code stringlengths 22 1.05M | apis listlengths 1 3.31k | extract_api stringlengths 75 3.25M |
|---|---|---|
import torch
import torch.nn as nn
class QNetwork(nn.Module):
"""Actor (Policy) Model using a Single DQN."""
def __init__(self, state_size, action_size, seed):
"""Initialize parameters and build model.
Params
======
state_size (int): Dimension of each state
acti... | [
"torch.manual_seed",
"torch.nn.ReLU",
"torch.nn.Linear"
] | [((469, 492), 'torch.manual_seed', 'torch.manual_seed', (['seed'], {}), '(seed)\n', (486, 492), False, 'import torch\n'), ((1409, 1432), 'torch.manual_seed', 'torch.manual_seed', (['seed'], {}), '(seed)\n', (1426, 1432), False, 'import torch\n'), ((594, 620), 'torch.nn.Linear', 'nn.Linear', (['state_size', '(128)'], {}... |
# Copyright 2017 <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, soft... | [
"fcntl.ioctl",
"socket.socket",
"os.open",
"pox.lib.addresses.EthAddr",
"ctypes.c_char_p",
"struct.pack",
"queue.Queue",
"struct.unpack",
"pox.lib.addresses.IPAddr",
"pox.core.core.callLater",
"pox.core.core.add_listener",
"ctypes.cast",
"pox.lib.pxpcap.PCap",
"pox.lib.addresses.parse_cidr... | [((3415, 3432), 'pox.lib.addresses.IPAddr', 'IPAddr', (['"""0.0.0.0"""'], {}), "('0.0.0.0')\n", (3421, 3432), False, 'from pox.lib.addresses import EthAddr, IPAddr\n'), ((3448, 3465), 'pox.lib.addresses.IPAddr', 'IPAddr', (['"""0.0.0.0"""'], {}), "('0.0.0.0')\n", (3454, 3465), False, 'from pox.lib.addresses import EthA... |
# 2020 <NAME> and <NAME>
import os
import json
import numpy as np
from typing import Set, List
from geopy.distance import great_circle
from scipy.spatial.ckdtree import cKDTree
from shapely.geometry import Polygon, shape, Point
from icarus_simulator.sat_core.coordinate_util import geo2cart
from icarus_simulator.stra... | [
"scipy.spatial.ckdtree.cKDTree",
"os.path.join",
"icarus_simulator.sat_core.coordinate_util.geo2cart",
"os.path.split",
"shapely.geometry.Point",
"os.path.dirname",
"shapely.geometry.Polygon",
"geopy.distance.great_circle",
"json.load",
"shapely.geometry.shape"
] | [((481, 506), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (496, 506), False, 'import os\n'), ((624, 661), 'os.path.join', 'os.path.join', (['library_dirname', '"""data"""'], {}), "(library_dirname, 'data')\n", (636, 661), False, 'import os\n'), ((684, 748), 'os.path.join', 'os.path.join', ... |
# coding: utf-8
"""
Grafeas API
An API to insert and retrieve annotations on cloud artifacts. # noqa: E501
OpenAPI spec version: v1alpha1
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
import pprint
import re # noqa: F401
import six
from grafeas.models.deployment_deta... | [
"six.iteritems"
] | [((7594, 7627), 'six.iteritems', 'six.iteritems', (['self.swagger_types'], {}), '(self.swagger_types)\n', (7607, 7627), False, 'import six\n')] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Author: stdrickforce (<NAME>)
# Email: <<EMAIL>> <<EMAIL>>
import cat
import time
def ignore_exception(func):
def wraps(*args, **kwargs):
try:
return func(*args, **kwargs)
except Exception:
pass
return wraps
@ignore_ex... | [
"cat.Transaction",
"cat.log_event",
"cat.init",
"time.sleep",
"random.random",
"cat.transaction",
"time.time"
] | [((329, 359), 'cat.transaction', 'cat.transaction', (['"""Trans"""', '"""T1"""'], {}), "('Trans', 'T1')\n", (344, 359), False, 'import cat\n'), ((1377, 1421), 'cat.init', 'cat.init', (['"""pycat"""'], {'debug': '(True)', 'logview': '(False)'}), "('pycat', debug=True, logview=False)\n", (1385, 1421), False, 'import cat\... |
# -*- coding: utf-8 -*-
import csv
from matplotlib import pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
def isValid(p, ep):
return p in ep.patterns
# CLASS ANALYSER
class Analyser:
"""
Représentation d'un résultat d'analyse
"""
def __init__(self):
"""
:para... | [
"csv.DictWriter"
] | [((980, 1041), 'csv.DictWriter', 'csv.DictWriter', (['outfile'], {'delimiter': '""";"""', 'fieldnames': 'fieldnames'}), "(outfile, delimiter=';', fieldnames=fieldnames)\n", (994, 1041), False, 'import csv\n')] |
#!/usr/bin/env python3
import sys, os, glob
from glbase3 import *
all_species = glload('species_annotations/species.glb')
newl = []
for file in glob.glob('pep_counts/*.txt'):
oh = open(file, 'rt')
count = int(oh.readline().split()[0])
oh.close()
species_name = os.path.split(file)[1].split('.')[0].l... | [
"glob.glob",
"os.path.split"
] | [((148, 177), 'glob.glob', 'glob.glob', (['"""pep_counts/*.txt"""'], {}), "('pep_counts/*.txt')\n", (157, 177), False, 'import sys, os, glob\n'), ((369, 388), 'os.path.split', 'os.path.split', (['file'], {}), '(file)\n', (382, 388), False, 'import sys, os, glob\n'), ((282, 301), 'os.path.split', 'os.path.split', (['fil... |
import torch
import torch.nn as nn
import csv
#image quantization
def quantization(x):
x_quan=torch.round(x*255)/255
return x_quan
#picecwise-linear color filter
def CF(img, param,pieces):
param=param[:,:,None,None]
color_curve_sum = torch.sum(param, 4) + 1e-30
total_image = img * 0
f... | [
"csv.DictReader",
"torch.Tensor",
"torch.round",
"torch.sum",
"torch.clamp"
] | [((99, 119), 'torch.round', 'torch.round', (['(x * 255)'], {}), '(x * 255)\n', (110, 119), False, 'import torch\n'), ((261, 280), 'torch.sum', 'torch.sum', (['param', '(4)'], {}), '(param, 4)\n', (270, 280), False, 'import torch\n'), ((702, 740), 'csv.DictReader', 'csv.DictReader', (['csvfile'], {'delimiter': '""","""'... |
#!/usr/bin/env python
# The MIT License (MIT)
# Copyright (c) 2014 <NAME>
# Technische Universität München (TUM)
# Autonomous Navigation for Flying Robots
# Homework 2.1
from plot import plot
class UserCode:
def __init__(self):
# initialize data you want to store in this object between calls to the meas... | [
"plot.plot"
] | [((1081, 1124), 'plot.plot', 'plot', (['"""max_roll_angle"""', 'self.max_roll_angle'], {}), "('max_roll_angle', self.max_roll_angle)\n", (1085, 1124), False, 'from plot import plot\n'), ((1133, 1178), 'plot.plot', 'plot', (['"""max_pitch_angle"""', 'self.max_pitch_angle'], {}), "('max_pitch_angle', self.max_pitch_angle... |
from configs import args
import tensorflow as tf
def forward(x, mode):
is_training = (mode == tf.estimator.ModeKeys.TRAIN)
x = tf.contrib.layers.embed_sequence(x, args.vocab_size, args.embed_dim)
x = tf.layers.dropout(x, 0.2, training=is_training)
feat_map = []
for k_size in [3, 4, 5]:
_... | [
"tensorflow.train.AdamOptimizer",
"tensorflow.shape",
"tensorflow.estimator.EstimatorSpec",
"tensorflow.nn.sparse_softmax_cross_entropy_with_logits",
"tensorflow.concat",
"tensorflow.argmax",
"tensorflow.train.get_global_step",
"tensorflow.layers.dropout",
"tensorflow.train.exponential_decay",
"te... | [((139, 207), 'tensorflow.contrib.layers.embed_sequence', 'tf.contrib.layers.embed_sequence', (['x', 'args.vocab_size', 'args.embed_dim'], {}), '(x, args.vocab_size, args.embed_dim)\n', (171, 207), True, 'import tensorflow as tf\n'), ((216, 263), 'tensorflow.layers.dropout', 'tf.layers.dropout', (['x', '(0.2)'], {'trai... |
# -*- python -*-
"""@file
@brief pyserial transport for pato
Copyright (c) 2014-2015 <NAME> <<EMAIL>>.
All rights reserved.
@page License
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:
1. Redistributions of source code ... | [
"util.protocol.ProtocolException",
"serial.Serial"
] | [((2234, 2264), 'serial.Serial', 'serial.Serial', (['*args'], {}), '(*args, **kwargs)\n', (2247, 2264), False, 'import serial\n'), ((2932, 2975), 'util.protocol.ProtocolException', 'ProtocolException', (['"""Failed to send request"""'], {}), "('Failed to send request')\n", (2949, 2975), False, 'from util.protocol impor... |
# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by <NAME>
# Extended by <NAME>
# --------------------------------------------------------
import os
import cv2
import numpy as np
import torch
impor... | [
"os.path.exists",
"xml.etree.ElementTree.parse",
"cv2.flip",
"numpy.random.rand",
"numpy.where",
"os.path.join",
"numpy.array",
"cv2.imread"
] | [((3434, 3493), 'os.path.join', 'os.path.join', (['self.data_path', '"""Annotations"""', "(index + '.xml')"], {}), "(self.data_path, 'Annotations', index + '.xml')\n", (3446, 3493), False, 'import os\n'), ((3509, 3527), 'xml.etree.ElementTree.parse', 'ET.parse', (['filename'], {}), '(filename)\n', (3517, 3527), True, '... |
import discord
import random
import asyncio
import logging
import urllib.request
from discord.ext import commands
bot = commands.Bot(command_prefix='nep ', description= "Nep Nep")
counter = 0
countTask = None
@bot.event
async def on_ready():
print('Logged in as')
print(bot.user.name)
# print(bot.user.id)
... | [
"discord.ext.commands.Bot",
"asyncio.sleep"
] | [((121, 179), 'discord.ext.commands.Bot', 'commands.Bot', ([], {'command_prefix': '"""nep """', 'description': '"""Nep Nep"""'}), "(command_prefix='nep ', description='Nep Nep')\n", (133, 179), False, 'from discord.ext import commands\n'), ((747, 763), 'asyncio.sleep', 'asyncio.sleep', (['(3)'], {}), '(3)\n', (760, 763... |
import os
import time
import argparse
import pandas as pd
from smf import SessionMF
parser = argparse.ArgumentParser()
parser.add_argument('--K', type=int, default=20, help="K items to be used in Recall@K and MRR@K")
parser.add_argument('--factors', type=int, default=100, help="Number of latent factors.")
parser.add_a... | [
"argparse.ArgumentParser",
"pandas.read_csv",
"os.path.join",
"smf.SessionMF",
"time.time"
] | [((94, 119), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (117, 119), False, 'import argparse\n'), ((1975, 2022), 'os.path.join', 'os.path.join', (['args.data_folder', 'args.train_data'], {}), '(args.data_folder, args.train_data)\n', (1987, 2022), False, 'import os\n'), ((2033, 2056), 'pandas... |
# coding: utf-8
"""
App Center Client
Microsoft Visual Studio App Center API # noqa: E501
OpenAPI spec version: preview
Contact: <EMAIL>
Project Repository: https://github.com/b3nab/appcenter-sdks
"""
import pprint
import re # noqa: F401
import six
class Device(object):
"""NOTE: This cl... | [
"six.iteritems"
] | [((23895, 23928), 'six.iteritems', 'six.iteritems', (['self.swagger_types'], {}), '(self.swagger_types)\n', (23908, 23928), False, 'import six\n')] |
from django.conf.urls import url
from django.contrib.auth import views as auth_views
from django.contrib.auth.forms import AuthenticationForm
from oscar.core.application import (
DashboardApplication as BaseDashboardApplication)
from oscar.core.loading import get_class
class DashboardApplication(BaseDashboardApp... | [
"oscar.core.loading.get_class",
"django.contrib.auth.views.LoginView.as_view",
"django.conf.urls.url",
"django.contrib.auth.views.LogoutView.as_view"
] | [((465, 506), 'oscar.core.loading.get_class', 'get_class', (['"""dashboard.views"""', '"""IndexView"""'], {}), "('dashboard.views', 'IndexView')\n", (474, 506), False, 'from oscar.core.loading import get_class\n'), ((525, 574), 'oscar.core.loading.get_class', 'get_class', (['"""dashboard.reports.app"""', '"""applicatio... |
import pandas as pd
import pickle
def read_metric_logs(bucket_type):
metrics = pd.DataFrame(columns=['source_type', 'target_type', 'stats'])
type_list_path = f'/l/users/shikhar.srivastava/data/pannuke/{bucket_type}/selected_types.csv'
type_list = pd.read_csv(type_list_path)['0']
for source_type in t... | [
"pandas.DataFrame",
"pickle.load",
"pandas.read_csv"
] | [((85, 146), 'pandas.DataFrame', 'pd.DataFrame', ([], {'columns': "['source_type', 'target_type', 'stats']"}), "(columns=['source_type', 'target_type', 'stats'])\n", (97, 146), True, 'import pandas as pd\n'), ((262, 289), 'pandas.read_csv', 'pd.read_csv', (['type_list_path'], {}), '(type_list_path)\n', (273, 289), True... |
# Machine Learning Online Class - Exercise 2: Logistic Regression
#
# Instructions
# ------------
#
# This file contains code that helps you get started on the logistic
# regression exercise. You will need to complete the following functions
# in this exericse:
#
# sigmoid.py
# costFunction.py
# predic... | [
"numpy.mean",
"predict.predict",
"numpy.ones",
"matplotlib.pyplot.ylabel",
"scipy.optimize.fmin_bfgs",
"matplotlib.pyplot.xlabel",
"plotDecisionBoundary.plot_decision_boundary",
"numpy.array",
"numpy.zeros",
"costFunction.cost_function",
"matplotlib.pyplot.ion",
"matplotlib.pyplot.axis",
"nu... | [((696, 705), 'matplotlib.pyplot.ion', 'plt.ion', ([], {}), '()\n', (703, 705), True, 'import matplotlib.pyplot as plt\n'), ((814, 855), 'numpy.loadtxt', 'np.loadtxt', (['"""ex2data1.txt"""'], {'delimiter': '""","""'}), "('ex2data1.txt', delimiter=',')\n", (824, 855), True, 'import numpy as np\n'), ((1827, 1855), 'matp... |
#poly_gauss_coil model
#conversion of Poly_GaussCoil.py
#converted by <NAME>, Mar 2016
r"""
This empirical model describes the scattering from *polydisperse* polymer
chains in theta solvents or polymer melts, assuming a Schulz-Zimm type
molecular weight distribution.
To describe the scattering from *monodisperse* poly... | [
"numpy.expm1",
"numpy.polyval",
"numpy.power",
"numpy.random.uniform"
] | [((3486, 3510), 'numpy.polyval', 'np.polyval', (['p', 'z[~index]'], {}), '(p, z[~index])\n', (3496, 3510), True, 'import numpy as np\n'), ((3677, 3700), 'numpy.random.uniform', 'np.random.uniform', (['(0)', '(4)'], {}), '(0, 4)\n', (3694, 3700), True, 'import numpy as np\n'), ((3740, 3763), 'numpy.random.uniform', 'np.... |
import os
from itertools import product
from concurrent import futures
from contextlib import closing
from datetime import datetime
import numpy as np
from . import _z5py
from .file import File, S3File
from .dataset import Dataset
from .shape_utils import normalize_slices
def product1d(inrange):
for ii in inrang... | [
"urllib2.urlopen",
"zipfile.ZipFile",
"datetime.datetime.utcnow",
"concurrent.futures.ThreadPoolExecutor",
"itertools.product",
"os.path.join",
"imageio.volread",
"numpy.sum"
] | [((11994, 12022), 'imageio.volread', 'volread', (['"""imageio:stent.npz"""'], {}), "('imageio:stent.npz')\n", (12001, 12022), False, 'from imageio import volread\n'), ((2191, 2207), 'itertools.product', 'product', (['*ranges'], {}), '(*ranges)\n', (2198, 2207), False, 'from itertools import product\n'), ((7395, 7444), ... |
from concurrent.futures import ThreadPoolExecutor
from functools import partial
from json import JSONDecodeError
import requests
from funcy.calc import cache
from funcy.debug import print_calls
from funcy.simple_funcs import curry
HEADERS = {
"Accept": "application/json, text/javascript, */*; q=0.01",
"User-A... | [
"concurrent.futures.ThreadPoolExecutor",
"funcy.calc.cache",
"functools.partial",
"requests.get"
] | [((597, 606), 'funcy.calc.cache', 'cache', (['(60)'], {}), '(60)\n', (602, 606), False, 'from funcy.calc import cache\n'), ((644, 666), 'requests.get', 'requests.get', (['HOME_URL'], {}), '(HOME_URL)\n', (656, 666), False, 'import requests\n'), ((2433, 2473), 'concurrent.futures.ThreadPoolExecutor', 'ThreadPoolExecutor... |
"""
Data creation:
Load the data, normalize it, and split into train and test.
"""
'''
Added the capability of loading pre-separated UCI train/test data
function LoadData_Splitted_UCI
'''
import numpy as np
import os
import pandas as pd
import tensorflow as tf
DATA_PATH = "../UCI_Datasets"
class DataGenerator:... | [
"numpy.random.normal",
"tensorflow.random.normal",
"numpy.mean",
"tensorflow.reduce_sum",
"os.path.join",
"numpy.random.seed",
"numpy.std",
"tensorflow.convert_to_tensor",
"numpy.loadtxt",
"numpy.load",
"tensorflow.compat.v1.Session",
"numpy.random.permutation"
] | [((714, 752), 'tensorflow.random.normal', 'tf.random.normal', ([], {'shape': '(Ntrain, Npar)'}), '(shape=(Ntrain, Npar))\n', (730, 752), True, 'import tensorflow as tf\n'), ((1174, 1220), 'tensorflow.convert_to_tensor', 'tf.convert_to_tensor', (['x_test'], {'dtype': 'tf.float32'}), '(x_test, dtype=tf.float32)\n', (1194... |
# This script adds a new message to a specific SQS queue
#
# Author - <NAME> 2013
#
#
#from __future__ import print_function
import sys
import Queue
import boto.sqs
import argparse
import socket
import datetime
import sys
import time
from boto.sqs.attributes import Attributes
parser = argparse.ArgumentParser()
parser.... | [
"threading.Thread.__init__",
"Queue.Queue",
"argparse.ArgumentParser"
] | [((287, 312), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (310, 312), False, 'import argparse\n'), ((1231, 1245), 'Queue.Queue', 'Queue.Queue', (['(0)'], {}), '(0)\n', (1242, 1245), False, 'import Queue\n'), ((766, 797), 'threading.Thread.__init__', 'threading.Thread.__init__', (['self'], {}... |
from typing import Optional
import pandas as pd
from dero.ml.typing import ModelDict, AllModelResultsDict, DfDict
def model_dict_to_df(model_results: ModelDict, model_name: Optional[str] = None) -> pd.DataFrame:
df = pd.DataFrame(model_results).T
df.drop('score', inplace=True)
df['score'] = model_results[... | [
"pandas.DataFrame"
] | [((676, 690), 'pandas.DataFrame', 'pd.DataFrame', ([], {}), '()\n', (688, 690), True, 'import pandas as pd\n'), ((223, 250), 'pandas.DataFrame', 'pd.DataFrame', (['model_results'], {}), '(model_results)\n', (235, 250), True, 'import pandas as pd\n'), ((1255, 1269), 'pandas.DataFrame', 'pd.DataFrame', ([], {}), '()\n', ... |
import pygame
from engine.utils import Rect
from engine.app import get_screen_size
# EXPORT
class View(object):
def __init__(self, rect=None):
if rect:
self.rect = rect
else:
res = get_screen_size()
self.rect = Rect(0,0,res[0],res[1])
def offset(self, d):
... | [
"engine.utils.Rect",
"engine.app.get_screen_size"
] | [((647, 662), 'engine.utils.Rect', 'Rect', (['self.rect'], {}), '(self.rect)\n', (651, 662), False, 'from engine.utils import Rect\n'), ((226, 243), 'engine.app.get_screen_size', 'get_screen_size', ([], {}), '()\n', (241, 243), False, 'from engine.app import get_screen_size\n'), ((268, 294), 'engine.utils.Rect', 'Rect'... |
from __future__ import print_function
import emcee
from multiprocessing import Pool
import numpy as np
import corner
import matplotlib.pyplot as plt
import sys
import scipy.optimize as op
from rbvfit.rb_vfit import rb_veldiff as rb_veldiff
from rbvfit import rb_setline as rb
import pdb
def plot_model(wave_obs,fnorm,e... | [
"numpy.log",
"emcee.EnsembleSampler",
"numpy.array",
"numpy.isfinite",
"rbvfit.rb_vfit.rb_veldiff",
"corner.corner",
"numpy.diff",
"numpy.concatenate",
"numpy.round",
"numpy.tile",
"scipy.optimize.minimize",
"IPython.display.Math",
"numpy.shape",
"numpy.random.randn",
"matplotlib.pyplot.... | [((1731, 1832), 'matplotlib.pyplot.subplots', 'plt.subplots', (['ntransition'], {'sharex': '(True)', 'sharey': '(False)', 'figsize': '(12, 18)', 'gridspec_kw': "{'hspace': 0}"}), "(ntransition, sharex=True, sharey=False, figsize=(12, 18),\n gridspec_kw={'hspace': 0})\n", (1743, 1832), True, 'import matplotlib.pyplot... |
#!/usr/bin/env python3
# -*- coding:utf-8 -*-
# Copyright (c) Megvii, Inc. and its affiliates.
import torch
from torch.utils.data.dataloader import DataLoader as torchDataLoader
from torch.utils.data.dataloader import default_collate
import os
import random
from .samplers import YoloBatchSampler
def ... | [
"torch.utils.data.dataloader.default_collate",
"os.getenv",
"os.path.join",
"torch.utils.data.sampler.SequentialSampler",
"os.path.dirname",
"torch.utils.data.sampler.RandomSampler",
"random.randint"
] | [((551, 583), 'os.getenv', 'os.getenv', (['"""YOLOX_DATADIR"""', 'None'], {}), "('YOLOX_DATADIR', None)\n", (560, 583), False, 'import os\n'), ((735, 771), 'os.path.join', 'os.path.join', (['yolox_path', '"""datasets"""'], {}), "(yolox_path, 'datasets')\n", (747, 771), False, 'import os\n'), ((677, 708), 'os.path.dirna... |
#!/usr/bin/python
# Copyright: Ansible Project
# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
DOCUMENTATION = r'''
---
module: ec2_vpc_vpn_info
version_added: 1.0.0
short_description:... | [
"ansible_collections.amazon.aws.plugins.module_utils.ec2.camel_dict_to_snake_dict",
"ansible_collections.amazon.aws.plugins.module_utils.core.AnsibleAWSModule"
] | [((7229, 7361), 'ansible_collections.amazon.aws.plugins.module_utils.core.AnsibleAWSModule', 'AnsibleAWSModule', ([], {'argument_spec': 'argument_spec', 'mutually_exclusive': "[['vpn_connection_ids', 'filters']]", 'supports_check_mode': '(True)'}), "(argument_spec=argument_spec, mutually_exclusive=[[\n 'vpn_connecti... |
import discord
from discord.ext import commands
from pathlib import Path
from config import bot
from collections import OrderedDict
import json
class RoleSelector(commands.Cog):
def __init__(self, bot):
self.bot = bot
self.messages_path = str(Path('cogs/data/messages.json'))
async def opener(... | [
"discord.ext.commands.Cog.listener",
"collections.OrderedDict",
"pathlib.Path",
"discord.utils.get",
"json.load",
"discord.Embed",
"json.dump"
] | [((537, 560), 'discord.ext.commands.Cog.listener', 'commands.Cog.listener', ([], {}), '()\n', (558, 560), False, 'from discord.ext import commands\n'), ((1312, 1361), 'discord.ext.commands.Cog.listener', 'commands.Cog.listener', ([], {'name': '"""on_raw_reaction_add"""'}), "(name='on_raw_reaction_add')\n", (1333, 1361)... |
#!/usr/bin/env python3
from .base_test import BaseTest
from fbc.symphony.cli.graphql_compiler.gql.utils_codegen import CodeChunk
class TestRendererDataclasses(BaseTest):
def test_codegen_write_simple_strings(self):
gen = CodeChunk()
gen.write('def sum(a, b):')
gen.indent()
gen.wri... | [
"fbc.symphony.cli.graphql_compiler.gql.utils_codegen.CodeChunk"
] | [((236, 247), 'fbc.symphony.cli.graphql_compiler.gql.utils_codegen.CodeChunk', 'CodeChunk', ([], {}), '()\n', (245, 247), False, 'from fbc.symphony.cli.graphql_compiler.gql.utils_codegen import CodeChunk\n'), ((503, 514), 'fbc.symphony.cli.graphql_compiler.gql.utils_codegen.CodeChunk', 'CodeChunk', ([], {}), '()\n', (5... |
from flask import Flask
def create_app():
app = Flask(__name__)
app.config['JSON_AS_ASCII'] = False
from .views import app as main_app
app.register_blueprint(main_app)
return app
| [
"flask.Flask"
] | [((54, 69), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (59, 69), False, 'from flask import Flask\n')] |
from numpy import logspace
from sys import path as sysPath
sysPath.append('../../src')
#load the module
from interfacePy import Cosmo
cosmo=Cosmo('../../src/data/eos2020.dat',0,1e5)
for T in logspace(-5,5,50):
print(
'T=',T,'GeV\t',
'H=',cosmo.Hubble(T),'GeV\t',
'h_eff=',cosmo.heff(T),... | [
"matplotlib.pyplot.figure",
"numpy.logspace",
"sys.path.append",
"interfacePy.Cosmo"
] | [((61, 88), 'sys.path.append', 'sysPath.append', (['"""../../src"""'], {}), "('../../src')\n", (75, 88), True, 'from sys import path as sysPath\n'), ((145, 193), 'interfacePy.Cosmo', 'Cosmo', (['"""../../src/data/eos2020.dat"""', '(0)', '(100000.0)'], {}), "('../../src/data/eos2020.dat', 0, 100000.0)\n", (150, 193), Fa... |
#!/usr/bin/env python3
import argparse
import logging
import sys
import zlib
sys.path.append("../..")
from bento.client.api import ClientConnection
from bento.common.protocol import *
import bento.common.util as util
function_name= "browser"
function_code= """
import requests
import zlib
import os
def browser(url, ... | [
"logging.basicConfig",
"logging.debug",
"argparse.ArgumentParser",
"bento.common.util.fatal",
"bento.client.api.ClientConnection",
"sys.path.append",
"zlib.decompress"
] | [((79, 103), 'sys.path.append', 'sys.path.append', (['"""../.."""'], {}), "('../..')\n", (94, 103), False, 'import sys\n'), ((661, 739), 'logging.basicConfig', 'logging.basicConfig', ([], {'format': '"""%(levelname)s:\t%(message)s"""', 'level': 'logging.DEBUG'}), "(format='%(levelname)s:\\t%(message)s', level=logging.D... |
from app import webapp, mysql
from app.models import Search , Utils, Collection, WebUtils
from flask import request, jsonify
from flask.ext.jsonpify import jsonify as jsonp
import json
'''
Generic search call
@params
q: search query
page: the page number of search results (default 0)
t... | [
"flask.request.args.get",
"app.mysql.connect",
"app.models.Utils.getAdmins",
"app.models.Collection",
"app.models.Search.getSearchCategoriesForApp",
"app.models.Search",
"app.webapp.route",
"app.models.Utils.errorResponse",
"app.models.Utils.getParam",
"app.models.WebUtils.fetchSearchResults",
"... | [((447, 470), 'app.webapp.route', 'webapp.route', (['"""/search"""'], {}), "('/search')\n", (459, 470), False, 'from app import webapp, mysql\n'), ((2094, 2124), 'app.webapp.route', 'webapp.route', (['"""/getCategories"""'], {}), "('/getCategories')\n", (2106, 2124), False, 'from app import webapp, mysql\n'), ((2231, 2... |
from flask import Flask, make_response
app = Flask(__name__)
@app.route("/")
@app.route("/index.html")
def index():
html = open("assets/index.html").read()
return html
@app.route("/assets/<name>")
def wasm(name):
r = make_response(open(f"assets/{name}","rb").read())
if name.endswith(".wasm"):
... | [
"flask.Flask"
] | [((46, 61), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (51, 61), False, 'from flask import Flask, make_response\n')] |
from .audio_source import AudioSource
from engine import disk
import pyglet.media
class AudioDirector(object):
"""Director for loading audio and controlling playback.
Attributes:
attenuation_distance (int): The default attenuation distance for newly
loaded audio. Existing audio will retai... | [
"engine.disk.DiskLoader.load_audio"
] | [((2846, 2893), 'engine.disk.DiskLoader.load_audio', 'disk.DiskLoader.load_audio', (['filepath', 'streaming'], {}), '(filepath, streaming)\n', (2872, 2893), False, 'from engine import disk\n')] |
import os
import time
print("=====================================================================")
print(" ")
print(" STARTING SYSTEM REPAIR ")
print(" ... | [
"os.system",
"time.sleep"
] | [((866, 933), 'os.system', 'os.system', (['"""dism.exe /Online /Cleanup-Image /AnalyzeComponentStore"""'], {}), "('dism.exe /Online /Cleanup-Image /AnalyzeComponentStore')\n", (875, 933), False, 'import os\n'), ((938, 951), 'time.sleep', 'time.sleep', (['(3)'], {}), '(3)\n', (948, 951), False, 'import time\n'), ((1033,... |
"""
SNMP subagent entrypoint.
"""
import asyncio
import functools
import os
import signal
import sys
import ax_interface
from sonic_ax_impl.mibs import ieee802_1ab
from . import logger
from .mibs.ietf import rfc1213, rfc2737, rfc2863, rfc3433, rfc4292, rfc4363
from .mibs.vendor import dell, cisco
# Background task u... | [
"ax_interface.Agent",
"functools.partial",
"os.getpid",
"sys.exit",
"asyncio.get_event_loop"
] | [((394, 418), 'asyncio.get_event_loop', 'asyncio.get_event_loop', ([], {}), '()\n', (416, 418), False, 'import asyncio\n'), ((1679, 1769), 'ax_interface.Agent', 'ax_interface.Agent', (['SonicMIB', '(update_frequency or DEFAULT_UPDATE_FREQUENCY)', 'event_loop'], {}), '(SonicMIB, update_frequency or DEFAULT_UPDATE_FREQUE... |
#!/usr/bin/env python
# Author: <NAME>
# Date: 2015oct31
from __future__ import print_function
import os
import sys
import stat
import errno
import shutil
import optparse
import traceback
import subprocess
wrappaconda_name_string = 'Wr[App]-A-Conda'
class AppAtizer(object):
def __init__(self):
# tmp ... | [
"subprocess.check_output",
"os.path.exists",
"os.link",
"optparse.OptionParser",
"os.chmod",
"os.path.isfile",
"os.path.isdir",
"os.mkdir",
"shutil.copy",
"shutil.rmtree",
"os.path.expanduser"
] | [((359, 392), 'os.path.expanduser', 'os.path.expanduser', (['"""~/Downloads"""'], {}), "('~/Downloads')\n", (377, 392), False, 'import os\n'), ((1494, 1517), 'optparse.OptionParser', 'optparse.OptionParser', ([], {}), '()\n', (1515, 1517), False, 'import optparse\n'), ((4366, 4395), 'os.path.exists', 'os.path.exists', ... |
import requests
class Wallet(object):
def __init__(self, testnet=False):
if testnet:
self.base_url = 'https://testnet.watchtower.cash/api/'
else:
self.base_url = 'https://watchtower.cash/api/'
def _get_utxos(self, wallet_hash, amount):
url = self.base_url + f'... | [
"requests.get"
] | [((362, 379), 'requests.get', 'requests.get', (['url'], {}), '(url)\n', (374, 379), False, 'import requests\n')] |
from PyQt5.QtWidgets import QTreeWidget
from PyQt5.Qt import pyqtSignal
from PyQt5.QtWidgets import QTreeWidgetItem
from PyQt5.Qt import Qt
class TreeWidget(QTreeWidget):
# enum ItemShowMode
ItemsCollapsed = 0
ItemsExpanded = 1
def __init__(self, parent=None):
super().__init__(parent)
s... | [
"PyQt5.Qt.pyqtSignal"
] | [((3741, 3768), 'PyQt5.Qt.pyqtSignal', 'pyqtSignal', (['QTreeWidgetItem'], {}), '(QTreeWidgetItem)\n', (3751, 3768), False, 'from PyQt5.Qt import pyqtSignal\n'), ((3807, 3834), 'PyQt5.Qt.pyqtSignal', 'pyqtSignal', (['QTreeWidgetItem'], {}), '(QTreeWidgetItem)\n', (3817, 3834), False, 'from PyQt5.Qt import pyqtSignal\n'... |
""":run
"""
import curses
import datetime
import json
import logging
import os
import re
import shlex
import shutil
import time
import uuid
from math import floor
from queue import Queue
from typing import Any
from typing import Callable
from typing import Dict
from typing import List
from typing import Optional
from ... | [
"logging.getLogger",
"os.path.exists",
"math.floor",
"shlex.split",
"shutil.which",
"re.match",
"time.sleep",
"os.getcwd",
"uuid.uuid4",
"os.path.dirname",
"datetime.datetime.now",
"os.path.basename",
"json.load",
"queue.Queue"
] | [((5542, 5549), 'queue.Queue', 'Queue', ([], {}), '()\n', (5547, 5549), False, 'from queue import Queue\n'), ((7222, 7277), 'logging.getLogger', 'logging.getLogger', (['f"""{__name__}_{self._subaction_type}"""'], {}), "(f'{__name__}_{self._subaction_type}')\n", (7239, 7277), False, 'import logging\n'), ((7725, 7741), '... |
# Copyright 2014 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompa... | [
"textwrap.dedent",
"ebcli.core.fileoperations.get_workspace_type",
"json.loads",
"ebcli.operations.commonops.get_current_branch_environment",
"ebcli.core.fileoperations.get_application_name",
"ebcli.objects.exceptions.NotInitializedError",
"os.path.abspath",
"ebcli.core.io.log_alert",
"ebcli.objects... | [((2820, 2848), 'cement.core.controller.expose', 'controller.expose', ([], {'hide': '(True)'}), '(hide=True)\n', (2837, 2848), False, 'from cement.core import controller\n'), ((1901, 1940), 'ebcli.core.fileoperations.get_workspace_type', 'fileoperations.get_workspace_type', (['None'], {}), '(None)\n', (1934, 1940), Fal... |
import unittest
import speak
class SpeakTests(unittest.TestCase):
"""
Unit test for the speak library
"""
def testHello(self):
self.assertEqual("Hello World!", speak.helloworld())
def testGoodbye(self):
self.assertEqual("Goodbye World!", speak.goodbyeworld())
if __name__ == "__mai... | [
"unittest.main",
"speak.goodbyeworld",
"speak.helloworld"
] | [((330, 345), 'unittest.main', 'unittest.main', ([], {}), '()\n', (343, 345), False, 'import unittest\n'), ((186, 204), 'speak.helloworld', 'speak.helloworld', ([], {}), '()\n', (202, 204), False, 'import speak\n'), ((276, 296), 'speak.goodbyeworld', 'speak.goodbyeworld', ([], {}), '()\n', (294, 296), False, 'import sp... |
#!/usr/bin/env python3
# METADATA OF THIS TAL_SERVICE:
problem="eggs"
service="confirm_min_throws"
args_list = [
('min',int),
('n_eggs',int),
('n_floors',int),
('lang',str),
('ISATTY',bool),
]
from sys import stderr, exit, argv
from random import randrange
from math import inf as IMPOSSIBLE
from ... | [
"multilanguage.Env",
"sys.exit",
"multilanguage.TALcolors"
] | [((367, 399), 'multilanguage.Env', 'Env', (['problem', 'service', 'args_list'], {}), '(problem, service, args_list)\n', (370, 399), False, 'from multilanguage import Env, Lang, TALcolors\n'), ((405, 419), 'multilanguage.TALcolors', 'TALcolors', (['ENV'], {}), '(ENV)\n', (414, 419), False, 'from multilanguage import Env... |
from django.contrib import admin
from .models import Doctor, ConsultationTime, Medicine, Allergy, Child, Parent
admin.site.site_header = "Allisto - We Do Good"
@admin.register(Doctor)
class DoctorAdmin(admin.ModelAdmin):
list_display = ('name', 'aadhar_number', 'specialization', 'email', 'phone_number')
lis... | [
"django.contrib.admin.register",
"django.contrib.admin.site.register"
] | [((165, 187), 'django.contrib.admin.register', 'admin.register', (['Doctor'], {}), '(Doctor)\n', (179, 187), False, 'from django.contrib import admin\n'), ((457, 479), 'django.contrib.admin.register', 'admin.register', (['Parent'], {}), '(Parent)\n', (471, 479), False, 'from django.contrib import admin\n'), ((735, 756)... |
from backend.entity.entity import DefinedFuntion
from backend.ir.dumper import Dumper
from backend.ir.stmt import Assign
from backend.ir.stmt import Return
from backend.ir.expr import Bin
from backend.ir.expr import Call
from backend.entity.scope import *
def import_ir(data, asm_file):
def_vars = list()
def_... | [
"backend.ir.expr.Bin",
"backend.ir.expr.Call",
"backend.ir.stmt.Return",
"backend.ir.stmt.Assign",
"backend.ir.dumper.Dumper"
] | [((963, 1034), 'backend.ir.stmt.Assign', 'Assign', ([], {'loc': "insn['line_number']", 'lhs': "insn['address']", 'rhs': "insn['value']"}), "(loc=insn['line_number'], lhs=insn['address'], rhs=insn['value'])\n", (969, 1034), False, 'from backend.ir.stmt import Assign\n'), ((3923, 3931), 'backend.ir.dumper.Dumper', 'Dumpe... |
import numpy as np
from pyquil.gate_matrices import X, Y, Z, H
from forest.benchmarking.operator_tools.superoperator_transformations import *
# Test philosophy:
# Using the by hand calculations found in the docs we check conversion
# between one qubit channels with one Kraus operator (Hadamard) and two
# Kraus operat... | [
"numpy.abs",
"numpy.eye",
"numpy.allclose",
"numpy.sqrt",
"numpy.random.rand",
"numpy.asarray",
"numpy.diag",
"numpy.kron",
"numpy.array",
"numpy.zeros",
"numpy.matmul"
] | [((3245, 3310), 'numpy.diag', 'np.diag', (['[1, -1, 1, -1, -1, 1, -1, 1, 1, -1, 1, -1, -1, 1, -1, 1]'], {}), '([1, -1, 1, -1, -1, 1, -1, 1, 1, -1, 1, -1, -1, 1, -1, 1])\n', (3252, 3310), True, 'import numpy as np\n'), ((3365, 3393), 'numpy.asarray', 'np.asarray', (['[[0, 0], [0, 1]]'], {}), '([[0, 0], [0, 1]])\n', (337... |
import numpy as np
import imageio
from PoissonTemperature import FiniteDifferenceMatrixConstruction
def ind_sub_conversion(img, ind2sub_fn, sub2ind_fn):
rows, cols = img.shape[:2]
num = rows*cols
arange = np.arange(rows*cols, dtype=np.int32)
ind2sub = np.empty((num, 2), dtype=np.int32)
ind2sub[:, ... | [
"numpy.arange",
"imageio.imwrite",
"numpy.floor",
"PoissonTemperature.FiniteDifferenceMatrixConstruction",
"numpy.remainder",
"numpy.empty",
"imageio.imread",
"numpy.save"
] | [((219, 257), 'numpy.arange', 'np.arange', (['(rows * cols)'], {'dtype': 'np.int32'}), '(rows * cols, dtype=np.int32)\n', (228, 257), True, 'import numpy as np\n'), ((270, 304), 'numpy.empty', 'np.empty', (['(num, 2)'], {'dtype': 'np.int32'}), '((num, 2), dtype=np.int32)\n', (278, 304), True, 'import numpy as np\n'), (... |
from distutils.version import LooseVersion
import requests
import os
import shutil
import threading
import webbrowser
from zipfile import ZipFile
from pathlib import Path
import traceback
import tempfile
# import concurrent.futures
from flask import Flask, url_for, make_response
from flask.json import dumps
from flask_... | [
"zipfile.ZipFile",
"flask.Flask",
"webbrowser.open",
"mindsdb.utilities.log.get_log",
"mindsdb.utilities.ps.wait_func_is_true",
"os.remove",
"pathlib.Path",
"flask.json.dumps",
"os.getpid",
"distutils.version.LooseVersion",
"mindsdb.utilities.config.Config",
"os.path.isabs",
"requests.get",
... | [((1458, 1473), 'mindsdb.utilities.log.get_log', 'get_log', (['"""http"""'], {}), "('http')\n", (1465, 1473), False, 'from mindsdb.utilities.log import get_log\n'), ((2168, 2197), 'distutils.version.LooseVersion', 'LooseVersion', (['mindsdb_version'], {}), '(mindsdb_version)\n', (2180, 2197), False, 'from distutils.ver... |
# Copyright Contributors to the Pyro-Cov project.
# SPDX-License-Identifier: Apache-2.0
import functools
import io
import logging
import math
import re
import sys
import torch
import torch.multiprocessing as mp
from Bio import AlignIO
from Bio.Phylo.NewickIO import Parser
from Bio.Seq import Seq
from Bio.SeqRecord im... | [
"logging.getLogger",
"re.search",
"Bio.AlignIO.read",
"Bio.Phylo.NewickIO.Parser.from_string",
"torch.full",
"Bio.Seq.Seq",
"torch.isfinite",
"torch.multiprocessing.Pool",
"functools.partial",
"re.sub",
"sys.stdout.flush",
"sys.stdout.write"
] | [((375, 402), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (392, 402), False, 'import logging\n'), ((531, 552), 'sys.stdout.write', 'sys.stdout.write', (['"""."""'], {}), "('.')\n", (547, 552), False, 'import sys\n'), ((557, 575), 'sys.stdout.flush', 'sys.stdout.flush', ([], {}), '()\n'... |
import numpy as np
import pandas as pd
from sklearn.linear_model import LinearRegression
def convert_to_sqft(str):
tokens = str.split(' - ')
if len(tokens) == 2:
return (float(tokens[0]) + float(tokens[1])) / 2
try:
return float(tokens[0])
except Exception:
return np.NAN
def co... | [
"pandas.get_dummies",
"numpy.where",
"sklearn.linear_model.LinearRegression",
"pandas.read_csv"
] | [((441, 459), 'sklearn.linear_model.LinearRegression', 'LinearRegression', ([], {}), '()\n', (457, 459), False, 'from sklearn.linear_model import LinearRegression\n'), ((549, 590), 'pandas.read_csv', 'pd.read_csv', (['"""./Bengaluru_House_Data.csv"""'], {}), "('./Bengaluru_House_Data.csv')\n", (560, 590), True, 'import... |
import warnings
from typing import Dict, Tuple
from lhotse import CutSet
from lhotse.dataset.sampling.base import CutSampler
def find_pessimistic_batches(
sampler: CutSampler, batch_tuple_index: int = 0
) -> Tuple[Dict[str, CutSet], Dict[str, float]]:
"""
Function for finding 'pessimistic' batches, i.e. ... | [
"warnings.warn"
] | [((2753, 2825), 'warnings.warn', 'warnings.warn', (['"""Empty sampler encountered in find_pessimistic_batches()"""'], {}), "('Empty sampler encountered in find_pessimistic_batches()')\n", (2766, 2825), False, 'import warnings\n')] |
# -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2017-06-03 08:41
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('book', '0009_book_folder'),
]
operations = [
migrations.AddField(
... | [
"django.db.models.DateTimeField",
"django.db.models.CharField"
] | [((389, 424), 'django.db.models.DateTimeField', 'models.DateTimeField', ([], {'auto_now': '(True)'}), '(auto_now=True)\n', (409, 424), False, 'from django.db import migrations, models\n'), ((542, 587), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(400)', 'unique': '(True)'}), '(max_length=400,... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
This module contains the necessary functions to load a text-corpus from
NLTK, contract all possible sentences, applying POS-tags to the
contracted sentences and compare that with the original text.
The information about which contraction+pos-tag pair gets expanded to
... | [
"nltk.corpus.reuters.sents",
"nltk.corpus.inaugural.sents",
"yaml.dump",
"nltk.corpus.brown.sents",
"yaml.load",
"nltk.corpus.gutenberg.sents",
"utils.load_stanford",
"utils.sent_to_ner",
"pprint.pprint"
] | [((11038, 11063), 'nltk.corpus.brown.sents', 'nltk.corpus.brown.sents', ([], {}), '()\n', (11061, 11063), False, 'import nltk\n'), ((11080, 11109), 'nltk.corpus.gutenberg.sents', 'nltk.corpus.gutenberg.sents', ([], {}), '()\n', (11107, 11109), False, 'import nltk\n'), ((11126, 11153), 'nltk.corpus.reuters.sents', 'nltk... |
# pylint: disable = C0111
from setuptools import find_packages, setup
setup(name="paperai",
# version="1.5.0",
# author="NeuML",
# description="AI-powered literature discovery and review engine for medical/scientific papers",
# long_description=DESCRIPTION,
# long_description_content_typ... | [
"setuptools.find_packages"
] | [((914, 982), 'setuptools.find_packages', 'find_packages', ([], {'where': '"""C:\\\\Users\\\\sxm\\\\Desktop\\\\paperai\\\\src\\\\python"""'}), "(where='C:\\\\Users\\\\sxm\\\\Desktop\\\\paperai\\\\src\\\\python')\n", (927, 982), False, 'from setuptools import find_packages, setup\n')] |
from io import BytesIO
from typing import List, Dict
from PIL import Image
from hit_analysis.commons.config import Config
from hit_analysis.commons.consts import IMAGE, CROP_X, CROP_Y, CROP_SIZE, FRAME_DECODED, CLASSIFIED, CLASS_ARTIFACT, ORIG_IMAGE
def append_to_frame(image: Image, detection: dict):
hit_img = ... | [
"io.BytesIO"
] | [((1155, 1164), 'io.BytesIO', 'BytesIO', ([], {}), '()\n', (1162, 1164), False, 'from io import BytesIO\n')] |
import numpy as np
import numpy.testing as npt
import slippy
import slippy.core as core
"""
If you add a material you need to add the properties that it will be tested with to the material_parameters dict,
the key should be the name of the class (what ever it is declared as after the class key word).
The value should ... | [
"slippy.asnumpy",
"slippy.core.Elastic",
"numpy.random.rand",
"numpy.random.seed"
] | [((2428, 2484), 'slippy.core.Elastic', 'core.Elastic', (['"""steel_6"""', "{'E': 200000000000.0, 'v': 0.3}"], {}), "('steel_6', {'E': 200000000000.0, 'v': 0.3})\n", (2440, 2484), True, 'import slippy.core as core\n'), ((2480, 2497), 'numpy.random.seed', 'np.random.seed', (['(0)'], {}), '(0)\n', (2494, 2497), True, 'imp... |
#!/usr/bin/env python
"""Restore files with ending BACKUP_ENDING to original files."""
# The copyright in this software is being made available under the BSD License,
# included below. This software may be subject to other third party and contributor
# rights, including patent rights, and no such rights are granted un... | [
"os.path.exists",
"os.rename",
"optparse.OptionParser",
"os.unlink",
"sys.exit"
] | [((2044, 2058), 'optparse.OptionParser', 'OptionParser', ([], {}), '()\n', (2056, 2058), False, 'from optparse import OptionParser\n'), ((2220, 2231), 'sys.exit', 'sys.exit', (['(1)'], {}), '(1)\n', (2228, 2231), False, 'import sys\n'), ((2436, 2460), 'os.path.exists', 'os.path.exists', (['old_name'], {}), '(old_name)\... |
# Copyright 2020-2021 OpenDR European Project
#
# 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... | [
"pyglet.gl.glGetDoublev",
"numpy.asarray",
"numpy.argsort",
"numpy.sum",
"numpy.zeros",
"pyglet.gl.glGetIntegerv",
"numpy.linalg.norm",
"numpy.transpose",
"pyglet.gl.GLdouble",
"pyglet.gl.gluUnProject"
] | [((1131, 1191), 'pyglet.gl.glGetDoublev', 'pyglet.gl.glGetDoublev', (['pyglet.gl.GL_MODELVIEW_MATRIX', 'mvmat'], {}), '(pyglet.gl.GL_MODELVIEW_MATRIX, mvmat)\n', (1153, 1191), False, 'import pyglet\n'), ((1200, 1260), 'pyglet.gl.glGetDoublev', 'pyglet.gl.glGetDoublev', (['pyglet.gl.GL_PROJECTION_MATRIX', 'pmat'], {}), ... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Dec 28 09:33:53 2020
@author: dhulls
"""
from __future__ import print_function
from __future__ import absolute_import
from argparse import ArgumentParser
import numpy as nm
import sys
sys.path.append('.')
from sfepy.base.base import IndexedStruct, St... | [
"sfepy.discrete.Equations",
"sfepy.discrete.conditions.EssentialBC",
"sfepy.solvers.ls.ScipyDirect",
"sfepy.discrete.Equation",
"argparse.ArgumentParser",
"sfepy.solvers.nls.Newton",
"sfepy.discrete.conditions.Conditions",
"sfepy.discrete.fem.Mesh.from_file",
"sfepy.discrete.Integral",
"sfepy.disc... | [((253, 273), 'sys.path.append', 'sys.path.append', (['"""."""'], {}), "('.')\n", (268, 273), False, 'import sys\n'), ((912, 928), 'argparse.ArgumentParser', 'ArgumentParser', ([], {}), '()\n', (926, 928), False, 'from argparse import ArgumentParser\n'), ((1183, 1237), 'sfepy.discrete.fem.Mesh.from_file', 'Mesh.from_fi... |
#!/usr/bin/env python3
from scripts.workflow import get_app_name, is_name_valid
from scripts.workflow import get_args, is_args_valid
from scripts.workflow import create_dir, create_app, create_templates_folder, create_static_folder, create_dockerfile
from scripts.manual import print_manual
from scripts.messages import... | [
"scripts.messages.success_msg",
"scripts.workflow.get_args",
"scripts.workflow.create_app",
"scripts.manual.print_manual",
"scripts.workflow.is_args_valid",
"scripts.workflow.create_dir",
"scripts.workflow.create_templates_folder",
"scripts.workflow.get_app_name",
"scripts.workflow.create_dockerfile... | [((381, 395), 'scripts.workflow.get_app_name', 'get_app_name', ([], {}), '()\n', (393, 395), False, 'from scripts.workflow import get_app_name, is_name_valid\n'), ((403, 413), 'scripts.workflow.get_args', 'get_args', ([], {}), '()\n', (411, 413), False, 'from scripts.workflow import get_args, is_args_valid\n'), ((466, ... |
import os
from pathlib import Path
from jinja2 import Template
import parser
from utils import write_to_file
from utils import mkdir_p
parser.init()
# parse and assign to vars
spec = parser.spec
def _concat(slice: str) -> str:
"""helper to concatenate each template slice."""
return "{}\n".format(slice)
... | [
"pathlib.Path.cwd",
"os.path.join",
"jinja2.Template",
"os.path.realpath",
"utils.write_to_file",
"parser.init"
] | [((138, 151), 'parser.init', 'parser.init', ([], {}), '()\n', (149, 151), False, 'import parser\n'), ((1371, 1391), 'jinja2.Template', 'Template', (['dockerfile'], {}), '(dockerfile)\n', (1379, 1391), False, 'from jinja2 import Template\n'), ((2335, 2371), 'utils.write_to_file', 'write_to_file', (['file_name', 'dockerf... |
import os
from datetime import datetime
import pytest
from entropylab import ExperimentResources, SqlAlchemyDB, PyNode, Graph
@pytest.mark.skipif(
datetime.utcnow() > datetime(2022, 6, 25),
reason="Please remove after two months have passed since the fix was merged",
)
def test_issue_204(initialized_project... | [
"datetime.datetime",
"os.path.exists",
"entropylab.Graph",
"datetime.datetime.utcnow",
"os.path.join",
"entropylab.SqlAlchemyDB",
"entropylab.PyNode",
"os.remove"
] | [((957, 1001), 'entropylab.PyNode', 'PyNode', ([], {'label': '"""root_node"""', 'program': 'root_node'}), "(label='root_node', program=root_node)\n", (963, 1001), False, 'from entropylab import ExperimentResources, SqlAlchemyDB, PyNode, Graph\n'), ((1019, 1086), 'entropylab.Graph', 'Graph', ([], {'resources': 'experime... |
"""users.country
Revision ID: 429d596c43a7
Revises: <PASSWORD>
Create Date: 2020-10-23 21:26:55.598146
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = '429d596c43a7'
down_revision = '77e0c0edaa04'
branch_labels = None
depends_on = None
def upgrade():
# ##... | [
"sqlalchemy.String",
"alembic.op.drop_column"
] | [((587, 621), 'alembic.op.drop_column', 'op.drop_column', (['"""users"""', '"""country"""'], {}), "('users', 'country')\n", (601, 621), False, 'from alembic import op\n'), ((426, 445), 'sqlalchemy.String', 'sa.String', ([], {'length': '(4)'}), '(length=4)\n', (435, 445), True, 'import sqlalchemy as sa\n')] |
import pandas as pd
def get_seasonality_weekly(bills, date_column='dates', group_column='level_4_name',
regular_only=False, promo_fact_column=None):
bills['week'] = pd.to_datetime(bills[date_column]).dt.week
bills['year'] = pd.to_datetime(bills[date_column]).dt.year
# - Группиру... | [
"pandas.to_datetime"
] | [((198, 232), 'pandas.to_datetime', 'pd.to_datetime', (['bills[date_column]'], {}), '(bills[date_column])\n', (212, 232), True, 'import pandas as pd\n'), ((261, 295), 'pandas.to_datetime', 'pd.to_datetime', (['bills[date_column]'], {}), '(bills[date_column])\n', (275, 295), True, 'import pandas as pd\n')] |
# Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import collections
import copy
import traceback
from telemetry import value as value_module
from telemetry.results import page_run
from telemetry.results im... | [
"telemetry.results.page_run.PageRun",
"copy.copy",
"traceback.format_exception",
"telemetry.results.progress_reporter.ProgressReporter"
] | [((3594, 3616), 'telemetry.results.page_run.PageRun', 'page_run.PageRun', (['page'], {}), '(page)\n', (3610, 3616), False, 'from telemetry.results import page_run\n'), ((1399, 1442), 'telemetry.results.progress_reporter.ProgressReporter', 'progress_reporter_module.ProgressReporter', ([], {}), '()\n', (1440, 1442), True... |
from tensorflow.keras.models import Model
import tensorflow as tf
from tensorflow import keras
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np
import cv2
import numpy as np
import pandas as pd
from tensorflow.keras.models import load_model
import tensorflow as tf
import os
#--------------... | [
"numpy.uint8",
"os.path.join",
"tensorflow.keras.preprocessing.image.array_to_img",
"tensorflow.GradientTape",
"tensorflow.squeeze",
"tensorflow.math.reduce_max",
"tensorflow.maximum",
"tensorflow.reduce_mean",
"tensorflow.keras.preprocessing.image.img_to_array",
"tensorflow.cast",
"matplotlib.c... | [((3903, 3940), 'tensorflow.reduce_mean', 'tf.reduce_mean', (['grads'], {'axis': '(0, 1, 2)'}), '(grads, axis=(0, 1, 2))\n', (3917, 3940), True, 'import tensorflow as tf\n'), ((4296, 4315), 'tensorflow.squeeze', 'tf.squeeze', (['heatmap'], {}), '(heatmap)\n', (4306, 4315), True, 'import tensorflow as tf\n'), ((4888, 49... |
import subprocess
import sys
import os
import setup_util
from os.path import expanduser
def start(args, logfile, errfile):
fwroot = args.fwroot
setup_util.replace_text("cakephp/app/Config/database.php", "'host' => '.*',", "'host' => '" + args.database_host + "',")
setup_util.replace_text("cakephp/app/Config/cor... | [
"setup_util.replace_text",
"subprocess.call",
"subprocess.check_call"
] | [((150, 274), 'setup_util.replace_text', 'setup_util.replace_text', (['"""cakephp/app/Config/database.php"""', '"""\'host\' => \'.*\',"""', '("\'host\' => \'" + args.database_host + "\',")'], {}), '(\'cakephp/app/Config/database.php\',\n "\'host\' => \'.*\',", "\'host\' => \'" + args.database_host + "\',")\n', (173,... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Common utility functions
Created on Sun May 27 16:37:42 2018
@author: chen
"""
import math
import cv2
import os
from imutils import paths
import numpy as np
import scipy.ndimage
def rotate_cooridinate(cooridinate_og,rotate_angle,rotate_center):
"""
calculat... | [
"numpy.sqrt",
"math.cos",
"numpy.array",
"imutils.paths.list_images",
"math.exp",
"os.path.exists",
"numpy.max",
"numpy.exp",
"numpy.concatenate",
"numpy.min",
"numpy.maximum",
"numpy.round",
"numpy.random.choice",
"numpy.int",
"cv2.imread",
"numpy.minimum",
"os.makedirs",
"numpy.p... | [((774, 806), 'numpy.array', 'np.array', (['[rotated_x, rotated_y]'], {}), '([rotated_x, rotated_y])\n', (782, 806), True, 'import numpy as np\n'), ((988, 1008), 'os.path.exists', 'os.path.exists', (['path'], {}), '(path)\n', (1002, 1008), False, 'import os\n'), ((2068, 2209), 'numpy.array', 'np.array', (['[box[0][::-1... |
import logging
import time
import re
import serial
from threading import Thread, Event
from respeaker import Microphone
from respeaker import BingSpeechAPI
from respeaker import PixelRing,pixel_ring
BING_KEY = '95e4fe8b3a324389be4595bd1813121c'
ser = serial.Serial('/dev/ttyS1',115200,timeout=0)
data=[0xAA,0x01,0x64,... | [
"logging.basicConfig",
"respeaker.pixel_ring.off",
"respeaker.pixel_ring.wait",
"respeaker.BingSpeechAPI",
"time.sleep",
"respeaker.Microphone",
"threading.Event",
"respeaker.pixel_ring.listen",
"serial.Serial",
"threading.Thread",
"re.search"
] | [((254, 300), 'serial.Serial', 'serial.Serial', (['"""/dev/ttyS1"""', '(115200)'], {'timeout': '(0)'}), "('/dev/ttyS1', 115200, timeout=0)\n", (267, 300), False, 'import serial\n'), ((2031, 2064), 'respeaker.Microphone', 'Microphone', ([], {'quit_event': 'quit_event'}), '(quit_event=quit_event)\n', (2041, 2064), False,... |
#!/usr/bin/env python
# encoding: utf-8
'''
@author: caroline
@license: (C) Copyright 2019-2022, Node Supply Chain Manager Corporation Limited.
@contact: <EMAIL>
@software: pycharm
@file: account_voteCredit.py
@time: 2020/1/8 11:23 上午
@desc:
'''
from apis.API import request_Api
def voteCredit(api_name, params):
'''... | [
"apis.API.request_Api"
] | [((693, 722), 'apis.API.request_Api', 'request_Api', (['api_name', 'params'], {}), '(api_name, params)\n', (704, 722), False, 'from apis.API import request_Api\n')] |
####################
# ES-DOC CIM Questionnaire
# Copyright (c) 2017 ES-DOC. All rights reserved.
#
# University of Colorado, Boulder
# http://cires.colorado.edu/
#
# This project is distributed according to the terms of the MIT license [http://www.opensource.org/licenses/MIT].
####################
from djan... | [
"django.db.models.TextField",
"django.db.models.ForeignKey",
"os.path.join",
"os.path.dirname",
"django.db.models.DateTimeField",
"Q.questionnaire.q_fields.QVersionField",
"django.db.models.UUIDField"
] | [((725, 772), 'os.path.join', 'os.path.join', (['APP_LABEL', 'PUBLICATION_UPLOAD_DIR'], {}), '(APP_LABEL, PUBLICATION_UPLOAD_DIR)\n', (737, 772), False, 'import os\n'), ((1323, 1352), 'django.db.models.UUIDField', 'models.UUIDField', ([], {'blank': '(False)'}), '(blank=False)\n', (1339, 1352), False, 'from django.db im... |
# -*- coding: utf-8 -*-
import os
import shutil
from django.conf import settings
from django.core.management import call_command
from django.test import TestCase
from six import StringIO
try:
from unittest.mock import patch
except ImportError:
from mock import patch
class CreateCommandTests(TestCase):
"... | [
"os.path.getsize",
"mock.patch",
"django.core.management.call_command",
"os.path.join",
"os.path.isfile",
"os.mkdir",
"shutil.rmtree",
"os.remove"
] | [((1716, 1758), 'mock.patch', 'patch', (['"""sys.stdout"""'], {'new_callable': 'StringIO'}), "('sys.stdout', new_callable=StringIO)\n", (1721, 1758), False, 'from mock import patch\n'), ((2144, 2186), 'mock.patch', 'patch', (['"""sys.stdout"""'], {'new_callable': 'StringIO'}), "('sys.stdout', new_callable=StringIO)\n",... |
import ADT_of_person as AP
import datetime as dm
#ADT Staff()
# Staff(self, str name, str sex, tuple birthday, tuple entey_date, int salary, str position)
# name(self)
# sex(self)
# en_year(self)
# salary(self)
# set_salary(self, new_salary)
# position(self)
# set_position(self, new_position... | [
"datetime.date",
"ADT_of_person.PersonValueError"
] | [((503, 521), 'datetime.date', 'dm.date', (['*birthday'], {}), '(*birthday)\n', (510, 521), True, 'import datetime as dm\n'), ((806, 827), 'ADT_of_person.PersonValueError', 'AP.PersonValueError', ([], {}), '()\n', (825, 827), True, 'import ADT_of_person as AP\n'), ((863, 881), 'datetime.date', 'dm.date', (['*birthday']... |
"""
Test signal handlers for completion.
"""
from datetime import datetime
from unittest.mock import patch
import ddt
import pytest
from completion import handlers
from completion.models import BlockCompletion
from completion.test_utils import CompletionSetUpMixin
from django.test import TestCase
from pytz import utc... | [
"datetime.datetime.utcnow",
"completion.models.BlockCompletion.objects.get",
"xblock.core.XBlock.register_temp_plugin",
"pytest.raises",
"completion.models.BlockCompletion.objects.filter",
"ddt.data",
"unittest.mock.patch"
] | [((2066, 2114), 'ddt.data', 'ddt.data', (['(True, 0.0)', '(False, 1.0)', '(None, 1.0)'], {}), '((True, 0.0), (False, 1.0), (None, 1.0))\n', (2074, 2114), False, 'import ddt\n'), ((2562, 2629), 'xblock.core.XBlock.register_temp_plugin', 'XBlock.register_temp_plugin', (['CustomScorableBlock', '"""custom_scorable"""'], {}... |
from typing import Tuple
import pygame
import numpy as np
from .wall import Wall
class MovingWall(Wall):
def __init__(self,
top: int = 0,
left: int = 0,
bottom: int = 1,
right: int = 1):
super().__init__(top, left, bottom, right)
... | [
"pygame.Surface",
"pygame.mask.from_surface",
"pygame.Rect"
] | [((633, 672), 'pygame.mask.from_surface', 'pygame.mask.from_surface', (['self.surf', '(50)'], {}), '(self.surf, 50)\n', (657, 672), False, 'import pygame\n'), ((810, 847), 'pygame.Rect', 'pygame.Rect', (['left', 'top', 'width', 'height'], {}), '(left, top, width, height)\n', (821, 847), False, 'import pygame\n'), ((480... |
import tensorflow as tf
import os
from bayes_filter import logging
from bayes_filter.filters import FreeTransitionVariationalBayes
from bayes_filter.feeds import DatapackFeed, IndexFeed
from bayes_filter.misc import make_example_datapack, maybe_create_posterior_solsets, get_screen_directions
from bayes_filter.datapack ... | [
"tensorflow.Graph",
"bayes_filter.misc.get_screen_directions",
"tensorflow.device",
"bayes_filter.filters.FreeTransitionVariationalBayes",
"os.makedirs",
"os.path.abspath",
"bayes_filter.logging.info",
"bayes_filter.datapack._load_array_file",
"bayes_filter.misc.maybe_create_posterior_solsets",
"b... | [((490, 531), 'os.makedirs', 'os.makedirs', (['output_folder'], {'exist_ok': '(True)'}), '(output_folder, exist_ok=True)\n', (501, 531), False, 'import os\n'), ((945, 1052), 'bayes_filter.datapack.DataPack', 'DataPack', (['"""/net/lofar1/data1/albert/imaging/data/P126+65_compact_raw/P126+65_full_compact_raw.h5"""'], {}... |
from typing import Dict, Any, Optional, List
import gym
import numpy as np
from collections import defaultdict
from flatland.core.grid.grid4_utils import get_new_position
from flatland.envs.agent_utils import EnvAgent, RailAgentStatus
from flatland.envs.rail_env import RailEnv, RailEnvActions
from envs.flatland.obse... | [
"gym.spaces.Discrete",
"envs.flatland.observations.segment_graph.Graph.get_virtual_position",
"gym.spaces.Box",
"numpy.count_nonzero",
"numpy.argmax",
"collections.defaultdict",
"envs.flatland.utils.gym_env.StepOutput",
"flatland.utils.rendertools.RenderTool",
"flatland.core.grid.grid4_utils.get_new... | [((5246, 5263), 'collections.defaultdict', 'defaultdict', (['list'], {}), '(list)\n', (5257, 5263), False, 'from collections import defaultdict\n'), ((6896, 6918), 'envs.flatland.utils.gym_env.StepOutput', 'StepOutput', (['o', 'r', 'd', 'i'], {}), '(o, r, d, i)\n', (6906, 6918), False, 'from envs.flatland.utils.gym_env... |
import torch
from torch import nn
class CBOWClassifier(nn.Module):
"""
Continuous bag of words classifier.
"""
def __init__(self, hidden_size, input_size, max_pool, dropout=0.5):
"""
:param hidden_size:
:param input_size:
:param max_pool: if true then max pool over word ... | [
"torch.nn.Sigmoid",
"torch.nn.Dropout",
"torch.nn.Tanh",
"torch.nn.Linear"
] | [((573, 594), 'torch.nn.Dropout', 'nn.Dropout', ([], {'p': 'dropout'}), '(p=dropout)\n', (583, 594), False, 'from torch import nn\n'), ((614, 658), 'torch.nn.Linear', 'nn.Linear', (['self.input_size', 'self.hidden_size'], {}), '(self.input_size, self.hidden_size)\n', (623, 658), False, 'from torch import nn\n'), ((678,... |
import numpy as np
import cv2 as cv
img = cv.imread('1.jpeg',cv.IMREAD_COLOR)
#for polygon we need to have set of points so we create a numpy array. and pts is an object.
pts = np.array([[20,33],[300,120], [67,79], [123,111], [144,134]], np.int32)
#the method polylines will actully draws a polygon by taking differe... | [
"cv2.polylines",
"cv2.imshow",
"numpy.array",
"cv2.destroyAllWindows",
"cv2.waitKey",
"cv2.imread"
] | [((43, 79), 'cv2.imread', 'cv.imread', (['"""1.jpeg"""', 'cv.IMREAD_COLOR'], {}), "('1.jpeg', cv.IMREAD_COLOR)\n", (52, 79), True, 'import cv2 as cv\n'), ((180, 256), 'numpy.array', 'np.array', (['[[20, 33], [300, 120], [67, 79], [123, 111], [144, 134]]', 'np.int32'], {}), '([[20, 33], [300, 120], [67, 79], [123, 111],... |
#!/usr/bin/env python2
from BeautifulSoup import BeautifulSoup, NavigableString
import urllib
import string
import re
class Entry(object):
def __init__(self, name, value, description, url):
self.name = name
self.value = value
self.description = description
self.url = url
def ... | [
"BeautifulSoup.NavigableString",
"re.sub"
] | [((3236, 3277), 're.sub', 're.sub', (['"""<\\\\s*b\\\\s*>"""', '"""<i>"""', 'description'], {}), "('<\\\\s*b\\\\s*>', '<i>', description)\n", (3242, 3277), False, 'import re\n'), ((3314, 3361), 're.sub', 're.sub', (['"""<\\\\s*/\\\\s*b\\\\s*>"""', '"""</i>"""', 'description'], {}), "('<\\\\s*/\\\\s*b\\\\s*>', '</i>', d... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# ------------------------------------------------------------------------------
#
# Copyright 2018-2019 Fetch.AI Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You ma... | [
"logging.getLogger",
"os.open",
"os.remove",
"os.path.exists",
"asyncio.StreamReader",
"asyncio.StreamReaderProtocol",
"asyncio.sleep",
"asyncio.get_event_loop",
"os.close",
"os.write",
"struct.pack",
"aea.exceptions.enforce",
"asyncio.open_connection",
"tempfile.mkdtemp",
"struct.unpack... | [((1210, 1237), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (1227, 1237), False, 'import logging\n'), ((4405, 4468), 'os.open', 'os.open', (['self._in_path', '(os.O_RDONLY | os.O_NONBLOCK | os.O_SYNC)'], {}), '(self._in_path, os.O_RDONLY | os.O_NONBLOCK | os.O_SYNC)\n', (4412, 4468), F... |
import scipy, numpy, typing, numbers
from tequila.objective import Objective
from tequila.objective.objective import assign_variable, Variable, format_variable_dictionary, format_variable_list
from .optimizer_base import Optimizer
from ._containers import _EvalContainer, _GradContainer, _HessContainer, _QngContainer
fr... | [
"collections.namedtuple",
"tequila.objective.objective.format_variable_dictionary",
"tequila.tools.qng.get_qng_combos",
"scipy.optimize.minimize",
"numpy.array",
"tequila.utils.exceptions.TequilaException",
"tequila.objective.objective.assign_variable"
] | [((587, 654), 'collections.namedtuple', 'namedtuple', (['"""SciPyReturnType"""', '"""energy angles history scipy_output"""'], {}), "('SciPyReturnType', 'energy angles history scipy_output')\n", (597, 654), False, 'from collections import namedtuple\n'), ((16511, 16552), 'tequila.objective.objective.format_variable_dict... |
#
# This file is part of the chi repository
# (https://github.com/DavAug/chi/) which is released under the
# BSD 3-clause license. See accompanying LICENSE.md for copyright notice and
# full license details.
#
import copy
import myokit
import myokit.formats.sbml as sbml
import numpy as np
class MechanisticModel(obj... | [
"numpy.alltrue",
"myokit.formats.sbml.SBMLImporter",
"myokit.pacing.blocktrain",
"myokit.Simulation",
"numpy.argsort",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.empty",
"copy.deepcopy",
"copy.copy",
"myokit.Name"
] | [((984, 1014), 'myokit.Simulation', 'myokit.Simulation', (['self._model'], {}), '(self._model)\n', (1001, 1014), False, 'import myokit\n'), ((1824, 1844), 'numpy.array', 'np.array', (['parameters'], {}), '(parameters)\n', (1832, 1844), True, 'import numpy as np\n'), ((2721, 2738), 'numpy.argsort', 'np.argsort', (['name... |
## Copyright (c) 2022, Team FirmWire
## SPDX-License-Identifier: BSD-3-Clause
from enum import Enum, auto
from .hw.soc import SOCPeripheral
class MemoryMapEntryType(Enum):
GENERIC = auto()
FILE_BACKED = auto()
PERIPHERAL = auto()
ANNOTATION = auto()
class MemoryMapEntry:
def __init__(self, ty, s... | [
"enum.auto"
] | [((188, 194), 'enum.auto', 'auto', ([], {}), '()\n', (192, 194), False, 'from enum import Enum, auto\n'), ((213, 219), 'enum.auto', 'auto', ([], {}), '()\n', (217, 219), False, 'from enum import Enum, auto\n'), ((237, 243), 'enum.auto', 'auto', ([], {}), '()\n', (241, 243), False, 'from enum import Enum, auto\n'), ((26... |
from vue.bridge import Object
import javascript
class VueDecorator:
__key__ = None
__parents__ = ()
__id__ = None
__value__ = None
def update(self, vue_dict):
base = vue_dict
for parent in self.__parents__:
base = vue_dict.setdefault(parent, {})
if self.__id__... | [
"vue.bridge.Object.from_js",
"javascript.this"
] | [((882, 899), 'vue.bridge.Object.from_js', 'Object.from_js', (['v'], {}), '(v)\n', (896, 899), False, 'from vue.bridge import Object\n'), ((744, 761), 'javascript.this', 'javascript.this', ([], {}), '()\n', (759, 761), False, 'import javascript\n'), ((824, 843), 'vue.bridge.Object.from_js', 'Object.from_js', (['arg'], ... |
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import keras
from keras.models import Model, load_model
from keras import backend as K
from keras.preprocessing.image import ImageDataGenerator
import tensorflow as tf
tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR) # mute deprecation warnings
from kera... | [
"keras.optimizers.Adam",
"os.path.exists",
"keras.models.load_model",
"keras.callbacks.ModelCheckpoint",
"tensorflow.Session",
"tensorflow.compat.v1.logging.set_verbosity",
"keras.preprocessing.image.ImageDataGenerator",
"os.path.isdir",
"keras.backend.clear_session",
"os.mkdir",
"tensorflow.Con... | [((220, 282), 'tensorflow.compat.v1.logging.set_verbosity', 'tf.compat.v1.logging.set_verbosity', (['tf.compat.v1.logging.ERROR'], {}), '(tf.compat.v1.logging.ERROR)\n', (254, 282), True, 'import tensorflow as tf\n'), ((797, 814), 'keras.backend.clear_session', 'K.clear_session', ([], {}), '()\n', (812, 814), True, 'fr... |
from setuptools import setup, find_packages
__name__ = "appJar"
__version__ = "0.94.0"
__author__ = "<NAME>"
__desc__ = "An easy-to-use, feature-rich GUI wrapper for tKinter. Designed specifically for use in the classroom, but powerful enough to be used anywhere."
__author_email__ = "<E... | [
"setuptools.setup"
] | [((1268, 1794), 'setuptools.setup', 'setup', ([], {'name': '__name__', 'packages': '__packages__', 'version': '__version__', 'description': '__desc__', 'long_description': '__long_description__', 'long_description_content_type': '"""text/markdown"""', 'author': '__author__', 'author_email': '__author_email__', 'url': '... |
import shapefile
class Andir:
def __init__(self):
self.kelurahan = shapefile.Writer(
'kelurahan_andir', shapeType=shapefile.POLYGON)
self.kelurahan.shapeType
self.kelurahan.field('kelurahan_di_andir', 'C')
self.kantor = shapefile.Writer(
'kantor_kelurahan_a... | [
"shapefile.Writer"
] | [((81, 145), 'shapefile.Writer', 'shapefile.Writer', (['"""kelurahan_andir"""'], {'shapeType': 'shapefile.POLYGON'}), "('kelurahan_andir', shapeType=shapefile.POLYGON)\n", (97, 145), False, 'import shapefile\n'), ((271, 340), 'shapefile.Writer', 'shapefile.Writer', (['"""kantor_kelurahan_andir"""'], {'shapeType': 'shap... |
# Copyright 2016-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import torch, glob, os
from .sparseConvNetTensor import SparseConvNetTensor
from .metadata import Metadata
import sparsecon... | [
"torch.index_select",
"sparseconvnet.SCN.ResolutionBasedScattering",
"torch.LongTensor",
"torch.load",
"torch.floor",
"torch.Tensor",
"torch.max",
"os.path.isfile",
"torch.ceil",
"torch.no_grad",
"torch.svd",
"torch.sum",
"glob.glob",
"threading.Thread",
"Queue.Queue",
"torch.cat",
"... | [((1504, 1545), 'torch.cat', 'torch.cat', (['[i.features for i in input]', '(1)'], {}), '([i.features for i in input], 1)\n', (1513, 1545), False, 'import torch, glob, os\n'), ((6751, 6763), 'torch.svd', 'torch.svd', (['w'], {}), '(w)\n', (6760, 6763), False, 'import torch, glob, os\n'), ((7126, 7141), 'torch.cat', 'to... |
import json
from django.core.exceptions import ObjectDoesNotExist
from django.db import transaction
from treebeard.mp_tree import MP_Node
try:
from wagtail.core.blocks import StreamValue
except ImportError: # pragma: no cover; fallback for Wagtail < 2.0
from wagtail.wagtailcore.blocks import StreamValue
... | [
"json.dumps",
"json.loads",
"treebeard.mp_tree.MP_Node._get_path",
"wagtail.wagtailcore.blocks.StreamValue"
] | [((538, 632), 'treebeard.mp_tree.MP_Node._get_path', 'MP_Node._get_path', (['parent_page.path', '(parent_page.depth + 1)', '(parent_page.numchild + offset)'], {}), '(parent_page.path, parent_page.depth + 1, parent_page.\n numchild + offset)\n', (555, 632), False, 'from treebeard.mp_tree import MP_Node\n'), ((2104, 2... |
from collections import OrderedDict
from unittest import TestCase
from frozenordereddict import FrozenOrderedDict
class TestFrozenOrderedDict(TestCase):
ITEMS_1 = (
("b", 2),
("a", 1),
)
ITEMS_2 = (
("d", 4),
("c", 3),
)
ODICT_1 = OrderedDict(ITEMS_1)
ODICT_2 ... | [
"collections.OrderedDict",
"frozenordereddict.FrozenOrderedDict"
] | [((287, 307), 'collections.OrderedDict', 'OrderedDict', (['ITEMS_1'], {}), '(ITEMS_1)\n', (298, 307), False, 'from collections import OrderedDict\n'), ((322, 342), 'collections.OrderedDict', 'OrderedDict', (['ITEMS_2'], {}), '(ITEMS_2)\n', (333, 342), False, 'from collections import OrderedDict\n'), ((394, 425), 'froze... |
import random
import unittest
from serial.serialutil import SerialException
from data_gateway.dummy_serial import DummySerial, constants, exceptions, random_bytes, random_string
from tests.base import BaseTestCase
class DummySerialTest(BaseTestCase):
def setUp(self):
"""Set up the test environment:
... | [
"data_gateway.dummy_serial.random_bytes",
"data_gateway.dummy_serial.random_string",
"data_gateway.dummy_serial.DummySerial",
"unittest.main",
"random.randint"
] | [((7544, 7559), 'unittest.main', 'unittest.main', ([], {}), '()\n', (7557, 7559), False, 'import unittest\n'), ((446, 461), 'data_gateway.dummy_serial.random_string', 'random_string', ([], {}), '()\n', (459, 461), False, 'from data_gateway.dummy_serial import DummySerial, constants, exceptions, random_bytes, random_str... |
# -*- coding: utf-8 -*-
"""
Created on %(date)s
@author: %Christian
"""
"""
#BASE +BN层
#dropout改为0.15
"""
import paddle
import paddle.nn as nn
import paddle.nn.functional as F
import paddlenlp as ppnlp
class QuestionMatching_base(nn.Layer):
'''
base模型
dropout改为0.15
'''
de... | [
"paddle.nn.BatchNorm1D",
"paddle.nn.Dropout",
"paddle.nn.Linear",
"paddle.nn.ReLU"
] | [((475, 527), 'paddle.nn.Dropout', 'nn.Dropout', (['(dropout if dropout is not None else 0.15)'], {}), '(dropout if dropout is not None else 0.15)\n', (485, 527), True, 'import paddle.nn as nn\n'), ((582, 626), 'paddle.nn.Linear', 'nn.Linear', (["self.ptm.config['hidden_size']", '(2)'], {}), "(self.ptm.config['hidden_s... |
from functools import partialmethod
import pandas as pd
from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine
import sqlite3
import click
import json
import pkg_resources
from itertools import combinations
from q2_mlab.db.schema import RegressionScore
from q2_mlab.plotting.components import (
... | [
"bokeh.transform.factor_cmap",
"q2_mlab.plotting.components.DataSourceComponent",
"bokeh.layouts.column",
"bokeh.layouts.row",
"bokeh.plotting.figure",
"bokeh.models.LegendItem",
"bokeh.models.widgets.Div",
"q2_mlab.plotting.components.ScatterComponent",
"pandas.read_sql_table",
"click.group",
"... | [((20971, 20999), 'click.group', 'click.group', (['"""mlab-plotting"""'], {}), "('mlab-plotting')\n", (20982, 20999), False, 'import click\n'), ((1122, 1189), 'pkg_resources.resource_stream', 'pkg_resources.resource_stream', (['__name__', '"""standard_deviations.json"""'], {}), "(__name__, 'standard_deviations.json')\n... |
from AIPS import AIPS
from AIPSTask import AIPSTask
from AIPSData import AIPSImage
from ObitTask import ObitTask
AIPS.userno = 103
image = AIPSImage('MANDELBROT', 'MANDL', 1, 1)
mandl = AIPSTask('mandl')
mandl.outdata = image
mandl.imsize[1:] = [ 512, 512 ]
mandl.go()
try:
template = ObitTask('Template')
te... | [
"AIPSTask.AIPSTask",
"ObitTask.ObitTask",
"AIPSData.AIPSImage"
] | [((141, 179), 'AIPSData.AIPSImage', 'AIPSImage', (['"""MANDELBROT"""', '"""MANDL"""', '(1)', '(1)'], {}), "('MANDELBROT', 'MANDL', 1, 1)\n", (150, 179), False, 'from AIPSData import AIPSImage\n'), ((189, 206), 'AIPSTask.AIPSTask', 'AIPSTask', (['"""mandl"""'], {}), "('mandl')\n", (197, 206), False, 'from AIPSTask impor... |
import bpy
import bmesh
import numpy
from random import randint
import time
# pointsToVoxels() has been modified from the function generate_blocks() in https://github.com/cagcoach/BlenderPlot/blob/master/blendplot.py
# Some changes to accomodate Blender 2.8's API changes were made,
# and the function has been made m... | [
"numpy.tile",
"numpy.reshape",
"numpy.unique",
"bmesh.update_edit_mesh",
"bpy.data.objects.new",
"bpy.data.meshes.new",
"bpy.context.collection.objects.link",
"bmesh.new",
"numpy.array",
"time.time",
"bpy.ops.mesh.primitive_cube_add"
] | [((721, 749), 'numpy.unique', 'numpy.unique', (['points'], {'axis': '(0)'}), '(points, axis=0)\n', (733, 749), False, 'import numpy\n'), ((806, 833), 'bpy.data.meshes.new', 'bpy.data.meshes.new', (['"""mesh"""'], {}), "('mesh')\n", (825, 833), False, 'import bpy\n'), ((862, 894), 'bpy.data.objects.new', 'bpy.data.objec... |
#!/usr/bin/python
#-*-coding:utf-8-*-
import json
import sys
import time
# TBD: auto discovery
# data_path = "/proc/fs/lustre/llite/nvmefs-ffff883f8a4f2800/stats"
data_path = "/proc/fs/lustre/lmv/shnvme3-clilmv-ffff8859d3e2d000/md_stats"
# use a dic1/dic2 to hold sampling data
def load_data(dic):
# Open file ... | [
"json.dumps",
"time.sleep"
] | [((942, 1003), 'json.dumps', 'json.dumps', (['dic'], {'indent': '(2)', 'sort_keys': '(True)', 'ensure_ascii': '(False)'}), '(dic, indent=2, sort_keys=True, ensure_ascii=False)\n', (952, 1003), False, 'import json\n'), ((1868, 1881), 'time.sleep', 'time.sleep', (['(2)'], {}), '(2)\n', (1878, 1881), False, 'import time\n... |
import unittest
from hashlib import sha1
import pickle
import numpy as np
from datasketch.lsh import MinHashLSH
from datasketch.minhash import MinHash
from datasketch.weighted_minhash import WeightedMinHashGenerator
class TestMinHashLSH(unittest.TestCase):
def test_init(self):
lsh = MinHashLSH(threshold=... | [
"datasketch.lsh.MinHashLSH",
"datasketch.weighted_minhash.WeightedMinHashGenerator",
"pickle.dumps",
"datasketch.minhash.MinHash",
"numpy.random.uniform",
"unittest.main"
] | [((5700, 5715), 'unittest.main', 'unittest.main', ([], {}), '()\n', (5713, 5715), False, 'import unittest\n'), ((299, 324), 'datasketch.lsh.MinHashLSH', 'MinHashLSH', ([], {'threshold': '(0.8)'}), '(threshold=0.8)\n', (309, 324), False, 'from datasketch.lsh import MinHashLSH\n'), ((409, 454), 'datasketch.lsh.MinHashLSH... |