ytzi/the-stack-dedup-python-filtered-docstrings

fe5faeef8ee1634c0f11e3b81c2ab55c90744a4f

1,239

py

Python

tests/test_utils.py

cenyk1230/cogdl

fa1f74d5c3a15b5a52abfc7cd3f04dce4b7dbcce

[ "MIT" ]

1,072

2019-08-02T05:46:21.000Z

2022-03-31T07:51:53.000Z

tests/test_utils.py

cenyk1230/cogdl

fa1f74d5c3a15b5a52abfc7cd3f04dce4b7dbcce

[ "MIT" ]

96

2019-08-05T17:27:22.000Z

2022-03-03T08:36:57.000Z

tests/test_utils.py

cenyk1230/cogdl

fa1f74d5c3a15b5a52abfc7cd3f04dce4b7dbcce

[ "MIT" ]

299

2019-08-08T07:33:10.000Z

2022-03-31T09:30:07.000Z

from sklearn.metrics import f1_score import torch from cogdl.utils import build_args_from_dict from cogdl.utils import accuracy, multiclass_f1, multilabel_f1, bce_with_logits_loss, cross_entropy_loss if __name__ == "__main__": test_build_args_from_dict()

31.769231

104

0.678773

from sklearn.metrics import f1_score import torch from cogdl.utils import build_args_from_dict from cogdl.utils import accuracy, multiclass_f1, multilabel_f1, bce_with_logits_loss, cross_entropy_loss def test_build_args_from_dict(): dic = {"arg1": "value1", "arg2": 2, "arg3": 0.3} args = build_args_from_dict(dic) assert args.arg1 == "value1" assert args.arg2 == 2 assert args.arg3 == 0.3 def test_evaluator(): pred = torch.randn(20, 5) target_one = torch.randint(0, 5, (20,)) target_mult = torch.randint(0, 2, (20, 5)).float() def f(x): return round(float(x), 5) _ = cross_entropy_loss(pred, target_one) _pred = torch.nn.functional.log_softmax(pred, dim=-1) acc = _pred.max(1)[1].eq(target_one).double().sum() / len(_pred) assert f(acc) == f(accuracy(_pred, target_one)) f1 = f1_score(target_one, _pred.max(1)[1], average="micro") assert f(f1) == f(multiclass_f1(_pred, target_one)) _ = bce_with_logits_loss(pred, target_mult) _pred = torch.zeros_like(pred) _pred[pred > 0] = 1 f1 = f1_score(target_mult, _pred, average="micro") assert f(f1) == f(multilabel_f1(pred, target_mult)) if __name__ == "__main__": test_build_args_from_dict()

930

0

46

c38a95aad8565a4d121edf838f6134f6a4a283f3

9,493

py

Python

analogistics/supply_chain/P8_performance_assessment/wh_indexes.py

aletuf93/analogistics

c5f76910683bc3a1cc6f24799f0299232b4fc522

[ "MIT" ]

null

analogistics/supply_chain/P8_performance_assessment/wh_indexes.py

aletuf93/analogistics

c5f76910683bc3a1cc6f24799f0299232b4fc522

[ "MIT" ]

null

analogistics/supply_chain/P8_performance_assessment/wh_indexes.py

aletuf93/analogistics

c5f76910683bc3a1cc6f24799f0299232b4fc522

[ "MIT" ]

null

# -*- coding: utf-8 -*- import pandas as pd import numpy as np import matplotlib.pyplot as plt from analogistics.statistics import time_series as ts from analogistics.supply_chain.information_framework import movementfunctionfromInventory from analogistics.explore import paretoDataframe def calculatePopularity(movements: pd.Series): """ Define the popularity for a SKU Args: movements (pd.Series): series of the movement with one item per day. Returns: pop_in (float): relative popularity IN per day. pop_out (float): realtiva popularity OUT per day. pop_absolute_in (float): popularity IN per day. pop_absolute_out (float): popularity OUT per day. """ pop_in = len(movements[movements > 0]) / len(movements) pop_out = len(movements[movements < 0]) / len(movements) pop_absolute_in = len(movements[movements > 0]) pop_absolute_out = len(movements[movements < 0]) return pop_in, pop_out, pop_absolute_in, pop_absolute_out def calculateCOI(inventory: pd.Series): """ Calculate the COI index of an SKU, given the inventory function Args: inventory (pd.Series): series of the inventory of an SKU. Returns: COI_in (float): COI index IN. COI_out (float): COI index OUT. """ # define inventory from movements movements = movementfunctionfromInventory(inventory) movements = movements.dropna() pop_in, pop_out, _, _ = calculatePopularity(movements['QUANTITY']) # calculate daily COI I_t_avg = np.nanmean(inventory) if I_t_avg > 0: COI_in = pop_in / I_t_avg COI_out = pop_out / I_t_avg else: COI_in = COI_out = np.nan return COI_in, COI_out def calculateTurn(inventory: pd.Series): """ Calculate the TURN index of an SKU, given the inventory function Args: inventory (pd.series): series of the inventory of an SKU. Returns: turn (float): Output turn index. """ # define inventory from movements movements = movementfunctionfromInventory(inventory) movements = movements.dropna() # calculate the average outbound quantity per day out_qty_day = -np.sum(movements[movements['QUANTITY'] < 0]['QUANTITY']) / len(movements) # calculate average inventory quantity I_t_avg = np.nanmean(inventory) if I_t_avg > 0: turn = out_qty_day / I_t_avg else: turn = np.nan return turn def calculateOrderCompletion(D_mov: pd.DataFrame, itemcode: str, itemfield: str = 'ITEMCODE', ordercodefield: str = 'ORDERCODE'): """ calculate the Order Completion (OC) index Args: D_mov (pd.DataFrame): dataframe with movements reporting ordercode and itemcode columns. itemcode (str): itemcode to calculate the order competion (OC) index. itemfield (str, optional): string name of D_mov clumn with itemcode. Defaults to 'ITEMCODE'. ordercodefield (str, optional): string name of D_mov clumn with ordercode. Defaults to 'ORDERCODE'. Returns: OC (float): Output OC index. """ # clean data D_mov = D_mov[[itemfield, ordercodefield]] D_mov = D_mov[D_mov[ordercodefield] != 'nan'] D_mov = D_mov.dropna() D_mov = D_mov.reset_index() orders = list(set(D_mov[D_mov[itemfield] == itemcode][ordercodefield])) idx = [j in orders for j in D_mov[ordercodefield]] D_orders = D_mov.loc[idx] OC = 0 for ordercode in orders: D_orders_filtered = D_orders[D_orders[ordercodefield] == ordercode] OC = OC + 1 / len(D_orders_filtered) return OC def fourierAnalysisInventory(inventory: pd.Series): """ fourier analysis of the inventory curve Args: inventory (pd.series): list of inventory values. Returns: first_carrier (TYPE): frequency (in 1/days) with the highest amplitude value. period (TYPE): period (in days) associated with the frequency with the highest amplitude value. """ D = ts.fourierAnalysis(np.array(inventory)) D = D.sort_values(by='Amplitude', ascending=False) first_carrier = D.iloc[0]['Frequency_domain_value'] # 1 / days period = 1 / first_carrier return first_carrier, period def updatePopularity(D_SKUs: pd.DataFrame): """ Update the popularity index Args: D_SKUs (pd.dataFrame): Input dataframe with SKUs. Returns: D_SKUs (pd.DataFrame): Output DataFrame with updated popularity. """ # create results columns D_SKUs['POP_IN'] = np.nan D_SKUs['POP_OUT'] = np.nan D_SKUs['POP_IN_TOT'] = np.nan D_SKUs['POP_OUT_TOT'] = np.nan for index, row in D_SKUs.iterrows(): # select inventory curve I_t = D_SKUs.loc[index]['INVENTORY_QTY'] # calculate the popularity movements = movementfunctionfromInventory(I_t) movements = movements.dropna() if len(movements) > 0: POP_IN, POP_OUT, POP_IN_TOT, POP_OUT_TOT = calculatePopularity(movements['QUANTITY']) # update the dataframe D_SKUs.at[index, 'POP_IN'] = POP_IN D_SKUs.at[index, 'POP_OUT'] = POP_OUT D_SKUs.at[index, 'POP_IN_TOT'] = POP_IN_TOT D_SKUs.at[index, 'POP_OUT_TOT'] = POP_OUT_TOT return D_SKUs def updateCOI(D_SKUs: pd.DataFrame): """ Update the COI index Args: D_SKUs (pd.DataFrame): Input dataframe with SKUs. Returns: D_SKUs (pd.DataFrame): Output DataFrame with updated COI. """ # create result columns D_SKUs['COI_IN'] = np.nan D_SKUs['COI_OUT'] = np.nan for index, row in D_SKUs.iterrows(): # select inventory curve I_t = D_SKUs.loc[index]['INVENTORY_QTY'] # calculate the popularity movements = movementfunctionfromInventory(I_t) movements = movements.dropna() if len(movements) > 0: COI_IN, COI_OUT = calculateCOI(I_t) # update the dataframe D_SKUs.at[index, 'COI_IN'] = COI_IN D_SKUs.at[index, 'COI_OUT'] = COI_OUT return D_SKUs def updateTURN(D_SKUs: pd.DataFrame): """ Update TURN index Args: D_SKUs (pd.DataFrame): Input dataframe with SKUs. Returns: D_SKUs (TYPE): Output DataFrame with updated TURN. """ # create result columns D_SKUs['TURN'] = np.nan for index, row in D_SKUs.iterrows(): # select inventory curve I_t = D_SKUs.loc[index]['INVENTORY_QTY'] # calculate the popularity movements = movementfunctionfromInventory(I_t) movements = movements.dropna() if len(movements) > 0: TURN = calculateTurn(I_t) # update the dataframe D_SKUs.at[index, 'TURN'] = TURN return D_SKUs def updateOrderCompletion(D_SKUs: pd.DataFrame, D_mov: pd.DataFrame): """ Update OC index Args: D_SKUs (pd.DataFrame): Input dataframe with SKUs. D_mov (pd.DataFrame): Input dataframe with movements. Returns: D_SKUs (pd.dataFrame): Output DataFrame with updated OC. """ # create result columns D_SKUs['OC'] = np.nan for index, row in D_SKUs.iterrows(): part = row['ITEMCODE'] # calculate the popularity OC = calculateOrderCompletion(D_mov, part, itemfield='ITEMCODE', ordercodefield='ORDERCODE') # update the dataframe D_SKUs.at[index, 'OC'] = OC return D_SKUs def updateFourieranalysis(D_SKUs: pd.DataFrame): """ Update the Fourier Analysis Args: D_SKUs (pd.DataFrame): Input dataframe with SKUs. Returns: D_SKUs (pd.DataFrame): Output DataFrame with updated fourier analysis. """ # create result columns D_SKUs['FOURIER_CARRIER'] = np.nan D_SKUs['FOURIER_PERIOD'] = np.nan for index, row in D_SKUs.iterrows(): # select inventory curve I_t = D_SKUs.loc[index]['INVENTORY_QTY'] # calculate the popularity movements = movementfunctionfromInventory(I_t) movements = movements.dropna() if len(movements) > 0: carrier, period = fourierAnalysisInventory(I_t) # update the dataframe D_SKUs.at[index, 'FOURIER_CARRIER'] = carrier D_SKUs.at[index, 'FOURIER_PERIOD'] = period return D_SKUs # %% PARETO AND HISTOGRAM PLOT def whIndexParetoPlot(D_SKUs: pd.DataFrame, columnIndex: str): """ Define the Pareto and histogram plot for a WH index Args: D_SKUs (pd.DataFrame): Input dataframe with SKUs. columnIndex (str): Name of the index to plot. Returns: output_figures (dict): Output dictionary with figures. """ output_figures = {} # define the pareto values D_SKUs_pop = paretoDataframe(D_SKUs, columnIndex) # build the pareto figures fig1 = plt.figure() plt.plot(np.arange(0, len(D_SKUs_pop)), D_SKUs_pop[f"{columnIndex}_CUM"], color='orange') plt.title(f"{columnIndex} Pareto curve") plt.xlabel("N. of SKUs") plt.ylabel("Popularity percentage") # save the Pareto figure output_figures[f"{columnIndex}_pareto"] = fig1 fig2 = plt.figure() plt.hist(D_SKUs_pop[columnIndex], color='orange') plt.title(f"{columnIndex} histogram") plt.xlabel(f"{columnIndex}") plt.ylabel("Frequency") # save the Pareto figure output_figures[f"{columnIndex}_hist"] = fig2 return output_figures

27.83871

107

0.651006

# -*- coding: utf-8 -*- import pandas as pd import numpy as np import matplotlib.pyplot as plt from analogistics.statistics import time_series as ts from analogistics.supply_chain.information_framework import movementfunctionfromInventory from analogistics.explore import paretoDataframe def calculatePopularity(movements: pd.Series): """ Define the popularity for a SKU Args: movements (pd.Series): series of the movement with one item per day. Returns: pop_in (float): relative popularity IN per day. pop_out (float): realtiva popularity OUT per day. pop_absolute_in (float): popularity IN per day. pop_absolute_out (float): popularity OUT per day. """ pop_in = len(movements[movements > 0]) / len(movements) pop_out = len(movements[movements < 0]) / len(movements) pop_absolute_in = len(movements[movements > 0]) pop_absolute_out = len(movements[movements < 0]) return pop_in, pop_out, pop_absolute_in, pop_absolute_out def calculateCOI(inventory: pd.Series): """ Calculate the COI index of an SKU, given the inventory function Args: inventory (pd.Series): series of the inventory of an SKU. Returns: COI_in (float): COI index IN. COI_out (float): COI index OUT. """ # define inventory from movements movements = movementfunctionfromInventory(inventory) movements = movements.dropna() pop_in, pop_out, _, _ = calculatePopularity(movements['QUANTITY']) # calculate daily COI I_t_avg = np.nanmean(inventory) if I_t_avg > 0: COI_in = pop_in / I_t_avg COI_out = pop_out / I_t_avg else: COI_in = COI_out = np.nan return COI_in, COI_out def calculateTurn(inventory: pd.Series): """ Calculate the TURN index of an SKU, given the inventory function Args: inventory (pd.series): series of the inventory of an SKU. Returns: turn (float): Output turn index. """ # define inventory from movements movements = movementfunctionfromInventory(inventory) movements = movements.dropna() # calculate the average outbound quantity per day out_qty_day = -np.sum(movements[movements['QUANTITY'] < 0]['QUANTITY']) / len(movements) # calculate average inventory quantity I_t_avg = np.nanmean(inventory) if I_t_avg > 0: turn = out_qty_day / I_t_avg else: turn = np.nan return turn def calculateOrderCompletion(D_mov: pd.DataFrame, itemcode: str, itemfield: str = 'ITEMCODE', ordercodefield: str = 'ORDERCODE'): """ calculate the Order Completion (OC) index Args: D_mov (pd.DataFrame): dataframe with movements reporting ordercode and itemcode columns. itemcode (str): itemcode to calculate the order competion (OC) index. itemfield (str, optional): string name of D_mov clumn with itemcode. Defaults to 'ITEMCODE'. ordercodefield (str, optional): string name of D_mov clumn with ordercode. Defaults to 'ORDERCODE'. Returns: OC (float): Output OC index. """ # clean data D_mov = D_mov[[itemfield, ordercodefield]] D_mov = D_mov[D_mov[ordercodefield] != 'nan'] D_mov = D_mov.dropna() D_mov = D_mov.reset_index() orders = list(set(D_mov[D_mov[itemfield] == itemcode][ordercodefield])) idx = [j in orders for j in D_mov[ordercodefield]] D_orders = D_mov.loc[idx] OC = 0 for ordercode in orders: D_orders_filtered = D_orders[D_orders[ordercodefield] == ordercode] OC = OC + 1 / len(D_orders_filtered) return OC def fourierAnalysisInventory(inventory: pd.Series): """ fourier analysis of the inventory curve Args: inventory (pd.series): list of inventory values. Returns: first_carrier (TYPE): frequency (in 1/days) with the highest amplitude value. period (TYPE): period (in days) associated with the frequency with the highest amplitude value. """ D = ts.fourierAnalysis(np.array(inventory)) D = D.sort_values(by='Amplitude', ascending=False) first_carrier = D.iloc[0]['Frequency_domain_value'] # 1 / days period = 1 / first_carrier return first_carrier, period def updatePopularity(D_SKUs: pd.DataFrame): """ Update the popularity index Args: D_SKUs (pd.dataFrame): Input dataframe with SKUs. Returns: D_SKUs (pd.DataFrame): Output DataFrame with updated popularity. """ # create results columns D_SKUs['POP_IN'] = np.nan D_SKUs['POP_OUT'] = np.nan D_SKUs['POP_IN_TOT'] = np.nan D_SKUs['POP_OUT_TOT'] = np.nan for index, row in D_SKUs.iterrows(): # select inventory curve I_t = D_SKUs.loc[index]['INVENTORY_QTY'] # calculate the popularity movements = movementfunctionfromInventory(I_t) movements = movements.dropna() if len(movements) > 0: POP_IN, POP_OUT, POP_IN_TOT, POP_OUT_TOT = calculatePopularity(movements['QUANTITY']) # update the dataframe D_SKUs.at[index, 'POP_IN'] = POP_IN D_SKUs.at[index, 'POP_OUT'] = POP_OUT D_SKUs.at[index, 'POP_IN_TOT'] = POP_IN_TOT D_SKUs.at[index, 'POP_OUT_TOT'] = POP_OUT_TOT return D_SKUs def updateCOI(D_SKUs: pd.DataFrame): """ Update the COI index Args: D_SKUs (pd.DataFrame): Input dataframe with SKUs. Returns: D_SKUs (pd.DataFrame): Output DataFrame with updated COI. """ # create result columns D_SKUs['COI_IN'] = np.nan D_SKUs['COI_OUT'] = np.nan for index, row in D_SKUs.iterrows(): # select inventory curve I_t = D_SKUs.loc[index]['INVENTORY_QTY'] # calculate the popularity movements = movementfunctionfromInventory(I_t) movements = movements.dropna() if len(movements) > 0: COI_IN, COI_OUT = calculateCOI(I_t) # update the dataframe D_SKUs.at[index, 'COI_IN'] = COI_IN D_SKUs.at[index, 'COI_OUT'] = COI_OUT return D_SKUs def updateTURN(D_SKUs: pd.DataFrame): """ Update TURN index Args: D_SKUs (pd.DataFrame): Input dataframe with SKUs. Returns: D_SKUs (TYPE): Output DataFrame with updated TURN. """ # create result columns D_SKUs['TURN'] = np.nan for index, row in D_SKUs.iterrows(): # select inventory curve I_t = D_SKUs.loc[index]['INVENTORY_QTY'] # calculate the popularity movements = movementfunctionfromInventory(I_t) movements = movements.dropna() if len(movements) > 0: TURN = calculateTurn(I_t) # update the dataframe D_SKUs.at[index, 'TURN'] = TURN return D_SKUs def updateOrderCompletion(D_SKUs: pd.DataFrame, D_mov: pd.DataFrame): """ Update OC index Args: D_SKUs (pd.DataFrame): Input dataframe with SKUs. D_mov (pd.DataFrame): Input dataframe with movements. Returns: D_SKUs (pd.dataFrame): Output DataFrame with updated OC. """ # create result columns D_SKUs['OC'] = np.nan for index, row in D_SKUs.iterrows(): part = row['ITEMCODE'] # calculate the popularity OC = calculateOrderCompletion(D_mov, part, itemfield='ITEMCODE', ordercodefield='ORDERCODE') # update the dataframe D_SKUs.at[index, 'OC'] = OC return D_SKUs def updateFourieranalysis(D_SKUs: pd.DataFrame): """ Update the Fourier Analysis Args: D_SKUs (pd.DataFrame): Input dataframe with SKUs. Returns: D_SKUs (pd.DataFrame): Output DataFrame with updated fourier analysis. """ # create result columns D_SKUs['FOURIER_CARRIER'] = np.nan D_SKUs['FOURIER_PERIOD'] = np.nan for index, row in D_SKUs.iterrows(): # select inventory curve I_t = D_SKUs.loc[index]['INVENTORY_QTY'] # calculate the popularity movements = movementfunctionfromInventory(I_t) movements = movements.dropna() if len(movements) > 0: carrier, period = fourierAnalysisInventory(I_t) # update the dataframe D_SKUs.at[index, 'FOURIER_CARRIER'] = carrier D_SKUs.at[index, 'FOURIER_PERIOD'] = period return D_SKUs # %% PARETO AND HISTOGRAM PLOT def whIndexParetoPlot(D_SKUs: pd.DataFrame, columnIndex: str): """ Define the Pareto and histogram plot for a WH index Args: D_SKUs (pd.DataFrame): Input dataframe with SKUs. columnIndex (str): Name of the index to plot. Returns: output_figures (dict): Output dictionary with figures. """ output_figures = {} # define the pareto values D_SKUs_pop = paretoDataframe(D_SKUs, columnIndex) # build the pareto figures fig1 = plt.figure() plt.plot(np.arange(0, len(D_SKUs_pop)), D_SKUs_pop[f"{columnIndex}_CUM"], color='orange') plt.title(f"{columnIndex} Pareto curve") plt.xlabel("N. of SKUs") plt.ylabel("Popularity percentage") # save the Pareto figure output_figures[f"{columnIndex}_pareto"] = fig1 fig2 = plt.figure() plt.hist(D_SKUs_pop[columnIndex], color='orange') plt.title(f"{columnIndex} histogram") plt.xlabel(f"{columnIndex}") plt.ylabel("Frequency") # save the Pareto figure output_figures[f"{columnIndex}_hist"] = fig2 return output_figures

0

871d15c7fed0e7ecb34d5e18a42a899c21404f83

202

py

Python

data_collection/gazette/spiders/sc_forquilhinha.py

kaiocp/querido-diario

86004049c6eee305e13066cf3607d30849bb099a

[ "MIT" ]

454

2018-04-07T03:32:57.000Z

2020-08-17T19:56:22.000Z

data_collection/gazette/spiders/sc_forquilhinha.py

kaiocp/querido-diario

86004049c6eee305e13066cf3607d30849bb099a

[ "MIT" ]

254

2020-08-18T14:09:43.000Z

2022-03-28T11:30:51.000Z

data_collection/gazette/spiders/sc_forquilhinha.py

kaiocp/querido-diario

86004049c6eee305e13066cf3607d30849bb099a

[ "MIT" ]

183

2018-04-11T15:09:37.000Z

2020-08-15T18:55:11.000Z

from gazette.spiders.base.fecam import FecamGazetteSpider

25.25

57

0.777228

from gazette.spiders.base.fecam import FecamGazetteSpider class ScForquilhinhaSpider(FecamGazetteSpider): name = "sc_forquilhinha" FECAM_QUERY = "cod_entidade:94" TERRITORY_ID = "4205456"

0

120

23

7d2d81b868d78570f829b82f7e1a603d8f307c26

25,424

py

Python

causallearn/score/LocalScoreFunction.py

softsys4ai/causal-config-labyrinth

4f50f9ff15429b0ac6ad0a99fbe4cfdd17e360fc

[ "MIT" ]

15

2022-01-20T12:35:35.000Z

2022-03-24T16:25:24.000Z

causallearn/score/LocalScoreFunction.py

softsys4ai/unicorn

4f50f9ff15429b0ac6ad0a99fbe4cfdd17e360fc

[ "MIT" ]

14

2022-01-23T00:20:00.000Z

2022-02-22T01:40:43.000Z

causallearn/score/LocalScoreFunction.py

softsys4ai/causal-config-labyrinth

4f50f9ff15429b0ac6ad0a99fbe4cfdd17e360fc

[ "MIT" ]

1

2022-02-23T08:59:24.000Z

import math import pandas as pd from causallearn.utils.ScoreUtils import * def local_score_BIC(Data, i, PAi, parameters=None): ''' Calculate the *negative* local score with BIC for the linear Gaussian continue data case Parameters ---------- Data: ndarray, (sample, features) i: current index PAi: parent indexes parameters: lambda_value, the penalty discount of bic Returns ------- score: local BIC score ''' if parameters is None: lambda_value = 1 else: lambda_value = parameters['lambda_value'] Data = np.mat(Data) T = Data.shape[0] X = Data[:, i] if len(PAi) != 0: PA = Data[:, PAi] D = PA.shape[1] # derive the parameters by maximum likelihood H = PA * pdinv(PA.T * PA) * PA.T E = X - H * X sigma2 = np.sum(np.power(E, 2)) / T # BIC score = T * np.log(sigma2) + lambda_value * D * np.log(T) else: sigma2 = np.sum(np.power(X, 2)) / T # BIC score = T * np.log(sigma2) return score def local_score_BDeu(Data, i, PAi, parameters=None): ''' Calculate the *negative* local score with BDeu for the discrete case Parameters ---------- Data: (sample, features) i: current index PAi: parent indexes parameters: sample_prior: sample prior structure_prior: structure prior r_i_map: number of states of the finite random variable X_{i} Returns ------- score: local BDeu score ''' if parameters is None: sample_prior = 1 # default sample_prior = 1 structure_prior = 1 # default structure_prior = 1 r_i_map = {i: len(np.unique(np.asarray(Data[:, i]))) for i in range(Data.shape[1])} else: sample_prior = parameters['sample_prior'] structure_prior = parameters['structure_prior'] r_i_map = parameters['r_i_map'] # calculate q_{i} q_i = 1 for pa in PAi: q_i *= r_i_map[pa] if len(PAi) != 0: # calculate N_{ij} names = ['x{}'.format(i) for i in range(Data.shape[1])] Data_pd = pd.DataFrame(Data, columns=names) parant_names = ['x{}'.format(i) for i in PAi] Data_pd_group_Nij = Data_pd.groupby(parant_names) Nij_map = {key: len(Data_pd_group_Nij.indices.get(key)) for key in Data_pd_group_Nij.indices.keys()} Nij_map_keys_list = list(Nij_map.keys()) # calculate N_{ijk} Nijk_map = {ij: Data_pd_group_Nij.get_group(ij).groupby('x{}'.format(i)).apply(len).reset_index() for ij in Nij_map.keys()} for v in Nijk_map.values(): v.columns = ['x{}'.format(i), 'times'] else: # calculate N_{ij} names = ['x{}'.format(i) for i in range(Data.shape[1])] Nij_map = {'': len(Data[:, i])} Nij_map_keys_list = [''] Data_pd = pd.DataFrame(Data, columns=names) # calculate N_{ijk} Nijk_map = {ij: Data_pd.groupby('x{}'.format(i)).apply(len).reset_index() for ij in Nij_map_keys_list} for v in Nijk_map.values(): v.columns = ['x{}'.format(i), 'times'] BDeu_score = 0 # first term vm = Data.shape[0] - 1 BDeu_score += len(PAi) * np.log(structure_prior / vm) + (vm - len(PAi)) * np.log(1 - (structure_prior / vm)) # second term for pa in range(len(Nij_map_keys_list)): Nij = Nij_map.get(Nij_map_keys_list[pa]) first_term = math.lgamma(sample_prior / q_i) - math.lgamma(Nij + sample_prior / q_i) second_term = 0 Nijk_list = Nijk_map.get(Nij_map_keys_list[pa])['times'].to_numpy() for Nijk in Nijk_list: second_term += math.lgamma(Nijk + sample_prior / (r_i_map[i] * q_i)) - math.lgamma( sample_prior / (r_i_map[i] * q_i)) BDeu_score += first_term + second_term return -BDeu_score def local_score_cv_general(Data, Xi, PAi, parameters): ''' Calculate the local score using negative k-fold cross-validated log likelihood as the score based on a regression model in RKHS Parameters ---------- Data: (sample, features) i: current index PAi: parent indexes parameters: kfold: k-fold cross validation lambda: regularization parameter Returns ------- score: local score ''' Data = np.mat(Data) PAi = list(PAi) T = Data.shape[0] X = Data[:, Xi] var_lambda = parameters['lambda'] # regularization parameter k = parameters['kfold'] # k-fold cross validation n0 = math.floor(T / k) gamma = 0.01 Thresh = 1E-5 if (len(PAi)): PA = Data[:, PAi] # set the kernel for X GX = np.sum(np.multiply(X, X), axis=1) Q = np.tile(GX, (1, T)) R = np.tile(GX.T, (T, 1)) dists = Q + R - 2 * X * X.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) # median value width = width * 2 theta = 1 / (width ** 2) Kx, _ = kernel(X, X, (theta, 1)) # Gaussian kernel H0 = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / (T) # for centering of the data in feature space Kx = H0 * Kx * H0 # kernel matrix for X # eig_Kx, eix = eigdec((Kx + Kx.T)/2, np.min([400, math.floor(T/2)]), evals_only=False) # /2 # IIx = np.where(eig_Kx > np.max(eig_Kx) * Thresh)[0] # eig_Kx = eig_Kx[IIx] # eix = eix[:, IIx] # mx = len(IIx) # set the kernel for PA Kpa = np.mat(np.ones((T, T))) for m in range(PA.shape[1]): G = np.sum((np.multiply(PA[:, m], PA[:, m])), axis=1) Q = np.tile(G, (1, T)) R = np.tile(G.T, (T, 1)) dists = Q + R - 2 * PA[:, m] * PA[:, m].T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) # median value width = width * 2 theta = 1 / (width ** 2) Kpa = np.multiply(Kpa, kernel(PA[:, m], PA[:, m], (theta, 1))[0]) H0 = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / (T) # for centering of the data in feature space Kpa = H0 * Kpa * H0 # kernel matrix for PA CV = 0 for kk in range(k): if (kk == 0): Kx_te = Kx[0:n0, 0:n0] Kx_tr = Kx[n0: T, n0: T] Kx_tr_te = Kx[n0: T, 0: n0] Kpa_te = Kpa[0:n0, 0: n0] Kpa_tr = Kpa[n0: T, n0: T] Kpa_tr_te = Kpa[n0: T, 0: n0] nv = n0 # sample size of validated data if (kk == k - 1): Kx_te = Kx[kk * n0:T, kk * n0: T] Kx_tr = Kx[0:kk * n0, 0: kk * n0] Kx_tr_te = Kx[0:kk * n0, kk * n0: T] Kpa_te = Kpa[kk * n0:T, kk * n0: T] Kpa_tr = Kpa[0: kk * n0, 0: kk * n0] Kpa_tr_te = Kpa[0:kk * n0, kk * n0: T] nv = T - kk * n0 if (kk < k - 1 and kk > 0): Kx_te = Kx[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kx_tr = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]))] Kx_tr_te = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.arange(kk * n0, (kk + 1) * n0))] Kpa_te = Kpa[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kpa_tr = Kpa[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]))] Kpa_tr_te = Kpa[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.arange(kk * n0, (kk + 1) * n0))] nv = n0 n1 = T - nv tmp1 = pdinv(Kpa_tr + n1 * var_lambda * np.mat(np.eye(n1))) tmp2 = tmp1 * Kx_tr * tmp1 tmp3 = tmp1 * pdinv(np.mat(np.eye(n1)) + n1 * var_lambda ** 2 / gamma * tmp2) * tmp1 A = (Kx_te + Kpa_tr_te.T * tmp2 * Kpa_tr_te - 2 * Kx_tr_te.T * tmp1 * Kpa_tr_te - n1 * var_lambda ** 2 / gamma * Kx_tr_te.T * tmp3 * Kx_tr_te - n1 * var_lambda ** 2 / gamma * Kpa_tr_te.T * tmp1 * Kx_tr * tmp3 * Kx_tr * tmp1 * Kpa_tr_te + 2 * n1 * var_lambda ** 2 / gamma * Kx_tr_te.T * tmp3 * Kx_tr * tmp1 * Kpa_tr_te) / gamma B = n1 * var_lambda ** 2 / gamma * tmp2 + np.mat(np.eye(n1)) L = np.linalg.cholesky(B) C = np.sum(np.log(np.diag(L))) # CV = CV + (nv*nv*log(2*pi) + nv*C + nv*mx*log(gamma) + trace(A))/2; CV = CV + (nv * nv * np.log(2 * np.pi) + nv * C + np.trace(A)) / 2 CV = CV / k else: # set the kernel for X GX = np.sum(np.multiply(X, X), axis=1) Q = np.tile(GX, (1, T)) R = np.tile(GX.T, (T, 1)) dists = Q + R - 2 * X * X.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) # median value width = width * 2 theta = 1 / (width ** 2) Kx, _ = kernel(X, X, (theta, 1)) # Gaussian kernel H0 = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / (T) # for centering of the data in feature space Kx = H0 * Kx * H0 # kernel matrix for X # eig_Kx, eix = eigdec((Kx + Kx.T) / 2, np.min([400, math.floor(T / 2)]), evals_only=False) # /2 # IIx = np.where(eig_Kx > np.max(eig_Kx) * Thresh)[0] # mx = len(IIx) CV = 0 for kk in range(k): if (kk == 0): Kx_te = Kx[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kx_tr = Kx[(kk + 1) * n0:T, (kk + 1) * n0: T] Kx_tr_te = Kx[(kk + 1) * n0:T, kk * n0: (kk + 1) * n0] nv = n0 if (kk == k - 1): Kx_te = Kx[kk * n0: T, kk * n0: T] Kx_tr = Kx[0: kk * n0, 0: kk * n0] Kx_tr_te = Kx[0:kk * n0, kk * n0: T] nv = T - kk * n0 if (kk < k - 1 and kk > 0): Kx_te = Kx[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kx_tr = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]))] Kx_tr_te = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.arange(kk * n0, (kk + 1) * n0))] nv = n0 n1 = T - nv A = (Kx_te - 1 / (gamma * n1) * Kx_tr_te.T * pdinv( np.mat(np.eye(n1)) + 1 / (gamma * n1) * Kx_tr) * Kx_tr_te) / gamma B = 1 / (gamma * n1) * Kx_tr + np.mat(np.eye(n1)) L = np.linalg.cholesky(B) C = np.sum(np.log(np.diag(L))) # CV = CV + (nv*nv*log(2*pi) + nv*C + nv*mx*log(gamma) + trace(A))/2; CV = CV + (nv * nv * np.log(2 * np.pi) + nv * C + np.trace(A)) / 2 CV = CV / k score = CV # negative cross-validated likelihood return score def local_score_cv_multi(Data, Xi, PAi, parameters): ''' Calculate the local score using negative k-fold cross-validated log likelihood as the score based on a regression model in RKHS for variables with multi-variate dimensions Parameters ---------- Data: (sample, features) i: current index PAi: parent indexes parameters: kfold: k-fold cross validation lambda: regularization parameter dlabel: for variables with multi-dimensions, indicate which dimensions belong to the i-th variable. Returns ------- score: local score ''' T = Data.shape[0] X = Data[:, parameters['dlabel'][Xi]] var_lambda = parameters['lambda'] # regularization parameter k = parameters['kfold'] # k-fold cross validation n0 = math.floor(T / k) gamma = 0.01 Thresh = 1E-5 if (len(PAi)): # set the kernel for X GX = np.sum(np.multiply(X, X), axis=1) Q = np.tile(GX, (1, T)) R = np.tile(GX.T, (T, 1)) dists = Q + R - 2 * X * X.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) # median value width = width * 3 ### theta = 1 / (width ** 2 * X.shape[1]) # Kx, _ = kernel(X, X, (theta, 1)) # Gaussian kernel H0 = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / (T) # for centering of the data in feature space Kx = H0 * Kx * H0 # kernel matrix for X # set the kernel for PA Kpa = np.mat(np.ones((T, T))) for m in range(len(PAi)): PA = Data[:, parameters['dlabel'][PAi[m]]] G = np.sum((np.multiply(PA, PA)), axis=1) Q = np.tile(G, (1, T)) R = np.tile(G.T, (T, 1)) dists = Q + R - 2 * PA * PA.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) # median value width = width * 3 ### theta = 1 / (width ** 2 * PA.shape[1]) Kpa = np.multiply(Kpa, kernel(PA, PA, (theta, 1))[0]) H0 = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / (T) # for centering of the data in feature space Kpa = H0 * Kpa * H0 # kernel matrix for PA CV = 0 for kk in range(k): if (kk == 0): Kx_te = Kx[0:n0, 0:n0] Kx_tr = Kx[n0: T, n0: T] Kx_tr_te = Kx[n0: T, 0: n0] Kpa_te = Kpa[0:n0, 0: n0] Kpa_tr = Kpa[n0: T, n0: T] Kpa_tr_te = Kpa[n0: T, 0: n0] nv = n0 # sample size of validated data if (kk == k - 1): Kx_te = Kx[kk * n0:T, kk * n0: T] Kx_tr = Kx[0:kk * n0, 0: kk * n0] Kx_tr_te = Kx[0:kk * n0, kk * n0: T] Kpa_te = Kpa[kk * n0:T, kk * n0: T] Kpa_tr = Kpa[0: kk * n0, 0: kk * n0] Kpa_tr_te = Kpa[0:kk * n0, kk * n0: T] nv = T - kk * n0 if (kk < k - 1 and kk > 0): Kx_te = Kx[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kx_tr = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]))] Kx_tr_te = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.arange(kk * n0, (kk + 1) * n0))] Kpa_te = Kpa[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kpa_tr = Kpa[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]))] Kpa_tr_te = Kpa[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.arange(kk * n0, (kk + 1) * n0))] nv = n0 n1 = T - nv tmp1 = pdinv(Kpa_tr + n1 * var_lambda * np.mat(np.eye(n1))) tmp2 = tmp1 * Kx_tr * tmp1 tmp3 = tmp1 * pdinv(np.mat(np.eye(n1)) + n1 * var_lambda ** 2 / gamma * tmp2) * tmp1 A = (Kx_te + Kpa_tr_te.T * tmp2 * Kpa_tr_te - 2 * Kx_tr_te.T * tmp1 * Kpa_tr_te - n1 * var_lambda ** 2 / gamma * Kx_tr_te.T * tmp3 * Kx_tr_te - n1 * var_lambda ** 2 / gamma * Kpa_tr_te.T * tmp1 * Kx_tr * tmp3 * Kx_tr * tmp1 * Kpa_tr_te + 2 * n1 * var_lambda ** 2 / gamma * Kx_tr_te.T * tmp3 * Kx_tr * tmp1 * Kpa_tr_te) / gamma B = n1 * var_lambda ** 2 / gamma * tmp2 + np.mat(np.eye(n1)) L = np.linalg.cholesky(B) C = np.sum(np.log(np.diag(L))) # CV = CV + (nv*nv*log(2*pi) + nv*C + nv*mx*log(gamma) + trace(A))/2; CV = CV + (nv * nv * np.log(2 * np.pi) + nv * C + np.trace(A)) / 2 CV = CV / k else: # set the kernel for X GX = np.sum(np.multiply(X, X), axis=1) Q = np.tile(GX, (1, T)) R = np.tile(GX.T, (T, 1)) dists = Q + R - 2 * X * X.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) # median value width = width * 3 ### theta = 1 / (width ** 2 * X.shape[1]) # Kx, _ = kernel(X, X, (theta, 1)) # Gaussian kernel H0 = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / (T) # for centering of the data in feature space Kx = H0 * Kx * H0 # kernel matrix for X CV = 0 for kk in range(k): if (kk == 0): Kx_te = Kx[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kx_tr = Kx[(kk + 1) * n0:T, (kk + 1) * n0: T] Kx_tr_te = Kx[(kk + 1) * n0:T, kk * n0: (kk + 1) * n0] nv = n0 if (kk == k - 1): Kx_te = Kx[kk * n0: T, kk * n0: T] Kx_tr = Kx[0: kk * n0, 0: kk * n0] Kx_tr_te = Kx[0:kk * n0, kk * n0: T] nv = T - kk * n0 if (kk < k - 1 and kk > 0): Kx_te = Kx[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kx_tr = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]))] Kx_tr_te = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.arange(kk * n0, (kk + 1) * n0))] nv = n0 n1 = T - nv A = (Kx_te - 1 / (gamma * n1) * Kx_tr_te.T * pdinv( np.mat(np.eye(n1)) + 1 / (gamma * n1) * Kx_tr) * Kx_tr_te) / gamma B = 1 / (gamma * n1) * Kx_tr + np.mat(np.eye(n1)) L = np.linalg.cholesky(B) C = np.sum(np.log(np.diag(L))) # CV = CV + (nv*nv*log(2*pi) + nv*C + nv*mx*log(gamma) + trace(A))/2; CV = CV + (nv * nv * np.log(2 * np.pi) + nv * C + np.trace(A)) / 2 CV = CV / k score = CV # negative cross-validated likelihood return score def local_score_marginal_general(Data, Xi, PAi, parameters): ''' Calculate the local score by negative marginal likelihood based on a regression model in RKHS Parameters ---------- Data: (sample, features) i: current index PAi: parent indexes parameters: None Returns ------- score: local score ''' T = Data.shape[0] X = Data[:, Xi] dX = X.shape[1] # set the kernel for X GX = np.sum(np.multiply(X, X), axis=1) Q = np.tile(GX, (1, T)) R = np.tile(GX.T, (T, 1)) dists = Q + R - 2 * X * X.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) width = width * 2.5 # kernel width theta = 1 / (width ** 2) H = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / T Kx, _ = kernel(X, X, (theta, 1)) Kx = H * Kx * H Thresh = 1E-5 eig_Kx, eix = eigdec((Kx + Kx.T) / 2, np.min([400, math.floor(T / 4)]), evals_only=False) # /2 IIx = np.where(eig_Kx > np.max(eig_Kx) * Thresh)[0] eig_Kx = eig_Kx[IIx] eix = eix[:, IIx] if (len(PAi)): PA = Data[:, PAi] widthPA = np.mat(np.empty((PA.shape[1], 1))) # set the kernel for PA for m in range(PA.shape[1]): G = np.sum((np.multiply(PA[:, m], PA[:, m])), axis=1) Q = np.tile(G, (1, T)) R = np.tile(G.T, (T, 1)) dists = Q + R - 2 * PA[:, m] * PA[:, m].T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) widthPA[m] = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) widthPA = widthPA * 2.5 # kernel width covfunc = np.asarray(['covSum', ['covSEard', 'covNoise']]) logtheta0 = np.vstack([np.log(widthPA), 0, np.log(np.sqrt(0.1))]) logtheta, fvals, iter = minimize(logtheta0, 'gpr_multi_new', -300, covfunc, PA, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0])) nlml, dnlml = gpr_multi_new(logtheta, covfunc, PA, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0]), nargout=2) else: covfunc = np.asarray(['covSum', ['covSEard', 'covNoise']]) PA = np.mat(np.zeros((T, 1))) logtheta0 = np.mat([100, 0, np.log(np.sqrt(0.1))]).T logtheta, fvals, iter = minimize(logtheta0, 'gpr_multi_new', -300, covfunc, PA, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0])) nlml, dnlml = gpr_multi_new(logtheta, covfunc, PA, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0]), nargout=2) score = nlml # negative log-likelihood return score def local_score_marginal_multi(Data, Xi, PAi, parameters): ''' Calculate the local score by negative marginal likelihood based on a regression model in RKHS for variables with multi-variate dimensions Parameters ---------- Data: (sample, features) i: current index PAi: parent indexes parameters: dlabel: for variables with multi-dimensions, indicate which dimensions belong to the i-th variable. Returns ------- score: local score ''' T = Data.shape[0] X = Data[:, parameters['dlabel'][Xi]] dX = X.shape[1] # set the kernel for X GX = np.sum(np.multiply(X, X), axis=1) Q = np.tile(GX, (1, T)) R = np.tile(GX.T, (T, 1)) dists = Q + R - 2 * X * X.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) widthX = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) widthX = widthX * 2.5 # kernel width theta = 1 / (widthX ** 2) H = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / T Kx, _ = kernel(X, X, (theta, 1)) Kx = H * Kx * H Thresh = 1E-5 eig_Kx, eix = eigdec((Kx + Kx.T) / 2, np.min([400, math.floor(T / 4)]), evals_only=False) # /2 IIx = np.where(eig_Kx > np.max(eig_Kx) * Thresh)[0] eig_Kx = eig_Kx[IIx] eix = eix[:, IIx] if (len(PAi)): widthPA_all = np.mat(np.empty((1, 0))) # set the kernel for PA PA_all = np.mat(np.empty((Data.shape[0], 0))) for m in range(len(PAi)): PA = Data[:, parameters['dlabel'][PAi[m]]] PA_all = np.hstack([PA_all, PA]) G = np.sum((np.multiply(PA, PA)), axis=1) Q = np.tile(G, (1, T)) R = np.tile(G.T, (T, 1)) dists = Q + R - 2 * PA * PA.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) widthPA = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) widthPA_all = np.hstack( [widthPA_all, widthPA * np.mat(np.ones((1, np.size(parameters['dlabel'][PAi[m]]))))]) widthPA_all = widthPA_all * 2.5 # kernel width covfunc = np.asarray(['covSum', ['covSEard', 'covNoise']]) logtheta0 = np.vstack([np.log(widthPA_all.T), 0, np.log(np.sqrt(0.1))]) logtheta, fvals, iter = minimize(logtheta0, 'gpr_multi_new', -300, covfunc, PA_all, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0])) nlml, dnlml = gpr_multi_new(logtheta, covfunc, PA_all, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0]), nargout=2) else: covfunc = np.asarray(['covSum', ['covSEard', 'covNoise']]) PA = np.mat(np.zeros((T, 1))) logtheta0 = np.mat([100, 0, np.log(np.sqrt(0.1))]).T logtheta, fvals, iter = minimize(logtheta0, 'gpr_multi_new', -300, covfunc, PA, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0])) nlml, dnlml = gpr_multi_new(logtheta, covfunc, PA, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0]), nargout=2) score = nlml # negative log-likelihood return score

40.484076

115

0.48411

import math import pandas as pd from causallearn.utils.ScoreUtils import * def local_score_BIC(Data, i, PAi, parameters=None): ''' Calculate the *negative* local score with BIC for the linear Gaussian continue data case Parameters ---------- Data: ndarray, (sample, features) i: current index PAi: parent indexes parameters: lambda_value, the penalty discount of bic Returns ------- score: local BIC score ''' if parameters is None: lambda_value = 1 else: lambda_value = parameters['lambda_value'] Data = np.mat(Data) T = Data.shape[0] X = Data[:, i] if len(PAi) != 0: PA = Data[:, PAi] D = PA.shape[1] # derive the parameters by maximum likelihood H = PA * pdinv(PA.T * PA) * PA.T E = X - H * X sigma2 = np.sum(np.power(E, 2)) / T # BIC score = T * np.log(sigma2) + lambda_value * D * np.log(T) else: sigma2 = np.sum(np.power(X, 2)) / T # BIC score = T * np.log(sigma2) return score def local_score_BDeu(Data, i, PAi, parameters=None): ''' Calculate the *negative* local score with BDeu for the discrete case Parameters ---------- Data: (sample, features) i: current index PAi: parent indexes parameters: sample_prior: sample prior structure_prior: structure prior r_i_map: number of states of the finite random variable X_{i} Returns ------- score: local BDeu score ''' if parameters is None: sample_prior = 1 # default sample_prior = 1 structure_prior = 1 # default structure_prior = 1 r_i_map = {i: len(np.unique(np.asarray(Data[:, i]))) for i in range(Data.shape[1])} else: sample_prior = parameters['sample_prior'] structure_prior = parameters['structure_prior'] r_i_map = parameters['r_i_map'] # calculate q_{i} q_i = 1 for pa in PAi: q_i *= r_i_map[pa] if len(PAi) != 0: # calculate N_{ij} names = ['x{}'.format(i) for i in range(Data.shape[1])] Data_pd = pd.DataFrame(Data, columns=names) parant_names = ['x{}'.format(i) for i in PAi] Data_pd_group_Nij = Data_pd.groupby(parant_names) Nij_map = {key: len(Data_pd_group_Nij.indices.get(key)) for key in Data_pd_group_Nij.indices.keys()} Nij_map_keys_list = list(Nij_map.keys()) # calculate N_{ijk} Nijk_map = {ij: Data_pd_group_Nij.get_group(ij).groupby('x{}'.format(i)).apply(len).reset_index() for ij in Nij_map.keys()} for v in Nijk_map.values(): v.columns = ['x{}'.format(i), 'times'] else: # calculate N_{ij} names = ['x{}'.format(i) for i in range(Data.shape[1])] Nij_map = {'': len(Data[:, i])} Nij_map_keys_list = [''] Data_pd = pd.DataFrame(Data, columns=names) # calculate N_{ijk} Nijk_map = {ij: Data_pd.groupby('x{}'.format(i)).apply(len).reset_index() for ij in Nij_map_keys_list} for v in Nijk_map.values(): v.columns = ['x{}'.format(i), 'times'] BDeu_score = 0 # first term vm = Data.shape[0] - 1 BDeu_score += len(PAi) * np.log(structure_prior / vm) + (vm - len(PAi)) * np.log(1 - (structure_prior / vm)) # second term for pa in range(len(Nij_map_keys_list)): Nij = Nij_map.get(Nij_map_keys_list[pa]) first_term = math.lgamma(sample_prior / q_i) - math.lgamma(Nij + sample_prior / q_i) second_term = 0 Nijk_list = Nijk_map.get(Nij_map_keys_list[pa])['times'].to_numpy() for Nijk in Nijk_list: second_term += math.lgamma(Nijk + sample_prior / (r_i_map[i] * q_i)) - math.lgamma( sample_prior / (r_i_map[i] * q_i)) BDeu_score += first_term + second_term return -BDeu_score def local_score_cv_general(Data, Xi, PAi, parameters): ''' Calculate the local score using negative k-fold cross-validated log likelihood as the score based on a regression model in RKHS Parameters ---------- Data: (sample, features) i: current index PAi: parent indexes parameters: kfold: k-fold cross validation lambda: regularization parameter Returns ------- score: local score ''' Data = np.mat(Data) PAi = list(PAi) T = Data.shape[0] X = Data[:, Xi] var_lambda = parameters['lambda'] # regularization parameter k = parameters['kfold'] # k-fold cross validation n0 = math.floor(T / k) gamma = 0.01 Thresh = 1E-5 if (len(PAi)): PA = Data[:, PAi] # set the kernel for X GX = np.sum(np.multiply(X, X), axis=1) Q = np.tile(GX, (1, T)) R = np.tile(GX.T, (T, 1)) dists = Q + R - 2 * X * X.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) # median value width = width * 2 theta = 1 / (width ** 2) Kx, _ = kernel(X, X, (theta, 1)) # Gaussian kernel H0 = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / (T) # for centering of the data in feature space Kx = H0 * Kx * H0 # kernel matrix for X # eig_Kx, eix = eigdec((Kx + Kx.T)/2, np.min([400, math.floor(T/2)]), evals_only=False) # /2 # IIx = np.where(eig_Kx > np.max(eig_Kx) * Thresh)[0] # eig_Kx = eig_Kx[IIx] # eix = eix[:, IIx] # mx = len(IIx) # set the kernel for PA Kpa = np.mat(np.ones((T, T))) for m in range(PA.shape[1]): G = np.sum((np.multiply(PA[:, m], PA[:, m])), axis=1) Q = np.tile(G, (1, T)) R = np.tile(G.T, (T, 1)) dists = Q + R - 2 * PA[:, m] * PA[:, m].T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) # median value width = width * 2 theta = 1 / (width ** 2) Kpa = np.multiply(Kpa, kernel(PA[:, m], PA[:, m], (theta, 1))[0]) H0 = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / (T) # for centering of the data in feature space Kpa = H0 * Kpa * H0 # kernel matrix for PA CV = 0 for kk in range(k): if (kk == 0): Kx_te = Kx[0:n0, 0:n0] Kx_tr = Kx[n0: T, n0: T] Kx_tr_te = Kx[n0: T, 0: n0] Kpa_te = Kpa[0:n0, 0: n0] Kpa_tr = Kpa[n0: T, n0: T] Kpa_tr_te = Kpa[n0: T, 0: n0] nv = n0 # sample size of validated data if (kk == k - 1): Kx_te = Kx[kk * n0:T, kk * n0: T] Kx_tr = Kx[0:kk * n0, 0: kk * n0] Kx_tr_te = Kx[0:kk * n0, kk * n0: T] Kpa_te = Kpa[kk * n0:T, kk * n0: T] Kpa_tr = Kpa[0: kk * n0, 0: kk * n0] Kpa_tr_te = Kpa[0:kk * n0, kk * n0: T] nv = T - kk * n0 if (kk < k - 1 and kk > 0): Kx_te = Kx[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kx_tr = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]))] Kx_tr_te = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.arange(kk * n0, (kk + 1) * n0))] Kpa_te = Kpa[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kpa_tr = Kpa[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]))] Kpa_tr_te = Kpa[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.arange(kk * n0, (kk + 1) * n0))] nv = n0 n1 = T - nv tmp1 = pdinv(Kpa_tr + n1 * var_lambda * np.mat(np.eye(n1))) tmp2 = tmp1 * Kx_tr * tmp1 tmp3 = tmp1 * pdinv(np.mat(np.eye(n1)) + n1 * var_lambda ** 2 / gamma * tmp2) * tmp1 A = (Kx_te + Kpa_tr_te.T * tmp2 * Kpa_tr_te - 2 * Kx_tr_te.T * tmp1 * Kpa_tr_te - n1 * var_lambda ** 2 / gamma * Kx_tr_te.T * tmp3 * Kx_tr_te - n1 * var_lambda ** 2 / gamma * Kpa_tr_te.T * tmp1 * Kx_tr * tmp3 * Kx_tr * tmp1 * Kpa_tr_te + 2 * n1 * var_lambda ** 2 / gamma * Kx_tr_te.T * tmp3 * Kx_tr * tmp1 * Kpa_tr_te) / gamma B = n1 * var_lambda ** 2 / gamma * tmp2 + np.mat(np.eye(n1)) L = np.linalg.cholesky(B) C = np.sum(np.log(np.diag(L))) # CV = CV + (nv*nv*log(2*pi) + nv*C + nv*mx*log(gamma) + trace(A))/2; CV = CV + (nv * nv * np.log(2 * np.pi) + nv * C + np.trace(A)) / 2 CV = CV / k else: # set the kernel for X GX = np.sum(np.multiply(X, X), axis=1) Q = np.tile(GX, (1, T)) R = np.tile(GX.T, (T, 1)) dists = Q + R - 2 * X * X.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) # median value width = width * 2 theta = 1 / (width ** 2) Kx, _ = kernel(X, X, (theta, 1)) # Gaussian kernel H0 = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / (T) # for centering of the data in feature space Kx = H0 * Kx * H0 # kernel matrix for X # eig_Kx, eix = eigdec((Kx + Kx.T) / 2, np.min([400, math.floor(T / 2)]), evals_only=False) # /2 # IIx = np.where(eig_Kx > np.max(eig_Kx) * Thresh)[0] # mx = len(IIx) CV = 0 for kk in range(k): if (kk == 0): Kx_te = Kx[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kx_tr = Kx[(kk + 1) * n0:T, (kk + 1) * n0: T] Kx_tr_te = Kx[(kk + 1) * n0:T, kk * n0: (kk + 1) * n0] nv = n0 if (kk == k - 1): Kx_te = Kx[kk * n0: T, kk * n0: T] Kx_tr = Kx[0: kk * n0, 0: kk * n0] Kx_tr_te = Kx[0:kk * n0, kk * n0: T] nv = T - kk * n0 if (kk < k - 1 and kk > 0): Kx_te = Kx[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kx_tr = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]))] Kx_tr_te = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.arange(kk * n0, (kk + 1) * n0))] nv = n0 n1 = T - nv A = (Kx_te - 1 / (gamma * n1) * Kx_tr_te.T * pdinv( np.mat(np.eye(n1)) + 1 / (gamma * n1) * Kx_tr) * Kx_tr_te) / gamma B = 1 / (gamma * n1) * Kx_tr + np.mat(np.eye(n1)) L = np.linalg.cholesky(B) C = np.sum(np.log(np.diag(L))) # CV = CV + (nv*nv*log(2*pi) + nv*C + nv*mx*log(gamma) + trace(A))/2; CV = CV + (nv * nv * np.log(2 * np.pi) + nv * C + np.trace(A)) / 2 CV = CV / k score = CV # negative cross-validated likelihood return score def local_score_cv_multi(Data, Xi, PAi, parameters): ''' Calculate the local score using negative k-fold cross-validated log likelihood as the score based on a regression model in RKHS for variables with multi-variate dimensions Parameters ---------- Data: (sample, features) i: current index PAi: parent indexes parameters: kfold: k-fold cross validation lambda: regularization parameter dlabel: for variables with multi-dimensions, indicate which dimensions belong to the i-th variable. Returns ------- score: local score ''' T = Data.shape[0] X = Data[:, parameters['dlabel'][Xi]] var_lambda = parameters['lambda'] # regularization parameter k = parameters['kfold'] # k-fold cross validation n0 = math.floor(T / k) gamma = 0.01 Thresh = 1E-5 if (len(PAi)): # set the kernel for X GX = np.sum(np.multiply(X, X), axis=1) Q = np.tile(GX, (1, T)) R = np.tile(GX.T, (T, 1)) dists = Q + R - 2 * X * X.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) # median value width = width * 3 ### theta = 1 / (width ** 2 * X.shape[1]) # Kx, _ = kernel(X, X, (theta, 1)) # Gaussian kernel H0 = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / (T) # for centering of the data in feature space Kx = H0 * Kx * H0 # kernel matrix for X # set the kernel for PA Kpa = np.mat(np.ones((T, T))) for m in range(len(PAi)): PA = Data[:, parameters['dlabel'][PAi[m]]] G = np.sum((np.multiply(PA, PA)), axis=1) Q = np.tile(G, (1, T)) R = np.tile(G.T, (T, 1)) dists = Q + R - 2 * PA * PA.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) # median value width = width * 3 ### theta = 1 / (width ** 2 * PA.shape[1]) Kpa = np.multiply(Kpa, kernel(PA, PA, (theta, 1))[0]) H0 = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / (T) # for centering of the data in feature space Kpa = H0 * Kpa * H0 # kernel matrix for PA CV = 0 for kk in range(k): if (kk == 0): Kx_te = Kx[0:n0, 0:n0] Kx_tr = Kx[n0: T, n0: T] Kx_tr_te = Kx[n0: T, 0: n0] Kpa_te = Kpa[0:n0, 0: n0] Kpa_tr = Kpa[n0: T, n0: T] Kpa_tr_te = Kpa[n0: T, 0: n0] nv = n0 # sample size of validated data if (kk == k - 1): Kx_te = Kx[kk * n0:T, kk * n0: T] Kx_tr = Kx[0:kk * n0, 0: kk * n0] Kx_tr_te = Kx[0:kk * n0, kk * n0: T] Kpa_te = Kpa[kk * n0:T, kk * n0: T] Kpa_tr = Kpa[0: kk * n0, 0: kk * n0] Kpa_tr_te = Kpa[0:kk * n0, kk * n0: T] nv = T - kk * n0 if (kk < k - 1 and kk > 0): Kx_te = Kx[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kx_tr = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]))] Kx_tr_te = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.arange(kk * n0, (kk + 1) * n0))] Kpa_te = Kpa[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kpa_tr = Kpa[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]))] Kpa_tr_te = Kpa[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.arange(kk * n0, (kk + 1) * n0))] nv = n0 n1 = T - nv tmp1 = pdinv(Kpa_tr + n1 * var_lambda * np.mat(np.eye(n1))) tmp2 = tmp1 * Kx_tr * tmp1 tmp3 = tmp1 * pdinv(np.mat(np.eye(n1)) + n1 * var_lambda ** 2 / gamma * tmp2) * tmp1 A = (Kx_te + Kpa_tr_te.T * tmp2 * Kpa_tr_te - 2 * Kx_tr_te.T * tmp1 * Kpa_tr_te - n1 * var_lambda ** 2 / gamma * Kx_tr_te.T * tmp3 * Kx_tr_te - n1 * var_lambda ** 2 / gamma * Kpa_tr_te.T * tmp1 * Kx_tr * tmp3 * Kx_tr * tmp1 * Kpa_tr_te + 2 * n1 * var_lambda ** 2 / gamma * Kx_tr_te.T * tmp3 * Kx_tr * tmp1 * Kpa_tr_te) / gamma B = n1 * var_lambda ** 2 / gamma * tmp2 + np.mat(np.eye(n1)) L = np.linalg.cholesky(B) C = np.sum(np.log(np.diag(L))) # CV = CV + (nv*nv*log(2*pi) + nv*C + nv*mx*log(gamma) + trace(A))/2; CV = CV + (nv * nv * np.log(2 * np.pi) + nv * C + np.trace(A)) / 2 CV = CV / k else: # set the kernel for X GX = np.sum(np.multiply(X, X), axis=1) Q = np.tile(GX, (1, T)) R = np.tile(GX.T, (T, 1)) dists = Q + R - 2 * X * X.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) # median value width = width * 3 ### theta = 1 / (width ** 2 * X.shape[1]) # Kx, _ = kernel(X, X, (theta, 1)) # Gaussian kernel H0 = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / (T) # for centering of the data in feature space Kx = H0 * Kx * H0 # kernel matrix for X CV = 0 for kk in range(k): if (kk == 0): Kx_te = Kx[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kx_tr = Kx[(kk + 1) * n0:T, (kk + 1) * n0: T] Kx_tr_te = Kx[(kk + 1) * n0:T, kk * n0: (kk + 1) * n0] nv = n0 if (kk == k - 1): Kx_te = Kx[kk * n0: T, kk * n0: T] Kx_tr = Kx[0: kk * n0, 0: kk * n0] Kx_tr_te = Kx[0:kk * n0, kk * n0: T] nv = T - kk * n0 if (kk < k - 1 and kk > 0): Kx_te = Kx[kk * n0: (kk + 1) * n0, kk * n0: (kk + 1) * n0] Kx_tr = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]))] Kx_tr_te = Kx[np.ix_(np.concatenate([np.arange(0, kk * n0), np.arange((kk + 1) * n0, T)]), np.arange(kk * n0, (kk + 1) * n0))] nv = n0 n1 = T - nv A = (Kx_te - 1 / (gamma * n1) * Kx_tr_te.T * pdinv( np.mat(np.eye(n1)) + 1 / (gamma * n1) * Kx_tr) * Kx_tr_te) / gamma B = 1 / (gamma * n1) * Kx_tr + np.mat(np.eye(n1)) L = np.linalg.cholesky(B) C = np.sum(np.log(np.diag(L))) # CV = CV + (nv*nv*log(2*pi) + nv*C + nv*mx*log(gamma) + trace(A))/2; CV = CV + (nv * nv * np.log(2 * np.pi) + nv * C + np.trace(A)) / 2 CV = CV / k score = CV # negative cross-validated likelihood return score def local_score_marginal_general(Data, Xi, PAi, parameters): ''' Calculate the local score by negative marginal likelihood based on a regression model in RKHS Parameters ---------- Data: (sample, features) i: current index PAi: parent indexes parameters: None Returns ------- score: local score ''' T = Data.shape[0] X = Data[:, Xi] dX = X.shape[1] # set the kernel for X GX = np.sum(np.multiply(X, X), axis=1) Q = np.tile(GX, (1, T)) R = np.tile(GX.T, (T, 1)) dists = Q + R - 2 * X * X.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) width = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) width = width * 2.5 # kernel width theta = 1 / (width ** 2) H = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / T Kx, _ = kernel(X, X, (theta, 1)) Kx = H * Kx * H Thresh = 1E-5 eig_Kx, eix = eigdec((Kx + Kx.T) / 2, np.min([400, math.floor(T / 4)]), evals_only=False) # /2 IIx = np.where(eig_Kx > np.max(eig_Kx) * Thresh)[0] eig_Kx = eig_Kx[IIx] eix = eix[:, IIx] if (len(PAi)): PA = Data[:, PAi] widthPA = np.mat(np.empty((PA.shape[1], 1))) # set the kernel for PA for m in range(PA.shape[1]): G = np.sum((np.multiply(PA[:, m], PA[:, m])), axis=1) Q = np.tile(G, (1, T)) R = np.tile(G.T, (T, 1)) dists = Q + R - 2 * PA[:, m] * PA[:, m].T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) widthPA[m] = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) widthPA = widthPA * 2.5 # kernel width covfunc = np.asarray(['covSum', ['covSEard', 'covNoise']]) logtheta0 = np.vstack([np.log(widthPA), 0, np.log(np.sqrt(0.1))]) logtheta, fvals, iter = minimize(logtheta0, 'gpr_multi_new', -300, covfunc, PA, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0])) nlml, dnlml = gpr_multi_new(logtheta, covfunc, PA, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0]), nargout=2) else: covfunc = np.asarray(['covSum', ['covSEard', 'covNoise']]) PA = np.mat(np.zeros((T, 1))) logtheta0 = np.mat([100, 0, np.log(np.sqrt(0.1))]).T logtheta, fvals, iter = minimize(logtheta0, 'gpr_multi_new', -300, covfunc, PA, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0])) nlml, dnlml = gpr_multi_new(logtheta, covfunc, PA, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0]), nargout=2) score = nlml # negative log-likelihood return score def local_score_marginal_multi(Data, Xi, PAi, parameters): ''' Calculate the local score by negative marginal likelihood based on a regression model in RKHS for variables with multi-variate dimensions Parameters ---------- Data: (sample, features) i: current index PAi: parent indexes parameters: dlabel: for variables with multi-dimensions, indicate which dimensions belong to the i-th variable. Returns ------- score: local score ''' T = Data.shape[0] X = Data[:, parameters['dlabel'][Xi]] dX = X.shape[1] # set the kernel for X GX = np.sum(np.multiply(X, X), axis=1) Q = np.tile(GX, (1, T)) R = np.tile(GX.T, (T, 1)) dists = Q + R - 2 * X * X.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) widthX = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) widthX = widthX * 2.5 # kernel width theta = 1 / (widthX ** 2) H = np.mat(np.eye(T)) - np.mat(np.ones((T, T))) / T Kx, _ = kernel(X, X, (theta, 1)) Kx = H * Kx * H Thresh = 1E-5 eig_Kx, eix = eigdec((Kx + Kx.T) / 2, np.min([400, math.floor(T / 4)]), evals_only=False) # /2 IIx = np.where(eig_Kx > np.max(eig_Kx) * Thresh)[0] eig_Kx = eig_Kx[IIx] eix = eix[:, IIx] if (len(PAi)): widthPA_all = np.mat(np.empty((1, 0))) # set the kernel for PA PA_all = np.mat(np.empty((Data.shape[0], 0))) for m in range(len(PAi)): PA = Data[:, parameters['dlabel'][PAi[m]]] PA_all = np.hstack([PA_all, PA]) G = np.sum((np.multiply(PA, PA)), axis=1) Q = np.tile(G, (1, T)) R = np.tile(G.T, (T, 1)) dists = Q + R - 2 * PA * PA.T dists = dists - np.tril(dists) dists = np.reshape(dists, (T ** 2, 1)) widthPA = np.sqrt(0.5 * np.median(dists[np.where(dists > 0)], axis=1)[0, 0]) widthPA_all = np.hstack( [widthPA_all, widthPA * np.mat(np.ones((1, np.size(parameters['dlabel'][PAi[m]]))))]) widthPA_all = widthPA_all * 2.5 # kernel width covfunc = np.asarray(['covSum', ['covSEard', 'covNoise']]) logtheta0 = np.vstack([np.log(widthPA_all.T), 0, np.log(np.sqrt(0.1))]) logtheta, fvals, iter = minimize(logtheta0, 'gpr_multi_new', -300, covfunc, PA_all, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0])) nlml, dnlml = gpr_multi_new(logtheta, covfunc, PA_all, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0]), nargout=2) else: covfunc = np.asarray(['covSum', ['covSEard', 'covNoise']]) PA = np.mat(np.zeros((T, 1))) logtheta0 = np.mat([100, 0, np.log(np.sqrt(0.1))]).T logtheta, fvals, iter = minimize(logtheta0, 'gpr_multi_new', -300, covfunc, PA, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0])) nlml, dnlml = gpr_multi_new(logtheta, covfunc, PA, 2 * np.sqrt(T) * eix * np.diag(np.sqrt(eig_Kx)) / np.sqrt(eig_Kx[0]), nargout=2) score = nlml # negative log-likelihood return score

0

2c9f5d52f1b4861421709e07ade22be53a597029

4,882

py

Python

src/data_generation/data_recorder.py

StanfordASL/NASA_ULI_Xplane_Simulator

051fa492b650545442c790cf04a8cdb19632bd02

[ "Apache-2.0" ]

4

2021-06-28T19:13:58.000Z

2021-12-10T03:10:38.000Z

src/data_generation/data_recorder.py

StanfordASL/NASA_ULI_Xplane_Simulator

051fa492b650545442c790cf04a8cdb19632bd02

[ "Apache-2.0" ]

null

src/data_generation/data_recorder.py

StanfordASL/NASA_ULI_Xplane_Simulator

051fa492b650545442c790cf04a8cdb19632bd02

[ "Apache-2.0" ]

1

2021-05-25T20:52:11.000Z

import sys import os # make sure this is a system variable in your bashrc NASA_ULI_ROOT_DIR = os.environ['NASA_ULI_ROOT_DIR'] XPC3_DIR = NASA_ULI_ROOT_DIR + '/src/' sys.path.append(XPC3_DIR) import numpy as np import xpc3 import xpc3_helper import time import os import mss import cv2 import settings screenShot = mss.mss() def record(client, outDir, startPerc = 1.5, endPerc = 10, freq = 10, numEpisodes = 1): """ Record data from training episodes in XPlane into a CSV and PNG files Args: client: XPlane Client outDir: output directory for csv file and png images ----------------- startPerc: percentage down runway to start collecting data endPerc: percentage down runway to finish collecting data (NOTE: this must be less than endPerc for the sinusoidal trajectory) freq: frequency to save data (NOTE: this is approximate due to computational overhead) numEpisodes: number of episodes to record for """ # Make data folder if it doesn't exist if not os.path.exists(outDir): os.makedirs(outDir) # Initialize the CSV file csvFile = outDir + 'labels.csv' with open(csvFile, 'w') as fd: fd.write('image_filename,absolute_time_GMT_seconds,relative_time_seconds,distance_to_centerline_meters,') fd.write('distance_to_centerline_NORMALIZED,downtrack_position_meters,downtrack_position_NORMALIZED,') fd.write('heading_error_degrees,heading_error_NORMALIZED,period_of_day,cloud_type\n') for i in range(numEpisodes): first = True percDownRunway = xpc3_helper.getPercDownRunway(client) currStep = 0 while percDownRunway > endPerc: time.sleep(0.5) percDownRunway = xpc3_helper.getPercDownRunway(client) while percDownRunway < endPerc: if ((percDownRunway > startPerc) and (percDownRunway < 45.0)) or ((percDownRunway > 51.5) and (percDownRunway < endPerc)): if first: startTime = client.getDREF("sim/time/zulu_time_sec")[0] addCurrData(client, outDir, csvFile, startTime, currStep, i + 1) first = False time.sleep(1 / freq) else: addCurrData(client, outDir, csvFile, startTime, currStep, i + 1) time.sleep(1 / freq) currStep += 1 else: time.sleep(1) percDownRunway = xpc3_helper.getPercDownRunway(client) def addCurrData(client, outDir, csvFile, startTime, currStep, episodeNum): """ Add current data to csv file and save off a screenshot Args: client: XPlane Client outDir: output directory for csv file and png images csvFile: name of the CSV file for non-image data (should be initialized already) startTime: absolute time that the episode started currStep: current step of saving data (for image labeling) episodeNum: number of the current episode (for image labeling) """ # Time step information absolute_time = client.getDREF("sim/time/zulu_time_sec")[0] time_step = absolute_time - startTime # Plane state information cte, dtp, he = xpc3_helper.getHomeState(client) # Environmental conditions local_time = client.getDREF("sim/time/local_time_sec")[0] if local_time < 5 * 3600 or local_time > 17 * 3600: period_of_day = 2 time_period = 'night' elif local_time > 12 * 3600 and local_time < 17 * 3600: period_of_day = 1 time_period = 'afternoon' else: period_of_day = 0 time_period = 'morning' cloud_cover = client.getDREF("sim/weather/cloud_type[0]")[0] weather = settings.WEATHER_TYPES[cloud_cover] # Image information img = cv2.cvtColor(np.array(screenShot.grab(settings.MONITOR)), cv2.COLOR_BGRA2BGR)[230:, :, :] img = cv2.resize(img, (settings.WIDTH, settings.HEIGHT)) img_name = 'MWH_Runway04_' + time_period + '_' + weather + '_' + str(episodeNum) + '_' + str(currStep) + '.png' # For now, just save the image to an output directory cv2.imwrite('%s%s' % (outDir, img_name), img) # Append everything to the csv file with open(csvFile, 'a') as fd: fd.write("%s,%f,%f,%f,%f,%f,%f,%f,%f,%d,%d\n" % (img_name, absolute_time, time_step, cte, cte / 10.0, dtp, dtp / 2982.0, he, he / 30.0, period_of_day, cloud_cover)) if __name__ == "__main__": main()

38.440945

134

0.630274

import sys import os # make sure this is a system variable in your bashrc NASA_ULI_ROOT_DIR = os.environ['NASA_ULI_ROOT_DIR'] XPC3_DIR = NASA_ULI_ROOT_DIR + '/src/' sys.path.append(XPC3_DIR) import numpy as np import xpc3 import xpc3_helper import time import os import mss import cv2 import settings screenShot = mss.mss() def main(): with xpc3.XPlaneConnect() as client: record(client, settings.OUT_DIR, endPerc = settings.END_PERC - 1.0, freq=settings.FREQUENCY, numEpisodes=len(settings.CASE_INDS)) def record(client, outDir, startPerc = 1.5, endPerc = 10, freq = 10, numEpisodes = 1): """ Record data from training episodes in XPlane into a CSV and PNG files Args: client: XPlane Client outDir: output directory for csv file and png images ----------------- startPerc: percentage down runway to start collecting data endPerc: percentage down runway to finish collecting data (NOTE: this must be less than endPerc for the sinusoidal trajectory) freq: frequency to save data (NOTE: this is approximate due to computational overhead) numEpisodes: number of episodes to record for """ # Make data folder if it doesn't exist if not os.path.exists(outDir): os.makedirs(outDir) # Initialize the CSV file csvFile = outDir + 'labels.csv' with open(csvFile, 'w') as fd: fd.write('image_filename,absolute_time_GMT_seconds,relative_time_seconds,distance_to_centerline_meters,') fd.write('distance_to_centerline_NORMALIZED,downtrack_position_meters,downtrack_position_NORMALIZED,') fd.write('heading_error_degrees,heading_error_NORMALIZED,period_of_day,cloud_type\n') for i in range(numEpisodes): first = True percDownRunway = xpc3_helper.getPercDownRunway(client) currStep = 0 while percDownRunway > endPerc: time.sleep(0.5) percDownRunway = xpc3_helper.getPercDownRunway(client) while percDownRunway < endPerc: if ((percDownRunway > startPerc) and (percDownRunway < 45.0)) or ((percDownRunway > 51.5) and (percDownRunway < endPerc)): if first: startTime = client.getDREF("sim/time/zulu_time_sec")[0] addCurrData(client, outDir, csvFile, startTime, currStep, i + 1) first = False time.sleep(1 / freq) else: addCurrData(client, outDir, csvFile, startTime, currStep, i + 1) time.sleep(1 / freq) currStep += 1 else: time.sleep(1) percDownRunway = xpc3_helper.getPercDownRunway(client) def addCurrData(client, outDir, csvFile, startTime, currStep, episodeNum): """ Add current data to csv file and save off a screenshot Args: client: XPlane Client outDir: output directory for csv file and png images csvFile: name of the CSV file for non-image data (should be initialized already) startTime: absolute time that the episode started currStep: current step of saving data (for image labeling) episodeNum: number of the current episode (for image labeling) """ # Time step information absolute_time = client.getDREF("sim/time/zulu_time_sec")[0] time_step = absolute_time - startTime # Plane state information cte, dtp, he = xpc3_helper.getHomeState(client) # Environmental conditions local_time = client.getDREF("sim/time/local_time_sec")[0] if local_time < 5 * 3600 or local_time > 17 * 3600: period_of_day = 2 time_period = 'night' elif local_time > 12 * 3600 and local_time < 17 * 3600: period_of_day = 1 time_period = 'afternoon' else: period_of_day = 0 time_period = 'morning' cloud_cover = client.getDREF("sim/weather/cloud_type[0]")[0] weather = settings.WEATHER_TYPES[cloud_cover] # Image information img = cv2.cvtColor(np.array(screenShot.grab(settings.MONITOR)), cv2.COLOR_BGRA2BGR)[230:, :, :] img = cv2.resize(img, (settings.WIDTH, settings.HEIGHT)) img_name = 'MWH_Runway04_' + time_period + '_' + weather + '_' + str(episodeNum) + '_' + str(currStep) + '.png' # For now, just save the image to an output directory cv2.imwrite('%s%s' % (outDir, img_name), img) # Append everything to the csv file with open(csvFile, 'a') as fd: fd.write("%s,%f,%f,%f,%f,%f,%f,%f,%f,%d,%d\n" % (img_name, absolute_time, time_step, cte, cte / 10.0, dtp, dtp / 2982.0, he, he / 30.0, period_of_day, cloud_cover)) if __name__ == "__main__": main()

190

0

23

e9e8e3d3249ddc6a3c68b462aadd0cf70fd33c59

581

py

Python

rsatest.py

PotatoDIY/rsamsg

2e324b9fc37a6bfcd9edf06214def00818e44380

[ "MIT" ]

null

rsatest.py

PotatoDIY/rsamsg

2e324b9fc37a6bfcd9edf06214def00818e44380

[ "MIT" ]

1

2021-04-30T21:03:26.000Z

rsatest.py

PotatoDIY/rsamsg

2e324b9fc37a6bfcd9edf06214def00818e44380

[ "MIT" ]

null

#!/usr/bin/python3 # -*- coding: utf-8 -*- from rsamsg import * #alice and bob #alice_pubkey, alice_privkey=gen() #bob_pubkey, bob_privkey=gen() alice_pubkey = loadfile("keys/alice_pubkey") alice_prikey = loadfile("keys/alice_prikey") bob_pubkey = loadfile("keys/bob_pubkey") bob_prikey = loadfile("keys/bob_prikey") #from alice message = "你好" #to bob crypto,signature=alice_to_bob(message,bob_pubkey,alice_prikey) # bob verify verifyed,msg=bob_get_msg_from_alice(crypto,signature,bob_prikey,alice_pubkey) if(verifyed): print(msg) else: print("err:{}".format(msg))

20.034483

77

0.748709

#!/usr/bin/python3 # -*- coding: utf-8 -*- from rsamsg import * #alice and bob #alice_pubkey, alice_privkey=gen() #bob_pubkey, bob_privkey=gen() alice_pubkey = loadfile("keys/alice_pubkey") alice_prikey = loadfile("keys/alice_prikey") bob_pubkey = loadfile("keys/bob_pubkey") bob_prikey = loadfile("keys/bob_prikey") #from alice message = "你好" #to bob crypto,signature=alice_to_bob(message,bob_pubkey,alice_prikey) # bob verify verifyed,msg=bob_get_msg_from_alice(crypto,signature,bob_prikey,alice_pubkey) if(verifyed): print(msg) else: print("err:{}".format(msg))

0

ab19dd13a41e5770195c38a79129d61c58d261cd

3,338

py

Python

scale/job/tasks/health_task.py

kaydoh/scale

1b6a3b879ffe83e10d3b9d9074835a4c3bf476ee

[ "Apache-2.0" ]

121

2015-11-18T18:15:33.000Z

2022-03-10T01:55:00.000Z

scale/job/tasks/health_task.py

kaydoh/scale

1b6a3b879ffe83e10d3b9d9074835a4c3bf476ee

[ "Apache-2.0" ]

1,415

2015-12-23T23:36:04.000Z

2022-01-07T14:10:09.000Z

scale/job/tasks/health_task.py

kaydoh/scale

1b6a3b879ffe83e10d3b9d9074835a4c3bf476ee

[ "Apache-2.0" ]

66

2015-12-03T20:38:56.000Z

2020-07-27T15:28:11.000Z

"""Defines the class for a node health check task""" from __future__ import unicode_literals import datetime from django.conf import settings from job.tasks.base_task import AtomicCounter from job.tasks.node_task import NodeTask from node.resources.node_resources import NodeResources from node.resources.resource import Cpus, Mem HEALTH_TASK_ID_PREFIX = 'scale_health' COUNTER = AtomicCounter() class HealthTask(NodeTask): """Represents a task that performs a health check on a node. This class is thread-safe. """ BAD_DAEMON_CODE = 2 LOW_DOCKER_SPACE_CODE = 3 BAD_LOGSTASH_CODE = 4 def __init__(self, framework_id, agent_id): """Constructor :param framework_id: The framework ID :type framework_id: string :param agent_id: The agent ID :type agent_id: string """ task_id = '%s_%s_%d' % (HEALTH_TASK_ID_PREFIX, framework_id, COUNTER.get_next()) super(HealthTask, self).__init__(task_id, 'Scale Health Check', agent_id) self._uses_docker = False self._docker_image = None self._docker_params = [] self._is_docker_privileged = False self._running_timeout_threshold = datetime.timedelta(minutes=15) health_check_commands = [] # Check if docker version works (indicates if daemon is working) bad_daemon_check = 'docker version' bad_daemon_check = 'timeout -s SIGKILL 10s %s' % bad_daemon_check # docker version has 10 seconds to succeed bad_daemon_check = '%s; if [[ $? != 0 ]]; then exit %d; fi' % (bad_daemon_check, HealthTask.BAD_DAEMON_CODE) health_check_commands.append(bad_daemon_check) # Check if docker ps works (also indicates if daemon is working) docker_ps_check = 'docker ps' docker_ps_check = 'timeout -s SIGKILL 10s %s' % docker_ps_check # docker ps has 10 seconds to succeed docker_ps_check = '%s; if [[ $? != 0 ]]; then exit %d; fi' % (docker_ps_check, HealthTask.BAD_DAEMON_CODE) health_check_commands.append(docker_ps_check) # Check if Docker disk space is below 1 GiB (assumes /var/lib/docker, ignores check otherwise) get_disk_space = 'df --output=avail /var/lib/docker | tail -1' test_disk_space = 'test `%s` -lt 1048576; if [[ $? == 0 ]]; then exit %d; fi' test_disk_space = test_disk_space % (get_disk_space, HealthTask.LOW_DOCKER_SPACE_CODE) low_docker_space_check = 'if [[ -d /var/lib/docker ]]; then %s; fi' % test_disk_space health_check_commands.append(low_docker_space_check) # Check to ensure that fluentd is reachable if settings.LOGGING_HEALTH_ADDRESS: logging_check = 'timeout -s SIGKILL 5s curl %s; if [[ $? != 0 ]]; then exit %d; fi' logging_check = logging_check % (settings.LOGGING_HEALTH_ADDRESS, HealthTask.BAD_LOGSTASH_CODE) health_check_commands.append(logging_check) self._command = ' && '.join(health_check_commands) # Node task properties self.task_type = 'health-check' self.title = 'Node Health Check' self.description = 'Checks the health status of the node' def get_resources(self): """See :meth:`job.tasks.base_task.Task.get_resources` """ return NodeResources([Cpus(0.1), Mem(32.0)])

40.216867

117

0.679449

"""Defines the class for a node health check task""" from __future__ import unicode_literals import datetime from django.conf import settings from job.tasks.base_task import AtomicCounter from job.tasks.node_task import NodeTask from node.resources.node_resources import NodeResources from node.resources.resource import Cpus, Mem HEALTH_TASK_ID_PREFIX = 'scale_health' COUNTER = AtomicCounter() class HealthTask(NodeTask): """Represents a task that performs a health check on a node. This class is thread-safe. """ BAD_DAEMON_CODE = 2 LOW_DOCKER_SPACE_CODE = 3 BAD_LOGSTASH_CODE = 4 def __init__(self, framework_id, agent_id): """Constructor :param framework_id: The framework ID :type framework_id: string :param agent_id: The agent ID :type agent_id: string """ task_id = '%s_%s_%d' % (HEALTH_TASK_ID_PREFIX, framework_id, COUNTER.get_next()) super(HealthTask, self).__init__(task_id, 'Scale Health Check', agent_id) self._uses_docker = False self._docker_image = None self._docker_params = [] self._is_docker_privileged = False self._running_timeout_threshold = datetime.timedelta(minutes=15) health_check_commands = [] # Check if docker version works (indicates if daemon is working) bad_daemon_check = 'docker version' bad_daemon_check = 'timeout -s SIGKILL 10s %s' % bad_daemon_check # docker version has 10 seconds to succeed bad_daemon_check = '%s; if [[ $? != 0 ]]; then exit %d; fi' % (bad_daemon_check, HealthTask.BAD_DAEMON_CODE) health_check_commands.append(bad_daemon_check) # Check if docker ps works (also indicates if daemon is working) docker_ps_check = 'docker ps' docker_ps_check = 'timeout -s SIGKILL 10s %s' % docker_ps_check # docker ps has 10 seconds to succeed docker_ps_check = '%s; if [[ $? != 0 ]]; then exit %d; fi' % (docker_ps_check, HealthTask.BAD_DAEMON_CODE) health_check_commands.append(docker_ps_check) # Check if Docker disk space is below 1 GiB (assumes /var/lib/docker, ignores check otherwise) get_disk_space = 'df --output=avail /var/lib/docker | tail -1' test_disk_space = 'test `%s` -lt 1048576; if [[ $? == 0 ]]; then exit %d; fi' test_disk_space = test_disk_space % (get_disk_space, HealthTask.LOW_DOCKER_SPACE_CODE) low_docker_space_check = 'if [[ -d /var/lib/docker ]]; then %s; fi' % test_disk_space health_check_commands.append(low_docker_space_check) # Check to ensure that fluentd is reachable if settings.LOGGING_HEALTH_ADDRESS: logging_check = 'timeout -s SIGKILL 5s curl %s; if [[ $? != 0 ]]; then exit %d; fi' logging_check = logging_check % (settings.LOGGING_HEALTH_ADDRESS, HealthTask.BAD_LOGSTASH_CODE) health_check_commands.append(logging_check) self._command = ' && '.join(health_check_commands) # Node task properties self.task_type = 'health-check' self.title = 'Node Health Check' self.description = 'Checks the health status of the node' def get_resources(self): """See :meth:`job.tasks.base_task.Task.get_resources` """ return NodeResources([Cpus(0.1), Mem(32.0)])

0

d997ece80f2c50ef76115ac62ab2023286b010bd

11,486

py

Python

bommerge/bommerge.py

sakoPO/bommerge

88a3697ce03908053c9d7c52fd3f78db0ce52371

[ "BSD-3-Clause" ]

null

bommerge/bommerge.py

sakoPO/bommerge

88a3697ce03908053c9d7c52fd3f78db0ce52371

[ "BSD-3-Clause" ]

null

bommerge/bommerge.py

sakoPO/bommerge

88a3697ce03908053c9d7c52fd3f78db0ce52371

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python try: from components import resistor from components import capacitor from components import voltage from components import tolerance except: from bommerge.components import resistor from bommerge.components import capacitor from bommerge.components import voltage from bommerge.components import tolerance from gui.projectConfigurationWidget import ProjectConfigurationWidget from parsers import csvToJson from utils import files import os from decimal import * try: import Tkinter as tk import ttk except ImportError: import tkinter as tk from tkinter import ttk if __name__ == "__main__": main()

41.168459

133

0.610134

#!/usr/bin/env python try: from components import resistor from components import capacitor from components import voltage from components import tolerance except: from bommerge.components import resistor from bommerge.components import capacitor from bommerge.components import voltage from bommerge.components import tolerance from gui.projectConfigurationWidget import ProjectConfigurationWidget from parsers import csvToJson from utils import files import os from decimal import * try: import Tkinter as tk import ttk except ImportError: import tkinter as tk from tkinter import ttk def loadProject(filename): project = files.load_json_file(filename) project_directory = files.get_directory_from_path(filename) print("Loading project: " + project_directory) for file in project: if not os.path.isabs(file['filename']): file['filename'] = os.path.normpath(os.path.join(project_directory, file['filename'])) print(project) return project def saveProject(filename, project): project_directory = files.get_directory_from_path(filename) for file in project: normalized_path = os.path.normpath(file['filename']) print(normalized_path) file['filename'] = os.path.relpath(normalized_path, project_directory) files.save_json_file(filename, project) def read_configuration(): user_dir = files.get_user_home_directory() configuration_file = user_dir + '/.bommerge/configuration.json' if files.file_exist(configuration_file): configuration = files.load_json_file(configuration_file) token = str(configuration['Distributors']['TME']['token']) app_secret = str(configuration['Distributors']['TME']['app_secret']) tme_config = {'token': token, 'app_secret': app_secret} return tme_config else: print("Unable to read bommerge configuration file. " + str(configuration_file)) def find_component(components_group, group, tme_config): def to_string(case): if case: return case return 'None' from distributor_connector import tme from distributor_connector import partkeepr distributors = [tme.TME(tme_config['token'], tme_config['app_secret']), partkeepr.Partkeepr("https://partkeepr.locallan", "auto", "auto")] for shop in distributors: for component in components_group: if 'Manufacturer Part Number' in component and component['Manufacturer Part Number'] != "": print("Request for " + component['Manufacturer Part Number']) found = shop.find_component(component['Manufacturer Part Number']) else: if group == "Capacitors": print("Request for " + to_string(component['Capacitance']) + " " + to_string( component['Voltage']) + ' ' + to_string(component['Case'])) try: capacitor_parameters = {'Capacitance': capacitor.convert_capacitance_co_farads(component['Capacitance']), 'Case': to_string(component['Case']), 'Voltage': voltage.string_to_voltage(component['Voltage']), 'Dielectric Type': component['Dielectric Type']} found = shop.find_capacitor_by_parameters(capacitor_parameters) if found: for part in found: if 'Voltage' in part['Parameters']: part['Parameters']['Voltage'] = voltage.volts_to_string(part['Parameters']['Voltage']) if 'Capacitance' in part['Parameters']: part['Parameters']['Capacitance'] = capacitor.farads_to_string(part['Parameters']['Capacitance']) except InvalidOperation: print(component) raise elif group == "Resistors": print("Request for " + to_string(component['Resistance']) + ' ' + to_string( component['Case']) + ' ' + to_string(component['Tolerance'])) if component['Resistance'] is None: print("Skipping...") component["Distributors"] = [] continue try: resistor_parameters = {'Resistance': resistor.convert_resistance_to_ohms(component['Resistance']), 'Case': component['Case'], 'Tolerance': tolerance.string_to_tolerance(component['Tolerance'])} found = shop.find_resistor_by_parameters(resistor_parameters) if found: for part in found: if 'Resistance' in part['Parameters']: part['Parameters']['Resistance'] = resistor.ohms_to_string(part['Parameters']['Resistance']) if 'Tolerance' in part['Parameters']: part['Parameters']['Tolerance'] = tolerance.tolerance_to_string(part['Parameters']['Tolerance']) except TypeError: print(component) raise elif group in ["IntegratedCircuits"] and component['Comment'] != '': print("Request for " + to_string(component['Comment'])) found = shop.find_component(component['Comment']) else: found = None if "Distributors" not in component: component["Distributors"] = [] if found: component["Distributors"].append({"Name": shop.name, "Components": found}) def find_component_comment(components_group, tme_config): from distributor_connector import tme shop = tme.tme() for component in components_group: if 'Comment' in component and component['Comment'] != "": print("Request for " + component['Comment']) found = shop.find_component(component['Comment']) if found: print(found) # for component in found['Data']['ProductList']: # print(component['Symbol'] + " : " + component['OriginalSymbol'] + " : " + component['Producer']) # if 'stockAndPrice' in found: # print(found['stockAndPrice']) def ged_distributor_stock(merged, tme_config): for group in merged.keys(): find_component(merged[group], group, tme_config) # find_component(merged["Resistors"]) # find_component_comment(merged["IntegratedCircuits"]) def parse_files_if_needed(project_file_list, destynation): print("Parsing csv files and saving results to: " + destynation) for f in project_file_list: file_path = f['filename'] if files.get_file_extension(file_path) == '.json': files.copy(file_path, destynation + '/' + files.get_filename_from_path(file_path)) else: csvToJson.convert(file_path, destynation) def remove_DNF_and_empty_components(components): to_remove = [] for capacitor in components['Capacitors']: if capacitor['Capacitance'] == 'DNF' or capacitor['Capacitance'] == '': to_remove.append(capacitor) for r in to_remove: components['Capacitors'].remove(r) # Remove empty resistors to_remove = [] for capacitor in components['Resistors']: if capacitor['Resistance'] == 'DNF' or capacitor['Resistance'] == '': to_remove.append(capacitor) for r in to_remove: components['Resistors'].remove(r) return components def mergeProject(project, workingDirectory, nogui): import os import automaticMerger import guiBOM as manual_merger directory = workingDirectory + "/tmp" files.make_directory_if_not_exist(directory) parse_files_if_needed(project, directory) for bom in project: bom['filename'] = os.path.join(directory, files.replace_file_extension(files.get_filename_from_path(bom['filename']), '.json')) components = automaticMerger.merge(project) if nogui is None: root = tk.Tk() root.title("BOM Merger") merger = manual_merger.ManualMerger(root, components) root.mainloop() if merger.result: components = merger.components else: components = None if components: files.save_json_file(os.path.join(directory, 'automerged.json'), components) from exporters import csvExporter csvExporter.save(dict(components), os.path.join(workingDirectory, "mergedBOM.csv")) components = remove_DNF_and_empty_components(components) tme_config = read_configuration() print(tme_config) ged_distributor_stock(components, tme_config) filename = directory + '/merged.json' files.save_json_file(filename, components) from gui import orderingDialog root = tk.Tk() orderingWidget = orderingDialog.OrderWidget(root, filename) root.mainloop() filename = directory + '/order.json' files.save_json_file(filename, orderingWidget.components) if orderingWidget.result: for supplier in orderingWidget.result.keys(): csvExporter.save_list(orderingWidget.result[supplier], workingDirectory + '/' + supplier + '_human_readable.csv') order_list = [] for component in orderingWidget.result[supplier]: order_list.append({'Part number': component['Shop Part Number'], 'Quantity': component['Quantity']}) csvExporter.save_list(order_list, workingDirectory + '/' + supplier + '.csv', write_header=False) class ProjectConfigWidget(ProjectConfigurationWidget): def load_project(self, filename): return loadProject(filename) def save_project_file(self, filename): project = self.files_widget.create_file_list() return saveProject(filename, project) def first_run(): user_dir = files.get_user_home_directory() configuration_file = user_dir + '/.bommerge/configuration.json' return files.file_exist(configuration_file) is False def main(): import argparse parser = argparse.ArgumentParser() parser.add_argument("-p", "--proj", help="Project definition file") parser.add_argument("--nogui", help="Run bommerge without gui, only automatical merge will be performed.") args = parser.parse_args() if first_run(): pass project = None if args.proj: project = loadProject(args.proj) working_directory = files.get_directory_from_path(args.proj) if project is None: projectConfigGui = ProjectConfigWidget() if projectConfigGui.result: working_directory = files.get_directory_from_path(projectConfigGui.result) project = loadProject(projectConfigGui.result) if project: mergeProject(project, working_directory, args.nogui) if __name__ == "__main__": main()

10,434

33

329

d499107a5099731a8a38c060088fba35d321c56e

6,764

py

Python

fairseq/data/token_block_dataset.py

Ruil/fairseq

5cd5c334631a2aca1d3cfaaaddeec1b56df9e0e4

[ "BSD-3-Clause" ]

null

fairseq/data/token_block_dataset.py

Ruil/fairseq

5cd5c334631a2aca1d3cfaaaddeec1b56df9e0e4

[ "BSD-3-Clause" ]

null

fairseq/data/token_block_dataset.py

Ruil/fairseq

5cd5c334631a2aca1d3cfaaaddeec1b56df9e0e4

[ "BSD-3-Clause" ]

null

# Copyright (c) 2017-present, Facebook, Inc. # All rights reserved. # # This source code is licensed under the license found in the LICENSE file in # the root directory of this source tree. An additional grant of patent rights # can be found in the PATENTS file in the same directory. import math import numpy as np import torch from . import FairseqDataset class TokenBlockDataset(FairseqDataset): """Break a Dataset of tokens into blocks. Args: dataset (~torch.utils.data.Dataset): dataset to break into blocks sizes (List[int]): sentence lengths (required for 'complete' and 'eos') block_size (int): maximum block size (ignored in 'eos' break mode) break_mode (str, optional): Mode used for breaking tokens. Values can be one of: - 'none': break tokens into equally sized blocks (up to block_size) - 'complete': break tokens into blocks (up to block_size) such that blocks contains complete sentences, although block_size may be exceeded if some sentences exceed block_size - 'eos': each block contains one sentence (block_size is ignored) include_targets (bool, optional): return next tokens as targets (default: False). """ @property

39.555556

101

0.567859

# Copyright (c) 2017-present, Facebook, Inc. # All rights reserved. # # This source code is licensed under the license found in the LICENSE file in # the root directory of this source tree. An additional grant of patent rights # can be found in the PATENTS file in the same directory. import math import numpy as np import torch from . import FairseqDataset class TokenBlockDataset(FairseqDataset): """Break a Dataset of tokens into blocks. Args: dataset (~torch.utils.data.Dataset): dataset to break into blocks sizes (List[int]): sentence lengths (required for 'complete' and 'eos') block_size (int): maximum block size (ignored in 'eos' break mode) break_mode (str, optional): Mode used for breaking tokens. Values can be one of: - 'none': break tokens into equally sized blocks (up to block_size) - 'complete': break tokens into blocks (up to block_size) such that blocks contains complete sentences, although block_size may be exceeded if some sentences exceed block_size - 'eos': each block contains one sentence (block_size is ignored) include_targets (bool, optional): return next tokens as targets (default: False). """ def __init__(self, dataset, sizes, block_size, pad, eos, break_mode=None, include_targets=False): super().__init__() self.dataset = dataset self.pad = pad self.eos = eos self.include_targets = include_targets self.slice_indices = [] print('sizes: ', sizes) print('len of sizes: ', len(sizes)) assert len(dataset) == len(sizes) sizes = np.array(sizes, dtype=int) if break_mode is None or break_mode == 'none': total_size = sum(sizes) print('total size: ', total_size) #sys.exit() length = math.ceil(total_size / block_size) print('block_size: ', block_size) #sys.exit() def block_at(i): start = i * block_size end = min(start + block_size, total_size) return (start, end) self.slice_indices = [block_at(i) for i in range(length)] #print('self.slice_indices: ', self.slice_indices) #print('len indices: ', len(self.slice_indices)) #sys.exit() elif break_mode == 'complete': tok_idx = 0 sz_idx = 0 curr_size = 0 while sz_idx < len(sizes): if curr_size + sizes[sz_idx] <= block_size or curr_size == 0: curr_size += sizes[sz_idx] sz_idx += 1 else: self.slice_indices.append((tok_idx, tok_idx + curr_size)) tok_idx += curr_size curr_size = 0 if curr_size > 0: self.slice_indices.append((tok_idx, tok_idx + curr_size)) elif break_mode == 'eos': self.slice_indices = np.empty((len(sizes), 2), dtype=int) curr = 0 for i, sz in enumerate(sizes): self.slice_indices[i] = (curr, curr + sz) curr += sz else: raise ValueError('Invalid break_mode: ' + break_mode) self.sizes = np.array([e - s for s, e in self.slice_indices]) #print('self.sizes: ', self.sizes) #sys.exit() self.slice_indices = np.array(self.slice_indices, dtype=int) # build index mapping block indices to the underlying dataset indices self.block_to_dataset_index = np.empty((len(self.slice_indices), 3), dtype=int) ds_idx, ds_remaining = -1, 0 for i, (s, e) in enumerate(self.slice_indices): to_consume = e - s if ds_remaining == 0: ds_idx += 1 ds_remaining = sizes[ds_idx] start_ds_idx = ds_idx start_offset = sizes[ds_idx] - ds_remaining while to_consume > ds_remaining: to_consume -= ds_remaining ds_idx += 1 ds_remaining = sizes[ds_idx] ds_remaining -= to_consume self.block_to_dataset_index[i] = ( start_ds_idx, # starting index in dataset start_offset, # starting offset within starting index ds_idx, # ending index in dataset ) #print('start_ds_idx: ', start_ds_idx) #print('start_offset', start_offset) #print('ds_idx', ds_idx) #sys.exit() #print('len self.slice_indices: ', len(self.slice_indices)) #print('map: ', self.block_to_dataset_index) #sys.exit() assert ds_remaining == 0 assert ds_idx == len(self.dataset) - 1 def __getitem__(self, index): print('len block_to_dataset_index: ', len(self.block_to_dataset_index)) start_ds_idx, start_offset, end_ds_idx = self.block_to_dataset_index[index] buffer = torch.cat([ self.dataset[idx] for idx in range(start_ds_idx, end_ds_idx + 1) ]) slice_s, slice_e = self.slice_indices[index] length = slice_e - slice_s s, e = start_offset, start_offset + length item = buffer[s:e] print('include targets: ', self.include_targets) #sys.exit() if self.include_targets: # *target* is the original sentence (=item) # *source* is rotated left by 1 (maybe left-padded with eos) # *past_target* is rotated left by 2 (left-padded as needed) if s == 0: source = torch.cat([item.new([self.eos]), buffer[0:e - 1]]) past_target = torch.cat([item.new([self.pad, self.eos]), buffer[0:e - 2]]) else: source = buffer[s - 1:e - 1] if s == 1: past_target = torch.cat([item.new([self.eos]), buffer[0:e - 2]]) else: past_target = buffer[s - 2:e - 2] print('idx: ', index) print('target: ', past_target) print('item: ', item) print('source: ', source) return source, item, past_target sys.exit() return item def __len__(self): return len(self.slice_indices) @property def supports_prefetch(self): return getattr(self.dataset, 'supports_prefetch', False) def prefetch(self, indices): self.dataset.prefetch({ ds_idx for index in indices for start_ds_idx, _, end_ds_idx in [self.block_to_dataset_index[index]] for ds_idx in range(start_ds_idx, end_ds_idx + 1) })

5,336

0

134

1bfa0533a1a96ae691f7676df2620d787c8e4bee

358

py

Python

scripts/a3_withdraw_matic.py

PatrickAlphaC/vrf_pizza

c39c03ea707234a814d3d57419111c8e049d87a9

[ "MIT" ]

9

2021-03-13T03:47:12.000Z

2021-09-01T13:49:58.000Z

scripts/a3_withdraw_matic.py

PatrickAlphaC/vrf_pizza

c39c03ea707234a814d3d57419111c8e049d87a9

[ "MIT" ]

1

2021-03-07T21:32:55.000Z

2021-03-29T00:34:22.000Z

scripts/a3_withdraw_matic.py

PatrickAlphaC/vrf_pizza

c39c03ea707234a814d3d57419111c8e049d87a9

[ "MIT" ]

1

2021-09-01T13:49:58.000Z

#!/usr/bin/python3 import os from brownie import VRF_Pizza, VRF_Pizza_RNG, accounts, network, config, interface STATIC_SEED = 123

27.538462

82

0.723464

#!/usr/bin/python3 import os from brownie import VRF_Pizza, VRF_Pizza_RNG, accounts, network, config, interface STATIC_SEED = 123 def main(): dev = accounts.add(os.getenv(config['wallets']['from_key'])) # Get the most recent PriceFeed Object vrf_pizza = VRF_Pizza[len(VRF_Pizza) - 1] vrf_pizza.withdraw(4000000000000000000, {'from': dev})

203

0

23

bc757e04afd30e67cca0d546bb738a5c4acbd1ce

1,460

py

Python

.venv/lib/python3.8/site-packages/vectorbt/utils/math.py

eo1989/VectorBTanalysis

bea3deaf2ee3fc114b308146f2af3e4f35f70197

[ "MIT" ]

null

.venv/lib/python3.8/site-packages/vectorbt/utils/math.py

eo1989/VectorBTanalysis

bea3deaf2ee3fc114b308146f2af3e4f35f70197

[ "MIT" ]

null

.venv/lib/python3.8/site-packages/vectorbt/utils/math.py

eo1989/VectorBTanalysis

bea3deaf2ee3fc114b308146f2af3e4f35f70197

[ "MIT" ]

null

"""Math utilities.""" import numpy as np from numba import njit rel_tol = 1e-10 abs_tol = 0. def is_close(a, b, rel_tol=rel_tol, abs_tol=abs_tol): """Tell whether two values are approximately equal.""" if np.isnan(a) or np.isnan(b): return False if np.isinf(a) or np.isinf(b): return False if a == b: return True return abs(a - b) <= max(rel_tol * max(abs(a), abs(b)), abs_tol) is_close_nb = njit(cache=True)(is_close) """Numba-compiled version of `is_close`.""" def is_close_or_less(a, b, rel_tol=rel_tol, abs_tol=abs_tol): """Tell whether the first value is approximately less than or equal to the second value.""" if is_close(a, b, rel_tol=rel_tol, abs_tol=abs_tol): return True return a < b @njit(cache=True) def is_close_or_less_nb(a, b, rel_tol=rel_tol, abs_tol=abs_tol): """Numba-compiled version of `is_close_or_less`.""" if is_close_nb(a, b, rel_tol=rel_tol, abs_tol=abs_tol): return True return a < b def is_less(a, b, rel_tol=rel_tol, abs_tol=abs_tol): """Tell whether the first value is approximately less than the second value.""" if is_close(a, b, rel_tol=rel_tol, abs_tol=abs_tol): return False return a < b @njit(cache=True) def is_less_nb(a, b, rel_tol=rel_tol, abs_tol=abs_tol): """Numba-compiled version of `is_less`.""" if is_close_nb(a, b, rel_tol=rel_tol, abs_tol=abs_tol): return False return a < b

27.54717

95

0.666438

"""Math utilities.""" import numpy as np from numba import njit rel_tol = 1e-10 abs_tol = 0. def is_close(a, b, rel_tol=rel_tol, abs_tol=abs_tol): """Tell whether two values are approximately equal.""" if np.isnan(a) or np.isnan(b): return False if np.isinf(a) or np.isinf(b): return False if a == b: return True return abs(a - b) <= max(rel_tol * max(abs(a), abs(b)), abs_tol) is_close_nb = njit(cache=True)(is_close) """Numba-compiled version of `is_close`.""" def is_close_or_less(a, b, rel_tol=rel_tol, abs_tol=abs_tol): """Tell whether the first value is approximately less than or equal to the second value.""" if is_close(a, b, rel_tol=rel_tol, abs_tol=abs_tol): return True return a < b @njit(cache=True) def is_close_or_less_nb(a, b, rel_tol=rel_tol, abs_tol=abs_tol): """Numba-compiled version of `is_close_or_less`.""" if is_close_nb(a, b, rel_tol=rel_tol, abs_tol=abs_tol): return True return a < b def is_less(a, b, rel_tol=rel_tol, abs_tol=abs_tol): """Tell whether the first value is approximately less than the second value.""" if is_close(a, b, rel_tol=rel_tol, abs_tol=abs_tol): return False return a < b @njit(cache=True) def is_less_nb(a, b, rel_tol=rel_tol, abs_tol=abs_tol): """Numba-compiled version of `is_less`.""" if is_close_nb(a, b, rel_tol=rel_tol, abs_tol=abs_tol): return False return a < b

0

d3ea9909cecbb0a14b18ea874848473f176f24e3

831

py

Python

tsaotun/lib/Docker/Image/rm.py

qazbnm456/tsaotun

70186faebd5303961d5996c758f7c9147c4439ba

[ "Apache-2.0" ]

47

2017-01-15T08:33:46.000Z

2022-02-11T22:37:48.000Z

tsaotun/lib/Docker/Image/rm.py

qazbnm456/dokcer

70186faebd5303961d5996c758f7c9147c4439ba

[ "Apache-2.0" ]

null

tsaotun/lib/Docker/Image/rm.py

qazbnm456/dokcer

70186faebd5303961d5996c758f7c9147c4439ba

[ "Apache-2.0" ]

2

2017-01-16T13:10:22.000Z

2019-03-28T17:05:04.000Z

"""This module contains `docker image rm` class""" from docker.errors import APIError from .command import Command class Rm(Command): """This class implements `docker image rm` command""" name = "image rm" require = []

24.441176

57

0.54994

"""This module contains `docker image rm` class""" from docker.errors import APIError from .command import Command class Rm(Command): """This class implements `docker image rm` command""" name = "image rm" require = [] def __init__(self): Command.__init__(self) self.settings[self.name] = None def eval_command(self, args): try: Images = [] images = args['images'] del args['images'] for Image in images: Images.append(Image) args['image'] = Image self.client.remove_image(**args) del args['image'] self.settings[self.name] = '\n'.join(Images) except APIError as e: raise e def final(self): return self.settings[self.name]

514

0

81

d7272969a073a6a76d09365b16f3fbe62aad6ad2

22,050

py

Python

vstools/readers.py

libyal/vstools

3e8bb323c4f1b51ff0dc18654707ab44b6bb6cd5

[ "Apache-2.0" ]

3

2017-07-02T11:01:22.000Z

2021-01-31T04:52:58.000Z

vstools/readers.py

libyal/vstools

3e8bb323c4f1b51ff0dc18654707ab44b6bb6cd5

[ "Apache-2.0" ]

7

2017-06-30T08:09:34.000Z

2018-03-22T07:29:51.000Z

vstools/readers.py

libyal/vstools

3e8bb323c4f1b51ff0dc18654707ab44b6bb6cd5

[ "Apache-2.0" ]

1

2017-09-10T07:34:04.000Z

# -*- coding: utf-8 -*- """Project and solution file reader classes.""" import abc import re from vstools import resources class FileReader(object): """File reader.""" def __init__(self, encoding='utf-8'): """Initializes a file reader. Args: encoding (str): encoding. """ super(FileReader, self).__init__() self._encoding = encoding self._file = None self._line = None def _ReadBinaryData(self, size): """Reads binary data. Args: size (int): number of bytes to read. Returns: bytes: binary data. """ return self._file.read(size) def _ReadLine(self, look_ahead=False): """Reads a line. Args: look_ahead (Optional[bool]): indicated if the line should be considered read (False) or not (True). Returns: str: line stripped of leading and trailing white space or None if no input is available. """ if self._line is not None: line = self._line if not look_ahead: self._line = None else: line = self._file.readline() if line: line = line.strip() if look_ahead: self._line = line if isinstance(line, bytes): line = line.decode(self._encoding) return line def Close(self): """Closes the file.""" self._file.close() def Open(self, filename): """Opens the file. Args: filename (str): path of the file. """ self._file = open(filename, 'rb') # pylint: disable=consider-using-with class VSProjectFileReader(FileReader): """Visual Studio project file reader.""" class VS2008ProjectFileReader(VSProjectFileReader): """Visual Studio 2008 project file reader.""" _CONFIGURATION_OPTIONS = { 'CharacterSet': 'character_set', 'ConfigurationType': 'output_type', 'ManagedExtensions': 'managed_extensions', 'WholeProgramOptimization': 'whole_program_optimization', } _TOOL_COMPILER_CONFIGURATION_OPTIONS = { 'AdditionalIncludeDirectories': 'include_directories', 'BasicRuntimeChecks': 'basic_runtime_checks', 'CompileAs': 'compile_as', 'DebugInformationFormat': 'debug_information_format', 'Detect64BitPortabilityProblems': 'detect_64bit_portability_problems', 'EnableFunctionLevelLinking': 'enable_function_level_linking', 'EnableIntrinsicFunctions': 'enable_intrinsic_functions', 'Optimization': 'optimization', 'PreprocessorDefinitions': 'preprocessor_definitions', 'RuntimeLibrary': 'runtime_library', 'SmallerTypeCheck': 'smaller_type_check', 'UsePrecompiledHeader': 'precompiled_header', 'WarnAsError': 'warning_as_error', 'WarningLevel': 'warning_level', } _TOOL_LIBRARIAN_CONFIGURATION_OPTIONS = { 'IgnoreAllDefaultLibraries': 'librarian_ignore_defaults', 'OutputFile': 'librarian_output_file', } _TOOL_LINKER_CONFIGURATION_OPTIONS = { 'AdditionalDependencies': 'additional_dependencies', 'AdditionalLibraryDirectories': 'library_directories', 'DataExecutionPrevention': 'data_execution_prevention', 'EnableCOMDATFolding': 'enable_comdat_folding', 'FixedBaseAddress': 'fixed_base_address', 'GenerateDebugInformation': 'generate_debug_information', 'ImportLibrary': 'linker_values_set', 'LinkIncremental': 'link_incremental', 'ModuleDefinitionFile': 'module_definition_file', 'OptimizeReferences': 'optimize_references', 'OutputDirectory': 'linker_output_directory', 'OutputFile': 'linker_output_file', 'RandomizedBaseAddress': 'randomized_base_address', 'SubSystem': 'sub_system', 'TargetMachine': 'target_machine', } def _ParseConfigurationOption( self, project_configuration, definition, name, line): """Parses a configuration option. Args: project_configuration (VSProjectConfiguration): project configuration. definition (str): definition of the configuration value in file. name (str): name of the configuration value in the project information. line (str): line that contains the configuration value. """ regex_pattern = '{0:s}="([^"]*)"'.format(definition) values = re.findall(regex_pattern, line) if len(values) == 1: setattr(project_configuration, name, values[0]) def _ParseConfigurationOptions( self, project_configuration, configuration_options, line): """Parses configuration options. Args: project_configuration (VSProjectConfiguration): project configuration. configuration_options (dict[str, str]): configuration options defined as a name per definition. line (str): line that contains the configuration value. """ configuration_definition, _, _ = line.partition('=') configuration_value = configuration_options.get( configuration_definition, None) if configuration_value: self._ParseConfigurationOption( project_configuration, configuration_definition, configuration_value, line) def _ReadConfiguration(self, line): """Reads a configuration. Args: line (str): line that contains the start of the configuration section. Returns: VSProjectConfiguration: configuration or None if no configuration was found. """ if not line or not line.startswith('<Configuration'): return None project_configuration = resources.VSProjectConfiguration() found_tool = False found_tool_compiler = False found_tool_librarian = False found_tool_linker = False while line: line = self._ReadLine() if line.startswith('</Configuration>'): break if found_tool: if line.startswith('/>'): found_tool = False found_tool_compiler = False found_tool_librarian = False found_tool_linker = False elif found_tool_compiler: self._ParseConfigurationOptions( project_configuration, self._TOOL_COMPILER_CONFIGURATION_OPTIONS, line) if isinstance( project_configuration.include_directories, str): project_configuration.include_directories = ( project_configuration.include_directories.split(';')) elif found_tool_librarian: self._ParseConfigurationOptions( project_configuration, self._TOOL_LIBRARIAN_CONFIGURATION_OPTIONS, line) elif found_tool_linker: self._ParseConfigurationOptions( project_configuration, self._TOOL_LINKER_CONFIGURATION_OPTIONS, line) additional_dependencies = ( project_configuration.additional_dependencies) if isinstance(additional_dependencies, str): # pylint: disable=no-member additional_dependencies = additional_dependencies.split(' ') project_configuration.additional_dependencies = [] for dependency in additional_dependencies: dependency.replace('$(ConfigurationName)', '$(Configuration)') project_configuration.additional_dependencies.append(dependency) if isinstance( project_configuration.library_directories, str): project_configuration.library_directories = ( project_configuration.library_directories.split(';')) elif line.startswith('Name="VCCLCompilerTool"'): found_tool_compiler = True elif line.startswith('Name="VCLibrarianTool"'): found_tool_librarian = True elif line.startswith('Name="VCLinkerTool"'): found_tool_linker = True elif line.startswith('<Tool'): found_tool = True elif line.startswith('Name='): # For more than 1 match findall will return a list with a tuple. values = re.findall('Name="([^|]*)[|]([^"]*)"', line)[0] if len(values) == 2: project_configuration.name = values[0] project_configuration.platform = values[1] else: self._ParseConfigurationOptions( project_configuration, self._CONFIGURATION_OPTIONS, line) # TODO: PlatformToolset. # TargetFrameworkVersion ? # Add the target machine when not defined. if not project_configuration.target_machine: if project_configuration.platform == 'Win32': project_configuration.target_machine = '1' # TODO: assuming here that 2 is x64. elif project_configuration.platform == 'x64': project_configuration.target_machine = '2' return project_configuration def _ReadConfigurations(self, project_information): """Reads the configurations. Args: project_information (VSProjectInformation): project information. """ # Find the start of the configurations section. result = False line = self._ReadLine() while line: result = line.startswith('<Configurations>') if result: break line = self._ReadLine() if not result: return while line: line = self._ReadLine() if line.startswith('</Configurations>'): break if line.startswith('<Configuration'): project_configuration = self._ReadConfiguration(line) if project_configuration: project_information.configurations.Append(project_configuration) def _ReadFiles(self, project_information): """Reads the files. Args: project_information (VSProjectInformation): project information. """ # Find the start of the files section. result = False line = self._ReadLine() while line: result = line.startswith('<Files>') if result: break line = self._ReadLine() if result: found_filter = False found_filter_source_files = False found_filter_header_files = False found_filter_resource_files = False while line: line = self._ReadLine() if line.startswith('</Files>'): break if found_filter: if line.startswith('</Filter>'): found_filter = False found_filter_source_files = False found_filter_header_files = False found_filter_resource_files = False elif found_filter_source_files: if line.startswith('RelativePath='): values = re.findall('RelativePath="([^"]*)"', line) if len(values) == 1: project_information.source_files.append(values[0]) elif found_filter_header_files: if line.startswith('RelativePath='): values = re.findall('RelativePath="([^"]*)"', line) if len(values) == 1: project_information.header_files.append(values[0]) elif found_filter_resource_files: if line.startswith('RelativePath='): values = re.findall('RelativePath="([^"]*)"', line) if len(values) == 1: project_information.resource_files.append(values[0]) elif line.startswith('Name="Source Files"'): found_filter_source_files = True elif line.startswith('Name="Header Files"'): found_filter_header_files = True elif line.startswith('Name="Resource Files"'): found_filter_resource_files = True elif line.startswith('<Filter'): found_filter = True def _ReadProjectInformation(self, project_information): """Reads project information. Args: project_information (VSProjectInformation): project information. """ line = self._ReadLine() while line: if line.startswith('>'): break if line.startswith('Name='): values = re.findall('Name="([^"]*)"', line) if len(values) == 1: project_information.name = values[0] elif line.startswith('ProjectGUID='): values = re.findall('ProjectGUID="{([^}]*)}"', line) if len(values) == 1: project_information.guid = values[0] elif line.startswith('RootNamespace='): values = re.findall('RootNamespace="([^"]*)"', line) if len(values) == 1: project_information.root_name_space = values[0] elif line.startswith('Keyword='): values = re.findall('Keyword="([^"]*)"', line) if len(values) == 1: project_information.keyword = values[0] line = self._ReadLine() def ReadHeader(self): """Reads a file header. Returns: bool: True if successful or false otherwise. """ # TODO check encoding? line = self._ReadLine() if not line or not line.startswith('<?xml version="1.0"'): return False line = self._ReadLine() if not line or not line.startswith('<VisualStudioProject'): return False line = self._ReadLine() if not line or not line.startswith('ProjectType="Visual C++"'): return False line = self._ReadLine() if not line or not line.startswith('Version="9,00"'): return False return True def ReadProject(self): """Reads the project. Returns: VSProjectInformation: project information if successful or None otherwise. """ project_information = resources.VSProjectInformation() self._ReadProjectInformation(project_information) self._ReadConfigurations(project_information) self._ReadFiles(project_information) return project_information class VS2010ProjectFileReader(VSProjectFileReader): """Visual Studio 2010 project file reader.""" # TODO: implement. class VS2012ProjectFileReader(VSProjectFileReader): """Visual Studio 2012 project file reader.""" # TODO: implement. class VS2013ProjectFileReader(VSProjectFileReader): """Visual Studio 2013 project file reader.""" # TODO: implement. class VS2015ProjectFileReader(VSProjectFileReader): """Visual Studio 2015 project file reader.""" # TODO: implement. class VS2017ProjectFileReader(VSProjectFileReader): """Visual Studio 2017 project file reader.""" # TODO: implement. class VS2019ProjectFileReader(VSProjectFileReader): """Visual Studio 2019 project file reader.""" # TODO: implement. class VSSolutionFileReader(FileReader): """Visual Studio solution file reader.""" # Note that redundant-returns-doc is broken for pylint 1.7.x for abstract # methods # pylint: disable=redundant-returns-doc @abc.abstractmethod def _CheckFormatVersion(self, line): """Checks the format version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ # pylint: disable=unused-argument def _CheckVisualStudioVersion(self, line): """Checks the Visual Studio version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ return False def ReadConfigurations(self): """Reads the configurations. Returns: VSConfigurations: configurations or None if not available. """ solution_configurations = resources.VSConfigurations() line = self._ReadLine(look_ahead=True) if not line or line != 'Global': return None found_section = False line = self._ReadLine() while line and line != 'EndGlobal': line = self._ReadLine() if found_section: if line == 'EndGlobalSection': found_section = False else: # For more than 1 match findall will return a list with a tuple. values = re.findall('([^|]*)[|]([^ ]*) = ([^|]*)[|]([^ ]*)', line) if len(values) == 1: values = values[0] if (len(values) == 4 and values[0] == values[2] and values[1] == values[3]): configuration = resources.VSSolutionConfiguration() configuration.name = values[0] configuration.platform = values[1] solution_configurations.Append(configuration) elif line == ('GlobalSection(SolutionConfigurationPlatforms) = ' 'preSolution'): found_section = True return solution_configurations def ReadHeader(self): """Reads a file header. Returns: bool: True if successful or false otherwise. """ binary_data = self._ReadBinaryData(5) if binary_data != b'\xef\xbb\xbf\r\n': return False line = self._ReadLine() if not line or not line.startswith( 'Microsoft Visual Studio Solution File, Format Version '): return False if not self._CheckFormatVersion(line): return False visual_studio_version_line = None line = self._ReadLine(look_ahead=True) while line: if line.startswith('# Visual C++ '): self._ReadLine() elif line.startswith('VisualStudioVersion = '): visual_studio_version_line = self._ReadLine() else: break line = self._ReadLine(look_ahead=True) if visual_studio_version_line and not self._CheckVisualStudioVersion( visual_studio_version_line): return False return True def ReadProject(self): """Reads a project. Returns: VSSolutionProject: project if successful or None otherwise. """ # 8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942 is a Visual C++ related GUID. line = self._ReadLine(look_ahead=True) if not line or not line.startswith( 'Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = '): return None # For more than 1 match findall will return a list with a tuple. values = re.findall( ('Project\$"{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}"\$ = "([^"]*)", ' '"([^"]*)\\.vcproj", ' '"{([0-9A-F]*-[0-9A-F]*-[0-9A-F]*-[0-9A-F]*-[0-9A-F]*)}"'), line) if len(values) != 1: return None values = values[0] if len(values) != 3: return None solution_project = resources.VSSolutionProject( values[0], values[1], values[2]) found_dependencies = False line = self._ReadLine() while line and line != 'EndProject': line = self._ReadLine() if found_dependencies: if line == 'EndProjectSection': found_dependencies = False else: # The dependencies are defined as: {%GUID%} = {%GUID%} # For more than 1 match findall will return a list with a tuple. guids = re.findall( ('{([0-9A-F]*-[0-9A-F]*-[0-9A-F]*-[0-9A-F]*-[0-9A-F]*)} = ' '{([0-9A-F]*-[0-9A-F]*-[0-9A-F]*-[0-9A-F]*-[0-9A-F]*)}'), line) if len(guids) == 1: guids = guids[0] if len(guids) == 2 and guids[0] == guids[1]: solution_project.AddDependency(guids[0]) elif line == 'ProjectSection(ProjectDependencies) = postProject': found_dependencies = True return solution_project def ReadProjects(self): """Reads the projects. Returns: list[VSSolutionProject]: projects in preserved order. """ solution_projects = [] solution_project = self.ReadProject() while solution_project: solution_projects.append(solution_project) solution_project = self.ReadProject() return solution_projects class VS2008SolutionFileReader(VSSolutionFileReader): """Visual Studio 2008 solution file reader.""" def _CheckFormatVersion(self, line): """Checks the format version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ return line.endswith(' 10.00') class VS2010SolutionFileReader(VSSolutionFileReader): """Visual Studio 2010 solution file reader.""" def _CheckFormatVersion(self, line): """Checks the format version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ return line.endswith(' 11.00') class VS2012SolutionFileReader(VSSolutionFileReader): """Visual Studio 2012 solution file reader.""" def _CheckFormatVersion(self, line): """Checks the format version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ return line.endswith(' 12.00') class VS2013SolutionFileReader(VS2012SolutionFileReader): """Visual Studio 2013 solution file reader.""" def _CheckVisualStudioVersion(self, line): """Checks the Visual Studio version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ version = line.split(' = ')[1] return version.startswith('12.') class VS2015SolutionFileReader(VS2012SolutionFileReader): """Visual Studio 2015 solution file reader.""" def _CheckVisualStudioVersion(self, line): """Checks the Visual Studio version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ version = line.split(' = ')[1] return version.startswith('14.') class VS2017SolutionFileReader(VS2012SolutionFileReader): """Visual Studio 2017 solution file reader.""" def _CheckVisualStudioVersion(self, line): """Checks the Visual Studio version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ version = line.split(' = ')[1] return version.startswith('15.') class VS2019SolutionFileReader(VS2012SolutionFileReader): """Visual Studio 2019 solution file reader.""" def _CheckVisualStudioVersion(self, line): """Checks the Visual Studio version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ version = line.split(' = ')[1] return version.startswith('15.')

28.451613

80

0.651519

# -*- coding: utf-8 -*- """Project and solution file reader classes.""" import abc import re from vstools import resources class FileReader(object): """File reader.""" def __init__(self, encoding='utf-8'): """Initializes a file reader. Args: encoding (str): encoding. """ super(FileReader, self).__init__() self._encoding = encoding self._file = None self._line = None def _ReadBinaryData(self, size): """Reads binary data. Args: size (int): number of bytes to read. Returns: bytes: binary data. """ return self._file.read(size) def _ReadLine(self, look_ahead=False): """Reads a line. Args: look_ahead (Optional[bool]): indicated if the line should be considered read (False) or not (True). Returns: str: line stripped of leading and trailing white space or None if no input is available. """ if self._line is not None: line = self._line if not look_ahead: self._line = None else: line = self._file.readline() if line: line = line.strip() if look_ahead: self._line = line if isinstance(line, bytes): line = line.decode(self._encoding) return line def Close(self): """Closes the file.""" self._file.close() def Open(self, filename): """Opens the file. Args: filename (str): path of the file. """ self._file = open(filename, 'rb') # pylint: disable=consider-using-with class VSProjectFileReader(FileReader): """Visual Studio project file reader.""" class VS2008ProjectFileReader(VSProjectFileReader): """Visual Studio 2008 project file reader.""" _CONFIGURATION_OPTIONS = { 'CharacterSet': 'character_set', 'ConfigurationType': 'output_type', 'ManagedExtensions': 'managed_extensions', 'WholeProgramOptimization': 'whole_program_optimization', } _TOOL_COMPILER_CONFIGURATION_OPTIONS = { 'AdditionalIncludeDirectories': 'include_directories', 'BasicRuntimeChecks': 'basic_runtime_checks', 'CompileAs': 'compile_as', 'DebugInformationFormat': 'debug_information_format', 'Detect64BitPortabilityProblems': 'detect_64bit_portability_problems', 'EnableFunctionLevelLinking': 'enable_function_level_linking', 'EnableIntrinsicFunctions': 'enable_intrinsic_functions', 'Optimization': 'optimization', 'PreprocessorDefinitions': 'preprocessor_definitions', 'RuntimeLibrary': 'runtime_library', 'SmallerTypeCheck': 'smaller_type_check', 'UsePrecompiledHeader': 'precompiled_header', 'WarnAsError': 'warning_as_error', 'WarningLevel': 'warning_level', } _TOOL_LIBRARIAN_CONFIGURATION_OPTIONS = { 'IgnoreAllDefaultLibraries': 'librarian_ignore_defaults', 'OutputFile': 'librarian_output_file', } _TOOL_LINKER_CONFIGURATION_OPTIONS = { 'AdditionalDependencies': 'additional_dependencies', 'AdditionalLibraryDirectories': 'library_directories', 'DataExecutionPrevention': 'data_execution_prevention', 'EnableCOMDATFolding': 'enable_comdat_folding', 'FixedBaseAddress': 'fixed_base_address', 'GenerateDebugInformation': 'generate_debug_information', 'ImportLibrary': 'linker_values_set', 'LinkIncremental': 'link_incremental', 'ModuleDefinitionFile': 'module_definition_file', 'OptimizeReferences': 'optimize_references', 'OutputDirectory': 'linker_output_directory', 'OutputFile': 'linker_output_file', 'RandomizedBaseAddress': 'randomized_base_address', 'SubSystem': 'sub_system', 'TargetMachine': 'target_machine', } def _ParseConfigurationOption( self, project_configuration, definition, name, line): """Parses a configuration option. Args: project_configuration (VSProjectConfiguration): project configuration. definition (str): definition of the configuration value in file. name (str): name of the configuration value in the project information. line (str): line that contains the configuration value. """ regex_pattern = '{0:s}="([^"]*)"'.format(definition) values = re.findall(regex_pattern, line) if len(values) == 1: setattr(project_configuration, name, values[0]) def _ParseConfigurationOptions( self, project_configuration, configuration_options, line): """Parses configuration options. Args: project_configuration (VSProjectConfiguration): project configuration. configuration_options (dict[str, str]): configuration options defined as a name per definition. line (str): line that contains the configuration value. """ configuration_definition, _, _ = line.partition('=') configuration_value = configuration_options.get( configuration_definition, None) if configuration_value: self._ParseConfigurationOption( project_configuration, configuration_definition, configuration_value, line) def _ReadConfiguration(self, line): """Reads a configuration. Args: line (str): line that contains the start of the configuration section. Returns: VSProjectConfiguration: configuration or None if no configuration was found. """ if not line or not line.startswith('<Configuration'): return None project_configuration = resources.VSProjectConfiguration() found_tool = False found_tool_compiler = False found_tool_librarian = False found_tool_linker = False while line: line = self._ReadLine() if line.startswith('</Configuration>'): break if found_tool: if line.startswith('/>'): found_tool = False found_tool_compiler = False found_tool_librarian = False found_tool_linker = False elif found_tool_compiler: self._ParseConfigurationOptions( project_configuration, self._TOOL_COMPILER_CONFIGURATION_OPTIONS, line) if isinstance( project_configuration.include_directories, str): project_configuration.include_directories = ( project_configuration.include_directories.split(';')) elif found_tool_librarian: self._ParseConfigurationOptions( project_configuration, self._TOOL_LIBRARIAN_CONFIGURATION_OPTIONS, line) elif found_tool_linker: self._ParseConfigurationOptions( project_configuration, self._TOOL_LINKER_CONFIGURATION_OPTIONS, line) additional_dependencies = ( project_configuration.additional_dependencies) if isinstance(additional_dependencies, str): # pylint: disable=no-member additional_dependencies = additional_dependencies.split(' ') project_configuration.additional_dependencies = [] for dependency in additional_dependencies: dependency.replace('$(ConfigurationName)', '$(Configuration)') project_configuration.additional_dependencies.append(dependency) if isinstance( project_configuration.library_directories, str): project_configuration.library_directories = ( project_configuration.library_directories.split(';')) elif line.startswith('Name="VCCLCompilerTool"'): found_tool_compiler = True elif line.startswith('Name="VCLibrarianTool"'): found_tool_librarian = True elif line.startswith('Name="VCLinkerTool"'): found_tool_linker = True elif line.startswith('<Tool'): found_tool = True elif line.startswith('Name='): # For more than 1 match findall will return a list with a tuple. values = re.findall('Name="([^|]*)[|]([^"]*)"', line)[0] if len(values) == 2: project_configuration.name = values[0] project_configuration.platform = values[1] else: self._ParseConfigurationOptions( project_configuration, self._CONFIGURATION_OPTIONS, line) # TODO: PlatformToolset. # TargetFrameworkVersion ? # Add the target machine when not defined. if not project_configuration.target_machine: if project_configuration.platform == 'Win32': project_configuration.target_machine = '1' # TODO: assuming here that 2 is x64. elif project_configuration.platform == 'x64': project_configuration.target_machine = '2' return project_configuration def _ReadConfigurations(self, project_information): """Reads the configurations. Args: project_information (VSProjectInformation): project information. """ # Find the start of the configurations section. result = False line = self._ReadLine() while line: result = line.startswith('<Configurations>') if result: break line = self._ReadLine() if not result: return while line: line = self._ReadLine() if line.startswith('</Configurations>'): break if line.startswith('<Configuration'): project_configuration = self._ReadConfiguration(line) if project_configuration: project_information.configurations.Append(project_configuration) def _ReadFiles(self, project_information): """Reads the files. Args: project_information (VSProjectInformation): project information. """ # Find the start of the files section. result = False line = self._ReadLine() while line: result = line.startswith('<Files>') if result: break line = self._ReadLine() if result: found_filter = False found_filter_source_files = False found_filter_header_files = False found_filter_resource_files = False while line: line = self._ReadLine() if line.startswith('</Files>'): break if found_filter: if line.startswith('</Filter>'): found_filter = False found_filter_source_files = False found_filter_header_files = False found_filter_resource_files = False elif found_filter_source_files: if line.startswith('RelativePath='): values = re.findall('RelativePath="([^"]*)"', line) if len(values) == 1: project_information.source_files.append(values[0]) elif found_filter_header_files: if line.startswith('RelativePath='): values = re.findall('RelativePath="([^"]*)"', line) if len(values) == 1: project_information.header_files.append(values[0]) elif found_filter_resource_files: if line.startswith('RelativePath='): values = re.findall('RelativePath="([^"]*)"', line) if len(values) == 1: project_information.resource_files.append(values[0]) elif line.startswith('Name="Source Files"'): found_filter_source_files = True elif line.startswith('Name="Header Files"'): found_filter_header_files = True elif line.startswith('Name="Resource Files"'): found_filter_resource_files = True elif line.startswith('<Filter'): found_filter = True def _ReadProjectInformation(self, project_information): """Reads project information. Args: project_information (VSProjectInformation): project information. """ line = self._ReadLine() while line: if line.startswith('>'): break if line.startswith('Name='): values = re.findall('Name="([^"]*)"', line) if len(values) == 1: project_information.name = values[0] elif line.startswith('ProjectGUID='): values = re.findall('ProjectGUID="{([^}]*)}"', line) if len(values) == 1: project_information.guid = values[0] elif line.startswith('RootNamespace='): values = re.findall('RootNamespace="([^"]*)"', line) if len(values) == 1: project_information.root_name_space = values[0] elif line.startswith('Keyword='): values = re.findall('Keyword="([^"]*)"', line) if len(values) == 1: project_information.keyword = values[0] line = self._ReadLine() def ReadHeader(self): """Reads a file header. Returns: bool: True if successful or false otherwise. """ # TODO check encoding? line = self._ReadLine() if not line or not line.startswith('<?xml version="1.0"'): return False line = self._ReadLine() if not line or not line.startswith('<VisualStudioProject'): return False line = self._ReadLine() if not line or not line.startswith('ProjectType="Visual C++"'): return False line = self._ReadLine() if not line or not line.startswith('Version="9,00"'): return False return True def ReadProject(self): """Reads the project. Returns: VSProjectInformation: project information if successful or None otherwise. """ project_information = resources.VSProjectInformation() self._ReadProjectInformation(project_information) self._ReadConfigurations(project_information) self._ReadFiles(project_information) return project_information class VS2010ProjectFileReader(VSProjectFileReader): """Visual Studio 2010 project file reader.""" # TODO: implement. class VS2012ProjectFileReader(VSProjectFileReader): """Visual Studio 2012 project file reader.""" # TODO: implement. class VS2013ProjectFileReader(VSProjectFileReader): """Visual Studio 2013 project file reader.""" # TODO: implement. class VS2015ProjectFileReader(VSProjectFileReader): """Visual Studio 2015 project file reader.""" # TODO: implement. class VS2017ProjectFileReader(VSProjectFileReader): """Visual Studio 2017 project file reader.""" # TODO: implement. class VS2019ProjectFileReader(VSProjectFileReader): """Visual Studio 2019 project file reader.""" # TODO: implement. class VSSolutionFileReader(FileReader): """Visual Studio solution file reader.""" # Note that redundant-returns-doc is broken for pylint 1.7.x for abstract # methods # pylint: disable=redundant-returns-doc @abc.abstractmethod def _CheckFormatVersion(self, line): """Checks the format version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ # pylint: disable=unused-argument def _CheckVisualStudioVersion(self, line): """Checks the Visual Studio version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ return False def ReadConfigurations(self): """Reads the configurations. Returns: VSConfigurations: configurations or None if not available. """ solution_configurations = resources.VSConfigurations() line = self._ReadLine(look_ahead=True) if not line or line != 'Global': return None found_section = False line = self._ReadLine() while line and line != 'EndGlobal': line = self._ReadLine() if found_section: if line == 'EndGlobalSection': found_section = False else: # For more than 1 match findall will return a list with a tuple. values = re.findall('([^|]*)[|]([^ ]*) = ([^|]*)[|]([^ ]*)', line) if len(values) == 1: values = values[0] if (len(values) == 4 and values[0] == values[2] and values[1] == values[3]): configuration = resources.VSSolutionConfiguration() configuration.name = values[0] configuration.platform = values[1] solution_configurations.Append(configuration) elif line == ('GlobalSection(SolutionConfigurationPlatforms) = ' 'preSolution'): found_section = True return solution_configurations def ReadHeader(self): """Reads a file header. Returns: bool: True if successful or false otherwise. """ binary_data = self._ReadBinaryData(5) if binary_data != b'\xef\xbb\xbf\r\n': return False line = self._ReadLine() if not line or not line.startswith( 'Microsoft Visual Studio Solution File, Format Version '): return False if not self._CheckFormatVersion(line): return False visual_studio_version_line = None line = self._ReadLine(look_ahead=True) while line: if line.startswith('# Visual C++ '): self._ReadLine() elif line.startswith('VisualStudioVersion = '): visual_studio_version_line = self._ReadLine() else: break line = self._ReadLine(look_ahead=True) if visual_studio_version_line and not self._CheckVisualStudioVersion( visual_studio_version_line): return False return True def ReadProject(self): """Reads a project. Returns: VSSolutionProject: project if successful or None otherwise. """ # 8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942 is a Visual C++ related GUID. line = self._ReadLine(look_ahead=True) if not line or not line.startswith( 'Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = '): return None # For more than 1 match findall will return a list with a tuple. values = re.findall( ('Project\$"{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}"\$ = "([^"]*)", ' '"([^"]*)\\.vcproj", ' '"{([0-9A-F]*-[0-9A-F]*-[0-9A-F]*-[0-9A-F]*-[0-9A-F]*)}"'), line) if len(values) != 1: return None values = values[0] if len(values) != 3: return None solution_project = resources.VSSolutionProject( values[0], values[1], values[2]) found_dependencies = False line = self._ReadLine() while line and line != 'EndProject': line = self._ReadLine() if found_dependencies: if line == 'EndProjectSection': found_dependencies = False else: # The dependencies are defined as: {%GUID%} = {%GUID%} # For more than 1 match findall will return a list with a tuple. guids = re.findall( ('{([0-9A-F]*-[0-9A-F]*-[0-9A-F]*-[0-9A-F]*-[0-9A-F]*)} = ' '{([0-9A-F]*-[0-9A-F]*-[0-9A-F]*-[0-9A-F]*-[0-9A-F]*)}'), line) if len(guids) == 1: guids = guids[0] if len(guids) == 2 and guids[0] == guids[1]: solution_project.AddDependency(guids[0]) elif line == 'ProjectSection(ProjectDependencies) = postProject': found_dependencies = True return solution_project def ReadProjects(self): """Reads the projects. Returns: list[VSSolutionProject]: projects in preserved order. """ solution_projects = [] solution_project = self.ReadProject() while solution_project: solution_projects.append(solution_project) solution_project = self.ReadProject() return solution_projects class VS2008SolutionFileReader(VSSolutionFileReader): """Visual Studio 2008 solution file reader.""" def _CheckFormatVersion(self, line): """Checks the format version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ return line.endswith(' 10.00') class VS2010SolutionFileReader(VSSolutionFileReader): """Visual Studio 2010 solution file reader.""" def _CheckFormatVersion(self, line): """Checks the format version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ return line.endswith(' 11.00') class VS2012SolutionFileReader(VSSolutionFileReader): """Visual Studio 2012 solution file reader.""" def _CheckFormatVersion(self, line): """Checks the format version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ return line.endswith(' 12.00') class VS2013SolutionFileReader(VS2012SolutionFileReader): """Visual Studio 2013 solution file reader.""" def _CheckVisualStudioVersion(self, line): """Checks the Visual Studio version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ version = line.split(' = ')[1] return version.startswith('12.') class VS2015SolutionFileReader(VS2012SolutionFileReader): """Visual Studio 2015 solution file reader.""" def _CheckVisualStudioVersion(self, line): """Checks the Visual Studio version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ version = line.split(' = ')[1] return version.startswith('14.') class VS2017SolutionFileReader(VS2012SolutionFileReader): """Visual Studio 2017 solution file reader.""" def _CheckVisualStudioVersion(self, line): """Checks the Visual Studio version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ version = line.split(' = ')[1] return version.startswith('15.') class VS2019SolutionFileReader(VS2012SolutionFileReader): """Visual Studio 2019 solution file reader.""" def _CheckVisualStudioVersion(self, line): """Checks the Visual Studio version. Args: line (str): line containing the Visual Studio format version. Returns: bool: True if successful or false otherwise. """ version = line.split(' = ')[1] return version.startswith('15.')

0

9103dc90b43809f95c0f53e862bd0ec25567ff06

14,802

py

Python

tests/test_cli.py

jhermann/pip-upgrader

ba8613d47cd91f1e1f4ae546c561eb030ba5ddf8

[ "Apache-2.0" ]

null

tests/test_cli.py

jhermann/pip-upgrader

ba8613d47cd91f1e1f4ae546c561eb030ba5ddf8

[ "Apache-2.0" ]

null

tests/test_cli.py

jhermann/pip-upgrader

ba8613d47cd91f1e1f4ae546c561eb030ba5ddf8

[ "Apache-2.0" ]

null

from __future__ import unicode_literals from subprocess import PIPE, Popen as popen from unittest import TestCase import responses from packaging.utils import canonicalize_name from pip_upgrader import __version__ as VERSION from pip_upgrader import cli from pip_upgrader.packages_status_detector import PackagesStatusDetector try: from unittest.mock import patch except ImportError: from mock import patch try: from io import StringIO except ImportError: # pragma: nocover from cStringIO import StringIO @patch('pip_upgrader.packages_interactive_selector.user_input', return_value='all') @patch('pip_upgrader.virtualenv_checker.is_virtualenv', return_value=True)

45.128049

119

0.657344

from __future__ import unicode_literals from subprocess import PIPE, Popen as popen from unittest import TestCase import responses from packaging.utils import canonicalize_name from pip_upgrader import __version__ as VERSION from pip_upgrader import cli from pip_upgrader.packages_status_detector import PackagesStatusDetector try: from unittest.mock import patch except ImportError: from mock import patch try: from io import StringIO except ImportError: # pragma: nocover from cStringIO import StringIO class TestHelp(TestCase): def test_returns_usage_information(self): output = popen(['pip-upgrade', '-h'], stdout=PIPE).communicate()[0] self.assertTrue('Usage:' in output.decode('utf-8')) output = popen(['pip-upgrade', '--help'], stdout=PIPE).communicate()[0] self.assertTrue('Usage:' in output.decode('utf-8')) class TestVersion(TestCase): def test_returns_version_information(self): output = popen(['pip-upgrade', '--version'], stdout=PIPE).communicate()[0] self.assertEqual(output.strip().decode('utf-8'), VERSION) @patch('pip_upgrader.packages_interactive_selector.user_input', return_value='all') @patch('pip_upgrader.virtualenv_checker.is_virtualenv', return_value=True) class TestCommand(TestCase): def _add_responses_mocks(self): for package in ['Django', 'celery', 'django-rest-auth', 'ipython']: with open('tests/fixtures/{}.json'.format(package)) as fh: body = fh.read() responses.add(responses.GET, "https://pypi.python.org/pypi/{}/json".format(package), body=body, content_type="application/json") with open('tests/fixtures/{}.html'.format(canonicalize_name(package))) as fh: body_html = fh.read() responses.add(responses.GET, "https://pypi.python.org/simple/{}".format(canonicalize_name(package)), body=body_html) def setUp(self): self._add_responses_mocks() @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '-p': []}) def test_command_basic_usage(self, options_mock, is_virtualenv_mock, user_input_mock): with patch('sys.stdout', new_callable=StringIO) as stdout_mock: cli.main() output = stdout_mock.getvalue() self.assertTrue(user_input_mock.called) self.assertIn('Available upgrades', output) self.assertIn('ipython ... up to date', output) self.assertIn('django-rest-auth ... upgrade available: 0.9.0 ==>', output) self.assertNotIn('ipdb', output) self.assertIn('Successfully upgraded', output) self.assertIn('this was a simulation using --dry-run', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '-p': []}) def test_command_simple_html_index_url(self, options_mock, is_virtualenv_mock, user_input_mock): with patch('sys.stdout', new_callable=StringIO) as stdout_mock, \ patch('pip_upgrader.packages_status_detector.PackagesStatusDetector.pip_config_locations', new=PackagesStatusDetector.pip_config_locations + ['pip.test.conf']): cli.main() output = stdout_mock.getvalue() self.assertTrue(user_input_mock.called) # checks if new index-url was discovered from config file self.assertIn('Setting API url', output) self.assertIn('https://pypi.python.org/simple/{package}', output) self.assertIn('Available upgrades', output) self.assertIn('ipython ... up to date', output) self.assertIn('django-rest-auth ... upgrade available: 0.9.0 ==>', output) self.assertNotIn('ipdb', output) self.assertIn('Successfully upgraded', output) self.assertIn('this was a simulation using --dry-run', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '-p': []}) @patch.dict('os.environ', {'PIP_INDEX_URL': 'https://pypi.python.org/simple/'}) def test_command_pip_index_url_environ(self, options_mock, is_virtualenv_mock, user_input_mock): with patch('sys.stdout', new_callable=StringIO) as stdout_mock: cli.main() output = stdout_mock.getvalue() self.assertTrue(user_input_mock.called) # checks if new index-url was discovered from config file self.assertIn('Setting API url', output) self.assertIn('https://pypi.python.org/simple/{package}', output) self.assertIn('Available upgrades', output) self.assertIn('ipython ... up to date', output) self.assertIn('django-rest-auth ... upgrade available: 0.9.0 ==>', output) self.assertNotIn('ipdb', output) self.assertIn('Successfully upgraded', output) self.assertIn('this was a simulation using --dry-run', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '-p': [], '--use-default-index': True}) def test_command__use_default_index(self, options_mock, is_virtualenv_mock, user_input_mock): with patch('sys.stdout', new_callable=StringIO) as stdout_mock, \ patch('pip_upgrader.packages_status_detector.PackagesStatusDetector.pip_config_locations', new=PackagesStatusDetector.pip_config_locations + ['pip.test.conf']): cli.main() output = stdout_mock.getvalue() # checks if new index-url was discovered from config file self.assertNotIn('Setting API url', output) self.assertIn('Successfully upgraded', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '-p': []}) def test_command_interactive_bad_choices(self, options_mock, is_virtualenv_mock, user_input_mock): user_input_mock.return_value = '' with patch('sys.stdout', new_callable=StringIO) as stdout_mock: cli.main() output = stdout_mock.getvalue() self.assertTrue(user_input_mock.called) self.assertIn('No choice selected', output) self.assertNotIn('Setting API url', output) user_input_mock.return_value = '5 6 7' with patch('sys.stdout', new_callable=StringIO) as stdout_mock: cli.main() output = stdout_mock.getvalue() self.assertTrue(user_input_mock.called) self.assertIn('No valid choice selected.', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '-p': ['all']}) def test_command_not_interactive_all_packages(self, options_mock, is_virtualenv_mock, user_input_mock): with patch('sys.stdout', new_callable=StringIO) as stdout_mock: cli.main() output = stdout_mock.getvalue() # no user_input should be called self.assertFalse(user_input_mock.called) self.assertNotIn('Setting API url', output) self.assertNotIn('Available upgrades', output) self.assertIn('Django ... upgrade available: 1.10 ==>', output) self.assertIn('django-rest-auth ... upgrade available: 0.9.0 ==>', output) self.assertIn('ipython ... up to date', output) self.assertNotIn('ipdb', output) self.assertIn('celery ... upgrade available: 3.1.1 ==>', output) self.assertIn('Successfully upgraded', output) self.assertIn('this was a simulation using --dry-run', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '-p': ['django', 'bad_package']}) def test_command_not_interactive_specific_package(self, options_mock, is_virtualenv_mock, user_input_mock): with patch('sys.stdout', new_callable=StringIO) as stdout_mock: cli.main() output = stdout_mock.getvalue() # no user_input should be called self.assertFalse(user_input_mock.called) self.assertNotIn('Setting API url', output) self.assertIn('Django ... upgrade available: 1.10 ==>', output) self.assertNotIn('django-rest-auth', output) self.assertNotIn('ipython ... up to date', output) self.assertNotIn('ipdb', output) self.assertNotIn('celery ... upgrade available: 3.1.1 ==>', output) self.assertIn('Successfully upgraded', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '-p': ['ipython']}) def test_command_not_interactive_all_packages_up_to_date(self, options_mock, is_virtualenv_mock, user_input_mock): with patch('sys.stdout', new_callable=StringIO) as stdout_mock: cli.main() output = stdout_mock.getvalue() # no user_input should be called self.assertFalse(user_input_mock.called) self.assertNotIn('Setting API url', output) self.assertIn('All packages are up-to-date.', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '-p': ['all'], '<requirements_file>': ['requirements/production.txt']}) def test_command_not_interactive_explicit_requirements(self, options_mock, is_virtualenv_mock, user_input_mock): with patch('sys.stdout', new_callable=StringIO) as stdout_mock: cli.main() output = stdout_mock.getvalue() # no user_input should be called self.assertFalse(user_input_mock.called) self.assertNotIn('Setting API url', output) self.assertNotIn('Django ... upgrade available: 1.10 ==>', output) self.assertNotIn('django-rest-auth', output) self.assertNotIn('ipython ... up to date', output) self.assertNotIn('ipdb', output) self.assertIn('celery ... upgrade available: 3.1.1 ==>', output) self.assertIn('Successfully upgraded', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '-p': ['all'], '<requirements_file>': ['requirements/local.txt']}) def test_command_not_recursive_requirements_include(self, options_mock, is_virtualenv_mock, user_input_mock): with patch('sys.stdout', new_callable=StringIO) as stdout_mock: cli.main() output = stdout_mock.getvalue() # no user_input should be called self.assertFalse(user_input_mock.called) self.assertIn('celery ... upgrade available: 3.1.1 ==>', output) self.assertIn('requirements/local.txt', output) self.assertIn('requirements/production.txt', output) self.assertIn('requirements/extra/debug.txt', output) self.assertIn('requirements/extra/debug2.txt', output) self.assertNotIn('requirements/extra/bad_file.txt', output) self.assertIn('Successfully upgraded', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '-p': ['django'], '--prerelease': True}) def test_command_not_specific_package_prerelease(self, options_mock, is_virtualenv_mock, user_input_mock): with patch('sys.stdout', new_callable=StringIO) as stdout_mock: cli.main() output = stdout_mock.getvalue() # no user_input should be called self.assertFalse(user_input_mock.called) self.assertNotIn('Setting API url', output) self.assertIn('Django ... upgrade available: 1.10 ==> 1.11rc1', output) self.assertNotIn('django-rest-auth', output) self.assertNotIn('ipython ... up to date', output) self.assertNotIn('ipdb', output) self.assertNotIn('celery ... upgrade available: 3.1.1 ==>', output) self.assertIn('Successfully upgraded', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '-p': ['django'], '--prerelease': True}) def test_command_not_specific_package_prerelease_html_api(self, options_mock, is_virtualenv_mock, user_input_mock): with patch('sys.stdout', new_callable=StringIO) as stdout_mock, \ patch('pip_upgrader.packages_status_detector.PackagesStatusDetector.pip_config_locations', new=PackagesStatusDetector.pip_config_locations + ['pip.test.conf']): cli.main() output = stdout_mock.getvalue() # no user_input should be called self.assertFalse(user_input_mock.called) self.assertIn('Setting API url', output) self.assertIn('Django ... upgrade available: 1.10 ==> 1.11rc1', output) self.assertNotIn('django-rest-auth', output) self.assertNotIn('ipython ... up to date', output) self.assertNotIn('ipdb', output) self.assertNotIn('celery ... upgrade available: 3.1.1 ==>', output) self.assertIn('Successfully upgraded', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '--skip-virtualenv-check': False, '-p': ['django']}) def test_command_not_interactive_not_virtualenv(self, options_mock, is_virtualenv_mock, user_input_mock): is_virtualenv_mock.return_value = False with patch('sys.stdout', new_callable=StringIO) as stdout_mock: cli.main() output = stdout_mock.getvalue() self.assertNotIn('Setting API url', output) self.assertIn("It seems you haven't activated a virtualenv", output) self.assertNotIn('Successfully upgraded', output) @responses.activate @patch('pip_upgrader.cli.get_options', return_value={'--dry-run': True, '--skip-virtualenv-check': True, '-p': ['django']}) def test_command_not_interactive_not_virtualenv_skip(self, options_mock, is_virtualenv_mock, user_input_mock): is_virtualenv_mock.return_value = False with patch('sys.stdout', new_callable=StringIO) as stdout_mock: cli.main() output = stdout_mock.getvalue() self.assertFalse(user_input_mock.called) self.assertNotIn('Setting API url', output) self.assertIn('Django ... upgrade available: 1.10 ==>', output) self.assertNotIn('django-rest-auth', output) self.assertNotIn('ipython ... up to date', output) self.assertNotIn('ipdb', output) self.assertNotIn('celery ... upgrade available: 3.1.1 ==>', output) self.assertIn('Successfully upgraded', output)

11,349

2,642

120

3762dac387dc47cb0414df8d63924698e9c65760

559

py

Python

code/wind-analysis/complete/wind-reducer-max.py

cssherry/ox-clo

4c771048f8b02639c7ac9e3609b92f08a2a345c1

[ "CC0-1.0" ]

null

code/wind-analysis/complete/wind-reducer-max.py

cssherry/ox-clo

4c771048f8b02639c7ac9e3609b92f08a2a345c1

[ "CC0-1.0" ]

null

code/wind-analysis/complete/wind-reducer-max.py

cssherry/ox-clo

4c771048f8b02639c7ac9e3609b92f08a2a345c1

[ "CC0-1.0" ]

null

#! /usr/bin/env python import sys speeds = dict() # counts = dict() # need this for extension for line in sys.stdin: try: line = line.strip() station, speed = line.split('\t') speed = float(speed) # Add code here to use the data if station in speeds: if speeds[station] < speed: speeds[station] = speed else: speeds[station] = speed except ValueError: pass for k, v in speeds.iteritems(): result = [k,str(v)] print ('\t'.join(result)) # add code here to output the results

17.46875

39

0.593918

#! /usr/bin/env python import sys speeds = dict() # counts = dict() # need this for extension for line in sys.stdin: try: line = line.strip() station, speed = line.split('\t') speed = float(speed) # Add code here to use the data if station in speeds: if speeds[station] < speed: speeds[station] = speed else: speeds[station] = speed except ValueError: pass for k, v in speeds.iteritems(): result = [k,str(v)] print ('\t'.join(result)) # add code here to output the results

0

9e57b930e0dbd8dcbcf97bd5461976d81c31f4a1

25,064

py

Python

pointnav_vo/vo/dataset/regression_geo_invariance_iter_dataset.py

rxlqn/PointNav-VO

6f7672482a3f1628a3b11025709518ee166e812b

[ "Apache-2.0" ]

25

2021-08-28T04:06:31.000Z

2022-03-02T23:03:13.000Z

pointnav_vo/vo/dataset/regression_geo_invariance_iter_dataset.py

rxlqn/PointNav-VO

6f7672482a3f1628a3b11025709518ee166e812b

[ "Apache-2.0" ]

11

2021-10-01T07:03:11.000Z

2022-03-26T02:28:44.000Z

pointnav_vo/vo/dataset/regression_geo_invariance_iter_dataset.py

rxlqn/PointNav-VO

6f7672482a3f1628a3b11025709518ee166e812b

[ "Apache-2.0" ]

5

2021-09-01T09:05:42.000Z

2022-01-27T10:11:37.000Z

#! /usr/bin/env python import os import h5py import random import time import copy import numpy as np from tqdm import tqdm from collections import OrderedDict, defaultdict import torch import torch.nn as nn from torch.utils.data import Dataset, IterableDataset from habitat import logger from habitat.utils.geometry_utils import ( quaternion_from_coeff, agent_state_target2ref, ) from pointnav_vo.utils.geometry_utils import ( quaternion_to_array, NormalizedDepth2TopDownViewHabitat, NormalizedDepth2TopDownViewHabitatTorch, ) from pointnav_vo.vo.dataset.regression_iter_dataset import BaseRegressionDataset from pointnav_vo.vo.common.common_vars import * FloatTensor = torch.FloatTensor class StatePairRegressionDataset(BaseRegressionDataset): r"""Data loader for state-pairs from Habitat simularo. """ def __init__( self, eval_flag=False, data_file=None, num_workers=0, act_type=-1, vis_size_w=256, vis_size_h=256, collision="-1", discretize_depth="none", discretized_depth_channels=0, gen_top_down_view=False, top_down_view_infos={}, geo_invariance_types=[], partial_data_n_splits=1, # data_aug=False, ): f"""Valid combination of action and geometric consistency types are: left OR right |-- inverse_data_augment_only left AND right |-- inverse_joint_train """ assert ( np.sum( [ "inverse_data_augment_only" in geo_invariance_types, "inverse_joint_train" in geo_invariance_types, ] ) <= 1 ), f"inverse_data_augment_only and inverse_joint_train should not appear together." if "inverse_joint_train" in geo_invariance_types: assert ( isinstance(act_type, list) and set(act_type) == set([TURN_LEFT, TURN_RIGHT]) ) or ( isinstance(act_type, int) and act_type == -1 ), f"When enabling joint-training with geometric inversion, action types must be [left, right] OR -1." else: assert isinstance(act_type, int) if "inverse_data_augment_only" in geo_invariance_types: assert ( act_type != MOVE_FORWARD ), f"Data augmentation for geometric consistency about inversion is not suitable for forward action." self._eval = eval_flag self._data_f = data_file self._num_workers = num_workers self._act_type = act_type self._collision = collision self._geo_invariance_types = geo_invariance_types self._len = 0 self._act_left_right_len = 0 self._vis_size_w = vis_size_w self._vis_size_h = vis_size_h self._partial_data_n_splits = partial_data_n_splits self._gen_top_down_view = gen_top_down_view self._top_down_view_infos = top_down_view_infos # RGB stored with uint8 self._rgb_pair_size = 2 * self._vis_size_w * self._vis_size_h * 3 # Depth stored with float16 self._depth_pair_size = 2 * self._vis_size_w * self._vis_size_h * 2 with h5py.File(data_file, "r", libver="latest") as f: self._chunk_size = f[list(f.keys())[0]]["prev_rgbs"].shape[0] # for rgb + depth self._chunk_bytes = int( np.ceil((self._rgb_pair_size + self._depth_pair_size) * self._chunk_size) ) # for misc information self._chunk_bytes += 20 * 2 logger.info(f"\nDataset: chunk bytes {self._chunk_bytes / (1024 * 1024)} MB\n") self._discretize_depth = discretize_depth self._discretized_depth_channels = discretized_depth_channels if self._discretize_depth == "hard": self._discretized_depth_end_vals = [] for i in np.arange(self._discretized_depth_channels): self._discretized_depth_end_vals.append( i * 1.0 / self._discretized_depth_channels ) self._discretized_depth_end_vals.append(1.0) logger.info("Get index mapping from h5py ...") all_chunk_keys = [] with h5py.File(data_file, "r", libver="latest") as f: for chunk_k in tqdm(sorted(f.keys())): all_chunk_keys.append(chunk_k) valid_idxes, transform_idxes = self._get_valid_idxes(f, chunk_k) self._len += len(valid_idxes) logger.info("... done.\n") if not self._eval: random.shuffle(all_chunk_keys) if num_workers == 0: # no separate worker self._chunk_splits = all_chunk_keys elif num_workers > 0: self._chunk_splits = defaultdict(list) for i, chunk_k in enumerate(all_chunk_keys): self._chunk_splits[i % num_workers].append(chunk_k) else: raise ValueError @property @property @property @property

38.56

148

0.615385

#! /usr/bin/env python import os import h5py import random import time import copy import numpy as np from tqdm import tqdm from collections import OrderedDict, defaultdict import torch import torch.nn as nn from torch.utils.data import Dataset, IterableDataset from habitat import logger from habitat.utils.geometry_utils import ( quaternion_from_coeff, agent_state_target2ref, ) from pointnav_vo.utils.geometry_utils import ( quaternion_to_array, NormalizedDepth2TopDownViewHabitat, NormalizedDepth2TopDownViewHabitatTorch, ) from pointnav_vo.vo.dataset.regression_iter_dataset import BaseRegressionDataset from pointnav_vo.vo.common.common_vars import * FloatTensor = torch.FloatTensor class StatePairRegressionDataset(BaseRegressionDataset): r"""Data loader for state-pairs from Habitat simularo. """ def __init__( self, eval_flag=False, data_file=None, num_workers=0, act_type=-1, vis_size_w=256, vis_size_h=256, collision="-1", discretize_depth="none", discretized_depth_channels=0, gen_top_down_view=False, top_down_view_infos={}, geo_invariance_types=[], partial_data_n_splits=1, # data_aug=False, ): f"""Valid combination of action and geometric consistency types are: left OR right |-- inverse_data_augment_only left AND right |-- inverse_joint_train """ assert ( np.sum( [ "inverse_data_augment_only" in geo_invariance_types, "inverse_joint_train" in geo_invariance_types, ] ) <= 1 ), f"inverse_data_augment_only and inverse_joint_train should not appear together." if "inverse_joint_train" in geo_invariance_types: assert ( isinstance(act_type, list) and set(act_type) == set([TURN_LEFT, TURN_RIGHT]) ) or ( isinstance(act_type, int) and act_type == -1 ), f"When enabling joint-training with geometric inversion, action types must be [left, right] OR -1." else: assert isinstance(act_type, int) if "inverse_data_augment_only" in geo_invariance_types: assert ( act_type != MOVE_FORWARD ), f"Data augmentation for geometric consistency about inversion is not suitable for forward action." self._eval = eval_flag self._data_f = data_file self._num_workers = num_workers self._act_type = act_type self._collision = collision self._geo_invariance_types = geo_invariance_types self._len = 0 self._act_left_right_len = 0 self._vis_size_w = vis_size_w self._vis_size_h = vis_size_h self._partial_data_n_splits = partial_data_n_splits self._gen_top_down_view = gen_top_down_view self._top_down_view_infos = top_down_view_infos # RGB stored with uint8 self._rgb_pair_size = 2 * self._vis_size_w * self._vis_size_h * 3 # Depth stored with float16 self._depth_pair_size = 2 * self._vis_size_w * self._vis_size_h * 2 with h5py.File(data_file, "r", libver="latest") as f: self._chunk_size = f[list(f.keys())[0]]["prev_rgbs"].shape[0] # for rgb + depth self._chunk_bytes = int( np.ceil((self._rgb_pair_size + self._depth_pair_size) * self._chunk_size) ) # for misc information self._chunk_bytes += 20 * 2 logger.info(f"\nDataset: chunk bytes {self._chunk_bytes / (1024 * 1024)} MB\n") self._discretize_depth = discretize_depth self._discretized_depth_channels = discretized_depth_channels if self._discretize_depth == "hard": self._discretized_depth_end_vals = [] for i in np.arange(self._discretized_depth_channels): self._discretized_depth_end_vals.append( i * 1.0 / self._discretized_depth_channels ) self._discretized_depth_end_vals.append(1.0) logger.info("Get index mapping from h5py ...") all_chunk_keys = [] with h5py.File(data_file, "r", libver="latest") as f: for chunk_k in tqdm(sorted(f.keys())): all_chunk_keys.append(chunk_k) valid_idxes, transform_idxes = self._get_valid_idxes(f, chunk_k) self._len += len(valid_idxes) logger.info("... done.\n") if not self._eval: random.shuffle(all_chunk_keys) if num_workers == 0: # no separate worker self._chunk_splits = all_chunk_keys elif num_workers > 0: self._chunk_splits = defaultdict(list) for i, chunk_k in enumerate(all_chunk_keys): self._chunk_splits[i % num_workers].append(chunk_k) else: raise ValueError @property def data_f(self): return self._data_f @property def num_workers(self): return self._num_workers @property def geo_invariance_types(self): return self._geo_invariance_types @property def act_left_right_len(self): return self._act_left_right_len def __len__(self): return int(self._len / self._partial_data_n_splits) def _get_valid_idxes(self, h5_f, chunk_k): act_left_right_idxes = np.where( (h5_f[chunk_k]["actions"][()] == TURN_LEFT) | (h5_f[chunk_k]["actions"][()] == TURN_RIGHT) )[0] self._act_left_right_len += len(act_left_right_idxes) transform_idxes = {} if isinstance(self._act_type, int): if self._act_type == -1: # all data is valid valid_act_idxes = np.arange(h5_f[chunk_k]["actions"].shape[0]) elif "inverse_data_augment_only" in self._geo_invariance_types: # in this situation, action must be left or right assert self._act_type != MOVE_FORWARD valid_act_idxes = act_left_right_idxes else: valid_act_idxes = np.where( h5_f[chunk_k]["actions"][()] == self._act_type )[0] else: assert isinstance(self._act_type, list) assert set(self._act_type) == set([TURN_LEFT, TURN_RIGHT]) valid_act_idxes = act_left_right_idxes if self._collision == "-1": final_valid_idxes = valid_act_idxes else: raise ValueError return list(final_valid_idxes), transform_idxes def _process_data(self, chunk_i, i): actions = [] rgb_pairs = [] depth_pairs = [] discretized_depth_pairs = [] top_down_view_pairs = [] delta_xs = [] delta_ys = [] delta_zs = [] delta_yaws = [] data_types = [] dz_regress_masks = [] chunk_idxs = [] entry_idxs = [] # rgb in HDF5: uint8, reshaped as a vector prev_rgb = self._prev_rgbs[i, :].reshape( (self._vis_size_h, self._vis_size_w, 3) ) cur_rgb = self._cur_rgbs[i, :].reshape((self._vis_size_h, self._vis_size_w, 3)) # depth in HDF5: float16, reshaped as a vector prev_depth = self._prev_depths[i, :].reshape( (self._vis_size_h, self._vis_size_w, 1) ) cur_depth = self._cur_depths[i, :].reshape( (self._vis_size_h, self._vis_size_w, 1) ) # discretize depth map to one-hot representation if self._discretize_depth == "hard": prev_discretized_depth = self._discretize_depth_func(i, prev_depth[..., 0]) cur_discretized_depth = self._discretize_depth_func(i, cur_depth[..., 0]) else: prev_discretized_depth = np.zeros((self._vis_size_h, self._vis_size_w, 1)) cur_discretized_depth = np.zeros((self._vis_size_h, self._vis_size_w, 1)) # generate top_down_view if self._gen_top_down_view: prev_top_down_view = [] cur_top_down_view = [] tmp_prev = torch.FloatTensor(prev_depth) tmp_cur = torch.FloatTensor(cur_depth) # opencv has issues with multiprocessing, # we have to move top-down-view generator inside child process to avoid permenant hang # https://github.com/opencv/opencv/issues/5150 top_down_view_generator = NormalizedDepth2TopDownViewHabitat( **self._top_down_view_infos ) prev_top_down_view.append( top_down_view_generator.gen_top_down_view(prev_depth) ) cur_top_down_view.append( top_down_view_generator.gen_top_down_view(cur_depth) ) prev_top_down_view = np.concatenate(prev_top_down_view, axis=2) cur_top_down_view = np.concatenate(cur_top_down_view, axis=2) else: prev_top_down_view = np.zeros((self._vis_size_h, self._vis_size_w, 1)) cur_top_down_view = np.zeros((self._vis_size_h, self._vis_size_w, 1)) # delta states of prev to cur delta_pos_cur_rel_to_prev = self._delta_positions[i, :] dx_cur_rel_to_prev = FloatTensor([delta_pos_cur_rel_to_prev[0]]) dy_cur_rel_to_prev = FloatTensor([delta_pos_cur_rel_to_prev[1]]) dz_cur_rel_to_prev = FloatTensor([delta_pos_cur_rel_to_prev[2]]) delta_rotation_quaternion_cur_rel_to_prev = self._delta_rotations[i, :] # NOTE: must use arctan2 to get correct yaw dyaw_cur_rel_to_prev = FloatTensor( [ 2 * np.arctan2( delta_rotation_quaternion_cur_rel_to_prev[1], delta_rotation_quaternion_cur_rel_to_prev[3], ) ] ) # three situations: # - no constrain on target action type # - this data's action type matches the target action type # - inverse_joint_train has been enabled # NOTE: be careful that this branch will NOT always execute. # For example, # when training separate action model for TURN_LEFT and enable inverse_data_augment_only, # if self._actions[i] == TURN_RIGHT, this branch will not be executed. if ( (self._act_type == -1) or ( isinstance(self._act_type, int) and (self._actions[i] == self._act_type) ) or ("inverse_joint_train" in self._geo_invariance_types) ): # action in HDF5: uint8 actions.append(self._actions[i]) data_types.append(CUR_REL_TO_PREV) dz_regress_masks.append(1.0) chunk_idxs.append(chunk_i) entry_idxs.append(i) # to allow more processes, we use uint8 here to save each worker's memory usage rgb_pair_cur_rel_to_prev = torch.ByteTensor( np.concatenate([prev_rgb, cur_rgb], axis=2) ) rgb_pairs.append(rgb_pair_cur_rel_to_prev) depth_pair_cur_rel_to_prev = FloatTensor( np.concatenate([prev_depth, cur_depth], axis=2) ) depth_pairs.append(depth_pair_cur_rel_to_prev) # save memory with unin8 discretized_depth_pair_cur_rel_to_prev = torch.ByteTensor( np.concatenate([prev_discretized_depth, cur_discretized_depth], axis=2) ) discretized_depth_pairs.append(discretized_depth_pair_cur_rel_to_prev) top_down_view_pair_cur_rel_to_prev = FloatTensor( np.concatenate([prev_top_down_view, cur_top_down_view], axis=2) ) top_down_view_pairs.append(top_down_view_pair_cur_rel_to_prev) delta_xs.append(dx_cur_rel_to_prev) delta_ys.append(dy_cur_rel_to_prev) delta_zs.append(dz_cur_rel_to_prev) delta_yaws.append(dyaw_cur_rel_to_prev) # valid situations: # - act_type != -1 # - inverse_data_augment_only has been enabled and self._actions[i] != self._act_type # - inverse_joint_train has been enabled flag1 = ( (self._act_type != -1) and ("inverse_data_augment_only" in self._geo_invariance_types) and (self._actions[i] != MOVE_FORWARD) and (self._actions[i] != self._act_type) ) flag2 = ( (self._act_type != -1) and (self._actions[i] != MOVE_FORWARD) and ("inverse_joint_train" in self._geo_invariance_types) ) if flag1 or flag2: # get the opposite action from self._actions[i], # namely, if self._actions[i] is TURN_LEFT, add TURN_RIGHT tmp_act_list = [TURN_LEFT, TURN_RIGHT] actions.append(tmp_act_list[1 - (self._actions[i] == TURN_RIGHT)]) chunk_idxs.append(chunk_i) entry_idxs.append(i) data_types.append(PREV_REL_TO_CUR) dz_regress_masks.append(1.0) # save memory rgb_pair_prev_rel_to_cur = torch.ByteTensor( np.concatenate([cur_rgb, prev_rgb], axis=2) ) rgb_pairs.append(rgb_pair_prev_rel_to_cur) depth_pair_prev_rel_to_cur = FloatTensor( np.concatenate([cur_depth, prev_depth], axis=2) ) depth_pairs.append(depth_pair_prev_rel_to_cur) # save memory discretized_depth_pair_prev_rel_to_cur = torch.ByteTensor( np.concatenate([cur_discretized_depth, prev_discretized_depth], axis=2) ) discretized_depth_pairs.append(discretized_depth_pair_prev_rel_to_cur) top_down_view_pair_prev_rel_to_cur = FloatTensor( np.concatenate([cur_top_down_view, prev_top_down_view], axis=2) ) top_down_view_pairs.append(top_down_view_pair_prev_rel_to_cur) prev_state = ( quaternion_from_coeff(self._prev_global_rotations[i, :]), self._prev_global_positions[i, :], ) cur_state = ( self._cur_global_rotations[i, :], self._cur_global_positions[i, :], ) delta_state_prev_rel_to_cur = agent_state_target2ref(cur_state, prev_state) delta_rotation_quaternion_prev_rel_to_cur = quaternion_to_array( delta_state_prev_rel_to_cur[0] ) delta_pos_prev_rel_to_cur = delta_state_prev_rel_to_cur[1] dx_prev_rel_to_cur = FloatTensor([delta_pos_prev_rel_to_cur[0]]) dy_prev_rel_to_cur = FloatTensor([delta_pos_prev_rel_to_cur[1]]) dz_prev_rel_to_cur = FloatTensor([delta_pos_prev_rel_to_cur[2]]) dyaw_prev_rel_to_cur = FloatTensor( [ 2 * np.arctan2( delta_rotation_quaternion_prev_rel_to_cur[1], delta_rotation_quaternion_prev_rel_to_cur[3], ) ] ) delta_xs.append(dx_prev_rel_to_cur) delta_ys.append(dy_prev_rel_to_cur) delta_zs.append(dz_prev_rel_to_cur) delta_yaws.append(dyaw_prev_rel_to_cur) actions = torch.Tensor(actions).long().unsqueeze(1) data_types = torch.Tensor(data_types).unsqueeze(1) rgb_pairs = torch.stack(rgb_pairs, dim=0) depth_pairs = torch.stack(depth_pairs, dim=0) discretized_depth_pairs = torch.stack(discretized_depth_pairs, dim=0) top_down_view_pairs = torch.stack(top_down_view_pairs, dim=0) delta_xs = torch.stack(delta_xs, dim=0) delta_ys = torch.stack(delta_ys, dim=0) delta_zs = torch.stack(delta_zs, dim=0) delta_yaws = torch.stack(delta_yaws, dim=0) dz_regress_masks = torch.Tensor(dz_regress_masks).unsqueeze(1) chunk_idxs = torch.Tensor(chunk_idxs).unsqueeze(1) entry_idxs = torch.Tensor(entry_idxs).unsqueeze(1) return ( data_types, rgb_pairs, depth_pairs, discretized_depth_pairs, top_down_view_pairs, actions, delta_xs, delta_ys, delta_zs, delta_yaws, dz_regress_masks, chunk_idxs, entry_idxs, ) def __iter__(self): try: worker_info = torch.utils.data.get_worker_info() except: worker_info = None if worker_info is None: # zero-worker data loading, return the full iterator chunk_list = self._chunk_splits worker_id = -1 else: # in a worker process chunk_list = self._chunk_splits[worker_info.id] worker_id = worker_info.id if not self._eval: random.shuffle(chunk_list) for chunk_k in chunk_list: # logger.info(f"Worker {worker_id} is loading {chunk_k} into memory ...") # tmp_start = time.time() # load data into memory with h5py.File( self._data_f, "r", libver="latest", # rdcc_nbytes=self._chunk_bytes, rdcc_nslots=1e7, ) as f: # get valid indexes valid_idxes, _ = self._get_valid_idxes(f, chunk_k) self._actions = f[chunk_k]["actions"][()] self._prev_rgbs = f[chunk_k]["prev_rgbs"][()] self._cur_rgbs = f[chunk_k]["cur_rgbs"][()] self._prev_depths = f[chunk_k]["prev_depths"][()] self._cur_depths = f[chunk_k]["cur_depths"][()] self._delta_positions = f[chunk_k]["delta_positions"][()] self._delta_rotations = f[chunk_k]["delta_rotations"][()] # for geometric consistency self._prev_global_positions = f[chunk_k]["prev_global_positions"][()] self._prev_global_rotations = f[chunk_k]["prev_global_rotations"][()] self._cur_global_positions = f[chunk_k]["cur_global_positions"][()] self._cur_global_rotations = f[chunk_k]["cur_global_rotations"][()] # tmp_interval = time.time() - tmp_start # logger.info(f"... worker {worker_id} done ({tmp_interval:.2f}s).") # NOTE: must use random.shuffle instead of np.random.shuffle to make it random # np.random.shuffle always produces same order. # Similar issue here: https://discourse.allennlp.org/t/how-to-shuffle-the-data-each-batch-when-lazy-true/233 # It seems like numpy changes shuffle behaviour: # - https://numpy.org/doc/stable/reference/random/generated/numpy.random.shuffle.html # - https://numpy.org/doc/stable/reference/random/generated/numpy.random.Generator.shuffle.html#numpy.random.Generator.shuffle if not self._eval: random.shuffle(valid_idxes) for i, idx in enumerate(valid_idxes): if self._eval: _use_cur_data = True else: if i % self._partial_data_n_splits == 0: _use_cur_data = True else: _use_cur_data = False if _use_cur_data: out = self._process_data(int(chunk_k.split("_")[1]), idx) yield out def normal_collate_func(batch): data_types = torch.cat([i[0] for i in batch], 0) rgb_pairs = torch.cat([i[1] for i in batch], 0) depth_pairs = torch.cat([i[2] for i in batch], 0) discretized_depth_pairs = torch.cat([i[3] for i in batch], 0) top_down_view_pairs = torch.cat([i[4] for i in batch], 0) actions = torch.cat([i[5] for i in batch], 0) delta_xs = torch.cat([i[6] for i in batch], 0) delta_ys = torch.cat([i[7] for i in batch], 0) delta_zs = torch.cat([i[8] for i in batch], 0) delta_yaws = torch.cat([i[9] for i in batch], 0) dz_regress_masks = torch.cat([i[10] for i in batch], 0) chunk_idxs = torch.cat([i[11] for i in batch], 0) entry_idxs = torch.cat([i[12] for i in batch], 0) return ( data_types, rgb_pairs, depth_pairs, discretized_depth_pairs, top_down_view_pairs, actions, delta_xs, delta_ys, delta_zs, delta_yaws, dz_regress_masks, chunk_idxs, entry_idxs, ) def fast_collate_func(data): batch = list(zip(*data)) data_types = torch.cat(batch[0], dim=0) # rgb_pairs = [_.detach().clone() for _ in batch[1]] # depth_pairs = [_.detach().clone() for _ in batch[2]] # discretized_depth_pairs = [_.detach().clone() for _ in batch[3]] # top_down_view_pairs = [_.detach().clone() for _ in batch[4]] # NOTE: torch.cat on CPU is really slow but it is fast on GPU (https://github.com/pytorch/pytorch/issues/18634). # So we have an 'ugly' hack here that we return a list and postpone torch.cat until data is tranferred to GPU. # Please do not push tensor to GPU within collate func. Reasons: # 1) GPU does not have that many memory to allocate all worker's batch; # 2) We do not need to have all batches on GPU, we just need one at a time. # # With large probability, you may encounter 'RunTimeError: too many openfiles.' # This is because PyTorch default uses file_descriptor as sharing strategies # (https://pytorch.org/docs/master/multiprocessing.html?highlight=sharing%20strategy#sharing-strategies). # Each tensor needs a file descriptor in shared memory. # Therefore, with pushing a list of tensors into shared memory, # we will have #file_descriptor \approx len(rgb_pairs) * 4 * #workers (this may be the upper bound since processes are killed after completion). # # However, for Ubuntu, by default the limit number of file_descriptor is 1024. # You have several options to eliminate this error: # 1) use command `ulimit -n X` to set the limit to X. For most systems, X <= 65535 # 2) change PyTorch's sharing stragety to file_system: torch.multiprocessing.set_sharing_strategy('file_system') # 3) replace all tensors with numpy.array since np.ndarray uses pickle instead of shared memory to communicate # (https://github.com/pytorch/pytorch/issues/973#issuecomment-291287925) # I did not benchmark this since create tensor from numpy need to copy data. # I prefer to distribute all this work across workers instead of handling them in main process. # # Please note, when using file_descriptor as sharing strategy, # if you have many workers in total from all your programs (saying 50) and do not set ulimit properly, # you may encounter some weird issues, such as: # - training hangs forever # - torch.save crashes and reports file too large # - torch.save successfully but the checkpoint file is corrupted # - RuntimeError: received 0 items of ancdata # - RuntimeError: unable to open shared memory object # ... # I could solve them by reducing the number of workers # but I do not have clear explanations why they fail without proper traceback. # # Unfortunately, using file_system as sharing strategy is not perfect. # As PyTorch doc states that it is prone to memory leak. # Alough PyTorhc designs a daemon to handle this, there are still possibilities that leak will happen. # # Overall, here are your choices: # 1) if you care about speed, use a list and choose sharing strategy based on your own consideration # 2) if you do not care about speed, use torch.cat here and you are safe: # rgb_pairs = torch.cat(batch[1], 0) # depth_pairs = torch.cat(batch[2], 0) # discretized_depth_pairs = torch.cat(batch[3], 0) # top_down_view_pairs = torch.cat(batch[4], 0) rgb_pairs = list(batch[1]) depth_pairs = list(batch[2]) discretized_depth_pairs = list(batch[3]) top_down_view_pairs = list(batch[4]) actions = torch.cat(batch[5], dim=0) delta_xs = torch.cat(batch[6], dim=0) delta_ys = torch.cat(batch[7], dim=0) delta_zs = torch.cat(batch[8], dim=0) delta_yaws = torch.cat(batch[9], dim=0) dz_regress_masks = torch.cat(batch[10], dim=0) chunk_idxs = torch.cat(batch[11], 0) entry_idxs = torch.cat(batch[12], 0) del batch[:] return ( data_types, rgb_pairs, depth_pairs, discretized_depth_pairs, top_down_view_pairs, actions, delta_xs, delta_ys, delta_zs, delta_yaws, dz_regress_masks, chunk_idxs, entry_idxs, )

19,688

0

258

35e3ccc0677f04b0f9a898da83053bc4351ca28a

699

py

Python

mapillary_tools/uploader_utils.py

duckonomy/mapillary_tools

6b9b20fb54e3a26510534f5fd788599c0790ecec

[ "BSD-2-Clause" ]

null

mapillary_tools/uploader_utils.py

duckonomy/mapillary_tools

6b9b20fb54e3a26510534f5fd788599c0790ecec

[ "BSD-2-Clause" ]

null

mapillary_tools/uploader_utils.py

duckonomy/mapillary_tools

6b9b20fb54e3a26510534f5fd788599c0790ecec

[ "BSD-2-Clause" ]

null

import os

31.772727

73

0.715308

import os def set_video_as_uploaded(video): current_base_path = os.path.dirname(video) new_base_path = os.path.join(current_base_path, "uploaded") if not os.path.exists(new_base_path): os.mkdir(new_base_path) # Move video to uploaded folder new_video_path = os.path.join(new_base_path, os.path.basename(video)) os.rename(video, new_video_path) # Move GPX file basename = os.path.basename(video) video_key = os.path.splitext(basename)[0] gpx_filename= "{}.gpx".format(video_key) gpx_path = os.path.join(current_base_path, gpx_filename) new_gpx_path = os.path.join(new_base_path, gpx_filename) os.rename(gpx_path, new_gpx_path)

666

0

23

651cd1831dd5eccc15391398626087e34c64f27c

765

py

Python

wordy/wordy.py

cmccandless/ExercismSolutions-python

d80bf441c842daa2eb446bdba9c03d3e8864ea58

[ "MIT" ]

null

wordy/wordy.py

cmccandless/ExercismSolutions-python

d80bf441c842daa2eb446bdba9c03d3e8864ea58

[ "MIT" ]

null

wordy/wordy.py

cmccandless/ExercismSolutions-python

d80bf441c842daa2eb446bdba9c03d3e8864ea58

[ "MIT" ]

null

op = { 'plus': lambda x, y: x + y, 'minus': lambda x, y: x - y, 'multiplied': lambda x, y: x * y, 'divided': lambda x, y: x / y, }

27.321429

54

0.439216

op = { 'plus': lambda x, y: x + y, 'minus': lambda x, y: x - y, 'multiplied': lambda x, y: x * y, 'divided': lambda x, y: x / y, } def calculate(expr): s = list(reversed(expr[:-1].split()[2:])) r, o = (0, op['plus']) while len(s) > 0: x = s.pop() try: r, o = (o(r, int(x)), None) except TypeError: raise ValueError('missing operation') except ValueError: if o is not None: raise ValueError('missing number') try: o = op[x] except Exception: raise ValueError('unknown operation') if x == 'multiplied' or x == 'divided': s.pop() return r

585

0

25

44e56108a3dfaf1d288521f22b2e95d208b3b8e5

901

py

Python

aiphysim/dataloading/koopman_dataset.py

perovai/deepkoopman

eb6de915f5ea1f20b47cb3a22a384f55c30f0558

[ "MIT" ]

null

aiphysim/dataloading/koopman_dataset.py

perovai/deepkoopman

eb6de915f5ea1f20b47cb3a22a384f55c30f0558

[ "MIT" ]

10

2021-07-07T09:24:33.000Z

2021-09-27T14:32:59.000Z

aiphysim/dataloading/koopman_dataset.py

perovai/deepkoopman

eb6de915f5ea1f20b47cb3a22a384f55c30f0558

[ "MIT" ]

null

import numpy as np import torch from torch.utils.data import Dataset

29.064516

87

0.63707

import numpy as np import torch from torch.utils.data import Dataset class KoopmanDataset(Dataset): def __init__(self, file_paths, sequence_length=51, limit=-1): self.file_paths = file_paths self.sequence_length = sequence_length self.input_dim = None self.data = [] for file in self.file_paths: self.data.append(self.load_file(file)) self.data = torch.cat([n for n in self.data]) if limit > 0: self.data = self.data[:limit] def load_file(self, file_path): x = torch.from_numpy(np.genfromtxt(file_path, delimiter=",", dtype=np.float32)) if self.input_dim is None: self.input_dim = x.shape[1] return x.reshape(-1, self.sequence_length, self.input_dim) def __len__(self): return len(self.data) def __getitem__(self, index): return self.data[index]

692

9

130

e693c32dff9ada05fbab24b39e3c9417628ef392

3,718

py

Python

tasks-deploy/code-lock/generate.py

irdkwmnsb/lkshl-ctf

e5c0200ddc8ba73df5f321b87b9763fb1bbaba57

[ "MIT" ]

3

2021-03-30T06:27:58.000Z

2021-04-03T17:56:35.000Z

tasks-deploy/code-lock/generate.py

irdkwmnsb/lkshl-ctf

e5c0200ddc8ba73df5f321b87b9763fb1bbaba57

[ "MIT" ]

null

tasks-deploy/code-lock/generate.py

irdkwmnsb/lkshl-ctf

e5c0200ddc8ba73df5f321b87b9763fb1bbaba57

[ "MIT" ]

null

TASK_URL = "http://code-lock.ctf.sicamp.ru" TITLE = "Кодовый замок" STATEMENT_TEMPLATE = f''' "Безопасность превыше всего" - сказал ваш приятель и поставил на входную дверь кодовый замок. Но теперь вам срочно нужно попасть к нему домой, а кода вы не знаете. Что же делать? [{TASK_URL}/{{0}}]({TASK_URL}/{{0}}) ''' tokens = ['CyCHgDjGEITw', 'mhLo7Fo1T0CB', 'MvXYeD9qdKbD', 'IcI8GUb3ifnu', 'WfClJasVVMqE', '6N111DvhAm1a', 'oKZdNHSWuEzB', '83xZkQHbnkB2', 'WAa0NtH4OhIq', 'hkiUVGhgnhQ9', 'cRx7j5c4BQ1f', 'T1HHyn3puLoX', 'Yydst5aHZyVp', 'cpnyMwLbKB5p', '8iHeN1y18NjN', 'LSwR2lsiDTA3', 'gG4EHjKbOZm2', 'zYgMKfs9y2Wc', 'oFw8MCETmi6p', '8cdmXvDNUZRM', 'HDmbVl56YPBr', 'tnBzvB42h501', 'Gk7rzhpwMyhf', 'fwHG0HAE6mpP', 'OQNSYN9nbfYR', 'w59HnPeSuwWt', 'QQpSYcygsvRy', 'dMTpLdze1Ex7', 'ULkRAfUEZy4U', 'Shpapnk5hsta', 'DVeq1osBM2YR', 'GyURFUZMB4Xm', 'X69RCwKq2u1l', 'kYPOfWmvzAWM', 'BKKTXLNiII07', '32neeyDHhzqB', 'GNwN6ZHCGCdw', '4P3IF6Upprg3', 'jTIiNfjvwByW', 'QVlqAFqMIJOf', 'jPhyNMm4X5Rn', 'AyJqWGxn89fb', 'eD526FoOaDYe', 'VKxmUzze44bm', 'SrlFcn7xYZ16', '5YPYsFFYXIVk', 'bmsWWn8pgEAS', 'yy6PPRzGx9n0', '21w2OU52qu1n', 'yz4IMAZNUxAg', 'U1BvSWxNl9Ol', 'AzWWPWmCXNyD', '2NmfDErj74Hy', 'OawqmtEXpyO5', '1t8Il35pZ4dC', 'D46PRTiXfS85', 'FALm3qlwKlby', 'y5p75Oc2Wlq1', 'KCGvCrvXm7Dv', 'kXRW6JlaWqAP', 'BRS3SNN1pE8i', '4kTbKTwv4TDa', 'seRMOBGjStBR', 'NEjfEx8hkIlw', 'CwDwPLL4lJ8h', 'JqrI0EvPVsUO', 'YuxW4zurp837', 'lqAfwBcmEIYB', 'gIEsoiXHNlaN', '9aArBkyeOkp0', 'e9fvVfyqxzMK', 'AtWnForNaW08', 'QfG31wSauKFk', 'jj8SFRXo0g10', 'UwgRJmdbVn6h', 'of7KckpcWd6l', 'vQC0iZzrFoy2', 'B35uVOu9MFP4', 'vJeWdKmi3bQ5', 'JCRWGhFBBBdT', 'zJtVGIIWcaRH', 'hCQfcouybmtC', 'I3Lvi2CBfg3r', 'hsGrtOj9RoSF', 'Z2M6Lpp38sP5', 'Ddd1Q5xIN1gF', 'vq6wMS9ot0zQ', 'hQjBcbnBCHxC', 'p1PwrBlPZ0ow', '6qJmIbbe6xoB', 'WQcb7xfEnOYR', 'Ey6vDVRYc2Vg', 'wEPIInOjeYUY', 'fb6WnAMMEgmY', 'Jm4yz5txSDmS', 'fXOMpdzreZvs', 'CkC0BkFtTlyq', 'DZ0gQRmgZsU1', 'DauMhJ1BsGza', 'hUUYMo9s2BPD', 'QQxDRxvmupZk', '4L7iiN4r06lT', '5zyfpXsYhBKg', 'JrNowXOUjujL', 'qTHahv28s258', 'rBu8EOrxNWZ5', '68pRpcX5n8Ev', 'jC6tKJcWjKtR', '8xasHzOz7jrx', 'e6OGhsh3lyer', '1Am3cf613rjd', 'VgN14kseLLgW', 'r0H7c44NjU4J', 'R8zcG9pVe4If', 'hz9enCVyG3Qe', '42ZrkxaG0Odd', 'BjAIeDoudYpr', 'c8XtYZASWW1E', 'XreXXid6ctjG', 'lu1Jl8lKScR5', 'ZbZuuURyxIxS', 'SeRZjEEHdjU5', '5wvjcDrLGtXE', 'TfoMA9ujFFZq', '2wUgbKrHw5MQ', 'bC9MrAkpJiRA', 'k8njmmSu5NXE', '0wEywfzDTs6l', 'iUVECD8GiYyE', 'O2hKKZqGekW6', 'CAXzTL2d1qO2', 'y797wsSFo5yg', '9RAhxCoi7VnP', 'MUzYZ9uHKkHp', 'hzFbJ1dTuW9l', 'xL313rNuBsdP', 'QffVzcK7XdwG', 'n0gE4RRtOLwv', 'KQOYiuUQc8ij', '9NtrplWWpd3F', '9sbNujphpvkK', 'TPo2EW4NtMms', 'lYT0LmVD3xW9', 'b1rhQTMP1Fx2', 'm6DaZ98S8G5i', 'GMYZBbKzuzlo', 'gzlFPb5KSvzm', 'RumlfxO98mbL', 'FDFcbQ3tqsqB', 'MFYBWyrNxrju', 'Yhz3FR5otGne', 'AkCV4tMFjjmN', 'DSLm94pZ7x2k', '2B3a4m8BtviD', 'DdpfmV6EcR2s', 'XZRnVv0pyTLM', 'Rec0l44sVRmo', 'ktyovd71S95u', 'RuxFDjYa3CzC', 'szRnOXD2BeKN', 'rGgeMiZEik6Q', 'ijj71npkEoqP', 'YpqcsLAkhR3n', 'dDQOSdN8opNw', 'J6Xyv2PcJIeY', 'eloBCeinF7Gp', 'YyUBfPqsv3An', 'arWweSmLMKkF', 'MhvfwsyrJXhb', 'QBqD3MDwBW6T', '1TmDk7sEdo8j', 'HnaaZYWYEhGY', '6IL7tGERPBoo', 'EdwBz7J0R1Sv', 'doKRJdkcVLOC', 'B6hAOtsGnnLb', 'gNjBR7OQuPFN', 'inMM26GlBXcY', 'sTBXHVijFmOR', 't8Lpl3Ad9rtc', '9KUt31evAPwJ', 'U0DZAVBlygDM', 'F7AGLWs6vR52', '7CeZX2qdLfKP', '4c73P4ua8mJv', 'nm84pMyyKjnT', 'JUl0SS3Oaglq', 'WtbMPWqY6n41', 'T2aTQb00cqx5', 'IB5yetiYZNGl', 'MXTPGNTcP02Q', 'PI82YnVTiBd5', 'YYyak43raQDP', 'CREXo6BLfX5Z', 'TXR49vSnEnzD', 'a5uy3qptZXQZ', 'TBnL6rzijVzJ', 'vFraC8uBBYMG', 'xoVeBYoWmkSX', 'QrkcALhYHdI4']

265.571429

3,209

0.743679

TASK_URL = "http://code-lock.ctf.sicamp.ru" TITLE = "Кодовый замок" STATEMENT_TEMPLATE = f''' "Безопасность превыше всего" - сказал ваш приятель и поставил на входную дверь кодовый замок. Но теперь вам срочно нужно попасть к нему домой, а кода вы не знаете. Что же делать? [{TASK_URL}/{{0}}]({TASK_URL}/{{0}}) ''' def generate(context): participant = context['participant'] token = tokens[participant.id % len(tokens)] return TaskStatement(TITLE, STATEMENT_TEMPLATE.format(token)) tokens = ['CyCHgDjGEITw', 'mhLo7Fo1T0CB', 'MvXYeD9qdKbD', 'IcI8GUb3ifnu', 'WfClJasVVMqE', '6N111DvhAm1a', 'oKZdNHSWuEzB', '83xZkQHbnkB2', 'WAa0NtH4OhIq', 'hkiUVGhgnhQ9', 'cRx7j5c4BQ1f', 'T1HHyn3puLoX', 'Yydst5aHZyVp', 'cpnyMwLbKB5p', '8iHeN1y18NjN', 'LSwR2lsiDTA3', 'gG4EHjKbOZm2', 'zYgMKfs9y2Wc', 'oFw8MCETmi6p', '8cdmXvDNUZRM', 'HDmbVl56YPBr', 'tnBzvB42h501', 'Gk7rzhpwMyhf', 'fwHG0HAE6mpP', 'OQNSYN9nbfYR', 'w59HnPeSuwWt', 'QQpSYcygsvRy', 'dMTpLdze1Ex7', 'ULkRAfUEZy4U', 'Shpapnk5hsta', 'DVeq1osBM2YR', 'GyURFUZMB4Xm', 'X69RCwKq2u1l', 'kYPOfWmvzAWM', 'BKKTXLNiII07', '32neeyDHhzqB', 'GNwN6ZHCGCdw', '4P3IF6Upprg3', 'jTIiNfjvwByW', 'QVlqAFqMIJOf', 'jPhyNMm4X5Rn', 'AyJqWGxn89fb', 'eD526FoOaDYe', 'VKxmUzze44bm', 'SrlFcn7xYZ16', '5YPYsFFYXIVk', 'bmsWWn8pgEAS', 'yy6PPRzGx9n0', '21w2OU52qu1n', 'yz4IMAZNUxAg', 'U1BvSWxNl9Ol', 'AzWWPWmCXNyD', '2NmfDErj74Hy', 'OawqmtEXpyO5', '1t8Il35pZ4dC', 'D46PRTiXfS85', 'FALm3qlwKlby', 'y5p75Oc2Wlq1', 'KCGvCrvXm7Dv', 'kXRW6JlaWqAP', 'BRS3SNN1pE8i', '4kTbKTwv4TDa', 'seRMOBGjStBR', 'NEjfEx8hkIlw', 'CwDwPLL4lJ8h', 'JqrI0EvPVsUO', 'YuxW4zurp837', 'lqAfwBcmEIYB', 'gIEsoiXHNlaN', '9aArBkyeOkp0', 'e9fvVfyqxzMK', 'AtWnForNaW08', 'QfG31wSauKFk', 'jj8SFRXo0g10', 'UwgRJmdbVn6h', 'of7KckpcWd6l', 'vQC0iZzrFoy2', 'B35uVOu9MFP4', 'vJeWdKmi3bQ5', 'JCRWGhFBBBdT', 'zJtVGIIWcaRH', 'hCQfcouybmtC', 'I3Lvi2CBfg3r', 'hsGrtOj9RoSF', 'Z2M6Lpp38sP5', 'Ddd1Q5xIN1gF', 'vq6wMS9ot0zQ', 'hQjBcbnBCHxC', 'p1PwrBlPZ0ow', '6qJmIbbe6xoB', 'WQcb7xfEnOYR', 'Ey6vDVRYc2Vg', 'wEPIInOjeYUY', 'fb6WnAMMEgmY', 'Jm4yz5txSDmS', 'fXOMpdzreZvs', 'CkC0BkFtTlyq', 'DZ0gQRmgZsU1', 'DauMhJ1BsGza', 'hUUYMo9s2BPD', 'QQxDRxvmupZk', '4L7iiN4r06lT', '5zyfpXsYhBKg', 'JrNowXOUjujL', 'qTHahv28s258', 'rBu8EOrxNWZ5', '68pRpcX5n8Ev', 'jC6tKJcWjKtR', '8xasHzOz7jrx', 'e6OGhsh3lyer', '1Am3cf613rjd', 'VgN14kseLLgW', 'r0H7c44NjU4J', 'R8zcG9pVe4If', 'hz9enCVyG3Qe', '42ZrkxaG0Odd', 'BjAIeDoudYpr', 'c8XtYZASWW1E', 'XreXXid6ctjG', 'lu1Jl8lKScR5', 'ZbZuuURyxIxS', 'SeRZjEEHdjU5', '5wvjcDrLGtXE', 'TfoMA9ujFFZq', '2wUgbKrHw5MQ', 'bC9MrAkpJiRA', 'k8njmmSu5NXE', '0wEywfzDTs6l', 'iUVECD8GiYyE', 'O2hKKZqGekW6', 'CAXzTL2d1qO2', 'y797wsSFo5yg', '9RAhxCoi7VnP', 'MUzYZ9uHKkHp', 'hzFbJ1dTuW9l', 'xL313rNuBsdP', 'QffVzcK7XdwG', 'n0gE4RRtOLwv', 'KQOYiuUQc8ij', '9NtrplWWpd3F', '9sbNujphpvkK', 'TPo2EW4NtMms', 'lYT0LmVD3xW9', 'b1rhQTMP1Fx2', 'm6DaZ98S8G5i', 'GMYZBbKzuzlo', 'gzlFPb5KSvzm', 'RumlfxO98mbL', 'FDFcbQ3tqsqB', 'MFYBWyrNxrju', 'Yhz3FR5otGne', 'AkCV4tMFjjmN', 'DSLm94pZ7x2k', '2B3a4m8BtviD', 'DdpfmV6EcR2s', 'XZRnVv0pyTLM', 'Rec0l44sVRmo', 'ktyovd71S95u', 'RuxFDjYa3CzC', 'szRnOXD2BeKN', 'rGgeMiZEik6Q', 'ijj71npkEoqP', 'YpqcsLAkhR3n', 'dDQOSdN8opNw', 'J6Xyv2PcJIeY', 'eloBCeinF7Gp', 'YyUBfPqsv3An', 'arWweSmLMKkF', 'MhvfwsyrJXhb', 'QBqD3MDwBW6T', '1TmDk7sEdo8j', 'HnaaZYWYEhGY', '6IL7tGERPBoo', 'EdwBz7J0R1Sv', 'doKRJdkcVLOC', 'B6hAOtsGnnLb', 'gNjBR7OQuPFN', 'inMM26GlBXcY', 'sTBXHVijFmOR', 't8Lpl3Ad9rtc', '9KUt31evAPwJ', 'U0DZAVBlygDM', 'F7AGLWs6vR52', '7CeZX2qdLfKP', '4c73P4ua8mJv', 'nm84pMyyKjnT', 'JUl0SS3Oaglq', 'WtbMPWqY6n41', 'T2aTQb00cqx5', 'IB5yetiYZNGl', 'MXTPGNTcP02Q', 'PI82YnVTiBd5', 'YYyak43raQDP', 'CREXo6BLfX5Z', 'TXR49vSnEnzD', 'a5uy3qptZXQZ', 'TBnL6rzijVzJ', 'vFraC8uBBYMG', 'xoVeBYoWmkSX', 'QrkcALhYHdI4']

160

0

25

80d96f5c5eee131c39bba40f38a78bb59c0e41f9

69

py

Python

playbook/roles/jupyter/files/.ipyparallel/profile_mpi/ipengine_config.py

kemusiro/rpicluster-for-openmpi

fb27da339e8f13efdcc108a005a26e335527ade1

[ "MIT" ]

null

playbook/roles/jupyter/files/.ipyparallel/profile_mpi/ipengine_config.py

kemusiro/rpicluster-for-openmpi

fb27da339e8f13efdcc108a005a26e335527ade1

[ "MIT" ]

null

playbook/roles/jupyter/files/.ipyparallel/profile_mpi/ipengine_config.py

kemusiro/rpicluster-for-openmpi

fb27da339e8f13efdcc108a005a26e335527ade1

[ "MIT" ]

null

c.IPEngineApp.wait_for_url_file = 30 c.RegistrationFactory.ip = '*'

17.25

36

0.768116

c.IPEngineApp.wait_for_url_file = 30 c.RegistrationFactory.ip = '*'

0

f714c0f34fff9800c3a67b955f8cc23e9eeb99c8

9,027

py

Python

emu/containers/docker_container.py

CONQ-Agency/android-emulator-container-scripts

0d5f55ca938818486a2ad638b91464e952e87cf4

[ "Apache-2.0" ]

null

emu/containers/docker_container.py

CONQ-Agency/android-emulator-container-scripts

0d5f55ca938818486a2ad638b91464e952e87cf4

[ "Apache-2.0" ]

1

2021-06-15T11:59:58.000Z

2021-06-16T12:08:38.000Z

emu/containers/docker_container.py

CONQ-Agency/android-emulator-container-scripts

0d5f55ca938818486a2ad638b91464e952e87cf4

[ "Apache-2.0" ]

1

2021-05-12T14:08:12.000Z

# Copyright 2019 The Android Open Source Project # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import logging import os import re import sys import shutil import abc import docker from tqdm import tqdm from emu.utils import mkdir_p class ProgressTracker(object): """Tracks progress using tqdm for a set of layers that are pushed.""" def update(self, entry): """Update the progress bars given a an entry..""" if "id" not in entry: return identity = entry["id"] if identity not in self.progress: self.idx += 1 self.progress[identity] = { "tqdm": tqdm(total=0, position=self.idx, unit="B", unit_scale=True), # The progress bar "total": 0, # Total of bytes we are shipping "status": "", # Status message. "current": 0, # Current of total already send. } prog = self.progress[identity] total = int(entry.get("progressDetail", {}).get("total", -1)) current = int(entry.get("progressDetail", {}).get("current", 0)) if prog["total"] != total and total != -1: prog["total"] = total prog["tqdm"].reset(total=total) if prog["status"] != entry["status"]: prog["tqdm"].set_description("{0} {1}".format(entry.get("status"), identity)) if current != 0: diff = current - prog["current"] prog["current"] = current prog["tqdm"].update(diff) class DockerContainer(object): """A Docker Device is capable of creating and launching docker images. In order to successfully create and launch a docker image you must either run this as root, or have enabled sudoless docker. """ TAG_REGEX = re.compile(r"[a-zA-Z0-9][a-zA-Z0-9._-]*:?[a-zA-Z0-9._-]*") def launch(self, port_map): """Launches the container with the given sha, publishing abd on port, and gRPC on port 8554 Returns the container. """ image = self.docker_image() client = docker.from_env() try: container = client.containers.run( image=image.id, privileged=True, publish_all_ports=True, detach=True, ports=port_map, ) print("Launched {} (id:{})".format(container.name, container.id)) print("docker logs -f {}".format(container.name)) print("docker stop {}".format(container.name)) return container except: logging.exception("Unable to run the %s", image_sha) print("Unable to start the container, try running it as:") print("./run.sh ", image_sha) def create_container(self, dest): """Creates the docker container, returning the sha of the container, or None in case of failure.""" identity = None image_tag = self.full_name() print("docker build {} -t {}".format(dest, image_tag)) try: api_client = self.get_api_client() logging.info("build(path=%s, tag=%s, rm=True, decode=True)", dest, image_tag) result = api_client.build(path=dest, tag=image_tag, rm=True, decode=True) for entry in result: if "stream" in entry: sys.stdout.write(entry["stream"]) if "aux" in entry and "ID" in entry["aux"]: identity = entry["aux"]["ID"] client = docker.from_env() image = client.images.get(identity) image.tag(self.repo + self.image_name(), "latest") except: logging.exception("Failed to create container.", exc_info=True) logging.warning("You can manually create the container as follows:") logging.warning("docker build -t %s %s", image_tag, dest) return identity def pull(self, image, tag): """Tries to retrieve the given image and tag. Return True if succeeded, False when failed. """ client = self.get_api_client() try: tracker = ProgressTracker() result = client.pull(self.repo + image, tag) for entry in result: tracker.update(entry) except: logging.info("Failed to retrieve image, this is not uncommon.", exc_info=True) return False return True def docker_image(self): """The docker local docker image if any Returns: {docker.models.images.Image}: A docker image object, or None. """ client = self.get_client() for img in client.images.list(): for tag in img.tags: if self.image_name() in tag: return img return None def available(self): """True if this container image is locally available.""" return self.docker_image() != None def can_pull(self): """True if this container image can be pulled from a registry.""" return self.pull(self.image_name(), self.docker_tag()) @abc.abstractmethod def write(self, destination): """Method responsible for writing the Dockerfile and all necessary files to build a container. Args: destination ({string}): A path to a directory where all the container files should reside. Raises: NotImplementedError: [description] """ raise NotImplementedError() @abc.abstractmethod def image_name(self): """The image name without the tag used to uniquely identify this image. Raises: NotImplementedError: [description] """ raise NotImplementedError() @abc.abstractmethod @abc.abstractmethod def depends_on(self): """Name of the system image this container is build on.""" raise NotImplementedError()

34.586207

107

0.583029

# Copyright 2019 The Android Open Source Project # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import logging import os import re import sys import shutil import abc import docker from tqdm import tqdm from emu.utils import mkdir_p class ProgressTracker(object): """Tracks progress using tqdm for a set of layers that are pushed.""" def __init__(self): # This tracks the information for a given layer id. self.progress = {} self.idx = -1 def __del__(self): for k in self.progress: self.progress[k]["tqdm"].close() def update(self, entry): """Update the progress bars given a an entry..""" if "id" not in entry: return identity = entry["id"] if identity not in self.progress: self.idx += 1 self.progress[identity] = { "tqdm": tqdm(total=0, position=self.idx, unit="B", unit_scale=True), # The progress bar "total": 0, # Total of bytes we are shipping "status": "", # Status message. "current": 0, # Current of total already send. } prog = self.progress[identity] total = int(entry.get("progressDetail", {}).get("total", -1)) current = int(entry.get("progressDetail", {}).get("current", 0)) if prog["total"] != total and total != -1: prog["total"] = total prog["tqdm"].reset(total=total) if prog["status"] != entry["status"]: prog["tqdm"].set_description("{0} {1}".format(entry.get("status"), identity)) if current != 0: diff = current - prog["current"] prog["current"] = current prog["tqdm"].update(diff) class DockerContainer(object): """A Docker Device is capable of creating and launching docker images. In order to successfully create and launch a docker image you must either run this as root, or have enabled sudoless docker. """ TAG_REGEX = re.compile(r"[a-zA-Z0-9][a-zA-Z0-9._-]*:?[a-zA-Z0-9._-]*") def __init__(self, repo=None): if repo and repo[-1] != "/": repo += "/" self.repo = repo def get_client(self): return docker.from_env() def get_api_client(self): try: api_client = docker.APIClient() logging.info(api_client.version()) return api_client except: logging.exception("Failed to create default client, trying domain socket.", exc_info=True) api_client = docker.APIClient(base_url="unix://var/run/docker.sock") logging.info(api_client.version()) return api_client def push(self): image = self.full_name() print("Pushing docker image: {}.. be patient this can take a while!".format(self.full_name())) tracker = ProgressTracker() try: client = docker.from_env() result = client.images.push(image, "latest", stream=True, decode=True) for entry in result: tracker.update(entry) self.docker_image().tag("{}{}:latest".format(self.repo, self.image_name())) except: logging.exception("Failed to push image.", exc_info=True) logging.warning("You can manually push the image as follows:") logging.warning("docker push %s", image) def launch(self, port_map): """Launches the container with the given sha, publishing abd on port, and gRPC on port 8554 Returns the container. """ image = self.docker_image() client = docker.from_env() try: container = client.containers.run( image=image.id, privileged=True, publish_all_ports=True, detach=True, ports=port_map, ) print("Launched {} (id:{})".format(container.name, container.id)) print("docker logs -f {}".format(container.name)) print("docker stop {}".format(container.name)) return container except: logging.exception("Unable to run the %s", image_sha) print("Unable to start the container, try running it as:") print("./run.sh ", image_sha) def create_container(self, dest): """Creates the docker container, returning the sha of the container, or None in case of failure.""" identity = None image_tag = self.full_name() print("docker build {} -t {}".format(dest, image_tag)) try: api_client = self.get_api_client() logging.info("build(path=%s, tag=%s, rm=True, decode=True)", dest, image_tag) result = api_client.build(path=dest, tag=image_tag, rm=True, decode=True) for entry in result: if "stream" in entry: sys.stdout.write(entry["stream"]) if "aux" in entry and "ID" in entry["aux"]: identity = entry["aux"]["ID"] client = docker.from_env() image = client.images.get(identity) image.tag(self.repo + self.image_name(), "latest") except: logging.exception("Failed to create container.", exc_info=True) logging.warning("You can manually create the container as follows:") logging.warning("docker build -t %s %s", image_tag, dest) return identity def clean(self, dest): if os.path.exists(dest): shutil.rmtree(dest) mkdir_p(dest) def pull(self, image, tag): """Tries to retrieve the given image and tag. Return True if succeeded, False when failed. """ client = self.get_api_client() try: tracker = ProgressTracker() result = client.pull(self.repo + image, tag) for entry in result: tracker.update(entry) except: logging.info("Failed to retrieve image, this is not uncommon.", exc_info=True) return False return True def full_name(self): if self.repo: return "{}{}:{}".format(self.repo, self.image_name(), self.docker_tag()) return (self.image_name(), self.docker_tag()) def latest_name(self): if self.repo: return "{}{}:{}".format(self.repo, self.image_name(), "latest") return (self.image_name(), "latest") def create_cloud_build_step(self, dest): return { "name": "gcr.io/cloud-builders/docker", "args": [ "build", "-t", self.full_name(), "-t", self.latest_name(), os.path.basename(dest), ], } def docker_image(self): """The docker local docker image if any Returns: {docker.models.images.Image}: A docker image object, or None. """ client = self.get_client() for img in client.images.list(): for tag in img.tags: if self.image_name() in tag: return img return None def available(self): """True if this container image is locally available.""" return self.docker_image() != None def build(self, dest): self.write(dest) return self.create_container(dest) def can_pull(self): """True if this container image can be pulled from a registry.""" return self.pull(self.image_name(), self.docker_tag()) @abc.abstractmethod def write(self, destination): """Method responsible for writing the Dockerfile and all necessary files to build a container. Args: destination ({string}): A path to a directory where all the container files should reside. Raises: NotImplementedError: [description] """ raise NotImplementedError() @abc.abstractmethod def image_name(self): """The image name without the tag used to uniquely identify this image. Raises: NotImplementedError: [description] """ raise NotImplementedError() @abc.abstractmethod def docker_tag(self): raise NotImplementedError() @abc.abstractmethod def depends_on(self): """Name of the system image this container is build on.""" raise NotImplementedError() def __str__(self): return self.image_name() + ":" + self.docker_tag()

2,254

0

350

0ddf1e275961fe3e95a3ee2b91a70698817c2960

3,618

py

Python

python/2020/day16.py

SylvainDe/aoc

b8a4609327831685ef94c9960350ff7bb5ace1a5

[ "MIT" ]

null

python/2020/day16.py

SylvainDe/aoc

b8a4609327831685ef94c9960350ff7bb5ace1a5

[ "MIT" ]

null

python/2020/day16.py

SylvainDe/aoc

b8a4609327831685ef94c9960350ff7bb5ace1a5

[ "MIT" ]

null

# vi: set shiftwidth=4 tabstop=4 expandtab: import datetime import re rules_re = re.compile(r"(?P<min>\d+)-(?P<max>\d+)") if __name__ == "__main__": begin = datetime.datetime.now() run_tests() get_solutions() end = datetime.datetime.now() print(end - begin)

28.046512

86

0.609729

# vi: set shiftwidth=4 tabstop=4 expandtab: import datetime import re rules_re = re.compile(r"(?P<min>\d+)-(?P<max>\d+)") def get_rule_from_string(string): name, values = string.split(": ") return (name, [(int(mini), int(maxi)) for mini, maxi in rules_re.findall(values)]) def get_ticket_from_string(string): return [int(n) for n in string.split(",")] def get_info_from_string(string): rules, ticket, tickets = string.split("\n\n") return ( [get_rule_from_string(r) for r in rules.splitlines()], get_ticket_from_string(ticket.splitlines()[1]), [get_ticket_from_string(s) for s in tickets.splitlines()[1:] if s], ) def get_info_from_file(file_path="../../resources/year2020_day16_input.txt"): with open(file_path) as f: return get_info_from_string(f.read()) def value_valid_for_a_field(rules, n): return any(mini <= n <= maxi for _, lst in rules for mini, maxi in lst) def validity_rate(rules, tickets): return sum(n for t in tickets for n in t if not value_valid_for_a_field(rules, n)) def guess_field_position(rules, tickets): positions = set(range(len(tickets[0]))) impossible_positions = {name: set() for name, _ in rules} for t in tickets: # Only valid tickets if all(value_valid_for_a_field(rules, n) for n in t): for i, n in enumerate(t): for name, lst in rules: if not any(mini <= n <= maxi for (mini, maxi) in lst): impossible_positions[name].add(i) return guess_positions(impossible_positions, positions) def guess_positions(impossible_positions, positions): found = dict() while impossible_positions: for name, imposs in impossible_positions.items(): possible = positions - imposs if len(possible) == 0: print("Impossible") return None elif len(possible) == 1: unique_pos = possible.pop() found[name] = unique_pos del impossible_positions[name] for name, imposs in impossible_positions.items(): imposs.add(unique_pos) break else: # TODO print("No change") return None return found def run_tests(): example1 = """class: 1-3 or 5-7 row: 6-11 or 33-44 seat: 13-40 or 45-50 your ticket: 7,1,14 nearby tickets: 7,3,47 40,4,50 55,2,20 38,6,12""" rules, ticket, tickets = get_info_from_string(example1) assert rules == [ ("class", [(1, 3), (5, 7)]), ("row", [(6, 11), (33, 44)]), ("seat", [(13, 40), (45, 50)]), ] assert ticket == [7, 1, 14] assert tickets == [[7, 3, 47], [40, 4, 50], [55, 2, 20], [38, 6, 12]] assert validity_rate(rules, tickets) example2 = """class: 0-1 or 4-19 row: 0-5 or 8-19 seat: 0-13 or 16-19 your ticket: 11,12,13 nearby tickets: 3,9,18 15,1,5 5,14,9""" rules, ticket, tickets = get_info_from_string(example2) assert guess_field_position(rules, tickets) == {"seat": 2, "class": 1, "row": 0} def get_solutions(): rules, ticket, tickets = get_info_from_file() print(validity_rate(rules, tickets) == 26053) mult = 1 field_position = guess_field_position(rules, tickets) for field, idx in field_position.items(): if field.startswith("departure"): mult *= ticket[idx] print(mult == 1515506256421) if __name__ == "__main__": begin = datetime.datetime.now() run_tests() get_solutions() end = datetime.datetime.now() print(end - begin)

3,097

0

230

a6e3a48eaa19202a70ac26f47f0ceced944359ba

750

py

Python

scripts/1_deploy_pokemon.py

abhicoder29/pokemon-nft

29d517ac996c878558795cc135cd17828976c179

[ "MIT" ]

1

2021-12-30T07:58:20.000Z

scripts/1_deploy_pokemon.py

abhicoder29/pokemon-nft

29d517ac996c878558795cc135cd17828976c179

[ "MIT" ]

null

scripts/1_deploy_pokemon.py

abhicoder29/pokemon-nft

29d517ac996c878558795cc135cd17828976c179

[ "MIT" ]

null

#!/usr/bin/python3 from brownie import Pokemon, accounts, network, config from scripts.helpful_scripts import fund import asyncio import json

34.090909

108

0.684

#!/usr/bin/python3 from brownie import Pokemon, accounts, network, config from scripts.helpful_scripts import fund import asyncio import json def main(): dev = accounts.add(config["wallets"]["from_key"]) print(network.show_active()) # publish_source = True if os.getenv("ETHERSCAN_TOKEN") else False # Currently having an issue with this publish_source = True pokemon = Pokemon.deploy( config["networks"][network.show_active()]["vrf_coordinator"], config["networks"][network.show_active()]["link_token"], config["networks"][network.show_active()]["keyhash"], config["networks"][network.show_active()]["fee"], {"from": dev}, publish_source=publish_source, ) return pokemon

584

0

23

fe8d456a5fa9c6585a8f352262524692f6af0703

4,442

py

Python

nets/mobilenet.py

bubbliiiing/arcface-tf2

b2d6b1c10898689f0f4f6c952feefb3eb43b8e7d

[ "MIT" ]

2

2022-03-08T03:49:14.000Z

2022-03-08T09:42:29.000Z

nets/mobilenet.py

bubbliiiing/arcface-tf2

b2d6b1c10898689f0f4f6c952feefb3eb43b8e7d

[ "MIT" ]

null

nets/mobilenet.py

bubbliiiing/arcface-tf2

b2d6b1c10898689f0f4f6c952feefb3eb43b8e7d

[ "MIT" ]

1

2022-03-16T01:51:20.000Z

from tensorflow.keras import backend as K from tensorflow.keras import initializers from tensorflow.keras.layers import (Activation, BatchNormalization, Conv2D, Dense, DepthwiseConv2D, Dropout, Flatten, PReLU) from tensorflow.keras.regularizers import l2

50.477273

119

0.660738

from tensorflow.keras import backend as K from tensorflow.keras import initializers from tensorflow.keras.layers import (Activation, BatchNormalization, Conv2D, Dense, DepthwiseConv2D, Dropout, Flatten, PReLU) from tensorflow.keras.regularizers import l2 def _conv_block(inputs, filters, kernel=(3, 3), strides=(1, 1), weight_decay=5e-4): x = Conv2D(filters, kernel, padding='same', use_bias=False, strides=strides, name='conv1', kernel_initializer=initializers.RandomNormal(stddev=0.1), kernel_regularizer=l2(weight_decay), bias_initializer='zeros')(inputs) x = BatchNormalization(name='conv1_bn', epsilon=1e-5)(x) return Activation(relu6, name='conv1_relu')(x) def _depthwise_conv_block(inputs, pointwise_conv_filters, depth_multiplier=1, strides=(1, 1), block_id=1, weight_decay=5e-4): x = DepthwiseConv2D((3, 3), padding='same', depth_multiplier=depth_multiplier, strides=strides, use_bias=False, name='conv_dw_%d' % block_id, depthwise_initializer=initializers.RandomNormal(stddev=0.1), depthwise_regularizer=l2(weight_decay), bias_initializer='zeros')(inputs) x = BatchNormalization(name='conv_dw_%d_bn' % block_id, epsilon=1e-5)(x) x = Activation(relu6, name='conv_dw_%d_relu' % block_id)(x) x = Conv2D(pointwise_conv_filters, (1, 1), padding='same', use_bias=False, strides=(1, 1), name='conv_pw_%d' % block_id, kernel_initializer=initializers.RandomNormal(stddev=0.1), kernel_regularizer=l2(weight_decay), bias_initializer='zeros')(x) x = BatchNormalization(name='conv_pw_%d_bn' % block_id, epsilon=1e-5)(x) return Activation(relu6, name='conv_pw_%d_relu' % block_id)(x) def relu6(x): return K.relu(x, max_value=6) def MobilenetV1(inputs, embedding_size, dropout_keep_prob=0.5, depth_multiplier=1, weight_decay=5e-4): x = _conv_block(inputs, 32, strides=(1, 1)) x = _depthwise_conv_block(x, 64, depth_multiplier, block_id=1, weight_decay=weight_decay) x = _depthwise_conv_block(x, 128, depth_multiplier, strides=(2, 2), block_id=2, weight_decay=weight_decay) x = _depthwise_conv_block(x, 128, depth_multiplier, block_id=3, weight_decay=weight_decay) x = _depthwise_conv_block(x, 256, depth_multiplier, strides=(2, 2), block_id=4, weight_decay=weight_decay) x = _depthwise_conv_block(x, 256, depth_multiplier, block_id=5, weight_decay=weight_decay) x = _depthwise_conv_block(x, 512, depth_multiplier, strides=(2, 2), block_id=6, weight_decay=weight_decay) x = _depthwise_conv_block(x, 512, depth_multiplier, block_id=7, weight_decay=weight_decay) x = _depthwise_conv_block(x, 512, depth_multiplier, block_id=8, weight_decay=weight_decay) x = _depthwise_conv_block(x, 512, depth_multiplier, block_id=9, weight_decay=weight_decay) x = _depthwise_conv_block(x, 512, depth_multiplier, block_id=10, weight_decay=weight_decay) x = _depthwise_conv_block(x, 512, depth_multiplier, block_id=11, weight_decay=weight_decay) x = _depthwise_conv_block(x, 1024, depth_multiplier, strides=(2, 2), block_id=12, weight_decay=weight_decay) x = _depthwise_conv_block(x, 1024, depth_multiplier, block_id=13, weight_decay=weight_decay) x = Conv2D(512, kernel_size=1, use_bias=False, name='sep', kernel_initializer=initializers.RandomNormal(stddev=0.1), kernel_regularizer=l2(weight_decay), bias_initializer='zeros')(x) x = BatchNormalization(name='sep_bn', epsilon=1e-5)(x) x = PReLU(alpha_initializer=initializers.constant(0.25), alpha_regularizer=l2(weight_decay), shared_axes=[1, 2])(x) x = BatchNormalization(name='bn2', epsilon=1e-5)(x) x = Dropout(dropout_keep_prob)(x) x = Flatten()(x) x = Dense(embedding_size, name='linear', kernel_initializer=initializers.RandomNormal(stddev=0.1), kernel_regularizer=l2(weight_decay), bias_initializer='zeros')(x) x = BatchNormalization(name='features', epsilon=1e-5)(x) return x

4,018

0

92

4f74195555db7ef71e27e1720160a87892b9d005

4,174

py

Python

medkit/bases/base_dataset.py

XanderJC/medkit-learn

13b06906f6d093c4978f52f1e8f06e998608faa3

[ "Apache-2.0" ]

14

2021-06-06T18:14:55.000Z

2022-03-18T14:00:05.000Z

medkit/bases/base_dataset.py

vanderschaarlab/medkit-learn

a8bed6e7a76769f28abfadb3231f139cbfe44b49

[ "Apache-2.0" ]

1

2021-06-13T05:34:21.000Z

2021-06-15T09:52:50.000Z

medkit/bases/base_dataset.py

vanderschaarlab/medkit-learn

a8bed6e7a76769f28abfadb3231f139cbfe44b49

[ "Apache-2.0" ]

1

2021-10-18T14:07:45.000Z

from .__head__ import * class BaseDataset(torch.utils.data.Dataset): """ Base Dataset class to be passed to torch Dataloader so train functions can be unified. Not particularly designed for end-user, but for pre-training models. """ def __len__(self): "Total number of samples" return self.N def __getitem__(self, index): "Generates one batch of data" return ( self.X_static[index], self.X_series[index], self.X_mask[index], self.y_series[index], ) def get_whole_batch(self): "Returns all data as a single batch" return self.X_static, self.X_series, self.X_mask, self.y_series class standard_dataset(BaseDataset): """ Dataset to be passed to a torch DataLoader """

34.213115

97

0.576186

from .__head__ import * class BaseDataset(torch.utils.data.Dataset): """ Base Dataset class to be passed to torch Dataloader so train functions can be unified. Not particularly designed for end-user, but for pre-training models. """ def __init__(self): super(BaseDataset, self).__init__() self.N = None # No. of items in dataset self.X_static = None # Static features [N,static_dim] self.X_series = None # Series features [N,max_seq_length,series_dim] self.X_mask = None # Mask [N,max_seq_length] self.y_series = None # Static features [N,max_seq_length] def __len__(self): "Total number of samples" return self.N def __getitem__(self, index): "Generates one batch of data" return ( self.X_static[index], self.X_series[index], self.X_mask[index], self.y_series[index], ) def get_whole_batch(self): "Returns all data as a single batch" return self.X_static, self.X_series, self.X_mask, self.y_series class standard_dataset(BaseDataset): """ Dataset to be passed to a torch DataLoader """ def __init__(self, domain, max_seq_length=50, test=False, save_scale=False): super(standard_dataset, self).__init__() scale = scaler(domain) fold = "train" if test: fold = "test" path_head = f"data/{domain.base_name}/{domain.base_name}_temporal_{fold}_data_eav.csv.gz" path = resource_filename("medkit", path_head) data = pd.read_csv(path) if domain.base_name == "icu": series_df = data series_df.fillna(series_df.mean(), inplace=True) else: series_df = pd.pivot_table( data, index=["id", "time"], columns="variable", values="value" ).reset_index(level=[0, 1]) series_df.fillna(method="ffill", inplace=True) series_df.fillna(0, inplace=True) unique_ids = pd.unique(series_df["id"]) self.N = len(unique_ids) series = torch.zeros((len(unique_ids), max_seq_length, domain.series_in_dim)) y_series = torch.zeros((len(unique_ids), max_seq_length)) for i, ids in enumerate(unique_ids): patient = series_df[series_df["id"] == ids].sort_values(by=["time"]) cov = patient[domain.series_names].to_numpy() if domain.bin_out_dim > 0: cov[:, -domain.bin_out_dim :] = ( cov[:, -domain.bin_out_dim :] > 0 ).astype(int) targets = patient[domain.action_names].to_numpy() targets = (targets > 0).astype(int) y = targets[:, 0] num_targets = targets.shape[1] for j in range(num_targets - 1): y += (2 ** (j + 1)) * targets[:, j + 1] seq_length = len(cov) cov = torch.tensor(cov) y = torch.tensor(y) if seq_length > max_seq_length: series[i, :, :] = cov[:max_seq_length, :] y_series[i, :] = y[:max_seq_length] else: series[i, :seq_length, :] = cov y_series[i, :seq_length] = y mask = (series[:, :, 0] != 0).float() path_head = ( f"data/{domain.base_name}/{domain.base_name}_static_{fold}_data.csv.gz" ) path = resource_filename("medkit", path_head) static_df = pd.read_csv(path) static_df.fillna(static_df.mean(), inplace=True) static = torch.zeros((len(unique_ids), domain.static_in_dim)) for i, ids in enumerate(unique_ids): patient = static_df[static_df["id"] == ids] cov = patient[domain.static_names].to_numpy() cov = torch.tensor(cov) static[i, :] = cov normed_series = scale.fit_series(series, mask) normed_static = scale.fit_static(static) if save_scale: scale.save_params() self.X_static = normed_static self.X_series = normed_series self.X_mask = mask self.y_series = y_series

3,304

0

54

45a0b3e934efd1b716e4e65e5d9b8da1fcedcf16

1,313

py

Python

colorthermoexample.py

majikpig/ubtech

8d21f4b522e06f998bfdf3b1947db23bfc349e3d

[ "MIT" ]

null

colorthermoexample.py

majikpig/ubtech

8d21f4b522e06f998bfdf3b1947db23bfc349e3d

[ "MIT" ]

null

colorthermoexample.py

majikpig/ubtech

8d21f4b522e06f998bfdf3b1947db23bfc349e3d

[ "MIT" ]

1

2019-03-23T16:08:30.000Z

import tempsensor import time import btnlib as btn import ledlib as led red = 80 orange = 75 yellow = 70 green = 65 blue = 60 purple = 55 while btn.isOn(btn.switch): #while the switch is on: led.turn_on(led.white) temp = tempsensor.tempF() #get the temp print temp if temp > red : led.turn_on_all() elif temp > orange : led.turn_off(led.red) led.turn_on(led.orange) led.turn_on(led.yellow) led.turn_on(led.green) led.turn_on(led.blue) led.turn_on(led.purple) elif temp > yellow : led.turn_off(led.red) led.turn_off(led.orange) led.turn_on(led.yellow) led.turn_on(led.green) led.turn_on(led.blue) led.turn_on(led.purple) elif temp > green : led.turn_off(led.red) led.turn_off(led.orange) led.turn_off(led.yellow) led.turn_on(led.green) led.turn_on(led.blue) led.turn_on(led.purple) elif temp > blue : led.turn_off(led.red) led.turn_off(led.orange) led.turn_off(led.yellow) led.turn_off(led.green) led.turn_on(led.blue) led.turn_on(led.purple) elif temp > purple : led.turn_off(led.red) led.turn_off(led.orange) led.turn_off(led.yellow) led.turn_off(led.green) led.turn_off(led.blue) led.turn_on(led.purple) else : led.turn_off_all() led.turn_on(led.white) time.sleep(0.5) led.turn_off(led.white) time.sleep(0.5) led.GPIO.cleanup()

20.84127

52

0.711348

import tempsensor import time import btnlib as btn import ledlib as led red = 80 orange = 75 yellow = 70 green = 65 blue = 60 purple = 55 while btn.isOn(btn.switch): #while the switch is on: led.turn_on(led.white) temp = tempsensor.tempF() #get the temp print temp if temp > red : led.turn_on_all() elif temp > orange : led.turn_off(led.red) led.turn_on(led.orange) led.turn_on(led.yellow) led.turn_on(led.green) led.turn_on(led.blue) led.turn_on(led.purple) elif temp > yellow : led.turn_off(led.red) led.turn_off(led.orange) led.turn_on(led.yellow) led.turn_on(led.green) led.turn_on(led.blue) led.turn_on(led.purple) elif temp > green : led.turn_off(led.red) led.turn_off(led.orange) led.turn_off(led.yellow) led.turn_on(led.green) led.turn_on(led.blue) led.turn_on(led.purple) elif temp > blue : led.turn_off(led.red) led.turn_off(led.orange) led.turn_off(led.yellow) led.turn_off(led.green) led.turn_on(led.blue) led.turn_on(led.purple) elif temp > purple : led.turn_off(led.red) led.turn_off(led.orange) led.turn_off(led.yellow) led.turn_off(led.green) led.turn_off(led.blue) led.turn_on(led.purple) else : led.turn_off_all() led.turn_on(led.white) time.sleep(0.5) led.turn_off(led.white) time.sleep(0.5) led.GPIO.cleanup()

0

18792a2154e363e0b2b8ccacb226f0fb273783c3

723

py

Python

sim_examples/inference_cnn_loadweight.py

thuime/XPEsim

ab97d4c3c5b32ce4804ca58ad0f0083bb9de11fc

[ "MIT" ]

27

2018-04-17T02:39:57.000Z

2022-03-25T13:51:14.000Z

sim_examples/inference_cnn_loadweight.py

Arvin-xd/XPEsim

ab97d4c3c5b32ce4804ca58ad0f0083bb9de11fc

[ "MIT" ]

1

2018-12-13T17:58:20.000Z

2021-04-15T15:32:04.000Z

sim_examples/inference_cnn_loadweight.py

Arvin-xd/XPEsim

ab97d4c3c5b32ce4804ca58ad0f0083bb9de11fc

[ "MIT" ]

14

2018-04-17T02:40:17.000Z

2021-12-24T22:11:40.000Z

import simulator import numpy as np ''' TODO Support CNN in the Hardware Evaluation ''' weights_dir = "./data/mnist-lenet.npz" image_dir = "./data/dataset/mnist/test.npy" batch_size = 10 # The number of input picture weights = np.load(weights_dir)['arr_0'].item() data = np.load(image_dir)[:batch_size] images = data[:, 0] labels = data[:, 1] params = simulator.Parameterinput() # Read parameters in simconfig # Define the neural network net = [ ['Conv2d',], ['Conv2d',], ['Linear',], ['Linear',], ['Linear',], ] # SIM HWsim = simulator.SystemSim(params) HWsim.apply(net, weights, images, labels) # Forward computing HWsim.show() # Show the result in console

22.59375

67

0.644537

import simulator import numpy as np ''' TODO Support CNN in the Hardware Evaluation ''' weights_dir = "./data/mnist-lenet.npz" image_dir = "./data/dataset/mnist/test.npy" batch_size = 10 # The number of input picture weights = np.load(weights_dir)['arr_0'].item() data = np.load(image_dir)[:batch_size] images = data[:, 0] labels = data[:, 1] params = simulator.Parameterinput() # Read parameters in simconfig # Define the neural network net = [ ['Conv2d',], ['Conv2d',], ['Linear',], ['Linear',], ['Linear',], ] # SIM HWsim = simulator.SystemSim(params) HWsim.apply(net, weights, images, labels) # Forward computing HWsim.show() # Show the result in console

0

ae3ea7a76f6a45e67113e758d9604cf094c6cf81

1,468

py

Python

07_docker/marathon_tweets/tweet_collector/get_tweets.py

bfc782/spice_weasel

7f2d7586ae485001a9b875b62d093fd04e28faa8

[ "CC0-1.0" ]

null

07_docker/marathon_tweets/tweet_collector/get_tweets.py

bfc782/spice_weasel

7f2d7586ae485001a9b875b62d093fd04e28faa8

[ "CC0-1.0" ]

null

07_docker/marathon_tweets/tweet_collector/get_tweets.py

bfc782/spice_weasel

7f2d7586ae485001a9b875b62d093fd04e28faa8

[ "CC0-1.0" ]

null

#import config import os from tweepy import OAuthHandler, Stream from tweepy.streaming import StreamListener import json import logging import pymongo import time client = pymongo.MongoClient("mongodb") db = client.tweets time.sleep(10) api_key = os.getenv('TWITTER_CONSUMER_API_KEY') api_secret = os.getenv('TWITTER_CONSUMER_API_SECRET') access_token = os.getenv('TWITTER_ACCESS_TOKEN') access_secret = os.getenv('TWITTER_ACCESS_TOKEN_SECRET') def authenticate(): '''Function for handling Twitter Auth. Pulls Env Variables in bash_profile''' auth = OAuthHandler(api_key, api_secret) auth.set_access_token(access_token, access_secret) return auth if __name__ == '__main__': auth = authenticate() listener = TwitterListener() stream = Stream(auth, listener) stream.filter(track=['marathon'], languages=['en'])

25.754386

90

0.681199

#import config import os from tweepy import OAuthHandler, Stream from tweepy.streaming import StreamListener import json import logging import pymongo import time client = pymongo.MongoClient("mongodb") db = client.tweets time.sleep(10) api_key = os.getenv('TWITTER_CONSUMER_API_KEY') api_secret = os.getenv('TWITTER_CONSUMER_API_SECRET') access_token = os.getenv('TWITTER_ACCESS_TOKEN') access_secret = os.getenv('TWITTER_ACCESS_TOKEN_SECRET') def authenticate(): '''Function for handling Twitter Auth. Pulls Env Variables in bash_profile''' auth = OAuthHandler(api_key, api_secret) auth.set_access_token(access_token, access_secret) return auth class TwitterListener(StreamListener): def on_data(self, data): '''This method is what happens to every tweet as it is intercepted in real time''' t = json.loads(data) tweet = { 'created_at': t['created_at'], 'text': t['text'], 'username': t['user']['screen_name'], 'followers_count': t['user']['followers_count'] } # logging.critical(f'\n\n TWEET INCOMING: {tweet["text"]}\n\n') db.collections.tweets.insert_one(tweet) def on_error(self, status): if status -- 420: print(status) return False if __name__ == '__main__': auth = authenticate() listener = TwitterListener() stream = Stream(auth, listener) stream.filter(track=['marathon'], languages=['en'])

84

512

23

6cef8f5b03beb08dc2b0a1f5dceed760540264db

859

py

Python

Script Examples/example_py_script.py

snichola/Aurora

3d38de87e9bb8affb309a0dd6f47c8479c5557be

[ "MIT" ]

null

Script Examples/example_py_script.py

snichola/Aurora

3d38de87e9bb8affb309a0dd6f47c8479c5557be

[ "MIT" ]

null

Script Examples/example_py_script.py

snichola/Aurora

3d38de87e9bb8affb309a0dd6f47c8479c5557be

[ "MIT" ]

null

import clr clr.AddReference("Aurora") clr.AddReference("System.Drawing") from Aurora import Global from Aurora.Settings import KeySequence from Aurora.Devices import DeviceKeys from Aurora.EffectsEngine import EffectLayer from System.Drawing import Color import System array_device_keys = System.Array[DeviceKeys]

37.347826

207

0.772992

import clr clr.AddReference("Aurora") clr.AddReference("System.Drawing") from Aurora import Global from Aurora.Settings import KeySequence from Aurora.Devices import DeviceKeys from Aurora.EffectsEngine import EffectLayer from System.Drawing import Color import System array_device_keys = System.Array[DeviceKeys] class main(): ID = "ExamplePyEffect" ForegroundColour = Color.Red BackgroundColour = Color.Black DefaultKeys = KeySequence(array_device_keys((DeviceKeys.TAB, DeviceKeys.Q, DeviceKeys.W, DeviceKeys.E, DeviceKeys.R, DeviceKeys.T, DeviceKeys.Y, DeviceKeys.U, DeviceKeys.I, DeviceKeys.O, DeviceKeys.P))) def UpdateLights(self, settings, state): layer = EffectLayer(self.ID) layer.PercentEffect(self.ForegroundColour, self.BackgroundColour, settings.Keys, System.DateTime.Now.Second, 60); return layer

199

321

23

021ec52cf537b565b4e716e86143546f5b5a72a2

1,692

py

Python

uninas/optimization/hpo/pymoo/mutation.py

cogsys-tuebingen/uninas

06729b9cf517ec416fb798ae387c5bd9c3a278ac

[ "MIT" ]

18

2020-11-22T16:03:08.000Z

2022-03-15T12:11:46.000Z

uninas/optimization/hpo/pymoo/mutation.py

cogsys-tuebingen/uninas

06729b9cf517ec416fb798ae387c5bd9c3a278ac

[ "MIT" ]

2

2022-01-04T08:10:17.000Z

2022-01-05T08:13:14.000Z

uninas/optimization/hpo/pymoo/mutation.py

cogsys-tuebingen/uninas

06729b9cf517ec416fb798ae387c5bd9c3a278ac

[ "MIT" ]

6

2021-03-08T07:08:52.000Z

2022-02-24T12:00:43.000Z

from pymoo.model.mutation import Mutation from pymoo.operators.mutation.no_mutation import NoMutation from pymoo.operators.mutation.polynomial_mutation import PolynomialMutation from pymoo.operators.integer_from_float_operator import IntegerFromFloatMutation from uninas.utils.args import ArgsInterface, Argument, Namespace from uninas.register import Register @Register.hpo_pymoo_crossover() class NoPymooMutation(AbstractPymooCrossover): """ No mutation at all """ @classmethod @Register.hpo_pymoo_mutation() class PolynomialPymooMutation(AbstractPymooCrossover): """ IntegerFromFloatMutation for integer variables, PolynomialMutation for floats """ @classmethod def args_to_add(cls, index=None) -> [Argument]: """ list arguments to add to argparse when this class (or a child class) is chosen """ return super().args_to_add(index) + [ Argument('type', default='int', type=str, choices=['int', 'real'], help='?'), Argument('eta', default=30, type=int, help='?'), ] @classmethod

35.25

94

0.706265

from pymoo.model.mutation import Mutation from pymoo.operators.mutation.no_mutation import NoMutation from pymoo.operators.mutation.polynomial_mutation import PolynomialMutation from pymoo.operators.integer_from_float_operator import IntegerFromFloatMutation from uninas.utils.args import ArgsInterface, Argument, Namespace from uninas.register import Register class AbstractPymooCrossover(ArgsInterface): @classmethod def from_args(cls, args: Namespace, index=None) -> Mutation: raise NotImplementedError @Register.hpo_pymoo_crossover() class NoPymooMutation(AbstractPymooCrossover): """ No mutation at all """ @classmethod def from_args(cls, args: Namespace, index=None) -> Mutation: return NoMutation() @Register.hpo_pymoo_mutation() class PolynomialPymooMutation(AbstractPymooCrossover): """ IntegerFromFloatMutation for integer variables, PolynomialMutation for floats """ @classmethod def args_to_add(cls, index=None) -> [Argument]: """ list arguments to add to argparse when this class (or a child class) is chosen """ return super().args_to_add(index) + [ Argument('type', default='int', type=str, choices=['int', 'real'], help='?'), Argument('eta', default=30, type=int, help='?'), ] @classmethod def from_args(cls, args: Namespace, index=None) -> Mutation: type_, eta = cls._parsed_arguments(['type', 'eta'], args, index=index) if type_ == 'int': return IntegerFromFloatMutation(clazz=PolynomialMutation, eta=eta) elif type_ == 'real': return PolynomialMutation(eta=eta) raise NotImplementedError

475

66

75

c5b1a0e5bbf1b1c1c34ff6523e7d2c68a22c4255

1,077

py

Python

list_files.py

diegomendesmoreno/stm8_standalone_programmer

6f37d0416c91ff6ff90df3d197b359a41bb23705

[ "MIT" ]

null

list_files.py

diegomendesmoreno/stm8_standalone_programmer

6f37d0416c91ff6ff90df3d197b359a41bb23705

[ "MIT" ]

null

list_files.py

diegomendesmoreno/stm8_standalone_programmer

6f37d0416c91ff6ff90df3d197b359a41bb23705

[ "MIT" ]

null

import os if __name__ == "__main__": file_list = FileList() file_list.list_files() print(file_list.num_files, "files listed") for f in file_list.files: print(f)

31.676471

59

0.508821

import os class FileList: def __init__(self): self.path = 'Bin/' # Search in the 'Bin' directory self.files = [] self.num_files = 0 def list_files(self): # r=root, d=directories, f = files for r, d, f in os.walk(self.path): for file in f: if '.s19' in file: self.files.append(os.path.join(file)) self.num_files = self.num_files + 1 if '.srec' in file: self.files.append(os.path.join(file)) self.num_files = self.num_files + 1 if '.ihx' in file: self.files.append(os.path.join(file)) self.num_files = self.num_files + 1 if '.hex' in file: self.files.append(os.path.join(file)) self.num_files = self.num_files + 1 if __name__ == "__main__": file_list = FileList() file_list.list_files() print(file_list.num_files, "files listed") for f in file_list.files: print(f)

819

-6

76

950517294b314e4c36db0912d9df4efeae2545e1

7,534

py

Python

cows/service/imps/csmlbackend/wfs_csmlstoredqueries.py

cedadev/cows

db9ed729c886b271ce85355b97e39243081e8246

[ "BSD-2-Clause" ]

2

2018-05-09T16:12:43.000Z

2018-08-21T17:10:22.000Z

cows/service/imps/csmlbackend/wfs_csmlstoredqueries.py

cedadev/cows

db9ed729c886b271ce85355b97e39243081e8246

[ "BSD-2-Clause" ]

null

cows/service/imps/csmlbackend/wfs_csmlstoredqueries.py

cedadev/cows

db9ed729c886b271ce85355b97e39243081e8246

[ "BSD-2-Clause" ]

null

# BSD Licence # Copyright (c) 2009, Science & Technology Facilities Council (STFC) # All rights reserved. # # See the LICENSE file in the source distribution of this software for # the full license text. """ This module contains CSML WFS 2.0 stored query implementations. To add a new stored query, write the functional code here, then describe the functionality as a new query in: wfs_csmllayer.CSMLStoredQueries.queries These query functions should either return a resultset (python list) containing the features, or 2 lists, one being the resultset, and the other containing string representations of XML addtional objects - in CSML these are going to be StorageDescriptors. """ import wfs_csmllayer import logging log = logging.getLogger(__name__) import csml.parser, csml.csmllibs.csmlextra from xml.etree import ElementTree as etree from pylons import request, config # qualifiedFeatureType='{http://ndg.nerc.ac.uk/csml}' + storagedescriptor.__class__.__name__ # emptyelem=etree.Element(qualifiedFeatureType) # log.debug(request.environ) # storagedescriptor.fileName.CONTENT='http://'+request.environ['HTTP_HOST']+'/filestore/' +storagedescriptor.fileName.CONTENT # csmlelem=storagedescriptor.toXML(emptyelem) # storagedescXML=etree.tostring(csmlelem) # return [csmlfi], [storagedescXML]

50.226667

157

0.765729

# BSD Licence # Copyright (c) 2009, Science & Technology Facilities Council (STFC) # All rights reserved. # # See the LICENSE file in the source distribution of this software for # the full license text. """ This module contains CSML WFS 2.0 stored query implementations. To add a new stored query, write the functional code here, then describe the functionality as a new query in: wfs_csmllayer.CSMLStoredQueries.queries These query functions should either return a resultset (python list) containing the features, or 2 lists, one being the resultset, and the other containing string representations of XML addtional objects - in CSML these are going to be StorageDescriptors. """ import wfs_csmllayer import logging log = logging.getLogger(__name__) import csml.parser, csml.csmllibs.csmlextra from xml.etree import ElementTree as etree from pylons import request, config class dummyfeaturefortesting(object): def __init__(self, x): self.x=x def toGML(self): return '<someGML>%s</someGML>'%self.x def _getCSMLFilename(): return 'csml%s.nc'%(csml.csmllibs.csmlextra.getRandomID()) def query_one_func(featureset, arg1='string1', arg2='string2'): result = [dummyfeaturefortesting(arg1 + ' ' + arg2)] return result def query_getFeatureByPhenomenon(featureset, phenomenon): return featureset.getFeaturesByPropertyEqualTo('csml:parameter', phenomenon) def query_getFeatureById(featureset, id): return [featureset.getFeatureByGMLid(id)] def query_extractPointFromPointSeries(featureset, featureid, timeinstance): #TODO: configure output directory #TODO: error handling csmloutputdir=config['cows.csml.publish_dir'] feature=featureset.getFeatureByGMLid(featureid)._feature ncname=_getCSMLFilename() newfeature, netcdfpath, storagedescriptor=feature.subsetToPoint(time=str(timeinstance), ncname=ncname, outputdir=csmloutputdir) #modify the rangeset of the feature to store the data inline and discard the storage descriptor. storagedescriptor.fileName.CONTENT=csmloutputdir+'/'+storagedescriptor.fileName.CONTENT data=storagedescriptor.getData() qlist=csml.parser.MeasureOrNullList() qlist.uom=newfeature.value.rangeSet.valueArray.valueComponent.uom qlist.CONTENT=str(data[0]) rs=csml.parser.RangeSet() rs.quantityList=qlist newfeature.value.rangeSet=rs #wrap the feature in a wfs CSMLFeatureInstance object: csmlfi=wfs_csmllayer.CSMLFeatureInstance('subset feature title', 'subset feature abstract', newfeature) return [csmlfi] #This following code is used to maintain the storage descriptor filename consistency, but has been commented out for this #operation as there is only a single point value. However code is left here as reminder as it will be needed #for other feature types soon #change the path of the storage descriptor to the download url - assumes routes maps to filestore #And serialise the storage descriptor as XML. # qualifiedFeatureType='{http://ndg.nerc.ac.uk/csml}' + storagedescriptor.__class__.__name__ # emptyelem=etree.Element(qualifiedFeatureType) # log.debug(request.environ) # storagedescriptor.fileName.CONTENT='http://'+request.environ['HTTP_HOST']+'/filestore/' +storagedescriptor.fileName.CONTENT # csmlelem=storagedescriptor.toXML(emptyelem) # storagedescXML=etree.tostring(csmlelem) # return [csmlfi], [storagedescXML] def query_extractPointSeriesFromPointSeries(featureset, featureid, starttime, endtime): csmloutputdir=config['cows.csml.publish_dir'] feature=featureset.getFeatureByGMLid(featureid)._feature timerange=(starttime, endtime,) subsetdictionary={'times':timerange} ncname=_getCSMLFilename() newfeature, netcdfpath, storagedescriptor=feature.subsetToPointSeries(outputdir=csmloutputdir, ncname=ncname,**subsetdictionary) #wrap this in a wfs CSMLFeatureInstance object: csmlfi=wfs_csmllayer.CSMLFeatureInstance('subset feature title', 'subset feature abstract', newfeature) #And serialise the storage descriptor as XML. qualifiedFeatureType='{http://ndg.nerc.ac.uk/csml}' + storagedescriptor.__class__.__name__ emptyelem=etree.Element(qualifiedFeatureType) log.debug(request.environ) #change the path of the storage descriptor to the download url - assumes routes maps to filestore #TODO: THIS SHOULD HANDLE SERVER PROXIES. storagedescriptor.fileName.CONTENT='http://'+request.environ['HTTP_HOST']+'/filestore/' +ncname csmlelem=storagedescriptor.toXML(emptyelem) storagedescXML=etree.tostring(csmlelem) return [csmlfi], [storagedescXML] def query_extractPointSeriesFromGridSeries(featureset, featureid, latitude, longitude, mintime, maxtime): csmloutputdir=config['cows.csml.publish_dir'] feature=featureset.getFeatureByGMLid(featureid)._feature timerange=(mintime, maxtime,) lat=float(latitude) lon=float(longitude) subsetdictionary={'time':timerange, 'latitude':lat, 'longitude':lon} ncname=_getCSMLFilename() newfeature, netcdfpath, storagedescriptor=feature.subsetToPointSeries(outputdir=csmloutputdir, ncname=ncname,**subsetdictionary) #wrap this in a wfs CSMLFeatureInstance object: csmlfi=wfs_csmllayer.CSMLFeatureInstance('subset feature title', 'subset feature abstract', newfeature) #And serialise the storage descriptor as XML. qualifiedFeatureType='{http://ndg.nerc.ac.uk/csml}' + storagedescriptor.__class__.__name__ emptyelem=etree.Element(qualifiedFeatureType) log.debug(request.environ) #change the path of the storage descriptor to the download url - assumes routes maps to filestore #TODO: THIS SHOULD HANDLE SERVER PROXIES. storagedescriptor.fileName.CONTENT='http://'+request.environ['HTTP_HOST']+'/filestore/' +ncname csmlelem=storagedescriptor.toXML(emptyelem) storagedescXML=etree.tostring(csmlelem) return [csmlfi], [storagedescXML] def query_extractGridSeriesFromGridSeries(featureset, featureid, bbox, mintime, maxtime): #TODO factor out code in common with other subsetting queries csmloutputdir=config['cows.csml.publish_dir'] feature=featureset.getFeatureByGMLid(featureid)._feature timerange=(mintime, maxtime,) #break the bounding box into latitude and longitude: #TODO, this really needs to be generic and refer to the srs of the underlying feature. bb=str(bbox).split(',') lat=(float(bb[1]),float(bb[3])) lon=(float(bb[0]),float(bb[2])) log.debug('requesting latitude: %s, longitude: %s'%(lat, lon)) ncname=_getCSMLFilename() newfeature, netcdfpath, storagedescriptor=feature.subsetToGridSeries(time=timerange, latitude=lat, longitude=lon, ncname=ncname, outputdir=csmloutputdir) #wrap this in a wfs CSMLFeatureInstance object: csmlfi=wfs_csmllayer.CSMLFeatureInstance('subset feature title', 'subset feature abstract', newfeature) #And serialise the storage descriptor as XML. qualifiedFeatureType='{http://ndg.nerc.ac.uk/csml}' + storagedescriptor.__class__.__name__ emptyelem=etree.Element(qualifiedFeatureType) log.debug(request.environ) #change the path of the storage descriptor to the download url - assumes routes maps to filestore storagedescriptor.fileName.CONTENT='http://'+request.environ['HTTP_HOST']+'/filestore/' +storagedescriptor.fileName.CONTENT csmlelem=storagedescriptor.toXML(emptyelem) storagedescXML=etree.tostring(csmlelem) return [csmlfi], [storagedescXML]

5,914

16

263

5bf3053088af5e798861a4a5b0c9a40c7343b799

1,383

py

Python

markov_chain/specialists.py

pesikj/DataAnalysisUsingPython

00269a7a7b5388fbbdcf3ddadd951a80a07f9c3a

[ "MIT" ]

null

markov_chain/specialists.py

pesikj/DataAnalysisUsingPython

00269a7a7b5388fbbdcf3ddadd951a80a07f9c3a

[ "MIT" ]

null

markov_chain/specialists.py

pesikj/DataAnalysisUsingPython

00269a7a7b5388fbbdcf3ddadd951a80a07f9c3a

[ "MIT" ]

null

import numpy as np from numpy.linalg import inv from scipy.stats import binom #a1 = failed #a2 = passed testPassingProbabilities = [0.7, 0.6, 0.8, 0.9] noOfSpecialistsCurrent = [100, 70, 50, 60] wantedSpecialists = 5 wantedWithProbability = 0.9 transitionMatrix = np.zeros((len(testPassingProbabilities) + 2, len(testPassingProbabilities) + 2)) transitionMatrix[0, 0] = 1 transitionMatrix[1, 1] = 1 for i in range(2, len(testPassingProbabilities) + 1): listIndex = i - 2 transitionMatrix[i, 0] = 1 - testPassingProbabilities[listIndex] transitionMatrix[i, i+1] = testPassingProbabilities[listIndex] transitionMatrix[i+1, 0] = 1 - testPassingProbabilities[-1] transitionMatrix[i+1, 1] = testPassingProbabilities[-1] Q = transitionMatrix[2:,2:] I = np.identity(len(testPassingProbabilities)) N = inv(I - Q) R = transitionMatrix[2:,:2] B = np.dot(N,R) passVector = B[:, 1] noOfSpecialistsFinal = round(sum(passVector * noOfSpecialistsCurrent), 3) print(f"The expected number of specialists is {noOfSpecialistsFinal}.") newStudentPassingProbability = float(passVector[0]) for employeesSentToCourse in range(wantedSpecialists, 100): probability = 1 - binom.cdf(wantedSpecialists - 1, employeesSentToCourse, newStudentPassingProbability) if probability > wantedWithProbability: print(f"{employeesSentToCourse} must be sent to the course.") break

34.575

107

0.748373

import numpy as np from numpy.linalg import inv from scipy.stats import binom #a1 = failed #a2 = passed testPassingProbabilities = [0.7, 0.6, 0.8, 0.9] noOfSpecialistsCurrent = [100, 70, 50, 60] wantedSpecialists = 5 wantedWithProbability = 0.9 transitionMatrix = np.zeros((len(testPassingProbabilities) + 2, len(testPassingProbabilities) + 2)) transitionMatrix[0, 0] = 1 transitionMatrix[1, 1] = 1 for i in range(2, len(testPassingProbabilities) + 1): listIndex = i - 2 transitionMatrix[i, 0] = 1 - testPassingProbabilities[listIndex] transitionMatrix[i, i+1] = testPassingProbabilities[listIndex] transitionMatrix[i+1, 0] = 1 - testPassingProbabilities[-1] transitionMatrix[i+1, 1] = testPassingProbabilities[-1] Q = transitionMatrix[2:,2:] I = np.identity(len(testPassingProbabilities)) N = inv(I - Q) R = transitionMatrix[2:,:2] B = np.dot(N,R) passVector = B[:, 1] noOfSpecialistsFinal = round(sum(passVector * noOfSpecialistsCurrent), 3) print(f"The expected number of specialists is {noOfSpecialistsFinal}.") newStudentPassingProbability = float(passVector[0]) for employeesSentToCourse in range(wantedSpecialists, 100): probability = 1 - binom.cdf(wantedSpecialists - 1, employeesSentToCourse, newStudentPassingProbability) if probability > wantedWithProbability: print(f"{employeesSentToCourse} must be sent to the course.") break

0

83de024d990b9741a3362c8d9bb1b9a580904364

14,833

py

Python

eosfactory/shell/wallet.py

ephdtrg/eosfactory

721843707cb277618142c6d9518e3f231cae3b79

[ "MIT" ]

null

eosfactory/shell/wallet.py

ephdtrg/eosfactory

721843707cb277618142c6d9518e3f231cae3b79

[ "MIT" ]

null

eosfactory/shell/wallet.py

ephdtrg/eosfactory

721843707cb277618142c6d9518e3f231cae3b79

[ "MIT" ]

null

import os import json import inspect import eosfactory.core.logger as logger import eosfactory.core.errors as errors import eosfactory.core.setup as setup import eosfactory.core.interface as interface import eosfactory.core.teos as teos if setup.node_api == "cleos": import eosfactory.core.cleos as cleos elif setup.node_api == "eosjs": import eosfactory.core.eosjs as cleos import eosfactory.core.manager as manager class Wallet(cleos.WalletCreate): ''' Create a new wallet locally and operate it. - **parameters**:: name: The name of the new wallet, defaults to `default`. is_verbose: If `0`, do not print unless on error, default is `1`. - **attributes**:: name: The name of the wallet. password: The password returned by wallet create. error: Whether any error ocurred. json: The json representation of the object. is_verbose: Verbosity at the constraction time. ''' wallet_keys = None wallet = None globals = None setup.node_api def index(self): ''' Lists opened wallets, * marks unlocked. Returns `cleos.WalletList` object ''' result = cleos.WalletList(is_verbose=0) logger.OUT(result.out_msg) def open(self): ''' Opens the wallet. Returns `WalletOpen` object ''' result = cleos.WalletOpen(self.name, is_verbose=False) logger.TRACE(''' * Wallet ``{}`` opened. '''.format(self.name)) def lock(self): ''' Lock the wallet. Returns `cleos.WalletLock` object. ''' result = cleos.WalletLock(self.name, is_verbose=False) logger.TRACE("Wallet `{}` locked.".format(self.name)) def lock_all(self): ''' Lock the wallet. Returns `cleos.WalletLock` object. ''' result = cleos.WalletLockAll(is_verbose=False) logger.TRACE("All wallets locked.") def unlock(self): ''' Unlock the wallet. Returns `WalletUnlock` object. ''' result = cleos.WalletUnlock( self.name, self.password, is_verbose=False) logger.TRACE(''' * Wallet ``{}`` unlocked. '''.format(self.name)) def open_unlock(self): ''' Open&Unlock automatics. ''' cleos.WalletOpen(self.name, is_verbose=False) cleos.WalletUnlock( self.name, self.password, is_verbose=False) def remove_key(self, account_or_key): ''' ''' self.open_unlock() removed_keys = [] account_name = None if isinstance(account_or_key, interface.Account): cleos.WalletRemove_key( interface.key_arg( account_or_key, is_owner_key=True, is_private_key=True), self.name, is_verbose=False) removed_keys.append(interface.key_arg( account_or_key, is_owner_key=True, is_private_key=False)) cleos.WalletRemove_key( interface.key_arg( account_or_key, is_owner_key=False, is_private_key=True), self.name, is_verbose=False) removed_keys.append(interface.key_arg( account_or_key, is_owner_key=False, is_private_key=False)) else: cleos.WalletRemove_key( interface.key_arg( account_or_key, is_private_key=True), self.name, is_verbose=False) removed_keys.append(interface.key_arg( account_or_key, is_private_key=False)) if account_name is None: if len(removed_keys) > 0: logger.TRACE(''' Removing key '{}' from the wallet '{}' '''.format(removed_keys[0], self.name), verbosity ) else: logger.TRACE(''' Removing keys of the account '{}' from the wallet '{}' '''.format(account_name, self.name) ) wallet_keys = cleos.WalletKeys(is_verbose=False) for key in removed_keys: if key in wallet_keys.json: raise errors.Error(''' Failed to remove key '{}' from the wallet '{}' '''.format(key, self.name)) logger.TRACE(''' * Cross-checked: all listed keys removed from the wallet. ''') return True def import_key(self, account_or_key): ''' Imports private keys of an account into wallet. Returns list of `cleos.WalletImport` objects ''' self.open_unlock() imported_keys = [] account_name = None if isinstance(account_or_key, interface.Account): account_name = account_or_key.name wallet_import = cleos.WalletImport( interface.key_arg( account_or_key, is_owner_key=True, is_private_key=True), self.name, is_verbose=False) imported_keys.append(interface.key_arg( account_or_key, is_owner_key=True, is_private_key=False)) wallet_import = cleos.WalletImport( interface.key_arg( account_or_key, is_owner_key=False, is_private_key=True), self.name, is_verbose=False) imported_keys.append(interface.key_arg( account_or_key, is_owner_key=False, is_private_key=False)) logger.TRACE(''' * Importing keys of the account ``{}`` into the wallet ``{}`` '''.format(account_name, self.name) ) else: wallet_import = cleos.WalletImport( interface.key_arg(account_or_key, is_private_key=True), self.name, is_verbose=False) logger.TRACE(''' * Importing keys into the wallet ``{}`` '''.format(self.name) ) return True wallet_keys = cleos.WalletKeys(is_verbose=False) if len(imported_keys) == 0: raise errors.Error(''' The list of imported keys is empty. ''') ok = True for key in imported_keys: if not key in wallet_keys.json: ok = False raise errors.Error(''' Failed to import keys of the account '{}' into the wallet '{}' '''.format( account_name if account_name else "n/a", self.name)) if ok: logger.TRACE(''' * Cross-checked: all account keys are in the wallet. ''') return True def restore_accounts(self): ''' ''' self.open_unlock() account_map = manager.account_map() new_map = {} wallet_keys = cleos.WalletKeys(is_verbose=0) if len(account_map) > 0: logger.INFO(''' ######### Restore cached account objects: ''') for name, object_name in account_map.items(): try: account_ = cleos.GetAccount( name, is_info=False, is_verbose=False) if account_.owner_key in wallet_keys.json and \ account_.active_key in wallet_keys.json: new_map[name] = object_name from eosfactory.shell.account import create_account create_account( object_name, name, restore=True, verbosity=None) except errors.AccountDoesNotExistError: pass manager.save_account_map(new_map) else: logger.INFO(''' * The wallet is empty. ''') def keys(self): ''' Lists public keys from all unlocked wallets. Returns `cleos.WalletKeys` object. ''' self.open_unlock() self.wallet_keys = cleos.WalletKeys(is_verbose=False) logger.TRACE(''' Keys in all open walets: {} '''.format(self.wallet_keys.out_msg)) def private_keys(self): ''' Lists public keys from all unlocked wallets. Returns `cleos.WalletKeys` object. ''' self.open_unlock() self.wallet_private_keys = cleos.WalletPrivateKeys(is_verbose=False) logger.TRACE(''' Keys in all open walets: {} '''.format(json.dumps( self.wallet_private_keys.json, indent=4))) def map_account(self, account_object_name, account_object): ''' ''' if not self.is_name_taken(account_object_name, account_object.name): account_map_json = manager.account_map(self) if account_map_json is None: return account_map_json[account_object.name] = account_object_name with open(self.wallet_dir + setup.account_map, "w") as out: out.write(json.dumps( account_map_json, indent=3, sort_keys=True)) logger.TRACE(''' * Account object ``{}`` stored in the file ``{}`` in the wallet directory: {} '''.format( account_object_name, setup.account_map, self.wallet_dir + setup.account_map))

34.256351

103

0.523697

import os import json import inspect import eosfactory.core.logger as logger import eosfactory.core.errors as errors import eosfactory.core.setup as setup import eosfactory.core.interface as interface import eosfactory.core.teos as teos if setup.node_api == "cleos": import eosfactory.core.cleos as cleos elif setup.node_api == "eosjs": import eosfactory.core.eosjs as cleos import eosfactory.core.manager as manager def wallet_json_read(): try: with open(manager.wallet_dir() + setup.password_map, "r") as input: return json.load(input) except: return {} def wallet_json_write(wallet_json): with open(manager.wallet_dir() + setup.password_map, "w+") as out: json.dump(wallet_json, out) def create_wallet( name=None, password=None, verbosity=None, file=False, globals=None): if globals: Wallet.globals = globals else: Wallet.globals = inspect.stack()[1][0].f_globals Wallet.wallet = Wallet(name, password, verbosity, file) Wallet.wallet.restore_accounts() def get_wallet(): return Wallet.wallet class Wallet(cleos.WalletCreate): ''' Create a new wallet locally and operate it. - **parameters**:: name: The name of the new wallet, defaults to `default`. is_verbose: If `0`, do not print unless on error, default is `1`. - **attributes**:: name: The name of the wallet. password: The password returned by wallet create. error: Whether any error ocurred. json: The json representation of the object. is_verbose: Verbosity at the constraction time. ''' wallet_keys = None wallet = None globals = None setup.node_api def __init__(self, name=None, password="", verbosity=None, file=False): cleos.set_local_nodeos_address_if_none() if name is None: name = setup.wallet_default_name else: name = setup.file_prefix() + name if not self.wallet is None: raise errors.Error(''' It can be only one ``Wallet`` object in the script; there is one named ``{}``. '''.format(wallet.name)) return self.wallet_dir = manager.wallet_dir() logger.INFO(''' * Wallet name is ``{}``, wallet directory is {}. '''.format(name, self.wallet_dir)) if not password: # look for password: passwords = wallet_json_read() if name in passwords: password = passwords[name] logger.INFO(''' The password is restored from the file: {} '''.format( os.path.join(self.wallet_dir, setup.password_map)), verbosity) cleos.WalletCreate.__init__(self, name, password, is_verbose=False) if self.is_created: # new password logger.INFO(''' * Created wallet ``{}``. '''.format(self.name), verbosity ) ############################################################################### # TO DO: detect live node!!!!!!!!!! if manager.is_local_testnet() or file or True: ############################################################################### password_map = wallet_json_read() password_map[name] = self.password wallet_json_write(password_map) logger.INFO(''' * Password is saved to the file ``{}`` in the wallet directory. '''.format(setup.password_map), verbosity ) else: logger.OUT(self.out_msg) else: logger.TRACE(''' Opened wallet ``{}`` '''.format(self.name)) def index(self): ''' Lists opened wallets, * marks unlocked. Returns `cleos.WalletList` object ''' result = cleos.WalletList(is_verbose=0) logger.OUT(result.out_msg) def open(self): ''' Opens the wallet. Returns `WalletOpen` object ''' result = cleos.WalletOpen(self.name, is_verbose=False) logger.TRACE(''' * Wallet ``{}`` opened. '''.format(self.name)) def lock(self): ''' Lock the wallet. Returns `cleos.WalletLock` object. ''' result = cleos.WalletLock(self.name, is_verbose=False) logger.TRACE("Wallet `{}` locked.".format(self.name)) def lock_all(self): ''' Lock the wallet. Returns `cleos.WalletLock` object. ''' result = cleos.WalletLockAll(is_verbose=False) logger.TRACE("All wallets locked.") def unlock(self): ''' Unlock the wallet. Returns `WalletUnlock` object. ''' result = cleos.WalletUnlock( self.name, self.password, is_verbose=False) logger.TRACE(''' * Wallet ``{}`` unlocked. '''.format(self.name)) def open_unlock(self): ''' Open&Unlock automatics. ''' cleos.WalletOpen(self.name, is_verbose=False) cleos.WalletUnlock( self.name, self.password, is_verbose=False) def remove_key(self, account_or_key): ''' ''' self.open_unlock() removed_keys = [] account_name = None if isinstance(account_or_key, interface.Account): cleos.WalletRemove_key( interface.key_arg( account_or_key, is_owner_key=True, is_private_key=True), self.name, is_verbose=False) removed_keys.append(interface.key_arg( account_or_key, is_owner_key=True, is_private_key=False)) cleos.WalletRemove_key( interface.key_arg( account_or_key, is_owner_key=False, is_private_key=True), self.name, is_verbose=False) removed_keys.append(interface.key_arg( account_or_key, is_owner_key=False, is_private_key=False)) else: cleos.WalletRemove_key( interface.key_arg( account_or_key, is_private_key=True), self.name, is_verbose=False) removed_keys.append(interface.key_arg( account_or_key, is_private_key=False)) if account_name is None: if len(removed_keys) > 0: logger.TRACE(''' Removing key '{}' from the wallet '{}' '''.format(removed_keys[0], self.name), verbosity ) else: logger.TRACE(''' Removing keys of the account '{}' from the wallet '{}' '''.format(account_name, self.name) ) wallet_keys = cleos.WalletKeys(is_verbose=False) for key in removed_keys: if key in wallet_keys.json: raise errors.Error(''' Failed to remove key '{}' from the wallet '{}' '''.format(key, self.name)) logger.TRACE(''' * Cross-checked: all listed keys removed from the wallet. ''') return True def import_key(self, account_or_key): ''' Imports private keys of an account into wallet. Returns list of `cleos.WalletImport` objects ''' self.open_unlock() imported_keys = [] account_name = None if isinstance(account_or_key, interface.Account): account_name = account_or_key.name wallet_import = cleos.WalletImport( interface.key_arg( account_or_key, is_owner_key=True, is_private_key=True), self.name, is_verbose=False) imported_keys.append(interface.key_arg( account_or_key, is_owner_key=True, is_private_key=False)) wallet_import = cleos.WalletImport( interface.key_arg( account_or_key, is_owner_key=False, is_private_key=True), self.name, is_verbose=False) imported_keys.append(interface.key_arg( account_or_key, is_owner_key=False, is_private_key=False)) logger.TRACE(''' * Importing keys of the account ``{}`` into the wallet ``{}`` '''.format(account_name, self.name) ) else: wallet_import = cleos.WalletImport( interface.key_arg(account_or_key, is_private_key=True), self.name, is_verbose=False) logger.TRACE(''' * Importing keys into the wallet ``{}`` '''.format(self.name) ) return True wallet_keys = cleos.WalletKeys(is_verbose=False) if len(imported_keys) == 0: raise errors.Error(''' The list of imported keys is empty. ''') ok = True for key in imported_keys: if not key in wallet_keys.json: ok = False raise errors.Error(''' Failed to import keys of the account '{}' into the wallet '{}' '''.format( account_name if account_name else "n/a", self.name)) if ok: logger.TRACE(''' * Cross-checked: all account keys are in the wallet. ''') return True def keys_in_wallets(self, keys): self.open_unlock() result = cleos.WalletKeys(is_verbose=False) for key in keys: if not key in result.json: return False return True def restore_accounts(self): ''' ''' self.open_unlock() account_map = manager.account_map() new_map = {} wallet_keys = cleos.WalletKeys(is_verbose=0) if len(account_map) > 0: logger.INFO(''' ######### Restore cached account objects: ''') for name, object_name in account_map.items(): try: account_ = cleos.GetAccount( name, is_info=False, is_verbose=False) if account_.owner_key in wallet_keys.json and \ account_.active_key in wallet_keys.json: new_map[name] = object_name from eosfactory.shell.account import create_account create_account( object_name, name, restore=True, verbosity=None) except errors.AccountDoesNotExistError: pass manager.save_account_map(new_map) else: logger.INFO(''' * The wallet is empty. ''') def delete_globals(self): account_map = manager.account_map() for name, object_name in account_map.items(): del Wallet.globals[object_name] def stop(self): cleos.WalletStop() def keys(self): ''' Lists public keys from all unlocked wallets. Returns `cleos.WalletKeys` object. ''' self.open_unlock() self.wallet_keys = cleos.WalletKeys(is_verbose=False) logger.TRACE(''' Keys in all open walets: {} '''.format(self.wallet_keys.out_msg)) def private_keys(self): ''' Lists public keys from all unlocked wallets. Returns `cleos.WalletKeys` object. ''' self.open_unlock() self.wallet_private_keys = cleos.WalletPrivateKeys(is_verbose=False) logger.TRACE(''' Keys in all open walets: {} '''.format(json.dumps( self.wallet_private_keys.json, indent=4))) def edit_account_map(self, text_editor="nano"): manager.edit_account_map(text_editor) def is_name_taken(self, account_object_name, account_name): while True: account_map_json = manager.account_map(self) if account_map_json is None: return False is_taken = False for name, object_name in account_map_json.items(): if object_name == account_object_name: if not name == account_name: logger.OUT(''' The given account object name ``{}`` points to an existing account, of the name {}, mapped in a file in directory: {} Cannot overwrite it. However, you can free the name by changing the mapping. Do you want to edit the file? '''.format( account_object_name, name, self.wallet_dir)) is_taken = True break if is_taken: temp = None if account_object_name in Wallet.globals: temp = Wallet.globals[account_object_name] del Wallet.globals[account_object_name] answer = input("y/n <<< ") if answer == "y": manager.edit_account_map() continue else: if temp: Wallet.globals[account_object_name] = temp raise errors.Error(''' Use the function 'manager.edit_account_map(text_editor="nano")' to edit the file. ''') else: break def map_account(self, account_object_name, account_object): ''' ''' if not self.is_name_taken(account_object_name, account_object.name): account_map_json = manager.account_map(self) if account_map_json is None: return account_map_json[account_object.name] = account_object_name with open(self.wallet_dir + setup.account_map, "w") as out: out.write(json.dumps( account_map_json, indent=3, sort_keys=True)) logger.TRACE(''' * Account object ``{}`` stored in the file ``{}`` in the wallet directory: {} '''.format( account_object_name, setup.account_map, self.wallet_dir + setup.account_map))

4,932

0

265

9ff5a5ee62d2ada8f035ed015df587c46f476bb6

302

py

Python

codes/Ex074.py

BelfortJoao/Curso-phyton01

79376233be228f39bf548f90b8d9bd5419ac067a

[ "MIT" ]

3

2021-08-17T14:02:14.000Z

2021-08-19T02:37:30.000Z

codes/Ex074.py

BelfortJoao/Curso-phyton01

79376233be228f39bf548f90b8d9bd5419ac067a

[ "MIT" ]

null

codes/Ex074.py

BelfortJoao/Curso-phyton01

79376233be228f39bf548f90b8d9bd5419ac067a

[ "MIT" ]

null

from random import randint x = (randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10)) print('sorteei os numeros:', end='') for n in x: print(f'{n}', end=", ") print(f"\nO maior valor na ordem foi {max(x)}") print(f"\nO menor valor na ordem foi {min(x)}")

37.75

100

0.625828

from random import randint x = (randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10), randint(1, 10)) print('sorteei os numeros:', end='') for n in x: print(f'{n}', end=", ") print(f"\nO maior valor na ordem foi {max(x)}") print(f"\nO menor valor na ordem foi {min(x)}")

0

6c38fa0bd9e315dd1842c9792fab88a708b5c6cb

15,911

py

Python

extensions/mark_invoices.py

time-track-tool/time-track-tool

a1c280f32a7766e460c862633b748fa206256f24

[ "MIT" ]

null

extensions/mark_invoices.py

time-track-tool/time-track-tool

a1c280f32a7766e460c862633b748fa206256f24

[ "MIT" ]

1

2019-07-03T13:32:38.000Z

extensions/mark_invoices.py

time-track-tool/time-track-tool

a1c280f32a7766e460c862633b748fa206256f24

[ "MIT" ]

1

2019-05-15T16:01:31.000Z

#! /usr/bin/python # Copyright (C) 2005 Dr. Ralf Schlatterbeck Open Source Consulting. # Reichergasse 131, A-3411 Weidling. # Web: http://www.runtux.com Email: office@runtux.com # All rights reserved # **************************************************************************** # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. # **************************************************************************** from cStringIO import StringIO from os.path import splitext from roundup.cgi.actions import Action, EditItemAction from roundup.cgi import templating from roundup import hyperdb from roundup.date import Date, Interval from roundup.cgi.exceptions import Redirect try : import ooopy.Transforms as Transforms from ooopy.OOoPy import OOoPy from ooopy.Transformer import Transformer, autosuper from ooopy.Transforms import renumber_all, get_meta, set_meta except ImportError : from rsclib.autosuper import autosuper Reject = ValueError # end class Invoice # end class Unmark_Invoice # end class Mark_Invoice # end class OOoPy_Invoice_Wrapper # end class Generate_Invoice # end class _Mark_Invoice # end class Mark_Invoice_Sent # end class Mark_Single_Invoice_Sent # end def create_file # end def handle # end class Download_Letter # end def handle # end class Personalized_Template class Edit_Payment_Action (EditItemAction, autosuper) : """ Remove items that did not change (for which we defined a hidden attribute in the mask) from the new items. Then proceed as usual like for EditItemAction. """ # end def _editnodes # end class Edit_Payment_Action # end def init

35.515625

80

0.539941

#! /usr/bin/python # Copyright (C) 2005 Dr. Ralf Schlatterbeck Open Source Consulting. # Reichergasse 131, A-3411 Weidling. # Web: http://www.runtux.com Email: office@runtux.com # All rights reserved # **************************************************************************** # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. # **************************************************************************** from cStringIO import StringIO from os.path import splitext from roundup.cgi.actions import Action, EditItemAction from roundup.cgi import templating from roundup import hyperdb from roundup.date import Date, Interval from roundup.cgi.exceptions import Redirect try : import ooopy.Transforms as Transforms from ooopy.OOoPy import OOoPy from ooopy.Transformer import Transformer, autosuper from ooopy.Transforms import renumber_all, get_meta, set_meta except ImportError : from rsclib.autosuper import autosuper Reject = ValueError class Invoice (Action, autosuper) : name = 'invoice actions' permissionType = 'Edit' def marked (self, send_it = False) : marked_spec = {'invoice_group' : self.invoice_group} if send_it : marked_spec ['send_it'] = True return self.db.invoice.filter (None, marked_spec) # end def marked def get_iv_template (self, iv) : """ Get the correct invoice_template for the invoice_level <= n_sent for the current invoice. """ db = self.db aboprice = db.abo.get (iv ['abo'], 'aboprice') iv_tmplates = db.abo_price.get (aboprice, 'invoice_template') if not iv_tmplates : raise Reject, \ ( db._ ('No invoice_template defined for all invoices: %s') % iv ['invoice_no'] ) ivts = [db.invoice_template.getnode (i) for i in iv_tmplates] ivts = [i for i in ivts if i ['invoice_level'] <= iv ['n_sent']] if not ivts : raise Reject, \ ( db._ ('No matching invoice_template for invoice %s') % iv ['invoice_no'] ) max = ivts [0] for ivt in ivts : if ivt ['invoice_level'] > max ['invoice_level'] : max = ivt return max # end def get_iv_template def handle (self) : # figure the request request = templating.HTMLRequest (self.client) filterspec = request.filterspec if request.classname != 'invoice' : raise Reject, self.db._ ('You can only mark invoices') # get invoice_group -- if existing: self.invoice_group = None try : self.invoice_group = filterspec ['invoice_group'][0] except KeyError : pass # end def handle def _unmark (self) : for i in self.marked () : self.db.invoice.set (i, invoice_group = None) self.db.commit () # end def _unmark def redirect (self) : url = templating.HTMLRequest (self.client).indexargs_url \ ('' , { '@template' : 'send' }) raise Redirect, url # end def redirect # end class Invoice class Unmark_Invoice (Invoice) : name = 'unmark' def handle (self) : ''' Remove mark created by Mark_Invoice. ''' self.__super.handle () self._unmark () self.redirect () # end def handle # end class Unmark_Invoice class Mark_Invoice (Invoice) : name = 'mark' def iv_filter (self, ids) : """ Filter invoices for - invoice belongs to a running subscription - invoice is in the correct self.invoice_group - correct interval: We do not want to send invoices before the interval of the invoice_template has expired after sending the last invoice (last_sent < now - interval) where interval is in months """ db = self.db retval = [] for id in ids : iv = self.db.invoice.getnode (id) abo = self.db.abo.getnode (iv ['abo']) if abo ['end'] : continue grp = self.db.abo_price.get (abo ['aboprice'], 'invoice_group') if grp != self.invoice_group : continue ivt = self.get_iv_template (iv) interval = ivt ['interval'] if iv ['last_sent'] > self.now - Interval ('%dm' % interval) : continue retval.append (iv) return retval # end def iv_filter def handle (self) : ''' Mark invoices with the given invoice_group. ''' self.__super.handle () self.now = Date ('.') if self.marked () : raise Reject, self.db._ ('invoices are already marked') invoice = self.db.invoice spec = \ { 'open' : True , 'period_start' : ';1m' } ids = invoice.filter (None, spec) invoices = self.iv_filter (ids) for i in invoices : invoice.set \ (i ['id'], send_it = True, invoice_group = self.invoice_group) self.db.commit () self.redirect () # end def handle # end class Mark_Invoice class OOoPy_Invoice_Wrapper (autosuper) : def __init__ (self, db, iv, date = None, address = None) : self.db = db if not date : date = Date ('.') self.items = {'date' : date} if iv : self.items ['invoice'] = iv if not address : address = self._deref ('invoice.payer') self.items ['address'] = address # end def __init__ def _pretty (self, item) : if isinstance (item, Date) : return item.pretty ('%d. %m. %Y') return str (item).decode ('utf-8') # end def _pretty def _deref (self, name) : """ dereference a dotted name -- we may want to cache this.""" names = name.split ('.') x = self.items [names [0]] if not x : raise KeyError, names [0] for i in names [1:] : p = x.cl.properties [i] if isinstance (p, hyperdb.Link) : x = self.db.getclass (p.classname).getnode (x [i]) else : x = x [i] if x : return x return "" # end def _split def __getitem__ (self, name) : return self._pretty (self._deref (name)) # end def __getitem__ def has_key (self, name) : try : self._deref (name) except KeyError : return False return True # end def has_key __contains__ = has_key # end class OOoPy_Invoice_Wrapper class Generate_Invoice (Invoice) : def handle (self) : ''' Prepare invoices for printout and send to browser.''' self.__super.handle () mimetype = None extension = None invoices = [self.db.invoice.getnode (i) for i in self.marked (True)] ivts = [(self.get_iv_template (i), i) for i in invoices] iv_by_tid = {} tp_by_tid = {} for i in ivts : tid = i [0]['id'] if tid not in iv_by_tid : iv_by_tid [tid] = [] tp_by_tid [tid] = i [0] iv_by_tid [tid].append (OOoPy_Invoice_Wrapper (self.db, i [1])) sio = {} for tid, tp in tp_by_tid.iteritems () : sio [tid] = StringIO () fileid = self.db.tmplate.get (tp ['tmplate'], 'files')[-1] file = StringIO (self.db.file.get (fileid, 'content')) extension = splitext (self.db.file.get (fileid, 'name'))[1] o = OOoPy (infile = file, outfile = sio [tid]) t = Transformer \ ( o.mimetype , get_meta (o.mimetype) , Transforms.Addpagebreak_Style () , Transforms.Mailmerge (iterator = iv_by_tid [tid]) , renumber_all (o.mimetype) , set_meta (o.mimetype) , Transforms.Fix_OOo_Tag () ) t.transform (o) mimetype = o.mimetype o.close () outfiles = sio.values () if len (outfiles) > 1 : out = StringIO () o = OOoPy (infile = outfiles [0], outfile = out) t = Transformer \ ( o.mimetype , get_meta (o.mimetype) , Transforms.Concatenate (* (outfiles [1:])) , renumber_all (o.mimetype) , set_meta (o.mimetype) , Transforms.Fix_OOo_Tag () ) t.transform (o) o.close () else : out = outfiles [0] h = self.client.additional_headers h ['Content-Type'] = mimetype h ['Content-Disposition'] = 'inline; filename=inv%s' % extension self.client.header () return out.getvalue () # end def handle # end class Generate_Invoice class _Mark_Invoice (Invoice) : def _mark_ivs (self, invoices) : ''' Mark the marked invoices as sent.''' now = Date ('.') for iv in invoices : id = iv ['id'] ivt = self.get_iv_template (iv) file = self.db.tmplate.get (ivt ['tmplate'], 'files') [-1] letter = self.db.letter.create \ ( subject = ivt ['name'] , address = iv.payer , date = now , files = [file] , messages = [] , invoice = id ) letters = iv ['letters'] letters.append (letter) self.db.invoice.set \ ( id , letters = letters , n_sent = iv ['n_sent'] + 1 , last_sent = now ) # end def _mark_ivs # end class _Mark_Invoice class Mark_Invoice_Sent (_Mark_Invoice) : def handle (self) : ''' Mark the marked invoices as sent and remove mark.''' self.__super.handle () invoices = [self.db.invoice.getnode (i) for i in self.marked (True)] self._mark_ivs (invoices) self._unmark () self.db.commit () self.redirect () # end def handle # end class Mark_Invoice_Sent class Mark_Single_Invoice_Sent (_Mark_Invoice) : def handle (self) : '''get current invoice and handle it''' self.__super.handle () invoice = self.db.invoice.getnode (self.context ['context'].id) invoices = [invoice] self._mark_ivs (invoices) self.db.commit () raise Redirect ('invoice%s' % invoice.id) # end def handle # end class Mark_Single_Invoice_Sent class Download_Letter (Action, autosuper) : def create_file (self, file, invoice, date, address) : if ( file.type not in ( 'application/vnd.sun.xml.writer' , 'application/vnd.oasis.opendocument.text' ) and splitext (file.name) [1] not in ('.sxw', '.odt') ) : raise Redirect, 'file%s/%s' % (file.id, file.name) out = StringIO () o = OOoPy (infile = StringIO (file.content), outfile = out) t = Transformer \ ( o.mimetype , Transforms.Editinfo () , Transforms.Field_Replace ( replace = OOoPy_Invoice_Wrapper (self.db, invoice, date, address) ) , Transforms.Fix_OOo_Tag () ) t.transform (o) o.close () h = self.client.additional_headers h ['Content-Type'] = file.type h ['Content-Disposition'] = 'inline; filename=inv.sxw' self.client.header () return out.getvalue () # end def create_file def handle (self) : request = templating.HTMLRequest (self.client) filterspec = request.filterspec if request.classname != 'letter' : raise Reject, self.db._ ('You can only download letters') # get id: try : self.id = request.form ['id'].value except KeyError : self.id = filterspec ['id'][0] letter = self.db.letter.getnode (str (self.id)) files = letter.files if not files : raise Redirect, 'letter%s' % self.id invoice = letter.invoice if invoice : invoice = self.db.invoice.getnode (invoice) return self.create_file \ ( self.db.file.getnode (files [0]) , invoice , letter.date , self.db.address.getnode (letter.address) ) # end def handle # end class Download_Letter class Personalized_Template (Download_Letter) : def handle (self) : request = templating.HTMLRequest (self.client) filterspec = request.filterspec _ = self.db._ if request.classname != 'address' : raise Reject, _ ('You can only download templates for an address') try : template = request.form ['tmplate'].value except KeyError : template = filterspec ['tmplate'][0] template = self.db.tmplate.getnode (template) address = self.db.address.getnode (self.context ['context'].id) files = template.files if not files : raise Reject, _ ('No files for %(tmplate)s' % template.name) return self.create_file \ ( self.db.file.getnode (files [0]) , None , Date ('.') , address ) # end def handle # end class Personalized_Template class Edit_Payment_Action (EditItemAction, autosuper) : """ Remove items that did not change (for which we defined a hidden attribute in the mask) from the new items. Then proceed as usual like for EditItemAction. """ def _editnodes (self, props, links) : # use props.items here, with iteritems we get a RuntimeError # "dictionary changed size during iteration" for (cl, id), val in props.items () : if ( cl == 'payment' and int (id) < 0 and sorted (val.keys ()) == ['invoice', 'receipt_no'] and val ['receipt_no'] == 'auto' ) : del props [(cl, id)] return EditItemAction._editnodes (self, props, links) # end def _editnodes # end class Edit_Payment_Action def init (instance) : reg = instance.registerAction reg ('mark_invoice', Mark_Invoice) reg ('unmark_invoice', Unmark_Invoice) reg ('mark_invoice_sent', Mark_Invoice_Sent) reg ('generate_invoice', Generate_Invoice) reg ('mark_single_invoice_sent', Mark_Single_Invoice_Sent) reg ('download_letter', Download_Letter) reg ('personalized_template', Personalized_Template) reg ('edit_payment', Edit_Payment_Action) # end def init

5,128

7,965

358

91e13dc5dce4394facd41c473ef017637c7b7efb

3,614

py

Python

lib/market/market_quote.py

myron0330/metatrade

b0358ad3dce6ba50e4801b6af557d7883d8a5d9a

[ "MIT" ]

1

2018-06-28T09:49:08.000Z

lib/market/market_quote.py

myron0330/metatrade

b0358ad3dce6ba50e4801b6af557d7883d8a5d9a

[ "MIT" ]

null

lib/market/market_quote.py

myron0330/metatrade

b0358ad3dce6ba50e4801b6af557d7883d8a5d9a

[ "MIT" ]

null

# -*- coding: UTF-8 -*- # **********************************************************************************# # File: # **********************************************************************************# import time from datetime import datetime from utils.dict import CompositeDict from utils.decorator import singleton from .. configs import logger from .. data.database_api import load_futures_rt_minute_data def _get_minute_price_info(universe): """ Get the latest info of stocks. Args: universe(list): universe list """ futures_rt_minute_data = load_futures_rt_minute_data(universe) info = dict() for symbol, minute_bar_list in futures_rt_minute_data.iteritems(): if minute_bar_list: item = minute_bar_list[-1] item.update({ 'secID': symbol }) info[symbol] = minute_bar_list[-1] return info @singleton

34.75

101

0.522413

# -*- coding: UTF-8 -*- # **********************************************************************************# # File: # **********************************************************************************# import time from datetime import datetime from utils.dict import CompositeDict from utils.decorator import singleton from .. configs import logger from .. data.database_api import load_futures_rt_minute_data def _get_minute_price_info(universe): """ Get the latest info of stocks. Args: universe(list): universe list """ futures_rt_minute_data = load_futures_rt_minute_data(universe) info = dict() for symbol, minute_bar_list in futures_rt_minute_data.iteritems(): if minute_bar_list: item = minute_bar_list[-1] item.update({ 'secID': symbol }) info[symbol] = minute_bar_list[-1] return info @singleton class MarketQuote(object): def __init__(self, clock=None, universe=None, bar_collection=None): self.clock = clock self.universe = universe self.bar_collection = bar_collection or dict() self._bar_version = -1 def fetch_data_from_database_api(self): """ Fetch data from database api. """ last_minute = None while True: cur_minute = self.clock.current_minute if last_minute != cur_minute: last_minute = cur_minute try: second = datetime.now().second if second < 10: time.sleep(10 - second) self._refresh_bar_collection() cur_info = self.bar_collection[self._bar_version] for future in self.universe: if future in cur_info: if cur_info[future]['barTime'] == last_minute: yield cur_info[future] except: import traceback logger.error('Fetch failed: %s' % (traceback.format_exc())) time.sleep(5) def publish_bar_data_section(self): """ Publish the latest surface bar data. """ last_minute = None while True: current_minute = self.clock.current_minute if last_minute != current_minute: last_minute = current_minute try: second = datetime.now().second if second < 2: time.sleep(2 - second) self._refresh_bar_collection() current_info = self.bar_collection[self._bar_version] response = CompositeDict() for symbol in self.universe: if symbol in current_info and current_info[symbol]['barTime'] == last_minute: response[last_minute][symbol] = current_info[symbol] if response: yield response except: import traceback logger.error('publish bar data failed: %s' % (traceback.format_exc())) time.sleep(5) def _bar_version_next(self): """ Bar version next. """ return (self._bar_version + 1) % 2 def _refresh_bar_collection(self): """ Refresh bar collection. """ self.bar_collection[self._bar_version_next()] = _get_minute_price_info(self.universe) self._bar_version = self._bar_version_next()

192

2,472

22

e68c200f43159bf514afe9d579f8930fcb12c17b

1,179

py

Python

src/shapefiles/migrations/0001_initial.py

ro-hit81/reposit

2d16ce6aaa565f5f659d8e370c888844a01f6030

[ "bzip2-1.0.6" ]

null

src/shapefiles/migrations/0001_initial.py

ro-hit81/reposit

2d16ce6aaa565f5f659d8e370c888844a01f6030

[ "bzip2-1.0.6" ]

null

src/shapefiles/migrations/0001_initial.py

ro-hit81/reposit

2d16ce6aaa565f5f659d8e370c888844a01f6030

[ "bzip2-1.0.6" ]

null

# Generated by Django 2.2.1 on 2019-08-03 05:44 import django.contrib.gis.db.models.fields from django.db import migrations, models

35.727273

114

0.579304

# Generated by Django 2.2.1 on 2019-08-03 05:44 import django.contrib.gis.db.models.fields from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Parcel', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('objectid', models.BigIntegerField()), ('parcelkey', models.CharField(max_length=26)), ('ownerid', models.CharField(max_length=30)), ('registered', models.CharField(max_length=50)), ('eastparcel', models.CharField(max_length=50)), ('westparcel', models.CharField(max_length=50)), ('northparce', models.CharField(max_length=50)), ('southparce', models.CharField(max_length=50)), ('parcelnoen', models.BigIntegerField()), ('shape_area', models.FloatField()), ('geom', django.contrib.gis.db.models.fields.MultiPolygonField(srid=4326)), ], ), ]

0

1,022

23

2aa5c07dd8585aedf7b1d130332630d71b1b552a

3,068

py

Python

sport.py

hexuustc/weixin_sport

6b4ab18dc48c9fb97301d2f193746effc4988f74

[ "MIT" ]

1

2021-09-26T06:54:44.000Z

sport.py

hexuustc/weixin_sport

6b4ab18dc48c9fb97301d2f193746effc4988f74

[ "MIT" ]

null

sport.py

hexuustc/weixin_sport

6b4ab18dc48c9fb97301d2f193746effc4988f74

[ "MIT" ]

null

# encoding=utf8 import requests import datetime import pytz import argparse import random import json if __name__ == "__main__": parser = argparse.ArgumentParser(description='weixin auto sport script.') parser.add_argument('user', help='your user name', type=str) parser.add_argument('password', help='your password', type=str) args = parser.parse_args() autorepoter = Report(user=args.user, password=args.password) count = 3 while count != 0: ret = autorepoter.report() if ret != False: break print("Sport Failed, retry...") count = count - 1 if count != 0: exit(0) else: exit(-1)

35.674419

159

0.550847

# encoding=utf8 import requests import datetime import pytz import argparse import random import json class Report(object): def __init__(self, user, password): self.user = user self.password = password def report(self): url = "https://xzdx.xyz/x/ym/yzmb/api.php" timenow = datetime.datetime.now(pytz.timezone('Asia/Shanghai')) print(timenow.hour) if timenow.hour<=8 and timenow.hour>=7: step = random.randint(1000,1500) elif timenow.hour<=12 and timenow.hour>=11: step = random.randint(2000,2500) elif timenow.hour<=18 and timenow.hour>=17: step = random.randint(4000,4500) elif timenow.hour<=23 and timenow.hour>=22: step = random.randint(6000,7000) else: step = random.randint(1500,2000) headers = { 'authority': 'xzdx.xyz', 'method': 'POST', 'path': '/x/ym/yzmb/api.php', 'scheme': 'https', 'accept': '*/*', 'accept-encoding': 'gzip, deflate, br', 'accept-language': 'zh-CN,zh;q=0.9,en;q=0.8,en-GB;q=0.7,en-US;q=0.6', 'content-length': '48', 'content-type': 'application/x-www-form-urlencoded; charset=UTF-8', 'origin': 'https://xzdx.xyz', 'referer': 'https://xzdx.xyz/x/ym/yzmb/', 'sec-ch-ua': '"Chromium";v="94", "Microsoft Edge";v="94", ";Not A Brand";v="99"', 'sec-ch-ua-mobile': '?0', 'sec-ch-ua-platform': '"Windows"', 'sec-fetch-dest': 'empty', 'sec-fetch-mode': 'cors', 'sec-fetch-site': 'same-origin', 'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36 Edg/94.0.992.31', 'x-requesteded-with':'XMLHttpRequest' } data = { 'user':self.user, 'password':self.password, 'steps':step } ret = requests.post(url,data=data,headers=headers) status = ret.status_code string = ret.content.decode('UTF-8') json_message = json.loads(string) code = json_message['code'] print(status) print(string) print(code) if status==200 and code=='200': print("Sport Success!") return True else: print("Sport Failed!") return False return False if __name__ == "__main__": parser = argparse.ArgumentParser(description='weixin auto sport script.') parser.add_argument('user', help='your user name', type=str) parser.add_argument('password', help='your password', type=str) args = parser.parse_args() autorepoter = Report(user=args.user, password=args.password) count = 3 while count != 0: ret = autorepoter.report() if ret != False: break print("Sport Failed, retry...") count = count - 1 if count != 0: exit(0) else: exit(-1)

2,314

0

76

9aca37e5b5791be898dfe5347b24154e7d5b9ccf

1,634

py

Python

aerisweather/responses/ObservationsSummaryDewPt.py

jkoelndorfer/aerisweather-python-sdk

ef37fe3132e87e7f86c2d1ba40a2ac2b7b4db604

[ "MIT" ]

5

2019-02-26T20:56:14.000Z

2021-05-05T21:04:45.000Z

aerisweather/responses/ObservationsSummaryDewPt.py

jkoelndorfer/aerisweather-python-sdk

ef37fe3132e87e7f86c2d1ba40a2ac2b7b4db604

[ "MIT" ]

2

2021-03-02T00:35:42.000Z

2021-03-03T17:07:37.000Z

aerisweather/responses/ObservationsSummaryDewPt.py

jkoelndorfer/aerisweather-python-sdk

ef37fe3132e87e7f86c2d1ba40a2ac2b7b4db604

[ "MIT" ]

8

2018-05-26T18:52:21.000Z

2022-01-20T19:47:15.000Z

class ObservationsSummaryDewPt: """ Defines an object for the observations summary period temp data. """ dewpt = {} def __init__(self, dewpt_json): """ Constructor - this takes an individual observations summary period's dewpoint json. { maxC": 5, "maxF": 41, "minC": -3, "minF": 26, "avgC": -0.6, "avgF": 30.9, "count": 23 }, """ self.dewpt = dewpt_json @property def maxC(self) -> float: """ The maximum dew point in Celsius. Null if unavailable. """ return self.dewpt["maxC"] @property def maxF(self) -> float: """ The maximum dew point in Fahrenheit. Null if unavailable. """ return self.dewpt["maxF"] @property def minC(self) -> float: """ The minimum dew point in Celsius. Null if unavailable. """ return self.dewpt["minC"] @property def minF(self) -> float: """ The minimum dew point in Fahrenheit. Null if unavailable. """ return self.dewpt["minF"] @property def avgC(self) -> float: """ The average dew point in Celsius. Null if unavailable. """ return self.dewpt["avgC"] @property def avgF(self) -> float: """ The average dew point in Fahrenheit. Null if unavailable. """ return self.dewpt["avgF"] @property def count(self) -> int: """ The total number of observations that included dew point information. """ return self.dewpt["count"]

28.172414

91

0.53672

class ObservationsSummaryDewPt: """ Defines an object for the observations summary period temp data. """ dewpt = {} def __init__(self, dewpt_json): """ Constructor - this takes an individual observations summary period's dewpoint json. { maxC": 5, "maxF": 41, "minC": -3, "minF": 26, "avgC": -0.6, "avgF": 30.9, "count": 23 }, """ self.dewpt = dewpt_json @property def maxC(self) -> float: """ The maximum dew point in Celsius. Null if unavailable. """ return self.dewpt["maxC"] @property def maxF(self) -> float: """ The maximum dew point in Fahrenheit. Null if unavailable. """ return self.dewpt["maxF"] @property def minC(self) -> float: """ The minimum dew point in Celsius. Null if unavailable. """ return self.dewpt["minC"] @property def minF(self) -> float: """ The minimum dew point in Fahrenheit. Null if unavailable. """ return self.dewpt["minF"] @property def avgC(self) -> float: """ The average dew point in Celsius. Null if unavailable. """ return self.dewpt["avgC"] @property def avgF(self) -> float: """ The average dew point in Fahrenheit. Null if unavailable. """ return self.dewpt["avgF"] @property def count(self) -> int: """ The total number of observations that included dew point information. """ return self.dewpt["count"]

0

ecf14aa3926e57d3af91bbd3bfcf4c68f37171a2

1,220

py

Python

receivePage.py

jb55/lightning-qt

34d6c990a74a5d6d8a10eb75a98d15a6c7eb1891

[ "BSD-3-Clause-Clear" ]

26

2019-05-15T17:35:58.000Z

2019-05-25T11:59:45.000Z

receivePage.py

jb55/lightning-qt

34d6c990a74a5d6d8a10eb75a98d15a6c7eb1891

[ "BSD-3-Clause-Clear" ]

16

2019-06-07T08:33:38.000Z

2021-08-30T10:16:47.000Z

receivePage.py

jb55/lightning-qt

34d6c990a74a5d6d8a10eb75a98d15a6c7eb1891

[ "BSD-3-Clause-Clear" ]

8

2019-06-12T13:29:14.000Z

2021-04-01T21:28:03.000Z

from PyQt5.QtWidgets import QWidget from forms.ui_receivePage import Ui_ReceivePage class ReceivePage(QWidget, Ui_ReceivePage): """The page to generate bolt11 invoices""" def clearForm(self): """Reset the form to the default values""" self.spinValue.setValue(1) self.lineLabel.setText("") self.lineDescription.setText("") self.spinExpiry.setValue(604800) # A week def generateInvoice(self): """Generate an invoice and display it""" amount_msat = self.spinValue.value() label = self.lineLabel.text() description = self.lineDescription.text() expiry = self.spinExpiry.value() invoice = self.plugin.rpc.invoice(amount_msat, label, description, expiry) # Condition to prevent RPC error if invoice: self.textResultInvoice.setText(invoice["bolt11"]) def initUi(self): """Initialize the UI by connecting actions""" self.buttonGenerate.clicked.connect(self.generateInvoice) self.buttonClear.clicked.connect(self.clearForm)

34.857143

82

0.656557

from PyQt5.QtWidgets import QWidget from forms.ui_receivePage import Ui_ReceivePage class ReceivePage(QWidget, Ui_ReceivePage): """The page to generate bolt11 invoices""" def __init__(self, plugin): super().__init__() self.setupUi(self) self.plugin = plugin self.initUi() def clearForm(self): """Reset the form to the default values""" self.spinValue.setValue(1) self.lineLabel.setText("") self.lineDescription.setText("") self.spinExpiry.setValue(604800) # A week def generateInvoice(self): """Generate an invoice and display it""" amount_msat = self.spinValue.value() label = self.lineLabel.text() description = self.lineDescription.text() expiry = self.spinExpiry.value() invoice = self.plugin.rpc.invoice(amount_msat, label, description, expiry) # Condition to prevent RPC error if invoice: self.textResultInvoice.setText(invoice["bolt11"]) def initUi(self): """Initialize the UI by connecting actions""" self.buttonGenerate.clicked.connect(self.generateInvoice) self.buttonClear.clicked.connect(self.clearForm)

111

0

26

f8eb53b19f7d0ed80f555946ddeb4af5858c61b4

2,698

py

Python

web/wrpbg/pb_server.py

mccreery/sandbox

43e81c7f908feedd8e1b6e28ee07870d02012f4c

[ "Unlicense" ]

1

2020-06-11T21:19:25.000Z

web/wrpbg/pb_server.py

mccreery/sandbox

43e81c7f908feedd8e1b6e28ee07870d02012f4c

[ "Unlicense" ]

null

web/wrpbg/pb_server.py

mccreery/sandbox

43e81c7f908feedd8e1b6e28ee07870d02012f4c

[ "Unlicense" ]

1

2020-06-11T21:19:26.000Z

import http.server, requests, json username_cache = {} whitelist = ("current.html", "runner64.png", "flags.min.css", "flags.png") mimes = { "html": "text/html", "css": "text/css", "png": "image/png", "json": "application/jsonn" } PAGE_404 = """<!DOCTYPE html> <html> <head> <meta charset="utf-8"> <title>404 Not Found</title> </head> <body> nuthin to see here bruh </body> </html> """ HEADERS = {"User-Agent": "Jobicade's Magnificent PB/WR grabber"} GAME_ID = "4pd0n31e" CATEGORY_ID = "wk6pexd1" USER_ID = "48g0ln2x" BASE = "http://www.speedrun.com/api/v1/" PB_QUERY = BASE + "users/" + USER_ID + "/personal-bests" WR_QUERY = BASE + "leaderboards/" + GAME_ID + "/category/" + CATEGORY_ID httpd = http.server.HTTPServer(('127.0.0.1', 80), RecordRequest) sa = httpd.socket.getsockname() print("Serving HTTP on", sa[0], "port", sa[1], "...") httpd.serve_forever()

27.252525

113

0.642328

import http.server, requests, json username_cache = {} whitelist = ("current.html", "runner64.png", "flags.min.css", "flags.png") mimes = { "html": "text/html", "css": "text/css", "png": "image/png", "json": "application/jsonn" } PAGE_404 = """<!DOCTYPE html> <html> <head> <meta charset="utf-8"> <title>404 Not Found</title> </head> <body> nuthin to see here bruh </body> </html> """ HEADERS = {"User-Agent": "Jobicade's Magnificent PB/WR grabber"} GAME_ID = "4pd0n31e" CATEGORY_ID = "wk6pexd1" USER_ID = "48g0ln2x" BASE = "http://www.speedrun.com/api/v1/" PB_QUERY = BASE + "users/" + USER_ID + "/personal-bests" WR_QUERY = BASE + "leaderboards/" + GAME_ID + "/category/" + CATEGORY_ID class RecordRequest(http.server.BaseHTTPRequestHandler): @staticmethod def json(url, path=None, **kwargs): root = requests.get(url, **kwargs, headers=HEADERS).json() if path: for key in path: root = root[key] return root def do_GET(self): if self.path[0] == "/": self.path = self.path[1:] headers_out = {} code = 200 redirects = ("current", "current.html", "index", "index.html") if self.path in redirects: code = 301 headers_out["Location"] = "/" self.path = "current.html" # This is the correct path, don't complain about it if self.path == "": self.path = "current.html" if self.path == "data": headers_out["Content-Type"] = "application/json; charset=utf-8" # Grab responses from speedrun.com... pb = RecordRequest.json(PB_QUERY, ("data", 0), params={"game": GAME_ID, "category": CATEGORY_ID}) wr = RecordRequest.json(WR_QUERY, ("data", "runs", 0, "run"), params={"top": 1, "timing": "realtime_noloads"}) wr_runner = wr["players"][0] if not wr_runner["id"] in username_cache: username_cache[wr_runner["id"]] = RecordRequest.json(wr_runner["uri"], ("data",)) pb["run"]["place"] = pb["place"] pb = pb["run"] wr["player"] = username_cache[wr_runner["id"]] response = json.dumps({"pb": pb, "wr": wr}).encode("utf-8") elif self.path in whitelist: headers_out["Content-Type"] = mimes[self.path[self.path.rfind(".")+1:]] with open(self.path, "rb") as f: response = f.read() else: code = 404 response = PAGE_404.encode("utf-8") headers_out["Content-Type"] = "text/html; charset=utf-8" headers_out["Content-Length"] = len(response) self.send_response(code) for key in headers_out: self.send_header(key, headers_out[key]) self.end_headers() self.wfile.write(response) httpd = http.server.HTTPServer(('127.0.0.1', 80), RecordRequest) sa = httpd.socket.getsockname() print("Serving HTTP on", sa[0], "port", sa[1], "...") httpd.serve_forever()

1,671

97

23

025a893749801984f1c46542201e277d879dc8b8

244

py

Python

tottle/types/objects/login.py

muffleo/tottle

69a5bdda879ab56d43505d517d3369a687c135a2

[ "MIT" ]

12

2020-09-06T15:31:34.000Z

2021-02-27T20:30:34.000Z

tottle/types/objects/login.py

cyanlabs-org/tottle

6cf02022ed7b445c9b5af475c6e854b91780d792

[ "MIT" ]

2

2021-04-13T06:43:42.000Z

2021-07-07T20:52:39.000Z

tottle/types/objects/login.py

cyanlabs-org/tottle

6cf02022ed7b445c9b5af475c6e854b91780d792

[ "MIT" ]

4

2020-09-12T03:09:25.000Z

2021-03-22T08:52:04.000Z

from pydantic import BaseModel from typing import Optional

24.4

47

0.741803

from pydantic import BaseModel from typing import Optional class LoginUrl(BaseModel): url: Optional[str] = None forward_text: Optional[str] = None bot_username: Optional[str] = None request_write_access: Optional[bool] = None

0

161

23

750320b65b80fda001114fd35158b9000f594ba5

2,060

py

Python

phuber/evaluator.py

dmizr/phuber

3b70eadd9bd1420047ada743ff5604eda48d63ac

[ "MIT" ]

12

2020-12-17T14:54:03.000Z

2021-12-13T21:30:13.000Z

phuber/evaluator.py

dmizr/phuber

3b70eadd9bd1420047ada743ff5604eda48d63ac

[ "MIT" ]

5

2020-12-30T21:18:05.000Z

2021-04-16T21:27:35.000Z

phuber/evaluator.py

dmizr/phuber

3b70eadd9bd1420047ada743ff5604eda48d63ac

[ "MIT" ]

7

2021-04-15T02:13:26.000Z

2021-12-01T21:20:59.000Z

import logging from typing import Optional import torch import tqdm from torch.utils.data import DataLoader from phuber.metrics import AccuracyMetric class Evaluator: """Model evaluator Args: model: model to be evaluated device: device on which to evaluate model loader: dataloader on which to evaluate model checkpoint_path: path to model checkpoint """ def evaluate(self) -> float: """Evaluates the model Returns: (float) accuracy (on a 0 to 1 scale) """ # Progress bar pbar = tqdm.tqdm(total=len(self.loader), leave=False) pbar.set_description("Evaluating... ") # Set to eval self.model.eval() # Loop for data, target in self.loader: with torch.no_grad(): # To device data, target = data.to(self.device), target.to(self.device) # Forward out = self.model(data) self.acc_metric.update(out, target) # Update progress bar pbar.update() pbar.close() accuracy = self.acc_metric.compute() self.logger.info(f"Accuracy: {accuracy:.4f}\n") return accuracy

23.678161

75

0.584466

import logging from typing import Optional import torch import tqdm from torch.utils.data import DataLoader from phuber.metrics import AccuracyMetric class Evaluator: """Model evaluator Args: model: model to be evaluated device: device on which to evaluate model loader: dataloader on which to evaluate model checkpoint_path: path to model checkpoint """ def __init__( self, model: torch.nn.Module, device: torch.device, loader: DataLoader, checkpoint_path: Optional[str] = None, ) -> None: # Logging self.logger = logging.getLogger() # Device self.device = device # Data self.loader = loader # Model self.model = model if checkpoint_path: self._load_from_checkpoint(checkpoint_path) # Metrics self.acc_metric = AccuracyMetric(k=1) def evaluate(self) -> float: """Evaluates the model Returns: (float) accuracy (on a 0 to 1 scale) """ # Progress bar pbar = tqdm.tqdm(total=len(self.loader), leave=False) pbar.set_description("Evaluating... ") # Set to eval self.model.eval() # Loop for data, target in self.loader: with torch.no_grad(): # To device data, target = data.to(self.device), target.to(self.device) # Forward out = self.model(data) self.acc_metric.update(out, target) # Update progress bar pbar.update() pbar.close() accuracy = self.acc_metric.compute() self.logger.info(f"Accuracy: {accuracy:.4f}\n") return accuracy def _load_from_checkpoint(self, checkpoint_path: str) -> None: checkpoint = torch.load(checkpoint_path, map_location=self.device) self.model.load_state_dict(checkpoint["model"]) self.logger.info(f"Checkpoint loaded: {checkpoint_path}")

742

0

54

8c562da3b379f70ca048f530b14ad2a31026c4c4

14,618

py

Python

gpcsup/__init__.py

braedon/gpcsup

a20c9fbc7d5c0191a87553b8588757b1528fe655

[ "MIT" ]

null

gpcsup/__init__.py

braedon/gpcsup

a20c9fbc7d5c0191a87553b8588757b1528fe655

[ "MIT" ]

null

gpcsup/__init__.py

braedon/gpcsup

a20c9fbc7d5c0191a87553b8588757b1528fe655

[ "MIT" ]

null

import functools import idna import logging import re import requests import rfc3339 import time from bottle import Bottle, request, response, static_file, template, redirect from datetime import timedelta from publicsuffixlist import PublicSuffixList from requests_oauthlib import OAuth1 from urllib.parse import urlsplit from utils.param_parse import (ParamParseError, parse_params, integer_param, string_param, boolean_param) from .misc import html_default_error_hander, security_headers, set_headers log = logging.getLogger(__name__) # Disable some logging to reduce log spam. # Elasticsearch logs all requests at (at least) INFO level. logging.getLogger('elasticsearch').setLevel(logging.WARNING) PSL_CACHE_SIZE = 10_000 psl = PublicSuffixList() # Domains are a series of two or more names, separated by periods, with an optional trailing period. # (Technically one name is allowed, but TLDs aren't usually HTTP sites.) # (Note that we actually strip any trailing period during normalization - along with lowercasing # characters - but support has been left in the regex for completeness.) # Each name can contain latin characters (case insensitive), digits, or dashes. # Names can't be longer than 63 characters, or start/end with a dash. # The final name - the TLD - can't be numeric (only digits). DOMAIN_REGEX = re.compile(r'^(?:[a-z\d](?:[a-z\d-]{0,61}[a-z\d])?\.)+(?!\d+\.?$)[a-z\d](?:[a-z\d-]{0,61}[a-z\d])?\.?$') DOMAIN_MAX_LENGTH = 253 REQUEST_TIMEOUT_INDIVIDUAL = 5 SCAN_START_TIMEOUT = 20 SCAN_TIMEOUT = 30 SCAN_AGENT = 'GpcSupBot' SCAN_HEADERS = {'User-Agent': f'{SCAN_AGENT}/0.1 (https://gpcsup.com)'} ROBOTS_MAX_CONTENT_LENGTH = 512 * 1024 # 512kB GPC_PATH = '/.well-known/gpc.json' GPC_MAX_CONTENT_LENGTH = 1024 # 1kB SCAN_TTL = timedelta(minutes=10) NEXT_SCAN_OFFSET = timedelta(days=7) SCAN_FAIL_OFFSETS = [ timedelta(days=1), timedelta(days=7), timedelta(days=30), ] SCAN_RESULT_MAX_AGE_SECS = SCAN_TTL.seconds SCAN_RESULT_HEADERS = {'Cache-Control': f'max-age={SCAN_RESULT_MAX_AGE_SECS}'} STATIC_FILE_MAX_AGE_SECS = timedelta(hours=1).seconds STATIC_FILE_HEADERS = {'Cache-Control': f'max-age={STATIC_FILE_MAX_AGE_SECS}'} SITES_PAGE_SIZE = 8 SERVER_READY = True class ScanError(Exception): """The scan has failed, and the user should be shown the specified template.""" @functools.lru_cache(maxsize=PSL_CACHE_SIZE)

36.636591

119

0.606718

import functools import idna import logging import re import requests import rfc3339 import time from bottle import Bottle, request, response, static_file, template, redirect from datetime import timedelta from publicsuffixlist import PublicSuffixList from requests_oauthlib import OAuth1 from urllib.parse import urlsplit from utils.param_parse import (ParamParseError, parse_params, integer_param, string_param, boolean_param) from .misc import html_default_error_hander, security_headers, set_headers log = logging.getLogger(__name__) # Disable some logging to reduce log spam. # Elasticsearch logs all requests at (at least) INFO level. logging.getLogger('elasticsearch').setLevel(logging.WARNING) PSL_CACHE_SIZE = 10_000 psl = PublicSuffixList() # Domains are a series of two or more names, separated by periods, with an optional trailing period. # (Technically one name is allowed, but TLDs aren't usually HTTP sites.) # (Note that we actually strip any trailing period during normalization - along with lowercasing # characters - but support has been left in the regex for completeness.) # Each name can contain latin characters (case insensitive), digits, or dashes. # Names can't be longer than 63 characters, or start/end with a dash. # The final name - the TLD - can't be numeric (only digits). DOMAIN_REGEX = re.compile(r'^(?:[a-z\d](?:[a-z\d-]{0,61}[a-z\d])?\.)+(?!\d+\.?$)[a-z\d](?:[a-z\d-]{0,61}[a-z\d])?\.?$') DOMAIN_MAX_LENGTH = 253 REQUEST_TIMEOUT_INDIVIDUAL = 5 SCAN_START_TIMEOUT = 20 SCAN_TIMEOUT = 30 SCAN_AGENT = 'GpcSupBot' SCAN_HEADERS = {'User-Agent': f'{SCAN_AGENT}/0.1 (https://gpcsup.com)'} ROBOTS_MAX_CONTENT_LENGTH = 512 * 1024 # 512kB GPC_PATH = '/.well-known/gpc.json' GPC_MAX_CONTENT_LENGTH = 1024 # 1kB SCAN_TTL = timedelta(minutes=10) NEXT_SCAN_OFFSET = timedelta(days=7) SCAN_FAIL_OFFSETS = [ timedelta(days=1), timedelta(days=7), timedelta(days=30), ] SCAN_RESULT_MAX_AGE_SECS = SCAN_TTL.seconds SCAN_RESULT_HEADERS = {'Cache-Control': f'max-age={SCAN_RESULT_MAX_AGE_SECS}'} STATIC_FILE_MAX_AGE_SECS = timedelta(hours=1).seconds STATIC_FILE_HEADERS = {'Cache-Control': f'max-age={STATIC_FILE_MAX_AGE_SECS}'} SITES_PAGE_SIZE = 8 SERVER_READY = True class ScanError(Exception): """The scan has failed, and the user should be shown the specified template.""" def __init__(self, template, **kwargs): self.template = template self.kwargs = kwargs @functools.lru_cache(maxsize=PSL_CACHE_SIZE) def extract_base_domain(domain, return_unknown=True): base_domain = psl.privatesuffix(domain) # If return_unknown is set, return the domain if its eTLD isn't known. if base_domain is None and return_unknown: base_domain = domain return base_domain def domain_is_www_subdomain(domain): base_domain = extract_base_domain(domain) return domain == f'www.{base_domain}' def normalise_domain(domain): domain = domain.lower() # Handle users copying domains with the scheme attached. # Only allow these two schemes - GPC is for HTTP(s). if domain.startswith('https://'): domain = domain[8:] elif domain.startswith('http://'): domain = domain[7:] # Similar to handling schemes, handle one slash at the end of the domain. if domain.endswith('/'): domain = domain[:-1] # Strip any optional trailing period from the domain. if domain.endswith('.'): domain = domain[:-1] try: # Convert to and from IDNA encoding with compatibility mapping enabled to normalise. domain = idna.decode(idna.encode(domain, uts46=True)) except idna.IDNAError: # Ignore IDNA errors and return the domain without IDNA normalisation. # Any IDNA error will cause check_domain() to fail anyway. pass return domain def check_domain(domain): try: # Convert domains to IDNA format before checking length and format. idna_domain = idna.encode(domain).decode('ASCII') except idna.IDNAError as e: log.warning('IDNA error when checking %(domain)s: %(error)s', {'domain': domain, 'error': e}) return False if len(idna_domain) > DOMAIN_MAX_LENGTH: return False match = DOMAIN_REGEX.fullmatch(idna_domain) if match is None: return False return True def extract_domain_from_url(url): split_url = urlsplit(url) domain = split_url.netloc if ':' in domain: domain = domain.split(':', 1)[0] return normalise_domain(domain) def construct_app(es_dao, well_known_sites_endpoint, testing_mode, **kwargs): app = Bottle() app.default_error_handler = html_default_error_hander app.install(security_headers) @app.get('/-/live') def live(): return 'Live' @app.get('/-/ready') def ready(): if SERVER_READY: return 'Ready' else: response.status = 503 return 'Unavailable' @app.get('/main.css') def css(): return static_file('main.css', root='static', headers=STATIC_FILE_HEADERS.copy()) # Set CORP to allow Firefox for Android to load icons. # Firefox for Android seems to consider the icon loader a different origin. # # Favicon stuff generated at: # https://favicon.io/favicon-generator/?t=gs&ff=Roboto Slab&fs=80&fc=%23fff&b=rounded&bc=%2300885D @app.get('/favicon.ico', sh_updates={'Cross-Origin-Resource-Policy': 'cross-origin'}) def icon(): return static_file('favicon.ico', root='static', headers=STATIC_FILE_HEADERS.copy()) @app.get('/<filename>.png', sh_updates={'Cross-Origin-Resource-Policy': 'cross-origin'}) def root_pngs(filename): return static_file(f'{filename}.png', root='static', headers=STATIC_FILE_HEADERS.copy()) @app.get('/<filename>.js') def root_js(filename): return static_file(f'{filename}.js', root='static', headers=STATIC_FILE_HEADERS.copy()) @app.get('/.well-known/gpc.json') def global_privacy_control(): return {'gpc': True, 'lastUpdate': '2021-07-17'} @app.get('/') def index(): try: params = parse_params(request.query.decode(), domain=string_param('domain', strip=True, min_length=1, max_length=DOMAIN_MAX_LENGTH)) domain = params.get('domain') except ParamParseError: domain = None if domain: domain = normalise_domain(domain) if not check_domain(domain): domain = None scanned_count, supporting_count = es_dao.count(timeout=30) r = template('index', domain=domain, scanned_count=scanned_count, supporting_count=supporting_count) set_headers(r, STATIC_FILE_HEADERS) return r @app.post('/') def check_site(): try: params = parse_params(request.forms.decode(), domain=string_param('domain', required=True, strip=True, min_length=1, max_length=DOMAIN_MAX_LENGTH), no_rescan=boolean_param('no_rescan', default=False, empty=True, strip=True)) except ParamParseError: return template('gpc_invalid', domain=None) domain = normalise_domain(params['domain']) if not check_domain(domain): return template('gpc_invalid', domain=domain) result = es_dao.get(domain) if result is not None: if params['no_rescan'] or result['status'] == 'pending': redirect(f'/sites/{domain}') # Non-pending scans should have a scan datetime. last_scan_dt = rfc3339.parse_datetime(result['last_scan_dt']) # If the last scan hasn't expired yet, don't rescan. if rfc3339.now() < last_scan_dt + SCAN_TTL: if testing_mode: log.info('Would have redirected to existing scan for %(domain)s if on prod.', {'domain': domain}) else: redirect(f'/sites/{domain}') r = requests.post(well_known_sites_endpoint, data={'domain': domain, 'rescan': 'true'}) r.raise_for_status() redirect(f'/sites/{domain}') @app.get('/sites/') def get_sites(): params = parse_params(request.params.decode(), page=integer_param('page', default=0, positive=True)) page = params['page'] offset = page * SITES_PAGE_SIZE total, results = es_dao.find(supports_gpc=True, is_base_domain=True, sort=['id'], offset=offset, limit=SITES_PAGE_SIZE, timeout=30) domains = [result[0]['domain'] for result in results] previous_page = page - 1 if page > 0 else None next_page = page + 1 next_offset = next_page * SITES_PAGE_SIZE if next_offset >= total: next_page = None return template('sites', domains=domains, previous_page=previous_page, next_page=next_page) @app.get('/sites/<domain>') def get_site(domain): domain = normalise_domain(domain) if not check_domain(domain): return template('gpc_invalid', domain=domain) # Well-Known doesn't scan www subdomains - redirect to the base domain instead. if domain_is_www_subdomain(domain): base_domain = extract_base_domain(domain) redirect(f'/sites/{base_domain}') result = es_dao.get(domain) if result is None: redirect(f'/?domain={domain}') status = result['status'] scan_data = result.get('scan_data') if status == 'pending': return template('gpc_pending', domain=domain) elif status == 'blocked': return template('gpc_blocked', domain=domain) elif status == 'failed' and not scan_data: return template('gpc_error', domain=domain) # Status should be `ok`, or `failed` but with a previously successful scan. # In either case, `scan_data` should be present. assert scan_data scheme = scan_data['scheme'] scan_dt = rfc3339.parse_datetime(result['scan_dt']) if result['scan_priority'] == 0: rescan_queued = True can_rescan = False else: rescan_queued = False last_scan_dt = rfc3339.parse_datetime(result['last_scan_dt']) can_rescan = (last_scan_dt + SCAN_TTL) < rfc3339.now() error = scan_data.get('error') if error: message = None if error == 'not-found': message = 'The GPC support resource was not found.' elif error in ('unexpected-scheme-redirect', 'unexpected-status', 'client-error', 'server-error', 'unexpected-status'): message = 'Server responded unexpectedly when fetching the GPC support resource.' elif error in ('parse-error', 'json-parse-error', 'unexpected-json-root-type', 'content-too-long', 'content-length-too-long', 'bad-content'): message = 'The GPC support resource is invalid.' elif error: log.error('Unsupported GPC scan error %(error)s', {'error': error}) r = template('gpc_unknown', scheme=scheme, domain=domain, message=message, scan_dt=scan_dt, rescan_queued=rescan_queued, can_rescan=can_rescan) set_headers(r, SCAN_RESULT_HEADERS) return r else: assert scan_data['found'], 'gpc.json should have been found if no error.' gpc_data = scan_data['gpc'] warnings = scan_data.get('warnings') or [] warnings += gpc_data.get('warning_codes') or [] message = None if warnings: message_parts = [] for warning in warnings: if warning == 'wrong-content-type': message_parts.append('incorrect content type') elif warning == 'invalid-update-field': message_parts.append('invalid last update field') if message_parts: message = ' and '.join(message_parts) + '.' last_update = gpc_data['parsed'].get('lastUpdate') template_name = 'gpc_supported' if gpc_data['parsed']['gpc'] else 'gpc_unsupported' r = template(template_name, scheme=scheme, domain=domain, last_update=last_update, message=message, scan_dt=scan_dt, rescan_queued=rescan_queued, can_rescan=can_rescan) set_headers(r, SCAN_RESULT_HEADERS) return r return app def run_twitter_worker(es_dao, twitter_consumer_key, twitter_consumer_secret, twitter_token_key, twitter_token_secret, testing_mode, **kwargs): oauth = OAuth1(client_key=twitter_consumer_key, client_secret=twitter_consumer_secret, resource_owner_key=twitter_token_key, resource_owner_secret=twitter_token_secret) while True: domains = es_dao.find_tweetable() if domains: for domain in domains: if testing_mode: log.info('Would tweet about `%(domain)s` supporting GPC.', {'domain': domain}) else: es_dao.set_tweeting(domain, wait_for=True) tweet = f'{domain} is reporting that it supports #GPC' r = requests.post('https://api.twitter.com/1.1/statuses/update.json', data={'status': tweet}, auth=oauth) r.raise_for_status() r_json = r.json() tweet_id = r_json['id_str'] log.info('Tweeted about `%(domain)s` supporting GPC. Tweet ID: `%(tweet_id)s`', {'domain': domain, 'tweet_id': tweet_id, 'full_response': r_json}) es_dao.set_tweeted(domain, wait_for=True) else: time.sleep(60)

12,017

0

187

60c96f5be72bddae518c87b5b2b4d754b4bd152e

1,158

py

Python

rhea/system/reset.py

mngr0/rhea

9ad8d193f7f78f1d192af438568d45fb5a398c8c

[ "MIT" ]

null

rhea/system/reset.py

mngr0/rhea

9ad8d193f7f78f1d192af438568d45fb5a398c8c

[ "MIT" ]

null

rhea/system/reset.py

mngr0/rhea

9ad8d193f7f78f1d192af438568d45fb5a398c8c

[ "MIT" ]

null

import myhdl from myhdl import delay

33.085714

76

0.582902

import myhdl from myhdl import delay class Reset(myhdl.ResetSignal): def __init__(self, val, active, async): """ Reset signal This is a thin wrapper around the myhdl.ResetSignal to provide the generator ``pulse`` that is often used in testbenches. Arguments: val (int, bool): default value of the reset signal active (int, bool): active state, when is reset active async (bool): asynchronous reset or not """ super(Reset, self).__init__(val, active, async) def pulse(self, delays=10): if isinstance(delays, int): self.next = self.active yield delay(delays) self.next = not self.active elif isinstance(delays, tuple): assert len(delays) in (1, 2, 3), "Incorrect number of delays" self.next = not self.active if len(delays) == 3 else self.active for dd in delays: yield delay(dd) self.next = not self.val self.next = not self.active else: raise ValueError("{} type not supported".format(type(delays)))

573

523

23

6b4c0e4b75266ca932765f704bc1f94c6b42332b

8,005

py

Python

frappe/database/query.py

juhiwue/frappe

77f88af74e037dcca0bae3f3ef1e8cae7fb0f699

[ "MIT" ]

null

frappe/database/query.py

juhiwue/frappe

77f88af74e037dcca0bae3f3ef1e8cae7fb0f699

[ "MIT" ]

null

frappe/database/query.py

juhiwue/frappe

77f88af74e037dcca0bae3f3ef1e8cae7fb0f699

[ "MIT" ]

null

import operator import re from typing import Any, Dict, List, Tuple, Union import frappe from frappe import _ from frappe.query_builder import Criterion, Field, Order def like(key: str, value: str) -> frappe.qb: """Wrapper method for `LIKE` Args: key (str): field value (str): criterion Returns: frappe.qb: `frappe.qb object with `LIKE` """ return Field(key).like(value) def func_in(key: str, value: Union[List, Tuple]) -> frappe.qb: """Wrapper method for `IN` Args: key (str): field value (Union[int, str]): criterion Returns: frappe.qb: `frappe.qb object with `IN` """ return Field(key).isin(value) def not_like(key: str, value: str) -> frappe.qb: """Wrapper method for `NOT LIKE` Args: key (str): field value (str): criterion Returns: frappe.qb: `frappe.qb object with `NOT LIKE` """ return Field(key).not_like(value) def func_not_in(key: str, value: Union[List, Tuple]): """Wrapper method for `NOT IN` Args: key (str): field value (Union[int, str]): criterion Returns: frappe.qb: `frappe.qb object with `NOT IN` """ return Field(key).notin(value) def func_regex(key: str, value: str) -> frappe.qb: """Wrapper method for `REGEX` Args: key (str): field value (str): criterion Returns: frappe.qb: `frappe.qb object with `REGEX` """ return Field(key).regex(value) def func_between(key: str, value: Union[List, Tuple]) -> frappe.qb: """Wrapper method for `BETWEEN` Args: key (str): field value (Union[int, str]): criterion Returns: frappe.qb: `frappe.qb object with `BETWEEN` """ return Field(key)[slice(*value)] def make_function(key: Any, value: Union[int, str]): """returns fucntion query Args: key (Any): field value (Union[int, str]): criterion Returns: frappe.qb: frappe.qb object """ return OPERATOR_MAP[value[0]](key, value[1]) def change_orderby(order: str): """Convert orderby to standart Order object Args: order (str): Field, order Returns: tuple: field, order """ order = order.split() if order[1].lower() == "asc": orderby, order = order[0], Order.asc return orderby, order orderby, order = order[0], Order.desc return orderby, order OPERATOR_MAP = { "+": operator.add, "=": operator.eq, "-": operator.sub, "!=": operator.ne, "<": operator.lt, ">": operator.gt, "<=": operator.le, ">=": operator.ge, "in": func_in, "not in": func_not_in, "like": like, "not like": not_like, "regex": func_regex, "between": func_between }

24.331307

101

0.672705

import operator import re from typing import Any, Dict, List, Tuple, Union import frappe from frappe import _ from frappe.query_builder import Criterion, Field, Order def like(key: str, value: str) -> frappe.qb: """Wrapper method for `LIKE` Args: key (str): field value (str): criterion Returns: frappe.qb: `frappe.qb object with `LIKE` """ return Field(key).like(value) def func_in(key: str, value: Union[List, Tuple]) -> frappe.qb: """Wrapper method for `IN` Args: key (str): field value (Union[int, str]): criterion Returns: frappe.qb: `frappe.qb object with `IN` """ return Field(key).isin(value) def not_like(key: str, value: str) -> frappe.qb: """Wrapper method for `NOT LIKE` Args: key (str): field value (str): criterion Returns: frappe.qb: `frappe.qb object with `NOT LIKE` """ return Field(key).not_like(value) def func_not_in(key: str, value: Union[List, Tuple]): """Wrapper method for `NOT IN` Args: key (str): field value (Union[int, str]): criterion Returns: frappe.qb: `frappe.qb object with `NOT IN` """ return Field(key).notin(value) def func_regex(key: str, value: str) -> frappe.qb: """Wrapper method for `REGEX` Args: key (str): field value (str): criterion Returns: frappe.qb: `frappe.qb object with `REGEX` """ return Field(key).regex(value) def func_between(key: str, value: Union[List, Tuple]) -> frappe.qb: """Wrapper method for `BETWEEN` Args: key (str): field value (Union[int, str]): criterion Returns: frappe.qb: `frappe.qb object with `BETWEEN` """ return Field(key)[slice(*value)] def make_function(key: Any, value: Union[int, str]): """returns fucntion query Args: key (Any): field value (Union[int, str]): criterion Returns: frappe.qb: frappe.qb object """ return OPERATOR_MAP[value[0]](key, value[1]) def change_orderby(order: str): """Convert orderby to standart Order object Args: order (str): Field, order Returns: tuple: field, order """ order = order.split() if order[1].lower() == "asc": orderby, order = order[0], Order.asc return orderby, order orderby, order = order[0], Order.desc return orderby, order OPERATOR_MAP = { "+": operator.add, "=": operator.eq, "-": operator.sub, "!=": operator.ne, "<": operator.lt, ">": operator.gt, "<=": operator.le, ">=": operator.ge, "in": func_in, "not in": func_not_in, "like": like, "not like": not_like, "regex": func_regex, "between": func_between } class Query: def get_condition(self, table: str, **kwargs) -> frappe.qb: """Get initial table object Args: table (str): DocType Returns: frappe.qb: DocType with initial condition """ if kwargs.get("update"): return frappe.qb.update(table) if kwargs.get("into"): return frappe.qb.into(table) return frappe.qb.from_(table) def criterion_query(self, table: str, criterion: Criterion, **kwargs) -> frappe.qb: """Generate filters from Criterion objects Args: table (str): DocType criterion (Criterion): Filters Returns: frappe.qb: condition object """ condition = self.add_conditions(self.get_condition(table, **kwargs), **kwargs) return condition.where(criterion) def add_conditions(self, conditions: frappe.qb, **kwargs): """Adding additional conditions Args: conditions (frappe.qb): built conditions Returns: conditions (frappe.qb): frappe.qb object """ if kwargs.get("orderby"): orderby = kwargs.get("orderby") order = kwargs.get("order") if kwargs.get("order") else Order.desc if isinstance(orderby, str) and len(orderby.split()) > 1: orderby, order = change_orderby(orderby) conditions = conditions.orderby(orderby, order=order) if kwargs.get("limit"): conditions = conditions.limit(kwargs.get("limit")) if kwargs.get("distinct"): conditions = conditions.distinct() if kwargs.get("for_update"): conditions = conditions.for_update() return conditions def misc_query(self, table: str, filters: Union[List, Tuple] = None, **kwargs): """Build conditions using the given Lists or Tuple filters Args: table (str): DocType filters (Union[List, Tuple], optional): Filters. Defaults to None. """ conditions = self.get_condition(table, **kwargs) if not filters: return conditions if isinstance(filters, list): for f in filters: if not isinstance(f, (list, tuple)): _operator = OPERATOR_MAP[filters[1]] if not isinstance(filters[0], str): conditions = make_function(filters[0], filters[2]) break conditions = conditions.where(_operator(Field(filters[0]), filters[2])) break else: _operator = OPERATOR_MAP[f[1]] conditions = conditions.where(_operator(Field(f[0]), f[2])) conditions = self.add_conditions(conditions, **kwargs) return conditions def dict_query(self, table: str, filters: Dict[str, Union[str, int]] = None, **kwargs) -> frappe.qb: """Build conditions using the given dictionary filters Args: table (str): DocType filters (Dict[str, Union[str, int]], optional): Filters. Defaults to None. Returns: frappe.qb: conditions object """ conditions = self.get_condition(table, **kwargs) if not filters: conditions = self.add_conditions(conditions, **kwargs) return conditions for key in filters: value = filters.get(key) _operator = OPERATOR_MAP["="] if not isinstance(key, str): conditions = conditions.where(make_function(key, value)) continue if isinstance(value, (list, tuple)): if isinstance(value[1], (list, tuple)) or value[0] in list(OPERATOR_MAP.keys())[-4:]: _operator = OPERATOR_MAP[value[0]] conditions = conditions.where(_operator(key, value[1])) else: _operator = OPERATOR_MAP[value[0]] conditions = conditions.where(_operator(Field(key), value[1])) else: conditions = conditions.where(_operator(Field(key), value)) conditions = self.add_conditions(conditions, **kwargs) return conditions def build_conditions( self, table: str, filters: Union[Dict[str, Union[str, int]], str, int] = None, **kwargs ) -> frappe.qb: """Build conditions for sql query Args: filters (Union[Dict[str, Union[str, int]], str, int]): conditions in Dict table (str): DocType Returns: frappe.qb: frappe.qb conditions object """ if isinstance(filters, int) or isinstance(filters, str): filters = {"name": str(filters)} if isinstance(filters, Criterion): criterion = self.criterion_query(table, filters, **kwargs) elif isinstance(filters, (list, tuple)): criterion = self.misc_query(table, filters, **kwargs) else: criterion = self.dict_query(filters=filters, table=table, **kwargs) return criterion def get_sql( self, table: str, fields: Union[List, Tuple], filters: Union[Dict[str, Union[str, int]], str, int] = None, **kwargs ): criterion = self.build_conditions(table, filters, **kwargs) if isinstance(fields, (list, tuple)): query = criterion.select(*kwargs.get("field_objects", fields)) elif isinstance(fields, Criterion): query = criterion.select(fields) else: query = criterion.select(fields) return query class Permission: @classmethod def check_permissions(cls, query, **kwargs): if not isinstance(query, str): query = query.get_sql() doctype = cls.get_tables_from_query(query) if isinstance(doctype, str): doctype = [doctype] for dt in doctype: dt = re.sub("^tab", "", dt) if not frappe.has_permission( dt, "select", user=kwargs.get("user"), parent_doctype=kwargs.get("parent_doctype"), ) and not frappe.has_permission( dt, "read", user=kwargs.get("user"), parent_doctype=kwargs.get("parent_doctype"), ): frappe.throw( _("Insufficient Permission for {0}").format(frappe.bold(dt)) ) @staticmethod def get_tables_from_query(query: str): return [table for table in re.findall(r"\w+", query) if table.startswith("tab")]

1,124

4,299

46

b32d432b5b14e98ef90fed8ac7f7c9ad1ef97f2b

1,470

py

Python

lib/exchange/upbit/adapter/post_orders_response_adapter.py

webclinic017/bitrush

5d76c98a17bb830dba1bdd103475c120903ded90

[ "MIT" ]

1

2022-01-09T21:17:23.000Z

lib/exchange/upbit/adapter/post_orders_response_adapter.py

webclinic017/bitrush

5d76c98a17bb830dba1bdd103475c120903ded90

[ "MIT" ]

null

lib/exchange/upbit/adapter/post_orders_response_adapter.py

webclinic017/bitrush

5d76c98a17bb830dba1bdd103475c120903ded90

[ "MIT" ]

1

2022-01-09T21:17:17.000Z

import json from decimal import Decimal from typing import Optional, Dict from lib.exchange.upbit.model.post_orders_response import PostOrdersResponse from lib.order.order import Order from lib.order.order_type import OrderType from lib.type import JsonString

28.823529

86

0.682993

import json from decimal import Decimal from typing import Optional, Dict from lib.exchange.upbit.model.post_orders_response import PostOrdersResponse from lib.order.order import Order from lib.order.order_type import OrderType from lib.type import JsonString class PostOrdersResponseAdapter(Order): response: PostOrdersResponse custom_order_id: str def __init__(self, response: Dict, custom_order_id: str): """ Args: custom_order_id (str): custom order id to group each order items """ self.response = PostOrdersResponse(**response) self.custom_order_id = custom_order_id def get_id(self) -> str: return self.custom_order_id def get_exchange(self) -> str: return "upbit" def is_filled(self) -> bool: return self.response.state != "wait" def get_order_type(self) -> OrderType: return OrderType.BUY if self.response.side == "bid" else OrderType.SELL def get_ticker(self) -> str: return self.response.market.replace("KRW-", "") def get_volume(self) -> Decimal: return Decimal(self.response.volume) if self.response.volume else Decimal("0") def get_avg_price(self) -> Decimal: return Decimal(self.response.price) if self.response.price else Decimal("0") def get_amount(self): # order is just placed return Decimal("0") def get_raw_data(self) -> Dict: return self.response.dict()

586

599

23

862cafed433a27c4c636e2ae6a6289b7ce389dab

2,788

py

Python

test/cut/test_cut_set_creation.py

pzelasko/lhotse

41984467d2ead1dc69f418638b969e46f63308c7

[ "Apache-2.0" ]

64

2020-04-27T14:55:15.000Z

2020-10-25T06:57:56.000Z

test/cut/test_cut_set_creation.py

pzelasko/lhotse

41984467d2ead1dc69f418638b969e46f63308c7

[ "Apache-2.0" ]

85

2020-04-26T06:29:47.000Z

2020-10-19T20:28:52.000Z

test/cut/test_cut_set_creation.py

pzelasko/lhotse

41984467d2ead1dc69f418638b969e46f63308c7

[ "Apache-2.0" ]

17

2020-06-19T06:26:33.000Z

2020-10-12T15:19:15.000Z

import pytest from lhotse.cut import make_windowed_cuts_from_features from lhotse.features import Features, FeatureSet def features(rec_id, start, duration): """Helper method for fixture readability (specify only relevant attributes).""" return Features( recording_id=rec_id, channels=0, start=start, duration=duration, sampling_rate=16000, type="irrelevant", num_frames=round(duration / 0.01), num_features=23, storage_type="irrelevant", storage_path="irrelevant", storage_key="irrelevant", frame_shift=0.01, ) @pytest.fixture # noinspection PyMethodMayBeStatic

34

83

0.641679

import pytest from lhotse.cut import make_windowed_cuts_from_features from lhotse.features import Features, FeatureSet def features(rec_id, start, duration): """Helper method for fixture readability (specify only relevant attributes).""" return Features( recording_id=rec_id, channels=0, start=start, duration=duration, sampling_rate=16000, type="irrelevant", num_frames=round(duration / 0.01), num_features=23, storage_type="irrelevant", storage_path="irrelevant", storage_key="irrelevant", frame_shift=0.01, ) @pytest.fixture def feature_set(): return FeatureSet( features=[features("rec-1", 0.0, 600.0), features("rec-2", 0.0, 357.0)] ) # noinspection PyMethodMayBeStatic class TestMakeWindowedCutsFromFeatures: def test_full_shift_no_shorter_cuts(self, feature_set): cut_set = make_windowed_cuts_from_features( feature_set=feature_set, cut_duration=5.0 ) assert len(cut_set) == 191 assert len([c for c in cut_set if c.recording_id == "rec-1"]) == 120 assert len([c for c in cut_set if c.recording_id == "rec-2"]) == 71 assert all(c.duration == 5.0 for c in cut_set) def test_full_shift_with_shorter_cuts(self, feature_set): cut_set = make_windowed_cuts_from_features( feature_set=feature_set, cut_duration=5.0, keep_shorter_windows=True ) assert len(cut_set) == 192 assert len([c for c in cut_set if c.recording_id == "rec-1"]) == 120 assert len([c for c in cut_set if c.recording_id == "rec-2"]) == 72 assert not all(c.duration == 5.0 for c in cut_set) def test_half_shift_no_shorter_cuts(self, feature_set): cut_set = make_windowed_cuts_from_features( feature_set=feature_set, cut_duration=5.0, cut_shift=2.5 ) assert len(cut_set) == 380 # below, the last window is only 2.5s duration assert len([c for c in cut_set if c.recording_id == "rec-1"]) == 239 # below, the last two windows are 2.0s and 4.5s duration assert len([c for c in cut_set if c.recording_id == "rec-2"]) == 141 assert all(c.duration == 5.0 for c in cut_set) def test_half_shift_with_shorter_cuts(self, feature_set): cut_set = make_windowed_cuts_from_features( feature_set=feature_set, cut_duration=5.0, cut_shift=2.5, keep_shorter_windows=True, ) assert len(cut_set) == 383 assert len([c for c in cut_set if c.recording_id == "rec-1"]) == 240 assert len([c for c in cut_set if c.recording_id == "rec-2"]) == 143 assert not all(c.duration == 5.0 for c in cut_set)

1,941

18

151

1cdf6f8a3f98fd2219e9f83b7c43e32f18d29505

3,608

py

Python

torchdynamo/allowed_functions.py

frank-wei/torchdynamo

26c4c1b593bebf4246e566749dade38254b59ffb

[ "BSD-3-Clause" ]

40

2022-03-02T01:29:29.000Z

2022-03-31T16:02:01.000Z

torchdynamo/allowed_functions.py

frank-wei/torchdynamo

26c4c1b593bebf4246e566749dade38254b59ffb

[ "BSD-3-Clause" ]

62

2022-03-11T00:12:37.000Z

2022-03-31T20:04:27.000Z

torchdynamo/allowed_functions.py

frank-wei/torchdynamo

26c4c1b593bebf4246e566749dade38254b59ffb

[ "BSD-3-Clause" ]

4

2022-03-09T18:43:20.000Z

2022-03-31T01:01:26.000Z

import builtins import collections import copy import functools import itertools import math import operator import types import warnings from functools import lru_cache import numpy import torch from . import config @lru_cache(None) @lru_cache(None) def _allowed_function_ids(): """ Walk torch.* and get the ids of all the stuff in it """ warnings.filterwarnings("ignore", category=UserWarning, module="torch.distributed") torch.distributions.Distribution.set_default_validate_args(False) torch_object_ids = dict() _find_torch_objects(torch) _find_torch_objects(math) for idx in _disallowed_function_ids(): if idx in torch_object_ids: del torch_object_ids[idx] return torch_object_ids def is_allowed(obj): """Is this safe to trace like torch.add ?""" return id(obj) in _allowed_function_ids() def is_disallowed(obj): """Is this safe to trace like torch.add ?""" return id(obj) in _disallowed_function_ids() @lru_cache(None) @lru_cache(None)

26.925373

87

0.625277

import builtins import collections import copy import functools import itertools import math import operator import types import warnings from functools import lru_cache import numpy import torch from . import config @lru_cache(None) def _disallowed_function_ids(): remove = [ True, False, None, collections.OrderedDict, copy.copy, copy.deepcopy, torch.autocast_decrement_nesting, torch.autocast_increment_nesting, torch.autograd.grad, torch.clear_autocast_cache, torch.cuda.current_device, torch.distributions.constraints.is_dependent, torch.distributions.normal.Normal, torch.inference_mode, torch.set_anomaly_enabled, torch.set_autocast_cache_enabled, torch.set_autocast_cpu_dtype, torch.set_autocast_cpu_enabled, torch.set_autocast_enabled, torch.set_autocast_gpu_dtype, torch.autograd.profiler.profile, warnings.warn, ] return {id(x) for x in remove} @lru_cache(None) def _allowed_function_ids(): """ Walk torch.* and get the ids of all the stuff in it """ warnings.filterwarnings("ignore", category=UserWarning, module="torch.distributed") torch.distributions.Distribution.set_default_validate_args(False) torch_object_ids = dict() def _find_torch_objects(module): if any( module.__name__.startswith(mod_name) for mod_name in config.allowed_functions_module_string_ignorelist ): return torch_object_ids[id(module)] = module.__name__ for name, obj in list(module.__dict__.items()): if id(obj) not in torch_object_ids: if isinstance(obj, types.ModuleType): if obj.__name__.startswith("torch."): torch_object_ids[id(obj)] = f"{module.__name__}.{name}" _find_torch_objects(obj) else: torch_object_ids[id(obj)] = f"{module.__name__}.{name}" _find_torch_objects(torch) _find_torch_objects(math) for idx in _disallowed_function_ids(): if idx in torch_object_ids: del torch_object_ids[idx] return torch_object_ids def is_allowed(obj): """Is this safe to trace like torch.add ?""" return id(obj) in _allowed_function_ids() def is_disallowed(obj): """Is this safe to trace like torch.add ?""" return id(obj) in _disallowed_function_ids() @lru_cache(None) def _builtin_function_ids(): rv = { id(v): f"builtins.{k}" for k, v in builtins.__dict__.items() if not k.startswith("_") and callable(v) } rv.update( { id(v): f"operator.{k}" for k, v in operator.__dict__.items() if not k.startswith("_") and callable(v) } ) rv.update( {id(v): f"functools.{v.__name__}" for v in (itertools.chain, itertools.islice)} ) rv[id(functools.reduce)] = "functools.reduce" return rv def is_builtin(obj): return id(obj) in _builtin_function_ids() @lru_cache(None) def _numpy_function_ids(): rv = dict() for mod in (numpy, numpy.random): rv.update( { id(v): f"{mod.__name__}.{k}" for k, v in mod.__dict__.items() if callable(v) and (getattr(v, "__module__", None) or mod.__name__) == mod.__name__ } ) return rv def is_numpy(obj): return isinstance(obj, numpy.ndarray) or id(obj) in _numpy_function_ids()

2,432

0

139

d10f5a7b45ca2a640954b3379de28abe47aa8a4b

9,790

py

Python

utils/cloze_mc_model.py

kenchan0226/control-sum-cmdp

5181e8e0c9bf6bef48f66457e06d3f398f4a428a

[ "MIT" ]

3

2021-08-10T02:31:24.000Z

2021-12-28T09:34:01.000Z

utils/cloze_mc_model.py

kenchan0226/control-sum-cmdp

5181e8e0c9bf6bef48f66457e06d3f398f4a428a

[ "MIT" ]

null

utils/cloze_mc_model.py

kenchan0226/control-sum-cmdp

5181e8e0c9bf6bef48f66457e06d3f398f4a428a

[ "MIT" ]

1

2021-12-02T15:53:22.000Z

from transformers import BertConfig, BertForSequenceClassification, BertTokenizer import torch import os import json import logging MAX_CONTEXT_LEN = 120 if __name__ == "__main__": cloze_model = ClozeMCModel("cuda:0") split_dir="/mnt/sharedfolder/hpchan/datasets/cased-cnn-dailymail_coref/train" with open(os.path.join(split_dir, "{}.json".format(0))) as f: js = json.loads(f.read()) """ masked_questions_ids_list = js["masked_question_ids_list"] multiple_choices_ids_list = js["multiple_choices_ids_list"] answer_id_list = js["answer_idx_list"] summary_sent_list = js["abstract"] summary_str = ' '.join(summary_sent_list) context_str_list = [summary_str for i in range(len(answer_id_list))] context_str_list[-1] = "Mentally ill inmates in Miami are housed on the `` forgotten floor '' Judge Steven Leifman says most are there as a result of `` avoidable felonies ''" confidence_score = cloze_model.compute_confidence_score(masked_questions_ids_list, multiple_choices_ids_list, answer_id_list, context_str_list) print(masked_questions_ids_list) print(multiple_choices_ids_list) print(context_str_list) print(answer_id_list) print(len(answer_id_list)) print(confidence_score) """ masked_questions_ids_2dlist = [] multiple_choices_ids_2dlist = [] answer_id_2dlist = [] context_str_2dlist = [] for i in range(3): with open(os.path.join(split_dir, "{}.json".format(i))) as f: js = json.loads(f.read()) masked_questions_ids_list = js["masked_question_ids_list"] multiple_choices_ids_list = js["multiple_choices_ids_list"] answer_id_list = js["answer_idx_list"] summary_sent_list = js["abstract"] summary_str = ' '.join(summary_sent_list) context_str_list = [summary_str for i in range(len(answer_id_list))] masked_questions_ids_2dlist.append(masked_questions_ids_list) multiple_choices_ids_2dlist.append(multiple_choices_ids_list) answer_id_2dlist.append(answer_id_list) context_str_2dlist.append(context_str_list) num_questions_per_sample = [len(questions) for questions in masked_questions_ids_2dlist] print(num_questions_per_sample) flattened_masked_questions_ids_list = [] flattened_answer_id_list = [] flattened_multiple_choices_ids_list = [] flattened_context_str_list = [] for masked_question_ids_list, answer_id_list, multiple_choices_ids_list, context_str_list in zip(masked_questions_ids_2dlist, answer_id_2dlist, multiple_choices_ids_2dlist, context_str_2dlist): flattened_masked_questions_ids_list += masked_question_ids_list flattened_answer_id_list += answer_id_list flattened_multiple_choices_ids_list += multiple_choices_ids_list flattened_context_str_list += context_str_list print(flattened_context_str_list) print(len(flattened_context_str_list)) print(len(flattened_masked_questions_ids_list)) print(len(flattened_answer_id_list)) print(len(flattened_multiple_choices_ids_list)) confidence_score = cloze_model.compute_confidence_score(flattened_masked_questions_ids_list, flattened_multiple_choices_ids_list, flattened_answer_id_list, flattened_context_str_list) print(confidence_score) num_processed_samples = 0 score_for_each_batch = [] for i in range(len(num_questions_per_sample)): # average for each batch avg_score = confidence_score[num_processed_samples:num_processed_samples+num_questions_per_sample[i]].mean(dim=0) score_for_each_batch.append(avg_score) print(num_processed_samples) print(num_processed_samples+num_questions_per_sample[i]) num_processed_samples += num_questions_per_sample[i] print(score_for_each_batch) score_for_each_batch = torch.cat(score_for_each_batch, dim=0) print(score_for_each_batch) print(score_for_each_batch.size())

56.264368

187

0.71665

from transformers import BertConfig, BertForSequenceClassification, BertTokenizer import torch import os import json import logging MAX_CONTEXT_LEN = 120 class ClozeMCModel: def __init__(self, device): self.device = device self.model_path = "saved_models/entity_cloze_mc_coref_cnn_remove_duplicate" config = BertConfig.from_pretrained(self.model_path) self.tokenizer = BertTokenizer.from_pretrained(self.model_path) self.model = BertForSequenceClassification.from_pretrained(self.model_path, config=config, cache_dir="../../").cuda() self.model.eval() self.batch_size = 42 ids = self.tokenizer.convert_tokens_to_ids(['[CLS]', '[SEP]', '[MC]']) self.cls_id = [ids[0]] self.sep_id = [ids[1]] self.mc_id = [ids[2]] def encode(self, masked_question_list, multiple_choices_list, answer_idx_list): masked_question_ids_list = [] multiple_choices_ids_list = [] answer_idx_list_filtered = [] for masked_question, multiple_choices, answer_idx in zip(masked_question_list, multiple_choices_list, answer_idx_list): masked_question_ids = self.tokenizer.convert_tokens_to_ids(self.tokenizer.tokenize(masked_question)) multiple_choices_str = multiple_choices[0] + ' [MC] ' + multiple_choices[1] + ' [MC] ' + multiple_choices[ 2] + ' [MC] ' + multiple_choices[3] multiple_choices_ids = self.tokenizer.convert_tokens_to_ids(self.tokenizer.tokenize(multiple_choices_str)) if len(masked_question_ids) <= 125 and len(multiple_choices_ids) <= 125: masked_question_ids_list.append(masked_question_ids) multiple_choices_ids_list.append(multiple_choices_ids) answer_idx_list_filtered.append(answer_idx) return masked_question_ids_list, multiple_choices_ids_list, answer_idx_list_filtered def compute_batch(self, masked_questions_ids_batch, multiple_choices_ids_batch, answer_ids_batch, context_str_batch): input_ids_list = [] input_lens = [] token_type_ids_list = [] for masked_question_ids, multiple_choices_ids, context_str in zip(masked_questions_ids_batch, multiple_choices_ids_batch, context_str_batch): context_ids = self.tokenizer.convert_tokens_to_ids(self.tokenizer.tokenize(context_str)) context_ids = context_ids[:MAX_CONTEXT_LEN] first_segment_ids = self.cls_id + masked_question_ids + self.sep_id first_segment_end_position = len(first_segment_ids) - 1 input_ids = first_segment_ids + context_ids + self.sep_id + multiple_choices_ids + self.sep_id input_ids_list.append(input_ids) input_lens.append(len(input_ids)) token_type_ids = [0 if i <= first_segment_end_position else 1 for i in range( len(input_ids) )] token_type_ids_list.append(token_type_ids) max_input_len = max(input_lens) input_ids_list_padded = [] token_type_ids_list_padded = [] for input_ids, token_type_ids in zip(input_ids_list, token_type_ids_list): padding_len = max_input_len - len(input_ids) input_ids_list_padded.append(input_ids + [self.tokenizer.pad_token_id] * padding_len) token_type_ids_list_padded.append(token_type_ids + [1] * padding_len) with torch.no_grad(): input_ids_tensor = torch.LongTensor(input_ids_list_padded).to(self.device) token_type_ids_tensor = torch.LongTensor(token_type_ids_list_padded).to(self.device) answer_ids_tensor = torch.LongTensor(answer_ids_batch).to(self.device) attention_mask = torch.ne(input_ids_tensor, self.tokenizer.pad_token_id).float() try: outputs = self.model(input_ids=input_ids_tensor, attention_mask=attention_mask, token_type_ids=token_type_ids_tensor) except: logging.info(input_ids_tensor.size()) logging.info(attention_mask.size()) logging.info(token_type_ids_tensor.size()) logging.info() for input_ids in input_ids_list_padded: logging.info(input_ids) logging.info(self.tokenizer(input_ids, clean_up_tokenization_spaces=False)) for token_type_ids in token_type_ids_list_padded: logging.info(token_type_ids) logging.info(attention_mask.cpu().numpy()) exit() logits = outputs[0] # [batch_size, 4] confidence_scores_all = torch.nn.functional.softmax(logits, dim=1) # [batch_size, 4] ground_truth_confidence_scores = torch.gather(confidence_scores_all, dim=1, index=answer_ids_tensor.unsqueeze(1)) # [batch_size] return ground_truth_confidence_scores def compute_confidence_score(self, masked_questions_ids_list, multiple_choices_ids_list, answer_id_list, context_str_list): iter_range = range(0, len(masked_questions_ids_list), self.batch_size) confidence_scores_list = [] for batch_start in iter_range: masked_questions_ids_batch = masked_questions_ids_list[batch_start:batch_start+self.batch_size] multiple_choices_ids_batch = multiple_choices_ids_list[batch_start:batch_start+self.batch_size] answer_id_batch = answer_id_list[batch_start:batch_start+self.batch_size] context_str_batch = context_str_list[batch_start:batch_start+self.batch_size] confidence_scores = self.compute_batch(masked_questions_ids_batch, multiple_choices_ids_batch, answer_id_batch, context_str_batch) # [batch_size] confidence_scores_list.append(confidence_scores) return torch.cat(confidence_scores_list, dim=0) # [len(masked_questions_ids_list)] if __name__ == "__main__": cloze_model = ClozeMCModel("cuda:0") split_dir="/mnt/sharedfolder/hpchan/datasets/cased-cnn-dailymail_coref/train" with open(os.path.join(split_dir, "{}.json".format(0))) as f: js = json.loads(f.read()) """ masked_questions_ids_list = js["masked_question_ids_list"] multiple_choices_ids_list = js["multiple_choices_ids_list"] answer_id_list = js["answer_idx_list"] summary_sent_list = js["abstract"] summary_str = ' '.join(summary_sent_list) context_str_list = [summary_str for i in range(len(answer_id_list))] context_str_list[-1] = "Mentally ill inmates in Miami are housed on the `` forgotten floor '' Judge Steven Leifman says most are there as a result of `` avoidable felonies ''" confidence_score = cloze_model.compute_confidence_score(masked_questions_ids_list, multiple_choices_ids_list, answer_id_list, context_str_list) print(masked_questions_ids_list) print(multiple_choices_ids_list) print(context_str_list) print(answer_id_list) print(len(answer_id_list)) print(confidence_score) """ masked_questions_ids_2dlist = [] multiple_choices_ids_2dlist = [] answer_id_2dlist = [] context_str_2dlist = [] for i in range(3): with open(os.path.join(split_dir, "{}.json".format(i))) as f: js = json.loads(f.read()) masked_questions_ids_list = js["masked_question_ids_list"] multiple_choices_ids_list = js["multiple_choices_ids_list"] answer_id_list = js["answer_idx_list"] summary_sent_list = js["abstract"] summary_str = ' '.join(summary_sent_list) context_str_list = [summary_str for i in range(len(answer_id_list))] masked_questions_ids_2dlist.append(masked_questions_ids_list) multiple_choices_ids_2dlist.append(multiple_choices_ids_list) answer_id_2dlist.append(answer_id_list) context_str_2dlist.append(context_str_list) num_questions_per_sample = [len(questions) for questions in masked_questions_ids_2dlist] print(num_questions_per_sample) flattened_masked_questions_ids_list = [] flattened_answer_id_list = [] flattened_multiple_choices_ids_list = [] flattened_context_str_list = [] for masked_question_ids_list, answer_id_list, multiple_choices_ids_list, context_str_list in zip(masked_questions_ids_2dlist, answer_id_2dlist, multiple_choices_ids_2dlist, context_str_2dlist): flattened_masked_questions_ids_list += masked_question_ids_list flattened_answer_id_list += answer_id_list flattened_multiple_choices_ids_list += multiple_choices_ids_list flattened_context_str_list += context_str_list print(flattened_context_str_list) print(len(flattened_context_str_list)) print(len(flattened_masked_questions_ids_list)) print(len(flattened_answer_id_list)) print(len(flattened_multiple_choices_ids_list)) confidence_score = cloze_model.compute_confidence_score(flattened_masked_questions_ids_list, flattened_multiple_choices_ids_list, flattened_answer_id_list, flattened_context_str_list) print(confidence_score) num_processed_samples = 0 score_for_each_batch = [] for i in range(len(num_questions_per_sample)): # average for each batch avg_score = confidence_score[num_processed_samples:num_processed_samples+num_questions_per_sample[i]].mean(dim=0) score_for_each_batch.append(avg_score) print(num_processed_samples) print(num_processed_samples+num_questions_per_sample[i]) num_processed_samples += num_questions_per_sample[i] print(score_for_each_batch) score_for_each_batch = torch.cat(score_for_each_batch, dim=0) print(score_for_each_batch) print(score_for_each_batch.size())

5,642

-2

130

145f855179547244441085eb5696c4ff8167f388

4,685

py

Python

tests/hypothesis2_4_masks.py

davtoh/RRTools

6dde2d4622719d9031bf21ffbf7723231a0e2003

[ "BSD-3-Clause" ]

1

2019-07-16T03:54:22.000Z

tests/hypothesis2_4_masks.py

davtoh/RRTools

6dde2d4622719d9031bf21ffbf7723231a0e2003

[ "BSD-3-Clause" ]

null

tests/hypothesis2_4_masks.py

davtoh/RRTools

6dde2d4622719d9031bf21ffbf7723231a0e2003

[ "BSD-3-Clause" ]

1

2019-07-09T02:49:06.000Z

from __future__ import division from __future__ import print_function from __future__ import absolute_import from builtins import range from past.utils import old_div from .tesisfunctions import Plotim,overlay,padVH import cv2 import numpy as np #from invariantMoments import centroid,invmoments,normalizedinvariantmoment,bwmoment from .tesisfunctions import sigmoid,histogram,brightness,getthresh,threshold,pad,graphpolygontest, polygontest #http://stackoverflow.com/questions/14725181/speed-up-iteration-over-numpy-arrays-opencv-cv2-image #http://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_imgproc/py_contours/py_contour_features/py_contour_features.html fn1 = r'im1_2.jpg' #fn1 = r"asift2Result_with_alfa1.png" #fn1 = r"im_completer_Result2.png" fore = cv2.imread(fn1) fore = cv2.resize(fore,(300,300)) name = fn1.split('\\')[-1].split(".")[0] fore2 = fore.copy() """ fore = fore.astype("float") fb = fore[:,:,0] fg = fore[:,:,1] fr = fore[:,:,2] # threshold retinal area alfa = -1 beta = 50 # if alfa >0 :if beta = 50 with noise, if beta = 200 without noise th = 1 kernel = np.ones((100,100),np.uint8) enhanced = sigmoid(fr,alfa,beta) thresh = cv2.threshold(enhanced.astype("uint8"),th,1,cv2.THRESH_BINARY_INV)[1] #dilation = cv2.dilate(thresh,kernel,iterations = 1) #erosion = cv2.erode(dilation,kernel,iterations = 1) #closing = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel) opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel) #dilation = cv2.dilate(opening,kernel,iterations = 1) lastthresh = opening """ P = brightness(fore) thresh = getthresh(cv2.resize(P,(300,300))) print(thresh) lastthresh=threshold(P,thresh,1,0) thresh,lastthresh = cv2.threshold(P,0,1,cv2.THRESH_BINARY+cv2.THRESH_OTSU) #lastthresh = pad(lastthresh,1) plotc = Plotim(name + " overlayed lastthresh", overlay(fore.copy(), lastthresh * 255, alpha=lastthresh)) plotc.show() # find biggest area contours,hierarchy = cv2.findContours(lastthresh.copy(),cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) print("objects: ",len(contours)) index = 0 maxarea = 0 #objectarea = np.sum(lastthresh) for i in range(len(contours)): area = cv2.contourArea(contours[i]) if area>maxarea: index = i maxarea = area print("area contour:",maxarea,"index: ",index) cnt = contours[index] print("optaining polygon test...") polygontest = graphpolygontest((P,cnt)).show() #DEFECTS pallet = [[0,0,0],[255,255,255]] pallet = np.array(pallet,np.uint8) imdefects = pallet[lastthresh] hull = cv2.convexHull(cnt,returnPoints = False) defects = cv2.convexityDefects(cnt,hull) distances = defects[:,0,3] two_max = np.argpartition(distances, -2)[-2:] # get indeces of two maximum values for i in range(defects.shape[0]): s,e,f,d = defects[i,0] start = tuple(cnt[s][0]) end = tuple(cnt[e][0]) far = tuple(cnt[f][0]) cv2.line(imdefects,start,end,[0,255,0],2) cv2.circle(imdefects,far,5,[0,0,255],-1) #SEPARATING LINE points = defects[:,0,2] x1,y1 = tuple(cnt[points[two_max[0]]][0]) x2,y2 = tuple(cnt[points[two_max[1]]][0]) m = old_div((y2-y1),float(x2-x1)) b = int(y1-x1*m) # find interception with xf and yf axis if b>imdefects.shape[0]: # if start outside yf start = int(old_div((imdefects.shape[0]-b),m)),imdefects.shape[0] # (yf-b)/m, yf else: # if start inside yf start = 0,b # 0,y y = int(m*imdefects.shape[1]+b) # m*xf+b if y<0: # if end outside yf end = int(old_div(-b,m)),0# x,0 else: # if end inside yf end = imdefects.shape[1],y # xf, y cv2.line(imdefects,start,end,[0,0,100],2) plotc = Plotim(name + " defects", imdefects) plotc.show() #ROI ROI = np.zeros(P.shape,dtype=np.uint8) cv2.drawContours(ROI,[cnt],0,1,-1) plotc = Plotim(name + " ROI", ROI) plotc.show() M = cv2.moments(cnt) # find moments #M2 = invmoments(ROI,Area=None,center=None) #cx = int(M['m10']/M['m00']) #cy = int(M['m01']/M['m00']) #x,y = centroid(ROI,maxarea) #normalizedinvariantmoment(ROI,maxarea,0,0,x,y) #n00 = bwmoment(ROI,0,0,cx,cy) #print "(cx,cy)",(cx,cy) #print "x,y",x,y #cv2.circle(fore, (cx,cy), 10, (0, 0, 255), -1, 8) #cv2.circle(fore, (int(x),int(y)), 10, (0, 255, 255), -1, 8) cv2.drawContours(fore,[cnt],0,(0, 0, 255),2) ellipse = cv2.fitEllipse(cnt) cv2.ellipse(fore,ellipse,(0,255,0),2) plotc = Plotim(name + " description", fore) plotc.show() mask = np.ones(P.shape,dtype=np.uint8) cv2.ellipse(mask,ellipse,0,-1) fore2[mask>0]=0 plotc = Plotim(name + " result", fore2) plotc.show() cv2.imwrite("mask_"+name+".png",fore2) """ # Saving the objects: import pickle data = {"thresh":thresh,"lastthresh":lastthresh,"cnt":cnt,"ellipse":ellipse,"polygontest":polygontest} with open("masks_"+name+'.pickle', 'w') as f: pickle.dump(data, f)"""

32.534722

137

0.704803

from __future__ import division from __future__ import print_function from __future__ import absolute_import from builtins import range from past.utils import old_div from .tesisfunctions import Plotim,overlay,padVH import cv2 import numpy as np #from invariantMoments import centroid,invmoments,normalizedinvariantmoment,bwmoment from .tesisfunctions import sigmoid,histogram,brightness,getthresh,threshold,pad,graphpolygontest, polygontest #http://stackoverflow.com/questions/14725181/speed-up-iteration-over-numpy-arrays-opencv-cv2-image #http://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_imgproc/py_contours/py_contour_features/py_contour_features.html fn1 = r'im1_2.jpg' #fn1 = r"asift2Result_with_alfa1.png" #fn1 = r"im_completer_Result2.png" fore = cv2.imread(fn1) fore = cv2.resize(fore,(300,300)) name = fn1.split('\\')[-1].split(".")[0] fore2 = fore.copy() """ fore = fore.astype("float") fb = fore[:,:,0] fg = fore[:,:,1] fr = fore[:,:,2] # threshold retinal area alfa = -1 beta = 50 # if alfa >0 :if beta = 50 with noise, if beta = 200 without noise th = 1 kernel = np.ones((100,100),np.uint8) enhanced = sigmoid(fr,alfa,beta) thresh = cv2.threshold(enhanced.astype("uint8"),th,1,cv2.THRESH_BINARY_INV)[1] #dilation = cv2.dilate(thresh,kernel,iterations = 1) #erosion = cv2.erode(dilation,kernel,iterations = 1) #closing = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel) opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel) #dilation = cv2.dilate(opening,kernel,iterations = 1) lastthresh = opening """ P = brightness(fore) thresh = getthresh(cv2.resize(P,(300,300))) print(thresh) lastthresh=threshold(P,thresh,1,0) thresh,lastthresh = cv2.threshold(P,0,1,cv2.THRESH_BINARY+cv2.THRESH_OTSU) #lastthresh = pad(lastthresh,1) plotc = Plotim(name + " overlayed lastthresh", overlay(fore.copy(), lastthresh * 255, alpha=lastthresh)) plotc.show() # find biggest area contours,hierarchy = cv2.findContours(lastthresh.copy(),cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) print("objects: ",len(contours)) index = 0 maxarea = 0 #objectarea = np.sum(lastthresh) for i in range(len(contours)): area = cv2.contourArea(contours[i]) if area>maxarea: index = i maxarea = area print("area contour:",maxarea,"index: ",index) cnt = contours[index] print("optaining polygon test...") polygontest = graphpolygontest((P,cnt)).show() #DEFECTS pallet = [[0,0,0],[255,255,255]] pallet = np.array(pallet,np.uint8) imdefects = pallet[lastthresh] hull = cv2.convexHull(cnt,returnPoints = False) defects = cv2.convexityDefects(cnt,hull) distances = defects[:,0,3] two_max = np.argpartition(distances, -2)[-2:] # get indeces of two maximum values for i in range(defects.shape[0]): s,e,f,d = defects[i,0] start = tuple(cnt[s][0]) end = tuple(cnt[e][0]) far = tuple(cnt[f][0]) cv2.line(imdefects,start,end,[0,255,0],2) cv2.circle(imdefects,far,5,[0,0,255],-1) #SEPARATING LINE points = defects[:,0,2] x1,y1 = tuple(cnt[points[two_max[0]]][0]) x2,y2 = tuple(cnt[points[two_max[1]]][0]) m = old_div((y2-y1),float(x2-x1)) b = int(y1-x1*m) # find interception with xf and yf axis if b>imdefects.shape[0]: # if start outside yf start = int(old_div((imdefects.shape[0]-b),m)),imdefects.shape[0] # (yf-b)/m, yf else: # if start inside yf start = 0,b # 0,y y = int(m*imdefects.shape[1]+b) # m*xf+b if y<0: # if end outside yf end = int(old_div(-b,m)),0# x,0 else: # if end inside yf end = imdefects.shape[1],y # xf, y cv2.line(imdefects,start,end,[0,0,100],2) plotc = Plotim(name + " defects", imdefects) plotc.show() #ROI ROI = np.zeros(P.shape,dtype=np.uint8) cv2.drawContours(ROI,[cnt],0,1,-1) plotc = Plotim(name + " ROI", ROI) plotc.show() M = cv2.moments(cnt) # find moments #M2 = invmoments(ROI,Area=None,center=None) #cx = int(M['m10']/M['m00']) #cy = int(M['m01']/M['m00']) #x,y = centroid(ROI,maxarea) #normalizedinvariantmoment(ROI,maxarea,0,0,x,y) #n00 = bwmoment(ROI,0,0,cx,cy) #print "(cx,cy)",(cx,cy) #print "x,y",x,y #cv2.circle(fore, (cx,cy), 10, (0, 0, 255), -1, 8) #cv2.circle(fore, (int(x),int(y)), 10, (0, 255, 255), -1, 8) cv2.drawContours(fore,[cnt],0,(0, 0, 255),2) ellipse = cv2.fitEllipse(cnt) cv2.ellipse(fore,ellipse,(0,255,0),2) plotc = Plotim(name + " description", fore) plotc.show() mask = np.ones(P.shape,dtype=np.uint8) cv2.ellipse(mask,ellipse,0,-1) fore2[mask>0]=0 plotc = Plotim(name + " result", fore2) plotc.show() cv2.imwrite("mask_"+name+".png",fore2) """ # Saving the objects: import pickle data = {"thresh":thresh,"lastthresh":lastthresh,"cnt":cnt,"ellipse":ellipse,"polygontest":polygontest} with open("masks_"+name+'.pickle', 'w') as f: pickle.dump(data, f)"""

0

8eb87ebacb5175749b25e51af42bb1da2f1af53b

4,924

py

Python

PyNewsletter.py

Diogo-Paulico/PyNewsletter

a8e4782e96a21fb436d020643083edb3008d0268

[ "MIT" ]

3

2021-02-16T11:40:23.000Z

2021-02-27T20:03:42.000Z

PyNewsletter.py

Diogo-Paulico/PyNewsletter

a8e4782e96a21fb436d020643083edb3008d0268

[ "MIT" ]

1

2021-02-27T20:43:06.000Z

PyNewsletter.py

Diogo-Paulico/PyNewsletter

a8e4782e96a21fb436d020643083edb3008d0268

[ "MIT" ]

null

import email, smtplib, ssl, sys, imaplib, email.header import pandas as pd from config import * from email import encoders from email.mime.base import MIMEBase from email.mime.multipart import MIMEMultipart from email.mime.text import MIMEText # Loads the csv file given by the CSV_FILE variable # @return -> list of email addresses contained in the column Email # Loads the email body from the TEXT_BODY_FILE body = open(TEXT_BODY_FILE,'r').read() # Removes the given email from the loaded CSV file containing the emails # @return -> True is the emailing list changed, False otherwise # will use the IMAP protocol to check the EMAIL_FOLDER for unseen messages with the subject given by CANCEL_SUBJECT_KEYWORD # @return -> the list of emails to be removed # will handle all the unsubcribing, getting the emails to unsubscribe using the getUnsubscribers() function # and remove them using the removeSubscriber(email_to_remove) function # @return -> list of email adresses removed from the mailing list # builds the message object for the emails given the email adress of the receiver (email_receiver) # @return -> message object "stringified" # builds the message object for the unsubscribed emails given the email adress of the receiver (email_receiver) and the path to the file containing the # message to be sent to unsubscribers (UNSUB_BODY_FILE) # @return -> message object "stringified" # Will import the email adresses, handle unsubscribing emails using the previously defined functions, # then it will send the unsub message to emails that asked to be removed if SEND_UNSUB_MESSAGE is set to True # and the newsletter to the emails present in the emailing list pyNewsletter()

35.941606

152

0.667141

import email, smtplib, ssl, sys, imaplib, email.header import pandas as pd from config import * from email import encoders from email.mime.base import MIMEBase from email.mime.multipart import MIMEMultipart from email.mime.text import MIMEText # Loads the csv file given by the CSV_FILE variable # @return -> list of email addresses contained in the column Email def buildContacts(): global df df = pd.read_csv(CSV_FILE) contacts = df.Email return contacts # Loads the email body from the TEXT_BODY_FILE body = open(TEXT_BODY_FILE,'r').read() # Removes the given email from the loaded CSV file containing the emails # @return -> True is the emailing list changed, False otherwise def removeSubscriber(email_to_remove): global df count = df.Email.count() df = df[df.Email != email_to_remove] df.Email.to_csv(CSV_FILE, index = False) return (df.Email.count() != count) # will use the IMAP protocol to check the EMAIL_FOLDER for unseen messages with the subject given by CANCEL_SUBJECT_KEYWORD # @return -> the list of emails to be removed def getUnsubscribers(): emailsToRemove=[] M = imaplib.IMAP4_SSL(IMAP_ADRESS) try: rv, data = M.login(SENDER_EMAIL, PASSWORD) except imaplib.IMAP4.error: print ("LOGIN FAILED!!! ") sys.exit(1) rv, data = M.select(EMAIL_FOLDER) if rv != 'OK': M.logout() return rv, data = M.search(None, '(UNSEEN SUBJECT "{0}")'.format(CANCEL_SUBJECT_KEYWORD)) if rv != 'OK' or str(data[0]) == "b''": return for num in data[0].split(): rv, data = M.fetch(num, '(RFC822)') if rv != 'OK': print("ERROR getting message", num) return msg = email.message_from_bytes(data[0][1]) hdr = email.header.make_header(email.header.decode_header(msg['Subject'])) subject = str(hdr) emailFrom = str(email.utils.parseaddr(msg['From'])[1]) emailsToRemove.append(emailFrom.strip()) M.close() M.logout() return emailsToRemove # will handle all the unsubcribing, getting the emails to unsubscribe using the getUnsubscribers() function # and remove them using the removeSubscriber(email_to_remove) function # @return -> list of email adresses removed from the mailing list def unsubHandler(): count = 0 toUnsub = getUnsubscribers() unSubd = [] emailingListChanged = False if toUnsub: for email in toUnsub: emailingListChanged = removeSubscriber(email) if emailingListChanged: count += 1 unSubd.append(email) print('Removed %d subscribers' % (count)) else: print('No subscribers removed') return unSubd # builds the message object for the emails given the email adress of the receiver (email_receiver) # @return -> message object "stringified" def messageBuilder(email_receiver): message = MIMEMultipart() message["From"] = SENDER_NAME message["To"] = email_receiver message["Subject"] = SUBJECT message.attach(MIMEText(body, "plain")) return message.as_string() # builds the message object for the unsubscribed emails given the email adress of the receiver (email_receiver) and the path to the file containing the # message to be sent to unsubscribers (UNSUB_BODY_FILE) # @return -> message object "stringified" def unsubMessageBuilder(email_receiver): unsubBody = open(UNSUB_BODY_FILE,'r').read() message = MIMEMultipart() message["From"] = SENDER_NAME message["To"] = email_receiver message["Subject"] = UNSUB_MESSAGE_SUBJECT message.attach(MIMEText(unsubBody, "plain")) return message.as_string() # Will import the email adresses, handle unsubscribing emails using the previously defined functions, # then it will send the unsub message to emails that asked to be removed if SEND_UNSUB_MESSAGE is set to True # and the newsletter to the emails present in the emailing list def pyNewsletter(): contacts = buildContacts() unsubEmails = unsubHandler() contacts = buildContacts() counter = 0 context = ssl.create_default_context() with smtplib.SMTP_SSL(SMTP_ADRESS, SSL_PORT, context=context) as server: try: server.login(SENDER_EMAIL, PASSWORD) if unsubEmails and SEND_UNSUB_MESSAGE: for unsubEmail in unsubEmails: server.sendmail(SENDER_EMAIL, unsubEmail, unsubMessageBuilder(unsubEmail)) for receiver_email in contacts: server.sendmail(SENDER_EMAIL, receiver_email, messageBuilder(receiver_email)) counter+=1 except: print("SMTP server connection error") print('Sent ' + str(counter) + ' out of '+ str(contacts.size) + ' emails.') pyNewsletter()

3,073

0

154

4aa1225b275666806c08c3f04e1756fc027da524

808

py

Python

aoc15-2.py

UnrelatedString/advent-of-code-2021

f802240ce01dc9e31f152915456aff2644b281e2

[ "MIT" ]

null

aoc15-2.py

UnrelatedString/advent-of-code-2021

f802240ce01dc9e31f152915456aff2644b281e2

[ "MIT" ]

1

2021-12-10T07:24:13.000Z

2021-12-11T05:10:50.000Z

aoc15-2.py

UnrelatedString/advent-of-code-2021

f802240ce01dc9e31f152915456aff2644b281e2

[ "MIT" ]

null

import sys from stuff import * import heapq as hq ls = lines()#chunks()#nums() cs = {} d = {} for y,l in enumerate(ls): for x,n in enumerate(l): n = eval(n) for Y in range(5): for X in range(5): c=complex(x+len(l)*X,y+len(ls)*Y) cs[c] = (n-1+X+Y)%9+1 d[c] = float('inf') #u.add(complex(x,y)) g = c #thank fuck for python's scoping being shit d[0] = 0 u = {*cs.keys()} h = [] hq.heappush(h,(0,(0,0))) while g in u: _,c = hq.heappop(h)#min(u,key=d.__getitem__) c = complex(*c) u.remove(c) for o in von_neumann: if c+o not in cs: continue if d[c+o] == float('inf'): hq.heappush(h,(d[c]+cs[c+o],c_t(c+o))) #uh? d[c+o] = min(d[c+o], d[c]+cs[c+o]) print(d[g])

21.837838

55

0.483911

import sys from stuff import * import heapq as hq ls = lines()#chunks()#nums() cs = {} d = {} for y,l in enumerate(ls): for x,n in enumerate(l): n = eval(n) for Y in range(5): for X in range(5): c=complex(x+len(l)*X,y+len(ls)*Y) cs[c] = (n-1+X+Y)%9+1 d[c] = float('inf') #u.add(complex(x,y)) g = c #thank fuck for python's scoping being shit d[0] = 0 u = {*cs.keys()} h = [] hq.heappush(h,(0,(0,0))) while g in u: _,c = hq.heappop(h)#min(u,key=d.__getitem__) c = complex(*c) u.remove(c) for o in von_neumann: if c+o not in cs: continue if d[c+o] == float('inf'): hq.heappush(h,(d[c]+cs[c+o],c_t(c+o))) #uh? d[c+o] = min(d[c+o], d[c]+cs[c+o]) print(d[g])

0

b9a14b5da4025ad529f64c2d622dcacffe4710d0

14,219

py

Python

ee/tasks/test/test_calculate_cohort.py

msnitish/posthog

cb86113f568e72eedcb64b5fd00c313d21e72f90

[ "MIT" ]

null

ee/tasks/test/test_calculate_cohort.py

msnitish/posthog

cb86113f568e72eedcb64b5fd00c313d21e72f90

[ "MIT" ]

null

ee/tasks/test/test_calculate_cohort.py

msnitish/posthog

cb86113f568e72eedcb64b5fd00c313d21e72f90

[ "MIT" ]

null

import json import urllib.parse from unittest.mock import patch from uuid import uuid4 from freezegun import freeze_time from ee.clickhouse.models.event import create_event from ee.clickhouse.util import ClickhouseTestMixin from posthog.client import sync_execute from posthog.models.cohort import Cohort from posthog.models.person import Person from posthog.tasks.calculate_cohort import insert_cohort_from_insight_filter from posthog.tasks.test.test_calculate_cohort import calculate_cohort_test_factory

39.279006

373

0.486673

import json import urllib.parse from unittest.mock import patch from uuid import uuid4 from freezegun import freeze_time from ee.clickhouse.models.event import create_event from ee.clickhouse.util import ClickhouseTestMixin from posthog.client import sync_execute from posthog.models.cohort import Cohort from posthog.models.person import Person from posthog.tasks.calculate_cohort import insert_cohort_from_insight_filter from posthog.tasks.test.test_calculate_cohort import calculate_cohort_test_factory def _create_event(**kwargs): kwargs.update({"event_uuid": uuid4()}) create_event(**kwargs) def _create_person(**kwargs): person = Person.objects.create(**kwargs) return Person(id=person.uuid) class TestClickhouseCalculateCohort(ClickhouseTestMixin, calculate_cohort_test_factory(_create_event, _create_person)): # type: ignore @patch("posthog.tasks.calculate_cohort.insert_cohort_from_insight_filter.delay") def test_create_stickiness_cohort(self, _insert_cohort_from_insight_filter): _create_person(team_id=self.team.pk, distinct_ids=["blabla"]) _create_event( team=self.team, event="$pageview", distinct_id="blabla", properties={"$math_prop": 1}, timestamp="2021-01-01T12:00:00Z", ) response = self.client.post( f"/api/projects/{self.team.id}/cohorts/?insight=STICKINESS&properties=%5B%5D&interval=day&display=ActionsLineGraph&events=%5B%7B%22id%22%3A%22%24pageview%22%2C%22name%22%3A%22%24pageview%22%2C%22type%22%3A%22events%22%2C%22order%22%3A0%7D%5D&shown_as=Stickiness&date_from=2021-01-01&entity_id=%24pageview&entity_type=events&stickiness_days=1&label=%24pageview", {"name": "test", "is_static": True}, ).json() cohort_id = response["id"] _insert_cohort_from_insight_filter.assert_called_once_with( cohort_id, { "insight": "STICKINESS", "properties": "[]", "interval": "day", "display": "ActionsLineGraph", "events": '[{"id":"$pageview","name":"$pageview","type":"events","order":0}]', "shown_as": "Stickiness", "date_from": "2021-01-01", "entity_id": "$pageview", "entity_type": "events", "stickiness_days": "1", "label": "$pageview", }, ) insert_cohort_from_insight_filter( cohort_id, { "date_from": "2021-01-01", "events": [ { "id": "$pageview", "type": "events", "order": 0, "name": "$pageview", "custom_name": None, "math": None, "math_property": None, "math_group_type_index": None, "properties": [], } ], "insight": "STICKINESS", "interval": "day", "selected_interval": 1, "shown_as": "Stickiness", "entity_id": "$pageview", "entity_type": "events", "entity_math": None, }, ) cohort = Cohort.objects.get(pk=cohort_id) people = Person.objects.filter(cohort__id=cohort.pk) self.assertEqual(people.count(), 1) @patch("posthog.tasks.calculate_cohort.insert_cohort_from_insight_filter.delay") def test_create_trends_cohort(self, _insert_cohort_from_insight_filter): _create_person(team_id=self.team.pk, distinct_ids=["blabla"]) with freeze_time("2021-01-01 00:06:34"): _create_event( team=self.team, event="$pageview", distinct_id="blabla", properties={"$math_prop": 1}, timestamp="2021-01-01T12:00:00Z", ) with freeze_time("2021-01-02 00:06:34"): _create_event( team=self.team, event="$pageview", distinct_id="blabla", properties={"$math_prop": 4}, timestamp="2021-01-01T12:00:00Z", ) response = self.client.post( f"/api/projects/{self.team.id}/cohorts/?interval=day&display=ActionsLineGraph&events=%5B%7B%22id%22%3A%22%24pageview%22%2C%22name%22%3A%22%24pageview%22%2C%22type%22%3A%22events%22%2C%22order%22%3A0%7D%5D&properties=%5B%5D&entity_id=%24pageview&entity_type=events&date_from=2021-01-01&date_to=2021-01-01&label=%24pageview", {"name": "test", "is_static": True}, ).json() cohort_id = response["id"] _insert_cohort_from_insight_filter.assert_called_once_with( cohort_id, { "interval": "day", "display": "ActionsLineGraph", "events": '[{"id":"$pageview","name":"$pageview","type":"events","order":0}]', "properties": "[]", "entity_id": "$pageview", "entity_type": "events", "date_from": "2021-01-01", "date_to": "2021-01-01", "label": "$pageview", }, ) insert_cohort_from_insight_filter( cohort_id, { "date_from": "2021-01-01", "date_to": "2021-01-01", "display": "ActionsLineGraph", "events": [ { "id": "$pageview", "type": "events", "order": 0, "name": "$pageview", "math": None, "math_property": None, "math_group_type_index": None, "properties": [], } ], "entity_id": "$pageview", "entity_type": "events", "insight": "TRENDS", "interval": "day", }, ) cohort = Cohort.objects.get(pk=cohort_id) people = Person.objects.filter(cohort__id=cohort.pk) self.assertEqual(cohort.errors_calculating, 0) self.assertEqual( people.count(), 1, { "a": sync_execute( "select person_id from person_static_cohort where team_id = {} and cohort_id = {} ".format( self.team.id, cohort.pk ) ), "b": sync_execute( "select person_id from person_static_cohort FINAL where team_id = {} and cohort_id = {} ".format( self.team.id, cohort.pk ) ), }, ) @patch("posthog.tasks.calculate_cohort.insert_cohort_from_insight_filter.delay") def test_create_trends_cohort_arg_test(self, _insert_cohort_from_insight_filter): # prior to 8124, subtitute parameters was called on insight cohorting which caused '%' in LIKE arguments to be interepreted as a missing parameter _create_person(team_id=self.team.pk, distinct_ids=["blabla"]) with freeze_time("2021-01-01 00:06:34"): _create_event( team=self.team, event="$pageview", distinct_id="blabla", properties={"$domain": "https://app.posthog.com/123"}, timestamp="2021-01-01T12:00:00Z", ) with freeze_time("2021-01-02 00:06:34"): _create_event( team=self.team, event="$pageview", distinct_id="blabla", properties={"$domain": "https://app.posthog.com/123"}, timestamp="2021-01-01T12:00:00Z", ) params = { "date_from": "2021-01-01", "date_to": "2021-01-01", "display": "ActionsLineGraph", "events": json.dumps([{"id": "$pageview", "name": "$pageview", "type": "events", "order": 0}]), "entity_id": "$pageview", "entity_type": "events", "insight": "TRENDS", "interval": "day", "properties": json.dumps( [{"key": "$domain", "value": "app.posthog.com", "operator": "icontains", "type": "event"}] ), } response = self.client.post( f"/api/projects/{self.team.id}/cohorts/?{urllib.parse.urlencode(params)}", {"name": "test", "is_static": True}, ).json() cohort_id = response["id"] _insert_cohort_from_insight_filter.assert_called_once_with( cohort_id, { "date_from": "2021-01-01", "date_to": "2021-01-01", "display": "ActionsLineGraph", "events": '[{"id": "$pageview", "name": "$pageview", "type": "events", "order": 0}]', "entity_id": "$pageview", "entity_type": "events", "insight": "TRENDS", "interval": "day", "properties": '[{"key": "$domain", "value": "app.posthog.com", "operator": "icontains", "type": "event"}]', }, ) insert_cohort_from_insight_filter( cohort_id, { "date_from": "2021-01-01", "date_to": "2021-01-01", "display": "ActionsLineGraph", "events": [ { "id": "$pageview", "type": "events", "order": 0, "name": "$pageview", "math": None, "math_property": None, "math_group_type_index": None, "properties": [], } ], "properties": [ {"key": "$domain", "value": "app.posthog.com", "operator": "icontains", "type": "event"} ], "entity_id": "$pageview", "entity_type": "events", "insight": "TRENDS", "interval": "day", }, ) cohort = Cohort.objects.get(pk=cohort_id) people = Person.objects.filter(cohort__id=cohort.pk) self.assertEqual(cohort.errors_calculating, 0) self.assertEqual( people.count(), 1, { "a": sync_execute( "select person_id from person_static_cohort where team_id = {} and cohort_id = {} ".format( self.team.id, cohort.pk ) ), "b": sync_execute( "select person_id from person_static_cohort FINAL where team_id = {} and cohort_id = {} ".format( self.team.id, cohort.pk ) ), }, ) @patch("posthog.tasks.calculate_cohort.insert_cohort_from_insight_filter.delay") def test_create_funnels_cohort(self, _insert_cohort_from_insight_filter): _create_person(team_id=self.team.pk, distinct_ids=["blabla"]) with freeze_time("2021-01-01 00:06:34"): _create_event( team=self.team, event="$pageview", distinct_id="blabla", properties={"$math_prop": 1}, timestamp="2021-01-01T12:00:00Z", ) with freeze_time("2021-01-02 00:06:34"): _create_event( team=self.team, event="$another_view", distinct_id="blabla", properties={"$math_prop": 4}, timestamp="2021-01-02T12:00:00Z", ) params = { "insight": "FUNNELS", "events": json.dumps( [ { "id": "$pageview", "math": None, "name": "$pageview", "type": "events", "order": 0, "properties": [], "math_property": None, }, { "id": "$another_view", "math": None, "name": "$another_view", "type": "events", "order": 1, "properties": [], "math_property": None, }, ] ), "display": "FunnelViz", "interval": "day", "layout": "horizontal", "date_from": "2021-01-01", "date_to": "2021-01-07", "funnel_step": 1, } response = self.client.post( f"/api/projects/{self.team.id}/cohorts/?{urllib.parse.urlencode(params)}", {"name": "test", "is_static": True}, ).json() cohort_id = response["id"] _insert_cohort_from_insight_filter.assert_called_once_with( cohort_id, { "insight": "FUNNELS", "events": '[{"id": "$pageview", "math": null, "name": "$pageview", "type": "events", "order": 0, "properties": [], "math_property": null}, {"id": "$another_view", "math": null, "name": "$another_view", "type": "events", "order": 1, "properties": [], "math_property": null}]', "display": "FunnelViz", "interval": "day", "layout": "horizontal", "date_from": "2021-01-01", "date_to": "2021-01-07", "funnel_step": "1", }, ) insert_cohort_from_insight_filter( cohort_id, params, ) cohort = Cohort.objects.get(pk=cohort_id) people = Person.objects.filter(cohort__id=cohort.pk) self.assertEqual(cohort.errors_calculating, 0) self.assertEqual(people.count(), 1)

13,078

561

69

ca605f86181c04b6e4c6071ff1fa0fae67e38c02

1,994

py

Python

core/urls.py

jianxinwang/GenEsysV

444b4685b603c3da5ac9d9265817cac98c33c97e

[ "BSD-3-Clause" ]

14

2019-02-27T13:57:36.000Z

2021-10-01T14:29:38.000Z

core/urls.py

jianxinwang/GenEsysV

444b4685b603c3da5ac9d9265817cac98c33c97e

[ "BSD-3-Clause" ]

11

2019-06-13T06:38:43.000Z

2021-06-15T13:51:39.000Z

core/urls.py

jianxinwang/GenEsysV

444b4685b603c3da5ac9d9265817cac98c33c97e

[ "BSD-3-Clause" ]

5

2019-02-27T13:57:40.000Z

2020-02-09T13:15:06.000Z

from django.urls import path import core.views as core_views urlpatterns = ( path('dataset-snippet/<int:study_id>', core_views.DatasetSnippetView.as_view(), name='dataset-snippet'), path('analysis-type-snippet/<int:dataset_id>', core_views.AnalysisTypeSnippetView.as_view(), name='analysis-type-snippet'), path('filter-snippet/<int:dataset_id>', core_views.FilterSnippetView.as_view(), name='filter-snippet'), path('attribute-snippet/<int:dataset_id>', core_views.AttributeSnippetView.as_view(), name='attribute-snippet'), path('search-router/', core_views.SearchRouterView.as_view(), name='search-router'), path('download-router/<int:search_log_id>', core_views.DownloadRouterView.as_view(), name='download-router'), path('additional-form-router/<int:dataset_id>/<int:analysis_type_id>', core_views.AdditionalFormRouterView.as_view(), name='additional-form-router'), path('base-search/', core_views.BaseSearchView.as_view(), name='base-search'), path('base-download/<int:search_log_id>', core_views.BaseDownloadView.as_view(), name='base-download'), path('save-search/', core_views.save_search, name='save-search'), path('saved-search-list/', core_views.SavedSearchListView.as_view(), name='saved-search-list'), path('retrieve-saved-search/<int:saved_search_id>', core_views.RetrieveSavedSearchView.as_view(), name='retrieve-saved-search'), path('core-document-view/<int:dataset_id>/<document_es_id>/', core_views.BaseDocumentView.as_view(), name='core-document-view'), path('core-document-review-create/<int:dataset_id>/<document_es_id>/', core_views.DocumentReviewCreateView.as_view(), name='core-document-review-create'), path('core-document-review-update/<int:dataset_id>/<int:document_review_id>/', core_views.DocumentReviewUpdateView.as_view(), name='core-document-review-update'), path('core-document-list/', core_views.DocumentReviewListView.as_view(), name='core-document-list'), )

73.851852

166

0.746239

from django.urls import path import core.views as core_views urlpatterns = ( path('dataset-snippet/<int:study_id>', core_views.DatasetSnippetView.as_view(), name='dataset-snippet'), path('analysis-type-snippet/<int:dataset_id>', core_views.AnalysisTypeSnippetView.as_view(), name='analysis-type-snippet'), path('filter-snippet/<int:dataset_id>', core_views.FilterSnippetView.as_view(), name='filter-snippet'), path('attribute-snippet/<int:dataset_id>', core_views.AttributeSnippetView.as_view(), name='attribute-snippet'), path('search-router/', core_views.SearchRouterView.as_view(), name='search-router'), path('download-router/<int:search_log_id>', core_views.DownloadRouterView.as_view(), name='download-router'), path('additional-form-router/<int:dataset_id>/<int:analysis_type_id>', core_views.AdditionalFormRouterView.as_view(), name='additional-form-router'), path('base-search/', core_views.BaseSearchView.as_view(), name='base-search'), path('base-download/<int:search_log_id>', core_views.BaseDownloadView.as_view(), name='base-download'), path('save-search/', core_views.save_search, name='save-search'), path('saved-search-list/', core_views.SavedSearchListView.as_view(), name='saved-search-list'), path('retrieve-saved-search/<int:saved_search_id>', core_views.RetrieveSavedSearchView.as_view(), name='retrieve-saved-search'), path('core-document-view/<int:dataset_id>/<document_es_id>/', core_views.BaseDocumentView.as_view(), name='core-document-view'), path('core-document-review-create/<int:dataset_id>/<document_es_id>/', core_views.DocumentReviewCreateView.as_view(), name='core-document-review-create'), path('core-document-review-update/<int:dataset_id>/<int:document_review_id>/', core_views.DocumentReviewUpdateView.as_view(), name='core-document-review-update'), path('core-document-list/', core_views.DocumentReviewListView.as_view(), name='core-document-list'), )

0

fa98caab9a7b0286b7b7c07c740bcf0da51f0601

203

py

Python

days/04-06-collections/D5/sorting.py

angersa/100daysofcode-with-python-course

4b7a28604214a49faf243c543f67bc8dc3eab349

[ "MIT" ]

null

days/04-06-collections/D5/sorting.py

angersa/100daysofcode-with-python-course

4b7a28604214a49faf243c543f67bc8dc3eab349

[ "MIT" ]

null

days/04-06-collections/D5/sorting.py

angersa/100daysofcode-with-python-course

4b7a28604214a49faf243c543f67bc8dc3eab349

[ "MIT" ]

null

disordered = {(10, 5): 'b', (3, 10): 'a', (5, 2): 'c'} # sort keys, then get values from original - fast sorted_list = sorted(disordered.items(), key=lambda x: x[0][1], reverse=True) print(sorted_list)

33.833333

77

0.640394

disordered = {(10, 5): 'b', (3, 10): 'a', (5, 2): 'c'} # sort keys, then get values from original - fast sorted_list = sorted(disordered.items(), key=lambda x: x[0][1], reverse=True) print(sorted_list)

0

b5036c9d9c6977e05e22272804dea05480f37a6c

8,284

py

Python

ichnaea/api/locate/tests/test_result.py

mikiec84/ichnaea

ec223cefb788bb921c0e7f5f51bd3b20eae29edd

[ "Apache-2.0" ]

348

2015-01-13T11:48:07.000Z

2022-03-31T08:33:07.000Z

ichnaea/api/locate/tests/test_result.py

mikiec84/ichnaea

ec223cefb788bb921c0e7f5f51bd3b20eae29edd

[ "Apache-2.0" ]

1,274

2015-01-02T18:15:56.000Z

2022-03-23T15:29:08.000Z

ichnaea/api/locate/tests/test_result.py

mikiec84/ichnaea

ec223cefb788bb921c0e7f5f51bd3b20eae29edd

[ "Apache-2.0" ]

149

2015-01-04T21:15:07.000Z

2021-12-10T06:05:09.000Z

from ichnaea.api.locate.constants import DataAccuracy, DataSource from ichnaea.api.locate.query import Query from ichnaea.api.locate.result import ( Position, PositionResultList, Region, RegionResultList, Result, ResultList, ) from ichnaea.models import encode_mac from ichnaea.tests.factories import WifiShardFactory

33.538462

83

0.601762

from ichnaea.api.locate.constants import DataAccuracy, DataSource from ichnaea.api.locate.query import Query from ichnaea.api.locate.result import ( Position, PositionResultList, Region, RegionResultList, Result, ResultList, ) from ichnaea.models import encode_mac from ichnaea.tests.factories import WifiShardFactory class TestResult(object): def test_repr(self): result = Result(region_code="DE", lat=1.0) rep = repr(result) assert rep.startswith("Result") assert "DE" not in rep assert "1.0" not in rep def test_data_accuracy(self): assert Result().data_accuracy is DataAccuracy.none def test_used_networks(self): wifi = WifiShardFactory.build() network = ("wifi", encode_mac(wifi.mac), True) assert Result().used_networks == [] assert Result(used_networks=[network]).used_networks == [network] class TestPosition(object): def test_repr(self): position = Position(lat=1.0, lon=-1.1, accuracy=100.0, score=2.0) rep = repr(position) assert rep.startswith("Position") assert "1.0" in rep assert "-1.1" in rep assert "100.0" in rep assert position.score == 2.0 def test_json(self): assert Position().json() == {"position": {"source": "query"}} assert Position(lat=1.0, lon=1.0, accuracy=2.0).json() == { "position": { "latitude": 1.0, "longitude": 1.0, "accuracy": 2.0, "source": "query", } } def test_data_accuracy(self): def check(accuracy, expected): pos = Position(lat=1.0, lon=1.0, accuracy=accuracy) assert pos.data_accuracy is expected check(None, DataAccuracy.none) check(0.0, DataAccuracy.high) check(100, DataAccuracy.high) check(20000.0, DataAccuracy.medium) check(10 ** 6, DataAccuracy.low) class TestRegion(object): def test_repr(self): region = Region( region_code="DE", region_name="Germany", accuracy=100.0, score=2.0 ) rep = repr(region) assert rep.startswith("Region") assert "DE" in rep assert "Germany" in rep assert region.score == 2.0 def test_data_accuracy(self): assert Region().data_accuracy is DataAccuracy.none region = Region(region_code="DE", region_name="Germany", accuracy=100000.0) assert region.data_accuracy is DataAccuracy.low region = Region(region_code="VA", region_name="Holy See", accuracy=1000.0) assert region.data_accuracy is DataAccuracy.medium class TestResultList(object): def _make_result(self): return Position( lat=1.0, lon=1.0, accuracy=10.0, score=0.5, source=DataSource.internal ) def test_init(self): results = ResultList(self._make_result()) assert len(results) == 1 def test_repr(self): results = ResultList([self._make_result(), self._make_result()]) rep = repr(results) assert rep.startswith("ResultList:") assert "Position<" in rep assert "lat:1.0" in rep assert "lon:1.0" in rep assert "accuracy:10.0" in rep assert "score:0.5" in rep def test_add(self): results = ResultList() results.add(self._make_result()) assert len(results) == 1 def test_add_many(self): results = ResultList(self._make_result()) results.add((self._make_result(), self._make_result())) assert len(results) == 3 def test_len(self): results = ResultList() results.add(self._make_result()) results.add(self._make_result()) assert len(results) == 2 def test_getitem(self): result = self._make_result() results = ResultList() results.add(result) assert results[0] == result def test_iterable(self): result = self._make_result() results = ResultList() results.add(result) results.add(result) for res in results: assert res == result class TestPositionResultList(object): def test_repr(self): assert repr(PositionResultList()).startswith("PositionResultList:") def test_best_empty(self): assert PositionResultList().best() is None def test_best(self): gb1 = Position(lat=51.5, lon=-0.1, accuracy=100000.0, score=0.6) gb2 = Position(lat=51.5002, lon=-0.1, accuracy=10000.0, score=1.5) gb3 = Position(lat=51.7, lon=-0.1, accuracy=1000.0, score=5.0) bt1 = Position(lat=27.5002, lon=90.5, accuracy=1000.0, score=0.5) bt2 = Position(lat=27.5, lon=90.5, accuracy=2000.0, score=2.0) bt3 = Position(lat=27.7, lon=90.7, accuracy=500.0, score=5.0) bt4 = Position(lat=27.9, lon=90.7, accuracy=300.0, score=5.0) # single result works assert PositionResultList([gb1]).best().lat == 51.5 # the lowest accuracy result from the best cluster wins assert PositionResultList([bt1, bt2]).best().lat == 27.5002 assert PositionResultList([gb1, bt2]).best().lat == 27.5 assert PositionResultList([gb1, gb2, bt2]).best().lat == 51.5002 assert PositionResultList([gb1, gb3, bt1, bt2]).best().lat == 51.7 assert PositionResultList([gb1, gb2, bt2, bt3]).best().lat == 27.7 # break tie by accuracy assert PositionResultList([gb3, bt3]).best().lat == 27.7 assert PositionResultList([bt3, bt4]).best().lat == 27.9 def test_satisfies(self): wifis = WifiShardFactory.build_batch(2) wifi_query = [{"macAddress": wifi.mac} for wifi in wifis] positions = PositionResultList( [ Position(lat=1.0, lon=1.0, accuracy=100.0, score=0.5), Position(lat=1.0, lon=1.0, accuracy=10000.0, score=0.6), ] ) query = Query(api_type="locate", wifi=wifi_query) assert positions.satisfies(query) def test_satisfies_empty(self): wifis = WifiShardFactory.build_batch(2) wifi_query = [{"macAddress": wifi.mac} for wifi in wifis] positions = PositionResultList() query = Query(api_type="locate", wifi=wifi_query) assert not positions.satisfies(query) def test_satisfies_fail(self): wifis = WifiShardFactory.build_batch(2) wifi_query = [{"macAddress": wifi.mac} for wifi in wifis] positions = PositionResultList( Position(lat=1.0, lon=1.0, accuracy=2500.0, score=2.0) ) query = Query(api_type="locate", wifi=wifi_query) assert not positions.satisfies(query) class TestRegionResultList(object): def test_repr(self): assert repr(RegionResultList()).startswith("RegionResultList:") def test_best_empty(self): assert RegionResultList().best() is None def test_best(self): us1 = Region( region_code="US", region_name="us", accuracy=200000.0, score=3.0, source=DataSource.geoip, ) us2 = Region( region_code="US", region_name="us", accuracy=200000.0, score=3.0, source=DataSource.geoip, ) gb1 = Region( region_code="GB", region_name="gb", accuracy=100000.0, score=5.0, source=DataSource.geoip, ) gb2 = Region( region_code="GB", region_name="gb", accuracy=100000.0, score=3.0, source=DataSource.geoip, ) # highest combined score wins assert RegionResultList([us1, gb1]).best().region_code == "GB" assert RegionResultList([us1, gb1, us2]).best().region_code == "US" # break tie by accuracy assert RegionResultList([us1, gb2]).best().region_code == "US" def test_satisfies(self): regions = RegionResultList( Region(region_code="DE", region_name="Germany", accuracy=100000.0) ) assert regions.satisfies(Query()) def test_satisfies_fail(self): assert not RegionResultList().satisfies(Query())

7,023

52

861

d40d1402ab5ddaccc60f54e6b0bffbc87134f18a

16,587

py

Python

vcstools/beam_calc.py

cplee1/vcstools_chris_duplicate

e929e01d886e6ce8c113af3b02c2590b441daa03

[ "AFL-3.0" ]

5

2020-07-01T13:18:53.000Z

2022-03-04T20:54:14.000Z

vcstools/beam_calc.py

cplee1/vcstools_chris_duplicate

e929e01d886e6ce8c113af3b02c2590b441daa03

[ "AFL-3.0" ]

44

2019-10-19T00:13:55.000Z

2022-01-01T04:42:02.000Z

vcstools/beam_calc.py

cplee1/vcstools_chris_duplicate

e929e01d886e6ce8c113af3b02c2590b441daa03

[ "AFL-3.0" ]

6

2019-10-29T10:51:51.000Z

2022-03-04T20:54:28.000Z

import os import sys import numpy as np import math #MWA scripts from mwa_pb import primary_beam from vcstools.pointing_utils import sex2deg from vcstools.metadb_utils import mwa_alt_az_za, get_common_obs_metadata, getmeta import logging logger = logging.getLogger(__name__) def pixel_area(ra_min, ra_max, dec_min, dec_max): """ Calculate the area of a pixel on the sky from the pixel borders Parameters: ----------- ra_min: float The Right Acension minimum in degrees ra_max: float The Right Acension maximum in degrees dec_min: float The Declination minimum in degrees dec_max: float The Declination maximum in degrees Returns: -------- area: float Area of the pixel in square degrees """ return (180./math.pi) * (ra_max - ra_min) * (math.sin(math.radians(dec_max)) - math.sin(math.radians(dec_min))) def field_of_view(obsid, beam_meta_data=None, dur=None): """ Will find the field-of-view of the observation (including the drift) in square degrees. Parameters: ----------- obsid: int The observation ID beam_meta_data: list OPTIONAL - the list of common metadata from vcstools.metadb_utils.get_common_obs_metadata. By default will download the metadata for you dur: int OPTIONAL - Duration of observation to calculate for in seconds By default will use the entire observation duration Returns: -------- area: float The field-of-view of the observation in square degrees """ if beam_meta_data is None: beam_meta_data = get_common_obs_metadata(obsid) if dur is None: dt = 296 else: dt = 100 # Change the dur to the inpur dur obsid, ra, dec, _, delays, centrefreq, channels = beam_meta_data beam_meta_data = [obsid, ra, dec, dur, delays, centrefreq, channels] # Make a pixel for each degree on the sky names_ra_dec = [] for ra in range(0,360): for dec in range(-90,90): names_ra_dec.append(["sky_pos", ra+0.5, dec+0.5]) # Get tile beam power for all pixels sky_powers = get_beam_power_over_time(beam_meta_data, names_ra_dec, degrees=True, dt=dt) # Find the maximum power over all time max_sky_powers = [] for pixel_power in sky_powers: temp_power = 0. for time_power in pixel_power: if time_power[0] > temp_power: temp_power = time_power[0] max_sky_powers.append(temp_power) # Find all pixels greater than the half power point and sum their area half_power_point = max(max_sky_powers) / 2 i = 0 area_sum = 0 for ra in range(0,360): for dec in range(-90,90): if max_sky_powers[i] > half_power_point: area_sum = area_sum + pixel_area(ra, ra+1, dec, dec+1) i = i + 1 return area_sum def beam_enter_exit(powers, duration, dt=296, min_power=0.3): """ Calculates when the source enters and exits the beam beam_enter_exit(min_power, powers, imax, dt): powers: list of powers fo the duration every dt and freq powers[times][freqs] dt: the time interval of how often powers are calculated duration: duration of the observation according to the metadata in seconds min_power: zenith normalised power cut off """ from scipy.interpolate import UnivariateSpline time_steps = np.array(range(0, duration, dt), dtype=float) #For each time step record the min power so even if the source is in #one freq channel it's recorded powers_freq_min = [] for p in powers: powers_freq_min.append(float(min(p) - min_power)) if min(powers_freq_min) > 0.: enter_beam = 0. exit_beam = 1. else: powers_freq_min = np.array(powers_freq_min) logger.debug("time_steps: {}".format(time_steps)) logger.debug("powers: {}".format(powers_freq_min)) try: spline = UnivariateSpline(time_steps, powers_freq_min , s=0.) except: return None, None if len(spline.roots()) == 2: enter_beam, exit_beam = spline.roots() enter_beam /= duration exit_beam /= duration elif len(spline.roots()) == 1: if powers_freq_min[0] > powers_freq_min[-1]: #power declines so starts in beem then exits enter_beam = 0. exit_beam = spline.roots()[0]/duration else: enter_beam = spline.roots()[0]/duration exit_beam = 1. else: enter_beam = 0. exit_beam = 1. return enter_beam, exit_beam def get_beam_power_over_time(beam_meta_data, names_ra_dec, dt=296, centeronly=True, verbose=False, option='analytic', degrees=False, start_time=0): """ Calulates the power (gain at coordinate/gain at zenith) for each source over time. get_beam_power_over_time(beam_meta_data, names_ra_dec, dt=296, centeronly=True, verbose=False, option = 'analytic') Args: beam_meta_data: [obsid,ra, dec, time, delays,centrefreq, channels] obsid metadata obtained from meta.get_common_obs_metadata names_ra_dec: and array in the format [[source_name, RAJ, DecJ]] dt: time step in seconds for power calculations (default 296) centeronly: only calculates for the centre frequency (default True) verbose: prints extra data to (default False) option: primary beam model [analytic, advanced, full_EE] start_time: the time in seconds from the begining of the observation to start calculating at """ obsid, _, _, time, delays, centrefreq, channels = beam_meta_data names_ra_dec = np.array(names_ra_dec) logger.info("Calculating beam power for OBS ID: {0}".format(obsid)) starttimes=np.arange(start_time,time+start_time,dt) stoptimes=starttimes+dt stoptimes[stoptimes>time]=time Ntimes=len(starttimes) midtimes=float(obsid)+0.5*(starttimes+stoptimes) if not centeronly: PowersX=np.zeros((len(names_ra_dec), Ntimes, len(channels))) PowersY=np.zeros((len(names_ra_dec), Ntimes, len(channels))) # in Hz frequencies=np.array(channels)*1.28e6 else: PowersX=np.zeros((len(names_ra_dec), Ntimes,1)) PowersY=np.zeros((len(names_ra_dec), Ntimes,1)) if centrefreq > 1e6: logger.warning("centrefreq is greater than 1e6, assuming input with units of Hz.") frequencies=np.array([centrefreq]) else: frequencies=np.array([centrefreq])*1e6 if degrees: RAs = np.array(names_ra_dec[:,1],dtype=float) Decs = np.array(names_ra_dec[:,2],dtype=float) else: RAs, Decs = sex2deg(names_ra_dec[:,1],names_ra_dec[:,2]) if len(RAs)==0: sys.stderr.write('Must supply >=1 source positions\n') return None if not len(RAs)==len(Decs): sys.stderr.write('Must supply equal numbers of RAs and Decs\n') return None if verbose is False: #Supress print statements of the primary beam model functions sys.stdout = open(os.devnull, 'w') for itime in range(Ntimes): # this differ's from the previous ephem_utils method by 0.1 degrees _, Azs, Zas = mwa_alt_az_za(midtimes[itime], ra=RAs, dec=Decs, degrees=True) # go from altitude to zenith angle theta = np.radians(Zas) phi = np.radians(Azs) for ifreq in range(len(frequencies)): #Decide on beam model if option == 'analytic': rX,rY=primary_beam.MWA_Tile_analytic(theta, phi, freq=frequencies[ifreq], delays=delays, zenithnorm=True, power=True) elif option == 'advanced': rX,rY=primary_beam.MWA_Tile_advanced(theta, phi, freq=frequencies[ifreq], delays=delays, zenithnorm=True, power=True) elif option == 'full_EE': rX,rY=primary_beam.MWA_Tile_full_EE(theta, phi, freq=frequencies[ifreq], delays=delays, zenithnorm=True, power=True) PowersX[:,itime,ifreq]=rX PowersY[:,itime,ifreq]=rY if verbose is False: sys.stdout = sys.__stdout__ Powers=0.5*(PowersX+PowersY) return Powers def find_sources_in_obs(obsid_list, names_ra_dec, obs_for_source=False, dt_input=100, beam='analytic', min_power=0.3, cal_check=False, all_volt=False, degrees_check=False, metadata_list=None): """ Either creates text files for each MWA obs ID of each source within it or a text file for each source with each MWA obs is that the source is in. Args: obsid_list: list of MWA obs IDs names_ra_dec: [[source_name, ra, dec]] dt: the time step in seconds to do power calculations beam: beam simulation type ['analytic', 'advanced', 'full_EE'] min_power: if above the minium power assumes it's in the beam cal_check: checks the MWA pulsar database if there is a calibration for the obsid all_volt: Use all voltages observations including some inital test data with incorrect formats degrees_check: if false ra and dec is in hms, if true in degrees Output [output_data, obsid_meta]: output_data: The format of output_data is dependant on obs_for_source. If obs_for_source is True: output_data = {jname:[[obsid, duration, enter, exit, max_power], [obsid, duration, enter, exit, max_power]]} If obs_for_source is False: ouput_data = {obsid:[[jname, enter, exit, max_power], [jname, enter, exit, max_power]]} obsid_meta: a list of the output of get_common_obs_metadata for each obsid """ #prepares metadata calls and calculates power powers = [] #powers[obsid][source][time][freq] obsid_meta = [] obsid_to_remove = [] for i, obsid in enumerate(obsid_list): if metadata_list: beam_meta_data, _ = metadata_list[i] else: beam_meta_data = get_common_obs_metadata(obsid) #beam_meta_data = obsid,ra_obs,dec_obs,time_obs,delays,centrefreq,channels if dt_input * 4 > beam_meta_data[3]: # If the observation time is very short then a smaller dt time is required # to get enough ower imformation dt = int(beam_meta_data[3] / 4.) else: dt = dt_input logger.debug("obsid: {0}, time_obs {1} s, dt {2} s".format(obsid, beam_meta_data[3], dt)) # Perform the file meta data call files_meta_data = getmeta(service='data_files', params={'obs_id':obsid, 'nocache':1}) if files_meta_data is None: logger.warning("No file metadata data found for obsid {}. Skipping".format(obsid)) obsid_to_remove.append(obsid) continue # Check raw voltage files raw_available = False raw_deleted = False for file_name in files_meta_data.keys(): if file_name.endswith('dat'): deleted = files_meta_data[file_name]['deleted'] if deleted: raw_deleted = True else: raw_available = True # Check combined voltage tar files comb_available = False comb_deleted = False for file_name in files_meta_data.keys(): if file_name.endswith('tar'): deleted = files_meta_data[file_name]['deleted'] if deleted: comb_deleted = True else: comb_available = True if raw_available or comb_available or all_volt: powers.append(get_beam_power_over_time(beam_meta_data, names_ra_dec, dt=dt, centeronly=True, verbose=False, option=beam, degrees=degrees_check)) obsid_meta.append(beam_meta_data) elif raw_deleted and comb_deleted: logger.warning('Raw and combined voltage files deleted for {}'.format(obsid)) obsid_to_remove.append(obsid) elif raw_deleted: logger.warning('Raw voltage files deleted for {}'.format(obsid)) obsid_to_remove.append(obsid) elif comb_deleted: logger.warning('Combined voltage files deleted for {}'.format(obsid)) obsid_to_remove.append(obsid) else: logger.warning('No raw or combined voltage files for {}'.format(obsid)) obsid_to_remove.append(obsid) for otr in obsid_to_remove: obsid_list.remove(otr) #chooses whether to list the source in each obs or the obs for each source output_data = {} if obs_for_source: for sn, source in enumerate(names_ra_dec): source_data = [] for on, obsid in enumerate(obsid_list): source_ob_power = powers[on][sn] if max(source_ob_power) > min_power: duration = obsid_meta[on][3] centre_freq = obsid_meta[on][5] #MHz channels = obsid_meta[on][6] bandwidth = (channels[-1] - channels[0] + 1.)*1.28 #MHz logger.debug("Running beam_enter_exit on obsid: {}".format(obsid)) enter_beam, exit_beam = beam_enter_exit(source_ob_power,duration, dt=dt, min_power=min_power) if enter_beam is not None: source_data.append([obsid, duration, enter_beam, exit_beam, max(source_ob_power)[0], centre_freq, bandwidth]) # For each source make a dictionary key that contains a list of # lists of the data for each obsid output_data[source[0]] = source_data else: #output a list of sorces for each obs for on, obsid in enumerate(obsid_list): duration = obsid_meta[on][3] obsid_data = [] for sn, source in enumerate(names_ra_dec): source_ob_power = powers[on][sn] if max(source_ob_power) > min_power: enter_beam, exit_beam = beam_enter_exit(source_ob_power, duration, dt=dt, min_power=min_power) obsid_data.append([source[0], enter_beam, exit_beam, max(source_ob_power)[0]]) # For each obsid make a dictionary key that contains a list of # lists of the data for each source/pulsar output_data[obsid] = obsid_data return output_data, obsid_meta

40.555012

115

0.5816

import os import sys import numpy as np import math #MWA scripts from mwa_pb import primary_beam from vcstools.pointing_utils import sex2deg from vcstools.metadb_utils import mwa_alt_az_za, get_common_obs_metadata, getmeta import logging logger = logging.getLogger(__name__) def pixel_area(ra_min, ra_max, dec_min, dec_max): """ Calculate the area of a pixel on the sky from the pixel borders Parameters: ----------- ra_min: float The Right Acension minimum in degrees ra_max: float The Right Acension maximum in degrees dec_min: float The Declination minimum in degrees dec_max: float The Declination maximum in degrees Returns: -------- area: float Area of the pixel in square degrees """ return (180./math.pi) * (ra_max - ra_min) * (math.sin(math.radians(dec_max)) - math.sin(math.radians(dec_min))) def field_of_view(obsid, beam_meta_data=None, dur=None): """ Will find the field-of-view of the observation (including the drift) in square degrees. Parameters: ----------- obsid: int The observation ID beam_meta_data: list OPTIONAL - the list of common metadata from vcstools.metadb_utils.get_common_obs_metadata. By default will download the metadata for you dur: int OPTIONAL - Duration of observation to calculate for in seconds By default will use the entire observation duration Returns: -------- area: float The field-of-view of the observation in square degrees """ if beam_meta_data is None: beam_meta_data = get_common_obs_metadata(obsid) if dur is None: dt = 296 else: dt = 100 # Change the dur to the inpur dur obsid, ra, dec, _, delays, centrefreq, channels = beam_meta_data beam_meta_data = [obsid, ra, dec, dur, delays, centrefreq, channels] # Make a pixel for each degree on the sky names_ra_dec = [] for ra in range(0,360): for dec in range(-90,90): names_ra_dec.append(["sky_pos", ra+0.5, dec+0.5]) # Get tile beam power for all pixels sky_powers = get_beam_power_over_time(beam_meta_data, names_ra_dec, degrees=True, dt=dt) # Find the maximum power over all time max_sky_powers = [] for pixel_power in sky_powers: temp_power = 0. for time_power in pixel_power: if time_power[0] > temp_power: temp_power = time_power[0] max_sky_powers.append(temp_power) # Find all pixels greater than the half power point and sum their area half_power_point = max(max_sky_powers) / 2 i = 0 area_sum = 0 for ra in range(0,360): for dec in range(-90,90): if max_sky_powers[i] > half_power_point: area_sum = area_sum + pixel_area(ra, ra+1, dec, dec+1) i = i + 1 return area_sum def from_power_to_gain(powers, cfreq, n, coh=True): from astropy.constants import c,k_B from math import sqrt obswl = c.value/cfreq #for coherent if coh: coeff = obswl**2*16*n/(4*np.pi*k_B.value) else: coeff = obswl**2*16*sqrt(n)/(4*np.pi*k_B.value) logger.debug("Wavelength {} m".format(obswl)) logger.debug("Gain coefficient: {}".format(coeff)) SI_to_Jy = 1e-26 return (powers*coeff)*SI_to_Jy def get_Trec(tab, obsfreq): Trec = 0.0 for r in range(len(tab)-1): if tab[r][0]==obsfreq: Trec = tab[r][1] elif tab[r][0] < obsfreq < tab[r+1][0]: Trec = ((tab[r][1] + tab[r+1][1])/2) if Trec == 0.0: logger.debug("ERROR getting Trec") return Trec def beam_enter_exit(powers, duration, dt=296, min_power=0.3): """ Calculates when the source enters and exits the beam beam_enter_exit(min_power, powers, imax, dt): powers: list of powers fo the duration every dt and freq powers[times][freqs] dt: the time interval of how often powers are calculated duration: duration of the observation according to the metadata in seconds min_power: zenith normalised power cut off """ from scipy.interpolate import UnivariateSpline time_steps = np.array(range(0, duration, dt), dtype=float) #For each time step record the min power so even if the source is in #one freq channel it's recorded powers_freq_min = [] for p in powers: powers_freq_min.append(float(min(p) - min_power)) if min(powers_freq_min) > 0.: enter_beam = 0. exit_beam = 1. else: powers_freq_min = np.array(powers_freq_min) logger.debug("time_steps: {}".format(time_steps)) logger.debug("powers: {}".format(powers_freq_min)) try: spline = UnivariateSpline(time_steps, powers_freq_min , s=0.) except: return None, None if len(spline.roots()) == 2: enter_beam, exit_beam = spline.roots() enter_beam /= duration exit_beam /= duration elif len(spline.roots()) == 1: if powers_freq_min[0] > powers_freq_min[-1]: #power declines so starts in beem then exits enter_beam = 0. exit_beam = spline.roots()[0]/duration else: enter_beam = spline.roots()[0]/duration exit_beam = 1. else: enter_beam = 0. exit_beam = 1. return enter_beam, exit_beam def get_beam_power_over_time(beam_meta_data, names_ra_dec, dt=296, centeronly=True, verbose=False, option='analytic', degrees=False, start_time=0): """ Calulates the power (gain at coordinate/gain at zenith) for each source over time. get_beam_power_over_time(beam_meta_data, names_ra_dec, dt=296, centeronly=True, verbose=False, option = 'analytic') Args: beam_meta_data: [obsid,ra, dec, time, delays,centrefreq, channels] obsid metadata obtained from meta.get_common_obs_metadata names_ra_dec: and array in the format [[source_name, RAJ, DecJ]] dt: time step in seconds for power calculations (default 296) centeronly: only calculates for the centre frequency (default True) verbose: prints extra data to (default False) option: primary beam model [analytic, advanced, full_EE] start_time: the time in seconds from the begining of the observation to start calculating at """ obsid, _, _, time, delays, centrefreq, channels = beam_meta_data names_ra_dec = np.array(names_ra_dec) logger.info("Calculating beam power for OBS ID: {0}".format(obsid)) starttimes=np.arange(start_time,time+start_time,dt) stoptimes=starttimes+dt stoptimes[stoptimes>time]=time Ntimes=len(starttimes) midtimes=float(obsid)+0.5*(starttimes+stoptimes) if not centeronly: PowersX=np.zeros((len(names_ra_dec), Ntimes, len(channels))) PowersY=np.zeros((len(names_ra_dec), Ntimes, len(channels))) # in Hz frequencies=np.array(channels)*1.28e6 else: PowersX=np.zeros((len(names_ra_dec), Ntimes,1)) PowersY=np.zeros((len(names_ra_dec), Ntimes,1)) if centrefreq > 1e6: logger.warning("centrefreq is greater than 1e6, assuming input with units of Hz.") frequencies=np.array([centrefreq]) else: frequencies=np.array([centrefreq])*1e6 if degrees: RAs = np.array(names_ra_dec[:,1],dtype=float) Decs = np.array(names_ra_dec[:,2],dtype=float) else: RAs, Decs = sex2deg(names_ra_dec[:,1],names_ra_dec[:,2]) if len(RAs)==0: sys.stderr.write('Must supply >=1 source positions\n') return None if not len(RAs)==len(Decs): sys.stderr.write('Must supply equal numbers of RAs and Decs\n') return None if verbose is False: #Supress print statements of the primary beam model functions sys.stdout = open(os.devnull, 'w') for itime in range(Ntimes): # this differ's from the previous ephem_utils method by 0.1 degrees _, Azs, Zas = mwa_alt_az_za(midtimes[itime], ra=RAs, dec=Decs, degrees=True) # go from altitude to zenith angle theta = np.radians(Zas) phi = np.radians(Azs) for ifreq in range(len(frequencies)): #Decide on beam model if option == 'analytic': rX,rY=primary_beam.MWA_Tile_analytic(theta, phi, freq=frequencies[ifreq], delays=delays, zenithnorm=True, power=True) elif option == 'advanced': rX,rY=primary_beam.MWA_Tile_advanced(theta, phi, freq=frequencies[ifreq], delays=delays, zenithnorm=True, power=True) elif option == 'full_EE': rX,rY=primary_beam.MWA_Tile_full_EE(theta, phi, freq=frequencies[ifreq], delays=delays, zenithnorm=True, power=True) PowersX[:,itime,ifreq]=rX PowersY[:,itime,ifreq]=rY if verbose is False: sys.stdout = sys.__stdout__ Powers=0.5*(PowersX+PowersY) return Powers def find_sources_in_obs(obsid_list, names_ra_dec, obs_for_source=False, dt_input=100, beam='analytic', min_power=0.3, cal_check=False, all_volt=False, degrees_check=False, metadata_list=None): """ Either creates text files for each MWA obs ID of each source within it or a text file for each source with each MWA obs is that the source is in. Args: obsid_list: list of MWA obs IDs names_ra_dec: [[source_name, ra, dec]] dt: the time step in seconds to do power calculations beam: beam simulation type ['analytic', 'advanced', 'full_EE'] min_power: if above the minium power assumes it's in the beam cal_check: checks the MWA pulsar database if there is a calibration for the obsid all_volt: Use all voltages observations including some inital test data with incorrect formats degrees_check: if false ra and dec is in hms, if true in degrees Output [output_data, obsid_meta]: output_data: The format of output_data is dependant on obs_for_source. If obs_for_source is True: output_data = {jname:[[obsid, duration, enter, exit, max_power], [obsid, duration, enter, exit, max_power]]} If obs_for_source is False: ouput_data = {obsid:[[jname, enter, exit, max_power], [jname, enter, exit, max_power]]} obsid_meta: a list of the output of get_common_obs_metadata for each obsid """ #prepares metadata calls and calculates power powers = [] #powers[obsid][source][time][freq] obsid_meta = [] obsid_to_remove = [] for i, obsid in enumerate(obsid_list): if metadata_list: beam_meta_data, _ = metadata_list[i] else: beam_meta_data = get_common_obs_metadata(obsid) #beam_meta_data = obsid,ra_obs,dec_obs,time_obs,delays,centrefreq,channels if dt_input * 4 > beam_meta_data[3]: # If the observation time is very short then a smaller dt time is required # to get enough ower imformation dt = int(beam_meta_data[3] / 4.) else: dt = dt_input logger.debug("obsid: {0}, time_obs {1} s, dt {2} s".format(obsid, beam_meta_data[3], dt)) # Perform the file meta data call files_meta_data = getmeta(service='data_files', params={'obs_id':obsid, 'nocache':1}) if files_meta_data is None: logger.warning("No file metadata data found for obsid {}. Skipping".format(obsid)) obsid_to_remove.append(obsid) continue # Check raw voltage files raw_available = False raw_deleted = False for file_name in files_meta_data.keys(): if file_name.endswith('dat'): deleted = files_meta_data[file_name]['deleted'] if deleted: raw_deleted = True else: raw_available = True # Check combined voltage tar files comb_available = False comb_deleted = False for file_name in files_meta_data.keys(): if file_name.endswith('tar'): deleted = files_meta_data[file_name]['deleted'] if deleted: comb_deleted = True else: comb_available = True if raw_available or comb_available or all_volt: powers.append(get_beam_power_over_time(beam_meta_data, names_ra_dec, dt=dt, centeronly=True, verbose=False, option=beam, degrees=degrees_check)) obsid_meta.append(beam_meta_data) elif raw_deleted and comb_deleted: logger.warning('Raw and combined voltage files deleted for {}'.format(obsid)) obsid_to_remove.append(obsid) elif raw_deleted: logger.warning('Raw voltage files deleted for {}'.format(obsid)) obsid_to_remove.append(obsid) elif comb_deleted: logger.warning('Combined voltage files deleted for {}'.format(obsid)) obsid_to_remove.append(obsid) else: logger.warning('No raw or combined voltage files for {}'.format(obsid)) obsid_to_remove.append(obsid) for otr in obsid_to_remove: obsid_list.remove(otr) #chooses whether to list the source in each obs or the obs for each source output_data = {} if obs_for_source: for sn, source in enumerate(names_ra_dec): source_data = [] for on, obsid in enumerate(obsid_list): source_ob_power = powers[on][sn] if max(source_ob_power) > min_power: duration = obsid_meta[on][3] centre_freq = obsid_meta[on][5] #MHz channels = obsid_meta[on][6] bandwidth = (channels[-1] - channels[0] + 1.)*1.28 #MHz logger.debug("Running beam_enter_exit on obsid: {}".format(obsid)) enter_beam, exit_beam = beam_enter_exit(source_ob_power,duration, dt=dt, min_power=min_power) if enter_beam is not None: source_data.append([obsid, duration, enter_beam, exit_beam, max(source_ob_power)[0], centre_freq, bandwidth]) # For each source make a dictionary key that contains a list of # lists of the data for each obsid output_data[source[0]] = source_data else: #output a list of sorces for each obs for on, obsid in enumerate(obsid_list): duration = obsid_meta[on][3] obsid_data = [] for sn, source in enumerate(names_ra_dec): source_ob_power = powers[on][sn] if max(source_ob_power) > min_power: enter_beam, exit_beam = beam_enter_exit(source_ob_power, duration, dt=dt, min_power=min_power) obsid_data.append([source[0], enter_beam, exit_beam, max(source_ob_power)[0]]) # For each obsid make a dictionary key that contains a list of # lists of the data for each source/pulsar output_data[obsid] = obsid_data return output_data, obsid_meta

719

0

46

be10b0d724e03294d196bc011b322a0131e5d9cc

668

py

Python

sample_list.py

xuanyuyt/libfacedetection

a2576ef7c5f35dd8bc64227b60948da8f4fd5d5e

[ "BSD-3-Clause" ]

null

sample_list.py

xuanyuyt/libfacedetection

a2576ef7c5f35dd8bc64227b60948da8f4fd5d5e

[ "BSD-3-Clause" ]

null

sample_list.py

xuanyuyt/libfacedetection

a2576ef7c5f35dd8bc64227b60948da8f4fd5d5e

[ "BSD-3-Clause" ]

null

# -*- coding=utf-8 -*- import os if __name__ == '__main__': # ================================================================== # # Select Sample List # # ================================================================== # output = open('ALL.txt', 'w') with open('Path_Xmls.txt', 'r') as fp: for oneFile in fp: xmlname = oneFile.strip() jpgname = xmlname.replace('.xml', '.jpg').replace('Annotations', 'JPEGImages') output.write(jpgname) output.write('\t') output.write(xmlname) output.write('\n') output.close()

37.111111

90

0.378743

# -*- coding=utf-8 -*- import os if __name__ == '__main__': # ================================================================== # # Select Sample List # # ================================================================== # output = open('ALL.txt', 'w') with open('Path_Xmls.txt', 'r') as fp: for oneFile in fp: xmlname = oneFile.strip() jpgname = xmlname.replace('.xml', '.jpg').replace('Annotations', 'JPEGImages') output.write(jpgname) output.write('\t') output.write(xmlname) output.write('\n') output.close()

0

cea272597e7c5a179183dd81f275ae2984ba6975

1,675

py

Python

superb/urls.py

gheyderov/E-commerce-website

9a87e8e6658a69fb017bdc3b36d6dc5417e3124e

[ "MIT" ]

null

superb/urls.py

gheyderov/E-commerce-website

9a87e8e6658a69fb017bdc3b36d6dc5417e3124e

[ "MIT" ]

null

superb/urls.py

gheyderov/E-commerce-website

9a87e8e6658a69fb017bdc3b36d6dc5417e3124e

[ "MIT" ]

null

"""superb URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/3.2/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.urls import path, include from django.conf.urls.static import static from django.conf import settings from rest_framework_simplejwt.views import ( TokenObtainPairView, TokenRefreshView, ) urlpatterns = [ path ('admin/', admin.site.urls), path('ckeditor/', include('ckeditor_uploader.urls')), path ('', include("core.urls")), path ('', include("blog.urls")), path ('', include("accounts.urls", namespace = "accounts")), path ('', include("order.urls", namespace="order")), path ('', include("products.urls")), path('api-auth/', include('rest_framework.urls')), path('api/', include('api.urls')), path('api/token/', TokenObtainPairView.as_view(), name='token_obtain_pair'), path('api/token/refresh/', TokenRefreshView.as_view(), name='token_refresh'), ] if settings.DEBUG: urlpatterns += static(settings.STATIC_URL, document_root = settings.STATIC_ROOT) urlpatterns += static(settings.MEDIA_URL, document_root = settings.MEDIA_ROOT)

37.222222

84

0.699701

"""superb URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/3.2/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.urls import path, include from django.conf.urls.static import static from django.conf import settings from rest_framework_simplejwt.views import ( TokenObtainPairView, TokenRefreshView, ) urlpatterns = [ path ('admin/', admin.site.urls), path('ckeditor/', include('ckeditor_uploader.urls')), path ('', include("core.urls")), path ('', include("blog.urls")), path ('', include("accounts.urls", namespace = "accounts")), path ('', include("order.urls", namespace="order")), path ('', include("products.urls")), path('api-auth/', include('rest_framework.urls')), path('api/', include('api.urls')), path('api/token/', TokenObtainPairView.as_view(), name='token_obtain_pair'), path('api/token/refresh/', TokenRefreshView.as_view(), name='token_refresh'), ] if settings.DEBUG: urlpatterns += static(settings.STATIC_URL, document_root = settings.STATIC_ROOT) urlpatterns += static(settings.MEDIA_URL, document_root = settings.MEDIA_ROOT)

0

e8aeb956c1e734978949a081f9e6a6d6823a2d71

164

py

Python

src/__main__.py

cesarabelfigueroa/FileSystem

fcd42f62ee406dbaf3180b0c15903c196c885e4a

[ "MIT" ]

null

src/__main__.py

cesarabelfigueroa/FileSystem

fcd42f62ee406dbaf3180b0c15903c196c885e4a

[ "MIT" ]

null

src/__main__.py

cesarabelfigueroa/FileSystem

fcd42f62ee406dbaf3180b0c15903c196c885e4a

[ "MIT" ]

null

from classes.Shell import Shell from classes.FileSystem import FileSystem main()

20.5

41

0.75

from classes.Shell import Shell from classes.FileSystem import FileSystem def main(): shell = Shell("./disk/Disk.bin") shell.createRoot() shell.execute() main()

61

0

23

539793bf8d49e145d5788dcd14ff3f0d24bf7a75

74

py

Python

amadeus/version.py

minjikarin/amadeus-python

14a004912ee8c36ee4fd79651ea1b23afe6b2a6e

[ "MIT" ]

null

amadeus/version.py

minjikarin/amadeus-python

14a004912ee8c36ee4fd79651ea1b23afe6b2a6e

[ "MIT" ]

null

amadeus/version.py

minjikarin/amadeus-python

14a004912ee8c36ee4fd79651ea1b23afe6b2a6e

[ "MIT" ]

null

version_info = (5, 3, 1) version = '.'.join(str(v) for v in version_info)

24.666667

48

0.648649

version_info = (5, 3, 1) version = '.'.join(str(v) for v in version_info)

0

9774458a9bbc1046d5b4bd5e8043fb960f7c9702

11,119

py

Python

Tests/varLib/instancer/names_test.py

odidev/fonttools

27b5f568f562971d7fbf64eeb027ea61e4939db4

[ "Apache-2.0", "MIT" ]

2,705

2016-09-27T10:02:12.000Z

2022-03-31T09:37:46.000Z

Tests/varLib/instancer/names_test.py

odidev/fonttools

27b5f568f562971d7fbf64eeb027ea61e4939db4

[ "Apache-2.0", "MIT" ]

1,599

2016-09-27T09:07:36.000Z

2022-03-31T23:04:51.000Z

Tests/varLib/instancer/names_test.py

odidev/fonttools

27b5f568f562971d7fbf64eeb027ea61e4939db4

[ "Apache-2.0", "MIT" ]

352

2016-10-07T04:18:15.000Z

2022-03-30T07:35:01.000Z

from fontTools.ttLib.tables import otTables from fontTools.otlLib.builder import buildStatTable from fontTools.varLib import instancer import pytest @pytest.mark.parametrize( "limits, expected, isNonRIBBI", [ # Regular ( {"wght": 400}, { (1, 3, 1, 0x409): "Test Variable Font", (2, 3, 1, 0x409): "Regular", (3, 3, 1, 0x409): "2.001;GOOG;TestVariableFont-Regular", (6, 3, 1, 0x409): "TestVariableFont-Regular", }, False, ), # Regular Normal (width axis Normal isn't included since it is elided) ( {"wght": 400, "wdth": 100}, { (1, 3, 1, 0x409): "Test Variable Font", (2, 3, 1, 0x409): "Regular", (3, 3, 1, 0x409): "2.001;GOOG;TestVariableFont-Regular", (6, 3, 1, 0x409): "TestVariableFont-Regular", }, False, ), # Black ( {"wght": 900}, { (1, 3, 1, 0x409): "Test Variable Font Black", (2, 3, 1, 0x409): "Regular", (3, 3, 1, 0x409): "2.001;GOOG;TestVariableFont-Black", (6, 3, 1, 0x409): "TestVariableFont-Black", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Black", }, True, ), # Thin ( {"wght": 100}, { (1, 3, 1, 0x409): "Test Variable Font Thin", (2, 3, 1, 0x409): "Regular", (3, 3, 1, 0x409): "2.001;GOOG;TestVariableFont-Thin", (6, 3, 1, 0x409): "TestVariableFont-Thin", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Thin", }, True, ), # Thin Condensed ( {"wght": 100, "wdth": 79}, { (1, 3, 1, 0x409): "Test Variable Font Thin Condensed", (2, 3, 1, 0x409): "Regular", (3, 3, 1, 0x409): "2.001;GOOG;TestVariableFont-ThinCondensed", (6, 3, 1, 0x409): "TestVariableFont-ThinCondensed", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Thin Condensed", }, True, ), # Condensed with unpinned weights ( {"wdth": 79, "wght": instancer.AxisRange(400, 900)}, { (1, 3, 1, 0x409): "Test Variable Font Condensed", (2, 3, 1, 0x409): "Regular", (3, 3, 1, 0x409): "2.001;GOOG;TestVariableFont-Condensed", (6, 3, 1, 0x409): "TestVariableFont-Condensed", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Condensed", }, True, ), ], ) @pytest.mark.parametrize( "limits, expected, isNonRIBBI", [ # Regular | Normal ( {"wght": 400}, { (1, 3, 1, 0x409): "Test Variable Font", (2, 3, 1, 0x409): "Normal", }, False, ), # Black | Negreta ( {"wght": 900}, { (1, 3, 1, 0x409): "Test Variable Font Negreta", (2, 3, 1, 0x409): "Normal", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Negreta", }, True, ), # Black Condensed | Negreta Zhuštěné ( {"wght": 900, "wdth": 79}, { (1, 3, 1, 0x409): "Test Variable Font Negreta Zhuštěné", (2, 3, 1, 0x409): "Normal", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Negreta Zhuštěné", }, True, ), ], ) @pytest.mark.parametrize( "limits, expected, isNonRIBBI", [ # Regular | Normal ( {"wght": 400}, { (1, 3, 1, 0x409): "Test Variable Font", (2, 3, 1, 0x409): "Italic", (6, 3, 1, 0x409): "TestVariableFont-Italic", }, False, ), # Black Condensed Italic ( {"wght": 900, "wdth": 79}, { (1, 3, 1, 0x409): "Test Variable Font Black Condensed", (2, 3, 1, 0x409): "Italic", (6, 3, 1, 0x409): "TestVariableFont-BlackCondensedItalic", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Black Condensed Italic", }, True, ), ], )

34.424149

88

0.559133

from fontTools.ttLib.tables import otTables from fontTools.otlLib.builder import buildStatTable from fontTools.varLib import instancer import pytest def test_pruningUnusedNames(varfont): varNameIDs = instancer.names.getVariationNameIDs(varfont) assert varNameIDs == set(range(256, 297 + 1)) fvar = varfont["fvar"] stat = varfont["STAT"].table with instancer.names.pruningUnusedNames(varfont): del fvar.axes[0] # Weight (nameID=256) del fvar.instances[0] # Thin (nameID=258) del stat.DesignAxisRecord.Axis[0] # Weight (nameID=256) del stat.AxisValueArray.AxisValue[0] # Thin (nameID=258) assert not any(n for n in varfont["name"].names if n.nameID in {256, 258}) with instancer.names.pruningUnusedNames(varfont): del varfont["fvar"] del varfont["STAT"] assert not any(n for n in varfont["name"].names if n.nameID in varNameIDs) assert "ltag" not in varfont def _test_name_records(varfont, expected, isNonRIBBI, platforms=[0x409]): nametable = varfont["name"] font_names = { (r.nameID, r.platformID, r.platEncID, r.langID): r.toUnicode() for r in nametable.names } for k in expected: if k[-1] not in platforms: continue assert font_names[k] == expected[k] font_nameids = set(i[0] for i in font_names) if isNonRIBBI: assert 16 in font_nameids assert 17 in font_nameids if "fvar" not in varfont: assert 25 not in font_nameids @pytest.mark.parametrize( "limits, expected, isNonRIBBI", [ # Regular ( {"wght": 400}, { (1, 3, 1, 0x409): "Test Variable Font", (2, 3, 1, 0x409): "Regular", (3, 3, 1, 0x409): "2.001;GOOG;TestVariableFont-Regular", (6, 3, 1, 0x409): "TestVariableFont-Regular", }, False, ), # Regular Normal (width axis Normal isn't included since it is elided) ( {"wght": 400, "wdth": 100}, { (1, 3, 1, 0x409): "Test Variable Font", (2, 3, 1, 0x409): "Regular", (3, 3, 1, 0x409): "2.001;GOOG;TestVariableFont-Regular", (6, 3, 1, 0x409): "TestVariableFont-Regular", }, False, ), # Black ( {"wght": 900}, { (1, 3, 1, 0x409): "Test Variable Font Black", (2, 3, 1, 0x409): "Regular", (3, 3, 1, 0x409): "2.001;GOOG;TestVariableFont-Black", (6, 3, 1, 0x409): "TestVariableFont-Black", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Black", }, True, ), # Thin ( {"wght": 100}, { (1, 3, 1, 0x409): "Test Variable Font Thin", (2, 3, 1, 0x409): "Regular", (3, 3, 1, 0x409): "2.001;GOOG;TestVariableFont-Thin", (6, 3, 1, 0x409): "TestVariableFont-Thin", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Thin", }, True, ), # Thin Condensed ( {"wght": 100, "wdth": 79}, { (1, 3, 1, 0x409): "Test Variable Font Thin Condensed", (2, 3, 1, 0x409): "Regular", (3, 3, 1, 0x409): "2.001;GOOG;TestVariableFont-ThinCondensed", (6, 3, 1, 0x409): "TestVariableFont-ThinCondensed", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Thin Condensed", }, True, ), # Condensed with unpinned weights ( {"wdth": 79, "wght": instancer.AxisRange(400, 900)}, { (1, 3, 1, 0x409): "Test Variable Font Condensed", (2, 3, 1, 0x409): "Regular", (3, 3, 1, 0x409): "2.001;GOOG;TestVariableFont-Condensed", (6, 3, 1, 0x409): "TestVariableFont-Condensed", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Condensed", }, True, ), ], ) def test_updateNameTable_with_registered_axes_ribbi( varfont, limits, expected, isNonRIBBI ): instancer.names.updateNameTable(varfont, limits) _test_name_records(varfont, expected, isNonRIBBI) def test_updatetNameTable_axis_order(varfont): axes = [ dict( tag="wght", name="Weight", values=[ dict(value=400, name="Regular"), ], ), dict( tag="wdth", name="Width", values=[ dict(value=75, name="Condensed"), ], ), ] nametable = varfont["name"] buildStatTable(varfont, axes) instancer.names.updateNameTable(varfont, {"wdth": 75, "wght": 400}) assert nametable.getName(17, 3, 1, 0x409).toUnicode() == "Regular Condensed" # Swap the axes so the names get swapped axes[0], axes[1] = axes[1], axes[0] buildStatTable(varfont, axes) instancer.names.updateNameTable(varfont, {"wdth": 75, "wght": 400}) assert nametable.getName(17, 3, 1, 0x409).toUnicode() == "Condensed Regular" @pytest.mark.parametrize( "limits, expected, isNonRIBBI", [ # Regular | Normal ( {"wght": 400}, { (1, 3, 1, 0x409): "Test Variable Font", (2, 3, 1, 0x409): "Normal", }, False, ), # Black | Negreta ( {"wght": 900}, { (1, 3, 1, 0x409): "Test Variable Font Negreta", (2, 3, 1, 0x409): "Normal", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Negreta", }, True, ), # Black Condensed | Negreta Zhuštěné ( {"wght": 900, "wdth": 79}, { (1, 3, 1, 0x409): "Test Variable Font Negreta Zhuštěné", (2, 3, 1, 0x409): "Normal", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Negreta Zhuštěné", }, True, ), ], ) def test_updateNameTable_with_multilingual_names(varfont, limits, expected, isNonRIBBI): name = varfont["name"] # langID 0x405 is the Czech Windows langID name.setName("Test Variable Font", 1, 3, 1, 0x405) name.setName("Normal", 2, 3, 1, 0x405) name.setName("Normal", 261, 3, 1, 0x405) # nameID 261=Regular STAT entry name.setName("Negreta", 266, 3, 1, 0x405) # nameID 266=Black STAT entry name.setName("Zhuštěné", 279, 3, 1, 0x405) # nameID 279=Condensed STAT entry instancer.names.updateNameTable(varfont, limits) _test_name_records(varfont, expected, isNonRIBBI, platforms=[0x405]) def test_updateNameTable_missing_axisValues(varfont): with pytest.raises(ValueError, match="Cannot find Axis Values \['wght=200'\]"): instancer.names.updateNameTable(varfont, {"wght": 200}) def test_updateNameTable_missing_stat(varfont): del varfont["STAT"] with pytest.raises( ValueError, match="Cannot update name table since there is no STAT table." ): instancer.names.updateNameTable(varfont, {"wght": 400}) @pytest.mark.parametrize( "limits, expected, isNonRIBBI", [ # Regular | Normal ( {"wght": 400}, { (1, 3, 1, 0x409): "Test Variable Font", (2, 3, 1, 0x409): "Italic", (6, 3, 1, 0x409): "TestVariableFont-Italic", }, False, ), # Black Condensed Italic ( {"wght": 900, "wdth": 79}, { (1, 3, 1, 0x409): "Test Variable Font Black Condensed", (2, 3, 1, 0x409): "Italic", (6, 3, 1, 0x409): "TestVariableFont-BlackCondensedItalic", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Black Condensed Italic", }, True, ), ], ) def test_updateNameTable_vf_with_italic_attribute( varfont, limits, expected, isNonRIBBI ): font_link_axisValue = varfont["STAT"].table.AxisValueArray.AxisValue[4] # Unset ELIDABLE_AXIS_VALUE_NAME flag font_link_axisValue.Flags &= ~instancer.names.ELIDABLE_AXIS_VALUE_NAME font_link_axisValue.ValueNameID = 294 # Roman --> Italic instancer.names.updateNameTable(varfont, limits) _test_name_records(varfont, expected, isNonRIBBI) def test_updateNameTable_format4_axisValues(varfont): # format 4 axisValues should dominate the other axisValues stat = varfont["STAT"].table axisValue = otTables.AxisValue() axisValue.Format = 4 axisValue.Flags = 0 varfont["name"].setName("Dominant Value", 297, 3, 1, 0x409) axisValue.ValueNameID = 297 axisValue.AxisValueRecord = [] for tag, value in (("wght", 900), ("wdth", 79)): rec = otTables.AxisValueRecord() rec.AxisIndex = next( i for i, a in enumerate(stat.DesignAxisRecord.Axis) if a.AxisTag == tag ) rec.Value = value axisValue.AxisValueRecord.append(rec) stat.AxisValueArray.AxisValue.append(axisValue) instancer.names.updateNameTable(varfont, {"wdth": 79, "wght": 900}) expected = { (1, 3, 1, 0x409): "Test Variable Font Dominant Value", (2, 3, 1, 0x409): "Regular", (16, 3, 1, 0x409): "Test Variable Font", (17, 3, 1, 0x409): "Dominant Value", } _test_name_records(varfont, expected, isNonRIBBI=True) def test_updateNameTable_elided_axisValues(varfont): stat = varfont["STAT"].table # set ELIDABLE_AXIS_VALUE_NAME flag for all axisValues for axisValue in stat.AxisValueArray.AxisValue: axisValue.Flags |= instancer.names.ELIDABLE_AXIS_VALUE_NAME stat.ElidedFallbackNameID = 266 # Regular --> Black instancer.names.updateNameTable(varfont, {"wght": 400}) # Since all axis values are elided, the elided fallback name # must be used to construct the style names. Since we # changed it to Black, we need both a typoSubFamilyName and # the subFamilyName set so it conforms to the RIBBI model. expected = {(2, 3, 1, 0x409): "Regular", (17, 3, 1, 0x409): "Black"} _test_name_records(varfont, expected, isNonRIBBI=True) def test_updateNameTable_existing_subfamily_name_is_not_regular(varfont): # Check the subFamily name will be set to Regular when we update a name # table to a non-RIBBI style and the current subFamily name is a RIBBI # style which isn't Regular. varfont["name"].setName("Bold", 2, 3, 1, 0x409) # subFamily Regular --> Bold instancer.names.updateNameTable(varfont, {"wght": 100}) expected = {(2, 3, 1, 0x409): "Regular", (17, 3, 1, 0x409): "Thin"} _test_name_records(varfont, expected, isNonRIBBI=True)

6,104

0

250

516979c22c20cedc5cccce7806521c8edb663484

1,482

py

Python

tests/migrations/0001_initial.py

ixc/wagtailstreamforms

93bf352219608e803948cd28385566e0ca63fa7c

[ "MIT" ]

null

tests/migrations/0001_initial.py

ixc/wagtailstreamforms

93bf352219608e803948cd28385566e0ca63fa7c

[ "MIT" ]

null

tests/migrations/0001_initial.py

ixc/wagtailstreamforms

93bf352219608e803948cd28385566e0ca63fa7c

[ "MIT" ]

1

2021-01-27T10:49:35.000Z

# Generated by Django 2.2.1 on 2019-05-17 19:15 from django.db import migrations, models import django.db.models.deletion import wagtailstreamforms.fields

34.465116

156

0.589069

# Generated by Django 2.2.1 on 2019-05-17 19:15 from django.db import migrations, models import django.db.models.deletion import wagtailstreamforms.fields class Migration(migrations.Migration): initial = True dependencies = [ ('wagtailstreamforms', '0001_initial'), ] operations = [ migrations.CreateModel( name='HookSelectModel', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('hooks', wagtailstreamforms.fields.HookSelectField(blank=True, help_text='Some hooks', null=True)), ], ), migrations.CreateModel( name='InvalidFormSettingsModel', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ], ), migrations.CreateModel( name='ValidFormSettingsModel', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255)), ('number', models.IntegerField()), ('form', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='advanced_settings', to='wagtailstreamforms.Form')), ], options={ 'abstract': False, }, ), ]

0

1,302

23

83ff131905fef6cb336a239bba7b3fdd20edf5cf

492

py

Python

PyRaMD/integrate/velocity_verlet.py

adodin/simple_MD

93d725e6cb3de9901b44967d75e3db9d726b936a

[ "MIT" ]

null

PyRaMD/integrate/velocity_verlet.py

adodin/simple_MD

93d725e6cb3de9901b44967d75e3db9d726b936a

[ "MIT" ]

5

2020-03-11T20:32:25.000Z

2020-03-12T00:43:06.000Z

PyRaMD/integrate/velocity_verlet.py

adodin/simple_MD

93d725e6cb3de9901b44967d75e3db9d726b936a

[ "MIT" ]

null

# Velocity Verlet Integrator as a Functor containing the integrator specs # Initializes Integrator with time step & force field

32.8

73

0.603659

# Velocity Verlet Integrator as a Functor containing the integrator specs class VelocityVerlet: # Initializes Integrator with time step & force field def __init__(self, dt, force_field): self.dt = dt self.force_field = force_field def __call__(self, x, v, m, *args, **kwargs): a_1 = self.force_field(x) x = x + v * self.dt + 0.5 * a_1 * self.dt**2 a_2 = self.force_field(x) v = v + 0.5 * (a_1 + a_2) * self.dt return x, v

284

0

76

e3bb77c5090710317d11e372d9d96a50cd00e5eb

8,369

py

Python

pyblockchain/blockchain.py

kadonoamino/python_blockchain

2ef52bccc812f0f7c48e61256d125e196ad51bce

[ "MIT" ]

null

pyblockchain/blockchain.py

kadonoamino/python_blockchain

2ef52bccc812f0f7c48e61256d125e196ad51bce

[ "MIT" ]

null

pyblockchain/blockchain.py

kadonoamino/python_blockchain

2ef52bccc812f0f7c48e61256d125e196ad51bce

[ "MIT" ]

null

import contextlib import hashlib import json import logging import sys import time import threading from ecdsa import NIST256p from ecdsa import VerifyingKey import requests import utils MINING_DIFFICULTY = 3 MINING_SENDER = 'THE BLOCKCHAIN' MINING_REWARD = 1.0 MINING_TIMER_SEC = 20 BLOCKCHAIN_PORT_RANGE = (5000, 5003) NEIGHBOURS_IP_RANGE_NUM = (0, 1) BLOCKCHAIN_NEIGHBOURS_SYNC_TIME_SEC = 20 logging.basicConfig(level=logging.INFO, stream=sys.stdout) logger = logging.getLogger(__name__)

35.163866

79

0.602342

import contextlib import hashlib import json import logging import sys import time import threading from ecdsa import NIST256p from ecdsa import VerifyingKey import requests import utils MINING_DIFFICULTY = 3 MINING_SENDER = 'THE BLOCKCHAIN' MINING_REWARD = 1.0 MINING_TIMER_SEC = 20 BLOCKCHAIN_PORT_RANGE = (5000, 5003) NEIGHBOURS_IP_RANGE_NUM = (0, 1) BLOCKCHAIN_NEIGHBOURS_SYNC_TIME_SEC = 20 logging.basicConfig(level=logging.INFO, stream=sys.stdout) logger = logging.getLogger(__name__) class BlockChain(object): def __init__(self, blockchain_address=None, port=None): self.transaction_pool = [] self.chain = [] self.neighbours = [] self.create_block(0, self.hash({})) self.blockchain_address = blockchain_address self.port = port self.mining_semaphore = threading.Semaphore(1) self.sync_neighbours_semaphore = threading.Semaphore(1) def run(self): self.sync_neighbours() self.resolve_conflicts() self.start_mining() def set_neighbours(self): self.neighbours = utils.find_neighbours( utils.get_host(), self.port, NEIGHBOURS_IP_RANGE_NUM[0], NEIGHBOURS_IP_RANGE_NUM[1], BLOCKCHAIN_PORT_RANGE[0], BLOCKCHAIN_PORT_RANGE[1]) logger.info({ 'action': 'set_neighbours', 'neighbours': self.neighbours }) def sync_neighbours(self): is_acquire = self.sync_neighbours_semaphore.acquire(blocking=False) if is_acquire: with contextlib.ExitStack() as stack: stack.callback(self.sync_neighbours_semaphore.release) self.set_neighbours() loop = threading.Timer( BLOCKCHAIN_NEIGHBOURS_SYNC_TIME_SEC, self.sync_neighbours) loop.start() def create_block(self, nonce, previous_hash): block = utils.sorted_dict_by_key({ 'timestamp': time.time(), 'transactions': self.transaction_pool, 'nonce': nonce, 'previous_hash': previous_hash }) self.chain.append(block) self.transaction_pool = [] for node in self.neighbours: requests.delete(f'http://{node}/transactions') return block def hash(self, block): sorted_block = json.dumps(block, sort_keys=True) return hashlib.sha256(sorted_block.encode()).hexdigest() def add_transaction(self, sender_blockchain_address, recipient_blockchain_address, value, sender_public_key=None, signature=None): transaction = utils.sorted_dict_by_key({ 'sender_blockchain_address': sender_blockchain_address, 'recipient_blockchain_address': recipient_blockchain_address, 'value': float(value) }) if sender_blockchain_address == MINING_SENDER: self.transaction_pool.append(transaction) return True if self.verify_transaction_signature( sender_public_key, signature, transaction): if (self.calculate_total_amount(sender_blockchain_address) < float(value)): logger.error( {'action': 'add_transaction', 'error': 'no_value'}) return False self.transaction_pool.append(transaction) return True return False def create_transaction(self, sender_blockchain_address, recipient_blockchain_address, value, sender_public_key, signature): is_transacted = self.add_transaction( sender_blockchain_address, recipient_blockchain_address, value, sender_public_key, signature) if is_transacted: for node in self.neighbours: requests.put( f'http://{node}/transactions', json={ 'sender_blockchain_address': sender_blockchain_address, 'recipient_blockchain_address': recipient_blockchain_address, 'value': value, 'sender_public_key': sender_public_key, 'signature': signature, } ) return is_transacted def verify_transaction_signature( self, sender_public_key, signature, transaction): sha256 = hashlib.sha256() sha256.update(str(transaction).encode('utf-8')) message = sha256.digest() signature_bytes = bytes().fromhex(signature) verifying_key = VerifyingKey.from_string( bytes().fromhex(sender_public_key), curve=NIST256p) verified_key = verifying_key.verify(signature_bytes, message) return verified_key def valid_proof(self, transactions, previous_hash, nonce, difficulty=MINING_DIFFICULTY): guess_block = utils.sorted_dict_by_key({ 'transactions': transactions, 'nonce': nonce, 'previous_hash': previous_hash }) guess_hash = self.hash(guess_block) return guess_hash[:difficulty] == '0'*difficulty def proof_of_work(self): transactions = self.transaction_pool.copy() previous_hash = self.hash(self.chain[-1]) nonce = 0 while self.valid_proof(transactions, previous_hash, nonce) is False: nonce += 1 return nonce def mining(self): # if not self.transaction_pool: # return False self.add_transaction( sender_blockchain_address=MINING_SENDER, recipient_blockchain_address=self.blockchain_address, value=MINING_REWARD) nonce = self.proof_of_work() previous_hash = self.hash(self.chain[-1]) self.create_block(nonce, previous_hash) logger.info({'action': 'mining', 'status': 'success'}) for node in self.neighbours: requests.put(f'http://{node}/consensus') return True def start_mining(self): is_acquire = self.mining_semaphore.acquire(blocking=False) if is_acquire: with contextlib.ExitStack() as stack: stack.callback(self.mining_semaphore.release) self.mining() loop = threading.Timer(MINING_TIMER_SEC, self.start_mining) loop.start() def calculate_total_amount(self, blockchain_address): total_amount = 0.0 for block in self.chain: for transaction in block['transactions']: value = float(transaction['value']) if blockchain_address == \ transaction['recipient_blockchain_address']: total_amount += value if blockchain_address == \ transaction['sender_blockchain_address']: total_amount -= value return total_amount def valid_chain(self, chain): pre_block = chain[0] current_index = 1 while current_index < len(chain): block = chain[current_index] if block['previous_hash'] != self.hash(pre_block): return False if not self.valid_proof( block['transactions'], block['previous_hash'], block['nonce'], MINING_DIFFICULTY): return False pre_block = block current_index += 1 return True def resolve_conflicts(self): longest_chain = None max_length = len(self.chain) for node in self.neighbours: response = requests.get(f'http://{node}/chain') if response.status_code == 200: response_json = response.json() chain = response_json['chain'] chain_length = len(chain) if chain_length > max_length and self.valid_chain(chain): max_length = chain_length longest_chain = chain if longest_chain: self.chain = longest_chain logger.info({'action': 'resolve_conflicts', 'status': 'replaced'}) return True logger.info({'action': 'resolve_conflicts', 'status': 'not_replaced'}) return False

7,413

4

455

58059077979675f58d0fbc442c579293c01a16d0

3,683

py

Python

Arrows.py

OceanNuclear/ComplexAnalysis

7adccc0d81ea1216e305d35e248e6d886c682e6c

[ "MIT" ]

null

Arrows.py

OceanNuclear/ComplexAnalysis

7adccc0d81ea1216e305d35e248e6d886c682e6c

[ "MIT" ]

null

Arrows.py

OceanNuclear/ComplexAnalysis

7adccc0d81ea1216e305d35e248e6d886c682e6c

[ "MIT" ]

null

#!/home/ocean/anaconda3/bin/python3 from numpy import cos, arccos, sin, arctan, tan, pi, sqrt, e; from numpy import array as ary; import numpy as np; tau = 2*pi from matplotlib import pyplot as plt import seaborn as sns #uses arrows to plot where each point lands after being transformed by the function LongComputationalTime = False x = np.linspace(-5,5, 50) y = np.linspace(-5,5, 40) startingPts = mymeshgrid(x,y) #Oh yeah computer memory problem. Now I've got a wobble in my grid. #startingPts = np.concatenate(np.transpose(np.meshgrid(x,y)), axis=0) cycleLen=len(startingPts) cycleLen=6 uncleanLandingPts = [complexFunc(z) for z in startingPts] landingPts = np.array([z if np.isfinite(z).all() else [0,0] for z in uncleanLandingPts]) sortedLandingPoints = np.reshape(landingPts,[len(x),len(y),2]) colorcycle = iter([rotateColorSpace(theta) for theta in np.linspace(0,tau, cycleLen)]) #Order=FABCDEF if LongComputationalTime: for n in range(len(startingPts)): plt.annotate("", xy=startingPts[n], xytext=landingPts[n],arrowprops=dict(color = next(colorcycle), arrowstyle= '<-', alpha=0.5,),)#use arrowheads #pass #plot the y direction gridlines landing location for n in range(len(x)): plt.plot(sortedLandingPoints[n,:,0],sortedLandingPoints[n,:,1], lw=0.8, alpha=1, color= "green")#next(colorcycle)) #for n in range (int(len(y)/2)) :next(colorcycle) #for n in range (int(cycleLen/3)): next(colorcycle) #shift the color cycle foward by 1/3 #plot the x direction gridlines landing location for n in range(len(y)): plt.plot(sortedLandingPoints[:,n,0],sortedLandingPoints[:,n,1], lw=0.8, alpha=1, color= "red")#next(colorcycle)) xmin = [min(startingPts[:,0]),min(landingPts[:,0])] xmax = [max(startingPts[:,0]),max(landingPts[:,0])] ymin = [min(startingPts[:,1]),min(landingPts[:,1])] ymax = [max(startingPts[:,1]),max(landingPts[:,1])] plt.xlim( min (xmin) , max ( xmax ) ) plt.ylim( min (ymin) , max ( ymax ) ) plt.show() plt.plot(landingPts[:,:]-np.ones(np.shape(landingPts[:,:]))) plt.show() Radius = 100 small = 0.001 st_line = np.linspace(0,0,100)-1j*np.logspace(np.log10(small),np.log10(Radius),100) theta=np.linspace(-pi/2,pi/2,200) theta_2 = theta[:int(len(theta)/2)] theta_3 = theta[int(len(theta)/2):] semiCirc= Radius*cos(theta)+1j*Radius*sin(theta) smallCirc =small*cos(-theta_2)+1j*small*sin(-theta_2) smallCirc2=small*cos(-theta_3)+1j*small*sin(-theta_3) reverse_st = -st_line[::-1] Dee = np.concatenate([smallCirc2,st_line,semiCirc,reverse_st,smallCirc]) color = sns.palettes.hls_palette(n_colors=6) for n in range(0,6): segment=complexInput(Dee)[100*n:100*(n+1)] plt.plot(segment.real,segment.imag,color=color[n]) #plt.xlim(-1,1) #plt.ylim(-1,1) #plt.scatter(complexInput(Dee).real[::20],complexInput(Dee.imag)[::20]) plt.show()

39.180851

147

0.684768

#!/home/ocean/anaconda3/bin/python3 from numpy import cos, arccos, sin, arctan, tan, pi, sqrt, e; from numpy import array as ary; import numpy as np; tau = 2*pi from matplotlib import pyplot as plt import seaborn as sns #uses arrows to plot where each point lands after being transformed by the function LongComputationalTime = False def complexFunc(point): #if LongComputationalTime == True [x,y] = point z = x+1j*y function = (z**2+4)/((z-3)*(z+1)*(z+6)*(z)) return [np.real(function),np.imag(function)] def complexInput(z): #if LongComputationalTime == False #RC=0.0000001 function = -(z+1)/((z-2)*(z+3)) #(z**2+4)/((z-3)*(z+1)*(z+6)*(z)) return function def mymeshgrid(x,y): coord = [] for x1 in x: for y1 in y: coord.append([x1,y1]) return np.array(coord).reshape([len(x)*len(y),2]) def rotateColorSpace(theta): #given a vector pointing at 1,0,0; we want to rotate it around the (1/sqrt(3))*[1,1,1] axis by theta degrees. w = cos(theta/2) x = sin(theta/2)/sqrt(3) y = sin(theta/2)/sqrt(3) z = sin(theta/2)/sqrt(3) A = ary([[ y*y+z*z, w*z-x*y,-w*y-x*z], [-w*z-x*y, x*x+z*z, w*x-y*z], [ w*y-x*z,-w*x-y*z, x*x+y*y]]) R = np.identity(3) # = identity matrix. R-= 2*A return (np.round(R@ary([1,0,0]))) x = np.linspace(-5,5, 50) y = np.linspace(-5,5, 40) startingPts = mymeshgrid(x,y) #Oh yeah computer memory problem. Now I've got a wobble in my grid. #startingPts = np.concatenate(np.transpose(np.meshgrid(x,y)), axis=0) cycleLen=len(startingPts) cycleLen=6 uncleanLandingPts = [complexFunc(z) for z in startingPts] landingPts = np.array([z if np.isfinite(z).all() else [0,0] for z in uncleanLandingPts]) sortedLandingPoints = np.reshape(landingPts,[len(x),len(y),2]) colorcycle = iter([rotateColorSpace(theta) for theta in np.linspace(0,tau, cycleLen)]) #Order=FABCDEF if LongComputationalTime: for n in range(len(startingPts)): plt.annotate("", xy=startingPts[n], xytext=landingPts[n],arrowprops=dict(color = next(colorcycle), arrowstyle= '<-', alpha=0.5,),)#use arrowheads #pass #plot the y direction gridlines landing location for n in range(len(x)): plt.plot(sortedLandingPoints[n,:,0],sortedLandingPoints[n,:,1], lw=0.8, alpha=1, color= "green")#next(colorcycle)) #for n in range (int(len(y)/2)) :next(colorcycle) #for n in range (int(cycleLen/3)): next(colorcycle) #shift the color cycle foward by 1/3 #plot the x direction gridlines landing location for n in range(len(y)): plt.plot(sortedLandingPoints[:,n,0],sortedLandingPoints[:,n,1], lw=0.8, alpha=1, color= "red")#next(colorcycle)) xmin = [min(startingPts[:,0]),min(landingPts[:,0])] xmax = [max(startingPts[:,0]),max(landingPts[:,0])] ymin = [min(startingPts[:,1]),min(landingPts[:,1])] ymax = [max(startingPts[:,1]),max(landingPts[:,1])] plt.xlim( min (xmin) , max ( xmax ) ) plt.ylim( min (ymin) , max ( ymax ) ) plt.show() plt.plot(landingPts[:,:]-np.ones(np.shape(landingPts[:,:]))) plt.show() Radius = 100 small = 0.001 st_line = np.linspace(0,0,100)-1j*np.logspace(np.log10(small),np.log10(Radius),100) theta=np.linspace(-pi/2,pi/2,200) theta_2 = theta[:int(len(theta)/2)] theta_3 = theta[int(len(theta)/2):] semiCirc= Radius*cos(theta)+1j*Radius*sin(theta) smallCirc =small*cos(-theta_2)+1j*small*sin(-theta_2) smallCirc2=small*cos(-theta_3)+1j*small*sin(-theta_3) reverse_st = -st_line[::-1] Dee = np.concatenate([smallCirc2,st_line,semiCirc,reverse_st,smallCirc]) color = sns.palettes.hls_palette(n_colors=6) for n in range(0,6): segment=complexInput(Dee)[100*n:100*(n+1)] plt.plot(segment.real,segment.imag,color=color[n]) #plt.xlim(-1,1) #plt.ylim(-1,1) #plt.scatter(complexInput(Dee).real[::20],complexInput(Dee.imag)[::20]) plt.show()

813

0

90

79b8a4167d43787a167e247f4ecbeea1783ea099

1,419

py

Python

src/tests/utils/test_process_hooks.py

DmitryBurnaev/podcast-service

53349a3f9aed22a8024d0c83380f9a02464962a3

[ "MIT" ]

5

2021-07-01T16:31:29.000Z

2022-01-29T14:32:13.000Z

src/tests/utils/test_process_hooks.py

DmitryBurnaev/podcast-service

53349a3f9aed22a8024d0c83380f9a02464962a3

[ "MIT" ]

45

2020-10-25T19:41:26.000Z

2022-03-25T06:31:58.000Z

src/tests/utils/test_process_hooks.py

DmitryBurnaev/podcast-service

53349a3f9aed22a8024d0c83380f9a02464962a3

[ "MIT" ]

1

2022-01-27T11:30:07.000Z

from core import settings from modules.podcast.utils import episode_process_hook from modules.podcast.models import EpisodeStatus

35.475

97

0.609584

from core import settings from modules.podcast.utils import episode_process_hook from modules.podcast.models import EpisodeStatus class TestEpisodeProcessHooks: def test_call_hook__ok(self, mocked_redis): mocked_redis.get.return_value = {"total_bytes": 1024} episode_process_hook( EpisodeStatus.DL_EPISODE_DOWNLOADING, "test-episode.mp3", total_bytes=1024, processed_bytes=124, ) mocked_redis.set.assert_called_with( "test-episode", { "event_key": "test-episode", "status": str(EpisodeStatus.DL_EPISODE_DOWNLOADING), "processed_bytes": 124, "total_bytes": 1024, }, ttl=settings.DOWNLOAD_EVENT_REDIS_TTL, ) def test_call_hook__with_chunks__ok(self, mocked_redis): mocked_redis.get.return_value = {"total_bytes": 1024, "processed_bytes": 200} episode_process_hook(EpisodeStatus.DL_EPISODE_DOWNLOADING, "test-episode.mp3", chunk=100) mocked_redis.set.assert_called_with( "test-episode", { "event_key": "test-episode", "status": str(EpisodeStatus.DL_EPISODE_DOWNLOADING), "processed_bytes": 200 + 100, "total_bytes": 1024, }, ttl=settings.DOWNLOAD_EVENT_REDIS_TTL, )

1,203

9

76

9c35893b27a1c1dbd31544a1f881eac44b0b9ec6

61

py

Python

xomx/feature_selection/__init__.py

perrin-isir/xomx

9ca0ad56c333ebf4444f38bd9fa59cdd4e533756

[ "BSD-3-Clause" ]

4

2021-12-16T21:34:32.000Z

2021-12-22T09:25:53.000Z

xomx/feature_selection/__init__.py

perrin-isir/xomx

9ca0ad56c333ebf4444f38bd9fa59cdd4e533756

[ "BSD-3-Clause" ]

2

2021-12-15T15:51:42.000Z

2022-03-31T08:17:26.000Z

xomx/feature_selection/__init__.py

perrin-isir/xomx

9ca0ad56c333ebf4444f38bd9fa59cdd4e533756

[ "BSD-3-Clause" ]

2

2021-12-14T16:50:39.000Z

2022-03-14T09:27:51.000Z

from .RFEExtraTrees import RFEExtraTrees, load_RFEExtraTrees

30.5

60

0.885246

from .RFEExtraTrees import RFEExtraTrees, load_RFEExtraTrees

0

5e3409be2e89ecf64071b4b6812018a6ca38c8c8

9,575

py

Python

src/julia/pseudo_python_cli.py

dpinol/pyjulia

cec4bf0b0eac7e39cecd8f3e7882563062903d0f

[ "MIT" ]

649

2016-09-09T07:38:19.000Z

2022-03-28T04:30:55.000Z

src/julia/pseudo_python_cli.py

dpinol/pyjulia

cec4bf0b0eac7e39cecd8f3e7882563062903d0f

[ "MIT" ]

362

2016-09-08T16:25:30.000Z

2022-03-05T23:15:05.000Z

src/julia/pseudo_python_cli.py

dpinol/pyjulia

cec4bf0b0eac7e39cecd8f3e7882563062903d0f

[ "MIT" ]

85

2016-11-08T09:32:44.000Z

2022-03-03T13:10:37.000Z

""" Pseudo Python command line interface. It tries to mimic a subset of Python CLI: https://docs.python.org/3/using/cmdline.html """ from __future__ import absolute_import, print_function import code import copy import runpy import sys import traceback from collections import namedtuple try: from types import SimpleNamespace except ImportError: from argparse import Namespace as SimpleNamespace ARGUMENT_HELP = """ positional arguments: script path to file (default: None) args arguments passed to program in sys.argv[1:] optional arguments: -h, --help show this help message and exit -i inspect interactively after running script. --version, -V Print the Python version number and exit. -VV is not supported. -c COMMAND Execute the Python code in COMMAND. -m MODULE Search sys.path for the named MODULE and execute its contents as the __main__ module. """ ArgDest = namedtuple("ArgDest", "dest names default") Optional = namedtuple("Optional", "name is_long argdest nargs action terminal") Result = namedtuple("Result", "option values") class PyArgumentParser(object): """ `ArgumentParser`-like parser with "terminal option" support. Major differences: * Formatted help has to be provided to `description`. * Many options for `.add_argument` are not supported. * Especially, there is no positional argument support: all positional arguments go into `ns.args`. * `.add_argument` can take boolean option `terminal` (default: `False`) to stop parsing after consuming the given option. """ # Once we drop Python 2, we can do: """ def add_argument(self, name, *alt, dest=None, nargs=None, action=None, default=None, terminal=False): """ # fmt: off def _find_matches(self, arg): """ Return a list of `.Result`. If value presents in `arg` (i.e., ``--long-option=value``), it becomes the element of `.Result.values` (a list). Otherwise, this list has to be filled by the caller (`_parse_until_terminal`). """ for opt in self._options: if arg == opt.name: return [Result(opt, [])] elif arg.startswith(opt.name): # i.e., len(arg) > len(opt.name): if opt.is_long and arg[len(opt.name)] == "=": return [Result(opt, [arg[len(opt.name) + 1:]])] elif not opt.is_long: if opt.nargs != 0: return [Result(opt, [arg[len(opt.name):]])] else: results = [Result(opt, [])] rest = "-" + arg[len(opt.name):] results.extend(self._find_matches(rest)) return results # arg="-ih" -> rest="-h" return [] # fmt: on if __name__ == "__main__": sys.exit(main())

30.110063

85

0.552376

""" Pseudo Python command line interface. It tries to mimic a subset of Python CLI: https://docs.python.org/3/using/cmdline.html """ from __future__ import absolute_import, print_function import code import copy import runpy import sys import traceback from collections import namedtuple try: from types import SimpleNamespace except ImportError: from argparse import Namespace as SimpleNamespace ARGUMENT_HELP = """ positional arguments: script path to file (default: None) args arguments passed to program in sys.argv[1:] optional arguments: -h, --help show this help message and exit -i inspect interactively after running script. --version, -V Print the Python version number and exit. -VV is not supported. -c COMMAND Execute the Python code in COMMAND. -m MODULE Search sys.path for the named MODULE and execute its contents as the __main__ module. """ def python(module, command, script, args, interactive): if command: sys.argv[0] = "-c" assert sys.argv sys.argv[1:] = args if script: sys.argv[0] = script banner = "" try: if command: scope = {} exec(command, scope) elif module: scope = runpy.run_module(module, run_name="__main__", alter_sys=True) elif script == "-": source = sys.stdin.read() exec(compile(source, "<stdin>", "exec"), scope) elif script: scope = runpy.run_path(script, run_name="__main__") else: interactive = True scope = None banner = None # show banner except Exception: if not interactive: raise traceback.print_exc() if interactive: code.interact(banner=banner, local=scope) ArgDest = namedtuple("ArgDest", "dest names default") Optional = namedtuple("Optional", "name is_long argdest nargs action terminal") Result = namedtuple("Result", "option values") class PyArgumentParser(object): """ `ArgumentParser`-like parser with "terminal option" support. Major differences: * Formatted help has to be provided to `description`. * Many options for `.add_argument` are not supported. * Especially, there is no positional argument support: all positional arguments go into `ns.args`. * `.add_argument` can take boolean option `terminal` (default: `False`) to stop parsing after consuming the given option. """ def __init__(self, prog=None, usage="%(prog)s [options] [args]", description=""): self.prog = sys.argv[0] if prog is None else prog self.usage = usage self.description = description self._dests = ["args"] self._argdests = [ArgDest("args", (), [])] self._options = [] self.add_argument("--help", "-h", "-?", action="store_true") def format_usage(self): return "usage: " + self.usage % {"prog": self.prog} # Once we drop Python 2, we can do: """ def add_argument(self, name, *alt, dest=None, nargs=None, action=None, default=None, terminal=False): """ def add_argument(self, name, *alt, **kwargs): return self._add_argument_impl(name, alt, **kwargs) # fmt: off def _add_argument_impl(self, name, alt, dest=None, nargs=None, action=None, default=None, terminal=False): if dest is None: if name.startswith("--"): dest = name[2:] elif not name.startswith("-"): dest = name else: raise ValueError(name) if not name.startswith("-"): raise NotImplementedError( "Positional arguments are not supported." " All positional arguments will be stored in `ns.args`.") if terminal and action is not None: raise NotImplementedError( "Terminal option is assumed to have argument." " Non-`None` action={} is not supported".format()) if nargs is not None and action is not None: raise TypeError("`nargs` and `action` are mutually exclusive") if action == "store_true": nargs = 0 assert nargs is None or isinstance(nargs, int) assert action in (None, "store_true") assert dest not in self._dests self._dests.append(dest) argdest = ArgDest( dest=dest, names=(name,) + alt, default=default, ) self._argdests.append(argdest) for arg in (name,) + alt: self._options.append(Optional( name=arg, is_long=arg.startswith("--"), argdest=argdest, nargs=nargs, action=action, terminal=terminal, )) def parse_args(self, args): ns = SimpleNamespace(**{ argdest.dest: copy.copy(argdest.default) for argdest in self._argdests }) args_iter = iter(args) self._parse_until_terminal(ns, args_iter) ns.args.extend(args_iter) if ns.help: self.print_help() self.exit() del ns.help return ns def _parse_until_terminal(self, ns, args_iter): seen = set() for a in args_iter: results = self._find_matches(a) if not results: ns.args.append(a) break for i, res in enumerate(results): dest = res.option.argdest.dest if dest in seen: self._usage_and_error( "{} provided more than twice" .format(", ".join(res.option.argdest.names))) seen.add(dest) num_args = res.option.nargs if num_args is None: num_args = 1 while len(res.values) < num_args: try: res.values.append(next(args_iter)) except StopIteration: self.error(self.format_usage()) if res.option.action == "store_true": setattr(ns, dest, True) else: value = res.values if res.option.nargs is None: value, = value setattr(ns, dest, value) if res.option.terminal: assert i == len(results) - 1 return def _find_matches(self, arg): """ Return a list of `.Result`. If value presents in `arg` (i.e., ``--long-option=value``), it becomes the element of `.Result.values` (a list). Otherwise, this list has to be filled by the caller (`_parse_until_terminal`). """ for opt in self._options: if arg == opt.name: return [Result(opt, [])] elif arg.startswith(opt.name): # i.e., len(arg) > len(opt.name): if opt.is_long and arg[len(opt.name)] == "=": return [Result(opt, [arg[len(opt.name) + 1:]])] elif not opt.is_long: if opt.nargs != 0: return [Result(opt, [arg[len(opt.name):]])] else: results = [Result(opt, [])] rest = "-" + arg[len(opt.name):] results.extend(self._find_matches(rest)) return results # arg="-ih" -> rest="-h" return [] # fmt: on def print_usage(self, file=None): print(self.format_usage(), file=file or sys.stdout) def print_help(self): self.print_usage() print() print(self.description) def exit(self, status=0): sys.exit(status) def _usage_and_error(self, message): self.print_usage(sys.stderr) print(file=sys.stderr) self.error(message) def error(self, message): print(message, file=sys.stderr) self.exit(2) def make_parser(description=__doc__ + ARGUMENT_HELP): parser = PyArgumentParser( prog=None if sys.argv[0] else "python", usage="%(prog)s [option] ... [-c cmd | -m mod | script | -] [args]", description=description, ) parser.add_argument("-i", dest="interactive", action="store_true") parser.add_argument("--version", "-V", action="store_true") parser.add_argument("-c", dest="command", terminal=True) parser.add_argument("-m", dest="module", terminal=True) return parser def parse_args_with(parser, args): ns = parser.parse_args(args) if ns.command and ns.module: parser.error("-c and -m are mutually exclusive") if ns.version: print("Python {0}.{1}.{2}".format(*sys.version_info)) parser.exit() del ns.version ns.script = None if (not (ns.command or ns.module)) and ns.args: ns.script = ns.args[0] ns.args = ns.args[1:] return ns def parse_args(args): return parse_args_with(make_parser(), args) def main(args=None): if args is None: args = sys.argv[1:] try: ns = parse_args(args) python(**vars(ns)) except SystemExit as err: return err.code except Exception: traceback.print_exc() return 1 if __name__ == "__main__": sys.exit(main())

6,153

0

412

e39df32cb7e8758760f31753af692ff76943f2fa

5,600

py

Python

sppas/sppas/src/ui/wxgui/dialogs/trsinfodialog.py

mirfan899/MTTS

3167b65f576abcc27a8767d24c274a04712bd948

[ "MIT" ]

null

sppas/sppas/src/ui/wxgui/dialogs/trsinfodialog.py

mirfan899/MTTS

3167b65f576abcc27a8767d24c274a04712bd948

[ "MIT" ]

null

sppas/sppas/src/ui/wxgui/dialogs/trsinfodialog.py

mirfan899/MTTS

3167b65f576abcc27a8767d24c274a04712bd948

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: UTF-8 -*- # --------------------------------------------------------------------------- # ___ __ __ __ ___ # / | \ | \ | \ / Automatic # \__ |__/ |__/ |___| \__ Annotation # \ | | | | \ of # ___/ | | | | ___/ Speech # # # http://www.sppas.org/ # # --------------------------------------------------------------------------- # Laboratoire Parole et Langage, Aix-en-Provence, France # Copyright (C) 2011-2016 Brigitte Bigi # # This banner notice must not be removed # --------------------------------------------------------------------------- # Use of this software is governed by the GNU Public License, version 3. # # SPPAS is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # SPPAS is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with SPPAS. If not, see <http://www.gnu.org/licenses/>. # # --------------------------------------------------------------------------- # File: trsinfodialog.py # ---------------------------------------------------------------------------- __docformat__ = """epytext""" __authors__ = """Brigitte Bigi""" __copyright__ = """Copyright (C) 2011-2015 Brigitte Bigi""" import wx from sppas.src.ui.wxgui.panels.trslist import TrsList from sppas.src.ui.wxgui.cutils.imageutils import spBitmap from sppas.src.ui.wxgui.cutils.ctrlutils import CreateGenButton from sppas.src.ui.wxgui.sp_icons import APP_ICON from sppas.src.ui.wxgui.sp_icons import CANCEL_ICON from sppas.src.ui.wxgui.sp_icons import INFO_ICON from sppas.src.ui.wxgui.sp_consts import FRAME_STYLE from sppas.src.ui.wxgui.sp_consts import FRAME_TITLE # ---------------------------------------------------------------------------- class TrsInfoDialog( wx.Dialog ): """ @author: Brigitte Bigi @contact: develop@sppas.org @license: GPL, v3 @summary: Open a dialog with information about a transcription. """ # End __init__ # ------------------------------------------------------------------------ # ------------------------------------------------------------------------ # Create the GUI # ------------------------------------------------------------------------ # ------------------------------------------------------------------------------

38.095238

136

0.563393

#!/usr/bin/env python # -*- coding: UTF-8 -*- # --------------------------------------------------------------------------- # ___ __ __ __ ___ # / | \ | \ | \ / Automatic # \__ |__/ |__/ |___| \__ Annotation # \ | | | | \ of # ___/ | | | | ___/ Speech # # # http://www.sppas.org/ # # --------------------------------------------------------------------------- # Laboratoire Parole et Langage, Aix-en-Provence, France # Copyright (C) 2011-2016 Brigitte Bigi # # This banner notice must not be removed # --------------------------------------------------------------------------- # Use of this software is governed by the GNU Public License, version 3. # # SPPAS is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # SPPAS is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with SPPAS. If not, see <http://www.gnu.org/licenses/>. # # --------------------------------------------------------------------------- # File: trsinfodialog.py # ---------------------------------------------------------------------------- __docformat__ = """epytext""" __authors__ = """Brigitte Bigi""" __copyright__ = """Copyright (C) 2011-2015 Brigitte Bigi""" import wx from sppas.src.ui.wxgui.panels.trslist import TrsList from sppas.src.ui.wxgui.cutils.imageutils import spBitmap from sppas.src.ui.wxgui.cutils.ctrlutils import CreateGenButton from sppas.src.ui.wxgui.sp_icons import APP_ICON from sppas.src.ui.wxgui.sp_icons import CANCEL_ICON from sppas.src.ui.wxgui.sp_icons import INFO_ICON from sppas.src.ui.wxgui.sp_consts import FRAME_STYLE from sppas.src.ui.wxgui.sp_consts import FRAME_TITLE # ---------------------------------------------------------------------------- class TrsInfoDialog( wx.Dialog ): """ @author: Brigitte Bigi @contact: develop@sppas.org @license: GPL, v3 @summary: Open a dialog with information about a transcription. """ def __init__(self, parent, prefsIO, trsname, trs): wx.Dialog.__init__(self, parent, title=FRAME_TITLE+" - Information", size=(580, -1), style=FRAME_STYLE) self.preferences = prefsIO self.trsname = trsname self.trs = trs self._create_gui() # End __init__ # ------------------------------------------------------------------------ # ------------------------------------------------------------------------ # Create the GUI # ------------------------------------------------------------------------ def _create_gui(self): self._init_infos() self._create_title_label() self._create_content() self._create_close_button() self._layout_components() self._set_focus_component() def _init_infos( self ): wx.GetApp().SetAppName( "trsinfo" ) # icon _icon = wx.EmptyIcon() _icon.CopyFromBitmap( spBitmap(APP_ICON) ) self.SetIcon(_icon) # colors self.SetBackgroundColour( self.preferences.GetValue('M_BG_COLOUR')) self.SetForegroundColour( self.preferences.GetValue('M_FG_COLOUR')) self.SetFont( self.preferences.GetValue('M_FONT')) def _create_title_label(self): self.title_layout = wx.BoxSizer(wx.HORIZONTAL) bmp = wx.BitmapButton(self, bitmap=spBitmap(INFO_ICON, 32, theme=self.preferences.GetValue('M_ICON_THEME')), style=wx.NO_BORDER) font = self.preferences.GetValue('M_FONT') font.SetWeight(wx.BOLD) font.SetPointSize(font.GetPointSize() + 2) self.title_label = wx.StaticText(self, label="Transcription file properties", style=wx.ALIGN_CENTER) self.title_label.SetFont( font ) self.title_layout.Add(bmp, flag=wx.TOP|wx.RIGHT|wx.ALIGN_RIGHT, border=5) self.title_layout.Add(self.title_label, flag=wx.EXPAND|wx.ALL|wx.wx.ALIGN_CENTER_VERTICAL, border=5) def _create_content(self): # the information panel self.trspanel = TrsList( self, self.trsname, self.trs) def _create_close_button(self): bmp = spBitmap(CANCEL_ICON, theme=self.preferences.GetValue('M_ICON_THEME')) color = self.preferences.GetValue('M_BG_COLOUR') self.btn_close = CreateGenButton(self, wx.ID_CLOSE, bmp, text=" Close", tooltip="Close this frame", colour=color) self.btn_close.SetFont( self.preferences.GetValue('M_FONT')) self.btn_close.SetDefault() self.btn_close.SetFocus() self.SetAffirmativeId(wx.ID_CLOSE) def _layout_components(self): vbox = wx.BoxSizer(wx.VERTICAL) vbox.Add(self.title_layout, 0, flag=wx.ALL|wx.EXPAND, border=5) vbox.Add(self.trspanel, 1, flag=wx.ALL|wx.EXPAND, border=0) vbox.Add(self.btn_close, 0, flag=wx.ALL|wx.EXPAND, border=5) self.SetMinSize((380,280)) self.SetSizer( vbox ) self.Show() def _set_focus_component(self): self.btn_close.SetFocus() # ------------------------------------------------------------------------------

2,480

0

216

b9df1422c289da33fd8f1fd710c8f912544cf226

14,741

py

Python

utils/syn_functions.py

droidadroit/nasbot

f8d5d0ba8b77c37ebaa6cd2ab148a2633ff20207

[ "MIT" ]

null

utils/syn_functions.py

droidadroit/nasbot

f8d5d0ba8b77c37ebaa6cd2ab148a2633ff20207

[ "MIT" ]

null

utils/syn_functions.py

droidadroit/nasbot

f8d5d0ba8b77c37ebaa6cd2ab148a2633ff20207

[ "MIT" ]

null

""" A collection of utilities for MF-GP Bandits. -- kandasamy@cs.cmu.edu """ # pylint: disable=import-error # pylint: disable=no-member # pylint: disable=invalid-name # pylint: disable=relative-import # pylint: disable=super-on-old-class import numpy as np # Local imports from ..opt.function_caller import get_euc_function_caller_from_function # Hartmann Functions --------------------------------------------------------------------- def hartmann(x, alpha, A, P, max_val=np.inf): """ Computes the hartmann function for any given A and P. """ log_sum_terms = (A * (P - x)**2).sum(axis=1) return min(max_val, alpha.dot(np.exp(-log_sum_terms))) def _get_hartmann_data(domain_dim): """ Returns A and P for the 3D hartmann function. """ # pylint: disable=bad-whitespace if domain_dim == 3: A = np.array([[3.0, 10, 30], [0.1, 10, 35], [3.0, 10, 30], [0.1, 10, 35]], dtype=np.float64) P = 1e-4 * np.array([[3689, 1170, 2673], [4699, 4387, 7470], [1091, 8732, 5547], [ 381, 5743, 8828]], dtype=np.float64) alpha = np.array([1.0, 1.2, 3.0, 3.2]) domain = [[0, 1]] * 3 opt_pt = np.array([0.114614, 0.555649, 0.852547]) max_val = 3.86278 elif domain_dim == 6: A = np.array([[ 10, 3, 17, 3.5, 1.7, 8], [0.05, 10, 17, 0.1, 8, 14], [ 3, 3.5, 1.7, 10, 17, 8], [ 17, 8, 0.05, 10, 0.1, 14]], dtype=np.float64) P = 1e-4 * np.array([[1312, 1696, 5569, 124, 8283, 5886], [2329, 4135, 8307, 3736, 1004, 9991], [2348, 1451, 3522, 2883, 3047, 6650], [4047, 8828, 8732, 5743, 1091, 381]], dtype=np.float64) alpha = np.array([1.0, 1.2, 3.0, 3.2]) domain = [[0, 1]] * 6 opt_pt = np.array([0.20169, 0.150011, 0.476874, 0.275332, 0.311652, 0.6573]) max_val = 3.322368 else: raise NotImplementedError('Only implemented in 3 and 6 dimensions.') return A, P, alpha, opt_pt, domain, max_val def get_hartmann_high_d_function_caller(domain_dim, **kwargs): """ Constructs a higher dimensional Hartmann function. """ group_dim = 6 num_groups = int(domain_dim/group_dim) A, P, alpha, l_opt_pt, l_domain_bounds, l_max_val = _get_hartmann_data(group_dim) hartmann_func = lambda x: hartmann(x, alpha, A, P, l_max_val) def _eval_highd_hartmann_func(x): """ Evaluates the higher dimensional hartmann function. """ ret = 0 for j in range(num_groups): ret += hartmann_func(x[j*group_dim:(j+1)*group_dim]) return ret opt_pt = np.tile(l_opt_pt, num_groups+1)[0:domain_dim] opt_val = num_groups * l_max_val domain_bounds = np.tile(np.array(l_domain_bounds).T, num_groups+1).T[0:domain_dim] return get_euc_function_caller_from_function(_eval_highd_hartmann_func, domain_bounds, vectorised=False, opt_pt=opt_pt, opt_val=opt_val, **kwargs) def get_hartmann_high_d_function_caller_from_descr(descr, **kwargs): """ Constructs a high dimensional hartmann function from a string. """ domain_dim = int(descr[8:]) return get_hartmann_high_d_function_caller(domain_dim, **kwargs) def get_hartmann_function_caller(domain_dim, **kwargs): """ Returns a FunctionCaller object for the hartmann function. """ A, P, alpha, opt_pt, domain_bounds, max_val = _get_hartmann_data(domain_dim) hartmann_func = lambda x: hartmann(x, alpha, A, P, max_val) return get_euc_function_caller_from_function(hartmann_func, domain_bounds, vectorised=False, opt_pt=opt_pt, opt_val=max_val, **kwargs) # Hartmann Functions end here ------------------------------------------------------------ # Shekel Function ------------------------------------------------------------------------ def shekel(x, C, beta, max_val=np.inf): """ Computes the Shekel function for the given C and beta. """ inv_terms = ((C.T - x)**2).sum(axis=1) + beta return min(max_val, (1/inv_terms).sum()) def _get_shekel_data(): """ Returns the C, beta parameters and optimal values for the shekel function. """ C = [[4, 1, 8, 6, 3, 2, 5, 8, 6, 7], [4, 1, 8, 6, 7, 9, 3, 1, 2, 3], [4, 1, 8, 6, 3, 2, 5, 8, 6, 7], [4, 1, 8, 6, 7, 9, 3, 1, 2, 3]] C = np.array(C, dtype=np.double) beta = 0.1 * np.array([1, 2, 2, 4, 4, 6, 3, 7, 5, 5], dtype=np.double) opt_pt = np.array([4, 4, 4, 4], dtype=np.double) opt_val = shekel(opt_pt, C, beta) domain_bounds = [[0, 10]] * 4 return C, beta, opt_pt, domain_bounds, opt_val def get_shekel_function_caller(**kwargs): """ Returns a FunctionCaller object for the hartmann function. """ C, beta, opt_pt, domain_bounds, opt_val = _get_shekel_data() shekel_func = lambda x: shekel(x, C, beta, opt_val) return get_euc_function_caller_from_function(shekel_func, domain_bounds, vectorised=False, opt_pt=opt_pt, opt_val=opt_val, **kwargs) # Shekel function ends here -------------------------------------------------------------- # Currin Exponential Function ------------------------------------------------------------ def currin_exp(x, alpha): """ Computes the currin exponential function. """ x1 = x[0] x2 = x[1] val_1 = 1 - alpha * np.exp(-1/(2 * x2)) val_2 = (2300*x1**3 + 1900*x1**2 + 2092*x1 + 60) / (100*x1**3 + 500*x1**2 + 4*x1 + 20) return val_1 * val_2 def get_currin_exp_function_caller(**kwargs): """ Returns a FunctionCaller object for the Currin Exponential function. """ currin_exp_func = lambda x: currin_exp(x, 1) opt_val = 13.798650 opt_pt = None domain_bounds = np.array([[0, 1], [0, 1]]) return get_euc_function_caller_from_function(currin_exp_func, domain_bounds=domain_bounds, vectorised=False, opt_val=opt_val, opt_pt=opt_pt, **kwargs) # Branin Function ------------------------------------------------------------------------ def branin(x, a, b, c, r, s, t): """ Computes the Branin function. """ x1 = x[0] x2 = x[1] neg_ret = a * (x2 - b*x1**2 + c*x1 - r)**2 + s*(1-t)*np.cos(x1) + s return -neg_ret def _get_branin_data(): """ Gets the constants for the branin function. """ a = 1 b = 5.1/(4*np.pi**2) c = 5/np.pi r = 6 s = 10 t = 1/(8*np.pi) opt_pt = np.array([np.pi, 2.275]) domain_bounds = np.array([[-5, 10], [0, 15]]) return a, b, c, r, s, t, opt_pt, domain_bounds def get_branin_function_caller(**kwargs): """ Returns a FunctionCaller object for the Branin function. """ a, b, c, r, s, t, opt_pt, domain_bounds = _get_branin_data() branin_func = lambda x: branin(x, a, b, c, r, s, t) opt_val = branin_func(opt_pt) return get_euc_function_caller_from_function(branin_func, domain_bounds=domain_bounds, vectorised=False, opt_val=opt_val, opt_pt=opt_pt, **kwargs) def get_branin_high_d_function_caller(domain_dim, **kwargs): """ Constructs a higher dimensional Hartmann function. """ group_dim = 2 num_groups = int(domain_dim/group_dim) a, b, c, r, s, t, opt_pt_2d, domain_bounds_2d = _get_branin_data() branin_func = lambda x: branin(x, a, b, c, r, s, t) def _eval_highd_branin_func(x): """ Evaluates higher dimensional branin function. """ ret = 0 for j in range(num_groups): ret += branin_func(x[j*group_dim:(j+1)*group_dim]) return ret opt_pt = np.tile(opt_pt_2d, num_groups+1)[0:domain_dim] opt_val = _eval_highd_branin_func(opt_pt) domain_bounds = np.tile(np.array(domain_bounds_2d).T, num_groups+1).T[0:domain_dim] return get_euc_function_caller_from_function(_eval_highd_branin_func, domain_bounds, vectorised=False, opt_pt=opt_pt, opt_val=opt_val, **kwargs) def get_branin_high_d_function_caller_from_descr(descr, **kwargs): """ Constructs a high dimensional hartmann function from a string. """ domain_dim = int(descr[7:]) return get_branin_high_d_function_caller(domain_dim, **kwargs) # Borehole Function ---------------------------------------------------------------------- def borehole(x, z, max_val): """ Computes the Bore Hole function. """ # pylint: disable=bad-whitespace rw = x[0] r = x[1] Tu = x[2] Hu = x[3] Tl = x[4] Hl = x[5] L = x[6] Kw = x[7] # Compute high fidelity function frac2 = 2*L*Tu/(np.log(r/rw) * rw**2 * Kw) f2 = min(max_val, 2 * np.pi * Tu * (Hu - Hl)/(np.log(r/rw) * (1 + frac2 + Tu/Tl))) # Compute low fidelity function f1 = 5 * Tu * (Hu - Hl)/(np.log(r/rw) * (1.5 + frac2 + Tu/Tl)) # Compute final output return f2*z + f1*(1-z) def get_borehole_function_caller(**kwargs): """ Returns a FunctionCaller object for the Borehold function. """ opt_val = 309.523221 opt_pt = None borehole_func = lambda x: borehole(x, 1, opt_val) domain_bounds = [[0.05, 0.15], [100, 50000], [63070, 115600], [990, 1110], [63.1, 116], [700, 820], [1120, 1680], [9855, 12045]] return get_euc_function_caller_from_function(borehole_func, domain_bounds, vectorised=False, opt_val=opt_val, opt_pt=opt_pt, **kwargs) # Park1 function ================================================================== def park1(x, max_val=np.inf): """ Computes the park1 function. """ x1 = x[0] x2 = x[1] x3 = x[2] x4 = x[3] ret1 = (x1/2) * (np.sqrt(1 + (x2 + x3**2)*x4/(x1**2)) - 1) ret2 = (x1 + 3*x4) * np.exp(1 + np.sin(x3)) return min(ret1 + ret2, max_val) def get_park1_function_caller(**kwargs): """ Returns the park1 function caller. """ opt_val = 25.5872304 opt_pt = None func = lambda x: park1(x, opt_val) domain_bounds = [[0, 1]] * 4 return get_euc_function_caller_from_function(func, domain_bounds, vectorised=False, opt_val=opt_val, opt_pt=opt_pt, **kwargs) # Park2 function ================================================================== def park2(x, max_val=np.inf): """ Comutes the park2 function """ x1 = x[0] x2 = x[1] x3 = x[2] x4 = x[3] ret = (2.0/3.0) * np.exp(x1 + x2) - x4*np.sin(x3) + x3 return min(ret, max_val) def get_park2_function_caller(**kwargs): """ Returns function caller for park2. """ opt_val = 5.925698 opt_pt = None func = lambda x: park2(x, opt_val) domain_bounds = [[0, 1]] * 4 return get_euc_function_caller_from_function(func, domain_bounds, vectorised=False, opt_val=opt_val, opt_pt=opt_pt, **kwargs) def get_high_d_function_from_low_d(domain_dim, group_dim, low_d_func): """ Constructs a higher dimensional Hartmann function. """ num_groups = int(domain_dim/group_dim) def _eval_highd_func(x): """ Evaluates the higher dimensional function. """ ret = 0 for j in range(num_groups): ret += low_d_func(x[j*group_dim: (j+1)*group_dim]) return ret return _eval_highd_func, num_groups def get_high_d_function_caller_from_low_d_func(domain_dim, low_d_func, low_d_domain_bounds, low_d_opt_val, low_d_opt_pt, **kwargs): """ Gets a low dimensional function caller from a high dimensional one. """ group_dim = len(low_d_domain_bounds) high_d_func, num_groups = get_high_d_function_from_low_d(domain_dim, group_dim, low_d_func) high_d_domain_bounds = np.tile(np.array(low_d_domain_bounds).T, num_groups+1).T[0:domain_dim] high_d_opt_pt = None high_d_opt_val = None if low_d_opt_pt is not None: high_d_opt_pt = np.tile(low_d_opt_pt, num_groups+1)[0:domain_dim] high_d_opt_val = high_d_func(high_d_opt_pt) elif low_d_opt_val is not None: high_d_opt_val = num_groups * low_d_opt_val # Return func_caller = get_euc_function_caller_from_function(high_d_func, high_d_domain_bounds, vectorised=False, opt_val=high_d_opt_val, opt_pt=high_d_opt_pt, **kwargs) return func_caller def get_high_d_function_caller_from_low_d_func_caller(domain_dim, low_d_func_caller, **kwargs): """ Gets a high dimensional function caller from a low dimensional one. """ return get_high_d_function_caller_from_low_d_func(domain_dim, low_d_func_caller.func, low_d_func_caller.domain.bounds, low_d_func_caller.opt_val, low_d_func_caller.raw_opt_pt, **kwargs) def get_high_d_function_caller_from_description(descr, **kwargs): """ Gets a high dimensional function caller from the description. """ segments = descr.split('-') domain_dim = int(segments[1]) descr_to_func_dict = {'hartmann': lambda: get_hartmann_function_caller(6,), 'branin': get_branin_function_caller, 'currinexp': get_currin_exp_function_caller, 'park1': get_park1_function_caller, 'park2': get_park2_function_caller, 'borehole': get_borehole_function_caller, 'shekel': get_shekel_function_caller} low_d_func_caller = descr_to_func_dict[segments[0].lower()](**kwargs) return get_high_d_function_caller_from_low_d_func_caller(domain_dim, low_d_func_caller, **kwargs) # Finally, one very convenient wrapper. def get_syn_function_caller_from_name(function_name, **kwargs): """ A very convenient wrapper so that you can just get the function from the name. """ #pylint: disable=too-many-return-statements if function_name.lower() == 'hartmann3': return get_hartmann_function_caller(3, descr=function_name, **kwargs) elif function_name.lower() == 'hartmann6': return get_hartmann_function_caller(6, descr=function_name, **kwargs) elif function_name.lower() == 'currinexp': return get_currin_exp_function_caller(descr=function_name, **kwargs) elif function_name.lower() == 'branin': return get_branin_function_caller(descr=function_name, **kwargs) elif function_name.lower() == 'borehole': return get_borehole_function_caller(descr=function_name, **kwargs) elif function_name.lower() == 'shekel': return get_shekel_function_caller(descr=function_name, **kwargs) elif function_name.lower() == 'park1': return get_park1_function_caller(descr=function_name, **kwargs) elif function_name.lower() == 'park2': return get_park2_function_caller(descr=function_name, **kwargs) else: return get_high_d_function_caller_from_description(descr=function_name, **kwargs)

42.976676

90

0.617462

""" A collection of utilities for MF-GP Bandits. -- kandasamy@cs.cmu.edu """ # pylint: disable=import-error # pylint: disable=no-member # pylint: disable=invalid-name # pylint: disable=relative-import # pylint: disable=super-on-old-class import numpy as np # Local imports from ..opt.function_caller import get_euc_function_caller_from_function # Hartmann Functions --------------------------------------------------------------------- def hartmann(x, alpha, A, P, max_val=np.inf): """ Computes the hartmann function for any given A and P. """ log_sum_terms = (A * (P - x)**2).sum(axis=1) return min(max_val, alpha.dot(np.exp(-log_sum_terms))) def _get_hartmann_data(domain_dim): """ Returns A and P for the 3D hartmann function. """ # pylint: disable=bad-whitespace if domain_dim == 3: A = np.array([[3.0, 10, 30], [0.1, 10, 35], [3.0, 10, 30], [0.1, 10, 35]], dtype=np.float64) P = 1e-4 * np.array([[3689, 1170, 2673], [4699, 4387, 7470], [1091, 8732, 5547], [ 381, 5743, 8828]], dtype=np.float64) alpha = np.array([1.0, 1.2, 3.0, 3.2]) domain = [[0, 1]] * 3 opt_pt = np.array([0.114614, 0.555649, 0.852547]) max_val = 3.86278 elif domain_dim == 6: A = np.array([[ 10, 3, 17, 3.5, 1.7, 8], [0.05, 10, 17, 0.1, 8, 14], [ 3, 3.5, 1.7, 10, 17, 8], [ 17, 8, 0.05, 10, 0.1, 14]], dtype=np.float64) P = 1e-4 * np.array([[1312, 1696, 5569, 124, 8283, 5886], [2329, 4135, 8307, 3736, 1004, 9991], [2348, 1451, 3522, 2883, 3047, 6650], [4047, 8828, 8732, 5743, 1091, 381]], dtype=np.float64) alpha = np.array([1.0, 1.2, 3.0, 3.2]) domain = [[0, 1]] * 6 opt_pt = np.array([0.20169, 0.150011, 0.476874, 0.275332, 0.311652, 0.6573]) max_val = 3.322368 else: raise NotImplementedError('Only implemented in 3 and 6 dimensions.') return A, P, alpha, opt_pt, domain, max_val def get_hartmann_high_d_function_caller(domain_dim, **kwargs): """ Constructs a higher dimensional Hartmann function. """ group_dim = 6 num_groups = int(domain_dim/group_dim) A, P, alpha, l_opt_pt, l_domain_bounds, l_max_val = _get_hartmann_data(group_dim) hartmann_func = lambda x: hartmann(x, alpha, A, P, l_max_val) def _eval_highd_hartmann_func(x): """ Evaluates the higher dimensional hartmann function. """ ret = 0 for j in range(num_groups): ret += hartmann_func(x[j*group_dim:(j+1)*group_dim]) return ret opt_pt = np.tile(l_opt_pt, num_groups+1)[0:domain_dim] opt_val = num_groups * l_max_val domain_bounds = np.tile(np.array(l_domain_bounds).T, num_groups+1).T[0:domain_dim] return get_euc_function_caller_from_function(_eval_highd_hartmann_func, domain_bounds, vectorised=False, opt_pt=opt_pt, opt_val=opt_val, **kwargs) def get_hartmann_high_d_function_caller_from_descr(descr, **kwargs): """ Constructs a high dimensional hartmann function from a string. """ domain_dim = int(descr[8:]) return get_hartmann_high_d_function_caller(domain_dim, **kwargs) def get_hartmann_function_caller(domain_dim, **kwargs): """ Returns a FunctionCaller object for the hartmann function. """ A, P, alpha, opt_pt, domain_bounds, max_val = _get_hartmann_data(domain_dim) hartmann_func = lambda x: hartmann(x, alpha, A, P, max_val) return get_euc_function_caller_from_function(hartmann_func, domain_bounds, vectorised=False, opt_pt=opt_pt, opt_val=max_val, **kwargs) # Hartmann Functions end here ------------------------------------------------------------ # Shekel Function ------------------------------------------------------------------------ def shekel(x, C, beta, max_val=np.inf): """ Computes the Shekel function for the given C and beta. """ inv_terms = ((C.T - x)**2).sum(axis=1) + beta return min(max_val, (1/inv_terms).sum()) def _get_shekel_data(): """ Returns the C, beta parameters and optimal values for the shekel function. """ C = [[4, 1, 8, 6, 3, 2, 5, 8, 6, 7], [4, 1, 8, 6, 7, 9, 3, 1, 2, 3], [4, 1, 8, 6, 3, 2, 5, 8, 6, 7], [4, 1, 8, 6, 7, 9, 3, 1, 2, 3]] C = np.array(C, dtype=np.double) beta = 0.1 * np.array([1, 2, 2, 4, 4, 6, 3, 7, 5, 5], dtype=np.double) opt_pt = np.array([4, 4, 4, 4], dtype=np.double) opt_val = shekel(opt_pt, C, beta) domain_bounds = [[0, 10]] * 4 return C, beta, opt_pt, domain_bounds, opt_val def get_shekel_function_caller(**kwargs): """ Returns a FunctionCaller object for the hartmann function. """ C, beta, opt_pt, domain_bounds, opt_val = _get_shekel_data() shekel_func = lambda x: shekel(x, C, beta, opt_val) return get_euc_function_caller_from_function(shekel_func, domain_bounds, vectorised=False, opt_pt=opt_pt, opt_val=opt_val, **kwargs) # Shekel function ends here -------------------------------------------------------------- # Currin Exponential Function ------------------------------------------------------------ def currin_exp(x, alpha): """ Computes the currin exponential function. """ x1 = x[0] x2 = x[1] val_1 = 1 - alpha * np.exp(-1/(2 * x2)) val_2 = (2300*x1**3 + 1900*x1**2 + 2092*x1 + 60) / (100*x1**3 + 500*x1**2 + 4*x1 + 20) return val_1 * val_2 def get_currin_exp_function_caller(**kwargs): """ Returns a FunctionCaller object for the Currin Exponential function. """ currin_exp_func = lambda x: currin_exp(x, 1) opt_val = 13.798650 opt_pt = None domain_bounds = np.array([[0, 1], [0, 1]]) return get_euc_function_caller_from_function(currin_exp_func, domain_bounds=domain_bounds, vectorised=False, opt_val=opt_val, opt_pt=opt_pt, **kwargs) # Branin Function ------------------------------------------------------------------------ def branin(x, a, b, c, r, s, t): """ Computes the Branin function. """ x1 = x[0] x2 = x[1] neg_ret = a * (x2 - b*x1**2 + c*x1 - r)**2 + s*(1-t)*np.cos(x1) + s return -neg_ret def _get_branin_data(): """ Gets the constants for the branin function. """ a = 1 b = 5.1/(4*np.pi**2) c = 5/np.pi r = 6 s = 10 t = 1/(8*np.pi) opt_pt = np.array([np.pi, 2.275]) domain_bounds = np.array([[-5, 10], [0, 15]]) return a, b, c, r, s, t, opt_pt, domain_bounds def get_branin_function_caller(**kwargs): """ Returns a FunctionCaller object for the Branin function. """ a, b, c, r, s, t, opt_pt, domain_bounds = _get_branin_data() branin_func = lambda x: branin(x, a, b, c, r, s, t) opt_val = branin_func(opt_pt) return get_euc_function_caller_from_function(branin_func, domain_bounds=domain_bounds, vectorised=False, opt_val=opt_val, opt_pt=opt_pt, **kwargs) def get_branin_high_d_function_caller(domain_dim, **kwargs): """ Constructs a higher dimensional Hartmann function. """ group_dim = 2 num_groups = int(domain_dim/group_dim) a, b, c, r, s, t, opt_pt_2d, domain_bounds_2d = _get_branin_data() branin_func = lambda x: branin(x, a, b, c, r, s, t) def _eval_highd_branin_func(x): """ Evaluates higher dimensional branin function. """ ret = 0 for j in range(num_groups): ret += branin_func(x[j*group_dim:(j+1)*group_dim]) return ret opt_pt = np.tile(opt_pt_2d, num_groups+1)[0:domain_dim] opt_val = _eval_highd_branin_func(opt_pt) domain_bounds = np.tile(np.array(domain_bounds_2d).T, num_groups+1).T[0:domain_dim] return get_euc_function_caller_from_function(_eval_highd_branin_func, domain_bounds, vectorised=False, opt_pt=opt_pt, opt_val=opt_val, **kwargs) def get_branin_high_d_function_caller_from_descr(descr, **kwargs): """ Constructs a high dimensional hartmann function from a string. """ domain_dim = int(descr[7:]) return get_branin_high_d_function_caller(domain_dim, **kwargs) # Borehole Function ---------------------------------------------------------------------- def borehole(x, z, max_val): """ Computes the Bore Hole function. """ # pylint: disable=bad-whitespace rw = x[0] r = x[1] Tu = x[2] Hu = x[3] Tl = x[4] Hl = x[5] L = x[6] Kw = x[7] # Compute high fidelity function frac2 = 2*L*Tu/(np.log(r/rw) * rw**2 * Kw) f2 = min(max_val, 2 * np.pi * Tu * (Hu - Hl)/(np.log(r/rw) * (1 + frac2 + Tu/Tl))) # Compute low fidelity function f1 = 5 * Tu * (Hu - Hl)/(np.log(r/rw) * (1.5 + frac2 + Tu/Tl)) # Compute final output return f2*z + f1*(1-z) def get_borehole_function_caller(**kwargs): """ Returns a FunctionCaller object for the Borehold function. """ opt_val = 309.523221 opt_pt = None borehole_func = lambda x: borehole(x, 1, opt_val) domain_bounds = [[0.05, 0.15], [100, 50000], [63070, 115600], [990, 1110], [63.1, 116], [700, 820], [1120, 1680], [9855, 12045]] return get_euc_function_caller_from_function(borehole_func, domain_bounds, vectorised=False, opt_val=opt_val, opt_pt=opt_pt, **kwargs) # Park1 function ================================================================== def park1(x, max_val=np.inf): """ Computes the park1 function. """ x1 = x[0] x2 = x[1] x3 = x[2] x4 = x[3] ret1 = (x1/2) * (np.sqrt(1 + (x2 + x3**2)*x4/(x1**2)) - 1) ret2 = (x1 + 3*x4) * np.exp(1 + np.sin(x3)) return min(ret1 + ret2, max_val) def get_park1_function_caller(**kwargs): """ Returns the park1 function caller. """ opt_val = 25.5872304 opt_pt = None func = lambda x: park1(x, opt_val) domain_bounds = [[0, 1]] * 4 return get_euc_function_caller_from_function(func, domain_bounds, vectorised=False, opt_val=opt_val, opt_pt=opt_pt, **kwargs) # Park2 function ================================================================== def park2(x, max_val=np.inf): """ Comutes the park2 function """ x1 = x[0] x2 = x[1] x3 = x[2] x4 = x[3] ret = (2.0/3.0) * np.exp(x1 + x2) - x4*np.sin(x3) + x3 return min(ret, max_val) def get_park2_function_caller(**kwargs): """ Returns function caller for park2. """ opt_val = 5.925698 opt_pt = None func = lambda x: park2(x, opt_val) domain_bounds = [[0, 1]] * 4 return get_euc_function_caller_from_function(func, domain_bounds, vectorised=False, opt_val=opt_val, opt_pt=opt_pt, **kwargs) def get_high_d_function_from_low_d(domain_dim, group_dim, low_d_func): """ Constructs a higher dimensional Hartmann function. """ num_groups = int(domain_dim/group_dim) def _eval_highd_func(x): """ Evaluates the higher dimensional function. """ ret = 0 for j in range(num_groups): ret += low_d_func(x[j*group_dim: (j+1)*group_dim]) return ret return _eval_highd_func, num_groups def get_high_d_function_caller_from_low_d_func(domain_dim, low_d_func, low_d_domain_bounds, low_d_opt_val, low_d_opt_pt, **kwargs): """ Gets a low dimensional function caller from a high dimensional one. """ group_dim = len(low_d_domain_bounds) high_d_func, num_groups = get_high_d_function_from_low_d(domain_dim, group_dim, low_d_func) high_d_domain_bounds = np.tile(np.array(low_d_domain_bounds).T, num_groups+1).T[0:domain_dim] high_d_opt_pt = None high_d_opt_val = None if low_d_opt_pt is not None: high_d_opt_pt = np.tile(low_d_opt_pt, num_groups+1)[0:domain_dim] high_d_opt_val = high_d_func(high_d_opt_pt) elif low_d_opt_val is not None: high_d_opt_val = num_groups * low_d_opt_val # Return func_caller = get_euc_function_caller_from_function(high_d_func, high_d_domain_bounds, vectorised=False, opt_val=high_d_opt_val, opt_pt=high_d_opt_pt, **kwargs) return func_caller def get_high_d_function_caller_from_low_d_func_caller(domain_dim, low_d_func_caller, **kwargs): """ Gets a high dimensional function caller from a low dimensional one. """ return get_high_d_function_caller_from_low_d_func(domain_dim, low_d_func_caller.func, low_d_func_caller.domain.bounds, low_d_func_caller.opt_val, low_d_func_caller.raw_opt_pt, **kwargs) def get_high_d_function_caller_from_description(descr, **kwargs): """ Gets a high dimensional function caller from the description. """ segments = descr.split('-') domain_dim = int(segments[1]) descr_to_func_dict = {'hartmann': lambda: get_hartmann_function_caller(6,), 'branin': get_branin_function_caller, 'currinexp': get_currin_exp_function_caller, 'park1': get_park1_function_caller, 'park2': get_park2_function_caller, 'borehole': get_borehole_function_caller, 'shekel': get_shekel_function_caller} low_d_func_caller = descr_to_func_dict[segments[0].lower()](**kwargs) return get_high_d_function_caller_from_low_d_func_caller(domain_dim, low_d_func_caller, **kwargs) # Finally, one very convenient wrapper. def get_syn_function_caller_from_name(function_name, **kwargs): """ A very convenient wrapper so that you can just get the function from the name. """ #pylint: disable=too-many-return-statements if function_name.lower() == 'hartmann3': return get_hartmann_function_caller(3, descr=function_name, **kwargs) elif function_name.lower() == 'hartmann6': return get_hartmann_function_caller(6, descr=function_name, **kwargs) elif function_name.lower() == 'currinexp': return get_currin_exp_function_caller(descr=function_name, **kwargs) elif function_name.lower() == 'branin': return get_branin_function_caller(descr=function_name, **kwargs) elif function_name.lower() == 'borehole': return get_borehole_function_caller(descr=function_name, **kwargs) elif function_name.lower() == 'shekel': return get_shekel_function_caller(descr=function_name, **kwargs) elif function_name.lower() == 'park1': return get_park1_function_caller(descr=function_name, **kwargs) elif function_name.lower() == 'park2': return get_park2_function_caller(descr=function_name, **kwargs) else: return get_high_d_function_caller_from_description(descr=function_name, **kwargs)

0

93c3a0380c312370c881e10fbe697c1f82ff806e

8,417

py

Python

bindings/pydairlib/lcm/process_lcm_log.py

Brian-Acosta/dairlib

88da55d6e4378b93a787f3587d08b8a60f2f03f0

[ "BSD-3-Clause" ]

32

2019-04-15T03:10:26.000Z

2022-03-28T17:27:03.000Z

bindings/pydairlib/lcm/process_lcm_log.py

Brian-Acosta/dairlib

88da55d6e4378b93a787f3587d08b8a60f2f03f0

[ "BSD-3-Clause" ]

157

2019-02-21T03:13:57.000Z

2022-03-09T19:13:59.000Z

bindings/pydairlib/lcm/process_lcm_log.py

Brian-Acosta/dairlib

88da55d6e4378b93a787f3587d08b8a60f2f03f0

[ "BSD-3-Clause" ]

22

2019-03-02T22:31:42.000Z

2022-03-10T21:28:50.000Z

import dairlib import drake import numpy as np # Class to easily convert list of lcmt_osc_tracking_data_t to numpy arrays

38.967593

116

0.667578

import dairlib import drake import numpy as np # Class to easily convert list of lcmt_osc_tracking_data_t to numpy arrays class lcmt_osc_tracking_data_t: def __init__(self): self.t = [] self.y_dim = 0 self.name = "" self.is_active = [] self.y = [] self.y_des = [] self.error_y = [] self.ydot = [] self.ydot_des = [] self.error_ydot = [] self.yddot_des = [] self.yddot_command = [] self.yddot_command_sol = [] def append(self, msg, t): self.t.append(t) self.is_active.append(msg.is_active) self.y.append(msg.y) self.y_des.append(msg.y_des) self.error_y.append(msg.error_y) self.ydot.append(msg.ydot) self.ydot_des.append(msg.ydot_des) self.error_ydot.append(msg.error_ydot) self.yddot_des.append(msg.yddot_des) self.yddot_command.append(msg.yddot_command) self.yddot_command_sol.append(msg.yddot_command_sol) def convertToNP(self): self.t = np.array(self.t) self.is_active = np.array(self.is_active) self.y = np.array(self.y) self.y_des = np.array(self.y_des) self.error_y = np.array(self.error_y) self.ydot = np.array(self.ydot) self.ydot_des = np.array(self.ydot_des) self.error_ydot = np.array(self.error_ydot) self.yddot_des = np.array(self.yddot_des) self.yddot_command = np.array(self.yddot_command) self.yddot_command_sol = np.array(self.yddot_command_sol) def process_log(log, pos_map, vel_map, act_map, controller_channel): t_x = [] t_u = [] t_controller_switch = [] t_contact_info = [] fsm = [] q = [] v = [] u_meas = [] u = [] kp = [] kd = [] t_pd = [] estop_signal = [] switch_signal = [] osc_debug = dict() contact_forces = [[], [], [], []] # Allocate space for all 4 point contacts contact_info_locs = [[], [], [], []] cassie_out = [] # Cassie out types osc_output = [] u_pd = [] t_u_pd = [] t_lcmlog_u = [] full_log = dict() channel_to_type_map = dict() unknown_types = set() known_lcm_types = [dairlib.lcmt_robot_output, dairlib.lcmt_cassie_out, dairlib.lcmt_controller_switch, dairlib.lcmt_osc_output, dairlib.lcmt_pd_config, dairlib.lcmt_robot_input, drake.lcmt_contact_results_for_viz, dairlib.lcmt_contact, dairlib.lcmt_input_supervisor_status] osc_debug_channels = ['OSC_DEBUG_WALKING', 'OSC_DEBUG_RUNNING', 'OSC_DEBUG_STANDING', 'OSC_DEBUG_JUMPING'] # osc_debug_channels = ['OSC_DEBUG_WALKING', 'OSC_DEBUG_RUNNING', 'OSC_DEBUG_JUMPING'] state_feedback_channels = ['CASSIE_STATE_SIMULATION', 'CASSIE_STATE_DISPATCHER'] for event in log: if event.channel not in full_log and event.channel not in unknown_types: for lcmtype in known_lcm_types: try: lcmtype.decode(event.data) channel_to_type_map[event.channel] = lcmtype except ValueError: continue if event.channel in channel_to_type_map: full_log[event.channel] = [] else: unknown_types.add(event.channel) if event.channel in full_log: full_log[event.channel].append(channel_to_type_map[event.channel].decode(event.data)) if event.channel in state_feedback_channels: msg = dairlib.lcmt_robot_output.decode(event.data) q_temp = [[] for i in range(len(msg.position))] v_temp = [[] for i in range(len(msg.velocity))] u_temp = [[] for i in range(len(msg.effort))] for i in range(len(q_temp)): q_temp[pos_map[msg.position_names[i]]] = msg.position[i] for i in range(len(v_temp)): v_temp[vel_map[msg.velocity_names[i]]] = msg.velocity[i] for i in range(len(u_temp)): u_temp[act_map[msg.effort_names[i]]] = msg.effort[i] q.append(q_temp) v.append(v_temp) u_meas.append(u_temp) t_x.append(msg.utime / 1e6) if event.channel == "CASSIE_INPUT" or event.channel == controller_channel: msg = dairlib.lcmt_robot_input.decode(event.data) u.append(msg.efforts) t_u.append(msg.utime / 1e6) if event.channel == "PD_CONTROL": msg = dairlib.lcmt_robot_input.decode(event.data) u_pd.append(msg.efforts) t_u_pd.append(msg.utime / 1e6) if event.channel == "INPUT_SWITCH": msg = dairlib.lcmt_controller_switch.decode(event.data) switch_signal.append(msg.channel == "OSC_STANDING") t_controller_switch.append(msg.utime / 1e6) if event.channel == "PD_CONFIG": msg = dairlib.lcmt_pd_config.decode(event.data) kp.append(msg.kp) kd.append(msg.kd) t_pd.append(msg.timestamp / 1e6) if event.channel == "CASSIE_OUTPUT_ECHO": msg = dairlib.lcmt_cassie_out.decode(event.data) cassie_out.append(msg) if event.channel in osc_debug_channels: msg = dairlib.lcmt_osc_output.decode(event.data) t_lcmlog_u.append(event.timestamp / 1e6) osc_output.append(msg) num_osc_tracking_data = len(msg.tracking_data) for i in range(num_osc_tracking_data): if msg.tracking_data[i].name not in osc_debug: osc_debug[msg.tracking_data[i].name] = lcmt_osc_tracking_data_t() osc_debug[msg.tracking_data[i].name].append(msg.tracking_data[i], msg.utime / 1e6) fsm.append(msg.fsm_state) if event.channel == "CASSIE_CONTACT_DRAKE" or event.channel == "CASSIE_CONTACT_MUJOCO": # Need to distinguish between front and rear contact forces # Best way is to track the contact location and group by proximity msg = drake.lcmt_contact_results_for_viz.decode(event.data) t_contact_info.append(msg.timestamp / 1e6) num_left_contacts = 0 num_right_contacts = 0 for i in range(msg.num_point_pair_contacts): if "toe_left" in msg.point_pair_contact_info[i].body2_name: if(num_left_contacts >= 2): continue contact_info_locs[num_left_contacts].append( msg.point_pair_contact_info[i].contact_point) contact_forces[num_left_contacts].append( msg.point_pair_contact_info[i].contact_force) num_left_contacts += 1 elif "toe_right" in msg.point_pair_contact_info[i].body2_name: if(num_right_contacts >= 2): continue contact_info_locs[2 + num_right_contacts].append( msg.point_pair_contact_info[i].contact_point) contact_forces[2 + num_right_contacts].append( msg.point_pair_contact_info[i].contact_force) num_right_contacts += 1 while num_left_contacts != 2: contact_forces[num_left_contacts].append((0.0, 0.0, 0.0)) contact_info_locs[num_left_contacts].append((0.0, 0.0, 0.0)) num_left_contacts += 1 while num_right_contacts != 2: contact_forces[2 + num_right_contacts].append((0.0, 0.0, 0.0)) contact_info_locs[2 + num_right_contacts].append((0.0, 0.0, 0.0)) num_right_contacts += 1 # Convert into numpy arrays t_x = np.array(t_x) t_u = np.array(t_u) t_lcmlog_u = np.array(t_lcmlog_u) t_controller_switch = np.array(t_controller_switch) t_contact_info = np.array(t_contact_info) t_pd = np.array(t_pd) fsm = np.array(fsm) q = np.array(q) v = np.array(v) u_meas = np.array(u_meas) u = np.array(u) u_pd = np.array(u_pd) kp = np.array(kp) kd = np.array(kd) estop_signal = np.array(estop_signal) switch_signal = np.array(switch_signal) contact_forces = np.array(contact_forces) contact_info_locs = np.array(contact_info_locs) for i in range(contact_info_locs.shape[1]): # Swap front and rear contacts if necessary # Order will be front contact in index 1 if contact_info_locs[0, i, 0] > contact_info_locs[1, i, 0]: contact_forces[[0, 1], i, :] = contact_forces[[1, 0], i, :] contact_info_locs[[0, 1], i, :] = contact_info_locs[[1, 0], i, :] if contact_info_locs[2, i, 0] > contact_info_locs[3, i, 0]: contact_forces[[2, 3], i, :] = contact_forces[[3, 2], i, :] contact_info_locs[[2, 3], i, :] = contact_info_locs[[3, 2], i, :] for key in osc_debug: osc_debug[key].convertToNP() x = np.hstack((q, v)) # combine into state vector return x, u_meas, t_x, u, t_u, contact_forces, contact_info_locs, \ t_contact_info, osc_debug, fsm, estop_signal, \ switch_signal, t_controller_switch, t_pd, kp, kd, cassie_out, u_pd, \ t_u_pd, osc_output, full_log, t_lcmlog_u

8,163

10

119

4893f6a866e8ab79f5abd9ffd38994d1c37af014

14,032

py

Python

navigation_old.py

mferg00/soccer-robot-ai

e25b685304fe671a0cccc17d666e9d22dc53e806

[ "Apache-2.0" ]

null

navigation_old.py

mferg00/soccer-robot-ai

e25b685304fe671a0cccc17d666e9d22dc53e806

[ "Apache-2.0" ]

null

navigation_old.py

mferg00/soccer-robot-ai

e25b685304fe671a0cccc17d666e9d22dc53e806

[ "Apache-2.0" ]

null

import RPi.GPIO as GPIO from drive import Drive from dribbler import Dribbler from field import Field from enum import Enum from kicker import Kicker import time import numpy as np ######### # ENUMS # # ############ # FUNCTIONS # these should be very generic ########### # VARIABLES # used for condition checking or generic functions within navigation class BALL_IN_DRIBBLER_DIST = 9 # min distance when ball is in the dribbler BALL_IN_DRIBBLER_ANGLE = 15 # ball must be within +-28 deg of fov to be in dribbler (32 is max) GOAL_DIST = 90 # distance to stop at to shoot for goal GOAL_ANGLE = 3 # goal must be within +-3 deg of fov to be in dribbler OBSTACLE_DIST = 30 # min dist to begin circ,ing object MIN_SPEED = 35 # the speed the robot will be at when its target is very close ############# # NAV CLASS # #

30.438178

153

0.553521

import RPi.GPIO as GPIO from drive import Drive from dribbler import Dribbler from field import Field from enum import Enum from kicker import Kicker import time import numpy as np ######### # ENUMS # # class state(Enum): none = 1 ball_search = 2 go_to_ball = 3 goal_search = 4 go_to_goal = 5 shoot_ball = 6 class search(Enum): none = 1 spin = 2 go_to_obstacle = 3 circle_obstacle = 4 next_obstacle = 5 ############ # FUNCTIONS # these should be very generic def within_angle(heading, limit): if(heading <= limit and heading >= -limit): return True return False def check_speed(speed): if speed > 100: speed = 100 if speed < -100: speed = -100 return speed def cap_ran(ran): if ran is None: return None if(ran < 5): ran = 5 elif(ran > 250): ran = 250 return ran ########### # VARIABLES # used for condition checking or generic functions within navigation class BALL_IN_DRIBBLER_DIST = 9 # min distance when ball is in the dribbler BALL_IN_DRIBBLER_ANGLE = 15 # ball must be within +-28 deg of fov to be in dribbler (32 is max) GOAL_DIST = 90 # distance to stop at to shoot for goal GOAL_ANGLE = 3 # goal must be within +-3 deg of fov to be in dribbler OBSTACLE_DIST = 30 # min dist to begin circ,ing object MIN_SPEED = 35 # the speed the robot will be at when its target is very close ############# # NAV CLASS # # class Navigation(): def __init__(self): # this is only changed once the ball is kicked self.switch_goal = False self.prev_state = state.none self.prev_ball = -1 self.prev_goal = -1 # CONDITIONS self.ball_in_dribbler = False self.ball_found = False self.goal_found = False self.goal_aligned = False # STATES self.state = state.none self.search = search.none # OBJECTS self.drive_sys = Drive() self.dribbler = Dribbler() self.field = Field() self.kicker = Kicker() # MOTOR pwm self.left_motor = 0 self.right_motor = 0 # range/headings self.obs_range = [None, None, None] self.obs_heading = [None, None, None] self.ball_range = None self.ball_heading = None self.goal_range = None self.goal_heading = None #################### # GENERIC FUNCTIONS # # input: left and right motor pwms # output: pwm value that gets larger the sharper the robot is turning # WORK IN PROGRESS def choose_drib_speed(self): # find ratio: -1 is spinning on spot, 1 is going straight ratio = 0 if(self.left_motor == 0 or self.right_motor == 0): ratio = 0 else: ratio = min(self.left_motor, self.right_motor)/max(self.left_motor, self.right_motor) # convert ratio to: 0 is straight, 2 is spinning on spot ratio = -ratio + 1 # if motor is going forward (ratio = 0), dribbler is at 50 pwm # if motor is doing a full spin (ratio = 2), dribbler is at 90 pwm speed = 60 + (ratio * 100) return check_speed(speed) # input: object heading/range # output: drive and center towards object, with speed slowing down based on proximity # example: object at 100cm, -16deg: # left_motor: 50 + 100/8 - -16 = 78.5 # right_motor: 50 + 100/8 + -16 = 46.5 def goto_object_simple(self, speed, ran, head): self.right_motor = check_speed( (MIN_SPEED * speed) + (ran / 5) - (head) ) self.left_motor = check_speed( (MIN_SPEED * speed) + (ran / 5) + (head) ) self.drive_sys.drive(self.left_motor, self.right_motor) # input: object target # output: drive towards object and avoid obstacles prev_heading = -999 def goto_object(self, speed=1, object='ball'): ''' def smooth(heading): if self.prev_heading == -999: self.prev_heading = heading else: if abs(self.prev_heading - heading) > 5: self.prev_heading -= np.sign(self.prev_heading)*5 else: self.prev_heading = heading return self.prev_heading''' if(self.obs_range[0] is not None and self.obs_range[0] <= self.ball_range): self.field.change_state(self.state) target_heading = self.field.update(self.obs_range, self.obs_heading, self.ball_range, self.ball_heading, self.goal_range, self.goal_heading) if object == 'ball': target_range = self.ball_range elif object == 'goal': target_range = self.goal_range else: return else: if object == 'ball': target_range = self.ball_range target_heading = self.ball_heading elif object == 'goal': target_range = self.goal_range target_heading = self.goal_heading self.goto_object_simple(speed, target_range, target_heading) def stop(self): self.drive_sys.stop() self.dribbler.stop() GPIO.cleanup() #################### # UPDATE FUNCTION # # input: vision feed values # output: true if goal needs to be switched def update(self, obs, ball, goal): # return true if goal needs to be switched, so vision can be changed from main function if(self.switch_goal): self.switch_goal = False return True # VISION INFO self.obs_range = [cap_ran(obs[0][0]), cap_ran(obs[1][0]), cap_ran(obs[2][0])] self.obs_heading = [obs[0][1], obs[1][1], obs[2][1]] self.ball_range = cap_ran(ball[0]) self.ball_heading = ball[1] self.goal_range = cap_ran(goal[0]) self.goal_heading = goal[1] # ACT BASED ON VISION INFO self.decide_conditions() self.decide_state() self.decide_action() return False ################## # DECIDE FUNCTIONS # decides what to do based on the data from update() # input: vision data # output: condition bool variables dribbler_counter = 0 def decide_conditions(self): # if ball is seen if(self.ball_range is not None): self.ball_found = True self.prev_ball = np.sign(self.ball_heading) # if ball is within dribbler range/angle if(self.ball_range < BALL_IN_DRIBBLER_DIST and within_angle(self.ball_heading, BALL_IN_DRIBBLER_ANGLE)): self.ball_in_dribbler = True else: self.ball_in_dribbler = False else: self.ball_found = False # if goal is seen if(self.goal_range is not None): self.goal_found = True self.prev_goal = np.sign(self.goal_heading) #if goal is within shooting range/angle if(self.goal_range < GOAL_DIST and within_angle(self.goal_heading, GOAL_ANGLE)): self.goal_aligned = True else: self.goal_aligned = False else: self.goal_found = False def change_state(self, state): self.state = state # input: condition variables # output: state value def decide_state(self): if(not self.ball_found and not self.ball_in_dribbler): self.state = state.ball_search elif(self.ball_found and not self.ball_in_dribbler): self.state = state.go_to_ball elif(self.ball_found and self.ball_in_dribbler and not self.goal_found): self.state = state.goal_search if(self.prev_state != self.state): self.drive_sys.stop() time.sleep(0.25) elif(self.ball_found and self.ball_in_dribbler and self.goal_found and not self.goal_aligned): self.state = state.go_to_goal elif(self.ball_found and self.ball_in_dribbler and self.goal_found and self.goal_aligned): self.state = state.shoot_ball else: self.state = state.ball_search self.prev_state = self.state # print(self.state) # input: state/search value # output: appropriate function def decide_action(self): if(self.state == state.ball_search): self.ball_search() else: self.search_lock = False if(self.state == state.go_to_ball): self.go_to_ball() if(self.state == state.goal_search): self.goal_search() if(self.state == state.go_to_goal): self.go_to_goal() if(self.state == state.shoot_ball): self.shoot_ball() # if state == none else: pass ################## # ACTION FUNCTIONS # # input: search value # output: appropriate ball searching method search_lock = False def ball_search(self): if(not self.search_lock): if(self.search == search.none): self.search = search.spin if(self.search == search.spin): # will not be true until until spin is complete #print("searching for ball") if(self.drive_sys.spin(speed=30, direction=self.prev_ball, radius=0, cycles=10)): self.search = search.go_to_obstacle if(self.search == search.go_to_obstacle): self.search_lock = True if(self.obs_range[0] is None): #print("searching for obstacle") self.drive_sys.spin(speed=30, direction=self.prev_ball, radius=0, cycles=None) else: if(self.obs_range[0] > OBSTACLE_DIST): #print("goi8ng to obstacle") self.goto_object_simple(1, self.obs_range[0], self.obs_heading[0]) else: self.search = search.circle_obstacle if(self.search == search.circle_obstacle): #print("circling obstacle") # will not be true until circle is complete if(self.circle_obstacle(adjust=100)): #print("CIRCLE OBSTACLE COMPLETE") # if after all that the ball is not found, restart the cycle again self.search = search.none self.search_lock = False orientate = True spin_out_timer = 0 right_wheel = 40 left_wheel = 30 prev_state = 0 adjust_counter = 0 # input: largest obstacle range/heading # output: circling obstacle def circle_obstacle(self, adjust=10): # count how many times the robot has to adjust based on if it saw the object if(self.obs_range[0] is None and self.prev_state is not None): self.adjust_counter += 1 self.prev_state = self.obs_range[0] # if it has reached the limit, reset everything for the next time the function is called if(self.adjust_counter >= adjust): self.orientate = True self.spin_out_timer = 0 self.right_wheel = 40 self.left_wheel = 30 self.prev_state = 0 self.adjust_counter = 0 self.drive_sys.stop() return True # if the robot needs to oreintate itself if(self.orientate and self.obs_range[0] is not None): self.drive_sys.drive(-30, 30) self.spin_out_timer = 0 # else if it needs to circle else: self.orientate = False if self.obs_range[0] is not None: self.spin_out_timer = 0 self.right_wheel = 40 self.left_wheel = 30 if(self.obs_range[0] is None): self.spin_out_timer += 1 self.right_wheel += 0.4 self.left_wheel -= 0.4 # spin in if(self.spin_out_timer >= 10): self.drive_sys.drive(self.right_wheel, self.left_wheel) # spin out if(self.spin_out_timer < 10): self.drive_sys.drive(-40, 40) return False # input: ball range/heading, ball_in_dribbler variable # output: driving to ball, turning dribbler on if in range # WILL DRIVE STRAIGHT TOWARDS BALL, IGNORING OPBSTACLES def go_to_ball(self): # self.goto_object_simple(1, self.ball_range, self.ball_heading) # REPLACE ^ WITH: self.goto_object(speed=1, object='ball') if(self.ball_range < 20): self.dribbler.start(95) else: self.dribbler.stop() # input: # output: turning in a circle without losing ball def goal_search(self): self.dribbler.start(90) self.drive_sys.spin(speed=20, direction=self.prev_goal, radius=10, cycles=None) def go_to_goal(self): self.dribbler.start(95) self.goto_object_simple(0.65, self.goal_range, self.goal_heading) # REPLACE ^ WITH: # self.goto_object(speed=0.65, object='goal') def shoot_ball(self): self.dribbler.stop() self.kicker.kick() self.drive_sys.stop() self.switch_goal = True

9,270

3,752

149

e8cc4bd94d2a885ce94833f097eea32502e6fb37

5,842

py

Python

DataMining/weather/cylinders.py

navijo/FlOYBD

beb4fb32598e955ce3b47ad647452c15a87cfae8

[ "MIT" ]

null

DataMining/weather/cylinders.py

navijo/FlOYBD

beb4fb32598e955ce3b47ad647452c15a87cfae8

[ "MIT" ]

7

2020-03-24T15:55:32.000Z

2021-08-23T20:43:13.000Z

DataMining/weather/cylinders.py

navijo/FlOYBD

beb4fb32598e955ce3b47ad647452c15a87cfae8

[ "MIT" ]

3

2017-07-26T11:46:05.000Z

2018-04-29T12:07:59.000Z

import simplekml import json from polycircles import polycircles import time from subprocess import call ''' https://github.com/LiquidGalaxyLAB/ViewYourData/blob/master/VYD_Project/VYD/Utils/PresentationManager/cylinder_generator.py https://developers.google.com/maps/documentation/geocoding/intro?hl=es-419 '''

40.853147

156

0.626498

import simplekml import json from polycircles import polycircles import time from subprocess import call class CylindersKml(object): def __init__(self, name, data): self.name = name self.data = data self.kml_var = simplekml.Kml() def makeKML(self): current_milli_time = int(round(time.time())) self.parseData() self.saveKml(current_milli_time) #self.sendKml(current_milli_time) def parseData(self): for element in self.data: if(not element['description'][0]==None and not element['description'][1]==None): self.newCylinder(element['name'], element['description'], element['coordinates'], element['extra']) self.newPointer(element['name'], element['description'], element['coordinates'], element['extra']) def newPointer(self, name, description, coordinates, extra): pointer_max = self.kml_var.newpoint(name=str(description[0])+ u'\u2103') pointer_min = self.kml_var.newpoint(name=str(description[1])+ u'\u2103') self.generatePointer(pointer_max, description[0], coordinates, 'max') self.generatePointer(pointer_min, description[1], coordinates, 'min') if extra: print ('There is extra !') def generatePointer(self, point, temp, coordinates, flag): point.altitudemode = 'relativeToGround' point.gxballoonvisibility = 0 point.style.iconstyle.scale = 0 point.style.labelstyle.scale = 1 point.style.balloonstyle.displaymode = 'hide' if flag == 'min': point.style.labelstyle.color = simplekml.Color.lightblue point.coords = [(float(coordinates['lng'])-0.025, float(coordinates['lat'])-0.025, 2200*int(temp))] elif flag == 'max': point.style.labelstyle.color = simplekml.Color.red point.coords = [(float(coordinates['lng']), float(coordinates['lat']), 2200*int(temp))] def newCylinder(self, name, description, coordinates, extra): shape_polycircle_max = self.kml_var.newmultigeometry(name=name+'-max') shape_polycircle_min = self.kml_var.newmultigeometry(name=name+'-min') self.generateCylinder(shape_polycircle_max, description[0], coordinates, 'max') self.generateCylinder(shape_polycircle_min, description[1], coordinates, 'min') if extra: print ('There is extra !') def generateCylinder(self, shape, temp, coordinates, flag): if flag == 'min': polycircle = polycircles.Polycircle(latitude=float(coordinates['lat'])-0.025, longitude=float(coordinates['lng'])-0.025, radius=1000, number_of_vertices=100) elif flag == 'max': polycircle = polycircles.Polycircle(latitude=float(coordinates['lat']), longitude=float(coordinates['lng']), radius=1000, number_of_vertices=100) latloncircle = polycircle.to_lon_lat() latlonaltcircle = [] polygon_circle = [] multiplier = 2000 temperature = int(temp) # 'Pal' cap a dalt i cercle al final del pal (a dalt de tot) for element in latloncircle: tup = (element[0], element[1], (temperature * multiplier) + 10,) latlonaltcircle.append(tup) # Cilindre (interior / exterior) for element in latloncircle: tup = (element[0], element[1], temperature * multiplier,) latlonaltcircle.append(tup) tup = (element[0], element[1], 0,) latlonaltcircle.append(tup) # Un altre cilindre (interior / exterior ?) for element in latloncircle: tup = (element[0], element[1], 0,) latlonaltcircle.append(tup) tup = (element[0], element[1], temperature * multiplier,) latlonaltcircle.append(tup) for element in latloncircle: tup = (element[0], element[1], 0,) latlonaltcircle.append(tup) pol = shape.newpolygon() pol.outerboundaryis = latlonaltcircle pol.altitudemode = simplekml.AltitudeMode.relativetoground pol.extrude = 5 pol.style.linestyle.width = 5000 polygon_circle.append(polycircle) latlonaltcircle = [] # Cyrcle (tapadera del cilindre) de dalt de tot (interior i exterior) for element in latloncircle: tup = (element[0], element[1], (temperature * multiplier) + 20,) latlonaltcircle.append(tup) pol = shape.newpolygon() pol.outerboundaryis = latlonaltcircle pol.altitudemode = simplekml.AltitudeMode.relativetoground pol.extrude = 5 self.addColor(pol, flag) pol.style.linestyle.width = 5000 polygon_circle.append(polycircle) def addColor(self, polygon, flag): if flag == 'min': polygon.style.polystyle.color = simplekml.Color.blue polygon.style.linestyle.color = simplekml.Color.blue elif flag =='max': polygon.style.polystyle.color = simplekml.Color.red polygon.style.linestyle.color = simplekml.Color.red def saveKml(self,current_milli_time): self.kml_var.save("./cylinders/cylinders_" + self.name+str(current_milli_time)+".kml") def sendKml(self,current_milli_time): command = "sshpass -p 'lqgalaxy' echo 'http://130.206.117.178:8000/cylinders_weather.kml' | ssh lg@192.168.88.242 'cat - > /var/www/html/kmls.txt'" call([command]) ''' https://github.com/LiquidGalaxyLAB/ViewYourData/blob/master/VYD_Project/VYD/Utils/PresentationManager/cylinder_generator.py https://developers.google.com/maps/documentation/geocoding/intro?hl=es-419 '''

5,186

6

315

58700b1ab5a6bb83d87d663e865662eaab49e36a

45,318

py

Python

plugins/bot_cockroach.py

opq-osc/botoy-plugins

8889942cfb5d44c94705b6841cbd821ed6ee6b4b

[ "MIT" ]

20

2021-04-22T14:34:27.000Z

2022-03-22T01:30:25.000Z

plugins/bot_cockroach.py

opq-osc/botoy-plugins

8889942cfb5d44c94705b6841cbd821ed6ee6b4b

[ "MIT" ]

1

2021-05-18T12:09:19.000Z

2021-05-19T04:23:49.000Z

plugins/bot_cockroach.py

opq-osc/botoy-plugins

8889942cfb5d44c94705b6841cbd821ed6ee6b4b

[ "MIT" ]

4

2021-06-13T04:21:09.000Z

2022-01-06T12:13:22.000Z

""" 来点小强+{可选小强数量} 可以艾特一个人使用 """ import base64 import random from io import BytesIO import httpx from botoy import GroupMsg, S from botoy import decorators as deco from botoy.parser import group as gp from PIL import Image 小强 = Image.open( BytesIO( base64.b64decode( """ iVBORw0KGgoAAAANSUhEUgAAAKAAAACgCAYAAACLz2ctAAAgAElEQVR4nOS9CZhdV3UlvM45d3zz q1dzlVRVUkmyRku2PINnMAQMNEOGJp2EpNMNSYD8nQQa0mkSOoHMCSGBJh0ShgRImAzYjhkcsLGN 5UG2LGuwNZVU81xvvPM5/Z1z75PKUkkqyaq08b+/z5ZU9d6799277j57r732PuT1jKJoMhx2Q1S5 wHEAOQBThKAHgCninwlC4AFoBcAATAIgiE0Iof58lWWhhVK4yb8vtRF5Dr4PEobIA1ggBBUhkJJ/ B/AECMSi81quCVzY+V6vM9xkaZjly3ufvF4LnPysH4UPBUIMdVgMEBwBtC17fRygENHFXCp5dA6o 70+Tf59+XGlPhCFqnKvrd8ZnCMDQCH6qTQdrcLSaFOOgODjtISP4BV0ZeS66xEiBQTSArB/hECF4 6Bx40C7g81+y5gKwANxp69ApRbjMB0C+LMtwZasmDoUCleW8R6fAbChwTAgIsrzjaES+T//geMTf Z9FwSN4kn5j3HvWCg0f84DfpRVzYJvAMAuw+32kQsiT4Xgr2sgAgkhtCoggFCngQy/KCEYH02OvW GvSIx8/vB0nihduogCOk1zn/UeQrQqHOqXc2YO+AEAcJNe4POWk5HkZvKDHKLxSACnyEoC4EOqnA 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69.082317

76

0.940553

""" 来点小强+{可选小强数量} 可以艾特一个人使用 """ import base64 import random from io import BytesIO import httpx from botoy import GroupMsg, S from botoy import decorators as deco from botoy.parser import group as gp from PIL import Image 小强 = Image.open( BytesIO( base64.b64decode( """ iVBORw0KGgoAAAANSUhEUgAAAKAAAACgCAYAAACLz2ctAAAgAElEQVR4nOS9CZhdV3UlvM45d3zz q1dzlVRVUkmyRku2PINnMAQMNEOGJp2EpNMNSYD8nQQa0mkSOoHMCSGBJh0ShgRImAzYjhkcsLGN 5UG2LGuwNZVU81xvvPM5/Z1z75PKUkkqyaq08b+/z5ZU9d6799277j57r732PuT1jKJoMhx2Q1S5 wHEAOQBThKAHgCninwlC4AFoBcAATAIgiE0Iof58lWWhhVK4yb8vtRF5Dr4PEobIA1ggBBUhkJJ/ B/AECMSi81quCVzY+V6vM9xkaZjly3ufvF4LnPysH4UPBUIMdVgMEBwBtC17fRygENHFXCp5dA6o 70+Tf59+XGlPhCFqnKvrd8ZnCMDQCH6qTQdrcLSaFOOgODjtISP4BV0ZeS66xEiBQTSArB/hECF4 6Bx40C7g81+y5gKwANxp69ApRbjMB0C+LMtwZasmDoUCleW8R6fAbChwTAgIsrzjaES+T//geMTf Z9FwSN4kn5j3HvWCg0f84DfpRVzYJvAMAuw+32kQsiT4Xgr2sgAgkhtCoggFCngQy/KCEYH02OvW GvSIx8/vB0nihduogCOk1zn/UeQrQqHOqXc2YO+AEAcJNe4POWk5HkZvKDHKLxSACnyEoC4EOqnA 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get_avator(qq): try: return Image.open( BytesIO( httpx.get( f"http://q1.qlogo.cn/g?b=qq&nk={qq}&s=640", timeout=10 ).content ) ) except Exception: return @deco.ignore_botself @deco.on_regexp(r"来点小强(\d{0,})") def receive_group_msg(ctx: GroupMsg): at_data = gp.at(ctx) if at_data: user = at_data.UserID[0] else: user = ctx.FromUserId avatar = get_avator(user) if not avatar: return if avatar.mode != "RGBA": avatar = avatar.convert("RGBA") avatar_width, avatar_height = avatar.size try: num = int(ctx._match.group(1)) except Exception: num = random.randint(1, 6) if num < 0: S.text('sb') return if num > 119: S.text('强子过多, 呼叫119吧') return 小强们 = [来只小强() for _ in range(num)] for 一只小强 in 小强们: x_offset, y_offset = int(一只小强.width * 0.3), int(一只小强.height * 0.3) x, y = random.randint(1, avatar_width - x_offset), random.randint( 1, avatar_height - y_offset ) avatar.paste(一只小强, (x, y), 一只小强) buf = BytesIO() avatar.save(buf, "png") S.image(buf) avatar.close()

1,395

0

68

7cef8e80ca6b2bbedf08d6f5a3faf512fb91050f

777

py

Python

pylabnet/hardware/interface/simple_p_gen.py

wi11dey/pylabnet

a6e3362f727c45aaa60e61496e858ae92e85574d

[ "MIT" ]

10

2020-01-07T23:28:49.000Z

2022-02-02T19:09:17.000Z

pylabnet/hardware/interface/simple_p_gen.py

wi11dey/pylabnet

a6e3362f727c45aaa60e61496e858ae92e85574d

[ "MIT" ]

249

2019-12-28T19:38:49.000Z

2022-03-28T16:45:32.000Z

pylabnet/hardware/interface/simple_p_gen.py

wi11dey/pylabnet

a6e3362f727c45aaa60e61496e858ae92e85574d

[ "MIT" ]

5

2020-11-17T19:45:10.000Z

2022-01-04T18:07:04.000Z

import abc

18.5

59

0.599743

import abc class SimplePGenInterface(abc.ABC): @abc.abstractmethod def activate_interface(self): pass @abc.abstractmethod def write(self, pb_obj, step_adj=True): pass @abc.abstractmethod def set_rep(self, rep_num): pass @abc.abstractmethod def start(self): pass @abc.abstractmethod def stop(self): pass @abc.abstractmethod def get_status(self): """Get status of the device 0 - 'Idle' 1 - 'Running' Exception is produced in the case of any error (for example, connection to the device is lost) :return: (int) status code Exception is produced in the case of error """ class PGenError(Exception): pass

86

632

46

17cc2151cef7cb62503e1ee06869d1ee88e9b6bb

1,113

py

Python

docs/_examples/mesh-smoothing.py

yijiangh/compas

a9e86edf6b602f47ca051fccedcaa88a5e5d3600

[ "MIT" ]

1

2019-03-27T22:32:56.000Z

docs/_examples/mesh-smoothing.py

yijiangh/compas

a9e86edf6b602f47ca051fccedcaa88a5e5d3600

[ "MIT" ]

null

docs/_examples/mesh-smoothing.py

yijiangh/compas

a9e86edf6b602f47ca051fccedcaa88a5e5d3600

[ "MIT" ]

null

"""Smooth a mesh. """ from compas.datastructures import Mesh from compas.geometry import smooth_area import compas_rhino __author__ = ['Tom Van Mele', 'Matthias Rippmann'] __copyright__ = 'Copyright 2017, BRG - ETH Zurich', __license__ = 'MIT' __email__ = 'van.mele@arch.ethz.ch' # select a Rhino mesh # and make it into a mesh datastructure guid = compas_rhino.select_mesh() mesh = compas_rhino.mesh_from_guid(Mesh, guid) # extract the data needed by the smoothing algorithm # identify the boundary as fixed vertices = mesh.get_vertices_attributes('xyz') faces = [mesh.face_vertices(fkey) for fkey in mesh.faces()] adjacency = [mesh.vertex_faces(key, ordered=True) for key in mesh.vertices()] fixed = mesh.vertices_on_boundary() # run the smoothing algorithm # update the mesh # display the result in Rhino smooth_area(vertices, faces, adjacency, fixed=fixed, kmax=100) for key, attr in mesh.vertices(True): attr['x'] = vertices[key][0] attr['y'] = vertices[key][1] attr['z'] = vertices[key][2] compas_rhino.mesh_draw(mesh)

25.295455

78

0.698113

"""Smooth a mesh. """ from compas.datastructures import Mesh from compas.geometry import smooth_area import compas_rhino __author__ = ['Tom Van Mele', 'Matthias Rippmann'] __copyright__ = 'Copyright 2017, BRG - ETH Zurich', __license__ = 'MIT' __email__ = 'van.mele@arch.ethz.ch' # select a Rhino mesh # and make it into a mesh datastructure guid = compas_rhino.select_mesh() mesh = compas_rhino.mesh_from_guid(Mesh, guid) # extract the data needed by the smoothing algorithm # identify the boundary as fixed vertices = mesh.get_vertices_attributes('xyz') faces = [mesh.face_vertices(fkey) for fkey in mesh.faces()] adjacency = [mesh.vertex_faces(key, ordered=True) for key in mesh.vertices()] fixed = mesh.vertices_on_boundary() # run the smoothing algorithm # update the mesh # display the result in Rhino smooth_area(vertices, faces, adjacency, fixed=fixed, kmax=100) for key, attr in mesh.vertices(True): attr['x'] = vertices[key][0] attr['y'] = vertices[key][1] attr['z'] = vertices[key][2] compas_rhino.mesh_draw(mesh)

0

e5c22083523c248ad1b2c6de86eb7566e358c791

7,922

py

Python

tests/managers/event_log_tests.py

dvzrv/softlayer-python

9a5f6c6981bcc370084537b4d1769383499ce90d

[ "MIT" ]

126

2015-01-05T05:09:22.000Z

2021-07-02T00:16:35.000Z

tests/managers/event_log_tests.py

dvzrv/softlayer-python

9a5f6c6981bcc370084537b4d1769383499ce90d

[ "MIT" ]

969

2015-01-05T15:55:31.000Z

2022-03-31T19:55:20.000Z

tests/managers/event_log_tests.py

dvzrv/softlayer-python

9a5f6c6981bcc370084537b4d1769383499ce90d

[ "MIT" ]

176

2015-01-22T11:23:40.000Z

2022-02-11T13:16:58.000Z

""" SoftLayer.tests.managers.event_log_tests ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :license: MIT, see LICENSE for more details. """ import SoftLayer from SoftLayer import fixtures from SoftLayer import testing

31.188976

99

0.454304

""" SoftLayer.tests.managers.event_log_tests ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :license: MIT, see LICENSE for more details. """ import SoftLayer from SoftLayer import fixtures from SoftLayer import testing class EventLogTests(testing.TestCase): def set_up(self): self.event_log = SoftLayer.EventLogManager(self.client) def test_get_event_logs(self): # Cast to list to force generator to get all objects result = list(self.event_log.get_event_logs()) expected = fixtures.SoftLayer_Event_Log.getAllObjects self.assertEqual(expected, result) self.assert_called_with('SoftLayer_Event_Log', 'getAllObjects') def test_get_event_logs_no_iteration(self): # Cast to list to force generator to get all objects result = self.event_log.get_event_logs(iterator=False) expected = fixtures.SoftLayer_Event_Log.getAllObjects self.assertEqual(expected, result) self.assert_called_with('SoftLayer_Event_Log', 'getAllObjects') def test_get_event_log_types(self): result = self.event_log.get_event_log_types() expected = fixtures.SoftLayer_Event_Log.getAllEventObjectNames self.assertEqual(expected, result) self.assert_called_with('SoftLayer_Event_Log', 'getAllEventObjectNames') def test_build_filter_no_args(self): result = self.event_log.build_filter(None, None, None, None, None, None) self.assertEqual(result, {}) def test_build_filter_min_date(self): expected = { 'eventCreateDate': { 'operation': 'greaterThanDate', 'options': [ { 'name': 'date', 'value': [ '2017-10-30T00:00:00.000000+00:00' ] } ] } } result = self.event_log.build_filter('10/30/2017', None, None, None, None, None) self.assertEqual(expected, result) def test_build_filter_max_date(self): expected = { 'eventCreateDate': { 'operation': 'lessThanDate', 'options': [ { 'name': 'date', 'value': [ '2017-10-31T00:00:00.000000+00:00' ] } ] } } result = self.event_log.build_filter(None, '10/31/2017', None, None, None, None) self.assertEqual(expected, result) def test_build_filter_min_max_date(self): expected = { 'eventCreateDate': { 'operation': 'betweenDate', 'options': [ { 'name': 'startDate', 'value': [ '2017-10-30T00:00:00.000000+00:00' ] }, { 'name': 'endDate', 'value': [ '2017-10-31T00:00:00.000000+00:00' ] } ] } } result = self.event_log.build_filter('10/30/2017', '10/31/2017', None, None, None, None) self.assertEqual(expected, result) def test_build_filter_min_date_pos_utc(self): expected = { 'eventCreateDate': { 'operation': 'greaterThanDate', 'options': [ { 'name': 'date', 'value': [ '2017-10-30T00:00:00.000000+05:00' ] } ] } } result = self.event_log.build_filter('10/30/2017', None, None, None, None, '+0500') self.assertEqual(expected, result) def test_build_filter_max_date_pos_utc(self): expected = { 'eventCreateDate': { 'operation': 'lessThanDate', 'options': [ { 'name': 'date', 'value': [ '2017-10-31T00:00:00.000000+05:00' ] } ] } } result = self.event_log.build_filter(None, '10/31/2017', None, None, None, '+0500') self.assertEqual(expected, result) def test_build_filter_min_max_date_pos_utc(self): expected = { 'eventCreateDate': { 'operation': 'betweenDate', 'options': [ { 'name': 'startDate', 'value': [ '2017-10-30T00:00:00.000000+05:00' ] }, { 'name': 'endDate', 'value': [ '2017-10-31T00:00:00.000000+05:00' ] } ] } } result = self.event_log.build_filter('10/30/2017', '10/31/2017', None, None, None, '+0500') self.assertEqual(expected, result) def test_build_filter_min_date_neg_utc(self): expected = { 'eventCreateDate': { 'operation': 'greaterThanDate', 'options': [ { 'name': 'date', 'value': [ '2017-10-30T00:00:00.000000-03:00' ] } ] } } result = self.event_log.build_filter('10/30/2017', None, None, None, None, '-0300') self.assertEqual(expected, result) def test_build_filter_max_date_neg_utc(self): expected = { 'eventCreateDate': { 'operation': 'lessThanDate', 'options': [ { 'name': 'date', 'value': [ '2017-10-31T00:00:00.000000-03:00' ] } ] } } result = self.event_log.build_filter(None, '10/31/2017', None, None, None, '-0300') self.assertEqual(expected, result) def test_build_filter_min_max_date_neg_utc(self): expected = { 'eventCreateDate': { 'operation': 'betweenDate', 'options': [ { 'name': 'startDate', 'value': [ '2017-10-30T00:00:00.000000-03:00' ] }, { 'name': 'endDate', 'value': [ '2017-10-31T00:00:00.000000-03:00' ] } ] } } result = self.event_log.build_filter('10/30/2017', '10/31/2017', None, None, None, '-0300') self.assertEqual(expected, result) def test_build_filter_name(self): expected = {'eventName': {'operation': 'Add Security Group'}} result = self.event_log.build_filter(None, None, 'Add Security Group', None, None, None) self.assertEqual(expected, result) def test_build_filter_id(self): expected = {'objectId': {'operation': 1}} result = self.event_log.build_filter(None, None, None, 1, None, None) self.assertEqual(expected, result) def test_build_filter_type(self): expected = {'objectName': {'operation': 'CCI'}} result = self.event_log.build_filter(None, None, None, None, 'CCI', None) self.assertEqual(expected, result)

7,198

17

482

96b5c9d649f8f78abe33dffa08a7507737a3b4c1

397

py

Python

sensors/MercurySwitchModule.py

akesiraju/raspberrypi

e8ae5e535a9953631ffa2d1e7de926c9dc19f961

[ "MIT" ]

2

2019-03-26T23:47:40.000Z

2020-03-28T03:23:31.000Z

sensors/MercurySwitchModule.py

akesiraju/raspberrypi

e8ae5e535a9953631ffa2d1e7de926c9dc19f961

[ "MIT" ]

1

2019-03-27T10:59:14.000Z

sensors/MercurySwitchModule.py

akesiraju/raspberrypi

e8ae5e535a9953631ffa2d1e7de926c9dc19f961

[ "MIT" ]

1

2018-07-14T23:55:14.000Z

import RPi.GPIO as GPIO import time #When the mercury is contact, we get a signal on 21 pin = 21 light = 20 GPIO.setmode(GPIO.BCM) GPIO.setup(pin, GPIO.IN) GPIO.setup(light, GPIO.OUT) while True: if GPIO.input(pin): print("contact") GPIO.output(light, GPIO.HIGH) else: print("no contact") GPIO.output(light, GPIO.LOW) time.sleep(0.3) GPIO.cleanup()

18.045455

51

0.647355

import RPi.GPIO as GPIO import time #When the mercury is contact, we get a signal on 21 pin = 21 light = 20 GPIO.setmode(GPIO.BCM) GPIO.setup(pin, GPIO.IN) GPIO.setup(light, GPIO.OUT) while True: if GPIO.input(pin): print("contact") GPIO.output(light, GPIO.HIGH) else: print("no contact") GPIO.output(light, GPIO.LOW) time.sleep(0.3) GPIO.cleanup()

0

d2714d988a8b9f099d118a01f597d6b3479b2a08

192

py

Python

src/cmp/cool_lang/ast/integer_node.py

codestrange/cool-compiler-2020

30508965d75a1a1d1362d0b51bef8da3978fd0c2

[ "MIT" ]

3

2020-01-14T04:47:32.000Z

2020-09-10T17:57:20.000Z

src/cmp/cool_lang/ast/integer_node.py

codestrange/cool-compiler-2020

30508965d75a1a1d1362d0b51bef8da3978fd0c2

[ "MIT" ]

5

2020-01-14T06:06:35.000Z

2020-02-19T01:01:33.000Z

src/cmp/cool_lang/ast/integer_node.py

codestrange/cool-compiler-2020

30508965d75a1a1d1362d0b51bef8da3978fd0c2

[ "MIT" ]

3

2020-01-14T04:58:24.000Z

2020-01-14T16:23:41.000Z

from .atomic_node import AtomicNode

27.428571

62

0.723958

from .atomic_node import AtomicNode class IntegerNode(AtomicNode): def __init__(self, token: str, line: int, column: int): super(IntegerNode, self).__init__(token, line, column)

97

9

49

076d01cdee74927f3950a2f36d0c2aa2fc2d6a1b

106

py

Python

dexp/cli/defaults.py

haesleinhuepf/dexp

2ea84f3db323724588fac565fae56f0d522bc5ca

[ "BSD-3-Clause" ]

16

2021-04-21T14:09:19.000Z

2022-03-22T02:30:59.000Z

dexp/cli/defaults.py

haesleinhuepf/dexp

2ea84f3db323724588fac565fae56f0d522bc5ca

[ "BSD-3-Clause" ]

28

2021-04-15T17:43:08.000Z

2022-03-29T16:08:35.000Z

dexp/cli/defaults.py

haesleinhuepf/dexp

2ea84f3db323724588fac565fae56f0d522bc5ca

[ "BSD-3-Clause" ]

3

2022-02-08T17:41:30.000Z

2022-03-18T15:32:27.000Z

_default_store = "dir" _default_clevel = 3 _default_codec = "zstd" _default_workers_backend = "threading"

21.2

38

0.792453

_default_store = "dir" _default_clevel = 3 _default_codec = "zstd" _default_workers_backend = "threading"

0

130a684460802de83781936238e59e5a10674077

110

py

Python

docker/template/handlers/birthday.py

izi-global/izir

d1a4bfb5c082c3de1956402ef0280564014a3bd8

[ "MIT" ]

null

docker/template/handlers/birthday.py

izi-global/izir

d1a4bfb5c082c3de1956402ef0280564014a3bd8

[ "MIT" ]

5

2021-03-18T21:01:05.000Z

2022-03-11T23:29:48.000Z

docker/template/handlers/birthday.py

izi-global/izir

d1a4bfb5c082c3de1956402ef0280564014a3bd8

[ "MIT" ]

null

import izi @izi.get("/birthday")

15.714286

53

0.672727

import izi @izi.get("/birthday") def home(name: str): return "Happy Birthday, {name}".format(name=name)

53

0

22

b42e01b497eed8a4616e56359654df96530b2429

37,311

py

Python

feersum_nlu/api/regex_entity_extractors_api.py

praekelt/feersum-nlu-api-wrappers

6580e2bab2c8a764fe868a505330b3fee6029074

[ "BSD-3-Clause" ]

9

2017-10-10T12:24:23.000Z

2021-08-18T14:07:51.000Z

feersum_nlu/api/regex_entity_extractors_api.py

praekelt/feersum-nlu-api-wrappers

6580e2bab2c8a764fe868a505330b3fee6029074

[ "BSD-3-Clause" ]

1

2020-12-06T11:03:25.000Z

2021-04-14T05:21:23.000Z

feersum_nlu/api/regex_entity_extractors_api.py

praekelt/feersum-nlu-api-wrappers

6580e2bab2c8a764fe868a505330b3fee6029074

[ "BSD-3-Clause" ]

2

2019-02-12T08:26:06.000Z

2022-02-01T09:39:47.000Z

# coding: utf-8 """ FeersumNLU API This is the HTTP API for Feersum NLU. See https://github.com/praekelt/feersum-nlu-api-wrappers for examples of how to use the API. # noqa: E501 OpenAPI spec version: 2.0.54.dev2 Contact: nlu@feersum.io Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from feersum_nlu.api_client import ApiClient class RegexEntityExtractorsApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def regex_entity_extractor_create(self, create_details, **kwargs): # noqa: E501 """Create a regular expression entity extractor. # noqa: E501 Create a new regular expression entity extractor or reload one from the trash. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_create(create_details, async_req=True) >>> result = thread.get() :param async_req bool :param RegexEntityExtractorCreateDetails create_details: The details of the instance to create. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_create_with_http_info(create_details, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_create_with_http_info(create_details, **kwargs) # noqa: E501 return data def regex_entity_extractor_create_with_http_info(self, create_details, **kwargs): # noqa: E501 """Create a regular expression entity extractor. # noqa: E501 Create a new regular expression entity extractor or reload one from the trash. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_create_with_http_info(create_details, async_req=True) >>> result = thread.get() :param async_req bool :param RegexEntityExtractorCreateDetails create_details: The details of the instance to create. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ all_params = ['create_details', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_create" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'create_details' is set if ('create_details' not in params or params['create_details'] is None): raise ValueError("Missing the required parameter `create_details` when calling `regex_entity_extractor_create`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'create_details' in params: body_params = params['create_details'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='RegexEntityExtractorInstanceDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_del(self, instance_name, **kwargs): # noqa: E501 """Delete named instance. # noqa: E501 Delete and get the details of the named regular expression entity extractor instance. Deleted models can be reloaded from the trash with the create operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_del(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_del_with_http_info(instance_name, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_del_with_http_info(instance_name, **kwargs) # noqa: E501 return data def regex_entity_extractor_del_with_http_info(self, instance_name, **kwargs): # noqa: E501 """Delete named instance. # noqa: E501 Delete and get the details of the named regular expression entity extractor instance. Deleted models can be reloaded from the trash with the create operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_del_with_http_info(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ all_params = ['instance_name', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_del" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'instance_name' is set if ('instance_name' not in params or params['instance_name'] is None): raise ValueError("Missing the required parameter `instance_name` when calling `regex_entity_extractor_del`") # noqa: E501 collection_formats = {} path_params = {} if 'instance_name' in params: path_params['instance_name'] = params['instance_name'] # noqa: E501 query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors/{instance_name}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='RegexEntityExtractorInstanceDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_get_details(self, instance_name, **kwargs): # noqa: E501 """Get details of named instance. # noqa: E501 Get the details of the named regular expression entity extractor instance. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_get_details(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_get_details_with_http_info(instance_name, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_get_details_with_http_info(instance_name, **kwargs) # noqa: E501 return data def regex_entity_extractor_get_details_with_http_info(self, instance_name, **kwargs): # noqa: E501 """Get details of named instance. # noqa: E501 Get the details of the named regular expression entity extractor instance. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_get_details_with_http_info(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ all_params = ['instance_name', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_get_details" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'instance_name' is set if ('instance_name' not in params or params['instance_name'] is None): raise ValueError("Missing the required parameter `instance_name` when calling `regex_entity_extractor_get_details`") # noqa: E501 collection_formats = {} path_params = {} if 'instance_name' in params: path_params['instance_name'] = params['instance_name'] # noqa: E501 query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors/{instance_name}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='RegexEntityExtractorInstanceDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_get_details_all(self, **kwargs): # noqa: E501 """Get list of regular expression entity extractors. # noqa: E501 Get the list of regular expression entity extractors. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_get_details_all(async_req=True) >>> result = thread.get() :param async_req bool :param str x_caller: :return: list[RegexEntityExtractorInstanceDetail] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_get_details_all_with_http_info(**kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_get_details_all_with_http_info(**kwargs) # noqa: E501 return data def regex_entity_extractor_get_details_all_with_http_info(self, **kwargs): # noqa: E501 """Get list of regular expression entity extractors. # noqa: E501 Get the list of regular expression entity extractors. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_get_details_all_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param str x_caller: :return: list[RegexEntityExtractorInstanceDetail] If the method is called asynchronously, returns the request thread. """ all_params = ['x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_get_details_all" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[RegexEntityExtractorInstanceDetail]', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_get_params(self, instance_name, **kwargs): # noqa: E501 """Get the editable model parameters of named regex entity extractor. # noqa: E501 Get the editable model parameters of named regex entity extractor. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_get_params(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: ModelParams If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_get_params_with_http_info(instance_name, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_get_params_with_http_info(instance_name, **kwargs) # noqa: E501 return data def regex_entity_extractor_get_params_with_http_info(self, instance_name, **kwargs): # noqa: E501 """Get the editable model parameters of named regex entity extractor. # noqa: E501 Get the editable model parameters of named regex entity extractor. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_get_params_with_http_info(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: ModelParams If the method is called asynchronously, returns the request thread. """ all_params = ['instance_name', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_get_params" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'instance_name' is set if ('instance_name' not in params or params['instance_name'] is None): raise ValueError("Missing the required parameter `instance_name` when calling `regex_entity_extractor_get_params`") # noqa: E501 collection_formats = {} path_params = {} if 'instance_name' in params: path_params['instance_name'] = params['instance_name'] # noqa: E501 query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors/{instance_name}/params', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ModelParams', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_retrieve(self, instance_name, text_input, **kwargs): # noqa: E501 """Extract information based on the regular expression. # noqa: E501 Extract the entities matching the regular expression. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_retrieve(instance_name, text_input, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param TextInput text_input: The input text. (required) :param str x_caller: :return: list[RegexEntity] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_retrieve_with_http_info(instance_name, text_input, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_retrieve_with_http_info(instance_name, text_input, **kwargs) # noqa: E501 return data def regex_entity_extractor_retrieve_with_http_info(self, instance_name, text_input, **kwargs): # noqa: E501 """Extract information based on the regular expression. # noqa: E501 Extract the entities matching the regular expression. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_retrieve_with_http_info(instance_name, text_input, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param TextInput text_input: The input text. (required) :param str x_caller: :return: list[RegexEntity] If the method is called asynchronously, returns the request thread. """ all_params = ['instance_name', 'text_input', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_retrieve" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'instance_name' is set if ('instance_name' not in params or params['instance_name'] is None): raise ValueError("Missing the required parameter `instance_name` when calling `regex_entity_extractor_retrieve`") # noqa: E501 # verify the required parameter 'text_input' is set if ('text_input' not in params or params['text_input'] is None): raise ValueError("Missing the required parameter `text_input` when calling `regex_entity_extractor_retrieve`") # noqa: E501 collection_formats = {} path_params = {} if 'instance_name' in params: path_params['instance_name'] = params['instance_name'] # noqa: E501 query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'text_input' in params: body_params = params['text_input'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors/{instance_name}/retrieve', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[RegexEntity]', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_set_params(self, instance_name, model_params, **kwargs): # noqa: E501 """Set the model parameters of named regex entity extractor. # noqa: E501 Set the model parameters of named regex entity extractor. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_set_params(instance_name, model_params, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param ModelParams model_params: The model parameters. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_set_params_with_http_info(instance_name, model_params, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_set_params_with_http_info(instance_name, model_params, **kwargs) # noqa: E501 return data def regex_entity_extractor_set_params_with_http_info(self, instance_name, model_params, **kwargs): # noqa: E501 """Set the model parameters of named regex entity extractor. # noqa: E501 Set the model parameters of named regex entity extractor. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_set_params_with_http_info(instance_name, model_params, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param ModelParams model_params: The model parameters. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ all_params = ['instance_name', 'model_params', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_set_params" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'instance_name' is set if ('instance_name' not in params or params['instance_name'] is None): raise ValueError("Missing the required parameter `instance_name` when calling `regex_entity_extractor_set_params`") # noqa: E501 # verify the required parameter 'model_params' is set if ('model_params' not in params or params['model_params'] is None): raise ValueError("Missing the required parameter `model_params` when calling `regex_entity_extractor_set_params`") # noqa: E501 collection_formats = {} path_params = {} if 'instance_name' in params: path_params['instance_name'] = params['instance_name'] # noqa: E501 query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'model_params' in params: body_params = params['model_params'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors/{instance_name}/params', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='RegexEntityExtractorInstanceDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_vaporise(self, instance_name, **kwargs): # noqa: E501 """Vaporise the named model. # noqa: E501 Permanently vaporises a model even if not trashed. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_vaporise(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_vaporise_with_http_info(instance_name, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_vaporise_with_http_info(instance_name, **kwargs) # noqa: E501 return data def regex_entity_extractor_vaporise_with_http_info(self, instance_name, **kwargs): # noqa: E501 """Vaporise the named model. # noqa: E501 Permanently vaporises a model even if not trashed. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_vaporise_with_http_info(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ all_params = ['instance_name', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_vaporise" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'instance_name' is set if ('instance_name' not in params or params['instance_name'] is None): raise ValueError("Missing the required parameter `instance_name` when calling `regex_entity_extractor_vaporise`") # noqa: E501 collection_formats = {} path_params = {} if 'instance_name' in params: path_params['instance_name'] = params['instance_name'] # noqa: E501 query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors/{instance_name}/vaporise', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='RegexEntityExtractorInstanceDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

43.034602

180

0.637319

# coding: utf-8 """ FeersumNLU API This is the HTTP API for Feersum NLU. See https://github.com/praekelt/feersum-nlu-api-wrappers for examples of how to use the API. # noqa: E501 OpenAPI spec version: 2.0.54.dev2 Contact: nlu@feersum.io Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from feersum_nlu.api_client import ApiClient class RegexEntityExtractorsApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def regex_entity_extractor_create(self, create_details, **kwargs): # noqa: E501 """Create a regular expression entity extractor. # noqa: E501 Create a new regular expression entity extractor or reload one from the trash. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_create(create_details, async_req=True) >>> result = thread.get() :param async_req bool :param RegexEntityExtractorCreateDetails create_details: The details of the instance to create. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_create_with_http_info(create_details, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_create_with_http_info(create_details, **kwargs) # noqa: E501 return data def regex_entity_extractor_create_with_http_info(self, create_details, **kwargs): # noqa: E501 """Create a regular expression entity extractor. # noqa: E501 Create a new regular expression entity extractor or reload one from the trash. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_create_with_http_info(create_details, async_req=True) >>> result = thread.get() :param async_req bool :param RegexEntityExtractorCreateDetails create_details: The details of the instance to create. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ all_params = ['create_details', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_create" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'create_details' is set if ('create_details' not in params or params['create_details'] is None): raise ValueError("Missing the required parameter `create_details` when calling `regex_entity_extractor_create`") # noqa: E501 collection_formats = {} path_params = {} query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'create_details' in params: body_params = params['create_details'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='RegexEntityExtractorInstanceDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_del(self, instance_name, **kwargs): # noqa: E501 """Delete named instance. # noqa: E501 Delete and get the details of the named regular expression entity extractor instance. Deleted models can be reloaded from the trash with the create operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_del(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_del_with_http_info(instance_name, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_del_with_http_info(instance_name, **kwargs) # noqa: E501 return data def regex_entity_extractor_del_with_http_info(self, instance_name, **kwargs): # noqa: E501 """Delete named instance. # noqa: E501 Delete and get the details of the named regular expression entity extractor instance. Deleted models can be reloaded from the trash with the create operation. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_del_with_http_info(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ all_params = ['instance_name', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_del" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'instance_name' is set if ('instance_name' not in params or params['instance_name'] is None): raise ValueError("Missing the required parameter `instance_name` when calling `regex_entity_extractor_del`") # noqa: E501 collection_formats = {} path_params = {} if 'instance_name' in params: path_params['instance_name'] = params['instance_name'] # noqa: E501 query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors/{instance_name}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='RegexEntityExtractorInstanceDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_get_details(self, instance_name, **kwargs): # noqa: E501 """Get details of named instance. # noqa: E501 Get the details of the named regular expression entity extractor instance. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_get_details(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_get_details_with_http_info(instance_name, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_get_details_with_http_info(instance_name, **kwargs) # noqa: E501 return data def regex_entity_extractor_get_details_with_http_info(self, instance_name, **kwargs): # noqa: E501 """Get details of named instance. # noqa: E501 Get the details of the named regular expression entity extractor instance. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_get_details_with_http_info(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ all_params = ['instance_name', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_get_details" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'instance_name' is set if ('instance_name' not in params or params['instance_name'] is None): raise ValueError("Missing the required parameter `instance_name` when calling `regex_entity_extractor_get_details`") # noqa: E501 collection_formats = {} path_params = {} if 'instance_name' in params: path_params['instance_name'] = params['instance_name'] # noqa: E501 query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors/{instance_name}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='RegexEntityExtractorInstanceDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_get_details_all(self, **kwargs): # noqa: E501 """Get list of regular expression entity extractors. # noqa: E501 Get the list of regular expression entity extractors. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_get_details_all(async_req=True) >>> result = thread.get() :param async_req bool :param str x_caller: :return: list[RegexEntityExtractorInstanceDetail] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_get_details_all_with_http_info(**kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_get_details_all_with_http_info(**kwargs) # noqa: E501 return data def regex_entity_extractor_get_details_all_with_http_info(self, **kwargs): # noqa: E501 """Get list of regular expression entity extractors. # noqa: E501 Get the list of regular expression entity extractors. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_get_details_all_with_http_info(async_req=True) >>> result = thread.get() :param async_req bool :param str x_caller: :return: list[RegexEntityExtractorInstanceDetail] If the method is called asynchronously, returns the request thread. """ all_params = ['x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_get_details_all" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[RegexEntityExtractorInstanceDetail]', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_get_params(self, instance_name, **kwargs): # noqa: E501 """Get the editable model parameters of named regex entity extractor. # noqa: E501 Get the editable model parameters of named regex entity extractor. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_get_params(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: ModelParams If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_get_params_with_http_info(instance_name, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_get_params_with_http_info(instance_name, **kwargs) # noqa: E501 return data def regex_entity_extractor_get_params_with_http_info(self, instance_name, **kwargs): # noqa: E501 """Get the editable model parameters of named regex entity extractor. # noqa: E501 Get the editable model parameters of named regex entity extractor. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_get_params_with_http_info(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: ModelParams If the method is called asynchronously, returns the request thread. """ all_params = ['instance_name', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_get_params" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'instance_name' is set if ('instance_name' not in params or params['instance_name'] is None): raise ValueError("Missing the required parameter `instance_name` when calling `regex_entity_extractor_get_params`") # noqa: E501 collection_formats = {} path_params = {} if 'instance_name' in params: path_params['instance_name'] = params['instance_name'] # noqa: E501 query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors/{instance_name}/params', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ModelParams', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_retrieve(self, instance_name, text_input, **kwargs): # noqa: E501 """Extract information based on the regular expression. # noqa: E501 Extract the entities matching the regular expression. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_retrieve(instance_name, text_input, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param TextInput text_input: The input text. (required) :param str x_caller: :return: list[RegexEntity] If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_retrieve_with_http_info(instance_name, text_input, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_retrieve_with_http_info(instance_name, text_input, **kwargs) # noqa: E501 return data def regex_entity_extractor_retrieve_with_http_info(self, instance_name, text_input, **kwargs): # noqa: E501 """Extract information based on the regular expression. # noqa: E501 Extract the entities matching the regular expression. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_retrieve_with_http_info(instance_name, text_input, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param TextInput text_input: The input text. (required) :param str x_caller: :return: list[RegexEntity] If the method is called asynchronously, returns the request thread. """ all_params = ['instance_name', 'text_input', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_retrieve" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'instance_name' is set if ('instance_name' not in params or params['instance_name'] is None): raise ValueError("Missing the required parameter `instance_name` when calling `regex_entity_extractor_retrieve`") # noqa: E501 # verify the required parameter 'text_input' is set if ('text_input' not in params or params['text_input'] is None): raise ValueError("Missing the required parameter `text_input` when calling `regex_entity_extractor_retrieve`") # noqa: E501 collection_formats = {} path_params = {} if 'instance_name' in params: path_params['instance_name'] = params['instance_name'] # noqa: E501 query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'text_input' in params: body_params = params['text_input'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors/{instance_name}/retrieve', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='list[RegexEntity]', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_set_params(self, instance_name, model_params, **kwargs): # noqa: E501 """Set the model parameters of named regex entity extractor. # noqa: E501 Set the model parameters of named regex entity extractor. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_set_params(instance_name, model_params, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param ModelParams model_params: The model parameters. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_set_params_with_http_info(instance_name, model_params, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_set_params_with_http_info(instance_name, model_params, **kwargs) # noqa: E501 return data def regex_entity_extractor_set_params_with_http_info(self, instance_name, model_params, **kwargs): # noqa: E501 """Set the model parameters of named regex entity extractor. # noqa: E501 Set the model parameters of named regex entity extractor. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_set_params_with_http_info(instance_name, model_params, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param ModelParams model_params: The model parameters. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ all_params = ['instance_name', 'model_params', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_set_params" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'instance_name' is set if ('instance_name' not in params or params['instance_name'] is None): raise ValueError("Missing the required parameter `instance_name` when calling `regex_entity_extractor_set_params`") # noqa: E501 # verify the required parameter 'model_params' is set if ('model_params' not in params or params['model_params'] is None): raise ValueError("Missing the required parameter `model_params` when calling `regex_entity_extractor_set_params`") # noqa: E501 collection_formats = {} path_params = {} if 'instance_name' in params: path_params['instance_name'] = params['instance_name'] # noqa: E501 query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None if 'model_params' in params: body_params = params['model_params'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors/{instance_name}/params', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='RegexEntityExtractorInstanceDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def regex_entity_extractor_vaporise(self, instance_name, **kwargs): # noqa: E501 """Vaporise the named model. # noqa: E501 Permanently vaporises a model even if not trashed. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_vaporise(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.regex_entity_extractor_vaporise_with_http_info(instance_name, **kwargs) # noqa: E501 else: (data) = self.regex_entity_extractor_vaporise_with_http_info(instance_name, **kwargs) # noqa: E501 return data def regex_entity_extractor_vaporise_with_http_info(self, instance_name, **kwargs): # noqa: E501 """Vaporise the named model. # noqa: E501 Permanently vaporises a model even if not trashed. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.regex_entity_extractor_vaporise_with_http_info(instance_name, async_req=True) >>> result = thread.get() :param async_req bool :param str instance_name: The name of the instance. (required) :param str x_caller: :return: RegexEntityExtractorInstanceDetail If the method is called asynchronously, returns the request thread. """ all_params = ['instance_name', 'x_caller'] # noqa: E501 all_params.append('async_req') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method regex_entity_extractor_vaporise" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'instance_name' is set if ('instance_name' not in params or params['instance_name'] is None): raise ValueError("Missing the required parameter `instance_name` when calling `regex_entity_extractor_vaporise`") # noqa: E501 collection_formats = {} path_params = {} if 'instance_name' in params: path_params['instance_name'] = params['instance_name'] # noqa: E501 query_params = [] header_params = {} if 'x_caller' in params: header_params['X-CALLER'] = params['x_caller'] # noqa: E501 form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIKeyHeader', 'APIKeyHeader_old'] # noqa: E501 return self.api_client.call_api( '/nlu/v2/regex_entity_extractors/{instance_name}/vaporise', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='RegexEntityExtractorInstanceDetail', # noqa: E501 auth_settings=auth_settings, async_req=params.get('async_req'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

120

0

27

e232c85608e7357dcbea2b73496a2fb0667670b1

516

py

Python

setup.py

bobjansen/django_fabv

cf8d1be8371c7574884f0405b6ca7f78a7c224b3

[ "BSD-3-Clause" ]

3

2015-05-18T13:49:36.000Z

2015-05-18T14:37:32.000Z

setup.py

bobjansen/django_fabv

cf8d1be8371c7574884f0405b6ca7f78a7c224b3

[ "BSD-3-Clause" ]

null

setup.py

bobjansen/django_fabv

cf8d1be8371c7574884f0405b6ca7f78a7c224b3

[ "BSD-3-Clause" ]

null

try: from setuptools import setup, find_packages except ImportError: from distutils.core import setup, find_packages setup( name = 'django_fabv', version = '0.1.1', url = 'https://pypi.python.org/pypi/django_fabv/0.1.0', include_package_data=True, packages=find_packages(), license = '3-clause BSD', author = 'Bob Jansen', author_email = 'bob.jansen@veneficus.nl', description = 'A/B module for Django based on ABingo', long_description=open('README.txt').read(), )

27.157895

59

0.680233

try: from setuptools import setup, find_packages except ImportError: from distutils.core import setup, find_packages setup( name = 'django_fabv', version = '0.1.1', url = 'https://pypi.python.org/pypi/django_fabv/0.1.0', include_package_data=True, packages=find_packages(), license = '3-clause BSD', author = 'Bob Jansen', author_email = 'bob.jansen@veneficus.nl', description = 'A/B module for Django based on ABingo', long_description=open('README.txt').read(), )

0

536290ee2514884e41f360d3529e625d5173f659

707

py

Python

Ago-Dic-2018/Ernesto Vela/Practica1Parcial2/ocp2.py

Arbupa/DAS_Sistemas

52263ab91436b2e5a24ce6f8493aaa2e2fe92fb1

[ "MIT" ]

41

2017-09-26T09:36:32.000Z

2022-03-19T18:05:25.000Z

Ago-Dic-2018/Ernesto Vela/Practica1Parcial2/ocp2.py

Arbupa/DAS_Sistemas

52263ab91436b2e5a24ce6f8493aaa2e2fe92fb1

[ "MIT" ]

67

2017-09-11T05:06:12.000Z

2022-02-14T04:44:04.000Z

Ago-Dic-2018/Ernesto Vela/Practica1Parcial2/ocp2.py

Arbupa/DAS_Sistemas

52263ab91436b2e5a24ce6f8493aaa2e2fe92fb1

[ "MIT" ]

210

2017-09-01T00:10:08.000Z

2022-03-19T18:05:12.000Z

programmer = Programmer() tester = Tester() project = ProjectManagement() print(project.process(programmer)) print(project.process(tester)) #La clase ProjectManagment es la que se puede extender #por eso la dejamos asi, ya que cumple con el principio #Abierto/Cerrado #(no le entendi muy bien)

19.638889

55

0.670438

class Programmer: def code(self): return 'I am Coding!' class Tester: def test(self): return 'I am Testing!' class ProjectManagement: def process(self, worker): if isinstance(worker, Programmer): return worker.code() elif isinstance(worker, Tester): return worker.test() else: return 'Hey there!, Something went wrong :C' programmer = Programmer() tester = Tester() project = ProjectManagement() print(project.process(programmer)) print(project.process(tester)) #La clase ProjectManagment es la que se puede extender #por eso la dejamos asi, ya que cumple con el principio #Abierto/Cerrado #(no le entendi muy bien)

266

-9

149

89e3547e029cf9e6f7b297217cd7135285370c2d

15,695

py

Python

rock4/softtest/pad/hierarchy/driver.py

RockFeng0/rock4automation

a29270ab9fa4cdc79f6453971b7c7a21f01442b0

[ "MIT" ]

5

2018-09-25T05:49:49.000Z

2021-12-30T11:06:09.000Z

rock4/softtest/pad/hierarchy/driver.py

RockFeng0/rock4automation

a29270ab9fa4cdc79f6453971b7c7a21f01442b0

[ "MIT" ]

3

2018-04-01T04:27:21.000Z

2019-01-03T11:02:33.000Z

rock4/softtest/pad/hierarchy/driver.py

RockFeng0/rock4automation

a29270ab9fa4cdc79f6453971b7c7a21f01442b0

[ "MIT" ]

7

2018-09-25T05:49:51.000Z

2021-12-30T11:06:11.000Z

# -*- encoding: utf-8 -*- ''' Current module: mobile.monkeyrunner.driver Rough version history: v1.0 Original version to use ******************************************************************** @AUTHOR: Administrator-Bruce Luo(罗科峰) MAIL: lkf20031988@163.com RCS: rock4.softtest.pad.hierarchy.driver,v 2.0 2017年2月7日 FROM: 2015年12月23日 ******************************************************************** ====================================================================== Android UI automation frame for python. Jython-monkeyrunner--need use jython to compileall monkeyrunner.jar & chimpchat.jar & hierarchyviewer2lib.jar ''' from com.android.monkeyrunner import MonkeyRunner,MonkeyDevice from com.android.monkeyrunner.easy import By,EasyMonkeyDevice from com.android.chimpchat.hierarchyviewer import HierarchyViewer import os,re,time import p_m_env class MobileApp(): ''' Mobile App Test.(need MonkeyRunner + Hierarchy)''' @classmethod @classmethod @classmethod def CloseApp(cls,app_package): ''' only close app . keep the session''' result = re.search(".*%s\r\n" %app_package,os.popen("adb shell ps").read()) if result: pid = re.findall("\w+",result.group())[1] f=open("tmp",'w') f.write("su\r\nkill -9 %s\r\nexit\r\nexit\r\n" %pid) f.close() os.system("adb shell <tmp") os.remove("tmp") @classmethod def IsAppInstalled(cls,app_package): ''' app_package app_component apk_path ''' if re.search(app_package,os.popen("adb shell pm list packages").read()): result = True else: result = False time.sleep(0.5) return result @classmethod def InstallApp(cls,apk_path): ''' install the app to mobile apk_path=r"c:\test.apk" ''' getattr(p_m_env.DEVICE,"installPackage")(apk_path) time.sleep(0.5) @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod class MobileElement(): ''' Mobile App Element Test.(need MonkeyRunner + Hierarchy)''' (by,value,parent,timeout) = (None,None,None,30) @classmethod @classmethod @classmethod def Swipe(cls,duration=2,steps=100): ''' 模拟用户滑动 cls.by = "positon" cls.value = [100,100,200,200] duration --> 设置拖动过程的耗时 steps --> 设置拖动过程的步长，步长较短的话，效果就是长按 ''' if cls.by == "position": if not isinstance(cls.value, list): raise Exception("Need list type:",cls.value) getattr(p_m_env.DEVICE,"drag'")((cls.value[0],cls.value[1]),(cls.value[2],cls.value[3]),duration,steps) @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod @classmethod if __name__ == "__main__": # monkeyrunner driver.py #等待连接 MobileApp.WaitForConnection() #登录的示例 component = "com.tianwen.aischool/.ui.publics.login.LoginActivity" MobileApp.LaunchApp(component) print "launch app ok" # 截图 MobileElement.by = "id" MobileElement.value = "id/login_user_img" MobileElement.SaveCurrentImageToFile(r"d:\auto\buffer\test.png") print "Saving a picture to a file. ok" #用户名 MobileElement.by = "id" MobileElement.value = "id/login_account_input";#使用android sdk中的工具-->hierarchyviewer.bat查看。还有一个辅助工具 uiautomatorviewer.bat MobileElement.TypeInClear("brucestudent1") print "Typing username(brucestudent1) ok" #密码 (MobileElement.by,MobileElement.value) = ("id","id/login_password_input") MobileElement.TypeInClear("123456") print "Typing password(123456) ok" #登录按钮 (MobileElement.by,MobileElement.value) = ("id","id/login_start_button") MobileElement.Touch() print "Tap login button ok" #验证信息 (MobileElement.by,MobileElement.value) = ("id","id/login_error_tip_text") result = MobileElement.GetText() print "verify login info" print "-->",result if "正在登录" in result: print "Login Test Pass" else: print "Login Test Fail" # 点击练习作业 print "->click link_text" (MobileElement.by,MobileElement.value,MobileElement.parent,MobileElement.timeout) = ("link_text",u"练习作业","id/homepage_exercise",30) MobileElement.Touch() print "Link_text is ok" # 点击练习作业 print "->click index" (MobileElement.by,MobileElement.value,MobileElement.parent) = ("index",[0,0,1,0],"id/grid") MobileElement.Touch() print "Index is ok"

33.680258

140

0.568652

# -*- encoding: utf-8 -*- ''' Current module: mobile.monkeyrunner.driver Rough version history: v1.0 Original version to use ******************************************************************** @AUTHOR: Administrator-Bruce Luo(罗科峰) MAIL: lkf20031988@163.com RCS: rock4.softtest.pad.hierarchy.driver,v 2.0 2017年2月7日 FROM: 2015年12月23日 ******************************************************************** ====================================================================== Android UI automation frame for python. Jython-monkeyrunner--need use jython to compileall monkeyrunner.jar & chimpchat.jar & hierarchyviewer2lib.jar ''' from com.android.monkeyrunner import MonkeyRunner,MonkeyDevice from com.android.monkeyrunner.easy import By,EasyMonkeyDevice from com.android.chimpchat.hierarchyviewer import HierarchyViewer import os,re,time import p_m_env class MobileApp(): ''' Mobile App Test.(need MonkeyRunner + Hierarchy)''' @classmethod def WaitForConnection(cls): print """ Connecting the device... Please check blow, if without an connection in long time: 1. USB-debug model is enabled 2. Device driver is installed """ p_m_env.DEVICE = MonkeyRunner.waitForConnection();#命令: adb wait-for-device print "connect ok" p_m_env.EASY_DEVICE = EasyMonkeyDevice(p_m_env.DEVICE) print "connect easy ok" p_m_env.HIERARCHY = p_m_env.DEVICE.getHierarchyViewer() print "connect hierarchy ok" @classmethod def LaunchApp(cls,app_component): # sample: app_component = com.mytest.aischool/.ui.publics.login.LoginActivity # adb shell am start -W -n com.tianwen.aischool/.ui.publics.login.LoginActivity getattr(p_m_env.DEVICE,"startActivity")(component=app_component) time.sleep(0.5) @classmethod def CloseApp(cls,app_package): ''' only close app . keep the session''' result = re.search(".*%s\r\n" %app_package,os.popen("adb shell ps").read()) if result: pid = re.findall("\w+",result.group())[1] f=open("tmp",'w') f.write("su\r\nkill -9 %s\r\nexit\r\nexit\r\n" %pid) f.close() os.system("adb shell <tmp") os.remove("tmp") @classmethod def IsAppInstalled(cls,app_package): ''' app_package app_component apk_path ''' if re.search(app_package,os.popen("adb shell pm list packages").read()): result = True else: result = False time.sleep(0.5) return result @classmethod def InstallApp(cls,apk_path): ''' install the app to mobile apk_path=r"c:\test.apk" ''' getattr(p_m_env.DEVICE,"installPackage")(apk_path) time.sleep(0.5) @classmethod def RemoveApp(cls,app_package): # sample: app_package = com.mytest.testschool # adb uninstall com.mytest.testschool getattr(p_m_env.DEVICE,"removePackage")(app_package) time.sleep(0.5) @classmethod def Click(cls,x,y): p_m_env.DEVICE.touch(x,y,MonkeyDevice.DOWN_AND_UP) @classmethod def TypeRaw(cls,msg): p_m_env.DEVICE.type(msg) @classmethod def WaitSecond(cls,sec): MonkeyRunner.sleep(sec) @classmethod def ShotScreen(cls,file_path): p_m_env.DEVICE.takeSnapshot().writeToFile(file_path,'png') @classmethod def Enter(cls): cls.Keyevent("KEYCODE_ENTER") @classmethod def GetCurrentActivity(cls): return getattr(p_m_env.HIERARCHY,"getFocusedWindowName")() @classmethod def Keyevent(cls,key_code_name): #adb shell input keyevent KEYCODE_HOME getattr(p_m_env.DEVICE,"press")(key_code_name,MonkeyDevice.DOWN_AND_UP) @classmethod def Back(cls): cls.Keyevent("KEYCODE_BACK") @classmethod def Menu(cls): cls.Keyevent("KEYCODE_MENU") @classmethod def Home(cls): cls.Keyevent("KEYCODE_HOME") @classmethod def Tab(cls): cls.Keyevent("KEYCODE_TAB") @classmethod def PageSwapUP(cls): cls.Keyevent(92);# KEYCODE_PAGE_UP @classmethod def PageSwapDOWN(cls): cls.Keyevent(93);# KEYCODE_PAGE_DOWN @classmethod def CursorUP(cls): cls.Keyevent(19);# KEYCODE_DPAD_UP @classmethod def CursorDOWN(cls): cls.Keyevent(20);# KEYCODE_DPAD_DOWN @classmethod def CursorLEFT(cls): cls.Keyevent(21);# KEYCODE_DPAD_LEFT @classmethod def CursorRIGHT(cls): cls.Keyevent(22);# KEYCODE_DPAD_RIGHT @classmethod def CursorMoveToHOME(cls): cls.Keyevent(122);# KEYCODE_MOVE_HOME @classmethod def CursorMoveToEND(cls): cls.Keyevent(123);# KEYCODE_MOVE_END @classmethod def selectCurrentCursor(cls): cls.Keyevent(23);# KEYCODE_DPAD_CENTER class MobileElement(): ''' Mobile App Element Test.(need MonkeyRunner + Hierarchy)''' (by,value,parent,timeout) = (None,None,None,30) @classmethod def Touch(cls): if cls.by == "position": if not isinstance(cls.value, list): raise Exception("Need list type:",cls.value) p_m_env.DEVICE.touch(cls.value[0],cls.value[1],MonkeyDevice.DOWN_AND_UP) else: point = cls.GetElementCenterPoint() p_m_env.DEVICE.touch(point.x,point.y,MonkeyDevice.DOWN_AND_UP) @classmethod def LongTouch(cls): if cls.by == "position": if not isinstance(cls.value, list): raise Exception("Need list type:",cls.value) getattr(p_m_env.DEVICE,"drag'")((cls.value[0],cls.value[1]),(cls.value[0],cls.value[1]),1,3) else: point = cls.GetElementCenterPoint() getattr(p_m_env.DEVICE,"drag'")((point.x,point.y),(point.x,point.y),0.5,10) @classmethod def Swipe(cls,duration=2,steps=100): ''' 模拟用户滑动 cls.by = "positon" cls.value = [100,100,200,200] duration --> 设置拖动过程的耗时 steps --> 设置拖动过程的步长，步长较短的话，效果就是长按 ''' if cls.by == "position": if not isinstance(cls.value, list): raise Exception("Need list type:",cls.value) getattr(p_m_env.DEVICE,"drag'")((cls.value[0],cls.value[1]),(cls.value[2],cls.value[3]),duration,steps) @classmethod def SwipeToObj(cls,dest_obj,duration=2,steps=3): if cls.by == "position": if not isinstance(cls.value, list): raise Exception("Need list type:",cls.value) src_xy = [cls.value[0], cls.value[0]] else: point1 = cls.GetElementCenterPoint() src_xy = [point1.x, point1.y] if dest_obj.by == "positon": if not isinstance(dest_obj.value, list): raise Exception("Need list type:",cls.value) dest_xy = [dest_obj.value[0], dest_obj.value[0]] else: point2 = dest_obj.GetElementCenterPoint() dest_xy = [point2.x, point2.y] getattr(p_m_env.DEVICE,"drag'")((src_xy[0],src_xy[1]),(dest_xy[0],dest_xy[1]),duration,steps) @classmethod def Type(cls, msg): if msg == "": return if msg == "SET_EMPTY": msg = "" cls.Touch() p_m_env.DEVICE.type(msg) @classmethod def TypeInClear(cls, msg): if msg == "": return if msg == "SET_EMPTY": msg = "" cls.Touch() text = cls.GetText() for i in range(len(text)): p_m_env.DEVICE.press('KEYCODE_DEL', MonkeyDevice.DOWN_AND_UP) p_m_env.DEVICE.press('KEYCODE_FORWARD_DEL', MonkeyDevice.DOWN_AND_UP) p_m_env.DEVICE.type(msg) @classmethod def SendEnter(cls): getattr(p_m_env.DEVICE,"press")("KEYCODE_ENTER",MonkeyDevice.DOWN_AND_UP) @classmethod def GetText(cls): view_node = cls.__get_view_node() return p_m_env.HIERARCHY.getText(view_node).encode("utf-8") @classmethod def SaveCurrentImageToFile(cls,file_path): if not os.path.isdir(os.path.dirname(file_path)): raise Exception("invalid file: %s" %file_path) view_node = cls.__get_view_node() screen_snapshot = getattr(p_m_env.DEVICE,"takeSnapshot")() point = p_m_env.HIERARCHY.getAbsolutePositionOfView(view_node) sub_img = screen_snapshot.getSubImage((point.x,point.y,view_node.width,view_node.height)) return sub_img.writeToFile(file_path) @classmethod def GetFocusedWindowName(cls): return getattr(p_m_env.HIERARCHY,"getFocusedWindowName")() @classmethod def GetElementCenterPoint(cls): view_node = cls.__get_view_node() point = p_m_env.HIERARCHY.getAbsoluteCenterOfView(view_node) print "center of view:",point return point @classmethod def GetElementRectPoint(cls): view_node = cls.__get_view_node() point = p_m_env.HIERARCHY.getAbsolutePositionOfView(view_node) (left,top) = (point.x,point.y) (right,bottom) = (point.x + view_node.width,point.y + view_node.height) return [(left,top),(right,bottom)] @classmethod def GetAttribute(cls, attr): view_node = cls.__get_view_node() return view_node.namedProperties @classmethod def IsExist(cls): if cls.__get_view_node(): return True return False @classmethod def IsVisible(cls): view_node = cls.__get_view_node() if not view_node: return False return p_m_env.HIERARCHY.visible(view_node) @classmethod def __getPropertyList(cls): return p_m_env.DEVICE.getPropertyList() @classmethod def __get_view_node(cls): view_node = None if cls.by == "id": view_node = cls.__find_element_by_id(cls.value) elif cls.by == "link_text": view_node = cls.__find_element_by_link_text(cls.parent,cls.value) elif cls.by == "index": view_node = cls.__find_element_by_index(cls.parent,cls.value) return view_node @classmethod def __wait(cls,aid): # MonkeyRunner search element need id(parent id or self id) endtime = time.time() + cls.timeout while True: view_node = p_m_env.HIERARCHY.findViewById(aid) if view_node: # print "-->'%s' is OK" %aid return view_node elif time.time()>endtime: # raise Exception("Timeout at %d seconds.Element(%s-%s-%s) not found." %(cls.timeout,cls.by,repr(cls.value),cls.parent)) print "Warning: Timeout at %d seconds.Element(%s-%s-%s) not found." %(cls.timeout,cls.by,repr(cls.value),cls.parent) return @classmethod def __find_element_by_id(cls,aid): # Sample usage: # node = __find_element_by_id("id/login_account_input") return cls.__wait(aid) @classmethod def __find_element_by_link_text(cls,root_id,strs): #Sample usage: # u"科目" --> u'\u79d1\u76ee' # node=__find_element_by_link_text(id,u'\u79d1\u76ee') if not isinstance(strs,unicode): raise Exception("Need unicode string:",strs) view_node = cls.__find_element_by_id(root_id) return cls.__search_element(view_node,strs) @classmethod def __find_element_by_index(cls,root_id,index_list): # sample usage: # __find_element_by_index("id/grid",[0,0,1,0]) if not isinstance(index_list,list): raise Exception("Need list type:",index_list) view_node = cls.__find_element_by_id(root_id) return cls.__search_element(view_node,index_list) @classmethod def __search_element(cls,child_node,strs_or_list): if not child_node: return # 依据index列表，返回节点 if isinstance(strs_or_list, list): for i in strs_or_list: if child_node.children: child_node = child_node.children[i] else: return return child_node # 递归遍历,返回节点 if "TextView" in child_node.name: mText = child_node.namedProperties.get("text:mText") if mText and mText.value == strs_or_list: # print strs_or_list.encode("utf-8") # print mText.value.encode("utf-8") return child_node else: for child in child_node.children: result = cls.__search_element(child,strs_or_list) if result: return result if __name__ == "__main__": # monkeyrunner driver.py #等待连接 MobileApp.WaitForConnection() #登录的示例 component = "com.tianwen.aischool/.ui.publics.login.LoginActivity" MobileApp.LaunchApp(component) print "launch app ok" # 截图 MobileElement.by = "id" MobileElement.value = "id/login_user_img" MobileElement.SaveCurrentImageToFile(r"d:\auto\buffer\test.png") print "Saving a picture to a file. ok" #用户名 MobileElement.by = "id" MobileElement.value = "id/login_account_input";#使用android sdk中的工具-->hierarchyviewer.bat查看。还有一个辅助工具 uiautomatorviewer.bat MobileElement.TypeInClear("brucestudent1") print "Typing username(brucestudent1) ok" #密码 (MobileElement.by,MobileElement.value) = ("id","id/login_password_input") MobileElement.TypeInClear("123456") print "Typing password(123456) ok" #登录按钮 (MobileElement.by,MobileElement.value) = ("id","id/login_start_button") MobileElement.Touch() print "Tap login button ok" #验证信息 (MobileElement.by,MobileElement.value) = ("id","id/login_error_tip_text") result = MobileElement.GetText() print "verify login info" print "-->",result if "正在登录" in result: print "Login Test Pass" else: print "Login Test Fail" # 点击练习作业 print "->click link_text" (MobileElement.by,MobileElement.value,MobileElement.parent,MobileElement.timeout) = ("link_text",u"练习作业","id/homepage_exercise",30) MobileElement.Touch() print "Link_text is ok" # 点击练习作业 print "->click index" (MobileElement.by,MobileElement.value,MobileElement.parent) = ("index",[0,0,1,0],"id/grid") MobileElement.Touch() print "Index is ok"

8,700

0

1,227

fa017755b8936f4b18dedb46a5a32403feb76580

452

py

Python

app/api/v1/models/usermodels.py

kiruidavid/SendIT254

ee14fdcd0964d18cc93312aec39987a0753e09f1

[ "MIT" ]

null

app/api/v1/models/usermodels.py

kiruidavid/SendIT254

ee14fdcd0964d18cc93312aec39987a0753e09f1

[ "MIT" ]

null

app/api/v1/models/usermodels.py

kiruidavid/SendIT254

ee14fdcd0964d18cc93312aec39987a0753e09f1

[ "MIT" ]

null

users = []

13.294118

67

0.579646

users = [] class Users(object): def __init__(self): self.db = users def create_account(self, email, phone_number, user_name, password): account = { "user_id": str(len(users) + 1), "email": email, "phone_number": phone_number, "user_name": user_name, "password": password } self.db.append(account) return account def get_users(self): res = self.db return res

333

-1

97

a2064944d6fc7908c704e0375eec3db9c30f3880

2,787

py

Python

core.py

vitus9988/arcalive_con_downloader

5e1612ab015565f95da0dba68e302375fc827695

[ "MIT" ]

null

core.py

vitus9988/arcalive_con_downloader

5e1612ab015565f95da0dba68e302375fc827695

[ "MIT" ]

null

core.py

vitus9988/arcalive_con_downloader

5e1612ab015565f95da0dba68e302375fc827695

[ "MIT" ]

null

# -*- coding: utf-8 -*- from bs4 import BeautifulSoup import requests import urllib.request from moviepy.video.io.VideoFileClip import VideoFileClip import os if __name__ == '__main__': #main('https://arca.live/e/56?target=title&keyword=%EB%9D%BC%EC%98%A4&sort=rank&p=1') con_download()

30.626374

146

0.527449

# -*- coding: utf-8 -*- from bs4 import BeautifulSoup import requests import urllib.request from moviepy.video.io.VideoFileClip import VideoFileClip import os def wc(url): headers = { "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.87 Safari/537.36"} html = requests.get(url, headers=headers).text soup = BeautifulSoup(html, "lxml") return soup def main(url): headers = { "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.87 Safari/537.36"} soup = wc(url) title = soup.find('div','title-row').text.strip() detail = soup.find('div','emoticons-wrapper') maintab = detail.find_all(loading='lazy') count = 1 if os.path.exists("{}".format(title)): print('이미 존재하는 콘') else: os.makedirs("{}".format(title)) for i in maintab: link = i.get('src') if link is None: link = i.get('data-src') print("http://{}".format(link[2:])) imglink = "http://{}".format(link[2:]) request_ = urllib.request.Request(imglink, None, headers) response = urllib.request.urlopen(request_) result = imglink.split('.') filetype = ''.join(result[-1]) if filetype == 'mp4': with open('{}/{}.{}'.format(title, count, filetype), "wb") as file: file.write(response.read()) mp4togif('{}/{}.{}'.format(title, count, filetype)) count += 1 else: with open('{}/{}.{}'.format(title, count, filetype), "wb") as file: file.write(response.read()) count += 1 remover(f"{title}") def mp4togif(filename): clip = VideoFileClip(filename) rename = filename.replace('.mp4', '.gif') clip.write_gif(rename, fps=30, fuzz=1) return clip def remover(filepath): filelist = os.listdir(filepath) for file in filelist: if 'mp4' in file: try: os.remove(f"{filepath}/{file}") except: print('mp4파일 삭제 오류') else: pass def con_download(): while 1: conUrl = input("원하는 콘 url을 입력하세요(종료하려면 q를 입력): ") if conUrl == 'q' or conUrl == 'Q' or conUrl == 'ㅂ': break else: try: main(conUrl) except: print('유효하지 않은 url이거나 잘못된 url') if __name__ == '__main__': #main('https://arca.live/e/56?target=title&keyword=%EB%9D%BC%EC%98%A4&sort=rank&p=1') con_download()

2,434

0

125

c82e1da6da58dbb8b151c18c5241dc8a78e80db8

5,215

py

Python

core/commands/create_domain.py

M-Spencer-94/configNOW

56828587253202089e77cfdfcf5329f2a7f09b3f

[ "PSF-2.0", "Apache-2.0", "MIT" ]

3

2019-07-09T20:02:48.000Z

2021-11-21T20:00:37.000Z

core/commands/create_domain.py

M-Spencer-94/configNOW

56828587253202089e77cfdfcf5329f2a7f09b3f

[ "PSF-2.0", "Apache-2.0", "MIT" ]

null

core/commands/create_domain.py

M-Spencer-94/configNOW

56828587253202089e77cfdfcf5329f2a7f09b3f

[ "PSF-2.0", "Apache-2.0", "MIT" ]

null

# ============================================================================ # # Copyright (c) 2007-2010 Integral Technology Solutions Pty Ltd, # All Rights Reserved. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OF THIRD PARTY RIGHTS. # IN NO EVENT SHALL THE COPYRIGHT HOLDER OR HOLDERS INCLUDED IN THIS NOTICE BE # LIABLE FOR ANY CLAIM, OR ANY SPECIAL INDIRECT OR CONSEQUENTIAL DAMAGES, OR # ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER # IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT # OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. # # FOR FURTHER INFORMATION PLEASE SEE THE INTEGRAL TECHNOLOGY SOLUTIONS # END USER LICENSE AGREEMENT (ELUA). # # ============================================================================ import common.assertions as assertions import common.logredirect as logredirect from java.io import File execfile('wlst/common.py') execfile('wlst/server.py') execfile('wlst/workmgr.py') execfile('wlst/deployment.py') execfile('wlst/createDomain.py') execfile('wlst/jdbc_offline.py') def run(cfg): """Create WebLogic Domain""" assertions.sanityCheckInstall(cfg) assertions.sanityCheckDomainConfig(cfg) if wlst_support: logredirect.setup() create_domain(cfg) else: raise Exception('WLST support required for this command')

42.398374

123

0.653883

# ============================================================================ # # Copyright (c) 2007-2010 Integral Technology Solutions Pty Ltd, # All Rights Reserved. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OF THIRD PARTY RIGHTS. # IN NO EVENT SHALL THE COPYRIGHT HOLDER OR HOLDERS INCLUDED IN THIS NOTICE BE # LIABLE FOR ANY CLAIM, OR ANY SPECIAL INDIRECT OR CONSEQUENTIAL DAMAGES, OR # ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER # IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT # OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. # # FOR FURTHER INFORMATION PLEASE SEE THE INTEGRAL TECHNOLOGY SOLUTIONS # END USER LICENSE AGREEMENT (ELUA). # # ============================================================================ import common.assertions as assertions import common.logredirect as logredirect from java.io import File execfile('wlst/common.py') execfile('wlst/server.py') execfile('wlst/workmgr.py') execfile('wlst/deployment.py') execfile('wlst/createDomain.py') execfile('wlst/jdbc_offline.py') def run(cfg): """Create WebLogic Domain""" assertions.sanityCheckInstall(cfg) assertions.sanityCheckDomainConfig(cfg) if wlst_support: logredirect.setup() create_domain(cfg) else: raise Exception('WLST support required for this command') def create_domain(configProperties): domainPath=configProperties.getProperty('wls.domain.dir') domainName=configProperties.getProperty('wls.domain.name') domainAppDir=configProperties.getProperty('wls.domain.app.dir') webLogicHome=configProperties.getProperty('wls.oracle.home') osbname=configProperties.getProperty('osb.name') soaname=configProperties.getProperty('soa.name') version=configProperties.getProperty('wls.version') try: if domainName=='': log.error("wls.domain.name property can't be empty") raise Exception('wls.domain.name property can not be empty') domainFullPath=str(domainPath) + '/' + str(domainName) checkDomainExistence(domainFullPath) log.info('Creating domain: ' + domainFullPath) __createDomain(configProperties) log.info("Reading domain") readDomain(domainFullPath) if version == '12' and (not soaname is None): log.debug("not plain WLS domain") jrfTemplateLoc=configProperties.getProperty('wls.template.jrf.file') ServiceTableName=configProperties.getProperty('jdbc.datasource.LocalSvcTblDataSource.Name') ServiceTableUser=configProperties.getProperty('jdbc.datasource.LocalSvcTblDataSource.Username') ServiceTableURL=configProperties.getProperty('jdbc.datasource.LocalSvcTblDataSource.URL') ServiceTableDriver=configProperties.getProperty('jdbc.datasource.LocalSvcTblDataSource.Driver') ServiceTablePassword=configProperties.getProperty('jdbc.datasource.LocalSvcTblDataSource.Password') __addTemplate(configProperties) log.info("Connecting to Service table") cd('/JDBCSystemResources/'+ServiceTableName+'/JdbcResource/'+ServiceTableName+'') cd('JDBCDriverParams/NO_NAME_0') set('DriverName','oracle.jdbc.OracleDriver') set('URL',ServiceTableURL) set('PasswordEncrypted',ServiceTablePassword) cd('Properties/NO_NAME_0') cd('Property/user') cmo.setValue(ServiceTableUser) log.debug(ServiceTableURL) log.debug(ServiceTableUser) log.info('Connected to ServiceTable'+ServiceTableName+'......Fetching DB Schema details now') getDatabaseDefaults() #print 'Coherence changes' #cd('/') #cd('Server/soa_server1') #create('member_config', 'CoherenceMemberConfig') #cd('CoherenceMemberConfig/member_config') #set('UnicastListenAddress', '121.0.0.1') log.debug('Finished updating 12c changes') else: __addTemplate(configProperties) __createMachines(0, configProperties) __createClusters(0, configProperties) __createServers(0, configProperties) __createWorkManagers(0, configProperties) __configureDeployments(0, configProperties) __configureDataSources(configProperties) log.info("Closing Template NOW") updateDomain() closeDomain() except Exception, error: log.error('Unable to create domain [' + str(domainPath) + '/' + str(domainName) + ']') raise error # __processPostDomainCreation(configProperties) def checkDomainExistence(domainPath): if File(domainPath).exists(): raise Exception('Cannot create domain as it already exists at ' + domainPath)

3,646

0

23

c56c8fcafd417e7a3375947337c8289dd86cfdbd

781

py

Python

urlunquote.py

kmorwood/mrequests

957b9a7496cb7514cb3c1270883f40e038a7e1ce

[ "MIT" ]

5

2021-08-14T15:58:29.000Z

2022-02-24T23:11:19.000Z

urlunquote.py

kmorwood/mrequests

957b9a7496cb7514cb3c1270883f40e038a7e1ce

[ "MIT" ]

2

2021-09-15T12:32:28.000Z

2022-01-10T02:32:31.000Z

urlunquote.py

kmorwood/mrequests

957b9a7496cb7514cb3c1270883f40e038a7e1ce

[ "MIT" ]

1

2021-11-28T16:46:04.000Z

def unquote(string): """Decode and replace URL percent-escapes in string. unquote('abc%20def') -> b'abc def'. Note: If a string, not a bytes object, is passed, it is encoded as UTF-8. This is only an issue if it contains unescaped non-ASCII characters, which URIs should not. """ if not string: return b'' if isinstance(string, str): string = string.encode('utf-8') bits = string.split(b'%') if len(bits) == 1: return string res = bytearray(bits[0]) append = res.append extend = res.extend for item in bits[1:]: try: append(int(item[:2], 16)) extend(item[2:]) except KeyError: append(b'%') extend(item) return bytes(res)

22.970588

78

0.564661

def unquote(string): """Decode and replace URL percent-escapes in string. unquote('abc%20def') -> b'abc def'. Note: If a string, not a bytes object, is passed, it is encoded as UTF-8. This is only an issue if it contains unescaped non-ASCII characters, which URIs should not. """ if not string: return b'' if isinstance(string, str): string = string.encode('utf-8') bits = string.split(b'%') if len(bits) == 1: return string res = bytearray(bits[0]) append = res.append extend = res.extend for item in bits[1:]: try: append(int(item[:2], 16)) extend(item[2:]) except KeyError: append(b'%') extend(item) return bytes(res)

0

2127d7f5da8e00b3ae835b2e11ef891db0f2c08f

664

py

Python

meeting_room_booking_service/app/models/meeting_room_reservation.py

cassioeskelsen/microservice_boilerplate

c2c09d93095cc87e54f70095e74f13a97458e7d9

[ "Apache-2.0" ]

null

meeting_room_booking_service/app/models/meeting_room_reservation.py

cassioeskelsen/microservice_boilerplate

c2c09d93095cc87e54f70095e74f13a97458e7d9

[ "Apache-2.0" ]

null

meeting_room_booking_service/app/models/meeting_room_reservation.py

cassioeskelsen/microservice_boilerplate

c2c09d93095cc87e54f70095e74f13a97458e7d9

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- from mongoengine import EmbeddedDocument, StringField, Document, EmailField, EmbeddedDocumentField, DateTimeField

26.56

113

0.680723

#!/usr/bin/env python3 # -*- coding: utf-8 -*- from mongoengine import EmbeddedDocument, StringField, Document, EmailField, EmbeddedDocumentField, DateTimeField class Room(EmbeddedDocument): name = StringField() class Employeer(EmbeddedDocument): name = StringField() class RoomReservation(Document): def __init__(self, *args, **kwargs): super(Document, self).__init__(*args, **kwargs) self.employeer = Employeer() self.room = Room() datehour = DateTimeField() employer = EmbeddedDocumentField(Employeer) room = EmbeddedDocumentField(Room) meta = { 'collection' : 'room_reservations' }

135

299

69

0d33a1a4d1cd0a62230fae875e71caf4206bae3e

2,325

py

Python

backend/app/core/cache.py

luccasPh/gobarber

3bc84c5098b534352ef794428ffb7b937bd3bbd6

[ "MIT" ]

1

2021-05-05T15:43:25.000Z

backend/app/core/cache.py

luccasPh/gobarber

3bc84c5098b534352ef794428ffb7b937bd3bbd6

[ "MIT" ]

null

backend/app/core/cache.py

luccasPh/gobarber

3bc84c5098b534352ef794428ffb7b937bd3bbd6

[ "MIT" ]

null

from app.schemas.appointment import Appointment import pickle from redis import Redis from typing import Any from datetime import timedelta from app.models.user import User as UserModel from .config import settings

32.746479

75

0.588387

from app.schemas.appointment import Appointment import pickle from redis import Redis from typing import Any from datetime import timedelta from app.models.user import User as UserModel from .config import settings class RedisCache(Redis): def __init__(self): if(settings.REDIS_URL): temp = settings.REDIS_URL.split(':') port = temp[-1] temp = temp[2].split('@') password = temp[0] host = temp[1] super().__init__( host=host, port=port, password=password, username="" ) else: super().__init__( host=settings.REDIS_HOST, port=settings.REDIS_PORT, password=settings.REDIS_PASSWORD, username=settings.REDIS_USER ) def set_to_cache(self, key: str, value: Any) -> None: self.setex(key, timedelta(seconds=3600), value=pickle.dumps(value)) def get_from_cache(self, key: str) -> Any: data = self.get(key) if not data: return None return pickle.loads(data) def invalidate_cache(self, key: str) -> None: self.delete(key) def invalidate_cache_prefix(self, prefix: str) -> None: keys = self.keys(f"{prefix}:*") pipeline = self.pipeline() for key in keys: pipeline.delete(key) pipeline.execute() def invalidate_cache_provider(self, user: UserModel) -> None: """ Delete the cache of a specific provider through the relationship between user and appointment """ appointment: Appointment for appointment in user.user_appointments: prefix = f"providers-appointments:{appointment.provider_id}" if self.keys(f"{prefix}:*"): self.invalidate_cache_prefix(prefix) def invalidate_cache_user(self, provider: UserModel) -> None: """ Delete the cache of a specific user through the relationship between user/provider and appointment """ appointment: Appointment for appointment in provider.provider_appointments: prefix = f"user-appointments:{appointment.user_id}" self.delete(prefix)

1,082

1,005

22

b2f1e5909e2fbd5772b468609d91bf3631253923

358

py

Python

tests/test_common/test_nano.py

CraftSpider/SpiderTools

4bf155feec7cb983e8d283d93552902ec85178a2

[ "MIT" ]

5

2019-10-14T13:50:02.000Z

2021-09-23T18:48:27.000Z

tests/test_common/test_nano.py

CraftSpider/SpiderTools

4bf155feec7cb983e8d283d93552902ec85178a2

[ "MIT" ]

null

tests/test_common/test_nano.py

CraftSpider/SpiderTools

4bf155feec7cb983e8d283d93552902ec85178a2

[ "MIT" ]

null

import spidertools.common.nano as nano import os

22.375

65

0.701117

import spidertools.common.nano as nano import os async def test_nanoclient(): client = nano.NanoClient("talosbot", os.getenv("TALOS_PSWD")) await client.init() marcy = await client.get_user("marcyt") projects = await marcy.get_projects() user = await projects[0].get_user() assert marcy == user await client.get_fundometer()

284

0

23

84a2f6fe3ad381cfe5315c1bfe35729e95a4a951

919

py

Python

shpfixer/utils/precisionredux.py

francbartoli/ShapeFixer

dfb975cb4d10f0194eef1e7d5edef73bbac89d38

[ "MIT" ]

null

shpfixer/utils/precisionredux.py

francbartoli/ShapeFixer

dfb975cb4d10f0194eef1e7d5edef73bbac89d38

[ "MIT" ]

null

shpfixer/utils/precisionredux.py

francbartoli/ShapeFixer

dfb975cb4d10f0194eef1e7d5edef73bbac89d38

[ "MIT" ]

null

from shapely.geometry import * from utils import geomerremovertools class PrecisionRedux(object): """Class PrecisionRedux for managing the precision of geometries """ class PrecisionReduxPoint(PrecisionRedux): """Derived class for Point""" class PrecisionReduxMultiPoint(PrecisionRedux): """Derived class for MultiPoint""" class PrecisionReduxLineString(PrecisionRedux): """Derived class for LineString""" class PrecisionReduxMultiLineString(PrecisionRedux): """Derived class for MultiLineString"""

19.978261

65

0.761697

from shapely.geometry import * from utils import geomerremovertools class PrecisionRedux(object): """Class PrecisionRedux for managing the precision of geometries """ def __init__(self, arg): super(PrecisionRedux, self).__init__() self.arg = arg def round(): pass class PrecisionReduxPoint(PrecisionRedux): """Derived class for Point""" def round_point(input): if isinstance (Point,input): pass class PrecisionReduxMultiPoint(PrecisionRedux): """Derived class for MultiPoint""" def round_multipoint(input): if isinstance (Multipoint,input): pass class PrecisionReduxLineString(PrecisionRedux): """Derived class for LineString""" def round_linestring(input): if isinstance (Linestring,input): pass class PrecisionReduxMultiLineString(PrecisionRedux): """Derived class for MultiLineString""" def round_multilinestring(input): if isinstance (MultiLinestring,input): pass

263

0

145

bdc017c5baa8abcf99007f79e8a9e29fed22cec4

1,077

py

Python

python/reciept.py

AlexShukhman/smop-backend-PUBLIC

d0f54d963bc0a3860181213049f7f26851badcaa

[ "Apache-2.0" ]

null

python/reciept.py

AlexShukhman/smop-backend-PUBLIC

d0f54d963bc0a3860181213049f7f26851badcaa

[ "Apache-2.0" ]

null

python/reciept.py

AlexShukhman/smop-backend-PUBLIC

d0f54d963bc0a3860181213049f7f26851badcaa

[ "Apache-2.0" ]

null

import json, os, sys from openpyxl import load_workbook """ This script is for creating receipts for Smop coders using data given from mongo """ if __name__ == '__main__': main()

25.046512

80

0.652739

import json, os, sys from openpyxl import load_workbook """ This script is for creating receipts for Smop coders using data given from mongo """ def readIn(): lines = sys.stdin.readlines() return json.loads(lines[0]) def main(): lines = readIn() #Ensure in correct directory directory_name = './api/models/' # #template file name template_file_name = 'Smop_Sales_Receipt_Template1.xlsx' #winner's username winner_name = lines[1] #winner's email winner_email = lines[2] #task name task_name = lines[3] #owner name owner_name = lines[4] #bounty bounty = lines[0] print(bounty, winner_email, winner_name, task_name, owner_name) wb = load_workbook(filename = directory_name + template_file_name) ws1 = wb.active ws1['C5'] = winner_name ws1['C6'] = winner_email ws1['B11'] = 1.0 ws1['D11'] = 'Top 3 Payout for task "%s" by %s' % (task_name, owner_name) ws1['F11'] = bounty wb.save(filename = task_name + '_' + winner_name + '.xlsx') if __name__ == '__main__': main()

847

0

46

050cd1985aea466a75989d2e36e84cd9e064860b

3,740

py

Python

applications/welcome/controllers/meteoritepage.py

winmill2/CS-411-UFO-Meteorite-Finder

8a3ae102a18df6a6f45fc425383dfa0facb61d13

[ "BSD-3-Clause" ]

null

applications/welcome/controllers/meteoritepage.py

winmill2/CS-411-UFO-Meteorite-Finder

8a3ae102a18df6a6f45fc425383dfa0facb61d13

[ "BSD-3-Clause" ]

null

applications/welcome/controllers/meteoritepage.py

winmill2/CS-411-UFO-Meteorite-Finder

8a3ae102a18df6a6f45fc425383dfa0facb61d13

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- # try something like if not session.met_index: session.met_index = 0 if not session.met_sort: session.met_sort = 'ID' if not session.met_display_flash: session.met_display_flash = 'No' if not session.met_filter_cat: session.met_filter_cat = 'ID' session.met_filter_text = ''

34

143

0.663636

# -*- coding: utf-8 -*- # try something like if not session.met_index: session.met_index = 0 if not session.met_sort: session.met_sort = 'ID' if not session.met_display_flash: session.met_display_flash = 'No' if not session.met_filter_cat: session.met_filter_cat = 'ID' session.met_filter_text = '' def meteorite(): page_count = items_per_page index = session.met_index sort_selection = session.met_sort filter_category = session.met_filter_cat search_text = session.met_filter_text if session.met_display_flash == 'Yes': response.flash = 'That field is expecting an integer to be searched (no letters or symbols).' session.met_display_flash = 'No' if (filter_category == "ID") and (not search_text == ''): met_set = db(db.Meteorite_table.id == search_text) elif (filter_category == "Mass") and (not search_text == ''): met_set = db(db.Meteorite_table.mass == search_text) elif (filter_category == "Geo Location") and (not search_text == ''): met_set = db(db.Meteorite_table.GeoLocation.contains(search_text)) elif (filter_category == "Name") and (not search_text == ''): met_set = db(db.Meteorite_table.name.contains(search_text)) elif (filter_category == "Class") and (not search_text == ''): met_set = db(db.Meteorite_table.class_met.contains(search_text)) elif (filter_category == "Year Seen") and (not search_text == ''): met_set = db(db.Meteorite_table.year_seen == search_text) else: met_set = db(db.Meteorite_table) count = met_set.count() if session.met_sort == 'ID': rows = met_set.select(orderby=db.Meteorite_table.id) elif session.met_sort == 'Mass': rows = met_set.select(orderby=db.Meteorite_table.mass) elif session.met_sort == 'Geo Location': rows = met_set.select(orderby=db.Meteorite_table.GeoLocation) elif session.met_sort == 'Name': rows = met_set.select(orderby=db.Meteorite_table.name) elif session.met_sort == 'Class': rows = met_set.select(orderby=db.Meteorite_table.class_met) elif session.met_sort == 'Year Seen': rows = met_set.select(orderby=db.Meteorite_table.year_seen) else: rows = met_set.select(orderby=db.Meteorite_table.id) return locals() def next_page(): session.met_index = session.met_index + items_per_page redirect(URL('meteorite')) def prev_page(): session.met_index = session.met_index - items_per_page redirect(URL('meteorite')) def set_filter(): session.met_index = 0 if (request.vars.filter == 'ID' or request.vars.filter == 'Mass' or request.vars.filter == 'Year Seen') and request.vars.search_text != '': if request.vars.search_text.isdigit(): session.met_filter_cat = request.vars.filter session.met_filter_text = request.vars.search_text else: session.met_display_flash = 'Yes' else: session.met_filter_cat = request.vars.filter session.met_filter_text = request.vars.search_text redirect(URL('meteorite')) def reset_filter(): session.met_index = 0 session.met_filter_cat = None session.met_filter_text = '' redirect(URL('meteorite')) def sort_met(): session.met_index = 0 if request.args(0) == 'A': session.met_sort = 'ID' elif request.args(0) == 'B': session.met_sort = 'Mass' elif request.args(0) == 'C': session.met_sort = 'Geo Location' elif request.args(0) == 'D': session.met_sort = 'Name' elif request.args(0) == 'E': session.met_sort = 'Class' elif request.args(0) == 'F': session.met_sort = 'Year Seen' redirect(URL('meteorite'))

3,275

0

138

97a694e5b108ae18df8c6c74128996964290ff48

7,413

py

Python

checks/drc_checks/magic/magic_gds_drc_check.py

efabless/google_mpw_precheck

b30e779ab0ff90e37e5c56795066a30804816e13

[ "Apache-2.0" ]

17

2020-11-13T12:24:28.000Z

2021-09-03T08:47:15.000Z

checks/drc_checks/magic/magic_gds_drc_check.py

efabless/google_mpw_precheck

b30e779ab0ff90e37e5c56795066a30804816e13

[ "Apache-2.0" ]

22

2020-11-06T16:23:47.000Z

2021-07-09T16:19:25.000Z

checks/drc_checks/magic/magic_gds_drc_check.py

efabless/google_mpw_precheck

b30e779ab0ff90e37e5c56795066a30804816e13

[ "Apache-2.0" ]

14

2020-11-13T12:24:33.000Z

2021-08-13T03:14:30.000Z

import argparse import gzip import logging import os import re import subprocess from pathlib import Path try: from checks.drc_checks.magic.converters import magic_drc_to_rdb, magic_drc_to_tcl, magic_drc_to_tr_drc, tr2klayout except ImportError: from converters import magic_drc_to_rdb, magic_drc_to_tcl, magic_drc_to_tr_drc, tr2klayout def violations_count(drc_content): """ design name violation message list of violations Total Count: """ split_line = '----------------------------------------' drc_sections = drc_content.split(split_line) if len(drc_sections) == 2: return 0 else: vio_dict = dict() for i in range(1, len(drc_sections) - 1, 2): vio_dict[drc_sections[i]] = len(drc_sections[i + 1].split("\n")) - 2 count = 0 for key in vio_dict: val = vio_dict[key] count += val logging.error(f"Violation Message \"{str(key.strip())} \"found {str(val)} Times.") return count if __name__ == "__main__": logging.basicConfig(level=logging.DEBUG, format=f"%(asctime)s | %(levelname)-7s | %(message)s", datefmt='%d-%b-%Y %H:%M:%S') parser = argparse.ArgumentParser(description='Runs magic and klayout drc checks on a given GDS.') parser.add_argument('--gds_input_file_path', '-g', required=True, help='GDS File to apply DRC checks on') parser.add_argument('--output_directory', '-o', required=True, help='Output Directory') parser.add_argument('--pdk_root', '-p', required=True, help='PDK Path') parser.add_argument('--design_name', '-d', required=True, help='Design Name') args = parser.parse_args() gds_input_file_path = Path(args.gds_input_file_path) output_directory = Path(args.output_directory) pdk_root = Path(args.pdk_root) design_name = args.design_name if gds_input_file_path.exists() and gds_input_file_path.suffix == ".gds": if output_directory.exists() and output_directory.is_dir(): if magic_gds_drc_check(gds_input_file_path, args.design_name, pdk_root, output_directory): logging.info("Magic GDS DRC Clean") else: logging.info("Magic GDS DRC Dirty") else: logging.error(f"{output_directory} is not valid") else: logging.error(f"{gds_input_file_path} is not valid")

47.825806

140

0.70835

import argparse import gzip import logging import os import re import subprocess from pathlib import Path try: from checks.drc_checks.magic.converters import magic_drc_to_rdb, magic_drc_to_tcl, magic_drc_to_tr_drc, tr2klayout except ImportError: from converters import magic_drc_to_rdb, magic_drc_to_tcl, magic_drc_to_tr_drc, tr2klayout def check_if_binary_has(word, filename): f = gzip.open(filename, 'r', errors='ignore') if 'gz' in str(filename) else open(filename, errors='ignore') content = f.read() f.close() return int(bool(re.search(word, content))) def is_valid_magic_drc_report(drc_content): split_line = '----------------------------------------' drc_sections = drc_content.split(split_line) return len(drc_sections) >= 2 def violations_count(drc_content): """ design name violation message list of violations Total Count: """ split_line = '----------------------------------------' drc_sections = drc_content.split(split_line) if len(drc_sections) == 2: return 0 else: vio_dict = dict() for i in range(1, len(drc_sections) - 1, 2): vio_dict[drc_sections[i]] = len(drc_sections[i + 1].split("\n")) - 2 count = 0 for key in vio_dict: val = vio_dict[key] count += val logging.error(f"Violation Message \"{str(key.strip())} \"found {str(val)} Times.") return count def magic_gds_drc_check(gds_ut_path, design_name, pdk_root, output_directory): parent_directory = Path(__file__).parent logs_directory = output_directory / 'logs' outputs_directory = output_directory / 'outputs' reports_directory = outputs_directory / 'reports' design_magic_drc_file_path = reports_directory / f"magic_drc_check.drc.report" installed_sram_modules_names = [] sram_maglef_files_generator = Path(pdk_root / "sky130A" / "libs.ref" / "sky130_sram_macros" / "maglef").glob('*.mag') for installed_sram in sram_maglef_files_generator: installed_sram_modules_names.append(installed_sram.stem) sram_modules_in_gds = [] for sram in installed_sram_modules_names: if check_if_binary_has(sram, gds_ut_path): sram_modules_in_gds.append(sram) # only the name of the module magicrc_file_path = parent_directory.parent.parent / 'tech-files' / 'sky130A.magicrc' magic_drc_tcl_path = parent_directory / 'magic_drc_check.tcl' design_magic_drc_mag_file_path = outputs_directory / f"{design_name}.magic.drc.mag" esd_fet = 'sky130_fd_io__signal_5_sym_hv_local_5term' # cli arguments for a tcl script has to be a string has_sram_as_str = str(check_if_binary_has('sram', gds_ut_path)) has_esd_fet_as_str = str(check_if_binary_has('sky130_fd_io__signal_5_sym_hv_local_5term', gds_ut_path)) # TODO(ahmad.nofal@efabless.com): This should be a command line argument os.environ['MAGTYPE'] = 'mag' run_magic_drc_check_cmd = ['magic', '-noconsole', '-dnull', '-rcfile', magicrc_file_path, magic_drc_tcl_path, gds_ut_path, design_name, pdk_root, design_magic_drc_file_path, design_magic_drc_mag_file_path, ' '.join(sram_modules_in_gds), esd_fet, has_sram_as_str, has_esd_fet_as_str] magic_drc_log_file_path = logs_directory / 'magic_drc_check.log' with open(magic_drc_log_file_path, 'w') as magic_drc_log: process = subprocess.run(run_magic_drc_check_cmd, stderr=magic_drc_log, stdout=magic_drc_log) if not design_magic_drc_file_path.exists(): logging.error(f"No {design_magic_drc_file_path} file produced by the drc check") return False drc_violations_count = process.returncode if drc_violations_count != 0: drc_violations_count = (drc_violations_count + 3) / 4 # TODO(ahmad.nofal@efabless.com): Check validity magic_drc_total_file_path = logs_directory / 'magic_drc_check.total' with open(magic_drc_total_file_path, 'w') as magic_drc_total: magic_drc_total.write(str(drc_violations_count)) # Write all different formats for drc violations reports using converters try: design_magic_rdb_file_path = reports_directory / f"magic_drc_check.rdb" magic_drc_to_rdb.convert(design_magic_drc_file_path, design_magic_rdb_file_path) design_magic_drc_tcl_file_path = reports_directory / f"magic_drc_check.tcl" magic_drc_to_tcl.convert(design_magic_drc_file_path, design_magic_drc_tcl_file_path) design_tr_drc_file_path = reports_directory / f"magic_drc_check.tr" magic_drc_to_tr_drc.convert(design_magic_drc_file_path, design_tr_drc_file_path) design_klayout_xml_file_path = reports_directory / f"magic_drc_check.xml" tr2klayout.convert(design_tr_drc_file_path, design_klayout_xml_file_path, design_name) except Exception as e: logging.warning(f"Error generating DRC violation report(s), the full set of Magic DRC reports will not be generated. {e}") with open(magic_drc_log_file_path) as magic_drc_log: log_content = magic_drc_log.read() if log_content.find("was used but not defined.") != -1: logging.error(f"The GDS is not valid/corrupt contains cells that are used but not defined. Please check: {magic_drc_log_file_path}") return False if log_content.find("Unrecognized layer (type) name \"<<<<<\"") != -1: logging.error(f"The GDS is not valid/corrupt contains cells. Please check: {magic_drc_log_file_path}") return False with open(design_magic_drc_file_path) as magic_drc_report: drc_content = magic_drc_report.read() if not is_valid_magic_drc_report(drc_content): logging.error(f"Incomplete DRC Report. Maybe you ran out of RAM. Please check: {magic_drc_log_file_path}") return False else: count = violations_count(drc_content) logging.info(f"{count} DRC violations") if count == 0 else logging.error(f"{count} DRC violations") return True if count == 0 else False if __name__ == "__main__": logging.basicConfig(level=logging.DEBUG, format=f"%(asctime)s | %(levelname)-7s | %(message)s", datefmt='%d-%b-%Y %H:%M:%S') parser = argparse.ArgumentParser(description='Runs magic and klayout drc checks on a given GDS.') parser.add_argument('--gds_input_file_path', '-g', required=True, help='GDS File to apply DRC checks on') parser.add_argument('--output_directory', '-o', required=True, help='Output Directory') parser.add_argument('--pdk_root', '-p', required=True, help='PDK Path') parser.add_argument('--design_name', '-d', required=True, help='Design Name') args = parser.parse_args() gds_input_file_path = Path(args.gds_input_file_path) output_directory = Path(args.output_directory) pdk_root = Path(args.pdk_root) design_name = args.design_name if gds_input_file_path.exists() and gds_input_file_path.suffix == ".gds": if output_directory.exists() and output_directory.is_dir(): if magic_gds_drc_check(gds_input_file_path, args.design_name, pdk_root, output_directory): logging.info("Magic GDS DRC Clean") else: logging.info("Magic GDS DRC Dirty") else: logging.error(f"{output_directory} is not valid") else: logging.error(f"{gds_input_file_path} is not valid")

4,952

0

69