Reset23/the-stack-v2-python · Datasets at Hugging Face

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######### # Imports ######### import json import time import tkinter as tk from tkinter import * ################ # Open JSON File # ############## with open('stats.json', 'r') as string: my_dict = json.load(string) string.close() #################### # Global Variables #################### p0 = my_dict['points'] p1 = my_dict['player1'] p2 = my_dict['player2'] items = list(p0.items()) bottom = len(items) + 1 timeStr = time.strftime("%Y-%m-%d_%H%M") lxVarList = [] activityList = [] # Player 1 p1JSON = list(p1.items()) p1WeekStats = p1JSON[2] p1MonthStats = p1JSON[3] p1TotalJSON = p1JSON[4] p1statListWeekScores = p1WeekStats[1] p1statListMonthScores = p1MonthStats[1] p1Totals = p1TotalJSON[1] p1TotalWeek = p1Totals['total week'] # Player 2 p2JSON = list(p2.items()) p2WeekStats = p2JSON[2] p2MonthStats = p2JSON[3] p2TotalJSON = p2JSON[4] p2statListWeekScores = p2WeekStats[1] p2statListMonthScores = p2MonthStats[1] p2Totals = p2TotalJSON[1] p2TotalWeek = p2Totals['total week'] def viewStats(): viewS = tk.Tk() viewS.configure(bg="turquoise") viewS.geometry("545x700") viewS.title("Lvl^") addPGreeting = tk.Label(text="Current Stats:", bg="mediumturquoise", fg="black", font="10", width=60, pady=20) addPGreeting.grid(row=0, columnspan=6, sticky=EW) #################### # Columns #################### # Players p1PlayerOne = tk.Label(viewS, text=p1['name'], width=6) p1PlayerOne.grid(row=1, column=1, columnspan=2, sticky=EW) p2PlayerTwo = tk.Label(viewS, text=p2['name'], width=6) p2PlayerTwo.grid(row=1, column=3, columnspan=2, sticky=EW) # Player1 p1Week = tk.Label(viewS, text="Week", width=6) p1Week.grid(row=2, column=1, sticky=EW) p1Month = tk.Label(viewS, text="Month", width=6) p1Month.grid(row=2, column=2, sticky=EW) # Player2 p2Week = tk.Label(viewS, text="Week", width=6) p2Week.grid(row=2, column=3, sticky=EW) p2Month = tk.Label(viewS, text="Month", width=6) p2Month.grid(row=2, column=4, sticky=EW) ############################# # Populates the Activity List ############################# row = 3 for category in p1statListWeekScores: labelEntry = tk.Label(viewS, text=category, width=14) labelEntry.grid(row=row, column=0, sticky=EW, pady=3, padx=18) row += 1 def changeWindow(): viewS.destroy() from main import mainPage mainPage() ################ # Player 1 Stats ################ # week row = 3 for stat in p1statListWeekScores: point = str(p1statListWeekScores[stat]) p1WeekPoints = tk.Label(viewS, text=point, width=6) p1WeekPoints.grid(row=row, column=1, sticky=EW) row += 1 # month row = 3 for stat in p1statListMonthScores: point = str(p1statListMonthScores[stat]) p1WeekPoints = tk.Label(viewS, text=point, width=6) p1WeekPoints.grid(row=row, column=2, sticky=EW) row += 1 ################ # Player 2 Stats ################ # week row = 3 for stat in p2statListWeekScores: point = str(p2statListWeekScores[stat]) p2WeekPoints = tk.Label(viewS, text=point, width=6) p2WeekPoints.grid(row=row, column=3, sticky=EW) row += 1 # month row = 3 for stat in p2statListMonthScores: point = str(p2statListMonthScores[stat]) p2WeekPoints = tk.Label(viewS, text=point, width=6) p2WeekPoints.grid(row=row, column=4, sticky=EW) row += 1 ############ # Clear Week ############ def cWeek(): row = 3 for stat in p1statListWeekScores: p1statListWeekScores[stat] = 0 p1WeekPoints = tk.Label(viewS, text=p1statListWeekScores[stat], width=6) p1WeekPoints.grid(row=row, column=1, sticky=EW) row += 1 p1Totals['total week'] = 0 row = 3 for stat in p2statListWeekScores: p2statListWeekScores[stat] = 0 p2WeekPoints = tk.Label(viewS, text=p2statListWeekScores[stat], width=6) p2WeekPoints.grid(row=row, column=3, sticky=EW) row += 1 p2Totals['total week'] = 0 a_file = open("stats.json", "w") json.dump(my_dict, a_file) a_file.close() archive = open("stats" + timeStr + ".json", "w") json.dump(my_dict, archive) archive.close() ############# # Clear Month ############# def cMonth(): row = 3 for stat in p1statListMonthScores: p1statListMonthScores[stat] = 0 p1MonthPoints = tk.Label(viewS, text=p1statListMonthScores[stat], width=6) p1MonthPoints.grid(row=row, column=2, sticky=EW) row += 1 p1Totals['total month'] = 0 row = 3 for stat in p2statListMonthScores: p2statListMonthScores[stat] = 0 p2MonthPoints = tk.Label(viewS, text=p2statListMonthScores[stat], width=6) p2MonthPoints.grid(row=row, column=4, sticky=EW) row += 1 p2Totals['total month'] = 0 a_file = open("stats.json", "w") json.dump(my_dict, a_file) a_file.close() archive = open("stats" + timeStr + ".json", "w") json.dump(my_dict, archive) archive.close() ########################## # Go Back and Quit Buttons ########################## em1 = tk.Label(viewS, text="", width=40, bg="turquoise") em1.grid(row=bottom + 1, columnspan=5, sticky=EW, pady=3, padx=18) clearWeek = Button(viewS, text="Clear Week", command=cWeek, width=12) clearWeek.grid(row=bottom + 2, column=1, columnspan=2, sticky=EW, padx=6) clearMonth = Button(viewS, text="Clear Month", command=cMonth, width=12) clearMonth.grid(row=bottom + 2, column=3, columnspan=2, sticky=EW, padx=6) em2 = tk.Label(viewS, text="", width=40, bg="turquoise") em2.grid(row=bottom + 3, columnspan=5, sticky=EW, pady=3, padx=18) goBack = Button(viewS, text="Go back", command=lambda *args: changeWindow(), width=30) goBack.grid(row=bottom + 4, column=1, columnspan=4, sticky=EW, padx=10) quitG = Button(viewS, text="Quit", command=viewS.destroy, width=30) quitG.grid(row=bottom + 5, column=1, columnspan=4, sticky=EW, padx=10) viewS.mainloop()

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# Train a Bayesian LSTM on the IMDB sentiment classification task. # To use the GPU: # THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python imdb_lstm_regression.py # To speed up Theano, create a ram disk: # mount -t tmpfs -o size=512m tmpfs /mnt/ramdisk # Then add flag THEANO_FLAGS='base_compiledir=/mnt/ramdisk' from __future__ import absolute_import from __future__ import print_function import numpy as np import sys import theano from callbacks import ModelTest from dataset import loader from keras.optimizers import SGD, RMSprop, Adagrad from keras.models import Sequential from keras.layers.core import Dense, Dropout from keras.layers.embeddings import Embedding from keras.layers.recurrent import LSTM, GRU, SimpleRNN from keras.regularizers import l2 # Process inpus: if len(sys.argv) == 1: print("Expected args: p_W, p_U, p_dense, p_emb, weight_decay, batch_size, maxlen") print("Using default args:") # sys.argv = ["", "0.", "0.", "0.", "0.", "1e-4", "128", "200"] sys.argv = ["", "0.25", "0.25", "0.25", "0.25", "1e-4", "128", "200"] args = [float(a) for a in sys.argv[1:]] print(args) p_W, p_U, p_dense, p_emb, weight_decay, batch_size, maxlen = args batch_size = int(batch_size) maxlen = int(maxlen) folder = "/scratch/home/Projects/rnn_dropout/exps/" filename = ("sa_DropoutLSTM_pW_%.2f_pU_%.2f_pDense_%.2f_pEmb_%.2f_reg_%f_batch_size_%d_cutoff_%d_epochs" % (p_W, p_U, p_dense, p_emb, weight_decay, batch_size, maxlen)) print(filename) # Global params: nb_words = 20000 skip_top = 0 test_split = 0.2 init_seed = 0 global_seed = 0 # Load data: print("Loading data...") dataset = loader(init_seed, maxlen, nb_words, skip_top, test_split) X_train, X_test, Y_train, Y_test = dataset.X_train, dataset.X_test, dataset.Y_train, dataset.Y_test mean_y_train, std_y_train = dataset.mean_y_train, dataset.std_y_train # Set seed: np.random.seed(global_seed) # Build model: print('Build model...') model = Sequential() model.add(Embedding(nb_words + dataset.index_from, 128, W_regularizer=l2(weight_decay), dropout=p_emb, input_length=maxlen, batch_input_shape=(batch_size, maxlen))) model.add(LSTM(128, W_regularizer=l2(weight_decay), U_regularizer=l2(weight_decay), b_regularizer=l2(weight_decay), dropout_W=p_W, dropout_U=p_U)) model.add(Dropout(p_dense)) model.add(Dense(1, W_regularizer=l2(weight_decay), b_regularizer=l2(weight_decay))) #optimiser = SGD(lr=0.1, decay=1e-6, momentum=0.9, nesterov=False) optimiser = 'adam' model.compile(loss='mean_squared_error', optimizer=optimiser) # Potentially load weights # model.load_weights("path") # Train model print("Train...") # Theano modeltest_1 = ModelTest(X_train[:100], mean_y_train + std_y_train * np.atleast_2d(Y_train[:100]).T, test_every_X_epochs=1, verbose=0, loss='euclidean', mean_y_train=mean_y_train, std_y_train=std_y_train) modeltest_2 = ModelTest(X_test, np.atleast_2d(Y_test).T, test_every_X_epochs=1, verbose=0, loss='euclidean', mean_y_train=mean_y_train, std_y_train=std_y_train) model.fit(X_train, Y_train, batch_size=batch_size, nb_epoch=250, callbacks=[modeltest_1, modeltest_2]) # # Tensorflow # modeltest_1 = ModelTest(X_train[:batch_size], # mean_y_train + std_y_train * np.atleast_2d(Y_train[:batch_size]).T, # test_every_X_epochs=1, verbose=0, loss='euclidean', # mean_y_train=mean_y_train, std_y_train=std_y_train, batch_size=batch_size) # tensorflow_test_size = batch_size * (len(X_test) / batch_size) # modeltest_2 = ModelTest(X_test[:tensorflow_test_size], np.atleast_2d(Y_test[:tensorflow_test_size]).T, # test_every_X_epochs=1, verbose=0, loss='euclidean', # mean_y_train=mean_y_train, std_y_train=std_y_train, batch_size=batch_size) # tensorflow_train_size = batch_size * (len(X_train) / batch_size) # model.fit(X_train[:tensorflow_train_size], Y_train[:tensorflow_train_size], # batch_size=batch_size, nb_epoch=250, callbacks=[modeltest_1, modeltest_2]) # Potentially save weights # model.save_weights("path", overwrite=True) # Evaluate model # Dropout approximation for training data: standard_prob = model.predict(X_train, batch_size=500, verbose=1) print(np.mean(((mean_y_train + std_y_train * np.atleast_2d(Y_train).T) - (mean_y_train + std_y_train * standard_prob))**2, 0)**0.5) # Dropout approximation for test data: standard_prob = model.predict(X_test, batch_size=500, verbose=1) print(np.mean((np.atleast_2d(Y_test).T - (mean_y_train + std_y_train * standard_prob))**2, 0)**0.5) # MC dropout for test data: T = 50 prob = np.array([modeltest_2.predict_stochastic(X_test, batch_size=500, verbose=0) for _ in xrange(T)]) prob_mean = np.mean(prob, 0) print(np.mean((np.atleast_2d(Y_test).T - (mean_y_train + std_y_train * prob_mean))**2, 0)**0.5)

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/Ch1-Image_Recognition/stacked_autoencoders_for_mnist_classification.py

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# -*- coding: utf-8 -*- # MNIST 숫자 분류를 위한 Stacked AutoEncoder 예제 # 절대 임포트 설정 from __future__ import division, print_function, absolute_import # 필요한 라이브러리들을 임포트 import tensorflow as tf import numpy as np import matplotlib.pyplot as plt # MNIST 데이터를 다운로드 한다. from tensorflow.examples.tutorials.mnist import input_data mnist = input_data.read_data_sets("MNIST_data/", one_hot=True) # 파라미터 설정 learning_rate_RMSProp = 0.01 learning_rate_Gradient_Descent = 0.5 training_epochs = 400 # epoch 횟수 (iteration) batch_size = 256 display_step = 1 # 몇 Step마다 log를 출력할지 결정한다. examples_to_show = 10 # reconstruct된 이미지 중 몇개를 보여줄지를 결정한다. n_hidden_1 = 200 # 첫번째 히든레이어의 노드 개수 n_hidden_2 = 200 # 두번째 히든레이어의 노드 개수 n_input = 784 # MNIST 데이터 input (이미지 크기: 28*28) # Stacked Autoencoder를 위한 파라미터들 # Input 데이터 설정 X = tf.placeholder("float", [None, n_input]) # 히든 레이어 1을 위한 Weights와 Biases Wh_1 = tf.Variable(tf.random_normal([n_input, n_hidden_1])) bh_1 = tf.Variable(tf.random_normal([n_hidden_1])) h_1 = tf.nn.sigmoid(tf.matmul(X, Wh_1) +bh_1) # 히든레이어 1의 activation (sigmoid 함수를 사용) # 히든 레이어 2을 위한 Weights와 Biases Wh_2 = tf.Variable(tf.random_normal([n_hidden_1, n_hidden_2])) bh_2 = tf.Variable(tf.random_normal([n_hidden_2])) h_2 = tf.nn.sigmoid(tf.matmul(h_1, Wh_2) +bh_2) # 히든레이어 2의 activation (sigmoid 함수를 사용) # Output 레이어를 위한 Weights와 Biases Wo = tf.Variable(tf.random_normal([n_hidden_2, n_input])) bo = tf.Variable(tf.random_normal([n_input])) y_pred = tf.nn.sigmoid(tf.matmul(h_2,Wo) + bo) # Output 레이어의 activation (sigmoid 함수를 사용) # Output 값(True Output)을 설정(=Input 값) y_true = X # Softmax Classifier를 위한 파라미터들 W = tf.Variable(tf.zeros([n_hidden_2, 10])) b = tf.Variable(tf.zeros([10])) y = tf.nn.softmax(tf.matmul(h_2, W) + b) # 예측된 Output : 두번째 히든레이어의 activation output을 input으로 사용한다. y_ = tf.placeholder(tf.float32, [None, 10]) # True Output # Optimization을 위한 파라미터들 # Autoencoder Optimization을 위한 파라미터들 cost = tf.reduce_mean(tf.pow(y_true - y_pred, 2)) # squared error loss 함수 optimizer = tf.train.RMSPropOptimizer(learning_rate_RMSProp).minimize(cost) # Softmax Classifier Optimization을 위한 파라미터들 cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y), reduction_indices=[1])) # cross-entropy loss 함수 train_step = tf.train.GradientDescentOptimizer(learning_rate_Gradient_Descent).minimize(cross_entropy) # Fine Tuning Optimization을 위한 파라미터들 finetuning_cost = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y), reduction_indices=[1])) + tf.reduce_mean(tf.pow(y_true - y_pred, 2)) # cross-entropy loss 함수 + squared error loss 함수 finetuning_train_step = tf.train.GradientDescentOptimizer(learning_rate_Gradient_Descent).minimize(finetuning_cost) # Step 1: Stacked Autoencoder pre-training # 변수들을 초기화한다. init = tf.initialize_all_variables() # graph를 실행한다. sess = tf.Session() sess.run(init) total_batch = int(mnist.train.num_examples/batch_size) # Training을 시작한다. for epoch in range(training_epochs): # 모든 배치들을 돌아가면서(Loop) 학습한다. for i in range(total_batch): batch_xs, batch_ys = mnist.train.next_batch(batch_size) # batch 데이터를 이용해서 트레이닝을 진행한다. _, cost_value = sess.run([optimizer, cost], feed_dict={X: batch_xs}) # 일정 epoch step마다 로그를 출력한다. if epoch % display_step == 0: print("Epoch:", '%04d' % (epoch+1), "cost=", "{:.9f}".format(cost_value)) print("Stacked Autoencoder pre-training Optimization Finished!") # Step 2: test 데이터셋을 autoencoder로 reconstruction 해본다. reconstructed_image = sess.run(y_pred, feed_dict={X: mnist.test.images[:examples_to_show]}) # 원본 이미지와 재구축(reconstructed)된 이미지를 비교한다. f, a = plt.subplots(2, 10, figsize=(10, 2)) for i in range(examples_to_show): a[0][i].imshow(np.reshape(mnist.test.images[i], (28, 28))) a[1][i].imshow(np.reshape(reconstructed_image[i], (28, 28))) f.show() plt.draw() #plt.waitforbuttonpress() # 버튼을 누를때까지 작업 정지 f.savefig('reconstructed_mnist_image.png') # reconstruction 결과를 png로 저장한다. # Step 3: Softmax Classifier를 학습한다. for i in range(1000): batch_xs, batch_ys = mnist.train.next_batch(100) sess.run(train_step, feed_dict={X: batch_xs, y_: batch_ys}) print("Softmax Classifier Optimization Finished!") # Step 4: 학습된 모델이 얼마나 정확한지를 출력한다. (Before fine-tuning) correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1)) accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32)) print("Accuracy(before fine-tuning): ") # Accuracy ~ 0.9282 print(sess.run(accuracy, feed_dict={X: mnist.test.images, y_: mnist.test.labels})) # Step 5: Fine-tuning softmax model # Training을 시작한다. for epoch in range(training_epochs): # 모든 배치들을 돌아가면서(Loop) 학습한다. for i in range(total_batch): batch_xs, batch_ys = mnist.train.next_batch(batch_size) # batch 데이터를 이용해서 트레이닝을 진행한다. _, cost_value = sess.run([finetuning_train_step, finetuning_cost], feed_dict={X: batch_xs, y_: batch_ys}) # 일정 epoch step마다 로그를 출력한다. if epoch % display_step == 0: print("Epoch:", '%04d' % (epoch+1), "cost=", "{:.9f}".format(cost_value)) print("Fine-tuning softmax model Optimization Finished!") # Step 6: 학습된 모델이 얼마나 정확한지를 출력한다. (After fine-tuning) print("Accuracy(after fine-tuning): ") # Accuracy ~ 0.9714 print(sess.run(accuracy, feed_dict={X: mnist.test.images, y_: mnist.test.labels}))

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ASKED = 'asked' MASTER = 'enabled' def settings(): # always use "schema_id" once Fedora 20 is no longer supported import gi key = 'schema_id' if gi.version_info >= (3, 14) else 'schema' from gi.repository import Gio return Gio.Settings(**{key: 'edu.wisc.cs.cbi'})

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import pygame class Ship: # 飞船类 def __init__(self, ai_game): # 初始化飞船并初始化其位置 self.screen = ai_game.screen self.screen_rect = ai_game.screen.get_rect() # 加载飞船图像并获取其外接矩形 self.image = pygame.image.load( "/Users/shilin/Documents/VSCode/Python/alien_incasion/images/ship.png" ) # 改变飞船大小 self.image = pygame.transform.scale(self.image, (50, 50)) self.rect = self.image.get_rect() # 放置飞船到窗口底部中央 self.rect.midbottom = self.screen_rect.midbottom # 移动标志 self.moving_right = False self.moving_left = False self.moving_up = False self.moving_down = False self.settings = ai_game.settings # 在飞船的x属性中储存小数 self.x = float(self.rect.x) self.y = float(self.rect.y) def update(self): # 根据移动标志调整飞船位置 # 限制移动范围 if self.moving_right and self.rect.right < self.screen_rect.right: self.x += self.settings.ship_speed # 更新self.x的值 if self.moving_left and self.rect.left > 0: self.x -= self.settings.ship_speed if self.moving_up and self.rect.top > 0: self.y -= self.settings.ship_speed # 更新self.y的值 if self.moving_down and self.rect.bottom < self.screen_rect.bottom: self.y += self.settings.ship_speed # 根据self.x的值更新rect对象 self.rect.x = self.x self.rect.y = self.y def blitme(self): # 在指定位置绘制飞船 self.screen.blit(self.image, self.rect)

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import shutil, os from analysis.planner_3D import Planner from bins.analyze_and_preprocess import get_lists_of_splitted_dataset from preprocessing.preprocessor import Preprocessor2D from config.default_configs import * from utils.files_utils import * from net_architecture.generic_UNet import Generic_UNet import numpy as np from utils.analysis_utils import get_pool_and_conv_props class Planner2D(Planner): def __init__(self, folder_of_cropped_data, preprocessing_out_folder): super(Planner2D, self).__init__(folder_of_cropped_data, preprocessing_out_folder) self.data_identifier = "UNet_2D" self.transpose_forward = [0, 1, 2] self.transpose_backward = [0, 1, 2] self.plans_fname = join(self.preprocessing_out_folder, default_plans_identifier + "_plans_2D.pkl") def load_plans(self): self.plans = load_pickle(self.plans_fname) self.plans_per_stage = self.plans['plans_per_stage'] self.dataset_properties = self.plans['dataset_properties'] self.transpose_forward = self.plans['transpose_forward'] self.transpose_backward = self.plans['transpose_backward'] def plan_exps(self): def get_stage_properties(current_spacing, original_spacing, original_shape, num_cases, transpose_forward, num_modalities, num_classes): current_spacing_transposed = np.array([current_spacing[i] for i in transpose_forward])[1:] new_median_shape = np.round(original_spacing / current_spacing * original_shape).astype(int) dataset_num_voxels = np.prod(new_median_shape) * num_cases input_patch_size = new_median_shape[transpose_forward][1:] net_numpool, net_pool_kernel_sizes, net_conv_kernel_sizes, input_patch_size, \ shape_must_be_divisible_by = get_pool_and_conv_props(current_spacing_transposed, input_patch_size, FEATUREMAP_MIN_EDGE_LENGTH_BOTTLENECK, Generic_UNet.MAX_NUMPOOL_2D) estimated_gpu_ram_consumption = Generic_UNet.compute_vram_consumption(input_patch_size, net_numpool, Generic_UNet.BASE_NUM_FEATURES_2D, Generic_UNet.MAX_FILTERS_2D, num_modalities, num_classes, net_pool_kernel_sizes) batch_size = int(np.floor(Generic_UNet.use_this_for_batch_size_computation_2D / estimated_gpu_ram_consumption * Generic_UNet.DEFAULT_BATCH_SIZE_2D)) if batch_size < dataset_min_batch_size_cap: raise RuntimeError("Unsupported patches size. patch-based solution will be implemented later.") # check if batch size is too large (more than 5 % of dataset) max_batch_size = np.round(batch_size_covers_max_percent_of_dataset * dataset_num_voxels / np.prod(input_patch_size)).astype(int) batch_size = min(batch_size, max_batch_size) plan = { 'batch_size': batch_size, 'num_pool_per_axis': net_numpool, 'patch_size': input_patch_size, 'median_patient_size_in_voxels': new_median_shape, 'current_spacing': current_spacing, 'original_spacing': original_spacing, 'pool_op_kernel_sizes': net_pool_kernel_sizes, 'conv_kernel_sizes': net_conv_kernel_sizes, 'do_dummy_2D_data_aug': False } return plan use_nonzero_mask_for_normalization = self.use_norm_mask() print("Are you using the nonzero maks for normalizaion?", use_nonzero_mask_for_normalization) spacings = self.dataset_properties['all_spacings'] sizes = self.dataset_properties['all_sizes'] all_classes = self.dataset_properties['all_classes'] modalities = self.dataset_properties['modalities'] num_modalities = len(list(modalities.keys())) target_spacing = self.get_target_spacing() new_shapes = np.array([np.array(i) / target_spacing * np.array(j) for i, j in zip(spacings, sizes)]) max_spacing_axis = np.argmax(target_spacing) remaining_axes = [i for i in list(range(3)) if i != max_spacing_axis] self.transpose_forward = [max_spacing_axis] + remaining_axes self.transpose_backward = [np.argwhere(np.array(self.transpose_forward) == i)[0][0] for i in range(3)] new_shapes = new_shapes[:, self.transpose_forward] # Calculations are based on the median shape of the datasets median_shape = np.median(np.vstack(new_shapes), 0) print("the median shape of the dataset is ", median_shape) max_shape = np.max(np.vstack(new_shapes), 0) print("the max shape in the dataset is ", max_shape) min_shape = np.min(np.vstack(new_shapes), 0) print("the min shape in the dataset is ", min_shape) print("Don't want feature maps smaller than ", FEATUREMAP_MIN_EDGE_LENGTH_BOTTLENECK, " in the bottleneck") # how many stages will the image pyramid have? self.plans_per_stage = [] self.plans_per_stage.append(get_stage_properties(target_spacing, target_spacing, median_shape, num_cases=len(self.list_of_cropped_npz_files), transpose_forward=self.transpose_forward, num_modalities=num_modalities, num_classes=len(all_classes) + 1)) print(self.plans_per_stage) self.plans_per_stage = self.plans_per_stage[::-1] self.plans_per_stage = {i: self.plans_per_stage[i] for i in range(len(self.plans_per_stage))} # convert to dict normalization_schemes = self.do_normalization_scheme() store_largest_connected_component, min_size_per_class, min_region_size_per_class = \ self.do_postprocessing() # these are independent of the stage plans = {'num_stages': len(list(self.plans_per_stage.keys())), 'num_modalities': num_modalities, 'modalities': modalities, 'normalization_schemes': normalization_schemes, 'dataset_properties': self.dataset_properties, 'list_of_npz_files': self.list_of_cropped_npz_files, 'original_spacings': spacings, 'original_sizes': sizes, 'preprocessing_data_folder': self.preprocessing_out_folder, 'num_classes': len(all_classes), 'all_classes': all_classes, 'base_num_features': Generic_UNet.BASE_NUM_FEATURES_3D, 'use_mask_for_norm': use_nonzero_mask_for_normalization, 'keep_only_largest_region': store_largest_connected_component, 'min_region_size_per_class': min_region_size_per_class, 'min_size_per_class': min_size_per_class, 'transpose_forward': self.transpose_forward, 'transpose_backward': self.transpose_backward, 'data_identifier': self.data_identifier, 'plans_per_stage': self.plans_per_stage} self.plans = plans self.save_plans() def do_preprocessing(self, num_threads): if os.path.isdir(join(self.preprocessing_out_folder, "gt_segmentations")): shutil.rmtree(join(self.preprocessing_out_folder, "gt_segmentations")) shutil.copytree(join(self.folder_of_cropped_data, "gt_segmentations"), join(self.preprocessing_out_folder, "gt_segmentations")) normalization_schemes = self.plans['normalization_schemes'] use_nonzero_mask_for_normalization = self.plans['use_mask_for_norm'] intensityproperties = self.plans['dataset_properties']['intensityproperties'] preprocessor = Preprocessor2D(normalization_schemes, use_nonzero_mask_for_normalization, intensityproperties, self.transpose_forward[0]) target_spacings = [i["current_spacing"] for i in self.plans_per_stage.values()] preprocessor.run(target_spacings, self.folder_of_cropped_data, self.preprocessing_out_folder, self.plans['data_identifier'], num_threads) if __name__ == "__main__": t = "Task_BoneSeg" print("\n\n\n", t) cropped_out_dir = os.path.join(cropped_output_dir, t) preprocessing_out_dir = os.path.join(preprocessing_output_dir, t) splitted_4D_out_dir_task = os.path.join(splitted_4D_out_dir, t) lists, modalities = get_lists_of_splitted_dataset(splitted_4D_out_dir_task) # need to be careful with RAM usage if t in ["Task_LITS", "Task_Liver", "Task_BoneSegOrigs", "Task_BoneSeg"]: threads = 3 elif t in ["Task_LungIntern", "Task_FibroticLungSeg", "Task_Lung", "Task_HepaticVessel"]: threads = 6 else: threads = 8 print("number of threads: ", threads, "\n") print("\n\n\n", t) exp_planner = Planner2D(cropped_out_dir, preprocessing_out_dir, threads) exp_planner.plan_exps() exp_planner.do_preprocessing()

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#CREATED AND MAINTAINED BY: SAMBIT KUMAR MISHRA #Email-ID: sambitmishra1968@gmail.com import math import cmath import matplotlib.pyplot as plt import matplotlib.image as img #=========================================================================================================================================================== # Defining lists to use through this program Eo = [] Q = [] dp = [] #[permittivity1,permeability1,permittivity2,permeability2] n = [0,0] B = [0,0] ba = [0,0] #[perpendicular,parallel] arr_phase = [0,0] #[transmission,reflection] arr_magnitude = [0,0] #[transmission,reflection] critical_angle = 0 #=========================================================================================================================================================== #Printing on the screen- Assumptions and sign conventions to be used. print("ASSUMPTIONS-NOTE THESE BEFORE PROCEEDING") print("_________________________________________________________________________________________________________________________________________________") print("") print("Assume that the complex Electric field is given by the equation: E = ((a+jb)x^ + (c+jd)y^ + (m+jn)z^)e*exp(-j*B*(xcos(Qx)+ycos(Qy)+zcos(Qz)))") print("Where ^ means cap, eg. x^ means unit vector in direction of x") print("j = complex imaginary number analogous to i in maths") print("e = natural log base") print("a,c,m are coefficients of real part whereas b,d,n are coefficients of imaginary part of Eo") print("Qx,Qy,Qz represent the angle made by the incident electric field wrt x,y,z axes respectively") print("Qi is the incident angle of wave wrt to the normal to the plane of incidence") print("_________________________________________________________________________________________________________________________________________________") print("") #=========================================================================================================================================================== # TAKING THE INPUTS FROM THE USER try: Eo = list(map(float, input("Enter the values of a,b,c,d,m,n in this exact order separated by space= ").split())) # w = float(input("Enter the frequency of the EM Wave in Hz= "))#We dont have to use because in B value it will get cancelled Nr and Dr Q = list(map(float, input("Enter the values of Qx,Qy,Qz,Qi in this exact order separated by spaces= ").split())) # Enter 0 if degrees and 1 if radians unit = int(input("Enter the unit of angle chosen:- TYPE '0' for degrees, TYPE '1' for radians ")) if unit == 0: Q[0] = math.radians(Q[0]) Q[1] = math.radians(Q[1]) Q[2] = math.radians(Q[2]) Q[3] = math.radians(Q[3]) # If the input type is chosen as radians then leave the value as it is. #This loop will exit only if the user enters proper values of dielectric properties while 1: dp = list(map(float, input( "Enter the values of permittivity_medium1, permeability_medium1, permittivity_medium2, permeability_medium2 in " "this same order separated by space= ").split())) if dp[3]*dp[2] == dp[1]*dp[0]: print("ERROR: Enter the values as per assumptions") else: break print("") print("For the following two categories:- TYPE '1' for XY, TYPE '2' for YZ, TYPE '3' for XZ") print("") poi = int(input("Enter the plane of interface= ")) pod = int(input("Enter the plane of dielectric= ")) #=========================================================================================================================================================== #CALCULATION OF POLARISATION OF WAVE polarisation = 0 #Declaration of polarisation variable for using in program. if poi == 1: if math.cos(Q[2]) == 0: polarisation = 1 # Perpendicular polarisation elif math.sin(Q[2]) == 0: polarisation = 0 # Parallel polarisation elif poi == 2: if math.cos(Q[0]) == 0: polarisation = 1 # Perpendicular polarisation elif math.sin(Q[0]) == 0: polarisation = 0 # Parallel polarisation elif poi == 3: if math.cos(Q[1]) == 0: polarisation = 1 # Perpendicular polarisation elif math.sin(Q[1]) == 0: polarisation = 0 # Parallel polarisation #=============================================================================================================================================================== #Calculation of the magnitude of Incident Electric Field: Absolute value of Eo Ei=0 #Declaration of Ei variable for i in range(0, 6): Ei += Eo[i]**2 # We have to take square root of this value(Ei) to obtain Magnitude of incident electric field. #=============================================================================================================================================================== #CALCULATION OF BREWSTER'S ANGLE #The square root value might come out to be negative hence complex square root must be taken into account so this step can be postponed # reading png image file im = img.imread('EMWAVE_2.png') # show image plt.imshow(im) #For Perpendicular Polarisation if ((dp[3]/dp[1])*(((dp[3]*dp[0])-(dp[1]*dp[2]))/((dp[3]*dp[2])-(dp[1]*dp[0])))) >= 0: ba[0] = math.atan(math.sqrt((dp[3]/dp[1])*(((dp[3]*dp[0])-(dp[1]*dp[2]))/((dp[3]*dp[2])-(dp[1]*dp[0]))))) else: print("BREWSTER ANGLE IS NOT POSSIBLE FOR THIS CASE") #For Parallel Polarisation if ((dp[2]/dp[0])*(((dp[1]*dp[2])-(dp[3]*dp[0]))/((dp[3]*dp[2])-(dp[1]*dp[0])))) >= 0: ba[1] = math.atan(math.sqrt((dp[2]/dp[0])*(((dp[1]*dp[2])-(dp[3]*dp[0]))/((dp[3]*dp[2])-(dp[1]*dp[0]))))) else: print("BREWSTER ANGLE IS NOT POSSIBLE FOR THIS CASE") #===================================================================================================================================================================== #The case when incident wave just grazes through the plane of dielectric interface #In this case no reflection or transmission of wave is possible. This is an exceptional case. if math.cos(Q[3]) == 0: print("NO TRANSMISSION OR REFLECTION POSSIBLE IN THIS CASE: BECAUSE THE WAVE GRAZES THROUGH THE PLANE OF INTERFACE") #ACTUAL CALCULATION BEGINS HERE else: n[0] = (120*math.pi)/(math.sqrt((dp[1])/(dp[0]))) #For medium 1 n[1] = (120*math.pi)/(math.sqrt((dp[3])/(dp[2]))) #For medium 2 B[0] = math.sqrt(dp[1]*dp[0]) #For medium 1 B[1] = math.sqrt(dp[3]*dp[2]) #For medium 2 b1 = n[1] * math.cos(Q[3]) b2 = n[0] * math.cos(Q[3]) #================================================================================================================================================================== #CASE-1: When the incident wave is at an angle greater than the critical Angle and medium 2 is rarer than medium 1 if ((B[0] / B[1]) * math.sin(Q[3])) >= 1 and (dp[3]*dp[2])<=(dp[1]*dp[0]): #================================================================================================================================================================== print("THIS IS THE CASE OF TOTAL INTERNAL REFLECTION") print("") critical_angle = math.asin(B[1]/B[0]) # reading png image file im = img.imread('EMWAVE_TIR.png') # show image plt.imshow(im) if (B[0] / B[1])*math.sin(Q[3]) > 1: if polarisation == 1: reflection_coefficient = (b1 - 1j*(n[0]*math.sqrt((((B[0]/B[1])*math.sin(Q[3]))**2)-1))) / (b1 + 1j*(n[0]*math.sqrt((((B[0]/B[1])*math.sin(Q[3]))**2)-1))) arr_phase[1] = (-2)*math.atan((n[0]*math.sqrt((((B[0]/B[1])*math.sin(Q[3]))**2)-1)) / b1) elif polarisation == 0: reflection_coefficient = (b2 - 1j*(n[1]*math.sqrt((((B[0]/B[1])*math.sin(Q[3]))**2)-1))) / (b2 + 1j*(n[1]*math.sqrt((((B[0]/B[1])*math.sin(Q[3]))**2)-1))) arr_phase[1] = (-2)*math.atan((n[1]*math.sqrt((((B[0]/B[1])*math.sin(Q[3]))**2)-1)) / b2) #Calculation of magnitude arr_magnitude[0] = "N/A" arr_phase[0] = "N/A" arr_magnitude[1] = reflection_coefficient * math.sqrt(Ei) elif (B[0] / B[1]) * math.sin(Q[3]) == 1: try: if Q[3] == critical_angle: if polarisation == 1: reflection_coefficient = (b1 - 1j*(n[0]*math.sqrt((((B[0]/B[1])*math.sin(Q[3]))**2)-1))) / (b1 + 1j*(n[0]*math.sqrt((((B[0]/B[1])*math.sin(Q[3]))**2)-1))) arr_phase[1] = (-2)*math.atan((n[0]*math.sqrt((((B[0]/B[1])*math.sin(Q[3]))**2)-1)) / b1) elif polarisation == 0: reflection_coefficient = (b2 - 1j*(n[1]*math.sqrt((((B[0]/B[1])*math.sin(Q[3]))**2)-1))) / (b2 + 1j*(n[1]*math.sqrt((((B[0]/B[1])*math.sin(Q[3]))**2)-1))) arr_phase[1] = (-2)*math.atan((n[1]*math.sqrt((((B[0]/B[1])*math.sin(Q[3]))**2)-1)) / b2) #Calculation of magnitude arr_magnitude[0] = "N/A" arr_phase[0] = "N/A" arr_magnitude[1] = reflection_coefficient * math.sqrt(Ei) else: print("ERROR: DISCREPANCY IN ANALYTICAL AND INPUT VALUES") except: print("ERROR!") else: print("ERROR: Please re-enter practical values in input") #================================================================================================================================================================== #CASE-2: When the wave is incident at Brewster's Angle elif Q[3]==ba[0] or Q[3]==ba[1]: #================================================================================================================================================================== #No reflection will take place in this case arr_magnitude[1] = "N/A" arr_phase[1] = "N/A" # reading png image file im = img.imread('EMWAVE_BA.png') # show image plt.imshow(im) a1 = n[0] * math.cos(transmitted_angle) a2 = n[1] * math.cos(transmitted_angle) #Case of perpendicular polarisation #-------------------------------------------------------- if polarisation == 1: transmission_coefficient = (2 * b1) / (b1 + a1) if transmission_coefficient >= 0: arr_phase[0] = (2) * math.atan((n[1] * math.sqrt(1 - math.pow((B[0] / B[1]) * math.cos(Q[3]), 2))) / (n[0] * math.sin(Q[3]))) else: arr_phase[0] = (-2) * math.atan((n[1] * math.sqrt(1 - math.pow((B[0] / B[1]) * math.cos(Q[3]), 2))) / (n[0] * math.sin(Q[3]))) # A phase change of Pi #Calculation of magnitude arr_magnitude[0] = transmission_coefficient * math.sqrt(Ei) #Case of parallel polarisation #-------------------------------------------------------- elif polarisation == 0: transmission_coefficient = (2 * b1) / (b2 + a2) if transmission_coefficient >= 0: arr_phase[0] = (2) * math.atan((n[1] * math.sqrt(1 - math.pow((B[0] / B[1]) * math.cos(Q[3]), 2))) / (n[0] * math.sin(Q[3]))) else: arr_phase[0] = (-2) * math.atan((n[1] * math.sqrt(1 - math.pow((B[0] / B[1]) * math.cos(Q[3]), 2))) / (n[0] * math.sin(Q[3]))) # A phase change of Pi #Calculation of magnitude arr_magnitude[0] = transmission_coefficient * math.sqrt(Ei) #================================================================================================================================================================== #CASE-3: The general case of reflection and transmission #if ((B[0] / B[1]) * math.sin(Q[3])) < 1: else: #================================================================================================================================================================== transmitted_angle = math.asin(B[0]/B[1]) * math.sin(Q[3]) a1 = n[0] * math.cos(transmitted_angle) a2 = n[1] * math.cos(transmitted_angle) # reading png image file im = img.imread('EMWAVE_2.png') # show image plt.imshow(im) # For the case of perpendicular polarisation if polarisation == 1: #---------------------------------------------- reflection_coefficient = (b1 - a1) / (b1 + a1) transmission_coefficient = (2 * b1) / (b1 + a1) if reflection_coefficient >= 0: #Calculation of phase of wave after reflection or transmission is a bit tricky: Need to look into that arr_phase[1] = (2) * math.atan((n[1] * math.sqrt(1 - math.pow((B[0] / B[1]) * math.sin(Q[3]), 2))) / (n[0] * math.cos(Q[3]))) else: arr_phase[1] = (-2) * math.atan((n[1] * math.sqrt(1 - math.pow((B[0] / B[1]) * math.sin(Q[3]), 2))) / (n[0] * math.cos(Q[3]))) # A phase change of Pi if transmission_coefficient >= 0: arr_phase[0] = (2) * math.atan((n[1] * math.sqrt(1 - math.pow((B[0] / B[1]) * math.cos(Q[3]), 2))) / (n[0] * math.sin(Q[3]))) else: arr_phase[0] = (-2) * math.atan((n[1] * math.sqrt(1 - math.pow((B[0] / B[1]) * math.cos(Q[3]), 2))) / (n[0] * math.sin(Q[3]))) # A phase change of Pi #Calculation of magnitude arr_magnitude[0] = transmission_coefficient * math.sqrt(Ei) arr_magnitude[1] = reflection_coefficient * math.sqrt(Ei) #---------------------------------------------------------------------------------------------------------------------------------- # For the case of parallel polarisation elif polarisation == 0: #------------------------------------------- reflection_coefficient = (b2 - a2) / (b2 + a2) transmission_coefficient = (2 * b1) / (b2 + a2) if reflection_coefficient >= 0: arr_phase[1] = (2) * math.atan((n[1] * math.sqrt(1 - math.pow((B[0] / B[1]) * math.sin(Q[3]), 2))) / (n[0] * math.cos(Q[3]))) else: arr_phase[1] = (-2) * math.atan((n[1] * math.sqrt(1 - math.pow((B[0] / B[1]) * math.sin(Q[3]), 2))) / (n[0] * math.cos(Q[3]))) # A phase change of Pi if transmission_coefficient >= 0: arr_phase[0] = (2) * math.atan((n[1] * math.sqrt(1 - math.pow((B[0] / B[1]) * math.cos(Q[3]), 2))) / (n[0] * math.sin(Q[3]))) else: arr_phase[0] = (-2) * math.atan((n[1] * math.sqrt(1 - math.pow((B[0] / B[1]) * math.cos(Q[3]), 2))) / (n[0] * math.sin(Q[3]))) # A phase change of Pi #Calculation of magnitude arr_magnitude[0] = transmission_coefficient * math.sqrt(Ei) arr_magnitude[1] = reflection_coefficient * math.sqrt(Ei) #====================================================================================================================================================================== # The final required values using the input values are printed below print("__________________________________________________________________________") print("The phase of transmitted wave is " + str(arr_phase[0])) print("The phase of reflected wave is " + str(arr_phase[1])) print("The magnitude of transmitted wave is " + str(arr_phase[0])) print("The magnitude of reflected wave is " + str(arr_phase[1])) print("") print("These were your final results. THANK YOU") print("__________________________________________________________________________") #====================================================================================================================================================================== except: # reading png image file im = img.imread('SORRY.png') # show image plt.imshow(im) print("__________________________________________") print("PLEASE RECHECK THE VALUES YOU HAVE ENTERED") print("__________________________________________") #THE END #FOR QUERIES/REMARKS CONTACT: SAMBIT KUMAR MISHRA (sambitmishra1968@gmail.com)

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import numpy as np from dataclasses import dataclass from typing import * from scipy.constants import Planck, speed_of_light, elementary_charge from scipy.integrate import odeint, solve_ivp import matplotlib.pyplot as plt from kinetics import Scaler, Parameters, run from style import set_style @dataclass class TAParams: pump_spectrum : np.ndarray probe_spectrum : np.ndarray time : np.ndarray tau_list : np.ndarray probe_time_env : Callable[[Scaler], Callable[[Scaler], Scaler]] pump_time_env: Callable[[Scaler], Callable[[Scaler], Scaler]] make_params : Any probe_scale = 0.1 @dataclass class TAResults: spectra : np.ndarray def run_TA(TA_params : TAParams) -> TAResults: params = TA_params.make_params( lambda t: TA_params.probe_time_env( np.min(TA_params.tau_list))(t) * TA_params.probe_spectrum * 0.1) pump_spectrum = TA_params.pump_spectrum probe_spectrum = TA_params.probe_spectrum result_A_0 = run(params, TA_params.time) A_0 = np.sum(result_A_0.spectral_fluxes, axis=0) spectra = [] pump = TA_params.pump_time_env(np.min(TA_params.tau_list)) for tau in TA_params.tau_list: print(f"{(tau / np.max(TA_params.tau_list)) * 100.0}%") probe = TA_params.pump_time_env(tau) exc_total = lambda t: pump(t) * pump_spectrum + probe(t) * probe_spectrum * 0.1 params = TA_params.make_params(exc_total) results = run(params, TA_params.time) spectra.append(np.sum(results.spectral_fluxes, axis=0) - A_0 * 0) spectra = np.array(spectra) return TAResults(spectra)

[ "rygr1645@colorado.edu" ]

rygr1645@colorado.edu

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16cb142fb04798313c43a073cf1e0ddd6f4bf13b

/timing/resources/time.py

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[]

no_license

iRhonin/timing

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refs/heads/master

2023-04-30T21:02:26.861632

2021-05-14T20:16:12

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from datetime import datetime import falcon from sqlalchemy import func from timing.authorization import Authorization from timing.models.time import Time, DATETIME_FORMAT from timing.paginate import Paginate from timing.schemas.time import TimeInSchema class TimesResource(object): @falcon.before(Authorization()) def on_post(self, req, resp): data = TimeInSchema( user_id=req.context['user_id'], createdAt=req.params.get('t', None), hours=req.media['hours'], ) time = Time(**data.dict(exclude_unset=True)) req.context.db_session.add(time) req.context.db_session.commit() resp.media = time.to_dict() @falcon.before(Authorization()) @falcon.before(Paginate()) def on_get(self, req, resp): time_query = self._get_times(req, query_on=Time) total_count = time_query.count() time_query = time_query \ .order_by(Time.created_at) \ .limit(req.context['limit']) \ .offset(req.context['offset']) \ resp.media = [t.to_dict() for t in time_query] resp.set_header('X-COUNT', total_count) @falcon.before(Authorization()) def on_get_calculator(self, req, resp): sum_times = self._get_times(req, query_on=func.sum(Time.hours)).one() sum_times = int(sum_times[0] or 0) resp.media = Time( created_at=datetime.utcnow(), hours=sum_times, ).to_dict() def _get_times(self, req, query_on): time_query = req.context.db_session.query(query_on) \ .filter(Time.user_id == req.context.user_id) if from_ := req.params.get('from'): time_query = time_query.filter( Time.created_at >= datetime.strptime(from_, DATETIME_FORMAT) ) if to_ := req.params.get('to'): time_query = time_query.filter( Time.created_at <= datetime.strptime(to_, DATETIME_FORMAT) ) return time_query

[ "fatahzade@gmail.com" ]

fatahzade@gmail.com

c19012af2e5fe52651cc00b9775abc1d3e4e6ea1

a71d5838e292e2c0c7371f7fc7870c7018820ae1

/day03/03_pie.py

71c8ec39a03c52234f30d2660394d2f3d37a995f

[]

no_license

skywalkerqwer/DataScience

be91541c3da383d15ee52d0101d2dbb0289c2fde

4cfd42f3a9795e295393cdb045852d46e99b6e59

refs/heads/master

2020-06-17T11:41:40.113864

2019-07-15T09:49:40

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""" 绘制饼状图 """ import numpy as np import matplotlib.pyplot as mp labels = ['Python', 'JavaScript', 'C++', 'Java', 'PHP'] values = [26, 17, 21, 29, 11] spaces = [0.05, 0.01, 0.01, 0.01, 0.01] colors = ['dodgerblue', 'orangered', 'limegreen', 'violet', 'gold'] mp.figure('Pie Chart', facecolor='lightgray') mp.title('Languages PR') mp.pie(values, spaces, labels, colors, '%.1f%%', shadow=True, startangle=0, radius=1) mp.legend() mp.show()

[ "15902162780@163.com" ]

15902162780@163.com

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/python/20/ccc20j4.py

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permissive

sadmanca/ccc-solutions

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2023-03-05T17:19:18.776037

2021-02-17T00:40:30

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# COMPLETE t = input() s = input() l = len(s) shifts = set() shifts.add(s) for i in range(l-1): s = s[1:]+s[0] shifts.add(s) cyc = False for string in shifts: for i in range(0, len(t)-l+1): if string == t[i:i+l]: cyc = True if cyc == True: print("yes") else: print("no")

[ "41028402+Sadman-Hossain@users.noreply.github.com" ]

41028402+Sadman-Hossain@users.noreply.github.com

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/quote/forms.py

1d803b8df3d24b45e9b8c59cb8586deddbaa426e

[]

no_license

mahdistt/CRM

48550b1bb8adbd012b254e42edefc69a572a33fc

a1aa33df4ef2e342268f8965d43bf026be61db37

refs/heads/master

2023-07-09T05:11:23.497844

2021-08-11T18:45:56

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from django import forms from . import models class QuoteCreateViewForm(forms.ModelForm): class Meta: model = models.QuoteItem fields = ( 'quote', 'product', 'price', 'quantity', 'discount', ) widgets = { 'quantity': forms.NumberInput, 'discount': forms.NumberInput, 'price': forms.NumberInput, 'quote': forms.Select, }

[ "80247767+mahdistt@users.noreply.github.com" ]

80247767+mahdistt@users.noreply.github.com

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/src/tests/integration/test_cli.py

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[ "BSD-2-Clause" ]

permissive

alexseitsinger/package-controller

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refs/heads/master

2022-12-11T18:00:17.922442

2019-08-21T02:24:35

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BSD-2-Clause

2022-12-08T05:50:25

2019-05-08T02:10:23

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py

import pytest from click.testing import CliRunner from package_controller.cli import main def test_add(): pass def test_build(): pass def test_commit(): pass def test_release(): pass def test_version(): pass

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16756928+alexseitsinger@users.noreply.github.com

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/decode.py

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[]

no_license

omri123/text_lord

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refs/heads/master

2022-04-09T11:39:20.561554

2020-03-12T22:05:04

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import torchtext from restorant_dataset import START, END from model import NoEncoderFConvDecoderModel from archive.utils import load_checkpoint, vocab_to_dictionary from restorant_dataset import get_dataset import os import pickle import copy def gready_decode_single(model: NoEncoderFConvDecoderModel, vocab: torchtext.vocab, stars: int, sample_id: int, start_token=START, end_token=END, device='cpu'): max_length = 25 src_tokens = torch.tensor([[sample_id, stars]], dtype=torch.int64, device=device) src_lengths = torch.full((1, 1), 5, device=device) reviews = torch.tensor([[vocab.stoi[start_token]]], dtype=torch.int64, device=device) sentence = [start_token] length = 0 while end_token not in sentence: logits, _ = model(src_tokens, src_lengths, reviews) logits_for_new_token = logits[0, -1, :] # batch, seq, vocab word_index = torch.argmax(logits_for_new_token).item() sentence.append(vocab.itos[word_index]) length += 1 if length > max_length: break sentence_by_indecies = [vocab.stoi[word] for word in sentence] reviews = torch.tensor([sentence_by_indecies], dtype=torch.int64, device=device) return ' '.join(sentence) def gready_decode(model, vocab, src_tokens, src_lengths, start_token, end_token): pass import torch from queue import PriorityQueue device = torch.device("cuda" if torch.cuda.is_available() else "cpu") class BeamSearchNode(object): def __init__(self, sentence, logProb, length): ''' :param sentence: a list of tokens!!! :param logProb: logp sum :param length: ''' self.sent = sentence self.logp = logProb self.leng = length def eval(self, alpha=1.0): reward = 0 # Add here a function for shaping a reward return - (self.logp / float(self.leng - 1 + 1e-6) + alpha * reward) def __lt__(self, other): return self.eval() <= other.eval() def beam_decode_single(model, vocab, sample_id, stars, beam_width=10, topk=1, device='cpu', SOS_token='<s>', EOS_token='</s>', MAX_LENGTH=50): """ decode single example using beam search. :param decoder: a NoEncoderFConvDecoderModel object :param vocab: :param sample_id: :param stars: :param beam_width: :param SOS_token: :param EOS_token: :param MAX_LENGTH: :return: """ src_tokens = torch.tensor([[sample_id, stars]], dtype=torch.int64, device=device) src_lengths = torch.full((1, 1), 5, device=device) review = [SOS_token] # review = torch.tensor([[vocab.stoi[SOS_token]]], dtype=torch.int64) solutions = [] nodes = PriorityQueue() node = BeamSearchNode(review, 0, 1) nodes.put(node) qsize = 1 while True: # finished if len(solutions) == topk: break # give up when decoding takes too long if qsize > 2000: for i in range(topk - len(solutions)): solutions.append(nodes.get()) break # fetch the best node node = nodes.get() review = node.sent review_int = [vocab.stoi[w] for w in review] review_torch = torch.tensor([review_int], dtype=torch.int64, device=device) if review[-1] == EOS_token: solutions.append(node) continue logits, _ = model(src_tokens, src_lengths, review_torch) predictions = torch.log_softmax(logits, dim=2) log_probs, indexes = torch.topk(predictions, beam_width) for new_k in range(beam_width): word_index = indexes[0, len(review)-1, new_k].item() word = vocab.itos[word_index] review_new = copy.deepcopy(node.sent) review_new.append(word) new_word_log_p = log_probs[0, 0, new_k].item() new_node = BeamSearchNode(review_new, node.logp + new_word_log_p, node.leng) nodes.put(new_node) qsize += 1 return [' '.join(s.sent) for s in solutions] def main(): foldername = '/cs/labs/dshahaf/omribloch/data/text_lord/restorant/train/note_tiny_no_noise_dim_32_ntokens_5_nconv_10_nsamples_102400_content_noise_0.001/' # foldername = '/cs/labs/dshahaf/omribloch/data/text_lord/restorant/train/note_EM_no_noise_dim_32_ntokens_10_nconv_4_nsamples_1024_content_noise_0.0/' vocab_path = os.path.join(foldername, 'vocab.pickle') model_ckpt_path = os.path.join(foldername, 'last_checkpoint.ckpt') with open(vocab_path, 'rb') as file: vocab = pickle.load(file) print('vocab was loaded') decoder_dictionary = vocab_to_dictionary(vocab) device = 'cpu' nsamples = 102400 ntokens = 5 dim = 32 content_noise = 0.001 dropout = 0 nconv = 10 model = load_checkpoint(model_ckpt_path, 'cpu', device, nsamples, decoder_dictionary.pad(), ntokens, dim, content_noise, dropout, decoder_dictionary, 50, nconv) print('model loaded') model.eval() dataset, vocab = get_dataset(10000, '/cs/labs/dshahaf/omribloch/data/text_lord/restorant/', vocab) for i in range(10): sid = dataset[i].id stars = dataset[i].stars # stars = 1 review_sentence = ' '.join(dataset[i].review) print(review_sentence) decoded_sentence = gready_decode_single(model, vocab, stars, sid) print(decoded_sentence) decoded_sentence = gready_decode_single(model, vocab, 1-stars, sid) print(decoded_sentence) print('-------------') decoded_sentence = beam_decode_single(model, vocab, sid, stars, topk=10, beam_width=4) for d in decoded_sentence: print(d) print('==============================') if __name__=='__main__': main()

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/task1/solution.py

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skeleta/python-retrospective

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refs/heads/master

2021-01-18T03:14:27.664850

2013-04-28T20:18:35

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SIGNS = ("Козирог", "Водолей", "Риби", "Овен", "Телец", "Близнаци", "Рак", "Лъв", "Дева", "Везни", "Скорпион", "Стрелец") RANGES = {1: 19, 2: 18, 3: 20, 4: 20, 5: 20, 6: 20, 7: 21, 8: 22, 9: 22, 10: 22, 11: 21, 12: 21} def what_is_my_sign(day, month): return SIGNS[month - 12 - (day <= RANGES[month])]

[ "ivankapukaranov@gmail.com" ]

ivankapukaranov@gmail.com

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/day 03/作业.py

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no_license

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2023-01-12T07:20:57.911545

2020-10-25T09:40:04

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# # 1.有变量name = "aleX leNb" 完成如下操作： # name = "aleX leNb" # # - 移除 name 变量对应的值两边的空格,并输出处理结果 # print(name.strip()) # # - 判断 name 变量是否以 "al" 开头,并输出结果 # print(name.startswith('al')) # # - 判断name变量是否以"Nb"结尾,并输出结果 # print(name.endswith('Nb')) # # - 将 name 变量对应的值中的所有的"l" 替换为 "p",并输出结果 # print(name.replace('l','p')) # # - 将name变量对应的值中的第一个"l"替换成"p",并输出结果 # print(name.replace('l','p',1)) # # - 将 name 变量对应的值根据所有的"l" 分割,并输出结果。 # print(name.split('l')) # # - 将name变量对应的值根据第一个"l"分割,并输出结果。 # print(name.split('l',1)) # # - 将 name 变量对应的值变大写,并输出结果 # print(name.upper()) # # - 将 name 变量对应的值变小写,并输出结果 # print(name.lower()) # # - 判断name变量对应的值字母"l"出现几次，并输出结果 # print(name.count('l')) # # - 如果判断name变量对应的值前四位"l"出现几次,并输出结果 # print(name.count('l',0,4)) # # - 请输出 name 变量对应的值的第 2 个字符? # print(name[1]) # # - 请输出 name 变量对应的值的前 3 个字符? # print(name[0:3]) # # - 请输出 name 变量对应的值的后 2 个字符? # print(name[-2:]) # # # 2.有字符串s = "123a4b5c" # s = "123a4b5c" # # - 通过对s切片形成新的字符串s1,s1 = "123" # print(s[0:3]) # # - 通过对s切片形成新的字符串s2,s2 = "a4b" # print(s[3:6]) # # - 通过对s切片形成新的字符串s3,s3 = "1345" # print(s[0:7:2]) # # - 通过对s切片形成字符串s4,s4 = "2ab" # print(s[1:6:2]) # # - 通过对s切片形成字符串s5,s5 = "c" # print(s[-1:]) # # - 通过对s切片形成字符串s6,s6 = "ba2" # print(s[-3:-8:-2]) # # # 3.使用while和for循环分别打印字符串s="asdfer"中每个元素。 # s="asdfer" # while: # i = 0 # while i < len(s): # print(s[i]) # i+=1 # for # for i in s: # print(i) # # # 4.使用for循环对s="asdfer"进行循环，但是每次打印的内容都是"asdfer"。 # s="asdfer" # for i in s: # print(s) # # # 5.使用for循环对s="abcdefg"进行循环，每次打印的内容是每个字符加上sb，例如：asb, bsb，csb,...gsb。 # s="abcdefg" # for i in s: # print(i.join('sb')) # # for i in s: # print(i + 'sb') # # # 6.使用for循环对s="321"进行循环，打印的内容依次是："倒计时3秒"，"倒计时2秒"，"倒计时1秒"，"出发！"。 # s="321" # for i in s: # print('倒计时'+ i +'秒！') # print('出发！') # # # 7.实现一个整数加法计算器(两个数相加)：如：content = input("请输入内容:") 用户输入：5+9或5+ 9或5 + 9，然后进行分割再进行计算。 # content = input("请输入内容:") # content_space = content.replace(' ','') # print(content_space) # list = content_space.split('+') # print(list) # sum = 0 # for i in list: # sum = sum + int(i) # print(sum) # # # 8.实现一个整数加法计算器（多个数相加）：如：content = input("请输入内容:") 用户输入：5+9+6 +12+ 13，然后进行分割再进行计算。 # content = input("请输入内容:") # content_space = content.replace(' ','') # print(content_space) # list = content_space.split('+') # sum = 0 # for i in list: # sum = sum + int(i) # print(sum) # # 9.计算用户输入的内容中有几个整数（以个位数为单位）。如：content = input("请输入内容：") # 如fhdal234slfh98769fjdla # str = '1234a' # content = 0 # for i in str: # if i.isdecimal() : # content +=1 # print(content) # # # # # 10.选做题**：写代码，完成下列需求：用户可持续输入（用while循环），用户使用的情况： # # 输入A，则显示走大路回家，然后在让用户进一步选择： # # 是选择公交车，还是步行？ # # 选择公交车，显示10分钟到家，并退出整个程序。 # # 选择步行，显示20分钟到家，并退出整个程序。 # # 输入B，则显示走小路回家，并退出整个程序。 # # 输入C，则显示绕道回家，然后在让用户进一步选择： # # 是选择游戏厅玩会，还是网吧？ # # 选择游戏厅，则显示 ‘一个半小时到家，爸爸在家，拿棍等你。’并让其重新输入A，B,C选项。 # # 选择网吧，则显示‘两个小时到家，妈妈已做好了战斗准备。’并让其重新输入A，B,C选项。 # while 1 : # print('A:走大路，B：走小路,C:绕道') # choice = input('请输入：') # choice_upper = choice.upper() # if choice_upper == 'A': # print('你选择了走大路') # choice1 = input('请选择A:坐公交，B：走路:') # choice_upper1 = choice1.upper() # if choice_upper1 == 'A': # print('坐公交，十分钟后到家') # break # else: # print('走路回家，二十分钟后到家') # break # elif choice_upper == 'B': # print('你选择了走小路') # break # else: # print('你选择了绕道') # choice2 = input('请选择A:区游戏厅，B：去网吧:') # choice_upper2 = choice2.upper() # if choice_upper2 == 'A': # print('一个半小时到家，爸爸在家，拿棍等你。') # else: # print('两个小时到家，妈妈已做好了战斗准备。') # # # 1.写代码：计算1 - 2 + 3 - 4 + 5 - 6... + 99中除了88以外所有数的总和？ # s1 = 0 # s2 = 0 # i = 1 # while i <= 99 : # if i % 2 == 0: # if i == 88: # i += 1 # continue # else: # s1 -= i # else: # s2 += i # i += 1 # print(s1+s2) # # # 2. ** 选做题： ** 选做题：判断一句话是否是回文.回文: 正着念和反着念是一样的.例如, 上海自来水来自海上 # str = input('请输入:') # if str[-1::-1] == str: # print("是") # else: # print('不是') # # # 3.制作趣味模板程序需求：等待用户输入名字、地点、爱好，根据用户的名字和爱好进行任意现实,如：敬爱可亲的xxx，最喜欢在xxx地方干xxx # your_name = input('请输入姓名') # your_place = input('请输入地点') # your_hobby = input('请输入爱好') # msg = '可亲的{name}，最喜欢在{place}地方干{hobby}'.format(name = your_name,place = your_place,hobby = your_hobby) # print(msg)

[ "zhangchenghao0617@qq.com" ]

zhangchenghao0617@qq.com

49bee32f7d8ddec8715ce98a577f088ab50e9d45

a961a54e8d466b1fb98aee86d437ed6872e98d18

/shows/management/commands/get_english_names.py

403bad44964aea456ad293b48eb19dc7b5d768de

[]

no_license

akaram94/animemelody

6bcc75e2746def0f3638b0e6acf6cf5b0e2b6f7c

2adf79f232d06733bbc8af4def3778ea55838efa

refs/heads/master

2023-08-19T00:19:43.688266

2020-07-27T16:24:56

268,275,539

0

null

2021-09-22T19:08:05

2020-05-31T12:29:51

Python

UTF-8

Python

false

1,233

py

from django.core.management.base import BaseCommand, CommandError from shows.models import Show, Theme import datetime import requests import json import time class Command(BaseCommand): help = ''' Used to import english show names from the Jikan API (rate limit of 2s) ''' def handle(self, *args, **options): feed_url = 'https://api.jikan.moe/v3/anime/' message = 'Getting english names...' shows = Show.objects.filter(english_name='') print(message) show_count = 0 # Retrieve all data from each endpoint for show in shows: current_url = feed_url + str(show.mal_id) time.sleep(2) r = requests.get(current_url) data = r.json() if data['title_english']: title_english = str(data['title_english']) else: title_english = None show.english_name = title_english show.save() show_count = show_count + 1 print(show_count) print('----------------------------------------------------------') print('Show Count: ' + str(show_count)) print('Successfully updated.')

[ "root@DESKTOP-FIFE14Q.localdomain" ]

root@DESKTOP-FIFE14Q.localdomain

ef967c7df544cf14fd81acac69d9aa53ed4449d0

9cd4bd2d3c43d14a78c4f72dd2d8c6900aec56c4

/TabuadaPython.py

7f386b00ecc7d585dacc937cfee125710246f99e

[]

no_license

paulorod07/Tabuada

937005686f0a9fb1c5b8a37dc49ae7178477c97f

14ced3e51ec0ce2c9c7c92bdf6696ce24a956a45

refs/heads/master

2020-04-27T16:22:05.703246

2019-03-08T06:41:19

174,481,856

0

null

UTF-8

Python

false

152

py

print('Bem Vindo a Tabuada!') numero = int(input('Digite um numero para a tabuada: ')) for n in range(11): print(numero, 'x', n, '=', numero * n)

[ "noreply@github.com" ]

paulorod07.noreply@github.com

e714abb10599586f922ae28ac3e229eafdfbbc3b

711ca7d1996f3eab0c9f8338fd49c9067274d5e5

/image_augment-master/test_detect_multi_process.py

34ce758c0c9c30786eaa30c6bbdf0b7112d8c2c3

[]

no_license

zj463261929/tools

408ccdbe93ae00d4825b74d6e37cc2bd77208504

47545fbbb6779378ad833a7b84c89cc91848e345

refs/heads/master

2020-03-20T13:01:10.970807

2019-07-22T02:36:12

137,446,532

0

null

UTF-8

Python

false

3,139

py

#coding=utf-8 import codecs import random import cv2, os import sys #sys是Python内建标准库 sys.path.append(os.getcwd()) from function import * import function as FUN import math import numpy as np import time from test_detect_single import img_aug from multiprocessing import Process image_dir = "/opt/zhangjing/Detectron/data/oil_vehicle_person_10cls/VOCdevkit2007/VOC2007/aug/img/" #原始图片路径 xml_dir = "/opt/zhangjing/Detectron/data/oil_vehicle_person_10cls/VOCdevkit2007/VOC2007/aug/xml/" #图片对应xml的路径 image_txt1 = "/opt/zhangjing/Detectron/data/oil_vehicle_person_10cls/VOCdevkit2007/VOC2007/aug/minitruck.txt"#原始图片标签对应的txt image_txt2 = "/opt/zhangjing/Detectron/data/oil_vehicle_person_10cls/VOCdevkit2007/VOC2007/aug/forklift.txt"#原始图片标签对应的txt image_txt3 = "/opt/zhangjing/Detectron/data/oil_vehicle_person_10cls/VOCdevkit2007/VOC2007/aug/digger.txt"#原始图片标签对应的txt '''image_txt4 = "/opt/oil_vehicle_person_10cls/VOCdevkit2007/VOC2007/ImageSets_8558/Main/train_4.txt"#原始图片标签对应的txt image_txt5 = "/opt/oil_vehicle_person_10cls/VOCdevkit2007/VOC2007/ImageSets_8558/Main/train_5.txt"#原始图片标签对应的txt image_txt6 = "/opt/oil_vehicle_person_10cls/VOCdevkit2007/VOC2007/ImageSets_8558/Main/train_6.txt"#原始图片标签对应的txt ''' save_img_dir = "/opt/zhangjing/Detectron/data/oil_vehicle_person_10cls/VOCdevkit2007/VOC2007/aug/img_aug/" save_xml_dir = "/opt/zhangjing/Detectron/data/oil_vehicle_person_10cls/VOCdevkit2007/VOC2007/aug/xml_aug/" #处理后保存的路径，每个增强方法会保存在对应文件夹下 if not os.path.exists(save_xml_dir): os.mkdir(save_xml_dir) if not os.path.exists(save_img_dir): os.mkdir(save_img_dir) if __name__ == "__main__": print time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(time.time())) print 'Parent process %s starts.' % os.getpid() #创建线程 my_process1 = Process(target = img_aug, args=(image_dir,xml_dir,image_txt1,save_img_dir,save_xml_dir) , name= 'ys_process1') my_process2 = Process(target = img_aug, args=(image_dir,xml_dir,image_txt2,save_img_dir,save_xml_dir) , name= 'ys_process2') my_process3 = Process(target = img_aug, args=(image_dir,xml_dir,image_txt3,save_img_dir,save_xml_dir) , name= 'ys_process3') ''' my_process4 = Process(target = img_aug, args=(image_dir,xml_dir,image_txt4,save_img_dir,save_xml_dir) , name= 'ys_process4') my_process5 = Process(target = img_aug, args=(image_dir,xml_dir,image_txt5,save_img_dir,save_xml_dir) , name= 'ys_process5') my_process6 = Process(target = img_aug, args=(image_dir,xml_dir,image_txt6,save_img_dir,save_xml_dir) , name= 'ys_process6') ''' #等待2s time.sleep(2) #启动线程 my_process1.start() my_process2.start() my_process3.start() '''my_process4.start() my_process5.start() my_process6.start()''' #等待线程结束 my_process1.join() my_process2.join() my_process3.join() '''my_process4.join() my_process5.join() my_process6.join()''' print time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(time.time())) print 'process %s ends.' % os.getpid()

[ "zhagnjing1@mail.e-u.cn" ]

zhagnjing1@mail.e-u.cn

424d47cd8ca4fd8aff8087b739e35b6c874f1161

35ce7e974e1651b1031841d84bce190be73be196

/autonomous_car/system/controller/pid_controller.py

7da59857bae3bd7f590eaffa8b93d5e6a45e0ef8

[]

no_license

th-sato/py-graduate-final-project

459b515b1ba4629fb55ca0f028f0bb92ab715167

48d7afb0c0c49ed98a1263c9efdfcf26e99673cd

refs/heads/master

2022-01-25T15:46:28.268045

2019-07-07T03:48:02

null

0

null

UTF-8

Python

false

2,583

py

class PIDController: def __init__(self): # Constantes do controlador # Proporcional self.KP = {'angle': 250.0, 'speed': 5.0} # Integral # self.KI = {'angle': 30.0, 'speed': 1.0} # Derivative # self.KD = {'angle': 1.0, 'speed': 1.0} self.max_error = 100000.0 self.min_error = -100000.0 # self.previous_i_error = {'angle': 0.0, 'speed': 0.0} # self.previous_d_error = {'angle': 0.0, 'speed': 0.0} # self.previous_time = 0.0 def reset(self, now_time): # self.previous_i_error = {'angle': 0, 'speed': 0} # self.previous_d_error = {'angle': 0, 'speed': 0} # self.previous_time = now_time return def proportional(self, error, variable): proporcional_controller = self.KP[variable] * error return self.__set_max(proporcional_controller, self.min_error, self.max_error) # def integral(self, error, time_interval, variable): # actual_error = error * time_interval # integral_part = self.previous_i_error[variable] + actual_error # self.previous_i_error[variable] = integral_part # integral_controller = self.KI[variable] * integral_part # return self.__set_max(integral_controller, self.min_error, self.max_error) # def derivative(self, error, time_interval, variable): # derivative_part = (error - self.previous_d_error[variable]) / time_interval # self.previous_d_error[variable] = error # derivative_controller = self.KD[variable] * derivative_part # return self.__set_max(derivative_controller, self.min_error, self.max_error) def p_controller(self, error, variable, interval=0.01): p = self.proportional(error, variable) # i = self.integral(error, interval, variable) # d = self.derivative(error, interval, variable) return p def output(self, distance_center, radius_curvature, run_time): try: # interval = run_time - self.previous_time # self.previous_time = run_time angle = self.p_controller(distance_center, 'angle') # speed = self.pid_controller(radius_curvature, interval) speed = 45 return speed, angle except Exception as e: print str(e) return 0, 0 @staticmethod def __set_max(value, min_value, max_value): if value > 0 and value > max_value: return max_value if value < 0 and value < min_value: return min_value return value

[ "thiagosato22@hotmail.com" ]

thiagosato22@hotmail.com

f15414bf81d05d0860a3345a7f7b0679f6cbba74

db35cba13f89601467b4bb4553d2b648c18fc3fb

/stores/topshop.py

8e7c906ff53b33b1ba4e7916231b878688d31d1a

[]

no_license

jitsejan/outfitter

e6d73fcc2ec46c5236207c8bb8e1e72fc8929c38

53faab3e30e312bbdbc4ca0154efe35592708a8b

refs/heads/master

2023-01-02T20:15:12.519289

2016-09-15T14:07:00

309,139,169

0

null

UTF-8

Python

false

6,113

py

################################################################################ # Application: Outfitter # File: topshop.py # Goal: topshop.py will retrieve specific information from a # given Topshop link and save the data to a variable # Input: url of website # Output: Target data # Example: info = crawl("http://eu.topman.com/en/tmeu/product/clothing-617800/mens-jumpers-cardigans-617811/charcoal-shawl-cardigan-4656120?bi=0&ps=20") # # History: 2015-09-28 - JJ Creation of the file # 2015-10-29 - JJ Added functionality to retrieve all images # ################################################################################ ################################################################################ # Imports ################################################################################ from product import Product ################################################################################ # Definitions ################################################################################ author = "JJ" appName = "Topshop Crawler" ################################################################################ # Functions ################################################################################ ################################################################################ # Classes ################################################################################ class TopshopProduct(Product): def __init__(self, *args, **kwargs): super(TopshopProduct,self).__init__('Topshop', *args, **kwargs) ################################################################################ # Function: _get_image # Input: tree # Output: URL of the image # Goal: Find the image URL and return it # Targets: Use a css selecter to find the image URL # Example: Find <meta property="og:image" content="http://media.topman.com/wcsstore/TopManEU/images/catalog/81F22KCHR_normal.jpg"/> def _get_images(self): images = [] try: # Use css to select image image_data = self._tree.cssselect('meta[property*=\'og:image\']') # Save the image link from the content field to the variable image images.append(image_data[0].attrib['content']) except: pass # Return the link to the image return images ################################################################################ # Function: _get_price # Input: tree # Output: Price in euro # Goal: Find the price and return it # Targets: Use a css selecter to find the price # Example: Find <span itemprop="offers"><meta itemprop="price" content="E 39,95"> def _get_price(self): price = "" try: # Use css to select the meta-tag with name equal to twitter:data1 price_meta = self._tree.cssselect('meta[property*=\'og:price:amount\']') # Save the price from the content field to the variable price price = price_meta[0].attrib['content'] except: pass # Return the price return price def _get_currency(self): currency = "" try: currency_meta = self._tree.cssselect('meta[property*=\'og:price:currency\']') currency = currency_meta[0].attrib['content'] except: pass # Return the currency return currency ################################################################################ # Function: _get_color # Input: tree # Output: Color # Goal: Find the color and return it # Targets: Use a css selecter to find the color # Example: Find <ul class="product_summary"><li class="product_colour">Colour: <span>GREY</span></li> def _get_color(self): color = "" try: # Use css to select to find the color color_meta = self._tree.cssselect('ul[class*=\'product_summary\'] li[class*=\'product_colour\'] span') # Save the price from the content field to the variable price color = color_meta[0].text_content().strip() except: pass # Return the color return color ################################################################################ # Function: _get_title # Input: tree # Output: Title # Goal: Find the title and return it # Targets: Use a css selecter to find the title # Example: Find <div class="title"><h1>ASOS Jumper<h1> def _get_title(self): title = "" try: # Use css to select the meta-tag with name equal to description title_data = self._tree.cssselect('meta[property*=\'og:description\']') # Retrieve the text from h1 and strip unwanted characters title = title_data[0].attrib['content'] except: pass # Return the title return title ################################################################################ # Function: _get_category # Input: self # Output: Title # Goal: Find the title and return it # Targets: Use a css selecter to find the title # Example: Find last word of description. There is no category explicitly def _get_category(self): category = "" try: # Use css to select the meta-tag with name equal to description category_data = self._tree.cssselect('meta[property*=\'og:description\']') # Retrieve the text and take the last word category = category_data[0].attrib['content'].rsplit(' ')[-1] except: pass # Return the title return category def _get_brand(self): brand = "" return brand ################################################################################ # main ################################################################################ def get_product(url): product = TopshopProduct(url) return product def get_price(url): product = TopshopProduct(url) return product.get_price()

[ "jitsejan@gmail.com" ]

jitsejan@gmail.com

f6cc157fcac65c81a3809080db0f1aac9d4e2f7d

82f40f23ea87d8ed09974a6ce87418cb7934b14b

/Logistic Regression & MultiLayer Perceptron/Code/logistic_kclass.py

83abd0da19f525bde30fef8e517fe84551510fd0

[]

no_license

priyankpshah/DataAnalysis_MachineLearning

22a69bea1426d3291461177a4ddfd67a9f19741b

68c7a27a84b341a2a19d7481410536c23750fa24

refs/heads/master

2021-06-08T14:51:05.167801

2016-12-15T21:37:28

null

0

null

UTF-8

Python

false

4,061

py

from __future__ import division from sklearn.datasets import load_iris, fetch_mldata from sklearn.cross_validation import KFold import numpy as np def indicator(class_fact, class_val): ind = [] for label in class_fact: if label == class_val: ind.append(1) else: ind.append(0) return np.asarray(ind) def Hypo(theta, X, thetas): den = exp_sum(thetas, X) hypo = np.exp(np.dot(X, theta)) hypo /= den return hypo def exp_sum(thetas, X): sum = 0 m, n = np.shape(thetas) for i in range(n): sum += np.exp(np.dot(X, thetas[:, i])) return sum def Find_Theta(X, Y, estimate, iterations): calssval = [0,1,2] x, y = np.shape(X) mul_theta = np.ones((y, len(calssval))) for j in range(iterations): for i, c in enumerate(calssval): theta = mul_theta[:, i] temp_hypo = Hypo(theta, X, mul_theta) ind = indicator(Y, c) theta_i = estimate * (np.sum((temp_hypo - ind).reshape(len(temp_hypo), 1) * X, axis=0)) theta_i = theta_i.reshape(theta.shape) theta = theta - theta_i mul_theta[:, i] = theta return mul_theta def confuide_mat(ytest, ypredict): cm = [] clab = [0,1,2] for i in clab: tmp = [0] * len(clab) for j in range(len(ytest)): if ytest[j] == i and ytest[j] == ypredict[j]: tmp[clab.index(i)] += 1 elif ytest[j] == i and ytest[j] != ypredict[j]: tmp[clab.index(ypredict[j])] += 1 cm.append(tmp) return np.array(cm) def predict(X_Test, thetas): Y_prediction = [] thetas = thetas.T #print thetas for x in X_Test: h = -np.inf for i, theta in enumerate(thetas): h_hat = np.dot(x, theta) #print h_hat if h_hat > h: h = h_hat label = i Y_prediction.append(label) return Y_prediction def confusion_mat(cm): precesion = np.zeros(2) recall = np.zeros(2) f1measure = np.zeros(2) accuracy = 0 tot = np.sum(confusion_mat) for i in range(0,2): for j in range(0,2): precesion[i] += cm[j][i] recall[i] += cm[i][j] if(i==j): accuracy = accuracy + cm[i][j] precesion[i] = cm[i][i]/precesion[i] recall[i] = cm[i][i]/recall[i] f1measure[i] = ((2*precesion[i]*recall[i])/(precesion[i]+recall[i])) accuracy = float(accuracy)/tot return precision,recall,f_measure,accuracy if __name__ == "__main__": mnist = fetch_mldata('MNIST original') X, Y = mnist.data / 255., mnist.target matrix = np.concatenate((X[Y == 0], X[Y == 1], X[Y == 2]), axis=0) y = np.concatenate((Y[Y == 0], Y[Y == 1], Y[Y == 2]), axis=0) kf = KFold(X.shape[0], n_folds=10, shuffle=True) accuracy = 0.0 precision = np.zeros(3) recall = np.zeros(3) f_measure = np.zeros(3) for train,test in kf: X_Train, X_Test = X[train], X[test] Y_Train, Y_Test = Y[train], Y[test] thetas = Find_Theta(X_Train, Y_Train, 0.001, 2500) Y_Prediction = predict(X_Test, thetas) cm = confuide_mat(Y_Test, Y_Prediction) pre, rec, f1, acc = confusion_mat(cm) precision = np.add(precision, pre) recall = np.add(recall, rec) f_measure = np.add(f_measure, f1) accuracy = accuracy + acc precision = map(lambda x: x/10, precision) recall = map(lambda x: x/10, recall) f1measure = map(lambda x: x/10, f_measure) accuracy /= 10 print " Confusion Matrix:"+ str(cm[0]) print "\t\t\t\t "+ str(cm[1]) print " Precesion: Recall: F-1 Measures" print "Class 0: " + str(round(precision[0],3))+" "+str(round(recall[0],3))+" "+str(round(f1measure[0],3)) print "Class 1: " + str(round(precision[1],3))+" "+str(round(recall[1],3))+" "+str(round(f1measure[1],3)) print "\nAccuracy: "+str(round(accuracy,3)*100)+ "%"

[ "priyank687@gmail.com" ]

priyank687@gmail.com

668cd341318eeaefb3cfccd3c9694710dc5d5f46

6dec3256279f73c563b116a8fa44900c4b51a4ce

/scrapy_demo/scrapy_demo/pipelines.py

736cf257e01c3b8c355daf21b7e4d34a1cf2bf32

[]

no_license

gannonk08/scrapy-demo

6802cfbe109ff428f58c5e9957ac109bfed282a0

86939c56b83c9142ac129f02769770128d1f6fc6

refs/heads/master

2020-07-05T22:50:47.026269

2016-11-17T21:09:01

73,976,758

1

null

UTF-8

Python

false

1,052

py

# -*- coding: utf-8 -*- # Define your item pipelines here # # Don't forget to add your pipeline to the ITEM_PIPELINES setting # See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html import psycopg2 import logging from spiders.items import awayTeamRushItem from scrapy.conf import settings from scrapy.exceptions import DropItem class ScrapyDemoPipeline(object): def __init__(self): self.connection = psycopg2.connect(host='localhost', database='scraping_demo', user='Gannon') self.cursor = self.connection.cursor() def process_item(self, item, spider): try: if type(item) is awayTeamRushItem: table = """awayteamrush""" self.cursor.execute("""INSERT INTO """ + table + """ (rusher, car, yds, avg, td, longest) VALUES(%s, %s, %s, %s, %s, %s)""", (item.get('rusher'), item.get('car'), item.get('yds'), item.get('avg'), item.get('td'), item.get('longest'))) self.connection.commit() self.cursor.fetchall() except psycopg2.DatabaseError, e: print "Error: %s" % e return item

[ "gannonk08@gmail.com" ]

gannonk08@gmail.com

595635a1e4beaf535e5f7640bd2b7ca17a517b2c

b205909a015abf08dc15133797c465fd58a48352

/sdes.py

4d2868d7e9e2d273c541caee44e96f0f1bba4ee5

[]

no_license

AlexanderFrancoletti/CryptographyHW1

2648f5b52053504ac6cbceb7964a596d91c1a4bb

2d0b728046b91d099c3f6af9996c805db0df566e

refs/heads/master

2020-03-29T05:20:02.226714

2018-09-20T17:02:00

149,577,970

0

null

UTF-8

Python

false

3,547

py

#Define keys initially IP = [2, 6, 3, 1, 4, 8, 5, 7] EP = [4, 1, 2, 3, 2, 3, 4, 1] IP_inverse = [4, 1, 3, 5, 7, 2, 8, 6] P10 = [3, 5, 2, 7, 4, 10, 1, 9, 8, 6] P8 = [6, 3, 7, 4, 8, 5, 10, 9] P4 = [2, 4, 3, 1] sbox0 = [[1, 0, 3, 2], [3, 2, 1, 0], [0, 2, 1, 3], [3, 1, 3, 2]] sbox1 = [[0, 1, 2, 3], [2, 0, 1, 3], [3, 0, 1, 0], [2, 1, 0, 3]] default_key = '1010000010' #Function which returns a string of bits randomized based on the key being used def permutate(original, key): return ''.join(original[i-1] for i in key) #bitList = [] #for char in bitString: # if char == '1': # bitList.append(1) # else: # bitList.append(0) #return bitList #Returns the left half of bits in any key def keyLeftHalf(bits): return bits[:(len(bits)/2)] #Returns the right half of bits in any key def keyRightHalf(bits): return bits[(len(bits)/2):] #Split the bits passed in into 2 different halves, and then perform a leftwise shift on each half #and returns the combined result def shift(bits): leftHalfShift = keyLeftHalf(bits)[1:] + keyLeftHalf(bits)[0] rightHalfShift = keyRightHalf(bits)[1:] + keyRightHalf(bits)[0] return leftHalfShift+rightHalfShift #This function generates the key from the first round of shifts def generateKey1(): return permutate(shift(permutate(default_key, P10)), P8) #This function generates the key from the second round of shifts def generateKey2(): return permutate(shift(shift(shift(permutate(default_key, P10)))), P8) #XOR function, this returns the string of bits created by applying the XOR operation between 2 bits def xor(bits, key): newBitString = '' for bit, key_bit in zip(map(int, bits), map(int, key)): if (bit != key_bit): newBitString = newBitString + '1' else: newBitString = newBitString + '0' return newBitString #This performs the non-linear sbox operations, which will transform the bits used as input #based on the sbox tables defined above def sboxLookup(bits, sbox): row = int(bits[0] + bits[3], 2) col = int(bits[1] + bits[2], 2) return '{0:02b}'.format(sbox[row][col]) #This is the function which will actually perform the DES algorithm by using the #helper functions above def fk(bits, key): #Split the bits into left and right halves left = keyLeftHalf(bits) right = keyRightHalf(bits) #Permutate the right half bits = permutate(right, EP) bits = xor(bits, key) #Transform the bits using the sbox table bits = sboxLookup(keyLeftHalf(bits), sbox0) + sboxLookup(keyRightHalf(bits), sbox1) #Permutate the resulting bits using the 4 bit key bits = permutate(bits, P4) #Perform xor operation on the return xor(bits, left) #Encryption call takes 8 bit inputs and calls the DES functions in order def encrypt(plainText): #bits = stringToBits(plainText) #Cipher the bits according to the IP key bits = permutate(plainText, IP) #Store the first key generated by the DES algorithm temp = fk(bits, generateKey1()) #Generate the second key for the DES algorithm bits = keyRightHalf(bits) + temp bits = fk(bits, generateKey2()) #Return the resulting encrypted string of bytes return permutate(bits + temp, IP_inverse) #Decryption call has identical operations as encrypt, with the exception of #calling the Key2 function first def decrypt(cipherText): bits = permutate(cipherText, IP) temp = fk(bits, generateKey2()) bits = keyRightHalf(bits) + temp bits = fk(bits, generateKey1()) return permutate(bits + temp, IP_inverse)

[ "alexander.francoletti@gmail.com" ]

alexander.francoletti@gmail.com

45deb898113df9ae83c65ce0424014c7fb729b1e

5ee088a8573a305ea30bfc6d083c4ec6a1112d1f

/doule_exit/InitialPedestrian.py

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no_license

Poloma07/CA_Multi_Exits

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refs/heads/master

2020-04-18T16:57:45.466170

2019-01-13T12:24:39

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import random import numpy as np import Data, Block import matplotlib.pyplot as plt def creatPeople(): ''' 产生随机行人 :return:行人列表 ''' allBlock = [] # 用于存放格子 allPeople = [] # 用于存放行人 # 将所有格子全部存入列表' for i in range(1, Data.ROOM_M): for j in range(1, Data.ROOM_N): b = Block.Block() b.x = i b.y = j if random.random() > 0.5: # 顺时针和逆时针行人各占一半 b.clock_wise = True else: b.clock_wise = False #----------初始化行人收益------------- b.income_inertia = np.zeros(9) b.income_wall = np.zeros(9) b.income_exit = np.zeros(9) b.income_memory = np.zeros(9) b.income_all = np.zeros(9) allBlock.append(b) # 添加行人 random.shuffle(allBlock) # 随机排序 allPeople = allBlock[:Data.PEOPLE_NUMBER] # 取前N个可有效防止无限产生随机数 return allPeople def creatAppointPeo(): ''' 产生指定行人 :return: 行人列表 ''' allPeople = [] b3 = Block.Block() b3.x = 3 b3.y = 10 b3.type = False b3.clock_wise = False b3.income_inertia = np.zeros(9) b3.income_wall = np.zeros(9) b3.income_exit = np.zeros(9) b3.income_memory = np.zeros(9) b3.income_all = np.zeros(9) allPeople.append(b3) return allPeople

[ "1279010287@qq.com" ]

1279010287@qq.com

0da39b2b6595f0a25f70e3735197ce8c382da45b

c7522a46908dfa0556ed6e2fe584fd7124ee5cdc

/ApplicationUsers/views.py

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[]

no_license

stheartsachu/Eventlee

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6b67dfc873203f1322c16664923ffe5a760d50ed

refs/heads/master

2022-11-13T14:48:39.097718

2020-06-30T04:54:45

276,000,638

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from django.shortcuts import render,HttpResponse,redirect,HttpResponseRedirect from ApplicationUsers.form import ApplicationuserForm # Create your views here. from ApplicationUsers.models import users def home(request): return render(request,"index.html") def Contact(request): return render(request,"contact.html") def gallery(request): return render(request,"gallery.html") def signup(request): if request.method == 'POST': form = ApplicationuserForm(request.POST) f = form.save(commit=False) f.first_name = request.POST['fn'] f.last_name = request.POST['ln'] f.email = request.POST['email'] if request.POST['p1'] == request.POST['p2']: f.password = request.POST['p2'] else: return HttpResponse("<h1> Password and Confirm password is not same</h1>") f.status = True f.save() return HttpResponse("User is created sucessfully now, can login to website") return render(request, 'registration.html') def login(request): if request.method == "POST": un = request.POST["email"] up = request.POST["password"] try: data = users.objects.get(email=un) except: return render(request, "login.html", {'emailerror': True}) dp = data.password active = data.status if (active == False): return render(request, "login.html", {'activeerror': True}) else: if (dp == up): request.session['emailid'] = un request.session['Authentication'] = True return HttpResponse("You are sucessfullly login") else: return render(request, "login.html", {'passworderror': True}) return render(request, "login.html")

[ "seartsachu@gmail.com" ]

seartsachu@gmail.com

0153dcd0356625cc5eeb56abefd0fa3a6ed54d56

1f0837796a613fcf1788b2361fe4d8d5943bcc47

/Tarea Nº1/Ejer7.py

5bd8720ac4dfec14680de5faa08d98c167e2b592

[]

no_license

LeonardoArroba/Tarea-de-Estructura

557f47206c007dad6a7ed5ecc8e29f73c1ab895c

d37e9e9fdf1a562c8f5d29c5fee8e836d87a32c9

refs/heads/main

2023-06-02T12:36:43.153125

2021-06-30T02:53:46

381,556,550

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#Determinar la cantidad de dinero que recibirá un trabajador por concepto de las horas extras trabajadas en una empresa, # sabiendo que cuando las horas de trabajo exceden de 40, el resto se consideran horas extras y que éstas se pagan al doble # de una hora normal cuando no exceden de 8; si las horas extras exceden de 8 se pagan las primeras 8 al doble de lo que # se paga por una hora normal y el resto al triple """Ejercicio 7""" class Trabajador: def __init__(self): pass def calcularJornada(self): ht, he, het=0,0,0 ph, phe, pt, ph8=0,0,0,0 ht = int(input("Ingrese horas trabajadas: ")) ph = float(input("Ingrese valor hora: ")) if ht > 40: he = ht-40 if he > 8: het = he-8 ph8 = 8*ph*2 ph8 =het*ph*3 else: ph8 = he*ph*2 pt = 40*ph+phe+ph8 else: pt = ht*ph print("Sobretiempo<8:{} Sobretiempo>8:{} Jornada:{} ".format(ph8,phe,pt)) tarea = Trabajador() tarea.calcularJornada()

[ "noreply@github.com" ]

LeonardoArroba.noreply@github.com

cdcf3cbc200241606b4cc9140c33f8aa85da216f

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/MyOwnSolution/compare_images2.py

91e3c8d21c645f96e8bf20b90a1abd0d7e2fdea6

[]

no_license

lalona/parking-spot-classifier

fbc34b385d3620513126c91ecc106c3727a0be63

835ae0a514daecf623ba456b2ee5cab26123f939

refs/heads/master

2020-04-07T09:44:28.396823

2019-05-02T19:51:14

158,263,531

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""" La idea es simple: con una imagen donde el espacio se encuentre vacio se compara con otra imagenes y dependiendo las diferencias se concluye si está ocupado o vacio """ import cv2 import os from skimage.measure import compare_ssim as ssim from skimage.measure import compare_nrmse as nrmse import pickle import argparse from operator import itemgetter from itertools import groupby import matplotlib.pyplot as plt import numpy as np from tqdm import tqdm import ntpath import json path_pklot = 'C:\\Eduardo\\ProyectoFinal\\Datasets\\PKLot' def getGrayscaleImage(filepath): """ Read the image files and converts it to gray scale :param filepath: the path to the image :return: the image in grayscale """ image = cv2.imread(filepath) return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) def extractUniqueItemsByKey(list, key): """ This will take a list and sorted by the key and then it will return the list with just the elements from that key without duplicates :param list: :param key: :return: """ list.sort(key=lambda x: x[key]) return [k for k, v in groupby(list, key=lambda x: x[key])] def getNewImageInfo(image_info): image_info['filepath'] = os.path.join(path_pklot, image_info['filepath'], image_info['filename']) return image_info def mse(imageA, imageB): # the 'Mean Squared Error' between the two images is the # sum of the squared difference between the two images; # NOTE: the two images must have the same dimension err = np.sum((imageA.astype("float") - imageB.astype("float")) ** 2) err /= float(imageA.shape[0] * imageA.shape[1]) # return the MSE, the lower the error, the more "similar" # the two images are return err def main(): parser = argparse.ArgumentParser(description='Select the type of reduced.') parser.add_argument("-f", "--filename", type=str, required=True, help='Path to the file the contains the dictionary with the info of the dataset reduced.') args = vars(parser.parse_args()) info_filename = args["filename"] # test set with open(info_filename, "rb") as fp: # Unpickling images_info = pickle.load(fp) grouper = itemgetter('parkinglot', 'space') images_info = sorted(images_info, key=grouper) parkinglots = extractUniqueItemsByKey(images_info, 'parkinglot') images_info_by_patkinglot = {} for parkinglot in parkinglots: image_info_parkinglot = [i for i in images_info if i['parkinglot'] == parkinglot] spaces_parkinglot = extractUniqueItemsByKey(image_info_parkinglot, 'space') images_info_by_spaces = {} for space in spaces_parkinglot: images_info_by_spaces[space] = [getNewImageInfo(i) for i in image_info_parkinglot if i['space'] == space] images_info_by_patkinglot[parkinglot] = images_info_by_spaces # Hasta este punto ya tengo un dictionario dividido por estacionamiento que a su vez se divide por espacios # Voy a obtener la lista de un espacio en particular de un estacionamiento, voy a obtener el primer espacio vacio que # encuentre y despues voy a compararlo con los demas # Mostrar en una ventana el espacio vacio y en la otra la comparacion y el resultado empty_space_filepath = '' errors = [] for parkinglot, images_info_by_spaces in images_info_by_patkinglot.items(): for space, images_info_of_space in images_info_by_spaces.items(): error_count_empty = 0 error_count_occupied = 0 error_empty = 0 error_occupied = 0 empty_space_filepath = '' example_list = images_info_of_space for example in tqdm(example_list): if example['state'] == '0' and len(empty_space_filepath) == 0: empty_space_filepath = example['filepath'] img_empty_space = getGrayscaleImage(empty_space_filepath) break for example in tqdm(example_list): comparision_space_filepath = example['filepath'] img_comparision_space = getGrayscaleImage(comparision_space_filepath) try: sim = ssim(img_empty_space, img_comparision_space) except: height1, width1 = img_empty_space.shape img_comparision_space = cv2.resize(img_comparision_space, (width1, height1)) sim = ssim(img_empty_space, img_comparision_space) nm = nrmse(img_empty_space, img_comparision_space) # m = mse(img_empty_space, img_comparision_space) space_comparing_name = 'state: {} sim: {} nrmse: {}'.format(example['state'], sim, nm) if sim < 0.4 and example['state'] == '0': error_count_empty += 1 error_empty += abs(0.4 - sim) if sim >= 0.4 and example['state'] == '1': error_count_occupied += 1 error_occupied += abs(sim - 0.4) if sim > 0.7: empty_space_filepath = example['filepath'] img_empty_space = img_comparision_space """ fig = plt.figure('title') plt.suptitle(space_comparing_name) # show first image ax = fig.add_subplot(1, 2, 1) plt.imshow(img_empty_space, cmap=plt.cm.gray) plt.axis("off") # show the second image ax = fig.add_subplot(1, 2, 2) plt.imshow(img_comparision_space, cmap=plt.cm.gray) plt.axis("off") # show the images plt.show() """ error_occupied = 0 if error_count_occupied == 0 else (error_occupied / error_count_occupied) error_empty = 0 if error_count_empty == 0 else (error_empty / error_count_empty) print('In the space {} in a total of {} there was an error of occupied {} {} empty {} {}'.format(space, len( example_list), error_count_occupied, error_occupied, error_count_empty, error_empty)) errors.append({'parkinglot': parkinglot, 'space': space, 'total': len(example_list), 'error_count_occupied': error_count_occupied, 'error_occupied': error_occupied, 'error_count_empty': error_count_empty, 'error_empty': error_empty}) info = {'dataset': info_filename, 'threshold': 0.4, 'comparision_method': 'sim', 'errors': errors} dataset_name = ntpath.basename(info_filename).split('.')[0] feedback_filename = '{}_{}_{}.json'.format(dataset_name, 0.4, 'sim') with open(feedback_filename, 'w') as outfile: json.dump(info, outfile) # s = ssim(grayscale_selected_image, grayscale_current_image) if __name__ == "__main__": main()

[ "sebastianxiro@gmail.com" ]

sebastianxiro@gmail.com

6846461a15b491de3c42e18d6aa4d646d87bad7a

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/Python基础笔记/13/代码/3.多继承.py

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[]

no_license

zhenguo96/test1

fe21510aea7feb674e52fd7a86d4177666f841c5

0d8de7e73e7e635d26462a0bc53c773d999498be

refs/heads/master

2020-05-03T13:09:53.592103

2019-04-06T07:08:47

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# # 多继承 # class Base1: # def __init__(self,name): # self.name = name # def t1(self): # print("Base1") # # class Base2: # def __init__(self,name): # self.name = name # def t2(self): # print("Base2") # # class Base3: # def __init__(self, name): # self.name = name # def t3(self): # print("Base3") # # # 多继承的子类 # class Child(Base1,Base2,Base3): # pass # child = Child('tom') # print(child.__dict__) # child.t1() # child.t2() # # 继承顺序 # print(Child.mro()) # print(Child.__mro__) #

[ "1148421588@qq.com" ]

1148421588@qq.com

a9c4497452165d55ce911de902394c5c85022e33

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/01_LiniarRegression/Live/linearRegressionWGradientDescent.py

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[]

no_license

EduardoFAFernandes/MyDeepLearningIntro

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a35a43f0690ddfa499097335d9b8aa058d1db021

refs/heads/master

2021-09-05T06:51:33.479757

2018-01-25T01:07:54

null

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null

UTF-8

Python

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py

from numpy import * def compute_error_for_given_points(m, b, points): totalError = 0 for point in points: totalError += (point[1] - (m * point[0] + b))**2 return totalError / float(size(points)) def step_gradient(current_b, current_m, points, learning_rate): gradient_m = 0 gradient_b = 0 N = float(len(points)) for point in points: x = point[0] y = point[1] gradient_m += -(2/N) * x *(y - ((current_m * x) + current_b)) gradient_b += -(2/N) * (y - ((current_m * x) + current_b)) new_b = current_b - (learning_rate * gradient_b) new_m = current_m - (learning_rate * gradient_m) return [ new_b, new_m] def gradient_descent_runner(points, initial_b, initial_m, learning_rate, num_iterations ): b = initial_b m = initial_m for i in range(num_iterations): b,m = step_gradient(b, m, array(points), learning_rate) return [b, m] def run(): points = genfromtxt('data.csv', delimiter = ',') #hyperparameters learning_rate = 0.0001 #y = mx + b initial_b = 0 initial_m = 0 num_iterations = 1000 print("Starting gradient descent at b = {0}, m = {1}, error = {2}".format( initial_b, initial_m, compute_error_for_given_points(initial_b, initial_m, points))) print("Running...") [b, m] = gradient_descent_runner(points, initial_b, initial_m, learning_rate, num_iterations ) print("After {0} iterations b = {1}, m = {2}, error = {3}".format( num_iterations, b, m, compute_error_for_given_points(b, m, points))) if __name__ == '__main__': run()

[ "nomeaocalhas3@gmail.com" ]

nomeaocalhas3@gmail.com

3a319731bfbf4784b70ae3333efef1452e0f0744

bb0af8077407b27f8c3b787d32bdd9c4b37e977a

/fitmodel_densitysplit/do_fitting/modelfitfullk.py

82cbe8d7dac400a6d8e1c6ddf94bc83a4de38ec0

[]

no_license

JulianWack/IfA-SummerStudent-2022

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d1c6ebe48e0a527fe6138c73adc35464538e2e04

refs/heads/main

2023-04-15T02:51:59.098422

2022-09-10T10:52:38

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null

UTF-8

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py

# Fit Kaiser with FoG term over largest possible k range # Identical to modelfit.py excepet for storing paths and line 94 import numpy as np import matplotlib.pyplot as plt from scipy.special import legendre, erf from datetime import timedelta import time from os import mkdir, listdir import helper_funcs as hf from astropy.cosmology import Planck18 as Planck18_astropy import camb import zeus from nbodykit.lab import * from nbodykit import style plt.style.use(style.notebook) ### MCMC functions### def logprior(theta, i, kmax): ''' The natural logarithm of the prior probability. Assume parameters independent such that log priors add. Note that normalization is irrelevant for MCMC.''' lp = 0. b1, beta, sigma = theta sigma_min, sigma_max = 1, 5 sigma_max = 5 if kmax < 0.075 else 60 lp_sigma = 0. if sigma_min < sigma < sigma_max else -np.inf b1_min, b1_max = 0, 3 if i == 0: beta_min, beta_max = -3, 3 else: beta_min, beta_max = 0, 3 lp_b1 = 0. if b1_min < b1 < b1_max else -np.inf lp_beta = 0. if beta_min < beta < beta_max else -np.inf return lp_b1 + lp_beta + lp_sigma def loglike(theta, data_multipoles, k, C_inv): '''Return logarithm of likelihood i.e. -0.5*chi2. data_multipoles must be an array of shape (len(ells), len(k)). theta is parameter vector: [b1, beta, sigma].''' ells = [0,2] model_multipoles = np.empty((len(ells), len(k))) b1, beta, sigma = theta model_multipoles[0] = ( 1/(2*(k*sigma)**5) * (np.sqrt(2*np.pi)*erf(k*sigma/np.sqrt(2))*(3*beta**2+(k*sigma)**4+2*beta*(k*sigma)**2) + np.exp(-0.5*(k*sigma)**2)*(-2*beta*(beta+2)*(k*sigma)**3-6*beta**2*k*sigma) ) ) * b1**2 * Plin(k) model_multipoles[1] = ( -5/(4*(k*sigma)**7) * (np.sqrt(2*np.pi)*erf(k*sigma/np.sqrt(2))*(-45*beta**2+(k*sigma)**6+(2*beta-3)*(k*sigma)**4+3*(beta-6)*beta*(k*sigma)**2) + np.exp(-0.5*(k*sigma)**2)*((4*beta*(beta+2)+6)*(k*sigma)**5+12*beta*(2*beta+3)*(k*sigma)**3+90*beta**2*k*sigma) ) ) * b1**2 * Plin(k) D_M = (data_multipoles - model_multipoles).flatten() return -0.5*D_M@(C_inv @ D_M) def logpost(theta, i, data_multipoles, k, C_inv): '''Returns the logarithm of the posterior. By Bayes' theorem, this is just the sum of the log prior and log likelihood (up to a irrelavant constant). Uses values for theta from pre-analysis step to inform prior ''' return logprior(theta, i, k[-1]) + loglike(theta, data_multipoles, k, C_inv) ##################### ### Set up MCMC ### LOS = [0,0,1] redshift = 0.2 BoxSize = 2000 cosmo = cosmology.Cosmology.from_astropy(Planck18_astropy) Plin = cosmology.LinearPower(cosmo, redshift, transfer='CLASS') sigma8_lin = Plin.sigma_r(8) # load Planck18 data for CAMB and find f*sigma8 at redshift # follows https://camb.readthedocs.io/en/latest/CAMBdemo.html pars=camb.read_ini('../planck_2018.ini') _ = pars.set_matter_power(redshifts=[redshift], kmax=1.4) pars.NonLinear = camb.model.NonLinear_none results = camb.get_results(pars) fs8_true = results.get_fsigma8()[0] ptile_labels = [r'$0^{th}$', r'$1^{st}$', r'$2^{nd}$', r'$3^{rd}$', r'$4^{th}$', r'$5^{th}$', r'$6^{th}$', r'$7^{th}$', r'$8^{th}$', r'$9^{th}$'] dk = 0.01 ells = [0,2] # load computed power spectra to deduce multipoles in each bin and P(k,mu) from data # need to pass location location of folder containing stored power spectra which lies one level lower in this case k_full, shotnoise, n_ptile, Pk_ells_full = hf.load_power_data('../', ells, get_data_Pkmus=False) # for given BoxSize, k is NaN above 0.034 possible_kmax = k_full[k_full<=0.343][1:] # ignore first k bin kmax_range = possible_kmax Nkmax = len(kmax_range) b1_fits, beta_fits, sigma_fits, delta_fs8 = np.full((n_ptile, Nkmax), np.nan), np.full((n_ptile, Nkmax), np.nan), np.full((n_ptile, Nkmax), np.nan), np.full((n_ptile, Nkmax), np.nan) b1_stds, beta_stds, sigma_stds, delta_fs8_stds = np.full((n_ptile, Nkmax), np.nan), np.full((n_ptile, Nkmax), np.nan), np.full((n_ptile, Nkmax), np.nan), np.full((n_ptile, Nkmax), np.nan) reduced_chi2 = np.full((n_ptile, Nkmax), np.nan) nsteps = 2500 ndim = 3 nwalkers = 8 start_b1 = 0.5 + 1*np.random.random(nwalkers) start_beta = 0.5 + 1*np.random.random(nwalkers) start_sigma = 1 + 4*np.random.random(nwalkers) start = np.column_stack([start_b1, start_beta, start_sigma]) ################### ### Run MCMC ### root_path = '../fit_results/FoG_fullk/' print("Fitting up to kmax=%.3f"%kmax_range[-1]) for i in range(n_ptile): store_path = root_path+'chains_ptile%d/'%i if 'chains_ptile%d'%i not in listdir(root_path): mkdir(store_path) cov_mat = np.loadtxt('../bruteforce_covmat/covariance_matricies/cov_ptile_%d.txt'%i) t1 = time.time() for j,kmax in enumerate(kmax_range): if 'k%d.npy'%j in listdir(store_path): continue # slice up to increasingly large kmax and find delta_fs8 for each bin mask = np.full(len(k_full), False) mask = k_full <= kmax mask[0] = False k_sliced = k_full[mask] Pk_ells_i = Pk_ells_full[:,:,mask][i] C_inv = hf.mock_cov_mat_inv(cov_mat, k_full, kmax) sampler = zeus.EnsembleSampler(nwalkers, ndim, logpost, maxiter=1e5, verbose=False, args=[i, Pk_ells_i, k_sliced, C_inv]) sampler.run_mcmc(start, nsteps) chain = sampler.get_chain(flat=True, discard=nsteps//2) # save chain without burn-in np.save(store_path+'k%d'%j, chain) b1_fits[i][j], b1_stds[i][j] = np.mean(chain[:,0]), np.std(chain[:,0]) # parameter space is sym about b1=0 for Kaiser model. To get non negative fs8 assure that b1 and beta have the same sign if i == 0: b1_fits[i][j] *= -1 beta_fits[i][j], beta_stds[i][j] = np.mean(chain[:,1]), np.std(chain[:,1]) delta_fs8[i][j] = 1 - sigma8_lin*(beta_fits[i][j]*b1_fits[i][j])/fs8_true delta_fs8_stds[i][j] = np.abs(sigma8_lin/fs8_true*(beta_stds[i][j]*b1_fits[i][j]+beta_fits[i][j]*b1_stds[i][j])) sigma_fits[i][j], sigma_stds[i][j] = np.mean(chain[:,2]), np.std(chain[:,2]) reduced_chi2[i][j] = -2*loglike([b1_fits[i][j], beta_fits[i][j], sigma_fits[i][j]], Pk_ells_i, k_sliced, C_inv) / (len(ells)*len(k_sliced)-ndim) t2 = time.time() print('Fitted %d-th percentile in %s'%(i,str(timedelta(seconds=t2-t1)))) ################ ### Store fit result ### np.savetxt(root_path+'b1_fits.txt', b1_fits) np.savetxt(root_path+'b1_stds.txt', b1_stds) np.savetxt(root_path+'beta_fits.txt', beta_fits) np.savetxt(root_path+'beta_stds.txt', beta_stds) np.savetxt(root_path+'delta_fs8.txt', delta_fs8) np.savetxt(root_path+'delta_fs8_stds.txt', delta_fs8_stds) np.savetxt(root_path+'sigma_fits.txt', sigma_fits) np.savetxt(root_path+'sigma_stds.txt', sigma_stds) np.savetxt(root_path+'reduced_chi2.txt', reduced_chi2) ######################## ### Make fs8 plot ### fig = plt.figure(figsize=(20,8)) for i in range(n_ptile): plt.plot(kmax_range, delta_fs8[i], label=ptile_labels[i]) plt.fill_between(kmax_range, delta_fs8[i]-delta_fs8_stds[i,:], delta_fs8[i]+delta_fs8_stds[i,:], alpha=0.1) plt.title(r'$\Delta f\sigma_8$ at $z=%.3f$'%redshift) plt.xlabel(r'$k_{max}$ [$h \ \mathrm{Mpc}^{-1}$]') plt.ylabel(r'$1 - (\sigma_8^{lin}*\beta*b_1) \ / \ (f\sigma_8)^{true}$') handles, labels = plt.gca().get_legend_handles_labels() fig.legend(handles, labels, loc='upper center', bbox_to_anchor=(0.5, -0.05), ncol=n_ptile) fig.savefig("../plots/KaiserFoG_fullk_dfs8_vs_kmax.pdf") ##################### ### Make fit plot ### fig = plt.figure(figsize=(26,18)) ax_b1 = plt.subplot(2,3,1) ax_beta = plt.subplot(2,3,2) ax_sigma = plt.subplot(2,3,3) ax_chi2 = plt.subplot(2,3,(4,6)) for i in range(n_ptile): ax_b1.plot(kmax_range, b1_fits[i], label=ptile_labels[i]) ax_b1.fill_between(kmax_range, b1_fits[i]-b1_stds[i], b1_fits[i]+b1_stds[i], alpha=0.1) ax_beta.plot(kmax_range, beta_fits[i], label=ptile_labels[i]) ax_beta.fill_between(kmax_range, beta_fits[i]-beta_stds[i], beta_fits[i]+beta_stds[i], alpha=0.1) ax_sigma.plot(kmax_range, sigma_fits[i], label=ptile_labels[i]) ax_sigma.fill_between(kmax_range, sigma_fits[i]-sigma_stds[i], sigma_fits[i]+sigma_stds[i], alpha=0.1) ax_chi2.plot(kmax_range[1:], reduced_chi2[i][1:], label=ptile_labels[i]) # first element negative, s.t. not shown on log scale ax_b1.set_title(r'$b_1$ mean and $1\sigma$ interval') ax_b1.set_xlabel(r'$k_{max}$ [$h \ \mathrm{Mpc}^{-1}$]') ax_b1.set_ylabel(r'$b_1$') ax_beta.set_title(r'$\beta$ mean and $1\sigma$ interval') ax_beta.set_xlabel(r'$k_{max}$ [$h \ \mathrm{Mpc}^{-1}$]') ax_beta.set_ylabel(r'$\beta$') ax_sigma.set_title(r'$\sigma$ mean and $1\sigma$ interval') ax_sigma.set_xlabel(r'$k_{max}$ [$h \ \mathrm{Mpc}^{-1}$]') ax_sigma.set_ylabel(r'$\sigma$ [$h^{-1} \ \mathrm{Mpc}$]') ax_chi2.set_title(r'reduced $\chi^2$') ax_chi2.set_yscale('log') ax_chi2.set_xlabel(r'$k_{max}$ [$h \ \mathrm{Mpc}^{-1}$]') ax_chi2.set_ylabel(r'$\chi^2 / dof$') handles, labels = plt.gca().get_legend_handles_labels() fig.legend(handles, labels, loc='upper center', bbox_to_anchor=(0.5, +0.05), ncol=n_ptile) fig.savefig("../plots/KaiserFoG_fullk_fits.pdf") #####################

[ "jwack@cuillin.roe.ac.uk" ]

jwack@cuillin.roe.ac.uk

964887bf2513e38eadfe80819f983c5826f676de

0b9f6534a99ff551f0006df78a24e8af30340580

/Source/BackupFiles/HDAPI/hdapi/API 문서/python_sample.py

08a1d2e3fc1c3952637678e603a976500b276f82

[]

no_license

jayirum/ChartProjSvr

9bac49865d1e081de0cbd7559d0d2cbdd26279c2

d69edfcb3ac3698e1bdfcf5862d5e63bb305cb52

refs/heads/master

2020-03-24T03:22:18.176911

2019-07-05T01:38:03

142,416,528

1

null

UTF-8

Python

false

130,254

py

#-*- coding: utf-8 -*- # Form implementation generated from reading ui file './python_sample.ui' # # Created by: PyQt4 UI code generator 4.11.4 # # WARNING! All changes made in this file will be lost! # Python version 2.7 from PyQt4 import QtCore, QtGui #from PyQt4.QAxContainer import * #from PyQt4.QtCore import * from PyQt4.QtGui import * from PyQt4.QAxContainer import * import time import os import sys reload(sys) sys.setdefaultencoding('utf-8') try: _fromUtf8 = QtCore.QString.fromUtf8 except AttributeError: def _fromUtf8(s): return s try: _encoding = QtGui.QApplication.UnicodeUTF8 def _translate(context, text, disambig): return QtGui.QApplication.translate(context, text, disambig, _encoding) except AttributeError: def _translate(context, text, disambig): return QtGui.QApplication.translate(context, text, disambig) class Ui_MainWindow(object): CONST_FO_SERIES = "101L6000" CONST_FO_SISE_51 = "51" # 국내선물호가 CONST_FO_SISE_65 = "65" # 국내선물체결 CONST_FO_SISE_58 = "58" # 국내상품선물호가 CONST_FO_SISE_71 = "71" # 국내상품선물체결 CONST_FO_ORDER_181 = "181" # 국내주문실시간접수 CONST_FO_ORDER_182 = "182" # 국내주문실시간미체결 CONST_FO_ORDER_183 = "183" # 국내주문실시간미결제 CONST_FO_ORDER_184 = "184" # 국내주문실시간잔고 CONST_FO_ORDER_185 = "185" # 국내주문실시간체결 CONST_FR_SERIES = "6AH16" CONST_FR_SISE_76 = "76" # 해외선물호가 CONST_FR_SISE_82 = "82" # 해외선물체결 CONST_FR_ORDER_196 = "196" # 해외주문실시간접수 CONST_FR_ORDER_186 = "186" # 해외주문실시간미체결 CONST_FR_ORDER_187 = "187" # 해외주문실시간미결제 CONST_FR_ORDER_188 = "188" # 해외주문실시간잔고 CONST_FR_ORDER_189 = "189" # 해외주문실시간체결 CONST_FX_SERIES = "EUR/USD" CONST_FX_SISE_171 = "171" #attributes m_AccListFO = {} m_AccListFR = {} m_AccListFX = {} m_TrQueryListFO = {} # 국내 조회 m_FidQueryListFO = {} # 국내 FID조회 m_TrOrderListFO = {} # 국내 주문 m_TrQueryListFR = {} m_FidQueryListFR = {} # 해외 FID조회 m_TrOrderListFR = {} m_TrQueryListFX = {} m_FidQueryListFX = {} # 해외 FID조회 m_TrOrderListFX = {} # 실시간 m_RealSiseListFO = {} m_RealOrderListFO = {} m_RealSiseListFR = {} m_RealOrderListFR = {} m_RealSiseListFX = {} m_RealOrderListFX = {} m_bUseComboTrChange = True def setupUi(self, MainWindow): _TOP_Pos = 50 MainWindow.setObjectName(_fromUtf8("MainWindow")) MainWindow.resize(800, 600) self.centralwidget = QtGui.QWidget(MainWindow) self.centralwidget.setObjectName(_fromUtf8("centralwidget")) self.label_6 = QtGui.QLabel(self.centralwidget) self.label_6.setGeometry(QtCore.QRect(10, 10, 56, 12)) self.label_6.setObjectName(_fromUtf8("label_6")) self.Edit_Path = QtGui.QLineEdit(self.centralwidget) self.Edit_Path.setGeometry(QtCore.QRect(70, 7, 400, 20)) self.Edit_Path.setObjectName(_fromUtf8("Edit_Path")) self.BTN_Connect = QtGui.QPushButton(self.centralwidget) self.BTN_Connect.setGeometry(QtCore.QRect(10, _TOP_Pos+10, 121, 23)) self.BTN_Connect.setObjectName(_fromUtf8("BTN_Connect")) self.BTN_DisConnect = QtGui.QPushButton(self.centralwidget) self.BTN_DisConnect.setGeometry(QtCore.QRect(150, _TOP_Pos+10, 111, 23)) self.BTN_DisConnect.setObjectName(_fromUtf8("BTN_DisConnect")) self.label = QtGui.QLabel(self.centralwidget) self.label.setGeometry(QtCore.QRect(10, _TOP_Pos+50, 56, 12)) self.label.setObjectName(_fromUtf8("label")) self.label_2 = QtGui.QLabel(self.centralwidget) self.label_2.setGeometry(QtCore.QRect(200, _TOP_Pos+50, 70, 12)) self.label_2.setObjectName(_fromUtf8("label_2")) self.label_3 = QtGui.QLabel(self.centralwidget) self.label_3.setGeometry(QtCore.QRect(401, _TOP_Pos+50, 111, 16)) self.label_3.setObjectName(_fromUtf8("label_3")) self.Edit_UserID = QtGui.QLineEdit(self.centralwidget) self.Edit_UserID.setGeometry(QtCore.QRect(70, _TOP_Pos+45, 113, 20)) self.Edit_UserID.setObjectName(_fromUtf8("Edit_UserID")) self.Edit_UserPW = QtGui.QLineEdit(self.centralwidget) self.Edit_UserPW.setGeometry(QtCore.QRect(280, _TOP_Pos+46, 113, 20)) self.Edit_UserPW.setEchoMode(QtGui.QLineEdit.Password) self.Edit_UserPW.setObjectName(_fromUtf8("Edit_UserPW")) self.Edit_CertPW = QtGui.QLineEdit(self.centralwidget) self.Edit_CertPW.setGeometry(QtCore.QRect(510, _TOP_Pos+47, 113, 20)) self.Edit_CertPW.setEchoMode(QtGui.QLineEdit.Password) self.Edit_CertPW.setObjectName(_fromUtf8("Edit_CertPW")) self.Btn_Login = QtGui.QPushButton(self.centralwidget) self.Btn_Login.setGeometry(QtCore.QRect(390, _TOP_Pos+80, 75, 23)) self.Btn_Login.setObjectName(_fromUtf8("Btn_Login")) self.Btn_Logout = QtGui.QPushButton(self.centralwidget) self.Btn_Logout.setGeometry(QtCore.QRect(550, _TOP_Pos+80, 75, 23)) self.Btn_Logout.setObjectName(_fromUtf8("Btn_Logout")) # 국내/해외/FX self.groupBox1 = QtGui.QGroupBox(self.centralwidget) self.groupBox1.setGeometry(QtCore.QRect(10, _TOP_Pos+110, 200, 41)) self.groupBox1.setObjectName(_fromUtf8("groupBox")) self.BtnRadio1 = QtGui.QRadioButton(self.groupBox1) self.BtnRadio1.setGeometry(QtCore.QRect(10, 10, 111, 22)) self.BtnRadio1.setObjectName(_fromUtf8("BtnRadio1")) self.BtnRadio2 = QtGui.QRadioButton(self.groupBox1) self.BtnRadio2.setGeometry(QtCore.QRect(70, 10, 111, 22)) self.BtnRadio2.setObjectName(_fromUtf8("BtnRadio2")) self.BtnRadio3 = QtGui.QRadioButton(self.groupBox1) self.BtnRadio3.setGeometry(QtCore.QRect(140, 10, 111, 22)) self.BtnRadio3.setObjectName(_fromUtf8("BtnRadio3")) # Tr조회, Fid조회, 주문 self.groupBox2 = QtGui.QGroupBox(self.centralwidget) self.groupBox2.setGeometry(QtCore.QRect(251, _TOP_Pos+110, 200, 41)) self.groupBox2.setObjectName(_fromUtf8("groupBox2")) self.BtnRadioQry1 = QtGui.QRadioButton(self.groupBox2) self.BtnRadioQry1.setGeometry(QtCore.QRect(10, 10, 111, 22)) self.BtnRadioQry1.setObjectName(_fromUtf8("BtnRadioQry1")) self.BtnRadioQry2 = QtGui.QRadioButton(self.groupBox2) self.BtnRadioQry2.setGeometry(QtCore.QRect(70, 10, 111, 22)) self.BtnRadioQry2.setObjectName(_fromUtf8("BtnRadioQry2")) self.BtnRadioQry3 = QtGui.QRadioButton(self.groupBox2) self.BtnRadioQry3.setGeometry(QtCore.QRect(140, 10, 111, 22)) self.BtnRadioQry3.setObjectName(_fromUtf8("BtnRadioQry3")) #해외 종목코드 수신 self.Btn_ReqJMCodeFR = QtGui.QPushButton(self.centralwidget) self.Btn_ReqJMCodeFR.setGeometry(QtCore.QRect(460, _TOP_Pos+120, 120, 23)) self.Btn_ReqJMCodeFR.setObjectName(_fromUtf8("Btn_ReqJMCodeFR")) # 계좌 콤보 self.label_4 = QtGui.QLabel(self.centralwidget) self.label_4.setGeometry(QtCore.QRect(10, _TOP_Pos+165, 56, 12)) self.label_4.setObjectName(_fromUtf8("label_4")) self.ComboAcc = QtGui.QComboBox(self.centralwidget) self.ComboAcc.setGeometry(QtCore.QRect(70, _TOP_Pos+160, 111, 22)) self.ComboAcc.setObjectName(_fromUtf8("ComboAcc")) self.label_acctNm = QtGui.QLabel(self.centralwidget) self.label_acctNm.setGeometry(QtCore.QRect(450, _TOP_Pos+165, 56, 12)) self.label_acctNm.setObjectName(_fromUtf8("label_acctNm")) #계좌비번 self.label_7 = QtGui.QLabel(self.centralwidget) self.label_7.setGeometry(QtCore.QRect(200, _TOP_Pos+165, 56, 12)) self.label_7.setObjectName(_fromUtf8("label_7")) self.Edit_AcctPW = QtGui.QLineEdit(self.centralwidget) self.Edit_AcctPW.setGeometry(QtCore.QRect(280, _TOP_Pos+160, 113, 20)) self.Edit_AcctPW.setEchoMode(QtGui.QLineEdit.Password) self.Edit_AcctPW.setObjectName(_fromUtf8("Edit_AcctPW")) #서비스 콤부 self.label_5 = QtGui.QLabel(self.centralwidget) self.label_5.setGeometry(QtCore.QRect(10, _TOP_Pos+200, 56, 12)) self.label_5.setObjectName(_fromUtf8("label_5")) self.ComboTr = QtGui.QComboBox(self.centralwidget) self.ComboTr.setGeometry(QtCore.QRect(70, _TOP_Pos+195, 200, 22)) self.ComboTr.setObjectName(_fromUtf8("ComboTr")) self.label_8 = QtGui.QLabel(self.centralwidget) self.label_8.setGeometry(QtCore.QRect(280, _TOP_Pos+200, 60, 12)) self.label_8.setObjectName(_fromUtf8("label_8")) self.label_tr = QtGui.QLabel(self.centralwidget) self.label_tr.setGeometry(QtCore.QRect(340, _TOP_Pos+200, 150, 12)) self.label_tr.setObjectName(_fromUtf8("label_tr")) # 입력 부분 self.label_10 = QtGui.QLabel(self.centralwidget) self.label_10.setGeometry(QtCore.QRect(10, _TOP_Pos+230, 60, 12)) self.label_10.setObjectName(_fromUtf8("label_10")) self.Edit_Input = QtGui.QLineEdit(self.centralwidget) self.Edit_Input.setGeometry(QtCore.QRect(70, _TOP_Pos+225, 450, 20)) self.Edit_Input.setObjectName(_fromUtf8("Edit_Input")) self.Edit_Input_FID = QtGui.QLineEdit(self.centralwidget) self.Edit_Input_FID.setGeometry(QtCore.QRect(525, _TOP_Pos+225, 120, 20)) self.Edit_Input_FID.setObjectName(_fromUtf8("Edit_Input_FID")) self.BTN_Query = QtGui.QPushButton(self.centralwidget) self.BTN_Query.setGeometry(QtCore.QRect(650, _TOP_Pos+224, 60, 22)) self.BTN_Query.setObjectName(_fromUtf8("BTN_Query")) # 실시간 self.groupBox3 = QtGui.QGroupBox(self.centralwidget) self.groupBox3.setGeometry(QtCore.QRect(10, _TOP_Pos+250, 200, 41)) self.groupBox3.setObjectName(_fromUtf8("groupBox")) self.label_11 = QtGui.QLabel(self.groupBox3) self.label_11.setGeometry(QtCore.QRect(10, 10, 111, 22)) self.label_11.setObjectName(_fromUtf8("label_11")) self.BtnRadioSiseReal = QtGui.QRadioButton(self.groupBox3) self.BtnRadioSiseReal.setGeometry(QtCore.QRect(70, 10, 111, 22)) self.BtnRadioSiseReal.setObjectName(_fromUtf8("BtnRadioSiseReal")) self.BtnRadioOrderReal = QtGui.QRadioButton(self.groupBox3) self.BtnRadioOrderReal.setGeometry(QtCore.QRect(140, 10, 111, 22)) self.BtnRadioOrderReal.setObjectName(_fromUtf8("BtnRadioOrderReal")) # 실시간 등록/해지 self.groupBox4 = QtGui.QGroupBox(self.centralwidget) self.groupBox4.setGeometry(QtCore.QRect(251, _TOP_Pos+250, 150, 41)) self.groupBox4.setObjectName(_fromUtf8("groupBox")) self.BtnRadioRealRegister = QtGui.QRadioButton(self.groupBox4) self.BtnRadioRealRegister.setGeometry(QtCore.QRect(10, 10, 111, 22)) self.BtnRadioRealRegister.setObjectName(_fromUtf8("BtnRadioRealRegister")) self.BtnRadioRealUnRegister = QtGui.QRadioButton(self.groupBox4) self.BtnRadioRealUnRegister.setGeometry(QtCore.QRect(70, 10, 111, 22)) self.BtnRadioRealUnRegister.setObjectName(_fromUtf8("BtnRadioRealUnRegister")) self.ComboReal = QtGui.QComboBox(self.centralwidget) self.ComboReal.setGeometry(QtCore.QRect(420, _TOP_Pos+260, 200, 22)) self.ComboReal.setObjectName(_fromUtf8("ComboReal")) self.label_12 = QtGui.QLabel(self.centralwidget) self.label_12.setGeometry(QtCore.QRect(10, _TOP_Pos+300, 60, 12)) self.label_12.setObjectName(_fromUtf8("label_12")) self.Edit_Input_Real_Key = QtGui.QLineEdit(self.centralwidget) self.Edit_Input_Real_Key.setGeometry(QtCore.QRect(70, _TOP_Pos+295, 50, 20)) self.Edit_Input_Real_Key.setObjectName(_fromUtf8("Edit_Input_Real_Key")) self.Edit_Input_Real_Val = QtGui.QLineEdit(self.centralwidget) self.Edit_Input_Real_Val.setGeometry(QtCore.QRect(130, _TOP_Pos+295, 250, 20)) self.Edit_Input_Real_Val.setObjectName(_fromUtf8("Edit_Input_Real_Val")) self.BTN_Query_Real = QtGui.QPushButton(self.centralwidget) self.BTN_Query_Real.setGeometry(QtCore.QRect(380, _TOP_Pos+294, 60, 22)) self.BTN_Query_Real.setObjectName(_fromUtf8("BTN_Query_Real")) self.multiline = QtGui.QPlainTextEdit(self.centralwidget) self.multiline.setGeometry(QtCore.QRect(10, _TOP_Pos+330, 781, 191)) self.multiline.setObjectName(_fromUtf8("listView")) MainWindow.setCentralWidget(self.centralwidget) self.menubar = QtGui.QMenuBar(MainWindow) self.menubar.setGeometry(QtCore.QRect(0, 0, 800, 21)) self.menubar.setObjectName(_fromUtf8("menubar")) MainWindow.setMenuBar(self.menubar) self.statusbar = QtGui.QStatusBar(MainWindow) self.statusbar.setObjectName(_fromUtf8("statusbar")) MainWindow.setStatusBar(self.statusbar) self.retranslateUi(MainWindow) self.SetupTabOrder() self.SetupSignal() def SetupSignal(self): QtCore.QObject.connect(self.BTN_Connect, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnConnect) QtCore.QObject.connect(self.BTN_DisConnect, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnDisConnect) QtCore.QObject.connect(self.Btn_Login, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnLogin) QtCore.QObject.connect(self.Btn_Logout, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnLogout) QtCore.QObject.connect(self.BtnRadio1, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnRadioAcctTpChange) QtCore.QObject.connect(self.BtnRadio2, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnRadioAcctTpChange) QtCore.QObject.connect(self.BtnRadio3, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnRadioAcctTpChange) QtCore.QObject.connect(self.BtnRadioQry1, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnRadioTrChange) QtCore.QObject.connect(self.BtnRadioQry2, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnRadioTrChange) QtCore.QObject.connect(self.BtnRadioQry3, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnRadioTrChange) QtCore.QObject.connect(self.Btn_ReqJMCodeFR, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnReqJmCodeFr) QtCore.QObject.connect(self.ComboAcc, QtCore.SIGNAL(_fromUtf8("currentIndexChanged(QString)")), self.OnComboAccChange) QtCore.QObject.connect(self.ComboTr, QtCore.SIGNAL(_fromUtf8("currentIndexChanged(QString)")), self.OnComboTrChange) QtCore.QObject.connect(self.BTN_Query, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnQuery) QtCore.QObject.connect(self.BtnRadioSiseReal, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnRadioRealChange) QtCore.QObject.connect(self.BtnRadioOrderReal, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnRadioRealChange) QtCore.QObject.connect(self.ComboReal, QtCore.SIGNAL(_fromUtf8("currentIndexChanged(QString)")), self.OnComboReal) QtCore.QObject.connect(self.BTN_Query_Real, QtCore.SIGNAL(_fromUtf8("clicked()")), self.OnRealRegister) def SetupTabOrder(self): QtCore.QMetaObject.connectSlotsByName(MainWindow) MainWindow.setTabOrder(self.BTN_Connect, self.Edit_UserID) MainWindow.setTabOrder(self.Edit_UserID, self.Edit_UserPW) MainWindow.setTabOrder(self.Edit_UserPW, self.Edit_CertPW) MainWindow.setTabOrder(self.Edit_CertPW, self.Btn_Login) MainWindow.setTabOrder(self.Btn_Login, self.ComboAcc) MainWindow.setTabOrder(self.ComboAcc, self.ComboTr) MainWindow.setTabOrder(self.ComboTr, self.Btn_Logout) MainWindow.setTabOrder(self.Btn_Logout, self.BTN_DisConnect) def SetupHDFOcx(self, MainWindow): self.HDF = QAxWidget("HDFCOMMAGENT.HDFCommAgentCtrl.1") self.HDF.connect(self.HDF, QtCore.SIGNAL("OnDataRecv(QString, int)"), self.OnDataRecv) self.HDF.connect(self.HDF, QtCore.SIGNAL("OnGetBroadData(QString, int)"), self.OnGetBroadData) self.HDF.connect(self.HDF, QtCore.SIGNAL("OnGetMsgWithRqId(int, QString, QString)"), self.OnGetMsgWithRqId) # 실행위치 설정 strPath = os.getcwd() self.Edit_Path.setText(_translate("MainWindow", strPath, None)) self.HDF.dynamicCall("CommSetOCXPath(" + strPath + ")") def HD_CommGetRepeatCnt(self, strTrCode, nRealType, strFildNm): nRqID = self.HDF.dynamicCall("CommGetRepeatCnt(QString, int, QString)", strTrCode, nRealType, strFildNm) return range(nRqID.toLongLong()[0]) def HD_CommRqData(self, strTrCode, strInputData, nInputLength, strPrevOrNext): nRqID = self.HDF.dynamicCall("CommRqData(QString, QString, LONG, QString)", strTrCode, strInputData, nInputLength, strPrevOrNext) return nRqID.toLongLong()[0] def HD_CommFIDRqData(self, strTrCode, strInputData, sReqFidList, sPrevOrNext): #BSTR sFidCode, BSTR sInputData, BSTR sReqFidList, LONG nLength, BSTR sPrevOrNext nRqID = self.HDF.dynamicCall("CommFIDRqData(QString, QString, QString, LONG, QString)", strTrCode, strInputData, sReqFidList, len(strInputData), sPrevOrNext) return nRqID.toLongLong()[0] def HD_CommJumunSvr(self, strTrCode, strInputData): nRqID = self.HDF.dynamicCall("CommJumunSvr(QString, QString)", strTrCode, strInputData) return nRqID.toLongLong()[0] def HD_CommGetData(self, strTrCode, nRealType, strRecNm, nIndex, strFieldNm): strFieldNm = unicode(str(strFieldNm).strip(), 'utf-8') strData = self.HDF.dynamicCall("CommGetData(QString, int, QString, int, QString)", strTrCode, nRealType, strRecNm, nIndex, strFieldNm) return strData.toString() def HD_RegReal(self, bReg, strValue, nKeyType): if ( bReg == True ): nRet = self.HDF.dynamicCall("CommSetBroad(QString, LONG)", strValue, nKeyType) else: nRet = self.HDF.dynamicCall("CommRemoveBroad(QString, LONG)", strValue, nKeyType) return nRet def HD_CommGetAccInfo(self): strData = self.HDF.dynamicCall("CommGetAccInfo()") return strData.toString() def HD_Login(self, strUserID, strUserWd, strCertPw): ret = self.HDF.dynamicCall("CommLogin(QString, QString, QString)", strUserID, strUserWd, strCertPw) def HD_Logout(self, strUserID): ret = self.HDF.dynamicCall("CommLogout(QString)", strUserID) def HD_CommReqMakeCod(self): ret = self.HDF.dynamicCall("CommReqMakeCod(QString, BOOL)", "JMCODE", False) def retranslateUi(self, MainWindow): MainWindow.setWindowTitle(_translate("MainWindow", "MainWindow", None)) self.label_6.setText(_translate("MainWindow", "실행위치", None)) self.BTN_Connect.setText(_translate("MainWindow", "통신관리자 실행", None)) self.BTN_DisConnect.setText(_translate("MainWindow", "통신관리자 종료", None)) self.label.setText(_translate("MainWindow", "사용자 ID", None)) self.label_2.setText(_translate("MainWindow", "HTS비번", None)) self.label_3.setText(_translate("MainWindow", "공인인증 비밀번호", None)) self.Btn_Login.setText(_translate("MainWindow", "로그인", None)) self.Btn_Logout.setText(_translate("MainWindow", "로그아웃", None)) self.label_4.setText(_translate("MainWindow", "계좌번호", None)) self.label_7.setText(_translate("MainWindow", "계좌비번", None)) self.label_5.setText(_translate("MainWindow", "조회유형", None)) self.label_8.setText(_translate("MainWindow", "TRCode : ", None)) self.label_10.setText(_translate("MainWindow", "Input : ", None)) self.BTN_Query.setText(_translate("MainWindow", "조회", None)) self.BtnRadio1.setText(_translate("MainWindow", "국내", None)) self.BtnRadio2.setText(_translate("MainWindow", "해외", None)) self.BtnRadio3.setText(_translate("MainWindow", "FX", None)) self.BtnRadio1.setChecked(True) self.BtnRadioQry1.setText(_translate("MainWindow", "TR", None)) self.BtnRadioQry2.setText(_translate("MainWindow", "FID", None)) self.BtnRadioQry3.setText(_translate("MainWindow", "주문", None)) self.BtnRadioQry1.setChecked(True) self.Btn_ReqJMCodeFR.setText(_translate("MainWindow", "해외종목코드 수신", None)) self.label_11.setText(_translate("MainWindow", "실시간", None)) self.BtnRadioSiseReal.setText(_translate("MainWindow", "시세", None)) self.BtnRadioOrderReal.setText(_translate("MainWindow", "주문", None)) self.BtnRadioSiseReal.setChecked(True) self.BtnRadioRealRegister.setText(_translate("MainWindow", "등록", None)) self.BtnRadioRealUnRegister.setText(_translate("MainWindow", "해지", None)) self.BtnRadioRealRegister.setChecked(True) self.label_12.setText(_translate("MainWindow", "실시간", None)) self.BTN_Query_Real.setText(_translate("MainWindow", "등록/해지", None)) self.Edit_UserID.setText(u"sivas99") self.Edit_UserPW.setText(u"qwe123") self.Edit_AcctPW.setText(u"1234") self.SetTrToDictionary_FO() self.SetTrToDictionary_FR() self.SetTrToDictionary_FX() self.SetRealToDictionary_FO() self.SetRealToDictionary_FR() self.SetRealToDictionary_FX() self.OnRadioTrChange() self.SetComboReal() pass def SetTrToDictionary_FO(self): self.m_TrQueryListFO.update({u"01.국내미체결주문조회" :[u"g11002.DQ0104&",u"계좌번호,11,딜러번호,3,계좌비번,8"]}) self.m_TrQueryListFO.update({u"02.국내체결내역리스트" :[u"g11002.DQ0107&",u"계좌번호,11,딜러번호,3,계좌비번,8"]}) self.m_TrQueryListFO.update({u"03.국내미결제약정조회" :[u"g11002.DQ0110&",u"계좌번호,11,딜러번호,3,계좌비번,8"]}) self.m_TrQueryListFO.update({u"04.국내고객예탁금조회" :[u"g11002.DQ0242&",u"계좌번호,11,계좌비번,8" ]}) self.m_TrQueryListFO.update({u"05.국내종목명조회" :[u"g11002.DQ0622&",u"exchtp,1,exchid,2,fotp,1"]}) self.m_TrQueryListFO.update({u"06.야간CME미체결주문조회":[u"g11002.DQ0116&",u"계좌번호,11,딜러번호,3,계좌비번,8"]}) self.m_TrQueryListFO.update({u"07.야간CME체결내역리스트":[u"g11002.DQ0119&",u"계좌번호,11,딜러번호,3,계좌비번,8"]}) self.m_TrQueryListFO.update({u"08.야간CME미결제약정조회":[u"g11002.DQ0122&",u"계좌번호,11,딜러번호,3,계좌비번,8"]}) self.m_FidQueryListFO.update({u"국내선물옵션마스터" :[u"s20001",u"종목,8,조회모드,1,조회건수,4",u"000075051057"]}) self.m_FidQueryListFO.update({u"국내주식선물마스터" :[u"s30001",u"종목,8,조회모드,1,조회건수,4",u"000075051057"]}) self.m_FidQueryListFO.update({u"야간CME선물옵션마스터" :[u"s21001",u"종목,8,조회모드,1,조회건수,4",u"000075051057"]}) self.m_TrOrderListFO.update({u"01.국내신규주문" :[u"g12001.DO1601&",u"계좌번호,11,계좌비번,8,종목,32,매매구분,1,체결구분,1,체결조건,1,주문가격,13,주문수량,5"]}) self.m_TrOrderListFO.update({u"02.국내정정주문" :[u"g12001.DO1901&",u"계좌번호,11,계좌비번,8,종목,32,매매구분,1,체결구분,1,체결조건,1,주문가격,13,주문수량,5,주문번호,7"]}) self.m_TrOrderListFO.update({u"03.국내취소주문" :[u"g12001.DO1701&",u"계좌번호,11,계좌비번,8,종목,32,매매구분,1,체결구분,1,체결조건,1,주문가격,13,주문수량,5,주문번호,7"]}) self.m_TrOrderListFO.update({u"04.CME국내신규주문" :[u"g12001.DO2201&",u"계좌번호,11,계좌비번,8,종목,32,매매구분,1,체결구분,1,체결조건,1,주문가격,13,주문수량,5"]}) self.m_TrOrderListFO.update({u"05.CME국내정정주문" :[u"g12001.DO2101&",u"계좌번호,11,계좌비번,8,종목,32,매매구분,1,체결구분,1,체결조건,1,주문가격,13,주문수량,5,주문번호,7"]}) self.m_TrOrderListFO.update({u"06.CME국내취소주문" :[u"g12001.DO2001&",u"계좌번호,11,계좌비번,8,종목,32,매매구분,1,체결구분,1,체결조건,1,주문가격,13,주문수량,5,주문번호,7"]}) pass def SetTrToDictionary_FR(self): self.m_TrQueryListFR.update({u"01.해외미체결주문내역" :[u"g11004.AQ0401%",u"조회유형,1,사용자ID,8,계좌번호,6,계좌비번,8"]}) self.m_TrQueryListFR.update({u"02.해외체결주문내역" :[u"g11004.AQ0402%",u"조회유형,1,사용자ID,8,계좌번호,6,계좌비번,8"]}) self.m_TrQueryListFR.update({u"03.해외미결제주문내역" :[u"g11004.AQ0403%",u"조회유형,1,사용자ID,8,계좌번호,6,계좌비번,8"]}) self.m_TrQueryListFR.update({u"04.해외예탁자산조회" :[u"g11004.AQ0607%",u"조회유형,1,사용자ID,8,계좌번호,6,계좌비번,8,groupnm,20,통화코드,3"]}) self.m_TrQueryListFR.update({u"05.해외일주월분틱" :[u"o44005",u"keyvalue,18,코드,32,조회일자,8,조회시간,10,다음구분,1,데이터구분,1,시간구분,3,데이터건수,5,장구분,1,허봉실봉구분,1"]}) self.m_FidQueryListFR.update({u"01.해외선물옵션마스터" :[u"o51000",u"종목,32", u"000001002003004005006007008009010011012013014015016017018019020021022023024025026027028029030031032033034035036037"]}) self.m_FidQueryListFR.update({u"02.해외호가정보" :[u"o51010",u"종목,32", u"000001002003004005006007"]}) self.m_FidQueryListFR.update({u"03.해외종목정보" :[u"o51210",u"종목,32", u"000001002003004005006007008009010011012013014015016017018019020021"]}) self.m_TrOrderListFR.update({u"01.해외신규주문" :[u"g12003.AO0401%",u"계좌번호,6,계좌비번,8,종목,32,매매구분,1,체결구분,1,체결조건,1,주문가격,15,주문수량,10,strtp,1,stopp,15,minqty,10"]}) self.m_TrOrderListFR.update({u"02.해외정정주문" :[u"g12003.AO0402%",u"계좌번호,6,계좌비번,8,종목,32,매매구분,1,체결구분,1,체결조건,1,주문가격,15,주문수량,10,주문번호,10,strtp,1,stopp,15,minqty,10"]}) self.m_TrOrderListFR.update({u"03.해외취소주문" :[u"g12003.AO0403%",u"계좌번호,6,계좌비번,8,종목,32,체결구분,1,체결조건,1,주문가격,15,주문수량,10,주문번호,10"]}) pass def SetTrToDictionary_FX(self): self.m_TrQueryListFX.update({u"01.FX자산내역조회" :[u"g11004.AQ0901%",u"조회유형,1,사용자ID,8,계좌번호,6,계좌비번,8"]}) self.m_TrQueryListFX.update({u"02.FX미체결내역조회" :[u"g11004.AQ0904%",u"조회유형,1,사용자ID,8,계좌번호,6,계좌비번,8"]}) self.m_TrQueryListFX.update({u"03.FX계좌정보Summary" :[u"g11004.AQ906%",u"조회유형,1,사용자ID,8,계좌번호,6,계좌비번,8"]}) self.m_TrQueryListFX.update({u"04.FX미청산포지션조회" :[u"g11004.AQ0908%",u"조회유형,1,사용자ID,8,계좌번호,6,계좌비번,8"]}) self.m_TrQueryListFX.update({u"05.FX청산포지션조회" :[u"g11004.AQ0910%",u"조회유형,1,사용자ID,8,계좌번호,6,계좌비번,8,groupnm,20,시작일자,8,종료일자,8"]}) self.m_FidQueryListFX.update({u"01.FX마스터" :[u"x00001",u"종목,10", u"000001002003004005006007008009010011012013014015016017018019020021022"]}) self.m_TrOrderListFX.update({u"01.FX신규주문" :[u"g12003.AO0501%",u"계좌번호,6,계좌비번,8,종목,32,매매구분,1,주문가격,20,주문수량,15,ordertr,10,체결구분,1,strtp,1,stopp,20,limitp,20,mrktrange,5,trailingstop,10,trdno,20,trdseq,5"]}) self.m_TrOrderListFX.update({u"02.FX정정주문" :[u"g12003.AO0502%",u"계좌번호,6,계좌비번,8,종목,32,주문번호,20,주문SEQ,15,주문가격,15,주문수량,10,ordertr,10,strtp,1,stopp,15,limitp,20,trailingstop,10"]}) self.m_TrOrderListFX.update({u"03.FX취소주문" :[u"g12003.AO0503%",u"계좌번호,6,계좌비번,8,종목,32,주문번호,20"]}) pass def SetRealToDictionary_FO(self): self.m_RealSiseListFO.update({u"01.국내선물호가" :[self.CONST_FO_SISE_51,u"종목"]}) self.m_RealSiseListFO.update({u"02.국내선물체결" :[self.CONST_FO_SISE_65,u"종목"]}) self.m_RealSiseListFO.update({u"03.국내옵션호가" :["52",u"종목"]}) self.m_RealSiseListFO.update({u"04.국내옵션체결" :["66",u"종목"]}) self.m_RealSiseListFO.update({u"05.국내상품선물호가" :[self.CONST_FO_SISE_58,u"종목"]}) self.m_RealSiseListFO.update({u"06.국내상품선물체결" :[self.CONST_FO_SISE_71,u"종목"]}) self.m_RealSiseListFO.update({u"07.국내상품옵션호가" :[u"59",u"종목"]}) self.m_RealSiseListFO.update({u"08.국내상품옵션체결" :[u"73",u"종목"]}) self.m_RealSiseListFO.update({u"09.국내CME선물호가" :[u"75",u"종목"]}) self.m_RealSiseListFO.update({u"10.국내CME선물체결" :[u"77",u"종목"]}) self.m_RealSiseListFO.update({u"11.국내주식선물호가" :[u"56",u"종목"]}) self.m_RealSiseListFO.update({u"12.국내주식선물체결" :[u"68",u"종목"]}) self.m_RealOrderListFO.update({u"01.국내주문실시간접수" :[self.CONST_FO_ORDER_181,u"계좌번호"]}) self.m_RealOrderListFO.update({u"02.국내주문실시간미체결" :[self.CONST_FO_ORDER_182,u"계좌번호"]}) self.m_RealOrderListFO.update({u"03.국내주문실시간미결제" :[self.CONST_FO_ORDER_183,u"계좌번호"]}) self.m_RealOrderListFO.update({u"04.국내주문실시간잔고" :[self.CONST_FO_ORDER_184,u"계좌번호"]}) self.m_RealOrderListFO.update({u"05.국내주문실시간체결" :[self.CONST_FO_ORDER_185,u"계좌번호"]}) pass def SetRealToDictionary_FR(self): self.m_RealSiseListFR.update({u"01.해외선물호가" :[self.CONST_FR_SISE_76,u"종목"]}) self.m_RealSiseListFR.update({u"02.해외선물체결" :[self.CONST_FR_SISE_82,u"종목"]}) self.m_RealOrderListFR.update({u"01.해외주문실시간접수" :[self.CONST_FR_ORDER_196,u"계좌번호"]}) self.m_RealOrderListFR.update({u"02.해외주문실시간미체결" :[self.CONST_FR_ORDER_186,u"계좌번호"]}) self.m_RealOrderListFR.update({u"03.해외주문실시간미결제" :[self.CONST_FR_ORDER_187,u"계좌번호"]}) self.m_RealOrderListFR.update({u"04.해외주문실시간잔고" :[self.CONST_FR_ORDER_188,u"계좌번호"]}) self.m_RealOrderListFR.update({u"05.해외주문실시간체결" :[self.CONST_FR_ORDER_189,u"계좌번호"]}) pass def SetRealToDictionary_FX(self): self.m_RealSiseListFX.update({u"01.FX체결" :[self.CONST_FX_SISE_171,u"종목"]}) self.m_RealOrderListFX.update({u"01.FX주문실시간접수" :[u"197",u"계좌번호"]}) self.m_RealOrderListFX.update({u"02.FX주문실시간미체결" :[u"191",u"계좌번호"]}) self.m_RealOrderListFX.update({u"03.FX주문실시간미청산" :[u"192",u"계좌번호"]}) self.m_RealOrderListFX.update({u"04.FX주문실시간청산" :[u"193",u"계좌번호"]}) self.m_RealOrderListFX.update({u"05.FX주문실시간자산" :[u"194",u"계좌번호"]}) self.m_RealOrderListFX.update({u"06.FX주문실시간요약" :[u"195",u"계좌번호"]}) pass def Util_WriteLog(self, strMsg): now = time.localtime(time.time()) strHead = time.strftime("[%H:%M:%S]", now) self.multiline.insertPlainText( strHead + strMsg + "\n") self.multiline.moveCursor(QTextCursor.End) def Util_GetCurDate(self): now = time.localtime(time.time()) strDate = time.strftime("%Y%m%d", now) return strDate def Util_FillStr(self, strSrc, nTotLen, chPad): nPadLen = nTotLen - len(strSrc) strPad = strSrc + chPad * nPadLen return strPad def OnConnect(self): self.Util_WriteLog("Connect") ret = self.HDF.dynamicCall("CommInit(1)") def OnDisConnect(self): self.OnLogout() self.HDF.dynamicCall("CommTerminate(1)") def OnLogin(self): self.Util_WriteLog("Login") strUserID = self.Edit_UserID.text() strUserPW = self.Edit_UserPW.text() strCertPW = self.Edit_CertPW.text() nRet = self.HD_Login(strUserID, strUserPW, strCertPW) pass def OnLogout(self): self.Util_WriteLog("Logout") strUserID = self.Edit_UserID.text() self.HD_Logout(strUserID) pass def OnReqJmCodeFr(self): self.Util_WriteLog("해외종목요청") self.HD_CommReqMakeCod() pass def GetAccOrTrDic(self, strQryTp): tmpList = [] tmpAccDic = {} tmpTrDic = {} tmpFidDic = {} if ( self.BtnRadio1.isChecked() == True ): #국내 tmpAccDic = self.m_AccListFO if ( self.BtnRadioQry1.isChecked() == True ): #TR조회 tmpTrDic = self.m_TrQueryListFO elif ( self.BtnRadioQry2.isChecked() == True ): #FID조회 tmpTrDic = self.m_FidQueryListFO elif ( self.BtnRadioQry3.isChecked() == True ): #주문 tmpTrDic = self.m_TrOrderListFO elif ( self.BtnRadio2.isChecked() == True ): #해외 tmpAccDic = self.m_AccListFR if ( self.BtnRadioQry1.isChecked() == True ): #TR조회 tmpTrDic = self.m_TrQueryListFR elif ( self.BtnRadioQry2.isChecked() == True ): #FID조회 tmpTrDic = self.m_FidQueryListFR elif ( self.BtnRadioQry3.isChecked() == True ): #주문 tmpTrDic = self.m_TrOrderListFR elif ( self.BtnRadio3.isChecked() == True ): #FX tmpAccDic = self.m_AccListFX if ( self.BtnRadioQry1.isChecked() == True ): #TR조회 tmpTrDic = self.m_TrQueryListFX elif ( self.BtnRadioQry2.isChecked() == True ): #FID조회 tmpTrDic = self.m_FidQueryListFX elif ( self.BtnRadioQry3.isChecked() == True ): #주문 tmpTrDic = self.m_TrOrderListFX if ( strQryTp == "ACC"): return tmpAccDic elif (strQryTp == "TR"): return tmpTrDic pass pass def GetRealDic(self): tmpRealDic = {} if ( self.BtnRadio1.isChecked() == True ): # 국내 if ( self.BtnRadioSiseReal.isChecked() == True ): # 시세 로드 tmpRealDic = self.m_RealSiseListFO else: #주문 로드 tmpRealDic = self.m_RealOrderListFO pass elif ( self.BtnRadio2.isChecked() == True ): if ( self.BtnRadioSiseReal.isChecked() == True ): # 시세 로드 tmpRealDic = self.m_RealSiseListFR else: #주문 로드 tmpRealDic = self.m_RealOrderListFR pass elif ( self.BtnRadio3.isChecked() == True ): if ( self.BtnRadioSiseReal.isChecked() == True ): # 시세 로드 tmpRealDic = self.m_RealSiseListFX else: #주문 로드 tmpRealDic = self.m_RealOrderListFX pass return tmpRealDic pass def OnRadioAcctTpChange(self): self.ComboAcc.clear() tmpAccDic = self.GetAccOrTrDic("ACC") tmpList = list(tmpAccDic.keys()) for i in range(len(tmpList)): strAcctNo = tmpList[i] self.ComboAcc.addItem(strAcctNo) pass self.OnRadioTrChange() self.OnRadioRealChange() pass def OnRadioTrChange(self): self.ComboTr.clear() tmpTrDic = self.GetAccOrTrDic("TR") tmpList = list(tmpTrDic.keys()) for i in range(len(tmpList)): strServiceNm = tmpList[i] self.ComboTr.addItem(strServiceNm) self.ComboTr.model().sort(0) bShow = False if ( self.BtnRadioQry2.isChecked() == True ): bShow = True self.Edit_Input_FID.setVisible(bShow) self.m_bUseComboTrChange = True pass def OnComboAccChange(self, strSelData): strInData = unicode(strSelData, 'utf-8') tmpAccDic = self.GetAccOrTrDic("ACC") strAcctNm = tmpAccDic.get(strInData) self.label_acctNm.setText(_fromUtf8(strAcctNm)) self.OnComboTrChange(self.ComboTr.currentText()) pass def OnComboTrChange(self, strSelData): strInData = unicode(strSelData, 'utf-8') tmpList = [] tmpTrDic = {} tmpTrDic = self.GetAccOrTrDic("TR") tmpList = tmpTrDic.get(strInData) if ( tmpList is None ): return None strTrCode = tmpList[0] self.label_tr.setText(strTrCode) #data parsing strData = str(tmpList[1]) commaArr = strData.split(",") strInput = "" self.Edit_Input.setText(strInput) for strItem in commaArr: if ( strItem == "계좌번호" ): strAcctNo = self.ComboAcc.currentText() strAcctNo = str(strAcctNo).strip() if ( self.BtnRadio1.isChecked() == True ): #국내 strInput += self.Util_FillStr(strAcctNo, 11, ' ') else: strInput += self.Util_FillStr(strAcctNo, 6, ' ') elif ( strItem == "계좌비번" ): strInput += self.Util_FillStr(self.Edit_AcctPW.text(), 8, ' ') elif ( strItem == "딜러번호" ): strInput += self.Util_FillStr("001", 3, ' ') #무조건 "001" elif ( strItem == "조회일자" or strItem == "시작일자" or strItem == "종료일자"): strInput += self.Util_FillStr(self.Util_GetCurDate(), 8, ' ') elif ( strItem == "exchtp" ): strInput += self.Util_FillStr("1", 1, ' ') #1:KRX elif ( strItem == "exchid" ): strInput += self.Util_FillStr("01", 2, ' ') #종목명의 2,3번째자리 ex)101FC000 -> 01 elif ( strItem == "fotp" ): strInput += self.Util_FillStr("F", 1, ' ') #F:선물, O:옵션 elif ( strItem == "종목" ): if ( self.BtnRadio1.isChecked() == True ): #국내 if ( self.BtnRadioQry2.isChecked() == True ): strInput += self.Util_FillStr(self.CONST_FO_SERIES, 8, ' ') #F:선물, O:옵션 else: strInput += self.Util_FillStr(self.CONST_FO_SERIES, 32, ' ') #F:선물, O:옵션 elif ( self.BtnRadio2.isChecked() == True ): strInput += self.Util_FillStr(self.CONST_FR_SERIES, 32, ' ') elif ( self.BtnRadio3.isChecked() == True ): strInput += self.Util_FillStr(self.CONST_FX_SERIES, 32, ' ') elif ( strItem == "매매구분" ): strInput += self.Util_FillStr("1", 1, ' ') #1:매수, 2:매도 elif ( strItem == "체결구분" ): strInput += self.Util_FillStr("1", 1, ' ') #1:지정가, 2:시장가 elif ( strItem == "체결조건" ): if ( self.BtnRadio1.isChecked() == True ): #국내 strInput += self.Util_FillStr("1", 1, ' ') #1:FAS, 2:FOK, 3:FAK else: strInput += self.Util_FillStr("1", 1, ' ') #0:DAY, 1:GTC, 3:IOC FAK 4:FOK elif ( strItem == "주문가격" ): if ( self.BtnRadio1.isChecked() == True ): #국내 strInput += self.Util_FillStr("23055", 13, ' ') #주문가격, 소수점 없음 else: strInput += self.Util_FillStr("8808", 15, ' ') #주문가격, 소수점 없음 elif ( strItem == "주문수량" ): strInput += self.Util_FillStr("1", 5, ' ') #주문수량 elif ( strItem == "주문번호" ): if ( self.BtnRadio1.isChecked() == True ): #국내 strInput += self.Util_FillStr("1111111", 7, ' ') else: strInput += self.Util_FillStr("0000000000", 10, ' ') elif ( strItem == "사용자ID" ): strInput += self.Util_FillStr(self.Edit_UserID.text(), 8, ' ') elif ( strItem == "조회유형" ): #무조건 1 strInput += self.Util_FillStr("1", 1, ' ') elif ( strItem == "groupnm" ): strInput += self.Util_FillStr(" ", 20, ' ') elif ( strItem == "통화코드" ): strInput += self.Util_FillStr("USD", 3, ' ') #USD(미국달러),EUR(유로화),JPY(일본엔화),KRW(한국원화) elif ( strItem == "부서코드" ): strInput += self.Util_FillStr("001", 3, ' ') elif ( strItem == "적요구분" ): strInput += self.Util_FillStr("1", 1, ' ') # 0(전체), 1(손익), 2(이자), 3(수수료), 4(입금), 5(출금), 6(기타) elif ( strItem == "조회모드" ): strInput += self.Util_FillStr("3", 1, ' ') #(1:LT 2:LE 3:EQ 4:GE 5:GT) elif ( strItem == "조회건수" ): strInput += self.Util_FillStr("0001", 4, ' ') elif ( strItem == "keyvalue"): strInput += self.Util_FillStr(" ", 18, ' ') elif ( strItem == "조회시간"): strInput += self.Util_FillStr("9999999999", 10, ' ') elif ( strItem == "다음구분"): strInput += self.Util_FillStr("0", 1, ' ') # 0:기본 elif ( strItem == "데이터구분"): strInput += self.Util_FillStr("1", 1, ' ') # 3:일, 4:주, 5:월, 2:분, 6:틱 elif ( strItem == "시간구분"): strInput += self.Util_FillStr("001", 3, ' ') # N분/틱 elif ( strItem == "데이터건수"): strInput += self.Util_FillStr("00010", 5, ' ') # 조회요청개수 elif ( strItem == "장구분"): strInput += self.Util_FillStr("1", 1, ' ') # 1:전산장, 0:본장 elif ( strItem == "허봉실봉구분"): strInput += self.Util_FillStr("0", 1, ' ') # 0:실봉만, 1:허봉+실봉 else: try: nFieldLen = int(strItem) if ( type(nFieldLen) is int ): #입력필드 길이 이므로 pass pass else: self.Util_WriteLog("UnKnown FieldNm : " + strItem) except ValueError: pass self.Edit_Input.setText( "[" + strInput + "]") if ( self.BtnRadioQry2.isChecked() == True ): strFidInput = str(tmpList[2]) self.Edit_Input_FID.setText("[" + strFidInput + "]") pass def OnQuery(self): strTr = self.label_tr.text() strInput = self.Edit_Input.text() strInput.replace("[", "") strInput.replace("]", "") strInputFid = self.Edit_Input_FID.text() strInputFid.replace("[", "") strInputFid.replace("]", "") nRqID = 0 strMsg = "" if ( self.BtnRadioQry3.isChecked() == True ): nRqID = self.HD_CommJumunSvr(strTr, strInput) strMsg = u"주문전송 UniqueID : " + str(nRqID) elif ( self.BtnRadioQry2.isChecked() == True ): nRqID = self.HD_CommFIDRqData(strTr, strInput, strInputFid, "") strMsg = u"조회요청(FID) UniqueID : " + str(nRqID) else: nRqID = self.HD_CommRqData(strTr, strInput, len(strInput), u"") strMsg = u"조회요청(TR) UniqueID : " + str(nRqID) self.Util_WriteLog( strMsg ) pass def OnRadioRealChange(self): self.ComboReal.clear() self.SetComboReal() strSelData = self.ComboReal.currentText() self.OnComboReal(strSelData) pass def SetComboReal(self): tmpRealDic = {} tmpRealDic = self.GetRealDic() tmpList = [] tmpList = list(tmpRealDic.keys()) for i in range(len(tmpList)): strRealServNo = tmpList[i] self.ComboReal.addItem(strRealServNo) self.ComboReal.model().sort(0) pass def OnComboReal(self, strSelData): strInData = unicode(strSelData, 'utf-8') tmpList = [] tmpRealDic = {} tmpRealDic = self.GetRealDic() tmpList = tmpRealDic.get(strInData) strInput = "" try: strItem = tmpList[0] self.Edit_Input_Real_Key.setText(tmpList[0]) strItem = tmpList[1] if ( strItem == "종목" ): if ( self.BtnRadio1.isChecked() == True ): strInput = self.Util_FillStr(self.CONST_FO_SERIES, 32, ' ') elif ( self.BtnRadio2.isChecked() == True ): strInput += self.Util_FillStr(self.CONST_FR_SERIES, 32, ' ') elif ( self.BtnRadio3.isChecked() == True ): strInput += self.Util_FillStr(self.CONST_FX_SERIES, 10, ' ') pass elif (strItem == "계좌번호" ): strAcctNo = self.ComboAcc.currentText() strInput = self.Util_FillStr(strAcctNo, 11, ' ') pass except TypeError: pass self.Edit_Input_Real_Val.setText( "[" + strInput + "]" ) pass def OnRealRegister(self): bReg = True strMsg = "" strValue = self.Edit_Input_Real_Val.text() nKeyType = int(self.Edit_Input_Real_Key.text()) strValue.replace("[", "") strValue.replace("]", "") if ( self.BtnRadioRealRegister.isChecked() == True ): bReg = True strMsg = u"실시간 등록 요청 Value[%s] Key[%d]" %(strValue, nKeyType) elif ( self.BtnRadioRealUnRegister.isChecked() == True ): bReg = False strMsg = u"실시간 해지 요청 Value[%s] Key[%d]" %(strValue, nKeyType) self.Util_WriteLog( strMsg ) self.HD_RegReal(bReg, strValue, nKeyType) pass def OnDataRecv(self, sTrCode, nRqID): strRecv = u"조회응답 Tr = [%s] UniqueID = [%d]" %(sTrCode, nRqID) self.Util_WriteLog( strRecv ) i = 0 if ( sTrCode == "o44020"): #MRKT.cod pass elif ( sTrCode == "o44021"): #PMCode.cod pass elif ( sTrCode == "o44022" ): #JMCode.cod(해외) nRptCnt = self.HD_CommGetRepeatCnt(sTrCode, -1, u"OutRec1") self.Util_WriteLog( u"수신개수 : " + str(nRptCnt)) for i in nRptCnt: strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"종목코드") self.Util_WriteLog(strData) pass elif (sTrCode == "g11002.DQ0104&" ): #국내미체결조회 self.procDQ0104(sTrCode) pass elif (sTrCode == "g11002.DQ0107&" ): #국내체결조회 self.procDQ0107(sTrCode) pass elif (sTrCode == "g11002.DQ0110&" ): #국내미체결조회 self.procDQ0110(sTrCode) pass elif (sTrCode == "g11002.DQ0242&" ): #국내고객예탁금조회 self.procDQ0242(sTrCode) pass elif sTrCode == "g11002.DQ0622&":#종목코드(국내) nRptCnt = self.HD_CommGetRepeatCnt(sTrCode, -1, u"OutRec1") for i in nRptCnt: strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"종목코드") self.Util_WriteLog(strData) pass elif (sTrCode == "g11002.DQ0116&"): pass elif (sTrCode == "g11002.DQ0119&"): #야간CME체결내역리스트 pass elif (sTrCode == "g11002.DQ0122&"): #야간CME미결제약정조회 pass elif (sTrCode == "s20001" ): #국내선물옵션마스터 self.procs20001(sTrCode) pass elif (sTrCode == "s30001" ): #국내주식선물마스터 pass elif (sTrCode == "s21001" ): #야간CME선물옵션마스터 pass elif (sTrCode == "g12001.DO1601&" ): #국내신규주문 self.procDO1000(sTrCode) pass elif (sTrCode == "g12001.DO1901&" ): #국내정정주문 self.procDO1000(sTrCode) pass elif (sTrCode == "g12001.DO1701&" ): #국내취소주문 self.procDO1000(sTrCode) pass elif (sTrCode == "g12001.DO2201&" ): #CME국내신규주문 self.procDO2000(sTrCode) pass elif (sTrCode == "g12001.DO2101&" ): #CME국내정정주문 self.procDO2000(sTrCode) pass elif (sTrCode == "g12001.DO2001&" ): #CME국내취소주문 self.procDO2000(sTrCode) pass elif (sTrCode == "g11004.AQ0401%"): #해외미체결주문내역 self.procAQ0401(sTrCode) pass elif (sTrCode == "g11004.AQ0402%"): #해외미체결주문내역 self.procAQ0402(sTrCode) pass elif (sTrCode == "g11004.AQ0403%"): self.procAQ0403(sTrCode) pass elif (sTrCode == "g11004.AQ0607%"): self.procAQ0607(sTrCode) pass elif (sTrCode == "o51000" ): #해외체결정보 self.proco51000(sTrCode) pass elif (sTrCode == "o51010" ): #해외호가정보 self.proco51010(sTrCode) pass elif (sTrCode == "o51210" ): #해외종목정보 self.proco51210(sTrCode) pass elif (sTrCode == "g12003.AO0401" ): #해외신규주문 self.procAO0400(sTrCode) pass elif (sTrCode == "g12003.AO0402" ): #해외정정주문 self.procAO0400(sTrCode) pass elif (sTrCode == "g12003.AO0403" ): #해외취소주문 self.procAO0400(sTrCode) pass elif sTrCode == "g11004.AQ0101%": #ㅖ좌목록 수신 self.Util_WriteLog(u"Recv Account List") self.procAQ0101(sTrCode) pass elif sTrCode == "g11004.AQ0450%": #해외미체결주문내역 self.procAQ0450(sTrCode) pass def OnGetBroadData(self, sTrCode, nRealType): strRealType = unicode(str(nRealType), 'utf-8') self.Util_WriteLog (u"실시간 수신 [%s] [%s]" % (sTrCode, strRealType)) if ( strRealType == self.CONST_FO_SISE_51 ): self.procReal51(sTrCode, nRealType) pass elif ( strRealType == self.CONST_FO_SISE_65 ): self.procReal65(sTrCode, nRealType) pass elif ( strRealType == self.CONST_FO_SISE_58 ): self.procReal58(sTrCode, nRealType) pass elif ( strRealType == self.CONST_FO_SISE_71 ): self.procReal71(sTrCode, nRealType) pass elif ( strRealType == self.CONST_FO_ORDER_181 ): self.procReal181(sTrCode, nRealType) pass elif ( strRealType == self.CONST_FO_ORDER_182 ): self.procReal182(sTrCode, nRealType) pass elif ( strRealType == self.CONST_FO_ORDER_183 ): self.procReal183(sTrCode, nRealType) pass elif ( strRealType == self.CONST_FO_ORDER_184 ): self.procReal184(sTrCode, nRealType) pass elif ( strRealType == self.CONST_FO_ORDER_185 ): self.procReal185(sTrCode, nRealType) pass elif ( strRealType == self.CONST_FR_SISE_76 ): self.procReal76(sTrCode, nRealType) pass elif ( strRealType == self.CONST_FR_SISE_82 ): # 해외 시세 체결 strCode = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목코드") strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"기준체결시간") strPric = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결가") self.Util_WriteLog("[" + strCode + "][" + strData + "][" + strPric + "]") pass elif (strRealType == self.CONST_FR_ORDER_196 ): self.procReal196(sTrCode, nRealType) pass elif (strRealType == self.CONST_FR_ORDER_186 ): self.procReal186(sTrCode, nRealType) pass elif (strRealType == self.CONST_FR_ORDER_187 ): self.procReal187(sTrCode, nRealType) pass elif (strRealType == self.CONST_FR_ORDER_188 ): self.procReal188(sTrCode, nRealType) pass elif (strRealType == self.CONST_FR_ORDER_189 ): self.procReal189(sTrCode, nRealType) pass elif (strRealType == self.CONST_FX_SISE_171): self.procReal171(sTrCode, nRealType) pass pass def procReal171(self, sTrCode, nRealType): strTime = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"호가시간 ") strBid = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매수호가 ") strData = strTime + " " + strBid self.Util_WriteLog(strData) pass def procReal189(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문번호 ") self.Util_WriteLog(u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌번호 ") self.Util_WriteLog(u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌명 ") self.Util_WriteLog(u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목 ") self.Util_WriteLog(u"종목 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매매구분 ") self.Util_WriteLog(u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문가격 ") self.Util_WriteLog(u"주문가격 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문수량 ") self.Util_WriteLog(u"주문수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결가격 ") self.Util_WriteLog(u"체결가격 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결수량 ") self.Util_WriteLog(u"체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"STOP가격 ") self.Util_WriteLog(u"STOP가격 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"약정금액 ") self.Util_WriteLog(u"약정금액 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문유형 ") self.Util_WriteLog(u"주문유형 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"수수료 ") self.Util_WriteLog(u"수수료 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문일자 ") self.Util_WriteLog(u"주문일자 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문시간 ") self.Util_WriteLog(u"주문시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문자 ") self.Util_WriteLog(u"주문자 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결일자 ") self.Util_WriteLog(u"체결일자 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결시간 ") self.Util_WriteLog(u"체결시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"거래소일자 ") self.Util_WriteLog(u"거래소일자 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"거래소시간 ") self.Util_WriteLog(u"거래소시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"통화코드 ") self.Util_WriteLog(u"통화코드 : " + strData) pass def procReal188(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌번호 ") self.Util_WriteLog(u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌명 ") self.Util_WriteLog(u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문가능금액") self.Util_WriteLog(u"주문가능금액: " + strData) pass def procReal187(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌번호 ") self.Util_WriteLog(u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌명 ") self.Util_WriteLog(u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목 ") self.Util_WriteLog(u"종목 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매매구분 ") self.Util_WriteLog(u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"평균단가 ") self.Util_WriteLog(u"평균단가 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"당일미결제수량 ") self.Util_WriteLog(u"당일미결제수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"미결제약정금액 ") self.Util_WriteLog(u"미결제약정금액 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"신규체결수량 ") self.Util_WriteLog(u"신규체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"신규체결금액 ") self.Util_WriteLog(u"신규체결금액 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"전환매체결수량 ") self.Util_WriteLog(u"전환매체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"전환매체결금액 ") self.Util_WriteLog(u"전환매체결금액 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"전환매Hold수량 ") self.Util_WriteLog(u"전환매Hold수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"수동청산Hold수량 ") self.Util_WriteLog(u"수동청산Hold수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"위탁증거금 ") self.Util_WriteLog(u"위탁증거금 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"통화코드 ") self.Util_WriteLog(u"통화코드 : " + strData) pass def procReal186(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌번호 ") self.Util_WriteLog(u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌명 ") self.Util_WriteLog(u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"기준일자 ") self.Util_WriteLog(u"기준일자 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문번호 ") self.Util_WriteLog(u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목 ") self.Util_WriteLog(u"종목 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매매구분 ") self.Util_WriteLog(u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문가격 ") self.Util_WriteLog(u"주문가격 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문수량 ") self.Util_WriteLog(u"주문수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결수량 ") self.Util_WriteLog(u"체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"잔량 ") self.Util_WriteLog(u"잔량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"STOP 가격 ") self.Util_WriteLog(u"STOP 가격 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문시간 ") self.Util_WriteLog(u"주문시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"거래소시간 ") self.Util_WriteLog(u"거래소시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문자 ") self.Util_WriteLog(u"주문자 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문구분 ") self.Util_WriteLog(u"주문구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"전략구분 ") self.Util_WriteLog(u"전략구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"최초원주문번호 ") self.Util_WriteLog(u"최초원주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"그룹주문번호 ") self.Util_WriteLog(u"그룹주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매수주문수량 ") self.Util_WriteLog(u"매수주문수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매도주문수량 ") self.Util_WriteLog(u"매도주문수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문유형 ") self.Util_WriteLog(u"주문유형 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"가격조건 ") self.Util_WriteLog(u"가격조건 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결조건 ") self.Util_WriteLog(u"체결조건 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"GTD일자 ") self.Util_WriteLog(u"GTD일자 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"IOC최소체결수량 ") self.Util_WriteLog(u"IOC최소체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"원주문번호 ") self.Util_WriteLog(u"원주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문순서 ") self.Util_WriteLog(u"주문순서 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"통화코드 ") self.Util_WriteLog(u"통화코드 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문금액 ") self.Util_WriteLog(u"주문금액 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문시작일자 ") self.Util_WriteLog(u"주문시작일자 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"옵션행사예약여부 ") self.Util_WriteLog(u"옵션행사예약여부 : " + strData) pass def procReal196(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문번호") self.Util_WriteLog(u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목코드") self.Util_WriteLog(u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문가격") self.Util_WriteLog(u"주문가격 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문수량") self.Util_WriteLog(u"주문수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매매구분") self.Util_WriteLog(u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문시간") self.Util_WriteLog(u"주문시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문구분") self.Util_WriteLog(u"주문구분(1:신규, 2:정정, 3:취소) : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"처리구분") self.Util_WriteLog(u"처리구분(0:정상, 1:거부) : " + strData) pass def procReal181(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문번호") self.Util_WriteLog(u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목코드") self.Util_WriteLog(u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문가격") self.Util_WriteLog(u"주문가격 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문수량") self.Util_WriteLog(u"주문수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매매구분") self.Util_WriteLog(u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"접수시간") self.Util_WriteLog(u"접수시간 : " + strData) pass def procReal182(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"key") self.Util_WriteLog(u"key : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌번호") self.Util_WriteLog(u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"딜러번호") self.Util_WriteLog(u"딜러번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌명") self.Util_WriteLog(u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"딜러명") self.Util_WriteLog(u"딜러명 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문번호") self.Util_WriteLog(u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목코드") self.Util_WriteLog(u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매매구분") self.Util_WriteLog(u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문가격") self.Util_WriteLog(u"주문가격 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문수량") self.Util_WriteLog(u"주문수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"정정수량") self.Util_WriteLog(u"정정수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"취소수량") self.Util_WriteLog(u"취소수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결수량") self.Util_WriteLog(u"체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"잔량") self.Util_WriteLog(u"잔량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"원주문번호") self.Util_WriteLog(u"원주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"최초원주문번호") self.Util_WriteLog(u"최초원주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"통신주문구분") self.Util_WriteLog(u"통신주문구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문전략구분") self.Util_WriteLog(u"주문전략구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문조작구분") self.Util_WriteLog(u"주문조작구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"거래소접수시간") self.Util_WriteLog(u"거래소접수시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"작업사원") self.Util_WriteLog(u"작업사원 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"그룹주문번호") self.Util_WriteLog(u"그룹주문번호 : " + strData) pass def procReal183(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"key") self.Util_WriteLog(u"key : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌번호") self.Util_WriteLog(u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"딜러번호") self.Util_WriteLog(u"딜러번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌명") self.Util_WriteLog(u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"딜러명") self.Util_WriteLog(u"딜러명 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목") self.Util_WriteLog(u"종목 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매매구분") self.Util_WriteLog(u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"전일 미결제 수량") self.Util_WriteLog(u"전일 미결제 수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"당일 미결제 수량") self.Util_WriteLog(u"당일 미결제 수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"미체결수량") self.Util_WriteLog(u"미체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"평균 단가") self.Util_WriteLog(u"평균 단가 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"당일미결제약정금액") self.Util_WriteLog(u"당일미결제약정금액 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"신규체결수량") self.Util_WriteLog(u"신규체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"신규체결금액") self.Util_WriteLog(u"신규체결금액 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"전환매 체결수량") self.Util_WriteLog(u"전환매 체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"전환매 체결금액") self.Util_WriteLog(u"전환매 체결금액 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"행사 신청수량") self.Util_WriteLog(u"행사 신청수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"행사 배정수량") self.Util_WriteLog(u"행사 배정수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"행사 거부수량") self.Util_WriteLog(u"행사 거부수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"만기수량") self.Util_WriteLog(u"행사 만기수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"장부단가") self.Util_WriteLog(u"장부단가 : " + strData) pass def procReal184(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌번호") self.Util_WriteLog(u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"딜러번호") self.Util_WriteLog(u"딜러번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌명") self.Util_WriteLog(u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"딜러명") self.Util_WriteLog(u"딜러명 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문가능금액") self.Util_WriteLog(u"주문가능금액 : " + strData) pass def procReal185(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"key") self.Util_WriteLog(u"key : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌번호") self.Util_WriteLog(u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"딜러번호") self.Util_WriteLog(u"딜러번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"계좌명") self.Util_WriteLog(u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"딜러명") self.Util_WriteLog(u"딜러명 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"주문번호") self.Util_WriteLog(u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목코드") self.Util_WriteLog(u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매매구분") self.Util_WriteLog(u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결가격") self.Util_WriteLog(u"체결가격 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결수량") self.Util_WriteLog(u"체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결시간") self.Util_WriteLog(u"체결시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"전략구분") self.Util_WriteLog(u"전략구분 : " + strData) pass def procReal76(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목코드") self.Util_WriteLog(u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"호가시간") self.Util_WriteLog(u"호가시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매도호가1") self.Util_WriteLog(u"매도호가1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매수호가1") self.Util_WriteLog(u"매수호가1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매도호가수량1") self.Util_WriteLog(u"매도호가수량1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매수호가수량1") self.Util_WriteLog(u"매수호가수량1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매도호가건수1") self.Util_WriteLog(u"매도호가건수1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매수호가건수1") self.Util_WriteLog(u"매수호가건수1 : " + strData) pass def procReal71(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목코드") self.Util_WriteLog(u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결시간") self.Util_WriteLog(u"체결시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"change") self.Util_WriteLog(u"전일대비 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"현재가") self.Util_WriteLog(u"현재가 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"cvolume") self.Util_WriteLog(u"체결량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"누적거래량") self.Util_WriteLog(u"누적거래량 : " + strData) pass def procReal58(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"kfutcode") self.Util_WriteLog(u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"hotime") self.Util_WriteLog(u"호가시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"offerho1") self.Util_WriteLog(u"매도호가1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"bidho1") self.Util_WriteLog(u"매수호가1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"offerrem1") self.Util_WriteLog(u"매도호가수량1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"bidrem1") self.Util_WriteLog(u"매수호가수량1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"offercnt1") self.Util_WriteLog(u"매도호가건수1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"bidcnt1") self.Util_WriteLog(u"매수호가건수1 : " + strData) pass def procReal51(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목코드") self.Util_WriteLog(u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"호가시간") self.Util_WriteLog(u"호가시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매도호가1") self.Util_WriteLog(u"매도호가1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매수호가1") self.Util_WriteLog(u"매수호가1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매도호가수량1") self.Util_WriteLog(u"매도호가수량1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매수호가수량1") self.Util_WriteLog(u"매수호가수량1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매도호가건수1") self.Util_WriteLog(u"매도호가건수1 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"매수호가건수1") self.Util_WriteLog(u"매수호가건수1 : " + strData) pass def procReal65(self, sTrCode, nRealType): strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"종목코드") self.Util_WriteLog(u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결시간") self.Util_WriteLog(u"체결시간 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"전일대비") self.Util_WriteLog(u"전일대비 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"현재가") self.Util_WriteLog(u"현재가 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"체결량") self.Util_WriteLog(u"체결량 : " + strData) strData = self.HD_CommGetData(sTrCode, nRealType, u"OutRec1", 0, u"누적거래량") self.Util_WriteLog(u"누적거래량 : " + strData) pass def procDO1000(self, sTrCode): strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"접수구분") self.Util_WriteLog( u"접수구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"처리구분") self.Util_WriteLog( u"처리구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"계좌번호") self.Util_WriteLog( u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"주문번호") self.Util_WriteLog( u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"종목코드") self.Util_WriteLog( u"종목코드 : " + strData) pass def procDO2000(self, sTrCode): strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"접수구분") self.Util_WriteLog( u"접수구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"처리구분") self.Util_WriteLog( u"처리구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"계좌번호") self.Util_WriteLog( u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"주문번호") self.Util_WriteLog( u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"종목코드") self.Util_WriteLog( u"종목코드 : " + strData) pass def procAO0400(self, sTrCode): strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"접수구분") self.Util_WriteLog( u"접수구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"주문번호") self.Util_WriteLog( u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"처리코드") self.Util_WriteLog( u"처리코드 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"처리메시지") self.Util_WriteLog( u"처리메시지 : " + strData) pass def procAQ0401(self, sTrCode): nRptCnt = self.HD_CommGetRepeatCnt(sTrCode, -1, u"OutRec1") self.Util_WriteLog( u"AQ0401 반복회수 : " + str(nRptCnt) ) for i in nRptCnt: self.Util_WriteLog( u"===============================================" ) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문번호 ") self.Util_WriteLog( u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌번호 ") self.Util_WriteLog( u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌명 ") self.Util_WriteLog( u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"종목코드 ") self.Util_WriteLog( u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"매매구분 ") self.Util_WriteLog( u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문가격 ") self.Util_WriteLog( u"주문가격 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문수량 ") self.Util_WriteLog( u"주문수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"체결수량 ") self.Util_WriteLog( u"체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"잔량 ") self.Util_WriteLog( u"잔량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문유형 ") self.Util_WriteLog( u"주문유형 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"STOP 가격 ") self.Util_WriteLog( u"STOP 가격 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문시간 ") self.Util_WriteLog( u"주문시간 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문자 ") self.Util_WriteLog( u"주문자 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"통신구분 ") self.Util_WriteLog( u"통신구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"전략구분 ") self.Util_WriteLog( u"전략구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"최초원주문번호 ") self.Util_WriteLog( u"최초원주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문일자 ") self.Util_WriteLog( u"주문일자 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"그룹 주문 번호 ") self.Util_WriteLog( u"그룹 주문 번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"가격조건 ") self.Util_WriteLog( u"가격조건 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"체결조건 ") self.Util_WriteLog( u"체결조건 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문종료일자 ") self.Util_WriteLog( u"주문종료일자 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"IOC 최소체결수량 ") self.Util_WriteLog( u"IOC 최소체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"통화코드 ") self.Util_WriteLog( u"통화코드 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문금액 ") self.Util_WriteLog( u"주문금액 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문시작일자 ") self.Util_WriteLog( u"주문시작일자 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"옵션행사예약여부 ") self.Util_WriteLog( u"옵션행사예약여부 : " + strData) pass def procAQ0402(self, sTrCode): nRptCnt = self.HD_CommGetRepeatCnt(sTrCode, -1, u"OutRec1") self.Util_WriteLog( u"AQ0402 반복회수 : " + str(nRptCnt) ) for i in nRptCnt: self.Util_WriteLog( u"===============================================" ) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문번호 ") self.Util_WriteLog( u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌번호 ") self.Util_WriteLog( u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌명 ") self.Util_WriteLog( u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"종목 ") self.Util_WriteLog( u"종목 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"매매구분 ") self.Util_WriteLog( u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문가격 ") self.Util_WriteLog( u"주문가격 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문수량 ") self.Util_WriteLog( u"주문수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"체결가격 ") self.Util_WriteLog( u"체결가격 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"체결수량 ") self.Util_WriteLog( u"체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"STOP가격 ") self.Util_WriteLog( u"STOP가격 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"약정금액 ") self.Util_WriteLog( u"약정금액 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문유형 ") self.Util_WriteLog( u"주문유형 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"수수료 ") self.Util_WriteLog( u"수수료 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문일자 ") self.Util_WriteLog( u"주문일자 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문시간 ") self.Util_WriteLog( u"주문시간 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문자 ") self.Util_WriteLog( u"주문자 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"체결일자 ") self.Util_WriteLog( u"체결일자 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"체결시간 ") self.Util_WriteLog( u"체결시간 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"거래소일자 ") self.Util_WriteLog( u"거래소일자 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"거래소시간 ") self.Util_WriteLog( u"거래소시간 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"통화코드 ") self.Util_WriteLog( u"통화코드 : " + strData) pass def procAQ0403(self, sTrCode): nRptCnt = self.HD_CommGetRepeatCnt(sTrCode, -1, u"OutRec1") print(nRptCnt) self.Util_WriteLog( u"AQ0403 반복회수 : " + str(nRptCnt) ) for i in nRptCnt: self.Util_WriteLog( u"===============================================" ) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌번호 ") self.Util_WriteLog( u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌명 ") self.Util_WriteLog( u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"종목 ") self.Util_WriteLog( u"종목 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"매매구분 ") self.Util_WriteLog( u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"당일순 미결제수량 ") self.Util_WriteLog( u"당일순 미결제수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"평균단가(소수점반영) ") self.Util_WriteLog( u"평균단가(소수점반영) : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"평균단가 ") self.Util_WriteLog( u"평균단가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"현재가 ") self.Util_WriteLog( u"현재가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"평가손익 ") self.Util_WriteLog( u"평가손익 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"위탁증거금 ") self.Util_WriteLog( u"위탁증거금 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"신규제한일 ") self.Util_WriteLog( u"신규제한일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"최종거래일 ") self.Util_WriteLog( u"최종거래일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"통화코드 ") self.Util_WriteLog( u"통화코드 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"옵션시장가치 ") self.Util_WriteLog( u"옵션시장가치 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"옵션행사예약여부 ") self.Util_WriteLog( u"옵션행사예약여부 : " + strData) pass def procAQ0607(self, sTrCode): nRptCnt = self.HD_CommGetRepeatCnt(sTrCode, -1, u"OutRec1") self.Util_WriteLog( u"AQ0607 반복회수 : " + str(nRptCnt) ) for i in nRptCnt: self.Util_WriteLog( u"===============================================" ) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌번호 ") self.Util_WriteLog( u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌명 ") self.Util_WriteLog( u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"통화코드 ") self.Util_WriteLog( u"통화코드 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"예탁금총액 ") self.Util_WriteLog( u"예탁금총액 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"예탁금잔액 ") self.Util_WriteLog( u"예탁금잔액 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"평가금액 ") self.Util_WriteLog( u"평가금액 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"미수금액 ") self.Util_WriteLog( u"미수금액 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"결제금액부족 ") self.Util_WriteLog( u"결제금액부족 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"미결제약정증거금 ") self.Util_WriteLog( u"미결제약정증거금 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"인출가능금 ") self.Util_WriteLog( u"인출가능금 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문가능금 ") self.Util_WriteLog( u"주문가능금 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"유지증거금 ") self.Util_WriteLog( u"유지증거금 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문증거금 ") self.Util_WriteLog( u"주문증거금 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"위탁증거금 ") self.Util_WriteLog( u"위탁증거금 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"거래수수료 ") self.Util_WriteLog( u"거래수수료 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"청산손익 ") self.Util_WriteLog( u"청산손익 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"평가손익 ") self.Util_WriteLog( u"평가손익 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"미발생 ") self.Util_WriteLog( u"미발생 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"추가증거금 ") self.Util_WriteLog( u"추가증거금 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"총계정자산가치 ") self.Util_WriteLog( u"총계정자산가치 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"외환고시환율 ") self.Util_WriteLog( u"외환고시환율 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"옵션매매대금 ") self.Util_WriteLog( u"옵션매매대금 : " + strData) pass def proco51000(self, sTrCode): strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"종목코드 ") self.Util_WriteLog( u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"한글종목명 ") self.Util_WriteLog( u"한글종목명 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"현재가 ") self.Util_WriteLog( u"현재가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"전일대비구분 ") self.Util_WriteLog( u"전일대비구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"전일대비 ") self.Util_WriteLog( u"전일대비 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"전일대비등락율 ") self.Util_WriteLog( u"전일대비등락율 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"직전대비구분 ") self.Util_WriteLog( u"직전대비구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"시가 ") self.Util_WriteLog( u"시가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"고가 ") self.Util_WriteLog( u"고가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"저가 ") self.Util_WriteLog( u"저가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"LT고가 ") self.Util_WriteLog( u"LT고가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"LT고가일 ") self.Util_WriteLog( u"LT고가일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"LT저가 ") self.Util_WriteLog( u"LT저가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"LT저가일 ") self.Util_WriteLog( u"LT저가일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"영업일 ") self.Util_WriteLog( u"영업일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"상승거래량 ") self.Util_WriteLog( u"상승거래량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"하락거래량 ") self.Util_WriteLog( u"하락거래량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"누적거래량 ") self.Util_WriteLog( u"누적거래량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"만기일 ") self.Util_WriteLog( u"만기일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"정산가 ") self.Util_WriteLog( u"정산가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"정산일 ") self.Util_WriteLog( u"정산일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"잔존일수 ") self.Util_WriteLog( u"잔존일수 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"매도호가 ") self.Util_WriteLog( u"매도호가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"매수호가 ") self.Util_WriteLog( u"매수호가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"기준가 ") self.Util_WriteLog( u"기준가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"전일거래량 ") self.Util_WriteLog( u"전일거래량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"전일거래량대비율 ") self.Util_WriteLog( u"전일거래량대비율 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"체결시간 ") self.Util_WriteLog( u"체결시간 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"국내시간 ") self.Util_WriteLog( u"국내시간 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"거래소구분 ") self.Util_WriteLog( u"거래소구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"ETH시작 ") self.Util_WriteLog( u"ETH시작 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"ETH종료 ") self.Util_WriteLog( u"ETH종료 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"영문종목명 ") self.Util_WriteLog( u"영문종목명 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"신규거래제한일 ") self.Util_WriteLog( u"신규거래제한일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"최종거래일 ") self.Util_WriteLog( u"최종거래일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"호가방식 ") self.Util_WriteLog( u"호가방식 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"주문제한폭 ") self.Util_WriteLog( u"주문제한폭 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"실물인수도시작일자") self.Util_WriteLog( u"실물인수도시작일자: " + strData) pass def proco51010(self, sTrCode): strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"종목코드") self.Util_WriteLog( u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"호가시간") self.Util_WriteLog( u"호가시간 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"매도호가1") self.Util_WriteLog( u"매도호가1 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"매수호가1") self.Util_WriteLog( u"매수호가1 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"매도호가잔량1") self.Util_WriteLog( u"매도호가잔량1 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"매수호가잔량1") self.Util_WriteLog( u"매수호가잔량1 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"매도호가건수1") self.Util_WriteLog( u"매도호가건수1 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"매수호가건수1") self.Util_WriteLog( u"매수호가건수1 : " + strData) pass def proco51210(self, sTrCode): strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"종목코드") self.Util_WriteLog( u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"최종거래일") self.Util_WriteLog( u"최종거래일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"거래소") self.Util_WriteLog( u"거래소 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"상장일") self.Util_WriteLog( u"상장일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"만기일") self.Util_WriteLog( u"만기일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"삭제일") self.Util_WriteLog( u"삭제일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"정산가") self.Util_WriteLog( u"정산가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"정산일") self.Util_WriteLog( u"정산일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"가격표시") self.Util_WriteLog( u"가격표시 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"장시작시간(CME)") self.Util_WriteLog( u"장시작시간(CME) : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"장종료시간(CME)") self.Util_WriteLog( u"장종료시간(CME) : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"장시작시간(한국)") self.Util_WriteLog( u"장시작시간(한국) : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"장종료시간(한국)") self.Util_WriteLog( u"장종료시간(한국) : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"거래통화") self.Util_WriteLog( u"거래통화 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"상품구분") self.Util_WriteLog( u"상품구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"매매여부") self.Util_WriteLog( u"매매여부 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"잔존일수") self.Util_WriteLog( u"잔존일수 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"ticksize") self.Util_WriteLog( u"ticksize : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"tickvalue") self.Util_WriteLog( u"tickvalue : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"최종결제일") self.Util_WriteLog( u"최종결제일 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"증거금") self.Util_WriteLog( u"증거금 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"계약단위") self.Util_WriteLog( u"계약단위 : " + strData) pass def procs20001(self, sTrCode): i = 0 strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"단축코드") self.Util_WriteLog(strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"호가수신시간") self.Util_WriteLog(strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"현재가") self.Util_WriteLog(strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"누적거래량") self.Util_WriteLog(strData) pass def procAQ0101(self, sTrCode): strData = self.HD_CommGetAccInfo() nAcctCnt = int(strData[0:5]) nLenAcctNo = 11 nLenAcctNm = 30 nLenAcctGb = 1 strAcctInfo = str(strData[5:]).encode('cp949') nLenAccInfo = nLenAcctNo + nLenAcctNm + nLenAcctGb #strSelAccGb = "1" #1:해외, 2:FX, 9:국내 #if ( self.BtnRadio1.isChecked() == True ): # strSelAccGb = "9" #국내 #elif ( self.BtnRadio2.isChecked() == True ): # strSelAccGb = "1" #해외 #elif ( self.BtnRadio3.isChecked() == True ): # strSelAccGb = "2" #FX for i in range(0, nAcctCnt): nStPos = (i*nLenAccInfo) strAcctNo = strAcctInfo[nStPos :nStPos+nLenAcctNo] strAcctNm = strAcctInfo[nStPos+(nLenAcctNo) :nStPos+nLenAcctNo+nLenAcctNm] strAcctGb = strAcctInfo[nStPos+(nLenAcctNo+nLenAcctNm):nStPos+nLenAcctNo+nLenAcctNm+nLenAcctGb] strAcctNm = unicode(strAcctNm, 'cp949') strAcctNo = unicode(strAcctNo.strip(), 'utf-8') strAcctNm = str(strAcctNm.strip()) tmpDic = {strAcctNo:strAcctNm} if ( strAcctGb == "9" ): self.m_AccListFO.update(tmpDic) elif(strAcctGb == "1" ): self.m_AccListFR.update(tmpDic) elif(strAcctGb == "2" ): self.m_AccListFX.update(tmpDic) self.Util_WriteLog(strAcctNo + "," + strAcctNm + "," + strAcctGb) self.OnRadioAcctTpChange() pass def procDQ0242(self, sTrCode): strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"계좌번호") self.Util_WriteLog( u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"예탁금액-총액") self.Util_WriteLog( u"예탁금액-총액 :" + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"예탁금액-현금") self.Util_WriteLog( u"예탁금액-현금 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"예탁금액-대용") self.Util_WriteLog( u"예탁금액-대용 :" + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"예탁외화") self.Util_WriteLog( u"예탁외화 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"당일손익") self.Util_WriteLog( u"당일손익 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"위탁수수료") self.Util_WriteLog( u"위탁수수료 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"당일순손익") self.Util_WriteLog( u"당일순손익 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"평가예탁총액") self.Util_WriteLog( u"평가예탁총액 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", 0, u"순자산-총평가액") self.Util_WriteLog( u"순자산-총평가액 : " + strData) pass def procAQ0450(self, sTrCode): nRptCnt = self.HD_CommGetRepeatCnt(sTrCode, -1, u"OutRec1") self.Util_WriteLog( u"AQ0450 조회개수 : " + str(nRptCnt) ) for i in nRptCnt: self.Util_WriteLog( u"===============================================" ) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문번호") self.Util_WriteLog(u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌번호") self.Util_WriteLog(u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌명") self.Util_WriteLog(u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"종목코드") self.Util_WriteLog(u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"매매구분") self.Util_WriteLog(u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문가격") self.Util_WriteLog(u"주문가격 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문수량") self.Util_WriteLog(u"주문수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"체결수량") self.Util_WriteLog(u"체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"잔량") self.Util_WriteLog(u"잔량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문유형") self.Util_WriteLog(u"주문유형 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"STOP 가격") self.Util_WriteLog(u"STOP 가격 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문시간") self.Util_WriteLog(u"주문시간 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문자 ") self.Util_WriteLog(u"주문자 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"통신구분") self.Util_WriteLog(u"통신구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"전략구분") self.Util_WriteLog(u"전략구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"최초원주문번호") self.Util_WriteLog(u"최초원주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문일자") self.Util_WriteLog(u"주문일자 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"그룹주문번호") self.Util_WriteLog(u"그룹주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"가격조건") self.Util_WriteLog(u"가격조건 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"체결조건") self.Util_WriteLog(u"체결조건 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"GTD일자") self.Util_WriteLog(u"GTD일자 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"IOC최소체결수량") self.Util_WriteLog(u"IOC최소체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"원주문번호") self.Util_WriteLog(u"원주문번호 : " + strData) pass def procDQ0104(self, sTrCode): nRptCnt = self.HD_CommGetRepeatCnt(sTrCode, -1, u"OutRec1") self.Util_WriteLog( u"DQ0104 조회개수 : " + str(nRptCnt) ) for i in nRptCnt: self.Util_WriteLog( u"===============================================" ) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌번호") self.Util_WriteLog( u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌명") self.Util_WriteLog( u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문번호") self.Util_WriteLog( u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"종목코드") self.Util_WriteLog( u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"매매구분") self.Util_WriteLog( u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문가격") self.Util_WriteLog( u"주문가격 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문수량") self.Util_WriteLog( u"주문수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"정정수량") self.Util_WriteLog( u"정정수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"취소수량") self.Util_WriteLog( u"취소수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"체결수량") self.Util_WriteLog( u"체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"잔량") self.Util_WriteLog( u"잔량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"원주문번호") self.Util_WriteLog( u"원주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"최초원주문번호") self.Util_WriteLog( u"최초원주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"통신주문구분") self.Util_WriteLog( u"통신주문구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문전략구분") self.Util_WriteLog( u"주문전략구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문조작구분") self.Util_WriteLog( u"주문조작구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"거래소접수시간") self.Util_WriteLog( u"거래소접수시간 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"작업사원") self.Util_WriteLog( u"작업사원 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"그룹주문번호") self.Util_WriteLog( u"그룹주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"딜러번호") self.Util_WriteLog( u"딜러번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"딜러명") self.Util_WriteLog( u"딜러명 : " + strData) pass def procDQ0107(self, sTrCode): nRptCnt = self.HD_CommGetRepeatCnt(sTrCode, -1, u"OutRec1") self.Util_WriteLog( u"DQ0107 조회개수 : " + str(nRptCnt) ) for i in nRptCnt: self.Util_WriteLog( u"===============================================" ) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌번호") self.Util_WriteLog( u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌명") self.Util_WriteLog( u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"주문번호") self.Util_WriteLog( u"주문번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"종목코드") self.Util_WriteLog( u"종목코드 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"매매구분") self.Util_WriteLog( u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"체결가격") self.Util_WriteLog( u"체결가격 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"체결수량") self.Util_WriteLog( u"체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"체결시간") self.Util_WriteLog( u"체결시간 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"전략구분") self.Util_WriteLog( u"전략구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"통신구분") self.Util_WriteLog( u"통신구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"딜러번호") self.Util_WriteLog( u"딜러번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"딜러좌명") self.Util_WriteLog( u"딜러좌명 : " + strData) pass def procDQ0110(self, sTrCode): nRptCnt = self.HD_CommGetRepeatCnt(sTrCode, -1, u"OutRec1") self.Util_WriteLog( u"DQ0110 조회개수 : " + str(nRptCnt) ) for i in nRptCnt: self.Util_WriteLog( u"===============================================" ) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌번호") self.Util_WriteLog( u"계좌번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"계좌명") self.Util_WriteLog( u"계좌명 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"종목") self.Util_WriteLog( u"종목 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"매매구분") self.Util_WriteLog( u"매매구분 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"전일미결제수량") self.Util_WriteLog( u"전일미결제수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"당일미결제수량") self.Util_WriteLog( u"당일미결제수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"미체결 수량") self.Util_WriteLog( u"미체결 수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"평균단가") self.Util_WriteLog( u"평균단가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"장부단가") self.Util_WriteLog( u"장부단가 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"당일미결제약정금액") self.Util_WriteLog( u"당일미결제약정금액 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"당일체결수량") self.Util_WriteLog( u"당일체결수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"당일체결금액") self.Util_WriteLog( u"당일체결금액 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"행사신청수량") self.Util_WriteLog( u"행사신청수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"행사배정수량") self.Util_WriteLog( u"행사배정수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"행사거부수량") self.Util_WriteLog( u"행사거부수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"만기수량") self.Util_WriteLog( u"만기수량 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"딜러번호") self.Util_WriteLog( u"딜러번호 : " + strData) strData = self.HD_CommGetData(sTrCode, -1, u"OutRec1", i, u"딜러명") self.Util_WriteLog( u"딜러명 : " + strData) pass def OnGetMsgWithRqId(self, nRqID, strErrCode, strErrMsg): strRecv = "조회응답 Tr = [%s] UniqueID = [%d]" %(strErrCode, nRqID) strRecvMsg = "메시지수신 UniqueID = [%s] ErrorCode=[%s] ErrorMessage=[%s]" % (str(nRqID), unicode(strErrCode), unicode(strErrMsg)) self.Util_WriteLog( strRecvMsg ) if __name__ == "__main__": import sys app = QtGui.QApplication(sys.argv) MainWindow = QtGui.QMainWindow() ui = Ui_MainWindow() ui.setupUi(MainWindow) ui.SetupHDFOcx(MainWindow) MainWindow.show() sys.exit(app.exec_())

[ "jay.bwkim@gmail.com" ]

jay.bwkim@gmail.com

b19eb4c4a4c8e2182848c6efdc592bdd73bafd78

7f004635957d252b7e8d7d6e0aee47e24aca0b82

/catkin_ws/src/sound_play/src/sound_play/libsoundplay.py

12c62a885fc10f5d991711f131baaf324d3e99cd

[]

no_license

Pontusun/CIS700_Team2

75bef2305f5ccb7992f152b9fca20ea475077833

17b125b652d3be41884d6f625b7424b00ca0a6dd

refs/heads/master

2021-01-10T16:02:19.327233

2016-02-11T22:20:46

44,488,662

1

3

null

2015-11-29T19:54:32

2015-10-18T17:35:24

CMake

UTF-8

Python

false

13,215

py

#!/usr/bin/env python #*********************************************************** #* Software License Agreement (BSD License) #* #* Copyright (c) 2009, Willow Garage, Inc. #* All rights reserved. #* #* Redistribution and use in source and binary forms, with or without #* modification, are permitted provided that the following conditions #* are met: #* #* * Redistributions of source code must retain the above copyright #* notice, this list of conditions and the following disclaimer. #* * Redistributions in binary form must reproduce the above #* copyright notice, this list of conditions and the following #* disclaimer in the documentation and/or other materials provided #* with the distribution. #* * Neither the name of the Willow Garage nor the names of its #* contributors may be used to endorse or promote products derived #* from this software without specific prior written permission. #* #* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS #* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT #* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS #* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE #* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, #* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, #* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; #* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER #* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT #* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN #* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE #* POSSIBILITY OF SUCH DAMAGE. #*********************************************************** # Author: Blaise Gassend import rospy import roslib import actionlib import os, sys from sound_play.msg import SoundRequest from sound_play.msg import SoundRequestGoal from sound_play.msg import SoundRequestAction ## \brief Class that publishes messages to the sound_play node. ## ## This class is a helper class for communicating with the sound_play node ## via the \ref sound_play.SoundRequest message. It has two ways of being used: ## ## - It can create Sound classes that represent a particular sound which ## can be played, repeated or stopped. ## ## - It provides methods for each way in which the sound_play.SoundRequest ## message can be invoked. class Sound(object): def __init__(self, client, snd, arg, volume=1.0): self.client = client self.snd = snd self.arg = arg self.vol = volume ## \brief Play the Sound. ## ## This method causes the Sound to be played once. def play(self, **kwargs): self.client.sendMsg(self.snd, SoundRequest.PLAY_ONCE, self.arg, vol=self.vol, **kwargs) ## \brief Play the Sound repeatedly. ## ## This method causes the Sound to be played repeatedly until stop() is ## called. def repeat(self, **kwargs): self.client.sendMsg(self.snd, SoundRequest.PLAY_START, self.arg, vol=self.vol, **kwargs) ## \brief Stop Sound playback. ## ## This method causes the Sound to stop playing. def stop(self): self.client.sendMsg(self.snd, SoundRequest.PLAY_STOP, self.arg) ## This class is a helper class for communicating with the sound_play node ## via the \ref sound_play.SoundRequest message. There is a one-to-one mapping ## between methods and invocations of the \ref sound_play.SoundRequest message. class SoundClient(object): def __init__(self, blocking=False): """ The SoundClient can send SoundRequests in two modes: non-blocking mode (by publishing a message to the soundplay_node directly) which will return as soon as the sound request has been sent, or blocking mode (by using the actionlib interface) which will wait until the sound has finished playing completely. The blocking parameter here is the standard behavior, but can be over-ridden. Each say/play/start/repeat method can take in an optional `blocking=True|False` argument that will over-ride the class-wide behavior. See soundclient_example.py for an example of this behavior. :param blocking: Used as the default behavior unless over-ridden, (default = false) """ self._blocking = blocking # NOTE: only one of these will be used at once, but we need to create # both the publisher and actionlib client here. self.actionclient = actionlib.SimpleActionClient( 'sound_play', SoundRequestAction) self.pub = rospy.Publisher('robotsound', SoundRequest, queue_size=5) ## \brief Create a voice Sound. ## ## Creates a Sound corresponding to saying the indicated text. ## ## \param s Text to say def voiceSound(self, s, volume=1.0): return Sound(self, SoundRequest.SAY, s, volume=volume) ## \brief Create a wave Sound. ## ## Creates a Sound corresponding to indicated file. ## ## \param s File to play. Should be an absolute path that exists on the ## machine running the sound_play node. def waveSound(self, sound, volume=1.0): if sound[0] != "/": rootdir = os.path.join(roslib.packages.get_pkg_dir('sound_play'),'sounds') sound = rootdir + "/" + sound return Sound(self, SoundRequest.PLAY_FILE, sound, volume=volume) ## \brief Create a builtin Sound. ## ## Creates a Sound corresponding to indicated builtin wave. ## ## \param id Identifier of the sound to play. def builtinSound(self, id, volume=1.0): return Sound(self, id, "", volume) ## \brief Say a string ## ## Send a string to be said by the sound_node. The vocalization can be ## stopped using stopSaying or stopAll. ## ## \param text String to say def say(self,text, voice='', volume=1.0, **kwargs): self.sendMsg(SoundRequest.SAY, SoundRequest.PLAY_ONCE, text, voice, volume, **kwargs) ## \brief Say a string repeatedly ## ## The string is said repeatedly until stopSaying or stopAll is used. ## ## \param text String to say repeatedly def repeat(self,text, volume=1.0, **kwargs): self.sendMsg(SoundRequest.SAY, SoundRequest.PLAY_START, text, vol=volume, **kwargs) ## \brief Stop saying a string ## ## Stops saying a string that was previously started by say or repeat. The ## argument indicates which string to stop saying. ## ## \param text Same string as in the say or repeat command def stopSaying(self,text): self.sendMsg(SoundRequest.SAY, SoundRequest.PLAY_STOP, text) ## \brief Plays a WAV or OGG file ## ## Plays a WAV or OGG file once. The playback can be stopped by stopWave or ## stopAll. ## ## \param sound Filename of the WAV or OGG file. Must be an absolute path valid ## on the computer on which the sound_play node is running def playWave(self, sound, volume=1.0, **kwargs): if sound[0] != "/": rootdir = os.path.join(roslib.packages.get_pkg_dir('sound_play'),'sounds') sound = rootdir + "/" + sound self.sendMsg(SoundRequest.PLAY_FILE, SoundRequest.PLAY_ONCE, sound, vol=volume, **kwargs) ## \brief Plays a WAV or OGG file repeatedly ## ## Plays a WAV or OGG file repeatedly until stopWave or stopAll is used. ## ## \param sound Filename of the WAV or OGG file. Must be an absolute path valid ## on the computer on which the sound_play node is running. def startWave(self, sound, volume=1.0, **kwargs): if sound[0] != "/": rootdir = os.path.join(roslib.packages.get_pkg_dir('sound_play'),'sounds') sound = rootdir + "/" + sound self.sendMsg(SoundRequest.PLAY_FILE, SoundRequest.PLAY_START, sound, vol=volume, **kwargs) ## \brief Stop playing a WAV or OGG file ## ## Stops playing a file that was previously started by playWave or ## startWave. ## ## \param sound Same string as in the playWave or startWave command def stopWave(self,sound): if sound[0] != "/": rootdir = os.path.join(roslib.package.get_pkg_dir('sound_play'),'sounds') sound = rootdir + "/" + sound self.sendMsg(SoundRequest.PLAY_FILE, SoundRequest.PLAY_STOP, sound) ## \brief Plays a WAV or OGG file ## ## Plays a WAV or OGG file once. The playback can be stopped by stopWaveFromPkg or ## stopAll. ## ## \param package Package name containing the sound file. ## \param sound Filename of the WAV or OGG file. Must be an path relative to the package valid ## on the computer on which the sound_play node is running def playWaveFromPkg(self, package, sound, volume=1.0, **kwargs): self.sendMsg(SoundRequest.PLAY_FILE, SoundRequest.PLAY_ONCE, sound, package, volume, **kwargs) ## \brief Plays a WAV or OGG file repeatedly ## ## Plays a WAV or OGG file repeatedly until stopWaveFromPkg or stopAll is used. ## ## \param package Package name containing the sound file. ## \param sound Filename of the WAV or OGG file. Must be an path relative to the package valid ## on the computer on which the sound_play node is running def startWaveFromPkg(self, package, sound, volume=1.0, **kwargs): self.sendMsg(SoundRequest.PLAY_FILE, SoundRequest.PLAY_START, sound, package, volume, **kwargs) ## \brief Stop playing a WAV or OGG file ## ## Stops playing a file that was previously started by playWaveFromPkg or ## startWaveFromPkg. ## ## \param package Package name containing the sound file. ## \param sound Filename of the WAV or OGG file. Must be an path relative to the package valid ## on the computer on which the sound_play node is running def stopWaveFromPkg(self,sound, package): self.sendMsg(SoundRequest.PLAY_FILE, SoundRequest.PLAY_STOP, sound, package) ## \brief Play a buildin sound ## ## Starts playing one of the built-in sounds. built-ing sounds are documented ## in \ref SoundRequest.msg. Playback can be stopped by stopall. ## ## \param sound Identifier of the sound to play. def play(self,sound, volume=1.0, **kwargs): self.sendMsg(sound, SoundRequest.PLAY_ONCE, "", vol=volume, **kwargs) ## \brief Play a buildin sound repeatedly ## ## Starts playing one of the built-in sounds repeatedly until stop or ## stopall is used. Built-in sounds are documented in \ref SoundRequest.msg. ## ## \param sound Identifier of the sound to play. def start(self,sound, volume=1.0, **kwargs): self.sendMsg(sound, SoundRequest.PLAY_START, "", vol=volume, **kwargs) ## \brief Stop playing a built-in sound ## ## Stops playing a built-in sound started with play or start. ## ## \param sound Same sound that was used to start playback def stop(self,sound): self.sendMsg(sound, SoundRequest.PLAY_STOP, "") ## \brief Stop all currently playing sounds ## ## This method stops all speech, wave file, and built-in sound playback. def stopAll(self): self.stop(SoundRequest.ALL) def sendMsg(self, snd, cmd, s, arg2="", vol=1.0, **kwargs): """ Internal method that publishes the sound request, either directly as a SoundRequest to the soundplay_node or through the actionlib interface (which blocks until the sound has finished playing). The blocking behavior is nominally the class-wide setting unless it has been explicitly specified in the play call. """ # Use the passed-in argument if it exists, otherwise fall back to the # class-wide setting. blocking = kwargs.get('blocking', self._blocking) msg = SoundRequest() msg.sound = snd # Threshold volume between 0 and 1. msg.volume = max(0, min(1, vol)) msg.command = cmd msg.arg = s msg.arg2 = arg2 rospy.logdebug('Sending sound request with volume = {}' ' and blocking = {}'.format(msg.volume, blocking)) # Defensive check for the existence of the correct communicator. if blocking and not self.pub: rospy.logerr('Publisher for SoundRequest must exist') return if not blocking and not self.actionclient: rospy.logerr('Action client for SoundRequest does not exist.') return if not blocking: # Publish message directly and return immediately self.pub.publish(msg) if self.pub.get_num_connections() < 1: rospy.logwarn("Sound command issued, but no node is subscribed" " to the topic. Perhaps you forgot to run" " soundplay_node.py?") else: # Block until result comes back. assert self.actionclient, 'Actionclient must exist' rospy.logdebug('Sending action client sound request [blocking]') self.actionclient.wait_for_server() goal = SoundRequestGoal() goal.sound_request = msg self.actionclient.send_goal(goal) self.actionclient.wait_for_result() rospy.logdebug('sound request response received') return

[ "genesis@nuc" ]

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/test/legacy_test/test_poisson_op.py

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2023-06-26T06:25:48.074273

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1

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2019-03-07T10:09:34

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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. # # 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 math import unittest import numpy as np from eager_op_test import OpTest import paddle paddle.enable_static() paddle.seed(100) def output_hist(out, lam, a, b): prob = [] bin = [] for i in range(a, b + 1): prob.append((lam**i) * math.exp(-lam) / math.factorial(i)) bin.append(i) bin.append(b + 0.1) hist, _ = np.histogram(out, bin) hist = hist.astype("float32") hist = hist / float(out.size) return hist, prob class TestPoissonOp1(OpTest): def setUp(self): self.op_type = "poisson" self.python_api = paddle.tensor.poisson self.config() self.attrs = {} self.inputs = {'X': np.full([2048, 1024], self.lam, dtype=self.dtype)} self.outputs = {'Out': np.ones([2048, 1024], dtype=self.dtype)} def config(self): self.lam = 10 self.a = 5 self.b = 15 self.dtype = "float64" def verify_output(self, outs): hist, prob = output_hist(np.array(outs[0]), self.lam, self.a, self.b) np.testing.assert_allclose(hist, prob, rtol=0.01) def test_check_output(self): self.check_output_customized(self.verify_output) def test_check_grad_normal(self): self.check_grad( ['X'], 'Out', user_defined_grads=[np.zeros([2048, 1024], dtype=self.dtype)], user_defined_grad_outputs=[ np.random.rand(2048, 1024).astype(self.dtype) ], ) class TestPoissonOp2(TestPoissonOp1): def config(self): self.lam = 5 self.a = 1 self.b = 8 self.dtype = "float32" class TestPoissonAPI(unittest.TestCase): def test_static(self): with paddle.static.program_guard( paddle.static.Program(), paddle.static.Program() ): x_np = np.random.rand(10, 10) x = paddle.static.data(name="x", shape=[10, 10], dtype='float64') y = paddle.poisson(x) exe = paddle.static.Executor() y_np = exe.run( paddle.static.default_main_program(), feed={"x": x_np}, fetch_list=[y], ) self.assertTrue(np.min(y_np) >= 0) def test_dygraph(self): with paddle.fluid.dygraph.base.guard(): x = paddle.randn([10, 10], dtype='float32') y = paddle.poisson(x) self.assertTrue(np.min(y.numpy()) >= 0) x = paddle.randn([10, 10], dtype='float32') x.stop_gradient = False y = paddle.poisson(x) y.backward() self.assertTrue(np.min(y.numpy()) >= 0) np.testing.assert_array_equal(np.zeros_like(x), x.gradient()) def test_fixed_random_number(self): # Test GPU Fixed random number, which is generated by 'curandStatePhilox4_32_10_t' if not paddle.is_compiled_with_cuda(): return print("Test Fixed Random number on GPU------>") paddle.disable_static() paddle.set_device('gpu') paddle.seed(2021) x = paddle.full([32, 3, 1024, 768], 10.0, dtype="float32") y = paddle.poisson(x) y_np = y.numpy() expect = [ 13.0, 13.0, 11.0, 8.0, 12.0, 6.0, 9.0, 15.0, 16.0, 6.0, 13.0, 12.0, 9.0, 15.0, 17.0, 8.0, 11.0, 16.0, 11.0, 10.0, ] np.testing.assert_array_equal(y_np[0, 0, 0, 0:20], expect) expect = [ 15.0, 7.0, 12.0, 8.0, 14.0, 10.0, 10.0, 11.0, 11.0, 11.0, 21.0, 6.0, 9.0, 13.0, 13.0, 11.0, 6.0, 9.0, 12.0, 12.0, ] np.testing.assert_array_equal(y_np[8, 1, 300, 200:220], expect) expect = [ 10.0, 15.0, 9.0, 6.0, 4.0, 13.0, 10.0, 10.0, 13.0, 12.0, 9.0, 7.0, 10.0, 14.0, 7.0, 10.0, 8.0, 5.0, 10.0, 14.0, ] np.testing.assert_array_equal(y_np[16, 1, 600, 400:420], expect) expect = [ 10.0, 9.0, 14.0, 12.0, 8.0, 9.0, 7.0, 8.0, 11.0, 10.0, 13.0, 8.0, 12.0, 9.0, 7.0, 8.0, 11.0, 11.0, 12.0, 5.0, ] np.testing.assert_array_equal(y_np[24, 2, 900, 600:620], expect) expect = [ 15.0, 5.0, 11.0, 13.0, 12.0, 12.0, 13.0, 16.0, 9.0, 9.0, 7.0, 9.0, 13.0, 11.0, 15.0, 6.0, 11.0, 9.0, 10.0, 10.0, ] np.testing.assert_array_equal(y_np[31, 2, 1023, 748:768], expect) x = paddle.full([16, 1024, 1024], 5.0, dtype="float32") y = paddle.poisson(x) y_np = y.numpy() expect = [ 4.0, 5.0, 2.0, 9.0, 8.0, 7.0, 4.0, 7.0, 4.0, 7.0, 6.0, 3.0, 10.0, 7.0, 5.0, 7.0, 2.0, 5.0, 5.0, 6.0, ] np.testing.assert_array_equal(y_np[0, 0, 100:120], expect) expect = [ 1.0, 4.0, 8.0, 11.0, 6.0, 5.0, 4.0, 4.0, 7.0, 4.0, 4.0, 7.0, 11.0, 6.0, 5.0, 3.0, 4.0, 6.0, 3.0, 3.0, ] np.testing.assert_array_equal(y_np[4, 300, 300:320], expect) expect = [ 7.0, 5.0, 4.0, 6.0, 8.0, 5.0, 6.0, 7.0, 7.0, 7.0, 3.0, 10.0, 5.0, 10.0, 4.0, 5.0, 8.0, 7.0, 5.0, 7.0, ] np.testing.assert_array_equal(y_np[8, 600, 600:620], expect) expect = [ 8.0, 6.0, 7.0, 4.0, 3.0, 0.0, 4.0, 6.0, 6.0, 4.0, 3.0, 10.0, 5.0, 1.0, 3.0, 8.0, 8.0, 2.0, 1.0, 4.0, ] np.testing.assert_array_equal(y_np[12, 900, 900:920], expect) expect = [ 2.0, 1.0, 14.0, 3.0, 6.0, 5.0, 2.0, 2.0, 6.0, 5.0, 7.0, 4.0, 8.0, 4.0, 8.0, 4.0, 5.0, 7.0, 1.0, 7.0, ] np.testing.assert_array_equal(y_np[15, 1023, 1000:1020], expect) paddle.enable_static() if __name__ == "__main__": unittest.main()

[ "noreply@github.com" ]

Shixiaowei02.noreply@github.com

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/chibi_file/__init__.py

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[]

no_license

dem4ply/chibi_file

462244dac712d88915f2b931c5f0822f6d1fa937

d27cef794512014b1602486edd0235052b38087a

refs/heads/master

2020-12-03T05:09:15.825690

2017-08-23T09:36:57

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import mmap import os import shutil def current_dir(): return os.getcwd() def inflate_dir( src ): if '~' in src: return os.path.expanduser( src ) else: return os.path.abspath( src ) def is_dir( src ): return os.path.isdir( src ) def is_file( src ): return os.path.isfile( src ) def ls( src=None ): if src is None: src = current_dir() return ( name for name in os.listdir( src ) ) def ls_only_dir( src=None ): return ( name for name in ls( src ) if is_dir( name ) ) def join( *patch ): return os.path.join( *patch ) def exists( file_name ): return os.path.exists( file_name ) def copy( source, dest ): shutil.copy( source, dest ) class Chibi_file: def __init__( self, file_name ): self._file_name = file_name if not self.exists: self.touch() self.reread() @property def file_name( self ): return self._file_name def __del__( self ): self._file_content.close() def find( self, string_to_find ): if isinstance( string_to_find, str ): string_to_find = string_to_find.encode() return self._file_content.find( string_to_find ) def reread( self ): with open( self._file_name, 'r' ) as f: self._file_content = mmap.mmap( f.fileno(), 0, prot=mmap.PROT_READ ) def __contains__( self, string ): return self.find( string ) >= 0 def append( self, string ): with open( self._file_name, 'a' ) as f: f.write( string ) self.reread() @property def exists( self ): return exists( self.file_name ) def touch( self ): open( self.file_name, 'a' ).close() def copy( self, dest ): copy( self.file_name, dest )

[ "dem4ply@gmail.com" ]

dem4ply@gmail.com

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/24. Swap Nodes in Pairs.py

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[]

no_license

brianhu0716/LeetCode-Solution

e7177af15e84e833ce8ab05027683ed4ac489643

158a4359c90b723545b22c4898047274cc1b80a6

refs/heads/main

2023-07-11T05:29:56.783795

2021-08-28T12:53:14

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UTF-8

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# -*- coding: utf-8 -*- """ Created on Sun Apr 11 15:06:14 2021 @author: Brian """ ''' 交換相鄰兩node的值即可 ''' class Solution: def swapPairs(self, head: ListNode) -> ListNode: while not head or not head.next : return head ptr = head while ptr and ptr.next: temp = ptr.val ptr.val = ptr.next.val ptr.next.val = temp ptr = ptr.next.next return head

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2020-04-13T16:08:59.845707

2018-07-30T18:26:12

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UTF-8

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"""html in standard nbconvert format, but with - a table of contents - toggle buttons for showing/hiding code & output cells - converts or removes (if no converter) latex tags (like \cite{abc}, \ref{}) """ from ipypublish.filters.replace_string import replace_string from ipypublish.html.create_tpl import create_tpl from ipypublish.html.ipypublish import latex_doc # from ipypublish.html.standard import inout_prompt from ipypublish.html.ipypublish import toc_sidebar from ipypublish.html.ipypublish import toggle_buttons from ipypublish.html.standard import content from ipypublish.html.standard import content_tagging from ipypublish.html.standard import document from ipypublish.html.standard import mathjax from ipypublish.html.standard import widgets from ipypublish.preprocessors.latex_doc_captions import LatexCaptions from ipypublish.preprocessors.latex_doc_html import LatexDocHTML from ipypublish.preprocessors.latex_doc_links import LatexDocLinks from ipypublish.preprocessors.latextags_to_html import LatexTagsToHTML from ipypublish.preprocessors.split_outputs import SplitOutputs oformat = 'HTML' config = {'TemplateExporter.filters': {'replace_string': replace_string}, 'Exporter.filters': {'replace_string': replace_string}, 'Exporter.preprocessors': [SplitOutputs, LatexDocLinks, LatexDocHTML, LatexTagsToHTML, LatexCaptions]} template = create_tpl([ document.tpl_dict, content.tpl_dict, content_tagging.tpl_dict, mathjax.tpl_dict, widgets.tpl_dict, # inout_prompt.tpl_dict, toggle_buttons.tpl_dict, toc_sidebar.tpl_dict, latex_doc.tpl_dict ])

[ "chrisj_sewell@hotmail.com" ]

chrisj_sewell@hotmail.com

003e7a2f14683e4f88eca45a7c30f8fd449eba92

aafedf44cbb6a2fd0616f01311e59bc55d19a87a

/todo/notes.py

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[ "MIT" ]

permissive

rakeshsingh/todo.txt

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refs/heads/master

2021-08-16T22:13:24.960790

2021-06-30T20:37:53

144,942,401

1

0

null

UTF-8

Python

false

4,986

py

import argparse from datetime import datetime import os import re import logging from .log import setup_logging from .exceptions import ( InvalidNotesFile, ) from .utils import( print_colorful, set_file, get_file, ) from .constants import ( DEFAULT_FILE_SEPERATOR, DEFAULT_FILE_SUFFIX, DEFAULT_NOTES_PREFIX, DEFAULT_NOTES_CATEGORY ) logger = logging.getLogger(__name__) ''' - Label it with the current month (it's best to start this at the beginning of a month if you can). Put contact information on the inside cover in case you lose it. - Start a new page every day. Put the date at the top of the page. - Metadata about the day goes in the margins. I use this to keep a log of who is front as well as taking medicine. - Write prose freely. - TODO items start with a -. Those represent things you need to do but haven't done yet. - When the item is finished, put a vertical line through the - to make it a +. - If the item either can't or won't be done, cross out the - to make it into a *. - If you have to put off a task to a later date, turn the - into a ->. If there is room, put a brief description of why it needs to be moved or when it is moved to. If there's no room feel free to write it out in prose form at the end of your page. - Notes start with a middot (·). They differ from prose as they are not complete sentences. If you need to, you can always turn them into TODO items later. - Write in pencil so you can erase mistakes. Erase carefully to avoid ripping the paper, You hardly need to use any force to erase things. - There is only one action, appending. Don't try and organize things by topic as you would on a computer. This is not a computer, this is paper. Paper works best when you append only. There is only one direction, forward. - If you need to relate a bunch of notes or todo items with a topic, skip a line and write out the topic ending with a colon. When ending the topical notes, skip another line. - Don't be afraid to write in it. If you end up using a whole notebook before the month is up, that is a success. Record insights, thoughts, feelings and things that come to your mind. You never know what will end up being useful later. - At the end of the month, look back at the things you did and summarize/index them in the remaining pages. Discover any leftover items that you haven't completed yet so you can either transfer them over to next month or discard them. It's okay to not get everything done. You may also want to scan it to back it up into the cloud. You may never reference these scans, but backups never hurt. ''' class NotesManager: """ Note file format: YYYYMMDD_[notes].txt examples: 20210101_notes.txt(default) 20180101-meeting-generic.txt 20180102_one-on-one_rohit.txt 20180102_interview_shiva-sundaram.txt """ def __init__(self): self.BASEDIR='./data/' def list(self, category=None): if category is None: category = '' for filename in os.listdir(self.BASEDIR): if category in filename: print(filename) class Note: """ Note file format: YYYYMMDD_[notes].txt examples: 20210101_notes.txt(default) 20180101-meeting-generic.txt 20180102_one-on-one_rohit.txt 20180102_interview_shiva-sundaram.txt """ def __init__(self, notes_date:str=datetime.today().strftime('%Y%m%d'),notes_prefix:str=DEFAULT_NOTES_PREFIX, notes_category:str=DEFAULT_NOTES_CATEGORY): self.notes_date = notes_date self.notes_category = notes_category self.notes_file_name = DEAFULT_FILE_SEPERATOR.join(notes_date, notes_prefix, notes_category,DEFAULT_FILE_SUFFIX) if get_file(self.notes_file_name): pass else: set_file(notes_file_name) def edit(line:int): pass def list_todos(): pass def list_notes(): pass def list_categories(): pass def list_people(): pass def get_context(): '''Provides summary of the note. What all people are mentioned in the note, what are the action items, and their statuses, what are the related topics''' pass if __name__ =='__main__': nm = NotesManager() parser = argparse.ArgumentParser() parser.add_argument("-n", "--new", action="store_true", help="create a new note\n usage: notes.py -c category detail") parser.add_argument("-l", "--list", action="store_true", help="list most recent notes") parser.add_argument("-c", "--category", help="category of the notes, e.g. meeting, todo, oneonone") parser.add_argument("-d", "--detail", help="additional details for the notes e.g. meeting subject, 1_1 person") args = parser.parse_args() if args.list: nm.list(args.category) elif args.new: nm.create(args.category, args.detail) nm.list(args.category) else: nm.list(args.category)

[ "kumar.rakesh@gmail.com" ]

kumar.rakesh@gmail.com

c02698bcbb5677d5aa1cdf687d66869a34eea59c

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/Python_codes/p02742/s024664971.py

37251941a04a71608f69d756b2f8eb6bf24e8a52

[]

no_license

Aasthaengg/IBMdataset

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refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

367,112,348

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H, W = [int(_) for _ in input().split()] if H == 1 or W == 1: ans = 1 else: ans = (H // 2) * (W // 2) * 2 if H % 2 == 1: ans += W // 2 if W % 2 == 1: ans += H // 2 if H % 2 == 1 and W % 2 == 1: ans += 1 print(ans)

[ "66529651+Aastha2104@users.noreply.github.com" ]

66529651+Aastha2104@users.noreply.github.com

7374ce7e683ccf1d4913b6f64fb04fb50b016df7

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/rsdns/tests/test_client.py

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[ "Apache-2.0" ]

permissive

masthalter/reddwarf

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HEAD

2016-11-08T16:12:16.783829

2012-04-26T22:26:56

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import httplib2 import mox import unittest from eventlet import pools from novaclient.client import HTTPClient from novaclient import exceptions from rsdns.client.dns_client import DNSaasClient ACCOUNT_ID = 1155 USERNAME = "test_user" API_KEY="key" AUTH_URL="urly" MANAGEMENT_BASE_URL="mgmter" class FakeResponse(object): def __init__(self, status): self.status = status class WhenDNSaasClientConnectsSuccessfully(unittest.TestCase): def setUp(self): self.mox = mox.Mox() def tearDown(self): self.mox.VerifyAll() def fake_auth(self, *args, **kwargs): self.auth_called = True def create_mock_client(self, fake_request_method): """ Creates a mocked DNSaasClient object, which calls "fake_request_method" instead of httplib2.request. """ class FakeHttpLib2(object): pass FakeHttpLib2.request = fake_request_method mock_client = self.mox.CreateMock(DNSaasClient) mock_client.http_pool = pools.Pool() mock_client.http_pool.create = FakeHttpLib2 mock_client.auth_token = 'token' return mock_client def test_make_request(self): kwargs = { 'headers': {}, 'body': "{}" } def fake_request(self, *args, **kwargs): return FakeResponse(200), '{"hi":"hello"}' mock_client = self.create_mock_client(fake_request) resp, body = DNSaasClient.request(mock_client, **kwargs) self.assertEqual(200, resp.status) self.assertEqual({"hi":"hello"}, body) def test_make_request_with_old_token(self): kwargs = { 'headers': {}, 'body': '{"message":"Invalid authentication token. Please renew."}' } def fake_request(self, *args, **kwargs): return FakeResponse(401), \ '{"message":"Invalid authentication token. Please renew."}' mock_client = self.create_mock_client(fake_request) mock_client.authenticate() mock_client.authenticate() mock_client.authenticate() self.mox.ReplayAll() self.assertRaises(exceptions.Unauthorized, DNSaasClient.request, mock_client, **kwargs) def test_make_request_with_old_token_2(self): kwargs = { 'headers': {}, 'body': "{}" } self.count = 0 def fake_request(_self, *args, **kwargs): self.count += 1 if self.count > 1: return FakeResponse(200), '{"hi":"hello"}' else: return FakeResponse(401), \ '{"message":"Invalid authentication token. ' \ 'Please renew."}' mock_client = self.create_mock_client(fake_request) mock_client.authenticate() self.mox.ReplayAll() resp, body = DNSaasClient.request(mock_client, **kwargs) self.assertEqual(200, resp.status) self.assertEqual({"hi":"hello"}, body)

[ "tim.simpson@rackspace.com" ]

tim.simpson@rackspace.com

89b926a667374d24e238ffecadfdddc4cc558e8b

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/configurations/configurations.py

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[]

no_license

ReubenBagtas/pytestFramework

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refs/heads/master

2020-06-02T04:06:45.139851

2019-06-09T16:34:38

null

0

null

UTF-8

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101

py

ALPHA = {} DELTA = {} PROD = {} DEMO = { 'google-homepage': 'https://www.google.com' } DEFAULT = {}

[ "reubenbagtas.com" ]

reubenbagtas.com

919cfaed50624e9fb97a068432bd5441d59ed4a1

ff9c646af161bc4d1d38093380d8e2deb54f42d1

/MiniAODAnalysis2/MiniAODAnalysis2/python/ConfFile_cfg.py

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[]

no_license

MatthiasHamer/CMS

3ab99a9008324e104913c03c2aa322a816a2d582

3594ba61e5d794917cf5e0136da743fd5e6190f9

refs/heads/master

2016-09-10T03:55:30.810030

2015-07-27T16:45:40

22,997,971

0

2

null

UTF-8

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py

import FWCore.ParameterSet.Config as cms process = cms.Process("Demo") process.load("FWCore.MessageService.MessageLogger_cfi") process.maxEvents = cms.untracked.PSet( input = cms.untracked.int32(-1) ) process.source = cms.Source("PoolSource", # replace 'myfile.root' with the source file you want to use fileNames = cms.untracked.vstring( 'file:myfile.root' ) ) process.demo = cms.EDAnalyzer('MiniAODAnalysis2' ) process.p = cms.Path(process.demo)

[ "Matthias.Hamer@cern.ch" ]

Matthias.Hamer@cern.ch

5fb4b852b0812c437735609954ef8693db355baf

75802efe7ac5e39d12c90b1ab91028f7a83f3623

/ex3_2_nonlinear_model.py

5527d8f1c41efad01b46792a6808fa3434ad63ef

[]

no_license

AOE-khkhan/PytorchZeroToAll

fbd5ecba967a4d7316667c028af37340518c451d

f8d9a392e44197de6c593dfd4b32cb192d3a6ba9

refs/heads/master

2020-09-02T12:21:32.800832

2018-05-09T12:38:52

null

0

null

UTF-8

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py

x_data = [1.0, 2.0, 3.0] y_data = [6.0, 17.0, 34.0] w2, w1, b = 1.0, 1.0, 0.0 # a random guess: random value lr = 1e-2 # a learning rate num_epochs = 100 # numbe rof epochs # our model forward pass def forward(x): return x * x * w2 + x * w1 + b # Loss function def loss(x, y): y_pred = forward(x) return (y_pred - y) * (y_pred - y) # compute gradient def gradient(x, y): dw2 = 2 * x ** 2 * (forward(x) - y) dw1 = 2 * x * (forward(x) - y) db = 1 * (forward(x) - y) return dw2, dw1, db # Before training print('predict (before training):', 4, forward(4)) # Training loop for epoch in range(num_epochs): l_ = None for x_val, y_val in zip(x_data, y_data): dw2, dw1, db = gradient(x_val, y_val) w2 += -lr * dw2 w1 += -lr * dw1 b += -lr * db l_ = loss(x_val, y_val) print("probress: {}, w2 = {}, w1 = {}, b = {}, loss = {}".format(epoch, w2, w1, b, l_)) # After training print("predict (after training)", "4 hours:", forward(4))

[ "sbkim0407@gmail.com" ]

sbkim0407@gmail.com

a911b9df049a048325fc20b414321d00fb1d10f4

64d36f801ff52465bb04b6783fab26359ffc6177

/python-basic/meta10.4.py

27ee8518f5623e3e896ed81b39d4010990855314

[]

no_license

asiachrispy/tensor

3ee3257e4c7cc518677395f81158a92339d410a2

29bbcd6350d3e4ce8363b25e86d708bce6612eac

refs/heads/master

2021-01-11T20:19:14.381846

2018-05-15T09:33:13

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py

# early stopping from numpy import loadtxt from xgboost import XGBClassifier from sklearn.cross_validation import train_test_split from sklearn.metrics import accuracy_score # load data dataset = loadtxt('pima-indians-diabetes.csv', delimiter=",") # split data into X and y X = dataset[:,0:8] Y = dataset[:,8] # split data into train and test sets seed = 7 test_size = 0.33 X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=test_size, random_state=seed) # fit model no training data model = XGBClassifier() eval_set = [(X_test, y_test)] model.fit(X_train, y_train, early_stopping_rounds=10, eval_metric="logloss", eval_set=eval_set, verbose=True) # make predictions for test data y_pred = model.predict(X_test) predictions = [round(value) for value in y_pred] # evaluate predictions accuracy = accuracy_score(y_test, predictions) print("Accuracy: %.2f%%" % (accuracy * 100.0))

[ "huangzhong@jd.com" ]

huangzhong@jd.com

10a0f0560d4f34d9937c65d9b6b1f0b3ba125dcb

4d8a66ebd98d18e407c20c93d4268b85f5548ed4

/public/http_request.py

9c15a12525a537248fd19e00abbaff92638d1ed6

[]

no_license

2295256562/API_Project

57cc40a9c79e855aa30a25db820bbffb0add6410

66b72690d765ed96a9d8ae72debeaba4fe7a5073

refs/heads/master

2022-12-14T10:20:32.753852

2019-10-10T13:40:22

213,394,060

0

null

2022-12-08T06:42:03

2019-10-07T13:42:25

Python

UTF-8

Python

false

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py

import copy import requests from config.globals import headers from config.globals import login_url from functools import lru_cache class HttpRequest: def __init__(self): self.headers_teml = { 'content-type': 'application/json', 'token': None } @lru_cache() def _login(self): """ :return: 返回token """ data = { "username": "", "password": "" } # url = login_url # r = requests.post(url=url, json=data, headers=headers) x = "ldddwlfwfwelof" return x def headers(self): headers = copy.deepcopy(self.headers_teml) headers.update({'token': self._login()}) return headers def http_request(self, url, data, http_method, header): """ http 请求基础类 :param url: 请求的url :param data: 请求数据 :param http_method: 请求方式 GET、POST :return: res """ # headers = self.headers() try: if http_method.upper() == 'GET': if data != None: res = requests.get(url, eval(data)) else: res = requests.get(url) elif http_method.upper() == 'POST': if data != None: res = requests.post(url, eval(data)) else: res = requests.post(url) else: raise NameError("你输入的请求方式不对，请你输入GET或POST") except Exception as e: raise e return res if __name__ == '__main__': C = HttpRequest().http_request('http://127.0.0.1:8000/api/reg', '{"username":"123425653","password":"1111"}', 'POST') print(C.headers)

[ "xinman.kuang@daddylab.com" ]

xinman.kuang@daddylab.com

5b6ae4546dda852369334665c79612273e580227

0eaf0d3f0e96a839f2ef37b92d4db5eddf4b5e02

/past3/e.py

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[]

no_license

silphire/atcoder

b7b02798a87048757745d99e8564397d1ca20169

f214ef92f13bc5d6b290746d5a94e2faad20d8b0

refs/heads/master

2023-09-03T17:56:30.885166

2023-09-02T14:16:24

245,110,029

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null

UTF-8

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py

n, m, q = map(int, input().split()) e = [set() for _ in range(n)] for i in range(m): u, v = map(int, input().split()) u -= 1 v -= 1 e[u].add(v) e[v].add(u) c = list(map(int, input().split())) for i in range(q): s = tuple(map(int, input().split())) vv = s[1] - 1 print(c[vv]) if s[0] == 1: for ee in e[vv]: c[ee] = c[vv] else: c[vv] = s[2]

[ "silphire@gmail.com" ]

silphire@gmail.com

9378b601770bd4c71b6a616ad9a7a895ad48a7b2

6b2a8dd202fdce77c971c412717e305e1caaac51

/solutions_5658571765186560_1/Python/StefanPochmann/D.py

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[]

no_license

alexandraback/datacollection

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076a7bc7693f3abf07bfdbdac838cb4ef65ccfcf

refs/heads/master

2021-01-24T18:27:24.417992

2017-05-23T09:23:38

84,313,442

2

4

null

UTF-8

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500

py

#f = open('D.in') #def input(): # return next(f) T = int(input()) for x in range(1, T + 1): X, R, C = map(int, input().split()) A = R * C s, S = sorted((R, C)) gabriel = A % X == 0 and \ (X == 1 or X == 2 or X == 3 and s >= 2 or X == 4 and s >= 3 or X == 5 and s >= 3 and A > 15 or X == 6 and s >= 4) print('Case #{}: {}'.format(x, 'GABRIEL' if gabriel else 'RICHARD'))

[ "eewestman@gmail.com" ]

eewestman@gmail.com

1537c16957f6dab218fa76a979c37a5ba45f9468

0b4b1dd3e5652572571128750f31d088b28b19ad

/blog/views.py

926c879a7599aea1421bbf3987c9a362189fe6b7

[]

no_license

cozynn/djangoProject

66d74d70efb8e0efeb4a2a21146e4a4473ab50e0

1bf95b7b906ce030616e994c091c9693e34c30ab

refs/heads/master

2023-02-02T19:07:37.276396

2020-12-20T19:23:02

323,114,124

0

null

UTF-8

Python

false

1,615

py

from django.shortcuts import render, get_object_or_404, redirect from django.utils import timezone from .models import Post from .forms import PostForm # Create your views here. def post_list(request): posts = Post.objects.filter(published_date__lte=timezone.now()).order_by('-published_date') return render(request, 'blog/post_list.html', {'posts': posts}) def post_detail(request, pk): post = get_object_or_404(Post, pk=pk) return render(request, 'blog/post_detail.html', {'post': post}) def post_new(request): if request.method == "POST": form = PostForm(request.POST) if form.is_valid(): post = form.save(commit=False) post.author = request.user post.published_date = timezone.now() post.save() return redirect('blog:post_detail', pk=post.pk) else: form = PostForm() return render(request, 'blog/post_edit.html', {'form': form}) def post_edit(request, pk): post = get_object_or_404(Post, pk=pk) if request.method == "POST": form = PostForm(request.POST, instance=post) if form.is_valid(): post = form.save(commit=False) post.author = request.user post.published_date = timezone.now() post.save() return redirect('blog:post_detail', pk=post.pk) else: form = PostForm(instance=post) return render(request, 'blog/post_edit.html', {'form': form}) def post_delete(request, pk): post = Post.objects.get(id=pk) post.author = request.user post.delete() return redirect('blog:post_list')

[ "cozynn@naver.com" ]

cozynn@naver.com

3c3d8847ece82de5f4ddb2fa122ea976e7da211e

2ee3a2b8971118b1a1e8c101382702d698021ad5

/weather/models.py

8372f28956277f086c9e5f53ff17faa6a968168c

[]

no_license

manikshahkataria/weather

29a34264fd281cf26758be06d19dd19bbd226cfc

1bb5160caab2dc287118ab7ed4a25cf575453ee4

refs/heads/master

2022-12-11T07:50:28.988645

2019-01-19T10:22:10

163,946,933

0

null

UTF-8

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226

py

from django.db import models class City(models.Model): name= models.CharField(max_length=25) def __str__(self): return self.name class Meta: verbose_name_plural='cities' # Create your models here.

[ "manikshah1998@gmail.com" ]

manikshah1998@gmail.com

170427ab7a1e4482bd8912d41bdaa5ebbaf1c595

fe969d059327d767c9eb442a441395fd5e389d6a

/OriginalCode-v1/create_graphs.py

09812b2133780e5e29a5211411aabf3c7a09eb36

[ "MIT" ]

permissive

Wayne-Bai/Graph

ba514418261189a89801ff10839fbfb651d98dc7

4b563c824d946471393a1c404810d6f39a49f7fb

refs/heads/master

2022-12-18T20:32:06.797842

2020-09-16T14:12:50

277,702,901

3

0

null

UTF-8

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import networkx as nx import numpy as np from utils import * from data import * from data_process import Graph_load_batch as ast_graph_load_batch def create(args): ### load datasets graphs=[] # synthetic graphs if args.graph_type=='ladder': graphs = [] for i in range(100, 201): graphs.append(nx.ladder_graph(i)) args.max_prev_node = 10 elif args.graph_type=='ladder_small': graphs = [] for i in range(2, 11): graphs.append(nx.ladder_graph(i)) args.max_prev_node = 10 elif args.graph_type=='tree': graphs = [] for i in range(2,5): for j in range(3,5): graphs.append(nx.balanced_tree(i,j)) args.max_prev_node = 256 elif args.graph_type=='caveman': # graphs = [] # for i in range(5,10): # for j in range(5,25): # for k in range(5): # graphs.append(nx.relaxed_caveman_graph(i, j, p=0.1)) graphs = [] for i in range(2, 3): for j in range(30, 81): for k in range(10): graphs.append(caveman_special(i,j, p_edge=0.3)) args.max_prev_node = 100 elif args.graph_type=='caveman_small': # graphs = [] # for i in range(2,5): # for j in range(2,6): # for k in range(10): # graphs.append(nx.relaxed_caveman_graph(i, j, p=0.1)) graphs = [] for i in range(2, 3): for j in range(6, 11): for k in range(20): graphs.append(caveman_special(i, j, p_edge=0.8)) # default 0.8 args.max_prev_node = 20 elif args.graph_type=='caveman_small_single': # graphs = [] # for i in range(2,5): # for j in range(2,6): # for k in range(10): # graphs.append(nx.relaxed_caveman_graph(i, j, p=0.1)) graphs = [] for i in range(2, 3): for j in range(8, 9): for k in range(100): graphs.append(caveman_special(i, j, p_edge=0.5)) args.max_prev_node = 20 elif args.graph_type.startswith('community'): num_communities = int(args.graph_type[-1]) print('Creating dataset with ', num_communities, ' communities') c_sizes = np.random.choice([12, 13, 14, 15, 16, 17], num_communities) #c_sizes = [15] * num_communities for k in range(3000): graphs.append(n_community(c_sizes, p_inter=0.01)) args.max_prev_node = 80 elif args.graph_type=='grid': graphs = [] for i in range(10,20): for j in range(10,20): graphs.append(nx.grid_2d_graph(i,j)) args.max_prev_node = 40 elif args.graph_type=='grid_small': graphs = [] for i in range(2,5): for j in range(2,6): graphs.append(nx.grid_2d_graph(i,j)) args.max_prev_node = 15 elif args.graph_type=='barabasi': graphs = [] for i in range(100,200): for j in range(4,5): for k in range(5): graphs.append(nx.barabasi_albert_graph(i,j)) args.max_prev_node = 130 elif args.graph_type=='barabasi_small': graphs = [] for i in range(4,21): for j in range(3,4): for k in range(10): graphs.append(nx.barabasi_albert_graph(i,j)) args.max_prev_node = 20 elif args.graph_type=='grid_big': graphs = [] for i in range(36, 46): for j in range(36, 46): graphs.append(nx.grid_2d_graph(i, j)) args.max_prev_node = 90 elif 'barabasi_noise' in args.graph_type: graphs = [] for i in range(100,101): for j in range(4,5): for k in range(500): graphs.append(nx.barabasi_albert_graph(i,j)) graphs = perturb_new(graphs,p=args.noise/10.0) args.max_prev_node = 99 # real graphs elif args.graph_type == 'enzymes': graphs= Graph_load_batch(min_num_nodes=10, name='ENZYMES') args.max_prev_node = 25 elif args.graph_type == 'enzymes_small': graphs_raw = Graph_load_batch(min_num_nodes=10, name='ENZYMES') graphs = [] for G in graphs_raw: if G.number_of_nodes()<=20: graphs.append(G) args.max_prev_node = 15 elif args.graph_type == 'protein': graphs = Graph_load_batch(min_num_nodes=20, name='PROTEINS_full') args.max_prev_node = 80 elif args.graph_type == 'DD': graphs = Graph_load_batch(min_num_nodes=100, max_num_nodes=500, name='DD',node_attributes=False,graph_labels=True) args.max_prev_node = 230 elif args.graph_type == 'citeseer': _, _, G = Graph_load(dataset='citeseer') G = max(nx.connected_component_subgraphs(G), key=len) G = nx.convert_node_labels_to_integers(G) graphs = [] for i in range(G.number_of_nodes()): G_ego = nx.ego_graph(G, i, radius=3) if G_ego.number_of_nodes() >= 50 and (G_ego.number_of_nodes() <= 400): graphs.append(G_ego) args.max_prev_node = 250 elif args.graph_type == 'citeseer_small': _, _, G = Graph_load(dataset='citeseer') G = max(nx.connected_component_subgraphs(G), key=len) G = nx.convert_node_labels_to_integers(G) graphs = [] for i in range(G.number_of_nodes()): G_ego = nx.ego_graph(G, i, radius=1) if (G_ego.number_of_nodes() >= 4) and (G_ego.number_of_nodes() <= 20): graphs.append(G_ego) shuffle(graphs) graphs = graphs[0:200] args.max_prev_node = 15 elif args.graph_type == 'AST' or args.graph_type == '200Graphs': graphs = ast_graph_load_batch(min_num_nodes=10, name=args.graph_type) # update edge_feature_output_dim if not args.max_node_feature_num: # print(type(graphs[1].nodes._nodes), graphs[1].nodes._nodes.keys()) args.max_node_feature_num = len(list(graphs[1].nodes._nodes._atlas[1].keys())) # now equals to 28 args.max_prev_node = 120 # TODO: args.max_edge_feature_num update if not args.edge_feature_output_dim: args.edge_feature_output_dim = args.max_edge_feature_num + 2 #int(args.max_prev_node * args.max_edge_feature_num) # 2 indicates two directions of edges if not args.node_feature_input_dim: args.node_feature_input_dim = args.max_node_feature_num + args.max_prev_node + args.edge_feature_output_dim # args.node_feature_input_dim = args.max_prev_node return graphs

[ "bwh.buaa@gmail.com" ]

bwh.buaa@gmail.com

8f296f11eca9ea2bac005150d59334d961aca574

2e423a357321278e08fb009812f5fd2f794f66e5

/users/migrations/0001_initial.py

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[]

no_license

rafnixg/platzigram

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e51a9d92c14c23d0de24cdda78ce9683955c43e3

refs/heads/master

2022-04-27T12:04:21.549548

2020-01-17T21:26:18

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null

2022-04-22T22:25:27

2019-09-03T21:41:51

Python

UTF-8

Python

false

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# Generated by Django 2.2.5 on 2019-09-04 17:42 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ] operations = [ migrations.CreateModel( name='Profile', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('website', models.URLField(blank=True)), ('biography', models.TextField(blank=True)), ('phone_number', models.CharField(blank=True, max_length=20)), ('picture', models.ImageField(blank=True, null=True, upload_to='users/pictures')), ('created', models.DateTimeField(auto_now_add=True)), ('modified', models.DateTimeField(auto_now=True)), ('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), ]

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import requests from datetime import datetime as dt from datetime import timedelta def request_weather(url): """request the weather from openweathermap.org API. Returns a dict of the json file""" response = requests.get(url) response_dict = response.json() return response_dict def parse_weather(weather_data_raw): """parse the useful weather data from dict of the openweathermap.org json data. returns another, slimmed down dict with the chosen elements""" parsed_weather = {} parsed_weather['sunrise'] = dt.fromtimestamp(weather_data_raw.get("city").get("sunrise")).time() parsed_weather['sunset'] = dt.fromtimestamp(weather_data_raw.get("city").get("sunset")).time() for period in weather_data_raw['list']: # limiting the parsed weather data to weather for the next day if dt.fromtimestamp(period.get("dt")).date() == dt.today().date() + timedelta(days=1): time_period = dt.fromtimestamp(period.get("dt")) # the dict key for each period is a 2-dight 24-hour time, e.g 15 for 3.00pm parsed_weather[str(time_period.time())[:2]] = [ str(time_period.time())[:2], round(period.get("main").get("temp")), period.get("weather")[0].get("main").center(15), str(period.get("clouds").get("all")).zfill(3), str(round(period.get("wind").get("speed"))).zfill(3) ] return parsed_weather

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from random import randint from math import sqrt def BozoSort(values, asc=True): if isinstance(values[0], list): list_temp = [] for i in values: for j in i: list_temp.append(j) values = list_temp num1 = randint(0, len(values)-1) num2 = randint(0, len(values)-1) temp = values[num1] values[num1] = values[num2] values[num2] = temp for i in range(0, len(values)): if i >= len(values) - 1: return values elif asc: if values[i] > values[i+1]: return BozoSort(values, asc) else: if values[i] < values[i+1]: return BozoSort(values, asc) try: n = int(input('Введите количество чисел n: ')) if 3 < n <= 100: values = list(map(int, input(f'Введите числа: ').split(' '))) if n != len(values): print('Неверное количество чисел') exit(1) print(*BozoSort(values)) print(*BozoSort(values, False)) size = int(sqrt(n)) arr = [] for i in range(0, size): arr.append(values[i*size:(i*size)+size]) print(*BozoSort(arr)) print(*BozoSort(arr, False)) print(*BozoSort(values[0:3])) print(*BozoSort(values[0:3], False)) else: print('Неверное количество чисел') exit(1) except ValueError: print("Вы ввели недопустимое значение") exit(1)

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import time from datetime import datetime from src.models.energy_sensor import EnergySensor from src.models.console_display import ConsoleDisplay from src.models.measure import Measure from src.repositories.user_repository import UserRepository from src.repositories.device_repository import DeviceRepository import config class Orchestator: def __init__(self, device, ref_voltage, ref_current, user_secret): self.sensor = EnergySensor(ref_voltage, ref_current) self.display = ConsoleDisplay() self.device = device self.user_repository = UserRepository(user_secret) self.device_repository = DeviceRepository(user_secret) self.user = self.user_repository.get_user_data() self.message = '' def loop(self): while(True): measure = Measure( self.sensor.get_voltage(), self.sensor.get_current(), self.__get_timestamp() ) try: self.device_repository.add_measure(self.device.ble_id, measure) self.message = 'Muestra enviada al servidor' except Exception as e: self.message = f'Error: {e}' self.device.set_last_measure(measure) self.display.set_ui(self.device, self.user, self.message) self.display.draw() time.sleep(config.TIME_BETWEEN_MEASUREMENTS) def __get_timestamp(self): return int(datetime.now().timestamp())

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# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from msrest.serialization import Model class AuthenticationDetailsValue(Model): """Authentication token value. :param token: Authentication token. :type token: str """ _attribute_map = { 'token': {'key': 'token', 'type': 'str'}, } def __init__(self, **kwargs): super(AuthenticationDetailsValue, self).__init__(**kwargs) self.token = kwargs.get('token', None)

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# Copyright Hybrid Logic Ltd. See LICENSE file for details. """ Run the acceptance tests. """ import sys import yaml from zope.interface import Interface, implementer from characteristic import attributes from eliot import add_destination from twisted.internet.error import ProcessTerminated from twisted.python.usage import Options, UsageError from twisted.python.filepath import FilePath from twisted.internet.defer import inlineCallbacks, returnValue from flocker.common.version import make_rpm_version from flocker.provision import PackageSource, CLOUD_PROVIDERS import flocker from flocker.provision._ssh import ( run_remotely) from flocker.provision._install import ( task_client_installation_test, install_cli, ) from effect.twisted import perform from flocker.provision._ssh._conch import make_dispatcher from .runner import run def remove_known_host(reactor, hostname): """ Remove all keys belonging to hostname from a known_hosts file. :param reactor: Reactor to use. :param bytes hostname: Remove all keys belonging to this hostname from known_hosts. """ return run(reactor, ['ssh-keygen', '-R', hostname]) def run_client_tests(reactor, node): """ Run the client acceptance tests. :param INode node: The node to run client acceptance tests against. :return int: The exit-code of trial. """ def check_result(f): f.trap(ProcessTerminated) if f.value.exitCode is not None: return f.value.exitCode else: return f return perform(make_dispatcher(reactor), run_remotely( username=node.get_default_username(), address=node.address, commands=task_client_installation_test() )).addCallbacks( callback=lambda _: 0, errback=check_result, ) class INodeRunner(Interface): """ Interface for starting and stopping nodes for acceptance testing. """ def start_nodes(reactor): """ Start nodes for running acceptance tests. :param reactor: Reactor to use. :return Deferred: Deferred which fires with a list of nodes to run tests against. """ def stop_nodes(reactor): """ Stop the nodes started by `start_nodes`. :param reactor: Reactor to use. :return Deferred: Deferred which fires when the nodes have been stopped. """ RUNNER_ATTRIBUTES = [ 'distribution', 'top_level', 'config', 'package_source' ] @implementer(INodeRunner) @attributes(RUNNER_ATTRIBUTES + [ 'provisioner', ], apply_immutable=True) class LibcloudRunner(object): """ Start and stop cloud nodes for acceptance testing. :ivar LibcloudProvioner provisioner: The provisioner to use to create the nodes. :ivar VolumeBackend volume_backend: The volume backend the nodes are configured with. """ def __init__(self): self.nodes = [] self.metadata = self.config.get('metadata', {}) try: creator = self.metadata['creator'] except KeyError: raise UsageError("Must specify creator metadata.") if not creator.isalnum(): raise UsageError( "Creator must be alphanumeric. Found {!r}".format(creator) ) self.creator = creator @inlineCallbacks def start_nodes(self, reactor, node_count): """ Start cloud nodes for client tests. :return list: List of addresses of nodes to connect to, for client tests. """ metadata = { 'purpose': 'client-testing', 'distribution': self.distribution, } metadata.update(self.metadata) for index in range(node_count): name = "client-test-%s-%d" % (self.creator, index) try: print "Creating node %d: %s" % (index, name) node = self.provisioner.create_node( name=name, distribution=self.distribution, metadata=metadata, ) except: print "Error creating node %d: %s" % (index, name) print "It may have leaked into the cloud." raise yield remove_known_host(reactor, node.address) self.nodes.append(node) del node returnValue(self.nodes) def stop_nodes(self, reactor): """ Deprovision the nodes provisioned by ``start_nodes``. """ for node in self.nodes: try: print "Destroying %s" % (node.name,) node.destroy() except Exception as e: print "Failed to destroy %s: %s" % (node.name, e) DISTRIBUTIONS = ('centos-7', 'ubuntu-14.04', 'ubuntu-15.04') PROVIDERS = tuple(sorted(CLOUD_PROVIDERS.keys())) class RunOptions(Options): description = "Run the client tests." optParameters = [ ['distribution', None, None, 'The target distribution. ' 'One of {}.'.format(', '.join(DISTRIBUTIONS))], ['provider', None, 'rackspace', 'The target provider to test against. ' 'One of {}.'.format(', '.join(PROVIDERS))], ['config-file', None, None, 'Configuration for providers.'], ['branch', None, None, 'Branch to grab packages from'], ['flocker-version', None, flocker.__version__, 'Version of flocker to install'], ['flocker-version', None, flocker.__version__, 'Version of flocker to install'], ['build-server', None, 'http://build.clusterhq.com/', 'Base URL of build server for package downloads'], ] optFlags = [ ["keep", "k", "Keep VMs around, if the tests fail."], ] synopsis = ('Usage: run-client-tests --distribution <distribution> ' '[--provider <provider>]') def __init__(self, top_level): """ :param FilePath top_level: The top-level of the flocker repository. """ Options.__init__(self) self.top_level = top_level def postOptions(self): if self['distribution'] is None: raise UsageError("Distribution required.") if self['config-file'] is not None: config_file = FilePath(self['config-file']) self['config'] = yaml.safe_load(config_file.getContent()) else: self['config'] = {} if self['flocker-version']: rpm_version = make_rpm_version(self['flocker-version']) os_version = "%s-%s" % (rpm_version.version, rpm_version.release) if os_version.endswith('.dirty'): os_version = os_version[:-len('.dirty')] else: os_version = None package_source = PackageSource( version=self['flocker-version'], os_version=os_version, branch=self['branch'], build_server=self['build-server'], ) if self['distribution'] not in DISTRIBUTIONS: raise UsageError( "Distribution %r not supported. Available distributions: %s" % (self['distribution'], ', '.join(DISTRIBUTIONS))) if self['provider'] not in PROVIDERS: raise UsageError( "Provider %r not supported. Available providers: %s" % (self['provider'], ', '.join(PROVIDERS))) if self['provider'] in CLOUD_PROVIDERS: # Configuration must include credentials etc for cloud providers. try: provider_config = self['config'][self['provider']] except KeyError: raise UsageError( "Configuration file must include a " "{!r} config stanza.".format(self['provider']) ) provisioner = CLOUD_PROVIDERS[self['provider']](**provider_config) self.runner = LibcloudRunner( config=self['config'], top_level=self.top_level, distribution=self['distribution'], package_source=package_source, provisioner=provisioner, ) from .acceptance import eliot_output @inlineCallbacks def main(reactor, args, base_path, top_level): """ :param reactor: Reactor to use. :param list args: The arguments passed to the script. :param FilePath base_path: The executable being run. :param FilePath top_level: The top-level of the flocker repository. """ options = RunOptions(top_level=top_level) add_destination(eliot_output) try: options.parseOptions(args) except UsageError as e: sys.stderr.write("%s: %s\n" % (base_path.basename(), e)) raise SystemExit(1) runner = options.runner from flocker.common.script import eliot_logging_service log_file = open("%s.log" % base_path.basename(), "a") log_writer = eliot_logging_service( log_file=log_file, reactor=reactor, capture_stdout=False) log_writer.startService() reactor.addSystemEventTrigger( 'before', 'shutdown', log_writer.stopService) try: nodes = yield runner.start_nodes(reactor, node_count=1) yield perform( make_dispatcher(reactor), install_cli(runner.package_source, nodes[0])) result = yield run_client_tests(reactor=reactor, node=nodes[0]) except: result = 1 raise finally: # Unless the tests failed, and the user asked to keep the nodes, we # delete them. if not (result != 0 and options['keep']): runner.stop_nodes(reactor) elif options['keep']: print "--keep specified, not destroying nodes." raise SystemExit(result)

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# %% import math import typing as ty from pathlib import Path import numpy as np import torch import torch.nn as nn import torch.nn.functional as F import zero import lib # %% class CrossLayer(nn.Module): def __init__(self, d, dropout): super().__init__() self.linear = nn.Linear(d, d) self.dropout = nn.Dropout(dropout) def forward(self, x0, x): return self.dropout(x0 * self.linear(x)) + x class DCNv2(nn.Module): def __init__( self, *, d_in: int, d: int, n_hidden_layers: int, n_cross_layers: int, hidden_dropout: float, cross_dropout: float, d_out: int, stacked: bool, categories: ty.Optional[ty.List[int]], d_embedding: int, ) -> None: super().__init__() if categories is not None: d_in += len(categories) * d_embedding category_offsets = torch.tensor([0] + categories[:-1]).cumsum(0) self.register_buffer('category_offsets', category_offsets) self.category_embeddings = nn.Embedding(sum(categories), d_embedding) nn.init.kaiming_uniform_(self.category_embeddings.weight, a=math.sqrt(5)) print(f'{self.category_embeddings.weight.shape=}') self.first_linear = nn.Linear(d_in, d) self.last_linear = nn.Linear(d if stacked else 2 * d, d_out) deep_layers = sum( [ [nn.Linear(d, d), nn.ReLU(True), nn.Dropout(hidden_dropout)] for _ in range(n_hidden_layers) ], [], ) cross_layers = [CrossLayer(d, cross_dropout) for _ in range(n_cross_layers)] self.deep_layers = nn.Sequential(*deep_layers) self.cross_layers = nn.ModuleList(cross_layers) self.stacked = stacked def forward(self, x_num, x_cat): if x_cat is not None: x_cat = self.category_embeddings(x_cat + self.category_offsets[None]) x = torch.cat([x_num, x_cat.view(x_cat.size(0), -1)], dim=-1) else: x = x_num x = self.first_linear(x) x_cross = x for cross_layer in self.cross_layers: x_cross = cross_layer(x, x_cross) if self.stacked: return self.last_linear(self.deep_layers(x_cross)).squeeze(1) else: return self.last_linear( torch.cat([x_cross, self.deep_layers(x)], dim=1) ).squeeze(1) # %% args, output = lib.load_config() # %% zero.set_randomness(args['seed']) dataset_dir = lib.get_path(args['data']['path']) stats: ty.Dict[str, ty.Any] = { 'dataset': dataset_dir.name, 'algorithm': Path(__file__).stem, **lib.load_json(output / 'stats.json'), } timer = zero.Timer() timer.run() D = lib.Dataset.from_dir(dataset_dir) X = D.build_X( normalization=args['data'].get('normalization'), num_nan_policy='mean', cat_nan_policy='new', cat_policy=args['data'].get('cat_policy', 'counter'), cat_min_frequency=args['data'].get('cat_min_frequency', 0.0), seed=args['seed'], ) if not isinstance(X, tuple): X = (X, None) zero.set_randomness(args['seed']) Y, y_info = D.build_y(args['data'].get('y_policy')) lib.dump_pickle(y_info, output / 'y_info.pickle') X = tuple(None if x is None else lib.to_tensors(x) for x in X) Y = lib.to_tensors(Y) device = lib.get_device() if device.type != 'cpu': X = tuple(None if x is None else {k: v.to(device) for k, v in x.items()} for x in X) Y_device = {k: v.to(device) for k, v in Y.items()} else: Y_device = Y X_num, X_cat = X if not D.is_multiclass: Y_device = {k: v.float() for k, v in Y_device.items()} train_size = len(X_num[lib.TRAIN]) batch_size = args['training']['batch_size'] epoch_size = stats['epoch_size'] = math.ceil(train_size / batch_size) loss_fn = ( F.binary_cross_entropy_with_logits if D.is_binclass else F.cross_entropy if D.is_multiclass else F.mse_loss ) args['model'].setdefault('d_embedding', None) model = DCNv2( d_in=X_num[lib.TRAIN].shape[1], d_out=D.info['n_classes'] if D.is_multiclass else 1, categories=lib.get_categories(X_cat), **args['model'], ).to(device) stats['n_parameters'] = lib.get_n_parameters(model) optimizer = lib.make_optimizer( args['training']['optimizer'], model.parameters(), args['training']['lr'], args['training']['weight_decay'], ) stream = zero.Stream(lib.IndexLoader(train_size, batch_size, True, device)) progress = zero.ProgressTracker(args['training']['patience']) training_log = {lib.TRAIN: [], lib.VAL: [], lib.TEST: []} timer = zero.Timer() checkpoint_path = output / 'checkpoint.pt' def print_epoch_info(): print(f'\n>>> Epoch {stream.epoch} | {lib.format_seconds(timer())} | {output}') print( ' | '.join( f'{k} = {v}' for k, v in { 'lr': lib.get_lr(optimizer), 'batch_size': batch_size, 'epoch_size': stats['epoch_size'], 'n_parameters': stats['n_parameters'], }.items() ) ) @torch.no_grad() def evaluate(parts): model.eval() metrics = {} predictions = {} for part in parts: predictions[part] = ( torch.cat( [ model(X_num[part][idx], None if X_cat is None else X_cat[part][idx]) for idx in lib.IndexLoader( len(X_num[part]), args['training']['eval_batch_size'], False, device, ) ] ) .cpu() .numpy() ) try: metrics[part] = lib.calculate_metrics( D.info['task_type'], Y[part].numpy(), # type: ignore[code] predictions[part], # type: ignore[code] 'logits', y_info, ) except ValueError as err: assert ( 'Target scores need to be probabilities for multiclass roc_auc' in str(err) ) metrics[part] = {'score': -999999999.0} for part, part_metrics in metrics.items(): print(f'[{part:<5}]', lib.make_summary(part_metrics)) return metrics, predictions def save_checkpoint(final): torch.save( { 'model': model.state_dict(), 'optimizer': optimizer.state_dict(), 'stream': stream.state_dict(), 'random_state': zero.get_random_state(), **{ x: globals()[x] for x in [ 'progress', 'stats', 'timer', 'training_log', ] }, }, checkpoint_path, ) lib.dump_stats(stats, output, final) lib.backup_output(output) # %% timer.run() for epoch in stream.epochs(args['training']['n_epochs']): print_epoch_info() model.train() epoch_losses = [] for batch_idx in epoch: optimizer.zero_grad() loss = loss_fn( model( X_num[lib.TRAIN][batch_idx], None if X_cat is None else X_cat[lib.TRAIN][batch_idx], ), Y_device[lib.TRAIN][batch_idx], ) if loss.isnan(): print('Loss is nan!') break loss.backward() optimizer.step() epoch_losses.append(loss.detach()) if loss.isnan(): break epoch_losses = torch.stack(epoch_losses).tolist() training_log[lib.TRAIN].extend(epoch_losses) print(f'[{lib.TRAIN}] loss = {round(sum(epoch_losses) / len(epoch_losses), 3)}') metrics, predictions = evaluate(lib.PARTS) for k, v in metrics.items(): training_log[k].append(v) progress.update(metrics[lib.VAL]['score']) if progress.success: print('New best epoch!') stats['best_epoch'] = stream.epoch stats['metrics'] = metrics save_checkpoint(False) for k, v in predictions.items(): np.save(output / f'p_{k}.npy', v) elif progress.fail: break # %% print('\nRunning the final evaluation...') model.load_state_dict(torch.load(checkpoint_path)['model']) stats['metrics'], predictions = evaluate(lib.PARTS) for k, v in predictions.items(): np.save(output / f'p_{k}.npy', v) stats['time'] = lib.format_seconds(timer()) save_checkpoint(True) print('Done!')

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import matplotlib.pyplot as plt # inputs a = float (input ("Enter a value: ")) b = float (input ("Enter b value: ")) ax = a + b ay = a - b bx = a - b by = a + b # Internal division section formula Px = ((a * a) + (b * b)) / (a + b) Py = ((a * a) + (2 * a * b) - (b * b)) / (a + b) # External division section formula Qx = ((a * a) - (2 * a * b) - (b * b)) / (a - b) Qy = ((a * a) + (b * b)) / (a - b) plt.figure(1) plt.scatter([ax, bx, Px], [ay, by, Py], color= 'r') plt.text(ax, ay + 0.5, '({},{})'.format(ax, ay)) plt.text(bx, by + 0.5, '({},{})'.format(bx, by)) plt.text(Px, Py + 0.5, '({},{})'.format(Px, Py)) plt.plot([ax, bx, Px], [ay, by, Py]) plt.title("Internal Division Section") plt.xlabel("X- Axis") plt.ylabel("Y- Axis") plt.grid(True) plt.show() plt.figure(2) plt.scatter([ax, bx, Qx], [ay, by, Qy], color= 'r') plt.text(ax, ay + 0.5, '({},{})'.format(ax, ay)) plt.text(bx, by + 0.5, '({},{})'.format(bx, by)) plt.text(Qx, Qy + 0.5, '({},{})'.format(Qx, Qy)) plt.plot([ax, bx, Qx], [ay, by, Qy]) plt.title("External Division Section") plt.xlabel("X- Axis") plt.ylabel("Y- Axis") plt.grid(True) plt.show() # Final coordinates internal_coordinates = (Px, Py) external_coordinates = (Qx, Qy) # Printing outputs print ("(Px, Py) = " + str (internal_coordinates)) print ("(Qx, Qy) = " + str (external_coordinates))

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Diptasri.noreply@github.com

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refs/heads/master

2023-02-20T20:32:00.527084

2021-01-25T15:16:07

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from django import forms from django.contrib.auth.forms import UserCreationForm, UserChangeForm from .models import CustomUser class UserForm(forms.ModelForm): """ Formulário para cadastrar usuário""" username = forms.CharField( label='Usuário', error_messages= { 'invalid': 'Nome de usuário inválido, informe apenas letras, números ou @, ., +, -, _', 'max_length': 'Você excedeu o limite de caracteres.', 'unique': 'Nome de usuário já existe.' }, help_text= "Requeridos 150 caracteres ou menos. Letras, dígitos e @ /. / + / - / _ apenas", widget=forms.TextInput(attrs={'placeholder':'Username'}) ) email = forms.EmailField( label='E-mail', error_messages={'invalid': 'E-mail inválido.'}, help_text='user@dominio.com', widget=forms.TextInput(attrs={'placeholder':'E-mail'}) ) first_name = forms.CharField( label='Nome', error_messages={'max_length': 'Nome não pode ter mais de 30 caracteres'}, widget=forms.TextInput(attrs={'placeholder':'Nome'}) ) last_name = forms.CharField( label='Sobrenome', error_messages={'max_length': 'Sobrenome não pode ter mais de 150 caracteres'}, widget=forms.TextInput(attrs={'placeholder':'Sobrenome'}) ) telefone = forms.CharField( label='Telefone', help_text='(xx) xxxxx-xxxx', widget=forms.TextInput(attrs={'placeholder':'Telefone...'}) ) password = forms.CharField( label='Senha', help_text="Digite uma senha segura", widget=forms.PasswordInput(attrs={'placeholder':'Senha'}) ) password2 = forms.CharField( label='Confirmar senha', widget=forms.PasswordInput(attrs={'placeholder':'Repetir senha'}) ) class Meta: model = CustomUser fields = ( 'username', 'email', 'first_name', 'last_name', 'telefone' ) def clean_password2(self): passwords = self.cleaned_data if passwords['password2'] != passwords['password']: raise forms.ValidationError("Senhas diferentes") return passwords['password2'] def save(self, commit=True): user = CustomUser.objects.create_user( username=self.cleaned_data['username'], email=self.cleaned_data['email'], password=self.cleaned_data['password'], first_name=self.cleaned_data['first_name'], last_name=self.cleaned_data['last_name'], telefone=self.cleaned_data['telefone'] ) return user class UserProfileForm(forms.ModelForm): """ Formulário para atualizar dados do usuário""" facebook = forms.CharField(widget=forms.TextInput(attrs={'placeholder': 'https://www.facebook.com/seu_username'}), required=False) instagram = forms.CharField(widget=forms.TextInput(attrs={'placeholder': 'https://www.instagram.com/seu_username'}), required=False) twitter = forms.CharField(widget=forms.TextInput(attrs={'placeholder': 'https://www.twitter.com/seu_username'}), required=False) class Meta: model = CustomUser fields = fields = ( 'username', 'email', 'first_name', 'last_name', 'telefone', 'facebook', 'instagram', 'twitter', 'bio' ) class CustomUserCreateForm(UserCreationForm): """ Formulário para criar usuário no painel administrativo""" class Meta: model = CustomUser fields = ('first_name', 'last_name', 'telefone') labels = {'username': 'Username/E-mail'} def save(self, commit=True): user = super().save(commit=False) user.set_password(self.cleaned_data["password1"]) user.username = self.cleaned_data["username"] if commit: user.save() return user class CustomUserChangeForm(UserChangeForm): """ Atualizar usuário no painel administrativo""" class Meta: model = CustomUser fields = ('email', 'first_name', 'last_name', 'telefone')

[ "thiagolsmail@gmail.com" ]

thiagolsmail@gmail.com

21d962029b74b4eafe0c5b512082596bdf3800f2

95e7cf518b8d71270a7de6e7c7254861010f5035

/garage/tf/algos/batch_polopt.py

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reslthrowaway/garage

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refs/heads/master

2020-03-28T08:32:58.835060

2018-09-08T21:55:41

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import time import tensorflow as tf from garage.algos import RLAlgorithm import garage.misc.logger as logger from garage.tf.plotter import Plotter from garage.tf.samplers import BatchSampler from garage.tf.samplers import VectorizedSampler class BatchPolopt(RLAlgorithm): """ Base class for batch sampling-based policy optimization methods. This includes various policy gradient methods like vpg, npg, ppo, trpo, etc. """ def __init__(self, env, policy, baseline, scope=None, n_itr=500, start_itr=0, batch_size=5000, max_path_length=500, discount=0.99, gae_lambda=1, plot=False, pause_for_plot=False, center_adv=True, positive_adv=False, store_paths=False, whole_paths=True, fixed_horizon=False, sampler_cls=None, sampler_args=None, force_batch_sampler=False, **kwargs): """ :param env: Environment :param policy: Policy :type policy: Policy :param baseline: Baseline :param scope: Scope for identifying the algorithm. Must be specified if running multiple algorithms simultaneously, each using different environments and policies :param n_itr: Number of iterations. :param start_itr: Starting iteration. :param batch_size: Number of samples per iteration. :param max_path_length: Maximum length of a single rollout. :param discount: Discount. :param gae_lambda: Lambda used for generalized advantage estimation. :param plot: Plot evaluation run after each iteration. :param pause_for_plot: Whether to pause before contiuing when plotting. :param center_adv: Whether to rescale the advantages so that they have mean 0 and standard deviation 1. :param positive_adv: Whether to shift the advantages so that they are always positive. When used in conjunction with center_adv the advantages will be standardized before shifting. :param store_paths: Whether to save all paths data to the snapshot. :return: """ self.env = env self.policy = policy self.baseline = baseline self.scope = scope self.n_itr = n_itr self.start_itr = start_itr self.batch_size = batch_size self.max_path_length = max_path_length self.discount = discount self.gae_lambda = gae_lambda self.plot = plot self.pause_for_plot = pause_for_plot self.center_adv = center_adv self.positive_adv = positive_adv self.store_paths = store_paths self.whole_paths = whole_paths self.fixed_horizon = fixed_horizon if sampler_cls is None: if self.policy.vectorized and not force_batch_sampler: sampler_cls = VectorizedSampler else: sampler_cls = BatchSampler if sampler_args is None: sampler_args = dict() self.sampler = sampler_cls(self, **sampler_args) self.init_opt() def start_worker(self, sess): self.sampler.start_worker() if self.plot: self.plotter = Plotter(self.env, self.policy, sess) self.plotter.start() def shutdown_worker(self): self.sampler.shutdown_worker() if self.plot: self.plotter.shutdown() def obtain_samples(self, itr): return self.sampler.obtain_samples(itr) def process_samples(self, itr, paths): return self.sampler.process_samples(itr, paths) def train(self, sess=None): created_session = True if (sess is None) else False if sess is None: sess = tf.Session() sess.__enter__() sess.run(tf.global_variables_initializer()) self.start_worker(sess) start_time = time.time() last_average_return = None for itr in range(self.start_itr, self.n_itr): itr_start_time = time.time() with logger.prefix('itr #%d | ' % itr): logger.log("Obtaining samples...") paths = self.obtain_samples(itr) logger.log("Processing samples...") samples_data = self.process_samples(itr, paths) last_average_return = samples_data["average_return"] logger.log("Logging diagnostics...") self.log_diagnostics(paths) logger.log("Optimizing policy...") self.optimize_policy(itr, samples_data) logger.log("Saving snapshot...") params = self.get_itr_snapshot(itr, samples_data) if self.store_paths: params["paths"] = samples_data["paths"] logger.save_itr_params(itr, params) logger.log("Saved") logger.record_tabular('Time', time.time() - start_time) logger.record_tabular('ItrTime', time.time() - itr_start_time) logger.dump_tabular(with_prefix=False) if self.plot: self.plotter.update_plot(self.policy, self.max_path_length) if self.pause_for_plot: input("Plotting evaluation run: Press Enter to " "continue...") self.shutdown_worker() if created_session: sess.close() return last_average_return def log_diagnostics(self, paths): self.policy.log_diagnostics(paths) self.baseline.log_diagnostics(paths) def init_opt(self): """ Initialize the optimization procedure. If using tensorflow, this may include declaring all the variables and compiling functions """ raise NotImplementedError def get_itr_snapshot(self, itr, samples_data): """ Returns all the data that should be saved in the snapshot for this iteration. """ raise NotImplementedError def optimize_policy(self, itr, samples_data): raise NotImplementedError

[ "reslthrowaway@yandex.com" ]

reslthrowaway@yandex.com

8602e4c68c80a37d2046a827fca331f3acf97906

c1cad053e9fbfe536722c13338fff63e471ff252

/Next.tech/Analyzing-Text-Data/solution/chunking.py

58c9c3ededb97de3f1ce991ac04f48ebe62345aa

[]

no_license

adataholic/Datascience

9bedfda47c3b84e72e9833b293ce2f602ca2ec9f

766a34c480eec61afdd0f485a4e77428cf3eba95

refs/heads/master

2020-12-27T01:33:55.458858

2020-01-06T23:48:28

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py

import nltk nltk.download('brown') import numpy as np from nltk.corpus import brown # Split a text into chunks def splitter(data, num_words): words = data.split(' ') output = [] cur_count = 0 cur_words = [] for word in words: cur_words.append(word) cur_count += 1 if cur_count == num_words: output.append(' '.join(cur_words)) cur_words = [] cur_count = 0 output.append(' '.join(cur_words) ) return output if __name__=='__main__': # Read the data from the Brown corpus data = ' '.join(brown.words()[:10000]) # Number of words in each chunk num_words = 1700 chunks = [] counter = 0 text_chunks = splitter(data, num_words) print "Number of text chunks =", len(text_chunks)

[ "akshaymm13b034@gmail.com" ]

akshaymm13b034@gmail.com

7c07de17053aa19697fa3b8ec39bfe5a624ff542

feca84ca57eee5045a1235006e472b4766ca3b06

/flaskapi/graphapp01.py

083c083606a6b6a7422cad37d931d98e190b6d4e

[]

no_license

Chasbott182/mycode

1b89fa5d1d94a4ff39c8ce98b046189a2d9df10f

5afcd3cc32feee16e0fecc85a6165aaa01f60774

refs/heads/main

2023-07-14T17:06:34.618830

2021-08-13T20:46:59

392,015,327

0

null

UTF-8

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py

#!/usr/bin/python3 import numpy as np # number operations import yaml # pyyaml for yaml import re # regex import paramiko # ssh into servers from flask import Flask, render_template import matplotlib.pyplot as plt def sshlogin(ip, un, passw): sshsession = paramiko.SSHClient() sshsession.set_missing_host_key_policy(paramiko.AutoAddPolicy()) sshsession.connect(hostname=ip, username=un, password=passw) ssh_stdin, ssh_stdout, ssh_stderr = sshsession.exec_command("cat /proc/uptime") sshresult = ssh_stdout.read().decode('utf-8').split()[0] with open("sshresult", "w") as myfile: myfile.write(sshresult) days = (int(float(sshresult)) / 86400) # convert uptime in sec to days sshsession.close() print(days) return days app = Flask(__name__) @app.route("/graphin") def graphin(): with open("C:\mycode\sshpass.yml") as sshpass: # creds for our servers creds = yaml.load(sshpass) svruptime = [] xtick = [] for cred in creds: xtick.append(cred['ip']) resp = sshlogin(cred['ip'], cred['un'], cred['passw']) svruptime.append(resp) xtick = tuple(xtick) # create a tuple svruptime = tuple(svruptime) # graphin N = 2 # total number of bars ind = np.arange(N) # the x locations for the groups width = 0.35 # the width of the bars: can also be len(x) sequence p1 = plt.bar(ind, svruptime, width) plt.ylabel('Uptime in Days') plt.title('Uptime of Servers in Days') plt.xticks(ind, xtick) plt.yticks(np.arange(0, 20, 1)) # prob want to turn this into a log scale plt.savefig('static/status.png') # might want to save this with timestamp for history purposes return render_template("graph.html") if __name__ == "__main__": app.run(host="0.0.0.0", port=3000)

[ "chasbott182@gmail.com" ]

chasbott182@gmail.com

3ffd2a81defe2dd17e7c4f0ee0d2e75c6f233e90

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/hud.py

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permissive

marax27/pyNoid

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refs/heads/master

2021-09-04T11:19:22.625982

2018-01-18T07:03:43

2018-01-18T07:08:23

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#!/usr/bin/python3 from constants import Constants from vec2 import vec2 import sdl2.sdlttf import sdl2.ext import sdl2 import misc class UIElement: def __init__(self): self.position = vec2(0,0) self.size = vec2(0,0) def centerHorizontally(self): self.position.x = (Constants.WINDOW_SIZE.x - self.size[0])//2 def centerVertically(self): self.position.y = (Constants.WINDOW_SIZE.y - self.size[1])//2 def center(self): self.centerHorizontally() self.centerVertically() class Text(UIElement): """Single piece of text.""" font_manager = sdl2.ext.FontManager('resources/vga_437.ttf', size=24) def __init__(self, text, renderer, size=None, color=None): self.position = vec2(0,0) self.texture = None self.load(text, renderer, size, color) def render(self, renderer, pos=None): """Render the text, using the renderer.""" r = sdl2.SDL_Rect(self.position[0] if not pos else pos[0], self.position[1] if not pos else pos[1], self.size[0], self.size[1]) sdl2.SDL_RenderCopy(renderer.renderer, self.texture, None, r) def load(self, text, renderer, size=None, color=None): """Update a Text object.""" if self.texture: sdl2.SDL_DestroyTexture(self.texture) #That does the trick. surf = Text.font_manager.render(text, size=size, color=color) sprite = sdl2.ext.SoftwareSprite(surf, True) self.size = (surf.w, surf.h) self.texture = sdl2.SDL_CreateTextureFromSurface(renderer.renderer, sprite.surface) class Button(UIElement): """Button class.""" IDLE, HOVER, PRESSED = 0x1001, 0x1002, 0x1003 @staticmethod def buildClickableText(message, renderer, idle_color, pressed_color, hover_color, size, pos=None): """Generates a text label that will change color according to whether it's pressed or not.""" return Button( Text(message, renderer, size, idle_color), Text(message, renderer, size, pressed_color), Text(message, renderer, size, hover_color), pos ) def __init__(self, idle_state, pressed_state, hover_state=None, pos=None): self.states = {} self.states[self.IDLE] = idle_state self.states[self.HOVER] = hover_state if hover_state is not None else idle_state self.states[self.PRESSED] = pressed_state self.state = self.IDLE self.position = pos if pos else vec2(0, 0) # Size restriction. if self.states[self.IDLE].size != self.states[self.HOVER].size or self.states[self.IDLE].size != self.states[self.PRESSED].size: raise ValueError() self.size = self.states[self.IDLE].size def render(self, renderer): self.states[self.state].render(renderer, self.position) def handleEvent(self, event): """Handle mouse events.""" mx, my = misc.getMousePos() if ((self.position[0] <= mx < self.position[0] + self.size[0]) and (self.position[1] <= my < self.position[1] + self.size[1])): if event.type == sdl2.SDL_MOUSEBUTTONDOWN: self.state = self.PRESSED else: self.state = self.HOVER else: self.state = self.IDLE def isPressed(self): return self.state == self.PRESSED class VerticalContainer: def __init__(self, elements=[], y_pos=0): self.elem = elements self.y_pos = y_pos self.adjust() def adjust(self): if len(self.elem): self.elem[0].position.y = self.y_pos for i in range(1, len(self.elem)): self.elem[i].position.y = self.elem[i-1].position.y+self.elem[i-1].size[1] for i in self.elem: i.centerHorizontally() def render(self, renderer): for i in self.elem: i.render(renderer)

[ "kacpert314@gmail.com" ]

kacpert314@gmail.com

6919b3a14f65b0c108aa619c12b7e531c0c04e51

6328387281d1b2b0bec13d51916d916fea1e7351

/myvenv/bin/easy_install-3.7

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[]

no_license

MedApplive/my-first-blog

81e40789efe28cf99c7a342f7b8c48e879e70b4c

0268eb6a64aa2733552b285accceba8cb82cd64d

refs/heads/master

2020-05-01T11:58:28.305631

2020-01-20T17:04:57

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null

2019-09-30T14:45:40

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#!/home/maurice/Documents/djangogirls/myvenv/bin/python3 # -*- coding: utf-8 -*- import re import sys from setuptools.command.easy_install import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit(main())

[ "msourir@gmail.com" ]

msourir@gmail.com

339b6652e6902305375b21f8ec23ad0e0f230c76

6ddd0cfdbaca412ee2b3a7a01e7fcaad63550ac2

/Python GUI/GUI window with various label,buttons,colors,font.py

b0274813b6a312766b548cf1260d2688c7d120c0

[]

no_license

pranshu798/Python-programs

b302be9c9fd3aaf66824857bdb8bb2d9b8a9b5de

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refs/heads/master

2022-12-08T15:52:21.625098

2020-09-14T11:57:26

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#Python program to demontrate complete details of GUI window from tkinter import * gui = Tk() def hello(): c = a.get() guil3 = Label(text=c, fg='red', bg='yellow', font=10).pack() def delete(): guil4 = Label(text='Delete', fg='red', bg='yellow', font=10).pack() a = StringVar() gui.title("Aliyas Shaik Button Program") gui.geometry("500x500+100+100") guil1 = Label(text='Label One', fg='red', bg='yellow', font=10).pack() button1 = Button(text='Enter', fg='red', bg='yellow', command=hello, font=10).pack() button2 = Button(text='Delete', fg='red', bg='yellow', command=delete, font=10).pack() # Place method places label @ specified place within the window text = Entry(textvariable=a).pack() gui.mainloop()

[ "pranshuverma798@gmail.com" ]

pranshuverma798@gmail.com

8402be75cce1ddbd62ff54e6ca1af746d547ba7e

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p04044/s043863854.py

77675a21e84977960d992326c6742602cc68d034

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

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N, L = map(int,input().split()) word = [] count = 0 while N > count: S = input() word.append(S) count += 1 word = sorted(word) ans = ''.join(word) print(ans)

[ "66529651+Aastha2104@users.noreply.github.com" ]

66529651+Aastha2104@users.noreply.github.com

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/poketypes/basic.py

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[ "BSD-2-Clause" ]

permissive

GrenderG/PokeDuino

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refs/heads/master

2021-06-01T02:33:46.419676

2016-06-29T09:57:47

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NOASSERTION

2020-08-05T16:44:29

2020-08-05T16:44:28

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import ctypes from . import encoding class PokeMetaStructure(type(ctypes.BigEndianStructure)): def __new__(metacls, name, bases, dct): cls = super().__new__(metacls, name, bases, dct) for member, adapter_type in cls._adapters_: cls.buildProperty(member, adapter_type) return cls def buildProperty(cls, member, adapter_type): def get(self): return adapter_type(getattr(self, member)) def set(self, value): if isinstance(value, adapter_type): setattr(self, member, value.value) else: setattr(self, member, value) if member.startswith("_"): property_name = member[1:] else: property_name = member + "_adapter" setattr(cls, property_name, property(fget=get, fset=set, doc="%s adapter to member %s" % (adapter_type.__name__, member))) class PokeStructure(ctypes.BigEndianStructure, metaclass=PokeMetaStructure): _pack_ = 1 _adapters_ = [] @classmethod def fromBytes(cls, data): return cls.from_buffer_copy(data) def bytes(self): return ctypes.string_at(ctypes.byref(self), ctypes.sizeof(self)) def bytecount(self): return ctypes.sizeof(self) def Pokearray(length): # okay, I learned. # It's not possible to use a custom base class # in a ctypes.Structure field. Forget about it @classmethod def fromBytes(cls, data): return cls(*data) def asBytes(self): return bytes(iter(self)) t = ctypes.c_uint8 * length t.fromBytes = fromBytes t.bytes = asBytes return t def Pokestring(length): @classmethod def fromString(cls, data, fillUp=False): encoded = encoding.encode(data) + encoding.ENDCHAR if fillUp: encoded = encoded.ljust(length, encoding.ENDCHAR) return cls(*encoded[:length]) def toString(self): encoded = self.bytes().partition(encoding.ENDCHAR)[0] return encoding.decode(encoded) t = Pokearray(length) t.fromString = fromString t.toString = toString return t def PaddingBytes(length): return ("padding", Pokearray(length))

[ "sven.koehler@student.hpi.uni-potsdam.de" ]

sven.koehler@student.hpi.uni-potsdam.de

e18bf50cd5e5c0cee6e3670840430470da5195de

f1e4a8ab1ce478b3a95e8e8a74faa16409ac86e2

/lambdas/InitializeDBCustomLambda/index.py

7d26789efb9fa031b09f6bbee5909f5d6e904771

[]

no_license

Ryanjlowe/pinpoint-engagement-scoring

6b761fd7ada905db251d42ec1d4b47c0e27ad810

a75f29f687c799ed6e0125c3c0044cc39c9dd2d5

refs/heads/master

2020-09-30T05:02:39.204421

2019-12-13T17:41:44

227,209,468

1

0

null

UTF-8

Python

false

3,868

py

import json import boto3 import logging import os from botocore.vendored import requests dynamodb = boto3.resource('dynamodb') PINPOINT_PROJECT_ID = os.environ.get('PINPOINT_PROJECT_ID') scoring_definition_table = dynamodb.Table(os.environ.get('SCORING_DEFINITION_TABLE')) def lambda_handler(event, context): global log_level log_level = str(os.environ.get('LOG_LEVEL')).upper() if log_level not in [ 'DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL' ]: log_level = 'ERROR' logging.getLogger().setLevel(log_level) logging.info(event) try: populate_score_definition('_email.click', 50) populate_score_definition('_email.open', 10) populate_score_definition('_email.delivered', 2) populate_score_definition('_email.hardbounce', -1000) populate_score_definition('_email.complaint', -1000) populate_score_definition('_email.unsubscribe', -500) populate_score_definition('_SMS.SUCCESS', 2) populate_score_definition('_SMS.OPTOUT', -500) populate_score_definition('_campaign.send', 2) populate_score_definition('_campaign.opened_notification', 50) populate_score_definition('_campaign.received_foreground', 2) populate_score_definition('_campaign.received_background', 2) populate_score_definition('_session.start', 2) populate_score_definition('_userauth.sign_up', 50) populate_score_definition('_monetization.purchase', 100) except Exception as e: logging.error('Received Error while populating default values: %s', e) send(event, context, 'FAILED', {}) else: send(event, context, 'SUCCESS', {}) def populate_score_definition(event_type, score_offset): try: scoring_definition_table.put_item( Item={ 'EventType': event_type, 'PinpointProjectId': PINPOINT_PROJECT_ID, 'ScoreOffset':score_offset } ) except Exception as e: logging.error('Received Error while populate_score_definition: %s', e) raise e ###### # Following taken from: https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/cfn-lambda-function-code-cfnresponsemodule.html#w2ab1c20c25c14b9c15 ###### # Copyright 2016 Amazon Web Services, Inc. or its affiliates. All Rights Reserved. # This file is licensed to you under the AWS Customer Agreement (the "License"). # You may not use this file except in compliance with the License. # A copy of the License is located at http://aws.amazon.com/agreement/ . # This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, express or implied. # See the License for the specific language governing permissions and limitations under the License. def send(event, context, responseStatus, responseData, physicalResourceId=None, noEcho=False): responseUrl = event['ResponseURL'] print(responseUrl) responseBody = {} responseBody['Status'] = responseStatus responseBody['Reason'] = 'See the details in CloudWatch Log Stream: ' + context.log_stream_name responseBody['PhysicalResourceId'] = physicalResourceId or context.log_stream_name responseBody['StackId'] = event['StackId'] responseBody['RequestId'] = event['RequestId'] responseBody['LogicalResourceId'] = event['LogicalResourceId'] responseBody['NoEcho'] = noEcho responseBody['Data'] = responseData json_responseBody = json.dumps(responseBody) print("Response body:\n" + json_responseBody) headers = { 'content-type' : '', 'content-length' : str(len(json_responseBody)) } try: response = requests.put(responseUrl, data=json_responseBody, headers=headers) print("Status code: " + response.reason) except Exception as e: print("send(..) failed executing requests.put(..): " + str(e))

[ "rjlowe@amazon.com" ]

rjlowe@amazon.com

e9dfc09020ce8682f64b107a1c8ad0d41d060345

b1b520c9bae5b241405dbc1a6b25ef928877c317

/defangIpAddress.py

7bed80a95e1468a02ca4701cc4900f4fa9552b8a

[]

no_license

TBobcat/Leetcode

0ee5d06be3f7f10077961a8e3aedcd28fe4cb85a

3b6e3d38ac2d5158329a9444ad7e7e7ee9d07176

refs/heads/main

2023-06-04T10:40:00.275728

2021-06-16T23:05:35

375,470,361

0

null

UTF-8

Python

false

660

py

def defangIPaddr(address): """ :type address: str :rtype: str """ ## use list(str) and str.join(list_str) ## join can also be used like this ## 'abc'.join(address1.split('.')) -> '1abc1abc1abc1' ## str.replace() would also be useful res = "" list_address = list(address) for i,char in enumerate(list_address): if char == ".": list_address[i] = "[.]" res = res.join(list_address) return res if __name__ == '__main__': address1 = "1.1.1.1" address2 = "255.100.50.0" print(defangIPaddr(address1)) print(defangIPaddr(address2)) else: pass

[ "xiangyuantech@gmail.com" ]

xiangyuantech@gmail.com

37dafa17ed9dc319a258358248dd28b2bbf33390

ee8c4c954b7c1711899b6d2527bdb12b5c79c9be

/assessment2/amazon/run/core/controllers/old.py

b834b8f7e61106d74a5d8d14bccffde5155b3848

[]

no_license

sqlconsult/byte

02ac9899aebea4475614969b594bfe2992ffe29a

548f6cb5038e927b54adca29caf02c981fdcecfc

refs/heads/master

2021-01-25T14:45:42.120220

2018-08-11T23:45:31

117,135,069

0

null

UTF-8

Python

false

360

py

#!/usr/bin/env python3 from flask import Blueprint, Flask, render_template, request, url_for controller = Blueprint('old', __name__, url_prefix='/old') # @controller.route('/<string:title>', methods=['GET']) # def lookup(title): # if title == 'Republic': # TODO 2 # return render_template('republic.html') # TODO 2 # else: # pass

[ "sqlconsult@hotmail.com" ]

sqlconsult@hotmail.com

4106443cb73c63c91456d1feb0e571e206168629

0ad1a9530f0765b07d568095cb1534babc4432f5

/utils/db.py

0391f7d7acc6be817a2340825b6016c54fba89ab

[ "MIT" ]

permissive

bryceweiner/Infiniti

18acc471b5882bd676e61b840bff793c22d6c272

5ea829dfa26c0948970329651d3cacff7788d116

refs/heads/master

2022-12-15T06:10:10.981048

2018-09-25T20:03:02

147,550,307

1

2

MIT

2022-12-07T23:52:23

2018-09-05T16:47:43

Python

UTF-8

Python

false

2,781

py

import rocksdb,time,ast from infiniti.params import * MAX_RETRY_CREATE_DB = 100 def writebatch(): return rocksdb.WriteBatch() def open_db(filename, logger=None, read_only=False): db_default_path = (filename, "wallet_test")[filename == ""] db_path = db_default_path retry_count = 0 db = None save_err=None while db is None and retry_count < MAX_RETRY_CREATE_DB: opts = rocksdb.Options() opts.create_if_missing = True opts.max_open_files = -1 opts.write_buffer_size = 67108864 opts.max_write_buffer_number = 3 opts.target_file_size_base = 67108864 opts.table_factory = rocksdb.BlockBasedTableFactory( filter_policy=rocksdb.BloomFilterPolicy(10), block_cache=rocksdb.LRUCache(2 * (1024 ** 3)), block_cache_compressed=rocksdb.LRUCache(500 * (1024 ** 2))) try: db = rocksdb.DB(db_path, opts, read_only) except Exception as err: save_err=err time.sleep(.1) retry_count += 1 if retry_count == MAX_RETRY_CREATE_DB: raise save_err return db def uuid_exists(object_db,uuid): try: _db = open_db(join_path(DATA_PATH,object_db)) it = _db.iteritems() it.seek(uuid) items = dict(itertools.takewhile(lambda item: item[0].startswith(uuid), it)) return len(items) == 0 except Exception as err: raise err def get_infiniti_object(object_db,uuid): """ All Inifiniti objects have a unique UUID, so just dump the object """ try: _db = open_db(join_path(DATA_PATH,object_db)) it = _db.iteritems() it.seek(uuid) result = {} for key,value in dict(itertools.takewhile(lambda item: item[0].startswith(uuid), it)): _uuid,_field = key.split('.') _value = value result.update = { _field : _value } return result except Exception as err: raise err def put_infiniti_object(object_db,obj): try: _db = open_db(join_path(DATA_PATH,object_db)) wb = writebatch() for attr in dir(obj): if attr.startswith('_') and not attr.startswith('__'): wb.put("{0}.{1}".format(obj.uuid,attr),getattr(obj,attr)) db.write(wb) return True except Exception as err: raise err def utxo_by_address(address,network,block_height): db = open_db(join_path(join_path(DATA_PATH,network),'utxo')) it = db.iteritems() it.seek_to_first() total = 0 utxo = [] for k,v in it: addr,amt = v.split('|') height,tx_hash = k.split('.') if address == addr: utxo.append({ 'amount':Decimal(amt), 'confirmations':int(int(block_height)-int(height)), 'tx_hash':tx_hash }) if len(utxo) > 0: return utxo else: return None def balance_by_address(address,network): db = open_db(join_path(join_path(DATA_PATH,network),'utxo')) it = db.iteritems() it.seek_to_first() total = 0 for k,v in it: addr,amt = v.split('|') if address == addr: total += Decimal(amt) return total

[ "bryce@altsystem.io" ]

bryce@altsystem.io

7436c86cf9c2ad83dacb6291b7f64493ca90f126

56e17984c230be6ee841264d65d7ba6ce949ceb1

/DateAndTime/Calendar_Module.py

a2a0fd44eca638970bd921c1fc7b96f6358a26ef

[]

no_license

Shamsullo/HackerRank_Python-

203b4277d7eb1de2236ff983415344a1409277d7

1f231f04cdd1cb0cd4e6a65318113ed15f1e47bc

refs/heads/master

2021-05-15T05:45:58.885667

2018-01-11T18:36:28

115,595,144

0

null

UTF-8

Python

false

262

py

import calendar, datetime input_date = input() month,day,year = map(int,input_date.split()) day_of_the_week = datetime.date(year,month,day) print calendar.day_name[day_of_the_week.weekday()].upper() #the code isn't giving an expected result, i wonder why?

[ "noreply@github.com" ]

Shamsullo.noreply@github.com

cdbf1c4051359a9d4660b03166c1b23f3c05428f

bb097a986d37c5b6d49bf6d1f9df17960e32e36e

/final_project/poi_id.py

9f2d37fc735529d2c4baaf05ebe14afbc6c019da

[]

no_license

noslav/enron_analysis

84e32fa2060c35d18e921cdb6647fd04019e7f57

9c98dfe8dcf71728cf8a8d75ab4b0c8468bd2d1e

refs/heads/master

2021-03-22T04:42:56.034087

2017-12-07T15:15:55

96,874,843

0

null

UTF-8

Python

false

20,872

py

#!/usr/bin/python import sys import pickle sys.path.append("../tools/") from feature_format import featureFormat, targetFeatureSplit from tester import dump_classifier_and_data import pandas import numpy as np from sklearn.feature_selection import SelectKBest from sklearn.feature_selection import chi2, f_classif, mutual_info_classif from sklearn.feature_selection import RFE from sklearn.linear_model import LogisticRegression from sklearn.decomposition import PCA from sklearn.ensemble import ExtraTreesClassifier from sklearn.model_selection import StratifiedShuffleSplit import matplotlib.pyplot as plt from sklearn.svm import SVC from sklearn.model_selection import StratifiedKFold from sklearn.feature_selection import RFECV import matplotlib.pyplot from sklearn.metrics import accuracy_score from sklearn.metrics import precision_score from sklearn.model_selection import cross_val_score #from sklearn.datasets import make_classification #=================================================================================# ### Task 1: Select what features you'll use. ### features_list is a list of strings, each of which is a feature name. ### The first feature must be "poi". ### for feature selection we run the selectKbest on the data set. enron_data = pickle.load(open("../final_project/final_project_dataset.pkl", "r")) #names of the columns in the 'enron_pickle_features.csv' data set. names = ["salary" , "to_messages" , "deferral_payments" , "total_payments" , "exercised_stock_options", "bonus" , "restricted_stock" , "shared_receipt_with_poi" , "restricted_stock_deferred", "total_stock_value", "expenses" , "loan_advances" , "from_messages" , "other" , "from_this_person_to_poi", "director_fees" , "deferred_income" , "long_term_incentive", "from_poi_to_this_person"] #getting the data and then reading them into dataframes for manipulation and feature #selection def makeDataFramesFeature(): enron_dataframe = pandas.read_csv('enron_pickle_features.csv') enron_poi = pandas.read_csv('enron_poi.csv') del enron_dataframe['Unnamed: 0'] del enron_poi['Unnamed: 0'] array_data = enron_dataframe.values X = array_data[:,0:19] array_poi = enron_poi.values.ravel() Y = array_poi return X, Y #X, Y = makeDataFramesFeature() def featureSelectKbest(X,Y): #Cannot be used since we have negative values test = SelectKBest(score_func= chi2, k=4) fit = test.fit(X, Y) # summarize scores np.set_printoptions(precision=3) print(fit.scores_) features = fit.transform(X) # summarize selected features print(features[0:6,:]) def featureRFE(X,Y): #recursive feature elimination using a random forest cl from sklearn.ensemble import RandomForestClassifier model = RandomForestClassifier(n_estimators=200) rfe = RFE(model, 4) fit = rfe.fit(X, Y) print("Num Features: %d") % fit.n_features_ print("Selected Features: %s") % fit.support_ print("Feature Ranking: %s") % fit.ranking_ #print names i = 0 namesdict = {} for values in names: namesdict[values] = fit.support_[i] i +=1 print namesdict #============================================================================== # featureRFEout = { 'salary': False, 'to_messages': False, \ # 'deferral_payments': False, 'total_payments': False, 'loan_advances': False, \ # 'bonus': True, 'restricted_stock_deferred': False, 'total_stock_value': True, \ # 'shared_receipt_with_poi': False, 'long_term_incentive': False, \ # 'exercised_stock_options': False, 'from_messages': False, 'other': True, \ # 'from_poi_to_this_person': False, 'from_this_person_to_poi': False, \ # 'deferred_income': False, 'expenses': True, 'restricted_stock': False, \ # 'director_fees': False } #============================================================================== #Recursive feature elimination using random forests suggest I should use #Bonus, total_stock_value, expenses and other (we can ignore this for now) def featureRFECross(X,Y): #recursive feature elimination super nice methoed to automatically #select good feature using a cross validation for classification svc = SVC(kernel="rbf") #taking too much time. #model = LogisticRegression() # The "accuracy" scoring is proportional to the number of correct # classifications rfecv = RFECV(estimator=svc, step=1, cv=StratifiedKFold(2), scoring='accuracy') rfecv.fit(X, Y) print("Optimal number of features : %d" % rfecv.n_features_) # Plot number of features VS. cross-validation scores plt.figure() plt.xlabel("Number of features selected") plt.ylabel("Cross validation score (nb of correct classifications)") plt.plot(range(1, len(rfecv.grid_scores_) + 1), rfecv.grid_scores_) plt.show() i = 0 namesdict = {} for values in names: namesdict[values] = rfecv.support_[i] i +=1 print namesdict def featurePCA(X,Y): #also tried this but I could not figure out how to name the features # for feature extraction feature extraction pca = PCA(n_components=4) fit = pca.fit(X) # summarize components print("Explained Variance: %s") % fit.explained_variance_ratio_ print(fit.components_) def featureETC(X,Y): #extra method learnt to select features # feature extraction using bagged trees namesdict = {} model = ExtraTreesClassifier() model.fit(X, Y) #print(model.feature_importances_) #print names i = 0 for values in names: namesdict[values] = model.feature_importances_[i] i +=1 print namesdict #============================================================================== # featureETCoutput = {'salary': 0.041632257710185139, 'to_messages': 0.039859107742246484,\ # 'deferral_payments': 0.024074150367185947, \ # 'total_payments': 0.064555518959854619, \ # 'loan_advances': 0.0093116015112734048, \ # 'bonus': 0.073052292449863596, \ # 'restricted_stock_deferred': 0.0042245370370370353,\ # 'total_stock_value': 0.09369028839725424, \ # 'shared_receipt_with_poi': 0.071123487226284629, \ # 'long_term_incentive': 0.04046480320342271, \ # 'exercised_stock_options': 0.1129150917901071, \ # 'from_messages': 0.024095798427395669, \ # 'other': 0.054538316103403574, \ # 'from_poi_to_this_person': 0.036628178381556319, \ # 'from_this_person_to_poi': 0.052257500165677206, \ # 'deferred_income': 0.10772890822303453, \ # 'expenses': 0.10845624961908869,\ # 'restricted_stock': 0.038109225603169372, \ # 'director_fees': 0.0032826870819597218} #============================================================================== #the results from feature RFE selection recommended using , exercised stock value, total_stock_value, expenses #===================================================================================# features_list = ['poi','salary', 'total_stock_value', 'expenses', 'bonus'] # You will need to use more features + your feature ### Load the dictionary containing the dataset with open("final_project_dataset.pkl", "r") as data_file: data_dict = pickle.load(data_file) #===================================================================================# ##plotting for outlier removal ### Task 2: Remove outliers #done in .rmd file data1 = featureFormat(data_dict, features_list) def plotSalaryStock(data): for point in data : salary = point[1] total_stock_value = point[2] matplotlib.pyplot.scatter(salary, total_stock_value) matplotlib.pyplot.xlabel("salary") matplotlib.pyplot.ylabel("total_stock_value") matplotlib.pyplot.show() def plotSalaryExpenses(data): for point in data : salary = point[1] expenses = point[3] matplotlib.pyplot.scatter(salary, expenses) matplotlib.pyplot.xlabel("salary") matplotlib.pyplot.ylabel("expenses") matplotlib.pyplot.show() def plotStockExpenses(data): for point in data : total_stock_value = point[2] expenses = point[3] matplotlib.pyplot.scatter(total_stock_value, expenses) matplotlib.pyplot.xlabel("total_stock_value") matplotlib.pyplot.ylabel("expenses") matplotlib.pyplot.show() def plotSalaryBonus(data): for point in data : salary = point[1] bonus = point[4] matplotlib.pyplot.scatter(salary, bonus) matplotlib.pyplot.xlabel("salary") matplotlib.pyplot.ylabel("bonus") matplotlib.pyplot.show() plotSalaryStock(data1) plotSalaryExpenses(data1) plotStockExpenses(data1) plotSalaryBonus(data1) #outliers were noticed in data in salary, bonus and total stock value #===================================================================================# #outlier removal functions def salaryOut(): outlierlist = [] for keys in data_dict : if type(data_dict[keys]["salary"]) == int or keys == "TRAVEL AGENCY IN THE PARK" or keys == "LOCKHART EUGENE E": if data_dict[keys]["salary"] > 2.5e7: data_dict[keys]["salary"] = "NaN" outlierlist.append(keys) elif data_dict[keys]["salary"] < 0: data_dict[keys]["salary"] = "NaN" outlierlist.append(keys) else: pass else: pass print "Salary outliers removed :", outlierlist, "\n" def totalStockValueOut(): outlierlist = [] for keys in data_dict : if type(data_dict[keys]["total_stock_value"]) == int or keys == "TRAVEL AGENCY IN THE PARK" or keys == "LOCKHART EUGENE E" : if data_dict[keys]["total_stock_value"] > 4.0e8: data_dict[keys]["total_stock_value"] = "NaN" outlierlist.append(keys) elif data_dict[keys]["total_stock_value"] < 0: data_dict[keys]["total_stock_value"] = "NaN" outlierlist.append(keys) else: pass else: pass print "Total stock value outliers removed :",outlierlist, "\n" def bonusOut(): outlierlist = [] for keys in data_dict : if type(data_dict[keys]["bonus"]) == int or keys == "TRAVEL AGENCY IN THE PARK" or keys == "LOCKHART EUGENE E": if data_dict[keys]["bonus"] > 0.8e8: data_dict[keys]["bonus"] = "NaN" outlierlist.append(keys) elif data_dict[keys]["bonus"]< 0: data_dict[keys]["bonus"] = "NaN" outlierlist.append(keys) else: pass else: pass print "Bonus outliers removed :" , outlierlist, "\n" def expenseOut(): outlierlist = [] for keys in data_dict : if type(data_dict[keys]["expenses"]) == int or keys == "TRAVEL AGENCY IN THE PARK" or keys == "LOCKHART EUGENE E": if data_dict[keys]["expenses"] > 5.0e6: data_dict[keys]["expenses"] = "NaN" outlierlist.append(keys) elif data_dict[keys]["expenses"]< 0: data_dict[keys]["expenses"] = "NaN" outlierlist.append(keys) else: pass else: pass print "Expenses outliers removed ", outlierlist, "\n" #removing salary outliers #removing total_stock_value outliers #removing bonus outliers #removing expense outliers salaryOut() totalStockValueOut() bonusOut() expenseOut() #===================================================================================# #replotting removed outliers print "Take a look at outlier removed graphs :" #reassinging data to new mat for looking at plots from new modified dictionaires data2 = featureFormat(data_dict, features_list) #plotting to see the effect of having removed outliers plotSalaryStock(data2) plotSalaryExpenses(data2) plotStockExpenses(data2) plotSalaryBonus(data2) ### Task 3: Create new feature(s) #===================================================================================# #making the new feature #Total number of "to emails" to this person - shared_receipt_with_poi - sent_by_poi_to_this_person. #The lower this number greater the relative importance since it means that most \ #of the communication to this person involved conversation with a poi or in the \ #same conversation with a poi. The number of emails from other people to this \ #person was low. def newFeature(): for keys in data_dict : if data_dict[keys].get("to_messages") and data_dict[keys].get("shared_receipt_with_poi") and data_dict[keys].get("from_poi_to_this_person") != 'NaN' : to = data_dict[keys].get("to_messages") shared = data_dict[keys].get("shared_receipt_with_poi") from_poi = data_dict[keys].get("from_poi_to_this_person") data_dict[keys]["relative_importance"] = to - (shared + from_poi) else: data_dict[keys]["relative_importance"] = "NaN" #print "relative_importance :", data_dict[keys].get("relative_importance") #print enron_data[keys].get("relative_importance") newFeature() def extractRelativeImportance(): #funtion to see the values of relative importance i = [] j = [] for keys in data_dict: if data_dict[keys]["relative_importance"] != 'NaN': i.append(data_dict[keys].get("relative_importance")) j.append(keys) else: pass return i, j ### Store to my_dataset for easy export below. #enron_dataframe.insert( my_dataset = data_dict #including the new features in the feature list features_list2 = ['poi','salary', 'total_stock_value', 'expenses', 'bonus', 'relative_importance'] ### Extract features and labels from dataset for local testing data3 = featureFormat(my_dataset, features_list2, sort_keys = True) labels, features = targetFeatureSplit(data3) ## done for finding out number of features to use. features_list4 = ["poi", "salary" , "to_messages" , "deferral_payments" , "total_payments" , "exercised_stock_options", "bonus" , "restricted_stock" , "shared_receipt_with_poi" , "restricted_stock_deferred", "total_stock_value", "expenses" , "loan_advances" , "from_messages" , "other" , "from_this_person_to_poi", "director_fees" , "deferred_income" , "long_term_incentive", "from_poi_to_this_person"] data4 = featureFormat(my_dataset, features_list4, sort_keys = True) labels4, features4 = targetFeatureSplit(data4) labels4 = np.array(labels4) features4 = np.array(features4) #===================================================================================# #trying the classifiers ### Task 4: Try a varity of classifiers ### Please name your classifier clf for easy export below. ### Note that if you want to do PCA or other multi-stage operations, ### you'll need to use Pipelines. For more info: ### http://scikit-learn.org/stable/modules/pipeline.html # Provided to give you a starting point. Try a variety of classifiers. def classifyNB(): from sklearn.naive_bayes import GaussianNB clf = GaussianNB() clf.fit(features_train, labels_train) pred = clf.predict(features_test) acc = accuracy_score(labels_test, pred) pres = precision_score(labels_test, pred) print acc , "NB Accuracy" , pres, "NB precision","\n" return clf , acc, pres def classifyDT(): from sklearn import tree clf = tree.DecisionTreeClassifier(criterion='gini', splitter='best', \ max_depth=None, min_samples_split=2, \ min_samples_leaf=1, min_weight_fraction_leaf=0.0,\ max_features=None, random_state=8, \ max_leaf_nodes=None, min_impurity_split=1e-07,\ class_weight=None, presort=False) clf.fit(features_train, labels_train) pred = clf.predict(features_test) acc = accuracy_score(labels_test, pred) pres = precision_score(labels_test, pred) print acc , "DT Accuracy" , pres, "DT precision", "\n" return clf , acc, pres def classifySVM(): from sklearn.svm import SVC clf = SVC(C=0.9, cache_size=200, class_weight=None, coef0=0.0, decision_function_shape=None, degree=3, gamma='auto', kernel='poly') clf.fit(features_train, labels_train) pred = clf.predict(features_test) acc = accuracy_score(labels_test, pred) pres = precision_score(labels_test, pred) print acc , "SVM Accuracy" , pres, "SVM precision" , "\n" return clf , acc, pres def classifyRF(): from sklearn.ensemble import RandomForestClassifier clf = RandomForestClassifier(n_estimators=200) clf.fit(features_train, labels_train) pred = clf.predict(features_test) acc = accuracy_score(labels_test, pred) pres = precision_score(labels_test, pred) print acc , "RF Accuracy" , pres, "RF precision" , "\n" return clf , acc, pres def classifyAB(): from sklearn.ensemble import AdaBoostClassifier clf = AdaBoostClassifier(base_estimator=None, n_estimators=200, \ learning_rate=0.5, algorithm='SAMME', random_state=None) clf.fit(features_train, labels_train) pred = clf.predict(features_test) acc = accuracy_score(labels_test, pred) pres = precision_score(labels_test, pred) print acc , "AB Accuracy" , pres, "AB precision" scores = cross_val_score(clf,features_test,pred ) print scores.mean() , "AB Cross val score" , "\n" return clf , acc, pres #give the number of splits on the validation step n_splits = 5 SSS = StratifiedShuffleSplit(n_splits, test_size=0.5, random_state=0) SSS.get_n_splits(features, labels) print SSS ,"\n" print "performing a stratified shuffle split for the validation process \ to ensure that an equal ratio of POIs to non-POIs are present in the training and \ test set", "\n" accuracyNB = [] precisionNB = [] accuracyRF = [] precisionRF = [] accuracyAB = [] precisionAB = [] accuracyDT = [] precisionDT = [] for train_index, test_index in SSS.split(features, labels): print "==================================================================" print "TRAIN:", train_index, "\n" "TEST:", test_index, "\n" features = np.array(features) labels = np.array(labels) features_train, features_test = features[train_index], features[test_index] labels_train, labels_test = labels[train_index], labels[test_index] clf1, acc1, prec1 = classifyNB() clf2, acc2, prec2 = classifyRF() clf3, acc3, prec3 = classifyAB() clf4, acc4, prec4 = classifyDT() accuracyNB.append(acc1) precisionNB.append(prec1) accuracyRF.append(acc2) precisionRF.append(prec2) accuracyAB.append(acc3) precisionAB.append(prec3) accuracyDT.append(acc4) precisionDT.append(prec4) print "==================================================================" print "average accuracy NB : " , float(sum(accuracyNB))/n_splits print "precision accuracy NB : " , float(sum(precisionNB))/n_splits print "average accuracy RF : " , float(sum(accuracyRF))/n_splits print "precision accuracy RF : " , float(sum(precisionRF))/n_splits print "average accuracy AB : " , float(sum(accuracyAB))/n_splits print "precision accuracy AB : " , float(sum(precisionAB))/n_splits print "average accuracy DT : " , float(sum(accuracyDT))/n_splits print "precision accuracy DT : " , float(sum(precisionDT))/n_splits #===================================================================================# #exporting features my_dataset = my_dataset features_list = features_list clf, acc, prec = classifyDT() #clf = classifyAB() #clf = classifySVM() #clf = classifyDT() dump_classifier_and_data(clf, my_dataset, features_list) #============================================================================== #============================================================================== # GaussianNB(priors=None) # Accuracy: 0.85629 Precision: 0.49612 Recall: 0.38400 F1: 0.43292 F2: 0.40218 # Total predictions: 14000 True positives: 768 False positives: 780 False negatives: 1232 True negatives: 11220 # #============================================================================== #==============================================================================

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import pytest from flask_login import login_user, login_manager, LoginManager from hktm import create_app, db from hktm.models import User, Lesson, LessonMaterial, MaterialType @pytest.fixture() def app(): app = create_app('test.cfg') return app @pytest.fixture() def auth_user(app): @app.login_manager.request_loader def load_user_from_request(request): return User.query.first() @pytest.fixture(scope='module') def test_client(): app = create_app('test.cfg') client = app.test_client() ctx = app.app_context() ctx.push() yield client ctx.pop() @pytest.fixture() def init_database(): db.create_all() db.session.commit() yield db db.drop_all() @pytest.fixture() def add_data(init_database): material_type1 = MaterialType('KJTS','Kanji Test','Instruction for Kanji Test') material_type2 = MaterialType('TRCP','Tracing','Instruction for Tracing') material_type3 = MaterialType('KJWR','Kanji Writing','Instruction for Kanji Writing') material_type4 = MaterialType('KJRD','Kanji Reading','Instruction for Kanji Reading') material_type5 = MaterialType('NWRD','New Reading','Instruction for New Reading') material_type6 = MaterialType('KT36','Kanji Test 3-6','Instruction for Kanji Test grades 3-6') user1 = User('user1@gmail.com','password') user1.grades = '1' user2 = User('user26@gmail.com','password') user2.grades = '2,6' user3 = User('userempty@gmail.com','password') user3.grades = '3' user4 = User('usernoteset@gmail.com','password') userAdmin = User('admin@hoshuko.com','password') userAdmin.grades = 'A123456789' lesson11 = Lesson('Grade 1 - Lesson 1','1') lesson12 = Lesson('Grade 1 - Lesson 2','1') lesson21 = Lesson('Grade 2 - Lesson 1','2') lesson22 = Lesson('Grade 2 - Lesson 2','2') lesson61 = Lesson('Grade 6 - Lesson 1','6') db.session.add_all([material_type1,material_type2,material_type3,material_type4,material_type5,material_type6]) db.session.add_all([user1, user2, user3, user4, userAdmin]) db.session.add_all([lesson11, lesson12, lesson21, lesson22, lesson61]) db.session.commit() lesson_mat_11_1 = LessonMaterial('Lesson 1 Material 1','something',lesson11.id,'KJTS') db.session.add(lesson_mat_11_1) db.session.commit() @pytest.fixture() def existing_user(): user = User('testuser@gmail.com','password') user.grades = '1' db.session.add(user) db.session.commit() @pytest.fixture def authenticated_request(test_client): user = User('testuser@gmail.com','password') user.grades = '1' db.session.add(user) db.session.commit() # with flask_app.test_request_context(): # yield login_user(User('testuser@gmail.com','password')) ######################################## fix for Live_server fixture and windows # @pytest.fixture(scope="session") # def flask_port(): # ## Ask OS for a free port. # # # with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: # s.bind(("", 0)) # addr = s.getsockname() # port = addr[1] # return port # # @pytest.fixture(scope="session", autouse=True) # def live_server(flask_port): # env = os.environ.copy() # env["FLASK_APP"] = "main.py" # server = subprocess.Popen(['flask', 'run', '--port', str(flask_port)], env=env) # try: # yield server # finally: # server.terminate()

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""" Custom model validators """ import re import django import jsonschema from django.core.exceptions import ValidationError from django.core.validators import BaseValidator from django.utils.translation import gettext_lazy as _ from users.CHQ_Scoring.github_score import CHQScore from django.conf import settings from users.utils import get_github_username from users import news class JSONSchemaValidator(BaseValidator): """validate json schemas against templates""" def compare(self, input, schema): try: jsonschema.validate(input, schema) except jsonschema.exceptions.ValidationError: raise django.core.exceptions.ValidationError( '%(value)s failed JSON schema check', params={'value': input}) def validate_no_news_source(value): """news needs to be part of news source""" if value not in news.NEWS_SITES: raise ValidationError( _('%(value)s is not an available news source'), params={'value': value}, ) def validate_github_url(value): """validate github profile""" pattern = r'github.com\/[a-zA-Z0-9]+(?:-[a-zA-Z0-9]+)*\/?$' if re.search(pattern, value) is None: raise ValidationError( _('%(value)s is not a valid github profile.'), params={'value': value}, ) def validate_github_user(value): """make sure github user is an actual user, consumes one api call""" user_name = get_github_username(value) chq_score = CHQScore(settings.GITHUB_TOKEN) if chq_score.check_user_exists(user_name) == False: raise ValidationError(_('github username %(value)s doesnt exist'), params={'value': user_name},)

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x.suwaidi@gmail.com

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/recipes/Python/438806_catenateFilesFactory/recipe-438806.py

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import os def catenateFilesFactory(isTextFiles=True, isClearTgt=True, isCreateTgt=True): """return a catenateFiles function parameterized by the factory arguments. isTextFiles: Catenate text files. If the last line of a non-empty file is not terminated by an EOL, append an EOL to it. isClearTgt If the target file already exists, clear its original contents before appending the source files. isCreateTgt If the target file does not already exist, and this parameter is True, create the target file; otherwise raise an IOError. """ eol = os.linesep lenEol = len(eol) def catenateFiles(tgtFile, *srcFiles): isTgtAppendEol = False if os.path.isfile(tgtFile): if isClearTgt: tgt = open(tgtFile, 'wb') tgt.close() elif isTextFiles: tgt = open(tgtFile, 'rb') data = tgt.read() tgt.close() if len(data) and (len(data) < lenEol or data[-lenEol:] != eol): isTgtAppendEol = True elif not isCreateTgt: raise IOError, "catenateFiles target file '%s' not found" % ( tgtFile) tgt = open(tgtFile, 'ab') if isTgtAppendEol: tgt.write(eol) for srcFile in srcFiles: src = open(srcFile, 'rb') data = src.read() src.close() tgt.write(data) if (isTextFiles and len(data) and (len(data) < lenEol or data[-lenEol:] != eol)): tgt.write(eol) tgt.close() return # Support reflection and doc string. catenateFiles.isTextFiles = isTextFiles catenateFiles.isClearTgt = isClearTgt catenateFiles.isCreateTgt = isCreateTgt if isTextFiles: docFileType = "text" else: docFileType = "binary" if isCreateTgt: docCreate = "Create tgtFile if it does not already exist." else: docCreate = "Require that tgtFile already exists." if isClearTgt: docClear = "replace" else: docClear = "append to" catenateFiles.__doc__ = """Catenate %s srcFiles to %s the tgtFile. %s All of the srcFiles must exist; otherwise raise an IOError. """ % (docFileType, docClear, docCreate) return catenateFiles

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betty@qburst.com

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wucg-python/dry1

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from django.shortcuts import render # Create your views here. from rest_framework import mixins from rest_framework.generics import GenericAPIView from rest_framework.response import Response from rest_framework.views import APIView from rest_framework import generics from api.models import Book, User from api.serializers import BookModelSerializer, UserModelSerializer from rest_framework import viewsets class BookAPIView(APIView): def get(self,request,*args,**kwargs): book_id = kwargs.get('id') if book_id: book = Book.objects.filter(id=book_id,is_delete=False) serialize = BookModelSerializer(book,many=True).data # print(serialize) return Response({ 'status':200, "message":"查询一个书籍", "result":serialize, }) else: books = Book.objects.filter(is_delete=False) serialize = BookModelSerializer(books,many=True).data return Response({ 'status': 200, "message": "查询所有书籍", "result": serialize, }) def post(self,request,*args,**kwargs): request_data = request.data print(request_data) if isinstance(request_data,dict): many = False elif isinstance(request_data,list): many = True else: return Response({ "status":400, "message":"添加失败" }) serialize = BookModelSerializer(data=request_data,many=many) serialize.is_valid(raise_exception=True) book = serialize.save() return Response({ 'status': 200, "message": "添加书籍", "result": BookModelSerializer(book,many=many).data, }) def delete(self,request,*args,**kwargs): id = kwargs.get('id') if id: # 删除单个 ids = [id] else: ids = request.data response = Book.objects.filter(id__in=ids,is_delete=False).update(is_delete=True) if response: return Response({ "status":200, "message":"删除成功", }) else: return Response({ "status": 400, "message": "删除失败或已被删除", }) # 更新单个整体 def put(self,request,*args,**kwargs): # 获取到修改的值 request_data = request.data # 获取到被修改的对象 book_id = kwargs.get('id') try: book_obj = Book.objects.get(id=book_id) except: return Response({ "status":400, "message":"对象不存在" }) serializer = BookModelSerializer(data=request_data,instance=book_obj,partial=True) serializer.is_valid(raise_exception=True) book = serializer.save() return Response({ "status":200, "message":"修改成功", "result":BookModelSerializer(book).data }) # def patch(self,request,*args,**kwargs): # # 获取到修改的值 # request_data = request.data # # 获取到被修改的对象 # book_id = kwargs.get('id') # try: # book_obj = Book.objects.get(id=book_id) # except: # return Response({ # "status": 400, # "message": "对象不存在" # }) # serializer = BookModelSerializer(data=request_data, instance=book_obj,partial=True) # serializer.is_valid(raise_exception=True) # book = serializer.save() # return Response({ # "status": 200, # "message": "修改成功", # "result": BookModelSerializer(book).data # }) def patch(self,request,*args,**kwargs): ''' 更新单个 id kwargs.get('id') 更新多个 [{},{},{}] :param request: :param args: :param kwargs: :return: ''' book_id = kwargs.get('id') request_data = request.data # 修改单个 if book_id and isinstance(request_data,dict): ids = [book_id] request_data = [request_data] elif not book_id and isinstance(request_data,list): ids = [] for i in request_data: id = i.pop('id',None) if id: ids.append(id) else: return Response({ 'status':400, "message":"id不存在" }) else: return Response({ "status":400, "message":"格式错误" }) books_obj = [] new_data = [] for index,id in enumerate(ids): print(index,id) try: book_obj = Book.objects.get(id) print(book_obj) books_obj.append(book_obj) new_data.append(request_data[index]) except: continue serializer = BookModelSerializer(data=new_data,instance=books_obj,partial=True,many=True) serializer.is_valid(raise_exception=True) datas = serializer.save() return Response({ "status":200, "message":"成功", "result": BookModelSerializer(datas).data }) class BookGenericAPIView(GenericAPIView, mixins.ListModelMixin, mixins.RetrieveModelMixin, mixins.DestroyModelMixin, mixins.CreateModelMixin, mixins.UpdateModelMixin, ): queryset = Book.objects.filter(is_delete=False) serializer_class = BookModelSerializer lookup_field = "id" def get(self,request,*args,**kwargs): if "id" in kwargs: return self.retrieve(request,*args,**kwargs) return self.list(request,*args,**kwargs) def post(self,request,*args,**kwargs): return self.create(request,*args,**kwargs) def delete(self,request,*args,**kwargs): return self.destroy(request,*args,**kwargs) def put(self,request,*args,**kwargs): return self.partial_update(request,*args,**kwargs) class BookGenerics(generics.ListAPIView, generics.ListCreateAPIView): queryset = Book.objects.filter() serializer_class = BookModelSerializer lookup_field = "id" class UserAPIView(viewsets.GenericViewSet, mixins.CreateModelMixin): queryset = User.objects.all() serializer_class = UserModelSerializer lookup_field = "id" def register(self,request,*args,**kwargs): return self.create(request,*args,**kwargs) def login(self,request,*args,**kwargs): request_data = request.data print(request_data) user= User.objects.filter(username=request_data.get('username'),password=request_data.get('password')) if user: return Response({ "status":200, "message":"登陆成功" }) return Response({ "status":400, "message":"登陆失败" })

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1490168051@qq.com

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/python/kyu_6/replace_with_alphabet_position.py

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""" https://www.codewars.com/kata/546f922b54af40e1e90001da """ from string import ascii_lowercase def alphabet_position(text): score = 1 score_dict = {} for i in ascii_lowercase: score_dict[i] = score score += 1 t = text.lower() out = '' for i in t: if i in score_dict: out += repr(score_dict[i]) + " " return out[0:-1] print(alphabet_position("The sunset sets at twelve o' clock.")) # '20 8 5 19 21 14 19 5 20 19 5 20 19 1 20 20 23 5 12 22 5 15 3 12 15 3 11' # '20 8 5 19 21 14 19 5 20 19 5 20 19 1 20 20 23 5 12 22 5 15 3 12 15 3 11'

[ "masster1987@inbox.ru" ]

masster1987@inbox.ru

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/todo/views.py

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foxy4096/DjangoToDo

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refs/heads/main

2023-09-02T03:34:33.144510

2021-11-12T10:21:17

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from django.views.generic import * from django.shortcuts import redirect from .models import ToDo class ToDoListView(ListView): model = ToDo context_object_name = "todos" class ToDoCreateView(CreateView): model = ToDo success_url = '/' fields = '__all__' def form_valid(self, form): form.save() return super().form_valid(form) class ToDoUpdateView(UpdateView): model = ToDo success_url = '/' fields = '__all__' def form_valid(self, form): form.save() return super().form_valid(form) class ToDoDeleteView(DeleteView): model = ToDo success_url = '/' def get_context_data(self, **kwargs): context = super(ToDoDeleteView, self).get_context_data(**kwargs) context['todo'] = ToDo.objects.get(pk=self.object.pk) return context

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mgupte7/python-examples1

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# ------------------------------------------------ # ----------------Python Read Files--------------- # ------------------------------------------------ # ex 1 - The open() function returns a file object, which has a read() method for reading the content of the file: f = open("demofile.txt", "r") print(f.read()) # ex 2 - Open a file on a different location: f = open("D:\\myfiles\welcome.txt", "r") print(f.read()) # ex 3 - Return the 5 first characters of the file: f = open("demofile.txt", "r") print(f.read(5)) # ex 4 - Read one line of the file: f = open("demofile.txt", "r") print(f.readline()) # ex 5 - Read two lines of the file: f = open("demofile.txt", "r") print(f.readline()) print(f.readline()) # ex 6 - Loop through the file line by line: f = open("demofile.txt", "r") for x in f: print(x) # ex 7 - Close the file when you are finish with it: f = open("demofile.txt", "r") print(f.readline()) f.close() # ex 8 # ex 9 # ex 10

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from django.urls import include, path, re_path from rest_framework import routers from .api import ( LoginView, LogoutView, AccountDetailView, PasswordChangeView, PasswordResetView, PasswordResetConfirmView, ExcelfileUploadView, UserAvatarView, UserView ) router = routers.SimpleRouter(trailing_slash=False) router.register(r'user', UserView) urlpatterns = [ # URLs that do not require a session or valid token path('auth/password/reset', PasswordResetView.as_view(), name='user_password_reset'), path('auth/password/reset/confirm', PasswordResetConfirmView.as_view(), name='user_password_reset_confirm'), path('auth/password/change', PasswordChangeView.as_view(), name='user_password_change'), path('auth/login', LoginView.as_view(), name='user_login'), # URLs that require a user to be logged in with a valid session / token. path('auth/logout', LogoutView.as_view(), name='auth_logout'), path('account/info', AccountDetailView.as_view(), name='account_details'), path('account/avatar', UserAvatarView.as_view(), name='account_avatar'), # path('user/list/trainmanager', UserListView.as_view(), name='user_list'), path('user/upload', ExcelfileUploadView.as_view(), name='user_upload'), # path('user/list/trainmanager', UserListView.as_view({'get': 'list'}), name='user_trainmanagerlist'), # path('user/list', UserListView.as_view({'get': 'list', 'patch': 'bulkdelete'}), name='user_list'), # path('user/list/<str:roles>', UserListView.as_view({'get': 'list'}), name='user_listrole'), ] urlpatterns += router.urls

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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db.models import Avg, Sum from .models import Consumption, User class ConsumptionQueryset(): """queryset for consumption data """ def get_consumption_avg_and_sum(): """get average and sum of consumption Get average and sum of consumption all time Returns: QuerySet (dict): consumption data for each user Raises: Consumption.DoesNotExist: if Consumption is not found """ consum_data = Consumption.objects.values('datetime').annotate( Avg('consumption'), Sum('consumption')).order_by('datetime') if consum_data.exists(): return consum_data else: raise Consumption.DoesNotExist def get_each_user_average_consumption(): """get user's average consumption Get user's average comsumption Returns: QuerySet (dict): consumption data for each user Raises: Consumption.DoesNotExist: if Consumption is not found """ consum_data = Consumption.objects.values('user_id').annotate( Avg('consumption')) if consum_data.exists(): return consum_data else: raise Consumption.DoesNotExist def get_user_consumption_order_by_date(user_id): """get user's consumption data order by datetime Get specified user's comsumption. Args: user_id (int): user id Returns: QuerySet (Consumption): consumption data for each user Raises: Consumption.DoesNotExist: if user is not found """ user = User.objects.get(id=user_id) consum_data = Consumption.objects.filter( user_id=user).order_by('datetime') if consum_data.exists(): return consum_data else: raise Consumption.DoesNotExist class UserQueryset(): """queryset for user data """ def get_all_user(): """get all user Get All user data. Args: user (User object): user model object Returns: QuerySet (User): all user data Raises: User.DoesNotExist: if user is not found """ user_data = User.objects.all() if user_data.exists(): return user_data else: raise User.DoesNotExist

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#!/usr/bin/env python import numpy as np import random from q1_softmax import softmax from q2_sigmoid import sigmoid, sigmoid_grad from q2_gradcheck import gradcheck_naive def forward_backward_prop(data, labels, params, dimensions): """ Forward and backward propagation for a two-layer sigmoidal network Compute the forward propagation and for the cross entropy cost, and backward propagation for the gradients for all parameters. Arguments: data -- M x Dx matrix, where each row is a training example. labels -- M x Dy matrix, where each row is a one-hot vector. params -- Model parameters, these are unpacked for you. dimensions -- A tuple of input dimension, number of hidden units and output dimension """ ### Unpack network parameters (do not modify) ofs = 0 Dx, H, Dy = (dimensions[0], dimensions[1], dimensions[2]) W1 = np.reshape(params[ofs:ofs+ Dx * H], (Dx, H)) ofs += Dx * H b1 = np.reshape(params[ofs:ofs + H], (1, H)) ofs += H W2 = np.reshape(params[ofs:ofs + H * Dy], (H, Dy)) ofs += H * Dy b2 = np.reshape(params[ofs:ofs + Dy], (1, Dy)) z1 = np.dot(data,W1) + b1 h = sigmoid(z1) z2 = np.dot(h,W2) + b2 yhat = softmax(z2) cost = -np.sum(labels*np.log(yhat)) d1 = yhat - labels d2 = d1.dot(W2.T) d3 = d2*sigmoid_grad(h) gradW2 = np.dot(h.T,d1) gradb2 = np.sum(d1,axis = 0) gradW1 = np.dot(data.T,d3) gradb1 = np.sum(d3,axis = 0) ### Stack gradients (do not modify) grad = np.concatenate((gradW1.flatten(), gradb1.flatten(), gradW2.flatten(), gradb2.flatten())) return cost, grad def sanity_check(): """ Set up fake data and parameters for the neural network, and test using gradcheck. """ print "Running sanity check..." N = 20 dimensions = [10, 5, 10] data = np.random.randn(N, dimensions[0]) # each row will be a datum labels = np.zeros((N, dimensions[2])) for i in xrange(N): labels[i, random.randint(0,dimensions[2]-1)] = 1 params = np.random.randn((dimensions[0] + 1) * dimensions[1] + ( dimensions[1] + 1) * dimensions[2], ) gradcheck_naive(lambda params: forward_backward_prop(data, labels, params, dimensions), params) def your_sanity_checks(): """ Use this space add any additional sanity checks by running: python q2_neural.py This function will not be called by the autograder, nor will your additional tests be graded. """ if __name__ == "__main__": sanity_check() your_sanity_checks()

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import bpy import os from ..main.common import imageFromPath class Glass: def __init__(self, BasePath,image_format): self.BasePath = BasePath self.image_format = image_format def create(self,Glass,Mat): CurMat = Mat.node_tree CurMat.nodes['Principled BSDF'].inputs['Transmission'].default_value = 1 Color = CurMat.nodes.new("ShaderNodeRGB") Color.location = (-400,200) Color.hide = True Color.label = "TintColor" Color.outputs[0].default_value = (float(Glass["TintColor"]["Red"])/255,float(Glass["TintColor"]["Green"])/255,float(Glass["TintColor"]["Blue"])/255,float(Glass["TintColor"]["Alpha"])/255) CurMat.links.new(Color.outputs[0],CurMat.nodes['Principled BSDF'].inputs['Base Color']) IOR = CurMat.nodes.new("ShaderNodeValue") IOR.location = (-400,-150) IOR.outputs[0].default_value = float(Glass["IOR"]) IOR.hide = True IOR.label = "IOR" CurMat.links.new(IOR.outputs[0],CurMat.nodes['Principled BSDF'].inputs['IOR']) rImg = imageFromPath(self.BasePath + Glass["Roughness"],self.image_format,True) rImgNode = CurMat.nodes.new("ShaderNodeTexImage") rImgNode.location = (-800,50) rImgNode.image = rImg rImgNode.label = "Roughness" CurMat.links.new(rImgNode.outputs[0],CurMat.nodes['Principled BSDF'].inputs['Roughness']) nImg = imageFromPath(self.BasePath + Glass["Normal"],self.image_format,True) nImgNode = CurMat.nodes.new("ShaderNodeTexImage") nImgNode.location = (-800,-300) nImgNode.image = nImg nImgNode.label = "Normal" nRgbCurve = CurMat.nodes.new("ShaderNodeRGBCurve") nRgbCurve.location = (-500,-300) nRgbCurve.hide = True nRgbCurve.mapping.curves[2].points[0].location = (0,1) nRgbCurve.mapping.curves[2].points[1].location = (1,1) nMap = CurMat.nodes.new("ShaderNodeNormalMap") nMap.location = (-200,-300) nMap.hide = True CurMat.links.new(nImgNode.outputs[0],nRgbCurve.inputs[1]) CurMat.links.new(nRgbCurve.outputs[0],nMap.inputs[1]) CurMat.links.new(nMap.outputs[0],CurMat.nodes['Principled BSDF'].inputs['Normal'])

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#libreria per generare grafici import matplotlib.pyplot as plt import matplotlib.patches as mpatches #lib to remove files import os print("Make the comparison Plots") plt.rc('xtick', labelsize=8) plt.rc('ytick', labelsize=8) plt.figure(figsize=(10, 5)) f=open("rewards_taxi_qlearning.txt","r") stringa=f.readline() n=0 while stringa!="":#count the number of rewards n+=1 stringa=f.readline() newRewards=[ 0 for i in range(n)] newRewardsSarsa=[ 0 for i in range(n)] #read q-learning rewards f=open("rewards_taxi_qlearning.txt","r") stringa=f.readline() n=0 while stringa!="":#make the rewards list newRewards[n]=stringa n+=1 stringa=f.readline() f.close() #read sarsa rewards f=open("rewards_taxi_sarsa.txt","r") stringa=f.readline() n=0 while stringa!="":#make the rewards list newRewardsSarsa[n]=stringa n+=1 stringa=f.readline() f.close() #eps list with numRewards slots eps=range(0,1000) plt.plot(eps,newRewards,'r',eps,newRewardsSarsa,'b') plt.title("Rewards collected over the time for Taxi game") plt.xlabel("Trials") plt.ylabel("Rewards") plt.grid()#put the grid qlearningLegend = mpatches.Patch(color='red', label='Q-learning') SarsaLegend = mpatches.Patch(color='blue', label='Sarsa') plt.legend(handles=[qlearningLegend,SarsaLegend]) plt.show()#print in output the plot and give the possibility to save it on your computer plt.savefig('taxi_sarsa_vs_Q_learning.png') os.remove("/home/giacomo/Scrivania/Q_Learning_Games_v2_/Sarsa_vs_Q_Learning/Taxi_Game/Taxi_Analysis/rewards_taxi_sarsa.txt") os.remove("/home/giacomo/Scrivania/Q_Learning_Games_v2_/Sarsa_vs_Q_Learning/Taxi_Game/Taxi_Analysis/rewards_taxi_qlearning.txt")#to remove the file

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gmc112/Synthesising-Images-Via-Imagination

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import tensorflow as tf import tensorflow.contrib.layers as tfcl import os import numpy as np import imageio import datetime import Utilities as util import Layers_gan as lay LEARNING_RATE = 2e-4 BATCH_SIZE = 64 HEIGHT = 128 WIDTH = 128 CHANNEL = 3 DATA_REPEATS = 4 EPOCHS = 1000 VERSION = "GAN_1" DATE = datetime.datetime.now().strftime("%d-%m-%H-%M-%S") SAVE_PATH = "./Project Out/" + VERSION + "/saved/" MODE = 1 # 0 For PNG, 1 for JPEG DROPOUT_RATE = 0.9 DISTORTED = False RESTORE = True # MODELS ARE TAKEN FROM EXAMPLE https://www.youtube.com/watch?v=yz6dNf7X7SA # The generator and discriminator functions are in theory the same layers though they have been heavily refactored to # improve modularity and reduce the repeated code across # Comments in the train function mark code sourced from the above link # These comments are relevant across all three GAN models def generator(input, random_dim, is_train, reuse=False): c4, c8, c16, c32, c64 = 512, 256, 128, 64, 32 # channel num s4 = 4 output_dim = CHANNEL # RGB image with tf.variable_scope('gen') as scope: if reuse: scope.reuse_variables() w1 = tf.get_variable('w1', shape=[random_dim, s4 * s4 * c4], dtype=tf.float32, initializer=tf.truncated_normal_initializer(stddev=0.02)) b1 = tf.get_variable('b1', shape=[c4 * s4 * s4], dtype=tf.float32, initializer=tf.constant_initializer(0.0)) flat_conv1 = tf.add(tf.matmul(input, w1), b1, name='flat_conv1') # Convolution, bias, activation, repeat! with tf.name_scope("gen1"): conv1 = tf.reshape(flat_conv1, shape=[-1, s4, s4, c4], name='conv1') bn1 = tfcl.batch_norm(conv1, is_training=is_train, epsilon=1e-5, decay=0.9, updates_collections=None, scope='bn1') act1 = tf.nn.relu(bn1, name='act1') tf.summary.histogram("conv_t_act", act1) # 8*8*256 # Convolution, bias, activation, repeat! act2 = lay.conv_t(act1, c8, "gen2", is_train, False) # 16*16*128 act3 = lay.conv_t(act2, c16, "gen3", is_train, False) # 32*32*64 act4 = lay.conv_t(act3, c32, "gen4", is_train, False) # 64*64*32 act5 = lay.conv_t(act4, c64, "gen5", is_train, False) # 128*128*3 return lay.conv_t(act5, output_dim, "gen6", is_train, True) def discriminator(input, is_train, reuse=False): c2, c4, c8, c16 = 64, 128, 256, 512 # channel num: 64, 128, 256, 512 with tf.variable_scope('dis') as scope: if reuse: scope.reuse_variables() act1 = lay.conv(input, c2, "dis1", is_train) act2 = lay.conv(act1, c4, "dis2", is_train) act3 = lay.conv(act2, c8, "dis3", is_train) act4 = lay.conv(act3, c16, "dis4", is_train) dim = int(np.prod(act4.get_shape()[1:])) fc1 = tf.reshape(act4, shape=[-1, dim], name='fc1') w2 = tf.get_variable('w2', shape=[fc1.shape[-1], 1], dtype=tf.float32, initializer=tf.truncated_normal_initializer(stddev=0.02)) b2 = tf.get_variable('b2', shape=[1], dtype=tf.float32, initializer=tf.constant_initializer(0.0)) logits = tf.add(tf.matmul(fc1, w2), b2, name='logits') return logits def train(output, restore): dataset, size = util.read_images(DATA_REPEATS, MODE) size = size * EPOCHS dataset = dataset.map(lambda path: util.parse_image(path, MODE, HEIGHT, WIDTH, CHANNEL, DISTORTED)) dataset = dataset.shuffle(buffer_size=10000) dataset = dataset.repeat(EPOCHS) dataset = dataset.batch(BATCH_SIZE) iterator = dataset.make_one_shot_iterator() image_batch = iterator.get_next() iterator_sum = dataset.make_one_shot_iterator() im_sum_batch = iterator_sum.get_next() # The following section is sourced as is from the above link random_dim = 100 with tf.variable_scope('input'): real_image = tf.placeholder('float', shape=[None, HEIGHT, WIDTH, CHANNEL], name='real_img') random_input = tf.placeholder('float', shape=[None, random_dim], name='rand_input') is_train = tf.placeholder('bool', name='is_train') fake_image = generator(random_input, random_dim, is_train) real_result = discriminator(real_image, is_train) fake_result = discriminator(fake_image, is_train, reuse=True) d_loss = tf.reduce_mean(fake_result) - tf.reduce_mean(real_result) # This optimizes the discriminator. dloss_summary = tf.summary.scalar("dis loss", d_loss) g_loss = -tf.reduce_mean(fake_result) # This optimizes the generator. gloss_summary = tf.summary.scalar("gen loss", g_loss) t_vars = tf.trainable_variables() d_vars = [var for var in t_vars if 'dis' in var.name] g_vars = [var for var in t_vars if 'gen' in var.name] trainer_d = tf.train.RMSPropOptimizer(learning_rate=LEARNING_RATE).minimize(d_loss, var_list=d_vars) trainer_g = tf.train.RMSPropOptimizer(learning_rate=LEARNING_RATE).minimize(g_loss, var_list=g_vars) d_clip = [v.assign(tf.clip_by_value(v, -0.01, 0.01)) for v in d_vars] # End of sourced section sess = tf.Session() saver = tf.train.Saver() sess.run(tf.global_variables_initializer()) sess.run(tf.local_variables_initializer()) if not os.path.exists("./log/" + VERSION + DATE): os.makedirs("./log/" + VERSION + DATE) writer = tf.summary.FileWriter("./log/" + VERSION + " " + DATE) writer.add_graph(sess.graph) merged = tf.summary.merge_all() i = 0 while True: try: # The following section is sourced as is from the above link except the Tensorboard summaries print("Running iteration {}/{}...".format(i, (size // BATCH_SIZE + 1)//6)) if restore: checkpoint = tf.train.latest_checkpoint(SAVE_PATH) if checkpoint is not None: saver.restore(sess=sess, save_path=checkpoint) restore = False d_iters = 5 g_iters = 1 for k in range(d_iters): train_noise = np.random.uniform(-1.0, 1.0, size=[BATCH_SIZE, random_dim]).astype(np.float32) # sess.run(iterator.initializer) train_image = sess.run(image_batch) # wgan clip weights sess.run(d_clip) # Update the discriminator _, dloss, m = sess.run([trainer_d, d_loss, merged], feed_dict={random_input: train_noise, real_image: train_image, is_train: True}) writer.add_summary(m, i) # Update the generator for k in range(g_iters): train_noise = np.random.uniform(-1.0, 1.0, size=[BATCH_SIZE, random_dim]).astype(np.float32) img = sess.run(im_sum_batch) _, gloss, m = sess.run([trainer_g, g_loss, merged], feed_dict={random_input: train_noise, real_image: img, is_train: True}) writer.add_summary(m, i) #End of Sourced section if i % 50 == 0: # save images print("saving samples") if not os.path.exists(output): os.makedirs(output) sample_noise = np.random.uniform(-1.0, 1.0, size=[BATCH_SIZE, random_dim]).astype(np.float32) imgtest = sess.run(fake_image, feed_dict={random_input: sample_noise, is_train: False}) imgtest = ((imgtest + 1.) / 2.) # Keep same scale and floats but remove negatives imgtest = imgtest * 255 imgtest = tf.cast(imgtest, dtype=tf.uint8) imgtest = sess.run(imgtest) n = 0 for img in imgtest: path = output + "/" + str(i) + "-" + str(n) + ".png" imageio.imwrite(path, img) n += 1 if not os.path.exists(output + "/grid"): os.makedirs(output + "/grid") path = output + "/grid/" + str(i) + ".png" imageio.imwrite(path, util.create_grid(imgtest, HEIGHT, WIDTH, BATCH_SIZE)) if i % 250 == 0: if not os.path.exists(SAVE_PATH): os.makedirs(SAVE_PATH) saver.save(sess=sess, save_path=SAVE_PATH + "VAE", global_step=i) i += 1 except tf.errors.OutOfRangeError: print("Training Complete") break print("Generating Final Output") output = output + "/final_" + VERSION if not os.path.exists(output): os.makedirs(output) for x in range(5): try: out_enc = np.random.standard_normal(size=(64, 128, 128, 3)) final_out = sess.run(fake_image, feed_dict={input: out_enc, is_train: False}) final_out = ((final_out + 1.) / 2.) # Keep same scale and floats but remove negatives final_out = final_out * 255 final_out = tf.cast(final_out, dtype=tf.uint8) final_out = sess.run(final_out) n = 0 for img in final_out: path = output + "/" + str(i) + "-" + str(n) + ".png" imageio.imwrite(path, img) n += 1 if not os.path.exists(output + "/grid"): os.makedirs(output + "/grid") path = output + "/grid/" + str(i) + ".png" imageio.imwrite(path, util.create_grid(imgtest, HEIGHT, WIDTH, BATCH_SIZE)) except tf.errors.OutOfRangeError: print("Finished Generating output") break if __name__ == "__main__": output = "./Project Out/" + VERSION + "/" + DATE util.save_params(output, LEARNING_RATE, BATCH_SIZE, DATA_REPEATS, DROPOUT_RATE, EPOCHS, DISTORTED) train(output, RESTORE)

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import numpy as np def set_balance(row, ratio): if row['ratio 3/(3+5)'] >= ratio: return '3p' elif row['ratio 5/(3+5)'] >= ratio: return '5p' elif np.isnan(row['reads_3p']) and np.isnan(row['reads_5p']): return 'unknown' elif np.isnan(row['reads_3p']): return '5p' elif np.isnan(row['reads_5p']): return '3p' else: return 'both' def find_in_mirna(row, df_loc): if df_loc[ (df_loc['chrom'] == row['chrom']) & (df_loc['start'] <= row['pos']) & (df_loc['orientation'] == row['orient_loc']) & (df_loc['stop'] >= row['pos'])].shape[0] != 0: temp = df_loc[ (df_loc['chrom'] == row['chrom']) & (df_loc['start'] <= row['pos']) & (df_loc['orientation'] == row['orient_loc']) & (df_loc['stop'] >= row['pos'])].values[0] if row['orient_loc'] == '+': start = row['pos'] - temp[2] + 1 stop = row['pos'] - temp[3] - 1 else: start = -(row['pos'] - temp[3] - 1) stop = -(row['pos'] - temp[2] + 1) localiz = [start, stop] else: localiz = [np.nan, np.nan] return localiz def find_arm(row): if row['-/+'] == '+': if row['start'] - row['start_pre'] < row['stop_pre'] - row['stop']: return '5p' else: return '3p' if row['-/+'] == '-': if row['start'] - row['start_pre'] < row['stop_pre'] - row['stop']: return '3p' else: return '5p' def from_start(row, column_start, column_stop): if row['orient_loc'] == '+': return row['pos'] - row[column_start] + 1 else: return row[column_stop] - row['pos'] + 1 def from_end(row, column_stop, column_start): if row['orient_loc'] == '+': return row['pos'] - row[column_stop] - 1 else: return row[column_start] - row['pos'] - 1 def find_localization(row, df_loc): # fix values that were not in reference if row['name'].lower() == 'hsa-mir-4477b' and \ row['start'] == 63819560 and \ row['stop'] == 63819669: row['Strand'] = '+' elif row['name'].lower() == 'hsa-mir-6723': row['Strand'] = '-' elif row['name'].lower() == 'hsa-mir-3656': row['Strand'] = '+' if (type(row['Strand']) != str and df_loc[(df_loc['name'].str.contains(row['name'].lower())) & (df_loc['chrom'] == row['chrom']) & (df_loc['start'] <= row['pos']) & (df_loc['stop'] >= row['pos'])].shape[0] != 0): localiz = df_loc[(df_loc['name'].str.contains(row['name'].lower())) & (df_loc['chrom'] == row['chrom']) & (df_loc['start'] <= row['pos']) & (df_loc['stop'] >= row['pos'])].values[0] elif df_loc[(df_loc['name'].str.contains(row['name'].lower())) & (df_loc['chrom'] == row['chrom']) & (df_loc['start'] <= row['pos']) & (df_loc['stop'] >= row['pos']) & (df_loc['orientation'] == row['Strand'])].shape[0] != 0: localiz = df_loc[(df_loc['name'].str.contains(row['name'].lower())) & (df_loc['chrom'] == row['chrom']) & (df_loc['start'] <= row['pos']) & (df_loc['stop'] >= row['pos']) & (df_loc['orientation'] == row['Strand'])].values[0] else: localiz = [np.nan, np.nan, np.nan, np.nan, np.nan, np.nan] return localiz def if_complex(row, complex_df): if complex_df[(complex_df['chrom'] == row['chrom']) & (complex_df['start'] == row['start']) & (complex_df['stop'] == row['stop']) & (complex_df['gene'] == row['gene']) & (complex_df['seq_type'] == row['seq_type'])].shape[0] != 0: values = complex_df[(complex_df['chrom'] == row['chrom']) & (complex_df['start'] == row['start']) & (complex_df['stop'] == row['stop']) & (complex_df['gene'] == row['gene']) & (complex_df['seq_type'] == row['seq_type'])]['complex'].unique() if 1 in values: return 1 else: return 0 else: return 0 def concat_ints(col): row = list(col.values) new_row = [] for x in row: new_row.append(str(x)) return '"' + ':'.join(new_row) + '"' def concat_alg(col): row = list(col.values) new_row = [] for x in row: new_row.append(str(x)) new_row = sorted(set(new_row)) return '"' + ':'.join(new_row) + '"' def type_of_mutation(row): if len(row['ref']) > len(row['alt']): return 'del' elif len(row['ref']) == len(row['alt']): return 'subst' elif ',' in row['alt']: return 'subst' else: return 'ins' def take_from_coord(coordinates, column_name, row): return coordinates[(coordinates['chr'] == row['chrom']) & (coordinates['start'] < int(row['pos'])) & (coordinates['stop'] > int(row['pos']))][column_name].values[0] def seq_type(value, list_df): if 'hsa-' in value: return 'mirna' elif value in list_df: return 'cancer_exome' else: return 'not_defined' def subst_type(row): if row['mutation_type'] == 'subst': if (((row['ref'] in ['A', 'G']) and (row['alt'] in ['A', 'G'])) or ((row['ref'] in ['C', 'T']) and (row['alt'] in ['C', 'T']))): return 'transition' else: return 'transversion' else: return 'n.a.'

[ "martyna.urbanek@gmail.com" ]

martyna.urbanek@gmail.com

b4c799535b5e0995f3c1d6c81b0b0eaede036e40

19200bc6b36e33f9dec1394b90ff41272601b16d

/gistApi/asgi.py

d22173ac28e314752aaea0d52dc74a9b1c28f963

[]

no_license

AnoshaRehan/github-gist-api-django

103c8f0656899cd6cf068ea7945f29a51eb90e56

4c0a97f7eebca276de050ae071aabe40331806e1

refs/heads/main

2023-03-02T09:48:38.647915

2021-02-14T08:19:04

338,624,345

0

null

UTF-8

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391

py

""" ASGI config for gistApi project. It exposes the ASGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/3.1/howto/deployment/asgi/ """ import os from django.core.asgi import get_asgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'gistApi.settings') application = get_asgi_application()

[ "anosha.rehan@lovefordata.com" ]

anosha.rehan@lovefordata.com

5f2b378d006e7aa2e46251661e0d4e03d3b9810f

d452e34253561a47b974e260dabd8dcda6e750a2

/supervised_learning/0x0B-face_verification/5-main.py

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[]

no_license

JohnCook17/holbertonschool-machine_learning

57fcb5b9d351826c3e3d5478b3b4fbe16cdfac9f

4200798bdbbe828db94e5585b62a595e3a96c3e6

refs/heads/master

2021-07-07T10:16:21.583107

2021-04-11T20:38:33

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#!/usr/bin/env python3 from align import FaceAlign import matplotlib.image as mpimg import matplotlib.pyplot as plt from matplotlib.patches import Circle import numpy as np fa = FaceAlign('models/landmarks.dat') test_img = mpimg.imread('HBTN/KirenSrinivasan.jpg') anchors = np.array([[0.194157, 0.16926692], [0.7888591, 0.15817115], [0.4949509, 0.5144414]], dtype=np.float32) aligned = fa.align(test_img, np.array([36, 45, 33]), anchors, 96) plt.imshow(aligned) ax = plt.gca() for anchor in anchors: ax.add_patch(Circle(anchor * 96, 1)) plt.show()

[ "jcook0017@gmail.com" ]

jcook0017@gmail.com

d5b8181aea069440370a3630b8e9b4e47a43870f

72c9e235b19b80d9e332c1f19e1c4e1e28ff2cac

/craw/spider/LJ_parser.py

c2d8b50614943d46663ac37ac69ad4d2e39a7455

[]

no_license

VinceLim68/python-craw

56a1299b4e3ac55a3690946a6f4ff8c2c1ef5b04

37d1570ee10d080e55b5b8cf885b7e7a3b00c81d

refs/heads/master

2021-01-20T06:12:10.753799

2017-10-28T13:56:30

89,851,102

1

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UTF-8

Python

false

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py

#coding:utf-8 from html_parser import HtmlParser import mytools import urllib2 from bs4 import BeautifulSoup import re class LjParser(HtmlParser): # 这些是2016.11.17重写的，原来那个出现了解析错误 def _get_new_datas(self,soup): page_datas = [] titles = soup.select("div.title > a") houseinfo = soup.select("div.houseInfo") positionInfo = soup.select("div.positionInfo") totalprices = soup.select("div.totalPrice") for title,info,position,totalPrice in zip(titles,houseinfo,positionInfo,totalprices): # each_data有些需要设置初始值 each_data = {'builded_year':0,'spatial_arrangement':'','floor_index':0,'total_floor':0} each_data['title'] = title.get_text() each_data['details_url'] = title.get('href') each_data['total_price'] = int(round(float(re.search('(\d+.?\d+)万'.decode('utf8'),totalPrice.get_text()).groups(0)[0]),0)) info_item = (info.get_text().split('|')) each_data['community_name'] = info_item[0].strip() # 第1个总是小区名称 for i in range(1,len(info_item)): d1 = {} d1 = self.parse_item(info_item[i].strip()) if d1.has_key('advantage') and each_data.has_key('advantage'): d1['advantage'] = each_data['advantage'] + ',' + d1['advantage'] each_data = dict(each_data, **d1) position = position.get_text().replace('\t','').replace('\n','').split() each_data['block'] = position[-1] if ')' not in position[0]: #链前的别墅会用'4层2008年建'的形式，加入')'，以便分隔 position[0] = position[0].replace('层', '层)') for item in position[0].split(')'): #2017.4.1链家格式有改 d1 = {} # d1 = self.parse_item(position[i].strip()) d1 = self.parse_item(item.strip()) #2017.4.1链家格式有改 each_data = dict(each_data, **d1) each_data['price'] = float(each_data['total_price']*10000/each_data['area']) each_data['from'] = "lianjia" each_data = self.pipe(each_data) if each_data.has_key('total_floor') and each_data.has_key('total_price') and each_data.has_key('area') and each_data.has_key('community_name'): page_datas.append(each_data) else: if mytools.ShowInvalideData(each_data):page_datas.append(each_data) return page_datas def _get_new_urls(self , soup): new_urls = set() # links = soup.select("div.page-box") links = soup.select("div.house-lst-page-box") #2016.11.11修改，网页改了 if len(links) == 0 : print "Only 1 page!!" else: t_page = eval(links[0].get('page-data'))['totalPage'] url = links[0].get('page-url') for i in range(1,t_page+1): new_urls.add("http://xm.lianjia.com" + url.replace("{page}",str(i))) return new_urls def _ischeck(self,soup): # 判断是否是验证界面 ischeck = soup.select("title") if len(ischeck) > 0: #如果找不到title,就认为不是验证界面 iscode = ischeck[0].get_text().strip() == "验证异常流量-链家网" else: iscode = False return iscode

[ "1500725439@qq.com" ]

1500725439@qq.com

7508ed13cb989f8e06150d4a366684e8cb626f4c

890c8b8e90e516a5a3880eca9b2d217662fe7d84

/armulator/armv6/opcodes/abstract_opcodes/usad8.py

6568222b03d6464463dd16b171bf86a89484d155

[ "MIT" ]

permissive

doronz88/armulator

b864135996f876c7857b79a314d4aa06cc19c549

0294feac2785c8947e5943ac0c34f941ee4b5fff

refs/heads/master

2022-11-05T08:14:42.405335

2020-06-18T23:53:17

273,363,061

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2020-06-18T23:51:03

2020-06-18T23:51:02

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from armulator.armv6.opcodes.abstract_opcode import AbstractOpcode from bitstring import BitArray class Usad8(AbstractOpcode): def __init__(self, m, d, n): super(Usad8, self).__init__() self.m = m self.d = d self.n = n def execute(self, processor): if processor.condition_passed(): absdiff1 = abs( processor.registers.get(self.n)[24:32].uint - processor.registers.get(self.m)[24:32].uint) absdiff2 = abs( processor.registers.get(self.n)[16:24].uint - processor.registers.get(self.m)[16:24].uint) absdiff3 = abs( processor.registers.get(self.n)[8:16].uint - processor.registers.get(self.m)[8:16].uint) absdiff4 = abs( processor.registers.get(self.n)[0:8].uint - processor.registers.get(self.m)[0:8].uint) result = absdiff1 + absdiff2 + absdiff3 + absdiff4 processor.registers.set(self.d, BitArray(uint=result, length=32))

[ "matan1008@gmail.com" ]

matan1008@gmail.com

8b5c5c6b77660de1cffa41c624fe3f6e1c9a7840

fa88ee925ec2a3ca1def17f1518d6b3e59cab197

/Database Preprocessing/prepare_protein_data.py

f8ba54116deca63a435cf94336b6c7590a31e788

[]

no_license

asadahmedtech/DEELIG

20d915851bc053db7647d94e3ee61570524339d7

3a3993fc903c40f1ce904111c8e085c79fb45df6

refs/heads/master

2023-05-19T21:53:18.196879

2021-06-09T14:15:18

264,231,113

9

5

null

UTF-8

Python

false

4,353

py

from Bio import * import os #PDB Parser from Bio.PDB.PDBParser import PDBParser from Bio.PDB.DSSP import DSSP from Bio.PDB.NACCESS import run_naccess, process_rsa_data import pickle #Labels for files """Secondary Structure in Millers Format H - Alpha Helix (4-12) = 1 B - Isolated Beta Bridge residue = 2 E - Strand = 3 G - 3-10 helix = 4 I - Pi Helix = 5 T - Turn = 6 S - bend = 7 - - None = 0 """ SS_Labels = {'H' : 1, 'B' : 2, 'E' : 3, 'G' : 4, 'I' : 5, 'T' : 6, 'S' : 7, '-' : 0} """Relactive Solvent Accessiblity (RSA) Threshold = 25 Exposed (> Threshold) = 1 Burried (<= Threshold) = 0 """ RSA_Threshold = 25 def parse_PSSM(file, path = '/home/binnu/Asad/dataset/new_db/pssm/'): pssm = {} with open(os.path.join(path, file), 'r') as f: lines = f.readlines() # lines = [i.split() if(len(i.split()) == 44) for i in lines] lines_new = [] for i in lines: i = i.split() if(len(i) == 44): lines_new.append(i) lines_new = [i[:22] for i in lines_new] for i in lines_new: scores = i[2:] scores = [int(temp_i) for temp_i in scores] pssm[i[0]] = scores # print(pssm) return pssm def calc_features(PATH, pdb_ligand_ID, OUTPATH): #Loading the files parser = PDBParser(PERMISSIVE = 1) PDB_id = pdb_ligand_ID[:4].lower() #+ '_pocket' filename = os.path.join(PATH, PDB_id + ".pdb") structure = parser.get_structure(PDB_id, filename) model = structure[0] #DSSP Analysis for SS, PHI, PSI dssp = DSSP(model, filename) #NACCESS Analysis for SASA rsa, asa = run_naccess(model, filename) rsa = process_rsa_data(rsa) # print(rsa) #Feature mapping to each atomic coordinate dssp_present, dssp_not_present = 0, 0 feature = dict() #The feature dictionary for model in structure: for chain in model: if(chain.get_full_id()[2] == pdb_ligand_ID.split('_')[2]): pssm_ID = chain.get_full_id()[0][:4].upper() + '_' + chain.get_full_id()[2] pssm = parse_PSSM(pssm_ID) start = True gap = 0 idx_prev = 0 for residue in chain: # if(start): # start_idx =residue.get_full_id()[3][1] # idx_prev = 0 idx = residue.get_full_id()[3][1] if(idx < 1): print(idx) a = 0 pass elif(idx - idx_prev >= 1): print(idx) a = 1 gap += idx - idx_prev -1 # elif(start): # gap += -1 # start = False for atom in residue: # print(atom.get_full_id()) ID = (atom.get_full_id()[2], atom.get_full_id()[3]) if(ID in list(dssp.keys())): if(rsa[ID]["all_atoms_abs"] > RSA_Threshold): rsa_label = 1 else: rsa_label = 0 print(gap, atom.get_full_id()[3][1], a) feat = (SS_Labels[dssp[ID][2]], dssp[ID][4]/360, dssp[ID][5]/360, rsa_label) + tuple(pssm[str(atom.get_full_id()[3][1] - gap)]) feature[tuple(atom.get_coord())] = feat print(pdb_ligand_ID[:4], ID, atom.get_coord(), feat) dssp_present += 1 else: print(">>> ID not present : ", atom.get_full_id()) dssp_not_present += 1 idx_prev = idx #Printing the Stats print("===> STATS : PDBID : %s , DSSP PRESENT : %s , DSSP NOT PRESENT : %s"%(PDB_id, dssp_present, dssp_not_present)) #Saving the feature to each PDB file with open(os.path.join(OUTPATH, pdb_ligand_ID + ".dat"), "wb+") as f: pickle.dump(feature, f) print("====> Dump completed") if __name__ == '__main__': input_dir = '/home/binnu/Asad/dataset/new_db/protein_pdb/' output_dir = "/home/binnu/Asad/dataset/new_db/protein_pdb_featurized/" IDs = '/home/binnu/Asad/dataset/new_db/PDB_ligands_chain_ID_pssm_Admet_padel.txt' files = open(IDs, 'r') files = files.readlines() files = [i[:-1] for i in files] files_done = os.listdir(output_dir) files_done = [i[:-4] for i in files_done] print(files_done) naccess_error = ['5FQD_LVY', '4EJG_NCT', '3N7A_FA1' , '2IJ7_TPF', '4EJH_0QA','2QJY_SMA','1WPG_TG1', '2A06_SMA','4UHL_VFV','3N8K_D1X','5FV9_Y6W','3N75_G4P','3B8H_NAD','3B82_NAD','3B78_NAD'] for file in files: if(file not in files_done) and file.split('_')[0] + '_' + file.split('_')[1] not in naccess_error: print("==> Featurizing : ", file) calc_features(input_dir, file, output_dir)

[ "aahmed3@student.nitw.ac.in" ]

aahmed3@student.nitw.ac.in

844abc176cf2c1ec5d48f1e98a0747b94eccebec

004b7726cfbedd6ecb6a1dec455211f1b1635919

/OCR_Test/gendata.py

8b5a276f17c703b35952b97c6ac1e980d94f708b

[]

no_license

bluedott/p3_fuckup

e1cafabeda43b2d190836bd994c4af5d5b8c2379

6ff119cded8c30ef3acfc02c5ecefaa4d9178520

refs/heads/main

2023-01-22T00:16:01.252835

2020-12-07T03:00:45

319,187,963

0

1

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UTF-8

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py

# GenData.py import sys import numpy as np import cv2 import os # module level variables ########################################################################## MIN_CONTOUR_AREA = 100 RESIZED_IMAGE_WIDTH = 20 RESIZED_IMAGE_HEIGHT = 30 ################################################################################################### def main(): imgTrainingNumbers = cv2.imread("training_chars_small_test.png") # read in training numbers image if imgTrainingNumbers is None: # if image was not read successfully print ("error: image not read from file \n\n") # print error message to std out os.system("pause") # pause so user can see error message return # and exit function (which exits program) # end if imgGray = cv2.cvtColor(imgTrainingNumbers, cv2.COLOR_BGR2GRAY) # get grayscale image imgBlurred = cv2.GaussianBlur(imgGray, (5,5), 0) # blur # filter image from grayscale to black and white imgThresh = cv2.adaptiveThreshold(imgBlurred, # input image 255, # make pixels that pass the threshold full white cv2.ADAPTIVE_THRESH_GAUSSIAN_C, # use gaussian rather than mean, seems to give better results cv2.THRESH_BINARY_INV, # invert so foreground will be white, background will be black 11, # size of a pixel neighborhood used to calculate threshold value 2) # constant subtracted from the mean or weighted mean cv2.imshow("imgThresh", imgThresh) # show threshold image for reference imgThreshCopy = imgThresh.copy() # make a copy of the thresh image, this in necessary b/c findContours modifies the image imgContours, npaContours, npaHierarchy = cv2.findContours(imgThreshCopy, # input image, make sure to use a copy since the function will modify this image in the course of finding contours cv2.RETR_EXTERNAL, # retrieve the outermost contours only cv2.CHAIN_APPROX_SIMPLE) # compress horizontal, vertical, and diagonal segments and leave only their end points # declare empty numpy array, we will use this to write to file later # zero rows, enough cols to hold all image data npaFlattenedImages = np.empty((0, RESIZED_IMAGE_WIDTH * RESIZED_IMAGE_HEIGHT)) intClassifications = [] # declare empty classifications list, this will be our list of how we are classifying our chars from user input, we will write to file at the end # possible chars we are interested in are digits 0 through 9, put these in list intValidChars intValidChars = [ord('0'), ord('1'), ord('2'), ord('3'), ord('4'), ord('5'), ord('6'), ord('7'), ord('8'), ord('9'), ord('A'), ord('B'), ord('C'), ord('D'), ord('E'), ord('F'), ord('G'), ord('H'), ord('I'), ord('J'), ord('K'), ord('L'), ord('M'), ord('N'), ord('O'), ord('P'), ord('Q'), ord('R'), ord('S'), ord('T'), ord('U'), ord('V'), ord('W'), ord('X'), ord('Y'), ord('Z')] for npaContour in npaContours: # for each contour if cv2.contourArea(npaContour) > MIN_CONTOUR_AREA: # if contour is big enough to consider [intX, intY, intW, intH] = cv2.boundingRect(npaContour) # get and break out bounding rect # draw rectangle around each contour as we ask user for input cv2.rectangle(imgTrainingNumbers, # draw rectangle on original training image (intX, intY), # upper left corner (intX+intW,intY+intH), # lower right corner (0, 0, 255), # red 2) # thickness imgROI = imgThresh[intY:intY+intH, intX:intX+intW] # crop char out of threshold image imgROIResized = cv2.resize(imgROI, (RESIZED_IMAGE_WIDTH, RESIZED_IMAGE_HEIGHT)) # resize image, this will be more consistent for recognition and storage cv2.imshow("imgROI", imgROI) # show cropped out char for reference cv2.imshow("imgROIResized", imgROIResized) # show resized image for reference cv2.imshow("training_numbers.png", imgTrainingNumbers) # show training numbers image, this will now have red rectangles drawn on it intChar = cv2.waitKey(0) # get key press if intChar == 27: # if esc key was pressed sys.exit() # exit program elif intChar in intValidChars: # else if the char is in the list of chars we are looking for . . . intClassifications.append(intChar) # append classification char to integer list of chars (we will convert to float later before writing to file) npaFlattenedImage = imgROIResized.reshape((1, RESIZED_IMAGE_WIDTH * RESIZED_IMAGE_HEIGHT)) # flatten image to 1d numpy array so we can write to file later npaFlattenedImages = np.append(npaFlattenedImages, npaFlattenedImage, 0) # add current flattened impage numpy array to list of flattened image numpy arrays # end if # end if # end for fltClassifications = np.array(intClassifications, np.float32) # convert classifications list of ints to numpy array of floats npaClassifications = fltClassifications.reshape((fltClassifications.size, 1)) # flatten numpy array of floats to 1d so we can write to file later print ("\n\ntraining complete !!\n") np.savetxt("classifications2.txt", npaClassifications) # write flattened images to file np.savetxt("flattened_images2.txt", npaFlattenedImages) # cv2.destroyAllWindows() # remove windows from memory return ################################################################################################### if __name__ == "__main__": main() # end if

[ "34089891+bluedott@users.noreply.github.com" ]

34089891+bluedott@users.noreply.github.com

84670e385fe2ed6a8e0c8a66732d455455589e1c

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/spotify_convert/migrations/0011_remove_addedsong_spotify_name.py

555b6a34320e1e011c126db41348d3376c956b96

[]

no_license

mvasiliou/spotify-convert-app

4bf86443ce9c216dc8a9bcbf3f7c81ff01828175

876e456c956fd0aeae65dc1db9f683373bfa9c9e

refs/heads/master

2021-01-19T13:37:19.060429

2017-02-18T17:25:00

82,402,537

0

null

UTF-8

Python

false

409

py

# -*- coding: utf-8 -*- # Generated by Django 1.9.2 on 2017-02-15 22:01 from __future__ import unicode_literals from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('spotify_convert', '0010_auto_20170215_1712'), ] operations = [ migrations.RemoveField( model_name='addedsong', name='spotify_name', ), ]

[ "mvasiliou94@gmail.com" ]

mvasiliou94@gmail.com

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/internet connection check.py

025e54ba14c6fdfcd2dcc55e5a6b72e06dbf6956

[]

no_license

thatscoding/Hacktoberfest-2023

e67594420d39340095dde77e02bcf20353a5f645

40cfc950487e040b192a304a9d387dda2988845b

refs/heads/main

2023-08-28T07:28:41.110272

2021-10-30T11:48:00

null

0

null

UTF-8

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py

import requests from requests.exceptions import ConnectionError def internet_connection_test(): url = 'https://www.google.com/' print(f'Attempting to connect to {url} to determine internet connection status.') try: print(url) resp = requests.get(url, timeout = 10) resp.text resp.status_code print(f'Connection to {url} was successful.') return True except ConnectionError as e: requests.ConnectionError print(f'Failed to connect to {url}.') return False except: print(f'Failed with unparsed reason.') return False internet_connection_test()

[ "noreply@github.com" ]

thatscoding.noreply@github.com

cfbc73e87a1f617dd5d05185217fead9b365b1cd

8c0e6de3a106ef148dd2994973f3f5cb807c70eb

/General Programing/Documentation Hub/imageviewer.py

ac39a35f9c94c5dffe56d0b6d169a8e29ad2f0fd

[]

no_license

TKprotich/Practices-and-Experimenting

8f8928cc43e6cb9996b064d66dc6783fc8edf362

211e11f3f52b36dd6dc944d3b503c81d412acb4b

refs/heads/main

2023-01-11T00:12:14.404189

2020-11-15T13:41:24

304,259,482

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import pyglet window = pyglet.window.Window() image = pyglet.resource.image('workout.JPG') @window.event def on_draw(): window.clear() image.blit(0, 0) pyglet.app.run()

[ "marchemjor@gmail.com" ]

marchemjor@gmail.com

4e1ab212e6ce46a3bc3a610e4685b7449006b6ef

ad9a1711ec2d36b57576b30a5550a481bc07452a

/PANDAS/ser_02.py

f5d076631ff20dc4605d988fb89dd07e2abd6ebf

[]

no_license

Harshad06/Python_programs

5ca0ba3ba8cbccbd39215efec96fb7b68307aa5a

ad908e59425b41c1bed032aaf9a115e123fd46c4

refs/heads/master

2023-06-22T07:44:45.435258

2021-07-26T08:16:22

347,367,223

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py

# porgam to depict deep copy # in pandas series # import module import pandas as pd # assign series ser = pd.Series(['Mandy', 'Ron', 'Jacob', 'Bayek']) # shallow copy copyser = ser.copy(deep=True) # comparing deep copied series # and original series print('\nBefore Operation:\n', copyser == ser) # assignmnet operation copyser[2] = 'Geeks' # comparing deep copied series # and original series print('\nAfter Operation:\n', copyser == ser) print('\nOriginal Dataframe after operation:\n', ser)

[ "harshad.shringi@gmail.com" ]

harshad.shringi@gmail.com

3f45f7cee6d8468efa1e1fb46e91f0292b773b93

22295cda10cf11472fee987093e0b245f6f96ef3

/common/infohistology/band073_tracks.py

bd72af8bb7165ed2ca221d979e82efa7299e791e

[]

no_license

sjara/jaratest

aecb9e3bcc1ff91db35e7cd551c0f4f3da0b690a

09bf2c76bd5bf45191a2c37c14171ae1e8902c4b

refs/heads/master

2023-08-11T09:55:17.684814

2023-08-03T22:03:31

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2023-04-11T18:14:08

2016-07-11T20:43:04

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py

''' TODO: - add reference to type of recording device used? e.g. tetrode vs silicon probe, probe geometry, etc. - 'shank' is very specific to silicon probes, replace with more generic info key? ''' subject = 'band073' tracks = [ {'subject':subject, 'brainArea':'LeftAC', 'histImage':'p1-C5-03', 'recordingTrack':'midlateralDiO', 'shank':1, 'atlasZ':180}, {'subject':subject, 'brainArea':'LeftAC', 'histImage':'p1_D1-03', 'recordingTrack':'medialDiD', 'shank':1, 'atlasZ':185}, {'subject':subject, 'brainArea':'LeftAC', 'histImage':'p1_D5-03', 'recordingTrack':'medialDiD', 'shank':2, 'atlasZ':193}, {'subject':subject, 'brainArea':'LeftAC', 'histImage':'p1-D2-03', 'recordingTrack':'midlateralDiO', 'shank':2, 'atlasZ':188}, {'subject':subject, 'brainArea':'LeftAC', 'histImage':'p2_A1-03', 'recordingTrack':'medialDiD', 'shank':3, 'atlasZ':200}, {'subject':subject, 'brainArea':'LeftAC', 'histImage':'p2_A5-03', 'recordingTrack':'medialDiD', 'shank':4, 'atlasZ':208}, {'subject':subject, 'brainArea':'RightAC', 'histImage':'p2-A2-02', 'recordingTrack':'middleDiO', 'shank':4, 'atlasZ':201}, {'subject':subject, 'brainArea':'RightAC', 'histImage':'p2-A5-02', 'recordingTrack':'middleDiO', 'shank':3, 'atlasZ':206}, {'subject':subject, 'brainArea':'RightAC', 'histImage':'p2-B3-02', 'recordingTrack':'middleDiO', 'shank':2, 'atlasZ':212}, {'subject':subject, 'brainArea':'RightAC', 'histImage':'p2-B5-02', 'recordingTrack':'medialDiD', 'shank':1, 'atlasZ':219}, {'subject':subject, 'brainArea':'RightAC', 'histImage':'p2-C2-02', 'recordingTrack':'middleDiO', 'shank':1, 'atlasZ':225}, ]

[ "jarauser@jararigtest" ]

jarauser@jararigtest

664fd5e22572825ff02d5842fce584a415d850a8

62bdde43ce88507530610a2b77d2ce0859eebc8b

/SWEA/queue/L5105-미로의_거리/L5105-미로의_거리-jiwoong.py

9ca4aecca30d1d8a77e4b2053a655343efd4a697

[]

no_license

j2woong1/algo-itzy

6810f688654105cf4aefda3b0876f714ca8cbd08

7cf6cd8383dd8e9ca63f605609aab003790e1565

refs/heads/master

2023-08-21T12:51:54.874102

2021-10-03T04:35:21

null

0

null

UTF-8

Python

false

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py

def bfs(x, y, z, visited): # 상하좌우 dx = [0, 1, 0, -1] dy = [-1, 0, 1, 0] # 현재 위치 queue q = [(x, y, z)] # 큐가 빌 때까지 while q: curr_x, curr_y, curr_z = q.pop(0) visited[curr_y][curr_x] = 1 for i in range(4): # 나가지 않으면 if 0 <= curr_y + dy[i] < N and 0 <= curr_x + dx[i] < N: new_x = curr_x + dx[i] new_y = curr_y + dy[i] if arr[new_y][new_x] == 3: return curr_z if not arr[new_y][new_x] and not visited[new_y][new_x]: q.append((new_x, new_y, curr_z + 1)) return 0 T = int(input()) for tc in range(1, T + 1): N = int(input()) arr = [] for i in range(N): arr.append(list(map(int, input()))) visited = [[0] * N for _ in range(N)] for i in range(N): for j in range(N): if arr[i][j] == 2: print(f'#{tc} {bfs(j, i, 0, visited)}')

[ "j2woong1@gmail.com" ]

j2woong1@gmail.com

78abb25a1c9ddc2546892cffbfa7b04ce2ad80ee

2298959b25d93360be8dc45f00e989cac96b5c5d

/ex40.py

6f7443d7d3dc28ec948c6a9106ff589391e9d7f1

[]

no_license

VigneshMcity/Python

6e7cdef7e4cb09eec587ca85073f8171aa9492ec

8970368210d6e8c3f6ab1f6e6cf3213dd51b004a

refs/heads/master

2020-04-14T20:08:27.298067

2019-12-13T07:17:04

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null

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435

py

class Song(object): def __init__(self, lyrics): self.lyrics = lyrics def sing_me_a_song(self): for line in self.lyrics: print(line) happy_bday = Song([ "Happy birthday to you", "I dont want to get sued", "So I'll stop right here" ]) bulls_on_parade = Song([ "They rally around the family", "With pocket full of sheels" ]) happy_bday.sing_me_a_song() bulls_on_parade.sing_me_a_song()

[ "vignesh.rajendran01@infosys.com" ]

vignesh.rajendran01@infosys.com