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#!/usr/bin/env python from __future__ import print_function from optparse import OptionParser import os import sys class ReadsSplitter: def __init__(self): self.options = None self.files_to_split = [] self.getOptions() def go(self): for fn in self.files_to_split: self.splitFile(fn) def getOptions(self): parser = OptionParser() parser.add_option("-u", "--unaligned", dest="unaligned_dir", \ help="Unaligned read directory", metavar="DIR") parser.add_option("-o", "--output", dest="output_dir",\ help="Directory for output", metavar="DIR",\ default="data/output/breakpoints/reads") (options, args) = parser.parse_args() self.options = options if options.unaligned_dir: for file_name in os.listdir(options.unaligned_dir): if 'unaligned' in file_name: self.files_to_split.append(options.unaligned_dir + file_name) def splitFile(self, fn): if not os.path.isfile(fn): warning("%s DOES NOT EXIST" %(fn)) exit(1) read_split_output_dir = self.options.output_dir ensure_dir(read_split_output_dir) read_split_output_1 = read_split_output_dir + os.path.split(fn)[1] + ".1" read_split_output_2 = read_split_output_dir + os.path.split(fn)[1] + ".2" read_file = open(fn, 'r') r_o_1 = open(read_split_output_1, 'w') r_o_2 = open(read_split_output_2, 'w') for read in self.read_read(read_file): h1 = read[0].strip() read_contents = read[1].strip() h2 = read[2].strip() read_quality = read[3].strip() # l = len(read_contents) l_1 = int(l / 3) l_2 = int(l - l_1) # left h1_1 = h1 + "/1\n" read_contents_1 = read_contents[0:l_1] + "\n" h2_1 = h2 + "/1\n" read_quality_1 = read_quality[0:l_1] + "\n" # right h1_2 = h1 + "/2\n" read_contents_2 = read_contents[l_2:]+ "\n" h2_2 = h2 + "/2\n" read_quality_2 = read_quality[l_2:] + "\n" r_o_1.write(h1_1) r_o_1.write(read_contents_1) r_o_1.write(h2_1) r_o_1.write(read_quality_1) r_o_2.write(h1_2) r_o_2.write(read_contents_2) r_o_2.write(h2_2) r_o_2.write(read_quality_2) r_o_1.close() r_o_2.close() read_file.close() def read_read(self, fp): while True: read_bundle = [] for i in range(4): read_bundle.append(fp.readline()) if not read_bundle[0]: break else: yield read_bundle def ensure_dir(f): d = os.path.dirname(f) if not os.path.exists(d): os.makedirs(d) def warning(*objs): print("\tINFO: ",*objs, file=sys.stderr) def main(): ''' splits read files for breakpoint ''' splitter = ReadsSplitter() splitter.go() if __name__=='__main__': main()
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# -*- coding: utf-8 -*- ''' Copyright (c) 2019 Colin Curtain 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. Author: Colin Curtain (ccbogel) https://github.com/ccbogel/QualCoder https://qualcoder.wordpress.com/ ''' from PyQt5 import QtWidgets, QtCore import os import sys import logging import traceback from GUI.ui_dialog_information import Ui_Dialog_information path = os.path.abspath(os.path.dirname(__file__)) logger = logging.getLogger(__name__) def exception_handler(exception_type, value, tb_obj): """ Global exception handler useful in GUIs. tb_obj: exception.__traceback__ """ tb = '\n'.join(traceback.format_tb(tb_obj)) text = 'Traceback (most recent call last):\n' + tb + '\n' + exception_type.__name__ + ': ' + str(value) print(text) logger.error(_("Uncaught exception: ") + text) QtWidgets.QMessageBox.critical(None, _('Uncaught Exception'), text) class DialogInformation(QtWidgets.QDialog): """ Dialog to display about information from html and text files for PyQDA development, version and license. The html is coded below because it avoids potential data file import errors with pyinstaller. Called from: qualcoder.MainWindow.about view_graph_original.ViewGraphOriginal.list_graph.TextGraphicsItem view_graph_original.ViewGraphOriginal.circular_graph.TextGraphicsItem """ title = "" text = "" def __init__(self, app, title, html="", parent=None): """Display information text in dialog. If no html is given, fill with About html. """ sys.excepthook = exception_handler QtWidgets.QDialog.__init__(self) self.ui = Ui_Dialog_information() self.ui.setupUi(self) self.setWindowFlags(self.windowFlags() & ~QtCore.Qt.WindowContextHelpButtonHint) font = 'font: ' + str(app.settings['fontsize']) + 'pt ' font += '"' + app.settings['font'] + '";' self.setStyleSheet(font) self.setWindowTitle(title) if html == "": self.setHtml(a) else: self.setHtml(html) def setHtml(self, html): """This method is used to populate the textEdit. Usually called from a View_graph TextGraphicsItem via a context menu. """ self.text = html self.ui.textEdit.setHtml(self.text) def accepted(self): """ Accepted button overridden method """ self.information = self.ui.textEdit.toPlainText() self.ui.Dialog_information.accept() a = '<h1 class="western">About QualCoder</h1>\ <h2 class="western">Version:</h2>\ <p>QualCoder 1.9 2020 March 11</p>\ <p>Depends on python 3.x, pyqt5 lxml Pillow ebooklib ply chardet pdfminer.six openpyxl</p>\ <p>VLC should also be installed.</p>\ <p>Tested on: Linux Mint 18.04, Ubuntu 19.04, Lubuntu 18.04, mostly tested on Windows 10, partly tested on Mac OS.</p>\ <p></p>\ <h2 class="western">Acknowledgements</h2>\ <p>Ronggui Huang and Zhang Gehao for creating RQDA, which inspired this software.</p>\ <p>Mike MacCana for the source code for the docx module.</p>\ <p>User: bit4 on stackoverflow who presented the source code to convert html to text.</p>\ <p>ebooklib: Aleksandar Erkalović (<a href="https://github.com/aerkalov">https://github.com/aerkalov</a>)</p>\ <p>The VideoLAN team for the bindings to VLC</p>\ <p>To various members on github for supporting this project.</p>\ <h2 class="western">Other details</h2\ <p>The qda data folder contains folders for imported documents, \ images, audio and video. It also contains the sqlite database, named data.qda, to store coding data.</p>\ <p>QualCoder creates a .qualcoder folder inside your home directory. \ This contains QualCoder.log, config.ini (for settings) and \ recent_project.txt. The config file contains the name of the current coder, \ default working directory and selected font.</p>\ <p>QualCoder is written in python 3 using Qt5 for the graphical interface.</p>\ <p>The REFI-QDA Project import and export are experimental and should not be relied upon. </p>\ <h2 class="western">License</h2>\ <p>MIT License</p>\ <p>Copyright (c) 2020 Colin Curtain</p>\ <p>Permission is hereby granted, free of charge, to any person<br />\ obtaining a copy of this software and associated documentation files<br />\ (the &quot;Software&quot;), to deal in the Software without<br />\ restriction, including without limitation the rights to use, copy,<br />\ modify, merge, publish, distribute, sublicense, and/or sell copies of<br />\ the Software, and to permit persons to whom the Software is furnished<br />\ to do so, subject to the following conditions:</p>\ <p>The above copyright notice and this permission notice shall be <br />\ included in all copies or substantial portions of the Software.</p>\ <p>THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF<br />\ ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE<br />\ WARRANTIES OF MERCHANTABILITY,</p>\ <p>FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT<br />\ SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,<br />\ DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR<br />\ OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR<br />\ THE USE OR OTHER DEALINGS IN THE SOFTWARE.</p>' if __name__ == "__main__": app = QtWidgets.QApplication(sys.argv) ui = DialogInformation(None, "a title", "") ui.show() sys.exit(app.exec_())
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# coding: utf-8 """ LUSID API FINBOURNE Technology # noqa: E501 The version of the OpenAPI document: 0.11.2342 Contact: info@finbourne.com Generated by: https://openapi-generator.tech """ import pprint import re # noqa: F401 import six class ResourceListOfPortfolio(object): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. """ """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. required_map (dict): The key is attribute name and the value is whether it is 'required' or 'optional'. """ openapi_types = { 'values': 'list[Portfolio]', 'href': 'str', 'links': 'list[Link]' } attribute_map = { 'values': 'values', 'href': 'href', 'links': 'links' } required_map = { 'values': 'required', 'href': 'optional', 'links': 'optional' } def __init__(self, values=None, href=None, links=None): # noqa: E501 """ ResourceListOfPortfolio - a model defined in OpenAPI :param values: (required) :type values: list[lusid.Portfolio] :param href: :type href: str :param links: :type links: list[lusid.Link] """ # noqa: E501 self._values = None self._href = None self._links = None self.discriminator = None self.values = values self.href = href self.links = links @property def values(self): """Gets the values of this ResourceListOfPortfolio. # noqa: E501 :return: The values of this ResourceListOfPortfolio. # noqa: E501 :rtype: list[Portfolio] """ return self._values @values.setter def values(self, values): """Sets the values of this ResourceListOfPortfolio. :param values: The values of this ResourceListOfPortfolio. # noqa: E501 :type: list[Portfolio] """ if values is None: raise ValueError("Invalid value for `values`, must not be `None`") # noqa: E501 self._values = values @property def href(self): """Gets the href of this ResourceListOfPortfolio. # noqa: E501 :return: The href of this ResourceListOfPortfolio. # noqa: E501 :rtype: str """ return self._href @href.setter def href(self, href): """Sets the href of this ResourceListOfPortfolio. :param href: The href of this ResourceListOfPortfolio. # noqa: E501 :type: str """ self._href = href @property def links(self): """Gets the links of this ResourceListOfPortfolio. # noqa: E501 :return: The links of this ResourceListOfPortfolio. # noqa: E501 :rtype: list[Link] """ return self._links @links.setter def links(self, links): """Sets the links of this ResourceListOfPortfolio. :param links: The links of this ResourceListOfPortfolio. # noqa: E501 :type: list[Link] """ self._links = links def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.openapi_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, ResourceListOfPortfolio): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other
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# (C) British Crown Copyright 2018, Met Office # # This file is part of cartopy. # # cartopy is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the # Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # cartopy is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License # along with cartopy. If not, see <https://www.gnu.org/licenses/>. """ Tests for the UTM coordinate system. """ from __future__ import (absolute_import, division, print_function) import numpy as np from numpy.testing import assert_almost_equal import pytest import cartopy.crs as ccrs def check_proj4_params(crs, other_args): expected = other_args | {'proj=utm', 'no_defs', 'units=m'} pro4_params = set(crs.proj4_init.lstrip('+').split(' +')) assert expected == pro4_params @pytest.mark.parametrize('south', [False, True]) def test_default(south): zone = 1 # Limits are fixed, so don't bother checking other zones. utm = ccrs.UTM(zone, southern_hemisphere=south) other_args = {'ellps=WGS84', 'zone={}'.format(zone)} if south: other_args |= {'south'} check_proj4_params(utm, other_args) assert_almost_equal(np.array(utm.x_limits), [-250000, 1250000]) assert_almost_equal(np.array(utm.y_limits), [-10000000, 25000000]) def test_ellipsoid_transform(): # USGS Professional Paper 1395, pp 269 - 271 globe = ccrs.Globe(ellipse='clrk66') utm = ccrs.UTM(zone=18, globe=globe) geodetic = utm.as_geodetic() other_args = {'ellps=clrk66', 'zone=18'} check_proj4_params(utm, other_args) assert_almost_equal(np.array(utm.x_limits), [-250000, 1250000]) assert_almost_equal(np.array(utm.y_limits), [-10000000, 25000000]) result = utm.transform_point(-73.5, 40.5, geodetic) assert_almost_equal(result, np.array([127106.5 + 500000, 4484124.4]), decimal=1) inverse_result = geodetic.transform_point(result[0], result[1], utm) assert_almost_equal(inverse_result, [-73.5, 40.5])
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import numpy as np import pyqtgraph as pg from datetime import datetime, timedelta from vnpy.trader.constant import Interval, Direction, Offset from vnpy.trader.engine import MainEngine from vnpy.trader.ui import QtCore, QtWidgets, QtGui from vnpy.trader.ui.widget import BaseMonitor, BaseCell, DirectionCell, EnumCell from vnpy.trader.ui.editor import CodeEditor from vnpy.event import Event, EventEngine from vnpy.chart import ChartWidget, CandleItem, VolumeItem from vnpy.trader.utility import load_json, save_json from ..engine import ( APP_NAME, EVENT_BACKTESTER_LOG, EVENT_BACKTESTER_BACKTESTING_FINISHED, EVENT_BACKTESTER_OPTIMIZATION_FINISHED, OptimizationSetting ) class BacktesterManager(QtWidgets.QWidget): """""" setting_filename = "cta_backtester_setting.json" signal_log = QtCore.pyqtSignal(Event) signal_backtesting_finished = QtCore.pyqtSignal(Event) signal_optimization_finished = QtCore.pyqtSignal(Event) def __init__(self, main_engine: MainEngine, event_engine: EventEngine): """""" super().__init__() self.main_engine = main_engine self.event_engine = event_engine self.backtester_engine = main_engine.get_engine(APP_NAME) self.class_names = [] self.settings = {} self.target_display = "" self.init_ui() self.register_event() self.backtester_engine.init_engine() self.init_strategy_settings() def init_strategy_settings(self): """""" self.class_names = self.backtester_engine.get_strategy_class_names() for class_name in self.class_names: setting = self.backtester_engine.get_default_setting(class_name) self.settings[class_name] = setting self.class_combo.addItems(self.class_names) def init_ui(self): """""" self.setWindowTitle("CTA回测") # Setting Part self.class_combo = QtWidgets.QComboBox() self.symbol_line = QtWidgets.QLineEdit("IF88.CFFEX") self.interval_combo = QtWidgets.QComboBox() for inteval in Interval: self.interval_combo.addItem(inteval.value) end_dt = datetime.now() start_dt = end_dt - timedelta(days=3 * 365) self.start_date_edit = QtWidgets.QDateEdit( QtCore.QDate( start_dt.year, start_dt.month, start_dt.day ) ) self.end_date_edit = QtWidgets.QDateEdit( QtCore.QDate.currentDate() ) self.rate_line = QtWidgets.QLineEdit("0.000025") self.slippage_line = QtWidgets.QLineEdit("0.2") self.size_line = QtWidgets.QLineEdit("300") self.pricetick_line = QtWidgets.QLineEdit("0.2") self.capital_line = QtWidgets.QLineEdit("1000000") self.inverse_combo = QtWidgets.QComboBox() self.inverse_combo.addItems(["正向", "反向"]) backtesting_button = QtWidgets.QPushButton("开始回测") backtesting_button.clicked.connect(self.start_backtesting) optimization_button = QtWidgets.QPushButton("参数优化") optimization_button.clicked.connect(self.start_optimization) self.result_button = QtWidgets.QPushButton("优化结果") self.result_button.clicked.connect(self.show_optimization_result) self.result_button.setEnabled(False) downloading_button = QtWidgets.QPushButton("下载数据") downloading_button.clicked.connect(self.start_downloading) self.order_button = QtWidgets.QPushButton("委托记录") self.order_button.clicked.connect(self.show_backtesting_orders) self.order_button.setEnabled(False) self.trade_button = QtWidgets.QPushButton("成交记录") self.trade_button.clicked.connect(self.show_backtesting_trades) self.trade_button.setEnabled(False) self.daily_button = QtWidgets.QPushButton("每日盈亏") self.daily_button.clicked.connect(self.show_daily_results) self.daily_button.setEnabled(False) self.candle_button = QtWidgets.QPushButton("K线图表") self.candle_button.clicked.connect(self.show_candle_chart) self.candle_button.setEnabled(False) edit_button = QtWidgets.QPushButton("代码编辑") edit_button.clicked.connect(self.edit_strategy_code) reload_button = QtWidgets.QPushButton("策略重载") reload_button.clicked.connect(self.reload_strategy_class) for button in [ backtesting_button, optimization_button, downloading_button, self.result_button, self.order_button, self.trade_button, self.daily_button, self.candle_button, edit_button, reload_button ]: button.setFixedHeight(button.sizeHint().height() * 2) form = QtWidgets.QFormLayout() form.addRow("交易策略", self.class_combo) form.addRow("本地代码", self.symbol_line) form.addRow("K线周期", self.interval_combo) form.addRow("开始日期", self.start_date_edit) form.addRow("结束日期", self.end_date_edit) form.addRow("手续费率", self.rate_line) form.addRow("交易滑点", self.slippage_line) form.addRow("合约乘数", self.size_line) form.addRow("价格跳动", self.pricetick_line) form.addRow("回测资金", self.capital_line) form.addRow("合约模式", self.inverse_combo) result_grid = QtWidgets.QGridLayout() result_grid.addWidget(self.trade_button, 0, 0) result_grid.addWidget(self.order_button, 0, 1) result_grid.addWidget(self.daily_button, 1, 0) result_grid.addWidget(self.candle_button, 1, 1) left_vbox = QtWidgets.QVBoxLayout() left_vbox.addLayout(form) left_vbox.addWidget(backtesting_button) left_vbox.addWidget(downloading_button) left_vbox.addStretch() left_vbox.addLayout(result_grid) left_vbox.addStretch() left_vbox.addWidget(optimization_button) left_vbox.addWidget(self.result_button) left_vbox.addStretch() left_vbox.addWidget(edit_button) left_vbox.addWidget(reload_button) # Result part self.statistics_monitor = StatisticsMonitor() self.log_monitor = QtWidgets.QTextEdit() self.log_monitor.setMaximumHeight(400) self.chart = BacktesterChart() self.chart.setMinimumWidth(1000) self.trade_dialog = BacktestingResultDialog( self.main_engine, self.event_engine, "回测成交记录", BacktestingTradeMonitor ) self.order_dialog = BacktestingResultDialog( self.main_engine, self.event_engine, "回测委托记录", BacktestingOrderMonitor ) self.daily_dialog = BacktestingResultDialog( self.main_engine, self.event_engine, "回测每日盈亏", DailyResultMonitor ) # Candle Chart self.candle_dialog = CandleChartDialog() # Layout vbox = QtWidgets.QVBoxLayout() vbox.addWidget(self.statistics_monitor) vbox.addWidget(self.log_monitor) hbox = QtWidgets.QHBoxLayout() hbox.addLayout(left_vbox) hbox.addLayout(vbox) hbox.addWidget(self.chart) self.setLayout(hbox) # Code Editor self.editor = CodeEditor(self.main_engine, self.event_engine) # Load setting setting = load_json(self.setting_filename) if not setting: return self.class_combo.setCurrentIndex( self.class_combo.findText(setting["class_name"]) ) self.symbol_line.setText(setting["vt_symbol"]) self.interval_combo.setCurrentIndex( self.interval_combo.findText(setting["interval"]) ) self.rate_line.setText(str(setting["rate"])) self.slippage_line.setText(str(setting["slippage"])) self.size_line.setText(str(setting["size"])) self.pricetick_line.setText(str(setting["pricetick"])) self.capital_line.setText(str(setting["capital"])) if not setting["inverse"]: self.inverse_combo.setCurrentIndex(0) else: self.inverse_combo.setCurrentIndex(1) def register_event(self): """""" self.signal_log.connect(self.process_log_event) self.signal_backtesting_finished.connect( self.process_backtesting_finished_event) self.signal_optimization_finished.connect( self.process_optimization_finished_event) self.event_engine.register(EVENT_BACKTESTER_LOG, self.signal_log.emit) self.event_engine.register( EVENT_BACKTESTER_BACKTESTING_FINISHED, self.signal_backtesting_finished.emit) self.event_engine.register( EVENT_BACKTESTER_OPTIMIZATION_FINISHED, self.signal_optimization_finished.emit) def process_log_event(self, event: Event): """""" msg = event.data self.write_log(msg) def write_log(self, msg): """""" timestamp = datetime.now().strftime("%H:%M:%S") msg = f"{timestamp}\t{msg}" self.log_monitor.append(msg) def process_backtesting_finished_event(self, event: Event): """""" statistics = self.backtester_engine.get_result_statistics() self.statistics_monitor.set_data(statistics) df = self.backtester_engine.get_result_df() self.chart.set_data(df) self.trade_button.setEnabled(True) self.order_button.setEnabled(True) self.daily_button.setEnabled(True) self.candle_button.setEnabled(True) def process_optimization_finished_event(self, event: Event): """""" self.write_log("请点击[优化结果]按钮查看") self.result_button.setEnabled(True) def start_backtesting(self): """""" class_name = self.class_combo.currentText() vt_symbol = self.symbol_line.text() interval = self.interval_combo.currentText() start = self.start_date_edit.date().toPyDate() end = self.end_date_edit.date().toPyDate() rate = float(self.rate_line.text()) slippage = float(self.slippage_line.text()) size = float(self.size_line.text()) pricetick = float(self.pricetick_line.text()) capital = float(self.capital_line.text()) if self.inverse_combo.currentText() == "正向": inverse = False else: inverse = True # Save backtesting parameters backtesting_setting = { "class_name": class_name, "vt_symbol": vt_symbol, "interval": interval, "rate": rate, "slippage": slippage, "size": size, "pricetick": pricetick, "capital": capital, "inverse": inverse, } save_json(self.setting_filename, backtesting_setting) # Get strategy setting old_setting = self.settings[class_name] dialog = BacktestingSettingEditor(class_name, old_setting) i = dialog.exec() if i != dialog.Accepted: return new_setting = dialog.get_setting() self.settings[class_name] = new_setting result = self.backtester_engine.start_backtesting( class_name, vt_symbol, interval, start, end, rate, slippage, size, pricetick, capital, inverse, new_setting ) if result: self.statistics_monitor.clear_data() self.chart.clear_data() self.trade_button.setEnabled(False) self.order_button.setEnabled(False) self.daily_button.setEnabled(False) self.candle_button.setEnabled(False) self.trade_dialog.clear_data() self.order_dialog.clear_data() self.daily_dialog.clear_data() self.candle_dialog.clear_data() def start_optimization(self): """""" class_name = self.class_combo.currentText() vt_symbol = self.symbol_line.text() interval = self.interval_combo.currentText() start = self.start_date_edit.date().toPyDate() end = self.end_date_edit.date().toPyDate() rate = float(self.rate_line.text()) slippage = float(self.slippage_line.text()) size = float(self.size_line.text()) pricetick = float(self.pricetick_line.text()) capital = float(self.capital_line.text()) if self.inverse_combo.currentText() == "正向": inverse = False else: inverse = True parameters = self.settings[class_name] dialog = OptimizationSettingEditor(class_name, parameters) i = dialog.exec() if i != dialog.Accepted: return optimization_setting, use_ga = dialog.get_setting() self.target_display = dialog.target_display self.backtester_engine.start_optimization( class_name, vt_symbol, interval, start, end, rate, slippage, size, pricetick, capital, inverse, optimization_setting, use_ga ) self.result_button.setEnabled(False) def start_downloading(self): """""" vt_symbol = self.symbol_line.text() interval = self.interval_combo.currentText() start_date = self.start_date_edit.date() end_date = self.end_date_edit.date() start = datetime(start_date.year(), start_date.month(), start_date.day()) end = datetime(end_date.year(), end_date.month(), end_date.day(), 23, 59, 59) self.backtester_engine.start_downloading( vt_symbol, interval, start, end ) def show_optimization_result(self): """""" result_values = self.backtester_engine.get_result_values() dialog = OptimizationResultMonitor( result_values, self.target_display ) dialog.exec_() def show_backtesting_trades(self): """""" if not self.trade_dialog.is_updated(): trades = self.backtester_engine.get_all_trades() self.trade_dialog.update_data(trades) self.trade_dialog.exec_() def show_backtesting_orders(self): """""" if not self.order_dialog.is_updated(): orders = self.backtester_engine.get_all_orders() self.order_dialog.update_data(orders) self.order_dialog.exec_() def show_daily_results(self): """""" if not self.daily_dialog.is_updated(): results = self.backtester_engine.get_all_daily_results() self.daily_dialog.update_data(results) self.daily_dialog.exec_() def show_candle_chart(self): """""" if not self.candle_dialog.is_updated(): history = self.backtester_engine.get_history_data() self.candle_dialog.update_history(history) trades = self.backtester_engine.get_all_trades() self.candle_dialog.update_trades(trades) self.candle_dialog.exec_() def edit_strategy_code(self): """""" class_name = self.class_combo.currentText() file_path = self.backtester_engine.get_strategy_class_file(class_name) self.editor.open_editor(file_path) self.editor.show() def reload_strategy_class(self): """""" self.backtester_engine.reload_strategy_class() self.class_combo.clear() self.init_strategy_settings() def show(self): """""" self.showMaximized() class StatisticsMonitor(QtWidgets.QTableWidget): """""" KEY_NAME_MAP = { "start_date": "首个交易日", "end_date": "最后交易日", "total_days": "总交易日", "profit_days": "盈利交易日", "loss_days": "亏损交易日", "capital": "起始资金", "end_balance": "结束资金", "total_return": "总收益率", "annual_return": "年化收益", "max_drawdown": "最大回撤", "max_ddpercent": "百分比最大回撤", "total_net_pnl": "总盈亏", "total_commission": "总手续费", "total_slippage": "总滑点", "total_turnover": "总成交额", "total_trade_count": "总成交笔数", "daily_net_pnl": "日均盈亏", "daily_commission": "日均手续费", "daily_slippage": "日均滑点", "daily_turnover": "日均成交额", "daily_trade_count": "日均成交笔数", "daily_return": "日均收益率", "return_std": "收益标准差", "sharpe_ratio": "夏普比率", "return_drawdown_ratio": "收益回撤比" } def __init__(self): """""" super().__init__() self.cells = {} self.init_ui() def init_ui(self): """""" self.setRowCount(len(self.KEY_NAME_MAP)) self.setVerticalHeaderLabels(list(self.KEY_NAME_MAP.values())) self.setColumnCount(1) self.horizontalHeader().setVisible(False) self.horizontalHeader().setSectionResizeMode( QtWidgets.QHeaderView.Stretch ) self.setEditTriggers(self.NoEditTriggers) for row, key in enumerate(self.KEY_NAME_MAP.keys()): cell = QtWidgets.QTableWidgetItem() self.setItem(row, 0, cell) self.cells[key] = cell def clear_data(self): """""" for cell in self.cells.values(): cell.setText("") def set_data(self, data: dict): """""" data["capital"] = f"{data['capital']:,.2f}" data["end_balance"] = f"{data['end_balance']:,.2f}" data["total_return"] = f"{data['total_return']:,.2f}%" data["annual_return"] = f"{data['annual_return']:,.2f}%" data["max_drawdown"] = f"{data['max_drawdown']:,.2f}" data["max_ddpercent"] = f"{data['max_ddpercent']:,.2f}%" data["total_net_pnl"] = f"{data['total_net_pnl']:,.2f}" data["total_commission"] = f"{data['total_commission']:,.2f}" data["total_slippage"] = f"{data['total_slippage']:,.2f}" data["total_turnover"] = f"{data['total_turnover']:,.2f}" data["daily_net_pnl"] = f"{data['daily_net_pnl']:,.2f}" data["daily_commission"] = f"{data['daily_commission']:,.2f}" data["daily_slippage"] = f"{data['daily_slippage']:,.2f}" data["daily_turnover"] = f"{data['daily_turnover']:,.2f}" data["daily_return"] = f"{data['daily_return']:,.2f}%" data["return_std"] = f"{data['return_std']:,.2f}%" data["sharpe_ratio"] = f"{data['sharpe_ratio']:,.2f}" data["return_drawdown_ratio"] = f"{data['return_drawdown_ratio']:,.2f}" for key, cell in self.cells.items(): value = data.get(key, "") cell.setText(str(value)) class BacktestingSettingEditor(QtWidgets.QDialog): """ For creating new strategy and editing strategy parameters. """ def __init__( self, class_name: str, parameters: dict ): """""" super(BacktestingSettingEditor, self).__init__() self.class_name = class_name self.parameters = parameters self.edits = {} self.init_ui() def init_ui(self): """""" form = QtWidgets.QFormLayout() # Add vt_symbol and name edit if add new strategy self.setWindowTitle(f"策略参数配置:{self.class_name}") button_text = "确定" parameters = self.parameters for name, value in parameters.items(): type_ = type(value) edit = QtWidgets.QLineEdit(str(value)) if type_ is int: validator = QtGui.QIntValidator() edit.setValidator(validator) elif type_ is float: validator = QtGui.QDoubleValidator() edit.setValidator(validator) form.addRow(f"{name} {type_}", edit) self.edits[name] = (edit, type_) button = QtWidgets.QPushButton(button_text) button.clicked.connect(self.accept) form.addRow(button) self.setLayout(form) def get_setting(self): """""" setting = {} for name, tp in self.edits.items(): edit, type_ = tp value_text = edit.text() if type_ == bool: if value_text == "True": value = True else: value = False else: value = type_(value_text) setting[name] = value return setting class BacktesterChart(pg.GraphicsWindow): """""" def __init__(self): """""" super().__init__(title="Backtester Chart") self.dates = {} self.init_ui() def init_ui(self): """""" pg.setConfigOptions(antialias=True) # Create plot widgets self.balance_plot = self.addPlot( title="账户净值", axisItems={"bottom": DateAxis(self.dates, orientation="bottom")} ) self.nextRow() self.drawdown_plot = self.addPlot( title="净值回撤", axisItems={"bottom": DateAxis(self.dates, orientation="bottom")} ) self.nextRow() self.pnl_plot = self.addPlot( title="每日盈亏", axisItems={"bottom": DateAxis(self.dates, orientation="bottom")} ) self.nextRow() self.distribution_plot = self.addPlot(title="盈亏分布") # Add curves and bars on plot widgets self.balance_curve = self.balance_plot.plot( pen=pg.mkPen("#ffc107", width=3) ) dd_color = "#303f9f" self.drawdown_curve = self.drawdown_plot.plot( fillLevel=-0.3, brush=dd_color, pen=dd_color ) profit_color = 'r' loss_color = 'g' self.profit_pnl_bar = pg.BarGraphItem( x=[], height=[], width=0.3, brush=profit_color, pen=profit_color ) self.loss_pnl_bar = pg.BarGraphItem( x=[], height=[], width=0.3, brush=loss_color, pen=loss_color ) self.pnl_plot.addItem(self.profit_pnl_bar) self.pnl_plot.addItem(self.loss_pnl_bar) distribution_color = "#6d4c41" self.distribution_curve = self.distribution_plot.plot( fillLevel=-0.3, brush=distribution_color, pen=distribution_color ) def clear_data(self): """""" self.balance_curve.setData([], []) self.drawdown_curve.setData([], []) self.profit_pnl_bar.setOpts(x=[], height=[]) self.loss_pnl_bar.setOpts(x=[], height=[]) self.distribution_curve.setData([], []) def set_data(self, df): """""" if df is None: return count = len(df) self.dates.clear() for n, date in enumerate(df.index): self.dates[n] = date # Set data for curve of balance and drawdown self.balance_curve.setData(df["balance"]) self.drawdown_curve.setData(df["drawdown"]) # Set data for daily pnl bar profit_pnl_x = [] profit_pnl_height = [] loss_pnl_x = [] loss_pnl_height = [] for count, pnl in enumerate(df["net_pnl"]): if pnl >= 0: profit_pnl_height.append(pnl) profit_pnl_x.append(count) else: loss_pnl_height.append(pnl) loss_pnl_x.append(count) self.profit_pnl_bar.setOpts(x=profit_pnl_x, height=profit_pnl_height) self.loss_pnl_bar.setOpts(x=loss_pnl_x, height=loss_pnl_height) # Set data for pnl distribution hist, x = np.histogram(df["net_pnl"], bins="auto") x = x[:-1] self.distribution_curve.setData(x, hist) class DateAxis(pg.AxisItem): """Axis for showing date data""" def __init__(self, dates: dict, *args, **kwargs): """""" super().__init__(*args, **kwargs) self.dates = dates def tickStrings(self, values, scale, spacing): """""" strings = [] for v in values: dt = self.dates.get(v, "") strings.append(str(dt)) return strings class OptimizationSettingEditor(QtWidgets.QDialog): """ For setting up parameters for optimization. """ DISPLAY_NAME_MAP = { "总收益率": "total_return", "夏普比率": "sharpe_ratio", "收益回撤比": "return_drawdown_ratio", "日均盈亏": "daily_net_pnl" } def __init__( self, class_name: str, parameters: dict ): """""" super().__init__() self.class_name = class_name self.parameters = parameters self.edits = {} self.optimization_setting = None self.use_ga = False self.init_ui() def init_ui(self): """""" QLabel = QtWidgets.QLabel self.target_combo = QtWidgets.QComboBox() self.target_combo.addItems(list(self.DISPLAY_NAME_MAP.keys())) grid = QtWidgets.QGridLayout() grid.addWidget(QLabel("目标"), 0, 0) grid.addWidget(self.target_combo, 0, 1, 1, 3) grid.addWidget(QLabel("参数"), 1, 0) grid.addWidget(QLabel("开始"), 1, 1) grid.addWidget(QLabel("步进"), 1, 2) grid.addWidget(QLabel("结束"), 1, 3) # Add vt_symbol and name edit if add new strategy self.setWindowTitle(f"优化参数配置:{self.class_name}") validator = QtGui.QDoubleValidator() row = 2 for name, value in self.parameters.items(): type_ = type(value) if type_ not in [int, float]: continue start_edit = QtWidgets.QLineEdit(str(value)) step_edit = QtWidgets.QLineEdit(str(1)) end_edit = QtWidgets.QLineEdit(str(value)) for edit in [start_edit, step_edit, end_edit]: edit.setValidator(validator) grid.addWidget(QLabel(name), row, 0) grid.addWidget(start_edit, row, 1) grid.addWidget(step_edit, row, 2) grid.addWidget(end_edit, row, 3) self.edits[name] = { "type": type_, "start": start_edit, "step": step_edit, "end": end_edit } row += 1 parallel_button = QtWidgets.QPushButton("多进程优化") parallel_button.clicked.connect(self.generate_parallel_setting) grid.addWidget(parallel_button, row, 0, 1, 4) row += 1 ga_button = QtWidgets.QPushButton("遗传算法优化") ga_button.clicked.connect(self.generate_ga_setting) grid.addWidget(ga_button, row, 0, 1, 4) self.setLayout(grid) def generate_ga_setting(self): """""" self.use_ga = True self.generate_setting() def generate_parallel_setting(self): """""" self.use_ga = False self.generate_setting() def generate_setting(self): """""" self.optimization_setting = OptimizationSetting() self.target_display = self.target_combo.currentText() target_name = self.DISPLAY_NAME_MAP[self.target_display] self.optimization_setting.set_target(target_name) for name, d in self.edits.items(): type_ = d["type"] start_value = type_(d["start"].text()) step_value = type_(d["step"].text()) end_value = type_(d["end"].text()) if start_value == end_value: self.optimization_setting.add_parameter(name, start_value) else: self.optimization_setting.add_parameter( name, start_value, end_value, step_value ) self.accept() def get_setting(self): """""" return self.optimization_setting, self.use_ga class OptimizationResultMonitor(QtWidgets.QDialog): """ For viewing optimization result. """ def __init__( self, result_values: list, target_display: str ): """""" super().__init__() self.result_values = result_values self.target_display = target_display self.init_ui() def init_ui(self): """""" self.setWindowTitle("参数优化结果") self.resize(1100, 500) table = QtWidgets.QTableWidget() table.setColumnCount(2) table.setRowCount(len(self.result_values)) table.setHorizontalHeaderLabels(["参数", self.target_display]) table.setEditTriggers(table.NoEditTriggers) table.verticalHeader().setVisible(False) table.horizontalHeader().setSectionResizeMode( 0, QtWidgets.QHeaderView.ResizeToContents ) table.horizontalHeader().setSectionResizeMode( 1, QtWidgets.QHeaderView.Stretch ) for n, tp in enumerate(self.result_values): setting, target_value, _ = tp setting_cell = QtWidgets.QTableWidgetItem(str(setting)) target_cell = QtWidgets.QTableWidgetItem(str(target_value)) setting_cell.setTextAlignment(QtCore.Qt.AlignCenter) target_cell.setTextAlignment(QtCore.Qt.AlignCenter) table.setItem(n, 0, setting_cell) table.setItem(n, 1, target_cell) vbox = QtWidgets.QVBoxLayout() vbox.addWidget(table) self.setLayout(vbox) class BacktestingTradeMonitor(BaseMonitor): """ Monitor for backtesting trade data. """ headers = { "tradeid": {"display": "成交号 ", "cell": BaseCell, "update": False}, "orderid": {"display": "委托号", "cell": BaseCell, "update": False}, "symbol": {"display": "代码", "cell": BaseCell, "update": False}, "exchange": {"display": "交易所", "cell": EnumCell, "update": False}, "direction": {"display": "方向", "cell": DirectionCell, "update": False}, "offset": {"display": "开平", "cell": EnumCell, "update": False}, "price": {"display": "价格", "cell": BaseCell, "update": False}, "volume": {"display": "数量", "cell": BaseCell, "update": False}, "datetime": {"display": "时间", "cell": BaseCell, "update": False}, "gateway_name": {"display": "接口", "cell": BaseCell, "update": False}, } class BacktestingOrderMonitor(BaseMonitor): """ Monitor for backtesting order data. """ headers = { "orderid": {"display": "委托号", "cell": BaseCell, "update": False}, "symbol": {"display": "代码", "cell": BaseCell, "update": False}, "exchange": {"display": "交易所", "cell": EnumCell, "update": False}, "type": {"display": "类型", "cell": EnumCell, "update": False}, "direction": {"display": "方向", "cell": DirectionCell, "update": False}, "offset": {"display": "开平", "cell": EnumCell, "update": False}, "price": {"display": "价格", "cell": BaseCell, "update": False}, "volume": {"display": "总数量", "cell": BaseCell, "update": False}, "traded": {"display": "已成交", "cell": BaseCell, "update": False}, "status": {"display": "状态", "cell": EnumCell, "update": False}, "datetime": {"display": "时间", "cell": BaseCell, "update": False}, "gateway_name": {"display": "接口", "cell": BaseCell, "update": False}, } class DailyResultMonitor(BaseMonitor): """ Monitor for backtesting daily result. """ headers = { "date": {"display": "日期", "cell": BaseCell, "update": False}, "trade_count": {"display": "成交笔数", "cell": BaseCell, "update": False}, "start_pos": {"display": "开盘持仓", "cell": BaseCell, "update": False}, "end_pos": {"display": "收盘持仓", "cell": BaseCell, "update": False}, "turnover": {"display": "成交额", "cell": BaseCell, "update": False}, "commission": {"display": "手续费", "cell": BaseCell, "update": False}, "slippage": {"display": "滑点", "cell": BaseCell, "update": False}, "trading_pnl": {"display": "交易盈亏", "cell": BaseCell, "update": False}, "holding_pnl": {"display": "持仓盈亏", "cell": BaseCell, "update": False}, "total_pnl": {"display": "总盈亏", "cell": BaseCell, "update": False}, "net_pnl": {"display": "净盈亏", "cell": BaseCell, "update": False}, } class BacktestingResultDialog(QtWidgets.QDialog): """ """ def __init__( self, main_engine: MainEngine, event_engine: EventEngine, title: str, table_class: QtWidgets.QTableWidget ): """""" super().__init__() self.main_engine = main_engine self.event_engine = event_engine self.title = title self.table_class = table_class self.updated = False self.init_ui() def init_ui(self): """""" self.setWindowTitle(self.title) self.resize(1100, 600) self.table = self.table_class(self.main_engine, self.event_engine) vbox = QtWidgets.QVBoxLayout() vbox.addWidget(self.table) self.setLayout(vbox) def clear_data(self): """""" self.updated = False self.table.setRowCount(0) def update_data(self, data: list): """""" self.updated = True data.reverse() for obj in data: self.table.insert_new_row(obj) def is_updated(self): """""" return self.updated class CandleChartDialog(QtWidgets.QDialog): """ """ def __init__(self): """""" super().__init__() self.dt_ix_map = {} self.updated = False self.init_ui() def init_ui(self): """""" self.setWindowTitle("回测K线图表") self.resize(1400, 800) # Create chart widget self.chart = ChartWidget() self.chart.add_plot("candle", hide_x_axis=True) self.chart.add_plot("volume", maximum_height=200) self.chart.add_item(CandleItem, "candle", "candle") self.chart.add_item(VolumeItem, "volume", "volume") self.chart.add_cursor() # Add scatter item for showing tradings self.trade_scatter = pg.ScatterPlotItem() candle_plot = self.chart.get_plot("candle") candle_plot.addItem(self.trade_scatter) # Set layout vbox = QtWidgets.QVBoxLayout() vbox.addWidget(self.chart) self.setLayout(vbox) def update_history(self, history: list): """""" self.updated = True self.chart.update_history(history) for ix, bar in enumerate(history): self.dt_ix_map[bar.datetime] = ix def update_trades(self, trades: list): """""" trade_data = [] for trade in trades: ix = self.dt_ix_map[trade.datetime] scatter = { "pos": (ix, trade.price), "data": 1, "size": 14, "pen": pg.mkPen((255, 255, 255)) } if trade.direction == Direction.LONG: scatter_symbol = "t1" # Up arrow else: scatter_symbol = "t" # Down arrow if trade.offset == Offset.OPEN: scatter_brush = pg.mkBrush((255, 255, 0)) # Yellow else: scatter_brush = pg.mkBrush((0, 0, 255)) # Blue scatter["symbol"] = scatter_symbol scatter["brush"] = scatter_brush trade_data.append(scatter) self.trade_scatter.setData(trade_data) def clear_data(self): """""" self.updated = False self.chart.clear_all() self.dt_ix_map.clear() self.trade_scatter.clear() def is_updated(self): """""" return self.updated
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# # @lc app=leetcode id=677 lang=python3 # # [677] Map Sum Pairs # https://leetcode.com/problems/map-sum-pairs/ # This problem is about the trie data structure. Each node keeps track of the sum of its children. # A new key overrides the original values. # import unittest from typing import Dict # @lc code=start class Node: def __init__(self, val: int = 0): self.value = val self.children: Dict[str, Node] = {} class MapSum: def __init__(self) -> None: """ Initialize your data structure here. """ self.root_node = Node() self.keys: Dict[str, int] = {} def insert(self, key: str, val: int) -> None: # override if key already exists val_diff = val - self.keys.get(key, 0) self.keys[key] = val # track count of prefix characters node = self.root_node for c in key: if c not in node.children: node.children[c] = Node() node = node.children[c] node.value += val_diff def sum(self, prefix: str) -> int: node = self.root_node for c in prefix: # return 0 if prefix doesn't exist if c not in node.children: return 0 node = node.children[c] return node.value # Your MapSum object will be instantiated and called as such: # obj = MapSum() # obj.insert(key,val) # param_2 = obj.sum(prefix) # @lc code=end class TestSolution(unittest.TestCase): def test_given(self) -> None: x = MapSum() x.insert("apple", 3) self.assertEqual(x.sum("ap"), 3) x.insert("app", 2) self.assertEqual(x.sum("ap"), 5) def test_override(self) -> None: x = MapSum() x.insert("apple", 3) x.insert("app", 2) x.insert("apple", 8) self.assertEqual(x.sum("ap"), 10) if __name__ == "__main__": unittest.main()
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# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union from ... import _utilities, _tables __all__ = [ 'GetSecurityContactResult', 'AwaitableGetSecurityContactResult', 'get_security_contact', ] @pulumi.output_type class GetSecurityContactResult: """ Contact details for security issues """ def __init__(__self__, alert_notifications=None, alerts_to_admins=None, email=None, id=None, name=None, phone=None, type=None): if alert_notifications and not isinstance(alert_notifications, str): raise TypeError("Expected argument 'alert_notifications' to be a str") pulumi.set(__self__, "alert_notifications", alert_notifications) if alerts_to_admins and not isinstance(alerts_to_admins, str): raise TypeError("Expected argument 'alerts_to_admins' to be a str") pulumi.set(__self__, "alerts_to_admins", alerts_to_admins) if email and not isinstance(email, str): raise TypeError("Expected argument 'email' to be a str") pulumi.set(__self__, "email", email) if id and not isinstance(id, str): raise TypeError("Expected argument 'id' to be a str") pulumi.set(__self__, "id", id) if name and not isinstance(name, str): raise TypeError("Expected argument 'name' to be a str") pulumi.set(__self__, "name", name) if phone and not isinstance(phone, str): raise TypeError("Expected argument 'phone' to be a str") pulumi.set(__self__, "phone", phone) if type and not isinstance(type, str): raise TypeError("Expected argument 'type' to be a str") pulumi.set(__self__, "type", type) @property @pulumi.getter(name="alertNotifications") def alert_notifications(self) -> str: """ Whether to send security alerts notifications to the security contact """ return pulumi.get(self, "alert_notifications") @property @pulumi.getter(name="alertsToAdmins") def alerts_to_admins(self) -> str: """ Whether to send security alerts notifications to subscription admins """ return pulumi.get(self, "alerts_to_admins") @property @pulumi.getter def email(self) -> str: """ The email of this security contact """ return pulumi.get(self, "email") @property @pulumi.getter def id(self) -> str: """ Resource Id """ return pulumi.get(self, "id") @property @pulumi.getter def name(self) -> str: """ Resource name """ return pulumi.get(self, "name") @property @pulumi.getter def phone(self) -> Optional[str]: """ The phone number of this security contact """ return pulumi.get(self, "phone") @property @pulumi.getter def type(self) -> str: """ Resource type """ return pulumi.get(self, "type") class AwaitableGetSecurityContactResult(GetSecurityContactResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetSecurityContactResult( alert_notifications=self.alert_notifications, alerts_to_admins=self.alerts_to_admins, email=self.email, id=self.id, name=self.name, phone=self.phone, type=self.type) def get_security_contact(security_contact_name: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetSecurityContactResult: """ Contact details for security issues :param str security_contact_name: Name of the security contact object """ __args__ = dict() __args__['securityContactName'] = security_contact_name if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-nextgen:security/v20170801preview:getSecurityContact', __args__, opts=opts, typ=GetSecurityContactResult).value return AwaitableGetSecurityContactResult( alert_notifications=__ret__.alert_notifications, alerts_to_admins=__ret__.alerts_to_admins, email=__ret__.email, id=__ret__.id, name=__ret__.name, phone=__ret__.phone, type=__ret__.type)
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__author__ = 'Niklas Rosenstein <rosensteinniklas@gmail.com>' __version__ = '1.7.6' import copy import glob import os import pkgutil import sys import traceback import typing as t import zipfile if t.TYPE_CHECKING: from sys import _MetaPathFinder def is_local(filename: str, pathlist: t.List[str]) -> bool: ''' Returns True if *filename* is a subpath of any of the paths in *pathlist*. ''' filename = os.path.abspath(filename) for path_name in pathlist: path_name = os.path.abspath(path_name) if is_subpath(filename, path_name): return True return False def is_subpath(path: str, parent: str) -> bool: ''' Returns True if *path* points to the same or a subpath of *parent*. ''' try: relpath = os.path.relpath(path, parent) except ValueError: return False # happens on Windows if drive letters don't match return relpath == os.curdir or not relpath.startswith(os.pardir) def eval_pth( filename: str, sitedir: str, dest: t.Optional[t.List[str]] = None, imports: t.Optional[t.List[t.Tuple[str, int, str]]] = None, ) -> t.List[str]: ''' Evaluates a `.pth` file (including support for `import` statements), and appends the result to the list *dest*. If *dest* is #None, it will fall back to `sys.path`. If *imports* is specified, it must be a list. `import` statements will not executed but instead appended to that list in tuples of (*filename*, *line*, *stmt*). ''' if dest is None: dest = sys.path if not os.path.isfile(filename): return [] with open(filename, 'r') as fp: for index, line in enumerate(fp): if line.startswith('import'): if imports is None: exec_pth_import(filename, index+1, line) else: imports.append((filename, index+1, line)) else: index = line.find('#') if index > 0: line = line[:index] line = line.strip() if not os.path.isabs(line): line = os.path.join(os.path.dirname(filename), line) line = os.path.normpath(line) if line and line not in dest: dest.insert(0, line) return dest def exec_pth_import(filename: str, lineno: int, line: str) -> None: line = '\n' * (lineno - 1) + line.strip() try: exec(compile(line, filename, 'exec')) except BaseException: traceback.print_exc() def extend_path(pth: t.List[str], name: str) -> t.List[str]: ''' Better implementation of #pkgutil.extend_path() which adds support for zipped Python eggs. The original #pkgutil.extend_path() gets mocked by this function inside the #localimport context. ''' def zip_isfile(z, name): name.rstrip('/') return name in z.namelist() pname = os.path.join(*name.split('.')) zname = '/'.join(name.split('.')) init_py = '__init__' + os.extsep + 'py' init_pyc = '__init__' + os.extsep + 'pyc' init_pyo = '__init__' + os.extsep + 'pyo' mod_path = list(pth) for path in sys.path: if zipfile.is_zipfile(path): try: egg = zipfile.ZipFile(path, 'r') addpath = ( zip_isfile(egg, zname + '/__init__.py') or zip_isfile(egg, zname + '/__init__.pyc') or zip_isfile(egg, zname + '/__init__.pyo')) fpath = os.path.join(path, path, zname) if addpath and fpath not in mod_path: mod_path.append(fpath) except (zipfile.BadZipfile, zipfile.LargeZipFile): pass # xxx: Show a warning at least? else: path = os.path.join(path, pname) if os.path.isdir(path) and path not in mod_path: addpath = ( os.path.isfile(os.path.join(path, init_py)) or os.path.isfile(os.path.join(path, init_pyc)) or os.path.isfile(os.path.join(path, init_pyo))) if addpath and path not in mod_path: mod_path.append(path) return [os.path.normpath(x) for x in mod_path] class localimport: def __init__( self, path: t.Union[t.List[str], str], parent_dir: t.Optional[str] = None, do_eggs: bool = True, do_pth: bool = True, do_autodisable: bool = True, ) -> None: if not parent_dir: frame = sys._getframe(1).f_globals if '__file__' in frame: parent_dir = os.path.dirname(os.path.abspath(frame['__file__'])) # Convert relative paths to absolute paths with parent_dir and # evaluate .egg files in the specified directories. self.path = [] if isinstance(path, str): path = [path] for path_name in path: if not os.path.isabs(path_name): if not parent_dir: raise ValueError('relative path but no parent_dir') path_name = os.path.join(parent_dir, path_name) path_name = os.path.normpath(path_name) self.path.append(path_name) if do_eggs: self.path.extend(glob.glob(os.path.join(path_name, '*.egg'))) self.meta_path: t.List[_MetaPathFinder] = [] self.modules: t.Dict[str, t.Any] = {} self.do_pth = do_pth self.in_context = False self.do_autodisable = do_autodisable self.pth_imports: t.List[t.Tuple[str, int, str]] = [] if self.do_pth: seen = set() for path_name in self.path: for fn in glob.glob(os.path.join(path_name, '*.pth')): if fn in seen: continue seen.add(fn) eval_pth(fn, path_name, dest=self.path, imports=self.pth_imports) def __enter__(self) -> 'localimport': # pkg_resources comes with setuptools. try: import pkg_resources nsdict = copy.deepcopy(pkg_resources._namespace_packages) # type: ignore declare_namespace = pkg_resources.declare_namespace pkg_resources.declare_namespace = self._declare_namespace # type: ignore except ImportError: nsdict = None declare_namespace = None # Save the global importer state. self.state = { 'nsdict': nsdict, 'declare_namespace': declare_namespace, 'nspaths': {}, 'path': sys.path[:], 'meta_path': sys.meta_path[:], 'disables': {}, 'pkgutil.extend_path': pkgutil.extend_path, } # Update the systems meta path and apply function mocks. sys.path[:] = self.path sys.meta_path[:] = self.meta_path + sys.meta_path pkgutil.extend_path = extend_path # type: ignore # If this function is called not the first time, we need to # restore the modules that have been imported with it and # temporarily disable the ones that would be shadowed. for key, mod in list(self.modules.items()): try: self.state['disables'][key] = sys.modules.pop(key) except KeyError: pass sys.modules[key] = mod # Evaluate imports from the .pth files, if any. for fn, lineno, stmt in self.pth_imports: exec_pth_import(fn, lineno, stmt) # Add the original path to sys.path. sys.path += self.state['path'] # Update the __path__ of all namespace modules. for key, mod in list(sys.modules.items()): if mod is None: # Relative imports could have lead to None-entries in # sys.modules. Get rid of them so they can be re-evaluated. prefix = key.rpartition('.')[0] if hasattr(sys.modules.get(prefix), '__path__'): del sys.modules[key] elif hasattr(mod, '__path__'): self.state['nspaths'][key] = copy.copy(mod.__path__) mod.__path__ = pkgutil.extend_path(mod.__path__, mod.__name__) self.in_context = True if self.do_autodisable: self.autodisable() return self def __exit__(self, *__) -> None: if not self.in_context: raise RuntimeError('context not entered') # Figure the difference of the original sys.path and the # current path. The list of paths will be used to determine # what modules are local and what not. local_paths = [] for path in sys.path: if path not in self.state['path']: local_paths.append(path) for path in self.path: if path not in local_paths: local_paths.append(path) # Move all meta path objects to self.meta_path that have not # been there before and have not been in the list before. for meta in sys.meta_path: if meta is not self and meta not in self.state['meta_path']: if meta not in self.meta_path: self.meta_path.append(meta) # Move all modules that shadow modules of the original system # state or modules that are from any of the localimport context # paths away. modules = sys.modules.copy() for key, mod in modules.items(): force_pop = False filename = getattr(mod, '__file__', None) if not filename and key not in sys.builtin_module_names: parent = key.rsplit('.', 1)[0] if parent in modules: filename = getattr(modules[parent], '__file__', None) else: force_pop = True if force_pop or (filename and is_local(filename, local_paths)): self.modules[key] = sys.modules.pop(key) # Restore the disabled modules. sys.modules.update(self.state['disables']) for key, mod in self.state['disables'].items(): try: parent_name = key.split('.')[-2] except IndexError: parent_name = None if parent_name and parent_name in sys.modules: parent_module = sys.modules[parent_name] setattr(parent_module, key.split('.')[-1], mod) # Restore the original __path__ value of namespace packages. for key, path_list in self.state['nspaths'].items(): try: sys.modules[key].__path__ = path_list except KeyError: pass # Restore the original state of the global importer. sys.path[:] = self.state['path'] sys.meta_path[:] = self.state['meta_path'] pkgutil.extend_path = self.state['pkgutil.extend_path'] try: import pkg_resources pkg_resources.declare_namespace = self.state['declare_namespace'] pkg_resources._namespace_packages.clear() # type: ignore pkg_resources._namespace_packages.update(self.state['nsdict']) # type: ignore except ImportError: pass self.in_context = False del self.state def _declare_namespace(self, package_name: str) -> None: ''' Mock for #pkg_resources.declare_namespace() which calls #pkgutil.extend_path() afterwards as the original implementation doesn't seem to properly find all available namespace paths. ''' self.state['declare_namespace'](package_name) mod = sys.modules[package_name] mod.__path__ = pkgutil.extend_path(mod.__path__, package_name) # type: ignore def discover(self) -> t.Iterable[pkgutil.ModuleInfo]: return pkgutil.iter_modules(self.path) def disable(self, module: t.Union[t.List[str], str]) -> None: if not isinstance(module, str): for module_name in module: self.disable(module_name) return sub_prefix = module + '.' modules = {} for key, mod in sys.modules.items(): if key == module or key.startswith(sub_prefix): try: parent_name = '.'.join(key.split('.')[:-1]) except IndexError: parent_name = None # Delete the child module reference from the parent module. modules[key] = mod if parent_name and parent_name in sys.modules: parent = sys.modules[parent_name] try: delattr(parent, key.split('.')[-1]) except AttributeError: pass # Pop all the modules we found from sys.modules for key, mod in modules.items(): del sys.modules[key] self.state['disables'][key] = mod def autodisable(self) -> None: for loader, name, ispkg in self.discover(): self.disable(name)
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import numpy as np import h5py import pandas as pd from svhn_io import load_svhn from keras_uncertainty.utils import classifier_calibration_curve, classifier_calibration_error EPSILON = 1e-10 def load_hdf5_data(filename): inp = h5py.File(filename, "r") preds = inp["preds"][...] inp.close() return preds NUM_ENSEMBLES = 15 NUM_BINS=7 #IOD_FILE_PATTERN = "cnn_svhn-num_ens-{}-preds.hdf5" #OUTPUT_PATTERN = "svhn-calibration-sub-deepensembles_1_num-ens-{}_cnn_svhn.csv" IOD_FILE_PATTERN = "deepensembles-cnn_svhn-num_ens-{}-preds.hdf5" OUTPUT_PATTERN = "svhn-calibration-deepensembles-num-ens-{}_cnn_svhn.csv" if __name__ == "__main__": for num_ens in range(1, NUM_ENSEMBLES + 1): (_, __), (___, y_true) = load_svhn() y_true = y_true.flatten() y_probs = load_hdf5_data(IOD_FILE_PATTERN.format(num_ens)) y_confs = np.max(y_probs, axis=1) y_pred = np.argmax(y_probs, axis=1) curve_conf, curve_acc = classifier_calibration_curve(y_pred, y_true, y_confs, num_bins=NUM_BINS) error = classifier_calibration_error(y_pred, y_true, y_confs, num_bins=NUM_BINS) print("Processing calibration curve for {} ensembles. Error: {}".format(num_ens, error)) output_df = pd.DataFrame(data={"conf": curve_conf, "acc": curve_acc}) output_df.to_csv(OUTPUT_PATTERN.format(num_ens), sep=';', index=False)
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from unittest import TestCase from rockaway.models import Track class TestTrackBasics(TestCase): def test_track_create_no_args(self): track = Track() self.assertFalse(track.hasDbEntry()) self.assertFalse(track.hasFile()) def test_track_create(self): args = {"Title": "Rockaway Beach", "Artist": "The Ramones", # FIXME--This and album will not just be strings "Album": "Rocket to Russia", "Year": 1977, "Genre": "Punk Rock", "Time": 126000} track = Track(**args) self.assertEqual(track.Title, args["Title"]) self.assertEqual(track.Year, 1977) # Alternate ways of looking up attributes self.assertEqual(track.genre, track.Genre) self.assertEqual(track.Time, track["Time"])
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""" Implementation of functions in the Numpy package. """ import math import sys import itertools from collections import namedtuple from llvmlite.llvmpy import core as lc import numpy as np import operator from . import builtins, callconv, ufunc_db, arrayobj from .imputils import Registry, impl_ret_new_ref, force_error_model from .. import typing, types, cgutils, numpy_support, utils from ..numpy_support import ufunc_find_matching_loop, select_array_wrapper, from_dtype from ..typing import npydecl from ..extending import overload, intrinsic from .. import errors registry = Registry() lower = registry.lower ######################################################################## # In the way we generate code, ufuncs work with scalar as well as # with array arguments. The following helper classes help dealing # with scalar and array arguments in a regular way. # # In short, the classes provide a uniform interface. The interface # handles the indexing of as many dimensions as the array may have. # For scalars, all indexing is ignored and when the value is read, # the scalar is returned. For arrays code for actual indexing is # generated and reading performs the appropriate indirection. class _ScalarIndexingHelper(object): def update_indices(self, loop_indices, name): pass def as_values(self): pass class _ScalarHelper(object): """Helper class to handle scalar arguments (and result). Note that store_data is only used when generating code for a scalar ufunc and to write the output value. For loading, the value is directly used without having any kind of indexing nor memory backing it up. This is the use for input arguments. For storing, a variable is created in the stack where the value will be written. Note that it is not supported (as it is unneeded for our current use-cases) reading back a stored value. This class will always "load" the original value it got at its creation. """ def __init__(self, ctxt, bld, val, ty): self.context = ctxt self.builder = bld self.val = val self.base_type = ty intpty = ctxt.get_value_type(types.intp) self.shape = [lc.Constant.int(intpty, 1)] lty = ctxt.get_data_type(ty) if ty != types.boolean else lc.Type.int(1) self._ptr = cgutils.alloca_once(bld, lty) def create_iter_indices(self): return _ScalarIndexingHelper() def load_data(self, indices): return self.val def store_data(self, indices, val): self.builder.store(val, self._ptr) @property def return_val(self): return self.builder.load(self._ptr) class _ArrayIndexingHelper(namedtuple('_ArrayIndexingHelper', ('array', 'indices'))): def update_indices(self, loop_indices, name): bld = self.array.builder intpty = self.array.context.get_value_type(types.intp) ONE = lc.Constant.int(lc.Type.int(intpty.width), 1) # we are only interested in as many inner dimensions as dimensions # the indexed array has (the outer dimensions are broadcast, so # ignoring the outer indices produces the desired result. indices = loop_indices[len(loop_indices) - len(self.indices):] for src, dst, dim in zip(indices, self.indices, self.array.shape): cond = bld.icmp(lc.ICMP_UGT, dim, ONE) with bld.if_then(cond): bld.store(src, dst) def as_values(self): """ The indexing helper is built using alloca for each value, so it actually contains pointers to the actual indices to load. Note that update_indices assumes the same. This method returns the indices as values """ bld = self.array.builder return [bld.load(index) for index in self.indices] class _ArrayHelper(namedtuple('_ArrayHelper', ('context', 'builder', 'shape', 'strides', 'data', 'layout', 'base_type', 'ndim', 'return_val'))): """Helper class to handle array arguments/result. It provides methods to generate code loading/storing specific items as well as support code for handling indices. """ def create_iter_indices(self): intpty = self.context.get_value_type(types.intp) ZERO = lc.Constant.int(lc.Type.int(intpty.width), 0) indices = [] for i in range(self.ndim): x = cgutils.alloca_once(self.builder, lc.Type.int(intpty.width)) self.builder.store(ZERO, x) indices.append(x) return _ArrayIndexingHelper(self, indices) def _load_effective_address(self, indices): return cgutils.get_item_pointer2(self.context, self.builder, data=self.data, shape=self.shape, strides=self.strides, layout=self.layout, inds=indices) def load_data(self, indices): model = self.context.data_model_manager[self.base_type] ptr = self._load_effective_address(indices) return model.load_from_data_pointer(self.builder, ptr) def store_data(self, indices, value): ctx = self.context bld = self.builder store_value = ctx.get_value_as_data(bld, self.base_type, value) assert ctx.get_data_type(self.base_type) == store_value.type bld.store(store_value, self._load_effective_address(indices)) def _prepare_argument(ctxt, bld, inp, tyinp, where='input operand'): """returns an instance of the appropriate Helper (either _ScalarHelper or _ArrayHelper) class to handle the argument. using the polymorphic interface of the Helper classes, scalar and array cases can be handled with the same code""" # first un-Optional Optionals if isinstance(tyinp, types.Optional): oty = tyinp tyinp = tyinp.type inp = ctxt.cast(bld, inp, oty, tyinp) # then prepare the arg for a concrete instance if isinstance(tyinp, types.ArrayCompatible): ary = ctxt.make_array(tyinp)(ctxt, bld, inp) shape = cgutils.unpack_tuple(bld, ary.shape, tyinp.ndim) strides = cgutils.unpack_tuple(bld, ary.strides, tyinp.ndim) return _ArrayHelper(ctxt, bld, shape, strides, ary.data, tyinp.layout, tyinp.dtype, tyinp.ndim, inp) elif types.unliteral(tyinp) in types.number_domain | set([types.boolean]): return _ScalarHelper(ctxt, bld, inp, tyinp) else: raise NotImplementedError('unsupported type for {0}: {1}'.format(where, str(tyinp))) _broadcast_onto_sig = types.intp(types.intp, types.CPointer(types.intp), types.intp, types.CPointer(types.intp)) def _broadcast_onto(src_ndim, src_shape, dest_ndim, dest_shape): '''Low-level utility function used in calculating a shape for an implicit output array. This function assumes that the destination shape is an LLVM pointer to a C-style array that was already initialized to a size of one along all axes. Returns an integer value: >= 1 : Succeeded. Return value should equal the number of dimensions in the destination shape. 0 : Failed to broadcast because source shape is larger than the destination shape (this case should be weeded out at type checking). < 0 : Failed to broadcast onto destination axis, at axis number == -(return_value + 1). ''' if src_ndim > dest_ndim: # This check should have been done during type checking, but # let's be defensive anyway... return 0 else: src_index = 0 dest_index = dest_ndim - src_ndim while src_index < src_ndim: src_dim_size = src_shape[src_index] dest_dim_size = dest_shape[dest_index] # Check to see if we've already mutated the destination # shape along this axis. if dest_dim_size != 1: # If we have mutated the destination shape already, # then the source axis size must either be one, # or the destination axis size. if src_dim_size != dest_dim_size and src_dim_size != 1: return -(dest_index + 1) elif src_dim_size != 1: # If the destination size is still its initial dest_shape[dest_index] = src_dim_size src_index += 1 dest_index += 1 return dest_index def _build_array(context, builder, array_ty, input_types, inputs): """Utility function to handle allocation of an implicit output array given the target context, builder, output array type, and a list of _ArrayHelper instances. """ intp_ty = context.get_value_type(types.intp) def make_intp_const(val): return context.get_constant(types.intp, val) ZERO = make_intp_const(0) ONE = make_intp_const(1) src_shape = cgutils.alloca_once(builder, intp_ty, array_ty.ndim, "src_shape") dest_ndim = make_intp_const(array_ty.ndim) dest_shape = cgutils.alloca_once(builder, intp_ty, array_ty.ndim, "dest_shape") dest_shape_addrs = tuple(cgutils.gep_inbounds(builder, dest_shape, index) for index in range(array_ty.ndim)) # Initialize the destination shape with all ones. for dest_shape_addr in dest_shape_addrs: builder.store(ONE, dest_shape_addr) # For each argument, try to broadcast onto the destination shape, # mutating along any axis where the argument shape is not one and # the destination shape is one. for arg_number, arg in enumerate(inputs): if not hasattr(arg, "ndim"): # Skip scalar arguments continue arg_ndim = make_intp_const(arg.ndim) for index in range(arg.ndim): builder.store(arg.shape[index], cgutils.gep_inbounds(builder, src_shape, index)) arg_result = context.compile_internal( builder, _broadcast_onto, _broadcast_onto_sig, [arg_ndim, src_shape, dest_ndim, dest_shape]) with cgutils.if_unlikely(builder, builder.icmp(lc.ICMP_SLT, arg_result, ONE)): msg = "unable to broadcast argument %d to output array" % ( arg_number,) loc = errors.loc_info.get('loc', None) if loc is not None: msg += '\nFile "%s", line %d, ' % (loc.filename, loc.line) context.call_conv.return_user_exc(builder, ValueError, (msg,)) real_array_ty = array_ty.as_array dest_shape_tup = tuple(builder.load(dest_shape_addr) for dest_shape_addr in dest_shape_addrs) array_val = arrayobj._empty_nd_impl(context, builder, real_array_ty, dest_shape_tup) # Get the best argument to call __array_wrap__ on array_wrapper_index = select_array_wrapper(input_types) array_wrapper_ty = input_types[array_wrapper_index] try: # __array_wrap__(source wrapped array, out array) -> out wrapped array array_wrap = context.get_function('__array_wrap__', array_ty(array_wrapper_ty, real_array_ty)) except NotImplementedError: # If it's the same priority as a regular array, assume we # should use the allocated array unchanged. if array_wrapper_ty.array_priority != types.Array.array_priority: raise out_val = array_val._getvalue() else: wrap_args = (inputs[array_wrapper_index].return_val, array_val._getvalue()) out_val = array_wrap(builder, wrap_args) ndim = array_ty.ndim shape = cgutils.unpack_tuple(builder, array_val.shape, ndim) strides = cgutils.unpack_tuple(builder, array_val.strides, ndim) return _ArrayHelper(context, builder, shape, strides, array_val.data, array_ty.layout, array_ty.dtype, ndim, out_val) def numpy_ufunc_kernel(context, builder, sig, args, kernel_class, explicit_output=True): # This is the code generator that builds all the looping needed # to execute a numpy functions over several dimensions (including # scalar cases). # # context - the code generation context # builder - the code emitter # sig - signature of the ufunc # args - the args to the ufunc # kernel_class - a code generating subclass of _Kernel that provides # explicit_output - if the output was explicit in the call # (ie: np.add(x,y,r)) arguments = [_prepare_argument(context, builder, arg, tyarg) for arg, tyarg in zip(args, sig.args)] if not explicit_output: ret_ty = sig.return_type if isinstance(ret_ty, types.ArrayCompatible): output = _build_array(context, builder, ret_ty, sig.args, arguments) else: output = _prepare_argument( context, builder, lc.Constant.null(context.get_value_type(ret_ty)), ret_ty) arguments.append(output) elif context.enable_nrt: # Incref the output context.nrt.incref(builder, sig.return_type, args[-1]) inputs = arguments[0:-1] output = arguments[-1] outer_sig = [a.base_type for a in arguments] #signature expects return type first, while we have it last: outer_sig = outer_sig[-1:] + outer_sig[:-1] outer_sig = typing.signature(*outer_sig) kernel = kernel_class(context, builder, outer_sig) intpty = context.get_value_type(types.intp) indices = [inp.create_iter_indices() for inp in inputs] loopshape = output.shape with cgutils.loop_nest(builder, loopshape, intp=intpty) as loop_indices: vals_in = [] for i, (index, arg) in enumerate(zip(indices, inputs)): index.update_indices(loop_indices, i) vals_in.append(arg.load_data(index.as_values())) val_out = kernel.generate(*vals_in) output.store_data(loop_indices, val_out) out = arguments[-1].return_val return impl_ret_new_ref(context, builder, sig.return_type, out) # Kernels are the code to be executed inside the multidimensional loop. class _Kernel(object): def __init__(self, context, builder, outer_sig): self.context = context self.builder = builder self.outer_sig = outer_sig def cast(self, val, fromty, toty): """Numpy uses cast semantics that are different from standard Python (for example, it does allow casting from complex to float). This method acts as a patch to context.cast so that it allows complex to real/int casts. """ if (isinstance(fromty, types.Complex) and not isinstance(toty, types.Complex)): # attempt conversion of the real part to the specified type. # note that NumPy issues a warning in this kind of conversions newty = fromty.underlying_float attr = self.context.get_getattr(fromty, 'real') val = attr(self.context, self.builder, fromty, val, 'real') fromty = newty # let the regular cast do the rest... return self.context.cast(self.builder, val, fromty, toty) def _ufunc_db_function(ufunc): """Use the ufunc loop type information to select the code generation function from the table provided by the dict_of_kernels. The dict of kernels maps the loop identifier to a function with the following signature: (context, builder, signature, args). The loop type information has the form 'AB->C'. The letters to the left of '->' are the input types (specified as NumPy letter types). The letters to the right of '->' are the output types. There must be 'ufunc.nin' letters to the left of '->', and 'ufunc.nout' letters to the right. For example, a binary float loop resulting in a float, will have the following signature: 'ff->f'. A given ufunc implements many loops. The list of loops implemented for a given ufunc can be accessed using the 'types' attribute in the ufunc object. The NumPy machinery selects the first loop that fits a given calling signature (in our case, what we call the outer_sig). This logic is mimicked by 'ufunc_find_matching_loop'. """ class _KernelImpl(_Kernel): def __init__(self, context, builder, outer_sig): super(_KernelImpl, self).__init__(context, builder, outer_sig) loop = ufunc_find_matching_loop( ufunc, outer_sig.args + (outer_sig.return_type,)) self.fn = ufunc_db.get_ufunc_info(ufunc).get(loop.ufunc_sig) self.inner_sig = typing.signature( *(loop.outputs + loop.inputs)) if self.fn is None: msg = "Don't know how to lower ufunc '{0}' for loop '{1}'" raise NotImplementedError(msg.format(ufunc.__name__, loop)) def generate(self, *args): isig = self.inner_sig osig = self.outer_sig cast_args = [self.cast(val, inty, outty) for val, inty, outty in zip(args, osig.args, isig.args)] with force_error_model(self.context, 'numpy'): res = self.fn(self.context, self.builder, isig, cast_args) dmm = self.context.data_model_manager res = dmm[isig.return_type].from_return(self.builder, res) return self.cast(res, isig.return_type, osig.return_type) return _KernelImpl ################################################################################ # Helper functions that register the ufuncs _kernels = {} # Temporary map from ufunc's to their kernel implementation class def register_unary_ufunc_kernel(ufunc, kernel): def unary_ufunc(context, builder, sig, args): return numpy_ufunc_kernel(context, builder, sig, args, kernel) def unary_ufunc_no_explicit_output(context, builder, sig, args): return numpy_ufunc_kernel(context, builder, sig, args, kernel, explicit_output=False) _any = types.Any # (array or scalar, out=array) lower(ufunc, _any, types.Array)(unary_ufunc) # (array or scalar) lower(ufunc, _any)(unary_ufunc_no_explicit_output) _kernels[ufunc] = kernel def register_binary_ufunc_kernel(ufunc, kernel): def binary_ufunc(context, builder, sig, args): return numpy_ufunc_kernel(context, builder, sig, args, kernel) def binary_ufunc_no_explicit_output(context, builder, sig, args): return numpy_ufunc_kernel(context, builder, sig, args, kernel, explicit_output=False) _any = types.Any # (array or scalar, array o scalar, out=array) lower(ufunc, _any, _any, types.Array)(binary_ufunc) # (scalar, scalar) lower(ufunc, _any, _any)(binary_ufunc_no_explicit_output) _kernels[ufunc] = kernel def register_unary_operator_kernel(operator, kernel, inplace=False): assert not inplace # are there any inplace unary operators? def lower_unary_operator(context, builder, sig, args): return numpy_ufunc_kernel(context, builder, sig, args, kernel, explicit_output=False) _arr_kind = types.Array lower(operator, _arr_kind)(lower_unary_operator) def register_binary_operator_kernel(op, kernel, inplace=False): def lower_binary_operator(context, builder, sig, args): return numpy_ufunc_kernel(context, builder, sig, args, kernel, explicit_output=False) def lower_inplace_operator(context, builder, sig, args): # The visible signature is (A, B) -> A # The implementation's signature (with explicit output) # is (A, B, A) -> A args = tuple(args) + (args[0],) sig = typing.signature(sig.return_type, *sig.args + (sig.args[0],)) return numpy_ufunc_kernel(context, builder, sig, args, kernel, explicit_output=True) _any = types.Any _arr_kind = types.Array formal_sigs = [(_arr_kind, _arr_kind), (_any, _arr_kind), (_arr_kind, _any)] for sig in formal_sigs: if not inplace: lower(op, *sig)(lower_binary_operator) else: lower(op, *sig)(lower_inplace_operator) ################################################################################ # Use the contents of ufunc_db to initialize the supported ufuncs for ufunc in ufunc_db.get_ufuncs(): if ufunc.nin == 1: register_unary_ufunc_kernel(ufunc, _ufunc_db_function(ufunc)) elif ufunc.nin == 2: register_binary_ufunc_kernel(ufunc, _ufunc_db_function(ufunc)) else: raise RuntimeError("Don't know how to register ufuncs from ufunc_db with arity > 2") @lower(operator.pos, types.Array) def array_positive_impl(context, builder, sig, args): '''Lowering function for +(array) expressions. Defined here (numba.targets.npyimpl) since the remaining array-operator lowering functions are also registered in this module. ''' class _UnaryPositiveKernel(_Kernel): def generate(self, *args): [val] = args return val return numpy_ufunc_kernel(context, builder, sig, args, _UnaryPositiveKernel, explicit_output=False) for _op_map in (npydecl.NumpyRulesUnaryArrayOperator._op_map, npydecl.NumpyRulesArrayOperator._op_map, ): for operator, ufunc_name in _op_map.items(): ufunc = getattr(np, ufunc_name) kernel = _kernels[ufunc] if ufunc.nin == 1: register_unary_operator_kernel(operator, kernel) elif ufunc.nin == 2: register_binary_operator_kernel(operator, kernel) else: raise RuntimeError("There shouldn't be any non-unary or binary operators") for _op_map in (npydecl.NumpyRulesInplaceArrayOperator._op_map, ): for operator, ufunc_name in _op_map.items(): ufunc = getattr(np, ufunc_name) kernel = _kernels[ufunc] if ufunc.nin == 1: register_unary_operator_kernel(operator, kernel, inplace=True) elif ufunc.nin == 2: register_binary_operator_kernel(operator, kernel, inplace=True) else: raise RuntimeError("There shouldn't be any non-unary or binary operators") del _kernels @intrinsic def _make_dtype_object(typingctx, desc): """Given a string or NumberClass description *desc*, returns the dtype object. """ def from_nb_type(nb_type): return_type = types.DType(nb_type) sig = return_type(desc) def codegen(context, builder, signature, args): # All dtype objects are dummy values in LLVM. # They only exist in the type level. return context.get_dummy_value() return sig, codegen if isinstance(desc, types.Literal): # Convert the str description into np.dtype then to numba type. nb_type = from_dtype(np.dtype(desc.literal_value)) return from_nb_type(nb_type) elif isinstance(desc, types.functions.NumberClass): thestr = str(desc.dtype) # Convert the str description into np.dtype then to numba type. nb_type = from_dtype(np.dtype(thestr)) return from_nb_type(nb_type) @overload(np.dtype) def numpy_dtype(desc): """Provide an implementation so that numpy.dtype function can be lowered. """ if isinstance(desc, (types.Literal, types.functions.NumberClass)): def imp(desc): return _make_dtype_object(desc) return imp else: raise TypeError('unknown dtype descriptor: {}'.format(desc))
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#!/usr/bin/env python # -*- coding: utf-8 -*- from setuptools import setup, find_packages import os import re def get_version(package): """ Return package version as listed in `__version__` in `init.py`. """ init_py = open(os.path.join(package, '__init__.py')).read() return re.match("__version__ = ['\"]([^'\"]+)['\"]", init_py).group(1) version = get_version('oauth_api') setup( name="django-oauth-api", version=version, description="OAuth API for Django using Django Rest Framework", classifiers=[ "Development Status :: 4 - Beta", "Environment :: Web Environment", "Framework :: Django", "License :: OSI Approved :: BSD License", "Operating System :: OS Independent", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3.6", "Topic :: Software Development :: Libraries :: Python Modules", ], keywords='django djangorestframework oauth oauth2 oauthlib', author='Tomi Pajunen', author_email='tomi@madlab.fi', url='https://github.com/eofs/django-oauth-api', license='BSD', packages=find_packages(), include_package_data=True, test_suite='runtests', install_requires=[ 'django>=1.11', 'oauthlib==2.0.7', ], zip_safe=False, )
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from django.contrib import admin from events.models import Place, Event, Attendance # Register your models here. class EventAdmin(admin.ModelAdmin): filter_horizontal = ('expected_members', ) class AttendanceAdmin(admin.ModelAdmin): list_display = ('event__name', 'member', 'attendance', 'proxy_to', 'accepted',) list_filter = ('event__name',) def event__name(self, obj): return str(obj.event) admin.site.register(Place) admin.site.register(Attendance, AttendanceAdmin) admin.site.register(Event, EventAdmin)
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# -*- coding: utf-8 -*- # Created at 03/09/2020 __author__ = 'raniys' import math import pytest from factorial_example import factorial_function @pytest.mark.sample def test_factorial_functionality(): print("Inside test_factorial_functionality") assert factorial_function(0) == 1 assert factorial_function(4) == 24 @pytest.mark.sample def test_standard_library(): print("Inside test_standard_library") for i in range(5): # verify whether factorial is calculated correctly # by checking against result against standard # library - math.factorial() assert math.factorial(i) == factorial_function(i) @pytest.mark.sample def test_negative_number(): print("Inside test_negative_number") # This test case would pass if Assertion Error # is raised. In this case, the input number is negative # hence, the test case passes with pytest.raises(AssertionError): factorial_function(-10)
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import requests import json # Get Current Patch def getCurrentVersion(): versionResponse = requests.get("https://ddragon.leagueoflegends.com/api/versions.json") version_patch_RawData = versionResponse.json() currentVersion = version_patch_RawData[0] print(currentVersion) return currentVersion #champions, items, summoner_spells, spells def GetDDragonData_Champions(): version = getCurrentVersion() #Champions Data response = requests.get("http://ddragon.leagueoflegends.com/cdn/"+version+"/data/en_US/champion.json") allChampionRawData = json.loads(response.text) ChampionIdToName = {} for key,champion in allChampionRawData['data'].items(): ChampionIdToName[int(champion['key'])] = champion['name'] print(ChampionIdToName) return ChampionIdToName def GetDDragonData_Items(): version = getCurrentVersion() response = requests.get("http://ddragon.leagueoflegends.com/cdn/"+version+"/data/en_US/item.json") allItemsRawData = json.loads(response.text) QuickPrinter(allItemsRawData) #Items Data ItemIdToName = {} for key,item in allItemsRawData['data'].items(): ItemIdToName[int(key)] = item['name'] print(ItemToToName) return ItemIdToName def QuickPrinter(String_to_Print): print(json.dumps(String_to_Print, indent=4, sort_keys=True)) #main() version = getCurrentVersion() GetDDragonData_Champions() GetDDragonData_Items()
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import numpy as np import nibabel as nib import os import sys sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/../../') from my_functions.matrix_stuff import * def manual_rigid_body(fname = 'example_brain.nii.gz', outmat = 'transformation.mat', outimg = 'example_brain_transformed.nii.gz', theta = np.radians([0,0,0]), translation_vec = [0,0,0], type = 'rotation', flip_coordinates = [True, False, False]): """ Function to perform a rigid body transformation based on manually determined parameters. Args: - fname (str): filepath to input nifti image (.nii.gz) - outmat (str): filepath of output 4x4 transformation matrix (.mat) - outimg (str): filepath of transformed output image (.nii.gz) - theta (np.array): vector of rotation angles in x,y,z dimension (in radians) - translation_vec (np.array): vector for translation in x,y,z (in image coordinates) - type (str): can be 'rotation' or 'translation' or 'rotation_translation' - flip_coordinates (boolean vector): indicates for which axis the sign of the offset needs to be flipped Returns: - M (np.array): output 4x4 transformation matrix - M is written to outmat - the output image (outimg) is written out Note on flip_coordinates: Voxel coordinates in the image are expected to increase in the following directions (it's similar to determining the reorient-command): - first dimension: left -> right - second dimension: posterir -> anterior - third dimension: inferior -> superior if they go the other way, change input variable accordingly, e.g.: flip_coordinates = [True, False, False] """ # get sform from image to determine offset of coordinate-system img = nib.load(fname) aff = img.get_affine() offset = aff[0:3,3] # which type of manipulation is requested if type == 'rotation': print('do rotation only') M = rotation(theta, offset, flip_coordinates) elif type == 'translation': print('do translation only') M = vector_to_translation_matrix(translation_vec) elif type == 'rotation_translation': print('do combined rotation and translation') M = rotation_translation(theta, translation_vec, offset, flip_coordinates) # save output matrix print('output matrix: ', M) print('save in: ', outmat) save_matrix4x4(M, outmat) # apply transformation to input image applywarp_command = "applywarp -i " + fname + " -r " + fname + " --premat=" + outmat + " --interp=nn -o " + outimg print('run flirt: ', applywarp_command) os.system(applywarp_command) return M
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from sys import maxsize class Contact: def __init__(self, first_name=None, middle_name=None, last_name=None, nickname=None, photo_path=None, photo_delete=False, title=None, company=None, address=None, telephones_all=None, telephone_home=None, telephone_mobile=None, telephone_work=None, telephone_fax=None, emails_all=None, email=None, email2=None, email3=None, homepage=None, birthday_day=None, birthday_month=None, birthday_year=None, anniversary_day=None, anniversary_month=None, anniversary_year=None, group=None, secondary_address=None, secondary_telephone_home=None, secondary_notes=None, id_contact=None): self.first_name = first_name self.middle_name = middle_name self.last_name = last_name self.nickname = nickname self.photo_path = photo_path self.photo_delete = photo_delete self.title = title self.company = company self.address = address self.telephones_all = telephones_all self.telephone_home = telephone_home self.telephone_mobile = telephone_mobile self.telephone_work = telephone_work self.telephone_fax = telephone_fax self.emails_all = emails_all self.email = email self.email2 = email2 self.email3 = email3 self.homepage = homepage self.birthday_day = birthday_day self.birthday_month = birthday_month self.birthday_year = birthday_year self.anniversary_day = anniversary_day self.anniversary_month = anniversary_month self.anniversary_year = anniversary_year self.group = group self.secondary_address = secondary_address self.secondary_telephone_home = secondary_telephone_home self.secondary_notes = secondary_notes self.id = id_contact def __repr__(self): return "%s: %s %s, %s" % (self.id, self.first_name, self.last_name, self.address) def __eq__(self, other): return (self.id is None or other.id is None or self.id == other.id) and \ self.check_for_none(self.first_name, other.first_name) and \ self.check_for_none(self.last_name, other.last_name) and \ self.check_for_none(self.address, other.address) def id_or_max(self): if self.id: return int(self.id) else: return maxsize def check_for_none(self, first, second): return first == second or (first is None and second == "") or (first == "" and second is None)
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import os from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker from .base import Base class MapperBase(): user = os.getenv("MYSQL_USER") key = os.getenv("MYSQL_KEY") host = os.getenv("MYSQL_HOST") port = os.getenv("MYSQL_PORT") def __init__(self, database): self.db = database if database == 'test': self.url = 'sqlite:///:memory:' else: self.url = \ 'mysql+mysqlconnector://{}:{}@{}:{}/{}'.format( self.user, self.key, self.host, self.port, self.db, ) self.engine = create_engine( self.url, connect_args={'use_pure': True} ) self.session = sessionmaker(bind=self.engine) self.base = Base def get_base(self): return self.base def get_engine(self): return self.engine def get_session(self): return self.session()
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import numpy as np import matplotlib.pyplot as plt import argparse def extract_name(word: str): return word.split('=')[-1] def extract_info(filename: str): filename_splitted = filename.split('_') assert len(filename_splitted) == 7 p = float(extract_name(filename_splitted[1])) iterations = int(extract_name(filename_splitted[2])) size = int(extract_name(filename_splitted[3])) G = int(extract_name(filename_splitted[4])) return p, iterations, size, G def load_metrics(filename: str) -> list: with open(filename, 'r') as f: return [float(line.strip()) for line in f] def plot_metrics(filename: str, metrics: list, output_path: str = None): p, iterations, size, G = extract_info(filename) x = np.linspace(0, iterations, len(metrics)) plt.rc('text', usetex=True) plt.rc('font', family='serif') plt.figure(figsize=(8, 5)) plt.grid(True, alpha=0.3) plt.plot(x, metrics, label=f'p = {p}, N = {size}, G = {G}') plt.ylabel(r'$\rho$', fontsize=14) plt.xlabel('$t$', fontsize=14) plt.xticks(fontsize=14) plt.yticks(fontsize=14) plt.legend(fontsize=13) if output_path is not None: plt.savefig(output_path, bbox_inches='tight') else: plt.show() def main(): parser = argparse.ArgumentParser(description='Plot positive edge density (rho)') parser.add_argument('--metrics-file', type=str, required=True, help='Path to calculated positive edge density') parser.add_argument('--output-figure', type=str, required=False, default=None, help='Where to save output figure') args = parser.parse_args() metrics = load_metrics(args.metrics_file) plot_metrics(args.metrics_file, metrics, args.output_figure) if __name__ == '__main__': main()
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from decimal import Decimal from urllib.parse import urlparse from django import forms from django.conf import settings from django.core.exceptions import ValidationError from django.db.models import Q from django.utils.safestring import mark_safe from django.utils.translation import gettext_lazy as _, pgettext_lazy from django_scopes.forms import SafeModelMultipleChoiceField from pretix.api.models import WebHook from pretix.api.webhooks import get_all_webhook_events from pretix.base.forms import I18nModelForm, SettingsForm from pretix.base.forms.widgets import SplitDateTimePickerWidget from pretix.base.models import ( Device, EventMetaProperty, Gate, GiftCard, Organizer, Team, ) from pretix.control.forms import ExtFileField, SplitDateTimeField from pretix.control.forms.event import SafeEventMultipleChoiceField from pretix.multidomain.models import KnownDomain class OrganizerForm(I18nModelForm): error_messages = { 'duplicate_slug': _("This slug is already in use. Please choose a different one."), } class Meta: model = Organizer fields = ['name', 'slug'] def clean_slug(self): slug = self.cleaned_data['slug'] if Organizer.objects.filter(slug__iexact=slug).exists(): raise forms.ValidationError( self.error_messages['duplicate_slug'], code='duplicate_slug', ) return slug class OrganizerDeleteForm(forms.Form): error_messages = { 'slug_wrong': _("The slug you entered was not correct."), } slug = forms.CharField( max_length=255, label=_("Event slug"), ) def __init__(self, *args, **kwargs): self.organizer = kwargs.pop('organizer') super().__init__(*args, **kwargs) def clean_slug(self): slug = self.cleaned_data.get('slug') if slug != self.organizer.slug: raise forms.ValidationError( self.error_messages['slug_wrong'], code='slug_wrong', ) return slug class OrganizerUpdateForm(OrganizerForm): def __init__(self, *args, **kwargs): self.domain = kwargs.pop('domain', False) self.change_slug = kwargs.pop('change_slug', False) kwargs.setdefault('initial', {}) self.instance = kwargs['instance'] if self.domain and self.instance: initial_domain = self.instance.domains.first() if initial_domain: kwargs['initial'].setdefault('domain', initial_domain.domainname) super().__init__(*args, **kwargs) if not self.change_slug: self.fields['slug'].widget.attrs['readonly'] = 'readonly' if self.domain: self.fields['domain'] = forms.CharField( max_length=255, label=_('Custom domain'), required=False, help_text=_('You need to configure the custom domain in the webserver beforehand.') ) def clean_domain(self): d = self.cleaned_data['domain'] if d: if d == urlparse(settings.SITE_URL).hostname: raise ValidationError( _('You cannot choose the base domain of this installation.') ) if KnownDomain.objects.filter(domainname=d).exclude(organizer=self.instance.pk, event__isnull=True).exists(): raise ValidationError( _('This domain is already in use for a different event or organizer.') ) return d def clean_slug(self): if self.change_slug: return self.cleaned_data['slug'] return self.instance.slug def save(self, commit=True): instance = super().save(commit) if self.domain: current_domain = instance.domains.first() if self.cleaned_data['domain']: if current_domain and current_domain.domainname != self.cleaned_data['domain']: current_domain.delete() KnownDomain.objects.create(organizer=instance, domainname=self.cleaned_data['domain']) elif not current_domain: KnownDomain.objects.create(organizer=instance, domainname=self.cleaned_data['domain']) elif current_domain: current_domain.delete() instance.cache.clear() for ev in instance.events.all(): ev.cache.clear() return instance class EventMetaPropertyForm(forms.ModelForm): class Meta: model = EventMetaProperty fields = ['name', 'default', 'required', 'protected', 'allowed_values'] widgets = { 'default': forms.TextInput() } class TeamForm(forms.ModelForm): def __init__(self, *args, **kwargs): organizer = kwargs.pop('organizer') super().__init__(*args, **kwargs) self.fields['limit_events'].queryset = organizer.events.all().order_by( '-has_subevents', '-date_from' ) class Meta: model = Team fields = ['name', 'all_events', 'limit_events', 'can_create_events', 'can_change_teams', 'can_change_organizer_settings', 'can_manage_gift_cards', 'can_change_event_settings', 'can_change_items', 'can_view_orders', 'can_change_orders', 'can_view_vouchers', 'can_change_vouchers'] widgets = { 'limit_events': forms.CheckboxSelectMultiple(attrs={ 'data-inverse-dependency': '#id_all_events', 'class': 'scrolling-multiple-choice scrolling-multiple-choice-large', }), } field_classes = { 'limit_events': SafeEventMultipleChoiceField } def clean(self): data = super().clean() if self.instance.pk and not data['can_change_teams']: if not self.instance.organizer.teams.exclude(pk=self.instance.pk).filter( can_change_teams=True, members__isnull=False ).exists(): raise ValidationError(_('The changes could not be saved because there would be no remaining team with ' 'the permission to change teams and permissions.')) return data class GateForm(forms.ModelForm): def __init__(self, *args, **kwargs): kwargs.pop('organizer') super().__init__(*args, **kwargs) class Meta: model = Gate fields = ['name', 'identifier'] class DeviceForm(forms.ModelForm): def __init__(self, *args, **kwargs): organizer = kwargs.pop('organizer') super().__init__(*args, **kwargs) self.fields['limit_events'].queryset = organizer.events.all().order_by( '-has_subevents', '-date_from' ) self.fields['gate'].queryset = organizer.gates.all() def clean(self): d = super().clean() if not d['all_events'] and not d['limit_events']: raise ValidationError(_('Your device will not have access to anything, please select some events.')) return d class Meta: model = Device fields = ['name', 'all_events', 'limit_events', 'security_profile', 'gate'] widgets = { 'limit_events': forms.CheckboxSelectMultiple(attrs={ 'data-inverse-dependency': '#id_all_events', 'class': 'scrolling-multiple-choice scrolling-multiple-choice-large', }), } field_classes = { 'limit_events': SafeEventMultipleChoiceField } class OrganizerSettingsForm(SettingsForm): auto_fields = [ 'contact_mail', 'imprint_url', 'organizer_info_text', 'event_list_type', 'event_list_availability', 'organizer_homepage_text', 'organizer_link_back', 'organizer_logo_image_large', 'giftcard_length', 'giftcard_expiry_years', 'locales', 'region', 'event_team_provisioning', 'primary_color', 'theme_color_success', 'theme_color_danger', 'theme_color_background', 'theme_round_borders', 'primary_font' ] organizer_logo_image = ExtFileField( label=_('Header image'), ext_whitelist=(".png", ".jpg", ".gif", ".jpeg"), max_size=10 * 1024 * 1024, required=False, help_text=_('If you provide a logo image, we will by default not show your organization name ' 'in the page header. By default, we show your logo with a size of up to 1140x120 pixels. You ' 'can increase the size with the setting below. We recommend not using small details on the picture ' 'as it will be resized on smaller screens.') ) favicon = ExtFileField( label=_('Favicon'), ext_whitelist=(".ico", ".png", ".jpg", ".gif", ".jpeg"), required=False, max_size=1 * 1024 * 1024, help_text=_('If you provide a favicon, we will show it instead of the default pretix icon. ' 'We recommend a size of at least 200x200px to accommodate most devices.') ) class WebHookForm(forms.ModelForm): events = forms.MultipleChoiceField( widget=forms.CheckboxSelectMultiple, label=pgettext_lazy('webhooks', 'Event types') ) def __init__(self, *args, **kwargs): organizer = kwargs.pop('organizer') super().__init__(*args, **kwargs) self.fields['limit_events'].queryset = organizer.events.all() self.fields['events'].choices = [ ( a.action_type, mark_safe('{} – <code>{}</code>'.format(a.verbose_name, a.action_type)) ) for a in get_all_webhook_events().values() ] if self.instance: self.fields['events'].initial = list(self.instance.listeners.values_list('action_type', flat=True)) class Meta: model = WebHook fields = ['target_url', 'enabled', 'all_events', 'limit_events'] widgets = { 'limit_events': forms.CheckboxSelectMultiple(attrs={ 'data-inverse-dependency': '#id_all_events' }), } field_classes = { 'limit_events': SafeModelMultipleChoiceField } class GiftCardCreateForm(forms.ModelForm): value = forms.DecimalField( label=_('Gift card value'), min_value=Decimal('0.00') ) def __init__(self, *args, **kwargs): self.organizer = kwargs.pop('organizer') initial = kwargs.pop('initial', {}) initial['expires'] = self.organizer.default_gift_card_expiry kwargs['initial'] = initial super().__init__(*args, **kwargs) def clean_secret(self): s = self.cleaned_data['secret'] if GiftCard.objects.filter( secret__iexact=s ).filter( Q(issuer=self.organizer) | Q(issuer__gift_card_collector_acceptance__collector=self.organizer) ).exists(): raise ValidationError( _('A gift card with the same secret already exists in your or an affiliated organizer account.') ) return s class Meta: model = GiftCard fields = ['secret', 'currency', 'testmode', 'expires', 'conditions'] field_classes = { 'expires': SplitDateTimeField } widgets = { 'expires': SplitDateTimePickerWidget, 'conditions': forms.Textarea(attrs={"rows": 2}) } class GiftCardUpdateForm(forms.ModelForm): class Meta: model = GiftCard fields = ['expires', 'conditions'] field_classes = { 'expires': SplitDateTimeField } widgets = { 'expires': SplitDateTimePickerWidget, 'conditions': forms.Textarea(attrs={"rows": 2}) }
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from setuptools import setup from setuptools import find_packages with open('README.rst') as f: LONG_DESCRIPTION = f.read() MAJOR_VERSION = '0' MINOR_VERSION = '11' MICRO_VERSION = '214' VERSION = "{}.{}.{}".format(MAJOR_VERSION, MINOR_VERSION, MICRO_VERSION) setup(name='yagmail', version=VERSION, description='Yet Another GMAIL client', long_description=LONG_DESCRIPTION, url='https://github.com/kootenpv/yagmail', author='Pascal van Kooten', author_email='kootenpv@gmail.com', license='MIT', extras_require={ "all": ["keyring"] }, keywords='email mime automatic html attachment', entry_points={ 'console_scripts': ['yagmail = yagmail.__main__:main'] }, classifiers=[ 'Environment :: Console', 'Intended Audience :: Developers', 'Intended Audience :: Customer Service', 'Intended Audience :: System Administrators', 'License :: OSI Approved :: MIT License', 'Operating System :: Microsoft', 'Operating System :: MacOS :: MacOS X', 'Operating System :: Unix', 'Operating System :: POSIX', 'Programming Language :: Python', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Topic :: Communications :: Email', 'Topic :: Communications :: Email :: Email Clients (MUA)', 'Topic :: Software Development', 'Topic :: Software Development :: Build Tools', 'Topic :: Software Development :: Debuggers', 'Topic :: Software Development :: Libraries', 'Topic :: Software Development :: Libraries :: Python Modules', 'Topic :: System :: Software Distribution', 'Topic :: System :: Systems Administration', 'Topic :: Utilities' ], packages=find_packages(), zip_safe=False, platforms='any')
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from jinja2 import Template from starlette.applications import Starlette from starlette.middleware import Middleware from starlette.middleware.sessions import SessionMiddleware from starlette.responses import PlainTextResponse, HTMLResponse from starlette_wtf import StarletteForm, CSRFProtectMiddleware, csrf_protect from wtforms import StringField from wtforms.validators import DataRequired class MyForm(StarletteForm): name = StringField('name', validators=[DataRequired()]) template = Template(''' <html> <body> <form method="post" novalidate> {{ form.csrf_token }} <div> {{ form.name(placeholder='Name') }} {% if form.name.errors -%} <span>{{ form.name.errors[0] }}</span> {%- endif %} </div> <button type="submit">Submit</button> </form> </body> </html> ''') app = Starlette(middleware=[ Middleware(SessionMiddleware, secret_key='***REPLACEME1***'), Middleware(CSRFProtectMiddleware, csrf_secret='***REPLACEME2***') ]) @app.route('/', methods=['GET', 'POST']) @csrf_protect async def index(request): """GET|POST /: form handler """ form = await MyForm.from_formdata(request) if form.validate_on_submit(): return PlainTextResponse('SUCCESS') html = template.render(form=form) return HTMLResponse(html)
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#подключение библиотек from PyQt5.QtCore import Qt from PyQt5.QtWidgets import QApplication, QWidget, QPushButton, QLabel,QVBoxLayout,QHBoxLayout, QMessageBox, QRadioButton #создание приложения и главного окна app=QApplication([]) main_win =QWidget() main_win.setWindowTitle('Конкурс от Crazy People') question =QLabel("В каком году канал получил золотую кнопку от YouTube?") btn_answer1 =QRadioButton('2005') btn_answer2 =QRadioButton('2010') btn_answer3 =QRadioButton('2015') btn_answer4 =QRadioButton('2020') layout_main=QVBoxLayout() h1=QHBoxLayout() h2=QHBoxLayout() h3=QHBoxLayout() h1.addWidget(question,alignment =Qt.AlignCenter) h2.addWidget(btn_answer1,alignment =Qt.AlignCenter) h2.addWidget(btn_answer2,alignment =Qt.AlignCenter) h3.addWidget(btn_answer3,alignment =Qt.AlignCenter) h3.addWidget(btn_answer4,alignment =Qt.AlignCenter) layout_main.addLayout(h1) layout_main.addLayout(h2) layout_main.addLayout(h3) main_win.setLayout(layout_main) def win (): win =QMessageBox() win.setText('Верно!') win.exec_() def lose(): lose =QMessageBox() lose.setText('«Нет, в 2015 году. Вы выиграли фирменный плакат') lose.exec_() btn_answer1.clicked.connect(lose) btn_answer2.clicked.connect(lose) btn_answer3.clicked.connect(win) btn_answer4.clicked.connect(lose) main_win.show() app.exec_()
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from action_class import Action place = 'place' upgrade = 'upgrade' target = 'target' top = 'upgrade 1' middle = 'upgrade 2' bottom = 'upgrade 3' ouch_script = [ Action(place, name='sub1', action='sub', position=(708, 540)), # Sub Action(place, name='sub2', action='sub', position=(984, 545)), # Sub2 Action('start', action='start', cost=0), Action(place, name='dart1', action='dart', position=(303, 671)), # Dart Action(place, name='Psi', action='Hero', position=(546, 309)), # Psi Action(target, name = 'Psi', action='Strong'), # Psi Strong Action(upgrade, name='sub1', action=bottom), # 001 Action(upgrade, name='sub2', action=bottom), # 001 Action(upgrade, name='sub1', action=middle), # 011 Action(upgrade, name='sub2', action=top), # 101 Action(upgrade, name='sub1', action=middle), # 021 Action(upgrade, name='sub2', action=top), # 201 Action(upgrade, name='sub1', action=bottom), # 022 Action(upgrade, name='sub2', action=bottom), # 202 Action(place, name='alch1', action='alch', position=(1009, 411)), # Alchemist Action(target, name = 'alch1', action='Strong'), # Strong Action(upgrade, name='alch1', action=top), # 100 Action(upgrade, name='alch1', action=top), # 200 Action(upgrade, name='sub2', action=bottom), # 203 Sub2 Action(place, name='ace1', action='ace', position=(845, 310)), # Ace Action(upgrade, name='ace1', action= bottom), # 001 Action(upgrade, name='ace1', action=bottom), # 002 Action(upgrade, name='ace1', action=bottom), # 003 Action(place, name='village1', action='Village', position=(990, 295)), # Village Action(upgrade, name='village1', action= middle), # 010 Action(upgrade, name='village1', action= middle), # 020 Action(upgrade, name='ace1', action=top), # 103 Ace Action(upgrade, name='ace1', action=top), # 203 Action(upgrade, name='sub2', action=bottom), # 204 Sub2 Action(upgrade, name='sub1', action=middle), # 023 Sub2 Action(upgrade, name='alch1', action=top), # 300 Alch Action(upgrade, name='alch1', action=top), # 400 Action(upgrade, name='alch1', action=bottom), # 401 Action(upgrade, name='ace1', action=bottom), # 204 Ace Action(place, name='sniper1', action='sniper', position=(85, 676)), # Sniper Action(upgrade, name='sniper1', action= top), # 100 Action(target, name = 'sniper1', action='Strong'), Action(upgrade, name='sniper1', action=top), # 200 Action(upgrade, name='sniper1', action=top), # 300 Action(upgrade, name='sniper1', action=top), # 400 Action(upgrade, name='sniper1', action=bottom), # 401 Action(upgrade, name='sniper1', action=bottom), # 402 Action('finish', action='finish', cost=0) ]
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def run(): my_list = [1, "Hello", True, 4.5] my_dict = {"firstname":"Facundo", "lastname":"Garcia"} superList = [ {"firstname":"Facundo", "lastname":"Garcia"}, {"firstname":"Miguel", "lastname":"Torres"}, {"firstname":"José", "lastname":"Rodelo"}, {"firstname":"Susana", "lastname":"Martinez"}, {"firstname":"Luis", "lastname":"Cruz"} ] superDict = { "naturalNums": [1,2,3,4,5], "integerNums": [-1,-2,0,1,2], "floatingNums": [1.1, 4.5, 6.43] } for k, v in superDict.items(): print(k, "-", v) for innerDict in superList: for k, v in innerDict.items(): print(k, "-", v) if __name__ == '__main__': run()
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import numpy as np import matplotlib.pyplot as plt import matplotlib.colors as colors from mpl_toolkits.axes_grid1 import make_axes_locatable #Key: # 1=sandstone 2=c_siltstone 3=f_siltstone # 4=marine_silt_shale 5=mudstone 6=wackestone 7=dolomite # 8=packstone 9=bafflestone facies_labels = ['SS', 'CSiS', 'FSiS', 'SiSh', 'MS', 'WS', 'D','PS', 'BS'] facies_colors = ['#F4D03F', '#F5B041','#DC7633','#6E2C00', '#1B4F72','#2E86C1', '#AED6F1', '#A569BD', '#196F3D'] #facies_color_map is a dictionary that maps facies labels #to their respective colors facies_color_map = {} for ind, label in enumerate(facies_labels): facies_color_map[label] = facies_colors[ind] def label_facies(row, labels): return labels[ row['Facies'] -1] def make_facies_log_plot(logs, facies_colors): #make sure logs are sorted by depth logs = logs.sort_values(by='Depth') cmap_facies = colors.ListedColormap( facies_colors[0:len(facies_colors)], 'indexed') ztop=logs.Depth.min(); zbot=logs.Depth.max() cluster=np.repeat(np.expand_dims(logs['Facies'].values,1), 100, 1) f, ax = plt.subplots(nrows=1, ncols=6, figsize=(8, 12)) ax[0].plot(logs.GR, logs.Depth, '-g') ax[1].plot(logs.ILD_log10, logs.Depth, '-') ax[2].plot(logs.DeltaPHI, logs.Depth, '-', color='0.5') ax[3].plot(logs.PHIND, logs.Depth, '-', color='r') ax[4].plot(logs.PE, logs.Depth, '-', color='black') im=ax[5].imshow(cluster, interpolation='none', aspect='auto', cmap=cmap_facies,vmin=1,vmax=9) divider = make_axes_locatable(ax[5]) cax = divider.append_axes("right", size="20%", pad=0.05) cbar=plt.colorbar(im, cax=cax) cbar.set_label((17*' ').join([' SS ', 'CSiS', 'FSiS', 'SiSh', ' MS ', ' WS ', ' D ', ' PS ', ' BS '])) cbar.set_ticks(range(0,1)); cbar.set_ticklabels('') for i in range(len(ax)-1): ax[i].set_ylim(ztop,zbot) ax[i].invert_yaxis() ax[i].grid() ax[i].locator_params(axis='x', nbins=3) ax[0].set_xlabel("GR") ax[0].set_xlim(logs.GR.min(),logs.GR.max()) ax[1].set_xlabel("ILD_log10") ax[1].set_xlim(logs.ILD_log10.min(),logs.ILD_log10.max()) ax[2].set_xlabel("DeltaPHI") ax[2].set_xlim(logs.DeltaPHI.min(),logs.DeltaPHI.max()) ax[3].set_xlabel("PHIND") ax[3].set_xlim(logs.PHIND.min(),logs.PHIND.max()) ax[4].set_xlabel("PE") ax[4].set_xlim(logs.PE.min(),logs.PE.max()) ax[5].set_xlabel('Facies') ax[1].set_yticklabels([]); ax[2].set_yticklabels([]); ax[3].set_yticklabels([]) ax[4].set_yticklabels([]); ax[5].set_yticklabels([]) ax[5].set_xticklabels([]) f.suptitle('Well: %s'%logs.iloc[0]['WellName'], fontsize=14,y=0.94) def compare_facies_plot(logs, compadre, facies_colors): """plot the facies plot as a function of depth for both the prediction and the actual lithofacies labels. """ #make sure logs are sorted by depth logs = logs.sort_values(by='Depth') cmap_facies = colors.ListedColormap( facies_colors[0:len(facies_colors)], 'indexed') ztop=logs.Depth.min(); zbot=logs.Depth.max() cluster1 = np.repeat(np.expand_dims(logs['Facies'].values,1), 100, 1) cluster2 = np.repeat(np.expand_dims(logs[compadre].values,1), 100, 1) f, ax = plt.subplots(nrows=1, ncols=7, figsize=(9, 12)) ax[0].plot(logs.GR, logs.Depth, '-g') ax[1].plot(logs.ILD_log10, logs.Depth, '-') ax[2].plot(logs.DeltaPHI, logs.Depth, '-', color='0.5') ax[3].plot(logs.PHIND, logs.Depth, '-', color='r') ax[4].plot(logs.PE, logs.Depth, '-', color='black') im1 = ax[5].imshow(cluster1, interpolation='none', aspect='auto', cmap=cmap_facies,vmin=1,vmax=9) im2 = ax[6].imshow(cluster2, interpolation='none', aspect='auto', cmap=cmap_facies,vmin=1,vmax=9) divider = make_axes_locatable(ax[6]) cax = divider.append_axes("right", size="20%", pad=0.05) cbar=plt.colorbar(im2, cax=cax) cbar.set_label((17*' ').join([' SS ', 'CSiS', 'FSiS', 'SiSh', ' MS ', ' WS ', ' D ', ' PS ', ' BS '])) cbar.set_ticks(range(0,1)); cbar.set_ticklabels('') for i in range(len(ax)-2): ax[i].set_ylim(ztop,zbot) ax[i].invert_yaxis() ax[i].grid() ax[i].locator_params(axis='x', nbins=3) ax[0].set_xlabel("GR") ax[0].set_xlim(logs.GR.min(),logs.GR.max()) ax[1].set_xlabel("ILD_log10") ax[1].set_xlim(logs.ILD_log10.min(),logs.ILD_log10.max()) ax[2].set_xlabel("DeltaPHI") ax[2].set_xlim(logs.DeltaPHI.min(),logs.DeltaPHI.max()) ax[3].set_xlabel("PHIND") ax[3].set_xlim(logs.PHIND.min(),logs.PHIND.max()) ax[4].set_xlabel("PE") ax[4].set_xlim(logs.PE.min(),logs.PE.max()) ax[5].set_xlabel('Facies') ax[6].set_xlabel(compadre) ax[1].set_yticklabels([]); ax[2].set_yticklabels([]); ax[3].set_yticklabels([]) ax[4].set_yticklabels([]); ax[5].set_yticklabels([]) ax[5].set_xticklabels([]) ax[6].set_xticklabels([]) f.suptitle('Well: %s'%logs.iloc[0]['WellName'], fontsize=14,y=0.94)
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import wx import numpy as np from imagepy.core.engine import Tool, Filter import scipy.ndimage as nimg class ScaleTool(Tool): def __init__(self, plg): self.plg = plg self.para = plg.para self.moving = False def snap(self, x, y, lim): plg = self.plg if abs(x-plg.lt)<lim and abs(y-(plg.tp+plg.bm)/2)<lim:return 'l' if abs(x-plg.rt)<lim and abs(y-(plg.tp+plg.bm)/2)<lim:return 'r' if abs(x-(plg.lt+plg.rt)/2)<lim and abs(y-plg.tp)<lim:return 't' if abs(x-(plg.lt+plg.rt)/2)<lim and abs(y-plg.bm)<lim:return 'b' if abs(x-plg.lt)<lim and abs(y-plg.tp)<lim:return 'lt' if abs(x-plg.rt)<lim and abs(y-plg.bm)<lim:return 'rb' if abs(x-plg.rt)<lim and abs(y-plg.tp)<lim:return 'rt' if abs(x-plg.lt)<lim and abs(y-plg.bm)<lim:return 'lb' if (x-plg.lt)*(x-plg.rt)<0 and (y-plg.tp)*(y-plg.bm)<0: self.ox, self.oy = x, y return True return False def mouse_down(self, ips, x, y, btn, **key): lim = 5.0/key['canvas'].get_scale() self.moving = self.snap(x, y, lim) print(self.moving) def mouse_up(self, ips, x, y, btn, **key): if self.moving : self.plg.preview(ips, self.para) def mouse_move(self, ips, x, y, btn, **key): lim = 5.0/key['canvas'].get_scale() if btn==None: self.cursor = wx.CURSOR_CROSS if isinstance(self.snap(x, y, lim), str): self.cursor = wx.CURSOR_HAND elif self.moving==True: self.plg.lt+=x-self.ox self.plg.rt+=x-self.ox self.plg.bm+=y-self.oy self.plg.tp+=y-self.oy self.ox, self.oy = x, y self.plg.count() self.plg.dialog.reset() ips.update = True elif self.moving != False: print("scale_tol.ScaleTool.mouse_move") if 'l' in self.moving:self.plg.lt = x if 'r' in self.moving:self.plg.rt = x if 't' in self.moving:self.plg.tp = y if 'b' in self.moving:self.plg.bm = y self.plg.count() self.plg.dialog.reset() ips.update = True class Plugin(Filter): modal = False title = 'Scale' note = ['all', 'auto_msk', 'auto_snap', 'preview'] para = {'kx': 1, 'ky':1, 'ox':0, 'oy':0, 'img':True, 'msk':False} view = [(float, (-100,100), 3, 'KX', 'kx', ''), (float, (-100,100), 3, 'KY', 'ky', ''), (int, (-10000,10000), 0, 'OffX', 'ox', 'pix'), (int, (-10000,10000), 0, 'OffY', 'oy', 'pix'), (bool, 'scale image', 'img'), (bool, 'scale mask', 'msk')] def draw(self, dc, f, **key): body = [(self.lt,self.bm),(self.rt,self.bm), (self.rt,self.tp),(self.lt,self.tp),(self.lt,self.bm)] dc.SetPen(wx.Pen((0,255,0), width=1, style=wx.SOLID)) dc.DrawLines([f(*i) for i in body]) for i in body:dc.DrawCircle(f(*i),2) dc.DrawCircle(f(self.lt, (self.tp+self.bm)/2),2) dc.DrawCircle(f(self.rt, (self.tp+self.bm)/2),2) dc.DrawCircle(f((self.lt+self.rt)/2, self.tp),2) dc.DrawCircle(f((self.lt+self.rt)/2, self.bm),2) def load(self, ips): self.bufroi = ips.roi self.lt, self.tp, self.rt, self.bm = 0, 0, ips.size[1], ips.size[0] if ips.roi!=None: box = ips.roi.get_box() if box[0]!=box[2] and box[1]!=box[3]: self.lt, self.tp, self.rt, self.bm = box self.orio = ((self.lt+self.rt)/2,(self.tp+self.bm)/2) self.oriw, self.orih = self.rt - self.lt, self.tp - self.bm self.para['ox'] = (self.lt+self.rt)/2 self.para['oy'] = (self.tp+self.bm)/2 self.para['kx'] = self.para['ky'] = 1 ips.mark = self ips.update = True ips.tool = ScaleTool(self) return True def count(self, dir=True): if dir: self.para['ox'] = int((self.lt+self.rt)/2) self.para['oy'] = int((self.tp+self.bm)/2) self.para['kx'] = (self.rt-self.lt)*1.0/self.oriw self.para['ky'] = (self.tp-self.bm)*1.0/self.orih else: self.lt = self.para['ox']-self.oriw*self.para['kx']/2 self.rt = self.para['ox']+self.oriw*self.para['kx']/2 self.bm = self.para['oy']-self.orih*self.para['ky']/2 self.tp = self.para['oy']+self.orih*self.para['ky']/2 def ok(self, ips, para=None): Filter.ok(self, ips, para) ips.mark = None ips.tool = None def cancel(self, ips): Filter.cancel(self, ips) ips.roi = self.bufroi ips.mark = None ips.tool = None ips.update = 'pix' def run(self, ips, img, buf, para = None): if para == None: para = self.para self.count(False) trans = np.array([[1/self.para['ky'],0],[0,1/self.para['kx']]]) o = np.array([self.para['oy'], self.para['ox']]) offset = self.orio[::-1]-trans.dot(o) if self.para['img']: nimg.affine_transform(img, trans, output=buf, offset=offset) trans = np.array([[self.para['kx'],0],[0, self.para['ky']]]) offset = o[::-1]-trans.dot(self.orio) if self.para['msk'] and self.bufroi!=None:ips.roi = self.bufroi.affine(trans, offset) if self.para['img'] and not ips.get_msk('out') is None: buf[ips.get_msk('out')] = img[ips.get_msk('out')] ips.update = True
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class std_logic(): """ class to represent a digital bit allowing for the same 9 values of a bit supported by IEEE 1164. ====== =============== Value Interpreatation ------ --------------- U Unitialized X Unknown 0 Strong 0 1 Strong 1 Z High Impedance W Weak unknown logic L Weak logic 0 H Weak logic 1 - Don't care ====== =============== Refer to https://en.wikipedia.org/wiki/IEEE_1164 for more details """ def __init__(self,initialvalue='U'): """ :param initialvalue: value to be loaded into the bit :type initialvalue: int, bool, str """ self._value = 'U' self.set(value=initialvalue) def __str__(self): return self._value def __repr__(self): base_repr = super().__repr__() return base_repr[:-2] + ':%s>'%self._value def __eq__(self, other): if issubclass(other.__class__,std_logic): return self._value == other._value else: raise NotImplementedError def __and__(self,other): return_value = NotImplemented if issubclass(other.__class__,std_logic): """ truth table from std_logic_1164-body.vhdl ---------------------------------------------------- | U X 0 1 Z W L H - | | ---------------------------------------------------- ( 'U', 'U', '0', 'U', 'U', 'U', '0', 'U', 'U' ), -- | U | ( 'U', 'X', '0', 'X', 'X', 'X', '0', 'X', 'X' ), -- | X | ( '0', '0', '0', '0', '0', '0', '0', '0', '0' ), -- | 0 | ( 'U', 'X', '0', '1', 'X', 'X', '0', '1', 'X' ), -- | 1 | ( 'U', 'X', '0', 'X', 'X', 'X', '0', 'X', 'X' ), -- | Z | ( 'U', 'X', '0', 'X', 'X', 'X', '0', 'X', 'X' ), -- | W | ( '0', '0', '0', '0', '0', '0', '0', '0', '0' ), -- | L | ( 'U', 'X', '0', '1', 'X', 'X', '0', '1', 'X' ), -- | H | ( 'U', 'X', '0', 'X', 'X', 'X', '0', 'X', 'X' ) -- | - | """ if self == std_logic('U'): if other == std_logic('0') or other == std_logic('L'): return_value = std_logic(0) else: return_value = std_logic('U') elif self == std_logic('X') or self == std_logic('-') or self == std_logic('W') or self == std_logic('Z'): if other == std_logic('U'): return_value = std_logic('U') elif other == std_logic('0') or other == std_logic('L'): return_value = std_logic(0) else: return_value = std_logic('X') elif self == std_logic('0') or self == std_logic('L'): return_value = std_logic(0) elif self == std_logic('1') or self == std_logic('H'): if other == std_logic('U'): return_value = std_logic('U') elif other == std_logic('0') or other == std_logic('L'): return_value = std_logic(0) elif other == std_logic('1') or other == std_logic('H'): return_value = std_logic(1) else: return_value = std_logic('X') else: raise TypeError('can not perform operation on classes') return return_value def __xor__(self, other): """ perfroms a bitwise xor operation :param other: :return: self ^ other """ return_value = NotImplemented if issubclass(other.__class__,std_logic): """ truth table from std_logic_1164-body.vhdl ---------------------------------------------------- | U X 0 1 Z W L H - | | ---------------------------------------------------- ('U', 'U', 'U', 'U', 'U', 'U', 'U', 'U', 'U'), -- | U | ('U', 'X', 'X', 'X', 'X', 'X', 'X', 'X', 'X'), -- | X | ('U', 'X', '0', '1', 'X', 'X', '0', '1', 'X'), -- | 0 | ('U', 'X', '1', '0', 'X', 'X', '1', '0', 'X'), -- | 1 | ('U', 'X', 'X', 'X', 'X', 'X', 'X', 'X', 'X'), -- | Z | ('U', 'X', 'X', 'X', 'X', 'X', 'X', 'X', 'X'), -- | W | ('U', 'X', '0', '1', 'X', 'X', '0', '1', 'X'), -- | L | ('U', 'X', '1', '0', 'X', 'X', '1', '0', 'X'), -- | H | ('U', 'X', 'X', 'X', 'X', 'X', 'X', 'X', 'X') -- | - | ); """ if self == std_logic('U'): return_value = std_logic('U') elif self == std_logic('X') or self == std_logic('-') or self == std_logic('W') or self == std_logic('Z'): if other == std_logic('U'): return_value = std_logic('U') else: return_value = std_logic('X') elif self == std_logic('1') or self == std_logic('H'): if other == std_logic('U'): return_value = std_logic('U') elif other == std_logic('0') or other == std_logic('L'): return_value = std_logic(1) elif other == std_logic('1') or other == std_logic('H'): return_value = std_logic(0) else: return_value = std_logic('X') elif self == std_logic('0') or self == std_logic('L'): if other == std_logic('U'): return_value = std_logic('U') elif other == std_logic('0') or other == std_logic('L'): return_value = std_logic(0) elif other == std_logic('1') or other == std_logic('H'): return_value = std_logic(1) else: return_value = std_logic('X') else: raise TypeError('can not perform operation on classes') return return_value def __or__(self,other): return_value = NotImplemented if issubclass(other.__class__,std_logic): """ truth table from std_logic_1164-body.vhdl ---------------------------------------------------- | U X 0 1 Z W L H - | | ---------------------------------------------------- ('U', 'U', 'U', '1', 'U', 'U', 'U', '1', 'U'), -- | U | ('U', 'X', 'X', '1', 'X', 'X', 'X', '1', 'X'), -- | X | ('U', 'X', '0', '1', 'X', 'X', '0', '1', 'X'), -- | 0 | ('1', '1', '1', '1', '1', '1', '1', '1', '1'), -- | 1 | ('U', 'X', 'X', '1', 'X', 'X', 'X', '1', 'X'), -- | Z | ('U', 'X', 'X', '1', 'X', 'X', 'X', '1', 'X'), -- | W | ('U', 'X', '0', '1', 'X', 'X', '0', '1', 'X'), -- | L | ('1', '1', '1', '1', '1', '1', '1', '1', '1'), -- | H | ('U', 'X', 'X', '1', 'X', 'X', 'X', '1', 'X') -- | - | ) """ if self == std_logic('U'): if other == std_logic('1') or other == std_logic('H'): return_value = std_logic(1) else: return_value = std_logic('U') elif self == std_logic('X') or self == std_logic('-') or self == std_logic('W') or self == std_logic('Z'): if other == std_logic('U'): return_value = std_logic('U') elif other == std_logic('1') or other == std_logic('H'): return_value = std_logic(1) else: return_value = std_logic('X') elif self == std_logic('1') or self == std_logic('H'): return_value = std_logic(1) elif self == std_logic('0') or self == std_logic('L'): if other == std_logic('U'): return_value = std_logic('U') elif other == std_logic('0') or other == std_logic('L'): return_value = std_logic(0) elif other == std_logic('1') or other == std_logic('H'): return_value = std_logic(1) else: return_value = std_logic('X') else: raise TypeError('can not perform operation on classes') return return_value def __invert__(self): """ truth table from std_logic_1164-body.vhdl ------------------------------------------------- | U X 0 1 Z W L H - | ------------------------------------------------- ('U', 'X', '1', '0', 'X', 'X', '1', '0', 'X') """ if self == std_logic('U'): return_value = std_logic('U') elif self == std_logic('X') or self == std_logic('-') or self == std_logic('W') or self == std_logic('Z'): return_value = std_logic('X') elif self == std_logic('0') or self == std_logic('L'): return_value = std_logic(1) elif self == std_logic('1') or self == std_logic('H'): return_value = std_logic(0) return return_value def set(self,value): """ in place value set :param value: value to be loaded into the bit :type value: int, bool, str """ if isinstance(value,str): if len(value) != 1: raise ValueError('length is not 1') if ((value == 'U') or (value == 'X') or (value == '0') or (value == '1') or (value == 'Z') or (value == 'W') or (value == 'L') or (value == 'H') or (value == '-')): self._value = value else: raise ValueError('Unsupported value, only U,X,0,1,Z,W,L,H or - is permitted') elif isinstance(value,bool): if value is False: self._value = '0' elif value is True: self._value = '1' else: raise ValueError('Illegal boolean value') elif isinstance(value,int): if (value == 0) or (value == 1): self._value = str(value) assert (self._value == '1') or (self._value == '0') else: raise ValueError('Unsupported integer value, only 0 or 1 is permitted') else: raise ValueError('Unsupported type')
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#!/usr/bin/env python """ Predefined bluesky scan plans """ import numpy as np import bluesky.plans as bp import bluesky.preprocessors as bpp import bluesky.plan_stubs as bps from .utility import load_config #@bpp.run_decorator() def collect_white_field(experiment, cfg_tomo, atfront=True): """ Collect white/flat field images by moving the sample out of the FOV """ # unpack devices det = experiment.det tomostage = experiment.tomostage # move sample out of the way _x = cfg_tomo['fronte_white_ksamX'] if atfront else cfg_tomo['back_white_ksamX'] _z = cfg_tomo['fronte_white_ksamZ'] if atfront else cfg_tomo['back_white_ksamZ'] yield from bps.mv(tomostage.ksamX, _x) yield from bps.mv(tomostage.ksamZ, _z) # setup detector yield from bps.mv(det.hdf1.nd_array_port, 'PROC1') yield from bps.mv(det.tiff1.nd_array_port, 'PROC1') yield from bps.mv(det.proc1.enable, 1) yield from bps.mv(det.proc1.reset_filter, 1) yield from bps.mv(det.proc1.num_filter, cfg_tomo['n_frames']) yield from bps.mv(det.cam.trigger_mode, "Internal") yield from bps.mv(det.cam.image_mode, "Multiple") yield from bps.mv(det.cam.num_images, cfg_tomo['n_frames']*cfg_tomo['n_white']) yield from bps.trigger_and_read([det]) # move sample back to FOV # NOTE: # not sure is this will work or not... yield from bps.mv(tomostage.ksamX, cfg_tomo['initial_ksamX']) yield from bps.mv(tomostage.ksamZ, cfg_tomo['initial_ksamZ']) #@bpp.run_decorator() def collect_dark_field(experiment, cfg_tomo): """ Collect dark field images by close the shutter """ det = experiment.det yield from bps.mv(det.hdf1.nd_array_port, 'PROC1') yield from bps.mv(det.tiff1.nd_array_port, 'PROC1') yield from bps.mv(det.proc1.enable, 1) yield from bps.mv(det.proc1.reset_filter, 1) yield from bps.mv(det.proc1.num_filter, cfg_tomo['n_frames']) yield from bps.mv(det.cam.trigger_mode, "Internal") yield from bps.mv(det.cam.image_mode, "Multiple") yield from bps.mv(det.cam.num_images, cfg_tomo['n_frames']*cfg_tomo['n_dark']) yield from bps.trigger_and_read([det]) #@bpp.run_decorator() def step_scan(experiment, cfg_tomo): """ Collect projects with step motion """ # unpack devices det = experiment.det tomostage = experiment.tomostage yield from bps.mv(det.hdf1.nd_array_port, 'PROC1') yield from bps.mv(det.tiff1.nd_array_port, 'PROC1') yield from bps.mv(det.proc1.enable, 1) yield from bps.mv(det.proc1.reset_filter, 1) yield from bps.mv(det.proc1.num_filter, cfg_tomo['n_frames']) angs = np.arange( cfg_tomo['omega_start'], cfg_tomo['omega_end']+cfg_tomo['omega_step']/2, cfg_tomo['omega_step'], ) for ang in angs: yield from bps.checkpoint() yield from bps.mv(tomostage.preci, ang) yield from bps.trigger_and_read([det]) #@bpp.run_decorator() def fly_scan(experiment, cfg_tomo): """ Collect projections with fly motion """ det = experiment.det psofly = experiment.psofly yield from bps.mv(det.hdf1.nd_array_port, 'PG1') yield from bps.mv(det.tiff1.nd_array_port, 'PG1') # we are assuming that the global psofly is available yield from bps.mv( psofly.start, cfg_tomo['omega_start'], psofly.end, cfg_tomo['omega_end'], psofly.scan_delta, abs(cfg_tomo['omega_step']), psofly.slew_speed, cfg_tomo['slew_speed'], ) # taxi yield from bps.mv(psofly.taxi, "Taxi") yield from bps.mv( det.cam.num_images, cfg_tomo['n_projections'], det.cam.trigger_mode, "Overlapped", ) # start the fly scan yield from bps.trigger(det, group='fly') yield from bps.abs_set(psofly.fly, "Fly", group='fly') yield from bps.wait(group='fly') def tomo_scan(experiment, cfg): """ Tomography scan plan based on given configuration """ # unpack devices det = experiment.det tomostage = experiment.tomostage shutter = experiment.shutter shutter_suspender = experiment.suspend_shutter cfg = load_config(cfg) if type(cfg) != dict else cfg # update the cached motor position in the dict in case exp goes wrong _cahed_position = experiment.cache_motor_position() # step 0: preparation acquire_time = cfg['tomo']['acquire_time'] n_white = cfg['tomo']['n_white'] n_dark = cfg['tomo']['n_dark'] angs = np.arange( cfg['tomo']['omega_start'], cfg['tomo']['omega_end']+cfg['tomo']['omega_step']/2, cfg['tomo']['omega_step'], ) n_projections = len(angs) cfg['tomo']['n_projections'] = n_projections total_images = n_white + n_projections + n_white + n_dark fp = cfg['output']['filepath'] fn = cfg['output']['fileprefix'] # calculate slew speed for fly scan # https://github.com/decarlof/tomo2bm/blob/master/flir/libs/aps2bm_lib.py # TODO: considering blue pixels, use 2BM code as ref if cfg['tomo']['type'].lower() == 'fly': scan_time = (acquire_time+cfg['tomo']['readout_time'])*n_projections slew_speed = (angs.max() - angs.min())/scan_time cfg['tomo']['slew_speed'] = slew_speed # need to make sure that the sample out position is the same for both front and back x0, z0 = tomostage.ksamX.position, tomostage.ksamZ.position dfx, dfz = cfg['tomo']['sample_out_position']['samX'], cfg['tomo']['sample_out_position']['samZ'] rotang = np.radians(cfg['tomo']['omega_end']-cfg['tomo']['omega_start']) rotm = np.array([[ np.cos(rotang), np.sin(rotang)], [-np.sin(rotang), np.cos(rotang)]]) dbxz = np.dot(rotm, np.array([dfx, dfz])) dbx = dbxz[0] if abs(dbxz[0]) > 1e-8 else 0.0 dbz = dbxz[1] if abs(dbxz[1]) > 1e-8 else 0.0 # now put the value to dict cfg['tomo']['initial_ksamX'] = x0 cfg['tomo']['initial_ksamZ'] = z0 cfg['tomo']['fronte_white_ksamX'] = x0 + dfx cfg['tomo']['fronte_white_ksamZ'] = z0 + dfz cfg['tomo']['back_white_ksamX'] = x0 + dbx cfg['tomo']['back_white_ksamZ'] = z0 + dbz @bpp.run_decorator() @bpp.stage_decorator([det]) def scan_closure(): # open shutter for beam yield from bps.mv(shutter, 'open') yield from bps.install_suspender(shutter_suspender) # config output for me in [det.tiff1, det.hdf1]: yield from bps.mv(me.file_path, fp) yield from bps.mv(me.file_name, fn) yield from bps.mv(me.file_write_mode, 2) yield from bps.mv(me.num_capture, total_images) yield from bps.mv(me.file_template, ".".join([r"%s%s_%06d",cfg['output']['type'].lower()])) if cfg['output']['type'] in ['tif', 'tiff']: yield from bps.mv(det.tiff1.enable, 1) yield from bps.mv(det.tiff1.capture, 1) yield from bps.mv(det.hdf1.enable, 0) elif cfg['output']['type'] in ['hdf', 'hdf1', 'hdf5']: yield from bps.mv(det.tiff1.enable, 0) yield from bps.mv(det.hdf1.enable, 1) yield from bps.mv(det.hdf1.capture, 1) else: raise ValueError(f"Unsupported output type {cfg['output']['type']}") # collect front white field yield from bps.mv(det.cam.frame_type, 0) # for HDF5 dxchange data structure yield from collect_white_field(experiment, cfg['tomo'], atfront=True) # collect projections yield from bps.mv(det.cam.frame_type, 1) # for HDF5 dxchange data structure if cfg['tomo']['type'].lower() == 'step': yield from step_scan(experiment, cfg['tomo']) elif cfg['tomo']['type'].lower() == 'fly': yield from fly_scan(experiment, cfg['tomo']) else: raise ValueError(f"Unsupported scan type: {cfg['tomo']['type']}") # collect back white field yield from bps.mv(det.cam.frame_type, 2) # for HDF5 dxchange data structure yield from collect_white_field(experiment, cfg['tomo'], atfront=False) # collect back dark field yield from bps.mv(det.cam.frame_type, 3) # for HDF5 dxchange data structure yield from bps.remove_suspender(shutter_suspender) yield from bps.mv(shutter, "close") yield from collect_dark_field(experiment, cfg['tomo']) return (yield from scan_closure())
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from pymongo import * from flask import * from flask_restful import * import datetime mongodb_url = "mongodb://Ranuga:ranuga2008@cluster0-shard-00-00.6n3dg.mongodb.net:27017,cluster0-shard-00-01.6n3dg.mongodb.net:27017,cluster0-shard-00-02.6n3dg.mongodb.net:27017/myFirstDatabase?ssl=true&replicaSet=atlas-uo9rgq-shard-0&authSource=admin&retryWrites=true&w=majority" app = Flask(__name__) app.debug = True app.secret_key = "development" cluster = MongoClient(mongodb_url) from server.routes import *
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""" Classes for GP models with Stan that perform transfer optimization. """ from argparse import Namespace import numpy as np import copy from .gp_stan import StanGp from .regression.transfer_regression import TransferRegression from ..util.misc_util import dict_to_namespace class StanTransferGp(StanGp): """ GP model with transferred prior mean based on a regression model. """ def __init__(self, params=None, data=None, verbose=None): self.set_params(params) self.set_verbose(verbose) self.set_model(data) def set_params(self, params): """Set self.params, the parameters for this model.""" super().set_params(params) params = dict_to_namespace(params) assert hasattr(params, 'transfer_config') self.params.transfer_config = params.transfer_config def set_model(self, data): """Set GP Stan model and regression model.""" self.model = self.get_model() self.regressor = self.get_regressor(data) #self.regressor = self.get_proxy_regressor(data) # TODO def get_regressor(self, data): """Return transfer (prior mean) regressor.""" # Define regressor regressor = TransferRegression(self.params.transfer_config) if len(data.x) < 1: regressor = None else: mean_errors = [] # TODO: remove extra files such as .DS_STORE (or ignore files that break) for i, reg in enumerate(regressor.model_fnames): try: val_acc = regressor.evaluate_model(reg, data.x) error = np.mean((data.y - val_acc) ** 2) mean_errors.append((error, i)) except: print(f'Transfer model file in tarball did not load: {reg}') mean_errors.sort() if mean_errors[0][0] > self.params.transfer_config.get('metric_threshold', 0.6): regressor.set_best_model(-1) else: regressor.set_best_model(mean_errors[0][1]) return regressor def get_proxy_regressor(self, data): if not data: regressor = None else: def regressor(x): return np.linalg.norm(x) return regressor def transform_data_y(self): """Transform data.y using PriorMeanDataTransformer.""" self.dt = PriorMeanDataTransformer(self.data, self.regressor, False) y_trans = self.dt.transform_y_data() self.data = Namespace(x=self.data.x, y=y_trans) def gen_list(self, x_list, z, s, nsamp): """ Draw nsamp samples from generative process, given list of inputs x_list, posterior sample z, and seed s. Parameters ---------- x_list : list List of numpy ndarrays each with shape=(self.params.ndimx,) z : Namespace Namespace of GP hyperparameters. s : int The seed, a positive integer. nsamp : int The number of samples to draw from generative process. Returns ------- list A list with len=len(x_list) of numpy ndarrays, each with shape=(nsamp,). """ x_list = self.transform_xin_list(x_list) pred_list = self.sample_gp_pred(nsamp, x_list) pred_list = [ self.dt.inv_transform_y_data(pr, x) for pr, x in zip(pred_list, x_list) ] return pred_list def postgen_list(self, x_list, s, nsamp): """ Draw nsamp samples from posterior predictive distribution, given list of inputs x_list and seed s. Parameters ---------- x_list : list List of numpy ndarrays each with shape=(self.params.ndimx,). s : int The seed, a positive integer. nsamp : int The number of samples to draw from the posterior predictive distribution. Returns ------- list A list with len=len(x_list) of numpy ndarrays, each with shape=(nsamp,). """ x_list = self.transform_xin_list(x_list) pred_list = self.sample_gp_post_pred( nsamp, x_list, full_cov=True, nloop=np.min([50, nsamp]) ) pred_list = [ self.dt.inv_transform_y_data(pr, x) for pr, x in zip(pred_list, x_list) ] return pred_list def __str__(self): return f'StanTransferGp with params={self.params}' class PriorMeanDataTransformer: """ A class to transform (and inverse transform) data, based on a prior mean regression. """ def __init__(self, data, prior_mean_f, verbose=True): """ Parameters ---------- data : Namespace Namespace containing data. prior_mean_f : function Prior mean function. verbose : bool If True, print description string. """ self._set_data(data) self._set_prior_mean_f(prior_mean_f) self._set_verbose(verbose) def _set_data(self, data): """Set self.data""" self.data = data def _set_prior_mean_f(self, prior_mean_f): """Set self.prior_mean_f.""" if prior_mean_f is None: # Default prior mean function is constant 0 function def prior_mean_f(x): return 0. self.prior_mean_f = prior_mean_f def _set_verbose(self, verbose): """Set verbose options.""" self.verbose = verbose if self.verbose: self._print_str() def transform_y_data(self, y_data=None, x_data=None): """Transform and return self.data.y""" # Transform self.data.y into new list y_trans = [y - self.prior_mean_f(x) for x, y in zip(self.data.x, self.data.y)] return y_trans def inv_transform_y_data(self, y_arr, x_single_arr): """Return inverse transform of y_arr.""" # Compute prior mean val for the single input prior_mean_val = self.prior_mean_f(x_single_arr) # Inverse transform y_arr into list y_inv_trans_list = [y + prior_mean_val for y in list(y_arr)] # Transform back to array and return y_inv_trans = np.array(y_inv_trans_list).reshape(-1) return y_inv_trans def _print_str(self): """Print a description string.""" print('*PriorMeanDataTransformer')
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# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union from ... import _utilities, _tables from . import outputs __all__ = [ 'GetManagementLockAtResourceLevelResult', 'AwaitableGetManagementLockAtResourceLevelResult', 'get_management_lock_at_resource_level', ] warnings.warn("""The 'latest' version is deprecated. Please migrate to the function in the top-level module: 'azure-native:authorization:getManagementLockAtResourceLevel'.""", DeprecationWarning) @pulumi.output_type class GetManagementLockAtResourceLevelResult: """ The lock information. """ def __init__(__self__, id=None, level=None, name=None, notes=None, owners=None, type=None): if id and not isinstance(id, str): raise TypeError("Expected argument 'id' to be a str") pulumi.set(__self__, "id", id) if level and not isinstance(level, str): raise TypeError("Expected argument 'level' to be a str") pulumi.set(__self__, "level", level) if name and not isinstance(name, str): raise TypeError("Expected argument 'name' to be a str") pulumi.set(__self__, "name", name) if notes and not isinstance(notes, str): raise TypeError("Expected argument 'notes' to be a str") pulumi.set(__self__, "notes", notes) if owners and not isinstance(owners, list): raise TypeError("Expected argument 'owners' to be a list") pulumi.set(__self__, "owners", owners) if type and not isinstance(type, str): raise TypeError("Expected argument 'type' to be a str") pulumi.set(__self__, "type", type) @property @pulumi.getter def id(self) -> str: """ The resource ID of the lock. """ return pulumi.get(self, "id") @property @pulumi.getter def level(self) -> str: """ The level of the lock. Possible values are: NotSpecified, CanNotDelete, ReadOnly. CanNotDelete means authorized users are able to read and modify the resources, but not delete. ReadOnly means authorized users can only read from a resource, but they can't modify or delete it. """ return pulumi.get(self, "level") @property @pulumi.getter def name(self) -> str: """ The name of the lock. """ return pulumi.get(self, "name") @property @pulumi.getter def notes(self) -> Optional[str]: """ Notes about the lock. Maximum of 512 characters. """ return pulumi.get(self, "notes") @property @pulumi.getter def owners(self) -> Optional[Sequence['outputs.ManagementLockOwnerResponse']]: """ The owners of the lock. """ return pulumi.get(self, "owners") @property @pulumi.getter def type(self) -> str: """ The resource type of the lock - Microsoft.Authorization/locks. """ return pulumi.get(self, "type") class AwaitableGetManagementLockAtResourceLevelResult(GetManagementLockAtResourceLevelResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetManagementLockAtResourceLevelResult( id=self.id, level=self.level, name=self.name, notes=self.notes, owners=self.owners, type=self.type) def get_management_lock_at_resource_level(lock_name: Optional[str] = None, parent_resource_path: Optional[str] = None, resource_group_name: Optional[str] = None, resource_name: Optional[str] = None, resource_provider_namespace: Optional[str] = None, resource_type: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetManagementLockAtResourceLevelResult: """ The lock information. Latest API Version: 2016-09-01. :param str lock_name: The name of lock. :param str parent_resource_path: An extra path parameter needed in some services, like SQL Databases. :param str resource_group_name: The name of the resource group. :param str resource_name: The name of the resource. :param str resource_provider_namespace: The namespace of the resource provider. :param str resource_type: The type of the resource. """ pulumi.log.warn("""get_management_lock_at_resource_level is deprecated: The 'latest' version is deprecated. Please migrate to the function in the top-level module: 'azure-native:authorization:getManagementLockAtResourceLevel'.""") __args__ = dict() __args__['lockName'] = lock_name __args__['parentResourcePath'] = parent_resource_path __args__['resourceGroupName'] = resource_group_name __args__['resourceName'] = resource_name __args__['resourceProviderNamespace'] = resource_provider_namespace __args__['resourceType'] = resource_type if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-native:authorization/latest:getManagementLockAtResourceLevel', __args__, opts=opts, typ=GetManagementLockAtResourceLevelResult).value return AwaitableGetManagementLockAtResourceLevelResult( id=__ret__.id, level=__ret__.level, name=__ret__.name, notes=__ret__.notes, owners=__ret__.owners, type=__ret__.type)
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import numpy as np import torch import torch.nn as nn import torch.nn.functional as F from mvn.utils.img import to_numpy, to_torch from mvn.utils import multiview def integrate_tensor_2d(heatmaps, softmax=True): """Applies softmax to heatmaps and integrates them to get their's "center of masses" Args: heatmaps torch tensor of shape (batch_size, n_heatmaps, h, w): input heatmaps Returns: coordinates torch tensor of shape (batch_size, n_heatmaps, 2): coordinates of center of masses of all heatmaps """ batch_size, n_heatmaps, h, w = heatmaps.shape heatmaps = heatmaps.reshape((batch_size, n_heatmaps, -1)) if softmax: heatmaps = nn.functional.softmax(heatmaps, dim=2) else: heatmaps = nn.functional.relu(heatmaps) heatmaps = heatmaps.reshape((batch_size, n_heatmaps, h, w)) mass_x = heatmaps.sum(dim=2) mass_y = heatmaps.sum(dim=3) mass_times_coord_x = mass_x * torch.arange(w).type(torch.float).to(mass_x.device) mass_times_coord_y = mass_y * torch.arange(h).type(torch.float).to(mass_y.device) x = mass_times_coord_x.sum(dim=2, keepdim=True) y = mass_times_coord_y.sum(dim=2, keepdim=True) if not softmax: x = x / mass_x.sum(dim=2, keepdim=True) y = y / mass_y.sum(dim=2, keepdim=True) coordinates = torch.cat((x, y), dim=2) coordinates = coordinates.reshape((batch_size, n_heatmaps, 2)) return coordinates def integrate_tensor_3d(volumes, softmax=True): batch_size, n_volumes, x_size, y_size, z_size = volumes.shape volumes = volumes.reshape((batch_size, n_volumes, -1)) if softmax: volumes = nn.functional.softmax(volumes, dim=2) else: volumes = nn.functional.relu(volumes) volumes = volumes.reshape((batch_size, n_volumes, x_size, y_size, z_size)) mass_x = volumes.sum(dim=3).sum(dim=3) mass_y = volumes.sum(dim=2).sum(dim=3) mass_z = volumes.sum(dim=2).sum(dim=2) mass_times_coord_x = mass_x * torch.arange(x_size).type(torch.float).to(mass_x.device) mass_times_coord_y = mass_y * torch.arange(y_size).type(torch.float).to(mass_y.device) mass_times_coord_z = mass_z * torch.arange(z_size).type(torch.float).to(mass_z.device) x = mass_times_coord_x.sum(dim=2, keepdim=True) y = mass_times_coord_y.sum(dim=2, keepdim=True) z = mass_times_coord_z.sum(dim=2, keepdim=True) if not softmax: x = x / mass_x.sum(dim=2, keepdim=True) y = y / mass_y.sum(dim=2, keepdim=True) z = z / mass_z.sum(dim=2, keepdim=True) coordinates = torch.cat((x, y, z), dim=2) coordinates = coordinates.reshape((batch_size, n_volumes, 3)) return coordinates, volumes def integrate_tensor_3d_with_coordinates(volumes, coord_volumes, softmax=True): batch_size, n_volumes, x_size, y_size, z_size = volumes.shape volumes = volumes.reshape((batch_size, n_volumes, -1)) if softmax: volumes = nn.functional.softmax(volumes, dim=2) else: volumes = nn.functional.relu(volumes) volumes = volumes.reshape((batch_size, n_volumes, x_size, y_size, z_size)) coordinates = torch.einsum("bnxyz, bxyzc -> bnc", volumes, coord_volumes) return coordinates #, volumes def unproject_heatmaps(heatmaps, proj_matricies, coord_volumes, volume_aggregation_method='sum', vol_confidences=None): device = heatmaps.device batch_size, n_views, n_joints, heatmap_shape = heatmaps.shape[0], heatmaps.shape[1], heatmaps.shape[2], tuple(heatmaps.shape[3:]) # 1,4,32,96x96 volume_shape = coord_volumes.shape[1:4] #64x64x64 volume_batch = torch.zeros(batch_size, n_joints, *volume_shape, device=device) # 1x32x64x64x64のTensor # TODO: speed up this this loop for batch_i in range(batch_size): coord_volume = coord_volumes[batch_i] # Bx64x64x64x3 -> 64x64x64x3 grid_coord = coord_volume.reshape((-1, 3)) # 262144x3 volume_batch_to_aggregate = torch.zeros(n_views, n_joints, *volume_shape, device=device) # 4x32x64x64x64 for view_i in range(n_views): heatmap = heatmaps[batch_i, view_i] # 1x4x32x96x96 -> 32x96x96 heatmap = heatmap.unsqueeze(0) # 1x32x96x96 (一番初めに次元を追加) grid_coord_proj = multiview.project_3d_points_to_image_plane_without_distortion( # 262144x3 proj_matricies[batch_i, view_i], grid_coord, convert_back_to_euclidean=False ) invalid_mask = grid_coord_proj[:, 2] <= 0.0 # depth must be larger than 0.0 #人がカメラに近づきすぎた場合に起こる?? grid_coord_proj[grid_coord_proj[:, 2] == 0.0, 2] = 1.0 # not to divide by zero grid_coord_proj = multiview.homogeneous_to_euclidean(grid_coord_proj) # transform to [-1.0, 1.0] range grid_coord_proj_transformed = torch.zeros_like(grid_coord_proj) # 262144x2 grid_coord_proj_transformed[:, 0] = 2 * (grid_coord_proj[:, 0] / heatmap_shape[0] - 0.5) # (0,0)->(96,96)の座標を、中心を(0,0)、左上を(-1,-1)、右下を(1,1)とする相対的な座標に変換 grid_coord_proj_transformed[:, 1] = 2 * (grid_coord_proj[:, 1] / heatmap_shape[1] - 0.5) grid_coord_proj = grid_coord_proj_transformed # prepare to F.grid_sample grid_coord_proj = grid_coord_proj.unsqueeze(1).unsqueeze(0) # 引数で指定された場所に一つ次元を足すらしい 1x262144x1x2。heatmapが1x32x96x96 try: current_volume = F.grid_sample(heatmap, grid_coord_proj, align_corners=True) # 1x32x262144x1 = Heatmap(1x32x96x96), grid_coord_proj(1x262144x1x2) except TypeError: # old PyTorch current_volume = F.grid_sample(heatmap, grid_coord_proj) # zero out non-valid points current_volume = current_volume.view(n_joints, -1) #32x262144 current_volume[:, invalid_mask] = 0.0 # reshape back to volume current_volume = current_volume.view(n_joints, *volume_shape) #32x64x64x64 # collect volume_batch_to_aggregate[view_i] = current_volume # agregate resulting volume if volume_aggregation_method.startswith('conf'): volume_batch[batch_i] = (volume_batch_to_aggregate * vol_confidences[batch_i].view(n_views, n_joints, 1, 1, 1)).sum(0) elif volume_aggregation_method == 'sum': volume_batch[batch_i] = volume_batch_to_aggregate.sum(0) elif volume_aggregation_method == 'max': volume_batch[batch_i] = volume_batch_to_aggregate.max(0)[0] elif volume_aggregation_method == 'softmax': volume_batch_to_aggregate_softmin = volume_batch_to_aggregate.clone() # 2x32x64x64x64(n_views, n_joints, *volume_shape) volume_batch_to_aggregate_softmin = volume_batch_to_aggregate_softmin.view(n_views, -1) # reshape volume_batch_to_aggregate_softmin = nn.functional.softmax(volume_batch_to_aggregate_softmin, dim=0) volume_batch_to_aggregate_softmin = volume_batch_to_aggregate_softmin.view(n_views, n_joints, *volume_shape) #reshape back volume_batch[batch_i] = (volume_batch_to_aggregate * volume_batch_to_aggregate_softmin).sum(0) else: raise ValueError("Unknown volume_aggregation_method: {}".format(volume_aggregation_method)) return volume_batch def gaussian_2d_pdf(coords, means, sigmas, normalize=True): normalization = 1.0 if normalize: normalization = (2 * np.pi * sigmas[:, 0] * sigmas[:, 0]) exp = torch.exp(-((coords[:, 0] - means[:, 0]) ** 2 / sigmas[:, 0] ** 2 + (coords[:, 1] - means[:, 1]) ** 2 / sigmas[:, 1] ** 2) / 2) return exp / normalization def render_points_as_2d_gaussians(points, sigmas, image_shape, normalize=True): device = points.device n_points = points.shape[0] yy, xx = torch.meshgrid(torch.arange(image_shape[0]).to(device), torch.arange(image_shape[1]).to(device)) grid = torch.stack([xx, yy], dim=-1).type(torch.float32) grid = grid.unsqueeze(0).repeat(n_points, 1, 1, 1) # (n_points, h, w, 2) grid = grid.reshape((-1, 2)) points = points.unsqueeze(1).unsqueeze(1).repeat(1, image_shape[0], image_shape[1], 1) points = points.reshape(-1, 2) sigmas = sigmas.unsqueeze(1).unsqueeze(1).repeat(1, image_shape[0], image_shape[1], 1) sigmas = sigmas.reshape(-1, 2) images = gaussian_2d_pdf(grid, points, sigmas, normalize=normalize) images = images.reshape(n_points, *image_shape) return images
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from calendar import timegm from datetime import date, datetime, time import sqlite3 from typing import Callable import julian # type: ignore def store_time(time_type: str, time_format: str = "") -> None: if time_type == "seconds": sqlite3.register_adapter(time, time_to_seconds) elif time_type == "text": sqlite3.register_adapter(time, time_to_text(time_format)) else: raise ValueError(f"Unknown time adapter: '{time_type}'") def store_date(date_type: str, date_format: str = "") -> None: if date_type == "julian": sqlite3.register_adapter(date, date_to_julian) elif date_type == "posix": sqlite3.register_adapter(date, date_to_posix) elif date_type == "text": sqlite3.register_adapter(date, date_to_text(date_format)) else: raise ValueError(f"Unknown date adapter: '{date_type}'") def store_datetime(datetime_type: str, datetime_format: str = "") -> None: if datetime_type == "julian": sqlite3.register_adapter(datetime, datetime_to_julian) elif datetime_type == "posix": sqlite3.register_adapter(datetime, datetime_to_posix) elif datetime_type == "text": sqlite3.register_adapter(datetime, datetime_to_text(datetime_format)) else: raise ValueError(f"Unknown datetime adapter: '{datetime_type}'") def time_to_seconds(t: time) -> float: return (60 * 60 * t.hour) + (60 * t.minute) + t.second + t.microsecond def time_to_text(format: str) -> Callable[[time], str]: def _time_to_text(t: time) -> str: return t.strftime(format) return _time_to_text def date_to_posix(d: date) -> int: return datetime_to_posix(datetime(d.year, d.month, d.day)) def date_to_julian(d: date) -> float: return datetime_to_julian(datetime(d.year, d.month, d.day)) def date_to_text(format: str) -> Callable[[date], str]: def _date_to_text(d: date) -> str: return d.strftime(format) return _date_to_text def datetime_to_posix(dt: datetime) -> int: return timegm(dt.utctimetuple()) def datetime_to_julian(dt: datetime) -> float: return float(julian.to_jd(dt)) def datetime_to_text(format: str) -> Callable[[datetime], str]: def _datetime_to_text(dt: datetime) -> str: return dt.strftime(format) return _datetime_to_text
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import click import logging from .constants import WELCOME_TEXT from .api import run_server from .logger import OrigamiLogger logger = OrigamiLogger( file_log_level=logging.DEBUG, console_log_level=logging.DEBUG) @click.group(invoke_without_command=True) @click.pass_context def main(ctx): """ Origami daemon is an application which deploys and manages demos on CloudCV servers. """ if not ctx.invoked_subcommand: click.echo(WELCOME_TEXT) main.add_command(run_server)
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from __future__ import annotations import itertools import math from dataclasses import dataclass from typing import Any @dataclass class TreeZipper: inner: Any path: list[int] def up(self): if self.path: return TreeZipper(self.inner, self.path[:-1]), self.path[-1] return None def get(self): v = self.inner for p in self.path: v = v[p] return v def set(self, x): v = self.inner for p in self.path[:-1]: v = v[p] v[self.path[-1]] = x def try_left(self): v = self.get() if isinstance(v, list): return TreeZipper(self.inner, self.path + [0]) return None def try_right(self): v = self.get() if isinstance(v, list): return TreeZipper(self.inner, self.path + [1]) return None class Whoop(Exception): pass def do_reduce_exp(v: TreeZipper, depth): if depth == 4 and isinstance(v.get(), list): # print("exploding") l, r = v.get() v.set(0) l_v = v came_from_left = False dont_go = False while True: # print("left", l_v, l_v.get()) if (l_v_n := l_v.try_left()) != None and not came_from_left: l_v = l_v_n break elif (l_v_n_v := l_v.up()) != None: # if we can up and didn't go left, do so l_v = l_v_n_v[0] came_from_left = l_v_n_v[1] == 0 else: dont_go = True # if we did nothing, we have to have reached the top and we were already from the left break if not dont_go: while True: if (l_v_n := l_v.try_right()) != None: l_v = l_v_n # try to go down and to the left if isinstance(l_v.get(), int): # if it's an int, add and quit l_v.set(l_v.get() + l) break l_v = v came_from_right = False dont_go = False while True: # print("right", l_v, l_v.get()) if (l_v_n := l_v.try_right()) != None and not came_from_right: l_v = l_v_n break elif (l_v_n_v := l_v.up()) != None: # if we can up and didn't go left, do so l_v = l_v_n_v[0] came_from_right = l_v_n_v[1] == 1 else: # if we did nothing, we have to have reached the top, bail dont_go = True break if not dont_go: while True: if (l_v_n := l_v.try_left()) != None: l_v = l_v_n # try to go down and to the left if isinstance(l_v.get(), int): # if it's an int, add and quit l_v.set(l_v.get() + r) break raise Whoop() if (l_v := v.try_left()) != None: do_reduce_exp(l_v, depth + 1) if (r_v := v.try_right()) != None: do_reduce_exp(r_v, depth + 1) def do_reduce_splt(v: TreeZipper): n_v = v.get() if isinstance(n_v, int): if n_v >= 10: # print("splitting") l_v = math.floor(n_v / 2) r_v = math.ceil(n_v / 2) v.set([l_v, r_v]) raise Whoop() # otherwise, go and reduce both sides if (l_v := v.try_left()) != None: do_reduce_splt(l_v) if (r_v := v.try_right()) != None: do_reduce_splt(r_v) def iter_red(l): # print("doing", l) while True: t = TreeZipper(l, []) try: # print(l) do_reduce_exp(t, 0) do_reduce_splt(t) except Whoop: pass else: print("did nothing") return def do_mag(v: TreeZipper): if isinstance(v.get(), int): return v.get() return 3 * do_mag(v.try_left()) + 2 * do_mag(v.try_right()) inp = [ [[[[7,1],[0,0]],[6,[8,2]]],[8,[3,8]]], [[[3,6],[9,4]],[[[5,9],5],[8,0]]], [[[2,2],2],[1,[[1,6],7]]], [[[[0,9],7],[[3,2],8]],[6,[7,9]]], [[[[4,1],6],[[7,6],[2,2]]],[[[1,1],9],4]], [[[8,[3,7]],3],[[4,4],[[9,1],[3,5]]]], [[4,[8,2]],[1,[0,5]]], [8,[8,7]], [[[[2,2],7],[3,[4,5]]],[[4,6],[[2,5],4]]], [[[5,5],[[5,1],3]],[[2,[8,2]],[[6,9],[1,5]]]], [0,7], [[[[5,1],3],[8,[5,3]]],7], [[5,[2,[0,6]]],[[[5,5],2],[9,[8,0]]]], [[[[3,4],2],0],4], [[[[5,3],[2,7]],6],[[4,0],[9,[7,2]]]], [[[3,[2,5]],[3,3]],7], [[[[5,1],1],[4,8]],[[5,[8,3]],2]], [[4,[[8,1],[8,5]]],[[[4,1],0],6]], [[[5,5],[5,9]],[0,[[6,8],[0,1]]]], [4,[[[7,9],4],0]], [[[[0,1],7],[[3,6],5]],[8,[5,[6,1]]]], [[[7,7],[8,0]],[6,[8,[7,9]]]], [[[9,2],1],6], [[[4,4],[2,[5,0]]],[[[2,6],6],[5,[4,3]]]], [[2,[[4,7],5]],1], [[8,7],[[[2,0],7],[1,[0,3]]]], [[9,[[9,3],[9,5]]],[[8,7],[[4,1],[6,5]]]], [[3,4],[[9,4],5]], [[5,[[8,3],5]],1], [[0,[[9,0],[3,2]]],[2,[7,[5,1]]]], [[9,[[9,5],[8,6]]],[[4,4],[[3,8],[1,6]]]], [[[1,[5,2]],9],[[4,6],[3,[8,0]]]], [[1,7],[[1,7],9]], [[[[3,4],3],[[7,5],[9,1]]],[[[5,0],[3,0]],[[7,9],6]]], [[[7,2],[[1,0],[5,6]]],[[[3,7],[8,9]],6]], [[[[1,1],1],[[8,6],[9,8]]],[[[1,8],4],[8,9]]], [[[8,9],0],3], [[[1,7],[1,[3,9]]],[6,[0,[8,5]]]], [[0,5],[6,5]], [[[[6,8],[4,5]],[[7,4],6]],[[3,6],5]], [[8,[[0,9],8]],[9,[7,[7,9]]]], [0,[[[7,1],2],[[0,4],4]]], [[0,[[9,1],5]],[1,4]], [3,4], [[[9,3],[1,3]],[[[4,8],3],[[1,3],[9,0]]]], [[[[5,1],7],[[9,2],8]],[[[6,8],[5,4]],[0,1]]], [8,[[1,[3,0]],[[7,9],4]]], [[[6,4],[[2,9],[9,0]]],[7,[[0,0],3]]], [[3,[[9,6],6]],2], [[5,[[3,1],[7,5]]],[[[6,7],9],[[4,6],[5,2]]]], [[[4,[6,5]],8],[[6,[8,0]],[[9,3],3]]], [[[[4,9],[2,8]],9],[[[5,0],0],[[3,4],[2,8]]]], [[3,[7,1]],[9,[[1,8],7]]], [[9,1],[0,[[0,7],[7,1]]]], [[7,[0,[7,6]]],[[[5,3],1],[6,[4,5]]]], [8,[[[2,1],[6,9]],[[3,3],[4,6]]]], [0,[7,[3,0]]], [[[[1,6],3],[5,[8,0]]],[[[6,6],7],1]], [[[7,[8,3]],3],[[[2,8],5],[0,[9,5]]]], [[[[5,1],4],[[1,2],1]],7], [[[3,[7,5]],7],3], [[9,[6,[1,1]]],[[[4,1],[2,2]],[[9,5],[7,7]]]], [2,7], [[[9,[8,6]],[[9,0],[6,5]]],[[[6,7],5],[[7,7],[2,3]]]], [[[0,[6,4]],2],[4,[7,[7,5]]]], [[[[6,1],[9,1]],[[6,1],9]],[[2,6],0]], [[0,[[1,8],[3,5]]],[4,[[8,2],[4,2]]]], [[[[9,3],[4,2]],2],[[[2,1],[7,1]],[4,8]]], [[[3,[0,2]],3],8], [[[4,[4,9]],9],[[[4,4],5],9]], [[[[8,2],7],9],[[[1,0],[3,8]],[[7,7],0]]], [[[3,2],[9,7]],[[9,[8,2]],[[5,5],3]]], [[[7,[3,1]],[[8,3],1]],[[[8,6],[7,0]],4]], [[9,[[9,1],5]],[[4,[1,1]],2]], [[[[7,4],[0,3]],7],[8,[6,[3,3]]]], [5,5], [[6,7],[1,[7,[8,1]]]], [[1,[0,4]],7], [[[4,0],[[0,1],[2,2]]],[9,[[9,9],[3,0]]]], [[[6,0],[[8,6],3]],[[5,1],[[8,1],[2,7]]]], [[[[8,3],7],5],[9,[[5,1],8]]], [[[[4,0],[5,2]],[[0,0],7]],2], [[[[0,1],6],2],[[8,2],6]], [[[[2,4],1],[[6,7],9]],[[[1,6],9],3]], [[5,5],[[8,[7,7]],[5,8]]], [[6,[[9,2],[9,7]]],[[[8,5],[4,4]],7]], [[[9,[7,7]],[6,0]],[7,[[8,7],[1,2]]]], [[7,[6,2]],[[9,[5,2]],[1,4]]], [[[7,[5,9]],[[3,9],[4,5]]],[0,6]], [[9,[8,[2,2]]],[[9,7],[1,1]]], [[[[2,3],4],[[4,8],9]],[[9,[8,6]],[[0,9],0]]], [[0,[[9,3],0]],[8,8]], [[[[2,9],6],[[2,8],9]],[[[0,5],6],[[6,1],7]]], [[9,[[8,3],[5,8]]],[[7,[3,0]],3]], [[[4,[4,2]],0],1], [[[[9,6],[5,8]],[6,2]],[[[8,0],[7,0]],[[5,6],4]]], [[[8,0],[[4,3],[7,4]]],[[3,[7,9]],[[7,3],6]]], [[3,[5,[0,3]]],[5,4]], [[[[1,2],[6,3]],1],[[7,[5,2]],[[8,8],7]]], [[4,[[8,0],[7,1]]],[[8,[8,0]],[[1,5],3]]] ] inp = [ [[[0,[5,8]],[[1,7],[9,6]]],[[4,[1,2]],[[1,4],2]]], [[[5,[2,8]],4],[5,[[9,9],0]]], [6,[[[6,2],[5,6]],[[7,6],[4,7]]]], [[[6,[0,7]],[0,9]],[4,[9,[9,0]]]], [[[7,[6,4]],[3,[1,3]]],[[[5,5],1],9]], [[6,[[7,3],[3,2]]],[[[3,8],[5,7]],4]], [[[[5,4],[7,7]],8],[[8,3],8]], [[9,3],[[9,9],[6,[4,9]]]], [[2,[[7,7],7]],[[5,8],[[9,3],[0,2]]]], [[[[5,2],5],[8,[3,7]]],[[5,[7,5]],[4,4]]] ] # inp = [ # [[[[[7,0],[7,7]],[[7,7],[7,8]]],[[[7,7],[8,8]],[[7,7],[8,7]]]],[7,[5,[[3,8],[1,4]]]]] # ] def do_add(l): it = iter(l) x = next(it) iter_red(x) for y in it: x = [x, y] iter_red(x) return x out = do_add(inp) print(out) print(do_mag(TreeZipper(out, []))) import copy inp = [ [[[[7,1],[0,0]],[6,[8,2]]],[8,[3,8]]], [[[3,6],[9,4]],[[[5,9],5],[8,0]]], [[[2,2],2],[1,[[1,6],7]]], [[[[0,9],7],[[3,2],8]],[6,[7,9]]], [[[[4,1],6],[[7,6],[2,2]]],[[[1,1],9],4]], [[[8,[3,7]],3],[[4,4],[[9,1],[3,5]]]], [[4,[8,2]],[1,[0,5]]], [8,[8,7]], [[[[2,2],7],[3,[4,5]]],[[4,6],[[2,5],4]]], [[[5,5],[[5,1],3]],[[2,[8,2]],[[6,9],[1,5]]]], [0,7], [[[[5,1],3],[8,[5,3]]],7], [[5,[2,[0,6]]],[[[5,5],2],[9,[8,0]]]], [[[[3,4],2],0],4], [[[[5,3],[2,7]],6],[[4,0],[9,[7,2]]]], [[[3,[2,5]],[3,3]],7], [[[[5,1],1],[4,8]],[[5,[8,3]],2]], [[4,[[8,1],[8,5]]],[[[4,1],0],6]], [[[5,5],[5,9]],[0,[[6,8],[0,1]]]], [4,[[[7,9],4],0]], [[[[0,1],7],[[3,6],5]],[8,[5,[6,1]]]], [[[7,7],[8,0]],[6,[8,[7,9]]]], [[[9,2],1],6], [[[4,4],[2,[5,0]]],[[[2,6],6],[5,[4,3]]]], [[2,[[4,7],5]],1], [[8,7],[[[2,0],7],[1,[0,3]]]], [[9,[[9,3],[9,5]]],[[8,7],[[4,1],[6,5]]]], [[3,4],[[9,4],5]], [[5,[[8,3],5]],1], [[0,[[9,0],[3,2]]],[2,[7,[5,1]]]], [[9,[[9,5],[8,6]]],[[4,4],[[3,8],[1,6]]]], [[[1,[5,2]],9],[[4,6],[3,[8,0]]]], [[1,7],[[1,7],9]], [[[[3,4],3],[[7,5],[9,1]]],[[[5,0],[3,0]],[[7,9],6]]], [[[7,2],[[1,0],[5,6]]],[[[3,7],[8,9]],6]], [[[[1,1],1],[[8,6],[9,8]]],[[[1,8],4],[8,9]]], [[[8,9],0],3], [[[1,7],[1,[3,9]]],[6,[0,[8,5]]]], [[0,5],[6,5]], [[[[6,8],[4,5]],[[7,4],6]],[[3,6],5]], [[8,[[0,9],8]],[9,[7,[7,9]]]], [0,[[[7,1],2],[[0,4],4]]], [[0,[[9,1],5]],[1,4]], [3,4], [[[9,3],[1,3]],[[[4,8],3],[[1,3],[9,0]]]], [[[[5,1],7],[[9,2],8]],[[[6,8],[5,4]],[0,1]]], [8,[[1,[3,0]],[[7,9],4]]], [[[6,4],[[2,9],[9,0]]],[7,[[0,0],3]]], [[3,[[9,6],6]],2], [[5,[[3,1],[7,5]]],[[[6,7],9],[[4,6],[5,2]]]], [[[4,[6,5]],8],[[6,[8,0]],[[9,3],3]]], [[[[4,9],[2,8]],9],[[[5,0],0],[[3,4],[2,8]]]], [[3,[7,1]],[9,[[1,8],7]]], [[9,1],[0,[[0,7],[7,1]]]], [[7,[0,[7,6]]],[[[5,3],1],[6,[4,5]]]], [8,[[[2,1],[6,9]],[[3,3],[4,6]]]], [0,[7,[3,0]]], [[[[1,6],3],[5,[8,0]]],[[[6,6],7],1]], [[[7,[8,3]],3],[[[2,8],5],[0,[9,5]]]], [[[[5,1],4],[[1,2],1]],7], [[[3,[7,5]],7],3], [[9,[6,[1,1]]],[[[4,1],[2,2]],[[9,5],[7,7]]]], [2,7], [[[9,[8,6]],[[9,0],[6,5]]],[[[6,7],5],[[7,7],[2,3]]]], [[[0,[6,4]],2],[4,[7,[7,5]]]], [[[[6,1],[9,1]],[[6,1],9]],[[2,6],0]], [[0,[[1,8],[3,5]]],[4,[[8,2],[4,2]]]], [[[[9,3],[4,2]],2],[[[2,1],[7,1]],[4,8]]], [[[3,[0,2]],3],8], [[[4,[4,9]],9],[[[4,4],5],9]], [[[[8,2],7],9],[[[1,0],[3,8]],[[7,7],0]]], [[[3,2],[9,7]],[[9,[8,2]],[[5,5],3]]], [[[7,[3,1]],[[8,3],1]],[[[8,6],[7,0]],4]], [[9,[[9,1],5]],[[4,[1,1]],2]], [[[[7,4],[0,3]],7],[8,[6,[3,3]]]], [5,5], [[6,7],[1,[7,[8,1]]]], [[1,[0,4]],7], [[[4,0],[[0,1],[2,2]]],[9,[[9,9],[3,0]]]], [[[6,0],[[8,6],3]],[[5,1],[[8,1],[2,7]]]], [[[[8,3],7],5],[9,[[5,1],8]]], [[[[4,0],[5,2]],[[0,0],7]],2], [[[[0,1],6],2],[[8,2],6]], [[[[2,4],1],[[6,7],9]],[[[1,6],9],3]], [[5,5],[[8,[7,7]],[5,8]]], [[6,[[9,2],[9,7]]],[[[8,5],[4,4]],7]], [[[9,[7,7]],[6,0]],[7,[[8,7],[1,2]]]], [[7,[6,2]],[[9,[5,2]],[1,4]]], [[[7,[5,9]],[[3,9],[4,5]]],[0,6]], [[9,[8,[2,2]]],[[9,7],[1,1]]], [[[[2,3],4],[[4,8],9]],[[9,[8,6]],[[0,9],0]]], [[0,[[9,3],0]],[8,8]], [[[[2,9],6],[[2,8],9]],[[[0,5],6],[[6,1],7]]], [[9,[[8,3],[5,8]]],[[7,[3,0]],3]], [[[4,[4,2]],0],1], [[[[9,6],[5,8]],[6,2]],[[[8,0],[7,0]],[[5,6],4]]], [[[8,0],[[4,3],[7,4]]],[[3,[7,9]],[[7,3],6]]], [[3,[5,[0,3]]],[5,4]], [[[[1,2],[6,3]],1],[[7,[5,2]],[[8,8],7]]], [[4,[[8,0],[7,1]]],[[8,[8,0]],[[1,5],3]]] ] m_v = 0 for l, r in itertools.permutations(inp, 2): l = copy.deepcopy(l) r = copy.deepcopy(r) v = [l, r] print(f"{l=} {r=}") do_add(v) m_v = max(do_mag(TreeZipper(v, [])), m_v) print(m_v)
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import json from unittest import TestCase from unittest.mock import Mock from utils import protocols from api.ontology import OntologyAPI from utils.protocols import ONTOLOGY_3PRIME_PARENT, ONTOLOGY_5PRIME_PARENT, ONTOLOGY_CITESEQ class TestProtocols(TestCase): def setUp(self) -> None: self.ontology_api = Mock() def test_is_10x__when_equal_3prime_parent__returns_true(self): # given lib_prep_protocol = { 'content': { 'library_construction_method': { 'ontology': ONTOLOGY_3PRIME_PARENT } } } # when is10x = protocols.is_10x(OntologyAPI(), lib_prep_protocol) # then self.assertTrue(is10x) def test_is_10x__when_equal_5prime_parent__returns_true(self): # given lib_prep_protocol = { 'content': { 'library_construction_method': { 'ontology': ONTOLOGY_5PRIME_PARENT } } } # when is10x = protocols.is_10x(self.ontology_api, lib_prep_protocol) # then self.assertTrue(is10x) def test_is_10x__when_equal_citeseq__returns_true(self): # given lib_prep_protocol = { 'content': { 'library_construction_method': { 'ontology': ONTOLOGY_CITESEQ } } } # when is10x = protocols.is_10x(self.ontology_api, lib_prep_protocol) # then self.assertTrue(is10x) def test_is_10x__when_not_descendant__returns_false(self): lib_prep_protocol = { "content": { "library_construction_method": { "ontology": "EFO:0000000", } } } self.ontology_api.is_equal_or_descendant = Mock(return_value=False) is10x = protocols.is_10x(self.ontology_api, lib_prep_protocol) self.assertFalse(is10x) def test_map_bam_schema__when_equals_citeseq__returns_10xV2(self): # given lib_prep_protocol = { "content": { "library_construction_method": { "ontology": ONTOLOGY_CITESEQ, } } } # when bam_schema = protocols.map_10x_bam_schema(self.ontology_api, lib_prep_protocol) # then self.assertEqual(bam_schema, '10xV2') def test_map_bam_schema__when_not_leaf_term__returns_none(self): # given lib_prep_protocol = { "content": { "library_construction_method": { "ontology": "EFO:0000000", } } } self.ontology_api.get_descendants = Mock(return_value=['descendant']) # not leaf term self.ontology_api.search = Mock(return_value={'ontology_name': 'name', 'iri': 'iri', 'label': "10x 5' v2"}) # when bam_schema = protocols.map_10x_bam_schema(self.ontology_api, lib_prep_protocol) # then self.assertEqual(bam_schema, None) def test_map_bam_schema__when_leaf_term__returns_correct_bam_schema(self): # given lib_prep_protocol = { "content": { "library_construction_method": { "ontology": "EFO:0000000", } } } self.ontology_api.get_descendants = Mock(return_value=[]) # leaf term self.ontology_api.search = Mock(return_value={'ontology_name': 'name', 'iri': 'iri', 'label': "10x 5' v2"}) # when bam_schema = protocols.map_10x_bam_schema(self.ontology_api, lib_prep_protocol) # then self.assertEqual(bam_schema, '10xV2') def test_version_10x_by_label__given_label__return_version(self): # given lib_prep_protocol = { "content": { "library_construction_method": { "ontology": "EFO:0009294", } } } self.ontology_api.search = Mock(return_value={'label': "10x 5' v2"}) # when bam_schema = protocols.version_10x_by_label(self.ontology_api, lib_prep_protocol) # then self.assertEqual(bam_schema, 'V2') def test_version_10x_by_label__given_label__return_version(self): # given lib_prep_protocol = { "content": { "library_construction_method": { "ontology": "EFO:0009294", } } } self.ontology_api.search = Mock(return_value={'label': "10x 3' v3"}) # when bam_schema = protocols.version_10x_by_label(self.ontology_api, lib_prep_protocol) # then self.assertEqual(bam_schema, 'V3')
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from sumy.parsers.plaintext import PlaintextParser #We're choosing a plaintext parser here, other parsers available for HTML etc. from sumy.nlp.tokenizers import Tokenizer from sumy.summarizers.lex_rank import LexRankSummarizer #We're choosing Lexrank, other algorithms are also built in def get_summary(text): # file = "plain_text.txt" #name of the plain-text file # parser = PlaintextParser.from_file(file, Tokenizer("english")) parser=PlaintextParser.from_string(text,Tokenizer("English")) summarizer = LexRankSummarizer() summary = summarizer(parser.document, 5) #Summarize the document with 5 sentences # for sentence in summary: # print(sentence) return summary
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import pandas as pd import cv2 import numpy as np dataset_path = 'fer2013/fer2013/fer2013.csv' image_size=(48,48) def load_fer2013(): data = pd.read_csv(dataset_path) pixels = data['pixels'].tolist() width, height = 48, 48 faces = [] for pixel_sequence in pixels: face = [int(pixel) for pixel in pixel_sequence.split(' ')] face = np.asarray(face).reshape(width, height) face = cv2.resize(face.astype('uint8'),image_size) faces.append(face.astype('float32')) faces = np.asarray(faces) faces = np.expand_dims(faces, -1) emotions = pd.get_dummies(data['emotion']).as_matrix() return faces, emotions def preprocess_input(x, v2=True): x = x.astype('float32') x = x / 255.0 if v2: x = x - 0.5 x = x * 2.0 return x
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import json from time import sleep import gspread import requests from gspread_formatting import * from oauth2client.service_account import ServiceAccountCredentials class Spreadsheet: # comment out all but one of these depending on which spreadsheet being used # URL = 'https://docs.google.com/spreadsheets/d/1WhExw_ReHnyPQYXl0p-kT6jYXpZW5w8-cq2ffK7niOs' # Sample Deep Space Scouting Sheet Machine # URL = 'https://docs.google.om/spreadsheets/d/1lOTML4TgNqv5OKUJU32keWu62__T9cFT3IL52kmPbKk' # Bethesda Week 2 Scouting Sheet Machine # URL = 'https://docs.google.com/spreadsheets/d/1C8hjCqMZmacyUe3SlRgW4o4HGqTRFozviK4WZ6Mu4yc' # Week 0 Scouting Sheet Machine # URL = 'https://docs.google.com/spreadsheets/d/1uYb9n_2IaGSRvOPZcuE59eUQjinaTSIN1SKqTQ6z2lQ' # Dickinson Center Week 0 Scouting Sheet Machine # URL = 'https://docs.google.com/spreadsheets/d/1_8tFjgxjGVA0__1BLkMV-ookfPLrnGDE8gZj6pQc1_k' # Centurion-KnightKrawler Week 0 Scouting Sheet Machine # URL = 'https://docs.google.com/spreadsheets/d/1Ftzcn5u5axYUkob1MXI8wV1KAD-8qjGkywqQjP4_AMo' # Haymarket Week 1 Scouting Sheet Machine # URL = 'https://docs.google.com/spreadsheets/d/1fRm4nZIT457zIpW5cyZrIvR0gSGt6oEcphVYiaH6eK8' # Owings Mills Week 3 Scouting Sheet Machine URL = 'https://docs.google.com/spreadsheets/d/1y8xtKJftg1mDbhfcmISWkyi4MgmSauveD9BY2bPNUCo/edit#gid=168604214' # CHCMP Scouting Sheet Machine # google sheets setup scope = ['https://spreadsheets.google.com/feeds'] creds = ServiceAccountCredentials.from_json_keyfile_name('client_secret_gsheets.json', scope) client = gspread.authorize(creds) # google sheets document sheet = client.open_by_url(URL) # individual worksheets of google sheets document key_worksheet = sheet.worksheet('Key') teams_worksheet = sheet.worksheet('Teams') sample_team_worksheet = sheet.worksheet('Sample Team') schedule_worksheet = sheet.worksheet('Schedule') team_data_worksheet = sheet.worksheet('Team Data') # setting event key to value in A1 of Key worksheet event_key = key_worksheet.cell(1, 1).value # 2537 cell format format_2537 = CellFormat(backgroundColor=Color(.148, .98, .216)) # 25fa37 converted to rgb out of 1 # tba setup tba_session = requests.Session() BASE_URL = 'https://www.thebluealliance.com/api/v3' # tba credentials setup with open('client_secret_tba.json') as json_file: data = json.load(json_file) tba_auth_key = data['tba_auth_key'] def __init__(self): """All TBA requests will have authentication key in header""" self.tba_session.headers.update({'X-TBA-Auth-Key': self.tba_auth_key}) def get_teams_from_event(self, event): """Returns all team keys from event in a list event: event key of intended competition (e.g. 2018vahay) """ teams_raw = self.tba_session.get(self.BASE_URL + '/event/%s/teams/keys' % event).json() teams = [] for team_raw in teams_raw: teams.append(team_raw[3:]) return teams def fill_teams(self, sheet, event): """Fills first column of specified sheet with all teams from specified sheet sheet: intended google sheet event: event key of intended competition (e.g. 2018vahay) """ column = [] for team in self.get_teams_from_event(event): column.append(team) for index in range(0, len(column)): sheet.update_cell(index + 1, 1, column[index]) def create_team_sheets(self): """Creates a scouting sheet for each team in competition event: event key of intended competition (e.g. 2018 vahay) """ teams = self.teams_worksheet.col_values(1) for team in teams: self.sheet.add_worksheet(team, self.sample_team_worksheet.row_count, self.sample_team_worksheet.col_count) def delete_team_sheets(self): """Deletes all individual team worksheets Used for testing """ teams = self.teams_worksheet.col_values(1) for team in teams: self.sheet.del_worksheet(self.sheet.worksheet(team)) def get_sample_sheet(self): """Returns the sample team sheet in 2D list format [row][column]""" sample_sheet = [] for row in range(1, self.sample_team_worksheet.row_count + 1): sample_sheet.append(self.sample_team_worksheet.row_values(row, value_render_option='FORMULA')) return sample_sheet def copy_sheet(self, copy_from, copy_to, team_num): """Copies every element from a list of values to a specified sheet copy_from: list from which values are copied copy_to: sheet to which values are copied """ i, j = 1, 1 for row in copy_from: for col in row: if col == 'Team #': copy_to.update_cell(i, j, team_num) sleep(1.01) elif col != '': copy_to.update_cell(i, j, col) sleep(1.01) # Quota is 100 requests per 100s, this does 100 requests per 101s j += 1 i += 1 j = 1 def copy_sample_to_team_sheets(self): """Copies sample sheet format to every team sheet""" sample_sheet = self.get_sample_sheet() for team in self.teams_worksheet.col_values(1): self.copy_sheet(sample_sheet, self.sheet.worksheet(team), team) def get_color_schedule(self, event, color): """Returns match schedule of specified color alliance in list event: event key of intended competition (e.g. 2018vahay) color: color of desired alliance schedule (e.g. red or blue) """ # event schedules get updated to elims event schedules once elims are reached # only elims schedule accessible in finished events schedule = [] event_list = self.tba_session.get(self.BASE_URL + '/event/%s/matches/simple' % event).json() # list of dicts for match in event_list: schedule.append(match['alliances'][color]['team_keys']) for alliance in schedule: for i in range(len(alliance)): alliance[i] = alliance[i][3:] # trims 'frc' from beginning of every team number return schedule def fill_schedule(self, event): """Auto fills Schedule worksheet with schedule event: event key of intended competition (e.g. 2018vahay) """ red_schedule = self.get_color_schedule(event, 'red') blue_schedule = self.get_color_schedule(event, 'blue') # updates num_matches to the correct number of matches and fill column 1 of spreadsheet with match number num_matches = 1 for match in range(len(red_schedule)): self.schedule_worksheet.update_cell(match + 1, 1, match + 1) num_matches += 1 sleep(1.01) for i in range(num_matches): for j in range(3): self.schedule_worksheet.update_cell(i + 1, j + 2, red_schedule[i][j]) sleep(1.01) self.schedule_worksheet.update_cell(i + 1, j + 5, blue_schedule[i][j]) sleep(1.01) def get_team_metrics_from_event(self, event): """Returns OPRs, DPRs, and CCWMs of all teams at event in dictionary of dictionaries event: event key of intended competition (e.g. 2018vahay) """ return self.tba_session.get(self.BASE_URL + '/event/%s/oprs' % event).json() def fill_team_data(self, event): """Auto fills Team Data worksheet with teams and their corresponding OPR, DPR, and CCWM event: event key if intended competition (e.g. 2018vahay) """ teams = self.get_teams_from_event(event) metrics = self.get_team_metrics_from_event(event) row = 2 team_col, opr_col, dpr_col, ccwm_col = 1, 2, 3, 4 for team in teams: self.team_data_worksheet.update_cell(row, team_col, team) sleep(1.01) self.team_data_worksheet.update_cell(row, opr_col, metrics['oprs']['frc' + team]) sleep(1.01) self.team_data_worksheet.update_cell(row, dpr_col, metrics['dprs']['frc' + team]) sleep(1.01) self.team_data_worksheet.update_cell(row, ccwm_col, metrics['ccwms']['frc' + team]) sleep(1.01) row += 1 def get_predictions_from_event(self, event): return self.tba_session.get(self.BASE_URL + '/event/%s/predictions' % event).json() def format_cells_in_schedule(self): cells_2537_raw = self.schedule_worksheet.findall('2537') cells_2537 = [] for cell in cells_2537_raw: cells_2537.append([cell.col + 64, cell.row]) # add 64 to column to match ascii character decimals for cell in cells_2537: b = bytes(str(cell[0]), 'utf8') ascii_char = b.decode('ascii') cell[0] = chr(int(ascii_char)) for i in range(len(cells_2537)): format_cell_range(self.schedule_worksheet, '%s%i:%s%i' % (cells_2537[i][0], cells_2537[i][1], cells_2537[i][0], cells_2537[i][1]), self.format_2537) def main(self): self.fill_teams(self.teams_worksheet, self.event_key) self.create_team_sheets() # self.delete_team_sheets() # print(self.get_sample_sheet()) # self.copy_sheet(self.get_sample_sheet(), self.sheet.worksheet('1086'), 1086) # testing on single sheet # print(len(self.get_sample_sheet())) self.copy_sample_to_team_sheets() # print(self.get_color_schedule(self.event_key, 'red')) self.fill_schedule(self.event_key) self.fill_team_data(self.event_key) # print(self.get_team_metrics_from_event(self.event_key)) # print(self.get_predictions_from_event(self.event_key)) self.format_cells_in_schedule() if __name__ == '__main__': spreadsheet = Spreadsheet() spreadsheet.main()
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import logging import os import numpy as np import torch from torch.utils.data import Dataset, DataLoader import torchvision.transforms as transforms from torch.utils.data.distributed import DistributedSampler from .dataset import CheXpert def _get_mean_and_std(dataset: Dataset): """Compute the mean and std of dataset.""" data_loader = DataLoader(dataset, batch_size=1, shuffle=False) mean = torch.zeros(3) std = torch.zeros(3) for i, (img, _) in enumerate(data_loader): if i % 1000 == 0: print(i) mean += img.mean(dim=(0, 2, 3)) std += img.std(dim=(0, 2, 3)) mean /= len(data_loader) std /= len(data_loader) return mean, std class Cutout(object): def __init__(self, length): self.length = length def __call__(self, img): h, w = img.size(1), img.size(2) mask = np.ones((h, w), np.float32) y = np.random.randint(h) x = np.random.randint(w) y1 = np.clip(y - self.length // 2, 0, h) y2 = np.clip(y + self.length // 2, 0, h) x1 = np.clip(x - self.length // 2, 0, w) x2 = np.clip(x + self.length // 2, 0, w) mask[y1:y2, x1:x2] = 0.0 mask = torch.from_numpy(mask) mask = mask.expand_as(img) img *= mask return img def _data_transforms_chexpert(): CHEXPERT_MEAN = [0.503, 0.503, 0.503] CHEXPERT_STD = [0.291, 0.291, 0.291] image_size = 256 train_transform = transforms.Compose( [ # transforms.ToPILImage(), transforms.RandomResizedCrop(image_size), # transforms.RandomHorizontalFlip(), transforms.ToTensor(), transforms.Normalize(CHEXPERT_MEAN, CHEXPERT_STD), ] ) # train_transform.transforms.append(Cutout(16)) test_transform = transforms.Compose( [ transforms.CenterCrop(image_size), transforms.ToTensor(), transforms.Normalize(CHEXPERT_MEAN, CHEXPERT_STD), ] ) return train_transform, test_transform # for centralized training def get_dataloader(dataset, datadir, train_bs, test_bs, dataidxs=None, policy="zeros"): return get_dataloader_chexpert(datadir, train_bs, test_bs, dataidxs, policy=policy) # for local devices def get_dataloader_test(dataset, datadir, train_bs, test_bs, dataidxs_train, dataidxs_test, policy="zeros"): return get_dataloader_test_chexpert(datadir, train_bs, test_bs, dataidxs_train, dataidxs_test, policy=policy) def get_dataloader_chexpert(datadir, train_bs, test_bs, dataidxs=None, policy="zeros"): dl_obj = CheXpert transform_train, transform_test = _data_transforms_chexpert() train_ds = dl_obj( datadir, dataidxs=dataidxs, train=True, transform=transform_train, download=False, policy=policy, ) test_ds = dl_obj( datadir, dataidxs=None, train=False, transform=transform_test, download=False, policy=policy, ) train_dl = DataLoader( dataset=train_ds, batch_size=train_bs, shuffle=True, drop_last=False, pin_memory=True, num_workers=4, ) test_dl = DataLoader( dataset=test_ds, batch_size=test_bs, shuffle=False, drop_last=False, pin_memory=True, num_workers=4, ) return train_dl, test_dl def get_dataloader_test_chexpert(datadir, train_bs, test_bs, dataidxs_train=None, dataidxs_test=None, policy="zeros"): dl_obj = CheXpert transform_train, transform_test = _data_transforms_chexpert() train_ds = dl_obj( datadir, dataidxs=dataidxs_train, train=True, transform=transform_train, download=True, policy=policy, ) test_ds = dl_obj( datadir, dataidxs=dataidxs_test, train=False, transform=transform_test, download=True, policy=policy, ) train_dl = DataLoader( dataset=train_ds, batch_size=train_bs, shuffle=True, drop_last=False, pin_memory=True, num_workers=4, ) test_dl = DataLoader( dataset=test_ds, batch_size=test_bs, shuffle=False, drop_last=False, pin_memory=True, num_workers=4, ) return train_dl, test_dl def distributed_centralized_chexpert_loader(dataset, data_dir, world_size, rank, batch_size): """ Used for generating distributed dataloader for accelerating centralized training """ train_bs = batch_size test_bs = batch_size transform_train, transform_test = _data_transforms_chexpert() train_dataset = CheXpert(data_dir=data_dir, dataidxs=None, train=True, transform=transform_train) test_dataset = CheXpert(data_dir=data_dir, dataidxs=None, train=False, transform=transform_test) train_sam = DistributedSampler(train_dataset, num_replicas=world_size, rank=rank) test_sam = DistributedSampler(test_dataset, num_replicas=world_size, rank=rank) train_dl = data.DataLoader( train_dataset, batch_size=train_bs, sampler=train_sam, pin_memory=True, num_workers=4, ) test_dl = data.DataLoader( test_dataset, batch_size=test_bs, sampler=test_sam, pin_memory=True, num_workers=4, ) class_num = 1000 train_data_num = len(train_dataset) test_data_num = len(test_dataset) return train_data_num, test_data_num, train_dl, test_dl, None, None, None, class_num def load_partition_data_chexpert( data_dir, partition_method="random", partition_alpha=None, client_number=100, batch_size=10, policy="zeros", ): transform_train, transform_test = _data_transforms_chexpert() train_dataset = CheXpert( data_dir=data_dir, dataidxs=None, train=True, transform=transform_train, policy=policy, ) test_dataset = CheXpert(data_dir=data_dir, dataidxs=None, train=False, transform=transform_test, policy=policy) # get local dataset if partition_method == "random": num_train_items = int(len(train_dataset) / client_number) num_test_items = int(len(test_dataset) / client_number) dict_client = {} all_train_idxs = list(range(len(train_dataset))) all_test_idxs = list(range(len(test_dataset))) for client_idx in range(client_number): dict_client[client_idx] = {} dict_client[client_idx]["train"] = set(np.random.choice(all_train_idxs, num_train_items, replace=False)) dict_client[client_idx]["test"] = set(np.random.choice(all_test_idxs, num_test_items, replace=False)) all_train_idxs = list(set(all_train_idxs) - dict_client[client_idx]["train"]) all_test_idxs = list(set(all_test_idxs) - dict_client[client_idx]["test"]) if len(all_train_idxs) > 0: all_client_idxs = list(range(client_number)) np.random.shuffle(all_client_idxs) choiced_client_idxs = all_client_idxs[: len(all_train_idxs)] for idx, client_idx in enumerate(choiced_client_idxs): dict_client[client_idx]["train"].add(all_train_idxs[idx]) if len(all_test_idxs) > 0: all_client_idxs = list(range(client_number)) np.random.shuffle(all_client_idxs) choiced_client_idxs = all_client_idxs[: len(all_test_idxs)] for idx, client_idx in enumerate(choiced_client_idxs): dict_client[client_idx]["test"].add(all_test_idxs[idx]) else: raise NotImplementedError # build dataloader train_dl = [] test_dl = [] for client_idx in range(client_number): train_data_idxs = list(dict_client[client_idx]["train"]) test_data_idxs = list(dict_client[client_idx]["test"]) train_dl_, test_dl_ = get_dataloader_test_chexpert( datadir=data_dir, dataidxs_train=train_data_idxs, dataidxs_test=test_data_idxs, train_bs=batch_size, test_bs=batch_size, policy=policy, ) train_dl.append(train_dl_) test_dl.append(test_dl_) logging.info(f"Client {client_idx} train data num: {len(train_dl_)} test data num: {len(test_dl_)}") logging.info("Partition data done") # logging.info("Partition data for each client: {}".format(dict_client)) train_data_num = len(train_dataset) test_data_num = len(test_dataset) train_data_global = train_dataset test_data_global = test_dataset data_local_num_dict = { client_idx: len(dict_client[client_idx]["train"]) + len(dict_client[client_idx]["test"]) for client_idx in range(client_number) } train_data_local_dict = {client_idx: train_dl_ for client_idx, train_dl_ in enumerate(train_dl)} test_data_local_dict = {client_idx: test_dl_ for client_idx, test_dl_ in enumerate(test_dl)} class_num = train_dataset.num_classes return ( train_data_num, test_data_num, train_data_global, test_data_global, data_local_num_dict, train_data_local_dict, test_data_local_dict, class_num, ) if __name__ == "__main__": data_path = os.path.join("D:\\", "dataset", "CheXpert", "CheXpert-v1.0-small") data = CheXpert(data_dir=data_path, transform=transforms.ToTensor()) print(len(data)) print(data[0][0]) print(data[0][1]) # mean, std = _get_mean_and_std(data) # print(mean, std) # train_transform, valid_transform = _data_transforms_chexpert() # print(train_transform) # print(valid_transform) ( train_data_num, test_data_num, train_data_global, test_data_global, data_local_num_dict, train_data_local_dict, test_data_local_dict, class_num, ) = load_partition_data_chexpert(data_dir=data_path, client_number=10, batch_size=10, policy="zeros") print(train_data_num, test_data_num, class_num)
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import json from collections import Iterable from pathlib import Path import cadquery as cq import matplotlib.pyplot as plt import plotly.graph_objects as go from cadquery import exporters import paramak from paramak.neutronics_utils import (add_stl_to_moab_core, define_moab_core_and_tags) from paramak.utils import get_hash class Reactor: """The Reactor object allows shapes and components to be added and then collective operations to be performed on them. Combining all the shapes is required for creating images of the whole reactor and creating a Graveyard (bounding box) that is needed for neutronics simulations. Args: shapes_and_components (list): list of paramak.Shape """ def __init__(self, shapes_and_components): self.material_tags = [] self.stp_filenames = [] self.stl_filenames = [] self.tet_meshes = [] self.graveyard = None self.solid = None self.shapes_and_components = shapes_and_components self.reactor_hash_value = None self.graveyard_offset = None # set by the make_graveyard method @property def stp_filenames(self): values = [] for shape_or_component in self.shapes_and_components: values.append(shape_or_component.stp_filename) return values @stp_filenames.setter def stp_filenames(self, value): self._stp_filenames = value @property def stl_filenames(self): values = [] for shape_or_component in self.shapes_and_components: values.append(shape_or_component.stl_filename) return values @stl_filenames.setter def stl_filenames(self, value): self._stl_filenames = value @property def largest_dimension(self): """Calculates a bounding box for the Reactor and returns the largest absolute value of the largest dimension of the bounding box""" largest_dimension = 0 for component in self.shapes_and_components: largest_dimension = max( largest_dimension, component.largest_dimension) self._largest_dimension = largest_dimension return largest_dimension @largest_dimension.setter def largest_dimension(self, value): self._largest_dimension = value @property def material_tags(self): """Returns a set of all the materials_tags used in the Reactor (excluding the plasma)""" values = [] for shape_or_component in self.shapes_and_components: if isinstance( shape_or_component, (paramak.Plasma, paramak.PlasmaFromPoints, paramak.PlasmaBoundaries)) is False: values.append(shape_or_component.material_tag) return values @material_tags.setter def material_tags(self, value): self._material_tags = value @property def tet_meshes(self): values = [] for shape_or_componet in self.shapes_and_components: values.append(shape_or_componet.tet_mesh) return values @tet_meshes.setter def tet_meshes(self, value): self._tet_meshes = value @property def shapes_and_components(self): """Adds a list of parametric shape(s) and or parametric component(s) to the Reactor object. This allows collective operations to be performed on all the shapes in the reactor. When adding a shape or component the stp_filename of the shape or component should be unique""" if hasattr(self, "create_solids"): ignored_keys = ["reactor_hash_value"] if get_hash(self, ignored_keys) != self.reactor_hash_value: self.create_solids() self.reactor_hash_value = get_hash(self, ignored_keys) return self._shapes_and_components @shapes_and_components.setter def shapes_and_components(self, value): if not isinstance(value, Iterable): raise ValueError("shapes_and_components must be a list") self._shapes_and_components = value @property def graveyard_offset(self): return self._graveyard_offset @graveyard_offset.setter def graveyard_offset(self, value): if value is None: self._graveyard_offset = None elif not isinstance(value, (float, int)): raise ValueError("graveyard_offset must be a number") elif value < 0: raise ValueError("graveyard_offset must be positive") self._graveyard_offset = value @property def solid(self): """This combines all the parametric shapes and compents in the reactor object and rotates the viewing angle so that .solid operations in jupyter notebook. """ list_of_cq_vals = [] for shape_or_compound in self.shapes_and_components: if isinstance( shape_or_compound.solid, cq.occ_impl.shapes.Compound): for solid in shape_or_compound.solid.Solids(): list_of_cq_vals.append(solid) else: list_of_cq_vals.append(shape_or_compound.solid.val()) compound = cq.Compound.makeCompound(list_of_cq_vals) compound = compound.rotate( startVector=(0, 1, 0), endVector=(0, 0, 1), angleDegrees=180 ) return compound @solid.setter def solid(self, value): self._solid = value def neutronics_description(self, include_plasma=False, include_graveyard=True ): """A description of the reactor containing material tags, stp filenames, and tet mesh instructions. This is used for neutronics simulations which require linkage between volumes, materials and identification of which volumes to tet mesh. The plasma geometry is not included by default as it is typically not included in neutronics simulations. The reason for this is that the low number density results in minimal interaction with neutrons. However, it can be added if the include_plasma argument is set to True. Returns: dictionary: a dictionary of materials and filenames for the reactor """ neutronics_description = [] for entry in self.shapes_and_components: if include_plasma is False and isinstance( entry, (paramak.Plasma, paramak.PlasmaFromPoints, paramak.PlasmaBoundaries)) is True: continue if entry.stp_filename is None: raise ValueError( "Set Shape.stp_filename for all the \ Reactor entries before using this method" ) if entry.material_tag is None: raise ValueError( "set Shape.material_tag for all the \ Reactor entries before using this method" ) neutronics_description.append(entry.neutronics_description()) # This add the neutronics description for the graveyard which is unique # as it is automatically calculated instead of being added by the user. # Also the graveyard must have 'Graveyard' as the material name if include_graveyard is True: self.make_graveyard() neutronics_description.append( self.graveyard.neutronics_description()) return neutronics_description def export_neutronics_description( self, filename="manifest.json", include_plasma=False, include_graveyard=True): """ Saves Reactor.neutronics_description to a json file. The resulting json file contains a list of dictionaries. Each dictionary entry comprises of a material and a filename and optionally a tet_mesh instruction. The json file can then be used with the neutronics workflows to create a neutronics model. Creating of the neutronics model requires linkage between volumes, materials and identification of which volumes to tet_mesh. If the filename does not end with .json then .json will be added. The plasma geometry is not included by default as it is typically not included in neutronics simulations. The reason for this is that the low number density results in minimal interactions with neutrons. However, the plasma can be added if the include_plasma argument is set to True. Args: filename (str, optional): the filename used to save the neutronics description include_plasma (Boolean, optional): should the plasma be included. Defaults to False as the plasma volume and material has very little impact on the neutronics results due to the low density. Including the plasma does however slow down the simulation. include_graveyard (Boolean, optional): should the graveyard be included. Defaults to True as this is needed for DAGMC models. """ path_filename = Path(filename) if path_filename.suffix != ".json": path_filename = path_filename.with_suffix(".json") path_filename.parents[0].mkdir(parents=True, exist_ok=True) with open(path_filename, "w") as outfile: json.dump( self.neutronics_description( include_plasma=include_plasma, include_graveyard=include_graveyard, ), outfile, indent=4, ) print("saved geometry description to ", path_filename) return str(path_filename) def export_stp(self, output_folder="", graveyard_offset=100, mode='solid'): """Writes stp files (CAD geometry) for each Shape object in the reactor and the graveyard. Args: output_folder (str): the folder for saving the stp files to graveyard_offset (float, optional): the offset between the largest edge of the geometry and inner bounding shell created. Defaults to 100. mode (str, optional): the object to export can be either 'solid' which exports 3D solid shapes or the 'wire' which exports the wire edges of the shape. Defaults to 'solid'. Returns: list: a list of stp filenames created """ if len(self.stp_filenames) != len(set(self.stp_filenames)): raise ValueError( "Set Reactor already contains a shape or component \ with this stp_filename", self.stp_filenames, ) filenames = [] for entry in self.shapes_and_components: if entry.stp_filename is None: raise ValueError( "set .stp_filename property for \ Shapes before using the export_stp method" ) filenames.append( str(Path(output_folder) / Path(entry.stp_filename))) entry.export_stp( filename=Path(output_folder) / Path(entry.stp_filename), mode=mode ) # creates a graveyard (bounding shell volume) which is needed for # nuetronics simulations self.make_graveyard(graveyard_offset=graveyard_offset) filenames.append( str(Path(output_folder) / Path(self.graveyard.stp_filename))) self.graveyard.export_stp( Path(output_folder) / Path(self.graveyard.stp_filename) ) return filenames def export_stl(self, output_folder="", tolerance=0.001): """Writes stl files (CAD geometry) for each Shape object in the reactor :param output_folder: the folder for saving the stp files to :type output_folder: str :param tolerance: the precision of the faceting :type tolerance: float :return: a list of stl filenames created :rtype: list """ if len(self.stl_filenames) != len(set(self.stl_filenames)): raise ValueError( "Set Reactor already contains a shape or component \ with this stl_filename", self.stl_filenames, ) filenames = [] for entry in self.shapes_and_components: print("entry.stl_filename", entry.stl_filename) if entry.stl_filename is None: raise ValueError( "set .stl_filename property for \ Shapes before using the export_stl method" ) filenames.append( str(Path(output_folder) / Path(entry.stl_filename))) entry.export_stl( Path(output_folder) / Path( entry.stl_filename), tolerance) # creates a graveyard (bounding shell volume) which is needed for # nuetronics simulations self.make_graveyard() filenames.append( str(Path(output_folder) / Path(self.graveyard.stl_filename))) self.graveyard.export_stl( Path(output_folder) / Path(self.graveyard.stl_filename) ) print("exported stl files ", filenames) return filenames def export_h5m( self, filename='dagmc.h5m', skip_graveyard=False, tolerance=0.001, graveyard_offset=100): """Converts stl files into DAGMC compatible h5m file using PyMOAB. The DAGMC file produced has not been imprinted and merged unlike the other supported method which uses Trelis to produce an imprinted and merged DAGMC geometry. If the provided filename doesn't end with .h5m it will be added Args: filename (str, optional): filename of h5m outputfile Defaults to "dagmc.h5m". skip_graveyard (boolean, optional): filename of h5m outputfile Defaults to False. tolerance (float, optional): the precision of the faceting Defaults to 0.001. graveyard_offset (float, optional): the offset between the largest edge of the geometry and inner bounding shell created. Defaults to 100. Returns: filename: output h5m filename """ path_filename = Path(filename) if path_filename.suffix != ".h5m": path_filename = path_filename.with_suffix(".h5m") path_filename.parents[0].mkdir(parents=True, exist_ok=True) moab_core, moab_tags = define_moab_core_and_tags() surface_id = 1 volume_id = 1 for item in self.shapes_and_components: item.export_stl(item.stl_filename, tolerance=tolerance) moab_core = add_stl_to_moab_core( moab_core, surface_id, volume_id, item.material_tag, moab_tags, item.stl_filename) volume_id += 1 surface_id += 1 if skip_graveyard is False: self.make_graveyard(graveyard_offset=graveyard_offset) self.graveyard.export_stl(self.graveyard.stl_filename) volume_id = 2 surface_id = 2 moab_core = add_stl_to_moab_core( moab_core, surface_id, volume_id, self.graveyard.material_tag, moab_tags, self.graveyard.stl_filename ) all_sets = moab_core.get_entities_by_handle(0) file_set = moab_core.create_meshset() moab_core.add_entities(file_set, all_sets) moab_core.write_file(str(path_filename)) return filename def export_physical_groups(self, output_folder=""): """Exports several JSON files containing a look up table which is useful for identifying faces and volumes. The output file names are generated from .stp_filename properties. Args: output_folder (str, optional): directory of outputfiles. Defaults to "". Raises: ValueError: if one .stp_filename property is set to None Returns: list: list of output file names """ filenames = [] for entry in self.shapes_and_components: if entry.stp_filename is None: raise ValueError( "set .stp_filename property for \ Shapes before using the export_stp method" ) filenames.append( str(Path(output_folder) / Path(entry.stp_filename))) entry.export_physical_groups( Path(output_folder) / Path(entry.stp_filename)) return filenames def export_svg(self, filename): """Exports an svg file for the Reactor.solid. If the filename provided doesn't end with .svg it will be added. Args: filename (str): the filename of the svg file to be exported """ path_filename = Path(filename) if path_filename.suffix != ".svg": path_filename = path_filename.with_suffix(".svg") path_filename.parents[0].mkdir(parents=True, exist_ok=True) with open(path_filename, "w") as out_file: exporters.exportShape(self.solid, "SVG", out_file) print("Saved file as ", path_filename) def export_graveyard( self, graveyard_offset=100, filename="Graveyard.stp"): """Writes an stp file (CAD geometry) for the reactor graveyard. This is needed for DAGMC simulations. This method also calls Reactor.make_graveyard with the offset. Args: filename (str): the filename for saving the stp file graveyard_offset (float): the offset between the largest edge of the geometry and inner bounding shell created. Defaults to Reactor.graveyard_offset Returns: str: the stp filename created """ self.make_graveyard(graveyard_offset=graveyard_offset) self.graveyard.export_stp(Path(filename)) return filename def make_graveyard(self, graveyard_offset=100): """Creates a graveyard volume (bounding box) that encapsulates all volumes. This is required by DAGMC when performing neutronics simulations. Args: graveyard_offset (float): the offset between the largest edge of the geometry and inner bounding shell created. Defaults to Reactor.graveyard_offset Returns: CadQuery solid: a shell volume that bounds the geometry, referred to as a graveyard in DAGMC """ self.graveyard_offset = graveyard_offset for component in self.shapes_and_components: if component.solid is None: component.create_solid() graveyard_shape = paramak.HollowCube( length=self.largest_dimension * 2 + graveyard_offset * 2, name="Graveyard", material_tag="Graveyard", stp_filename="Graveyard.stp", stl_filename="Graveyard.stl", ) self.graveyard = graveyard_shape return graveyard_shape def export_2d_image( self, filename="2d_slice.png", xmin=0.0, xmax=900.0, ymin=-600.0, ymax=600.0): """Creates a 2D slice image (png) of the reactor. Args: filename (str): output filename of the image created Returns: str: png filename created """ path_filename = Path(filename) if path_filename.suffix != ".png": path_filename = path_filename.with_suffix(".png") path_filename.parents[0].mkdir(parents=True, exist_ok=True) fig, ax = plt.subplots() # creates indvidual patches for each Shape which are combined together for entry in self.shapes_and_components: patch = entry._create_patch() ax.add_collection(patch) ax.axis("equal") ax.set(xlim=(xmin, xmax), ylim=(ymin, ymax)) ax.set_aspect("equal", "box") Path(filename).parent.mkdir(parents=True, exist_ok=True) plt.savefig(filename, dpi=100) plt.close() print("\n saved 2d image to ", str(path_filename)) return str(path_filename) def export_html(self, filename="reactor.html"): """Creates a html graph representation of the points for the Shape objects that make up the reactor. Note, If filename provided doesn't end with .html then it will be appended. Args: filename (str): the filename to save the html graph Returns: plotly figure: figure object """ path_filename = Path(filename) if path_filename.suffix != ".html": path_filename = path_filename.with_suffix(".html") path_filename.parents[0].mkdir(parents=True, exist_ok=True) fig = go.Figure() fig.update_layout( {"title": "coordinates of components", "hovermode": "closest"} ) # accesses the Shape traces for each Shape and adds them to the figure for entry in self.shapes_and_components: fig.add_trace(entry._trace()) fig.write_html(str(path_filename)) print("Exported html graph to ", str(path_filename)) return fig
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#!/usr/bin/python2 """ Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to you 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 resource_management import * def hive_service( name, action='start'): import params if name == 'metastore': pid_file = format("{hive_pid_dir}/{hive_metastore_pid}") cmd = format( "env HADOOP_HOME={hadoop_home} JAVA_HOME={java64_home} {start_metastore_path} {hive_log_dir}/hive.out {hive_log_dir}/hive.err {pid_file} {hive_server_conf_dir}") elif name == 'hiveserver2': pid_file = format("{hive_pid_dir}/{hive_pid}") cmd = format( "env JAVA_HOME={java64_home} {start_hiveserver2_path} {hive_log_dir}/hive-server2.out {hive_log_dir}/hive-server2.err {pid_file} {hive_server_conf_dir}") if action == 'start': demon_cmd = format("{cmd}") no_op_test = format("ls {pid_file} >/dev/null 2>&1 && ps `cat {pid_file}` >/dev/null 2>&1") Execute(demon_cmd, user=params.hive_user, not_if=no_op_test ) if params.hive_jdbc_driver == "com.mysql.jdbc.Driver" or params.hive_jdbc_driver == "oracle.jdbc.driver.OracleDriver": db_connection_check_command = format( "{java64_home}/bin/java -cp {check_db_connection_jar}:/usr/share/java/{jdbc_jar_name} org.apache.ambari.server.DBConnectionVerification {hive_jdbc_connection_url} {hive_metastore_user_name} {hive_metastore_user_passwd} {hive_jdbc_driver}") Execute(db_connection_check_command, path='/usr/sbin:/sbin:/usr/local/bin:/bin:/usr/bin') elif action == 'stop': demon_cmd = format("kill `cat {pid_file}` >/dev/null 2>&1 && rm -f {pid_file}") Execute(demon_cmd)
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""" Logging module for printing status during an exploit, and internally within ``pwntools``. Exploit Developers ------------------ By using the standard ``from pwn import *``, an object named ``log`` will be inserted into the global namespace. You can use this to print out status messages during exploitation. For example,:: log.info('Hello, world!') prints:: [*] Hello, world! Additionally, there are some nifty mechanisms for performing status updates on a running job (e.g. when brute-forcing).:: p = log.progress('Working') p.status('Reticulating splines') time.sleep(1) p.success('Got a shell!') The verbosity of logging can be most easily controlled by setting ``log_level`` on the global ``context`` object.:: log.info("No you see me") context.log_level = 'error' log.info("Now you don't") The purpose of this attribute is to control what gets printed to the screen, not what gets emitted. This means that you can put all logging events into a log file, while only wanting to see a small subset of them on your screen. Pwnlib Developers ----------------- A module-specific logger can be imported into the module via:: from pwnlib.log import getLogger log = getLogger(__name__) This provides an easy way to filter logging programmatically or via a configuration file for debugging. When using ``progress``, you should use the ``with`` keyword to manage scoping, to ensure the spinner stops if an exception is thrown. Technical details ----------------- Familiarity with the :mod:`logging` module is assumed. A pwnlib root logger named 'pwnlib' is created and a custom handler and formatter is installed for it. The handler determines its logging level from :data:`context.log_level`. Ideally :data:`context.log_level` should only affect which records will be emitted by the handler such that e.g. logging to a file will not be changed by it. But for performance reasons it is not feasible log everything in the normal case. In particular there are tight loops inside :mod:`pwnlib.tubes.tube`, which we would like to be able to debug, but if we are not debugging them, they should not spit out messages (even to a log file). For this reason there are a few places inside pwnlib, that will not even emit a record without :data:`context.log_level` being set to `logging.DEBUG` or below. Log records created by ``Progress`` and ``Logger`` objects will set ``'pwnlib_msgtype'`` on the ``extra`` field to signal which kind of message was generated. This information is used by the formatter to prepend a symbol to the message, e.g. ``'[+] '`` in ``'[+] got a shell!'`` This field is ignored when using the ``logging`` module's standard formatters. All status updates (which are not dropped due to throttling) on progress loggers result in a log record being created. The ``extra`` field then carries a reference to the ``Progress`` logger as ``'pwnlib_progress'``. If the custom handler determines that :data:`term.term_mode` is enabled, log records that have a ``'pwnlib_progess'`` in their ``extra`` field will not result in a message being emitted but rather an animated progress line (with a spinner!) being created. Note that other handlers will still see a meaningful log record. The custom handler will only handle log records whith a level of at least :data:`context.log_level`. Thus if e.g. the level for the ``'pwnlib.tubes.ssh'`` is set to ``'DEBUG'`` no additional output will show up unless :data:`context.log_level` is also set to ``'DEBUG'``. Other handlers will however see the extra log records generated by the ``'pwnlib.tubes.ssh'`` logger. """ from __future__ import absolute_import from __future__ import division import logging import os import random import re import six import sys import threading import time from pwnlib import term from pwnlib.config import register_config from pwnlib.context import Thread from pwnlib.context import context from pwnlib.exception import PwnlibException from pwnlib.term import spinners from pwnlib.term import text __all__ = [ 'getLogger', 'install_default_handler', 'rootlogger' ] # list of prefixes to use for the different message types. note that the `text` # module won't add any escape codes if `pwnlib.context.log_console.isatty()` is `False` _msgtype_prefixes = { 'status' : [text.magenta, 'x'], 'success' : [text.bold_green, '+'], 'failure' : [text.bold_red, '-'], 'debug' : [text.bold_red, 'DEBUG'], 'info' : [text.bold_blue, '*'], 'warning' : [text.bold_yellow, '!'], 'error' : [text.on_red, 'ERROR'], 'exception' : [text.on_red, 'ERROR'], 'critical' : [text.on_red, 'CRITICAL'], 'info_once' : [text.bold_blue, '*'], 'warning_once' : [text.bold_yellow, '!'], } def read_log_config(settings): log = getLogger(__name__) for key, value in settings.items(): if '.' not in key: log.warn("Invalid configuration option %r in section %r" % (key, 'log')) continue msgtype, key = key.split('.', 1) if key == 'color': current = _msgtype_prefixes[msgtype][0] _msgtype_prefixes[msgtype][0] = getattr(text, value, current) elif key == 'symbol': _msgtype_prefixes[msgtype][1] = value else: log.warn("Unknown configuration option %r in section %r" % (key, 'log')) register_config('log', read_log_config) # the text decoration to use for spinners. the spinners themselves can be found # in the `pwnlib.term.spinners` module _spinner_style = text.bold_blue class Progress(object): """ Progress logger used to generate log records associated with some running job. Instances can be used as context managers which will automatically declare the running job a success upon exit or a failure upon a thrown exception. After :meth:`success` or :meth:`failure` is called the status can no longer be updated. This class is intended for internal use. Progress loggers should be created using :meth:`Logger.progress`. """ def __init__(self, logger, msg, status, level, args, kwargs): self._logger = logger self._msg = msg self._status = status self._level = level self._stopped = False self.last_status = 0 self.rate = kwargs.pop('rate', 0) self._log(status, args, kwargs, 'status') # it is a common use case to create a logger and then immediately update # its status line, so we reset `last_status` to accommodate this pattern self.last_status = 0 def _log(self, status, args, kwargs, msgtype): # Logs are strings, not bytes. Handle Python3 bytes() objects. status = six.ensure_text(status) # this progress logger is stopped, so don't generate any more records if self._stopped: return msg = self._msg if msg and status: msg += ': ' msg += status self._logger._log(self._level, msg, args, kwargs, msgtype, self) def status(self, status, *args, **kwargs): """status(status, *args, **kwargs) Logs a status update for the running job. If the progress logger is animated the status line will be updated in place. Status updates are throttled at one update per 100ms. """ now = time.time() if (now - self.last_status) > self.rate: self.last_status = now self._log(status, args, kwargs, 'status') def success(self, status = 'Done', *args, **kwargs): """success(status = 'Done', *args, **kwargs) Logs that the running job succeeded. No further status updates are allowed. If the Logger is animated, the animation is stopped. """ self._log(status, args, kwargs, 'success') self._stopped = True def failure(self, status = 'Failed', *args, **kwargs): """failure(message) Logs that the running job failed. No further status updates are allowed. If the Logger is animated, the animation is stopped. """ self._log(status, args, kwargs, 'failure') self._stopped = True def __enter__(self): return self def __exit__(self, exc_typ, exc_val, exc_tb): # if the progress logger is already stopped these are no-ops if exc_typ is None: self.success() else: self.failure() class Logger(object): """ A class akin to the :class:`logging.LoggerAdapter` class. All public methods defined on :class:`logging.Logger` instances are defined on this class. Also adds some ``pwnlib`` flavor: * :meth:`progress` (alias :meth:`waitfor`) * :meth:`success` * :meth:`failure` * :meth:`indented` * :meth:`info_once` * :meth:`warning_once` (alias :meth:`warn_once`) Adds ``pwnlib``-specific information for coloring, indentation and progress logging via log records ``extra`` field. Loggers instantiated with :func:`getLogger` will be of this class. """ _one_time_infos = set() _one_time_warnings = set() def __init__(self, logger=None): if logger is None: # This is a minor hack to permit user-defined classes which inherit # from a tube (which do not actually reside in the pwnlib library) # to receive logging abilities that behave as they would expect from # the rest of the library module = self.__module__ if not module.startswith('pwnlib'): module = 'pwnlib.' + module # - end hack - logger_name = '%s.%s.%s' % (module, self.__class__.__name__, id(self)) logger = logging.getLogger(logger_name) self._logger = logger def _getlevel(self, levelString): if isinstance(levelString, six.integer_types): return levelString return logging._levelNames[levelString.upper()] def _log(self, level, msg, args, kwargs, msgtype, progress = None): # Logs are strings, not bytes. Handle Python3 bytes() objects. msg = six.ensure_text(msg) extra = kwargs.get('extra', {}) extra.setdefault('pwnlib_msgtype', msgtype) extra.setdefault('pwnlib_progress', progress) kwargs['extra'] = extra self._logger.log(level, msg, *args, **kwargs) def progress(self, message, status = '', *args, **kwargs): """progress(message, status = '', *args, level = logging.INFO, **kwargs) -> Progress Creates a new progress logger which creates log records with log level `level`. Progress status can be updated using :meth:`Progress.status` and stopped using :meth:`Progress.success` or :meth:`Progress.failure`. If `term.term_mode` is enabled the progress logger will be animated. The progress manager also functions as a context manager. Using context managers ensures that animations stop even if an exception is raised. .. code-block:: python with log.progress('Trying something...') as p: for i in range(10): p.status("At %i" % i) time.sleep(0.5) x = 1/0 """ level = self._getlevel(kwargs.pop('level', logging.INFO)) return Progress(self, message, status, level, args, kwargs) def waitfor(self, *args, **kwargs): """Alias for :meth:`progress`.""" return self.progress(*args, **kwargs) def indented(self, message, *args, **kwargs): """indented(message, *args, level = logging.INFO, **kwargs) Log a message but don't put a line prefix on it. Arguments: level(int): Alternate log level at which to set the indented message. Defaults to :const:`logging.INFO`. """ level = self._getlevel(kwargs.pop('level', logging.INFO)) self._log(level, message, args, kwargs, 'indented') def success(self, message, *args, **kwargs): """success(message, *args, **kwargs) Logs a success message. """ self._log(logging.INFO, message, args, kwargs, 'success') def failure(self, message, *args, **kwargs): """failure(message, *args, **kwargs) Logs a failure message. """ self._log(logging.INFO, message, args, kwargs, 'failure') def info_once(self, message, *args, **kwargs): """info_once(message, *args, **kwargs) Logs an info message. The same message is never printed again. """ m = message % args if m not in self._one_time_infos: if self.isEnabledFor(logging.INFO): self._one_time_infos.add(m) self._log(logging.INFO, message, args, kwargs, 'info_once') def warning_once(self, message, *args, **kwargs): """warning_once(message, *args, **kwargs) Logs a warning message. The same message is never printed again. """ m = message % args if m not in self._one_time_warnings: if self.isEnabledFor(logging.WARNING): self._one_time_warnings.add(m) self._log(logging.WARNING, message, args, kwargs, 'warning_once') def warn_once(self, *args, **kwargs): """Alias for :meth:`warning_once`.""" return self.warning_once(*args, **kwargs) # logging functions also exposed by `logging.Logger` def debug(self, message, *args, **kwargs): """debug(message, *args, **kwargs) Logs a debug message. """ self._log(logging.DEBUG, message, args, kwargs, 'debug') def info(self, message, *args, **kwargs): """info(message, *args, **kwargs) Logs an info message. """ self._log(logging.INFO, message, args, kwargs, 'info') def hexdump(self, message, *args, **kwargs): # cyclic dependencies FTW! # TODO: Move pwnlib.util.fiddling.hexdump into a new module. import pwnlib.util.fiddling self.info(pwnlib.util.fiddling.hexdump(message, *args, **kwargs)) def warning(self, message, *args, **kwargs): """warning(message, *args, **kwargs) Logs a warning message. """ self._log(logging.WARNING, message, args, kwargs, 'warning') def warn(self, *args, **kwargs): """Alias for :meth:`warning`.""" return self.warning(*args, **kwargs) def error(self, message, *args, **kwargs): """error(message, *args, **kwargs) To be called outside an exception handler. Logs an error message, then raises a ``PwnlibException``. """ self._log(logging.ERROR, message, args, kwargs, 'error') raise PwnlibException(message % args) def exception(self, message, *args, **kwargs): """exception(message, *args, **kwargs) To be called from an exception handler. Logs a error message, then re-raises the current exception. """ kwargs["exc_info"] = 1 self._log(logging.ERROR, message, args, kwargs, 'exception') raise def critical(self, message, *args, **kwargs): """critical(message, *args, **kwargs) Logs a critical message. """ self._log(logging.CRITICAL, message, args, kwargs, 'critical') def log(self, level, message, *args, **kwargs): """log(level, message, *args, **kwargs) Logs a message with log level `level`. The ``pwnlib`` formatter will use the default :mod:`logging` formater to format this message. """ self._log(level, message, args, kwargs, None) def isEnabledFor(self, level): """isEnabledFor(level) -> bool See if the underlying logger is enabled for the specified level. """ effectiveLevel = self._logger.getEffectiveLevel() if effectiveLevel == 1: effectiveLevel = context.log_level return effectiveLevel <= level def setLevel(self, level): """setLevel(level) Set the logging level for the underlying logger. """ with context.local(log_level=level): self._logger.setLevel(context.log_level) def addHandler(self, handler): """addHandler(handler) Add the specified handler to the underlying logger. """ self._logger.addHandler(handler) def removeHandler(self, handler): """removeHandler(handler) Remove the specified handler from the underlying logger. """ self._logger.removeHandler(handler) @property def level(self): return self._logger.level @level.setter def level(self, value): with context.local(log_level=value): self._logger.level = context.log_level class Handler(logging.StreamHandler): """ A custom handler class. This class will report whatever :data:`context.log_level` is currently set to as its log level. If :data:`term.term_mode` is enabled log records originating from a progress logger will not be emitted but rather an animated progress line will be created. An instance of this handler is added to the ``'pwnlib'`` logger. """ @property def stream(self): return context.log_console @stream.setter def stream(self, value): pass def emit(self, record): """ Emit a log record or create/update an animated progress logger depending on whether :data:`term.term_mode` is enabled. """ # We have set the root 'pwnlib' logger to have a logLevel of 1, # when logging has been enabled via install_default_handler. # # If the level is 1, we should only process the record if # context.log_level is less than the record's log level. # # If the level is not 1, somebody else expressly set the log # level somewhere on the tree, and we should use that value. level = logging.getLogger(record.name).getEffectiveLevel() if level == 1: level = context.log_level if level > record.levelno: return progress = getattr(record, 'pwnlib_progress', None) # if the record originates from a `Progress` object and term handling # is enabled we can have animated spinners! so check that if progress is None or not term.term_mode: super(Handler, self).emit(record) return # yay, spinners! # since we want to be able to update the spinner we overwrite the # message type so that the formatter doesn't output a prefix symbol msgtype = record.pwnlib_msgtype record.pwnlib_msgtype = 'animated' msg = "%s\n" % self.format(record) # we enrich the `Progress` object to keep track of the spinner if not hasattr(progress, '_spinner_handle'): spinner_handle = term.output('') msg_handle = term.output(msg) stop = threading.Event() def spin(): '''Wheeeee!''' state = 0 states = random.choice(spinners.spinners) while True: prefix = '[%s] ' % _spinner_style(states[state]) spinner_handle.update(prefix) state = (state + 1) % len(states) if stop.wait(0.1): break t = Thread(target = spin) t.daemon = True t.start() progress._spinner_handle = spinner_handle progress._msg_handle = msg_handle progress._stop_event = stop progress._spinner_thread = t else: progress._msg_handle.update(msg) # if the message type was not a status message update, then we should # stop the spinner if msgtype != 'status': progress._stop_event.set() progress._spinner_thread.join() style, symb = _msgtype_prefixes[msgtype] prefix = '[%s] ' % style(symb) progress._spinner_handle.update(prefix) class Formatter(logging.Formatter): """ Logging formatter which performs custom formatting for log records containing the ``'pwnlib_msgtype'`` attribute. Other records are formatted using the `logging` modules default formatter. If ``'pwnlib_msgtype'`` is set, it performs the following actions: * A prefix looked up in `_msgtype_prefixes` is prepended to the message. * The message is prefixed such that it starts on column four. * If the message spans multiple lines they are split, and all subsequent lines are indented. This formatter is used by the handler installed on the ``'pwnlib'`` logger. """ # Indentation from the left side of the terminal. # All log messages will be indented at list this far. indent = ' ' # Newline, followed by an indent. Used to wrap multiple lines. nlindent = '\n' + indent def format(self, record): # use the default formatter to actually format the record msg = super(Formatter, self).format(record) # then put on a prefix symbol according to the message type msgtype = getattr(record, 'pwnlib_msgtype', None) # if 'pwnlib_msgtype' is not set (or set to `None`) we just return the # message as it is if msgtype is None: return msg if msgtype in _msgtype_prefixes: style, symb = _msgtype_prefixes[msgtype] prefix = '[%s] ' % style(symb) elif msgtype == 'indented': prefix = self.indent elif msgtype == 'animated': # the handler will take care of updating the spinner, so we will # not include it here prefix = '' else: # this should never happen prefix = '[?] ' msg = prefix + msg msg = self.nlindent.join(msg.splitlines()) return msg # we keep a dictionary of loggers such that multiple calls to `getLogger` with # the same name will return the same logger def getLogger(name): return Logger(logging.getLogger(name)) class LogfileHandler(logging.FileHandler): def __init__(self): super(LogfileHandler, self).__init__('', delay=1) @property def stream(self): return context.log_file @stream.setter def stream(self, value): pass def handle(self, *a, **kw): if self.stream.name is not None: super(LogfileHandler, self).handle(*a, **kw) iso_8601 = '%Y-%m-%dT%H:%M:%S' fmt = '%(asctime)s:%(levelname)s:%(name)s:%(message)s' log_file = LogfileHandler() log_file.setFormatter(logging.Formatter(fmt, iso_8601)) # # The root 'pwnlib' logger is declared here. To change the target of all # 'pwntools'-specific logging, only this logger needs to be changed. # # Logging cascades upward through the hierarchy, # so the only point that should ever need to be # modified is the root 'pwnlib' logger. # # For example: # map(rootlogger.removeHandler, rootlogger.handlers) # logger.addHandler(myCoolPitchingHandler) # rootlogger = getLogger('pwnlib') console = Handler() formatter = Formatter() console.setFormatter(formatter) def install_default_handler(): '''install_default_handler() Instantiates a :class:`Handler` and :class:`Formatter` and installs them for the ``pwnlib`` root logger. This function is automatically called from when importing :mod:`pwn`. ''' logger = logging.getLogger('pwnlib') if console not in logger.handlers: logger.addHandler(console) logger.addHandler(log_file) logger.setLevel(1)
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import rows import os from timeit import default_timer import json output_path = '../package/data/' class Brasilio(object): def __init__(self, output_path='../package/data/', verbose=False): self.verbose = verbose self.output_path = output_path self.timer = default_timer def __enter__(self): # Cria diretório package if not os.path.exists(self.output_path): os.makedirs(self.output_path) # Cria resouces.py vazio json.dump([], open("resources.json", "w"), indent=2) # Start Timer self.start = self.timer() return self def __exit__(self, *args): # Cria datapackage create_datapackage(self.output_path, verbose=False) # End Timer end = self.timer() self.elapsed_secs = end - self.start self.elapsed = self.elapsed_secs # millisecs if self.verbose: print('Sucesso!\n Sua captura demorou: {0:.2f} s'.format(self.elapsed)) def generate_resources(filename, verbose=False): data_path = os.path.join(output_path, filename) if verbose: print('Reading Data') data = rows.import_from_csv(data_path) translate = {int: 'integer', str: 'string'} resource = {'format': "csv", "url": "http://brasil.io/dataset/{}?format=csv".format(filename.split('.')[0]), "path": data_path, "profile": "tabular-data-resource", 'schema': { 'fields': []} } for i, field in enumerate(data.field_names): resource['schema']['fields'].append({'name': field, 'type': translate[data.field_types[i].TYPE[0]]}) if verbose: print('Writing resources.json') # print(type(resources)) # print(json.dumps(resources)) resources = json.load(open("resources.json", "r")) resources.append(resource) json.dump(resources, open("resources.json", "w"), indent=2) def create_datapackage(output_path, verbose=False): # Criar o datapackage.json if verbose: print("Criando datapackage.json") with open("metadata.json", "r") as mfd: output = json.load(mfd) with open("resources.json", "r") as rfd: output['resources'] = json.load(rfd) with open("../package/datapackage.json", "w") as datapackage: json.dump(output, datapackage, indent=2) if __name__ == '__main__': pass
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#!/usr/bin/env python3 import os import pathlib import sys import subprocess def has_cargo_fmt(): """Runs a quick check to see if cargo fmt is installed.""" try: c = subprocess.run(["cargo", "fmt", "--", "--help"], capture_output=True) except OSError: return False else: return c.returncode == 0 def get_modified_files(): """Returns a list of all modified files.""" c = subprocess.run( ["git", "diff-index", "--cached", "--name-only", "HEAD"], capture_output=True ) return [pathlib.Path(os.fsdecode(p)) for p in c.stdout.splitlines()] def run_format_check(files): rust_files = [x for x in files if x.suffix == "rs" and x.isfile()] if not rust_files: return 0 ret = subprocess.run( ["cargo", "fmt", "--", "--check", "--color=always"] + rust_files ) if ret.returncode != 0: print("", file=sys.stderr) print( "\033[1m\033[2minfo: to fix this run `cargo fmt --all` and " "commit again\033[0m", file=sys.stderr, ) return ret.returncode def main(): if not has_cargo_fmt(): print("warning: cargo fmt not installed") return sys.exit(run_format_check(get_modified_files())) if __name__ == "__main__": main()
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import os import distutils.spawn import mpi4py from mpi4py import MPI def check_mpi(): mpiexec_path, _ = os.path.split(distutils.spawn.find_executable("mpiexec")) for executable, path in mpi4py.get_config().items(): if executable not in ['mpicc', 'mpicxx', 'mpif77', 'mpif90', 'mpifort']: continue if mpiexec_path not in path: raise ImportError("mpi4py may not be configured against the same version of 'mpiexec' that you are using. The 'mpiexec' path is {mpiexec_path} and mpi4py.get_config() returns:\n{mpi4py_config}\n".format(mpiexec_path=mpiexec_path, mpi4py_config=mpi4py.get_config())) if 'Open MPI' not in MPI.get_vendor(): raise ImportError("mpi4py must have been installed against Open MPI in order for StructOpt to function correctly.") vendor_number = ".".join([str(x) for x in MPI.get_vendor()[1]]) if vendor_number not in mpiexec_path: raise ImportError("The MPI version that mpi4py was compiled against does not match the version of 'mpiexec'. mpi4py's version number is {}, and mpiexec's path is {}".format(MPI.get_vendor(), mpiexec_path)) check_mpi()
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import queue import time import numpy as np class CameraInformation: def __init__(self, cam_id: str): self._frame_queue: queue.Queue = queue.Queue(maxsize=1) self._frame_shape = None self._last_frame_time = None self.is_online = True self.node_id = cam_id def write_frame(self, frame): try: self._frame_queue.get_nowait() except queue.Empty: pass self._frame_shape = frame.shape self._last_frame_time = time.time() self._frame_queue.put_nowait(frame) def read_frame(self,): try: frame = self._frame_queue.get(timeout=2) if not self.is_online: self.is_online = True return frame except queue.Empty: if self.is_online: self.is_online = False return np.zeros(self._frame_shape)
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# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT from __future__ import unicode_literals from ..utils import Generate5tt def test_Generate5tt_inputs(): input_map = dict( algorithm=dict( argstr='%s', mandatory=True, position=-3, ), args=dict(argstr='%s', ), bval_scale=dict(argstr='-bvalue_scaling %s', ), environ=dict( nohash=True, usedefault=True, ), grad_file=dict( argstr='-grad %s', extensions=None, xor=['grad_fsl'], ), grad_fsl=dict( argstr='-fslgrad %s %s', xor=['grad_file'], ), in_bval=dict(extensions=None, ), in_bvec=dict( argstr='-fslgrad %s %s', extensions=None, ), in_file=dict( argstr='%s', extensions=None, mandatory=True, position=-2, ), nthreads=dict( argstr='-nthreads %d', nohash=True, ), out_file=dict( argstr='%s', extensions=None, mandatory=True, position=-1, ), ) inputs = Generate5tt.input_spec() for key, metadata in list(input_map.items()): for metakey, value in list(metadata.items()): assert getattr(inputs.traits()[key], metakey) == value def test_Generate5tt_outputs(): output_map = dict(out_file=dict(extensions=None, ), ) outputs = Generate5tt.output_spec() for key, metadata in list(output_map.items()): for metakey, value in list(metadata.items()): assert getattr(outputs.traits()[key], metakey) == value
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#!/usr/bin/env python from setuptools import setup def readme(): with open('README.md') as f: return f.read() setup( name='impasse', # Version chosen for parity with Assimp since we need ABI compatibility version='5.0.6', license='BSD', description='Alternate Python bindings for the Open Asset Import Library (ASSIMP)', long_description=readme(), long_description_content_type="text/markdown", url='https://github.com/SaladDais/Impasse', author='Salad Dais', author_email='SaladDais@users.noreply.github.com', packages=['impasse'], data_files=[ ('share/impasse', ['README.md']), # TODO: Make these proper console scripts # ('share/examples/impasse', ['scripts/' + f for f in os.listdir('scripts/')]), ], install_requires=['numpy', 'cffi'], python_requires='>=3.7', zip_safe=False, tests_require=[ "pytest", ], test_suite='tests', )
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from __future__ import absolute_import from __future__ import print_function import sys import os # the next line can be removed after installation sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.dirname( os.path.dirname(os.path.dirname(os.path.abspath(__file__))))))) from veriloggen import * import veriloggen.thread as vthread import veriloggen.types.axi as axi def mkLed(): m = Module('blinkled') clk = m.Input('CLK') rst = m.Input('RST') datawidth = 32 addrwidth = 10 myaxi = vthread.AXIM(m, 'myaxi', clk, rst, datawidth) ram_a = vthread.RAM(m, 'ram_a', clk, rst, datawidth, addrwidth) ram_b = vthread.RAM(m, 'ram_b', clk, rst, datawidth, addrwidth) ram_c = vthread.RAM(m, 'ram_c', clk, rst, datawidth, addrwidth) mulstrm = vthread.Stream(m, 'mul_stream', clk, rst) mulx = mulstrm.source('x') muly = mulstrm.source('y') mulz = mulx * muly mulstrm.sink(mulz, 'z') macstrm = vthread.Stream(m, 'mac_stream', clk, rst) a = macstrm.source('a') b = macstrm.source('b') a = a + 1 b = b + 1 sub = macstrm.substream(mulstrm) sub.to_source('x', a) sub.to_source('y', b) c = sub.from_sink('z') size = macstrm.parameter('size') sum, sum_valid = macstrm.ReduceAddValid(c, size) macstrm.sink(sum, 'sum', when=sum_valid, when_name='sum_valid') actstrm = vthread.Stream(m, 'act_stream', clk, rst) a = actstrm.source('a') b = actstrm.source('b') a = a + 1 b = b + 1 a = a + 1 b = b + 1 sub = actstrm.substream(mulstrm) sub.to_source('x', a) sub.to_source('y', b) c = sub.from_sink('z') size = actstrm.parameter('size') sum, sum_valid = actstrm.ReduceAddValid(c, size) sum = actstrm.Mux(sum > 0, sum, 0) actstrm.sink(sum, 'sum', when=sum_valid, when_name='sum_valid') all_ok = m.TmpReg(initval=0) def comp_stream_mul(size, offset): mulstrm.set_source('x', ram_a, offset, size) mulstrm.set_source('y', ram_b, offset, size) mulstrm.set_sink('z', ram_c, offset, size) mulstrm.run() mulstrm.join() def comp_stream_mac(size, offset): macstrm.set_source('a', ram_a, offset, size) macstrm.set_source('b', ram_b, offset, size) macstrm.set_parameter('size', size) macstrm.set_sink('sum', ram_c, offset, 1) macstrm.run() macstrm.join() def comp_stream_act(size, offset): actstrm.set_source('a', ram_a, offset, size) actstrm.set_source('b', ram_b, offset, size) actstrm.set_parameter('size', size) actstrm.set_sink('sum', ram_c, offset, 1) actstrm.run() actstrm.join() def comp_sequential_mul(size, offset): sum = 0 for i in range(size): a = ram_a.read(i + offset) b = ram_b.read(i + offset) sum = a * b ram_c.write(i + offset, sum) def comp_sequential_mac(size, offset): sum = 0 for i in range(size): a = ram_a.read(i + offset) + 1 b = ram_b.read(i + offset) + 1 sum += a * b ram_c.write(offset, sum) def comp_sequential_act(size, offset): sum = 0 for i in range(size): a = ram_a.read(i + offset) + 1 + 1 b = ram_b.read(i + offset) + 1 + 1 sum += a * b if sum <= 0: sum = 0 ram_c.write(offset, sum) def check(size, offset_stream, offset_seq): for i in range(size): st = ram_c.read(i + offset_stream) sq = ram_c.read(i + offset_seq) if vthread.verilog.NotEql(st, sq): all_ok.value = False if all_ok: print('# verify: PASSED') else: print('# verify: FAILED') def comp(size): all_ok.value = True # mul # stream offset = 0 myaxi.dma_read(ram_a, offset, 0, size) myaxi.dma_read(ram_b, offset, 512, size) comp_stream_mul(size, offset) myaxi.dma_write(ram_c, offset, 1024, size) # sequential offset = size myaxi.dma_read(ram_a, offset, 0, size) myaxi.dma_read(ram_b, offset, 512, size) comp_sequential_mul(size, offset) myaxi.dma_write(ram_c, offset, 1024 * 2, size) # verification print('# MUL') check(size, 0, offset) # mac # stream offset = 0 myaxi.dma_read(ram_a, offset, 0, size) myaxi.dma_read(ram_b, offset, 512, size) comp_stream_mac(size, offset) myaxi.dma_write(ram_c, offset, 1024, 1) # sequential offset = size myaxi.dma_read(ram_a, offset, 0, size) myaxi.dma_read(ram_b, offset, 512, size) comp_sequential_mac(size, offset) myaxi.dma_write(ram_c, offset, 1024 * 2, 1) # verification print('# MAC') check(1, 0, offset) # act # stream offset = 0 myaxi.dma_read(ram_a, offset, 0, size) myaxi.dma_read(ram_b, offset, 512, size) comp_stream_act(size, offset) myaxi.dma_write(ram_c, offset, 1024, 1) # sequential offset = size myaxi.dma_read(ram_a, offset, 0, size) myaxi.dma_read(ram_b, offset, 512, size) comp_sequential_act(size, offset) myaxi.dma_write(ram_c, offset, 1024 * 2, 1) # verification print('# ACT') check(1, 0, offset) vthread.finish() th = vthread.Thread(m, 'th_comp', clk, rst, comp) fsm = th.start(32) try: actstrm.draw_graph() except: pass return m def mkTest(memimg_name=None): m = Module('test') # target instance led = mkLed() # copy paras and ports params = m.copy_params(led) ports = m.copy_sim_ports(led) clk = ports['CLK'] rst = ports['RST'] memory = axi.AxiMemoryModel(m, 'memory', clk, rst, memimg_name=memimg_name) memory.connect(ports, 'myaxi') uut = m.Instance(led, 'uut', params=m.connect_params(led), ports=m.connect_ports(led)) #simulation.setup_waveform(m, uut) simulation.setup_clock(m, clk, hperiod=5) init = simulation.setup_reset(m, rst, m.make_reset(), period=100) init.add( Delay(1000000), Systask('finish'), ) return m def run(filename='tmp.v', simtype='iverilog', outputfile=None): if outputfile is None: outputfile = os.path.splitext(os.path.basename(__file__))[0] + '.out' memimg_name = 'memimg_' + outputfile test = mkTest(memimg_name=memimg_name) if filename is not None: test.to_verilog(filename) sim = simulation.Simulator(test, sim=simtype) rslt = sim.run(outputfile=outputfile) lines = rslt.splitlines() if simtype == 'iverilog' or (simtype == 'verilator' and lines[-1].startswith('-')): rslt = '\n'.join(lines[:-1]) return rslt if __name__ == '__main__': rslt = run(filename='tmp.v') print(rslt)
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# Licensed under the Apache License: http://www.apache.org/licenses/LICENSE-2.0 # For details: https://github.com/nedbat/coveragepy/blob/master/NOTICE.txt """Tests for coverage.numbits""" import json import sqlite3 from hypothesis import example, given, settings from hypothesis.strategies import sets, integers from coverage import env from coverage.numbits import ( nums_to_numbits, numbits_to_nums, numbits_union, numbits_intersection, numbits_any_intersection, num_in_numbits, register_sqlite_functions, ) from tests.coveragetest import CoverageTest # Hypothesis-generated line number data line_numbers = integers(min_value=1, max_value=9999) line_number_sets = sets(line_numbers) # When coverage-testing ourselves, hypothesis complains about a test being # flaky because the first run exceeds the deadline (and fails), and the second # run succeeds. Disable the deadline if we are coverage-testing. default_settings = settings() if env.METACOV: default_settings = settings(default_settings, deadline=None) def good_numbits(numbits): """Assert that numbits is good.""" # It shouldn't end with a zero byte, that should have been trimmed off. assert (not numbits) or (numbits[-1] != 0) class NumbitsOpTest(CoverageTest): """Tests of the numbits operations in numbits.py.""" run_in_temp_dir = False @given(line_number_sets) @settings(default_settings) def test_conversion(self, nums): numbits = nums_to_numbits(nums) good_numbits(numbits) nums2 = numbits_to_nums(numbits) assert nums == set(nums2) @given(line_number_sets, line_number_sets) @settings(default_settings) def test_union(self, nums1, nums2): nb1 = nums_to_numbits(nums1) good_numbits(nb1) nb2 = nums_to_numbits(nums2) good_numbits(nb2) nbu = numbits_union(nb1, nb2) good_numbits(nbu) union = numbits_to_nums(nbu) assert nums1 | nums2 == set(union) @given(line_number_sets, line_number_sets) @settings(default_settings) def test_intersection(self, nums1, nums2): nb1 = nums_to_numbits(nums1) good_numbits(nb1) nb2 = nums_to_numbits(nums2) good_numbits(nb2) nbi = numbits_intersection(nb1, nb2) good_numbits(nbi) intersection = numbits_to_nums(nbi) assert nums1 & nums2 == set(intersection) @given(line_number_sets, line_number_sets) @settings(default_settings) def test_any_intersection(self, nums1, nums2): nb1 = nums_to_numbits(nums1) good_numbits(nb1) nb2 = nums_to_numbits(nums2) good_numbits(nb2) inter = numbits_any_intersection(nb1, nb2) expect = bool(nums1 & nums2) assert expect == bool(inter) @given(line_numbers, line_number_sets) @settings(default_settings) @example(152, {144}) def test_num_in_numbits(self, num, nums): numbits = nums_to_numbits(nums) good_numbits(numbits) is_in = num_in_numbits(num, numbits) assert (num in nums) == is_in class NumbitsSqliteFunctionTest(CoverageTest): """Tests of the SQLite integration for numbits functions.""" run_in_temp_dir = False def setup_test(self): super().setup_test() conn = sqlite3.connect(":memory:") register_sqlite_functions(conn) self.cursor = conn.cursor() self.cursor.execute("create table data (id int, numbits blob)") self.cursor.executemany( "insert into data (id, numbits) values (?, ?)", [ (i, nums_to_numbits(range(i, 100, i))) for i in range(1, 11) ] ) self.addCleanup(self.cursor.close) def test_numbits_union(self): res = self.cursor.execute( "select numbits_union(" + "(select numbits from data where id = 7)," + "(select numbits from data where id = 9)" + ")" ) expected = [ 7, 9, 14, 18, 21, 27, 28, 35, 36, 42, 45, 49, 54, 56, 63, 70, 72, 77, 81, 84, 90, 91, 98, 99, ] answer = numbits_to_nums(list(res)[0][0]) assert expected == answer def test_numbits_intersection(self): res = self.cursor.execute( "select numbits_intersection(" + "(select numbits from data where id = 7)," + "(select numbits from data where id = 9)" + ")" ) answer = numbits_to_nums(list(res)[0][0]) assert [63] == answer def test_numbits_any_intersection(self): res = self.cursor.execute( "select numbits_any_intersection(?, ?)", (nums_to_numbits([1, 2, 3]), nums_to_numbits([3, 4, 5])) ) answer = [any_inter for (any_inter,) in res] assert [1] == answer res = self.cursor.execute( "select numbits_any_intersection(?, ?)", (nums_to_numbits([1, 2, 3]), nums_to_numbits([7, 8, 9])) ) answer = [any_inter for (any_inter,) in res] assert [0] == answer def test_num_in_numbits(self): res = self.cursor.execute("select id, num_in_numbits(12, numbits) from data order by id") answer = [is_in for (id, is_in) in res] assert [1, 1, 1, 1, 0, 1, 0, 0, 0, 0] == answer def test_numbits_to_nums(self): res = self.cursor.execute("select numbits_to_nums(?)", [nums_to_numbits([1, 2, 3])]) assert [1, 2, 3] == json.loads(res.fetchone()[0])
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#!/usr/bin/env python3 import os import math from cereal import car, log from common.numpy_fast import clip, interp from common.realtime import sec_since_boot, config_realtime_process, Priority, Ratekeeper, DT_CTRL from common.profiler import Profiler from common.params import Params, put_nonblocking import cereal.messaging as messaging from selfdrive.config import Conversions as CV from selfdrive.swaglog import cloudlog from selfdrive.boardd.boardd import can_list_to_can_capnp from selfdrive.car.car_helpers import get_car, get_startup_event, get_one_can from selfdrive.controls.lib.lane_planner import CAMERA_OFFSET from selfdrive.controls.lib.drive_helpers import update_v_cruise, initialize_v_cruise from selfdrive.controls.lib.longcontrol import LongControl, STARTING_TARGET_SPEED from selfdrive.controls.lib.latcontrol_pid import LatControlPID from selfdrive.controls.lib.latcontrol_indi import LatControlINDI from selfdrive.controls.lib.latcontrol_lqr import LatControlLQR from selfdrive.controls.lib.latcontrol_angle import LatControlAngle from selfdrive.controls.lib.events import Events, ET from selfdrive.controls.lib.alertmanager import AlertManager from selfdrive.controls.lib.vehicle_model import VehicleModel from selfdrive.controls.lib.longitudinal_planner import LON_MPC_STEP from selfdrive.locationd.calibrationd import Calibration from selfdrive.hardware import HARDWARE, TICI from selfdrive.car.hyundai.scc_smoother import SccSmoother from selfdrive.ntune import ntune_get, ntune_isEnabled LDW_MIN_SPEED = 31 * CV.MPH_TO_MS LANE_DEPARTURE_THRESHOLD = 0.1 STEER_ANGLE_SATURATION_TIMEOUT = 1.0 / DT_CTRL STEER_ANGLE_SATURATION_THRESHOLD = 2.5 # Degrees SIMULATION = "SIMULATION" in os.environ NOSENSOR = "NOSENSOR" in os.environ IGNORE_PROCESSES = set(["rtshield", "uploader", "deleter", "loggerd", "logmessaged", "tombstoned", "logcatd", "proclogd", "clocksd", "updated", "timezoned", "manage_athenad"]) ThermalStatus = log.DeviceState.ThermalStatus State = log.ControlsState.OpenpilotState PandaType = log.PandaState.PandaType Desire = log.LateralPlan.Desire LaneChangeState = log.LateralPlan.LaneChangeState LaneChangeDirection = log.LateralPlan.LaneChangeDirection EventName = car.CarEvent.EventName class Controls: def __init__(self, sm=None, pm=None, can_sock=None): config_realtime_process(4 if TICI else 3, Priority.CTRL_HIGH) # Setup sockets self.pm = pm if self.pm is None: self.pm = messaging.PubMaster(['sendcan', 'controlsState', 'carState', 'carControl', 'carEvents', 'carParams']) self.camera_packets = ["roadCameraState", "driverCameraState"] if TICI: self.camera_packets.append("wideRoadCameraState") self.sm = sm if self.sm is None: ignore = ['driverCameraState', 'managerState'] if SIMULATION else None self.sm = messaging.SubMaster(['deviceState', 'pandaState', 'modelV2', 'liveCalibration', 'driverMonitoringState', 'longitudinalPlan', 'lateralPlan', 'liveLocationKalman', 'managerState', 'liveParameters', 'radarState'] + self.camera_packets, ignore_alive=ignore, ignore_avg_freq=['radarState', 'longitudinalPlan']) self.can_sock = can_sock if can_sock is None: can_timeout = None if os.environ.get('NO_CAN_TIMEOUT', False) else 100 self.can_sock = messaging.sub_sock('can', timeout=can_timeout) if TICI: self.log_sock = messaging.sub_sock('androidLog') # wait for one pandaState and one CAN packet hw_type = messaging.recv_one(self.sm.sock['pandaState']).pandaState.pandaType has_relay = hw_type in [PandaType.blackPanda, PandaType.uno, PandaType.dos] print("Waiting for CAN messages...") get_one_can(self.can_sock) self.CI, self.CP = get_car(self.can_sock, self.pm.sock['sendcan'], has_relay) # read params params = Params() self.is_metric = params.get_bool("IsMetric") self.is_ldw_enabled = params.get_bool("IsLdwEnabled") self.enable_lte_onroad = params.get_bool("EnableLteOnroad") community_feature_toggle = params.get_bool("CommunityFeaturesToggle") openpilot_enabled_toggle = params.get_bool("OpenpilotEnabledToggle") passive = params.get_bool("Passive") or not openpilot_enabled_toggle # detect sound card presence and ensure successful init sounds_available = HARDWARE.get_sound_card_online() car_recognized = self.CP.carName != 'mock' fuzzy_fingerprint = self.CP.fuzzyFingerprint # If stock camera is disconnected, we loaded car controls and it's not dashcam mode controller_available = self.CP.enableCamera and self.CI.CC is not None and not passive and not self.CP.dashcamOnly community_feature = self.CP.communityFeature or fuzzy_fingerprint community_feature_disallowed = community_feature and (not community_feature_toggle) self.read_only = not car_recognized or not controller_available or \ self.CP.dashcamOnly or community_feature_disallowed if self.read_only: self.CP.safetyModel = car.CarParams.SafetyModel.noOutput # Write CarParams for radard cp_bytes = self.CP.to_bytes() params.put("CarParams", cp_bytes) put_nonblocking("CarParamsCache", cp_bytes) self.CC = car.CarControl.new_message() self.AM = AlertManager() self.events = Events() self.LoC = LongControl(self.CP, self.CI.compute_gb) self.VM = VehicleModel(self.CP) if self.CP.steerControlType == car.CarParams.SteerControlType.angle: self.LaC = LatControlAngle(self.CP) elif self.CP.lateralTuning.which() == 'pid': self.LaC = LatControlPID(self.CP) elif self.CP.lateralTuning.which() == 'indi': self.LaC = LatControlINDI(self.CP) elif self.CP.lateralTuning.which() == 'lqr': self.LaC = LatControlLQR(self.CP) self.initialized = False self.state = State.disabled self.enabled = False self.active = False self.can_rcv_error = False self.soft_disable_timer = 0 self.v_cruise_kph = 255 self.v_cruise_kph_last = 0 self.mismatch_counter = 0 self.can_error_counter = 0 self.last_blinker_frame = 0 self.saturated_count = 0 self.distance_traveled = 0 self.last_functional_fan_frame = 0 self.events_prev = [] self.current_alert_types = [ET.PERMANENT] self.logged_comm_issue = False # scc smoother self.is_cruise_enabled = False self.cruiseVirtualMaxSpeed = 0 self.clu_speed_ms = 0. self.apply_accel = 0. self.fused_accel = 0. self.lead_drel = 0. self.aReqValue = 0. self.aReqValueMin = 0. self.aReqValueMax = 0. self.angle_steers_des = 0. # TODO: no longer necessary, aside from process replay self.sm['liveParameters'].valid = True self.startup_event = get_startup_event(car_recognized, controller_available, fuzzy_fingerprint) if not sounds_available: self.events.add(EventName.soundsUnavailable, static=True) if community_feature_disallowed: self.events.add(EventName.communityFeatureDisallowed, static=True) if not car_recognized: self.events.add(EventName.carUnrecognized, static=True) elif self.read_only: self.events.add(EventName.dashcamMode, static=True) # controlsd is driven by can recv, expected at 100Hz self.rk = Ratekeeper(100, print_delay_threshold=None) self.prof = Profiler(False) # off by default def update_events(self, CS): """Compute carEvents from carState""" self.events.clear() self.events.add_from_msg(CS.events) self.events.add_from_msg(self.sm['driverMonitoringState'].events) # Handle startup event if self.startup_event is not None: self.events.add(self.startup_event) self.startup_event = None # Don't add any more events if not initialized if not self.initialized: self.events.add(EventName.controlsInitializing) return # Create events for battery, temperature, disk space, and memory if self.sm['deviceState'].batteryPercent < 1 and self.sm['deviceState'].chargingError: # at zero percent battery, while discharging, OP should not allowed self.events.add(EventName.lowBattery) if self.sm['deviceState'].thermalStatus >= ThermalStatus.red: self.events.add(EventName.overheat) if self.sm['deviceState'].freeSpacePercent < 7: # under 7% of space free no enable allowed self.events.add(EventName.outOfSpace) if self.sm['deviceState'].memoryUsagePercent > 90: self.events.add(EventName.lowMemory) # Alert if fan isn't spinning for 5 seconds if self.sm['pandaState'].pandaType in [PandaType.uno, PandaType.dos]: if self.sm['pandaState'].fanSpeedRpm == 0 and self.sm['deviceState'].fanSpeedPercentDesired > 50: if (self.sm.frame - self.last_functional_fan_frame) * DT_CTRL > 5.0: self.events.add(EventName.fanMalfunction) else: self.last_functional_fan_frame = self.sm.frame # Handle calibration status cal_status = self.sm['liveCalibration'].calStatus if cal_status != Calibration.CALIBRATED: if cal_status == Calibration.UNCALIBRATED: self.events.add(EventName.calibrationIncomplete) else: self.events.add(EventName.calibrationInvalid) # Handle lane change if self.sm['lateralPlan'].laneChangeState == LaneChangeState.preLaneChange: direction = self.sm['lateralPlan'].laneChangeDirection if (CS.leftBlindspot and direction == LaneChangeDirection.left) or \ (CS.rightBlindspot and direction == LaneChangeDirection.right): self.events.add(EventName.laneChangeBlocked) elif self.sm['lateralPlan'].autoLaneChangeEnabled and self.sm['lateralPlan'].autoLaneChangeTimer > 0: self.events.add(EventName.autoLaneChange) else: if direction == LaneChangeDirection.left: self.events.add(EventName.preLaneChangeLeft) else: self.events.add(EventName.preLaneChangeRight) elif self.sm['lateralPlan'].laneChangeState in [LaneChangeState.laneChangeStarting, LaneChangeState.laneChangeFinishing]: self.events.add(EventName.laneChange) if self.can_rcv_error or not CS.canValid: self.events.add(EventName.canError) safety_mismatch = self.sm['pandaState'].safetyModel != self.CP.safetyModel or self.sm['pandaState'].safetyParam != self.CP.safetyParam if safety_mismatch or self.mismatch_counter >= 200: self.events.add(EventName.controlsMismatch) if not self.sm['liveParameters'].valid: self.events.add(EventName.vehicleModelInvalid) if len(self.sm['radarState'].radarErrors): self.events.add(EventName.radarFault) elif not self.sm.valid["pandaState"]: self.events.add(EventName.usbError) elif not self.sm.all_alive_and_valid(): self.events.add(EventName.commIssue) if not self.logged_comm_issue: cloudlog.error(f"commIssue - valid: {self.sm.valid} - alive: {self.sm.alive}") self.logged_comm_issue = True else: self.logged_comm_issue = False if not self.sm['lateralPlan'].mpcSolutionValid and not (EventName.turningIndicatorOn in self.events.names): self.events.add(EventName.plannerError) if not self.sm['liveLocationKalman'].sensorsOK and not NOSENSOR: if self.sm.frame > 5 / DT_CTRL: # Give locationd some time to receive all the inputs self.events.add(EventName.sensorDataInvalid) if not self.sm['liveLocationKalman'].posenetOK: self.events.add(EventName.posenetInvalid) if not self.sm['liveLocationKalman'].deviceStable: self.events.add(EventName.deviceFalling) if log.PandaState.FaultType.relayMalfunction in self.sm['pandaState'].faults: self.events.add(EventName.relayMalfunction) if self.sm['longitudinalPlan'].fcw or (self.enabled and self.sm['modelV2'].meta.hardBrakePredicted): self.events.add(EventName.fcw) if TICI and self.enable_lte_onroad: logs = messaging.drain_sock(self.log_sock, wait_for_one=False) messages = [] for m in logs: try: messages.append(m.androidLog.message) except UnicodeDecodeError: pass for err in ["ERROR_CRC", "ERROR_ECC", "ERROR_STREAM_UNDERFLOW", "APPLY FAILED"]: for m in messages: if err not in m: continue csid = m.split("CSID:")[-1].split(" ")[0] evt = {"0": EventName.wideRoadCameraError, "1": EventName.roadCameraError, "2": EventName.driverCameraError}.get(csid, None) if evt is not None: self.events.add(evt) # TODO: fix simulator if not SIMULATION: #if not NOSENSOR: # if not self.sm['liveLocationKalman'].gpsOK and (self.distance_traveled > 1000) and \ # (not TICI or self.enable_lte_onroad): # # Not show in first 1 km to allow for driving out of garage. This event shows after 5 minutes # self.events.add(EventName.noGps) if not self.sm.all_alive(self.camera_packets): self.events.add(EventName.cameraMalfunction) if self.sm['modelV2'].frameDropPerc > 20: self.events.add(EventName.modeldLagging) # Check if all manager processes are running not_running = set(p.name for p in self.sm['managerState'].processes if not p.running) if self.sm.rcv_frame['managerState'] and (not_running - IGNORE_PROCESSES): self.events.add(EventName.processNotRunning) # Only allow engagement with brake pressed when stopped behind another stopped car #if CS.brakePressed and self.sm['longitudinalPlan'].vTargetFuture >= STARTING_TARGET_SPEED \ #and self.CP.openpilotLongitudinalControl and CS.vEgo < 0.3: #self.events.add(EventName.noTarget) def data_sample(self): """Receive data from sockets and update carState""" # Update carState from CAN can_strs = messaging.drain_sock_raw(self.can_sock, wait_for_one=True) CS = self.CI.update(self.CC, can_strs) self.sm.update(0) all_valid = CS.canValid and self.sm.all_alive_and_valid() if not self.initialized and (all_valid or self.sm.frame * DT_CTRL > 2.0): self.initialized = True Params().put_bool("ControlsReady", True) # Check for CAN timeout if not can_strs: self.can_error_counter += 1 self.can_rcv_error = True else: self.can_rcv_error = False # When the panda and controlsd do not agree on controls_allowed # we want to disengage openpilot. However the status from the panda goes through # another socket other than the CAN messages and one can arrive earlier than the other. # Therefore we allow a mismatch for two samples, then we trigger the disengagement. if not self.enabled: self.mismatch_counter = 0 if not self.sm['pandaState'].controlsAllowed and self.enabled: self.mismatch_counter += 1 self.distance_traveled += CS.vEgo * DT_CTRL return CS def state_transition(self, CS): """Compute conditional state transitions and execute actions on state transitions""" self.v_cruise_kph_last = self.v_cruise_kph # if stock cruise is completely disabled, then we can use our own set speed logic self.CP.enableCruise = self.CI.CP.enableCruise #if not self.CP.enableCruise: # self.v_cruise_kph = update_v_cruise(self.v_cruise_kph, CS.buttonEvents, self.enabled, self.is_metric) #elif self.CP.enableCruise and CS.cruiseState.enabled: # self.v_cruise_kph = CS.cruiseState.speed * CV.MS_TO_KPH SccSmoother.update_cruise_buttons(self, CS, self.CP.openpilotLongitudinalControl) # decrease the soft disable timer at every step, as it's reset on # entrance in SOFT_DISABLING state self.soft_disable_timer = max(0, self.soft_disable_timer - 1) self.current_alert_types = [ET.PERMANENT] # ENABLED, PRE ENABLING, SOFT DISABLING if self.state != State.disabled: # user and immediate disable always have priority in a non-disabled state if self.events.any(ET.USER_DISABLE): self.state = State.disabled self.current_alert_types.append(ET.USER_DISABLE) elif self.events.any(ET.IMMEDIATE_DISABLE): self.state = State.disabled self.current_alert_types.append(ET.IMMEDIATE_DISABLE) else: # ENABLED if self.state == State.enabled: if self.events.any(ET.SOFT_DISABLE): self.state = State.softDisabling self.soft_disable_timer = 50 # 0.5s self.current_alert_types.append(ET.SOFT_DISABLE) # SOFT DISABLING elif self.state == State.softDisabling: if not self.events.any(ET.SOFT_DISABLE): # no more soft disabling condition, so go back to ENABLED self.state = State.enabled elif self.events.any(ET.SOFT_DISABLE) and self.soft_disable_timer > 0: self.current_alert_types.append(ET.SOFT_DISABLE) elif self.soft_disable_timer <= 0: self.state = State.disabled # PRE ENABLING elif self.state == State.preEnabled: if not self.events.any(ET.PRE_ENABLE): self.state = State.enabled else: self.current_alert_types.append(ET.PRE_ENABLE) # DISABLED elif self.state == State.disabled: if self.events.any(ET.ENABLE): if self.events.any(ET.NO_ENTRY): self.current_alert_types.append(ET.NO_ENTRY) else: if self.events.any(ET.PRE_ENABLE): self.state = State.preEnabled else: self.state = State.enabled self.current_alert_types.append(ET.ENABLE) self.v_cruise_kph = initialize_v_cruise(CS.vEgo, CS.buttonEvents, self.v_cruise_kph_last) # Check if actuators are enabled self.active = self.state == State.enabled or self.state == State.softDisabling if self.active: self.current_alert_types.append(ET.WARNING) # Check if openpilot is engaged self.enabled = self.active or self.state == State.preEnabled def state_control(self, CS): """Given the state, this function returns an actuators packet""" # Update VehicleModel params = self.sm['liveParameters'] x = max(params.stiffnessFactor, 0.1) #sr = max(params.steerRatio, 0.1) if ntune_isEnabled('useLiveSteerRatio'): sr = max(params.steerRatio, 0.1) else: sr = max(ntune_get('steerRatio'), 0.1) self.VM.update_params(x, sr) lat_plan = self.sm['lateralPlan'] long_plan = self.sm['longitudinalPlan'] actuators = car.CarControl.Actuators.new_message() if CS.leftBlinker or CS.rightBlinker: self.last_blinker_frame = self.sm.frame # State specific actions if not self.active: self.LaC.reset() self.LoC.reset(v_pid=CS.vEgo) long_plan_age = DT_CTRL * (self.sm.frame - self.sm.rcv_frame['longitudinalPlan']) # no greater than dt mpc + dt, to prevent too high extraps dt = min(long_plan_age, LON_MPC_STEP + DT_CTRL) + DT_CTRL a_acc_sol = long_plan.aStart + (dt / LON_MPC_STEP) * (long_plan.aTarget - long_plan.aStart) v_acc_sol = long_plan.vStart + dt * (a_acc_sol + long_plan.aStart) / 2.0 # Gas/Brake PID loop #actuators.gas, actuators.brake = self.LoC.update(self.active, CS, v_acc_sol, long_plan.vTargetFuture, a_acc_sol, self.CP) # scc smoother actuators.gas, actuators.brake = self.LoC.update(self.active and CS.cruiseState.speed > 1., CS, v_acc_sol, long_plan.vTargetFuture, a_acc_sol, self.CP, self.sm['radarState']) # Steering PID loop and lateral MPC actuators.steer, actuators.steeringAngleDeg, lac_log = self.LaC.update(self.active, CS, self.CP, self.VM, params, lat_plan) # Check for difference between desired angle and angle for angle based control angle_control_saturated = self.CP.steerControlType == car.CarParams.SteerControlType.angle and \ abs(actuators.steeringAngleDeg - CS.steeringAngleDeg) > STEER_ANGLE_SATURATION_THRESHOLD if angle_control_saturated and not CS.steeringPressed and self.active: self.saturated_count += 1 else: self.saturated_count = 0 # Send a "steering required alert" if saturation count has reached the limit if (lac_log.saturated and not CS.steeringPressed) or \ (self.saturated_count > STEER_ANGLE_SATURATION_TIMEOUT): if len(lat_plan.dPathPoints): # Check if we deviated from the path left_deviation = actuators.steer > 0 and lat_plan.dPathPoints[0] < -0.1 right_deviation = actuators.steer < 0 and lat_plan.dPathPoints[0] > 0.1 # if left_deviation or right_deviation: # self.events.add(EventName.steerSaturated) return actuators, v_acc_sol, a_acc_sol, lac_log def publish_logs(self, CS, start_time, actuators, v_acc, a_acc, lac_log): """Send actuators and hud commands to the car, send controlsstate and MPC logging""" CC = car.CarControl.new_message() CC.enabled = self.enabled CC.actuators = actuators CC.cruiseControl.override = True CC.cruiseControl.cancel = self.CP.enableCruise and not self.enabled and CS.cruiseState.enabled # Some override values for Honda # brake discount removes a sharp nonlinearity brake_discount = (1.0 - clip(actuators.brake * 3., 0.0, 1.0)) speed_override = max(0.0, (self.LoC.v_pid + CS.cruiseState.speedOffset) * brake_discount) CC.cruiseControl.speedOverride = float(speed_override if self.CP.enableCruise else 0.0) CC.cruiseControl.accelOverride = self.CI.calc_accel_override(CS.aEgo, self.sm['longitudinalPlan'].aTarget, CS.vEgo, self.sm['longitudinalPlan'].vTarget) CC.hudControl.setSpeed = float(self.v_cruise_kph * CV.KPH_TO_MS) CC.hudControl.speedVisible = self.enabled CC.hudControl.lanesVisible = self.enabled CC.hudControl.leadVisible = self.sm['longitudinalPlan'].hasLead right_lane_visible = self.sm['lateralPlan'].rProb > 0.5 left_lane_visible = self.sm['lateralPlan'].lProb > 0.5 CC.hudControl.rightLaneVisible = bool(right_lane_visible) CC.hudControl.leftLaneVisible = bool(left_lane_visible) recent_blinker = (self.sm.frame - self.last_blinker_frame) * DT_CTRL < 5.0 # 5s blinker cooldown ldw_allowed = self.is_ldw_enabled and CS.vEgo > LDW_MIN_SPEED and not recent_blinker \ and not self.active and self.sm['liveCalibration'].calStatus == Calibration.CALIBRATED meta = self.sm['modelV2'].meta if len(meta.desirePrediction) and ldw_allowed: l_lane_change_prob = meta.desirePrediction[Desire.laneChangeLeft - 1] r_lane_change_prob = meta.desirePrediction[Desire.laneChangeRight - 1] cameraOffset = ntune_get("cameraOffset") l_lane_close = left_lane_visible and (self.sm['modelV2'].laneLines[1].y[0] > -(1.08 + cameraOffset)) r_lane_close = right_lane_visible and (self.sm['modelV2'].laneLines[2].y[0] < (1.08 - cameraOffset)) CC.hudControl.leftLaneDepart = bool(l_lane_change_prob > LANE_DEPARTURE_THRESHOLD and l_lane_close) CC.hudControl.rightLaneDepart = bool(r_lane_change_prob > LANE_DEPARTURE_THRESHOLD and r_lane_close) if CC.hudControl.rightLaneDepart or CC.hudControl.leftLaneDepart: self.events.add(EventName.ldw) clear_event = ET.WARNING if ET.WARNING not in self.current_alert_types else None alerts = self.events.create_alerts(self.current_alert_types, [self.CP, self.sm, self.is_metric]) self.AM.add_many(self.sm.frame, alerts, self.enabled) self.AM.process_alerts(self.sm.frame, clear_event) CC.hudControl.visualAlert = self.AM.visual_alert if not self.read_only and self.initialized: # send car controls over can can_sends = self.CI.apply(CC, self) self.pm.send('sendcan', can_list_to_can_capnp(can_sends, msgtype='sendcan', valid=CS.canValid)) force_decel = (self.sm['driverMonitoringState'].awarenessStatus < 0.) or \ (self.state == State.softDisabling) # Curvature & Steering angle params = self.sm['liveParameters'] lat_plan = self.sm['lateralPlan'] steer_angle_without_offset = math.radians(CS.steeringAngleDeg - params.angleOffsetAverageDeg) curvature = -self.VM.calc_curvature(steer_angle_without_offset, CS.vEgo) self.angle_steers_des = math.degrees(self.VM.get_steer_from_curvature(-lat_plan.curvature, CS.vEgo)) self.angle_steers_des += params.angleOffsetDeg # controlsState dat = messaging.new_message('controlsState') dat.valid = CS.canValid controlsState = dat.controlsState controlsState.alertText1 = self.AM.alert_text_1 controlsState.alertText2 = self.AM.alert_text_2 controlsState.alertSize = self.AM.alert_size controlsState.alertStatus = self.AM.alert_status controlsState.alertBlinkingRate = self.AM.alert_rate controlsState.alertType = self.AM.alert_type controlsState.alertSound = self.AM.audible_alert controlsState.canMonoTimes = list(CS.canMonoTimes) controlsState.longitudinalPlanMonoTime = self.sm.logMonoTime['longitudinalPlan'] controlsState.lateralPlanMonoTime = self.sm.logMonoTime['lateralPlan'] controlsState.enabled = self.enabled controlsState.active = self.active controlsState.curvature = curvature controlsState.steeringAngleDesiredDeg = self.angle_steers_des controlsState.state = self.state controlsState.engageable = not self.events.any(ET.NO_ENTRY) controlsState.longControlState = self.LoC.long_control_state controlsState.vPid = float(self.LoC.v_pid) controlsState.vCruise = float(self.cruiseVirtualMaxSpeed if self.CP.openpilotLongitudinalControl else self.v_cruise_kph) controlsState.upAccelCmd = float(self.LoC.pid.p) controlsState.uiAccelCmd = float(self.LoC.pid.i) controlsState.ufAccelCmd = float(self.LoC.pid.f) controlsState.vTargetLead = float(v_acc) controlsState.aTarget = float(a_acc) controlsState.cumLagMs = -self.rk.remaining * 1000. controlsState.startMonoTime = int(start_time * 1e9) controlsState.forceDecel = bool(force_decel) controlsState.canErrorCounter = self.can_error_counter controlsState.angleSteers = steer_angle_without_offset * CV.RAD_TO_DEG controlsState.cluSpeedMs = self.clu_speed_ms controlsState.applyAccel = self.apply_accel controlsState.fusedAccel = self.fused_accel controlsState.leadDist = self.lead_drel controlsState.aReqValue = self.aReqValue controlsState.aReqValueMin = self.aReqValueMin controlsState.aReqValueMax = self.aReqValueMax controlsState.steerRatio = self.VM.sR controlsState.steerRateCost = ntune_get('steerRateCost') controlsState.steerActuatorDelay = ntune_get('steerActuatorDelay') if self.CP.steerControlType == car.CarParams.SteerControlType.angle: controlsState.lateralControlState.angleState = lac_log elif self.CP.lateralTuning.which() == 'pid': controlsState.lateralControlState.pidState = lac_log elif self.CP.lateralTuning.which() == 'lqr': controlsState.lateralControlState.lqrState = lac_log elif self.CP.lateralTuning.which() == 'indi': controlsState.lateralControlState.indiState = lac_log self.pm.send('controlsState', dat) # carState car_events = self.events.to_msg() cs_send = messaging.new_message('carState') cs_send.valid = CS.canValid cs_send.carState = CS cs_send.carState.events = car_events self.pm.send('carState', cs_send) # carEvents - logged every second or on change if (self.sm.frame % int(1. / DT_CTRL) == 0) or (self.events.names != self.events_prev): ce_send = messaging.new_message('carEvents', len(self.events)) ce_send.carEvents = car_events self.pm.send('carEvents', ce_send) self.events_prev = self.events.names.copy() # carParams - logged every 50 seconds (> 1 per segment) if (self.sm.frame % int(50. / DT_CTRL) == 0): cp_send = messaging.new_message('carParams') cp_send.carParams = self.CP self.pm.send('carParams', cp_send) # carControl cc_send = messaging.new_message('carControl') cc_send.valid = CS.canValid cc_send.carControl = CC self.pm.send('carControl', cc_send) # copy CarControl to pass to CarInterface on the next iteration self.CC = CC def step(self): start_time = sec_since_boot() self.prof.checkpoint("Ratekeeper", ignore=True) # Sample data from sockets and get a carState CS = self.data_sample() self.prof.checkpoint("Sample") self.update_events(CS) if not self.read_only and self.initialized: # Update control state self.state_transition(CS) self.prof.checkpoint("State transition") # Compute actuators (runs PID loops and lateral MPC) actuators, v_acc, a_acc, lac_log = self.state_control(CS) self.prof.checkpoint("State Control") # Publish data self.publish_logs(CS, start_time, actuators, v_acc, a_acc, lac_log) self.prof.checkpoint("Sent") def controlsd_thread(self): while True: self.step() self.rk.monitor_time() self.prof.display() def main(sm=None, pm=None, logcan=None): controls = Controls(sm, pm, logcan) controls.controlsd_thread() if __name__ == "__main__": main()
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import cozmo name = input("What is your name? ") def cozmo_program(robot: cozmo.robot.Robot): robot.say_text( f"Hi! My name is Cozmo. How are you, {name}?").wait_for_completed() cozmo.run_program(cozmo_program)
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# Copyright (c) 2016 Uber Technologies, Inc. # # 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 __future__ import absolute_import, unicode_literals, print_function import pytest from thriftrw._buffer import ReadBuffer from thriftrw._buffer import WriteBuffer from thriftrw.errors import EndOfInputError def test_empty_write_buffer(): buff = WriteBuffer(10) assert buff.length == 0 assert buff.capacity == 10 assert buff.value == b'' def test_empty_read_buffer(): buff = ReadBuffer(b'') assert buff.take(0) == b'' with pytest.raises(EndOfInputError): buff.take(1) def test_simple_write(): buff = WriteBuffer(10) buff.write_bytes(b'hello ') buff.write_bytes(b'world') assert buff.value == b'hello world' assert buff.length == 11 def test_simple_read(): buff = ReadBuffer(b'abcd') assert buff.take(1) == b'a' assert buff.take(2) == b'bc' with pytest.raises(EndOfInputError): buff.take(2) assert buff.take(1) == b'd' def test_write_clear(): buff = WriteBuffer(10) buff.write_bytes(b'foo') buff.clear() assert buff.value == b'' assert buff.capacity == 10 assert buff.length == 0
[ [ [ 1126, 1141 ] ], [ [ 1143, 1159 ] ], [ [ 1161, 1175 ] ], [ [ 1184, 1190 ], [ 1565, 1571 ], [ 1938, 1944 ] ], [ [ 1221, 1231 ], [ 1508, 1518 ], [ 1842, 1852 ] ], [ [ 1261, 1272 ], [ 1361, 1372 ], [ 1656, 1667 ], [ 2061, 2072 ] ], [ [ 1301, 1316 ], [ 1579, 1594 ], [ 1952, 1967 ] ], [ [ 1323, 1346 ] ], [ [ 1471, 1493 ] ], [ [ 1624, 1641 ] ], [ [ 1811, 1827 ] ], [ [ 2030, 2046 ] ] ]
from binascii import crc32 from contextlib import contextmanager from datetime import datetime, timedelta, timezone from pathlib import Path from osgeo import gdal import pytest import rasterio from click.testing import CliRunner from rasterio import DatasetReader from rasterio.enums import Compression from rio_cogeo import cogeo import eodatasets3 from eodatasets3.model import DatasetDoc from tests import assert_file_structure from tests.common import assert_same_as_file from . import assert_image h5py = pytest.importorskip( "h5py", reason="Extra dependencies needed to run wagl package test. " "Try pip install eodatasets3[wagl]", ) # These test datasets come from running `tests/integration/h5downsample.py` on a real # wagl output. WAGL_LANDSAT_OUTPUT: Path = ( Path(__file__).parent / "data/wagl-input/LC80920842016180LGN01/LC80920842016180LGN01.wagl.h5" ) WAGL_SENTINEL_OUTPUT: Path = ( Path(__file__).parent / "data/wagl-input/S2A_OPER_MSI_L1C_TL_EPAE_20201031T022859_A027984_T53JQJ_N02.09/" "S2A_OPER_MSI_L1C_TL_EPAE_20201031T022859_A027984_T53JQJ_N02.09.wagl.h5" ) # The matching Level1 metadata (produced by landsat_l1_prepare.py) L1_METADATA_PATH: Path = ( Path(__file__).parent / "data/wagl-input/LC08_L1TP_092084_20160628_20170323_01_T1.yaml" ) S2_L1_METADATA_PATH: Path = ( Path(__file__).parent / "data/wagl-input/S2A_MSIL1C_20201031T004711_N0209_R102_T53JQJ_20201031T022859.odc-metadata.yaml" ) def test_whole_landsat_wagl_package( l1_ls8_dataset: DatasetDoc, l1_ls8_folder: Path, tmp_path: Path ): out = tmp_path from eodatasets3.scripts import packagewagl # No warnings should be logged during package. # We could tighten this to specific warnings if it proves too noisy, but it's # useful for catching things like unclosed files. with expect_no_warnings(): res = CliRunner().invoke( packagewagl.run, map( str, (WAGL_LANDSAT_OUTPUT, "--level1", L1_METADATA_PATH, "--output", out), ), catch_exceptions=False, ) # The last line of output ends with the dataset path. words, reported_metadata = res.output.splitlines()[-1].rsplit(" ", 1) expected_folder = out / "ga_ls8c_ard_3/092/084/2016/06/28" assert_file_structure( expected_folder, { "ga_ls8c_ard_3-2-1_092084_2016-06-28_final.odc-metadata.yaml": "", "ga_ls8c_ard_3-2-1_092084_2016-06-28_final.proc-info.yaml": "", "ga_ls8c_ard_3-2-1_092084_2016-06-28_final.sha1": "", "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band01.tif": "", "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band02.tif": "", "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band03.tif": "", "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band04.tif": "", "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band05.tif": "", "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band06.tif": "", "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band07.tif": "", "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band08.tif": "", "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_thumbnail.jpg": "", "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band01.tif": "", "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band02.tif": "", "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band03.tif": "", "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band04.tif": "", "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band05.tif": "", "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band06.tif": "", "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band07.tif": "", "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band08.tif": "", "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_thumbnail.jpg": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_azimuthal-exiting.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_azimuthal-incident.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_combined-terrain-shadow.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_exiting-angle.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_fmask.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_incident-angle.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_nbar-contiguity.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_nbart-contiguity.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_relative-azimuth.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_relative-slope.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_satellite-azimuth.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_satellite-view.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_solar-azimuth.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_solar-zenith.tif": "", "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_time-delta.tif": "", }, ) [output_metadata] = expected_folder.rglob("*.odc-metadata.yaml") assert reported_metadata == str( output_metadata ), "Cli didn't report the expected output path" # Checksum should include all files other than itself. [checksum_file] = expected_folder.rglob("*.sha1") all_output_files = set( p.relative_to(checksum_file.parent) for p in expected_folder.rglob("*") if p != checksum_file ) files_in_checksum = { Path(line.split("\t")[1]) for line in checksum_file.read_text().splitlines() } assert all_output_files == files_in_checksum # Verify the computed contiguity looks the same. (metadata fields will depend on it) [image] = expected_folder.rglob("*_oa_*nbar-contiguity.tif") assert_image(image, nodata=255, unique_pixel_counts={0: 1978, 1: 4184}) [image] = expected_folder.rglob("*_oa_*nbart-contiguity.tif") assert_image(image, nodata=255, unique_pixel_counts={0: 1979, 1: 4183}) assert_same_as_file( { "$schema": "https://schemas.opendatacube.org/dataset", # A stable ID is taken from the WAGL doc. "id": "787eb74c-e7df-43d6-b562-b796137330ae", "label": "ga_ls8c_ard_3-2-1_092084_2016-06-28_final", "product": { "href": "https://collections.dea.ga.gov.au/product/ga_ls8c_ard_3", "name": "ga_ls8c_ard_3", }, "crs": "epsg:32655", "geometry": { "coordinates": [ [ [386_170.809_107_605_5, -3_787_581.737_315_514_6], [393_422.698_122_467_44, -3_754_539.332_156_166_4], [402_370.463_567_812_2, -3_717_207.883_853_628_3], [405_296.703_429_750_9, -3_713_106.822_612_258_6], [405_302.307_692_307_7, -3_713_085.0], [560_999.714_134_832_8, -3_745_790.820_117_99], [591_203.344_050_317_7, -3_755_934.776_849_929_2], [593_107.5, -3_756_373.614_649_681_4], [593_066.089_284_004_1, -3_756_560.384_007_281_6], [593_115.0, -3_756_576.810_780_758], [593_115.0, -3_769_934.639_090_926_4], [555_895.771_981_598_6, -3_924_204.823_795_153], [554_316.830_569_659_8, -3_931_326.117_549_759], [553_913.572_308_820_1, -3_932_420.854_216_015], [550_505.686_408_068, -3_946_546.219_392_854], [548_673.645_879_151_9, -3_946_645.831_477_726_3], [548_393.076_923_077, -3_947_407.5], [543_888.417_289_877_3, -3_946_906.014_911_907], [535_826.373_854_402_9, -3_947_344.365_997_631_6], [362_232.941_315_876_84, -3_905_575.014_223_633], [362_109.819_892_458_1, -3_904_490.351_889_350_5], [360_592.5, -3_904_126.385_350_318_6], [361_565.347_585_850_9, -3_899_693.716_286_561_5], [360_585.0, -3_891_057.151_898_734_3], [366_618.297_729_428_5, -3_863_717.869_440_751], [386_170.809_107_605_5, -3_787_581.737_315_514_6], ] ], "type": "Polygon", }, "grids": { "default": { "shape": [79, 78], "transform": [ 2981.153_846_153_846, 0.0, 360_585.0, 0.0, -2966.202_531_645_569_7, -3_713_085.0, 0.0, 0.0, 1.0, ], }, "panchromatic": { "shape": [157, 156], "transform": [ 1490.480_769_230_769_3, 0.0, 360_592.5, 0.0, -1492.452_229_299_363, -3_713_092.5, 0.0, 0.0, 1.0, ], }, }, "properties": { "datetime": datetime(2016, 6, 28, 0, 2, 28, 624_635), "dea:dataset_maturity": "final", "dtr:end_datetime": datetime(2016, 6, 28, 0, 2, 43, 114_771), "dtr:start_datetime": datetime(2016, 6, 28, 0, 2, 14, 25815), "eo:cloud_cover": 63.069_613_577_531_236, "eo:gsd": 1490.480_769_230_769_3, "eo:instrument": "OLI_TIRS", "eo:platform": "landsat-8", "eo:sun_azimuth": 33.655_125_34, "eo:sun_elevation": 23.988_361_72, "fmask:clear": 32.735_343_657_403_305, "fmask:cloud": 63.069_613_577_531_236, "fmask:cloud_shadow": 4.139_470_857_647_722, "fmask:snow": 0.005_053_323_801_138_007, "fmask:water": 0.050_518_583_616_596_675, "gqa:abs_iterative_mean_x": 0.21, "gqa:abs_iterative_mean_xy": 0.27, "gqa:abs_iterative_mean_y": 0.18, "gqa:abs_x": 0.3, "gqa:abs_xy": 0.39, "gqa:abs_y": 0.25, "gqa:cep90": 0.46, "gqa:iterative_mean_x": -0.17, "gqa:iterative_mean_xy": 0.21, "gqa:iterative_mean_y": 0.12, "gqa:iterative_stddev_x": 0.19, "gqa:iterative_stddev_xy": 0.25, "gqa:iterative_stddev_y": 0.17, "gqa:mean_x": -0.1, "gqa:mean_xy": 0.14, "gqa:mean_y": 0.1, "gqa:stddev_x": 0.35, "gqa:stddev_xy": 0.45, "gqa:stddev_y": 0.29, "landsat:collection_category": "T1", "landsat:collection_number": 1, "landsat:landsat_product_id": "LC08_L1TP_092084_20160628_20170323_01_T1", "landsat:landsat_scene_id": "LC80920842016180LGN01", "landsat:wrs_path": 92, "landsat:wrs_row": 84, "odc:dataset_version": "3.2.1", "odc:file_format": "GeoTIFF", "odc:processing_datetime": datetime(2019, 7, 11, 23, 29, 29, 21245), "odc:producer": "ga.gov.au", "odc:product_family": "ard", "odc:region_code": "092084", }, "measurements": { "nbar_blue": { "path": "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band02.tif" }, "nbar_coastal_aerosol": { "path": "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band01.tif" }, "nbar_green": { "path": "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band03.tif" }, "nbar_nir": { "path": "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band05.tif" }, "nbar_panchromatic": { "grid": "panchromatic", "path": "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band08.tif", }, "nbar_red": { "path": "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band04.tif" }, "nbar_swir_1": { "path": "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band06.tif" }, "nbar_swir_2": { "path": "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_band07.tif" }, "nbart_blue": { "path": "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band02.tif" }, "nbart_coastal_aerosol": { "path": "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band01.tif" }, "nbart_green": { "path": "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band03.tif" }, "nbart_nir": { "path": "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band05.tif" }, "nbart_panchromatic": { "grid": "panchromatic", "path": "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band08.tif", }, "nbart_red": { "path": "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band04.tif" }, "nbart_swir_1": { "path": "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band06.tif" }, "nbart_swir_2": { "path": "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_band07.tif" }, "oa_azimuthal_exiting": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_azimuthal-exiting.tif" }, "oa_azimuthal_incident": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_azimuthal-incident.tif" }, "oa_combined_terrain_shadow": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_combined-terrain-shadow.tif" }, "oa_exiting_angle": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_exiting-angle.tif" }, "oa_fmask": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_fmask.tif" }, "oa_incident_angle": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_incident-angle.tif" }, "oa_nbar_contiguity": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_nbar-contiguity.tif" }, "oa_nbart_contiguity": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_nbart-contiguity.tif" }, "oa_relative_azimuth": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_relative-azimuth.tif" }, "oa_relative_slope": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_relative-slope.tif" }, "oa_satellite_azimuth": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_satellite-azimuth.tif" }, "oa_satellite_view": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_satellite-view.tif" }, "oa_solar_azimuth": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_solar-azimuth.tif" }, "oa_solar_zenith": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_solar-zenith.tif" }, "oa_time_delta": { "path": "ga_ls8c_oa_3-2-1_092084_2016-06-28_final_time-delta.tif" }, }, "accessories": { "checksum:sha1": { "path": "ga_ls8c_ard_3-2-1_092084_2016-06-28_final.sha1" }, "metadata:processor": { "path": "ga_ls8c_ard_3-2-1_092084_2016-06-28_final.proc-info.yaml" }, "thumbnail:nbar": { "path": "ga_ls8c_nbar_3-2-1_092084_2016-06-28_final_thumbnail.jpg" }, "thumbnail:nbart": { "path": "ga_ls8c_nbart_3-2-1_092084_2016-06-28_final_thumbnail.jpg" }, }, "lineage": {"level1": ["fb1c622e-90aa-50e8-9d5e-ad69db82d0f6"]}, }, output_metadata, ) [proc_info] = expected_folder.rglob("*.proc-info.yaml") assert_same_as_file( { "fmask": { "parameters": { "cloud_buffer_distance_metres": 0.0, "cloud_shadow_buffer_distance_metres": 0.0, "frantz_parallax_sentinel_2": False, }, "percent_class_distribution": { "clear": 32.735_343_657_403_305, "cloud": 63.069_613_577_531_236, "cloud_shadow": 4.139_470_857_647_722, "snow": 0.005_053_323_801_138_007, "water": 0.050_518_583_616_596_675, }, }, "software_versions": [ { "name": "modtran", "url": "http://www.ontar.com/software/productdetails.aspx?item=modtran", "version": "6.0.1", }, { "name": "wagl", "url": "https://github.com/GeoscienceAustralia/wagl.git", "version": "5.3.1+118.g9edd420", }, { "name": "eugl", "url": "https://github.com/OpenDataCubePipelines/eugl.git", "version": "0.0.2+69.gb1d1231", }, {"name": "gverify", "url": None, "version": "v0.25c"}, { "name": "fmask", "url": "https://bitbucket.org/chchrsc/python-fmask", "version": "0.5.3", }, { "name": "tesp", "url": "https://github.com/OpenDataCubePipelines/tesp.git", "version": "0.6.1", }, { "name": "eodatasets3", "url": "https://github.com/GeoscienceAustralia/eo-datasets", "version": eodatasets3.__version__, }, ], }, proc_info, ignore_fields=("gqa", "wagl"), ) # All produced tifs should be valid COGs for image in expected_folder.rglob("*.tif"): assert cogeo.cog_validate(image), f"Failed COG validation: {image}" # Check one of the images explicitly. [image] = expected_folder.rglob("*_nbar_*_band08.tif") with rasterio.open(image) as d: d: DatasetReader assert d.count == 1, "Expected one band" assert d.nodata == -999.0 # Verify the pixel values haven't changed. assert crc32(d.read(1).tobytes()) == 3_381_159_350 # (Rasterio's checksum is zero on some datasets for some reason? So we use crc above...) assert d.checksum(1) == 58403 # The last overview is an odd size because of the tiny test data image size. assert d.overviews(1) == [8, 16, 31] assert d.driver == "GTiff" assert d.dtypes == ("int16",) assert d.compression == Compression.deflate assert d.height == 157 assert d.width == 156 # The reduced resolution makes it hard to test the chosen block size... assert d.block_shapes == [(26, 156)] # Check the overviews use default 512 block size. # (Rasterio doesn't seem to have an api for this?) assert gdal.Open(str(image)).GetRasterBand(1).GetOverview(1).GetBlockSize() == [ 512, 512, ], "Expected overviews to have a larger block size." # OA data should have no overviews. [*oa_images] = expected_folder.rglob("*_oa_*.tif") assert oa_images for image in oa_images: # fmask is the only OA that should have overviews according to spec (and Josh). if "fmask" in image.name: assert_image(image, overviews=[8, 16, 26]) else: assert_image(image, overviews=[]) # Check we didn't get height/width mixed up again :) # (The small size of our test data makes this slightly silly, though...) [thumb_path] = expected_folder.rglob("*_nbar_*.jpg") assert_image(thumb_path, bands=3, shape=(7, 8)) def test_maturity_calculation(): from eodatasets3 import wagl # Simplified. Only a few ancillary parts that matter to us. wagl_doc = { "ancillary": { "aerosol": { "id": ["99d73c48-9985-51d2-9639-d37bcdfe119e"], "tier": "AATSR_CMP_MONTH", "value": 0.047_813_605_517_148_97, }, "brdf": { "alpha_1": { "band_1": 0.407_471_513_826_581_4, "band_2": 0.407_472_440_438_251_7, "band_3": 0.564_374_828_124_185, "band_4": 0.452_550_357_394_962_35, "band_5": 0.720_394_875_348_492_4, "band_6": 0.475_077_458_430_413_66, "band_7": 0.549_934_518_094_732, }, "alpha_2": { "band_1": 0.177_715_841_252_848_28, "band_2": 0.177_716_091_422_247_15, "band_3": 0.136_703_039_045_401_32, "band_4": 0.167_629_648_004_969_63, "band_5": 0.090_148_975_875_461_32, "band_6": 0.121_059_126_731_143_88, "band_7": 0.181_073_714_539_622_23, }, "id": [ "2e95bdec-42e4-50a2-9a4c-1ea970e2696d", "d02e1c58-7379-5c2d-a080-995838550d0d", ], "tier": "DEFINITIVE", }, "elevation": { "id": [ "8ad73086-72cf-561a-aa0f-1e3c64d53384", "e75ac77d-1ed0-55a5-888b-9ae48080eae9", ] }, "ozone": { "id": ["83914de1-c12e-5035-af8d-e2dc1baa54d4"], "tier": "DEFINITIVE", "value": 0.295, }, "water_vapour": { "id": ["e68035cd-1cd3-57fc-9b0e-2bf710a3df87"], "tier": "DEFINITIVE", "value": 0.490_000_009_536_743_16, }, } } # July 2002 is when we consider our BRDF to be good enough: both Aqua # and Terra satellites were now operational. acq_before_brdf = datetime(2002, 6, 29, tzinfo=timezone.utc) acq_after_brdf = datetime(2002, 7, 1, tzinfo=timezone.utc) proc_after_brdf = acq_after_brdf + timedelta(days=7) # Normal, final dataset. Processed just outside of NRT window. assert ( wagl._determine_maturity( acq_after_brdf, acq_after_brdf + timedelta(hours=49), wagl_doc ) == "final" ) # NRT when processed < 48 hours assert ( wagl._determine_maturity( acq_after_brdf, acq_after_brdf + timedelta(hours=1), wagl_doc ) == "nrt" ) assert ( wagl._determine_maturity( acq_before_brdf, acq_before_brdf + timedelta(hours=47), wagl_doc ) == "nrt" ) # Before 2001: final if water vapour is definitive. assert ( wagl._determine_maturity( acq_before_brdf, acq_before_brdf + timedelta(days=3), wagl_doc ) == "final" ) # Interim whenever water vapour is fallback. wagl_doc["ancillary"]["water_vapour"]["tier"] = "FALLBACK_DATASET" assert ( wagl._determine_maturity(acq_after_brdf, proc_after_brdf, wagl_doc) == "interim" ) assert ( wagl._determine_maturity( acq_before_brdf, acq_before_brdf + timedelta(days=3), wagl_doc ) == "interim" ) wagl_doc["ancillary"]["water_vapour"]["tier"] = "DEFINITIVE" # Fallback BRDF (when at least one is fallback) wagl_doc["ancillary"]["brdf"]["tier"] = "FALLBACK_DEFAULT" assert ( wagl._determine_maturity(acq_after_brdf, proc_after_brdf, wagl_doc) == "interim" ) @contextmanager def expect_no_warnings(): """Throw an assertion error if any warnings are produced.""" with pytest.warns(None) as warning_record: yield # We could tighten this to specific warnings if it proves too noisy, but it's # useful for catching things like unclosed files. if warning_record: messages = "\n".join(f"- {w.message} ({w})\n" for w in warning_record) raise AssertionError(f"Expected no warnings to be produced, got:\n {messages}") def test_sentinel_wagl_package(tmp_path: Path): out = tmp_path from eodatasets3.scripts import packagewagl # No warnings should have been logged during package. # We could tighten this to specific warnings if it proves too noisy, but it's # useful for catching things like unclosed files. with expect_no_warnings(): res = CliRunner().invoke( packagewagl.run, map( str, ( WAGL_SENTINEL_OUTPUT, "--level1", S2_L1_METADATA_PATH, "--output", out, # Our weird scaled test dataset resolution "--oa-resolution", 998.1818181818181, ), ), catch_exceptions=False, ) # The last line of output ends with the dataset path. words, reported_metadata = res.output.splitlines()[-1].rsplit(" ", 1) expected_folder = out / "ga_s2am_ard_3/53/JQJ/2020/10/31" assert_file_structure( expected_folder, { "20201031T022859": { "ga_s2am_ard_3-2-1_53JQJ_2020-10-31_final.odc-metadata.yaml": "", "ga_s2am_ard_3-2-1_53JQJ_2020-10-31_final.proc-info.yaml": "", "ga_s2am_ard_3-2-1_53JQJ_2020-10-31_final.sha1": "", "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band01.tif": "", "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band02.tif": "", "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band03.tif": "", "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band04.tif": "", "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band05.tif": "", "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band06.tif": "", "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band07.tif": "", "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band08a.tif": "", "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band08.tif": "", "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band11.tif": "", "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band12.tif": "", "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_thumbnail.jpg": "", "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band01.tif": "", "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band02.tif": "", "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band03.tif": "", "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band04.tif": "", "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band05.tif": "", "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band06.tif": "", "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band07.tif": "", "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band08a.tif": "", "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band08.tif": "", "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band11.tif": "", "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band12.tif": "", "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_thumbnail.jpg": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_azimuthal-exiting.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_azimuthal-incident.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_combined-terrain-shadow.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_exiting-angle.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_fmask.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_incident-angle.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_nbar-contiguity.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_nbart-contiguity.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_relative-azimuth.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_relative-slope.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_satellite-azimuth.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_satellite-view.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_solar-azimuth.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_solar-zenith.tif": "", "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_time-delta.tif": "", } }, ) [output_metadata] = expected_folder.rglob("*.odc-metadata.yaml") # Checksum should include all files other than itself. [checksum_file] = expected_folder.rglob("*.sha1") all_output_files = set( p.relative_to(checksum_file.parent) for p in expected_folder.rglob("*") if p != checksum_file and not p.is_dir() ) files_in_checksum = { Path(line.split("\t")[1]) for line in checksum_file.read_text().splitlines() } assert all_output_files == files_in_checksum # Verify the computed contiguity looks the same. (metadata fields will depend on it) [image] = expected_folder.rglob("*_oa_*nbar-contiguity.tif") assert_image(image, nodata=255, unique_pixel_counts={0: 5367, 1: 6733}) [image] = expected_folder.rglob("*_oa_*nbart-contiguity.tif") assert_image(image, nodata=255, unique_pixel_counts={0: 5367, 1: 6733}) assert_same_as_file( { "$schema": "https://schemas.opendatacube.org/dataset", "id": "14cfa990-7e2f-4f0c-bd5e-b4cb28c27e8d", "label": "ga_s2am_ard_3-2-1_53JQJ_2020-10-31_final", "product": { "name": "ga_s2am_ard_3", "href": "https://collections.dea.ga.gov.au/product/ga_s2am_ard_3", }, "crs": "epsg:32753", "geometry": { "type": "Polygon", "coordinates": [ [ [731901.8181818182, 6790240.0], [728854.7368421053, 6790240.0], [752174.154338321, 6890002.646902946], [759379.8080509851, 6900040.0], [762411.0326110948, 6900040.0], [763218.8851094716, 6900040.0], [809760.0, 6900040.0], [809760.0, 6790240.0], [732900.0, 6790240.0], [731901.8181818182, 6790240.0], ] ], }, "grids": { "default": { "shape": [110, 110], "transform": [ 998.1818181818181, 0.0, 699960.0, 0.0, -998.1818181818181, 6900040.0, 0.0, 0.0, 1.0, ], }, "a": { "shape": [55, 55], "transform": [ 1996.3636363636363, 0.0, 699960.0, 0.0, -1996.3636363636363, 6900040.0, 0.0, 0.0, 1.0, ], }, "b": { "shape": [19, 19], "transform": [ 5778.9473684210525, 0.0, 699960.0, 0.0, -5778.9473684210525, 6900040.0, 0.0, 0.0, 1.0, ], }, "c": { "shape": [19, 19], "transform": [ 5778.947368421053, 0.0, 699960.0, 0.0, -5778.947368421053, 6900040.0, 0.0, 0.0, 1.0, ], }, }, "properties": { "datetime": "2020-10-31T00:55:10.954414", "dea:dataset_maturity": "final", "eo:cloud_cover": 11.063428320692061, "eo:gsd": 998.1818181818181, "eo:instrument": "MSI", "eo:platform": "sentinel-2a", "eo:sun_azimuth": 62.9424764928076, "eo:sun_elevation": 26.8398246645449, "fmask:clear": 73.65382838133374, "fmask:cloud": 11.063428320692061, "fmask:cloud_shadow": 0.6983135097842945, "fmask:snow": 14.583962676987106, "fmask:water": 0.0004671112027989303, "gqa:abs_iterative_mean_x": 0.42, "gqa:abs_iterative_mean_xy": 0.53, "gqa:abs_iterative_mean_y": 0.32, "gqa:abs_x": 0.69, "gqa:abs_xy": 1.07, "gqa:abs_y": 0.82, "gqa:cep90": 0.97, "gqa:iterative_mean_x": 0.4, "gqa:iterative_mean_xy": 0.4, "gqa:iterative_mean_y": 0.04, "gqa:iterative_stddev_x": 0.29, "gqa:iterative_stddev_xy": 0.53, "gqa:iterative_stddev_y": 0.44, "gqa:mean_x": 0.38, "gqa:mean_xy": 0.39, "gqa:mean_y": -0.07, "gqa:stddev_x": 1.18, "gqa:stddev_xy": 2.24, "gqa:stddev_y": 1.9, "odc:dataset_version": "3.2.1", "odc:file_format": "GeoTIFF", "odc:processing_datetime": "2021-02-10T03:25:22.635668", "odc:producer": "ga.gov.au", "odc:product_family": "ard", "odc:region_code": "53JQJ", "sat:orbit_state": "descending", "sat:relative_orbit": 102, "sentinel:datastrip_id": "S2A_OPER_MSI_L1C_DS_EPAE_20201031T022859_S20201031T004711_N02.09", "sentinel:sentinel_tile_id": "S2A_OPER_MSI_L1C_TL_EPAE_20201031T022859_A027984_T53JQJ_N02.09", "sentinel:datatake_start_datetime": "2020-10-31T02:28:59", }, "measurements": { "nbar_blue": { "path": "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band02.tif" }, "nbar_coastal_aerosol": { "path": "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band01.tif", "grid": "b", }, "nbar_green": { "path": "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band03.tif" }, "nbar_nir_1": { "path": "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band08.tif" }, "nbar_nir_2": { "path": "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band08a.tif", "grid": "a", }, "nbar_red": { "path": "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band04.tif" }, "nbar_red_edge_1": { "path": "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band05.tif", "grid": "a", }, "nbar_red_edge_2": { "path": "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band06.tif", "grid": "a", }, "nbar_red_edge_3": { "path": "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band07.tif", "grid": "a", }, "nbar_swir_2": { "path": "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band11.tif", "grid": "a", }, "nbar_swir_3": { "path": "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_band12.tif", "grid": "a", }, "nbart_blue": { "path": "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band02.tif" }, "nbart_coastal_aerosol": { "path": "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band01.tif", "grid": "b", }, "nbart_green": { "path": "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band03.tif" }, "nbart_nir_1": { "path": "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band08.tif" }, "nbart_nir_2": { "path": "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band08a.tif", "grid": "a", }, "nbart_red": { "path": "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band04.tif" }, "nbart_red_edge_1": { "path": "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band05.tif", "grid": "a", }, "nbart_red_edge_2": { "path": "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band06.tif", "grid": "a", }, "nbart_red_edge_3": { "path": "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band07.tif", "grid": "a", }, "nbart_swir_2": { "path": "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band11.tif", "grid": "a", }, "nbart_swir_3": { "path": "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_band12.tif", "grid": "a", }, "oa_azimuthal_exiting": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_azimuthal-exiting.tif" }, "oa_azimuthal_incident": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_azimuthal-incident.tif" }, "oa_combined_terrain_shadow": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_combined-terrain-shadow.tif" }, "oa_exiting_angle": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_exiting-angle.tif" }, "oa_fmask": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_fmask.tif", "grid": "c", }, "oa_incident_angle": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_incident-angle.tif" }, "oa_nbar_contiguity": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_nbar-contiguity.tif" }, "oa_nbart_contiguity": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_nbart-contiguity.tif" }, "oa_relative_azimuth": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_relative-azimuth.tif" }, "oa_relative_slope": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_relative-slope.tif" }, "oa_satellite_azimuth": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_satellite-azimuth.tif" }, "oa_satellite_view": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_satellite-view.tif" }, "oa_solar_azimuth": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_solar-azimuth.tif" }, "oa_solar_zenith": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_solar-zenith.tif" }, "oa_time_delta": { "path": "ga_s2am_oa_3-2-1_53JQJ_2020-10-31_final_time-delta.tif" }, }, "accessories": { "checksum:sha1": { "path": "ga_s2am_ard_3-2-1_53JQJ_2020-10-31_final.sha1" }, "metadata:processor": { "path": "ga_s2am_ard_3-2-1_53JQJ_2020-10-31_final.proc-info.yaml" }, "thumbnail:nbar": { "path": "ga_s2am_nbar_3-2-1_53JQJ_2020-10-31_final_thumbnail.jpg" }, "thumbnail:nbart": { "path": "ga_s2am_nbart_3-2-1_53JQJ_2020-10-31_final_thumbnail.jpg" }, }, "lineage": {"level1": ["e27200c1-0a9c-5e24-bfe1-bbbb3f3bdedc"]}, }, output_metadata, ) [proc_info] = expected_folder.rglob("*.proc-info.yaml") assert_same_as_file( { "fmask": { "parameters": { "cloud_buffer_distance_metres": 0.0, "cloud_shadow_buffer_distance_metres": 0.0, "frantz_parallax_sentinel_2": False, }, "percent_class_distribution": { "clear": 73.65382838133374, "cloud": 11.063428320692061, "cloud_shadow": 0.6983135097842945, "snow": 14.583962676987106, "water": 0.0004671112027989303, }, }, "software_versions": [ { "name": "modtran", "url": "http://www.ontar.com/software/productdetails.aspx?item=modtran", "version": "6.0.1", }, { "name": "wagl", "url": "https://github.com/GeoscienceAustralia/wagl.git", "version": "5.4.1", }, { "name": "eugl", "url": "https://github.com/OpenDataCubePipelines/eugl.git", "version": "0.2.1", }, {"name": "gverify", "url": None, "version": "v0.25c"}, { "name": "fmask", "url": "https://bitbucket.org/chchrsc/python-fmask", "version": "0.5.4", }, { "name": "tesp", "url": "https://github.com/OpenDataCubePipelines/tesp.git", "version": "0.6.2", }, { "name": "eodatasets3", "url": "https://github.com/GeoscienceAustralia/eo-datasets", "version": eodatasets3.__version__, }, ], }, proc_info, ignore_fields=("gqa", "wagl"), ) # All produced tifs should be valid COGs for image in expected_folder.rglob("*.tif"): assert cogeo.cog_validate(image), f"Failed COG validation: {image}"
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import scrapy, re from alleco.objects.official import Official class ross_t(scrapy.Spider): name = "ross_t" muniName = "ROSS" muniType = "TOWNSHIP" complete = True def start_requests(self): urls = ['https://www.ross.pa.us/245/Board-of-Commissioners', 'https://www.ross.pa.us/225/Other-Elected-Officials'] for url in urls: yield scrapy.Request(url=url, callback=self.parse) def parse(self, response): if response.url[-2]=='r': for quote in response.xpath('//div[@class="cpTabPanels"]'): arr = [i.strip() for i in quote.xpath('.//text()').getall() if len(i.strip())>0 and '$' not in i] temp = [] peeps = [] for i in arr: temp.append(i) if '@' in i: peeps.append(temp) temp = [] for pers in peeps: name = self._name(pers[1]) if "Commissioner" in pers[1] else None yield Official( muniName=self.muniName, muniType=self.muniType, office="COMMISSIONER", district=pers[0].upper(), name=name, email=pers[-1], vacant=name==None, url=response.url) elif response.url[-2]=='l': for quote in response.xpath('//div[contains(h2/text(),"Ross Tax Collector")]/p[1]'): yield Official( muniName=self.muniName, muniType=self.muniType, office="TAX COLLECTOR", name=quote.xpath('text()[1]').get(), email=quote.xpath('a/@href').get(), phone=quote.xpath('text()[2]').get(), url=response.url) def _name(self,string): return string.split(",")[0][13:]
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""" 状态模式 """ from __future__ import annotations from abc import ABC, abstractmethod class Context: # 状态(状态模式的判断) _state: State = None def __init__(self, state: State) -> None: self.transition_to(state) def transition_to(self, state: State) -> None: # 根据不同状态,切换上下文 self._state = state self._state.context = self # 最终执行器的操作 def request1(self): self._state.handle1() def request2(self): self._state.handle2() class State(ABC): @property def context(self) -> Context: return self._context @context.setter def context(self, context: Context) -> None: self._context = context @abstractmethod def handle1(self) -> None: pass @abstractmethod def handle2(self) -> None: pass class ConcreteStateA(State): def handle1(self) -> None: print('执行了A—1') self.context.transition_to(ConcreteStateB()) def handle2(self) -> None: print('执行了A-2') class ConcreteStateB(State): def handle1(self) -> None: print('执行了B—1') def handle2(self) -> None: print('执行了B—2') self.context.transition_to(ConcreteStateA()) if __name__ == '__main__': context = Context(ConcreteStateA()) context.request1() context.request2() context.request2()
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# -*- coding: utf-8 -*- # Copyright 2020 Green Valley Belgium NV # # 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. # # @@license_version:1.7@@ import json from mcfw.rpc import arguments, returns from rogerthat.models import Message from rogerthat.models.properties.forms import FormResult from rogerthat.rpc import users from rogerthat.service.api import messaging from rogerthat.to.messaging.forms import TextBlockFormTO, TextBlockTO, FormTO from rogerthat.to.messaging.service_callback_results import FormAcknowledgedCallbackResultTO from rogerthat.to.service import UserDetailsTO from rogerthat.utils.app import get_app_user_tuple from solutions import translate from solutions.common.dal import get_solution_main_branding, get_solution_settings from solutions.common.models import SolutionInboxMessage @arguments(service_user=users.User, service_identity=unicode, message_key=unicode, app_user=users.User, name=unicode, answer_id=unicode, parent_inbox_message=SolutionInboxMessage) def process_updated_customer_signup_message(service_user, service_identity, message_key, app_user, name, answer_id, parent_inbox_message): # type: (users.User, unicode, unicode, users.User, unicode, unicode, SolutionInboxMessage) -> None from solutions.common.bizz.messaging import MESSAGE_TAG_DENY_SIGNUP from solutions.common.restapi.services import rest_create_service_from_signup with users.set_user(service_user): sln_settings = get_solution_settings(service_user) if answer_id == 'decline': widget = TextBlockTO() widget.max_chars = 1024 form = TextBlockFormTO() form.type = TextBlockTO.TYPE form.widget = widget form.positive_button = translate(sln_settings.main_language, 'Confirm') form.negative_button = translate(sln_settings.main_language, 'Cancel') form.javascript_validation = """function run(result) { return result.value ? true : '%s'; }""" % translate(sln_settings.main_language, 'this_field_is_required', _duplicate_backslashes=True) human_user, app_id = get_app_user_tuple(app_user) messaging.send_form(parent_key=parent_inbox_message.message_key, parent_message_key=parent_inbox_message.message_key, message=translate(sln_settings.main_language, 'signup_not_ok'), member=human_user.email(), app_id=app_id, flags=Message.FLAG_AUTO_LOCK, branding=get_solution_main_branding(service_user).branding_key, tag=json.dumps({'__rt__.tag': MESSAGE_TAG_DENY_SIGNUP, 'signup_key': parent_inbox_message.category_key}), form=form, service_identity=service_identity, alert_flags=Message.ALERT_FLAG_VIBRATE) elif answer_id == 'approve': result = rest_create_service_from_signup(parent_inbox_message.category_key, force=True) # type: CreateServiceStatusTO if not result.success: messaging.send(parent_message_key=message_key, message=result.errormsg, answers=[], flags=Message.FLAG_ALLOW_DISMISS, branding=get_solution_main_branding(service_user).branding_key, tag=None, service_identity=service_identity) @returns(FormAcknowledgedCallbackResultTO) @arguments(service_user=users.User, status=int, form_result=FormResult, answer_id=unicode, member=unicode, message_key=unicode, tag=unicode, received_timestamp=int, acked_timestamp=int, parent_message_key=unicode, result_key=unicode, service_identity=unicode, user_details=[UserDetailsTO]) def deny_signup(service_user, status, form_result, answer_id, member, message_key, tag, received_timestamp, acked_timestamp, parent_message_key, result_key, service_identity, user_details): from solutions.common.restapi import rest_customer_signup_reply with users.set_user(service_user): if answer_id == FormTO.POSITIVE: tag_dict = json.loads(tag) rest_customer_signup_reply(tag_dict['signup_key'], form_result.result.value)
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import os import time import pickle import math import numpy as np import linecache import matplotlib.pyplot as plt # from matplotlib.pyplot import MultipleLocator import grid data_path = 'E:/dataset/didi/processed' save_path = 'E:/dataset/didi/processed/order_20161101_sampled_value_map_fig' data_file_name = 'processed_data' # '.pkl' will be added for binary file value_map_file_name = 'value_map' # '.pkl' will be added for binary file n_time_unit = 144 size_hexagon_to_edge = 0.0048 hexagon_size_factor_for_plot = 1 range_map_longitude = [103.96, 104.18] range_map_latitude = [30.59, 30.77] size_hexagon = size_hexagon_to_edge * 2 / math.sqrt(3) # length to the point if not os.path.exists(save_path): os.mkdir(save_path) with open(os.path.join(data_path, data_file_name+'.pkl'), 'rb') as f: data = pickle.load(f) with open(os.path.join(data_path, value_map_file_name+'.pkl'), 'rb') as f: value_map = pickle.load(f) # make hexagon grid = grid.Hexagon(size_to_edge=size_hexagon_to_edge*hexagon_size_factor_for_plot) grid_interval_lo = size_hexagon * 1.5 grid_interval_la = size_hexagon_to_edge * 2 grid_centers = [] for la in np.arange(range_map_latitude[1]-size_hexagon, range_map_latitude[0]-0.00001, -grid_interval_la): row = [] count = 0 for lo in np.arange(range_map_longitude[0], range_map_longitude[1]+0.00001, grid_interval_lo): if count % 2 == 0: row.append([lo, la]) else: row.append([lo, la+size_hexagon_to_edge]) count += 1 grid_centers.append(row) grid_centers_mat = np.array(grid_centers) shape_grid_centers_mat = grid_centers_mat.shape n_grids = shape_grid_centers_mat[0]*shape_grid_centers_mat[1] grid_index_mat = np.arange(n_grids).reshape(shape_grid_centers_mat[:2]) print('shape of grids is', shape_grid_centers_mat) print('number of grids is', n_grids) grid_centers_flat_T = grid_centers_mat.reshape(n_grids, 2).T max_value = np.max(value_map) min_value = np.min(value_map) print('maximum value in value_map is', max_value) print('minimum value in value_map is', min_value) # value_map = (value_map - min_value) / max_value # max_value = np.max(value_map) # min_value = np.min(value_map) # print('maximum value in value_map after normalization is', max_value) # print('minimum value in value_map after normalization is', min_value) for t in range(n_time_unit): fig = plt.figure() plt.title('value map of time unit %d' % t) plt.scatter(grid_centers_flat_T[0], grid_centers_flat_T[1], c=value_map[t], marker='H', s=100, alpha=0.5) plt.colorbar() fig.savefig(os.path.join(save_path, '%d.jpg'%t))
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w = int(input()) h = int(input()) for i in range(h): output = str() for j in range(w): if (i + j) % 2 == 0: output += '0' else: output += '1' print(output)
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from bridges.symbol import * class Text(Symbol): def __init__(self, label = None): super(Text, self).__init__() if label is not None: self._text = label else: self._text = "" self.stroke_width = 1.0 self._font_size = None self._anchor_alignment_lr = None self._anchor_alignment_tb = None self._locx = 0.0 self._locy = 0.0 def get_shape_type(self): return "text" @property def text(self): return self._text @text.setter def text(self, t): self._text = t @property def font_size(self): return self._font_size @font_size.setter def font_size(self, s): if(s < 0.0): raise ValueError("Font size is too small") self._font_size = s def set_anchor_alignment(self, typeLR, typeTB): self._anchor_alignment_lr = typeLR self._anchor_alignment_tb = typeTB def set_anchor_location(self, x, y): self._locx = x self._locy = y def get_json_representation(self): json_builder = super(Text, self).get_json_representation() json_builder['anchor-location'] = [self._locx, self._locy] json_builder['text'] = self.text if self.font_size is not None: json_builder['font-size'] =self.font_size if self._anchor_alignment_lr is not None: json_builder['anchor-alignmentLR'] = self._anchor_alignment_lr if self._anchor_alignment_tb is not None: json_builder['anchor-alignmentTB'] = self._anchor_alignment_tb return json_builder
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import torch import torch.nn as nn import rdkit.Chem as Chem import torch.nn.functional as F from hgraph.nnutils import * from hgraph.encoder import IncHierMPNEncoder from hgraph.mol_graph import MolGraph from hgraph.inc_graph import IncTree, IncGraph class HTuple(): def __init__(self, node=None, mess=None, vmask=None, emask=None): self.node, self.mess = node, mess self.vmask, self.emask = vmask, emask class HierMPNDecoder(nn.Module): def __init__(self, vocab, avocab, rnn_type, embed_size, hidden_size, latent_size, depthT, depthG, dropout, attention=False): super(HierMPNDecoder, self).__init__() self.vocab = vocab self.avocab = avocab self.hidden_size = hidden_size self.embed_size = embed_size self.latent_size = latent_size self.use_attention = attention self.itensor = torch.LongTensor([]).cuda() self.hmpn = IncHierMPNEncoder(vocab, avocab, rnn_type, embed_size, hidden_size, depthT, depthG, dropout) self.rnn_cell = self.hmpn.tree_encoder.rnn self.E_assm = self.hmpn.E_i self.E_order = torch.eye(MolGraph.MAX_POS).cuda() self.topoNN = nn.Sequential( nn.Linear(hidden_size + latent_size, hidden_size), nn.ReLU(), nn.Dropout(dropout), nn.Linear(hidden_size, 1) ) self.clsNN = nn.Sequential( nn.Linear(hidden_size + latent_size, hidden_size), nn.ReLU(), nn.Dropout(dropout), nn.Linear(hidden_size, vocab.size()[0]) ) self.iclsNN = nn.Sequential( nn.Linear(hidden_size + latent_size, hidden_size), nn.ReLU(), nn.Dropout(dropout), nn.Linear(hidden_size, vocab.size()[1]) ) self.matchNN = nn.Sequential( nn.Linear(hidden_size + embed_size + MolGraph.MAX_POS, hidden_size), nn.ReLU(), ) self.W_assm = nn.Linear(hidden_size, latent_size) if latent_size != hidden_size: self.W_root = nn.Linear(latent_size, hidden_size) if self.use_attention: self.A_topo = nn.Linear(hidden_size, latent_size) self.A_cls = nn.Linear(hidden_size, latent_size) self.A_assm = nn.Linear(hidden_size, latent_size) self.topo_loss = nn.BCEWithLogitsLoss(size_average=False) self.cls_loss = nn.CrossEntropyLoss(size_average=False) self.icls_loss = nn.CrossEntropyLoss(size_average=False) self.assm_loss = nn.CrossEntropyLoss(size_average=False) def apply_tree_mask(self, tensors, cur, prev): fnode, fmess, agraph, bgraph, cgraph, scope = tensors agraph = agraph * index_select_ND(cur.emask, 0, agraph) bgraph = bgraph * index_select_ND(cur.emask, 0, bgraph) cgraph = cgraph * index_select_ND(prev.vmask, 0, cgraph) return fnode, fmess, agraph, bgraph, cgraph, scope def apply_graph_mask(self, tensors, hgraph): fnode, fmess, agraph, bgraph, scope = tensors agraph = agraph * index_select_ND(hgraph.emask, 0, agraph) bgraph = bgraph * index_select_ND(hgraph.emask, 0, bgraph) return fnode, fmess, agraph, bgraph, scope def update_graph_mask(self, graph_batch, new_atoms, hgraph): new_atom_index = hgraph.vmask.new_tensor(new_atoms) hgraph.vmask.scatter_(0, new_atom_index, 1) new_atom_set = set(new_atoms) new_bonds = [] #new bonds are the subgraph induced by new_atoms for zid in new_atoms: for nid in graph_batch[zid]: if nid not in new_atom_set: continue new_bonds.append( graph_batch[zid][nid]['mess_idx'] ) new_bond_index = hgraph.emask.new_tensor(new_bonds) if len(new_bonds) > 0: hgraph.emask.scatter_(0, new_bond_index, 1) return new_atom_index, new_bond_index def init_decoder_state(self, tree_batch, tree_tensors, src_root_vecs): batch_size = len(src_root_vecs) num_mess = len(tree_tensors[1]) agraph = tree_tensors[2].clone() bgraph = tree_tensors[3].clone() for i,tup in enumerate(tree_tensors[-1]): root = tup[0] assert agraph[root,-1].item() == 0 agraph[root,-1] = num_mess + i for v in tree_batch.successors(root): mess_idx = tree_batch[root][v]['mess_idx'] assert bgraph[mess_idx,-1].item() == 0 bgraph[mess_idx,-1] = num_mess + i new_tree_tensors = tree_tensors[:2] + [agraph, bgraph] + tree_tensors[4:] htree = HTuple() htree.mess = self.rnn_cell.get_init_state(tree_tensors[1], src_root_vecs) htree.emask = torch.cat( [bgraph.new_zeros(num_mess), bgraph.new_ones(batch_size)], dim=0 ) return htree, new_tree_tensors def attention(self, src_vecs, batch_idx, queries, W_att): size = batch_idx.size() if batch_idx.dim() > 1: batch_idx = batch_idx.view(-1) queries = queries.view(-1, queries.size(-1)) src_vecs = src_vecs.index_select(0, batch_idx) att_score = torch.bmm( src_vecs, W_att(queries).unsqueeze(-1) ) att_vecs = F.softmax(att_score, dim=1) * src_vecs att_vecs = att_vecs.sum(dim=1) return att_vecs if len(size) == 1 else att_vecs.view(size[0], size[1], -1) def get_topo_score(self, src_tree_vecs, batch_idx, topo_vecs): if self.use_attention: topo_cxt = self.attention(src_tree_vecs, batch_idx, topo_vecs, self.A_topo) else: topo_cxt = src_tree_vecs.index_select(index=batch_idx, dim=0) return self.topoNN( torch.cat([topo_vecs, topo_cxt], dim=-1) ).squeeze(-1) def get_cls_score(self, src_tree_vecs, batch_idx, cls_vecs, cls_labs): if self.use_attention: cls_cxt = self.attention(src_tree_vecs, batch_idx, cls_vecs, self.A_cls) else: cls_cxt = src_tree_vecs.index_select(index=batch_idx, dim=0) cls_vecs = torch.cat([cls_vecs, cls_cxt], dim=-1) cls_scores = self.clsNN(cls_vecs) if cls_labs is None: #inference mode icls_scores = self.iclsNN(cls_vecs) #no masking else: vocab_masks = self.vocab.get_mask(cls_labs) icls_scores = self.iclsNN(cls_vecs) + vocab_masks #apply mask by log(x + mask): mask=0 or -INF return cls_scores, icls_scores def get_assm_score(self, src_graph_vecs, batch_idx, assm_vecs): if self.use_attention: assm_cxt = self.attention(src_graph_vecs, batch_idx, assm_vecs, self.A_assm) else: assm_cxt = index_select_ND(src_graph_vecs, 0, batch_idx) return (self.W_assm(assm_vecs) * assm_cxt).sum(dim=-1) def forward(self, src_mol_vecs, graphs, tensors, orders): batch_size = len(orders) tree_batch, graph_batch = graphs tree_tensors, graph_tensors = tensors inter_tensors = tree_tensors src_root_vecs, src_tree_vecs, src_graph_vecs = src_mol_vecs init_vecs = src_root_vecs if self.latent_size == self.hidden_size else self.W_root(src_root_vecs) htree, tree_tensors = self.init_decoder_state(tree_batch, tree_tensors, init_vecs) hinter = HTuple( mess = self.rnn_cell.get_init_state(inter_tensors[1]), emask = self.itensor.new_zeros(inter_tensors[1].size(0)) ) hgraph = HTuple( mess = self.rnn_cell.get_init_state(graph_tensors[1]), vmask = self.itensor.new_zeros(graph_tensors[0].size(0)), emask = self.itensor.new_zeros(graph_tensors[1].size(0)) ) all_topo_preds, all_cls_preds, all_assm_preds = [], [], [] new_atoms = [] tree_scope = tree_tensors[-1] for i in range(batch_size): root = tree_batch.nodes[ tree_scope[i][0] ] clab, ilab = self.vocab[ root['label'] ] all_cls_preds.append( (init_vecs[i], i, clab, ilab) ) #cluster prediction new_atoms.extend(root['cluster']) subgraph = self.update_graph_mask(graph_batch, new_atoms, hgraph) graph_tensors = self.hmpn.embed_graph(graph_tensors) + (graph_tensors[-1],) #preprocess graph tensors maxt = max([len(x) for x in orders]) max_cls_size = max( [len(attr) * 2 for node,attr in tree_batch.nodes(data='cluster')] ) for t in range(maxt): batch_list = [i for i in range(batch_size) if t < len(orders[i])] assert htree.emask[0].item() == 0 and hinter.emask[0].item() == 0 and hgraph.vmask[0].item() == 0 and hgraph.emask[0].item() == 0 subtree = [], [] for i in batch_list: xid, yid, tlab = orders[i][t] subtree[0].append(xid) if yid is not None: mess_idx = tree_batch[xid][yid]['mess_idx'] subtree[1].append(mess_idx) subtree = htree.emask.new_tensor(subtree[0]), htree.emask.new_tensor(subtree[1]) htree.emask.scatter_(0, subtree[1], 1) hinter.emask.scatter_(0, subtree[1], 1) cur_tree_tensors = self.apply_tree_mask(tree_tensors, htree, hgraph) cur_inter_tensors = self.apply_tree_mask(inter_tensors, hinter, hgraph) cur_graph_tensors = self.apply_graph_mask(graph_tensors, hgraph) htree, hinter, hgraph = self.hmpn(cur_tree_tensors, cur_inter_tensors, cur_graph_tensors, htree, hinter, hgraph, subtree, subgraph) new_atoms = [] for i in batch_list: xid, yid, tlab = orders[i][t] all_topo_preds.append( (htree.node[xid], i, tlab) ) #topology prediction if yid is not None: mess_idx = tree_batch[xid][yid]['mess_idx'] new_atoms.extend( tree_batch.nodes[yid]['cluster'] ) #NOTE: regardless of tlab = 0 or 1 if tlab == 0: continue cls = tree_batch.nodes[yid]['smiles'] clab, ilab = self.vocab[ tree_batch.nodes[yid]['label'] ] mess_idx = tree_batch[xid][yid]['mess_idx'] hmess = self.rnn_cell.get_hidden_state(htree.mess) all_cls_preds.append( (hmess[mess_idx], i, clab, ilab) ) #cluster prediction using message inter_label = tree_batch.nodes[yid]['inter_label'] inter_label = [ (pos, self.vocab[(cls, icls)][1]) for pos,icls in inter_label ] inter_size = self.vocab.get_inter_size(ilab) if len(tree_batch.nodes[xid]['cluster']) > 2: #uncertainty occurs only when previous cluster is a ring nth_child = tree_batch[yid][xid]['label'] #must be yid -> xid (graph order labeling is different from tree) cands = tree_batch.nodes[yid]['assm_cands'] icls = list(zip(*inter_label))[1] cand_vecs = self.enum_attach(hgraph, cands, icls, nth_child) if len(cand_vecs) < max_cls_size: pad_len = max_cls_size - len(cand_vecs) cand_vecs = F.pad(cand_vecs, (0,0,0,pad_len)) batch_idx = hgraph.emask.new_tensor( [i] * max_cls_size ) all_assm_preds.append( (cand_vecs, batch_idx, 0) ) #the label is always the first of assm_cands subgraph = self.update_graph_mask(graph_batch, new_atoms, hgraph) topo_vecs, batch_idx, topo_labels = zip_tensors(all_topo_preds) topo_scores = self.get_topo_score(src_tree_vecs, batch_idx, topo_vecs) topo_loss = self.topo_loss(topo_scores, topo_labels.float()) topo_acc = get_accuracy_bin(topo_scores, topo_labels) cls_vecs, batch_idx, cls_labs, icls_labs = zip_tensors(all_cls_preds) cls_scores, icls_scores = self.get_cls_score(src_tree_vecs, batch_idx, cls_vecs, cls_labs) cls_loss = self.cls_loss(cls_scores, cls_labs) + self.icls_loss(icls_scores, icls_labs) cls_acc = get_accuracy(cls_scores, cls_labs) icls_acc = get_accuracy(icls_scores, icls_labs) if len(all_assm_preds) > 0: assm_vecs, batch_idx, assm_labels = zip_tensors(all_assm_preds) assm_scores = self.get_assm_score(src_graph_vecs, batch_idx, assm_vecs) assm_loss = self.assm_loss(assm_scores, assm_labels) assm_acc = get_accuracy_sym(assm_scores, assm_labels) else: assm_loss, assm_acc = 0, 1 loss = (topo_loss + cls_loss + assm_loss) / batch_size return loss, cls_acc, icls_acc, topo_acc, assm_acc def enum_attach(self, hgraph, cands, icls, nth_child): cands = self.itensor.new_tensor(cands) icls_vecs = self.itensor.new_tensor(icls * len(cands)) icls_vecs = self.E_assm( icls_vecs ) nth_child = self.itensor.new_tensor([nth_child] * len(cands.view(-1))) order_vecs = self.E_order.index_select(0, nth_child) cand_vecs = hgraph.node.index_select(0, cands.view(-1)) cand_vecs = torch.cat( [cand_vecs, icls_vecs, order_vecs], dim=-1 ) cand_vecs = self.matchNN(cand_vecs) if len(icls) == 2: cand_vecs = cand_vecs.view(-1, 2, self.hidden_size).sum(dim=1) return cand_vecs def decode(self, src_mol_vecs, greedy=True, max_decode_step=100, beam=5): src_root_vecs, src_tree_vecs, src_graph_vecs = src_mol_vecs batch_size = len(src_root_vecs) tree_batch = IncTree(batch_size, node_fdim=2, edge_fdim=3) graph_batch = IncGraph(self.avocab, batch_size, node_fdim=self.hmpn.atom_size, edge_fdim=self.hmpn.atom_size + self.hmpn.bond_size) stack = [[] for i in range(batch_size)] init_vecs = src_root_vecs if self.latent_size == self.hidden_size else self.W_root(src_root_vecs) batch_idx = self.itensor.new_tensor(range(batch_size)) cls_scores, icls_scores = self.get_cls_score(src_tree_vecs, batch_idx, init_vecs, None) root_cls = cls_scores.max(dim=-1)[1] icls_scores = icls_scores + self.vocab.get_mask(root_cls) root_cls, root_icls = root_cls.tolist(), icls_scores.max(dim=-1)[1].tolist() super_root = tree_batch.add_node() for bid in range(batch_size): clab, ilab = root_cls[bid], root_icls[bid] root_idx = tree_batch.add_node( batch_idx.new_tensor([clab, ilab]) ) tree_batch.add_edge(super_root, root_idx) stack[bid].append(root_idx) root_smiles = self.vocab.get_ismiles(ilab) new_atoms, new_bonds, attached = graph_batch.add_mol(bid, root_smiles, [], 0) tree_batch.register_cgraph(root_idx, new_atoms, new_bonds, attached) #invariance: tree_tensors is equal to inter_tensors (but inter_tensor's init_vec is 0) tree_tensors = tree_batch.get_tensors() graph_tensors = graph_batch.get_tensors() htree = HTuple( mess = self.rnn_cell.get_init_state(tree_tensors[1]) ) hinter = HTuple( mess = self.rnn_cell.get_init_state(tree_tensors[1]) ) hgraph = HTuple( mess = self.rnn_cell.get_init_state(graph_tensors[1]) ) h = self.rnn_cell.get_hidden_state(htree.mess) h[1 : batch_size + 1] = init_vecs #wiring root (only for tree, not inter) for t in range(max_decode_step): batch_list = [ bid for bid in range(batch_size) if len(stack[bid]) > 0 ] if len(batch_list) == 0: break batch_idx = batch_idx.new_tensor(batch_list) cur_tree_nodes = [stack[bid][-1] for bid in batch_list] subtree = batch_idx.new_tensor(cur_tree_nodes), batch_idx.new_tensor([]) subgraph = batch_idx.new_tensor( tree_batch.get_cluster_nodes(cur_tree_nodes) ), batch_idx.new_tensor( tree_batch.get_cluster_edges(cur_tree_nodes) ) htree, hinter, hgraph = self.hmpn(tree_tensors, tree_tensors, graph_tensors, htree, hinter, hgraph, subtree, subgraph) topo_scores = self.get_topo_score(src_tree_vecs, batch_idx, htree.node.index_select(0, subtree[0])) topo_scores = torch.sigmoid(topo_scores) if greedy: topo_preds = topo_scores.tolist() else: topo_preds = torch.bernoulli(topo_scores).tolist() new_mess = [] expand_list = [] for i,bid in enumerate(batch_list): if topo_preds[i] > 0.5 and tree_batch.can_expand(stack[bid][-1]): expand_list.append( (len(new_mess), bid) ) new_node = tree_batch.add_node() #new node label is yet to be predicted edge_feature = batch_idx.new_tensor( [stack[bid][-1], new_node, 0] ) #parent to child is 0 new_edge = tree_batch.add_edge(stack[bid][-1], new_node, edge_feature) stack[bid].append(new_node) new_mess.append(new_edge) else: child = stack[bid].pop() if len(stack[bid]) > 0: nth_child = tree_batch.graph.in_degree(stack[bid][-1]) #edge child -> father has not established edge_feature = batch_idx.new_tensor( [child, stack[bid][-1], nth_child] ) new_edge = tree_batch.add_edge(child, stack[bid][-1], edge_feature) new_mess.append(new_edge) subtree = subtree[0], batch_idx.new_tensor(new_mess) subgraph = [], [] htree, hinter, hgraph = self.hmpn(tree_tensors, tree_tensors, graph_tensors, htree, hinter, hgraph, subtree, subgraph) cur_mess = self.rnn_cell.get_hidden_state(htree.mess).index_select(0, subtree[1]) if len(expand_list) > 0: idx_in_mess, expand_list = zip(*expand_list) idx_in_mess = batch_idx.new_tensor( idx_in_mess ) expand_idx = batch_idx.new_tensor( expand_list ) forward_mess = cur_mess.index_select(0, idx_in_mess) cls_scores, icls_scores = self.get_cls_score(src_tree_vecs, expand_idx, forward_mess, None) scores, cls_topk, icls_topk = hier_topk(cls_scores, icls_scores, self.vocab, beam) if not greedy: scores = torch.exp(scores) #score is output of log_softmax shuf_idx = torch.multinomial(scores, beam, replacement=True).tolist() for i,bid in enumerate(expand_list): new_node, fa_node = stack[bid][-1], stack[bid][-2] success = False cls_beam = range(beam) if greedy else shuf_idx[i] for kk in cls_beam: #try until one is chemically valid if success: break clab, ilab = cls_topk[i][kk], icls_topk[i][kk] node_feature = batch_idx.new_tensor( [clab, ilab] ) tree_batch.set_node_feature(new_node, node_feature) smiles, ismiles = self.vocab.get_smiles(clab), self.vocab.get_ismiles(ilab) fa_cluster, _, fa_used = tree_batch.get_cluster(fa_node) inter_cands, anchor_smiles, attach_points = graph_batch.get_assm_cands(fa_cluster, fa_used, ismiles) if len(inter_cands) == 0: continue elif len(inter_cands) == 1: sorted_cands = [(inter_cands[0], 0)] nth_child = 0 else: nth_child = tree_batch.graph.in_degree(fa_node) icls = [self.vocab[ (smiles,x) ][1] for x in anchor_smiles] cands = inter_cands if len(attach_points) <= 2 else [ (x[0],x[-1]) for x in inter_cands ] cand_vecs = self.enum_attach(hgraph, cands, icls, nth_child) batch_idx = batch_idx.new_tensor( [bid] * len(inter_cands) ) assm_scores = self.get_assm_score(src_graph_vecs, batch_idx, cand_vecs).tolist() sorted_cands = sorted( list(zip(inter_cands, assm_scores)), key = lambda x:x[1], reverse=True ) for inter_label,_ in sorted_cands: inter_label = list(zip(inter_label, attach_points)) if graph_batch.try_add_mol(bid, ismiles, inter_label): new_atoms, new_bonds, attached = graph_batch.add_mol(bid, ismiles, inter_label, nth_child) tree_batch.register_cgraph(new_node, new_atoms, new_bonds, attached) tree_batch.update_attached(fa_node, inter_label) success = True break if not success: #force backtrack child = stack[bid].pop() #pop the dummy new_node which can't be added nth_child = tree_batch.graph.in_degree(stack[bid][-1]) edge_feature = batch_idx.new_tensor( [child, stack[bid][-1], nth_child] ) new_edge = tree_batch.add_edge(child, stack[bid][-1], edge_feature) child = stack[bid].pop() if len(stack[bid]) > 0: nth_child = tree_batch.graph.in_degree(stack[bid][-1]) edge_feature = batch_idx.new_tensor( [child, stack[bid][-1], nth_child] ) new_edge = tree_batch.add_edge(child, stack[bid][-1], edge_feature) return graph_batch.get_mol()
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#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All rights reserved. import unittest import numpy as np import numpy.testing as npt import six from caffe2.python import core, workspace from ml.rl.caffe_utils import C2 from ml.rl.preprocessing import identify_types, normalization from ml.rl.preprocessing.identify_types import BOXCOX, CONTINUOUS, ENUM from ml.rl.preprocessing.normalization import ( NormalizationParameters, sort_features_by_normalization, ) from ml.rl.preprocessing.preprocessor_net import PreprocessorNet from ml.rl.test.preprocessing_util import ( BOXCOX_FEATURE_ID, ENUM_FEATURE_ID, PROBABILITY_FEATURE_ID, id_to_type, read_data, ) from ml.rl.test.utils import NumpyFeatureProcessor from scipy import special class TestNormalization(unittest.TestCase): def _feature_type_override(self, feature_id): """ This should only be used to test CONTINUOUS_ACTION """ if id_to_type(feature_id) == identify_types.CONTINUOUS_ACTION: return identify_types.CONTINUOUS_ACTION return None def test_prepare_normalization_and_normalize(self): feature_value_map = read_data() normalization_parameters = {} for name, values in feature_value_map.items(): normalization_parameters[name] = normalization.identify_parameter( values, 10, feature_type=self._feature_type_override(name) ) for k, v in normalization_parameters.items(): if id_to_type(k) == CONTINUOUS: self.assertEqual(v.feature_type, CONTINUOUS) self.assertIs(v.boxcox_lambda, None) self.assertIs(v.boxcox_shift, None) elif id_to_type(k) == BOXCOX: self.assertEqual(v.feature_type, BOXCOX) self.assertIsNot(v.boxcox_lambda, None) self.assertIsNot(v.boxcox_shift, None) else: assert v.feature_type == id_to_type(k) sorted_features, _ = sort_features_by_normalization(normalization_parameters) norm_net = core.Net("net") C2.set_net(norm_net) preprocessor = PreprocessorNet() input_matrix = np.zeros([10000, len(sorted_features)], dtype=np.float32) for i, feature in enumerate(sorted_features): input_matrix[:, i] = feature_value_map[feature] input_matrix_blob = "input_matrix_blob" workspace.FeedBlob(input_matrix_blob, np.array([], dtype=np.float32)) output_blob, _ = preprocessor.normalize_dense_matrix( input_matrix_blob, sorted_features, normalization_parameters, "", False ) workspace.FeedBlob(input_matrix_blob, input_matrix) workspace.RunNetOnce(norm_net) normalized_feature_matrix = workspace.FetchBlob(output_blob) normalized_features = {} on_column = 0 for feature in sorted_features: norm = normalization_parameters[feature] if norm.feature_type == ENUM: column_size = len(norm.possible_values) else: column_size = 1 normalized_features[feature] = normalized_feature_matrix[ :, on_column : (on_column + column_size) ] on_column += column_size self.assertTrue( all( [ np.isfinite(parameter.stddev) and np.isfinite(parameter.mean) for parameter in normalization_parameters.values() ] ) ) for k, v in six.iteritems(normalized_features): self.assertTrue(np.all(np.isfinite(v))) feature_type = normalization_parameters[k].feature_type if feature_type == identify_types.PROBABILITY: sigmoidv = special.expit(v) self.assertTrue( np.all( np.logical_and(np.greater(sigmoidv, 0), np.less(sigmoidv, 1)) ) ) elif feature_type == identify_types.ENUM: possible_values = normalization_parameters[k].possible_values self.assertEqual(v.shape[0], len(feature_value_map[k])) self.assertEqual(v.shape[1], len(possible_values)) possible_value_map = {} for i, possible_value in enumerate(possible_values): possible_value_map[possible_value] = i for i, row in enumerate(v): original_feature = feature_value_map[k][i] self.assertEqual( possible_value_map[original_feature], np.where(row == 1)[0][0] ) elif feature_type == identify_types.QUANTILE: for i, feature in enumerate(v[0]): original_feature = feature_value_map[k][i] expected = NumpyFeatureProcessor.value_to_quantile( original_feature, normalization_parameters[k].quantiles ) self.assertAlmostEqual(feature, expected, 2) elif feature_type == identify_types.BINARY: pass elif ( feature_type == identify_types.CONTINUOUS or feature_type == identify_types.BOXCOX ): one_stddev = np.isclose(np.std(v, ddof=1), 1, atol=0.01) zero_stddev = np.isclose(np.std(v, ddof=1), 0, atol=0.01) zero_mean = np.isclose(np.mean(v), 0, atol=0.01) self.assertTrue( np.all(zero_mean), "mean of feature {} is {}, not 0".format(k, np.mean(v)), ) self.assertTrue(np.all(np.logical_or(one_stddev, zero_stddev))) elif feature_type == identify_types.CONTINUOUS_ACTION: less_than_max = v < 1 more_than_min = v > -1 self.assertTrue( np.all(less_than_max), "values are not less than 1: {}".format(v[less_than_max == False]), ) self.assertTrue( np.all(more_than_min), "values are not more than -1: {}".format(v[more_than_min == False]), ) else: raise NotImplementedError() def test_normalize_dense_matrix_enum(self): normalization_parameters = { 1: NormalizationParameters( identify_types.ENUM, None, None, None, None, [12, 4, 2], None, None, None, ), 2: NormalizationParameters( identify_types.CONTINUOUS, None, 0, 0, 1, None, None, None, None ), 3: NormalizationParameters( identify_types.ENUM, None, None, None, None, [15, 3], None, None, None ), } norm_net = core.Net("net") C2.set_net(norm_net) preprocessor = PreprocessorNet() inputs = np.zeros([4, 3], dtype=np.float32) feature_ids = [2, 1, 3] # Sorted according to feature type inputs[:, feature_ids.index(1)] = [12, 4, 2, 2] inputs[:, feature_ids.index(2)] = [1.0, 2.0, 3.0, 3.0] inputs[:, feature_ids.index(3)] = [15, 3, 15, normalization.MISSING_VALUE] input_blob = C2.NextBlob("input_blob") workspace.FeedBlob(input_blob, np.array([0], dtype=np.float32)) normalized_output_blob, _ = preprocessor.normalize_dense_matrix( input_blob, feature_ids, normalization_parameters, "", False ) workspace.FeedBlob(input_blob, inputs) workspace.RunNetOnce(norm_net) normalized_feature_matrix = workspace.FetchBlob(normalized_output_blob) np.testing.assert_allclose( np.array( [ [1.0, 1, 0, 0, 1, 0], [2.0, 0, 1, 0, 0, 1], [3.0, 0, 0, 1, 1, 0], [3.0, 0, 0, 1, 0, 0], # Missing values should go to all 0 ] ), normalized_feature_matrix, ) def test_persistency(self): feature_value_map = read_data() normalization_parameters = {} for name, values in feature_value_map.items(): normalization_parameters[name] = normalization.identify_parameter( values, feature_type=self._feature_type_override(name) ) s = normalization.serialize(normalization_parameters) read_parameters = normalization.deserialize(s) # Unfortunately, Thrift serializatin seems to lose a bit of precision. # Using `==` will be false. self.assertEqual(read_parameters.keys(), normalization_parameters.keys()) for k in normalization_parameters: self.assertEqual( read_parameters[k].feature_type, normalization_parameters[k].feature_type, ) self.assertEqual( read_parameters[k].possible_values, normalization_parameters[k].possible_values, ) for field in [ "boxcox_lambda", "boxcox_shift", "mean", "stddev", "quantiles", "min_value", "max_value", ]: if getattr(normalization_parameters[k], field) is None: self.assertEqual( getattr(read_parameters[k], field), getattr(normalization_parameters[k], field), ) else: npt.assert_allclose( getattr(read_parameters[k], field), getattr(normalization_parameters[k], field), ) def test_preprocessing_network(self): feature_value_map = read_data() normalization_parameters = {} for name, values in feature_value_map.items(): normalization_parameters[name] = normalization.identify_parameter( values, feature_type=self._feature_type_override(name) ) test_features = NumpyFeatureProcessor.preprocess( feature_value_map, normalization_parameters ) net = core.Net("PreprocessingTestNet") C2.set_net(net) preprocessor = PreprocessorNet() name_preprocessed_blob_map = {} for feature_name in feature_value_map: workspace.FeedBlob(str(feature_name), np.array([0], dtype=np.int32)) preprocessed_blob, _ = preprocessor.preprocess_blob( str(feature_name), [normalization_parameters[feature_name]] ) name_preprocessed_blob_map[feature_name] = preprocessed_blob workspace.CreateNet(net) for feature_name, feature_value in six.iteritems(feature_value_map): feature_value = np.expand_dims(feature_value, -1) workspace.FeedBlob(str(feature_name), feature_value) workspace.RunNetOnce(net) for feature_name in feature_value_map: normalized_features = workspace.FetchBlob( name_preprocessed_blob_map[feature_name] ) if feature_name != ENUM_FEATURE_ID: normalized_features = np.squeeze(normalized_features, -1) tolerance = 0.01 if feature_name == BOXCOX_FEATURE_ID: # At the limit, boxcox has some numerical instability tolerance = 0.5 non_matching = np.where( np.logical_not( np.isclose( normalized_features, test_features[feature_name], rtol=tolerance, atol=tolerance, ) ) ) self.assertTrue( np.all( np.isclose( normalized_features, test_features[feature_name], rtol=tolerance, atol=tolerance, ) ), "{} does not match: {} {}".format( feature_name, normalized_features[non_matching].tolist(), test_features[feature_name][non_matching].tolist(), ), ) def test_type_override(self): # Take a feature that should be identified as probability feature_value_map = read_data() probability_values = feature_value_map[PROBABILITY_FEATURE_ID] # And ask for a binary anyways parameter = normalization.identify_parameter( probability_values, feature_type=identify_types.BINARY ) self.assertEqual(parameter.feature_type, "BINARY")
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import speech_recognition as sr r=sr.Recognizer() with sr.Microphone() as source: print("Say Something") sudio=r.listen(source) print("Time over") try: print("Text: "+r.recognize_google(audio)) except: pass
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import tkinter from tkinter import * win = Tk() sb = Spinbox(win, from_=0, to=10) sb.pack() win.mainloop()
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import citysim3d.envs from visual_dynamics.envs import Env class ServoingEnv(citysim3d.envs.SimpleQuadPanda3dServoingEnv, Env): def _get_config(self): config = super(ServoingEnv, self)._get_config() config.update({'env': self.env, 'max_time_steps': self.max_time_steps, 'distance_threshold': self.distance_threshold}) return config # class ServoingEnv(citysim3d.envs.ServoingEnv, Env): # def _get_config(self): # config = super(ServoingEnv, self)._get_config() # config.update({'env': self.env}) # return config # # # class SimpleQuadPanda3dServoingEnv(citysim3d.envs.SimpleQuadPanda3dServoingEnv, ServoingEnv): # def _get_config(self): # config = super(SimpleQuadPanda3dServoingEnv, self)._get_config() # config.update({'env': self.env, # 'max_time_steps': self.max_time_steps, # 'distance_threshold': self.distance_threshold}) # return config
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from .dynamic_iterbased_runner import DynamicIterBasedRunner __all__ = ['DynamicIterBasedRunner']
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#Django Imports from django.conf import settings #Python Imports import requests, os #Local Imports from .at_utils import AfricasTalkingException #Import Afica's Talking Settings AFRICAS_TALKING_SETTINGS = getattr(settings,'AFRICAS_TALKING',{}) API_KEY = AFRICAS_TALKING_SETTINGS.get('API_KEY',None) USERNAME = AFRICAS_TALKING_SETTINGS.get('USERNAME',None) SHORTCODE = AFRICAS_TALKING_SETTINGS.get('SHORTCODE',None) AFRICAS_TALKING_SEND = AFRICAS_TALKING_SETTINGS.get('SEND',False) AFRICAS_TALKING_API_BASE = 'http://api.africastalking.com/version1' HEADERS = {'Accept': 'application/json','apikey':API_KEY} PARAMS = {'username':USERNAME,'bulkSMSMode':1} if SHORTCODE: PARAMS['from'] = SHORTCODE def send_raw(to,message): if not AFRICAS_TALKING_SEND: raise AfricasTalkingException("Africas Talking called when send not set to True") if API_KEY is None: raise AfricasTalkingException('AFRICAS_TALKING var has not set API_KEY') if USERNAME is None: raise AfricasTalkingException('AFRICAS_TALKING var has not set a USERNAME') params = {'to':to,'message':message} params.update(PARAMS) send_url = os.path.join(AFRICAS_TALKING_API_BASE,'messaging') post = requests.post(send_url,data=params,headers=HEADERS) #Raise requests.exceptions.HTTPError if 4XX or 5XX post.raise_for_status() return post.json() def send(to,message): data = send_raw(to,message) ''' Example of JSON Response {u'SMSMessageData': {u'Message': u'Sent to 1/1 Total Cost: USD 0.0109', u'Recipients': [{ u'status': u'Success', #u'status': u'Invalid Phone Number', u'cost': u'KES 1.0000', u'number': u'+254708054321', u'messageId': u'ATXid_b50fada5b1af078f2277cacb58ef2447' }] } } ''' # Return tuple (messageId, messageSuccess, extra_data) recipients = data['SMSMessageData']['Recipients'] if len(recipients) == 1: msg_id = recipients[0]['messageId'] msg_success = recipients[0]['status'] == 'Success' return msg_id, msg_success, {'status':recipients[0]['status']} def balance(): if API_KEY is None: raise AfricasTalkingException('AFRICAS_TALKING var has not set API_KEY') if USERNAME is None: raise AfricasTalkingException('AFRICAS_TALKING var has not set a USERNAME') params = {'username':USERNAME} send_url = os.path.join(AFRICAS_TALKING_API_BASE,'user') post = requests.get(send_url,params=params,headers=HEADERS) #Raise requests.exceptions.HTTPError if 4XX or 5XX post.raise_for_status() data = post.json() return data['UserData']['balance'] def fetch(last_received_id=0): if API_KEY is None: raise AfricasTalkingException('AFRICAS_TALKING var has not set API_KEY') if USERNAME is None: raise AfricasTalkingException('AFRICAS_TALKING var has not set a USERNAME') params = {'username':USERNAME,'lastReceivedId':last_received_id} send_url = os.path.join(AFRICAS_TALKING_API_BASE,'messaging') post = requests.get(send_url,params=params,headers=HEADERS) return post
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#! /usr/bin/env python # encoding: utf-8 # WARNING! Do not edit! https://waf.io/book/index.html#_obtaining_the_waf_file import os,sys,traceback,base64,signal try: import cPickle except ImportError: import pickle as cPickle try: import subprocess32 as subprocess except ImportError: import subprocess try: TimeoutExpired=subprocess.TimeoutExpired except AttributeError: class TimeoutExpired(Exception): pass def run(): txt=sys.stdin.readline().strip() if not txt: sys.exit(1) [cmd,kwargs,cargs]=cPickle.loads(base64.b64decode(txt)) cargs=cargs or{} if not'close_fds'in kwargs: kwargs['close_fds']=False ret=1 out,err,ex,trace=(None,None,None,None) try: proc=subprocess.Popen(cmd,**kwargs) try: out,err=proc.communicate(**cargs) except TimeoutExpired: if kwargs.get('start_new_session')and hasattr(os,'killpg'): os.killpg(proc.pid,signal.SIGKILL) else: proc.kill() out,err=proc.communicate() exc=TimeoutExpired(proc.args,timeout=cargs['timeout'],output=out) exc.stderr=err raise exc ret=proc.returncode except Exception as e: exc_type,exc_value,tb=sys.exc_info() exc_lines=traceback.format_exception(exc_type,exc_value,tb) trace=str(cmd)+'\n'+''.join(exc_lines) ex=e.__class__.__name__ tmp=[ret,out,err,ex,trace] obj=base64.b64encode(cPickle.dumps(tmp)) sys.stdout.write(obj.decode()) sys.stdout.write('\n') sys.stdout.flush() while 1: try: run() except KeyboardInterrupt: break
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# -*- coding: utf-8 -*- """ Class and program to colorize python source code for ANSI terminals. Based on an HTML code highlighter by Jurgen Hermann found at: http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/52298 Modifications by Fernando Perez (fperez@colorado.edu). Information on the original HTML highlighter follows: MoinMoin - Python Source Parser Title: Colorize Python source using the built-in tokenizer Submitter: Jurgen Hermann Last Updated:2001/04/06 Version no:1.2 Description: This code is part of MoinMoin (http://moin.sourceforge.net/) and converts Python source code to HTML markup, rendering comments, keywords, operators, numeric and string literals in different colors. It shows how to use the built-in keyword, token and tokenize modules to scan Python source code and re-emit it with no changes to its original formatting (which is the hard part). """ from __future__ import print_function from __future__ import unicode_literals __all__ = ['ANSICodeColors','Parser'] _scheme_default = 'Linux' # Imports import StringIO import keyword import os import optparse import sys import token import tokenize try: generate_tokens = tokenize.generate_tokens except AttributeError: # Python 3. Note that we use the undocumented _tokenize because it expects # strings, not bytes. See also Python issue #9969. generate_tokens = tokenize._tokenize from IPython.utils.coloransi import * ############################################################################# ### Python Source Parser (does Hilighting) ############################################################################# _KEYWORD = token.NT_OFFSET + 1 _TEXT = token.NT_OFFSET + 2 #**************************************************************************** # Builtin color schemes Colors = TermColors # just a shorthand # Build a few color schemes NoColor = ColorScheme( 'NoColor',{ token.NUMBER : Colors.NoColor, token.OP : Colors.NoColor, token.STRING : Colors.NoColor, tokenize.COMMENT : Colors.NoColor, token.NAME : Colors.NoColor, token.ERRORTOKEN : Colors.NoColor, _KEYWORD : Colors.NoColor, _TEXT : Colors.NoColor, 'normal' : Colors.NoColor # color off (usu. Colors.Normal) } ) LinuxColors = ColorScheme( 'Linux',{ token.NUMBER : Colors.LightCyan, token.OP : Colors.Yellow, token.STRING : Colors.LightBlue, tokenize.COMMENT : Colors.LightRed, token.NAME : Colors.Normal, token.ERRORTOKEN : Colors.Red, _KEYWORD : Colors.LightGreen, _TEXT : Colors.Yellow, 'normal' : Colors.Normal # color off (usu. Colors.Normal) } ) LightBGColors = ColorScheme( 'LightBG',{ token.NUMBER : Colors.Cyan, token.OP : Colors.Blue, token.STRING : Colors.Blue, tokenize.COMMENT : Colors.Red, token.NAME : Colors.Normal, token.ERRORTOKEN : Colors.Red, _KEYWORD : Colors.Green, _TEXT : Colors.Blue, 'normal' : Colors.Normal # color off (usu. Colors.Normal) } ) # Build table of color schemes (needed by the parser) ANSICodeColors = ColorSchemeTable([NoColor,LinuxColors,LightBGColors], _scheme_default) class Parser: """ Format colored Python source. """ def __init__(self, color_table=None,out = sys.stdout): """ Create a parser with a specified color table and output channel. Call format() to process code. """ self.color_table = color_table and color_table or ANSICodeColors self.out = out def format(self, raw, out = None, scheme = ''): return self.format2(raw, out, scheme)[0] def format2(self, raw, out = None, scheme = ''): """ Parse and send the colored source. If out and scheme are not specified, the defaults (given to constructor) are used. out should be a file-type object. Optionally, out can be given as the string 'str' and the parser will automatically return the output in a string.""" string_output = 0 if out == 'str' or self.out == 'str' or \ isinstance(self.out,StringIO.StringIO): # XXX - I don't really like this state handling logic, but at this # point I don't want to make major changes, so adding the # isinstance() check is the simplest I can do to ensure correct # behavior. out_old = self.out self.out = StringIO.StringIO() string_output = 1 elif out is not None: self.out = out # Fast return of the unmodified input for NoColor scheme if scheme == 'NoColor': error = False self.out.write(raw) if string_output: return raw,error else: return None,error # local shorthands colors = self.color_table[scheme].colors self.colors = colors # put in object so __call__ sees it # Remove trailing whitespace and normalize tabs self.raw = raw.expandtabs().rstrip() # store line offsets in self.lines self.lines = [0, 0] pos = 0 raw_find = self.raw.find lines_append = self.lines.append while 1: pos = raw_find('\n', pos) + 1 if not pos: break lines_append(pos) lines_append(len(self.raw)) # parse the source and write it self.pos = 0 text = StringIO.StringIO(self.raw) error = False try: for atoken in generate_tokens(text.readline): self(*atoken) except tokenize.TokenError as ex: msg = ex.args[0] line = ex.args[1][0] self.out.write("%s\n\n*** ERROR: %s%s%s\n" % (colors[token.ERRORTOKEN], msg, self.raw[self.lines[line]:], colors.normal) ) error = True self.out.write(colors.normal+'\n') if string_output: output = self.out.getvalue() self.out = out_old return (output, error) return (None, error) def __call__(self, toktype, toktext, start_pos, end_pos, line): """ Token handler, with syntax highlighting.""" (srow,scol) = start_pos (erow,ecol) = end_pos colors = self.colors owrite = self.out.write # line separator, so this works across platforms linesep = os.linesep # calculate new positions oldpos = self.pos newpos = self.lines[srow] + scol self.pos = newpos + len(toktext) # send the original whitespace, if needed if newpos > oldpos: owrite(self.raw[oldpos:newpos]) # skip indenting tokens if toktype in [token.INDENT, token.DEDENT]: self.pos = newpos return # map token type to a color group if token.LPAR <= toktype and toktype <= token.OP: toktype = token.OP elif toktype == token.NAME and keyword.iskeyword(toktext): toktype = _KEYWORD color = colors.get(toktype, colors[_TEXT]) #print '<%s>' % toktext, # dbg # Triple quoted strings must be handled carefully so that backtracking # in pagers works correctly. We need color terminators on _each_ line. if linesep in toktext: toktext = toktext.replace(linesep, '%s%s%s' % (colors.normal,linesep,color)) # send text owrite('%s%s%s' % (color,toktext,colors.normal)) def main(argv=None): """Run as a command-line script: colorize a python file or stdin using ANSI color escapes and print to stdout. Inputs: - argv(None): a list of strings like sys.argv[1:] giving the command-line arguments. If None, use sys.argv[1:]. """ usage_msg = """%prog [options] [filename] Colorize a python file or stdin using ANSI color escapes and print to stdout. If no filename is given, or if filename is -, read standard input.""" parser = optparse.OptionParser(usage=usage_msg) newopt = parser.add_option newopt('-s','--scheme',metavar='NAME',dest='scheme_name',action='store', choices=['Linux','LightBG','NoColor'],default=_scheme_default, help="give the color scheme to use. Currently only 'Linux'\ (default) and 'LightBG' and 'NoColor' are implemented (give without\ quotes)") opts,args = parser.parse_args(argv) if len(args) > 1: parser.error("you must give at most one filename.") if len(args) == 0: fname = '-' # no filename given; setup to read from stdin else: fname = args[0] if fname == '-': stream = sys.stdin else: try: stream = open(fname) except IOError as msg: print(msg, file=sys.stderr) sys.exit(1) parser = Parser() # we need nested try blocks because pre-2.5 python doesn't support unified # try-except-finally try: try: # write colorized version to stdout parser.format(stream.read(),scheme=opts.scheme_name) except IOError as msg: # if user reads through a pager and quits, don't print traceback if msg.args != (32,'Broken pipe'): raise finally: if stream is not sys.stdin: stream.close() # in case a non-handled exception happened above if __name__ == "__main__": main()
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# Last Updated: 2.2 from datetime import datetime from util.diagMessage import DiagMessage # Logger class # Buffers and writes messages to a file class Logger: BUFFER_MAX = 10 DEFAULT_FN = "../log.txt" # Constructor for logger class # Params: fn - file name to use or leave default # log - flag to keep a log file or not # Return: Logger instance def __init__(self, fn = DEFAULT_FN, log = True): #{{{ self.keep_log = log self.fn = fn self.log_buffer = [] if self.keep_log: self.log(DiagMessage("LOG0000I")) #}}} # Append line to internal log buffer, flush if needed # Params: diag - DiagMessage to log # flush - bool flag for flushing buffer early # Return: None def log(self, diag, flush=False): #{{{ if self.keep_log: self.log_buffer.append(str(datetime.now()) + " - " + diag.msg) if len(self.log_buffer) >= self.BUFFER_MAX or flush: self._write() elif not flush: print(diag.msg) #}}} # Write contents of buffer out to file # Params: None # Return: None def _write(self): #{{{ print("Writing log...") if debug else None with open(self.fn,'a') as logfile: for line in self.log_buffer: try: logfile.write(line) except TypeError: logfile.write(str(datetime.now())+" - LOG ERR") except UnicodeEncodeError: logfile.write(str(line.encode("utf-8","replace"))) logfile.write("\n") del self.log_buffer[:] #}}}
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# Standard Library from copy import deepcopy # 3rd Party # Internal # ########################################################################### # class MetaData (dict): """ A class for holding information about an object """ def __init__ (self,*args,**kwargs): super(MetaData,self).__init__(*args,**kwargs) def __repr__ (self): reprout = 'MetaData {' if len(self) == 0: return reprout + "}" reprout += "\n" for key in self: value = str(repr(self[key])).split("\n") reprout += " "+str(key)+" : " reprout += value[0].strip()+"\n" if len(value) > 1: reprout += " "*(len(key))+" ...\n" reprout += "}\n" return reprout def __str__ (self): return super(MetaData,self).__repr__() def _type_check_other (self,other): if not isinstance(other,dict): raise TypeError("other must be a subclass of dict") def __add__ (self,other): return self.combine(other,key_conflicts='raise') def __iadd__ (self,other): self._type_check_other(other) for key in other: if key in self: continue self[key] = other[key] return self def combine (self,other,key_conflicts='ignore',return_=False): """ Combine two MetaData dictionaries together. Parameters ---------- other : dict subclass Any dictionary object will work including other MetaData Dictionaries key_conflicts : 'ignore' (default), 'merge', 'warn', 'raise' Defined the method to handle key conflicts * ignore : if key is in conflict, keep the current key with no warning * merge : convert key to string and add integers until unique key is found * warn : print a warning message for key conflicts. Keep current key * raise : raise error message for key conflicts. return_ : boolean If True then it will keep the data in place and return a copy with with the concatenation Returns ------- info : MetaData Returns an information object with keys and information concatenated from the two Raises ------ KeyError : If key_conflicts=='raise' is True and conflicts exist between two keys Notes ----- __1)__ If a key is in conflict but the data the key refers to is the same then no messages or errors will be raised Special cases ------------- add operator : info1 + info2 This will raise errors for key conflicts between the two iadd operator : info1 += info2 This will ignore key conflicts and always takes info1 keys as default """ self._type_check_other(other) def errmsg (key): return "Warning: key conflict '"+str(key)+"'" key_conflicts = key_conflicts.lower() if return_: out = self.copy() else: out = self if key_conflicts=='merge': for key in other: if key in self and self[key]==other[key]: continue i = 0 base_key = deepcopy(key) while key in self: key = str(base_key)+"_"+str(i) i += 1 out[key] = other[base_key] return out # else: for key in other: if key in self: # if the data's the same don't worry about it if self[key]==other[key]: continue # resolve conflicts if key_conflicts=='raise': raise KeyError(errmsg(key)) elif key_conflicts=='warn': print(errmsg(key)) else: continue out[key] = other[key] if return_: return out def copy (self): return deepcopy(self) def header_list(self): """returns a list of the values belonging to keys beginning header_ """ keys = list(self.keys()) headers = [] for key in keys: try: keystart = key[:7] if keystart == "header_": headers.append(self[key]) except: pass return headers def guess_observation_time(self, headers=None): if headers == None: headers = self.header_list() obs_time = None for hdr in headers: try: obs_time = hdr["ut"] break except: pass return obs_time def guess_airmass(self, headers): if headers == None: headers = self.header_list() airmass = None for hdr in headers: try: airmass = hdr["airmass"] break except: pass return airmass def guess_object_name(self): return None
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Inc('dfaccto/util.py', abs=True) class _Event(ModuleContext): def __init__(self): ModuleContext.__init__(self) self._setup_packages() def _setup_packages(self): self.pkg = Pkg('dfaccto_event', x_templates={self.File('generic/package.vhd.tpl'): self.File('pkg/dfaccto_event.vhd')}) with self.pkg: self.tEvent = self.TypeEvent('Event') def TypeEvent(self, name, stb_bits=None, ack_bits=None): tlogic = Util.tlogic if stb_bits is not None: tsdata = Util.TypeUnsigned('{}Strb'.format(name), width=stb_bits) else: tsdata = None if ack_bits is not None: tadata = Util.TypeUnsigned('{}Ack'.format(name), width=ack_bits) else: tadata = None return TypeC(name, x_is_event=True, x_definition=self.Part('types/definition/event.part.tpl'), x_format_ms=self.Part('types/format/event_ms.part.tpl'), x_format_sm=self.Part('types/format/event_sm.part.tpl'), x_wrapeport=self.Part('types/wrapeport/event.part.tpl'), x_wrapeconv=self.Part('types/wrapeconv/event.part.tpl'), x_wrapipmap=self.Part('types/wrapipmap/event.part.tpl'), x_wrapigmap=None, x_tlogic=tlogic, x_tsdata=tsdata, x_tadata=tadata, x_cnull=lambda t: Con('{}Null'.format(name), t, value=Lit({'stb': False, 'ack': False}))) Event = _Event()
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# -*- coding: utf-8 -*- # Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is # holder of all proprietary rights on this computer program. # You can only use this computer program if you have closed # a license agreement with MPG or you get the right to use the computer # program from someone who is authorized to grant you that right. # Any use of the computer program without a valid license is prohibited and # liable to prosecution. # # Copyright©2019 Max-Planck-Gesellschaft zur Förderung # der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute # for Intelligent Systems. All rights reserved. # # Contact: ps-license@tuebingen.mpg.de from __future__ import absolute_import from __future__ import print_function from __future__ import division import numpy as np import torch import torch.nn.functional as F from .utils import rot_mat_to_euler def find_dynamic_lmk_idx_and_bcoords(vertices, pose, dynamic_lmk_faces_idx, dynamic_lmk_b_coords, neck_kin_chain, dtype=torch.float32): ''' Compute the faces, barycentric coordinates for the dynamic landmarks To do so, we first compute the rotation of the neck around the y-axis and then use a pre-computed look-up table to find the faces and the barycentric coordinates that will be used. Special thanks to Soubhik Sanyal (soubhik.sanyal@tuebingen.mpg.de) for providing the original TensorFlow implementation and for the LUT. Parameters ---------- vertices: torch.tensor BxVx3, dtype = torch.float32 The tensor of input vertices pose: torch.tensor Bx(Jx3), dtype = torch.float32 The current pose of the body model dynamic_lmk_faces_idx: torch.tensor L, dtype = torch.long The look-up table from neck rotation to faces dynamic_lmk_b_coords: torch.tensor Lx3, dtype = torch.float32 The look-up table from neck rotation to barycentric coordinates neck_kin_chain: list A python list that contains the indices of the joints that form the kinematic chain of the neck. dtype: torch.dtype, optional Returns ------- dyn_lmk_faces_idx: torch.tensor, dtype = torch.long A tensor of size BxL that contains the indices of the faces that will be used to compute the current dynamic landmarks. dyn_lmk_b_coords: torch.tensor, dtype = torch.float32 A tensor of size BxL that contains the indices of the faces that will be used to compute the current dynamic landmarks. ''' batch_size = vertices.shape[0] aa_pose = torch.index_select(pose.view(batch_size, -1, 3), 1, neck_kin_chain) rot_mats = batch_rodrigues( aa_pose.view(-1, 3), dtype=dtype).view(batch_size, -1, 3, 3) rel_rot_mat = torch.eye(3, device=vertices.device, dtype=dtype).unsqueeze_(dim=0) for idx in range(len(neck_kin_chain)): rel_rot_mat = torch.bmm(rot_mats[:, idx], rel_rot_mat) y_rot_angle = torch.round( torch.clamp(-rot_mat_to_euler(rel_rot_mat) * 180.0 / np.pi, max=39)).to(dtype=torch.long) neg_mask = y_rot_angle.lt(0).to(dtype=torch.long) mask = y_rot_angle.lt(-39).to(dtype=torch.long) neg_vals = mask * 78 + (1 - mask) * (39 - y_rot_angle) y_rot_angle = (neg_mask * neg_vals + (1 - neg_mask) * y_rot_angle) dyn_lmk_faces_idx = torch.index_select(dynamic_lmk_faces_idx, 0, y_rot_angle) dyn_lmk_b_coords = torch.index_select(dynamic_lmk_b_coords, 0, y_rot_angle) return dyn_lmk_faces_idx, dyn_lmk_b_coords def vertices2landmarks(vertices, faces, lmk_faces_idx, lmk_bary_coords): ''' Calculates landmarks by barycentric interpolation Parameters ---------- vertices: torch.tensor BxVx3, dtype = torch.float32 The tensor of input vertices faces: torch.tensor Fx3, dtype = torch.long The faces of the mesh lmk_faces_idx: torch.tensor L, dtype = torch.long The tensor with the indices of the faces used to calculate the landmarks. lmk_bary_coords: torch.tensor Lx3, dtype = torch.float32 The tensor of barycentric coordinates that are used to interpolate the landmarks Returns ------- landmarks: torch.tensor BxLx3, dtype = torch.float32 The coordinates of the landmarks for each mesh in the batch ''' # Extract the indices of the vertices for each face # BxLx3 batch_size, num_verts = vertices.shape[:2] device = vertices.device lmk_faces = torch.index_select(faces, 0, lmk_faces_idx.view(-1)).view( batch_size, -1, 3) lmk_faces += torch.arange( batch_size, dtype=torch.long, device=device).view(-1, 1, 1) * num_verts lmk_vertices = vertices.view(-1, 3)[lmk_faces].view( batch_size, -1, 3, 3) landmarks = torch.einsum('blfi,blf->bli', [lmk_vertices, lmk_bary_coords]) return landmarks def lbs(betas, pose, v_template, shapedirs, posedirs, J_regressor, parents, lbs_weights, pose2rot=True, dtype=torch.float32): ''' Performs Linear Blend Skinning with the given shape and pose parameters Parameters ---------- betas : torch.tensor BxNB The tensor of shape parameters pose : torch.tensor Bx(J + 1) * 3 The pose parameters in axis-angle format v_template torch.tensor BxVx3 The template mesh that will be deformed shapedirs : torch.tensor 1xNB The tensor of PCA shape displacements posedirs : torch.tensor Px(V * 3) The pose PCA coefficients J_regressor : torch.tensor JxV The regressor array that is used to calculate the joints from the position of the vertices parents: torch.tensor J The array that describes the kinematic tree for the model lbs_weights: torch.tensor N x V x (J + 1) The linear blend skinning weights that represent how much the rotation matrix of each part affects each vertex pose2rot: bool, optional Flag on whether to convert the input pose tensor to rotation matrices. The default value is True. If False, then the pose tensor should already contain rotation matrices and have a size of Bx(J + 1)x9 dtype: torch.dtype, optional Returns ------- verts: torch.tensor BxVx3 The vertices of the mesh after applying the shape and pose displacements. joints: torch.tensor BxJx3 The joints of the model ''' batch_size = max(betas.shape[0], pose.shape[0]) device = betas.device # Add shape contribution v_shaped = v_template + blend_shapes(betas, shapedirs) # v_shaped *= scale # Get the joints # NxJx3 array J = vertices2joints(J_regressor, v_shaped) # 3. Add pose blend shapes # N x J x 3 x 3 ident = torch.eye(3, dtype=dtype, device=device) if pose2rot: rot_mats = batch_rodrigues( pose.view(-1, 3), dtype=dtype).view([batch_size, -1, 3, 3]) pose_feature = (rot_mats[:, 1:, :, :] - ident).view([batch_size, -1]) # (N x P) x (P, V * 3) -> N x V x 3 pose_offsets = torch.matmul(pose_feature, posedirs) \ .view(batch_size, -1, 3) else: pose_feature = pose[:, 1:].view(batch_size, -1, 3, 3) - ident rot_mats = pose.view(batch_size, -1, 3, 3) pose_offsets = torch.matmul(pose_feature.view(batch_size, -1), posedirs).view(batch_size, -1, 3) v_posed = pose_offsets + v_shaped # 4. Get the global joint location J_transformed, A = batch_rigid_transform(rot_mats, J, parents, dtype=dtype) # 5. Do skinning: # W is N x V x (J + 1) W = lbs_weights.unsqueeze(dim=0).expand([batch_size, -1, -1]) # (N x V x (J + 1)) x (N x (J + 1) x 16) num_joints = J_regressor.shape[0] T = torch.matmul(W, A.view(batch_size, num_joints, 16)) \ .view(batch_size, -1, 4, 4) homogen_coord = torch.ones([batch_size, v_posed.shape[1], 1], dtype=dtype, device=device) v_posed_homo = torch.cat([v_posed, homogen_coord], dim=2) v_homo = torch.matmul(T, torch.unsqueeze(v_posed_homo, dim=-1)) verts = v_homo[:, :, :3, 0] return verts, J_transformed def vertices2joints(J_regressor, vertices): ''' Calculates the 3D joint locations from the vertices Parameters ---------- J_regressor : torch.tensor JxV The regressor array that is used to calculate the joints from the position of the vertices vertices : torch.tensor BxVx3 The tensor of mesh vertices Returns ------- torch.tensor BxJx3 The location of the joints ''' return torch.einsum('bik,ji->bjk', [vertices, J_regressor]) def blend_shapes(betas, shape_disps): ''' Calculates the per vertex displacement due to the blend shapes Parameters ---------- betas : torch.tensor Bx(num_betas) Blend shape coefficients shape_disps: torch.tensor Vx3x(num_betas) Blend shapes Returns ------- torch.tensor BxVx3 The per-vertex displacement due to shape deformation ''' # Displacement[b, m, k] = sum_{l} betas[b, l] * shape_disps[m, k, l] # i.e. Multiply each shape displacement by its corresponding beta and # then sum them. blend_shape = torch.einsum('bl,mkl->bmk', [betas, shape_disps]) return blend_shape def batch_rodrigues(rot_vecs, epsilon=1e-8, dtype=torch.float32): ''' Calculates the rotation matrices for a batch of rotation vectors Parameters ---------- rot_vecs: torch.tensor Nx3 array of N axis-angle vectors Returns ------- R: torch.tensor Nx3x3 The rotation matrices for the given axis-angle parameters ''' batch_size = rot_vecs.shape[0] device = rot_vecs.device angle = torch.norm(rot_vecs + 1e-8, dim=1, keepdim=True) rot_dir = rot_vecs / angle cos = torch.unsqueeze(torch.cos(angle), dim=1) sin = torch.unsqueeze(torch.sin(angle), dim=1) # Bx1 arrays rx, ry, rz = torch.split(rot_dir, 1, dim=1) K = torch.zeros((batch_size, 3, 3), dtype=dtype, device=device) zeros = torch.zeros((batch_size, 1), dtype=dtype, device=device) K = torch.cat([zeros, -rz, ry, rz, zeros, -rx, -ry, rx, zeros], dim=1) \ .view((batch_size, 3, 3)) ident = torch.eye(3, dtype=dtype, device=device).unsqueeze(dim=0) rot_mat = ident + sin * K + (1 - cos) * torch.bmm(K, K) return rot_mat def transform_mat(R, t): ''' Creates a batch of transformation matrices Args: - R: Bx3x3 array of a batch of rotation matrices - t: Bx3x1 array of a batch of translation vectors Returns: - T: Bx4x4 Transformation matrix ''' # No padding left or right, only add an extra row return torch.cat([F.pad(R, [0, 0, 0, 1]), F.pad(t, [0, 0, 0, 1], value=1)], dim=2) def batch_rigid_transform(rot_mats, joints, parents, dtype=torch.float32): """ Applies a batch of rigid transformations to the joints Parameters ---------- rot_mats : torch.tensor BxNx3x3 Tensor of rotation matrices joints : torch.tensor BxNx3 Locations of joints parents : torch.tensor BxN The kinematic tree of each object dtype : torch.dtype, optional: The data type of the created tensors, the default is torch.float32 Returns ------- posed_joints : torch.tensor BxNx3 The locations of the joints after applying the pose rotations rel_transforms : torch.tensor BxNx4x4 The relative (with respect to the root joint) rigid transformations for all the joints """ joints = torch.unsqueeze(joints, dim=-1) rel_joints = joints.clone() rel_joints[:, 1:] -= joints[:, parents[1:]] transforms_mat = transform_mat( rot_mats.reshape(-1, 3, 3), rel_joints.reshape(-1, 3, 1)).reshape(-1, joints.shape[1], 4, 4) # transforms_mat[:, 0][:,:3,:3] *= scale transform_chain = [transforms_mat[:, 0]] for i in range(1, parents.shape[0]): # Subtract the joint location at the rest pose # No need for rotation, since it's identity when at rest curr_res = torch.matmul(transform_chain[parents[i]], transforms_mat[:, i]) transform_chain.append(curr_res) transforms = torch.stack(transform_chain, dim=1) # The last column of the transformations contains the posed joints posed_joints = transforms[:, :, :3, 3] # The last column of the transformations contains the posed joints posed_joints = transforms[:, :, :3, 3] joints_homogen = F.pad(joints, [0, 0, 0, 1]) rel_transforms = transforms - F.pad( torch.matmul(transforms, joints_homogen), [3, 0, 0, 0, 0, 0, 0, 0]) return posed_joints, rel_transforms
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""" foxBMS Software License Copyright 2010-2016, Fraunhofer-Gesellschaft zur Foerderung der angewandten Forschung e.V. All rights reserved. BSD 3-Clause License Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. We kindly request you to use one or more of the following phrases to refer to foxBMS in your hardware, software, documentation or advertising materials: "This product uses parts of foxBMS" "This product includes parts of foxBMS" "This product is derived from foxBMS" If you use foxBMS in your products, we encourage you to contact us at: CONTACT INFORMATION Fraunhofer IISB ; Schottkystrasse 10 ; 91058 Erlangen, Germany Dr.-Ing. Vincent LORENTZ +49 9131-761-346 info@foxbms.org www.foxbms.org :author: Martin Giegerich <martin.giegerich@iisb.fraunhofer.de> """ import stm32interface import argparse import sys import logging """ flash tool implementation to the STM32F4 microcontroller - for detailed insight to the USART protocol refer to STM32 appnote AN3155 - for detailed insight to the device bootloader" refer to STM32 appnote AN2606 """ class STM32Flasher(stm32interface.STM32Interface): def __init__(self, port = None, file = None, baudrate=115200, address = 0x08000000, goaddress = -1, bytes = 256,**kwargs): stm32interface.STM32Interface.__init__(self, port, baudrate) self._file = file self.bytes = bytes self.address = address self._doBeforeInit() self.init() def _doBeforeInit(self): ''' abstract method to optionally reset microcontroller or toggle boot pins ''' pass def __enter__(self): return self def read(self): data = [] length = self.bytes address = self.address logging.debug("Flash Read Start, Length: {0}, Address: {1:#x} ".format(length, address)) while length > 256: logging.debug("Read {0} bytes at {1:#x}".format(256, address)) data = data + self.readMemory(address, 256) address += 256 length -= 256 logging.info("[{0}/{1}] read ".format(self.bytes-length, self.bytes)) logging.debug("Read {0} bytes at {1:#x}".format(length, address)) data = data + self.readMemory(address, length) logging.info("[{0}/{1}] read".format(self.bytes, self.bytes)) return data def write(self, data): logging.debug("Flash Write Start") length = len(data) alllng = len(data) address = self.address offset = 0 while length > 256: logging.debug("Write {0} bytes at {1:#x}".format(256, address)) self.writeMemory(address, data[offset:offset+256]) offset += 256 address += 256 length -= 256 logging.info("[{0}/{1}] written".format(alllng-length, alllng)) logging.debug("Write {0} bytes at {1:#x}".format(length, address)) self.writeMemory(address, data[offset:offset+length] ) logging.info("[{0}/{1}] written".format(alllng, alllng)) #logging.info("Flash Write End") def erase(self): logging.info("Flash Erase Start") super(STM32Flasher, self).erase() logging.info("Flash Erase End") def verify(self, data): logging.info("Flash verify") self.bytes = len(data) verify = self.read() if data == verify: logging.info("Verify successful") return True else: self.veriFail = str(len(data)) + ' vs ' + str(len(verify)) + '\n' for i in xrange(0, len(data)): if data[i] != verify[i]: self.veriFail += hex(i) + ': ' + hex(data[i]) + ' vs ' + hex(verify[i]) + '\n' logging.error(self.veriFail) return False def __str__(self): id = self.getId()[1:3] # id without length byte and ack byte version = self.getVersion() return "ID: %s Bootloader version: %x" % (hex(reduce(lambda x, y: x*0x100+y, id)), version[0]) def auto_int(x): return int(x, 0) def main(): parser = argparse.ArgumentParser(description='STM32 flash tool', formatter_class=argparse.RawDescriptionHelpFormatter, epilog = '''\ Example: %s --port COM3 --erase --write --verify build/src/general/foxbms_flash.bin Copyright (c) 2015, 2016 Fraunhofer IISB. All rights reserved. This program has been released under the conditions of the 3-clause BSD license. ''' % sys.argv[0]) parser.add_argument('-v', '--verbosity', action='count', default=0, help="increase output verbosity") parser.add_argument('--erase', '-e', action='store_true', help='erase firmware') parser.add_argument('--read', '-r', action='store_true', help='read and store firmware') parser.add_argument('--write', '-w', action='store_true', help='writes firmware') parser.add_argument('--verify', '-y', action='store_true', help='verify the firmware') parser.add_argument('--bytes', '-s', type=int, default = 256, help='bytes to read from the firmware') parser.add_argument('--bauds', '-b', type=int, default=115200, help='transfer speed (bauds)') parser.add_argument('--port', '-p', type=str, default='/dev/tty.usbserial-ftCYPMYJ', help='ttyUSB port') parser.add_argument('--address', '-a', type=auto_int, default=0x08000000, help='target address') parser.add_argument('--goaddress', '-g', type=auto_int, default=-1, help='start address (use -1 for default)') parser.add_argument('firmware', metavar = 'FIRMWARE FILE', help='firmware binary') args = parser.parse_args() if args.verbosity == 1: logging.basicConfig(level = logging.INFO) elif args.verbosity > 1: logging.basicConfig(level = logging.DEBUG) else: logging.basicConfig(level = logging.ERROR) if args.read: if args.erase: parser.error('Cannot use --erase together with --read') if args.write: parser.error('Cannot use --write together with --read') if args.bytes == None: parser.error('Please give a length (in bytes) to read') with STM32Flasher(**vars(args)) as flasher: if args.write or args.verify: with open(args.firmware, 'rb') as f: data = map(lambda c: ord(c), f.read()) if args.erase: flasher.erase() if args.write: flasher.write(data) if args.verify: flasher.verify(data) if args.read: rdata = flasher.read() with open(args.firmware, 'wb') as f: f.write(''.join(map(chr,rdata))) if args.goaddress > -1: flasher.go(args.goaddress) if __name__ == "__main__": main()
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#!/usr/bin/env python # -*- coding: utf-8 -*- import country_converter as coco import pandas as pd from covsirphy.util.term import Term from covsirphy.loading.db_base import _RemoteDatabase class _OWID(_RemoteDatabase): """ Access "Our World In Data". https://github.com/owid/covid-19-data/tree/master/public/data https://ourworldindata.org/coronavirus Args: filename (str): CSV filename to save records """ # URL for vaccine data URL_V = "https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/vaccinations/" URL_V_REC = f"{URL_V}vaccinations.csv" URL_V_LOC = f"{URL_V}locations.csv" # URL for PCR data URL_P = "https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/testing/" URL_P_REC = f"{URL_P}covid-testing-all-observations.csv" # Citation CITATION = "Hasell, J., Mathieu, E., Beltekian, D. et al." \ " A cross-country database of COVID-19 testing. Sci Data 7, 345 (2020)." \ " https://doi.org/10.1038/s41597-020-00688-8" # Column names and data types # {"name in database": "name defined in Term class"} COL_DICT = { "date": Term.DATE, "location": Term.COUNTRY, Term.PROVINCE: Term.PROVINCE, "iso_code": Term.ISO3, "vaccines": Term.PRODUCT, "total_vaccinations": Term.VAC, "people_vaccinated": Term.V_ONCE, "people_fully_vaccinated": Term.V_FULL, "tests": Term.TESTS, } def download(self, verbose): """ Download the dataset from the server and set the list of primary sources. Args: verbose (int): level of verbosity Returns: pandas.DataFrame Index reset index Columns defined by the first values of self.COL_DICT.values() Note: If @verbose is equal to or over 1, how to show the list will be explained. """ # Download datasets if verbose: print("Retrieving datasets from Our World In Data https://github.com/owid/covid-19-data/") # Vaccinations v_rec_cols = [ "date", "location", "iso_code", "total_vaccinations", "people_vaccinated", "people_fully_vaccinated"] v_rec_df = pd.read_csv(self.URL_V_REC, usecols=v_rec_cols) v_loc_df = pd.read_csv(self.URL_V_LOC, usecols=["location", "vaccines"]) v_df = v_rec_df.merge(v_loc_df, how="left", on="location") # Tests pcr_rec_cols = ["ISO code", "Date", "Daily change in cumulative total", "Cumulative total"] pcr_df = pd.read_csv(self.URL_P_REC, usecols=pcr_rec_cols) pcr_df = pcr_df.rename(columns={"ISO code": "iso_code", "Date": "date"}) pcr_df["cumsum"] = pcr_df.groupby("iso_code")["Daily change in cumulative total"].cumsum() pcr_df = pcr_df.assign(tests=lambda x: x["Cumulative total"].fillna(x["cumsum"])) # Combine data (vaccinations/tests) df = v_df.set_index(["iso_code", "date"]) df = df.combine_first(pcr_df.set_index(["iso_code", "date"]).loc[:, ["tests"]]) df = df.reset_index() # Location (country/province) df["location"] = df["location"].replace( { # COG "Congo": "Republic of the Congo", } ) df = df.loc[~df["iso_code"].str.contains("OWID_")] df["location"] = df.groupby("iso_code")["location"].bfill() df.loc[df["location"] == df["iso_code"], "location"] = None df.loc[df["location"].isna(), "location"] = df.loc[df["location"].isna(), "iso_code"].apply( lambda x: coco.convert(x, to="name_short", not_found=None)) df[self.PROVINCE] = self.UNKNOWN return df
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# ----------------------------------------------------------------------------- # # Copyright (C) 2021 CERN & Newcastle University for the benefit of the # BioDynaMo collaboration. 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. # # See the LICENSE file distributed with this work for details. # See the NOTICE file distributed with this work for additional information # regarding copyright ownership. # # ----------------------------------------------------------------------------- class Print: PURPLE = '\033[95m' CYAN = '\033[96m' DARKCYAN = '\033[36m' BLUE = '\033[94m' GREEN = '\033[92m' YELLOW = '\033[93m' RED = '\033[91m' BOLD = '\033[1m' UNDERLINE = '\033[4m' END = '\033[0m' @staticmethod def success(message): print(Print.BOLD + Print.GREEN + str(message) + Print.END) @staticmethod def error(message): print(Print.RED + str(message) + Print.END) @staticmethod def warning(message): print(Print.YELLOW + str(message) + Print.END) @staticmethod def new_step(message): print('\n' + Print.BOLD + Print.BLUE + str(message) + Print.END)
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from __future__ import unicode_literals, division, absolute_import from builtins import * # noqa pylint: disable=unused-import, redefined-builtin from io import StringIO import pytest from jinja2 import Template from flexget.entry import Entry from flexget.logger import capture_output from flexget.manager import get_parser, Session from flexget.task import TaskAbort from flexget.components.series import db def age_series(**kwargs): import datetime session = Session() session.query(db.EpisodeRelease).update({'first_seen': datetime.datetime.now() - datetime.timedelta(**kwargs)}) session.commit() @pytest.fixture(scope='class', params=['internal', 'guessit'], ids=['internal', 'guessit'], autouse=True) def config(request): """Override and parametrize default config fixture for all series tests.""" newconfig = Template(request.cls.config).render({'parser': request.param}) # Make sure we remembered to put the section in config assert request.cls.config != newconfig, 'config parameterization did nothing?' return newconfig class TestQuality(object): config = """ templates: global: parsing: series: {{parser}} tasks: exact_quality: mock: - {title: 'QTest.S01E01.HDTV.XViD-FlexGet'} - {title: 'QTest.S01E01.PDTV.XViD-FlexGet'} - {title: 'QTest.S01E01.DSR.XViD-FlexGet'} - {title: 'QTest.S01E01.1080p.XViD-FlexGet'} - {title: 'QTest.S01E01.720p.XViD-FlexGet'} series: - QTest: quality: 720p quality_fail: mock: - {title: 'Q2Test.S01E01.HDTV.XViD-FlexGet'} - {title: 'Q2Test.S01E01.PDTV.XViD-FlexGet'} - {title: 'Q2Test.S01E01.DSR.XViD-FlexGet'} series: - Q2Test: quality: 720p min_quality: mock: - {title: 'MinQTest.S01E01.HDTV.XViD-FlexGet'} - {title: 'MinQTest.S01E01.PDTV.XViD-FlexGet'} - {title: 'MinQTest.S01E01.DSR.XViD-FlexGet'} - {title: 'MinQTest.S01E01.1080p.XViD-FlexGet'} - {title: 'MinQTest.S01E01.720p.XViD-FlexGet'} series: - MinQTest: quality: ">720p" max_quality: mock: - {title: 'MaxQTest.S01E01.HDTV.XViD-FlexGet'} - {title: 'MaxQTest.S01E01.PDTV.XViD-FlexGet'} - {title: 'MaxQTest.S01E01.DSR.XViD-FlexGet'} - {title: 'MaxQTest.S01E01.1080p.XViD-FlexGet'} - {title: 'MaxQTest.S01E01.720p.XViD-FlexGet'} - {title: 'MaxQTest.S01E01.720p.bluray-FlexGet'} series: - MaxQTest: quality: "<720p <=HDTV" min_max_quality: mock: - {title: 'MinMaxQTest.S01E01.HDTV.XViD-FlexGet'} - {title: 'MinMaxQTest.S01E01.PDTV.XViD-FlexGet'} - {title: 'MinMaxQTest.S01E01.DSR.XViD-FlexGet'} - {title: 'MinMaxQTest.S01E01.720p.XViD-FlexGet'} - {title: 'MinMaxQTest.S01E01.HR.XViD-FlexGet'} - {title: 'MinMaxQTest.S01E01.1080p.XViD-FlexGet'} series: - MinMaxQTest: quality: 480p-hr max_unknown_quality: mock: - {title: 'MaxUnknownQTest.S01E01.XViD-FlexGet'} series: - MaxUnknownQTest: quality: "<=hdtv" quality_from_group: mock: - {title: 'GroupQual.S01E01.HDTV.XViD-FlexGet'} - {title: 'GroupQual.S01E01.PDTV.XViD-FlexGet'} - {title: 'GroupQual.S01E01.DSR.XViD-FlexGet'} - {title: 'GroupQual.S01E01.1080p.XViD-FlexGet'} - {title: 'GroupQual.S01E01.720p.XViD-FlexGet'} - {title: 'Other.S01E01.hdtv.dd5.1.XViD-FlexGet'} - {title: 'Other.S01E01.720p.hdtv.XViD-FlexGet'} series: 720P: - GroupQual # Test that an integer group name doesn't cause an exception. 1080: - Test hdtv <hr !dd5.1: - Other quality_in_series_name: mock: - title: my 720p show S01E01 - title: my 720p show S01E02 720p series: - my 720p show: quality: '<720p' """ def test_exact_quality(self, execute_task): """Series plugin: choose by quality""" task = execute_task('exact_quality') assert task.find_entry('accepted', title='QTest.S01E01.720p.XViD-FlexGet'), \ '720p should have been accepted' assert len(task.accepted) == 1, 'should have accepted only one' def test_quality_fail(self, execute_task): task = execute_task('quality_fail') assert not task.accepted, 'No qualities should have matched' def test_min_quality(self, execute_task): """Series plugin: min_quality""" task = execute_task('min_quality') assert task.find_entry('accepted', title='MinQTest.S01E01.1080p.XViD-FlexGet'), \ 'MinQTest.S01E01.1080p.XViD-FlexGet should have been accepted' assert len(task.accepted) == 1, 'should have accepted only one' def test_max_quality(self, execute_task): """Series plugin: max_quality""" task = execute_task('max_quality') assert task.find_entry('accepted', title='MaxQTest.S01E01.HDTV.XViD-FlexGet'), \ 'MaxQTest.S01E01.HDTV.XViD-FlexGet should have been accepted' assert len(task.accepted) == 1, 'should have accepted only one' def test_min_max_quality(self, execute_task): """Series plugin: min_quality with max_quality""" task = execute_task('min_max_quality') assert task.find_entry('accepted', title='MinMaxQTest.S01E01.HR.XViD-FlexGet'), \ 'MinMaxQTest.S01E01.HR.XViD-FlexGet should have been accepted' assert len(task.accepted) == 1, 'should have accepted only one' def test_max_unknown_quality(self, execute_task): """Series plugin: max quality with unknown quality""" task = execute_task('max_unknown_quality') assert len(task.accepted) == 1, 'should have accepted' def test_group_quality(self, execute_task): """Series plugin: quality from group name""" task = execute_task('quality_from_group') assert task.find_entry('accepted', title='GroupQual.S01E01.720p.XViD-FlexGet'), \ 'GroupQual.S01E01.720p.XViD-FlexGet should have been accepted' assert len(task.accepted) == 1, 'should have accepted only one (no entries should pass for series `other`' def test_quality_in_series_name(self, execute_task): """Make sure quality in title does not get parsed as quality""" task = execute_task('quality_in_series_name') assert task.find_entry('accepted', title='my 720p show S01E01'), \ 'quality in title should not have been parsed' assert len(task.accepted) == 1, 'should not have accepted 720p entry' class TestDatabase(object): config = """ templates: global: parsing: series: {{parser}} series: - some series - progress tasks: test_1: mock: - {title: 'Some.Series.S01E20.720p.XViD-FlexGet'} test_2: mock: - {title: 'Some.Series.S01E20.720p.XViD-DoppelGanger'} progress_1: mock: - {title: 'Progress.S01E20.720p-FlexGet'} - {title: 'Progress.S01E20.HDTV-FlexGet'} progress_2: mock: - {title: 'Progress.S01E20.720p.Another-FlexGet'} - {title: 'Progress.S01E20.HDTV-Another-FlexGet'} """ def test_database(self, execute_task): """Series plugin: simple database""" task = execute_task('test_1') task = execute_task('test_2') assert task.find_entry('rejected', title='Some.Series.S01E20.720p.XViD-DoppelGanger'), \ 'failed basic download remembering' def test_doppelgangers(self, execute_task): """Series plugin: doppelganger releases (dupes)""" task = execute_task('progress_1') assert task.find_entry('accepted', title='Progress.S01E20.720p-FlexGet'), \ 'best quality not accepted' # should not accept anything task = execute_task('progress_1') assert not task.accepted, 'repeated execution accepted' # introduce new doppelgangers task = execute_task('progress_2') assert not task.accepted, 'doppelgangers accepted' class TestFilterSeries(object): config = """ templates: global: parsing: series: {{parser}} tasks: test: mock: - {title: 'Some.Series.S01E20.720p.XViD-FlexGet'} - {title: 'Another.Series.S01E20.720p.XViD-FlexGet'} - {title: 'Another.Series.S01E21.1080p.H264-FlexGet'} - {title: 'Date.Series.10-11-2008.XViD'} - {title: 'Date.Series.10.12.2008.XViD'} - {title: 'Date.Series.2008-10-13.XViD'} - {title: 'Date.Series.10.14.09.XViD'} - {title: 'Date Series 2010 11 17 XViD'} - {title: 'Useless title', filename: 'Filename.Series.S01E26.XViD'} - {title: 'Empty.Description.S01E22.XViD', description: ''} # test chaining regexp: reject: - 1080p series: - another series - date series - filename series - empty description - (some) series metainfo_series_override: metainfo_series: yes mock: - {title: 'Test.Series.with.extra.crap.S01E02.PDTV.XViD-FlexGet'} - {title: 'Other.Show.with.extra.crap.S02E01.PDTV.XViD-FlexGet'} series: - Test Series test_all_series_mode: mock: - {title: 'Test.Series.S01E02.PDTV.XViD-FlexGet'} - {title: 'Test Series - 1x03 - PDTV XViD-FlexGet'} - {title: 'Other.Show.S02E01.PDTV.XViD-FlexGet'} - {title: 'other show season 2 episode 2'} - {title: 'Date.Show.03-29-2012.HDTV.XViD-FlexGet'} all_series: yes test_alternate_name: mock: - title: The.Show.S01E01 - title: Other.Name.S01E02 - title: many.names.S01E01 - title: name.1.S01E02 - title: name.2.S01E03 - title: paren.title.2013.S01E01 series: - The Show: alternate_name: Other Name - many names: alternate_name: - name 1 - name 2 - paren title (US): alternate_name: paren title 2013 test_input_order_preserved: series: - Some Show """ def test_smoke(self, execute_task): """Series plugin: test several standard features""" task = execute_task('test') # normal passing assert task.find_entry(title='Another.Series.S01E20.720p.XViD-FlexGet'), \ 'Another.Series.S01E20.720p.XViD-FlexGet should have passed' # series with brackets assert task.find_entry('accepted', title='Some.Series.S01E20.720p.XViD-FlexGet'), \ 'Some.Series.S01E20.720p.XViD-FlexGet should have been accepted' # date formats df = ['Date.Series.10-11-2008.XViD', 'Date.Series.10.12.2008.XViD', 'Date Series 2010 11 17 XViD', 'Date.Series.2008-10-13.XViD', 'Date.Series.10.14.09.XViD'] for d in df: entry = task.find_entry(title=d) assert entry, 'Date format did not match %s' % d assert 'series_parser' in entry, 'series_parser missing from %s' % d assert entry['series_parser'].id_type == 'date', '%s did not return three groups for dates' % d # parse from filename assert task.find_entry(filename='Filename.Series.S01E26.XViD'), 'Filename parsing failed' # empty description assert task.find_entry(title='Empty.Description.S01E22.XViD'), 'Empty Description failed' # chaining with regexp plugin assert task.find_entry('rejected', title='Another.Series.S01E21.1080p.H264-FlexGet'), \ 'regexp chaining' def test_metainfo_series_override(self, execute_task): """Series plugin: override metainfo_series""" task = execute_task('metainfo_series_override') # Make sure the metainfo_series plugin is working first entry = task.find_entry('entries', title='Other.Show.with.extra.crap.S02E01.PDTV.XViD-FlexGet') assert entry['series_guessed'], 'series should have been guessed' assert entry['series_name'] == entry['series_parser'].name == 'Other Show With Extra Crap', \ 'metainfo_series is not running' # Make sure the good series data overrode metainfo data for the listed series entry = task.find_entry('accepted', title='Test.Series.with.extra.crap.S01E02.PDTV.XViD-FlexGet') assert not entry.get('series_guessed'), 'series plugin should override series_guessed' assert entry['series_name'] == entry['series_parser'].name == 'Test Series', \ 'Series name should be \'Test Series\', was: entry: %s, parser: %s' % ( entry['series_name'], entry['series_parser'].name) def test_all_series_mode(self, execute_task): """Series plugin: test all option""" task = execute_task('test_all_series_mode') assert task.find_entry('accepted', title='Test.Series.S01E02.PDTV.XViD-FlexGet') task.find_entry('accepted', title='Test Series - 1x03 - PDTV XViD-FlexGet') entry = task.find_entry('accepted', title='Test Series - 1x03 - PDTV XViD-FlexGet') assert entry assert entry.get('series_name') == 'Test Series' entry = task.find_entry('accepted', title='Other.Show.S02E01.PDTV.XViD-FlexGet') assert entry.get('series_guessed') entry2 = task.find_entry('accepted', title='other show season 2 episode 2') # Make sure case is normalized so series are marked with the same name no matter the case in the title assert entry.get('series_name') == entry2.get( 'series_name') == 'Other Show', 'Series names should be in title case' entry = task.find_entry('accepted', title='Date.Show.03-29-2012.HDTV.XViD-FlexGet') assert entry.get('series_guessed') assert entry.get('series_name') == 'Date Show' def test_alternate_name(self, execute_task): task = execute_task('test_alternate_name') assert all(e.accepted for e in task.all_entries), 'All releases should have matched a show' @pytest.mark.parametrize('reverse', [False, True]) def test_input_order_preserved(self, manager, execute_task, reverse): """If multiple versions of an episode are acceptable, make sure the first one is accepted.""" entries = [ Entry(title='Some Show S01E01 720p proper', url='http://a'), Entry(title='Some Show S01E01 1080p', url='http://b') ] if reverse: entries.reverse() task = execute_task('test_input_order_preserved', options={'inject': entries}) assert task.accepted[0] == entries[0], 'first entry should have been accepted' class TestEpisodeAdvancement(object): config = """ templates: global: parsing: series: {{parser}} tasks: test_backwards_1: mock: - {title: 'backwards s02e12'} - {title: 'backwards s02e10'} series: - backwards test_backwards_2: mock: - {title: 'backwards s02e01'} series: - backwards test_backwards_3: mock: - {title: 'backwards s01e01'} series: - backwards test_backwards_okay_1: mock: - {title: 'backwards s01e02'} series: - backwards: tracking: backfill test_backwards_okay_2: mock: - {title: 'backwards s01e03'} series: - backwards: tracking: no test_forwards_1: mock: - {title: 'forwards s01e01'} series: - forwards test_forwards_2: mock: - {title: 'forwards s02e01'} series: - forwards test_forwards_3: mock: - {title: 'forwards s03e01'} series: - forwards test_forwards_4: mock: - {title: 'forwards s04e02'} series: - forwards test_forwards_5: mock: - {title: 'forwards s05e01'} series: - forwards test_forwards_okay_1: mock: - {title: 'forwards s05e01'} series: - forwards: tracking: no test_unordered: mock: - {title: 'zzz s01e05'} - {title: 'zzz s01e06'} - {title: 'zzz s01e07'} - {title: 'zzz s01e08'} - {title: 'zzz s01e09'} - {title: 'zzz s01e10'} - {title: 'zzz s01e15'} - {title: 'zzz s01e14'} - {title: 'zzz s01e13'} - {title: 'zzz s01e12'} - {title: 'zzz s01e11'} - {title: 'zzz s01e01'} series: - zzz test_seq1: mock: - title: seq 05 series: - seq test_seq2: mock: - title: seq 06 series: - seq test_seq3: mock: - title: seq 10 series: - seq test_seq4: mock: - title: seq 01 series: - seq """ def test_backwards(self, execute_task): """Series plugin: episode advancement (backwards)""" task = execute_task('test_backwards_1') assert task.find_entry('accepted', title='backwards s02e12'), \ 'backwards s02e12 should have been accepted' assert task.find_entry('accepted', title='backwards s02e10'), \ 'backwards s02e10 should have been accepted within grace margin' task = execute_task('test_backwards_2') assert task.find_entry('accepted', title='backwards s02e01'), \ 'backwards s02e01 should have been accepted, in current season' task = execute_task('test_backwards_3') assert task.find_entry('rejected', title='backwards s01e01'), \ 'backwards s01e01 should have been rejected, in previous season' task = execute_task('test_backwards_okay_1') assert task.find_entry('accepted', title='backwards s01e02'), \ 'backwards s01e01 should have been accepted, backfill enabled' task = execute_task('test_backwards_okay_2') assert task.find_entry('accepted', title='backwards s01e03'), \ 'backwards s01e01 should have been accepted, tracking off' def test_forwards(self, execute_task): """Series plugin: episode advancement (future)""" task = execute_task('test_forwards_1') assert task.find_entry('accepted', title='forwards s01e01'), \ 'forwards s01e01 should have been accepted' task = execute_task('test_forwards_2') assert task.find_entry('accepted', title='forwards s02e01'), \ 'forwards s02e01 should have been accepted' task = execute_task('test_forwards_3') assert task.find_entry('accepted', title='forwards s03e01'), \ 'forwards s03e01 should have been accepted' task = execute_task('test_forwards_4') assert task.find_entry('rejected', title='forwards s04e02'), \ 'forwards s04e02 should have been rejected' task = execute_task('test_forwards_5') assert task.find_entry('rejected', title='forwards s05e01'), \ 'forwards s05e01 should have been rejected' task = execute_task('test_forwards_okay_1') assert task.find_entry('accepted', title='forwards s05e01'), \ 'forwards s05e01 should have been accepted with tracking turned off' def test_unordered(self, execute_task): """Series plugin: unordered episode advancement""" task = execute_task('test_unordered') assert len(task.accepted) == 12, \ 'not everyone was accepted' def test_sequence(self, execute_task): # First should be accepted task = execute_task('test_seq1') entry = task.find_entry('accepted', title='seq 05') assert entry['series_id'] == 5 # Next in sequence should be accepted task = execute_task('test_seq2') entry = task.find_entry('accepted', title='seq 06') assert entry['series_id'] == 6 # Should be too far in the future task = execute_task('test_seq3') entry = task.find_entry(title='seq 10') assert entry not in task.accepted, 'Should have been too far in future' # Should be too far in the past task = execute_task('test_seq4') entry = task.find_entry(title='seq 01') assert entry not in task.accepted, 'Should have been too far in the past' class TestFilterSeriesPriority(object): config = """ templates: global: parsing: series: {{parser}} tasks: test: mock: - {title: 'foobar 720p s01e01'} - {title: 'foobar hdtv s01e01'} regexp: reject: - 720p series: - foobar """ def test_priorities(self, execute_task): """Series plugin: regexp plugin is able to reject before series plugin""" task = execute_task('test') assert task.find_entry('rejected', title='foobar 720p s01e01'), \ 'foobar 720p s01e01 should have been rejected' assert task.find_entry('accepted', title='foobar hdtv s01e01'), \ 'foobar hdtv s01e01 is not accepted' class TestPropers(object): config = """ templates: global: parsing: series: {{parser}} # prevents seen from rejecting on second execution, # we want to see that series is able to reject disable: builtins series: - test - foobar - asfd: quality: HR-1080p - V - tftest: propers: 3 hours - notest: propers: no tasks: propers_1: mock: - {title: 'Test.S01E01.720p-FlexGet'} # introduce proper, should be accepted propers_2: mock: - {title: 'Test.S01E01.720p.Proper-FlexGet'} # introduce non-proper, should not be downloaded propers_3: mock: - {title: 'Test.S01E01.FlexGet'} # introduce proper at the same time, should nuke non-proper and get proper proper_at_first: mock: - {title: 'Foobar.S01E01.720p.FlexGet'} - {title: 'Foobar.S01E01.720p.proper.FlexGet'} # test a lot of propers at once lot_propers: mock: - {title: 'V.2009.S01E01.PROPER.HDTV.A'} - {title: 'V.2009.S01E01.PROPER.HDTV.B'} - {title: 'V.2009.S01E01.PROPER.HDTV.C'} diff_quality_1: mock: - {title: 'Test.S01E02.720p-FlexGet'} # low quality proper, should not be accepted diff_quality_2: mock: - {title: 'Test.S01E02.HDTV.Proper-FlexGet'} # min + max quality with propers min_max_quality_1: mock: - {title: 'asfd.S01E01.720p-FlexGet'} min_max_quality_2: mock: - {title: 'asfd.S01E01.720p.Proper-FlexGet'} proper_timeframe_1: mock: - {title: 'TFTest.S01E01.720p-FlexGet'} proper_timeframe_2: mock: - {title: 'TFTest.S01E01.720p.proper-FlexGet'} no_propers_1: mock: - {title: 'NoTest.S01E01.720p-FlexGet'} no_propers_2: mock: - {title: 'NoTest.S01E01.720p.proper-FlexGet'} proper_upgrade_1: mock: - {title: 'Test.S02E01.hdtv.proper'} proper_upgrade_2: mock: - {title: 'Test.S02E01.hdtv.real.proper'} anime_proper_1: mock: - title: test 04v0 hdtv anime_proper_2: mock: - title: test 04 hdtv fastsub_proper_1: mock: - title: test s01e01 Fastsub hdtv fastsub_proper_2: mock: - title: test s01e01 Fastsub repack hdtv fastsub_proper_3: mock: - title: test s01e01 hdtv fastsub_proper_4: mock: - title: test s01e01 proper hdtv """ def test_propers_timeframe(self, execute_task): """Series plugin: propers timeframe""" task = execute_task('proper_timeframe_1') assert task.find_entry('accepted', title='TFTest.S01E01.720p-FlexGet'), \ 'Did not accept before timeframe' # let 6 hours pass age_series(hours=6) task = execute_task('proper_timeframe_2') assert task.find_entry('rejected', title='TFTest.S01E01.720p.proper-FlexGet'), \ 'Did not reject after proper timeframe' def test_no_propers(self, execute_task): """Series plugin: no propers at all""" task = execute_task('no_propers_1') assert len(task.accepted) == 1, 'broken badly' task = execute_task('no_propers_2') assert len(task.rejected) == 1, 'accepted proper' def test_min_max_propers(self, execute_task): """Series plugin: min max propers""" task = execute_task('min_max_quality_1') assert len(task.accepted) == 1, 'uhh, broken badly' task = execute_task('min_max_quality_2') assert len(task.accepted) == 1, 'should have accepted proper' def test_lot_propers(self, execute_task): """Series plugin: proper flood""" task = execute_task('lot_propers') assert len(task.accepted) == 1, 'should have accepted (only) one of the propers' def test_diff_quality_propers(self, execute_task): """Series plugin: proper in different/wrong quality""" task = execute_task('diff_quality_1') assert len(task.accepted) == 1 task = execute_task('diff_quality_2') assert len(task.accepted) == 0, 'should not have accepted lower quality proper' def test_propers(self, execute_task): """Series plugin: proper accepted after episode is downloaded""" # start with normal download ... task = execute_task('propers_1') assert task.find_entry('accepted', title='Test.S01E01.720p-FlexGet'), \ 'Test.S01E01-FlexGet should have been accepted' # rejects downloaded task = execute_task('propers_1') assert task.find_entry('rejected', title='Test.S01E01.720p-FlexGet'), \ 'Test.S01E01-FlexGet should have been rejected' # accepts proper task = execute_task('propers_2') assert task.find_entry('accepted', title='Test.S01E01.720p.Proper-FlexGet'), \ 'new undownloaded proper should have been accepted' # reject downloaded proper task = execute_task('propers_2') assert task.find_entry('rejected', title='Test.S01E01.720p.Proper-FlexGet'), \ 'downloaded proper should have been rejected' # reject episode that has been downloaded normally and with proper task = execute_task('propers_3') assert task.find_entry('rejected', title='Test.S01E01.FlexGet'), \ 'Test.S01E01.FlexGet should have been rejected' def test_proper_available(self, execute_task): """Series plugin: proper available immediately""" task = execute_task('proper_at_first') assert task.find_entry('accepted', title='Foobar.S01E01.720p.proper.FlexGet'), \ 'Foobar.S01E01.720p.proper.FlexGet should have been accepted' def test_proper_upgrade(self, execute_task): """Series plugin: real proper after proper""" task = execute_task('proper_upgrade_1') assert task.find_entry('accepted', title='Test.S02E01.hdtv.proper') task = execute_task('proper_upgrade_2') assert task.find_entry('accepted', title='Test.S02E01.hdtv.real.proper') def test_anime_proper(self, execute_task): task = execute_task('anime_proper_1') assert task.accepted, 'ep should have accepted' task = execute_task('anime_proper_2') assert task.accepted, 'proper ep should have been accepted' def test_fastsub_proper(self, execute_task): task = execute_task('fastsub_proper_1') assert task.accepted, 'ep should have accepted' task = execute_task('fastsub_proper_2') assert task.accepted, 'proper ep should have been accepted' task = execute_task('fastsub_proper_3') assert task.accepted, 'proper ep should have been accepted' task = execute_task('fastsub_proper_4') assert task.accepted, 'proper ep should have been accepted' class TestSimilarNames(object): # hmm, not very good way to test this .. seriesparser should be tested alone? config = """ templates: global: parsing: series: {{parser}} tasks: test: mock: - {title: 'FooBar.S03E01.DSR-FlexGet'} - {title: 'FooBar: FirstAlt.S02E01.DSR-FlexGet'} - {title: 'FooBar: SecondAlt.S01E01.DSR-FlexGet'} series: - FooBar - 'FooBar: FirstAlt' - 'FooBar: SecondAlt' test_ambiguous: mock: - title: Foo.2.2 series: - Foo: identified_by: sequence - Foo 2: identified_by: sequence """ def test_names(self, execute_task): """Series plugin: similar namings""" task = execute_task('test') assert task.find_entry('accepted', title='FooBar.S03E01.DSR-FlexGet'), 'Standard failed?' assert task.find_entry('accepted', title='FooBar: FirstAlt.S02E01.DSR-FlexGet'), 'FirstAlt failed' assert task.find_entry('accepted', title='FooBar: SecondAlt.S01E01.DSR-FlexGet'), 'SecondAlt failed' def test_ambiguous(self, execute_task): task = execute_task('test_ambiguous') # In the event of ambiguous match, more specific one should be chosen assert task.find_entry('accepted', title='Foo.2.2')['series_name'] == 'Foo 2' class TestDuplicates(object): config = """ templates: global: parsing: series: {{parser}} # just cleans log a bit .. disable: - seen tasks: test_dupes: mock: - {title: 'Foo.2009.S02E04.HDTV.XviD-2HD[FlexGet]'} - {title: 'Foo.2009.S02E04.HDTV.XviD-2HD[ASDF]'} series: - Foo 2009 test_1: mock: - {title: 'Foo.Bar.S02E04.HDTV.XviD-2HD[FlexGet]'} - {title: 'Foo.Bar.S02E04.HDTV.XviD-2HD[ASDF]'} series: - foo bar test_2: mock: - {title: 'Foo.Bar.S02E04.XviD-2HD[ASDF]'} - {title: 'Foo.Bar.S02E04.HDTV.720p.XviD-2HD[FlexGet]'} - {title: 'Foo.Bar.S02E04.DSRIP.XviD-2HD[ASDF]'} - {title: 'Foo.Bar.S02E04.HDTV.1080p.XviD-2HD[ASDF]'} - {title: 'Foo.Bar.S02E03.HDTV.XviD-FlexGet'} - {title: 'Foo.Bar.S02E05.720p.HDTV.XviD-YYY'} series: - foo bar test_true_dupes: mock: - {title: 'Dupe.S02E04.HDTV.XviD-FlexGet'} - {title: 'Dupe.S02E04.HDTV.XviD-FlexGet'} - {title: 'Dupe.S02E04.HDTV.XviD-FlexGet'} series: - dupe """ def test_dupes(self, execute_task): """Series plugin: dupes with same quality""" task = execute_task('test_dupes') assert len(task.accepted) == 1, 'accepted both' def test_true_dupes(self, execute_task): """Series plugin: true duplicate items""" task = execute_task('test_true_dupes') assert len(task.accepted) == 1, 'should have accepted (only) one' def test_downloaded(self, execute_task): """Series plugin: multiple downloaded and new episodes are handled correctly""" task = execute_task('test_1') task = execute_task('test_2') # these should be accepted accepted = ['Foo.Bar.S02E03.HDTV.XviD-FlexGet', 'Foo.Bar.S02E05.720p.HDTV.XviD-YYY'] for item in accepted: assert task.find_entry('accepted', title=item), \ '%s should have been accepted' % item # these should be rejected rejected = ['Foo.Bar.S02E04.XviD-2HD[ASDF]', 'Foo.Bar.S02E04.HDTV.720p.XviD-2HD[FlexGet]', 'Foo.Bar.S02E04.DSRIP.XviD-2HD[ASDF]', 'Foo.Bar.S02E04.HDTV.1080p.XviD-2HD[ASDF]'] for item in rejected: assert task.find_entry('rejected', title=item), \ '%s should have been rejected' % item class TestQualities(object): config = """ templates: global: parsing: series: {{parser}} disable: builtins series: - FooBar: qualities: - SDTV - 720p - 1080p - FooBaz: upgrade: yes qualities: - hdtv - hr - 720p - FooBum: quality: 720p-1080i upgrade: yes - FooD: target: 720p timeframe: 0 hours upgrade: yes tasks: test_1: mock: - {title: 'FooBar.S01E01.PDTV-FlexGet'} - {title: 'FooBar.S01E01.1080p-FlexGet'} - {title: 'FooBar.S01E01.HR-FlexGet'} test_2: mock: - {title: 'FooBar.S01E01.720p-FlexGet'} propers_1: mock: - {title: 'FooBar.S01E02.720p-FlexGet'} propers_2: mock: - {title: 'FooBar.S01E02.720p.Proper-FlexGet'} upgrade_1: mock: - {title: 'FooBaz.S01E02.pdtv-FlexGet'} - {title: 'FooBaz.S01E02.HR-FlexGet'} upgrade_2: mock: - {title: 'FooBaz.S01E02.720p-FlexGet'} - {title: 'FooBaz.S01E02.1080p-FlexGet'} upgrade_3: mock: - {title: 'FooBaz.S01E02.hdtv-FlexGet'} - {title: 'FooBaz.S01E02.720p rc-FlexGet'} quality_upgrade_1: mock: - title: FooBum.S03E01.1080p # too high - title: FooBum.S03E01.hdtv # too low - title: FooBum.S03E01.720p # in range quality_upgrade_2: mock: - title: FooBum.S03E01.1080i # should be upgraded to - title: FooBum.S03E01.720p-ver2 # Duplicate ep target_1: mock: - title: Food.S06E11.hdtv target_2: mock: - title: Food.S06E11.1080p - title: Food.S06E11.720p """ def test_qualities(self, execute_task): """Series plugin: qualities""" task = execute_task('test_1') assert task.find_entry('accepted', title='FooBar.S01E01.PDTV-FlexGet'), \ 'Didn''t accept FooBar.S01E01.PDTV-FlexGet' assert task.find_entry('accepted', title='FooBar.S01E01.1080p-FlexGet'), \ 'Didn''t accept FooBar.S01E01.1080p-FlexGet' assert not task.find_entry('accepted', title='FooBar.S01E01.HR-FlexGet'), \ 'Accepted FooBar.S01E01.HR-FlexGet' task = execute_task('test_2') assert task.find_entry('accepted', title='FooBar.S01E01.720p-FlexGet'), \ 'Didn''t accept FooBar.S01E01.720p-FlexGet' # test that it rejects them afterwards task = execute_task('test_1') assert task.find_entry('rejected', title='FooBar.S01E01.PDTV-FlexGet'), \ 'Didn\'t reject FooBar.S01E01.PDTV-FlexGet' assert task.find_entry('rejected', title='FooBar.S01E01.1080p-FlexGet'), \ 'Didn\'t reject FooBar.S01E01.1080p-FlexGet' assert not task.find_entry('accepted', title='FooBar.S01E01.HR-FlexGet'), \ 'Accepted FooBar.S01E01.HR-FlexGet' def test_propers(self, execute_task): """Series plugin: qualities + propers""" task = execute_task('propers_1') assert task.accepted task = execute_task('propers_2') assert task.accepted, 'proper not accepted' task = execute_task('propers_2') assert not task.accepted, 'proper accepted again' def test_qualities_upgrade(self, execute_task): task = execute_task('upgrade_1') assert task.find_entry('accepted', title='FooBaz.S01E02.HR-FlexGet'), 'HR quality should be accepted' assert len(task.accepted) == 1, 'Only best quality should be accepted' task = execute_task('upgrade_2') assert task.find_entry('accepted', title='FooBaz.S01E02.720p-FlexGet'), '720p quality should be accepted' assert len(task.accepted) == 1, 'Only best quality should be accepted' task = execute_task('upgrade_3') assert not task.accepted, 'Should not have accepted worse qualities' def test_quality_upgrade(self, execute_task): task = execute_task('quality_upgrade_1') assert len(task.accepted) == 1, 'Only one ep should have passed quality filter' assert task.find_entry('accepted', title='FooBum.S03E01.720p') task = execute_task('quality_upgrade_2') assert len(task.accepted) == 1, 'one ep should be valid upgrade' assert task.find_entry('accepted', title='FooBum.S03E01.1080i') def test_target_upgrade(self, execute_task): task = execute_task('target_1') assert len(task.accepted) == 1, 'Only one ep should have been grabbed' assert task.find_entry('accepted', title='Food.S06E11.hdtv') task = execute_task('target_2') assert len(task.accepted) == 1, 'one ep should be valid upgrade' assert task.find_entry('accepted', title='Food.S06E11.720p'), 'Should upgrade to `target`' class TestIdioticNumbering(object): config = """ templates: global: parsing: series: {{parser}} series: - FooBar: identified_by: ep tasks: test_1: mock: - {title: 'FooBar.S01E01.PDTV-FlexGet'} test_2: mock: - {title: 'FooBar.102.PDTV-FlexGet'} """ def test_idiotic(self, execute_task): """Series plugin: idiotic numbering scheme""" task = execute_task('test_1') task = execute_task('test_2') entry = task.find_entry(title='FooBar.102.PDTV-FlexGet') assert entry, 'entry not found?' assert entry['series_season'] == 1, 'season not detected' assert entry['series_episode'] == 2, 'episode not detected' class TestNormalization(object): config = """ templates: global: parsing: series: {{parser}} disable: [seen] tasks: test_1: mock: - {title: 'FooBar.S01E01.PDTV-FlexGet'} series: - FOOBAR test_2: mock: - {title: 'FooBar.S01E01.PDTV-aoeu'} series: - foobar test_3: mock: - title: Foo bar & co 2012.s01e01.sdtv.a series: - foo bar & co 2012 test_4: mock: - title: Foo bar & co 2012.s01e01.sdtv.b series: - Foo/Bar and Co. (2012) """ def test_capitalization(self, execute_task): """Series plugin: configuration capitalization""" task = execute_task('test_1') assert task.find_entry('accepted', title='FooBar.S01E01.PDTV-FlexGet') task = execute_task('test_2') assert task.find_entry('rejected', title='FooBar.S01E01.PDTV-aoeu') def test_normalization(self, execute_task): task = execute_task('test_3') assert task.find_entry('accepted', title='Foo bar & co 2012.s01e01.sdtv.a') task = execute_task('test_4') assert task.find_entry('rejected', title='Foo bar & co 2012.s01e01.sdtv.b') class TestMixedNumbering(object): config = """ templates: global: parsing: series: {{parser}} series: - FooBar: identified_by: ep tasks: test_1: mock: - {title: 'FooBar.S03E07.PDTV-FlexGet'} test_2: mock: - {title: 'FooBar.0307.PDTV-FlexGet'} """ def test_mixednumbering(self, execute_task): """Series plugin: Mixed series numbering""" task = execute_task('test_1') assert task.find_entry('accepted', title='FooBar.S03E07.PDTV-FlexGet') task = execute_task('test_2') assert task.find_entry('rejected', title='FooBar.0307.PDTV-FlexGet') class TestExact(object): config = """ templates: global: parsing: series: {{parser}} tasks: auto: mock: - {title: 'ABC.MIAMI.S01E01.PDTV-FlexGet'} - {title: 'ABC.S01E01.PDTV-FlexGet'} - {title: 'ABC.LA.S01E01.PDTV-FlexGet'} series: - ABC - ABC LA - ABC Miami name_regexp: mock: - title: show s09e05 hdtv - title: show a s09e06 hdtv series: - show: name_regexp: ^show exact: yes date: mock: - title: date show 04.01.2011 hdtv - title: date show b 04.02.2011 hdtv series: - date show: exact: yes """ def test_auto(self, execute_task): """Series plugin: auto enable exact""" task = execute_task('auto') assert task.find_entry('accepted', title='ABC.S01E01.PDTV-FlexGet') assert task.find_entry('accepted', title='ABC.LA.S01E01.PDTV-FlexGet') assert task.find_entry('accepted', title='ABC.MIAMI.S01E01.PDTV-FlexGet') def test_with_name_regexp(self, execute_task): task = execute_task('name_regexp') assert task.find_entry('accepted', title='show s09e05 hdtv') assert not task.find_entry('accepted', title='show a s09e06 hdtv') def test_dated_show(self, execute_task): task = execute_task('date') assert task.find_entry('accepted', title='date show 04.01.2011 hdtv') assert not task.find_entry('accepted', title='date show b 04.02.2011 hdtv') class TestTimeframe(object): config = """ templates: global: parsing: series: {{parser}} series: - test: timeframe: 5 hours target: 720p tasks: test_no_waiting: mock: - {title: 'Test.S01E01.720p-FlexGet'} test_stop_waiting_1: mock: - {title: 'Test.S01E02.HDTV-FlexGet'} test_stop_waiting_2: mock: - {title: 'Test.S01E02.720p-FlexGet'} test_proper_afterwards: mock: - {title: 'Test.S01E02.720p.Proper-FlexGet'} test_expires: mock: - {title: 'Test.S01E03.pdtv-FlexGet'} test_min_max_fail: series: - mm test: timeframe: 5 hours target: 720p quality: hdtv+ <=720p mock: - {title: 'MM Test.S01E02.pdtv-FlexGet'} - {title: 'MM Test.S01E02.1080p-FlexGet'} test_min_max_pass: series: - mm test: timeframe: 5 hours target: 720p quality: hdtv+ <=720p mock: - {title: 'MM Test.S01E02.pdtv-FlexGet'} - {title: 'MM Test.S01E02.hdtv-FlexGet'} - {title: 'MM Test.S01E02.1080p-FlexGet'} test_qualities_fail: series: - q test: timeframe: 5 hours qualities: - hdtv - 1080p mock: - {title: 'Q Test.S01E02.pdtv-FlexGet'} - {title: 'Q Test.S01E02.1080p-FlexGet'} test_qualities_pass: series: - q test: timeframe: 5 hours qualities: - sdtv - 720p mock: - {title: 'Q Test.S01E02.1080p-FlexGet'} test_with_quality_1: series: - q test: timeframe: 5 hours quality: hdtv+ target: 720p mock: - title: q test s01e01 pdtv 720p test_with_quality_2: series: - q test: timeframe: 5 hours quality: hdtv+ target: 720p mock: - title: q test s01e01 hdtv """ def test_no_waiting(self, execute_task): """Series plugin: no timeframe waiting needed""" task = execute_task('test_no_waiting') assert task.find_entry('accepted', title='Test.S01E01.720p-FlexGet'), \ '720p not accepted immediattely' def test_stop_waiting(self, execute_task): """Series plugin: timeframe quality appears, stop waiting, proper appears""" task = execute_task('test_stop_waiting_1') assert task.entries and not task.accepted task = execute_task('test_stop_waiting_2') assert task.find_entry('accepted', title='Test.S01E02.720p-FlexGet'), \ '720p should have caused stop waiting' task = execute_task('test_proper_afterwards') assert task.find_entry('accepted', title='Test.S01E02.720p.Proper-FlexGet'), \ 'proper should have been accepted' def test_expires(self, execute_task): """Series plugin: timeframe expires""" # first execution should not accept anything task = execute_task('test_expires') assert not task.accepted # let 3 hours pass age_series(hours=3) task = execute_task('test_expires') assert not task.accepted, 'expired too soon' # let another 3 hours pass, should expire now! age_series(hours=6) task = execute_task('test_expires') assert task.accepted, 'timeframe didn\'t expire' def test_min_max_fail(self, execute_task): task = execute_task('test_min_max_fail') assert not task.accepted # Let 6 hours pass, timeframe should not even been started, as pdtv doesn't meet min_quality age_series(hours=6) task = execute_task('test_min_max_fail') assert task.entries and not task.accepted def test_min_max_pass(self, execute_task): task = execute_task('test_min_max_pass') assert not task.accepted # Let 6 hours pass, timeframe should expire and accept hdtv copy age_series(hours=6) task = execute_task('test_min_max_pass') assert task.find_entry('accepted', title='MM Test.S01E02.hdtv-FlexGet') assert len(task.accepted) == 1 def test_qualities_fail(self, execute_task): task = execute_task('test_qualities_fail') assert task.find_entry('accepted', title='Q Test.S01E02.1080p-FlexGet'), \ 'should have accepted wanted quality' assert len(task.accepted) == 1 # Let 6 hours pass, timeframe should not even been started, as we already have one of our qualities age_series(hours=6) task = execute_task('test_qualities_fail') assert task.entries and not task.accepted def test_qualities_pass(self, execute_task): task = execute_task('test_qualities_pass') assert not task.accepted, 'None of the qualities should have matched' # Let 6 hours pass, timeframe should expire and accept 1080p copy age_series(hours=6) task = execute_task('test_qualities_pass') assert task.find_entry('accepted', title='Q Test.S01E02.1080p-FlexGet') assert len(task.accepted) == 1 def test_with_quality(self, execute_task): task = execute_task('test_with_quality_1') assert not task.accepted, 'Entry does not pass quality' age_series(hours=6) # Entry from first test feed should not pass quality task = execute_task('test_with_quality_1') assert not task.accepted, 'Entry does not pass quality' # Timeframe should not yet have started task = execute_task('test_with_quality_2') assert not task.accepted, 'Timeframe should not yet have passed' age_series(hours=6) task = execute_task('test_with_quality_2') assert task.accepted, 'Timeframe should have passed' class TestBacklog(object): config = """ templates: global: parsing: series: {{parser}} tasks: backlog: mock: - {title: 'Test.S01E01.hdtv-FlexGet'} series: - test: {timeframe: 6 hours} """ def testBacklog(self, manager, execute_task): """Series plugin: backlog""" task = execute_task('backlog') assert task.entries and not task.accepted, 'no entries at the start' # simulate test going away from the task del (manager.config['tasks']['backlog']['mock']) age_series(hours=12) task = execute_task('backlog') assert task.accepted, 'backlog is not injecting episodes' class TestManipulate(object): """Tests that it's possible to manipulate entries before they're parsed by series plugin""" config = """ templates: global: parsing: series: {{parser}} tasks: test_1: mock: - {title: 'PREFIX: Test.S01E01.hdtv-FlexGet'} series: - test test_2: mock: - {title: 'PREFIX: Test.S01E01.hdtv-FlexGet'} series: - test manipulate: - title: extract: '^PREFIX: (.*)' """ def testManipulate(self, execute_task): """Series plugin: test manipulation priority""" # should not work with the prefix task = execute_task('test_1') assert not task.accepted, 'series accepted even with prefix?' assert not task.accepted, 'series rejecte even with prefix?' task = execute_task('test_2') assert task.accepted, 'manipulate failed to pre-clean title' class TestFromGroup(object): config = """ templates: global: parsing: series: {{parser}} tasks: test: mock: - {title: '[Ignored] Test 12'} - {title: '[FlexGet] Test 12'} - {title: 'Test.13.HDTV-Ignored'} - {title: 'Test.13.HDTV-FlexGet'} - {title: 'Test.14.HDTV-Name'} - {title: 'Test :: h264 10-bit | Softsubs (FlexGet) | Episode 3'} - {title: 'Test :: h264 10-bit | Softsubs (Ignore) | Episode 3'} series: - test: {from_group: [Name, FlexGet]} """ def test_from_group(self, execute_task): """Series plugin: test from_group""" task = execute_task('test') assert task.find_entry('accepted', title='[FlexGet] Test 12') assert task.find_entry('accepted', title='Test.13.HDTV-FlexGet') assert task.find_entry('accepted', title='Test.14.HDTV-Name') assert task.find_entry('accepted', title='Test :: h264 10-bit | Softsubs (FlexGet) | Episode 3') class TestBegin(object): config = """ templates: global: parsing: series: {{parser}} eps: mock: - {title: 'WTest.S02E03.HDTV.XViD-FlexGet'} - {title: 'W2Test.S02E03.HDTV.XViD-FlexGet'} tasks: season_id_test: template: eps series: - WTest: begin: S02 - W2Test: begin: S03 before_ep_test: template: eps series: - WTest: begin: S02E05 - W2Test: begin: S03E02 after_ep_test: template: eps series: - WTest: begin: S02E03 - W2Test: begin: S02E01 before_seq_test: mock: - title: WTest.1.HDTV.XViD-FlexGet - title: W2Test.13.HDTV.XViD-FlexGet series: - WTest: begin: 2 - W2Test: begin: 120 after_seq_test: mock: - title: WTest.2.HDTV.XViD-FlexGet - title: W2Test.123.HDTV.XViD-FlexGet series: - WTest: begin: 2 - W2Test: begin: 120 before_date_test: mock: - title: WTest.2001.6.6.HDTV.XViD-FlexGet - title: W2Test.12.30.2012.HDTV.XViD-FlexGet series: - WTest: begin: '2009-05-05' - W2Test: begin: '2012-12-31' after_date_test: mock: - title: WTest.2009.5.5.HDTV.XViD-FlexGet - title: W2Test.1.1.2013.HDTV.XViD-FlexGet series: - WTest: begin: '2009-05-05' - W2Test: begin: '2012-12-31' test_advancement1: mock: - title: WTest.S01E01 series: - WTest test_advancement2: mock: - title: WTest.S03E01 series: - WTest test_advancement3: mock: - title: WTest.S03E01 series: - WTest: begin: S03E01 """ def test_season_id(self, execute_task): task = execute_task('season_id_test') assert task.find_entry('accepted', title='WTest.S02E03.HDTV.XViD-FlexGet'), \ 'Entry should have been accepted, it\'s after the begin episode' assert task.find_entry('rejected', title='W2Test.S02E03.HDTV.XViD-FlexGet'), \ 'Entry should have been rejected, it\'s before the begin episode' def test_before_ep(self, execute_task): task = execute_task('before_ep_test') assert not task.accepted, 'No entries should have been accepted, they are before the begin episode' def test_after_ep(self, execute_task): task = execute_task('after_ep_test') assert len(task.accepted) == 2, 'Entries should have been accepted, they are not before the begin episode' def test_before_seq(self, execute_task): task = execute_task('before_seq_test') assert not task.accepted, 'No entries should have been accepted, they are before the begin episode' def test_after_seq(self, execute_task): task = execute_task('after_seq_test') assert len(task.accepted) == 2, 'Entries should have been accepted, they are not before the begin episode' def test_before_date(self, execute_task): task = execute_task('before_date_test') assert not task.accepted, 'No entries should have been accepted, they are before the begin episode' def test_after_date(self, execute_task): task = execute_task('after_date_test') assert len(task.accepted) == 2, 'Entries should have been accepted, they are not before the begin episode' def test_advancement(self, execute_task): # Put S01E01 into the database as latest download task = execute_task('test_advancement1') assert task.accepted # Just verify regular ep advancement would block S03E01 task = execute_task('test_advancement2') assert not task.accepted, 'Episode advancement should have blocked' # Make sure ep advancement doesn't block it when we've set begin to that ep task = execute_task('test_advancement3') assert task.accepted, 'Episode should have been accepted' class TestSeriesPremiere(object): config = """ templates: global: parsing: series: {{parser}} metainfo_series: yes series_premiere: yes tasks: test: mock: - {title: 'Foobar.S01E01.PDTV-FlexGet'} - {title: 'Foobar.S01E11.1080p-FlexGet'} - {title: 'Foobar.S02E02.HR-FlexGet'} """ def testOnlyPremieres(self, execute_task): """Test series premiere""" task = execute_task('test') assert task.find_entry('accepted', title='Foobar.S01E01.PDTV-FlexGet', series_name='Foobar', series_season=1, series_episode=1), 'Series premiere should have been accepted' assert len(task.accepted) == 1 # TODO: Add more tests, test interaction with series plugin and series_exists class TestImportSeries(object): config = """ templates: global: parsing: series: {{parser}} tasks: timeframe_max: configure_series: settings: propers: 12 hours target: 720p timeframe: 5 minutes quality: "<=720p <=bluray" from: mock: - title: the show mock: - title: the show s03e02 1080p bluray - title: the show s03e02 hdtv test_import_altnames: configure_series: from: mock: - {title: 'the show', configure_series_alternate_name: 'le show'} mock: - title: le show s03e03 """ def test_timeframe_max(self, execute_task): """Tests configure_series as well as timeframe with max_quality.""" task = execute_task('timeframe_max') assert not task.accepted, 'Entry shouldnot have been accepted on first run.' age_series(minutes=6) task = execute_task('timeframe_max') assert task.find_entry('accepted', title='the show s03e02 hdtv'), \ 'hdtv should have been accepted after timeframe.' def test_import_altnames(self, execute_task): """Tests configure_series with alternate_name.""" task = execute_task('test_import_altnames') entry = task.find_entry(title='le show s03e03') assert entry.accepted, 'entry matching series alternate name should have been accepted.' assert entry['series_name'] == 'the show', 'entry series should be set to the main name' class TestIDTypes(object): config = """ templates: global: parsing: series: {{parser}} tasks: all_types: series: - episode - seasonless episode - date - sequence - stupid id: id_regexp: (\\dcat) mock: - title: episode S03E04 - title: episode 3x05 - title: date 2011.4.3 other crap hdtv - title: date 4.5.11 - title: sequence 003 - title: sequence 4 - title: stupid id 3cat - title: seasonless episode e01 """ def test_id_types(self, execute_task): task = execute_task('all_types') for entry in task.entries: assert entry['series_name'], '%s not parsed by series plugin' % entry['title'] assert entry['series_id_type'] in entry['series_name'] class TestCaseChange(object): config = """ templates: global: parsing: series: {{parser}} tasks: first: mock: - title: theshow s02e04 series: - TheShow second: mock: - title: thEshoW s02e04 other series: - THESHOW """ def test_case_change(self, execute_task): task = execute_task('first') # Make sure series_name uses case from config, make sure episode is accepted assert task.find_entry('accepted', title='theshow s02e04', series_name='TheShow') task = execute_task('second') # Make sure series_name uses new case from config, make sure ep is rejected because we have a copy assert task.find_entry('rejected', title='thEshoW s02e04 other', series_name='THESHOW') class TestInvalidSeries(object): config = """ templates: global: parsing: series: {{parser}} tasks: blank: mock: - title: whatever series: - '': quality: 720p """ def test_blank_series(self, execute_task): """Make sure a blank series doesn't crash.""" task = execute_task('blank') assert not task.aborted, 'Task should not have aborted' class TestDoubleEps(object): config = """ templates: global: parsing: series: {{parser}} tasks: test_double1: mock: - title: double S01E02-E03 series: - double test_double2: mock: - title: double S01E03 series: - double """ def test_double(self, execute_task): # First should be accepted task = execute_task('test_double1') assert task.find_entry('accepted', title='double S01E02-E03') # We already got ep 3 as part of double, should not be accepted task = execute_task('test_double2') assert not task.find_entry('accepted', title='double S01E03') class TestAutoLockin(object): config = """ templates: global: parsing: series: {{parser}} series: - FooBar - BarFood tasks: try_date_1: mock: - title: FooBar 2012-10-10 HDTV lock_ep: mock: - title: FooBar S01E01 HDTV - title: FooBar S01E02 HDTV - title: FooBar S01E03 HDTV try_date_2: mock: - title: FooBar 2012-10-11 HDTV test_special_lock: mock: - title: BarFood christmas special HDTV - title: BarFood easter special HDTV - title: BarFood haloween special HDTV - title: BarFood bad special HDTV try_reg: mock: - title: BarFood S01E01 HDTV - title: BarFood 2012-9-9 HDTV """ def test_ep_lockin(self, execute_task): task = execute_task('try_date_1') assert task.find_entry('accepted', title='FooBar 2012-10-10 HDTV'), \ 'dates should be accepted before locked in on an identifier type' task = execute_task('lock_ep') assert len(task.accepted) == 3, 'All ep mode episodes should have been accepted' task = execute_task('try_date_2') assert not task.find_entry('accepted', title='FooBar 2012-10-11 HDTV'), \ 'dates should not be accepted after series has locked in to ep mode' def test_special_lock(self, execute_task): """Make sure series plugin does not lock in to type 'special'""" task = execute_task('test_special_lock') assert len(task.accepted) == 4, 'All specials should have been accepted' task = execute_task('try_reg') assert len(task.accepted) == 2, 'Specials should not have caused episode type lock-in' class TestReruns(object): config = """ templates: global: parsing: series: {{parser}} tasks: one_accept: mock: - title: the show s01e01 - title: the show s01e01 different series: - the show rerun: 2 mock_output: yes """ def test_one_accept(self, execute_task): task = execute_task('one_accept') assert len(task.mock_output) == 1, \ 'should have accepted once!: %s' % ', '.join(e['title'] for e in task.mock_output) class TestSpecials(object): config = """ templates: global: parsing: series: {{parser}} tasks: preferspecials: mock: - title: the show s03e04 special series: - the show: prefer_specials: True nopreferspecials: mock: - title: the show s03e05 special series: - the show: prefer_specials: False assumespecial: mock: - title: the show SOMETHING series: - the show: assume_special: True noassumespecial: mock: - title: the show SOMETHING series: - the show: assume_special: False special_looks_like_season_pack: mock: - title: Doctor.Who.S07.Special.The.Science.of.Doctor.Who.WS.XviD-Flexget series: - Doctor Who """ def test_prefer_specials(self, execute_task): # Test that an entry matching both ep and special is flagged as a special when prefer_specials is True task = execute_task('preferspecials') entry = task.find_entry('accepted', title='the show s03e04 special') assert entry.get('series_id_type') == 'special', 'Entry which should have been flagged a special was not.' def test_not_prefer_specials(self, execute_task): # Test that an entry matching both ep and special is flagged as an ep when prefer_specials is False task = execute_task('nopreferspecials') entry = task.find_entry('accepted', title='the show s03e05 special') assert entry.get('series_id_type') != 'special', 'Entry which should not have been flagged a special was.' def test_assume_special(self, execute_task): # Test that an entry with no ID found gets flagged as a special and accepted if assume_special is True task = execute_task('assumespecial') entry = task.find_entry(title='the show SOMETHING') assert entry.get('series_id_type') == 'special', 'Entry which should have been flagged as a special was not.' assert entry.accepted, 'Entry which should have been accepted was not.' def test_not_assume_special(self, execute_task): # Test that an entry with no ID found does not get flagged as a special and accepted if assume_special is False task = execute_task('noassumespecial') entry = task.find_entry(title='the show SOMETHING') assert entry.get('series_id_type') != 'special', 'Entry which should not have been flagged as a special was.' assert not entry.accepted, 'Entry which should not have been accepted was.' def test_special_looks_like_a_season_pack(self, execute_task): """Make sure special episodes are not being parsed as season packs""" task = execute_task('special_looks_like_season_pack') entry = task.find_entry(title='Doctor.Who.S07.Special.The.Science.of.Doctor.Who.WS.XviD-Flexget') assert entry.get('series_id_type') == 'special', 'Entry should have been flagged as a special' assert not entry['season_pack'], 'Entry should not have been flagged as a season pack' assert entry.accepted, 'Entry which should not have been accepted was.' class TestAlternateNames(object): config = """ templates: global: parsing: series: {{parser}} tasks: alternate_name: series: - Some Show: begin: S01E01 alternate_name: Other Show another_alternate_name: series: - Some Show: alternate_name: Good Show set_other_alternate_name: mock: - title: Third.Show.S01E01 - title: Other.Show.S01E01 series: - Some Show: alternate_name: Third Show rerun: 0 duplicate_names_in_different_series: series: - First Show: begin: S01E01 alternate_name: Third Show - Second Show: begin: S01E01 alternate_name: Third Show """ def test_set_alternate_name(self, execute_task): # Tests that old alternate names are not kept in the database. task = execute_task('alternate_name') task = execute_task('set_other_alternate_name') assert task.find_entry('accepted', title='Third.Show.S01E01'), \ 'A new alternate name should have been associated with the series.' assert task.find_entry('undecided', title='Other.Show.S01E01'), \ 'The old alternate name for the series is still present.' def test_duplicate_alternate_names_in_different_series(self, execute_task): with pytest.raises(TaskAbort) as ex: execute_task('duplicate_names_in_different_series') # only test that the reason is about alternate names, not which names. reason = 'Error adding alternate name' assert ex.value.reason[:27] == reason, \ 'Wrong reason for task abortion. Should be about duplicate alternate names.' # Test the DB behaves like we expect ie. alternate names cannot def test_alternate_names_are_removed_from_db(self, execute_task): from flexget.manager import Session with Session() as session: execute_task('alternate_name') # test the current state of alternate names assert len(session.query(db.AlternateNames).all()) == 1, 'There should be one alternate name present.' assert session.query(db.AlternateNames).first().alt_name == 'Other Show', \ 'Alternate name should have been Other Show.' # run another task that overwrites the alternate names execute_task('another_alternate_name') assert len(session.query(db.AlternateNames).all()) == 1, \ 'The old alternate name should have been removed from the database.' assert session.query(db.AlternateNames).first().alt_name == 'Good Show', \ 'The alternate name in the database should be the new one, Good Show.' class TestCLI(object): config = """ templates: global: parsing: series: {{parser}} tasks: learn_series: series: - Some Show - Other Show mock: - title: Some Series S01E01 - title: Other Series S01E02 """ def test_series_list(self, manager, execute_task): """Very rudimentary test, mostly makes sure this doesn't crash.""" execute_task('learn_series') options = get_parser().parse_args(['series', 'list', '--porcelain']) buffer = StringIO() with capture_output(buffer, loglevel='error'): manager.handle_cli(options=options) lines = buffer.getvalue().split('\n') assert all(any(line.lstrip().startswith(series) for line in lines) for series in ['Some Show', 'Other Show']) class TestSeriesRemove(object): config = """ templates: global: parsing: series: {{parser}} tasks: get_episode: seen: local series: - My Show mock: - title: My Show S01E01 1080p - title: My Show S01E01 720p remove_episode: seen: no mock: - title: My Show S01E01 series_name: My Show series_id: S01E01 accept_all: yes series_remove: yes """ def test_remove_episode(self, execute_task): task = execute_task('get_episode') assert len(task.accepted) == 1 first_rls = task.accepted[0] task = execute_task('get_episode') assert not task.accepted, 'series plugin duplicate blocking not working?' task = execute_task('remove_episode') task = execute_task('get_episode') assert len(task.accepted) == 1, 'new release not accepted after forgetting ep' assert task.accepted[0] != first_rls, 'same release accepted on second run' class TestSeriesSeasonPack(object): _config = """ templates: global: parsing: series: internal series: - foo: season_packs: yes - bar: season_packs: yes tracking: backfill - baz: season_packs: 3 - boo: season_packs: always - bla: season_packs: only - bro: season_packs: threshold: 1 reject_eps: yes tasks: multiple_formats: mock: - title: foo.s01.720p-flexget - title: foo.2xALL.720p-flexget foo_s01: mock: - title: foo.s01.720p-flexget foo_s02: mock: - title: foo.s02.720p-flexget foo_s03: mock: - title: foo.s03.720p-flexget foo_s01ep1: mock: - title: foo.s01e1.720p-flexget foo_s02ep1: mock: - title: foo.s02e1.720p-flexget season_pack_priority: mock: - title: foo.s01e1.720p-flexget - title: foo.s01e2.720p-flexget - title: foo.s01e3.720p-flexget - title: foo.s01e4.720p-flexget - title: foo.s01e5.720p-flexget - title: foo.s01.720p-flexget respect_begin: series: - bar: begin: s02e01 season_packs: yes mock: - title: bar.s01.720p-flexget - title: bar.s02.720p-flexget several_seasons: mock: - title: foo.s03.720p-flexget - title: foo.s07.720p-flexget - title: foo.s03.1080p-flexget - title: foo.s06.720p-flexget - title: foo.s09.720p-flexget test_backfill_1: mock: - title: bar.s03.720p-flexget test_backfill_2: mock: - title: bar.s02.720p-flexget test_backfill_3: mock: - title: bar.s03e01.720p-flexget test_backfill_4: mock: - title: bar.s02e01.1080p-flexget test_specific_season_pack_threshold_1: mock: - title: baz.s01e01.720p-flexget - title: baz.s01e02.720p-flexget - title: baz.s01e03.720p-flexget test_specific_season_pack_threshold_2: mock: - title: baz.s01.720p-flexget test_specific_season_pack_threshold_3: mock: - title: baz.s01e01.720p-flexget - title: baz.s01e02.720p-flexget - title: baz.s01e03.720p-flexget - title: baz.s01e04.720p-flexget test_always_get_season_pack_1: mock: - title: boo.s01e01.720p-flexget - title: boo.s01e02.720p-flexget - title: boo.s01e03.720p-flexget - title: boo.s01e04.720p-flexget test_always_get_season_pack_2: mock: - title: boo.s01.720p-flexget test_only_get_season_packs: mock: - title: bla.s01.720p-flexget - title: bla.s02e01.720p-flexget test_proper_season_pack: mock: - title: foo.s01.720p-flexget - title: foo.s01.720p.proper-flexget test_proper_season_pack_2: mock: - title: foo.s01.720p-flexget test_proper_season_pack_3: mock: - title: foo.s01.720p.proper-flexget test_all_series: mock: - title: show.name.s01.720p.HDTV-Group all_series: season_packs: yes test_with_dict_config_1: mock: - title: bro.s01e01.720p.HDTV-Flexget - title: bro.s01.720p.HDTV-Flexget test_with_dict_config_2: mock: - title: bro.s02.720p.HDTV-Flexget """ @pytest.fixture() def config(self): """Overrides outer config fixture since season pack support does not work with guessit parser""" return self._config def test_season_pack_simple(self, execute_task): task = execute_task('foo_s01') assert len(task.accepted) == 1 def test_basic_tracking(self, execute_task): task = execute_task('foo_s01') assert len(task.accepted) == 1 task = execute_task('foo_s01ep1') assert len(task.accepted) == 0 task = execute_task('foo_s02ep1') assert len(task.accepted) == 1 def test_season_pack_takes_priority(self, execute_task): task = execute_task('season_pack_priority') assert len(task.accepted) == 1 entry = task.find_entry(title='foo.s01.720p-flexget') assert entry.accepted def test_respect_begin(self, execute_task): task = execute_task('respect_begin') assert len(task.accepted) == 1 entry = task.find_entry(title='bar.s02.720p-flexget') assert entry.accepted def test_tracking_rules_old_eps(self, execute_task): task = execute_task('foo_s01') assert len(task.accepted) == 1 task = execute_task('foo_s02') assert len(task.accepted) == 1 task = execute_task('foo_s01ep1') assert not task.accepted def test_tracking_rules_old_season(self, execute_task): task = execute_task('foo_s02') assert len(task.accepted) == 1 task = execute_task('foo_s01') assert not task.accepted def test_tracking_rules_new_season(self, execute_task): task = execute_task('foo_s01') assert len(task.accepted) == 1 task = execute_task('foo_s03') assert not task.accepted def test_several_seasons(self, execute_task): task = execute_task('several_seasons') assert len(task.accepted) == 4 def test_multiple_formats(self, execute_task): task = execute_task('multiple_formats') assert len(task.accepted) == 2 def test_backfill(self, execute_task): task = execute_task('test_backfill_1') assert len(task.accepted) == 1 task = execute_task('test_backfill_2') assert len(task.accepted) == 1 task = execute_task('test_backfill_3') assert not task.accepted task = execute_task('test_backfill_4') assert not task.accepted def test_default_threshold(self, execute_task): task = execute_task('foo_s01ep1') assert len(task.accepted) == 1 task = execute_task('foo_s01') assert len(task.accepted) == 0 def test_specific_season_pack_threshold_positive(self, execute_task): task = execute_task('test_specific_season_pack_threshold_1') assert len(task.accepted) == 3 task = execute_task('test_specific_season_pack_threshold_2') assert len(task.accepted) == 1 def test_specific_season_pack_threshold_negative(self, execute_task): task = execute_task('test_specific_season_pack_threshold_3') assert len(task.accepted) == 4 task = execute_task('test_specific_season_pack_threshold_2') assert not task.accepted def test_loose_threshold(self, execute_task): task = execute_task('test_always_get_season_pack_1') assert len(task.accepted) == 4 task = execute_task('test_always_get_season_pack_2') assert len(task.accepted) == 1 def test_exclusive(self, execute_task): task = execute_task('test_only_get_season_packs') assert len(task.accepted) == 1 entry = task.find_entry(title='bla.s01.720p-flexget') assert entry.accepted def test_proper_season_pack(self, execute_task): """Series plugin: proper available immediately""" task = execute_task('test_proper_season_pack') assert task.find_entry('accepted', title='foo.s01.720p.proper-flexget') def test_proper_season_pack_2(self, execute_task): """Series plugin: proper available immediately""" task = execute_task('test_proper_season_pack_2') assert task.find_entry('accepted', title='foo.s01.720p-flexget') task = execute_task('test_proper_season_pack_3') assert task.find_entry('accepted', title='foo.s01.720p.proper-flexget') def test_all_series(self, execute_task): task = execute_task('test_all_series') assert task.find_entry('accepted', title='show.name.s01.720p.HDTV-Group') def test_advanced_config(self, execute_task): task = execute_task('test_with_dict_config_1') assert not task.find_entry('accepted', title='bro.s01e01.720p.HDTV-Flexget') assert task.find_entry('accepted', title='bro.s01.720p.HDTV-Flexget') execute_task('test_with_dict_config_2', options={'inject': [Entry(title='bro.s02e01.720p.HDTV-Flexget', url='')], 'immortal': True}) task = execute_task('test_with_dict_config_2') assert task.find_entry('accepted', title='bro.s02.720p.HDTV-Flexget') class TestSeriesDDAudio(object): _config = """ templates: global: parsing: series: internal tasks: min_quality: mock: - {title: 'MinQATest.S01E01.720p.XViD.DD5.1-FlexGet'} - {title: 'MinQATest.S01E01.720p.XViD.DDP5.1-FlexGet'} series: - MinQATest: quality: ">dd5.1" max_quality: mock: - {title: 'MaxQATest.S01E01.720p.XViD.DD5.1-FlexGet'} - {title: 'MaxQATest.S01E01.720p.XViD.DD+5.1-FlexGet'} series: - MaxQATest: quality: "<=dd5.1" test_channels: mock: - {title: 'Channels.S01E01.1080p.HDTV.DD+2.0-FlexGet'} - {title: 'Channels.S01E01.1080p.HDTV.DD+5.1-FlexGet'} - {title: 'Channels.S01E01.1080p.HDTV.DD+7.1-FlexGet'} series: - Channels: quality: dd+5.1 """ @pytest.fixture() def config(self): """Overrides outer config fixture since DD+ and arbitrary channels support does not work with guessit parser""" return self._config def test_min_quality(self, execute_task): """Series plugin: min_quality""" task = execute_task('min_quality') assert task.find_entry('accepted', title='MinQATest.S01E01.720p.XViD.DDP5.1-FlexGet'), \ 'MinQATest.S01E01.720p.XViD.DDP5.1-FlexGet should have been accepted' assert len(task.accepted) == 1, 'should have accepted only two' def test_max_quality(self, execute_task): """Series plugin: max_quality""" task = execute_task('max_quality') assert task.find_entry('accepted', title='MaxQATest.S01E01.720p.XViD.DD5.1-FlexGet'), \ 'MaxQATest.S01E01.720p.XViD.DD5.1-FlexGet should have been accepted' assert len(task.accepted) == 1, 'should have accepted only one' def test_channels(self, execute_task): """Series plugin: max_quality""" task = execute_task('test_channels') assert task.find_entry(title='Channels.S01E01.1080p.HDTV.DD+7.1-FlexGet'), \ 'Channels.S01E01.1080p.HDTV.DD+7.1-FlexGet should have been accepted' assert len(task.accepted) == 1, 'should have accepted only one'
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#!/usr/bin/env python """ Copyright 2017 ARM Limited 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. """ # pylint: disable=unused-argument import mock def create(*args, **kwargs): """ Create a Mock object that imitates a valid Cloud module. :param args: Not used :param kwargs: Not used :return: mock.MagicMock """ attrs = {"client.get_suite.return_value": True, "get_campaign_id.side_effect": [True, KeyError], "get_campaigns.return_value": True, "update_testcase.return_value": True, "upload_results.side_effect": [True, False]} mock_module = mock.MagicMock() mock_module.configure_mock(**attrs) return mock_module
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# Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You 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 argparse import json import logging import uuid from random import sample import cassandra.concurrent from cassandra.cluster import Cluster from cassandra.policies import RoundRobinPolicy, TokenAwarePolicy from solrcloudpy import SolrConnection, SearchOptions from six.moves import input solr_connection = None solr_collection = None SOLR_UNIQUE_KEY = None cassandra_cluster = None cassandra_session = None cassandra_table = None logging.basicConfig() logging.getLogger().setLevel(logging.INFO) logging.getLogger().handlers[0].setFormatter( logging.Formatter(fmt="%(asctime)s %(levelname)s:%(name)s: %(message)s", datefmt="%Y-%m-%dT%H:%M:%S")) def init(args): global solr_connection solr_connection = SolrConnection(args.solr) global solr_collection solr_collection = solr_connection[args.collection] global SOLR_UNIQUE_KEY SOLR_UNIQUE_KEY = args.solrIdField dc_policy = RoundRobinPolicy() token_policy = TokenAwarePolicy(dc_policy) global cassandra_cluster cassandra_cluster = Cluster(contact_points=args.cassandra, port=args.cassandraPort, protocol_version=int(args.cassandraProtocolVersion), load_balancing_policy=token_policy) global cassandra_session cassandra_session = cassandra_cluster.connect(keyspace=args.cassandraKeyspace) global cassandra_table cassandra_table = args.cassandraTable def delete_by_query(args): if args.query: se = SearchOptions() se.commonparams.q(args.query) \ .fl(SOLR_UNIQUE_KEY) \ .fl('id') for fq in args.filterquery if args.filterquery is not None else []: se.commonparams.fq(fq) query = se elif args.jsonparams: se = SearchOptions(**json.loads(args.jsonparams)) se.commonparams.fl(SOLR_UNIQUE_KEY) \ .fl('id') query = se else: raise RuntimeError("either query or jsonparams is required") if check_query(query): logging.info("Collecting tiles ....") solr_docs = do_solr_query(query) if confirm_delete(len(solr_docs)): deleted_ids = do_delete(solr_docs, query) logging.info("Deleted tile IDs %s" % json.dumps([str(doc_id) for doc_id in deleted_ids], indent=2)) else: logging.info("Exiting") return else: logging.info("Exiting") return def confirm_delete(num_found): do_continue = input( "This action will delete %s record(s) from SOLR and Cassandra. Are you sure you want to Continue? y/n: " % num_found) while do_continue not in ['y', 'n']: do_continue = input( "This action will delete %s record(s) from SOLR and Cassandra. Are you sure you want to Continue? y/n: " % num_found) return do_continue == 'y' def check_query(query): solr_response = solr_collection.search(query) num_found = solr_response.result.response.numFound if num_found == 0: logging.info("Query returned 0 results") return False do_continue = input("Query found %s matching documents. Continue? [y]/n/(s)ample: " % num_found) while do_continue not in ['y', 'n', 's', '']: do_continue = input("Query found %s matching documents. Continue? [y]/n/(s)ample: " % num_found) if do_continue == 'y' or do_continue == '': return True elif do_continue == 'n': return False else: se = SearchOptions() se.commonparams.q('%s:%s' % (SOLR_UNIQUE_KEY, sample(solr_response.result.response.docs, 1)[0][SOLR_UNIQUE_KEY])) logging.info(json.dumps(solr_collection.search(se).result.response.docs[0], indent=2)) return check_query(query) def do_solr_query(query): doc_ids = [] next_cursor_mark = "*" query.commonparams.sort('%s asc' % SOLR_UNIQUE_KEY) while True: query.commonparams.remove_param('cursorMark') query.commonparams.add_params(cursorMark=next_cursor_mark) solr_response = solr_collection.search(query) try: result_next_cursor_mark = solr_response.result.nextCursorMark except AttributeError: # No Results return [] if result_next_cursor_mark == next_cursor_mark: break else: next_cursor_mark = solr_response.result.nextCursorMark doc_ids.extend([uuid.UUID(doc['id']) for doc in solr_response.result.response.docs]) return doc_ids def do_delete(doc_ids, query): logging.info("Executing Cassandra delete...") delete_from_cassandra(doc_ids) logging.info("Executing Solr delete...") delete_from_solr(query) return doc_ids def delete_from_cassandra(doc_ids): statement = cassandra_session.prepare("DELETE FROM %s WHERE tile_id=?" % cassandra_table) results = cassandra.concurrent.execute_concurrent_with_args(cassandra_session, statement, [(doc_id,) for doc_id in doc_ids]) for (success, result) in results: if not success: logging.warning("Could not delete tile %s" % result) def delete_from_solr(query): solr_collection.delete(query, commit=False) solr_collection.commit() def parse_args(): parser = argparse.ArgumentParser(description='Delete data from NEXUS using a Solr Query', formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument('--solr', help='The url of the SOLR server.', required=True, metavar='127.0.0.1:8983') parser.add_argument('--collection', help='The name of the SOLR collection.', required=True, metavar='nexustiles') parser.add_argument('--solrIdField', help='The name of the unique ID field for this collection.', required=False, default='solr_id_s', metavar='solr_id_s') parser.add_argument('--cassandra', help='The hostname(s) or IP(s) of the Cassandra server(s).', required=True, nargs='+', metavar=('127.0.0.100', '127.0.0.101')) parser.add_argument('-k', '--cassandraKeyspace', help='The Cassandra keyspace.', required=True, metavar='nexustiles') group = parser.add_mutually_exclusive_group(required=True) group.add_argument('-q', '--query', help='The ''q'' parameter passed to SOLR Search', metavar='*:*') group.add_argument('--jsonparams', help='Full query prameters formatted as JSON') parser.add_argument('-fq', '--filterquery', help='The ''fq'' parameter passed to SOLR Search. Only used if --jsonparams is not provided', required=False, nargs='+') parser.add_argument('-t', '--cassandraTable', help='The name of the cassandra table.', required=False, default='sea_surface_temp') parser.add_argument('-p', '--cassandraPort', help='The port used to connect to Cassandra.', required=False, default='9042') parser.add_argument('-pv', '--cassandraProtocolVersion', help='The version of the Cassandra protocol the driver should use.', required=False, choices=['1', '2', '3', '4', '5'], default='3') return parser.parse_args() if __name__ == "__main__": the_args = parse_args() init(the_args) delete_by_query(the_args)
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from decimal import * # Purpose: read in SSDEEP output and print findings. # Author: Tanner G. def main(): file = open("ssdeep_comparison", "r") # read past first line of output file.readline() filea_data = file.readline() fileb_data = file.readline() file.close() totalCount = 0 similarities = 0 index = 0 max_len = len(filea_data) while index < max_len: totalCount +=1 if filea_data[index] == "," or fileb_data[index] == ",": index = max_len totalCount -=1 break elif filea_data[index] == fileb_data[index]: similarities +=1 index +=1 else: index+=1 continue print("------------------") print("Stats from ssdeep:") print("------------------") print("Total Count: " + str(totalCount)) print("Similarities: " + str(similarities)) ratio = (Decimal(similarities)/Decimal(totalCount) * 100) print ("Hash similarity detected: " + str(ratio)[:5] + "%") outputFile = open("ssdeep_stats", "w") outputFile.write("count:"+str(totalCount)+",ratio:"+str(ratio)[:5]+"\n") outputFile.close() if __name__ == "__main__": main()
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#!/usr/bin/env python import cPickle from functools import wraps def redis_lru(capacity=5000, slice=slice(None)): def decorator(func): cache_keys = "lru:keys:%s" % (func.__name__,) cache_vals = "lru:vals:%s" % (func.__name__,) cache_hits = "lru:hits:%s" % (func.__name__,) cache_miss = "lru:miss:%s" % (func.__name__,) lvars = [None] # closure mutable def add(key, value): eject() conn = lvars[0] conn.incr(cache_miss) conn.hset(cache_vals, key, cPickle.dumps(value)) conn.zadd(cache_keys, 0, key) return value def get(key): conn = lvars[0] value = conn.hget(cache_vals, key) if value: conn.incr(cache_hits) conn.zincrby(cache_keys, key, 1.0) value = cPickle.loads(value) return value def eject(): conn = lvars[0] count = min((capacity / 10) or 1, 1000) if conn.zcard(cache_keys) >= capacity: eject = conn.zrange(cache_keys, 0, count) conn.zremrangebyrank(cache_keys, 0, count) conn.hdel(cache_vals, *eject) @wraps(func) def wrapper(*args, **kwargs): conn = lvars[0] if conn: items = args + tuple(sorted(kwargs.items())) key = cPickle.dumps(items[slice]) return get(key) or add(key, func(*args, **kwargs)) else: return func(*args, **kwargs) def info(): conn = lvars[0] size = int(conn.zcard(cache_keys) or 0) hits, misses = int(conn.get(cache_hits) or 0), int(conn.get(cache_miss) or 0) return hits, misses, capacity, size def clear(): conn = lvars[0] conn.delete(cache_keys, cache_vals) conn.delete(cache_hits, cache_miss) def init(conn): lvars[0] = conn wrapper.init = init wrapper.info = info wrapper.clear = clear return wrapper return decorator
[ [ [ 29, 36 ], [ 480, 487 ], [ 718, 725 ], [ 1153, 1160 ] ], [ [ 59, 64 ], [ 1019, 1024 ] ], [ [ 70, 79 ] ] ]
swizzle_table = [ [ b"\x00", b"\x01", b"\x40", b"\x03", b"\x10", b"\x21", b"\x50", b"\x23", b"\x04", b"\x09", b"\x44", b"\x0b", b"\x14", b"\x29", b"\x54", b"\x2b", ], [ b"\x08", b"\x11", b"\x48", b"\x13", b"\x18", b"\x31", b"\x58", b"\x33", b"\x0c", b"\x19", b"\x4c", b"\x1b", b"\x1c", b"\x39", b"\x5c", b"\x3b", ], [ b"\x80", b"\x05", b"\xc0", b"\x07", b"\x90", b"\x25", b"\xd0", b"\x27", b"\x84", b"\x0d", b"\xc4", b"\x0f", b"\x94", b"\x2d", b"\xd4", b"\x2f", ], [ b"\x88", b"\x15", b"\xc8", b"\x17", b"\x98", b"\x35", b"\xd8", b"\x37", b"\x8c", b"\x1d", b"\xcc", b"\x1f", b"\x9c", b"\x3d", b"\xdc", b"\x3f", ], [ b"\x02", b"\x41", b"\x42", b"\x43", b"\x12", b"\x61", b"\x52", b"\x63", b"\x06", b"\x49", b"\x46", b"\x4b", b"\x16", b"\x69", b"\x56", b"\x6b", ], [ b"\x0a", b"\x51", b"\x4a", b"\x53", b"\x1a", b"\x71", b"\x5a", b"\x73", b"\x0e", b"\x59", b"\x4e", b"\x5b", b"\x1e", b"\x79", b"\x5e", b"\x7b", ], [ b"\x82", b"\x45", b"\xc2", b"\x47", b"\x92", b"\x65", b"\xd2", b"\x67", b"\x86", b"\x4d", b"\xc6", b"\x4f", b"\x96", b"\x6d", b"\xd6", b"\x6f", ], [ b"\x8a", b"\x55", b"\xca", b"\x57", b"\x9a", b"\x75", b"\xda", b"\x77", b"\x8e", b"\x5d", b"\xce", b"\x5f", b"\x9e", b"\x7d", b"\xde", b"\x7f", ], [ b"\x20", b"\x81", b"\x60", b"\x83", b"\x30", b"\xa1", b"\x70", b"\xa3", b"\x24", b"\x89", b"\x64", b"\x8b", b"\x34", b"\xa9", b"\x74", b"\xab", ], [ b"\x28", b"\x91", b"\x68", b"\x93", b"\x38", b"\xb1", b"\x78", b"\xb3", b"\x2c", b"\x99", b"\x6c", b"\x9b", b"\x3c", b"\xb9", b"\x7c", b"\xbb", ], [ b"\xa0", b"\x85", b"\xe0", b"\x87", b"\xb0", b"\xa5", b"\xf0", b"\xa7", b"\xa4", b"\x8d", b"\xe4", b"\x8f", b"\xb4", b"\xad", b"\xf4", b"\xaf", ], [ b"\xa8", b"\x95", b"\xe8", b"\x97", b"\xb8", b"\xb5", b"\xf8", b"\xb7", b"\xac", b"\x9d", b"\xec", b"\x9f", b"\xbc", b"\xbd", b"\xfc", b"\xbf", ], [ b"\x22", b"\xc1", b"\x62", b"\xc3", b"\x32", b"\xe1", b"\x72", b"\xe3", b"\x26", b"\xc9", b"\x66", b"\xcb", b"\x36", b"\xe9", b"\x76", b"\xeb", ], [ b"\x2a", b"\xd1", b"\x6a", b"\xd3", b"\x3a", b"\xf1", b"\x7a", b"\xf3", b"\x2e", b"\xd9", b"\x6e", b"\xdb", b"\x3e", b"\xf9", b"\x7e", b"\xfb", ], [ b"\xa2", b"\xc5", b"\xe2", b"\xc7", b"\xb2", b"\xe5", b"\xf2", b"\xe7", b"\xa6", b"\xcd", b"\xe6", b"\xcf", b"\xb6", b"\xed", b"\xf6", b"\xef", ], [ b"\xaa", b"\xd5", b"\xea", b"\xd7", b"\xba", b"\xf5", b"\xfa", b"\xf7", b"\xae", b"\xdd", b"\xee", b"\xdf", b"\xbe", b"\xfd", b"\xfe", b"\xff", ], ] MOSHI_SET_OFFSET = 0 MOSHI_TERMINATION = 2 MOSHI_VECTOR_SPEED = 5 MOSHI_RASTER_SPEED = 4 MOSHI_CUT_ABS = 15 MOSHI_CUT_HORIZ = 14 MOSHI_CUT_VERT = 11 MOSHI_MOVE_ABS = 7 MOSHI_MOVE_HORIZ = 6 MOSHI_MOVE_VERT = 3 MOSHI_FREEMOTOR = 1 MOSHI_ESTOP = 1 MOSHI_EPILOGUE = 2 MOSHI_PROLOGUE = 6 # 6 also seen at laser startup. MOSHI_LASER = 7 MOSHI_READ = 14 # 14 is also sometimes done as a keepalive each 3.4 seconds. class MoshiBlob: """ MoshiBlobs are datablobs of Moshi types. These are series of commands which should be executed as a program within the Moshicontroller. """ def __init__(self, channel=None): self.data = bytearray() # Queued additional commands programs. self.channel = channel self.last_x = 0 self.last_y = 0 self.offset_x = 0 self.offset_y = 0 self._stage = 0 def __len__(self): return len(self.data) def pipe_int8(self, value): """ Write an 8 bit into to the current program. """ v = bytes( bytearray( [ value & 0xFF, ] ) ) self.write(v) def pipe_int16le(self, value): """ Write a 16 bit little-endian value to the current program. """ v = bytes( bytearray( [ (value >> 0) & 0xFF, (value >> 8) & 0xFF, ] ) ) self.write(v) def write(self, bytes_to_write): """ Writes data to the queue, this will be moved into the buffer by the thread in a threadsafe manner. :param bytes_to_write: data to write to the queue. :return: """ self.data += bytes_to_write return self def vector_speed(self, speed_mms, normal_speed_mms): """ Vector Speed Byte. (0x00 position), followed by 2 int8 values. Jog and Normal Speed. These values are limited to integer values which are 1 to 256. :return: """ assert self._stage == 0 self._stage = 1 if self.channel: self.channel( "Vector Cut Speed: %d mm/s Normal Speed: %d mm/s" % (int(speed_mms), int(normal_speed_mms)) ) self.write(swizzle_table[MOSHI_VECTOR_SPEED][0]) if speed_mms > 256: speed_mms = 256 if speed_mms < 1: speed_mms = 1 self.pipe_int8(speed_mms - 1) self.pipe_int8(normal_speed_mms - 1) def raster_speed(self, speed_mms): """ Write speed for raster programs. """ assert self._stage == 0 self._stage = 1 if self.channel: self.channel("Raster Header Speed: %d cm/s" % int(speed_mms)) self.write(swizzle_table[MOSHI_RASTER_SPEED][0]) speed_cms = int(round(speed_mms / 10)) if speed_cms == 0: speed_cms = 1 self.pipe_int8(speed_cms - 1) def set_offset(self, z, x, y): """ 2nd Command For Jump. (0x03 position), followed by 3 int16le (2) :return: """ assert self._stage == 1 self._stage = 2 self.offset_x = x self.offset_y = y if self.channel: self.channel("Set Location z: %d, x: %d, y: %d" % (int(z), int(x), int(y))) self.write(swizzle_table[MOSHI_SET_OFFSET][0]) self.pipe_int16le(z) # Unknown, always zero. self.pipe_int16le(x) # x self.pipe_int16le(y) # y def termination(self): """ Terminal Commands for Jump/Program. (last 7 bytes). (4) :return: """ # assert self._stage == 3 self._stage = 4 if self.channel: self.channel("Termination.") for i in range(7): self.write(swizzle_table[MOSHI_TERMINATION][0]) def cut_abs(self, x, y): """ Write an absolute position cut value. Laser will cut to this position from the current stored head position. Head position is stored on the Moshiboard """ assert 2 <= self._stage <= 3 self._stage = 3 if x < 0: x = 0 if y < 0: y = 0 self.last_x = x self.last_y = y x -= self.offset_x y -= self.offset_y if self.channel: self.channel("Cut x: %d y: %d" % (int(x), int(y))) self.write(swizzle_table[MOSHI_CUT_ABS][1]) self.pipe_int16le(int(x)) self.pipe_int16le(int(y)) def move_abs(self, x, y): """ Write an absolute position move value. Laser will move without cutting to this position from the current stored head position. Head position is stored on the Moshiboard """ assert 2 <= self._stage <= 3 self._stage = 3 if x < 0: x = 0 if y < 0: y = 0 self.last_x = x self.last_y = y x -= self.offset_x y -= self.offset_y if self.channel: self.channel("Move x: %d y: %d" % (int(x), int(y))) self.write(swizzle_table[MOSHI_MOVE_ABS][0]) self.pipe_int16le(int(x)) self.pipe_int16le(int(y)) def move_vertical_abs(self, y): """ Write an absolute position vertical move. Laser will move the y position without cutting to the new position from the head position stored in the Moshiboard. """ assert 2 <= self._stage <= 3 self._stage = 3 self.last_y = y y -= self.offset_y if self.channel: self.channel("Move Vertical y: %d" % int(y)) self.write(swizzle_table[MOSHI_MOVE_VERT][0]) self.pipe_int16le(int(y)) def move_horizontal_abs(self, x): """ Write an absolute position horizontal move. Laser will move the x position without cutting to the new position from the head position stored in the Moshiboard. """ assert 2 <= self._stage <= 3 self._stage = 3 self.last_x = x x -= self.offset_x if self.channel: self.channel("Move Horizontal x: %d" % int(x)) self.write(swizzle_table[MOSHI_MOVE_HORIZ][0]) self.pipe_int16le(int(x)) def cut_horizontal_abs(self, x): """ Write an absolute position horizontal cut. Laser will cut to the x position with laser firing to the new position from the head position stored in the Moshiboard. """ assert 2 <= self._stage <= 3 self._stage = 3 self.last_x = x x -= self.offset_x if self.channel: self.channel("Cut Horizontal x: %d" % int(x)) self.write(swizzle_table[MOSHI_CUT_HORIZ][0]) self.pipe_int16le(int(x)) def cut_vertical_abs(self, y): """ Write an absolute position vertical cut. Laser will cut to the y position with laser firing to the new position from the head position stored in the Moshiboard """ assert 2 <= self._stage <= 3 self._stage = 3 self.last_y = y y -= self.offset_y if self.channel: self.channel("Cut Vertical y: %d" % int(y)) self.write(swizzle_table[MOSHI_CUT_VERT][0]) self.pipe_int16le(int(y)) @staticmethod def _swizzle(b, p7, p6, p5, p4, p3, p2, p1, p0): return ( ((b >> 0) & 1) << p0 | ((b >> 1) & 1) << p1 | ((b >> 2) & 1) << p2 | ((b >> 3) & 1) << p3 | ((b >> 4) & 1) << p4 | ((b >> 5) & 1) << p5 | ((b >> 6) & 1) << p6 | ((b >> 7) & 1) << p7 ) @staticmethod def convert(q): """ Translated Moshiboard swizzle into correct Moshi command code. Moshiboards command codes have 16 values with 16 different swizzled values. There are two different swizzles depending on the parity of the particular code. These codes are used randomly by Moshi's native software. The board itself reads these all the same. """ if q & 1: return MoshiBlob._swizzle(q, 7, 6, 2, 4, 3, 5, 1, 0) else: return MoshiBlob._swizzle(q, 5, 1, 7, 2, 4, 3, 6, 0) @staticmethod def reconvert(q): """ Counter-translate a particular command code back into correct values. """ for m in range(5): q = MoshiBlob.convert(q) return q
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from core.models import User from django.http import HttpResponse, JsonResponse from django.shortcuts import get_object_or_404 from drf_yasg import openapi from drf_yasg.utils import swagger_auto_schema from rest_framework import permissions, status from rest_framework.decorators import api_view, permission_classes from rest_framework.parsers import JSONParser from requests.exceptions import ConnectionError from projects.models import ( Page, Project, ProjectMemberRole, ProjectAuditParameters, AvailableAuditParameters, Script, ) from projects.serializers import ( PageSerializer, ProjectSerializer, ProjectMemberRoleSerializer, ProjectAuditParametersSerializer, AvailableAuditParameterSerializer, ScriptSerializer, ) from projects.permissions import ( check_if_member_of_project, check_if_admin_of_project, is_admin_of_project, ) from audits.tasks import get_wpt_audit_configurations def get_user_projects(user_id): return Project.objects.filter(members__id=user_id, is_active=True) @swagger_auto_schema( methods=["get"], responses={ 200: openapi.Response( "Returns a list of all the user’s projects", ProjectSerializer(many=True) ) }, tags=["Projects"], ) @swagger_auto_schema( methods=["post"], request_body=ProjectSerializer, responses={201: openapi.Response("Returns the created project", ProjectSerializer)}, tags=["Projects"], ) @api_view(["GET", "POST"]) @permission_classes([permissions.IsAuthenticated]) def project_list(request): if request.method == "GET": projects = get_user_projects(request.user.id) serializer = ProjectSerializer( projects, many=True, context={"user_id": request.user.id} ) return JsonResponse(serializer.data, safe=False) elif request.method == "POST": data = JSONParser().parse(request) serializer = ProjectSerializer(data=data, context={"user_id": request.user.id}) if serializer.is_valid(): project = Project.objects.create(**serializer.validated_data) project.save() return JsonResponse( {"uuid": project.uuid, **serializer.data}, status=status.HTTP_201_CREATED, ) return JsonResponse(serializer.errors, status=status.HTTP_400_BAD_REQUEST) @swagger_auto_schema( methods=["get"], responses={200: openapi.Response("", ProjectSerializer)}, tags=["Projects"], ) @api_view(["GET"]) @permission_classes([permissions.IsAuthenticated]) def first_project(request): """Returns the first project of the user. This is used to speed up the loading of the first project page""" projects = get_user_projects(request.user.id) serializer = ProjectSerializer( projects.first(), context={"user_id": request.user.id} ) return JsonResponse(serializer.data) @swagger_auto_schema( methods=["get"], responses={ 200: openapi.Response("Returns details of a project.", ProjectSerializer) }, tags=["Projects"], ) @swagger_auto_schema( methods=["put"], request_body=ProjectSerializer, responses={ 200: openapi.Response( "Updates a project. Allows for partial updates.", ProjectSerializer ) }, tags=["Projects"], ) @swagger_auto_schema( methods=["delete"], responses={204: "No content"}, tags=["Projects"] ) @api_view(["GET", "PUT", "DELETE"]) @permission_classes([permissions.IsAuthenticated]) def project_detail(request, project_uuid): project = get_object_or_404(Project, pk=project_uuid) check_if_member_of_project(request.user.id, project.uuid) if request.method == "GET": if is_admin_of_project(request.user.id, project.uuid): serializer = ProjectSerializer( project, context={"user_id": request.user.id} ) return JsonResponse(serializer.data) serializer = ProjectSerializer( project, fields=( "uuid", "name", "project_members", "pages", "scripts", "audit_parameters_list", "screenshot_url", "latest_audit_at", "has_siblings", ), context={"user_id": request.user.id}, ) return JsonResponse(serializer.data) elif request.method == "PUT": check_if_admin_of_project(request.user.id, project.uuid) data = JSONParser().parse(request) serializer = ProjectSerializer( project, data=data, partial=True, context={"user_id": request.user.id} ) if serializer.is_valid(): serializer.save() return JsonResponse(serializer.data) return JsonResponse(serializer.errors, status=status.HTTP_400_BAD_REQUEST) elif request.method == "DELETE": check_if_admin_of_project(request.user.id, project.uuid) project.delete() return JsonResponse({}, status=status.HTTP_204_NO_CONTENT) @swagger_auto_schema( methods=["get"], responses={ 200: openapi.Response( "Returns a list of all pages in the project", PageSerializer(many=True) ) }, tags=["Pages"], ) @swagger_auto_schema( methods=["post"], request_body=PageSerializer, responses={201: openapi.Response("Returns the created page", PageSerializer)}, tags=["Pages"], ) @api_view(["GET", "POST"]) @permission_classes([permissions.IsAuthenticated]) def project_page_list(request, project_uuid): project = Project.objects.get(uuid=project_uuid) check_if_member_of_project(request.user.id, project.uuid) if request.method == "GET": pages = project.pages.all() serializer = PageSerializer(pages, many=True) return JsonResponse(serializer.data, safe=False) elif request.method == "POST": check_if_admin_of_project(request.user.id, project.uuid) data = JSONParser().parse(request) serializer = PageSerializer(data=data) if serializer.is_valid(): page = Page.objects.create(project=project, **serializer.validated_data) page.save() return JsonResponse( {"uuid": page.uuid, **serializer.data}, status=status.HTTP_201_CREATED ) return JsonResponse(serializer.errors, status=status.HTTP_400_BAD_REQUEST) @swagger_auto_schema( methods=["get"], responses={200: openapi.Response("Returns details of a page.", PageSerializer)}, tags=["Pages"], ) @swagger_auto_schema( methods=["put"], request_body=PageSerializer, responses={ 200: openapi.Response( "Updates a page. Allows for partial updates.", PageSerializer ) }, tags=["Pages"], ) @swagger_auto_schema(methods=["delete"], responses={204: "No content"}, tags=["Pages"]) @api_view(["GET", "PUT", "DELETE"]) @permission_classes([permissions.IsAuthenticated]) def project_page_detail(request, project_uuid, page_uuid): project = get_object_or_404(Project, pk=project_uuid) page = get_object_or_404(Page, pk=page_uuid) check_if_member_of_project(request.user.id, project.uuid) if page.project != project: return JsonResponse({}, status=status.HTTP_400_BAD_REQUEST) if request.method == "GET": serializer = PageSerializer(page) return JsonResponse(serializer.data) elif request.method == "PUT": check_if_admin_of_project(request.user.id, project.uuid) data = JSONParser().parse(request) serializer = PageSerializer(page, data=data) if serializer.is_valid(): serializer.save() return JsonResponse(serializer.data) return JsonResponse(serializer.errors, status=status.HTTP_400_BAD_REQUEST) elif request.method == "DELETE": check_if_admin_of_project(request.user.id, project.uuid) page.delete() return JsonResponse({}, status=status.HTTP_204_NO_CONTENT) @swagger_auto_schema( methods=["post"], request_body=ProjectAuditParametersSerializer, responses={ 201: openapi.Response( "Returns the created project audit parameter", ProjectAuditParametersSerializer, ) }, tags=["Project Audit Parameters"], ) @api_view(["POST"]) @permission_classes([permissions.IsAuthenticated]) def project_audit_parameter_list(request, project_uuid): project = Project.objects.get(uuid=project_uuid) check_if_admin_of_project(request.user.id, project.uuid) data = JSONParser().parse(request) serializer = ProjectAuditParametersSerializer(data=data) if serializer.is_valid(): audit_parameter = ProjectAuditParameters.objects.create( project=project, **serializer.validated_data ) audit_parameter.save() serializer = ProjectAuditParametersSerializer(audit_parameter) return JsonResponse(serializer.data, status=status.HTTP_201_CREATED) return JsonResponse(serializer.errors, status=status.HTTP_400_BAD_REQUEST) @swagger_auto_schema( methods=["get"], responses={ 200: openapi.Response( "Returns the details of a project audit parameter.", ProjectAuditParametersSerializer, ) }, tags=["Project Audit Parameters"], ) @swagger_auto_schema( methods=["put"], request_body=ProjectAuditParametersSerializer, responses={ 200: openapi.Response( "Updates a project audit parameter. Allows for partial updates.", ProjectAuditParametersSerializer, ) }, tags=["Project Audit Parameters"], ) @swagger_auto_schema( methods=["delete"], responses={204: "No content"}, tags=["Project Audit Parameters"] ) @api_view(["GET", "PUT", "DELETE"]) @permission_classes([permissions.IsAuthenticated]) def project_audit_parameters_detail(request, project_uuid, audit_parameters_uuid): project = get_object_or_404(Project, pk=project_uuid) audit_parameters = get_object_or_404( ProjectAuditParameters, pk=audit_parameters_uuid ) check_if_member_of_project(request.user.id, project.uuid) if audit_parameters.project != project: return JsonResponse({}, status=status.HTTP_400_BAD_REQUEST) if request.method == "GET": serializer = ProjectAuditParametersSerializer(audit_parameters) return JsonResponse(serializer.data) elif request.method == "PUT": check_if_admin_of_project(request.user.id, project.uuid) data = JSONParser().parse(request) serializer = ProjectAuditParametersSerializer(audit_parameters, data=data) if serializer.is_valid(): serializer.save() return JsonResponse(serializer.data) return JsonResponse(serializer.errors, status=status.HTTP_400_BAD_REQUEST) elif request.method == "DELETE": check_if_admin_of_project(request.user.id, project.uuid) audit_parameters.delete() return JsonResponse({}, status=status.HTTP_204_NO_CONTENT) @swagger_auto_schema( methods=["put"], request_body=ProjectMemberRoleSerializer, responses={ 200: openapi.Response( "Updates a project member. Allows for partial updates.", ProjectMemberRoleSerializer, ) }, tags=["Project Members"], ) @swagger_auto_schema( methods=["delete"], responses={204: "No content"}, tags=["Project Members"] ) @api_view(["PUT", "DELETE"]) @permission_classes([permissions.IsAuthenticated]) def project_member_detail(request, project_uuid, user_id): project = get_object_or_404(Project, pk=project_uuid) check_if_admin_of_project(request.user.id, project.uuid) project_member = ProjectMemberRole.objects.filter( project_id=project_uuid, user_id=user_id ) if not project_member: return HttpResponse( "No project member was found", status=status.HTTP_404_NOT_FOUND ) if request.method == "PUT": data = JSONParser().parse(request) if "is_admin" in data and type(data["is_admin"]) is bool: project_member.update(is_admin=data["is_admin"]) serializer = ProjectMemberRoleSerializer(project_member.first()) return JsonResponse(serializer.data) return HttpResponse( "Please provide a valid 'is_admin' value.", status=status.HTTP_400_BAD_REQUEST, ) elif request.method == "DELETE": project_member.delete() return JsonResponse({}, status=status.HTTP_204_NO_CONTENT) @swagger_auto_schema( methods=["post"], request_body=openapi.Schema( type="object", properties={"user_id": openapi.Schema(type="string")} ), responses={ 201: openapi.Response( "Returns the updated project with the new member.", ProjectSerializer ) }, tags=["Project Members"], ) @api_view(["POST"]) @permission_classes([permissions.IsAuthenticated]) def project_members(request, project_uuid): project = get_object_or_404(Project, pk=project_uuid) check_if_admin_of_project(request.user.id, project.uuid) data = JSONParser().parse(request) if "user_id" in data: if not ProjectMemberRole.objects.filter( project_id=project_uuid, user_id=data["user_id"] ): user = User.objects.filter(id=data["user_id"]) if not user: return HttpResponse( "No user found with this id", status=status.HTTP_404_NOT_FOUND ) project = Project.objects.filter(uuid=project_uuid).first() project.members.add(user.first(), through_defaults={"is_admin": False}) serializer = ProjectSerializer(project) return JsonResponse(serializer.data) return HttpResponse( "The user is already a member of the project", status=status.HTTP_400_BAD_REQUEST, ) return HttpResponse( "You must provide a user_id", status=status.HTTP_400_BAD_REQUEST ) @swagger_auto_schema( methods=["post"], request_body=openapi.Schema( type="object", properties={"wpt_instance_url": openapi.Schema(type="string")} ), responses={ 201: openapi.Response( "Returns discovered available audit parameters for the WPT instance URL passed in parameter", AvailableAuditParameterSerializer, ) }, tags=["Project Audit Parameters"], ) @api_view(["POST"]) def discover_available_audit_parameters(request): data = JSONParser().parse(request) if "wpt_instance_url" in data: try: get_wpt_audit_configurations(data["wpt_instance_url"]) except ConnectionError: return JsonResponse( { "error": "UNREACHABLE", "details": "The WPT instance is not reachable, please check the URL", }, status=status.HTTP_400_BAD_REQUEST, ) available_audit_parameters = AvailableAuditParameters.objects.filter( is_active=True ) serializer = AvailableAuditParameterSerializer( available_audit_parameters, many=True ) return JsonResponse(serializer.data, safe=False) return JsonResponse( { "error": "MISSING_PARAMETER", "details": "You must provide a wpt_instance_url in the request body", }, status=status.HTTP_400_BAD_REQUEST, ) @swagger_auto_schema( methods=["get"], responses={ 200: openapi.Response( "Returns all WebPageTest available audit parameters", AvailableAuditParameterSerializer, ) }, tags=["Project Audit Parameters"], ) @api_view(["GET"]) @permission_classes([permissions.IsAuthenticated]) def available_audit_parameters(request): available_audit_parameters = AvailableAuditParameters.objects.filter(is_active=True) serializer = AvailableAuditParameterSerializer( available_audit_parameters, many=True ) return JsonResponse(serializer.data, safe=False) @swagger_auto_schema( methods=["post"], request_body=ScriptSerializer, responses={201: openapi.Response("Returns the created script", ScriptSerializer)}, tags=["Scripts"], ) @api_view(["POST"]) @permission_classes([permissions.IsAuthenticated]) def project_scripts(request, project_uuid): project = Project.objects.get(uuid=project_uuid) check_if_admin_of_project(request.user.id, project.uuid) data = JSONParser().parse(request) serializer = ScriptSerializer(data=data) if serializer.is_valid(): script = Script.objects.create(project=project, **serializer.validated_data) script.save() return JsonResponse( {"uuid": script.uuid, **serializer.data}, status=status.HTTP_201_CREATED ) return JsonResponse(serializer.errors, status=status.HTTP_400_BAD_REQUEST) @swagger_auto_schema( methods=["put"], request_body=ScriptSerializer, responses={ 200: openapi.Response( "Updates a script. Allows for partial updates.", ScriptSerializer ) }, tags=["Scripts"], ) @swagger_auto_schema( methods=["delete"], responses={204: "No content"}, tags=["Scripts"] ) @api_view(["PUT", "DELETE"]) @permission_classes([permissions.IsAuthenticated]) def project_script_detail(request, project_uuid, script_uuid): project = get_object_or_404(Project, pk=project_uuid) script = get_object_or_404(Script, pk=script_uuid) check_if_member_of_project(request.user.id, project.uuid) if script.project != project: return JsonResponse({}, status=status.HTTP_400_BAD_REQUEST) elif request.method == "PUT": check_if_admin_of_project(request.user.id, project.uuid) data = JSONParser().parse(request) serializer = ScriptSerializer(script, data=data) if serializer.is_valid(): serializer.save() return JsonResponse(serializer.data) return JsonResponse(serializer.errors, status=status.HTTP_400_BAD_REQUEST) elif request.method == "DELETE": check_if_admin_of_project(request.user.id, project.uuid) script.delete() return JsonResponse({}, status=status.HTTP_204_NO_CONTENT)
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"""Provides the Objector class.""" from json import loads from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union from .exceptions import ClientException, RedditAPIException from .models.reddit.base import RedditBase from .util import snake_case_keys if TYPE_CHECKING: # pragma: no cover from ... import praw class Objector: """The objector builds :class:`.RedditBase` objects.""" @classmethod def parse_error( cls, data: Union[List[Any], Dict[str, Dict[str, str]]] ) -> Optional[RedditAPIException]: """Convert JSON response into an error object. :param data: The dict to be converted. :returns: An instance of :class:`~.RedditAPIException`, or ``None`` if ``data`` doesn't fit this model. """ if isinstance(data, list): # Fetching a Submission returns a list (of two items). Although it's handled # manually in `Submission._fetch()`, assume it's a possibility here. return None errors = data.get("json", {}).get("errors") if errors is None: return None if len(errors) < 1: # See `Collection._fetch()`. raise ClientException("successful error response", data) return RedditAPIException(errors) @classmethod def check_error(cls, data: Union[List[Any], Dict[str, Dict[str, str]]]): """Raise an error if the argument resolves to an error object.""" error = cls.parse_error(data) if error: raise error def __init__(self, reddit: "praw.Reddit", parsers: Optional[Dict[str, Any]] = None): """Initialize an Objector instance. :param reddit: An instance of :class:`~.Reddit`. """ self.parsers = {} if parsers is None else parsers self._reddit = reddit def _objectify_dict(self, data): """Create RedditBase objects from dicts. :param data: The structured data, assumed to be a dict. :returns: An instance of :class:`~.RedditBase`. """ if {"conversation", "messages", "modActions"}.issubset(data): parser = self.parsers["ModmailConversation"] elif {"actionTypeId", "author", "date"}.issubset(data): # Modmail mod action data = snake_case_keys(data) parser = self.parsers["ModmailAction"] elif {"bodyMarkdown", "isInternal"}.issubset(data): # Modmail message data = snake_case_keys(data) parser = self.parsers["ModmailMessage"] elif {"kind", "short_name", "violation_reason"}.issubset(data): # This is a Rule parser = self.parsers["rule"] elif {"isAdmin", "isDeleted"}.issubset(data): # Modmail author data = snake_case_keys(data) # Prevent clobbering base-36 id del data["id"] data["is_subreddit_mod"] = data.pop("is_mod") parser = self.parsers[self._reddit.config.kinds["redditor"]] elif {"banStatus", "muteStatus", "recentComments"}.issubset(data): # Modmail user data = snake_case_keys(data) data["created_string"] = data.pop("created") parser = self.parsers[self._reddit.config.kinds["redditor"]] elif {"displayName", "id", "type"}.issubset(data): # Modmail subreddit data = snake_case_keys(data) parser = self.parsers[self._reddit.config.kinds[data["type"]]] elif {"date", "id", "name"}.issubset(data) or { "id", "name", "permissions", }.issubset(data): parser = self.parsers[self._reddit.config.kinds["redditor"]] elif {"text", "url"}.issubset(data): if "color" in data or "linkUrl" in data: parser = self.parsers["Button"] else: parser = self.parsers["MenuLink"] elif {"children", "text"}.issubset(data): parser = self.parsers["Submenu"] elif {"height", "url", "width"}.issubset(data): parser = self.parsers["Image"] elif {"isSubscribed", "name", "subscribers"}.issubset(data): # discards icon and subscribed information return self._reddit.subreddit(data["name"]) elif {"authorFlairType", "name"}.issubset(data): # discards flair information return self._reddit.redditor(data["name"]) elif {"parent_id"}.issubset(data): parser = self.parsers[self._reddit.config.kinds["comment"]] elif "collection_id" in data.keys(): parser = self.parsers["Collection"] elif {"moderators", "moderatorIds", "allUsersLoaded", "subredditId"}.issubset( data ): data = snake_case_keys(data) moderators = [] for mod_id in data["moderator_ids"]: mod = snake_case_keys(data["moderators"][mod_id]) mod["mod_permissions"] = list(mod["mod_permissions"].keys()) moderators.append(mod) data["moderators"] = moderators parser = self.parsers["moderator-list"] elif "username" in data.keys(): data["name"] = data.pop("username") parser = self.parsers[self._reddit.config.kinds["redditor"]] else: if "user" in data: parser = self.parsers[self._reddit.config.kinds["redditor"]] data["user"] = parser.parse({"name": data["user"]}, self._reddit) return data return parser.parse(data, self._reddit) def objectify( self, data: Optional[Union[Dict[str, Any], List[Any]]] ) -> Optional[Union[RedditBase, Dict[str, Any], List[Any]]]: """Create RedditBase objects from data. :param data: The structured data. :returns: An instance of :class:`~.RedditBase`, or ``None`` if given ``data`` is ``None``. """ # pylint: disable=too-many-return-statements if data is None: # 204 no content return None if isinstance(data, list): return [self.objectify(item) for item in data] if "json" in data and "errors" in data["json"]: errors = data["json"]["errors"] if len(errors) > 0: raise RedditAPIException(errors) if "kind" in data and ( "shortName" in data or data["kind"] in ("menu", "moderators") ): # This is a widget parser = self.parsers.get(data["kind"], self.parsers["widget"]) return parser.parse(data, self._reddit) if {"kind", "data"}.issubset(data) and data["kind"] in self.parsers: parser = self.parsers[data["kind"]] return parser.parse(data["data"], self._reddit) if "json" in data and "data" in data["json"]: if "websocket_url" in data["json"]["data"]: return data if "things" in data["json"]["data"]: # Submission.reply return self.objectify(data["json"]["data"]["things"]) if "rules" in data["json"]["data"]: return self.objectify(loads(data["json"]["data"]["rules"])) if "url" in data["json"]["data"]: # Subreddit.submit # The URL is the URL to the submission, so it's removed. del data["json"]["data"]["url"] parser = self.parsers[self._reddit.config.kinds["submission"]] if data["json"]["data"]["id"].startswith( f"{self._reddit.config.kinds['submission']}_" ): # With polls, Reddit returns a fullname but calls it an "id". This # fixes this by coercing the fullname into an id. data["json"]["data"]["id"] = data["json"]["data"]["id"].split( "_", 1 )[1] else: parser = self.parsers["LiveUpdateEvent"] return parser.parse(data["json"]["data"], self._reddit) if "rules" in data: return self.objectify(data["rules"]) elif isinstance(data, dict): return self._objectify_dict(data) return data
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from .core import * SCHEMA_VERSION = 'v2.6.5' SCHEMA_URL = 'https://vega.github.io/schema/vega/v2.6.5.json'
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"""Various input/output utility functions""" from typing import Any, Optional import os import re from io import BytesIO import cloudpickle import pandas as pd from zstandard import ZstdCompressor, ZstdDecompressor COMPRESSION_MAX_OUTPUT_SIZE = 10 ** 9 # 1GB def pickle_dumps(variable: object) -> bytes: pickle: bytes = cloudpickle.dumps(variable) return pickle def pickle_loads(dumped_pickle: bytes) -> Any: return cloudpickle.loads(dumped_pickle) def save_df(df: pd.DataFrame, format: str = "csv") -> bytes: pandas_version: int = int(re.sub("[^0-9]", "", pd.__version__)) if format == "csv": csv_buffer = BytesIO() if pandas_version >= 120: df.to_csv(csv_buffer, index=False) else: csv_buffer.write(df.to_csv(index=False).encode("utf-8")) csv_buffer.seek(0) return csv_buffer.getvalue() else: raise ValueError("Invalid method: {method}. Choose 'csv'.") def compress(data: bytes, method: Optional[str] = "zstd") -> bytes: if method == "zstd": compressor = ZstdCompressor(level=3, write_checksum=True) compressed_data = compressor.compress(data) elif method is None: compressed_data = data # elif compression == "lz4": # import lz4.frame # data = lz4.frame.compress(data, compression_level=3, content_checksum=True) else: raise ValueError("Invalid compression method: {method}. Choose 'zstd' or None.") return compressed_data def decompress( data: bytes, method: Optional[str] = "zstd", max_output_size: int = COMPRESSION_MAX_OUTPUT_SIZE ) -> bytes: if method == "zstd": decompressor = ZstdDecompressor() decompressed_data = decompressor.decompress(data, max_output_size=max_output_size) elif method is None: decompressed_data = data else: raise ValueError("Invalid compression method: {method}. Choose 'zstd' or None.") return decompressed_data
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# coding: utf-8 from __future__ import unicode_literals from io import StringIO, BytesIO from pathlib import Path import pytest from .util import load_test_model from ..tokens import Doc from ..strings import StringStore from .. import util # These languages are used for generic tokenizer tests – only add a language # here if it's using spaCy's tokenizer (not a different library) # TODO: re-implement generic tokenizer tests _languages = ['bn', 'da', 'de', 'en', 'es', 'fi', 'fr', 'ga', 'he', 'hu', 'id', 'it', 'nb', 'nl', 'pl', 'pt', 'ro', 'ru', 'sv', 'tr', 'ar', 'xx'] _models = {'en': ['en_core_web_sm'], 'de': ['de_core_news_sm'], 'fr': ['fr_core_news_sm'], 'xx': ['xx_ent_web_sm'], 'en_core_web_md': ['en_core_web_md'], 'es_core_news_md': ['es_core_news_md']} # only used for tests that require loading the models # in all other cases, use specific instances @pytest.fixture(params=_models['en']) def EN(request): return load_test_model(request.param) @pytest.fixture(params=_models['de']) def DE(request): return load_test_model(request.param) @pytest.fixture(params=_models['fr']) def FR(request): return load_test_model(request.param) @pytest.fixture() def RU(request): pymorphy = pytest.importorskip('pymorphy2') return util.get_lang_class('ru')() #@pytest.fixture(params=_languages) #def tokenizer(request): #lang = util.get_lang_class(request.param) #return lang.Defaults.create_tokenizer() @pytest.fixture def tokenizer(): return util.get_lang_class('xx').Defaults.create_tokenizer() @pytest.fixture def en_tokenizer(): return util.get_lang_class('en').Defaults.create_tokenizer() @pytest.fixture def en_vocab(): return util.get_lang_class('en').Defaults.create_vocab() @pytest.fixture def en_parser(en_vocab): nlp = util.get_lang_class('en')(en_vocab) return nlp.create_pipe('parser') @pytest.fixture def es_tokenizer(): return util.get_lang_class('es').Defaults.create_tokenizer() @pytest.fixture def de_tokenizer(): return util.get_lang_class('de').Defaults.create_tokenizer() @pytest.fixture def fr_tokenizer(): return util.get_lang_class('fr').Defaults.create_tokenizer() @pytest.fixture def hu_tokenizer(): return util.get_lang_class('hu').Defaults.create_tokenizer() @pytest.fixture def fi_tokenizer(): return util.get_lang_class('fi').Defaults.create_tokenizer() @pytest.fixture def ro_tokenizer(): return util.get_lang_class('ro').Defaults.create_tokenizer() @pytest.fixture def id_tokenizer(): return util.get_lang_class('id').Defaults.create_tokenizer() @pytest.fixture def sv_tokenizer(): return util.get_lang_class('sv').Defaults.create_tokenizer() @pytest.fixture def bn_tokenizer(): return util.get_lang_class('bn').Defaults.create_tokenizer() @pytest.fixture def ga_tokenizer(): return util.get_lang_class('ga').Defaults.create_tokenizer() @pytest.fixture def he_tokenizer(): return util.get_lang_class('he').Defaults.create_tokenizer() @pytest.fixture def nb_tokenizer(): return util.get_lang_class('nb').Defaults.create_tokenizer() @pytest.fixture def da_tokenizer(): return util.get_lang_class('da').Defaults.create_tokenizer() @pytest.fixture def ja_tokenizer(): janome = pytest.importorskip("MeCab") return util.get_lang_class('ja').Defaults.create_tokenizer() @pytest.fixture def th_tokenizer(): pythainlp = pytest.importorskip("pythainlp") return util.get_lang_class('th').Defaults.create_tokenizer() @pytest.fixture def tr_tokenizer(): return util.get_lang_class('tr').Defaults.create_tokenizer() @pytest.fixture def ar_tokenizer(): return util.get_lang_class('ar').Defaults.create_tokenizer() @pytest.fixture def ru_tokenizer(): pymorphy = pytest.importorskip('pymorphy2') return util.get_lang_class('ru').Defaults.create_tokenizer() @pytest.fixture def stringstore(): return StringStore() @pytest.fixture def en_entityrecognizer(): return util.get_lang_class('en').Defaults.create_entity() @pytest.fixture def text_file(): return StringIO() @pytest.fixture def text_file_b(): return BytesIO() def pytest_addoption(parser): parser.addoption("--models", action="store_true", help="include tests that require full models") parser.addoption("--vectors", action="store_true", help="include word vectors tests") parser.addoption("--slow", action="store_true", help="include slow tests") for lang in _languages + ['all']: parser.addoption("--%s" % lang, action="store_true", help="Use %s models" % lang) for model in _models: if model not in _languages: parser.addoption("--%s" % model, action="store_true", help="Use %s model" % model) def pytest_runtest_setup(item): for opt in ['models', 'vectors', 'slow']: if opt in item.keywords and not item.config.getoption("--%s" % opt): pytest.skip("need --%s option to run" % opt) # Check if test is marked with models and has arguments set, i.e. specific # language. If so, skip test if flag not set. if item.get_marker('models'): for arg in item.get_marker('models').args: if not item.config.getoption("--%s" % arg) and not item.config.getoption("--all"): pytest.skip("need --%s or --all option to run" % arg)
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from loss.BCELoss import cal_bce_loss from loss.HEL import cal_hel_loss from loss.IOULoss import cal_iou_loss, cal_weighted_iou_loss from loss.L12Loss import cal_mae_loss, cal_mse_loss from loss.SSIM import cal_ssim_loss supported_loss = dict( bce=cal_bce_loss, hel=cal_hel_loss, iou=cal_iou_loss, weighted_iou=cal_weighted_iou_loss, mae=cal_mae_loss, mse=cal_mse_loss, ssim=cal_ssim_loss, ) def get_loss_combination_with_cfg(loss_cfg: dict) -> dict: loss_combination = {} for loss_name, with_loss in loss_cfg.items(): if with_loss: if loss_func := supported_loss.get(loss_name): loss_combination[loss_name] = loss_func else: raise Exception(f"{loss_name} is not be supported!") return loss_combination
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#!/usr/bin/env python3 #https://codeforces.com/group/H9K9zY8tcT/contest/297258/problem/B #heap? from queue import PriorityQueue n = int(input()) g = {} c = {str(i):0 for i in range(1,n+1)} #children count for i in range(1,n+1): k = str(i) g[k] = input().split() # l[0]=weight; l[1]=no use; l[2:] parents; for p in g[k][2:]: c[p] += 1 q = PriorityQueue() [q.put((int(g[k][0]),k)) for k in c if c[k]==0] m = 0 i = n-1 while not q.empty(): w,k = q.get() l = i + w i -= 1 if l>m: m = l for p in g[k][2:]: c[p] -= 1 if c[p]==0: q.put((int(g[p][0]),p)) print(m)
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from django.forms import ModelForm from .models import MRIScan class MRIScanForm(ModelForm): class Meta: model = MRIScan fields = ['case_id', 't1', 't1ce', 't2', 'flair']
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# coding=utf-8 # Copyright 2020 The Google Research Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tests for task_set.tasks.fixed_text_rnn_classification.""" from absl.testing import parameterized from task_set import registry from task_set.tasks import family_test_utils from task_set.tasks.fixed import fixed_text_rnn_classification # pylint: disable=unused-import import tensorflow.compat.v1 as tf class FixedTextRNNClassificationTest(family_test_utils.SingleTaskTestCase): def test_right_number_of_tasks(self): task_names = registry.task_registry.get_all_fixed_config_names() self.assertLen(task_names, 12) @parameterized.parameters(registry.task_registry.get_all_fixed_config_names()) def test_tasks(self, task_name): self.task_test(registry.task_registry.get_instance(task_name)) if __name__ == "__main__": tf.test.main()
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# get hsv values using trackbar import cv2 import numpy as np import time # A required callback method that goes into the trackbar function. def nothing(x): pass # Initializing the webcam feed. cap = cv2.VideoCapture(0) cap.set(3,1280) cap.set(4,720) # Create a window named trackbars. cv2.namedWindow("Trackbars") # Now create 6 trackbars that will control the lower and upper range of # H,S and V channels. The Arguments are like this: Name of trackbar, # window name, range,callback function. For Hue the range is 0-179 and # for S,V its 0-255. cv2.createTrackbar("L - H", "Trackbars", 0, 179, nothing) cv2.createTrackbar("L - S", "Trackbars", 0, 255, nothing) cv2.createTrackbar("L - V", "Trackbars", 0, 255, nothing) cv2.createTrackbar("U - H", "Trackbars", 179, 179, nothing) cv2.createTrackbar("U - S", "Trackbars", 255, 255, nothing) cv2.createTrackbar("U - V", "Trackbars", 255, 255, nothing) while True: # Start reading the webcam feed frame by frame. ret, frame = cap.read() if not ret: break # Flip the frame horizontally (Not required) frame = cv2.flip( frame, 1 ) # Convert the BGR image to HSV image. hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) # Get the new values of the trackbar in real time as the user changes # them l_h = cv2.getTrackbarPos("L - H", "Trackbars") l_s = cv2.getTrackbarPos("L - S", "Trackbars") l_v = cv2.getTrackbarPos("L - V", "Trackbars") u_h = cv2.getTrackbarPos("U - H", "Trackbars") u_s = cv2.getTrackbarPos("U - S", "Trackbars") u_v = cv2.getTrackbarPos("U - V", "Trackbars") # Set the lower and upper HSV range according to the value selected # by the trackbar lower_range = np.array([l_h, l_s, l_v]) upper_range = np.array([u_h, u_s, u_v]) # Filter the image and get the binary mask, where white represents # your target color mask = cv2.inRange(hsv, lower_range, upper_range) # You can also visualize the real part of the target color (Optional) res = cv2.bitwise_and(frame, frame, mask=mask) # Converting the binary mask to 3 channel image, this is just so # we can stack it with the others mask_3 = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR) # stack the mask, orginal frame and the filtered result stacked = np.hstack((mask_3,frame,res)) # Show this stacked frame at 40% of the size. cv2.imshow('Trackbars',cv2.resize(stacked,None,fx=0.4,fy=0.4)) # If the user presses ESC then exit the program key = cv2.waitKey(1) if key == 27: break # If the user presses `s` then print this array. if key == ord('s'): thearray = [[l_h,l_s,l_v],[u_h, u_s, u_v]] print(thearray) # Also save this array as penval.npy np.save('penval',thearray) break # Release the camera & destroy the windows. cap.release() cv2.destroyAllWindows()
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# -*- coding: utf-8 -*- """ Microsoft-Windows-Direct3D10_1 GUID : 9b7e4c8f-342c-4106-a19f-4f2704f689f0 """ from construct import Int8sl, Int8ul, Int16ul, Int16sl, Int32sl, Int32ul, Int64sl, Int64ul, Bytes, Double, Float32l, Struct from etl.utils import WString, CString, SystemTime, Guid from etl.dtyp import Sid from etl.parsers.etw.core import Etw, declare, guid @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=1, version=0) class Microsoft_Windows_Direct3D10_1_1_0(Etw): pattern = Struct( "pObject" / Int64ul, "CchOldDebugObjectName" / Int32ul, "OldDebugObjectName" / Bytes(lambda this: this.CchOldDebugObjectName), "CchNewDebugObjectName" / Int32ul, "NewDebugObjectName" / Bytes(lambda this: this.CchNewDebugObjectName) ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=2, version=0) class Microsoft_Windows_Direct3D10_1_2_0(Etw): pattern = Struct( "pObject" / Int64ul, "CchDebugObjectName" / Int32ul, "DebugObjectName" / Bytes(lambda this: this.CchDebugObjectName) ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=3, version=0) class Microsoft_Windows_Direct3D10_1_3_0(Etw): pattern = Struct( "pID3D10_1Device" / Int64ul, "pIDXGIDevice" / Int64ul, "pIDXGIAdapter" / Int64ul, "CreationFlags" / Int32ul, "FeatureLevel" / Int32ul, "hKMAdapter" / Int32ul, "hUMAdapter" / Int64ul, "UMAdapterVersion" / Int64ul, "hKMDevice" / Int32ul, "hUMDevice" / Int64ul, "UMDeviceVersion" / Int64ul, "UMDeviceFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=4, version=0) class Microsoft_Windows_Direct3D10_1_4_0(Etw): pattern = Struct( "pID3D10_1Device" / Int64ul, "pIDXGIDevice" / Int64ul, "pIDXGIAdapter" / Int64ul, "CreationFlags" / Int32ul, "FeatureLevel" / Int32ul, "hKMAdapter" / Int32ul, "hUMAdapter" / Int64ul, "UMAdapterVersion" / Int64ul, "hKMDevice" / Int32ul, "hUMDevice" / Int64ul, "UMDeviceVersion" / Int64ul, "UMDeviceFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=5, version=0) class Microsoft_Windows_Direct3D10_1_5_0(Etw): pattern = Struct( "pID3D10_1Device" / Int64ul, "pIDXGIDevice" / Int64ul, "pIDXGIAdapter" / Int64ul, "CreationFlags" / Int32ul, "FeatureLevel" / Int32ul, "hKMAdapter" / Int32ul, "hUMAdapter" / Int64ul, "UMAdapterVersion" / Int64ul, "hKMDevice" / Int32ul, "hUMDevice" / Int64ul, "UMDeviceVersion" / Int64ul, "UMDeviceFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=6, version=0) class Microsoft_Windows_Direct3D10_1_6_0(Etw): pattern = Struct( "pID3D10Resource" / Int64ul, "pIDXGISurface" / Int64ul, "pID3D10_1Device" / Int64ul, "Dimension" / Int32ul, "Usage" / Int32ul, "Width" / Int32ul, "Height" / Int32ul, "Depth" / Int32ul, "MipLevels" / Int32ul, "ArraySize" / Int32ul, "Format" / Int32ul, "SampleCount" / Int32ul, "SampleQuality" / Int32ul, "BindFlags" / Int32ul, "CPUAccessFlags" / Int32ul, "MiscFlags" / Int32ul, "hKMResource" / Int32ul, "hUMResource" / Int64ul, "UMResourceMiscFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=7, version=0) class Microsoft_Windows_Direct3D10_1_7_0(Etw): pattern = Struct( "pID3D10Resource" / Int64ul, "pIDXGISurface" / Int64ul, "pID3D10_1Device" / Int64ul, "Dimension" / Int32ul, "Usage" / Int32ul, "Width" / Int32ul, "Height" / Int32ul, "Depth" / Int32ul, "MipLevels" / Int32ul, "ArraySize" / Int32ul, "Format" / Int32ul, "SampleCount" / Int32ul, "SampleQuality" / Int32ul, "BindFlags" / Int32ul, "CPUAccessFlags" / Int32ul, "MiscFlags" / Int32ul, "hKMResource" / Int32ul, "hUMResource" / Int64ul, "UMResourceMiscFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=8, version=0) class Microsoft_Windows_Direct3D10_1_8_0(Etw): pattern = Struct( "pID3D10Resource" / Int64ul, "pIDXGISurface" / Int64ul, "pID3D10_1Device" / Int64ul, "Dimension" / Int32ul, "Usage" / Int32ul, "Width" / Int32ul, "Height" / Int32ul, "Depth" / Int32ul, "MipLevels" / Int32ul, "ArraySize" / Int32ul, "Format" / Int32ul, "SampleCount" / Int32ul, "SampleQuality" / Int32ul, "BindFlags" / Int32ul, "CPUAccessFlags" / Int32ul, "MiscFlags" / Int32ul, "hKMResource" / Int32ul, "hUMResource" / Int64ul, "UMResourceMiscFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=9, version=0) class Microsoft_Windows_Direct3D10_1_9_0(Etw): pattern = Struct( "pID3D10Resource" / Int64ul, "pIDXGISurface" / Int64ul, "pID3D10_1Device" / Int64ul, "Dimension" / Int32ul, "Usage" / Int32ul, "Width" / Int32ul, "Height" / Int32ul, "Depth" / Int32ul, "MipLevels" / Int32ul, "ArraySize" / Int32ul, "Format" / Int32ul, "SampleCount" / Int32ul, "SampleQuality" / Int32ul, "BindFlags" / Int32ul, "CPUAccessFlags" / Int32ul, "MiscFlags" / Int32ul, "hKMResource" / Int32ul, "hUMResource" / Int64ul, "UMResourceMiscFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=10, version=0) class Microsoft_Windows_Direct3D10_1_10_0(Etw): pattern = Struct( "pID3D10Resource" / Int64ul, "pIDXGISurface" / Int64ul, "pID3D10_1Device" / Int64ul, "Dimension" / Int32ul, "Usage" / Int32ul, "Width" / Int32ul, "Height" / Int32ul, "Depth" / Int32ul, "MipLevels" / Int32ul, "ArraySize" / Int32ul, "Format" / Int32ul, "SampleCount" / Int32ul, "SampleQuality" / Int32ul, "BindFlags" / Int32ul, "CPUAccessFlags" / Int32ul, "MiscFlags" / Int32ul, "hKMResource" / Int32ul, "hUMResource" / Int64ul, "UMResourceMiscFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=11, version=0) class Microsoft_Windows_Direct3D10_1_11_0(Etw): pattern = Struct( "pID3D10Resource" / Int64ul, "pIDXGISurface" / Int64ul, "pID3D10_1Device" / Int64ul, "Dimension" / Int32ul, "Usage" / Int32ul, "Width" / Int32ul, "Height" / Int32ul, "Depth" / Int32ul, "MipLevels" / Int32ul, "ArraySize" / Int32ul, "Format" / Int32ul, "SampleCount" / Int32ul, "SampleQuality" / Int32ul, "BindFlags" / Int32ul, "CPUAccessFlags" / Int32ul, "MiscFlags" / Int32ul, "hKMResource" / Int32ul, "hUMResource" / Int64ul, "UMResourceMiscFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=12, version=0) class Microsoft_Windows_Direct3D10_1_12_0(Etw): pattern = Struct( "pID3D10Resource" / Int64ul, "pIDXGISurface" / Int64ul, "pID3D10_1Device" / Int64ul, "Dimension" / Int32ul, "Usage" / Int32ul, "Width" / Int32ul, "Height" / Int32ul, "Depth" / Int32ul, "MipLevels" / Int32ul, "ArraySize" / Int32ul, "Format" / Int32ul, "SampleCount" / Int32ul, "SampleQuality" / Int32ul, "BindFlags" / Int32ul, "CPUAccessFlags" / Int32ul, "MiscFlags" / Int32ul, "hKMResource" / Int32ul, "hUMResource" / Int64ul, "UMResourceMiscFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=13, version=0) class Microsoft_Windows_Direct3D10_1_13_0(Etw): pattern = Struct( "pID3D10Resource" / Int64ul, "pIDXGISurface" / Int64ul, "pID3D10_1Device" / Int64ul, "Dimension" / Int32ul, "Usage" / Int32ul, "Width" / Int32ul, "Height" / Int32ul, "Depth" / Int32ul, "MipLevels" / Int32ul, "ArraySize" / Int32ul, "Format" / Int32ul, "SampleCount" / Int32ul, "SampleQuality" / Int32ul, "BindFlags" / Int32ul, "CPUAccessFlags" / Int32ul, "MiscFlags" / Int32ul, "hKMResource" / Int32ul, "hUMResource" / Int64ul, "UMResourceMiscFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=14, version=0) class Microsoft_Windows_Direct3D10_1_14_0(Etw): pattern = Struct( "pID3D10Resource" / Int64ul, "pIDXGISurface" / Int64ul, "pID3D10_1Device" / Int64ul, "Dimension" / Int32ul, "Usage" / Int32ul, "Width" / Int32ul, "Height" / Int32ul, "Depth" / Int32ul, "MipLevels" / Int32ul, "ArraySize" / Int32ul, "Format" / Int32ul, "SampleCount" / Int32ul, "SampleQuality" / Int32ul, "BindFlags" / Int32ul, "CPUAccessFlags" / Int32ul, "MiscFlags" / Int32ul, "hKMResource" / Int32ul, "hUMResource" / Int64ul, "UMResourceMiscFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=15, version=0) class Microsoft_Windows_Direct3D10_1_15_0(Etw): pattern = Struct( "pID3D10Resource" / Int64ul, "pIDXGISurface" / Int64ul, "pID3D10_1Device" / Int64ul, "Dimension" / Int32ul, "Usage" / Int32ul, "Width" / Int32ul, "Height" / Int32ul, "Depth" / Int32ul, "MipLevels" / Int32ul, "ArraySize" / Int32ul, "Format" / Int32ul, "SampleCount" / Int32ul, "SampleQuality" / Int32ul, "BindFlags" / Int32ul, "CPUAccessFlags" / Int32ul, "MiscFlags" / Int32ul, "hKMResource" / Int32ul, "hUMResource" / Int64ul, "UMResourceMiscFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=16, version=0) class Microsoft_Windows_Direct3D10_1_16_0(Etw): pattern = Struct( "pID3D10Resource" / Int64ul, "pIDXGISurface" / Int64ul, "pID3D10_1Device" / Int64ul, "Dimension" / Int32ul, "Usage" / Int32ul, "Width" / Int32ul, "Height" / Int32ul, "Depth" / Int32ul, "MipLevels" / Int32ul, "ArraySize" / Int32ul, "Format" / Int32ul, "SampleCount" / Int32ul, "SampleQuality" / Int32ul, "BindFlags" / Int32ul, "CPUAccessFlags" / Int32ul, "MiscFlags" / Int32ul, "hKMResource" / Int32ul, "hUMResource" / Int64ul, "UMResourceMiscFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=17, version=0) class Microsoft_Windows_Direct3D10_1_17_0(Etw): pattern = Struct( "pID3D10Resource" / Int64ul, "pIDXGISurface" / Int64ul, "pID3D10_1Device" / Int64ul, "Dimension" / Int32ul, "Usage" / Int32ul, "Width" / Int32ul, "Height" / Int32ul, "Depth" / Int32ul, "MipLevels" / Int32ul, "ArraySize" / Int32ul, "Format" / Int32ul, "SampleCount" / Int32ul, "SampleQuality" / Int32ul, "BindFlags" / Int32ul, "CPUAccessFlags" / Int32ul, "MiscFlags" / Int32ul, "hKMResource" / Int32ul, "hUMResource" / Int64ul, "UMResourceMiscFlags" / Int32ul ) @declare(guid=guid("9b7e4c8f-342c-4106-a19f-4f2704f689f0"), event_id=18, version=0) class Microsoft_Windows_Direct3D10_1_18_0(Etw): pattern = Struct( "Resources" / Int32ul, "pIDXGISurfaces" / Int64ul, "hNewKMResources" / Int32ul )
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# Generated by Django 2.0.4 on 2018-04-24 01:54 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('blog', '0001_initial'), ] operations = [ migrations.RenameField( model_name='post', old_name='sub_Title', new_name='sub_title', ), migrations.RemoveField( model_name='comment', name='vote', ), migrations.AddField( model_name='comment', name='text', field=models.CharField(default=1, max_length=150), preserve_default=False, ), ]
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# -*- coding: utf-8 -*- from __future__ import absolute_import import mock from exam import fixture from sentry.interfaces.template import Template from sentry.models import Event from sentry.testutils import TestCase class TemplateTest(TestCase): @fixture def interface(self): return Template.to_python(dict( filename='foo.html', context_line='hello world', lineno=1, )) def test_serialize(self): result = self.interface.to_json() self.assertEquals(result['filename'], 'foo.html') self.assertEquals(result['context_line'], 'hello world') self.assertEquals(result['lineno'], 1) def test_get_hash(self): result = self.interface.get_hash() self.assertEquals(result, ['foo.html', 'hello world']) @mock.patch('sentry.interfaces.template.get_context') @mock.patch('sentry.interfaces.template.Template.get_traceback') def test_to_string_returns_traceback(self, get_traceback, get_context): get_traceback.return_value = 'traceback' event = mock.Mock(spec=Event) result = self.interface.to_string(event) get_traceback.assert_called_once_with(event, get_context.return_value) self.assertEquals(result, 'Stacktrace (most recent call last):\n\ntraceback') def test_serialize_unserialize_behavior(self): result = type(self.interface).to_python(self.interface.to_json()) assert result.to_json() == self.interface.to_json()
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from django.shortcuts import render def contrib_file(request): return render(request, "dpaste/contribute.html")
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from tkinter import messagebox from ClientInsert import * class ClientEdit(ClientInsert): def __init__(self, db, id_cliente, master): super().__init__(db, master) self.title('Editar Cliente') self.__id_cliente = id_cliente self.__list = master table_cliente = db.select("CLIENTE", ["*"], ['id_cliente'], [str(id_cliente)])[0] table_municipio = db.select("MUNICIPIO", ["id_uf_municipio", "nome_municipio"], ["id_municipio"], [str(table_cliente["id_municipio_cliente"])])[0] table_uf = db.select("UF", ["nome_uf"], ["id_uf"], [str(table_municipio["id_uf_municipio"])])[0] table_telefone = db.select("TELEFONE", ["numero_telefone", "ddd_telefone"], ["id_cliente_telefone"], [str(id_cliente)]) telefones = "" for telefone in table_telefone: if (telefone['ddd_telefone'] != 0 and telefone['numero_telefone'] != 0): telefones += str(telefone['ddd_telefone']) telefones += str(telefone['numero_telefone']) self._ClientForm__str_rsocial.set( table_cliente['rsocial_cliente']) self._ClientForm__str_nfantasia.set( table_cliente['nfantasia_cliente']) self._ClientForm__tracer_cnpj.set( str(table_cliente['cnpj_cliente'])) self._ClientForm__tracer_iestadual.set( str(table_cliente['iestadual_cliente'])) self._ClientForm__tracer_imunicipal.set( str(table_cliente['imunicipal_cliente'])) self._ClientForm__str_logradouro.set( table_cliente['logradouro_cliente']) self._ClientForm__str_complemento.set( table_cliente['complemento_cliente']) self._ClientForm__tracer_cep.set( str(table_cliente['cep_cliente'])) self._ClientForm__tracer_telefone.set( telefones) celular = str(table_cliente['ddd_cel_cliente']) celular += str(table_cliente['ncel_cliente']) self._ClientForm__tracer_ncel.set( celular) self._ClientForm__str_bairro.set( table_cliente['bairro_cliente']) self._ClientForm__str_email.set( table_cliente['email_cliente']) self._ClientForm__str_url.set( table_cliente['url_cliente']) self._ClientForm__str_municipio.set(table_municipio["nome_municipio"]) self._ClientForm__str_uf.set(table_uf["nome_uf"]) self._ClientForm__int_whatsapp.set(table_cliente["whatsapp_cliente"]) self._ClientForm__button_salvar.config( command=self.__button_salvar_action) for i in range(0, len(self._ClientInsert__list_ufs)): if self._ClientInsert__list_ufs[i] == table_uf['nome_uf']: self._ClientForm__combo_uf.current(i) for i in range(0, len(self._ClientInsert__list_municipios)): if self._ClientInsert__list_municipios[i] == table_municipio['nome_municipio']: self._ClientForm__combo_municipio.current(i) def __button_salvar_action(self): data = self._ClientInsert__data_validation() if data == None: return else: self.__database_update(data) def __database_update(self, data): rsocial = data[0] nfantasia = data[1] cnpj = data[2] iestadual = data[3] imunicipal = data[4] logradouro = data[5] complemento = data[6] bairro = data[7] municipio = data[8] uf = data[9] cep = data[10] telefone = data[11] ncel = data[12] whatsapp = data[13] email = data[14] url = data[15] uf_id = str(self._ClientInsert__db.select("UF", ['id_uf'], ['nome_uf'], [uf])[0]['id_uf']) municipio_id = self._ClientInsert__db.select("MUNICIPIO", ['id_municipio'], ['nome_municipio', 'id_uf_municipio'], [municipio, uf_id]) if len(municipio_id) == 0: self._ClientInsert__db.insert("MUNICIPIO", ['nome_municipio', 'id_uf_municipio'], [municipio, uf_id]) municipio_id = str( self._ClientInsert__db.last_insert_id()[0]['LAST_INSERT_ID()']) else: municipio_id = str(municipio_id[0]['id_municipio']) self._ClientInsert__db.update("CLIENTE", ['bairro_cliente', 'cep_cliente', 'rsocial_cliente', 'ncel_cliente', 'ddd_cel_cliente', 'nfantasia_cliente', 'whatsapp_cliente', 'cnpj_cliente', 'iestadual_cliente', 'imunicipal_cliente', 'logradouro_cliente', 'email_cliente', 'complemento_cliente', 'url_cliente', 'id_municipio_cliente'], [bairro, cep, rsocial, ncel[2:], ncel[:2], nfantasia, whatsapp, cnpj, iestadual, imunicipal, logradouro, email, complemento, url, municipio_id], ['id_cliente'], [str(self.__id_cliente)]) table_telefone_id = self._ClientInsert__db.select("TELEFONE", ['id_telefone'], ['id_cliente_telefone'], [str(self.__id_cliente)]) self._ClientInsert__db.update("TELEFONE", ['ddd_telefone', 'numero_telefone'], [self._ClientInsert__ddd_telefone, self._ClientInsert__number_telefone], ['id_telefone'], [str(table_telefone_id[0]['id_telefone'])]) self._ClientInsert__db.update("TELEFONE", ['ddd_telefone', 'numero_telefone'], [self._ClientInsert__ddd_telefone2, self._ClientInsert__number_telefone2], ['id_telefone'], [str(table_telefone_id[1]['id_telefone'])]) self._ClientInsert__db.update("TELEFONE", ['ddd_telefone', 'numero_telefone'], [self._ClientInsert__ddd_telefone3, self._ClientInsert__number_telefone3], ['id_telefone'], [str(table_telefone_id[2]['id_telefone'])]) messagebox.showinfo("Informação", "Dados alterados!", parent=self) self.destroy() self.__list.filter_client()
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template = """<!DOCTYPE html> <html> <head> <meta charset="UTF-8"> <title>Title of the document</title> <script type="text/javascript" src="https://s3.tradingview.com/tv.js"></script> <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/milligram/1.3.0/milligram.min.css"> <style> .tradingview-widget-container {{ position: sticky; top: 20px; }} .stocks-view {{ display: flex; flex-wrap: nowrap; }} .stocks-listing {{ width: 780px; flex-wrap: nowrap; padding: 20px; }} .stocks-graph {{ flex-wrap: nowrap; padding: 20px; }} th.sticky-header {{ position: sticky; top: 0; z-index: 10; background-color: white; }} .positive-movement {{ color: green; font-weight: bold; }} .negative-movement {{ color: red; font-weight: bold; }} .blue-category {{ background-color: lightsteelblue; }} </style> </head> <body> {} <div class="stocks-view"> <div class="stocks-listing"> <table> <thead> <tr> <th class="sticky-header">Symbol</th> <th class="sticky-header">April 1 2019</th> <th class="sticky-header">Dec 2 2019</th> <th class="sticky-header">Today</th> <th class="sticky-header">Movement since April 1 2019</th> <th class="sticky-header">Movement since Dec 2 2019</th> <th class="sticky-header">Bankruptcy probability</th> </tr> </thead> <tbody> {} </tbody> </table> </div> <div class="stocks-graph" <!-- TradingView Widget BEGIN --> <div class="tradingview-widget-container"> <div id="tradingview_63a66"></div> <div class="tradingview-widget-copyright"><a href="https://www.tradingview.com/symbols/AAPL/" rel="noopener" target="_blank"><span class="blue-text">AAPL Chart</span></a> by TradingView</div> </div> <!-- TradingView Widget END --> </div> </div> <script type="text/javascript"> function renderChart(symbol) {{ new TradingView.widget( {{ "width": 750, "height": 500, "symbol": symbol, "interval": "180", "timezone": "Etc/UTC", "theme": "light", "style": "1", "locale": "en", "toolbar_bg": "#f1f3f6", "enable_publishing": false, "allow_symbol_change": true, "container_id": "tradingview_63a66" }} ); }} document.addEventListener('DOMContentLoaded', function(){{ renderChart('BA'); }}, false); </script> </body> </html>"""
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