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lyzustc/Reinforcement_Learning
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import tensorflow as tf import numpy as np from DQN import DQN class DoubleDQN(DQN): def __init__( self, n_actions, n_features, sess, learning_rate=0.01, reward_decay=0.9, e_greedy=0.9, replace_target_iter=300, memory_size=500, batch_size=32, e_greedy_increment=None, store_q = False ): super(DoubleDQN, self). __init__( n_actions, n_features, sess, learning_rate, reward_decay, e_greedy, replace_target_iter, memory_size, batch_size, e_greedy_increment, store_q ) def learn(self): s, a, r, s_ = self.sample() if self.learn_step_counter % self.replace_target_iter == 0: self.sess.run(self.replace_target_op) print('\ntarget_params_replaced\n') q_next, q_eval = self.sess.run( [self.q_next, self.q_eval], feed_dict={self.s_: s_, self.s: s} ) q_target = q_eval.copy() batch_index = np.arange(self.batch_size) q_next_new = self.sess.run(self.q_eval, feed_dict={self.s: s_}) max_actions = np.argmax(q_next_new, axis=1) q_target[batch_index, a] = r + self.gamma * q_next[batch_index, max_actions] _, self.cost = self.sess.run([self._train_op, self.loss], feed_dict={self.s: s, self.q_target: q_target}) self.epsilon = self.epsilon + self.epsilon_increment if self.epsilon < self.epsilon_max else self.epsilon_max self.learn_step_counter += 1 if __name__ == '__main__': import gym import matplotlib.pyplot as plt env = gym.make("Pendulum-v0") env.seed(1) MEMORY_SIZE = 3000 ACTION_SPACE = 11 sess = tf.Session() with tf.variable_scope("Natural_DQN"): natural_DQN = DQN( n_actions=ACTION_SPACE, n_features=env.observation_space.shape[0], memory_size=MEMORY_SIZE, e_greedy_increment=0.001, sess=sess, store_q = True ) with tf.variable_scope("Double_DQN"): double_DQN = DoubleDQN( n_actions=ACTION_SPACE, n_features=env.observation_space.shape[0], memory_size=MEMORY_SIZE, e_greedy_increment=0.001, sess=sess, store_q=True ) sess.run(tf.global_variables_initializer()) def train(learner): total_steps = 0 s = env.reset() while True: # env.render() a = learner.choose_action(s) f_action = (a - (ACTION_SPACE - 1) / 2) / ((ACTION_SPACE - 1) / 4) s_new, reward, done, info = env.step(np.array([f_action])) reward /= 10 learner.store_transition(s, a, reward, s_new) if total_steps > MEMORY_SIZE: learner.learn() if total_steps - MEMORY_SIZE > 20000: break s = s_new total_steps += 1 return learner.q q_natural = train(natural_DQN) q_double = train(double_DQN) plt.plot(np.array(q_natural), c='r', label='natural') plt.plot(np.array(q_double), c='b', label='double') plt.legend(loc='best') plt.ylabel('Q eval') plt.xlabel('training steps') plt.grid() plt.show()
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#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2018/12/10/9:24 # @Author : SnrsGu # @Email : SnrsGu@qq.com & SnrsGu@gmail.com # @File : salary_site_analyze.py # @Software: PyCharm from functools import reduce import pandas as pd from pylab import * mpl.rcParams['font.sans-serif'] = ['SimHei'] plt.rcParams['axes.unicode_minus'] = False def alter(list): a = str(list) w_rex = '([\d+\.\d]*)-([\d+\.\d]*)万/月' k_rex = '([\d+\.\d]*)-([\d+\.\d]*)千/月' w_x = re.findall(w_rex, a) # 获得待处理的万元每月的数据 k_x = re.findall(k_rex, a) # 获得待处理的千元每月的数据 w_xx = eval(str(w_x).replace('(', '').replace(')', '')) k_xx = eval(str(k_x).replace('(', '').replace(')', '')) w = [] k = [] for w_ in w_xx: w.append(int(eval(w_) * 10)) for k_ in k_xx: w.append(eval(k_)) zong = w + k return reduce(lambda x, y: x + y, zong) / len(zong) def salary_site(df): area = ['北京-东城区', '北京-丰台区', '北京-大兴区', '北京-延庆区', '北京-房山区', '北京-昌平区', '北京-朝阳区', '北京-海淀区', '北京-石景山区', '北京-西城区', '北京-通州区', '北京-门头沟区','北京-顺义区'] salary_mean = [] for i in area: a = int(alter(list(df[df['company_site'].isin([i])].dropna(how='any').salary.values))) salary_mean.append(a) print(salary_mean) plt.barh(area, salary_mean, color='lime') ax = plt.gca() for i in ax.spines: ax.spines[i].set_color('none') ax.xaxis.grid(True) plt.title('前程无忧Python招聘地区与工资关系') plt.xlabel('薪资区间(千/月)') plt.show() if __name__ == '__main__': df = pd.read_csv('51job.csv', encoding='gbk') salary_site(df)
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import argparse import logging import os import math import random import cv2 as cv import numpy as np import torch import torch.nn.functional as F from torch.utils.data import Sampler from skimage.measure import label import scipy.ndimage import scipy.ndimage.morphology from torchvision import transforms from config import im_size, epsilon, epsilon_sqr, device def clip_gradient(optimizer, grad_clip): """ Clips gradients computed during backpropagation to avoid explosion of gradients. :param optimizer: optimizer with the gradients to be clipped :param grad_clip: clip value """ for group in optimizer.param_groups: for param in group['params']: if param.grad is not None: param.grad.data.clamp_(-grad_clip, grad_clip) def save_checkpoint(epoch, epochs_since_improvement, model, optimizer, loss, is_best, logdir): state = {'epoch': epoch, 'epochs_since_improvement': epochs_since_improvement, 'loss': loss, 'model': model, 'optimizer': optimizer, 'torch_seed': torch.get_rng_state(), 'torch_cuda_seed': torch.cuda.get_rng_state(), 'np_seed': np.random.get_state(), 'python_seed': random.getstate()} filename = logdir + '/checkpoint_' + str(epoch) + '_' + str(loss) + '.tar' # filename = 'checkpoint.tar' torch.save(state, filename) # If this checkpoint is the best so far, store a copy so it doesn't get overwritten by a worse checkpoint if is_best: torch.save(state, logdir + '/BEST_checkpoint.tar') def save_checkpoint_2(epoch, epochs_since_improvement, model, optimizer, loss, is_best): state = {'epoch': epoch, 'epochs_since_improvement': epochs_since_improvement, 'loss': loss, 'model': model, 'optimizer': optimizer} filename = 'checkpoints_2/checkpoint_' + str(epoch) + '_' + str(loss) + '.tar' # filename = 'checkpoint.tar' torch.save(state, filename) # If this checkpoint is the best so far, store a copy so it doesn't get overwritten by a worse checkpoint if is_best: torch.save(state, 'checkpoints_2/BEST_checkpoint.tar') def save_checkpoint_4(epoch, epochs_since_improvement, model, optimizer, loss, is_best): state = {'epoch': epoch, 'epochs_since_improvement': epochs_since_improvement, 'loss': loss, 'model': model, 'optimizer': optimizer} filename = 'checkpoints_4/checkpoint_' + str(epoch) + '_' + str(loss) + '.tar' # filename = 'checkpoint.tar' torch.save(state, filename) # If this checkpoint is the best so far, store a copy so it doesn't get overwritten by a worse checkpoint if is_best: torch.save(state, 'checkpoints_4/BEST_checkpoint.tar') def save_checkpoint_5(epoch, epochs_since_improvement, model, optimizer, loss, is_best): state = {'epoch': epoch, 'epochs_since_improvement': epochs_since_improvement, 'loss': loss, 'model': model, 'optimizer': optimizer} filename = 'checkpoints_5/checkpoint_' + str(epoch) + '_' + str(loss) + '.tar' # filename = 'checkpoint.tar' torch.save(state, filename) # If this checkpoint is the best so far, store a copy so it doesn't get overwritten by a worse checkpoint if is_best: torch.save(state, 'checkpoints_5/BEST_checkpoint.tar') class AverageMeter(object): """ Keeps track of most recent, average, sum, and count of a metric. """ def __init__(self): self.reset() def reset(self): self.val = 0 self.avg = 0 self.sum = 0 self.count = 0 def update(self, val, n=1): self.val = val self.sum += val * n self.count += n self.avg = self.sum / self.count def adjust_learning_rate(optimizer, shrink_factor): """ Shrinks learning rate by a specified factor. :param optimizer: optimizer whose learning rate must be shrunk. :param shrink_factor: factor in interval (0, 1) to multiply learning rate with. """ print("\nDECAYING learning rate.") for param_group in optimizer.param_groups: param_group['lr'] = param_group['lr'] * shrink_factor print("The new learning rate is %f\n" % (optimizer.param_groups[0]['lr'],)) def get_learning_rate(optimizer): return optimizer.param_groups[0]['lr'] def accuracy(scores, targets, k=1): batch_size = targets.size(0) _, ind = scores.topk(k, 1, True, True) correct = ind.eq(targets.view(-1, 1).expand_as(ind)) correct_total = correct.view(-1).float().sum() # 0D tensor return correct_total.item() * (100.0 / batch_size) def parse_args(): parser = argparse.ArgumentParser(description='Train face network') # general parser.add_argument('--checkpointdir', type=str) parser.add_argument('--print-freq', type=int, default=100) parser.add_argument('--logdir', type=str) parser.add_argument('--random-interp', type=bool, default=True, help='randomly choose interpolation') parser.add_argument('--start-epoch', type=int, default=0, help='start epoch.') parser.add_argument('--end-epoch', type=int, default=1000, help='training epoch size.') parser.add_argument('--lr', type=float, default=0.001, help='start learning rate') parser.add_argument('--lr-step', type=int, default=10, help='period of learning rate decay') parser.add_argument('--optimizer', default='adam', help='optimizer') parser.add_argument('--weight-decay', type=float, default=0.0, help='weight decay') parser.add_argument('--mom', type=float, default=0.9, help='momentum') parser.add_argument('--batch-size', type=int, default=32, help='batch size in each context') parser.add_argument('--checkpoint', type=str, default=None, help='checkpoint') parser.add_argument('--pretrained', type=bool, default=False, help='pretrained model') parser.add_argument('--data-augumentation', type=bool, default=False, help='is augument data or not') parser.add_argument('--beta1', type=float, default=0.5, help='beta1 for adam.') parser.add_argument('--beta2', type=float, default=0.999, help='beta2 for adam.') args = parser.parse_args() return args def get_logger(): logger = logging.getLogger() handler = logging.StreamHandler() formatter = logging.Formatter("%(asctime)s %(levelname)s \t%(message)s") handler.setFormatter(formatter) logger.addHandler(handler) logger.setLevel(logging.DEBUG) return logger def safe_crop(mat, x, y, crop_size=(im_size, im_size)): crop_height, crop_width = crop_size if len(mat.shape) == 2: ret = np.zeros((crop_height, crop_width), np.uint8) else: ret = np.zeros((crop_height, crop_width, 3), np.uint8) crop = mat[y:y + crop_height, x:x + crop_width] h, w = crop.shape[:2] ret[0:h, 0:w] = crop if crop_size != (im_size, im_size): ret = cv.resize(ret, dsize=(im_size, im_size), interpolation=cv.INTER_NEAREST) return ret def gauss(x, sigma): y = np.exp(-x ** 2 / (2 * sigma ** 2)) / (sigma * np.sqrt(2 * np.pi)) return y def dgauss(x, sigma): y = -x * gauss(x, sigma) / (sigma ** 2) return y def gaussgradient(im, sigma): epsilon = 1e-2 halfsize = np.ceil(sigma * np.sqrt(-2 * np.log(np.sqrt(2 * np.pi) * sigma * epsilon))).astype(np.int32) size = 2 * halfsize + 1 hx = np.zeros((size, size)) for i in range(0, size): for j in range(0, size): u = [i - halfsize, j - halfsize] hx[i, j] = gauss(u[0], sigma) * dgauss(u[1], sigma) hx = hx / np.sqrt(np.sum(np.abs(hx) * np.abs(hx))) hy = hx.transpose() gx = scipy.ndimage.convolve(im, hx, mode='nearest') gy = scipy.ndimage.convolve(im, hy, mode='nearest') return gx, gy def compute_gradient_loss(pred, target, trimap): pred_x, pred_y = gaussgradient(pred, 1.4) target_x, target_y = gaussgradient(target, 1.4) pred_amp = np.sqrt(pred_x ** 2 + pred_y ** 2) target_amp = np.sqrt(target_x ** 2 + target_y ** 2) error_map = (pred_amp - target_amp) ** 2 loss = np.sum(error_map[trimap == 128]) return loss / 1000. def getLargestCC(segmentation): labels = label(segmentation, connectivity=1) largestCC = labels == np.argmax(np.bincount(labels.flat)) return largestCC def compute_connectivity_error(pred, target, trimap, step=0.1): # pred = pred / 255.0 # target = target / 255.0 h, w = pred.shape thresh_steps = list(np.arange(0, 1 + step, step)) l_map = np.ones_like(pred, dtype=np.float) * -1 for i in range(1, len(thresh_steps)): pred_alpha_thresh = (pred >= thresh_steps[i]).astype(np.int) target_alpha_thresh = (target >= thresh_steps[i]).astype(np.int) omega = getLargestCC(pred_alpha_thresh * target_alpha_thresh).astype(np.int) flag = ((l_map == -1) & (omega == 0)).astype(np.int) l_map[flag == 1] = thresh_steps[i - 1] l_map[l_map == -1] = 1 pred_d = pred - l_map target_d = target - l_map pred_phi = 1 - pred_d * (pred_d >= 0.15).astype(np.int) target_phi = 1 - target_d * (target_d >= 0.15).astype(np.int) loss = np.sum(np.abs(pred_phi - target_phi)[trimap == 128]) return loss / 1000. # alpha prediction loss: the abosolute difference between the ground truth alpha values and the # predicted alpha values at each pixel. However, due to the non-differentiable property of # absolute values, we use the following loss function to approximate it. def mse_core(pred, true, mask): return F.mse_loss(pred * mask, true * mask, reduction='sum') / (torch.sum(mask) + epsilon) def alpha_prediction_loss(y_pred, y_true): mask = y_true[:, 1, :] pred = y_pred[:, 0, :] true = y_true[:, 0, :] return mse_core(pred, true, mask) def composition_loss(y_pred, y_true, image, fg, bg): mask = y_true[:, 1:2, :, :] mask = torch.cat((mask, mask, mask), dim=1) pred = y_pred[:, :, :] pred = pred.reshape((-1, 1, pred.shape[1], pred.shape[2])) pred = torch.cat((pred, pred, pred), dim=1) true = y_true[:, 0, :, :] merged = pred * fg + (1 - pred) * bg return mse_core(merged, image, mask) / 3. # compute the MSE error given a prediction, a ground truth and a trimap. # pred: the predicted alpha matte # target: the ground truth alpha matte # trimap: the given trimap # def compute_mse(pred, alpha, trimap): num_pixels = float((trimap == 128).sum()) return ((pred - alpha) ** 2).sum() / num_pixels # compute the SAD error given a prediction and a ground truth. # def compute_sad(pred, alpha): diff = np.abs(pred - alpha) return np.sum(diff) / 1000 def draw_str(dst, target, s): x, y = target cv.putText(dst, s, (x + 1, y + 1), cv.FONT_HERSHEY_PLAIN, 1.0, (0, 0, 0), thickness=2, lineType=cv.LINE_AA) cv.putText(dst, s, (x, y), cv.FONT_HERSHEY_PLAIN, 1.0, (255, 255, 255), lineType=cv.LINE_AA) def ensure_folder(folder): if not os.path.exists(folder): os.makedirs(folder) interp_list = [cv.INTER_NEAREST, cv.INTER_LINEAR, cv.INTER_CUBIC, cv.INTER_LANCZOS4] def maybe_random_interp(cv2_interp): if np.random.rand() < 0.5: return np.random.choice(interp_list) return cv2_interp num_fgs = 431 num_bgs_per_fg = 100 num_bgs = num_fgs * num_bgs_per_fg split_ratio = 0.2 out_names_train = 0 out_names_valid = 0 def split_name(split, num, split_index): if(split == 'train'): names = np.arange(num) np.random.shuffle(names) names_train = names[:split_index] names_valid = names[split_index:] global out_names_train out_names_train = names_train global out_names_valid out_names_valid = names_valid return out_names_train, out_names_valid class InvariantSampler(Sampler): def __init__(self, data_source, split, batch_size): super().__init__(data_source) self.data_source = data_source self.split = split self.batch_size = batch_size def generate(self): names_train, names_valid = split_name(self.split, num_fgs * 8, math.ceil(num_fgs * (1-split_ratio)) * 8) if self.split == 'train': names = names_train else: names = names_valid np.random.shuffle(names) names = names * self.batch_size names = np.expand_dims(names, 1) reduces = np.copy(names) for i in np.arange(1, self.batch_size): temp = names + i reduces = np.concatenate([reduces, temp], axis=1) reduces = reduces.reshape(-1) return np.asarray(reduces) def __iter__(self): self.names = self.generate() return iter(self.names) def __len__(self): return len(self.names) class RandomSampler(Sampler): def __init__(self, data_source, replacement=False, num_samples=None): super().__init__(data_source) self.data_source = data_source self.replacement = replacement self._num_samples = num_samples def num_samples(self): # dataset size might change at runtime if self._num_samples is None: return len(self.data_source) return self._num_samples def __iter__(self): n = self.__len__() if self.replacement: return iter(torch.randint(high=n, size=(self.num_samples,), dtype=torch.int64).tolist()) return iter(torch.randperm(n).tolist()) def __len__(self): return self.num_samples()
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from cmath import sin, cos, sqrt, log, tan from pylab import arctan2, pi def csc(x): return 1/sin(x) def cot(x): return 1/tan(x) def integ1(x, a): return -(csc(x) * sqrt(-2 * a**2 + cos(2 * x) - 1) * log(sqrt(-2 * a**2 + cos(2 * x) - 1) + sqrt(2) * cos(x)))/sqrt(2 * a**2 * csc(x)**2 + 2) def integ(x, a): return 4/pi * (csc(x)**2 * (sqrt(2) * csc(x) * (-2 * a**2 + cos(2 * x) - 1)**(3/2) * log(sqrt(-2 * a**2 + cos(2 * x) - 1) + sqrt(2) * cos(x)) - (2 * a**2 * cot(x) * (-2 * a**2 + cos(2 * x) - 1))/(a**2 + 1)))/(12 * (a**2 * csc(x)**2 + 1)**(3/2)) H1 = 20 H2 = 24 h = 20 s12 = integ(arctan2(H2, -H1), h/H2) - integ(arctan2(H2, H1), h/H2) s21 = integ(arctan2(H1, -H2), h/H1) - integ(arctan2(H1, H2), h/H1) I = 2 * (s12 + s21) print(I/(2*pi), ' frazione dei muoni totali')
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udhayprakash/PythonMaterial
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/python3/14_Code_Quality/01_static_typing/k_Union_type.py
7cb6191172607e458c2ef7ba4024f2f628d5f8c7
[]
no_license
https://github.com/udhayprakash/PythonMaterial
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e72f44e147141ebc9bf9ec126b70a5fcdbfbd076
refs/heads/develop
2023-07-08T21:07:33.154577
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""" Purpose: Union type """ from typing import Union def is_even_whole(num) -> Union[bool, str]: if num < 0: return "Not a whole number" return True if num % 2 == 0 else False assert is_even_whole(10) is True assert is_even_whole(19) is False assert is_even_whole(-2) == "Not a whole number" def is_even_whole2(num) -> Union[bool, Exception]: if num < 0: return Exception("Not a whole number") return True if num % 2 == 0 else False assert is_even_whole2(10) is True assert is_even_whole2(19) is False res = is_even_whole2(-2) assert res.args[0] == "Not a whole number"
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NickSwainston/blindsearch_scripts
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/blindsearch_database.py
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[]
no_license
https://github.com/NickSwainston/blindsearch_scripts
83f9bf0c0ba12a07975e8f827b1f00df6483a25f
53c83d3f566db6ff9953b719ec16cac1f345de20
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#!/usr/bin/env python import os, datetime, logging import sqlite3 as lite from optparse import OptionParser #NB zeus does not have argparse! DB_FILE = os.environ['CMD_BS_DB_DEF_FILE'] #how many seconds the sqlite database conection takes until it times out TIMEOUT=120 def dict_factory(cursor, row): d = {} for idx, col in enumerate(cursor.description): d[col[0]] = row[idx] return d def database_blindsearch_start(obsid, pointing, comment): con = lite.connect(DB_FILE, timeout = TIMEOUT) with con: cur = con.cursor() cur.execute("""INSERT INTO Blindsearch(Started, Obsid, Pointing, Comment, TotalProc, TotalErrors, TotalDS, TotalDE, TotalJobComp, BeamformProc, BeamformErrors, BeamformDS, BeamformDE, BeamformJobComp, PrepdataProc, PrepdataErrors, PrepdataDS, PrepdataDE, PrepdataJobComp, FFTProc, FFTErrors, FFTDS, FFTDE, FFTJobComp, AccelProc, AccelErrors, AccelDS, AccelDE, AccelJobComp, FoldProc, FoldErrors, FoldDS, FoldDE, FoldJobComp, CandTotal, CandOverNoise, CandDect) VALUES(?,?,?,?, ?,?,?,?,?, ?,?,?,?,?, ?,?,?,?,?, ?,?,?,?,?, ?,?,?,?,?, ?,?,?,?,?, ?,?,?)""", (datetime.datetime.now(), obsid, pointing, comment, 0.0, 0, 0, 0, 0, 0.0, 0, 0, 0, 0, 0.0, 0, 0, 0, 0, 0.0, 0, 0, 0, 0, 0.0, 0, 0, 0, 0, 0.0, 0, 0, 0, 0, 0, 0, 0)) vcs_command_id = cur.lastrowid return vcs_command_id def database_script_list(bs_id, command, arguments_list, threads, expe_proc_time, attempt=1): """ Will create all the rows in the database for each job """ #works out the table from the command if command == 'prepsubband': table = 'Prepdata' elif command == 'realfft': table = 'FFT' elif command == 'accelsearch': table = 'Accel' elif command == 'prepfold': table = 'Fold' print "attempt: "+str(attempt) con = lite.connect(DB_FILE, timeout = TIMEOUT) with con: cur = con.cursor() row_id_list = [] for ai, arguments in enumerate(arguments_list): cur.execute("INSERT OR IGNORE INTO "+table+" (Rownum, AttemptNum, BSID, Command, Arguments, CPUs, ExpProc) VALUES(?, ?, ?, ?, ?, ?, ?)", (ai, attempt, bs_id, command, arguments, threads, expe_proc_time)) row_id_list.append(cur.lastrowid) return row_id_list def database_script_start(table, bs_id, rownum, attempt_num, time=datetime.datetime.now()): con = lite.connect(DB_FILE, timeout = TIMEOUT) with con: cur = con.cursor() cur.execute("UPDATE "+table+" SET Started=? WHERE Rownum=? AND AttemptNum=? AND BSID=?", (time, rownum, attempt_num, bs_id)) row_id = cur.lastrowid return row_id def database_script_stop(table, bs_id, rownum, attempt_num, errorcode, end_time=datetime.datetime.now()): con = lite.connect(DB_FILE, timeout = TIMEOUT) con.row_factory = lite.Row with con: cur = con.cursor() #get script data cur.execute("SELECT * FROM "+table+" WHERE Rownum=? AND AttemptNum=? AND BSID=?", (rownum, attempt_num, bs_id)) columns = cur.fetchone() #get blindsearch data cur.execute("SELECT * FROM Blindsearch WHERE Rownum="+str(bs_id)) bs_columns = cur.fetchone() if int(errorcode) == 0: #add processing times and job completion count end_s = date_to_sec(str(end_time)) start_s = date_to_sec(columns['Started']) processing = (end_s - start_s) cur.execute("UPDATE "+table+\ " SET Proc=?, Ended=?, Exit=? WHERE Rownum=? AND AttemptNum=? AND BSID=?", (processing, end_time, errorcode, rownum, attempt_num, bs_id)) tot_proc = float(bs_columns['TotalProc']) + processing job_proc = float(bs_columns[table+'Proc']) + processing tot_jc = int(bs_columns['TotalJobComp']) + 1 job_jc = int(bs_columns[table+'JobComp']) + 1 cur.execute("UPDATE Blindsearch SET TotalProc=?, "+table+\ "Proc=?, TotalJobComp=?, "+table+\ "JobComp=? WHERE Rownum=?", (str(tot_proc)[:9], str(job_proc)[:9], str(tot_jc)[:9], str(job_jc)[:9], bs_id)) else: tot_er = int(bs_columns['TotalErrors']) + 1 job_er = int(bs_columns[table+'Errors']) + 1 cur.execute("UPDATE "+table+\ " SET Ended=?, Exit=? WHERE Rownum=? AND AttemptNum=? AND BSID=?", (end_time, errorcode, rownum, attempt_num, bs_id)) cur.execute("UPDATE Blindsearch SET TotalErrors=?, "+table+\ "Errors=? WHERE Rownum=?", (tot_er,job_er, bs_id)) return def database_script_check(table, bs_id, attempt_num): """ Searches for any jobs that didn't work and return the data needed to send them off again """ con = lite.connect(DB_FILE, timeout = TIMEOUT) con.row_factory = lite.Row with con: cur = con.cursor() #get script data cur.execute("SELECT * FROM "+table+" WHERE AttemptNum=? AND BSID=?", (attempt_num, bs_id)) rows = cur.fetchall() error_data = [] for row in rows: if row['Started'] == None or row['Ended'] == None or row['Exit'] != 0: error_data.append([row['Command'], row['Arguments'], row['ExpProc']]) return error_data def database_mass_process(table, bs_id, dm_file_int=None): #goes through jobs of that id and command type and counts errors and processing time query = "SELECT * FROM " + table + " WHERE BSID=" + str(bs_id) if dm_file_int is not None: query += " AND DMFileInt=" + str(dm_file_int) print query con = lite.connect(DB_FILE, timeout = TIMEOUT) con.row_factory = dict_factory cur = con.cursor() cur.execute(query) rows = cur.fetchall() processing = 0. errors = 0 for row in rows: #print row['Ended'], row['Started'] #processsing += if not row['Ended'] == None and not row['Started'] == None: end_s = date_to_sec(row['Ended']) start_s = date_to_sec(row['Started']) if (end_s - start_s) >= 0.: processing += (end_s - start_s) else: print "error in processing calc" print "row num: " + str(row) print "End secs: " + str(end_s) print "Strat secs: " + str(start_s) exit() if str(row['Exit']).endswith("\n"): if not str(row['Exit'])[:-1] == "0": errors += 1 else: if not row['Exit'] == 0: errors += 1 #TODO make a better fix try: nodes = float(rows[0]['CPUs']) except: nodes =1 print "Processing time (s): " + str(processing) print "Errors number: " + str(errors) print "Nodes: " + str(nodes) print "Database Table name: " + str(table) query = "SELECT * FROM Blindsearch WHERE Rownum='" + str(bs_id) + "'" cur.execute(query) row = cur.fetchall() tot_proc = row[0]['TotalProc'] if tot_proc: new_total_proc = tot_proc + processing/3600.*nodes else: new_total_proc = 0. + processing/3600.*nodes tot_er = row[0]['TotalErrors'] if tot_er: new_total_er = tot_er + errors else: new_total_er = 0 + errors job_proc = row[0][table+'Proc'] if job_proc: new_job_proc = job_proc + processing/3600.*nodes else: new_job_proc = 0. + processing/3600.*nodes job_er = row[0][table+'Errors'] if job_er: new_job_er = job_er + errors else: new_job_er = 0 + errors print new_total_proc, new_total_er, new_job_proc, new_job_er con = lite.connect(DB_FILE, timeout = TIMEOUT) with con: cur = con.cursor() cur.execute("UPDATE Blindsearch SET TotalProc=?, TotalErrors=?, "+table+"Proc=?, "+table+"Errors=? WHERE Rownum=?", (str(new_total_proc)[:9], new_total_er, str(new_job_proc)[:9], new_job_er, bs_id)) def database_mass_update(table,file_location): print table with open(file_location,'r') as csv: con = lite.connect(DB_FILE, timeout = TIMEOUT) con.row_factory = lite.Row with con: cur = con.cursor() lines = csv.readlines() for i,l in enumerate(lines): l = l.split(',') if i % 2 == 0: rownum = l[2] attempt_num = l[3] bs_id = l[1] cur.execute("UPDATE "+table+\ " SET Started=? WHERE Rownum=? AND AttemptNum=? AND BSID=?", (l[0], rownum, attempt_num, bs_id)) else: end_time = l[0] errorcode = l[1] cur.execute("SELECT * FROM "+table+" WHERE Rownum=? AND AttemptNum=? AND BSID=?", (rownum, attempt_num, bs_id)) columns = cur.fetchone() #get blindsearch data cur.execute("SELECT * FROM Blindsearch WHERE Rownum="+str(bs_id)) bs_columns = cur.fetchone() if int(errorcode) == 0: #add processing times and job completion count end_s = date_to_sec(str(end_time)) start_s = date_to_sec(columns['Started']) processing = (end_s - start_s) cur.execute("UPDATE "+table+\ " SET Proc=?, Ended=?, Exit=? WHERE Rownum=? AND AttemptNum=? AND BSID=?", (processing, end_time, errorcode, rownum, attempt_num, bs_id)) tot_proc = float(bs_columns['TotalProc']) + processing job_proc = float(bs_columns[table+'Proc']) + processing tot_jc = int(bs_columns['TotalJobComp']) + 1 job_jc = int(bs_columns[table+'JobComp']) + 1 cur.execute("UPDATE Blindsearch SET TotalProc=?, "+table+\ "Proc=?, TotalJobComp=?, "+table+\ "JobComp=? WHERE Rownum=?", (str(tot_proc)[:9], str(job_proc)[:9], str(tot_jc)[:9], str(job_jc)[:9], bs_id)) else: tot_er = int(bs_columns['TotalErrors']) + 1 job_er = int(bs_columns[table+'Errors']) + 1 cur.execute("UPDATE "+table+\ " SET Ended=?, Exit=? WHERE Rownum=? AND AttemptNum=? AND BSID=?", (end_time, errorcode, rownum, attempt_num, bs_id)) cur.execute("UPDATE Blindsearch SET TotalErrors=?, "+table+\ "Errors=? WHERE Rownum=?", (tot_er,job_er, bs_id)) return def database_beamform_find(table,file_location, bs_id): time_now = datetime.datetime.now() #go through the batch file for info with open("{0}.batch".format(file_location),'r') as batch: lines = batch.readlines() for l in lines: if l.startswith("export OMP_NUM_THREADS"): nodes = l.split("=")[1] if l.startswith("srun"): command = "make_beam" #I don't think these needs to be more robust arguments = l.split(command)[1] with open("{0}.out".format(file_location),'r') as output: lines = output.readlines() find_check = False for l in lines: if "**FINISHED BEAMFORMING**" in l: find_check = True time_seconds = float(l[1:10]) #So this may be inaccurate because now isn't when the job #finished but should get the right delta time_then = datetime.datetime.now() - datetime.timedelta(seconds=time_seconds) row_num = database_script_start(table, bs_id, command, arguments, nodes, None,\ time_then) database_script_stop(table, row_num, 0, end_time=time_now) if not find_check: #no finshed string so likely it failed: #TODO make this more robust to work out how long it ran before it died row_num = database_script_start(table, bs_id, command, arguments, nodes, None, time_now) database_script_stop(table, bs_id, rownum, attempt_num, end_time=time_now) def date_to_sec(string): #just an approximation (doesn't even use year and month date, time = string.split(' ') y,m,d = date.split('-') h,mi,s = time.split(':') s_out = ((float(d)*24. + float(h))*60. + float(mi))*60. + float(s) #print "hours " + str(float(d)*24. + float(h)) #print "Minutes " + str((float(d)*24. + float(h))*60. + float(mi)) #print "secounds " + str(s_out) return s_out if __name__ == '__main__': from optparse import OptionParser, OptionGroup, SUPPRESS_HELP parser = OptionParser(usage = "usage: %prog <options>" + """ Script used to manage the VCS database by recording the scripts process_vcs.py uses and prints the database. Common commands: blindsearch_database.py -m vc blindsearch_database.py -m vs -c <presto command> """) parser.add_option("-m", "--mode", dest="mode", metavar="mode", default='v', type=str, help='This script has three modes: "vc" used to view the database commands, "vs" used to view the database scripts, "vp" view processing and error statistics, "s" used to start a record of a script on the database, "e" used to record the end time and error code of a script on the database, "p" counts errors and processing time for one id and "b" is a special mode for receiving the total time of beamforming jobs. Default mode is v') parser.add_option("-f", "--file_location", dest="file_location", metavar="file_location", type=str, help='mass update csv file location.') view_options = OptionGroup(parser, 'View Options') view_options.add_option("--recent", dest="recent", metavar="HOURS", default=None, type=float, help="print only jobs started in the last N hours") view_options.add_option("--number", dest="n", metavar="N", default=20, type=int, help="number of jobs to print [default=%default]") view_options.add_option("--all", dest="all", action="store_true", help="print all lines of the database") view_options.add_option("-s", "--startrow", dest="startrow", default=0, type=int, help="ignore any row earlier than this one") view_options.add_option("-e", "--endrow", dest="endrow", default=None, type=int, help="ignore any row later than this one") view_options.add_option("-o", "--obsid", dest="obsid", default=None, type=str, help="Only prints one obsid's jobs.") start_options = OptionGroup(parser, 'Script Start Options') start_options.add_option("-b", "--bs_id", dest="bs_id", default=None, type=str, help="The row number of the blindsearch command of the databse") start_options.add_option("-c", "--command", dest="command", default=None, type=str, help="The script name being run. eg volt_download.py.") start_options.add_option("-a", "--attempt_num", dest="attempt_num", default=None, type=str, help="The attempt number of a script.") start_options.add_option("-n", "--nodes", dest="nodes", default=None, type=int, help="The number of cpu nodes used.") start_options.add_option("-d", "--dm_file_int", dest="dm_file_int", default=None, type=int, help="The DM file reference eg 1 = DM_002_004.") end_options = OptionGroup(parser, 'Script End Options') end_options.add_option("--errorcode", dest="errorcode", default=None, type=str, help="Error code of scripts.") end_options.add_option("-r", "--rownum", dest="rownum", default=None, type=str, help="The row number of the script.") parser.add_option_group(view_options) parser.add_option_group(start_options) parser.add_option_group(end_options) (opts, args) = parser.parse_args() #work out table if opts.command == 'rfifind': table = 'RFI' elif opts.command == 'prepsubband': table = 'Prepdata' elif opts.command == 'realfft': table = 'FFT' elif opts.command == 'accelsearch': table = 'Accel' elif opts.command == 'prepfold': table = 'Fold' elif opts.mode == 'vc' or opts.mode == 'vp': table = 'Blindsearch' elif opts.mode == 'b' or opts.command == 'make_beam': table = 'Beamform' if opts.mode == "s": vcs_row = database_script_start(table, opts.bs_id, opts.rownum, opts.attempt_num) elif opts.mode == "e": database_script_stop(table, opts.bs_id, opts.rownum, opts.attempt_num, opts.errorcode) elif opts.mode == 'p': database_mass_process(table, opts.bs_id, dm_file_int=opts.dm_file_int) elif opts.mode == 'm': if opts.file_location: file_loc = opts.file_location else: file_loc = opts.command + '_temp_database_file.csv' database_mass_update(table,file_loc) elif opts.mode == 'b': database_beamform_find(table,opts.file_location, opts.bs_id) elif opts.mode.startswith("v"): con = lite.connect(DB_FILE, timeout = TIMEOUT) con.row_factory = dict_factory query = "SELECT * FROM " + table if opts.obsid: query += " WHERE Arguments LIKE '%" + str(opts.obsid) + "%'" if opts.recent is not None: query += ''' WHERE Started > "%s"''' % str(datetime.datetime.now() - relativedelta(hours=opts.recent)) logging.debug(query) if opts.bs_id and not opts.mode == 'vp': query += " WHERE BSID='" + str(opts.bs_id) + "'" elif opts.mode == 'vp' and opts.bs_id: query += " WHERE Rownum='" + str(opts.bs_id) + "'" if opts.dm_file_int: query += " WHERE DMFileInt='" + str(opts.dm_file_int) + "'" if opts.attempt_num: if "WHERE" in query: query += " AND AttemptNum='" + str(opts.attempt_num) + "'" else: query += " WHERE AttemptNum='" + str(opts.attempt_num) + "'" if opts.errorcode: if "WHERE" in query: query += " AND Exit='" + str(opts.errorcode) + "'" else: query += " WHERE Exit='" + str(opts.errorcode) + "'" with con: cur = con.cursor() cur.execute(query) rows = cur.fetchall() if opts.startrow and opts.endrow is None: rows = rows[opts.startrow:] elif opts.endrow is not None: rows = rows[opts.startrow:opts.endrow+1] elif not (opts.all or opts.recent): rows = rows[-opts.n:] if opts.mode == "vc": print 'Row# ','Obsid ','Pointing ','Started ','Comments' print '--------------------------------------------------------------------------------------------------' for row in rows: print '%-5s' % (str(row['Rownum']).rjust(4)), print '%-12s' % (row['Obsid']), print '%-30s' % (row['Pointing']), print '%-22s' % (row['Started'][:19]), print row['Comment'] #print "\n" if opts.mode == "vs": if (table =='RFI' or table == 'Prepdata'): print 'BDIS ','Row# ','Atm#','Started ','Ended ','Exit_Code','ProcTime ','ExpecTime ','Arguments' else: print 'BDIS ','Row# ','DM_i ','Atm#','Started ','Ended ','Err_Code','ProcTime ','ExpecTime ','CPUs','Arguments' print '--------------------------------------------------------------------------------------------------' for row in rows: #BSID INT, Command TEXT, Arguments TEXT, Started date, Ended date, Exit print '%-5s' % (row['BSID']), print '%-5s' % (str(row['Rownum']).rjust(4)), if not (table =='RFI' or table == 'Prepdata' or table == 'Beamform'): if str(row['DMFileInt']).endswith('\n'): print '%-5s' % str((row['DMFileInt']))[:-1], else: print '%-5s' % (row['DMFileInt']), print '%-5s' % (row['AttemptNum']), if row['Started'] is None: print '%-22s' % (row['Started']), else: print '%-22s' % (row['Started'][:19]), if row['Ended'] is None: print '%-22s' % (row['Ended']), else: print '%-22s' % (row['Ended'][:19]), print '%-7s' % (row['Proc']), print '%-7s' % (row['ExpProc']), if str(row['Exit']).endswith('\n'): print '%-5s' % str(row['Exit'])[:-1], else: print '%-5s' % (row['Exit']), print '%-5s' % (row['CPUs']), print row['Arguments'], print "\n" if opts.mode == "vp": for ri, row in enumerate(rows): if ri%20 == 0: print 'Row# | Total proc | err# | Beamform proc | err# | Prep proc | err# | FFT proc | err# | Accel proc | err# | Fold proc | err# |' print '-----|------------|------|---------------|------|-----------|------|----------|------|------------|------|-----------|------|' #TotalProc FLOAT, TotalErrors INT, RFIProc FLOAT, RFIErrors INT, PrepdataProc FLOAT, PrepdataErrors INT, FFTProc FLOAT, FFTErrors INT, AccelProc FLOAT, AccelErrors INT, FoldProc FLOAT, FoldErrors INT, print '{:4s} |{:11.2f} |{:5d} | {:13.2f} |{:5d} | {:9.2f} |{:5d} | {:8.2f} |{:5d} | {:10.2f} |{:5d} | {:9.2f} |{:5d} |'.format(str(row['Rownum']).rjust(4),row['TotalProc'],row['TotalErrors'],row['BeamformProc'],row['BeamformErrors'],row['PrepdataProc'],row['PrepdataErrors'],row['FFTProc'],row['FFTErrors'],row['AccelProc'],row['AccelErrors'],row['FoldProc'],row['FoldErrors'])
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def imprime(numero): i = 1 lista = [] while i <= numero: lista.append(i) for e in lista: print(e, end = ' ') print('\n') i+=1
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permissive
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import os import configparser from flask_script import Manager, Command from vendcli import ( app, views, ) from vendcli.models.meta import ( engine, Session ) from vendcli.models import Transaction, Source manager = Manager(app) session = Session() source_list = session.query(Source) @manager.command def cash_pull(): denom = {1:'Single',5:'Five',10:'Ten',20:'Twenty',50:'Fifty',100:'Hundred'} value = [1,5,10,20,50,100] for i in range(0,6): amount = cli.prompt('Please enter the total for '+denom[value[i]]+'s') @manager.command def coin_pull(): denom = {100:'Dollar',50:'Fifty-cent',25:'Quarter',10:'Dime',5:'Nickle',1:'Penny'} value = [100,50,25,10,5,1] for d in value: amount = cli.prompt('Please enter the total for '+denom[d]+'s') @manager.command def add_expense(): new_purv = cli.prompt_choice('Is this for an existing purveyor?',default='y') if(new_purv): ptypecli.prompt_choices('Purveyor type:') acct=cli.prompt('Account Number') pnum=cli.prompt('Phone Number') addr=cli.prompt('Street Address') addr2=cli.prompt('Street Address 2') city=cli.prompt('City') state=cli.prompt('State Code') postal=cli.prompt('Postal Code') # purv_num=generate_purveyor(pname=name,pacct=acct,pnum=pnum,saddr=addr,saddr2=addr2,city=city,postal=postal) else: purv_num = cli.prompt('Purveyor Number') exp_date=cli.prompt('Date of Expense') amount=cli.prompt('Total Expense') supply=cli.prompt('Cost of Supplies') other=cli.prompt('Other Expenses') if(__name__=='__main__'): manager.run()
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Python
false
false
1,685
py
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accountability.py
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0.637389
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rohidev001/databricks_adf_repo
15,530,601,766,650
37587709c56613ff227a3140b382b6d33726d60f
7112ebabcbab081b92dd2d31001b66291b208273
/notebooks/Users/r.rahul.deshmukh@sapphireondemand.com/mynotebook.py
a7b086c63c58a2932debc25c5ae0640aa447e7a6
[]
no_license
https://github.com/rohidev001/databricks_adf_repo
582d401e503e7788cdacfe83b0977667f47fbccd
df0c9ab24eca3ee64cc2989077cd07bb7072fe86
refs/heads/master
2020-03-26T16:04:59.425323
2018-08-20T08:25:57
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2018-08-17T06:35:25
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2018-08-17T07:26:34
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Python
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# Databricks notebook source # COMMAND ---------- # rest1.py # This script should demo databricks REST API. # ref: # goog: With python how to authenticate to REST API? # http://docs.python-requests.org/en/latest/ import requests usr='r.rahul.deshmukh@sapphireondemand.com' pas='dapi748a8e2e3d9113f3e74463038cef972d' hhost = 'https://abc-12345-911.cloud.databricks.com/api/1.2' clusters_list = hhost+'/clusters/list' rq1 = requests.get(clusters_list, auth=(usr,pas)) print(rq1.status_code) print(rq1.json()) print("hello")
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Python
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py
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mynotebook.py
2
0.731203
0.663534
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19
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mich326/scored
13,486,197,327,230
7ff70680bf20834d2169f0517848b57ee90e1f85
7af634b9162dae00d13c6a85382a60e221ad3591
/scored.py
8394e9d12ba748a7fb7d53d7cfaf6c6f8073337b
[]
no_license
https://github.com/mich326/scored
d7e820de69ab239b473794f89cacacfc890b0a00
3634faff00cd6406928a05b81e7fc50ff2380085
refs/heads/master
2021-01-15T15:54:51.631049
2016-03-10T02:34:03
2016-03-10T02:34:03
50,685,317
0
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2016-01-29T19:17:52
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from selenium import webdriver from bs4 import BeautifulSoup, SoupStrainer import time, sys, os, difflib, fileinput, re, urllib2, cookielib, json, multiprocessing if os.path.exists(os.getcwd()+'/scored.log'): os.remove(os.getcwd()+'/scored.log') if os.path.exists(os.getcwd()+'/journals.txt'): os.remove(os.getcwd()+'/journals.txt') if os.path.exists(os.getcwd()+'/issuelist.txt'): os.remove(os.getcwd()+'/issuelist.txt') if os.path.exists(os.getcwd()+'/seedlist.txt'): os.remove(os.getcwd()+'/seedlist.txt') '''Purpose: To create seedlist of journal issues and extract article page metadata from journal sites Inputs: URL of website num - 0, 1, 2 (indicating file with xpaths, classtag or xpath) input1 - location of file of xpaths if num ==0; class tag string if num == 1; xpath tag string if num ==2 ''' class scored(object): def __init__(self, url, num, input1): self.driver = webdriver.PhantomJS() self.driver.set_window_size(1024, 768) self.cj = cookielib.CookieJar() self.opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(self.cj)) self.xpages = 10 self.url = url self.log = os.getcwd() + '/scored.log' self.f = open(self.log,'ab+') self.num = num self.input1 = input1 def tear_down(self): self.driver.quit() return True def get_journal_list(self): self.driver.get(self.url) fname = 'journals.txt' with open(fname, 'ab+') as f: if self.num == 0: try: self.f.write('Name of file: %s\n' %self.input1 ) xpathList = [line.strip() for line in open(self.input1)] for xpath in xpathList: xpathElement = self.driver.find_element_by_xpath(xpath) self.f.write('xpath: %s\n' %xpathElement.get_attribute('href')) f.write('%s\n' %xpathElement.get_attribute('href')) except: print 'The file ' + self.input1 + ' does not exist' elif self.num == 1: try: classTagArray = self.driver.find_elements_by_class_name(self.input1) self.f.write('Using %s as class tag \n' %self.input1) for classTag in classTagArray: self.f.write('class: %s\n' %classTag.find_element_by_tag_name('a').get_attribute('href')) f.write('%s\n' %classTag.find_element_by_tag_name('a').get_attribute('href')) except: print 'The class_name '+ self.input1 + 'is not valid on the input site provided' elif self.num == 2: try: allXpaths = self.driver.find_elements_by_xpath(self.input1) for i in allXpaths: if 'journal' in i.find_element_by_tag_name('a').get_attribute('href'): if self.url in i.find_element_by_tag_name('a').get_attribute('href'): currLink = (i.find_element_by_tag_name('a').get_attribute('href'))+'issues' else: currLink = i.find_element_by_tag_name('a').get_attribute('href') f.write('%s\n' %currLink) except: print 'The xpath provided, ' + self.input1 + 'is not valid for the input site provided' else: print 'Please enter a legal input' self.tear_down() def get_issues_list(self): ''' get all issues ''' fname = 'issuelist.txt' jfname = 'journals.txt' try: journals = [line.rstrip() for line in open(jfname)] except: self.f.write('No journals.txt\n') sys.exit() for j in journals: soup = self.get_page_soup(j) self.get_list(soup, j, fname) def get_articles_list(self): ''' generate the journals lists from the issues list ''' fname = 'seedlist.txt' iname = 'issuelist.txt' issues = [] again = True try: issues = [line.rstrip() for line in open(iname)] except: self.f.write('No issuelist.txt\n') sys.exit() for page in issues: soup = self.get_page_soup(page) self.get_list(soup, page, fname) def get_html(self, link, selenium=None): ''' reach html using urllib2 & cookies ''' if selenium: self.driver.get(link) time.sleep(5) self.tear_down() return self.driver.page_source else: try: request = urllib2.Request(link) response = self.opener.open(request) time.sleep(5) self.cj.clear() return response.read() except: print 'unable to reach link' return False def get_page_soup(self, link, selenium = None, strain=None): ''' return html using BS for a page ''' print 'in get_page_soup ', link if selenium: html = self.get_html(link, selenium=True) else: html = self.get_html(link) if html: if strain: strainer = SoupStrainer(id=strain) try: return BeautifulSoup(html, parse_only=strainer) except: return False else: try: return BeautifulSoup(html) except: return False def get_list(self, soup, soupURL, filename, pubHouse=None): ''' generate issuelist from all issues on a given page''' stopwords = ['facebook', 'twitter', 'youtube', 'linkedin', 'membership', 'subscribe', 'subscription', 'blog',\ 'submit', 'contact', 'listserve', 'login', 'disclaim', 'editor', 'section', 'librarian', 'alert',\ '#', 'email', '?', 'copyright', 'license', 'charges', 'terms', 'mailto:', 'submission', 'author',\ 'media', 'news', 'rss', 'mobile', 'help', 'award', 'meetings','job', 'access', 'privacy', 'features'\ 'information', 'search', 'book', 'aim'] currLink = '' issues = [] issuelist = [] links = [] seeds = [] eachlink = '' try: journals = [line.rstrip() for line in open('journals.txt')] except: journals = [] self.f.write('No journals.txt to compare urls against. \n') if 'seedlist.txt' in filename: try: issues = [line.rstrip() for line in open('issuelist.txt')] except: issues = [] self.f.write('No issuelist.txt to compare urls against. \n') for link in soup.find_all('a', href=True): if not pubHouse: pubHouse = 'http://'+self.url.split('http://')[1].split('/')[0] doi = self.link_has_doi(link.get('href')) try: allLines = [line.rstrip() for line in open(filename)] except: allLines = [] try: issuesTmp = [line.rstrip() for line in open('issuelistTmp.txt')] except: issuesTmp = [] allLines += journals + issues + issuesTmp allLines.append(soupURL) with open(filename,'ab+') as f: currLink = self.get_link(link.get('href'), pubHouse) textDiff = self.compare_text(currLink.rstrip(), allLines) if pubHouse in currLink: if 'issuelist.txt' in filename: if currLink.lower().startswith('http') or doi: if not(any(word in currLink.lower() for word in stopwords)): if textDiff == True: if re.findall('issue', link.get('href').lower()): if re.findall('issue', link.getText().lower()): f.write('%s\n' %currLink) else: issuelist.append(currLink) else: links.append(currLink) elif 'seedlist.txt' in filename: if currLink.lower().startswith('http') or doi: if not(any(word in currLink.lower() for word in stopwords)): if 'abs' in currLink.lower(): f.write('%s\n' %currLink) seeds.append(currLink) elif 'full' in currLink.lower(): if textDiff == True: f.write('%s\n' %currLink) seeds.append(currLink) else: if not(any(word in currLink.lower() for word in stopwords)): if textDiff == True: f.write('%s\n' %currLink) # recursion for finding issuelist if necessary if 'issuelist.txt' in filename: with open(filename,'ab+') as f: if len(issuelist) == 0: for i in links: f.write('%s\n' %i) links = [] return else: with open('issuelistTmp.txt', 'ab+') as t: t.write('%s\n' %issuelist[0]) soup = self.get_page_soup(issuelist[0]) self.get_list(soup, issuelist[0].rstrip(), filename, pubHouse) #try selenium to access the page if 'seedlist.txt' in filename: if len(seeds) == 0: soup = self.get_page_soup(soupURL, selenium=True) for link in soup.find_all('a', href=True): doi = self.link_has_doi(link.get('href')) currLink = self.get_link(link.get('href'), pubHouse) textDiff = self.compare_text(currLink.strip(), allLines) with open(filename,'ab+') as f: if currLink.lower().startswith('http') or doi: if not(any(word in currLink.lower() for word in stopwords)): if textDiff == True: if 'abs' in currLink.lower(): f.write('%s\n' %currLink) allLines.append(currLink) elif 'full' in currLink.lower(): if textDiff == True: f.write('%s\n' %currLink) allLines.append(currLink) def get_link (self, link, pubHouse): ''' utility function for generating an absolute link if necessary ''' if not link.lower().startswith('http'): if pubHouse: return pubHouse+link else: return link def link_has_doi (self, link): ''' utility function to check if a link is a doi link ''' if not link.lower().startswith('http'): if 'doi/' in link: return True elif any([self.is_number(i) for i in link.split('/')]): return True else: return False def is_number(self,s): ''' utility function to check if a string is a decimal number''' try: float(s) if '.' in s: return True else: return False except ValueError: return False def compare_text(self, url, urlList): ''' check for link in a urlList ''' textDiff = '' diffList = [] if self.url == url or self.url+'/' == url: return False elif urlList == [] or len(urlList) < 2: return True elif filter(lambda x: url in x, urlList): return False else: for i in urlList: textDiff = '' for _,s in enumerate(difflib.ndiff(url, i)): if s[0] == ' ': continue elif s[0] == '+': textDiff += s[2] diffList.append(textDiff) for diff in diffList: if diff == None or ('abs' in diff.lower() and len(diff) <= 9): return False return True def get_meta_data(self, soup): ''' get page metadata using BS''' metaDict = {} authors = [] pubdate = [] subject = [] keywords = [] format = '' fileType = '' doiidentifier = '' pubidentifier = '' source = '' title = '' rights = '' contentType = '' try: allMeta = soup.findAll('meta') except: print 'no metaData' return False for tag in allMeta: if tag.get('name'): if 'creator' in tag.get('name').lower() or 'author' in tag.get('name').lower(): authors.append(tag.get('content')) if 'type' in tag.get('name').lower(): fileType = tag.get('content') if 'subject' in tag.get('name').lower(): subjet.append(tag.get('content')) if 'keyword' in tag.get('name').lower(): keywords.append(tag.get('content')) if 'format' in tag.get('name').lower(): format = tag.get('content') if 'title' in tag.get('name').lower(): title = tag.get('content') if 'source' in tag.get('name').lower(): source = tag.get('content') if 'rights' in tag.get('name').lower(): rights = tag.get('content') if 'date' in tag.get('name').lower(): pubdate.append(tag.get('content')) try: pubdate.append(tag.get('scheme')) except: continue if 'identifier' in tag.get('name').lower(): try: if 'doi' in tag.get('scheme').lower(): doiidentifier = tag.get('content') except: continue try: if 'publisher' in tag.get('scheme').lower(): pubidentifier = tag.get('content') except: continue return {'metaAuthors':authors, 'date':pubdate, 'subject':subject, 'keywords':keywords, 'format':format, 'fileType':fileType, 'doi':doiidentifier, 'pubid':pubidentifier, 'source':source, 'metaTitle':title, 'rights':rights, 'contentType':contentType} def get_full_text(self, page): ''' Extract the data from a page ''' metaDict = {} contentDict = {} abstract = '' authors = [] affilations = [] soup = self.get_page_soup(page) metaDict = self.get_meta_data(soup) print 'text from: ', page if not os.path.exists(os.getcwd()+'/jsonFilesAMS'): os.makedirs(os.getcwd()+'/jsonFilesAMS') contentDict['id'] = page try: for i in soup.find_all(class_=re.compile("^abstr")): abstract += i.find('p').text.encode('utf-8') except: print 'Abstract was not found on this page' try: title = soup.find_all(class_=re.compile("itle")) contentDict['title'] = title.text.encode('utf-8') except: print 'Title was not found on this page' contentDict['title'] = 'Null' try: ack = soup.find_all(class_=re.compile("cknowledgement")) contentDict['acknowledgement'] = ack.text.encode('utf-8') except: print 'Acknowledgements not found on this page' contentDict['acknowledgement'] = 'Null' try: for x in soup.find_all(class_=re.compile("uthor")): try: for k in x.find_all('strong'): authors.append(k.text.encode('utf-8')) except: continue try: y = x.find_all('p') if not authors: for z in y: authors.append(z.text.encode('utf-8')) else: for z in y: affilations.append(z.text.encode('utf-8')) except: continue except: print 'Citation Authors info not found on this page' contentDict['citation_authors'] = 'Null' contentDict['abstract'] = abstract contentDict['citation_authors'] = authors contentDict['citation_affilations'] = affilations if metaDict: contentDict.update(metaDict) if abstract: filenameJSON = os.getcwd()+ '/jsonFiles/'+ page.split('://')[1].replace('/','-').replace('.','-') +'.json' with open(filenameJSON, 'w+') as f: json.dump(contentDict, f) def main(): print 'Extracting Data from Journals...' journals.get_journal_list() journals.get_issues_list() journals.get_articles_list() if __name__ == '__main__': main()
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Python
false
false
13,793
py
1
scored.py
1
0.61669
0.612557
0
503
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tbobm/99problems
12,592,844,115,553
3cb71a2b56972f44c874c1a856efe8cb69b2166e
d70b4d184cb80ee14e306755f7ef4bab5ee94f7b
/python/lists/P10.py
e2ba57602b7ca2d09d19a7219640857f05f612be
[]
no_license
https://github.com/tbobm/99problems
e29f65a59aa93f3ddca45ff114e24b1e3661f774
492146625bbe173fb31658a552d1c353eb11600f
refs/heads/master
2021-06-01T05:42:13.412190
2016-07-16T14:43:07
2016-07-16T14:43:07
null
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# encoding: utf-8 # 1.10 (*) Run-length encoding of a list. # Use the result of problem 1.09 to implement the so-called run-length encoding data compression method. Consecutive duplicates of elements are encoded as terms [N,E] where N is the number of duplicates of the element E. # # Example: # ?- encode([a,a,a,a,b,c,c,a,a,d,e,e,e,e],X). # X = [[4,a],[1,b],[2,c],[2,a],[1,d][4,e]] def func(data): last_elem = data[:1][0] res = [] counter = 1 for elem in data[1:]: if elem == last_elem: counter += 1 if elem != last_elem: res.append([counter, last_elem]) counter = 1 last_elem = elem res.append([counter, last_elem]) return res
UTF-8
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false
731
py
29
P10.py
27
0.573187
0.547196
0
23
30.826087
224
xiewjsir/learns
5,360,119,233,352
4d91365563e554b79b5f6c008515bc63beef00cd
5ca045803301e62caa7bb0946933621344161848
/python/learnspider/dzdp/dzdp/spiders/spider.py
770d5f15003eb80c4ff01ce01d40e9dbed7bd4c2
[]
no_license
https://github.com/xiewjsir/learns
9d5b1f85fff29b97027fefe1376f8088e0fc6f4e
23808c34f294faf73055e5d4262fd5738a3ef214
refs/heads/master
2021-11-24T02:08:52.191540
2021-11-09T09:11:59
2021-11-09T09:11:59
163,933,868
0
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from scrapy import Spider, Request import re from lxml import etree import json from urllib.parse import quote from dzdp.items import StoreItem, StorePictureItem from copy import deepcopy class Dzdp_spider(Spider): name = 'dzdp' allowed_domains = ['dianping.com'] classifys = { 'c21151': '购宠', # 'c21150': '宠物食品', # 'c20692': '宠物店' } def start_requests(self): for classify in list(self.classifys.keys()): for i in range(100): url = "http://www.dianping.com/shenzhen/ch95/g25147p{}".format(str(i+1)) yield Request(url=url, callback=self.parse) def parse(self, response): selector = etree.HTML(response.text) stores = selector.xpath("//div[@class='shop-list J_shop-list shop-all-list']/ul/li") for store in stores: print(store) name = store.xpath(".//div[@class='tit']/a/@title") print(name)
UTF-8
Python
false
false
978
py
51
spider.py
37
0.6
0.572917
0
30
30.766667
92
kevincrane/kevcrablog
16,484,084,520,333
9b5209731bf512f68380a4a85385a06e0e1d40eb
21fce83c2ebf4651cff8afe7191cf247b2c3969e
/app/kevcrablog/forms.py
c6afd9df59ab17e9c254eea682b9bf1b1f8ff886
[]
no_license
https://github.com/kevincrane/kevcrablog
51a211877d45de3bf5ce5f72769f769258b68924
1522fb5b718d67228626d5cf2910e004f4ce4db4
refs/heads/master
2021-01-10T20:13:17.619042
2018-06-28T00:04:39
2018-06-28T00:04:39
17,099,676
0
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from flask_wtf import Form from wtforms import TextField, TextAreaField from wtforms import validators from wtforms.widgets import TextArea, HTMLString class MarkdownWidget(TextArea): """ Replacement TextArea for blog Markdown - When typing, text is converted to markdown and displayed in HTML div 'markdown-preview' """ def __call__(self, field, **kwargs): html = super(MarkdownWidget, self).__call__(field, id='markdown-input', **kwargs) return HTMLString(html) class PostForm(Form): """ Form for new blog Post object """ title = TextField(u'Post Title', validators=[validators.InputRequired("Please enter a good title.")]) body = TextAreaField(u'Content', validators=[validators.InputRequired("This would be the worst blog post.")], widget=MarkdownWidget()) class CommentForm(Form): """ Form for a Comment on a blog Post """ body = TextAreaField(u'Comment', validators=[validators.InputRequired("Say something at least.")]) author = TextField(u'Name', validators=[validators.InputRequired("Don't be scared, what's your name?")])
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py
57
forms.py
23
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0.688869
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30
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ZhengkunTian/OpenTransformer
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a2ebead905608bc05551bf324c0ca555f03da730
b7f3d206f25221770fd707209f4343886e9639a9
/otrans/encoder/base.py
5109de6cf7530ad7b64c4fdbfa451b7c3a334c8f
[ "MIT" ]
permissive
https://github.com/ZhengkunTian/OpenTransformer
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refs/heads/master
2022-07-26T19:40:11.824668
2022-07-21T01:25:09
2022-07-21T01:25:09
226,343,764
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81
MIT
false
2021-11-08T04:27:05
2019-12-06T14:12:00
2021-11-05T01:39:19
2021-11-08T04:27:04
185
262
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Python
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# File : base.py # Author : Zhengkun Tian # Email : zhengkun.tian@outlook.com import torch import torch.nn as nn class BaseEncoder(nn.Module): def __init__(self): super(BaseEncoder, self).__init__() def forward(self, inputs, inputs_mask, **kargs): raise NotImplementedError def inference(self, inputs, inputs_mask, cache=None, **kargs): raise NotImplementedError
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0.667488
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akiitr/python0
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9c30e1e26df8598fa44a8e6582fbe5957dd20288
ef59676cee1fc4c523dac85db2d6bdb5454d7658
/coursera_automation_google_python/c2/week6.py
102f9b8f2c4bd813966a8e6e854b9d822a15786b
[]
no_license
https://github.com/akiitr/python0
549bdc9c31b63ffa3101c7dbaff2f75e7a733a26
8e4be64c4b6017cfdbe1b87ae3eac779a169acb8
refs/heads/master
2021-08-18T08:19:36.177206
2021-06-02T07:15:31
2021-06-02T07:15:31
210,405,972
0
0
null
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#Python script for the reanming the old username to new username #!/usr/bin/env python3 import sys,subprocess f = open(sys.argv[1]) lines = f.readlines() f.close() for line in lines: line_new = line.strip().replace('jane','jdoe') sub_inputs = ["mv",line.strip(),line_new] subprocess.run(sub_inputs) #Bash file for the finding the files to be ranamed #!/bin/bash touch oldFiles.txt files=$(grep 'jane_' ~/data/list.txt | cut -d ' ' -f3) for i in $files; do if test -e "/home/student-00-242fe9494c70$i"; then echo "file $i exists" echo "/home/student-00-242fe9494c70$i" >> oldFiles.txt else echo "file $i does not exist" fi done
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from typing import Sequence from edspdf import Box, PDFDoc, Pipeline, registry from edspdf.utils.alignment import align_box_labels @registry.factory.register("mask-classifier") def simple_mask_classifier_factory( x0: float, y0: float, x1: float, y1: float, pipeline: Pipeline = None, name: str = "mask-classifier", threshold: float = 1.0, ): """ The simplest form of mask classification. You define the mask, everything else is tagged as pollution. Parameters ---------- pipeline: Pipeline The pipeline object name: str The name of the component x0: float The x0 coordinate of the mask y0: float The y0 coordinate of the mask x1: float The x1 coordinate of the mask y1: float The y1 coordinate of the mask threshold: float The threshold for the alignment Examples -------- === "API-based" ```python pipeline.add_pipe( "mask-classifier", name="classifier", config={ "threshold": 0.9, "x0": 0.1, "y0": 0.1, "x1": 0.9, "y1": 0.9, }, ) ``` === "Configuration-based" ```toml [components.classifier] @classifiers = "mask-classifier" x0 = 0.1 y0 = 0.1 x1 = 0.9 y1 = 0.9 threshold = 0.9 ``` """ return MaskClassifier( pipeline=pipeline, name=name, masks=[ Box( label="body", x0=x0, y0=y0, x1=x1, y1=y1, ) ], threshold=threshold, ) @registry.factory.register("multi-mask-classifier") def mask_classifier_factory( pipeline: Pipeline = None, name: str = "multi-mask-classifier", threshold: float = 1.0, **masks: Box, ): """ A generalisation, wherein the user defines a number of regions. The following configuration produces _exactly_ the same classifier as `mask.v1` example above. Any bloc that is not part of a mask is tagged as `pollution`. Parameters ---------- pipeline: Pipeline The pipeline object name: str threshold: float The threshold for the alignment masks: Dict[str, Box] The masks Examples -------- === "API-based" ```python pipeline.add_pipe( "multi-mask-classifier", name="classifier", config={ "threshold": 0.9, "mymask": {"x0": 0.1, "y0": 0.1, "x1": 0.9, "y1": 0.3, "label": "body"}, }, ) ``` === "Configuration-based" ```toml [components.classifier] @factory = "multi-mask-classifier" threshold = 0.9 [components.classifier.mymask] label = "body" x0 = 0.1 y0 = 0.1 x1 = 0.9 y1 = 0.9 ``` The following configuration defines a `header` region. === "API-based" ```python pipeline.add_pipe( "multi-mask-classifier", name="classifier", config={ "threshold": 0.9, "body": {"x0": 0.1, "y0": 0.1, "x1": 0.9, "y1": 0.3, "label": "header"}, "header": {"x0": 0.1, "y0": 0.3, "x1": 0.9, "y1": 0.9, "label": "body"}, }, ) ``` === "Configuration-based" ```toml [components.classifier] @factory = "multi-mask-classifier" threshold = 0.9 [components.classifier.header] label = "header" x0 = 0.1 y0 = 0.1 x1 = 0.9 y1 = 0.3 [components.classifier.body] label = "body" x0 = 0.1 y0 = 0.3 x1 = 0.9 y1 = 0.9 ``` """ return MaskClassifier( pipeline=pipeline, name=name, masks=list(masks.values()), threshold=threshold, ) class MaskClassifier: """ Simple mask classifier, that labels every box inside one of the masks with its label. """ def __init__( self, pipeline: Pipeline = None, name: str = "multi-mask-classifier", masks: Sequence[Box] = (), threshold: float = 1.0, ): self.name = name masks = list(masks) masks.append( Box( label="pollution", x0=-10000, x1=10000, y0=-10000, y1=10000, ) ) self.masks = masks self.threshold = threshold def __call__(self, doc: PDFDoc) -> PDFDoc: doc.content_boxes = align_box_labels( src_boxes=self.masks, dst_boxes=doc.content_boxes, threshold=self.threshold, ) return doc
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PROVINCES = { 'Britannia':'2', 'Germania inferior':'3', 'Belgica':'4', 'Lugdunensis':'5', 'Germania superior':'6', 'Aquitania':'7', 'Alpes poeninae':'8', 'Alpes cottiae':'9', 'Alpes maritimae':'10', 'Narbonensis':'11', 'Tarraconensis':'12', 'Lusitania':'13', 'Baetica':'14', 'Italia (Italy)':'15', 'Corsica':'16', 'Sardinia':'17', 'Raetia':'18', 'Noricum':'19', 'Pannonia superior':'20', 'Pannonia inferior':'21', 'Dalmatia (=Illyricum)':'22', 'Dacia':'23', 'Moesia superior':'24', 'Moesia inferior':'25', 'Thracia (Thrace)':'26', 'Macedonia':'27', 'Epirus':'28', 'Achaea':'29', 'Creta (Crete)':'30', 'Bithynia et Pontus':'31', 'Asia':'32', 'Galatia':'33', 'Lycia et Pamphylia':'34', 'Cappadocia':'35', 'Cilicia':'36', 'Armenia':'37', 'Assyria':'38', 'Mesopotamia':'39', 'Syria':'40', 'Cyprus':'41', 'Iudaea (Judea)':'42', 'Arabia':'43', 'Aegyptus (Egypt)':'44', 'Cyrenaica':'45', 'Africa Proconsularis':'46', 'Numidia':'47', 'Mauretania Caesariensis':'48', 'Mauretania Tingitana':'49', 'Sicilia (Sicily)':'50' } CITIES = { 'London': 'A', 'Trier': 'B', 'Paris': 'C', 'Marseilles': 'D', 'Saguntum': 'E', 'New Carthage': 'F', 'Ravenna': 'G', 'Roma (Rome)': 'H', 'Syracuse': 'I', 'Philippi': 'J', 'Pharsalus': 'K', 'Actium': 'L', 'Athens': 'M', 'Byzantium/Constantinople': 'N', 'Nicomedia': 'O', 'Pergamum/Pergamon': 'P', 'Edessa': 'Q', 'Antioch': 'R', 'Seleucia-Ctesiphon': 'S', 'Sidon': 'T', 'Jerusalem': 'U', 'Alexandria': 'V', 'Memphis': 'W', 'Carthage': 'X', 'Cirta': 'Y', 'Cadiz': 'Z' } DATES = { 'RANGE Second Punic War': '218-201', 'Battles of Ticinum and Trebia': '218', 'Battle of Lake Trasimene': '217', 'Battle of Cannae' : '216', 'Hannibal takes Capua and is supported by Philip V of Macedon': '215', 'defeat of Syracuse; death of Archimedes': '212', 'defeat of Hasdrubal at Metaurus River': '215', 'Romans conquer Spain': '206', 'end of First Macedonia War': '205', 'Scipio invades Africa': '204', 'Hannibal recalled': '203', 'Battle of Zama': '202', 'treaty signed after second punic war': '201', 'Spain made into two provinces': '197', 'Philip V defeated at Cynoscephalae (Second Macedonian War)': '197', 'Antiochus III of Syria defeated at Magnesia': '190', 'Third Macedonian War ends at Pydna': '168', 'Illyricum made a province': '167', 'RANGE Third Punic War; destruction of Carthage; Africa made a province': '149-146', 'Fourth Macedonian War ends': '148', 'revolt of Achaean League; Achaea and Macedonia made a province': '146', 'Tiberius Gracchus, tribune of the plebs': '133', 'RANGE Gaius Gracchus, tribune of the plebs': '123-122', 'RANGE Gaius Marius, consul six times, five times in a row (104-100)': '107-100', 'RANGE Social War': '91-87', 'siege of Rome': '82', 'RANGE Sulla dictator': '81-80', 'RANGE revolt of Spartacus in Italy': '73-71', 'Pompey and Crassus consuls': '70', 'Gaius Julius Caesar consul': '59', 'Caesar begins first five-year command in Gaul': '58', 'RANGE Caesar’s conquest of Britain': '55-54', 'Crassus killed at Carrhae against Parthians': '53', 'Gaul made a province': '51', 'DAY (# month year) senate declares martial law against Caesar': '7 january 49', 'DAY (# month year) Caesar crosses the Rubicon River, thereby declaring civil war': '11 january 49', 'Pompey defeated at Pharsalus by Caesar': '48', 'DAY (# month year) Caesar assassinated': '15 march 44' }
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# coding=utf-8 # Copyright 2022 The Google Research Authors. # # 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. #!/usr/bin/python # # Copyright 2021 The On Combining Bags to Better Learn from # Label Proportions 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. """Generating Training Bags for two straddle bags.""" import pickle import random import numpy as np import pandas as pd def makeonlybagswithtwostraddle(n_clusters, straddle_inclusion_first, straddle_inclusion_second, tail_inclusion, p_law_param, n_straddle, n_tail, trainfile, cluster_dir, option, directory_to_read, random_seed=None, numpy_seed=None): # pylint: disable=unused-argument """Generating Training Bags for two straddle bags.""" random.seed(random_seed) np.random.seed(numpy_seed) train_df = pd.read_csv(trainfile) train_df.reset_index(drop=True, inplace=True) # ###Reading instead of creating cluster_to_indices_list = pickle.load( open(directory_to_read + "cluster_indices", "rb")) for cluster_label in range(n_clusters): print("size of cluster ", cluster_label, " is ", len(cluster_to_indices_list[cluster_label])) # All Bags all_bags_list = [] # #create the first straddle bags straddle_bags_first = [] for _ in range(n_straddle): this_bag = [] for cluster_label in range(n_clusters - 1): no_of_indices = len(cluster_to_indices_list[cluster_label]) no_of_sampled_indices = np.random.binomial( n=no_of_indices, p=straddle_inclusion_first[cluster_label]) this_bag = this_bag + random.sample( cluster_to_indices_list[cluster_label], no_of_sampled_indices) straddle_bags_first.append(this_bag) print("A straddle bag created") all_bags_list.append(this_bag) straddle_bags_file = cluster_dir + "straddle_bags_first" with open(straddle_bags_file, "wb") as writing_to_straddle_bags_file: pickle.dump(straddle_bags_first, writing_to_straddle_bags_file) # #create the second straddle bags straddle_bags_second = [] for _ in range(n_straddle): this_bag = [] for cluster_label in range(1, n_clusters): no_of_indices = len(cluster_to_indices_list[cluster_label]) no_of_sampled_indices = np.random.binomial( n=no_of_indices, p=straddle_inclusion_second[cluster_label - 1]) this_bag = this_bag + random.sample( cluster_to_indices_list[cluster_label], no_of_sampled_indices) straddle_bags_second.append(this_bag) print("A straddle bag created") all_bags_list.append(this_bag) straddle_bags_file = cluster_dir + "straddle_bags_second" with open(straddle_bags_file, "wb") as writing_to_straddle_bags_file: pickle.dump(straddle_bags_second, writing_to_straddle_bags_file) # create the tail bags cluster_label_to_tail_bags_list = [] for cluster_label in range(n_clusters): this_cluster_tail_bags = [] no_of_indices = len(cluster_to_indices_list[cluster_label]) for _ in range(n_tail): no_of_sampled_indices = np.random.binomial( n=no_of_indices, p=tail_inclusion[cluster_label]) this_bag = random.sample(cluster_to_indices_list[cluster_label], no_of_sampled_indices) this_bag.sort() this_cluster_tail_bags.append(this_bag) all_bags_list.append(this_bag) cluster_label_to_tail_bags_list.append(this_cluster_tail_bags) tail_bags_file = cluster_dir + "tail_bags_" + str(cluster_label) with open(tail_bags_file, "wb") as writing_to_tail_bags_file: pickle.dump(this_cluster_tail_bags, writing_to_tail_bags_file) # write all bags all_bags_file = cluster_dir + "all_bags" with open(all_bags_file, "wb") as writing_to_all_bags_file: pickle.dump(all_bags_list, writing_to_all_bags_file) # create the raw training set using all bags new_train_df = pd.DataFrame() bag_no = 1 for bag_list in all_bags_list: if not bag_list: continue this_bag_df = train_df.iloc[bag_list].copy() this_bag_df["bag"] = bag_no new_train_df = new_train_df.append(this_bag_df, ignore_index=True) bag_no = bag_no + 1 new_train_df = new_train_df.sample(frac=1) new_train_df.to_csv(cluster_dir + "full_train.csv", index=False)
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from flask import Flask, render_template, request import pickle import numpy as np with open('rf_pickle_model.pkl','rb') as file: model = pickle.load(file) app = Flask(__name__) @app.route('/') def man(): return render_template('home.html') @app.route('/predict', methods=['POST','GET']) def home(): V1 = 0.000010 V2 = -0.000021 V3 = -0.000015 V4 = -0.000020 V5 = -0.000006 V6 = -0.000028 V7 = 0.000005 V8 = -0.000004 V9 = -0.000004 V10= 0.000005 V11= -0.000004 V12= -0.000022 V13= 0.000008 V14= -0.000003 V15= 0.000013 V16= 0.000026 V17= -0.000016 V18= 0.000029 V19= 0.000009 V20= 0.000007 V21= -0.000010 V22= 8.675109e-07 V23= 0.000001 V24= 0.000019 V25= -0.000007 V26= 0.000008 V27= 9.956689e-07 V28= -0.000001 average= sum([V1,V2,V3,V4,V5,V6,V7,V8,V9,V10,V11,V12,V13,V14,V15,V16,V17,V18,V19,V20,V21,V22,V23,V24,V25,V26,V27,V28])/28 time= request.form['D'] time_difference= request.form['E'] Amount= request.form['F'] cond= request.form['G'] min= request.form['H'] import pandas as pd import pickle df = pd.read_pickle('C:/Users/Vaishnavi M Shetty/Desktop/code for classification of credit card/dfmod.pickle') from sklearn.preprocessing import StandardScaler from sklearn.model_selection import train_test_split f1 = ['V1','V2','V3','V4','V5','V6','V7','V8','V9','V10','V11','V12','V13','V14','V15','V16','V17','V18','V19','V20','V21','V22','V23','V24','V25','V26','V27','V28','Amount','cond','time_difference','average'] std_x = StandardScaler() X = df.drop('Class', axis=1) y = df['Class'] X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42) X_train[f1] = std_x.fit_transform(X_train[f1]) arr = [V1,V2,V3,V4,V5,V6,V7,V8,V9,V10,V11,V12,V13,V14,V15,V16,V17,V18,V19,V20,V21,V22,V23,V24,V25,V26,V27,V28,Amount,cond,time_difference,average] arr1 = std_x.transform([arr]) import json # arr1 = np.array([['arr']]) arr2 = np.array([[time, min]]) arr = np.concatenate((arr1, arr2), axis=1) output = model.predict(arr) return render_template('after.html', pred=min) if __name__ == "__main__": app.run(debug=True)
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import asyncio from functools import partial import requests from conjureup import __version__ as VERSION from conjureup.app_config import app GA_ID = "UA-1018242-61" SENTRY_DSN = ('https://27ee3b60dbb8412e8acf6bc159979165:' 'b3828e6bfc05432bb35fb12f6f97fdf6@sentry.io/180147') TELEMETRY_ASYNC_QUEUE = "telemetry-async-queue" def track_screen(screen_name): app.log.debug('Showing screen: {}'.format(screen_name)) if app.no_track: return args = dict(cd=screen_name, t="screenview") if 'spell' in app.config: args['cd1'] = app.config['spell'] if not app.loop: app.loop = asyncio.get_event_loop() app.loop.run_in_executor(None, partial(_post_track, args)) def track_event(category, action, label): "" app.log.debug('{}: {} {}'.format(category, action, label)) if app.no_track: return args = dict(ec=category, ea=action, el=label, t='event') if 'spell' in app.config: args['cd1'] = app.config['spell'] if not app.loop: app.loop = asyncio.get_event_loop() app.loop.run_in_executor(None, partial(_post_track, args)) def track_exception(description, is_fatal=True): "" if app.no_track: return exf = 1 if is_fatal else 0 args = dict(t='exception', exd=description, exf=exf) if 'spell' in app.config: args['cd1'] = app.config['spell'] if not app.loop: app.loop = asyncio.get_event_loop() app.loop.run_in_executor(None, partial(_post_track, args)) def _post_track(arg_dict): params = dict(tid=GA_ID, v=1, aip=1, ds='app', cid=app.session_id, av=VERSION, an="Conjure-Up") params.update(arg_dict) try: requests.post("http://www.google-analytics.com/collect", data=params) except Exception: pass # ignore failures to submit telemetry
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#!/usr/bin/env python from functools import wraps class NegArgError(Exception): def __init__(self, name, n): super().__init__() self.message = 'argument {0} for {1} negative'.format(n, name) class TooLargeArgError(Exception): def __init__(self, name, n): super().__init__() self.message = 'argument {0} for {1} too large'.format(n, name) def check_min(f): @wraps(f) def wrapped(n): if n < 0: raise NegArgError(f.__name__, n) return f(n) return wrapped def check_max(f): @wraps(f) def wrapped(n): if n > 12: raise TooLargeArgError(f.__name__, n) return f(n) return wrapped @check_max @check_min def fact(n): '''compute factorial of given number''' if n == 0: return 1 else: return n*fact(n - 1) if __name__ == '__main__': import sys for n in [3, 7, 22, -1]: try: print(f'{n}! = {fact(n)}') except Exception as error: print(f'### error: {error.message}', file=sys.stderr) print(f'function name: {fact.__name__}') print(f'function docs: {fact.__doc__}')
UTF-8
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false
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1,167
py
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decorator.py
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0.533847
0.520994
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AvaneeshKolluri/Agile_Methods_Project
16,844,861,774,585
6b6a7a3520f116075d9219624d7caad5f80e54d8
39accf0a2ecff0bd0e16c912a6c7d3e353769b07
/test_userStory13.py
721494ea52914aba1033edd0a4504a593ca5bc73
[]
no_license
https://github.com/AvaneeshKolluri/Agile_Methods_Project
4b7529d735ad8b3b4edae6aa81fd6acc28da17f0
00959adc3e103ce3f67778d667f77054068c674d
refs/heads/master
2023-01-21T05:20:43.937680
2020-11-30T00:17:39
2020-11-30T00:17:39
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0
1
null
false
2020-10-26T22:47:09
2020-09-18T23:43:40
2020-10-26T21:12:22
2020-10-26T22:46:49
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HTML
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import unittest from userStories import userStory13 import HtmlTestRunner class TestUserStory13Class(unittest.TestCase): def test_UserStory13_1(self): resultsList = userStory13("InputGedFiles/UserStory13_GED/testUserStory13-1.ged") self.assertEqual(resultsList, []) def test_UserStory13_2(self): resultsList = userStory13("InputGedFiles/UserStory13_GED/testUserStory13-2.ged") self.maxDiff = None #print(resultsList) self.assertEqual(resultsList, ['ERROR: INDIVIDUAL: US13: 122: Family F2 has two children (I10, I12) with implausible birth dates (1000-01-01, 0999-11-01)', 'ERROR: INDIVIDUAL: US13: 58: Family F1 has two children (I3, I5) with implausible birth dates (1000-01-01, 1000-05-01)', 'ERROR: INDIVIDUAL: US13: 58: Family F1 has two children (I4, I5) with implausible birth dates (1000-01-02, 1000-05-01)', 'ERROR: INDIVIDUAL: US13: 76: Family F1 has two children (I3, I7) with implausible birth dates (1000-01-01, 0999-10-01)', 'ERROR: INDIVIDUAL: US13: 76: Family F1 has two children (I4, I7) with implausible birth dates (1000-01-02, 0999-10-01)', 'ERROR: INDIVIDUAL: US13: 76: Family F1 has two children (I5, I7) with implausible birth dates (1000-05-01, 0999-10-01)', 'ERROR: INDIVIDUAL: US13: 95: Family F2 has two children (I12, I9) with implausible birth dates (0999-11-01, 1000-01-01)']) if __name__ == '__main__': #warnings.filterwarnings("ignore") unittest.main(testRunner=HtmlTestRunner.HTMLTestRunner(output='./reports'))
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py
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test_userStory13.py
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neuroradiology/Gooey
17,497,696,777,048
2991a58d585d642149ac9148bfdf8b7819c0023a
dd3ca62ee1dab07eaf84ebbc0535d8e5627e1f62
/gooey/tests/test_processor.py
0fd866687200b777c10008e65e54508eb8b6582f
[ "MIT" ]
permissive
https://github.com/neuroradiology/Gooey
f03b51677be1fb280485b689434afdb725da0e29
59684fc507c118b683f22f968d733b71afde4ee1
refs/heads/master
2021-08-15T22:15:13.252224
2021-01-24T17:23:24
2021-01-24T17:23:24
23,333,982
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MIT
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2021-01-24T17:23:24
2014-08-26T01:04:20
2018-04-24T19:37:02
2021-01-24T17:23:24
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import re import unittest from gooey.gui.processor import ProcessController class TestProcessor(unittest.TestCase): def test_extract_progress(self): # should pull out a number based on the supplied # regex and expression processor = ProcessController(r"^progress: (\d+)%$", None, False, 'utf-8') self.assertEqual(processor._extract_progress(b'progress: 50%'), 50) processor = ProcessController(r"total: (\d+)%$", None, False, 'utf-8') self.assertEqual(processor._extract_progress(b'my cool total: 100%'), 100) def test_extract_progress_returns_none_if_no_regex_supplied(self): processor = ProcessController(None, None, False, 'utf-8') self.assertIsNone(processor._extract_progress(b'Total progress: 100%')) def test_extract_progress_returns_none_if_no_match_found(self): processor = ProcessController(r'(\d+)%$', None, False, 'utf-8') self.assertIsNone(processor._extract_progress(b'No match in dis string')) def test_eval_progress(self): # given a match in the string, should eval the result regex = r'(\d+)/(\d+)$' processor = ProcessController(regex, r'x[0] / x[1]', False,False, 'utf-8') match = re.search(regex, '50/50') self.assertEqual(processor._eval_progress(match), 1.0) def test_eval_progress_returns_none_on_failure(self): # given a match in the string, should eval the result regex = r'(\d+)/(\d+)$' processor = ProcessController(regex, r'x[0] *^/* x[1]', False, False,'utf-8') match = re.search(regex, '50/50') self.assertIsNone(processor._eval_progress(match))
UTF-8
Python
false
false
1,705
py
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test_processor.py
109
0.635777
0.616422
0
39
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lucyemmel/speedwagon-foundation-shop
5,360,119,232,226
a2550f4a7f4e7d574584d7a2ef5db74376595e1b
de5d7bab4e35b3f2a6426ce09e0d9726443c3737
/simple_ecommerce/simple_ecommerce/middleware.py
ec466cee584dc3e13ae19a081d1c7cd23816016e
[]
no_license
https://github.com/lucyemmel/speedwagon-foundation-shop
595135643e7ac325d356c46c68b6ab02221b4882
e62bc4593dfafb74e260e46339f55c0d4d0345f8
refs/heads/main
2022-12-30T20:22:16.477284
2020-10-21T15:08:57
2020-10-21T15:08:57
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class FramingControlMiddleware: def __init__(self, get_response): self.get_response = get_response def __call__(self, request): response = self.get_response(request) response['Content-Security-Policy'] = 'frame-ancestors http://localhost:3000 http://127.0.0.1:3000' return response
UTF-8
Python
false
false
324
py
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middleware.py
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0.657407
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9
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Nauendorf/fizzbuzz_python
16,698,832,876,359
2f9bcec26fd4fdc51b52dc6dea5bc598d9e6571a
969adb984423cbc4e7e8716dbf84519ff03cde1f
/notes.py
51ead3e3b65a89f8cab57c2b934c1074aeebda84
[]
no_license
https://github.com/Nauendorf/fizzbuzz_python
b08d534c0d7b4201548d405c05a3e99436c89833
935be824d0238c14c78d5d1937fefd68a6455124
refs/heads/master
2020-12-27T01:09:07.645030
2020-02-15T11:32:36
2020-02-15T11:32:36
237,714,334
1
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null
null
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# import sys # # # test = sys # # # print([a for a in dir(test)]) # print([a for a in dir(test) if not a.startswith('__')]) # print(', '.join(i for i in dir(sys) if not i.startswith('__'))) import sys import platform def getsysinfo(): return [a for a in dir(platform) if not a.startswith('__') and print(getattr(platform, a) and print(a))] print(getsysinfo())
UTF-8
Python
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false
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py
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notes.py
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0.577114
0.577114
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19.1
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pecata83/soft-uni-python-solutions
2,070,174,273,475
eec18a869c8b9e7e71740088826b767c8bd49d1d
f95e0c64792ff7c00b997bd645181f74b3aa3add
/Python Advanced/01. Stacks and Queues Exercise/04.01.py
7a7b2eea4a29b0820443893ada929ebd4ad18edb
[]
no_license
https://github.com/pecata83/soft-uni-python-solutions
6f28fde73ff261c8294c1dd5ea0ad72b6bb4e342
e9746b4b60e803376e475c1e6638964ca4013849
refs/heads/main
2023-02-25T18:01:11.933019
2021-02-02T20:49:28
2021-02-02T20:49:28
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clothes_stack = [int(x) for x in input().split()] rack_capacity = int(input()) current_rack_capacity = rack_capacity racks_used = 1 while clothes_stack: cloth = clothes_stack.pop() if current_rack_capacity >= cloth: current_rack_capacity -= cloth else: racks_used += 1 current_rack_capacity = rack_capacity - cloth print(racks_used)
UTF-8
Python
false
false
375
py
191
04.01.py
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0.650667
0.645333
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NicolasBerveglieri/STAGEM2
1,752,346,688,366
2ade4d4346ebd66c6eea1cb589abd69eb6fbcf4b
537f91bc0a6d0b33550c8378a416c3856e876f9f
/moead_ego.py
e9b30608d3fa9bdf59caad11abf6a45ed71666a0
[]
no_license
https://github.com/NicolasBerveglieri/STAGEM2
69ce502ba52b5e8729e4c969d3a1f08258fe553d
8119f5e4973b1b2023233bdb0ea5228d50437b00
refs/heads/master
2020-03-18T12:24:39.457129
2018-10-02T17:09:26
2018-10-02T17:09:26
134,724,856
0
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# -*- coding: utf-8 -*- """ Created on Wed May 2 15:49:04 2018 @author: nicol """ import numpy.linalg as np from scipy.spatial import distance import heapq from random import randint import random from random import * import sys import sklearn from sklearn.svm import SVR import numpy as np from meoadubqp import * from expected_improvement import * from ZDT1_problem import * from evo_op import * from Aggreg import * from sklearn.gaussian_process import GaussianProcessRegressor from sklearn.gaussian_process.kernels import (RBF, Matern, RationalQuadratic, ExpSineSquared, DotProduct, ConstantKernel) import itertools def moead_EGO(problem,filename,weight_size=24,init_pop=30,update_pop=24,saves=[10,30,70,100,-1]): current_save=0 save = [] #creation des vecteurs de poids weights = weight_vectors(weight_size) solution_size=problem.number_of_variables #solutions initiales current_solutions = [[uniform(-100,100) for x in range(0,solution_size)] for y in range(len(weights))] # leurs valeurs current_solutionsV = [problem(current_solutions[x]) for x in range(len(current_solutions))] gp_kernel = 1.0 * RBF(length_scale=1.0, length_scale_bounds=(1e-1, 10.0)) #debut de la boucle total_eval = 0 #len(current_solutions) while(total_eval < 20): print(total_eval) total_eval+= 1 if total_eval == saves[current_save]: save.append(offline_filter([x.tolist() for x in current_solutionsV])) save[current_save].sort() save[current_save] = list(save[current_save] for save[current_save],_ in itertools.groupby(save[current_save])) current_save+=1 gp1 = GaussianProcessRegressor(kernel =gp_kernel) gp2 = GaussianProcessRegressor(kernel =gp_kernel) # Fit to data using Maximum Likelihood Estimation of the parameters if len(current_solutions) < 231: gp1.fit(current_solutions,[current_solutionsV[x][0] for x in range(len(current_solutions))]) gp2.fit(current_solutions,[current_solutionsV[x][1] for x in range(len(current_solutions))]) else: print("MAX SOLUTION") sol_fit = current_solutions[-200:] solV_fit = current_solutionsV[-200:] gp1.fit(sol_fit,[solV_fit[x][0] for x in range(len(sol_fit))]) gp2.fit(sol_fit,[solV_fit[x][1] for x in range(len(sol_fit))]) #création des gaussians process valuesS = [] for i in range(len(weights)): values = [weighted_sum(weights[i],current_solutionsV[x]) for x in range(len(current_solutionsV))] # Instanciate a Gaussian Process model # kernel = C(1.0, (1e-3, 1e3)) * RBF(10, (1e-2, 1e2)) valuesS += [values] newsol = moead_EI([gp1,gp2] , valuesS ,problem.number_of_variables,weights) newsolV = [problem(newsol[x]) for x in range(len(newsol))] current_solutions += newsol current_solutionsV += newsolV big_save(filename,save,current_solutions,current_solutionsV) return current_solutions, current_solutionsV
UTF-8
Python
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py
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moead_ego.py
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andrewschreiber/agent
1,915,555,443,579
5bee984bf94786b07bae012b1f55c7f5369eda8d
a011e4096ce9635419cd2d19883ccbd979bbb9a3
/tensorboard/plugins/debugger/debugger_server_test.py
b95f90ff2d6a930ac4222b32f918c1a3ebab250c
[ "Apache-2.0" ]
permissive
https://github.com/andrewschreiber/agent
d9cdd480cb7d7d596095256e223b7b6773ababf5
7ad0b37e8ce3ea1f5ff0eac02c23195736ed6f68
refs/heads/master
2020-03-31T08:31:13.695921
2019-05-07T02:21:50
2019-05-07T02:21:50
152,060,727
16
2
Apache-2.0
true
2019-04-29T05:57:49
2018-10-08T10:21:50
2019-04-02T21:36:16
2019-04-29T05:57:48
78,607
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Python
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# Copyright 2017 The TensorFlow 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. # ============================================================================== """Tests the debugger data server, which receives and writes debugger events.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import json import tensorflow as tf # pylint: disable=ungrouped-imports, wrong-import-order from google.protobuf import json_format from tensorflow.core.debug import debugger_event_metadata_pb2 from tensorboard.compat.proto import event_pb2 from tensorboard.plugins.debugger import constants from tensorboard.plugins.debugger import debugger_server_lib from tensorboard.plugins.debugger import numerics_alert from tensorboard.util import tensor_util # pylint: enable=ungrouped-imports, wrong-import-order class FakeEventsWriterManager(object): """An events writer manager that tracks events that would be written. During normal usage, the debugger data server would write events to disk. Unfortunately, this test cannot depend on TensorFlow's record reader due to GRPC library conflicts (b/35006065). Hence, we use a fake EventsWriter that keeps track of events that would be written to disk. """ def __init__(self, events_output_list): """Constructs a fake events writer, which appends events to a list. Args: events_output_list: The list to append events that would be written to disk. """ self.events_written = events_output_list def dispose(self): """Does nothing. This implementation creates no file.""" def write_event(self, event): """Pretends to write an event to disk. Args: event: The event proto. """ self.events_written.append(event) class DebuggerDataServerTest(tf.test.TestCase): def setUp(self): self.events_written = [] events_writer_manager = FakeEventsWriterManager(self.events_written) self.stream_handler = debugger_server_lib.DebuggerDataStreamHandler( events_writer_manager=events_writer_manager) self.stream_handler.on_core_metadata_event(event_pb2.Event()) def tearDown(self): tf.compat.v1.test.mock.patch.stopall() def _create_event_with_float_tensor(self, node_name, output_slot, debug_op, list_of_values): """Creates event with float64 (double) tensors. Args: node_name: The string name of the op. This lacks both the output slot as well as the name of the debug op. output_slot: The number that is the output slot. debug_op: The name of the debug op to use. list_of_values: A python list of values within the tensor. Returns: A `Event` with a summary containing that node name and a float64 tensor with those values. """ event = event_pb2.Event() value = event.summary.value.add( tag=node_name, node_name="%s:%d:%s" % (node_name, output_slot, debug_op), tensor=tensor_util.make_tensor_proto( list_of_values, dtype=tf.float64, shape=[len(list_of_values)])) plugin_content = debugger_event_metadata_pb2.DebuggerEventMetadata( device="/job:localhost/replica:0/task:0/cpu:0", output_slot=output_slot) value.metadata.plugin_data.plugin_name = constants.DEBUGGER_PLUGIN_NAME value.metadata.plugin_data.content = tf.compat.as_bytes( json_format.MessageToJson( plugin_content, including_default_value_fields=True)) return event def _verify_event_lists_have_same_tensor_values(self, expected, gotten): """Checks that two lists of events have the same tensor values. Args: expected: The expected list of events. gotten: The list of events we actually got. """ self.assertEqual(len(expected), len(gotten)) # Compare the events one at a time. for expected_event, gotten_event in zip(expected, gotten): self.assertEqual(expected_event.summary.value[0].node_name, gotten_event.summary.value[0].node_name) self.assertAllClose( tensor_util.make_ndarray(expected_event.summary.value[0].tensor), tensor_util.make_ndarray(gotten_event.summary.value[0].tensor)) self.assertEqual(expected_event.summary.value[0].tag, gotten_event.summary.value[0].tag) def testOnValueEventWritesHealthPill(self): """Tests that the stream handler writes health pills in order.""" # The debugger stream handler receives 2 health pill events. received_events = [ self._create_event_with_float_tensor( "MatMul", 0, "DebugNumericSummary", list(range(1, 15))), self._create_event_with_float_tensor( "add", 0, "DebugNumericSummary", [x * x for x in range(1, 15)]), self._create_event_with_float_tensor( "MatMul", 0, "DebugNumericSummary", [x + 42 for x in range(1, 15)]), ] for event in received_events: self.stream_handler.on_value_event(event) # Verify that the stream handler wrote them to disk in order. self._verify_event_lists_have_same_tensor_values(received_events, self.events_written) def testOnValueEventIgnoresIrrelevantOps(self): """Tests that non-DebugNumericSummary ops are ignored.""" # Receive a DebugNumericSummary event. numeric_summary_event = self._create_event_with_float_tensor( "MatMul", 42, "DebugNumericSummary", list(range(1, 15))) self.stream_handler.on_value_event(numeric_summary_event) # Receive a non-DebugNumericSummary event. self.stream_handler.on_value_event( self._create_event_with_float_tensor("add", 0, "DebugIdentity", list(range(1, 15)))) # The stream handler should have only written the DebugNumericSummary event # to disk. self._verify_event_lists_have_same_tensor_values([numeric_summary_event], self.events_written) def testCorrectStepIsWritten(self): events_written = [] metadata_event = event_pb2.Event() metadata_event.log_message.message = json.dumps({"session_run_index": 42}) stream_handler = debugger_server_lib.DebuggerDataStreamHandler( events_writer_manager=FakeEventsWriterManager(events_written)) stream_handler.on_core_metadata_event(metadata_event) # The server receives 2 events. It should assign both the correct step. stream_handler.on_value_event( self._create_event_with_float_tensor("MatMul", 0, "DebugNumericSummary", list(range(1, 15)))) stream_handler.on_value_event( self._create_event_with_float_tensor("Add", 0, "DebugNumericSummary", list(range(2, 16)))) self.assertEqual(42, events_written[0].step) self.assertEqual(42, events_written[1].step) def testSentinelStepValueAssignedWhenExecutorStepCountKeyIsMissing(self): events_written = [] metadata_event = event_pb2.Event() metadata_event.log_message.message = json.dumps({}) stream_handler = debugger_server_lib.DebuggerDataStreamHandler( events_writer_manager=FakeEventsWriterManager(events_written)) stream_handler.on_core_metadata_event(metadata_event) health_pill_event = self._create_event_with_float_tensor( "MatMul", 0, "DebugNumericSummary", list(range(1, 15))) stream_handler.on_value_event(health_pill_event) self.assertGreater(events_written[0].step, 0) def testSentinelStepValueAssignedWhenMetadataJsonIsInvalid(self): events_written = [] metadata_event = event_pb2.Event() metadata_event.log_message.message = "some invalid JSON string" stream_handler = debugger_server_lib.DebuggerDataStreamHandler( events_writer_manager=FakeEventsWriterManager(events_written)) stream_handler.on_core_metadata_event(metadata_event) health_pill_event = self._create_event_with_float_tensor( "MatMul", 0, "DebugNumericSummary", list(range(1, 15))) stream_handler.on_value_event(health_pill_event) self.assertGreater(events_written[0].step, 0) def testAlertingEventCallback(self): numerics_alert_callback = tf.compat.v1.test.mock.Mock() stream_handler = debugger_server_lib.DebuggerDataStreamHandler( events_writer_manager=FakeEventsWriterManager( self.events_written), numerics_alert_callback=numerics_alert_callback) stream_handler.on_core_metadata_event(event_pb2.Event()) # The stream handler receives 1 good event and 1 with an NaN value. stream_handler.on_value_event( self._create_event_with_float_tensor("Add", 0, "DebugNumericSummary", [0] * 14)) stream_handler.on_value_event( self._create_event_with_float_tensor("Add", 0, "DebugNumericSummary", [ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ])) # The second event should have triggered the callback. numerics_alert_callback.assert_called_once_with( numerics_alert.NumericsAlert("/job:localhost/replica:0/task:0/cpu:0", "Add:0", 0, 1, 0, 0)) # The stream handler receives an event with a -Inf value. numerics_alert_callback.reset_mock() stream_handler.on_value_event( self._create_event_with_float_tensor("Add", 0, "DebugNumericSummary", [ 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ])) numerics_alert_callback.assert_called_once_with( numerics_alert.NumericsAlert("/job:localhost/replica:0/task:0/cpu:0", "Add:0", 0, 0, 1, 0)) # The stream handler receives an event with a +Inf value. numerics_alert_callback.reset_mock() stream_handler.on_value_event( self._create_event_with_float_tensor("Add", 0, "DebugNumericSummary", [ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0 ])) numerics_alert_callback.assert_called_once_with( numerics_alert.NumericsAlert("/job:localhost/replica:0/task:0/cpu:0", "Add:0", 0, 0, 0, 1)) # The stream handler receives an event without any pathetic values. numerics_alert_callback.reset_mock() stream_handler.on_value_event( self._create_event_with_float_tensor("Add", 0, "DebugNumericSummary", [ 0, 0, 0, 0, 1, 2, 3, 0, 0, 0, 0, 0, 0, 0 ])) # assert_not_called is not available in Python 3.4. self.assertFalse(numerics_alert_callback.called) if __name__ == "__main__": tf.test.main()
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py
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yb8350/OnrestChatbot
2,645,699,889,464
b547bae6649cd987615096fcc12e30ab383830e5
17e4570eadefa3fc31a6ff2d9fac113c1f72ece8
/mrp.py
673ec84834729d1e66e43b90f981068c7681c87e
[]
no_license
https://github.com/yb8350/OnrestChatbot
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import re import math import datetime import pandas as pd from konlpy.tag import Komoran kom = Komoran(userdic='./UserDictionaryData.txt') SongLocation = pd.read_csv ('./SongLocation.csv') EmoDic = pd.read_csv ('./EmotionalDictionary.csv') negative = [('않', 'VX'), ('못하', 'VX'), ('말', 'VX'), ('아니', 'MAG'), ('아니', 'VCN'), ('안', 'MAG'), ('못', 'MAG'), ('지 않', 'EP'),('지 말', 'EP'),('지 못', 'EP'),('지 마', 'EC'),('지 마라', 'EC'),('진 않', 'EP'),('진 말', 'EP'),('진 못', 'EP'),('진 마', 'EC'),('진 마라', 'EC'),('질 않', 'EP'),('질 못', 'EP'),('질 말', 'EP'),('질 마', 'EC'),('질 마라', 'EC')] emotion = ['XR', 'VA', 'VV', 'VX', 'NNG', 'MAG', 'NNP', 'MM', 'NA'] angle = [75, 45, 15, 345, 315, 285, 255, 225, 195, 165, 135, 105] ed = {} for i in range(len(EmoDic)): ed[(EmoDic.abbr[i], EmoDic.wc[i])] = EmoDic.num[i] #사용자 감정 분석 함수 def emotionAnalysis(diary): vector = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] #1. 영어 제거 diary = re.sub('[^ㄱ-ㅣ 가-힣 \n]+', '', diary) #2. 형태소 분석 try: res = kom.pos(diary, flatten=False) except: return 0, 0 #3. 부정어 처리 NegSentences = [] d_index = [] for i in range(len(res)): for j in range(len(res[i])): if res[i][j] in negative : NegSentences.append(res[i]) d_index.append(i) break d_index.reverse() if len(d_index) > 0: for i in d_index: del res[i] emo = [] neg = False for ng in NegSentences : for i in range(len(ng)): if ng[i] in negative: neg = True if ng[i][1] == 'EC' or ng[i][1] == 'EF': if len(emo) > 0 and neg == True : for i in emo: if i < 6 : vector[i+6] += 1; else: vector[i-6] += 1; else: if len(emo) > 0: for i in emo: vector[i] += 1; emo = [] neg = False elif ng[i] in ed.keys(): emo.append(ed[ng[i]]-1) #4. 필요없는 품사 제거 + BoW word = {} bow = [] for voca in res: for i in range(len(voca)): if voca[i][1] in emotion: if voca[i] not in word.keys(): word[voca[i]] = len(word) bow.insert(len(word)-1,1) else: index = word.get(voca[i]) bow[index] += 1 #5. 감성사전 탐색 for w in word: if w in ed.keys(): vector[ed[w]-1] += bow[word.get(w)] #6. 정규화, 좌표값 계산 sum = 0 x = 0 y = 0 for i in vector: sum += i if sum == 0 : return 0, 0 for i in range(12): vector[i] /= sum x += vector[i] * math.cos((angle[i]/180) * math.pi) y += vector[i] * math.sin((angle[i]/180) * math.pi) x /= 12 y /= 12 return x, y # 좌표를 통해 감정 카테고리 판단하는 함수 def SelectCategory(x, y): if x == 0 and y == 0: return 0 myradians = math.atan2(y, x) mydegrees = math.degrees(myradians) if mydegrees >= 60 and mydegrees < 90: return 1 elif mydegrees >= 30 and mydegrees < 60: return 2 elif mydegrees >= 0 and mydegrees < 30: return 3 elif mydegrees >= -30 and mydegrees < 0: return 4 elif mydegrees >= -60 and mydegrees < -30: return 5 elif mydegrees >= -90 and mydegrees < -60: return 6 elif mydegrees >= -120 and mydegrees < -90: return 7 elif mydegrees >= -150 and mydegrees < -120: return 8 elif mydegrees >= -180 and mydegrees < -150: return 9 elif mydegrees >= 150 and mydegrees < 180: return 10 elif mydegrees >= 120 and mydegrees < 150: return 11 elif mydegrees >= 90 and mydegrees < 120: return 12 #감정 분석 결과를 통해 음악 추천 방식을 결정하는 함수 def resultCheck(feelX, feelY, diaryX, diaryY): check = -1 if diaryX == 0 and diaryY == 0: if feelX == 0 and feelY == 0: return check else: check = 1 return check elif feelX == 0 and feelY == 0: check = 0 return check feelCateNum = SelectCategory(feelX, feelY) diaryCateNum = SelectCategory(diaryX, diaryY) absCateNum = abs(diaryCateNum - feelCateNum) #1번 카테고리는 2번 카테고리까지만 허용 if diaryCateNum == 1: if absCateNum == 0 or feelCateNum == 2: check = 0 # 카테고리가 같거나 양옆까지만 허용 elif absCateNum == 0 or absCateNum == 1: check = 0 else: check = 1 return check #사용자 감정에 가장 근접한 음악 추천 함수 def musicRecommend(diaryX, diaryY): leng = len(SongLocation) userCategory = SelectCategory(diaryX, diaryY) distance = [] for i in range(leng): songCategory = SongLocation.CategoryNum[i] dis = round(math.sqrt( math.pow(SongLocation.x[i] - diaryX , 2) + math.pow(SongLocation.y[i] - diaryY , 2)), 5) distance.append(dis) SongLocation['distance'] = distance resultSort = SongLocation.sort_values(by='distance') resultSort = resultSort.reset_index(drop=True) result = [] for i in range(leng): songData = [] if userCategory-1 <= resultSort.CategoryNum[i] and userCategory+1 >= resultSort.CategoryNum[i]: songData.append(resultSort.SongName[i]) songData.append(resultSort.Singer[i]) songData.append(resultSort.Image[i]) songData.append(resultSort.SongNum[i]) result.append(songData) if len(result) == 3: break return result #랜덤 음악 추천 함수 def randomMusic(cateNum): bitMask = SongLocation['CategoryNum'] == cateNum randomList = SongLocation[bitMask] playList = randomList.sample(n=3) # result 추천할 곡의 데이터 리스트 형태 result = [] for i in range(len(playList)): songList = [] songList.append(playList['SongName'].iloc[i]) songList.append(playList['Singer'].iloc[i]) songList.append(playList['Image'].iloc[i]) songList.append(playList['SongNum'].iloc[i]) result.append(songList) return result
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from numpy import * import re from openopt.kernel.baseSolver import baseSolver from openopt.kernel.nonOptMisc import Vstack, Find, isspmatrix #import os try: import pyipopt pyipoptInstalled = True except: pyipoptInstalled = False class ipopt(baseSolver): __name__ = 'ipopt' __license__ = "CPL" __authors__ = 'Carl Laird (Carnegie Mellon University) and Andreas Wachter' __alg__ = "A. Wachter and L. T. Biegler, On the Implementation of a Primal-Dual Interior Point Filter Line Search Algorithm for Large-Scale Nonlinear Programming, Mathematical Programming 106(1), pp. 25-57, 2006 " __homepage__ = 'http://www.coin-or.org/' __info__ = "requires pyipopt made by Eric Xu You" __optionalDataThatCanBeHandled__ = ['A', 'Aeq', 'b', 'beq', 'lb', 'ub', 'c', 'h'] _canHandleScipySparse = True # CHECK ME! #__isIterPointAlwaysFeasible__ = lambda self, p: p.__isNoMoreThanBoxBounded__() optFile = 'auto' options = '' def __init__(self): pass def __solver__(self, p): if not pyipoptInstalled: p.err('you should have pyipopt installed') # try: # os.close(1); os.close(2) # may not work for non-Unix OS # except: # pass nvar = p.n x_L = p.lb x_U = p.ub ncon = p.nc + p.nh + p.b.size + p.beq.size g_L, g_U = zeros(ncon), zeros(ncon) g_L[:p.nc] = -inf g_L[p.nc+p.nh:p.nc+p.nh+p.b.size] = -inf # IPOPT non-linear constraints, both eq and ineq if p.isFDmodel: r = [] if p.nc != 0: r.append(p._getPattern(p.user.c)) if p.nh != 0: r.append(p._getPattern(p.user.h)) if p.nb != 0: r.append(p.A) if p.nbeq != 0: r.append(p.Aeq) if len(r)>0: if all([isinstance(elem, ndarray) for elem in r]): r = vstack(r) else: r = Vstack(r) if isspmatrix(r): from scipy import __version__ if __version__.startswith('0.7.3') or __version__.startswith('0.7.2') or __version__.startswith('0.7.1') or __version__.startswith('0.7.0'): p.pWarn('updating scipy to version >= 0.7.4 is very recommended for the problem with the solver IPOPT') else: r = array([]) if isspmatrix(r): I, J, _ = Find(r) # DON'T remove it! I, J = array(I, int64), array(J, int64) elif isinstance(r, ndarray): if r.size == 0: I, J= array([], dtype=int64),array([], dtype=int64) else: I, J = where(r) else: p.disp('unimplemented type:%s' % str(type(r))) # dense matrix? nnzj = len(I) else: I, J = where(ones((ncon, p.n))) #I, J = None, None nnzj = ncon * p.n #TODO: reduce it def eval_g(x): r = array(()) if p.userProvided.c: r = p.c(x) if p.userProvided.h: r = hstack((r, p.h(x))) r = hstack((r, p._get_AX_Less_B_residuals(x), p._get_AeqX_eq_Beq_residuals(x))) return r def eval_jac_g(x, flag, userdata = (I, J)): (I, J) = userdata if flag and p.isFDmodel: return (I, J) r = [] if p.userProvided.c: r.append(p.dc(x)) if p.userProvided.h: r.append(p.dh(x)) if p.nb != 0: r.append(p.A) if p.nbeq != 0: r.append(p.Aeq) # TODO: fix it! if any([isspmatrix(elem) for elem in r]): r = Vstack([(atleast_2d(elem) if elem.ndim < 2 else elem) for elem in r]) elif len(r)!=0: r = vstack(r) if p.isFDmodel: # TODO: make it more properly R = (r.tocsr() if isspmatrix(r) else r)[I, J] if isspmatrix(R): return R.A elif isinstance(R, ndarray): return R else: p.err('bug in OpenOpt-ipopt connection, inform OpenOpt developers, type(R) = %s' % type(R)) if flag: return (I, J) else: if isspmatrix(r): r = r.A return r.flatten() """ This function might be buggy, """ # // comment by Eric nnzh = 0 def eval_h(lagrange, obj_factor, flag): return None # def apply_new(x): # return True nlp = pyipopt.create(nvar, x_L, x_U, ncon, g_L, g_U, nnzj, nnzh, p.f, p.df, eval_g, eval_jac_g) if self.optFile == 'auto': lines = ['# generated automatically by OpenOpt\n','print_level 0\n'] lines.append('tol ' + str(p.ftol)+ '\n') lines.append('constr_viol_tol ' + str(p.contol)+ '\n') lines.append('max_iter ' + str(min(15000, p.maxIter))+ '\n') if self.options != '' : for s in re.split(',|;', self.options): lines.append(s.strip().replace('=', ' ', 1) + '\n') if p.nc == 0: lines.append('jac_d_constant yes\n') if p.nh == 0: lines.append('jac_c_constant yes\n') if p.castFrom.lower() in ('lp', 'qp', 'llsp'): lines.append('hessian_constant yes\n') ipopt_opt_file = open('ipopt.opt', 'w') ipopt_opt_file.writelines(lines) ipopt_opt_file.close() try: x, zl, zu, obj = nlp.solve(p.x0)[:4] if p.point(p.xk).betterThan(p.point(x)): obj = p.fk p.xk = p.xk.copy() # for more safety else: p.xk, p.fk = x.copy(), obj if p.istop == 0: p.istop = 1000 finally: nlp.close()
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import json from django.core.serializers import serialize from rest_framework.response import Response from .serializers import ListingSerializer, BookingInfoSerializer from .models import Listing, BookingInfo from rest_framework.decorators import api_view from rest_framework.views import APIView from rest_framework import status from rest_framework import mixins from rest_framework import generics from django.http import JsonResponse from datetime import datetime class ListingView(mixins.ListModelMixin, mixins.CreateModelMixin, generics.GenericAPIView): queryset = Listing.objects.all() serializer_class = ListingSerializer def get(self, request, *args, **kwargs): Listings = Listing.objects.all() BookingInfos = BookingInfo.objects.all() JsonListings = json.loads(serialize("json", Listings)) data = [] check_in = request.GET['check_in'] check_out = request.GET['check_out'] max_price = request.GET['max_price'] for each in BookingInfos: for obj in JsonListings: if each.id == obj["fields"]["blocksday"]: # datetime.strptime(obj["fields"]["blockdays_start"], "%Y-%m-%d").strftime("%d-%m-%Y") if int(max_price) >= int(each.price): data.append({"listing_type": obj["fields"]["listing_type"], "title": obj["fields"]["title"], "country": obj["fields"]["country"], "city": obj["fields"]["city"], "price": each.price }) data = sorted(data, key=lambda k: int(k['price']), reverse=False) return JsonResponse({"items": data}, content_type='application/json') # return self.list(request, *args, **kwargs) def post(self, request, *args, **kwargs): return self.create(request, *args, **kwargs) class ListingDetail(mixins.RetrieveModelMixin, mixins.UpdateModelMixin, mixins.DestroyModelMixin, generics.GenericAPIView): queryset = Listing.objects.all() serializer_class = ListingSerializer def get(self, request, *args, **kwargs): return self.retrieve(request, *args, **kwargs) def put(self, request, *args, **kwargs): return self.update(request, *args, **kwargs) def delete(self, request, *args, **kwargs): return self.destroy(request, *args, **kwargs)
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# 2. Во втором массиве сохранить индексы четных элементов первого массива. Например, если дан массив со значениями 8, 3, 15, 6, 4, 2, # то во второй массив надо заполнить значениями 1, 4, 5, 6 (или 0, 3, 4, 5 - если индексация начинается с нуля), # т.к. именно в этих позициях первого массива стоят четные числа. import random SIZE = 10 min_item = 2 max_item = 100 array_1 = [random.randint(min_item, max_item) for _ in range(SIZE)] ar_index = [] for i in range(len(array_1)): if array_1[i] % 2 == 0: ar_index.append(i) # Вывод на экран результата print(f'Дан массив чисел {array_1}') print('Необходимо вывести индексы четных чисел в массиве.') print(f'В данном массиве четные числа расположены под индексами {ar_index}')
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/openstack_dashboard/dashboards/project/floating_ips/tests.py
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# Copyright 2012 United States Government as represented by the # Administrator of the National Aeronautics and Space Administration. # All Rights Reserved. # # Copyright 2012 Nebula, Inc. # Copyright (c) 2012 X.commerce, a business unit of eBay Inc. # # 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. from unittest import mock from django.urls import reverse from django.utils.http import urlencode from openstack_dashboard import api from openstack_dashboard.test import helpers as test from openstack_dashboard.usage import quotas from horizon.workflows import views INDEX_URL = reverse('horizon:project:floating_ips:index') NAMESPACE = "horizon:project:floating_ips" class FloatingIpViewTests(test.TestCase): def setUp(self): super().setUp() api_mock = mock.patch.object( api.neutron, 'is_extension_floating_ip_port_forwarding_supported').start() api_mock.return_value = True @test.create_mocks({api.neutron: ('floating_ip_target_list', 'tenant_floating_ip_list')}) def test_associate(self): self.mock_floating_ip_target_list.return_value = \ self._get_fip_targets() self.mock_tenant_floating_ip_list.return_value = \ self.floating_ips.list() url = reverse('%s:associate' % NAMESPACE) res = self.client.get(url) self.assertTemplateUsed(res, views.WorkflowView.template_name) workflow = res.context['workflow'] choices = dict(workflow.steps[0].action.fields['ip_id'].choices) # Verify that our "associated" floating IP isn't in the choices list. self.assertNotIn(self.floating_ips.first(), choices) self.mock_floating_ip_target_list.assert_called_once_with( test.IsHttpRequest()) self.mock_tenant_floating_ip_list.assert_called_once_with( test.IsHttpRequest()) @test.create_mocks({api.neutron: ('floating_ip_target_list_by_instance', 'tenant_floating_ip_list')}) def test_associate_with_instance_id(self): targets = self._get_fip_targets() target = targets[0] self.mock_floating_ip_target_list_by_instance.return_value = [target] self.mock_tenant_floating_ip_list.return_value = \ self.floating_ips.list() base_url = reverse('%s:associate' % NAMESPACE) params = urlencode({'instance_id': target.instance_id}) url = '?'.join([base_url, params]) res = self.client.get(url) self.assertTemplateUsed(res, views.WorkflowView.template_name) workflow = res.context['workflow'] choices = dict(workflow.steps[0].action.fields['ip_id'].choices) # Verify that our "associated" floating IP isn't in the choices list. self.assertNotIn(self.floating_ips.first(), choices) self.mock_floating_ip_target_list_by_instance.assert_called_once_with( test.IsHttpRequest(), target.instance_id) self.mock_tenant_floating_ip_list.assert_called_once_with( test.IsHttpRequest()) def _get_compute_ports(self): return [p for p in self.ports.list() if not p.device_owner.startswith('network:')] def _get_fip_targets(self): server_dict = dict((s.id, s.name) for s in self.servers.list()) targets = [] for p in self._get_compute_ports(): for ip in p.fixed_ips: targets.append(api.neutron.FloatingIpTarget( p, ip['ip_address'], server_dict.get(p.device_id))) targets[-1].port_forwardings = [] return targets @staticmethod def _get_target_id(port): return '%s_%s' % (port.id, port.fixed_ips[0]['ip_address']) @test.create_mocks({api.neutron: ('floating_ip_target_list', 'tenant_floating_ip_list')}) def test_associate_with_port_id(self): compute_port = self._get_compute_ports()[0] associated_fips = [fip.id for fip in self.floating_ips.list() if fip.port_id] self.mock_floating_ip_target_list.return_value = \ self._get_fip_targets() self.mock_tenant_floating_ip_list.return_value = \ self.floating_ips.list() base_url = reverse('%s:associate' % NAMESPACE) params = urlencode({'port_id': compute_port.id}) url = '?'.join([base_url, params]) res = self.client.get(url) self.assertTemplateUsed(res, views.WorkflowView.template_name) workflow = res.context['workflow'] choices = dict(workflow.steps[0].action.fields['ip_id'].choices) # Verify that our "associated" floating IP isn't in the choices list. self.assertFalse(set(associated_fips) & set(choices.keys())) self.mock_floating_ip_target_list.assert_called_once_with( test.IsHttpRequest()) self.mock_tenant_floating_ip_list.assert_called_once_with( test.IsHttpRequest()) @test.create_mocks({api.neutron: ('floating_ip_associate', 'floating_ip_target_list', 'tenant_floating_ip_list')}) def test_associate_post(self): floating_ip = [fip for fip in self.floating_ips.list() if not fip.port_id][0] compute_port = self._get_compute_ports()[0] port_target_id = self._get_target_id(compute_port) self.mock_tenant_floating_ip_list.return_value = \ self.floating_ips.list() self.mock_floating_ip_target_list.return_value = \ self._get_fip_targets() self.mock_floating_ip_associate.return_value = None form_data = {'port_id': port_target_id, 'ip_id': floating_ip.id} url = reverse('%s:associate' % NAMESPACE) res = self.client.post(url, form_data) self.assertRedirectsNoFollow(res, INDEX_URL) self.mock_tenant_floating_ip_list.assert_called_once_with( test.IsHttpRequest()) self.mock_floating_ip_target_list.assert_called_once_with( test.IsHttpRequest()) self.mock_floating_ip_associate.assert_called_once_with( test.IsHttpRequest(), floating_ip.id, port_target_id) @test.create_mocks({api.neutron: ('floating_ip_associate', 'floating_ip_target_list', 'tenant_floating_ip_list')}) def test_associate_post_with_redirect(self): floating_ip = [fip for fip in self.floating_ips.list() if not fip.port_id][0] compute_port = self._get_compute_ports()[0] port_target_id = self._get_target_id(compute_port) self.mock_tenant_floating_ip_list.return_value = \ self.floating_ips.list() self.mock_floating_ip_target_list.return_value = \ self._get_fip_targets() self.mock_floating_ip_associate.return_value = None next = reverse("horizon:project:instances:index") form_data = {'port_id': port_target_id, 'next': next, 'ip_id': floating_ip.id} url = reverse('%s:associate' % NAMESPACE) res = self.client.post(url, form_data) self.assertRedirectsNoFollow(res, next) self.mock_tenant_floating_ip_list.assert_called_once_with( test.IsHttpRequest()) self.mock_floating_ip_target_list.assert_called_once_with( test.IsHttpRequest()) self.mock_floating_ip_associate.assert_called_once_with( test.IsHttpRequest(), floating_ip.id, port_target_id) @test.create_mocks({api.neutron: ('floating_ip_associate', 'floating_ip_target_list', 'tenant_floating_ip_list')}) def test_associate_post_with_exception(self): floating_ip = [fip for fip in self.floating_ips.list() if not fip.port_id][0] compute_port = self._get_compute_ports()[0] port_target_id = self._get_target_id(compute_port) self.mock_tenant_floating_ip_list.return_value = \ self.floating_ips.list() self.mock_floating_ip_target_list.return_value = \ self._get_fip_targets() self.mock_floating_ip_associate.side_effect = self.exceptions.nova form_data = {'port_id': port_target_id, 'ip_id': floating_ip.id} url = reverse('%s:associate' % NAMESPACE) res = self.client.post(url, form_data) self.assertRedirectsNoFollow(res, INDEX_URL) self.mock_tenant_floating_ip_list.assert_called_once_with( test.IsHttpRequest()) self.mock_floating_ip_target_list.assert_called_once_with( test.IsHttpRequest()) self.mock_floating_ip_associate.assert_called_once_with( test.IsHttpRequest(), floating_ip.id, port_target_id) @test.create_mocks({api.nova: ('server_list',), api.neutron: ('floating_ip_disassociate', 'floating_ip_pools_list', 'floating_ip_port_forwarding_list', 'is_extension_supported', 'tenant_floating_ip_list')}) def test_disassociate_post(self): floating_ip = self.floating_ips.first() self.mock_is_extension_supported.return_value = False self.mock_floating_ip_port_forwarding_list.return_value = [] self.mock_server_list.return_value = [self.servers.list(), False] self.mock_tenant_floating_ip_list.return_value = \ self.floating_ips.list() self.mock_floating_ip_pools_list.return_value = self.pools.list() self.mock_floating_ip_disassociate.return_value = None action = "floating_ips__disassociate__%s" % floating_ip.id res = self.client.post(INDEX_URL, {"action": action}) self.assertMessageCount(success=1) self.assertRedirectsNoFollow(res, INDEX_URL) self.mock_server_list.assert_called_once_with(test.IsHttpRequest(), detailed=False) self.mock_tenant_floating_ip_list.assert_called_once_with( test.IsHttpRequest()) self.mock_floating_ip_pools_list.assert_called_once_with( test.IsHttpRequest()) self.mock_floating_ip_disassociate.assert_called_once_with( test.IsHttpRequest(), floating_ip.id) self.mock_is_extension_supported.assert_called_once_with( test.IsHttpRequest(), 'dns-integration') @test.create_mocks({api.nova: ('server_list',), api.neutron: ('floating_ip_disassociate', 'floating_ip_port_forwarding_list', 'floating_ip_pools_list', 'is_extension_supported', 'tenant_floating_ip_list')}) def test_disassociate_post_with_exception(self): floating_ip = self.floating_ips.first() self.mock_is_extension_supported.return_value = False self.mock_floating_ip_port_forwarding_list.return_value = [] self.mock_server_list.return_value = [self.servers.list(), False] self.mock_tenant_floating_ip_list.return_value = \ self.floating_ips.list() self.mock_floating_ip_pools_list.return_value = self.pools.list() self.mock_floating_ip_disassociate.side_effect = self.exceptions.nova action = "floating_ips__disassociate__%s" % floating_ip.id res = self.client.post(INDEX_URL, {"action": action}) self.assertRedirectsNoFollow(res, INDEX_URL) self.mock_server_list.assert_called_once_with(test.IsHttpRequest(), detailed=False) self.mock_tenant_floating_ip_list.assert_called_once_with( test.IsHttpRequest()) self.mock_floating_ip_pools_list.assert_called_once_with( test.IsHttpRequest()) self.mock_floating_ip_disassociate.assert_called_once_with( test.IsHttpRequest(), floating_ip.id) self.mock_is_extension_supported.assert_called_once_with( test.IsHttpRequest(), 'dns-integration') @test.create_mocks({api.neutron: ('tenant_floating_ip_list', 'is_extension_supported', 'floating_ip_port_forwarding_list', 'floating_ip_pools_list'), api.nova: ('server_list',), quotas: ('tenant_quota_usages',)}) def test_allocate_button_attributes(self): floating_ips = self.floating_ips.list() floating_pools = self.pools.list() quota_data = self.neutron_quota_usages.first() self.mock_is_extension_supported.return_value = False self.mock_tenant_floating_ip_list.return_value = floating_ips self.mock_floating_ip_port_forwarding_list.return_value = [] self.mock_floating_ip_pools_list.return_value = floating_pools self.mock_server_list.return_value = [self.servers.list(), False] self.mock_tenant_quota_usages.return_value = quota_data res = self.client.get(INDEX_URL) allocate_action = self.getAndAssertTableAction(res, 'floating_ips', 'allocate') self.assertEqual(set(['ajax-modal']), set(allocate_action.classes)) self.assertEqual('Allocate IP To Project', allocate_action.verbose_name) self.assertIsNone(allocate_action.policy_rules) url = 'horizon:project:floating_ips:allocate' self.assertEqual(url, allocate_action.url) self.mock_tenant_floating_ip_list.assert_called_with( test.IsHttpRequest()) self.mock_floating_ip_pools_list.assert_called_with( test.IsHttpRequest()) self.mock_server_list.assert_called_once_with(test.IsHttpRequest(), detailed=False) self.assert_mock_multiple_calls_with_same_arguments( self.mock_tenant_quota_usages, 3, mock.call(test.IsHttpRequest(), targets=('floatingip', ))) self.mock_is_extension_supported.assert_called_once_with( test.IsHttpRequest(), 'dns-integration', ) @test.create_mocks({api.neutron: ('tenant_floating_ip_list', 'is_extension_supported', 'floating_ip_port_forwarding_list', 'floating_ip_pools_list'), api.nova: ('server_list',), quotas: ('tenant_quota_usages',)}) def test_allocate_button_disabled_when_quota_exceeded(self): floating_ips = self.floating_ips.list() floating_pools = self.pools.list() quota_data = self.neutron_quota_usages.first() quota_data['floatingip']['available'] = 0 self.mock_is_extension_supported.return_value = False self.mock_tenant_floating_ip_list.return_value = floating_ips self.mock_floating_ip_port_forwarding_list.return_value = [] self.mock_floating_ip_pools_list.return_value = floating_pools self.mock_server_list.return_value = [self.servers.list(), False] self.mock_tenant_quota_usages.return_value = quota_data res = self.client.get(INDEX_URL) allocate_action = self.getAndAssertTableAction(res, 'floating_ips', 'allocate') self.assertIn('disabled', allocate_action.classes, 'The create button should be disabled') self.assertEqual('Allocate IP To Project (Quota exceeded)', allocate_action.verbose_name) self.mock_tenant_floating_ip_list.assert_called_with( test.IsHttpRequest()) self.mock_floating_ip_pools_list.assert_called_with( test.IsHttpRequest()) self.mock_server_list.assert_called_once_with(test.IsHttpRequest(), detailed=False) self.assert_mock_multiple_calls_with_same_arguments( self.mock_tenant_quota_usages, 3, mock.call(test.IsHttpRequest(), targets=('floatingip', ))) self.mock_is_extension_supported.assert_called_once_with( test.IsHttpRequest(), 'dns-integration', ) @test.create_mocks({api.neutron: ('floating_ip_pools_list', 'is_extension_supported'), quotas: ('tenant_quota_usages',)}) @test.update_settings(OPENSTACK_NEUTRON_NETWORK={'enable_quotas': True}) def test_correct_quotas_displayed(self): self.mock_is_extension_supported.side_effect = [False, True, False] self.mock_tenant_quota_usages.return_value = \ self.neutron_quota_usages.first() self.mock_floating_ip_pools_list.return_value = self.pools.list() url = reverse('%s:allocate' % NAMESPACE) res = self.client.get(url) self.assertEqual(res.context['usages']['floatingip']['quota'], self.neutron_quotas.first().get('floatingip').limit) self.mock_is_extension_supported.assert_called_once_with( test.IsHttpRequest(), 'dns-integration') self.mock_tenant_quota_usages.assert_called_once_with( test.IsHttpRequest(), targets=('floatingip',)) self.mock_floating_ip_pools_list.assert_called_once_with( test.IsHttpRequest())
UTF-8
Python
false
false
18,370
py
2,064
tests.py
1,011
0.601361
0.599565
0
388
46.345361
80
seer-group/Robokit_TCP_API_py
10,256,381,914,790
3de4c836ce118267b15478ec09a3bd78d52ce990
c0151d01bdedd17484b4f3d83bfc77ca7b39f2c9
/rbkApiCopyFile.py
49bedbab4d75e38204ae1325ccd45707a800ba03
[]
no_license
https://github.com/seer-group/Robokit_TCP_API_py
5e9f369fcabd6ab262da26e52af0e3f8bfb0eef7
a407ea56767ec50cfea4ed301a6c2c9894de3845
refs/heads/master
2022-12-13T02:42:52.794738
2018-03-21T06:08:47
2018-03-21T06:08:47
null
0
0
null
null
null
null
null
null
null
null
null
null
null
null
null
from rbkNetProtoEnums import * import rbkNetProtoEnums import json import socket import os so = socket.socket(socket.AF_INET, socket.SOCK_STREAM) so.settimeout(2) #so.connect(('192.168.4.109', API_PORT_STATE)) so.connect(('192.168.192.5', API_PORT_ROBOD)) so.send(packMsg(1, robot_daemon_scp_req, { "path": '/log', "filename": 'robokit_2018 - 01 - 29_12 - 49 - 01.109.log'})) data = so.recv(16) jsonDataLen = 0 if(len(data) < 16): print('pack head error') os.system('pause') so.close() quit() else: jsonDataLen = unpackHead(data) data = so.recv(1024) logfile = open('log.zip', 'wb') logfile.write(data) logfile.close() os.system('pause') so.close()
UTF-8
Python
false
false
683
py
15
rbkApiCopyFile.py
14
0.666179
0.5959
0
32
20.34375
84
tireub/Chromaffin
14,491,219,659,008
60fe9696164535111da5ca0eadaaa7487ea51763
79f1eafcfa8089615bdcc0cc2048e10826a9c2f3
/Models.py
c5d9ea609d7e5cbaee1e392c65014f492b89eb4d
[]
no_license
https://github.com/tireub/Chromaffin
b35a1890c603aeff523f33afa235dc52eec68ca9
56ddec1cc988a4a8361a46c8da7d4ce6d95f2d54
refs/heads/master
2020-04-05T05:11:11.352452
2018-12-27T11:23:45
2018-12-27T11:23:45
156,584,633
0
0
null
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from sqlalchemy import Column, Integer, String, Date, ForeignKey, DECIMAL from sqlalchemy.orm import relationship from Base import Base class Cell(Base): __tablename__ = 'cell' id = Column(Integer, primary_key=True) name = Column(String(100)) date = Column(Date) stimulation_time = Column(Integer) stimulation_type_id = Column(Integer, ForeignKey("stimulation_type.id")) stimulation_type = relationship("StimulationType") vesicles = relationship("Vesicle", back_populates="cell") membranes = relationship("MembranePoint", back_populates="cell") def __init__(self, name, date): self.name = name self.date = date class StimulationType(Base): __tablename__ = "stimulation_type" id = Column(Integer, primary_key=True) chemical = Column(String(100)) def __init__(self, chemical): self.chemical = chemical class MembranePoint(Base): __tablename__ = "membrane_point" id = Column(Integer, primary_key=True) cell_id = Column(Integer, ForeignKey("cell.id")) cell = relationship("Cell", back_populates="membranes") x = Column(DECIMAL(6,4)) y = Column(DECIMAL(6,4)) def __init__(self, cell_id, x, y): self.cell_id = cell_id self.x = x self.y = y class Vesicle(Base): __tablename__ = "vesicle" id = Column(Integer, primary_key=True) track_duration = Column(Integer) cell_id = Column(Integer, ForeignKey("cell.id")) cell = relationship("Cell", back_populates="vesicles") behaviour = relationship("VesicleBehaviour", back_populates="vesicle") positions = relationship("Position", back_populates="vesicle") def __init__(self, duration, cell): self.track_duration = duration self.cell = cell class BehaviourType(Base): __tablename__ = "behaviour_type" id = Column(Integer, primary_key=True) type = Column(String(20)) def __init__(self, type): self.type = type class VesicleBehaviour(Base): __tablename__ = "vesicle_behaviour" vesicle_id = Column(Integer, ForeignKey("vesicle.id"), primary_key=True) vesicle = relationship("Vesicle", back_populates="behaviour") time_status = Column(Integer, primary_key=True) behaviour_type_id = Column(Integer, ForeignKey("behaviour_type.id")) behaviour_type = relationship("BehaviourType") def __init__(self, vesicle, time): self.vesicle = vesicle self.time_status = time class MSD(Base): __tablename__ = "msd" vesicle_id = Column(Integer, ForeignKey("vesicle.id"), primary_key=True) vesicle = relationship("Vesicle") deltat = Column(Integer, primary_key=True) before_after_stimu = Column(Integer, primary_key=True) value = Column(DECIMAL(8,6)) def __init__(self, vesicle, deltat, value, beforeafter): self.vesicle = vesicle self.before_after_stimu = beforeafter self.deltat = deltat self.value = value class Position(Base): __tablename__ = "position" id = Column(Integer, primary_key=True) x = Column(DECIMAL(6,4)) y = Column(DECIMAL(6,4)) z = Column(DECIMAL(6,4)) t = Column(Integer) vesicle_id = Column(Integer, ForeignKey("vesicle.id")) vesicle = relationship("Vesicle", back_populates="positions") membrane_point_id = Column(Integer, ForeignKey("membrane_point.id")) membrane_point = relationship("MembranePoint") distance = Column(DECIMAL(6,4)) def __init__(self, vesicle, x, y, z, t): self.vesicle = vesicle self.x = x self.y = y self.z = z self.t = t
UTF-8
Python
false
false
3,608
py
24
Models.py
21
0.646341
0.640244
0
123
28.317073
76
Prorok1015/Summary
9,131,100,475,899
00dfc66e2341af153ea28d0c28607ad2bd024fb2
99ab6f0e9efcd67be68125f04f4229c0f5b698be
/script/PageAlgoritm.py
da8014e6cc6f47c2c9f3d475f90d17ebd3e91355
[]
no_license
https://github.com/Prorok1015/Summary
516c7c0d55b9cd4a2c4de4f5dc1d98aa794f9d3c
51ac376f5aa7f8de545a648e60c5be3bf2cb0c39
refs/heads/master
2022-11-07T06:57:56.166778
2020-06-22T12:20:50
2020-06-22T12:20:50
251,022,376
0
0
null
null
null
null
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null
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from wiki.models import settingUser, Page, PageStatmant, randomUnicalPage class Algoritm(): hour = 0 def do(self): self.hour += 1 settings = settingUser.objects.all() for setting in settings: if settingUser.One_hour == setting.Time_to_new_page: PageStatmant.objects.create(User = setting.User, Pages = randomUnicalPage(User=setting.User)) if settingUser.Two_hour == setting.Time_to_new_page: if self.hour%2 == 0: PageStatmant.objects.create(User = setting.User, Pages = randomUnicalPage(User=setting.User)) if settingUser.Six_hour == setting.Time_to_new_page: if self.hour%6 == 0: PageStatmant.objects.create(User = setting.User, Pages = randomUnicalPage(User=setting.User)) if settingUser.One_day == setting.Time_to_new_page: if self.hour == 24: PageStatmant.objects.create(User = setting.User, Pages = randomUnicalPage(User=setting.User)) if self.hour == 24: self.hour = 0
UTF-8
Python
false
false
1,146
py
31
PageAlgoritm.py
18
0.582897
0.573298
0
29
38.310345
113
QCAPI-DRIP/DRIP
15,238,544,011,700
e39729ad81dc1edc71e74bd4051bdb3dcafb0577
5836cc43cd4ee1bcf22e168eba6a7539d0876b3b
/drip_parser/src/rpc_server.py
eb44724b1f77e7753bba605fab21932191fbe488
[ "Apache-2.0" ]
permissive
https://github.com/QCAPI-DRIP/DRIP
d2ce1816a6b0aeda0cac44d7763cadf0c5999941
57a8fd69327f38805597a3c040938206b9728048
refs/heads/master
2020-04-06T14:46:01.628824
2018-11-14T13:30:41
2018-11-14T13:30:41
157,553,634
0
0
Apache-2.0
true
2018-11-14T13:34:08
2018-11-14T13:34:08
2018-11-14T13:33:53
2018-11-14T13:30:42
134,680
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# To change this license header, choose License Headers in Project Properties. # To change this template file, choose Tools | Templates # and open the template in the editor. import os import os.path import pika import sys import tempfile import time import json import yaml from transformer.docker_compose_transformer import * from os.path import expanduser def init_chanel(args): if len(args) > 1: rabbitmq_host = args[1] queue_name = args[2] #tosca_2_docker_compose_queue else: rabbitmq_host = '127.0.0.1' connection = pika.BlockingConnection(pika.ConnectionParameters(host=rabbitmq_host)) channel = connection.channel() channel.queue_declare(queue=queue_name) return channel def start(channel): channel.basic_qos(prefetch_count=1) channel.basic_consume(on_request, queue=queue_name) print(" [x] Awaiting RPC requests") channel.start_consuming() def on_request(ch, method, props, body): response = handle_delivery(body) ch.basic_publish(exchange='', routing_key=props.reply_to, properties=pika.BasicProperties(correlation_id=\ props.correlation_id), body=str(response)) ch.basic_ack(delivery_tag=method.delivery_tag) def handle_delivery(message): parsed_json_message = json.loads(message) params = parsed_json_message["parameters"] param = params[0] value = yaml.load(param['value']) tosca_file_name = param["name"] current_milli_time = lambda: int(round(time.time() * 1000)) try: tosca_file_path = tempfile.gettempdir() + "/transformer_files/" + str(current_milli_time()) + "/" except NameError: import sys tosca_file_path = os.path.dirname(os.path.abspath(sys.argv[0])) + "/transformer_files/" + str(current_milli_time()) + "/" if not os.path.exists(tosca_file_path): os.makedirs(tosca_file_path) with open(tosca_file_path + "/" + tosca_file_name + ".yml", 'w') as outfile: outfile.write(str(value)) if queue_name == "tosca_2_docker_compose_queue": transformer = DockerComposeTransformer(tosca_file_path + "/" + tosca_file_name + ".yml"); compose = transformer.getnerate_compose('3.3') response = {} current_milli_time = lambda: int(round(time.time() * 1000)) response["creationDate"] = current_milli_time() response["parameters"] = [] parameter = {} parameter['value'] = str(yaml.dump(compose)) parameter['name'] = 'docker-compose.yml' parameter['encoding'] = 'UTF-8' response["parameters"].append(parameter) print ("Output message: %s" % json.dumps(response)) return response def test_local(): home = expanduser("~") transformer = DockerComposeTransformer(home+"/Downloads/tosca.yml") vresion = '2'; compose = transformer.getnerate_compose(vresion) print yaml.dump(compose) with open(home+'/Downloads/docker-compose.yml', 'w') as outfile: yaml.dump(compose, outfile, default_flow_style=False) # response = {} # current_milli_time = lambda: int(round(time.time() * 1000)) # response["creationDate"] = current_milli_time() # response["parameters"] = [] # # parameter = {} # parameter['value'] = str(yaml.dump(compose)) # parameter['name'] = 'docker-compose.yml' # parameter['encoding'] = 'UTF-8' # response["parameters"].append(parameter) # print response if __name__ == "__main__": if(sys.argv[1] == "test_local"): test_local() else: print sys.argv channel = init_chanel(sys.argv) global queue_name queue_name = sys.argv[2] start(channel) # try: ## for node in tosca.nodetemplates: ## print "Name %s Type: %s " %(node.name,node.type) ## ## for input in tosca.inputs: ## print input.name # ## for node in tosca.nodetemplates: ## for relationship, trgt in node.relationships.items(): ## rel_template = trgt.get_relationship_template() ## for rel in rel_template: ## print "source %s Relationship: %s target: %s" %(rel.source.type,rel.type,rel.target.type) ## print dir(rel) # response = {} # current_milli_time = lambda: int(round(time.time() * 1000)) # response["creationDate"] = current_milli_time() # response["parameters"] = [] # vm_nodes = [] # # for node in tosca.nodetemplates: # if not node.relationships.items() and 'docker' in node.type.lower(): # print "1Adding: %s , %s" %(node.name,node.type) # vm_nodes.append(node) ## else: # for relationship, trgt in node.relationships.items(): # if relationship.type == EntityType.HOSTEDON: # rel_template = trgt.get_relationship_template() # for rel in rel_template: # print "2Adding: %s , %s" %(rel.target.name,rel.target.type) ## print "Name: %s Type: %s " %(node.name, node.type) # vm_nodes.append(rel.target) # # ## if not compute_nodes: ## for node in tosca.nodetemplates: ### print dir(node) ## print "Name: %s Type: %s props: %s"%(node.name,node.type,node.get_properties().keys()) # # for vm in vm_nodes: # result = {} # parameter = {} # result['name'] = vm.name # result['size'] = 'Medium' # if 'dockers' in vm.get_properties(): # result['docker'] = vm.get_properties()['dockers'].value # elif 'artifacts' in vm.templates[next(iter(vm.templates))]: # artifacts = vm.templates[next(iter(vm.templates))]['artifacts'] # result['docker'] = artifacts['docker_image']['file'] ## print "1st Key: %s" %next(iter(vm.templates)) ## print vm.templates[next(iter(vm.templates))] # ## print dir(compute_node.get_properties()['dockers'] ) ## print "dockers. Name: %s Type: %s Value: %s" % (compute_node.get_properties()['dockers'].name, compute_node.get_properties()['dockers'].type, compute_node.get_properties()['dockers'].value ) # parameter['value'] = str(json.dumps(result)) # parameter['attributes'] = 'null' # parameter["url"] = "null" # parameter["encoding"] = "UTF-8" # response["parameters"].append(parameter) ## print "Name: %s Type: %s properties: %s" %(vm.name,vm.type,vm.get_properties().keys()) ## # print ("Output message: %s" % json.dumps(response)) # # except AttributeError as e: # z = e # print z
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7,015
py
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rpc_server.py
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0.571205
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jfangwpi/Interactive_planning_and_sensing
9,294,309,255,955
729484341a57bc2f5da26f57d3b33f04c3363824
881067724ddcf277c21854f647eaa56054944e15
/src/lcmtypes/python/graph_data/map_data.py
03d8d3f576c3f61116955b7b8dfafda67634be9c
[ "MIT" ]
permissive
https://github.com/jfangwpi/Interactive_planning_and_sensing
004d58ccdcaa1178e24a1186119e862e86afbf3f
00042c51c2fdc020b7b1c184286cf2b513ed9096
refs/heads/master
2023-02-13T03:13:46.496128
2020-05-29T18:24:49
2020-05-29T18:24:49
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"""LCM type definitions This file automatically generated by lcm. DO NOT MODIFY BY HAND!!!! """ try: import cStringIO.StringIO as BytesIO except ImportError: from io import BytesIO import struct import graph_data.vertex_data class map_data(object): __slots__ = ["num_v_", "vertex_"] __typenames__ = ["int64_t", "graph_data.vertex_data"] __dimensions__ = [None, ["num_v_"]] def __init__(self): self.num_v_ = 0 self.vertex_ = [] def encode(self): buf = BytesIO() buf.write(map_data._get_packed_fingerprint()) self._encode_one(buf) return buf.getvalue() def _encode_one(self, buf): buf.write(struct.pack(">q", self.num_v_)) for i0 in range(self.num_v_): assert self.vertex_[i0]._get_packed_fingerprint() == graph_data.vertex_data._get_packed_fingerprint() self.vertex_[i0]._encode_one(buf) def decode(data): if hasattr(data, 'read'): buf = data else: buf = BytesIO(data) if buf.read(8) != map_data._get_packed_fingerprint(): raise ValueError("Decode error") return map_data._decode_one(buf) decode = staticmethod(decode) def _decode_one(buf): self = map_data() self.num_v_ = struct.unpack(">q", buf.read(8))[0] self.vertex_ = [] for i0 in range(self.num_v_): self.vertex_.append(graph_data.vertex_data._decode_one(buf)) return self _decode_one = staticmethod(_decode_one) _hash = None def _get_hash_recursive(parents): if map_data in parents: return 0 newparents = parents + [map_data] tmphash = (0x1b4d686d48fd87f0+ graph_data.vertex_data._get_hash_recursive(newparents)) & 0xffffffffffffffff tmphash = (((tmphash<<1)&0xffffffffffffffff) + (tmphash>>63)) & 0xffffffffffffffff return tmphash _get_hash_recursive = staticmethod(_get_hash_recursive) _packed_fingerprint = None def _get_packed_fingerprint(): if map_data._packed_fingerprint is None: map_data._packed_fingerprint = struct.pack(">Q", map_data._get_hash_recursive([])) return map_data._packed_fingerprint _get_packed_fingerprint = staticmethod(_get_packed_fingerprint)
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Python
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py
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map_data.py
109
0.609436
0.597204
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pratik-iiitkalyani/Python
4,398,046,547,850
985bfa7d6dec4eddc1595d3bb9f22e74dbf87b71
a4653fb6c5a7a9e6db0457480e9e860c5304b2b8
/OOPs/operator_overloading_polymorphism.py
896d16f3dad5ca64e1cdc90af473147c7c904b36
[]
no_license
https://github.com/pratik-iiitkalyani/Python
c315ca1f3a2446ccb871b74026edae97daec3773
082ae6d833f151054567d737de543898ebfe1d87
refs/heads/master
2020-08-07T05:59:21.930089
2020-01-04T17:05:27
2020-01-04T17:05:27
213,324,642
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# operator overloading # polymorphism - many forms # method overriding is also a example of polymorphism class Phone: def __init__(self, brand, model, price): self.brand = brand self.model = model self.price = price def phone_name(self): return f"{self.brand} {self.model}" def __add__(self, other): # overload + operator in our class return self.price + other.price def __mul__(self, other): # overload * operator in our class return self.price * other.price class Smartphone(Phone): def __init__(self, brand, model, price, camera): super().__init__(brand, model, price) self.camera = camera def phone_name(self): return f"{self.brand} {self.model} and price is {self.price}" # polymorphism - + having two different form(one is adding int and another is adding string) # 2 + 3 = 5 # 'pratik' + ' kumar' = 'pratik kumar' # l = [1,2,3] # s = 'pratik # len(l), len(s) different form of len function my_phone = Phone('Nokia', '1100', 1000) my_phone2 = Phone('Nokia', '1600', 1200) my_smartphone = Smartphone('oneplus', '5t', 33000, '26 MP') # polymorphism because here we use two diffirent form of phone_name method print(my_smartphone.phone_name()) print(my_phone.phone_name()) # overload +, * operator in our class print(my_phone + my_phone2) print(my_phone * my_phone2)
UTF-8
Python
false
false
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py
172
operator_overloading_polymorphism.py
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PreciadoAlex/PreciadoAlex.github.io
7,876,970,057,386
73a4a90c6ee8d45111ea1436135712c640ef4365
3da1fbc9e7b826bbe7d4b92574b882896786d5b2
/Projects/Python_start/Preciado_StepOneWhile.py
e540603e9fc37ae87be1b0b7b740b014c934e04f
[]
no_license
https://github.com/PreciadoAlex/PreciadoAlex.github.io
0b451dc7f082b49f909b9d90cdac43cc4ddd6892
fc2163d4534de3fa7d73397377a7afd6ef07b225
refs/heads/master
2021-09-24T08:45:04.761435
2018-10-06T08:11:15
2018-10-06T08:11:15
110,735,773
0
0
null
null
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acc = 1 while acc < 11: print (acc) acc = acc + 1
UTF-8
Python
false
false
64
py
23
Preciado_StepOneWhile.py
16
0.453125
0.390625
0
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stompingBubble/PythonBootcamp
16,655,883,190,545
5c9917d3961d6dc7d74119f9705e8f632946b1c3
a2735476958c0315e43d3b6ffe8b22701b9a469e
/TicTacToe1.py
89a29c7e48c8c560c9ee150787030f8a256ef96d
[]
no_license
https://github.com/stompingBubble/PythonBootcamp
ad67fd32fcf01ccaabd0eb0d183ef1496ff22423
fcb51b6ecda0f0812d46ba3dd0b1d15660e334e7
refs/heads/master
2021-07-17T22:40:41.887419
2017-10-24T17:37:39
2017-10-24T17:37:39
null
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# -*- coding: utf-8 -*- """ Spyder Editor """ # In[1]: import os # global variables board = [" "] * 10 game_state = True position = 0 player = {"Player one": [True, "X"], "Player two": [False, "O"]} number_of_tries = 0 invalid_input = True not_empty_position = True # In[2]: def clear_game(): global board, game_state, position, number_of_tries, invalid_input board = [" "] * 10 game_state = True position = 0 number_of_tries = 0 invalid_input = True # In[3]: def print_board(): global board print("|" + board[0] + "|" + board[1] + "|" + board[2] + "|") print("|" + board[3] + "|" + board[4] + "|" + board[5] + "|") print("|" + board[6] + "|" + board[7] + "|" + board[8] + "|") # In[] def print_currently_playing(): global player for key in player.items(): if key[1][0]: print("Playing right now: ", key[0]) # In[] def check_input(): global position, invalid_input if position > 10 or position < 0: print("Invalid position, input number between 1-9") invalid_input = True else: if check_if_position_is_empty(): print("Position is not empty, try again:") invalid_input = True else: invalid_input = False return invalid_input # In[25]: def take_input(): global position, invalid_input, number_of_tries, player invalid_input = True while (invalid_input): print_currently_playing() position = int(input("Input player position: ")) check_input() # In[9]: def place_player(): global board, position, player if player["Player one"][0]: board[position - 1] = player["Player one"][1] elif player["Player two"][0]: board[position - 1] = player["Player two"][1] # In[10]: def switch_player(): global player if player["Player one"][0]: player["Player one"][0] = False player["Player two"][0] = True else: player["Player one"][0] = True player["Player two"][0] = False # In[11]: def ask_to_play_again(): global game_state ans = input("Want to play again (y/n)? ") if ans == "Y" or ans == "y": game_state = True clear_game() else: game_state = False return game_state # In[12]: def check_if_position_is_empty(): global board, position, not_empty_position not_empty_position = True if board[position - 1] == " ": not_empty_position = False else: not_empty_position = True return not_empty_position # In[16]: def check_if_winner(): global board, player for key in player.items(): if (board[0] == key[1][1] and board[1] == key[1][1] and board[2] == key[1][1]) or ( board[3] == key[1][1] and board[4] == key[1][1] and board[5] == key[1][1]) or ( board[6] == key[1][1] and board[7] == key[1][1] and board[8] == key[1][1]) or ( board[0] == key[1][1] and board[3] == key[1][1] and board[6] == key[1][1]) or ( board[1] == key[1][1] and board[4] == key[1][1] and board[7] == key[1][1]) or ( board[2] == key[1][1] and board[5] == key[1][1] and board[8] == key[1][1]) or ( board[0] == key[1][1] and board[4] == key[1][1] and board[8] == key[1][1]) or ( board[2] == key[1][1] and board[4] == key[1][1] and board[6] == key[1][1]): clear() print_board() print("***", key[0], " is the winner***") ask_to_play_again() # In[] clear = lambda: os.system('cls') # In[ ]: clear_game() while (game_state): print_board() take_input() place_player() check_if_winner() switch_player() number_of_tries += 1 if number_of_tries == 9: ask_to_play_again() clear()
UTF-8
Python
false
false
3,869
py
12
TicTacToe1.py
11
0.522874
0.490049
0
156
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99
gyang274/leetcode
1,537,598,340,098
a0a33e104deed965366b17861cbb5d1079ae3a15
242f1dafae18d3c597b51067e2a8622c600d6df2
/src/1500-1599/1545.kth.bit.in.nth.binary.str.py
640b92fde1db7a7e99d812700ada70b960178614
[]
no_license
https://github.com/gyang274/leetcode
a873adaa083270eb05ddcdd3db225025533e0dfe
6043134736452a6f4704b62857d0aed2e9571164
refs/heads/master
2021-08-07T15:15:01.885679
2020-12-22T20:57:19
2020-12-22T20:57:19
233,179,192
1
0
null
null
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null
null
null
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class Solution: def findKthBit(self, n: int, k: int) -> str: f, k = 0, k while n > 1: m = 1 << (n - 1) if k == m: return str(1 ^ f) elif k > m: k = (1 << n) - k f = f ^ 1 n -= 1 return str(0 ^ f) if __name__ == '__main__': solver = Solution() cases = [ (1, 0), (2, 0), (2, 3), ] rslts = [solver.findKthBit(n, k) for n, k in cases] for cs, rs in zip(cases, rslts): print(f"case: {cs} | solution: {rs}")
UTF-8
Python
false
false
491
py
1,461
1545.kth.bit.in.nth.binary.str.py
1,456
0.429735
0.399185
0
23
20.347826
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ascorblack/library
14,860,586,850,374
36bdce419df8a22dad050aadd34ad62939d5e20e
1d3d3a645662a40674ef3748882f3bccc464001e
/gui.py
7bb6146ad32123915223a7b0163ca52b2658247d
[]
no_license
https://github.com/ascorblack/library
88e280b5a8d20f39c73038a82874fe61a9417599
46616bb730f422b25d7454917d0dfc6a43f9dbb6
refs/heads/main
2023-07-28T15:15:08.538299
2021-09-08T06:54:03
2021-09-08T06:54:03
null
0
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import eel from eel import expose import os import json import numpy as np from PIL import Image from io import BytesIO import base64 from mainElastic import Book, show_warn, get_all_categories from recommendation_ai.ai_rec import get_similarity, get_cosine_book from sys import exit db = Book() def add_stat(name_stat, item): with open("stats_log.json", "r", encoding="utf8") as f: data = json.load(f) with open("stats_log.json", "w", encoding="utf8") as f: if type(data[name_stat]) == list: data[name_stat].append(item) elif type(data[name_stat]) == dict: data[name_stat][item[0]] = data[name_stat].get(item[0], []) if name_stat == "viewed": try: check_exist = np.where(np.array(data[name_stat][item[0]]) == item[1])[0][0] data[name_stat][item[0]].pop(check_exist) except: pass data[name_stat][item[0]].append(item[1]) json.dump(data, f, ensure_ascii=False, indent=4) @expose def del_stat(name_stat, item): data = json.load(open("stats_log.json", "r", encoding="utf8")) with open("stats_log.json", "w", encoding="utf8") as f: if type(data[name_stat]) == list: data[name_stat].pop(np.where(np.array(data[name_stat]) == item)[0][0]) elif type(data[name_stat]) == dict: data[name_stat][item[0]] = data[name_stat].get(item[0], []) data[name_stat][item[0]].pop(np.where(np.array(data[name_stat][item[0]]) == item[1])[0][0]) json.dump(data, f, ensure_ascii=False, indent=4) @expose def get_stat(what="all"): data = json.load(open("stats_log.json", "r", encoding="utf8")) if what == "all": return data else: return data[what] @expose def check_favorite(author, title): data = get_stat("favorite") try: check = np.where(np.array(data) == [author, title])[0][0] return True except: return False @expose def stat_add(name_stat, item): add_stat(name_stat, item) @expose def get_viewed_books(): with open("stats_log.json", "r", encoding="utf8") as f: data = json.load(f) books = data["viewed"]["All"] clear_all = [] for x in books: if not x in clear_all: clear_all.append(x) return clear_all[-5:][::-1] @expose def all_categories(): return get_all_categories() @expose def random_book_category(category): return db.get_random_book_category(category) @expose def search_book(query): books_author = db.author_books(query) books_title = db.find_book(query) if books_author != [] or books_title != []: add_stat("search", query) return [books_author, books_title] @expose def info_book(author, title): return db.info_book(author, title) @expose def get_book_id(id_): return db.get_book_id(id_) @expose def get_text(author, title): return db.get_book(author, title) @expose def open_pdf(author, title, category): if not os.path.isfile(f"web/books_pdf/{author} [[]] {title.replace('?', '')}.pdf"): open(f"web/books_pdf/{author} [[]] {title.replace('?', '')}.pdf", "wb").write( db.get_pdf_bytes_book(author, title) ) add_stat("viewed", (category, (author, title))) add_stat("viewed", ("All", (author, title))) cosine_stat = get_stat("books_viewed_cosine") if len(cosine_stat) >= 11: mean_cosines = np.mean(cosine_stat) set_stat("books_viewed_cosine", [mean_cosines]) try: add_stat("books_viewed_cosine", get_cosine_book(author, title)) except: print("Книги нет в векторизированных") return os.path.abspath(f"web/books_pdf/{author} [[]] {title.replace('?', '')}.pdf") @expose def add_book(author, title, text, category, cover=None): text = text.encode("utf-8").decode("utf-8") try: if cover != None: image = Image.open(BytesIO(base64.b64decode(cover.replace("data:image/jpeg;base64,", "")))) image.thumbnail((190, 288), Image.ANTIALIAS) image = db.get_cover_bytes(image) else: image = None res = db.add_book(author=author, title=title, category=category, text=text, cover_book=image) if not np.where(np.array(get_stat("user_books")) == [author, title])[0] and not res: add_stat("user_books", [author, title]) return res except: import traceback print(traceback.format_exc()) return "ERROR ADD BOOK" @expose def del_book(author, title, category): try: del_stat("user_books", [author, title]) del_stat("viewed", (category, (author, title))) del_stat("viewed", ("All", (author, title))) if check_favorite(author, title): del_stat("favorite", (author, title)) db.del_book(author, title) return True except: import traceback print(traceback.format_exc()) return False @expose def books_category_paginated(category, page): return db.get_category_book(category, page, 25) @expose def get_count_category(category): return db.count_category(category) @expose def get_recommendation(author, title, count=5): result = [] try: for author, title in get_similarity(author, title, count): result.append(info_book(author, title)) return result except: return None @expose def average_cosine_rec(count=10): books_cosine = get_stat("books_viewed_cosine") if len(books_cosine) < 1: return [] result = [] for author, title in get_similarity(cosine=np.mean(books_cosine), count=count): result.append(info_book(author, title)) return result @expose def set_stat(stat_name, new_data): data = get_stat("all") with open("stats_log.json", "w", encoding="utf8") as f: if type(stat_name) == str: data[stat_name] = new_data elif type(stat_name) == list: way_str = "data" for stat in stat_name: way_str += f"['{stat}']" way_str += " = new_data" exec(way_str, globals(), locals()) json.dump(data, f, ensure_ascii=False, indent=4) @expose def fast_search(query): search_result = db.similarity_search(query) return {"authors": search_result[0][:5], "titles": search_result[1][:5]} @expose def get_user_book_info(): books = list(set([(x[0], x[1]) for x in get_stat("user_books")])) books_info = [] for book in books: books_info.append(db.info_book(book[0], book[1])) return books_info def create_stats(): if not os.path.isfile("stats_log.json"): with open("stats_log.json", "w", encoding="utf8") as f: data = { "viewed": {"All": []}, "favorite": [], "search": [], "books_viewed_cosine": [], "user_books": [] } json.dump(data, f, ensure_ascii=False, indent=4) try: check = json.load(open("stats_log.json", "r", encoding="utf8")) except json.decoder.JSONDecodeError: with open("stats_log.json", "w", encoding="utf8") as f: data = { "viewed": {"All": []}, "favorite": [], "search": [], "books_viewed_cosine": [], "user_books": [] } json.dump(data, f, ensure_ascii=False, indent=4) create_stats() def clear_books(): if not os.path.isdir("web/books_pdf"): os.mkdir("web/books_pdf") favorites = [f"{book[0]} [[]] {book[1]}.pdf".replace('?', '') for book in get_stat("favorite")] for book in os.listdir("web/books_pdf/"): if book not in favorites: os.remove(f"web/books_pdf/{book}") clear_books() options = { 'mode': "chrome", 'host': "localhost", 'port': 7521, 'size': (1600, 1000) } if __name__ == '__main__': eel.init('web') eel.browsers.set_path("chrome", os.path.abspath("chrome-win\\chrome.exe")) eel.start("index.html", options=options, suppress_error=True, cmdline_args=['--no-experiments', '--incognito'], disable_cache=True, close_callback=None)
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fzhcary/TCEF_Python_2020
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6bd7c67c30fee5165412d87413c7bdb69ae3aca5
cf0dfc31213c0a8cd0c6c0b5837fff07c2501991
/selection_sort.py
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[]
no_license
https://github.com/fzhcary/TCEF_Python_2020
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2023-02-27T16:25:28.340662
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# Selection Sort def selection_sort(nums): size = len(nums) for j in range(1, size): # on the last run, j: size -1 max_number = nums[size - j] max_i = size - j for i in range(0, size - j): if nums[i] > max_number: max_i = i max_number = nums[i] # swap max_i and size-1 nums[max_i], nums[size - j] = nums[size - j], nums[max_i] return nums if __name__ == "__main__": import random print(selection_sort([])) print(selection_sort([1])) print(selection_sort([26, 54, 93, 17, 77, 31, 44, 55, 20])) n = 20 a = list(range(n)) random.shuffle(a) print(a) assert(selection_sort(a) == list(range(n)))
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saif409/Construction_management_system
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debd80ab07d1f495f9972aa823ffdb6ab8123853
900780eedf00e1fbeab43d229e0b83acf76d668d
/sadmin/urls.py
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[]
no_license
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2021-05-01T15:04:30
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from django.urls import path from.import views urlpatterns = [ path('', views.user_login, name="login"), path('home/', views.home, name="home"), path('user_logout/', views.user_logout, name="user_logout") ]
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DTUWindEnergy/PyWake
16,166,256,903,451
5d734a02cc2cf3826cb028f498c4e678687671e7
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/py_wake/examples/data/ParqueFicticio/_parque_ficticio.py
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[ "MIT" ]
permissive
https://github.com/DTUWindEnergy/PyWake
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refs/heads/master
2023-08-20T09:00:30.946594
2023-08-10T12:07:55
2023-08-10T12:07:55
164,115,313
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2022-11-07T08:47:06
2019-01-04T14:10:20
2022-11-04T02:27:01
2022-11-07T07:30:13
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from py_wake.site.wasp_grid_site import WaspGridSite, load_wasp_grd from py_wake.examples.data.ParqueFicticio import ParqueFicticio_path from py_wake import np from py_wake.site.distance import TerrainFollowingDistance """ min x: 262878 min y: 6504214 max x: 265078 max y: 6507414.0 Resolution: 100 columns: 23 rows: 33 30 and 200 m """ class ParqueFicticioSite(WaspGridSite): def __init__(self, distance=TerrainFollowingDistance(distance_resolution=2000), mode='valid'): ds = load_wasp_grd(ParqueFicticio_path, speedup_using_pickle=True) WaspGridSite.__init__(self, ds, distance, mode) self.initial_position = np.array([ [263655.0, 6506601.0], [263891.1, 6506394.0], [264022.2, 6506124.0], [264058.9, 6505891.0], [264095.6, 6505585.0], [264022.2, 6505365.0], [264022.2, 6505145.0], [263936.5, 6504802.0], ])
UTF-8
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_parque_ficticio.py
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0x913/python-practice-projects
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/python practice projects/Exceptions & Files/finally.py
979cc498b947bf7ccd5dae1c388638015de2b35b
[]
no_license
https://github.com/0x913/python-practice-projects
42af39ad6eed5ef82ff18a66523beecb4739805f
d3aea4a2b2bba4e1dabd56633be47e19c13ede16
refs/heads/master
2021-02-05T20:33:27.197069
2020-02-28T18:41:44
2020-02-28T18:41:44
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try: print(1) print(10 / 0) except ZeroDivisionError: print(unknown_var) finally: print("This is executed last")
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finally.py
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paris3200/AdventOfCode
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0a70a9873bf09d56fd72faf0a00174660aaf07e6
/code/2021/10/tests.py
f92b17b003a0cd23858007f465a5bc809ec74e4c
[]
no_license
https://github.com/paris3200/AdventOfCode
40ef0828e70ed6736212a3cfe0574c6a26fe94bd
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refs/heads/master
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2022-12-12T11:52:14
2022-12-12T11:52:14
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import pytest from aoc_10 import is_valid, part_one, complete_lines, score_autocomplete, part_two @pytest.mark.parametrize( ("line", "expected"), ( ("{([(<{}[<>[]}>{[]{[(<()>", "}"), ("[({(<(())[]>[[{[]{<()<>>", True), ), ) def test_is_valid(line, expected) -> None: assert is_valid(line) == expected def test_part_one() -> None: assert part_one("data/test_input") == 26397 @pytest.mark.parametrize( ("line", "expected"), ( ("[({(<(())[]>[[{[]{<()<>>", "}}]])})]"), ("[(()[<>])]({[<{<<[]>>(", ")}>]})"), ), ) def test_complete_lines(line, expected) -> None: assert complete_lines(line) == expected @pytest.mark.parametrize( ("completion", "expected"), ( ("}}]])})]", 288957), (")}>]})", 5566), ), ) def test_complete_lines(completion, expected) -> None: assert score_autocomplete(completion) == expected def test_part_two() -> None: assert part_two("data/test_input") == 288957
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py
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lim0606/likelion
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87bc40f3b6dcd4dd88aa5af262374569cfb0f34b
aac3b8e8c01d93f71bb1bab05dbc9588ba3b765a
/w5_flaskr_upgrade/apps/flaskr_mvc.py
6615cac11f724a85ba80389deef813be37bfe462
[]
no_license
https://github.com/lim0606/likelion
4f4a505e8e1cf1ce92e0c091d188f67fda5c3e26
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refs/heads/master
2021-01-22T04:43:56.803627
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# -*- coding: utf-8 -*- # all the imports from flask import request, redirect, url_for,\ render_template from apps import app from database import Database from datetime import datetime dataStorage = Database() @app.route('/', methods=['GET', 'POST']) def show_entries(): entries = dataStorage.out() return render_template('show_entries.html', entries=entries) @app.route('/add', methods=['POST']) def add_entry(): entry = {} entry['id'] = dataStorage.newid() entry['title'] = request.form['title'] entry['contents'] = request.form['contents'] entry['datetime'] = datetime.now() entry['likecount'] = 0 dataStorage.put(entry) return redirect(url_for('show_entries')) @app.route('/del/<key>', methods=['GET']) def del_entry(key): dataStorage.delete(key) return redirect(url_for('show_entries')) @app.route('/like/<key>', methods=['GET']) def like_entry(key): entry = dataStorage.select(key) entry['likecount'] += 1 dataStorage.update(key, entry) return redirect(url_for('show_entries')) @app.route('/dislike/<key>', methods=['GET']) def dislike_entry(key): entry = dataStorage.select(key) if entry['likecount'] > 0: entry['likecount'] -= 1 dataStorage.update(key, entry) return redirect(url_for('show_entries')) @app.route('/edit/<key>', methods=['GET']) def edit_entry(key): entry = dataStorage.select(key) return render_template('edit_entry.html', entry=entry) @app.route('/apply_edited/<key>', methods=['POST']) def apply_edited_entry(key): entry = dataStorage.select(key) entry['id'] = int(key) entry['title'] = request.form['title'] entry['contents'] = request.form['contents'] entry['datetime'] = datetime.now() entry['likecount'] = entry['likecount'] dataStorage.update(key, entry) return redirect(url_for('show_entries')) from operator import itemgetter @app.route('/top_entries') def top_entries(): entries = dataStorage.out() # get all entries entries = sorted(entries, key=itemgetter('likecount'), reverse=True) # the same with the above statement # entries = sorted(entries, key=lambda item: item['likecount'], reverse=True) # if len(entries) > 3: # return render_template('top_entries.html', entries=entries[1:3]) # else: # return render_template('top_entries.html', entries=entries) return render_template('top_entries.html', entries=entries)
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flaskr_mvc.py
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ElTapia/computacion-grafica
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83c523604f4028d288a3769e92be85f12c76c032
77e31a5c86c78ce2e4967532417435275dc07b58
/Ejercicios/Ejercicio_3/Version Windows/Ejercicio_3_Windows.py
2555458a754a74e1bb13f2720a1e2275fa5f2fb1
[ "MIT" ]
permissive
https://github.com/ElTapia/computacion-grafica
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refs/heads/main
2023-08-23T14:10:21.792322
2021-11-01T15:42:21
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# coding=utf-8 """Ejercicio 3: Planeta tierra orbitando alrededor del sol y luna alrededor de la tierra Extra: La tierra y la luna también tienen movimiento de rotación. """ import glfw from OpenGL.GL import * import OpenGL.GL.shaders import numpy as np import sys import os.path sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) import planet_shape as ps import easy_shaders_Mac as es import transformations as tr import math __author__ = "Daniel Calderon" __license__ = "MIT" # We will use 32 bits data, so an integer has 4 bytes # 1 byte = 8 bits SIZE_IN_BYTES = 4 # A class to store the application control class Controller: fillPolygon = True # we will use the global controller as communication with the callback function controller = Controller() def on_key(window, key, scancode, action, mods): if action != glfw.PRESS: return global controller if key == glfw.KEY_SPACE: controller.fillPolygon = not controller.fillPolygon elif key == glfw.KEY_ESCAPE: glfw.set_window_should_close(window, True) else: print('Unknown key') if __name__ == "__main__": # Initialize glfw if not glfw.init(): glfw.set_window_should_close(window, True) width = 600 height = 600 window = glfw.create_window(width, height, "Ejercicio 3: Movimiento órbitas Tierra y luna", None, None) if not window: glfw.terminate() glfw.set_window_should_close(window, True) glfw.make_context_current(window) # Connecting the callback function 'on_key' to handle keyboard events glfw.set_key_callback(window, on_key) # Creating our shader program and telling OpenGL to use it pipeline = es.SimpleTransformShaderProgram() glUseProgram(pipeline.shaderProgram) # Setting up the clear screen color glClearColor(0.15, 0.15, 0.15, 1.0) # Creating shapes on GPU memory # * Crea contorno de la tierra contourTierra = ps.createContorno(100) gpuContourTierra = es.GPUShape().initBuffers() gpuContourTierra.fillBuffers(contourTierra.vertices, contourTierra.indices, GL_STATIC_DRAW) # * Crea shape de la tierra shapeTierra = ps.createPlanet(100, [0, 0, 1]) gpuTierra = es.GPUShape().initBuffers() gpuTierra.fillBuffers(shapeTierra.vertices, shapeTierra.indices, GL_STATIC_DRAW) # * Crea trayectoria de la tierra trayectoriaTierra = ps.createTrayectoria(200) gpuTrayectoriaTierra = es.GPUShape().initBuffers() gpuTrayectoriaTierra.fillBuffers(trayectoriaTierra.vertices, trayectoriaTierra.indices, GL_STATIC_DRAW) # * Crea contorno del sol contourSol = ps.createContorno(100) gpuContourSol = es.GPUShape().initBuffers() gpuContourSol.fillBuffers(contourSol.vertices, contourSol.indices, GL_STATIC_DRAW) # * Crea shape del sol shapeSol = ps.createPlanet(100, [1, 1, 0]) gpuSol = es.GPUShape().initBuffers() gpuSol.fillBuffers(shapeSol.vertices, shapeSol.indices, GL_STATIC_DRAW) # * Crea trayectoria de la luna trayectoriaLuna = ps.createTrayectoria(100) gpuTrayectoriaLuna = es.GPUShape().initBuffers() gpuTrayectoriaLuna.fillBuffers(trayectoriaLuna.vertices, trayectoriaLuna.indices, GL_STATIC_DRAW) # * Crea shape de la luna shapeLuna = ps.createPlanet(100, [0.5, 0.5, 0.5]) gpuLuna = es.GPUShape().initBuffers() gpuLuna.fillBuffers(shapeLuna.vertices, shapeLuna.indices, GL_STATIC_DRAW) glBindVertexArray(gpuSol.vao) # Creating our shader program and telling OpenGL to use it pipeline = es.SimpleTransformShaderProgram() glUseProgram(pipeline.shaderProgram) pipeline.setupVAO(gpuContourTierra) pipeline.setupVAO(gpuTierra) pipeline.setupVAO(gpuTrayectoriaTierra) pipeline.setupVAO(gpuContourSol) pipeline.setupVAO(gpuSol) pipeline.setupVAO(gpuTrayectoriaLuna) pipeline.setupVAO(gpuLuna) while not glfw.window_should_close(window): # Using GLFW to check for input events glfw.poll_events() # Filling or not the shapes depending on the controller state if (controller.fillPolygon): glPolygonMode(GL_FRONT_AND_BACK, GL_FILL) else: glPolygonMode(GL_FRONT_AND_BACK, GL_LINE) # Clearing the screen in both, color and depth glClear(GL_COLOR_BUFFER_BIT) # Using the time as the theta parameter theta = glfw.get_time() # * Tamaño trayectoria tierra trayectoriaTierraTransform = tr.matmul([ tr.translate(0, 0, 0), tr.uniformScale(1.4) ]) # updating the transform attribute glUniformMatrix4fv(glGetUniformLocation(pipeline.shaderProgram, "transform"), 1, GL_TRUE, trayectoriaTierraTransform) # drawing function pipeline.drawCall(gpuTrayectoriaTierra, mode=GL_LINES) # * Tamaño contorno tierra contourTierraTransform = tr.matmul([ tr.rotationZ(-theta), tr.translate(math.sin(theta/10)*0.7, math.cos(theta/10)*0.7, 0), tr.uniformScale(0.307) ]) # updating the transform attribute glUniformMatrix4fv(glGetUniformLocation(pipeline.shaderProgram, "transform"), 1, GL_TRUE, contourTierraTransform) # drawing function pipeline.drawCall(gpuContourTierra, mode=GL_TRIANGLES) # * Movimiento tierra tierraTransform = tr.matmul([ tr.rotationZ(-theta), tr.translate(math.sin(theta/10)*0.7, math.cos(theta/10)*0.7, 0), tr.uniformScale(0.3) ]) # updating the transform attribute glUniformMatrix4fv(glGetUniformLocation(pipeline.shaderProgram, "transform"), 1, GL_TRUE, tierraTransform) # drawing function pipeline.drawCall(gpuTierra) # * Tamaño contorno sol contourSolTransform = tr.matmul([ tr.translate(0, 0, 0), tr.uniformScale(0.507) ]) # updating the transform attribute glUniformMatrix4fv(glGetUniformLocation(pipeline.shaderProgram, "transform"), 1, GL_TRUE, contourSolTransform) # drawing function pipeline.drawCall(gpuContourSol, mode=GL_TRIANGLES) # * Posición sol solTransform = tr.matmul([ tr.translate(0, 0, 0), tr.uniformScale(0.5) ]) glUniformMatrix4fv(glGetUniformLocation(pipeline.shaderProgram, "transform"), 1, GL_TRUE, solTransform) pipeline.drawCall(gpuSol) # * Tamaño trayectoria luna trayectoriaLunaTransform = tr.matmul([ #tr.rotationZ(-theta), tr.translate(math.sin(theta*1.1)*0.7, math.cos(theta*1.1)*0.7, 0), tr.uniformScale(0.6) ]) # updating the transform attribute glUniformMatrix4fv(glGetUniformLocation(pipeline.shaderProgram, "transform"), 1, GL_TRUE, trayectoriaLunaTransform) # drawing function pipeline.drawCall(gpuTrayectoriaLuna, mode=GL_LINES) # * Movimiento luna lunaTransform = tr.matmul([ tr.translate(math.sin(theta*1.1)*0.7, math.cos(theta*1.1)*0.7, 0), tr.rotationZ(-theta), tr.translate(math.sin(theta*2)*0.3, math.cos(theta*2)*0.3, 0), tr.uniformScale(0.1) ]) glUniformMatrix4fv(glGetUniformLocation(pipeline.shaderProgram, "transform"), 1, GL_TRUE, lunaTransform) pipeline.drawCall(gpuLuna) # Once the drawing is rendered, buffers are swap so an uncomplete drawing is never seen. glfw.swap_buffers(window) # freeing GPU memory gpuTierra.clear() gpuContourTierra.clear() gpuTrayectoriaTierra.clear() gpuTrayectoriaLuna.clear() gpuSol.clear() gpuContourSol.clear() gpuLuna.clear() glfw.terminate()
UTF-8
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urudaro/data-ue
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/Sorbisterit_powder_for_oral_or_rectal_suspension_SmPC.py
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[]
no_license
https://github.com/urudaro/data-ue
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refs/heads/master
2021-01-22T12:02:16.931087
2013-07-16T14:05:41
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{'_data': [['Common', [['Metabolism', u'hyperkalcemi, hypokalemi, hypomagnesemi'], ['GI', u'illam\xe5ende, kr\xe4kningar']]], ['Uncommon', [['GI', u'f\xf6rstoppning, diarr\xe9, tarmobstruktion, ulceration, kolonnekros som kan ge perforation, anorexi']]], ['Rare', [['GI', u'i sv\xe5ra fall ileus ocklusion (beroende p\xe5 sammanklumpning av pulvret i tarmen), fekal klumpbildning efter rektal administrering till barn, gastrointestinal konkretion efter oral administrering till nyf\xf6dda. Hematochezi har observerats hos prematura barn och nyf\xf6dda med l\xe5g f\xf6delsevikt som f\xe5tt lavemang inneh\xe5llande polystyrensulfonatharts. Vid oral administrering kan patienter f\xe5 sv\xe5rt att sv\xe4lja den ganska stora m\xe4ngden utr\xf6rt pulver. Omfattningen av dessa besv\xe4r \xe4r beroende av individuell disposition, sjukdom, administrering och behandlingstidens l\xe4ngd.']]], ['Very rare', [['Respiratory', u'akut bronkit och/eller bronkopneumoni vid inhalation av kalciumpolystyrensulfonat']]]], '_pages': [4, 4], u'_rank': 5, u'_type': u'LSFU'}
UTF-8
Python
false
false
1,198
py
3,177
Sorbisterit_powder_for_oral_or_rectal_suspension_SmPC.py
3,177
0.679466
0.660267
0.016694
15
78.933333
630
noh-hyeonseong/python3-algorithm-level1
4,037,269,290,431
c2dd1be41120c2c01716a3f9db7a579ff46b99ce
8f5e4e2aa50a629c93ad7be317d7139f7394e699
/행렬의덧셈.py
de18616f213d7beb321d6caf468a217abc79197e
[]
no_license
https://github.com/noh-hyeonseong/python3-algorithm-level1
d0c9b76d539e6cab5c68bb6c5a7ba12e87073640
5aec6c24fb3c3fb2833bdc80e4af7c0bd9e8fddd
refs/heads/master
2023-06-06T02:34:02.882296
2021-06-29T06:16:05
2021-06-29T06:16:05
null
0
0
null
null
null
null
null
null
null
null
null
null
null
null
null
import numpy as np def solution(arr1, arr2): """ 행렬은 numpy 모듈을 활용하면 더 쉽게 풀 수 있음 import numpy as np """ #numpy 사용 코드 A = np.array(arr1) B = np.array(arr2) answer = (A + B).tolist() print(answer) return answer #기존 코드 # answer = [] # for i, j in zip(arr1, arr2): # tempArr = [] # for k, p in zip(i, j): # tempArr.append(k+p) # answer.append(tempArr) # return answer
UTF-8
Python
false
false
507
py
24
행렬의덧셈.py
24
0.512035
0.498906
0
23
18.913043
34
Green-Project/Green
6,768,868,465,423
14579c9cf1a109d063bbb61aa549a955b59c7e7b
82459da507886101871a750241b1b108baccbb9f
/IA/api/config.py
f8cbf33520fe19a799a294258131aa153b32be0e
[]
no_license
https://github.com/Green-Project/Green
e5be745a31a1623eb6336dae3a5aec1a72f90b1c
da491f7278cc3acaf24c7441ae14d0922a266b58
refs/heads/main
2023-06-19T11:06:10.401324
2021-07-04T11:22:23
2021-07-04T11:22:23
317,233,527
2
0
null
false
2020-12-10T17:30:29
2020-11-30T13:32:46
2020-12-10T15:22:17
2020-12-10T17:30:28
2,482
3
0
3
JavaScript
false
false
env = { "SERVER_PORT": 8000, "TOKEN_SECRET": "hsf7ClN471QKJ6DPgreI" }
UTF-8
Python
false
false
77
py
52
config.py
23
0.623377
0.506494
0
4
18.5
42
AdamR77/Palindrom
13,675,175,881,382
61a8a1817c62bf2c138232bf2c48e8814b25073f
358cb092e7c15884f81b7269640f730bfcb69422
/palindrom.py
be2ab1ae954b6070b09416f1a79b4605adca618d
[]
no_license
https://github.com/AdamR77/Palindrom
18ba7ffb48070377e0bba3b7f4d4205a2ca74f0a
5b1c714662385a7a8849690f517b1b144998217a
refs/heads/main
2023-08-23T11:31:49.206317
2021-10-13T20:03:25
2021-10-13T20:03:25
416,882,078
0
0
null
false
2021-10-17T15:56:09
2021-10-13T20:02:33
2021-10-13T20:03:27
2021-10-17T15:56:09
1
0
0
2
Python
false
false
def check_palindrom (string): reversed_string = string[::-1] if string == reversed_string: return True else: return False #spr string = "madam" if check_palindrom(string) == True: print(string," is palnindrom")
UTF-8
Python
false
false
244
py
1
palindrom.py
1
0.631148
0.627049
0
11
20.909091
35
neuracr/privacyAggretationTSPOC
17,806,934,433,482
cd7e723648ea1413b399b313ec8715d357d8df1f
99bf30df817ee022e7e4ac43b26bbac5a58a2a5f
/main.py
496259fe198ae8ea89b4cb560cc3b72e197c4797
[]
no_license
https://github.com/neuracr/privacyAggretationTSPOC
8f6b4dc42f584cfebbdbfff1a90a7dc8642957fb
c878bf4ba89b3011fa2eb701f83768c31064b9e4
refs/heads/master
2021-02-05T21:01:13.269003
2020-09-22T09:38:21
2020-09-22T09:38:21
243,832,133
0
0
null
null
null
null
null
null
null
null
null
null
null
null
null
import logging from poc.aggregator import Aggregator from poc.participant import Participant from poc.ttp import TTPBasic import matplotlib.pyplot as plt big_delta = 2000 # delta eps = 0.5 small_delta = 0.001 n = 120 gamma = 0.5 logger = logging.getLogger(__name__) def experiment_basic(n, t, eps, small_delta, big_delta, gamma): """Simulate an aggregation of n participants at time t.""" # We create the different parties of the experiment aggregator = Aggregator() participants = [Participant(big_delta) for _ in range(n)] # The TTP chooses a g, p, P ttp = TTPBasic() # initialization # The TTP generates the sk for each participant and # the aggregator ttp.init_generator(n) # The TTP distributes the parameter and sk to the participants # The aggregator gets sk0 aggregator.g, aggregator.P, aggregator.p = ttp.g, ttp.P, ttp.p aggregator.sk = ttp.generate_sk() aggregator.init_cipher_basic() # The participants receive the parameter and their key for p in participants: p.small_delta = small_delta p.eps = eps p.gamma = gamma p.n = n p.g, p.P, p.p = ttp.g, ttp.P, ttp.p p.sk = ttp.generate_sk() p.init_cipher_basic() # Now the participants share their private value x to the aggregator for p in participants: aggregator.append_contribution(p.noisy_enc(t)) # Once all participants have sent their contribution, the aggretator # ... aggregates res = aggregator.aggregate_basic(t) logger.info("modulo for the experiment: %d" % (ttp.p)) logger.info("result of the aggregation: %d." % (res)) real_res = 0 for p in participants: real_res += p.x real_res %= ttp.p logger.info("real sum: %d." % (real_res)) logger.info("error: %d" % (modular_abs(res, real_res, ttp.p))) return(res, real_res, ttp.p) def modular_abs(x, y, p): return(min((x-y) % p, (y-x) % p)) if __name__ == "__main__": logging.basicConfig(level=logging.INFO) # L = [] # for i in range(1000): # res, real_res, p = experiment_basic(n, 1337, eps, small_delta, # big_delta, gamma) # L.append((abs(res-real_res)/real_res)*100) # plt.hist(L, bins=10) # plt.show() res, real_res, p = experiment_basic(n, 1337, eps, small_delta, big_delta, gamma)
UTF-8
Python
false
false
2,439
py
12
main.py
11
0.614596
0.600656
0
81
29.111111
72
Ilfarro/live_code_django
506,806,186,717
2a6ddc7c82d8068aeeff17eabbf63bbced4ecf8b
4d2d0f1b51ddfccb2f3aaec0e97025f94d3c0c95
/home/migrations/0006_home_barang_deskripsi.py
8dcbea8c0e8c7a3dea0ca4c98565129b2d4a20b8
[]
no_license
https://github.com/Ilfarro/live_code_django
ea446dc7efc930e4f04293bde020a909bf7a5288
5ababb51fe583b1d907dffd50cb43672805f31fd
refs/heads/master
2020-04-22T19:22:15.097587
2019-02-14T03:55:51
2019-02-14T03:55:51
170,605,321
0
0
null
null
null
null
null
null
null
null
null
null
null
null
null
# Generated by Django 2.1.7 on 2019-02-14 03:05 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('home', '0005_remove_home_barang_deksripsi'), ] operations = [ migrations.AddField( model_name='home_barang', name='deskripsi', field=models.TextField(default=None), preserve_default=False, ), ]
UTF-8
Python
false
false
434
py
12
0006_home_barang_deskripsi.py
8
0.592166
0.548387
0
19
21.842105
54
Anri-Lombard/PythonBootcamp
6,347,961,682,829
6b54921fd7019587f2bdd9eebb1cb63ab2d057d8
5e0a08cd66692443f477245a2ec45ff4e672bcba
/day2/18.py
c0fb375b51155f5bced7d7558be17df01fa74f44
[]
no_license
https://github.com/Anri-Lombard/PythonBootcamp
30b224294de7878cf65066943285c788b2ab9505
8504d1fd15b47a9cbe187f4e99e598265dec0b5d
refs/heads/main
2023-04-14T18:10:43.997879
2021-04-25T04:17:09
2021-04-25T04:17:09
341,822,181
0
0
null
null
null
null
null
null
null
null
null
null
null
null
null
# num_char = len(input("What is your name? ")) # # print("Your name has " + str(num_char) + " characters.") a = 123 # use type() function to investigate types print(type(a))
UTF-8
Python
false
false
174
py
78
18.py
67
0.643678
0.626437
0
7
24
58
nathaliatvrs/checagem_precos
6,038,724,047,262
17603d3c594b144ddd8beb7214c71c0a78ffdd91
8a833ffd5a0d65e3a954982e6ff35061dfb6968c
/pdleo/leo.py
ce0b4950ba89b03dbcc04dd1a91f6fc7c55658b2
[ "MIT" ]
permissive
https://github.com/nathaliatvrs/checagem_precos
4ab7c62d3ac9feddc3d1c0d8b0299cec33acbc5c
025c143f8ab921c54d4283ca34335597989e4666
refs/heads/master
2020-11-25T01:51:20.945006
2019-12-16T21:35:53
2019-12-16T21:35:53
228,437,873
0
0
null
null
null
null
null
null
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#!/usr/bin/env python # coding: utf-8 # ## Importando bibliotecas # In[3]: import pandas as pd import re from io import BytesIO from os import listdir from os.path import join from unicodedata import normalize import platform # In[8]: if platform.system() == 'Linux': from IPython.core.magic import register_line_cell_magic from concurrent.futures import ProcessPoolExecutor, as_completed # ## Funções # #### bmldev.loads # In[9]: def __char_validation(char): invalid = ['', '\n', '\t'] if char in invalid: return False return True def __line_validation(line, qtd_columns, delimiter): line_data = line.split(delimiter) line_data = list(map(str.strip, line_data)) len_line = len(line_data) if (len_line == qtd_columns): return line_data.copy() if (len_line == qtd_columns+2): if (not __char_validation(line_data[0]) and not __char_validation(line_data[-1])): return line_data[1:-1] raise ValueError('Quantidade inválida de colunas na linha') def __str_to_float(text, ind_cut, negative=False): pref = text[:ind_cut].replace('.', '').replace(',', '') suf = text[ind_cut:].replace(',', '.') if (negative): return float(pref + suf) * -1 else: return float(pref + suf) def __to_numeric(val): if (re.search(r'^(\d\d)?\d\d\.\d\d?\.\d\d(\d\d)?$', val)): # verificação de padrão de data (xx.xx.xxxx) return val found_re = re.search(r'[\.]\d{3}$', val) # verfica *.xxx (positivo) if (found_re): try: val.replace('.', '') return int(val.replace('.', '')) except: return val found_re = re.search(r'[\.]\d{3}-$', val) # verfica *.xxx (negativo) if (found_re): try: val.replace('.', '') return int(val[:-1].replace('.', '')) * -1 except: return val found_re = re.search(r'[\.\,]\d+$', val) # verfica *.xx ou *,xx (positivo) if (found_re): try: return __str_to_float(val, found_re.span()[0]) except: return val found_re = re.search(r'[\.\,]\d+-$', val) # verfica *.xx ou *,xx (negativo) if (found_re): try: return __str_to_float(val[:-1], found_re.span()[0], True) except: return val if (re.search(r'^\d+-$', val)): return (int(val[:-1])*-1) if (re.search(r'^\d+$', val)): return (int(val)) return val def __back_to_blank(text, begin): for ind in range(begin,-1,-1): if (text[ind-1] == ' '): return(ind) return 0 def __end_column(text, begin): ind = text[begin:].find(' ') if (ind < 0): return ind ind = ind + 3 for i in range(ind + begin, len(text)): if (text[i] != ' '): return i return None def __get_begin_end(text, column): begin = text.find(column) if (begin < 0): return None # retorno caso nao encontre a coluna end = __end_column(text, begin) if not(end): return None # retorno caso encontre algum erro no end return (begin, end) def __conditions(header, line): if (len(line) < len(header)): return False if (re.search(r'^-+$', line)): return False if (line == header): return False return True def txts_to_pd(arquivos, qtd_columns, has_header=True, encoding='latin-1', delimiter='|', cols_names=None): header_names = [] dic = {i:[] for i in range(qtd_columns)} for arquivo in arquivos: arq = arquivo.readlines() if type(arquivo) == BytesIO else open(arquivo, "r", encoding=encoding) for line in arq: line = line.decode(encoding) if type(arquivo) == BytesIO else line done = False try: data = __line_validation(line, qtd_columns, delimiter) done = True except: done = False if (done): for i in range(len(data)): data[i] = __to_numeric(data[i]) if (not header_names): if (has_header): # print(data) header_names = data else: if (data != header_names): for i in range(qtd_columns): if (isinstance(data[i], str)): dic[i].append(data[i].strip()) else: dic[i].append(data[i]) df = pd.DataFrame.from_dict(dic) # print(header_names) if (len(header_names) == qtd_columns) & (cols_names == None): df.columns = header_names elif (cols_names != None): df.columns = cols_names return df def zvlike_to_df(columns, file, skip=6, encoding="latin-1"): coord = {} df = dict([(col, []) for col in columns]) header = '' cont = 0 # force break with open(file, "r", encoding=encoding) as slar: for line in slar.readlines()[skip:]: if not (header): header = line for col in columns: coord[col] = __get_begin_end(header, col) else: if (__conditions(header, line)): for col in columns: value = line[__back_to_blank(line, coord[col][0]):coord[col][1]].strip() df[col].append(__to_numeric(value)) cont += 1 # force break if (cont > 75): break # force break return pd.DataFrame.from_dict(df) def get_lineData(line, n_cols, delimiter): line_data = line[1:-2].split(delimiter) line_data = list(map(str.strip, line_data)) len_line = len(line_data) if (len_line == n_cols): # if (not __char_validation(line_data[0]) and not __char_validation(line_data[-1])): return line_data return None def line_to_dict(lines, n_cols, delimiter): dic = {i:[] for i in range(n_cols)} if type(lines) != list: lines = [lines] for line in lines: # print(line) data = get_lineData(line, n_cols, delimiter) if data: for i in range(n_cols): data[i] = __to_numeric(data[i]) if (isinstance(data[i], str)): dic[i].append(data[i].strip()) else: dic[i].append(data[i]) return dic def file_to_df(path, n_cols, delimiter, encoding, slice_size=10): lines = path.readlines() if type(path) == BytesIO else open(path, "r", encoding=encoding) dic_all = {i:[] for i in range(n_cols)} header_names = None for line in lines: line = line.decode(encoding) if type(path) == BytesIO else line data = get_lineData(line, n_cols, delimiter) if data: if not header_names: header_names = data.copy() elif data != header_names: ret = line_to_dict(line, n_cols, delimiter) for key, vals in ret.items(): for val in vals: dic_all[key].append(val) df = pd.DataFrame.from_dict(dic_all) df.columns = header_names return df def read_files(files, n_cols, delimiter, encoding): futures = [] result = pd.DataFrame() with ProcessPoolExecutor(max_workers=4) as executor: for path in files: # futures.append(executor.submit(txts_to_pd, [path], n_cols)) futures.append(executor.submit(file_to_df, path, n_cols, delimiter, encoding)) for future in as_completed(futures): ret = future.result() result = pd.concat([result, ret]).reset_index(drop=True) return result if platform.system() == 'Linux': def sap_to_df(paths, n_cols, has_header=True, encoding='latin-1', delimiter='|', cols_names=None): if type(paths) != list: paths = [paths] df = read_files(paths, n_cols, delimiter=delimiter, encoding=encoding) if cols_names: df.columns = cols_names return df # #### Funções utilitárias # In[10]: def arquivo_valido(file): return not '~lock' in file or not '~$' in file def remover_acentos(txt): return normalize('NFKD', txt).encode('ASCII', 'ignore').decode('ASCII') def normaliza(txt): return str(txt).lower().replace(' ','_').replace('.','') def buscar_bases(path, nome=None): for file in listdir(path): if (re.search(nome, remover_acentos(file), flags=re.IGNORECASE)) and arquivo_valido(file): caminho = join(path, file) try: return caminho except: print('Palavra chave não encontrada:', nome) def renomeia_colunas(colunas): return [(str(col)[0].upper() + str(col)[1:]).replace('_',' ') for col in colunas] def normaliza_colunas(cols): colunas = [] try: cols=cols.tolist() except: return cols for col in cols: try: colunas.append(remover_acentos(normaliza(col))) except: colunas.append(col) return colunas def leitura_dic_bases(bases, normaliza=True, Linux=False): dfs={} for base in bases: if bases[base]['tipo'] == 'txt': print ("Lendo base {}...".format(base), end='') try: if Linux: dfs[base] = sap_to_df(bases[base]['path'],bases[base]['columns']) else: dfs[base] = txts_to_pd([bases[base]['path']],bases[base]['columns']) if normaliza: dfs[base].columns = normaliza_colunas(dfs[base].columns) print('ok') except Exception as e: print('erro ao ler base:') print(e) else: print ("Lendo base {}...".format(base), end='') try: if 'sheet' in bases[base]: dfs[base] = pd.read_excel(bases[base]['path'],bases[base]['sheet']) else: dfs[base] = pd.read_excel(bases[base]['path']) if normaliza: dfs[base].columns = normaliza_colunas(dfs[base].columns) print('ok') except Exception as e: print('erro ao ler base:') print(e) return dfs def close_program(msg=''): print('{}'.format(msg), flush=True) input('Press any key to exit.') exit() # In[7]: if platform.system() == 'Linux': @register_line_cell_magic def handle(line, cell): try: exec(cell) except Exception as e: print(e) print('Em:') print(cell) input('Pressione enter para sair') # #### Funções de criação # In[5]: def cria_elemento(tipo, palavra_chave, diretorio='bases', col=0, sheet_name=None): dic = {} dic['tipo'] = tipo dic['path'] = buscar_bases(diretorio, nome=palavra_chave) if tipo == 'txt': dic['columns'] = col if tipo == 'excel' and sheet_name != None: dic['sheet'] = sheet_name return dic def cria_dfs(tipos=[], nomes_bases=[], palavras_chave=[], cols=[], sheet_names=[], diretorio='bases', normaliza_colunas=True): #Informa o S.O. if platform.system() == 'Linux': linux = True else: linux=False bases={} cont_col=0 #contador para atribuir o n° de colunas aos arquvios .txt names=False #boleano para atribuir sheets caso existam if len(sheet_names) > 0: cont_sheet=0 names=True if len(tipos) == len(nomes_bases) == len(palavras_chave): for i in range(len(tipos)): #Arquivos .txt if tipos[i] == 'txt': if cont_col < len(cols): aux = cria_elemento(tipo=tipos[i], palavra_chave = palavras_chave[i], col = cols[cont_col], diretorio = diretorio) cont_col+=1 else: print('Erro em informações de colunas') #Arquivos .xlsx if tipos[i] == 'excel': if not(names): aux = cria_elemento(tipo=tipos[i], palavra_chave = palavras_chave[i], diretorio = diretorio) if names: aux = cria_elemento(tipo=tipos[i], palavra_chave = palavras_chave[i], sheet_name = sheet_names[cont_sheet], diretorio = diretorio) cont_sheet+=1 names = False if not(cont_sheet<len(sheet_names)) else names bases[nomes_bases[i]] = aux else: print('Erro, dados de entrada incorretos') return leitura_dic_bases(bases, normaliza=normaliza_colunas, Linux=linux)
UTF-8
Python
false
false
13,029
py
2
leo.py
1
0.520981
0.516754
0
422
29.829384
150
mawunyodm/PointOfSale
11,501,922,439,663
6d711285ceab7c7592a2cc48d5dd808772035bbd
459797c1ed60c9899f882710418555dd7261257d
/Authentication.py
404ddcbd77df400f5cea7903f56930f3b5709150
[]
no_license
https://github.com/mawunyodm/PointOfSale
2f3f286974b0475767eb3a72bb6ce7c14eb567c3
894b705bd47ad415d21b4ee8fe8cbf6c3cb7c6d0
refs/heads/master
2023-03-01T00:10:39.685128
2021-02-11T05:55:10
2021-02-11T05:55:10
null
0
0
null
null
null
null
null
null
null
null
null
null
null
null
null
from tkinter import * from tkinter import messagebox import sqlite3 authScreen = Tk() authScreen.title("POS START") authScreen.geometry("500x300") spacingFrame = Frame(authScreen) frame = Frame(bg="green",padx=10) welcomeLabel = Label(frame,text="STOP & SHOP",font=("roboto",10,"bold"),pady=10) # CREATING AND/OR CONNECTING TO LOGIN DATABASE conn = sqlite3.connect("db/userAuthentication.db") c = conn.cursor() # c.execute("""CREATE TABLE Users( # firstName text, # lastName text, # password varchar # )""") # c.execute("INSERT INTO users (firstName,lastName,password) VALUES('Emmanuel','Mukombero','Manue4578')") # creating all necessary functions of system modules def back(): oplogin.destroy() def operatorlogin(): conn = sqlite3.connect("db/userAuthentication.db") c = conn.cursor() c.execute("SELECT * FROM Users") records = c.fetchall() for record in records: if usernameEntry.get() == record[0] and passwordEntry.get() == record[2]: response = messagebox.showinfo("LOGIN SUCCESS","You have successfully logged in.") if response == "ok": oplogin.destroy() import pointOfSale elif len(usernameEntry.get()) == 0 or len(passwordEntry.get()) == 0: messagebox.showerror("FILL IN","Fill in all fields") else: messagebox.showerror("LOGIN FAIL","Incorrect username or password") conn.commit() conn.close() # CREATING OPERATOR LOGIN SCREEN def operatorLogin(): global oplogin oplogin = Tk() oplogin.title("OPERATOR LOGIN") oplogin.geometry("500x300") # create labels for logins usernameLabel = Label(oplogin,text="Username",font=("roboto",10)) passwordLabel = Label(oplogin,text="Password",font=("roboto",10)) # create entry widgets for login global usernameEntry global passwordEntry usernameEntry = Entry(oplogin,width=35) passwordEntry = Entry(oplogin,width=35,show="-") # create login and back button loginBtn = Button(oplogin,text="Login",font=("roboto",10),command=operatorlogin) backBtn = Button(oplogin,text="Back",font=("roboto",10),command=back) # displaying widgets on screen usernameLabel.grid(row=0,column=0,pady=(100,20),padx=(100,10)) passwordLabel.grid(row=1,column=0,padx=(100,10)) usernameEntry.grid(row=0,column=1,pady=(100,20)) passwordEntry.grid(row=1,column=1) loginBtn.grid(row=2,column=0,columnspan=2,pady=20,padx=(150,0),ipadx=50) backBtn.grid(row=3,column=0,columnspan=2,padx=(150,0),ipadx=50) def adminlogin(): conn = sqlite3.connect("db/userAuthentication.db") c = conn.cursor() c.execute("SELECT * FROM Users") records = c.fetchall() for record in records: if usernameEntry.get() == record[0] and passwordEntry.get() == record[2]: response = messagebox.showinfo("LOGIN SUCCESS","You have successfully logged in.") if response == "ok": adlogin.destroy() import adminView elif len(usernameEntry.get()) == 0 or len(passwordEntry.get()) == 0: messagebox.showerror("FILL IN","Fill in all fields") else: messagebox.showerror("LOGIN FAIL","Incorrect username or password") conn.commit() conn.close() # if str(usernameEntry.get()) == "Emmanuel" and str(passwordEntry.get()) == "Mukombero": # response = messagebox.showinfo("LOGIN SUCCESS","You have successfully logged in.") # if response == "ok": # adlogin.destroy() # # import adminView # else: # messagebox.showerror("LOGIN FAIL","Incorrect username or password, try again.") # CREATING ADMIN LOGIN SCREEN def adminLogin(): global adlogin adlogin = Tk() adlogin.title("ADMIN LOGIN") adlogin.geometry("500x300") def adback(): adlogin.destroy() # create labels for logins usernameLabel = Label(adlogin,text="Username",font=("roboto",10)) passwordLabel = Label(adlogin,text="Password",font=("roboto",10)) global usernameEntry global passwordEntry # create entry widgets for login usernameEntry = Entry(adlogin,width=35) passwordEntry = Entry(adlogin,width=35,show="-") # create login and back button loginBtn = Button(adlogin,text="Login",font=("roboto",10),command=adminlogin) backBtn = Button(adlogin,text="Back",font=("roboto",10),command=adback) # displaying widgets on screen usernameLabel.grid(row=0,column=0,pady=(100,20),padx=(100,10)) passwordLabel.grid(row=1,column=0,padx=(100,10)) usernameEntry.grid(row=0,column=1,pady=(100,20)) passwordEntry.grid(row=1,column=1) loginBtn.grid(row=2,column=0,columnspan=2,pady=20,padx=(150,0),ipadx=50) backBtn.grid(row=3,column=0,columnspan=2,padx=(150,0),ipadx=50) # Creating Login Options Buttons AdminloginOptionBtn = Button(authScreen,text="LOGIN \n AS ADMIN",font=("roboto",10,"bold"),command=adminLogin) OperatorloginOptionBtn = Button(authScreen,text="LOGIN \n AS OPERATOR",font=("roboto",10,"bold"),command=operatorLogin) # Displaying Widgets to screen spacingFrame.grid(row=0,column=0,columnspan=2,pady=10) frame.grid(row=1,column=0,columnspan=2,ipadx=130) welcomeLabel.grid(row=1,column=0,columnspan=2,ipadx=100) # Displaying Buttons on the screen AdminloginOptionBtn.grid(row=2,column=0,pady=(50,10),ipady=5,ipadx=35,padx=(0,70),columnspan=2) OperatorloginOptionBtn.grid(row=3,column=0,pady=10,ipady=5,padx=(0,70),ipadx=20,columnspan=2) conn.commit() conn.close() authScreen.mainloop()
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Authentication.py
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Genza999/readme_cli
18,391,049,962,858
8ad74ab861702762f76c7c858451d832b81abedd
fea9d83430fe4ba6bfc858d155ca92fcc5dfbe9a
/setup.py
b1442f681f6a3e98c05bf6d4d9e373a4bf2bd44c
[ "MIT" ]
permissive
https://github.com/Genza999/readme_cli
3f9c5699889dfc8d3e7ed86f52df3158bd12123b
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refs/heads/main
2023-01-01T12:07:59.815321
2020-10-21T13:48:11
2020-10-21T13:48:11
304,986,941
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import io import os import re import sys from setuptools import find_packages from setuptools import setup if sys.version_info[:3] < (3, 0, 0): print("Requires Python 3 to run.") sys.exit(1) def read(filename): filename = os.path.join(os.path.dirname(__file__), filename) text_type = type(u"") with io.open(filename, mode="r", encoding='utf-8') as fd: return re.sub(text_type(r':[a-z]+:`~?(.*?)`'), text_type(r'``\1``'), fd.read()) setup( name="read_me_cli", version="0.2.1", url="https://github.com/Genza999/readme_cli", license='MIT', author="Kisekka David", author_email="cartpix@gmail.com", description="Command line tool that displays github README.md content for github repositories", long_description=read("README.rst"), install_requires=[ 'beautifulsoup4==4.9.3', 'certifi==2020.6.20', 'chardet==3.0.4', 'idna==2.10', 'requests==2.24.0', 'soupsieve==2.0.1', 'urllib3==1.25.10', 'urwid==2.1.2' ], keywords='readme cli readme.md github repository', include_package_data=True, packages=["readme_cli"], entry_points={"console_scripts": ["readme_cli = readme_cli.main:main"]}, python_requires=">=3", classifiers=[ 'Development Status :: 2 - Pre-Alpha', 'License :: OSI Approved :: MIT License', 'Programming Language :: Python', 'Programming Language :: Python :: 2', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', ], )
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s3593810/IoT-Based-Automation
5,093,831,228,413
cc0a4b6149a49997e89381e1078ee6082a7fb21a
f2c6a0fbbc1728ab409975157dfdf00826b23e74
/App_Logging.py
45a6d26fff2c1fbd450ce99daaba05bddcede9cf
[]
no_license
https://github.com/s3593810/IoT-Based-Automation
9f140ba3492f59a49680e66a673402cacd20fd42
ecbd24282789748710ce7d3043361fb4347dbebd
refs/heads/master
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2019-04-07T11:04:55
2019-04-07T11:04:55
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import logging class SenseHatApp_logging: logger = logging.getLogger(name='AppLogger') def __init__(self): self.logger.setLevel(logging.DEBUG) formatter = logging.Formatter( '[%(asctime)s:%(module)s:%(lineno)s:%(levelname)s] %(message)s' ) filehandler = logging.FileHandler('SenseHatApp.log') filehandler.setLevel(logging.DEBUG) filehandler.setFormatter(formatter) self.logger.addHandler(filehandler)
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dcollins4096/p19_newscripts
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04a643a77927bc56ab58c7df91d4733321e61e51
/tools_data/annotate_hair.py
ad6584f0d03d804fdd70e93a6ad8734a3a100c30
[]
no_license
https://github.com/dcollins4096/p19_newscripts
d2fae1807170a4d70cf4c87222a6258211f993ff
23c780dd15b60944ed354406706de85282d0bee6
refs/heads/master
2023-07-21T11:53:55.188383
2023-07-18T17:38:21
2023-07-18T17:38:21
215,159,839
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import yt import matplotlib.pyplot as plt from yt.visualization.plot_modifications import * import pyximport; pyximport.install() import particle_ops import particle_grid_mask from scipy.spatial import ConvexHull import h5py import time import numpy as na import os import pdb import copy class HairCallback(PlotCallback): """ Add streamlines to any plot, using the *field_x* and *field_y* from the associated data, skipping every *factor* datapoints like 'quiver'. *density* is the index of the amount of the streamlines. *field_color* is a field to be used to colormap the streamlines. If *display_threshold* is supplied, any streamline segments where *field_color* is less than the threshold will be removed by having their line width set to 0. """ _type_name = "hair" _supported_geometries = ("cartesian", "spectral_cube", "polar", "cylindrical") def __init__( self, field_x, field_y, factor=16, density=1, field_color=None, display_threshold=None, plot_args=None, this_looper=None, frame=None, core_id=None ): PlotCallback.__init__(self) def_plot_args = {} self.this_looper=this_looper self.frame=frame self.core_id=core_id self.field_x = field_x self.field_y = field_y self.field_color = field_color self.factor = factor self.dens = density self.display_threshold = display_threshold if plot_args is None: plot_args = def_plot_args self.plot_args = plot_args def __call__(self, plot): import pdb bounds = self._physical_bounds(plot) xx0, xx1, yy0, yy1 = self._plot_bounds(plot) # We are feeding this size into the pixelizer, where it will properly # set it in reverse order nx = plot.image._A.shape[1] // self.factor ny = plot.image._A.shape[0] // self.factor pixX = plot.data.ds.coordinates.pixelize( plot.data.axis, plot.data, self.field_x, bounds, (nx, ny) ) pixY = plot.data.ds.coordinates.pixelize( plot.data.axis, plot.data, self.field_y, bounds, (nx, ny) ) if self.field_color: field_colors = plot.data.ds.coordinates.pixelize( plot.data.axis, plot.data, self.field_color, bounds, (nx, ny) ) if self.display_threshold: mask = field_colors > self.display_threshold lwdefault = matplotlib.rcParams["lines.linewidth"] if "linewidth" in self.plot_args: linewidth = self.plot_args["linewidth"] else: linewidth = lwdefault try: linewidth *= mask self.plot_args["linewidth"] = linewidth except ValueError as e: err_msg = ( "Error applying display threshold: linewidth" + "must have shape ({}, {}) or be scalar" ) err_msg = err_msg.format(nx, ny) raise ValueError(err_msg) from e else: field_colors = None X, Y = ( np.linspace(xx0, xx1, nx, endpoint=True), np.linspace(yy0, yy1, ny, endpoint=True), ) streamplot_args = { "x": X, "y": Y, "u": pixX, "v": pixY, "density": self.dens, "color": field_colors, } streamplot_args.update(self.plot_args) plot._axes.streamplot(**streamplot_args) plot._axes.set_xlim(xx0, xx1) plot._axes.set_ylim(yy0, yy1) #new stuff import trackage obnoxious_counter=0 try: xax =plot.data.ds.coordinates.x_axis[plot.data.axis] yax =plot.data.ds.coordinates.y_axis[plot.data.axis] xaf = 'xyz'[xax] yaf = 'xyz'[yax] obnoxious_counter=1 core_id = self.core_id this_looper=self.this_looper thtr=this_looper.tr ms = trackage.mini_scrubber(thtr,core_id) ms.particle_pos(core_id) frame_ind = np.where(this_looper.tr.frames ==self.frame)[0][0] obnoxious_counter=2 all_x,all_y,all_z=ms.particle_x,ms.particle_y, ms.particle_z all_p = [all_x,all_y,all_z] all_p_s = np.stack(all_p) max_max = all_p_s.max(axis=1).max(axis=1) min_min = all_p_s.min(axis=1).min(axis=1) cen = 0.5*(min_min+max_max) XX,YY= all_p[xax].transpose(), all_p[yax].transpose() plot._axes.scatter(XX[0,:],YY[0,:], c='k') plot._axes.plot(XX[:frame_ind+1,:],YY[:frame_ind+1,:], c=[0.5]*4, zorder=7, linewidth=0.1) plot._axes.scatter(XX[frame_ind,:],YY[frame_ind,:], c='r', s=1,zorder=1) except: print("Failed by ",obnoxious_counter) pdb.set_trace() #plot._axes.set_xlim(xx0, xx1) #plot._axes.set_ylim(yy0, yy1)
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justincurl/prior-time
19,155,554,177,324
472787400978210e38254cdc15c865d5f15b34d7
8227e890fc6e222c600342024a2cac1838f97d97
/otime/config.py
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refs/heads/master
2021-04-24T13:32:56.437632
2020-12-27T02:09:47
2020-12-27T02:09:47
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""" This file includes all available configuration options for the otime app. Modify this file to set all your preferences - also modify `templates/otime/Results.html` to your liking which will be displayed after all questions of all blocks have been answered. It's not recommended to edit any of the other files. Be sure to also check the README.md file! """ import random from .block import Block #: The total budget available for each choice TOTAL_BUDGET = 5 NUM_BLOCKS = 4 #: Set to True if you want blocks to be randomized in order RANDOMIZE_BLOCKS = False #: Set to True if the choices per question in a block should be visualized as a slider #: as opposed to single radio buttons VISUALIZE_CHOICES_AS_SLIDER = False #: The configuration for all blocks to be displayed to the user #: Note: #: - The given delays are treated as WEEKS where an initial delay of 0 means today. #: - The order of interest_rates given is the order in which they will be display, i.e. #: to change the order of display just change the order of values here """ Edit the number of choices and values to put in the blocks here """ block_order = [i for i in range(NUM_BLOCKS)] if RANDOMIZE_BLOCKS: random.shuffle(block_order) BLOCKS = [ Block( values=[5, 4, 3, 2], initial_payout_delay=0, initial_to_last_payout_delay=1, number_of_choices=6, decrease_rate=0.8, block_index= int(block_order[0]) ), Block( values=[5, 4, 3, 2], initial_payout_delay=0, initial_to_last_payout_delay=2, number_of_choices=6, decrease_rate=0.8, block_index= int(block_order[1]) ), Block( values=[5, 4, 3, 2], initial_payout_delay=1, initial_to_last_payout_delay=1, number_of_choices=6, decrease_rate=0.8, block_index= int(block_order[2]) ), Block( values=[5, 4, 3, 2], initial_payout_delay=1, initial_to_last_payout_delay=2, number_of_choices=6, decrease_rate=0.8, block_index= int(block_order[3]) ) ]
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AndrewGYork/msim
8,478,265,488,337
7205dbe00cc852d02a809b710677d29f035ac0d7
cc6886ef475eebfa2f0e126a04041f5ec5427ff8
/data_processing/convolve_sparse.py
4ed41e647be0d42461f48ea3e2a11027343f9ba1
[]
no_license
https://github.com/AndrewGYork/msim
5d88784b21235f124d0c21ef835b69bdfe672039
5eb8370eb0979cf564b956a7e1adb3038d8f505e
refs/heads/master
2021-01-13T00:52:25.160450
2015-10-15T17:14:28
2015-10-15T17:14:28
44,332,737
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import time import numpy def convolve_sparse(a, locations_list, amplitude_list=None): if amplitude_list == None: amplitude_list = [1 for l in locations_list] assert len(locations_list) == len(amplitude_list) output = numpy.zeros_like(a) for j, location in enumerate(locations_list): assert len(location) == len(a.shape) input_slices = [ slice( max(0, location[i]), min(a.shape[i], a.shape[i] + location[i])) for i in range(len(a.shape))] output_slices = [ slice( max(0, -location[i]), min(a.shape[i], a.shape[i] - location[i])) for i in range(len(a.shape))] output[output_slices] += amplitude_list[j] * a[input_slices] return output a = numpy.zeros((50, 500, 500)) a[3, 10, 10] = 1 location_list = [ (-3, 0, 0), (1, 1, -1) ] print "Convolving with list..." start = time.time() b = convolve_sparse(a, location_list) end = time.time() print "Done convolving." print "Time:", end-start import pylab fig = pylab.figure() pylab.imshow(b.max(axis=0), cmap=pylab.cm.gray, interpolation='nearest') fig.show()
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convolve_sparse.py
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LibreChou/Data-Finance-Cup
1,047,972,039,537
620a9e1e83f66c5ffda6142acf8ddeb268f8856f
76e7a508d6a4fb07f2ee3a596ecb84e20a717041
/xm_80.py
afead151f42e8b8271100da22ee4f9ba59760a70
[]
no_license
https://github.com/LibreChou/Data-Finance-Cup
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55efd7c6438c697bb4d1ddcd30b12c2c6e9fe0e0
refs/heads/master
2022-04-20T20:17:07.342575
2019-12-21T02:00:08
2019-12-21T02:00:08
null
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# !pip install xgboost --user # !pip install tqdm --user # !pip install seaborn --user import pandas as pd from sklearn.preprocessing import MinMaxScaler def load_xgb_data(): train = pd.read_csv("new_data/train.csv") train_target = pd.read_csv('new_data/train_target.csv') train = train.merge(train_target, on='id') test = pd.read_csv("new_data/test.csv") test['target'] = -1 df = pd.concat([train, test], sort=False, axis=0) # 删除重复列 duplicated_features = ['x_0', 'x_1', 'x_2', 'x_3', 'x_4', 'x_5', 'x_6', 'x_7', 'x_8', 'x_9', 'x_10', 'x_11', 'x_13', 'x_15', 'x_17', 'x_18', 'x_19', 'x_21', 'x_23', 'x_24', 'x_36', 'x_37', 'x_38', 'x_57', 'x_58', 'x_59', 'x_60', 'x_77', 'x_78'] + \ ['x_22', 'x_40', 'x_70'] + \ ['x_41'] + \ ['x_43'] + \ ['x_45'] + \ ['x_61'] # df = df.drop(columns=duplicated_features) ############### ############### x_feature = [] for i in range(79): x_feature.append('x_{}'.format(i)) no_features = ['id', 'target', 'isNew'] features = [] numerical_features = ['lmt', 'certValidBegin', 'certValidStop'] categorical_features = [fea for fea in df.columns if fea not in numerical_features + no_features] ########### import time df['certValidPeriod'] = df['certValidStop'] - df['certValidBegin'] df['begin'] = df['certValidBegin'].apply(lambda x: time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(x))) df['end'] = df['certValidStop'].apply(lambda x: time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(x))) df['begin'] = df['begin'].apply(lambda x: int(x.split('-')[0])) df['end'] = df['end'].apply(lambda x: int(x.split('-')[0])) df['val_period'] = df['end'] - df['begin'] ########### # 0.76新加 ########### cols = [] df['certId12'] = df['certId'].apply(lambda x: int(str(x)[:2]) if x != -999 else -999) df['certId34'] = df['certId'].apply(lambda x: int(str(x)[2:4]) if x != -999 else -999) df['certId56'] = df['certId'].apply(lambda x: int(str(x)[4:]) if x != -999 else -999) from sklearn.preprocessing import LabelEncoder df['certId12_basicLevel'] = df['certId12'].astype(str) + df['basicLevel'].astype(str) df['certId34_basicLevel'] = df['certId34'].astype(str) + df['basicLevel'].astype(str) df['certId56_basicLevel'] = df['certId56'].astype(str) + df['basicLevel'].astype(str) df['certId12_loanProduct'] = df['certId12'].astype(str) + df['loanProduct'].astype(str) df['certId34_loanProduct'] = df['certId34'].astype(str) + df['loanProduct'].astype(str) df['certId56_loanProduct'] = df['certId56'].astype(str) + df['loanProduct'].astype(str) # cols += ['certId12_loanProduct', 'certId34_loanProduct','certId56_loanProduct'] cols += ['certId12_basicLevel', 'certId34_basicLevel', 'certId56_basicLevel', 'certId12_loanProduct', 'certId34_loanProduct', 'certId56_loanProduct'] df['dist56'] = df['dist'].apply(lambda x: int(str(x)[4:]) if x != -999 else -999) df['dist56_basicLevel'] = df['dist56'].astype(str) + df['basicLevel'].astype(str) df['dist56_loanProduct'] = df['dist56'].astype(str) + df['loanProduct'].astype(str) # cols += ['dist56_loanProduct'] cols += ['dist56_basicLevel', 'dist56_loanProduct'] # 估计有用 # df['residentAddr56'] = df['residentAddr'].apply(lambda x: int(str(x)[4:]) if x != -999 else -999) # df['residentAddr56_basicLevel'] = df['residentAddr56'].astype(str) + df['basicLevel'].astype(str) # df['residentAddr56_loanProduct'] = df['residentAddr56'].astype(str) + df['loanProduct'].astype(str) # cols += ['residentAddr56_loanProduct'] # cols += ['residentAddr56_basicLevel', 'residentAddr56_loanProduct'] #### # df['certId12_lmt'] = df.groupby('certId12')['lmt'].transform('mean') # df['certId12_lmt'] = df.groupby('certId12')['lmt'].transform('median') # df['certId34_lmt'] = df.groupby('certId34')['lmt'].transform('mean') # df['certId34_lmt'] = df.groupby('certId34')['lmt'].transform('median') # df['certId56_lmt'] = df.groupby('certId56')['lmt'].transform('mean') # df['certId56_lmt'] = df.groupby('certId56')['lmt'].transform('median') ################ # things not work # df['certId12_edu'] = df['certId12'].astype(str) + df['edu'].astype(str) # df['certId34_edu'] = df['certId34'].astype(str) + df['edu'].astype(str) # df['certId56_edu'] = df['certId56'].astype(str) + df['edu'].astype(str) # 'certId12_edu', 'certId34_edu','certId56_edu' # useless = ['x_59','x_22','x_23','x_24','x_30','x_31','x_32','x_35','x_36','x_37','x_38','x_39','x_40','x_42', # 'x_57','x_58','x_60','x_69','x_70','x_77','x_78','ncloseCreditCard','unpayIndvLoan','unpayOtherLoan', # 'unpayNormalLoan','5yearBadloan','x_21','x_19','is_edu_equal','x_9','x_7','x_8','x_4','x_10','x_11', # 'x_1','x_6','x_13','x_3','x_18','x_15','x_17','x_2','x_5'] ################ # 待尝试 # 四个一起降分 # df['certId12_job'] = df['certId12'].astype(str) + df['job'].astype(str) # df['certId12_ethnic'] = df['certId12'].astype(str) + df['ethnic'].astype(str) # cols += ['certId12_job', 'certId12_ethnic'] # df['certId12_edu'] = df['certId12'].astype(str) + df['edu'].astype(str) # df['certId12_highestEdu'] = df['certId12'].astype(str) + df['highestEdu'].astype(str) # cols += ['certId12_edu', 'certId12_highestEdu'] # df['edu_basicLevel'] = df['edu'].astype(str) + df['basicLevel'].astype(str) # df['edu_loanProduct'] = df['edu'].astype(str) + df['loanProduct'].astype(str) # df['edu_lmt'] = df.groupby('edu')['lmt'].transform('mean') # df['edu_lmt'] = df.groupby('edu')['lmt'].transform('median') # cols += ['edu_basicLevel', 'edu_loanProduct'] # df['highestEdu_basicLevel'] = df['highestEdu'].astype(str) + df['basicLevel'].astype(str) # df['highestEdu_loanProduct'] = df['highestEdu'].astype(str) + df['loanProduct'].astype(str) # df['highestEdu_lmt'] = df.groupby('highestEdu')['lmt'].transform('mean') # df['highestEdu_lmt'] = df.groupby('highestEdu')['lmt'].transform('median') # cols += ['highestEdu_basicLevel', 'highestEdu_loanProduct'] for col in cols: lab = LabelEncoder() df[col] = lab.fit_transform(df[col]) cols += ['certId12', 'certId34', 'certId56', 'dist56'] cols += ['bankCard', 'residentAddr', 'certId', 'dist', 'age', 'job', 'basicLevel', 'loanProduct', 'val_period'] # count for col in cols: df['{}_count'.format(col)] = df.groupby(col)['id'].transform('count') df['is_edu_equal'] = (df['edu'] == df['highestEdu']).astype(int) print(df.shape) feature = [fea for fea in df.columns if fea not in no_features + ['begin', 'end']] train, test = df[:len(train)], df[len(train):] return train,test,feature train,test,feature=load_xgb_data() import numpy as np import xgboost as xgb from sklearn.model_selection import StratifiedKFold, KFold n_fold = 5 y_scores = 0 y_pred_l1 = np.zeros([n_fold, test.shape[0]]) y_pred_all_l1 = np.zeros(test.shape[0]) fea_importances = np.zeros(len(feature)) label = ['target'] # [1314, 4590] kfold = StratifiedKFold(n_splits=n_fold, shuffle=True, random_state=1314) for i, (train_index, valid_index) in enumerate(kfold.split(train[feature], train[label])): if i != 1: print(i) X_train, y_train, X_valid, y_valid = train.loc[train_index][feature], train[label].loc[train_index], \ train.loc[valid_index][feature], train[label].loc[valid_index] bst = xgb.XGBClassifier(max_depth=3, n_estimators=10000,verbosity=1, learning_rate=0.01) bst.fit(X_train, y_train, eval_set=[(X_valid, y_valid)], eval_metric='auc', verbose=500, early_stopping_rounds=500) y_pred_l1[i] = bst.predict_proba(test[feature])[:, 1] y_pred_all_l1 += y_pred_l1[i] y_scores += bst.best_score fea_importances += bst.feature_importances_ test['target'] = y_pred_all_l1 / 4 print('average score is {}'.format(y_scores / 4))
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xm_80.py
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jakebyford/web-scraping-challenge
17,497,696,791,287
9a351f42e96e1a18208cf2c37f20b700c16508f5
0a54454a452e91d2c4b53c6cd01fecb1c6bd2e6f
/Mission to Mars/app.py
c9db3cd5a35986212db77d000aa657a9ab5b3acc
[]
no_license
https://github.com/jakebyford/web-scraping-challenge
c8f28d6502d7e956d220b8c717eb0c61a1dcee1f
a8e0f764c2a5c4122d361f54aa0b4ad69e9c0be8
refs/heads/master
2022-12-13T03:11:23.310368
2020-09-02T21:26:45
2020-09-02T21:26:45
290,950,206
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from flask import Flask, render_template, redirect from flask_pymongo import PyMongo import scrape_mars app = Flask(__name__) #Allowing mongo to be used in flask - use mars_app - is the identical code in mongodb mongo = PyMongo(app, uri = "mongodb://localhost:27017/mars_app") @app.route("/") def init_browser(): # mars_data_db = mongo.db.mars_collection.find_one() return render_template("index.html", mars = mars_data_db) @app.route("/scrape") def scrape(): mars_data = scrape_mars.scrape_info() mongo.db.mars_collection.update({}, mars_data, upsert = True) return redirect("/") if __name__ == "__main__": app.run(debug = True)
UTF-8
Python
false
false
671
py
2
app.py
2
0.66766
0.660209
0
31
20.645161
85
ztl2004/recover
5,385,889,017,475
aa0efed1aff12d8032b96c27d9cdd568bae84c67
d783ce5216bafe180f6d63986e7754a1df490139
/models.py
031b86e776d57fa9d4d5bfb8472486bee983ba9d
[]
no_license
https://github.com/ztl2004/recover
4e91dcb1020bd12d3577e11bf0e1cd1bc5d6cda2
0367af4145488fb487293e09a81a229d9b103377
refs/heads/master
2021-01-19T00:16:33.427391
2013-07-06T11:52:53
2013-07-06T11:52:53
null
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from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, Integer, String, ForeignKey, DateTime, BigInteger, Text Base = declarative_base() class Rat(Base): __tablename__ = 'rats' id = Column(Integer, primary_key=True) name = Column(String(100)) title = Column(String(100)) def __init__(self, name, title): self.name = name self.title = title def __repr__(self): return "<Rat('%s','%s')>" % (self.name, self.title) class Event(Base): __tablename__ = 'event' id = Column(Integer, primary_key=True) title = Column(String(500)) location = Column(String(500)) content = Column(Text) def __init__(self, name): self.title = title self.location = location self.content = content def __repr__(self): return "<Event('%s')>" % (self.title)
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py
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models.py
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0.600902
0.587373
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adambaranec/math
11,287,174,079,024
d56bf712fd061d9cf0b937b7364cbd09cf9f577e
7780dc31dc58ce153409b3f043543bbff1a3c707
/count.py
454d309b08a1c6753c3a46ab8a1f3b7bd7424c34
[]
no_license
https://github.com/adambaranec/math
828c087fc2516d0f783493b1219b9f685773cc1e
1294428f79a27d85c1d85a9ed378bc01587c1b9e
refs/heads/main
2023-08-22T05:17:53.160958
2021-10-19T18:27:43
2021-10-19T18:27:43
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import ui, math, texts as tx from tkinter import messagebox def prvy(): if ui.shape.get() == 1: try: getside = ui.dlzka.get() side = float(getside) obsah = side * side zapis = str(obsah) stav = tx.writesqarea + zapis ui.l_obsahstvorca.pack_forget() ui.l_obsahstvorca.pack() ui.l_obsahstvorca.config(text=stav) except ValueError: messagebox.showerror(tx.attention, tx.accept) if ui.shape.get() == 2: try: geta = ui.a.get() getb = ui.b.get() sidea = float(geta) sideb = float(getb) obsah = sidea * sideb zapis = str(obsah) stav = tx.writerectarea + zapis ui.l_obsahobdlznika.pack_forget() ui.l_obsahobdlznika.pack() ui.l_obsahobdlznika.config(text=stav) except ValueError: messagebox.showerror(tx.attention, tx.accept) if ui.shape.get() == 3: try: getr = ui.r.get() radius = float(getr) obsah = math.pi * radius*radius zapis = str(obsah) stav = tx.writecirclea + zapis ui.l_obsahkruhu.pack_forget() ui.l_obsahkruhu.pack() ui.l_obsahkruhu.config(text=stav) except ValueError: messagebox.showerror(tx.attention, tx.accept) if ui.shape.get() == 4: try: geta = ui.a.get() getb = ui.b.get() sidea = float(geta) sideb = float(getb) vysledok = sidea*sidea + sideb*sideb zapis = str(vysledok) stav = tx.writepytres + zapis ui.l_vysledokvety.pack_forget() ui.l_vysledokvety.pack() ui.l_vysledokvety.config(text=stav) except ValueError: messagebox.showerror(tx.attention, tx.accept) def druhy(): if ui.shape.get() == 1: try: getside = ui.dlzka.get() side = float(getside) obvod = side * 4 zapis = str(obvod) stav = tx.writesqper + zapis ui.l_obvodstvorca.pack_forget() ui.l_obvodstvorca.pack() ui.l_obvodstvorca.config(text=stav) except ValueError: messagebox.showerror(tx.attention, tx.accept) if ui.shape.get() == 2: try: geta = ui.a.get() getb = ui.b.get() sidea = int(geta) sideb = int(getb) obvod = 2 * (sidea + sideb) zapis = str(obvod) stav = tx.writerectper + zapis ui.l_obvodobdlznika.pack_forget() ui.l_obvodobdlznika.pack() ui.l_obvodobdlznika.config(text=stav) except ValueError: messagebox.showerror(tx.attention, tx.accept) if ui.shape.get() == 3: try: getr = ui.r.get() radius = int(getr) obvod = 2 * math.pi * radius zapis = str(obvod) stav = tx.writecirclep + zapis ui.l_obvodkruhu.pack_forget() ui.l_obvodkruhu.pack() ui.l_obvodkruhu.config(text=stav) except ValueError: messagebox.showerror(tx.attention, tx.accept) if ui.shape.get() == 4: try: geta = ui.a.get() getb = ui.b.get() sidea = int(geta) sideb = int(getb) vypocet = sidea*sidea + sideb*sideb vysledok = math.sqrt(vypocet) zapis = str(vysledok) stav = tx.writepytlen + zapis ui.l_dlzkaodvesny.pack_forget() ui.l_dlzkaodvesny.pack() ui.l_dlzkaodvesny.config(text=stav) except ValueError: messagebox.showerror(tx.attention, tx.accept) ui.obsah.config(command=prvy) ui.obvod.config(command=druhy) ui.vysledok.config(command=prvy) ui.realna_dlzka.config(command=druhy)
UTF-8
Python
false
false
3,877
py
8
count.py
7
0.535208
0.53237
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115
32.721739
56
ZZhangsyx/RE01_NOAA_GPM
5,815,385,725,879
33a96e8037b81b040a923baf2246f655d44ad74e
73982949ace4ef0dfc0df98accabaf45de8fc20c
/Code/Train_class.py
bf5be2e17635bf9057240cc3e79fd78ffdcac453
[]
no_license
https://github.com/ZZhangsyx/RE01_NOAA_GPM
5c959efb7c734046f3c8ee1942081defb20194f2
fbba1ce5f90fb8953cbde8813b0956f5ddf6c0f5
refs/heads/master
2023-07-14T06:34:16.194060
2021-08-25T01:38:40
2021-08-25T01:38:40
null
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# coding=utf-8 """ Author: Zhang Zhi Email: zhangzh49@mail2.sysu.edu.cn Date: 2021/1/5 """ import numpy as np import pandas as pd import tensorflow as tf import os from imblearn.over_sampling import SMOTE import joblib from sklearn.model_selection import RandomizedSearchCV from sklearn.ensemble import RandomForestClassifier from sklearn.svm import SVC from scipy.stats import randint import xgboost as xgb def calculate_acc(A, B, isShow=True): """ :param A: Label :param B: Predict value :param isShow: Whether to plot :return: Evaluation indicators: POD, FAR, accuracy, F1-score """ A[A != 0] = 1 B[B != 0] = 1 A, B = np.array(A), np.array(B) num_A = len(A) TP = np.sum(np.multiply(A, B)) TN = np.sum((A + B) == 0) FP = np.sum((A - B) == -1) FN = np.sum((A - B) == 1) POD = TP / np.sum(A) FAR = FP / np.sum(B) accuracy = (TP + TN) / num_A precision = TP / (TP + FP) recall = TP / (TP + FN) F = precision * recall * 2 / (precision + recall) if isShow: print('****** Evaluation Score ******') print("POD: ", '%.3f' % POD) print("FAR: ", '%.3f' % FAR) print("ACC: ", '%.3f' % accuracy) print("F: ", '%.3f' % F, '\n') return POD, FAR, accuracy, F class Model(object): def __init__(self, model_name, basin_name): """ :param model_name: Model name :param basin_name: Basin name """ self.name = model_name self.basin = basin_name self.path = '../Model/' + self.name + '_C_' + self.basin + '.pkl' def load(self): """ :return: Load model """ if os.path.isfile(self.path): self.model = joblib.load(self.path) return self.model else: print('Model didnt exsit!') def predict(self, x_train, x_test, y_train, y_test): """ :param x_train: Input feature in training step :param x_test: Input feature in testing step :param y_train: Output feature in training step :param y_test: Output feature in testing step :return: Predicting class value (Rain/No rain) """ print('Predicting ' + self.name + ':') train_class_pre = self.model.predict(x_train) calculate_acc(train_class_pre, y_train) test_class_pre = self.model.predict(x_test) calculate_acc(test_class_pre, y_test) return train_class_pre, test_class_pre def SVM(x_train, x_test, y_train, y_test, BN): """ :param BN: Basin name's abbreviation [str] :param x_train: Input feature in training step :param x_test: Input feature in testing step :param y_train: Output feature in training step :param y_test: Output feature in testing step """ Model_SVM = Model(model_name='SVM', basin_name=BN) if os.path.isfile(Model_SVM.path): model = Model_SVM.load() else: model = SVC(C=1, kernel='rbf', shrinking=True, max_iter=-1) model.fit(x_train, y_train) joblib.dump(model, Model_SVM.path) model = Model_SVM.load() train_class_pre, test_class_pre = Model_SVM.predict( x_train, x_test, y_train, y_test) return train_class_pre, test_class_pre def RF(x_train, x_test, y_train, y_test, BN): Model_RF = Model(model_name='RF', basin_name=BN) if os.path.isfile(Model_RF.path): model = Model_RF.load() else: model = RandomForestClassifier(random_state=2020) param_distribs = {'n_estimators': randint(low=1, high=200), 'max_features': randint(low=1, high=10), } rnd_search = RandomizedSearchCV( model, param_distributions=param_distribs, n_iter=10, cv=5, random_state=2020) rnd_search.fit(x_train, y_train) model = rnd_search.best_estimator_ print('Model RFC Fitted!') joblib.dump(model, Model_RF.path) model = Model_RF.load() train_class_pre, test_class_pre = Model_RF.predict( x_train, x_test, y_train, y_test) return train_class_pre, test_class_pre def ANN(x_train, x_test, y_train, y_test, BN): checkpoint_ANN = '../model/ANN_C_' + BN + '.ckpt' model = tf.keras.models.Sequential([ tf.keras.layers.Flatten(), tf.keras.layers.Dense(128, activation='relu'), tf.keras.layers.Dense(128, activation='relu'), tf.keras.layers.Dense(64, activation='relu'), tf.keras.layers.Dense(32, activation='relu'), tf.keras.layers.Dense(2, activation='softmax') ]) model.compile( optimizer='adam', loss=tf.keras.losses.SparseCategoricalCrossentropy( from_logits=False), metrics=['sparse_categorical_accuracy']) if os.path.exists(checkpoint_ANN + '.index'): print('-------------load the model-----------------') model.load_weights(checkpoint_ANN) cp_callback = tf.keras.callbacks.ModelCheckpoint(filepath=checkpoint_ANN, save_weights_only=True, save_best_only=True) if not os.path.isfile(checkpoint_ANN): model.fit( np.array(x_train), np.array(y_train), batch_size=128, epochs=100, validation_data=[ np.array(x_test), np.array(y_test)], validation_freq=1, callbacks=[cp_callback]) print('Predicting ANN:') train_class_pre = model.predict(x_train).argmax(axis=1) calculate_acc(train_class_pre, y_train) test_class_pre = model.predict(x_test).argmax(axis=1) calculate_acc(test_class_pre, y_test) return train_class_pre, test_class_pre def XGB(x_train, x_test, y_train, y_test, BN): Model_XGB = Model(model_name='XGB', basin_name=BN) if os.path.isfile(Model_XGB.path): model = Model_XGB.load() else: model = xgb.XGBClassifier( max_depth=5, n_estimators=1000, colsample_bytree=0.8, subsample=0.8, nthread=10, learning_rate=0.1, min_child_weight=2) model.fit(x_train, y_train) print('Model XGBC Fitted!') joblib.dump(model, Model_XGB.path) model = Model_XGB.load() train_class_pre, test_class_pre = Model_XGB.predict( x_train, x_test, y_train, y_test) return train_class_pre, test_class_pre def Train_class(in_path, out_path, BN, BS, isBalance): """ :param in_path: Csv path :param out_path: Save path :param BN: Basin name's abbreviation [str] :param BS: One word to express basin [str] :param isBalance: Whether the data is balance in class distribution :return: Predicting class value to csv file """ print('Loading data...') csv_name = os.path.join(in_path, 'data_DEA1.csv') data_pro = pd.read_csv(csv_name) data_pro['Time'] = pd.to_datetime(data_pro['Time']) data_pro = data_pro.set_index('Time') print('Data processing...') Train = data_pro['2015':'2017'] Test = data_pro['2018'] y_train, y_test = Train['isRain_CMPA'], Test['isRain_CMPA'] x_train = Train.drop(['isRain_CMPA', 'CMPA_' + BS], axis=1) x_test = Test.drop(['isRain_CMPA', 'CMPA_' + BS], axis=1) if not isBalance: smo = SMOTE(random_state=42) x_train, y_train = smo.fit_sample(x_train, y_train) print('Execute modeling..') nonsen, Test['ANN_class'] = ANN(x_train, x_test, y_train, y_test, BN) nonsen, Test['SVM_class'] = SVM(x_train, x_test, y_train, y_test, BN) nonsen, Test['RF_class'] = RF(x_train, x_test, y_train, y_test, BN) nonsen, Test['XGB_class'] = XGB(x_train, x_test, y_train, y_test, BN) # Compare with GPM isRain_GPM = np.array(Test['GPM_' + BS]) isRain_GPM[isRain_GPM > 0] = 1 Test['GPM_class'] = isRain_GPM calculate_acc(isRain_GPM, y_test) # Save Test.to_csv(os.path.join(out_path, 'Test_class' + BN + '.csv'), index=True) else: print('Execute modeling..') Train['SVM_class'], Test['SVM_class'] = SVM(x_train, x_test, y_train, y_test) Train['RF_class'], Test['RF_class'] = RF(x_train, x_test, y_train, y_test) Train['ANN_class'], Test['ANN_class'] = ANN(x_train, x_test, y_train, y_test) Train['XGB_class'], Test['XGB_class'] = XGB(x_train, x_test, y_train, y_test) # Compare with GPM isRain_GPM = np.array(Train['GPM_' + BS]) isRain_GPM[isRain_GPM > 0] = 1 Train['GPM_class'] = isRain_GPM calculate_acc(isRain_GPM, y_train) isRain_GPM = np.array(Test['GPM_' + BS]) isRain_GPM[isRain_GPM > 0] = 1 Test['GPM_class'] = isRain_GPM calculate_acc(isRain_GPM, y_test) # Save Train.to_csv(os.path.join(out_path, 'Train_class' + BN + '.csv'), index=True) Test.to_csv(os.path.join(out_path, 'Test_class' + BN + '.csv'), index=True) print('Code deal!') def main(): BN = 'DJ' BS = 'DongJ' processed_path = '../data/processed_' + BN +'2' DEA_path = processed_path + '/DEA' isBalance = False Train_class(DEA_path, processed_path, BN, BS, isBalance) if __name__ == '__main__': main()
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Train_class.py
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colbyjantzen/my-first-blog
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/blog/migrations/0007_auto_20180226_2126.py
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# -*- coding: utf-8 -*- # Generated by Django 1.11.8 on 2018-02-27 02:26 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('blog', '0006_post_date'), ] operations = [ migrations.AlterField( model_name='temperature', name='date', field=models.DateField(), ), ]
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import onnx import onnx_graphsurgeon as gs import sclblonnx as so H=192 W=640 MODEL1=f'lite_hr_depth_k_t_encoder_{H}x{W}.onnx' MODEL2=f'lite_hr_depth_k_t_depth_{H}x{W}.onnx' MODEL3=f'lite_hr_depth_k_t_encoder_depth_{H}x{W}.onnx' graph1 = gs.import_onnx(onnx.load(MODEL1)) for n in graph1.nodes: for cn in n.inputs: if cn.name[-1:] != 'a': cn.name = f'{cn.name}a' else: pass for cn in n.outputs: if cn.name[-1:] != 'a': cn.name = f'{cn.name}a' else: pass graph1_outputs = [o.name for o in graph1.outputs] print(f'graph1 outputs: {graph1_outputs}') onnx.save(gs.export_onnx(graph1), "graph1.onnx") graph2 = gs.import_onnx(onnx.load(MODEL2)) graph2_inputs = [] for n in graph2.nodes: for cn in n.inputs: if cn.name[-1:] != 'b': cn.name = f'{cn.name}b' else: pass for cn in n.outputs: if cn.name[-1:] != 'b': cn.name = f'{cn.name}b' else: pass graph2_inputs = [i.name for i in graph2.inputs] print(f'graph2 inputs: {graph2_inputs}') onnx.save(gs.export_onnx(graph2), "graph2.onnx") """ graph1 outputs: [ '317a', '852a', '870a', '897a', '836a' ] graph2 inputs: [ '0b', 'input.1b', 'input.13b', 'input.25b', 'input.37b' ] """ sg1 = so.graph_from_file('graph1.onnx') sg2 = so.graph_from_file('graph2.onnx') sg3 = so.merge( sg1, sg2, outputs=graph1_outputs, inputs=graph2_inputs ) so.graph_to_file(sg3, MODEL3)
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#!/usr/bin/python Users = ['mlh', 'foo', 'bar'] raw_input ('Enter your user name:') in Users
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/calculator.py
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"""CLI application for a prefix-notation calculator.""" from functools import reduce from arithmetic import (add, subtract, multiply, divide, square, cube, power, mod, ) while True: command = input("> ").split(" ") operator = command[0] if operator == "q": break else: if len(command) == 3: try: num1 = float(command[1]) num2 = float(command[2]) if operator == '+': print(add(num1, num2)) elif operator == '-': print(subtract(num1, num2)) elif operator == '*': print(multiply(num1, num2)) elif operator == '/': print(divide(num1, num2)) elif operator == 'pow': print(power(num1, num2)) elif operator == 'mod': print(mod(num1, num2)) else: print("Not a valid command") except ValueError: print("Please enter a number after the operator") elif len(command) == 2: try: num1 = float(command[1]) if operator == 'square': print(square(num1)) elif operator == 'cube': print(cube(num1)) else: print("Not a valid command") except ValueError: print("Please enter a number after the operator") elif len(command) > 3: numbers = [] for num in command[1:]: try: num = float(num) numbers.append(num) except ValueError: print('Please enter numbers after the operator') if operator == '+': print(reduce(add, numbers)) elif operator == '-': print(reduce(subtract, numbers)) elif operator == '*': print(reduce(multiply, numbers)) elif operator == '/': print(reduce(divide, numbers)) else: print("Not a valid command") else: print("Not a valid command")
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yl54/interview-problems
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/python/tree/contacts.py
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# # Complete the 'contacts' function below. # # The function is expected to return an INTEGER_ARRAY. # The function accepts 2D_STRING_ARRAY queries as parameter. # """ given a set of queries to add a string to the state and find a string implement these queries """ """ test cases different starting characters a single string multiple strings with the same prefixes multiple strings with the partially same prefixes multiple strings with the different prefixes """ """ ways to do this use a trie to store all of the combinations while building the trie, you can store the number of strings that the prefix is a substring of. this makes it so you don't have to recurse further once you get to the query prefix """ def contacts(queries): return optimizeTrie(queries) # -- trie node implementation -- # trie node class class Node: # init function def __init__(self): # dict to next trie node # keys: alphabet characters # values: next trie node self.children = {} # count of words it is a prefix of self.count = 0 # is word self.is_word = False # -- trie with no optimization -- # function for this def noOptimizeTrie(queries): # check if the input is illegal # hold results result = [] # create a root trie node that is empty root = Node() # for each query for q in queries: # if the command is add if q[0] == "add": # run the add function root = noOptimizeAdd(root, q[1]) # else if the command is find elif q[0] == "find": # run the find function result.append(noOptimizeFind(root, q[1])) # else: # illegal # return results return result # function to add to the trie node # input: # - root of trie # - string def noOptimizeAdd(root, input): # hold onto current pointer of trie # start at the root current = root # loop over characters of string in order for i in range(0, len(input)): # get the character of the character to the prefix array ch = input[i] # if the children array has no child there if ch not in current.children: # create a new trie node node = Node() # assign it to that array index current.children[ch] = node # traverse to the child at the index current = current.children[ch] # set is_word to true for the current pointer's trie node current.is_word = True # return trie root return root # function to find the number of matches in the trie # - root of trie # - string def noOptimizeFind(root, input): # hold onto current pointer of trie # start at the root current = root # hold onto matches of words found result = 0 # track if we need to keep continuing cont = True i = 0 # for i in range 0 to length of string while i < len(input): # get the character at the index ch = input[i] # if the children array does not have a trie node at the index if ch not in current.children: cont = False # break break # traverse to the child node current = current.children[ch] i += 1 if cont: # go through the rest of the children result += findAllChildren(current) # return number of matches return result # function for recursive traversal def findAllChildren(node): # -- illegal case -- # -- base case -- # hold onto result result = 0 # for all children for ch in node.children: # result += result += findAllChildren(node.children[ch]) # check if current one is a word if node.is_word: result += 1 # return number return result # -- trie with substring with count optimization -- def optimizeTrie(queries): # check if the input is illegal # hold results result = [] # create a root trie node that is empty root = Node() # for each query for q in queries: # if the command is add if q[0] == "add": # run the add function _, root = optimizeAdd(root, q[1], 0) # else if the command is find elif q[0] == "find": # run the find function result.append(optimizeFind(root, q[1])) # else: # illegal # return results return result # function to add to the trie node # this will need to be a recursive function to return results up the trie # input: # - root of trie # - string # - index of string currently evaluated # # return: # - number of subwords def optimizeAdd(node, input, index): # -- illegal case -- # check if index is out of bounds for string if index >= len(input): # return 0 return 0, node # -- current case -- #print(index) # get the index of the character to the prefix array ch = input[index] # hold onto whether a new child was created new_child = False next_node = None # if the children array has no child there if ch not in node.children: # create a new trie node next_node = Node() # assign it to that array index node.children[ch] = next_node else: next_node = node.children[ch] # result = recurse to child array and index + 1 result, next_node = optimizeAdd(next_node, input, index + 1) # check if the current node is the last index if index == len(input) - 1: # set the trie node is word to true next_node.is_word = True result += 1 # set the current trie node word count to result next_node.count += result # -- return result -- # return result return result, node # function to find the number of matches in the trie # - root of trie # - string def optimizeFind(root, input): # hold onto current pointer of trie # start at the root current = root # hold onto index of string i = 0 # while the index is less than the string length while i < len(input): # get the character at the index ch = input[i] # if the children array does not have a trie node at the index if ch not in current.children: # break break # traverse to the child node current = current.children[ch] i += 1 # check if it reached the end of the input string if i == len(input): # return trie number of subwords return current.count # return 0 return 0
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adamLange/freecadutil
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/PyOCCLevelUtils.py
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[]
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from OCC.Geom import Geom_BSplineSurface, Handle_Geom_BSplineSurface from OCC.TColgp import TColgp_Array2OfPnt from OCC.TColStd import TColStd_Array1OfReal, TColStd_Array2OfReal, TColStd_Array1OfInteger from OCC.gp import gp_Vec, gp_Trsf, gp_Pnt from OCC.BRepBuilderAPI import BRepBuilderAPI_MakeFace import numpy as np from OCCUtils.edge import Edge import OCCUtils class NurbsSurfaceBase: def __init__(self,**kwargs): self.uDegree = 2 self.vDegree = 2 self.uPeriodic = False self.vPeriodic = False self.uStartMultiplicity = 3 self.vStartMultiplicity = 3 self.uEndMultiplicity = 3 self.vEndMultiplicity = 3 def getPoles(self): poles = [] poleSequence = [] for sketch in self.sketchList: points = [] geo = [] for G in sketch.Geometry: if not G.Construction: geo.append(G) vec = sketch.Placement.multVec(geo[0].StartPoint) vec = gp_Pnt(vec.x,vec.y,vec.z) points.append(vec) poleSequence.append(vec) for line in geo: vec = sketch.Placement.multVec(line.EndPoint) vec = gp_Pnt(vec.x,vec.y,vec.z) points.append(vec) poleSequence.append(vec) poles.append(points) n_u = len(poles[0]) n_v = len(poles) return (poleSequence,n_u,n_v) def toPyOCC(self,dbg=False): poles,n_u,n_v = self.getPoles() Poles = TColgp_Array2OfPnt(1,n_u,1,n_v) for n,i in enumerate(poles): iu = n%n_u iv = n/n_u Poles.SetValue(iu+1,iv+1,i) weights = [1]*(n_u*n_v) Weights = TColStd_Array2OfReal(1,n_u,1,n_v) for n,i in enumerate(weights): iu = n%n_u iv = n/n_u Weights.SetValue(iu+1,iv+1,i) if not self.uPeriodic: n_increasing = (n_u + self.uDegree + 1) - (self.uStartMultiplicity-1) - (self.uEndMultiplicity-1) else: n_increasing = n_u + 1 uknots = [] uknots.extend(np.linspace(0,1.0,n_increasing).tolist()) UKnots = TColStd_Array1OfReal(1,len(uknots)) for n,i in enumerate(uknots): UKnots.SetValue(n+1,i) l = [self.uStartMultiplicity] m = [1]*(len(uknots)-2) r = [self.uEndMultiplicity] m.extend(r) l.extend(m) uMults = l UMults = TColStd_Array1OfInteger(1,len(uMults)) for n,i in enumerate(uMults): UMults.SetValue(n+1,i) if not self.vPeriodic: n_increasing = (n_v + self.vDegree + 1) - (self.vStartMultiplicity-1) - (self.vEndMultiplicity-1) else: n_increasing = n_v + 1 vknots = [] vknots.extend(np.linspace(0,1.0,n_increasing).tolist()) VKnots = TColStd_Array1OfReal(1,len(vknots)) for n,i in enumerate(vknots): VKnots.SetValue(n+1,i) l = [self.vStartMultiplicity] m = [1]*(len(vknots)-2) r = [self.vEndMultiplicity] m.extend(r) l.extend(m) vMults = l VMults = TColStd_Array1OfInteger(1,len(vMults)) for n,i in enumerate(vMults): VMults.SetValue(n+1,i) if dbg: return {'poles':poles,'weights':weights,'uknots':uknots,'vknots':vknots,'umults':uMults,'vmults':vMults,'udegree':self.uDegree,'vdegree':self.vDegree} #return (Poles,Weights,UKnots,VKnots,UMults,VMults,self.UDegree,self.vDegree,UPeriodic,VPeriodic) return Geom_BSplineSurface(Poles,Weights,UKnots,VKnots,UMults,VMults,self.uDegree,self.vDegree,self.uPeriodic,self.vPeriodic) def TopoDS_Face(self): surf = self.toPyOCC() hsurf = Handle_Geom_BSplineSurface(surf) facemaker = BRepBuilderAPI_MakeFace() facemaker.Init(hsurf,True,0.001) return facemaker.Face() class RibMaker(NurbsSurfaceBase): def __init__(self,pointsList,l0,l1,l2,**kwargs): """ pointsList is a list of gp_pnt l0, l1, and l2 are TopoDS_Edge """ NurbsSurfaceBase.__init__(self,**kwargs) self.pts = pointsList self.l0 = Edge(l0) self.l1 = Edge(l1) self.l2 = Edge(l2) self.a = (self.l0.curve.Value(0)).as_vec() r1, r2, r3 = self.getRVecs(0) A = np.matrix([[r1.X(),r1.Y(),r1.Z()], [r2.X(),r2.Y(),r2.Z()], [r3.X(),r3.Y(),r3.Z()] ],dtype='float64') self.AI = A.I def getRVecs(self,t): l0t = (self.l0.curve.Value(t)).as_vec() l1t = (self.l1.curve.Value(t)).as_vec() l2t = (self.l2.curve.Value(t)).as_vec() r1 = l1t - l0t r2 = l2t - l0t r3 = gp_Vec(r1.XYZ()) r3.Cross(r2) r3 = r3/r3.Magnitude() r4 = gp_Vec(r1.XYZ()) r4.Cross(r3) r4 = r4/r4.Magnitude() # unit vector in plane and perpenducular # to r1 r2 = r4*(r4.Dot(r2)) # This is the r2 you are looking for return r1, r2, r3 def T(self,t): """ Get the transformation matrix, T at parameter t. """ r1,r2,r3 = self.getRVecs(t) B = np.matrix([[r1.X(),r1.Y(),r1.Z()], [r2.X(),r2.Y(),r2.Z()], [r3.X(),r3.Y(),r3.Z()] ],dtype='float64') return self.AI*B def getSection(self,t): M = self.T(t) trsf_pts = [] b = (self.l0.curve.Value(t)).as_vec() for pnt in self.pts: pnt = pnt.as_vec() - self.a pnt = np.matrix([pnt.X(),pnt.Y(),pnt.Z()],dtype='float64').T trsf_pt = (pnt.T * M).T p = gp_Pnt((gp_Vec(trsf_pt[0,0],trsf_pt[1,0],trsf_pt[2,0]) + b).XYZ()) trsf_pts.append(p) return trsf_pts def getSections(self,tMin,tMax,numSections): sections = [] for t in np.linspace(tMin,tMax,numSections): sections.append(self.getSection(t)) return sections def getPoles(self): poles = [] sections = self.getSections(0,1.0,10) n_u = len(sections[0]) n_v = len(sections) for row in sections: poles.extend(row) return (poles,n_u,n_v) from OCC.Geom import Geom_Plane from OCC.GeomAPI import GeomAPI_IntCS class RibMakerL0Normal(RibMaker): def getRVecs(self,t): p0 = gp_Pnt() vec = gp_Vec() self.l0.curve.D1(t,p0,vec) plane = Geom_Plane( p0, vec.as_dir() ) intcs1 = GeomAPI_IntCS(self.l1.curve.GetHandle(),plane.GetHandle()) intcs2 = GeomAPI_IntCS(self.l2.curve.GetHandle(),plane.GetHandle()) u1, v1, w1 = intcs1.Parameters(1) u2, v2, w2 = intcs2.Parameters(1) p1 = self.l1.curve.Value(w1) p2 = self.l2.curve.Value(w2) r1 = p1.as_vec() - p0.as_vec() r2 = p2.as_vec() - p0.as_vec() r3 = gp_Vec(r1.XYZ()) r3.Cross(r2) r3 = r3/r3.Magnitude() r4 = gp_Vec(r1.XYZ()) r4.Cross(r3) r4 = r4/r4.Magnitude() r2 = r4*(r4.Dot(r2)) return r1, r2 ,r3 class RibMakerTranslatePlane(RibMaker): def __init__(self,pointsList,l0,l1,l2,**kwargs): NurbsSurfaceBase.__init__(self,**kwargs) self.pts = pointsList self.l0 = Edge(l0) self.l1 = Edge(l1) self.l2 = Edge(l2) self.a = (self.l0.curve.Value(0)).as_vec() p0 = self.l0.curve.Value(0).as_vec() p1 = self.l1.curve.Value(0).as_vec() p2 = self.l2.curve.Value(0).as_vec() r1 = p1 - p0 r2 = p2 - p0 r3 = gp_Vec(r2.XYZ()) r3.Cross(r1) r3 = r3/r3.Magnitude() r4 = gp_Vec(r1.XYZ()) r4.Cross(r3) r4 = r4/r4.Magnitude() r2 = r4*(r4.Dot(r2)) self.planeNormal = r3.as_dir() A = np.matrix([[r1.X(),r1.Y(),r1.Z()], [r2.X(),r2.Y(),r2.Z()], [r3.X(),r3.Y(),r3.Z()] ],dtype='float64') self.AI = A.I def getRVecs(self,t): p0 = self.l0.curve.Value(t) plane = Geom_Plane(p0, self.planeNormal) intcs1 = GeomAPI_IntCS(self.l1.curve.GetHandle(),plane.GetHandle()) intcs2 = GeomAPI_IntCS(self.l2.curve.GetHandle(),plane.GetHandle()) u1, v1, w1 = intcs1.Parameters(1) u2, v2, w2 = intcs2.Parameters(1) p1 = self.l1.curve.Value(w1) p2 = self.l2.curve.Value(w2) r1 = p1.as_vec() - p0.as_vec() r2 = p2.as_vec() - p0.as_vec() r3 = gp_Vec(r2.XYZ()) r3.Cross(r1) r3 = r3/r3.Magnitude() r4 = gp_Vec(r1.XYZ()) r4.Cross(r3) r4 = r4/r4.Magnitude() r2 = r4*(r4.Dot(r2)) return r1, r2 ,r3 class SectionProjectionSurface(NurbsSurfaceBase): from OCC.BRepProj import BRepProj_Projection from OCC.BRepIntCurveSurface import BRepIntCurveSurface_Inter from OCC.gp import gp_Lin,gp_Dir,gp_Vec import pdb def __init__(self,point,rootWire,face1,face2,**kwargs): """ @param point gp_Pnt @param rootWire TopoDS_Wire @param face1 TopoDS_Face @param face2 TopoDS_Face """ #NurbsSurfaceBase.__init__(self) self.basePoint = point self.rootWire = rootWire self.face1 = face1 self.face2 = face2 self.uDegree = 2 self.vDegree = 1 self.uPeriodic = True self.vPeriodic = False self.uStartMultiplicity = 1 self.vStartMultiplicity = 2 self.uEndMultiplicity = 1 self.vEndMultiplicity = 2 def getPoles(self): poles = [] poleSequence = [] rootPoleSequence = [] tipPoleSequence = [] rootBSpline = OCCUtils.edge.Edge(OCCUtils.Topo(self.rootWire).edges().next()).adaptor.BSpline().GetObject() inter = self.BRepIntCurveSurface_Inter() for i in range(rootBSpline.NbPoles()): currentRootPole = rootBSpline.Pole(i+1) vec = self.gp_Vec(self.basePoint,currentRootPole) direction = self.gp_Dir(vec) line = self.gp_Lin(self.basePoint,direction) inter.Init(self.face1,line,1e-6) rootPoleSequence.append(inter.Pnt()) inter.Init(self.face2,line,1e-6) tipPoleSequence.append(inter.Pnt()) poleSequence.extend(rootPoleSequence) poleSequence.extend(tipPoleSequence) n_u = rootBSpline.NbPoles() n_v = 2 return (poleSequence,n_u,n_v) """ TODO make classes inhereting from RibMaker that A. has a plane which is always parallel to the plane defined by l0(0) l1(0) l2(0) B. has a plane which is always perpendicular to l0(t) C. has a plane which revolves around l0 - For A B and C, a handy oce class will be GeomAPI_IntCS """
UTF-8
Python
false
false
11,035
py
16
PyOCCLevelUtils.py
15
0.54599
0.51527
0
384
27.736979
162
dsr373/phase-locked-loops
3,504,693,336,795
12301e239c0ce1a52eef9fda7b5beb95097bac87
40b46d370ec4c4763627566df36f6d723b7a33be
/python/analysis/vco_freqs.py
d2b8122faa6a4d2020ac83f186f53111a4b6a721
[]
no_license
https://github.com/dsr373/phase-locked-loops
fdb6e14e9f5711e8e33c3a510f07073dff69f581
3e89b8c84de6f9af1f3b6b3d7fac8d5e950342c2
refs/heads/master
2021-02-07T11:46:07.742683
2018-10-22T20:26:13
2018-10-22T20:26:13
244,021,483
0
0
null
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import numpy as np import matplotlib.pyplot as plt import matplotlib import csv from ..measurement.utils.gui_utils import def_input FONTSIZE = 20 # the measurements are dictionaries from the expected_v to arrays of the measured values v_in = {} f_out = {} results = {} with open('data/vco/vco_R1M.tsv') as fin: reader = csv.reader(fin, delimiter='\t') reader.next() # skip first row - those are the headings for row in reader: # construct the measurements dict exp_v = float(row[0]) v_A = float(row[2]) f_B = float(row[4]) if exp_v in v_in.keys(): v_in[exp_v].append(v_A) f_out[exp_v].append(f_B) else: v_in[exp_v] = [v_A] f_out[exp_v] = [f_B] xs, ys, sigX, sigY = [], [], [], [] for exp_v in v_in.keys(): xs.append(np.mean(v_in[exp_v])) ys.append(np.mean(f_out[exp_v])) sigX.append(np.std(v_in[exp_v])) sigY.append(np.std(f_out[exp_v])) fig, ax = plt.subplots(figsize=(12, 8)) matplotlib.rcParams.update({'errorbar.capsize': 5}) ax.errorbar(xs, ys, yerr=sigY, xerr=sigX, fmt='+', markersize=8) ax.set_title('Output of VCO', fontsize=FONTSIZE) ax.set_xlabel('Input Voltage (V)', fontsize=FONTSIZE) ax.set_ylabel('Output Frequency (Hz)', fontsize=FONTSIZE) ax.tick_params(labelsize=FONTSIZE-4) ax.set_xlim(left=-0.1, right=5.1) plt.show() saveopt = def_input('Save figure? (y/n)', default='n') if saveopt == 'y': figname = raw_input('file name: ') fig.savefig('docs/%s.pdf' % figname, bbox_inches='tight')
UTF-8
Python
false
false
1,549
py
32
vco_freqs.py
30
0.622337
0.612008
0
53
28.226415
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humabilgin/2048-Game-With-Expectimax-Algorithm
17,162,689,326,044
8363c21ac5db695171ee372f6962a4ed9b777368
7cb3ae5a61bef09ccd6308a4b2cae422a7455943
/2048-expectimax-ai-master/expectimax.py
b5031d73c916b0764c0017d358bae3b93e061463
[]
no_license
https://github.com/humabilgin/2048-Game-With-Expectimax-Algorithm
4f0419bc6c44a0ee31b1cc3a492089cd38a5685e
f79f71b3910f0102c4fd6eca0688a88efeb0b8b8
refs/heads/main
2023-06-29T19:08:35.527415
2021-07-30T09:32:13
2021-07-30T09:32:13
391,004,572
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import math import time import numpy as np UP, DOWN, LEFT, RIGHT = range(4) class Expectimax(): def get_move(self, board): best_move, _ = self.maximize(board) return best_move #degerlendirme fonksiyonu def evaluationFunction(self, board, n_empty): grid = board.grid empty_w = 50000 # bos karelerin saglayacagi fayda degeri loss_w = 2 # kareler arasindaki farkin verecegi zarar degerinin alıncagi üstel deger utility = 0 #fayda loss = 0 #zarar p_grid = np.sum(np.power(grid, 2)) # grid 4*4luk bir matrix. Hepsinin ikinci kuvveti alınıp toplanıyor. s_grid = np.sqrt(grid) # gridin kök alınmış hali # kök alınmış matrisin yan yana olan satır ve sütunlarının farklarının mutlak değerleri toplanıyor loss = -np.sum(np.abs(s_grid[::,0] - s_grid[::,1])) -np.sum(np.abs(s_grid[::,1] - s_grid[::,2])) - np.sum(np.abs(s_grid[::,2] - s_grid[::,3])) loss += -np.sum(np.abs(s_grid[0,::] - s_grid[1,::])) -np.sum(np.abs(s_grid[1,::] - s_grid[2,::])) -np.sum(np.abs(s_grid[2,::] - s_grid[3,::])) #negatif bir sayı oluşur loss_u = loss ** loss_w # kareler arasindaki farkin verecegi toplam zarar degeri empty_u = n_empty * empty_w # bos karelerin verecegi toplam utility degeri p_grid_u = p_grid utility += (p_grid + empty_u + loss_u) #utility toplami icin bos karelerin faydasi, smoothness degerlerinin verdigi zarar ve matrixin #değerlerinin buyuklugu toplanir. return (utility, empty_u, loss_u, p_grid_u) # subtreelerden gelen degerlerin en buyugunun secildiği fonksiyon def maximize(self, board, depth = 0): moves = board.get_available_moves() #yapilabilecek hamleler alinir moves_boards = [] for m in moves: m_board = board.clone() # o anki hamle uygulanırsa olusacak boardu olusturacagiz m_board.move(m) # move fonksiyonu ile olusturuyoruz moves_boards.append((m, m_board)) # tüm hamlelerin boardlarının tutuldugu listeye ekliyoruz best_utility = (float('-inf'),0,0,0) # tüm utilityler arasında en iyi olani tutulacak best_direction = None for mb in moves_boards: utility = self.chance(mb[1], depth + 1) # her hamlenin tahtasinin chance degeri hesaplanir if utility[0] >= best_utility[0]: # bu degerlerin en buyugu secilir best_utility = utility best_direction = mb[0] return best_direction, best_utility # en iyi hamle donulur # bir sonraki elde yapılabilecek hamlelerin optimal olmadigi kabul edilir ve her subtreenin ortalamasi alinir. def chance(self, board, depth = 0): empty_cells = board.get_available_cells() # bos hucreler listesi noOfEmpty = len(empty_cells) # bos hucre sayisi #if n_empty >= 7 and depth >= 5: # return self.eval_board(board, n_empty) if noOfEmpty >= 6 and depth >= 3: # bos hucre sayisi 6dan buyukse ve derinlik 3ten buyukse return self.evaluationFunction(board, noOfEmpty) # utility degerlerini dondur if 6 > noOfEmpty >= 0 and depth >= 5: # bos hucre sayisi 6-0 arasindaysa ve derinlik 5ten buyukse return self.evaluationFunction(board, noOfEmpty) # utility degerlerini dondur # bos hucre sayisi arttıkca derinlik artıyor. Bunun sebebi oyunun zorlasmasıdır. Bir diger sebebi ise # oyun kolayken buyuk bir derinlik vermenin sureyi uzatacak olmasidir. Bu yüzden zorlastikca derinlik artıyor. if noOfEmpty == 0: _, utility = self.maximize(board, depth + 1) #yon ignore edilir return utility possible_tiles = [] # her el yeni bir sayi tahtaya eklenir chanceOf2 = (.95 * (1 / noOfEmpty)) # random olarak 2 gelme olasiligi daha cok chanceOf4 = (.05 * (1 / noOfEmpty)) # random olarak 4 gelme olasiligi daha az for empty_cell in empty_cells: possible_tiles.append((empty_cell, 2, chanceOf2)) possible_tiles.append((empty_cell, 4, chanceOf4)) totalUtility = [0, 0, 0, 0] for t in possible_tiles: t_board = board.clone() t_board.insert_tile(t[0], t[1]) # 4 ya da 2 eklenir _, utility = self.maximize(t_board, depth + 1) for i in range(4): totalUtility[i] += utility[i] * t[2] return tuple(totalUtility)
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py
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expectimax.py
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0.612104
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102
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bruecksen/pumpwerk
16,750,372,463,222
a707df1e0c691e9a5e4648cc6f294690602e2191
491bd7a305859b380d777f3420b099d4790ca807
/pumpwerk/food/migrations/0001_initial.py
bcad2f3a3228d1e92fd0424890e124214bb8d120
[ "MIT" ]
permissive
https://github.com/bruecksen/pumpwerk
65103eb741c49691b203b419e9752dad996fd089
e76df6bedee3e338b10106565f0f6139fa63994c
refs/heads/master
2023-05-31T20:59:24.721234
2022-11-16T15:20:36
2022-11-16T15:20:36
251,088,621
0
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MIT
false
2023-05-10T01:56:30
2020-03-29T17:17:49
2022-10-21T13:01:27
2023-05-10T01:56:29
2,076
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Python
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# Generated by Django 2.2.6 on 2020-02-25 20:23 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='Bill', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('month', models.PositiveSmallIntegerField(choices=[(1, 'January'), (2, 'February'), (3, 'March'), (4, 'April'), (5, 'May'), (6, 'June'), (7, 'July'), (8, 'August'), (9, 'September'), (10, 'October'), (11, 'November'), (12, 'December')])), ('year', models.PositiveIntegerField()), ('days_in_month', models.PositiveIntegerField(editable=False)), ('terra_daily_rate', models.DecimalField(decimal_places=2, max_digits=8)), ('users', models.ManyToManyField(to=settings.AUTH_USER_MODEL)), ], options={ 'unique_together': {('month', 'year')}, }, ), migrations.CreateModel( name='UserBill', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('attendance_days', models.PositiveIntegerField()), ('total', models.DecimalField(decimal_places=2, max_digits=8)), ('has_payed', models.BooleanField(default=False)), ('is_notified', models.BooleanField(default=False)), ('bill', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='food.Bill')), ], ), ]
UTF-8
Python
false
false
1,827
py
70
0001_initial.py
64
0.568692
0.550082
0
42
42.5
255
JasonOwenss/pyforum
7,670,811,592,752
9cdb94bd59321d3cc221f1d617c3f79da0d30656
e42052c97a2026f51a129079780f4ad1c3d50e31
/pyforum/Forum_project/admin.py
2ff1f603ee64a4d3c1871fdc27bcd930e6db1f43
[]
no_license
https://github.com/JasonOwenss/pyforum
20c79041d6a2d2280b1283d74031bacbf9b26aca
bec7b483eb1b76caaea8651a384d6983e23cf9e1
refs/heads/master
2020-04-11T06:42:17.957727
2018-12-15T05:54:20
2018-12-15T05:54:20
161,588,835
0
0
null
null
null
null
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null
null
null
null
null
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from django.contrib import admin from .models import Forum,Comment admin.site.register(Forum) admin.site.register(Comment) # Register your models here.
UTF-8
Python
false
false
161
py
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admin.py
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0.770186
0.770186
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eggplantisme/NetworkEvolution
18,571,438,608,043
9662915257f1029593beea63d9d297e7a319f2f7
dfbbd8bbf0d364475ab3eee67ba858c9604af4ff
/_EdgeSort_.py
ca4a5c8b7357f1997ed36c647ddf6c48fdf0d2cb
[]
no_license
https://github.com/eggplantisme/NetworkEvolution
3dfaffa8a4c2558235084e7dab350caaef2a58b8
fcb01afd52f8f0726af9cca2f260da0e571f723f
refs/heads/master
2020-11-27T11:25:11.592186
2019-12-21T12:04:17
2019-12-21T12:04:17
221,919,968
0
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null
null
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import random import numpy as np import math import matplotlib.pyplot as plt import matplotlib as mpl import time import pickle import os from scipy import optimize from getEdgeTime import get_all_edge_time from getFeatureJudge import get_feature_dict from getNet import get_mat import _EnsembleJudge_ import getEdgePair from __Configuration import * class EdgeSort: # 排序 + Δk-k图验证BA理论 def __init__(self, net_name): global TRAIN_EDGE_RATIO TRAIN_EDGE_RATIO = 0.4 self.net_name = net_name self.all_days = dict() # {'real':[0, 0, ...], 'random ':[], ' } 三个时间列表 + 边列表 file_name = ".\\sort\\" + net_name + "_" + str(TRAIN_EDGE_RATIO) + ".pkl" if os.path.exists(file_name) is False: self.base_train_edges = None self.ensemble_train_edges = None self.test_edges = None self.edges, self.real_days = self.get_sort_edges() self.shuffle_edges = list(self.edges) random.shuffle(self.shuffle_edges) self.random_days = self.random_sort() # edges 对应的随机排序后的时间 self.sort_days = self.vote_sort() # edges 对应的使用ensemble方法排序后的时间 with open(file_name, 'wb') as file: self.all_days['real'] = self.real_days # [1, 1, 1, 1, 2, 2, 3] self.all_days['random'] = self.random_days # [..., 0, ..., 1, ...] self.all_days['ensemble'] = self.sort_days # [..., 0, ..., 1, ...] self.all_days['edges'] = self.edges pickle.dump(self.all_days, file) else: with open(file_name, 'rb') as file: self.all_days = pickle.load(file) self.real_days = self.all_days['real'] self.random_days = self.all_days['random'] self.sort_days = self.all_days['ensemble'] self.edges = self.all_days['edges'] def get_sort_edges(self): """ 获取两个训练边集以及要排序的测试边集,并找到测试边集的真实顺序 :return: """ self.base_train_edges, self.ensemble_train_edges, self.test_edges = getEdgePair.ensemble_get_train_test_edges( TRAIN_EDGE_RATIO, self.net_name) edge_days = get_all_edge_time(self.net_name) edges = [] days = [] sorted_edge_days = sorted(set(edge_days.values())) for i in sorted_edge_days: i_day_edges = [edge for edge in edge_days.keys() if edge_days[edge] == i] print("i_day_edges:", i_day_edges.__len__()) edges.extend(i_day_edges) days.extend([sorted_edge_days.index(i)] * i_day_edges.__len__()) return edges, days def random_sort(self): shuffle_edges_copy = list(self.shuffle_edges) # 深拷贝 edges_l = shuffle_edges_copy.__len__() # 冒泡排序 for i in range(edges_l): for j in range(i): x = random.random() if x < 0.5: new_edge_judge = 1 else: new_edge_judge = -1 if new_edge_judge > 0: temp = shuffle_edges_copy[i] shuffle_edges_copy[j + 1:i + 1] = shuffle_edges_copy[j:i] shuffle_edges_copy[j] = temp break else: pass days = [0] * edges_l for edge in shuffle_edges_copy: sort_day = shuffle_edges_copy.index(edge) real_index = self.edges.index(edge) days[real_index] = sort_day print("random sort finished!") return days def vote_sort(self): shuffle_edges_copy = list(self.shuffle_edges) # 深拷贝 edge_score = dict(zip(shuffle_edges_copy, [0] * len(shuffle_edges_copy))) # 每条边的投票分数 # ensemble 判断 获取模型 judge_methods = [BEST_SINGLE, NODE2VEC_PAIR_NN, UNION_PAIR_NN] ensemble = _EnsembleJudge_.EnsembleJudge(self.net_name, self.base_train_edges, self.test_edges, judge_methods, self.ensemble_train_edges) model = ensemble for edge1 in shuffle_edges_copy: _edge2s = shuffle_edges_copy[shuffle_edges_copy.index(edge1):] for edge2 in _edge2s: # 根据rule指标判断新旧 judge = model.get_ep_judge((edge1, edge2)) if judge == 1: edge_score[edge1] += 1 else: edge_score[edge2] += 1 # 按value排序 sorted_edge_score_list = sorted(edge_score.items(), key=lambda item: item[1]) sorted_edge_score = dict() for tuple_score in sorted_edge_score_list: sorted_edge_score[tuple_score[0]] = tuple_score[1] # 构造每条边的位置列表 sorted_edge = list(sorted_edge_score.keys()) days = [0] * sorted_edge.__len__() for edge in sorted_edge: sort_day = sorted_edge.index(edge) real_index = self.edges.index(edge) days[real_index] = sort_day print("vote sort finished!") return days def plot_sort(self): random_days = np.array(self.random_days) real_days = np.array(self.real_days) sort_days = np.array(self.sort_days) # 真实情况 plt.figure(figsize=(10, 5)) plt.subplot(3, 1, 1) plt.yticks([]) plt.title(self.net_name + ' real times') plt.imshow(real_days[np.newaxis, :], aspect='auto', cmap=mpl.cm.cool) cb = plt.colorbar() cb.set_label("time") # 随机判定排序 rn_auc = self.auc_after_sort(random_days, real_days) # 统一排序后和排序前的时间粒度(即真实某时刻有多少条边,排序后也如此) for i in range(real_days.size): pos = np.where(random_days == i) random_days[pos] = real_days[i] rn_corr = round(np.corrcoef(random_days, real_days)[0, 1], 3) plt.subplot(3, 1, 2) plt.yticks([]) plt.title('random sort, correlation coefficient:' + str(rn_corr) + " Accuracy:" + str(rn_auc)) plt.imshow(random_days[np.newaxis, :], aspect='auto', cmap=mpl.cm.cool) cb = plt.colorbar() cb.set_label("time") # ensemble判断 vote排序 vote_auc = self.auc_after_sort(sort_days, real_days) # 统一排序后和排序前的时间粒度(即真实某时刻有多少条边,排序后也如此) for i in range(real_days.size): pos = np.where(sort_days == i) sort_days[pos] = real_days[i] vote_corr = round(np.corrcoef(sort_days, real_days)[0, 1], 3) plt.subplot(3, 1, 3) plt.yticks([]) plt.title( 'vote sort by ensemble, correlation coefficient:' + str(vote_corr) + " Accuracy:" + str(vote_auc)) plt.imshow(sort_days[np.newaxis, :], aspect='auto', cmap=mpl.cm.cool) cb = plt.colorbar() cb.set_label("time") plt.tight_layout() plt.savefig("./Result/sort/" + self.net_name + "_sort.png", dpi=600) plt.show() @staticmethod def auc_after_sort(_sorted, _real): diff_time_ep_num = 0 right_ep_num = 0 for edge1 in range(len(_real)): for edge2 in range(edge1, len(_real)): if _real[edge1] != _real[edge2]: diff_time_ep_num += 1 if (_real[edge2] > _real[edge1]) == (_sorted[edge2] > _sorted[edge1]): right_ep_num += 1 return round(right_ep_num / diff_time_ep_num, 3) def ba_validation(self): plt.figure(figsize=(30, 10)) # 按第一个真实时间点来分before_edges和after_edges first_real_day = min(self.real_days) real_before_edges = [] for edge in self.edges: i = self.edges.index(edge) if self.real_days[i] <= first_real_day: real_before_edges.append(edge) before_nodes_degree = self.get_node_degree_from_edges(real_before_edges) after_nodes_degree = self.get_node_degree_from_edges(self.edges) plt.subplot(1, 3, 1) self.plot_deltak_k(before_nodes_degree, after_nodes_degree, "real") # 按第一个真实时间点来分的before_edges数量来分vote_sort_edges vote_sort_before_edges = [] for edge in self.edges: i = self.edges.index(edge) if self.sort_days[i] < len(real_before_edges): vote_sort_before_edges.append(edge) vote_sort_before_node_degree = self.get_node_degree_from_edges(vote_sort_before_edges) plt.subplot(1, 3, 2) self.plot_deltak_k(vote_sort_before_node_degree, after_nodes_degree, "sort") # vote_sort_edges 一半一半来分 half_vote_sort_before_edges = [] for edge in self.edges: i = self.edges.index(edge) if self.sort_days[i] < (len(self.edges) / 2): half_vote_sort_before_edges.append(edge) half_vote_sort_before_node_degree = self.get_node_degree_from_edges(half_vote_sort_before_edges) plt.subplot(1, 3, 3) self.plot_deltak_k(half_vote_sort_before_node_degree, after_nodes_degree, "half_sort") plt.savefig("./Result/BA_validation/" + self.net_name + "_scatter.png", dpi=600) plt.show() @staticmethod def line(x, a, b): return a * x + b def plot_deltak_k(self, before_nodes_degree, after_nodes_degree, mode): # TODO 散点图拟合直线 k_list = [] delta_k_list = [] for node in before_nodes_degree: k = before_nodes_degree[node] delta_k = after_nodes_degree[node] - before_nodes_degree[node] if k > 50 or delta_k > 50: pass else: k_list.append(k) delta_k_list.append(delta_k) # 拟合 a, b = optimize.curve_fit(self.line, k_list, delta_k_list)[0] x1 = np.arange(0, max(k_list), 0.01) y1 = a * x1 + b print("A is", a) # 绘图 plt.title("Average Δk - k for net " + self.net_name + ": " + mode + ". a is " + str(round(a, 3)), fontsize=25, fontweight='bold') plt.xlabel("k", fontsize=15, fontweight='bold') plt.ylabel("Δk", fontsize=15, fontweight='bold') plt.scatter(k_list, delta_k_list) plt.plot(x1, y1, "r") plt.tight_layout() # # 获取k_Δk数据 # k_delta_k = dict() # k_node_num = dict() # for node in before_nodes_degree: # k = before_nodes_degree[node] # delta_k = after_nodes_degree[node] - before_nodes_degree[node] # if k in k_delta_k.keys(): # k_delta_k[k] += delta_k # k_node_num[k] += 1 # else: # k_delta_k[k] = delta_k # k_node_num[k] = 1 # for k in k_delta_k.keys(): # k_delta_k[k] = k_delta_k[k] / k_node_num[k] # 取均值 # # 绘图 # sorted_k_delta_k = dict() # for k in sorted(k_delta_k): # sorted_k_delta_k[k] = k_delta_k[k] # plt.title("Average Δk - k for net " + self.net_name + ": " + mode, fontsize=25, fontweight='bold') # plt.xlabel("k", fontsize=15, fontweight='bold') # plt.ylabel("Δk", fontsize=15, fontweight='bold') # plt.plot(list(sorted_k_delta_k.keys()), list(sorted_k_delta_k.values()), "-*") # plt.tight_layout() @staticmethod def get_node_degree_from_edges(edges): """ 根据 [边对列表] 获取 {节点度的词典} :param edges: :return: """ node_degree = dict() for edge in edges: if edge[0] not in node_degree.keys(): node_degree[edge[0]] = 1 else: node_degree[edge[0]] += 1 if edge[1] not in node_degree.keys(): node_degree[edge[1]] = 1 else: node_degree[edge[1]] += 1 return node_degree def main(): net_names = protein_net_names for net_name in net_names: edge_sort = EdgeSort(net_name) # edge_sort.plot_sort() edge_sort.ba_validation() if __name__ == '__main__': main()
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info9117/BlueGarden_Project
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91754e5c7252806a723e7e060a7a8b2beb0e72ad
/models/unit.py
bb62845953b54bb5e2af553d5c7d4e3fa996f315
[]
no_license
https://github.com/info9117/BlueGarden_Project
e0ce7f0ff0b68eed6297abc25c7405d383665579
b85f0a7ba610e580f9c2da3d25b69421cd9373fe
refs/heads/master
2020-12-11T03:34:19.589083
2016-06-02T03:55:49
2016-06-02T03:55:49
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2016-05-30T10:35:45
2016-04-18T09:19:07
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JavaScript
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from shared import db class Unit(db.Model): __tablename__ = 'units' id = db.Column('id', db.Integer, primary_key=True) name = db.Column('name', db.String(10), unique=True, nullable=False) def __init__(self, name): self.name = name
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/posts/views.py
cbefd69c0c9841f0d1946e3f24361e80ac64bda3
[]
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https://github.com/KristianHolsheimer/blog
aa8712b0dac4073cb2a49447d43b76a7069254d7
f9b932e07018a65dc85759d15d1dff83a5f0d903
refs/heads/master
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2020-07-07T01:35:53
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import logging from django.shortcuts import render, get_object_or_404 from .models import Post, Tag logger = logging.getLogger(__name__) def log_request(view): def view_that_also_logs(request, *args, **kwargs): logger.debug('request.__dict__', extra={'request': request.__dict__}) return view(request, *args, **kwargs) return view_that_also_logs @log_request def index(request): posts_ds = Post.objects.filter(is_live=True, category=Post.CATEGORY_DS).order_by('-pub_date')[:5] posts_eng = Post.objects.filter(is_live=True, category=Post.CATEGORY_ENG).order_by('-pub_date')[:5] tags = Post.all_live_tags() context = {'posts_ds': posts_ds, 'posts_eng': posts_eng, 'tags': tags} return render(request, 'posts/index.html', context) @log_request def post(request, post_name): logger.debug(dict(request)) post_obj = get_object_or_404(Post, name=post_name, is_live=True) return render(request, 'posts/post_site.html', {'post': post_obj}) @log_request def tag(request, tag_name): logger.debug(dict(request)) tag_obj = get_object_or_404(Tag, name=tag_name) return render(request, 'posts/tag_site.html', {'tag': tag_obj})
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kojicz983/talkabout
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630dfca405f5a799ef79a94f175df3f48b54c471
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/talkabout/apps/cruises/ports/apps.py
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[]
no_license
https://github.com/kojicz983/talkabout
901174af9dbe1e9f9ad050b5aa21a4700d482d21
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refs/heads/master
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2018-12-23T21:19:03
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from django.apps import AppConfig class PortsConfig(AppConfig): name = 'talkabout.apps.cruises.ports'
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wfeng1991/learnpy
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/py/leetcode/67.py
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[]
no_license
https://github.com/wfeng1991/learnpy
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refs/heads/master
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2018-09-28T02:16:31
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class Solution(object): def addBinary(self, a, b): """ :type a: str :type b: str :rtype: str """ la=len(a) lb=len(b) if la<lb: return self.addBinary(b,a) a=a[::-1] b=b[::-1] i = 0 carry=0 r='' while i<la: ia=ord(a[i])-48 ib=0 if i<lb: ib=ord(b[i])-48 if ia+ib+carry==3: r='1'+r carry=1 elif ia+ib+carry==2: r='0'+r carry=1 else: r=str(ia+ib+carry)+r carry=0 i+=1 if carry==1: r='1'+r return r print(Solution().addBinary('1010','1011'))
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barlettacarmen/Smile
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617440d59c5855b8ed8b2c6de55ae9dae991e4ab
0418fae22897f0015b92b58069a33b275b60c73a
/Smile/files/server.py
87652f11bd0ee27771929afc3abc520528e7cfeb
[ "BSD-3-Clause", "MIT", "Apache-2.0", "LicenseRef-scancode-other-permissive", "BSD-2-Clause", "LicenseRef-scancode-unknown-license-reference" ]
permissive
https://github.com/barlettacarmen/Smile
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refs/heads/master
2021-01-11T20:08:01.523628
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# ___ # / /\ # /___/ \ # \___\ /_ \_\_\_ # / /\\/ /| \_ # /___/ \_/ | \_\_\_ \_ \_ \_ \_ \_\_\_ # \ \ / \ | \_ \_\_\_ \_ \_ \_\_ # \___\//\_\| \_\_\_ \_ \_ \_ \_\_\_ \_\_\_ # /___/ \ # \ \ / # \___\/ # # Copyright 2017 Fabiola Casasopra, Carmen Barletta, Gabriele Iannone, Guido Lanfranchi, Francesco Maio # # 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. get_ipython().magic('matplotlib inline') from pynq import Overlay Overlay("base.bit").download() from pynq.iop import Arduino_Analog from pynq.iop import ARDUINO from pynq.iop import ARDUINO_GROVE_A1, ARDUINO_GROVE_A2, ARDUINO_GROVE_A3, ARDUINO_GROVE_A4 from pynq.board import LED, RGBLED import time import socket import numpy as np import matplotlib.pyplot as plt TEMP_BEFORE_SENDING = 20 #frequency with which sensors will take input from outside FREQUENCY = 0.05 TIME_OF_EVENT = 60 # fixed as 60sec for the demo # In final implementation it must be set with respect to the duration of the event MAX_LEDS = 4 MAX_RGB_LEDS = 2 MAX_RGB_VALUE = 8 global flag_crowded global ss def Main(): host = "10.79.3.204" port = 5001 mySocket = socket.socket() mySocket.bind((host,port)) mySocket.listen(1) conn, addr = mySocket.accept() print ("Connection from: " + str(addr)) flag_crowded = 0 data = conn.recv(1024).decode() while data !="ciao": time.sleep(0.1) while True: readSensorsInput() conn.send ("gente".encode()) while not data: time.sleep(1) data = conn.recv(1024).decode() getNotice(str(data)) flag_crowded = 0 conn.close() def readSensorsInput(): #inizialize readers pins proximityPresence1= Arduino_Analog(ARDUINO,ARDUINO_GROVE_A4) proximityPresence2= Arduino_Analog(ARDUINO,ARDUINO_GROVE_A3) proximitySound= Arduino_Analog(ARDUINO,ARDUINO_GROVE_A2) proximityLight= Arduino_Analog(ARDUINO,ARDUINO_GROVE_A1) crowdLevel = 0 ss = 0 #start state valuesPresence1 = np.zeros(TEMP_BEFORE_SENDING) valuesPresence2 = np.zeros(TEMP_BEFORE_SENDING) valuesSound = np.zeros(TEMP_BEFORE_SENDING) valuesLight = np.zeros(TEMP_BEFORE_SENDING) #calibration for i in range(0,TEMP_BEFORE_SENDING): valuesPresence1[i] = proximityPresence1.read()[1] valuesPresence2[i] = proximityPresence2.read()[1] #valuesSound.append(proximitySound.read()[1]) #valuesLight.append(proximityLight.read()[1]) time.sleep(FREQUENCY) cal1 = np.mean(valuesPresence1) cal2 = np.mean(valuesPresence2) while True: #inizialize lists for values valuesPresence1 = np.zeros(TEMP_BEFORE_SENDING) valuesPresence2 = np.zeros(TEMP_BEFORE_SENDING) #valuesSound = list() #valuesLight = list() valuesSound = np.zeros(TEMP_BEFORE_SENDING) valuesLight = np.zeros(TEMP_BEFORE_SENDING) #plt.axis([0,TEMP_BEFORE_SENDING,0,3]) #plt.ion() #read input from sensors for i in range(0,TEMP_BEFORE_SENDING): valuesPresence1[i] = proximityPresence1.read()[1] valuesPresence2[i] = proximityPresence2.read()[1] valuesSound[i] = proximitySound.read()[0] valuesLight[i] = proximityLight.read()[0] #valueSound.append(proximitySound.read()[1]) #valueLight.append(proximityLight.read()[1]) time.sleep(FREQUENCY) #y = valuesSound[i] #plt.plot(i,y) #plt.show() #debug #print (len(valuesPresence1)) #print (valuesPresence1) #print (valuesPresence2) #print (valueSound) #print (valueLight) #processInput (valuesPresence1, valuesPresence2, valueSound) avg1 = np.mean(valuesPresence1) avg2 = np.mean(valuesPresence2) #implemento una macchina a stati. # 0 ENTRAMBI SENSORI BASSI # 1 PRIMO ALTO SECONDO BASSO MA CI ARRIVO DA 0 # 2 PRIMO BASSO SECONDO ALTO MA CI ARRIVO DA 0 # 3 ENTRAMBI ALTI # 4 PRIMO BASSO SECONDO ALTO MA CI ARRIVO DA 1 # 5 PRIMO ALTO SECONDO BASSO MA CI ARRIVO DA 2 if ss == 0: print("sono nello stato 0") if avg1 > 1.2*cal1 and avg2 < 1.2*cal2: ss = 1 elif avg1 < 1.2*cal1 and avg2 > 1.2*cal2: ss = 2 elif avg1 > 1.2*cal1 and avg2 > 1.2*cal2: ss = 3 elif avg1 < 1.2*cal1 and avg2 < 1.2*cal2: ss = 0 elif ss == 1: print("sono nello stato 1") if avg1 > 1.2*cal1 and avg2 < 1.2*cal2: ss = 1 elif avg1 < 1.2*cal1 and avg2 > 1.2*cal2: ss = 4 elif avg1 > 1.2*cal1 and avg2 > 1.2*cal2: ss = 3 elif avg1 < 1.2*cal1 and avg2 < 1.2*cal2: ss = 0 elif ss == 2: print("sono nello stato 2") if avg1 > 1.2*cal1 and avg2 < 1.2*cal2: ss = 5 elif avg1 < 1.2*cal1 and avg2 > 1.2*cal2: ss = 2 elif avg1 > 1.2*cal1 and avg2 > 1.2*cal2: ss = 3 elif avg1 < 1.2*cal1 and avg2 < 1.2*cal2: ss = 0 elif ss == 3: print("sono nello stato 3") print("c e qualcuno fermo") ss = 0 elif ss == 4: print("sono nello stato 4") flag_crowded = 1 ss = 0 break elif ss == 5: print("sono nello stato 5") flag_crowded = 0 print("uscito qualcuno") ss = 0 def getNotice(s): proximityLight= Arduino_Analog(ARDUINO,ARDUINO_GROVE_A1) valuesLight = np.zeros(TEMP_BEFORE_SENDING) #read input from sensors for i in range(0,TEMP_BEFORE_SENDING): valuesLight[i] = proximityLight.read()[0] time.sleep(FREQUENCY) avgLight = sum(valuesLight)/TEMP_BEFORE_SENDING print(avgLight) threshold = 1 accesi = 0 if avgLight > threshold: accesi = 2 else: accesi = 1 rgb_leds = [RGBLED(i+MAX_LEDS) for i in range (MAX_RGB_LEDS)] for i in range(MAX_RGB_LEDS): rgb_leds[i].off() if s == "focus": for i in range (accesi): rgb_leds[i].on(3) #light blue elif s == "party": for i in range (accesi): rgb_leds[i].on(4) #red elif s == "dinner": rgb_leds[0].on(4) #red rgb_leds[1].on(6) #yellow elif s == "sleep": for i in range (accesi): rgb_leds[i].on(5) #purple elif s == "workout": for i in range (accesi): rgb_leds[i].on(2) #green elif s == "chill": for i in range (accesi): rgb_leds[i].on(1) #blue elif s == "travel": for i in range (accesi): rgb_leds[i].on(6) #yellow elif s == "nomatch": for i in range (accesi): rgb_leds[i].on(7) #white elif s == "noevent": for i in range (accesi): rgb_leds[i].off() # shut down everything else: print("Error in data transmission from Calendar!") time.sleep(TIME_OF_EVENT) for i in range (MAX_RGB_LEDS): rgb_leds[i].off() # shut down everything if __name__ == '__main__': Main()
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cashila/block-exploder
19,207,093,768,461
3bf9cc1d3d49b7885ccd40e2288ee48620917b5e
0918cc441ad199a86ed9879ff6dace165de3b40e
/syncer/serializers.py
e83c5ade38add54d45758031f9ceba171811379d
[]
no_license
https://github.com/cashila/block-exploder
b97c47b147f6463f0966e9d8c4ebf06c510b57e8
1ac611a4adc1c114b7ab09f81d3f9aaf27e39490
refs/heads/master
2021-01-23T09:38:20.025755
2017-08-21T16:13:45
2017-08-21T16:13:45
102,586,814
0
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2017-09-06T09:00:01
2017-09-06T09:00:01
2017-06-17T03:17:14
2017-08-23T19:31:12
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class VoutSerializer(object): @staticmethod def to_database(vout): return { "value": vout.value, "asm": vout.asm, "addresses": vout.addresses, "type": vout.type, "reqSigs": vout.reqSigs, "spent": vout.spent } class VinSerializer(object): @staticmethod def to_database(vin): return { "prev_txid": vin.prev_txid, "vout_index": vin.vout_index, "hex": vin.hex, "sequence": vin.sequence, "coinbase": vin.coinbase } class TransactionSerializer(object): @staticmethod def to_database(tr): formatted = { "version": tr.version, "locktime": tr.locktime, "txid": tr.txid, "vin": [], "vout": [], "total": tr.total, "blockhash": tr.blockhash, "blocktime": tr.blocktime } for v in tr.vin: formatted['vin'].append(VinSerializer.to_database(v)) for v in tr.vout: formatted['vout'].append(VoutSerializer.to_database(v)) return formatted class BlockSerializer(object): @staticmethod def to_database(block): if not type(block.tx[0]) == unicode: tx = [tr.txid for tr in block.tx] else: tx = block.tx return { "hash": block.hash, "size": block.size, "height": block.height, "version": block.version, "merkleroot": block.merkleroot, "tx": tx, "time": block.time, "nonce": block.nonce, "bits": block.bits, "difficulty": str(block.difficulty), "chainwork": hex(block.chainwork), "previousblockhash": block.previousblockhash, "nextblockhash": block.nextblockhash, "target": hex(block.target), "dat": block.dat, "total": str(block.total), "work": block.work, "chain": block.chain } class HashrateSerializer(object): @staticmethod def to_database(rate, timestamp): return { "hashrate": rate, "timestamp": timestamp } class SyncHistorySerializer(object): @staticmethod def to_database(start_time, end_time, start_block_height, end_block_height): return { "start_time": start_time, "end_time": end_time, "start_block_height": start_block_height, "end_block_height": end_block_height } class NetworkStatsSerializer(object): @staticmethod def to_database(supply, blockchain_size): return { "supply": supply, "blockchain_size": blockchain_size } class PriceSerializer(object): @staticmethod def to_database(price): return { "usd_price": price } class ClientInfoSerializer(object): @staticmethod def to_database(version, ip, peer_info): # If ipify api stops working don't update ip field if ip: return { "version": version, "ip": ip, "peer_info": peer_info } else: return { "version": version, "peer_info": peer_info } class ClientSyncProgressSerializer(object): @staticmethod def to_database(progress): return { "sync_progress": progress }
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bellancal/CAN_Invader
7,782,480,751,348
d77df5bffa552c2f0ae8e6757dbfc5cfd67c927c
80d7b43447fea4755987124c1a7cd4993d1840f5
/bg.py
489745faca45b1f1c32587748507dc597157929a
[]
no_license
https://github.com/bellancal/CAN_Invader
686e2bdf0b136c781adad8d4a340033e6f86360f
c2892e3ab1e906e289459faa221620f1624c8652
refs/heads/master
2020-04-05T23:08:45.960723
2018-02-23T22:56:59
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from tkinter import * import tkinter.messagebox import tkinter as tk import tkinter.ttk as ttk import tkinter.font as font import subprocess from subprocess import Popen, CREATE_NEW_CONSOLE, PIPE import os import ConfigFile import configparser import socket import sys import threading import traceback """ Purpose: Main file that creates the gui using TK widgets for the CAN INVADER control. This program will launch the BT server and initiate message using server. This program will also monitor for server status and CAN responses for the diagnostic requests and present these to user. Author: Louis V Bellanca / LBELLAN1@FORD.COM Date: April 2016 first release ver2.0 | May 14 2016 major updates: -added a new socket server for gui in new thread to monitor for incoming request for button controls - to be used with Klippel tool """ #TODO:determine supplier of AHU from CAN bus. #TODO: get input from buld sheet to decode configuration #TODO:If connect is pressed with no server? # Define global variables here cfg = configparser.ConfigParser() engineering_mode = False command_error = False CREATE_NO_WINDOW = 0x08000000 # set defaults for the size default_sizex = "662" default_sizey = "478" fileOK = "" MasterVol1 = 1 MasterVol2 = 16 def ConfigSelect(selection=None): print("Configuration selected = " + str(selection)) if selection is not None: LoadConfig(ConfigFile.config_list2[selection]["filename"]) def LoadConfig(filetoload): # sub to check the config file and load data global sizex, sizey, fileOK, config_file, loaded_freq # refer to the file to see if a config is defined fileOK = cfg.read(filetoload) if fileOK: print("ini file read in bg = " + str(fileOK)) loaded_config.set("Config file = " + filetoload) # ConfigFile.CFT = filetoload print("Attempting to load config = " + filetoload) config_file = filetoload # CheckTP() CheckAMP() CheckAHU() CheckSpeaker() CheckVIN() CheckBassTreb() CheckCAN(bus_type=cfg['CAN']['busType'].lower(), speed=cfg['CAN']['speed'].lower()) # Note if already connected and CAN changes then settings will not take effect since a disconnect is needed. # if the config file does not have the section 'SIZE', then add it to the config-file if not cfg.has_section('SIZE'): cfg.add_section('SIZE') # set default size sizex = default_sizex sizey = default_sizey print("cfg section SIZE not found - to be added!!") # else just return the the value of globle->settings else: sizex = cfg['SIZE']['X'] sizey = cfg['SIZE']['Y'] print ("Size x =" + sizex + " Size y =" + sizey) # change the window to the defined size root.geometry("%sx%s" % (sizex, sizey)) loaded_freq.set('Default Freq = ' + cfg['DUT']['FM_FREQ']) #set bass and trebel to defaults # bass_scale.set(7) # treb_scale.set(0) #clear frequency to restore default fin.delete(0, END) else: print("Missing Config File!!" + str(fileOK)) tkinter.messagebox.showinfo("Config File Error", "The specified configuration file could not be found:" + filetoload ) loaded_config.set("Config file not found!") def CheckBassTreb(): print("Check bass and treble values") if cfg.has_section('BASS'): bass_default = int(cfg['BASS']['VALUE']) else: bass_default = 7 if cfg.has_section('TREBLE'): treb_default = int(cfg['TREBLE']['VALUE']) else: treb_default = 0 print("Bass default = " + str(bass_default)) print("Treb default = " + str(treb_default)) bass_scale.set(bass_default) treb_scale.set(treb_default) def CheckCAN(bus_type=None, speed=None): # set gui to match default setting global CONNECTED_BUS_SPEED, CONNECTED_BUS_TYPE, User_Connect print("bus=" + bus_type + " speed=" + speed, " connected type=" + CONNECTED_BUS_TYPE) if User_Connect and ((CONNECTED_BUS_SPEED != "None" and CONNECTED_BUS_SPEED != speed) or (CONNECTED_BUS_TYPE != "None" and CONNECTED_BUS_TYPE != bus_type)): tkinter.messagebox.showinfo("CAN Config Not Implemented", "CAN speed or type change detected. You must disconnect and reconnect to make this effective!") return if bus_type == 'hs' and speed == '500': sp_500_HS.set(True) CONNECTED_BUS_SPEED = speed CONNECTED_BUS_TYPE = bus_type CAN_setup0() elif bus_type == 'hs' and speed == '125': sp_125_HS.set(True) CONNECTED_BUS_SPEED = speed CONNECTED_BUS_TYPE = bus_type CAN_setup1() elif bus_type == 'ms' and speed == '125': sp_125_MS.set(True) CONNECTED_BUS_SPEED = speed CONNECTED_BUS_TYPE = bus_type CAN_setup3() elif bus_type == 'ms' and speed == '500': sp_500_MS.set(True) CONNECTED_BUS_SPEED = speed CONNECTED_BUS_TYPE = bus_type CAN_setup2() else: print("Invalid CAN settings in ini file!") def CheckSpeaker(): # checks for speaker type in the ini file and sets program accordingly # Enter in config file as: # [SPEAKER] # type = Panasonic | Clarion | Visteon if cfg.has_section('SPEAKER'): sptype = cfg['SPEAKER']['TYPE'] sptype = sptype.lower() if sptype == '1': #no tweeter Speaker1.set(True) Sp1_change() print("Speaker type 1") elif sptype == '2': #with tweeter Speaker2.set(True) Sp2_change() print("Speaker type 2") elif sptype == '3': #undefined Speaker3.set(True) print("Speaker type 3") Sp3_change() else: print("Invalid Speaker type defined - check config") else: print("No Speaker type found") def CheckAMP(): """ Run as part of load config only. checks for AMP in the ini file and sets program accordingly - also determines the default volume setting Enter in config file as: [AMP] If volume is missing then last loaded volume will persists """ global default_volume_front, default_volume_rear print("Checking for AMP in config file only...") if cfg.has_section('AMP'): amptype = cfg['AMP']['TYPE'] amptype = amptype.lower() if amptype == '1': # THX Amp_THX_Present.set(True) Amp_SONY_Present.set(False) Amp_HARMAN_Present.set(False) print("THX AMP is present") default_volume_front= cfg['AMP']['VOLUME_FRONT'] default_volume_rear = cfg['AMP']['VOLUME_REAR'] elif amptype == '2': # SONY Amp_SONY_Present.set(True) Amp_THX_Present.set(False) Amp_HARMAN_Present.set(False) print("THX AMP is present") default_volume_front= cfg['AMP']['VOLUME_FRONT'] default_volume_rear = cfg['AMP']['VOLUME_REAR'] elif amptype == '3': # HARMNA Amp_SONY_Present.set(False) Amp_THX_Present.set(False) Amp_HARMAN_Present.set(True) print("HARMAN AMP is present") default_volume_front= cfg['AMP']['VOLUME_FRONT'] default_volume_rear = cfg['AMP']['VOLUME_REAR'] elif amptype == '0': # NO AMP Amp_THX_Present.set(False) Amp_SONY_Present.set(False) Amp_HARMAN_Present.set(False) print("No AMP present") default_volume_front= cfg['DUT']['VOLUME_FRONT'] default_volume_rear = cfg['DUT']['VOLUME_REAR'] else: print("Invalid AMP type defined - check config") Amp_THX_Present.set(False) Amp_SONY_Present.set(False) else: print("No AMP type found during autocheck") default_volume_front= cfg['DUT']['VOLUME_FRONT'] default_volume_rear = cfg['DUT']['VOLUME_REAR'] loaded_volume.set('Default Front Volume Setting = ' + default_volume_front) loaded_Rvolume.set('Default Rear Volume Setting = ' + default_volume_rear) print('Default Front Volume Setting = ' + default_volume_front) print('Default Rear Volume Setting = ' + default_volume_rear) def AMP_autocheck(): """ Run each time a BT connection is made and will force the AMP setting based on results and is independent of the config.ini file. """ global default_volume_front, default_volume_rear print("Auto check for AMP") # do auto check for AMP THX and HARMAN use same messages so need to decide which to run based on config if Amp_HARMAN_Present.get(): if speaker_All(False): print("HARMAN AMP FOUND in AutoCHECK!!") default_volume_front = cfg['AMP']['VOLUME_FRONT'] default_volume_rear = cfg['AMP']['VOLUME_REAR'] return else: # check for THX AMP Amp_THX_Present.set(True) # source to send messsage to AMP Amp_HARMAN_Present.set(False) # source to send messsage to AMP Amp_SONY_Present.set(False) # source to send messsage to AMP if speaker_All(False): print("THX AMP FOUND in AutoCHECK!!") default_volume_front = cfg['AMP']['VOLUME_FRONT'] default_volume_rear = cfg['AMP']['VOLUME_REAR'] return # if none found then check for SONY ano Amp_THX_Present.set(False) # source to send messsage to AMP Amp_SONY_Present.set(True) # source to send messsage to AMP Amp_HARMAN_Present.set(False) # source to send messsage to AMP if speaker_All(False): print("SONY AMP FOUND in AutoCHECK!!") default_volume_front = cfg['AMP']['VOLUME_FRONT'] default_volume_rear = cfg['AMP']['VOLUME_REAR'] return else: print("NO AMP FOUND in AutoCHECK!!") Amp_THX_Present.set(False) Amp_SONY_Present.set(False) Amp_HARMAN_Present.set(False) # source to send messsage to AMP default_volume_front= cfg['DUT']['VOLUME_FRONT'] default_volume_rear = cfg['DUT']['VOLUME_REAR'] loaded_volume.set('Default Front Volume Setting = ' + default_volume_front) loaded_Rvolume.set('Default Rear Volume Setting = ' + default_volume_rear) print('Default Front Volume Setting = ' + default_volume_front) print('Default Rear Volume Setting = ' + default_volume_rear) def CheckAHU(): """ checks for AHU type in the ini file and sets program accordingly Enter in config file as: [AHU] type = Panasonic | Clarion | Visteon """ if cfg.has_section('AHU'): ahutype = cfg['AHU']['TYPE'] ahutype = ahutype.lower() if ahutype == 'panasonic': AHU_Pana.set(True) AHU_changeP() elif ahutype == 'clarion': AHU_Clar.set(True) AHU_changeC() elif ahutype == 'visteon': AHU_Vist.set(True) AHU_changeV() elif ahutype == 'visteon-gap': AHU_VistGap.set(True) AHU_changeVGap() elif ahutype == 'pana-gap': AHU_PanaGap.set(True) AHU_changePGap() else: print("Invalid AHU type defined - check config") else: print("No AHU type found") def CheckTP(): """ checks for additional tester present ID and sends the TP On command Enter in config file as: [TESTERPRESENT] idlist = 7DF, 777, 711 """ if cfg.has_section('TESTERPRESENT'): canid = cfg['TESTERPRESENT']['IDLIST'].split(',') for id in canid: id = id.replace(" ", "") # remove whitespacec if present id = id.upper() print ("Enable TP for :" + id) testerPon(forceid=id) else: print("No additional TP") def CheckVIN(): """" checks for presence of the VIN ECU to query and displays the correct button Enter in config file as: [VIN] ecu = bcm sync, ahu, ipc, bcm, abs - only list 1!!! """ global VIN_ecu, vin_y, vin_x if cfg.has_section('VIN'): VIN_ecu = cfg['VIN']['ECU'].upper() print("VIN ecu = " + VIN_ecu) # hide all and show the ones used HideVINbuttons() if VIN_ecu == "SYNC": print("Show VIN-SYNC") app.getVINsync_b.pack() app.getVINsync_b.place(rely=vin_y, relx=.40) elif VIN_ecu == "AHU": print("Show VIN-AHU") app.getVINahu_b.pack() app.getVINahu_b.place(rely=vin_y, relx=vin_x) elif VIN_ecu == "ABS": print("Show VIN-ABS") app.getVINabs_b.pack() app.getVINabs_b.place(rely=vin_y, relx=0) elif VIN_ecu == "BCM": print("Show VIN-BCM") app.getVINbcm_b.pack() app.getVINbcm_b.place(rely=vin_y, relx=vin_x * 2) elif VIN_ecu == "IPC": print("Show VIN-IPC") app.getVINipc_b.pack() app.getVINipc_b.place(rely=vin_y, relx=vin_x * 3) elif VIN_ecu == "RCM": print("Show VIN-RCM") app.getVINrcm_b.pack() app.getVINrcm_b.place(rely=vin_y, relx=vin_x * 4) else: print("No VIN ecu in config") def HideVINbuttons(): app.getVINahu_b.place_forget() app.getVINabs_b.place_forget() app.getVINsync_b.place_forget() app.getVINbcm_b.place_forget() app.getVINipc_b.place_forget() app.getVINrcm_b.place_forget() def ReadVIN(): """" query the vehicle for the VIN data """ global VIN_ecu if VIN_ecu == "SYNC": print("get VIN-SYNC") get_VIN_SYNC() elif VIN_ecu == "AHU": print("get VIN-AHU") get_VIN_AHU() elif VIN_ecu == "ABS": print("get VIN-ABS") get_VIN_ABS() elif VIN_ecu == "BCM": print("get VIN-BCM") get_VIN_BCM() elif VIN_ecu == "IPC": print("get VIN-IPC") get_VIN_IPC() elif VIN_ecu == "RCM": print("get VIN-RCM") get_VIN_RCM() elif VIN_ecu == "PCM": print("get VIN-PCM") get_VIN_PCM() else: print("No VIN ecu in config") def Hide(action): print("hiding =" + str(action)) if action: app.startserver_b.place_forget() app.connect_b.place_forget() # app.setBass_b.place_forget() # app.setTreb_b.place_forget() # bass_in.place_forget() # treb_in.place_forget() app.radioOn_b.place_forget() app.Testerp_b.place_forget() app.TesterpOff_b.place_forget() app.Test_b.place_forget() tpid.place_forget() tpid_off.place_forget() HideVINbuttons() else: app.onepress_b.place_forget() app.startserver_b.pack(in_=app.frame) app.startserver_b.place(rely=.12, relx=.2) app.onepress_b.pack(in_=app.frame) app.onepress_b.place(rely=.12, relx=0) app.connect_b.pack(in_=app.frame) app.connect_b.place(rely=.12, relx=.3) # app.setBass_b.pack(in_=app.frame) # app.setBass_b.place(rely=.2, relx=0) # app.setTreb_b.pack(in_=app.frame) # app.setTreb_b.place(rely=.2, relx=.34) # bass_in.pack(in_=app.frame) # bass_in.place(rely=.21, relx=.18) # treb_in.pack(in_=app.frame) # treb_in.place(rely=.21, relx=.52) app.radioOn_b.pack(in_=app.frame) app.radioOn_b.place(rely=.12, relx=.4) app.Testerp_b.pack(in_=app.frame) app.Testerp_b.place(rely=.95, relx=0) app.TesterpOff_b.pack(in_=app.frame) app.TesterpOff_b.place(rely=.9, relx=0) app.Test_b.pack(in_=app.frame) app.Test_b.place(rely=.9, relx=.2) tpid.pack(in_=app.frame) tpid.place(rely=.96, relx=.1) tpid_off.pack(in_=app.frame) tpid_off.place(rely=.91, relx=.1) app.getVINahu_b.pack() app.getVINahu_b.place(rely=vin_y, relx=vin_x) app.getVINabs_b.pack() app.getVINabs_b.place(rely=vin_y, relx=0) app.getVINsync_b.pack() app.getVINsync_b.place(rely=vin_y, relx=vin_x * 5) app.getVINbcm_b.pack() app.getVINbcm_b.place(rely=vin_y, relx=vin_x * 2) app.getVINipc_b.pack() app.getVINipc_b.place(rely=vin_y, relx=vin_x * 3) app.getVINrcm_b.pack() app.getVINrcm_b.place(rely=vin_y, relx=vin_x * 4) def quitme(): # write the window size to the ini file for next startup global fileOK, servercmd, config_file if fileOK: cfg.set('SIZE', 'X', str(root.winfo_width())) cfg.set('SIZE', 'Y', str(root.winfo_height())) print("Saving Configuration data...") cfg.write(open(config_file, "w")) disconnect() try: s.close() servercmd.kill() except: pass sys.exit() def left_mouse(event): print("Left Mouse @ {},{}".format(event.x, event.y)) def right_mouse(event): print("Right Mouse @ {},{}".format(event.x, event.y)) def a_key(event): global engineering_mode global MasterVol1, MasterVol2 print("{},{}".format(event.x, event.y), event.char) if event.char == 'E': engineering_mode = not engineering_mode Hide(not engineering_mode) print("toggle engineering mode = " + str(engineering_mode)) elif event.char == 'T': CheckVIN() elif event.char == '+': # create a popup menu self.setVol1_b = Button(master, text="Vol=1", command=set_vol1, fg="white", bg="green") if MasterVol1 < 30: MasterVol1 += 1 app.setVol1_b.configure(text="Vol=" + str(MasterVol1)) elif event.char == '-': # create a popup menu self.setVol1_b = Button(master, text="Vol=1", command=set_vol1, fg="white", bg="green") if MasterVol1 > 0 : MasterVol1 -= 1 app.setVol1_b.configure(text="Vol=" + str(MasterVol1)) elif event.char == '>': # create a popup menu self.setVol1_b = Button(master, text="Vol=1", command=set_vol1, fg="white", bg="green") if MasterVol2 < 30: MasterVol2 += 1 app.setVol16_b.configure(text="Vol=" + str(MasterVol2)) elif event.char == '<': # create a popup menu self.setVol1_b = Button(master, text="Vol=1", command=set_vol1, fg="white", bg="green") if MasterVol2 > 0 : MasterVol2 -= 1 app.setVol16_b.configure(text="Vol=" + str(MasterVol2)) # popupw = Menu(root, tearoff=0) # popupw.add_command(label="Display the label") # popupw.add_command(input("hi")) # # display the popup menu # try: # popupw.tk_popup(event.x_root, event.y_root, 0) # finally: # # make sure to release the grab (Tk 8.0a1 only) # popupw.grab_release() def about(): tkinter.messagebox.showinfo("CAN Invader BT Controller", "Ver 3.0 - June 17, 2016 \r\n Ford Motor Company \r\n Contact:LbeLLan1@Ford.com\r\n") print("width =" + str(root.winfo_width())) print("height =" + str(root.winfo_height())) # print (root.winfo_geometry()) def show_instructions(): # show pdf instruction guide subprocess.Popen("instructions.pdf",shell=True) def start_server(): global command_error, servercmd # see if already connected if User_Connect: print("server already connected") tkinter.messagebox.showinfo("Server Started", "Server already started and connected!") return # see if server already running but not connected try: server_status = servercmd.poll() print ("Check server status = " + str(server_status) + "(None = running)") if server_status is None: tkinter.messagebox.showinfo("Server Started", "Server already started but not connected!") return except: print("server status run check failed (means not running yet).") command_error = False print("starting server") # global servercmd servercmd = subprocess.Popen([sys.executable, "tcp_server.py", "--CONFIG", config_file], creationflags=CREATE_NEW_CONSOLE) def onepress(): global command_error, default_volume_front, servercmd if User_Connect: print("already connected") tkinter.messagebox.showinfo("Server Running", "Server already started and connected!") return print("onepress started") command_error = False # see if server already running but not connected try: server_status = servercmd.poll() print ("Check server status = " + str(server_status) + "(None = running)") if server_status is None: print( "Server already started but not connected!") else: # number means tereminated and need to start again start_server() except: # can occur first time server_status is checked since servercmd not defined print("server not running - starting now") start_server() # if connect not successful then do not perform other commands! a = connect() if a: AMP_autocheck() # another check to make sure of AMP presence radio_on() set_bass() set_treble() set_freq() set_vol_default(default_volume_front) ReadVIN() else: # close active server disconnect() def testerPon(forceid=None): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error command_error = False print("tester present on") id1 = tpid.get() if id1 != "": id1 = "," + id1 if forceid is not None: # forceid takes precedence id1 = "," + str(forceid) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'testerPresentOn' + id1], creationflags=CREATE_NO_WINDOW) def testerPoff(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error command_error = False print("tester present off") id1 = tpid_off.get() if id1 != "": id1 = "," + id1 p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'testerPresentOff' + id1], creationflags=CREATE_NO_WINDOW) def connect(): global command_error, CONNECTED_BUS_SPEED, CONNECTED_BUS_TYPE command_error = False print("BT connect") # see if server already running but not connected try: server_status = servercmd.poll() print ("Check server status = " + str(server_status) + "(None = running)") if server_status is None: print( "Server already started..will attemp to connect!") else: # number means tereminated and need to start again tkinter.messagebox.showinfo("No Server","No server running - please start this first!" ) return except: # can occur first time server_status is checked since servercmd not defined tkinter.messagebox.showinfo("No Server","No server running - please start this first!" ) return os.system("start /wait cmd /c bt_connect_only.bat") if sp_125_HS.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'configureCAN,125,hs'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) print("Set CAN 125 HS") #todo: set connect status flags CONNECTED_BUS_SPEED = "125" CONNECTED_BUS_TYPE = "hs" elif sp_125_MS.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'configureCAN,125,ms'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) print("Set CAN 125 MS") CONNECTED_BUS_SPEED = "125" CONNECTED_BUS_TYPE = "ms" elif sp_500_MS.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'configureCAN,500,ms'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) print("Set CAN 500 MS") CONNECTED_BUS_SPEED = "500" CONNECTED_BUS_TYPE = "ms" elif sp_500_HS.get(): print("Set CAN 500 HS") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'configureCAN,500,hs'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) CONNECTED_BUS_SPEED = "500" CONNECTED_BUS_TYPE = "hs" else: print("Set CAN from ini") # no configuration chosen so use default in ini file p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'configureCAN'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) # CheckCAN(bus_type = cfg['CAN']['busType'].lower(), speed = cfg['CAN']['speed'].lower()) stdout, stderr = p.communicate() print(stdout + stderr) if stdout.find(b'ConfigOK') > 0: global User_Connect User_Connect = True os.system("start /wait cmd /c TP_on.bat") CheckTP() # keep this here print("Connected OK!") # CheckAHU() # CheckSpeaker() # CheckVIN() ReadVIN() AMP_autocheck() return True else: User_Connect = False print("Failed to connect via BT!") tkinter.messagebox.showinfo("Connection Error", "No BT connection made! Please check setup. Make sure BlueTooth dongle is attached to PC. Check that CAN Invader is in range and attached to vehicle diagnostic port. Make sure BT MAC address is correect in setup file. Try unplugging and reconnecting CAN INVADER to vehicle." ) return False def radio_on(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error print("Radio On") # os.system("start /wait cmd /c radio_on_AHU.bat") p = Popen([sys.executable, "pynetcat.py",'localhost','50000','radioOnahu'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() print(stdout + stderr) if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def set_bass(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error b = bass_scale.get() if b == "": b = '0E' # max else: b = format(int(b) + 7, '02X') if Amp_THX_Present.get() or Amp_SONY_Present.get() or Amp_HARMAN_Present.get(): print("AMP Set BASS =" + b) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPsetBassX,' + b], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) elif AHU_VistGap.get(): #Convert b to signed integer' #convert to decimal ivalue= bass_scale.get() if ivalue == "": ivalue = '07' # max else: ivalue = (tohex(ivalue,8)) #converts to signed integer - local function here ivalue = ivalue.replace('x', '') ivalue = ivalue[-2:] print("Set BassV=" + ivalue) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setBassVisteon,' + ivalue], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) elif AHU_PanaGap.get(): #new add for DS-JK2T-18D15-CA #Convert b to signed integer' #convert to decimal ivalue= bass_scale.get() if ivalue == "": ivalue = '07' # max else: ivalue = (tohex(ivalue,8)) #converts to signed integer - local function here ivalue = ivalue.replace('x', '') ivalue = ivalue[-2:] print("Set BassV=" + ivalue) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setBassX,' + ivalue], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) else: print("Set Bass=" + b) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setBassX,' + b], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def tohex(val, nbits): return hex((val + (1 << nbits)) % (1 << nbits)) def set_treble(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error print("Set Treble") # os.system("start /wait cmd /c setTrebX.bat") t = treb_scale.get() if t == "": t = '07' # nominal else: t = format(int(t) + 7,'02X') if Amp_THX_Present.get() or Amp_SONY_Present.get() or Amp_HARMAN_Present.get(): print("AMP Set Treble =" + t) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPsetTrebX,' + t], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) elif AHU_VistGap.get(): ivalue= treb_scale.get() if ivalue == "": ivalue = '07' # max else: ivalue = (tohex(ivalue,8)) #converts to signed integer - local function here ivalue = ivalue.replace('x', '') ivalue = ivalue[-2:] print("Set TrebleV=" + ivalue) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setTrebVisteon,' + ivalue], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) elif AHU_PanaGap.get(): #new add for the Pana DS-JK2T-18D15-CA ivalue= treb_scale.get() if ivalue == "": ivalue = '07' # max else: ivalue = (tohex(ivalue,8)) #converts to signed integer - local function here ivalue = ivalue.replace('x', '') ivalue = ivalue[-2:] print("Set TrebleV=" + ivalue) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setTrebX,' + ivalue], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) else: print("Set Treble=" + t) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setTrebX,' + t], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def set_freq(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error f = fin.get() if f != "": f_float = max(float(f), 87.5) # needs to be at least 87.5 f_float = min(f_float, 108) # limit to 108 fint = int(f_float * 10) print("Set Frequency " + f + " " + str(fint)) p=Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setFreqX,' + str(fint)], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) else: print("Set Frequency to default") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setFreq'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def set_vol1(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error v = format(MasterVol1, '02x') if Amp_THX_Present.get() or Amp_SONY_Present.get() or Amp_HARMAN_Present.get(): print("AMP Set Vol " + str(MasterVol1)) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPsetVolumeX,' + v], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) elif AHU_VistGap.get(): # setvolfront command uses the vol lookup table to adjust the volume steps print("Set Vol GAP " + str(MasterVol1)) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeFront,' + v], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) else: print("Set Vol " + str(MasterVol1)) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeX,' + v], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def set_vol5(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error if Amp_THX_Present.get() or Amp_SONY_Present.get() or Amp_HARMAN_Present.get(): print("AMP Set Vol 5") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPsetVolumeX,05'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) elif AHU_VistGap.get(): # setvolfront command uses the vol lookup table to adjust the volume steps print("Set Vol GAP 5" ) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeFront,05'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) else: print("Set Vol 5") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeX,05'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c setVolumeX5.bat") stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def set_vol19(): """ This was changed from a static 19 setting to the FRONT DEFAULT volume setting """ if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error vf = format(int(default_volume_front), '02x') if Amp_THX_Present.get() or Amp_SONY_Present.get() or Amp_HARMAN_Present.get(): print("AMP Set Vol Front = " + default_volume_front) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPsetVolumeX,' + vf], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) elif AHU_VistGap.get(): # setvolfront command uses the vol lookup table to adjust the volume steps print("Set Vol GAP Front = " + default_volume_front) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeFront,' + vf], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) else: print("Set Vol Front = " + default_volume_front) # os.system("start /wait cmd /c setVolumeX13.bat") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeX,' + vf], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def set_vol16(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error v = format(MasterVol2, '02x') if Amp_THX_Present.get() or Amp_SONY_Present.get() or Amp_HARMAN_Present.get(): print("AMP Set Vol" + str(MasterVol2)) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPsetVolumeX,' + v], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) elif AHU_VistGap.get(): # setvolfront command uses the vol lookup table to adjust the volume steps print("Set Vol GAP " + str(MasterVol2)) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeFront,' + v], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) else: print("Set Vol " + str(MasterVol2)) v = format(MasterVol2, '02x') p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeX,' + v], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def set_vol22(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error vr = format(int(default_volume_rear), '02x') if Amp_THX_Present.get() or Amp_SONY_Present.get() or Amp_HARMAN_Present.get(): print("AMP Set Vol Rear = " + default_volume_rear) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPsetVolumeX,' + vr], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) elif AHU_VistGap.get(): # setvolfront command uses the vol lookup table to adjust the volume steps print("Set Vol GAP Rear = " + default_volume_rear) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeFront,' + vr], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) else: print("Set Vol Rear = " + default_volume_rear) # os.system("start /wait cmd /c setVolumeX13.bat") p=Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeX,' + vr], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True return False else: command_error = False return True def set_volX(): """ Take input form gui and send in volume - needs to be sent in HEX format!! """ if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error v = v_scale.get() if v != "": v = format(int(v), '02x') if Amp_THX_Present.get() or Amp_SONY_Present.get() or Amp_HARMAN_Present.get(): print("AMP Set Vol X =" + v) p = Popen([sys.executable, "pynetcat.py",'localhost','50000','AMPsetVolumeX,' + v], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) elif AHU_VistGap.get(): # setvolfront command uses the vol lookup table to adjust the volume steps print("Set Vol GAP " + v) p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeFront,' + v], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) else: print("Set Vol X =" + v) p = Popen([sys.executable, "pynetcat.py",'localhost','50000','setVolumeX,' + v], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) else: # no data entered so assume default defined in setVolumeX command that is 0 if Amp_THX_Present.get() or Amp_SONY_Present.get(): print("AMP Set Vol X = 0") p = Popen([sys.executable, "pynetcat.py",'localhost','50000','AMPsetVolumeX'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) elif AHU_VistGap.get(): print("Set Vol GAP = 0") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeFront'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) else: print("Set Vol X = 0") p = Popen([sys.executable, "pynetcat.py",'localhost','50000','setVolumeX'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) # check responses stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def set_vol_default(v_dec): global command_error # convert to hex for command as ini file is NOT in hex format!! v = format(int(v_dec), '02x') if v != "": if Amp_THX_Present.get() or Amp_SONY_Present.get() or Amp_HARMAN_Present.get(): print("AMP Set Vol Default =" + v) p = Popen([sys.executable, "pynetcat.py",'localhost','50000','AMPsetVolumeX,' + v], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) elif AHU_VistGap.get(): print("Set Vol GAP default") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'setVolumeFront,' + v], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) else: print("Set Vol Default =" + v) p = Popen([sys.executable, "pynetcat.py",'localhost','50000','setVolumeX,' + v], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True return False else: command_error = False loaded_volume.set('Default Front Volume Setting = ' + str(v_dec)) return True else: print("Default volume missing") command_error = True return False def get_VIN_AHU(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error command_error = False print("Get VIN ahu") # os.system("start /wait cmd /c log_VIN_AHU.bat") p = Popen([sys.executable, "pynetcat.py",'localhost','50000','readVIN'], creationflags=CREATE_NO_WINDOW, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False fv = stdout.find(b'vin=') VIN_read = str(stdout) VIN_read = VIN_read[fv + 6:fv + 23] print("VIN = " + VIN_read) info_l4.config(state=NORMAL) info_l4.delete(1.0, END) info_l4.insert(1.0, "VIN = " + VIN_read) info_l4.config(state=DISABLED) def get_VIN_ABS(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error command_error = False print("Get VIN abs") # os.system("start /wait cmd /c log_VIN_ABS.bat") p = Popen([sys.executable, "pynetcat.py",'localhost','50000','readVINabs'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False fv = stdout.find(b'vin=') VIN_read = str(stdout) VIN_read = VIN_read[fv + 6:fv + 23] print("VIN = " + VIN_read) info_l4.config(state=NORMAL) info_l4.delete(1.0, END) info_l4.insert(1.0, "VIN = " + VIN_read) info_l4.config(state=DISABLED) def get_VIN_SYNC(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error command_error = False print("Get VIN sync") p = Popen([sys.executable, "pynetcat.py",'localhost','50000','readVINsync'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c log_VIN_SYNC.bat") stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False fv = stdout.find(b'vin=') VIN_read = str(stdout) VIN_read = VIN_read[fv + 6:fv + 23] print("VIN = " + VIN_read) info_l4.config(state=NORMAL) info_l4.delete(1.0, END) info_l4.insert(1.0, "VIN = " + VIN_read) info_l4.config(state=DISABLED) def get_VIN_BCM(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error command_error = False print("Get VIN bcm") p = Popen([sys.executable, "pynetcat.py",'localhost','50000','readVINbcm'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False fv = stdout.find(b'vin=') VIN_read = str(stdout) VIN_read = VIN_read[fv + 6:fv + 23] print("VIN = " + VIN_read) info_l4.config(state=NORMAL) info_l4.delete(1.0, END) info_l4.insert(1.0, "VIN = " + VIN_read) info_l4.config(state=DISABLED) # TODO-test PCM get VIN and add button def get_VIN_PCM(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error command_error = False print("Get VIN pcm") p = Popen([sys.executable, "pynetcat.py",'localhost','50000','readVINpcm'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False fv = stdout.find(b'vin=') VIN_read = str(stdout) VIN_read = VIN_read[fv + 6:fv + 23] print("VIN = " + VIN_read) info_l4.config(state=NORMAL) info_l4.delete(1.0, END) info_l4.insert(1.0, "VIN = " + VIN_read) info_l4.config(state=DISABLED) def get_VIN_RCM(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error command_error = False print("Get VIN rcm") p = Popen([sys.executable, "pynetcat.py",'localhost','50000','readVINrcm'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False fv = stdout.find(b'vin=') VIN_read = str(stdout) VIN_read = VIN_read[fv + 6:fv + 23] print("VIN = " + VIN_read) info_l4.config(state=NORMAL) info_l4.delete(1.0, END) info_l4.insert(1.0, "VIN = " + VIN_read) info_l4.config(state=DISABLED) def get_VIN_IPC(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error command_error = False print("Get VIN ipc") p = Popen([sys.executable, "pynetcat.py",'localhost','50000','readVINipc'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c log_VIN_SYNC.bat") stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False fv = stdout.find(b'vin=') VIN_read = str(stdout) VIN_read = VIN_read[fv + 6:fv + 23] print("VIN = " + VIN_read) info_l4.config(state=NORMAL) info_l4.delete(1.0, END) info_l4.insert(1.0, "VIN = " + VIN_read) info_l4.config(state=DISABLED) def disconnect(): global User_Connect, CONNECTED_BUS_TYPE, CONNECTED_BUS_SPEED global command_error, servercmd print("BT Disconnect") os.system("start /wait cmd /c bt_disconnect.bat") global User_Connect User_Connect = False command_error = False info_l4.config(state=NORMAL) info_l4.delete(1.0, END) info_l4.insert(1.0, "VIN = <no connection>") info_l4.config(state=DISABLED) CONNECTED_BUS_SPEED = "None" CONNECTED_BUS_TYPE = "None" try: servercmd.kill() except: pass def speaker_LF(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error # take into account the speaker config, AHU type, and AMP presence print("Speaker LF") # Check for AMP first if Amp_THX_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableLFtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_SONY_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableLFtwt8'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_HARMAN_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableLFtwt4H'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # then check by AHU and speaker type elif AHU_Clar.get(): if Speaker1.get(): # no tweeters print("AHU=Clar, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableLF4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: # with tweeters p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableLFtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif AHU_Pana.get() or AHU_PanaGap.get(): print("Panasonic") if Speaker1.get(): # no tweeters print("AHU=Pana, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableLF4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: # with tweeters print("AHU=Pana, Speaker=2/3") # os.system("start /wait cmd /c speakerEnableLFtwt_Clarion.bat") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableLFtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif AHU_Vist.get() or AHU_VistGap.get(): # print("Visteon") if Speaker1.get(): print("AHU=Visteon, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableLF'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableLFtwt'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def speaker_RF(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error print("Speaker RF") if Amp_THX_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableRFtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_SONY_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableRFtwt8'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_HARMAN_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableRFtwt4H'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # then check by AHU and speaker type elif AHU_Clar.get(): if Speaker1.get(): print("AHU=Clar, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRF4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRFtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif AHU_Pana.get() or AHU_PanaGap.get(): # os.system("start /wait cmd /c speakerEnableRFtwt_Panasonic.bat") if Speaker1.get(): print("AHU=Pana, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRF4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: print("AHU=Pana, Speaker=2") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRFtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif AHU_Vist.get() or AHU_VistGap.get(): if Speaker1.get(): print("AHU=Visteon, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRF'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRFtwt'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def speaker_LR(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error print("Speaker LR") if Amp_THX_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableLRtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_SONY_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableLRtwt8'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_HARMAN_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableLRtwt4H'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # then check by AHU and speaker type elif AHU_Clar.get(): if Speaker1.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableLR4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableLR4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif AHU_Pana.get()or AHU_PanaGap.get(): if Speaker1.get(): print("AHU=Pana, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableLR4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: print("AHU=Pana, Speaker=2") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableLR4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif AHU_Vist.get() or AHU_VistGap.get(): if Speaker1.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableLR'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableLR'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def speaker_RR(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error print("Speaker RR") if Amp_THX_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableRRtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_SONY_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableRRtwt8'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_HARMAN_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableRRtwt4H'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # then check by AHU and speaker type elif AHU_Clar.get(): if Speaker1.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRR4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRR4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif AHU_Pana.get()or AHU_PanaGap.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRR4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c speakerEnableRR_Panasonic.bat") elif AHU_Vist.get() or AHU_VistGap.get(): if Speaker1.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRR'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRR'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def speaker_All(check=True): # check used to supress waring when used as AMP Detector if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error print("Speaker All") if Amp_THX_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableAllOn4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_SONY_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableAllOn8'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_HARMAN_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableAllOn4H'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # then check by AHU and speaker type elif AHU_Clar.get(): # works on P552 p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableAllOn4Clarion'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c speakerEnableAllOn_Clarion.bat") elif AHU_Pana.get()or AHU_PanaGap.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableAllOn4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c speakerEnableAllOn_Panasonic.bat") elif AHU_Vist.get() or AHU_VistGap.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableAllOn'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c speakerEnableAllOn_Visteon.bat") stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") if check: command_error = True return False else: command_error = False return True def speaker_Center(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return # os.system("start /wait cmd /c speakerEnableCntr_Clarion.bat") global command_error print("Speaker Center") if Amp_THX_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableCntr'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_SONY_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableCntr8'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_HARMAN_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableCntrH'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # then check by AHU and speaker type elif AHU_Clar.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableCntrtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c speakerEnableAllOn_Clarion.bat") elif AHU_Pana.get()or AHU_PanaGap.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableCntrtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c speakerEnableAllOn_Panasonic.bat") elif AHU_Vist.get() or AHU_VistGap.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableCntrtwt'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c speakerEnableAllOn_Visteon.bat") stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def speaker_Sub(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return print("Speaker Sub") # os.system("start /wait cmd /c speakerEnableSub_Clarion.bat") global command_error if Amp_THX_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableSub4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_SONY_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableSub8'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_HARMAN_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableSub4H'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # then check by AHU and speaker type elif AHU_Clar.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableSub4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c speakerEnableAllOn_Clarion.bat") elif AHU_Pana.get()or AHU_PanaGap.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableSub4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c speakerEnableAllOn_Panasonic.bat") elif AHU_Vist.get() or AHU_VistGap.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableSub'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # os.system("start /wait cmd /c speakerEnableAllOn_Visteon.bat") stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def speaker_FrontOnly(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error print("Speaker Front Only") if Amp_THX_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableFtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_SONY_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableFtwt8'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_HARMAN_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableFtwt4H'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # then check by AHU and speaker type elif AHU_Clar.get(): if Speaker1.get(): print("AHU=Clar, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableF4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableFtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif AHU_Pana.get()or AHU_PanaGap.get(): if Speaker1.get(): print("AHU=Pana, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableF4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: print("AHU=Pana, Speaker=2") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableFtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif AHU_Vist.get() or AHU_VistGap.get(): if Speaker1.get(): print("AHU=Visteon, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableF'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableFtwt'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def speaker_RearOnly(): if not User_Connect: tkinter.messagebox.showinfo("No Connection", "Please connect to a CAN device") return global command_error print("Speaker Rear Only") if Amp_THX_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableRtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_SONY_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableRtwt8'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif Amp_HARMAN_Present.get(): p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'AMPspeakerEnableRtwt4H'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) # then check by AHU and speaker type elif AHU_Clar.get(): if Speaker1.get(): print("AHU=Clar, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableR4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif AHU_Pana.get()or AHU_PanaGap.get(): if Speaker1.get(): print("AHU=Pana, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableR4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: print("AHU=Pana, Speaker=2") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRtwt4'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) elif AHU_Vist.get() or AHU_VistGap.get(): if Speaker1.get(): print("AHU=Visteon, Speaker=1") p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableR'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) else: p = Popen([sys.executable, "pynetcat.py", 'localhost', '50000', 'speakerEnableRtwt'], creationflags=CREATE_NEW_CONSOLE, stdout=PIPE, stderr=PIPE) stdout, stderr = p.communicate() if stdout.find(b'Error') > 0: print("Error sending last command!") command_error = True else: command_error = False def CAN_setup0(): #500 HS if User_Connect: if (CONNECTED_BUS_SPEED == "500") and (CONNECTED_BUS_TYPE == "hs"): sp_500_HS.set(True) else: sp_500_HS.set(False) tkinter.messagebox.showinfo("CAN Config 500 HS Not Implemented", "CAN speed or type change detected. You must disconnect and reconnect to make this effective!") return if sp_500_HS.get: sp_125_HS.set(False) sp_125_MS.set(False) sp_500_MS.set(False) sp_500_HS.set(True) # print("sp_500=" + str(sp_500_HS.get())) print("CAN setup 0") def CAN_setup1(): #125 HS if User_Connect: #and ((CONNECTED_BUS_SPEED != "None") or (CONNECTED_BUS_TYPE != "None")) if (CONNECTED_BUS_SPEED == "125") and (CONNECTED_BUS_TYPE == "hs"): sp_125_HS.set(True) else: sp_125_HS.set(False) tkinter.messagebox.showinfo("CAN Config 125 HS Not Implemented", "CAN speed or type change detected. You must disconnect and reconnect to make this effective!") return if sp_125_HS.get: sp_125_HS.set(True) sp_125_MS.set(False) sp_500_MS.set(False) sp_500_HS.set(False) print("CAN setup 1") def CAN_setup2(): #500 MS if User_Connect: if (CONNECTED_BUS_SPEED == "500") and (CONNECTED_BUS_TYPE == "ms"): sp_500_MS.set(True) else: sp_500_MS.set(False) tkinter.messagebox.showinfo("CAN Config 500 MS Not Implemented", "CAN speed or type change detected. You must disconnect and reconnect to make this effective!") return if sp_500_MS.get: sp_125_HS.set(False) sp_125_MS.set(False) sp_500_MS.set(True) sp_500_HS.set(False) print("CAN setup 2") def CAN_setup3(): # 125 MS if User_Connect: if (CONNECTED_BUS_SPEED == "125") and (CONNECTED_BUS_TYPE == "ms"): sp_125_MS.set(True) else: sp_125_MS.set(False) tkinter.messagebox.showinfo("CAN Config 125 MS Not Implemented", "CAN speed or type change detected. You must disconnect and reconnect to make this effective!") return if sp_125_MS.get: sp_125_HS.set(False) sp_125_MS.set(True) sp_500_MS.set(False) sp_500_HS.set(False) print("CAN setup 3") def AHU_changeP(): print("AHU Change") if AHU_Pana.get(): print("Panasonic") AHU_Pana.set(True) AHU_Clar.set(False) AHU_Vist.set(False) AHU_VistGap.set(False) AHU_PanaGap.set(False) def AHU_changeC(): print("AHU Change") if AHU_Clar.get(): print("Clarion") AHU_Pana.set(False) AHU_Clar.set(True) AHU_Vist.set(False) AHU_VistGap.set(False) AHU_PanaGap.set(False) def AHU_changeV(): print("AHU Change") if AHU_Vist.get(): print("Visteon") AHU_Pana.set(False) AHU_Clar.set(False) AHU_Vist.set(True) AHU_VistGap.set(False) AHU_PanaGap.set(False) def AHU_changeVGap(): print("AHU Change") if AHU_VistGap.get(): print("Visteon Gap") AHU_Pana.set(False) AHU_Clar.set(False) AHU_Vist.set(False) AHU_VistGap.set(True) AHU_PanaGap.set(False) def AHU_changePGap(): #added on Dec 12 2017 print("AHU Change") if AHU_PanaGap.get(): print("Pana Gap") AHU_Pana.set(False) AHU_Clar.set(False) AHU_Vist.set(False) AHU_VistGap.set(False) AHU_PanaGap.set(True) def Amp_SONY_Change(): print("AMP Change") if Amp_SONY_Present.get(): print("SONY AMP") Amp_THX_Present.set(False) Amp_SONY_Present.set(True) Amp_HARMAN_Present.set(False) def Amp_THX_Change(): print("AMP Change") if Amp_THX_Present.get(): print("THX AMP") Amp_THX_Present.set(True) Amp_SONY_Present.set(False) Amp_HARMAN_Present.set(False) def Amp_HARMAN_Change(): print("AMP Change") if Amp_HARMAN_Present.get(): print("HARMAN AMP") Amp_THX_Present.set(False) Amp_SONY_Present.set(False) Amp_HARMAN_Present.set(True) def Sp1_change(): if Speaker1.get(): Speaker2.set(False) Speaker1.set(True) Speaker3.set(False) def Sp2_change(): if Speaker2.get(): Speaker1.set(False) Speaker2.set(True) Speaker3.set(False) def Sp3_change(): if Speaker3.get(): Speaker1.set(False) Speaker2.set(False) Speaker3.set(True) def on_closing(): # handle the close x press if tkinter.messagebox.askokcancel("Quit", "Do you want to quit?"): # root.destroy() quitme() def listenloop(s): # creates thread that monitors for incoming data to the gui port 50001 # to use run this in command line: python pynetcat.py localhost 50001 data global default_volume_front size = 1024 while True: try: client, address = s.accept() print("Client " + str(address) + " connected!") data = client.recv(size) if data: try: data = str(data) print("command recd = " + data) if data.find("about")>0: about() elif data.find("speakerlf")>0: speaker_LF() elif data.find("speakerrf")>0: speaker_RF() elif data.find("speakerlr")>0: speaker_LR() elif data.find("speakerrr")>0: speaker_RR() elif data.find("startBT")>0: onepress() elif data.find("speakerAll")>0: speaker_All() elif data.find("speakerCenter")>0: speaker_Center() elif data.find("speakerSub")>0: speaker_Sub() elif data.find("disconnect")>0: disconnect() elif data.find("config")>0: filename = data[data.find('=') + 1:] filename = str(filename).replace("'","") # remove quotes print("Klippel config :" + filename) LoadConfig(filename) elif data.find("volDownF")>0: default_volume_int = int(default_volume_front) - 1 default_volume_int = max(0, default_volume_int) print("Klippel Vol Down Front = " + str(default_volume_int)) default_volume_front= str(default_volume_int) set_vol_default(default_volume_front) elif data.find("volUpF")>0: default_volume_int = int(default_volume_front) + 1 default_volume_int = min(30, default_volume_int) print("Klippel Vol Up Front = " + str(default_volume_int)) default_volume_front= str(default_volume_int) set_vol_default(default_volume_front) except: print(traceback.format_exc()) print('Command Execution failed!') client.send(b'OK') client.close() except (KeyboardInterrupt, SystemExit): s.close() exit() except socket.timeout: print("Waiting for incoming connection" ) class App: def __init__(self, master): # reference global variables for button position - makes organizing easier global speaker_y, speaker_x, volume_y, vin_y self.frame = Frame(master, relief=SUNKEN) # master.geometry("320x400") master.geometry("%sx%s" % (default_sizex, default_sizey)) master.title("CAN Invader Script Controller") master.bind("<Button-1>", left_mouse) master.bind("<Button-3>", right_mouse) master.bind("<Key>", a_key) self.frame.pack() # info_l1 = Label(master, text="Config... ")# + ConfigFile.config_file) # info_l1.pack(side=TOP) # info_l2 = Label(master, text="Connection Status = NOT CONNECTED") # info_l2.pack(side=TOP) self.disconnect_b = Button(master, text="Disconnect", command=disconnect, fg="red", bg="white", height=1, width=10, font=font1) self.disconnect_b.pack(side=BOTTOM) disconnect_b_ttp = CreateToolTip(self.disconnect_b, "Disconnects BT and stops server - use if changing config") self.startserver_b = Button(master, text="Start Serv", command=start_server, fg="white", bg="blue") self.startserver_b.pack(in_=self.frame) self.startserver_b.place(rely=.12, relx=0) startserver_b_ttp = CreateToolTip(self.startserver_b, "Press First - This needs to be running for other commands to work!") self.connect_b = Button(master, text="Connect", command=connect, fg="blue", bg="white") self.connect_b.pack() self.connect_b.place(rely=.12, relx=.3) Connect_b_ttp = CreateToolTip(self.connect_b, "Connects BT, initializes CAN and starts default TP message.") self.radioOn_b = Button(master, text="Radio On", command=radio_on, fg="white", bg="purple") self.radioOn_b.pack() self.radioOn_b.place(rely=.12, relx=.4) setradioOn__ttp = CreateToolTip(self.radioOn_b, "Enables audio system and sets mode to FM.") self.setBass_b = Button(master, text="Set Bass", command=set_bass, fg="blue", bg="yellow") self.setBass_b.pack() self.setBass_b.place(rely=.2, relx=.2) setBass_b_ttp = CreateToolTip(self.setBass_b, "Set Bass. Select value using slider on right.") self.setTreb_b = Button(master, text="Set Treb", command=set_treble, fg="blue", bg="yellow") self.setTreb_b.pack() self.setTreb_b.place(rely=.2, relx=.34) setTreb_b_ttp = CreateToolTip(self.setTreb_b, "Set Treble. Select value using slider on right.") self.getVINahu_b = Button(master, text="VIN AHU", command=get_VIN_AHU, fg="white", bg="brown", height=2, width=7, font=font1) self.getVINahu_b.pack() self.getVINahu_b.place(rely=vin_y, relx=vin_x) getVINahu_b_ttp = CreateToolTip(self.getVINahu_b, "Read VIN from AHU in F190.") self.getVINabs_b = Button(master, text="VIN ABS", command=get_VIN_ABS, fg="white", bg="brown", height=2, width=7, font=font1) self.getVINabs_b.pack() self.getVINabs_b.place(rely=vin_y, relx=0) getVINabs_b_ttp = CreateToolTip(self.getVINabs_b, "Read VIN from ABS module in F190.") self.getVINsync_b = Button(master, text="VIN SYNC", command=get_VIN_SYNC, fg="white", bg="brown", height=2, width=8, font=font1) self.getVINsync_b.pack() self.getVINsync_b.place(rely=vin_y, relx=vin_x * 5) getVINsync_b_ttp = CreateToolTip(self.getVINsync_b, "Read VIN from SYNC in F190.") self.getVINbcm_b = Button(master, text="VIN BCM", command=get_VIN_BCM, fg="white", bg="brown", height=2, width=7, font=font1) self.getVINbcm_b.pack() self.getVINbcm_b.place(rely=vin_y, relx=vin_x * 2) getVINbcm_b_ttp = CreateToolTip(self.getVINbcm_b, "Read VIN from BCM in F190.") self.getVINipc_b = Button(master, text="VIN IPC", command=get_VIN_IPC, fg="white", bg="brown", height=2, width=7, font=font1) self.getVINipc_b.pack() self.getVINipc_b.place(rely=vin_y, relx=vin_x * 3) getVINipc_b_ttp = CreateToolTip(self.getVINipc_b, "Read VIN from IPC in F190.") self.getVINrcm_b = Button(master, text="VIN RCM", command=get_VIN_RCM, fg="white", bg="brown", height=2, width=7, font=font1) self.getVINrcm_b.pack() self.getVINrcm_b.place(rely=vin_y, relx=vin_x * 4) getVINrcm_b_ttp = CreateToolTip(self.getVINrcm_b, "Read VIN from RCM in F190.") self.setFreq_b = Button(master, text="Set Freq", command=set_freq, fg="blue", bg="orange", height=2, width=7, font=font1) self.setFreq_b.pack() self.setFreq_b.place(rely=.12, relx=.64) # creat tool tips here setFreq_b_ttp = CreateToolTip(self.setFreq_b, "Use box to enter optional frequency. If blank default used.") self.setVol1_b = Button(master, text="Vol=1", command=set_vol1, fg="white", bg="green", height=2, width=6, font=font1) self.setVol1_b.pack() self.setVol1_b.place(rely=volume_y, relx=0) setVol1_b_ttp = CreateToolTip(self.setVol1_b, "Use + and - to adjust the value of this button.") self.setVol5_b = Button(master, text="Vol=5", command=set_vol5, fg="white", bg="green", height=2, width=6, font=font1) self.setVol5_b.pack() self.setVol5_b.place(rely=volume_y, relx=.16) self.setVol16_b = Button(master, text="Vol=16", command=set_vol16, fg="white", bg="green", height=2, width=6, font=font1) self.setVol16_b.pack() self.setVol16_b.place(rely=volume_y, relx=.32) setVol16_b_ttp = CreateToolTip(self.setVol16_b, "Use < and > to adjust the value of this button.") self.setVol19_b = Button(master, text="Vol Front", command=set_vol19, fg="white", bg="lime", height=2, width=6, font=font1, wraplength=60) self.setVol19_b.pack() self.setVol19_b.place(rely=volume_y, relx=.48) setVol19_b_ttp = CreateToolTip(self.setVol19_b, "Press to set the volume to FRONT default setting") # self.setVol19_b = Button(master, text="Vol=19", command=set_vol19, fg="white", bg="green", height=2, width=6, font=font1) # self.setVol19_b.pack() # self.setVol19_b.place(rely=volume_y, relx=.48) self.setVol22_b = Button(master, text="Vol Rear", command=set_vol22, fg="white", bg="lime", height=2, width=6, font=font1, wraplength=60) self.setVol22_b.pack() self.setVol22_b.place(rely=volume_y, relx=.64) setVol22_b_ttp = CreateToolTip(self.setVol22_b, "Press to set the volume to REAR default setting") # self.setVol22_b = Button(master, text="Vol=22", command=set_vol22, fg="white", bg="green", height=2, width=6, font=font1) # self.setVol22_b.pack() # self.setVol22_b.place(rely=volume_y, relx=.64) self.setVolX_b = Button(master, text="Set VolX", command=set_volX, fg="white", bg="green", height=2, width=7, font=font1) self.setVolX_b.pack() self.setVolX_b.place(rely=volume_y, relx=.8) setVolX_b_ttp = CreateToolTip(self.setVolX_b, "Use slider on right to select desired value") self.speakerLF_b = Button(master, text="Speaker LF", command=speaker_LF, fg="white", bg="black", height=2, width=10, font=font1) self.speakerLF_b.pack() self.speakerLF_b.place(rely=speaker_y + .12, relx=speaker_x) speakerLF_b_ttp = CreateToolTip(self.speakerLF_b, "Enable LEFT FRONT speaker only") self.speakerCenter_b = Button(master, text="Speaker Center", command=speaker_Center, fg="white", bg="black", height=2, width=12, font=font1) self.speakerCenter_b.pack() self.speakerCenter_b.place(rely=speaker_y + .12, relx=speaker_x + .2) speakerCenter_b_ttp = CreateToolTip(self.speakerCenter_b, "Enable Center Speaker only") self.speakerRF_b = Button(master, text="Speaker RF", command=speaker_RF, fg="white", bg="black", height=2, width=10, font=font1) self.speakerRF_b.pack() self.speakerRF_b.place(rely=speaker_y + .12, relx=speaker_x + .43) speakerRF_b_ttp = CreateToolTip(self.speakerRF_b, "Enable RIGHT FRONT speaker only") self.speakerF_b = Button(master, text="Spk. Front", command=speaker_FrontOnly, fg="white", bg="gray", height=2, width=10, font=font1) self.speakerF_b.pack() self.speakerF_b.place(rely=speaker_y + .12, relx=speaker_x + .63) speakerF_b_ttp = CreateToolTip(self.speakerF_b, "Enable ALL FRONT speakers only") self.speakerRR_b = Button(master, text="Speaker RR", command=speaker_RR, fg="white", bg="black", height=2, width=10, font=font1) self.speakerRR_b.pack() self.speakerRR_b.place(rely=speaker_y + .28, relx=speaker_x + .43) speakerRR_b_ttp = CreateToolTip(self.speakerRR_b, "Enable RIGHT REAR speaker only") self.speakerR_b = Button(master, text="Spk. Rear", command=speaker_RearOnly, fg="white", bg="gray", height=2, width=10, font=font1) self.speakerR_b.pack() self.speakerR_b.place(rely=speaker_y + .28, relx=speaker_x + .63) speakerR_b_ttp = CreateToolTip(self.speakerR_b, "Enable ALL REAR speakers only") self.speakerSub_b = Button(master, text="Speaker Sub", command=speaker_Sub, fg="white", bg="black", height=2, width=10, font=font1) self.speakerSub_b.pack() self.speakerSub_b.place(rely=speaker_y + .28, relx=speaker_x + .2) speakerSub_b_ttp = CreateToolTip(self.speakerSub_b, "Enable Subwoofer only") self.speakerLR_b = Button(master, text="Speaker LR", command=speaker_LR, fg="white", bg="black", height=2, width=10, font=font1) self.speakerLR_b.pack() self.speakerLR_b.place(rely=speaker_y + .28, relx=speaker_x) speakerLR_b_ttp = CreateToolTip(self.speakerLR_b, "Enable LEFT REAR speaker only") self.speakerAll_b = Button(master, text="Speaker ALL", command=speaker_All, fg="white", bg="black", height=6, width=7, font=font1, wraplength=80) self.speakerAll_b.pack() self.speakerAll_b.place(rely=speaker_y + .12, relx=speaker_x + .82) speakerAll_b_ttp = CreateToolTip(self.speakerAll_b, "Turn all speakers on to original setting") self.Testerp_b = Button(master, text="TesterP On", command=testerPon, fg="blue", bg="pink") self.Testerp_b.pack() self.Testerp_b.place(rely=1, relx=0) self.TesterpOff_b = Button(master, text="TesterP Off", command=testerPoff, fg="blue", bg="pink") self.TesterpOff_b.pack() self.TesterpOff_b.place(rely=.84, relx=.80) self.onepress_b = Button(master, text="Start Here!", command=onepress, fg="white", bg="blue", height=2, width=10, font=font1) self.onepress_b.pack() self.onepress_b.place(rely=.12, relx=0) onepress_b_ttp = CreateToolTip(self.onepress_b, "Starts server, configures CAN, TP on, radio on, sets treb bass vol and freq to default") self.Test_b = Button(master, text="Test", command=NONE, fg="blue", bg="pink") self.Test_b.pack() self.Test_b.place(rely=.9, relx=0) class CreateToolTip(object): # create a tooltip for a given widget def __init__(self, widget, text='widget info'): self.widget = widget self.text = text self.widget.bind("<Enter>", self.enter) self.widget.bind("<Leave>", self.close) def enter(self, event=None): x = y = 0 x, y, cx, cy = self.widget.bbox("insert") x += self.widget.winfo_rootx() + 25 y += self.widget.winfo_rooty() + 20 # creates a toplevel window self.tw = tk.Toplevel(self.widget) # Leaves only the label and removes the app window self.tw.wm_overrideredirect(True) self.tw.wm_geometry("+%d+%d" % (x, y)) label = tk.Label(self.tw, text=self.text, justify='left', background='yellow', relief='solid', borderwidth=1, font=("times", "10", "normal")) label.pack(ipadx=1) def close(self, event=None): if self.tw: self.tw.destroy() # ================================================================================================================== # ================================================================================================================== # create global variable for the configuration file User_Connect = False root = Tk() CONNECTED_BUS_TYPE = "None" CONNECTED_BUS_SPEED = "None" loaded_config = StringVar() loaded_config.set('Config file not loaded!!') e_popup = False VIN_ecu = "" ocolor = root.cget('bg') info_l1 = Label(root, textvariable=loaded_config, font ="12") info_l1.pack(side=TOP) info_l1.place(relx=0) default_volume_front = 0 default_volume_rear = 0 # global positioning variables to make life easier speaker_y = .47 speaker_x = 0 volume_y = .42 vin_y = .27 vin_x = .16 # FRONT volume label loaded_volume = StringVar() loaded_volume.set('Front Volume Setting = tbd') info_l3 = Label(root, textvariable=loaded_volume, font="12") info_l3.pack(side=TOP) info_l3.place(relx=.65) # REAR volume label loaded_Rvolume = StringVar() loaded_Rvolume.set('Rear Volume Setting = tbd') info_l13 = Label(root, textvariable=loaded_Rvolume, font="12") info_l13.pack() info_l13.place(rely=.05, relx=.65) # VIN label info_l4 = Text(root, height=1) info_l4.insert(1.0,'VIN = <no connection>') info_l4.pack() info_l4.place(relx=.65, rely=.94) info_l4.configure(bg=root.cget('bg'), relief=FLAT, font="12") # Freq label loaded_freq = StringVar() loaded_freq.set('Default Freq = ') info_l5 = Label(root, textvariable=loaded_freq, font="12") info_l5.pack() info_l5.place(relx=.78, rely=.19) # Define fonts to use font1 = font.Font(family='Helvetica', size='14') tpid = Entry(root, bd =2, width=3) tpid.pack() tpid.place(rely=.76, relx=.82) tpid_ttp = CreateToolTip(tpid, "Enter optional ECU ID for tester present on message. ex: 7DF") fin = Entry(root, bd =2, width=5) fin.pack() fin.place(rely=.13, relx=.8) fin_ttp = CreateToolTip(fin, "Enter valid FM freq from 87.50 to 108.00") v_scale = Scale(root, from_=30, to=0) v_scale.pack() v_scale.place(rely=speaker_y - .12, relx=.935) tpid_off = Entry(root, bd=2, width=3) tpid_off.pack() tpid_off.place(rely=.92, relx=.82) tpid_off_ttp = CreateToolTip(tpid_off, "Enter ECU ID to disable tester present message. ex: 7DF") # bass_in = Entry(root, bd=2, width=2) # bass_in.pack() # bass_in.place(rely=.21, relx=.285) # bass_in_ttp = CreateToolTip(bass_in, "Enter bass -7 to 7. Defaults to 7(max)") bass_scale = Scale(root, from_=7, to=-7, showvalue=7, width=10, length=50, sliderlength=20) bass_scale.pack() bass_scale.place(rely=.17, relx=.275) #bass_scale.set(7) # treb_in = Entry(root, bd=2, width=2) # treb_in.pack() # treb_in.place(rely=.21, relx=.427) # treb_in_ttp = CreateToolTip(treb_in, "Enter treble -7 to 7. Defaults to 0(nom)") treb_scale = Scale(root, from_=7, to=-7, showvalue=7, width=10, length=50, sliderlength=20) treb_scale.pack() treb_scale.place(rely=.17, relx=.427) #treb_scale.set(0) # create a top level menu menubar = Menu(root) menubar.add_command(label="Quit!", command=on_closing) # add CAN setup selection to menu bar sp_500_HS = tk.BooleanVar() sp_500_HS.set(False) sp_125_HS = tk.BooleanVar() sp_125_HS.set(False) sp_500_MS = tk.BooleanVar() sp_500_MS.set(False) sp_125_MS = tk.BooleanVar() sp_125_MS.set(False) cansp_menu = tk.Menu(menubar, background='white') cansp_menu.add_checkbutton(label="500K on HS", onvalue=True, offvalue=False, variable=sp_500_HS, command=CAN_setup0) cansp_menu.add_checkbutton(label="125K on HS", onvalue=True, offvalue=False, variable=sp_125_HS, command=CAN_setup1) cansp_menu.add_checkbutton(label="500K on MS", onvalue=True, offvalue=False, variable=sp_500_MS, command=CAN_setup2) cansp_menu.add_checkbutton(label="125K on MS", onvalue=True, offvalue=False, variable=sp_125_MS, command=CAN_setup3) menubar.add_cascade(label='CAN Setup', menu=cansp_menu) # add AMP setup selection to menu bar # ECU Diagnostic Reception ID 0x0783 CAN ID for physically addressed diagnostic requests.This parameter is only relevant, if a 11 bit identifier (=> normal addressing) is used. # ECU Diagnostic Transmission ID 0x078B CAN ID for physically addressed diagnostic responses.This parameter is only relevant, if a 11 bit identifier (=> normal addressing) is used. Amp_THX_Present = tk.BooleanVar() Amp_THX_Present.set(False) Amp_SONY_Present = tk.BooleanVar() Amp_SONY_Present.set(False) Amp_HARMAN_Present = tk.BooleanVar() Amp_HARMAN_Present.set(False) Amp_menu = tk.Menu(menubar, background='white') Amp_menu.add_checkbutton(label="THX AMP", onvalue=True, offvalue=False, variable=Amp_THX_Present, command=Amp_THX_Change) Amp_menu.add_checkbutton(label="SONY AMP", onvalue=True, offvalue=False, variable=Amp_SONY_Present, command=Amp_SONY_Change) Amp_menu.add_checkbutton(label="HARMAN AMP", onvalue=True, offvalue=False, variable=Amp_HARMAN_Present, command=Amp_HARMAN_Change) menubar.add_cascade(label='AMP', menu=Amp_menu) # add AHU selection to menu bar AHU_Pana = tk.BooleanVar() AHU_Clar = tk.BooleanVar() AHU_Vist = tk.BooleanVar() AHU_VistGap = tk.BooleanVar() AHU_PanaGap = tk.BooleanVar() AHU_Pana.set(True) AHU_Clar.set(False) AHU_Vist.set(False) AHU_VistGap.set(False) AHU_PanaGap.set(False) AHU_menu = tk.Menu(menubar, background='white') AHU_menu.add_checkbutton(label="Panasonic", onvalue=True, offvalue=False, variable=AHU_Pana, command=AHU_changeP) AHU_menu.add_checkbutton(label="Clarion", onvalue=True, offvalue=False, variable=AHU_Clar, command=AHU_changeC) AHU_menu.add_checkbutton(label="Visteon", onvalue=True, offvalue=False, variable=AHU_Vist, command=AHU_changeV) AHU_menu.add_checkbutton(label="Visteon-GAP", onvalue=True, offvalue=False, variable=AHU_VistGap, command=AHU_changeVGap) AHU_menu.add_checkbutton(label="Pana-1DIN", onvalue=True, offvalue=False, variable=AHU_PanaGap, command=AHU_changePGap) menubar.add_cascade(label='AHU', menu=AHU_menu) # add Speaker Setup selection to menu bar Speaker1 = tk.BooleanVar() Speaker2 = tk.BooleanVar() Speaker3 = tk.BooleanVar() Speaker1.set(True) Speaker2.set(False) Speaker3.set(False) speaker_menu = tk.Menu(menubar,background='white') speaker_menu.add_checkbutton(label="No Tweeters", onvalue=True, offvalue=False, variable=Speaker1, command=Sp1_change) speaker_menu.add_checkbutton(label="With Tweeters", onvalue=True, offvalue=False, variable=Speaker2, command=Sp2_change) speaker_menu.add_checkbutton(label="Config 3", onvalue=True, offvalue=False, variable=Speaker3, command=Sp3_change) menubar.add_cascade(label='Speakers', menu=speaker_menu) info_l2 = Label(root, text="Connection Status = NOT CONNECTED", font="12") info_l2.pack(side=TOP) info_l2.place(relx=0, rely=.05) # Check Connection Status in periodic update loop def task(): global e_popup, servercmd ConfigFile.User_AMP_Selection = Amp_THX_Present.get() # print("AMP present = " + str(User_AMP_Selection)) print("User Connect = " + str(User_Connect)) # print("OOBD Connect = " + str(OOBDControl.ConnectTest)) if not User_Connect: info_l2.configure(text="Connection Status = NOT CONNECTED", fg='red') else: info_l2.configure(text="Connection Status = CONNECTED!", fg='green') if command_error: root.configure(background='red') if not e_popup: tkinter.messagebox.showinfo("CAN Error", "No response, Late response or Negative response (7F) from last message request!") e_popup = True # show only 1 popup - no need to over do it! else: root.configure(background=ocolor) e_popup = False # check the servercmd status if showing connected - someone may have closed it then nothing will work!! if User_Connect: server_status = servercmd.poll() print ("Server status = " + str(server_status) + "(None = running)") if server_status is not None: # server was terminated and needs to restart print("Server was terminated unexpectedly!! Forcing disconnect...") tkinter.messagebox.showinfo("Error", "Server process was terminated unexpectedly!! Forcing disconnect...") disconnect() root.after(4000, task) # reschedule event every 4 seconds after first call # start the periodic check loop for first time - need this here!! root.after(1000, task) # add Configuration Config_menu = tk.Menu(menubar, background='white') for i in range(len(ConfigFile.config_list2)): # submenu.add_command(label=ConfigFile.config_list[i], command=lambda : ConfigSelect(selection=i)) Config_menu.add_command(label=ConfigFile.config_list2[i]["displayname"], command=lambda s=i: ConfigSelect(selection=s)) menubar.add_cascade(label='Configuration', menu=Config_menu) # add about item to menu bar Help_menu = tk.Menu(menubar, background='white') Help_menu.add_command(label="About", command=about) Help_menu.add_command(label="Instructions", command=show_instructions) # Help_menu.add_separator() #submenu = Menu(Help_menu) # automatically scroll thru the list and add to the menu the displayname #for i in range(len(ConfigFile.config_list2)): # submenu.add_command(label=ConfigFile.config_list[i], command=lambda : ConfigSelect(selection=i)) # submenu.add_command(label=ConfigFile.config_list2[i]["displayname"], command=lambda s=i: ConfigSelect(selection=s)) #Help_menu.add_cascade(label='Configuration', menu=submenu, underline=0) menubar.add_cascade(label='Help', menu=Help_menu) # display the menu root.config(menu=menubar) # Calls the app class above app = App(root) # hide engineering mode things Hide(True) # Load the configuration file if present - needs to be done after to App(root) and Hide(True) to allow hiding/showing for the buttons LoadConfig(ConfigFile.config_file_default) config_file = ConfigFile.config_file_default # add handler for the exit root.protocol("WM_DELETE_WINDOW", on_closing) # set up listening socket HOST = 'localhost' # Symbolic name same as the tcp_server name PORT = 50001 # equal to tcpserver port + 1 - needs to be unique to avoid confusion s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) print('Socket created') # Bind socket to local host and port try: s.bind((HOST, PORT)) except socket.error as msg: print ('Bind failed. Error Code : ' + str(msg[0]) + ' Message ' + msg[1]) #sys.exit() print ('Socket bind complete') # Start listening on socket s.listen(5) # set backlog s.settimeout(2) print('Socket now listening') # start new thread for incoming server #threading.Thread(target=listenloop, args=(s,)).start() listen_thread = threading.Thread(target=listenloop, args=(s,)) listen_thread.daemon = True listen_thread.start() root.mainloop()
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twcannon/MSDataSci
16,844,861,757,753
7d7bb2f0bff956a4cd9ba2cc8040f5419fdb53d9
d11fefd843ba5f3909871c8ec64e36b4bd2f37c3
/DATA505/projects/P1_cannon.py
2d0bc5a049dd49c78c8120b0cae4a61c843599ce
[]
no_license
https://github.com/twcannon/MSDataSci
d7065ff16537c23c2a29a95e2f79565cd15df4b0
443ef45cf6594f61ae35ad16c62b040c9386e2c2
refs/heads/master
2023-07-19T02:14:09.665138
2020-05-22T14:10:48
2020-05-22T14:10:48
195,902,104
0
0
null
false
2023-07-06T21:42:00
2019-07-09T00:06:58
2020-05-22T14:11:08
2023-07-06T21:41:59
163,298
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Python
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import numpy as np from scipy import spatial import matplotlib.pyplot as plt debug = False sample_data = np.genfromtxt('501/data/project_one/TABLE2.csv', delimiter = ',') print('Sample Data: \n'+sample_data) if debug else next doc_labels = ['cl','c2','c3','c4','c5','m1','m2','m3','m4'] terms = ['human','interface','computer','user','system','response','time','EPS','survey','trees','graph','minors'] T,S,D = np.linalg.svd(sample_data, full_matrices = False) print('Calculated T Data: \n'+T) if debug else next print('Calculated S Data: \n'+S) if debug else next print('Calculated D Data: \n'+D) if debug else next Si = 1/S Si = Si*np.identity(9) print('S Inverse: \n'+Si) if debug else next Dt = np.transpose(D) print('Transposed D: \n'+Dt) if debug else next def plot_labels(data,labels,offset): for i in range(len(labels)): plt.text(data[i,0]+offset, data[i,1]-offset, labels[i], fontsize=8) plt.scatter(T[:,0], T[:,1], color='red', marker='.', label='Terms') plt.scatter(Dt[:,0], Dt[:,1], color='blue', marker='s', label='Documents') plot_labels(T,terms,0.015) plot_labels(Dt,doc_labels,0.015) plt.title('2-D plot of Terms and Documents with Queries') plt.xlabel('Dimension-1') plt.ylabel('Dimension-2') plt.legend() plt.show() q_labels = ['q1','q2','q3','q4','q5'] X = [[0,0,0,1,0], [1,0,1,0,0], [1,1,0,0,0], [1,1,1,0,1], [0,0,1,2,0], [0,1,0,1,1], [0,1,0,0,0], [0,0,1,1,0], [0,1,1,0,0], [0,0,0,0,0], [0,0,0,0,0], [0,0,0,0,0]] Q = np.matmul(np.matmul(np.transpose(X),T),Si) print('Calculated Query Data: \n'+Q) if debug else next plt.scatter(T[:,0], T[:,1], color='red', marker='.', label='Terms') plt.scatter(Dt[:,0], Dt[:,1], color='blue', marker='s', label='Documents') plt.scatter(Q[:,0], Q[:,1], color='green', marker='x', label='Queries') plot_labels(T,terms,0.015) plot_labels(Dt,doc_labels,0.015) plot_labels(Q,q_labels,0.015) plt.title('2-D plot of Terms and Documents with Queries') plt.xlabel('Dimension-1') plt.ylabel('Dimension-2') plt.legend() plt.show() T_dist_list = [] T_dist_index = [] Dt_dist_list = [] Dt_dist_index = [] for i in range(len(Q)): T_dist_list.append([np.inf,np.inf,np.inf]) T_dist_index.append([np.inf,np.inf,np.inf]) Dt_dist_list.append([np.inf,np.inf,np.inf]) Dt_dist_index.append([np.inf,np.inf,np.inf]) q=Q[i,0:2] for j in range(len(T)): t=T[j,0:2] list_max = np.amax(T_dist_list[i]) min_index = np.where(T_dist_list[i] == np.amax(list_max))[0][0] d = spatial.distance.cosine(q, t) if d < list_max: T_dist_list[i][min_index] = d T_dist_index[i][min_index] = j print(T_dist_list) if debug else next print(T_dist_index) if debug else next for k in range(len(Dt)): dt=Dt[k,0:2] list_max = np.amax(Dt_dist_list[i]) min_index = np.where(Dt_dist_list[i] == np.amax(list_max))[0][0] d = spatial.distance.cosine(q, t) if d < list_max: Dt_dist_list[i][min_index] = d Dt_dist_index[i][min_index] = k print(Dt_dist_list) if debug else next print(Dt_dist_index) if debug else next for i in range(len(Q)): print('\nThe three closest Terms by cosine distance to Query {} are:'.format(q_labels[i])) for j in range(len(T_dist_list[i])): print(' Term: {}, by a distance of: {}'.format(terms[T_dist_index[i][j]],T_dist_list[i][j])) for i in range(len(Q)): print('\nThe three closest Documents by cosine distance to Query {} are:'.format(q_labels[i])) for j in range(len(T_dist_list[i])): print(' Document: {}, by a distance of: {}'.format(doc_labels[T_dist_index[i][j]],T_dist_list[i][j]))
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P1_cannon.py
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ai-how/inputpipeline
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/input.py
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[]
no_license
https://github.com/ai-how/inputpipeline
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2021-05-10T21:18:59.341871
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import tensorflow as tf import threading ##================================================## ## good practice to limit data processing to CPU ## ##================================================## def return_batch(train, list_of_columns): with tf.device("/cpu:0"): train = train.sample(frac=1).reset_index(drop=True) # ensure the train data is shuffled at each epoch X_train = train[[list_of_columns]] # list_of_columns indicating the set of features to be used for training Y_train = train['labels'] # labels corresponds to target variable return X_train, Y_train queue_capacity = 2000 # indicates how much a queue can hold at any time queue = tf.RandomShuffleQueue(shapes = [[no_of_features],[]], dtypes = [tf.float32, tf.int32 capacity=queue_capacity min_after_dequeue=1000) ##================================================## ## placeholder to hold features and labels data ## ##================================================## X = tf.placeholder(dtype=tf.float32, shape = [None,no_of_features]) Y = tf.placeholder(dtype=tf.int32, shape = [None,]) ##================================================## ## operation to fill and close the queue ## ##================================================## enqueue_op = queue.enqueue_many([X,Y]) close_op = queue.close() ##================================================## ## operation to fetch mini-batches in training ## ##================================================## X_batch, Y_batch = queue.dequeue_many(128) # 128 is the size of mini-batch, ususally a hyperparameter def enqueue(sess, train,list_of_columns): for i in range(no_epochs): # run the loop for no. of epochs used for model training X_train, Y_train = return_batch(train, list_of_columns) start_pos =0 ##================================================## ## ensures the queue is filled all the time ## ##================================================## while start_pos < X_train.shape[0]: end_pos = start_pos+queue_capacity feed_X = X_train[start_pos:end_pos] feed_Y = Y_train[start_pos:end_pos] sess.run(enqueue_op, feed_dict = {X: feed_X, Y: feed_Y}) start_pos + = queue_capacity sess.run(close_op) ##================================================## ## operation to start the queue and fetch data ## ##================================================## with tf.Session as sess: tf.train.start_queue_runners(sess=sess) enqueue_thread = threading.Thread(target=enqueue, args=(sess,train,list_of_columns)) enqueue_thread.start() ##================================================## ## fetch minibatches in each iteration ## ##================================================## for i in range(no_epochs): for in range(no_of_iter): batch_X, batch_Y = sess.run([X_batch, Y_batch]) # batch_X and batch_y shapes are (128,no_of_features), (1,128) # use these mini-batches to train your AI models
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mohnish-gobo/ifog_light_hue
1,554,778,176,644
5fff5c58814f2d301871addd5f98f419a4dfeccf
6e2344a342577b51faefcc30f762be675d4209ab
/app.py
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2020-06-20T10:21:25.512204
2016-11-28T18:32:51
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#!/usr/bin/env python import urllib import json import os import requests from flask import Flask from flask import request from flask import make_response # Flask app should start in global layout app = Flask(__name__) @app.route('/webhook', methods=['POST']) def webhook(): req = request.get_json(silent=True, force=True) #print("Request:") #print(json.dumps(req, indent=4)) res = makeWebhookResult(req) res = json.dumps(res, indent=4) print(res) r = make_response(res) r.headers['Content-Type'] = 'application/json' return r def makeWebhookResult(req): #if req.get("result").get("action") != "light": #return {} result = req.get("result") parameters = result.get("parameters") state = parameters.get("light1") brightness = parameters.get("number") if state == "": state = 'on' if brightness == "": brightness = 250 elif int(brightness) > 250: brightness = 250 else: brightness = int(brightness) #print(json.dumps(item, indent=4)) url = "http://ac9baf93.ngrok.io/api/PwZ5n9cSlbRssx0bMipb69lNIj4Sn7m8vTLwS2bR/lights/6/state" body = {"on": True,"bri": brightness} print("State:") print(state) print("URL:") print(url) print("BODY:") print(body) if state == 'on': body = {"on": True,"bri": brightness} else: body = {"on": False, "bri": 0 } response = requests.put(url, data=json.dumps(body)) if response.status_code == 200: if state == 'on': speech = "The light is now switched " + state + " with brightness of " + str(brightness) if state == 'off': speech = "The light is now switched " + state else: speech = "The light was not switched " + state + " due to an error. Please try again." print("Response:") print(speech) return { "speech": speech, "displayText": speech, # "data": data, # "contextOut": [], "source": "ifog_light_hue" } if __name__ == '__main__': port = int(os.getenv('PORT', 5000)) print('Starting app on port %d' % port) app.run(debug=True, port=port, host='0.0.0.0')
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snaiperx8/pizza
4,217,657,892,271
7e3e6e6caafd376f2949cf50338d17de94799dd8
437f47b9420c9dbdcb519e8f2187a0ba2c8bf52f
/pizza/urls.py
fc84cbba56f50e647bc0ad84b4296bae968ba9c0
[]
no_license
https://github.com/snaiperx8/pizza
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refs/heads/master
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from django.contrib import admin from django.urls import path from django.conf.urls.static import static from django.conf import settings from authenticate_app.views import login_view, logout_view, signup_view, home urlpatterns = [ path('admin/', admin.site.urls), path('', home, name = 'home-url'), path('accounts/login/', login_view, name = 'login-url'), path('accounts/logout/', logout_view, name = 'logout-url'), path('accounts/signup/', signup_view, name = 'signup-url'), ] + static(settings.MEDIA_URL, document_root = settings.MEDIA_ROOT)
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chenxuhl/Nestnet
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aa1621bae671a34b5ec4ad3ece918301bd9ba276
/main.py
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[]
no_license
https://github.com/chenxuhl/Nestnet
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# -*- coding:utf-8 -*- # Author : Ray # Data : 2019/7/25 2:15 PM from data import * from model import * import warnings warnings.filterwarnings('ignore') # os.environ['CUDA_VISIBLE_DEVICES'] = '0' aug_args = dict( rotation_range = 0.2, width_shift_range = 0.05, height_shift_range = 0.05, shear_range = 0.05, zoom_range = 0.05, horizontal_flip = True, vertical_flip = True, fill_mode = 'nearest' ) #生成训练数据,返回迭代器 train_gene = trainGenerator(batch_size=2,aug_dict=aug_args,train_path='data/train/', image_folder='train_img',label_folder='train_label', image_color_mode='rgb',label_color_mode='rgb', image_save_prefix='image',label_save_prefix='label', flag_multi_class=True,num_class=4,save_to_dir=None ) val_gene = valGenerator(batch_size=2,aug_dict=aug_args,val_path='data/train/', image_folder='val_img',label_folder='val_label', image_color_mode='rgb',label_color_mode='rgb', image_save_prefix='image',label_save_prefix='label', flag_multi_class=True,num_class=4,save_to_dir=None ) tensorboard = TensorBoard(log_dir='./log') # model, loss_function = unet(num_class=4) model, loss_function = nestnet(num_class=4,dropout_rate = 0.5) model.compile(optimizer=Adam(lr = 8e-4),loss=loss_function,metrics=['accuracy']) model.summary() model_checkpoint = ModelCheckpoint('welding_nestnet_v1_4.hdf5',monitor='val_loss',verbose=1,save_best_only=True) history = model.fit_generator(train_gene, steps_per_epoch=63, epochs=10, verbose=1, callbacks=[model_checkpoint,tensorboard], validation_data=val_gene, validation_steps=1 #validation/batchsize )
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CesarAcjotaMerma/Ecommerce_Django
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/myvenv/Scripts/django-admin.py
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[]
no_license
https://github.com/CesarAcjotaMerma/Ecommerce_Django
7d086925d4a7d75fd3fb4d3c9f22bdf21c1f5c30
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refs/heads/master
2023-07-11T18:06:54.514752
2021-08-03T04:28:55
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#!c:\users\usuario\documents\4to semestre\pasantia\pasantia_proyecto\myvenv\scripts\python.exe from django.core import management if __name__ == "__main__": management.execute_from_command_line()
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rahasayantan/Work-For-Reference
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/others/stepwiseResults.py
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refs/heads/master
2022-01-15T05:48:17.226826
2019-07-03T11:31:36
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import pandas as pd import numpy as np import datetime as dt import gc from sklearn.preprocessing import MinMaxScaler from encoding import cat2MeanShiftEncode from sklearn.externals import joblib from stepwiseSelectionRegression import stepwiseOLS ''' dftrainStat = joblib.load("../input2/trainStat33.pkl") dftrainStat2 = joblib.load("../input2/trainStat06.pkl") dftrainStat3 = joblib.load("../input2/trainStat39.pkl") ''' trainparcel = joblib.load("../input2/trainparcel.pkl") train1 = joblib.load("../input/trainnum9Impute.pkl") train2 = joblib.load("../input/trainlblcat.pkl") #trainparcel = pd.DataFrame(trainparcel) #trainparcel.columns = ['parcelid'] train = train#pd.concat((trainparcel,train1,train2), axis = 1) train_y = joblib.load("../input2/y.pkl") train['train_y'] = train_y ''' train.set_index('parcelid', inplace = True) dftrainStat.set_index('parcelid', inplace = True) dftrainStat2.set_index('parcelid', inplace = True) dftrainStat3.set_index('parcelid', inplace = True) train = train.join(dftrainStat) train = train.join(dftrainStat2, rsuffix='1') train = train.join(dftrainStat3, rsuffix='2') ''' stepwiseOLS(train, train_y) #'taxdelinquencyyear_countenc0', 'poolcnt_countenc0', 'hashottuborspa_countenc0','bedroomcnt_countenc0', #'regionidzip_meanshftenc0', 'assessmentyear_meanshftenc0', 'buildingclasstypeid_meanshftenc0', 'propertycountylandusecode_meanshftenc0', 'rawcensustractandblock_meanshftenc0', 'taxdelinquencyflag_meanshftenc0', 'propertyzoningdesc_meanshftenc0', 'poolcnt_meanshftenc0' #'regionidzip_medianenc0', 'assessmentyear_medianenc0', 'buildingclasstypeid_medianenc0','propertycountylandusecode_medianenc0', 'rawcensustractandblock_medianenc0', 'taxdelinquencyflag_medianenc0', 'propertyzoningdesc_medianenc0', 'poolcnt_medianenc0' #'regionidzip_meanenc0', 'assessmentyear_meanenc0', 'buildingclasstypeid_meanenc0','propertycountylandusecode_meanenc0', 'rawcensustractandblock_meanenc0', 'taxdelinquencyflag_meanenc0', 'propertyzoningdesc_meanenc0', 'poolcnt_meanenc0'
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ictsc/prep-pstate
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/ictsc_prep_school/pstate/migrations/0019_auto_20190801_1405.py
7a62601b2b3a853babdc70e3fb741e54276260f7
[]
no_license
https://github.com/ictsc/prep-pstate
69ce346ec5c63f9e86a79c44c700f6365877ee50
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refs/heads/master
2023-03-09T08:36:09.768824
2020-10-14T15:52:50
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# Generated by Django 2.0.4 on 2019-08-01 05:05 import datetime from django.db import migrations, models from django.utils.timezone import utc class Migration(migrations.Migration): dependencies = [ ('pstate', '0018_auto_20190801_1314'), ] operations = [ migrations.AddField( model_name='github', name='name', field=models.CharField(default='ictsc-problems', max_length=100), ), migrations.AlterField( model_name='problem', name='end_date', field=models.DateTimeField(blank=True, default=datetime.datetime(2019, 8, 1, 5, 5, 44, 184187, tzinfo=utc), null=True, verbose_name='問題公開終了日時'), ), migrations.AlterField( model_name='problem', name='start_date', field=models.DateTimeField(blank=True, default=datetime.datetime(2019, 8, 1, 5, 5, 44, 184147, tzinfo=utc), null=True, verbose_name='問題公開日時'), ), ]
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0019_auto_20190801_1405.py
76
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sdpython/mlstatpy
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ac768a35cc145185aa940bbb8255c40ec38a7c6f
/mlstatpy/ml/_neural_tree_node.py
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permissive
https://github.com/sdpython/mlstatpy
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refs/heads/main
2023-08-17T11:06:14.258773
2023-08-05T22:35:27
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# coding: utf-8 import numpy import numpy.random as rnd from scipy.special import expit, softmax, kl_div as kl_fct # pylint: disable=E0611 from ._neural_tree_api import _TrainingAPI class NeuralTreeNode(_TrainingAPI): """ One node in a neural network. :param weights: weights :param bias: bias, if None, draws a random number :param activation: activation function :param nodeid: node id :param tag: unused but to add information on how this node was created """ @staticmethod def _relu(x): "Relu function." return numpy.maximum(x, 0) @staticmethod def _leakyrelu(x): "Leaky Relu function." return numpy.maximum(x, 0) + numpy.minimum(x, 0) * 0.01 @staticmethod def _drelu(x): "Derivative of the Relu function." res = numpy.ones(x.shape, dtype=x.dtype) res[x < 0] = 0.0 return res @staticmethod def _dleakyrelu(x): "Derivative of the Leaky Relu function." res = numpy.ones(x.shape, dtype=x.dtype) res[x < 0] = 0.01 return res @staticmethod def _dsigmoid(x): "Derivativ of the sigmoid function." y = expit(x) return y * (1 - y) @staticmethod def _softmax(x): "Derivative of the softmax function." if len(x.shape) == 2: return softmax(x, axis=1) return softmax(x) @staticmethod def _dsoftmax(x): "Derivative of the softmax function." soft = softmax(x) grad = -soft @ soft.T diag = numpy.diag(soft) return diag + grad @staticmethod def get_activation_function(activation): """ Returns the activation function. It returns a function *y=f(x)*. """ if activation == "softmax": return NeuralTreeNode._softmax if activation == "softmax4": return lambda x: NeuralTreeNode._softmax(x * 4) if activation in {"logistic", "expit", "sigmoid"}: return expit if activation == "sigmoid4": return lambda x: expit(x * 4) if activation == "relu": return NeuralTreeNode._relu if activation == "leakyrelu": return NeuralTreeNode._leakyrelu if activation == "identity": return lambda x: x raise ValueError( # pragma: no cover f"Unknown activation function '{activation}'." ) @staticmethod def get_activation_gradient_function(activation): """ Returns the activation function. It returns a function *y=f'(x)*. About the sigmoid: .. math:: \\begin{array}{rcl} f(x) &=& \\frac{1}{1 + e^{-x}} \\\\ f'(x) &=& \\frac{e^{-x}}{(1 + e^{-x})^2} = f(x)(1-f(x)) \\end{array} """ if activation == "softmax": return NeuralTreeNode._dsoftmax if activation == "softmax4": return lambda x: NeuralTreeNode._dsoftmax(x) * 4 if activation in {"logistic", "expit", "sigmoid"}: return NeuralTreeNode._dsigmoid if activation == "sigmoid4": return lambda x: NeuralTreeNode._dsigmoid(x) * 4 if activation == "relu": return NeuralTreeNode._drelu if activation == "leakyrelu": return NeuralTreeNode._dleakyrelu if activation == "identity": return lambda x: numpy.ones(x.shape, dtype=x.dtype) raise ValueError( # pragma: no cover f"Unknown activation gradient function '{activation}'." ) @staticmethod def get_activation_loss_function(activation): """ Returns a default loss function based on the activation function. It returns two functions *g=loss(x,y)*. """ if activation in {"logistic", "expit", "sigmoid", "sigmoid4"}: # regression + regularization return lambda x, y: (x - y) ** 2 if activation in {"softmax", "softmax4"}: cst = numpy.finfo(numpy.float32).eps # classification def kl_fct2(x, y): return kl_fct(x + cst, y + cst) return kl_fct2 if activation in {"identity", "relu", "leakyrelu"}: # regression return lambda x, y: (x - y) ** 2 raise ValueError(f"Unknown activation function '{activation}'.") @staticmethod def get_activation_dloss_function(activation): """ Returns the derivative of the default loss function based on the activation function. It returns a function *df(x,y)/dw, df(w)/dw* where *w* are the weights. """ if activation in {"logistic", "expit", "sigmoid", "sigmoid4"}: # regression + regularization def dregrdx(x, y): return (x - y) * 2 return dregrdx if activation in {"softmax", "softmax4"}: # classification cst = numpy.finfo(numpy.float32).eps def dclsdx(x, y): return numpy.log(x + cst) - numpy.log(y + cst) return dclsdx if activation in {"identity", "relu", "leakyrelu"}: # regression def dregdx(x, y): return (x - y) * 2 return dregdx raise ValueError( # pragma: no cover f"Unknown activation function '{activation}'." ) def __init__(self, weights, bias=None, activation="sigmoid", nodeid=-1, tag=None): self.tag = tag if isinstance(weights, int): if activation.startswith("softmax"): weights = rnd.randn(2, weights) else: weights = rnd.randn(weights) if isinstance(weights, list): weights = numpy.array(weights) if len(weights.shape) == 1: self.n_outputs = 1 if bias is None: bias = rnd.randn() self.coef = numpy.empty(len(weights) + 1) self.coef[1:] = weights self.coef[0] = bias elif len(weights.shape) == 2: self.n_outputs = weights.shape[0] if bias is None: bias = rnd.randn(self.n_outputs) shape = list(weights.shape) shape[1] += 1 self.coef = numpy.empty(shape) self.coef[:, 1:] = weights self.coef[:, 0] = bias else: raise RuntimeError( # pragma: no cover f"Unexpected weights shape: {weights.shape}" ) self.activation = activation self.nodeid = nodeid self._set_fcts() def _set_fcts(self): self.activation_ = NeuralTreeNode.get_activation_function(self.activation) self.gradient_ = NeuralTreeNode.get_activation_gradient_function( self.activation ) self.losss_ = NeuralTreeNode.get_activation_loss_function(self.activation) self.dlossds_ = NeuralTreeNode.get_activation_dloss_function(self.activation) @property def input_weights(self): "Returns the weights." if self.n_outputs == 1: return self.coef[1:] return self.coef[:, 1:] @property def bias(self): "Returns the weights." if self.n_outputs == 1: return self.coef[0] return self.coef[:, 0] def __getstate__(self): "usual" return { "coef": self.coef, "activation": self.activation, "nodeid": self.nodeid, "n_outputs": self.n_outputs, "tag": self.tag, } def __setstate__(self, state): "usual" self.coef = state["coef"] self.activation = state["activation"] self.nodeid = state["nodeid"] self.n_outputs = state["n_outputs"] self.tag = state["tag"] self._set_fcts() def __eq__(self, obj): if self.coef.shape != obj.coef.shape: return False if any( map(lambda xy: xy[0] != xy[1], zip(self.coef.ravel(), obj.coef.ravel())) ): return False if self.activation != obj.activation: return False return True def __repr__(self): "usual" if len(self.coef.shape) == 1: return "%s(weights=%r, bias=%r, activation=%r)" % ( self.__class__.__name__, self.coef[1:], self.coef[0], self.activation, ) return "%s(weights=%r, bias=%r, activation=%r)" % ( self.__class__.__name__, self.coef[:, 1:], self.coef[:, 0], self.activation, ) def _predict(self, X): "Computes inputs of the activation function." if self.n_outputs == 1: return X @ self.coef[1:] + self.coef[0] if len(X.shape) == 2: return X @ self.coef[:, 1:].T + self.coef[:, 0] res = X.reshape((1, -1)) @ self.coef[:, 1:].T + self.coef[:, 0] return res.ravel() def predict(self, X): "Computes neuron outputs." y = self._predict(X) return self.activation_(y) @property def ndim(self): "Returns the input dimension." if len(self.coef.shape) == 1: return self.coef.shape[0] - 1 return self.coef.shape[1] - 1 @property def ndim_out(self): "Returns the output dimension." if len(self.coef.shape) == 1: return 1 return self.coef.shape[0] @property def training_weights(self): "Returns the weights stored in the neuron." return self.coef.ravel() def update_training_weights(self, X, add=True): # pylint: disable=W0237 """ Updates weights. :param X: training datasets :param add: addition or replace """ if add: self.coef += X.reshape(self.coef.shape) else: numpy.copyto(self.coef, X.reshape(self.coef.shape)) def fill_cache(self, X): """ Creates a cache with intermediate results. ``lX`` is the results before the activation function, ``aX`` is the results after the activation function, the prediction. """ cache = dict(lX=self._predict(X)) cache["aX"] = self.activation_(cache["lX"]) return cache def _common_loss_dloss(self, X, y, cache=None): """ Common beginning to methods *loss*, *dlossds*, *dlossdw*. """ if cache is not None and "aX" in cache: act = cache["aX"] else: act = self.predict(X) return act def loss(self, X, y, cache=None): """ Computes the loss. Returns a float. """ act = self._common_loss_dloss(X, y, cache=cache) if len(X.shape) == 1: return self.losss_(act, y) # pylint: disable=E1120 return self.losss_(act, y) # pylint: disable=E1120 def dlossds(self, X, y, cache=None): """ Computes the loss derivative due to prediction error. """ act = self._common_loss_dloss(X, y, cache=cache) return self.dlossds_(act, y) def gradient_backward(self, graddx, X, inputs=False, cache=None): """ Computes the gradients at point *X*. :param graddx: existing gradient against the inputs :param X: computes the gradient in X :param inputs: if False, derivative against the coefficients, otherwise against the inputs. :param cache: cache intermediate results :return: gradient """ if cache is None: cache = self.fill_cache(X) pred = cache["aX"] ga = self.gradient_(pred) if len(ga.shape) == 2: f = graddx @ ga else: f = graddx * ga if inputs: if len(self.coef.shape) == 1: rgrad = numpy.empty(X.shape) rgrad[:] = self.coef[1:] rgrad *= f else: rgrad = numpy.sum(self.coef[:, 1:] * f.reshape((-1, 1)), axis=0) return rgrad rgrad = numpy.empty(self.coef.shape) if len(self.coef.shape) == 1: rgrad[0] = 1 rgrad[1:] = X rgrad *= f else: rgrad[:, 0] = 1 rgrad[:, 1:] = X rgrad *= f.reshape((-1, 1)) return rgrad
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# Exercise 3.31 # Author: Noah Waterfield Price def L3(x, n=None, epsilon=None, return_n=False): if (n is None and epsilon is None) or \ (n is not None and epsilon is not None): print 'Error: Either n or epsilon must be given (not both)' term = x / (1. + x) s = term if n is not None: for i in range(2, n + 1): # recursive relation between ci and c(i-1) term *= (i - 1.) / i * x / (1. + x) s += term return (s, n) if return_n is True else s elif epsilon is not None: i = 1 while abs(term) > epsilon: i += 1 # recursive relation between ci and c(i-1) term *= (i - 1.) / i * x / (1. + x) s += term return (s, i) if return_n is True else s print L3(10, n=100) print L3(10, n=1000, return_n=True) print L3(10, epsilon=1e-10) print L3(10, epsilon=1e-10, return_n=True) """ Sample run: python L3_flexible.py 2.39788868474 (2.397895272798365, 1000) 2.39789527188 (2.397895271877886, 187 """
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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('widgetbox', '0003_auto_20150522_0959'), ] operations = [ migrations.RenameModel('ButtonPlugin', 'Button'), migrations.RenameModel('QuotePlugin', 'Quote'), migrations.RenameModel('GalleryPlugin', 'Gallery'), migrations.RenameModel('GalleryImagePlugin', 'GalleryImage'), ]
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#!/usr/bin/env python3 required_fields = sorted(["byr", "iyr", "eyr", "hgt", "hcl", "ecl", "pid", "cid"]) temp_required_fields = sorted(["byr", "iyr", "eyr", "hgt", "hcl", "ecl", "pid"]) passports = [] valid_passports = [] with open("input_0401") as input: passport = [] for line in input: if not line.strip(): passports.append(passport) passport = [] else: _line = line.replace("\n", " ").split() passport.extend(_line) else: passports.append(passport) for passport in passports: fields = [] for field in passport: fields.append(field.split(":")[0]) fields.sort() if fields == temp_required_fields or fields == required_fields: valid_passports.append(passport) print(len(valid_passports))
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lwoloszy/personal_website
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/pelicanconf.py
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#!/usr/bin/env python # -*- coding: utf-8 -*- # from __future__ import unicode_literals AUTHOR = u'Luke Woloszyn' SITEURL = u'http://lukewoloszyn.com' SITENAME = u'Luke Woloszyn' SITESUBTITLE = u'data scientist, outdoor enthusiast, music lover, sports fan' ARTICLE_URL = '{date:%Y}/{date:%m}/{date:%d}/{slug}.html' ARTICLE_SAVE_AS = '{date:%Y}/{date:%m}/{date:%d}/{slug}.html' RELATIVE_URLS = True TYPOGRIFY = True THEME = '../crowsfoot' # PATH = 'content' ARTICLE_PATHS = ['blog'] # MENUITEMS = [('blog', '/'), ('cv', '/misc/cv.pdf')] MENUITEMS = [('Blog', '/'), ] PROFILE_IMAGE_URL = '/images/personal.jpg' STATIC_PATHS = ['images', 'extra/robots.txt', 'extra/favicon.ico', 'misc'] EXTRA_PATH_METADATA = { 'extra/robots.txt': {'path': 'robots.txt'}, 'extra/favicon.ico': {'path': 'favicon.ico'}, } PLUGIN_PATHS = ['../pelican-plugins'] PLUGINS = ['render_math'] TIMEZONE = 'America/Los_Angeles' DEFAULT_LANG = u'en' DEFAULT_PAGINATION = None # addresses EMAIL_ADDRESS = 'luke.woloszyn@gmail.com' GITHUB_ADDRESS = 'https://github.com/lwoloszy' LINKEDIN_ADDRESS = 'https://www.linkedin.com/in/lukewoloszyn' TWITTER_ADDRESS = 'https://www.twitter.com/lukewoloszyn' # feed FEED_RSS = 'feeds/rss.xml' FEED_MAX_ITEMS = 10 SHOW_ARTICLE_AUTHOR = False LICENSE_NAME = "CC BY-SA" LICENSE_URL = "https://creativecommons.org/licenses/by-sa/3.0/" LOAD_CONTENT_CACHE = False
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