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print "Salam Alaikom !" import sys # if statement ------------------------------- if False: print "hi" print "Hello Wolrd!" if True: print "1" print "2" # array -------------------------------------- days = ["Monday", 'Tuesday', 'Wednesday', 'Thursday', 'Friday'] print days[0]; a=1; b=2 # -------------------------------------------- print a,b,'\n' if len(sys.argv)>1: print 'passed arguments are: ',str(sys.argv) if len(sys.argv)==1: print 'passed argument is: ',str(sys.argv[0]) raw_input("\n\nPress the enter key to exit")
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import unittest from app.models import News News=news.News class NewsTest(unittest.TestCase): ''' Test class to test the behaviour of the news class ''' if __name__ == '__main__': unittest.main()
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"""Implements A* Search functionality.""" from ...helpers import PriorityQueue from ...exceptions import NonexistentNodeError def a_star_search(graph, start, goal): """Runs an A* search on the specified graph to find a path from the ''start'' node to the ''goal'' node. Returns a list of nodes specifying a minimal path between the two nodes. If no path exists (disconnected components), returns an empty list. """ all_nodes = graph.get_all_node_ids() if start not in all_nodes: raise NonexistentNodeError(start) if goal not in all_nodes: raise NonexistentNodeError(goal) came_from, cost_so_far, goal_reached = _a_star_search_internal(graph, start, goal) if goal_reached: path = reconstruct_path(came_from, start, goal) path.reverse() return path else: return [] # A* Search Helpers def _a_star_search_internal(graph, start, goal): """Performs an A* search, returning information about whether the goal node was reached and path cost information that can be used to reconstruct the path. """ frontier = PriorityQueue() frontier.put(start, 0) came_from = {start: None} cost_so_far = {start: 0} goal_reached = False while not frontier.empty(): current = frontier.get() if current == goal: goal_reached = True break for next_node in graph.neighbors(current): new_cost = cost_so_far[current] + graph.edge_cost(current, next_node) if next_node not in cost_so_far or new_cost < cost_so_far[next_node]: cost_so_far[next_node] = new_cost priority = new_cost + heuristic(goal, next_node) frontier.put(next_node, priority) came_from[next_node] = current return came_from, cost_so_far, goal_reached
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# -*- coding: utf-8 -*- # Part of Odoo. See LICENSE file for full copyright and licensing details. import collections import json import itertools import operator from odoo import api, fields, models, tools, _ from odoo.exceptions import ValidationError class SurveyQuestion(models.Model): """ Questions that will be asked in a survey. Each question can have one of more suggested answers (eg. in case of multi-answer checkboxes, radio buttons...). Technical note: survey.question is also the model used for the survey's pages (with the "is_page" field set to True). A page corresponds to a "section" in the interface, and the fact that it separates the survey in actual pages in the interface depends on the "questions_layout" parameter on the survey.survey model. Pages are also used when randomizing questions. The randomization can happen within a "page". Using the same model for questions and pages allows to put all the pages and questions together in a o2m field (see survey.survey.question_and_page_ids) on the view side and easily reorganize your survey by dragging the items around. It also removes on level of encoding by directly having 'Add a page' and 'Add a question' links on the tree view of questions, enabling a faster encoding. However, this has the downside of making the code reading a little bit more complicated. Efforts were made at the model level to create computed fields so that the use of these models still seems somewhat logical. That means: - A survey still has "page_ids" (question_and_page_ids filtered on is_page = True) - These "page_ids" still have question_ids (questions located between this page and the next) - These "question_ids" still have a "page_id" That makes the use and display of these information at view and controller levels easier to understand. """ _name = 'survey.question' _description = 'Survey Question' _rec_name = 'title' _order = 'sequence,id' @api.model # question generic data title = fields.Char('Title', required=True, translate=True) description = fields.Html( 'Description', translate=True, sanitize=False, # TDE TODO: sanitize but find a way to keep youtube iframe media stuff help="Use this field to add additional explanations about your question or to illustrate it with pictures or a video") survey_id = fields.Many2one('survey.survey', string='Survey', ondelete='cascade') scoring_type = fields.Selection(related='survey_id.scoring_type', string='Scoring Type', readonly=True) sequence = fields.Integer('Sequence', default=10) # page specific is_page = fields.Boolean('Is a page?') question_ids = fields.One2many('survey.question', string='Questions', compute="_compute_question_ids") questions_selection = fields.Selection( related='survey_id.questions_selection', readonly=True, help="If randomized is selected, add the number of random questions next to the section.") random_questions_count = fields.Integer( 'Random questions count', default=1, help="Used on randomized sections to take X random questions from all the questions of that section.") # question specific page_id = fields.Many2one('survey.question', string='Page', compute="_compute_page_id", store=True) question_type = fields.Selection([ ('text_box', 'Multiple Lines Text Box'), ('char_box', 'Single Line Text Box'), ('numerical_box', 'Numerical Value'), ('date', 'Date'), ('datetime', 'Datetime'), ('simple_choice', 'Multiple choice: only one answer'), ('multiple_choice', 'Multiple choice: multiple answers allowed'), ('matrix', 'Matrix')], string='Question Type', compute='_compute_question_type', readonly=False, store=True) is_scored_question = fields.Boolean( 'Scored', compute='_compute_is_scored_question', readonly=False, store=True, copy=True, help="Include this question as part of quiz scoring. Requires an answer and answer score to be taken into account.") # -- scoreable/answerable simple answer_types: numerical_box / date / datetime answer_numerical_box = fields.Float('Correct numerical answer', help="Correct number answer for this question.") answer_date = fields.Date('Correct date answer', help="Correct date answer for this question.") answer_datetime = fields.Datetime('Correct datetime answer', help="Correct date and time answer for this question.") answer_score = fields.Float('Score', help="Score value for a correct answer to this question.") # -- char_box save_as_email = fields.Boolean( "Save as user email", compute='_compute_save_as_email', readonly=False, store=True, copy=True, help="If checked, this option will save the user's answer as its email address.") save_as_nickname = fields.Boolean( "Save as user nickname", compute='_compute_save_as_nickname', readonly=False, store=True, copy=True, help="If checked, this option will save the user's answer as its nickname.") # -- simple choice / multiple choice / matrix suggested_answer_ids = fields.One2many( 'survey.question.answer', 'question_id', string='Types of answers', copy=True, help='Labels used for proposed choices: simple choice, multiple choice and columns of matrix') allow_value_image = fields.Boolean('Images on answers', help='Display images in addition to answer label. Valid only for simple / multiple choice questions.') # -- matrix matrix_subtype = fields.Selection([ ('simple', 'One choice per row'), ('multiple', 'Multiple choices per row')], string='Matrix Type', default='simple') matrix_row_ids = fields.One2many( 'survey.question.answer', 'matrix_question_id', string='Matrix Rows', copy=True, help='Labels used for proposed choices: rows of matrix') # -- display & timing options column_nb = fields.Selection([ ('12', '1'), ('6', '2'), ('4', '3'), ('3', '4'), ('2', '6')], string='Number of columns', default='12', help='These options refer to col-xx-[12|6|4|3|2] classes in Bootstrap for dropdown-based simple and multiple choice questions.') is_time_limited = fields.Boolean("The question is limited in time", help="Currently only supported for live sessions.") time_limit = fields.Integer("Time limit (seconds)") # -- comments (simple choice, multiple choice, matrix (without count as an answer)) comments_allowed = fields.Boolean('Show Comments Field') comments_message = fields.Char('Comment Message', translate=True, default=lambda self: _("If other, please specify:")) comment_count_as_answer = fields.Boolean('Comment Field is an Answer Choice') # question validation validation_required = fields.Boolean('Validate entry') validation_email = fields.Boolean('Input must be an email') validation_length_min = fields.Integer('Minimum Text Length', default=0) validation_length_max = fields.Integer('Maximum Text Length', default=0) validation_min_float_value = fields.Float('Minimum value', default=0.0) validation_max_float_value = fields.Float('Maximum value', default=0.0) validation_min_date = fields.Date('Minimum Date') validation_max_date = fields.Date('Maximum Date') validation_min_datetime = fields.Datetime('Minimum Datetime') validation_max_datetime = fields.Datetime('Maximum Datetime') validation_error_msg = fields.Char('Validation Error message', translate=True, default=lambda self: _("The answer you entered is not valid.")) constr_mandatory = fields.Boolean('Mandatory Answer') constr_error_msg = fields.Char('Error message', translate=True, default=lambda self: _("This question requires an answer.")) # answers user_input_line_ids = fields.One2many( 'survey.user_input.line', 'question_id', string='Answers', domain=[('skipped', '=', False)], groups='survey.group_survey_user') # Conditional display is_conditional = fields.Boolean( string='Conditional Display', copy=False, help="""If checked, this question will be displayed only if the specified conditional answer have been selected in a previous question""") triggering_question_id = fields.Many2one( 'survey.question', string="Triggering Question", copy=False, compute="_compute_triggering_question_id", store=True, readonly=False, help="Question containing the triggering answer to display the current question.", domain="""[('survey_id', '=', survey_id), '&', ('question_type', 'in', ['simple_choice', 'multiple_choice']), '|', ('sequence', '<', sequence), '&', ('sequence', '=', sequence), ('id', '<', id)]""") triggering_answer_id = fields.Many2one( 'survey.question.answer', string="Triggering Answer", copy=False, compute="_compute_triggering_answer_id", store=True, readonly=False, help="Answer that will trigger the display of the current question.", domain="[('question_id', '=', triggering_question_id)]") _sql_constraints = [ ('positive_len_min', 'CHECK (validation_length_min >= 0)', 'A length must be positive!'), ('positive_len_max', 'CHECK (validation_length_max >= 0)', 'A length must be positive!'), ('validation_length', 'CHECK (validation_length_min <= validation_length_max)', 'Max length cannot be smaller than min length!'), ('validation_float', 'CHECK (validation_min_float_value <= validation_max_float_value)', 'Max value cannot be smaller than min value!'), ('validation_date', 'CHECK (validation_min_date <= validation_max_date)', 'Max date cannot be smaller than min date!'), ('validation_datetime', 'CHECK (validation_min_datetime <= validation_max_datetime)', 'Max datetime cannot be smaller than min datetime!'), ('positive_answer_score', 'CHECK (answer_score >= 0)', 'An answer score for a non-multiple choice question cannot be negative!'), ('scored_datetime_have_answers', "CHECK (is_scored_question != True OR question_type != 'datetime' OR answer_datetime is not null)", 'All "Is a scored question = True" and "Question Type: Datetime" questions need an answer'), ('scored_date_have_answers', "CHECK (is_scored_question != True OR question_type != 'date' OR answer_date is not null)", 'All "Is a scored question = True" and "Question Type: Date" questions need an answer') ] @api.depends('is_page') @api.depends('survey_id.question_and_page_ids.is_page', 'survey_id.question_and_page_ids.sequence') def _compute_question_ids(self): """Will take all questions of the survey for which the index is higher than the index of this page and lower than the index of the next page.""" for question in self: if question.is_page: next_page_index = False for page in question.survey_id.page_ids: if page._index() > question._index(): next_page_index = page._index() break question.question_ids = question.survey_id.question_ids.filtered( lambda q: q._index() > question._index() and (not next_page_index or q._index() < next_page_index) ) else: question.question_ids = self.env['survey.question'] @api.depends('survey_id.question_and_page_ids.is_page', 'survey_id.question_and_page_ids.sequence') def _compute_page_id(self): """Will find the page to which this question belongs to by looking inside the corresponding survey""" for question in self: if question.is_page: question.page_id = None else: page = None for q in question.survey_id.question_and_page_ids.sorted(): if q == question: break if q.is_page: page = q question.page_id = page @api.depends('question_type', 'validation_email') @api.depends('question_type') @api.depends('is_conditional') def _compute_triggering_question_id(self): """ Used as an 'onchange' : Reset the triggering question if user uncheck 'Conditional Display' Avoid CacheMiss : set the value to False if the value is not set yet.""" for question in self: if not question.is_conditional or question.triggering_question_id is None: question.triggering_question_id = False @api.depends('triggering_question_id') def _compute_triggering_answer_id(self): """ Used as an 'onchange' : Reset the triggering answer if user unset or change the triggering question or uncheck 'Conditional Display'. Avoid CacheMiss : set the value to False if the value is not set yet.""" for question in self: if not question.triggering_question_id \ or question.triggering_question_id != question.triggering_answer_id.question_id\ or question.triggering_answer_id is None: question.triggering_answer_id = False @api.depends('question_type', 'scoring_type', 'answer_date', 'answer_datetime', 'answer_numerical_box') def _compute_is_scored_question(self): """ Computes whether a question "is scored" or not. Handles following cases: - inconsistent Boolean=None edge case that breaks tests => False - survey is not scored => False - 'date'/'datetime'/'numerical_box' question types w/correct answer => True (implied without user having to activate, except for numerical whose correct value is 0.0) - 'simple_choice / multiple_choice': set to True even if logic is a bit different (coming from answers) - question_type isn't scoreable (note: choice questions scoring logic handled separately) => False """ for question in self: if question.is_scored_question is None or question.scoring_type == 'no_scoring': question.is_scored_question = False elif question.question_type == 'date': question.is_scored_question = bool(question.answer_date) elif question.question_type == 'datetime': question.is_scored_question = bool(question.answer_datetime) elif question.question_type == 'numerical_box' and question.answer_numerical_box: question.is_scored_question = True elif question.question_type in ['simple_choice', 'multiple_choice']: question.is_scored_question = True else: question.is_scored_question = False # ------------------------------------------------------------ # VALIDATION # ------------------------------------------------------------ def validate_question(self, answer, comment=None): """ Validate question, depending on question type and parameters for simple choice, text, date and number, answer is simply the answer of the question. For other multiple choices questions, answer is a list of answers (the selected choices or a list of selected answers per question -for matrix type-): - Simple answer : answer = 'example' or 2 or question_answer_id or 2019/10/10 - Multiple choice : answer = [question_answer_id1, question_answer_id2, question_answer_id3] - Matrix: answer = { 'rowId1' : [colId1, colId2,...], 'rowId2' : [colId1, colId3, ...] } return dict {question.id (int): error (str)} -> empty dict if no validation error. """ self.ensure_one() if isinstance(answer, str): answer = answer.strip() # Empty answer to mandatory question if self.constr_mandatory and not answer and self.question_type not in ['simple_choice', 'multiple_choice']: return {self.id: self.constr_error_msg} # because in choices question types, comment can count as answer if answer or self.question_type in ['simple_choice', 'multiple_choice']: if self.question_type == 'char_box': return self._validate_char_box(answer) elif self.question_type == 'numerical_box': return self._validate_numerical_box(answer) elif self.question_type in ['date', 'datetime']: return self._validate_date(answer) elif self.question_type in ['simple_choice', 'multiple_choice']: return self._validate_choice(answer, comment) elif self.question_type == 'matrix': return self._validate_matrix(answer) return {} def _index(self): """We would normally just use the 'sequence' field of questions BUT, if the pages and questions are created without ever moving records around, the sequence field can be set to 0 for all the questions. However, the order of the recordset is always correct so we can rely on the index method.""" self.ensure_one() return list(self.survey_id.question_and_page_ids).index(self) # ------------------------------------------------------------ # STATISTICS / REPORTING # ------------------------------------------------------------ def _prepare_statistics(self, user_input_lines): """ Compute statistical data for questions by counting number of vote per choice on basis of filter """ all_questions_data = [] for question in self: question_data = {'question': question, 'is_page': question.is_page} if question.is_page: all_questions_data.append(question_data) continue # fetch answer lines, separate comments from real answers all_lines = user_input_lines.filtered(lambda line: line.question_id == question) if question.question_type in ['simple_choice', 'multiple_choice', 'matrix']: answer_lines = all_lines.filtered( lambda line: line.answer_type == 'suggestion' or ( line.answer_type == 'char_box' and question.comment_count_as_answer) ) comment_line_ids = all_lines.filtered(lambda line: line.answer_type == 'char_box') else: answer_lines = all_lines comment_line_ids = self.env['survey.user_input.line'] skipped_lines = answer_lines.filtered(lambda line: line.skipped) done_lines = answer_lines - skipped_lines question_data.update( answer_line_ids=answer_lines, answer_line_done_ids=done_lines, answer_input_done_ids=done_lines.mapped('user_input_id'), answer_input_skipped_ids=skipped_lines.mapped('user_input_id'), comment_line_ids=comment_line_ids) question_data.update(question._get_stats_summary_data(answer_lines)) # prepare table and graph data table_data, graph_data = question._get_stats_data(answer_lines) question_data['table_data'] = table_data question_data['graph_data'] = json.dumps(graph_data) all_questions_data.append(question_data) return all_questions_data def _get_stats_data_answers(self, user_input_lines): """ Statistics for question.answer based questions (simple choice, multiple choice.). A corner case with a void record survey.question.answer is added to count comments that should be considered as valid answers. This small hack allow to have everything available in the same standard structure. """ suggested_answers = [answer for answer in self.mapped('suggested_answer_ids')] if self.comment_count_as_answer: suggested_answers += [self.env['survey.question.answer']] count_data = dict.fromkeys(suggested_answers, 0) for line in user_input_lines: if line.suggested_answer_id or (line.value_char_box and self.comment_count_as_answer): count_data[line.suggested_answer_id] += 1 table_data = [{ 'value': _('Other (see comments)') if not sug_answer else sug_answer.value, 'suggested_answer': sug_answer, 'count': count_data[sug_answer] } for sug_answer in suggested_answers] graph_data = [{ 'text': _('Other (see comments)') if not sug_answer else sug_answer.value, 'count': count_data[sug_answer] } for sug_answer in suggested_answers] return table_data, graph_data class SurveyQuestionAnswer(models.Model): """ A preconfigured answer for a question. This model stores values used for * simple choice, multiple choice: proposed values for the selection / radio; * matrix: row and column values; """ _name = 'survey.question.answer' _rec_name = 'value' _order = 'sequence, id' _description = 'Survey Label' question_id = fields.Many2one('survey.question', string='Question', ondelete='cascade') matrix_question_id = fields.Many2one('survey.question', string='Question (as matrix row)', ondelete='cascade') sequence = fields.Integer('Label Sequence order', default=10) value = fields.Char('Suggested value', translate=True, required=True) value_image = fields.Image('Image', max_width=256, max_height=256) is_correct = fields.Boolean('Is a correct answer') answer_score = fields.Float('Score for this choice', help="A positive score indicates a correct choice; a negative or null score indicates a wrong answer") @api.constrains('question_id', 'matrix_question_id') def _check_question_not_empty(self): """Ensure that field question_id XOR field matrix_question_id is not null""" for label in self: if not bool(label.question_id) != bool(label.matrix_question_id): raise ValidationError(_("A label must be attached to only one question."))
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#!/usr/bin/env python import argparse import os import subprocess import tempfile if __name__ == '__main__': p = argparse.ArgumentParser() p.add_argument("-c", "--cluster", default="no-vep") p.add_argument("script") args, unparsed_args = p.parse_known_args() submit(args.script, unparsed_args, cluster=args.cluster)
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""" Compression using the average of signal as a magnitude """ import numpy as np from .compressor import Compressor class CompressorMagnitude: """ The average of the signal is used to perform the compression on the input data signal. Check the Compressor class on how the thresholding is done with the magnitude Attributes ---------- __magnitude: float magnitude calculated using the average of the signal __compressor: Compressor object to call the compress function using the magnitude calculated """ def compress(self, data): """ Apply thresholding techniques to remove the signal below the magnitude Parameters ---------- data: array_like input data signal, mostly coefficients output of the decompose Returns ------- array_like thresholded data/ coefficients """ self.__magnitude = np.sum(data, axis=0) lenD = len(data) return self.__compressor.compress(data, (self.__magnitude / lenD)) def getCompressionRate(self, data): """ Run the compression calculation on the data to check how well the compressor performed Parameters ---------- data: array_like input data from the final step of re-construction Returns ------- float percentage of the compression """ return self.__compressor.calculateCompressionRate(data) def getMagnitude(self): """ Returns the calculated magnitude Returns ------- float calculated magnitude """ return self.__magnitude
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- from wordcloud import WordCloud, ImageColorGenerator from PIL import Image import numpy as np import random if __name__ == '__main__': import re import multidict as multidict text = getFrequencyDictForText(open('lorem-ipsum.txt').read()) mkcloud('lorem-ipsum.png', text, '#FFF2CC', '#F030A8')
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# -*- coding: utf-8 -*- from enum import Enum # エリア定義
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import torch import torch.nn as nn import torch.nn.functional as F from torch.nn.functional import softmax import torch.optim as optim from torch.autograd import Variable import math import numpy as np from utils import write_pkl, read_pkl if __name__ == "__main__": '''self-attention''' input_data = torch.tensor(np.arange(24.).reshape(2,3,4),dtype=torch.float32) attention = Multi_Head_SelfAttention(num_head=3,num_vocab=3,input_dim=4,hidden_dim=5,out_dim=5) output_data = attention(input_data) print("output_data: \n",output_data) '''position encoder''' # input_data = torch.tensor([[[1,0,1,0],[0,2,0,2],[1,1,1,1]], [[1,0,1,0],[0,2,0,2],[1,1,1,1]] ],dtype=torch.float32) # print("input_data:\n",input_data) # positional_encoder = PositionalEncoder(d_model=4) # 该参数代表输出的嵌入维度,因为需要和输入的 # output_data = positional_encoder(input_data) # print("output_data:\n", output_data)
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import os import unittest from main import main from sqlite_dissect.utilities import DotDict class TestCASEExport(unittest.TestCase): """ This class tests a parsing of a file and ensuring that it properly generates a CASE export file. """
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#!/usr/bin/python3 import requests from discord.ext import commands TOKEN = "Your Discord token here" OWNER_ID = 0 # Your user ID here RTT_USERNAME = "Realtime Trains API username" RTT_PASSWORD = "Realtime Trains API password" ## BOT SETUP bot = commands.Bot(command_prefix = ">") # Comment to respond to messages from anyone @bot.check ## UTILITY FUNCTIONS ## COMMANDS @bot.command() @bot.command() @bot.command() bot.run(TOKEN)
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#Operadores Aritmeticos n1 = int( input('Digite um número: ' ) ) n2 = int( input('Digite outro número: ' ) ) soma = n1 + n2 prod = n1 * n2 div = n1 / n2 divint = n1 // n2 exp = n1 ** n2 resto = n1 % n2 # {: } os dois pontos formatam o valor da mascara conforme as diretrizes #quebra de linha é \n # end= escrever o conteudo no final do print print( 'A soma é {}, \no produto é {} \ne a divisão é {:.2}. '.format( soma, prod, div ), end='' ) print( 'A divisão inteira é {}, \na potenciação é {} \ne o resto da divisão é {}'.format( divint, exp, resto ) )
[ 2, 18843, 324, 2850, 317, 799, 15103, 418, 198, 198, 77, 16, 796, 493, 7, 5128, 10786, 19511, 578, 23781, 299, 21356, 647, 78, 25, 705, 1267, 1267, 198, 77, 17, 796, 493, 7, 5128, 10786, 19511, 578, 503, 305, 299, 21356, 647, 78, ...
2.35443
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# (C) Copyright 1996-2016 ECMWF. # # This software is licensed under the terms of the Apache Licence Version 2.0 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0. # In applying this licence, ECMWF does not waive the privileges and immunities # granted to it by virtue of its status as an intergovernmental organisation nor # does it submit to any jurisdiction. from Magics.macro import * #Loading GRIB file data = mgrib(grib_input_file_name='2m_temperature.grib',grib_field_position=1) #Setting output output = output( output_formats = ['png'], output_name = 'contour9', output_name_first_page_number = 'off') #Setting the geographical area area = mmap( subpage_lower_left_latitude = 34.5, subpage_lower_left_longitude = -10.67, subpage_map_projection = 'cylindrical', subpage_upper_right_latitude = 71.05, subpage_upper_right_longitude = 31.55, ) #Setting the coastlines background = mcoast( map_coastline_land_shade = 'on', map_coastline_land_shade_colour = 'cream') foreground = mcoast( map_coastline_land_shade = 'off', map_grid_line_style = 'dash', map_grid_colour = 'grey', map_label = 'on', map_coastline_colour = 'black') #Defining the contour contour = mcont( contour = 'off', contour_highlight_frequency = 100, contour_highlight_thickness = 5, contour_hilo = 'off', contour_interval = 2.0, contour_label = 'off', contour_level_selection_type = 'interval', contour_line_thickness = 3, contour_shade = 'on', contour_shade_colour_list = ['rgb(0.3,0.3,0.3)', 'rgb(0.4,0.4,0.4)', 'rgb(0.5,0.5,0.5)', 'rgb(0.6,0.6,0.6)', 'rgb(0.7,0.7,0.7)', 'rgb(0.8,0.8,0.8)', 'rgb(0.35,0,0.6)', 'rgb(0.5,0,0.9)', 'rgb(0.6,0.2,1)', 'rgb(0.75,0.4,1)', 'rgb(0.85,0.6,1)', 'rgb(0,0,0.75)', 'rgb(0,0,1)', 'rgb(0.2,0.4,1)', 'rgb(0.4,0.7,1)', 'rgb(0.6,0.9,1)', 'rgb(0,0.55,0.19)', 'rgb(0.15,0.75,0.1)', 'rgb(0.5,0.85,0)', 'rgb(0.65,0.95,0)', 'rgb(0.8,1,0.2)', 'rgb(0.65,0.65,0)', 'rgb(0.8,0.8,0)', 'rgb(0.92,0.92,0)', 'rgb(1,1,0)', 'rgb(1,1,0.6)', 'rgb(0.85,0.45,0)', 'rgb(1,0.5,0)', 'rgb(1,0.62,0)', 'rgb(1,0.74,0)', 'rgb(1,0.85,0)', 'rgb(0.6,0,0)', 'rgb(0.8,0,0)', 'rgb(1,0,0)', 'rgb(1,0.4,0.4)', 'rgb(1,0.6,0.6)', 'rgb(1,0.75,0.75)'], contour_shade_colour_method = 'list', contour_shade_max_level = 42.0, contour_shade_method = 'area_fill', contour_shade_min_level = -32.0, legend = 'on', ) #Picking the grib metadata title = mtext( text_lines = ['<font size="1">2m temperature (Range: -32 .. 42)</font>','<magics_title/>'], text_justification = 'left', text_font_size = 0.6, text_colour = 'charcoal') #Plotting plot(output,area,background,data,title,contour,foreground) #For documentation only tofortran('contour9',output,area,data,background,contour,foreground,title) tomv4('contour9',contour) tohtml('contour9',data,contour)
[ 2, 357, 34, 8, 15069, 8235, 12, 5304, 13182, 14326, 37, 13, 198, 2, 220, 198, 2, 770, 3788, 318, 11971, 739, 262, 2846, 286, 262, 24843, 10483, 594, 10628, 362, 13, 15, 198, 2, 543, 460, 307, 6492, 379, 2638, 1378, 2503, 13, 430...
1.859753
1,697
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#! /bin/python # config store & parse # # @file: config # @time: 2022/02/05 # @author: Mori # import json from tornado.util import ObjectDict global_config = ObjectDict()
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import asyncio from datetime import datetime import serial from logger import root_logger from . import const from .typing import NooliteCommand, BaseNooliteRemote, MotionSensor from typing import Dict, Callable import typing lg = root_logger.getChild('noolite') def _get_tty(tty_name) -> serial.Serial: """ Подключение к последовательному порту :param tty_name: имя порта :return: """ serial_port = serial.Serial(tty_name, 9600, timeout=2) if not serial_port.is_open: serial_port.open() serial_port.flushInput() serial_port.flushOutput() return serial_port
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import pytest from airbyte_dto_factory import * from airbyte_config_model import * @pytest.fixture def dummy_source_dto(): """ Creates a dummy SourceDto """ source = SourceDto() source.source_definition_id = 'ef69ef6e-aa7f-4af1-a01d-ef775033524e' source.source_id = '7d95ec85-47c6-42d4-a7a2-8e5c22c810d2' source.workspace_id = 'f3b9e848-790c-4cdd-a475-5c6bb156dc10' source.connection_configuration = { 'access_token': '**********' } source.name = 'apache/superset' source.source_name = 'GitHub' source.tag = 'tag1' return source @pytest.fixture def dummy_destination_dto(): """ Creates a dummy DestinationDto """ destination = DestinationDto() destination.destination_definition_id = '25c5221d-dce2-4163-ade9-739ef790f503' destination.destination_id = 'a41cb2f8-fcce-4c91-adfe-37c4586609f5' destination.workspace_id = 'f3b9e848-790c-4cdd-a475-5c6bb156dc10' destination.connection_configuration = { 'database': 'postgres', 'host': 'hostname.com', 'port': '5432', 'schema': 'demo', 'username': 'devrel_master', 'password': '**********' } destination.name = 'devrel-rds' destination.destination_name = 'Postgres' destination.tag = 'tag2' return destination @pytest.fixture def dummy_source_definitions(): """ Create a dummy source definition (as dict) """ source_definitions = [{'sourceDefinitionId': 'c2281cee-86f9-4a86-bb48-d23286b4c7bd', 'name': 'Slack', 'dockerRepository': 'airbyte/source-slack', 'dockerImageTag': '0.1.9', 'documentationUrl': 'https://docs.airbyte.io/integrations/sources/slack', 'icon': 'icon.png'}, {'sourceDefinitionId': 'ef69ef6e-aa7f-4af1-a01d-ef775033524e', 'name': 'GitHub', 'dockerRepository': 'airbyte/source-github-singer', 'dockerImageTag': '0.1.7', 'documentationUrl': 'https://hub.docker.com/r/airbyte/source-github-singer', 'icon': None}] return source_definitions @pytest.fixture def dummy_destination_definitions(): """ c=Create a dummy destination definition (as dict) """ destination_definitions = [{'destinationDefinitionId': '22f6c74f-5699-40ff-833c-4a879ea40133', 'name': 'BigQuery', 'dockerRepository': 'airbyte/destination-bigquery', 'dockerImageTag': '0.3.12', 'documentationUrl': 'https://docs.airbyte.io/integrations/destinations/bigquery', 'icon': None}, {'destinationDefinitionId': '25c5221d-dce2-4163-ade9-739ef790f503', 'name': 'Postgres', 'dockerRepository': 'airbyte/destination-postgres', 'dockerImageTag': '0.3.5', 'documentationUrl': 'https://docs.airbyte.io/integrations/destinations/postgres', 'icon': None}] return destination_definitions @pytest.fixture def dummy_source_dict(): """ Creates a dummy source dict """ source_dict = { 'sourceDefinitionId': 'ef69ef6e-aa7f-4af1-a01d-ef775033524e', 'sourceId': '7d95ec85-47c6-42d4-a7a2-8e5c22c810d2', 'workspaceId': 'f3b9e848-790c-4cdd-a475-5c6bb156dc10', 'connectionConfiguration': {'access_token': '**********'}, 'name': 'apache/superset', 'sourceName': 'GitHub', 'tag': 'tag1' } return source_dict @pytest.fixture def dummy_destination_dict(): """ Creates a dummy destination dict """ destination_dict = { 'destinationDefinitionId': '25c5221d-dce2-4163-ade9-739ef790f503', 'destinationId': 'a41cb2f8-fcce-4c91-adfe-37c4586609f5', 'workspaceId': 'f3b9e848-790c-4cdd-a475-5c6bb156dc10', 'connectionConfiguration': { 'database': 'postgres', 'host': 'hostname.com', 'port': '5432', 'schema': 'demo', 'username': 'devrel_master', 'password': '**********' }, 'name': 'devrel-rds', 'destinationName': 'Postgres', 'tag': 'tag2' } return destination_dict @pytest.fixture def dummy_airbyte_dto_factory(dummy_source_definitions, dummy_destination_definitions): """ Create a dummy AirbyteDtoFactory given a set of dummy source and destination definitions """ dto_factory = AirbyteDtoFactory(dummy_source_definitions, dummy_destination_definitions) return dto_factory @pytest.fixture def dummy_secrets_dict(): """ Create dummy secrets for the dummy sources and destinations (as dict) """ secrets_dict = { 'sources': { 'GitHub': {'access_token': 'ghp_SECRET_TOKEN'}, 'Slack': {'token': 'SLACK_SECRET_TOKEN'} }, 'destinations': { 'Postgres': {'password': 'SECRET_POSTGRES_PASSWORD'} } } return secrets_dict @pytest.fixture
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from typing import List class QubotConfigTerminalInfo: """ Abstracts information on the terminal nodes to find. """ class QubotConfigModelParameters: """ Abstracts information on the Q-Learning model parameters. """ def __init__(self, alpha=0.5, gamma=0.6, epsilon=1, decay=0.01, train_episodes=1000, test_episodes=100, step_limit=100): """ Initializes the model configuration parameters. :param alpha: Higher alpha => consider more recent information (learning rate). :param gamma: Higher gamma => long term rewards. :param epsilon: Higher epsilon => favor exploitation. :param decay: Higher decay => epsilon decreases faster (more randomness). :param train_episodes: The number of episodes to train Qubot on. :param test_episodes: The number of episodes to test Qubot on. :param step_limit: Maximum number of steps to take before force-exiting the episode. """ self.alpha = alpha self.gamma = gamma self.epsilon = epsilon self.decay = decay self.train_episodes = train_episodes self.test_episodes = test_episodes self.step_limit = step_limit class QubotDriverParameters: """ Abstracts information on the Selenium Driver parameters. """ def __init__(self, use_cache: bool = False, max_urls: int = 10): """ Initializes the Selenium configuration parameters. :param use_cache: Use the cache when scraping the website under test? :param max_urls: Maximum number of recursive URLs to visit during scraping. """ self.use_cache = use_cache self.max_urls = max_urls
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#!/usr/bin/env python3 # coding: utf-8 from __future__ import unicode_literals, print_function from collections import Counter from .db import new_session, Tweet import string import re zh = re.compile(r"[\u4e00-\u9fa5]+") other = re.compile(r"[a-zA-Z0-9_]+") bad = ("_ 1 2 3 4 5 I O RT The a and are be bit co com for gt http https html in " "is it jpg ly me media my not of on org p pbs png r s status t that the this to " "twimg via www you").split() alphanum = set(string.ascii_letters + string.digits) def freq(texts, limit=400, p=12): '''Find the most frequent words and their frequencies in a set of texts. :param texts: a list of strings :type texts: List[str] :param int limit: a soft limit to cut off some words :param int p: longest word length :return: list of words and frequencies :rtype: List[(str, int)] ''' cnt = Counter() cntE = Counter() for l in texts: # find all Chinese for w in zh.findall(l): saw = set() for ln in range(2, p+1): # all length for i in range(len(w)-(ln-1)): # all start pos saw.add(w[i:i+ln].strip('的').lstrip('了')) for v in saw: cnt[v] += 1 # English words and digits for w in other.findall(l): cntE[w] += 1 for w in bad: cntE[w] = 0 # remove # find top `limit` ones freqs = cnt.most_common(limit) # initialize results as top 10 English words & digits results = list(cntE.most_common(10)) # already in results filt = Counter() # from longest to shortest for ln in range(p, 1, -1): # find all with this length but a part of longer ones cur = [(k, v) for k, v in freqs if len(k) == ln] # filter some with `filt` cur = [(k, v) for k, v in cur if k not in filt or filt[k] * 2 < v] cur.sort(key=lambda t: t[1], reverse=True) results.extend(cur) # put all parts into `filt` for w, v in cur: for l in range(2, ln): for i in range(len(w)-(l-1)): filt[w[i:i+l]] += v # print(results) return results if __name__ == '__main__': session = new_session() texts = [i.text for i in session.query(Tweet.text).filter(Tweet.sender == 'masked')] cnt = freq(texts) print(sorted([(v, k) for k, v in cnt], reverse=True))
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from twilio.rest import Client if __name__ == '__main__': from configure import ACCOUNT_SID,AUTO_TOKEN,FROM_NUM,TO_NUM msg = '测试一下,亲爱的路人' send_sms(ACCOUNT_SID,AUTO_TOKEN,FROM_NUM,TO_NUM,msg)
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#!/usr/bin/env python3 import os import sys from pyrevolve import parser from pyrevolve.util import Supervisor here = os.path.dirname(os.path.abspath(__file__)) rvpath = os.path.abspath(os.path.join(here, '..', 'revolve')) sys.path.append(os.path.dirname(os.path.abspath(__file__))) class OnlineEvolutionSupervisor(Supervisor): """ Supervisor class that adds some output filtering for ODE errors """ def write_stderr(self, data): """ :param data: :return: """ if 'ODE Message 3' in data: self.ode_errors += 1 elif data.strip(): sys.stderr.write(data) if self.ode_errors >= 100: self.ode_errors = 0 sys.stderr.write('ODE Message 3 (100)\n') if __name__ == "__main__": settings = parser.parse_args() manager_settings = sys.argv[1:] supervisor = OnlineEvolutionSupervisor( manager_cmd=settings.manager, manager_args=manager_settings, world_file=settings.world, simulator_cmd=settings.simulator_cmd, simulator_args=["--verbose"], plugins_dir_path=os.path.join(rvpath, 'build', 'lib'), models_dir_path=os.path.join(rvpath, 'models') ) if settings.manager is None: ret = supervisor.launch_simulator() else: ret = supervisor.launch() sys.exit(ret)
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#!/usr/bin/python import urllib2 import json import sys from optparse import OptionParser usage = "usage: %prog [options] host" parser = OptionParser(usage = usage) parser.add_option("-t", "--token", dest="token", default="", type='string', help="token") (options, args) = parser.parse_args() if len(args) != 1: parser.print_usage() sys.exit(1) host = args[0] data = { "token": options.token } dataStr = json.dumps(data) print urllib2.urlopen('http://%s/private/refreshStore' % host, dataStr).read()
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# -*- coding: utf-8 -*- from __future__ import unicode_literals import re import difflib import logging import functools from string import punctuation as punct from eplist import utils from eplist.episode import Episode from eplist.settings import Settings try: from bs4 import BeautifulSoup Soup = functools.partial(BeautifulSoup) except ImportError: try: from BeautifulSoup import BeautifulStoneSoup as Soup except ImportError: logging.critical("Error: BeautifulSoup was not found, unable to parse AniDB") priority = 3 anidb_client = 'eprenamer' anidb_version = '1' anidb_proto = '1' anidb_http_url = 'http://api.anidb.net:9001/httpapi?{}' anidb_request = "request=anime&client={}&clientver={}&protover={}&aid={{}}" anidb_request = anidb_request.format(anidb_client, anidb_version, anidb_proto) anidb_http_url = anidb_http_url.format(anidb_request) def _parse_local(title): """ Try to find the anime ID (aid) in the dump file provided by AniDB """ if not utils.file_exists_in_resources('animetitles.dat'): logging.warning("AniDB database file not found, unable to poll AniDB at this time") logging.warning("Try using the --update-db option to download an copy of it") return -1 logging.info("Searching the AniDB database file") title = title.lower() regex = re.compile(r'(?P<aid>\d+)\|(?P<type>\d)\|(?P<lang>.+)\|(?P<title>.*)') sequence = difflib.SequenceMatcher(lambda x: x in punct, title.lower()) guesses = [] with utils.open_file_in_resources('animetitles.dat') as f: for line in f: res = regex.search(line) if not res: continue original_title = utils.encode(res.group('title').lower()) clean_title = utils.prepare_title(utils.encode(res.group('title'))).lower() if utils.prepare_title(title) in (original_title, clean_title): return int(res.group('aid')) sequence.set_seq2(clean_title.lower()) ratio = sequence.quick_ratio() if ratio > .80: d = dict(ratio=ratio, aid=res.group('aid'), title=original_title) guesses.append(d) if guesses: logging.info("{} possibilities".format(len(guesses))) guesses = sorted(guesses, key=lambda x: x['ratio']) aid = guesses[0]['aid'] name = guesses[0]['title'] logging.error("Closest show to '{}' on AniDB is '{}'' with id {}".format(title, name, aid)) for guess in guesses[1:]: logging.info("Similar show {} [{}] also found".format(guess['title'], guess['aid'])) return -1 def _connect_HTTP(aid): """ Connect to AniDB using the public HTTP Api, this is used as an alternative to the UDP connection function """ url = anidb_http_url.format(aid) resp = utils.get_url_descriptor(url) if resp is None: return utils.show_not_found soup = Soup(resp.content) if soup.find('error'): logging.error("Temporally banned from AniDB, most likely due to flooding") return [] episodes = soup.findAll('episode') if not episodes: return utils.show_not_found eplist = [] for e in episodes: # 1 is a normal episode, 2 is a special # with beautifulsoup3 it returns a list of attribute dictionaries # rather than just a single dictionary like in bs4 if 'type' in e.epno.attrs: ep_type = e.epno.attrs['type'] else: ep_type = e.epno.attrs[0][1] if ep_type not in ('1', '2'): continue title = e.find('title', {'xml:lang': 'en'}) title = title.getText() if ep_type == '1': epNum = int(e.epno.getText()) type_ = "Episode" else: epNum = int(e.epno.getText()[1:]) type_ = "OVA" e = Episode(title=title, number=epNum, count=epNum, type=type_) eplist.append(e) return eplist
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import os import numpy as np from dylightful.utilities import load_parsed_dyno, get_dir from dylightful.parser import load_env_partners_mixed from dylightful.bar_plot import make_barplot dirname = os.path.dirname(__file__) save_dir = "/media/julian/INTENSO/ZIKV/" name = "ZIKV-Pro-427-1_dynophore" traj_path = save_dir + name + ".json" prefix = "ligand" pml = save_dir + name + ".pml" ligand_path = save_dir + name + "_time_series.json" topology = save_dir + "topo0.pdb" trajectory = save_dir + "trajectory.dcd" traj_path = os.path.join(dirname, traj_path) time_ser, num_obs = load_parsed_dyno(traj_path=ligand_path) time_ser = time_ser print(type(time_ser)) print(time_ser.shape) print(time_ser[0:2, :]) # traj_path = os.path.join(dirname, traj_path) # env_partners = load_env_partners_mixed(json_path=traj_path) # env_partner_arr = [] # for partner in env_partners.keys(): # env_partner_arr.append(env_partners[partner]) # env_partner_arr = np.array(env_partner_arr) # time_ser = env_partner_arr.T # print(type(time_ser)) # print(time_ser.shape) # print(time_ser[0:2,:]) save_path = get_dir(traj_path) base = save_dir make_barplot( time_ser=time_ser, ylabel="Ligand Perspective", yticks=np.arange(time_ser.shape[1]), prefix=prefix, save_path=save_path, )
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from typing import Optional import click from click import Context from opta.exceptions import UserErrors @click.command() @click.pass_context @click.argument("command", required=False) def help(context: Context, command: Optional[str]) -> None: """ Get help for Opta. Example: opta help opta help apply """ command_context = context.parent.command # type: ignore if command is not None: try: command_context = command_context.commands[command] # type: ignore except KeyError: raise UserErrors( "Invalid Command. Please use correct commands mentioned in `opta help|-h|--help " ) print(command_context.get_help(context))
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from django.conf.urls.defaults import * from django.contrib.comments.feeds import LatestCommentsFeed from django.views.generic.simple import direct_to_template, redirect_to from codereviewr.settings import PROJECT_PATH, DEBUG from codereviewr.feeds import * #feeds dictionary feeds = { 'code': CodeFeed, 'comments': LatestCommentsFeed, 'language': LanguageFeed, 'latest': LatestFeed, 'user': UserFeed, } urlpatterns = patterns('', (r'^code/', include('codereviewr.code.urls')), # Admin (r'^admin/code/language/refresh/$', 'code.views.refresh_languages'), (r'^admin/', include('django.contrib.admin.urls')), # OpenID (r'^openid/$', 'openid_cr.views.begin', {'redirect_to': '/openid/complete/'}), (r'^openid/complete/$', 'openid_cr.views.complete'), (r'^openid/signout/$', 'openid_cr.views.signout'), # account registration (r'^accounts/', include('registration.urls')), #for homepage - testing (r'^$', direct_to_template, {'template': 'homepage.html'}), #Feeds (r'^feeds/(?P<url>.*)/$', 'django.contrib.syndication.views.feed', {'feed_dict': feeds}), ) if DEBUG: urlpatterns += patterns('', (r'^media/(.*)$', 'django.views.static.serve', {'document_root': '%s/../media' % (PROJECT_PATH)}) )
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'''Train CIFAR10 with PyTorch.''' import torch import random import os import argparse from model import get_model from data import get_data, make_planeloader from utils import get_loss_function, get_scheduler, get_random_images, produce_plot, get_noisy_images, AttackPGD from evaluation import decision_boundary from options import options from utils import simple_lapsed_time ''' This module calculates and saves prediction arrays for different saved models. E.g. if you have saved models with the structure: /path/to/saved/models - model_1.pth - model_2.pth - model_3.pth then this script will make a new folder /path/to/saved/models/predictions which will save the following prediction arrays: /path/to/save/models/predictions - model_1_preds.pth - model_2_preds.pth - model_3_preds.pth Note: the original model paths should be of the form: ResNet18.pth ... i.e. the name of the model used should be the same as the model in model.py ''' args = options().parse_args() print(args) device = 'cuda' if torch.cuda.is_available() else 'cpu' torch.manual_seed(args.set_data_seed) trainloader, testloader = get_data(args) paths = [os.path.join(args.load_net, p) for p in os.listdir(args.load_net) if 'pred' not in p] for path in paths: os.makedirs(os.path.join(args.load_net, path, 'predictions'), exist_ok=True) for p in sorted(os.listdir(path)): if 'pred' not in p: if 'wide' in path.lower(): args.net = 'WideResNet' # Here the net path is saved like '/path/to/saved/models/WideResNet_10.pth' args.widen_factor = int(path.split('/')[-1].split('.')[0].split('_')[1]) else: args.net = path.split('/')[-1].split('.')[0] net = get_model(args, device) temp_path = os.path.join(path,p) net.load_state_dict(torch.load(temp_path)) pred_arr = [] for run in range(args.epochs): random.seed(a=(args.set_data_seed+run), version=2) images, labels, image_ids = get_random_images(testloader.dataset) planeloader = make_planeloader(images, args) preds = decision_boundary(args, net, planeloader, device) pred_arr.append(torch.stack(preds).argmax(1).cpu()) torch.save(pred_arr, os.path.join(args.load_net, path, 'predictions') + '/' + temp_path.split('/')[-1].split('.pth')[0] + '_preds.pth')
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"""flatten.py -- Flattens HDF5 dataset. """ import glob import math import os import h5py import numpy as np import scipy.io def flatten(source: str, dest: str, packets_per_chunk: int = 1000, synthetic: bool = False, silent: bool = True, constant_features_path: str = 'constant_features.mat') -> (int, int): """Flatten an HDF5 dataset. :param source: path to original dataset. :param dest: path to store flattened dataset. :param packets_per_chunk: number of packets to process at a time. Ideally the number of symbols per chunk is < 1000. :param synthetic: flag the source dataset as being synthetic (changes data input format). :param silent: suppress output. :param constant_features_path: path to constant features. :return: tuple containing the number of (symbols, packets) converted. """ data = h5py.File(source, 'r') num_packets = len(data['rxLltfFftOut1']) # Load constant features. This contains the indices for data and pilot tones. constant_features = scipy.io.loadmat(constant_features_path, squeeze_me=True) constant_features = constant_features['constant'] # Values in `constant_features.mat` are one-indexed so we subtract one for zero-indexed. he_ltf_data_indices = constant_features['iMDataTone_Heltf'][()].astype(np.int32) - 1 he_ltf_pilot_indices = constant_features['iMPilotTone_Heltf'][()].astype(np.int32) - 1 data_indices = constant_features['iMDataTone_HePpdu'][()].astype(np.int32) - 1 pilot_indices = constant_features['iMPilotTone_HePpdu'][()].astype(np.int32) - 1 # Create the file to write the data to. output = h5py.File(dest, 'w') for chunk in range(math.ceil(num_packets / packets_per_chunk)): chunk_indices = np.arange(chunk * packets_per_chunk, min((chunk + 1) * packets_per_chunk, num_packets)) # Fixes bug with h5py version on TACC. chunk_indices = list(chunk_indices) # Load L-LTF fields. rx_l_ltf_1 = np.array(data['rxLltfFftOut1'][chunk_indices]) rx_l_ltf_2 = np.array(data['rxLltfFftOut2'][chunk_indices]) # Load HE-LTF and split into data and pilot. rx_he_ltf = np.array(data['rxHeltfFftOut'][chunk_indices]) rx_he_ltf_data = rx_he_ltf[:, he_ltf_data_indices] rx_he_ltf_pilot = rx_he_ltf[:, he_ltf_pilot_indices] # Load RX and TX data symbols and split into data and pilot, keeping track of the corresponding LTF fields. # FIXME: This is very slow. On the other hand, I can't be bothered to make it faster since it only runs once. ltf_indices = [] rx_symbols = [] rx_ref_data = [] tx_symbols = [] if synthetic: for i, j in enumerate(chunk_indices): iterator = (data['rxHePpduFftOut'][j], data['rxHePpdutoneMappedFreq'][j], data['txConstellation'][j]) for rx_symbol, rx_ref_symbol, tx_symbol in zip(*iterator): ltf_indices.append(i) rx_symbols.append(rx_symbol) rx_ref_data.append(rx_ref_symbol) tx_symbols.append(tx_symbol) else: for i, j in enumerate(chunk_indices): iterator = (data[f'rxHePpduFftOut{j}'], data[f'rxHePpdutoneMappedFreq{j}'], data[f'txConstellation{j}']) for rx_symbol, rx_ref_symbol, tx_symbol in zip(*iterator): ltf_indices.append(i) rx_symbols.append(rx_symbol) rx_ref_data.append(rx_ref_symbol) tx_symbols.append(tx_symbol) num_symbols = len(ltf_indices) ltf_indices = np.array(ltf_indices) rx_symbols = np.array(rx_symbols) rx_ref_data = np.array(rx_ref_data) tx_symbols = np.array(tx_symbols) rx_data = rx_symbols[:, data_indices] rx_pilot = rx_symbols[:, pilot_indices] tx_data = tx_symbols[:, data_indices] tx_pilot = tx_symbols[:, pilot_indices] # Duplicate the entries in the LTF fields so that we have `num_symbols` entries. rx_l_ltf_1 = np.array([rx_l_ltf_1[ltf_indices[i]] for i in range(num_symbols)]) rx_l_ltf_2 = np.array([rx_l_ltf_2[ltf_indices[i]] for i in range(num_symbols)]) rx_he_ltf_data = np.array([rx_he_ltf_data[ltf_indices[i]] for i in range(num_symbols)]) rx_he_ltf_pilot = np.array([rx_he_ltf_pilot[ltf_indices[i]] for i in range(num_symbols)]) # Lump the arrays together and save them. arrays = { 'rx_l_ltf_1': rx_l_ltf_1, 'rx_l_ltf_2': rx_l_ltf_2, 'rx_he_ltf_data': rx_he_ltf_data, 'rx_he_ltf_pilot': rx_he_ltf_pilot, 'rx_data': rx_data, 'rx_pilot': rx_pilot, 'rx_ref_data': rx_ref_data, 'tx_data': tx_data, 'tx_pilot': tx_pilot } for key, value in arrays.items(): if key not in output: output.create_dataset(name=key, data=value, maxshape=(None, *value.shape[1:]), chunks=True) else: output[key].resize(output[key].shape[0] + value.shape[0], axis=0) output[key][-value.shape[0]:] = value if not silent: print(f'Wrote {num_symbols} symbols in {len(chunk_indices)} packets.') if not silent: print(f'TOTAL: {output["rx_l_ltf_1"].shape[0]} symbols in {num_packets} packets.') return output['rx_l_ltf_1'].shape[0], num_packets def flatten_dir(source_dir: str, dest_dir: str, packets_per_chunk: int = 1000, synthetic: bool = False, silent: bool = True, force: bool = False, constant_features_path: str = 'constant_features.mat') -> (int, int): """Flatten all HDF5 files in a directory and place them in another. :param source_dir: source directory. :param dest_dir: destination directory. :param packets_per_chunk: number of packets to process at a time. :param synthetic: flag the source dataset as being synthetic (changes data input format). :param silent: suppress output. :param force: force reprocessing of already-processed files. :param constant_features_path: path to constant features. :return: tuple containing the number of (symbols, packets) converted. """ total_symbols = 0 total_packets = 0 for source in glob.glob(f'{source_dir}/*.h5'): if 'flat' in source: if not silent: print(f'{source} is already flattened. Skipping.') print() continue dest = f'{dest_dir}/{os.path.splitext(os.path.basename(source))[0]}_flat.h5' if not force and os.path.exists(dest): if not silent: print(f'{dest_dir} exists. Skipping.') print() continue num_symbols, num_packets = flatten(source, dest, packets_per_chunk, synthetic=synthetic, silent=silent, constant_features_path=constant_features_path) total_symbols += num_symbols total_packets += num_packets if not silent: print() if not silent: print(f'TOTAL: {total_symbols} symbols in {total_packets} packets.') if __name__ == '__main__': main()
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import string import unicodedata SLUG_CHARS_DISPLAY = '[a-z0-9-]' _SLUG_CHARS = string.ascii_lowercase + string.digits + '-' _SLUG_SIZE = 50 def slugify(text): '''Returns the slug of a string (that can be used in an URL for example.''' slug = unicodedata.normalize('NFKD', text).encode('ascii', 'ignore') slug = slug.decode('utf-8').lower().replace(' ', '-') slug = ''.join(c for c in slug if c in _SLUG_CHARS) return slug[:_SLUG_SIZE]
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from scapy.all import * ap_list = [] sniff(iface='en0', prn=ssid, count=10, timeout=3, store=0) # for packet in sniff(offline='sample.pcap', prn=changePacketParameters): # packets.append(packet) # for packet in packets: # if packet.haslayer(TCP): # writeToPcapFile(packet) # print(packet.show())
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import capnp import tarfile import io from .session import get_active_session from ..common import RainException, ids, ID from ..common.attributes import attributes_to_capnp from ..common.content_type import check_content_type, encode_value from ..common import DataType def blob(value, label="const", content_type=None, encode=None): """ Create a constant data object with accompanying data. Given `value` may be either `bytes` or any object to be encoded with `encoding` content type. Strings are encoded with utf-8 by default. Specify at most one of `content_type` and `encode`. """ if content_type is not None: if encode is not None: raise RainException("Specify only one of content_type and encode") if not isinstance(value, bytes): raise RainException("content_type only allowed for `bytes`") if encode is None and isinstance(value, str): encode = "text:utf-8" if content_type is not None: raise RainException("content_type not allowed for `str`, use `encode=...`") if encode is not None: check_content_type(encode) value = encode_value(value, content_type=encode) content_type = encode if not isinstance(value, bytes): raise RainException( "Invalid blob type (only str or bytes are allowed without `encode`)") dataobj = DataObject(label, content_type=content_type) dataobj.data = value return dataobj def pickled(val, label="pickle"): """ Create a data object with pickled `val`. A shorthand for `blob(val, ancode='pickle')`. The default label is "pickle". """ return blob(val, encode='pickle', label=label) def to_data(obj): """Convert an object to DataObject/DataObjectPart""" if isinstance(obj, DataObject): return obj from .task import Task if isinstance(obj, Task): if len(obj.outputs) == 1: return obj.outputs[0] if len(obj.outputs) == 0: raise RainException("{} does not have any output".format(obj)) else: raise RainException("{} returns multiple outputs".format(obj)) if isinstance(obj, str) or isinstance(obj, bytes): raise RainException( "Instance of {!r} cannot be used as a data object.\n" "Hint: Wrap it with `blob` to use it as data object." .format(type(obj))) raise RainException( "Instance of {!r} cannot be used as a data object.\n" "Hint: Wrap it with `pickled` or `blob(encode=...)` to use it as a data object." .format(type(obj)))
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# Copyright 2021 NVIDIA Corporation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from legate.pandas.common import types as ty from legate.pandas.config import OpCode from legate.pandas.core.pattern import Map, Projection, ScalarMap
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""" Django settings for backend project. Generated by 'django-admin startproject' using Django 2.1.4. Since the start of the project, we have upgraded the version to 2.1.7 For more information on this file, see https://docs.djangoproject.com/en/2.1/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.1/ref/settings/ """ import os import datetime # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.1/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = "%qviowlmp*kitbai+y!%1y=jdl_o3_#7+_ud6l9uwn$$=bxt1y" ALLOWED_HOSTS = "*" CORS_ORIGIN_ALLOW_ALL = True # Application definition INSTALLED_APPS = [ # Personal, "custom_models", # BASE "django.contrib.admin", "django.contrib.auth", "django.contrib.contenttypes", "django.contrib.sessions", "django.contrib.messages", "django.contrib.staticfiles", # Requirements "corsheaders", "rest_framework", "djoser", "rest_framework_swagger", "rest_framework.authtoken", ] MIDDLEWARE = [ "django.middleware.security.SecurityMiddleware", "django.contrib.sessions.middleware.SessionMiddleware", "django.middleware.common.CommonMiddleware", "django.middleware.csrf.CsrfViewMiddleware", "django.contrib.auth.middleware.AuthenticationMiddleware", "django.contrib.messages.middleware.MessageMiddleware", "django.middleware.clickjacking.XFrameOptionsMiddleware", "corsheaders.middleware.CorsMiddleware", ] ROOT_URLCONF = "config.urls" WSGI_APPLICATION = "config.wsgi.application" TEMPLATES = [ { "BACKEND": "django.template.backends.django.DjangoTemplates", "DIRS": [], "APP_DIRS": True, "OPTIONS": { "context_processors": [ "django.template.context_processors.debug", "django.template.context_processors.request", "django.contrib.auth.context_processors.auth", "django.contrib.messages.context_processors.messages", ] }, } ] # Password validation # https://docs.djangoproject.com/en/2.1/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { "NAME": "django.contrib.auth.password_validation.UserAttributeSimilarityValidator" }, {"NAME": "django.contrib.auth.password_validation.MinimumLengthValidator"}, {"NAME": "django.contrib.auth.password_validation.CommonPasswordValidator"}, {"NAME": "django.contrib.auth.password_validation.NumericPasswordValidator"}, ] REST_FRAMEWORK = { "DEFAULT_PERMISSION_CLASSES": ( "rest_framework.permissions.IsAuthenticatedOrReadOnly", ), "DEFAULT_AUTHENTICATION_CLASSES": ( "rest_framework.authentication.SessionAuthentication", "rest_framework.authentication.BasicAuthentication", "rest_framework_jwt.authentication.JSONWebTokenAuthentication", ), } LANGUAGE_CODE = "en-us" TIME_ZONE = "Canada/Eastern" USE_I18N = True USE_L10N = True USE_TZ = True CORS_ALLOW_HEADERS = [ "accept", "accept-encoding", "authorization", "content-disposition", "content-type", "origin", "user-agent", "x-csrftoken", "x-requested-with", ] # Allow the user to log in by email or username AUTH_USER_MODEL = "custom_models.User" # JWT settings for authentication JWT_AUTH = { "JWT_EXPIRATION_DELTA": datetime.timedelta(hours=1), "JWT_ALLOW_REFRESH": True, } SIMPLE_JWT = {"AUTH_HEADER_TYPES": ("JWT",)} # Swagger settings for documentation SWAGGER_SETTINGS = { "LOGIN_URL": "rest_framework:login", "LOGOUT_URL": "rest_framework:logout", } # Djoser settings for Rest Login (https://djoser.readthedocs.io/en/latest/settings.html) DJOSER = { "SET_PASSWORD_RETYPE": True, "SEND_ACTIVATION_EMAIL": False, "PERMISSIONS": { # Admin Only "activation": ["rest_framework.permissions.IsAdminUser"], # "set_username": ["rest_framework.permissions.IsAdminUser"], "user_delete": ["rest_framework.permissions.IsAdminUser"], "user_list": ["rest_framework.permissions.IsAdminUser"], "password_reset": ["rest_framework.permissions.IsAdminUser"], # Authenticated "token_destroy": ["rest_framework.permissions.IsAuthenticated"], # Current User or Admin "user": ["djoser.permissions.CurrentUserOrAdmin"], "set_password": ["djoser.permissions.CurrentUserOrAdmin"], # Any "password_reset_confirm": ["rest_framework.permissions.AllowAny"], "user_create": ["rest_framework.permissions.AllowAny"], "token_create": ["rest_framework.permissions.AllowAny"], }, }
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from openrec.tf1.recommenders.recommender import Recommender from openrec.tf1.recommenders.bpr import BPR from openrec.tf1.recommenders.pmf import PMF from openrec.tf1.recommenders.ucml import UCML from openrec.tf1.recommenders.vbpr import VBPR from openrec.tf1.recommenders.vanilla_youtube_rec import VanillaYouTubeRec from openrec.tf1.recommenders.youtube_rec import YouTubeRec from openrec.tf1.recommenders.rnn_rec import RNNRec
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import copy import itertools import os import time import numpy as np import pandas as pd import scipy.io as scio import yaml import factorAnalysisIOTools as IOTools from factorAnalysisCalTools import prepare_RET_dict, time_horizon_dict if __name__ == '__main__': config_path = r"D:\HX_proj\factorAnalysis\updateStockPoolConfig.yaml" updateSP = UpdateStockPool(config_path) updateSP.update_stock_info() updateSP.update_stock_pool_basic() updateSP.update_stock_HS300() updateSP.update_stock_ZZ500() updateSP.update_stock_ZZ800() stock_pool_name = 'STOCK_POOL_basic' stock_pool_path = f"E:\\data\\interday\\{stock_pool_name}.pkl" update_benchmark_return(stock_pool_path=stock_pool_path,stock_pool_name=stock_pool_name,benchmark_ret_save_dir = r"E:\data\interday")
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""" Running operational space control with the PyGame display. The arm will move the end-effector to a target orientation, which can be changed by pressing the left/right arrow keys. """ import numpy as np from os import environ environ['PYGAME_HIDE_SUPPORT_PROMPT'] = '1' import pygame from abr_control.arms import threejoint as arm # from abr_control.arms import twojoint as arm from abr_control.interfaces import PyGame from abr_control.utils import transformations from abr_control.controllers import OSC, Damping # initialize our robot config robot_config = arm.Config(use_cython=True) # create our arm simulation arm_sim = arm.ArmSim(robot_config) # damp the movements of the arm damping = Damping(robot_config, kv=10) # create operational space controller ctrlr = OSC(robot_config, kp=50, null_controllers=[damping], # control (gamma) out of [x, y, z, alpha, beta, gamma] ctrlr_dof = [False, False, False, False, False, True]) # create our interface interface = PyGame(robot_config, arm_sim, dt=.001, on_keypress=on_keypress) interface.connect() interface.theta = -3 * np.pi / 4 feedback = interface.get_feedback() R = robot_config.R('EE', feedback['q']) interface.on_keypress(interface, None) try: print('\nSimulation starting...') print('Press left or right arrow to change target orientation angle.\n') count = 0 while 1: # get arm feedback feedback = interface.get_feedback() hand_xyz = robot_config.Tx('EE', feedback['q']) target = np.hstack([np.zeros(3), interface.target_angles]) u = ctrlr.generate( q=feedback['q'], dq=feedback['dq'], target=target, ) # apply the control signal, step the sim forward interface.send_forces( u, update_display=True if count % 20 == 0 else False) count += 1 finally: # stop and reset the simulation interface.disconnect() print('Simulation terminated...')
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# coding=utf-8 import pytest import epab.utils from epab.utils import _next_version as nv @pytest.mark.long
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from __future__ import absolute_import from irods.message import iRODSMessage, StringStringMap, RodsHostAddress, STR_PI, MsParam, MsParamArray, RuleExecutionRequest from irods.api_number import api_number from io import open as io_open from irods.message import Message, StringProperty
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# Array showing guitar string's relative pitches, in semi-tones, with "0" being low E # ["Low E", "A", "D", "G", "B", "High E"] strings = [40, 45, 50, 55, 60, 65];
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from apscheduler.schedulers.background import BackgroundScheduler from apscheduler.triggers.cron import CronTrigger from kalliope.core.ConfigurationManager import BrainLoader from kalliope.core.SynapseLauncher import SynapseLauncher from kalliope.core import Utils from kalliope.core.Models import Event
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""" turtle-example-suite: tdemo_nim.py Play nim against the computer. The player who takes the last stick jest the winner. Implements the model-view-controller design pattern. """ zaimportuj turtle zaimportuj random zaimportuj time SCREENWIDTH = 640 SCREENHEIGHT = 480 MINSTICKS = 7 MAXSTICKS = 31 HUNIT = SCREENHEIGHT // 12 WUNIT = SCREENWIDTH // ((MAXSTICKS // 5) * 11 + (MAXSTICKS % 5) * 2) SCOLOR = (63, 63, 31) HCOLOR = (255, 204, 204) COLOR = (204, 204, 255) dla z w range(3): s = state[z] ^ xored jeżeli s <= state[z]: move = (z, s) zwróć move rand = random.randint(m > 1, state[z]-1) zwróć z, rand klasa NimModel(object): albo_inaczej self.player == 0: self.player = 1 row, col = computerzug(self.sticks) self.move(row, col) self.player = 0 def game_over(self): zwróć self.sticks == [0, 0, 0] def notify_move(self, row, col): jeżeli self.sticks[row] <= col: zwróć self.move(row, col) klasa Stick(turtle.Turtle): self.game.controller.notify_move(self.row, self.col) klasa NimView(object): self.display("... a moment please ...") self.screen.tracer(Prawda) def display(self, msg1, msg2=Nic): self.screen.tracer(Nieprawda) self.writer.clear() jeżeli msg2 jest nie Nic: self.writer.goto(0, - SCREENHEIGHT // 2 + 48) self.writer.pencolor("red") self.writer.write(msg2, align="center", font=("Courier",18,"bold")) self.writer.goto(0, - SCREENHEIGHT // 2 + 20) self.writer.pencolor("black") self.writer.write(msg1, align="center", font=("Courier",14,"bold")) self.screen.tracer(Prawda) def setup(self): self.screen.tracer(Nieprawda) dla row w range(3): dla col w range(self.model.sticks[row]): self.sticks[(row, col)].color(SCOLOR) dla row w range(3): dla col w range(self.model.sticks[row], MAXSTICKS): self.sticks[(row, col)].color("white") self.display("Your turn! Click leftmost stick to remove.") self.screen.tracer(Prawda) def notify_move(self, row, col, maxspalte, player): jeżeli player == 0: farbe = HCOLOR dla s w range(col, maxspalte): self.sticks[(row, s)].color(farbe) inaczej: self.display(" ... thinking ... ") time.sleep(0.5) self.display(" ... thinking ... aaah ...") farbe = COLOR dla s w range(maxspalte-1, col-1, -1): time.sleep(0.2) self.sticks[(row, s)].color(farbe) self.display("Your turn! Click leftmost stick to remove.") def notify_over(self): jeżeli self.game.model.winner == 0: msg2 = "Congrats. You're the winner!!!" inaczej: msg2 = "Sorry, the computer jest the winner." self.display("To play again press space bar. To leave press ESC.", msg2) def clear(self): jeżeli self.game.state == Nim.OVER: self.screen.clear() klasa NimController(object): self.game.screen.onkey(self.game.model.setup, "space") self.game.screen.onkey(self.game.view.clear, "Escape") self.game.view.display("Press space bar to start game") self.game.screen.listen() def notify_move(self, row, col): jeżeli self.BUSY: zwróć self.BUSY = Prawda self.game.model.notify_move(row, col) self.BUSY = Nieprawda klasa Nim(object): CREATED = 0 RUNNING = 1 OVER = 2 def main(): mainscreen = turtle.Screen() mainscreen.mode("standard") mainscreen.setup(SCREENWIDTH, SCREENHEIGHT) nim = Nim(mainscreen) zwróć "EVENTLOOP" jeżeli __name__ == "__main__": main() turtle.mainloop()
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#Author : Nemuel Wainaina import socket from colorama import init, Fore #some color, haha init() GREEN = Fore.GREEN BLUE = Fore.BLUE RED = Fore.RED GRAY = Fore.LIGHTBLACK_EX RESET = Fore.RESET def is_port_open(target, port): ''' This function simply attempts to create a connection to the target machine on the specified port and based on whether or not the connection is successful, prints to the user whether or not the port is open ''' try: s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.connect((target, port)) print(f"{GREEN}[+] Port {port} is Open {RESET}") return True except: #Comment out the line in order to exclude the results for closed ports print(f"{GRAY}[-] Port {port} is Closed {RESET}") return False finally: s.close()
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import numpy as np import os import json import cv2 import sys np.random.seed(2020) # to ensure you always get the same train/test split data_path = '../data/RedLights2011_Medium' gts_path = '../data/hw02_annotations' split_path = '../data/hw02_splits' os.makedirs(split_path, exist_ok=True) # create directory if needed split_test = True # set to True and run when annotations are available train_frac = 0.85 # get sorted list of files: file_names = sorted(os.listdir(data_path)) # remove any non-JPEG files: file_names = [f for f in file_names if '.jpg' in f] # split file names into train and test file_names_train = [] file_names_test = [] np.random.shuffle(file_names) file_names_train = file_names[0:(int(train_frac * len(file_names)))] file_names_test = file_names[(int(train_frac * len(file_names))):] assert (len(file_names_train) + len(file_names_test)) == len(file_names) assert len(np.intersect1d(file_names_train,file_names_test)) == 0 np.save(os.path.join(split_path,'file_names_train.npy'),file_names_train) np.save(os.path.join(split_path,'file_names_test.npy'),file_names_test) # Function for viewing annotations one by one if needed if split_test: with open(os.path.join(gts_path, 'formatted_annotations_students.json'),'r') as f: gts = json.load(f) # Use file_names_train and file_names_test to apply the split to the # annotations gts_train = {} gts_test = {} for i in range(len(file_names_train)): gts_train[file_names_train[i]] = gts[file_names_train[i]] for i in range(len(file_names_test)): gts_test[file_names_test[i]] = gts[file_names_test[i]] with open(os.path.join(gts_path, 'annotations_train.json'),'w') as f: json.dump(gts_train,f) with open(os.path.join(gts_path, 'annotations_test.json'),'w') as f: json.dump(gts_test,f)
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import logging from watchFaceParser.models.elements.basic.compositeElement import CompositeElement
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import logging import time import typing from urllib.parse import urlparse, parse_qs import fire YGO_SCHEME = 'ygo' YGO_NETLOC = 'deck' DEFAULT_HEADER = '#created by ...\n' CARD_SEP_SYM = '_' CARD_MULTI_SYM = '*' DEFAULT_SYM = '#' NO_SYM = '!' MAIN_HEADER = 'main\n' EXTRA_HEADER = 'extra\n' SIDE_HEADER = 'side\n' DEFAULT_YDK_NAME: str = "default" + "_" + str(int(time.time())) if __name__ == '__main__': fire.Fire(save_file)
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# -*- coding: utf-8 -*- """Tests for the MDWeb Navigation parser. Tests to write * Handle symlinks * File already open * Non supported extension (.xls) * Permissions Maybe test? * atime, mtime * large file """ import datetime from pyfakefs import fake_filesystem_unittest from unittest import skip try: # Python >= 3.3 from unittest import mock except ImportError: # Python < 3.3 import mock from mdweb.Page import PageMetaInf, Page, load_page from mdweb.Exceptions import ( PageMetaInfFieldException, PageParseException, ContentException, ) class TestPageMeta(fake_filesystem_unittest.TestCase): """PageMetaInf object tests.""" def setUp(self): """Create fake filesystem.""" self.setUpPyfakefs() def test_parse_empty_string(self): """Empty string should parse successfully.""" file_string = u"" meta_inf = PageMetaInf(file_string) self.assertIsNone(meta_inf.author) self.assertIsNone(meta_inf.date) self.assertIsNone(meta_inf.description) self.assertIsNone(meta_inf.nav_name) self.assertEqual(meta_inf.order, 0) self.assertIsNone(meta_inf.template) self.assertIsNone(meta_inf.title) def test_parse_some_fields(self): """A few defined fields should parse successfully.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Date: February 1st, 2016 """ meta_inf = PageMetaInf(file_string) self.assertIsNone(meta_inf.author) self.assertEqual(meta_inf.date, datetime.datetime(2016, 2, 1, 0, 0)) self.assertEqual(meta_inf.description, u'The minimalistic markdown NaCMS') self.assertEqual(meta_inf.order, 0) self.assertIsNone(meta_inf.template) self.assertEqual(meta_inf.title, u'MDWeb') def test_parse_all_fields(self): """All available fields should parse successfully.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Author: Chad Rempp Date: February 1st, 2016 Order: 1 Template: page_home.html Nav Name: Home Page Sitemap Changefreq: Monthly Sitemap Priority: 0.5 Teaser: This is a teaser paragraph that will be availble to pages Teaser Image: /contentassets/home/00041_thumb.jpg """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.author, u'Chad Rempp') self.assertEqual(meta_inf.date, datetime.datetime(2016, 2, 1, 0, 0)) self.assertEqual(meta_inf.description, u'The minimalistic markdown NaCMS') self.assertEqual(meta_inf.order, 1) self.assertEqual(meta_inf.template, u'page_home.html') self.assertEqual(meta_inf.title, u'MDWeb') self.assertEqual(meta_inf.nav_name, u'Home Page') self.assertEqual(meta_inf.sitemap_changefreq, u'Monthly') self.assertEqual(meta_inf.sitemap_priority, u'0.5') self.assertEqual(meta_inf.teaser, u'This is a teaser paragraph that will be availble to pages') self.assertEqual(meta_inf.teaser_image, u'/contentassets/home/00041_thumb.jpg') def test_metainf_spacing(self): """Spacing should not matter in parsing.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Author: Chad Rempp Date : February 1st, 2016 Order: 1 Template: page_home.html """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.author, u'Chad Rempp') self.assertEqual(meta_inf.date, datetime.datetime(2016, 2, 1, 0, 0)) self.assertEqual(meta_inf.description, u'The minimalistic markdown NaCMS') self.assertEqual(meta_inf.order, 1) self.assertEqual(meta_inf.template, u'page_home.html') self.assertEqual(meta_inf.title, u'MDWeb') def test_comments(self): """Comments should be skipped during parsing.""" file_string = u"""# This is a comment Title: MDWeb Description: The minimalistic markdown NaCMS #Author: Chad Rempp #Date: February 1st, 2016 Order: 1 Template: page_home.html # # Nothing to see here """ meta_inf = PageMetaInf(file_string) self.assertIsNone(meta_inf.author) self.assertIsNone(meta_inf.date) self.assertEqual(meta_inf.description, u'The minimalistic markdown NaCMS') self.assertEqual(meta_inf.order, 1) self.assertEqual(meta_inf.template, u'page_home.html') self.assertEqual(meta_inf.title, u'MDWeb') def test_unicode(self): """Parser should handle unicode.""" file_string = u"""Title: советских Description: ᚠᛇᚻ᛫ᛒᛦᚦ᛫ᚠᚱᚩᚠᚢᚱ᛫ᚠᛁᚱᚪ᛫ᚷᛖᚻᚹᛦᛚᚳᚢᛗ Author: Οδυσσέα Ελύτη Date: February 1st, 2016 Order: 1 Template: ღმერთსი.html """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.author, u'Οδυσσέα Ελύτη') self.assertEqual(meta_inf.date, datetime.datetime(2016, 2, 1, 0, 0)) self.assertEqual(meta_inf.description, u'ᚠᛇᚻ᛫ᛒᛦᚦ᛫ᚠᚱᚩᚠᚢᚱ᛫ᚠᛁᚱᚪ᛫ᚷᛖᚻᚹᛦᛚᚳᚢᛗ') self.assertEqual(meta_inf.order, 1) self.assertEqual(meta_inf.template, u'ღმერთსი.html') self.assertEqual(meta_inf.title, u'советских') def test_parse_multiline_field(self): """Multiline fields should parse successfully.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Author: Chad Rempp Date: February 1st, 2016 Order: 1 Template: page_home.html Nav Name: Home Page Sitemap Changefreq: Monthly Sitemap Priority: 0.5 Teaser: This is a teaser paragraph that will be available to pages and the teaser may span multiple lines indented with whitespace even if the line looks like a metainf field Not A Field: This won't get parsed as a field Teaser Image: /contentassets/home/00041_thumb.jpg """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.teaser, u'This is a teaser paragraph that will be available to pages and the teaser may span multiple lines indented with whitespace even if the line looks like a metainf field Not A Field: This won\'t get parsed as a field') def test_parse_custom_field(self): """Multiline fields should parse successfully.""" file_string = u"""Title: MDWeb Description: The minimalistic markdown NaCMS Author: Chad Rempp Summary Image: blah.jpg """ meta_inf = PageMetaInf(file_string) self.assertEqual(meta_inf.custom_summary_image, u'blah.jpg') @skip def test_unpublished_page(self): """Unpublished pages should have the correct attr value.""" self.assertEqual(1, 2) class TestPage(fake_filesystem_unittest.TestCase): """Page object tests.""" def setUp(self): """Create fake filesystem.""" self.setUpPyfakefs() def test_page_instantiation(self): """A page should be instantiated with appropriate attributes.""" file_string = u"This is a page" self.fs.create_file('/my/content/about/history.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/about/history.md')) self.assertEqual(page.page_path, '/my/content/about/history.md') self.assertEqual(page.url_path, 'about/history') self.fs.create_file('/my/content/super/deep/url/path/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/super/deep/url/path/index.md')) self.assertEqual(page.page_path, '/my/content/super/deep/url/path/index.md') self.assertEqual(page.url_path, 'super/deep/url/path') def test_unparsable_path(self): """An unparsable page path should raise PageParseException.""" file_string = u"" self.fs.create_file('/my/content/index', contents=file_string) # Not an MD file self.assertRaises(PageParseException, load_page, '/my/content', '/my/content/index') @mock.patch('mdweb.Page.PageMetaInf') def test_repr(self, mock_page_meta_inf): """A Page object should return the proper repr.""" file_string = u"" self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) self.assertEqual(str(page), '/my/content/index.md') @mock.patch('mdweb.Page.PageMetaInf') def test_parse_empty_file(self, mock_page_meta_inf): """An empty file should parse properly.""" file_string = u"" self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with('') self.assertEqual(page.markdown_str, '') self.assertEqual(page.page_html, '') def test_no_file(self): """If the path has no file a ContentException should be raised.""" self.assertRaises(ContentException, load_page, '/my/content', '/my/content/index.md') @mock.patch('mdweb.Page.PageMetaInf') def test_no_meta_inf(self, mock_page_meta_inf): """A page with no meta information should parse.""" # pylint: disable=C0301 # pylint: disable=E501 file_string = u"""Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.""" self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with('') self.assertEqual(page.markdown_str, '''Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''') self.assertEqual(page.page_html, '''<p>Now is the time for all good men to come to the aid of their country. This is just a regular paragraph.</p> <p>The quick brown fox jumped over the lazy dog's back.</p>''') @mock.patch('mdweb.Page.PageMetaInf') def test_page_with_meta_inf(self, mock_page_meta_inf): """A page with meta info should parse the content and meta inf.""" file_string = '''```metainf Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ``` Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''' self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with(''' Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ''') self.assertEqual(page.markdown_str, ''' Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back.''') self.assertEqual(page.page_html, '''<p>Now is the time for all good men to come to the aid of their country. This is just a regular paragraph.</p> <p>The quick brown fox jumped over the lazy dog's back.</p>''') @mock.patch('mdweb.Page.PageMetaInf') def test_page_with_slash_star_slash(self, mock_page_meta_inf): """A page with /*/ in the content should parse corectly. Regression test for https://github.com/crempp/mdweb/issues/47""" file_string = '''```metainf Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ``` Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. This is a link that blows up the parser [asdf](https://web.archive.org/web/*/http://site.com) The quick brown fox jumped over the lazy dog's back.''' self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with(''' Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ''') self.assertEqual(page.markdown_str, ''' Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. This is a link that blows up the parser [asdf](https://web.archive.org/web/*/http://site.com) The quick brown fox jumped over the lazy dog's back.''') self.assertEqual(page.page_html, '''<p>Now is the time for all good men to come to the aid of their country. This is just a regular paragraph.</p> <p>This is a link that blows up the parser <a href="https://web.archive.org/web/*/http://site.com">asdf</a></p> <p>The quick brown fox jumped over the lazy dog's back.</p>''') @mock.patch('mdweb.Page.PageMetaInf') def test_page_with_second_metainf(self, mock_page_meta_inf): """A page with a second metainf should only parse the first""" file_string = '''```metainf Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ``` Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. Here is another metainf block ```metainf Title: Fake Block ``` The quick brown fox jumped over the lazy dog's back.''' self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with(''' Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ''') self.assertEqual(page.markdown_str, ''' Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. Here is another metainf block ```metainf Title: Fake Block ``` The quick brown fox jumped over the lazy dog's back.''') self.assertEqual(page.page_html, '''<p>Now is the time for all good men to come to the aid of their country. This is just a regular paragraph.</p> <p>Here is another metainf block <code>metainf Title: Fake Block</code></p> <p>The quick brown fox jumped over the lazy dog's back.</p>''') @mock.patch('mdweb.Page.PageMetaInf') def test_markdown_formatting(self, mock_page_meta_inf): """Markdown should parse correctly. We won't test this extensively as we should trust the markdown libraries to test themselves. """ file_string = '''```metainf Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ``` Examples taken from https://daringfireball.net/projects/markdown/basics A First Level Header ==================== A Second Level Header --------------------- Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back. ### Header 3 > This is a blockquote. > > This is the second paragraph in the blockquote. > > ## This is an H2 in a blockquote --------------------------------------- Some of these words *are emphasized*. Some of these words _are emphasized also_. Use two asterisks for **strong emphasis**. Or, if you prefer, __use two underscores instead__. --------------------------------------- * Candy. * Gum. * Booze. --------------------------------------- 1. Red 2. Green 3. Blue --------------------------------------- * A list item. With multiple paragraphs. * Another item in the list. --------------------------------------- This is an [example link](http://example.com/). This is an [example link](http://example.com/ "With a Title"). --------------------------------------- I get 10 times more traffic from [Google][1] than from [Yahoo][2] or [MSN][3]. [1]: http://google.com/ "Google" [2]: http://search.yahoo.com/ "Yahoo Search" [3]: http://search.msn.com/ "MSN Search" I start my morning with a cup of coffee and [The New York Times][NY Times]. [ny times]: http://www.nytimes.com/ --------------------------------------- ![alt text](/path/to/img.jpg "Title") ![alt text][id] [id]: /path/to/img.jpg "Title" --------------------------------------- I strongly recommend against using any `<blink>` tags. I wish SmartyPants used named entities like `&mdash;` instead of decimal-encoded entites like `&#8212;`. If you want your page to validate under XHTML 1.0 Strict, you've got to put paragraph tags in your blockquotes: <blockquote> <p>For example.</p> </blockquote> ---------------------------------------''' self.fs.create_file('/my/content/index.md', contents=file_string) page = Page(*load_page('/my/content', '/my/content/index.md')) mock_page_meta_inf.assert_called_once_with(''' Title: MDWeb Examples Description: Examples of how to use MDWeb Order: 4 ''') self.assertEqual(page.markdown_str, ''' Examples taken from https://daringfireball.net/projects/markdown/basics A First Level Header ==================== A Second Level Header --------------------- Now is the time for all good men to come to the aid of their country. This is just a regular paragraph. The quick brown fox jumped over the lazy dog's back. ### Header 3 > This is a blockquote. > > This is the second paragraph in the blockquote. > > ## This is an H2 in a blockquote --------------------------------------- Some of these words *are emphasized*. Some of these words _are emphasized also_. Use two asterisks for **strong emphasis**. Or, if you prefer, __use two underscores instead__. --------------------------------------- * Candy. * Gum. * Booze. --------------------------------------- 1. Red 2. Green 3. Blue --------------------------------------- * A list item. With multiple paragraphs. * Another item in the list. --------------------------------------- This is an [example link](http://example.com/). This is an [example link](http://example.com/ "With a Title"). --------------------------------------- I get 10 times more traffic from [Google][1] than from [Yahoo][2] or [MSN][3]. [1]: http://google.com/ "Google" [2]: http://search.yahoo.com/ "Yahoo Search" [3]: http://search.msn.com/ "MSN Search" I start my morning with a cup of coffee and [The New York Times][NY Times]. [ny times]: http://www.nytimes.com/ --------------------------------------- ![alt text](/path/to/img.jpg "Title") ![alt text][id] [id]: /path/to/img.jpg "Title" --------------------------------------- I strongly recommend against using any `<blink>` tags. I wish SmartyPants used named entities like `&mdash;` instead of decimal-encoded entites like `&#8212;`. If you want your page to validate under XHTML 1.0 Strict, you've got to put paragraph tags in your blockquotes: <blockquote> <p>For example.</p> </blockquote> ---------------------------------------''') # pylint: disable=C0301 # pylint: disable=E501 self.assertEqual(page.page_html, '''<p>Examples taken from https://daringfireball.net/projects/markdown/basics</p> <h1>A First Level Header</h1> <h2>A Second Level Header</h2> <p>Now is the time for all good men to come to the aid of their country. This is just a regular paragraph.</p> <p>The quick brown fox jumped over the lazy dog's back.</p> <h3>Header 3</h3> <blockquote> <p>This is a blockquote.</p> <p>This is the second paragraph in the blockquote.</p> <h2>This is an H2 in a blockquote</h2> </blockquote> <hr /> <p>Some of these words <em>are emphasized</em>. Some of these words <em>are emphasized also</em>.</p> <p>Use two asterisks for <strong>strong emphasis</strong>. Or, if you prefer, <strong>use two underscores instead</strong>.</p> <hr /> <ul> <li>Candy.</li> <li>Gum.</li> <li>Booze.</li> </ul> <hr /> <ol> <li>Red</li> <li>Green</li> <li>Blue</li> </ol> <hr /> <ul> <li> <p>A list item.</p> <p>With multiple paragraphs.</p> </li> <li> <p>Another item in the list.</p> </li> </ul> <hr /> <p>This is an <a href="http://example.com/">example link</a>.</p> <p>This is an <a href="http://example.com/" title="With a Title">example link</a>.</p> <hr /> <p>I get 10 times more traffic from <a href="http://google.com/" title="Google">Google</a> than from <a href="http://search.yahoo.com/" title="Yahoo Search">Yahoo</a> or <a href="http://search.msn.com/" title="MSN Search">MSN</a>.</p> <p>I start my morning with a cup of coffee and <a href="http://www.nytimes.com/">The New York Times</a>.</p> <hr /> <p><img alt="alt text" src="/path/to/img.jpg" title="Title" /></p> <p><img alt="alt text" src="/path/to/img.jpg" title="Title" /></p> <hr /> <p>I strongly recommend against using any <code>&lt;blink&gt;</code> tags.</p> <p>I wish SmartyPants used named entities like <code>&amp;mdash;</code> instead of decimal-encoded entites like <code>&amp;#8212;</code>.</p> <p>If you want your page to validate under XHTML 1.0 Strict, you've got to put paragraph tags in your blockquotes:</p> <pre><code>&lt;blockquote&gt; &lt;p&gt;For example.&lt;/p&gt; &lt;/blockquote&gt; </code></pre> <hr />''')
[ 2, 532, 9, 12, 19617, 25, 3384, 69, 12, 23, 532, 9, 12, 198, 37811, 51, 3558, 329, 262, 10670, 13908, 42115, 30751, 13, 198, 198, 51, 3558, 284, 3551, 198, 220, 1635, 33141, 5659, 28751, 198, 220, 1635, 9220, 1541, 1280, 198, 220,...
2.538434
8,456
if __name__ == '__main__': run()
[ 628, 628, 198, 198, 361, 11593, 3672, 834, 6624, 705, 834, 12417, 834, 10354, 198, 220, 220, 220, 1057, 3419, 628 ]
2.095238
21
# This is actually not even needed apparently # pytest_plugins = ["harvest"]
[ 2, 770, 318, 1682, 407, 772, 2622, 5729, 198, 2, 12972, 9288, 62, 37390, 796, 14631, 9869, 4223, 8973 ]
4
19
#fly from .ModelIO import ModelIO from .ModelConfig import ModelConfig
[ 2, 12254, 201, 198, 6738, 764, 17633, 9399, 1330, 9104, 9399, 201, 198, 6738, 764, 17633, 16934, 1330, 9104, 16934, 201, 198, 201, 198 ]
3.166667
24
""" Simple data classes for storing feedback to present to learners. """ __all__ = ['Feedback', 'FeedbackKind', 'FeedbackCategory', "CompositeFeedbackFunction", "FeedbackResponse"] from pedal.core.formatting import FeedbackFieldWrapper from pedal.core.location import Location from pedal.core.report import MAIN_REPORT from pedal.core.feedback_category import FeedbackKind, FeedbackCategory, FeedbackStatus PEDAL_DEVELOPERS = ["Austin Cory Bart <acbart@udel.edu>", "Luke Gusukuma <lukesg08@vt.edu>"] class Feedback: """ A class for storing raw feedback. Attributes: label (str): An internal name for this specific piece of feedback. The label should be an underscore-separated string following the same conventions as names in Python. They do not have to be globally unique, but labels should be as unique as possible (especially within a category). tool (str, optional): An internal name for indicating the tool that created this feedback. Should be taken directly from the Tool itself. If `None`, then this was not created by a tool but directly by the control script. category (str): A human-presentable name showable to the learner, indicating what sort of feedback this falls into (e.g., "runtime", "syntax", "algorithm"). More than one feedback will be in a category, but a feedback cannot be in more than one category. kind (str): The pedagogical role of this feedback, e.g., "misconception", "mistake", "hint", "constraint". Usually, a piece of Feedback is pointing out a mistake, but feedback can also be used for various other purposes. justification (str): An instructor-facing string briefly describing why this feedback was selected. Serves as a "TL;DR" for this feedback category, useful for debugging why a piece of feedback appeared. priority (str): An indication of how important this feedback is relative to other types of feedback in the same category. Might be "high/medium/low". Exactly how this gets used is up to the resolver, but typicaly it helps break ties. valence (int): Indicates whether this is negative, positive, or neutral feedback. Either 1, -1, or 0. title (str, optional): A formal, student-facing title for this feedback. If None, indicates that the :py:attr:`~pedal.core.feedback.Feedback.label` should be used instead. message (str): A markdown-formatted message (aka also supporting HTML) that could be rendered to the user. message_template (str): A markdown-formatted message template that will be used if a ``message`` is None. Any ``fields`` will be injected into the template IF the ``condition`` is met. fields (Dict[str,Any]): The raw data that was used to interpolate the template to produce the message. location (:py:attr:`~pedal.core.location.Location` or int): Information about specific locations relevant to this message. score (int): A numeric score to modify the students' total score, indicating their overall performance. It is ultimately up to the Resolver to decide how to combine all the different scores; a typical strategy would be to add all the scores together for any non-muted feedback. correct (bool): Indicates that the entire submission should be considered correct (success) and that the task is now finished. muted (bool): Whether this piece of feedback is something that should be shown to a student. There are various use cases for muted feedback: they can serve as flags for later conditionals, suppressed default kinds of feedback, or perhaps feedback that is interesting for analysis but not pedagogically helpful to give to the student. They will still contribute to overall score, but not to the correcntess of the submission. unscored (bool): Whether or not this piece of feedback contributes to the score/correctness. else_message (str): A string to render as a message when a NEGATIVE valence feedback is NOT triggered, or a POSITIVE valence feedback IS triggered. TODO: Should we also have an else_message_template? Probably. activate (bool): Used for default feedback objects without a custom condition, to indicate whether they should be considered triggered. Defaults to True; setting this to False means that the feedback object will be deactivated. Note that most inheriting Feedback Functions will not respect this parameter. author (List[str]): A list of names/emails that indicate who created this piece of feedback. They can be either names, emails, or combinations in the style of `"Cory Bart <acbart@udel.edu>"`. version (str): A version string in the style of Semantic Version (semvar) such as `"0.0.1"`. The last (third) digit should be incremented for small bug fixes/changes. The middle (second) digit should be used for more serious and intense changes. The first digit should be incremented when changes are made on exposure to learners or some other evidence-based motivation. tags (list[:py:class:`~pedal.core.tag.Tag`]): Any tags that you want to attach to this feedback. parent (int, str, or `pedal.core.feedback.Feedback`): Information about what logical grouping within the submission this belongs to. Various tools can chunk up a submission (e.g., by section), they can use this field to keep track of how that decision was made. Resolvers can also use this information to organize feedback or to report multiple categories. report (:py:class:`~pedal.core.report.Report`): The Report object to attach this feedback to. Defaults to MAIN_REPORT. Unspecified fields will be filled in by inspecting the current Feedback Function context. """ POSITIVE_VALENCE = 1 NEUTRAL_VALENCE = 0 NEGATIVE_VALENCE = -1 CATEGORIES = FeedbackCategory KINDS = FeedbackKind label = None category = None justification = None constant_fields = None fields = None field_names = None kind = None title = None message = None message_template = None else_message = None priority = None valence = None location = None score = None correct = None muted = None unscored = None tool = None version = '1.0.0' author = PEDAL_DEVELOPERS tags = None parent = None activate: bool _status: str _exception: Exception or None _met_condition: bool _stored_args: tuple _stored_kwargs: dict #MAIN_REPORT def _handle_condition(self): """ Actually handle the condition check, updating message and report. """ # Self-attach to a given report? self._exception = None try: self._met_condition = self.condition(*self._stored_args, **self._stored_kwargs) # Generate the message field as needed if self._met_condition: self.message = self._get_message() self._status = FeedbackStatus.ACTIVE else: self._status = FeedbackStatus.INACTIVE except Exception as e: self._met_condition = False self._exception = e self._status = FeedbackStatus.ERROR if self.report is not None: if self._met_condition: self.report.add_feedback(self) else: self.report.add_ignored_feedback(self) # Free up these temporary fields after condition is handled # del self._stored_args # del self._stored_kwargs if self._exception is not None: raise self._exception def condition(self, *args, **kwargs): """ Detect if this feedback is present in the code. Defaults to true through the `activate` parameter. Returns: bool: Whether or not this feedback's condition was detected. """ return self.activate def _get_message(self): """ Determines the appropriate value for the message. It will attempt to use this instance's message, but if it's not available then it will try to generate one from the message_template. Then, it returns a generic message. You can override this to create a truly dynamic message, if you want. Returns: str: The message for this feedback. """ if self.message is not None: return self.message if self.message_template is not None: fields = {field: FeedbackFieldWrapper(field, value, self.report.format) for field, value in self.fields.items()} return self.message_template.format(**fields) return "No feedback message provided" def _get_child_feedback(self, feedback, active): """ Callback function that Reports will call when a new piece of feedback is being considered. By default, does nothing. This is useful for :py:class:`pedal.core.group.FeedbackGroup`, most other feedbacks will just not care. The ``active`` parameter controls whether or not the condition for the feedback was met. """ def __str__(self): """ Create a string representation of this piece of Feedback for quick, dev purposes. Returns: str: String representation """ return "<Feedback ({},{})>".format(self.category, self.label) def __repr__(self): """ Create a string representation of this piece of Feedback that displays considerably more information. Returns: str: String representation with more data """ metadata = "" if self.tool is not None: metadata += ", tool=" + self.tool if self.category is not None: metadata += ", category=" + self.category if self.priority is not None: metadata += ", priority=" + self.priority if self.parent is not None: metadata += ", parent=" + str(self.parent.label) return "Feedback({}{})".format(self.label, metadata) def update_location(self, location): """ Updates both the fields and location attribute. TODO: Handle less information intelligently. """ if isinstance(location, int): location = Location(location) self.location = location self.fields['location'] = location class FeedbackResponse(Feedback): """ An extension of :py:class:`~pedal.core.feedback.Feedback` that is meant to indicate that the class should not have any condition behind its response. """ def CompositeFeedbackFunction(*functions): """ Decorator for functions that return multiple types of feedback functions. Args: functions (callable): A list of callable functions. Returns: callable: The decorated function. """ def CompositeFeedbackFunction_with_attrs(function): """ Args: function: Returns: """ CompositeFeedbackFunction_with_attrs.functions = functions return function return CompositeFeedbackFunction_with_attrs class FeedbackGroup(Feedback): """ An extension of :py:class:`~pedal.core.feedback.Feedback` that is meant to indicate that this class will start a new Group context within the report and do something interesting with any children it gets. """ DEFAULT_CATEGORY_PRIORITY = [ "highest", # Static Feedback.CATEGORIES.SYNTAX, Feedback.CATEGORIES.MISTAKES, Feedback.CATEGORIES.INSTRUCTOR, Feedback.CATEGORIES.ALGORITHMIC, # Dynamic Feedback.CATEGORIES.RUNTIME, Feedback.CATEGORIES.STUDENT, Feedback.CATEGORIES.SPECIFICATION, Feedback.CATEGORIES.POSITIVE, Feedback.CATEGORIES.INSTRUCTIONS, Feedback.CATEGORIES.UNKNOWN, "lowest" ]
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from pathlib import Path from fhir.resources.codesystem import CodeSystem from oops_fhir.utils import CodeSystemConcept __all__ = ["PrecisionEstimateType"] _resource = CodeSystem.parse_file(Path(__file__).with_suffix(".json")) class PrecisionEstimateType: """ PrecisionEstimateType Method of reporting variability of estimates, such as confidence intervals, interquartile range or standard deviation. Status: draft - Version: 4.0.1 Copyright None http://terminology.hl7.org/CodeSystem/precision-estimate-type """ ci = CodeSystemConcept( { "code": "CI", "definition": "confidence interval.", "display": "confidence interval", } ) """ confidence interval confidence interval. """ iqr = CodeSystemConcept( { "code": "IQR", "definition": "interquartile range.", "display": "interquartile range", } ) """ interquartile range interquartile range. """ sd = CodeSystemConcept( { "code": "SD", "definition": "standard deviation.", "display": "standard deviation", } ) """ standard deviation standard deviation. """ se = CodeSystemConcept( {"code": "SE", "definition": "standard error.", "display": "standard error"} ) """ standard error standard error. """
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""" Author : A. Emerick Date : May 2016 Purpose: """ __author__ = "aemerick <emerick@astro.columbia.edu>" # external import numpy as np #from collections import OrderedDict import os, h5py from scipy.interpolate import interp1d try: import dill as pickle except: print("WARNING: Dill unavailable, attempting to use pickle, which may crash") try: import pickle as pickle except: print("WARNING: cPickle unavailable, using pickle - data dumps will be slow") import pickle # internal from . import imf as imf #from . import star as star from onezone.cython_ext import cython_star as star from . import config as config from .constants import CONST as const from . import performance_tools as perf def restart(filename): """ Restart evolution from chosen picked output file """ zone = pickle.load( open(filename, 'r')) zone.evolve() return class Zone: """ Zone Class Single zone gas reservoir attached to star formation and chemical enrichment models. Parameters for a given simulation can be set using config. Zone initializes a simulation using initial conditions parameters set in config. Once initialized and abundances are set, simulation can be evolved: >>> sim = Zone() >>> sim.set_initial_abundances(list_of_element_names) >>> sim.evolve() I/O controlled by config parameters, but can be done manually with a full (pickle) dump or an output of summary statistics: >>> sim.write_full_pickle() >>> sim.write_summary_output() """ def set_initial_abundances(self, elements, abundances = None): """ Set initial abundances using a list of desired elements and associated abundances. If no abundances are provided, all are set to zero except H and He. Abundances dict does not have to be complete """ self.initial_abundances = {} # OrderedDict() if abundances == None: abundances = {'empty' : 0.0} for e in elements: if e in abundances.keys(): self.initial_abundances[e] = abundances[e] elif e == 'H': self.initial_abundances[e] = 0.75*(1.0 - self.Z) elif e == 'He': self.initial_abundances[e] = 0.25*(1.0 - self.Z) elif e == 'm_metal': self.initial_abundances[e] = self.Z elif e == 'm_tot': self.initial_abundances[e] = 1.0 else: self.initial_abundances[e] = 0.0 for e in self.initial_abundances.keys(): self.species_masses[e] = self.M_gas * self.initial_abundances[e] self.halo_masses[e] = 0.0 # # One day, set this as list with second list of conditionals # so one can (at runtime) arbitrarily track on any condition # self.special_mass_accumulator = {} # OrderedDict() self.special_mass_accumulator['m_massive'] = 0.0 return None def _accumulate_new_sn(self): """ Looks through all stars, checking to see if any new SN or SNIa occured in current timestep. Adds these to the counters """ star_type = list(self.all_stars.property_asarray('type')) #if np.size(star_type) > 1: self.N_SNIa += star_type.count('new_SNIa_remnant') self.N_SNII += star_type.count('new_remnant') return def evolve(self): """ Evolves the system until the end time assigned in config, using a constant timestep. This handles the formation of new stars, gas inflow and outflow, enrichment from stars, and outputs. """ config.global_values.profiler.start_timer("total_time",True) while self.t <= config.zone.t_final: config.global_values.profiler.start_timer('compute_dt') self._compute_dt() config.global_values.profiler.end_timer('compute_dt') # # Check if output conditions are met # config.global_values.profiler.start_timer('check_output') self._check_output() config.global_values.profiler.end_timer('check_output') # # I) Evolve stars, computing ejecta rates and abundances # config.global_values.profiler.start_timer('evolve_stars') self._evolve_stars() config.global_values.profiler.end_timer('evolve_stars') # # II) Sum up and store number of supernovae # config.global_values.profiler.start_timer('accumulate_sn') self._accumulate_new_sn() config.global_values.profiler.end_timer('accumulate_sn') # # III) Compute SFR and make new stars # config.global_values.profiler.start_timer('compute_sfr') self._compute_sfr() config.global_values.profiler.end_timer('compute_sfr') config.global_values.profiler.start_timer('make_stars') self.M_sf = self._make_new_stars() config.global_values.profiler.end_timer('make_stars') # # IV) Compute inflow and outflow # config.global_values.profiler.start_timer('outflow_inflow_mdot') self._compute_outflow() self._compute_inflow() self._compute_mdot_dm() config.global_values.profiler.end_timer('outflow_inflow_mdot') # # V) Add/remove gas from zone due to inflow, # outflow, SF, and stellar ejecta # abundances = self.abundances temp1 = abundances['m_metal'] * 1.0 new_gas_mass = self.M_gas + (self.Mdot_in + self.Mdot_ej_masses['m_tot'] -\ self.Mdot_out) * self.dt - self.M_sf +\ self.SN_ej_masses['m_tot'] # # VI) Check if reservoir is empty # if self.M_gas <= 0: self.M_gas = 0.0 _my_print("Gas in zone depleted. Ending simulation") break # # VII) Compute increase / decrease of individual abundances # for e in self.species_masses.keys(): self.species_masses[e] = self.species_masses[e] + (self.Mdot_in * self.Mdot_in_abundances(e) +\ self.Mdot_ej_masses[e] -\ self.Mdot_out_species[e]) * self.dt -\ self.M_sf * abundances[e] + self.SN_ej_masses[e] self.halo_masses[e] = self.halo_masses[e] + self.Mdot_out_species[e] * self.dt # no halo accretion for now. self.M_gas = new_gas_mass self.M_DM = self.M_DM + self.Mdot_DM * self.dt # # VII) i) ensure metallicity is consistent with new abundances # self._update_metallicity() # # VIII) End of evolution, increment counters # config.global_values.profiler.start_timer('update_globals') self.t += self.dt self._cycle_number += 1 self._update_globals() config.global_values.profiler.end_timer('update_globals') outstr = "======================================================\n" +\ "===== Cycle = %00005i time = %5.5E =======\n"%(self._cycle_number,self.t) +\ "======================================================\n" config.global_values.profiler.write_performance(outstr=outstr) # # At end of simulation, force summary and dump # outputs # config.global_values.profiler.end_timer("total_time") config.global_values.profiler.write_performance(outstr=outstr) self._check_output(force=True) self._clean_up() return @property @property def abundances(self): """ Returns dictionary of abundances """ abund = {} for x in self.species_masses.keys(): abund[x] = self.species_masses[x] / self.M_gas return abund @property def Mdot_in_abundances(self, e): """ Inflow abundances """ if e == 'H': abund = 0.75 elif e == 'He': abund = 0.25 elif e == 'm_tot': abund = 1.0 else: abund = 0.0 return abund @property @property def _evolve_stars(self): """ Evolve stars using star list methods, and compute the total amount of ejecta from winds and supernova """ # # zero mass accumulators before evolving # for key in self.species_masses.keys(): self.Mdot_ej_masses[key] = 0.0 self.SN_ej_masses[key] = 0.0 # # advance each star one timestep # optional mass arguments mean stars add # to ejecta bins during evolution (winds and SN) # to limit number of loops through star list # self.all_stars.evolve(self.t, self.dt, ej_masses = self.Mdot_ej_masses, sn_masses = self.SN_ej_masses, special_accumulator = self.special_mass_accumulator) self.Mdot_ej = self.Mdot_ej_masses['m_tot'] * config.units.time for e in self.species_masses.keys(): self.Mdot_ej_masses[e] *= config.units.time return # # set total dM/dt from all stellar winds # # self.Mdot_ej = 0.0 # mass_loss_rate = self.all_stars.property_asarray('Mdot_ej') * config.units.time # self.Mdot_ej = np.sum( mass_loss_rate ) # # set dM/dt for all species # add up SN ejecta # # i = 0 # for e in self.species_masses.iterkeys(): # # add wind ejecta abundaces from "stars" and stars that may have formed SN # but were alive for part of timestep. # # self.Mdot_ej_masses[e] = np.sum(self.all_stars.species_asarray('Mdot_ej_' + e, 'star') * self.all_stars.property_asarray('Mdot_ej','star')) # self.Mdot_ej_masses[e] += np.sum(self.all_stars.species_asarray('Mdot_ej_' + e, 'new_WD') * self.all_stars.property_asarray('Mdot_ej', 'new_WD')) # self.Mdot_ej_masses[e] += np.sum(self.all_stars.species_asarray('Mdot_ej_' + e, 'new_remnant') * self.all_stars.property_asarray('Mdot_ej','new_remnant')) # self.Mdot_ej_masses[e] *= config.units.time # # self.SN_ej_masses[e] = np.sum(self.all_stars.species_asarray('SN_ej_' + e, 'new_SNIa_remnant')) # self.SN_ej_masses[e] += np.sum(self.all_stars.species_asarray('SN_ej_' + e, 'new_remnant')) # i = i + 1 # # # # return def _make_new_stars(self, M_sf = -1): """ Sample IMF to make new stars. Includes methods to handle low SFR's, i.e. when SFR * dt < maximum star mass """ # # compute the amount of gas to convert # into stars this timestep. Otherwise, make fixed # mass of stars # if (M_sf < 0.0): M_sf = self.dt * self.Mdot_sf if config.zone.use_SF_mass_reservoir and M_sf > 0.0: # # Accumulate mass into "reservoir" and wait until # this is surpassed to form stars # self._M_sf_reservoir += M_sf if (self._M_sf_reservoir > config.zone.SF_mass_reservoir_size): # sample from IMF until M_sf is reached M_sf = self._M_sf_reservoir self._M_sf_reservoir = 0.0 # reset counter else: M_sf = 0.0 elif (config.zone.use_stochastic_mass_sampling and\ M_sf < config.zone.stochastic_sample_mass) and M_sf > 0.0: # # Prevent undersampling the IMF by requiring minimum mass # threshold. Allow SF to happen stochastically when M_sf is # below this threshold # probability_of_sf = M_sf / config.zone.stochastic_sample_mass if (probability_of_sf > np.random.random()): M_sf = config.zone.stochastic_sample_mass else: M_sf = 0.0 # # Make new stars if M_gas->star > 0 # if M_sf > 0.0: # sample from IMF and sum sampled stars # to get actual star formation mass config.global_values.profiler.start_timer('make_stars-imf',True) star_masses = config.zone.imf.sample(M = M_sf) config.global_values.profiler.end_timer('make_stars-imf') M_sf = np.sum(star_masses) if config.zone.minimum_star_particle_mass > 0: select = star_masses > config.zone.minimum_star_particle_mass i_unresolved = 0 if np.size(star_masses[star_masses<=config.zone.minimum_star_particle_mass]) > 0: i_unresolved = 1 # add each new star to the star list ids = np.zeros(np.size(star_masses[select]) + i_unresolved) if np.size(ids) == 1: ids = [ids] i = 0 config.global_values.profiler.start_timer('make_stars-add',True) for i,m in enumerate(star_masses[select]): ids[i] = self._assign_particle_id() self.all_stars.add_new_star( star.Star(M=m,Z=self.Z, abundances=self.abundances, tform=self.t,id=ids[i])) if i_unresolved > 0: if i > 0: i = i + 1 ids[i] = self._assign_particle_id() M_unresolved = np.sum( star_masses[star_masses<=config.zone.minimum_star_particle_mass]) self.all_stars.add_new_star( star.Star(M=M_unresolved,Z=self.Z, abundances=self.abundances,tform=self.t, id= ids[i], star_type = "unresolved_star")) config.global_values.profiler.end_timer('make_stars-add') else: # add each new star to the star list ids = np.zeros(np.size(star_masses)) for i,m in enumerate(star_masses): ids[i] = self._assign_particle_id() self.all_stars.add_new_star( star.Star(M=m, Z=self.Z, abundances=self.abundances, tform=self.t,id=ids[i])) return M_sf def _assign_particle_id(self): """ Generates unique, consecutive ID for particle """ if (not hasattr(self, '_global_id_counter')): self._global_id_counter = 0 num = self._global_id_counter self._global_id_counter += 1 return num def _compute_mdot_dm(self): """ For cosmological simulations, computes growth of DM halo """ self.Mdot_DM = 0.0 if not config.zone.cosmological_evolution: return self.Mdot_DM = 46.1 * ( self.M_DM / 1.0E12 )**(1.1) *\ (1.0 + 1.11 * self.current_redshift) *\ np.sqrt( config.units.omega_matter * (1.0 + self.current_redshift)**3 + config.units.omega_lambda) self.Mdot_DM *= const.yr_to_s self.Mdot_DM /= config.units.time return def _compute_inflow(self): """ Compute inflow rate, as a function of outflow """ self.Mdot_in = config.zone.inflow_factor * self.Mdot_out return def _compute_outflow(self): """ Compute outflow rate, as a function of SFR """ # If either of the discrete SF sampling methods are used, # outflow should be determined by mass of stars formed, not # rate factor = config.zone.mass_loading_factor if config.zone.cosmological_evolution: factor = factor * (1.0 + self.current_redshift)**(-config.zone.mass_loading_index/2.0) elif config.zone.mass_outflow_method == 1: # mass outflow is controlled by a mass loading factor parameter if config.zone.use_SF_mass_reservoir or config.zone.use_stochastic_mass_sampling: self.Mdot_out = config.zone.mass_loading_factor * self.M_sf / self.dt else: self.Mdot_out = config.zone.mass_loading_factor * self.Mdot_sf elif config.zone.mass_outflow_method == 4: self.Mdot_out = self._interpolate_tabulated_outflow('m_tot') * config.zone.outflow_factor * self.Mdot_sf * self.M_gas for e in self.Mdot_out_species.keys(): self.Mdot_out_species[e] = self.Mdot_ej_masses[e] * config.zone.wind_ejection_fraction +\ (self.SN_ej_masses[e] * config.zone.sn_ejection_fraction / self.dt) for e in ['H','He']: # throw out ambient self.Mdot_out_species[e] = self.Mdot_out * self.abundances[e] elif config.zone.mass_outflow_method == 2 or config.zone.mass_outflow_method == 3: # these are fractional outflow rates: self.Mdot_out = self._interpolate_tabulated_outflow('m_tot') # get total outflow rate for e in self.Mdot_out_species.keys(): self.Mdot_out_species[e] = self._interpolate_tabulated_outflow(e) # for each species if config.zone.mass_outflow_method == 2: # outflow depends on sfr # multiply by SFR and current total amount of each species self.Mdot_out = self.Mdot_out * self.Mdot_sf * self.M_gas for e in self.Mdot_out_species.keys(): self.Mdot_out_species[e] = self.Mdot_out_species[e] * self.Mdot_sf * (self.M_gas * self.abundances[e]) else: # outflow is a fixed fraction of injection - use mass loading factor for total, H, and He self.Mdot_out = config.zone.mass_loading_factor * (self.M_sf / self.dt) for e in self.abundances.keys(): self.Mdot_out_species[e] = (self.Mdot_ej_masses[e] + self.SN_ej_masses[e]) / self.dt # converted to a rate for consistency #if 'H' in self.Mdot_out_species.keys(): self.Mdot_out_species['H'] = self.Mdot_out * self.abundances['H'] #if 'He' in self.Mdot_out_species.keys(): self.Mdot_out_species['He'] = self.Mdot_out * self.abundances['He'] return @property def _compute_sfr(self): """ Compute SFR using method set in config """ if config.zone.star_formation_method == 0: # no star formation self.Mdot_sf = 0.0 elif config.zone.star_formation_method == 1: # constant, user supplied SFR self.Mdot_sf = config.zone.constant_SFR elif config.zone.star_formation_method == 2 : self.Mdot_sf = config.zone.SFR_efficiency * self.M_gas elif config.zone.star_formation_method == 3: self.Mdot_sf = config.zone.SFR_dyn_efficiency * self.M_gas / self.t_dyn elif config.zone.star_formation_method == 4 : # interpolate SFR from tabulated SFH self.Mdot_sf = self._interpolate_SFR() return def _check_output(self, force = False): """ Checks output conditions, output if any are met """ if force: self.write_output() self.write_full_pickle() self.write_summary_output() return # # Otherwise output based on user supplied conditions # # # check for full write out # if( (self.t - self._t_last_dump) >= config.io.dt_dump and\ config.io.dt_dump > 0 ): self._t_last_dump = self.t self.write_output() if( self._cycle_number == 0 or\ ((self._cycle_number - self._cycle_last_dump) >= config.io.cycle_dump )\ and config.io.cycle_dump > 0 ): self._cycle_last_dump = self._cycle_number self.write_output() if( (self.t - self._t_last_pickle) >= config.io.dt_pickle and\ config.io.dt_pickle > 0 ): self._t_last_pickle = self.t self.write_full_pickle() if( self._cycle_number == 0 or\ ((self._cycle_number - self._cycle_last_pickle) >= config.io.cycle_pickle )\ and config.io.cycle_pickle > 0 ): self._cycle_last_pickle = self._cycle_number self.write_full_pickle() # # now check for partial (summary) writes # if( self._cycle_number == 0 or\ (self._cycle_number - self._cycle_last_summary >= config.io.cycle_summary)\ and config.io.cycle_summary > 0): self._cycle_last_summary = self._cycle_number self.write_summary_output() if( ((self.t - self._t_last_summary) > config.io.dt_summary) and config.io.dt_summary > 0 ): self._t_last_summary = self.t self.write_summary_output() return def write_output(self): """ Output the full information needed to reconstruct the simulation. This is the mass, metallicity, birth mass, age, abundance, and type for each star, along with the current gas mass, dark matter mass, sfr, and gas abundances. """ # make an HDF5 file to write out to name = config.io.dump_output_basename + "_%0004i"%(self._output_number) + '.h5' hf = h5py.File(name, 'w') zone_grp = hf.create_group('zone') star_grp = hf.create_group('star') params = hf.create_group('parameters') # save parameters for param_list, grpname in [ (config.units,'units'),\ (config.zone,'zone'),\ (config.stars,'stars'),\ (config.io,'io'), (config.data,'data_table')]: subgrp = params.create_group(grpname) for p in dir(param_list): # There may be a better way to do this, but I don't want to have # to explicityly state any params, just print all. Need to skip # all objects or functions though if ('__' in p) or\ callable( getattr(param_list, p))\ or (p[0] == '_') or p == 'imf': continue #print p, getattr(param_list,p) val = getattr(param_list,p) if val is None: val = "None" subgrp.attrs[p] = val # # save meta-data as attributes # self._accumulate_summary_data() hf.attrs['current_time'] = self.t # # Save zone parameters. This is anything to do with gas or DM # properties zone_grp.attrs['M_gas'] = self.M_gas zone_grp.attrs['M_DM'] = self.M_DM zone_grp.attrs['M_star'] = self._summary_data['M_star'] zone_grp.attrs['M_star_o'] = self._summary_data['M_star_o'] zone_grp.attrs['Z_gas'] = self.Z for e in self.abundances.keys(): zone_grp.attrs[e] = self.abundances[e] zone_grp.attrs[e + '_mass'] = self.species_masses[e] # # Save star parameters as lists of values # star_dict = {} # OrderedDict() _gather_properties = { 'mass' : 'mass', 'birth_mass' : 'birth_mass', 'metallicity' : 'metallicity', 'age' : 'age'} for k in _gather_properties: star_dict[k] = np.asarray(self.all_stars.property_asarray( _gather_properties[k])) star_dict['type'] = np.asarray(self.all_stars.property_asarray('type')).astype('S') Nstars = np.size(star_dict['mass']) if Nstars > 1: # there has to be a better way to do this... but various iterations # of the below did not work b/c of the different variable types... # doing this the slow way...... # star_data = [None]*Nstars # for i in np.arange(Nstars): # star_data[i] = (star_dict['id'][i], star_dict['type'][i], # star_dict['initial_mass'][i], # star_dict['masses'][i], star_dict['age'][i], # star_dict['metallicity'][i]) # star_data = np.array(star_data, dtype = [ ('id',star_dict['id'].dtype), # ('type',star_dict['type'].dtype), # ('birth_mass',star_dict['initial_mass'].dtype), # ('mass',star_dict['masses'].dtype), # ('age',star_dict['age'].dtype), # ('metallicity',star_dict['metallicity'].dtype)]) # star_data = np.column_stack( # (star_dict['masses'].astype('float64'), star_dict['initial_mass'].astype('float64'), # star_dict['metallicity'].astype('float64'), star_dict['id'].astype('int64'), # star_dict['type'].astype('str'), # star_dict['age'].astype('float64'))).ravel().view([ ('mass', np.dtype('float64')), # ('initial_mass', np.dtype('float64')), # ('metallicity', np.dtype('float64')), # ('id', np.dtype('int64')), # ('type', np.dtype('str')), # ('age', np.dtype('float64'))]) for k in star_dict.keys(): star_grp.create_dataset(k, data=star_dict[k]) else: Nstars = 0 star_data = np.zeros(1) for k in star_dict.keys(): star_grp.create_dataset(k, data = star_data) star_grp.attrs['number_of_stars'] = Nstars hf.close() self._output_number += 1 return def write_full_pickle(self): """ Pickle current simulation """ name = str(config.io.pickle_output_basename + "_%00004i"%(self.pickle_output_number)) _my_print("Writing full dump output as " + name + " at time t = %4.4f"%(self.t)) pickle.dump( self , open(name, "wb"), -1) self.pickle_output_number += 1 return def _accumulate_summary_data(self): """ Set up list of all of the data to output. Sum over particle properties to do this. """ self._summary_data = {} # OrderedDict() self._summary_data['t'] = self.t self._summary_data['M_gas'] = self.M_gas self._summary_data['M_DM'] = self.M_DM self._summary_data['M_star'] = np.sum(self.all_stars.M()) self._summary_data['M_star_o'] = np.sum( self.all_stars.M_o()) self._summary_data['Z_gas'] = self.Z self._summary_data['Z_star'] = np.average( self.all_stars.Z() ) self._summary_data['N_star'] = self.N_stars self._summary_data['N_SNIa'] = self.N_SNIa self._summary_data['N_SNII'] = self.N_SNII sum_names = ['Mdot_ej', 'L_FUV', 'L_LW', 'Q0', 'Q1'] for n in sum_names: self._summary_data[n] = np.sum(np.asarray(self.all_stars.property_asarray(n))) self._summary_data['L_bol'] = np.sum(np.asarray(self.all_stars.property_asarray('luminosity'))) self._summary_data['L_wind'] = np.sum(np.asarray(self.all_stars.property_asarray('mechanical_luminosity'))) self._summary_data['L_Q0'] = np.sum(self.all_stars.property_asarray('Q0') * self.all_stars.property_asarray('E0')) self._summary_data['L_Q1'] = np.sum(self.all_stars.property_asarray('Q1') * self.all_stars.property_asarray('E1')) # now do all of the abundances for e in self.abundances.keys(): self._summary_data[e] = self.abundances[e] self._summary_data[e + '_mass'] = self.species_masses[e] self._summary_data[e + '_halo_mass'] = self.halo_masses[e] for key in self.special_mass_accumulator.keys(): self._summary_data[key] = self.special_mass_accumulator[key] if config.io.radiation_binned_output: condition_1 = {'mass': lambda x : (x.M_o >= 1.0) * (x.M_o < 8.0) * (x.properties['type'] == 'star')} condition_2 = {'mass': lambda x : (x.M_o >= 8.0) * (x.M_o < 16.0) * (x.properties['type'] == 'star')} condition_3 = {'mass': lambda x : (x.M_o >= 16.0) * (x.M_o < 24.0) * (x.properties['type'] == 'star')} condition_4 = {'mass': lambda x : (x.M_o >= 24.0) * (x.M_o < 1000.0) * (x.properties['type'] == 'star')} self._summary_data['low_mass_LQ0'] = np.sum(self.all_stars.property_asarray('Q0', subset_condition = condition_1) *\ self.all_stars.property_asarray('E0', subset_condition = condition_1)) self._summary_data['int_mass_LQ0'] = np.sum(self.all_stars.property_asarray('Q0', subset_condition = condition_2) *\ self.all_stars.property_asarray('E0', subset_condition = condition_2)) self._summary_data['high_mass_LQ0'] = np.sum(self.all_stars.property_asarray('Q0', subset_condition = condition_3) *\ self.all_stars.property_asarray('E0', subset_condition = condition_3)) self._summary_data['vhigh_mass_LQ0'] = np.sum(self.all_stars.property_asarray('Q0', subset_condition = condition_4) *\ self.all_stars.property_asarray('E0', subset_condition = condition_4)) self._summary_data['low_mass_LQ1'] = np.sum(self.all_stars.property_asarray('Q1', subset_condition = condition_1) *\ self.all_stars.property_asarray('E1', subset_condition = condition_1)) self._summary_data['int_mass_LQ1'] = np.sum(self.all_stars.property_asarray('Q1', subset_condition = condition_2) *\ self.all_stars.property_asarray('E1', subset_condition = condition_2)) self._summary_data['high_mass_LQ1'] = np.sum(self.all_stars.property_asarray('Q1', subset_condition = condition_3) *\ self.all_stars.property_asarray('E1', subset_condition = condition_3)) self._summary_data['vhigh_mass_LQ1'] = np.sum(self.all_stars.property_asarray('Q1', subset_condition = condition_4) *\ self.all_stars.property_asarray('E1', subset_condition = condition_4)) FUV_1 = self.all_stars.property_asarray('L_FUV', subset_condition = condition_1) FUV_2 = self.all_stars.property_asarray('L_FUV', subset_condition = condition_2) FUV_3 = self.all_stars.property_asarray('L_FUV', subset_condition = condition_3) FUV_4 = self.all_stars.property_asarray('L_FUV', subset_condition = condition_4) self._summary_data['low_mass_LFUV'] = np.sum(FUV_1) self._summary_data['int_mass_LFUV'] = np.sum(FUV_2) self._summary_data['high_mass_LFUV'] = np.sum(FUV_3) self._summary_data['vhigh_mass_LFUV'] = np.sum(FUV_4) LW_1 = self.all_stars.property_asarray('L_LW', subset_condition = condition_1) LW_2 = self.all_stars.property_asarray('L_LW', subset_condition = condition_2) LW_3 = self.all_stars.property_asarray('L_LW', subset_condition = condition_3) LW_4 = self.all_stars.property_asarray('L_LW', subset_condition = condition_4) self._summary_data['low_mass_LLW'] = np.sum(LW_1) self._summary_data['int_mass_LLW'] = np.sum(LW_2) self._summary_data['high_mass_LLW'] = np.sum(LW_3) self._summary_data['vhigh_mass_LLW'] = np.sum(LW_4) self._summary_data['low_mass_count'] = np.size(FUV_1) self._summary_data['int_mass_count'] = np.size(FUV_2) self._summary_data['high_mass_count'] = np.size(FUV_3) self._summary_data['vhigh_mass_count'] = np.size(FUV_4) return def write_summary_output(self): """ Write out summary output by appending to ASCII file. Filename is overwritten at first write out, so be careful. """ self._accumulate_summary_data() ncol = np.size(self._summary_data.keys()) if self._summary_output_number == 0: # print the header only once header = " " + " ".join(list(self._summary_data.keys())) + "\n" f = open(config.io.summary_output_filename,'w') f.write(header) else: f = open(config.io.summary_output_filename, 'a') fmt = "%5.5E "*ncol + "\n" # output_val = list(self._summary_data.values()) # f.write(fmt% ()) #print(self._summary_data) #print(self._summary_data.values()) f.writelines("%5.5E "% x for x in self._summary_data.values() ) f.write("\n") self._summary_output_number += 1 self._summary_data.clear() f.close()
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""" Graphing the program flow module. This module aids in understanding the flow of program by creating a visual map (network graph or map) of the program flow path. The graph map is in DOT and GML (XML) types. !!! warning "Required installation" * pycallgraph (run `pip install pycallgraph`) * [Graphviz](http://www.graphviz.org) visualization software # Author - Christopher Teh Boon Sung ------------------------------------ """ import os import re import pycallgraph from pycallgraph.output import GraphvizOutput class Graph(GraphvizOutput): """ Graph class. Creates a network map by showing/tracing the program flow. DOT and GML (XML) files will be created to show the flow. Use a dedicated Graph Editor like [yEd]( http://www.yworks.com/products/yed) to view the network map. Inherits the `pycallgraph.output.GraphvizOutput` class to modify certain default output/behavior. Override the following base methods ```text prepare_graph_attributes node edge done update ``` # METHODS trace: traces the program flow and creates (.dot) DOT and (.gml) GML files """ def __init__(self, **kwargs): """ Create and initialize the Graph object. # Arguments kwargs (dict): change any attributes or initialize new attributes with this dictionary """ self.graph_attributes = None GraphvizOutput.__init__(self, **kwargs) def prepare_graph_attributes(self): """ Override to change the default attributes for graph, nodes, and edges. # Returns None: """ # change the font name and size and to have arrows for edges self.graph_attributes = { 'graph': { 'overlap': 'scalexy', 'fontname': 'Arial', 'fontsize': 9, 'fontcolor': '#000000ff', # black }, 'node': { 'fontname': 'Arial', 'fontsize': 9, 'fontcolor': '#000000ff', 'style': 'filled', 'shape': 'rect', }, 'edge': { 'arrowhead': 'normal', 'fontname': 'Arial', 'fontsize': 9, 'fontcolor': '#000000ff', } } def node(self, key, attr): """ Override to delete newlines and number and length of function calls in node labels. # Returns str: node label """ for k in attr.keys(): attr[k] = re.sub(r'\\n.*', '', attr[k]) return '"{}" [{}];'.format(key, self.attrs_from_dict(attr)) def edge(self, edge, attr): """ Override to delete edge labels. # Returns str: edge label """ return '"{0.src_func}" -> "{0.dst_func}"'.format(edge, self.attrs_from_dict(attr)) def done(self): """ Override to avoid creating the graph picture file. # Returns None: """ pass # do nothing (bypass the parent's done function) def update(self): """ Override to avoid warning message to implement all abstract methods. Does nothing. # Returns None: """ pass @staticmethod def _colorize(txt, cls_dict): """ Change the color of nodes depending on class. !!! note `_colorize` is a static method. # Arguments txt (str): DOT text cls_dict (dict): node colors (`None` by default) # Returns str: color text """ # cls is the class name; clr is its node color (in hexadecimal, must be 8 letters long) for cls, clr in cls_dict.items(): fmt = cls + r'\..*color = "#.{8}"' for match in re.finditer(fmt, txt): nend = match.end() txt = txt[:nend - 9] + clr + txt[nend - 1:] # substitute for the desired color return txt def trace(self, fn, fname, exclude_from_trace=None, strings_to_delete=None, class_colors=None): """ Trace the program flow and creates DOT (*.dot) and GML (*.gml) files. # Arguments fn (object): function to call for the entry point to trace the program flow fname (str): filename for graph files (do not supply file extension) exclude_from_trace (list): names (`str`) to exclude from trace (`None` by default) strings_to_delete (list): text (`str`) to remove from graph files (`None` by default) class_colors (dict): node colors (`None` by default) # Returns None: """ # 1. filter out some unwanted functions and classes: config = pycallgraph.Config() if exclude_from_trace is not None: config.trace_filter = pycallgraph.GlobbingFilter(exclude=exclude_from_trace) # 2. trace the program flow: with pycallgraph.PyCallGraph(output=self, config=config): fn() # entry point for tracing the program flow dotstr = self.generate() # 3. customize the output: # 3a. delete strings if strings_to_delete is not None: for rx in strings_to_delete: dotstr = rx.sub('', dotstr) # 3b. customization: change color for class nodes if class_colors is not None: dotstr = Graph._colorize(dotstr, class_colors) # 4. create the DOT file fname_dot = fname + '.dot' with open(fname_dot, 'wt') as fdot: fdot.write(dotstr) # 5. create the GML (XML) file fname_gml = fname + '.gml' cmd = 'dot ' + fname_dot + ' | gv2gml >' + fname_gml os.system(cmd) # use the dot.exe to convert the DOT file into GML file
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# A Discord bot that does typical dad things # By Jason Saini and James Nguyen # Created: January 31, 2021 # Modified: January 20, 2022 import discord from os import getenv from requests import get, Session from dadjokes import Dadjoke from pyowm import OWM from dotenv import load_dotenv import yfinance as yf # setup client and tokens load_dotenv('token.env') client = discord.Client() DISCORD_TOKEN = getenv('DISCORD_TOKEN') WEATHER_TOKEN = getenv('WEATHER_TOKEN') COIN_TOKEN = getenv('COIN_TOKEN') OWNER_ID = getenv('OWNER_ID') owm = OWM(WEATHER_TOKEN) mgr = owm.weather_manager() cmc = Session() cmc.headers.update({'Accepts': 'application/json', 'X-CMC_PRO_API_KEY': COIN_TOKEN}) cmc_url = 'https://pro-api.coinmarketcap.com' @client.event @client.event client.run(DISCORD_TOKEN)
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import getopt import shlex from config import config from dogbot.cqsdk.utils import reply from dogbot.models import * def material(bot, message): """用法: -material [-h] [-r [-o]] 职业 -h : 打印本帮助 -r : 逆查 -o : 珠子逆查 职业 : 职业名, 可以是日文原文或者黑话. 原文一概采用未cc的初始职业名. 也接受单位的日文原文或者黑话. 例: -matrial 士兵 -matrial -r 月影 -matrial -r -o アルケミスト """ try: cmd, *args = shlex.split(message.text) except ValueError: return False if not cmd[0] in config['trigger']: return False if not cmd[1:] == 'material': return False try: options, args = getopt.gnu_getopt(args, 'hro') except getopt.GetoptError: # 格式不对 reply(bot, message, material.__doc__) return True # 拆参数 is_reverse = False is_orb = False for o, a in options: if o == '-r': # 反查 is_reverse = True elif o == '-o': # 珠子反查 is_orb = True elif o == '-h': # 帮助 reply(bot, message, material.__doc__) return True # 必须要有职业参数 if len(args) < 1: reply(bot, message, material.__doc__) return True target_name = args[0] target = Class.objects(Q(name=target_name) | Q(translate=target_name) | Q(nickname=target_name)).first() if not target: target = Unit.objects(Q(name=target_name) | Q(nickname=target_name)).first() if target: target = target.class_ if not target: reply(bot, message, '没找到这个职业/单位...') return True msg = '{}({}):\n'.format(target.name, target.translate) if not is_reverse: # 查询素材 if target.cc_material: msg += '\nCC素材: ' for mat in target.cc_material: msg += '[{}] '.format(mat.translate) else: msg += '\n该职业没有CC' if target.awake_material: msg += '\n觉醒素材: ' for mat in target.awake_material: msg += '[{}] '.format(mat.translate) msg += '\n珠子: ' for mat in target.awake_orb: msg += '({}) '.format(mat.translate) else: msg += '\n该职业没有觉醒' else: # 反查 if not is_orb: cc_usage = Class.objects(cc_material=target) if cc_usage: msg += '\nCC所用: ' for usage in cc_usage: msg += '[{}] '.format(usage.translate) else: msg += '\n该职业不会被CC所使用' awake_usage = Class.objects(awake_material=target) if awake_usage: msg += '\n觉醒所用: ' for usage in awake_usage: msg += '[{}] '.format(usage.translate) else: msg += '\n该职业不会被觉醒所使用' else: orb_usage = Class.objects(awake_orb=target) if orb_usage: msg += '\n珠子所用: ' for usage in orb_usage: msg += '[{}] '.format(usage.translate) else: msg += '\n该职业并不是珠子' reply(bot, message, msg) return True
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import torch import torch.nn as nn import torch.nn.functional as F import caption.utils.inference import caption.decoders.vanilla from framework.modules.embeddings import Embedding from framework.modules.global_attention import GlobalAttention
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import pytest @pytest.mark.parametrize(['x', 'y', 'ans'], [(1, 1, 2), (1, 2, 3), (1, 3, 4), (1, 4, 5)]) @pytest.mark.parametrize(['x', 'y', 'ans'], [(1, 1, 2), pytest.mark.xfail((1, 1, 3), reason='bad mojo'), ('ug', 'ly', 'ugly'), pytest.mark.skip(('cth', 'ulu', 'cthulu'))], ids=['good', 'bad', 'ugly', 'evil'])
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""" This is a demonstration of xml.etree (part of the standard library), which is used to parse, modify and create XML files. """ import xml.etree.ElementTree as ET tree = ET.parse('country_data.xml') root = tree.getroot() # The top level tag. print(root.tag) # The tag of the first sub-element. print(root[0].tag) # The attributes of the first sub-element. print(root[0].attrib) print() # The names of the countries and their neighbors. for country in root: if 'name' in country.attrib: print(country.attrib['name']) for element in country: if element.tag == 'neighbor': if 'name' in element.attrib: print(' ' + element.attrib['name'])
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from django.db import models from django.db.models import CASCADE from schedule.models.calendar import Calendar from schedule.models.eventType import EventType
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"""Prints name and description of available network adapters.""" import sys import pysoem if __name__ == '__main__': print('script started') if len(sys.argv) > 1: read_eeprom_of_first_slave(sys.argv[1]) else: print('give ifname as script argument')
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from scan_lib import nero as n CONSTANT_EPOH = 100 CONSTANT_EPOH_1 = 10
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"""Shows a sample tklife application""" from tkinter import StringVar, Widget from tkinter.constants import END from tkinter.ttk import Button, Entry, Label from .widgets import NewTable from .constants import COLUMNSPAN, PADX, PADY from .mixins import generate_event_for from . import Main from .arrange import Autogrid PADDING = { PADX: 6, PADY: 6 } @generate_event_for def show_dialog_for(widget): """Example of event generation decorator for a function""" return '<<ShowDialog>>' App().mainloop()
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# -*- coding: utf-8 -*- ########################################################################### # Copyright (c), The AiiDA team. All rights reserved. # # This file is part of the AiiDA code. # # # # The code is hosted on GitHub at https://github.com/aiidateam/aiida_core # # For further information on the license, see the LICENSE.txt file # # For further information please visit http://www.aiida.net # ########################################################################### def TcodExporterFactory(module): """ Return a suitable BaseTcodtranslator subclass. """ from aiida.common.pluginloader import BaseFactory return BaseFactory(module, BaseTcodtranslator, 'aiida.tools.dbexporters.tcod_plugins') class BaseTcodtranslator(object): """ Base translator from calculation-specific input and output parameters to TCOD CIF dictionary tags. """ _plugin_type_string = None @classmethod def get_software_package(cls,calc,**kwargs): """ Returns the package or program name that was used to produce the structure. Only package or program name should be used, e.g. 'VASP', 'psi3', 'Abinit', etc. """ raise NotImplementedError("not implemented in base class") @classmethod def get_software_package_version(cls,calc,**kwargs): """ Returns software package version used to compute and produce the computed structure file. Only version designator should be used, e.g. '3.4.0', '2.1rc3'. """ raise NotImplementedError("not implemented in base class") @classmethod def get_software_package_compilation_timestamp(cls,calc,**kwargs): """ Returns the timestamp of package/program compilation in ISO 8601 format. """ raise NotImplementedError("not implemented in base class") @classmethod def get_software_executable_path(cls,calc,**kwargs): """ Returns the file-system path to the executable that was run for this computation. """ try: code = calc.inp.code if not code.is_local(): return code.get_attr('remote_exec_path') except Exception: return None return None @classmethod def get_total_energy(cls,calc,**kwargs): """ Returns the total energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_one_electron_energy(cls,calc,**kwargs): """ Returns one electron energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_exchange_correlation_energy(cls,calc,**kwargs): """ Returns exchange correlation (XC) energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_ewald_energy(cls,calc,**kwargs): """ Returns Ewald energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_hartree_energy(cls,calc,**kwargs): """ Returns Hartree energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_fermi_energy(cls,calc,**kwargs): """ Returns Fermi energy in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_number_of_electrons(cls,calc,**kwargs): """ Returns the number of electrons. """ raise NotImplementedError("not implemented in base class") @classmethod def get_computation_wallclock_time(cls,calc,**kwargs): """ Returns the computation wallclock time in seconds. """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_type_symbol(cls,calc,**kwargs): """ Returns a list of atom types. Each atom site MUST occur only once in this list. List MUST be sorted. """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_type_valence_configuration(cls,calc,**kwargs): """ Returns valence configuration of each atom type. The list order MUST be the same as of get_atom_type_symbol(). """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_type_basisset(cls,calc,**kwargs): """ Returns a list of basisset names for each atom type. The list order MUST be the same as of get_atom_type_symbol(). """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_site_residual_force_Cartesian_x(cls,calc,**kwargs): """ Returns a list of x components for Cartesian coordinates of residual force for atom. The list order MUST be the same as in the resulting structure. """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_site_residual_force_Cartesian_y(cls,calc,**kwargs): """ Returns a list of y components for Cartesian coordinates of residual force for atom. The list order MUST be the same as in the resulting structure. """ raise NotImplementedError("not implemented in base class") @classmethod def get_atom_site_residual_force_Cartesian_z(cls,calc,**kwargs): """ Returns a list of z components for Cartesian coordinates of residual force for atom. The list order MUST be the same as in the resulting structure. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_X(cls,calc,**kwargs): """ Returns a number of points in the Brillouin zone along reciprocal lattice vector X. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_Y(cls,calc,**kwargs): """ Returns a number of points in the Brillouin zone along reciprocal lattice vector Y. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_Z(cls,calc,**kwargs): """ Returns a number of points in the Brillouin zone along reciprocal lattice vector Z. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_shift_X(cls,calc,**kwargs): """ Returns the shift of the Brillouin zone points along reciprocal lattice vector X. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_shift_Y(cls,calc,**kwargs): """ Returns the shift of the Brillouin zone points along reciprocal lattice vector Y. """ raise NotImplementedError("not implemented in base class") @classmethod def get_BZ_integration_grid_shift_Z(cls,calc,**kwargs): """ Returns the shift of the Brillouin zone points along reciprocal lattice vector Z. """ raise NotImplementedError("not implemented in base class") @classmethod def get_integration_smearing_method(cls,calc,**kwargs): """ Returns the smearing method name as string. """ raise NotImplementedError("not implemented in base class") @classmethod def get_integration_smearing_method_other(cls,calc,**kwargs): """ Returns the smearing method name as string if the name is different from specified in cif_dft.dic. """ raise NotImplementedError("not implemented in base class") @classmethod def get_integration_Methfessel_Paxton_order(cls,calc,**kwargs): """ Returns the order of Methfessel-Paxton approximation if used. """ raise NotImplementedError("not implemented in base class") @classmethod def get_kinetic_energy_cutoff_wavefunctions(cls,calc,**kwargs): """ Returns kinetic energy cutoff for wavefunctions in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_kinetic_energy_cutoff_charge_density(cls,calc,**kwargs): """ Returns kinetic energy cutoff for charge density in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_kinetic_energy_cutoff_EEX(cls,calc,**kwargs): """ Returns kinetic energy cutoff for exact exchange (EEX) operator in eV. """ raise NotImplementedError("not implemented in base class") @classmethod def get_pseudopotential_atom_type(cls,calc,**kwargs): """ Returns a list of atom types. Each atom type MUST occur only once in this list. List MUST be sorted. """ raise NotImplementedError("not implemented in base class") @classmethod def get_pseudopotential_type(cls,calc,**kwargs): """ Returns a list of pseudopotential types. List MUST be sorted by atom types. """ raise NotImplementedError("not implemented in base class") @classmethod def get_pseudopotential_type_other_name(cls,calc,**kwargs): """ Returns a list of other pseudopotential type names. List MUST be sorted by atom types. """ raise NotImplementedError("not implemented in base class")
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# # This source file is part of the EdgeDB open source project. # # Copyright 2019-present MagicStack Inc. and the EdgeDB authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import asyncio import logging import socket import ssl import typing from . import abstract from . import base_client from . import compat from . import con_utils from . import errors from . import transaction from .protocol import asyncio_proto __all__ = ( 'create_async_client', 'AsyncIOClient' ) logger = logging.getLogger(__name__) class AsyncIOClient(base_client.BaseClient, abstract.AsyncIOExecutor): """A lazy connection pool. A Client can be used to manage a set of connections to the database. Connections are first acquired from the pool, then used, and then released back to the pool. Once a connection is released, it's reset to close all open cursors and other resources *except* prepared statements. Clients are created by calling :func:`~edgedb.asyncio_client.create_async_client`. """ __slots__ = () _impl_class = _AsyncIOPoolImpl async def aclose(self): """Attempt to gracefully close all connections in the pool. Wait until all pool connections are released, close them and shut down the pool. If any error (including cancellation) occurs in ``aclose()`` the pool will terminate by calling AsyncIOClient.terminate() . It is advisable to use :func:`python:asyncio.wait_for` to set a timeout. """ await self._impl.aclose()
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from .dataset import validate_dataset from .metadata import validate_source_metadata, validate_view_metadata from .project import validate_project from .views import validate_views
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import sys from ViaBTCAPI.ViaBTCAPI import ViaBTCAPI EXCHANGE_URL = "http://localhost:8080/" USER_ID = 1 USER_ID_2 = 2 UPDATE_MONEY = 0.1 ORDER_PRICE = 0.1 if len(sys.argv) > 1: EXCHANGE_URL = sys.argv[1] api = ViaBTCAPI(EXCHANGE_URL) # get consts from exchange resp = api.market_list() m = resp["result"][0] market, stock, money = m["name"], m["stock"], m["money"] # balance change r = api.balance_query(user_id=USER_ID, asset=money) balance_before = float(r["result"][money]["available"]) _ = api.balance_update(user_id=USER_ID, asset=money, amount=UPDATE_MONEY) r = api.balance_query(user_id=USER_ID, asset=money) balance_after = float(r["result"][money]["available"]) assert(balance_after == balance_before + UPDATE_MONEY) # limit order creation r = api.order_put_limit( user_id=USER_ID, market=market, side='BUY', amount=UPDATE_MONEY, price=ORDER_PRICE, taker_fee_rate=0, maker_fee_rate=0) r = api.order_depth(market=market, limit=10) bid_prices = [float(b[0]) for b in r["result"]["bids"]] assert(ORDER_PRICE in bid_prices) bid_volume = [float(b[1]) for b in r["result"]["bids"] if float(b[0]) == ORDER_PRICE][0] # create the second user and execute the order _ = api.balance_update(user_id=USER_ID_2, asset=stock, amount=bid_volume) r = api.order_put_limit( user_id=USER_ID_2, market=market, side='SELL', amount=bid_volume, price=ORDER_PRICE, taker_fee_rate=0, maker_fee_rate=0) r = api.order_depth(market=market, limit=10) prices = [float(b[0]) for b in r["result"]["bids"] + r["result"]["asks"]] assert(ORDER_PRICE not in prices) # reset balances for user_id in [USER_ID, USER_ID_2]: for asset in [money, stock]: r = api.balance_query(user_id=user_id, asset=asset) balance_current = float(r["result"][asset]["available"]) r = api.balance_update(user_id=user_id, asset=asset, amount=(-1) * balance_current) print("All tests have been passed!")
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# HelpMate Speech Synthesis Connection 2020 from google.cloud import texttospeech # Instantiates a client client = texttospeech.TextToSpeechClient() # Set the text input to be synthesized synthesis_input = texttospeech.types.SynthesisInput(text="Hello, World!") # Build the voice request, select the language code ("en-US") and the ssml # voice gender ("neutral") voice = texttospeech.types.VoiceSelectionParams( language_code='en-US', ssml_gender=texttospeech.enums.SsmlVoiceGender.NEUTRAL) # Select the type of audio file you want returned audio_config = texttospeech.types.AudioConfig( audio_encoding=texttospeech.enums.AudioEncoding.MP3) # Perform the text-to-speech request on the text input with the selected # voice parameters and audio file type response = client.synthesize_speech(synthesis_input, voice, audio_config) # The response's audio_content is binary. with open('output.mp3', 'wb') as out: # Write the response to the output file. out.write(response.audio_content) print('Audio content written to file "output.mp3"')
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import re import json from typing import Optional, List, Dict from . import operators from .models.baseoperator import BaseOperator from .dagrun import DAGRun from ..cache import TriggerflowCache from .other.notebook import display_graph
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3.825397
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# Copyright (C) 2013, Maxime Biais <maxime@biais.org> from .market import Market import time import base64 import hmac import urllib.request import urllib.parse import urllib.error import urllib.request import urllib.error import urllib.parse import hashlib import sys import json import re import logging import config
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"""add_pending_artifact Revision ID: 0f81e9efc84a Revises: 61a1763b9c8d Create Date: 2019-10-24 15:13:36.705288 """ import zeus.db.types from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = "0f81e9efc84a" down_revision = "61a1763b9c8d" branch_labels = () depends_on = None
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2.338129
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""" Copyright 2021 supakeen Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import enum from typing import Optional, Any class _context: """Contexts are for storing various flags about what happened to types used within them.""" overflow: bool promotion: bool class _value: """A value, we store the raw 'python' integer and only go into/out of bits and fixed width on certain operations. This allows for easier conversion during calculation. """ class default(_context): """Some default values that do generally what people expect, these mimic the `c_stdint` context and are exported on the module level directly for short imports.""" _signed_behavior = _behavior( overflow=_behavior_overflow.TRUNCATE, promotion=_behavior_promotion.EXCEPTION, ) i8 = _signed(8, _signed_behavior) i16 = _signed(16, _signed_behavior) i32 = _signed(32, _signed_behavior) i64 = _signed(64, _signed_behavior) _unsigned_behavior = _behavior( overflow=_behavior_overflow.TRUNCATE, promotion=_behavior_promotion.EXCEPTION, ) u8 = _unsigned(8, _unsigned_behavior) u16 = _unsigned(16, _unsigned_behavior) u32 = _unsigned(32, _unsigned_behavior) u64 = _unsigned(64, _unsigned_behavior) # Exporting the `default` context for short imports. i8 = default.i8 i16 = default.i16 i32 = default.i32 i64 = default.i64 u8 = default.u8 u16 = default.u16 u32 = default.u32 u64 = default.u64
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3.212435
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my_coro = simple_coroutine() next(my_coro) my_coro.send(42)
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2.068966
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from django.conf.urls.defaults import * urlpatterns = patterns('', url(r'^trigger-500$', 'sentry.tests.views.raise_exc', name='sentry-raise-exc'), url(r'^', include('sentry.urls')), )
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from pathlib import Path from subprocess import PIPE, run # nosec from typing import List from cruft import exceptions def get_diff(repo0: Path, repo1: Path) -> str: """Compute the raw diff between two repositories.""" try: diff = run( _git_diff("--no-ext-diff", "--no-color", str(repo0), str(repo1)), cwd=str(repo0), stdout=PIPE, stderr=PIPE, ).stdout.decode() except UnicodeDecodeError: raise exceptions.ChangesetUnicodeError() # By default, git diff --no-index will output full paths like so: # --- a/tmp/tmpmp34g21y/remote/.coveragerc # +++ b/tmp/tmpmp34g21y/local/.coveragerc # We don't want this as we may need to apply the diff later on. # Note that diff headers contain repo0 and repo1 with both "a" and "b" # prefixes: headers for new files have a/repo1, headers for deleted files # have b/repo0. for repo in [repo0, repo1]: diff = diff.replace("a" + str(repo), "a").replace("b" + str(repo), "b") # This replacement is needed for renamed/moved files to be recognized properly # Renamed files in the diff don't have the "a" or "b" prefix and instead look like # /tmp/tmpmp34g21y/remote/.coveragerc # If we replace repo paths which are like /tmp/tmpmp34g21y/remote # we would end up with /.coveragerc which doesn't work. # We also need to replace the trailing slash. As a result, we only do # this after the above replacement is made as the trailing slash is needed there. diff = diff.replace(str(repo0) + "/", "").replace(str(repo1) + "/", "") return diff def display_diff(repo0: Path, repo1: Path): """Displays the diff between two repositories.""" run(_git_diff(str(repo0), str(repo1)))
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2.625185
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from octopus.lib import dataobj BASE_ARTICLE_STRUCT = { "fields": { "id": {"coerce": "unicode"}, # Note that we'll leave these in for ease of use by the "created_date": {"coerce": "utcdatetime"}, # caller, but we'll need to ignore them on the conversion "last_updated": {"coerce": "utcdatetime"} # to the real object }, "objects": ["admin", "bibjson"], "structs": { "admin": { "fields": { "in_doaj": {"coerce": "bool", "get__default": False}, "publisher_record_id": {"coerce": "unicode"}, "upload_id": {"coerce": "unicode"} } }, "bibjson": { "fields": { "title": {"coerce": "unicode", "set__ignore_none": True}, "year": {"coerce": "unicode", "set__ignore_none": True}, "month": {"coerce": "unicode", "set__ignore_none": True}, "abstract": {"coerce": "unicode", "set__ignore_none": True} }, "lists": { "identifier": {"contains": "object"}, "link": {"contains": "object"}, "author": {"contains": "object"}, "keywords": {"coerce": "unicode", "contains": "field"}, "subject": {"contains": "object"}, }, "objects": [ "journal", ], "structs": { "identifier": { "fields": { "type": {"coerce": "unicode"}, "id": {"coerce": "unicode"} } }, "link": { "fields": { "type": {"coerce": "unicode"}, "url": {"coerce": "url"}, "content_type": {"coerce": "unicde"} } }, "author": { "fields": { "name": {"coerce": "unicode"}, "email": {"coerce": "unicode"}, "affiliation": {"coerce": "unicode"} } }, "journal": { "fields": { "start_page": {"coerce": "unicode", "set__ignore_none": True}, "end_page": {"coerce": "unicode", "set__ignore_none": True}, "volume": {"coerce": "unicode", "set__ignore_none": True}, "number": {"coerce": "unicode", "set__ignore_none": True}, "publisher": {"coerce": "unicode", "set__ignore_none": True}, "title": {"coerce": "unicode", "set__ignore_none": True}, "country": {"coerce": "unicode", "set__ignore_none": True} }, "lists": { "license": {"contains": "object"}, "language": {"coerce": "unicode", "contains": "field", "set__ignore_none": True} }, "structs": { "license": { "fields": { "title": {"coerce": "unicode"}, "type": {"coerce": "unicode"}, "url": {"coerce": "unicode"}, "version": {"coerce": "unicode"}, "open_access": {"coerce": "bool"}, } } } }, "subject": { "fields": { "scheme": {"coerce": "unicode"}, "term": {"coerce": "unicode"}, "code": {"coerce": "unicode"} } }, } } } } ARTICLE_REQUIRED = { "required": ["bibjson"], "structs": { "bibjson": { "required": [ "title", "author", # One author required "identifier" # One type of identifier is required ], "structs": { "identifier": { "required": ["type", "id"] }, "link": { "required": ["type", "url"] }, "author": { "required": ["name"] }, } } } }
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1.60493
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import sys from random import * def dispatch_gen(settings, rmgseed = 0): """ Short function that prepares map generation and then dispatches to generation modules """ # Seed with a specific seed if one was provided if rmgseed != 0: print("seed:" + str(rmgseed)) seed(rmgseed) module_name = "modules.%s.__init__" % settings.module_name rmg_module = __import__(module_name, fromlist=[module_name]) max_attempts = 5 for i in range(max_attempts): hmap = None print("[i]At attempt %d of %d for for module %s to generate given these settings" % (i+1, max_attempts, settings.module_name)) hmap = rmg_module.gen(settings) if hmap != None: print("[+]Successful at attempt %d/%d for module %s to generate given these settings" % (i+1, max_attempts, settings.module_name)) break else: print("[!]Failed at attempt %d/%d for module %s to generate given these settings" % (i+1, max_attempts, settings.module_name)) return hmap
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#!/usr/bin/env python """ metrics.py Metrics calculation for the analysis/report part of the openff-benchmark workflow By: David F. Hahn Version: Nov 25 2020 """ import numpy as np from rdkit import Chem from rdkit.Chem import TorsionFingerprints def calc_tfd(ref_mol, query_mol): """ Calculate Torsion Fingerprint Deviation between two molecular structures. RDKit is required for TFD calculation. References ---------- Modified from the following code: https://github.com/MobleyLab/benchmarkff/03_analysis/compare_ffs.py TFD reference: https://pubs.acs.org/doi/10.1021/ci2002318 Parameters ---------- ref_mol : RDKit RDMol query_mol : RDKit RDMol Returns ------- tfd : float Torsion Fingerprint Deviation between ref and query molecules """ # check if the molecules are the same # tfd requires the two molecules must be instances of the same molecule rsmiles = Chem.MolToSmiles(ref_mol) qsmiles = Chem.MolToSmiles(query_mol) if rsmiles != qsmiles: print( f"- WARNING: The reference mol {ref_mol.GetProp('_Name')} and " f"query mol {query_mol.GetProp('_Name')} do NOT have the same " f"SMILES strings as determined by RDKit MolToSmiles. " f"\n {rsmiles}\n {qsmiles}" ) tfd = np.nan # calculate the TFD else: try: tfd = TorsionFingerprints.GetTFDBetweenMolecules(ref_mol, query_mol) # triggered for molecules such as urea except IndexError: print( f"- Error calculating TFD on molecule {ref_mol.GetProp('_Name')}." " Possibly no non-terminal rotatable bonds found." ) tfd = np.nan return tfd
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from simple_rest_client.resource import AsyncResource, Resource films_actions = { 'list': { 'method': 'GET', 'url': 'films' }, 'retrieve': { 'method': 'GET', 'url': 'films/{}', }, 'schema': { 'method': 'GET', 'url': 'films/schema', }, } people_actions = { 'list': { 'method': 'GET', 'url': 'people' }, 'retrieve': { 'method': 'GET', 'url': 'people/{}', }, 'schema': { 'method': 'GET', 'url': 'people/schema', }, } planets_actions = { 'list': { 'method': 'GET', 'url': 'planets' }, 'retrieve': { 'method': 'GET', 'url': 'planets/{}', }, 'schema': { 'method': 'GET', 'url': 'planets/schema', }, } species_actions = { 'list': { 'method': 'GET', 'url': 'species' }, 'retrieve': { 'method': 'GET', 'url': 'species/{}', }, 'schema': { 'method': 'GET', 'url': 'species/schema', }, } starships_actions = { 'list': { 'method': 'GET', 'url': 'starships' }, 'retrieve': { 'method': 'GET', 'url': 'starships/{}', }, 'schema': { 'method': 'GET', 'url': 'starships/schema', }, } vehicles_actions = { 'list': { 'method': 'GET', 'url': 'vehicles' }, 'retrieve': { 'method': 'GET', 'url': 'vehicles/{}', }, 'schema': { 'method': 'GET', 'url': 'vehicles/schema', }, }
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#!/usr/bin/env python ''' Generates an EdX style XML question from the provided YAML question file. ''' from pathlib import Path from random import sample import click import yaml from lxml import etree @click.command() @click.argument('file_name') if __name__ == '__main__': gen()
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#Python3 #Permite calcular cuantos años han sido bisiestos en un rango de años ###### DEFINICIONES ###### ###### IMPLEMENTACION ###### an1 = int(input("Digite el año mayor que desea comparar ")) an2 = int(input("Digite el año menor ")) dif = an1 - an2 cont = 0 for indice in range (an2, an1+1): if bisiesto(indice) == True: cont = cont + 1 print ("La diferencia entre ", an1, " y ", an2, " es de ", dif) if (cont >0): print ("Entre este intervalo de años hay ", cont, " años bisiestos ") else: print("No hay años bisiestos en este intervalo ")
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import supriya.osc from supriya.commands.Request import Request from supriya.enums import RequestId class GroupFreeAllRequest(Request): """ A /g_freeAll request. :: >>> import supriya >>> server = supriya.Server.default().boot() >>> group = supriya.Group().allocate() >>> group.extend([supriya.Synth(), supriya.Group()]) >>> group[1].extend([supriya.Synth(), supriya.Group()]) >>> group[1][1].extend([supriya.Synth(), supriya.Group()]) :: >>> print(server) NODE TREE 0 group 1 group 1000 group 1001 default out: 0.0, amplitude: 0.1, frequency: 440.0, gate: 1.0, pan: 0.5 1002 group 1003 default out: 0.0, amplitude: 0.1, frequency: 440.0, gate: 1.0, pan: 0.5 1004 group 1005 default out: 0.0, amplitude: 0.1, frequency: 440.0, gate: 1.0, pan: 0.5 1006 group :: >>> request = supriya.commands.GroupFreeAllRequest(group) >>> request.to_osc() OscMessage('/g_freeAll', 1000) :: >>> with server.osc_protocol.capture() as transcript: ... request.communicate(server=server) ... _ = server.sync() ... :: >>> for entry in transcript: ... (entry.label, entry.message) ... ('S', OscMessage('/g_freeAll', 1000)) ('S', OscMessage('/sync', 2)) ('R', OscMessage('/n_end', 1001, -1, -1, -1, 0)) ('R', OscMessage('/n_end', 1003, -1, -1, -1, 0)) ('R', OscMessage('/n_end', 1005, -1, -1, -1, 0)) ('R', OscMessage('/n_end', 1006, -1, -1, -1, 1, -1, -1)) ('R', OscMessage('/n_end', 1004, -1, -1, -1, 1, -1, -1)) ('R', OscMessage('/n_end', 1002, -1, -1, -1, 1, -1, -1)) ('R', OscMessage('/synced', 2)) :: >>> print(server) NODE TREE 0 group 1 group 1000 group :: >>> print(server.query_local_nodes(True)) NODE TREE 0 group 1 group 1000 group """ ### CLASS VARIABLES ### request_id = RequestId.GROUP_FREE_ALL ### INITIALIZER ### ### PUBLIC METHODS ### ### PUBLIC PROPERTIES ### @property
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from itertools import chain from logging import info import torch from mylog import log from memory.trajectory import Trajectory from optimizer import setup_optimizer from agents.on_policy.online_agent import OnlineAgent from actors.on_policy.online_actor import OnlineActor from critics.on_policy.online_critic import OnlineCritic class PPOAgent(OnlineAgent): """One variant of Proximal Policy Optimizaation agent :args T: number of max steps used for bootstrapping (to be computationnally efficient, bootstrapping horizon is variable). :args actor: actor used :args critic: critic used :args opt_name: 'rmsprop' ('sgd' deprecated) :args lr: unscaled learning rate :args dt: framerate :args weigth_decay: weight decay """
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import logging import os import sys sys.path.append('..') import itertools import json import random import torch from misc import util
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""" This module is used in `SaveDICOM_Image.py` and used as the optional argument `parametric_map` in write functions of `Classes.py` and in "writeNewPixelArray" of `DeveloperTools.py`. The functions in this module capture special versions of DICOM with unique parameters/attributes/values. **How to use:** provide the parametric_map in the functions mentioned previously as a string. This string is the name of one of the functions in the ParametricClass (eg. parametric_map="RGB" or parametric_map="SEG") """ import pydicom from pydicom.dataset import Dataset from pydicom.sequence import Sequence import numpy as np import datetime import struct # Could insert a method regarding ROI colours, like in ITK-SNAP??? # rwv_sequence = Sequence() # dicom.RealWorldValueMappingSequence = rwv_sequence # rwv_slope = Dataset() # rwv_slope.RealWorldValueSlope = 1 # rwv_sequence.append(rwv_slope) # quantity_def = Dataset() # quantity_def_sequence = Sequence() # quantity_def.QuantityDefinitionSequence = quantity_def_sequence # value_type = Dataset() # value_type.ValueType = "CODE" # quantity_def_sequence.append(value_type) # concept_code = Dataset() # concept_code_sequence = Sequence() # concept_code.ConceptCodeSequence = concept_code_sequence # code_code = Dataset() # code_code.CodeValue = "113041" # code_code.CodingSchemeDesignator = "DCM" # code_code.CodeMeaning = "Apparent Diffusion Coefficient" # concept_code_sequence.append(code_code) # rwv_sequence.append(quantity_def) # measure_units = Dataset() # measure_units_sequence = Sequence() # measure_units.MeasurementUnitsCodeSequence = measure_units_sequence # measure_code = Dataset() # measure_code.CodeValue = "um2/s" # measure_code.CodingSchemeDesignator = "UCUM" # measure_code.CodeMeaning = "um2/s" # measure_units_sequence.append(measure_code) # rwv_sequence.append(measure_units)
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from datetime import timedelta, datetime from airflow import DAG from airflow.operators.dummy_operator import DummyOperator from airflow import AirflowException args = { "owner": "dataroots", "start_date": datetime(2020, 10, 12), } with DAG( dag_id="example_dag", catchup=False, max_active_runs=1, default_args=args, schedule_interval="*/5 * * * *" ) as dag: task_a = DummyOperator( task_id="task_a" ) task_b = DummyOperator( task_id="task_b" ) task_c = DummyOperator( task_id="task_c" ) task_d = DummyOperator( task_id="task_d" ) task_a >> [task_b, task_c] >> task_d
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import pytest from stellar_sdk import BumpSequence, Operation from . import *
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# Purpose: Implement time stepping scheme to solve individual and coupled state equations # Record of revisions: # Date Programmer Description of change # ======== ============= ===================== # 09-2020 A. Elkouk Original code import numpy as np # ---------------------------------------------------------------------------------------------------------------------- # Explicit (forward) Euler method # ---------------------------------------------------------------------------------------------------------------------- def explicitEuler(f_S, S0, T, dt, **kwargs): """ Solve dS/dt = f_S(S, t), S(0)=S0, for n=T/dt steps Parameters ---------- f_S : function State function for given model sub-domain (canopy, unsaturated zone, saturated zone) S0 : float State initial condition at t=0 T : float or int Time period [days] dt : float or int Time step [days] kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : ndarray Integrated state for n=T/dt time steps t : ndarray Time steps [days] """ n = int(T / dt) t = np.zeros(n + 1) dS = np.zeros(n + 1) dS[0] = S0 t[0] = 0 for k in range(n): t[k + 1] = t[k] + dt dS[k + 1] = dS[k] + (dt * f_S(dS[k], **kwargs)) if dS[k + 1] < 0.0: dS[k + 1] = 0.0 return dS, t def explicitEuler_coupled_states(f_S, S0, T, dt, precip, **kwargs): """ Solve dS/dt = f_S(S, t), S(0)=S0, for n=T/dt steps Parameters ---------- f_S : function Coupled state function of the model sub-domains (e.g. canopy, unsaturated zone, and saturated zone) S0 : array_like State initial conditions at t=0 (e.g. [canopy, unsaturated zone, and saturated zone]) T : float or int Time period [days] dt : float or int Time step [days] precip : array_like Precipitation flux [mm days^-1] at n=T/dt time step kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : ndarray Integrated states for n=T/dt time steps with shape (n, nbr_states) RO : ndarray Total runoff [mm day^-1] for n=T/dt time steps t : ndarray Time steps [days] """ n = int(T / dt) nS = len(S0) t = np.zeros(n + 1) dS = np.zeros((n + 1, nS)) RO = np.zeros(n + 1) dS[0, :] = S0 t[0] = 0 for k in range(n): t[k + 1] = t[k] + dt Sk, RO_k = f_S(dS[k], precip[k], **kwargs) RO[k] = RO_k dS[k + 1, :] = dS[k, :] + (dt * np.array(Sk)) dS = np.where(dS < 0.0, 0.0, dS) return dS, RO, t # ---------------------------------------------------------------------------------------------------------------------- # Heun's method # ---------------------------------------------------------------------------------------------------------------------- def Heun(f_S, S0, T, dt, **kwargs): """ Solve dS/dt = f_S(S, t), S(0)=S0, for n=T/dt steps using the explicit Heun's method Parameters ---------- f_S : function State function for given model sub-domain (canopy, unsaturated zone, saturated zone) S0 : float State initial condition at t=0 T : float or int Time period [days] dt : float or int Time step [days] kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : ndarray Integrated state for n=T/dt time steps t : ndarray Time steps [days] """ n = int(T / dt) t = np.zeros(n + 1) dS = np.zeros(n + 1) dS[0] = S0 t[0] = 0 for k in range(n): t[k + 1] = t[k] + dt K1 = f_S(dS[k], **kwargs) K2 = f_S((K1 * dt) + dS[k], **kwargs) dS[k + 1] = dS[k] + (0.5 * dt * (K1 + K2)) if dS[k + 1] < 0.0: dS[k + 1] = 0.0 return dS, t def Heun_ndt(f_S, Si, dt, T, **kwargs): """ Solve dS/dt = f_S(S, t), S(t=t_i)=Si, at t=T with n steps (n=T/dt), using the explicit Heun's method Parameters ---------- f_S : function State function for given model sub-domain (canopy, unsaturated zone, saturated zone) Si : float State at time t=t_i dt : float or int Time step [days] T : float or int Time period [days] kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : float Integrated state at t=ndt with n=T/dt """ n = int(T / dt) dS = Si for _ in range(n): K1 = f_S(dS, **kwargs) K2 = f_S((K1 * dt) + dS, **kwargs) dS = dS + (0.5 * dt * (K1 + K2)) return dS def Heun_adaptive_substep(f_S, Si, dt, T, tau_r, tau_abs, s=0.9, rmin=0.1, rmax=4.0, EPS=10 ** (-10), **kwargs): """ Solve dS/dt = f_S(S, t), S(t=t_i)=Si, using the explicit Heun's method with numerical error control and adaptive sub stepping Parameters ---------- f_S : function State function for given model sub-domain (canopy, unsaturated zone, saturated zone) Si : float State at time t=t_i dt : float or int Time step [days] T : float or int Time period [days] tau_r : float Relative truncation error tolerance tau_abs : float Absolute truncation error tolerance s : float Safety factor rmin, rmax : float Step size multiplier constraints EPS : float Machine constant kwargs : dict *kwargs* are used to specify the additional parameters used by the the state function (f_S) Returns ------- dS : list Integrated state time : list Time steps [days] """ t = 0 dS = [Si] time = [t] while t < T: t += dt y1 = Heun_ndt(f_S, Si, dt, dt, **kwargs) y2 = Heun_ndt(f_S, Si, dt/2, dt, **kwargs) err = abs(y1 - y2) diff = err - ((tau_r * abs(y2)) + tau_abs) if diff < 0: Si = y2 dS.append(Si) time.append(dt) dt = dt * min(s * np.sqrt((tau_r * abs(y2) + tau_abs) / (max(err, EPS))), rmax) elif diff > 0: t -= dt dt = dt * max(s * np.sqrt((tau_r * abs(y2) + tau_abs) / (max(err, EPS))), rmin) return dS, time
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from typing import Optional, Callable, Any import grpc import requests as r import env import urllib.parse as url import inspect from client import ml_pipelines as cl import test_api as api
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from mybitbank.libs.bitcoinrpc.authproxy import AuthServiceProxy, JSONRPCException __all__ = ['AuthServiceProxy', 'JSONRPCException']
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""" Module for MYISAM2 driver. """ from PyQt5.Qt import qWarning, QApplication, QRegExp # type: ignore from PyQt5.QtXml import QDomDocument # type: ignore from PyQt5.QtWidgets import QMessageBox, QWidget # type: ignore from pineboolib.core.utils.utils_base import auto_qt_translate_text from pineboolib.application.utils.check_dependencies import check_dependencies from pineboolib.application.database.pnsqlquery import PNSqlQuery from pineboolib.application.database.pnsqlcursor import PNSqlCursor from pineboolib.core.utils.utils_base import text2bool from pineboolib.application.metadata.pnfieldmetadata import PNFieldMetaData from pineboolib.fllegacy import flapplication from pineboolib.fllegacy.flutil import FLUtil from pineboolib.application import project import traceback from pineboolib import logging from PyQt5.QtCore import QTime, QDate, QDateTime, Qt # type: ignore from typing import Any, Iterable, Optional, Union, List, Dict, cast logger = logging.getLogger(__name__) class FLMYSQL_MYISAM2(object): """MYISAM2 Driver class.""" version_: str conn_ = None name_: str alias_: str lastError_: Optional[str] cursorsArray_: Dict[str, Any] # IApiCursor noInnoDB: bool mobile_: bool pure_python_: bool defaultPort_: int cursor_ = None db_ = None engine_ = None session_ = None declarative_base_ = None def __init__(self): """Create empty driver.""" self.version_ = "0.8" self.conn_ = None self.name_ = "FLMYSQL_MyISAM2" self.open_ = False self.alias_ = "MySQL MyISAM (PyMySQL)" self.cursorsArray_ = {} self.noInnoDB = True self._dbname = None self.mobile_ = True self.pure_python_ = True self.defaultPort_ = 3306 self.rowsFetched: Dict[str, int] = {} self.active_create_index = True self.db_ = None self.engine_ = None self.session_ = None self.declarative_base_ = None self.lastError_ = None def version(self) -> str: """Get driver version.""" return self.version_ def driverName(self) -> str: """Get driver name.""" return self.name_ def pure_python(self) -> bool: """Return if this driver is pure python.""" return self.pure_python_ def safe_load(self) -> Any: """Check dependencies for this driver.""" return check_dependencies({"pymysql": "PyMySQL", "sqlalchemy": "sqlAlchemy"}, False) def mobile(self) -> bool: """Check if is suitable for mobile platform.""" return self.mobile_ def isOpen(self) -> bool: """Return if driver has an open connection.""" return self.open_ def DBName(self) -> Any: """Return database name.""" return self._dbname def connect(self, db_name, db_host, db_port, db_userName, db_password) -> Any: """Connect to a database.""" self._dbname = db_name check_dependencies({"pymysql": "PyMySQL", "sqlalchemy": "sqlAlchemy"}) from sqlalchemy import create_engine # type: ignore import pymysql try: self.conn_ = pymysql.connect( host=db_host, user=db_userName, password=db_password, db=db_name, charset="utf8", autocommit=True, ) self.engine_ = create_engine( "mysql+mysqldb://%s:%s@%s:%s/%s" % (db_userName, db_password, db_host, db_port, db_name) ) except pymysql.Error as e: if project._splash: project._splash.hide() if "Unknown database" in str(e): if project._DGI and not project.DGI.localDesktop(): return False ret = QMessageBox.warning( QWidget(), "Pineboo", "La base de datos %s no existe.\n¿Desea crearla?" % db_name, cast(QMessageBox, QMessageBox.Ok | QMessageBox.No), ) if ret == QMessageBox.No: return False else: try: tmpConn = pymysql.connect( host=db_host, user=db_userName, password=db_password, charset="utf8", autocommit=True, ) cursor = tmpConn.cursor() try: cursor.execute("CREATE DATABASE %s" % db_name) except Exception: print("ERROR: FLMYSQL2.connect", traceback.format_exc()) cursor.execute("ROLLBACK") cursor.close() return False cursor.close() return self.connect(db_name, db_host, db_port, db_userName, db_password) except Exception: qWarning(traceback.format_exc()) QMessageBox.information( QWidget(), "Pineboo", "ERROR: No se ha podido crear la Base de Datos %s" % db_name, QMessageBox.Ok, ) print("ERROR: No se ha podido crear la Base de Datos %s" % db_name) return False else: QMessageBox.information( QWidget(), "Pineboo", "Error de conexión\n%s" % str(e), QMessageBox.Ok ) return False if self.conn_: self.open_ = True # self.conn_.autocommit(True) # self.conn_.set_character_set('utf8') return self.conn_ def cursor(self) -> Any: """Get current cursor for db.""" if not self.conn_: raise Exception("Not connected") if not self.cursor_: self.cursor_ = self.conn_.cursor() return self.cursor_ def engine(self) -> Any: """Get current driver engine.""" return self.engine_ def session(self) -> None: """Get sqlAlchemy session.""" if self.session_ is None: from sqlalchemy.orm import sessionmaker # type: ignore # from sqlalchemy import event # from pineboolib.pnobjectsfactory import before_commit, after_commit Session = sessionmaker(bind=self.engine()) self.session_ = Session() # event.listen(Session, 'before_commit', before_commit, self.session_) # event.listen(Session, 'after_commit', after_commit, self.session_) def declarative_base(self) -> Any: """Get sqlAlchemy declarative base.""" if self.declarative_base_ is None: from sqlalchemy.ext.declarative import declarative_base # type: ignore self.declarative_base_ = declarative_base() return self.declarative_base_ def formatValueLike(self, type_, v: Any, upper) -> str: """Format value for database LIKE expression.""" res = "IS NULL" if v: if type_ == "bool": s = str(v[0]).upper() if s == flapplication.aqApp.tr("Sí")[0].upper(): res = "=1" elif flapplication.aqApp.tr("No")[0].upper(): res = "=0" elif type_ == "date": from pineboolib.application.utils.date_conversion import date_dma_to_amd date_amd = date_dma_to_amd(str(v)) if date_amd: res = " LIKE '%" + date_amd + "'" else: logger.warning("formatValueLike: failed to convert %s to ISO date format", v) elif type_ == "time": t = v.toTime() res = " LIKE '" + t.toString(Qt.ISODate) + "%'" else: res = str(v) if upper: res = res.upper() res = " LIKE '" + res + "%'" return res def formatValue(self, type_, v: Any, upper) -> Union[str, bool, None]: """Format value for database WHERE comparison.""" # util = FLUtil() s: Union[str, bool, None] = None # if v == None: # v = "" # TODO: psycopg2.mogrify ??? if v is None: return "NULL" if type_ == "bool" or type_ == "unlock": s = text2bool(v) elif type_ == "date": # val = util.dateDMAtoAMD(v) val = v if val is None: s = "Null" else: s = "'%s'" % val elif type_ == "time": s = "'%s'" % v elif type_ in ("uint", "int", "double", "serial"): if s == "Null": s = "0" else: s = v elif type_ in ("string", "stringlist"): if v == "": s = "Null" else: if type_ == "string": v = auto_qt_translate_text(v) if upper and type_ == "string": v = v.upper() s = "'%s'" % v elif type_ == "pixmap": if v.find("'") > -1: v = self.normalizeValue(v) s = "'%s'" % v else: s = v # print ("PNSqlDriver(%s).formatValue(%s, %s) = %s" % (self.name_, type_, v, s)) return s def tables(self, type_name=None) -> list: """Introspect tables in database.""" tl: List[str] = [] if not self.isOpen(): return tl q_tables = PNSqlQuery() q_tables.exec_("show tables") while q_tables.next(): tl.append(q_tables.value(0)) return tl def nextSerialVal(self, table, field) -> Any: """Get next serial value for given table and field.""" if not self.isOpen(): logger.warning("%s::beginTransaction: Database not open", self.name_) return None # if not self.transaction(): # self.setLastError("No se puede iniciar la transacción", "BEGIN WORK") # return None max = 0 cur_max = 0 updateQry = False ret = None q = PNSqlQuery() q.setSelect("max(%s)" % field) q.setFrom(table) q.setWhere("1 = 1") if not q.exec_(): logger.warning("not exec sequence") return None if q.first() and q.value(0) is not None: max = q.value(0) if not self.conn_: raise Exception("must be connected") cursor = self.conn_.cursor() strQry: Optional[str] = "SELECT seq FROM flseqs WHERE tabla = '%s' AND campo ='%s'" % ( table, field, ) try: cur_max = 0 cursor.execute(strQry) line = cursor.fetchone() if line: cur_max = line[0] except Exception: logger.warning( "%s:: La consulta a la base de datos ha fallado", self.name_, traceback.format_exc() ) self.rollbackTransaction() return if cur_max > 0: updateQry = True ret = cur_max else: ret = max ret += 1 strQry = None if updateQry: if ret > cur_max: strQry = "UPDATE flseqs SET seq=%s WHERE tabla = '%s' AND campo = '%s'" % ( ret, table, field, ) else: strQry = "INSERT INTO flseqs (tabla,campo,seq) VALUES('%s','%s',%s)" % ( table, field, ret, ) if strQry is not None: try: cursor.execute(strQry) except Exception: logger.warning( "%s:: La consulta a la base de datos ha fallado\n %s", self.name_, traceback.format_exc(), ) self.rollbackTransaction() return # if not self.commitTransaction(): # qWarning("%s:: No se puede aceptar la transacción" % self.name_) # return None return ret def queryUpdate(self, name, update, filter) -> str: """Return a templates UPDATE sql.""" sql = "UPDATE %s SET %s WHERE %s" % (name, update, filter) return sql def savePoint(self, n) -> bool: """Perform a transaction savepoint.""" if n == 0: return True if not self.isOpen(): logger.warning("%s::savePoint: Database not open", self.name_) return False cursor = self.cursor() try: cursor.execute("SAVEPOINT sv_%s" % n) except Exception: self.setLastError("No se pudo crear punto de salvaguarda", "SAVEPOINT sv_%s" % n) logger.warning( "MySQLDriver:: No se pudo crear punto de salvaguarda SAVEPOINT sv_%s \n %s ", n, traceback.format_exc(), ) return False return True def canSavePoint(self) -> bool: """Retrieve if this driver can perform savepoints.""" return False def canTransaction(self) -> bool: """Retrieve if this driver can perform transactions.""" return False def rollbackSavePoint(self, n) -> bool: """Rollback transaction to last savepoint.""" if n == 0: return True if not self.isOpen(): logger.warning("%s::rollbackSavePoint: Database not open", self.name_) return False cursor = self.cursor() try: cursor.execute("ROLLBACK TO SAVEPOINT sv_%s" % n) except Exception: self.setLastError( "No se pudo rollback a punto de salvaguarda", "ROLLBACK TO SAVEPOINTt sv_%s" % n ) logger.warning( "%s:: No se pudo rollback a punto de salvaguarda ROLLBACK TO SAVEPOINT sv_%s\n %s", self.name_, n, traceback.format_exc(), ) return False return True def setLastError(self, text, command) -> None: """Set last error from database.""" self.lastError_ = "%s (%s)" % (text, command) def lastError(self) -> Optional[str]: """Get last error happened on database.""" return self.lastError_ def commitTransaction(self) -> bool: """Commit database transaction.""" if not self.isOpen(): logger.warning("%s::commitTransaction: Database not open", self.name_) cursor = self.cursor() try: cursor.execute("COMMIT") except Exception: self.setLastError("No se pudo aceptar la transacción", "COMMIT") logger.warning( "%s:: No se pudo aceptar la transacción COMMIT\n %s", self.name_, traceback.format_exc(), ) return False return True def rollbackTransaction(self) -> bool: """Rollback database transaction.""" if not self.isOpen(): logger.warning("%s::rollbackTransaction: Database not open", self.name_) cursor = self.cursor() if self.canSavePoint(): try: cursor.execute("ROLLBACK") except Exception: self.setLastError("No se pudo deshacer la transacción", "ROLLBACK") logger.warning( "%s:: No se pudo deshacer la transacción ROLLBACK\n %s", self.name_, traceback.format_exc(), ) return False else: qWarning( "%s:: No se pudo deshacer la transacción ROLLBACK\n %s" % (self.name_, traceback.format_exc()) ) return True def transaction(self) -> bool: """Start new database transaction.""" if not self.isOpen(): logger.warning("%s::transaction: Database not open", self.name_) cursor = self.cursor() try: cursor.execute("START TRANSACTION") except Exception: self.setLastError("No se pudo crear la transacción", "BEGIN WORK") logger.warning( "%s:: No se pudo crear la transacción BEGIN\n %s", self.name_, traceback.format_exc(), ) return False return True def releaseSavePoint(self, n) -> bool: """Remove named savepoint from database.""" if n == 0: return True if not self.isOpen(): qWarning("%s::releaseSavePoint: Database not open" % self.name_) return False cursor = self.cursor() try: cursor.execute("RELEASE SAVEPOINT sv_%s" % n) except Exception: self.setLastError( "No se pudo release a punto de salvaguarda", "RELEASE SAVEPOINT sv_%s" % n ) qWarning( "MySQLDriver:: No se pudo release a punto de salvaguarda RELEASE SAVEPOINT sv_%s\n %s" % (n, traceback.format_exc()) ) return False return True def setType(self, type_, leng=None) -> str: """Template a SQL data type.""" if leng: return "::%s(%s)" % (type_, leng) else: return "::%s" % type_ def refreshQuery(self, curname, fields, table, where, cursor, conn) -> None: """Perform a query.""" if curname not in self.cursorsArray_.keys(): self.cursorsArray_[curname] = cursor sql = "SELECT %s FROM %s WHERE %s " % (fields, table, where) sql = self.fix_query(sql) try: self.cursorsArray_[curname].execute(sql) except Exception: print("*", sql) qWarning("CursorTableModel.Refresh\n %s" % traceback.format_exc()) def fix_query(self, val: str) -> str: """Fix values on SQL.""" ret_ = val.replace("'true'", "1") ret_ = ret_.replace("'false'", "0") ret_ = ret_.replace("'0'", "0") ret_ = ret_.replace("'1'", "1") # ret_ = ret_.replace(";", "") return ret_ def useThreads(self) -> bool: """Return if this driver supports threads.""" return False def useTimer(self) -> bool: """Return if this driver supports timer.""" return True def fetchAll(self, cursor, tablename, where_filter, fields, curname) -> List[Any]: """Fetch all pending rows on cursor.""" if curname not in self.rowsFetched.keys(): self.rowsFetched[curname] = 0 rowsF = [] try: rows = list(self.cursorsArray_[curname]) if self.rowsFetched[curname] < len(rows): i = 0 for row in rows: i += 1 if i > self.rowsFetched[curname]: rowsF.append(row) self.rowsFetched[curname] = i except Exception: logger.error("%s:: fetchAll:%s", self.name_, traceback.format_exc()) return rowsF def existsTable(self, name) -> bool: """Return if table exists.""" if not self.isOpen(): return False t = PNSqlQuery() t.setForwardOnly(True) ok = t.exec_("SHOW TABLES LIKE '%s'" % name) if ok: ok = t.next() return ok def sqlCreateTable(self, tmd) -> Optional[str]: """Create a table from given MTD.""" # util = FLUtil() if not tmd: return None primaryKey = None sql = "CREATE TABLE %s (" % tmd.name() # seq = None fieldList = tmd.fieldList() unlocks = 0 for field in fieldList: if field.type() == "unlock": unlocks += 1 if unlocks > 1: qWarning(u"%s : No se ha podido crear la tabla %s" % (self.name_, tmd.name())) qWarning(u"%s : Hay mas de un campo tipo unlock. Solo puede haber uno." % self.name_) return None i = 1 for field in fieldList: sql = sql + field.name() if field.type() == "int": sql += " INT" elif field.type() in ["uint", "serial"]: sql += " INT UNSIGNED" elif field.type() in ("bool", "unlock"): sql += " BOOL" elif field.type() == "double": sql += " DECIMAL(%s,%s)" % ( field.partInteger() + field.partDecimal() + 5, field.partDecimal() + 5, ) elif field.type() == "time": sql += " TIME" elif field.type() == "date": sql += " DATE" elif field.type() in ["pixmap", "stringlist"]: sql += " MEDIUMTEXT" elif field.type() == "string": if field.length() > 0: if field.length() > 255: sql += " VARCHAR" else: sql += " CHAR" sql += "(%s)" % field.length() else: sql += " CHAR(255)" elif field.type() == "bytearray": sql = sql + " LONGBLOB" if field.isPrimaryKey(): if primaryKey is None: sql += " PRIMARY KEY" primaryKey = field.name() else: qWarning( QApplication.tr("FLManager : Tabla-> ") + tmd.name() + QApplication.tr( " . Se ha intentado poner una segunda clave primaria para el campo " ) + field.name() + QApplication.tr(" , pero el campo ") + primaryKey + QApplication.tr( " ya es clave primaria. Sólo puede existir una clave primaria en FLTableMetaData," " use FLCompoundKey para crear claves compuestas." ) ) return None else: if field.isUnique(): sql += " UNIQUE" if not field.allowNull(): sql += " NOT NULL" else: sql += " NULL" if not i == len(fieldList): sql += "," i = i + 1 engine = ") ENGINE=INNODB" if not self.noInnoDB else ") ENGINE=MyISAM" sql += engine sql += " DEFAULT CHARACTER SET = utf8 COLLATE = utf8_bin" qWarning("NOTICE: CREATE TABLE (%s%s)" % (tmd.name(), engine)) return sql def Mr_Proper(self) -> None: """Cleanup database like mr.proper.""" util = FLUtil() if not self.db_: raise Exception("must be connected") self.db_.dbAux().transaction() qry = PNSqlQuery(None, "dbAux") qry2 = PNSqlQuery(None, "dbAux") qry3 = PNSqlQuery(None, "dbAux") # qry4 = PNSqlQuery(None, "dbAux") # qry5 = PNSqlQuery(None, "dbAux") steps = 0 self.active_create_index = False rx = QRegExp("^.*\\d{6,9}$") if rx in self.tables(): listOldBks = self.tables()[rx] else: listOldBks = [] qry.exec_( "select nombre from flfiles where nombre regexp" "'.*[[:digit:]][[:digit:]][[:digit:]][[:digit:]]-[[:digit:]][[:digit:]].*:[[:digit:]][[:digit:]]$' or nombre regexp" "'.*alteredtable[[:digit:]][[:digit:]][[:digit:]][[:digit:]].*' or (bloqueo=0 and nombre like '%.mtd')" ) util.createProgressDialog(util.tr("Borrando backups"), len(listOldBks) + qry.size() + 2) while qry.next(): item = qry.value(0) util.setLabelText(util.tr("Borrando registro %s") % item) qry2.exec_("DELETE FROM flfiles WHERE nombre ='%s'" % item) if item.find("alteredtable") > -1: if self.existsTable(item.replace(".mtd", "")): util.setLabelText(util.tr("Borrando tabla %s" % item)) qry2.exec_("DROP TABLE %s CASCADE" % item.replace(".mtd", "")) steps = steps + 1 util.setProgress(steps) for item in listOldBks: if self.existsTable(item): util.setLabelText(util.tr("Borrando tabla %s" % item)) qry2.exec_("DROP TABLE %s CASCADE" % item) steps = steps + 1 util.setProgress(steps) util.setLabelText(util.tr("Inicializando cachés")) steps = steps + 1 util.setProgress(steps) qry.exec_("DELETE FROM flmetadata") qry.exec_("DELETE FROM flvar") self.db_.manager().cleanupMetaData() # self.db_.driver().commit() util.destroyProgressDialog() steps = 0 qry3.exec_("SHOW TABLES") util.createProgressDialog(util.tr("Comprobando base de datos"), qry3.size()) while qry3.next(): item = qry3.value(0) # print("Comprobando", item) # qry2.exec_("alter table %s convert to character set utf8 collate utf8_bin" % item) mustAlter = self.mismatchedTable(item, item) if mustAlter: conte = self.db_.managerModules().content("%s.mtd" % item) if conte: msg = util.tr( "La estructura de los metadatos de la tabla '%s' y su " "estructura interna en la base de datos no coinciden. " "Intentando regenerarla." % item ) logger.warning("%s", msg) self.alterTable2(conte, conte, None, True) steps = steps + 1 util.setProgress(steps) self.db_.dbAux().driver().transaction() self.active_create_index = True steps = 0 # sqlCursor = PNSqlCursor(None, True, self.db_.dbAux()) engine = "MyISAM" if self.noInnoDB else "INNODB" convert_engine = False do_ques = True sqlQuery = PNSqlQuery(None, self.db_.dbAux()) sql_query2 = PNSqlQuery(None, self.db_.dbAux()) if sqlQuery.exec_("SHOW TABLES"): util.setTotalSteps(sqlQuery.size()) while sqlQuery.next(): item = sqlQuery.value(0) steps = steps + 1 util.setProgress(steps) util.setLabelText(util.tr("Creando índices para %s" % item)) mtd = self.db_.manager().metadata(item, True) if not mtd: continue fL = mtd.fieldList() if not fL: continue for it in fL: if not it or not it.type() == "pixmap": continue cur = PNSqlCursor(item, True, self.db_.dbAux()) cur.select(it.name() + " not like 'RK@%'") while cur.next(): v = cur.value(it.name()) if v is None: continue v = self.db_.manager().storeLargeValue(mtd, v) if v: buf = cur.primeUpdate() buf.setValue(it.name(), v) cur.update(False) # sqlCursor.setName(item, True) # self.db_.dbAux().driver().commit() sql_query2.exec_( "show table status where Engine='%s' and Name='%s'" % (engine, item) ) if not sql_query2.next(): if do_ques: res = QMessageBox.question( None, util.tr("Mr. Proper"), util.tr( "Existen tablas que no son del tipo %s utilizado por el driver de la conexión actual.\n" "Ahora es posible convertirlas, pero asegurése de tener una COPIA DE SEGURIDAD,\n" "se pueden peder datos en la conversión de forma definitiva.\n\n" "¿ Quiere convertirlas ?" % (engine) ), QMessageBox.Yes, QMessageBox.No, ) if res == QMessageBox.Yes: convert_engine = True do_ques = False if convert_engine: conte = self.db_.managerModules().content("%s.mtd" % item) self.alterTable2(conte, conte, None, True) self.active_create_index = False util.destroyProgressDialog() def alterTable(self, mtd1, mtd2, key: Optional[str], force=False) -> bool: """Alter a table following mtd instructions.""" return self.alterTable2(mtd1, mtd2, key, force) def hasCheckColumn(self, mtd) -> bool: """Retrieve if MTD has a check column.""" field_list = mtd.fieldList() if not field_list: return False for field in field_list: if field.isCheck() or field.name().endswith("_check_column"): return True return False def alterTable2(self, mtd1, mtd2, key: Optional[str], force=False) -> bool: """Alter a table following mtd instructions.""" if not self.db_: raise Exception("must be connected") util = FLUtil() oldMTD = None newMTD = None doc = QDomDocument("doc") docElem = None if not util.domDocumentSetContent(doc, mtd1): print("FLManager::alterTable : " + util.tr("Error al cargar los metadatos.")) else: docElem = doc.documentElement() oldMTD = self.db_.manager().metadata(docElem, True) if oldMTD and oldMTD.isQuery(): return True if oldMTD and self.hasCheckColumn(oldMTD): return False if not util.domDocumentSetContent(doc, mtd2): print("FLManager::alterTable : " + util.tr("Error al cargar los metadatos.")) return False else: docElem = doc.documentElement() newMTD = self.db_.manager().metadata(docElem, True) if not oldMTD: oldMTD = newMTD if not oldMTD.name() == newMTD.name(): print( "FLManager::alterTable : " + util.tr("Los nombres de las tablas nueva y vieja difieren.") ) if oldMTD and not oldMTD == newMTD: del oldMTD if newMTD: del newMTD return False oldPK = oldMTD.primaryKey() newPK = newMTD.primaryKey() if not oldPK == newPK: print( "FLManager::alterTable : " + util.tr("Los nombres de las claves primarias difieren.") ) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False if not force and self.db_.manager().checkMetaData(oldMTD, newMTD): if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return True if not self.db_.manager().existsTable(oldMTD.name()): print( "FLManager::alterTable : " + util.tr("La tabla %1 antigua de donde importar los registros no existe.").arg( oldMTD.name() ) ) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False fieldList = oldMTD.fieldList() # oldField = None if not fieldList: print("FLManager::alterTable : " + util.tr("Los antiguos metadatos no tienen campos.")) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False fieldNamesOld = [] if not force: for it in fieldList: if newMTD.field(it.name()) is not None: fieldNamesOld.append(it.name()) renameOld = "%salteredtable%s" % ( oldMTD.name()[0:5], QDateTime().currentDateTime().toString("ddhhssz"), ) if not self.db_.dbAux(): if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False # self.db_.dbAux().transaction() fieldList = newMTD.fieldList() if not fieldList: qWarning("FLManager::alterTable : " + util.tr("Los nuevos metadatos no tienen campos")) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False q = PNSqlQuery(None, "dbAux") in_sql = "ALTER TABLE %s RENAME TO %s" % (oldMTD.name(), renameOld) logger.warning(in_sql) if not q.exec_(in_sql): qWarning( "FLManager::alterTable : " + util.tr("No se ha podido renombrar la tabla antigua.") ) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False if not self.db_.manager().createTable(newMTD): self.db_.dbAux().rollbackTransaction() if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False self.db_.dbAux().transaction() if not force and key and len(key) == 40: c = PNSqlCursor("flfiles", True, self.db_.dbAux()) # oldCursor.setModeAccess(oldCursor.Browse) c.setForwardOnly(True) c.setFilter("nombre='%s.mtd'" % renameOld) c.select() if not c.next(): # c.setModeAccess(c.Insert) # c.refreshBuffer() # c.setValueBuffer("nombre","%s.mtd" % renameOld) # c.setValueBuffer("contenido", mtd1) # c.setValueBuffer("sha", key) # c.commitBuffer() in_sql = ( "INSERT INTO flfiles(nombre,contenido,idmodulo,sha) VALUES ('%s.mtd','%s','%s','%s')" % ( renameOld, mtd1, self.db_.managerModules().idModuleOfFile("%s.mtd" % oldMTD.name()), key, ) ) logger.warning(in_sql) q.exec_(in_sql) ok = False if force and fieldNamesOld: # sel = fieldNamesOld.join(",") # in_sql = "INSERT INTO %s(%s) SELECT %s FROM %s" % (newMTD.name(), sel, sel, renameOld) # logger.warning(in_sql) # ok = q.exec_(in_sql) if not ok: self.db_.dbAux().rollbackTransaction() if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return self.alterTable2(mtd1, mtd2, key, True) if not ok: from pymysql.cursors import DictCursor oldCursor = self.conn_.cursor(DictCursor) # print("Lanzando!!", "SELECT * FROM %s WHERE 1 = 1" % (renameOld)) oldCursor.execute("SELECT * FROM %s WHERE 1 = 1" % (renameOld)) result_set = oldCursor.fetchall() totalSteps = len(result_set) # oldCursor = PNSqlCursor(renameOld, True, "dbAux") # oldCursor.setModeAccess(oldCursor.Browse) # oldCursor.setForwardOnly(True) # oldCursor.select() # totalSteps = oldCursor.size() util.createProgressDialog( util.tr("Reestructurando registros para %s...") % newMTD.alias(), totalSteps ) util.setLabelText(util.tr("Tabla modificada")) step = 0 newBuffer = None newField = None listRecords = [] newBufferInfo = self.recordInfo2(newMTD.name()) vector_fields = {} default_values = {} v = None for it2 in fieldList: oldField = oldMTD.field(it2.name()) if ( oldField is None or not result_set or oldField.name() not in result_set[0].keys() ): if oldField is None: oldField = it2 if it2.type() != PNFieldMetaData.Serial: v = it2.defaultValue() step += 1 default_values[str(step)] = v step += 1 vector_fields[str(step)] = it2 step += 1 vector_fields[str(step)] = oldField # step2 = 0 ok = True x = 0 for row in result_set: x += 1 newBuffer = newBufferInfo i = 0 while i < step: v = None if str(i + 1) in default_values.keys(): i += 1 v = default_values[str(i)] i += 1 newField = vector_fields[str(i)] i += 1 oldField = vector_fields[str(i)] else: i += 1 newField = vector_fields[str(i)] i += 1 oldField = vector_fields[str(i)] v = row[newField.name()] if ( (not oldField.allowNull() or not newField.allowNull()) and (v is None) and newField.type() != PNFieldMetaData.Serial ): defVal = newField.defaultValue() if defVal is not None: v = defVal if v is not None and newField.type() == "string" and newField.length() > 0: v = v[: newField.length()] if (not oldField.allowNull() or not newField.allowNull()) and v is None: if oldField.type() == PNFieldMetaData.Serial: v = int(self.nextSerialVal(newMTD.name(), newField.name())) elif oldField.type() in ["int", "uint", "bool", "unlock"]: v = 0 elif oldField.type() == "double": v = 0.0 elif oldField.type() == "time": v = QTime.currentTime() elif oldField.type() == "date": v = QDate.currentDate() else: v = "NULL"[: newField.length()] # new_b = [] for buffer in newBuffer: if buffer[0] == newField.name(): new_buffer = [] new_buffer.append(buffer[0]) new_buffer.append(buffer[1]) new_buffer.append(newField.allowNull()) new_buffer.append(buffer[3]) new_buffer.append(buffer[4]) new_buffer.append(v) new_buffer.append(buffer[6]) listRecords.append(new_buffer) break # newBuffer.setValue(newField.name(), v) if listRecords: if not self.insertMulti(newMTD.name(), listRecords): ok = False listRecords = [] util.setProgress(totalSteps) util.destroyProgressDialog() if ok: self.db_.dbAux().commit() if force: q.exec_("DROP TABLE %s CASCADE" % renameOld) else: self.db_.dbAux().rollbackTransaction() q.exec_("DROP TABLE %s CASCADE" % oldMTD.name()) q.exec_("ALTER TABLE %s RENAME TO %s" % (renameOld, oldMTD.name())) if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return False if oldMTD and oldMTD != newMTD: del oldMTD if newMTD: del newMTD return True def insertMulti(self, table_name, records: Iterable) -> bool: """Insert several rows at once.""" if not records: return False if not self.db_: raise Exception("must be connected") mtd = self.db_.manager().metadata(table_name) fList = [] vList = [] cursor_ = self.cursor() for f in records: field = mtd.field(f[0]) if field.generated(): fList.append(field.name()) value = f[5] if field.type() in ("string", "stringlist"): value = self.db_.normalizeValue(value) value = self.formatValue(field.type(), value, False) vList.append(value) sql = """INSERT INTO %s(%s) values (%s)""" % ( table_name, ", ".join(fList), ", ".join(map(str, vList)), ) if not fList: return False try: cursor_.execute(sql) except Exception as exc: print(sql, "\n", exc) return False return True def mismatchedTable(self, table1, tmd_or_table2: str, db_=None) -> bool: """Check if table does not match MTD with database schema.""" if db_ is None: db_ = self.db_ if isinstance(tmd_or_table2, str): mtd = db_.manager().metadata(tmd_or_table2, True) if not mtd: return False mismatch = False processed_fields = [] try: recMtd = self.recordInfo(tmd_or_table2) recBd = self.recordInfo2(table1) if recMtd is None: raise Exception("Error obtaining recordInfo for %s" % tmd_or_table2) # fieldBd = None for fieldMtd in recMtd: # fieldBd = None found = False for field in recBd: if field[0] == fieldMtd[0]: processed_fields.append(field[0]) found = True if self.notEqualsFields(field, fieldMtd): mismatch = True recBd.remove(field) break if not found: if fieldMtd[0] not in processed_fields: mismatch = True break if len(recBd) > 0: mismatch = True except Exception: logger.exception("mismatchedTable: Unexpected error") return mismatch else: return self.mismatchedTable(table1, tmd_or_table2.name(), db_) def recordInfo2(self, tablename) -> List[list]: """Obtain current cursor information on columns.""" if not self.isOpen(): raise Exception("MYISAM2: conn not opened") if not self.conn_: raise Exception("must be connected") info = [] cursor = self.conn_.cursor() cursor.execute("SHOW FIELDS FROM %s" % tablename) # print("Campos", tablename) for field in cursor.fetchall(): col_name = field[0] allow_null = True if field[2] == "NO" else False tipo_ = field[1] if field[1].find("(") > -1: tipo_ = field[1][: field[1].find("(")] # len_ len_ = "0" if field[1].find("(") > -1: len_ = field[1][field[1].find("(") + 1 : field[1].find(")")] precision_ = 0 tipo_ = self.decodeSqlType(tipo_) if tipo_ in ["uint", "int", "double"]: len_ = "0" # print("****", tipo_, field) else: if len_.find(",") > -1: precision_ = int(len_[len_.find(",") :]) len_ = len_[: len_.find(",")] len_n = int(len_) if len_n == 255 and tipo_ == "string": len_n = 0 default_value_ = field[4] primary_key_ = True if field[3] == "PRI" else False # print("***", field) # print("Nombre:", col_name) # print("Tipo:", tipo_) # print("Nulo:", allow_null) # print("longitud:", len_) # print("Precision:", precision_) # print("Defecto:", default_value_) info.append( [col_name, tipo_, allow_null, len_n, precision_, default_value_, primary_key_] ) # info.append(desc[0], desc[1], not desc[6], , part_decimal, default_value, is_primary_key) return info def decodeSqlType(self, t: str) -> str: """Translate types.""" ret = t if t in ["char", "varchar", "text"]: ret = "string" elif t == "int": ret = "uint" elif t == "date": ret = "date" elif t == "mediumtext": ret = "stringlist" elif t == "tinyint": ret = "bool" elif t in ["decimal", "double"]: ret = "double" elif t == "longblob": ret = "bytearray" elif t == "time": ret = "time" else: logger.warning("formato desconocido %s", ret) return ret def recordInfo(self, tablename_or_query: str) -> Optional[List[list]]: """Obtain current cursor information on columns.""" if not self.isOpen(): return None if not self.db_: raise Exception("Must be connected") info = [] if isinstance(tablename_or_query, str): tablename = tablename_or_query doc = QDomDocument(tablename) stream = self.db_.managerModules().contentCached("%s.mtd" % tablename) util = FLUtil() if not util.domDocumentSetContent(doc, stream): print( "FLManager : " + QApplication.tr("Error al cargar los metadatos para la tabla") + tablename ) return self.recordInfo2(tablename) # docElem = doc.documentElement() mtd = self.db_.manager().metadata(tablename, True) if not mtd: return self.recordInfo2(tablename) fL = mtd.fieldList() if not fL: del mtd return self.recordInfo2(tablename) for f in mtd.fieldNames(): field = mtd.field(f) info.append( [ field.name(), field.type(), not field.allowNull(), field.length(), field.partDecimal(), field.defaultValue(), field.isPrimaryKey(), ] ) del mtd return info def notEqualsFields(self, field1: List[Any], field2: List[Any]) -> bool: """Check if two field definitions are equal.""" # print("comparando", field1, field1[1], field2, field2[1]) ret = False try: if not field1[2] == field2[2] and not field2[6]: ret = True if field1[1] == "stringlist" and not field2[1] in ("stringlist", "pixmap"): ret = True elif field1[1] == "string" and ( not field2[1] in ("string", "time", "date") or not field1[3] == field2[3] ): if field1[3] == 0 and field2[3] == 255: pass else: ret = True elif field1[1] == "uint" and not field2[1] in ("int", "uint", "serial"): ret = True elif field1[1] == "bool" and not field2[1] in ("bool", "unlock"): ret = True elif field1[1] == "double" and not field2[1] == "double": ret = True except Exception: print(traceback.format_exc()) return ret def normalizeValue(self, text) -> Optional[str]: """Escape values, suitable to prevent sql injection.""" if text is None: return None import pymysql return pymysql.escape_string(text) # text = text.replace("'", "''") # text = text.replace('\\"', '\\\\"') # text = text.replace("\\n", "\\\\n") # text = text.replace("\\r", "\\\\r") # return text def cascadeSupport(self) -> bool: """Check if database supports CASCADE.""" return True def canDetectLocks(self) -> bool: """Check if driver can detect locks.""" return True def desktopFile(self) -> bool: """Return if this database is a file.""" return False def execute_query(self, q: str) -> Any: """Execute a SQL query.""" if not self.isOpen(): logger.warning("MySQLDriver::execute_query. DB is closed") return False cursor = self.cursor() try: q = self.fix_query(q) cursor.execute(q) except Exception: self.setLastError("No se puedo ejecutar la siguiente query %s" % q, q) logger.warning( "MySQLDriver:: No se puedo ejecutar la siguiente query %s\n %s", q, traceback.format_exc(), ) return cursor
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1.823421
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# -*- coding: utf-8 -*- #! \file ./doit/support/cmd/errors.py #! \author Jiří Kučera, <sanczes@gmail.com> #! \stamp 2016-02-15 13:19:12 (UTC+01:00, DST+00:00) #! \project DoIt!: Tools and Libraries for Building DSLs #! \license MIT #! \version 0.0.0 #! \fdesc @pyfile.docstr # """\ Command processor's errors.\ """ __license__ = """\ Copyright (c) 2014 - 2017 Jiří Kučera. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\ """ from doit.support.errors import DoItError ERROR_COMMAND_PROCESSOR = DoItError.alloc_codes(1) ERROR_COMMAND = DoItError.alloc_codes(1) class CommandProcessorError(DoItError): """ """ __slots__ = [ 'traceback' ] def __init__(self, tb, emsg): """ """ DoItError.__init__(self, ERROR_COMMAND_PROCESSOR, emsg) self.traceback = tb #-def def __str__(self): """ """ if self.traceback is not None: return "%s %s" % (self.traceback, DoItError.__str__(self)) return DoItError.__str__(self) #-def #-class class CommandError(DoItError): """ """ __slots__ = [ 'ecls', 'emsg', 'tb' ] def __init__(self, ecls, emsg, tb): """ """ DoItError.__init__(self, ERROR_COMMAND, "%s: %s" % (ecls, emsg)) self.ecls = ecls self.emsg = emsg self.tb = tb #-def def __repr__(self): """ """ return "%s(\"%s\")" % (self.ecls, self.emsg) #-def #-class
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2.432879
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#!/usr/bin/env python # Copyright 2015 Google Inc. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Read config file for noto tools. One could also just define some environment variables, but using Python for this lets you keep your environment and shell prefs clean. This expects a file named '.notoconfig' in the users home directory. It should contain lines consisting of a name, '=' and a path. The expected names are 'noto_tools', 'noto_fonts', 'noto_cjk', 'noto_emoji', and 'noto_source'. The values are absolute paths to the base directories of these noto repositories. Formerly these were a single repository so the paths could all be reached from a single root, but that is no longer the case. """ from os import path _ERR_MSG = """ Could not find ~/.notoconfig or /usr/local/share/noto/config. Nototools uses this file to locate resources it uses, since many resources such as fonts and sample_texts are not installed in locations relative to the nototools python files and scripts. Please create one of the above config files containing a line like the following, where the absolute path to the root of the git repo on your machine follows the '=' character: noto_tools=/path/to/root/of/nototools If you use any of the other noto repos, add similar lines for 'noto_emoji', 'noto_fonts', 'noto_cjk', 'noto_source', or 'noto_fonts_alpha'. """ _values = {} _config_path = None # so we know def _setup(): """The config consists of lines of the form <name> = <value>. values will hold a mapping from the <name> to value. Blank lines and lines starting with '#' are ignored.""" global _config_path paths = [path.expanduser("~/.notoconfig"), "/usr/local/share/noto/config"] for configfile in paths: if path.exists(configfile): with open(configfile, "r") as f: for line in f: line = line.strip() if not line or line.startswith("#"): continue k, v = line.split("=", 1) _values[k.strip()] = v.strip() _config_path = configfile break # This needs to be silent. It causes a makefile error in noto-emoji, # which expects stdout to consist only of the output of a python # script it runs. _setup() # convenience for names we expect. # By default we allow running without a config, since many small tools don't # require it. But if you run code that calls noto_tools and provides no # default, we assume you do require it and raise an exception. def noto_tools(default=""): """Local path to nototools git repo. If this is called, we require config to be set up.""" result = _values.get("noto_tools", default) if result: return result raise Exception(_ERR_MSG) def noto_fonts(default=""): """Local path to noto-font git repo""" return _values.get("noto_fonts", default) def noto_cjk(default=""): """Local path to noto-cjk git repo""" return _values.get("noto_cjk", default) def noto_emoji(default=""): """Local path to noto-emoji git repo""" return _values.get("noto_emoji", default) def noto_source(default=""): """Local path to noto-source git repo""" return _values.get("noto_source", default) def noto_fonts_alpha(default=""): """Local path to noto-fonts-alpha git repo""" return _values.get("noto_fonts_alpha", default) if __name__ == "__main__": keyset = set(_values.keys()) if not keyset: print("no keys defined, probably no notoconfig file was found.") else: wid = max(len(k) for k in keyset) fmt = "%%%ds: %%s" % wid for k in sorted(keyset): print(fmt % (k, get(k))) print("config: %s" % _config_path)
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2.853351
1,507
import os import re for svg in [file for file in os.listdir(os.getcwd()) if '.svg' in file]: file_path = '{}/{}'.format(os.getcwd(), svg) with open (file_path, 'r', encoding='utf-8') as svg_file: content = svg_file.read() target = re.search('fill=".*?"', content) if target != None: fixed_content = content.replace(target.group(), '') with open (file_path, 'w', encoding='utf-8') as svg_file: svg_file.write(fixed_content) print('done 1') print('all done')
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2.172691
249
import base64
[ 11748, 2779, 2414, 628 ]
3.75
4
from datetime import datetime @execution_time random_func()
[ 6738, 4818, 8079, 1330, 4818, 8079, 628, 198, 31, 18558, 1009, 62, 2435, 628, 198, 25120, 62, 20786, 3419 ]
3.315789
19
# Copyright 2018 Analytics Zoo Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import json import pandas as pd from prophet import Prophet from prophet.serialize import model_to_json, model_from_json from zoo.automl.common.metrics import Evaluator from zoo.automl.model.abstract import BaseModel, ModelBuilder
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3.707207
222
# pylint: disable=too-few-public-methods,missing-docstring highlight = Highlight()
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2.9
30
# -*- coding: utf-8 -*- import json import gzip import math import multiprocessing as mp import os import re import shutil from tempfile import mkstemp from typing import Optional, Sequence from xml.dom.minidom import getDOMImplementation, parseString from xml.parsers.expat import ExpatError import cx_Oracle import MySQLdb import MySQLdb.cursors from interpro7dw import logger from interpro7dw.ebi import pdbe from interpro7dw.ebi.interpro import production as ippro, utils from interpro7dw.utils import DumpFile, KVdb, Store, loadobj, url2dict _DC_STATUSES = {v: k for k, v in utils.DC_STATUSES.items()} _TAGS = { "cazy": "CAZY", "cog": "COG", "genprop": "GENPROP", "ec": "EC", "intenz": "EC", "interpro": "INTERPRO", "pfam": "PFAM", "pdbe": "PDBE", "pirsf": "PIRSF", "prosite": "PROSITE", "prositedoc": "PROSITEDOC", "superfamily": "SSF", "swissprot": "SWISSPROT", "tigrfams": "TIGRFAMs" }
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2.386139
404
import pytest import math import numpy as np from ball import ball import matplotlib.pyplot as plt import copy from itertools import combinations import sys import pandas as pd from calculator import calculator import json import dataframes from plotter import plotter from random import random ''' in order to test the functions of the plotter class, data must be collected to plot In order to test the simplest aspects - such as that total energy = pe+ke, and conservation of energy, the simulation of a single ball - a simple pendulum - will be tested ''' def test_list_lengths(): ''' lots of lists are created by the plotter class, and the length of them should be known, as it should be the number of iterations in a lot of case ''' ''' as testing class attributes, not results, need to call a new class instance''' theta = math.pi/6 #initial starting angle! get_results = calculator(0.0001,50000) get_results.get_balls(number = 1,positions= [[1 * math.sin(theta), -1 * math.cos(theta)]], velocities= [[0,0]], radii=[0.02], masses=[1], anchors= [[0,0]]) get_results.calculate(approximation='rk2', density=0) plot = plotter('system_states_over_time', 1) assert len(plot.timelist) == 50000 assert len(plot.total_ke_list) == 50000 assert len(plot.total_pe_list) == 50000 assert len(plot.total_energy_by_time) == 50000 assert len(plot.potential_energy_by_time) == 50000 assert len(plot.kinetic_energy_by_time) == 50000 assert len(plot.list_position_by_time) == 50000 def test_energy_addition(): ''' test to ensure that the when adding kinetic and potential energy to get total energy, that the addition is done correctly ''' ''' use is close due to errors in floating point maths''' energies = plotter_init() ke = energies[0] pe = energies[1] total = energies[2] assert (np.isclose(total[0] , (np.add(ke[0] , pe[0])))).all(), "total energy does not equal potential plus kinetic at the start" random_time = 50000 * random() random_time_int = math.floor(random_time) assert (np.isclose(total[random_time_int], (np.add(ke[random_time_int] ,pe[random_time_int])))).all(), "total energy does not equal potential plus kinetic at the a random point" def two_ball_init(): ''' some of the results rely on the tota energy of the system, and therefore this is to check that these things are caluclated correctly with a more complicated system ''' theta = math.pi/6 #initial starting angle! get_results = calculator(0.0001,50000) get_results.get_balls(number = 2,positions= [[1 * math.sin(theta), -1 * math.cos(theta)], [0,-0.4]], velocities= [[0,0], [0,0]], radii=[0.02,0.02], masses=[1,1], anchors= [[0,0], [0.4]]) get_results.calculate(approximation='rk2', density=0) plot = plotter('system_states_over_time', 2) return plot def test_two_ball_energy(): ''' testing that the total energy of the system is calculated correctly - kinetic plus potential. ''' plot = two_ball_init() ke = plot.total_kinetic_energy pe = plot.total_potential_energy total = plot.total_energy() ke_plus_pe = ke + pe assert np.isclose(ke_plus_pe[0], total[0]).all(), "total energy not equal to kinetic plus potential at start" random_time = 50000 * random() random_time_int = math.floor(random_time) assert np.isclose(ke_plus_pe[random_time_int], total[random_time_int]).all(), "total energy not equal to kinetic plus potential at random time"
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2.891606
1,227
# functions/add.py import torch from torch.autograd import Function from _ext import my_lib
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3.444444
27