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# -*- coding: utf-8 -*- """ Notifications ------------- Example showing how to add notifications to a characteristic and handle the responses. Updated on 2019-07-03 by hbldh <<EMAIL>> """ import sys import logging import asyncio import platform from bleak import BleakClient from bleak import _logger as logger CH...
[ "logging.getLogger", "logging.StreamHandler", "asyncio.sleep", "platform.system", "bleak._logger.info", "bleak.BleakClient", "asyncio.get_event_loop", "bleak._logger.addHandler" ]
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from django.shortcuts import render,redirect from .forms import usernameForm,DateForm,UsernameAndDateForm, DateForm_2 from django.contrib import messages from django.contrib.auth.models import User import cv2 import dlib import imutils from imutils import face_utils from imutils.video import VideoStream from imutils.fa...
[ "cv2.rectangle", "sklearn.preprocessing.LabelEncoder", "users.models.Time", "django.contrib.messages.warning", "users.models.Time.objects.filter", "cv2.imshow", "django.contrib.auth.models.User.objects.filter", "numpy.array", "face_recognition.face_encodings", "cv2.destroyAllWindows", "face_reco...
[((1205, 1219), 'matplotlib.use', 'mpl.use', (['"""Agg"""'], {}), "('Agg')\n", (1212, 1219), True, 'import matplotlib as mpl\n'), ((1771, 1803), 'dlib.get_frontal_face_detector', 'dlib.get_frontal_face_detector', ([], {}), '()\n', (1801, 1803), False, 'import dlib\n'), ((1817, 1905), 'dlib.shape_predictor', 'dlib.shape...
import re import string DATA = '05.txt' def react(polymer): pairs = '|'.join([a + b + '|' + b + a for a, b in zip(string.ascii_lowercase, string.ascii_uppercase)]) length = len(polymer) while 1: polymer = re.sub(pairs, '', polymer) if len(polymer) == length: retu...
[ "re.sub" ]
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import json import cherrypy import engine class WebServer(object): @cherrypy.expose def index(self): return open('public/index.html', encoding='utf-8') @cherrypy.expose class GetOptionsService(object): @cherrypy.tools.accept(media='text/plain') def GET(self): return json.dumps({ ...
[ "engine.get_default_dataset_headers", "cherrypy.tools.json_out", "cherrypy.tools.accept", "json.loads", "engine.get_all_default_datasets", "engine.get_providers", "engine.execute", "engine.get_algorithms", "cherrypy.HTTPError" ]
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from typing import Union from tuprolog import logger # noinspection PyUnresolvedReferences import jpype.imports # noinspection PyUnresolvedReferences import it.unibo.tuprolog.solve.exception.error as errors from tuprolog.core import Term, Atom from tuprolog.solve import ExecutionContext, Signature ExistenceError = err...
[ "tuprolog.logger.debug" ]
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import pybullet as p import pybullet_data import gym from gym import spaces from gym.utils import seeding import numpy as np from math import sqrt import random import time import math import cv2 import torch import os def random_crop(imgs, out): """ args: imgs: shape (B,C,H,W) ...
[ "pybullet_data.getDataPath", "math.sqrt", "pybullet.computeViewMatrixFromYawPitchRoll", "pybullet.setGravity", "time.sleep", "numpy.array", "pybullet.disconnect", "gym.utils.seeding.np_random", "pybullet.connect", "pybullet.addUserDebugLine", "pybullet.getNumJoints", "pybullet.getCameraImage",...
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import dash import dash_core_components as dcc import dash_html_components as html import dash_bootstrap_components as dbc import pandas as pd import numpy as np import altair as alt import vega_datasets alt.data_transformers.enable('default') alt.data_transformers.disable_max_rows() app = dash.Dash(__name__, assets_f...
[ "altair.selection_single", "pandas.read_csv", "altair.binding_range", "dash_html_components.P", "dash.dependencies.Output", "altair.Chart", "altair.Scale", "dash.dependencies.Input", "altair.data_transformers.enable", "altair.X", "altair.Y", "altair.Legend", "dash_html_components.H2", "das...
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import os import pdb import warnings import numpy as np import torch import torch.nn as nn import torch.utils.data import torch.backends.cudnn import torch.optim as optim import dataloaders from utils.utils import AverageMeter from utils.loss import build_criterion from utils.metrics import Evaluator from utils.step_...
[ "retrain_model.build_autodeeplab.Retrain_Autodeeplab", "torch.load", "os.path.join", "torch.nn.DataParallel", "numpy.argmax", "dataloaders.make_data_loader", "os.path.isfile", "torch.cuda.is_available", "os.path.isdir", "os.mkdir", "utils.utils.AverageMeter", "pdb.set_trace", "torch.no_grad"...
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# The MIT License (MIT) # Copyright (c) 2021 <NAME> # 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, merg...
[ "home.Home", "login.Login", "context.Context", "pmu.axp192", "machine.reset", "settings.load" ]
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## Program: VMTK ## Language: Python ## Date: January 12, 2018 ## Version: 1.4 ## Copyright (c) <NAME>, <NAME>, All rights reserved. ## See LICENSE file for details. ## This software is distributed WITHOUT ANY WARRANTY; without even ## the implied warranty of MERCHANTABILITY or FITNESS FOR A PAR...
[ "pytest.fixture", "vmtk.vmtksurfacereader.vmtkSurfaceReader", "vmtk.vmtksurfaceconnectivity.vmtkSurfaceConnectivity", "os.path.join" ]
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# Author: <NAME> <<EMAIL>> # <NAME> <<EMAIL>> # # License: BSD-3-Clause import os.path as op import numpy as np from numpy.testing import assert_array_equal import pytest from mne import pick_types from mne.datasets import testing from mne.io.tests.test_raw import _test_raw_reader from mne.io.cnt import rea...
[ "mne.datasets.testing.data_path", "mne.pick_types", "mne.io.cnt.read_raw_cnt", "os.path.join", "mne.io.tests.test_raw._test_raw_reader", "pytest.warns", "numpy.array", "numpy.testing.assert_array_equal", "mne.annotations.read_annotations" ]
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import urllib.request, json import pandas as pd baseUrl = 'https://avoindata.eduskunta.fi/api/v1/tables/VaskiData' parameters = 'rows?columnName=Eduskuntatunnus&columnValue=LA%25&perPage=100' page = 0 df = '' while True: print(f'Fetching page number {page}') with urllib.request.urlopen(f'{baseUrl}/{parameters...
[ "pandas.DataFrame" ]
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# -*- coding: utf-8 -*- """ Created on Mon Sep 20 16:15:37 2021 @author: em42363 """ # In[1]: Import functions ''' CatBoost is a high-performance open source library for gradient boosting on decision trees ''' from catboost import CatBoostRegressor from sklearn.model_selection import train_test_split import pandas a...
[ "numpy.mean", "sys.path.insert", "numpy.sqrt", "UTuning.scorer.Precision", "pandas.read_csv", "sklearn.model_selection.train_test_split", "UTuning.scorer.Accuracy", "numpy.asarray", "UTuning.plots.error_accuracy_plot", "catboost.CatBoostRegressor", "os.path.dirname", "numpy.linspace", "UTuni...
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import logging from platform import system from tqdm import tqdm from multiprocessing import Lock loggers = {} # https://stackoverflow.com/questions/38543506/ class TqdmLoggingHandler(logging.Handler): def __init__(self, level=logging.NOTSET): super(TqdmLoggingHandler, self).__init__(level) def emit...
[ "logging.getLogger", "tqdm.tqdm.write", "logging.Formatter", "platform.system", "logging.getLevelName", "multiprocessing.Lock" ]
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import cv2 import sys import playsound face_cascade = cv2.CascadeClassifier('cascades/haarcascade_frontalface_default.xml') # capture video using cv2 video_capture = cv2.VideoCapture(0) while True: # capture frame by frame, i.e, one by one ret, frame = video_capture.read() gray = cv2.cvtColor(frame...
[ "cv2.rectangle", "playsound.playsound", "cv2.imshow", "cv2.VideoCapture", "cv2.cvtColor", "sys.exit", "cv2.CascadeClassifier", "cv2.waitKey" ]
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# vim:set et sw=4 ts=4: import logging import sys import jmespath from . import sis, classes # logging logging.basicConfig(stream=sys.stdout, level=logging.WARNING) logger = logging.getLogger(__name__) # SIS endpoint enrollments_uri = "https://apis.berkeley.edu/sis/v2/enrollments" # apparently some courses have LA...
[ "logging.basicConfig", "jmespath.search", "logging.getLogger" ]
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from flatland.envs.agent_utils import RailAgentStatus from flatland.envs.malfunction_generators import malfunction_from_params, MalfunctionParameters from flatland.envs.observations import GlobalObsForRailEnv from flatland.envs.rail_env import RailEnv from flatland.envs.rail_generators import sparse_rail_generator from...
[ "os.path.exists", "PIL.Image.fromarray", "msgpack.load", "flatland.envs.schedule_generators.sparse_schedule_generator", "argparse.ArgumentParser", "flatland.envs.observations.GlobalObsForRailEnv", "os.makedirs", "msgpack.dump", "flatland.envs.malfunction_generators.malfunction_from_params", "rando...
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# -*- coding: utf-8 -*- # Generated by Django 2.2.4 on 2019-08-21 19:53 # this file is auto-generated so don't do flake8 on it # flake8: noqa from __future__ import absolute_import, unicode_literals from django.db import migrations, models import django.utils.timezone def copy_date_done_to_date_created(apps, schem...
[ "django.db.models.DateTimeField", "django.db.migrations.RunPython", "django.db.models.F" ]
[((1351, 1447), 'django.db.migrations.RunPython', 'migrations.RunPython', (['copy_date_done_to_date_created', 'reverse_copy_date_done_to_date_created'], {}), '(copy_date_done_to_date_created,\n reverse_copy_date_done_to_date_created)\n', (1371, 1447), False, 'from django.db import migrations, models\n'), ((522, 543)...
import torch.nn as nn from utils.BBBlayers import BBBConv2d, BBBLinearFactorial, FlattenLayer class BBB3Conv3FC(nn.Module): """ Simple Neural Network having 3 Convolution and 3 FC layers with Bayesian layers. """ def __init__(self, outputs, inputs): super(BBB3Conv3FC, self).__init__() ...
[ "torch.nn.Softplus", "utils.BBBlayers.FlattenLayer", "torch.nn.ModuleList", "utils.BBBlayers.BBBLinearFactorial", "utils.BBBlayers.BBBConv2d", "torch.nn.MaxPool2d" ]
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import os from tensorflow.contrib.learn.python.learn.datasets import base import numpy as np import IPython from subprocess import call from keras.preprocessing import image from influence.dataset import DataSet from influence.inception_v3 import preprocess_input BASE_DIR = 'data' # TODO: change def fill(X, Y, id...
[ "keras.preprocessing.image.img_to_array", "numpy.arange", "influence.inception_v3.preprocess_input", "os.path.exists", "numpy.savez", "os.listdir", "numpy.reshape", "subprocess.call", "numpy.random.seed", "numpy.concatenate", "numpy.savez_compressed", "os.rename", "tensorflow.contrib.learn.p...
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import OpenPNM import numpy as np import OpenPNM.Physics.models as pm class GenericLinearTransportTest: def setup_class(self): self.net = OpenPNM.Network.Cubic(shape=[5, 5, 5]) self.phase = OpenPNM.Phases.GenericPhase(network=self.net) Ps = self.net.Ps Ts = self.net.Ts self...
[ "OpenPNM.Physics.GenericPhysics", "numpy.ones", "OpenPNM.Algorithms.GenericLinearTransport", "numpy.absolute", "numpy.size", "OpenPNM.Network.Cubic", "numpy.sum", "numpy.zeros", "OpenPNM.Phases.GenericPhase", "numpy.array", "numpy.isnan", "numpy.concatenate", "numpy.all", "numpy.arange" ]
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from optimizer.utils.intbounds import IntBounds class TestIntBounds(object): def test_make_gt(self): i0 = IntBounds() i1 = i0.make_gt(IntBounds(10, 10)) assert i1.lower == 11 def test_make_gt_already_bounded(self): i0 = IntBounds() i1 = i0.make_gt(IntBounds(10, 10))...
[ "optimizer.utils.intbounds.IntBounds" ]
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from libTask import Queue from common import configParams from common import common def main(): cp = configParams.ConfigParams("config.json") detectGeneralQueue = Queue.DQueue(cp, len(cp.detect_general_ids), cp.modelPath, common.GENERALDETECT_METHOD_ID, cp.GPUDevices, cp.detect_g...
[ "common.configParams.ConfigParams" ]
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import torch, torchvision import detectron2 from detectron2.utils.logger import setup_logger setup_logger() # import some common libraries import numpy as np import os, json, cv2, random # import some common detectron2 utilities from detectron2 import model_zoo from detectron2.engine import DefaultPredic...
[ "detectron2.config.get_cfg", "argparse.ArgumentParser", "detectron2.model_zoo.get_checkpoint_url", "detectron2.model_zoo.get_config_file", "detectron2.data.MetadataCatalog.get", "time.time", "detectron2.engine.DefaultPredictor", "cv2.imread", "detectron2.utils.logger.setup_logger" ]
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"""AMQP Table Encoding/Decoding""" import struct import decimal import calendar from datetime import datetime from pika import exceptions from pika.compat import unicode_type, PY2, long, as_bytes def encode_short_string(pieces, value): """Encode a string value as short string and append it to pieces list ret...
[ "pika.exceptions.ShortStringTooLong", "pika.exceptions.InvalidFieldTypeException", "pika.compat.as_bytes", "struct.pack", "pika.exceptions.UnsupportedAMQPFieldException", "decimal.Decimal", "struct.unpack_from" ]
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from pylaas_core.abstract.abstract_service import AbstractService import time from pylaas_core.interface.technical.container_configurable_aware_interface import ContainerConfigurableAwareInterface class DummyConfigurable(AbstractService, ContainerConfigurableAwareInterface): def __init__(self) -> None: ...
[ "time.time" ]
[((375, 386), 'time.time', 'time.time', ([], {}), '()\n', (384, 386), False, 'import time\n')]
from django.urls import reverse_lazy, reverse from django.utils.decorators import method_decorator from django.views.generic import ListView, DetailView, CreateView, DeleteView, UpdateView from .models import BlogPost from django.contrib.auth.decorators import login_required class BlogPostHomeView(ListView): mode...
[ "django.urls.reverse", "django.utils.decorators.method_decorator", "django.urls.reverse_lazy" ]
[((464, 513), 'django.utils.decorators.method_decorator', 'method_decorator', (['login_required'], {'name': '"""dispatch"""'}), "(login_required, name='dispatch')\n", (480, 513), False, 'from django.utils.decorators import method_decorator\n'), ((708, 757), 'django.utils.decorators.method_decorator', 'method_decorator'...
# Copyright (c) 2016 <NAME>, 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...
[ "manila.context.get_admin_context", "manila.tests.db_utils.create_snapshot_instance", "manila.share.snapshot_access.ShareSnapshotInstanceAccess", "mock.Mock", "manila.utils.IsAMatcher", "manila.tests.db_utils.create_share", "ddt.data", "copy.deepcopy", "manila.tests.db_utils.create_snapshot" ]
[((1617, 1709), 'ddt.data', 'ddt.data', (['constants.ACCESS_STATE_QUEUED_TO_APPLY', 'constants.ACCESS_STATE_QUEUED_TO_DENY'], {}), '(constants.ACCESS_STATE_QUEUED_TO_APPLY, constants.\n ACCESS_STATE_QUEUED_TO_DENY)\n', (1625, 1709), False, 'import ddt\n'), ((1190, 1250), 'manila.share.snapshot_access.ShareSnapshotIn...
# This sample tests the type checker's reportUnnecessaryCast feature. from typing import cast, Union def foo(a: int): # This should generate an error if # reportUnnecessaryCast is enabled. b = cast(int, a) c: Union[int, str] = "hello" d = cast(int, c)
[ "typing.cast" ]
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from http import HTTPStatus from typing import Iterable, Union, Mapping from flask import request from flask_restful import Resource, fields, marshal from metadata_service.proxy import get_proxy_client popular_table_fields = { 'database': fields.String, 'cluster': fields.String, 'schema': fields.String, ...
[ "flask.request.args.get", "flask_restful.fields.String", "flask_restful.fields.Nested", "flask_restful.marshal", "metadata_service.proxy.get_proxy_client" ]
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import requests import logging import cfscrape import os from manhwaDownloader.constants import CONSTANTS as CONST logging.basicConfig(level=logging.DEBUG) folderPath = os.path.join(CONST.OUTPUTPATH, 'serious-taste-of-forbbiden-fruit') logging.info(len([file for file in os.walk(folderPath)])) walkList = [file for fi...
[ "logging.basicConfig", "os.path.join", "os.walk" ]
[((116, 156), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.DEBUG'}), '(level=logging.DEBUG)\n', (135, 156), False, 'import logging\n'), ((171, 237), 'os.path.join', 'os.path.join', (['CONST.OUTPUTPATH', '"""serious-taste-of-forbbiden-fruit"""'], {}), "(CONST.OUTPUTPATH, 'serious-taste-of-forbbi...
# define custom R2 metrics for Keras backend from keras import backend as K def r2_keras(y_true, y_pred): SS_res = K.sum(K.square( y_true - y_pred )) SS_tot = K.sum(K.square( y_true - K.mean(y_true) ) ) return ( 1 - SS_res/(SS_tot + K.epsilon()) ) # base model architecture definition def model(): ...
[ "pandas.read_csv", "keras.layers.GlobalMaxPooling1D", "numpy.array", "keras.layers.Activation", "keras.layers.Dense", "keras.preprocessing.sequence.pad_sequences", "sklearn.decomposition.FastICA", "sklearn.model_selection.KFold", "xgboost.sklearn.XGBRegressor", "sklearn.metrics.r2_score", "numpy...
[((1722, 1755), 'pandas.read_csv', 'pd.read_csv', (['"""../input/train.csv"""'], {}), "('../input/train.csv')\n", (1733, 1755), True, 'import pandas as pd\n'), ((1763, 1795), 'pandas.read_csv', 'pd.read_csv', (['"""../input/test.csv"""'], {}), "('../input/test.csv')\n", (1774, 1795), True, 'import pandas as pd\n'), ((1...
# Copyright 2020 Huawei Technologies Co., Ltd # # 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...
[ "mindspore.common.api._cell_graph_executor.compile", "numpy.ones", "mindspore.ops.operations.Mul", "mindspore.nn.TrainOneStepCell", "mindspore.ops.operations.MatMul", "mindspore.ops.operations.Reshape", "mindspore.context.reset_auto_parallel_context", "pytest.raises", "mindspore.common.initializer.i...
[((2366, 2381), 'numpy.ones', 'np.ones', (['[8, 8]'], {}), '([8, 8])\n', (2373, 2381), True, 'import numpy as np\n'), ((2411, 2427), 'numpy.ones', 'np.ones', (['[64, 8]'], {}), '([64, 8])\n', (2418, 2427), True, 'import numpy as np\n'), ((2569, 2601), 'mindspore.nn.TrainOneStepCell', 'TrainOneStepCell', (['net', 'optim...
# -*- coding: utf-8 -*- """ Created on Mon Sep 7 10:59:00 2020 @author: user """ import numpy as np import multiprocessing as mp import matplotlib.pyplot as plt import time import itertools import ctypes def formfactor(args): # with AL_dist_flat_glo.get_lock: AL_dist_flat_glo_r = np.frombuffer(AL_dist_flat_...
[ "matplotlib.pyplot.savefig", "matplotlib.pyplot.xscale", "matplotlib.pyplot.ylabel", "matplotlib.pyplot.show", "matplotlib.pyplot.xlabel", "matplotlib.pyplot.plot", "multiprocessing.Value", "numpy.subtract", "matplotlib.pyplot.yscale", "matplotlib.pyplot.figure", "numpy.array", "multiprocessin...
[((1464, 1493), 'numpy.load', 'np.load', (['"""./AL_dist_flat.npy"""'], {}), "('./AL_dist_flat.npy')\n", (1471, 1493), True, 'import numpy as np\n'), ((1582, 1605), 'numpy.logspace', 'np.logspace', (['(-2)', '(3)', '(100)'], {}), '(-2, 3, 100)\n', (1593, 1605), True, 'import numpy as np\n'), ((1782, 1807), 'multiproces...
# coding: utf-8 import io import cairo # pycairo import cairocffi from pycairo_to_cairocffi import _UNSAFE_pycairo_context_to_cairocffi from cairocffi_to_pycairo import _UNSAFE_cairocffi_context_to_pycairo import pango_example def test(): cairocffi_context = cairocffi.Context(cairocffi.PDFSurface(N...
[ "cairocffi.PDFSurface", "pango_example.write_example_pdf", "io.BytesIO", "pycairo_to_cairocffi._UNSAFE_pycairo_context_to_cairocffi", "cairocffi_to_pycairo._UNSAFE_cairocffi_context_to_pycairo" ]
[((392, 447), 'cairocffi_to_pycairo._UNSAFE_cairocffi_context_to_pycairo', '_UNSAFE_cairocffi_context_to_pycairo', (['cairocffi_context'], {}), '(cairocffi_context)\n', (428, 447), False, 'from cairocffi_to_pycairo import _UNSAFE_cairocffi_context_to_pycairo\n'), ((474, 527), 'pycairo_to_cairocffi._UNSAFE_pycairo_conte...
import random goat1 = random.randint(1, 3) goat2 = random.randint(1, 3) while goat1 == goat2: goat2 = random.randint(1, 3) success = 0 tries = 1_000_000 for _ in range(tries): options = [1, 2, 3] choice = random.randint(1, 3) options.remove(choice) if choice == goat1: options.remove(goat...
[ "random.randint" ]
[((23, 43), 'random.randint', 'random.randint', (['(1)', '(3)'], {}), '(1, 3)\n', (37, 43), False, 'import random\n'), ((52, 72), 'random.randint', 'random.randint', (['(1)', '(3)'], {}), '(1, 3)\n', (66, 72), False, 'import random\n'), ((108, 128), 'random.randint', 'random.randint', (['(1)', '(3)'], {}), '(1, 3)\n', ...
#!/usr/bin/env python3 import random N = 32 M = 64 # NOTE: 0 is a reserved value randu = lambda x: random.randint(1, 2**x-1) randU32 = lambda: randu(32) randU64 = lambda: randu(64) fmt_by_dtype = { 'u32hex': '0x{:08x}', 'u64hex': '0x{:016x}', } cpp_by_dtype = { 'u32hex': 'uint32_t', 'u64hex': 'ui...
[ "random.randint" ]
[((105, 134), 'random.randint', 'random.randint', (['(1)', '(2 ** x - 1)'], {}), '(1, 2 ** x - 1)\n', (119, 134), False, 'import random\n')]
# ------------------------------------------------------------------ # # RDF and CN related analysis # # ------------------------------------------------------------------ import sys py_path = '../../../../postprocessing/' sys.path.insert(0, py_path) py_path = '../../../../postprocessing/io_operations/' sys.path.inse...
[ "cn_and_rdf_lmp.compute_time_average", "sys.path.insert" ]
[((225, 252), 'sys.path.insert', 'sys.path.insert', (['(0)', 'py_path'], {}), '(0, py_path)\n', (240, 252), False, 'import sys\n'), ((307, 334), 'sys.path.insert', 'sys.path.insert', (['(0)', 'py_path'], {}), '(0, py_path)\n', (322, 334), False, 'import sys\n'), ((565, 623), 'cn_and_rdf_lmp.compute_time_average', 'crl....
""" Test the integrations related to the internal interface implementation and the 'Interface' interface itself """ import pytest from cppython_core.schema import InterfaceConfiguration from pytest_cppython.plugin import InterfaceIntegrationTests from cppython.console import ConsoleInterface class TestCLIInterface(...
[ "pytest.fixture", "cppython_core.schema.InterfaceConfiguration", "cppython.console.ConsoleInterface" ]
[((406, 438), 'pytest.fixture', 'pytest.fixture', ([], {'name': '"""interface"""'}), "(name='interface')\n", (420, 438), False, 'import pytest\n'), ((688, 712), 'cppython_core.schema.InterfaceConfiguration', 'InterfaceConfiguration', ([], {}), '()\n', (710, 712), False, 'from cppython_core.schema import InterfaceConfig...
#@contact <NAME> (<EMAIL>), Georgia Institute of Technology #@version 1.0 #@date 2021-08-17 #Influence-guided Data Augmentation for Neural Tensor Completion (DAIN) #This software is free of charge under research purposes. #For commercial purposes, please contact the main author. import torch from torch imp...
[ "torch.mul", "model.MLP", "torch.from_numpy", "torch.pow", "torch.nn.MSELoss", "torch.cuda.is_available", "torch.sum", "copy.deepcopy", "numpy.arange", "os.path.exists", "argparse.ArgumentParser", "os.mkdir", "sklearn.model_selection.train_test_split", "torch.empty", "torch.cuda.empty_ca...
[((636, 708), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Run DAIN for the MLP architecture"""'}), "(description='Run DAIN for the MLP architecture')\n", (659, 708), False, 'import argparse\n'), ((2034, 2046), 'torch.nn.MSELoss', 'nn.MSELoss', ([], {}), '()\n', (2044, 2046), False, 'f...
from datetime import datetime, timedelta import jwt from flask import current_app from app import db from app.user.repository import UserRepository class AuthService: def __init__(self) -> None: self._user_repository = UserRepository(db.session) def create_token(self, data) -> dict: user = ...
[ "jwt.decode", "datetime.timedelta", "app.user.repository.UserRepository", "datetime.datetime.utcnow" ]
[((235, 261), 'app.user.repository.UserRepository', 'UserRepository', (['db.session'], {}), '(db.session)\n', (249, 261), False, 'from app.user.repository import UserRepository\n'), ((1267, 1340), 'jwt.decode', 'jwt.decode', (['token', "current_app.config['SECRET_KEY']"], {'algorithms': "['HS512']"}), "(token, current_...
import os from Bio import AlignIO, Phylo from Bio.Phylo.TreeConstruction import DistanceCalculator, DistanceTreeConstructor class Phylogenetic: def __init__(self, PATH): self.PATH=PATH def binary_sequence_generator(self, input_kmer_pattern, label): string_inp="".join([ 'A' if x==0 else 'C'...
[ "Bio.Phylo.TreeConstruction.DistanceTreeConstructor", "os.path.join", "Bio.Phylo.TreeConstruction.DistanceCalculator" ]
[((850, 880), 'Bio.Phylo.TreeConstruction.DistanceCalculator', 'DistanceCalculator', (['"""identity"""'], {}), "('identity')\n", (868, 880), False, 'from Bio.Phylo.TreeConstruction import DistanceCalculator, DistanceTreeConstructor\n'), ((1047, 1072), 'Bio.Phylo.TreeConstruction.DistanceTreeConstructor', 'DistanceTreeC...
import torch import functools if torch.__version__.startswith('0'): from .sync_bn.inplace_abn.bn import InPlaceABNSync BatchNorm2d = functools.partial(InPlaceABNSync, activation='none') BatchNorm2d_class = InPlaceABNSync relu_inplace = False else: # BatchNorm2d_class = BatchNorm2d = torch.nn.SyncBa...
[ "torch.__version__.startswith", "functools.partial" ]
[((34, 67), 'torch.__version__.startswith', 'torch.__version__.startswith', (['"""0"""'], {}), "('0')\n", (62, 67), False, 'import torch\n'), ((142, 194), 'functools.partial', 'functools.partial', (['InPlaceABNSync'], {'activation': '"""none"""'}), "(InPlaceABNSync, activation='none')\n", (159, 194), False, 'import fun...
import os import sys import numpy as np import pandas as pd def get_columns_percent_dataframe(df: pd.DataFrame, totals_column=None, percent_names=True) -> pd.DataFrame: """ @param totals_column: (default = use sum of columns) @param percent_names: Rename names from 'col' => 'col %' Return a dataframe...
[ "pandas.read_csv", "numpy.isnan", "pandas.DataFrame", "os.stat", "pandas.notnull" ]
[((407, 435), 'pandas.DataFrame', 'pd.DataFrame', ([], {'index': 'df.index'}), '(index=df.index)\n', (419, 435), True, 'import pandas as pd\n'), ((1630, 1643), 'numpy.isnan', 'np.isnan', (['val'], {}), '(val)\n', (1638, 1643), True, 'import numpy as np\n'), ((1756, 1770), 'pandas.notnull', 'pd.notnull', (['df'], {}), '...
from SemiBin.main import generate_data_single import os import pytest import logging import pandas as pd def test_generate_data_coassembly(): logger = logging.getLogger('SemiBin') logger.setLevel(logging.INFO) sh = logging.StreamHandler() sh.setFormatter(logging.Formatter('%(asctime)s - %(message)s')) ...
[ "logging.getLogger", "logging.StreamHandler", "pandas.read_csv", "os.makedirs", "logging.Formatter", "SemiBin.main.generate_data_single" ]
[((156, 184), 'logging.getLogger', 'logging.getLogger', (['"""SemiBin"""'], {}), "('SemiBin')\n", (173, 184), False, 'import logging\n'), ((228, 251), 'logging.StreamHandler', 'logging.StreamHandler', ([], {}), '()\n', (249, 251), False, 'import logging\n'), ((351, 398), 'os.makedirs', 'os.makedirs', (['"""output_coass...
#!/usr/bin/env python # -*- coding: utf-8 -*- import sys from cx_Freeze import setup,Executable icondata='icon.ico' base = None # GUI=有効, CUI=無効 にする if sys.platform == 'win32' : base = 'win32GUI' exe = Executable(script = 'main.py', base = base, #icon=icondata ...
[ "cx_Freeze.Executable", "cx_Freeze.setup" ]
[((209, 248), 'cx_Freeze.Executable', 'Executable', ([], {'script': '"""main.py"""', 'base': 'base'}), "(script='main.py', base=base)\n", (219, 248), False, 'from cx_Freeze import setup, Executable\n'), ((326, 423), 'cx_Freeze.setup', 'setup', ([], {'name': '"""MSman"""', 'version': '"""0.1"""', 'description': '"""Mine...
from __future__ import division import numpy as np import matplotlib.pyplot as plt import shellmodelutilities as smutil # Set bin width and range bin_width = 0.20 Emax = 14 Nbins = int(np.ceil(Emax/bin_width)) Emax_adjusted = bin_width*Nbins # Trick to get an integer number of bins bins = np.linspace(0,Emax_adjust...
[ "shellmodelutilities.read_energy_levels", "numpy.ceil", "numpy.floor", "numpy.linspace", "matplotlib.pyplot.FuncFormatter", "matplotlib.colors.LogNorm", "matplotlib.pyplot.subplots", "matplotlib.pyplot.show" ]
[((295, 335), 'numpy.linspace', 'np.linspace', (['(0)', 'Emax_adjusted', '(Nbins + 1)'], {}), '(0, Emax_adjusted, Nbins + 1)\n', (306, 335), True, 'import numpy as np\n'), ((498, 516), 'matplotlib.pyplot.subplots', 'plt.subplots', (['(1)', '(1)'], {}), '(1, 1)\n', (510, 516), True, 'import matplotlib.pyplot as plt\n'),...
# Licensed under a 3-clause BSD style license - see LICENSE.rst """ sbpy bandpass Module """ __all__ = [ 'bandpass' ] import os from astropy.utils.data import get_pkg_data_filename def bandpass(name): """Retrieve bandpass transmission spectrum from sbpy. Parameters ---------- name : string ...
[ "synphot.SpectralElement.from_file" ]
[((4891, 4928), 'synphot.SpectralElement.from_file', 'synphot.SpectralElement.from_file', (['fn'], {}), '(fn)\n', (4924, 4928), False, 'import synphot\n')]
from django.http import HttpResponse from django.shortcuts import render, redirect from community.models import Community # Create your views here. def search_basic(request): communities = None if request.POST: community_query = request.POST.get('community_search', False) communities = Commun...
[ "django.shortcuts.render", "community.models.Community.objects.filter" ]
[((499, 572), 'django.shortcuts.render', 'render', (['request', '"""search/search_basic.html"""', "{'communities': communities}"], {}), "(request, 'search/search_basic.html', {'communities': communities})\n", (505, 572), False, 'from django.shortcuts import render, redirect\n'), ((314, 371), 'community.models.Community...
# OxfordInstruments_ILM200.py class, to perform the communication between the Wrapper and the device # Copyright (c) 2017 QuTech (Delft) # Code is available under the available under the `MIT open-source license <https://opensource.org/licenses/MIT>`__ # # <NAME> <<EMAIL>>, 2017 # <NAME> <<EMAIL>>, 2016 # <NAME> <<EMAI...
[ "logging.info", "logging.debug", "time.sleep" ]
[((1353, 1407), 'logging.debug', 'logging.debug', (["(__name__ + ' : Initializing instrument')"], {}), "(__name__ + ' : Initializing instrument')\n", (1366, 1407), False, 'import logging\n'), ((2719, 2807), 'logging.info', 'logging.info', (["(__name__ + ' : Send the following command to the device: %s' % message)"], {}...
# This file is Copyright 2019 Volatility Foundation and licensed under the Volatility Software License 1.0 # which is available at https://www.volatilityfoundation.org/license/vsl-v1.0 # """A module containing a collection of plugins that produce data typically found in Mac's lsmod command.""" from volatility3.framewor...
[ "volatility3.framework.renderers.format_hints.Hex", "volatility3.framework.configuration.requirements.TranslationLayerRequirement", "volatility3.framework.objects.utility.array_to_string", "volatility3.framework.configuration.requirements.SymbolTableRequirement", "volatility3.framework.contexts.Module" ]
[((1706, 1761), 'volatility3.framework.contexts.Module', 'contexts.Module', (['context', 'darwin_symbols', 'layer_name', '(0)'], {}), '(context, darwin_symbols, layer_name, 0)\n', (1721, 1761), False, 'from volatility3.framework import renderers, interfaces, contexts\n'), ((810, 952), 'volatility3.framework.configurati...
"""Subdivided icosahedral mesh generation""" from __future__ import print_function import numpy as np # following: http://blog.andreaskahler.com/2009/06/creating-icosphere-mesh-in-code.html # hierarchy: # Icosphere -> Triangle -> Point class IcoSphere: """ Usage: IcoSphere(level) Maximum supported level =...
[ "numpy.sqrt", "numpy.asarray", "numpy.arcsin", "numpy.array", "matplotlib.pyplot.figure", "numpy.arctan2", "numpy.cos", "numpy.linalg.norm", "numpy.sin", "matplotlib.pyplot.show" ]
[((7381, 7414), 'numpy.sqrt', 'np.sqrt', (['(x ** 2 + y ** 2 + z ** 2)'], {}), '(x ** 2 + y ** 2 + z ** 2)\n', (7388, 7414), True, 'import numpy as np\n'), ((5460, 5472), 'matplotlib.pyplot.figure', 'plt.figure', ([], {}), '()\n', (5470, 5472), True, 'import matplotlib.pyplot as plt\n'), ((5538, 5580), 'numpy.asarray',...
#!/usr/bin/env python # Copyright JS Foundation and other contributors, http://js.foundation # # 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....
[ "os.path.exists", "os.makedirs", "os.path.join", "os.symlink", "os.path.splitext", "os.getcwd", "os.path.normpath", "os.path.split", "sys.exit", "fnmatch.filter", "os.path.islink", "os.path.abspath", "os.walk", "os.path.relpath" ]
[((2005, 2036), 'os.path.join', 'os.path.join', (['root_dir', 'sub_dir'], {}), '(root_dir, sub_dir)\n', (2017, 2036), False, 'import os\n'), ((2092, 2108), 'os.walk', 'os.walk', (['src_dir'], {}), '(src_dir)\n', (2099, 2108), False, 'import os\n'), ((3803, 3825), 'os.path.normpath', 'os.path.normpath', (['path'], {}), ...
from math import sqrt import emoji num = int(input("Digite um número: ")) raiz = sqrt(num) print("A raiz do número {0} é {1:.2f}.".format(num, raiz)) print(emoji.emojize("Hello World! :earth_americas:", use_aliases=True))
[ "emoji.emojize", "math.sqrt" ]
[((81, 90), 'math.sqrt', 'sqrt', (['num'], {}), '(num)\n', (85, 90), False, 'from math import sqrt\n'), ((156, 220), 'emoji.emojize', 'emoji.emojize', (['"""Hello World! :earth_americas:"""'], {'use_aliases': '(True)'}), "('Hello World! :earth_americas:', use_aliases=True)\n", (169, 220), False, 'import emoji\n')]
from __future__ import print_function import argparse import os import time, platform import cv2 import torch import torch.optim as optim from torch.utils.data import DataLoader from datasets import DATASET_NAMES, BipedDataset, TestDataset, dataset_info from losses import * from model import DexiNed # from model0C ...
[ "torch.cuda.device_count", "model.DexiNed", "datasets.dataset_info", "torch.utils.tensorboard.SummaryWriter", "time.ctime", "argparse.ArgumentParser", "platform.system", "utils.visualize_result", "cv2.putText", "os.path.isfile", "utils.save_image_batch_to_disk", "time.time", "torch.cuda.empt...
[((655, 699), 'os.path.join', 'os.path.join', (['args.output_dir', '"""current_res"""'], {}), "(args.output_dir, 'current_res')\n", (667, 699), False, 'import os\n'), ((704, 747), 'os.makedirs', 'os.makedirs', (['imgs_res_folder'], {'exist_ok': '(True)'}), '(imgs_res_folder, exist_ok=True)\n', (715, 747), False, 'impor...
from __future__ import absolute_import from django.conf.urls import patterns, url from django_comments.feeds import LatestCommentFeed from custom_comments import views feeds = { 'comments': LatestCommentFeed, } urlpatterns = patterns('', url(r'^post/$', views.custom_submit_comment), url(r'^flag/(\d+)...
[ "django.conf.urls.url", "django_comments.feeds.LatestCommentFeed" ]
[((253, 296), 'django.conf.urls.url', 'url', (['"""^post/$"""', 'views.custom_submit_comment'], {}), "('^post/$', views.custom_submit_comment)\n", (256, 296), False, 'from django.conf.urls import patterns, url\n'), ((303, 351), 'django.conf.urls.url', 'url', (['"""^flag/(\\\\d+)/$"""', 'views.custom_flag_comment'], {})...
from __future__ import division from cctbx.array_family import flex from cctbx import xray from cctbx import crystal from cctbx import maptbx from cctbx.maptbx import minimization from libtbx.test_utils import approx_equal import random from cctbx.development import random_structure from cctbx import sgtbx if (1): r...
[ "cctbx.sgtbx.space_group_info", "random.seed", "libtbx.test_utils.approx_equal", "cctbx.array_family.flex.set_random_seed", "cctbx.xray.scatterer", "cctbx.crystal.symmetry", "cctbx.maptbx.minimization.run" ]
[((319, 333), 'random.seed', 'random.seed', (['(0)'], {}), '(0)\n', (330, 333), False, 'import random\n'), ((336, 359), 'cctbx.array_family.flex.set_random_seed', 'flex.set_random_seed', (['(0)'], {}), '(0)\n', (356, 359), False, 'from cctbx.array_family import flex\n'), ((397, 475), 'cctbx.crystal.symmetry', 'crystal....
from pytest import raises from datek_app_utils.env_config.base import BaseConfig from datek_app_utils.env_config.errors import InstantiationForbiddenError class SomeOtherMixinWhichDoesntRelateToEnvConfig: color = "red" class TestConfig: def test_iter(self, monkeypatch, key_volume, base_config_class): ...
[ "pytest.raises" ]
[((1550, 1585), 'pytest.raises', 'raises', (['InstantiationForbiddenError'], {}), '(InstantiationForbiddenError)\n', (1556, 1585), False, 'from pytest import raises\n')]
# -*- coding: utf-8 -*- # Name: comprehend # Version: 0.1a2 # Owner: <NAME> # Maintainer(s): import boto3 def get_sentiment(text, language_code='en'): """Get sentiment. Inspects text and returns an inference of the prevailing sentiment (positive, neutral, mixed, or negative). Args: text: UT...
[ "boto3.client" ]
[((825, 851), 'boto3.client', 'boto3.client', (['"""comprehend"""'], {}), "('comprehend')\n", (837, 851), False, 'import boto3\n')]
from sys import argv from getopt import getopt from os import R_OK, access from string import Template DEFAULT_DATASET_FILE_PATH = "dataset/data.csv" DEFAULT_DATASET_COLUMNS = ['surface (m2)', 'height (m)', 'latitude', 'housing_type', 'longitude', 'country_code', 'city'] DEFAULT_VISU = ["sca...
[ "getopt.getopt", "os.access", "string.Template" ]
[((407, 480), 'getopt.getopt', 'getopt', (['argv[1:]', '"""dc"""', "['dataset-file=', 'columns=', 'visus=', 'range=']"], {}), "(argv[1:], 'dc', ['dataset-file=', 'columns=', 'visus=', 'range='])\n", (413, 480), False, 'from getopt import getopt\n'), ((1149, 1175), 'os.access', 'access', (['dataset_file', 'R_OK'], {}), ...
# Must run example4.py first # Read an Excel sheet and save running config of devices using pandas import pandas as pd from netmiko import ConnectHandler # Read Excel file of .xlsx format data = pd.read_excel(io="Example4-Device-Details.xlsx", sheet_name=0) # Convert data to data frame df = pd.DataFrame(data=data) ...
[ "pandas.DataFrame", "netmiko.ConnectHandler", "pandas.read_excel" ]
[((198, 260), 'pandas.read_excel', 'pd.read_excel', ([], {'io': '"""Example4-Device-Details.xlsx"""', 'sheet_name': '(0)'}), "(io='Example4-Device-Details.xlsx', sheet_name=0)\n", (211, 260), True, 'import pandas as pd\n'), ((296, 319), 'pandas.DataFrame', 'pd.DataFrame', ([], {'data': 'data'}), '(data=data)\n', (308, ...
"""Utilities for interacting with GitHub""" import os import json import webbrowser import stat import sys from git import Repo from .context import Context event_dict = { "added_to_project": ( lambda event: "{} added the issue to a project.".format(event["actor"]["login"]) ), "assigned": ( ...
[ "os.path.expanduser", "json.loads", "os.makedirs", "git.Repo.clone_from", "webbrowser.open", "os.chmod", "os.path.isfile", "os.path.isdir", "sys.exit", "json.dump" ]
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# Generated by Django 3.0.7 on 2020-09-18 05:52 from django.conf import settings from django.db import migrations, models import django.db.models.deletion import multiselectfield.db.fields class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(setting...
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import pytest import gen from dcos_installer import cli def test_default_arg_parser(): parser = cli.get_argument_parser().parse_args([]) assert parser.verbose is False assert parser.port == 9000 assert parser.action == 'genconf' def test_set_arg_parser(): argument_parser = cli.get_argument_pars...
[ "pytest.raises", "dcos_installer.cli.get_argument_parser" ]
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import hashlib import unittest from colicoords.cell import Cell, CellList from colicoords.preprocess import data_to_cells from test import testcase from test.test_functions import load_testdata class DataTest(testcase.ArrayTestCase): def setUp(self): self.data = load_testdata('ds1') def t...
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# --------------------------------------------------------------------------- # # Importing section # --------------------------------------------------------------------------- # import os import sys import argparse import logging import json from classes.alerts import SlackClient from influxdb import InfluxDBClient...
[ "logging.getLogger", "logging.basicConfig", "influxdb.InfluxDBClient", "classes.data_manager.DataManager", "argparse.ArgumentParser", "classes.alerts.SlackClient", "os.path.isfile", "sys.exit" ]
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- __author__ = 'ipetrash' import re DEBUG = False def merge_str_literal(text: str) -> str: def _on_match(m: re.Match): return m.group().replace('"+"', '') return re.sub(r'".+?"(\+".+?")+ ', _on_match, text) lines = """ function II1I1_II takes real I...
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from common.commons import * DATA_PATH = os.environ["DATA_PATH"] def core(): clusterPath = join(DATA_PATH, 'shapes') roots = listdir(clusterPath) roots = [i for i in roots if not (i.startswith('.') or i.endswith('.pickle'))] pattern = {} for root in roots: root sizes = listdir(join(...
[ "networkx.connected_component_subgraphs", "abstractPatch.loadPairMulti", "networkx.Graph", "pairs.shapePairs", "pairs.createPairs", "pairs.importShape" ]
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# -*- coding: utf-8 -*- import os import sys import tensorflow as tf import numpy as np import data_utils from translate import Transliteration from flask import Flask, request, jsonify transliteration = Transliteration() app = Flask(__name__) # Flask 객체 선언, 파라미터로 어플리케이션 패키지의 이름을 넣어 준다. app.config['JSON_AS_ASCII'] =...
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# -*- coding: utf-8 -*- {{{ # vim: set fenc=utf-8 ft=python sw=4 ts=4 sts=4 et: # # Copyright 2019, Battelle Memorial Institute. # # 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...
[ "logging.getLogger", "os.path.getsize", "statistics.stdev", "datetime.datetime.utcnow", "volttron.platform.agent.utils.vip_main", "volttron.platform.agent.utils.load_config", "volttron.platform.vip.agent.Core.receiver", "datetime.timedelta", "volttron.platform.agent.utils.setup_logging", "volttron...
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# -*- coding: utf-8 -*- """ Global app forms """ # Standard Library import re # Django Library from django import forms from django.contrib.auth.forms import UserChangeForm, UserCreationForm from django.utils.translation import ugettext_lazy as _ # Thirdparty Library from dal import autocomplete # Localfolder Librar...
[ "django.utils.translation.ugettext_lazy", "django.forms.IntegerField", "django.forms.CharField", "django.forms.TextInput" ]
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from unittest import mock import pytest from django.http import HttpRequest from rest_framework.response import Response from rest_framework.test import APIClient from drf_viewset_profiler.middleware import LineProfilerViewSetMiddleware @pytest.fixture def api_client(): return APIClient() @pytest.fixture def ...
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# This allows for running the example when the repo has been cloned import sys from os.path import abspath sys.path.extend([abspath(".")]) # Example code follows import logging import numpy as np import matplotlib.pyplot as plt import muDIC.vlab as vlab import muDIC as dic """ This example case runs an experiment whe...
[ "matplotlib.pyplot.ylabel", "muDIC.vlab.SyntheticImageGenerator", "numpy.array", "muDIC.ImageStack", "muDIC.Mesher", "matplotlib.pyplot.xlabel", "muDIC.DICAnalysis", "matplotlib.pyplot.title", "muDIC.vlab.rosta_speckle", "muDIC.DICInput", "matplotlib.pyplot.show", "logging.basicConfig", "mat...
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import urllib.request from bs4 import BeautifulSoup import csv import requests import os import json import time import glob files = glob.glob("/Users/nakamura/git/d_iiif/iiif/src/collections/nijl/data/json/*.json") for i in range(len(files)): file = files[i] file_id = file.split("/")[-1].replace(".json", "...
[ "os.path.exists", "requests.get", "glob.glob", "json.load", "json.dump" ]
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import numpy as np from sawyer.mujoco.tasks.base import ComposableTask class TransitionTask(ComposableTask): """ Task to pick up an object with the robot gripper. Success condition: - Object is grasped and has been lifted above the table """ def __init__(self): pass def compute_...
[ "numpy.array", "numpy.linalg.norm" ]
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import arcade import os SPRITE_SCALING = 0.5 SPRITE_NATIVE_SIZE = 128 SPRITE_SIZE = int(SPRITE_NATIVE_SIZE * SPRITE_SCALING) SCREEN_WIDTH = SPRITE_SIZE * 14 SCREEN_HEIGHT = SPRITE_SIZE * 10 MOVEMENT_SPEED = 5 COIN_SCALE = 0.7 class Room: """ This class holds all the information about the ...
[ "arcade.draw_text", "arcade.draw_texture_rectangle", "arcade.check_for_collision_with_list", "arcade.load_texture", "arcade.start_render", "arcade.load_sound", "os.chdir", "arcade.PhysicsEngineSimple", "arcade.AnimatedWalkingSprite", "arcade.run", "os.path.abspath", "arcade.SpriteList", "arc...
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# Copyright (c) 2018 gevent community # # 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, di...
[ "os.path.exists", "re.split", "os.listdir", "os.close", "psutil.Process", "unittest.SkipTest", "os.getpid", "os.system", "tempfile.mkstemp", "os.remove" ]
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from django.contrib.messages.constants import DEFAULT_LEVELS from user_messages.api import get_messages def messages(request): """ Return a lazy 'messages' context variable as well as 'DEFAULT_MESSAGE_LEVELS'. """ return { "messages": get_messages(request=request), "DEFAULT_MESSAG...
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# -*- coding: utf-8 -*- import matplotlib.pyplot as plt import numpy as np import pandas as pd from ..events import events_plot from ..stats import standardize as nk_standardize def signal_plot( signal, sampling_rate=None, subplots=False, standardize=False, labels=None, **kwargs ): """Plot signal with events...
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"""Only one validation per mission, user and actor Revision ID: <KEY> Revises: <KEY> Create Date: 2021-10-14 11:22:01.124488 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = "<KEY>" down_revision = "<KEY>" branch_labels = None depends_on = None def upgrade(): ...
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# Copyright 2020 <NAME> (Falcons) # SPDX-License-Identifier: Apache-2.0 #!/usr/bin/python import os import sys import argparse from rtdb2 import RtDB2Store, RTDB2_DEFAULT_PATH import rtdb2tools from hexdump import hexdump # Main structure of the program if __name__ == "__main__": # Argument parsing. descript...
[ "rtdb2tools.guessAgentId", "rtdb2.RtDB2Store", "argparse.ArgumentParser", "hexdump.hexdump" ]
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from __future__ import print_function from __future__ import division import os import gym import numpy as np from skimage.transform import resize from skimage.color import rgb2gray class Atari(object): s_dim = [84, 84, 1] a_dim = 3 def __init__(self, args, record_video=False): self.env = gym.m...
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# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not u...
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#!/usr/bin/env python3 import shlex from tkinter import * from tkinter import messagebox from psutil import Popen top = Tk() top.title("Franka Gripper Control") top.geometry("300x75") def open(): node_process = Popen(shlex.split('rosrun franka_interactive_controllers libfranka_gripper_run 1')) messagebox.showinfo...
[ "shlex.split", "tkinter.messagebox.showinfo" ]
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#!/usr/bin/env python """This tool builds or repacks the client binaries. This handles invocations for the build across the supported platforms including handling Visual Studio, pyinstaller and other packaging mechanisms. """ import logging import os import platform import time # pylint: disable=unused-import from ...
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# coding=utf-8 # Copyright 2022 The ML Fairness Gym Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicab...
[ "recsim.environments.interest_exploration.create_environment", "environments.recommenders.recsim_wrapper.RecsimWrapper", "absl.testing.absltest.main", "test_util.run_test_simulation" ]
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import argparse import csv import os from moss_client.core import submit_and_dl, parse_moss_reports data_folder = 'data' def handle_input(user_id, base_folder, parse, only_parse, join_file, batch): global data_folder abs_path = os.path.abspath(os.path.dirname(__file__)) root_data_folder = os.path.join(ab...
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#!/usr/bin/python # pylint: disable=W0223 """ Get a list of teams """ from html.parser import HTMLParser import requests class ChkTeams(HTMLParser): """ Extract team names from page """ def __init__(self): HTMLParser.__init__(self) self.retval = [] def handle_starttag(self, tag, a...
[ "html.parser.HTMLParser.__init__", "requests.get" ]
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import frappe @frappe.whitelist() def filt_itemby_supplier(doctype, txt, searchfield, start, page_len, filters): return frappe.db.sql("""Select parent from `tabItem Supplier` where supplier= %s""",(filters.get("supplier"))); @frappe.whitelist() def filteritem(doctype, txt, searchfield, start, page_len, filters...
[ "frappe.whitelist", "frappe.db.sql" ]
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import os import sys import unittest # Set Python search path to the parent directory sys.path.append(os.path.join(os.path.dirname(__file__), '..')) from lib.config import * class TestLibConfig(unittest.TestCase): def test_config_noconfigfile(self): config = BeaconConfigParser('not_exist.cfg') wit...
[ "unittest.main", "os.path.dirname" ]
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from kivy.uix.screenmanager import ScreenManager from kivy.uix.boxlayout import BoxLayout from kivy.lang.builder import Builder from kivy.animation import Animation from kivy.core.window import Window from kivymd.app import MDApp import kivymd import kivy print( ) def version(): kivy.require('2.0.0') print( )
[ "kivy.require" ]
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import functools import itertools import numbers from ..backend_object import BackendObject from ..annotation import Annotation def normalize_types_two_args(f): @functools.wraps(f) def normalizer(self, region, o): """ Convert any object to an object that we can process. """ if ...
[ "itertools.count", "functools.wraps" ]
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import logging from episodes import find_updates, db, count_all from logging import error as logi from flask import Flask, jsonify, request def create_app(config, debug=False, testing=False, config_overrides=None): app = Flask(__name__) app.config.from_object(config) app.config['JSON_AS_ASCII'] = False ...
[ "logging.basicConfig", "flask.request.args.get", "scraper.update_episodes", "flask.Flask", "episodes.db.close", "episodes.db.connect", "episodes.find_updates", "episodes.count_all", "logging.error", "flask.request.headers.get", "flask.jsonify" ]
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# -*- coding: utf-8 -*- # catapult: runs python scripts in already running processes to eliminate the # python interpreter startup time. # # The lexicon for sparv.saldo.annotate and sparv.saldo.compound can be pre-loaded and # shared between processes. See the variable annotators in handle and start. # # Run scripts in...
[ "logging.basicConfig", "os.path.exists", "logging.getLogger", "sparv.util.run.main", "socket.socket", "re.compile", "multiprocessing.Process", "multiprocessing.cpu_count", "os.getcwd", "os.chdir", "runpy.run_module", "builtins.range", "sparv.util.PickledLexicon", "sparv.util.system.kill_pr...
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import datetime def iso_extract_info(string): """ Will get all of the info and return it as an array :param string: ISO formatted string that will be used for extraction :return: array [year, month, day, military_time_hour, minutes, hours] :note: every item is an int except for minutes ...
[ "datetime.date" ]
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from django.urls import path from issue_template.views import IssueTemplateView urlpatterns = [ path( '<str:owner>/<str:repo>/<str:token_auth>/', IssueTemplateView.as_view() ), ]
[ "issue_template.views.IssueTemplateView.as_view" ]
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import collections import nltk import os from sklearn import ( datasets, model_selection, feature_extraction, linear_model, naive_bayes, ensemble ) def extract_features(corpus): '''Extract TF-IDF features from corpus''' sa_stop_words = nltk.corpus.stopwords.words("english") # words that might in...
[ "sklearn.feature_extraction.text.TfidfTransformer", "sklearn.linear_model.SGDClassifier", "sklearn.ensemble.VotingClassifier", "nltk.corpus.stopwords.words", "sklearn.model_selection.train_test_split", "sklearn.feature_extraction.text.CountVectorizer", "sklearn.datasets.load_files", "sklearn.linear_mo...
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# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. 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 requ...
[ "nemo.collections.tts.torch.helpers.general_padding", "torch.from_numpy", "transformers.AlbertTokenizer.from_pretrained", "nemo.utils.logging.info", "pathlib.Path", "torch.cuda.amp.autocast", "torch.view_as_real", "torch.finfo", "json.loads", "pickle.load", "librosa.filters.mel", "torch.save",...
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from flask import Flask, request, jsonify from flask_cors import CORS from run import run_ansys from api.validate import spec_present, data_type_validate, spec_keys_validate, ansys_overload_check ansys_processing_count = 0 # debug # import ipdb; ipdb.set_trace() app = Flask(__name__) CORS(app) # local development co...
[ "flask_cors.CORS", "flask.Flask", "api.validate.spec_keys_validate", "flask.request.get_json", "api.validate.ansys_overload_check", "api.validate.data_type_validate", "api.validate.spec_present", "run.run_ansys", "flask.jsonify" ]
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from django.db import models class Category(models.Model): title = models.CharField(max_length=20) class Meta: db_table = 'category' verbose_name = ("Category") verbose_name_plural = ("Categories") def __str__(self): return self.title
[ "django.db.models.CharField" ]
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