Datasets:

anton-l

/

python_sample_10k

like 0

lemanouthe/feliciano

d9f2b6598aed26ba78e30afffa1cae60d5ddaaf0

4bb005fc2d550bf35cfcb3732356db2886abfd8e

/configuration/migrations/0001_initial.py

f827c71bdb7ecf6c30629cd50d1a43373a4eaca6

no_license

https://github.com/lemanouthe/feliciano

5d0a64cd0adc00c8ddc9a04719144cbb193a06c3

20e49309a038263714fca4131eb25ed2702a3e47

refs/heads/master

# Generated by Django 2.2.5 on 2019-09-30 15:23 from django.db import migrations, models import django.db.models.deletion import tinymce.models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='AboutConfig', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('titre', models.CharField(max_length=50)), ('content', tinymce.models.HTMLField(verbose_name='content')), ('open_hour', models.CharField(max_length=255)), ('phone', models.CharField(max_length=50)), ('yoe', models.IntegerField()), ('menu', models.IntegerField()), ('satff', models.IntegerField()), ('happy_customer', models.IntegerField()), ('description', models.TextField()), ('status', models.BooleanField(default=True)), ('date_add', models.DateTimeField(auto_now_add=True)), ('date_upd', models.DateTimeField(auto_now=True)), ], options={ 'verbose_name': 'AboutConfig', 'verbose_name_plural': 'AboutConfigs', }, ), migrations.CreateModel( name='Day', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('jour', models.CharField(max_length=50)), ('status', models.BooleanField(default=True)), ('date_add', models.DateTimeField(auto_now_add=True)), ('date_upd', models.DateTimeField(auto_now=True)), ], options={ 'verbose_name': 'Day', 'verbose_name_plural': 'Days', }, ), migrations.CreateModel( name='Icon', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=50)), ('status', models.BooleanField(default=True)), ('date_add', models.DateTimeField(auto_now_add=True)), ('date_upd', models.DateTimeField(auto_now=True)), ], options={ 'verbose_name': 'Icon', 'verbose_name_plural': 'Icons', }, ), migrations.CreateModel( name='Instagram', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('image1', models.ImageField(upload_to='home/insta')), ('image2', models.ImageField(upload_to='home/insta')), ('image3', models.ImageField(upload_to='home/insta')), ('image4', models.ImageField(upload_to='home/insta')), ('image5', models.ImageField(upload_to='home/insta')), ('image6', models.ImageField(upload_to='home/insta')), ('status', models.BooleanField(default=True)), ('date_add', models.DateTimeField(auto_now_add=True)), ('date_upd', models.DateTimeField(auto_now=True)), ], options={ 'verbose_name': 'Instagram', 'verbose_name_plural': 'Instagrams', }, ), migrations.CreateModel( name='Social', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(choices=[('FB', 'facebook'), ('TW', 'twitter'), ('INS', 'instagram'), ('GOO', 'google')], max_length=100)), ('lien', models.URLField()), ('status', models.BooleanField(default=True)), ('date_add', models.DateTimeField(auto_now_add=True)), ('date_upd', models.DateTimeField(auto_now=True)), ], options={ 'verbose_name': 'Social', 'verbose_name_plural': 'Socials', }, ), migrations.CreateModel( name='Temoin', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=50)), ('job', models.CharField(max_length=50)), ('comment', models.TextField()), ('image', models.ImageField(upload_to='testimonial')), ('status', models.BooleanField(default=True)), ('date_add', models.DateTimeField(auto_now_add=True)), ('date_upd', models.DateTimeField(auto_now=True)), ], options={ 'verbose_name': 'Temoin', 'verbose_name_plural': 'Temoins', }, ), migrations.CreateModel( name='WorkingHour', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('start_hour', models.CharField(max_length=50)), ('end_hour', models.CharField(max_length=50)), ('status', models.BooleanField(default=True)), ('date_add', models.DateTimeField(auto_now_add=True)), ('date_upd', models.DateTimeField(auto_now=True)), ('jour', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='day_working', to='configuration.Day')), ], options={ 'verbose_name': 'WorkingHour', 'verbose_name_plural': 'WorkingHours', }, ), migrations.CreateModel( name='ServiceConfig', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('titre', models.CharField(max_length=50)), ('description', models.TextField()), ('status', models.BooleanField(default=True)), ('date_add', models.DateTimeField(auto_now_add=True)), ('date_upd', models.DateTimeField(auto_now=True)), ('icone', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='icon_service', to='configuration.Icon')), ], options={ 'verbose_name': 'ServiceConfig', 'verbose_name_plural': 'ServiceConfigs', }, ), migrations.CreateModel( name='MainConfig', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('nom', models.CharField(max_length=50)), ('description', models.TextField()), ('text1', models.CharField(max_length=50)), ('text2', models.CharField(max_length=50)), ('text3', models.CharField(max_length=50)), ('image1', models.ImageField(upload_to='home/')), ('image2', models.ImageField(upload_to='home/')), ('image3', models.ImageField(upload_to='home/')), ('scroll_image', models.ImageField(upload_to='home/')), ('tel', models.CharField(max_length=15)), ('email', models.EmailField(max_length=255)), ('status', models.BooleanField(default=True)), ('date_add', models.DateTimeField(auto_now_add=True)), ('date_upd', models.DateTimeField(auto_now=True)), ('instagram', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='insta_config', to='configuration.Instagram')), ('social', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='social_config', to='configuration.Social')), ('working_hour', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='working_config', to='configuration.WorkingHour')), ], options={ 'verbose_name': 'MainConfig', 'verbose_name_plural': 'MainConfigs', }, ), ]

UTF-8

Python

py

0001_initial.py

oasysokubo/pacAI

0297384776d9e836d0cc1bebb27a187d8d489a4b

0ef639c85334c42e7958e40009d47d0a9c5123ae

/src/pacai/student/multiagents.py

797caecb4f8b0f4323c6a48f5111261f3a50276e

no_license

https://github.com/oasysokubo/pacAI

b3e93b2ca23f341a5cd8b48ce31c17c3e54b0ae6

8d2f28be01c7aa388e0f8c8689a50d521cdd27da

refs/heads/master

Python

import random import sys from pacai.agents.base import BaseAgent from pacai.agents.search.multiagent import MultiAgentSearchAgent from pacai.core import distance class ReflexAgent(BaseAgent): """ A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch the method headers. """ def __init__(self, index, **kwargs): super().__init__(index) def getAction(self, gameState): """ You do not need to change this method, but you're welcome to. `ReflexAgent.getAction` chooses among the best options according to the evaluation function. Just like in the previous project, this method takes a `pacai.core.gamestate.AbstractGameState` and returns some value from `pacai.core.directions.Directions`. """ # Collect legal moves. legalMoves = gameState.getLegalActions() # Choose one of the best actions. scores = [self.evaluationFunction(gameState, action) for action in legalMoves] bestScore = max(scores) bestIndices = [index for index in range(len(scores)) if scores[index] == bestScore] chosenIndex = random.choice(bestIndices) # Pick randomly among the best. return legalMoves[chosenIndex] def evaluationFunction(self, currentGameState, action): """ Design a better evaluation function here. The evaluation function takes in the current `pacai.bin.pacman.PacmanGameState` and an action, and returns a number, where higher numbers are better. Make sure to understand the range of different values before you combine them in your evaluation function. """ successorGameState = currentGameState.generatePacmanSuccessor(action) # Useful information you can extract. newPosition = successorGameState.getPacmanPosition() # oldPosition = currentGameState.getPacmanPosition() newFood = successorGameState.getFood() oldFood = currentGameState.getFood() # oldScore = currentGameState.getScore() newScore = successorGameState.getScore() newGhostStates = successorGameState.getGhostStates() # newScaredTimes = [ghostState.getScaredTimer() for ghostState in newGhostStates] # *** Your Code Here *** all_food = newFood.asList() # check if adversary is near for ghost in newGhostStates: isBrave = ghost.isBraveGhost() ghostPosition = ghost.getPosition() if isBrave: if distance.manhattan(newPosition, ghostPosition) < 2: # run away return -999999 # get distance from pacman to all food food_dist = [(1.0 / distance.euclidean(newPosition, food)) for food in all_food] food_dist.sort() # if pacman isnt moving or food is not being eaten --> penalize old_food_ct = oldFood.count() new_food_ct = newFood.count() if old_food_ct != new_food_ct: if new_food_ct == 0: return 0 return newScore + food_dist[0] else: return food_dist[-1] - abs(newScore) class MinimaxAgent(MultiAgentSearchAgent): """ A minimax agent. Here are some method calls that might be useful when implementing minimax. `pacai.core.gamestate.AbstractGameState.getNumAgents()`: Get the total number of agents in the game `pacai.core.gamestate.AbstractGameState.getLegalActions`: Returns a list of legal actions for an agent. Pacman is always at index 0, and ghosts are >= 1. `pacai.core.gamestate.AbstractGameState.generateSuccessor`: Get the successor game state after an agent takes an action. `pacai.core.directions.Directions.STOP`: The stop direction, which is always legal, but you may not want to include in your search. Method to Implement: `pacai.agents.base.BaseAgent.getAction`: Returns the minimax action from the current gameState using `pacai.agents.search.multiagent.MultiAgentSearchAgent.getTreeDepth` and `pacai.agents.search.multiagent.MultiAgentSearchAgent.getEvaluationFunction`. """ def __init__(self, index, **kwargs): super().__init__(index, **kwargs) self.nodes_expanded = 0 def getAction(self, gameState): evalfn = self.getEvaluationFunction() num_agents = gameState.getNumAgents() tree_depth = self.getTreeDepth() def max_value(state, agent_idx, depth): if depth == tree_depth or state.isOver(): return evalfn(state) v = -(sys.maxsize - 1) if agent_idx == 0: actions = state.getLegalActions(agent_idx) actions.remove('Stop') for action in actions: next_state = state.generateSuccessor(agent_idx, action) v = max(v, min_value(next_state, agent_idx + 1, depth)) return v def min_value(state, agent_idx, depth): v = sys.maxsize if depth == tree_depth or state.isOver(): return evalfn(state) if agent_idx == (num_agents - 1): actions = state.getLegalActions(agent_idx) for action in actions: next_state = state.generateSuccessor(agent_idx, action) v = min(v, max_value(next_state, 0, depth + 1)) return v else: actions = state.getLegalActions(agent_idx) for action in actions: next_state = state.generateSuccessor(agent_idx, action) v = min(v, min_value(next_state, agent_idx + 1, depth)) return v pacman_moves = [] actions = gameState.getLegalActions() actions.remove('Stop') for action in actions: next_state = gameState.generateSuccessor(0, action) agent_idx = next_state.getLastAgentMoved() item = (action, min_value(next_state, agent_idx + 1, 0)) pacman_moves.append(item) action_to_take = max(pacman_moves, key=lambda pacman_moves: pacman_moves[1]) return action_to_take[0] class AlphaBetaAgent(MultiAgentSearchAgent): """ A minimax agent with alpha-beta pruning. Method to Implement: `pacai.agents.base.BaseAgent.getAction`: Returns the minimax action from the current gameState using `pacai.agents.search.multiagent.MultiAgentSearchAgent.getTreeDepth` and `pacai.agents.search.multiagent.MultiAgentSearchAgent.getEvaluationFunction`. """ def __init__(self, index, **kwargs): super().__init__(index, **kwargs) def getAction(self, gameState): evalfn = self.getEvaluationFunction() num_agents = gameState.getNumAgents() tree_depth = self.getTreeDepth() def max_value(state, agent_idx, depth, alpha, beta): if depth == tree_depth or state.isOver(): return evalfn(state) v = -(sys.maxsize - 1) if agent_idx == 0: actions = state.getLegalActions(agent_idx) actions.remove('Stop') for action in actions: next_state = state.generateSuccessor(agent_idx, action) v = max(v, min_value(next_state, agent_idx + 1, depth, alpha, beta)) if v >= beta: return v alpha = max(alpha, v) return v def min_value(state, agent_idx, depth, alpha, beta): v = sys.maxsize if depth == tree_depth or state.isOver(): return evalfn(state) if agent_idx == (num_agents - 1): actions = state.getLegalActions(agent_idx) for action in actions: next_state = state.generateSuccessor(agent_idx, action) v = min(v, max_value(next_state, 0, depth + 1, alpha, beta)) if v <= alpha: return v beta = min(beta, v) return v else: actions = state.getLegalActions(agent_idx) for action in actions: next_state = state.generateSuccessor(agent_idx, action) v = min(v, min_value(next_state, agent_idx + 1, depth, alpha, beta)) if v <= alpha: return v beta = min(beta, v) return v pacman_moves = [] actions = gameState.getLegalActions() actions.remove('Stop') ninf = -(sys.maxsize - 1) pinf = sys.maxsize for action in actions: next_state = gameState.generateSuccessor(0, action) agent_idx = next_state.getLastAgentMoved() item = (action, min_value(next_state, agent_idx + 1, 0, ninf, pinf)) pacman_moves.append(item) action_to_take = max(pacman_moves, key=lambda pacman_moves: pacman_moves[1]) return action_to_take[0] class ExpectimaxAgent(MultiAgentSearchAgent): """ An expectimax agent. All ghosts should be modeled as choosing uniformly at random from their legal moves. Method to Implement: `pacai.agents.base.BaseAgent.getAction`: Returns the expectimax action from the current gameState using `pacai.agents.search.multiagent.MultiAgentSearchAgent.getTreeDepth` and `pacai.agents.search.multiagent.MultiAgentSearchAgent.getEvaluationFunction`. """ def __init__(self, index, **kwargs): super().__init__(index, **kwargs) def getAction(self, gameState): evalfn = self.getEvaluationFunction() num_agents = gameState.getNumAgents() tree_depth = self.getTreeDepth() def expectiminimax(state, agent_idx, depth, is_chance): v = 0 if depth == tree_depth or state.isOver(): return evalfn(state) # pacman's turn if agent_idx == 0 and not is_chance: v = -(sys.maxsize - 1) actions = state.getLegalActions(agent_idx) actions.remove('Stop') for action in actions: next_state = state.generateSuccessor(agent_idx, action) v = max(v, expectiminimax(next_state, agent_idx + 1, depth, True)) # at a chance node elif is_chance: v = 0 # calculate chance node for final adversary agent if agent_idx == (num_agents - 1): actions = state.getLegalActions(agent_idx) for action in actions: next_state = state.generateSuccessor(agent_idx, action) v += (expectiminimax(next_state, 0, depth + 1, False)) # chance node for adversary agents elif agent_idx % num_agents != 0: actions = state.getLegalActions(agent_idx) for action in actions: next_state = state.generateSuccessor(agent_idx, action) v += (expectiminimax(next_state, agent_idx + 1, depth, True)) v = float(v / len(actions)) return v pacman_moves = [] actions = gameState.getLegalActions() actions.remove('Stop') for action in actions: next_state = gameState.generateSuccessor(0, action) agent_idx = next_state.getLastAgentMoved() item = (action, expectiminimax(next_state, agent_idx + 1, 0, True)) pacman_moves.append(item) action_to_take = max(pacman_moves, key=lambda pacman_moves: pacman_moves[1]) return action_to_take[0] def betterEvaluationFunction(currentGameState): """ Your extreme ghost-hunting, pellet-nabbing, food-gobbling, unstoppable evaluation function. DESCRIPTION: <write something here so we know what you did> Note: I thought I needed all these factors but apparently just the score, food distance, and capsule distance was enough... if game is not over: d = dist to closest food pellet c = dist to closest capsule t = average scared time for all ghosts b = ghosts are brave p = penalty for num_food not changing g = dist to closest ghost gs = dist to closest scared ghost utility = score + (10 * d) + (20 * c) + (t * (100 * gs)) - (100 * g) - (10 * p) - b else: utility = (w1 * isWin) - [(w2 * isLose) + (w3 * num_food)] + score = (10000 * isWin) - [(10000 * isLose) + (10 * num_food)] + score """ pac_pos = currentGameState.getAgentPosition(0) num_agents = currentGameState.getNumAgents() ghost_position = [currentGameState.getAgentPosition(i) for i in range(1, num_agents)] capsule_position = currentGameState.getCapsules() score = currentGameState.getScore() num_food = currentGameState.getNumFood() food_list = currentGameState.getFood().asList() win = 1 if currentGameState.isWin() else 0 lose = 1 if currentGameState.isLose() else 0 over = 1 if currentGameState.isOver() else 0 food_dist = [(1.0 / (distance.euclidean(pac_pos, food))) for food in food_list] ghost_dist = [(1.0 / (distance.euclidean(pac_pos, ghost))) for ghost in ghost_position if int(distance.euclidean(pac_pos, ghost)) != 0] capsule_dist = [(1.0 / distance.euclidean(pac_pos, capsule)) for capsule in capsule_position if int(distance.euclidean(pac_pos, capsule) != 0)] sorted(food_dist) sorted(ghost_dist) sorted(capsule_dist) if len(capsule_dist) == 0: capsule_dist = 0 else: capsule_dist = capsule_dist[0] num_brave = 0 time_scared = 0 closest_scared = sys.maxsize for i in range(1, num_agents): ghost_state = currentGameState.getAgentState(i) if ghost_state.isBraveGhost(): num_brave += 1 else: time_scared += ghost_state.getScaredTimer() ghost_pos = ghost_state.getPosition() if distance.euclidean(pac_pos, ghost_pos) < closest_scared: closest_scared = distance.euclidean(pac_pos, ghost_pos) closest_scared = 0 if closest_scared == sys.maxsize else (1.0 / (closest_scared)) if num_brave != (num_agents - 1): time_scared = float(time_scared) / (num_agents - 1 - num_brave) if over == 0: utility = score + (10 * food_dist[0]) + (100 * capsule_dist) # \ # + (time_scared * (400 * closest_scared)) \ # - ((200 * (num_agents - 1 - num_brave)) # - (100 * ghost_dist[0])) - (10 * num_food) - num_brave # print('Over utility: ', utility) return utility else: utility = (1000 * win) - ((1000 * lose) + (10 * num_food)) + score # + (100 * (num_agents - 1 - num_brave)) # + (time_scared * (200 * closest_scared)) \ # print('Win/Lose utility: ', utility) return utility class ContestAgent(MultiAgentSearchAgent): """ Your agent for the mini-contest. You can use any method you want and search to any depth you want. Just remember that the mini-contest is timed, so you have to trade off speed and computation. Ghosts don't behave randomly anymore, but they aren't perfect either -- they'll usually just make a beeline straight towards Pacman (or away if they're scared!) Method to Implement: `pacai.agents.base.BaseAgent.getAction` """ def __init__(self, index, **kwargs): super().__init__(index, **kwargs) def getAction(self, gameState): evalfn = betterEvaluationFunction num_agents = gameState.getNumAgents() tree_depth = 3 * self.getTreeDepth() def max_value(state, agent_idx, depth, alpha, beta): if depth == tree_depth or state.isOver(): return evalfn(state) v = -(sys.maxsize - 1) if agent_idx == 0: actions = state.getLegalActions(agent_idx) actions.remove('Stop') for action in actions: next_state = state.generateSuccessor(agent_idx, action) v = max(v, min_value(next_state, agent_idx + 1, depth, alpha, beta)) if v >= beta: return v alpha = max(alpha, v) return v def min_value(state, agent_idx, depth, alpha, beta): v = sys.maxsize if depth == tree_depth or state.isOver(): return evalfn(state) if agent_idx == (num_agents - 1): actions = state.getLegalActions(agent_idx) for action in actions: next_state = state.generateSuccessor(agent_idx, action) v = min(v, max_value(next_state, 0, depth + 1, alpha, beta)) if v <= alpha: return v beta = min(beta, v) return v else: actions = state.getLegalActions(agent_idx) for action in actions: next_state = state.generateSuccessor(agent_idx, action) v = min(v, min_value(next_state, agent_idx + 1, depth, alpha, beta)) if v <= alpha: return v beta = min(beta, v) return v pacman_moves = [] actions = gameState.getLegalActions() actions.remove('Stop') ninf = -(sys.maxsize - 1) pinf = sys.maxsize for action in actions: next_state = gameState.generateSuccessor(0, action) agent_idx = next_state.getLastAgentMoved() item = (action, min_value(next_state, agent_idx + 1, 0, ninf, pinf)) pacman_moves.append(item) action_to_take = max(pacman_moves, key=lambda pacman_moves: pacman_moves[1]) return action_to_take[0]

UTF-8

Python

py

multiagents.py

Seabreg/chiasm-shell

9b7d86dffc14f29e40bda3c375cf7aa6472caf5b

ddd8940c63a64bc0f1924f28bb3bc0ab9037cda9

/chiasm_shell/chiasm_shell.py

a5b5a3229579ae71def5197590afb3feae18d9fc

permissive

https://github.com/Seabreg/chiasm-shell

d08d159c0ad90841b38ce348b2ac5595b57a5dbe

e20ed9fdf3fcb87d9469aa6fd52bf9e3eed92bc7

refs/heads/master

#!/usr/bin/env python """ Main class and method for chiasm shell. :author: Ben Cheney :license: MIT """ from __future__ import absolute_import import logging import chiasm_shell.config as config l = logging.getLogger('chiasm_shell.chiasm_shell') class ChiasmShell(object): """ Utility class for kicking off the shell. """ def run(self): """ Creates the default backend and starts the loop. """ backend = config.get_backends()[config.get_default_backend()] info_str = "Chiasm Shell - {}".format(config.__VERSION__) l.info(info_str) while True: l.debug("outer loop spinning up a new shell") l.info("Current arch is %s", backend.get_arch()) backend.cmdloop() if backend.launch_module is not None: backend = backend.launch_module else: break def main(): """ Public method for starting Chiasm Shell. """ ChiasmShell().run() if __name__ == '__main__': main()

UTF-8

Python

py

chiasm_shell.py

davidcarvalho/code-snippets

13cddd9a7136e01b06b7a80e536b931bcb75c258

67e18e48337134e144dadeaa3f619952658af1fa

/code_snippets/print_dict.py

b3e7628c09b7a702b1f7a99a4eddf2ad916883c1

no_license

https://github.com/davidcarvalho/code-snippets

e687f3fa2176b7c9c8cb87c2dce4e64cfb3aa339

d0c0904b2ea0668b4c58bb269ac27f3eded0827c

refs/heads/master

def dict_print(dict1): for key in dict1.keys(): if type(dict1[key]) is dict: dict_print(dict1[key]) else: print(f'Dictionary key {key} for dictionary value {dict1[key]}') d = {x: x ** 2 for x in [2, 3, 4, 5, 6, 7]} print(d) dict_print(d)

UTF-8

Python

py

print_dict.py

isabella232/altimeter

e9bc4554d8a297b95d4552d1de7753dc49c8ca8c

b3610065d63cd2a78a8b3563576ea6597d76ea3b

/altimeter/aws/access/accessor.py

898c69da644bd7763dbe95d2b2d0e0fdf315b378

permissive

https://github.com/isabella232/altimeter

5d0d7c7efcaef2613b0a11a4249b7322a9aaf8de

7969fa62de54546e7548aa998bb2f42b78e69851

refs/heads/master

"""Classes defining multi-stage AWS access methods. Provides the ability to auth to an account via 1+ bridge accounts and to try multiple methods.""" from dataclasses import dataclass, field from datetime import datetime import json import os from pathlib import Path from typing import Any, Dict, List, Optional, Type import boto3 from altimeter.aws.access.exceptions import AccountAuthException from altimeter.core.log import Logger from altimeter.core.log_events import LogEvent @dataclass(frozen=True) class SessionCacheValue: """A SessionCacheValue represents a value in a :class:`.SessionCache`. Args: session: boto3 Session object expiration: expiration time for this cache value. """ session: boto3.Session expiration: datetime def is_expired(self) -> bool: """Determine if this cache value is expired Returns: True if this session is value is expired, else False. """ return datetime.utcnow().replace(tzinfo=None) >= self.expiration.replace(tzinfo=None) class SessionCache: """A SessionCache is a cache for boto3 Sessions.""" def __init__(self) -> None: self._cache: Dict[str, SessionCacheValue] = {} @staticmethod def _build_key( account_id: str, role_name: str, role_session_name: str, region: Optional[str] ) -> str: """Build a key for a :class:`.SessionCache` representing a unique Session. Args: account_id: session account id role_name: session role name role_session_name: session role session name region: session region Returns: string cache key """ return f"{account_id}:{role_name}:{role_session_name}:{region}" def put( self, session: boto3.Session, expiration: datetime, account_id: str, role_name: str, role_session_name: str, region: Optional[str] = None, ) -> None: """Put a Session into the cache. Args: session: session to cache expiration: expiration time for this entry account_id: session account id role_name: session role name role_session_name: session role session name region: session region """ cache_key = SessionCache._build_key(account_id, role_name, role_session_name, region) self._cache[cache_key] = SessionCacheValue(session, expiration) def get( self, account_id: str, role_name: str, role_session_name: str, region: Optional[str] = None ) -> Optional[SessionCacheValue]: """Get a session from the cache. Args: account_id: session account id role_name: session role name role_session_name: session role session name region: session region Returns: SessionCacheValue if one is found, else None. """ cache_key = SessionCache._build_key(account_id, role_name, role_session_name, region) cache_val = self._cache.get(cache_key) if cache_val is not None: if cache_val.is_expired(): del self._cache[cache_key] else: return self._cache[cache_key] return None @dataclass(frozen=True) class AccessStep: """Represents a single access step to get to an account. Args: role_name: role name for this step account_id: account_id for this step. If empty this step is assumed to be the last in a chain of multiple AccessSteps external_id: external_id to use for access (if needed). """ role_name: str account_id: Optional[str] = field(default=None) external_id: Optional[str] = field(default=None) def __str__(self) -> str: account = self.account_id if self.account_id else "target" return f"{self.role_name}@{account}" def to_dict(self) -> Dict[str, Any]: """Generate a dict representation of this AccessStep Returns: dict representation of this AccessStep """ return { "role_name": self.role_name, "external_id": self.external_id, "account_id": self.account_id, } @classmethod def from_dict(cls: Type["AccessStep"], data: Dict[str, Any]) -> "AccessStep": """Create an AccessStep from a dict containing AccessStep data. Args: data: AccessStep data dict Returns: AccessStep object Raises: ValueError if data is not valid """ role_name = data.get("role_name") if role_name is None: raise ValueError(f"{cls.__name__} missing key 'role_name': {data}") external_id = data.get("external_id") if not external_id: external_id_env_var = data.get("external_id_env_var") if external_id_env_var is not None: external_id = os.environ.get(external_id_env_var) if external_id is None: raise ValueError( f"Missing env var '{external_id_env_var}' for {cls.__name__} {data}" ) account_id = data.get("account_id") return cls(role_name=role_name, external_id=external_id, account_id=account_id) class MultiHopAccessor: """A MultiHopAccessor contains a list of AccessSteps defining how to gain access to an account. Args: role_session_name: role session name to use for session creation. access_steps: list of AccessSteps defining how to access a final destination account. """ def __init__(self, role_session_name: str, access_steps: List[AccessStep]): self.role_session_name = role_session_name if not access_steps: raise ValueError("One or more access steps must be specified") for access_step in access_steps[:-1]: if not access_step.account_id: raise ValueError( "Non-final AccessStep of a MultiHopAccessor must specify an account_id" ) if access_steps[-1].account_id: raise ValueError( "The last AccessStep of a MultiHopAccessor must not specify account_id" ) self.access_steps = access_steps self.session_cache = SessionCache() def get_session(self, account_id: str, region: Optional[str] = None) -> boto3.Session: """Get a session for an account_id by iterating through the :class:`.AccessStep`s of this :class:`.MultiHopAccessor`. Args: account_id: account to access region: region to use during session creation. Returns: boto3 Session for accessing account_id """ logger = Logger() cws = boto3.Session(region_name=region) for access_step in self.access_steps: access_account_id = access_step.account_id if access_step.account_id else account_id role_name = access_step.role_name external_id = access_step.external_id session_cache_value = self.session_cache.get( account_id=access_account_id, role_name=role_name, role_session_name=self.role_session_name, region=region, ) if session_cache_value is None: logger.debug(event=LogEvent.AuthToAccountStart) sts_client = cws.client("sts") role_arn = f"arn:aws:iam::{access_account_id}:role/{role_name}" assume_args = {"RoleArn": role_arn, "RoleSessionName": self.role_session_name} if external_id: assume_args["ExternalId"] = external_id assume_resp = sts_client.assume_role(**assume_args) creds = assume_resp["Credentials"] expiration = creds["Expiration"] cws = boto3.Session( aws_access_key_id=creds["AccessKeyId"], aws_secret_access_key=creds["SecretAccessKey"], aws_session_token=creds["SessionToken"], region_name=region, ) self.session_cache.put( session=cws, expiration=expiration, account_id=access_account_id, role_name=role_name, role_session_name=self.role_session_name, region=region, ) logger.debug(event=LogEvent.AuthToAccountEnd) else: cws = session_cache_value.session return cws def __str__(self) -> str: return f'accessor:{self.role_session_name}:{",".join([str(access_step) for access_step in self.access_steps])}' def to_dict(self) -> Dict[str, Any]: """Generate a dict representation of this MultiHopAccessor Returns: dict representation of this MultiHopAccessor """ return { "role_session_name": self.role_session_name, "access_steps": [access_step.to_dict() for access_step in self.access_steps], } @classmethod def from_dict(cls: Type["MultiHopAccessor"], data: Dict[str, Any]) -> "MultiHopAccessor": """Build a MultiHopAccessor from a dict representation. Args: data: dict of data representing a MultiHopAccessor Returns: MultiHopAccessor object """ access_step_dicts = data.get("access_steps") if access_step_dicts is None: raise ValueError(f"{cls.__name__} missing key 'access_steps': {data}") access_steps = [ AccessStep.from_dict(access_step_dict) for access_step_dict in access_step_dicts ] role_session_name = data.get("role_session_name") if role_session_name is None: raise ValueError(f"{cls.__name__} missing key 'role_session_name': {data}") return cls(role_session_name, access_steps) @dataclass(frozen=True) class Accessor: """An Accessor consists of a list of MultiHopAccessors. It provides a method `get_session` which will iterate through the MultiHopAccessors until a session can be obtained to a target account. If an Accessor has no MultiHopAccessors it simply uses the local session to attempt to access the account. If the session does not match the requested target account id, ValueError is thrown. Args: multi_hop_accessors: List of MultiHopAccessors """ multi_hop_accessors: List[MultiHopAccessor] = field(default_factory=list) def get_session(self, account_id: str, region: Optional[str] = None) -> boto3.Session: """Get a boto3 session for a given account. Args: account_id: target account id region: session region Returns: boto3.Session object """ logger = Logger() with logger.bind(auth_account_id=account_id): if self.multi_hop_accessors: for mha in self.multi_hop_accessors: # pylint: disable=not-an-iterable with logger.bind(auth_accessor=str(mha)): try: session = mha.get_session(account_id=account_id, region=region) return session except Exception as ex: logger.debug(event=LogEvent.AuthToAccountFailure, exception=str(ex)) raise AccountAuthException(f"Unable to access {account_id} using {str(self)}") # local run mode session = boto3.Session(region_name=region) sts_client = session.client("sts") sts_account_id = sts_client.get_caller_identity()["Account"] if sts_account_id != account_id: raise ValueError(f"BUG: sts_account_id {sts_account_id} != {account_id}") return session def __str__(self) -> str: return ", ".join( [str(mha) for mha in self.multi_hop_accessors] # pylint: disable=not-an-iterable ) def to_dict(self) -> Dict[str, Any]: """Generate a dict representation of this Accessor. Returns: dict representation of this Accessor. """ mha_dicts = [ mha.to_dict() for mha in self.multi_hop_accessors # pylint: disable=not-an-iterable ] data = {"accessors": mha_dicts} return data @classmethod def from_dict(cls: Type["Accessor"], data: Dict[str, Any]) -> "Accessor": """Create an Accessor from a dict representation. Args: data: dict representation of an Accessor Returns: Accessor object """ multi_hop_accessors: List[MultiHopAccessor] = [] accessor_dicts = data.get("accessors", []) for accessor_dict in accessor_dicts: multi_hop_accessor = MultiHopAccessor.from_dict(accessor_dict) multi_hop_accessors.append(multi_hop_accessor) return cls(multi_hop_accessors=multi_hop_accessors) @classmethod def from_file(cls: Type["Accessor"], filepath: Path) -> "Accessor": """Create an Accessor from json content in a file Args: filepath: Path to json accessor definition Returns: Accessor """ with filepath.open("r") as fp: data = json.load(fp) return cls.from_dict(data)

UTF-8

Python

py

accessor.py

theMagicalKarp/python-xml-parsing-benchmark

c95b37e324410d534eece2cc55e3e102c7d4bc9b

e7b30e2a05aa8bd440a8b5f5fc0c1e38365dbd9a

/tools/__init__.py

7c8267e3098ef108200139436aed93e1a5bae75e

no_license

https://github.com/theMagicalKarp/python-xml-parsing-benchmark

97394cae255ff74c14dc3e052175b44a7288e687

5819eedbab0c53bcec1c791f029c1945673c8a01

refs/heads/master

import sys, profilers, pstats class ProfileManager(object): """ Profile Manager Handles and runs mulitiple profiles to generates reports. Attributes: profiler_list: list of profiler objects compare each run xml_data: A string representation of our xml file """ def __init__(self, profiler_list, xml_file_name): self.profiler_list = profiler_list xml_file = open(xml_file_name) self.xml_data = xml_file.read() xml_file.close() def print_stats(self, stats, results, sample_size): """ Prints stats This allows for a controlled output format. Also this should only be only called under the context of several profiles under the same conditions. Args: stats: list of Pstat objects results: list of result items sample_size: number of samples ran """ num_passed = sum(res.passed for res in results) print '////////////////////////////////////////////////////////' print '///// Average number of calls per sample, %s' % (stats.total_calls/(sample_size)) print '///// Average run time per sample, %s seconds' % (stats.total_tt/(sample_size)) print '///// %d out of %d test passed' % (num_passed, sample_size) print '////////////////////////////////////////////////////////' stats.sort_stats('time') stats.print_stats() def print_current_status(self, to_write): """ Print current status Is our standard format for printing and updating a line on the prompt. Args: to_write: a new stirng to replace our current line with """ print to_write, sys.stdout.flush() print "\r", def search_tag_by_attribute(self, tag, attribute, attribute_value, sample_size = 25): """ Search tag by attribute This runs all of our profiles stored in profiler list and aggergates all of our stats from each run. This specificly runs the search tag by attribute on each profiler. Args: tag: the name of the tag we need to find attribute: the attribute are we inspecting attribute_value: the value of our attrubte we are trying to find sample_size: the number of samples we would like to collect """ results_by_profile = {} stats_by_profile = {} expected_result = {'tag':tag, 'attribute_value':attribute_value} for profiler in self.profiler_list: print '----- Running Profiler on %s -----' % (profiler.name) results_by_profile[profiler] = [] num_passed = 0 for sample_num in xrange(sample_size): self.print_current_status(' Currently profiling sample %s...' % (sample_num+1)) result = profiler.search_tag_by_attribute(self.xml_data, tag, attribute, attribute_value, sample_num) num_passed = num_passed+1 if result.test(expected_result) else num_passed results_by_profile[profiler].append(result) if profiler in stats_by_profile: stats_by_profile[profiler].add(result.profile_result) else: stats_by_profile[profiler] = pstats.Stats(result.profile_result) self.print_stats(stats_by_profile[profiler], results_by_profile[profiler], sample_size) return stats_by_profile

UTF-8

Python

py

__init__.py

fryslie/eulerbend

76e53c3563c11936fb522333bce3298fb680f618

291e736b4eca07dd55f62a342ed4000b99aa28b5

/eulerbend_ipkiss.py

4b30ea76ce47924d81d58b2084423bfe73cc7ddf

no_license

https://github.com/fryslie/eulerbend

4970fb3aa8bfbffa5b4fd0a5d66a8b997f9025d8

00ae6a7968579dacebe267cff9ac90a3f4a4dfa0

refs/heads/master

""" Generate an euler bend with IPKISS """ from __future__ import division import numpy as np from scipy.special import fresnel import technologies.silicon_photonics import ipkiss3.all as i3 def _euler_bend_center_line_shape(R=10, theta=np.pi/2, num_points=1000): """ Args: R (float): minimal bend radius theta (float): final angle (in radians) num_points (int): resolution of the shape """ L = R * theta # HALF of total length s = np.linspace(0, L, num_points // 2) f = np.sqrt(np.pi * R * L) + 1e-18 # for numerical stability y1, x1 = fresnel(s / f) # first, rotate by the final angle x2, y2 = np.dot( np.array([[np.cos(theta), np.sin(theta)], [-np.sin(theta), np.cos(theta)]]), np.stack([x1, y1], 0), ) # then, flip along the x-axis (and reverse direction of the curve): x2, y2 = -x2[::-1], y2[::-1] # then translate from (x2[0], y2[0]) to (x1[-1], y1[-1]) x2, y2 = x2 - x2[0] + x1[-1], y2 - y2[0] + y1[-1] x = f * np.concatenate([x1, x2], 0) y = f * np.concatenate([y1, y2], 0) return zip(x, y) class EulerBend(i3.PCell): """ An Euler Bend for IPKISS """ _name_prefix = "EULER_BEND" trace_template = i3.WaveguideTemplateProperty( doc="trace template for the waveguide" ) def _default_trace_template(self): return i3.TECH.PCELLS.WG.DEFAULT waveguide = i3.ChildCellProperty(doc="waveguide") def _default_waveguide(self): return i3.RoundedWaveguide(trace_template=self.trace_template) class Layout(i3.LayoutView): """ Layout for the IPKISS Euler Bend """ min_radius = i3.PositiveNumberProperty(doc="minimum Euler bend radius") def _default_min_radius(self): if self.end_point is None: return 10 x, y = self.end_point # the final angle is twice the angle between start and finish. theta = 2 * np.arctan2(y, x) x_final = _euler_bend_center_line_shape(R=1, theta=theta, num_points=4)[-1][0] return x / x_final end_angle = i3.PositiveNumberProperty(doc="angle (in degrees) at the end of the Euler bend.") def _default_end_angle(self): if self.end_point is None: return 90 x, y = self.end_point return 2 * np.arctan2(y, x) * i3.RAD2DEG num_points = i3.PositiveNumberProperty( doc="resolution of the euler bend shape.", default=1000, ) end_point = i3.Coord2Property( doc=( "(optional) coordinates of the end of the Euler bend.\n" "if given, this will override `min_radius` and `end_angle`." ), default=None, ) core_width = i3.PositiveNumberProperty( doc="default core width of the waveguide", default=i3.TECH.WG.WIRE_WIDTH, ) cladding_width = i3.PositiveNumberProperty( doc="default cladding width of the waveguide", default=i3.TECH.WG.CLADDING_WIDTH, ) def _default_trace_template(self): trace = self.cell.trace_template.get_default_view(i3.LayoutView) trace.set( core_width=self.core_width, cladding_width=self.cladding_width, ) return trace def _default_waveguide(self): waveguide = self.cell.waveguide.get_default_view(i3.LayoutView) center_line = _euler_bend_center_line_shape( R=self.min_radius, theta=self.end_angle * i3.DEG2RAD, num_points=self.num_points, ) waveguide.set( shape=center_line, trace_template=self.trace_template, bend_radius=self.min_radius, ) return waveguide def _generate_instances(self, insts): insts += i3.SRef(reference=self.waveguide) return insts def _generate_ports(self, ports): ports += self.waveguide.ports return ports if __name__ == "__main__": cell = EulerBend() layout = cell.Layout(end_angle=90, core_width=1, min_radius=10) layout.visualize(annotate=True) layout.write_gdsii("eulerbend.gds")

UTF-8

Python

py

eulerbend_ipkiss.py

simon-pikalov/deep_learning_course_matirial

2019122ef982ced8b3457f1070649319c7093c85

32e5077d41894607daec358998a72c01bc90ce21

/logistic_regression/ergent_classifier.py

e355cd65608236d3b8da1afa18456a52c4cb3998

no_license

https://github.com/simon-pikalov/deep_learning_course_matirial

19889c9496ef464e87ad7054358ebb9cccd4817d

5b438208745d3e430efb2e389e1ade9ef65811c4

refs/heads/main

import numpy as np import tensorflow.compat.v1 as tf import os import numpy as np import matplotlib.pyplot as plt tf.disable_v2_behavior() tf.disable_eager_execution() os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' vocabulary_size = 0 # can use "global" keyword word2location = {} data = ["Where are you? I'm trying to reach you for half an hour already, contact me ASAP I need to leave now!", "I want to go out for lunch, let me know in the next couple of minutes if you would like to join.", "I was wondering whether you are planning to attend the party we are having next month.", "I wanted to share my thoughts with you."] def prepare_vocabulary(data): idx = 0 for sentence in data: for word in sentence.split(): # better use nltk.word_tokenize(sentence) and perform some stemming etc.!!! if word not in word2location: word2location[word] = idx idx += 1 return idx def convert2vec(sentence): res_vec = np.zeros(vocabulary_size) for word in sentence.split(): # also here... if word in word2location: res_vec[word2location[word]] += 1 return res_vec def logistic_fun(z): return 1 / (1.0 + np.exp(-z)) features = vocabulary_size eps = 1e-12 x = tf.placeholder(tf.float32, [None, features]) y_ = tf.placeholder(tf.float32, [None, 1]) W = tf.Variable(tf.zeros([features,1])) b = tf.Variable(tf.zeros([1])) y = 1 / (1.0 + tf.exp(-(tf.matmul(x,W) + b))) loss1 = -(y_*tf.log(y+eps) + (1-y_) * tf.log( 1 - y + eps)) loss = tf.reduce_mean(loss1) update = tf.train.GradientDescentOptimizer(0.00001).minimize(loss) data_x = np.array([convert2vec(data[0]), convert2vec(data[1]), convert2vec(data[2]), convert2vec(data[3])]) data_y = np.array([[1],[1],[0],[0]]) sess = tf.Session() sess.run(tf.global_variables_initializer()) print(data_x) print(data_y) for i in range(0,10000): sess.run(update, feed_dict = {x:data_x, y_:data_y}) #BGD # test1 = "I need you now! Please answer ASAP!" test2 = "I wanted to hear your thoughts about my plans." # pdb.set_trace() print('Prediction for: "' + test1 + '"', logistic_fun(np.matmul(np.array([convert2vec(test1)]), sess.run(W)) + sess.run(b))[0][0]) print('Prediction for: "' + test2 + '"', logistic_fun(np.matmul(np.array([convert2vec(test2)]), sess.run(W)) + sess.run(b))[0][0])

UTF-8

Python

py

ergent_classifier.py

bipashasen/CTC-Transformer-Spech-Recognition

071d64e0a36de2cd1650eee221c90c70a6a4ecea

e7a4d237203a32ab61d7e922eee457f039bb535e

/create_features_temp.py

a2225748a4a1240d041862101ad19bec06074307

no_license

https://github.com/bipashasen/CTC-Transformer-Spech-Recognition

cb3e1d34c51037550b8eb96ed878a77a52d1a999

ee6dc06aac79e0e582488cd4e337f139e5f3e1f8

refs/heads/master

import soundfile as sf import os import numpy as np from numpy import asarray from numpy import save from numpy import savez import sys folder_path = sys.argv[1] features_folder_path = sys.argv[2] featureAudioMapping = sys.argv[3] feature_size = 3200 def processFeatures(): featureAudioMap = list() maxFrameLength = -1 for root, dirs, files in os.walk(folder_path): for file in files: if file.endswith('.flac'): # read the audio file and store the features # in features_folder_path with the same name as audio_file audioFilePath = root + '/' + file data, samplerate = sf.read(audioFilePath) data = np.append(data, [0]*(feature_size-data.shape[0]%feature_size)) data = data.reshape(int(data.shape[0]/feature_size), feature_size) if data.shape[0] > maxFrameLength: maxFrameLength = data.shape[0] maxAudioFile = audioFilePath featureFilePath = features_folder_path + file.split('.')[0] + '.npz' savez(featureFilePath, data) #featureFilePath = features_folder_path + file.split('.')[0] + '.npy' #save(featureFilePath, data) # add the mapping to a file featureAudioMap.append(audioFilePath + ' ' + featureFilePath) print('Max sequence length : ' + str(maxFrameLength)) print('Max audio file : ' + maxAudioFile) # save the mapping into a file with open(featureAudioMapping, 'w') as f: for line in featureAudioMap: f.write(line + '\n') if __name__ == "__main__": processFeatures()

UTF-8

Python

py

create_features_temp.py

Naive96/AdventOfCode

1bc85a493d186475606b2bfe4b1a5401947b4f46

361c629165244dbabcee15571ff4de1a18d0e6b7

/test/Day2/TestDay2.py

20fddc9420b789e70685c11afde793dd3f08817e

no_license

https://github.com/Naive96/AdventOfCode

17a071e1437c632d3b1fd1a036f6c584c5637f53

a7cdb18ccb7777f120ef673b164d9dd91ed6910c

refs/heads/main

import unittest from src.Day2 import part1 from src.Day2 import part2 class TestDay2(unittest.TestCase): def test_part1(self): pwds = ['1-3 a: abcde', '1-3 b: cdefg', '2-9 c: ccccccccc'] result = part1.execute(pwds) self.assertEqual(result, 2) def test_part2(self): pwds = ['1-3 a: abcde', '1-3 b: cdefg', '2-9 c: ccccccccc'] result = part2.execute(pwds) self.assertEqual(result, 1)

UTF-8

Python

py

TestDay2.py

prantoran/prac

bc8b40ebb4f95a4bf32c5c2d6cab76de69a13b3b

2be0db6b3bde8401095b95b2043202d934713265

/envp/lib/python3.7/tempfile.py

2201d99252a7a40153702fb0362e7407baf05063

no_license

https://github.com/prantoran/prac

cd13f3cf2fed196481dd0c7a1d32407ffcad6aa1

b0925fcd2cb4c8b27673bfd145aaee7537243114

refs/heads/master

/home/prantoran/miniconda3/lib/python3.7/tempfile.py

UTF-8

Python

py

tempfile.py

Aeroone/YSTR-CVL

d87d0dba2c0273d3a5872e139686e390537bfbb3

773211e16baf1b7a8105f1aa20b0d5c7a370c78c

/model_VisualSemanticEmbedding.py

5b5c8f4694392b4c0a0ff76016c966dc69eadb10

no_license

https://github.com/Aeroone/YSTR-CVL

b149ae84e24c12806ea10f5b4150e70bb2cfdf7e

be586f279a4634ee006fb2594902fc9e91f1e17a

refs/heads/master

import torch import torch.nn as nn import torch.nn.functional as F from torch.autograd import Variable import config import torchvision.models as models ### use the visual semantic text embedding model here ### class VisualSemanticEmbedding(nn.Module): def __init__(self, embed_ndim): super(VisualSemanticEmbedding, self).__init__() self.embed_ndim = embed_ndim # image feature --- use vgg16 --- if config.use_vgg: self.img_encoder = models.vgg16(pretrained = True) for param in self.img_encoder.parameters(): param.requires_grad = False self.feat_extractor = nn.Sequential(*(self.img_encoder.classifier[i] for i in range(6))) # turn to the same dimension of the text! self.W = nn.Linear(4096, embed_ndim, False) # text feature self.text_encoder = nn.GRU(embed_ndim, embed_ndim, 1) # GRU(input_size, hidden_size, num_layers) def forward(self, img, txt): ##################### ### image feature ### img_feat = self.img_encoder.features(img) img_feat = img_feat.view(img_feat.size(0), -1) img_feat = self.feat_extractor(img_feat) img_feat = self.W(img_feat) ##################### ##################### ### text feature ### h0 = torch.zeros(1, img.size(0), self.embed_ndim) h0 = Variable(h0.cuda() if config.is_cuda else h0) # the initial hidden state for each element in the batch _, txt_feat = self.text_encoder(txt, h0) txt_feat = txt_feat.squeeze() ##################### return img_feat, txt_feat

UTF-8

Python

py

model_VisualSemanticEmbedding.py

Sunjjjjjj/AAI_simulator_py2

c6c18fc20a3fb3bf6b5a2c8657f68b54e205b41d

6adcffdbc4af75c3ccde5bfc638d248241f4bf19

/MODIS_combine.py

97dd3d55fdafc7c6c2d8057fb247413a16b2886f

no_license

https://github.com/Sunjjjjjj/AAI_simulator_py2

fedd9b9050ea8b4c3dc4980ece3e21c08831c1f1

4f98c3feae1c27f28397aa8683c8c3af06673cf4

refs/heads/master

# -*- coding: utf-8 -*- """ Intercomparison among satellite data @author: sunj """ import sys, os import shutil import time import numpy as np import numpy.ma as ma import matplotlib.pyplot as plt from netCDF4 import Dataset import glob import tables from scipy import ndimage from mpl_toolkits.basemap import Basemap import seaborn as sns from matplotlib.colors import ListedColormap from sklearn.metrics import mean_squared_error from scipy.optimize import leastsq from shutil import copyfile import subprocess from scipy import optimize from scipy.interpolate import griddata from math import sqrt #from OMAERO import gridOMAERO, OMAERO4cfg #from MODIS import gridMODIS, MODIS4cfg from pyhdf.SD import SD, SDC from scipy.misc import bytescale #plt.rcParams.update({'xtick.color': 'k','ytick.color':'k','text.color':'k','axes.labelcolor':'k', 'lines.linewidth':2,'font.size':22,'axes.labelsize':22,'axes.titlesize':22,'xtick.labelsize':18,'ytick.labelsize':18,'legend.fontsize':22}) plt.rcParams.update({'xtick.color': 'k','ytick.color':'k','text.color':'k','axes.labelcolor':'k', 'lines.linewidth':2,'font.size':14,'axes.labelsize':14,'axes.titlesize':14,'xtick.labelsize':12,'ytick.labelsize':12,'legend.fontsize':14}) year = 2017 month = 1 days = list(np.arange(26,30,1)) days.remove(28) day = 26 aerlat = -33.46 aerlon = -70.66 print 'Calculate time zone' if abs(aerlon)%15 < 7.5: jetlag = abs(aerlon)//15 else: jetlag = abs(aerlon)//15+1 if aerlon<0: jetlag = - jetlag print jetlag ROI = [-40,-12.5,-97.5,-70] crival = 2 res = 0.5 print '**** Reading MODIS %02i-%02i-%4i' % (day, month, year) moddir = '/nobackup/users/sunj/MODIS/AQUA/MYD021KM/%4i/%02i/%02i/' % (year, month, day) coordir = '/nobackup/users/sunj/MODIS/AQUA/MYD03/%4i/%02i/%02i/' % (year, month, day) filelist = glob.glob( moddir + '*.hdf') coorlist = glob.glob( coordir + '*.hdf') red = [] modlat = [] modlon = [] plt.figure(figsize=(4.5,4), frameon = False) for i in range(len(filelist)): data = SD(filelist[i], SDC.READ) coor = SD(coorlist[i], SDC.READ) selected_sds = data.select('EV_250_Aggr1km_RefSB') selected_sds_attributes = selected_sds.attributes() for key, value in selected_sds_attributes.iteritems(): if key == 'reflectance_scales': reflectance_scales_250_Aggr1km_RefSB = np.asarray(value) if key == 'reflectance_offsets': reflectance_offsets_250_Aggr1km_RefSB = np.asarray(value) sds_data_250_Aggr1km_RefSB = selected_sds.get() selected_sds = data.select('EV_500_Aggr1km_RefSB') selected_sds_attributes = selected_sds.attributes() for key, value in selected_sds_attributes.iteritems(): if key == 'reflectance_scales': reflectance_scales_500_Aggr1km_RefSB = np.asarray(value) if key == 'reflectance_offsets': reflectance_offsets_500_Aggr1km_RefSB = np.asarray(value) sds_data_500_Aggr1km_RefSB = selected_sds.get() selected_sds = coor.select('Latitude') myd03_lat = selected_sds.get() selected_sds = coor.select('Longitude') myd03_long = selected_sds.get() data_shape = sds_data_250_Aggr1km_RefSB.shape along_track = data_shape[1] cross_trak = data_shape[2] z = np.zeros((along_track, cross_trak,3)) for i in np.arange(along_track): for j in np.arange(cross_trak): z[i,j,0] = ( sds_data_250_Aggr1km_RefSB[0,i,j] - \ reflectance_offsets_250_Aggr1km_RefSB[0] ) * \ reflectance_scales_250_Aggr1km_RefSB[0] for i in np.arange(along_track): for j in np.arange(cross_trak): z[i,j,1] = ( sds_data_500_Aggr1km_RefSB[1,i,j] - \ reflectance_offsets_500_Aggr1km_RefSB[1] ) * \ reflectance_scales_500_Aggr1km_RefSB[1] for i in np.arange(along_track): for j in np.arange(cross_trak): z[i,j,2] = ( sds_data_500_Aggr1km_RefSB[0,i,j] - \ reflectance_offsets_500_Aggr1km_RefSB[0] ) * \ reflectance_scales_500_Aggr1km_RefSB[0] z[ z > 1 ] = 1.0 z[ z < 0 ] = 0.0 lat_min = myd03_lat[0,0] lat_max = myd03_lat[along_track-1,cross_trak-1] lat_0 = lat_min + (lat_max - lat_min) / 2. long_min = min(myd03_long[0,0],myd03_long[along_track-1,cross_trak-1]) long_max = max(myd03_long[0,0],myd03_long[along_track-1,cross_trak-1]) lon_0 = long_min + (long_max - long_min) / 2. #----------------------------------------------------------------------------------------# # Orthographic Map Projection fig = plt.figure() ax = fig.add_subplot(111) ax.patch.set_facecolor((0.75,0.75,0.75)) m1 = Basemap(projection='ortho',lon_0=lon_0,lat_0=lat_0,resolution=None) xpt0, ypt0 = m1(lon_0,lat_0) xpt1, ypt1 = m1(myd03_long[0,0],myd03_lat[0,0]) xpt2, ypt2 = m1(myd03_long[0,cross_trak-1],myd03_lat[0,cross_trak-1]) xpt3, ypt3 = m1(myd03_long[along_track-1,cross_trak-1], \ myd03_lat[along_track-1,cross_trak-1]) xpt4, ypt4 = m1(myd03_long[along_track-1,0],myd03_lat[along_track-1,0]) llx = min(xpt1,xpt2,xpt3,xpt4) - xpt0 # lower left lly = min(ypt1,ypt2,ypt3,ypt4) - ypt0 urx = max(xpt1,xpt2,xpt3,xpt4) - xpt0 # upper right ury = max(ypt1,ypt2,ypt3,ypt4) - ypt0 m = Basemap(projection='ortho',lon_0=lon_0,lat_0=lat_0,resolution='l',\ llcrnrx=llx,llcrnry=lly,urcrnrx=urx,urcrnry=ury) x_igrid, y_igrid = m(myd03_long,myd03_lat) x_igrid = x_igrid - xpt0 y_igrid = y_igrid - ypt0 z_igrid_01 = np.zeros((along_track, cross_trak)) z_igrid_02 = np.zeros((along_track, cross_trak)) z_igrid_03 = np.zeros((along_track, cross_trak)) for i in np.arange(2030): for j in np.arange(1354): z_igrid_01[i,j] = z[i,j,0] z_igrid_02[i,j] = z[i,j,1] z_igrid_03[i,j] = z[i,j,2] x1_igrid = x_igrid.ravel() y1_igrid = y_igrid.ravel() z_igrid_01 = z_igrid_01.ravel() z_igrid_02 = z_igrid_02.ravel() z_igrid_03 = z_igrid_03.ravel() xy1_igrid = np.vstack((x1_igrid, y1_igrid)).T xi, yi = np.mgrid[llx:urx:1000j, lly:ury:1000j] z_01 = griddata(xy1_igrid, z_igrid_01, (xi, yi), method='cubic') z_02 = griddata(xy1_igrid, z_igrid_02, (xi, yi), method='cubic') z_03 = griddata(xy1_igrid, z_igrid_03, (xi, yi), method='cubic') rgb_projected = np.zeros((1000, 1000,3)) for i in np.arange(1000): for j in np.arange(1000): rgb_projected[i,j,0] = z_01[i,j] rgb_projected[i,j,1] = z_02[i,j] rgb_projected[i,j,2] = z_03[i,j] #rgb_projected[ z > 1 ] = 1.0 #rgb_projected[ z < 0 ] = 0.0 whereAreNaNs = np.isnan(rgb_projected); rgb_projected[whereAreNaNs] = 0.75; img = m.imshow(np.rot90(np.fliplr(rgb_projected)), origin='lower') m.drawcoastlines() m.drawparallels(np.arange(-90.,120.,5.), color='k', labels=[True,False,False,False]) m.drawmeridians(np.arange(0.,420.,5.), color='k', labels=[False,False,False,True]) ax.set_xlabel("", fontsize=10) ax.set_ylabel("", fontsize=10)

UTF-8

Python

py

MODIS_combine.py

vfat0/safe-transaction-service

eb35a4aa12a59cac12efb1a19c8cb039065df0c3

063bb17c8a6ee197f0ef5e228ebb7735287d064a

/safe_transaction_service/history/tests/test_tasks.py

5a4e36efbeeae64e1b122d727cdd69b86fde5401

permissive

https://github.com/vfat0/safe-transaction-service

55790f5ad4d35e39f563aa66017f31057ecc64ba

a8c48343a5d32971828f1d9c9e9fd113aeaef7fd

refs/heads/master

import logging from unittest.mock import MagicMock, patch from django.test import TestCase from eth_account import Account from ..tasks import BlockchainRunningTask, BlockchainRunningTaskManager from .factories import EthereumEventFactory, InternalTxFactory, WebHookFactory logger = logging.getLogger(__name__) class TestTasks(TestCase): @patch('requests.post') def test_send_webhook_task(self, mock_post: MagicMock): EthereumEventFactory() with self.assertRaises(AssertionError): mock_post.assert_called() to = Account.create().address WebHookFactory(address='') WebHookFactory(address=Account.create().address) WebHookFactory(address=to) InternalTxFactory(to=to) self.assertEqual(mock_post.call_count, 2) def test_blockchain_running_task(self): # Test context manager class A: def __init__(self, id: str): self.id = id BlockchainRunningTaskManager().delete_all_tasks() a = A('custom-task-id') b = A('another-task_id') with BlockchainRunningTask(a) as blockchain_running_task: self.assertEqual(blockchain_running_task.blockchain_running_task_manager.get_running_tasks(), [a.id]) with BlockchainRunningTask(b): self.assertEqual(blockchain_running_task.blockchain_running_task_manager.get_running_tasks(), [b.id, a.id]) self.assertEqual(BlockchainRunningTaskManager().get_running_tasks(), [])

UTF-8

Python

py

test_tasks.py

profjefer/biological-cells-counter

339cdf95a0bf01ca4fe1f81ea282cc3ee2a725dc

e3674c95e31ccd76b0d5c0d0674326d17c552584

/project/tests/dip_test.py

9471369dbccd52fd8842738b47e1db3180045028

no_license

https://github.com/profjefer/biological-cells-counter

2780b66f57d8ed4b6407eb91c294630bea0ce5e3

cfa0fba93371577e0098434343e00fc68234e9b0

refs/heads/main

import sys import os import cv2 from colorama import init from termcolor import colored sys.path.append('../') from dip.segmentation_dip import segmentation from shared.counter import count_cells, change_cells_to_rgb def read_file(path_to_file): f = open(path_to_file, 'r') files = f.read() f.close() return files.split('\n') def main(): init() effectiveness = [] number_of_tests = 0 path_to_file = sys.argv[1] if len(sys.argv) > 1 else exit("Missing argument: path_to_file") if os.path.exists(path_to_file) is False: exit("File not found: " + path_to_file) files = read_file(path_to_file) for file in files: path_to_image = '../../train_set/' + file + '/images/' + file + '.png' print(f'Path to file: {path_to_image}') if os.path.exists(path_to_image) is False: print(colored(f'File not found', 'red')) continue try: image = cv2.imread(path_to_image, cv2.CV_8UC1) prepared_image = segmentation(image) prepared_image = prepared_image.tolist() image, cells = count_cells(prepared_image) number_of_cells = len(cells) path_to_mask = '../../train_set/' + file + '/masks/' number_of_masks = len(os.listdir(path_to_mask)) indicator = number_of_cells/number_of_masks effectiveness.append(indicator) if indicator <= 1 else 1 print(colored(f'Effectiveness = {indicator}', 'green')) print(colored('TEST PASS', 'green')) number_of_tests += 1 except Exception as e: print(colored(e, 'red')) print(colored('TEST FAIL', 'red')) avg = sum(effectiveness)/len(effectiveness) if len(effectiveness) > 0 else 0 print() print('SUMMARY') print(f'Succeeded tests: {number_of_tests/len(files)}') print(f'Algorithm average: {avg}') if __name__ == "__main__": main()

UTF-8

Python

py

dip_test.py

xusl/android-wilhelm

fc5a8f09060324dfdf040ff7b1ac63e4db20de9f

ebd585fdafb22d31fcd6d04b209f81e88d1a2083

/modem_proc/core/products/build/SConscript

b31ea370704e024ae230bab6d5b180c6ed858686

permissive

https://github.com/xusl/android-wilhelm

fd28144253cd9d7de0646f96ff27a1f4a9bec6e3

13c59cb5b0913252fe0b5c672d8dc2bf938bb720

refs/heads/master

# Title: Sconscript # License: License # Copyright 2010 Qualcomm Inc # Description: General Description # Sconscript for CoreBSP Products CMM scripts # Team: Functional Area # CoreBSP Products 8960 # Target: Target # MSM8960 # Author: Author # $Author: rvennam $ # Location: Perforce Revision # $Header: //source/qcom/qct/core/products/labtools/legacy/8960/Modem/core/products/build/SConscript $ # Edits: Edits # Created for MSM8960 on 3/8/2011 # ------------------------------------------------------------------------------------------ import datetime import time # Class for a CMM script to be included in the dialog class CMMScript: def __init__(self, scriptname, altname, path, team, numargs): self.scriptname = scriptname self.altname = altname self.path = path self.team = team self.numargs = numargs self.argmapping = {} # T32 dialog file class class T32Dialog: def __init__(self): self.height = 0 self.width = 0 self.title = "Nothing" self.textheight = 0 self.textwidth = 0 self.editheight = 0 self.editwidth = 0 self.chooseboxwidth = 0 self.chooseboxheight = 0 # Function that writes the dialogfile def writedialogfile(): dialogfile = open(T32_Dialog,'w') # Throw in all the comments for the cmm file dialogfile.write('//\t Title: std_dialogauto.dlg') dialogfile.write('\n\n//\t License: License') dialogfile.write('\n//\t Copyright 2010 Qualcomm Inc ') dialogfile.write('\n\n//\t Description: General Description') dialogfile.write('\n//\t This T32 dialog presents user with options to collect logs.') dialogfile.write('\n\n//\t Input: Inputs') dialogfile.write('\n//\t None') dialogfile.write('\n\n//\t Output: Outputs') dialogfile.write('\n//\t None') dialogfile.write('\n\n//\t Usage: Usage') dialogfile.write('\n//\t Not meant for standalone usage') dialogfile.write('\n\n//\t Team: Functional Area') dialogfile.write('\n//\t CoreBSP Products 8660') dialogfile.write('\n\n//\t Target: Target') dialogfile.write('\n//\t MSM8660') dialogfile.write('\n\n//\t Author: Author') dialogfile.write('\n//\t $Author: amcheriy $') dialogfile.write('\n\n//\t Location: Perforce Revision') dialogfile.write('\n//\t $Header: //depot/asic/msm8660/temp_dev/AMSS/products/8660/build/ms/std_buildconfig $') dialogfile.write('\n\n//\t Edits: Edits') dialogfile.write('\n//\t Autogenerated on '+datetime.datetime.now().strftime("%A %d/%m/%Y %H:%M:%S")) dialogfile.write('\n// ---------------------------------------------------------------------------------') dialogfile.write("\n \n \n") dialogfile.write('HEADER \"%s\"' % (window.title)) dialogfile.write('\n \n') dialogfile.write('pos 0. 0. %s. %s.' % (window.width, window.height)) dialogfile.write('\n') dialogfile.write('BOX \"Select Log Type\"') dialogfile.write('\n \n') # Scan the list for i in range(0,len(scripts)): # For each script, create an edit box corresponding to the number of the arguments # Position the edit boxes like a 2D matrix # Labels created for the edit boxes have the format : EDIT(script number)(argument number) - starting from 0 for argcount in range(0,int(scripts[i].numargs)): dialogfile.write('pos %s. %s %s. %s.' % (str(window.chooseboxwidth + 2 + (window.editwidth + 2) * argcount), i*2 + 2.5 , window.editwidth, window.editheight)) dialogfile.write('\n') dialogfile.write('EDIT%s%s: EDIT \"\" \"\"' % (str(i), str(argcount))) dialogfile.write('\n') dialogfile.write('\n \n') for i in range(0,len(scripts)): # For each script, create an edit box corresponding to the number of the arguments # Position the edit boxes like a 2D matrix # Labels created for the edit boxes have the format : EDIT(script number)(argument number) - starting from 0 for argcount in range(0,int(scripts[i].numargs)): dialogfile.write('pos %s. %s %s. %s.' % (str(window.chooseboxwidth + 2 + (window.editwidth + 2) * argcount), i*2 + 1.5 , window.editwidth, window.editheight)) dialogfile.write('\n') dialogfile.write('TEXT%s%s: TEXT \"%s\"' % (str(i), str(argcount), scripts[i].argmapping[argcount+1])) dialogfile.write('\n') dialogfile.write('\n \n') # Create the choosebox dialogfile.write('pos 1. 2. %s. %s.' % (window.chooseboxwidth, window.chooseboxheight)) dialogfile.write('\n') # Scan the list for i in range(0,len(scripts)): argstring ="" for argcount in range(0,int(scripts[i].numargs)): argstring = argstring + " &arg" + str(argcount) dialogfile.write('LOGTYPE.%s: CHOOSEBOX \"%s\"' %(scripts[i].altname.replace(' ',''), scripts[i].altname)) dialogfile.write('\n') dialogfile.write('(&') dialogfile.write('\n \t') # On selecting an item in the choosebox, you need to pick up the string from the corresponding edit box created above for argcount in range(0,int(scripts[i].numargs)): dialogfile.write('&arg%s=DIALOG.STRING(EDIT%s%s)' % ( str(argcount), str(i), str(argcount))) dialogfile.write('\n \t') dialogfile.write('do %s/%s %s' % (scripts[i].path, scripts[i].scriptname, argstring)) dialogfile.write('\n') dialogfile.write(')') dialogfile.write('\n') def writemodemconfigfile(): # Create the file from scratch every single time build_config_file = open(CMM_Build_Config,'w') # Throw in all the comments for the cmm file build_config_file.write('//\t Title: std_buildconfig') build_config_file.write('\n\n//\t License: License') build_config_file.write('\n//\t Copyright 2010 Qualcomm Inc ') build_config_file.write('\n\n//\t Description: General Description') build_config_file.write('\n//\t This script contains build information.') build_config_file.write('\n\n//\t Input: Inputs') build_config_file.write('\n//\t None') build_config_file.write('\n\n//\t Output: Outputs') build_config_file.write('\n//\t None') build_config_file.write('\n\n//\t Usage: Usage') build_config_file.write('\n//\t do std_buildconfig') build_config_file.write('\n\n//\t Team: Functional Area') build_config_file.write('\n//\t CoreBSP Products 8960') build_config_file.write('\n\n//\t Target: Target') build_config_file.write('\n//\t MSM8960') build_config_file.write('\n\n//\t Author: Author') build_config_file.write('\n//\t $Author: rvennam $') build_config_file.write('\n\n//\t Location: Perforce Revision') build_config_file.write('\n//\t $Header: //depot/asic/msm8960/temp_dev/AMSS/products/8660/build/ms/std_buildconfig $') build_config_file.write('\n\n//\t Edits: Edits') build_config_file.write('\n//\t Autogenerated on '+datetime.datetime.now().strftime("%A %d/%m/%Y %H:%M:%S")) build_config_file.write('\n// ---------------------------------------------------------------------------------') build_config_file.write('\n \n \n \n') # Declare your GLOBAL variables here build_config_file.write('\n GLOBAL &MODEM_BUILDID') build_config_file.write('\n GLOBAL &MODEM_BUILDIDM') build_config_file.write('\n GLOBAL &CHIPSET') build_config_file.write('\n GLOBAL &MODEM_BUILDMSDIR') build_config_file.write('\n GLOBAL &MODEM_MBNDIR') build_config_file.write('\n GLOBAL &MODEM_ELFFILE') build_config_file.write('\n GLOBAL &MODEM_TIMESTAMP') build_config_file.write('\n GLOBAL &BUILDID') build_config_file.write('\n GLOBAL &BUILDIDM') build_config_file.write('\n GLOBAL &CHIPSET') build_config_file.write('\n GLOBAL &BUILDROOT') build_config_file.write('\n GLOBAL &COREDIR') build_config_file.write('\n GLOBAL &PRODUCTSDIR') build_config_file.write('\n GLOBAL &BUILDMSDIR') build_config_file.write('\n GLOBAL &MBNDIR') build_config_file.write('\n GLOBAL &ELFFILE') build_config_file.write('\n GLOBAL &TIMESTAMP') build_config_file.write('\n // GLOBAL &BOOTLOADERFLAVOR') # Format it well build_config_file.write('\n \n') build_config_file.write('\n &MODEM_BUILDID='+buildid) build_config_file.write('\n &MODEM_BUILDIDM='+env.Dump('BUILD_ID').replace('\'','\"')) build_config_file.write('\n &CHIPSET=\"MSM'+chipset+'\"') build_config_file.write('\n &MODEM_BUILDMSDIR='+'os.ppd()+'+'\"/../../build/ms\"') build_config_file.write('\n &MODEM_MBNDIR=\"&BUILDMSDIR\"+'+'\"/bin/&BUILDID\"') build_config_file.write('\n &MODEM_ELFFILE=\"M'+elfname+'\"') build_config_file.write('\n &MODEM_TIMESTAMP=\"'+str(int(time.time()+0.5))+'\"') build_config_file.write('\n &BUILDID='+buildid) build_config_file.write('\n &BUILDIDM='+env.Dump('BUILD_ID').replace('\'','\"')) build_config_file.write('\n &CHIPSET=\"MSM'+chipset+'\"') build_config_file.write('\n &PRODUCTSDIR='+'os.ppd()') build_config_file.write('\n &BUILDROOT='+'os.ppd()+'+'\"/../..\"') build_config_file.write('\n &COREDIR='+'os.ppd()+'+'\"/..\"') build_config_file.write('\n &BUILDMSDIR='+'os.ppd()+'+'\"/../../build/ms\"') build_config_file.write('\n &MBNDIR=\"&BUILDMSDIR\"+'+'\"/bin/&BUILDID\"') build_config_file.write('\n &ELFFILE=\"M'+elfname+'\"') build_config_file.write('\n &TIMESTAMP=\"'+str(int(time.time()+0.5))+'\"') build_config_file.write('\n // &BOOTLOADERFLAVOR=\"'+ bootloaderflavor + '\"') # Now be a good sport and end the cmm file build_config_file.write('\n \n') build_config_file.write('ENDDO') build_config_file.close() def writebootconfigfile(): # Create the file from scratch every single time build_config_file = open(CMM_Build_Config,'w') # Throw in all the comments for the cmm file build_config_file.write('//\t Title: std_buildconfig') build_config_file.write('\n\n//\t License: License') build_config_file.write('\n//\t Copyright 2010 Qualcomm Inc ') build_config_file.write('\n\n//\t Description: General Description') build_config_file.write('\n//\t This script contains build information.') build_config_file.write('\n\n//\t Input: Inputs') build_config_file.write('\n//\t None') build_config_file.write('\n\n//\t Output: Outputs') build_config_file.write('\n//\t None') build_config_file.write('\n\n//\t Usage: Usage') build_config_file.write('\n//\t do std_buildconfig') build_config_file.write('\n\n//\t Team: Functional Area') build_config_file.write('\n//\t CoreBSP Products 8960') build_config_file.write('\n\n//\t Target: Target') build_config_file.write('\n//\t MSM8660') build_config_file.write('\n\n//\t Author: Author') build_config_file.write('\n//\t $Author: rvennam $') build_config_file.write('\n\n//\t Location: Perforce Revision') build_config_file.write('\n//\t $Header: //depot/asic/msm8960/temp_dev/AMSS/products/8660/build/ms/std_buildconfig $') build_config_file.write('\n\n//\t Edits: Edits') build_config_file.write('\n//\t Autogenerated on '+datetime.datetime.now().strftime("%A %d/%m/%Y %H:%M:%S")) build_config_file.write('\n// ---------------------------------------------------------------------------------') build_config_file.write('\n \n \n \n') # Declare your GLOBAL variables here build_config_file.write('\n GLOBAL &BOOT_BUILDID') build_config_file.write('\n GLOBAL &BOOT_BUILDIDM') build_config_file.write('\n GLOBAL &BOOT_MBNDIR') build_config_file.write('\n GLOBAL &BOOT_TIMESTAMP') # Format it well build_config_file.write('\n \n') build_config_file.write('\n &BOOT_BUILDID='+buildid) build_config_file.write('\n &BOOT_BUILDIDM='+env.Dump('BUILD_ID').replace('\'','\"')) build_config_file.write('\n &BOOT_MBNDIR=\"&BUILDMSDIR\"+'+'\"/bin/&BUILDID\"') build_config_file.write('\n &BOOT_TIMESTAMP=\"'+str(int(time.time()+0.5))+'\"') # Now be a good sport and end the cmm file build_config_file.write('\n \n') build_config_file.write('ENDDO') build_config_file.close() # Technically, the sconscript starts here Import('env') env = env.Clone() if env.has_key('QDSP6_PROC'): # CMM Source Path print "COREBSP Products SConscript \n" CMM_source = env.subst('$COREBSP_ROOT')+'/products' CMM_Build_Config = CMM_source + '/std_buildconfig.cmm' T32_Dialog = CMM_source + '/std_dialogauto.dlg' env.VariantDir('${BUILDPATH}',CMM_source, duplicate=0) # Do all the processing here. Write the file separately # Build ID has an M appended to indicate modem build buildidm = env.Dump('BUILD_ID').replace('\'','\"') # Remove the M buildid = buildidm.replace('M\"','\"') # Replace the quotes from the output of env.Dump chipset = str(env.Dump('MSM_ID')).replace('\'','') asicid = str(env.Dump('BUILD_ASIC')).replace('\'','') buildidstr = str(env.Dump('BUILD_ID')).replace('\'','') buildver = str(env.Dump('BUILD_VER')).replace('\'','') # ELF name combines the three together elfname=asicid + buildidstr + buildver # Bootloader flavor is hardcoded in the build, provided here bootloaderflavor = 'AAABQNBG' # Script is the list of scripts to be included in the dialog scripts = [] # Delcare the scripts here one after the other # Fields : Scriptname, Alternate Name (appears in the dialog), Location (with respect # to CORE directory or BUILD\MS directory, Team responsible for it, Number of arguments it # takes and the mapping of those arguments script1=CMMScript("ULogDump","ULOG Log","&COREDIR/power/ulog/scripts","Power", "1") script1.argmapping = { 1 : 'Log Path'} script2=CMMScript("NPADump","NPA Log","&COREDIR/power/npa/scripts","Power","1") script2.argmapping = { 1: 'Log Path'} script3=CMMScript("testclocks_8660","Test Clock ","&BUILDMSDIR","Systemdrivers","1") script3.argmapping = { 1: 'Clock Name'} # Add each one to the list scripts = [script1, script2, script3] # Set parameters for the Dialog box here window = T32Dialog() window.height = len(scripts)*5 window.width = (len(scripts) + 3) * 8 window.title = "Collect Logs" window.textheight = 1 window.textwidth = 5 window.editheight = 1 window.editwidth = 10 window.chooseboxwidth = 10 window.chooseboxheight = 2 #print scripts[0].argmapping[1] # Write the config file writemodemconfigfile() # Write the dialog file writedialogfile() if env.has_key('BUILD_BOOT_CHAIN'): CMM_source = env.subst('$COREBSP_ROOT')+'/products' CMM_Build_Config = CMM_source + '/std_buildconfig.cmm' env.VariantDir('${BUILDPATH}',CMM_source, duplicate=0) # Do all the processing here. Write the file separately # Build ID has an M appended to indicate modem build buildidm = env.Dump('BUILD_ID').replace('\'','\"') # Remove the M buildid = buildidm.replace('M\"','\"') # Write the boot config file writebootconfigfile()

UTF-8

Python

SConscript

murielsilveira/django13-agenda

f868aa8062846f61e49fe145162a911adc2fbe48

f31b053d591d5c8c536be873a8627773a0211579

/sistema/views.py

0a18c82de7a22088111de55d84259dc5920b171e

permissive

https://github.com/murielsilveira/django13-agenda

89ebec2eba67ef8886be6cfe38b9fcfa61157929

027a5b495cfab6a3fe832e86ac5cf4a90ee5b9fc

refs/heads/master

#!/usr/bin/python # -*- coding: utf-8 -*- from django.template import RequestContext from django.shortcuts import render_to_response, get_object_or_404, redirect def sistema(request): """ Define para onde o usuário será encaminhado """ #logado = True #if logado: #return redirect(login) return redirect(menu) def menu(request): """ Exibe o menu do sistema, a página principal """ return render_to_response('sistema/logado.html', context_instance=RequestContext(request)) def login(request): """ Exibe a tela de login do sistema """ return render_to_response('sistema/login.html', context_instance=RequestContext(request))

UTF-8

Python

py

views.py

cms-sw/cmssw

bf8127530a6fe2d0482867209de1ee81743afd79

a5a99f646e371b45974a6fb6ccc06b0a674818f2

/DPGAnalysis/HcalNanoAOD/python/hcalRecHitTable_cff.py

5478e4c8261c6310bc4c8aa2b1b175e15058581f

permissive

https://github.com/cms-sw/cmssw

4ecd2c1105d59c66d385551230542c6615b9ab58

19c178740257eb48367778593da55dcad08b7a4f

refs/heads/master

Apache-2.0

C++

import FWCore.ParameterSet.Config as cms from PhysicsTools.NanoAOD.common_cff import Var,P3Vars hbheRecHitTable = cms.EDProducer("HBHERecHitFlatTableProducer", src = cms.InputTag("hbhereco"), cut = cms.string(""), name = cms.string("RecHitHBHE"), doc = cms.string("HCAL barrel and endcap rec hits"), singleton = cms.bool(False), # the number of entries is variable extension = cms.bool(False), # this is the main table for the object variables = cms.PSet( detId = Var('detid().rawId()', 'int', precision=-1, doc='detId'), energy = Var('energy', 'float', precision=14, doc='energy'), time = Var('time', 'float', precision=14, doc='hit time'), ieta = Var('id().ieta()', 'int', precision=-1, doc='ieta'), iphi = Var('id().iphi()', 'int', precision=-1, doc='iphi'), depth = Var('id().depth()', 'int', precision=-1, doc='depth') ) ) hfRecHitTable = cms.EDProducer("HFRecHitFlatTableProducer", src = cms.InputTag("hfreco"), cut = cms.string(""), name = cms.string("RecHitHF"), doc = cms.string("HCAL forward (HF) rec hits"), singleton = cms.bool(False), # the number of entries is variable extension = cms.bool(False), # this is the main table for the object variables = cms.PSet( detId = Var('detid().rawId()', 'int', precision=-1, doc='detId'), energy = Var('energy', 'float', precision=14, doc='energy'), time = Var('time', 'float', precision=14, doc='hit time'), ieta = Var('id().ieta()', 'int', precision=-1, doc='ieta'), iphi = Var('id().iphi()', 'int', precision=-1, doc='iphi'), depth = Var('id().depth()', 'int', precision=-1, doc='depth') ) ) hoRecHitTable = cms.EDProducer("HORecHitFlatTableProducer", src = cms.InputTag("horeco"), cut = cms.string(""), name = cms.string("RecHitHO"), doc = cms.string("HCAL outer (HO) rec hits"), singleton = cms.bool(False), # the number of entries is variable extension = cms.bool(False), # this is the main table for the object variables = cms.PSet( detId = Var('detid().rawId()', 'int', precision=-1, doc='detId'), energy = Var('energy', 'float', precision=14, doc='energy'), time = Var('time', 'float', precision=14, doc='hit time'), ieta = Var('id().ieta()', 'int', precision=-1, doc='ieta'), iphi = Var('id().iphi()', 'int', precision=-1, doc='iphi'), depth = Var('id().depth()', 'int', precision=-1, doc='depth') ) ) hcalRecHitTableSeq = cms.Sequence( hbheRecHitTable + hfRecHitTable + hoRecHitTable ) hcalRecHitTableTask = cms.Task( hbheRecHitTable, hfRecHitTable, hoRecHitTable, )

UTF-8

Python

py

hcalRecHitTable_cff.py

vivekaxl/LexisNexis

a7902bfc34e0b39bc4dbfdfaeac37cd542356e69

1a2ca64839723ede3134a0781128b0dc0b5f6ab8

/ExtractFeatures/Data/rahul/deTuner.py

34024d1fd48909f828b44ce6c63365dde514dff0

no_license

https://github.com/vivekaxl/LexisNexis

bc8ee0b92ae95a200c41bd077082212243ee248c

5fa3a818c3d41bd9c3eb25122e1d376c8910269c

refs/heads/master

import sys, os sys.path.append(os.environ['HOME'] + '/git/axe/axe') sys.path.insert(0, os.getcwd() + '/_imports'); from demos import * import sk; # @UnresolvedImport from dectree import * from settings import * from settingsWhere import * from pdb import set_trace from abcd import _Abcd from Prediction import rforest, CART, Bugs from methods1 import createTbl from random import uniform as rand, randint as randi, choice as any tree = treeings() # set_trace() def say(l): sys.stdout.write(str(l)) def settings(**d): return o( name = "Differention Evolution", what = "DE tuner. Tune the predictor parameters parameters", author = "Rahul Krishna", adaptation = "https://github.com/ai-se/Rahul/blob/master/DEADANT/deadant.py", copyleft = "(c) 2014, MIT license, http://goo.gl/3UYBp", seed = 1, np = 10, k = 100, tiny = 0.01, de = o(np = 5, iter = 5, epsilon = 1.01, N = 20, f = 0.3, cf = 0.4, lives = 100) ).update(**d) The = settings() class diffEvol(object): """ Differential Evolution """ def __init__(self, model, data): self.frontier = [] self.model = model(data) def new(self): # Creates a new random instance return [randi(d[0], d[1]) for d in self.model.indep()] def initFront(self, N): # Initialize frontier for _ in xrange(N): self.frontier.append(self.new()) def extrapolate(self, l2, l3, l4): return [max(d[0], min(d[1], int(a + The.de.f * (b - c)))) for a, b, c, d in zip(l2, l3, l4, self.model.indep())] def one234(self, one, pop, f = lambda x:id(x)): def oneOther(): x = any(pop) while f(x) in seen: x = any(pop) seen.append(f(x)) return x seen = [ f(one) ] return oneOther(), oneOther(), oneOther() def dominates(self, one, two): # set_trace() return self.model.depen(one) > self.model.depen(two) def DE(self): self.initFront(The.de.N) lives = The.de.lives while lives > 0: better = False for pos, l1 in enumerate(self.frontier): lives -= 1 l2, l3, l4 = self.one234(l1, self.frontier) new = self.extrapolate(l2, l3, l4) if self.dominates(new, l1): self.frontier.pop(pos) self.frontier.insert(pos, new) better = True elif self.dominates(l1, new): better = False else: self.frontier.append(new) better = True if better: lives += 1 return self.frontier class tuneRF(object): # Tune RF def __init__(self, data): self.data = data self.train = createTbl(data[:-1]) self.test = createTbl([data[-1]]) # set_trace() def depen(self, rows): mod = rforest(self.train, self.test , tunings = rows # n_est, max_feat, mss, msl , smoteit = True) g = _Abcd(before = Bugs(self.test), after = mod, show = False)[-1] return g def indep(self): return [(10, 1e3) # n_estimators , (1, 100) # max_features , (1, 10) # min_samples_leaf , (2, 10) # min_samples_split ] class tuneCART(object): # Tune CART def __init__(self, data): self.data = data self.train = createTbl(data[:-1]) self.test = createTbl([data[-1]]) def depen(self, rows): mod = CART(self.train, self.test , tunings = rows , smoteit = True) g = _Abcd(before = Bugs(self.test), after = mod, show = False)[-1] return g def indep(self): return [(1, 50) # max_depth , (2, 20) # min_samples_split , (1, 20) # min_samples_leaf , (1, 100) # max features , (2, 1e3)] # max_leaf_nodes def _test(data): m = tuneRF(data) vals = [(m.any()) for _ in range(10)] vals1 = [m.score(v) for v in vals] print(vals, vals1) def _de(model, data): "DE" DE = diffEvol(model, data); # set_trace() res = sorted([k for k in DE.DE()], key = lambda F: F[-1])[-1] return res def tuner(model, data): if model == rforest: return _de(tuneRF, data) elif model == CART: return _de(tuneCART, data) if __name__ == '__main__': from timeit import time data = explore(dir = '../Data/')[0][-1] # Only training data to tune. for m in [tuneRF, tuneCART]: t = time.time() mdl = m(data) # _test(data) tunings = _de(m, data) print tunings print mdl.depen(tunings) print time.time() - t # print _de() # print main() # import sk; xtile = sk.xtile # print xtile(G) # main(dir = 'Data/')

UTF-8

Python

py

deTuner.py

mwesterhof/wapsandbox

953f2b3e58c784aa4d13e29263bcc27d08187cfb

b341d7630b19a8a65eefb985e102cffef6b64c09

/products/urls.py

64f80270e00aa50577b41ef85c3b211c4492b2d2

no_license

https://github.com/mwesterhof/wapsandbox

e8f05ecfcfe9cfe9435653fb2a337b2ce62edb0a

17e476de45527993fec4b61f92a62558864fe310

refs/heads/master

from django.urls import path from .views import OrderProduct, ProductList, ProductDetail urlpatterns = [ path('', ProductList.as_view(), name='product_list'), path('<int:pk>/', ProductDetail.as_view(), name='product_detail'), path('<int:pk>/order/', OrderProduct.as_view(), name='product_order') ]

UTF-8

Python

py

urls.py

kevinholst/politifact_tools

5bf64a107c94c8582a3b2b1cdd718744abce045a

06b08b237a34b80d8cfafe07b10c38aa8838983d

/politifact_score.py

07ef006da6b7ab82e2a98dcafed8451c2c5ad694

no_license

https://github.com/kevinholst/politifact_tools

a4c8a5ac727803c1490a59fd6e6c8ab1aa922a5c

0c442f47faadba71460b3ad8e96a0cec564c1105

refs/heads/master

from __future__ import division, print_function from bs4 import BeautifulSoup import requests import numpy as np BASE = 'http://www.politifact.com/personalities/' SCORING = np.array([2, 1, 0, -1, -2, -3]) def get_truthiness_score(name): page = requests.get(BASE + name) soup = BeautifulSoup(page.content) values = np.zeros(6, dtype='int') rulings = soup.find_all('span', {'class': 'chartlist__count'}) for i, ruling in enumerate(rulings): values[i] = int(ruling.contents[0].split()[0]) number_of_rulings = values.sum() values *= SCORING score = values.sum()/number_of_rulings return score

UTF-8

Python

py

politifact_score.py

romanitalian/online_school_bread_blog

65799ca15000a1965cce90985de352d1aff15a3f

f415e4adfaa3a3e243022744e34422b3315f7f37

/notes/01/dec/main_1.py

2bee488c99db1b49dfdf9eb1cad376792560cb8b

no_license

https://github.com/romanitalian/online_school_bread_blog

706d52a96a45ce40d983b9fe66523e7afd07455d

19590400fafd37d225761e309e709d5004da0fb2

refs/heads/main

from datetime import datetime def counter_decorator(func): cnt = 0 def wrapper(): nonlocal cnt cnt += 1 print(cnt) res = func() return res return wrapper @counter_decorator def foo(): print(datetime.now()) foo() foo() foo()

UTF-8

Python

py

main_1.py

javier123454321/complexity

724fd46bf9894c5db93bfdc42bf98f68c9e4aacb

3726d860eb6b1fe051126179084283b58bf5a121

/fractals1/fractals2.py

a75e00036a3a6278f80d277b4622712a61eb46ac

no_license

https://github.com/javier123454321/complexity

538304e6b25d6cd68dab6fead7a92de4d0c1a930

3b5fd2e54a845910bbd30eea90c58c4ffc5f7945

refs/heads/master

Python

import rhinoscriptsyntax as rs import ghpythonlib as ghp def fractalizeCurve(curve, numsteps, output_lines): numsteps -= 1 #Get endpoints from input curve curvePoints = rs.AddPoints(rs.CurvePoints(curve)) pt0 = curvePoints[0] pt1 = curvePoints[1] #rotate input curve by input angle and form a triangle new_pt = rs.RotateObject(pt1, pt0, angle, axis=None, copy=True) new_line1 = rs.AddCurve([pt0, new_pt]) new_line2 = rs.AddCurve([new_pt, pt1]) #Append all the new lines into an input list output_lines.append(new_line1) output_lines.append(new_line2) #iterate the function as many times as requested if numsteps > 0: fractalizeCurve(new_line1, (numsteps), output_lines) fractalizeCurve(new_line2, (numsteps), output_lines) else: return output_lines a = [] fractalizeCurve(inputCrv, recursion_steps, a)

UTF-8

Python

py

fractals2.py

ranjiayu/EntryFormGenerator

44d8899b8a7266397271a3b79cbcb96245fc83a6

c7e6c8f8d0f770e4f1b53617affaf52f56c8a097

/form/models.py

a1f3bddff5581d482d7db305272e0aa1e8c63c54

no_license

https://github.com/ranjiayu/EntryFormGenerator

94dca535ef2e6a8cc91ff0f266a1baedaa5ca327

3a38b51a1ced173be0753b7d374cbe75a5ea8531

refs/heads/master

from __future__ import unicode_literals from django.db import models # Create your models here. class Form(models.Model): title = models.CharField(max_length=70) author = models.CharField(max_length=70) password = models.CharField(max_length=70, default='') create_time = models.DateTimeField(auto_now_add=True) def __unicode__(self): return self.title class Meta: ordering = ['-create_time'] class Key(models.Model): form = models.ForeignKey('Form', null=True, on_delete=models.CASCADE) keyLabel = models.CharField(max_length=70, null=False, blank=False) keyType = models.CharField(max_length=10, null=False, blank=False) create_time = models.DateTimeField(auto_now_add=True) def __unicode__(self): return self.keyLabel class Meta: ordering = ['-create_time'] class KeyContent(models.Model): key = models.ForeignKey('Key', null=True, on_delete=models.CASCADE) content = models.TextField() create_time = models.DateTimeField(auto_now_add=True) def __unicode__(self): return self.content class Meta: ordering = ['-create_time']

UTF-8

Python

py

models.py

vaankiller/leetcode

12c913fb991222908b7316f58955be2613342214

1c74dee0cf5efcdcebb52455cb8a11de210a02ab

/py2/273. Integer to English Words.py

9fb4b1bec6048ade2cc86f1f630168d726979089

no_license

https://github.com/vaankiller/leetcode

f8072abad23ee41bda2a80d1a536120f11ada50f

88b434bd493e6cb2f70267b40a87c2d881d89cb0

refs/heads/master

__author__ = 'vaan' unit = ["Zero ", "One ", "Two ", "Three ", "Four ", "Five ", "Six ", "Seven ", "Eight ", "Nine "]; decade = ["Zero", "Ten", "Twenty ", "Thirty ", "Forty ", "Fifty ", "Sixty ", "Seventy ", "Eighty ", "Ninety "] tenth = ["Ten ", "Eleven ", "Twelve ", "Thirteen ", "Fourteen ", "Fifteen ", "Sixteen ", "Seventeen ", "Eighteen ", "Nineteen "] hundred = "Hundred " thousand = "Thousand " million = "Million " billion = "Billion " dct = {} dct["unit"] = unit dct["decade"] = decade dct["tenth"] = tenth dct[hundred] = 100 dct[thousand] = 1000 dct[million] = 1000000 dct[billion] = 1000000000 class Solution(object): def numberToWords(self, num): """ :type num: int :rtype: str """ ret = self.pre(num) return ret[0:-1] def pre(self, num): ret = "" if num is None: return ret if num >= dct[billion]: ret += self.pre(num/dct[billion]) + billion + (self.pre(num % dct[billion]) if num % dct[billion] else "") elif num >= dct[million]: ret += self.pre(num/dct[million]) + million + (self.pre(num % dct[million]) if num % dct[million] else "") elif num >= dct[thousand]: ret += self.pre(num/dct[thousand]) + thousand + (self.pre(num % dct[thousand]) if num % dct[thousand] else "") elif num >= dct[hundred]: ret += self.pre(num/dct[hundred]) + hundred + (self.pre(num % dct[hundred]) if num % dct[hundred] else "") elif num >= 20: ret += dct["decade"][num/10] + (self.pre(num % 10) if num % 10 else "") elif num >= 10: ret += tenth[num % 10] else: ret += dct["unit"][num] return ret s = Solution() print s.numberToWords(2147891236) print s.pre(2147891236)

UTF-8

Python

py

273. Integer to English Words.py

PouceHeure/py_light_mas

c32bb52e4cfaaa5ff50d038970f044e67af6c230

61fa9ae05e3fc5d926a56814743fd4dee8c08acd

/lib/py_light_mas/environnemnt.py

a43b431089fb18d0df6eeded6a532701d0bf21c6

no_license

https://github.com/PouceHeure/py_light_mas

ee2b99a5b671df8db6e6cf60112754d2223e8a10

05b01d9e9d0584fca02dd4f45f5eceaae3eeb606

refs/heads/master

class Environnemnt: """abstract class """ def on_event_new_tick(self): """method trigged when the simulation passed a new tick """ def on_event_show(self): """method trigged when the simulation ask to show the current state of the env """ def event_new_tick(self): self.on_event_new_tick() def event_show(self): self.on_event_show()

UTF-8

Python

py

environnemnt.py

clademorin/Email-Address-Extractor

d6ed6dd74712c53e0502a1e0847186f2b272f74b

85d56946b1bc672492b3b3f4782be37751c2d03d

/Email-Address-Extractor.py

bf33898d27b21ec582dc5735f4871d71d5ce89a2

no_license

https://github.com/clademorin/Email-Address-Extractor

e1dedcf37239e7f4dca3155731a307f087b2dda7

ad405d2fcc92273bbc3c2fa45f7664c5eaa9b834

refs/heads/master

from tkinter import END, Frame, Tk, Button, Label, Text import pyperclip import re def creaelenco(): indirizzi = '' test = text_input.get("1.0", END).strip() elenco = re.findall("([\S]*@[\S]*\.[\w]*)", test) for i in elenco: indirizzi += i.replace('\n', '').replace('<', '')+';' indirizzi = indirizzi[:-1] text_output.delete("1.0", END) text_output.insert("1.0", indirizzi) interfaccia = Tk() interfaccia.geometry("600x600") interfaccia.title("Email Address Extractor") testo = Frame(interfaccia, bd=3, relief="ridge", padx=15, pady=15) testo.pack() lb_input = Label(testo, text="Input:") lb_input.pack() text_input = Text(testo, bg="white", fg="black", padx=20, pady=20, height=9) text_input.pack() bt_input = Button(testo, text="Extract", command=creaelenco) bt_input.pack(pady=10) output = Frame(interfaccia, bd=3, relief="ridge", padx=15, pady=15) output.pack() lb_output = Label(output, text="Output:") lb_output.pack() text_output = Text(output, bg="white", fg="black", padx=20, pady=20, height=9) text_output.pack() bt_copy = Button(output, text="Copy to clipboard", command=lambda: pyperclip.copy(text_output.get('1.0', END))) bt_copy.pack(pady=10) interfaccia.mainloop()

UTF-8

Python

py

Email-Address-Extractor.py

jaydeep1412/Catalent

968c32f0ce7c52d73ffb956b7dd1448fece38cbd

e4ca0195b9f29f2622ab29f56ca380cc73d25f94

/myapp/migrations/0004_auto_20201104_1510.py

33f49e164f0d5af55075ed0514836e4283a20661

no_license

https://github.com/jaydeep1412/Catalent

e09838ec5f4cf90097985932a9814f4c23e08dfa

b79eae3e41de3e9bec3fb39ab6664b53d7cc1b49

refs/heads/master

# Generated by Django 3.1.2 on 2020-11-04 20:10 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('myapp', '0003_auto_20201104_1441'), ] operations = [ migrations.AlterField( model_name='analysis', name='CorrelationOfStandards', field=models.FloatField(blank=True, null=True), ), migrations.AlterField( model_name='analysis', name='peakTailing', field=models.FloatField(blank=True, null=True), ), migrations.AlterField( model_name='analysis', name='resolution', field=models.FloatField(blank=True, null=True), ), ]

UTF-8

Python

py

0004_auto_20201104_1510.py

thomas-mckay/test-pycoins

796e5b3167785e90fdf5432cce0d69f1f81e3927

607b04038659b4028b0818ba41dc5ba96db6ad94

/tests/views/test_account.py

c5b5bf8fdbad670e27bd82e39f2baf9f8f8dcc25

no_license

https://github.com/thomas-mckay/test-pycoins

bf6a812bb270e89a42ab2ba7e23eaf61ffe4a330

6ddca95e7bfa5f6352f3af17549aeed7c817c2e6

refs/heads/master

from django.conf import settings from django.http import HttpResponse from django.urls import reverse from mock import mock from ..utils import PyCoinsTestCase class AccountViewsTestCase(PyCoinsTestCase): def test_user_detail_view__no_auth(self): url = reverse('user-details') response = self.client.get(url) self.assertRedirects(response, '{}?next={}'.format(settings.LOGIN_URL, url), status_code=302, target_status_code=200, fetch_redirect_response=True) def test_user_detail_view__auth_ok(self): self.login_as_user(self.client) response = self.client.get(reverse('user-details')) self.assertEqual(response.status_code, 200) def test_user_home_view(self): response = self.client.get(reverse('home')) self.assertEqual(response.status_code, 200) def test_user_api_docs_view(self): response = self.client.get(reverse('api_docs')) self.assertEqual(response.status_code, 200) def test_user_signup_view(self): response = self.client.get(reverse('signup')) self.assertEqual(response.status_code, 200) def test_user_login_view(self): response = self.client.get(reverse('login')) self.assertEqual(response.status_code, 200) def test_user_password_reset_view(self): response = self.client.get(reverse('password-reset')) self.assertEqual(response.status_code, 200) def test_user_password_reset_confirm_view(self): response = self.client.get(reverse('password_reset_confirm', kwargs=dict(uidb64='foo', token='ba-bar'))) self.assertEqual(response.status_code, 200) def test_user_account_confirm_email_view(self): with mock.patch('pycoins.views.account.VerifyEmailView.post') as mock_post: mock_post.return_value = HttpResponse(status=200) response = self.client.get(reverse('account_confirm_email', kwargs=dict(key='foo'))) self.assertRedirects(response, '{}?info=Your+email+has+been+confirmed.'.format(reverse('home')), status_code=302, target_status_code=200, fetch_redirect_response=True) self.assertEqual(mock_post.call_count, 1)

UTF-8

Python

py

test_account.py

YikeZhou/csp-solution

88f0cf0882fa4067d660fa2e6eb8f8e67dcf89d7

aaf19a505caaf6b6fe379ddcecffd4b26e8ec3cb

/201712/3.py

0710d6f5ac278556739f5829c3006ba0c441c78c

no_license

https://github.com/YikeZhou/csp-solution

cb8a07b925ab6bb50bd0637ebc151d83b31fb7d2

9b7fe8be09863c87a54830e5a22a356ba9c7143e

refs/heads/master

''' File: 3.py Project: 201712 File Created: Sunday, 6th September 2020 10:10:23 am Author: zyk ----- Last Modified: Sunday, 6th September 2020 4:49:46 pm Modified By: zyk ----- 2020 - HUST ''' from datetime import datetime, timedelta class Time: def __init__(self, year, month, day, hour, minute): self.dt = datetime(year, month, day, hour, minute) @classmethod def parse(cls, num): return cls(int(num / 100000000), int((num % 100000000) / 1000000), int((num % 1000000) / 10000), int((num % 10000) / 100), int(num % 100)) def __repr__(self): return 'Time({0.dt.year!r}, {0.dt.month!r}, {0.dt.day!r}, {0.dt.hour!r}, {0.dt.minute!r})'.format(self) def __str__(self): return '{0.dt.year!r}'.format(self).zfill(4) + '{0.dt.month!r}'.format(self).zfill(2) + '{0.dt.day!r}'.format(self).zfill(2) + '{0.dt.hour!r}'.format(self).zfill(2) + '{0.dt.minute!r}'.format(self).zfill(2) def inc(self): one_min = timedelta(minutes=1) self.dt += one_min Weekdays = {'sun': 0, 'mon': 1, 'tue': 2, 'wed': 3, 'thu': 4, 'fri': 5, 'sat': 6} Months = {'jan': 1, 'feb': 2, 'mar': 3, 'apr': 4, 'may': 5, 'jun': 6, 'jul': 7, 'aug': 8, 'sep': 9, 'oct': 10, 'nov': 11, 'dec': 12} def get_month(s): if s.lower() in Months.keys(): return Months[s.lower()] else: return int(s) def get_weekday(s): if s.lower() in Weekdays.keys(): return Weekdays[s.lower()] else: return int(s) class Task: def __init__(self, minutes, hours, day_of_month, month, day_of_week, command): # save command str and interval self.command = command self.minutes = list() if minutes == '*': self.minutes.append((0, 59)) else: ms = minutes.split(sep=',') for m in ms: if '-' in m: a, b = map(int, m.split(sep='-')) self.minutes.append((a, b)) else: a = int(m) self.minutes.append((a, a)) self.hours = list() if hours == '*': self.hours.append((0, 23)) else: hs = hours.split(sep=',') for h in hs: if '-' in h: a, b = map(int, h.split(sep='-')) self.hours.append((a, b)) else: a = int(h) self.hours.append((a, a)) self.day_of_month = list() if day_of_month == '*': self.day_of_month.append((1, 31)) else: doms = day_of_month.split(sep=',') for dom in doms: if '-' in dom: a, b = map(int, dom.split(sep='-')) self.day_of_month.append((a, b)) else: a = int(dom) self.day_of_month.append((a, a)) self.month = list() if month == '*': self.month.append((1, 12)) else: mos = month.split(sep=',') for mo in mos: if '-' in mo: a, b = map(get_month, mo.split(sep='-')) self.month.append((a, b)) else: a = get_month(mo) self.month.append((a, a)) self.day_of_week = list() if day_of_week == '*': self.day_of_week.append((0, 6)) else: dows = day_of_week.split(sep=',') for dow in dows: if '-' in dow: a, b = map(get_weekday, dow.split(sep='-')) self.day_of_week.append((a, b)) else: a = get_weekday(dow) self.day_of_week.append((a, a)) def match(self, t: Time): # month for (b, e) in self.month: if b <= t.dt.month and t.dt.month <= e: break else: return False # day of month for (b, e) in self.day_of_month: if b <= t.dt.day and t.dt.day <= e: break else: return False # hour for (b, e) in self.hours: if b <= t.dt.hour and t.dt.hour <= e: break else: return False # minute for (b, e) in self.minutes: if b <= t.dt.minute and t.dt.minute <= e: break else: return False # day of week for (b, e) in self.day_of_week: dow = (t.dt.weekday() + 1) % 7 if b <= dow and dow <= e: break else: return False return True n, s, t = map(int, input().split()) confs = list() # read n lines for i in range(n): # crontab config info minutes, hours, day_of_month, month, day_of_week, command = input().split() # process each field confs.append(Task(minutes, hours, day_of_month, month, day_of_week, command)) start = Time.parse(s) end = Time.parse(t) cur = start while cur.dt != end.dt: for conf in confs: if conf.match(cur): print(cur, conf.command) cur.inc()

UTF-8

Python

py

3.py

a-luna/vigorish

e51a384cb382be35e775bbf7f019f4340e79bf34

b7500e25551e14fd71694bf7a240eb7c95e38f20

/src/vigorish/tasks/sync_data_no_prompts.py

153192904826f3837c75dcf15e5f46b58e87d036

permissive

https://github.com/a-luna/vigorish

5f05af1d44745af91a82f84886dd81f8a2cf7489

84bd02311b35e2789d741d8cb10a3e4e584f0255

refs/heads/master

MIT

Python

"""Menu item that returns the user to the previous menu.""" import subprocess from halo import Halo from vigorish.cli.components import ( get_random_cli_color, get_random_dots_spinner, print_heading, print_message, ) from vigorish.enums import DataSet, SyncDirection, VigFile from vigorish.tasks.base import Task from vigorish.tasks.sync_scraped_data import SyncScrapedDataTask from vigorish.util.result import Result SYNC_STATUS_TEXT_COLOR = { "out_of_sync": "bright_green", "in_sync": "blue", "sync_complete": "bright_green", "error": "bright_red", } class SyncDataNoPromptsTask(Task): def __init__(self, app): super().__init__(app) self.s3_sync = SyncScrapedDataTask(self.app) self.sync_direction = None self.year = None self.file_type = None self.data_sets_int = 0 self.data_set = None self.task_number = 0 self.sync_files = {} self.sync_results = [] self.spinners = {} self.results = {} @property def data_sets(self): if self.file_type == VigFile.COMBINED_GAME_DATA: return [DataSet.ALL] return sorted(ds for ds in DataSet if ds in self.valid_data_sets() and self.data_sets_int & ds == ds) @property def total_tasks(self): return len(self.data_sets) @property def all_files_are_in_sync(self): return all(not out_of_sync for (out_of_sync, _, _) in self.sync_files.values()) def execute(self, sync_direction, year, file_type, data_sets_int): self.sync_direction = sync_direction self.year = year self.file_type = file_type self.data_sets_int = data_sets_int self.subscribe_to_events() for data_set in self.data_sets: self.task_number += 1 self.data_set = data_set self.report_sync_results() self.results[data_set] = self.s3_sync.execute(sync_direction, file_type, data_set, year) if self.results[data_set].failure: return self.results self.spinners[data_set].stop() self.report_sync_results() self.unsubscribe_from_events() return self.results def valid_data_sets(self): data_set_file_type_map = { VigFile.SCRAPED_HTML: list(DataSet), VigFile.PARSED_JSON: list(DataSet), VigFile.COMBINED_GAME_DATA: [DataSet.ALL], VigFile.PATCH_LIST: [ DataSet.BBREF_GAMES_FOR_DATE, DataSet.BBREF_BOXSCORES, DataSet.BROOKS_GAMES_FOR_DATE, DataSet.BROOKS_PITCHFX, ], } return data_set_file_type_map[self.file_type] def report_sync_results(self): subprocess.run(["clear"]) self.print_header_message() if not self.sync_results: return for task_result in self.sync_results: print_message(task_result[0], wrap=False, fg=task_result[1]) def print_header_message(self): src_folder = "S3 bucket" if self.sync_direction == SyncDirection.DOWN_TO_LOCAL else "local folder" dest_folder = "local folder" if self.sync_direction == SyncDirection.DOWN_TO_LOCAL else "S3 bucket" heading = f"Syncing data from {src_folder} to {dest_folder}" print_heading(heading, fg="bright_yellow") def error_occurred(self, error_message): self.sync_results.append((error_message, SYNC_STATUS_TEXT_COLOR["error"])) self.results[self.data_set] = Result.Fail(error_message) def get_s3_objects_start(self): subprocess.run(["clear"]) self.spinners["default"] = Halo( spinner=get_random_dots_spinner(), color=get_random_cli_color(), text="Retrieving data for all objects stored in S3...", ) self.spinners["default"].start() def get_s3_objects_complete(self): self.spinners["default"].stop() def find_out_of_sync_files_start(self): self.spinners[self.data_set] = Halo( spinner=get_random_dots_spinner(), color=get_random_cli_color(), text=( f"Analyzing MLB {self.year} {self.file_type} {self.data_set} files " f"(Task {self.task_number}/{self.total_tasks})..." ), ) self.spinners[self.data_set].start() def find_out_of_sync_files_complete(self, sync_results): (out_of_sync, new_files, update_files) = sync_results self.sync_files[self.data_set] = (out_of_sync, new_files, update_files) sync_files = self.sync_files_text(out_of_sync, new_files, update_files) text_color = SYNC_STATUS_TEXT_COLOR["out_of_sync"] if out_of_sync else SYNC_STATUS_TEXT_COLOR["in_sync"] self.sync_results.append((sync_files, text_color)) def sync_files_text(self, out_of_sync, new_files, update_files): sync_count = len(new_files) + len(update_files) sync_files = f"{sync_count} files out of sync" if out_of_sync else "All files in sync" return ( f"[{self.year} {self.file_type} {self.data_set}] {sync_files} (Task {self.task_number}/{self.total_tasks})" ) def sync_files_start(self, name, complete, total): self.report_sync_results() self.sync_files_progress(name, complete, total) def sync_files_progress(self, name, complete, total): direction = "Down" if self.sync_direction == SyncDirection.DOWN_TO_LOCAL else "Up" percent = complete / float(total) progress_message = f"{direction}loading: {name} | {percent:.0%} ({complete}/{total} Files)" self.spinners[self.data_set].text = progress_message def sync_files_complete(self): dest_folder = "local folder" if self.sync_direction == SyncDirection.DOWN_TO_LOCAL else "s3 bucket" src_folder = "s3 bucket" if self.sync_direction == SyncDirection.DOWN_TO_LOCAL else "local folder" sync_complete = f"[{self.year} {self.file_type} {self.data_set}] {dest_folder} is in sync with {src_folder}!" self.sync_results.append((sync_complete, SYNC_STATUS_TEXT_COLOR["sync_complete"])) def subscribe_to_events(self): self.s3_sync.events.error_occurred += self.error_occurred self.s3_sync.events.get_s3_objects_start += self.get_s3_objects_start self.s3_sync.events.get_s3_objects_complete += self.get_s3_objects_complete self.s3_sync.events.find_out_of_sync_files_start += self.find_out_of_sync_files_start self.s3_sync.events.find_out_of_sync_files_complete += self.find_out_of_sync_files_complete self.s3_sync.events.sync_files_start += self.sync_files_start self.s3_sync.events.sync_files_progress += self.sync_files_progress self.s3_sync.events.sync_files_complete += self.sync_files_complete def unsubscribe_from_events(self): self.s3_sync.events.error_occurred -= self.error_occurred self.s3_sync.events.get_s3_objects_start -= self.get_s3_objects_start self.s3_sync.events.get_s3_objects_complete -= self.get_s3_objects_complete self.s3_sync.events.find_out_of_sync_files_start -= self.find_out_of_sync_files_start self.s3_sync.events.find_out_of_sync_files_complete -= self.find_out_of_sync_files_complete self.s3_sync.events.sync_files_start -= self.sync_files_start self.s3_sync.events.sync_files_progress -= self.sync_files_progress self.s3_sync.events.sync_files_complete -= self.sync_files_complete

UTF-8

Python

py

sync_data_no_prompts.py

matiasz8/tasty-broccoli

97483978c2a7a45ac43b4cd388cc438f1c98a974

da2437008a3c386413ab10e093253104f01f162e

/lattuga/views.py

4d2abda2cb9456523be4628fc00b81dfeddcc51d

no_license

https://github.com/matiasz8/tasty-broccoli

57a9b3e33e70cf866f752ffcc75b63a4c5f80654

c5ff0f3ee20e5833ac09640d77d02dcc0decc51f

refs/heads/main

from django.shortcuts import render from django.shortcuts import HttpResponse def index(request): return HttpResponse(f"<html><p>Response Tasty OK</p></html>", status=201)

UTF-8

Python

py

views.py

JesusRivera98/reportes-neurociencias

df66811fbafaf5fdce1327bf97e3b81ab00081cf

dc9275f75d3855d591bfed41ee5a82f50fd320b1

/src/main/python/controladores/LNSController.py

459646acfb888c4489ae0be79f070ad57cfe576d

no_license

https://github.com/JesusRivera98/reportes-neurociencias

477a3fbc8d0ac40f289b5f70bee6f193d509243f

da39a4135e6715bab68c87a4efeefc45f11a7297

refs/heads/master

#Controlador de la vista de LNSWindowWidget from PyQt5 import QtWidgets, QtCore from vistas.LNSWindowWidget import * from MainWindowController import * from ReporteModel import * from pruebas.LNSPrueba import * from PruebaModel import * from ControllerModel import * class LNSController(QtWidgets.QWidget, ControllerModel): #Atributo empleado para realizar el cambio de vista switch_window = QtCore.pyqtSignal(object, object) def __init__(self, mainWindow, reporteModel=None): QtWidgets.QWidget.__init__(self) self.lnsView = LNSWindowWidget(mainWindow) self.lnsView.pbStart.clicked.connect(self.getDatos) self.reporteModel = reporteModel self.invalidArgs = list() def changeView(self): """ Método encargado de notificar los elementos que serán pasados como parámetros a la siguiente vista """ self.switch_window.emit(self.invalidArgs, self.lnsPrueba) def getDatos(self): """ Método que toma los datos ingresados en la vista de LNS """ view = self.lnsView span = view.sbSpan.value() total = view.sbTotal.value() valores = (span, total) self.lnsPrueba = LNSPrueba(valores) #toma anos de escolaridad del paciente datos = self.reporteModel.reporte['educacion'] self.lnsPrueba.calcularPERP(datos) self.changeView() def emptyInvalidArgs(self): """ Método que se encarga de vacíar la lista de elementos inválidos en la vista """ self.invalidArgs = list() def addInvalidArg(self, arg): """ Método que se encarga de añadir a la lista de elementos inválidos, aquel parámetro especificado Args: arg: String a añadir a la lista de elementos inválidos """ if len(self.invalidArgs) == 0: self.invalidArgs = [arg] else: tempList = self.invalidArgs tempList.append(arg) self.invalidArgs = tempList def getListMenu(self): """ Método que se regresa el id del menu en la vista de LNS """ return self.lnsView.lWVistas def getProgressBar(self): """ Método que se encarga de regresar el valor de la barra de progreso """ return self.lnsView.progressBar def getProgressBar(self): """ Método que se encarga de regresar el valor de la barra de progreso """ return self.lnsView.progressBar def updateButtonText(self, text): """ Método que se encarga de actulaizar el texto del botón de la vista """ self.lnsView.pbStart.setText(text) # Pruebas unitarias #if __name__ == "__main__": # import sys # app = QtWidgets.QApplication(sys.argv) # fluidezWindow = QtWidgets.QWidget() # fluidezVerbalController = LNSController(fluidezWindow) # fluidezWindow.show() # sys.exit(app.exec_())

UTF-8

Python

py

LNSController.py

Envinorma/back-office

2ab2fda878fb34adc9c28af78b1af977ecef05cc

1c8d46b8cb7b680cf809158be9c652e00126592c

/back_office/pages/edit_parameter_element/form_handling.py

f290e5b8f88fd054c73c6119519612b64deba0f4

permissive

https://github.com/Envinorma/back-office

c060b8a3da659ec2b539f00bb711ce5a460bcabf

2d2c082d40b8c3cb58d2bc0295801baf16cb983d

refs/heads/main

MIT

Python

import json import traceback from dataclasses import dataclass from typing import Dict, List, Optional from envinorma.models import ArreteMinisteriel, StructuredText from envinorma.models.condition import load_condition from envinorma.models.text_elements import EnrichedString, Table from envinorma.parametrization import AlternativeSection, AMWarning, Condition, InapplicableSection, ParameterElement from back_office.helpers.parse_table import parse_table from back_office.pages.edit_parameter_element.target_sections_form import TargetSectionFormValues from back_office.utils import DATA_FETCHER, AMOperation, ensure_not_none class FormHandlingError(Exception): pass def _build_condition(condition: Optional[str]) -> Condition: if not condition: raise FormHandlingError('La condition doit être définie.') try: return load_condition(json.loads(condition)) except Exception: raise FormHandlingError( f'Erreur inattendue dans la condition :\n{condition}\n' f'Erreur complète :\n{traceback.format_exc()}' ) @dataclass class _Modification: section_id: str target_alineas: Optional[List[int]] new_text: Optional[StructuredText] propagate_in_subsection: Optional[bool] def _parse_table(element: str) -> EnrichedString: try: result = parse_table(element) except ValueError as exc: raise FormHandlingError(str(exc)) if isinstance(result, Table): return EnrichedString('', table=result) if isinstance(result, str): return EnrichedString(result) raise ValueError(f'Impossible de parser {element}') def _extract_alineas(text: str) -> List[EnrichedString]: return [_parse_table(line) for line in text.split('\n')] _MIN_NB_CHARS = 1 def _check_and_build_new_text(title: str, content: str) -> StructuredText: if len(title or '') < _MIN_NB_CHARS: raise FormHandlingError(f'Le champ "Titre" doit contenir au moins {_MIN_NB_CHARS} caractères.') if len(content or '') < _MIN_NB_CHARS: raise FormHandlingError(f'Le champ "Contenu du paragraphe" doit contenir au moins {_MIN_NB_CHARS} caractères.') return StructuredText(EnrichedString(title), _extract_alineas(content), [], None) def _build_new_text(new_text_title: Optional[str], new_text_content: Optional[str]) -> Optional[StructuredText]: if not new_text_title and not new_text_content: return None if new_text_title and not new_text_content: raise FormHandlingError('Le champ "Contenu du paragraphe" doit être défini.') if new_text_content and not new_text_title: raise FormHandlingError('Le champ "Titre" doit être défini.') return _check_and_build_new_text(new_text_title or '', new_text_content or '') def _simplify_alineas(section: StructuredText, target_alineas: Optional[List[int]]) -> Optional[List[int]]: if not target_alineas: return None if len(set(target_alineas)) == len(section.outer_alineas): return None return target_alineas def _build_target_version( section_id_to_section: Dict[str, StructuredText], new_text_title: Optional[str], new_text_content: Optional[str], section_id: str, target_alineas: Optional[List[int]], propagate_in_subsection: Optional[bool], ) -> _Modification: if not section_id: raise FormHandlingError('La section visée doit être sélectionnée.') if section_id not in section_id_to_section: raise FormHandlingError(f'La section "{section_id}" n\'existe pas.') section = section_id_to_section[section_id] simplified_target_alineas = _simplify_alineas(section, target_alineas) new_text = _build_new_text(new_text_title, new_text_content) return _Modification(section_id, simplified_target_alineas, new_text, propagate_in_subsection) def _build_target_versions(am: ArreteMinisteriel, form_values: TargetSectionFormValues) -> List[_Modification]: new_texts_titles = form_values.new_texts_titles or len(form_values.target_sections) * [None] new_texts_contents = form_values.new_texts_contents or len(form_values.target_sections) * [None] target_sections = form_values.target_sections target_alineas = form_values.target_alineas or len(form_values.target_sections) * [None] propagate_in_subsection = form_values.propagate_in_subsection or len(form_values.target_sections) * [None] section_id_to_section = {section.id: section for section in am.descendent_sections()} return [ _build_target_version(section_id_to_section, title, content, section, alineas, propagate_in_subsection) for title, content, section, alineas, propagate_in_subsection in zip( new_texts_titles, new_texts_contents, target_sections, target_alineas, propagate_in_subsection ) ] def _build_inapplicable_section(condition: Condition, modification: _Modification) -> InapplicableSection: return InapplicableSection( modification.section_id, modification.target_alineas, condition=condition, subsections_are_inapplicable=modification.propagate_in_subsection if modification.propagate_in_subsection is not None else True, ) def _build_am_warning(section_id: str, warning_content: str) -> AMWarning: min_len = 10 if len(warning_content or '') <= min_len: raise FormHandlingError(f'Le champ "Contenu de l\'avertissement" doit contenir au moins {min_len} caractères.') return AMWarning(section_id, warning_content) def _build_parameter_object( operation: AMOperation, condition: Optional[Condition], modification: _Modification, warning_content: str, ) -> ParameterElement: if operation == AMOperation.ADD_ALTERNATIVE_SECTION: return AlternativeSection( section_id=modification.section_id, new_text=ensure_not_none(modification.new_text), condition=ensure_not_none(condition), ) if operation == AMOperation.ADD_CONDITION: return _build_inapplicable_section(ensure_not_none(condition), modification) if operation == AMOperation.ADD_WARNING: return _build_am_warning(modification.section_id, warning_content) raise NotImplementedError(f'Not implemented for operation {operation}') def _extract_new_parameter_objects( operation: AMOperation, am: ArreteMinisteriel, target_section_form_values: TargetSectionFormValues, condition_str: Optional[str], warning_content: str, ) -> List[ParameterElement]: condition = _build_condition(condition_str) if operation != AMOperation.ADD_WARNING else None target_versions = _build_target_versions(am, target_section_form_values) return [ _build_parameter_object(operation, condition, target_version, warning_content) for target_version in target_versions ] def _check_consistency(operation: AMOperation, parameters: List[ParameterElement]) -> None: for parameter in parameters: if operation == AMOperation.ADD_CONDITION: assert isinstance(parameter, InapplicableSection), f'Expect InapplicableSection, got {type(parameter)}' elif operation == AMOperation.ADD_ALTERNATIVE_SECTION: assert isinstance(parameter, AlternativeSection), f'Expect AlternativeSection, got {type(parameter)}' elif operation == AMOperation.ADD_WARNING: assert isinstance(parameter, AMWarning), f'Expect AMWarning, got {type(parameter)}' else: raise ValueError(f'Unexpected operation {operation}') def extract_and_upsert_new_parameter( operation: AMOperation, am_id: str, parameter_id: Optional[str], target_section_form_values: TargetSectionFormValues, condition: Optional[str], warning_content: str, ) -> None: am = DATA_FETCHER.load_am(am_id) if not am: raise ValueError(f'AM with id {am_id} not found!') new_parameters = _extract_new_parameter_objects( operation, am, target_section_form_values, condition, warning_content ) _check_consistency(operation, new_parameters) _upsert_parameters(am_id, new_parameters, parameter_id) def _upsert_parameters(am_id: str, new_parameters: List[ParameterElement], parameter_id: Optional[str]): if parameter_id is not None: if len(new_parameters) != 1: raise ValueError('Must have only one parameter when updating a specific parameter..') DATA_FETCHER.upsert_parameter(am_id, new_parameters[0], parameter_id) else: for parameter in new_parameters: DATA_FETCHER.upsert_parameter(am_id, parameter, None)

UTF-8

Python

py

form_handling.py

RavinduAye/pythonProject

988a34f26a4857c18b4ed92bad6dd01e7317c00c

c0cf536e04147bff8daf35cf47f7bec245e11951

/venv/Lib/site-packages/detecting/utils/misc.py

ec6efdbd4291d03c5c47fa09e8118b278571ba83

no_license

https://github.com/RavinduAye/pythonProject

8f29c5bedc1f23a4901db2abbaa0e439de526d2a

ff1ecb407f33697b02f2f2061912841e168fd33f

refs/heads/master

import tensorflow as tf # 用于删除数值都为0的候选框 def trim_zeros(boxes, name=None): '''Often boxes are represented with matrices of shape [N, 4] and are padded with zeros. This removes zero boxes. Args --- boxes: [N, 4] matrix of boxes. non_zeros: [N] a 1D boolean mask identifying the rows to keep ''' # 对候选框数值求和 non_zeros = tf.cast(tf.reduce_sum(tf.abs(boxes), axis=1), tf.bool) # 只留下数值不为0的候选框 boxes = tf.boolean_mask(boxes, non_zeros, name=name) # 返回数值不为0的候选框 return boxes, non_zeros # 图片元数据解析 def parse_image_meta(meta): '''Parses a tensor that contains image attributes to its components. Args --- meta: [..., 12] Returns --- a dict of the parsed tensors. ''' meta = meta.numpy() # 原始图片shape ori_shape = meta[..., 0:3] # resize后图片shape img_shape = meta[..., 3:6] # 填充后图片shape pad_shape = meta[..., 6:9] # 图片缩放因子 scale = meta[..., 9:11] # 图片是否翻转 flip = meta[..., 11] return { 'ori_shape': ori_shape, 'img_shape': img_shape, 'pad_shape': pad_shape, 'scale': scale, 'flip': flip } # 计算一个批次中填充后的图片的最大高度和宽度 def calc_batch_padded_shape(meta): ''' Args --- meta: [batch_size, 12] Returns --- nd.ndarray. Tuple of (height, width) ''' # meta[:, 6:8]填充后的图片shape # tf.reduce_max计算最大值 return tf.cast(tf.reduce_max(meta[:, 6:8], axis=0), tf.int32).numpy() # 得到resize后的图片shape def calc_img_shapes(meta): ''' Args --- meta: [..., 12] Returns --- nd.ndarray. [..., (height, width)] ''' # meta[:, 3:5]resize后的图片shape return tf.cast(meta[..., 3:5], tf.int32).numpy() # 得到填充后的图片shape def calc_pad_shapes(meta): ''' Args --- meta: [..., 12] Returns --- nd.ndarray. [..., (height, width)] ''' # meta[:, 6:8]填充后的图片shape return tf.cast(meta[..., 6:8], tf.int32).numpy()

UTF-8

Python

py

misc.py

pkolt/django-filefieldtools

1d18197602e08bfd7d07320381ab026621ed5a93

ad8790306f06b9d0bbf33f0b43a9f811f328079d

/tests/app/tests/test_tools.py

96cc58cd4bb4073b1603e7d9252f3b384eff2a24

permissive

https://github.com/pkolt/django-filefieldtools

1064d0ed1b06e016ae0c01cd1495fc525cc2f4c3

4e886c9ab173449aa925c107cb9e8f353343e253

refs/heads/master

# -*- coding: utf-8 -*- from django.utils import unittest from filefieldtools.tools import (clean_filename, translate_filename, control_length, upload_to) class TestTools(unittest.TestCase): def test_translate_filename(self): value = translate_filename(u'Прайс для клиентов') self.assertEqual(value, 'Prays dlya klientov') def test_clean_name(self): value = clean_filename(' Price_-_.for clients.xls ') self.assertEqual(value, 'Price-for-clients.xls') value = clean_filename('Price for clients') self.assertEqual(value, 'Price-for-clients') value = clean_filename(u'Прайс для клиентов.xls') self.assertEqual(value, 'Prays-dlya-klientov.xls') def test_upload_to(self): value = upload_to()(None, 'picture.jpg') self.assertEqual(value, 'uploads/picture.jpg') value = upload_to('books/authors')(None, 'picture.jpg') self.assertEqual(value, 'uploads/books/authors/picture.jpg') value = upload_to('books/authors', to_lower=False)(None, 'Picture.JPG') self.assertEqual(value, 'uploads/books/authors/Picture.JPG') value = upload_to('books/authors')(None, 'Picture.JPG') self.assertEqual(value, 'uploads/books/authors/picture.jpg') value = upload_to('books/authors', to_hash=True)(None, 'Picture.JPG') self.assertNotEqual(value, 'uploads/books/authors/picture.jpg') self.assertTrue(value.startswith('uploads/books/authors/')) self.assertTrue(value.endswith('.jpg')) value = upload_to('books/%Y/%m/%d')(None, 'Picture.JPG') year, month, day = value.split('/')[2:5] self.assertTrue(year.isdigit()) self.assertTrue(month.isdigit()) self.assertTrue(day.isdigit()) def test_control_length(self): # lenght = 49 value = control_length('uploads/books/authors/client_prices_abcdefghi.xls', 50) self.assertEqual(value, 'uploads/books/authors/client_prices_abcdefghi.xls') # lenght = 50 value = control_length('uploads/books/authors/client_prices_abcdefghij.xls', 50) self.assertEqual(value, 'uploads/books/authors/client_prices_abcdefghij.xls') # length = 51 value = control_length('uploads/books/authors/client_prices_abcdefghijk.xls', 50) self.assertEqual(value, 'uploads/books/authors/client_prices_abcdefghij.xls') # length = 51 value = control_length('uploads/books/authors/client_prices_abcdefghi-k.xls', 50) self.assertEqual(value, 'uploads/books/authors/client_prices_abcdefghi.xls') # length = 51 value = control_length('uploads/books/12345678901234567890123/authors/a.xls', 50) self.assertEqual(value, 'uploads/books/12345678901234567890123/authors/a.xls')

UTF-8

Python

py

test_tools.py

hafiztsalavin/catatanDasarPython

748c766e32e1b3d154558db6c113c6a7203c87e1

da82d899f9c057138524923e0ef50b5a50a0abf2

/stack and queue/stack and queue/stack and queue/queue.py

8ad667ede6c796344733f1cb94dc73b70cbe2880

no_license

https://github.com/hafiztsalavin/catatanDasarPython

e0827410ffc7f6ea11b79e02c25a3cd574e4ccba

32b68eabdb52fc11dff9a50fadd92aeb3d57b945

refs/heads/master

Python

from collections import deque # ANTRIAN Antrian = deque([1,2,3,4,5,6,7,8]) print ('tumpukan sekarang ',Antrian) Antrian.append(9) print ('tumpukan sekarang ',Antrian) Antrian.append(10) print ('tumpukan sekarang ',Antrian) keluar = Antrian.popleft() print ('data yang keluar : ',keluar) print ('tumpukan sekarang ',Antrian) keluar = Antrian.popleft() print ('data yang keluar : ',keluar) print ('tumpukan sekarang ',Antrian) keluar = Antrian.popleft() print ('data yang keluar : ',keluar) print ('tumpukan sekarang ',Antrian)

UTF-8

Python

py

queue.py

pycalphad/scheil

3515049d730a477ebbd9a06aaeacbb42bdef5ca6

7c008d1e34080359840f368462106a0336e1928f

/scheil/simulate.py

beba5d183e6ee54c45f6ffe99e2d62dd5cdbd409

permissive

https://github.com/pycalphad/scheil

b9e1df2ba073bc6767f3f8a0ff0145ab7e349514

05a89a914db0f268142a91fa4045f9dca2ce9930

refs/heads/master

MIT

Python

import sys import numpy as np from pycalphad import equilibrium, variables as v from pycalphad.codegen.callables import build_phase_records from pycalphad.core.calculate import _sample_phase_constitution from pycalphad.core.utils import instantiate_models, unpack_components, filter_phases, point_sample from .solidification_result import SolidificationResult from .utils import local_sample, get_phase_amounts from .ordering import create_ordering_records, rename_disordered_phases def is_converged(eq): """ Return true if there are phase fractions that are non-NaN Parameters ---------- eq : pycalphad.LightDataset """ if np.any(~np.isnan(eq.NP)): return True return False def _update_points(eq, points_dict, dof_dict, local_pdens=0, verbose=False): """ Update the points_dict by appending new points. Parameters ---------- eq : pycalphad.LightDataset Point equilibrium result. Incompatible with xarray.Dataset objects. points_dict : dict[str, np.ndarray] Map of phase name to array of points dof_dict : dict[str, list[int]] Map of phase name to the sublattice degrees of freedom. local_pdens : Optional[int] Point density for local sampling. If zero (the default) only the equilibrium site fractions will be added. verbose : Optional[bool] """ # Update the points dictionary with local samples around the equilibrium site fractions for vtx in eq.vertex.squeeze(): ph = str(eq.Phase.squeeze()[vtx]) pts = points_dict.get(ph) if pts is not None: if verbose: print(f'Adding points to {ph}. ', end='') dof = dof_dict[ph] eq_pts = eq.Y.squeeze()[vtx, :sum(dof)].reshape(1, -1) if local_pdens > 0: points_dict[ph] = np.concatenate([pts, local_sample(eq_pts, dof, pdens=local_pdens)], axis=0) else: points_dict[ph] = np.concatenate([pts, eq_pts], axis=0) def simulate_scheil_solidification(dbf, comps, phases, composition, start_temperature, step_temperature=1.0, liquid_phase_name='LIQUID', eq_kwargs=None, stop=0.0001, verbose=False, adaptive=True): """Perform a Scheil-Gulliver solidification simulation. Parameters ---------- dbf : pycalphad.Database Database object. comps : list List of components in the system. phases : list List of phases in the system. composition : Dict[v.X, float] Dictionary of independent `v.X` composition variables. start_temperature : float Starting temperature for simulation. Must be single phase liquid. step_temperature : Optional[float] Temperature step size. Defaults to 1.0. liquid_phase_name : Optional[str] Name of the phase treated as liquid (i.e. the phase with infinitely fast diffusion). Defaults to 'LIQUID'. eq_kwargs: Optional[Dict[str, Any]] Keyword arguments for equilibrium stop: Optional[float] Stop when the phase fraction of liquid is below this amount. adaptive: Optional[bool] Whether to add additional points near the equilibrium points at each step. Only takes effect if ``points`` is in the eq_kwargs dict. Returns ------- SolidificationResult """ eq_kwargs = eq_kwargs or dict() STEP_SCALE_FACTOR = 1.2 # How much to try to adapt the temperature step by MAXIMUM_STEP_SIZE_REDUCTION = 5.0 T_STEP_ORIG = step_temperature phases = filter_phases(dbf, unpack_components(dbf, comps), phases) ordering_records = create_ordering_records(dbf, comps, phases) models = instantiate_models(dbf, comps, phases) if verbose: print('building PhaseRecord objects... ', end='') phase_records = build_phase_records(dbf, comps, phases, [v.N, v.P, v.T], models) if verbose: print('done') filtered_disordered_phases = {ord_rec.disordered_phase_name for ord_rec in ordering_records} solid_phases = sorted((set(phases) | filtered_disordered_phases) - {liquid_phase_name}) temp = start_temperature independent_comps = sorted([str(comp)[2:] for comp in composition.keys()]) x_liquid = {comp: [composition[v.X(comp)]] for comp in independent_comps} fraction_solid = [0.0] temperatures = [temp] phase_amounts = {ph: [0.0] for ph in solid_phases} if adaptive: dof_dict = {phase_name: list(map(len, mod.constituents)) for phase_name, mod in models.items()} eq_kwargs.setdefault('calc_opts', {}) # TODO: handle per-phase/unpackable points and pdens if 'points' not in eq_kwargs['calc_opts']: if verbose: print('generating points... ', end='') points_dict = {} for phase_name, mod in models.items(): if verbose: print(phase_name, end=' ') pdens = eq_kwargs['calc_opts'].get('pdens', 50) points_dict[phase_name] = _sample_phase_constitution(mod, point_sample, True, pdens=pdens) eq_kwargs['calc_opts']['points'] = points_dict if verbose: print('done') converged = False phases_seen = {liquid_phase_name, ''} liquid_comp = composition while fraction_solid[-1] < 1: conds = {v.T: temp, v.P: 101325.0, v.N: 1.0} comp_conds = liquid_comp fmt_comp_conds = ', '.join([f'{c}={val:0.2f}' for c, val in comp_conds.items()]) conds.update(comp_conds) eq = equilibrium(dbf, comps, phases, conds, model=models, phase_records=phase_records, to_xarray=False, **eq_kwargs) if adaptive: _update_points(eq, eq_kwargs['calc_opts']['points'], dof_dict, verbose=verbose) eq = eq.get_dataset() # convert LightDataset to Dataset for fancy indexing eq = rename_disordered_phases(eq, ordering_records) eq_phases = eq.Phase.values.squeeze().tolist() new_phases_seen = set(eq_phases).difference(phases_seen) if len(new_phases_seen) > 0: if verbose: print(f'New phases seen: {new_phases_seen}. ', end='') phases_seen |= new_phases_seen if liquid_phase_name not in eq["Phase"].values.squeeze(): found_ph = set(eq_phases) - {''} if verbose: print(f'No liquid phase found at T={temp:0.3f}, {fmt_comp_conds}. (Found {found_ph}) ', end='') if len(found_ph) == 0: # No phases found in equilibrium. Just continue on lowering the temperature without changing anything if verbose: print(f'(Convergence failure) ', end='') if T_STEP_ORIG / step_temperature > MAXIMUM_STEP_SIZE_REDUCTION: # Only found solid phases and the step size has already been reduced. Stop running without converging. if verbose: print('Maximum step size reduction exceeded. Stopping.') converged = False break else: # Only found solid phases. Try reducing the step size to zero-in on the correct phases if verbose: print(f'Stepping back and reducing step size.') temp += step_temperature step_temperature /= STEP_SCALE_FACTOR temp -= step_temperature continue # TODO: Will break if there is a liquid miscibility gap liquid_vertex = sorted(np.nonzero(eq["Phase"].values.squeeze().flat == liquid_phase_name))[0] liquid_comp = {} for comp in independent_comps: x = float(eq["X"].isel(vertex=liquid_vertex).squeeze().sel(component=comp).values) x_liquid[comp].append(x) liquid_comp[v.X(comp)] = x np_liq = np.nansum(eq.where(eq["Phase"] == liquid_phase_name).NP.values) current_fraction_solid = float(fraction_solid[-1]) found_phase_amounts = [(liquid_phase_name, np_liq)] # tuples of phase name, amount for solid_phase in solid_phases: if solid_phase not in eq_phases: phase_amounts[solid_phase].append(0.0) continue np_tieline = np.nansum(eq.isel(vertex=eq_phases.index(solid_phase))["NP"].values.squeeze()) found_phase_amounts.append((solid_phase, np_tieline)) delta_fraction_solid = (1 - current_fraction_solid) * np_tieline current_fraction_solid += delta_fraction_solid phase_amounts[solid_phase].append(delta_fraction_solid) fraction_solid.append(current_fraction_solid) temperatures.append(temp) NL = 1 - fraction_solid[-1] if verbose: phase_amnts = ' '.join([f'NP({ph})={amnt:0.3f}' for ph, amnt in found_phase_amounts]) if NL < 1.0e-3: print(f'T={temp:0.3f}, {fmt_comp_conds}, ΔT={step_temperature:0.3f}, NL: {NL:.2E}, {phase_amnts} ', end='') else: print(f'T={temp:0.3f}, {fmt_comp_conds}, ΔT={step_temperature:0.3f}, NL: {NL:0.3f}, {phase_amnts} ', end='') if NL < stop: if verbose: print(f'Liquid fraction below criterion {stop} . Stopping at {fmt_comp_conds}') converged = True break if verbose: print() # add line break temp -= step_temperature if fraction_solid[-1] < 1: for comp in independent_comps: x_liquid[comp].append(np.nan) fraction_solid.append(1.0) temperatures.append(temp) # set the final phase amount to the phase fractions in the eutectic # this method gives the sum total phase amounts of 1.0 by construction for solid_phase in solid_phases: if solid_phase in eq_phases: amount = np.nansum(eq.isel(vertex=eq_phases.index(solid_phase))["NP"].values.squeeze()) phase_amounts[solid_phase].append(float(amount) * (1 - current_fraction_solid)) else: phase_amounts[solid_phase].append(0.0) return SolidificationResult(x_liquid, fraction_solid, temperatures, phase_amounts, converged, "scheil") def simulate_equilibrium_solidification(dbf, comps, phases, composition, start_temperature, step_temperature=1.0, liquid_phase_name='LIQUID', adaptive=True, eq_kwargs=None, binary_search_tol=0.1, verbose=False): """ Compute the equilibrium solidification path. Decreases temperature until no liquid is found, performing a binary search to get the soildus temperature. dbf : pycalphad.Database Database object. comps : list List of components in the system. phases : list List of phases in the system. composition : Dict[v.X, float] Dictionary of independent `v.X` composition variables. start_temperature : float Starting temperature for simulation. Should be single phase liquid. step_temperature : Optional[float] Temperature step size. Defaults to 1.0. liquid_phase_name : Optional[str] Name of the phase treated as liquid (i.e. the phase with infinitely fast diffusion). Defaults to 'LIQUID'. eq_kwargs: Optional[Dict[str, Any]] Keyword arguments for equilibrium binary_search_tol : float Stop the binary search when the difference between temperatures is less than this amount. adaptive: Optional[bool] Whether to add additional points near the equilibrium points at each step. Only takes effect if ``points`` is in the eq_kwargs dict. """ eq_kwargs = eq_kwargs or dict() phases = filter_phases(dbf, unpack_components(dbf, comps), phases) ordering_records = create_ordering_records(dbf, comps, phases) filtered_disordered_phases = {ord_rec.disordered_phase_name for ord_rec in ordering_records} solid_phases = sorted((set(phases) | filtered_disordered_phases) - {liquid_phase_name}) independent_comps = sorted([str(comp)[2:] for comp in composition.keys()]) models = instantiate_models(dbf, comps, phases) if verbose: print('building PhaseRecord objects... ', end='') phase_records = build_phase_records(dbf, comps, phases, [v.N, v.P, v.T], models) if verbose: print('done') conds = {v.P: 101325, v.N: 1.0} conds.update(composition) if adaptive: dof_dict = {phase_name: list(map(len, mod.constituents)) for phase_name, mod in models.items()} eq_kwargs.setdefault('calc_opts', {}) # TODO: handle per-phase/unpackable points and pdens if 'points' not in eq_kwargs['calc_opts']: # construct a points dict for the user points_dict = {} for phase_name, mod in models.items(): pdens = eq_kwargs['calc_opts'].get('pdens', 50) points_dict[phase_name] = _sample_phase_constitution(mod, point_sample, True, pdens=pdens) eq_kwargs['calc_opts']['points'] = points_dict temperatures = [] x_liquid = {comp: [] for comp in independent_comps} fraction_solid = [] phase_amounts = {ph: [] for ph in solid_phases} # instantaneous phase amounts cum_phase_amounts = {ph: [] for ph in solid_phases} converged = False current_T = start_temperature if verbose: print('T=') while (fraction_solid[-1] < 1 if len(fraction_solid) > 0 else True) and not converged: sys.stdout.flush() conds[v.T] = current_T if verbose: print(f'{current_T} ', end='') eq = equilibrium(dbf, comps, phases, conds, model=models, phase_records=phase_records, to_xarray=False, **eq_kwargs) if not is_converged(eq): if verbose: comp_conds = {cond: val for cond, val in conds.items() if isinstance(cond, v.X)} print(f"Convergence failure at T={conds[v.T]} X={comp_conds} ") if adaptive: # Update the points dictionary with local samples around the equilibrium site fractions _update_points(eq, eq_kwargs['calc_opts']['points'], dof_dict) if liquid_phase_name in eq.Phase: # Add the liquid phase composition # TODO: will break in a liquid miscibility gap liquid_vertex = np.nonzero(eq.Phase == liquid_phase_name)[-1][0] for comp in independent_comps: x_liquid[comp].append(float(eq.X[..., liquid_vertex, eq.component.index(comp)])) temperatures.append(current_T) current_T -= step_temperature else: # binary search to find the solidus T_high = current_T + step_temperature # High temperature, liquid T_low = current_T # Low temperature, solids only found_ph = set(eq.Phase[eq.Phase != ''].tolist()) if verbose: print(f'Found phases {found_ph}. Starting binary search between T={(T_low, T_high)} ', end='') while (T_high - T_low) > binary_search_tol: bin_search_T = (T_high - T_low) * 0.5 + T_low conds[v.T] = bin_search_T eq = equilibrium(dbf, comps, phases, conds, model=models, phase_records=phase_records, to_xarray=False, **eq_kwargs) if adaptive: # Update the points dictionary with local samples around the equilibrium site fractions _update_points(eq, eq_kwargs['calc_opts']['points'], dof_dict) if not is_converged(eq): if verbose: comp_conds = {cond: val for cond, val in conds.items() if isinstance(cond, v.X)} print(f"Convergence failure at T={conds[v.T]} X={comp_conds} ") if liquid_phase_name in eq.Phase: T_high = bin_search_T else: T_low = bin_search_T converged = True conds[v.T] = T_low temperatures.append(T_low) eq = equilibrium(dbf, comps, phases, conds, model=models, phase_records=phase_records, to_xarray=False, **eq_kwargs) if not is_converged(eq): if verbose: comp_conds = {cond: val for cond, val in conds.items() if isinstance(cond, v.X)} print(f"Convergence failure at T={conds[v.T]} X={comp_conds} ") if verbose: found_phases = set(eq.Phase[eq.Phase != ''].tolist()) print(f"Finshed binary search at T={conds[v.T]} with phases={found_phases} and NP={eq.NP.squeeze()[:len(found_phases)]}") if adaptive: # Update the points dictionary with local samples around the equilibrium site fractions _update_points(eq, eq_kwargs['calc_opts']['points'], dof_dict) # Set the liquid phase composition to NaN for comp in independent_comps: x_liquid[comp].append(float(np.nan)) # Calculate fraction of solid and solid phase amounts current_fraction_solid = 0.0 eq = rename_disordered_phases(eq.get_dataset(), ordering_records) current_cum_phase_amnts = get_phase_amounts(eq.Phase.values.squeeze(), eq.NP.squeeze(), solid_phases) for solid_phase, amount in current_cum_phase_amnts.items(): # Since the equilibrium calculations always give the "cumulative" phase amount, # we need to take the difference to get the instantaneous. cum_phase_amounts[solid_phase].append(amount) if len(phase_amounts[solid_phase]) == 0: phase_amounts[solid_phase].append(amount) else: phase_amounts[solid_phase].append(amount - cum_phase_amounts[solid_phase][-2]) current_fraction_solid += amount fraction_solid.append(current_fraction_solid) converged = True if np.isclose(fraction_solid[-1], 1.0) else False return SolidificationResult(x_liquid, fraction_solid, temperatures, phase_amounts, converged, "equilibrium")

UTF-8

Python

py

simulate.py

ADebut/Leetcode

ab5bfe079e43ab1ad3193155b2e40067859bf51a

792ae5d2a5c17af4f2ccfa582e3aeec569a6809a

/152. Maximum Product Subarray.py

92c11b929ddaf29f1906129aaf0cb68135999799

no_license

https://github.com/ADebut/Leetcode

396b8b95ad5b5e623db2839bbfdec861c4c1731f

7333d481e00e8c1bc5b827d1d4ccd6e4d291abd7

refs/heads/master

class Solution: def maxProduct(self, nums: List[int]) -> int: MAX = nums[0] dp_min = [0 for x in range(len(nums))] dp_max = [0 for x in range(len(nums))] dp_min[0] = dp_max[0] = nums[0] for i in range(1, len(nums)): dp_max[i] = max([dp_max[i - 1] * nums[i], dp_min[i - 1] * nums[i], nums[i]]) dp_min[i] = min([dp_max[i - 1] * nums[i], dp_min[i - 1] * nums[i], nums[i]]) MAX = max(MAX, dp_max[i]) return MAX

UTF-8

Python

py

152. Maximum Product Subarray.py

annahs/atmos_research

a114324ab9b8a364f48d0c174257652b44f7339b

bff706dc4ce7552200e1d515afa9f0c461eb18a5

/WHI_CO_vs_alt.py

c8fa617483a4e0c8a83293de520f046a08fd05c4

permissive

https://github.com/annahs/atmos_research

1fffc24d43ddacf460a6d16f0b5264e6692023c5

b5853c9b12e327492f8f8ba5069bca3fd2e981c8

refs/heads/master

import matplotlib.pyplot as plt import numpy as np from matplotlib import dates import os import pickle from datetime import datetime from pprint import pprint import sys from datetime import timedelta import calendar import mysql.connector from pyhdf.SD import SD, SDC, SDS year_to_plot = 2009 #fire times timezone = timedelta(hours = -8) fire_time1 = [datetime.strptime('2009/07/27 00:00', '%Y/%m/%d %H:%M'), datetime.strptime('2009/08/08 00:00', '%Y/%m/%d %H:%M')] #row_datetimes follwing Takahama et al (2011) doi:10.5194/acp-11-6367-2011 #PST fire_time1_UNIX_UTC_start = float(calendar.timegm((fire_time1[0]-timezone).utctimetuple())) fire_time1_UNIX_UTC_end = float(calendar.timegm((fire_time1[1]-timezone).utctimetuple())) fire_time2 = [datetime.strptime('2010/07/26 09:00', '%Y/%m/%d %H:%M'), datetime.strptime('2010/07/28 09:30', '%Y/%m/%d %H:%M')] #jason's BC clear report #PST fire_time2_UNIX_UTC_start = float(calendar.timegm((fire_time2[0]-timezone).utctimetuple())) fire_time2_UNIX_UTC_end = float(calendar.timegm((fire_time2[1]-timezone).utctimetuple())) #database connection cnx = mysql.connector.connect(user='root', password='Suresh15', host='localhost', database='black_carbon') cursor = cnx.cursor() #set up cluster dictionaries default_data = {} other_data = {} GC_LRT = dict.fromkeys(range(1,47)) GC_NPac = dict.fromkeys(range(1,47)) GC_SPac = dict.fromkeys(range(1,47)) GC_Cont = dict.fromkeys(range(1,47)) GC_all = dict.fromkeys(range(1,47)) for key in GC_LRT: GC_LRT [key] =[] GC_NPac[key] =[] GC_SPac[key] =[] GC_Cont[key] =[] GC_all[key] =[] default_data['NPac'] = GC_NPac default_data['SPac'] = GC_SPac default_data['Cont'] = GC_Cont default_data['LRT'] = GC_LRT default_data['all'] = GC_all lat = 20 #20 corresponds to 50deg lon = 7 #7 corresponds to -122.5deg molar_mass_BC = 12.0107 #in g/mol ng_per_g = 10**9 R = 8.3144621 # in m3*Pa/(K*mol) GEOS_Chem_factor = 10**-9 start_hour = 4 end_hour = 16 data_dir = 'C:/Users/Sarah Hanna/Documents/Data/WHI long term record/GOES-Chem/Junwei_runs/default/' os.chdir(data_dir) for file in os.listdir(data_dir): if file.endswith('.hdf'): file_year = int(file[2:6]) file_month = int(file[6:8]) file_day = int(file[8:10]) file_hour = int(file[11:13]) GC_datetime = datetime(file_year,file_month,file_day,file_hour) GC_UNIX_UTC_ts = calendar.timegm(GC_datetime.utctimetuple()) if file_year not in [year_to_plot]: continue if start_hour <= file_hour < end_hour: #ignore any times not in the 2000-0800 window #avoid fire times if (fire_time1_UNIX_UTC_start <= GC_UNIX_UTC_ts <= fire_time1_UNIX_UTC_end) or (fire_time2_UNIX_UTC_start <= GC_UNIX_UTC_ts <= fire_time2_UNIX_UTC_end): continue #avoid high RH times cursor.execute(('SELECT RH from whi_high_rh_times_2009to2012 where high_RH_start_time <= %s and high_RH_end_time > %s'),(GC_UNIX_UTC_ts,GC_UNIX_UTC_ts)) RH_data = cursor.fetchone() if RH_data != None: if RH_data[0] > 90: continue #get appropriate cluster cursor.execute(('SELECT cluster_number FROM whi_ft_cluster_times_2009to2012 where cluster_start_time <= %s and cluster_end_time > %s'),(GC_UNIX_UTC_ts,GC_UNIX_UTC_ts)) cluster_number_result = cursor.fetchone() if cluster_number_result == None: continue else: cluster_number = cluster_number_result[0] if cluster_number in [1,3,5,10]: cluster = 'NPac' if cluster_number in [6,8,9]: cluster = 'SPac' if cluster_number in [4]: cluster = 'Cont' if cluster_number in [2,7]: cluster = 'LRT' hdf_file = SD(file, SDC.READ) GC_CO = hdf_file.select('IJ-AVG-$::CO') #3d CO data in ppbv (molBC/molAIR) pressures = hdf_file.select('PEDGE-$::PSURF') hydrophilic_BC = hdf_file.select('IJ-AVG-$::BCPI') #3d conc data in ppbv (molBC/molAIR) hydrophobic_BC = hdf_file.select('IJ-AVG-$::BCPO') i=0 for level in range(1,47): pressure = pressures[level,lat,lon] total_BC_ppbv = hydrophilic_BC[level,lat,lon] + hydrophobic_BC[level,lat,lon] BC_conc_ngm3 = total_BC_ppbv*molar_mass_BC*ng_per_g*GEOS_Chem_factor*(101325/(R*273)) #101325/(R*273) corrects to STP CO_ppbv = GC_CO[level,lat,lon] BC_CO = BC_conc_ngm3/CO_ppbv default_data[cluster][level].append([pressure,CO_ppbv,GC_datetime]) default_data['all'][level].append([pressure,CO_ppbv,GC_datetime]) hdf_file.end() mean_dict = {'all':[],'NPac':[],'SPac':[],'Cont':[],'LRT':[]} for cluster in default_data: for level in default_data[cluster]: FT_intervals = {} for row in default_data[cluster][level]: GC_datetime = row[2] pressure = row[0] CO = row[1] if start_hour <= GC_datetime.hour < (start_hour+6): period_midtime = datetime(GC_datetime.year,GC_datetime.month,GC_datetime.day,7) if (start_hour+6) <= GC_datetime.hour < end_hour: period_midtime = datetime(GC_datetime.year,GC_datetime.month,GC_datetime.day,13) if period_midtime in FT_intervals: FT_intervals[period_midtime].append([pressure,CO]) else: FT_intervals[period_midtime] = [[pressure,CO]] temp = [] #get 6-hr means - analogous to measurements for period_midtime in FT_intervals: mean_conc = np.mean([row[1] for row in FT_intervals[period_midtime]]) mean_pressure = np.mean([row[0] for row in FT_intervals[period_midtime]]) temp.append([mean_pressure,mean_conc]) #get medians for each level average_p = np.mean([row[0] for row in temp]) med_CO = np.median([row[1] for row in temp]) min_err_CO = med_CO - np.percentile([row[1] for row in temp],25) max_err_CO = np.percentile([row[1] for row in temp],75) - med_CO mean_dict[cluster].append([average_p,med_CO,min_err_CO,max_err_CO]) cursor.execute(('''SELECT measCO.UNIX_UTC_start_time, mc.cluster_number, measCO.CO_ppbv FROM whi_gc_and_sp2_6h_mass_concs mc JOIN whi_co_data measCO on mc.CO_meas_id = measCO.id WHERE mc.RH_threshold = 90 and measCO.CO_ppbv < 250''') ) data = cursor.fetchall() CO_by_cluster = { 'all':[], 'NPac':[], 'SPac':[], 'Cont':[], 'LRT':[] } for row in data: CO_start_time = datetime.utcfromtimestamp(row[0]) cluster_number = row[1] CO_conc = row[2] if CO_start_time.year == year_to_plot: CO_by_cluster['all'].append(CO_conc) if cluster_number in [6,8,9]: CO_by_cluster['SPac'].append(CO_conc) if cluster_number in [4]: CO_by_cluster['Cont'].append(CO_conc) if cluster_number in [2,7]: CO_by_cluster['LRT'].append(CO_conc) if cluster_number in [1,3,5,10]: CO_by_cluster['NPac'].append(CO_conc) cnx.close() #### plotting cluster_list = ['all','NPac','SPac','Cont','LRT'] colors = ['k','c','g','m','b'] fig = plt.figure() ax1 = plt.subplot2grid((1,1), (0,0), colspan=1) default_concs = [row[1] for row in mean_dict['all']] default_concs_min_err = [row[2] for row in mean_dict['all']] default_concs_max_err = [row[3] for row in mean_dict['all']] default_pressures = [row[0] for row in mean_dict['all']] #ax1.errorbar(108, 781.5,xerr=[[13],[28]],fmt='o',color = colors[i]) #ax1.errorbar(105.6, 781.5,xerr=[[11.7],[12.6]],fmt='o',color = 'b') #2009,2010 (june-aug) #ax1.errorbar(106.4, 781.5,xerr=[[7],[35]],fmt='o',color = 'b') #2009 (june-aug) ax1.errorbar(103, 781.5,xerr=[[13],[13]],fmt='o',color = 'r') #2010 (june-aug) #ax1.errorbar(141.4, 781.5,xerr=[[10],[7]],fmt='o',color = colors[i]) #2012 (apr-may) ax1.errorbar(default_concs, default_pressures,xerr=[default_concs_min_err,default_concs_max_err],fmt='s',color = 'b',linestyle='-') ax1.invert_yaxis() ax1.axhspan(770,793, facecolor='grey', alpha=0.25) #95% CI for pressure at WHI ax1.set_ylim(910,510) ax1.set_xlim(80,240) #ax1.text(0.25, 0.9,'All Data', transform=ax1.transAxes) ax1.set_xlabel('CO ppbv') ax1.set_ylabel('Pressure (hPa)') plt.show() fig, axes = plt.subplots(3,2, figsize=(8, 10), facecolor='w', edgecolor='k') fig.subplots_adjust(hspace = 0., wspace=0.0) axs = axes.ravel() axes[-1, -1].axis('off') i=0 for cluster in cluster_list: print cluster default_concs = [row[1] for row in mean_dict[cluster]] default_concs_min_err = [row[2] for row in mean_dict[cluster]] default_concs_max_err = [row[3] for row in mean_dict[cluster]] default_pressures = [row[0] for row in mean_dict[cluster]] meas_CO = [np.mean(CO_by_cluster[cluster])] meas_CO_min = [meas_CO - np.percentile(CO_by_cluster[cluster],25)] meas_CO_max = [np.percentile(CO_by_cluster[cluster],75) - meas_CO] vert_plot_GC = axs[i].errorbar(default_concs, default_pressures,xerr=[default_concs_min_err,default_concs_max_err],fmt='.',color = colors[i],linestyle='-') vert_plot_meas = axs[i].errorbar(meas_CO, 781.5,xerr=[meas_CO_min,meas_CO_max],fmt='o',color = colors[i]) axs[i].invert_yaxis() axs[i].axhspan(770,793, facecolor='grey', alpha=0.25) #95% CI for pressure at WHI axs[i].set_ylim(910,510) axs[i].set_xlim(80,240) if i == 0: axs[i].text(0.25, 0.9,'All Data', transform=axs[i].transAxes) if i == 1: axs[i].text(0.25, 0.9,'N. Pacific', transform=axs[i].transAxes) if i == 2: axs[i].text(0.25, 0.9,'S. Pacific', transform=axs[i].transAxes) axs[i].set_ylabel('Pressure (hPa)') if i == 3: axs[i].text(0.25, 0.9,'N. Canada', transform=axs[i].transAxes) axs[i].set_xlabel('CO ppbv') if i == 4: axs[i].text(0.25, 0.9,'W. Pacific/Asia', transform=axs[i].transAxes) axs[i].set_xlabel('CO ppbv') if i in [1,3]: axs[i].yaxis.set_label_position('right') axs[i].yaxis.tick_right() if i in [0,1,2]: axs[i].set_xticklabels([]) i+=1 data_dir = 'C:/Users/Sarah Hanna/Documents/Data/WHI long term record/CO data/' os.chdir(data_dir) plt.savefig('GCv10 vertical profile - CO ' + str(year_to_plot) + '.png',bbox_inches='tight') plt.show()

UTF-8

Python

py

WHI_CO_vs_alt.py

abraker95/ultimate_osu_analyzer

314cb333f7043433d9937335e701a5d65fa15c36

05167f142a1c05fc18612da9d7628ce0ba396ec3

/osu/local/monitor.py

7c916a9557a62dd718e0252bc41dd91df8cb529e

permissive

https://github.com/abraker95/ultimate_osu_analyzer

73494c6507cc97d4cf627c16184cd87be632579b

8b211a01c2364d51b8bf08e045e9280ec3a04242

refs/heads/master

MIT

Python

import watchdog.observers import watchdog.events import os class Monitor(watchdog.observers.Observer): def __init__(self, osu_path): watchdog.observers.Observer.__init__(self) if not os.path.exists(osu_path): raise Exception(f'"{osu_path}" does not exist!') self.osu_path = osu_path self.monitors = {} self.start() def __del__(self): self.stop() def create_replay_monitor(self, name, callback): replay_path = f'{self.osu_path}/data/r' if not os.path.exists(replay_path): raise Exception(f'"{replay_path}" does not exist!') class EventHandler(watchdog.events.FileSystemEventHandler): def on_created(self, event): callback(event.src_path) print(f'Created file creation monitor for {self.osu_path}/data/r') self.monitors[name] = self.schedule(EventHandler(), replay_path, recursive=False) def create_map_montor(self, name, callback, beatmap_path): # TODO pass

UTF-8

Python