code stringlengths 22 1.05M | apis listlengths 1 3.31k | extract_api stringlengths 75 3.25M |
|---|---|---|
# coding=utf-8
import tensorflow as tf
v = tf.Variable(0, dtype=tf.float32, name='v3')
# 在没有声明滑动平均模型时只有一个变量v，所以下面的语句只会输出v:0
for variables in tf.global_variables():
print(variables.name)
ema = tf.train.ExponentialMovingAverage(0.99)
# 加入命名空间中
maintain_averages_op = ema.apply(tf.global_variables())
# 在申明滑动平均模型之后，T... | [
"tensorflow.Variable",
"tensorflow.Session",
"tensorflow.train.Saver",
"tensorflow.global_variables",
"tensorflow.global_variables_initializer",
"tensorflow.assign",
"tensorflow.train.ExponentialMovingAverage"
] | [((44, 87), 'tensorflow.Variable', 'tf.Variable', (['(0)'], {'dtype': 'tf.float32', 'name': '"""v3"""'}), "(0, dtype=tf.float32, name='v3')\n", (55, 87), True, 'import tensorflow as tf\n'), ((143, 164), 'tensorflow.global_variables', 'tf.global_variables', ([], {}), '()\n', (162, 164), True, 'import tensorflow as tf\n'... |
"""
validataclass
Copyright (c) 2021, binary butterfly GmbH and contributors
Use of this source code is governed by an MIT-style license that can be found in the LICENSE file.
"""
from datetime import date
from typing import Any
from .string_validator import StringValidator
from validataclass.exceptions import Invali... | [
"validataclass.exceptions.InvalidDateError",
"datetime.date.fromisoformat"
] | [((1329, 1360), 'datetime.date.fromisoformat', 'date.fromisoformat', (['date_string'], {}), '(date_string)\n', (1347, 1360), False, 'from datetime import date\n'), ((1406, 1424), 'validataclass.exceptions.InvalidDateError', 'InvalidDateError', ([], {}), '()\n', (1422, 1424), False, 'from validataclass.exceptions import... |
#!/usr/bin/env python
# coding: utf-8
from __future__ import print_function
from __future__ import absolute_import
import os
import re
import shutil
import stat
import sys
import tct
from os.path import exists as ospe, join as ospj
from tct import deepget
params = tct.readjson(sys.argv[1])
binabspath = sys.argv[2]
... | [
"tct.make_snapshot_of_milestones",
"os.path.exists",
"tct.deepget",
"shutil.copy2",
"os.path.join",
"os.chmod",
"shutil.copytree",
"tct.readjson",
"os.path.split",
"os.path.isdir",
"tct.save_the_result",
"sys.exit",
"os.stat",
"re.subn"
] | [((269, 294), 'tct.readjson', 'tct.readjson', (['sys.argv[1]'], {}), '(sys.argv[1])\n', (281, 294), False, 'import tct\n'), ((328, 361), 'tct.readjson', 'tct.readjson', (["params['factsfile']"], {}), "(params['factsfile'])\n", (340, 361), False, 'import tct\n'), ((375, 413), 'tct.readjson', 'tct.readjson', (["params['m... |
import logging
import random
import time
import src.support.outbound_routing as ob
from src.support.creds import build_cred, build_proof_request, build_schema, build_credential_proposal, build_proof_proposal
import src.support.settings as config
# This file containst the functions that perform transaction-specific
# ... | [
"src.support.creds.build_proof_request",
"logging.debug",
"src.support.outbound_routing.get_pres_ex_records",
"src.support.creds.build_credential_proposal",
"src.support.settings.agent_data.update_package_no",
"src.support.outbound_routing.send_proof_proposal",
"src.support.outbound_routing.get_schema",... | [((949, 1129), 'src.support.creds.build_credential_proposal', 'build_credential_proposal', (['config.agent_data.current_connection'], {'comment': '"""request for payment agreement credential"""', 'schema_name': '"""payment agreement"""', 'prop_schema': 'proposal'}), "(config.agent_data.current_connection, comment=\n ... |
#
# To run locally, execute:
#
# spark-submit --master local[2] wide_and_deep_example.py
#
S3_ROOT_DIR = 's3://{YOUR_S3_BUCKET}/{YOUR_S3_PATH}/'
batch_size = 100
worker_count = 1
server_count = 1
import metaspore as ms
spark = ms.spark.get_session(batch_size=batch_size,
worker_count=wo... | [
"metaspore.spark.get_session",
"pyspark.ml.evaluation.BinaryClassificationEvaluator",
"metaspore.nn.WideAndDeepModule",
"metaspore.PyTorchEstimator",
"metaspore.input.read_s3_csv"
] | [((232, 333), 'metaspore.spark.get_session', 'ms.spark.get_session', ([], {'batch_size': 'batch_size', 'worker_count': 'worker_count', 'server_count': 'server_count'}), '(batch_size=batch_size, worker_count=worker_count,\n server_count=server_count)\n', (252, 333), True, 'import metaspore as ms\n'), ((468, 827), 'me... |
# dockerpty.
#
# Copyright 2014 <NAME> <<EMAIL>>
#
# 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 ag... | [
"dockerpty.pty.RunOperation",
"dockerpty.pty.ExecOperation",
"dockerpty.pty.PseudoTerminal",
"dockerpty.pty.exec_create"
] | [((950, 1064), 'dockerpty.pty.RunOperation', 'RunOperation', (['client', 'container'], {'interactive': 'interactive', 'stdout': 'stdout', 'stderr': 'stderr', 'stdin': 'stdin', 'logs': 'logs'}), '(client, container, interactive=interactive, stdout=stdout,\n stderr=stderr, stdin=stdin, logs=logs)\n', (962, 1064), Fals... |
import numpy as np
from astroquery.hitran import Hitran
from astropy import units as un
from astropy.constants import c, k_B, h, u
def calc_solid_angle(radius,distance):
'''
Convenience function to calculate solid angle from radius and distance, assuming a disk shape.
Parameters
----------
radius ... | [
"numpy.sqrt"
] | [((945, 973), 'numpy.sqrt', 'np.sqrt', (['(solid_angle / np.pi)'], {}), '(solid_angle / np.pi)\n', (952, 973), True, 'import numpy as np\n')] |
from random import shuffle#自带洗牌方法
from copy import deepcopy
class Solution(object):
def __init__(self, nums):
"""
:type nums: List[int]
:type size: int
"""
self.nums=nums
def reset(self):
"""
Resets the array to its original configurati... | [
"random.shuffle",
"copy.deepcopy"
] | [((537, 556), 'copy.deepcopy', 'deepcopy', (['self.nums'], {}), '(self.nums)\n', (545, 556), False, 'from copy import deepcopy\n'), ((602, 615), 'random.shuffle', 'shuffle', (['nums'], {}), '(nums)\n', (609, 615), False, 'from random import shuffle\n')] |
# Copyright (c) Facebook, Inc. and its affiliates.
import numpy as np
from termcolor import colored
import logging
import torch.nn as nn
import torch.utils.data
log = logging.getLogger(__name__)
import torch
import numpy as np
import math
class Dataset(torch.utils.data.Dataset):
def __init__(self, x, y):
... | [
"logging.getLogger",
"torch.nn.Tanh",
"numpy.array",
"torch.sum",
"numpy.mean",
"torch.mean",
"torch.zeros_like",
"numpy.random.permutation",
"torch.Tensor",
"torch.autograd.grad",
"torch.cat",
"torch.clamp",
"torch.nn.Softplus",
"math.ceil",
"torch.log",
"torch.stack",
"torch.nn.Lin... | [((169, 196), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (186, 196), False, 'import logging\n'), ((4210, 4239), 'numpy.random.permutation', 'np.random.permutation', (['n_data'], {}), '(n_data)\n', (4231, 4239), True, 'import numpy as np\n'), ((1774, 1795), 'numpy.array', 'np.array', (... |
import unittest
import os
import sys
import argparse
import numpy as np
import audacity as aud
print('Module file:')
print(aud.__file__)
SCRIPT_DIR = os.path.split(os.path.realpath(__file__))[0]
PACKAGE_DIR = os.path.realpath(os.path.join(SCRIPT_DIR,'..'))
DATA_DIR = os.path.join(PACKAGE_DIR, 'data')
TEST_FILE_1 = ... | [
"audacity.Aup",
"argparse.ArgumentParser",
"os.path.join",
"os.path.realpath",
"unittest.main"
] | [((271, 304), 'os.path.join', 'os.path.join', (['PACKAGE_DIR', '"""data"""'], {}), "(PACKAGE_DIR, 'data')\n", (283, 304), False, 'import os\n'), ((320, 356), 'os.path.join', 'os.path.join', (['DATA_DIR', '"""test-1.aup"""'], {}), "(DATA_DIR, 'test-1.aup')\n", (332, 356), False, 'import os\n'), ((229, 259), 'os.path.joi... |
# -*- coding: utf-8 -*-
"""
# @Time : 24/10/18 2:40 PM
# @Author : <NAME>
# @FileName: plot_result.py
# @Software: PyCharm
# @Github ： https://github.com/hzm2016
"""
import collections
import matplotlib.pyplot as plt
import numpy as np
import pickle
import copy as cp
from baselines.deepq.assembly.src.value_funct... | [
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"pickle.load",
"numpy.array",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.tight_layout",
... | [((719, 773), 'numpy.array', 'np.array', (['[40, 40, 0, 5, 5, 5, 542, -36, 188, 5, 5, 5]'], {}), '([40, 40, 0, 5, 5, 5, 542, -36, 188, 5, 5, 5])\n', (727, 773), True, 'import numpy as np\n'), ((780, 844), 'numpy.array', 'np.array', (['[-40, -40, -40, -5, -5, -5, 538, -42, 192, -5, -5, -5]'], {}), '([-40, -40, -40, -5, ... |
from repacolors import ColorScale
from .colorbrewer import PALETTES as CBPALETTES
PALETTES = {
"ryb": ["#fe2713", "#fd5307", "#fb9900", "#fabc00", "#fefe34", "#d1e92c", "#66b032", "#0492ce", "#0347fe", "#3e01a4", "#8600af", "#a7194b"],
"rybw3": ["#FE2712", "#FC600A", "#FB9902", "#FCCC1A", "#FEFE33", "#B2D732"... | [
"repacolors.ColorScale"
] | [((790, 808), 'repacolors.ColorScale', 'ColorScale', (['colors'], {}), '(colors)\n', (800, 808), False, 'from repacolors import ColorScale\n')] |
# Copyright (c) 2019 <NAME> <<EMAIL>>
# See the COPYRIGHT file for more information
import subprocess
import time
def ping(guest_ip):
out = subprocess.run(['ping', '-c 1', guest_ip], capture_output=True)
return out.returncode == 0
def nmap_ssh(guest_ip):
out = subprocess.run(['nmap', guest_ip, '-PN', ... | [
"subprocess.run",
"time.time"
] | [((147, 210), 'subprocess.run', 'subprocess.run', (["['ping', '-c 1', guest_ip]"], {'capture_output': '(True)'}), "(['ping', '-c 1', guest_ip], capture_output=True)\n", (161, 210), False, 'import subprocess\n'), ((278, 350), 'subprocess.run', 'subprocess.run', (["['nmap', guest_ip, '-PN', '-p ssh']"], {'capture_output'... |
import json
from urllib.parse import urljoin
from django.conf import settings
import requests
def get_ticket_endpoint():
return urljoin(settings.ZENDESK_BASE_URL, '/api/v2/tickets.json')
def zendesk_auth():
return (
'{username}/token'.format(username=settings.ZENDESK_API_USERNAME),
settings... | [
"json.dumps",
"urllib.parse.urljoin"
] | [((135, 193), 'urllib.parse.urljoin', 'urljoin', (['settings.ZENDESK_BASE_URL', '"""/api/v2/tickets.json"""'], {}), "(settings.ZENDESK_BASE_URL, '/api/v2/tickets.json')\n", (142, 193), False, 'from urllib.parse import urljoin\n'), ((1054, 1073), 'json.dumps', 'json.dumps', (['payload'], {}), '(payload)\n', (1064, 1073)... |
from django.conf import settings
from rest_framework.routers import DefaultRouter, SimpleRouter
from message_service.mailing.api.views import (
ClientsViewSet,
MailingViewSet,
MessageViewSet,
)
from message_service.users.api.views import UserViewSet
if settings.DEBUG:
router = DefaultRouter()
else:
... | [
"rest_framework.routers.SimpleRouter",
"rest_framework.routers.DefaultRouter"
] | [((296, 311), 'rest_framework.routers.DefaultRouter', 'DefaultRouter', ([], {}), '()\n', (309, 311), False, 'from rest_framework.routers import DefaultRouter, SimpleRouter\n'), ((331, 345), 'rest_framework.routers.SimpleRouter', 'SimpleRouter', ([], {}), '()\n', (343, 345), False, 'from rest_framework.routers import De... |
#! /usr/bin/env python
from math import factorial
import numpy as np
# test passed
def generate_poly(max_exponent,max_diff,symbol):
f=np.zeros((max_diff+1, max_exponent+1), dtype=float)
for k in range(max_diff+1):
for i in range(max_exponent+1):
if (i - k) >= 0:
f[k,i] = factorial(i)*symbol**(i-k)/facto... | [
"math.factorial",
"numpy.zeros"
] | [((137, 192), 'numpy.zeros', 'np.zeros', (['(max_diff + 1, max_exponent + 1)'], {'dtype': 'float'}), '((max_diff + 1, max_exponent + 1), dtype=float)\n', (145, 192), True, 'import numpy as np\n'), ((315, 331), 'math.factorial', 'factorial', (['(i - k)'], {}), '(i - k)\n', (324, 331), False, 'from math import factorial\... |
# ---
# jupyter:
# jupytext:
# formats: ipynb,py:light
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.11.0
# kernelspec:
# display_name: Python 3
# language: python
# name: python3
# ---
import torch
def train... | [
"torch.vstack",
"torch.cuda.empty_cache",
"torch.randn"
] | [((3316, 3336), 'torch.randn', 'torch.randn', (['(15, 1)'], {}), '((15, 1))\n', (3327, 3336), False, 'import torch\n'), ((3341, 3360), 'torch.randn', 'torch.randn', (['(9, 1)'], {}), '((9, 1))\n', (3352, 3360), False, 'import torch\n'), ((3362, 3382), 'torch.vstack', 'torch.vstack', (['(a, b)'], {}), '((a, b))\n', (337... |
import sqlite3
import pandas as pd
import re
import random
from bs4 import BeautifulSoup
class Process:
SEQ_LENGTH = 40
sql_transaction = []
dataset = []
cursor_train = None
cursor_validation = None
cursor_test = None
# I know in advance that there are 199819620 rows
NUM_ROWS = 19... | [
"random.shuffle",
"sqlite3.connect",
"pandas.read_csv",
"bs4.BeautifulSoup",
"re.sub"
] | [((610, 662), 'sqlite3.connect', 'sqlite3.connect', (["(database_dir + '/sequence_train.db')"], {}), "(database_dir + '/sequence_train.db')\n", (625, 662), False, 'import sqlite3\n'), ((829, 879), 'sqlite3.connect', 'sqlite3.connect', (["(database_dir + '/sequence_val.db')"], {}), "(database_dir + '/sequence_val.db')\n... |
from django.conf.urls import url
from . import views
urlpatterns = [
#url(r'^view/(?P<pk>[0-9]+)', views.ArticleDetailView.as_view(), name = "detail"),
#url(r'', views.ArticleIndexView.as_view(), name = "index"),
url(r'login', views.Login.as_view()),
url(r'logout', views.Logout.as_view()),
... | [
"django.conf.urls.url"
] | [((444, 464), 'django.conf.urls.url', 'url', (['""""""', 'views.Panel'], {}), "('', views.Panel)\n", (447, 464), False, 'from django.conf.urls import url\n')] |
"""
Copyright (c) Contributors to the Open 3D Engine Project. For complete copyright and license terms please see the LICENSE at the root of this distribution.
SPDX-License-Identifier: Apache-2.0 OR MIT
"""
# setup path
import azlmbr.legacy.general as general
import azlmbr.bus as bus
import azlmbr.editor as editor
im... | [
"azlmbr.entity.EntityId",
"azlmbr.editor.EditorEntityAPIBus",
"azlmbr.editor.EditorComponentAPIBus",
"azlmbr.legacy.general.find_editor_entity"
] | [((675, 713), 'azlmbr.legacy.general.find_editor_entity', 'general.find_editor_entity', (['"""WhiteBox"""'], {}), "('WhiteBox')\n", (701, 713), True, 'import azlmbr.legacy.general as general\n'), ((1471, 1585), 'azlmbr.editor.EditorComponentAPIBus', 'editor.EditorComponentAPIBus', (['bus.Broadcast', '"""AddComponentsOf... |
from dask.distributed import Client
import dask.dataframe as dd
import pandas as pd
import numpy as np
import os
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from sklearn.manifold import TSNE
from sklearn.decomposition import PCA
from IPython.display import display, HTML
from sklearn.cluster import KMeans... | [
"sklearn.metrics.f1_score",
"numpy.unique",
"pandas.read_csv",
"os.path.join",
"sklearn.metrics.recall_score",
"matplotlib.pyplot.rcParams.update",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.axes",
"functools.partial",
"matplotlib.pyplot.scatter",
"matplotlib.cm.tab20",
"pandas.DataFrame",... | [((2021, 2059), 'matplotlib.pyplot.rcParams.update', 'plt.rcParams.update', (["{'font.size': 14}"], {}), "({'font.size': 14})\n", (2040, 2059), True, 'import matplotlib.pyplot as plt\n'), ((2306, 2333), 'matplotlib.pyplot.figure', 'plt.figure', ([], {'figsize': '(10, 8)'}), '(figsize=(10, 8))\n', (2316, 2333), True, 'i... |
#!/usr/bin/env python3
# encoding: utf-8
import torch.nn.functional as F
from rls.algorithms.single.dqn import DQN
from rls.common.decorator import iton
from rls.utils.torch_utils import n_step_return
class DDQN(DQN):
"""
Double DQN, https://arxiv.org/abs/1509.06461
Double DQN + LSTM, https... | [
"rls.utils.torch_utils.n_step_return"
] | [((1115, 1207), 'rls.utils.torch_utils.n_step_return', 'n_step_return', (['BATCH.reward', 'self.gamma', 'BATCH.done', 'q_target_next_max', 'BATCH.begin_mask'], {}), '(BATCH.reward, self.gamma, BATCH.done, q_target_next_max,\n BATCH.begin_mask)\n', (1128, 1207), False, 'from rls.utils.torch_utils import n_step_return... |
#!/usr/bin/python3
import os
os.system('wget \
https://opendata.arcgis.com/datasets/6ac5e325468c4cb9b905f1728d6fbf0f_0.csv \
-O hifld_hospital.csv')
| [
"os.system"
] | [((29, 154), 'os.system', 'os.system', (['"""wget https://opendata.arcgis.com/datasets/6ac5e325468c4cb9b905f1728d6fbf0f_0.csv -O hifld_hospital.csv"""'], {}), "(\n 'wget https://opendata.arcgis.com/datasets/6ac5e325468c4cb9b905f1728d6fbf0f_0.csv -O hifld_hospital.csv'\n )\n", (38, 154), False, 'import os\n')] |
import argparse
import subprocess
import sys
import logging
logger = logging.getLogger("helper")
def azcli(command):
process = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
out,err = process.communicate()
logger.debug(str(out,"utf-8"))
exit_code = process.returncode
if ... | [
"logging.getLogger",
"subprocess.Popen",
"sys.exit"
] | [((70, 97), 'logging.getLogger', 'logging.getLogger', (['"""helper"""'], {}), "('helper')\n", (87, 97), False, 'import logging\n'), ((133, 206), 'subprocess.Popen', 'subprocess.Popen', (['command'], {'stdout': 'subprocess.PIPE', 'stderr': 'subprocess.PIPE'}), '(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n... |
from Vertex import Vertex
import pygame
from Colours import Colours
class Grid:
def createGrid(self, rows, width):
grid = []
space = width // rows
for x in range(rows):
grid.append([])
for i in range(rows):
vertex = Vertex(space, rows, x, i... | [
"pygame.display.update",
"Vertex.Vertex",
"pygame.draw.line"
] | [((964, 987), 'pygame.display.update', 'pygame.display.update', ([], {}), '()\n', (985, 987), False, 'import pygame\n'), ((510, 585), 'pygame.draw.line', 'pygame.draw.line', (['window', 'Colours.BLACK', '(0, x * space)', '(width, x * space)'], {}), '(window, Colours.BLACK, (0, x * space), (width, x * space))\n', (526, ... |
# -*- coding: utf-8 -*-
# -----------------------------------------------------------------------------
# (C) British Crown copyright. The Met Office.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are me... | [
"iris.cube.CubeList",
"numpy.ones",
"improver.synthetic_data.set_up_test_cubes.set_up_variable_cube",
"improver.precipitation_type.shower_condition_probability.ShowerConditionProbability",
"numpy.array",
"numpy.zeros",
"pytest.raises",
"pytest.fixture"
] | [((2584, 2617), 'pytest.fixture', 'pytest.fixture', ([], {'name': '"""test_cubes"""'}), "(name='test_cubes')\n", (2598, 2617), False, 'import pytest\n'), ((2745, 2755), 'iris.cube.CubeList', 'CubeList', ([], {}), '()\n', (2753, 2755), False, 'from iris.cube import CubeList\n'), ((9135, 9171), 'improver.precipitation_ty... |
# pylint: disable=no-member, too-many-locals, no-self-use
"""Vessels File Upload """
import time
from flask import request
# from library.couch_database import CouchDatabase
from library.postgresql_queries import PostgreSQL
from library.couch_queries import Queries
from library.common import Common
from library... | [
"flask.request.args.get",
"flask.request.files.getlist",
"library.couch_queries.Queries",
"library.aws_s3.AwsS3",
"library.postgresql_queries.PostgreSQL",
"time.time",
"flask.request.headers.get"
] | [((523, 532), 'library.couch_queries.Queries', 'Queries', ([], {}), '()\n', (530, 532), False, 'from library.couch_queries import Queries\n'), ((558, 570), 'library.postgresql_queries.PostgreSQL', 'PostgreSQL', ([], {}), '()\n', (568, 570), False, 'from library.postgresql_queries import PostgreSQL\n'), ((592, 599), 'li... |
import tensorflow as tf
import numpy as np
from tqdm.notebook import tqdm
class System():
def __init__(self,
num_part,
dim,
Ansatz=None,
External=None,
Internal=None,
Sampler=None
):
self... | [
"tensorflow.random.uniform",
"tensorflow.reshape",
"tensorflow.reduce_sum",
"tensorflow.math.sqrt",
"numpy.linalg.norm",
"numpy.sum",
"numpy.zeros",
"numpy.random.uniform",
"tensorflow.convert_to_tensor",
"tqdm.notebook.tqdm",
"tensorflow.norm"
] | [((842, 929), 'tensorflow.random.uniform', 'tf.random.uniform', (['(batch_size, dim)'], {'minval': '(-2)', 'maxval': '(2)', 'dtype': 'tf.dtypes.float64'}), '((batch_size, dim), minval=-2, maxval=2, dtype=tf.dtypes.\n float64)\n', (859, 929), True, 'import tensorflow as tf\n'), ((2594, 2617), 'numpy.zeros', 'np.zeros... |
from setuptools import setup
setup(
name='torch-dimcheck',
version='0.0.1',
description='Dimensionality annotations for tensor parameters and return values',
packages=['torch_dimcheck'],
author='<NAME>',
author_email='<EMAIL>',
)
| [
"setuptools.setup"
] | [((30, 236), 'setuptools.setup', 'setup', ([], {'name': '"""torch-dimcheck"""', 'version': '"""0.0.1"""', 'description': '"""Dimensionality annotations for tensor parameters and return values"""', 'packages': "['torch_dimcheck']", 'author': '"""<NAME>"""', 'author_email': '"""<EMAIL>"""'}), "(name='torch-dimcheck', ver... |
#!/usr/bin/env python
from os import (
path as os_path,
mkdir as os_mkdir,
getcwd
)
from argparse import ArgumentParser
from logging import (
Logger,
getLogger
)
from glob import glob
from typing import (
Dict,
)
from colored import fg, bg, attr
from brs_utils import (
create_logger
)
from... | [
"logging.getLogger",
"os.path.exists",
"colored.fg",
"os.path.join",
"os.mkdir",
"colored.attr",
"os.path.getmtime",
"brs_utils.create_logger"
] | [((729, 748), 'logging.getLogger', 'getLogger', (['__name__'], {}), '(__name__)\n', (738, 748), False, 'from logging import Logger, getLogger\n'), ((2136, 2172), 'brs_utils.create_logger', 'create_logger', (['parser.prog', 'args.log'], {}), '(parser.prog, args.log)\n', (2149, 2172), False, 'from brs_utils import create... |
import functools
import heapq
import logging
from collections import deque
from threading import Condition, RLock
from typing import Any, Callable, List, NamedTuple, Optional
from pytils.mixins import DaemonHandler
from ._config.time import DEFAULT_TIME_SUPPLIER, TimeSupplier, TimeType, ZERO_DURATION
__all__ = [
... | [
"logging.getLogger",
"collections.deque",
"threading.RLock",
"heapq.heappop",
"heapq.heappush",
"threading.Condition"
] | [((842, 875), 'logging.getLogger', 'logging.getLogger', (['"""pytils.clock"""'], {}), "('pytils.clock')\n", (859, 875), False, 'import logging\n'), ((1683, 1694), 'threading.Condition', 'Condition', ([], {}), '()\n', (1692, 1694), False, 'from threading import Condition, RLock\n'), ((1722, 1750), 'collections.deque', '... |
"""Execute validated & constructed query on device.
Accepts input from front end application, validates the input and
returns errors if input is invalid. Passes validated parameters to
construct.py, which is used to build & run the Netmiko connections or
hyperglass-frr API calls, returns the output back to the front e... | [
"hyperglass.util.parse_exception",
"hyperglass.exceptions.ResponseEmpty",
"httpx.AsyncClient",
"hyperglass.log.log.error",
"hyperglass.exceptions.RestError",
"hyperglass.log.log.debug"
] | [((947, 992), 'hyperglass.log.log.debug', 'log.debug', (['"""Query parameters: {}"""', 'self.query'], {}), "('Query parameters: {}', self.query)\n", (956, 992), False, 'from hyperglass.log import log\n'), ((2077, 2116), 'hyperglass.log.log.debug', 'log.debug', (['"""URL endpoint: {}"""', 'endpoint'], {}), "('URL endpoi... |
import test_agent
print('Logging in')
Meerkat = test_agent.TestAgent(username='meerkat', password='<PASSWORD>', endpoint='/messages/')
Pangolin = test_agent.TestAgent(username='pangolin', password='<PASSWORD>', endpoint='/messages/')
Badger = test_agent.TestAgent(username='badger', password='<PASSWORD>', endpoint='/me... | [
"test_agent.TestAgent"
] | [((49, 140), 'test_agent.TestAgent', 'test_agent.TestAgent', ([], {'username': '"""meerkat"""', 'password': '"""<PASSWORD>"""', 'endpoint': '"""/messages/"""'}), "(username='meerkat', password='<PASSWORD>', endpoint=\n '/messages/')\n", (69, 140), False, 'import test_agent\n'), ((147, 239), 'test_agent.TestAgent', '... |
""" Unit tests for the HR solver. """
import pytest
from matching import Matching
from matching import Player as Resident
from matching.games import HospitalResident
from matching.players import Hospital
from .params import HOSPITAL_RESIDENT, make_game, make_prefs
@HOSPITAL_RESIDENT
def test_init(resident_names, h... | [
"matching.players.Hospital",
"matching.games.HospitalResident",
"matching.games.HospitalResident.create_from_dictionaries",
"pytest.raises",
"matching.Player"
] | [((1226, 1316), 'matching.games.HospitalResident.create_from_dictionaries', 'HospitalResident.create_from_dictionaries', (['resident_prefs', 'hospital_prefs', 'capacities_'], {}), '(resident_prefs, hospital_prefs,\n capacities_)\n', (1267, 1316), False, 'from matching.games import HospitalResident\n'), ((4191, 4211)... |
import date
import os
def get_time_delta(kline_type = '1_day'):
if kline_type.lower() == '1_day'.lower():
return 0
kline_array = kline_type.split("_")
if len(kline_array) != 2:
raise ValueError('KLine_type {0} not supported'.format(kline_type))
if kline_array[1].lower() == 'min'.lower()... | [
"date.create_kline_time_string"
] | [((1617, 1681), 'date.create_kline_time_string', 'date.create_kline_time_string', (['(9)', '(30)', '(time_delta * time_interval)'], {}), '(9, 30, time_delta * time_interval)\n', (1646, 1681), False, 'import date\n'), ((1769, 1833), 'date.create_kline_time_string', 'date.create_kline_time_string', (['(13)', '(0)', '(tim... |
from collections import defaultdict
def check_winner(cards):
for card_index, card in cards.items():
for index in range(5):
complete_line = all([x[1] for x in card[index]])
complete_column = all([card[x][index][1] for x in range(5)])
if complete_line or complete_column:
... | [
"collections.defaultdict"
] | [((508, 525), 'collections.defaultdict', 'defaultdict', (['list'], {}), '(list)\n', (519, 525), False, 'from collections import defaultdict\n')] |
"""
Demonstrates the hover functionality of mpldatacursor as well as point labels
and a custom formatting function. Notice that overlapping points have both
labels displayed.
"""
import string
import matplotlib.pyplot as plt
import numpy as np
from mpldatacursor import datacursor
np.random.seed(1977)
x, y = np.random.... | [
"numpy.random.random",
"numpy.random.seed",
"matplotlib.pyplot.subplots",
"mpldatacursor.datacursor",
"matplotlib.pyplot.show"
] | [((281, 301), 'numpy.random.seed', 'np.random.seed', (['(1977)'], {}), '(1977)\n', (295, 301), True, 'import numpy as np\n'), ((310, 335), 'numpy.random.random', 'np.random.random', (['(2, 26)'], {}), '((2, 26))\n', (326, 335), True, 'import numpy as np\n'), ((379, 393), 'matplotlib.pyplot.subplots', 'plt.subplots', ([... |
import torch
import torch.nn as nn
class FilterResponseNorm(nn.Module):
def __init__(self, num_features, eps=1e-6, use_TLU=True):
super(FilterResponseNorm, self).__init__()
self.num_features = num_features
self.eps = eps
self.use_TLU = use_TLU
self.weight = nn.Parameter(t... | [
"torch.max",
"torch.nn.init.uniform_",
"torch.nn.init.zeros_",
"torch.Tensor"
] | [((629, 658), 'torch.nn.init.uniform_', 'nn.init.uniform_', (['self.weight'], {}), '(self.weight)\n', (645, 658), True, 'import torch.nn as nn\n'), ((667, 692), 'torch.nn.init.zeros_', 'nn.init.zeros_', (['self.bias'], {}), '(self.bias)\n', (681, 692), True, 'import torch.nn as nn\n'), ((319, 345), 'torch.Tensor', 'tor... |
from time import time
def profile(funcao):
def funcao_wrapper(*args, **kwargs):
inicio = time()
resultado = funcao(*args, **kwargs)
fim = time()
print(fim - inicio)
return resultado
return funcao_wrapper
@profile
def f(n):
return 'Executei f {}'.format(n)
print(f... | [
"time.time"
] | [((103, 109), 'time.time', 'time', ([], {}), '()\n', (107, 109), False, 'from time import time\n'), ((168, 174), 'time.time', 'time', ([], {}), '()\n', (172, 174), False, 'from time import time\n')] |
import numpy as np
# import matplotlib.pyplot as plt
from scipy.cluster.vq import kmeans
# def plothist(x):
# vmin = x.min()-1
# vmax = x.max()+1
# bins = np.arange(vmin, vmax, (vmax - vmin)/50)
# plt.hist(x, bins=bins)
# plt.show()
# def scatterpred(pred):
# plt.scatter(pred[:,0], pred[:,1])
... | [
"numpy.zeros",
"scipy.cluster.vq.kmeans"
] | [((564, 578), 'numpy.zeros', 'np.zeros', (['nb_c'], {}), '(nb_c)\n', (572, 578), True, 'import numpy as np\n'), ((840, 854), 'numpy.zeros', 'np.zeros', (['nb_c'], {}), '(nb_c)\n', (848, 854), True, 'import numpy as np\n'), ((866, 883), 'numpy.zeros', 'np.zeros', (['c.shape'], {}), '(c.shape)\n', (874, 883), True, 'impo... |
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 20 13:32:20 2021
#--- ag csv results to single file based on dashboard_dbs
#--- <NAME> (<EMAIL>)
#--- Jul, 2021.
#--- Dev-log in: https://github.com/Murilodsv/py-jules
@author: muril
"""
# DEBUG import os; os.chdir('C:/Murilo/py-jules')
#---------------... | [
"os.path.exists",
"time.time",
"util.df_csv",
"os.getcwd"
] | [((1562, 1568), 'time.time', 'time', ([], {}), '()\n', (1566, 1568), False, 'from time import time\n'), ((1722, 1750), 'util.df_csv', 'u.df_csv', (["(wd + '/' + dash_nm)"], {}), "(wd + '/' + dash_nm)\n", (1730, 1750), True, 'import util as u\n'), ((1919, 1937), 'os.path.exists', 'os.path.exists', (['fn'], {}), '(fn)\n'... |
import os
from django.conf.urls.defaults import *
# Uncomment the next two lines to enable the admin:
# from django.contrib import admin
# admin.autodiscover()
urlpatterns = patterns('',
# Example:
# (r'^django_amf_example/', include('django_amf_example.foo.urls')),
# Uncomment the admin/doc line below ... | [
"os.path.join"
] | [((832, 862), 'os.path.join', 'os.path.join', (['"""flex"""', '"""deploy"""'], {}), "('flex', 'deploy')\n", (844, 862), False, 'import os\n')] |
# coding: utf-8
"""
MolecularMatch MMPower
MMPower API # noqa: E501
OpenAPI spec version: 1.0.0
Contact: <EMAIL>
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
import pprint
import re # noqa: F401
import six
class PrivateTrial(object):
"""NOTE: This class is auto g... | [
"six.iteritems"
] | [((50583, 50616), 'six.iteritems', 'six.iteritems', (['self.swagger_types'], {}), '(self.swagger_types)\n', (50596, 50616), False, 'import six\n')] |
import argparse
import gym
import gym_module_select
from stable_baselines.common.vec_env import DummyVecEnv
def init_parse_argument():
parser = argparse.ArgumentParser()
parser.add_argument('-e', '--num-exp', help='num experiment episode', type=int, default=10)
args = parser.parse_args()
return args
... | [
"gym.make",
"argparse.ArgumentParser",
"stable_baselines.common.vec_env.DummyVecEnv"
] | [((357, 426), 'gym.make', 'gym.make', (['"""ModuleSelect-v1"""'], {'verbose': '(1)', 'save_log_flag': '(True)', 'log_num': '(7)'}), "('ModuleSelect-v1', verbose=1, save_log_flag=True, log_num=7)\n", (365, 426), False, 'import gym\n'), ((495, 522), 'stable_baselines.common.vec_env.DummyVecEnv', 'DummyVecEnv', (['[lambda... |
import unittest
from flask_script import Manager, Shell, Server
from app import app, db
from app.fake_populate import populate
manager = Manager(app)
def make_shell_context():
return dict(app=app)
@manager.command
def recreate_db():
"""
Create the SQL database.
"""
db.drop_all()
db.create_all... | [
"app.db.session.commit",
"flask_script.Server",
"flask_script.Manager",
"flask_script.Shell",
"app.fake_populate.populate",
"app.read_licenses.read",
"app.db.create_all",
"app.db.drop_all",
"unittest.TextTestRunner",
"unittest.TestLoader"
] | [((138, 150), 'flask_script.Manager', 'Manager', (['app'], {}), '(app)\n', (145, 150), False, 'from flask_script import Manager, Shell, Server\n'), ((289, 302), 'app.db.drop_all', 'db.drop_all', ([], {}), '()\n', (300, 302), False, 'from app import app, db\n'), ((307, 322), 'app.db.create_all', 'db.create_all', ([], {}... |
from makememe.generator.prompts.prompt import Prompt
import datetime
from PIL import Image
from makememe.generator.design.image_manager import Image_Manager
class Waiting(Prompt):
name = "Waiting"
description = "waiting"
def __init__(self):
self.instruction = """
###
Message:I've been waiting for... | [
"datetime.datetime.now",
"makememe.generator.design.image_manager.Image_Manager.add_text",
"PIL.Image.alpha_composite"
] | [((928, 1045), 'makememe.generator.design.image_manager.Image_Manager.add_text', 'Image_Manager.add_text', ([], {'base': 'base', 'text': "meme_text['subject']", 'position': '(600, 950)', 'font_size': '(40)', 'wrapped_width': '(20)'}), "(base=base, text=meme_text['subject'], position=(600,\n 950), font_size=40, wrapp... |
from python_helper import log, Test, SettingHelper, RandomHelper, ObjectHelper, TestHelper, ReflectionHelper, Constant
from python_framework import EncapsulateItWithGlobalException, GlobalException, ExceptionHandler, HttpStatus
LOG_HELPER_SETTINGS = {
log.LOG : False,
log.INFO : True,
log.SUCCESS : True,
... | [
"python_framework.GlobalException",
"python_helper.ReflectionHelper.getClass",
"python_helper.Test",
"python_helper.TestHelper.getRaisedException",
"python_framework.EncapsulateItWithGlobalException"
] | [((830, 864), 'python_framework.EncapsulateItWithGlobalException', 'EncapsulateItWithGlobalException', ([], {}), '()\n', (862, 864), False, 'from python_framework import EncapsulateItWithGlobalException, GlobalException, ExceptionHandler, HttpStatus\n'), ((931, 965), 'python_framework.EncapsulateItWithGlobalException',... |
# -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-03-30 12:46
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('app', '0005_auto_20180330_1813'),
]
operations = [
... | [
"django.db.models.ManyToManyField"
] | [((434, 536), 'django.db.models.ManyToManyField', 'models.ManyToManyField', ([], {'blank': '(True)', 'related_name': '"""incubator_follows"""', 'to': 'settings.AUTH_USER_MODEL'}), "(blank=True, related_name='incubator_follows', to=\n settings.AUTH_USER_MODEL)\n", (456, 536), False, 'from django.db import migrations,... |
# encoding=utf-8
from airtest.core.win import Windows
import unittest
import numpy
import time
from testconf import try_remove
SNAPSHOT = "win_snapshot.png"
class TestWin(unittest.TestCase):
@classmethod
def setUpClass(cls):
w = Windows()
w.start_app("calc")
time.sleep(1)
cl... | [
"unittest.main",
"airtest.core.win.Windows",
"testconf.try_remove",
"time.sleep"
] | [((825, 840), 'unittest.main', 'unittest.main', ([], {}), '()\n', (838, 840), False, 'import unittest\n'), ((250, 259), 'airtest.core.win.Windows', 'Windows', ([], {}), '()\n', (257, 259), False, 'from airtest.core.win import Windows\n'), ((296, 309), 'time.sleep', 'time.sleep', (['(1)'], {}), '(1)\n', (306, 309), Fals... |
# Import required libraries
import cv2
from os.path import os, dirname
import tensorflow as tf
import numpy as np
from tqdm import tqdm
import random
# List of categories (directories names)
CATEGORIES = ["bad_apple", "bad_grape", "bad_pear", "cherry", "good_apple", "good_avocado", "good_grape", "good_pear", "ripe_avo... | [
"random.shuffle",
"os.path.os.listdir",
"numpy.array",
"tensorflow.keras.models.load_model",
"os.path.os.path.join",
"os.path.os.path.abspath"
] | [((618, 664), 'os.path.os.path.join', 'os.path.join', (['main_dir', '"""database"""', '"""training"""'], {}), "(main_dir, 'database', 'training')\n", (630, 664), False, 'from os.path import os, dirname\n'), ((679, 724), 'os.path.os.path.join', 'os.path.join', (['main_dir', '"""database"""', '"""testing"""'], {}), "(mai... |
"""Covers import of data downloaded from the
`Meadows online behavior platform <https://meadows-research.com/>`_.
For information on available file types see the meadows
`documentation on downloads <https://meadows-research.com/documentation\
/researcher/downloads/>`_.
"""
from os.path import basename
import numpy
fr... | [
"numpy.stack",
"scipy.io.loadmat",
"os.path.basename"
] | [((948, 962), 'scipy.io.loadmat', 'loadmat', (['fpath'], {}), '(fpath)\n', (955, 962), False, 'from scipy.io import loadmat\n'), ((1543, 1583), 'numpy.stack', 'numpy.stack', (['[data[v] for v in utv_vars]'], {}), '([data[v] for v in utv_vars])\n', (1554, 1583), False, 'import numpy\n'), ((3258, 3273), 'os.path.basename... |
import unittest
import torch
from torchvision.models.resnet import BasicBlock, Bottleneck
from nuscenes.prediction.models.backbone import ResNetBackbone, MobileNetBackbone
class TestBackBones(unittest.TestCase):
def count_layers(self, model):
if isinstance(model[4][0], BasicBlock):
n_convs ... | [
"nuscenes.prediction.models.backbone.MobileNetBackbone",
"nuscenes.prediction.models.backbone.ResNetBackbone",
"torch.ones"
] | [((597, 623), 'nuscenes.prediction.models.backbone.ResNetBackbone', 'ResNetBackbone', (['"""resnet18"""'], {}), "('resnet18')\n", (611, 623), False, 'from nuscenes.prediction.models.backbone import ResNetBackbone, MobileNetBackbone\n'), ((640, 666), 'nuscenes.prediction.models.backbone.ResNetBackbone', 'ResNetBackbone'... |
#!/usr/bin/python3
# -*- coding: utf-8 -*-
# @File : Qrbar_test.py
import cv2
import numpy as np
from pyzbar.pyzbar import decode
img = cv2.imread('qrcode.png')
for barcode in decode(img):
print(barcode.data.decode('utf-8'))
print(barcode.data)
pts = np.array([barcode.polygon], np.int32)
pts = pts.... | [
"pyzbar.pyzbar.decode",
"numpy.array",
"cv2.imread"
] | [((141, 165), 'cv2.imread', 'cv2.imread', (['"""qrcode.png"""'], {}), "('qrcode.png')\n", (151, 165), False, 'import cv2\n'), ((181, 192), 'pyzbar.pyzbar.decode', 'decode', (['img'], {}), '(img)\n', (187, 192), False, 'from pyzbar.pyzbar import decode\n'), ((268, 305), 'numpy.array', 'np.array', (['[barcode.polygon]', ... |
#!/usr/bin/env python
"""
"""
from __future__ import print_function
import argparse
import sys
from . import common
from . import helper
from . import vcs_tool
PARAMS = {}
PARAMS['this_script'] = common.get_script_name_from_filename(__file__)
def setup_and_dispatch():
parser = argparse.ArgumentParser(
... | [
"sys.exit"
] | [((1295, 1306), 'sys.exit', 'sys.exit', (['(0)'], {}), '(0)\n', (1303, 1306), False, 'import sys\n')] |
from django.db import models
# from themall.models import Customer
# Create your models here.
class Seller(models.Model):
email = models.OneToOneField('themall.Customer', on_delete=models.CASCADE, to_field='email')
store_name = models.CharField(max_length=100)
slug = models.SlugField(max_length=100)
descrip... | [
"django.db.models.OneToOneField",
"django.db.models.TextField",
"django.db.models.SlugField",
"django.db.models.CharField"
] | [((136, 225), 'django.db.models.OneToOneField', 'models.OneToOneField', (['"""themall.Customer"""'], {'on_delete': 'models.CASCADE', 'to_field': '"""email"""'}), "('themall.Customer', on_delete=models.CASCADE, to_field\n ='email')\n", (156, 225), False, 'from django.db import models\n'), ((236, 268), 'django.db.mode... |
# Copyright (c) 2017-2021, <NAME>. All rights reserved.
# For licensing, see https://github.com/mudita/MuditaOS/LICENSE.md
import time
import pytest
from harness import log
from harness.dom_parser_utils import *
from harness.interface.defs import key_codes
from bt_fixtures import *
@pytest.mark.rt1051
@pytest.mark.us... | [
"pytest.mark.usefixtures",
"time.sleep",
"pytest.mark.skipif"
] | [((306, 347), 'pytest.mark.usefixtures', 'pytest.mark.usefixtures', (['"""bt_all_devices"""'], {}), "('bt_all_devices')\n", (329, 347), False, 'import pytest\n'), ((349, 384), 'pytest.mark.usefixtures', 'pytest.mark.usefixtures', (['"""bt_reset"""'], {}), "('bt_reset')\n", (372, 384), False, 'import pytest\n'), ((386, ... |
import smtplib, ssl, os
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
from .html_template import emailHtml
from .text_template import emailText
port = 465
context = ssl.create_default_context()
def sendEmail(emailData):
adminUser = os.getenv("ADMIN_USERNAME")
password =... | [
"os.getenv",
"smtplib.SMTP_SSL",
"ssl.create_default_context",
"email.mime.multipart.MIMEMultipart",
"email.mime.text.MIMEText"
] | [((206, 234), 'ssl.create_default_context', 'ssl.create_default_context', ([], {}), '()\n', (232, 234), False, 'import smtplib, ssl, os\n'), ((278, 305), 'os.getenv', 'os.getenv', (['"""ADMIN_USERNAME"""'], {}), "('ADMIN_USERNAME')\n", (287, 305), False, 'import smtplib, ssl, os\n'), ((321, 344), 'os.getenv', 'os.geten... |
import requests
import os
import json
import datetime
'''
Pulls a dbml file from the API. User must manually add the file id, found in the 'response_ids.json' file generated from dbml_post_to_api.py
'''
url='http://ec2-54-167-67-34.compute-1.amazonaws.com/api/dbmls' #url of the API
id = '6192b1f31c2a512293f... | [
"requests.get"
] | [((422, 449), 'requests.get', 'requests.get', (['f"""{url}/{id}"""'], {}), "(f'{url}/{id}')\n", (434, 449), False, 'import requests\n')] |
from openpyxl import load_workbook
def getRowCount(file):
wb = load_workbook(file)
sheet = wb.active
return sheet.max_row
def getColumnCount(file):
wb = load_workbook(file)
sheet = wb.active
return sheet.max_column
def getCellData(file, cell):
wb = load_workbook(file)
sheet = wb.acti... | [
"openpyxl.load_workbook"
] | [((69, 88), 'openpyxl.load_workbook', 'load_workbook', (['file'], {}), '(file)\n', (82, 88), False, 'from openpyxl import load_workbook\n'), ((172, 191), 'openpyxl.load_workbook', 'load_workbook', (['file'], {}), '(file)\n', (185, 191), False, 'from openpyxl import load_workbook\n'), ((281, 300), 'openpyxl.load_workboo... |
# pommerman/cli/run_battle.py
# pommerman/agents/TensorFlowAgent/pit.py
import atexit
from datetime import datetime
import os
import random
import sys
import time
import argparse
import numpy as np
from pommerman import helpers, make
from TensorFlowAgent import TensorFlowAgent
from pommerman import utility
import ... | [
"tensorflow.reset_default_graph",
"argparse.ArgumentParser",
"tensorflow.Session",
"tensorflow.train.Saver",
"tensorflow.global_variables_initializer",
"numpy.array",
"TensorFlowAgent.TensorFlowAgent",
"numpy.zeros"
] | [((1290, 1314), 'tensorflow.reset_default_graph', 'tf.reset_default_graph', ([], {}), '()\n', (1312, 1314), True, 'import tensorflow as tf\n'), ((1580, 1605), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (1603, 1605), False, 'import argparse\n'), ((701, 717), 'numpy.zeros', 'np.zeros', (['(1,... |
import numpy as np
import tensorflow as tf
import unittest
from xcenternet.model.evaluation.overlap import compute_overlap
from xcenternet.model.evaluation.mean_average_precision import MAP
class TestMeanAveragePrecision(unittest.TestCase):
def setUp(self):
self.map_bboxes = np.array(
[
... | [
"numpy.array",
"tensorflow.constant",
"unittest.main",
"xcenternet.model.evaluation.overlap.compute_overlap",
"xcenternet.model.evaluation.mean_average_precision.MAP"
] | [((4629, 4644), 'unittest.main', 'unittest.main', ([], {}), '()\n', (4642, 4644), False, 'import unittest\n'), ((291, 435), 'numpy.array', 'np.array', (['[[[20, 10, 80, 60], [10, 40, 40, 90], [0, 0, 100, 100]], [[0, 0, 10, 10], [\n 20, 20, 40, 90], [80, 20, 100, 50]]]'], {'dtype': 'np.float64'}), '([[[20, 10, 80, 60... |
# Copyright 2017 The Sonnet Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... | [
"sonnet.examples.rmc_learn_to_execute.build_and_train",
"tensorflow.ones",
"sonnet.examples.learn_to_execute.LearnToExecute",
"sonnet.nets.MLP",
"tensorflow.test.main",
"sonnet.RelationalMemory",
"sonnet.examples.rmc_learn_to_execute.SequenceModel",
"tensorflow.zeros"
] | [((3048, 3062), 'tensorflow.test.main', 'tf.test.main', ([], {}), '()\n', (3060, 3062), True, 'import tensorflow as tf\n'), ((1280, 1376), 'sonnet.RelationalMemory', 'snt.RelationalMemory', ([], {'mem_slots': '(2)', 'head_size': '(4)', 'num_heads': '(1)', 'num_blocks': '(1)', 'gate_style': '"""unit"""'}), "(mem_slots=2... |
import os.path
from typing import Sequence, Optional, Dict
import numpy as np
import pandas as pd
from nk_sent2vec import Sent2Vec as _Sent2Vec
from d3m import container, utils
from d3m.primitive_interfaces.transformer import TransformerPrimitiveBase
from d3m.primitive_interfaces.base import CallResult
from d3m.contai... | [
"d3m.primitive_interfaces.base.CallResult",
"numpy.array",
"nk_sent2vec.Sent2Vec",
"d3m.container.DataFrame"
] | [((5704, 5730), 'd3m.container.DataFrame', 'd3m_DataFrame', (['embedded_df'], {}), '(embedded_df)\n', (5717, 5730), True, 'from d3m.container import DataFrame as d3m_DataFrame\n'), ((5034, 5080), 'nk_sent2vec.Sent2Vec', '_Sent2Vec', ([], {'path': "self.volumes['sent2vec_model']"}), "(path=self.volumes['sent2vec_model']... |
# ============================================================================
#
# Copyright (c) 2007-2010 Integral Technology Solutions Pty Ltd,
# All Rights Reserved.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABIL... | [
"validation_helper.printHeader",
"java.io.File"
] | [((1218, 1276), 'validation_helper.printHeader', 'helper.printHeader', (['"""[VALIDATING] admin server properties"""'], {}), "('[VALIDATING] admin server properties')\n", (1236, 1276), True, 'import validation_helper as helper\n'), ((6765, 6779), 'java.io.File', 'File', (['filename'], {}), '(filename)\n', (6769, 6779),... |
import sys
# import the GameState of the game
from Game.GameStateConnect4 import GameState
# import all agents
from Agents.MCTS import MCTSTree
from Agents.Random import RandomAgent
from Agents.AlphaBeta import AlphaBetaAgent
# creates the board string for connect4 (full of zeros)
start_board_list = ["000000 ... | [
"Game.GameStateConnect4.GameState",
"Agents.Random.RandomAgent",
"Agents.MCTS.MCTSTree",
"sys.exit",
"Agents.AlphaBeta.AlphaBetaAgent"
] | [((663, 688), 'Game.GameStateConnect4.GameState', 'GameState', (['start_board', '(1)'], {}), '(start_board, 1)\n', (672, 688), False, 'from Game.GameStateConnect4 import GameState\n'), ((1115, 1130), 'Agents.MCTS.MCTSTree', 'MCTSTree', (['state'], {}), '(state)\n', (1123, 1130), False, 'from Agents.MCTS import MCTSTree... |
import os
import subprocess
import tempfile
try:
from PyQt5.QtCore import QBuffer, QIODevice, Qt
from PyQt5.QtGui import QImage
except ImportError:
from PySide2.QtCore import QBuffer, QIODevice, Qt
from PySide2.QtGui import QImage
from .texture_format import TextureFormat
def imageToBytes(image):
... | [
"os.path.exists",
"tempfile.gettempdir",
"os.getpid",
"PySide2.QtCore.QBuffer",
"PySide2.QtGui.QImage",
"os.remove"
] | [((331, 340), 'PySide2.QtCore.QBuffer', 'QBuffer', ([], {}), '()\n', (338, 340), False, 'from PySide2.QtCore import QBuffer, QIODevice, Qt\n'), ((944, 969), 'os.path.exists', 'os.path.exists', (['temp_path'], {}), '(temp_path)\n', (958, 969), False, 'import os\n'), ((618, 630), 'PySide2.QtGui.QImage', 'QImage', (['path... |
##########################################################################
# PyPipe - Copyright (C) AGrigis, 2017
# Distributed under the terms of the CeCILL-B license, as published by
# the CEA-CNRS-INRIA. Refer to the LICENSE file or to
# http://www.cecill.info/licences/Licence_CeCILL-B_V1-en.html
# for details.
####... | [
"PySide2.QtGui.QFont",
"PySide2.QtWidgets.QTreeWidgetItem"
] | [((490, 526), 'PySide2.QtGui.QFont', 'QtGui.QFont', (['""""""', '(9)', 'QtGui.QFont.Bold'], {}), "('', 9, QtGui.QFont.Bold)\n", (501, 526), False, 'from PySide2 import QtGui\n'), ((2512, 2589), 'PySide2.QtWidgets.QTreeWidgetItem', 'QtWidgets.QTreeWidgetItem', (['parent_item', "[module_name, 'None', 'None', 'None']"], {... |
"""
Module implements simple ORM for SQLite.
Module excludes using many-to-many and one-to-many relationships.
Trying to save the same object (update) with another aggregated object
will rewrite old object!
"""
import os
import sqlite3
from array import array
from inspect import *
import builtins
import sys
import lo... | [
"logging.basicConfig",
"sqlite3.connect",
"os.path.getsize",
"logging.getLogger"
] | [((864, 937), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.DEBUG', 'filename': 'log_file', 'filemode': '"""a"""'}), "(level=logging.DEBUG, filename=log_file, filemode='a')\n", (883, 937), False, 'import logging\n'), ((983, 1015), 'logging.getLogger', 'logging.getLogger', (['"""main_logger"""'],... |
from setuptools import setup, find_packages
with open("README.md", "r") as fh:
long_description = fh.read()
setup(
name="algorithms",
version="0.1",
description="Implements a few optimisation algorithms",
long_description=long_description,
long_description_content_type="text/markdown",
ur... | [
"setuptools.find_packages"
] | [((379, 394), 'setuptools.find_packages', 'find_packages', ([], {}), '()\n', (392, 394), False, 'from setuptools import setup, find_packages\n')] |
import pandas as pd
import dimensionality_reduction_functions as dim_red
from plotting_functions import colored_line_plot, colored_line_and_scatter_plot, colored_line_plot_projected_data
# Number of PCA components
ndim = 3
####################################### EXAMPLE 4: CYCLOPROPYLIDENE BIFURCATION ###############... | [
"dimensionality_reduction_functions.pathreducer",
"dimensionality_reduction_functions.transform_new_data",
"plotting_functions.colored_line_and_scatter_plot",
"pandas.DataFrame",
"plotting_functions.colored_line_plot_projected_data"
] | [((882, 971), 'dimensionality_reduction_functions.pathreducer', 'dim_red.pathreducer', (['file', 'ndim'], {'stereo_atoms': 'stereo_atoms_B', 'input_type': '"""Distances"""'}), "(file, ndim, stereo_atoms=stereo_atoms_B, input_type=\n 'Distances')\n", (901, 971), True, 'import dimensionality_reduction_functions as dim... |
'''
This code compares the loc and iloc in pandas dataframe
'''
__author__ = "<NAME>"
__email__ = "<EMAIL>"
import pandas as pd
import timeit
df_test = pd.DataFrame()
tlist = []
tlist2 = []
################ this code creates a dataframe df_test ##################
###############with two columns and 5000000 entrie... | [
"pandas.DataFrame"
] | [((156, 170), 'pandas.DataFrame', 'pd.DataFrame', ([], {}), '()\n', (168, 170), True, 'import pandas as pd\n')] |
from functools import total_ordering
from random import shuffle
class Player:
def __init__(self, name):
self.name = name
self.hand = []
def __str__(self):
return self.name
def play(self):
return self.hand.pop()
def receive(self, cards):
for card in cards:
... | [
"random.shuffle"
] | [((1331, 1350), 'random.shuffle', 'shuffle', (['self.cards'], {}), '(self.cards)\n', (1338, 1350), False, 'from random import shuffle\n')] |
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
cz2 = (0.7, 0.7, 0.7)
cz = (0.3, 0.3, 0.3)
cy = (0.7, 0.4, 0.12)
ci = (0.1, 0.3, 0.5)
ct = (0.7, 0.2, 0.1)
ax = plt.figure(figsize=(5,4)).gca()
ax.xaxis.set_major_locator(MaxNLocator(integer=True))
ax.yaxis.grid(True)
ax.set_... | [
"matplotlib.pyplot.figure",
"matplotlib.ticker.MaxNLocator",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.legend"
] | [((1091, 1139), 'matplotlib.pyplot.legend', 'plt.legend', ([], {'handles': '[bt, cat, cet, mat, mmt, ht]'}), '(handles=[bt, cat, cet, mat, mmt, ht])\n', (1101, 1139), True, 'import matplotlib.pyplot as plt\n'), ((1153, 1191), 'matplotlib.pyplot.savefig', 'plt.savefig', (['"""curvetest.png"""'], {'dpi': '(1500)'}), "('c... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
DataWorkshop: application to handle data, e.g. generated from imageviewer
Author: <NAME>
Created: Sep. 23rd, 2015
"""
from ...utils import datautils
from ...utils import miscutils
from ...utils import funutils
from ...utils import resutils
import wx
import wx.lib.mix... | [
"wx.App"
] | [((1259, 1297), 'wx.App', 'wx.App', ([], {'redirect': 'logon', 'filename': '"""log"""'}), "(redirect=logon, filename='log')\n", (1265, 1297), False, 'import wx\n')] |
"""Authorization token handling."""
import logging
from functools import wraps
from flask import g, request
from requests import get
from pydantic.error_wrappers import ValidationError
from bayesian.utility.user_utils import get_user, UserException, UserNotFoundException
from bayesian.utility.v2.sa_models import Header... | [
"logging.getLogger",
"requests.get",
"functools.wraps",
"bayesian.utility.user_utils.get_user",
"bayesian.exceptions.HTTPError",
"flask.request.headers.get"
] | [((466, 493), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (483, 493), False, 'import logging\n'), ((757, 793), 'flask.request.headers.get', 'request.headers.get', (['"""Authorization"""'], {}), "('Authorization')\n", (776, 793), False, 'from flask import g, request\n'), ((1273, 1284), ... |
import time
from signal import pause
import logging
import RPi.GPIO as GPIO
GPIO.setmode(GPIO.BCM)
logger = logging.getLogger(__name__)
map_edge_parse = {'falling':GPIO.FALLING, 'rising':GPIO.RISING, 'both':GPIO.BOTH}
map_pull_parse = {'pull_up':GPIO.PUD_UP, 'pull_down':GPIO.PUD_DOWN, 'pull_off':GPIO.PUD_OFF}
map_edg... | [
"logging.getLogger",
"RPi.GPIO.add_event_detect",
"RPi.GPIO.setup",
"time.perf_counter",
"time.sleep",
"signal.pause",
"RPi.GPIO.remove_event_detect",
"RPi.GPIO.input",
"RPi.GPIO.setmode"
] | [((76, 98), 'RPi.GPIO.setmode', 'GPIO.setmode', (['GPIO.BCM'], {}), '(GPIO.BCM)\n', (88, 98), True, 'import RPi.GPIO as GPIO\n'), ((109, 136), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (126, 136), False, 'import logging\n'), ((1899, 1918), 'time.perf_counter', 'time.perf_counter', ([... |
from setuptools import setup
setup(name='gtkpass',
version='0.2.7',
description='A GTK+ 3 program for the standard unix password manager',
url='http://github.com/raghavsub/gtkpass',
author='<NAME>',
author_email='<EMAIL>',
license='MIT',
packages=['gtkpass'],
entry_point... | [
"setuptools.setup"
] | [((30, 366), 'setuptools.setup', 'setup', ([], {'name': '"""gtkpass"""', 'version': '"""0.2.7"""', 'description': '"""A GTK+ 3 program for the standard unix password manager"""', 'url': '"""http://github.com/raghavsub/gtkpass"""', 'author': '"""<NAME>"""', 'author_email': '"""<EMAIL>"""', 'license': '"""MIT"""', 'packa... |
import pytest
import time
from .utils import (
init_app, init_db, clean_db,
add_flow, add_run, add_step, add_task, add_artifact,
_test_list_resources, _test_single_resource, add_metadata, get_heartbeat_ts
)
pytestmark = [pytest.mark.integration_tests]
# Fixtures begin
@pytest.fixture
def cli(loop, aiohtt... | [
"time.time"
] | [((15496, 15507), 'time.time', 'time.time', ([], {}), '()\n', (15505, 15507), False, 'import time\n')] |
import torch
from torch.optim import lr_scheduler
from tqdm import tqdm
from torchsummary import summary
from torch.utils.tensorboard import SummaryWriter
from apex import amp
from loss import dice
from pathlib import Path
from data import CaseDataset, load_case, save_pred, \
orient_crop_case, regions_crop_case, re... | [
"apex.amp.scale_loss",
"torch.softmax",
"numpy.array",
"apex.amp.initialize",
"transform.crop_pad",
"torch.squeeze",
"transform.pad",
"numpy.arange",
"torch.isnan",
"torch.utils.tensorboard.SummaryWriter",
"apex.amp.load_state_dict",
"pathlib.Path",
"data.resample_normalize_case",
"numpy.t... | [((881, 903), 'transform.pad', 'pad', (['input', 'patch_size'], {}), '(input, patch_size)\n', (884, 903), False, 'from transform import pad, crop_pad, to_numpy, to_tensor, resize\n'), ((958, 998), 'numpy.array', 'np.array', (['[(i // 2) for i in patch_size]'], {}), '([(i // 2) for i in patch_size])\n', (966, 998), True... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jan 09 22:25:07 2019
@author: arnaudhub
"""
#import pandas as pd
from sqlalchemy import create_engine
from sqlalchemy.sql import text
import configparser,os
from urllib import parse
#import sql.connector
config = configparser.ConfigParser()
config.re... | [
"urllib.parse.quote_plus",
"configparser.ConfigParser",
"os.path.expanduser"
] | [((283, 310), 'configparser.ConfigParser', 'configparser.ConfigParser', ([], {}), '()\n', (308, 310), False, 'import configparser, os\n'), ((333, 375), 'os.path.expanduser', 'os.path.expanduser', (['"""~/Bureau/OBJDOMO.cnf"""'], {}), "('~/Bureau/OBJDOMO.cnf')\n", (351, 375), False, 'import configparser, os\n'), ((502, ... |
from multiml import logger
from multiml.task.pytorch import PytorchASNGNASTask
from multiml.task.pytorch import PytorchASNGNASBlockTask
from . import PytorchConnectionRandomSearchAgent
from multiml.task.pytorch.datasets import StoreGateDataset, NumpyDataset
import numpy as np
class PytorchASNGNASAgent(PytorchConnect... | [
"multiml.task.pytorch.PytorchASNGNASBlockTask",
"multiml.logger.info",
"multiml.task.pytorch.PytorchASNGNASTask"
] | [((2035, 2607), 'multiml.task.pytorch.PytorchASNGNASTask', 'PytorchASNGNASTask', ([], {'asng_args': 'self.asng_args', 'subtasks': 'asng_block_list', 'variable_mapping': "self._connectiontask_args['variable_mapping']", 'saver': 'self._saver', 'device': "self._connectiontask_args['device']", 'gpu_ids': 'None', 'amp': '(F... |
import os
import pytest
from petisco import FlaskApplication
SWAGGER_DIR = os.path.dirname(os.path.abspath(__file__)) + "/application/"
app = FlaskApplication(application_name="petisco", swagger_dir=SWAGGER_DIR).get_app()
@pytest.fixture
def client():
with app.app.test_client() as c:
yield c
@pytest... | [
"os.path.abspath",
"petisco.FlaskApplication"
] | [((95, 120), 'os.path.abspath', 'os.path.abspath', (['__file__'], {}), '(__file__)\n', (110, 120), False, 'import os\n'), ((146, 215), 'petisco.FlaskApplication', 'FlaskApplication', ([], {'application_name': '"""petisco"""', 'swagger_dir': 'SWAGGER_DIR'}), "(application_name='petisco', swagger_dir=SWAGGER_DIR)\n", (16... |
from sklearn.datasets import load_iris
from sklearn.linear_model import LogisticRegression
from flask import Blueprint, jsonify, request, flash, redirect, render_template
from web_app.models import User
from web_app.statsmodels import load_model
from web_app.services.basilica_service import connection as basilica_con... | [
"sklearn.datasets.load_iris",
"flask.render_template",
"web_app.statsmodels.load_model",
"sklearn.linear_model.LogisticRegression",
"web_app.models.User.query.filter",
"web_app.services.basilica_service.connection.embed_sentence",
"flask.Blueprint"
] | [((344, 379), 'flask.Blueprint', 'Blueprint', (['"""stats_routes"""', '__name__'], {}), "('stats_routes', __name__)\n", (353, 379), False, 'from flask import Blueprint, jsonify, request, flash, redirect, render_template\n'), ((439, 465), 'sklearn.datasets.load_iris', 'load_iris', ([], {'return_X_y': '(True)'}), '(retur... |
import argparse
import os
import pyprind
import utils
import treetk
import treetk.rstdt
def main(args):
"""
We use n-ary ctrees (ie., *.labeled.nary.ctree) to generate dtrees.
Morey et al. (2018) demonstrate that scores evaluated on these dtrees are superficially lower than those on right-heavy binarize... | [
"os.listdir",
"argparse.ArgumentParser",
"treetk.ctree2dtree",
"os.path.join",
"treetk.sexp2tree",
"treetk.rstdt.assign_heads",
"pyprind.prog_bar"
] | [((402, 418), 'os.listdir', 'os.listdir', (['path'], {}), '(path)\n', (412, 418), False, 'import os\n'), ((844, 871), 'pyprind.prog_bar', 'pyprind.prog_bar', (['filenames'], {}), '(filenames)\n', (860, 871), False, 'import pyprind\n'), ((1723, 1748), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n... |
from contextlib import closing
import h5py
import numpy as np
def save_h5(outfile, dictionary):
""" Saves passed dictionary to an h5 file
Parameters
----------
outfile : string
Name of output h5 file
dictionary : dictionary
Dictionary that will be saved
"""
def save_layer(... | [
"numpy.asarray",
"h5py.File"
] | [((1659, 1687), 'h5py.File', 'h5py.File', (['feature_file', '"""r"""'], {}), "(feature_file, 'r')\n", (1668, 1687), False, 'import h5py\n'), ((622, 645), 'h5py.File', 'h5py.File', (['outfile', '"""w"""'], {}), "(outfile, 'w')\n", (631, 645), False, 'import h5py\n'), ((1830, 1848), 'numpy.asarray', 'np.asarray', (['f[ke... |
# -*- coding: utf-8 -*-
""" Helper functions for VariationalModel class """
from __future__ import print_function
from __future__ import division
import math
import random
import tensorflow as tf
from tensorflow.contrib.legacy_seq2seq.python.ops import seq2seq as s2s
def linearOutcomePrediction(zs, pa... | [
"tensorflow.contrib.legacy_seq2seq.python.ops.seq2seq.core_rnn_cell.EmbeddingWrapper",
"tensorflow.sigmoid",
"tensorflow.matmul",
"tensorflow.contrib.legacy_seq2seq.python.ops.seq2seq.embedding_rnn_decoder",
"tensorflow.contrib.legacy_seq2seq.python.ops.seq2seq.rnn.static_rnn",
"tensorflow.contrib.legacy_... | [((648, 717), 'tensorflow.contrib.legacy_seq2seq.python.ops.seq2seq.variable_scope.variable_scope', 's2s.variable_scope.variable_scope', (["(scope or 'outcomepred')"], {'reuse': '(True)'}), "(scope or 'outcomepred', reuse=True)\n", (681, 717), True, 'from tensorflow.contrib.legacy_seq2seq.python.ops import seq2seq as s... |
"""empty message
Revision ID: b9ab1a9a2113
Revises:
Create Date: 2021-11-28 22:41:01.160642
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = 'b9ab1a9a2113'
down_revision = None
branch_labels = None
depends_on = None
def upgrade():
# ### commands auto gene... | [
"sqlalchemy.ForeignKeyConstraint",
"sqlalchemy.Float",
"alembic.op.drop_table",
"sqlalchemy.PrimaryKeyConstraint",
"sqlalchemy.Date",
"sqlalchemy.Integer",
"sqlalchemy.String"
] | [((1073, 1098), 'alembic.op.drop_table', 'op.drop_table', (['"""currates"""'], {}), "('currates')\n", (1086, 1098), False, 'from alembic import op\n'), ((1103, 1128), 'alembic.op.drop_table', 'op.drop_table', (['"""curpairs"""'], {}), "('curpairs')\n", (1116, 1128), False, 'from alembic import op\n'), ((575, 604), 'sql... |
import os
from pathlib import Path
import pandas as pd
from lime.lime_tabular import LimeTabularExplainer
from ml_editor.data_processing import get_split_by_author
FEATURE_DISPLAY_NAMES = {
"num_questions": "물음표 빈도",
"num_periods": "마침표 빈도",
"num_commas": "쉼표 빈도",
"num_exclam": "느낌표 빈도",
"num_quot... | [
"pandas.read_csv",
"pathlib.Path",
"lime.lime_tabular.LimeTabularExplainer",
"os.path.dirname",
"ml_editor.data_processing.get_split_by_author"
] | [((1881, 1922), 'pathlib.Path', 'Path', (['"""../data/writers_with_features.csv"""'], {}), "('../data/writers_with_features.csv')\n", (1885, 1922), False, 'from pathlib import Path\n'), ((1932, 1966), 'pandas.read_csv', 'pd.read_csv', (['(curr_path / data_path)'], {}), '(curr_path / data_path)\n', (1943, 1966), True, '... |
"""
Tests for the test utils.
"""
import pytest
from straitlets import Serializable, Integer
from straitlets.test_utils import assert_serializables_equal
def test_assert_serializables_equal():
class Foo(Serializable):
x = Integer()
y = Integer()
class Bar(Serializable):
x = Integer(... | [
"straitlets.Integer",
"pytest.raises"
] | [((238, 247), 'straitlets.Integer', 'Integer', ([], {}), '()\n', (245, 247), False, 'from straitlets import Serializable, Integer\n'), ((260, 269), 'straitlets.Integer', 'Integer', ([], {}), '()\n', (267, 269), False, 'from straitlets import Serializable, Integer\n'), ((312, 321), 'straitlets.Integer', 'Integer', ([], ... |
import numpy
from fdm.geometry import create_close_point_finder
def create_weights_distributor(close_point_finder):
def distribute(point, value):
close_points = close_point_finder(point)
distance_sum = sum(close_points.values())
return dict(
{p: (1. - distance/distance_sum)*va... | [
"fdm.geometry.create_close_point_finder",
"numpy.copy",
"numpy.zeros"
] | [((589, 607), 'numpy.copy', 'numpy.copy', (['matrix'], {}), '(matrix)\n', (599, 607), False, 'import numpy\n'), ((622, 640), 'numpy.copy', 'numpy.copy', (['vector'], {}), '(vector)\n', (632, 640), False, 'import numpy\n'), ((1565, 1585), 'numpy.copy', 'numpy.copy', (['matrix_a'], {}), '(matrix_a)\n', (1575, 1585), Fals... |
import unittest
from csound import output, orchestra
from csound.orchestra import gen08
from data import constants as c
from data import get
class TestSounds(unittest.TestCase):
def test_simple_soundwaves(self):
# Get all data
place = "Madrid"
mad2t = get(c.T, location=place)
ma... | [
"csound.orchestra.oscillator1",
"data.get",
"csound.orchestra.gen08",
"csound.output.get_csd"
] | [((285, 309), 'data.get', 'get', (['c.T'], {'location': 'place'}), '(c.T, location=place)\n', (288, 309), False, 'from data import get\n'), ((325, 349), 'data.get', 'get', (['c.P'], {'location': 'place'}), '(c.P, location=place)\n', (328, 349), False, 'from data import get\n'), ((365, 389), 'data.get', 'get', (['c.W'],... |
#!/usr/bin/env python
"""
Nicholas' Example API code for interacting with Alienvault API.
This is just Example code written by NMA.IO.
There isn't really much you can do with the API just yet, so
this will be a work in progress.
Grab your API key here:
https://www.alienvault.com/documentation/usm-anywhere/api/ali... | [
"base64.b64encode"
] | [((828, 873), 'base64.b64encode', 'base64.b64encode', (["('%s:%s' % (apiuser, apikey))"], {}), "('%s:%s' % (apiuser, apikey))\n", (844, 873), False, 'import base64\n')] |
from timebox.timebox import TimeBox
from timebox.utils.exceptions import InvalidPandasIndexError
import pandas as pd
import numpy as np
import unittest
import os
import logging
class TestTimeBoxPandas(unittest.TestCase):
def test_save_pandas(self):
file_name = 'save_pandas.npb'
df = pd.read_csv('t... | [
"os.path.exists",
"pandas.read_csv",
"timebox.timebox.TimeBox.save_pandas",
"timebox.timebox.TimeBox",
"numpy.array",
"unittest.main",
"pandas.to_datetime",
"os.remove"
] | [((2124, 2139), 'unittest.main', 'unittest.main', ([], {}), '()\n', (2137, 2139), False, 'import unittest\n'), ((306, 377), 'pandas.read_csv', 'pd.read_csv', (['"""timebox/tests/data/ETH-USD_combined_utc.csv"""'], {'index_col': '(0)'}), "('timebox/tests/data/ETH-USD_combined_utc.csv', index_col=0)\n", (317, 377), True,... |
from typing import Any
from flaskapp.models import Activities, Logs, LogsToActivities, db
from sqlalchemy.sql.expression import desc, func
"""
Este modulo contiene funciones para escribir y leer los logs desde el chatbot
"""
MAX_LOGS_PER_QUERY = 5
MAX_STR_SIZE_LOGS = 128
def write_log(
chatid: int,
intent: ... | [
"flaskapp.models.Activities.query.filter_by",
"flaskapp.models.LogsToActivities",
"flaskapp.models.db.session.commit",
"sqlalchemy.sql.expression.desc",
"flaskapp.models.Activities",
"flaskapp.models.Logs",
"sqlalchemy.sql.expression.func.max"
] | [((1232, 1251), 'flaskapp.models.db.session.commit', 'db.session.commit', ([], {}), '()\n', (1249, 1251), False, 'from flaskapp.models import Activities, Logs, LogsToActivities, db\n'), ((1843, 1862), 'flaskapp.models.db.session.commit', 'db.session.commit', ([], {}), '()\n', (1860, 1862), False, 'from flaskapp.models ... |
""" Luhn Algorithm """
from typing import List
def is_luhn(string: str) -> bool:
"""
Perform Luhn validation on input string
Algorithm:
* Double every other digit starting from 2nd last digit.
* Subtract 9 if number is greater than 9.
* Sum the numbers
*
>>> test_cases = [79927398710, ... | [
"doctest.testmod"
] | [((1181, 1198), 'doctest.testmod', 'doctest.testmod', ([], {}), '()\n', (1196, 1198), False, 'import doctest\n')] |
"""
==================
welly
==================
"""
from .project import Project
from .well import Well
from .header import Header
from .curve import Curve
from .synthetic import Synthetic
from .location import Location
from .crs import CRS
from . import tools
from . import quality
def read_las(path, **kwargs):
"... | [
"pkg_resources.get_distribution"
] | [((1709, 1735), 'pkg_resources.get_distribution', 'get_distribution', (['__name__'], {}), '(__name__)\n', (1725, 1735), False, 'from pkg_resources import get_distribution, DistributionNotFound\n')] |
#!/usr/bin/env python3
"""
Build the demos
Usage: python setup.py build_ext -i
"""
import numpy as np
from distutils.core import setup
from Cython.Build import cythonize
from setuptools.extension import Extension
from os.path import join
extending = Extension("extending",
sources=['extending.py... | [
"Cython.Build.cythonize",
"os.path.join",
"numpy.get_include"
] | [((760, 781), 'Cython.Build.cythonize', 'cythonize', (['extensions'], {}), '(extensions)\n', (769, 781), False, 'from Cython.Build import cythonize\n'), ((361, 377), 'numpy.get_include', 'np.get_include', ([], {}), '()\n', (375, 377), True, 'import numpy as np\n'), ((534, 593), 'os.path.join', 'join', (['""".."""', '""... |
#!/usr/bin/env python
# encoding: utf-8
import signal
import sys
#import pandas as pd
#import numpy as np
def setGlobals(g):
#print globals()
globals().update(g)
#print globals()
def exit():
mtsExit(0)
def quit(signum):
sys.exit(signum)
def quitNow(signum,frame):
quit(signum)
def initializ... | [
"signal.signal",
"sys.exit"
] | [((244, 260), 'sys.exit', 'sys.exit', (['signum'], {}), '(signum)\n', (252, 260), False, 'import sys\n'), ((343, 380), 'signal.signal', 'signal.signal', (['signal.SIGINT', 'quitNow'], {}), '(signal.SIGINT, quitNow)\n', (356, 380), False, 'import signal\n'), ((385, 423), 'signal.signal', 'signal.signal', (['signal.SIGTE... |
from enum import Enum
import json
from SCA11H.commands.base.PostCommand import PostCommand
class Command(Enum):
# Restore BCG factory settings.(BCG parameters, direction and running mode)
Restore = ('restore', 'restore')
# Restore default BCG parameters
SetDefaultParameters = ('set_default_pars', 'r... | [
"json.dumps"
] | [((533, 570), 'json.dumps', 'json.dumps', (["{'cmd': command.value[0]}"], {}), "({'cmd': command.value[0]})\n", (543, 570), False, 'import json\n')] |
#!/usr/bin/env python3
import pandas as pd
ft_input='TEMP_DIR/tmp-predictions_reformatted_gexpnn20200320allCOHORTS.tsv'
df = pd.read_csv(ft_input,sep='\t')
# Get all tumors present in df (ACC, BRCA, ...)
temp = df['Label'].unique()
u_tumor = {} #k=tumor, v=1
for t in temp:
t= t.split(":")[0]
if t not in u_t... | [
"pandas.read_csv"
] | [((128, 159), 'pandas.read_csv', 'pd.read_csv', (['ft_input'], {'sep': '"""\t"""'}), "(ft_input, sep='\\t')\n", (139, 159), True, 'import pandas as pd\n')] |