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from dialog_api.users_pb2 import RequestLoadFullUsers, ResponseLoadFullUsers, FullUser
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import json
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#Python's random module includes a function choice(data) that returns a #random element from a non-empty sequence. The random modul includes a #more basic function randrange,with parameterization similar to the #built-in range function , that return a random choice from the given #range.Using only the randrange funciton,implement your own version of #the choice function. import random lottoMax = list() lottoMax = [random.randrange(1,50,1) for i in range(1,8)] print(lottoMax)
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#!/usr/bin/env python3 """Tables: data: pk timestamp field_name field_value source_record We don't know what type each value will have, so have a column for int, float, str and bool and leave all but the appropriate value type NULL. Docs claim that NULL values take no space, so... Still so many ways we could make this more space efficient, most obviously by partitioning field_name (and even timestamp?) into foreign keys. field_name - could store this in a separate table so that it's only a foreign key in the data table. Something like: fields: id field_name field_type source_record - an id indexing a table where raw source records are stored, so that we can re-parse and recreate whatever data we want if needed. Current implementation is simple and inefficient in both computation and storage. TODO: Allow wildcarding field selection, so client can specify 'S330*,Knud*' """ import logging import sys import json sys.path.append('.') from logger.utils.formats import Python_Record from logger.utils.das_record import DASRecord try: import pymongo MONGO_ENABLED = True except ImportError: MONGO_ENABLED = False ################################################################################
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# ============================================================================= # Inicializacin de la aplicacin: __init__.py # ============================================================================= """ Este archivo tendr la funcin de crear la aplicacin, que iniciar la base de datos y registrar los molodelos. Para ejecutar: 1) En un terminal de linux ir a la ruta: >> cd Documentos/TFM/ElectricRoute/flask_auth_app >> export FLASK_APP=project >> export FLASK_DEBUG=1 >> Si se va a lanzar flask_app en local: export DB_HOST=0.0.0.0 >> Si se va a lanzar flask_app en local: export GRAFANA_HOST=0.0.0.0 >> flask run 2) Abrir el navegador e ir a la ruta http://localhost:5000/login 3") Insertar un mail y una contrasea (cualquier) Ejemplo: User: blanca@hotmail.com Password: blanca """ # Se cargan las librerias from flask import Flask from flask_login import LoginManager from flask_mysqldb import MySQL from os import environ from .BE.Output import BaseDatos # Se inicializa SQLAlchemy db = MySQL() # Se crea la app
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from store.cifar10 import Cifar10 import torchvision.transforms as transforms import time import matplotlib.pyplot as plt batch_size = 1 rel_sample_size = 10000 ds = Cifar10(input_data_folder="/home/aarati/datasets/cifar-10-batches-py", \ max_batches=2, batch_size=batch_size, rel_sample_size=rel_sample_size, \ max_samples=1, transform=transforms.ToTensor()) ds.count_num_points() ds.generate_IR() all_times = [] for i in range(10): start = time.time() ds.initialize_samples() end = time.time() all_times.append(end-start) s = ds.samples[0].get() print(all_times) # Sample creation time for sample size: # 1: [0.349, 0.306, 0.431, 0.303, 0.18, 0.69, 0.557, 0.681, 0.424, 0.300] # 10: [0.742, 0.685, 0.679, 0.676, 0.673, 0.676, 0.551, 0.673, 0.669, 0.670] # 100: [0.713, 0.672, 0.668, 0.671, 0.668, 0.680, 0.682, 0.675, 0.673, 0.669] # 1000: [0.738, 0.689, 0.704, 0.693, 0.684, 0.683, 0.678, 0.677, 0.700, 0.687] # 10000: [0.765, 0.727, 0.717, 0.740, 0.723, 0.774, 0.720, 0.868, 0.724, 0.771] # Plotting code # x = [1, 10, 50, 100, 1000, 10000] # y = [0.45, 0.702, 0.703, 0.708, 0.715, 0.746] # plt.plot(x, y, color='b', marker='o', markerfacecolor='k', markersize=10, fillstyle='full', linewidth=3, linestyle='solid') # plt.xscale('log') # plt.ylim(0.40, 0.78) # plt.xlabel("Reservoir Sample Size", fontsize=20, fontweight='semibold', fontname='serif') # plt.ylabel("Creation Time (s)", fontsize=20, fontweight='semibold', fontname='serif') # plt.xticks(x, [1, 10, '', 100, 1000, 10000]) # _, ticks = plt.xticks() # for tick in ticks: # tick.set_fontsize(16) # tick.set_fontweight('medium') # tick.set_fontname('serif') # _, ticks = plt.yticks() # for tick in ticks: # tick.set_fontsize(16) # tick.set_fontweight('medium') # tick.set_fontname('serif') # plt.show()
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"""Plugin that invokes the built-in template renderer.""" __all__ = [ "RenderOptions", "render", ] from typing import Dict, List from pydantic import BaseModel from beet import Context, configurable
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import sys import tkinter from .customtkinter_tk import CTk from .customtkinter_frame import CTkFrame from .appearance_mode_tracker import AppearanceModeTracker from .customtkinter_color_manager import CTkColorManager
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import pytest from backtest.strategy import BuyAndHoldEqualAllocation
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# SPDX-License-Identifier: Apache-2.0 from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np import onnx from ..base import Base from . import expect
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#!/usr/bin/python # -*- coding: utf-8 -*- """ Python-nvd3 is a Python wrapper for NVD3 graph library. NVD3 is an attempt to build re-usable charts and chart components for d3.js without taking away the power that d3.js gives you. Project location : https://github.com/areski/python-nvd3 """ from .NVD3Chart import NVD3Chart, TemplateMixin
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""" Date: 2021/09/23 Target: config utilities for yml file. implementation adapted from Slimmable: https://github.com/JiahuiYu/slimmable_networks.git """ import os import yaml def get_config(config_file): assert os.path.exists(config_file), 'File {} not exist.'.format(config_file) return Config(config_file)
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from marshmallow import Schema, fields, validate from sqlalchemy import Column, String, Integer, Float, Date, ForeignKey from sqlalchemy.orm import relationship from ..funders.entities import Funder, FunderSchema from src.api import db from src.shared.entity import Base
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### # Copyright Notice: # Copyright 2016 Distributed Management Task Force, Inc. All rights reserved. # License: BSD 3-Clause License. For full text see link: https://github.com/DMTF/python-redfish-utility/blob/master/LICENSE.md ### """ Commit Command for RDMC """ import sys from optparse import OptionParser from rdmc_helper import ReturnCodes, InvalidCommandLineErrorOPTS, \ NoChangesFoundOrMadeError, NoCurrentSessionEstablished from rdmc_base_classes import RdmcCommandBase
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from django.conf import settings from django.contrib.auth.decorators import user_passes_test from django.core.paginator import Paginator from django.core.urlresolvers import reverse from django.http import Http404, HttpResponseRedirect, HttpResponse from django.shortcuts import render_to_response from django.template import RequestContext from django.utils.encoding import smart_unicode, iri_to_uri from django.utils.translation import ugettext_lazy as _ from django.views.decorators.cache import never_cache from rosetta.conf import settings as rosetta_settings from rosetta.polib import pofile from rosetta.poutil import find_pos, pagination_range from rosetta.signals import entry_changed, post_save import re import rosetta import datetime import unicodedata import hashlib import os def home(request): """ Displays a list of messages to be translated """ def fix_nls(in_, out_): """Fixes submitted translations by filtering carriage returns and pairing newlines at the begging and end of the translated string with the original """ if 0 == len(in_) or 0 == len(out_): return out_ if "\r" in out_ and "\r" not in in_: out_ = out_.replace("\r", '') if "\n" == in_[0] and "\n" != out_[0]: out_ = "\n" + out_ elif "\n" != in_[0] and "\n" == out_[0]: out_ = out_.lstrip() if "\n" == in_[-1] and "\n" != out_[-1]: out_ = out_ + "\n" elif "\n" != in_[-1] and "\n" == out_[-1]: out_ = out_.rstrip() return out_ version = rosetta.get_version(True) if 'rosetta_i18n_fn' in request.session: rosetta_i18n_fn = request.session.get('rosetta_i18n_fn') rosetta_i18n_app = get_app_name(rosetta_i18n_fn) rosetta_i18n_lang_code = request.session['rosetta_i18n_lang_code'] rosetta_i18n_lang_bidi = rosetta_i18n_lang_code.split('-')[0] in settings.LANGUAGES_BIDI rosetta_i18n_write = request.session.get('rosetta_i18n_write', True) if rosetta_i18n_write: rosetta_i18n_pofile = pofile(rosetta_i18n_fn) for entry in rosetta_i18n_pofile: entry.md5hash = hashlib.md5(entry.msgid.encode("utf8") + entry.msgstr.encode("utf8")).hexdigest() else: rosetta_i18n_pofile = request.session.get('rosetta_i18n_pofile') if 'filter' in request.GET: if request.GET.get('filter') in ('untranslated', 'translated', 'fuzzy', 'all'): filter_ = request.GET.get('filter') request.session['rosetta_i18n_filter'] = filter_ return HttpResponseRedirect(reverse('rosetta-home')) rosetta_i18n_filter = request.session.get('rosetta_i18n_filter', 'all') if '_next' in request.POST: rx = re.compile(r'^m_([0-9a-f]+)') rx_plural = re.compile(r'^m_([0-9a-f]+)_([0-9]+)') file_change = False for key, value in request.POST.items(): md5hash = None plural_id = None if rx_plural.match(key): md5hash = str(rx_plural.match(key).groups()[0]) # polib parses .po files into unicode strings, but # doesn't bother to convert plural indexes to int, # so we need unicode here. plural_id = unicode(rx_plural.match(key).groups()[1]) elif rx.match(key): md5hash = str(rx.match(key).groups()[0]) if md5hash is not None: entry = rosetta_i18n_pofile.find(md5hash, 'md5hash') # If someone did a makemessage, some entries might # have been removed, so we need to check. if entry: old_msgstr = entry.msgstr if plural_id is not None: plural_string = fix_nls(entry.msgstr_plural[plural_id], value) entry.msgstr_plural[plural_id] = plural_string else: entry.msgstr = fix_nls(entry.msgid, value) is_fuzzy = bool(request.POST.get('f_%s' % md5hash, False)) old_fuzzy = 'fuzzy' in entry.flags if old_fuzzy and not is_fuzzy: entry.flags.remove('fuzzy') elif not old_fuzzy and is_fuzzy: entry.flags.append('fuzzy') file_change = True if old_msgstr != value or old_fuzzy != is_fuzzy: entry_changed.send(sender=entry, user=request.user, old_msgstr=old_msgstr, old_fuzzy=old_fuzzy, pofile=rosetta_i18n_fn, language_code=rosetta_i18n_lang_code, ) else: request.session['rosetta_last_save_error'] = True if file_change and rosetta_i18n_write: try: # Provide defaults in case authorization is not required. request.user.first_name = getattr(request.user, 'first_name', 'Anonymous') request.user.last_name = getattr(request.user, 'last_name', 'User') request.user.email = getattr(request.user, 'email', 'anonymous@user.tld') rosetta_i18n_pofile.metadata['Last-Translator'] = unicodedata.normalize('NFKD', u"%s %s <%s>" % (request.user.first_name, request.user.last_name, request.user.email)).encode('ascii', 'ignore') rosetta_i18n_pofile.metadata['X-Translated-Using'] = u"django-rosetta %s" % rosetta.get_version(False) rosetta_i18n_pofile.metadata['PO-Revision-Date'] = datetime.datetime.now().strftime('%Y-%m-%d %H:%M%z') except UnicodeDecodeError: pass try: rosetta_i18n_pofile.save() rosetta_i18n_pofile.save_as_mofile(rosetta_i18n_fn.replace('.po', '.mo')) post_save.send(sender=None, language_code=rosetta_i18n_lang_code, request=request) # Try auto-reloading via the WSGI daemon mode reload mechanism if rosetta_settings.WSGI_AUTO_RELOAD and \ 'mod_wsgi.process_group' in request.environ and \ request.environ.get('mod_wsgi.process_group', None) and \ 'SCRIPT_FILENAME' in request.environ and \ int(request.environ.get('mod_wsgi.script_reloading', '0')): try: os.utime(request.environ.get('SCRIPT_FILENAME'), None) except OSError: pass # Try auto-reloading via uwsgi daemon reload mechanism if rosetta_settings.UWSGI_AUTO_RELOAD: try: import uwsgi # pretty easy right? uwsgi.reload() except: # we may not be running under uwsgi :P pass except: request.session['rosetta_i18n_write'] = False request.session['rosetta_i18n_pofile'] = rosetta_i18n_pofile # Retain query arguments query_arg = '' if 'query' in request.REQUEST: query_arg = '?query=%s' % request.REQUEST.get('query') if 'page' in request.GET: if query_arg: query_arg = query_arg + '&' else: query_arg = '?' query_arg = query_arg + 'page=%d' % int(request.GET.get('page')) return HttpResponseRedirect(reverse('rosetta-home') + iri_to_uri(query_arg)) rosetta_i18n_lang_name = _(request.session.get('rosetta_i18n_lang_name')) rosetta_i18n_lang_code = request.session.get('rosetta_i18n_lang_code') if 'query' in request.REQUEST and request.REQUEST.get('query', '').strip(): query = request.REQUEST.get('query').strip() rx = re.compile(re.escape(query), re.IGNORECASE) paginator = Paginator([e for e in rosetta_i18n_pofile if not e.obsolete and rx.search(smart_unicode(e.msgstr) + smart_unicode(e.msgid) + u''.join([o[0] for o in e.occurrences]))], rosetta_settings.MESSAGES_PER_PAGE) else: if rosetta_i18n_filter == 'untranslated': paginator = Paginator(rosetta_i18n_pofile.untranslated_entries(), rosetta_settings.MESSAGES_PER_PAGE) elif rosetta_i18n_filter == 'translated': paginator = Paginator(rosetta_i18n_pofile.translated_entries(), rosetta_settings.MESSAGES_PER_PAGE) elif rosetta_i18n_filter == 'fuzzy': paginator = Paginator([e for e in rosetta_i18n_pofile.fuzzy_entries() if not e.obsolete], rosetta_settings.MESSAGES_PER_PAGE) else: paginator = Paginator([e for e in rosetta_i18n_pofile if not e.obsolete], rosetta_settings.MESSAGES_PER_PAGE) if 'page' in request.GET and int(request.GET.get('page')) <= paginator.num_pages and int(request.GET.get('page')) > 0: page = int(request.GET.get('page')) else: page = 1 messages = paginator.page(page).object_list if rosetta_settings.MAIN_LANGUAGE and rosetta_settings.MAIN_LANGUAGE != rosetta_i18n_lang_code: main_language = None for language in settings.LANGUAGES: if language[0] == rosetta_settings.MAIN_LANGUAGE: main_language = _(language[1]) break fl = ("/%s/" % rosetta_settings.MAIN_LANGUAGE).join(rosetta_i18n_fn.split("/%s/" % rosetta_i18n_lang_code)) po = pofile(fl) main_messages = [] for message in messages: message.main_lang = po.find(message.msgid).msgstr needs_pagination = paginator.num_pages > 1 if needs_pagination: if paginator.num_pages >= 10: page_range = pagination_range(1, paginator.num_pages, page) else: page_range = range(1, 1 + paginator.num_pages) ADMIN_MEDIA_PREFIX = settings.STATIC_URL ENABLE_TRANSLATION_SUGGESTIONS = rosetta_settings.BING_APP_ID and rosetta_settings.ENABLE_TRANSLATION_SUGGESTIONS BING_APP_ID = rosetta_settings.BING_APP_ID MESSAGES_SOURCE_LANGUAGE_NAME = rosetta_settings.MESSAGES_SOURCE_LANGUAGE_NAME MESSAGES_SOURCE_LANGUAGE_CODE = rosetta_settings.MESSAGES_SOURCE_LANGUAGE_CODE if 'rosetta_last_save_error' in request.session: del(request.session['rosetta_last_save_error']) rosetta_last_save_error = True return render_to_response('rosetta/pofile.html', locals(), context_instance=RequestContext(request)) else: return list_languages(request) home = never_cache(home) home = user_passes_test(lambda user: can_translate(user), settings.LOGIN_URL)(home) download_file = never_cache(download_file) download_file = user_passes_test(lambda user: can_translate(user), settings.LOGIN_URL)(download_file) def list_languages(request): """ Lists the languages for the current project, the gettext catalog files that can be translated and their translation progress """ languages = [] if 'filter' in request.GET: if request.GET.get('filter') in ('project', 'third-party', 'django', 'all'): filter_ = request.GET.get('filter') request.session['rosetta_i18n_catalog_filter'] = filter_ return HttpResponseRedirect(reverse('rosetta-pick-file')) rosetta_i18n_catalog_filter = request.session.get('rosetta_i18n_catalog_filter', 'project') third_party_apps = rosetta_i18n_catalog_filter in ('all', 'third-party') django_apps = rosetta_i18n_catalog_filter in ('all', 'django') project_apps = rosetta_i18n_catalog_filter in ('all', 'project') has_pos = False for language in settings.LANGUAGES: pos = find_pos(language[0], project_apps=project_apps, django_apps=django_apps, third_party_apps=third_party_apps) has_pos = has_pos or len(pos) languages.append( (language[0], _(language[1]), [(get_app_name(l), os.path.realpath(l), pofile(l)) for l in pos], ) ) ADMIN_MEDIA_PREFIX = settings.STATIC_URL version = rosetta.get_version(True) return render_to_response('rosetta/languages.html', locals(), context_instance=RequestContext(request)) list_languages = never_cache(list_languages) list_languages = user_passes_test(lambda user: can_translate(user), settings.LOGIN_URL)(list_languages) def lang_sel(request, langid, idx): """ Selects a file to be translated """ if langid not in [l[0] for l in settings.LANGUAGES]: raise Http404 else: rosetta_i18n_catalog_filter = request.session.get('rosetta_i18n_catalog_filter', 'project') third_party_apps = rosetta_i18n_catalog_filter in ('all', 'third-party') django_apps = rosetta_i18n_catalog_filter in ('all', 'django') project_apps = rosetta_i18n_catalog_filter in ('all', 'project') file_ = find_pos(langid, project_apps=project_apps, django_apps=django_apps, third_party_apps=third_party_apps)[int(idx)] request.session['rosetta_i18n_lang_code'] = langid request.session['rosetta_i18n_lang_name'] = unicode([l[1] for l in settings.LANGUAGES if l[0] == langid][0]) request.session['rosetta_i18n_fn'] = file_ po = pofile(file_) for entry in po: entry.md5hash = hashlib.md5(entry.msgid.encode("utf8") + entry.msgstr.encode("utf8")).hexdigest() request.session['rosetta_i18n_pofile'] = po try: os.utime(file_, None) request.session['rosetta_i18n_write'] = True except OSError: request.session['rosetta_i18n_write'] = False return HttpResponseRedirect(reverse('rosetta-home')) lang_sel = never_cache(lang_sel) lang_sel = user_passes_test(lambda user: can_translate(user), settings.LOGIN_URL)(lang_sel)
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# to run this, add code from experiments_HSCC2021.py
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# -*- coding: utf-8 -*- # # Copyright 2014 Red Hat, Inc. # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. """ DRAC Management Driver """ from oslo.utils import excutils from oslo.utils import importutils from ironic.common import boot_devices from ironic.common import exception from ironic.common.i18n import _ from ironic.common.i18n import _LE from ironic.drivers import base from ironic.drivers.modules.drac import common as drac_common from ironic.drivers.modules.drac import resource_uris from ironic.openstack.common import log as logging pywsman = importutils.try_import('pywsman') LOG = logging.getLogger(__name__) _BOOT_DEVICES_MAP = { boot_devices.DISK: 'HardDisk', boot_devices.PXE: 'NIC', boot_devices.CDROM: 'Optical', } # IsNext constants PERSISTENT = '1' """ Is the next boot config the system will use. """ NOT_NEXT = '2' """ Is not the next boot config the system will use. """ ONE_TIME_BOOT = '3' """ Is the next boot config the system will use, one time boot only. """ def _get_next_boot_mode(node): """Get the next boot mode. To see a list of supported boot modes see: http://goo.gl/aEsvUH (Section 7.2) :param node: an ironic node object. :raises: DracClientError on an error from pywsman library. :returns: a dictionary containing: :instance_id: the instance id of the boot device. :is_next: whether it's the next device to boot or not. One of PERSISTENT, NOT_NEXT, ONE_TIME_BOOT constants. """ client = drac_common.get_wsman_client(node) options = pywsman.ClientOptions() filter_query = ('select * from DCIM_BootConfigSetting where IsNext=%s ' 'or IsNext=%s' % (PERSISTENT, ONE_TIME_BOOT)) try: doc = client.wsman_enumerate(resource_uris.DCIM_BootConfigSetting, options, filter_query=filter_query) except exception.DracClientError as exc: with excutils.save_and_reraise_exception(): LOG.error(_LE('DRAC driver failed to get next boot mode for ' 'node %(node_uuid)s. Reason: %(error)s.'), {'node_uuid': node.uuid, 'error': exc}) items = drac_common.find_xml(doc, 'DCIM_BootConfigSetting', resource_uris.DCIM_BootConfigSetting, find_all=True) # This list will have 2 items maximum, one for the persistent element # and another one for the OneTime if set boot_mode = None for i in items: instance_id = drac_common.find_xml(i, 'InstanceID', resource_uris.DCIM_BootConfigSetting).text is_next = drac_common.find_xml(i, 'IsNext', resource_uris.DCIM_BootConfigSetting).text boot_mode = {'instance_id': instance_id, 'is_next': is_next} # If OneTime is set we should return it, because that's # where the next boot device is if is_next == ONE_TIME_BOOT: break return boot_mode def _create_config_job(node): """Create a configuration job. This method is used to apply the pending values created by set_boot_device(). :param node: an ironic node object. :raises: DracClientError on an error from pywsman library. :raises: DracConfigJobCreationError on an error when creating the job. """ client = drac_common.get_wsman_client(node) options = pywsman.ClientOptions() options.add_selector('CreationClassName', 'DCIM_BIOSService') options.add_selector('Name', 'DCIM:BIOSService') options.add_selector('SystemCreationClassName', 'DCIM_ComputerSystem') options.add_selector('SystemName', 'DCIM:ComputerSystem') options.add_property('Target', 'BIOS.Setup.1-1') options.add_property('ScheduledStartTime', 'TIME_NOW') doc = client.wsman_invoke(resource_uris.DCIM_BIOSService, options, 'CreateTargetedConfigJob') return_value = drac_common.find_xml(doc, 'ReturnValue', resource_uris.DCIM_BIOSService).text # NOTE(lucasagomes): Possible return values are: RET_ERROR for error # or RET_CREATED job created (but changes will be # applied after the reboot) # Boot Management Documentation: http://goo.gl/aEsvUH (Section 8.4) if return_value == drac_common.RET_ERROR: error_message = drac_common.find_xml(doc, 'Message', resource_uris.DCIM_BIOSService).text raise exception.DracConfigJobCreationError(error=error_message) def _check_for_config_job(node): """Check if a configuration job is already created. :param node: an ironic node object. :raises: DracClientError on an error from pywsman library. :raises: DracConfigJobCreationError if the job is already created. """ client = drac_common.get_wsman_client(node) options = pywsman.ClientOptions() try: doc = client.wsman_enumerate(resource_uris.DCIM_LifecycleJob, options) except exception.DracClientError as exc: with excutils.save_and_reraise_exception(): LOG.error(_LE('DRAC driver failed to list the configuration jobs ' 'for node %(node_uuid)s. Reason: %(error)s.'), {'node_uuid': node.uuid, 'error': exc}) items = drac_common.find_xml(doc, 'DCIM_LifecycleJob', resource_uris.DCIM_LifecycleJob, find_all=True) for i in items: name = drac_common.find_xml(i, 'Name', resource_uris.DCIM_LifecycleJob) if 'BIOS.Setup.1-1' not in name.text: continue job_status = drac_common.find_xml(i, 'JobStatus', resource_uris.DCIM_LifecycleJob).text # If job is already completed or failed we can # create another one. # Job Control Documentation: http://goo.gl/o1dDD3 (Section 7.2.3.2) if job_status.lower() not in ('completed', 'failed'): job_id = drac_common.find_xml(i, 'InstanceID', resource_uris.DCIM_LifecycleJob).text reason = (_('Another job with ID "%s" is already created ' 'to configure the BIOS. Wait until existing job ' 'is completed or is cancelled') % job_id) raise exception.DracConfigJobCreationError(error=reason)
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import numpy as np import matplotlib.pyplot as plt #grid number on half space (without the origin) N=150 #total grid number = 2*N + 1 (with origin) N_g=2*N+1 #finite barrier potential value = 300 (meV) potential_value=300 #building potential: # #Hamiltonian matrix: V=potential(potential_value) H=Hamiltonian(V) #sort the eigenvalue and get the corresponding eigenvector eigenvalue,eigenvector=np.linalg.eig(H) idx=np.argsort(eigenvalue) eigenvalue=eigenvalue[idx] eigenvector=eigenvector[:,idx] #visualize fig=plt.figure(figsize=(18,6)) ax1=fig.add_subplot(131) x=np.linspace(0,10,11) ax1.plot(x,eigenvalue[0:11],'r.',label='numerical') ax1.set_xlabel('n') ax1.set_ylabel('$E_n (meV)$') ax1.set_title('eigen energies') ax1.grid(True) ax1.legend() ax2=fig.add_subplot(132) x=np.linspace(-5,5,301) #x/lamda_0 x=x/(np.sqrt(2)*10**(10-9)/np.pi) y1=eigenvector[:,0] y2=eigenvector[:,1] y3=eigenvector[:,2] y4=eigenvector[:,3] y5=eigenvector[:,4] ax2.plot(x,(y1),label='$_{n=0}(x)$') ax2.plot(x,(y2),label='$_{n=1}(x)$') ax2.plot(x,(y3),label='$_{n=2}(x)$') ax2.set_xlabel('position ($x/_0$) ') ax2.set_ylabel('wavefunction') ax2.set_title('wave function in different eigen state') ax2.legend() ax2.grid(True) ax3=fig.add_subplot(133) ax3.plot(x,(y1**2),label='$^2_{n=0}(x)$') ax3.plot(x,(y2**2),label='$^2_{n=1}(x)$') ax3.plot(x,(y3**2),label='$^2_{n=2}(x)$') ax3.set_xlabel('position ($x/_0$) ') ax3.set_ylabel('square wavefunction') ax3.set_title('probability distribution in finite barrier well') ax3.grid(True) ax3.legend() plt.show()
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from .BaseSVDD import BaseSVDD
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import setuptools import glob import os required = [ "requests", "pandas", "arrow", "socketIO-client-nexus" ] setuptools.setup(name='iex-api-python', version="0.0.5", description='Fetch data from the IEX API', long_description=open('README.md').read().strip(), author='Daniel E. Cook', author_email='danielecook@gmail.com', url='http://www.github.com/danielecook/iex-api-python', packages=['iex'], install_requires=required, keywords=['finance', 'stock', 'market', 'market-data', 'IEX', 'API'], license='MIT License', zip_safe=False)
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import os import click import logging from pathlib import Path from dotenv import find_dotenv, load_dotenv from keras.callbacks import ModelCheckpoint, EarlyStopping import src.utils.utils as ut import src.utils.model_utils as mu import src.models.model as md import src.models.data_generator as dg import src.data.dataframe as dat if __name__ == '__main__': log_fmt = '%(asctime)s - %(name)s - %(levelname)s - %(message)s' logging.basicConfig(level=logging.INFO, format=log_fmt) project_dir = Path(__file__).resolve().parents[2] load_dotenv(find_dotenv()) main()
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""" MIT License Copyright (c) 2020 Shantanu Ghosh Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import numpy from matplotlib import pyplot import pandas as pd import os from Propensity_socre_network import Propensity_socre_network from Utils import Utils from dataloader import DataLoader csv_path = "Dataset/ihdp_sample.csv" # 139 treated # 747 - 139 = 608 control # 747 total split_size = 0.8 device = Utils.get_device() dL = DataLoader() np_covariates_X_train, np_covariates_X_test, np_covariates_Y_train, np_covariates_Y_test = \ dL.preprocess_data_from_csv(csv_path, split_size) ps_train_set = dL.convert_to_tensor(np_covariates_X_train, np_covariates_Y_train) train_parameters_NN = { "epochs": 75, "lr": 0.001, "batch_size": 32, "shuffle": True, "train_set": ps_train_set, "model_save_path": "./Propensity_Model/NN_PS_model_iter_id_" + str(1) + "_epoch_{0}_lr_{1}.pth" } # ps using NN ps_net_NN = Propensity_socre_network() print("############### Propensity Score neural net Training ###############") ps_net_NN.train(train_parameters_NN, device, phase="train") # eval eval_parameters_NN = { "eval_set": ps_train_set, "model_path": "./Propensity_Model/NN_PS_model_iter_id_{0}_epoch_75_lr_0.001.pth" .format(1) } ps_score_list_NN = ps_net_NN.eval_return_complete_list(eval_parameters_NN, device, phase="eval") treated_ps_list = [d["prop_score"] for d in ps_score_list_NN if d['treatment'] == 1] control_ps_list = [d["prop_score"] for d in ps_score_list_NN if d['treatment'] == 0] for ps_dict in treated_ps_list: print(ps_dict) print("--------------") for ps_dict in control_ps_list: print(ps_dict) print("treated: " + str(len(treated_ps_list))) print("control: " + str(len(control_ps_list))) print("total: " + str(len(treated_ps_list) + len(control_ps_list))) bins1 = numpy.linspace(0, 1, 100) bins2 = numpy.linspace(0, 0.2, 100) bins3 = numpy.linspace(0.2, 0.5, 100) bins4 = numpy.linspace(0.5, 1, 100) draw(treated_ps_list, control_ps_list, bins1) draw(treated_ps_list, control_ps_list, bins2) draw(treated_ps_list, control_ps_list, bins3) draw(treated_ps_list, control_ps_list, bins4)
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# Copyright (c) 2016-2019. Mount Sinai School of Medicine # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import print_function, division, absolute_import import logging from Bio.Seq import reverse_complement from pyensembl import Transcript from ..common import groupby_field from .transcript_helpers import interval_offset_on_transcript from .effect_helpers import changes_exonic_splice_site from .effect_collection import EffectCollection from .effect_prediction_coding import predict_variant_coding_effect_on_transcript from .effect_classes import ( Failure, Intergenic, Intragenic, NoncodingTranscript, IncompleteTranscript, FivePrimeUTR, ThreePrimeUTR, Intronic, IntronicSpliceSite, SpliceAcceptor, SpliceDonor, StartLoss, ExonLoss, ExonicSpliceSite, ) logger = logging.getLogger(__name__) def predict_variant_effects(variant, raise_on_error=False): """Determine the effects of a variant on any transcripts it overlaps. Returns an EffectCollection object. Parameters ---------- variant : Variant raise_on_error : bool Raise an exception if we encounter an error while trying to determine the effect of this variant on a transcript, or simply log the error and continue. """ # if this variant isn't overlapping any genes, return a # Intergenic effect # TODO: look for nearby genes and mark those as Upstream and Downstream # effects try: gene_ids = variant.gene_ids transcripts = variant.transcripts except: if raise_on_error: raise else: return [] if len(gene_ids) == 0: effects = [Intergenic(variant)] else: # list of all MutationEffects for all genes & transcripts effects = [] # group transcripts by their gene ID transcripts_grouped_by_gene = \ groupby_field(transcripts, 'gene_id') # want effects in the list grouped by the gene they come from for gene_id in sorted(gene_ids): if gene_id not in transcripts_grouped_by_gene: # intragenic variant overlaps a gene but not any transcripts gene = variant.genome.gene_by_id(gene_id) effects.append(Intragenic(variant, gene)) else: # gene ID has transcripts overlapped by this variant for transcript in transcripts_grouped_by_gene[gene_id]: if raise_on_error: effect = predict_variant_effect_on_transcript( variant=variant, transcript=transcript) else: effect = predict_variant_effect_on_transcript_or_failure( variant=variant, transcript=transcript) effects.append(effect) return EffectCollection(effects) def predict_variant_effect_on_transcript_or_failure(variant, transcript): """ Try predicting the effect of a variant on a particular transcript but suppress raised exceptions by converting them into `Failure` effect values. """ try: return predict_variant_effect_on_transcript( variant=variant, transcript=transcript) except (AssertionError, ValueError) as error: logger.warn( "Encountered error annotating %s for %s: %s", variant, transcript, error) return Failure(variant, transcript) def predict_variant_effect_on_transcript(variant, transcript): """Return the transcript effect (such as FrameShift) that results from applying this genomic variant to a particular transcript. Parameters ---------- transcript : Transcript Transcript we're going to apply mutation to. """ if transcript.__class__ is not Transcript: raise TypeError( "Expected %s : %s to have type Transcript" % ( transcript, type(transcript))) # check for non-coding transcripts first, since # every non-coding transcript is "incomplete". if not transcript.is_protein_coding: return NoncodingTranscript(variant, transcript) if not transcript.complete: return IncompleteTranscript(variant, transcript) # since we're using inclusive base-1 coordinates, # checking for overlap requires special logic for insertions is_insertion = variant.is_insertion # determine if any exons are deleted, and if not, # what is the closest exon and how far is this variant # from that exon (overlapping the exon = 0 distance) completely_lost_exons = [] # list of which (exon #, Exon) pairs this mutation overlaps overlapping_exon_numbers_and_exons = [] distance_to_nearest_exon = float("inf") start_in_exon = False end_in_exon = False nearest_exon = None variant_start = variant.trimmed_base1_start variant_end = variant.trimmed_base1_end for i, exon in enumerate(transcript.exons): if variant_start <= exon.start and variant_end >= exon.end: completely_lost_exons.append(exon) if is_insertion and exon.strand == "+" and variant_end == exon.end: # insertions after an exon don't overlap the exon distance = 1 elif is_insertion and exon.strand == "-" and variant_start == exon.start: distance = 1 else: distance = exon.distance_to_interval(variant_start, variant_end) if distance == 0: overlapping_exon_numbers_and_exons.append((i + 1, exon)) # start is contained in current exon if exon.start <= variant_start <= exon.end: start_in_exon = True # end is contained in current exon if exon.end >= variant_end >= exon.start: end_in_exon = True elif distance < distance_to_nearest_exon: distance_to_nearest_exon = distance nearest_exon = exon if len(overlapping_exon_numbers_and_exons) == 0: intronic_effect_class = choose_intronic_effect_class( variant=variant, nearest_exon=nearest_exon, distance_to_exon=distance_to_nearest_exon) return intronic_effect_class( variant=variant, transcript=transcript, nearest_exon=nearest_exon, distance_to_exon=distance_to_nearest_exon) elif len(completely_lost_exons) > 0 or ( len(overlapping_exon_numbers_and_exons) > 1): # if spanning multiple exons, or completely deleted an exon # then consider that an ExonLoss mutation exons = [exon for (_, exon) in overlapping_exon_numbers_and_exons] return ExonLoss(variant, transcript, exons) assert len(overlapping_exon_numbers_and_exons) == 1 exon_number, exon = overlapping_exon_numbers_and_exons[0] exonic_effect_annotation = exonic_transcript_effect( variant, exon, exon_number, transcript) # simple case: both start and end are in the same if start_in_exon and end_in_exon: return exonic_effect_annotation elif isinstance(exonic_effect_annotation, ExonicSpliceSite): # if mutation bleeds over into intro but even just # the exonic portion got annotated as an exonic splice site # then return it return exonic_effect_annotation return ExonicSpliceSite( variant=variant, transcript=transcript, exon=exon, alternate_effect=exonic_effect_annotation) def choose_intronic_effect_class( variant, nearest_exon, distance_to_exon): """ Infer effect of variant which does not overlap any exon of the given transcript. """ assert distance_to_exon > 0, \ "Expected intronic effect to have distance_to_exon > 0, got %d" % ( distance_to_exon,) if nearest_exon.strand == "+": # if exon on positive strand start_before = variant.trimmed_base1_start < nearest_exon.start start_same = variant.trimmed_base1_start == nearest_exon.start before_exon = start_before or (variant.is_insertion and start_same) else: # if exon on negative strand end_after = variant.trimmed_base1_end > nearest_exon.end end_same = variant.trimmed_base1_end == nearest_exon.end before_exon = end_after or (variant.is_insertion and end_same) # distance cutoffs based on consensus splice sequences from # http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2947103/ # 5' splice site: MAG|GURAGU consensus # M is A or C; R is purine; | is the exon-intron boundary # 3' splice site: YAG|R if distance_to_exon <= 2: if before_exon: # 2 last nucleotides of intron before exon are the splice # acceptor site, typically "AG" return SpliceAcceptor else: # 2 first nucleotides of intron after exon are the splice donor # site, typically "GT" return SpliceDonor elif not before_exon and distance_to_exon <= 6: # variants in nucleotides 3-6 at start of intron aren't as certain # to cause problems as nucleotides 1-2 but still implicated in # alternative splicing return IntronicSpliceSite elif before_exon and distance_to_exon <= 3: # nucleotide -3 before exon is part of the 3' splicing # motif but allows for more degeneracy than the -2, -1 nucleotides return IntronicSpliceSite else: # intronic mutation unrelated to splicing return Intronic def exonic_transcript_effect(variant, exon, exon_number, transcript): """Effect of this variant on a Transcript, assuming we already know that this variant overlaps some exon of the transcript. Parameters ---------- variant : Variant exon : pyensembl.Exon Exon which this variant overlaps exon_number : int Index (starting from 1) of the given exon in the transcript's sequence of exons. transcript : pyensembl.Transcript """ genome_ref = variant.trimmed_ref genome_alt = variant.trimmed_alt variant_start = variant.trimmed_base1_start variant_end = variant.trimmed_base1_end # clip mutation to only affect the current exon if variant_start < exon.start: # if mutation starts before current exon then only look # at nucleotides which overlap the exon logger.info('Mutation in variant %s starts before exon %s', variant, exon) assert len(genome_ref) > 0, "Unexpected insertion into intron" n_skip_start = exon.start - variant_start genome_ref = genome_ref[n_skip_start:] genome_alt = genome_alt[n_skip_start:] genome_start = exon.start else: genome_start = variant_start if variant_end > exon.end: # if mutation goes past exon end then only look at nucleotides # which overlap the exon logger.info('Mutation in variant %s ends after exon %s', variant, exon) n_skip_end = variant_end - exon.end genome_ref = genome_ref[:-n_skip_end] genome_alt = genome_alt[:len(genome_ref)] genome_end = exon.end else: genome_end = variant_end transcript_offset = interval_offset_on_transcript( genome_start, genome_end, transcript) if transcript.on_backward_strand: cdna_ref = reverse_complement(genome_ref) cdna_alt = reverse_complement(genome_alt) else: cdna_ref = genome_ref cdna_alt = genome_alt n_ref = len(cdna_ref) expected_ref = str( transcript.sequence[transcript_offset:transcript_offset + n_ref]) if cdna_ref != expected_ref: raise ValueError( ("Found ref nucleotides '%s' in sequence" " of %s at offset %d (chromosome positions %d:%d)" " but variant %s has '%s'") % ( expected_ref, transcript, transcript_offset, genome_start, genome_end, variant, cdna_ref)) utr5_length = min(transcript.start_codon_spliced_offsets) # does the variant start inside the 5' UTR? if utr5_length > transcript_offset: # does the variant end after the 5' UTR, within the coding region? if utr5_length < transcript_offset + n_ref: # TODO: we *might* lose the Kozak sequence or the start codon # but without looking at the modified sequence how can we tell # for sure that this is a start-loss variant? return StartLoss(variant, transcript) else: # if variant contained within 5' UTR return FivePrimeUTR(variant, transcript) utr3_offset = max(transcript.stop_codon_spliced_offsets) + 1 if transcript_offset >= utr3_offset: return ThreePrimeUTR(variant, transcript) exon_start_offset = interval_offset_on_transcript( exon.start, exon.end, transcript) exon_end_offset = exon_start_offset + len(exon) - 1 # Further below we're going to try to predict exonic splice site # modifications, which will take this effect_annotation as their # alternative hypothesis for what happens if splicing doesn't change. # If the mutation doesn't affect an exonic splice site, then # we'll just return this effect. coding_effect_annotation = predict_variant_coding_effect_on_transcript( variant=variant, transcript=transcript, trimmed_cdna_ref=cdna_ref, trimmed_cdna_alt=cdna_alt, transcript_offset=transcript_offset) if changes_exonic_splice_site( transcript=transcript, transcript_ref=cdna_ref, transcript_alt=cdna_alt, transcript_offset=transcript_offset, exon_start_offset=exon_start_offset, exon_end_offset=exon_end_offset, exon_number=exon_number): return ExonicSpliceSite( variant=variant, transcript=transcript, exon=exon, alternate_effect=coding_effect_annotation) return coding_effect_annotation
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# OS-Level Imports import os import sys import multiprocessing from multiprocessing import cpu_count # Library Imports import tensorflow as tf from tensorflow.keras import mixed_precision from tensorflow.python.distribute.distribute_lib import Strategy # Internal Imports from Utils.enums import Environment, Accelerator # Global Configuration Variables environment = Environment.GoogleColab accelerator = Accelerator.GPU strategy = None cpu_no = multiprocessing.cpu_count() batch_size = 64 latent_dim = 100 epochs = 10 supervised_samples_ratio = 0.05 save_interval = 17 super_batches = 1 unsuper_batches = 1 prefetch_no = tf.data.AUTOTUNE eager_execution = True model_summary = False resume_training = False result_path = './results/' dataset_path = './dataset/'
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from power_audit import PowerAudit if __name__ == '__main__': main()
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from turbo.flux import Mutation, register, dispatch, register_dispatch import mutation_types
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import logging import os import io from fastapi import APIRouter, Depends, Header from fastapi.responses import FileResponse, StreamingResponse from fastapi import HTTPException, status import pyarrow as pa import pyarrow.parquet as pq from data_service.api.query_models import ( InputTimePeriodQuery, InputTimeQuery, InputFixedQuery ) from data_service.config import config from data_service.api.response_models import ErrorMessage from data_service.config.config import get_settings from data_service.config.dependencies import get_processor from data_service.core.processor import Processor from data_service.api.auth import authorize_user data_router = APIRouter() log = logging.getLogger(__name__)
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from utils import sanitize
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import json import argparse from argus.callbacks import MonitorCheckpoint, \ EarlyStopping, LoggingToFile, ReduceLROnPlateau from torch.utils.data import DataLoader from src.datasets import FreesoundDataset, FreesoundNoisyDataset, RandomDataset from src.datasets import get_corrected_noisy_data, FreesoundCorrectedNoisyDataset from src.mixers import RandomMixer, AddMixer, SigmoidConcatMixer, UseMixerWithProb from src.transforms import get_transforms from src.argus_models import FreesoundModel from src.utils import load_noisy_data, load_folds_data from src import config parser = argparse.ArgumentParser() parser.add_argument('--experiment', required=True, type=str) args = parser.parse_args() BATCH_SIZE = 128 CROP_SIZE = 256 DATASET_SIZE = 128 * 256 NOISY_PROB = 0.01 CORR_NOISY_PROB = 0.42 MIXER_PROB = 0.8 WRAP_PAD_PROB = 0.5 CORRECTIONS = True if config.kernel: NUM_WORKERS = 2 else: NUM_WORKERS = 8 SAVE_DIR = config.experiments_dir / args.experiment PARAMS = { 'nn_module': ('AuxSkipAttention', { 'num_classes': len(config.classes), 'base_size': 64, 'dropout': 0.4, 'ratio': 16, 'kernel_size': 7, 'last_filters': 8, 'last_fc': 4 }), 'loss': ('OnlyNoisyLSoftLoss', { 'beta': 0.7, 'noisy_weight': 0.5, 'curated_weight': 0.5 }), 'optimizer': ('Adam', {'lr': 0.0009}), 'device': 'cuda', 'aux': { 'weights': [1.0, 0.4, 0.2, 0.1] }, 'amp': { 'opt_level': 'O2', 'keep_batchnorm_fp32': True, 'loss_scale': "dynamic" } } if __name__ == "__main__": if not SAVE_DIR.exists(): SAVE_DIR.mkdir(parents=True, exist_ok=True) else: print(f"Folder {SAVE_DIR} already exists.") with open(SAVE_DIR / 'source.py', 'w') as outfile: outfile.write(open(__file__).read()) print("Model params", PARAMS) with open(SAVE_DIR / 'params.json', 'w') as outfile: json.dump(PARAMS, outfile) folds_data = load_folds_data(use_corrections=CORRECTIONS) noisy_data = load_noisy_data() corrected_noisy_data = get_corrected_noisy_data() for fold in config.folds: val_folds = [fold] train_folds = list(set(config.folds) - set(val_folds)) save_fold_dir = SAVE_DIR / f'fold_{fold}' print(f"Val folds: {val_folds}, Train folds: {train_folds}") print(f"Fold save dir {save_fold_dir}") train_fold(save_fold_dir, train_folds, val_folds, folds_data, noisy_data, corrected_noisy_data)
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#Day 1.3 Exercise!! #First way I thought to do it without help name = input("What is your name? ") print(len(name)) #Way I found to do it from searching google print(len(input("What is your name? ")))
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from typing import TypedDict from .utils.Classes.String import String from .utils.assert_string import assert_string from .utils.merge import merge default_options: _IsStrongPasswordOptions = { "min_length": 8, "min_uppercase": 1, "min_lowercase": 1, "min_numbers": 1, "min_symbols": 1, "return_score": False, "points_per_unique": 1, "points_per_repeat": 0.5, "points_for_containing_lower": 10, "points_for_containing_upper": 10, "points_for_containing_number": 10, "points_for_containing_symbol": 10, }
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#!/usr/bin/env python # -*- coding: utf-8 -*- from __future__ import unicode_literals # Python imports. import logging import datetime import calendar # Django imports. from django.db import transaction # Rest Framework imports. from rest_framework import serializers # Third Party Library imports # local imports. from boilerplate_app.models import User, Projects
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from __future__ import absolute_import, unicode_literals import warnings from wagtail.wagtailcore.blocks import * # noqa warnings.warn("wagtail.wagtailadmin.blocks has moved to wagtail.wagtailcore.blocks", UserWarning, stacklevel=2)
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import codecs from datetime import datetime, timedelta from optparse import make_option from os import path, unlink from django.conf import settings from django.core.management.base import BaseCommand, CommandError import commonware.log from olympia import amo from olympia.addons.models import Addon, Persona from olympia.stats.models import ThemeUpdateCount from . import get_date_from_file, save_stats_to_file log = commonware.log.getLogger('adi.themeupdatecount')
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import numpy as np import pickle import matplotlib.pyplot as plt import os import fnmatch folder = "GP/" ktype = "lin/" matrices=os.listdir(folder+ktype) for matrix in matrices: if fnmatch.fnmatch(matrix, '*_val_*'): with open(folder+ktype+matrix, "rb") as pickleFile: results = pickle.load(pickleFile) arrray = results[2] # Enable interactive mode plt.ion() # Draw the grid lines plt.grid(True) plt.plot(results[1],results[2],label=matrix) plt.xscale('symlog', linthreshx=20) plt.legend(loc='upper left') plt.show()
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#!/usr/bin/env python2.7 # coding=utf-8 import logging import traceback import time from FATERUI.common.camera.camera import Camera from . import CameraMindVision from FATERUI.common.camera.common_tools import * import cv2 # from aoi.common.infraredcontrol import infraredcontrol from time import sleep import datetime
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import pytest
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# This script allows to download a single file from a remote ZIP archive # without downloading the whole ZIP file itself. # The hosting server needs to support the HTTP range header for it to work import zipfile import requests import argparse if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('URL', type=str, help='URL to zip file, e.g. https://example.com/myfile.zip') parser.add_argument('FILE_PATH', type=str, help='Path of the desired file in the ZIP file, e.g. myfolder/mydocument.docx') parser.add_argument('OUTPUT_FILE', type=str, help='Local path to write the file to, e.g. /home/user/mydocument.docx') args = parser.parse_args() download_file(args.URL, args.FILE_PATH, args.OUTPUT_FILE)
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import Image import readMDA import h5py import os import numpy from mmpad_image import open_mmpad_tif import numpy as np import scipy as sp import sys #import libtiff from cxparams import CXParams as CXP
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""" Support for file notification. For more details about this platform, please refer to the documentation at https://home-assistant.io/components/notify.file/ """ import logging import os import homeassistant.util.dt as dt_util from homeassistant.components.notify import ( ATTR_TITLE, DOMAIN, BaseNotificationService) from homeassistant.helpers import validate_config _LOGGER = logging.getLogger(__name__) def get_service(hass, config): """Get the file notification service.""" if not validate_config({DOMAIN: config}, {DOMAIN: ['filename', 'timestamp']}, _LOGGER): return None filename = config['filename'] timestamp = config['timestamp'] return FileNotificationService(hass, filename, timestamp) # pylint: disable=too-few-public-methods
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""" Example 035: Scheduled sending and delayed routing """ from os import path from docusign_esign.client.api_exception import ApiException from flask import render_template, session, Blueprint, request from ..examples.eg035_scheduled_sending import Eg035ScheduledSendingController from ...docusign import authenticate from ...ds_config import DS_CONFIG from ...error_handlers import process_error from ...consts import pattern eg = "eg035" # reference (and url) for this example eg035 = Blueprint("eg035", __name__) def get_args(): """Get request and session arguments""" # More data validation would be a good idea here # Strip anything other than characters listed signer_email = pattern.sub("", request.form.get("signer_email")) signer_name = pattern.sub("", request.form.get("signer_name")) resume_date = request.form.get("resume_date") envelope_args = { "signer_email": signer_email, "signer_name": signer_name, "resume_date": resume_date, "status": "sent", } args = { "account_id": session["ds_account_id"], "base_path": session["ds_base_path"], "access_token": session["ds_access_token"], "envelope_args": envelope_args } return args
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#-- THIS LINE SHOULD BE THE FIRST LINE OF YOUR SUBMISSION! --# #-- THIS LINE SHOULD BE THE LAST LINE OF YOUR SUBMISSION! ---# ### DO NOT SUBMIT THE FOLLOWING LINES!!! THESE ARE FOR LOCAL TESTING ONLY! # ((10+24) - (3+4+3)) * 0.3 assert(tally([10,24], [3,4,3], 0.30) == 7.20) # if the result would be negative, 0 is returned instead assert(tally([10], [20], 0.1) == 0)
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#!/usr/bin/env python3 """ Given a set of dominos, construct a linear sequence For example, if the set of dominos is [ (0,0) (1,0), (1,1)] then a valid linear sequence of length four would be (0,0),(0,1),(1,1),(1,0) In this script we first create a set of dominos to sample from. Then every permutation of that set is tested to see whether the sequence is a valid linear sequence. If the sequence is invalid, a counter is incremented to record how long the sequence was. """ # http://www.domino-games.com/domino-rules/double-six.html import itertools ''' list_of_dominos = [ (0,0), (1,0), (2, 0), (3, 0), (4, 0), (5, 0), (6, 0), (1,1), (2, 1), (3, 1), (4, 1), (5, 1), (6, 1), (2, 2), (3, 2), (4, 2), (5, 2), (6, 2), (3, 3), (4, 3), (5, 3), (6, 3), (4, 4), (5, 4), (6, 4), (5, 5), (6, 5), (6, 6)] ''' list_of_dominos = [(0,0),(1,0),(2,0),(3,0), (1,1),(2,1),(3,1), (2,2),(3,2), (3,3)] print("number of unique dominos in this set is",len(list_of_dominos)) # 28! = 3*10^29 #print(list_of_dominos) broke_on={} for indx in range(11): broke_on[indx+1]=0 print("initialized data structure (nothing up my sleeve):",broke_on) for this_perm in itertools.permutations(list_of_dominos): if(this_perm[0][1] != this_perm[1][0]): #print("broke on first pair") broke_on[1] += 1 elif(this_perm[1][1] != this_perm[2][0]): #print("broke on second pair") broke_on[2] += 1 elif(this_perm[2][1] != this_perm[3][0]): broke_on[3] += 1 elif(this_perm[3][1] != this_perm[4][0]): broke_on[4] += 1 elif(this_perm[4][1] != this_perm[5][0]): broke_on[5] += 1 elif(this_perm[5][1] != this_perm[6][0]): broke_on[6] += 1 elif(this_perm[6][1] != this_perm[7][0]): broke_on[7] += 1 elif(this_perm[7][1] != this_perm[8][0]): broke_on[8] += 1 elif(this_perm[8][1] != this_perm[9][0]): broke_on[9] += 1 elif(this_perm[9][1] != this_perm[10][0]): broke_on[10] += 1 else: print("made it to another pair") print(this_perm) break print(broke_on)
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## Unit 4 Project - Two Player Game ## Gavin Weiss - Computer Programming II ## The Elder Scrolls X # A fan made 2 player game successor the The Elder Scrolls Series # Two players start off in an arena # Can choose starting items # Can choose classes ## Libraries import time # Self explanatory import random # Self explanatory import os # Used for Linux commands import os, platform # For Linux intro ## Functions ## Code def intro1(): # This is an intro for Linux sleep() os.system("figlet Elder Scrolls X") sleep() return def intro2(): # Intro for anything else sleep() print("\n\t Elder Scrolls X") sleep() return if platform.system() == "Linux": intro1() else: intro2() def CharCreation(): # Function to ask questions for class choosing sleep() print("=> What kind of class do you want?") sleep() print("> 1 - Knight") #sleep() print("> 2 - Thief") #sleep() print("> 3 - Lancer") sleep() return sleep() print("=> Player 1 : What is your name?") name1 = input("> ") # "name1" is Player 1's name sleep() print("=> Player 1,") CharCreation() CharCreationChoice1 = input("> ") if CharCreationChoice1 == ("1"): # Knight player1 = Player1(name1, 200, 150, 50, 200) if CharCreationChoice1 == ("2"): # Thief player1 = Player1(name1, 100, 200, 100, 50) if CharCreationChoice1 == ("3"): # Lancer player1 = Player1(name1, 100, 100, 100, 100) sleep() player1.Stats() # Prints the stats for Player 1 sleep() print("=> Player 2 : What is your name?") name2 = input("> ") # "name2" is Player 2's name CharCreation() CharCreationChoice2 = input("> ") if CharCreationChoice2 == ("1"): # Knight player2 = Player2(name2, 200, 150, 50, 200) if CharCreationChoice2 == ("2"): # Thief player2 = Player2(name2, 100, 200, 100, 50) if CharCreationChoice2 == ("3"): # Lancer player2 = Player2(name2, 100, 100, 100, 100) player2.Stats() # Prints Player 2's stats
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# Copyright 2014 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. import subprocess from catapult_base import cloud_storage from telemetry.core import platform from telemetry.util import image_util from telemetry.util import rgba_color HIGHLIGHT_ORANGE_FRAME = rgba_color.WEB_PAGE_TEST_ORANGE
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"""Proxy to handle account communication with Renault servers.""" from __future__ import annotations from collections.abc import Awaitable from datetime import timedelta import logging from typing import Callable, TypeVar from renault_api.kamereon.exceptions import ( AccessDeniedException, KamereonResponseException, NotSupportedException, ) from homeassistant.core import HomeAssistant from homeassistant.helpers.update_coordinator import DataUpdateCoordinator, UpdateFailed T = TypeVar("T")
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#Programa Principal soma(4,5)
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#!/usr/bin/env python3 # =================================================================================== # Copyright (C) 2019 Fraunhofer Gesellschaft. All rights reserved. # =================================================================================== # This Acumos software file is distributed by Fraunhofer Gesellschaft # 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 # # This file 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_END========================================================== """ Provides an example of Docker URI cli on-boarding """ import requests import os import json # properties of the model model_name = "my-model-1" dockerImageURI = "cicd.ai4eu-dev.eu:7444/myimages/onboardingtest:v3" #Docker image URI looks like: example.com:port/image-tag:version license_file = "./license-1.0.0.json" protobuf_file = "./model.proto" # setup parameters host = os.environ['ACUMOS_HOST'] # FQHN like aiexp-preprod.ai4europe.eu token = os.environ['ACUMOS_TOKEN'] # format is 'acumos_username:API_TOKEN' advanced_api = "https://" + host + ":443/onboarding-app/v2/advancedModel" files= {'license': ('license.json', open(license_file, 'rb'), 'application.json'), 'protobuf': ('model.proto', open(protobuf_file, 'rb'), 'text/plain')} headers = {"Accept": "application/json", "modelname": model_name, "Authorization": token, "dockerFileURL": dockerImageURI, 'isCreateMicroservice': 'false'} #send request response = requests.post(advanced_api, files=files, headers=headers) #check response if response.status_code == 201: body = json.loads(response.text) solution_id = body['result']['solutionId'] print("Docker uri is pushed successfully on {" + host + "}, response is: ", response.status_code, " - solutionId: ", solution_id) else: print("Docker uri is not pushed on {" + host + "}, response is: ", response.status_code)
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# -*- coding: utf-8 -*- # Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved. # This program is free software; you can redistribute it and/or modify # it under the terms of the MIT License. # This program 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 # MIT License for more details. """ResNetVariant for Detection.""" from zeus.common import ClassType, ClassFactory from zeus.modules.connections.connections import MultiOutputGetter
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#!/usr/bin/env python2 # -*- coding: utf-8 -*- """ Created on Fri Jan 20 08:40:22 2017 @author: fabio """ import ee import ee.mapclient ee.Initialize() collection = ee.ImageCollection('MODIS/MCD43A4_NDVI') lista = collection.toList(10) #print lista.getInfo() image = ee.Image('LC8_L1T/LC81910312016217LGN00') #print image.getInfo() bandNames = image.bandNames() print('Band Names: ', bandNames.getInfo()) b1scale = image.select('B1').projection().nominalScale() print('Band 1 scale: ', b1scale.getInfo()) b8scale = image.select('B8').projection().nominalScale() print('Band 8 scale: ', b8scale.getInfo()) ndvi = image.normalizedDifference(['B5', 'B4']) ee.mapclient.addToMap(ndvi, {'min' : -1, "max": 1}, "NDVI") ee.mapclient.centerMap(12.3536,41.7686,9)
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# Copyright 2019 The Bazel Authors. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import tempfile import unittest from private import helpers if __name__ == '__main__': unittest.main()
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from django.contrib import admin from .models import Contato, Venda, FormaPagamento admin.site.register(Contato) admin.site.register(Venda) admin.site.register(FormaPagamento)
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import os import re import urllib from datetime import datetime from pathlib import Path from typing import Dict, List, Tuple, Union from money.currency import Currency from money.money import Money from werkzeug.utils import secure_filename from pome import g from pome.models.encoder import PomeEncodable RECORDED_TX_FOLDER_NAME = os.path.join("transactions", "recorded") def total_amount(self, formatted=False) -> Union[Money, str]: to_return = Money("0", Currency(g.company.accounts_currency_code)) for line in self.lines: to_return += line.amount.amount() if not formatted: return to_return return to_return.format(g.company.locale) regex_date = re.compile("^\d{4}\-(0[1-9]|1[012])\-(0[1-9]|[12][0-9]|3[01])$") regex_ISO8601 = re.compile( "^(-?(?:[1-9][0-9]*)?[0-9]{4})-(1[0-2]|0[1-9])-(3[01]|0[1-9]|[12][0-9])T(2[0-3]|[01][0-9]):([0-5][0-9]):([0-5][0-9])(\.[0-9]+)?(Z|[+-](?:2[0-3]|[01][0-9]):[0-5][0-9])?$" )
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2.124473
474
from __future__ import unicode_literals from __future__ import print_function import moya from moya.compat import text_type from requests_oauthlib import OAuth1Session
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3.431373
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""" Cartesian genetic programming """ import operator as op import random import copy import math from settings import VERBOSE, N_COLS, LEVEL_BACK # function set def protected_div(a, b): if abs(b) < 1e-6: return a return a / b fs = [Function(op.add, 2), Function(op.sub, 2), Function(op.mul, 2), Function(protected_div, 2), Function(op.neg, 1), Function(math.cos, 1), Function(math.sin, 1), Function(math.tan, 1), Function(math.atan2, 2)] Individual.function_set = fs Individual.max_arity = max(f.arity for f in fs) def evolve(pop, mut_rate, mu, lambda_): """ Evolve the population *pop* using the mu + lambda evolutionary strategy :param pop: a list of individuals, whose size is mu + lambda. The first mu ones are previous parents. :param mut_rate: mutation rate :return: a new generation of individuals of the same size """ pop = sorted(pop, key=lambda ind: ind.fitness) # stable sorting parents = pop[-mu:] # generate lambda new children via mutation offspring = [] for _ in range(lambda_): parent = random.choice(parents) offspring.append(parent.mutate(mut_rate)) return parents + offspring def create_population(n): """ Create a random population composed of n individuals. """ return [Individual() for _ in range(n)]
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2.911447
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from historia.pops.logic.logic_base import LogicBase from historia.economy.enums.resource import Good
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3.1875
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import argparse import cv2 import numpy as np import os import _pickle as pickle from descriptors import HOG #from skimage.morphology import skeletonize # run image filtering and HOG feature extraction if __name__ == '__main__': # require image directory and name of descriptor to use parser = argparse.ArgumentParser(description='Extract image feature vectors using feature descriptors') parser.add_argument('-p', '--path', required=True, nargs='?', action='store', const='./images/', type=str, dest='im_path', help='The filepath of the image directory') parser.add_argument('-d', '--descriptor', required=True, choices=['hog'], nargs='?', action='store', const='hog', type=str, dest='desc_name', help='The name of the descriptor to use') args = vars(parser.parse_args()) im_path = args['im_path'] desc_name = args['desc_name'] main(im_path, desc_name)
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2.350333
451
import abc
[ 11748, 450, 66, 628, 198 ]
2.6
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from django.contrib import admin from .models import Placement_Company_Detail,Profile,StudentBlogModel,ResorcesModel admin.site.register(Placement_Company_Detail) admin.site.register(Profile) admin.site.register(StudentBlogModel) admin.site.register(ResorcesModel)
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import torch as t import torch_geometric.utils as utils def qw_score(graph): """ qw_score, :param graph: """ score = utils.degree(graph.edge_index[0]) return score.sort() def construct_node_tree(graph, node, trees, opt): """ K_level, m_ary :param graph: :param node: :param opt: """ m = opt.m K = opt.K tree = [node] now = 0 for i in range(K - 1): for j in range(m ** i): root = tree[now] tree += trees[root] now += 1 zero = t.zeros(graph.x[-1].shape) x = graph.x graph.x = t.cat([graph.x, zero[None, :]], dim=0) tree = graph.x[tree] graph.x = x return tree
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2.037791
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from typing import Optional, Any def test(actions: list[str], val: list[list[int]]): cache: Optional[LFUCache] = None result: list[Optional[Any]] = [] for i, v in zip(actions, val): if i == 'LFUCache': cache = LFUCache(v[0]) result.append(None) elif i == 'put': assert cache result.append((i, v, cache.put(v[0], v[1]))) elif i == 'get': assert cache result.append((i, v, cache.get(v[0]))) print(result) if __name__ == '__main__': actions = ["LFUCache","put","put","get","put","get","get","put","get","get","get"] values = [[2],[1,1],[2,2],[1],[3,3],[2],[3],[4,4],[1],[3],[4]] test(actions, values) # actions2 = ["LFUCache","put","put","get","get","get","put","put","get","get","get","get"] # values2 = [[3],[2,2],[1,1],[2],[1],[2],[3,3],[4,4],[3],[2],[1],[4]] # test(actions2, values2) # actions3 = ["LFUCache","put","put","put","put","put","get","put","get","get","put","get","put","put","put","get","put","get","get","get","get","put","put","get","get","get","put","put","get","put","get","put","get","get","get","put","put","put","get","put","get","get","put","put","get","put","put","put","put","get","put","put","get","put","put","get","put","put","put","put","put","get","put","put","get","put","get","get","get","put","get","get","put","put","put","put","get","put","put","put","put","get","get","get","put","put","put","get","put","put","put","get","put","put","put","get","get","get","put","put","put","put","get","put","put","put","put","put","put","put"] # values3 = [[10],[10,13],[3,17],[6,11],[10,5],[9,10],[13],[2,19],[2],[3],[5,25],[8],[9,22],[5,5],[1,30],[11],[9,12],[7],[5],[8],[9],[4,30],[9,3],[9],[10],[10],[6,14],[3,1],[3],[10,11],[8],[2,14],[1],[5],[4],[11,4],[12,24],[5,18],[13],[7,23],[8],[12],[3,27],[2,12],[5],[2,9],[13,4],[8,18],[1,7],[6],[9,29],[8,21],[5],[6,30],[1,12],[10],[4,15],[7,22],[11,26],[8,17],[9,29],[5],[3,4],[11,30],[12],[4,29],[3],[9],[6],[3,4],[1],[10],[3,29],[10,28],[1,20],[11,13],[3],[3,12],[3,8],[10,9],[3,26],[8],[7],[5],[13,17],[2,27],[11,15],[12],[9,19],[2,15],[3,16],[1],[12,17],[9,1],[6,19],[4],[5],[5],[8,1],[11,7],[5,2],[9,28],[1],[2,2],[7,4],[4,22],[7,24],[9,26],[13,28],[11,26]] # test(actions3, values3)
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2.210325
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#/* # * Copyright (C) 2017 - This file is part of libecc project # * # * Authors: # * Ryad BENADJILA <ryadbenadjila@gmail.com> # * Arnaud EBALARD <arnaud.ebalard@ssi.gouv.fr> # * Jean-Pierre FLORI <jean-pierre.flori@ssi.gouv.fr> # * # * Contributors: # * Nicolas VIVET <nicolas.vivet@ssi.gouv.fr> # * Karim KHALFALLAH <karim.khalfallah@ssi.gouv.fr> # * # * This software is licensed under a dual BSD and GPL v2 license. # * See LICENSE file at the root folder of the project. # */ import struct keccak_rc = [ 0x0000000000000001, 0x0000000000008082, 0x800000000000808A, 0x8000000080008000, 0x000000000000808B, 0x0000000080000001, 0x8000000080008081, 0x8000000000008009, 0x000000000000008A, 0x0000000000000088, 0x0000000080008009, 0x000000008000000A, 0x000000008000808B, 0x800000000000008B, 0x8000000000008089, 0x8000000000008003, 0x8000000000008002, 0x8000000000000080, 0x000000000000800A, 0x800000008000000A, 0x8000000080008081, 0x8000000000008080, 0x0000000080000001, 0x8000000080008008 ] keccak_rot = [ [ 0, 36, 3, 41, 18 ], [ 1, 44, 10, 45, 2 ], [ 62, 6, 43, 15, 61 ], [ 28, 55, 25, 21, 56 ], [ 27, 20, 39, 8, 14 ], ] # Keccak function # SHA-3 context class
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2.160804
597
import csv from pathlib import Path from datetime import datetime from lps.models import * from lps.schemas import * SEED_FOLDER_PATH = Path("db/seeds/")
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2.824561
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a = int(input()) b = int(input()) print(a*b//(GCD(a,b)))
[ 198, 64, 796, 493, 7, 15414, 28955, 198, 65, 796, 493, 7, 15414, 28955, 198, 4798, 7, 64, 9, 65, 1003, 7, 38, 8610, 7, 64, 11, 65, 22305, 198 ]
1.933333
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""" Build a derived collection with the maximum value from each 'group' defined in the source collection. """ __author__ = 'Dan Gunter <dkgunter@lbl.gov>' __date__ = '5/21/14' from matgendb.builders import core from matgendb.builders import util from matgendb.query_engine import QueryEngine _log = util.get_builder_log("incr")
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3.074766
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from __future__ import unicode_literals from dvc.output.ssh import OutputSSH from dvc.dependency.base import DependencyBase
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3.405405
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import torch import torch.nn as nn import optflow.compute_tvl1_energy as compute_tvl1_energy
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2.90625
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import numpy as np import time import cv2 import argparse import sys import os import glob import json from pathlib import Path if __name__ == "__main__": main()
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2.461538
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# -*- coding: utf-8 -*- """ Tencent is pleased to support the open source community by making PaaS (BlueKing PaaS Community Edition) available. Copyright (C) 2017-2021 THL A29 Limited, a Tencent company. All rights reserved. Licensed under the MIT License (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://opensource.org/licenses/MIT 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 sys from django.test import TestCase from django.utils.module_loading import import_string from pipeline.tests.mock import * # noqa from pipeline.tests.mock_settings import * # noqa
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import numpy as np def _check_mne(name): """Helper to check if h5py is installed""" try: import mne except ImportError: raise ImportError('Please install MNE-python to use %s.' % name) return mne def raw_to_mask(raw, ixs, events=None, tmin=None, tmax=None): """ A function to transform MNE data into pactools input signals. It select the one channel on which you to estimate PAC, or two channels for cross-channel PAC. It also returns a mask generator, that mask the data outside a given window around an event. The mask generator returns a number of masks equal to the number of events times the number of windows (i.e. the number of pairs (tmin, tmax)). Warning: events is stored in indices, tmin and tmax are stored in seconds. Parameters ---------- raw : an instance of Raw, containing data of shape (n_channels, n_times) The data used to calculate PAC ixs : int or couple of int The indices for the low/high frequency channels. If only one is given, the same channel is used for both low_sig and high_sig. events : array, shape (n_events, 3) | array, shape (n_events,) | None MNE events array. To be supplied if data is 2D and output should be split by events. In this case, `tmin` and `tmax` must be provided. If `ndim == 1`, it is assumed to be event indices, and all events will be grouped together. Otherwise, events will be grouped along the third dimension. tmin : float | list of floats, shape (n_windows, ) | None If `events` is not provided, it is the start time to use in `raw`. If `events` is provided, it is the time (in seconds) to include before each event index. If a list of floats is given, then PAC is calculated for each pair of `tmin` and `tmax`. Defaults to `min(raw.times)`. tmax : float | list of floats, shape (n_windows, ) | None If `events` is not provided, it is the stop time to use in `raw`. If `events` is provided, it is the time (in seconds) to include after each event index. If a list of floats is given, then PAC is calculated for each pair of `tmin` and `tmax`. Defaults to `max(raw.times)`. Attributes ---------- low_sig : array, shape (1, n_points) Input data for the phase signal high_sig : array or None, shape (1, n_points) Input data for the amplitude signal. If None, we use low_sig for both signals. mask : MaskIterator instance Object that behaves like a list of mask, without storing them all. The PAC will only be evaluated where the mask is False. Examples -------- >>> from pactools import raw_to_mask >>> low_sig, high_sig, mask = raw_to_mask(raw, ixs, events, tmin, tmax) >>> n_masks = len(mask) >>> for one_mask in mask: ... pass """ mne = _check_mne('raw_to_mask') if not isinstance(raw, mne.io.BaseRaw): raise ValueError('Must supply Raw as input') ixs = np.atleast_1d(ixs) fs = raw.info['sfreq'] data = raw[:][0] n_channels, n_points = data.shape low_sig = data[ixs[0]][None, :] if ixs.shape[0] > 1: high_sig = data[ixs[1]][None, :] else: high_sig = None mask = MaskIterator(events, tmin, tmax, n_points, fs) return low_sig, high_sig, mask
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2.693038
1,264
import collections from itertools import combinations from collections import Counter
[ 11748, 17268, 198, 6738, 340, 861, 10141, 1330, 17790, 198, 6738, 17268, 1330, 15034, 198 ]
5.733333
15
import random
[ 11748, 4738, 628 ]
5
3
import pymysql.cursors from ..mod_check import app
[ 11748, 279, 4948, 893, 13976, 13, 66, 1834, 669, 198, 6738, 11485, 4666, 62, 9122, 1330, 598, 628 ]
2.888889
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import time import board import busio from digitalio import DigitalInOut from adafruit_esp32spi import adafruit_esp32spi from adafruit_esp32spi import adafruit_esp32spi_wifimanager import neopixel # Import Philips Hue Bridge from adafruit_hue import Bridge # Get wifi details and more from a secrets.py file try: from secrets import secrets except ImportError: print("WiFi and API secrets are kept in secrets.py, please add them there!") raise # ESP32 SPI esp32_cs = DigitalInOut(board.ESP_CS) esp32_ready = DigitalInOut(board.ESP_BUSY) esp32_reset = DigitalInOut(board.ESP_RESET) spi = busio.SPI(board.SCK, board.MOSI, board.MISO) esp = adafruit_esp32spi.ESP_SPIcontrol(spi, esp32_cs, esp32_ready, esp32_reset) status_light = neopixel.NeoPixel(board.NEOPIXEL, 1, brightness=0.2) wifi = adafruit_esp32spi_wifimanager.ESPSPI_WiFiManager(esp, secrets, status_light) # Attempt to load bridge username and IP address from secrets.py try: username = secrets['hue_username'] bridge_ip = secrets['bridge_ip'] my_bridge = Bridge(wifi, bridge_ip, username) except: # Perform first-time bridge setup my_bridge = Bridge(wifi) ip = my_bridge.discover_bridge() username = my_bridge.register_username() print('ADD THESE VALUES TO SECRETS.PY: \ \n\t"bridge_ip":"{0}", \ \n\t"hue_username":"{1}"'.format(ip, username)) raise # Enumerate all lights on the bridge my_bridge.get_lights() # Turn on the light my_bridge.set_light(1, on=True) # RGB colors to Hue-Compatible HSL colors hsl_y = my_bridge.rgb_to_hsb([255, 255, 0]) hsl_b = my_bridge.rgb_to_hsb([0, 0, 255]) hsl_w = my_bridge.rgb_to_hsb([255, 255, 255]) hsl_colors = [hsl_y, hsl_b, hsl_w] # Set the light to Python colors! for color in hsl_colors: my_bridge.set_light(1, hue=int(color[0]), sat=int(color[1]), bri=int(color[2])) time.sleep(5) # Set a predefinedscene # my_bridge.set_group(1, scene='AB34EF5') # Turn off the light my_bridge.set_light(1, on=False)
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2.344944
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# # Copyright (c) 2013-2018 Joris Vink <joris@coders.se> # # Permission to use, copy, modify, and distribute this software for any # purpose with or without fee is hereby granted, provided that the above # copyright notice and this permission notice appear in all copies. # # THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES # WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF # MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR # ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES # WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN # ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF # OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. # import kore import socket # Setup the server object. server = EchoServer() # Create a task that will execute inside of Kore as a co-routine. kore.task_create(server.run())
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3.408602
279
# -*- coding:utf-8 -*- """ """ __date__ = "14/12/2017" __author__ = "zhaojm"
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1.925
40
import asyncio import logging import traceback import uuid from typing import Optional, Tuple, Any, Callable from pesto.ws.core.payload_parser import PayloadParser, PestoConfig from pesto.ws.core.pesto_feature import PestoFeatures from pesto.ws.core.utils import load_class, async_exec from pesto.ws.features.algorithm_wrapper import AlgorithmWrapper from pesto.ws.features.converter.image.image_roi import ImageROI, DummyImageROI from pesto.ws.features.payload_converter import PayloadConverter from pesto.ws.features.payload_debug import PayloadDebug from pesto.ws.features.response_serializer import ResponseSerializer from pesto.ws.features.schema_validation import SchemaValidation from pesto.ws.features.stateful_response import StatefulResponse from pesto.ws.features.stateless_response import StatelessResponse from pesto.ws.service.describe import DescribeService from pesto.ws.service.job_result import ResultType log = logging.getLogger(__name__)
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3.348432
287
# -*- coding: utf-8 -*- import logging import os import re import sys
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2.730769
26
import configparser import os import typing from sitri.providers.base import ConfigProvider
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4.086957
23
from typing import Any, Dict, List from xpanse.const import V2_PREFIX from xpanse.endpoint import ExEndpoint from xpanse.iterator import ExResultIterator
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3.25
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from bfio import BioReader import argparse, logging import numpy as np from pathlib import Path import filepattern, multiprocessing, utils from concurrent.futures import ThreadPoolExecutor COLORS = ['red', 'green', 'blue', 'yellow', 'magenta', 'cyan', 'gray'] def get_number(s): """ Check that s is number If s is a number, first attempt to convert it to an int. If integer conversion fails, attempt to convert it to a float. If float conversion fails, return None. Inputs: s - An input string or number Outputs: value - Either float, int or None """ try: return [int(si) for si in s.split('-')] except ValueError: try: return [float(si) for si in s.split('-')] except ValueError: return None def get_bounds(br,lower_bound,upper_bound): """ Calculate upper and lower pixel values for image rescaling This method calculates the upper and lower percentiles for a given image. The lower_bound and upper_bound must be floats in the range 0-1, where 0.01 indicates 1%. The values returned are pixel intensity values. Images are read in tiles to prevent images from being completely read into memory. This permits calculation of percentiles on images that are larger than memory. Args: br (bfio.BioReader): A BioReader object to access a tiled tiff lower_bound (float): Lower bound percentile, must be in 0.00-1.00 upper_bound (float): Upper bound percentile, must be in 0.00-1.00 Returns: [list]: List of upper and lower bound values in pixel intensity units. """ # TODO: Replace pixel buffer with histogram/fingerprint to handle # larger images and/or larger percentile values # Make sure the inputs are properly formatted assert isinstance(lower_bound,float) and isinstance(upper_bound,float) assert lower_bound >= 0 and lower_bound <= 1.0 assert upper_bound >= 0 and upper_bound <= 1.0 # Get the image size in pixels image_size = br.num_x() * br.num_y() # Get number of pixels needed to get percentile information upper_bound_size = int(image_size * (1-upper_bound)) lower_bound_size = int(image_size * lower_bound) # Create the pixel buffer dtype = br.read_metadata().image().Pixels.get_PixelType() upper_bound_vals = np.zeros((2*upper_bound_size,),dtype=dtype) lower_bound_vals = np.full((2*lower_bound_size,),np.iinfo(dtype).max,dtype=dtype) # Load image tiles and sort pixels for x in range(0,br.num_x(),1024): # Load the first tile tile = br.read_image(X=[x,min([x+1024,br.num_x()])],Z=[0,1]) # Sort the non-zero values tile_sorted = np.sort(tile[tile.nonzero()],axis=None) # Store the upper and lower bound pixel values temp = tile_sorted[-upper_bound_size:] upper_bound_vals[:temp.size] = temp temp = tile_sorted[:lower_bound_size] lower_bound_vals[-temp.size:] = temp # Resort the pixels upper_bound_vals = np.sort(upper_bound_vals,axis=None) lower_bound_vals = np.sort(lower_bound_vals,axis=None) return [lower_bound_vals[lower_bound_size],upper_bound_vals[-upper_bound_size]] if __name__=="__main__": # Initialize the logger logging.basicConfig(format='%(asctime)s - %(name)-8s - %(levelname)-8s - %(message)s', datefmt='%d-%b-%y %H:%M:%S') logger = logging.getLogger("main") logger.setLevel(logging.INFO) ''' Argument parsing ''' logger.info("Parsing arguments...") parser = argparse.ArgumentParser(prog='main', description='Builds a DeepZoom color pyramid.') # Input arguments parser.add_argument('--filePattern', dest='filePattern', type=str, help='Filename pattern used to separate data', required=True) parser.add_argument('--inpDir', dest='inpDir', type=str, help='Input image collection to be processed by this plugin', required=True) parser.add_argument('--layout', dest='layout', type=str, help='Color ordering (e.g. 1,11,,,,5,6)', required=True) parser.add_argument('--bounds', dest='bounds', type=str, help='Set bounds (should be float-float, int-int, or blank, e.g. 0.01-0.99,0-16000,,,,,)', required=False) # Output arguments parser.add_argument('--outDir', dest='outDir', type=str, help='Output pyramid path.', required=True) # Parse the arguments args = parser.parse_args() filePattern = args.filePattern logger.info('filePattern = {}'.format(filePattern)) inpDir = args.inpDir if (Path.is_dir(Path(args.inpDir).joinpath('images'))): # switch to images folder if present fpath = str(Path(args.inpDir).joinpath('images').absolute()) logger.info('inpDir = {}'.format(inpDir)) layout = args.layout logger.info('layout = {}'.format(layout)) bounds = args.bounds logger.info('bounds = {}'.format(bounds)) outDir = args.outDir logger.info('outDir = {}'.format(outDir)) outDir = Path(outDir) # Parse the layout layout = [None if l=='' else int(l) for l in layout.split(',')] if len(layout)>7: layout = layout[:7] # Parse the bounds if bounds != None: bounds = [[None] if l=='' else get_number(l) for l in bounds.split(',')] bounds = bounds[:len(layout)] else: bounds = [[None] for _ in layout] # Parse files fp = filepattern.FilePattern(inpDir,filePattern) count = 0 for files in fp.iterate(group_by='c'): outDirFrame = outDir.joinpath('{}_files'.format(count)) outDirFrame.mkdir() count += 1 bioreaders = [] threads = [] with ThreadPoolExecutor(max([multiprocessing.cpu_count()//2,2])) as executor: for i,l in enumerate(layout): if l == None: bioreaders.append(None) continue f_path = [f for f in files if f['c']==l] if len(f_path)==0: continue f_path = f_path[0]['file'] bioreaders.append(BioReader(f_path,max_workers=multiprocessing.cpu_count())) if layout[i] != None: if isinstance(bounds[i][0],float): logger.info('{}: Getting percentile bounds {}...'.format(Path(bioreaders[-1]._file_path).name, bounds[i])) threads.append(executor.submit(get_bounds,bioreaders[-1],bounds[i][0],bounds[i][1])) elif isinstance(bounds[i][0],int): bioreaders[-1].bounds = bounds[i] else: bioreaders[-1].bounds = [0,np.iinfo(bioreaders[-1].read_metadata().image().Pixels.get_PixelType()).max] for i in reversed(range(len(layout))): if isinstance(bounds[i][0],int): logger.info('Color {}: {} (rescaling to {})'.format(COLORS[i], Path(Path(bioreaders[i]._file_path).name).name, bioreaders[i].bounds)) continue if layout[i] == None: continue bioreaders[i].bounds = threads.pop().result() logger.info('Color {}: {} (rescaling to {})'.format(COLORS[i], Path(Path(bioreaders[i]._file_path).name).name, bioreaders[i].bounds)) for br in bioreaders: if br != None: br_meta = br file_info = utils.dzi_file(br_meta,outDirFrame,0) encoder = utils.DeepZoomChunkEncoder(file_info) file_writer = utils.DeepZoomWriter(outDirFrame) utils._get_higher_res(0,bioreaders,file_writer,encoder)
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2.127328
3,919
from kinetics.reaction_classes.reaction_base_class import Reaction
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3.882353
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from ctypes import * from migi.decorators import stdcall _native_message_box_w.intercept()
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2.852941
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from adapters.adapter_with_battery import AdapterWithBattery from devices.switch.selector_switch import SelectorSwitch
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4.033333
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# -*- coding: utf-8 -*- """ """ import scrapy from tennis_model.tennis_model_scraper.tennis_model_scraper import items if __name__ == '__main__': pass
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from aoc20211219a import *
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2.545455
11
import json import requests from .exceptions import ( RequestsError, RequestsTimeoutError, RPCError ) _default_endpoint = 'http://localhost:9500' _default_timeout = 30 def base_request(method, params=None, endpoint=_default_endpoint, timeout=_default_timeout) -> str: """ Basic RPC request Parameters --------- method: str RPC Method to call params: :obj:`list`, optional Parameters for the RPC method endpoint: :obj:`str`, optional Endpoint to send request to timeout: :obj:`int`, optional Timeout in seconds Returns ------- str Raw output from the request Raises ------ TypeError If params is not a list or None RequestsTimeoutError If request timed out RequestsError If other request error occured """ if params is None: params = [] elif not isinstance(params, list): raise TypeError(f'invalid type {params.__class__}') try: payload = { "id": "1", "jsonrpc": "2.0", "method": method, "params": params } headers = { 'Content-Type': 'application/json' } resp = requests.request('POST', endpoint, headers=headers, data=json.dumps(payload), timeout=timeout, allow_redirects=True) return resp.content except requests.exceptions.Timeout as err: raise RequestsTimeoutError(endpoint) from err except requests.exceptions.RequestException as err: raise RequestsError(endpoint) from err def rpc_request(method, params=None, endpoint=_default_endpoint, timeout=_default_timeout) -> dict: """ RPC request Parameters --------- method: str RPC Method to call params: :obj:`list`, optional Parameters for the RPC method endpoint: :obj:`str`, optional Endpoint to send request to timeout: :obj:`int`, optional Timeout in seconds Returns ------- dict Returns dictionary representation of RPC response Example format: { "jsonrpc": "2.0", "id": 1, "result": ... } Raises ------ RPCError If RPC response returned a blockchain error See Also -------- base_request """ raw_resp = base_request(method, params, endpoint, timeout) try: resp = json.loads(raw_resp) if 'error' in resp: raise RPCError(method, endpoint, str(resp['error'])) return resp except json.decoder.JSONDecodeError as err: raise RPCError(method, endpoint, raw_resp) from err # TODO: Add GET requests
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2.394231
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#!/usr/bin/env python # -*- coding: utf-8 -*- import time import socket import threading import rospy from publisher import * import cv2 import imagezmq import numpy as np from sensor_msgs.msg import Image from cv_bridge import CvBridge, CvBridgeError # setup socket to python3 video streamer # Helper class implementing an IO daemon thread for imgzmq recv # Receive from broadcast # There are 2 hostname styles; comment out the one you don't need hostname = "127.0.0.1" # Use to receive from localhost # hostname = "192.168.86.38" # Use to receive from other computer if __name__ == '__main__': try: # parser = argparse.ArgumentParser() # parser.add_argument('--gp', action="store_true", help="Option to publish gaze position (2D) data") # args = parser.parse_args(rospy.myargv()[1:]) ''' Initiate the Video Stream Subscription over Image ZMQ ''' imgzmq_port = 5555 hostname = "/tmp/tobiiVid"; imgzmq_port = 0 receiver = VideoStreamSubscriber(hostname, imgzmq_port) ''' Create publisher ''' # Default publish the 3D gaze position data vidpub = rospy.Publisher("tobii_video", Image, queue_size=10) bridge = CvBridge() rospy.init_node('tobii_image_sender', anonymous=True) while not rospy.is_shutdown(): # get from py3 sent_msg_string, frame = receiver.receive() image = cv2.imdecode(np.frombuffer(frame, dtype='uint8'), -1) image = np.frombuffer(frame, dtype='uint8') image = image.reshape(1080, 1920, 3) print(image.shape, sent_msg_string) # Parse sent message to convert to ros formats frametime, counter = parse_sent_msg(sent_msg_string) # publish to ROS im_ros = bridge.cv2_to_imgmsg(image, "bgr8") im_ros.header.stamp = rospy.Time.from_sec(frametime) im_ros.header.frame_id = str(counter) vidpub.publish(im_ros) except (rospy.ROSInterruptException, KeyboardInterrupt, SystemExit): sys.exit(0)
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2.324561
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import sys import numpy import numpy as np from snappy import Product from snappy import ProductData from snappy import ProductIO from snappy import ProductUtils from snappy import FlagCoding ############## import csv ###############MSVR from sklearn.svm import SVR from sklearn.preprocessing import StandardScaler from sklearn.pipeline import make_pipeline ######################## if len(sys.argv) != 2: print("usage: %s <file>" % sys.argv[0]) sys.exit(1) file = sys.argv[1] print("Reading...") product = ProductIO.readProduct(file) width = product.getSceneRasterWidth() height = product.getSceneRasterHeight() name = product.getName() description = product.getDescription() band_names = product.getBandNames() print("Product: %s, %s" % (name, description)) print("Raster size: %d x %d pixels" % (width, height)) print("Start time: " + str(product.getStartTime())) print("End time: " + str(product.getEndTime())) print("Bands: %s" % (list(band_names))) ##--------------------------------------------------------------------------------- with open('rice_LUT.csv','r') as dest_f: data_iter = csv.reader(dest_f, delimiter = ',', quotechar = '"') data = [data for data in data_iter] data_array = np.asarray(data, dtype = np.float32) VV = data_array[:,1] VH = data_array[:,2] PAI = data_array[:,0] X=np.column_stack((VV,VH)) Y = PAI #SVR training pipeline = make_pipeline(StandardScaler(), SVR(kernel='rbf', epsilon=0.105, C=250, gamma = 2.8), ) SVRmodel=pipeline.fit(X,Y) # Predictfor validation data valX = X; y_out = pipeline.predict(valX); ##--------------------------------------------------------------------------------- bandc11 = product.getBand('C11') bandc22 = product.getBand('C22') laiProduct = Product('LAI', 'LAI', width, height) laiBand = laiProduct.addBand('lai', ProductData.TYPE_FLOAT32) laiFlagsBand = laiProduct.addBand('lai_flags', ProductData.TYPE_UINT8) writer = ProductIO.getProductWriter('BEAM-DIMAP') ProductUtils.copyGeoCoding(product, laiProduct) ProductUtils.copyMetadata(product, laiProduct) ProductUtils.copyTiePointGrids(product, laiProduct) laiFlagCoding = FlagCoding('lai_flags') laiFlagCoding.addFlag("LAI_LOW", 1, "LAI below 0") laiFlagCoding.addFlag("LAI_HIGH", 2, "LAI above 5") group = laiProduct.getFlagCodingGroup() #print(dir(group)) group.add(laiFlagCoding) laiFlagsBand.setSampleCoding(laiFlagCoding) laiProduct.setProductWriter(writer) laiProduct.writeHeader('LAImap_output.dim') c11 = numpy.zeros(width, dtype=numpy.float32) c22 = numpy.zeros(width, dtype=numpy.float32) print("Writing...") for y in range(height): print("processing line ", y, " of ", height) c11 = bandc11.readPixels(0, y, width, 1, c11) c22 = bandc22.readPixels(0, y, width, 1, c22) Z=np.column_stack((c11,c22)) #ndvi = (r10 - r7) / (r10 + r7) lai = pipeline.predict(Z); laiBand.writePixels(0, y, width, 1, lai) laiLow = lai < 0.0 laiHigh = lai > 5.0 laiFlags = numpy.array(laiLow + 2 * laiHigh, dtype=numpy.int32) laiFlagsBand.writePixels(0, y, width, 1, laiFlags) laiProduct.closeIO() print("Done.")
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2.551364
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import fiona d = { "type": "Feature", "id": "0", "properties": { "ADMINFORES": "99081600010343", "REGION": "08", "FORESTNUMB": "16", "FORESTORGC": "0816", "FORESTNAME": "El Yunque National Forest", "GIS_ACRES": 55829.81, "SHAPE_AREA": 0.0193062316937, "SHAPE_LEN": 0.754287568301, }, "geometry": { "type": "MultiPolygon", "coordinates": [ [ [ [-65.73293016000002, 18.33284838999998], [-65.73293445000002, 18.331367639999996], [-65.73189660000003, 18.331369719999998], [-65.73040952000002, 18.33137273], [-65.72620770999998, 18.33138113000001], [-65.72303074000001, 18.331387389999975], [-65.71763471000003, 18.331393549999973], [-65.71717587, 18.331394069999988], [-65.71297922999997, 18.331403290000026], [-65.71248787000002, 18.33140437999998], [-65.70898332000002, 18.33141236], [-65.70846269999998, 18.331413540000028], [-65.70470655999998, 18.331422009999983], [-65.70340513999997, 18.33142491000001], [-65.70268779000003, 18.331419400000016], [-65.70098910000002, 18.33140635000001], 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18.25164811000002], [-65.91628292000001, 18.25191947000002], [-65.91627997, 18.253774229999976], [-65.91627848000002, 18.25477933000002], [-65.91627578999999, 18.255991100000017], [-65.91626445999998, 18.261137089999977], [-65.91625448000002, 18.26512563], [-65.91625524, 18.26536785000002], [-65.91625922999998, 18.266019389999997], [-65.91632637999999, 18.266198929999973], [-65.91632625, 18.266542049999998], [-65.91631202000002, 18.267959780000012], [-65.91631167000003, 18.267977850000022], [-65.91630744000003, 18.268755800000008], [-65.91630715999997, 18.268808560000025], [-65.91625932, 18.270663520000028], [-65.91625911, 18.270671989999983], [-65.91625876, 18.270887870000024], [-65.91625875, 18.27455298000001], [-65.91625871999997, 18.274613149999993], [-65.91625811, 18.279979179999998], [-65.91626000000002, 18.280340190000004], [-65.91625800000003, 18.281121770000027], [-65.91625804, 18.281356930000015], [-65.91618933000001, 18.281356570000014], [-65.91500064000002, 18.281350369999984], [-65.91296770999998, 18.281339800000012], [-65.91253340999998, 18.281337529999973], [-65.91229578999997, 18.281336280000005], [-65.90998387000002, 18.281324219999988], [-65.90871597, 18.281318759999976], [-65.90216367, 18.28129032999999], [-65.90111256, 18.281285760000003], [-65.89913740999998, 18.28127711000002], [-65.89885119000002, 18.28127286], [-65.89237293000002, 18.281247450000023], [-65.89048616000002, 18.281239140000025], [-65.88711766, 18.28122424999998], [-65.88599235999999, 18.281219249999992], [-65.88291291000002, 18.28120555999999], [-65.88291178999998, 18.28584490999998], [-65.88291048999997, 18.291010749999998], [-65.88290905000002, 18.29165870999998], [-65.88291565999998, 18.302684020000015], [-65.88291612, 18.303763930000002], [-65.88291874999999, 18.31314200999998], [-65.88292098, 18.314737100000002], [-65.88292178, 18.316319510000028], [-65.88292336, 18.320099939999977], [-65.88292583999998, 18.325711160000026], [-65.88292658, 18.32707603], [-65.88292819999998, 18.330798640000012], [-65.88292837, 18.331260059999977], [-65.88087401000001, 18.331255440000007], [-65.87894735999998, 18.331251090000023], [-65.87603802000001, 18.33124448000001], [-65.87461601000001, 18.33124122999999], [-65.86804993999999, 18.331420340000022], [-65.86763531000003, 18.331420009999988], [-65.86672666999999, 18.33141931], [-65.86648867999997, 18.331419100000005], [-65.86635653000002, 18.331419170000004], [-65.86273363999999, 18.331421009999985], [-65.85793086000001, 18.331423389999998], [-65.85789242999999, 18.33142171999998], [-65.85542400000003, 18.331424019999986], [-65.85350249999999, 18.331425749999994], [-65.84982063000001, 18.33142908000002], [-65.84969439000002, 18.331429189999994], [-65.84969428, 18.331550279999988], [-65.84969804000002, 18.33796344000001], [-65.84969840999997, 18.338737999999978], [-65.8497021, 18.345083629999976], [-65.84970268000001, 18.346151969999994], [-65.84970370000002, 18.34806388999999], [-65.84281220000003, 18.348051429999998], [-65.83631126, 18.348039400000005], [-65.83572038, 18.348038309999993], [-65.82972193, 18.348027020000018], [-65.82915395999999, 18.348025940000014], [-65.82799924, 18.34802375999999], [-65.82479099, 18.34801637999999], [-65.82399432, 18.34801453], [-65.82321229000001, 18.348012719999986], [-65.82141923, 18.348008540000023], [-65.82131368, 18.34800831000001], [-65.81955477000002, 18.348004189999983], [-65.81593006999998, 18.347995690000005], [-65.81524768000003, 18.347994099999994], [-65.81430688, 18.347991850000028], [-65.81409592, 18.34799134000002], [-65.81219464999998, 18.347986839999976], [-65.81037927, 18.347982520000016], [-65.80875237999999, 18.347978650000016], [-65.80848982999998, 18.34797801000002], [-65.80829098999999, 18.347977609999987], [-65.80772302000003, 18.347976930000016], [-65.80733909999998, 18.34797567999999], [-65.80353065000003, 18.347967859999983], [-65.80071562, 18.347962040000027], [-65.79902959999998, 18.34795853999998], [-65.79798546, 18.34795637000002], [-65.79009180999998, 18.347941110000022], [-65.78932427000001, 18.347939639999993], [-65.78840032, 18.347937820000027], [-65.78753816, 18.347936129999994], [-65.78601164000003, 18.347933119999993], [-65.78038322999998, 18.347921919999976], [-65.77934201, 18.347919479999973], [-65.77871169000002, 18.347918520000007], [-65.77776547000002, 18.347916520000012], [-65.77676473999998, 18.347914670000023], [-65.77662666999998, 18.347914370000012], [-65.77532722000001, 18.347911739999972], [-65.77499889, 18.347911039999985], [-65.77385053, 18.347908700000005], [-65.77354066999999, 18.34790806000001], [-65.76955748, 18.347899840000025], [-65.76888499, 18.347898439999994], [-65.76835487, 18.347897349999982], [-65.76683013000002, 18.34789416000001], [-65.76222604999998, 18.347884490000013], [-65.75909141, 18.347877840000024], [-65.75869390000003, 18.347874339999976], [-65.75078702000002, 18.34780397999998], [-65.74961532999998, 18.347793539999998], [-65.74804139999998, 18.347743690000016], [-65.74783091, 18.347737010000003], [-65.74728348000002, 18.347736259999976], [-65.74297489999998, 18.347730169999977], [-65.74044021999998, 18.347710549999988], [-65.73974084000002, 18.347705140000016], [-65.73561567000002, 18.34767314999999], [-65.73484725999998, 18.347665380000024], [-65.73302854000002, 18.347646950000012], [-65.73294028999999, 18.347646069999996], [-65.73293561999998, 18.346632310000018], [-65.73292482, 18.344269059999988], [-65.73292071999998, 18.343373789999987], [-65.73291719000002, 18.34259155000001], [-65.73290365999998, 18.339655180000022], [-65.73291784000003, 18.337885169999993], [-65.73292518, 18.334980180000002], [-65.73292579000002, 18.334753429999978], [-65.73293016000002, 18.33284838999998], ] ], [ [ [-66.16262245000001, 18.051031109999997], [-66.16184043999999, 18.049737929999992], [-66.1619091, 18.04731941], [-66.16514587, 18.04502678], [-66.16511536000002, 18.044198989999984], [-66.16511725999999, 18.043462750000003], [-66.16511725999999, 18.043279649999988], [-66.16594887000002, 18.04355812], [-66.16832161000002, 18.041448590000016], [-66.16813087000003, 18.040346150000005], [-66.16640091, 18.04031180999999], [-66.16698073999999, 18.03862952999998], [-66.16720580999998, 18.037527080000018], [-66.16765975999999, 18.033853529999988], [-66.16861915999999, 18.034097669999994], [-66.16942024000002, 18.033731460000013], [-66.16954613000001, 18.03507804999998], [-66.16970443999998, 18.036489490000008], [-66.16989517000002, 18.037008290000017], [-66.17005347999998, 18.038480760000027], [-66.17072487000002, 18.03927802999999], [-66.17091750999998, 18.039522169999998], [-66.17117309999998, 18.039552689999994], [-66.17162131999999, 18.039552689999994], [-66.17216492, 18.039308549999987], [-66.17245293000002, 18.039155960000016], [-66.17293358, 18.039094920000025], [-66.17320251000001, 18.039094920000025], [-66.17344666000002, 18.039094920000025], [-66.17376709000001, 18.03928185000001], [-66.17305756000002, 18.042036059999987], [-66.17280005999999, 18.04304695000002], [-66.17234993, 18.044912339999996], [-66.17170142999998, 18.050027849999992], [-66.17182922, 18.050394059999974], [-66.17035484000002, 18.051618580000024], [-66.16718483, 18.05198096999999], [-66.16692733999997, 18.051458360000026], [-66.16661072, 18.050817489999986], [-66.16660117999999, 18.050874710000016], [-66.16659355000002, 18.05092811999998], [-66.16641808000003, 18.052057269999978], [-66.16641426000001, 18.052072529999975], [-66.16576958000002, 18.05623436000002], [-66.16262245000001, 18.051031109999997], ] ], [ [ [-66.53508758999999, 18.392507550000005], [-66.53519820999998, 18.391786579999973], [-66.53970336999998, 18.392427440000006], [-66.53828812, 18.397306440000023], [-66.53822708000001, 18.39755821], [-66.53777313, 18.398542399999997], [-66.53761481999999, 18.400304790000007], [-66.53463554000001, 18.40027046], [-66.53440475000002, 18.399271010000007], [-66.53497124, 18.39718819000001], [-66.53505897999997, 18.396612170000026], [-66.53450774999999, 18.395158770000023], [-66.53466796999999, 18.394887919999974], [-66.53466796999999, 18.39454841999998], [-66.53477286999998, 18.394208909999975], [-66.53480911000003, 18.393922809999992], [-66.53482628, 18.39348030000002], [-66.5349865, 18.393175129999975], [-66.53508758999999, 18.392507550000005], ] ], ], }, } from shapely.geometry import shape print(shape(d["geometry"]))
[ 11748, 277, 32792, 198, 198, 67, 796, 1391, 198, 220, 220, 220, 366, 4906, 1298, 366, 38816, 1600, 198, 220, 220, 220, 366, 312, 1298, 366, 15, 1600, 198, 220, 220, 220, 366, 48310, 1298, 1391, 198, 220, 220, 220, 220, 220, 220, 2...
1.58383
14,583
from __future__ import print_function import argparse, sys from .utils import is_textfile if __name__ == '__main__': sys.exit(main(sys.argv[1:]))
[ 6738, 11593, 37443, 834, 1330, 3601, 62, 8818, 198, 11748, 1822, 29572, 11, 25064, 198, 6738, 764, 26791, 1330, 318, 62, 5239, 7753, 198, 198, 361, 11593, 3672, 834, 6624, 705, 834, 12417, 834, 10354, 198, 220, 220, 220, 25064, 13, 37...
2.796296
54
if __name__ == "__main__": print("Nothing yet...")
[ 361, 11593, 3672, 834, 6624, 366, 834, 12417, 834, 1298, 198, 220, 220, 220, 3601, 7203, 18465, 1865, 9313, 8, 198 ]
2.619048
21
import base64 from sqlalchemy import Column, String, LargeBinary from sqlalchemy.orm import relationship from sqlalchemy.ext.hybrid import hybrid_property from sqlalchemy.orm.exc import NoResultFound from vantage6.common.globals import STRING_ENCODING from .base import Base, Database
[ 11748, 2779, 2414, 198, 198, 6738, 44161, 282, 26599, 1330, 29201, 11, 10903, 11, 13601, 33, 3219, 198, 6738, 44161, 282, 26599, 13, 579, 1330, 2776, 198, 6738, 44161, 282, 26599, 13, 2302, 13, 12114, 10236, 1330, 14554, 62, 26745, 198,...
3.567901
81
from checkov.common.models.enums import CheckResult, CheckCategories from checkov.terraform.checks.resource.base_resource_check import BaseResourceCheck check = EKSSecretsEncryption()
[ 6738, 2198, 709, 13, 11321, 13, 27530, 13, 268, 5700, 1330, 6822, 23004, 11, 6822, 34, 26129, 198, 6738, 2198, 709, 13, 353, 430, 687, 13, 42116, 13, 31092, 13, 8692, 62, 31092, 62, 9122, 1330, 7308, 26198, 9787, 628, 198, 198, 9122...
3.528302
53
""" AnalysisNode is the base class that all analysis nodes inherit from. """ import logging import operator from functools import reduce from random import random from time import time from typing import Tuple, Sequence, List, Dict, Optional from celery.canvas import Signature from django.conf import settings from django.core.cache import cache from django.db import connection, models from django.db.models import Value, IntegerField from django.db.models.aggregates import Count from django.db.models.deletion import CASCADE, SET_NULL from django.db.models.query_utils import Q from django.dispatch import receiver from django.utils import timezone from django_dag.models import node_factory, edge_factory from django_extensions.db.models import TimeStampedModel from lazy import lazy from model_utils.managers import InheritanceManager from analysis.exceptions import NonFatalNodeError, NodeParentErrorsException, NodeConfigurationException, \ NodeParentNotReadyException, NodeNotFoundException, NodeOutOfDateException from analysis.models.enums import GroupOperation, NodeStatus, NodeColors, NodeErrorSource, AnalysisTemplateType from analysis.models.models_analysis import Analysis from analysis.models.nodes.node_counts import get_extra_filters_q, get_node_counts_and_labels_dict from annotation.annotation_version_querysets import get_variant_queryset_for_annotation_version from classification.models import Classification, post_delete from library.database_utils import queryset_to_sql from library.django_utils import thread_safe_unique_together_get_or_create from library.log_utils import report_event from library.utils import format_percent from snpdb.models import BuiltInFilters, Sample, Variant, VCFFilter, Wiki, Cohort, VariantCollection, \ ProcessingStatus, GenomeBuild, AlleleSource from snpdb.variant_collection import write_sql_to_variant_collection from variantgrid.celery import app def get_q(self, disable_cache=False): """ A Django Q object representing the Variant filters for this node. This is the method to override in subclasses - not get_queryset() as: Chains of filters to a reverse foreign key relationship causes Multiple joins, so use Q objects which are combined at the end qs = qs.filter(table_1__val=1) qs = qs.filter(table_2__val=2) This is not necessarily equal to: qs.filter(table_1__val=1, table_2__val=2) @see https://docs.djangoproject.com/en/2/topics/db/queries/#spanning-multi-valued-relationships """ # We need this for node counts, and doing a grid query (each page) - and it can take a few secs to generate # for some nodes (Comp HET / pheno) so cache it cache_key = self._get_cache_key() + f"q_cache={disable_cache}" q: Optional[Q] = None if settings.ANALYSIS_NODE_CACHE_Q: # Disable for unit tests q = cache.get(cache_key) if q is None: if disable_cache is False: if cache_q := self._get_node_cache_q(): return cache_q if self.has_input(): q = self.get_parent_q() if self.modifies_parents(): if node_q := self._get_node_q(): q &= node_q else: q = self.q_all() if node_q := self._get_node_q(): q = node_q cache.set(cache_key, q) return q def _get_node_cache_q(self) -> Optional[Q]: q = None if self.node_cache: q = self.node_cache.variant_collection.get_q() return q def _get_node_q(self) -> Optional[Q]: raise NotImplementedError() def _get_unfiltered_queryset(self, **extra_annotation_kwargs): """ Unfiltered means before the get_q() is applied extra_annotation_kwargs is applied AFTER node's annotation kwargs """ qs = self._get_model_queryset() a_kwargs = self.get_annotation_kwargs() a_kwargs.update(extra_annotation_kwargs) if a_kwargs: # Clear ordering, @see # https://docs.djangoproject.com/en/3.0/topics/db/aggregation/#interaction-with-default-ordering-or-order-by qs = qs.annotate(**a_kwargs).order_by() return qs def get_queryset(self, extra_filters_q=None, extra_annotation_kwargs=None, inner_query_distinct=False, disable_cache=False): if extra_annotation_kwargs is None: extra_annotation_kwargs = {} qs = self._get_unfiltered_queryset(**extra_annotation_kwargs) q = self.get_q(disable_cache=disable_cache) if extra_filters_q: q &= extra_filters_q filtered_qs = qs.filter(q) if self.queryset_requires_distinct: if inner_query_distinct: qs = qs.filter(pk__in=filtered_qs.values_list("pk", flat=True)) else: qs = filtered_qs.distinct() else: qs = filtered_qs return qs def get_extra_grid_config(self): return {} def get_class_name(self): return self.__class__.__name__ def get_identifier(self): return f"{self.get_class_name()}-{self.pk}" def get_css_classes(self): """ returns list of css classes - set on "node > .node-overlay" on node appearance update """ css_classes = [] if self.output_node: css_classes.append("output-node") if self.analysis.template_type == AnalysisTemplateType.TEMPLATE and self.analysisvariable_set.exists(): css_classes.append("variable-node") return css_classes def get_input_count(self): parents = self.get_non_empty_parents() return sum([p.get_output_count() for p in parents]) def get_output_count(self): # TODO: Move the if not modify parents code in here. if self.count is not None: return self.count count = self.get_queryset().count() self.count = count self.save() return count def _get_method_summary(self): raise NotImplementedError() def get_method_summary(self): errors = self.get_errors(flat=True) if not errors: html_summary = self._get_method_summary() else: html_summary = "<b>incorrectly configured</b><ul>" for error in errors: html_summary += f"<li>{error}</li>" html_summary += "</ul>" return html_summary def get_node_name(self): """ Automatic node name """ raise NotImplementedError(f"Node Class: {self.get_class_name()}") def _get_genome_build_errors(self, field_name, field_genome_build: GenomeBuild) -> List: """ Used to quickly add errors about genome build mismatches This only happens in templates (ran template on sample with different build than hardcoded data) In normal analyses, autocomplete restrictions should not allow you to configure data from other builds """ errors = [] if field_genome_build != self.analysis.genome_build: msg = f"{field_name} genome build: {field_genome_build} different from analysis build: {self.analysis.genome_build}" errors.append(msg) return errors def _get_configuration_errors(self) -> List: return [] def get_parents_and_errors(self): """ Returns error array, includes any min/max parent error and node config error """ if self.has_input(): return self.get_parent_subclasses_and_errors() return [], [] def get_errors(self, include_parent_errors=True, flat=False): """ returns a tuple of (NodeError, str) unless flat=True where it's only string """ errors = [] for analysis_error in self.analysis.get_errors(): errors.append((NodeErrorSource.ANALYSIS, analysis_error)) _, parent_errors = self.get_parents_and_errors() if include_parent_errors: errors.extend(parent_errors) if self.errors: errors.append((NodeErrorSource.INTERNAL_ERROR, self.errors)) errors.extend((NodeErrorSource.CONFIGURATION, ce) for ce in self._get_configuration_errors()) if flat: errors = AnalysisNode.flatten_errors(errors) return errors def inherits_parent_columns(self): return self.min_inputs == 1 and self.max_inputs == 1 def _get_node_extra_columns(self): return [] def _get_inherited_columns(self): extra_columns = [] if self.inherits_parent_columns(): parent = self.get_single_parent() extra_columns.extend(parent.get_extra_columns()) return extra_columns def get_extra_columns(self): cache_key = self._get_cache_key() + "_extra_columns" extra_columns = cache.get(cache_key) if extra_columns is None: extra_columns = [] if self.is_valid(): extra_columns.extend(self._get_inherited_columns()) # Only add columns that are unique, as otherwise filters get added twice. node_extra_columns = self._get_node_extra_columns() for col in node_extra_columns: if col not in extra_columns: extra_columns.append(col) cache.set(cache_key, extra_columns) return extra_columns def _get_node_extra_colmodel_overrides(self): """ Subclasses should override to add colmodel overrides for JQGrid """ return {} def _get_inherited_colmodel_overrides(self): extra_overrides = {} if self.inherits_parent_columns(): parent = self.get_single_parent() extra_overrides.update(parent.get_extra_colmodel_overrides()) return extra_overrides def get_extra_colmodel_overrides(self): """ For JQGrid - subclasses should override _get_node_extra_colmodel_overrides """ extra_overrides = {} if self.is_valid() and self.uses_parent_queryset: extra_overrides.update(self._get_inherited_colmodel_overrides()) extra_overrides.update(self._get_node_extra_colmodel_overrides()) return extra_overrides def get_node_classification(self): if self.is_source(): classification = "source" else: classification = "filter" return classification def has_input(self): return self.max_inputs != 0 def is_source(self): return self.has_input() is False def is_valid(self): return not self.get_errors() def is_ready(self): return NodeStatus.is_ready(self.status) def bump_version(self): if self.version > 0: DELETE_CACHE_TASK = "analysis.tasks.node_update_tasks.delete_old_node_versions" app.send_task(DELETE_CACHE_TASK, args=(self.pk, self.version)) self.version += 1 self.status = NodeStatus.DIRTY self.count = None self.errors = None self.cloned_from = None def modifies_parents(self): """ Can overwrite and set to False to use parent counts """ return True def get_unmodified_single_parent_node(self) -> Optional['AnalysisNode']: """ If a node doesn't modify single parent - can use that in some places to re-use cache """ if self.is_valid() and self.has_input() and not self.modifies_parents(): try: return self.get_single_parent() except ValueError: pass return None def _get_cached_label_count(self, label) -> Optional[int]: """ Override for optimisation. Returning None means we need to run the SQL to get the count """ try: if self.cloned_from: # If cloned (and we or original haven't changed) - use those counts try: node_count = NodeCount.load_for_node_version(self.cloned_from, label) return node_count.count except NodeCount.DoesNotExist: # Should only ever happen if original bumped version since we were loaded # otherwise should have cascade set cloned_from to NULL pass if self.has_input(): parent_non_zero_label_counts = [] for parent in self.get_non_empty_parents(): if parent.count != 0: # count=0 has 0 for all labels parent_node_count = NodeCount.load_for_node(parent, label) if parent_node_count.count != 0: parent_non_zero_label_counts.append(parent_node_count.count) if not parent_non_zero_label_counts: # logging.info("all parents had 0 %s counts", label) return 0 if not self.modifies_parents(): if len(parent_non_zero_label_counts) == 1: # logging.info("Single parent, no modification, using that") return parent_non_zero_label_counts[0] except NodeCount.DoesNotExist: pass except Exception as e: logging.warning("Trouble getting cached %s count: %s", label, e) return None def get_grid_node_id_and_version(self): """ Uses parent node_id/version if possible to re-use cache """ node_id = self.pk version = self.version if self.cloned_from: node_id = self.cloned_from.node_id version = self.cloned_from.version if parent := self.get_unmodified_single_parent_node(): node_id, version = parent.get_grid_node_id_and_version() return node_id, version def node_counts(self): """ This is inside Celery task """ self.count = None counts_to_get = {BuiltInFilters.TOTAL} counts_to_get.update([i[0] for i in self.analysis.get_node_count_types()]) label_counts = {} for label in counts_to_get: label_count = self._get_cached_label_count(label) if label_count is not None: label_counts[label] = label_count counts_to_get -= set(label_counts) logging.debug("%s cached counts: %s", self, label_counts) if counts_to_get: logging.debug("%s needs DB request for %s", self, counts_to_get) retrieved_label_counts = get_node_counts_and_labels_dict(self) label_counts.update(retrieved_label_counts) node_version = NodeVersion.get(self) for label, count in label_counts.items(): NodeCount.objects.create(node_version=node_version, label=label, count=count) return NodeStatus.READY, label_counts[BuiltInFilters.TOTAL] def _load(self): """ Override to do anything interesting """ pass def load(self): """ load is called after parents are run """ # logging.debug("node %d (%d) load()", self.id, self.version) start = time() self._load() # Do before counts in case it affects anything status, count = self.node_counts() load_seconds = time() - start self.update(status=status, count=count, load_seconds=load_seconds) def add_parent(self, parent, *args, **kwargs): if not parent.visible: raise NonFatalNodeError("Not connecting children to invisible nodes!") existing_connect = parent.children.through.objects.filter(parent=parent, child=self) if not existing_connect.exists(): super().add_parent(parent) self.parents_changed = True else: logging.error("Node(pk=%d).add_parent(pk=%d) already exists!", self.pk, parent.pk) def remove_parent(self, parent): """ disconnects parent by deleting edge """ # Ok to have multiple, just delete first edge = parent.children.through.objects.filter(parent=parent, child=self).first() if edge: # could be some kind of race condition? edge.delete() self.parents_changed = True def handle_ancestor_input_samples_changed(self): pass def update(self, **kwargs): """ Updates Node if self.version matches DB - otherwise throws NodeOutOfDateException """ self_qs = AnalysisNode.objects.filter(pk=self.pk, version=self.version) updated = self_qs.update(**kwargs) if not updated: raise NodeOutOfDateException() def save(self, **kwargs): """ To avoid race conditions, don't use save() in a celery task (unless running in scheduling_single_worker) instead use update() method above """ # logging.debug("save: pk=%s kwargs=%s", self.pk, str(kwargs)) super_save = super().save if self.parents_changed or self.ancestor_input_samples_changed: self.handle_ancestor_input_samples_changed() if self.auto_node_name: self.name = self.get_node_name() # TODO: This causes lots of DB queries... should we change this? self.valid = self.is_valid() if not self.valid: self.shadow_color = NodeColors.ERROR self.appearance_dirty = True elif self.shadow_color == NodeColors.ERROR: # Need to allow nodes to set to warning self.shadow_color = NodeColors.VALID self.appearance_dirty = True if self.appearance_dirty: self.appearance_version += 1 if self.parents_changed or self.queryset_dirty: self.bump_version() super_save(**kwargs) if self.update_children: # We also need to bump if node has it's own sample - as in templates, we set fields in toposort order # So we could go from having multiple proband samples to only one later (thus can set descendants) for kid in self.children.select_subclasses(): kid.ancestor_input_samples_changed = self.is_source() or self.ancestor_input_samples_changed or \ self.get_samples_from_node_only_not_ancestors() kid.appearance_dirty = False kid.queryset_dirty = True kid.save() # Will bump versions else: super_save(**kwargs) # Make sure this always exists NodeVersion.objects.get_or_create(node=self, version=self.version) # Modify our analyses last updated time Analysis.objects.filter(pk=self.analysis.pk).update(modified=timezone.now()) def adjust_cloned_parents(self, old_new_map): """ If you need to do something with old/new parents """ pass class NodeColumnSummaryCacheCollection(models.Model): node_version = models.ForeignKey(NodeVersion, on_delete=CASCADE) variant_column = models.TextField(null=False) extra_filters = models.TextField(null=False)
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import os import traceback from flask import render_template, send_from_directory, current_app, g from .emailing import email
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# 'from ... import ...' statement from sys import exit main()
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from dataclasses import dataclass from typing import List from typing import Union from postmanparser.description import Description from postmanparser.exceptions import InvalidObjectException from postmanparser.exceptions import MissingRequiredFieldException
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#!/usr/bin/env python # -*- coding: utf-8 -*- import json import pip import os import sys if __name__ == "__main__": main()
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""" Console scripts David Megginson April 2015 This is a big, ugly module to support the libhxl console scripts, including (mainly) argument parsing. License: Public Domain Documentation: https://github.com/HXLStandard/libhxl-python/wiki """ from __future__ import print_function import argparse, json, logging, os, re, requests, sys # Do not import hxl, to avoid circular imports import hxl.converters, hxl.filters, hxl.io logger = logging.getLogger(__name__) # In Python2, sys.stdin is a byte stream; in Python3, it's a text stream STDIN = sys.stdin.buffer # Posix exit codes EXIT_OK = 0 EXIT_ERROR = 1 EXIT_SYNTAX = 2 # # Console script entry points # def hxladd(): """Console script for hxladd.""" run_script(hxladd_main) def hxlappend(): """Console script for hxlappend.""" run_script(hxlappend_main) def hxlclean(): """Console script for hxlclean""" run_script(hxlclean_main) def hxlcount(): """Console script for hxlcount.""" run_script(hxlcount_main) def hxlcut(): """Console script for hxlcut.""" run_script(hxlcut_main) def hxldedup(): """Console script for hxldedup.""" run_script(hxldedup_main) def hxlhash(): """Console script for hxlhash.""" run_script(hxlhash_main) def hxlmerge(): """Console script for hxlmerge.""" run_script(hxlmerge_main) def hxlrename(): """Console script for hxlrename.""" run_script(hxlrename_main) def hxlreplace(): """Console script for hxlreplace.""" run_script(hxlreplace_main) def hxlfill(): """Console script for hxlreplace.""" run_script(hxlfill_main) def hxlexpand(): """Console script for hxlexpand.""" run_script(hxlexpand_main) def hxlexplode(): """Console script for hxlexplode.""" run_script(hxlexplode_main) def hxlimplode(): """Console script for hxlimplode.""" run_script(hxlimplode_main) def hxlselect(): """Console script for hxlselect.""" run_script(hxlselect_main) def hxlsort(): """Console script for hxlsort.""" run_script(hxlsort_main) def hxlspec(): """Console script for hxlspec.""" run_script(hxlspec_main) def hxltag(): """Console script for hxltag.""" run_script(hxltag_main) def hxlvalidate(): """Console script for hxlvalidate.""" run_script(hxlvalidate_main) # # Main scripts for command-line tools. # def hxladd_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxladd with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Add new columns with constant values to a HXL dataset.') parser.add_argument( '-s', '--spec', help='Constant value to add to each row (may repeat option)', metavar='header#<tag>=<value>', action='append', required=True ) parser.add_argument( '-b', '--before', help='Add new columns before existing ones rather than after them.', action='store_const', const=True, default=False ) args = parser.parse_args(args) do_common_args(args) with make_source(args, stdin) as source, make_output(args, stdout) as output: filter = hxl.filters.AddColumnsFilter(source, specs=args.spec, before=args.before) hxl.io.write_hxl(output.output, filter, show_tags=not args.strip_tags) return EXIT_OK def hxlappend_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlappend with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Concatenate two HXL datasets') # repeatable argument parser.add_argument( '-a', '--append', help='HXL file to append (may repeat option).', metavar='file_or_url', action='append', default=[] ) parser.add_argument( '-l', '--list', help='URL or filename of list of URLs (may repeat option). Will appear after sources in -a options.', action='append', default=[] ) parser.add_argument( '-x', '--exclude-extra-columns', help='Don not add extra columns not in the original dataset.', action='store_const', const=True, default=False ) add_queries_arg(parser, 'From --append datasets, include only rows matching at least one query.') args = parser.parse_args(args) do_common_args(args) append_sources = [] for append_source in args.append: append_sources.append(hxl.data(append_source, True)) for list_source in args.list: for append_source in hxl.filters.AppendFilter.parse_external_source_list(hxl.data(list_source, True)): append_sources.append(hxl.data(append_source, True)) with make_source(args, stdin) as source, make_output(args, stdout) as output: filter = hxl.filters.AppendFilter( source, append_sources=append_sources, add_columns=(not args.exclude_extra_columns), queries=args.query ) hxl.io.write_hxl(output.output, filter, show_headers=not args.remove_headers, show_tags=not args.strip_tags) return EXIT_OK def hxlclean_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlclean with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Clean data in a HXL file.') parser.add_argument( '-w', '--whitespace', help='Comma-separated list of tag patterns for whitespace normalisation.', metavar='tag,tag...', type=hxl.model.TagPattern.parse_list ) parser.add_argument( '-u', '--upper', help='Comma-separated list of tag patterns for uppercase conversion.', metavar='tag,tag...', type=hxl.model.TagPattern.parse_list ) parser.add_argument( '-l', '--lower', help='Comma-separated list of tag patterns for lowercase conversion.', metavar='tag,tag...', type=hxl.model.TagPattern.parse_list ) parser.add_argument( '-d', '--date', help='Comma-separated list of tag patterns for date normalisation.', metavar='tag,tag...', type=hxl.model.TagPattern.parse_list ) parser.add_argument( '--date-format', help='Date formatting string in strftime format (defaults to %%Y-%%m-%%d).', default=None, metavar='format', ) parser.add_argument( '-n', '--number', help='Comma-separated list of tag patternss for number normalisation.', metavar='tag,tag...', type=hxl.model.TagPattern.parse_list ) parser.add_argument( '--number-format', help='Number formatting string in printf format (without leading %%).', default=None, metavar='format', ) parser.add_argument( '--latlon', help='Comma-separated list of tag patterns for lat/lon normalisation.', metavar='tag,tag...', type=hxl.model.TagPattern.parse_list ) parser.add_argument( '-p', '--purge', help='Purge unparseable dates, numbers, and lat/lon during cleaning.', action='store_const', const=True, default=False ) add_queries_arg(parser, 'Clean only rows matching at least one query.') args = parser.parse_args(args) do_common_args(args) with make_source(args, stdin) as source, make_output(args, stdout) as output: filter = hxl.filters.CleanDataFilter( source, whitespace=args.whitespace, upper=args.upper, lower=args.lower, date=args.date, date_format=args.date_format, number=args.number, number_format=args.number_format, latlon=args.latlon, purge=args.purge, queries=args.query ) hxl.io.write_hxl(output.output, filter, show_headers=not args.remove_headers, show_tags=not args.strip_tags) return EXIT_OK def hxlcount_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlcount with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ # Command-line arguments parser = make_args('Generate aggregate counts for a HXL dataset') parser.add_argument( '-t', '--tags', help='Comma-separated list of column tags to count.', metavar='tag,tag...', type=hxl.model.TagPattern.parse_list, default='loc,org,sector,adm1,adm2,adm3' ) parser.add_argument( '-a', '--aggregator', help='Aggregator statement', metavar='statement', action='append', type=hxl.filters.Aggregator.parse, default=[] ) add_queries_arg(parser, 'Count only rows that match at least one query.') args = parser.parse_args(args) do_common_args(args) with make_source(args, stdin) as source, make_output(args, stdout) as output: filter = hxl.filters.CountFilter(source, patterns=args.tags, aggregators=args.aggregator, queries=args.query) hxl.io.write_hxl(output.output, filter, show_tags=not args.strip_tags) return EXIT_OK def hxlmerge_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlmerge with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Merge part of one HXL dataset into another.') parser.add_argument( '-m', '--merge', help='HXL file to write (if omitted, use standard output).', metavar='filename', required=True ) parser.add_argument( '-k', '--keys', help='HXL tag(s) to use as a shared key.', metavar='tag,tag...', required=True, type=hxl.model.TagPattern.parse_list ) parser.add_argument( '-t', '--tags', help='Comma-separated list of column tags to include from the merge dataset.', metavar='tag,tag...', required=True, type=hxl.model.TagPattern.parse_list ) parser.add_argument( '-r', '--replace', help='Replace empty values in existing columns (when available) instead of adding new ones.', action='store_const', const=True, default=False ) parser.add_argument( '-O', '--overwrite', help='Used with --replace, overwrite existing values.', action='store_const', const=True, default=False ) add_queries_arg(parser, 'Merged data only from rows that match at least one query.') args = parser.parse_args(args) do_common_args(args) with make_source(args, stdin) as source, make_output(args, stdout) as output, hxl.io.data(args.merge, True) if args.merge else None as merge_source: filter = hxl.filters.MergeDataFilter( source, merge_source=merge_source, keys=args.keys, tags=args.tags, replace=args.replace, overwrite=args.overwrite, queries=args.query ) hxl.io.write_hxl(output.output, filter, show_tags=not args.strip_tags) return EXIT_OK def hxlrename_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlrename with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Rename and retag columns in a HXL dataset') parser.add_argument( '-r', '--rename', help='Rename an old tag to a new one, with an optional new text header (may repeat option).', action='append', metavar='#?<original_tag>:<Text header>?#?<new_tag>', default=[], type=hxl.filters.RenameFilter.parse_rename ) args = parser.parse_args(args) do_common_args(args) with make_source(args, stdin) as source, make_output(args, stdout) as output: filter = hxl.filters.RenameFilter(source, args.rename) hxl.io.write_hxl(output.output, filter, show_tags=not args.strip_tags) return EXIT_OK def hxlreplace_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlreplace with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Replace strings in a HXL dataset') inline_group = parser.add_argument_group('Inline replacement') map_group = parser.add_argument_group('External substitution map') inline_group.add_argument( '-p', '--pattern', help='String or regular expression to search for', nargs='?' ) inline_group.add_argument( '-s', '--substitution', help='Replacement string', nargs='?' ) inline_group.add_argument( '-t', '--tags', help='Tag patterns to match', metavar='tag,tag...', type=hxl.model.TagPattern.parse_list ) inline_group.add_argument( '-r', '--regex', help='Use a regular expression instead of a string', action='store_const', const=True, default=False ) map_group.add_argument( '-m', '--map', help='Filename or URL of a mapping table using the tags #x_pattern (required), #x_substitution (required), #x_tag (optional), and #x_regex (optional), corresponding to the inline options above, for multiple substitutions.', metavar='PATH', nargs='?' ) add_queries_arg(parser, 'Replace only in rows that match at least one query.') args = parser.parse_args(args) do_common_args(args) with make_source(args, stdin) as source, make_output(args, stdout) as output: if args.map: replacements = hxl.filters.ReplaceDataFilter.Replacement.parse_map(hxl.io.data(args.map, True)) else: replacements = [] if args.pattern: for tag in args.tags: replacements.append(hxl.filters.ReplaceDataFilter.Replacement(args.pattern, args.substitution, tag, args.regex)) filter = hxl.filters.ReplaceDataFilter(source, replacements, queries=args.query) hxl.io.write_hxl(output.output, filter, show_tags=not args.strip_tags) return EXIT_OK def hxlfill_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlfill with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Fill empty cells in a HXL dataset') parser.add_argument( '-t', '--tag', help='Fill empty cells only in matching columns (default: fill in all)', metavar='tagpattern,...', type=hxl.model.TagPattern.parse, ) add_queries_arg(parser, 'Fill only in rows that match at least one query.') args = parser.parse_args(args) do_common_args(args) with make_source(args, stdin) as source, make_output(args, stdout) as output: filter = hxl.filters.FillDataFilter(source, pattern=args.tag, queries=args.query) hxl.io.write_hxl(output.output, filter, show_tags=not args.strip_tags) return EXIT_OK def hxlexpand_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlexpand with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Expand lists in cells by repeating rows') parser.add_argument( '-t', '--tags', help='Comma-separated list of tag patterns for columns with lists to expand', metavar='tag,tag...', type=hxl.model.TagPattern.parse_list, nargs="?" ) parser.add_argument( "-s", '--separator', help='string separating list items (defaults to "|")', metavar='string', default="|" ) parser.add_argument( "-c", '--correlate', help='correlate list values instead of producing a cartesian product', action='store_const', const=True, default=False ) add_queries_arg(parser, 'Limit list expansion to rows matching at least one query.') args = parser.parse_args(args) do_common_args(args) with make_source(args, stdin) as source, make_output(args, stdout) as output: filter = hxl.filters.ExpandListsFilter(source, patterns=args.tags, separator=args.separator, correlate=args.correlate, queries=args.query) hxl.io.write_hxl(output.output, filter, show_tags=not args.strip_tags) return EXIT_OK def hxlexplode_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlexplode with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Explode a wide dataset into a long dataset') parser.add_argument( '-H', '--header-att', help='attribute to add to the label column (defaults to "label")', metavar='att', default="label" ) parser.add_argument( '-V', '--value-att', help='attribute to add to the value column (defaults to "value")', metavar='tagpattern', default="value" ) args = parser.parse_args(args) do_common_args(args) with make_source(args, stdin) as source, make_output(args, stdout) as output: filter = hxl.filters.ExplodeFilter(source, header_attribute=args.header_att, value_attribute=args.value_att) hxl.io.write_hxl(output.output, filter, show_tags=not args.strip_tags) return EXIT_OK def hxlimplode_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlexplode with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Implode a long dataset into a wide dataset.') parser.add_argument( '-L', '--label', help='HXL tag pattern for the label column', metavar='tagpattern', required=True, type=hxl.model.TagPattern.parse, ) parser.add_argument( '-V', '--value', help='HXL tag pattern for the value column', metavar='tagpattern', required=True, type=hxl.model.TagPattern.parse, ) args = parser.parse_args(args) do_common_args(args) with make_source(args, stdin) as source, make_output(args, stdout) as output: filter = hxl.filters.ImplodeFilter(source, label_pattern=args.label, value_pattern=args.value) hxl.io.write_hxl(output.output, filter, show_tags=not args.strip_tags) return EXIT_OK def hxlselect_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlselect with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ # Command-line arguments parser = make_args('Filter rows in a HXL dataset.') parser.add_argument( '-q', '--query', help='Query expression for selecting rows (may repeat option for logical OR). <op> may be =, !=, <, <=, >, >=, ~, or !~', action='append', metavar='<tagspec><op><value>', required=True ) parser.add_argument( '-r', '--reverse', help='Show only lines *not* matching criteria', action='store_const', const=True, default=False ) args = parser.parse_args(args) do_common_args(args) with make_source(args, stdin) as source, make_output(args, stdout) as output: filter = hxl.filters.RowFilter(source, queries=args.query, reverse=args.reverse) hxl.io.write_hxl(output.output, filter, show_tags=not args.strip_tags) return EXIT_OK def hxlsort_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlcut with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Sort a HXL dataset.') parser.add_argument( '-t', '--tags', help='Comma-separated list of tags to for columns to use as sort keys.', metavar='tag,tag...', type=hxl.model.TagPattern.parse_list ) parser.add_argument( '-r', '--reverse', help='Flag to reverse sort order.', action='store_const', const=True, default=False ) args = parser.parse_args(args) do_common_args(args) with make_source(args, stdin) as source, make_output(args, stdout) as output: filter = hxl.filters.SortFilter(source, args.tags, args.reverse) hxl.io.write_hxl(output.output, filter, show_tags=not args.strip_tags) return EXIT_OK def hxlspec_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlspec with command-line arguments. Args: args (list): a list of command-line arguments stdin (io.IOBase): alternative standard input (mainly for testing) stdout (io.IOBase): alternative standard output (mainly for testing) stderr (io.IOBase): alternative standard error (mainly for testing) """ parser = make_args('Process a HXL JSON spec') args = parser.parse_args(args) do_common_args(args) spec = get_json(args.infile) source = hxl.io.from_spec(spec, allow_local_ok=True) with make_output(args, stdout) as output: hxl.io.write_hxl(output.output, source, show_tags=not args.strip_tags) def hxltag_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxltag with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Add HXL tags to a raw CSV file.') parser.add_argument( '-a', '--match-all', help='Match the entire header text (not just a substring)', action='store_const', const=True, default=False ) parser.add_argument( '-m', '--map', help='Mapping expression', required=True, action='append', metavar='Header Text#tag', type=hxl.converters.Tagger.parse_spec ) parser.add_argument( '-d', '--default-tag', help='Default tag for non-matching columns', metavar='#tag', type=hxl.model.Column.parse ) args = parser.parse_args(args) do_common_args(args) with make_input(args, stdin) as input, make_output(args, stdout) as output: tagger = hxl.converters.Tagger(input, args.map, default_tag=args.default_tag, match_all=args.match_all) hxl.io.write_hxl(output.output, hxl.io.data(tagger), show_tags=not args.strip_tags) return EXIT_OK def hxlvalidate_main(args, stdin=STDIN, stdout=sys.stdout, stderr=sys.stderr): """ Run hxlvalidate with command-line arguments. @param args A list of arguments, excluding the script name @param stdin Standard input for the script @param stdout Standard output for the script @param stderr Standard error for the script """ parser = make_args('Validate a HXL dataset.') parser.add_argument( '-s', '--schema', help='Schema file for validating the HXL dataset (if omitted, use the default core schema).', metavar='schema', default=None ) parser.add_argument( '-a', '--all', help='Include all rows in the output, including those without errors', action='store_const', const=True, default=False ) parser.add_argument( '-e', '--error-level', help='Minimum error level to show (defaults to "info") ', choices=['info', 'warning', 'error'], metavar='info|warning|error', default='info' ) args = parser.parse_args(args) do_common_args(args) with make_input(args, stdin) as input, make_output(args, stdout) as output: def callback(e): """Show a validation error message.""" if e.rule.severity == 'info': if args.error_level != 'info': return Counter.infos += 1 elif e.rule.severity == 'warning': if args.error_level == 'error': return Counter.warnings += 1 else: Counter.errors += 1 message = '[{}] '.format(e.rule.severity) if e.row: if e.rule: message += "{},{}: ".format(e.row.row_number + 1, e.rule.tag_pattern) else: message += "{}: ".format(e.row.row_number + 1) elif e.rule: message += "<dataset>,{}: ".format(e.rule.tag_pattern) else: message += "<dataset>: " if e.value: message += '"{}" '.format(e.value) if e.message: message += e.message message += "\n" output.write(message) output.write("Validating {} with schema {} ...\n".format(args.infile or "<standard input>", args.schema or "<default>")) source = hxl.io.data(input) if args.schema: with make_input(args, None, args.schema) as schema_input: schema = hxl.schema(schema_input, callback=callback) else: schema = hxl.schema(callback=callback) schema.validate(source) if args.error_level == 'info': output.write("{:,} error(s), {:,} warnings, {:,} suggestions\n".format(Counter.errors, Counter.warnings, Counter.infos)) elif args.error_level == 'warning': output.write("{:,} error(s), {:,} warnings\n".format(Counter.errors, Counter.warnings)) else: output.write("{:,} error(s)\n".format(Counter.errors)) if Counter.errors > 0: output.write("Validation failed.\n") return EXIT_ERROR else: output.write("Validation succeeded.\n") return EXIT_OK # # Utility functions # def run_script(func): """Try running a command-line script, with exception handling.""" try: sys.exit(func(sys.argv[1:], STDIN, sys.stdout)) except KeyboardInterrupt: logger.error("Interrupted") sys.exit(EXIT_ERROR) def make_args(description, hxl_output=True): """Set up parser with default arguments. @param description: usage description to show @param hxl_output: if True (default), include options for HXL output. @returns: an argument parser, partly set up. """ parser = argparse.ArgumentParser(description=description) parser.add_argument( 'infile', help='HXL file to read (if omitted, use standard input).', nargs='?' ) if hxl_output: parser.add_argument( 'outfile', help='HXL file to write (if omitted, use standard output).', nargs='?' ) parser.add_argument( '--sheet', help='Select sheet from a workbook (1 is first sheet)', metavar='number', type=int, nargs='?' ) parser.add_argument( '--selector', help='JSONPath expression for starting point in JSON input', metavar='path', nargs='?' ) parser.add_argument( '--http-header', help='Custom HTTP header to send with request', metavar='header', action='append' ) if hxl_output: parser.add_argument( '--remove-headers', help='Strip text headers from the CSV output', action='store_const', const=True, default=False ) parser.add_argument( '--strip-tags', help='Strip HXL tags from the CSV output', action='store_const', const=True, default=False ) parser.add_argument( "--ignore-certs", help="Don't verify SSL connections (useful for self-signed)", action='store_const', const=True, default=False ) parser.add_argument( '--log', help='Set minimum logging level', metavar='debug|info|warning|error|critical|none', choices=['debug', 'info', 'warning', 'error', 'critical'], default='error' ) return parser def do_common_args(args): """Process standard args""" logging.basicConfig(format='%(levelname)s (%(name)s): %(message)s', level=args.log.upper()) def make_source(args, stdin=STDIN): """Create a HXL input source.""" # construct the input object input = make_input(args, stdin) return hxl.io.data(input) def make_input(args, stdin=sys.stdin, url_or_filename=None): """Create an input object""" if url_or_filename is None: url_or_filename = args.infile # sheet index sheet_index = args.sheet if sheet_index is not None: sheet_index -= 1 # JSONPath selector selector = args.selector http_headers = make_headers(args) return hxl.io.make_input( url_or_filename or stdin, sheet_index=sheet_index, selector=selector, allow_local=True, http_headers=http_headers, verify_ssl=(not args.ignore_certs) ) def make_output(args, stdout=sys.stdout): """Create an output stream.""" if args.outfile: return FileOutput(args.outfile) else: return StreamOutput(stdout)
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