r\\n df.to_excel(writer, sheet_name=\\\"Dark phase area data\\\") \\r\\n\\r\\n # Calculate the sum connected length of each object.\\r\\n if self.varSumConnectedLength.get():\\r\\n # Status update.\\r\\n self.write(status, \\\"Calculating sum connected ligament length.\\\")\\r\\n sumLength_average_bright, sumLength_SD_bright, \\\\\\r\\n sumLength_all_bright = \\\\\\r\\n measure.connectedLength(bright, estSizeB,\\r\\n showSteps=showSteps,\\r\\n returnAll=True,\\r\\n pdf=pdf)\\r\\n try:\\r\\n sumLength_num_bright = len(sumLength_all_bright)\\r\\n except TypeError:\\r\\n sumLength_num_bright = 0\\r\\n sumLength_average_dark, sumLength_SD_dark, sumLength_all_dark = \\\\\\r\\n measure.connectedLength(dark, estSizeD,\\r\\n showSteps=showSteps,\\r\\n returnAll=True,\\r\\n pdf=pdf)\\r\\n try:\\r\\n sumLength_num_dark = len(sumLength_all_dark)\\r\\n except TypeError:\\r\\n sumLength_num_dark = 0\\r\\n # Results update.\\r\\n if sumLength_average_bright != 0:\\r\\n self.write(results, \\\"Bright phase sum connected length:\\\",\\r\\n round(sumLength_average_bright,2), \\\"±\\\",\\r\\n round(sumLength_SD_bright), \\\"pixels.\\\")\\r\\n if sumLength_average_dark != 0:\\r\\n self.write(results, \\\"Dark phase sum connected length:\\\",\\r\\n round(sumLength_average_dark,2), \\\"±\\\",\\r\\n round(sumLength_SD_dark), \\\"pixels.\\\")\\r\\n\\r\\n if outputExcel:\\r\\n if sumLength_average_bright != 0:\\r\\n df = pd.DataFrame(sumLength_all_bright)\\r\\n df.to_excel(writer,\\r\\n sheet_name=\\\"Bright phase sum length data\\\")\\r\\n if sumLength_average_dark != 0:\\r\\n df = pd.DataFrame(sumLength_all_dark)\\r\\n df.to_excel(writer,\\r\\n sheet_name=\\\"Dark phase sum length data\\\") \\r\\n\\r\\n # Save excel file\\r\\n if outputExcel:\\r\\n writer.save()\\r\\n\\r\\n # Save the pdf.\\r\\n if savePDF:\\r\\n plt.title('Summary')\\r\\n plt.axis('off')\\r\\n fs = 10\\r\\n yloc = 0.95\\r\\n xloc = 0.01\\r\\n space = 0.05\\r\\n out = 'Image: ' + fnametype\\r\\n plt.text(xloc, yloc, out, fontsize=fs)\\r\\n yloc -= space\\r\\n out = 'Pixel size: ' + str(pixelSize)\\r\\n plt.text(xloc, yloc, out, fontsize=fs)\\r\\n yloc -= space\\r\\n out = 'Bright phase area fraction: ' + str(round(areaFracBright,3))\\r\\n plt.text(xloc, yloc, out, fontsize=fs)\\r\\n yloc -= space\\r\\n out = 'Rough diameter estimate: ' + str(round(estSize,3))+' pixels.'\\r\\n plt.text(xloc, yloc, out, fontsize=fs)\\r\\n yloc -= space*2\\r\\n\\r\\n out = 'Bright phase:'\\r\\n plt.text(xloc, yloc, out, fontsize=fs, fontweight='bold')\\r\\n yloc -= space\\r\\n if diameter_average_bright != 0:\\r\\n out = ('Ligament diameter: ' +\\r\\n str(round(diameter_average_bright*pixelSize,3)) +\\r\\n ' ± ' + str(round(diameter_SD_bright*pixelSize,3)) +\\r\\n ' nm')\\r\\n plt.text(xloc, yloc, out, fontsize=fs)\\r\\n yloc -= space\\r\\n if length_average_bright != 0:\\r\\n out = ('Ligament length: ' +\\r\\n str(round(length_average_bright*pixelSize,3)) +\\r\\n ' ± ' + str(round(length_SD_bright*pixelSize,3)) +\\r\\n ' nm')\\r\\n plt.text(xloc, yloc, out, fontsize=fs)\\r\\n yloc -= space\\r\\n if area_average_bright != 0:\\r\\n out = ('Object area: ' +\\r\\n str(round(area_average_bright*pixelSize**2,3)) +\\r\\n ' ± ' + str(round(area_SD_bright*pixelSize**2,3)) +\\r\\n r' nm$^2$')\\r\\n plt.text(xloc, yloc, out, fontsize=fs)\\r\\n yloc -= space\\r\\n if sumLength_average_bright != 0:\\r\\n out = ('Sum connected length: ' +\\r\\n str(round(sumLength_average_bright*pixelSize,3)) +\\r\\n ' ± ' + str(round(sumLength_SD_bright*pixelSize,3)) +\\r\\n ' nm')\\r\\n plt.text(xloc, yloc, out, fontsize=fs)\\r\\n yloc -= space\\r\\n yloc -= space\\r\\n\\r\\n out = 'Dark phase:'\\r\\n plt.text(xloc, yloc, out, fontsize=fs, fontweight='bold')\\r\\n yloc -= space\\r\\n if diameter_average_dark != 0:\\r\\n out = ('Ligament diameter: ' +\\r\\n str(round(diameter_average_dark*pixelSize,3)) +\\r\\n ' ± ' + str(round(diameter_SD_dark*pixelSize,3)) +\\r\\n ' nm')\\r\\n plt.text(xloc, yloc, out, fontsize=fs)\\r\\n yloc -= space\\r\\n if length_average_dark != 0:\\r\\n out = ('Ligament length: ' +\\r\\n str(round(length_average_dark*pixelSize,3)) +\\r\\n ' ± ' + str(round(length_SD_dark*pixelSize,3)) +\\r\\n ' nm')\\r\\n plt.text(xloc, yloc, out, fontsize=fs)\\r\\n yloc -= space\\r\\n if area_average_dark != 0:\\r\\n out = ('Object area: ' +\\r\\n str(round(area_average_dark*pixelSize**2,3)) +\\r\\n ' ± ' + str(round(area_SD_dark*pixelSize**2,3)) +\\r\\n r' nm$^2$')\\r\\n plt.text(xloc, yloc, out, fontsize=fs)\\r\\n yloc -= space\\r\\n if sumLength_average_dark != 0:\\r\\n out = ('Sum connected length: ' +\\r\\n str(round(sumLength_average_dark*pixelSize,3)) +\\r\\n ' ± ' + str(round(sumLength_SD_dark*pixelSize,3)) +\\r\\n ' nm')\\r\\n plt.text(xloc, yloc, out, fontsize=fs)\\r\\n yloc -= space\\r\\n \\r\\n\\r\\n pdf.savefig()\\r\\n plt.close()\\r\\n pdf.close()\\r\\n\\r\\n # Append data to the saveAll\\r\\n newdata = np.array(\\r\\n [[fnametype,\\r\\n round(pixelSize,2),\\r\\n round(areaFracBright,3),\\r\\n round(estSize*pixelSize,3),\\r\\n round(diameter_average_bright*pixelSize,3),\\r\\n round(diameter_SD_bright*pixelSize,3),\\r\\n diameter_num_bright,\\r\\n round(diameter_average_dark*pixelSize,3),\\r\\n round(diameter_SD_dark*pixelSize,3),\\r\\n diameter_num_dark,\\r\\n round(length_average_bright*pixelSize,3),\\r\\n round(length_SD_bright*pixelSize,3),\\r\\n length_num_bright,\\r\\n round(length_average_dark*pixelSize,3),\\r\\n round(length_SD_dark*pixelSize,3),\\r\\n length_num_dark,\\r\\n round(area_average_bright*pixelSize**2,3),\\r\\n round(area_SD_bright*pixelSize**2,3),\\r\\n area_num_bright,\\r\\n round(area_average_dark*pixelSize**2,3),\\r\\n round(area_SD_dark*pixelSize**2,3),\\r\\n area_num_dark,\\r\\n round(sumLength_average_bright*pixelSize,3),\\r\\n round(sumLength_SD_bright*pixelSize,3),\\r\\n sumLength_num_bright,\\r\\n round(sumLength_average_dark*pixelSize,3),\\r\\n round(sumLength_SD_dark*pixelSize,3),\\r\\n sumLength_num_dark\\r\\n ]])\\r\\n \\r\\n\\r\\n \\r\\n self.saveAll = np.append(self.saveAll, newdata, axis=0)\\r\\n\\r\\n # Add new line to status and results\\r\\n self.write(results, '')\\r\\n self.write(status, '')\",\n \"def calculate_bandwidth(self, complist):\\n\\n self.type = complist[0]\\n self.spot = complist[2]\\n self.value = complist[1]\\n self.fail = False\\n\\n if self.spot == \\\"1\\\" or self.spot == \\\"2\\\":\\n # print \\\"Calculation if Loop 1st filter\\\"\\n if self.type == \\\"C\\\":\\n if self.c1 == 0:\\n self.c1 = self.value\\n else:\\n self.fail = True\\n else:\\n if self.r1 == 0:\\n self.r1 = self.value\\n else:\\n self.fail = True\\n\\n if self.spot == \\\"3\\\" or self.spot == \\\"4\\\":\\n # print \\\"Calculation if loop 2nd filter\\\"\\n if self.type == \\\"C\\\":\\n if self.c2 == 0:\\n self.c2 = self.value\\n else:\\n self.fail = True\\n else: #self.type == \\\"R\\\"\\n if self.r2 == 0:\\n self.r2 = self.value\\n else:\\n self.fail = True\\n\\n if self.c1 != 0 and self.c2 != 0 and self.r1 != 0 and self.r2 != 0:\\n cf_low = int((1/(2*pi*(self.r1)*(self.c1))/1000))\\n #print \\\"hello!\\\"\\n cf_low = str(cf_low)\\n self.cutoff_freql = cf_low\\n self.cutoff_freql_text = cf_low + \\\"K\\\"\\n print self.cutoff_freql_text\\n cf_high = int((1/(2*pi*(self.r2)*(self.c2))/1000))\\n cf_high = str(cf_high)\\n self.cutoff_freqh = cf_high\\n self.cutoff_freqh_text = cf_high + \\\"K\\\"\\n print self.cutoff_freqh_text\\n voltage_change = float((self.r2)/self.r1)\\n voltage = 5 + voltage_change\\n self.voltage = str(voltage)\\n print self.voltage\",\n \"def process(self, stream):\\n\\n # Extract data and weight arrays, averaging over beams\\n data = np.mean(stream.hfb[:], axis=2)\\n weight = np.mean(stream.weight[:], axis=2)\\n\\n # Number of samples per data point in the HFB data:\\n # n_samp = delta_nu * delta_t * (1 - frac_lost), where\\n # delta_nu is the frequency resolution (390.625 kHz / 128),\\n # delta_t the integration time (~10.066 s), and\\n # frac_lost is the fraction of integration that was lost upstream\\n freq_width = stream._data[\\\"index_map/freq/width\\\"][0] * 1e6\\n nsubfreq = len(stream._data[\\\"index_map/subfreq\\\"])\\n delta_nu = freq_width / nsubfreq\\n delta_t = np.median(np.diff(stream._data[\\\"index_map/time/ctime\\\"]))\\n frac_lost = stream[\\\"flags/frac_lost\\\"][0]\\n n_samp = delta_nu * delta_t * (1.0 - frac_lost)\\n\\n # Ideal radiometer equation\\n radiometer = data**2 * tools.invert_no_zero(n_samp)\\n\\n # Radiometer noise test: the sensitivity metric would be unity for\\n # an ideal radiometer, it would be higher for data with RFI\\n sensitivity_metric = 2.0 * tools.invert_no_zero(radiometer * weight)\\n\\n # Boolean mask indicating data that are contaminated by RFI\\n mask = sensitivity_metric > self.threshold\\n\\n # Create container to hold output\\n out = HFBRFIMask(axes_from=stream, attrs_from=stream)\\n\\n if self.keep_sens:\\n out.add_dataset(\\\"sens\\\")\\n out.sens[:] = sensitivity_metric\\n\\n # Save mask to output container\\n out.mask[:] = mask\\n\\n # Add beam selection to RFI mask attributes\\n out.attrs[\\\"beam\\\"] = stream._data[\\\"index_map\\\"][\\\"beam\\\"][:]\\n\\n # Return output container\\n return out\",\n \"def calculate(self) -> float:\",\n \"def calc_flux_array(self):\\n \\n # First determine the associated spectrum\\n self.compute_template_spectrum()\\n\\n # Calculate baseline counts to normalise fluxes we scan over\\n # Go from 10**(bin_min)*mean up to 10**(bin_max)*mean in nbins steps\\n b = self.setup_b_instance(0,add_ps_mask=True)\\n mean = np.sum(b.CTB_masked_compressed[0])/len(b.CTB_masked_compressed[0])\\n A_array = mean*10**np.linspace(self.bin_min,self.bin_max,self.nbins)\\n\\n # Array to get LLs when no profile likelihood run\\n norun = np.array([1.0, 1.0, 1.0, 1.0])\\n\\n # Now setup and compute the arrays\\n LL_array = np.array([]) \\n A_array_short = np.array([])\\n spect_array = np.array([])\\n\\n for i in range(len(A_array)):\\n print \\\"on i =\\\",i\\n # Calculate LL\\n if i == 0:\\n b1 = self.setup_b_instance(A_array[i],add_ps_mask=True)\\n else:\\n for key in b1.fixed_template_dict_nested.keys():\\n b1.fixed_template_dict_nested[key] = b1.fixed_template_dict_nested[key]*A_array[i]/A_array[i-1]\\n ll_val = b1.ll(norun,4,4)\\n # Make triangle\\n\\n # Append to arrays\\n LL_array = np.append(LL_array,ll_val)\\n A_array_short = np.append(A_array_short,A_array[i])\\n spect_array = self.spectrum*np.array(A_array_short)\\n\\n # Save output\\n np.save(work_dir+'ScanOutput/'+self.tag+'/En_array-'+str(self.flux_array_ebin)+'.npy',self.En_center)\\n np.save(work_dir+'ScanOutput/'+self.tag+'/LL_array-'+str(self.flux_array_ebin)+'.npy',LL_array)\\n np.save(work_dir+'ScanOutput/'+self.tag+'/Flux_array-'+str(self.flux_array_ebin)+'.npy',spect_array)\",\n \"def make_bispectra(self, bgwindow=4):\\n\\n bisp = lambda d, ij, jk, ki: d[:,ij] * d[:,jk] * n.conj(d[:,ki]) # bispectrum for pol data\\n\\n self.triples = self.make_triples()\\n self.bispectra = n.ma.zeros((len(self.data), len(self.triples)), dtype='complex')\\n\\n for i in xrange((bgwindow/2)+self.twidth, len(self.data)-( (bgwindow/2)+2*self.twidth )):\\n# for i in xrange((bgwindow/2)+self.twidth, len(self.data)-( (bgwindow/2)+self.twidth ), max(1,self.twidth)): # leaves gaps in data\\n diff = self.tracksub(i, bgwindow=bgwindow)\\n\\n if len(n.shape(diff)) == 1: # no track\\n continue\\n\\n diffmean = n.mean(diff, axis=2) # if all zeros, just make mean # bit of a hack\\n\\n for trip in xrange(len(self.triples)):\\n ij, jk, ki = self.triples[trip]\\n self.bispectra[i, trip] = bisp(diffmean, ij, jk, ki).mean(axis=0) # Stokes I bispectrum. Note we are averaging after forming bispectrum, so not technically a Stokes I bispectrum.\",\n \"def FIR_estimate(self):\\r\\n raise NotImplementedError\",\n \"def fbank(signal,samplerate=16000,winlen=0.025,winstep=0.01,\\n nfilt=26,nfft=512,lowfreq=0,highfreq=None,preemph=0.97): \\n highfreq= highfreq or samplerate/2\\n print \\\"preemph %s\\\"%(preemph)\\n signal = sigproc.preemphasis(signal,preemph)\\n frames = sigproc.framesig(signal, winlen*samplerate, winstep*samplerate)\\n matchframes(frames[0], frames[1])\\n pspec = sigproc.powspec(frames,nfft)\\n energy = pylab.sum(pspec,1) # this stores the total energy in each frame\\n energy = pylab.where(energy == 0, pylab.finfo(float).eps, energy) # if energy is zero, we get problems with log\\n fb = get_filterbanks(nfilt, nfft, samplerate, lowfreq, highfreq)\\n print \\\"len(fb) %s\\\"%(len(fb))\\n colour = \\\"k-\\\"\\n for i in range(len(fb)):\\n if colour == \\\"k-\\\":\\n colour = \\\"r-\\\"\\n else:\\n colour = \\\"k-\\\"\\n startedplot = False\\n midpoint = 0\\n for j in range(len(fb[i])):\\n if fb[i][j] > 0:\\n if startedplot == False:\\n startedplot = j\\n if j > 0:\\n pylab.plot([j-1, j], [fb[i][j-1], fb[i][j]], colour)\\n if fb[i][j] == 1.0:\\n midpoint = j\\n else:\\n if not startedplot == False:\\n pylab.plot([j-1, j], [fb[i][j-1], 0], colour)\\n try:\\n print \\\"slope to midpoint %.3f, slope from midpoint %.3f\\\"%(1.0/float(midpoint-startedplot), 1.0/float(midpoint-j+1))\\n except:\\n pass\\n break\\n pylab.show()\\n feat = pylab.dot(pspec, fb.T) # compute the filterbank energies\\n feat = pylab.where(feat == 0, pylab.finfo(float).eps, feat) # if feat is zero, we get problems with log\\n return feat, energy\",\n \"def _get_f50_worker(self, ra, dec, wave, sncut, \\n direct_sigmas = False, linewidth = None):\\n\\n logger = logging.getLogger(name=\\\"ShotSensitivity\\\")\\n\\n try:\\n [x for x in ra]\\n except TypeError:\\n ra = array([ra]) \\n dec = array([dec]) \\n wave = array([wave]) \\n\\n coords = SkyCoord(ra=ra, dec=dec, unit=\\\"deg\\\")\\n wave_rect = self.extractor.get_wave()\\n pixsize_aa = wave_rect[1] - wave_rect[0]\\n\\n # This will give 999 once the noise is scaled suitably\\n badval = 999*1e17/pixsize_aa\\n\\n # Size of window in wave elements\\n filter_len = 2*self.wavenpix + 1\\n\\n if type(wave) != type(None):\\n wave_passed = True\\n else:\\n wave_passed = False\\n convolution_filter = ones(filter_len) \\n mask = True*ones(len(coords), dtype=int)\\n \\n noise = []\\n \\n info_results = self.extractor.get_fiberinfo_for_coords(\\n coords,\\n radius=self.rad,\\n ffsky=self.ffsky,\\n return_fiber_info=True,\\n fiber_lower_limit=2, \\n verbose=False\\n )\\n\\n id_, aseps, aifux, aifuy, axc, ayc, ara, adec, adata, aerror, afmask, afiberid, \\\\\\n amultiframe = info_results\\n \\n \\n I = None\\n fac = None\\n norm_all = []\\n amp = [] \\n nan_fib_mask = []\\n\\n for i, c in enumerate(coords):\\n \\n sel = (id_ == i)\\n\\n if type(wave) != type(None):\\n logger.debug(\\\"Running on source {:f} {:f} {:f}\\\".format(ra[i], dec[i], wave[i]))\\n else:\\n logger.debug(\\\"Running on position {:f} {:f}\\\".format(ra[i], dec[i]))\\n\\n logger.debug(\\\"Found {:d} fibers\\\".format(sum(sel)))\\n\\n if sum(sel) > 0:\\n \\n # fiber properties \\n xc = axc[sel][0]\\n yc = ayc[sel][0]\\n ifux = aifux[sel]\\n ifuy = aifuy[sel]\\n data = adata[sel]\\n error = aerror[sel]\\n fmask = afmask[sel]\\n fiberid = afiberid[sel]\\n multiframe = amultiframe[sel]\\n seps = aseps[sel]\\n\\n # Flag the zero elements as bad\\n fmask[(abs(data) < 1e-30) | (abs(error) < 1e-30)] = False\\n\\n iclosest = argmin(seps)\\n\\n amp.append(fiberid[iclosest])\\n\\n if len(self.bad_amps) > 0:\\n amp_flag = amp_flag_from_fiberid(fiberid[iclosest], \\n self.bad_amps)\\n else:\\n amp_flag = True\\n \\n # XXX Could be faster - reloads the file every run\\n meteor_flag = meteor_flag_from_coords(c, self.shotid)\\n\\n if not (amp_flag and meteor_flag):\\n logger.debug(\\\"The data here are bad, position is masked\\\")\\n if wave_passed:\\n noise.append(badval)\\n norm_all.append(1.0)\\n # value doesn't matter as in amp flag\\n nan_fib_mask.append(True)\\n continue\\n else:\\n mask[i] = False\\n \\n weights, I, fac = self.extractor.build_weights(xc, yc, ifux, ifuy, self.moffat, \\n I=I, fac=fac, return_I_fac = True)\\n \\n # (See Greg Zeimann's Remedy code)\\n # normalized in the fiber direction\\n norm = sum(weights, axis=0) \\n weights = weights/norm\\n\\n\\n result = self.extractor.get_spectrum(data, error, fmask, weights,\\n remove_low_weights = False,\\n sclean_bad = self.sclean_bad,\\n return_scleaned_mask = True)\\n \\n spectrum_aper, spectrum_aper_error, scleaned = [res for res in result] \\n \\n if wave_passed:\\n \\n index = where(wave_rect >= wave[i])[0][0]\\n ilo = index - self.wavenpix\\n ihi = index + self.wavenpix + 1\\n\\n # If lower index less than zero, truncate\\n if ilo < 0:\\n ilo = 0\\n \\n if ihi < 0:\\n ihi = 0\\n \\n # Output lots of information for very detailed debugging\\n if logger.getEffectiveLevel() == logging.DEBUG: \\n logger.debug(\\\"Table of fibers:\\\")\\n logger.debug(\\\"# fiberid wave_index ifux ifuy weight noise mask\\\")\\n for fibidx, fid in enumerate(fiberid):\\n for wi, (tw, tnoise, tmask) in enumerate(zip((weights*norm)[fibidx, ilo:ihi], \\n error[fibidx, ilo:ihi], fmask[fibidx, ilo:ihi]), \\n ilo): \\n logger.debug(\\\"{:s} {:d} {:f} {:f} {:f} {:f} {:s}\\\".format(fid, wi, ifux[fibidx], \\n ifuy[fibidx], tw, tnoise, \\n str(tmask)))\\n\\n\\n # Mask source if bad values within the central 3 wavebins\\n nan_fib = bad_central_mask(weights*norm, logical_not(fmask), \\n index) \\n nan_fib_mask.append(nan_fib)\\n\\n # Account for NaN and masked spectral bins\\n bad = isnan(spectrum_aper_error[ilo:ihi])\\n goodfrac = 1.0 - sum(bad)/len(bad)\\n\\n\\n if all(isnan(spectrum_aper_error[ilo:ihi])):\\n sum_sq = badval\\n else:\\n sum_sq = \\\\\\n sqrt(nansum(square(spectrum_aper_error[ilo:ihi])/goodfrac))\\n\\n norm_all.append(mean(norm[ilo:ihi]))\\n noise.append(sum_sq)\\n else:\\n logger.debug(\\\"Convolving with window to get flux limits versus wave\\\")\\n\\n\\n # Use astropy convolution so NaNs are ignored\\n convolved_variance = convolve(square(spectrum_aper_error),\\n convolution_filter, \\n normalize_kernel=False)\\n std = sqrt(convolved_variance)\\n\\n # Also need to convolve aperture corrections to get\\n # a total apcor across the wavelength window\\n convolved_norm = convolve(norm,\\n convolution_filter, \\n normalize_kernel=True)\\n\\n # To get mean account for the edges in\\n # the convolution\\n for iend in range(self.wavenpix):\\n edge_fac = filter_len/(filter_len + iend - self.wavenpix)\\n convolved_norm[iend] *= edge_fac\\n convolved_norm[-iend - 1] *= edge_fac\\n\\n\\n # Mask wavelengths with too many bad pixels\\n # equivalent to nan_fib in the wave != None mode\\n wunorm = weights*norm\\n for index in range(len(convolved_variance)):\\n if not bad_central_mask(wunorm, logical_not(fmask), index):\\n std[index] = badval\\n\\n noise.append(std)\\n norm_all.append(convolved_norm)\\n \\n else:\\n if wave_passed:\\n noise.append(badval)\\n norm_all.append(1.0)\\n amp.append(\\\"000\\\")\\n nan_fib_mask.append(True)\\n else:\\n noise.append(badval*ones(len(wave_rect)))\\n norm_all.append(ones(len(wave_rect)))\\n amp.append(\\\"000\\\")\\n mask[i] = False\\n\\n\\n \\n # Apply the galaxy mask \\n gal_mask = ones(len(coords), dtype=int)\\n for gal_region in self.gal_regions:\\n dummy_wcs = create_dummy_wcs(gal_region.center,\\n imsize=2*gal_region.height)\\n # zero if near galaxy\\n gal_mask = gal_mask & invert(gal_region.contains(coords, dummy_wcs))\\n\\n noise = array(noise)\\n snoise = pixsize_aa*1e-17*noise\\n\\n if wave_passed:\\n\\n bad = (gal_mask < 0.5) | (snoise > 998) | isnan(snoise) | invert(nan_fib_mask)\\n\\n normnoise = snoise/norm_all\\n\\n if not direct_sigmas:\\n normnoise = self.f50_from_noise(normnoise, wave, sncut,\\n linewidth = linewidth)\\n\\n \\n normnoise[bad] = 999.\\n\\n return normnoise, amp, norm_all\\n\\n else:\\n mask[gal_mask < 0.5] = False\\n \\n if self.badshot:\\n mask[:] = False\\n\\n bad = (snoise > 998) | logical_not(isfinite(snoise))\\n normnoise = snoise/norm_all\\n\\n if not direct_sigmas:\\n normnoise = self.f50_from_noise(normnoise, wave, sncut,\\n linewidth = linewidth)\\n\\n normnoise[bad] = 999\\n\\n return normnoise, mask, amp, norm_all\",\n \"def run(self):\\n qubit = self.qubit\\n\\n routine = self.routine\\n\\n # Saving some typing for parameters that are only read ;)\\n allowed_delta_f = self.get_param_value(\\\"allowed_delta_f\\\")\\n f_unit = self.get_param_value(\\\"f_unit\\\")\\n f_factor = self.get_param_value(\\\"f_factor\\\")\\n delta_f_unit = self.get_param_value(\\\"delta_f_unit\\\")\\n delta_f_factor = self.get_param_value(\\\"delta_f_factor\\\")\\n max_iterations = self.get_param_value(\\\"max_iterations\\\")\\n transition = self.get_param_value(\\\"transition_name\\\")\\n\\n # Finding the ramsey experiment in the pipulse calibration\\n pipulse_calib = routine.routine_steps[-1]\\n ramsey = pipulse_calib.routine_steps[-1]\\n\\n # Transition frequency from last Ramsey\\n freq = qubit[f\\\"{transition}_freq\\\"]()\\n\\n # Retrieving the frequency difference\\n max_waiting_seconds = self.get_param_value(\\\"max_waiting_seconds\\\")\\n for i in range(max_waiting_seconds):\\n try:\\n routine.delta_f = (\\n ramsey.analysis.proc_data_dict[\\n \\\"analysis_params_dict\\\"][\\n qubit.name][\\\"exp_decay\\\"][\\\"new_qb_freq\\\"] -\\n ramsey.analysis.proc_data_dict[\\n \\\"analysis_params_dict\\\"][\\n qubit.name][\\\"exp_decay\\\"][\\\"old_qb_freq\\\"])\\n break\\n except KeyError:\\n log.warning(\\n \\\"Could not find frequency difference between current \\\"\\n \\\"and last Ramsey measurement, delta_f not updated\\\")\\n break\\n except AttributeError:\\n # FIXME: Unsure if this can also happen on real set-up\\n log.warning(\\n \\\"Analysis not yet run on last Ramsey measurement, \\\"\\n \\\"frequency difference not updated\\\")\\n time.sleep(1)\\n\\n # Progress update\\n if self.get_param_value('verbose'):\\n print(f\\\"Iteration {routine.iteration}, {transition}-freq \\\"\\n f\\\"{freq / f_factor} {f_unit}, frequency \\\"\\n f\\\"difference = {routine.delta_f / delta_f_factor} \\\"\\n f\\\"{delta_f_unit}\\\")\\n\\n # Check if the absolute frequency difference is small enough\\n if np.abs(routine.delta_f) < allowed_delta_f:\\n # Success\\n if self.get_param_value('verbose'):\\n print(f\\\"{transition}-frequency found to be \\\"\\n f\\\"{freq / f_factor} {f_unit} within \\\"\\n f\\\"{allowed_delta_f / delta_f_factor} \\\"\\n f\\\"{delta_f_unit} of previous value.\\\")\\n\\n elif routine.iteration < max_iterations:\\n # No success yet, adding a new rabi-ramsey and decision step\\n if self.get_param_value('verbose'):\\n print(f\\\"Allowed error (\\\"\\n f\\\"{allowed_delta_f / delta_f_factor} \\\"\\n f\\\"{delta_f_unit}) not yet achieved, adding new\\\"\\n \\\" round of PiPulse calibration...\\\")\\n\\n routine.add_next_pipulse_step()\\n\\n step_settings = {'qubits': self.qubits}\\n routine.add_step(\\n FindFrequency.Decision,\\n 'decision',\\n step_settings,\\n )\\n\\n routine.iteration += 1\\n return\\n\\n else:\\n # No success yet, reached max iterations\\n msg = (f\\\"{self.step_label} routine finished for {qubit.name}, \\\"\\n \\\"desired precision not necessarily achieved within the \\\"\\n f\\\"maximum number of iterations ({max_iterations}).\\\")\\n log.warning(msg)\\n\\n if self.get_param_value('verbose'):\\n print(msg)\\n\\n if self.get_param_value('verbose'):\\n # Printing termination update\\n print(f\\\"FindFrequency routine finished: \\\"\\n f\\\"{transition}-frequencies for {qubit.name} \\\"\\n f\\\"is {freq / f_factor} {f_unit}.\\\")\",\n \"def spectrum(datapath, run, forcebins = False):\\n runpath = datapath + '/' + run\\n events = [evnt for evnt in listdir(runpath) if not isfile(join(runpath,evnt))]\\n allTraces = []\\n total_time = 0\\n pulses = {'zero': [], 'one': [], 'two': [], 'three': [], 'other': []}\\n times = {'zero': [], 'one': [], 'two': [], 'three': [], 'other': []}\\n #camextratime = 25e-6\\n for event in events:\\n if int(event)> 3:\\n break\\n print(event)\\n e = sbc.DataHandling.GetSBCEvent.GetEvent(runpath,event)\\n if e[\\\"slowDAQ\\\"][\\\"loaded\\\"]:\\n #print(e[\\\"fastDAQ\\\"].keys())\\n cgate = e[\\\"fastDAQ\\\"][\\\"CAMgate\\\"]\\n #dcam = np.diff(cgate)\\n fdt = e['fastDAQ']['time']\\n #camOffTimes = np.sort(np.array([fdt[i] for i in range(len(dcam)) if dcam[i] > 0.5]))\\n \\n #camOnTimes = np.sort(np.array([fdt[i] for i in range(len(dcam)) if dcam[i] < 0.5]))\\n fddt = fdt[1]-fdt[0]\\n tfast = fdt[-1]-fdt[0]\\n LED_on = [fdt[i] for i in range(len(cgate)) if cgate[i]<-0.5]\\n blockedFraction = ((len(LED_on)*fddt))/tfast\\n print(blockedFraction)\\n tr = e[\\\"PMTtraces\\\"]\\n trac = tr[\\\"traces\\\"]\\n dt = tr[\\\"dt\\\"]\\n #event_time = (tr['t0_sec'][-1]+tr['t0_frac'][-1]-tr['t0_sec'][0] - tr['t0_frac'][0])[0]\\n event_time = (((e[\\\"slowDAQ\\\"][\\\"elapsed_time\\\"][-1]-e[\\\"slowDAQ\\\"][\\\"elapsed_time\\\"][0]))*(1-blockedFraction))\\n #print(event_time)\\n total_time += event_time\\n\\n #f,axes = plt.subplots(1,5,sharey=True)\\n #f.suptitle(runpath+\\\"/\\\"+str(event))\\n #pmttracetime = e[\\\"PMTtraces\\\"][\\\"t0_sec\\\"][:,0]+e[\\\"PMTtraces\\\"][\\\"t0_frac\\\"][:,0]\\n #d=sbc.AnalysisModules.PMTfastDAQalignment.PMTandFastDAQalignment(e)\\n #pmtalign = d[\\\"PMT_trigt0_sec\\\"]+d[\\\"PMT_trigt0_frac\\\"]\\n #tracetimes = pmttracetime - pmtalign\\n #camoffindex = 0\\n #camonindex = 0\\n for i in range(len(trac)):\\n #print(i)\\n \\\"\\\"\\\"\\n thistracetime = tracetimes[i]\\n \\n #nearestcamoff = min(camOffTimes, key=lambda x:abs(x-thistracetime))\\n #nearestcamon = min(camOnTimes, key=lambda x:abs(x-thistracetime))\\n print(camOffTimes[camoffindex])\\n print(thistracetime)\\n if thistracetime > camOffTimes[camoffindex]:\\n camoffindex += 1\\n if thistracetime > camOnTimes[camonindex]:\\n camonindex += 1 \\n if camoffindex<len(camOffTimes)-1:\\n if abs(camOffTimes[camoffindex]-thistracetime)<camextratime:\\n print('excluding a trace near a camera off')\\n continue\\n if camonindex<len(camOnTimes)-1:\\n if abs(camOnTimes[camonindex]-thistracetime)<camextratime:\\n print('excluding a trace near a camera on')\\n continue\\n \\\"\\\"\\\"\\n trace = np.fabs(trac[i][0])\\n if max(trace) == 128:\\n trace = stitchTraces(trace,np.fabs(e[\\\"PMTtraces\\\"][\\\"traces\\\"][i][1]))\\n dt_tr = dt[i][0]\\n\\n # populate dictionaries arrays based on how many pulses there were\\n [a,n,totInt,pktimes] = SBC_pulse_integrator_bressler(trace,dt_tr)\\n if n == 0:\\n number = 'zero'\\n allTraces.append(a)\\n elif n == 1:\\n number = 'one'\\n allTraces.append(a)\\n times['one'].append(pktimes[0])\\n elif n == 2:\\n number = 'two'\\n allTraces.append(a)\\n elif n == 3:\\n number = 'three'\\n allTraces.append(a)\\n else:\\n number = 'other'\\n allTraces.append(a)\\n \\\"\\\"\\\"\\n #if a != None:\\n if isZero:\\n if j < 5:\\n if isNegative:\\n if random() >0:\\n print(runpath+\\\"/\\\"+str(event)+\\\" pmt trace \\\"+str(i))\\n tPMT = np.arange(len(trace))*dt_tr\\n axes[j].plot(tPMT,trace,lw=3)\\n axes[j].set_xlabel(\\\"time (s)\\\",fontsize=25)\\n axes[j].set_ylabel(\\\"PMT response (ADC)\\\",fontsize=25)\\n j+=1\\n \\n \\n plt.show\\n \\\"\\\"\\\"\\n pulses[number].append(a)\\n gc.collect()\\n \\n \\n for k in pulses:\\n pulses[k] = [x for x in pulses[k] if x != None]\\n \\n allTraces = [x for x in allTraces if x != None]\\n \\n plt.figure()\\n\\n Nbins = int(np.floor(np.sqrt(len(allTraces))))\\n allvals, bins, _ = plt.hist(allTraces,Nbins,label='all traces')\\n \\n areaVals = {'zero': [], 'one': [], 'two': [], 'three': [], 'other': []}\\n for k in pulses:\\n if k != 'other':\\n areaVals[k], _, _ = plt.hist(pulses[k],bins,histtype = 'step',\\n linewidth = 3,label= k+' hits')\\n plt.legend(fontsize=12)\\n plt.show() \\n #spe_spectrum = areaVals['one']\\n \\n #def gaussian(x,mu,sigma,amplitude):\\n # return amplitude * np.exp(-((x - mu) /(np.sqrt(2)* sigma))**2 )\\n \\n #params_spe, params_cov_spe = scipy.optimize.curve_fit(gaussian,bins[:len(areaVals['one'])],\\n # spe_spectrum,\\n # p0=[0.4e8,1e7,40])\\n #params_twohits, params_cov_twohits = scipy.optimize.curve_fit(gaussian,\\n # bins[:len(areaVals['two'])],\\n # areaVals['two'],\\n # p0=[0.8e8,1e7,10])\\n #mu_spe = params_spe[0]\\n #mu_2 = params_twohits[0] - mu_spe\\n #print(mu_spe)\\n #print(mu_2)\\n \\n #mu_avg = (mu_spe + mu_2)*0.5\\n #mu_avg = get_gain(datapath,run)\\n mu_avg = 1e7\\n print(mu_avg)\\n\\n \\n plt.figure()\\n plt.grid(True)\\n if isinstance(forcebins,np.ndarray):\\n bins=forcebins\\n fullspect,_,_=plt.hist([t/mu_avg for t in allTraces],\\n forcebins,label='all traces')\\n \\n else:\\n fullspect,bins,_=plt.hist([t/mu_avg for t in allTraces],\\n int(np.floor(np.sqrt(len(allTraces)))),label='all traces')\\n \\n #print(bins)\\n plt.yscale('log')\\n plt.xlabel('phe based on a gain of '+str(mu_avg)+' electrons per phe')\\n plt.legend()\\n plt.show\\n print(sum(fullspect)/total_time)\\n print(\\\"The Total Exposure Time of run \\\"+str(runpath)+ \\\" was \\\"+str(total_time)+\\\" Seconds\\\")\\n print(\\\"The overall PMT trigger rate was \\\" + str(len(allTraces)/total_time)+ \\\"Hz\\\")\\n return [fullspect,bins,total_time]\",\n \"def bf_analysis():\\r\\n\\r\\n global params\\r\\n n = params['n']\\r\\n level = params['level']\\r\\n bfmin = params['bfmin']\\r\\n bfmax = params['bfmax']\\r\\n bfstep = params['bfstep']\\r\\n ns = params['ns']\\r\\n po = params['po']\\r\\n pe = params['pe']\\r\\n pf = params['pf']\\r\\n bf_dir = create_dir(TIMES_PATH + 'bf')\\r\\n filename = datetime.datetime.now().strftime(DATE_FORMAT) + '.csv'\\r\\n with open(bf_dir + filename, 'wb') as csvfile:\\r\\n fw = csv.writer(csvfile)\\r\\n fw.writerow(('lv', 'ns', 'bf', 'nt', 'no', 'ne', 'nf',\\r\\n 'method1', 'method2', 'method3_1', 'method3_2'))\\r\\n bf = bfmin\\r\\n while bf <= bfmax:\\r\\n nt = int(round(bf * ns))\\r\\n no = max(int(round(po * nt)), 1)\\r\\n ne = max(int(round(pe * no)), 1)\\r\\n nf = max(int(round(pf * nt)), 1)\\r\\n times = [0] * 4\\r\\n for i in range(n):\\r\\n times = map(sum, zip(times, get_times(level, ns, nt, no, ne, nf)))\\r\\n show_progress('bf', bf, bfmin, bfmax, bfstep, i, n)\\r\\n times = map(lambda x: float(x) / n, times)\\r\\n fw.writerow((level, ns, bf, nt, no, ne, nf) + tuple(times))\\r\\n bf += bfstep\\r\\n csvfile.close()\",\n \"def bruno_mes(self):\\n MI = -125\\n MA = 125\\n INCR = 19\\n####################################################################\\n ### CHANNEL 1\\n self.write('CHN 1')\\n self.write('CHN?')\\n print 'Acting on channel:',self.read()\\n self.write('WAVE ARB')\\n self.write('ARBLOAD ARB1')\\n self.write('FREQ 100')\\n self.write('DCOFFS 0.05')\\n self.write('AMPL 0.1')\\n \\n l =(125,-125,125)#arange(MI,MA,INCR) # the ramp\\n# lll = copy(l)[::-1][1:-1]\\n# l = concatenate((l,lll))\\n self.write_array_to_byte(l,1)\",\n \"def test_baseline_spect(self, b0, x0, a, fwhm):\\n x = np.linspace(-1, 1, 100)\\n sigma = fwhm / np.sqrt(8 * np.log(2))\\n y = a * np.exp(-((x - x0) ** 2) / (2 * sigma**2)) + b0\\n\\n b0_guess = guess.constant_spectral_offset(y)\\n\\n self.assertAlmostEqual(b0, b0_guess, delta=0.1)\",\n \"def calculate(self):\",\n \"def calculate_fmin_Band(self):\\n if self.F0 is None and self.Band is not None:\\n raise ValueError(\\\"Band option can only be set if F0 is also given.\\\")\\n elif self.F0 is not None and self.Band is not None:\\n self.fmin = self.F0 - 0.5 * self.Band\\n elif self.noiseSFTs and not self.mfd.endswith(\\\"v4\\\"):\\n logger.info(\\\"Generating SFTs with full bandwidth from noiseSFTs.\\\")\\n elif self.F0 is None:\\n err_msg = \\\"Need F0 and Band,\\\"\\n if not self.mfd.endswith(\\\"v4\\\"):\\n err_msg += \\\" or noiseSFTs,\\\"\\n err_msg += \\\" or at least F0 to auto-estimate bandwidth around it.\\\"\\n if self.mfd.endswith(\\\"v4\\\"):\\n err_msg += (\\n f\\\" Since we are using {self.mfd}, we need this even with noiseSFTs.\\\"\\n )\\n raise ValueError(err_msg)\\n else:\\n extraBins = (\\n # matching extraBinsFull in XLALCreateFstatInput():\\n # https://lscsoft.docs.ligo.org/lalsuite/lalpulsar/_compute_fstat_8c_source.html#l00490\\n lalpulsar.FstatOptionalArgsDefaults.Dterms\\n + int(lalpulsar.FstatOptionalArgsDefaults.runningMedianWindow / 2)\\n + 1\\n )\\n logger.info(\\n \\\"Estimating required SFT frequency range from properties\\\"\\n \\\" of signal to inject plus {:d} extra bins either side\\\"\\n \\\" (corresponding to default F-statistic settings).\\\".format(extraBins)\\n )\\n minCoverFreq, maxCoverFreq = utils.get_covering_band(\\n tref=self.tref,\\n tstart=self.tstart,\\n tend=self.tend,\\n F0=self.F0,\\n F1=self.F1,\\n F2=self.F2,\\n F0band=0.0,\\n F1band=0.0,\\n F2band=0.0,\\n maxOrbitAsini=getattr(self, \\\"asini\\\", 0.0),\\n minOrbitPeriod=getattr(self, \\\"period\\\", 0.0),\\n maxOrbitEcc=getattr(self, \\\"ecc\\\", 0.0),\\n )\\n self.fmin = minCoverFreq - extraBins / self.Tsft\\n self.Band = maxCoverFreq - minCoverFreq + 2 * extraBins / self.Tsft\\n if hasattr(self, \\\"fmin\\\"):\\n logger.info(\\n \\\"Generating SFTs with fmin={}, Band={}\\\".format(self.fmin, self.Band)\\n )\",\n \"def spectral_check(self, ):\\r\\n a, b = self.dfa, self.dfm.copy()\\r\\n b['ts_a']=a.ts\\r\\n b['flux_a'] = a.flux\\r\\n b['dflux'] = (b.flux-b.flux_a)/b.flux_unc\\r\\n b['eflux100_a'] = a.eflux100\\r\\n b['deflux'] = (b.eflux100-b.eflux100_a)/b.eflux100_unc\\r\\n b['pindex_a'] = a.pindex\\r\\n b['gdelta'] = (b.pindex-b.pindex_a)/b.pindex_unc\\r\\n self.dfm = b # since copy\\r\\n\\r\\n fig,axx = plt.subplots(1,2, figsize=(10,5), sharey=True)\\r\\n hkw = dict(bins=np.linspace(-5,5,51), histtype='step', lw=2, density=True)\\r\\n\\r\\n cut = (b.ts>50) & ~pd.isnull(b.deflux) & ~pd.isnull(b.gdelta) &\\\\\\r\\n (b.modelname==\\\"LogParabola\\\") & (b.pindex<3) & (b.pindex>0.5) &\\\\\\r\\n (b.e0>500) &(b.eflux100_unc>0) &(b.pindex_unc>0)\\r\\n self.check_total = sum(cut)\\r\\n for ax, title, val in zip(axx.flatten(), ['Energy Flux', 'Spectral index'], [b.deflux, b.gdelta]): \\r\\n\\r\\n df=val[cut]\\r\\n ax.hist(df.clip(-5,5), label='mean {:5.2f}\\\\nstd {:5.2f}'.format(df.mean(),df.std()), **hkw);\\r\\n ax.grid(alpha=0.5); \\r\\n x=np.linspace(-4,4)\\r\\n ax.plot(x, stats.norm.pdf(x), '--g' );\\r\\n ax.set(xlabel='normalized fit deviation', title=title, )\\r\\n ax.legend(loc='upper left',prop=dict(family='monospace'))\\r\\n fig.suptitle('Normalized devations of fit from model', fontsize=16);\\r\\n\\r\\n return fig\",\n \"def brate(self):\\n try:\\n return self.pos / self.runtime\\n except ZeroDivisionError:\\n return 0\",\n \"def test_filt_abmag(self):\\n sun = Sun.from_builtin('E490_2014')\\n V = get_bandpass('johnson v')\\n wave, fluxd = sun.filt(V, unit=u.ABmag)\\n assert np.isclose(fluxd.value, -26.77, atol=0.007)\",\n \"def detect_bispectra(self, sigma=5., tol=1.3, Q=0, show=0, save=0):\\n try:\\n ba = self.bispectra\\n except AttributeError:\\n print 'Need to make bispectra first.'\\n return\\n\\n# ntr = lambda num: num*(num-1)*(num-2)/6 # theoretical number of triples\\n ntr = lambda num: len(self.triples) # consider possibility of zeros in data and take mean number of good triples over all times\\n\\n # using s=S/Q\\n# mu = lambda s: s/(1+s) # for independent bispectra, as in kulkarni 1989\\n mu = lambda s: 1. # for bispectra at high S/N from visibilities?\\n sigbQ3 = lambda s: n.sqrt((1 + 3*mu(s)**2) + 3*(1 + mu(s)**2)*s**2 + 3*s**4) # from kulkarni 1989, normalized by Q**3, also rogers et al 1995\\n s = lambda basnr, nants: (2.*basnr/n.sqrt(ntr(nants)))**(1/3.)\\n\\n # measure SNR_bl==Q from sigma clipped times with normal mean and std of bispectra. put into time,dm order\\n bamean = ba.real.mean(axis=1)\\n bastd = ba.real.std(axis=1)\\n\\n (meanmin,meanmax) = sigma_clip(bamean) # remove rfi\\n (stdmin,stdmax) = sigma_clip(bastd) # remove rfi\\n clipped = n.where((bamean > meanmin) & (bamean < meanmax) & (bastd > stdmin) & (bastd < stdmax) & (bamean != 0.0))[0] # remove rf\\n\\n bameanstd = ba[clipped].real.mean(axis=1).std()\\n basnr = bamean/bameanstd\\n if Q:\\n print 'Using given Q =', Q\\n else:\\n Q = ((bameanstd/2.)*n.sqrt(ntr(self.nants)))**(1/3.)\\n # Q = n.median( bastd[clipped]**(1/3.) ) # alternate for Q\\n print 'Estimating noise per baseline from data. Q =', Q\\n self.Q = Q\\n\\n # detect\\n cands = n.where( (bastd/Q**3 < tol*sigbQ3(s(basnr, self.nants))) & (basnr > sigma) )[0] # define compact sources with good snr\\n print cands\\n\\n # plot snrb lc and expected snr vs. sigb relation\\n if show or save:\\n p.figure()\\n ax = p.axes()\\n p.subplot(211)\\n p.title(str(self.nskip/self.nbl)+' nskip, ' + str(len(cands))+' candidates', transform = ax.transAxes)\\n p.plot(basnr, 'b.')\\n if len(cands) > 0:\\n p.plot(cands, basnr[cands], 'r*')\\n p.ylim(-2*basnr[cands].max(),2*basnr[cands].max())\\n p.xlabel('Integration')\\n p.ylabel('SNR$_{bisp}$')\\n p.subplot(212)\\n p.plot(bastd/Q**3, basnr, 'b.')\\n\\n # plot reference theory lines\\n smax = s(basnr.max(), self.nants)\\n sarr = smax*n.arange(0,51)/50.\\n p.plot(sigbQ3(sarr), 1/2.*sarr**3*n.sqrt(ntr(self.nants)), 'k')\\n p.plot(tol*sigbQ3(sarr), 1/2.*sarr**3*n.sqrt(ntr(self.nants)), 'k--')\\n p.plot(bastd[cands]/Q**3, basnr[cands], 'r*')\\n\\n if len(cands) > 0:\\n p.axis([0, tol*sigbQ3(s(basnr[cands].max(), self.nants)), -0.5*basnr[cands].max(), 1.1*basnr[cands].max()])\\n\\n # show spectral modulation next to each point\\n for candint in cands:\\n sm = n.single(round(self.specmod(candint),1))\\n p.text(bastd[candint]/Q**3, basnr[candint], str(sm), horizontalalignment='right', verticalalignment='bottom')\\n p.xlabel('$\\\\sigma_b/Q^3$')\\n p.ylabel('SNR$_{bisp}$')\\n if save:\\n if save == 1:\\n savename = self.file.split('.')[:-1]\\n savename.append(str(self.nskip/self.nbl) + '_bisp.png')\\n savename = string.join(savename,'.')\\n elif isinstance(save, string):\\n savename = save\\n print 'Saving file as ', savename\\n p.savefig(self.pathout+savename)\\n\\n return basnr[cands], bastd[cands], cands\",\n \"def _calibrate_measurement(self):\\n\\n cold_blackbody = bb_radiance(self.cbb.header.cbb_temperature + 273.15,\\n self.cbb.data.wavelength)\\n warm_blackbody = bb_radiance(self.wbb.header.wbb_temperature + 273.15,\\n self.wbb.data.wavelength)\\n\\n self.wbb.data.average_spectrum[0] = 1\\n self.wbb.data.average_spectrum[2047] = 1\\n\\n calibration_slope = ((warm_blackbody - cold_blackbody) /\\n (self.wbb.data.average_spectrum - self.cbb.data.average_spectrum))\\n calibration_offset = warm_blackbody - (self.wbb.data.average_spectrum * \\n calibration_slope)\\n\\n self.wbb.calibrate_file(calibration_slope, calibration_offset)\\n self.cbb.calibrate_file(calibration_slope, calibration_offset)\\n self.sam.calibrate_file(calibration_slope, calibration_offset)\\n\\n if not self.dwr is None:\\n self.dwr.calibrate_file(calibration_slope, calibration_offset)\\n\\n plate_temperature = self.dwr.header.spare_f[0]\\n if (self.plate == -1) :\\n plate_emissivity = self.dwr.header.spare_f[1]\\n\\n plate_blackbody = bb_radiance(plate_temperature + 273.15,\\n self.dwr.data.wavelength)\\n plate_emission = plate_emissivity * plate_blackbody\\n\\n self.dwr.data.average_spectrum = ((self.dwr.data.average_spectrum - \\n plate_emission) / (1 - plate_emissivity))\",\n \"def query(self):\\n self._measurements[self.KEY_FMIX].df = self.fetch_data_fmix()\\n self._measurements[self.KEY_EMIS].df = self.co2_calc(self._measurements[self.KEY_FMIX].df)\",\n \"def retarder(self):\\n self.spectrum = self.spectrum\",\n \"def calculate(self, raw=False):\\n \\n with energy_units(\\\"int\\\"):\\n if self.system is not None:\\n if isinstance(self.system,Molecule):\\n #self._calculate_Molecule(rwa) \\n spect = self._calculate_monomer(raw=raw)\\n elif isinstance(self.system, Aggregate):\\n spect = self._calculate_aggregate( \\n relaxation_tensor=\\n self._relaxation_tensor,\\n rate_matrix=\\n self._rate_matrix,\\n relaxation_hamiltonian=\\n self._relaxation_hamiltonian,\\n raw=raw)\\n else:\\n raise Exception(\\\"System to calculate spectrum for not defined\\\")\\n \\n return spect\",\n \"def make_bispectra(self, bgwindow=4):\\n\\n bisp = lambda d, ij, jk, ki: d[:,ij] * d[:,jk] * n.conj(d[:,ki]) # bispectrum for pol data\\n# bisp = lambda d, ij, jk, ki: n.complex(d[ij] * d[jk] * n.conj(d[ki])) # without pol axis\\n\\n triples = self.make_triples()\\n meanbl = self.data.mean(axis=2).mean(axis=0) # find bls with no zeros in either pol to ignore in triples\\n self.triples = triples[n.all(meanbl[triples][:,0] != 0j, axis=1) & n.all(meanbl[triples][:,1] != 0j, axis=1) & n.all(meanbl[triples][:,2] != 0j, axis=1)] # only take triples if both pols are good. may be smaller than set for an individual pol\\n\\n # set up arrays for bispectrum and for weighting data (ignoring zeros)\\n bispectra = n.zeros((len(self.dmarr), len(self.data), len(self.triples)), dtype='complex')\\n truearr = n.ones( (self.npol, self.nbl, len(self.chans)))\\n falsearr = n.zeros( (self.npol, self.nbl, len(self.chans)))\\n\\n # iterate over dm trials and integrations\\n for d in xrange(len(self.dmarr)):\\n twidth = n.round(self.twidths[d])\\n dmwidth = int(n.round(n.max(self.dmtrack0[d][0]) - n.min(self.dmtrack0[d][0])))\\n\\n for i in xrange((bgwindow/2)+twidth, len(self.data)-( (bgwindow/2)+2*twidth+dmwidth )): # dmwidth avoided at end, others are split on front and back side of time iteration\\n# for i in xrange((bgwindow/2)+twidth, len(self.data)-( (bgwindow/2)+twidth+dmwidth ), max(1,twidth/2)): # can step by twidth/2, but messes up data products\\n diff = self.tracksub(d, i, bgwindow=bgwindow)\\n\\n if len(n.shape(diff)) == 1: # no track\\n continue\\n\\n# **need to redo for self.flags**\\n weightarr = n.where(diff != 0j, truearr, falsearr) # ignore zeros in mean across channels # bit of a hack\\n try:\\n diffmean = n.average(diff, axis=2, weights=weightarr)\\n except ZeroDivisionError:\\n diffmean = n.mean(diff, axis=2) # if all zeros, just make mean # bit of a hack\\n\\n for trip in xrange(len(self.triples)):\\n ij, jk, ki = self.triples[trip]\\n bispectra[d, i, trip] = bisp(diffmean, ij, jk, ki).mean(axis=0) # Stokes I bispectrum. Note we are averaging after forming bispectrum, so not technically a Stokes I bispectrum.\\n print 'dedispersed for ', self.dmarr[d]\\n self.bispectra = n.ma.masked_array(bispectra, bispectra == 0j)\",\n \"def calculate(self):\\n\\n beta = 1 # or 0.5 or 2 can also calculate F2 or F0.5 measure\\n\\n beta_squared = beta * beta\\n precision = Precision()\\n precision.confusion_matrix = self.confusion_matrix\\n precision = precision.calculate()\\n recall = Recall()\\n recall.confusion_matrix = self.confusion_matrix\\n recall = recall.calculate()\\n\\n denominator = beta_squared * precision + recall\\n\\n if denominator != 0:\\n return (1 + beta_squared) * ((precision * recall) / denominator)\\n else:\\n return 0\",\n \"def Bo_Bosol_calc(self):\\n self.Bosol = (self.g*self.alpha * self.srflx ) \\n #ZEROS FOR T3W APPLICATION\\n self.Bo = np.zeros([self.b.shape[0]])\",\n \"def calc(self):\\n\\n # the following if query ensures that volume- and interaction-terms\\n # are only calculated if tau > 0.\\n # (to avoid nan-values from invalid function-evaluations)\\n\\n if self.V.tau.shape == (1,):\\n Isurf = self.surface()\\n # differentiation for non-existing canopy, as otherwise NAN values\\n if self.V.tau > 0.:\\n Ivol = self.volume()\\n if self.int_Q is True:\\n Iint = self.interaction()\\n else:\\n Iint = np.array([0.])\\n else:\\n Ivol = np.array([0.])\\n Iint = np.array([0.])\\n else:\\n # calculate surface-term (valid for any tau-value)\\n Isurf = self.surface()\\n\\n # store initial parameter-values\\n old_t_0 = self.t_0\\n old_p_0 = self.p_0\\n old_t_ex = self.t_ex\\n old_p_ex = self.p_ex\\n\\n old_tau = self.V._get_tau()\\n old_omega = self.V._get_omega()\\n old_NN = self.SRF._get_NormBRDF()\\n\\n # set mask for tau > 0.\\n mask = old_tau > 0.\\n valid_index = np.where(mask)\\n inval_index = np.where(~mask)\\n\\n # set parameter-values to valid values for calculation\\n self.t_0 = old_t_0[valid_index[0]]\\n self.p_0 = old_p_0[valid_index[0]]\\n self.t_ex = old_t_ex[valid_index[0]]\\n self.p_ex = old_p_ex[valid_index[0]]\\n\\n # squeezing the arrays is necessary since the setter-function for\\n # tau, omega and NormBRDF automatically adds an axis to the arrays!\\n self.V.tau = np.squeeze(old_tau[valid_index[0]])\\n if np.array(self.V.omega).size != 1:\\n self.V.omega = np.squeeze(old_omega[valid_index[0]])\\n if np.array(self.SRF.NormBRDF).size != 1:\\n self.SRF.NormBRDF = np.squeeze(old_NN[valid_index[0]])\\n\\n # calculate volume and interaction term where tau-values are valid\\n _Ivol = self.volume()\\n if self.int_Q is True:\\n _Iint = self.interaction()\\n else:\\n _Iint = np.full_like(self.t_0, 0.)\\n\\n # reset parameter values to old values\\n self.t_0 = old_t_0\\n self.p_0 = old_p_0\\n self.t_ex = old_t_ex\\n self.p_ex = old_p_ex\\n\\n # squeezing the arrays is necessary since the setter-function for\\n # tau, omega and NormBRDF automatically add an axis to the arrays!\\n self.V.tau = np.squeeze(old_tau)\\n self.V.omega = np.squeeze(old_omega)\\n self.SRF.NormBRDF = np.squeeze(old_NN)\\n\\n # combine calculated volume-contributions for valid tau-values\\n # with zero-arrays for invalid tau-values\\n Ivol = np.ones_like(self.t_0)\\n Ivol[valid_index[0]] = _Ivol\\n Ivol[inval_index[0]] = np.ones_like(Ivol[inval_index[0]]) * 0.\\n\\n # combine calculated interaction-contributions for valid tau-values\\n # with zero-arrays for invalid tau-values\\n if self.int_Q is True:\\n Iint = np.ones_like(self.t_0)\\n Iint[valid_index[0]] = _Iint\\n Iint[inval_index[0]] = np.ones_like(Iint[inval_index[0]]) * 0.\\n else:\\n Iint = np.full_like(self.t_0, 0.)\\n\\n return Isurf + Ivol + Iint, Isurf, Ivol, Iint\",\n \"def spectate(self):\\n pass\",\n \"def band_penalty(self):\\n fc_ix = np.argmin(np.abs(self.f - self.fc)) # Index to frequency array closes to center frequency\\n # Number of indexes on each side of center frequency, not extending outside, only up to 10 kHz\\n n = min(fc_ix, self.ix10k - fc_ix)\\n if n == 0:\\n return 0.0\\n return np.mean(np.square(self.fr[fc_ix - n:fc_ix] - self.fr[fc_ix + n - 1:fc_ix - 1:-1]))\",\n \"def get_b(self):\\n return ((self.b_plus_bstar / self.n_pos) + (self.b_minus_bstar / self.n_neg)) / 2\",\n \"def run(self, freqs, b='disc', scale=False, get_alpha='calc', save_alpha='none',\\n freqUnit='GHz', block=[1, 1], reuse_override='check'):\\n get_alpha = self.alpha_options[get_alpha[0].lower()]\\n save_alpha = self.alpha_options[save_alpha[0].lower()]\\n freqs, freqUnit = self.set_freqs(freqs=freqs, freqUnit=freqUnit)\\n reuse = self.check_reuse(freqs, scale, get_alpha, save_alpha,\\n reuse_override=reuse_override.lower())\\n C_timer = datetime.datetime.now()\\n if not reuse:\\n self.freqs = freqs\\n self.freqUnit = utils.proc_unit(freqUnit)\\n self.scale = scale\\n self.get_alpha = get_alpha\\n self.save_alpha = save_alpha\\n if self.verbose:\\n s = '{} at {} frequencies ({} - {} {})'.format(self.planet, len(freqs),\\n freqs[0], freqs[-1],\\n utils.proc_unit(freqUnit))\\n else:\\n s = '{} at {} {}'.format(self.planet, freqs[0], utils.proc_unit(freqUnit))\\n self.log.add(s, self.verbose)\\n self.alpha_layers(freqs=self.freqs, atmos=self.atmos,\\n scale=scale, get_alpha=get_alpha, save_alpha=save_alpha)\\n D_timer = datetime.datetime.now()\\n if self.verbose:\\n print(\\\"Absoprtion calc took {:.1f} s\\\".format(utils.timer(D_timer - C_timer)))\\n self.set_b(b=b, block=block)\\n brtplt, datplt = self.set_bright_plots()\\n is_img = self.set_image()\\n\\n # Loop over b values\\n self.init_run()\\n runStart = datetime.datetime.now()\\n self.log.add('Run start ' + str(runStart), False)\\n for i, bv in enumerate(self.b):\\n # Figure out which alpha to use for this b. For now only one.\\n j = self.map_b_to_atm(bv)\\n is_img.i = i\\n if self.verbose == 'loud':\\n print('{} of {} (view {}) '.format(i + 1, len(self.b), bv), end='')\\n self.bright_run(b=bv, freqs=self.freqs, atm=self.atmos[j], alpha=self.alpha[j],\\n is_img=is_img, brtplt=brtplt)\\n runStop = datetime.datetime.now()\\n missed_planet = self.rNorm is None\\n self.set_header(missed_planet, runStart, runStop)\\n self.log.add('Run stop ' + str(runStop), False)\\n self.populate_data_return(runStart, runStop)\\n if self.verbose:\\n print(\\\"RT calc took {:.1f} s\\\".format(utils.timer(runStop - runStart)))\\n\\n # ##Write output files\\n if self.config.write_output_files:\\n output_file = '{}_{}{}{}.dat'.format(self.planet, self.data_type, is_img.block,\\n runStart.strftime(\\\"%Y%m%d_%H%M%S\\\"))\\n output_file = os.path.join(self.config.output_directory, output_file)\\n if self.verbose == 'loud':\\n print('\\\\nWriting {} data to {}'.format(self.data_type, output_file))\\n self.fIO.write(output_file, self.data_return)\\n\\n if brtplt is not None:\\n brtplt.alpha()\\n if self.data_type == 'spectrum' or self.data_type == 'profile' and len(freqs) > 1:\\n datplt.Tb()\\n if self.data_type == 'profile':\\n datplt.profile()\\n datplt.show()\\n\\n return self.data_return\",\n \"def exercise2b(self):\\n self.b2 = calibrate_image(self.b1)\\n plt.axis('off')\\n plt.imshow(self.b2)\\n plt.show()\\n misc.imsave(\\\"B2.png\\\", self.b2)\\n misc.imsave(\\\"B2_Brightness.png\\\", print_brightness(self.b2))\",\n \"def do_fft(self):\\n start = time.time()\\n self.record_chunk()\\n self.window()\\n self.calculate_mags()\\n end = time.time()\",\n \"def integrate_spectrum(self):\\n flux = sum(self.spectrum)\\n return flux\",\n \"def compute(self):\\n Y = self.data[1]\\n # Create an order 3 lowpass butterworth filter\\n b, a = signal.butter(3, 0.05)\\n # Apply the filter to Y. Use lfilter_zi to choose the initial condition of the filter\\n zi = signal.lfilter_zi(b, a)\\n z, _ = signal.lfilter(b, a, Y, zi=zi * Y[0])\\n # Apply the filter again, to have a result filtered at an order the same as filtfilt\\n z2, _ = signal.lfilter(b, a, z, zi=zi * z[0])\\n # Use filtfilt to apply the filter\\n self.data[2] = signal.filtfilt(b, a, Y)\\n self.data[3] = self.data[2] - self.data[1] - self.dataSpan * 0.3\\n self.updatePlot()\",\n \"def compute_rate(self):\\n bg_rate = self.counts.data / self.livetime.data\\n\\n bg_rate /= self.counts.bin_volume\\n\\n bg_rate = bg_rate.to('MeV-1 sr-1 s-1')\\n\\n self.bg_rate.data = bg_rate\\n self.bg_rate.data_err = (np.sqrt(self.counts.data) / (self.counts.bin_volume * self.livetime.data)).to(\\n 'MeV-1 sr-1 s-1')\",\n \"def _calc(self):\\r\\n tot_sum: float = 0 # ? total sum of the noise values\\r\\n max_amp: float = 0 # ? keep the sum in [0,1]\\r\\n amp: float = 1.0 # ? amplitude of each noise value\\r\\n freq: float = 1.0 # ? frequency for getting the detailed noise\\r\\n\\r\\n # for each octave we twice the frequency and multiply the amplitude \\r\\n # by persistance to get the detailed noise value\\r\\n # to keep the final sum value in the range [0, 1] we keep track of the \\r\\n # max amplitude (sum of all the amplitudes)\\r\\n for octave in range(self.octaves):\\r\\n noise_obj = PerlinNoise(self.inp_x*freq, self.inp_y*freq, self.inp_z*freq)\\r\\n # ? multiply the noise value by the amplitude\\r\\n tot_sum += noise_obj.val() * amp\\r\\n max_amp += amp\\r\\n\\r\\n amp *= self.persist\\r\\n freq *= 2.0 # double the freq each iteration\\r\\n\\r\\n # value is in the range [0,1]\\r\\n self.value = tot_sum / max_amp\",\n \"def band_penalty(self):\\n fc_ix = np.argmin(np.abs(self.f - self.fc)) # Index to frequency array closes to center frequency\\n # Number of indexes on each side of center frequency, not extending outside, only up to 10 kHz\\n n = min(fc_ix, self.ix10k - fc_ix)\\n if n == 0:\\n return 0.0\\n return np.mean(np.square(self.fr[fc_ix - n:fc_ix] - (self.gain - self.fr[fc_ix + n - 1:fc_ix - 1:-1])))\",\n \"def inst_bp(instrument,array=\\\"2\\\"):\\n\\n if instrument == \\\"MUSTANG2\\\" or instrument == \\\"MUSTANG\\\":\\n srms = (300*u.um).to(\\\"m\\\") # surface RMS (microns)\\n ### Reference: https://science.nrao.edu/facilities/gbt/proposing/GBTpg.pdf\\n EA90 = 0.36 # Aperture efficiency at 90 GHz\\n ### The beam efficiencies should be taken as 1.37* Aperture Efficiency\\n R90 = np.exp(-4.0*np.pi*(srms/(const.c/(9.0e10*u.s**-1))).value) #\\n Gnot = EA90/R90 # Unphysical, but see documentation...\\n if instrument == \\\"MUSTANG2\\\":\\n flow = 75.0 # GHz\\n fhig = 105.0 # GHz\\n else:\\n flow = 82.5 # GHz\\n fhig = 97.5 # GHz\\n \\n farr = np.arange(flow,fhig,1.0) # frequency array.\\n tran = farr*0.0 + 1.0 # Let the transmission be unity everywhere.\\n Larr = const.c.value/(farr*1.0e9) # Keep calm and carry on.\\n ### Old formula:\\n #Ruze = Gnot * np.exp(-4.0*np.pi*(srms.value)/Larr)\\n ### Correct formula: (10 April 2018)\\n Ruze = Gnot * np.exp(-(4.0*np.pi*srms.value/Larr)**2)\\n NRuz = Ruze / np.max(Ruze) # Normalize it\\n band = tran * Ruze # Bandpass, with (unnormalized) Ruze efficiency\\n \\n if instrument == \\\"NIKA2\\\" or instrument == \\\"NIKA\\\":\\n caldir='/home/romero/NIKA2/NIKA_SVN/Processing/Pipeline/Calibration/BP/'\\n bpfile=caldir+'Transmission_2017_Jan_NIKA2_v1.fits'\\n hdulist = fits.open(bpfile)\\n\\n if array == \\\"1H\\\": # 1mm (260 GHz) array, Horizontal Polarization\\n tbdata = hdulist[1].data # 1H\\n freq = tbdata.field(0)\\n tran = tbdata.field(1)\\n erro = tbdata.field(2)\\n atmt = tbdata.field(3)\\n cfreq1h = np.sum(freq*tran)/np.sum(tran)\\n \\n if array == \\\"1V\\\": # 1mm (260 GHz) array, Vertical Polarization\\n tbdata = hdulist[2].data # 1V\\n freq = tbdata.field(0)\\n tran = tbdata.field(1)\\n erro = tbdata.field(2)\\n atmt = tbdata.field(3)\\n cfreq1v = np.sum(freq*tran)/np.sum(tran)\\n \\n if array == \\\"2\\\": # 2mm (150 GHz) array\\n tbdata = hdulist[3].data # 2\\n freq = tbdata.field(0)\\n tran = tbdata.field(1)\\n erro = tbdata.field(2)\\n atmt = tbdata.field(3)\\n cfreq2 = np.sum(freq*tran)/np.sum(tran)\\n\\n ### Trim the zero-frequency listing, if any.\\n gi=np.where(freq > 0)\\n freq = freq[gi]\\n tran = tran[gi]\\n erro = erro[gi]\\n atmt = atmt[gi]\\n \\n### Calculate Aperture efficiencies from information found at:\\n### http://www.iram.es/IRAMES/mainwiki/Iram30mEfficiencies\\n Beff = 0.630 # at 210 GHz\\n Aeff = Beff/1.27 # See text on webpage\\n srms = (66.0*u.um).to(\\\"m\\\") # surface RMS (microns)\\n R210 = np.exp(-4.0*np.pi*(srms/(const.c/(2.1e11*u.s**-1))).value) #\\n Gnot = Aeff/R210 # Unphysical, but see documentation...\\n\\n Larr = const.c.value/(freq*1.0e9) # Keep calm and carry on. \\n Ruze = Gnot * np.exp(-4.0*np.pi*(srms.value)/Larr)\\n NRuz = Ruze / np.max(Ruze) # Normalize it\\n band = tran * Ruze # Bandpass, with (unnormalized) Ruze efficiency\\n farr = freq\\n \\n#########################################################################\\n\\n if instrument == 'ACT90':\\n srms = (27.0*u.um).to(\\\"m\\\") # surface RMS (microns)\\n EA90 = 0.95 # I'm making this number up...\\n R90 = np.exp(-4.0*np.pi*(srms/(const.c/(9.0e10*u.s**-1))).value) #\\n Gnot = EA90/R90 # Unphysical, but see documentation...\\n flow = 65.0 # GHz\\n fhig = 125.0 # GHz\\n farr = np.arange(flow,fhig,1.0) # frequency array.\\n freq_ref = 90.0 # I took EA90 to be a fictitious aperature efficiency at 90 GHz\\n band = ruze_eff(farr,freq_ref,EA90,srms)\\n\\n if instrument == 'ACT150':\\n srms = (27.0*u.um).to(\\\"m\\\") # surface RMS (microns)\\n EA90 = 0.95 # I'm making this number up...\\n R90 = np.exp(-4.0*np.pi*(srms/(const.c/(9.0e10*u.s**-1))).value) #\\n Gnot = EA90/R90 # Unphysical, but see documentation...\\n flow = 120.0 # GHz\\n fhig = 180.0 # GHz\\n farr = np.arange(flow,fhig,1.0) # frequency array.\\n freq_ref = 90.0 # I took EA90 to be a fictitious aperature efficiency at 90 GHz\\n band = ruze_eff(farr,freq_ref,EA90,srms)\\n\\n\\n return band, farr\",\n \"def beam(xb,yb,zb,wx,wy,wavelen):\\n\\n zRx = np.pi * wx**2 / wavelen\\n zRy = np.pi * wy**2 / wavelen \\n \\n sqrtX = np.sqrt( 1 + np.power(zb/zRx,2) ) \\n sqrtY = np.sqrt( 1 + np.power(zb/zRy,2) ) \\n intensity = np.exp( -2.*( np.power(xb/(wx*sqrtX ),2) \\\\\\n + np.power(yb/(wy*sqrtY),2) )) / sqrtX / sqrtY\\n return intensity\",\n \"def _calc_fgs_cr_mag(self, to_compute, band_series, guider_throughput, guider_gain, return_dataframe=False):\\n to_return = []\\n\\n # Create initial dataframe\\n df = pd.DataFrame(GSC_BAND_WAVELENGTH, columns=['Wavelength'], index=GSC_BAND_NAMES)\\n\\n # Add magnitudes\\n df = pd.concat([df, band_series], axis=1, sort=True)\\n df = df.rename(columns={0: 'Mag'})\\n\\n # Sort to order of increasing wavelength\\n df = df.sort_values(by=['Wavelength'])\\n\\n # Calculate and add ABMagnitudes\\n def ab_mag(row):\\n if row.name in self._present_calculated_mags:\\n return utils.convert_to_abmag(row['Mag'], row.name)\\n else:\\n return -999\\n\\n df['ABMag'] = df.apply(lambda row: ab_mag(row), axis=1)\\n\\n # Convert AB mag to flux (photons/s/m**2/micron)\\n def calc_flux(row):\\n if row['ABMag'] != -999:\\n return 10.0 ** (-(row['ABMag'] + 48.6) / 2.5) * (1.0e4 / (PLANCK * row['Wavelength']))\\n else:\\n return -999\\n\\n df['Flux'] = df.apply(lambda row: calc_flux(row), axis=1)\\n\\n # Add extended wavelengths and compute flux\\n extended_waves = np.array([3.0, 4.0, 5.0, 5.5])\\n mag = np.full(4, np.nan)\\n abmag = np.full(4, np.nan)\\n flux = df.at[df.index[-1], \\\"Flux\\\"] * 2.17**2 / extended_waves**2\\n in_data = list(map(list, zip(extended_waves, mag, abmag, flux)))\\n df2 = pd.DataFrame(in_data, columns=['Wavelength', 'Mag', 'ABMag', 'Flux'],\\n index=['Extend1', 'Extend2', 'Extend3', 'Extend4'])\\n df = pd.concat([df, df2], axis=0)\\n\\n # Add throughput data to dataframe\\n df['Throughput'] = df['Wavelength'].map(guider_throughput)\\n\\n # Compute number of photons reaching the FGS-Guider detector per second per micron.\\n def calc_signal(row):\\n if row['Flux'] != -999:\\n return row['Flux'] * row['Throughput'] * 25\\n else:\\n return -999\\n\\n df['Signal'] = df.apply(lambda row: calc_signal(row), axis=1)\\n\\n # Can't compute if we only have J, H, and K # TODO will be changed later\\n if {'tmassJmag', 'tmassHmag', 'tmassKsMag'} == set(self._present_calculated_mags):\\n raise ValueError('Cannot compute FGS countrate & magnitude for a guide star ({}) with only 2MASS '\\n 'data'.format(self.id))\\n\\n # Reset the shortest/2nd shortest bands to 0 if they are missing\\n if df.at['JpgMag', 'Signal'] == -999:\\n df.at['JpgMag', 'Signal'] = 0\\n if df.at['SDSSgMag', 'Signal'] == -999:\\n df.at['SDSSgMag', 'Signal'] = 0\\n\\n # Throw out any bands for which you don't have data\\n df_short = df[df['Signal'] != -999]\\n\\n # Integrate flux in photons per second per micron over the FGS-Guider wavelength range. Use trapezoid formula.\\n trapezoid = np.zeros(len(df_short) - 1)\\n for i in range(len(trapezoid)):\\n trapezoid[i] = (df_short.at[df_short.index[i + 1], \\\"Wavelength\\\"] -\\n df_short.at[df_short.index[i], \\\"Wavelength\\\"]) * \\\\\\n (df_short.at[df_short.index[i], \\\"Signal\\\"] +\\n df_short.at[df_short.index[i + 1], \\\"Signal\\\"]) / 2.0\\n electrons = np.sum(trapezoid)\\n\\n # Compute FGS countrate using conversion of # electrons => 1 count\\n fgs_countrate = electrons / guider_gain\\n\\n if to_compute.lower() == 'countrate' or to_compute.lower() == 'both':\\n to_return.append(fgs_countrate)\\n\\n # Compute FGS magnitude\\n length = len(df_short) - 1\\n trap1 = np.zeros(length)\\n trap2 = np.zeros(length)\\n for i in range(length):\\n trap1[i] = (df_short.at[df_short.index[i + 1], \\\"Wavelength\\\"] -\\n df_short.at[df_short.index[i], \\\"Wavelength\\\"]) * \\\\\\n (df_short.at[df_short.index[i], \\\"Signal\\\"] +\\n df_short.at[df_short.index[i + 1], \\\"Signal\\\"]) / 2.0\\n trap2[i] = (df_short.at[df_short.index[i + 1], \\\"Wavelength\\\"] -\\n df_short.at[df_short.index[i], \\\"Wavelength\\\"]) * \\\\\\n (df_short.at[df_short.index[i], \\\"Throughput\\\"] +\\n df_short.at[df_short.index[i + 1], \\\"Throughput\\\"]) / 2.0\\n\\n sum_signal = np.sum(trap1)\\n sum_throughput = np.sum(trap2)\\n\\n if self.guider == 1:\\n mag_conversion = MAG_CONVERSION_G1\\n elif self.guider == 2:\\n mag_conversion = MAG_CONVERSION_G2\\n else:\\n raise ValueError(\\\"Guider value must be an integer either 1 or 2\\\")\\n\\n fgs_magnitude = -2.5 * np.log10(sum_signal / sum_throughput) + mag_conversion\\n\\n if to_compute.lower() == 'magnitude' or to_compute.lower() == 'both':\\n to_return.append(fgs_magnitude)\\n\\n if return_dataframe is True:\\n to_return.append(df)\\n\\n return to_return\",\n \"def estimate(self, bases, freqs, **kwargs):\\n \\n # Make sure that frequencies are provided for every basis measured\\n if len(bases) != len(freqs):\\n print(\\\"Error, must provide frequency data for all bases measured.\\\")\\n return\\n\\n # Go through the keyword arguments and set mu and eps if required.\\n mu = 1e-4\\n eps = 0.1 \\n\\n if \\\"mu\\\" in kwargs:\\n mu = kwargs[\\\"mu\\\"]\\n if \\\"eps\\\" in kwargs:\\n eps = kwargs[\\\"eps\\\"]\\n\\n # Separate the bases out into measured and unmeasured\\n meas_bs_idx = []\\n unmeas_bs_idx = []\\n\\n for x in range(self.dim):\\n if x in bases:\\n meas_bs_idx.append(x)\\n else:\\n unmeas_bs_idx.append(x)\\n\\n # Handle the vertical slope separately\\n if -1 in bases:\\n meas_bs_idx.append(-1)\\n else:\\n unmeas_bs_idx.append(-1)\\n\\n # Begin with the initial state, the maximally mixed state\\n rho_0 = (1.0 / self.dim) * np.eye(self.dim)\\n rho_n = rho_0\\n\\n \\\"\\\"\\\"print(\\\"Measured bases are \\\", end = \\\"\\\")\\n print(meas_bs_idx)\\n print(\\\"Unmeasured bases are \\\", end = \\\"\\\")\\n print(unmeas_bs_idx)\\\"\\\"\\\"\\n \\n n = 1\\n\\n # Iterate\\n while (n):\\n ########################################################\\n # Compute W(rho)\\n # I might eventually put this in a separate method, but\\n # for now I'm going to leave it here to avoid having to\\n # repeatedly pass the same (large chunk of) information \\n # to some helper function.\\n ########################################################\\n term_1 = np.zeros((self.dim, self.dim))\\n term_2 = np.zeros((self.dim, self.dim))\\n\\n # Compute the first sum, which contains the measurement \\n # frequencies and the measured bases. Note that in theory\\n # the bases may not be in ascending order, however the \\n # frequencies will be generated in the same order as the \\n # bases are placed in the list. So create a separate counter\\n # for frequencies to just iterate through them one at a time\\n # as we go through the bases by their slope index.\\n freq_idx = 0 \\n for basis_idx in meas_bs_idx:\\n for proj_idx in range(self.dim):\\n this_projector = self.projectors[basis_idx][proj_idx]\\n\\n p_num = freqs[freq_idx][proj_idx] \\n p_denom = np.trace(np.dot(rho_n, this_projector))\\n prefactor = p_num / p_denom\\n\\n term_1 = term_1 + (prefactor * this_projector)\\n freq_idx += 1\\n\\n # If there are no unmeasured basis, do nothing\\n if len(unmeas_bs_idx) != 0:\\n # Compute the second sum, which is over all the unmeasured bases.\\n for basis_idx in unmeas_bs_idx:\\n for proj_idx in range(self.dim):\\n this_projector = self.projectors[basis_idx][proj_idx]\\n\\n prefactor = log(np.trace(np.dot(rho_n, this_projector)))\\n\\n term_2 = term_2 + (prefactor * this_projector)\\n \\n \\n # Finally, compute W(rho)\\n W_rho_n = term_1 - mu * term_2\\n ########################################################\\n\\n #print(\\\"n = \\\" + str(n))\\n #print(rho_n) \\n\\n # Check if we've got a good estimate. If the desired accuracy \\n # is satisfied by the most recent rho_n, then we're done. \\n # Return the estimator and the number of steps.\\n # If not, increment n and keep going.\\n if self.check_accuracy(W_rho_n, rho_n):\\n return rho_n, n \\n else:\\n n += 1\\n\\n # Compute the next term in the series. It's a big ugly expression,\\n # so I've separated out a term 'clump', and also the num/denom\\n clump = W_rho_n - np.trace(np.dot(W_rho_n, rho_n)) * np.eye(self.dim)\\n \\n numerator = np.dot(np.eye(self.dim) + eps * clump, \\\\\\n np.dot(rho_n, np.eye(self.dim) + eps * clump))\\n denominator = 1 + (eps ** 2) * np.trace(np.dot(np.dot(clump, clump), rho_n))\\n\\n rho_np1 = numerator / denominator\\n rho_n = rho_np1\",\n \"def test_bayes_updates_good_data(self):\\r\\n # result for first -> fourth calculated by hand\\r\\n for obs, exp in zip(bayes_updates(self.test), self.result):\\r\\n self.assertFloatEqualAbs(obs, exp, 1e-11)\",\n \"def calculate_flux(self, band):\\n\\n if (self.wavelength[0] > band.wavelength[0] or\\n self.wavelength[-1] < band.wavelength[-1]):\\n\\n warn('Spectrum does not cover the whole bandpass, '\\n 'extrapolating...')\\n dw = np.median(np.diff(self.wavelength.value))\\n spec_wavelength = np.arange(\\n band.wavelength.value[0],\\n band.wavelength.value[-1] + dw, dw) * angstrom\\n spec_flux = np.interp(spec_wavelength, self.wavelength,\\n self.flux.value)\\n\\n else:\\n spec_wavelength = self.wavelength\\n spec_flux = self.flux.value\\n\\n i, j = spec_wavelength.searchsorted(\\n Quantity([band.wavelength[0], band.wavelength[-1]]))\\n wavelength = spec_wavelength[i:j]\\n flux = spec_flux[i:j]\\n\\n dw_band = np.median(np.diff(band.wavelength))\\n dw_spec = np.median(np.diff(wavelength))\\n\\n if dw_spec.value > dw_band.value > 20:\\n\\n warn('Spectrum wavelength sampling interval {0:.2f}, but bandpass'\\n 'sampling interval {1:.2f}'.format(dw_spec, dw_band))\\n\\n # Interpolate the spectrum to the passband wavelengths:\\n flux = np.interp(band.wavelength, wavelength, flux)\\n band_transmission = band.transmission\\n wavelength = band.wavelength\\n\\n else:\\n # Interpolate the band transmission to the spectrum wavelengths:\\n band_transmission = np.interp(\\n wavelength, band.wavelength, band.transmission)\\n\\n # Weight by the response and wavelength, appropriate when we're\\n # counting the number of photons within the band:\\n flux = (np.trapz(band_transmission * flux * wavelength, wavelength) /\\n np.trapz(band_transmission * wavelength, wavelength))\\n flux *= erg / s / cm ** 2 / angstrom\\n\\n return flux\",\n \"def getB(self):\\n return ((self.bPlusbStar() / self.nPos) + (self.bMinusbStar / self.nNeg)) / 2\",\n \"def calculate(self):\\n if self.sampling_timer.IsRunning():\\n return\\n if self.daq.data0 == []:\\n average = 0.0\\n else:\\n average = mean(self.daq.data0)\\n res_string = '%.2f' %average\\n self.control_box.result_box.SetLabel(res_string)\",\n \"def calculate(self):\\r\\n\\r\\n pass\",\n \"def calbands( band = 0, tmo = 30 ) :\\n optimizeThresholds(band,tmo)\\n flattenPhases(band,tmo)\\n calibrateSpectra(band=band,tmo=tmo)\",\n \"def b_minus_bstar(self):\\n running_total = 0\\n for i in range(self.prob.num):\\n if self.alphas[i] > 1e-5 and self.prob.Y[i] == -1:\\n ayxx = 0\\n for j in range(self.prob.num):\\n ayxx += (self.alphas[j] + self.etas[j]) * self.prob.Y[j] * self.prob.xkernel(self.prob.X[j],\\n self.prob.X[i])\\n abcxx = 0\\n for j in range(self.prob.num):\\n abcxx += (self.alphas[j] + self.deltas[j]) * self.prob.xkernel(self.prob.X[j], self.prob.X[i])\\n abcxx *= (1 / self.prob.gamma)\\n running_total += -1 + abcxx - ayxx\\n return running_total\",\n \"def bandpass(filename,f1,f2,Q,wout=True,plot=True):\\n start=time.time()\\n n, data, data_dB,sr,ch=inputwav(filename)\\n b, a = butter(Q,Wn=(f1/sr,f2/sr),btype='bandpass')\\n data_filtered=lfilter(b,a,data,axis=0)\\n print('Applying FFT...')\\n if wout==True:\\n print('Exporting...')\\n sf.write(filename[0:len(filename)-4]+'_BP.wav',data_filtered,sr,'PCM_16')\\n if plot==True:\\n print('Plotting...')\\n py.close()\\n w, h = freqz(b,a,worN=16384)\\n fig, (ax1, ax2) = py.subplots(nrows=2)\\n ax1.semilogx(0.5*sr*w/np.pi,abs(h),'k-')\\n ax1.set_xlabel('Frequency (Hz)')\\n ax1.set_ylabel('Rel. Amplitude')\\n ax1.grid()\\n ax1.set_ylim(0,1.1)\\n ax1.set_xlim(1,20000)\\n ax2.plot(data,'k-',label='Raw data')\\n ax2.plot(data_filtered,'m-',lw=1,label='Filtered data')\\n ax2.set_xlim(0,10000)\\n ax2.set_ylim(-1,1)\\n ax2.set_ylabel('Amplitude (Norm Bits)')\\n ax2.set_xlabel('Samples')\\n ax2.legend(loc=2,frameon=False,ncol=2)\\n py.subplots_adjust(hspace=0.35) \\n print('Done!')\\n end=time.time()\\n elapsed=int(1000*(end-start))\\n print('...............................')\\n print('Completed in '+str(elapsed)+' milliseconds.')\\n return data_filtered\",\n \"def b_plus_bstar(self):\\n running_total = 0\\n for i in range(self.prob.num):\\n if self.alphas[i] > 1e-5 and self.prob.Y[i] == 1:\\n ayxx = 0\\n for j in range(self.prob.num):\\n ayxx += (self.alphas[j] + self.etas[j]) * self.prob.Y[j] * self.prob.xkernel(self.prob.X[j],\\n self.prob.X[i])\\n abcxx = 0\\n for j in range(self.prob.num):\\n abcxx += (self.alphas[j] + self.deltas[j]) * self.prob.xkernel(self.prob.X[j], self.prob.X[i])\\n abcxx *= (1 / self.prob.gamma)\\n running_total += 1 - abcxx - ayxx\\n return running_total\",\n \"def calculate(self):\\r\\n pass\",\n \"def _calculate_fuel(self):\\n self._fuel = self._calculate_fuel_r(self._mass)\",\n \"def bPlusbStar(self):\\n running_total = 0\\n for i in range(self.prob.num):\\n if self.alphas[i] > 1e-5 and self.prob.Y[i] == 1:\\n ayxx = 0\\n for j in range(self.prob.num):\\n ayxx += self.alphas[j] * self.prob.Y[j] * self.prob.xkernel(self.prob.X[i], self.prob.X[j])\\n abcxx = 0\\n for j in range(self.prob.num):\\n abcxx += (self.alphas[j] + self.deltas[j]) * self.prob.xkernel(self.prob.X[i], self.prob.X[j])\\n abcxx *= (1 / self.prob.gamma)\\n running_total += 1 - abcxx - ayxx\\n return running_total\",\n \"def calc_fffb_inhibition(self) -> None:\\n # Feedforward inhibition\\n ffi = self.spec.ff * max(self.avg_net - self.spec.ff0, 0)\\n # Feedback inhibition\\n self.fbi = self.spec.fb_dt * (self.spec.fb * self.avg_act - self.fbi)\\n # Global inhibition\\n self.gc_i = self.spec.gi * (ffi * self.fbi)\",\n \"def test_9(self):\\n\\n sq_qe = gen_step_qe(1.42, 0.9)\\n test_ill = Illumination()\\n # test_qef = qe_filter(sq_qe)\\n\\n filtered_ill = test_ill * sq_qe\\n\\n assert isinstance(filtered_ill, Illumination)\\n\\n #plt.plot(filtered_ill.get_spectrum('eV')[0, :], filtered_ill.get_spectrum('eV')[1, :], label=\\\"filtered\\\")\\n #plt.plot(test_ill.get_spectrum('eV')[0, :], test_ill.get_spectrum('eV')[1, :], label=\\\"original\\\")\\n\\n #plt.xlabel('wavelength (eV)')\\n #plt.ylabel('spectrum (W/eV/m^2)')\\n\\n #plt.legend()\\n\\n #plt.show()\",\n \"def compute_bias(ics, vbc):\\n import os, time\\n from seren3.array import SimArray\\n \\n # Compute size of grid and boxsize (for this patch)\\n N = vbc.shape[0]\\n boxsize = ics.boxsize.in_units(\\\"Mpc a h**-1\\\") * (float(N) / float(ics.header.N))\\n\\n # Compute vbc @ z=1000\\n z = ics.z\\n rms = vbc_rms(vbc)\\n rms_recom = rms * (1001./z)\\n\\n # Check for PS and run CICsASS if needed\\n fname_vbc0 = vbc_ps_fname(0., z, boxsize)\\n if not os.path.isfile(fname_vbc0):\\n exit_code = run_cicsass(boxsize, z, 0., fname_vbc0)\\n\\n fname_vbcrecom = vbc_ps_fname(rms_recom, z, boxsize)\\n if not os.path.isfile(fname_vbcrecom):\\n exit_code = run_cicsass(boxsize, z, rms_recom, fname_vbcrecom)\\n\\n # Load power spectra and compute bias\\n ps_vbc0 = np.loadtxt(fname_vbc0, unpack=True)\\n ps_vbcrecom = np.loadtxt(fname_vbcrecom, unpack=True)\\n\\n # Should have same lenghts if finished writing\\n count = 0\\n while len(ps_vbcrecom[1]) != len(ps_vbc0[1]):\\n count += 1\\n if count > 10:\\n raise Exception(\\\"Reached sleep limit. Filesizes still differ\\\")\\n time.sleep(5)\\n ps_vbc0 = np.loadtxt(fname_vbc0, unpack=True)\\n ps_vbcrecom = np.loadtxt(fname_vbcrecom, unpack=True)\\n\\n #CDM bias\\n b_cdm = ps_vbcrecom[1] / ps_vbc0[1]\\n # Baryon bias\\n b_b = ps_vbcrecom[2] / ps_vbc0[2]\\n # Wavenumber\\n k_bias = SimArray(ps_vbcrecom[0] / ics.cosmo[\\\"h\\\"], \\\"h Mpc**-1\\\")\\n\\n return k_bias, b_cdm, b_b\",\n \"def diff_bmf(mass_arr, volume, cvar_err, sim_bool, h1_bool): \\n if sim_bool:\\n mass_arr = np.log10(mass_arr)\\n \\n if not h1_bool:\\n # changing from h=0.7 to h=1\\n mass_arr = np.log10((10**mass_arr) / 2.041)\\n \\n if survey == 'eco':\\n bin_min = np.round(np.log10((10**9.4) / 2.041), 1)\\n bin_max = np.round(np.log10((10**11.8) / 2.041), 1)\\n bins = np.linspace(bin_min, bin_max, 7)\\n \\n if survey == 'resolvea':\\n bin_min = np.round(np.log10((10**9.4) / 2.041), 1)\\n bin_max = np.round(np.log10((10**11.5) / 2.041), 1)\\n bins = np.linspace(bin_min, bin_max, 7) \\n\\n if survey == 'resolveb':\\n bin_min = np.round(np.log10((10**9.1) / 2.041), 1)\\n bin_max = np.round(np.log10((10**11.5) / 2.041), 1)\\n bins = np.linspace(bin_min, bin_max, 7) \\n \\n\\n # Unnormalized histogram and bin edges\\n counts, edg = np.histogram(mass_arr, bins=bins) # paper used 17 bins\\n dm = edg[1] - edg[0] # Bin width\\n maxis = 0.5 * (edg[1:] + edg[:-1]) # Mass axis i.e. bin centers\\n # Normalized to volume and bin width\\n err_poiss = np.sqrt(counts) / (volume * dm)\\n\\n phi = counts / (volume * dm) # not a log quantity\\n return maxis, phi, err_poiss, bins, counts\",\n \"def runBrighterFatter():\\n RunData([getFiles(mintime=(15, 12, 20), maxtime=(15, 24, 16), folder='data/31Jul/')[0],], out='I800nmlow',\\n wavelength='l800l')\\n RunData([getFiles(mintime=(15, 28, 40), maxtime=(15, 39, 21), folder='data/31Jul/')[2],], out='I800nmmed',\\n wavelength='l800m')\\n RunData([getFiles(mintime=(15, 40, 07), maxtime=(15, 45, 14), folder='data/29Jul/')[4],], out='I800nmhigh',\\n wavelength='l800h')\",\n \"def pre_process(self):\\n t1_start = perf_counter()\\n wav_arr_raw = np.array(self.raw_data['spectrum_0'].attrs['wavelengths'])\\n self.wavelengths = wav_arr_raw\\n self.back_spectra_arr = np.array(self.raw_data['spectrum_0'].attrs['background'])\\n\\n corr_data = []\\n times_proc = []\\n\\n # extract reference point for 0 seconds\\n time_ref = str(self.raw_data['spectrum_0'].attrs['creation_timestamp'])\\n\\n # spectrometer adds 'b' and quotation marks to timestamps that must be removed\\n # some spectra are taken on X.000000s which does not have a .%f component - use try and except\\n try:\\n time_ref = datetime.strptime((time_ref.replace('b','')).replace('\\\\'',''),\\\"%Y-%m-%dT%H:%M:%S.%f\\\")\\n except ValueError:\\n time_ref = datetime.strptime((time_ref.replace('b','')).replace('\\\\'',''),\\\"%Y-%m-%dT%H:%M:%S\\\")\\n\\n print('Measurement was started at {}, \\\\n normalising times and applying a background correction \\\\n'.format(time_ref))\\n\\n # applies background correction\\n for counter, spectra in enumerate(self.raw_data.keys()):\\n corr_data.append(self.raw_data[spectra]-self.back_spectra_arr)\\n time = str(self.raw_data[spectra].attrs['creation_timestamp'])\\n try:\\n time = datetime.strptime((time.replace('b','')).replace('\\\\'',''),\\\"%Y-%m-%dT%H:%M:%S.%f\\\")\\n except ValueError:\\n time = datetime.strptime((time.replace('b','')).replace('\\\\'',''),\\\"%Y-%m-%dT%H:%M:%S\\\")\\n deltatime = time - time_ref\\n times_proc.append(deltatime.total_seconds())\\n\\n self.times = np.array(times_proc)\\n print('Measurement contains {} spectra with {} wavelengths \\\\n'.format(len(self.times),len(self.wavelengths)))\\n\\n # data is stored as a pd Dataframe with elapsed times as indices and wavelengths as columns\\n pre_proc_data = pd.DataFrame(corr_data, index = self.times, columns = self.wavelengths)\\n\\n # data may be disordered in time when iterated through\\n # sort the data by elapsed time\\n self.pre_proc_data = pre_proc_data.sort_index(axis=0)\\n self.times = np.sort(self.times)\\n\\n t1_stop = perf_counter()\\n print(\\\"Elapsed time for pre-processing:\\\", t1_stop-t1_start)\\n\\n return self.pre_proc_data\",\n \"def __call__(self, frame_num):\\n quant_sys = self.quant_sys\\n quant_sys.propagate(10)\\n\\n # propagate the wigner function\\n self.img_clasical_rho.set_array(\\n (quant_sys.D22 + quant_sys.D11).real\\n #quant_sys.get_classical_rho()\\n )\\n\\n self.img_Upsilon2.set_array(\\n quant_sys.quantum_rho.real\\n )\\n\\n return self.img_clasical_rho, self.img_Upsilon2\",\n \"def compute_rate(self):\\n bg_rate = self.counts_cube.data / self.livetime_cube.data\\n\\n bg_rate /= self.counts_cube.bin_volume\\n # bg_rate.set_zero_level()\\n\\n # import IPython; IPython.embed()\\n bg_rate = bg_rate.to('1 / (MeV sr s)')\\n\\n self.background_cube.data = bg_rate\",\n \"def calculate_abs(self):\\n ref_spectra_raw = np.array(self.raw_data['spectrum_0'].attrs['reference'])\\n self.ref_spectra_arr = np.subtract(ref_spectra_raw,self.back_spectra_arr)\\n abs=-np.log10(self.pre_proc_data.div(self.ref_spectra_arr))\\n self.abs_data=abs\\n return self.abs_data\",\n \"def simulate_spectrum(file_name = \\\"bands_full.dat\\\", k0=0,kf= 0.576,Nk=200,E_max=0.5,E_min=-0.5,Ne=200,gamma_k=0.002,gamma=0.004,lambda_0=20,orbital=\\\"pz\\\",suffix=\\\"\\\"):\\n\\n #define energy and momentum domains\\n dk = (kf-k0)/Nk\\n momenta = np.linspace(k0, kf+dk, Nk)\\n energies = np.linspace(E_min, E_max, Ne)\\n\\n #initialize spectral function A_final to zero\\n A_final = []\\n for i_k in range(len(momenta)):\\n I_e = []\\n for j_e in range(len(energies)):\\n I_e.append(0)\\n A_final.append(I_e)\\n\\n #compute all lorenztian functions\\n all_lor = compute_functions(file_name,E_max,E_min,gamma,gamma_k)\\n\\n #evaluate all functions\\n print \\\"Evaluating functions\\\"\\n for func in all_lor:\\n s = np.vectorize(func)\\n A = s(momenta[:,None],energies[None,:])\\n A_final += A\\n\\n #print output\\n file_output = \\\"\\\"\\\"A_gammak_%(gamma_k)s_gammae_%(gamma)s_Nk_%(Nk)s_Ne_%(Ne)s_lambda_%(lambda_0)s_%(orbital)s%(suffix)s\\\"\\\"\\\"%locals()\\n file = open(file_output,'w')\\n for i in range(len(momenta)):\\n for j in range(len(energies)):\\n print >> file,momenta[i],energies[j],A_final[i][j]\\n print >> file,\\\"\\\"\\n file.close()\\n\\n return file_output\",\n \"def f2b(self, fres, f):\\n return f / fres\",\n \"def calculate(self):\\n pass\",\n \"def _calculate_a_value(self, bval, nvalue, nyr, cmag, ref_mag):\\n\\n denominator = np.sum(nyr * np.exp(-bval * (cmag - ref_mag)))\\n return nvalue / denominator\",\n \"def compute(self):\\n # get the values in widgets\\n if self.first:\\n self.first = False\\n type = self.type\\n nfilter = self.nfilter\\n order = self.order\\n npass = self.npass\\n else:\\n type = self.typeComboBox.currentIndex()\\n nfilter = int(str(self.filterComboBox.currentText()))\\n order = self.orderSpinBox.value()\\n npass = self.nbpassSpinBox.value()\\n self.data[2] = self.data[1] # Restore initial values\\n for i in range(npass):\\n if type == 0:\\n self.data[2] = MovAver(self.data[2], nfilter)\\n else:\\n self.data[2] = signal.savgol_filter(self.data[2],\\n window_length = nfilter,\\n polyorder = order)\\n self.data[3] = self.data[2] - self.data[1] - self.diffshift\\n self.type = type\\n self.nfilter = nfilter\\n self.npass = npass\\n if type == 1:\\n self.order = order\\n self.updatePlot()\",\n \"def detect_bispectra(self, sigma=5., tol=1.3, Q=0, show=0, save=0):\\n\\n try:\\n ba = self.bispectra\\n except AttributeError:\\n print 'Need to make bispectra first.'\\n return\\n\\n# ntr = lambda num: num*(num-1)*(num-2)/6 # assuming all triples are present\\n ntr = lambda num: len(self.triples) # consider possibility of zeros in data and take mean number of good triples over all times\\n\\n # using s=S/Q\\n mu = lambda s: 1. # for bispectra formed from visibilities\\n sigbQ3 = lambda s: n.sqrt((1 + 3*mu(s)**2) + 3*(1 + mu(s)**2)*s**2 + 3*s**4) # from kulkarni 1989, normalized by Q**3, also rogers et al 1995\\n s = lambda basnr, nants: (2.*basnr/n.sqrt(ntr(nants)))**(1/3.) # see rogers et al. 1995 for factor of 2\\n\\n # measure SNR_bl==Q from sigma clipped times with normal mean and std of bispectra. put into time,dm order\\n bamean = ba.real.mean(axis=2).transpose()\\n bastd = ba.real.std(axis=2).transpose()\\n\\n bameanstd = []\\n for dmind in xrange(len(self.dmarr)):\\n (meanmin,meanmax) = sigma_clip(bamean[:, dmind]) # remove rfi to estimate noise-like parts\\n (stdmin,stdmax) = sigma_clip(bastd[:, dmind])\\n clipped = n.where((bamean[:, dmind] > meanmin) & (bamean[:, dmind] < meanmax) & (bastd[:, dmind] > stdmin) & (bastd[:, dmind] < stdmax) & (bamean[:, dmind] != 0.0))[0] # remove rfi and zeros\\n bameanstd.append(ba[dmind][clipped].real.mean(axis=1).std())\\n\\n bameanstd = n.array(bameanstd)\\n basnr = bamean/bameanstd # = S**3/(Q**3 / n.sqrt(n_tr)) = s**3 * n.sqrt(n_tr)\\n if Q:\\n print 'Using given Q =', Q\\n else:\\n Q = ((bameanstd/2.)*n.sqrt(ntr(self.nants)))**(1/3.)\\n # Q = n.median( bastd[clipped]**(1/3.) ) # alternate for Q\\n print 'Estimating noise per baseline from data. Q (per DM) =', Q\\n self.Q = Q\\n\\n # detect\\n cands = n.where( (bastd/Q**3 < tol*sigbQ3(s(basnr, self.nants))) & (basnr > sigma) ) # get compact sources with high snr\\n\\n # plot snrb lc and expected snr vs. sigb relation\\n if show or save:\\n for dmbin in xrange(len(self.dmarr)):\\n cands_dm = cands[0][n.where(cands[1] == dmbin)[0]] # find candidates for this dmbin\\n p.figure(range(len(self.dmarr)).index(dmbin)+1)\\n ax = p.axes()\\n p.subplot(211)\\n p.title(str(self.nskip/self.nbl) + ' nskip, ' + str(dmbin) + ' dmbin, ' + str(len(cands_dm))+' candidates', transform = ax.transAxes)\\n p.plot(basnr[:,dmbin], 'b.')\\n if len(cands_dm) > 0:\\n p.plot(cands_dm, basnr[cands_dm,dmbin], 'r*')\\n p.ylim(-2*basnr[cands_dm,dmbin].max(),2*basnr[cands_dm,dmbin].max())\\n p.xlabel('Integration',fontsize=12,fontweight=\\\"bold\\\")\\n p.ylabel('SNR_b',fontsize=12,fontweight=\\\"bold\\\")\\n ax.spines['top'].set_visible(False)\\n ax.spines['right'].set_visible(False)\\n ax.spines['bottom'].set_position(('outward', 20))\\n ax.spines['left'].set_position(('outward', 30))\\n ax.yaxis.set_ticks_position('left')\\n ax.xaxis.set_ticks_position('bottom')\\n p.subplot(212)\\n p.plot(bastd[:,dmbin]/Q[dmbin]**3, basnr[:,dmbin], 'b.')\\n\\n # plot reference theory lines\\n smax = s(basnr[:,dmbin].max(), self.nants)\\n sarr = smax*n.arange(0,101)/100.\\n p.plot(sigbQ3(sarr), 1/2.*sarr**3*n.sqrt(ntr(self.nants)), 'k')\\n p.plot(tol*sigbQ3(sarr), 1/2.*sarr**3*n.sqrt(ntr(self.nants)), 'k--')\\n p.plot(bastd[cands_dm,dmbin]/Q[dmbin]**3, basnr[cands_dm,dmbin], 'r*')\\n ax.spines['top'].set_visible(False)\\n ax.spines['right'].set_visible(False)\\n ax.spines['bottom'].set_position(('outward', 20))\\n ax.spines['left'].set_position(('outward', 30))\\n ax.yaxis.set_ticks_position('left')\\n ax.xaxis.set_ticks_position('bottom')\\n\\n if len(cands_dm) > 0:\\n p.axis([0, tol*sigbQ3(s(basnr[cands_dm,dmbin].max(), self.nants)), -0.5*basnr[cands_dm,dmbin].max(), 1.1*basnr[cands_dm,dmbin].max()])\\n\\n # show spectral modulation next to each point\\n for candint in cands_dm:\\n sm = n.single(round(self.specmod(dmbin,candint),1))\\n p.text(bastd[candint,dmbin]/Q[dmbin]**3, basnr[candint,dmbin], str(sm), horizontalalignment='right', verticalalignment='bottom')\\n p.xlabel('sigma_b/Q^3',fontsize=12,fontweight=\\\"bold\\\")\\n p.ylabel('SNR_b',fontsize=12,fontweight=\\\"bold\\\")\\n if save:\\n if save == 1:\\n savename = self.file.split('.')[:-1]\\n savename.append(str(self.nskip/self.nbl) + '_' + str(dmbin) + '_bisp.png')\\n savename = string.join(savename,'.')\\n elif isinstance(save, string):\\n savename = save\\n print 'Saving file as ', savename\\n p.savefig(self.pathout+savename)\\n\\n return basnr[cands], bastd[cands], zip(cands[0],cands[1])\",\n \"def test_bayes_updates_permuted(self):\\r\\n for obs, exp in zip(bayes_updates(self.permuted), self.result):\\r\\n self.assertFloatEqualAbs(obs, exp, 1e-11)\",\n \"def compute(self):\\n return self.elbo_component / self.get_intervals_recorded()\",\n \"def calculate(self):\\n\\n return self._calculate_volume(self.ground_truth)\",\n \"def proz(): \\r\\n print(\\\"processing: \\\",CURDATA()[0]) \\r\\n Check_180turn(left_boundary,right_boundary)\\r\\n EF() #exponential window multiplication + fourier\\r\\n APK0() #1. Phase correction 0th Ordnung\\r\\n APK1() #1. Phase correction 1st Ordnung\\r\\n ABS() #Baseline correction\\r\\n APK()\\r\\n ABS() #Baseline correction\\r\\n Check_180turn(left_boundary,right_boundary)\",\n \"def calculate_output(self):\",\n \"def binned_fft(self):\\n self.fft()\\n self.fft_bins_y = self.binn_fft()\\n self.fft_bins_y = np.asarray(self.fft_bins_y) * UPDATE_FACTOR + self.last_fft_bins_y *(1 - UPDATE_FACTOR)\\n self.last_fft_bins_y = self.fft_bins_y\",\n \"def __dmr_analysis(self, debug=False):\\n global hfAdcRange, adcCountRange\\n if self.buffer is None or len(self.buffer) != self.bufsize:\\n self.set_eval_error(f'Data length ({len(self.buffer)}) differs from expected ({self.bufsize})')\\n return None\\n\\n It = self.buffer[:self.bufsize//2]\\n Qt = self.buffer[self.bufsize//2:]\\n\\n self.results['ADC_I'] = hfAdcRange * (It * 2 / adcCountRange - 1)\\n self.results['ADC_Q'] = hfAdcRange * (Qt * 2 / adcCountRange - 1)\\n\\n # subtract the DC component and convert to int32\\n It = np.around(It-np.mean(It)).astype('int32')\\n Qt = np.around(Qt-np.mean(Qt)).astype('int32')\\n\\n # find the bit error rate and constant symbol intervals\\n maxlen = 20*200 # max length of returned Iref, Qref\\n numerr, numbit, Iref, Qref, symlenref = get_ber(It, Qt, maxlen)\\n\\n if numerr is None or numbit is None:\\n self.set_eval_error(f'Too small data length - {len(self.buffer)}')\\n return None\\n\\n ber = numerr/numbit\\n\\n return ber\",\n \"def idealOpAmp():\",\n \"def y(self):\\n #print(xdb.xray_lines(self.element)[self.line].energy/1000)\\n #self.output_params={}\\n #print(self.getBulkCon(self.element,self.botchem,self.botden))\\n x = self.x + self.qoff\\n if not self.__fit__:\\n self.output_params['scaler_parameters']={}\\n return self.fluCalFun(x)\\n #return self.x\",\n \"def eval_fis(self,fis):\\n #res = 0.0\\n #for cl_state in self.classes:\\n # res += cl_state.eval_fis(fis)\\n #print \\\"=>\\\",res\\n #return 1.0/res\\n try:\\n correct,count = self.quality_fis(fis)\\n except Exception as err:\\n print err\\n correct = 0\\n return correct\",\n \"def bispectrum(self,l_edges,ratio=0.5,configuration=\\\"equilateral\\\",scale=None):\\n\\n\\t\\tassert not self._masked,\\\"Bispectrum calculation for masked maps is not allowed yet!\\\"\\n\\t\\tassert l_edges is not None\\n\\n\\t\\tif self.side_angle.unit.physical_type==\\\"length\\\":\\n\\t\\t\\traise NotImplementedError(\\\"Bispectrum measurement not implemented yet if side physical unit is length!\\\")\\n\\n\\t\\t#Check folding ratio\\n\\t\\tif (configuration==\\\"folded\\\") and not(ratio>0 and ratio<1):\\n\\t\\t\\traise ValueError(\\\"Folding ratio should be between 0 and 1!\\\")\\n\\n\\t\\t#Multipole edges\\n\\t\\tl = 0.5*(l_edges[:-1] + l_edges[1:])\\n\\n\\t\\t#Calculate FFT of the map via FFT\\n\\t\\tft_map = fftengine.rfft2(self.data)\\n\\n\\t\\t#Scale pixels if scaling is provided\\n\\t\\tif scale is not None:\\n\\t\\t\\tsc = scale(self.getEll())\\n\\t\\t\\tft_map *= np.cbrt(sc)\\n\\n\\t\\t#Calculate bispectrum\\n\\t\\tif configuration in (\\\"equilateral\\\",\\\"folded\\\"):\\n\\t\\t\\tbispectrum = _topology.bispectrum(ft_map,ft_map,ft_map,self.side_angle.to(u.deg).value,l_edges,configuration,ratio)\\n\\t\\telse:\\n\\t\\t\\traise NotImplementedError(\\\"Bispectrum configuration '{0}' not implemented!\\\".format(configuration))\\n\\n\\t\\t#Return\\n\\t\\treturn l,bispectrum\",\n \"def get_b(self):\\n return ((self.s_pos / self.n_pos) + (self.s_neg / self.n_neg)) / 2\",\n \"def bmi_calculate(self):\\r\\n try:\\r\\n manager_obj = BMI_Manager(self.data)\\r\\n manager_obj.bmi_calculation()\\r\\n except Exception as ex:\\r\\n print(\\\"Exception in bmi_calculate function\\\")\",\n \"def _calculate_strehl(self):\\n\\n self.strehl = np.exp(-1*((2*np.pi/self.science_wavelength)*self.high_order_wfe)**2)\",\n \"def start(self):\\n lastbeat = time.time()\\n averages = []\\n for x in range(self.keep_amount):\\n averages.append(1)\\n while self.run:\\n cur_amount = len(averages)\\n if self.keep_amount != cur_amount:\\n if self.keep_amount < cur_amount:\\n while self.keep_amount != len(averages):\\n averages.pop(0)\\n elif self.keep_amount < cur_amount:\\n avg = sum(averages)/cur_amount\\n while self.keep_amount != len(averages):\\n averages.append(avg)\\n self.do_fft()\\n mag = self.get_average(self.s_freq, self.e_freq)\\n avg = sum(averages)/self.keep_amount\\n averages.pop(0)\\n if (mag/avg)-1 > self.percent:\\n now = time.time()\\n if ((now-lastbeat) > self.wait_time) and self.relative_range() > .009:\\n lastbeat = now\\n self.detect_func()\\n averages.append(avg)\\n else:\\n averages.append(mag)\\n else:\\n averages.append(mag)\",\n \"def bMinusbStar(self):\\n running_total = 0\\n for i in range(self.prob.num):\\n if self.alphas[i] > 1e-5 and self.prob.Y[i] == -1:\\n ayxx = 0\\n for j in range(self.prob.num):\\n ayxx += self.alphas[j] * self.prob.Y[j] * self.prob.xkernel(self.prob.X[i], self.prob.X[j])\\n abcxx = 0\\n for j in range(self.prob.num):\\n abcxx += (self.alphas[j] + self.deltas[j]) * self.prob.xkernel(self.prob.X[i], self.prob.X[j])\\n abcxx *= (1 / self.prob.gamma)\\n running_total += -1 + abcxx - ayxx\\n return running_total\",\n \"def test_bayes_factor_b(self):\\n model_1 = ufloat(2, 1)\\n model_2 = ufloat(4, 1)\\n expected_result = ufloat(-4, 2.82842712474619032)\\n actual_result = utils.bayes_factor(model_1, model_2)\\n assert_almost_equal(actual_result.n, expected_result.n)\\n assert_almost_equal(actual_result.s, expected_result.s)\",\n \"def test_intra_power_law_fit(self):\\n\\n\\t\\tprint(type(self.fc_layers[0:2]), self.fc_layers[0:2])\\n\\t\\tdetails= self.watcher.analyze(layers=self.fc_layers[0:2], intra=True, randomize=False, vectors=False, pl_package=POWERLAW_PACKAGE, xmax=XMAX_FORCE)\\n\\t\\tactual_alpha = details.alpha[0]\\n\\t\\t#actual_best_fit = details.best_fit[0]\\n\\t\\t#print(actual_alpha,actual_best_fit)\\n\\n\\t\\texpected_alpha = 2.654 # not very accurate because of the sparisify transform\\n\\t\\t#expected_best_fit = LOG_NORMAL\\n\\t\\tself.assertAlmostEqual(actual_alpha,expected_alpha, places=1)\\n\\t\\t#self.assertEqual(actual_best_fit, expected_best_fit)\",\n \"def vbmstep(self):\\n for k in range(self.k):\\n self.beta_k[k] = self.beta_0 + self.counts[k]\\n self.m_k[k] = (1 / self.beta_k[k]) * (self.beta_0 * self.m_0 +\\n self.counts[k] * self.means[k])\\n\\n tmp = (self.beta_0 * self.counts[k]) / (self.beta_0 + self.counts[k])\\n tmp2 = (self.means[k] - self.m_0)\\n tmp = np.linalg.inv(self.W_0) + self.counts[k] * self.covars[k] + tmp * tmp2 @ tmp2.T\\n self.w_k[k] = np.linalg.inv(tmp)\\n self.nu_k[k] = self.nu_0 + self.counts[k]\\n self.alpha_k[k] = self.alpha_0[k] + self.counts[k]\",\n \"def fractional_absorbtion(self, port='Substrate'):\\n\\n base = self.sims[0].conf['General']['results_dir']\\n self.log.info('Computing fractional absorbtion for group at %s' % base)\\n vals = np.zeros(self.num_sims)\\n freqs = np.zeros(self.num_sims)\\n wvlgths = np.zeros(self.num_sims)\\n spectra = np.zeros(self.num_sims)\\n path = self.sims[0].conf['Simulation']['input_power_wv']\\n wv_vec, p_vec = np.loadtxt(path, usecols=(0, 2), unpack=True, delimiter=',')\\n p_wv = interpolate.interp1d(wv_vec, p_vec, kind='linear',\\n bounds_error=False, fill_value='extrapolate')\\n # Assuming the sims have been grouped by frequency, sum over all of\\n # them\\n for i, sim in enumerate(self.sims):\\n # Unpack data for the port we passed in as an argument\\n ref, trans, absorb = sim.data['transmission_data'][port]\\n freq = sim.conf['Simulation']['params']['frequency']\\n wvlgth = consts.c / freq\\n wvlgth_nm = wvlgth * 1e9\\n freqs[i] = freq\\n wvlgths[i] = wvlgth\\n # Get solar power from chosen spectrum\\n # Get p at wvlength by interpolation\\n sun_pow = p_wv(wvlgth_nm)\\n spectra[i] = sun_pow * wvlgth_nm\\n vals[i] = absorb * sun_pow * wvlgth_nm\\n sim.clear_data()\\n # Use Trapezoid rule to perform the integration. Note all the\\n # necessary factors of the wavelength have already been included\\n # above\\n wvlgths = wvlgths[::-1]\\n vals = vals[::-1]\\n spectra = spectra[::-1]\\n integrated_absorbtion = intg.trapz(vals, x=wvlgths * 1e9)\\n power = intg.trapz(spectra, x=wvlgths * 1e9)\\n # factor of 1/10 to convert A*m^-2 to mA*cm^-2\\n #wv_fact = consts.e/(consts.c*consts.h*10)\\n #wv_fact = .1\\n #Jsc = (Jsc*wv_fact)/power\\n frac_absorb = integrated_absorbtion / power\\n outf = os.path.join(base, 'fractional_absorbtion.dat')\\n with open(outf, 'w') as out:\\n out.write('%f\\\\n' % frac_absorb)\\n self.log.info('Fractional Absorbtion = %f' % frac_absorb)\\n return frac_absorb\",\n \"def check(self, data_input, debug_flag):\\n self.results = [ [], [], [], False, [] ]\\n _result = {}\\n _wave1_t = data_input[0][0]\\n _wave2_t = data_input[0][1]\\n _wave3_t = data_input[0][2] \\n _wave1_p = data_input[1][0]\\n _wave2_p = data_input[1][1]\\n _wave3_p = data_input[1][2]\\n\\n #Step1: b vs a\\n #Step1.1: time_analaysis\\n _result = {} \\n _result[str(\\\"b_a_t\\\")] = EW_fibonacci.check_fibratio(_wave2_t, _wave1_t)\\n self.results[0].append(_result)\\n\\n #Step1.2: price_analaysis\\n _result = {} \\n _result[str(\\\"b_a_p\\\")] = EW_fibonacci.check_fibratio(_wave2_p, _wave1_p)\\n self.results[0].append(_result)\\n\\n\\n #Step2: c vs b\\n #Step2.1: time_analaysis\\n _result = {} \\n _result[str(\\\"c_b_t\\\")] = EW_fibonacci.check_fibratio(_wave3_t, _wave2_t)\\n self.results[1].append(_result)\\n\\n #Step2.2: price_analaysis\\n _result = {} \\n _result[str(\\\"c_b_p\\\")] = EW_fibonacci.check_fibratio(_wave3_p, _wave2_p)\\n self.results[1].append(_result)\\n\\n \\n #Step3: c vs a\\n #Step3.1: time_analaysis\\n _result = {} \\n _result[str(\\\"c_a_t\\\")] = EW_fibonacci.check_fibratio(_wave3_t, _wave1_t)\\n self.results[2].append(_result)\\n\\n #Step3.2: price_analaysis\\n _result = {} \\n _result[str(\\\"c_a_p\\\")] = EW_fibonacci.check_fibratio(_wave3_p, _wave1_p)\\n self.results[2].append(_result)\\n\\n\\n #Step4: Check if this a-b-c is valid or not and which pattern can be chosen\\n self.results[3], self.results[4] = self.check_type(data_input, debug_flag)\\n\\n\\n #Step5: return the results\\n return self.results\",\n \"def run_results(self):\\n calculation_band = self.ctx.workchain_bands.get_outputs(link_type=LinkType.CALL)[0]\\n\\n self.report('workchain succesfully completed'.format())\\n self.out('band_parameters', calculation_band.out.output_parameters)\\n self.out('bandstructure', calculation_band.out.output_band)\",\n \"def _calculate_fuel_simple(self):\\n self._fuel_simple = (self.mass // 3) - 2\",\n \"def chisq_bs_fft(vis_arr, A, bis, sigma, order=FFT_INTERP_DEFAULT):\\n im_info, (uv1, uv2, uv3) = A \\n \\n bisamples = sampler(vis_arr, im_info, [uv1, uv2, uv3], order=order, sample_type=\\\"bs\\\")\\n\\n return np.sum(np.abs(((bis - bisamples)/sigma))**2)/(2.*len(bis))\",\n \"def inactivation(self):\\n\\n def boltzmann(voltage, vhalf, k):\\n\\n voltage = list(map(lambda x: float(x), voltage))\\n exponent = np.exp(np.divide(np.subtract(voltage, vhalf), k))\\n return (1/ (exponent + 1))\\n\\n def find_v_half(current, voltage):\\n \\\"\\\"\\\"\\n current: array of normalized IV curve\\n voltage: array of the test potentials\\n \\\"\\\"\\\"\\n for i in range(len(voltage)):\\n if current.iloc[i] < 0.5:\\n continue\\n elif current.iloc[i] == 0.5:\\n return voltage.iloc[i]\\n else:\\n volt1 = float(voltage.iloc[i-1])\\n volt2 = float(voltage.iloc[i])\\n curr1 = float(current.iloc[i-1])\\n curr2 = float(current.iloc[i])\\n V_half = volt1 + (volt1 - volt2)*(0.5 - curr1)/(curr1 - curr2)\\n return V_half\\n\\n v_half = []\\n for i in range(self.n_cols):\\n current = self.screened_data.iloc[:,i]\\n #print(current)\\n v_half.append(find_v_half(current, self.xaxis))\\n print('Median: ', np.median(v_half))\\n print('Min: ', np.min(v_half))\\n print('Max: ', np.max(v_half))\\n return 0\\n\\n initial_guess = [-42, 7]\\n popt, pcov = curve_fit(boltzmann, self.xaxis, self.averaged_data, p0= initial_guess)\\n plt.plot(self.xaxis, self.averaged_data, label = 'Average of all models')\\n plt.plot(boltzmann(self.xaxis, *initial_guess), label = 'Initial Guess')\\n plt.plot(self.xaxis, boltzmann(self.xaxis, *popt), label = 'Best Fit')\\n plt.xlabel('Voltage (mV)')\\n plt.ylabel('Normalized Current')\\n plt.title('Steady State Inactivation')\\n plt.legend()\\n plt.savefig('inactivation_boltzmann_fit.png')\\n return popt[0]\",\n \"def obtain_data(self):\\n ##MODIFY THIS\\n #ipdb.set_trace()\\n print('obtain_data')\\n print(self.enabler)\\n print(self.index)\\n helper = '>'+str(1+int(self.chann_span.get()))+'Q'\\n print('helper='+helper)\\n while(self.enabler):\\n #print('size'+str(1+int(self.chann_span.get())))\\n #print('offset'+str(self.index-self.index_offset))\\n A2 = struct.unpack(helper, fpga.read('A2', (1+int(self.chann_span.get()))*8, ((self.index-self.index_offset)*8))) \\n #print(A2)\\n #print(str(10*np.log10(A2))+'dB')\\n self.amp_a2[0] = np.mean(A2)\\n self.amp_a2 = np.roll(self.amp_a2, -1)\\n B2 = struct.unpack(helper, fpga.read('B2', (1+int(self.chann_span.get()))*8, ((self.index-self.index_offset)*8)))\\n self.amp_b2[0] = np.mean(B2)\\n self.amp_b2 = np.roll(self.amp_b2, -1)\\n AB_re = struct.unpack(helper, fpga.read('AB_re', (1+int(self.chann_span.get()))*8, ((self.index-self.index_offset)*8)))\\n self.ab_re[0] = np.mean(AB_re)\\n self.ab_re = np.roll(self.ab_re, -1)\\n AB_im = struct.unpack(helper, fpga.read('AB_im', (1+int(self.chann_span.get()))*8, ((self.index-self.index_offset)*8)))\\n self.ab_im[0] = np.mean(AB_im)\\n self.ab_im = np.roll(self.ab_im, -1) \\n # print('RE:' + str(self.ab_re)+ '\\\\t IM:' +str(self.ab_im))\\n log_a = 10*np.log10(np.mean(self.amp_a2)+1.0)\\n log_b = 10*np.log10(np.mean(self.amp_b2)+1.0) \\n ang = np.rad2deg(np.arctan2(np.mean(self.ab_im), np.mean(self.ab_re))) #review the way of avg this... i dont know if its the most correct way to do it...\\n self.a2.set(log_a)\\n self.b2.set(log_b)\\n self.ang.set(ang)\\n self.amp_rel.set(log_a-log_b)\\n return 1\",\n \"def calculate_dark_current(image, i, int_time):\\n dark_data_dir = r'F:\\\\TEMPO\\\\Data\\\\GroundTest\\\\FPS\\\\Integration_Sweep\\\\Dark'\\n data_path_name_split = image.split('_')\\n #print(data_path_name_split)\\n all_int_files = [each for each in os.listdir(dark_data_dir) \\\\\\n if each.endswith('_'+data_path_name_split[-1])] \\n print(all_int_files)\\n \\n dark_data_file = os.path.join(dark_data_dir, all_int_files[0])\\n IDL_variable = readsav(dark_data_file) \\n all_full_frame = IDL_variable.q \\n quad = all_full_frame[:, i, :, :]\\n active_quad = np.mean(quad[:, 4:1028, 10:1034], axis=0) \\n tsoc = np.mean(quad[:, 4:1028, 1034:1056], axis=0)\\n bias_subtracted_quad = perform_bias_subtraction_ave(active_quad, tsoc)\\n smear_subtracted_quad, smear_signal = perform_smear_subtraction(bias_subtracted_quad[10:1000, :], int_time)\\n return smear_subtracted_quad\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6264825","0.5765228","0.57305443","0.57027525","0.5698685","0.5697205","0.56671035","0.5649315","0.5634285","0.56256074","0.5624231","0.56226474","0.5614191","0.5581222","0.55639535","0.5559925","0.5559376","0.5537073","0.5524306","0.55227923","0.55111337","0.5504402","0.5493176","0.5486467","0.5483682","0.54766107","0.5472156","0.5471102","0.5467795","0.54659337","0.5461799","0.54587543","0.5458639","0.54538757","0.54526937","0.5436951","0.54133815","0.5411977","0.54072237","0.54048085","0.5404453","0.53845084","0.5381331","0.53812915","0.537866","0.5371272","0.5368133","0.536769","0.5361596","0.5356486","0.5342029","0.5335099","0.5333806","0.5333183","0.5332689","0.53290576","0.5324837","0.5323165","0.5323149","0.5320945","0.53205","0.5315784","0.53140485","0.5309223","0.53026015","0.53024316","0.53010195","0.5297728","0.5293308","0.5289845","0.5288629","0.52856016","0.52815926","0.5273339","0.526677","0.5266644","0.5266619","0.52649105","0.52646595","0.5250708","0.5250212","0.52496874","0.52493703","0.5236328","0.52309096","0.5230029","0.5229183","0.522825","0.52134794","0.52069664","0.52033955","0.5200593","0.51974076","0.5194796","0.5193684","0.5193369","0.5190385","0.5184464","0.51680595","0.5164832","0.5164794"],"string":"[\n \"0.6264825\",\n \"0.5765228\",\n \"0.57305443\",\n \"0.57027525\",\n \"0.5698685\",\n \"0.5697205\",\n \"0.56671035\",\n \"0.5649315\",\n \"0.5634285\",\n \"0.56256074\",\n \"0.5624231\",\n \"0.56226474\",\n \"0.5614191\",\n \"0.5581222\",\n \"0.55639535\",\n \"0.5559925\",\n \"0.5559376\",\n \"0.5537073\",\n \"0.5524306\",\n \"0.55227923\",\n \"0.55111337\",\n \"0.5504402\",\n \"0.5493176\",\n \"0.5486467\",\n \"0.5483682\",\n \"0.54766107\",\n \"0.5472156\",\n \"0.5471102\",\n \"0.5467795\",\n \"0.54659337\",\n \"0.5461799\",\n \"0.54587543\",\n \"0.5458639\",\n \"0.54538757\",\n \"0.54526937\",\n \"0.5436951\",\n \"0.54133815\",\n \"0.5411977\",\n \"0.54072237\",\n \"0.54048085\",\n \"0.5404453\",\n \"0.53845084\",\n \"0.5381331\",\n \"0.53812915\",\n \"0.537866\",\n \"0.5371272\",\n \"0.5368133\",\n \"0.536769\",\n \"0.5361596\",\n \"0.5356486\",\n \"0.5342029\",\n \"0.5335099\",\n \"0.5333806\",\n \"0.5333183\",\n \"0.5332689\",\n \"0.53290576\",\n \"0.5324837\",\n \"0.5323165\",\n \"0.5323149\",\n \"0.5320945\",\n \"0.53205\",\n \"0.5315784\",\n \"0.53140485\",\n \"0.5309223\",\n \"0.53026015\",\n \"0.53024316\",\n \"0.53010195\",\n \"0.5297728\",\n \"0.5293308\",\n \"0.5289845\",\n \"0.5288629\",\n \"0.52856016\",\n \"0.52815926\",\n \"0.5273339\",\n \"0.526677\",\n \"0.5266644\",\n \"0.5266619\",\n \"0.52649105\",\n \"0.52646595\",\n \"0.5250708\",\n \"0.5250212\",\n \"0.52496874\",\n \"0.52493703\",\n \"0.5236328\",\n \"0.52309096\",\n \"0.5230029\",\n \"0.5229183\",\n \"0.522825\",\n \"0.52134794\",\n \"0.52069664\",\n \"0.52033955\",\n \"0.5200593\",\n \"0.51974076\",\n \"0.5194796\",\n \"0.5193684\",\n \"0.5193369\",\n \"0.5190385\",\n \"0.5184464\",\n \"0.51680595\",\n \"0.5164832\",\n \"0.5164794\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":88599,"cells":{"query":{"kind":"string","value":"Sum up all 1's in a list, and calculate the product sum Return the original list and the summed If the list only contains one 1, dont calculate the sum >>> sum_ones((1, 1, 2), 112) [(1, 1, 2), (2, 2)], [2, 4] >>> sum_ones((1, 2), 2) [(1, 2)], [2] >>> sum_ones((2, ), 2) [(2,)], [2]"},"document":{"kind":"string","value":"def sum_ones(part, prod):\n if part in sum_ones_memory:\n partList, prodList = sum_ones_memory[part]\n else:\n n1 = part.count(1)\n partList = [part]\n prodList = [prod]\n if n1 > 1:\n npart = tuple(filter(lambda x: x != 1, part))\n npart = (n1,) + npart\n partList.append(npart)\n prodList.append(prod * n1)\n\n sum_ones_memory[part] = partList, prodList\n return partList, prodList"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def sum_list(numbers):\n\t\n\tif len(numbers) == 0:\n\t\treturn 0 \n\n\tsum = numbers[0] +sum_list(numbers[1:])\n\treturn sum","def zero_sum(list):\n if not list:\n return 0\n else:\n return sum(list)","def mult_and_sum(*arg_list):\r\n result = numpy.empty(arg_list[0].shape, dtype=numpy.float32)\r\n result[:] = nodata\r\n array_stack = numpy.array(arg_list[0::2])\r\n scalar_list = numpy.array(arg_list[1::2])\r\n # make a valid mask as big as a single array\r\n valid_mask = numpy.logical_and.reduce(\r\n array_stack != pop_nodata, axis=0)\r\n\r\n # mask out all invalid elements but reshape so there's still the same\r\n # number of arrays\r\n valid_array_elements = (\r\n array_stack[numpy.broadcast_to(valid_mask, array_stack.shape)])\r\n array_stack = None\r\n\r\n # sometimes this array is empty, check first before reshaping\r\n if valid_array_elements.size != 0:\r\n valid_array_elements = valid_array_elements.reshape(\r\n -1, numpy.count_nonzero(valid_mask))\r\n # multiply each element of the scalar with each row of the valid\r\n # array stack, then sum along the 0 axis to get the result\r\n result[valid_mask] = numpy.sum(\r\n (valid_array_elements.T * scalar_list).T, axis=0)\r\n scalar_list = None\r\n valid_mask = None\r\n valid_array_elements = None\r\n return result","def ones(dice):\n return sum([x for x in dice if x == 1])","def sum_product(numbers: List[int]) -> Tuple[int, int]:\n#[SOLUTION]\n sum_value = 0\n prod_value = 1\n\n for n in numbers:\n sum_value += n\n prod_value *= n\n return sum_value, prod_value","def list_product(lst):\n prod = 1\n for val in lst:\n prod *= val\n return prod","def mono_sum(l):\n r = next(l)\n for m in l: r = r + m\n return r","def product(mylist):\r\n temp = 1\r\n for num in mylist:\r\n temp *= num\r\n return temp","def prod(lst):\n res = 1.\n for x in lst: res *= x\n return res","def postitionalSum(list1, list2):\r\n\r\n myList = []\r\n\r\n if list1 == []:\r\n return []\r\n else:\r\n myList.append(list1[0]+list2[0])\r\n list1.remove(list1[0]), list2.remove(list2[0])\r\n postitionalSum(list1, list2)\r\n return myList","def summed(L):\r\n result = 0\r\n for e in L:\r\n result = result + e # or result += e\r\n return result","def prod(lst):\n return reduce(mul, lst, 1)","def add_list_numbers(incoming_list):\n # summation=0\n if incoming_list:\n summation = sum(incoming_list)\n else:\n summation = 0\n return summation","def addOnes(x,m):\n n = x.size/m\n one = np.ones((m,1))\n x = x.reshape((m,n))\n judge = np.sum(x[:,0] == one.flatten())\n if judge != m:\n x = np.hstack((one,x))\n return x","def sum_list(input_list: List[float]) -> float:\n return sum(input_list)","def sum_list(input_list: List[float]) -> float:\n return sum(input_list)","def ll_sum(some_list):\n #This function will return total value of all integers combinded.\n result = 0\n if type(some_list) == list: #Check the element is list or not?\n for i in range(len(some_list)):\n result += ll_sum(some_list[i]) # if it's a list call this function \n #so it will call over and over untill it found element that not a list.\n elif type(some_list) == float or type(some_list) == int: #if it's not list return it value.\n result += some_list\n return result","def prod(lst):\n if len(lst) == 0:\n return 0\n x = lst[0]\n for v in lst[1:]:\n x *= v\n return x","def prod(lst):\n if len(lst) == 0:\n return 0\n x = lst[0]\n for v in lst[1:]:\n x *= v\n return x","def sum(*args):\n return reduce(lambda x, y: x + y, args)","def prod(l):\n r = 1\n for x in l:\n r *= x\n return r","def sum_list(lst):\n\n if lst == []:\n return 0\n else:\n return lst[0] + sum_list(lst[1:])","def add_list_numbers(incoming_list):\n if incoming_list: #if incoming_list is not None and len(incoming_list) > 0\n return_value = sum(incoming_list)\n else:\n return_value = 0\n return return_value","def add_entries(entries_list):\r\n #| - add_entries\r\n sum_tot = 0.\r\n for entry in entries_list:\r\n if entry is None:\r\n summand = 0.\r\n else:\r\n summand = entry\r\n sum_tot += summand\r\n\r\n return(sum_tot)\r\n #__|\r","def add_list_numbers(incoming_list):\n if incoming_list:\n retval = sum(incoming_list)\n else:\n retval = 0\n return retval","def summed(*values):\n values = [_normalize(v) for v in values]\n for v in zip(*values):\n yield sum(v)","def sumValues(aList):\r\n sum = 0\r\n for d in aList:\r\n sum += d\r\n return sum","def sum_unique(l):\n pass","def multiplication_total_of(num_list):","def sum(values):\n total = 0\n for i in values:\n total += i\n return total","def sum_squared(variable_list):\n return sum([el * el for el in variable_list])","def singles(counts):\n return (counts==1).sum()","def sum_mixed_list(mxd_lst: List[Union[int, float]]) -> float:\n return sum(mxd_lst)","def sum_values(values):\n return (sum(values))","def intprod(xs):\n out = 1\n for x in xs:\n out *= x\n return out","def reduce_by_multiplication(data):\n total = 1\n for num in data:\n total *= num\n return total","def canSum(lst, target):\n\n return canSumHelper(lst, target, {})","def sum_tensors(xs: List[Optional[torch.Tensor]]) ->Optional[torch.Tensor]:\n idx = next((idx for idx, tensor in enumerate(xs) if tensor is not None), -1)\n if idx == -1:\n return None\n ret = xs[idx]\n for tensor in xs[idx + 1:]:\n if tensor is not None:\n ret = ret + tensor\n return ret","def product(numbers):\n p = 1\n for x in numbers:\n p *= x\n return p","def product(numbers):\n p = 1\n for x in numbers:\n p *= x\n return p","def single_number(nums: List[int]) -> int:\n ones = 0\n twos = 0\n\n for num in nums:\n # Record number that appears twice.\n twos |= (ones & num)\n\n # Record number that appears once.\n ones ^= num\n\n # Remove number that is on ones and twos.\n common_bit_mask = ~(ones & twos)\n ones &= common_bit_mask\n twos &= common_bit_mask\n return ones","def lsum (inlist):\r\n s = 0\r\n for item in inlist:\r\n s = s + item\r\n return s","def prod(L):\n res = 1\n for e in L:\n res *= e\n return res","def sum_node_list(node_list):\n node_list = [n for n in node_list if n is not None]\n if node_list == []:\n return None\n\n from operator import add\n from functools import reduce\n return reduce(add, node_list)","def sum_node_list(node_list):\r\n from operator import add\r\n from functools import reduce\r\n return reduce(add, node_list)","def multiply_list(lst):\n if lst == []:\n return 1\n else:\n return lst[0] * multiply_list(lst[1:])","def sum_node_list(node_list):\n from operator import add\n from functools import reduce\n return reduce(add, node_list)","def sum_of_numbers(numbers):\r\n return sum(numbers)","def sum_list(input_list: List[float]) -> float:\n sum: float = 0\n for i in input_list:\n sum = sum + i\n return sum","def multiply_ints(list_of_ints):\n\n products_of_all_ints_except_ind = [None] * len(list_of_ints)\n postproduct = 1\n\n for idx in xrange(len(list_of_ints) - 1, -1, -1):\n products_of_all_ints_except_ind[idx] = postproduct\n postproduct *= list_of_ints[idx]\n\n preproduct = 1\n \n for idx, num in enumerate(list_of_ints):\n products_of_all_ints_except_ind[idx] *= preproduct\n preproduct *= num\n\n return products_of_all_ints_except_ind","def custom_sum(*args):\n return functools.reduce(lambda x, y: x + y, args)","def MySum( l ):\n\n #checking if arg is a list\n if isinstance(l, list):\n\n #adding all numbs\n result = 0\n\n for numb in l:\n result = result + int(numb)\n\n return result\n\n else:\n return \"Argument is not a list\"","def sum_all_element(my_list):\n result = 0\n for i in range(len(my_list)):\n result = result + int(my_list[i])\n return result","def sum(inputList):\n sum=0#the sum of the list starts from 0\n for num in inputList:\n sum=sum+num#add all number in the list\n print(\"the sum is\",sum)","def add(numbers):\n sum1 = 0\n for i in numbers:\n sum1 = sum1+i\n\n return sum1","def recursive_sum(lst):\n\n if lst == []:\n return 0\n\n else:\n\n return lst[0] + recursive_sum(lst[1:])","def sum_f(f, xs):\n sum = 0\n for x in xs:\n sum += f(x)\n return sum","def possible_sums(numbers: Iterator[SnailfishNumber]) -> Iterator[SnailfishNumber]:\n yield from (a + b for a, b in permutations(numbers, 2))","def sum(lists) -> list:\r\n return list(np.sum(lists, 0))","def lsquare_of_sums(inlist):\r\n s = sum(inlist)\r\n return float(s)*s","def sum_items(a_list):\r\n assert len(a_list) >= 0, \"Length of List cannot be negative\"\r\n sum = 0\r\n if len(a_list) == 0:\r\n return sum\r\n else:\r\n for i in range(len(a_list)):\r\n sum += a_list[i]\r\n return sum","def recurrent_sum_of_elements_in_list(lst):\n if len(lst) == 0:\n return 0\n elif len(lst) == 1:\n return lst[0]\n return lst[0] + recurrent_sum_of_elements_in_list(lst[1:])","def lsummult (list1,list2):\r\n if len(list1) <> len(list2):\r\n raise ValueError, \"Lists not equal length in summult.\"\r\n s = 0\r\n for item1,item2 in pstats.abut(list1,list2):\r\n s = s + item1*item2\r\n return s","def SUM(*args):\n return _group_function(lambda x, y: x + y, *args)","def custom_sum(*args):\n return functools.reduce(lambda x, y: x + y, args)","def custom_sum(*args):\n return functools.reduce(lambda x, y: x + y, args)","def ll_sum(x):\n xlist = []\n for i in x:\n for num in i:\n xlist.append(num)\n return sum(xlist)","def sum_numbers(numbers):\n sum = 0\n for number in numbers:\n sum += number\n\n return sum","def sum_items(numbers):\n total = 0\n for item in numbers:\n total += item\n return total","def sum(*args):\n result = 0\n for i in args:\n result += i\n return result","def check_sum(cls, values):\n _v = [0 if v is None else v for v in values.values()]\n if abs(sum(_v) - 1) > 0.01:\n raise ValueError(\n f\"All values must approximately sum to 1. Sum to {sum(_v)}\"\n )\n return values","def sum_list_elements(input_list):\n print(f\"Sumatorio de los elementos dela lista: {sum(input_list)}\")","def prod(l):\n return reduce(lambda a, b: a*b, l)","def sum(lst):\n total = 0\n for i in lst:\n total += i\n return total","def sum(*nums): \n s=0\n for num in nums:\n s += num\n return s","def make_sum_in_2(a1, *rest):\n def helper(a, alist, acc):\n \"\"\"\n a: first argument\n alist: scheme list; rest of arguments\n acc: sum result so far\n \"\"\"\n if isNull(alist):\n if isNumber(a) and a == 0:\n return acc\n elif isNumber(acc) and acc == 0:\n return a\n elif isNumber(a) and isNumber(acc):\n return a + acc\n elif isList(acc):\n return append(acc, List(plus, a))\n else:\n return append(List(acc), List(plus, a))\n else:\n # more arguments in alist to process\n p = car(alist)\n q = cdr(alist)\n if isNumber(a) and a == 0:\n return helper(p, q, acc)\n elif isNumber(acc) and acc == 0:\n return helper(p, q, a)\n elif isNumber(a) and isNumber(acc):\n return helper(p, q, acc + a)\n else:\n if isList(acc):\n return helper(p, q, append(acc, List(plus, a)))\n else:\n return helper(p, q, append(List(acc), List(plus, a)))\n\n rests = List(*rest)\n return helper(a1, rests, 0)","def one(x):\n return zero(x) + 1","def multiply(numbers):\n prod = 1\n for i in numbers:\n prod = prod*i\n return prod","def num_of_ones(n, binary_list):\n # Start with no 1's\n num_ones = 0 \n while n > 0: \n for num in binary_list:\n # Start with the largest binary number\n # 1 occurs when num is equal to n or n can be subtracted positively \n if (num - n) <= 0:\n # Add 1 to tally and subtract binary num\n num_ones += 1\n n = n - num\n # Continue with new n\n return num_ones","def __call__(self, *array_list):\n valid_mask = numpy.zeros(array_list[0].shape, dtype=bool)\n result = numpy.empty_like(array_list[0])\n result[:] = 0\n for array in array_list:\n local_valid_mask = array != _INDEX_NODATA\n result[local_valid_mask] += array[local_valid_mask]\n valid_mask |= local_valid_mask\n result[~valid_mask] = _INDEX_NODATA\n return result","def multiply_list(input):\n result = 1\n #if there is no numbers in list return False\n if not input:\n return False\n #if the list contains strings or 0 return False\n else: \n for x in input:\n if type(x) == str or x == 0:\n return False \n else:\n result = result*x\n return result","def prefix_sum(x):\n if x.shape[0] == 1:\n return x\n\n if x.shape[0] % 2 == 1:\n z = x[:-1]\n z_ps = prefix_sum(z)\n return torch.cat([z_ps, z_ps[-1:] + x[-1:]], 0)\n\n y = x[::2] + x[1::2]\n y_ps = prefix_sum(y)\n\n result = torch.cat([(y_ps - x[1::2])[:, None], y_ps[:, None]], 1)\n result = result.reshape(x.shape)\n\n return result","def multi_1(cur,p,n):\n\tr=p\n\tfor k in range(0,n-1):\n\t\tr=sum(cur,r,p)\n\treturn r","def product(*nums):\n\treturn reduce((lambda x, y: x * y), nums)","def factsum(x):\n return sum(list(map(lambda x: factorial(x), getdigits(x))))","def add_this_many(x, y, lst):\n for elem in lst:\n if elem == 1:\n lst.append(y)","def summedOdds(L):\r\n result = 0\r\n for e in L:\r\n if e % 2 == 1:\r\n result = result + e # or result += e\r\n return result","def ones(*args):\n dims = list(args)\n assert type(dims[0]) == int\n return params_func(cmd, \"ones\", params=dims, return_type='FloatTensor')","def power_list_sum(s):\n x = len(s)\n my_list = []\n for i in range(1 << x):\n my_list.append(sum(([s[j] for j in range(x) if (i & (1 << j))])))\n\n return sorted(my_list)","def mul_if_sum(entries: Iterable[int]) -> int:\n for x, y in itertools.combinations(entries, 2):\n if x + y == 2020:\n return x * y\n else:\n raise NotImplementedError","def sum_fuel(fuel_list):\n return functools.reduce(lambda a, b: a+b, fuel_list)","def sumsq(values):\n\n return sum(map(lambda x: x ** 2, values))","def one_from_cartesian_product_of_one_basis(self):\n return self.sum_of_monomials( zip( self._sets_keys(), (set.one_basis() for set in self._sets)) )","def add_list_numbers(incoming_list: list):\n return sum(incoming_list)","def sum_list(num_list):\n # return sum(num_list)\n sum_list = 0\n for number in num_list:\n sum_list += number\n print(sum_list)\n \n # code prints out the sum_list for each value, increasing by the value each time\n # final output is the sum of numbers\n # currently no output for '[]' as input ","def sum_numbers(op_sum):\n collection = []\n for op in op_sum.operators:\n # Strip numeric coefficient off\n collected = False\n num = 1\n n_removed = 0\n op = collect_numbers(op)\n if op.tensors[0].name == \"$number\":\n num = op.tensors[0].content\n new_op = Operator(op.tensors[1:])\n else:\n num = 1\n new_op = op\n\n # Sum the numbers of equal operators\n for i, (collected_op, collected_num) in enumerate(collection):\n if collected_op == new_op:\n collected = True\n collection[i] = (new_op, num + collected_num)\n break\n if not collected:\n collection.append((new_op, num))\n return [(o, num) for o, num in collection if abs(num) > 10**(-10)]","def fsum(iterable):\n return 0.0","def power_sum(power, *args):\n total = 0\n for i in args:\n total += pow(i, power)\n return total","def binary_ones(lst_sorted):\n i = 0\n res = []\n while lst_sorted[i][1] == 1:\n res.append(lst_sorted[i])\n i += 1\n return res","def test_add():\n l = [1, 2, 3, 4]\n assert s7.add(*l) == sum(l)\n assert s7.add(100, 200) == 300\n assert s7.add(1.0, 2.0, 100.0) == 103.0"],"string":"[\n \"def sum_list(numbers):\\n\\t\\n\\tif len(numbers) == 0:\\n\\t\\treturn 0 \\n\\n\\tsum = numbers[0] +sum_list(numbers[1:])\\n\\treturn sum\",\n \"def zero_sum(list):\\n if not list:\\n return 0\\n else:\\n return sum(list)\",\n \"def mult_and_sum(*arg_list):\\r\\n result = numpy.empty(arg_list[0].shape, dtype=numpy.float32)\\r\\n result[:] = nodata\\r\\n array_stack = numpy.array(arg_list[0::2])\\r\\n scalar_list = numpy.array(arg_list[1::2])\\r\\n # make a valid mask as big as a single array\\r\\n valid_mask = numpy.logical_and.reduce(\\r\\n array_stack != pop_nodata, axis=0)\\r\\n\\r\\n # mask out all invalid elements but reshape so there's still the same\\r\\n # number of arrays\\r\\n valid_array_elements = (\\r\\n array_stack[numpy.broadcast_to(valid_mask, array_stack.shape)])\\r\\n array_stack = None\\r\\n\\r\\n # sometimes this array is empty, check first before reshaping\\r\\n if valid_array_elements.size != 0:\\r\\n valid_array_elements = valid_array_elements.reshape(\\r\\n -1, numpy.count_nonzero(valid_mask))\\r\\n # multiply each element of the scalar with each row of the valid\\r\\n # array stack, then sum along the 0 axis to get the result\\r\\n result[valid_mask] = numpy.sum(\\r\\n (valid_array_elements.T * scalar_list).T, axis=0)\\r\\n scalar_list = None\\r\\n valid_mask = None\\r\\n valid_array_elements = None\\r\\n return result\",\n \"def ones(dice):\\n return sum([x for x in dice if x == 1])\",\n \"def sum_product(numbers: List[int]) -> Tuple[int, int]:\\n#[SOLUTION]\\n sum_value = 0\\n prod_value = 1\\n\\n for n in numbers:\\n sum_value += n\\n prod_value *= n\\n return sum_value, prod_value\",\n \"def list_product(lst):\\n prod = 1\\n for val in lst:\\n prod *= val\\n return prod\",\n \"def mono_sum(l):\\n r = next(l)\\n for m in l: r = r + m\\n return r\",\n \"def product(mylist):\\r\\n temp = 1\\r\\n for num in mylist:\\r\\n temp *= num\\r\\n return temp\",\n \"def prod(lst):\\n res = 1.\\n for x in lst: res *= x\\n return res\",\n \"def postitionalSum(list1, list2):\\r\\n\\r\\n myList = []\\r\\n\\r\\n if list1 == []:\\r\\n return []\\r\\n else:\\r\\n myList.append(list1[0]+list2[0])\\r\\n list1.remove(list1[0]), list2.remove(list2[0])\\r\\n postitionalSum(list1, list2)\\r\\n return myList\",\n \"def summed(L):\\r\\n result = 0\\r\\n for e in L:\\r\\n result = result + e # or result += e\\r\\n return result\",\n \"def prod(lst):\\n return reduce(mul, lst, 1)\",\n \"def add_list_numbers(incoming_list):\\n # summation=0\\n if incoming_list:\\n summation = sum(incoming_list)\\n else:\\n summation = 0\\n return summation\",\n \"def addOnes(x,m):\\n n = x.size/m\\n one = np.ones((m,1))\\n x = x.reshape((m,n))\\n judge = np.sum(x[:,0] == one.flatten())\\n if judge != m:\\n x = np.hstack((one,x))\\n return x\",\n \"def sum_list(input_list: List[float]) -> float:\\n return sum(input_list)\",\n \"def sum_list(input_list: List[float]) -> float:\\n return sum(input_list)\",\n \"def ll_sum(some_list):\\n #This function will return total value of all integers combinded.\\n result = 0\\n if type(some_list) == list: #Check the element is list or not?\\n for i in range(len(some_list)):\\n result += ll_sum(some_list[i]) # if it's a list call this function \\n #so it will call over and over untill it found element that not a list.\\n elif type(some_list) == float or type(some_list) == int: #if it's not list return it value.\\n result += some_list\\n return result\",\n \"def prod(lst):\\n if len(lst) == 0:\\n return 0\\n x = lst[0]\\n for v in lst[1:]:\\n x *= v\\n return x\",\n \"def prod(lst):\\n if len(lst) == 0:\\n return 0\\n x = lst[0]\\n for v in lst[1:]:\\n x *= v\\n return x\",\n \"def sum(*args):\\n return reduce(lambda x, y: x + y, args)\",\n \"def prod(l):\\n r = 1\\n for x in l:\\n r *= x\\n return r\",\n \"def sum_list(lst):\\n\\n if lst == []:\\n return 0\\n else:\\n return lst[0] + sum_list(lst[1:])\",\n \"def add_list_numbers(incoming_list):\\n if incoming_list: #if incoming_list is not None and len(incoming_list) > 0\\n return_value = sum(incoming_list)\\n else:\\n return_value = 0\\n return return_value\",\n \"def add_entries(entries_list):\\r\\n #| - add_entries\\r\\n sum_tot = 0.\\r\\n for entry in entries_list:\\r\\n if entry is None:\\r\\n summand = 0.\\r\\n else:\\r\\n summand = entry\\r\\n sum_tot += summand\\r\\n\\r\\n return(sum_tot)\\r\\n #__|\\r\",\n \"def add_list_numbers(incoming_list):\\n if incoming_list:\\n retval = sum(incoming_list)\\n else:\\n retval = 0\\n return retval\",\n \"def summed(*values):\\n values = [_normalize(v) for v in values]\\n for v in zip(*values):\\n yield sum(v)\",\n \"def sumValues(aList):\\r\\n sum = 0\\r\\n for d in aList:\\r\\n sum += d\\r\\n return sum\",\n \"def sum_unique(l):\\n pass\",\n \"def multiplication_total_of(num_list):\",\n \"def sum(values):\\n total = 0\\n for i in values:\\n total += i\\n return total\",\n \"def sum_squared(variable_list):\\n return sum([el * el for el in variable_list])\",\n \"def singles(counts):\\n return (counts==1).sum()\",\n \"def sum_mixed_list(mxd_lst: List[Union[int, float]]) -> float:\\n return sum(mxd_lst)\",\n \"def sum_values(values):\\n return (sum(values))\",\n \"def intprod(xs):\\n out = 1\\n for x in xs:\\n out *= x\\n return out\",\n \"def reduce_by_multiplication(data):\\n total = 1\\n for num in data:\\n total *= num\\n return total\",\n \"def canSum(lst, target):\\n\\n return canSumHelper(lst, target, {})\",\n \"def sum_tensors(xs: List[Optional[torch.Tensor]]) ->Optional[torch.Tensor]:\\n idx = next((idx for idx, tensor in enumerate(xs) if tensor is not None), -1)\\n if idx == -1:\\n return None\\n ret = xs[idx]\\n for tensor in xs[idx + 1:]:\\n if tensor is not None:\\n ret = ret + tensor\\n return ret\",\n \"def product(numbers):\\n p = 1\\n for x in numbers:\\n p *= x\\n return p\",\n \"def product(numbers):\\n p = 1\\n for x in numbers:\\n p *= x\\n return p\",\n \"def single_number(nums: List[int]) -> int:\\n ones = 0\\n twos = 0\\n\\n for num in nums:\\n # Record number that appears twice.\\n twos |= (ones & num)\\n\\n # Record number that appears once.\\n ones ^= num\\n\\n # Remove number that is on ones and twos.\\n common_bit_mask = ~(ones & twos)\\n ones &= common_bit_mask\\n twos &= common_bit_mask\\n return ones\",\n \"def lsum (inlist):\\r\\n s = 0\\r\\n for item in inlist:\\r\\n s = s + item\\r\\n return s\",\n \"def prod(L):\\n res = 1\\n for e in L:\\n res *= e\\n return res\",\n \"def sum_node_list(node_list):\\n node_list = [n for n in node_list if n is not None]\\n if node_list == []:\\n return None\\n\\n from operator import add\\n from functools import reduce\\n return reduce(add, node_list)\",\n \"def sum_node_list(node_list):\\r\\n from operator import add\\r\\n from functools import reduce\\r\\n return reduce(add, node_list)\",\n \"def multiply_list(lst):\\n if lst == []:\\n return 1\\n else:\\n return lst[0] * multiply_list(lst[1:])\",\n \"def sum_node_list(node_list):\\n from operator import add\\n from functools import reduce\\n return reduce(add, node_list)\",\n \"def sum_of_numbers(numbers):\\r\\n return sum(numbers)\",\n \"def sum_list(input_list: List[float]) -> float:\\n sum: float = 0\\n for i in input_list:\\n sum = sum + i\\n return sum\",\n \"def multiply_ints(list_of_ints):\\n\\n products_of_all_ints_except_ind = [None] * len(list_of_ints)\\n postproduct = 1\\n\\n for idx in xrange(len(list_of_ints) - 1, -1, -1):\\n products_of_all_ints_except_ind[idx] = postproduct\\n postproduct *= list_of_ints[idx]\\n\\n preproduct = 1\\n \\n for idx, num in enumerate(list_of_ints):\\n products_of_all_ints_except_ind[idx] *= preproduct\\n preproduct *= num\\n\\n return products_of_all_ints_except_ind\",\n \"def custom_sum(*args):\\n return functools.reduce(lambda x, y: x + y, args)\",\n \"def MySum( l ):\\n\\n #checking if arg is a list\\n if isinstance(l, list):\\n\\n #adding all numbs\\n result = 0\\n\\n for numb in l:\\n result = result + int(numb)\\n\\n return result\\n\\n else:\\n return \\\"Argument is not a list\\\"\",\n \"def sum_all_element(my_list):\\n result = 0\\n for i in range(len(my_list)):\\n result = result + int(my_list[i])\\n return result\",\n \"def sum(inputList):\\n sum=0#the sum of the list starts from 0\\n for num in inputList:\\n sum=sum+num#add all number in the list\\n print(\\\"the sum is\\\",sum)\",\n \"def add(numbers):\\n sum1 = 0\\n for i in numbers:\\n sum1 = sum1+i\\n\\n return sum1\",\n \"def recursive_sum(lst):\\n\\n if lst == []:\\n return 0\\n\\n else:\\n\\n return lst[0] + recursive_sum(lst[1:])\",\n \"def sum_f(f, xs):\\n sum = 0\\n for x in xs:\\n sum += f(x)\\n return sum\",\n \"def possible_sums(numbers: Iterator[SnailfishNumber]) -> Iterator[SnailfishNumber]:\\n yield from (a + b for a, b in permutations(numbers, 2))\",\n \"def sum(lists) -> list:\\r\\n return list(np.sum(lists, 0))\",\n \"def lsquare_of_sums(inlist):\\r\\n s = sum(inlist)\\r\\n return float(s)*s\",\n \"def sum_items(a_list):\\r\\n assert len(a_list) >= 0, \\\"Length of List cannot be negative\\\"\\r\\n sum = 0\\r\\n if len(a_list) == 0:\\r\\n return sum\\r\\n else:\\r\\n for i in range(len(a_list)):\\r\\n sum += a_list[i]\\r\\n return sum\",\n \"def recurrent_sum_of_elements_in_list(lst):\\n if len(lst) == 0:\\n return 0\\n elif len(lst) == 1:\\n return lst[0]\\n return lst[0] + recurrent_sum_of_elements_in_list(lst[1:])\",\n \"def lsummult (list1,list2):\\r\\n if len(list1) <> len(list2):\\r\\n raise ValueError, \\\"Lists not equal length in summult.\\\"\\r\\n s = 0\\r\\n for item1,item2 in pstats.abut(list1,list2):\\r\\n s = s + item1*item2\\r\\n return s\",\n \"def SUM(*args):\\n return _group_function(lambda x, y: x + y, *args)\",\n \"def custom_sum(*args):\\n return functools.reduce(lambda x, y: x + y, args)\",\n \"def custom_sum(*args):\\n return functools.reduce(lambda x, y: x + y, args)\",\n \"def ll_sum(x):\\n xlist = []\\n for i in x:\\n for num in i:\\n xlist.append(num)\\n return sum(xlist)\",\n \"def sum_numbers(numbers):\\n sum = 0\\n for number in numbers:\\n sum += number\\n\\n return sum\",\n \"def sum_items(numbers):\\n total = 0\\n for item in numbers:\\n total += item\\n return total\",\n \"def sum(*args):\\n result = 0\\n for i in args:\\n result += i\\n return result\",\n \"def check_sum(cls, values):\\n _v = [0 if v is None else v for v in values.values()]\\n if abs(sum(_v) - 1) > 0.01:\\n raise ValueError(\\n f\\\"All values must approximately sum to 1. Sum to {sum(_v)}\\\"\\n )\\n return values\",\n \"def sum_list_elements(input_list):\\n print(f\\\"Sumatorio de los elementos dela lista: {sum(input_list)}\\\")\",\n \"def prod(l):\\n return reduce(lambda a, b: a*b, l)\",\n \"def sum(lst):\\n total = 0\\n for i in lst:\\n total += i\\n return total\",\n \"def sum(*nums): \\n s=0\\n for num in nums:\\n s += num\\n return s\",\n \"def make_sum_in_2(a1, *rest):\\n def helper(a, alist, acc):\\n \\\"\\\"\\\"\\n a: first argument\\n alist: scheme list; rest of arguments\\n acc: sum result so far\\n \\\"\\\"\\\"\\n if isNull(alist):\\n if isNumber(a) and a == 0:\\n return acc\\n elif isNumber(acc) and acc == 0:\\n return a\\n elif isNumber(a) and isNumber(acc):\\n return a + acc\\n elif isList(acc):\\n return append(acc, List(plus, a))\\n else:\\n return append(List(acc), List(plus, a))\\n else:\\n # more arguments in alist to process\\n p = car(alist)\\n q = cdr(alist)\\n if isNumber(a) and a == 0:\\n return helper(p, q, acc)\\n elif isNumber(acc) and acc == 0:\\n return helper(p, q, a)\\n elif isNumber(a) and isNumber(acc):\\n return helper(p, q, acc + a)\\n else:\\n if isList(acc):\\n return helper(p, q, append(acc, List(plus, a)))\\n else:\\n return helper(p, q, append(List(acc), List(plus, a)))\\n\\n rests = List(*rest)\\n return helper(a1, rests, 0)\",\n \"def one(x):\\n return zero(x) + 1\",\n \"def multiply(numbers):\\n prod = 1\\n for i in numbers:\\n prod = prod*i\\n return prod\",\n \"def num_of_ones(n, binary_list):\\n # Start with no 1's\\n num_ones = 0 \\n while n > 0: \\n for num in binary_list:\\n # Start with the largest binary number\\n # 1 occurs when num is equal to n or n can be subtracted positively \\n if (num - n) <= 0:\\n # Add 1 to tally and subtract binary num\\n num_ones += 1\\n n = n - num\\n # Continue with new n\\n return num_ones\",\n \"def __call__(self, *array_list):\\n valid_mask = numpy.zeros(array_list[0].shape, dtype=bool)\\n result = numpy.empty_like(array_list[0])\\n result[:] = 0\\n for array in array_list:\\n local_valid_mask = array != _INDEX_NODATA\\n result[local_valid_mask] += array[local_valid_mask]\\n valid_mask |= local_valid_mask\\n result[~valid_mask] = _INDEX_NODATA\\n return result\",\n \"def multiply_list(input):\\n result = 1\\n #if there is no numbers in list return False\\n if not input:\\n return False\\n #if the list contains strings or 0 return False\\n else: \\n for x in input:\\n if type(x) == str or x == 0:\\n return False \\n else:\\n result = result*x\\n return result\",\n \"def prefix_sum(x):\\n if x.shape[0] == 1:\\n return x\\n\\n if x.shape[0] % 2 == 1:\\n z = x[:-1]\\n z_ps = prefix_sum(z)\\n return torch.cat([z_ps, z_ps[-1:] + x[-1:]], 0)\\n\\n y = x[::2] + x[1::2]\\n y_ps = prefix_sum(y)\\n\\n result = torch.cat([(y_ps - x[1::2])[:, None], y_ps[:, None]], 1)\\n result = result.reshape(x.shape)\\n\\n return result\",\n \"def multi_1(cur,p,n):\\n\\tr=p\\n\\tfor k in range(0,n-1):\\n\\t\\tr=sum(cur,r,p)\\n\\treturn r\",\n \"def product(*nums):\\n\\treturn reduce((lambda x, y: x * y), nums)\",\n \"def factsum(x):\\n return sum(list(map(lambda x: factorial(x), getdigits(x))))\",\n \"def add_this_many(x, y, lst):\\n for elem in lst:\\n if elem == 1:\\n lst.append(y)\",\n \"def summedOdds(L):\\r\\n result = 0\\r\\n for e in L:\\r\\n if e % 2 == 1:\\r\\n result = result + e # or result += e\\r\\n return result\",\n \"def ones(*args):\\n dims = list(args)\\n assert type(dims[0]) == int\\n return params_func(cmd, \\\"ones\\\", params=dims, return_type='FloatTensor')\",\n \"def power_list_sum(s):\\n x = len(s)\\n my_list = []\\n for i in range(1 << x):\\n my_list.append(sum(([s[j] for j in range(x) if (i & (1 << j))])))\\n\\n return sorted(my_list)\",\n \"def mul_if_sum(entries: Iterable[int]) -> int:\\n for x, y in itertools.combinations(entries, 2):\\n if x + y == 2020:\\n return x * y\\n else:\\n raise NotImplementedError\",\n \"def sum_fuel(fuel_list):\\n return functools.reduce(lambda a, b: a+b, fuel_list)\",\n \"def sumsq(values):\\n\\n return sum(map(lambda x: x ** 2, values))\",\n \"def one_from_cartesian_product_of_one_basis(self):\\n return self.sum_of_monomials( zip( self._sets_keys(), (set.one_basis() for set in self._sets)) )\",\n \"def add_list_numbers(incoming_list: list):\\n return sum(incoming_list)\",\n \"def sum_list(num_list):\\n # return sum(num_list)\\n sum_list = 0\\n for number in num_list:\\n sum_list += number\\n print(sum_list)\\n \\n # code prints out the sum_list for each value, increasing by the value each time\\n # final output is the sum of numbers\\n # currently no output for '[]' as input \",\n \"def sum_numbers(op_sum):\\n collection = []\\n for op in op_sum.operators:\\n # Strip numeric coefficient off\\n collected = False\\n num = 1\\n n_removed = 0\\n op = collect_numbers(op)\\n if op.tensors[0].name == \\\"$number\\\":\\n num = op.tensors[0].content\\n new_op = Operator(op.tensors[1:])\\n else:\\n num = 1\\n new_op = op\\n\\n # Sum the numbers of equal operators\\n for i, (collected_op, collected_num) in enumerate(collection):\\n if collected_op == new_op:\\n collected = True\\n collection[i] = (new_op, num + collected_num)\\n break\\n if not collected:\\n collection.append((new_op, num))\\n return [(o, num) for o, num in collection if abs(num) > 10**(-10)]\",\n \"def fsum(iterable):\\n return 0.0\",\n \"def power_sum(power, *args):\\n total = 0\\n for i in args:\\n total += pow(i, power)\\n return total\",\n \"def binary_ones(lst_sorted):\\n i = 0\\n res = []\\n while lst_sorted[i][1] == 1:\\n res.append(lst_sorted[i])\\n i += 1\\n return res\",\n \"def test_add():\\n l = [1, 2, 3, 4]\\n assert s7.add(*l) == sum(l)\\n assert s7.add(100, 200) == 300\\n assert s7.add(1.0, 2.0, 100.0) == 103.0\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.595099","0.58707553","0.5846285","0.5818005","0.58091325","0.5784409","0.5705578","0.5697676","0.56917393","0.5681991","0.56177396","0.555534","0.5501804","0.5495922","0.546188","0.546188","0.5457171","0.5431213","0.5431213","0.54213077","0.53874594","0.5378755","0.53755105","0.53656137","0.53595465","0.5343651","0.5327367","0.53222346","0.5321152","0.53196466","0.5312755","0.52905756","0.52881205","0.5283355","0.52698517","0.52636814","0.5261164","0.5261042","0.52555835","0.52555835","0.5252761","0.5249539","0.524683","0.52458024","0.52351826","0.52218837","0.52042687","0.52020645","0.51831776","0.5177126","0.5165367","0.516376","0.51505464","0.5147227","0.5145449","0.5143399","0.51269954","0.51237047","0.51147044","0.5110678","0.51094157","0.5108945","0.5101551","0.5100319","0.5085587","0.5085587","0.5083195","0.50813746","0.5080836","0.5075314","0.50660706","0.505939","0.5051048","0.5049664","0.50335294","0.5029779","0.5028338","0.50253034","0.50227785","0.5020366","0.5018149","0.4996832","0.49904945","0.4989523","0.498385","0.49830773","0.4983059","0.49820825","0.4972671","0.49642023","0.4943884","0.4940749","0.4937882","0.49376082","0.49348673","0.49308816","0.49301842","0.4927393","0.49270916","0.4904761"],"string":"[\n \"0.595099\",\n \"0.58707553\",\n \"0.5846285\",\n \"0.5818005\",\n \"0.58091325\",\n \"0.5784409\",\n \"0.5705578\",\n \"0.5697676\",\n \"0.56917393\",\n \"0.5681991\",\n \"0.56177396\",\n \"0.555534\",\n \"0.5501804\",\n \"0.5495922\",\n \"0.546188\",\n \"0.546188\",\n \"0.5457171\",\n \"0.5431213\",\n \"0.5431213\",\n \"0.54213077\",\n \"0.53874594\",\n \"0.5378755\",\n \"0.53755105\",\n \"0.53656137\",\n \"0.53595465\",\n \"0.5343651\",\n \"0.5327367\",\n \"0.53222346\",\n \"0.5321152\",\n \"0.53196466\",\n \"0.5312755\",\n \"0.52905756\",\n \"0.52881205\",\n \"0.5283355\",\n \"0.52698517\",\n \"0.52636814\",\n \"0.5261164\",\n \"0.5261042\",\n \"0.52555835\",\n \"0.52555835\",\n \"0.5252761\",\n \"0.5249539\",\n \"0.524683\",\n \"0.52458024\",\n \"0.52351826\",\n \"0.52218837\",\n \"0.52042687\",\n \"0.52020645\",\n \"0.51831776\",\n \"0.5177126\",\n \"0.5165367\",\n \"0.516376\",\n \"0.51505464\",\n \"0.5147227\",\n \"0.5145449\",\n \"0.5143399\",\n \"0.51269954\",\n \"0.51237047\",\n \"0.51147044\",\n \"0.5110678\",\n \"0.51094157\",\n \"0.5108945\",\n \"0.5101551\",\n \"0.5100319\",\n \"0.5085587\",\n \"0.5085587\",\n \"0.5083195\",\n \"0.50813746\",\n \"0.5080836\",\n \"0.5075314\",\n \"0.50660706\",\n \"0.505939\",\n \"0.5051048\",\n \"0.5049664\",\n \"0.50335294\",\n \"0.5029779\",\n \"0.5028338\",\n \"0.50253034\",\n \"0.50227785\",\n \"0.5020366\",\n \"0.5018149\",\n \"0.4996832\",\n \"0.49904945\",\n \"0.4989523\",\n \"0.498385\",\n \"0.49830773\",\n \"0.4983059\",\n \"0.49820825\",\n \"0.4972671\",\n \"0.49642023\",\n \"0.4943884\",\n \"0.4940749\",\n \"0.4937882\",\n \"0.49376082\",\n \"0.49348673\",\n \"0.49308816\",\n \"0.49301842\",\n \"0.4927393\",\n \"0.49270916\",\n \"0.4904761\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7017122"},"document_rank":{"kind":"string","value":"0"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":885,"numItemsPerPage":100,"numTotalItems":95772,"offset":88500,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6IjVHZDBvd0g5MTM2eDZjc1FvbE1zcktNWUZoRVFoUm5PVVVybEpjOUhaUEEifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc4NTgxMjEyMiwianRpIjoiNmZkNjBmZGUtNGVmOC00ZDA1LWI3NDQtZmUxNDM3ZmZjNDg4Iiwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3ODU4MTU3MjIsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.IoK4GgRZIGVHOZT-3s9WMMyBxOqeJnQneb-1Et1pL7aO_l8-vQHKcpAbkGUerYE_G-zSIaR0Rscj_wBpH4aNDw","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":95772,"numBytesParquet":1928375891}]},"discussionsStats":{"closed":1,"open":1,"total":2},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
Convert the integer from decimal to hex | def _convert_to_hex(self, integer):
hex_string = str(hex(int(integer)))[2:]
length = len(hex_string)
if length == 1:
hex_string = str(0) + hex_string
return hex_string | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def int_to_hex(num):\n return hex(num)",
"def int_to_hex(n):\r\n #return \"0x%X\" % n\r\n return hex(n)",
"def int2hex(n: int) -> str:",
"def int_to_hex(a):\n return hex(a)",
"def int_to_hexstr(data: int) -> str:\n return \"%0.2X\" % data",
"def conv_hex(num):\n\n if num < 10:\n ... | [
"0.85311806",
"0.8476238",
"0.8375074",
"0.8229931",
"0.7800177",
"0.76471466",
"0.7494922",
"0.74854594",
"0.7398706",
"0.7394598",
"0.73338336",
"0.7332243",
"0.732811",
"0.7318254",
"0.721986",
"0.71589303",
"0.70401853",
"0.7032715",
"0.70237076",
"0.7009764",
"0.6910827"... | 0.78436655 | 4 |
Assemble mac address from the list | def _get_mac_address(self, mac_numbers):
mac = ""
for num in mac_numbers:
num = self._convert_to_hex(num)
mac = ':'.join((mac, num))
mac = mac[1:]
return mac | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def mac_address(self):\n mac = [\n self.random.randint(0x00, 0xff),\n self.random.randint(0x00, 0xff),\n self.random.randint(0x00, 0xff),\n self.random.randint(0x00, 0xff),\n self.random.randint(0x00, 0xff),\n self.random.randint(0x00, 0xff)\... | [
"0.7022228",
"0.68802977",
"0.6582795",
"0.6570698",
"0.6570698",
"0.6570698",
"0.6570698",
"0.6556131",
"0.6456271",
"0.6389757",
"0.63864744",
"0.6316981",
"0.6316593",
"0.63095945",
"0.6283913",
"0.62120837",
"0.6191361",
"0.6191361",
"0.61385566",
"0.61184037",
"0.6116887... | 0.740949 | 0 |
Read private key and certificates from files. Return (private key, certificates) chain pair. | def read_chain_pair(private_key, certificates):
with open(private_key, 'rb') as f:
private_key = f.read()
with open(certificates, 'rb') as f:
certificates = f.read()
return (private_key, certificates) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def load_key_and_cert(key_file, cert_file):\n with open(cert_file, 'rb') as f:\n cert = x509.load_pem_x509_certificate(f.read(), default_backend())\n with open(key_file, 'rb') as f:\n key = serialization.load_pem_private_key(f.read(), None, backend=default_backend())\n\n ... | [
"0.6391459",
"0.62914973",
"0.5971284",
"0.59437066",
"0.58221966",
"0.57909185",
"0.57617474",
"0.5750648",
"0.564614",
"0.5595037",
"0.5582063",
"0.55411404",
"0.54925364",
"0.5485883",
"0.54124856",
"0.5362128",
"0.5354524",
"0.5340389",
"0.5324609",
"0.5308338",
"0.526386... | 0.8233212 | 0 |
If store is set it should be an EventStore object where we'll save events as they arrive | def __init__(self, store=None):
self.sockets = []
self.poller = zmq.core.poll.Poller()
self.mh = MessageHandler()
self.store = store | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_store(self, store):\n self.store = store",
"def setSessionStore(self, store):\n pass",
"def _set_store(self, store):\n for method in list(self.methods.values()):\n method.__servicemethod__['store'] = store\n self._store = store",
"def do(self, store: \"GrocerySt... | [
"0.7089652",
"0.6831267",
"0.6632132",
"0.6583045",
"0.62921906",
"0.626166",
"0.6146996",
"0.60109043",
"0.5977724",
"0.5927897",
"0.59195673",
"0.58189577",
"0.5815198",
"0.5811567",
"0.57356155",
"0.57228196",
"0.57043916",
"0.5689016",
"0.56362695",
"0.5594212",
"0.554945... | 0.48892748 | 98 |
Add sock (a zmq socket) to list of sockets we'll listen for events on | def listen(self, sock):
self.sockets.append(sock)
self.poller.register(sock, zmq.POLLIN) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_socket(self, socket):\n self.add_sockets([socket])",
"def add_sockets(self, sockets):\n if self.io_loop is None:\n self.io_loop = IOLoop.current()\n\n for sock in sockets:\n self._sockets[sock.fileno()] = sock\n self.io_loop.add_handler(sock.fileno(),... | [
"0.6908348",
"0.675583",
"0.66643906",
"0.64296603",
"0.60607636",
"0.6004247",
"0.5915704",
"0.58805346",
"0.5824161",
"0.5776066",
"0.56614673",
"0.56568986",
"0.56186587",
"0.560656",
"0.5605178",
"0.5531999",
"0.5525945",
"0.55209213",
"0.55099356",
"0.547657",
"0.5465054... | 0.7839191 | 0 |
Get the next event. Wait for timeout milliseconds or forever if timeout is None | def getEvent(self, timeout=None):
socks = self.poller.poll(timeout)
if not socks:
return
msg = socks[0][0].recv()
d = self.mh.unserialize(msg)
e = Event.fromDict(d)
if self.store:
_id = self.store.addEvent(e)
e.id = _id
return e | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_next_event(self, timeout=None):\n ret = self.inq.Wait(timeout)\n return ret",
"async def _read_event(self, timeout: int=None):\n event = None\n try:\n event = await wait_for(self.get_event(), timeout=timeout)\n except TimeoutError:\n pass\n\n ... | [
"0.87932193",
"0.717155",
"0.70189875",
"0.66396683",
"0.65838164",
"0.65481365",
"0.65381086",
"0.65064025",
"0.63976747",
"0.6372901",
"0.63268286",
"0.63096327",
"0.6288369",
"0.62413335",
"0.6240144",
"0.6238906",
"0.62270033",
"0.6205946",
"0.6071406",
"0.6068982",
"0.60... | 0.5931091 | 24 |
Applies network layers and ops on input image(s) x. | def forward(self, x, test=False):
sources = list()
loc = list()
conf = list()
# apply bases layers and cache source layer outputs
for k in range(len(self.base)):
x = self.base[k](x)
if k in self.feature_layer:
if len(sources) == 0:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def apply_network(inputs):\n return apply_layer(tf.sigmoid(apply_layer(inputs, 64)), 1)",
"def forward(self, x):\n for task_module_name in self.task_module_name_path[self.task_idx]:\n for layer in self.task_modules[task_module_name]:\n x = layer(x)\n #x = self.task_... | [
"0.65620095",
"0.63693756",
"0.6366089",
"0.63534147",
"0.6309185",
"0.6308151",
"0.6257753",
"0.6208064",
"0.6199206",
"0.619269",
"0.61763096",
"0.616371",
"0.6153872",
"0.6143252",
"0.61291367",
"0.61276346",
"0.61222804",
"0.61158955",
"0.6111172",
"0.60992426",
"0.608334... | 0.0 | -1 |
Get normalized strings for the group items in the group. Then sort them by frequency. Normalize the text for comparison by removing spaces and punctuation, and setting all letters to lower case. The exemplar for the group is the longest prenormalized value. So if we have three | def normalized_exact_matches(group, row_count) -> tuple[int, int, list[list]]:
# Sort the fields by normalized values
filled = defaultdict(list)
for field in group:
if key := re.sub(r"\W+", "", field.value).lower():
filled[key].append(field)
# Bring the field with the longest value ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def main(str_text):\n\n frequencies = count_value(str_text)\n sorted_data = sort_dict(frequencies)\n\n return sorted_data",
"def _textualize_group(group):\n # The final string. A list is used for performance.\n ret_str = []\n\n ones = int(group[2])\n tens = int(group[1])\n hundreds = int(... | [
"0.612385",
"0.6013692",
"0.5886225",
"0.58484906",
"0.5825418",
"0.5696492",
"0.5666141",
"0.5631283",
"0.56154144",
"0.5601557",
"0.55016863",
"0.5499204",
"0.5485176",
"0.54496175",
"0.5447808",
"0.53935516",
"0.5383511",
"0.535823",
"0.53225",
"0.53172135",
"0.5288765",
... | 0.5639996 | 7 |
Return the best partial ratio match from fuzzywuzzy module. | def top_partial_ratio(group):
scores = []
for c0, c1 in combinations(group, 2):
score = fuzz.partial_ratio(c0.value, c1.value)
field = c0 if len(c0.value) >= len(c1.value) else c1
scores.append(FuzzyRatioScore(score, field))
scores = sorted(scores, reverse=True, key=lambda s: (s.sco... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fuzzy_partial_ratio(thing_1, thing_2):\n return fuzz.partial_ratio(thing_1, thing_2)",
"def fuzzy_ratio(thing_1, thing_2):\n return fuzz.ratio(thing_1, thing_2)",
"def find_best_match(fpl_teams: List[str], team: str) -> Tuple[str, int]:\n best_ratio = 0.0\n best_match = None\n for t in fpl_teams... | [
"0.767117",
"0.706915",
"0.7045623",
"0.69615054",
"0.688134",
"0.68650913",
"0.6457859",
"0.62769884",
"0.6275168",
"0.60757107",
"0.6075642",
"0.60390335",
"0.60216784",
"0.60216784",
"0.5956916",
"0.5956916",
"0.59508455",
"0.59213847",
"0.5902485",
"0.5899878",
"0.5849218... | 0.7887274 | 0 |
Return the best token set ratio match from fuzzywuzzy module. | def top_token_set_ratio(group):
scores = []
for c0, c1 in combinations(group, 2):
score = fuzz.token_set_ratio(c0.value, c1.value)
tokens_0 = len(c0.value.split())
tokens_1 = len(c1.value.split())
if tokens_0 > tokens_1:
field = c0
tokens = tokens_0
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fuzzy_token_sort_ratio(thing_1, thing_2):\n return fuzz.token_sort_ratio(thing_1, thing_2)",
"def find_best_match(fpl_teams: List[str], team: str) -> Tuple[str, int]:\n best_ratio = 0.0\n best_match = None\n for t in fpl_teams:\n if fuzz.partial_ratio(t, team) > best_ratio:\n best... | [
"0.7019757",
"0.6915708",
"0.6894662",
"0.6811242",
"0.6709782",
"0.6509443",
"0.62935543",
"0.6287032",
"0.62503135",
"0.6221222",
"0.62034714",
"0.6132662",
"0.6018528",
"0.59871924",
"0.59778166",
"0.59441316",
"0.59365857",
"0.59181213",
"0.58937454",
"0.5874365",
"0.5842... | 0.75352436 | 0 |
Make pod specification for Kubernetes | def make_pod_spec(self):
spec = {
'containers': [{
'name': self.framework.model.app.name,
'imageDetails': {
},
'ports': [{
'containerPort':
self.framework.model.config['advertised-port'],
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_pod_spec():\n md = metadata()\n cfg = config()\n\n if cfg.get(\"enable-sidecar\"):\n with open(\"reactive/spec_template_ha.yaml\") as spec_file:\n pod_spec_template = spec_file.read()\n else:\n with open(\"reactive/spec_template.yaml\") as spec_file:\n pod_s... | [
"0.7959695",
"0.7671487",
"0.7217666",
"0.67198086",
"0.6675382",
"0.6622293",
"0.6397979",
"0.6320169",
"0.6240289",
"0.60877234",
"0.59261304",
"0.5921372",
"0.58255005",
"0.5815334",
"0.5736419",
"0.56606907",
"0.5654171",
"0.5562911",
"0.5464203",
"0.5450449",
"0.5433386"... | 0.76017493 | 2 |
Return all arguments required to execute CLI | def get_arguments(self):
args = self.parser.parse_args()
config = None
with open(args.config_file, "r") as f:
config = json.load(f)
if "collections" in config:
if len(config["collections"]) > 0:
collection = config["collections"][0]
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_cli_arguments(self):\n pass",
"def __get_cli_args():\r\n parser = argparse.ArgumentParser()\r\n o = parser.add_mutually_exclusive_group()\r\n o.add_argument('-a', action='store_true')\r\n o.add_argument('-b', action='store_true')\r\n parser.add_argument('-suite', help='suite file na... | [
"0.8434595",
"0.7754269",
"0.7644272",
"0.76297367",
"0.76230663",
"0.75364363",
"0.74571276",
"0.7417445",
"0.7412155",
"0.7406127",
"0.7401388",
"0.73903877",
"0.73764217",
"0.7358373",
"0.73560494",
"0.7318047",
"0.73040634",
"0.72991544",
"0.7276237",
"0.72737163",
"0.725... | 0.0 | -1 |
Returns the API version based on the release track. | def GetApiVersion(cls):
if cls.ReleaseTrack() == base.ReleaseTrack.ALPHA:
return 'alpha'
elif cls.ReleaseTrack() == base.ReleaseTrack.BETA:
return 'beta'
return 'v1' | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_version(self):\n return self.api_version",
"def get_api_version(session: \"Session\") -> str:\n component_versions = get_component_versions(session)\n return str(component_versions.get(CoordConsts.KEY_API_VERSION, \"2.0.0\"))",
"def api_version(self) -> Optional[str]:\n return pulum... | [
"0.7356627",
"0.73361796",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",
"0.73104286",... | 0.8126857 | 0 |
Returns the resource schema path. | def GetSchemaPath(cls, for_help=False):
return export_util.GetSchemaPath(
'compute', cls.GetApiVersion(), 'BackendService', for_help=for_help) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_bundled_schema_path():\n return str(data.load_resource(\"schema\"))",
"def _get_base_schema_path(base_schema: str = None) -> str:\n biothings_schema_path = LOADER.filename(\"data_models/biothings.model.jsonld\")\n base_schema_path = biothings_schema_path if base_schema is None else base_schema\n... | [
"0.8129537",
"0.7225695",
"0.7073041",
"0.70640045",
"0.68459177",
"0.6833207",
"0.67889005",
"0.67540175",
"0.67540175",
"0.6610404",
"0.64634776",
"0.6445213",
"0.6430494",
"0.6416756",
"0.6370232",
"0.63636297",
"0.62787116",
"0.62350994",
"0.6226971",
"0.6226971",
"0.6224... | 0.7178181 | 2 |
Create Backend Services patch request. | def ComposePatchRequest(self, client, backend_service_ref, replacement):
if backend_service_ref.Collection() == 'compute.regionBackendServices':
return (
client.apitools_client.regionBackendServices,
'Patch',
client.messages.ComputeRegionBackendServicesPatchRequest(
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def requestfactory_patch(self, path, data=None, content_type=client.MULTIPART_CONTENT, **extra):\r\n\r\n data = data or {}\r\n patch_data = self._encode_data(data, content_type)\r\n\r\n parsed = urlparse.urlparse(path)\r\n request = {\r\n 'CONTENT_LENGTH': len(patch_data),\r\n 'CONTENT_TY... | [
"0.6822116",
"0.6498407",
"0.6371376",
"0.6356031",
"0.6331954",
"0.63101476",
"0.618666",
"0.61838037",
"0.61745155",
"0.61538756",
"0.61318535",
"0.6130529",
"0.61251915",
"0.6110662",
"0.6103166",
"0.6076066",
"0.6054936",
"0.6054936",
"0.6054936",
"0.6049838",
"0.6041006"... | 0.6702764 | 1 |
Resonsible for loading configs and setting up client | def load_config(self, config_file, usage):
config = configparser.ConfigParser()
config.read(config_file)
auth_id = config.get('SMARTY STREETS', 'auth_id' )
auth_token = config.get('SMARTY STREETS', 'auth_token')
api_credentials = StaticCredentials(auth_id, auth_token)
cli... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def config():",
"def config():",
"def client_setup(self):\n self.client = Client()",
"def configure(self):",
"def configure(self):",
"def configure(self):",
"def configure(self):",
"def _configure(self):\n pass",
"def config():\n config_django()\n config_svisor()",
"def __init... | [
"0.7131933",
"0.7131933",
"0.70558983",
"0.68658847",
"0.68658847",
"0.68658847",
"0.68658847",
"0.68388593",
"0.6827142",
"0.68141896",
"0.67925876",
"0.67326516",
"0.67191195",
"0.6715665",
"0.6709162",
"0.6709162",
"0.6655134",
"0.6629441",
"0.6599594",
"0.65726084",
"0.65... | 0.6837061 | 8 |
Responsible for sending request to service | def send_request(self, params, address_data):
try:
# Stream considered a batch of one
self.client.send_batch(address_data)
return address_data
except exceptions.SmartyException as err:
print(err)
return | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ServiceRequest(self):\n #- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -\n pass",
"def _send_request(self):\n route_chosen = self.comboBox_route_list.currentText()\n route_id = route_chosen.split(',')[0] #to get the id of the route\n trip_headsign_ch... | [
"0.7657708",
"0.73205423",
"0.7213784",
"0.7085317",
"0.6995092",
"0.69075006",
"0.68932",
"0.681189",
"0.66904163",
"0.6668911",
"0.66416377",
"0.66416377",
"0.6629037",
"0.6605246",
"0.65916795",
"0.6575594",
"0.6537439",
"0.6485675",
"0.64799434",
"0.64799434",
"0.6435945"... | 0.0 | -1 |
Reponsible for validating input addresses in stream or batch form. returns a list containing a single Address object for stream input and multiple for batch input. | def validate(self, params, address_input_data):
processed_address_list = []
# check avoids redundancy for combined 'forward geocode and validate'
# option as API does both by default
if self.__is_address_list_processed:
processed_address_list = address_input_data
els... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __process_smarty_request_list(self, request_list, address_input_data ):\n assert(len(address_input_data) == self.__total_addresses_in_request_list)\n\n processed_address_list = []\n address_iterator = iter(address_input_data)\n for unprocessed_request in request_list: \n ... | [
"0.6725842",
"0.6710126",
"0.6240761",
"0.6221789",
"0.62037283",
"0.6125183",
"0.61011887",
"0.61011887",
"0.61011887",
"0.6095425",
"0.6018221",
"0.5996222",
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"0.59931666",
"0.59471816",
"0.5929042",
"0.5874366",
"0.5863718",
"0.5857947",
"0.5847198",
"0.5830124... | 0.7343851 | 0 |
Reponsible for forward geocoding input addresses in stream or batch form. returns a list containing a single Address object for stream input and multiple for batch input. | def forward_geocode(self, params, address_input_data ):
processed_address_list = []
# check avoids redundancy for combined 'forward geocode and validate'
# option as API does both by default
if self.__is_address_list_processed:
processed_address_list = address_input_data
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def addresses(self) -> pulumi.Input[Sequence[pulumi.Input[str]]]:\n return pulumi.get(self, \"addresses\")",
"def validate(self, params, address_input_data):\n processed_address_list = []\n # check avoids redundancy for combined 'forward geocode and validate' \n # option as API does b... | [
"0.6530636",
"0.64462525",
"0.63802785",
"0.6370371",
"0.6355637",
"0.616385",
"0.6150521",
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"0.5960874",
"0.5960874",
"0.5901883",
"0.5866094",
"0.58648705",
"0.5802863",
"0.5780841",
"0.57634604",
"0.57634604",
"0.5756493",
"0.57322425",
"0.5726187",
"0.56785333... | 0.7548706 | 0 |
Returns a list of requests each containing SmartyAddressService.MAX_ADDRESSES_PER_REQUEST address input strings. Input Address strings are converted smarty street Lookup objects. The request list is a list of batch partitions, smarty street Batch objects, which serves as the overall address batch. | def __prepare_smarty_request_list(self, address_list):
single_request_batch_partition = Batch()
addresses_per_request = 0
request_list = []
for address in address_list:
if addresses_per_request == SmartyAddressService.MAX_ADDRESSES_PER_REQUEST:
request_list.ap... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __process_smarty_request_list(self, request_list, address_input_data ):\n assert(len(address_input_data) == self.__total_addresses_in_request_list)\n\n processed_address_list = []\n address_iterator = iter(address_input_data)\n for unprocessed_request in request_list: \n ... | [
"0.5991902",
"0.50746",
"0.50179887",
"0.5004752",
"0.4969774",
"0.4932725",
"0.48918006",
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"0.48422703",
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"0.48248988",
"0.47963837",
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"0.47551847",
"0.47398427",
"0.4738118",
"0.4730094",
"0.47092748",
"0.46977097",
"0.4692... | 0.7343559 | 0 |
Process request list through smarty streets API and assign response to corresponding address objects. Each individual request contains SmartyAddressService.MAX_ADDRESSES_PER_REQUEST address Lookups, which are assigned candidate addresses by their api. This function chooses the top candidate is chosen and assigns desire... | def __process_smarty_request_list(self, request_list, address_input_data ):
assert(len(address_input_data) == self.__total_addresses_in_request_list)
processed_address_list = []
address_iterator = iter(address_input_data)
for unprocessed_request in request_list:
params = {}... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __prepare_smarty_request_list(self, address_list):\n single_request_batch_partition = Batch()\n addresses_per_request = 0\n request_list = []\n for address in address_list:\n if addresses_per_request == SmartyAddressService.MAX_ADDRESSES_PER_REQUEST:\n requ... | [
"0.67963153",
"0.56317437",
"0.5481398",
"0.54446745",
"0.5351575",
"0.5254347",
"0.51797926",
"0.50109726",
"0.4875006",
"0.48727018",
"0.4871034",
"0.4861196",
"0.4853113",
"0.48028946",
"0.4739545",
"0.47258613",
"0.4718744",
"0.470152",
"0.46981382",
"0.46929234",
"0.4670... | 0.6969019 | 0 |
Displays an options menu with the given options by executing dmenu with the provided list of arguments. Returns the chosen option or None if none of the given options was chosen. | def dmenu(options, args=[], path=DEFAULT_DMENU_PATH):
dmenu = subprocess.Popen([path] + args,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE)
option_lines = '\n'.join(map(str, options))
option = dmenu.communicate(option_lines.encode('utf-8'))[0] \
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run(self, args=[], path=DEFAULT_DMENU_PATH):\n options = self.create_options()\n option = dmenu(options, args=args, path=path)\n if option:\n self.handle_option(option, options)",
"def menuItem(*args):\n\toptionsWindow()",
"def show(self):\n # Display the menu.\n ... | [
"0.69564426",
"0.65855235",
"0.6582707",
"0.64486706",
"0.64389974",
"0.6281806",
"0.6219096",
"0.60309243",
"0.6030296",
"0.5987751",
"0.5915396",
"0.5903842",
"0.5899842",
"0.5889831",
"0.58847314",
"0.58633196",
"0.5862723",
"0.58552134",
"0.5834016",
"0.57824904",
"0.5700... | 0.79341877 | 0 |
Returns a list of options. Each option should have a __str__ function. To be overwritten by subclasses. | def create_options(self):
return [] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _getOptions(self):\n args = []\n for iname, value in self.options:\n args.append('-' + iname)\n if value != 'true':\n args.append(value)\n return args",
"def getOptionsNames(self) -> List[unicode]:\n ...",
"def get_options(self):\n return []",
"def all_options(self... | [
"0.7744731",
"0.7684556",
"0.7572338",
"0.7344777",
"0.7327094",
"0.7252559",
"0.7191892",
"0.7009248",
"0.6922074",
"0.6905703",
"0.68965507",
"0.6893068",
"0.6864366",
"0.6856245",
"0.6714529",
"0.66810274",
"0.66718227",
"0.6670524",
"0.665573",
"0.6653253",
"0.6648187",
... | 0.6918581 | 9 |
Handles the option chosen in the dmenu. To be overwritten by subclasses. | def handle_option(self, option, options):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getMenuOption():\n return menu_option",
"def handle_select(self):\n #self.selected = input('>> ')\n self.selected = '0'\n if self.selected in ['Q', 'q']:\n sys.exit(1)\n elif self.selected in ['B', 'b']:\n self.back_to_menu = True\n return True\... | [
"0.673435",
"0.66599476",
"0.66203",
"0.65081906",
"0.6503948",
"0.6503179",
"0.64747703",
"0.64747703",
"0.6417105",
"0.6362919",
"0.63450885",
"0.631465",
"0.6263112",
"0.6202966",
"0.6188523",
"0.61634606",
"0.61166906",
"0.60992646",
"0.6090097",
"0.60768914",
"0.6067128"... | 0.6845839 | 0 |
Creates the options with the create_options function and passes them to dmenu with the additional arguments. If an option was selected it is passed to the handle_option function. | def run(self, args=[], path=DEFAULT_DMENU_PATH):
options = self.create_options()
option = dmenu(options, args=args, path=path)
if option:
self.handle_option(option, options) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def menuItem(*args):\n\toptionsWindow()",
"def optionMenu(*args, alwaysCallChangeCommand: bool=True, annotation: Union[AnyStr, bool]=\"\",\n backgroundColor: Union[List[float, float, float], bool]=None, beforeShowPopup:\n Script=None, changeCommand: Script=None, defineTemplate: AnyStr... | [
"0.65391994",
"0.64011323",
"0.6330111",
"0.6309242",
"0.62822783",
"0.6005424",
"0.60025024",
"0.5913053",
"0.5886426",
"0.58417106",
"0.57628626",
"0.57540554",
"0.5687309",
"0.56249946",
"0.5620401",
"0.5612325",
"0.5583547",
"0.55540794",
"0.5524454",
"0.5461041",
"0.5457... | 0.68001723 | 0 |
Builds a simple TCN model for a classification task | def build_model(sequence_length: int,
channels: int,
filters: List[int],
num_classes:int,
kernel_size: int,
return_sequence:bool = False):
inputs = Input(shape=(sequence_length, channels), name="inputs")
tcn_block = TCN(filters, ke... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_simple_cnn_text_classifier(\n tok2vec, nr_class, exclusive_classes: bool = ..., **cfg\n):\n ...",
"def build_classifier_model():\n model = keras.Sequential([\n keras.layers.SimpleRNN(64, input_shape=(\n special_train_data.shape[1], special_train_data.shape[2])),\n kera... | [
"0.71211946",
"0.69382614",
"0.6906103",
"0.68612593",
"0.68130636",
"0.67430156",
"0.6741936",
"0.6705188",
"0.67038774",
"0.6694892",
"0.66709346",
"0.6634681",
"0.66216224",
"0.6617651",
"0.6607445",
"0.6606493",
"0.65538424",
"0.6550777",
"0.65458614",
"0.653813",
"0.6536... | 0.63886184 | 35 |
Return a MatchUp dataset object for testing | def return_MatchUpTest_r__():
####################################################################################################################
# 1. Initialise test data
####################################################################################################################
values = arr... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test(self) -> tf.contrib.data.Dataset:\n return self.__test_dataset",
"def get_dataset(self):\n if self.mode == \"test\":\n return OnlineQueryDataset(self.mode, self.df, self.tokenizer)\n else:\n return OnlineQueryDataset(self.mode, self.df_reindex, self.tokenizer)"... | [
"0.60991913",
"0.59801537",
"0.590321",
"0.58124125",
"0.5796239",
"0.5700579",
"0.5692139",
"0.56579125",
"0.5635389",
"0.56350327",
"0.5593532",
"0.5573973",
"0.55623806",
"0.5521337",
"0.55109745",
"0.5507842",
"0.55040926",
"0.5502235",
"0.547906",
"0.5468841",
"0.5455943... | 0.54437053 | 22 |
Return a MatchUp dataset object for testing | def return_MatchUpTest_rsw():
####################################################################################################################
# 1. Initialise test data
####################################################################################################################
w2_matchup1 ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test(self) -> tf.contrib.data.Dataset:\n return self.__test_dataset",
"def get_dataset(self):\n if self.mode == \"test\":\n return OnlineQueryDataset(self.mode, self.df, self.tokenizer)\n else:\n return OnlineQueryDataset(self.mode, self.df_reindex, self.tokenizer)"... | [
"0.6105403",
"0.59885746",
"0.5901588",
"0.5820917",
"0.5801885",
"0.57081044",
"0.5693726",
"0.56677276",
"0.56453776",
"0.564505",
"0.5599134",
"0.55832756",
"0.5564017",
"0.552816",
"0.55132306",
"0.5511637",
"0.55106306",
"0.55045444",
"0.54888856",
"0.54743016",
"0.54616... | 0.0 | -1 |
Return a MatchUp dataset object for testing | def return_MatchUpTest___w():
####################################################################################################################
# 1. Initialise test data
####################################################################################################################
w1 = array([... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test(self) -> tf.contrib.data.Dataset:\n return self.__test_dataset",
"def get_dataset(self):\n if self.mode == \"test\":\n return OnlineQueryDataset(self.mode, self.df, self.tokenizer)\n else:\n return OnlineQueryDataset(self.mode, self.df_reindex, self.tokenizer)"... | [
"0.6102343",
"0.5986422",
"0.5898837",
"0.58181185",
"0.5799401",
"0.570617",
"0.56921023",
"0.5665207",
"0.56421",
"0.564138",
"0.55963594",
"0.5580343",
"0.5563257",
"0.55256814",
"0.55107045",
"0.5510297",
"0.55078745",
"0.55020255",
"0.54860723",
"0.5471566",
"0.5458956",... | 0.0 | -1 |
Test for Transform2NormInd.run() for test ``eopy.matchup.matchupIO.MatchUp`` object with data for multiple matchup series random uncertainty type only | def test_run_multi_r__(self):
# Test Description
# ================
#
# 1. This test intialises an example *eopy.matchup.matchupIO.MatchUp* object
#
# 2. Compare transformed dataset to expected value
##############################################################... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def return_MatchUpTest_r__():\n\n ####################################################################################################################\n # 1. Initialise test data\n ####################################################################################################################\n\n v... | [
"0.618169",
"0.61430645",
"0.59169275",
"0.57321066",
"0.57125336",
"0.5702606",
"0.5576436",
"0.55339223",
"0.5435399",
"0.54145247",
"0.53927404",
"0.53498745",
"0.534863",
"0.5331139",
"0.5256002",
"0.5251248",
"0.5210866",
"0.5170504",
"0.5157448",
"0.51404893",
"0.511381... | 0.68906015 | 0 |
Test for Transform2NormInd.run() for test ``eopy.matchup.matchupIO.MatchUp`` object with data for multiple matchup series random uncertainty type only | def test_run_single___w(self):
# Test Description
# ================
#
# 1. This test intialises an example *eopy.matchup.matchupIO.MatchUp* object
#
# 2. Compare transformed dataset to expected value
#############################################################... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_run_multi_r__(self):\n\n # Test Description\n # ================\n #\n # 1. This test intialises an example *eopy.matchup.matchupIO.MatchUp* object\n #\n # 2. Compare transformed dataset to expected value\n\n ################################################... | [
"0.68889105",
"0.6180161",
"0.5917096",
"0.57318056",
"0.5712777",
"0.5701163",
"0.55743426",
"0.5532345",
"0.5433569",
"0.5414042",
"0.53910625",
"0.5350428",
"0.5347398",
"0.5328523",
"0.5253318",
"0.52499676",
"0.52101165",
"0.5169099",
"0.51579434",
"0.5140735",
"0.511289... | 0.61428434 | 2 |
A simple NonRepairableRBD with three intermediate nodes in series. | def rbd_series() -> NonRepairableRBD:
edges = [(1, 2), (2, 3), (3, 4), (4, 5)]
reliabilities = {
2: surv.Weibull.from_params([20, 2]),
3: surv.Weibull.from_params([100, 3]),
4: surv.Weibull.from_params([50, 20]),
}
return NonRepairableRBD(edges, reliabilities) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rbd_repeated_component_parallel() -> NonRepairableRBD:\n edges = [(1, 2), (1, 3), (1, 4), (1, 5), (2, 6), (3, 6), (4, 6), (5, 6)]\n reliabilities = {\n 2: FixedEventProbability.from_params(1 - 0.8),\n 3: FixedEventProbability.from_params(1 - 0.9),\n 4: FixedEventProbability.from_para... | [
"0.6469559",
"0.64268315",
"0.6084605",
"0.57024527",
"0.5674748",
"0.56264883",
"0.56160796",
"0.5606025",
"0.56040335",
"0.5561237",
"0.5558424",
"0.5544655",
"0.54072654",
"0.5387844",
"0.53377455",
"0.53331965",
"0.52934223",
"0.5282019",
"0.52817273",
"0.52617866",
"0.52... | 0.6040757 | 3 |
A simple NonRepairableRBD with three intermediate nodes in parallel. | def rbd_parallel() -> NonRepairableRBD:
edges = [(1, 2), (1, 3), (1, 4), (2, 5), (3, 5), (4, 5)]
reliabilities = {
2: FixedEventProbability.from_params(1 - 0.8),
3: FixedEventProbability.from_params(1 - 0.9),
4: FixedEventProbability.from_params(1 - 0.85),
}
return NonRepairableR... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rbd_repeated_component_parallel() -> NonRepairableRBD:\n edges = [(1, 2), (1, 3), (1, 4), (1, 5), (2, 6), (3, 6), (4, 6), (5, 6)]\n reliabilities = {\n 2: FixedEventProbability.from_params(1 - 0.8),\n 3: FixedEventProbability.from_params(1 - 0.9),\n 4: FixedEventProbability.from_para... | [
"0.6714331",
"0.6077196",
"0.5871187",
"0.5761095",
"0.575306",
"0.57487047",
"0.5707745",
"0.5683427",
"0.56822884",
"0.5626346",
"0.5609467",
"0.5545553",
"0.553127",
"0.55290705",
"0.55273926",
"0.55230594",
"0.5517176",
"0.55019444",
"0.547357",
"0.5447232",
"0.54407746",... | 0.7042741 | 0 |
Example 6.10 from Modarres & Kaminskiy. | def rbd1() -> NonRepairableRBD:
qp = 0.03
qv = 0.01
edges = [
("source", "pump1"),
("source", "pump2"),
("pump1", "valve"),
("pump2", "valve"),
("valve", "sink"),
]
reliabilities = {
"pump1": FixedEventProbability.from_params(qp),
"pump2": Fixe... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_pagination(self):\n self.check_pagination()",
"def paginated(self) -> global___Snippet.Paginated:",
"def test_pagination(self):\n for page in range(1, 5):\n self._test_one_page(page=page)",
"def index(request):\n\n queryset_list = Todo.objects.all() #.order_by(\"-timestam... | [
"0.6430027",
"0.63266945",
"0.5850248",
"0.58150655",
"0.5708066",
"0.56947297",
"0.5693278",
"0.56105494",
"0.5602378",
"0.5580202",
"0.5572011",
"0.55451834",
"0.55417097",
"0.5530029",
"0.5465714",
"0.5439728",
"0.5436072",
"0.54357344",
"0.5380605",
"0.5379788",
"0.534536... | 0.0 | -1 |
Fig. 16.1 from "UNIT 16 RELIABILITY EVALUATION OF COMPLEX SYSTEMS" by | def rbd3() -> NonRepairableRBD:
edges = [
(0, 1),
(0, 3),
(1, 2),
(3, 4),
(1, 5),
(3, 5),
(5, 2),
(5, 4),
(2, 6),
(4, 6),
]
reliabilities = {
1: FixedEventProbability.from_params(1 - 0.95),
2: FixedEventProbabili... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exercise_b2_106():\r\n pass",
"def exercise_b2_113():\r\n pass",
"def exercise_b2_53():\r\n pass",
"def exercise_b2_93():\r\n pass",
"def exercise_b2_70():\r\n pass",
"def exercise_b2_95():\r\n pass",
"def exercise_b2_107():\r\n pass",
"def exercise_b2_98():\r\n pass",
"... | [
"0.64974594",
"0.6486075",
"0.6471702",
"0.6450107",
"0.64436185",
"0.6400729",
"0.6381994",
"0.6331832",
"0.6328109",
"0.6320709",
"0.6289737",
"0.62463313",
"0.61991066",
"0.61939657",
"0.6116703",
"0.60365844",
"0.6014344",
"0.60068136",
"0.5940624",
"0.5919313",
"0.584285... | 0.0 | -1 |
Basically rbd_parallel with a repeated component (component 2). | def rbd_repeated_component_parallel() -> NonRepairableRBD:
edges = [(1, 2), (1, 3), (1, 4), (1, 5), (2, 6), (3, 6), (4, 6), (5, 6)]
reliabilities = {
2: FixedEventProbability.from_params(1 - 0.8),
3: FixedEventProbability.from_params(1 - 0.9),
4: FixedEventProbability.from_params(1 - 0.8... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rbd_parallel() -> NonRepairableRBD:\n edges = [(1, 2), (1, 3), (1, 4), (2, 5), (3, 5), (4, 5)]\n reliabilities = {\n 2: FixedEventProbability.from_params(1 - 0.8),\n 3: FixedEventProbability.from_params(1 - 0.9),\n 4: FixedEventProbability.from_params(1 - 0.85),\n }\n return No... | [
"0.66087776",
"0.59290457",
"0.5882417",
"0.5852172",
"0.5571424",
"0.5562024",
"0.55331624",
"0.544469",
"0.537368",
"0.5371877",
"0.5354507",
"0.5273932",
"0.5170079",
"0.51246303",
"0.50607854",
"0.5056613",
"0.50508237",
"0.50475144",
"0.50254637",
"0.5022691",
"0.4972075... | 0.7394611 | 0 |
Example 6.10 from Modarres & Kaminskiy, w/ valve k=2. | def rbd1_koon() -> NonRepairableRBD:
qp = 0.03
qv = 0.01
edges = [
("source", "pump1"),
("source", "pump2"),
("pump1", "valve"),
("pump2", "valve"),
("valve", "sink"),
]
reliabilities = {
"pump1": FixedEventProbability.from_params(qp),
"pump2":... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def k(x):\n if x < 3:\n return 1\n else:\n return 3",
"def kthsmall(v, k):\n n=len(v)\n k-=1\n if k<0 or k >= n:\n return -1\n l=0\n u=n-1\n while True:\n m=part(v,l,u)\n if m==k: return v[m]\n if m<k: l = m+1\n else: u=m-1",
"def test_k_rank_approximate(corpus):\n r... | [
"0.60299236",
"0.59745216",
"0.595954",
"0.59423935",
"0.584232",
"0.57831573",
"0.5767858",
"0.5766451",
"0.5740797",
"0.57142466",
"0.5708032",
"0.56949073",
"0.5677055",
"0.56758654",
"0.5663218",
"0.5658442",
"0.56492513",
"0.56461674",
"0.5622466",
"0.56185037",
"0.56175... | 0.0 | -1 |
rbd2 but k of node 7 is =2. | def rbd2_koon() -> NonRepairableRBD:
edges = [(1, 2), (2, 3), (2, 4), (4, 7), (3, 5), (5, 6), (6, 7), (7, 8)]
reliabilities = {
2: surv.Weibull.from_params([20, 2]),
3: surv.Weibull.from_params([100, 3]),
4: surv.Weibull.from_params([50, 20]),
5: surv.Weibull.from_params([15, 1.2... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rbd3_koon2() -> NonRepairableRBD:\n edges, reliabilities = rbd3_nodes_edges_components()\n k = {2: 2}\n return NonRepairableRBD(edges, reliabilities, k)",
"def rbd3_koon1() -> NonRepairableRBD:\n edges, reliabilities = rbd3_nodes_edges_components()\n k = {5: 2}\n return NonRepairableRBD(edg... | [
"0.64837515",
"0.6033989",
"0.58228284",
"0.56298786",
"0.5610498",
"0.5605671",
"0.55991936",
"0.55821586",
"0.5548604",
"0.55299145",
"0.5437083",
"0.54195094",
"0.53975606",
"0.5387104",
"0.53656757",
"0.5359423",
"0.5346822",
"0.53252655",
"0.53040564",
"0.5302914",
"0.52... | 0.6389324 | 1 |
Fig. 16.1 from "UNIT 16 RELIABILITY EVALUATION OF COMPLEX SYSTEMS" by | def rbd3_koon1() -> NonRepairableRBD:
edges, reliabilities = rbd3_nodes_edges_components()
k = {5: 2}
return NonRepairableRBD(edges, reliabilities, k) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exercise_b2_106():\r\n pass",
"def exercise_b2_113():\r\n pass",
"def exercise_b2_53():\r\n pass",
"def exercise_b2_93():\r\n pass",
"def exercise_b2_70():\r\n pass",
"def exercise_b2_95():\r\n pass",
"def exercise_b2_107():\r\n pass",
"def exercise_b2_98():\r\n pass",
"... | [
"0.64974594",
"0.6486075",
"0.6471702",
"0.6450107",
"0.64436185",
"0.6400729",
"0.6381994",
"0.6331832",
"0.6328109",
"0.6320709",
"0.6289737",
"0.62463313",
"0.61991066",
"0.61939657",
"0.6116703",
"0.60365844",
"0.6014344",
"0.60068136",
"0.5940624",
"0.5919313",
"0.584285... | 0.0 | -1 |
Fig. 16.1 from "UNIT 16 RELIABILITY EVALUATION OF COMPLEX SYSTEMS" by | def rbd3_koon2() -> NonRepairableRBD:
edges, reliabilities = rbd3_nodes_edges_components()
k = {2: 2}
return NonRepairableRBD(edges, reliabilities, k) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exercise_b2_106():\r\n pass",
"def exercise_b2_113():\r\n pass",
"def exercise_b2_53():\r\n pass",
"def exercise_b2_93():\r\n pass",
"def exercise_b2_70():\r\n pass",
"def exercise_b2_95():\r\n pass",
"def exercise_b2_107():\r\n pass",
"def exercise_b2_98():\r\n pass",
"... | [
"0.6498275",
"0.6486834",
"0.64725345",
"0.64507645",
"0.6444394",
"0.64013785",
"0.6382778",
"0.6332466",
"0.63291615",
"0.6320123",
"0.6290228",
"0.6246944",
"0.6199687",
"0.61948127",
"0.61174875",
"0.60374105",
"0.60128015",
"0.600762",
"0.59412605",
"0.59189135",
"0.5842... | 0.0 | -1 |
Fig. 16.1 from "UNIT 16 RELIABILITY EVALUATION OF COMPLEX SYSTEMS" by | def rbd3_koon3() -> NonRepairableRBD:
edges, reliabilities = rbd3_nodes_edges_components()
k = {2: 2, 5: 2}
return NonRepairableRBD(edges, reliabilities, k) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exercise_b2_106():\r\n pass",
"def exercise_b2_113():\r\n pass",
"def exercise_b2_53():\r\n pass",
"def exercise_b2_93():\r\n pass",
"def exercise_b2_70():\r\n pass",
"def exercise_b2_95():\r\n pass",
"def exercise_b2_107():\r\n pass",
"def exercise_b2_98():\r\n pass",
"... | [
"0.6497635",
"0.6486453",
"0.6471992",
"0.6449999",
"0.6443822",
"0.6400814",
"0.6382336",
"0.6332183",
"0.63283956",
"0.6321123",
"0.6289827",
"0.6246541",
"0.6199174",
"0.6194083",
"0.61166835",
"0.60365397",
"0.6014905",
"0.60070395",
"0.5940377",
"0.59195703",
"0.58420813... | 0.0 | -1 |
A s31t NonRepairableRBD. Returns the {nodes, edges, reliabilities} dict, useful so k(4) can be changed. | def rbd_koon_parallel_args() -> dict:
edges = [
("s", 1),
("s", 2),
("s", 3),
(1, "v"),
(2, "v"),
(3, "v"),
("v", "t"),
]
reliabilities = {
1: FixedEventProbability.from_params(1 - 0.85),
2: FixedEventProbability.from_params(1 - 0.8),
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rbd3() -> NonRepairableRBD:\n edges = [\n (0, 1),\n (0, 3),\n (1, 2),\n (3, 4),\n (1, 5),\n (3, 5),\n (5, 2),\n (5, 4),\n (2, 6),\n (4, 6),\n ]\n reliabilities = {\n 1: FixedEventProbability.from_params(1 - 0.95),\n 2:... | [
"0.63566744",
"0.61939704",
"0.6183409",
"0.5971229",
"0.5923295",
"0.58287877",
"0.57894695",
"0.57524437",
"0.56865156",
"0.56339127",
"0.55662555",
"0.5546968",
"0.55356383",
"0.55251706",
"0.5411057",
"0.5369534",
"0.5272418",
"0.52036285",
"0.5199326",
"0.5199326",
"0.51... | 0.0 | -1 |
A s2121t NonRepairableRBD. Returns the {nodes, edges, reliabilities} dict, useful so k("v1") and k("v2") can be changed. | def rbd_koon_composite_args() -> dict:
edges = [
("s", "a1"),
("s", "a2"),
("a1", "v1"),
("a2", "v1"),
("v1", "b1"),
("v1", "b2"),
("b1", "v2"),
("b2", "v2"),
("v2", "t"),
]
reliabilities = {
"a1": FixedEventProbability.from_par... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rbd2_koon() -> NonRepairableRBD:\n edges = [(1, 2), (2, 3), (2, 4), (4, 7), (3, 5), (5, 6), (6, 7), (7, 8)]\n reliabilities = {\n 2: surv.Weibull.from_params([20, 2]),\n 3: surv.Weibull.from_params([100, 3]),\n 4: surv.Weibull.from_params([50, 20]),\n 5: surv.Weibull.from_para... | [
"0.6541109",
"0.62995857",
"0.6245844",
"0.6200806",
"0.5809427",
"0.57995814",
"0.5757092",
"0.57419133",
"0.5635102",
"0.56157184",
"0.5562107",
"0.5405884",
"0.53785056",
"0.5335042",
"0.5329623",
"0.5286221",
"0.518313",
"0.51592094",
"0.5080275",
"0.5080275",
"0.5011181"... | 0.44809136 | 86 |
NonRepairableRBD that can easily trap an algorithm into including a nonminimal pathset. | def rbd_koon_nonminimal_args() -> dict:
edges = [("s", 1), (1, 2), (2, "t"), (1, 3), (3, 4), (4, 5), (5, 2)]
reliabilities = {
1: FixedEventProbability.from_params(1 - 0.85),
2: FixedEventProbability.from_params(1 - 0.8),
3: FixedEventProbability.from_params(1 - 0.9),
4: FixedEve... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def findPathsToBase(A,bSize):\n M,N = A.shape\n pressedPaths = []\n\n #For every two nodes in the base find all paths between them\n for b1 in range(bSize):\n for b2 in range(bSize):\n #Remove all other base nodes from the graph so that\n #we only find paths that go through... | [
"0.5449761",
"0.52811486",
"0.5208564",
"0.5168064",
"0.5162988",
"0.51568395",
"0.5100747",
"0.5063701",
"0.5040022",
"0.5039273",
"0.5003334",
"0.4956348",
"0.493884",
"0.49005526",
"0.48649785",
"0.48636755",
"0.48515064",
"0.48509452",
"0.4834413",
"0.48296255",
"0.480976... | 0.0 | -1 |
NonRepairableRBD arguments that make for a 12121 NonRepairableRBD. | def rbd_double_parallel_args() -> dict:
edges = [
("s", 1),
("s", 2),
(1, 3),
(2, 3),
(3, 4),
(3, 5),
(4, "t"),
(5, "t"),
]
reliabilities = {
1: FixedEventProbability.from_params(1 - 0.85),
2: FixedEventProbability.from_params(1... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _fill_reserved(self) -> None:\n\n mpi_like_settings = [\n MpirunSettings,\n MpiexecSettings,\n OrterunSettings,\n PalsMpiexecSettings,\n ]\n for settings in mpi_like_settings:\n self._reserved_run_args[settings] = [\n \"... | [
"0.6048893",
"0.5647877",
"0.5194115",
"0.51527035",
"0.51167774",
"0.5028656",
"0.48770243",
"0.48340666",
"0.48278674",
"0.48270103",
"0.48165074",
"0.48086333",
"0.47527084",
"0.47426146",
"0.47352806",
"0.47196856",
"0.4709852",
"0.46833894",
"0.46754393",
"0.4664449",
"0... | 0.0 | -1 |
Compute the intersection area of a numpy array of boxes and a single box. | def intersection(boxes, box):
ix = np.maximum(0, np.minimum(box[2], boxes[:,2]) - np.maximum(box[0], boxes[:,0]))
iy = np.maximum(0, np.minimum(box[3], boxes[:,3]) - np.maximum(box[1], boxes[:,1]))
return ix*iy | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def compute_inters(box, boxes, box_area):\n # Calculate intersection areas\n y1 = np.maximum(box[0], boxes[:, 0])\n y2 = np.minimum(box[2], boxes[:, 2])\n x1 = np.maximum(box[1], boxes[:, 1])\n x2 = np.minimum(box[3], boxes[:, 3])\n return np.divide(np.maximum(x2 - x1, 0) * np.maximum(y2 - y1, 0)... | [
"0.7640445",
"0.73185265",
"0.7236327",
"0.7168402",
"0.7168402",
"0.7132642",
"0.7098993",
"0.70911914",
"0.7082353",
"0.70558786",
"0.696013",
"0.6940942",
"0.6880113",
"0.68699026",
"0.6814332",
"0.68049055",
"0.6767781",
"0.66969436",
"0.66479206",
"0.66479206",
"0.664419... | 0.78136355 | 0 |
Crop an image to a given area and transform target accordingly. | def crop(sample, crop_area, in_crop_threshold):
transformed_sample = {}
crop_area = np.array(crop_area)
bboxes = sample["bboxes"]
intersections = intersection(bboxes, crop_area)
bbox_areas = (bboxes[:,2:] - bboxes[:,:2]).prod(axis=1)
in_crop = (intersections/bbox_areas > in_crop_threshold)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def crop_image(input_image, output_image, start_x, start_y, width, height):\n box = (start_x, start_y, start_x + width, start_y + height)\n output_img = img.crop(box)\n output_img.save(output_image +\".png\")",
"def crop_to_target(x, target):\n\n if target.ndim==3:\n t_h, t_w = target.shape[1]... | [
"0.7249574",
"0.7102095",
"0.69499886",
"0.68971294",
"0.6881923",
"0.6724614",
"0.6645402",
"0.6645402",
"0.6605522",
"0.66024446",
"0.6594706",
"0.6582623",
"0.65712684",
"0.6554446",
"0.6519422",
"0.64856726",
"0.6482021",
"0.64787054",
"0.64579284",
"0.6450153",
"0.644404... | 0.5892808 | 57 |
Resize an image to given dimensions and transform the target accordingly. | def resize(sample, target_image_size, bbox_diag_threshold):
transformed_sample = {}
image = sample["image"]
scale_factors = np.array(target_image_size)/np.array(_size(image))
bboxes = sample["bboxes"]
bboxes = bboxes * np.tile(scale_factors, 2)
not_too_small = np.linalg.norm(bboxes[:,2:] - bbo... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def resize(image_path, target_dimensions, image_format):\n with Image.open(image_path) as img:\n img = img.resize(target_dimensions, resample=Image.LANCZOS)\n if image_format == 'PNG':\n img = img.convert('RGBA')\n else:\n img = img.convert('RGB')\n img.save(ima... | [
"0.73642147",
"0.7287396",
"0.72173774",
"0.71214217",
"0.7111653",
"0.7009032",
"0.69824106",
"0.6782985",
"0.6747425",
"0.67268914",
"0.66843146",
"0.66701424",
"0.66636115",
"0.6641147",
"0.6636635",
"0.6615918",
"0.66053194",
"0.65742534",
"0.6569193",
"0.65666544",
"0.65... | 0.0 | -1 |
ensures that the correct number of keys and values are emitted | def test_has_correct_number_of_keys_and_values(self):
self.has_correct_number_of_keys_and_values(2, 1) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_reduce(key, values):\n yield \"%s: %d\\n\" % (key, len(values))",
"def iter_values_len(self):\n for key, values in self.data.items():\n yield key, len(values)",
"def reduce_length(key, values):\n yield str((key, len(values)))",
"def reducer(key, vals):\n count = 0\n for p i... | [
"0.5706788",
"0.57027614",
"0.55487025",
"0.54131407",
"0.539261",
"0.53575903",
"0.5339979",
"0.5187678",
"0.5187663",
"0.5140506",
"0.5138147",
"0.5101639",
"0.5050154",
"0.50461453",
"0.50327146",
"0.50267106",
"0.50193614",
"0.4986483",
"0.49846265",
"0.49811524",
"0.4981... | 0.60382676 | 0 |
ensures that a line is emitted for each word in each file | def test_emits_line_for_each_word_in_each_file(self):
with open(self.default_fixture) as f:
output = self.run_mapper()
input = f.readlines()
num_files = len(input)
total_words = 0
for line in input:
total_words += len(line.strip().split... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def word_runner(self):\n with open(self.filename) as doc:\n text = doc.readlines()\n for line in text:\n for word in line.split():\n yield word",
"def word_iterator(folder):\n for filename in glob.glob(os.path.join(folder, \"*.txt\")):\n with codecs.op... | [
"0.6799167",
"0.6284839",
"0.61223036",
"0.60836124",
"0.60295254",
"0.5902215",
"0.5849417",
"0.5822456",
"0.57699835",
"0.57522106",
"0.569624",
"0.56763154",
"0.56692684",
"0.5667381",
"0.56594104",
"0.56553334",
"0.5640591",
"0.56372964",
"0.56246144",
"0.5605495",
"0.559... | 0.6906594 | 0 |
tests that 1 is appended to each line of output | def test_appends_one(self):
ends_with_one = '.*1$'
self.are_all_matches(re.compile(ends_with_one)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def outputStatus(self, line):\r\n for l in line.strip('\\r\\n').split('\\n'):\r\n self.output('%s: %s' % (ctime(), l), 0)",
"def out(value):\n output.append(value)\n return False",
"def flush_output():\n if len(buffered) == 1:\n code.add_line(\"append_result(%s)\" % b... | [
"0.61662585",
"0.59604585",
"0.57874274",
"0.5667662",
"0.56272227",
"0.56033826",
"0.5602316",
"0.5590414",
"0.5580968",
"0.5541745",
"0.55312794",
"0.5523322",
"0.55218935",
"0.54936326",
"0.54936326",
"0.54936326",
"0.54936326",
"0.54936326",
"0.54936326",
"0.54883444",
"0... | 0.525319 | 43 |
ensures that the correct number of keys and values are emitted | def test_has_correct_number_of_keys_and_values(self):
self.has_correct_number_of_keys_and_values(2, 1) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_reduce(key, values):\n yield \"%s: %d\\n\" % (key, len(values))",
"def iter_values_len(self):\n for key, values in self.data.items():\n yield key, len(values)",
"def reduce_length(key, values):\n yield str((key, len(values)))",
"def reducer(key, vals):\n count = 0\n for p i... | [
"0.5707167",
"0.5701873",
"0.55485255",
"0.5414439",
"0.5392383",
"0.53581417",
"0.5340053",
"0.51869917",
"0.5186937",
"0.51407546",
"0.5138803",
"0.51028943",
"0.5050025",
"0.5047798",
"0.5033274",
"0.5025732",
"0.5018922",
"0.49879548",
"0.49855825",
"0.49825802",
"0.49825... | 0.6038293 | 1 |
tests that each line is accounted for in the sum produced as output | def test_sum_of_output_equals_length_of_input(self):
output_total_sum = 0
for line in self.run_reducer_tokenize():
output_total_sum += int(line[1][0])
with open(self.default_fixture) as f:
input_len = len(f.readlines())
self.assertEqual(output_total_sum, input... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_expected_sum(inputs, expected):\n print(\"\\nRunning test_expected with {} as input and {} as expected output\".format(inputs, expected))\n assert inputs[0] + inputs[1] == expected",
"def test_sum(n, m, o, result):\n from series import sum_series\n assert sum_series(n, m, o) == result",
"d... | [
"0.6509527",
"0.61868066",
"0.61228985",
"0.59584236",
"0.59546816",
"0.5910473",
"0.59024125",
"0.58850664",
"0.5883609",
"0.5875183",
"0.585172",
"0.58443475",
"0.58325183",
"0.5818679",
"0.58184326",
"0.58069396",
"0.5782557",
"0.5773281",
"0.57656586",
"0.5758806",
"0.573... | 0.6357645 | 1 |
copies the current's object polygon to a new target_class | def copy_site_poly_view(request):
CLASSES = {
'Site': Site,
'ResearchEvent': ResearchEvent,
'ArchEnt': ArchEnt,
'MonumentProtection': MonumentProtection,
}
current_id = request.GET.get('current-id', '')
current_class = request.GET.get('current-class', '')
target_cla... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def deepcopy(self, exterior=None, label=None, **kwargs):\n return Polygon(\n exterior=np.copy(self.exterior) if exterior is None else exterior,\n label=self.label if label is None else label,\n **kwargs\n )",
"def copy(self):\n return type(self)(self._geojson... | [
"0.6006419",
"0.5972897",
"0.5870376",
"0.55767095",
"0.5563367",
"0.55278015",
"0.55184525",
"0.54930973",
"0.5431373",
"0.54146475",
"0.54030544",
"0.5359345",
"0.5356176",
"0.5337278",
"0.52976567",
"0.5295898",
"0.5295589",
"0.5265743",
"0.5262307",
"0.52414525",
"0.52370... | 0.57748646 | 3 |
General interactive prompt to guide the user through data collection. | def prompt():
# Inform the user on what price data has been taken
print("\nCurrent available historical data for calibration: ")
data_files = listdir('call_data/')
for i in range(len(data_files)):
print(data_files[i])
# Ask the user if they would like to sample more points
done = False
while done != True:
i... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_dataset_prompt():\n\n print(\"\")\n print(\"Let's start by choosing what features you'd like to look at/explore!\")",
"def do_prompt(self):\n # we need _something_ in the dictionary even if the user decides to use all defaults\n # otherwise for some unknown reason it won't work\n ... | [
"0.70390576",
"0.66458213",
"0.6361144",
"0.6237969",
"0.62158227",
"0.6172849",
"0.6152461",
"0.61271065",
"0.6122236",
"0.6117527",
"0.6057254",
"0.6041768",
"0.603955",
"0.60375905",
"0.5943918",
"0.5861413",
"0.5837267",
"0.5837267",
"0.58278203",
"0.5807767",
"0.5795216"... | 0.65522325 | 2 |
Allows the user to select which portfolios to analyze | def analyze():
# Analyze the available data
coins = ''
params = []
done = False
while done != True:
S_0_dat, K_dat, V_dat, T, coin = analysis.load()
theta, T = analysis.LM(S_0_dat, K_dat, V_dat, T)
params.append([theta, T, coin])
if coins == '':
coins = coin
else:
coins += ', ' + coin + '.'
try:... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def project_visibility_menu():\n projects = [i.split('.')[0] for i in os.listdir('HousingPriceScraper/HousingPriceScraper/spiders/SpiderGroups')[:-1]]\n print('Available projects are:\\n')\n for project in enumerate(projects):\n print('\\t{} - {}'.format(project[0], project[1]))\n print('\\t{} -... | [
"0.56866527",
"0.56662923",
"0.54835486",
"0.5365236",
"0.530161",
"0.5246109",
"0.5241945",
"0.5217639",
"0.52151227",
"0.5170465",
"0.515381",
"0.5141848",
"0.5120152",
"0.5090627",
"0.5072182",
"0.50395954",
"0.5031503",
"0.50193703",
"0.50174224",
"0.4972539",
"0.49604633... | 0.0 | -1 |
Simple script for obaining the amount desired to invest | def invest():
done = False
while done != True:
inp = input("\nInitial investment into Crypto market: ")
try:
S_0 = float(inp)
done = True
except Exception:
print("Unable to convert to suitable format. Please try again.")
return S_0 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def deposit(amt) :\r\n\tglobal bal\r\n\tbal_in = bal\r\n\t#PREMISES FOR NEXT LINE: \r\n\t# (amt >= 0)\r\n\t# (bal >= 0)\r\n\t# (bal == bal_in)\r\n\tbal = bal + amt\r\n\t#PREMISES FOR ATTACHED PROOF, IF ANY: \r\n\t# (bal == (bal_old + amt))\r\n\t# (amt >= 0)\r\n\t# (bal_old >= 0)\r\n\t# (bal_old == bal_in)\r\n\t#PR... | [
"0.6801968",
"0.6597183",
"0.6584977",
"0.63846654",
"0.6377838",
"0.63749546",
"0.6327555",
"0.629521",
"0.6278848",
"0.62471265",
"0.6238845",
"0.6189341",
"0.6188443",
"0.6178253",
"0.6167095",
"0.6157759",
"0.6147748",
"0.614369",
"0.6135853",
"0.6080904",
"0.6078427",
... | 0.5987601 | 35 |
This script analyzes possible portfolios based on the calculated parameters on the observed data, and the user inputted investment. | def generate_portfolio(S_0, params):
public_client = gdax.PublicClient()
allvar = []
sumvar = 0
for coin in params:
theta = coin[0]
v = theta[0]
T = coin[1]
prod_id = coin[2]
# Get the current value of the coin, i.e. how much you bought
name = prod_id + '-USD'
stats = public_client.get_product_24hr_st... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def before_trading_start(context, data):\n factors = pipeline_output('ff_example')\n\n # get the data we're going to use\n returns = factors['returns']\n mkt_cap = factors.sort_values(['market_cap'], ascending=True)\n be_me = factors.sort_values(['be_me'], ascending=True)\n\n # to compose the six... | [
"0.6095031",
"0.5822337",
"0.58005035",
"0.5798782",
"0.5752552",
"0.57133955",
"0.5679745",
"0.56412446",
"0.5630844",
"0.5596643",
"0.5596643",
"0.5586385",
"0.55733144",
"0.55497605",
"0.55235076",
"0.54996634",
"0.54918146",
"0.5452439",
"0.54508233",
"0.54480547",
"0.537... | 0.5986981 | 1 |
Convert the character in the [ ] for a task into a TaskStatus | def _get_status_from_char(char: str) -> TaskStatus:
if char == "c":
return TaskStatus.CANCELED
elif char == "b":
return TaskStatus.BLOCKED
elif char == " ":
return TaskStatus.UNSCHEDULED
elif char == "x":
return TaskStatus.DONE
elif char == "?":
return TaskSta... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def task_status():\n pass",
"def task_status(self) -> str:\n return self._task_status",
"async def get_task_status(task_id: TaskId):",
"def fuota_task_status(self) -> Optional[str]:\n return pulumi.get(self, \"fuota_task_status\")",
"def _parse_status(self, status):\n if status in (... | [
"0.6113151",
"0.60610837",
"0.5982466",
"0.58361703",
"0.5676092",
"0.562448",
"0.5620659",
"0.5590581",
"0.5534794",
"0.5493304",
"0.5449712",
"0.5449053",
"0.5443019",
"0.54307556",
"0.54105866",
"0.53677195",
"0.5367107",
"0.53506756",
"0.53475046",
"0.5340073",
"0.5264325... | 0.7188169 | 0 |
Slices a panel once at an angle into two new panels | def single_slice_panels(page,
horizontal_vertical=None,
type_choice=None,
skew_side=None,
number_to_slice=0
):
# Remove panels which are too small
relevant_panels = []
if len(page.childre... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _slice_at_axis(sl, axis):\n return (slice(None),) * axis + (sl,) + (...,)",
"def animate_slices_multi(field='uu1', datadir1='data/', datadir2='data/', proc=-1, extension='xz',\n format='native', tmin=0., tmax=1.e38, wait=0.,\n amin=0., amax=1., transform='', oldfile=Fal... | [
"0.57020974",
"0.5570688",
"0.5558747",
"0.545153",
"0.5445056",
"0.543105",
"0.535599",
"0.5348452",
"0.5087993",
"0.50807226",
"0.50238377",
"0.50055045",
"0.5003114",
"0.49961782",
"0.49961782",
"0.49851263",
"0.49696037",
"0.49594927",
"0.49540603",
"0.49380317",
"0.49127... | 0.63570553 | 0 |
This function move panel boundaries to transform them into trapezoids and rhombuses | def box_transform_panels(page, type_choice=None, pattern=None):
if type_choice is None:
type_choice_prob = np.random.random()
if type_choice_prob < cfg.panel_box_trapezoid_ratio:
type_choice = "trapezoid"
else:
type_choice = "rhombus"
if type_choice == "trapezoi... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def adjust_mario_position(self):\n self.last_x_position = self.mario.rect.right\n self.mario.rect.x += round(self.mario.x_vel)\n self.check_mario_x_collisions()\n\n if self.mario.in_transition_state == False:\n self.mario.rect.y += round(self.mario.y_vel)\n self.check_mario_y_collisions()... | [
"0.6025496",
"0.5948489",
"0.58940256",
"0.5790465",
"0.5725575",
"0.56771463",
"0.5674935",
"0.567056",
"0.5657837",
"0.56499887",
"0.56087935",
"0.55989015",
"0.5590386",
"0.55410814",
"0.55279523",
"0.54960006",
"0.54941237",
"0.54902667",
"0.54861367",
"0.5482337",
"0.548... | 0.5458356 | 21 |
This function takes all the first child panels of a page and moves them to form a zigzag or a rhombus pattern | def box_transform_page(page, direction_list=[]):
if len(page.children) > 1:
# For all children of the page
for idx in range(0, len(page.children)-1):
# Take two children at a time
p1 = page.get_child(idx)
p2 = page.get_child(idx+1)
change_proportio... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def box_transform_panels(page, type_choice=None, pattern=None):\n\n if type_choice is None:\n type_choice_prob = np.random.random()\n if type_choice_prob < cfg.panel_box_trapezoid_ratio:\n type_choice = \"trapezoid\"\n else:\n type_choice = \"rhombus\"\n\n if type_c... | [
"0.6271615",
"0.54973686",
"0.5387132",
"0.5235147",
"0.52252686",
"0.5174454",
"0.5173184",
"0.5033678",
"0.5033185",
"0.5014299",
"0.5011081",
"0.50006324",
"0.49946687",
"0.49603772",
"0.49424213",
"0.49365565",
"0.49298054",
"0.49220905",
"0.49138784",
"0.48819068",
"0.48... | 0.62816256 | 0 |
Adds panel boundary transformations to the page | def add_transforms(page):
# Transform types
# Allow choosing multiple
transform_choice = ["slice", "box"]
# Slicing panels into multiple panels
# Works best with large panels
if "slice" in transform_choice:
page = single_slice_panels(page)
# Makes v cuts happen more often 1/4 ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_main_panel(self):\n self.panel = wx.Panel(self)\n\n self.init_plot()\n self.canvas = FigCanvas(self.panel, -1, self.fig)\n\n self.control_box = VSControlBox(self.panel, -1, 'Information board')\n\n self.vbox = wx.BoxSizer(wx.VERTICAL)\n self.vbox.Add(self.canvas... | [
"0.5654674",
"0.55271375",
"0.5385923",
"0.5355535",
"0.53435576",
"0.53429335",
"0.5328772",
"0.52715266",
"0.5230099",
"0.52209806",
"0.5134633",
"0.50963074",
"0.50835866",
"0.506619",
"0.5044313",
"0.50324744",
"0.5028184",
"0.5028184",
"0.5023393",
"0.500031",
"0.4988787... | 0.605634 | 0 |
Convert a package (as found by setuptools.find_packages) e.g. "foo.bar" to usable path e.g. "foo/bar" No idea if this works on windows | def package_to_path(package):
return package.replace('.','/') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_package_path():\n package_name = get_package_name()\n return package_name.replace('.', '/')",
"def get_packages_path_from_package(package):\n root = finder.get_package_root(package)\n\n if is_built_package(package):\n package_name_folder = os.path.dirname(root)\n\n return os.pat... | [
"0.7921618",
"0.7368294",
"0.7326123",
"0.70896804",
"0.70801365",
"0.6791065",
"0.6757227",
"0.67504627",
"0.6700731",
"0.66353977",
"0.66276276",
"0.6621615",
"0.6564424",
"0.6564424",
"0.65590894",
"0.6505718",
"0.63585734",
"0.6354153",
"0.62997335",
"0.6271722",
"0.62491... | 0.8622001 | 0 |
Get the subdirectories within a package This will include resources (nonsubmodules) and submodules | def find_subdirectories(package):
try:
subdirectories = next(os.walk(package_to_path(package)))[1]
except StopIteration:
subdirectories = []
return subdirectories | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def walk_package(pkgname, root):\n dirs = []\n files = []\n for name in pkg_resources.resource_listdir(pkgname, str(root)):\n fullname = root / name\n if pkg_resources.resource_isdir(pkgname, str(fullname)):\n dirs.append(fullname)\n else:\n files.append(Path(nam... | [
"0.7408176",
"0.6981932",
"0.6977739",
"0.69128346",
"0.6908319",
"0.6908319",
"0.6908319",
"0.68290293",
"0.67712396",
"0.6679647",
"0.6656998",
"0.6650802",
"0.66113985",
"0.65714127",
"0.65617687",
"0.6516385",
"0.65129155",
"0.65035087",
"0.6490898",
"0.64712936",
"0.6428... | 0.7587221 | 0 |
Find all files in a subdirectory and return paths relative to dir This is similar to (and uses) setuptools.findall However, the paths returned are in the form needed for package_data | def subdir_findall(dir, subdir):
strip_n = len(dir.split('/'))
path = '/'.join((dir, subdir))
return ['/'.join(s.split('/')[strip_n:]) for s in setuptools.findall(path)] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _find_files_to_package(self, path):\n for root, dirs, files in os.walk(path):\n root_parts = pathlib.Path(root).relative_to(path).parts\n if self._include_directory(root_parts):\n for f in files:\n if self._include_file(root_parts, f):\n ... | [
"0.7423802",
"0.73017514",
"0.72350556",
"0.7135453",
"0.7109446",
"0.7099377",
"0.7064924",
"0.70476",
"0.70066994",
"0.6970505",
"0.6923695",
"0.6891978",
"0.6889596",
"0.6840696",
"0.6823787",
"0.6811101",
"0.68091035",
"0.6807877",
"0.68076265",
"0.6768948",
"0.67390597",... | 0.7272002 | 2 |
For a list of packages, find the package_data This function scans the subdirectories of a package and considers all nonsubmodule subdirectories as resources, including them in the package_data Returns a dictionary suitable for setup(package_data=) | def find_package_data(packages):
package_data = {}
for package in packages:
package_data[package] = []
for subdir in find_subdirectories(package):
if '.'.join((package, subdir)) in packages: # skip submodules
logging.debug("skipping submodule %s/%s" % (package, subdir... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_package_data(package):\n walk = [(dirpath.replace(package + os.sep, '', 1), filenames)\n for dirpath, dirnames, filenames in os.walk(package)\n if not os.path.exists(os.path.join(dirpath, '__init__.py'))]\n\n filepaths = []\n for base, filenames in walk:\n filepaths.ex... | [
"0.74882954",
"0.7475205",
"0.7218244",
"0.7056486",
"0.68890065",
"0.68552727",
"0.66472167",
"0.6606134",
"0.6553142",
"0.6551368",
"0.6509173",
"0.62634075",
"0.6203264",
"0.6189386",
"0.61807597",
"0.6176723",
"0.61635065",
"0.6163499",
"0.6126401",
"0.6013186",
"0.601318... | 0.76023054 | 0 |
r"""Compute the fixed point as described in the paper by Botev et al. | def _fixed_point(t, N, squared_integers, grid_data_dct2):
# ell = 7 corresponds to the 5 steps recommended in the paper
ell = tf.constant(7, ztypes.float)
# Fast evaluation of |f^l|^2 using the DCT, see Plancherel theorem
f = (
tf.constant(0.5, ztypes.float)
* tf.math.pow(
t... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fixed_point(is_zero, plus, minus, f, x):\n\n @memo_Y\n def _fixed_point(fixed_point_fun):\n def __fixed_point(collected, new):\n diff = minus(new, collected)\n if is_zero(diff):\n return collected\n return fixed_point_fun(plus(collected, diff), f(dif... | [
"0.7288447",
"0.63831216",
"0.6331708",
"0.6310987",
"0.62785643",
"0.6213673",
"0.6211178",
"0.61968625",
"0.6118697",
"0.6110409",
"0.6091076",
"0.6086669",
"0.59297514",
"0.5889126",
"0.5873738",
"0.58619815",
"0.5842633",
"0.5819706",
"0.5756298",
"0.5717596",
"0.5702371"... | 0.56695026 | 25 |
Root finding algorithm. Based on MATLAB implementation by Botev et al. >>> From the matlab code >>> ints = np.arange(1, 51) >>> ans = _root(_fixed_point, N=50, args=(50, ints, ints)) >>> np.allclose(ans, 9.237610787616029e05) True | def _find_root(function, N, squared_integers, grid_data_dct2):
# From the implementation by Botev, the original paper author
# Rule of thumb of obtaining a feasible solution
N2 = tf.math.maximum(
tf.math.minimum(tf.constant(1050, ztypes.float), N),
tf.constant(50, ztypes.float),
)
t... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def find_root(function, point_a, point_b, step, tol, max_iterations, \n show_process = False):\n left_point , right_point = search_interval_3d(function, point_a, point_b, \n step, tol, max_iterations,\n ... | [
"0.73860395",
"0.70872056",
"0.6967801",
"0.69340694",
"0.69075763",
"0.68714964",
"0.6838874",
"0.6783198",
"0.67171526",
"0.6622454",
"0.6563255",
"0.65425867",
"0.64857024",
"0.64850307",
"0.64433384",
"0.64288294",
"0.6416696",
"0.64105165",
"0.64094615",
"0.6380394",
"0.... | 0.65467143 | 11 |
Generate the save path for an image. If a modifier string is provided, this is added between the existing name and the extension. e.g. fname="moon.jpeg" modstirng="cropped" > "moon_cropped.jpeg". This is then joined with the output directory. If no modiifer, just returns joined path of outdir and fname. | def genSavePath(outdir, fname, modstring=None):
if modstring:
base,ext = os.path.splitext(fname)
fname = f"{base}_{modstring}.{ext}"
writepath = os.path.join(outdir, fname)
return writepath | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def output_filename(self, modifier):\n fs = self._filesystem\n output_filename = fs.join(self._root_output_dir, self._test_name)\n return fs.splitext(output_filename)[0] + modifier",
"def name_final_path(out_img_folder):\n if out_img_folder == None:\n return \"./.out_hidden_images\... | [
"0.6506808",
"0.61701065",
"0.5883275",
"0.5868304",
"0.5847001",
"0.5811345",
"0.5766814",
"0.5759355",
"0.57464373",
"0.57153183",
"0.5675875",
"0.5666476",
"0.5665445",
"0.5655566",
"0.56509286",
"0.5640137",
"0.562522",
"0.55997884",
"0.55983824",
"0.5587275",
"0.55767787... | 0.731317 | 0 |
Convert image to a regular baseline JPEG. Quality option is ignored if useexistingqtables=True. | def savebaselineJPEG(image, fname, outpath, optimize=True, quality=75, recompressed=False, useexistingqtables=False, preserve_name=False):
if not preserve_name:
if recompressed:
fpath = genSavePath(outpath, fname, modstring=f"recompressed_q{quality}")
else:
fpath = genSavePa... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def convert_to_jpeg(image, quality=90):\n\n\t# Load the image into a new BytesIO\n\tsImg = BytesIO(image)\n\n\t# Create an empty BytesIO for the new image\n\tsNewImg = BytesIO(b'')\n\n\t# Create a new Pillow instance from the raw data\n\toImg = Pillow.open(sImg)\n\n\t# If the mode is not valid\n\tif oImg.mode not ... | [
"0.54743165",
"0.54736084",
"0.5438891",
"0.54282427",
"0.541862",
"0.53912777",
"0.53576815",
"0.52602875",
"0.5242374",
"0.52363783",
"0.52289176",
"0.521572",
"0.5162085",
"0.51128095",
"0.51099354",
"0.5074247",
"0.50239307",
"0.5019632",
"0.5016915",
"0.5016185",
"0.4993... | 0.7245555 | 0 |
Save a rotated version of theimage. | def saverotation(image, fname, outpath, degreescounterlockwise=90, preserve_name=False):
if not preserve_name:
fpath = genSavePath(outpath, fname, modstring=f"rotated_{degreescounterlockwise}")
else:
fpath = genSavePath(outpath, fname)
im = copy(image)
im = im.rotate(degreescounterlockwi... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rotate(image_path):\n try:\n with Image.open(image_path) as img:\n img = ImageOps.exif_transpose(img)\n img.save(image_path, format=img.format, quality=95)\n except Exception as e:\n log.warn(f'Cannot rotate input image: [{e}]')",
"def apply_rotation(image):\n\n\t# L... | [
"0.70346487",
"0.68889385",
"0.682253",
"0.6747778",
"0.6635483",
"0.6627623",
"0.6563121",
"0.6496392",
"0.6405352",
"0.63929117",
"0.63382024",
"0.6252712",
"0.61955154",
"0.61868703",
"0.61305135",
"0.6124323",
"0.61061513",
"0.60409236",
"0.60030663",
"0.5996765",
"0.5981... | 0.7409973 | 0 |
Save a scaled copy of the image, uses a single scale factor for both x,y axes to maintain aspect ratio | def saverescale(image, fname, outpath, scalefactor=0.5, preserve_name=False):
if not preserve_name:
fpath = genSavePath(outpath, fname, modstring=f"resize_{scalefactor}")
else:
fpath = genSavePath(outpath, fname)
newsize = (int(image.width * scalefactor), int(image.height * scalefactor))
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exportImg(self):\n if self.superSampling:\n print(\"Exporting with size adjusted\")\n self.img = self.img.resize((int(self.width/2),int(self.height/2)),Image.NEAREST)\n self.img.save(self.fileName,\"PNG\")",
"def save_image_with_scale(path, variable):\n\n arr = variable... | [
"0.7007898",
"0.69334567",
"0.6804052",
"0.6749671",
"0.6498489",
"0.64127666",
"0.63798004",
"0.6349806",
"0.6243057",
"0.62239367",
"0.61422914",
"0.6138981",
"0.61325663",
"0.61003655",
"0.61003655",
"0.6086245",
"0.60752183",
"0.6060752",
"0.6048594",
"0.60214186",
"0.600... | 0.6704548 | 4 |
Save a thumbnail of the image, preserves aspect ratio, so longest side will be of size[max(x,y)] | def savethumb(image, fname, outpath, size=(128,128), preserve_name=False):
if not preserve_name:
fpath = genSavePath(outpath, fname, modstring=f"thumbnail_{size[0]}_{size[1]}")
else:
fpath = genSavePath(outpath, fname)
im = copy(image)
im.thumbnail(size)
try:
im.save(fpath, s... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_thumbnail(filepath):\n img = Image.open(filepath)\n thumb = None\n w, h = img.size\n\n # if it is exactly 128x128, do nothing\n if w == 128 and h == 128:\n return True\n\n # if the width and height are equal, scale down\n if w == h:\n thumb = img.resize((128, 128), Image... | [
"0.6931515",
"0.68739617",
"0.68509567",
"0.68389434",
"0.6793269",
"0.6591011",
"0.6537345",
"0.6449486",
"0.6414779",
"0.6377539",
"0.6353064",
"0.63198406",
"0.6311073",
"0.6295751",
"0.6291895",
"0.6244799",
"0.6227591",
"0.6221736",
"0.6218256",
"0.62178695",
"0.6205242"... | 0.7045417 | 0 |
Save a cropped version of the image. | def savecrop(image, fname, outpath, cropabsolute=None, cropfactors=[0.2, 0.2, 0.2, 0.2], preserve_name=False):
if cropabsolute:
if type(cropabsolute) != list:
raise Exception("cropabsolute must be a list of length 4.")
else:
if len(cropabsolute) !=4:
raise Exc... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Save_Image_Crop(img, x, y, width, height, filename = None, path = 'Predictions'):\n img = img[y:y+height, x:x+width,:]\n\n if filename is not None:\n try: \n os.mkdir(path)\n except OSError as error: \n print('') \n fig, ax = plt.subplots(figsize=(18, 20))\n ... | [
"0.7306745",
"0.69884664",
"0.6980087",
"0.6949157",
"0.687741",
"0.6825131",
"0.6791875",
"0.66822034",
"0.66574806",
"0.66544116",
"0.66482884",
"0.66326034",
"0.65988314",
"0.6507213",
"0.6493506",
"0.6481142",
"0.6444658",
"0.63948953",
"0.6392374",
"0.63720816",
"0.63054... | 0.70799524 | 1 |
Flip the image on the x or y axis | def saveflip(image, fname, outpath, axis='x', preserve_name=False):
if not preserve_name:
fpath = genSavePath(outpath, fname, modstring=f"mirror_{axis}")
else:
fpath = genSavePath(outpath, fname)
im = copy(image)
if axis == 'x':
im = im.transpose(Image.FLIP_LEFT_RIGHT)
elif a... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def flip_image(img, vert=True):\n if vert:\n return img.transpose(Image.FLIP_TOP_BOTTOM)\n else:\n return img.transpose(Image.FLIP_LEFT_RIGHT)",
"def vflip(img):\n #if not _is_pil_image(img):\n # raise TypeError('img should be PIL Image. Got {}'.format(type(img)))\n\n return img.t... | [
"0.76031363",
"0.75496536",
"0.75196064",
"0.751224",
"0.7474454",
"0.7395922",
"0.7393975",
"0.73869336",
"0.7386315",
"0.7383523",
"0.7346391",
"0.73111284",
"0.72888714",
"0.7244896",
"0.72281134",
"0.7200845",
"0.7131485",
"0.7130178",
"0.7129639",
"0.71281487",
"0.712679... | 0.71528536 | 16 |
Save a watermarked version of the image. resize watermark to 10% of the image height, with a minimum height of 40 | def savewatermarked(image, fname, outpath, watermark, preserve_name=False):
im = image.copy()
if not preserve_name:
fpath = genSavePath(outpath, fname, modstring=f"watermarked")
else:
fpath = genSavePath(outpath, fname)
targetheight = int(image.height / 10)
waterwidthscaler = wa... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_watermark(self, image, watermark, position='scale', opacity=1, format=None):",
"def watermark(im, credits, opacity=1):\n # First resize mark to make it appropriate size\n logoURL = 'https://s3.amazonaws.com/static.thecrimson.com' + \\\n '/images/feature/thc-logo-large.png'\n imfile = Stri... | [
"0.7318583",
"0.6755734",
"0.66474384",
"0.6608156",
"0.6311425",
"0.5929534",
"0.5910654",
"0.58472747",
"0.58287114",
"0.58228457",
"0.5805072",
"0.56639534",
"0.5578972",
"0.55572283",
"0.5513554",
"0.5510311",
"0.55005735",
"0.5479865",
"0.5456375",
"0.5421586",
"0.541545... | 0.78452754 | 0 |
Perform colour enhancements to the image. | def saveenhanced(image, fname, outpath, colourfactor=1, brightnessfactor=1, contrastfactor=1, sharpnessfactor=1, preserve_name=False):
estring = "col{}br{}con{}sh{}".format(colourfactor, brightnessfactor, contrastfactor, sharpnessfactor)
if not preserve_name:
fpath = genSavePath(outpath, fname, modstri... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __enhance_image(self, img):\n\n blue = self.g.clahe.apply(img[:,:,0])\n green = self.g.clahe.apply(img[:,:,1])\n red = self.g.clahe.apply(img[:,:,2])\n img[:,:,0] = blue\n img[:,:,1] = green\n img[:,:,2] = red\n return img",
"def _adjust_color_img(self, result... | [
"0.79571605",
"0.67238367",
"0.6699741",
"0.66279745",
"0.66164297",
"0.6579595",
"0.65684307",
"0.64621973",
"0.63937193",
"0.63469017",
"0.63373184",
"0.63109785",
"0.6228176",
"0.61978406",
"0.61928",
"0.61690545",
"0.61679554",
"0.6136985",
"0.6136281",
"0.6107434",
"0.60... | 0.0 | -1 |
Save a version of the file with an added border, controlled by the colour and width parameters. | def saveborder(image, fname, outpath, width=20, colour="black", preserve_name=False):
im = image.copy()
if not preserve_name:
fpath = genSavePath(outpath, fname, modstring=f"border{width}{colour}")
else:
fpath = genSavePath(outpath, fname)
im = ImageOps.expand(im, border=width, fill=col... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save_visualization_to_file(self, file_name, length = 90):\n session = self.capture_last(length)\n visualizer.animate(session , 0, length, name = file_name, min_x = -1, max_x = 1, min_y = -1, max_y = 1, show = False )",
"def write(self, file_name, width=1500.0, height=1000.0):\n with ope... | [
"0.5784574",
"0.56733894",
"0.5626295",
"0.5541043",
"0.5428487",
"0.5386171",
"0.5383418",
"0.53502595",
"0.5343739",
"0.5342087",
"0.5294229",
"0.5275449",
"0.52629405",
"0.5256234",
"0.5255994",
"0.52103263",
"0.5183001",
"0.5153634",
"0.51445657",
"0.5137024",
"0.51188093... | 0.72179383 | 0 |
Save a simulated fragmented file version of the file. Trunfactor specifies how much of the data, sequentially from the start of file, should be written to the new file. | def savefragment(filepath, fname, outpath, truncfactor=0.5, preserve_name=False):
# Read data
infile = open(filepath, 'rb')
data = infile.read()
infile.close()
# Write truncated filepath
if not preserve_name:
fpath = genSavePath(outpath, fname, modstring=f"truncated{truncfactor}")
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def write_data(infbfile,begin_N,dur_N,outfbfile):\n infbfile.seek_to_sample(begin_N)\n for i in range(begin_N,(begin_N+dur_N)):\n data = infbfile.read_sample()\n data.tofile(outfbfile)",
"def save(self, fname):\n lh_data = self.data[:len(self.lh_vertno)]\n rh_data = self.data[-l... | [
"0.53168994",
"0.52053297",
"0.50609237",
"0.5041503",
"0.5023959",
"0.49947497",
"0.49635452",
"0.495652",
"0.49504188",
"0.49476227",
"0.494738",
"0.49422064",
"0.49133167",
"0.4913253",
"0.49015784",
"0.48993456",
"0.48802665",
"0.48687673",
"0.4865208",
"0.48493338",
"0.4... | 0.62867725 | 0 |
Detects Xepr instances which are waiting for connections from XeprAPI clients. For this to work, the API has to be enabled in Xepr (menu "Processing" > submenu "XeprAPI" > menu item "Enable Xepr API"). Xepr instances which already are connected to an XeprAPI client are not listed. | def getXeprInstances():
apilib = _loadapilib()
instances = _findInst(apilib)
return dict([(p, t) for p, t in instances]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _wait_active(client, request_id, max_num):\n logging.info('Waiting for instances to be active')\n while True:\n res = client.describe_spot_fleet_instances(SpotFleetRequestId=request_id)\n if len(res['ActiveInstances']) == max_num:\n logging.info('Instances are active now.')\n ... | [
"0.6325874",
"0.57466775",
"0.55821526",
"0.5577072",
"0.54760903",
"0.54682326",
"0.543734",
"0.5412187",
"0.5394259",
"0.53219014",
"0.5313654",
"0.52691233",
"0.5248033",
"0.5224936",
"0.52046394",
"0.5202071",
"0.52012694",
"0.5174187",
"0.51666844",
"0.51602364",
"0.5159... | 0.6125134 | 1 |
Creates Experiment object to create a new experiment or to access an experiment already set up by the operator of the Xepr application. | def XeprExperiment(self, *p, **k):
# noinspection PyTypeChecker
return Experiment(self, *p, **k) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_experiment_if_needed(tr):\n exp = tr.getExperiment(EXPERIMENT_ID)\n if None == exp:\n create_project_if_needed(tr)\n exp = tr.createNewExperiment(EXPERIMENT_ID, 'DEFAULT_EXPERIMENT')\n \n return exp",
"def create_experiment(self):\n experiment = wandb.init(\n name=self._n... | [
"0.7578074",
"0.7373269",
"0.72146213",
"0.7015423",
"0.69071597",
"0.6736371",
"0.65408194",
"0.64728445",
"0.64639014",
"0.6389977",
"0.63315874",
"0.62304384",
"0.622714",
"0.61377406",
"0.6132721",
"0.6109624",
"0.6044673",
"0.59917486",
"0.5942433",
"0.5940935",
"0.59142... | 0.7045335 | 3 |
Closes the API and tells Xepr to shut down its API support as well. After that, the API support of Xepr has to be re enabled manually by the Xepr operator (menu "Processing" > submenu "XeprAPI" > menu item "Enable Xepr API") to be able to establish the Xepr API again. | def XeprClose(self):
with self._lock:
for func in self._dynamicmethods:
delattr(self, func)
self._dynamicmethods = []
self._printmsg('Closing API...', newline=False)
if self._API.XeprDisableAPI(1) == SUCCESS:
self._printmsg('done.... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def close(self):\n self.__aceQLHttpApi.close()",
"def _close(self):\n log.Debug('dpbx.close():')",
"def close(self):\n self.controller.DisableDevice()\n self.controller.StopPolling()\n self.controller.Disconnect(False)",
"def close(self):\n if self.dev_open:\n ... | [
"0.6518419",
"0.6297029",
"0.6261232",
"0.6248867",
"0.61627144",
"0.6101848",
"0.6072765",
"0.60054755",
"0.6004206",
"0.6000544",
"0.5971086",
"0.5967516",
"0.59390146",
"0.593771",
"0.5916162",
"0.59158105",
"0.59158105",
"0.590212",
"0.5895577",
"0.5895577",
"0.5895577",
... | 0.83324784 | 0 |
Refreshes the Xepr GUI. | def XeprGUIrefresh(self):
with self._lock:
self._API.XeprRefreshGUI() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def refresh(self):\n\t\tself.win.refresh()\n\t\tfor c in self.components:\n\t\t\tc.refresh()",
"def refresh_dialog(self):\n self._client.update_elements()",
"def refresh(self):\n self.Refresh()",
"def Refresh(self):\n pass",
"def refresh(self):\n self.__refresh()",
"def refresh(... | [
"0.7118413",
"0.6885529",
"0.6867989",
"0.66451275",
"0.65044814",
"0.6423347",
"0.6417798",
"0.6398829",
"0.63724816",
"0.6371857",
"0.63682497",
"0.6328148",
"0.63234603",
"0.63234603",
"0.6223904",
"0.62109405",
"0.6206273",
"0.6206273",
"0.6206273",
"0.6157153",
"0.609169... | 0.85330975 | 0 |
Check whether dataset is available. | def datasetAvailable(self):
dset = None
try:
dset = self._getcopy()
except Exception:
pass
if dset is not None:
self._parent.destroyDset(dset)
return True
return False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def data_available(dataset_name=None):\r\n for file_list in data_resources[dataset_name]['files']:\r\n for file in file_list:\r\n if not os.path.exists(os.path.join(data_path, dataset_name, file)):\r\n return False\r\n return True",
"def check_dataset_exists(dataset):\n ... | [
"0.7826292",
"0.7441684",
"0.72973037",
"0.7230916",
"0.7226951",
"0.70393974",
"0.7030351",
"0.70008165",
"0.6950723",
"0.6928618",
"0.6912717",
"0.69047856",
"0.683975",
"0.6828007",
"0.67924714",
"0.667985",
"0.6654125",
"0.6600955",
"0.6577739",
"0.6553427",
"0.6533301",
... | 0.78361577 | 0 |
Get the list of functional units for the experiment. | def getFuList(self):
if self._fupardict:
return self._fupardict.keys()
buf = self._parent.Xeprbuf(10000)
self.aqGetExpFuList(buf, 10000)
return buf.get_unicode_str().split(',') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_units(self) -> List[str]:\n result = []\n for elements in self._get_results_list():\n result.append(elements[3])\n return result",
"def getListOfUnits(self, *args):\n return _libsbml.UnitDefinition_getListOfUnits(self, *args)",
"def client_units(self) -> List[Flyi... | [
"0.7093225",
"0.65067303",
"0.6453618",
"0.6437445",
"0.6428049",
"0.63517296",
"0.6145797",
"0.60083926",
"0.59385496",
"0.59025174",
"0.5840358",
"0.5831512",
"0.5831512",
"0.58269817",
"0.58130693",
"0.5776839",
"0.57549787",
"0.57283396",
"0.5718893",
"0.5671003",
"0.5671... | 0.5055429 | 91 |
Get the list of paramater names for the functional unit funame. | def getFuParList(self, funame):
if not self._fupardict:
buf = self._parent.Xeprbuf(10000)
for fu in self.getFuList():
self.aqGetExpFuParList(fu, buf, 10000)
parlist = [x for x in buf.get_unicode_str().split(',') if self.aqGetParType('%s.%s' % (fu, x)) != s... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def parameter_names(self) -> List[str]:",
"def parameterNames(self, p_int): # real signature unknown; restored from __doc__\n return []",
"def get_param_names(hf):\n parameters = get_params(hf)\n return [p.name for p in parameters]",
"def get_str_param_names(self):\n # Exclude self.api an... | [
"0.7988936",
"0.74989027",
"0.7314254",
"0.7287591",
"0.72515583",
"0.7218516",
"0.71054345",
"0.70339245",
"0.7012955",
"0.6996692",
"0.6981282",
"0.6979131",
"0.69392234",
"0.68479455",
"0.68444264",
"0.6826156",
"0.6822841",
"0.6799787",
"0.67326",
"0.6730319",
"0.6724998"... | 0.61655676 | 60 |
Finds the fully qualified parameter name for the name given by param | def findParam(self, param, findall=False):
param = param.replace('*', '').strip()
if not param:
if not findall:
return
return []
if param in self._fuparhist and not findall:
return self._fuparhist[param]
p = param.split('.')
if ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def param_name(p):\n prefix = ['limit_', 'error_', 'fix_']\n for prf in prefix:\n if p.startswith(prf):\n return p[len(prf):]\n return p",
"def get_param_name(self, param_id, syselem):\n\n with self.__connection.cursor() as cursor:\n query = \"SELECT NAME FROM %s WHER... | [
"0.7109423",
"0.6902756",
"0.6839676",
"0.68305796",
"0.68224156",
"0.68224156",
"0.68224156",
"0.68224156",
"0.68224156",
"0.6680651",
"0.6656476",
"0.6656476",
"0.66398823",
"0.66398823",
"0.66398823",
"0.6597125",
"0.6567056",
"0.65526336",
"0.65026873",
"0.6357738",
"0.62... | 0.66429484 | 12 |
Get the name of the experiment. | def aqGetExpName(self):
return self._expname | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def experiment_name(self):\n # type: () -> string_types\n return self._experiment_name",
"def get_name() -> str:\n pass",
"def get_name() -> str:",
"def name(self) -> pulumi.Output[str]:\n return pulumi.get(self, \"name\")",
"def name(self) -> pulumi.Output[str]:\n return... | [
"0.8646592",
"0.7509479",
"0.7353975",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"0.7329796",
"... | 0.0 | -1 |
Equivalent to using the operator [], except for the additional enum parameter. | def getParam(self, name, enum=None):
return Parameter(self, name, enum) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_additional_properties_with_array_of_enums(self):\n pass",
"def convertToEnumItemArray(byte: int, enumType: cern.japc.value.EnumType) -> typing.List[cern.japc.value.EnumItem]:\n ...",
"def convertToEnumItemSetArray(byte: int, enumType: cern.japc.value.EnumType) -> typing.List[cern.japc.va... | [
"0.5966134",
"0.586653",
"0.57834995",
"0.5671007",
"0.5469387",
"0.5347836",
"0.51718843",
"0.5109061",
"0.5109061",
"0.51058966",
"0.50422406",
"0.5024083",
"0.49625045",
"0.4904923",
"0.49036974",
"0.48679268",
"0.48582023",
"0.48460153",
"0.48249942",
"0.48193696",
"0.481... | 0.0 | -1 |
Decrypt this guardian's share of one or more ballots | def decrypt_ballot_shares(
request: DecryptBallotSharesRequest = Body(...),
scheduler: Scheduler = Depends(get_scheduler),
) -> Any:
ballots = [
CiphertextAcceptedBallot.from_json_object(ballot)
for ballot in request.encrypted_ballots
]
context = CiphertextElectionContext.from_json_o... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_pam_secret(self, key):\n\n\n privateKeyA=self.rand() \n privateKeyB=self.rand() \n publicKeyA = int(pow(genrated,privateKeyA,prime))\n publicKeyB = int(pow(genrated,privateKeyB,prime))\n\n resp = self.process(\n requests.get(f\"{self.api_url}/secretman/GetSecre... | [
"0.629344",
"0.5591807",
"0.5542672",
"0.54974806",
"0.54797286",
"0.54184014",
"0.540358",
"0.53940344",
"0.5366817",
"0.5345882",
"0.5340164",
"0.522527",
"0.51924723",
"0.5167279",
"0.51538104",
"0.5105933",
"0.5103906",
"0.5103906",
"0.5098788",
"0.50672245",
"0.5058073",... | 0.6520781 | 0 |
Check the value for limits according to topic. If out of limit, notify over telegram | def limitsExsess(topic, value):
if isNotifyTime(topic):
if "temperature" in topic:
val = float(value)
if val < MIN_TEMPERATURE or val > MAX_TEMPERATURE:
notifyTelegram("Temperature out of bounds: "+value+"degC")
return True
if "CO" in topic:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def allowedLimit(self, number, msg=None):\n return allowed_limit(number, msg)",
"async def max(self, ctx, limit: int):\n self.data_check(ctx)\n server = ctx.message.server\n\n self.riceCog2[server.id][\"max\"] = limit\n dataIO.save_json(self.warning_settings,\n ... | [
"0.6885966",
"0.6692245",
"0.66228366",
"0.6284632",
"0.627446",
"0.6245816",
"0.62092686",
"0.61613834",
"0.613513",
"0.609418",
"0.6056963",
"0.6042189",
"0.60258657",
"0.5984116",
"0.59698874",
"0.59312063",
"0.59092206",
"0.5906563",
"0.58542055",
"0.5850616",
"0.5809356"... | 0.78263 | 0 |
Gets valid user credentials from storage. If nothing has been stored, or if the stored credentials are invalid, the OAuth2 flow is completed to obtain the new credentials. | def get_credentials():
#home_dir = os.path.expanduser('~')
home_dir = (HOME_DIR)
credential_dir = os.path.join(home_dir, '.credentials')
print("Credentials folder: ",credential_dir)
if not os.path.exists(credential_dir):
os.makedirs(credential_dir)
credential_path = os.path.join(credenti... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _load_user_credentials(self, storage):\n # Set up a Flow object to be used if we need to authenticate.\n flow = client.flow_from_clientsecrets(\n self.client_secrets,\n scope=self.api_scopes,\n message=tools.message_if_missing(self.client_secrets))\n\n # Re... | [
"0.7571305",
"0.7356556",
"0.71548086",
"0.711909",
"0.70713574",
"0.7026156",
"0.6991323",
"0.6962775",
"0.69490343",
"0.6940299",
"0.6935988",
"0.6906218",
"0.6900573",
"0.68998826",
"0.6857519",
"0.68309605",
"0.6792369",
"0.6785002",
"0.67753786",
"0.67753786",
"0.6775378... | 0.6240862 | 88 |
Converts encoded sequences into an array with sequence strings | def decode_one_hot(encoded_sequences):
if len(encoded_sequences.shape) == 3:
s = encoded_sequences.shape
encoded_sequences = encoded_sequences.reshape(1, s[0], s[1], s[2])
#num_samples, _, _, seq_length = np.shape(encoded_sequences)
_, num_samples, _, seq_length = np.shape(encoded_sequences... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def decode_sequence(self, sequence=list) -> str:\n try:\n out = []\n for word in sequence:\n out.append(self.decode(word))\n return(out)\n except Exception as error:\n print(f\"Error: self.decode_sequence({sequence}) -> {error}\")",
"de... | [
"0.69954103",
"0.68113625",
"0.65563",
"0.6483455",
"0.64378685",
"0.6263874",
"0.6176669",
"0.61550325",
"0.61276937",
"0.61096597",
"0.6037147",
"0.6029054",
"0.5999388",
"0.59981567",
"0.59195274",
"0.59060395",
"0.5906004",
"0.58647674",
"0.5854323",
"0.58464247",
"0.5812... | 0.5643979 | 32 |
Get a string that describes the target (for e.g. metadata). | def data_name(self):
return "Bispectrum" | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getInfo(self):\n return self.name + \" [\" + self.target_type + \"]\"",
"def target(self) -> Optional[str]:\n return pulumi.get(self, \"target\")",
"def target_name(self):\n return self._target_name",
"def name(self) -> str:\n return self.inst['targetname']",
"def get_target... | [
"0.73063004",
"0.72933376",
"0.7276515",
"0.7202048",
"0.71281767",
"0.696577",
"0.6881676",
"0.68652797",
"0.6742786",
"0.67377156",
"0.6706205",
"0.66736144",
"0.6576408",
"0.6562085",
"0.6562085",
"0.6562085",
"0.6562085",
"0.6562085",
"0.6562085",
"0.6562085",
"0.6562085"... | 0.0 | -1 |
Get the feature dimension of this data. | def feature_size(self):
return self.fingerprint_length | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def feature_dimension(self) -> int:\n return self._feature_dimension",
"def feature_dim(self):\n return feature_dim_from_test_system(self)",
"def features_dim(self):\n if not self.exposes_features:\n return None\n\n dim = self._features_op.outputs[0].get_shape().as_list()... | [
"0.89637285",
"0.86458623",
"0.8564586",
"0.83512133",
"0.8064637",
"0.7931219",
"0.78060144",
"0.7794164",
"0.77869695",
"0.77869695",
"0.77869695",
"0.77869695",
"0.7766574",
"0.7721604",
"0.7697934",
"0.7682128",
"0.7605907",
"0.75448817",
"0.75407034",
"0.75349915",
"0.75... | 0.0 | -1 |
Convert the units of a bispectrum descriptor. Since these do not really have units this function does nothing yet. | def convert_units(array, in_units="None"):
if in_units == "None" or in_units is None:
return array
else:
raise Exception("Unsupported unit for bispectrum descriptors.") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def convert_units(self):\n for prod in (\"ier\", \"ier_inc_rain\"):\n self.data[prod].data[:] /= 1e6",
"def backconvert_units(array, out_units):\n if out_units == \"None\" or out_units is None:\n return array\n else:\n raise Exception(\"Unsupported unit for b... | [
"0.7362858",
"0.697799",
"0.68368673",
"0.6746229",
"0.67332226",
"0.6689847",
"0.6652228",
"0.6625354",
"0.6573514",
"0.6546448",
"0.65275437",
"0.64689595",
"0.6373749",
"0.63324165",
"0.6316742",
"0.6294838",
"0.6258834",
"0.62498343",
"0.6219283",
"0.62110245",
"0.6167998... | 0.7536837 | 0 |
Convert the units of a bispectrum descriptor. Since these do not really have units this function does nothing yet. | def backconvert_units(array, out_units):
if out_units == "None" or out_units is None:
return array
else:
raise Exception("Unsupported unit for bispectrum descriptors.") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def convert_units(array, in_units=\"None\"):\n if in_units == \"None\" or in_units is None:\n return array\n else:\n raise Exception(\"Unsupported unit for bispectrum descriptors.\")",
"def convert_units(self):\n for prod in (\"ier\", \"ier_inc_rain\"):\n sel... | [
"0.7536962",
"0.7362253",
"0.68372786",
"0.674662",
"0.6732477",
"0.66885984",
"0.665177",
"0.6623838",
"0.6573811",
"0.65471977",
"0.65269375",
"0.64705104",
"0.6375094",
"0.6330455",
"0.6316037",
"0.62951684",
"0.6259092",
"0.6249572",
"0.6218803",
"0.6210326",
"0.6170082",... | 0.69773746 | 2 |
Perform actual bispectrum calculation. | def _calculate(self, atoms, outdir, grid_dimensions, **kwargs):
use_fp64 = kwargs.get("use_fp64", False)
lammps_format = "lammps-data"
ase_out_path = os.path.join(outdir, "lammps_input.tmp")
ase.io.write(ase_out_path, atoms, format=lammps_format)
nx = grid_dimensions[0]
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def calculate_ft(self):\n \n # Create a function which is able to evaluate B**2\n ffunc = scipy.interpolate.interp1d(self.psigrid, self.e.getF()[self.tind])\n def b2_func(R, Z, psi):\n bt = ffunc(psi)/R\n br = -self.psifunc.ev(R, Z, dy=1)/R\n bz = self.p... | [
"0.6264825",
"0.5765228",
"0.57305443",
"0.57027525",
"0.5698685",
"0.5697205",
"0.56671035",
"0.5649315",
"0.5634285",
"0.56256074",
"0.5624231",
"0.56226474",
"0.5614191",
"0.5581222",
"0.55639535",
"0.5559925",
"0.5559376",
"0.5537073",
"0.5524306",
"0.55227923",
"0.551113... | 0.0 | -1 |
Sum up all 1's in a list, and calculate the product sum Return the original list and the summed If the list only contains one 1, dont calculate the sum >>> sum_ones((1, 1, 2), 112) [(1, 1, 2), (2, 2)], [2, 4] >>> sum_ones((1, 2), 2) [(1, 2)], [2] >>> sum_ones((2, ), 2) [(2,)], [2] | def sum_ones(part, prod):
if part in sum_ones_memory:
partList, prodList = sum_ones_memory[part]
else:
n1 = part.count(1)
partList = [part]
prodList = [prod]
if n1 > 1:
npart = tuple(filter(lambda x: x != 1, part))
npart = (n1,) + npart
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sum_list(numbers):\n\t\n\tif len(numbers) == 0:\n\t\treturn 0 \n\n\tsum = numbers[0] +sum_list(numbers[1:])\n\treturn sum",
"def zero_sum(list):\n if not list:\n return 0\n else:\n return sum(list)",
"def mult_and_sum(*arg_list):\r\n result = numpy.empty(arg_list[0].shape, dtype=... | [
"0.595099",
"0.58707553",
"0.5846285",
"0.5818005",
"0.58091325",
"0.5784409",
"0.5705578",
"0.5697676",
"0.56917393",
"0.5681991",
"0.56177396",
"0.555534",
"0.5501804",
"0.5495922",
"0.546188",
"0.546188",
"0.5457171",
"0.5431213",
"0.5431213",
"0.54213077",
"0.53874594",
... | 0.7017122 | 0 |
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