code stringlengths 22 1.05M | apis listlengths 1 3.31k | extract_api stringlengths 75 3.25M |
|---|---|---|
"""articles and categories tables
Revision ID: d842da27e2b3
Revises: <PASSWORD>
Create Date: 2021-08-15 17:22:40.491374
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = '<KEY>'
down_revision = '5<PASSWORD>'
branch_labels = None
depends_on = None
def upgrade():... | [
"sqlalchemy.ForeignKeyConstraint",
"sqlalchemy.DateTime",
"alembic.op.drop_table",
"alembic.op.f",
"sqlalchemy.Text",
"sqlalchemy.PrimaryKeyConstraint",
"sqlalchemy.Integer",
"sqlalchemy.String"
] | [((1463, 1488), 'alembic.op.drop_table', 'op.drop_table', (['"""articles"""'], {}), "('articles')\n", (1476, 1488), False, 'from alembic import op\n'), ((1564, 1591), 'alembic.op.drop_table', 'op.drop_table', (['"""categories"""'], {}), "('categories')\n", (1577, 1591), False, 'from alembic import op\n'), ((537, 566), ... |
################################################################################
# This software was developed by the University of Tennessee as part of the
# Distributed Data Analysis of Neutron Scattering Experiments (DANSE)
# project funded by the US National Science Foundation.
#
# See the license text in license.t... | [
"wx.Button",
"wx.Dialog.__init__",
"wx.GridBagSizer",
"wx.TextCtrl.__init__",
"wx.BoxSizer",
"wx.StaticLine",
"wx.lib.scrolledpanel.ScrolledPanel.__init__"
] | [((614, 657), 'wx.lib.scrolledpanel.ScrolledPanel.__init__', 'ScrolledPanel.__init__', (['self', '*args'], {}), '(self, *args, **kwds)\n', (636, 657), False, 'from wx.lib.scrolledpanel import ScrolledPanel\n'), ((887, 928), 'wx.TextCtrl.__init__', 'wx.TextCtrl.__init__', (['self', '*args'], {}), '(self, *args, **kwds)\... |
import json
from datetime import date, datetime
from hamcrest import assert_that, has_entries
from brunns.json.decoder import ExtendedJSONDecoder
def test_decode_date():
# Given
given = """{"somedate": "1968-07-21", "foo": 99, "bar": "sausages"}"""
# When
actual = json.loads(given, cls=ExtendedJSON... | [
"datetime.datetime",
"json.loads",
"datetime.date",
"hamcrest.has_entries"
] | [((286, 328), 'json.loads', 'json.loads', (['given'], {'cls': 'ExtendedJSONDecoder'}), '(given, cls=ExtendedJSONDecoder)\n', (296, 328), False, 'import json\n'), ((546, 588), 'json.loads', 'json.loads', (['given'], {'cls': 'ExtendedJSONDecoder'}), '(given, cls=ExtendedJSONDecoder)\n', (556, 588), False, 'import json\n'... |
# -*- coding: utf-8 -*-
"""
jishaku.models
~~~~~~~~~~~~~~
Functions for modifying or interfacing with discord.py models.
:copyright: (c) 2021 Devon (Gorialis) R
:license: MIT, see LICENSE for more details.
"""
import copy
import typing
import discord
from jishaku.types import ContextT
async def copy_context_wi... | [
"copy.copy"
] | [((695, 717), 'copy.copy', 'copy.copy', (['ctx.message'], {}), '(ctx.message)\n', (704, 717), False, 'import copy\n')] |
"""
Package responsable for fetching the translations.
"""
import asyncio
import logging
import os
from concurrent.futures._base import CancelledError
import telepot
from telepot.namedtuple import InlineQueryResultArticle, InputTextMessageContent
import helpers
BASE_URL = os.environ['BOT_BASE_URL']
class Transla... | [
"telepot.glance",
"telepot.namedtuple.InputTextMessageContent",
"helpers.get_lang_name",
"asyncio.get_event_loop",
"logging.info"
] | [((1418, 1469), 'telepot.glance', 'telepot.glance', (['inline_query'], {'flavor': '"""inline_query"""'}), "(inline_query, flavor='inline_query')\n", (1432, 1469), False, 'import telepot\n'), ((611, 635), 'asyncio.get_event_loop', 'asyncio.get_event_loop', ([], {}), '()\n', (633, 635), False, 'import asyncio\n'), ((1036... |
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from... | [
"pulumi.get",
"pulumi.getter",
"pulumi.set",
"pulumi.InvokeOptions",
"pulumi.runtime.invoke"
] | [((3537, 3574), 'pulumi.getter', 'pulumi.getter', ([], {'name': '"""accessEndpoints"""'}), "(name='accessEndpoints')\n", (3550, 3574), False, 'import pulumi\n'), ((3732, 3773), 'pulumi.getter', 'pulumi.getter', ([], {'name': '"""applicationSettings"""'}), "(name='applicationSettings')\n", (3745, 3773), False, 'import p... |
#!/usr/bin/env python
import logging
FORMAT = '%(levelname)-8s [%(asctime)-15s] : %(message)s'
logging.basicConfig(format=FORMAT, level=logging.DEBUG)
if __name__ == '__main__':
lvl_name = logging.getLevelName( logging.getLogger().getEffectiveLevel() )
print("Logging at level: {}".format(lvl_name))
logg... | [
"logging.basicConfig",
"logging.getLogger",
"logging.warn",
"logging.debug",
"logging.fatal",
"logging.info",
"logging.error"
] | [((97, 152), 'logging.basicConfig', 'logging.basicConfig', ([], {'format': 'FORMAT', 'level': 'logging.DEBUG'}), '(format=FORMAT, level=logging.DEBUG)\n', (116, 152), False, 'import logging\n'), ((316, 346), 'logging.debug', 'logging.debug', (['"""debug message"""'], {}), "('debug message')\n", (329, 346), False, 'impo... |
import subprocess
def lease(ifacename):
shellcommand = r"sudo dhcpcd "+ifacename
process = subprocess.run(shellcommand, shell=True, check=True, stdout=subprocess.PIPE, universal_newlines=True)
output = list(filter(None,map(str.strip, process.stdout.split("\n"))))
return output
| [
"subprocess.run"
] | [((101, 206), 'subprocess.run', 'subprocess.run', (['shellcommand'], {'shell': '(True)', 'check': '(True)', 'stdout': 'subprocess.PIPE', 'universal_newlines': '(True)'}), '(shellcommand, shell=True, check=True, stdout=subprocess.PIPE,\n universal_newlines=True)\n', (115, 206), False, 'import subprocess\n')] |
from nose.tools import eq_, ok_
from django.core.urlresolvers import reverse
from .base import ManageTestCase
class TestTasksTester(ManageTestCase):
def test_dashboard(self):
url = reverse('manage:tasks_tester')
response = self.client.get(url)
eq_(response.status_code, 200)
res... | [
"nose.tools.ok_",
"nose.tools.eq_",
"django.core.urlresolvers.reverse"
] | [((198, 228), 'django.core.urlresolvers.reverse', 'reverse', (['"""manage:tasks_tester"""'], {}), "('manage:tasks_tester')\n", (205, 228), False, 'from django.core.urlresolvers import reverse\n'), ((277, 307), 'nose.tools.eq_', 'eq_', (['response.status_code', '(200)'], {}), '(response.status_code, 200)\n', (280, 307),... |
'''
Process IMDb datasets and store them as parquet files
'''
import datetime
import os
import pyspark.sql.functions as F
import util
def fix_year(col):
'''
Fix the year column by getting rid of bad values
Params
- col: column name
'''
# Get today's date
now = datetime.datetime.now()
... | [
"os.path.join",
"datetime.datetime.now",
"pyspark.sql.functions.col",
"os.path.abspath",
"util.create_spark_session"
] | [((296, 319), 'datetime.datetime.now', 'datetime.datetime.now', ([], {}), '()\n', (317, 319), False, 'import datetime\n'), ((756, 798), 'os.path.join', 'os.path.join', (['source', '"""name.basics.tsv.gz"""'], {}), "(source, 'name.basics.tsv.gz')\n", (768, 798), False, 'import os\n'), ((3650, 3693), 'os.path.join', 'os.... |
from enum import Enum, auto, unique
class AutoName(Enum):
def _generate_next_value_(self, start, count, last_values) -> str:
assert isinstance(self, str)
region_sep = "_REGION_INTERNAL"
if self != region_sep and \
("$" + region_sep.lower()) not in last_values:
#... | [
"enum.auto"
] | [((718, 724), 'enum.auto', 'auto', ([], {}), '()\n', (722, 724), False, 'from enum import Enum, auto, unique\n'), ((742, 748), 'enum.auto', 'auto', ([], {}), '()\n', (746, 748), False, 'from enum import Enum, auto, unique\n'), ((767, 773), 'enum.auto', 'auto', ([], {}), '()\n', (771, 773), False, 'from enum import Enum... |
import numpy as np
import utils as ut
import detector as det
from sklearn.preprocessing import PolynomialFeatures
from sklearn.linear_model import LinearRegression
class GazeModel:
"""Linear regression model for gaze estimation.
"""
def __init__(self, calibration_images, calibration_positions):
"... | [
"sklearn.preprocessing.PolynomialFeatures",
"detector.find_pupil",
"numpy.ones",
"numpy.asarray",
"numpy.asscalar",
"numpy.linalg.lstsq",
"utils.pupil_to_int",
"sklearn.linear_model.LinearRegression",
"numpy.round"
] | [((1090, 1131), 'numpy.linalg.lstsq', 'np.linalg.lstsq', (['D', 'targets_X'], {'rcond': 'None'}), '(D, targets_X, rcond=None)\n', (1105, 1131), True, 'import numpy as np\n'), ((1154, 1195), 'numpy.linalg.lstsq', 'np.linalg.lstsq', (['D', 'targets_Y'], {'rcond': 'None'}), '(D, targets_Y, rcond=None)\n', (1169, 1195), Tr... |
import logging
import multiprocessing
import time
from radosgw_agent import worker
from radosgw_agent import client
from radosgw_agent.util import get_dev_logger
from radosgw_agent.exceptions import NotFound, HttpError
log = logging.getLogger(__name__)
dev_log = get_dev_logger(__name__)
# the replica log api only s... | [
"logging.getLogger",
"radosgw_agent.util.get_dev_logger",
"radosgw_agent.client.get_log_info",
"radosgw_agent.client.set_worker_bound",
"radosgw_agent.client.list_metadata_keys",
"radosgw_agent.client.get_log",
"time.sleep",
"radosgw_agent.client.connection",
"radosgw_agent.client.get_metadata_secti... | [((228, 255), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (245, 255), False, 'import logging\n'), ((266, 290), 'radosgw_agent.util.get_dev_logger', 'get_dev_logger', (['__name__'], {}), '(__name__)\n', (280, 290), False, 'from radosgw_agent.util import get_dev_logger\n'), ((1956, 1990)... |
from nose import tools
import minIRC_Client
from minIRC_Client import log
from minIRC_Client.client import Client
import asyncio
import sys
logger = log.setup_custom_logger('root.tests', level=5)
HOST = '127.0.0.1'
PORT = 10101
channels = set()
users = {}
def setup():
loop = asyncio.get_event_loop()
client... | [
"minIRC_Client.client.Client",
"asyncio.get_event_loop",
"sys.exit",
"minIRC_Client.log.setup_custom_logger"
] | [((150, 196), 'minIRC_Client.log.setup_custom_logger', 'log.setup_custom_logger', (['"""root.tests"""'], {'level': '(5)'}), "('root.tests', level=5)\n", (173, 196), False, 'from minIRC_Client import log\n'), ((285, 309), 'asyncio.get_event_loop', 'asyncio.get_event_loop', ([], {}), '()\n', (307, 309), False, 'import as... |
# -*- coding: utf-8 -*-
"""
eve.io.mongo.flask_pymongo
~~~~~~~~~~~~~~~~~~~
Flask extension to create Mongo connection and database based on
configuration.
:copyright: (c) 2017 by <NAME>.
:license: BSD, see LICENSE for more details.
"""
from flask import current_app
from pymongo import MongoC... | [
"pymongo.uri_parser.validate_options",
"pymongo.MongoClient",
"pymongo.uri_parser.parse_uri"
] | [((1790, 1832), 'pymongo.uri_parser.validate_options', 'uri_parser.validate_options', (['client_kwargs'], {}), '(client_kwargs)\n', (1817, 1832), False, 'from pymongo import MongoClient, uri_parser\n'), ((2496, 2524), 'pymongo.MongoClient', 'MongoClient', ([], {}), '(**client_kwargs)\n', (2507, 2524), False, 'from pymo... |
# -*- coding: utf-8 -*-
import django.contrib.admin.helpers
from ajaximage.utils import format_image
from django.contrib.admin.utils import display_for_field
from django.core.files.storage import default_storage
from django.db.models import Field
from django.db.models.fields.files import FileDescriptor, ImageFieldFile
... | [
"ajaximage.utils.format_image",
"django.contrib.admin.utils.display_for_field"
] | [((2151, 2170), 'ajaximage.utils.format_image', 'format_image', (['value'], {}), '(value)\n', (2163, 2170), False, 'from ajaximage.utils import format_image\n'), ((2196, 2248), 'django.contrib.admin.utils.display_for_field', 'display_for_field', (['value', 'field', 'empty_value_display'], {}), '(value, field, empty_val... |
'''
Created on Mar 5, 2019
@author: <NAME>
'''
from labs.common import ConfigConst
from labs.common.ConfigUtil import ConfigUtil
from labs.module06.MqttClientConnector import MqttClientConnector
'''
# importing SensorData class to use the attributes of sensor
'''
from labs.common.SensorData import SensorD... | [
"labs.common.DataUtil.DataUtil",
"labs.common.SensorData.SensorData",
"labs.common.ConfigUtil.ConfigUtil",
"labs.module06.MqttClientConnector.MqttClientConnector",
"datetime.datetime.now",
"logging.info"
] | [((566, 624), 'labs.common.ConfigUtil.ConfigUtil', 'ConfigUtil', (['"""../../../config/ConnectedDevicesConfig.props"""'], {}), "('../../../config/ConnectedDevicesConfig.props')\n", (576, 624), False, 'from labs.common.ConfigUtil import ConfigUtil\n'), ((775, 800), 'labs.common.SensorData.SensorData', 'SensorData', (['t... |
import math
from typing import TYPE_CHECKING, Any, List, Optional, Tuple, Union
import moderngl as mgl
import numpy as np
import vpype as vp
from ._utils import ColorType, load_program, load_texture_array
if TYPE_CHECKING: # pragma: no cover
from .engine import Engine
ResourceType = Union[mgl.Buffer, mgl.Text... | [
"vpype.as_vector",
"math.ceil",
"math.floor",
"numpy.array",
"numpy.empty",
"numpy.concatenate",
"numpy.arange"
] | [((1260, 1586), 'numpy.array', 'np.array', (['[(0, 0), (paper_size[0], 0), (paper_size[0], paper_size[1]), (0, paper_size\n [1]), (paper_size[0], shadow_size), (paper_size[0] + shadow_size,\n shadow_size), (paper_size[0] + shadow_size, paper_size[1] + shadow_size\n ), (shadow_size, paper_size[1] + shadow_size)... |
""" Helper and utility functions for the library. """
from copy import deepcopy
from dataclasses import asdict
import hashlib
import json
import logging
import os
import platform
import shutil
import subprocess
import sys
from typing import Dict
TIMESTAMP_FORMAT = "%Y-%m-%d-T%H%M%S"
"""The datetime format string used... | [
"logging.getLogger",
"logging.StreamHandler",
"copy.deepcopy",
"os.path.exists",
"dataclasses.asdict",
"subprocess.Popen",
"platform.platform",
"subprocess.run",
"logging.FileHandler",
"logging.addLevelName",
"logging.root.manager.loggerDict.items",
"shutil.which",
"logging.warning",
"logg... | [((1999, 2046), 'os.path.exists', 'os.path.exists', (['f"""{prefix}{CONFIGURATION_FILE}"""'], {}), "(f'{prefix}{CONFIGURATION_FILE}')\n", (2013, 2046), False, 'import os\n'), ((9147, 9176), 'logging.getLogRecordFactory', 'logging.getLogRecordFactory', ([], {}), '()\n', (9174, 9176), False, 'import logging\n'), ((9320, ... |
# coding=utf-8
# Copyright 2021 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | [
"tensorflow.tile",
"tensorflow.equal",
"tensorflow.shape",
"tf_agents.networks.actor_distribution_rnn_network.ActorDistributionRnnNetwork",
"tensorflow.reduce_sum",
"numpy.log",
"tf_agents.utils.nest_utils.flatten_up_to",
"tf_agents.networks.network.tf_inspect.getargspec",
"tf_agents.specs.tensor_sp... | [((3503, 3540), 'numpy.zeros', 'np.zeros', (['(h, w, d)'], {'dtype': 'np.float32'}), '((h, w, d), dtype=np.float32)\n', (3511, 3540), True, 'import numpy as np\n'), ((9877, 9936), 'tensorflow.nest.map_structure', 'tf.nest.map_structure', (['(lambda l: None)', 'preprocessing_layers'], {}), '(lambda l: None, preprocessin... |
import numpy as np
__all__ = [
'Task'
]
class Task(object):
def __init__(self, ndim=None, seed=None):
self._ndim = ndim
self.rng = np.random.RandomState(seed)
def set_seed(self, seed=None):
self.rng = np.random.RandomState(seed)
def name(self):
return self.__class__.__name__
def ndim(self... | [
"numpy.random.get_state",
"numpy.random.set_state",
"skopt.learning.gaussian_process.kernels.Matern",
"numpy.random.seed",
"numpy.random.RandomState"
] | [((145, 172), 'numpy.random.RandomState', 'np.random.RandomState', (['seed'], {}), '(seed)\n', (166, 172), True, 'import numpy as np\n'), ((222, 249), 'numpy.random.RandomState', 'np.random.RandomState', (['seed'], {}), '(seed)\n', (243, 249), True, 'import numpy as np\n'), ((713, 734), 'numpy.random.get_state', 'np.ra... |
import pandas as pd
import gensim
import multiprocessing
import numpy as np
from utils import pickle_obj, semantic_search_author, semantic_search_word, get_related_authors, get_related_words, translate_dict
from sklearn.manifold import TSNE
from bokeh.plotting import figure, show, output_notebook, output_file, save
fro... | [
"pandas.read_csv",
"gensim.test.utils.get_tmpfile",
"multiprocessing.cpu_count",
"numpy.concatenate",
"gensim.models.doc2vec.Doc2Vec",
"time.time",
"gensim.utils.simple_preprocess"
] | [((479, 531), 'pandas.read_csv', 'pd.read_csv', (['"""assets/dataframes/all_authors_df_2004"""'], {}), "('assets/dataframes/all_authors_df_2004')\n", (490, 531), True, 'import pandas as pd\n'), ((540, 577), 'pandas.read_csv', 'pd.read_csv', (['"""assets/dataframes/suDf"""'], {}), "('assets/dataframes/suDf')\n", (551, 5... |
from unittest import TestCase
from numpy import array, ndarray
from numpy.testing import assert_array_equal
from trigger import accel_value, trigger_time
class TriggerTimeTest(TestCase):
def test_estimates_when_function_exceeds(self):
function = 10
t = array([1599574034])
trig_level = 100
... | [
"numpy.array",
"numpy.ndarray",
"trigger.trigger_time",
"trigger.accel_value",
"numpy.testing.assert_array_equal"
] | [((275, 294), 'numpy.array', 'array', (['[1599574034]'], {}), '([1599574034])\n', (280, 294), False, 'from numpy import array, ndarray\n'), ((339, 350), 'numpy.ndarray', 'ndarray', (['[]'], {}), '([])\n', (346, 350), False, 'from numpy import array, ndarray\n'), ((368, 405), 'trigger.trigger_time', 'trigger_time', (['f... |
import json
import maya
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
days = {
0:'monday',
1:'tuesday',
2:'wednesday',
3:'thursday',
4:'friday',
5:'saturday',
6:'sunday'
}
NEWLINE = '\n'
SPACE = ' '
COLON = ':'
def day(t):
# where t means unformatted time
... | [
"matplotlib.pyplot.ylabel",
"numpy.arange",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.close",
"maya.parse",
"matplotlib.pyplot.scatter",
"pandas.DataFrame",
"matplotlib.pyplot.title",
"json.dump",
"matplotlib.pyplot.show"
] | [((3456, 3465), 'matplotlib.pyplot.gca', 'plt.gca', ([], {}), '()\n', (3463, 3465), True, 'import matplotlib.pyplot as plt\n'), ((3893, 3959), 'pandas.DataFrame', 'pd.DataFrame', (["{'day': arj_day, 'hour': arj_hour, 'date': arj_date}"], {}), "({'day': arj_day, 'hour': arj_hour, 'date': arj_date})\n", (3905, 3959), Tru... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function
import ctypes, sys
import platform
#import shutil
import os
# 是否是Windows系统
def is_windows():
return platform.system() == "Windows"
# 是否是管理员权限执行，用于link等需要管理员权限时的判断
def is_admin():
if is_windows():
try:
return ctypes.windll.she... | [
"os.path.exists",
"os.makedirs",
"os.symlink",
"os.path.split",
"os.path.isfile",
"platform.system",
"ctypes.windll.shell32.IsUserAnAdmin",
"os.system"
] | [((843, 857), 'os.system', 'os.system', (['cmd'], {}), '(cmd)\n', (852, 857), False, 'import os\n'), ((1042, 1061), 'os.path.exists', 'os.path.exists', (['dir'], {}), '(dir)\n', (1056, 1061), False, 'import os\n'), ((1294, 1314), 'os.symlink', 'os.symlink', (['src', 'dst'], {}), '(src, dst)\n', (1304, 1314), False, 'im... |
from .base import Command
import actions
class Move(Command):
def _execute(self, args):
if len(args) == 2:
step = float(args[1])
self.logger.debug("Got step of " + str(step))
if step > 0:
self.logger.debug("Got direction of %s" % args[0])
... | [
"actions.left",
"actions.right",
"actions.forward",
"actions.backwards"
] | [((384, 405), 'actions.forward', 'actions.forward', (['step'], {}), '(step)\n', (399, 405), False, 'import actions\n'), ((484, 507), 'actions.backwards', 'actions.backwards', (['step'], {}), '(step)\n', (501, 507), False, 'import actions\n'), ((586, 604), 'actions.left', 'actions.left', (['step'], {}), '(step)\n', (598... |
from sqlalchemy import (
MetaData,
Table,
Column,
Integer,
DateTime,
NVARCHAR,
String,
Index,
Boolean,
)
from migrate.changeset.constraint import ForeignKeyConstraint, UniqueConstraint
meta = MetaData()
field = Table(
"field",
meta,
Column("id", Integer, primary_key=Tr... | [
"sqlalchemy.Table",
"migrate.changeset.constraint.ForeignKeyConstraint",
"sqlalchemy.MetaData",
"migrate.changeset.constraint.UniqueConstraint",
"sqlalchemy.String",
"sqlalchemy.Index",
"sqlalchemy.Column"
] | [((230, 240), 'sqlalchemy.MetaData', 'MetaData', ([], {}), '()\n', (238, 240), False, 'from sqlalchemy import MetaData, Table, Column, Integer, DateTime, NVARCHAR, String, Index, Boolean\n'), ((660, 704), 'sqlalchemy.Index', 'Index', (['"""ix_field_study_id"""', 'field.c.study_id'], {}), "('ix_field_study_id', field.c.... |
### cpx-noise-synth v1.0
### CircuitPython (on CPX) synth module for noise on internal speaker
### This plays a noise with some pitch colouration
### listening on MIDI channel 10
### Tested with CPX and CircuitPython and 4.0.0-beta.7
### Needs recent adafruit_midi module
### copy this file to CPX as code.py
### MI... | [
"array.array",
"math.pow",
"audioio.RawSample",
"audioio.AudioOut",
"digitalio.DigitalInOut",
"random.randint",
"adafruit_midi.MIDI"
] | [((1880, 1924), 'digitalio.DigitalInOut', 'digitalio.DigitalInOut', (['board.SPEAKER_ENABLE'], {}), '(board.SPEAKER_ENABLE)\n', (1902, 1924), False, 'import digitalio\n'), ((2014, 2045), 'audioio.AudioOut', 'audioio.AudioOut', (['board.SPEAKER'], {}), '(board.SPEAKER)\n', (2030, 2045), False, 'import audioio\n'), ((268... |
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
from torch.autograd import Function
from torch.autograd import Variable
from utils.box_utils import decode
class RefineDetect(Function):
"""At test time, Detect is the final layer of SSD. Decode location preds,
apply non-maximum suppress... | [
"utils.box_utils.decode",
"torch.zeros"
] | [((1597, 1631), 'torch.zeros', 'torch.zeros', (['(1)', 'self.num_priors', '(4)'], {}), '(1, self.num_priors, 4)\n', (1608, 1631), False, 'import torch\n'), ((1654, 1703), 'torch.zeros', 'torch.zeros', (['(1)', 'self.num_priors', 'self.num_classes'], {}), '(1, self.num_priors, self.num_classes)\n', (1665, 1703), False, ... |
#encoding=utf-8
import os
import sys
import time
import logging
import requests
# import gevent
import json
ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0, ROOT)
from mq import MessageQueue
def process(body):
in_data = json.loads(body)
content = in_data.get('content', '')... | [
"os.path.abspath",
"mq.MessageQueue",
"json.loads",
"sys.path.insert"
] | [((175, 199), 'sys.path.insert', 'sys.path.insert', (['(0)', 'ROOT'], {}), '(0, ROOT)\n', (190, 199), False, 'import sys\n'), ((263, 279), 'json.loads', 'json.loads', (['body'], {}), '(body)\n', (273, 279), False, 'import json\n'), ((368, 457), 'mq.MessageQueue', 'MessageQueue', ([], {'host': '"""myhost"""', 'port': '"... |
import numpy as np
import sys
from flare import gp, env, struc, kernels
from flare.modules import analyze_gp, qe_parsers
from mc_kernels import mc_simple
from scipy.optimize import minimize
import time
import datetime
def sweep(txt_name, data_file, cell, training_snaps, cutoffs, kernel,
kernel_grad, initial... | [
"numpy.abs",
"numpy.sqrt",
"datetime.datetime.now",
"flare.modules.analyze_gp.MDAnalysis",
"flare.modules.analyze_gp.get_gp_from_snaps",
"flare.modules.analyze_gp.predict_forces_on_test_set",
"time.time"
] | [((466, 504), 'flare.modules.analyze_gp.MDAnalysis', 'analyze_gp.MDAnalysis', (['data_file', 'cell'], {}), '(data_file, cell)\n', (487, 504), False, 'from flare.modules import analyze_gp, qe_parsers\n'), ((1611, 1649), 'flare.modules.analyze_gp.MDAnalysis', 'analyze_gp.MDAnalysis', (['data_file', 'cell'], {}), '(data_f... |
# Generated by Django 3.1.7 on 2021-04-26 13:27
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('checkout', '0005_order_user_profile'),
]
operations = [
migrations.AlterField(
model_name='order',
name='county',
... | [
"django.db.models.CharField"
] | [((336, 391), 'django.db.models.CharField', 'models.CharField', ([], {'blank': '(True)', 'default': '""""""', 'max_length': '(80)'}), "(blank=True, default='', max_length=80)\n", (352, 391), False, 'from django.db import migrations, models\n'), ((514, 569), 'django.db.models.CharField', 'models.CharField', ([], {'blank... |
import torch
from torch import nn
from pytorch_lightning.core.lightning import LightningModule
class RBVPredictor(LightningModule):
@staticmethod
def add_model_specific_args(parent_parser):
parser = parent_parser.add_argument_group("Model parameters")
parser.add_argument("--lr", type=float, d... | [
"torch.nn.ReLU",
"torch.nn.Dropout",
"torch.abs",
"torch.nn.Flatten",
"torch.nn.Conv2d",
"torch.nn.HuberLoss",
"torch.nn.MaxPool2d",
"torch.nn.Linear",
"torch.cat"
] | [((446, 460), 'torch.nn.HuberLoss', 'nn.HuberLoss', ([], {}), '()\n', (458, 460), False, 'from torch import nn\n'), ((2688, 2729), 'torch.nn.Linear', 'nn.Linear', ([], {'in_features': '(1)', 'out_features': '(16)'}), '(in_features=1, out_features=16)\n', (2697, 2729), False, 'from torch import nn\n'), ((3210, 3251), 't... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from typing import List, Tuple, Union
from hwt.code import If
from hwt.interfaces.utils import addClkRstn
from hwt.pyUtils.arrayQuery import iter_with_last
from hwt.serializer.mode import serializeParamsUniq
from hwt.synthesizer.interfaceLevel.unitImplHelpers import getS... | [
"hwt.interfaces.utils.addClkRstn",
"hwtLib.handshaked.compBase.HandshakedCompBase._config",
"hwt.synthesizer.interfaceLevel.unitImplHelpers.getSignalName",
"hwt.synthesizer.param.Param",
"hwt.synthesizer.utils.to_rtl_str"
] | [((1333, 1365), 'hwtLib.handshaked.compBase.HandshakedCompBase._config', 'HandshakedCompBase._config', (['self'], {}), '(self)\n', (1359, 1365), False, 'from hwtLib.handshaked.compBase import HandshakedCompBase\n'), ((1418, 1426), 'hwt.synthesizer.param.Param', 'Param', (['(1)'], {}), '(1)\n', (1423, 1426), False, 'fro... |
# Copyright 2019 <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 agreed to in writing, softwa... | [
"mishmash_rpc_grpc.MishmashServiceStub",
"uuid.uuid4"
] | [((2156, 2222), 'mishmash_rpc_grpc.MishmashServiceStub', 'mishmash_rpc_grpc.MishmashServiceStub', (['ConnectionFactory.__channel'], {}), '(ConnectionFactory.__channel)\n', (2193, 2222), False, 'import mishmash_rpc_grpc\n'), ((1098, 1110), 'uuid.uuid4', 'uuid.uuid4', ([], {}), '()\n', (1108, 1110), False, 'import uuid\n... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Apr 29 16:10:21 2018
@author: michelcassard
"""
import seaborn as sns
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.pyplot as plt2
import pandas as pd
from pandas import datetime
import math, time
import itertools
from sklearn im... | [
"keras.layers.core.Flatten",
"matplotlib.pyplot.ylabel",
"numpy.hstack",
"numpy.log",
"math.sqrt",
"numpy.array",
"numpy.cov",
"numpy.mean",
"numpy.reshape",
"numpy.repeat",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"pandas.concat",
"keras.layers.convolutional.MaxPooling1D",
... | [((1014, 1090), 'os.chdir', 'os.chdir', (['"""/Users/michelcassard/Dropbox (MIT)/15.960 Independant Study/Data"""'], {}), "('/Users/michelcassard/Dropbox (MIT)/15.960 Independant Study/Data')\n", (1022, 1090), False, 'import os\n'), ((1134, 1152), 'pandas.ExcelFile', 'pd.ExcelFile', (['file'], {}), '(file)\n', (1146, 1... |
# coding=utf-8
# Copyright 2021 TF-Transformers Authors.
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | [
"tensorflow.shape",
"tf_transformers.activations.get_activation",
"tensorflow.keras.utils.register_keras_serializable",
"tensorflow.range",
"tensorflow.keras.layers.Dense",
"tensorflow.gather",
"tensorflow.matmul",
"tensorflow.keras.layers.LayerNormalization",
"tensorflow.reshape",
"tensorflow.nn.... | [((834, 901), 'tensorflow.keras.utils.register_keras_serializable', 'tf.keras.utils.register_keras_serializable', ([], {'package': '"""legacyai.text"""'}), "(package='legacyai.text')\n", (876, 901), True, 'import tensorflow as tf\n'), ((2164, 2298), 'tensorflow.keras.layers.Dense', 'tf.keras.layers.Dense', (['self._hid... |
# This file contains utility code for parsing UTXO information
#
# Author: <NAME>
#
import base58
import binascii
import hashlib
import re
# This helper function gets an address from a scriptSig
def address_from_scriptsig(script_sig):
# Get the pubkey from the scriptSig
ascii_pubkey = script_sig.split(" ")[1]
# ... | [
"hashlib.sha256",
"hashlib.new",
"base58.b58encode",
"re.match",
"binascii.unhexlify"
] | [((354, 386), 'binascii.unhexlify', 'binascii.unhexlify', (['ascii_pubkey'], {}), '(ascii_pubkey)\n', (372, 386), False, 'import binascii\n'), ((398, 422), 'binascii.unhexlify', 'binascii.unhexlify', (['"""00"""'], {}), "('00')\n", (416, 422), False, 'import binascii\n'), ((503, 527), 'hashlib.new', 'hashlib.new', (['"... |
# -*- coding: utf-8 -*-
import scrapy
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule
from ..utils import extract_CN_from_content
from ..items import ScrapySpiderItem
import re
class A411Spider(CrawlSpider):
name = '411'
allowed_domains = ['cangyuan.gov.cn']
sta... | [
"scrapy.linkextractors.LinkExtractor",
"re.search"
] | [((1251, 1311), 'scrapy.linkextractors.LinkExtractor', 'LinkExtractor', ([], {'allow': '"""/cyxrmzf/[a-z]+\\\\d+/\\\\d+/index\\\\.html"""'}), "(allow='/cyxrmzf/[a-z]+\\\\d+/\\\\d+/index\\\\.html')\n", (1264, 1311), False, 'from scrapy.linkextractors import LinkExtractor\n'), ((1338, 1390), 'scrapy.linkextractors.LinkEx... |
from torch import nn
import numpy as np
import torch
import os
from networks.Autoencoder import Encoder, Decoder
from dataLoader import data_load
######################
# Create the Model #
######################
class Model(nn.Module):
def __init__(self, c):
super(Model, self).__init__()
self.... | [
"os.path.exists",
"dataLoader.data_load",
"torch.load",
"torch.nn.DataParallel",
"networks.Autoencoder.Decoder",
"os.mkdir",
"torch.no_grad",
"networks.Autoencoder.Encoder"
] | [((620, 769), 'dataLoader.data_load', 'data_load', ([], {'path_input': '"""sample-dataset/damage/dmg"""', 'path_output': '"""sample-dataset/damage/dmg"""', 'batch_size': '(10)', 'dataset_size': '(1000)', 'shuffle': '(False)'}), "(path_input='sample-dataset/damage/dmg', path_output=\n 'sample-dataset/damage/dmg', bat... |
import os
import gettext
import random
import discord
from discord.ext import commands
from discord_slash import SlashCommand
from discord_slash.utils import manage_commands
from bot_config import BOT_NAME, BOT_PREFIX, BOT_LANGUAGE, BOT_ENV_TOKEN
# Localization things
translation = gettext.translation('userpicker', ... | [
"gettext.translation",
"random.sample",
"discord.Activity",
"discord_slash.SlashCommand"
] | [((286, 372), 'gettext.translation', 'gettext.translation', (['"""userpicker"""'], {'localedir': '"""./locale"""', 'languages': '[BOT_LANGUAGE]'}), "('userpicker', localedir='./locale', languages=[\n BOT_LANGUAGE])\n", (305, 372), False, 'import gettext\n'), ((4635, 4672), 'discord_slash.SlashCommand', 'SlashCommand... |
from urllib.parse import quote,unquote
from estring.consts import greece_md,greece_upperch
from estring.estring import is_int_str,is_float_str
import re
from efuntool.ebooltool import blor_rtrn_first
from efuntool.etypetool import is_number
#####
def rplc(s,d):
for k in d:
s = s.replace(k,d[k])
return(... | [
"re.compile",
"urllib.parse.quote",
"estring.estring.is_int_str",
"efuntool.etypetool.is_number",
"urllib.parse.unquote"
] | [((1389, 1405), 'estring.estring.is_int_str', 'is_int_str', (['s[0]'], {}), '(s[0])\n', (1399, 1405), False, 'from estring.estring import is_int_str, is_float_str\n'), ((1983, 1991), 'urllib.parse.quote', 'quote', (['k'], {}), '(k)\n', (1988, 1991), False, 'from urllib.parse import quote, unquote\n'), ((2142, 2158), 'e... |
from aitime.data import DataPool
from aitime.train import KFoldTrainer
"""
Complete the logical process of training and evaluation
"""
# 1. Create a DataPool - an object to hold all the data I have
dp = DataPool()
# 2. Extract Sequences from raw data
dp.extract_sequences()
# 3. Extract Windows from Sequences
dp... | [
"aitime.data.DataPool",
"aitime.train.KFoldTrainer"
] | [((209, 219), 'aitime.data.DataPool', 'DataPool', ([], {}), '()\n', (217, 219), False, 'from aitime.data import DataPool\n'), ((542, 558), 'aitime.train.KFoldTrainer', 'KFoldTrainer', (['dp'], {}), '(dp)\n', (554, 558), False, 'from aitime.train import KFoldTrainer\n')] |
from django.urls import path, include
from rest_framework.routers import DefaultRouter
from recipe.views import TagsViewSet, IngredientsViewSet, RecipeViewSet
router = DefaultRouter()
router.register('tags', TagsViewSet)
router.register('ingredients', IngredientsViewSet)
router.register("recipes", RecipeViewSet)
... | [
"rest_framework.routers.DefaultRouter",
"django.urls.include"
] | [((170, 185), 'rest_framework.routers.DefaultRouter', 'DefaultRouter', ([], {}), '()\n', (183, 185), False, 'from rest_framework.routers import DefaultRouter\n'), ((367, 387), 'django.urls.include', 'include', (['router.urls'], {}), '(router.urls)\n', (374, 387), False, 'from django.urls import path, include\n')] |
import csv
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import make_interp_spline
x1 = []
y1 = []
x2 = []
y2 = []
with open("barrier_width.csv", "r", encoding='utf8') as csvfile:
plots = csv.reader(csvfile, delimiter=",")
for row in plots:
x1.append(float(row... | [
"numpy.polyfit",
"numpy.array",
"matplotlib.pyplot.subplots",
"scipy.interpolate.make_interp_spline",
"csv.reader",
"numpy.poly1d",
"matplotlib.pyplot.show"
] | [((586, 626), 'numpy.array', 'np.array', (['[x for x in x1]'], {'dtype': '"""float"""'}), "([x for x in x1], dtype='float')\n", (594, 626), True, 'import numpy as np\n'), ((633, 673), 'numpy.array', 'np.array', (['[y for y in y1]'], {'dtype': '"""float"""'}), "([y for y in y1], dtype='float')\n", (641, 673), True, 'imp... |
import os
def data_file(path):
this_dir = os.path.dirname(__file__)
data_dir = os.path.join(this_dir, 'testdata')
return os.path.join(data_dir, path)
| [
"os.path.dirname",
"os.path.join"
] | [((48, 73), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (63, 73), False, 'import os\n'), ((89, 123), 'os.path.join', 'os.path.join', (['this_dir', '"""testdata"""'], {}), "(this_dir, 'testdata')\n", (101, 123), False, 'import os\n'), ((135, 163), 'os.path.join', 'os.path.join', (['data_dir... |
import os
import time
import yaml
import pickle
import numpy as np
from random import shuffle
from sklearn.neighbors import KDTree
ALL_LAYERS = np.array([[8,2],
[8,4],
[8,6],
[8,8],
[13,2],
[13,4],
... | [
"numpy.mean",
"os.listdir",
"pickle.dump",
"random.shuffle",
"os.makedirs",
"yaml.dump",
"numpy.where",
"numpy.random.choice",
"os.path.join",
"pickle.load",
"numpy.array",
"os.path.isdir",
"numpy.concatenate",
"numpy.std",
"time.time",
"numpy.random.shuffle"
] | [((146, 247), 'numpy.array', 'np.array', (['[[8, 2], [8, 4], [8, 6], [8, 8], [13, 2], [13, 4], [13, 6], [13, 8], [17, 2\n ], [17, 4]]'], {}), '([[8, 2], [8, 4], [8, 6], [8, 8], [13, 2], [13, 4], [13, 6], [13, 8\n ], [17, 2], [17, 4]])\n', (154, 247), True, 'import numpy as np\n'), ((507, 518), 'time.time', 'time.... |
# Copyright 2015 Cisco Systems, 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 requi... | [
"unittest.main",
"yabgp.message.attribute.aggregator.Aggregator.parse",
"yabgp.message.attribute.aggregator.Aggregator.construct"
] | [((1971, 1986), 'unittest.main', 'unittest.main', ([], {}), '()\n', (1984, 1986), False, 'import unittest\n'), ((961, 1022), 'yabgp.message.attribute.aggregator.Aggregator.parse', 'Aggregator.parse', ([], {'value': "b'\\x00\\x00p\\xd5>\\xe7\\xffy'", 'asn4': '(True)'}), "(value=b'\\x00\\x00p\\xd5>\\xe7\\xffy', asn4=True... |
import os
import unittest
import numpy as np
import pandas as pd
from lusidtools import logger
from lusidtools.cocoon.dateorcutlabel import DateOrCutLabel
from parameterized import parameterized
from datetime import datetime
import pytz
class CocoonDateOrCutLabelTests(unittest.TestCase):
@classmethod
def se... | [
"datetime.datetime",
"pytz.timezone",
"os.getenv",
"parameterized.parameterized.expand",
"lusidtools.cocoon.dateorcutlabel.DateOrCutLabel",
"numpy.array",
"numpy.datetime64",
"pandas.Timestamp"
] | [((3750, 4420), 'parameterized.parameterized.expand', 'parameterized.expand', (["[['YYYY-mm-dd_dashes', '2019-09-01', '%Y-%m-%d',\n '2019-09-01T00:00:00+00:00'], ['dd/mm/YYYY_ forwardslashes',\n '01/09/2019', '%d/%m/%Y', '2019-09-01T00:00:00+00:00'], [\n 'YYYY-mm-dd HH:MM:SS_dashes_and_colons', '2019-09-01 6:3... |
"""
PyTorch implementation of VAE found at: https://github.com/pytorch/examples/tree/master/vae.
"""
import torch
from torch import nn
import torch.nn.functional as F
class VAE(nn.Module):
def __init__(self, input_length, n_sensor_channel,
n_hidden = 400,
n_latent_features=20, no_variational=False... | [
"torch.randn_like",
"torch.exp",
"torch.nn.Linear"
] | [((383, 435), 'torch.nn.Linear', 'nn.Linear', (['(input_length * n_sensor_channel)', 'n_hidden'], {}), '(input_length * n_sensor_channel, n_hidden)\n', (392, 435), False, 'from torch import nn\n'), ((454, 492), 'torch.nn.Linear', 'nn.Linear', (['n_hidden', 'n_latent_features'], {}), '(n_hidden, n_latent_features)\n', (... |
# -*- coding: utf-8 -*-
"""
Unit tests for the statistics module.
:copyright: Copyright 2014-2016 by the Elephant team, see `doc/authors.rst`.
:license: Modified BSD, see LICENSE.txt for details.
"""
from __future__ import division
import itertools
import math
import sys
import unittest
import neo
import numpy as np... | [
"numpy.random.rand",
"elephant.kernels.GaussianKernel",
"elephant.statistics.fanofactor",
"elephant.statistics.lvr",
"elephant.kernels.__dict__.values",
"quantities.Quantity",
"elephant.kernels.TriangularKernel",
"numpy.array",
"elephant.statistics.isi",
"neo.core.SpikeTrain",
"numpy.arange",
... | [((42616, 42631), 'unittest2.main', 'unittest.main', ([], {}), '()\n', (42629, 42631), True, 'import unittest2 as unittest\n'), ((771, 863), 'numpy.array', 'np.array', (['[[0.3, 0.56, 0.87, 1.23], [0.02, 0.71, 1.82, 8.46], [0.03, 0.14, 0.15, 0.92]]'], {}), '([[0.3, 0.56, 0.87, 1.23], [0.02, 0.71, 1.82, 8.46], [0.03, 0.... |
import time
import numpy as np
from utils.misc_utils import create_testfiles
with open('parameters.txt', 'r') as inf:
parameters = eval(inf.read())
# Parameter initialization
features_per_node = 9
tree_depth = 3
nodes = 0
for i in range(tree_depth + 1):
nodes += np.power(4, i)
state_size = features_per_node... | [
"utils.misc_utils.create_testfiles",
"numpy.power"
] | [((275, 289), 'numpy.power', 'np.power', (['(4)', 'i'], {}), '(4, i)\n', (283, 289), True, 'import numpy as np\n'), ((485, 554), 'utils.misc_utils.create_testfiles', 'create_testfiles', (['current_parameters', 'test_nr'], {'nr_trials_per_test': '(100)'}), '(current_parameters, test_nr, nr_trials_per_test=100)\n', (501,... |
from django.contrib import admin
# Register your models here.
from profiles.models import User
class UserAdmin(admin.ModelAdmin):
pass
admin.site.register(User, UserAdmin) | [
"django.contrib.admin.site.register"
] | [((142, 178), 'django.contrib.admin.site.register', 'admin.site.register', (['User', 'UserAdmin'], {}), '(User, UserAdmin)\n', (161, 178), False, 'from django.contrib import admin\n')] |
from KerasUtils import save_trn_history, load_trn_history
class BaseLearner(object):
"""docstring for ClassName"""
# to be defined in each subclass
def __init__(self, input_shape, labels, verbose=True):
raise NotImplementedError("error message")
def save_weight(self, weight_path: Union[str, P... | [
"KerasUtils.save_trn_history",
"KerasUtils.load_trn_history"
] | [((748, 812), 'KerasUtils.save_trn_history', 'save_trn_history', ([], {'history': 'self.trn_his', 'saving_path': 'history_path'}), '(history=self.trn_his, saving_path=history_path)\n', (764, 812), False, 'from KerasUtils import save_trn_history, load_trn_history\n'), ((883, 925), 'KerasUtils.load_trn_history', 'load_tr... |
import struct
import factor_graph_pb2
import random
NVAR = 1000000
NQVAR = 1000000
fo = open("crf_mix/graph.variables.pb", "wb")
for i in range(0,NVAR):
v = factor_graph_pb2.Variable()
v.id = i
v.initialValue = 0
if random.random() < 0.8:
v.initialValue = 1
v.dataType = 0
v.isEvidence = True
v.cardinality ... | [
"factor_graph_pb2.Weight",
"factor_graph_pb2.GraphEdge",
"factor_graph_pb2.Factor",
"struct.pack",
"factor_graph_pb2.Variable",
"random.random"
] | [((2314, 2339), 'factor_graph_pb2.Weight', 'factor_graph_pb2.Weight', ([], {}), '()\n', (2337, 2339), False, 'import factor_graph_pb2\n'), ((2465, 2490), 'factor_graph_pb2.Weight', 'factor_graph_pb2.Weight', ([], {}), '()\n', (2488, 2490), False, 'import factor_graph_pb2\n'), ((161, 188), 'factor_graph_pb2.Variable', '... |
import numpy as np
from tensorflow.python.framework import ops
from tensorflow.python.framework import graph_util
from tensorflow.python.profiler.internal.flops_registry import (
_reduction_op_flops,
_binary_per_element_op_flops,
)
from tensorflow.keras import Sequential, Model
@ops.RegisterStatistics("FusedB... | [
"tensorflow.python.profiler.internal.flops_registry._binary_per_element_op_flops",
"tensorflow.compat.v1.RunMetadata",
"tensorflow.python.framework.ops.OpStats",
"tensorflow.compat.v1.profiler.profile",
"tensorflow.python.framework.ops.RegisterStatistics",
"tensorflow.python.framework.convert_to_constants... | [((290, 341), 'tensorflow.python.framework.ops.RegisterStatistics', 'ops.RegisterStatistics', (['"""FusedBatchNormV3"""', '"""flops"""'], {}), "('FusedBatchNormV3', 'flops')\n", (312, 341), False, 'from tensorflow.python.framework import ops\n'), ((1087, 1125), 'tensorflow.python.framework.ops.RegisterStatistics', 'ops... |
# -*- coding: utf-8 -*-
# This sample demonstrates handling intents from an Alexa skill using the Alexa Skills Kit SDK for Python.
# Please visit https://alexa.design/cookbook for additional examples on implementing slots, dialog management,
# session persistence, api calls, and more.
# This sample is built using the ... | [
"logging.getLogger",
"ask_sdk_dynamodb.adapter.DynamoDbAdapter",
"ask_sdk_core.utils.is_request_type",
"os.environ.get",
"boto3.resource",
"ask_sdk_core.skill_builder.CustomSkillBuilder",
"ask_sdk_core.utils.get_intent_name",
"ask_sdk_core.utils.is_intent_name"
] | [((789, 816), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (806, 816), False, 'import logging\n'), ((894, 939), 'os.environ.get', 'os.environ.get', (['"""DYNAMODB_PERSISTENCE_REGION"""'], {}), "('DYNAMODB_PERSISTENCE_REGION')\n", (908, 939), False, 'import os\n'), ((957, 1006), 'os.envi... |
import logging
import math
import typing
import torch
import mantrap.agents
import mantrap.constants
from ..base.particle import ParticleEnvironment
class PotentialFieldEnvironment(ParticleEnvironment):
"""Simplified version of social forces environment class.
The simplified model assumes static agents (a... | [
"torch.abs",
"logging.debug",
"torch.atan2",
"torch.sign",
"torch.zeros"
] | [((3728, 3742), 'torch.zeros', 'torch.zeros', (['(2)'], {}), '(2)\n', (3739, 3742), False, 'import torch\n'), ((4563, 4625), 'logging.debug', 'logging.debug', (['f"""particle {particle.id} impact = {ego_impact}"""'], {}), "(f'particle {particle.id} impact = {ego_impact}')\n", (4576, 4625), False, 'import logging\n'), (... |
import random
suits = ['Spades', 'Hearts', 'Clubs', 'Diamonds']
cards = ['A', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'J', 'Q', 'K']
nums = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 10, 10]
deck = []
for suit in suits:
for card in cards:
deck.append(f'{card} of {suit}')
values = dict(zip(cards, nums))
v... | [
"random.choices",
"random.choice"
] | [((387, 412), 'random.choices', 'random.choices', (['deck'], {'k': '(2)'}), '(deck, k=2)\n', (401, 412), False, 'import random\n'), ((790, 815), 'random.choices', 'random.choices', (['deck'], {'k': '(2)'}), '(deck, k=2)\n', (804, 815), False, 'import random\n'), ((1366, 1385), 'random.choice', 'random.choice', (['deck'... |
#%%
import os
import pandas as pd
import numpy as np
import copy
from tqdm import tqdm
from plot import plot
from utils.evaluator import evaluate, set_thresholds
from utils.evaluator_seg import compute_anomaly_scores, compute_metrics
# Univariate
from utils.data_loader import load_kpi, load_IoT_fridge
# Multivariate
... | [
"numpy.mean",
"numpy.flip",
"numpy.average",
"numpy.where",
"utils.evaluator.evaluate",
"os.path.join",
"numpy.max",
"plot.plot",
"os.path.isdir",
"copy.deepcopy",
"pandas.DataFrame",
"utils.evaluator_seg.compute_anomaly_scores",
"utils.evaluator.set_thresholds",
"utils.evaluator_seg.compu... | [((6713, 6737), 'copy.deepcopy', 'copy.deepcopy', (['ts_scores'], {}), '(ts_scores)\n', (6726, 6737), False, 'import copy\n'), ((6793, 6816), 'pandas.DataFrame', 'pd.DataFrame', (['ts_scores'], {}), '(ts_scores)\n', (6805, 6816), True, 'import pandas as pd\n'), ((7380, 7482), 'plot.plot', 'plot', (['model_name', 'ts_sc... |
"""
Инициализация бота bot, машины состояния storage и диспетчера dp.
"""
import os
import sys
from pathlib import Path
from aiogram import Bot, Dispatcher, types
from aiogram.contrib.fsm_storage.memory import MemoryStorage
DATA_DIR = os.path.join(Path(__file__).parents[1])
sys.path.append(DATA_DIR)
from data impor... | [
"aiogram.contrib.fsm_storage.memory.MemoryStorage",
"pathlib.Path",
"aiogram.Dispatcher",
"aiogram.Bot",
"sys.path.append"
] | [((278, 303), 'sys.path.append', 'sys.path.append', (['DATA_DIR'], {}), '(DATA_DIR)\n', (293, 303), False, 'import sys\n'), ((337, 397), 'aiogram.Bot', 'Bot', ([], {'token': 'config.BOT_TOKEN', 'parse_mode': 'types.ParseMode.HTML'}), '(token=config.BOT_TOKEN, parse_mode=types.ParseMode.HTML)\n', (340, 397), False, 'fro... |
# -*- coding: utf-8 -*-
# copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Unit tests for (dunder) composition functionality attached to the base class."""
__author__ = ["fkiraly"]
__all__ = []
from sklearn.preprocessing import StandardScaler
from sktime.classification.compose import Classifi... | [
"sktime.classification.distance_based.KNeighborsTimeSeriesClassifier",
"sktime.transformations.series.exponent.ExponentTransformer",
"sktime.utils._testing.panel._make_panel_X",
"sklearn.preprocessing.StandardScaler",
"sktime.utils._testing.panel._make_classification_y"
] | [((728, 790), 'sktime.utils._testing.panel._make_classification_y', '_make_classification_y', ([], {'n_instances': '(10)', 'random_state': 'RAND_SEED'}), '(n_instances=10, random_state=RAND_SEED)\n', (750, 790), False, 'from sktime.utils._testing.panel import _make_classification_y, _make_panel_X\n'), ((799, 874), 'skt... |
"""
This module provides an abstraction for managing cameras.
"""
try:
import cStringIO as io
except ImportError:
import io
from .check_platform import ON_RASPI
from ..utils.super_logger import logger
CAMERA_AVAILABLE = False
# Import the proper libraries depending on platform
if ON_RASPI:
try:
... | [
"cv2.imencode",
"picamera.PiCamera",
"cv2.VideoCapture",
"io.BytesIO"
] | [((1116, 1135), 'cv2.VideoCapture', 'cv2.VideoCapture', (['(0)'], {}), '(0)\n', (1132, 1135), False, 'import cv2\n'), ((1282, 1301), 'picamera.PiCamera', 'picamera.PiCamera', ([], {}), '()\n', (1299, 1301), False, 'import picamera\n'), ((2481, 2493), 'io.BytesIO', 'io.BytesIO', ([], {}), '()\n', (2491, 2493), False, 'i... |
#!/usr/bin/env python3
import argparse
import zlib
import sys
def matches(string, datastr, index):
substr = datastr[index:index+len(string)]
return substr.lower() == string.lower()
def can_split(last_block, blockiness):
checksum = zlib.crc32(last_block.encode('UTF-8'))
return (checksum % blockiness) ... | [
"sys.stdin.read",
"argparse.ArgumentParser"
] | [((547, 617), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Split a Turtle file into slices"""'}), "(description='Split a Turtle file into slices')\n", (570, 617), False, 'import argparse\n'), ((970, 986), 'sys.stdin.read', 'sys.stdin.read', ([], {}), '()\n', (984, 986), False, 'import ... |
import os
from shutil import rmtree
from databoard import (db, deployment_path, ramp_config, ramp_data_path,
ramp_kits_path)
def recreate_db():
"""Initialisation of a test database."""
db.session.close()
db.drop_all()
db.create_all()
print(db)
def deploy():
if os.gete... | [
"databoard.db.drop_all",
"os.getenv",
"os.makedirs",
"os.path.join",
"databoard.db.create_all",
"databoard.db.session.close",
"shutil.rmtree"
] | [((219, 237), 'databoard.db.session.close', 'db.session.close', ([], {}), '()\n', (235, 237), False, 'from databoard import db, deployment_path, ramp_config, ramp_data_path, ramp_kits_path\n'), ((242, 255), 'databoard.db.drop_all', 'db.drop_all', ([], {}), '()\n', (253, 255), False, 'from databoard import db, deploymen... |
# https://atcoder.jp/contests/practice2/tasks/practice2_d
import sys
from atcoder.maxflow import MFGraph
def main() -> None:
n, m = map(int, sys.stdin.readline().split())
s = n * m
t = s + 1
g = MFGraph(t + 1)
grid = [list(sys.stdin.readline().strip()) for _ in range(n)]
def enc(i: int, j: ... | [
"sys.stdin.readline",
"atcoder.maxflow.MFGraph"
] | [((215, 229), 'atcoder.maxflow.MFGraph', 'MFGraph', (['(t + 1)'], {}), '(t + 1)\n', (222, 229), False, 'from atcoder.maxflow import MFGraph\n'), ((149, 169), 'sys.stdin.readline', 'sys.stdin.readline', ([], {}), '()\n', (167, 169), False, 'import sys\n'), ((247, 267), 'sys.stdin.readline', 'sys.stdin.readline', ([], {}... |
from aetherling.helpers.nameCleanup import cleanName
from magma import *
from magma.frontend.coreir_ import GetCoreIRBackend
from aetherling.modules.hydrate import Dehydrate, Hydrate
from mantle.coreir.memory import DefineRAM, getRAMAddrWidth
__all__ = ['DefineRAMAnyType', 'RAMAnyType']
@cache_definition
def DefineR... | [
"magma.frontend.coreir_.GetCoreIRBackend",
"aetherling.modules.hydrate.Hydrate",
"mantle.coreir.memory.DefineRAM",
"mantle.coreir.memory.getRAMAddrWidth",
"aetherling.modules.hydrate.Dehydrate"
] | [((650, 668), 'mantle.coreir.memory.getRAMAddrWidth', 'getRAMAddrWidth', (['n'], {}), '(n)\n', (665, 668), False, 'from mantle.coreir.memory import DefineRAM, getRAMAddrWidth\n'), ((1107, 1119), 'aetherling.modules.hydrate.Dehydrate', 'Dehydrate', (['t'], {}), '(t)\n', (1116, 1119), False, 'from aetherling.modules.hydr... |
from pySDC.projects.parallelSDC.newton_vs_sdc import main as main_newton_vs_sdc
from pySDC.projects.parallelSDC.newton_vs_sdc import plot_graphs as plot_graphs_newton_vs_sdc
from pySDC.projects.parallelSDC.nonlinear_playground import main, plot_graphs
def test_main():
main()
plot_graphs()
def test_newton_vs_... | [
"pySDC.projects.parallelSDC.newton_vs_sdc.main",
"pySDC.projects.parallelSDC.nonlinear_playground.main",
"pySDC.projects.parallelSDC.nonlinear_playground.plot_graphs",
"pySDC.projects.parallelSDC.newton_vs_sdc.plot_graphs"
] | [((275, 281), 'pySDC.projects.parallelSDC.nonlinear_playground.main', 'main', ([], {}), '()\n', (279, 281), False, 'from pySDC.projects.parallelSDC.nonlinear_playground import main, plot_graphs\n'), ((286, 299), 'pySDC.projects.parallelSDC.nonlinear_playground.plot_graphs', 'plot_graphs', ([], {}), '()\n', (297, 299), ... |
from __future__ import division
from __future__ import absolute_import
from builtins import object
from past.utils import old_div
from nose.tools import (assert_equal, assert_not_equal, raises,
assert_almost_equal)
from nose.plugins.skip import SkipTest
from .test_helpers import assert_items_alm... | [
"logging.getLogger",
"numpy.testing.assert_allclose",
"numpy.log",
"past.utils.old_div",
"numpy.array",
"nose.tools.raises",
"pandas.DataFrame",
"openpathsampling.numerics.WHAM"
] | [((7392, 7412), 'nose.tools.raises', 'raises', (['RuntimeError'], {}), '(RuntimeError)\n', (7398, 7412), False, 'from nose.tools import assert_equal, assert_not_equal, raises, assert_almost_equal\n'), ((7906, 7926), 'nose.tools.raises', 'raises', (['RuntimeError'], {}), '(RuntimeError)\n', (7912, 7926), False, 'from no... |
#!/usr/bin/env python
from policy_sentry.shared.database import connect_db
from policy_sentry.querying.actions import get_actions_with_access_level
import json
if __name__ == '__main__':
db_session = connect_db('bundled')
output = get_actions_with_access_level(db_session, 'all', 'Permissions management')
p... | [
"policy_sentry.shared.database.connect_db",
"json.dumps",
"policy_sentry.querying.actions.get_actions_with_access_level"
] | [((205, 226), 'policy_sentry.shared.database.connect_db', 'connect_db', (['"""bundled"""'], {}), "('bundled')\n", (215, 226), False, 'from policy_sentry.shared.database import connect_db\n'), ((240, 314), 'policy_sentry.querying.actions.get_actions_with_access_level', 'get_actions_with_access_level', (['db_session', '"... |
#/usr/bin/env python
from os.path import join, split
import numpy as np
import matplotlib.pyplot as plt
import pandas
from dtk import process
from gaitanalysis import gait, controlid
from gaitanalysis.utils import _percent_formatter
directory = split(__file__)[0]
perturbation_data = gait.WalkingData(join(directory,... | [
"numpy.ones_like",
"numpy.sqrt",
"numpy.hstack",
"gaitanalysis.controlid.SimpleControlSolver",
"os.path.join",
"os.path.split",
"numpy.argsort",
"matplotlib.pyplot.rcParams.update",
"matplotlib.pyplot.tight_layout",
"numpy.linalg.norm",
"matplotlib.pyplot.subplots",
"dtk.process.coefficient_of... | [((1197, 1270), 'gaitanalysis.controlid.SimpleControlSolver', 'controlid.SimpleControlSolver', (['perturbation_data.steps', 'sensors', 'controls'], {}), '(perturbation_data.steps, sensors, controls)\n', (1226, 1270), False, 'from gaitanalysis import gait, controlid\n'), ((2152, 2179), 'matplotlib.pyplot.rcParams.update... |
import bs4 as bs
import requests
import webbrowser
#values = input('Enter the question or error ') #Getting the query from the user to proceed further.
values = "python+import+error"
try:
url = 'https://stackoverflow.com/search?q='+values #The URL which will get encoded in UTF-8 format and sent.
resp = req... | [
"bs4.BeautifulSoup",
"webbrowser.open_new",
"requests.get"
] | [((419, 449), 'bs4.BeautifulSoup', 'bs.BeautifulSoup', (['resp', '"""lxml"""'], {}), "(resp, 'lxml')\n", (435, 449), True, 'import bs4 as bs\n'), ((1886, 1913), 'webbrowser.open_new', 'webbrowser.open_new', (['answer'], {}), '(answer)\n', (1905, 1913), False, 'import webbrowser\n'), ((317, 334), 'requests.get', 'reques... |
# -*- coding: utf-8 -*-
import unittest
import markdown
from regdown import (
DEFAULT_RENDER_BLOCK_REFERENCE,
extract_labeled_paragraph,
regdown,
)
class RegulationsExtensionTestCase(unittest.TestCase):
def test_label(self):
text = "{my-label} This is a paragraph with a label."
self.... | [
"regdown.regdown",
"regdown.extract_labeled_paragraph",
"markdown.Markdown"
] | [((11593, 11636), 'regdown.extract_labeled_paragraph', 'extract_labeled_paragraph', (['"""my-label"""', 'text'], {}), "('my-label', text)\n", (11618, 11636), False, 'from regdown import DEFAULT_RENDER_BLOCK_REFERENCE, extract_labeled_paragraph, regdown\n'), ((11874, 11917), 'regdown.extract_labeled_paragraph', 'extract... |
from __future__ import with_statement # this is to work with python2.5
from validation import vworkspace
with vworkspace() as w:
w.props.flatten_code_unroll = False
w.all_functions.validate_phases("coarse_grain_parallelization","flatten_code","coarse_grain_parallelization","loop_fusion")
| [
"validation.vworkspace"
] | [((113, 125), 'validation.vworkspace', 'vworkspace', ([], {}), '()\n', (123, 125), False, 'from validation import vworkspace\n')] |
#!/usr/bin/env python
from optparse import OptionParser
import signal
import sys
import logging
from meerkat_backend_interface.coordinator import Coordinator
from meerkat_backend_interface.logger import log, set_logger
def cli(prog = sys.argv[0]):
"""Command line interface.
"""
usage = "usage: %prog [op... | [
"meerkat_backend_interface.coordinator.Coordinator",
"meerkat_backend_interface.logger.log.info",
"optparse.OptionParser",
"meerkat_backend_interface.logger.set_logger",
"sys.exit"
] | [((341, 366), 'optparse.OptionParser', 'OptionParser', ([], {'usage': 'usage'}), '(usage=usage)\n', (353, 366), False, 'from optparse import OptionParser\n'), ((1147, 1185), 'meerkat_backend_interface.logger.log.info', 'log.info', (['"""Coordinator shutting down."""'], {}), "('Coordinator shutting down.')\n", (1155, 11... |
from setuptools import setup
setup(name='gym_PVDER',
version='0.0.1',
install_requires=['gym','scipy','numpy','matplotlib']#And any other dependencies required
)
| [
"setuptools.setup"
] | [((30, 132), 'setuptools.setup', 'setup', ([], {'name': '"""gym_PVDER"""', 'version': '"""0.0.1"""', 'install_requires': "['gym', 'scipy', 'numpy', 'matplotlib']"}), "(name='gym_PVDER', version='0.0.1', install_requires=['gym', 'scipy',\n 'numpy', 'matplotlib'])\n", (35, 132), False, 'from setuptools import setup\n'... |
from django.db import models
from django.contrib.auth.models import User
from PIL import Image
# Create your models here.
class KhaanDaanUsers(models.Model):
user = models.OneToOneField(User, on_delete=models.CASCADE)
name = models.CharField(max_length=50)
mobile_no = models.CharField(max_length=10,null=Fa... | [
"django.db.models.ImageField",
"django.db.models.OneToOneField",
"django.db.models.EmailField",
"django.db.models.CharField"
] | [((170, 222), 'django.db.models.OneToOneField', 'models.OneToOneField', (['User'], {'on_delete': 'models.CASCADE'}), '(User, on_delete=models.CASCADE)\n', (190, 222), False, 'from django.db import models\n'), ((234, 265), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(50)'}), '(max_length=50)\n... |
import pygame
from pygame.locals import *
from enum import Enum
X = 0
Y = 1
groundPos = 450 # global temporary variable (useless once collision is implemented) ; might use this for a global death barrier (below screen)
def cap(maxVal, eq): # caps a value to prevent an equation from breaking said cap ; global ... | [
"pygame.image.load",
"pygame.sprite.Sprite.__init__",
"pygame.Rect"
] | [((833, 881), 'pygame.image.load', 'pygame.image.load', (["(imgName + '/spritesheetR.png')"], {}), "(imgName + '/spritesheetR.png')\n", (850, 881), False, 'import pygame\n'), ((902, 950), 'pygame.image.load', 'pygame.image.load', (["(imgName + '/spritesheetL.png')"], {}), "(imgName + '/spritesheetL.png')\n", (919, 950)... |
import os
import uuid
import base64
import functools
from random import SystemRandom
from sortedcontainers import SortedList, SortedDict
import logging
logger = logging.getLogger(__name__)
#crypto imports
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives import hashes
# own ... | [
"logging.getLogger",
"functools.cmp_to_key",
"networking.Message",
"os.urandom",
"base64.b64encode",
"uuid.uuid4",
"cryptography.hazmat.backends.default_backend",
"functools.lru_cache",
"random.SystemRandom",
"cryptography.hazmat.primitives.hashes.SHA256"
] | [((161, 188), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (178, 188), False, 'import logging\n'), ((3090, 3123), 'functools.lru_cache', 'functools.lru_cache', ([], {'maxsize': '(4096)'}), '(maxsize=4096)\n', (3109, 3123), False, 'import functools\n'), ((3423, 3454), 'functools.lru_cach... |
import torch
from torchvision import datasets, transforms
from torch.autograd import Function
def load_data_fashion_mnist(batch_size, resize=None):
"""download Fashion-MNIST dataset, then load into memory"""
trans = [transforms.ToTensor()]
if resize:
trans.insert(0, transforms.Resize(resize))
t... | [
"torchvision.datasets.FashionMNIST",
"torchvision.datasets.CIFAR10",
"torchvision.transforms.Normalize",
"torch.utils.data.DataLoader",
"torchvision.transforms.Resize",
"torchvision.transforms.ToTensor",
"torchvision.transforms.Compose"
] | [((327, 352), 'torchvision.transforms.Compose', 'transforms.Compose', (['trans'], {}), '(trans)\n', (345, 352), False, 'from torchvision import datasets, transforms\n'), ((371, 457), 'torchvision.datasets.FashionMNIST', 'datasets.FashionMNIST', ([], {'root': '"""../Data"""', 'train': '(True)', 'transform': 'trans', 'do... |
from helpers import render
def aboutus(request):
return render(request, {}, 'news/aboutus.html')
def help(request):
return render(request, {}, 'news/help.html')
def buttons(request):
return render(request, {}, 'news/buttons.html')
| [
"helpers.render"
] | [((66, 106), 'helpers.render', 'render', (['request', '{}', '"""news/aboutus.html"""'], {}), "(request, {}, 'news/aboutus.html')\n", (72, 106), False, 'from helpers import render\n'), ((141, 178), 'helpers.render', 'render', (['request', '{}', '"""news/help.html"""'], {}), "(request, {}, 'news/help.html')\n", (147, 178... |
import builtins
from collections import abc
from copy import copy as _copy
from typing import (Generic,
Iterable,
Iterator,
Tuple,
overload)
from .core import red_black
from .core.abcs import LegacyInputIterator
from .core.tokenization imp... | [
"copy.copy",
"builtins.map"
] | [((5876, 5892), 'copy.copy', '_copy', (['first_arg'], {}), '(first_arg)\n', (5881, 5892), True, 'from copy import copy as _copy\n'), ((2944, 2968), 'builtins.map', 'builtins.map', (['repr', 'self'], {}), '(repr, self)\n', (2956, 2968), False, 'import builtins\n')] |
# -*- coding: utf-8 -*-
"""
Algorithms for TableDataExtractor.
.. codeauthor:: <NAME> <<EMAIL>>
"""
import logging
import numpy as np
from sympy import Symbol
from sympy import factor_list, factor
from tabledataextractor.exceptions import MIPSError
from tabledataextractor.table.parse import StringParser, CellParser... | [
"logging.getLogger",
"numpy.copy",
"numpy.insert",
"sympy.Symbol",
"tabledataextractor.table.parse.StringParser",
"numpy.full_like",
"numpy.unique",
"numpy.delete",
"numpy.sort",
"tabledataextractor.table.parse.CellParser",
"numpy.core.defchararray.replace",
"numpy.array_equal",
"numpy.vstac... | [((329, 356), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (346, 356), False, 'import logging\n'), ((744, 763), 'tabledataextractor.table.parse.StringParser', 'StringParser', (['regex'], {}), '(regex)\n', (756, 763), False, 'from tabledataextractor.table.parse import StringParser, CellP... |
from flask import Blueprint, render_template
connect4_bp = Blueprint('connect4', __name__, template_folder='templates', static_folder='static', url_prefix='/connect4')
@connect4_bp.route('')
def connect4():
return render_template('connect4.html')
| [
"flask.render_template",
"flask.Blueprint"
] | [((60, 173), 'flask.Blueprint', 'Blueprint', (['"""connect4"""', '__name__'], {'template_folder': '"""templates"""', 'static_folder': '"""static"""', 'url_prefix': '"""/connect4"""'}), "('connect4', __name__, template_folder='templates', static_folder=\n 'static', url_prefix='/connect4')\n", (69, 173), False, 'from ... |
# type: ignore
# -*- coding: utf-8 -*-
#
# ramstk.analyses.mil_hdbk_217f.models.capacitor.py is part of the RAMSTK Project
#
# All rights reserved.
# Copyright since 2007 Doyle "weibullguy" Rowland doyle.rowland <AT> reliaqual <DOT> com
"""Capacitor MIL-HDBK-217F Constants and Calculations Module."""
# Standard ... | [
"math.exp"
] | [((11865, 11925), 'math.exp', 'exp', (['(_f3 * ((temperature_active + 273.0) / _ref_temp) ** _f4)'], {}), '(_f3 * ((temperature_active + 273.0) / _ref_temp) ** _f4)\n', (11868, 11925), False, 'from math import exp\n')] |
#! /usr/bin/env python3
# -*- coding: utf-8 -*-
# vim:fenc=utf-8
#
# Copyright © 2021 <NAME> <<EMAIL>>
#
# Distributed under terms of the MIT license.
"""
"""
import os
import base64
import json
import dash_html_components as html
import dash_core_components as dcc
from dash.dependencies import Input,Output,State
fr... | [
"dash_html_components.Button",
"dash_html_components.H3",
"dash.dependencies.Input",
"os.exit",
"dash_core_components.Store",
"base64.decodebytes",
"dash_html_components.Div",
"os.path.exists",
"dash_core_components.Download",
"os.listdir",
"dash.dependencies.Output",
"json.dumps",
"dash.dep... | [((462, 473), 'os.getcwd', 'os.getcwd', ([], {}), '()\n', (471, 473), False, 'import os\n'), ((3699, 3741), 'os.path.join', 'os.path.join', (['full_data_folder', 'session_id'], {}), '(full_data_folder, session_id)\n', (3711, 3741), False, 'import os\n'), ((4006, 4037), 'dash.dependencies.Output', 'Output', (['"""file-d... |
import sys
import numpy as np
#import preprocess_blockSVD as pre_svd
import multiprocessing
import time
import matplotlib.pyplot as plt
#import greedyPCA_SV as gpca
#import greedyPCA as gpca
from math import ceil
from functools import partial
from itertools import product
# compute single mean_th factor for all tiles... | [
"numpy.prod",
"matplotlib.pyplot.ylabel",
"multiprocessing.Process",
"multiprocessing.cpu_count",
"numpy.array_split",
"numpy.array",
"numpy.arange",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"itertools.product",
"numpy.asarray",
"numpy.diff",
"numpy... | [((3485, 3510), 'numpy.append', 'np.append', (['d_row', 'dims[0]'], {}), '(d_row, dims[0])\n', (3494, 3510), True, 'import numpy as np\n'), ((3522, 3547), 'numpy.append', 'np.append', (['d_col', 'dims[1]'], {}), '(d_col, dims[1])\n', (3531, 3547), True, 'import numpy as np\n'), ((3782, 3813), 'numpy.zeros', 'np.zeros',... |
# Generated by Django 2.1.5 on 2019-06-22 14:20
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("hora_extra", "0003_auto_20190208_0020"),
]
operations = [
migrations.AddField(
model_name="horaextra",
name="horas",... | [
"django.db.models.DecimalField"
] | [((339, 401), 'django.db.models.DecimalField', 'models.DecimalField', ([], {'decimal_places': '(2)', 'default': '(1)', 'max_digits': '(5)'}), '(decimal_places=2, default=1, max_digits=5)\n', (358, 401), False, 'from django.db import migrations, models\n')] |
from math import ceil
from aspen.database.models import TreeType
from aspen.workflows.nextstrain_run.builder_base import BaseNextstrainConfigBuilder
def builder_factory(tree_type: TreeType, group, template_args, **kwargs):
# This is basically a router -- We'll switch between which build types
# based on a va... | [
"math.ceil"
] | [((4066, 4103), 'math.ceil', 'ceil', (['(self.num_included_samples / 4.0)'], {}), '(self.num_included_samples / 4.0)\n', (4070, 4103), False, 'from math import ceil\n')] |
import pandas
from emat.learn.feature_selection import SelectUniqueColumns
def test_select_unique_columns():
df = pandas.DataFrame({
'Aa': [1,2,3,4,5,6,7],
'Bb': [4,6,5,4,6,2,2],
'Cc': [1,2,3,4,5,6,7],
'Dd': [4,5,6,7,8,8,2],
'Ee': [10,20,30,40,50,60,70],
'Ff': [44,55,66,77,88,88,22],
})
s = SelectUn... | [
"pandas.DataFrame",
"emat.learn.feature_selection.SelectUniqueColumns"
] | [((120, 334), 'pandas.DataFrame', 'pandas.DataFrame', (["{'Aa': [1, 2, 3, 4, 5, 6, 7], 'Bb': [4, 6, 5, 4, 6, 2, 2], 'Cc': [1, 2, 3, \n 4, 5, 6, 7], 'Dd': [4, 5, 6, 7, 8, 8, 2], 'Ee': [10, 20, 30, 40, 50, 60,\n 70], 'Ff': [44, 55, 66, 77, 88, 88, 22]}"], {}), "({'Aa': [1, 2, 3, 4, 5, 6, 7], 'Bb': [4, 6, 5, 4, 6, 2... |
import sublime_plugin
import os
class CurrentPathStatusCommand(sublime_plugin.EventListener):
def updateStatus(self, view):
dirty = view.is_dirty() and '**' or '--'
eol = view.line_endings()[0]
encoding = view.encoding()
path = '%s%s%s' % (
' ' * 30,
... | [
"os.getenv"
] | [((360, 377), 'os.getenv', 'os.getenv', (['"""HOME"""'], {}), "('HOME')\n", (369, 377), False, 'import os\n')] |
import unittest
import codesmith.common.common as c
EVENT = {
'StackId': 'arn:aws:cloudformation:us-west-2:123456789012:stack/teststack/51af3dc0-da77-11e4-872e-1234567db123'
}
class TestCommon(unittest.TestCase):
def test_is_same_region(self):
# 1. Correctness
for r1, r2 in [
(Non... | [
"unittest.main",
"codesmith.common.common.is_same_region"
] | [((817, 832), 'unittest.main', 'unittest.main', ([], {}), '()\n', (830, 832), False, 'import unittest\n'), ((474, 505), 'codesmith.common.common.is_same_region', 'c.is_same_region', (['EVENT', 'r1', 'r2'], {}), '(EVENT, r1, r2)\n', (490, 505), True, 'import codesmith.common.common as c\n'), ((727, 758), 'codesmith.comm... |
import wx
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.backends.backend_wxagg import \
FigureCanvasWxAgg as FigureCanvas, \
NavigationToolbar2WxAgg as NavigationToolbar
class Overview(wx.Panel):
def __init__(self, ParentFrame, Data):
# Create Data Frame win... | [
"matplotlib.backends.backend_wxagg.FigureCanvasWxAgg",
"numpy.ptp",
"numpy.sqrt",
"matplotlib.pyplot.ylabel",
"numpy.array",
"wx.EVT_CHECKBOX",
"wx.Panel.__init__",
"numpy.arange",
"numpy.where",
"matplotlib.pyplot.xlabel",
"wx.CheckBox",
"numpy.vstack",
"numpy.round",
"wx.EVT_COMBOBOX",
... | [((35587, 35627), 'matplotlib.pyplot.figure', 'plt.figure', ([], {'facecolor': '(0.95, 0.95, 0.95)'}), '(facecolor=(0.95, 0.95, 0.95))\n', (35597, 35627), True, 'from matplotlib import pyplot as plt\n'), ((35647, 35689), 'matplotlib.backends.backend_wxagg.FigureCanvasWxAgg', 'FigureCanvas', (['self', 'wx.ID_ANY', 'self... |
import numpy as np
import pytest
from numpy.testing import assert_almost_equal, assert_raises, assert_warns
from ...tools import linear, power
from .. import Dcorr
class TestDcorrStat:
@pytest.mark.parametrize("n", [100, 200])
@pytest.mark.parametrize("obs_stat", [1.0])
@pytest.mark.parametrize("obs_pval... | [
"pytest.mark.parametrize",
"numpy.random.seed",
"numpy.testing.assert_almost_equal"
] | [((193, 233), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""n"""', '[100, 200]'], {}), "('n', [100, 200])\n", (216, 233), False, 'import pytest\n'), ((239, 281), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""obs_stat"""', '[1.0]'], {}), "('obs_stat', [1.0])\n", (262, 281), False, 'import pyt... |
# Copyright (c) 2013-2015 Centre for Advanced Internet Architectures,
# Swinburne University of Technology. All rights reserved.
#
# Author: <NAME> (<EMAIL>)
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# 1. Redist... | [
"bgproc.get_proc_list_items",
"fabric.api.puts",
"bgproc.clear_proc_list",
"fabric.api.run",
"fabric.api.settings",
"fabric.api.execute",
"hosttype.get_type_cached"
] | [((2417, 2449), 'hosttype.get_type_cached', 'get_type_cached', (['env.host_string'], {}), '(env.host_string)\n', (2432, 2449), False, 'from hosttype import get_type_cached\n'), ((3561, 3595), 'fabric.api.run', 'run', (["('kill -0 %s' % pid)"], {'pty': '(False)'}), "('kill -0 %s' % pid, pty=False)\n", (3564, 3595), Fals... |
'''
Module to define the dataset(s) used for training and validation
'''
__author__ = '<NAME>'
from simpleml.datasets import PandasDataset
import os
import numpy as np
import pandas as pd
import requests
import cv2
from tqdm import tqdm
current_directory = os.path.dirname(os.path.realpath(__file__))
NEGATIVE_IMAG... | [
"os.listdir",
"os.path.join",
"requests.get",
"os.path.realpath",
"os.path.isfile",
"cv2.cvtColor",
"pandas.concat"
] | [((279, 305), 'os.path.realpath', 'os.path.realpath', (['__file__'], {}), '(__file__)\n', (295, 305), False, 'import os\n'), ((350, 405), 'os.path.join', 'os.path.join', (['current_directory', '"""../../data/negative/"""'], {}), "(current_directory, '../../data/negative/')\n", (362, 405), False, 'import os\n'), ((450, ... |
from __future__ import print_function
from pymel.core import hide, showHidden, selected, select
from .. import core
from ..nodeApi import fossilNodes
class QuickHideControls(object):
'''
Toggle the visibility of the selected rig controls.
'''
controlsToHide = []
hideMain = False
mainSha... | [
"pymel.core.select",
"pymel.core.hide",
"pymel.core.showHidden",
"pymel.core.selected"
] | [((2535, 2545), 'pymel.core.selected', 'selected', ([], {}), '()\n', (2543, 2545), False, 'from pymel.core import hide, showHidden, selected, select\n'), ((2964, 2974), 'pymel.core.selected', 'selected', ([], {}), '()\n', (2972, 2974), False, 'from pymel.core import hide, showHidden, selected, select\n'), ((947, 957), ... |
import re
import unicodedata
def snakify_text(text: str) -> str:
"""This is to transform a text string so it can be used as a folder name.
The 4 normalisation forms:
https://en.wikipedia.org/wiki/Unicode_equivalence#Normalization
"""
result: str = text.lower().strip()
result = re.sub(r"[\\/&]... | [
"re.sub",
"unicodedata.normalize"
] | [((305, 335), 're.sub', 're.sub', (['"""[\\\\\\\\/&]"""', '""""""', 'result'], {}), "('[\\\\\\\\/&]', '', result)\n", (311, 335), False, 'import re\n'), ((348, 375), 're.sub', 're.sub', (['"""[,.]"""', '""" """', 'result'], {}), "('[,.]', ' ', result)\n", (354, 375), False, 'import re\n'), ((390, 416), 're.sub', 're.su... |
#!/usr/bin/python3
# File: test_state.py
# Authors: <NAME> - <NAME>
# email(s): <<EMAIL>>
# <<EMAIL>>
"""
This Module Defines Unittest for models/state.py.
Unittest classes:
TestAmenity_instantiation
TestAmenity_save
TestAmenity_to_dict
"""
import os
import models
import unittest
from datetime i... | [
"models.state.State",
"models.storage.all",
"os.rename",
"time.sleep",
"datetime.datetime.today",
"unittest.main",
"os.remove"
] | [((5656, 5671), 'unittest.main', 'unittest.main', ([], {}), '()\n', (5669, 5671), False, 'import unittest\n'), ((1085, 1092), 'models.state.State', 'State', ([], {}), '()\n', (1090, 1092), False, 'from models.state import State\n'), ((1283, 1290), 'models.state.State', 'State', ([], {}), '()\n', (1288, 1290), False, 'f... |
import urllib.request,json
from .models import Source,Article
# Article=article.Article
# Source = source.Source
api_key = '<KEY>'
# base_url = None
# article_url = None
# def configure_request(app):
# global api_key,base_url,article_url
# api_key = app.config['NEWS_API_KEY']
# base_url = app.config['SO... | [
"json.loads"
] | [((723, 750), 'json.loads', 'json.loads', (['get_source_data'], {}), '(get_source_data)\n', (733, 750), False, 'import urllib.request, json\n'), ((2058, 2086), 'json.loads', 'json.loads', (['get_article_data'], {}), '(get_article_data)\n', (2068, 2086), False, 'import urllib.request, json\n')] |