code stringlengths 20 1.04M | apis list | extract_api stringlengths 75 9.94M |
|---|---|---|
from django.shortcuts import render
# Create your views here.
from django.shortcuts import render
from django.http import HttpResponse
from django.contrib.auth.decorators import login_required
@login_required
def index(request):
context = {
"user": request.user
}
return render(request, "viewer/c... | [
"django.shortcuts.render"
] | [((295, 356), 'django.shortcuts.render', 'render', (['request', '"""viewer/contents/list.html"""'], {'context': 'context'}), "(request, 'viewer/contents/list.html', context=context)\n", (301, 356), False, 'from django.shortcuts import render\n')] |
# Generated by Django 2.2.1 on 2019-05-13 12:54
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('events', '0003_remove_event_subscriber'),
]
operations = [
migrations.RenameField(
model_name='event',
old_name='finished_da... | [
"django.db.migrations.RenameField"
] | [((231, 328), 'django.db.migrations.RenameField', 'migrations.RenameField', ([], {'model_name': '"""event"""', 'old_name': '"""finished_date"""', 'new_name': '"""starter_date"""'}), "(model_name='event', old_name='finished_date',\n new_name='starter_date')\n", (253, 328), False, 'from django.db import migrations\n')... |
#!/usr/bin/env python3
import warnings
warnings.filterwarnings("ignore")
import sys
import matplotlib
import numpy as np
import random
import itertools
import socket
sys.path.append('./src')
sys.path.append('./src/data_loader')
sys.path.append('./src/algorithms')
sys.path.append('./src/helper')
sys.path.append('./s... | [
"sys.path.append",
"warnings.filterwarnings"
] | [((40, 73), 'warnings.filterwarnings', 'warnings.filterwarnings', (['"""ignore"""'], {}), "('ignore')\n", (63, 73), False, 'import warnings\n'), ((170, 194), 'sys.path.append', 'sys.path.append', (['"""./src"""'], {}), "('./src')\n", (185, 194), False, 'import sys\n'), ((195, 231), 'sys.path.append', 'sys.path.append',... |
from typing import Union, Tuple
import torch
from torch import Tensor
import torch.nn.functional as F
from torch.nn import Sequential, Linear, BatchNorm1d, PReLU
import torch_geometric
from torch_geometric.typing import PairTensor, Adj, OptTensor, Size
from torch_geometric.nn.conv import MessagePassing
from tor... | [
"torch.nn.PReLU",
"torch.ones",
"torch.nn.ModuleList",
"torch.nn.BatchNorm1d",
"torch.nn.functional.dropout",
"torch.nn.Linear"
] | [((2324, 2345), 'torch.nn.ModuleList', 'torch.nn.ModuleList', ([], {}), '()\n', (2343, 2345), False, 'import torch\n'), ((2370, 2391), 'torch.nn.ModuleList', 'torch.nn.ModuleList', ([], {}), '()\n', (2389, 2391), False, 'import torch\n'), ((4453, 4512), 'torch.nn.functional.dropout', 'F.dropout', (['out'], {'p': 'self.... |
from pyspark import SparkConf, SparkContext
def load_movie_names():
movieNames = {}
skip_first = True
with open("ml-latest-small/movies.csv") as f:
for line in f:
if skip_first:
skip_first = False
continue
fields = line.split(",")
... | [
"pyspark.SparkContext",
"pyspark.SparkConf"
] | [((2396, 2419), 'pyspark.SparkContext', 'SparkContext', ([], {'conf': 'conf'}), '(conf=conf)\n', (2408, 2419), False, 'from pyspark import SparkConf, SparkContext\n'), ((2326, 2337), 'pyspark.SparkConf', 'SparkConf', ([], {}), '()\n', (2335, 2337), False, 'from pyspark import SparkConf, SparkContext\n')] |
#!/usr/bin/env python3
from pathlib import Path
import ee
import io
from googleapiclient.http import MediaIoBaseDownload
from apiclient import discovery
import logging
logging.getLogger("googleapiclient.discovery_cache").setLevel(logging.ERROR)
class gdrive(object):
def __init__(self):
self.initialize... | [
"apiclient.discovery.build",
"io.BytesIO",
"googleapiclient.http.MediaIoBaseDownload",
"ee.Credentials",
"pathlib.Path",
"ee.Initialize",
"logging.getLogger"
] | [((171, 223), 'logging.getLogger', 'logging.getLogger', (['"""googleapiclient.discovery_cache"""'], {}), "('googleapiclient.discovery_cache')\n", (188, 223), False, 'import logging\n'), ((323, 338), 'ee.Initialize', 'ee.Initialize', ([], {}), '()\n', (336, 338), False, 'import ee\n'), ((366, 382), 'ee.Credentials', 'ee... |
'''
Created on 2017年10月20日
天天美食
@author: dell
'''
from scrapy import Spider
from scrapy.http import Request
from ipproxytool.items import FoodBookItem
from scrapy import Selector
import re
class TtMeiShiBookSpider(Spider):
'''爬取菜谱'''
name = 'tt_mei_shi_book'
download_delay = 0.5
start_urls = [
... | [
"ipproxytool.items.FoodBookItem",
"scrapy.Selector",
"scrapy.http.Request",
"re.sub"
] | [((1468, 1484), 'scrapy.Selector', 'Selector', ([], {'text': 'i'}), '(text=i)\n', (1476, 1484), False, 'from scrapy import Selector\n'), ((1504, 1518), 'ipproxytool.items.FoodBookItem', 'FoodBookItem', ([], {}), '()\n', (1516, 1518), False, 'from ipproxytool.items import FoodBookItem\n'), ((2024, 2130), 'scrapy.http.Re... |
#!/usr/bin/python
# This scripts loads a pretrained model and a input TEST file (with correct tags) in CoNLL format (each line a token, sentences separated by an empty line).
# The input sentences are passed to the model for tagging. Prints the tokens, the correct tags, and the predicted tags in a CoNLL format to stdou... | [
"util.preprocessing.addCharInformation",
"pandas.DataFrame",
"util.preprocessing.createMatrices",
"util.preprocessing.addCasingInformation",
"util.conlleval.evaluate",
"sklearn.metrics.confusion_matrix",
"neuralnets.BiLSTM.BiLSTM.loadModel",
"pandas.set_option",
"util.preprocessing.readCoNLL"
] | [((936, 970), 'util.preprocessing.readCoNLL', 'readCoNLL', (['inputPath', 'inputColumns'], {}), '(inputPath, inputColumns)\n', (945, 970), False, 'from util.preprocessing import readCoNLL, createMatrices, addCharInformation, addCasingInformation\n'), ((971, 1000), 'util.preprocessing.addCharInformation', 'addCharInform... |
#
# 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 ... | [
"apache.aurora.executor.common.executor_timeout.ExecutorTimeout",
"apache.aurora.executor.common.resource_manager.ResourceManagerProvider",
"apache.aurora.executor.aurora_executor.AuroraExecutor",
"os.path.join",
"os.path.abspath",
"pkg_resources.resource_stream",
"twitter.common.log.options.LogOptions.... | [((1795, 1831), 'os.environ.get', 'os.environ.get', (['"""MESOS_SANDBOX"""', '"""."""'], {}), "('MESOS_SANDBOX', '.')\n", (1809, 1831), False, 'import os\n'), ((1833, 1858), 'twitter.common.app.configure', 'app.configure', ([], {'debug': '(True)'}), '(debug=True)\n', (1846, 1858), False, 'from twitter.common import app... |
from django.apps import AppConfig
from django.utils.translation import gettext_lazy as _
class PhotologueConfig(AppConfig):
name = 'photologue'
verbose_name = _('Работа с изображениями')
| [
"django.utils.translation.gettext_lazy"
] | [((169, 196), 'django.utils.translation.gettext_lazy', '_', (['"""Работа с изображениями"""'], {}), "('Работа с изображениями')\n", (170, 196), True, 'from django.utils.translation import gettext_lazy as _\n')] |
from datetime import datetime, timedelta
from django.core.management.base import BaseCommand
from django.core.management.base import CommandError
from django.db.models import F
from experiments.models import Experiment, ExperimentHistory
from random import randrange
class Command(BaseCommand):
help = 'Creates his... | [
"experiments.models.ExperimentHistory.objects.filter",
"experiments.models.ExperimentHistory.objects.get_or_create",
"django.db.models.F",
"datetime.timedelta",
"random.randrange",
"datetime.datetime.now",
"experiments.models.Experiment.objects.get"
] | [((2184, 2217), 'experiments.models.Experiment.objects.get', 'Experiment.objects.get', ([], {'slug': 'slug'}), '(slug=slug)\n', (2206, 2217), False, 'from experiments.models import Experiment, ExperimentHistory\n'), ((2656, 2711), 'experiments.models.ExperimentHistory.objects.filter', 'ExperimentHistory.objects.filter'... |
import binascii
import pytest
from aioxrpy import decimals, serializer
from aioxrpy.definitions import RippleTransactionType, RippleTransactionFlags
from aioxrpy.keys import RippleKey
from aioxrpy.rpc import RippleJsonRpc
@pytest.fixture
def master():
# Master account from genesis ledger
# https://xrpl.org/... | [
"aioxrpy.rpc.RippleJsonRpc",
"aioxrpy.decimals.xrp_to_drops",
"aioxrpy.keys.RippleKey",
"aioxrpy.serializer.serialize",
"aioxrpy.serializer.deserialize"
] | [((383, 413), 'aioxrpy.keys.RippleKey', 'RippleKey', ([], {'private_key': '"""<KEY>"""'}), "(private_key='<KEY>')\n", (392, 413), False, 'from aioxrpy.keys import RippleKey\n'), ((551, 589), 'aioxrpy.rpc.RippleJsonRpc', 'RippleJsonRpc', (['"""http://localhost:5005"""'], {}), "('http://localhost:5005')\n", (564, 589), F... |
from dataclasses import dataclass, field
from typing import Dict, List, Optional
import pandas as pd
@dataclass
class Individualization(object):
"""
Individualize a mechanistic model by incorporating gene expression levels.
Attributes
----------
parameters : List[str]
List of model param... | [
"dataclasses.field",
"pandas.read_csv"
] | [((3773, 3792), 'dataclasses.field', 'field', ([], {'default': 'None'}), '(default=None)\n', (3778, 3792), False, 'from dataclasses import dataclass, field\n'), ((3811, 3842), 'dataclasses.field', 'field', ([], {'default': '"""w_"""', 'init': '(False)'}), "(default='w_', init=False)\n", (3816, 3842), False, 'from datac... |
# Copyright (c) 2021 Graphcore Ltd. All rights reserved.
import popart.ir as pir
import popart.ir.ops as ops
import popart._internal.ir as _ir
import popart
from utils import contains_op_of_type
import numpy as np
from numpy.testing import assert_array_equal
import pytest
# `import test_util` requires adding to sys.pa... | [
"popart.ir.Ir",
"popart.ir.ops.host_store",
"numpy.testing.assert_array_equal",
"utils.contains_op_of_type",
"popart.AnchorReturnType",
"test_util.create_test_device",
"pytest.raises",
"numpy.arange",
"popart.PyStepIO",
"popart.ir.d2h_stream",
"pathlib.Path",
"pytest.mark.parametrize",
"popa... | [((647, 696), 'popart.ir.d2h_stream', 'pir.d2h_stream', (['y.shape', 'y.dtype'], {'name': '"""y_stream"""'}), "(y.shape, y.dtype, name='y_stream')\n", (661, 696), True, 'import popart.ir as pir\n'), ((701, 725), 'popart.ir.ops.host_store', 'ops.host_store', (['y_d2h', 'y'], {}), '(y_d2h, y)\n', (715, 725), True, 'impor... |
import torch
import torch.distributed.deprecated as dist
import model
import time
import sys
def run():
modell = model.CNN()
# modell = model.AlexNet()
size = dist.get_world_size()
rank = dist.get_rank()
group_list = []
for i in range(size):
group_list.append(i)
group = dist.new_... | [
"torch.distributed.deprecated.get_world_size",
"torch.distributed.deprecated.broadcast",
"model.CNN",
"torch.zeros_like",
"torch.distributed.deprecated.new_group",
"torch.distributed.deprecated.get_rank",
"torch.distributed.deprecated.reduce",
"sys.exit",
"torch.distributed.deprecated.init_process_g... | [((119, 130), 'model.CNN', 'model.CNN', ([], {}), '()\n', (128, 130), False, 'import model\n'), ((174, 195), 'torch.distributed.deprecated.get_world_size', 'dist.get_world_size', ([], {}), '()\n', (193, 195), True, 'import torch.distributed.deprecated as dist\n'), ((207, 222), 'torch.distributed.deprecated.get_rank', '... |
#! /usr/bin/env python
import os
import cv2
import argparse
import numpy as np
from face_detection import face_detection
from face_points_detection import face_points_detection
from face_swap import warp_image_2d, warp_image_3d, mask_from_points, apply_mask, correct_colours, transformation_from_points
def select_fa... | [
"face_swap.mask_from_points",
"argparse.ArgumentParser",
"numpy.ones",
"face_detection.face_detection",
"numpy.mean",
"cv2.erode",
"cv2.imshow",
"cv2.seamlessClone",
"cv2.imwrite",
"os.path.dirname",
"numpy.max",
"cv2.setMouseCallback",
"cv2.boundingRect",
"cv2.destroyAllWindows",
"face_... | [((368, 386), 'face_detection.face_detection', 'face_detection', (['im'], {}), '(im)\n', (382, 386), False, 'from face_detection import face_detection\n'), ((1443, 1460), 'numpy.min', 'np.min', (['points', '(0)'], {}), '(points, 0)\n', (1449, 1460), True, 'import numpy as np\n'), ((1481, 1498), 'numpy.max', 'np.max', (... |
""" wxyz top-level automation
this should be executed from within an environment created from
the .github/locks/conda.*.lock appropriate for your platform. See CONTRIBUTING.md.
"""
import json
import os
# pylint: disable=expression-not-assigned,W0511,too-many-lines
import shutil
import subprocess
import time
... | [
"_scripts._paths.ALL_SPELL_DOCS",
"_scripts._paths.LINT_GROUPS.items",
"_scripts._paths.LICENSE.read_text",
"_scripts._paths.MANIFEST_TEMPLATE.render",
"json.dumps",
"_scripts._paths.WHEELS.values",
"shutil.rmtree",
"_scripts._paths.TS_PACKAGE_CONTENT.values",
"_scripts._paths.TS_README_TMPL.render"... | [((1491, 1511), 'doit.create_after', 'create_after', (['"""docs"""'], {}), "('docs')\n", (1503, 1511), False, 'from doit import create_after\n'), ((25113, 25137), 'shutil.which', 'shutil.which', (['"""hunspell"""'], {}), "('hunspell')\n", (25125, 25137), False, 'import shutil\n'), ((25145, 25165), 'doit.create_after', ... |
"""Module that exposes local file system calls as an RPC service."""
import os
import os.path
import stat
from typing import List, Optional
from outrun.filesystem.common import Attributes
class LocalFileSystemService:
"""RPC service that exposes local file system operations."""
#
# File operations
... | [
"os.mkdir",
"os.unlink",
"os.fsync",
"os.lseek",
"os.statvfs",
"os.close",
"os.link",
"os.utime",
"os.fdatasync",
"os.open",
"os.chmod",
"os.mknod",
"os.stat",
"os.rename",
"os.pwrite",
"os.chown",
"os.pread",
"os.mkfifo",
"os.rmdir",
"os.listdir",
"os.readlink",
"os.dup",
... | [((400, 420), 'os.open', 'os.open', (['path', 'flags'], {}), '(path, flags)\n', (407, 420), False, 'import os\n'), ((512, 538), 'os.open', 'os.open', (['path', 'flags', 'mode'], {}), '(path, flags, mode)\n', (519, 538), False, 'import os\n'), ((629, 655), 'os.pread', 'os.pread', (['fh', 'size', 'offset'], {}), '(fh, si... |
import os
import time
import glob
import numpy
import pandas
import pytest
# convert all numpy warnings into errors so they can be detected in tests
numpy.seterr(all='raise')
@pytest.fixture(scope='session')
def tests_path():
return os.path.abspath(os.path.dirname(__file__))
@pytest.fixture(s... | [
"os.remove",
"numpy.seterr",
"pandas.read_csv",
"os.path.dirname",
"numpy.allclose",
"pytest.fixture",
"time.sleep",
"os.path.isfile",
"glob.glob",
"os.path.join"
] | [((160, 185), 'numpy.seterr', 'numpy.seterr', ([], {'all': '"""raise"""'}), "(all='raise')\n", (172, 185), False, 'import numpy\n'), ((192, 223), 'pytest.fixture', 'pytest.fixture', ([], {'scope': '"""session"""'}), "(scope='session')\n", (206, 223), False, 'import pytest\n'), ((304, 335), 'pytest.fixture', 'pytest.fix... |
# -*- coding: utf-8 -*-
"""
FED3 Viz: A tkinter program for visualizing FED3 Data
@author: https://github.com/earnestt1234
"""
#try to disable warning
import warnings
import matplotlib.cbook
warnings.filterwarnings("ignore",category=matplotlib.cbook.mplDeprecation)
import datetime as dt
import emoji
import matplotlib... | [
"getdata.getdata.average_plot_onstart",
"tkinter.ttk.Progressbar",
"getdata.getdata.grouped_meal_size_histogram",
"plots.plots.heatmap_chronogram",
"os.path.dirname",
"plots.plots.date_filter_okay",
"tkinter.ttk.Frame",
"fed_inspect.fed_inspect.get_arguments_affecting_settings",
"pandas.isna",
"tk... | [((192, 267), 'warnings.filterwarnings', 'warnings.filterwarnings', (['"""ignore"""'], {'category': 'matplotlib.cbook.mplDeprecation'}), "('ignore', category=matplotlib.cbook.mplDeprecation)\n", (215, 267), False, 'import warnings\n'), ((172000, 172016), 'matplotlib.pyplot.close', 'plt.close', (['"""all"""'], {}), "('a... |
import pandas as pd
import os
import functools
from utils.parse_csv_to_df import parse_cases
from sqlalchemy import create_engine
def import_tables_from_csv():
print("Importing time series csv into database...")
""" Imports time series covid files into current db"""
# find latest file in COVID-19 folder
... | [
"pandas.merge",
"utils.parse_csv_to_df.parse_cases",
"os.getenv"
] | [((556, 617), 'os.getenv', 'os.getenv', (['"""SQLALCHEMY_DATABASE_URI"""', '"""sqlite:///api/site.db"""'], {}), "('SQLALCHEMY_DATABASE_URI', 'sqlite:///api/site.db')\n", (565, 617), False, 'import os\n'), ((1044, 1067), 'utils.parse_csv_to_df.parse_cases', 'parse_cases', (['f[0]', 'f[1]'], {}), '(f[0], f[1])\n', (1055,... |
import unittest
from pandas import DataFrame
from hockeydata import get_play_by_plays
from hockeydata.scrape.scrape import game_html_pbp, get_players
import hockeydata.scrape.html_pbp as html_pbp
class TestAPI(unittest.TestCase):
@classmethod
def setUpClass(cls):
pass
#TODO currently the tests are ... | [
"unittest.main",
"hockeydata.scrape.scrape.get_players",
"hockeydata.scrape.html_pbp.get_event_player_1",
"hockeydata.scrape.html_pbp.get_event_player_2",
"hockeydata.scrape.html_pbp.get_event_player_3",
"hockeydata.get_play_by_plays"
] | [((8877, 8892), 'unittest.main', 'unittest.main', ([], {}), '()\n', (8890, 8892), False, 'import unittest\n'), ((7497, 7560), 'hockeydata.scrape.html_pbp.get_event_player_1', 'html_pbp.get_event_player_1', (['description', '"""FAC"""', '"""N.J"""', 'players'], {}), "(description, 'FAC', 'N.J', players)\n", (7524, 7560)... |
# type: ignore
from pipyadc import ADS1256, ADS1256_default_config
from pipyadc.ADS1256_definitions import (
NEG_AINCOM,
POS_AIN0,
POS_AIN1,
POS_AIN2,
POS_AIN3,
)
from .base import LabDataService
class PiPyADCService(LabDataService):
"""
Provides pressure readings from a vacuum gauge, rea... | [
"pipyadc.ADS1256"
] | [((742, 773), 'pipyadc.ADS1256', 'ADS1256', (['ADS1256_default_config'], {}), '(ADS1256_default_config)\n', (749, 773), False, 'from pipyadc import ADS1256, ADS1256_default_config\n')] |
from django.urls import path, include
from wx_app import views
urlpatterns = [
path('', views.wx_web, name='wx_web'),
path('ht', views.wx_main, name='wx_main'),
path('createmenu/', views.create_menu, name='creat_menu')
]
| [
"django.urls.path"
] | [((84, 121), 'django.urls.path', 'path', (['""""""', 'views.wx_web'], {'name': '"""wx_web"""'}), "('', views.wx_web, name='wx_web')\n", (88, 121), False, 'from django.urls import path, include\n'), ((127, 168), 'django.urls.path', 'path', (['"""ht"""', 'views.wx_main'], {'name': '"""wx_main"""'}), "('ht', views.wx_main... |
# 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 Li... | [
"pyramid.path.AssetResolver",
"json.load",
"whitenoise.WhiteNoise"
] | [((654, 669), 'pyramid.path.AssetResolver', 'AssetResolver', ([], {}), '()\n', (667, 669), False, 'from pyramid.path import AssetResolver\n'), ((2151, 2209), 'whitenoise.WhiteNoise', 'WhiteNoise', (['app'], {'immutable_file_test': 'manifest'}), '(app, **wh_config, immutable_file_test=manifest)\n', (2161, 2209), False, ... |
from subprocess import call
from sys import platform as _platform
from colors import logcolors
def init():
call('git init')
def createReadme():
if _platform == "linux" or _platform == "linux2":
call('touch README.md')
elif _platform == "darwin":
call('touch README.md')
elif _platform... | [
"subprocess.call"
] | [((113, 129), 'subprocess.call', 'call', (['"""git init"""'], {}), "('git init')\n", (117, 129), False, 'from subprocess import call\n'), ((1648, 1684), 'subprocess.call', 'call', (["('git remote add origin ' + url)"], {}), "('git remote add origin ' + url)\n", (1652, 1684), False, 'from subprocess import call\n'), ((1... |
# ***** BEGIN GPL LICENSE BLOCK *****
#
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distribute... | [
"bpy.app.handlers.render_complete.append",
"os.path.basename",
"bpy.app.handlers.render_pre.append",
"bpy.app.handlers.render_complete.remove",
"time.time",
"shlex.quote",
"datetime.timedelta",
"bpy.app.handlers.render_pre.remove"
] | [((1774, 1785), 'time.time', 'time.time', ([], {}), '()\n', (1783, 1785), False, 'import time\n'), ((1983, 2018), 'os.path.basename', 'os.path.basename', (['bpy.data.filepath'], {}), '(bpy.data.filepath)\n', (1999, 2018), False, 'import os\n'), ((2200, 2256), 'bpy.app.handlers.render_complete.append', 'bpy.app.handlers... |
"""Extract the changelog for the current version."""
import subprocess
from dephell_changelogs import parse_changelog
with open("./CHANGELOG.rst") as fd:
cl = parse_changelog(fd.read())
tag = subprocess.run(
["git", "describe", "--tags"], stdout=subprocess.PIPE
).stdout.decode()
if tag[0] != "v":
raise V... | [
"subprocess.run"
] | [((199, 268), 'subprocess.run', 'subprocess.run', (["['git', 'describe', '--tags']"], {'stdout': 'subprocess.PIPE'}), "(['git', 'describe', '--tags'], stdout=subprocess.PIPE)\n", (213, 268), False, 'import subprocess\n')] |
from importlib.metadata import entry_points
from setuptools import setup, find_packages
with open('README.rst', encoding='UTF-8') as f:
readme = f.read()
setup(
name='pgbackup',
version='1.0.1',
description='Database backups locally or to AWS S3.',
long_description=readme,
author=... | [
"setuptools.find_packages"
] | [((458, 478), 'setuptools.find_packages', 'find_packages', (['"""src"""'], {}), "('src')\n", (471, 478), False, 'from setuptools import setup, find_packages\n')] |
###############
#
# Transform R to Python Copyright (c) 2019 <NAME> Released under the MIT license
#
###############
import os
import numpy as np
import pystan
import pandas
import pickle
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.preprocessing import LabelEncoder
fish_num_climate_4 = pandas.... | [
"pandas.DataFrame",
"pickle.dump",
"matplotlib.pyplot.show",
"seaborn.scatterplot",
"pandas.read_csv",
"pandas.get_dummies",
"matplotlib.pyplot.legend",
"os.path.exists",
"sklearn.preprocessing.LabelEncoder",
"numpy.arange",
"numpy.array",
"pystan.StanModel",
"numpy.unique"
] | [((313, 352), 'pandas.read_csv', 'pandas.read_csv', (['"""4-3-1-fish-num-4.csv"""'], {}), "('4-3-1-fish-num-4.csv')\n", (328, 352), False, 'import pandas\n'), ((424, 513), 'seaborn.scatterplot', 'sns.scatterplot', ([], {'x': '"""temperature"""', 'y': '"""fish_num"""', 'hue': '"""human"""', 'data': 'fish_num_climate_4'}... |
import cv2
import numpy as np
cap=cv2.VideoCapture(0)
while True:
_, frame=cap.read()
laplacian=cv2.Laplacian(frame,cv2.CV_64F)
sobelx=cv2.Sobel(frame,cv2.CV_64F,1,0,ksize=5)
sobely=cv2.Sobel(frame,cv2.CV_64F,0,1,ksize=5)
edges=cv2.Canny(frame,200,200)#builtin edge detector
... | [
"cv2.Canny",
"cv2.waitKey",
"cv2.imshow",
"cv2.VideoCapture",
"cv2.destroyAllWindows",
"cv2.Sobel",
"cv2.Laplacian"
] | [((36, 55), 'cv2.VideoCapture', 'cv2.VideoCapture', (['(0)'], {}), '(0)\n', (52, 55), False, 'import cv2\n'), ((569, 592), 'cv2.destroyAllWindows', 'cv2.destroyAllWindows', ([], {}), '()\n', (590, 592), False, 'import cv2\n'), ((111, 143), 'cv2.Laplacian', 'cv2.Laplacian', (['frame', 'cv2.CV_64F'], {}), '(frame, cv2.CV... |
import time
import numpy as np
import scipy.misc as scm
import os
import vn
import tensorflow as tf
import argparse
from denoisingdata import VnDenoisingData
import tensorflow.contrib.icg as icg
class VnDenoisingCell(tf.contrib.icg.VnBasicCell):
def call(self, t, inputs):
# get the variables
u =... | [
"tensorflow.contrib.icg.activation_rbf",
"tensorflow.train.Coordinator",
"tensorflow.reduce_sum",
"argparse.ArgumentParser",
"tensorflow.clip_by_value",
"time.strftime",
"tensorflow.contrib.icg.utils.Params",
"tensorflow.ConfigProto",
"numpy.mean",
"tensorflow.nn.conv2d",
"tensorflow.RunOptions"... | [((1755, 1780), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (1778, 1780), False, 'import argparse\n'), ((2221, 2291), 'tensorflow.contrib.icg.utils.loadYaml', 'tf.contrib.icg.utils.loadYaml', (['args.network_config', "['network', 'reg']"], {}), "(args.network_config, ['network', 'reg'])\n", ... |
from typing import Dict, Tuple, Type, Union, cast
from django.test.client import AsyncClient # type:ignore
from django.test.client import Client
import pytest
from strawberry_django_plus.optimizer import DjangoOptimizerExtension
from tests.utils import GraphQLTestClient
@pytest.fixture(params=["sync", "async", "sy... | [
"typing.cast",
"strawberry_django_plus.optimizer.DjangoOptimizerExtension.enabled.set",
"pytest.fixture",
"strawberry_django_plus.optimizer.DjangoOptimizerExtension.enabled.reset"
] | [((277, 364), 'pytest.fixture', 'pytest.fixture', ([], {'params': "['sync', 'async', 'sync_no_optimizer', 'async_no_optimizer']"}), "(params=['sync', 'async', 'sync_no_optimizer',\n 'async_no_optimizer'])\n", (291, 364), False, 'import pytest\n'), ((806, 858), 'strawberry_django_plus.optimizer.DjangoOptimizerExtensi... |
from rest_framework.decorators import api_view, permission_classes
from rest_framework.permissions import IsAuthenticated
from rest_framework.response import Response
from rest_registration.decorators import api_view_serializer_class_getter
from rest_registration.settings import registration_settings
@api_view_seria... | [
"rest_framework.decorators.permission_classes",
"rest_framework.decorators.api_view",
"rest_framework.response.Response",
"rest_registration.decorators.api_view_serializer_class_getter"
] | [((306, 400), 'rest_registration.decorators.api_view_serializer_class_getter', 'api_view_serializer_class_getter', (['(lambda : registration_settings.PROFILE_SERIALIZER_CLASS)'], {}), '(lambda : registration_settings.\n PROFILE_SERIALIZER_CLASS)\n', (338, 400), False, 'from rest_registration.decorators import api_vi... |
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import pandas as pd
import seaborn as sns
# Let seaborn decide the styles
sns.set(rc={})
# Modified from:
# https://scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html
def draw_confusion_matrix(cm, ... | [
"matplotlib.pyplot.tight_layout",
"seaborn.lineplot",
"matplotlib.pyplot.show",
"seaborn.heatmap",
"pandas.DataFrame.from_dict",
"seaborn.barplot",
"numpy.expand_dims",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.style.use",
"seaborn.boxplot",
"numpy.array",
"matplotlib.pyplot.figure",
... | [((165, 179), 'seaborn.set', 'sns.set', ([], {'rc': '{}'}), '(rc={})\n', (172, 179), True, 'import seaborn as sns\n'), ((383, 407), 'matplotlib.pyplot.style.use', 'plt.style.use', (['"""default"""'], {}), "('default')\n", (396, 407), True, 'import matplotlib.pyplot as plt\n'), ((451, 481), 'numpy.array', 'np.array', ([... |
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
# Iterative BFS
# Change the deque to stack will give DFS
from collections import deque
class Solution:
def maxDepth(self, root: TreeNode) -> int:
... | [
"collections.deque"
] | [((393, 400), 'collections.deque', 'deque', ([], {}), '()\n', (398, 400), False, 'from collections import deque\n')] |
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
# Copyright 2019 <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file e... | [
"fairscale.nn.pipe.pipeline.clock_cycles"
] | [((863, 881), 'fairscale.nn.pipe.pipeline.clock_cycles', 'clock_cycles', (['(1)', '(1)'], {}), '(1, 1)\n', (875, 881), False, 'from fairscale.nn.pipe.pipeline import clock_cycles\n'), ((913, 931), 'fairscale.nn.pipe.pipeline.clock_cycles', 'clock_cycles', (['(1)', '(3)'], {}), '(1, 3)\n', (925, 931), False, 'from fairs... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2019/12/29 15:44
# @Author : MengnanChen
# @File : combine_sound.py
# @Software: PyCharm
import os
import glob
import random
from tqdm import tqdm
import numpy as np
import soundfile as sf
import librosa
SAMPLE_RATE = 48000
def combine_rnnoise_contribu... | [
"tqdm.tqdm",
"soundfile.read",
"os.makedirs",
"random.shuffle",
"librosa.load",
"os.path.join",
"numpy.concatenate"
] | [((354, 392), 'os.makedirs', 'os.makedirs', (['output_dir'], {'exist_ok': '(True)'}), '(output_dir, exist_ok=True)\n', (365, 392), False, 'import os\n'), ((459, 486), 'random.shuffle', 'random.shuffle', (['sound_files'], {}), '(sound_files)\n', (473, 486), False, 'import random\n'), ((667, 684), 'tqdm.tqdm', 'tqdm', ([... |
"""
Python package `sledge`: semantic evaluation of clustering results.
The package performs an evaluation of clustering results through
the semantic relationship between the significant frequent patterns
identified among the cluster items.
The method uses an internal validation technique to evaluate
the cluster rath... | [
"numpy.count_nonzero",
"pandas.DataFrame.from_dict",
"numpy.concatenate",
"numpy.sort",
"numpy.min",
"numpy.mean",
"numpy.array",
"numpy.max",
"numpy.diff",
"numpy.delete",
"numpy.unique"
] | [((4960, 5013), 'numpy.mean', 'np.mean', (['descriptor_set_size[descriptor_set_size > 0]'], {}), '(descriptor_set_size[descriptor_set_size > 0])\n', (4967, 5013), True, 'import numpy as np\n'), ((6068, 6174), 'pandas.DataFrame.from_dict', 'pd.DataFrame.from_dict', (["{'S': support_score, 'L': length_score, 'E': exclusi... |
# -*- coding: utf-8 -*-
#
# Copyright 2016 <NAME>
#
# 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 agree... | [
"matplotlib.pyplot.title",
"argparse.ArgumentParser",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.style.use",
"matplotlib.pyplot.tight_layout",
"numpy.linspace",
"math.log",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.legend",
"matplotlib.use",
"matplotlib.pyplot.... | [((611, 632), 'matplotlib.use', 'matplotlib.use', (['"""Agg"""'], {}), "('Agg')\n", (625, 632), False, 'import matplotlib\n'), ((919, 949), 'matplotlib.pyplot.figure', 'pyplot.figure', ([], {'figsize': '(13, 8)'}), '(figsize=(13, 8))\n', (932, 949), False, 'from matplotlib import pyplot\n'), ((954, 980), 'matplotlib.py... |
# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'datacred.ui'
#
# Created by: PyQt5 UI code generator 5.6
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Form(object):
def setupUi(self, Form):
Form.setObjectName("Fo... | [
"PyQt5.QtWidgets.QLabel",
"PyQt5.QtWidgets.QSizePolicy",
"PyQt5.QtWidgets.QHBoxLayout",
"PyQt5.QtCore.QSize",
"PyQt5.QtWidgets.QGroupBox",
"PyQt5.QtGui.QFont",
"growingtextedit.GrowingTextEdit",
"PyQt5.QtWidgets.QVBoxLayout",
"PyQt5.QtCore.QMetaObject.connectSlotsByName"
] | [((376, 466), 'PyQt5.QtWidgets.QSizePolicy', 'QtWidgets.QSizePolicy', (['QtWidgets.QSizePolicy.Preferred', 'QtWidgets.QSizePolicy.Minimum'], {}), '(QtWidgets.QSizePolicy.Preferred, QtWidgets.\n QSizePolicy.Minimum)\n', (397, 466), False, 'from PyQt5 import QtCore, QtGui, QtWidgets\n'), ((787, 800), 'PyQt5.QtGui.QFon... |
# -*- coding: utf-8 -*-
# Copyright (c) 2016, French National Center for Scientific Research (CNRS)
# Distributed under the (new) BSD License. See LICENSE for more info.
import numpy as np
import collections
import logging
import os
import json
from ..core import Node, register_node_type, ThreadPollInput, InputStream... | [
"os.mkdir",
"os.path.exists",
"pyqtgraph.Qt.QtCore.Signal",
"json.dumps",
"collections.OrderedDict",
"os.path.join",
"pyqtgraph.util.mutex.Mutex"
] | [((4470, 4493), 'pyqtgraph.Qt.QtCore.Signal', 'QtCore.Signal', (['str', 'int'], {}), '(str, int)\n', (4483, 4493), False, 'from pyqtgraph.Qt import QtCore, QtGui\n'), ((1507, 1532), 'collections.OrderedDict', 'collections.OrderedDict', ([], {}), '()\n', (1530, 1532), False, 'import collections\n'), ((1825, 1847), 'os.m... |
import numpy as np
from scipy.sparse import csr_matrix
from feature_mining.em_base import ExpectationMaximization
from feature_mining import ParseAndModel
from datetime import datetime
import os
import logging
import time
class EmVectorByFeature(ExpectationMaximization):
"""
Vectorized implementation of EM al... | [
"feature_mining.em_base.ExpectationMaximization.__init__",
"numpy.subtract",
"os.getcwd",
"logging.warning",
"numpy.power",
"feature_mining.ParseAndModel",
"numpy.ones",
"time.time",
"logging.info",
"scipy.sparse.csr_matrix",
"numpy.array",
"numpy.where",
"numpy.column_stack",
"numpy.dot"
... | [((9692, 9703), 'time.time', 'time.time', ([], {}), '()\n', (9701, 9703), False, 'import time\n'), ((9751, 9891), 'feature_mining.ParseAndModel', 'ParseAndModel', ([], {'feature_list': "['sound', 'battery', ['screen', 'display']]", 'filename': '"""../tests/data/parse_and_model/iPod.final"""', 'nlines': '(100)'}), "(fea... |
"""
``LivePossessionLoader`` loads possession data for a game and creates :obj:`~pbpstats.resources.possessions.possession.Possession` objects for each possession
The following code will load possession data for game id "0021900001" from a pbp file located in the ``/pbp`` subdirectory of the ``/data`` directory
.. co... | [
"pbpstats.resources.possessions.possession.Possession",
"pbpstats.data_loader.live.enhanced_pbp.loader.LiveEnhancedPbpLoader"
] | [((1564, 1636), 'pbpstats.data_loader.live.enhanced_pbp.loader.LiveEnhancedPbpLoader', 'LiveEnhancedPbpLoader', (['game_id', 'source_loader.enhanced_pbp_source_loader'], {}), '(game_id, source_loader.enhanced_pbp_source_loader)\n', (1585, 1636), False, 'from pbpstats.data_loader.live.enhanced_pbp.loader import LiveEnha... |
from mock import patch
from corehq.apps.app_manager.models import LinkedApplication, Module
from corehq.apps.app_manager.views.utils import get_blank_form_xml
from corehq.apps.linked_domain.const import (
LINKED_MODELS_MAP,
MODEL_APP,
MODEL_CASE_SEARCH,
MODEL_FLAGS,
MODEL_USER_DATA,
)
from corehq.a... | [
"corehq.apps.app_manager.models.LinkedApplication.get",
"corehq.apps.linked_domain.models.AppLinkDetail",
"corehq.apps.users.models.WebUser.create",
"corehq.apps.linked_domain.models.DomainLink.link_domains",
"mock.patch",
"corehq.util.test_utils.flag_enabled",
"corehq.apps.app_manager.views.utils.get_b... | [((2786, 2824), 'corehq.util.test_utils.flag_enabled', 'flag_enabled', (['"""SYNC_SEARCH_CASE_CLAIM"""'], {}), "('SYNC_SEARCH_CASE_CLAIM')\n", (2798, 2824), False, 'from corehq.util.test_utils import flag_enabled\n'), ((3959, 4002), 'corehq.util.test_utils.flag_enabled', 'flag_enabled', (['"""MULTI_MASTER_LINKED_DOMAIN... |
import pandas as pd
import random,time
import numpy as np
import math,copy
from sklearn.linear_model import LogisticRegression
from sklearn.tree import DecisionTreeRegressor
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report, confusion_matrix, accuracy_score
from skle... | [
"pandas.read_csv",
"sklearn.model_selection.train_test_split",
"result.measure.calculate_recall",
"sklearn.preprocessing.MinMaxScaler",
"result.measure.calculate_far",
"sklearn.preprocessing.LabelEncoder",
"time.time",
"result.measure.measure_final_score",
"sklearn.linear_model.LogisticRegression",
... | [((737, 768), 'pandas.read_csv', 'pd.read_csv', (['"""dataset/bank.csv"""'], {}), "('dataset/bank.csv')\n", (748, 768), True, 'import pandas as pd\n'), ((1160, 1201), 'numpy.where', 'np.where', (["(dataset_orig['age'] >= 25)", '(1)', '(0)'], {}), "(dataset_orig['age'] >= 25, 1, 0)\n", (1168, 1201), True, 'import numpy ... |
# !/usr/bin/env python
# coding=UTF-8
"""
@Author: <NAME>
@LastEditors: <NAME>
@Description:
@Date: 2021-08-12
@LastEditTime: 2022-03-19
英文字符串的一些基本操作
"""
import re
from string import punctuation
from typing import List, NoReturn
import nltk
from nltk.tokenize import word_tokenize as nltk_word_tokenize
import stanza
... | [
"flair.models.SequenceTagger.load",
"flair.data.Sentence",
"re.finditer",
"nltk.data.find",
"nltk.download",
"segtok.tokenizer.word_tokenizer",
"stanza.Pipeline",
"nltk.pos_tag",
"syntok.tokenizer.Tokenizer",
"re.sub",
"nltk.tokenize.word_tokenize"
] | [((2672, 2707), 'flair.data.Sentence', 'Sentence', (['s'], {'use_tokenizer': 'tokenize'}), '(s, use_tokenizer=tokenize)\n', (2680, 2707), False, 'from flair.data import Sentence\n'), ((2721, 2750), 'flair.models.SequenceTagger.load', 'SequenceTagger.load', (['tag_type'], {}), '(tag_type)\n', (2740, 2750), False, 'from ... |
#!/usr/bin/python
import roslib; roslib.load_manifest('cv_bridge')
import rospy
import unittest
from cv_bridge import cv_bridge
import numpy as np
import struct
class MatNDTest(unittest.TestCase):
def setUp(self):
self.mat = np.array(range(24), np.uint8)
self.mat = np.reshape(self.mat, (2,3,4))
self.ass... | [
"unittest.main",
"cv_bridge.cv_bridge.NumpyBridge",
"struct.pack",
"numpy.array",
"numpy.reshape",
"roslib.load_manifest"
] | [((33, 66), 'roslib.load_manifest', 'roslib.load_manifest', (['"""cv_bridge"""'], {}), "('cv_bridge')\n", (53, 66), False, 'import roslib\n'), ((1898, 1913), 'unittest.main', 'unittest.main', ([], {}), '()\n', (1911, 1913), False, 'import unittest\n'), ((277, 308), 'numpy.reshape', 'np.reshape', (['self.mat', '(2, 3, 4... |
import subprocess
print("This program extracts a clip out of any video file")
dict = {
"4k" : str("-vf scale=3840:2160"),
"1080p" : str("-vf scale=1920:1080"),
"720p" : str("-vf scale=1280:720"),
"480p" : str("-vf scale=852:480"),
"360p" : str("-vf scale=480:360"),
"H264" : str("-vcodec libx264"... | [
"subprocess.call"
] | [((1795, 1927), 'subprocess.call', 'subprocess.call', (['f"""ffmpeg -i {filename} -ss {start} -to {end} {resolution} {codec} {bitrate} {audio} {output}"""'], {'shell': '(True)'}), "(\n f'ffmpeg -i {filename} -ss {start} -to {end} {resolution} {codec} {bitrate} {audio} {output}'\n , shell=True)\n", (1810, 1927), F... |
"""
This file is used to generate ../data/COCO+TLESS_fusion_rendering dataset.
Use fusion & rendering strategy
"""
from utils.sixd import load_sixd, load_COCO, load_yaml
from rendering.model import Model3D
from rendering.utils import create_pose, build_6D_poses
from rendering.renderer import Renderer
from tools.fps imp... | [
"os.mkdir",
"lxml.etree.Element",
"random.shuffle",
"numpy.ones",
"pycocotools.mask.encode",
"numpy.random.randint",
"numpy.linalg.norm",
"lxml.etree.SubElement",
"os.path.join",
"numpy.round",
"tools.fps.fps_utils.farthest_point_sampling",
"numpy.copy",
"os.path.dirname",
"numpy.savetxt",... | [((1279, 1293), 'numpy.identity', 'np.identity', (['(3)'], {}), '(3)\n', (1290, 1293), True, 'import numpy as np\n'), ((2068, 2145), 'numpy.loadtxt', 'np.loadtxt', (['"""/data/ZHANGXIN/pose_estimation_code/ssd-6d-master/views-337.txt"""'], {}), "('/data/ZHANGXIN/pose_estimation_code/ssd-6d-master/views-337.txt')\n", (2... |
########### Get People Listed and Specific People Info ###########
import http.client, urllib.request, urllib.parse, urllib.error, base64, requests, json
# Subscription Key to identify my Service in Azure
subscription_key = '<KEY>'
print("You will create a new person")
person = input("What's the name... | [
"requests.post"
] | [((1157, 1251), 'requests.post', 'requests.post', (["(group_url + groupid + '/persons')"], {'params': 'params', 'json': 'body', 'headers': 'headers'}), "(group_url + groupid + '/persons', params=params, json=body,\n headers=headers)\n", (1170, 1251), False, 'import http.client, urllib.request, urllib.parse, urllib.e... |
"""justdoist URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/2.0/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-bas... | [
"main.views.Register.as_view",
"django.contrib.staticfiles.urls.staticfiles_urlpatterns",
"django.conf.urls.url",
"django.urls.path"
] | [((2127, 2152), 'django.contrib.staticfiles.urls.staticfiles_urlpatterns', 'staticfiles_urlpatterns', ([], {}), '()\n', (2150, 2152), False, 'from django.contrib.staticfiles.urls import staticfiles_urlpatterns\n'), ((941, 972), 'django.urls.path', 'path', (['"""admin/"""', 'admin.site.urls'], {}), "('admin/', admin.sit... |
"""
Parser containing all Gooey widgets.
"""
from gooey import GooeyParser
parser = GooeyParser()
parser.add_argument('--textfield', default=2, widget="TextField")
parser.add_argument('--textarea', default="oneline twoline", widget='Textarea')
parser.add_argument('--password', default="<PASSWORD>", widget='Password... | [
"gooey.GooeyParser"
] | [((87, 100), 'gooey.GooeyParser', 'GooeyParser', ([], {}), '()\n', (98, 100), False, 'from gooey import GooeyParser\n')] |
# (c) 2020 <NAME>
# This code is licensed under MIT license (see LICENSE.txt for details)
import scipy.ndimage.filters as imagefilter
import numpy as np
IMG_WIDTH = 64
IMG_HEIGHT = 64
sharpen = np.array((
[1, 1, 1],
[1, 1, 1],
[1, 1, 1]), dtype="int")
sharpen = np.flip(sharpen)
print(sharpen)
res = []
for i in r... | [
"scipy.ndimage.filters.convolve",
"numpy.array",
"numpy.arange",
"numpy.flip"
] | [((197, 253), 'numpy.array', 'np.array', (['([1, 1, 1], [1, 1, 1], [1, 1, 1])'], {'dtype': '"""int"""'}), "(([1, 1, 1], [1, 1, 1], [1, 1, 1]), dtype='int')\n", (205, 253), True, 'import numpy as np\n'), ((269, 285), 'numpy.flip', 'np.flip', (['sharpen'], {}), '(sharpen)\n', (276, 285), True, 'import numpy as np\n'), ((... |
# 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 t... | [
"solum.objects.load",
"mock.patch",
"solum.api.controllers.camp.v1_1.formats.FormatsController"
] | [((699, 763), 'mock.patch', 'mock.patch', (['"""pecan.request"""'], {'new_callable': 'fakes.FakePecanRequest'}), "('pecan.request', new_callable=fakes.FakePecanRequest)\n", (709, 763), False, 'import mock\n'), ((765, 831), 'mock.patch', 'mock.patch', (['"""pecan.response"""'], {'new_callable': 'fakes.FakePecanResponse'... |
import unittest
from nose.tools import *
from streetaddress import StreetAddressFormatter, StreetAddressParser
class TestStreetAddress(unittest.TestCase):
def setUp(self):
self.addr_parser = StreetAddressParser()
self.addr_formatter = StreetAddressFormatter()
def test_success_abbrev_street_a... | [
"streetaddress.StreetAddressFormatter",
"streetaddress.StreetAddressParser"
] | [((205, 226), 'streetaddress.StreetAddressParser', 'StreetAddressParser', ([], {}), '()\n', (224, 226), False, 'from streetaddress import StreetAddressFormatter, StreetAddressParser\n'), ((257, 281), 'streetaddress.StreetAddressFormatter', 'StreetAddressFormatter', ([], {}), '()\n', (279, 281), False, 'from streetaddre... |
try:
from Crypto.Cipher import ARC2
from Crypto import Random
except:
import sys
sys.exit("You Need To Download First pycrypto Module.\nusing the following command : 'pip3 install pycrypto'")
import time
import platform
import base64
import os
import hashlib
class fileOnARC2():
"""This Class Is To Encrypt And De... | [
"os.remove",
"base64.b64decode",
"time.time",
"Crypto.Cipher.ARC2.new",
"Crypto.Random.new",
"sys.exit"
] | [((85, 208), 'sys.exit', 'sys.exit', (['"""You Need To Download First pycrypto Module.\nusing the following command : \'pip3 install pycrypto\'"""'], {}), '(\n """You Need To Download First pycrypto Module.\nusing the following command : \'pip3 install pycrypto\'"""\n )\n', (93, 208), False, 'import sys\n'), ((10... |
import torch
from scripts.study_case.ID_13.torch_geometric.data import Data
class Batch(Data):
def __init__(self, batch=None, **kwargs):
super(Batch, self).__init__(**kwargs)
self.batch = batch
@staticmethod
def from_data_list(data_list):
keys = [set(data.keys) for data in data_li... | [
"torch.cat",
"torch.full"
] | [((1055, 1085), 'torch.cat', 'torch.cat', (['batch.batch'], {'dim': '(-1)'}), '(batch.batch, dim=-1)\n', (1064, 1085), False, 'import torch\n'), ((636, 681), 'torch.full', 'torch.full', (['(num_nodes,)', 'i'], {'dtype': 'torch.long'}), '((num_nodes,), i, dtype=torch.long)\n', (646, 681), False, 'import torch\n')] |
import logging
import os
from typing import Optional
from django.core.management.base import CommandParser
from django.utils.timezone import now
from jutil.command import SafeCommand
from jsanctions.services import delete_old_sanction_list_files
from jsanctions.models import SanctionsListFile
from jsanctions.un import ... | [
"os.path.basename",
"django.utils.timezone.now",
"jsanctions.un.import_un_sanctions",
"jsanctions.models.SanctionsListFile.objects.create_from_filename",
"jsanctions.models.SanctionsListFile.objects.get",
"jsanctions.models.SanctionsListFile.objects.filter",
"jsanctions.services.delete_old_sanction_list... | [((364, 391), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (381, 391), False, 'import logging\n'), ((2258, 2302), 'jsanctions.un.import_un_sanctions', 'import_un_sanctions', (['source'], {'verbose': 'verbose'}), '(source, verbose=verbose)\n', (2277, 2302), False, 'from jsanctions.un imp... |
import numpy as np
import chainer
from chainer import cuda, Function, report, training, utils, Variable
from chainer import datasets, iterators, optimizers, serializers, reporter
from chainer.dataset import convert
from chainer.dataset import iterator as iterator_module
from chainer import Link, Chain, ChainList
... | [
"chainer.functions.mean_squared_error",
"chainer.function.no_backprop_mode",
"chainer.optimizers.Adam",
"chainer.training.Trainer",
"chainer.links.Convolution2D",
"chainer.reporter.report",
"chainer.training.extensions.PrintReport",
"chainer.reporter.DictSummary",
"chainer.reporter.report_scope",
... | [((2873, 2918), 'chainer.training.make_extension', 'training.make_extension', ([], {'trigger': "(1, 'epoch')"}), "(trigger=(1, 'epoch'))\n", (2896, 2918), False, 'from chainer import cuda, Function, report, training, utils, Variable\n'), ((3727, 3775), 'numpy.int32', 'np.int32', (['(train_data.shape[0] / 10 * train_rat... |
import collections
import re
from vee.semver import Version
class Provision(collections.MutableMapping):
@classmethod
def coerce(cls, input_):
return input_ if isinstance(input_, cls) else cls(input_)
def __init__(self, input_=None):
self._data = {}
if isinstance(input_, s... | [
"re.match",
"vee.semver.Version.coerce"
] | [((821, 846), 're.match', 're.match', (['"""^\\\\w+$"""', 'chunk'], {}), "('^\\\\w+$', chunk)\n", (829, 846), False, 'import re\n'), ((952, 992), 're.match', 're.match', (['"""^(\\\\w+)\\\\s*=\\\\s*(.+)$"""', 'chunk'], {}), "('^(\\\\w+)\\\\s*=\\\\s*(.+)$', chunk)\n", (960, 992), False, 'import re\n'), ((1599, 1620), 'v... |
"""
generate_segments.py
--------------------
For every OpenStreetMap segment with zero parallel sidewalks,
generate two new 'improvement concept' geometries, one for each
side of the street centerline.
"""
import click
import pandas as pd
from tqdm import tqdm
import warnings
from pg_data_etl import Database
from ... | [
"click.argument",
"warnings.filterwarnings",
"click.command",
"network_routing.pg_db_connection",
"pandas.concat"
] | [((361, 394), 'warnings.filterwarnings', 'warnings.filterwarnings', (['"""ignore"""'], {}), "('ignore')\n", (384, 394), False, 'import warnings\n'), ((398, 413), 'click.command', 'click.command', ([], {}), '()\n', (411, 413), False, 'import click\n'), ((415, 439), 'click.argument', 'click.argument', (['"""county"""'], ... |
import os
from ..utils import extract_frames, resize_frames
from ..boundingbox import BBoxFilter
class OTP():
"""
General Framework for Object Trajectory Proposal (OTP)
"""
def __init__(self, vind, working_root, vsize = 240):
frames, fps, orig_size = extract_frames(os.path.join(working_root,
'sn... | [
"os.path.join"
] | [((281, 336), 'os.path.join', 'os.path.join', (['working_root', "('snippets/' + vind + '.mp4')"], {}), "(working_root, 'snippets/' + vind + '.mp4')\n", (293, 336), False, 'import os\n')] |
# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import scipy
import scipy.spatial
from .standardize import standardize
def distance(X=None, method="mahalanobis"):
"""Distance.
Compute distance using different metrics.
Parameters
----------
X : array or DataFrame
A datafra... | [
"scipy.linalg.inv",
"scipy.spatial.distance.mahalanobis",
"pandas.DataFrame"
] | [((1355, 1376), 'scipy.linalg.inv', 'scipy.linalg.inv', (['cov'], {}), '(cov)\n', (1371, 1376), False, 'import scipy\n'), ((755, 770), 'pandas.DataFrame', 'pd.DataFrame', (['X'], {}), '(X)\n', (767, 770), True, 'import pandas as pd\n'), ((1492, 1563), 'scipy.spatial.distance.mahalanobis', 'scipy.spatial.distance.mahala... |
# 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... | [
"DialogClassParameters.DialogClassParameters.__init__"
] | [((1010, 1131), 'DialogClassParameters.DialogClassParameters.__init__', 'DialogClassParameters.DialogClassParameters.__init__', (['self', 'winId', 'winLabel', 'dClass', 'createId', 'setterFn', 'creationFlag'], {}), '(self, winId, winLabel,\n dClass, createId, setterFn, creationFlag)\n', (1062, 1131), False, 'import ... |
from django.shortcuts import render, redirect, get_object_or_404
from .models import TodoList
from .forms import TodoForm
from django.utils import timezone
from django.contrib import messages
from .forms import CreateUserForm
from django.contrib.auth import login, logout, authenticate
from django.contrib.auth.decorator... | [
"django.contrib.auth.decorators.login_required",
"django.shortcuts.redirect",
"django.contrib.messages.error",
"django.utils.timezone.now",
"django.shortcuts.get_object_or_404",
"django.contrib.auth.logout",
"django.contrib.auth.authenticate",
"django.shortcuts.render",
"django.contrib.messages.succ... | [((374, 411), 'django.contrib.auth.decorators.login_required', 'login_required', ([], {'login_url': '"""loginpage"""'}), "(login_url='loginpage')\n", (388, 411), False, 'from django.contrib.auth.decorators import login_required\n'), ((577, 614), 'django.contrib.auth.decorators.login_required', 'login_required', ([], {'... |
#####################################################################################
# CLASSICS - CalcuLAtionS of Self Interaction Cross Sections #
# by <NAME>, <NAME>, <NAME>, <NAME> and <NAME> #
#####################################################################################
# Requirement... | [
"scipy.special.loggamma",
"numpy.log",
"numpy.logspace",
"numpy.angle",
"numpy.clip",
"numpy.sin",
"numpy.array",
"numpy.loadtxt",
"numpy.cos",
"scipy.special.kn",
"numpy.log10",
"scipy.special.gamma",
"numpy.sqrt"
] | [((5345, 5383), 'numpy.logspace', 'np.logspace', (['(-5)', '(5)', '(101)'], {'endpoint': '(True)'}), '(-5, 5, 101, endpoint=True)\n', (5356, 5383), True, 'import numpy as np\n'), ((5396, 5433), 'numpy.logspace', 'np.logspace', (['(-3)', '(3)', '(61)'], {'endpoint': '(True)'}), '(-3, 3, 61, endpoint=True)\n', (5407, 543... |
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import init
import math
class BasicBlock(nn.Module):
def __init__(self, in_channels, out_channels, stride):
super(BasicBlock, self).__init__()
reduction = 0.5
if 2 == stride:
reduction = 1
elif in_channels > out_c... | [
"math.sqrt",
"torch.nn.Sequential",
"torch.nn.functional.avg_pool2d",
"torch.nn.Conv2d",
"torch.nn.BatchNorm2d",
"torch.nn.init.kaiming_normal",
"torch.nn.functional.relu"
] | [((1166, 1194), 'torch.nn.BatchNorm2d', 'nn.BatchNorm2d', (['out_channels'], {}), '(out_channels)\n', (1180, 1194), True, 'import torch.nn as nn\n'), ((1256, 1271), 'torch.nn.Sequential', 'nn.Sequential', ([], {}), '()\n', (1269, 1271), True, 'import torch.nn as nn\n'), ((2067, 2081), 'torch.nn.functional.relu', 'F.rel... |
import os
import maya.cmds as cmds
from cmt.io.obj import import_obj, export_obj
import cmt.shortcuts as shortcuts
def get_blendshape_node(geometry):
"""Get the first blendshape node upstream from the given geometry.
:param geometry: Name of the geometry
:return: The blendShape node name
"""
geo... | [
"cmt.io.obj.import_obj",
"maya.cmds.listHistory",
"maya.cmds.nodeType",
"maya.cmds.listConnections",
"maya.cmds.disconnectAttr",
"cmt.io.obj.export_obj",
"maya.cmds.delete",
"maya.cmds.duplicate",
"maya.cmds.setAttr",
"cmt.shortcuts.get_shape",
"os.path.join",
"os.listdir",
"maya.cmds.blendS... | [((328, 357), 'cmt.shortcuts.get_shape', 'shortcuts.get_shape', (['geometry'], {}), '(geometry)\n', (347, 357), True, 'import cmt.shortcuts as shortcuts\n'), ((931, 960), 'cmt.shortcuts.get_shape', 'shortcuts.get_shape', (['geometry'], {}), '(geometry)\n', (950, 960), True, 'import cmt.shortcuts as shortcuts\n'), ((181... |
# 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... | [
"mxnet.nd.ones",
"mxnet.sym.Convolution",
"nose.runmodule",
"mxnet.nd.zeros",
"mxnet.contrib.tensorrt.init_tensorrt_params",
"mxnet.sym.Variable",
"mxnet.gpu",
"mxnet.nd.random.uniform",
"mxnet.sym.BatchNorm"
] | [((957, 981), 'mxnet.nd.ones', 'mx.nd.ones', (['(1, 1, 3, 3)'], {}), '((1, 1, 3, 3))\n', (967, 981), True, 'import mxnet as mx\n'), ((1023, 1040), 'mxnet.nd.zeros', 'mx.nd.zeros', (['(1,)'], {}), '((1,))\n', (1034, 1040), True, 'import mxnet as mx\n'), ((1081, 1098), 'mxnet.nd.zeros', 'mx.nd.zeros', (['(1,)'], {}), '((... |
# database.py
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from sqlalchemy.ext.declarative import declarative_base
engine = create_engine("sqlite:///./data/songs.db", connect_args={"check_same_thread": False})
OrmSession = sessionmaker(autocommit=False, autoflush=False, bind=engine)
Ba... | [
"sqlalchemy.create_engine",
"sqlalchemy.ext.declarative.declarative_base",
"sqlalchemy.orm.sessionmaker"
] | [((158, 248), 'sqlalchemy.create_engine', 'create_engine', (['"""sqlite:///./data/songs.db"""'], {'connect_args': "{'check_same_thread': False}"}), "('sqlite:///./data/songs.db', connect_args={\n 'check_same_thread': False})\n", (171, 248), False, 'from sqlalchemy import create_engine\n'), ((257, 317), 'sqlalchemy.o... |
import argparse
from pathlib import Path
import matplotlib.pyplot as plt
from datastructs.instance import Instance
from datastructs.result import Result
import vizualization.gantt
def _parse_args():
parser = argparse.ArgumentParser(description='Show a gantt chart for a energy limits scheduling result.')
par... | [
"pathlib.Path",
"matplotlib.pyplot.show",
"argparse.ArgumentParser"
] | [((216, 317), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Show a gantt chart for a energy limits scheduling result."""'}), "(description=\n 'Show a gantt chart for a energy limits scheduling result.')\n", (239, 317), False, 'import argparse\n'), ((1070, 1080), 'matplotlib.pyplot.sh... |
# -*- coding: UTF-8 -*-
"""
:Script: movepnts.py
:Author: <EMAIL>
:Modified: 2017-04-06
:Notes:
:- arcpy.da.FeatureClassToNumPyArray(in_table, field_names, {where_clause},
: {spatial_reference}, {explode_to_points},
: {skip_nulls}, {null_va... | [
"arcpy.da.NumPyArrayToFeatureClass",
"arcpy.da.FeatureClassToNumPyArray",
"arcpy.CopyFeatures_management",
"numpy.array",
"arcpytools_pnt.fc_info"
] | [((1076, 1107), 'numpy.array', 'np.array', (['[dx, dy]'], {'dtype': '"""<f8"""'}), "([dx, dy], dtype='<f8')\n", (1084, 1107), True, 'import numpy as np\n'), ((1145, 1159), 'arcpytools_pnt.fc_info', 'fc_info', (['in_fc'], {}), '(in_fc)\n', (1152, 1159), False, 'from arcpytools_pnt import fc_info, tweet\n'), ((1362, 1421... |
from algoplex.api.common.market_data import MarketData
import threading
import os
import time
class MarketDataSim(MarketData):
def __init__(self, market_data_file):
self.market_data_file = market_data_file
self.subscribers = []
self.subscribed = False
self.watcher = None
se... | [
"threading.Thread",
"os.path.dirname",
"time.sleep"
] | [((1170, 1217), 'threading.Thread', 'threading.Thread', ([], {'target': 'self.watch_market_data'}), '(target=self.watch_market_data)\n', (1186, 1217), False, 'import threading\n'), ((448, 473), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (463, 473), False, 'import os\n'), ((1721, 1736), 't... |
# Data Preprocessing Template
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.preprocessing import Imputer
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import S... | [
"pandas.read_csv",
"sklearn.model_selection.train_test_split"
] | [((369, 392), 'pandas.read_csv', 'pd.read_csv', (['"""Data.csv"""'], {}), "('Data.csv')\n", (380, 392), True, 'import pandas as pd\n'), ((980, 1033), 'sklearn.model_selection.train_test_split', 'train_test_split', (['X', 'y'], {'test_size': '(0.2)', 'random_state': '(0)'}), '(X, y, test_size=0.2, random_state=0)\n', (9... |
import os
FFMPEG_PATH = os.path.join("external_tools", "ffmpeg", "bin")
SOX_PATH = os.path.join("external_tools", "sox")
# you must have a valid Opensubtitles User-Agent for subtitle downloading to work!
opensubtitles_credentials = {'user': 'user', 'password': 'password'}
| [
"os.path.join"
] | [((25, 72), 'os.path.join', 'os.path.join', (['"""external_tools"""', '"""ffmpeg"""', '"""bin"""'], {}), "('external_tools', 'ffmpeg', 'bin')\n", (37, 72), False, 'import os\n'), ((84, 121), 'os.path.join', 'os.path.join', (['"""external_tools"""', '"""sox"""'], {}), "('external_tools', 'sox')\n", (96, 121), False, 'im... |
import infomaker
import datetime
root = infomaker.infomaker()
if __name__ == "__main__":
while 1:#메인루프
if datetime.date.today() != root.start:#날짜가 바뀌면 재시작
root.start = datetime.date.today()
try:
print(root.weather("개포동"))
print(root.music_rank(5))
... | [
"infomaker.infomaker",
"datetime.date.today"
] | [((42, 63), 'infomaker.infomaker', 'infomaker.infomaker', ([], {}), '()\n', (61, 63), False, 'import infomaker\n'), ((121, 142), 'datetime.date.today', 'datetime.date.today', ([], {}), '()\n', (140, 142), False, 'import datetime\n'), ((195, 216), 'datetime.date.today', 'datetime.date.today', ([], {}), '()\n', (214, 216... |
import rdflib
import numpy as np
from sklearn.utils.validation import check_is_fitted
from gensim.models.word2vec import Word2Vec
import tqdm
import copy
from rdf2vec.graph import Vertex
from hashlib import md5
import itertools
from rdf2vec.walkers import RandomWalker
import findspark
import os
import shutil
import ti... | [
"os.mkdir",
"pyspark.SparkContext",
"pyspark.SparkConf",
"os.path.isdir",
"time.gmtime",
"sklearn.utils.validation.check_is_fitted",
"time.time",
"gensim.models.word2vec.Word2Vec",
"shutil.rmtree",
"findspark.init",
"os.path.join",
"os.listdir"
] | [((1265, 1289), 'os.listdir', 'os.listdir', (['self.dirname'], {}), '(self.dirname)\n', (1275, 1289), False, 'import os\n'), ((3791, 3807), 'findspark.init', 'findspark.init', ([], {}), '()\n', (3805, 3807), False, 'import findspark\n'), ((3834, 3845), 'pyspark.SparkConf', 'SparkConf', ([], {}), '()\n', (3843, 3845), F... |
"""
basic game for learning reinforcement learning
"""
import numpy as np
import gym
# basic implementation
env = gym.make("CartPole-v0")
best_params = [0 for _ in range(4)]
max_steps = 0
for times in range(1000):
observation = env.reset()
params = np.random.random(4)
for step in range(200):
action = int(np.d... | [
"gym.make",
"numpy.dot",
"numpy.median",
"keras.layers.Dropout",
"numpy.zeros",
"numpy.random.random",
"numpy.array",
"keras.layers.Dense",
"numpy.mean",
"numpy.random.randint",
"numpy.random.rand",
"keras.models.Sequential"
] | [((117, 140), 'gym.make', 'gym.make', (['"""CartPole-v0"""'], {}), "('CartPole-v0')\n", (125, 140), False, 'import gym\n'), ((471, 490), 'numpy.random.random', 'np.random.random', (['(4)'], {}), '(4)\n', (487, 490), True, 'import numpy as np\n'), ((713, 736), 'gym.make', 'gym.make', (['"""CartPole-v0"""'], {}), "('Cart... |
# Copyright 2020 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... | [
"autosynth.providers.apiary.list_apis",
"unittest.mock.patch.object",
"unittest.mock.patch.dict"
] | [((697, 731), 'unittest.mock.patch.object', 'patch.object', (['GitHub', '"""list_files"""'], {}), "(GitHub, 'list_files')\n", (709, 731), False, 'from unittest.mock import patch\n'), ((733, 783), 'unittest.mock.patch.dict', 'patch.dict', (['os.environ', "{'GITHUB_TOKEN': 'unused'}"], {}), "(os.environ, {'GITHUB_TOKEN':... |
import numpy as np
from scipy import (special, stats)
from astropy.io import fits
def get_j_rv(dataframe):
jv = []
for i in range(len(dataframe)):
jv.append(np.sqrt((2/np.pi) * dataframe["t"].iloc[i] * (dataframe["RV jitter"].iloc[i]**2 - 0.11**2)))
jv_data = np.array(jv)
return jv_data
#y... | [
"numpy.log",
"scipy.stats.norm.logpdf",
"numpy.array",
"numpy.exp",
"scipy.special.logsumexp",
"numpy.sqrt"
] | [((282, 294), 'numpy.array', 'np.array', (['jv'], {}), '(jv)\n', (290, 294), True, 'import numpy as np\n'), ((626, 681), 'scipy.stats.norm.logpdf', 'stats.norm.logpdf', (['y'], {'loc': 'mu_single', 'scale': 'sigma_single'}), '(y, loc=mu_single, scale=sigma_single)\n', (643, 681), False, 'from scipy import special, stat... |
from config import SHORT_COMMANDS
class Command:
"""
A command object, mainly for the preprocessing.
Required for both HTML tags and system commands (both preprocessing commands [^cmd] and processing commands [@cmd])
"""
def __init__(self, command="", parms=[], spaces=0, text=""):
self.comm... | [
"config.SHORT_COMMANDS.items"
] | [((3710, 3732), 'config.SHORT_COMMANDS.items', 'SHORT_COMMANDS.items', ([], {}), '()\n', (3730, 3732), False, 'from config import SHORT_COMMANDS\n')] |
import pytest
from primrose.base.pipeline import AbstractPipeline
from primrose.base.pipeline import PipelineModeType
from primrose.configuration.configuration import Configuration
from primrose.data_object import DataObject
from primrose.readers.csv_reader import CsvReader
from primrose.base.transformer_sequence impor... | [
"primrose.base.transformer_sequence.TransformerSequence",
"primrose.node_factory.NodeFactory",
"primrose.base.pipeline.PipelineModeType.names",
"pandas.read_csv",
"testfixtures.LogCapture",
"logging.info",
"pytest.raises",
"primrose.configuration.configuration.Configuration",
"primrose.base.pipeline... | [((1650, 1726), 'primrose.configuration.configuration.Configuration', 'Configuration', ([], {'config_location': 'None', 'is_dict_config': '(True)', 'dict_config': 'config'}), '(config_location=None, is_dict_config=True, dict_config=config)\n', (1663, 1726), False, 'from primrose.configuration.configuration import Confi... |
# plot.py
#
# Copyright (c) [2017] [yukirin]
#
# This software is released under the MIT License.
# http://opensource.org/licenses/mit-license.php
# ==============================================================================
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d.axes3d import ... | [
"matplotlib.pyplot.title",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"numpy.array",
"numpy.squeeze",
"mpl_toolkits.mplot3d.axes3d.Axes3D"
] | [((367, 385), 'numpy.squeeze', 'np.squeeze', (['actual'], {}), '(actual)\n', (377, 385), True, 'import numpy as np\n'), ((398, 417), 'numpy.squeeze', 'np.squeeze', (['predict'], {}), '(predict)\n', (408, 417), True, 'import numpy as np\n'), ((449, 482), 'matplotlib.pyplot.title', 'plt.title', (['"""NN [LSTM] $\\\\sin(x... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from fincalc import Bankomat
# Выполнить индивидуальное задание 1 лабораторной работы 12, максимально задействовав
# имеющиеся в Python средства перегрузки операторов.
# Вариант 11.
# Выполнить индивидуальное задание 1 лабораторной работы 13, оформив все классы програм... | [
"fincalc.Bankomat"
] | [((625, 676), 'fincalc.Bankomat', 'Bankomat', ([], {'start_sum': '(150)', 'new_sum': '(200)', 'final_sum': '(350)'}), '(start_sum=150, new_sum=200, final_sum=350)\n', (633, 676), False, 'from fincalc import Bankomat\n'), ((711, 762), 'fincalc.Bankomat', 'Bankomat', ([], {'start_sum': '(200)', 'new_sum': '(288)', 'final... |
from django.test import RequestFactory, TestCase
from studies.logic.game import Game
from studies.models import StudiesNotesProgression
from studies.tests.speed_set_up import SpeedSetUP
class GameTest(TestCase):
def setUp(self):
# Every test needs access to the request factory.
self.factory = Requ... | [
"studies.tests.speed_set_up.SpeedSetUP",
"studies.logic.game.Game",
"studies.models.StudiesNotesProgression.objects.filter",
"django.test.RequestFactory"
] | [((316, 332), 'django.test.RequestFactory', 'RequestFactory', ([], {}), '()\n', (330, 332), False, 'from django.test import RequestFactory, TestCase\n'), ((356, 368), 'studies.tests.speed_set_up.SpeedSetUP', 'SpeedSetUP', ([], {}), '()\n', (366, 368), False, 'from studies.tests.speed_set_up import SpeedSetUP\n'), ((389... |
from glob import glob
def create_neg_annotations() -> None:
"""
Create a list of negative images as per OpenCV guidlines
:return: None
"""
with open("bg.txt", "w+") as file_:
file_.write('\n'.join(glob("negatives/*.jpg")))
if __name__ == "__main__":
create_neg_annotations() | [
"glob.glob"
] | [((227, 250), 'glob.glob', 'glob', (['"""negatives/*.jpg"""'], {}), "('negatives/*.jpg')\n", (231, 250), False, 'from glob import glob\n')] |
from django.contrib.gis.db import models
from django.core.exceptions import ValidationError
import magic
from ... import tasks
from ..common import ChecksumFile, ModifiableEntry, SpatialEntry
from ..constants import DB_SRID
from ..mixins import TaskEventMixin
def validate_archive(field_file):
"""Validate file is... | [
"django.contrib.gis.db.models.ForeignKey",
"django.core.exceptions.ValidationError",
"django.contrib.gis.db.models.CharField",
"django.contrib.gis.db.models.TextField",
"django.contrib.gis.db.models.GeometryCollectionField",
"django.contrib.gis.db.models.OneToOneField"
] | [((892, 949), 'django.contrib.gis.db.models.ForeignKey', 'models.ForeignKey', (['ChecksumFile'], {'on_delete': 'models.CASCADE'}), '(ChecksumFile, on_delete=models.CASCADE)\n', (909, 949), False, 'from django.contrib.gis.db import models\n'), ((1270, 1315), 'django.contrib.gis.db.models.CharField', 'models.CharField', ... |
# coding: utf-8
from __future__ import unicode_literals
import re
import json
from .common import InfoExtractor
from ..compat import compat_HTTPError
from ..utils import (
ExtractorError,
int_or_none,
parse_iso8601,
str_or_none,
urlencode_postdata,
clean_html,
)
class ShahidIE(InfoExtractor)... | [
"re.match",
"json.dumps"
] | [((3489, 3519), 're.match', 're.match', (['self._VALID_URL', 'url'], {}), '(self._VALID_URL, url)\n', (3497, 3519), False, 'import re\n'), ((1815, 1883), 'json.dumps', 'json.dumps', (["{'email': email, 'password': password, 'basic': 'false'}"], {}), "({'email': email, 'password': password, 'basic': 'false'})\n", (1825,... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import torch
import torch.nn as nn
def array2samples_distance(array1, array2):
"""
arguments:
array1: the array, size: (num_point, num_feature)
array2: the samples, size: (num_point, num_feature)
returns:
distances: each entry is the ... | [
"torch.mean",
"torch.ones",
"torch.randint",
"torch.unsqueeze",
"torch.FloatTensor",
"torch.randn",
"torch.max",
"torch.arange",
"torch.zeros",
"torch.reshape",
"torch.sum",
"torch.min"
] | [((778, 805), 'torch.sum', 'torch.sum', (['distances'], {'dim': '(1)'}), '(distances, dim=1)\n', (787, 805), False, 'import torch\n'), ((821, 871), 'torch.reshape', 'torch.reshape', (['distances', '(num_point2, num_point1)'], {}), '(distances, (num_point2, num_point1))\n', (834, 871), False, 'import torch\n'), ((934, 9... |
from pygears.util.test_utils import synth_check_fixt
from pygears.util.test_utils import formal_check_fixt
from pygears.util.test_utils import hdl_check_fixt
from pygears.util.test_utils import clear
from pygears.util.test_utils import sim_cls
from pygears.util.test_utils import cosim_cls
from pygears.util.test_utils i... | [
"pytest.fixture"
] | [((371, 399), 'pytest.fixture', 'pytest.fixture', ([], {'autouse': '(True)'}), '(autouse=True)\n', (385, 399), False, 'import pytest\n')] |
# -*- coding: utf-8 -*-
# Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and Contributors and Contributors
# See license.txt
from __future__ import unicode_literals
import frappe
import unittest
from erpnext.stock.get_item_details import get_pos_profile
from erpnext.accounts.doctype.pos_profile.pos_profile import g... | [
"frappe.db.exists",
"erpnext.accounts.doctype.pos_profile.pos_profile.get_child_nodes",
"frappe.db.sql",
"frappe.db.get_value",
"frappe._dict",
"erpnext.stock.get_item_details.get_pos_profile"
] | [((2956, 3008), 'frappe.db.sql', 'frappe.db.sql', (['"""delete from `tabPOS Payment Method`"""'], {}), "('delete from `tabPOS Payment Method`')\n", (2969, 3008), False, 'import frappe\n'), ((3010, 3055), 'frappe.db.sql', 'frappe.db.sql', (['"""delete from `tabPOS Profile`"""'], {}), "('delete from `tabPOS Profile`')\n"... |
####################################################################################################
#
# nth_root_module.py
#
# Author:
# <NAME>
#
# The module for learning facts about the nth root. Note that for each n, "NthRoot(n)" is a
# different function
#
#
######################################################... | [
"polya.main.messages.announce_module",
"polya.main.terms.Var",
"polya.main.terms.root",
"polya.util.timer.start",
"polya.util.timer.stop"
] | [((1027, 1076), 'polya.main.messages.announce_module', 'messages.announce_module', (['"""nth root value module"""'], {}), "('nth root value module')\n", (1051, 1076), True, 'import polya.main.messages as messages\n'), ((1085, 1108), 'polya.util.timer.start', 'timer.start', (['timer.ROOT'], {}), '(timer.ROOT)\n', (1096,... |
import tensorflow as tf
from tensorflow.keras.layers import Embedding, Bidirectional, LSTM, Dense
from tensorflow.python.framework.func_graph import convert_structure_to_signature
class Char_level_bidirectional(tf.keras.Model):
def __init__(self, vocab_size, embedding_dim, rnn_units):
super().__init__(se... | [
"tensorflow.keras.layers.Embedding",
"tensorflow.keras.layers.LSTM",
"tensorflow.zeros",
"tensorflow.keras.layers.Dense"
] | [((465, 532), 'tensorflow.keras.layers.Embedding', 'Embedding', ([], {'input_dim': 'self.vocab_size', 'output_dim': 'self.embedding_dim'}), '(input_dim=self.vocab_size, output_dim=self.embedding_dim)\n', (474, 532), False, 'from tensorflow.keras.layers import Embedding, Bidirectional, LSTM, Dense\n'), ((724, 741), 'ten... |
from typing import Callable, List, NoReturn, Optional, Union
import numpy as np
from nptyping import Array
from .metrics import Metrics
from .range import Range
def _validate_heartbeats(heartbeats: List[int]) -> [None, NoReturn]:
# TODO: Custom error class
# TODO: Validate heartbeats length. They should con... | [
"numpy.count_nonzero",
"numpy.average",
"numpy.ndenumerate",
"numpy.std",
"numpy.percentile",
"numpy.mean",
"numpy.array"
] | [((960, 1002), 'numpy.percentile', 'np.percentile', (['data', 'low_border_percentile'], {}), '(data, low_border_percentile)\n', (973, 1002), True, 'import numpy as np\n'), ((1021, 1064), 'numpy.percentile', 'np.percentile', (['data', 'high_border_percentile'], {}), '(data, high_border_percentile)\n', (1034, 1064), True... |
# -*- coding: utf-8 -*-
"""Top-level package for bleak."""
__author__ = """<NAME>"""
__email__ = "<EMAIL>"
import os
import sys
import logging
import platform
import asyncio
from bleak.__version__ import __version__ # noqa: F401
from bleak.backends.bluezdbus import check_bluez_version
from bleak.exc import BleakEr... | [
"bleak.exc.BleakError",
"argparse.ArgumentParser",
"logging.StreamHandler",
"bleak.backends.bluezdbus.check_bluez_version",
"os.environ.get",
"logging.Formatter",
"platform.win32_ver",
"logging.NullHandler",
"platform.system",
"logging.getLogger"
] | [((414, 441), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (431, 441), False, 'import logging\n'), ((335, 364), 'os.environ.get', 'os.environ.get', (['"""READTHEDOCS"""'], {}), "('READTHEDOCS')\n", (349, 364), False, 'import os\n'), ((461, 482), 'logging.NullHandler', 'logging.NullHandl... |
# Generated by Django 3.2.4 on 2021-11-15 05:38
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('players', '0003_rename_u... | [
"django.db.models.OneToOneField",
"django.db.migrations.swappable_dependency",
"django.db.models.BigAutoField",
"django.db.models.CharField",
"django.db.models.IntegerField"
] | [((227, 284), 'django.db.migrations.swappable_dependency', 'migrations.swappable_dependency', (['settings.AUTH_USER_MODEL'], {}), '(settings.AUTH_USER_MODEL)\n', (258, 284), False, 'from django.db import migrations, models\n'), ((479, 575), 'django.db.models.BigAutoField', 'models.BigAutoField', ([], {'auto_created': '... |
import time
from parking_lot.entities.parking_lot import ParkingLot
from parking_lot.repositories.parking_slot import ParkingSlotRepository
from typing import List
from parking_lot.entities.car import Car
from parking_lot.entities.merchant import Merchant
from parking_lot.repositories.car import CarRepository
from park... | [
"parking_lot.exceptions.ParkingLotExistsException",
"parking_lot.repositories.parking_slot.ParkingSlotRepository",
"parking_lot.exceptions.ParkingLotNotExistsException",
"parking_lot.repositories.parking_lots.ParkingLotRepository",
"time.strftime",
"parking_lot.entities.parking_slot.ParkingSlot",
"parki... | [((719, 751), 'parking_lot.entities.merchant.Merchant', 'Merchant', (['(1)', '"""ABC"""', '"""2020-01-01"""'], {}), "(1, 'ABC', '2020-01-01')\n", (727, 751), False, 'from parking_lot.entities.merchant import Merchant\n'), ((812, 834), 'parking_lot.repositories.parking_lots.ParkingLotRepository', 'ParkingLotRepository',... |
from abc import abstractmethod
from misc.learn_weights.entities_strategy.best import Best
from tools.cache_manager import CacheManager
class AbsMetric(object):
def __init__(self, cache_dir='../examples/caches', pre_processors=None, multipleEntitiesStrategy=Best()):
"""
Initiates the extractor, w... | [
"misc.learn_weights.entities_strategy.best.Best",
"tools.cache_manager.CacheManager.instance"
] | [((264, 270), 'misc.learn_weights.entities_strategy.best.Best', 'Best', ([], {}), '()\n', (268, 270), False, 'from misc.learn_weights.entities_strategy.best import Best\n'), ((618, 641), 'tools.cache_manager.CacheManager.instance', 'CacheManager.instance', ([], {}), '()\n', (639, 641), False, 'from tools.cache_manager ... |
from django.apps import apps
from django.contrib import admin
from django.contrib.auth import get_user_model
from django.contrib.auth.admin import UserAdmin as BaseUserAdmin
from .conf import LOGIN_TYPE_MA, LOGIN_TYPE_XBL, config
from .models import MicrosoftAccount, XboxLiveAccount
__all__ = [
"MicrosoftAccountA... | [
"django.contrib.admin.site.is_registered",
"django.contrib.auth.get_user_model",
"django.contrib.admin.site.register",
"django.contrib.admin.register",
"django.apps.apps.is_installed",
"django.contrib.admin.site.unregister"
] | [((451, 467), 'django.contrib.auth.get_user_model', 'get_user_model', ([], {}), '()\n', (465, 467), False, 'from django.contrib.auth import get_user_model\n'), ((596, 625), 'django.apps.apps.is_installed', 'apps.is_installed', (['"""djangoql"""'], {}), "('djangoql')\n", (613, 625), False, 'from django.apps import apps\... |
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