code stringlengths 22 1.05M | apis listlengths 1 3.31k | extract_api stringlengths 75 3.25M |
|---|---|---|
"""
This module implements methods for generating random attributes from nodes in a graph based on distribution and range.
Method generate() will create all the necessary attributes for the graph:
Collection: name.
Dataset collection: name.
System collection: name.
System: system criticality, environme... | [
"random.choices",
"random.randint"
] | [((3899, 3943), 'random.choices', 'random.choices', (['population', 'probability'], {'k': 'n'}), '(population, probability, k=n)\n', (3913, 3943), False, 'import random\n'), ((3371, 3443), 'random.randint', 'random.randint', (['time_ranges[time_metric][0]', 'time_ranges[time_metric][1]'], {}), '(time_ranges[time_metric... |
"""
Provide quantilized form of Adder2d, https://arxiv.org/pdf/1912.13200.pdf
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Function
import math
from . import extra as ex
from .number import qsigned
class Adder2d(ex.Adder2d):
def __init__(self,
... | [
"torch.Tensor",
"torch.rand"
] | [((3422, 3447), 'torch.rand', 'torch.rand', (['(10)', '(3)', '(10)', '(10)'], {}), '(10, 3, 10, 10)\n', (3432, 3447), False, 'import torch\n'), ((1474, 1489), 'torch.Tensor', 'torch.Tensor', (['(1)'], {}), '(1)\n', (1486, 1489), False, 'import torch\n'), ((1521, 1536), 'torch.Tensor', 'torch.Tensor', (['(1)'], {}), '(1... |
import sys
import asyncio
import uvloop
asyncio.set_event_loop_policy(uvloop.EventLoopPolicy())
from aiohttp import web
from aiohttp_session import get_session, setup
from aiohttp_session.cookie_storage import EncryptedCookieStorage
import aiohttp_jinja2
import jinja2
import user
import search
#import personal
impo... | [
"asyncio.get_event_loop",
"asyncio.sleep",
"ssl.create_default_context",
"jinja2.FileSystemLoader",
"uvloop.EventLoopPolicy",
"aiohttp.web.run_app",
"aiohttp_session.cookie_storage.EncryptedCookieStorage",
"util.routes.static",
"aiohttp.web.Application"
] | [((2034, 2113), 'aiohttp.web.run_app', 'web.run_app', (['app'], {'ssl_context': 'ssl_context', 'host': 'secrets.HOST', 'port': 'secrets.PORT'}), '(app, ssl_context=ssl_context, host=secrets.HOST, port=secrets.PORT)\n', (2045, 2113), False, 'from aiohttp import web\n'), ((70, 94), 'uvloop.EventLoopPolicy', 'uvloop.Event... |
import logging
from airflow.models import BaseOperator
from airflow.operators.sensors import BaseSensorOperator
from airflow.plugins_manager import AirflowPlugin
from airflow.utils.decorators import apply_defaults
log = logging.getLogger(__name__)
#Test comment
class CustomOperator(BaseOperator):
@apply_defaults... | [
"logging.getLogger"
] | [((222, 249), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (239, 249), False, 'import logging\n')] |
from django.urls import path
from raids import views
urlpatterns = [
path('encounter', views.encounter, name='raids_encounter'),
path('dispatch', views.dispatch_loot_system, name='raids_dispatch'),
path('search', views.search, name='raids_search'),
# Ajax
path('ajax/autocomplete', views.ajax_autoc... | [
"django.urls.path"
] | [((74, 132), 'django.urls.path', 'path', (['"""encounter"""', 'views.encounter'], {'name': '"""raids_encounter"""'}), "('encounter', views.encounter, name='raids_encounter')\n", (78, 132), False, 'from django.urls import path\n'), ((138, 205), 'django.urls.path', 'path', (['"""dispatch"""', 'views.dispatch_loot_system'... |
""" Module to handle attributes related to the site location and details """
import re
import logging
from osg_configure.modules import utilities
from osg_configure.modules import configfile
from osg_configure.modules import validation
from osg_configure.modules.baseconfiguration import BaseConfiguration
__all__ = [... | [
"re.split",
"osg_configure.modules.validation.valid_domain",
"osg_configure.modules.utilities.blank",
"osg_configure.modules.validation.valid_email",
"logging.getLogger",
"osg_configure.modules.utilities.get_vos",
"osg_configure.modules.configfile.Option",
"osg_configure.modules.baseconfiguration.Base... | [((931, 958), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (948, 958), False, 'import logging\n'), ((8680, 8703), 'osg_configure.modules.utilities.get_vos', 'utilities.get_vos', (['None'], {}), '(None)\n', (8697, 8703), False, 'from osg_configure.modules import utilities\n'), ((9079, 91... |
import datetime
from typing import Dict, Optional
import dateparser
import regex
def get_element_text(el) -> str:
return ''.join(el.strings).strip()
def parse_int(
s: str, numbers_map: Dict[str, int], thousands_separator: str
) -> int:
m = regex.search(r'\d+', s.strip().replace(thousands_separator, '')... | [
"dateparser.parse"
] | [((832, 851), 'dateparser.parse', 'dateparser.parse', (['s'], {}), '(s)\n', (848, 851), False, 'import dateparser\n')] |
# Generated by Django 3.2.7 on 2022-03-07 15:25
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('blog', '0006_change_content_field_to_richtextuploading'),
]
operations = [
migrations.AddField(
model_name='post',
n... | [
"django.db.models.CharField"
] | [((353, 408), 'django.db.models.CharField', 'models.CharField', ([], {'blank': '(True)', 'max_length': '(500)', 'null': '(True)'}), '(blank=True, max_length=500, null=True)\n', (369, 408), False, 'from django.db import migrations, models\n')] |
import threading
import time
from django_formset_vuejs.models import Book
def start_cleanup_job():
def cleanup_db():
while True:
time.sleep(60*60)
print('hello')
Book.objects.all().delete()
thread1 = threading.Thread(target=cleanup_db)
thread1.start()
| [
"threading.Thread",
"django_formset_vuejs.models.Book.objects.all",
"time.sleep"
] | [((256, 291), 'threading.Thread', 'threading.Thread', ([], {'target': 'cleanup_db'}), '(target=cleanup_db)\n', (272, 291), False, 'import threading\n'), ((156, 175), 'time.sleep', 'time.sleep', (['(60 * 60)'], {}), '(60 * 60)\n', (166, 175), False, 'import time\n'), ((213, 231), 'django_formset_vuejs.models.Book.object... |
#-----------------------------------------------------------------------------
# luna2d DeployTool
# This is part of luna2d engine
# Copyright 2014-2017 <NAME>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to
# de... | [
"utils.get_luna2d_path",
"argparse.ArgumentParser",
"utils.make_from_template",
"os.path.exists",
"sdkmodule_android.get_ignored_files",
"sdkmodule_android.apply_constants",
"shutil.rmtree"
] | [((1648, 1671), 'utils.get_luna2d_path', 'utils.get_luna2d_path', ([], {}), '()\n', (1669, 1671), False, 'import utils\n'), ((2129, 2217), 'utils.make_from_template', 'utils.make_from_template', (['template_path', 'args.project_path', 'constants', 'ignored_files'], {}), '(template_path, args.project_path, constants,\n ... |
def process(self):
self.edit("LATIN")
self.replace("CAPITAL LETTER D WITH SMALL LETTER Z", "Dz")
self.replace("CAPITAL LETTER DZ", "DZ")
self.edit("AFRICAN", "african")
self.edit("WITH LONG RIGHT LEG", "long", "right", "leg")
self.edit('LETTER YR', "yr")
self.edit("CAPITAL LETTER O WITH... | [
"glyphNameFormatter.exporters.printRange"
] | [((1598, 1628), 'glyphNameFormatter.exporters.printRange', 'printRange', (['"""Latin Extended-B"""'], {}), "('Latin Extended-B')\n", (1608, 1628), False, 'from glyphNameFormatter.exporters import printRange\n')] |
import os
from PlotterBokeh import PlotterBokeh
from BusInfo import BusInfo
def start_live_streaming(doc):
if doc is None:
raise NotImplementedError()
# Set the initial location as Yokohama station
lat=35.46591430126525
lng=139.62125644093177
apiKey = os.getenv('GMAP_TOKEN')
plotter ... | [
"BusInfo.BusInfo.update",
"PlotterBokeh.PlotterBokeh",
"os.getenv"
] | [((283, 306), 'os.getenv', 'os.getenv', (['"""GMAP_TOKEN"""'], {}), "('GMAP_TOKEN')\n", (292, 306), False, 'import os\n'), ((322, 357), 'PlotterBokeh.PlotterBokeh', 'PlotterBokeh', (['lat', 'lng', 'apiKey', 'doc'], {}), '(lat, lng, apiKey, doc)\n', (334, 357), False, 'from PlotterBokeh import PlotterBokeh\n'), ((373, 3... |
import torch as th
import torch.nn as nn
import torch.nn.functional as F
from typing import Dict, List, Optional, Tuple
from tpp.models.encoders.base.variable_history import VariableHistoryEncoder
from tpp.pytorch.models import MLP
from tpp.utils.events import Events
class RecurrentEncoder(VariableHistoryEncoder):
... | [
"torch.nn.functional.normalize",
"tpp.pytorch.models.MLP"
] | [((2288, 2471), 'tpp.pytorch.models.MLP', 'MLP', ([], {'units': 'units_mlp', 'activations': 'activation_mlp', 'constraint': 'constraint_mlp', 'dropout_rates': 'dropout_mlp', 'input_shape': 'self.rnn.hidden_size', 'activation_final': 'activation_final_mlp'}), '(units=units_mlp, activations=activation_mlp, constraint=con... |
import os
import glob
import numpy as np
from datetime import datetime
from scipy.io import loadmat
from PIL import Image
np.random.seed(42)
def calc_age(taken, dob):
birth = datetime.fromordinal(max(int(dob) - 366, 1))
# assume the photo was taken in the middle of the year
if birth.month < 7:
... | [
"numpy.random.seed",
"os.path.basename",
"scipy.io.loadmat",
"numpy.asarray",
"numpy.isnan",
"os.path.join",
"numpy.random.shuffle"
] | [((124, 142), 'numpy.random.seed', 'np.random.seed', (['(42)'], {}), '(42)\n', (138, 142), True, 'import numpy as np\n'), ((435, 452), 'scipy.io.loadmat', 'loadmat', (['mat_path'], {}), '(mat_path)\n', (442, 452), False, 'from scipy.io import loadmat\n'), ((2190, 2216), 'numpy.random.shuffle', 'np.random.shuffle', (['i... |
from simulation.dm_control_cur.utility_classes.simulator import Simulation
class ResidualSimulation(Simulation):
def __init__(
self,
controller_load_model=True,
controller_num_episodes=50,
**kwargs
):
super().__init__(**kwargs)
self.controller = ... | [
"simulation.dm_control_cur.utility_classes.simulator.Simulation"
] | [((320, 527), 'simulation.dm_control_cur.utility_classes.simulator.Simulation', 'Simulation', ([], {'load_model': 'controller_load_model', 'label': '"""controller"""', 'name_model': 'self.NAME_MODEL', 'task': 'self.TASK', 'num_episodes': 'controller_num_episodes', 'batch_size': 'self.BATCH_SIZE', 'duration': 'self.DURA... |
"""
Copyright 2020 <NAME>. See LICENSE for details.
"""
import logging
import time
import farc
from . import phy_sx127x
class PhySX127xAhsm(farc.Ahsm):
"""The physical layer (PHY) state machine for a Semtech SX127x device.
Automates the behavior of the Semtech SX127x family of radio transceivers.
For... | [
"farc.Signal.register",
"farc.Framework._event_loop.time",
"logging.debug",
"logging.warning",
"farc.Event",
"time.sleep",
"logging.info",
"farc.TimeEvent"
] | [((3581, 3612), 'farc.Signal.register', 'farc.Signal.register', (['"""_ALWAYS"""'], {}), "('_ALWAYS')\n", (3601, 3612), False, 'import farc\n'), ((3621, 3654), 'farc.Signal.register', 'farc.Signal.register', (['"""_PHY_RQST"""'], {}), "('_PHY_RQST')\n", (3641, 3654), False, 'import farc\n'), ((4451, 4488), 'farc.Event'... |
from common.http_response import json_response_builder as response
from common.jwt import get_user_id as get_id_from_request
from common.jwt import auth_require
from common.project_const import const
from icde.capture import icde_capture
from . import access as icde_access
@auth_require
@icde_capture(const.PAPER_SH... | [
"common.jwt.get_user_id",
"icde.capture.icde_capture",
"common.http_response.json_response_builder"
] | [((293, 324), 'icde.capture.icde_capture', 'icde_capture', (['const.PAPER_SHARE'], {}), '(const.PAPER_SHARE)\n', (305, 324), False, 'from icde.capture import icde_capture\n'), ((376, 408), 'icde.capture.icde_capture', 'icde_capture', (['const.PAPER_SEARCH'], {}), '(const.PAPER_SEARCH)\n', (388, 408), False, 'from icde.... |
from trial_of_the_stones.models.page_model import PageModel
import selenium
import unittest
import time
def trial_of_the_stones_automation():
'''
Source web page: https://techstepacademy.com/trial-of-the-stones
:return:
'''
# open web page
page = PageModel(selenium.webdriver.Chrome())
pag... | [
"unittest.TestCase",
"selenium.webdriver.Chrome",
"time.sleep"
] | [((504, 517), 'time.sleep', 'time.sleep', (['(2)'], {}), '(2)\n', (514, 517), False, 'import time\n'), ((284, 311), 'selenium.webdriver.Chrome', 'selenium.webdriver.Chrome', ([], {}), '()\n', (309, 311), False, 'import selenium\n'), ((669, 688), 'unittest.TestCase', 'unittest.TestCase', ([], {}), '()\n', (686, 688), Fa... |
from random import randint
"""
For an array of size 10^6 the execution time of the randomized version was 10x faster.
I used an already sorted array, which is an example of a worst case scenario.
The algorithm by selection always the smallest element as the pivot makes n recursive calls
and because the partition step ... | [
"random.randint"
] | [((909, 929), 'random.randint', 'randint', (['left', 'right'], {}), '(left, right)\n', (916, 929), False, 'from random import randint\n')] |
# -*- coding: utf-8 -*-
"""BioImagePy dataset metadata definitions.
This module contains classes that allows to describe the
metadata of scientific dataset
Classes
-------
DataSet
RawDataSet
ProcessedDataSet
"""
import re
from bioimageit_core.config import ConfigAccess
from bioimageit_core.data import RawData, Pro... | [
"bioimageit_core.metadata.query.query_list_single",
"re.split",
"bioimageit_core.data.ProcessedData",
"bioimageit_core.data.RawData",
"bioimageit_core.metadata.factory.metadataServices.get",
"bioimageit_core.config.ConfigAccess.instance"
] | [((1010, 1059), 'bioimageit_core.metadata.factory.metadataServices.get', 'metadataServices.get', (["config['service']"], {}), "(config['service'], **config)\n", (1030, 1059), False, 'from bioimageit_core.metadata.factory import metadataServices\n'), ((2004, 2034), 'bioimageit_core.data.RawData', 'RawData', (['self.meta... |
from flask import send_from_directory
from appserver import app
@app.server.route('/static/<path>')
def serve_static(path):
return send_from_directory('assets', path) | [
"flask.send_from_directory",
"appserver.app.server.route"
] | [((68, 102), 'appserver.app.server.route', 'app.server.route', (['"""/static/<path>"""'], {}), "('/static/<path>')\n", (84, 102), False, 'from appserver import app\n'), ((138, 173), 'flask.send_from_directory', 'send_from_directory', (['"""assets"""', 'path'], {}), "('assets', path)\n", (157, 173), False, 'from flask i... |
from django.utils.translation import ugettext_lazy as _
MESSAGES = {
'VacancyChange': _('Vacancy status change now pending...') + ' <span data-uk-spinner="ratio: 0.5"></span>',
'Not_VacancyChange':
'<span class="red-text" data-uk-icon="ban"></span> To add new pipeline action you have to disab... | [
"django.utils.translation.ugettext_lazy"
] | [((91, 132), 'django.utils.translation.ugettext_lazy', '_', (['"""Vacancy status change now pending..."""'], {}), "('Vacancy status change now pending...')\n", (92, 132), True, 'from django.utils.translation import ugettext_lazy as _\n'), ((355, 388), 'django.utils.translation.ugettext_lazy', '_', (['"""Action delete n... |
import io
from typing import Optional
import boto3
import botocore
from adventure_anywhere.definitions import SavesGateway
s3 = boto3.resource("s3")
class S3BucketSavesGateway(SavesGateway):
bucket_name: str
def __init__(self, bucket_name: str) -> None:
self.bucket_name = bucket_name
def fetc... | [
"boto3.resource"
] | [((131, 151), 'boto3.resource', 'boto3.resource', (['"""s3"""'], {}), "('s3')\n", (145, 151), False, 'import boto3\n')] |
import numpy as np
from fym.core import BaseEnv, BaseSystem
from fym.utils import rot
def hat(v):
v1, v2, v3 = v.squeeze()
return np.array([
[0, -v3, v2],
[v3, 0, -v1],
[-v2, v1, 0]
])
class Quadrotor(BaseEnv):
"""
Prof. <NAME>'s model for quadrotor UAV is used.
- ht... | [
"numpy.eye",
"fym.core.BaseSystem",
"numpy.ravel",
"numpy.zeros",
"fym.utils.rot.dcm2angle",
"numpy.array",
"numpy.linalg.inv",
"numpy.diag",
"numpy.linalg.pinv",
"numpy.vstack"
] | [((141, 193), 'numpy.array', 'np.array', (['[[0, -v3, v2], [v3, 0, -v1], [-v2, v1, 0]]'], {}), '([[0, -v3, v2], [v3, 0, -v1], [-v2, v1, 0]])\n', (149, 193), True, 'import numpy as np\n'), ((897, 917), 'numpy.vstack', 'np.vstack', (['(0, 0, 1)'], {}), '((0, 0, 1))\n', (906, 917), True, 'import numpy as np\n'), ((926, 95... |
import os
import sys
import logging
import json
import requests
import datetime
from msal import ConfidentialClientApplication
# Reusable function to create a logging mechanism
def create_logger(logfile=None):
# Create a logging handler that will write to stdout and optionally to a log file
stdout_handler = l... | [
"logging.error",
"logging.FileHandler",
"logging.basicConfig",
"json.loads",
"datetime.datetime.today",
"logging.StreamHandler",
"json.dumps",
"logging.info",
"requests.get",
"datetime.datetime.now",
"os.getenv"
] | [((319, 352), 'logging.StreamHandler', 'logging.StreamHandler', (['sys.stdout'], {}), '(sys.stdout)\n', (340, 352), False, 'import logging\n'), ((729, 855), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.INFO', 'format': '"""%(asctime)s - %(name)s - %(levelname)s - %(message)s"""', 'handlers': 'h... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import time
import math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.optim as optim
import torch.utils.data
from torch.utils.data import DataLoader
import torchvision.transforms as transfor... | [
"numpy.mean",
"torch.no_grad",
"data_load_mix.get_dataset_deform",
"torch.utils.data.DataLoader",
"os.path.exists",
"torch.optim.lr_scheduler.CosineAnnealingLR",
"math.log10",
"skimage.measure.compare_ssim",
"utils.count_parameters_in_MB",
"csv.writer",
"torch.manual_seed",
"torch.autograd.Var... | [((2975, 2998), 'torch.manual_seed', 'torch.manual_seed', (['(2018)'], {}), '(2018)\n', (2992, 2998), False, 'import torch\n'), ((3007, 3035), 'torch.cuda.manual_seed', 'torch.cuda.manual_seed', (['(2018)'], {}), '(2018)\n', (3029, 3035), False, 'import torch\n'), ((3144, 3155), 'torch.nn.L1Loss', 'nn.L1Loss', ([], {})... |
import random
import numpy as np
import matplotlib.pyplot as plt
import copy
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib import colors
##
counting = [0 for i in range(12)]
counting_temp = [0 for i in range(12)]
def refresh_counting(num):
global counting
counting[num] += 1... | [
"random.shuffle",
"copy.deepcopy",
"random.choice"
] | [((771, 794), 'copy.deepcopy', 'copy.deepcopy', (['counting'], {}), '(counting)\n', (784, 794), False, 'import copy\n'), ((2251, 2281), 'random.shuffle', 'random.shuffle', (['self.card_deck'], {}), '(self.card_deck)\n', (2265, 2281), False, 'import random\n'), ((3487, 3512), 'random.choice', 'random.choice', (['self.ha... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = "<NAME>"
'''
async web application
'''
import logging;logging.basicConfig(level=logging.INFO)
import asyncio,os,json,time
from datetime import datetime
from aiohttp import web
from jinja2 import Environment,FileSystemLoader
from config import configs
impo... | [
"os.path.abspath",
"aiohttp.web.Response",
"asyncio.get_event_loop",
"handlers.cookie2user",
"logging.basicConfig",
"coreweb.add_static",
"coreweb.add_routes",
"aiohttp.web.HTTPFound",
"time.time",
"json.dumps",
"logging.info",
"jinja2.FileSystemLoader",
"datetime.datetime.fromtimestamp",
... | [((117, 156), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.INFO'}), '(level=logging.INFO)\n', (136, 156), False, 'import logging\n'), ((4654, 4678), 'asyncio.get_event_loop', 'asyncio.get_event_loop', ([], {}), '()\n', (4676, 4678), False, 'import asyncio, os, json, time\n'), ((444, 474), 'logg... |
#!/usr/bin/python
#!/usr/bin/python3
import sys
import subprocess
import struct
with open(sys.argv[1], "rb") as f:
while True:
word = f.read(8)
if len(word) == 8:
print("%016x" % struct.unpack('Q', word));
elif len(word) == 4:
print("00000000... | [
"struct.unpack"
] | [((229, 253), 'struct.unpack', 'struct.unpack', (['"""Q"""', 'word'], {}), "('Q', word)\n", (242, 253), False, 'import struct\n'), ((328, 352), 'struct.unpack', 'struct.unpack', (['"""I"""', 'word'], {}), "('I', word)\n", (341, 352), False, 'import struct\n')] |
from config import db, ma
class Folder(db.Model):
__tablename__ = "folder"
__table_args__ = {"schema": "eagle_db"}
id = db.Column(db.Integer, primary_key=True)
parentFolderId = db.Column(db.String(45))
folderId = db.Column(db.String(45))
folderName = db.Column(db.String(100))
sta... | [
"config.db.String",
"config.db.Column"
] | [((140, 179), 'config.db.Column', 'db.Column', (['db.Integer'], {'primary_key': '(True)'}), '(db.Integer, primary_key=True)\n', (149, 179), False, 'from config import db, ma\n'), ((212, 225), 'config.db.String', 'db.String', (['(45)'], {}), '(45)\n', (221, 225), False, 'from config import db, ma\n'), ((253, 266), 'conf... |
import sqlite3
# import win32api
banco = sqlite3.connect('pixClientes.db')
cursor = banco.cursor()
cursor.execute('''
CREATE TABLE IF NOT EXISTS registros (
data_pagamento_pix DATE,
valor_pix NUMERIC (10,2)
);''')
#criando a função que insere um pix
def inserirPix... | [
"sqlite3.connect"
] | [((50, 83), 'sqlite3.connect', 'sqlite3.connect', (['"""pixClientes.db"""'], {}), "('pixClientes.db')\n", (65, 83), False, 'import sqlite3\n')] |
'''
File: attention_cell_sequence.py
Project: component
File Created: Friday, 28th December 2018 6:05:05 pm
Author: xiaofeng (<EMAIL>)
-----
Last Modified: Friday, 28th December 2018 6:50:40 pm
Modified By: xiaofeng (<EMAIL>>)
-----
Copyright 2018.06 - 2018 onion Math, onion Math
'''
import collections
import numpy a... | [
"tensorflow.reduce_sum",
"tensorflow.identity",
"tensorflow.get_variable_scope",
"tensorflow.reshape",
"tensorflow.matmul",
"tensorflow.get_variable",
"tensorflow.nn.softmax",
"tensorflow.concat",
"tensorflow.variable_scope",
"tensorflow.orthogonal_initializer",
"tensorflow.control_dependencies"... | [((503, 569), 'collections.namedtuple', 'collections.namedtuple', (['"""AttentionState"""', "('cell_state', 'output')"], {}), "('AttentionState', ('cell_state', 'output'))\n", (525, 569), False, 'import collections\n'), ((2033, 2136), 'tensorflow.layers.dense', 'tf.layers.dense', ([], {'inputs': 'self._encoder_sequence... |
import matplotlib.pyplot as plt
def add_cuts(ax, cuts, N):
if cuts[-1] != N:
cuts.append(N)
print(len(cuts))
c_last = 0
for c in cuts:
color = 'k'
ax.plot([c, c], [c, c_last], color)
ax.plot([c, c_last], [c, c], color)
ax.plot([c, c_last], [c_last, c_last], colo... | [
"networkx.Graph",
"matplotlib.pyplot.subplots",
"networkx.draw",
"matplotlib.pyplot.show"
] | [((472, 500), 'matplotlib.pyplot.subplots', 'plt.subplots', ([], {'figsize': '(4, 4)'}), '(figsize=(4, 4))\n', (484, 500), True, 'import matplotlib.pyplot as plt\n'), ((750, 760), 'matplotlib.pyplot.show', 'plt.show', ([], {}), '()\n', (758, 760), True, 'import matplotlib.pyplot as plt\n'), ((833, 861), 'matplotlib.pyp... |
#! -*- encoding:utf-8 -*-
"""
@File : run_dapt_task.py
@Author : <NAME>
@Contact : <EMAIL>
@Dscpt :
"""
import argparse
import logging
import os
import time
from pprint import pprint
from transformers import AlbertTokenizer, BertTokenizer
from dapt_task.data import *
from dapt_task.controller import... | [
"argparse.ArgumentParser",
"logging.basicConfig",
"dapt_task.controller.DomainAdaptivePreTrain",
"transformers.AlbertTokenizer.from_pretrained",
"os.path.basename",
"logging.StreamHandler",
"time.strftime",
"time.time",
"logging.Formatter",
"utils.common.result_dump",
"utils.common.mkdir_if_note... | [((486, 515), 'logging.getLogger', 'logging.getLogger', (['"""run_task"""'], {}), "('run_task')\n", (503, 515), False, 'import logging\n'), ((526, 549), 'logging.StreamHandler', 'logging.StreamHandler', ([], {}), '()\n', (547, 549), False, 'import logging\n'), ((593, 679), 'logging.Formatter', 'logging.Formatter', (['"... |
"""
Script goal,
Open land cover data and build a simple cover map
"""
#==============================================================================
__title__ = "LandCover"
__author__ = "<NAME>"
__version__ = "v1.0(12.03.2021)"
__email__ = "<EMAIL>"
#=================================================... | [
"pandas.Timestamp",
"matplotlib.pyplot.show",
"scipy.stats.mode",
"os.getcwd",
"pandas.read_csv",
"xarray.open_rasterio",
"cartopy.feature.GSHHSFeature",
"cartopy.crs.PlateCarree",
"xarray.open_dataset",
"dask.diagnostics.ProgressBar",
"xarray.Dataset",
"os.path.isfile",
"numpy.mean",
"pan... | [((705, 716), 'os.getcwd', 'os.getcwd', ([], {}), '()\n', (714, 716), False, 'import os\n'), ((9710, 9757), 'scipy.stats.mode', 'sp.stats.mode', (['da'], {'axis': 'None', 'nan_policy': '"""omit"""'}), "(da, axis=None, nan_policy='omit')\n", (9723, 9757), True, 'import scipy as sp\n'), ((9855, 9876), 'numpy.mean', 'np.m... |
import pygame
import anime
import random
pygame.init()
screen = pygame.display.set_mode((800, 600))
squares = []
entrance = {
'x' : -50,
'y' : 300
}
exit = {
'x' : 850,
'y' : 300
}
episode = anime.Episode(entrance, exit)
playing = True
while playing:
mx, my = pygame.mouse.get_pos()
for e in p... | [
"pygame.quit",
"anime.filter.Spring",
"pygame.Surface",
"random.randint",
"pygame.event.get",
"pygame.display.set_mode",
"pygame.init",
"pygame.display.flip",
"pygame.time.wait",
"pygame.mouse.get_pos",
"anime.Episode"
] | [((42, 55), 'pygame.init', 'pygame.init', ([], {}), '()\n', (53, 55), False, 'import pygame\n'), ((66, 101), 'pygame.display.set_mode', 'pygame.display.set_mode', (['(800, 600)'], {}), '((800, 600))\n', (89, 101), False, 'import pygame\n'), ((209, 238), 'anime.Episode', 'anime.Episode', (['entrance', 'exit'], {}), '(en... |
import torch
import matplotlib as mpl
mpl.use('agg')
import numpy as np
import os
import scipy.integrate as integrate
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from matplotlib.lines import Line2D
from matplotlib import rc
def plotPred(args, t, xT, uPred, uTarget, epoch, bidx=0):
'''
Plots a s... | [
"torch.mean",
"matplotlib.rc",
"numpy.abs",
"matplotlib.pyplot.close",
"matplotlib.pyplot.subplot2grid",
"numpy.insert",
"numpy.max",
"matplotlib.use",
"matplotlib.pyplot.figure",
"numpy.min",
"numpy.linspace",
"torch.pow",
"matplotlib.colorbar.ColorbarBase",
"matplotlib.pyplot.savefig",
... | [((38, 52), 'matplotlib.use', 'mpl.use', (['"""agg"""'], {}), "('agg')\n", (45, 52), True, 'import matplotlib as mpl\n'), ((357, 373), 'matplotlib.pyplot.close', 'plt.close', (['"""all"""'], {}), "('all')\n", (366, 373), True, 'import matplotlib.pyplot as plt\n'), ((467, 491), 'matplotlib.rc', 'rc', (['"""text"""'], {'... |
#!/usr/bin/env python3
import argparse
import requests
from bioschemas_indexer import indexer
# MAIN
parser = argparse.ArgumentParser('Run a test query against the Solr instance')
parser.add_argument('query')
args = parser.parse_args()
_, solr = indexer.read_conf()
solrSuggester = 'http://' + solr['SOLR_SERVER'] + ... | [
"bioschemas_indexer.indexer.read_conf",
"argparse.ArgumentParser",
"requests.get"
] | [((113, 182), 'argparse.ArgumentParser', 'argparse.ArgumentParser', (['"""Run a test query against the Solr instance"""'], {}), "('Run a test query against the Solr instance')\n", (136, 182), False, 'import argparse\n'), ((250, 269), 'bioschemas_indexer.indexer.read_conf', 'indexer.read_conf', ([], {}), '()\n', (267, 2... |
#!/usr/bin/env python3
from itertools import permutations
from pathlib import Path
class Figure(frozenset):
@classmethod
def parse(cls, text):
lines = [l for l in text.splitlines() if l]
for digit in range(10):
digittext = ''.join(l[3 * digit:3 * (digit + 1)] for l in lines)
... | [
"itertools.permutations",
"pathlib.Path"
] | [((944, 970), 'itertools.permutations', 'permutations', (['unknownchars'], {}), '(unknownchars)\n', (956, 970), False, 'from itertools import permutations\n'), ((1830, 1848), 'pathlib.Path', 'Path', (['"""input"""', '"""8"""'], {}), "('input', '8')\n", (1834, 1848), False, 'from pathlib import Path\n')] |
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from builtins import range
import utils
import argparse
import time
import os
import sys
import random
import math
import json
import codecs
import numpy as np
import utils
from util... | [
"json.dump",
"numpy.save",
"argparse.ArgumentParser",
"utils.build_lang",
"codecs.open",
"random.shuffle",
"random.seed",
"sys.exit"
] | [((376, 435), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Dialog2Vec Generator"""'}), "(description='Dialog2Vec Generator')\n", (399, 435), False, 'import argparse\n'), ((878, 900), 'random.seed', 'random.seed', (['args.seed'], {}), '(args.seed)\n', (889, 900), False, 'import random\n... |
class Solution:
def wallsAndGates(self, rooms: List[List[int]]) -> None:
"""
Do not return anything, modify rooms in-place instead.
"""
if not rooms:
return
INF = 2 ** 31 - 1
m, n = len(rooms), len(rooms[0])
from collections import deque
qu... | [
"collections.deque"
] | [((324, 331), 'collections.deque', 'deque', ([], {}), '()\n', (329, 331), False, 'from collections import deque\n')] |
import more_itertools as mit
import functools as ftl
from recipes.testing import Expect
from astropy.io.fits.hdu.base import _BaseHDU
from pathlib import Path
from pySHOC import shocCampaign, shocHDU, shocNewHDU, shocBiasHDU, shocFlatHDU
import pytest
import numpy as np
import os
import tempfile as tmp
# TODO: old + n... | [
"numpy.random.seed",
"recipes.testing.Expect",
"tempfile.mkstemp",
"astropy.io.fits.hdu.base._BaseHDU.readfrom",
"pathlib.Path",
"numpy.random.randint",
"os.close",
"numpy.arange",
"pytest.mark.parametrize",
"pySHOC.shocCampaign.load"
] | [((648, 669), 'numpy.random.seed', 'np.random.seed', (['(12345)'], {}), '(12345)\n', (662, 669), True, 'import numpy as np\n'), ((854, 873), 'tempfile.mkstemp', 'tmp.mkstemp', (['""".txt"""'], {}), "('.txt')\n", (865, 873), True, 'import tempfile as tmp\n'), ((967, 979), 'os.close', 'os.close', (['fp'], {}), '(fp)\n', ... |
import sys
import os
from tests.test_single_file import PhysicalData
from tests.test_single_file import SingleFile
import pytest
class Rootpath:
"""
@overvieww: class of the absolute path of root directory
"""
def __init__(self, opts):
self.rootpath = opts[1] #TODO study how to resolve the cons... | [
"os.walk",
"os.sep.join",
"sys.exc_info"
] | [((1175, 1193), 'os.walk', 'os.walk', (['root_path'], {}), '(root_path)\n', (1182, 1193), False, 'import os\n'), ((696, 710), 'sys.exc_info', 'sys.exc_info', ([], {}), '()\n', (708, 710), False, 'import sys\n'), ((2270, 2284), 'sys.exc_info', 'sys.exc_info', ([], {}), '()\n', (2282, 2284), False, 'import sys\n'), ((134... |
import logging
def set_custom_log_info(file):
logging.basicConfig(filename=file , level=logging.INFO)
def report(e:Exception):
logging.exception(str(e)) | [
"logging.basicConfig"
] | [((49, 103), 'logging.basicConfig', 'logging.basicConfig', ([], {'filename': 'file', 'level': 'logging.INFO'}), '(filename=file, level=logging.INFO)\n', (68, 103), False, 'import logging\n')] |
import numpy as np
import open3d as o3d
import os
from argparse import ArgumentParser
parser = ArgumentParser()
parser.add_argument("--red", type = float, default = 0.5)
parser.add_argument("--blue", type = float, default = 0.4)
parser.add_argument("--green", type = float, default = 0.4)
parser.add_argument("--source_... | [
"argparse.ArgumentParser",
"numpy.asarray",
"open3d.geometry.PointCloud",
"open3d.io.read_point_cloud",
"open3d.io.write_point_cloud",
"open3d.visualization.draw_geometries",
"numpy.array",
"open3d.utility.Vector3dVector",
"os.listdir"
] | [((96, 112), 'argparse.ArgumentParser', 'ArgumentParser', ([], {}), '()\n', (110, 112), False, 'from argparse import ArgumentParser\n'), ((1053, 1111), 'os.listdir', 'os.listdir', (['f"""./pointcloud_transformed/{args.source_dir}/"""'], {}), "(f'./pointcloud_transformed/{args.source_dir}/')\n", (1063, 1111), False, 'im... |
from db import cursor
from db import db as mongodb
from pymongo import ASCENDING
import bson
import datetime
mongo_user = mongodb['user']
mongo_video = mongodb['video']
mongo_author = mongodb['author']
# 用户相关
INSERT_USER_SQL = """
INSERT INTO `user` (`name`, `password`, `credit`, `exp`, `gmt_create`, `role`)
VALUES (... | [
"db.cursor.fetchone",
"db.cursor.executemany",
"db.cursor.execute"
] | [((1853, 1890), 'db.cursor.execute', 'cursor.execute', (['INSERT_USER_SQL', 'item'], {}), '(INSERT_USER_SQL, item)\n', (1867, 1890), False, 'from db import cursor\n'), ((1899, 1948), 'db.cursor.execute', 'cursor.execute', (['GET_USER_ID_SQL', "each_doc['name']"], {}), "(GET_USER_ID_SQL, each_doc['name'])\n", (1913, 194... |
"""Rainbow HAT GPIO Touch Driver."""
try:
import RPi.GPIO as GPIO
except ImportError:
raise ImportError("""This library requires the RPi.GPIO module.
Install with: sudo pip install RPi.GPIO""")
PIN_A = 21
PIN_B = 20
PIN_C = 16
GPIO.setmode(GPIO.BCM)
GPIO.setwarnings(False)
class Button(object):
"""Repr... | [
"RPi.GPIO.setmode",
"RPi.GPIO.setup",
"RPi.GPIO.input",
"RPi.GPIO.setwarnings",
"RPi.GPIO.add_event_detect"
] | [((238, 260), 'RPi.GPIO.setmode', 'GPIO.setmode', (['GPIO.BCM'], {}), '(GPIO.BCM)\n', (250, 260), True, 'import RPi.GPIO as GPIO\n'), ((261, 284), 'RPi.GPIO.setwarnings', 'GPIO.setwarnings', (['(False)'], {}), '(False)\n', (277, 284), True, 'import RPi.GPIO as GPIO\n'), ((767, 828), 'RPi.GPIO.setup', 'GPIO.setup', (['s... |
#!/usr/bin/python
import xml.sax
import sys
import os
import nltk
from nltk import sent_tokenize
from nltk.corpus import stopwords
from nltk.tokenize import RegexpTokenizer
from nltk.tokenize import TreebankWordTokenizer,ToktokTokenizer
from nltk.stem import PorterStemmer
from nltk.corpus import stopwords
from nltk.... | [
"threading.Thread",
"re.split",
"os.makedirs",
"os.getcwd",
"re.finditer",
"os.path.exists",
"time.sleep",
"time.time",
"nltk.corpus.stopwords.words",
"Stemmer.Stemmer"
] | [((492, 503), 'time.time', 'time.time', ([], {}), '()\n', (501, 503), False, 'import time\n'), ((575, 601), 'nltk.corpus.stopwords.words', 'stopwords.words', (['"""english"""'], {}), "('english')\n", (590, 601), False, 'from nltk.corpus import stopwords\n'), ((646, 672), 'Stemmer.Stemmer', 'Stemmer.Stemmer', (['"""engl... |
from django.contrib import admin
from .models import Category, Movie, Comment
class CategoryAdmin(admin.ModelAdmin):
list_display = ['name', 'slug']
prepopulated_fields = {'slug': ('name',)}
admin.site.register(Category, CategoryAdmin)
class FilmAdmin(admin.ModelAdmin):
list_display = ['name', 'slug', ... | [
"django.contrib.admin.site.register"
] | [((202, 246), 'django.contrib.admin.site.register', 'admin.site.register', (['Category', 'CategoryAdmin'], {}), '(Category, CategoryAdmin)\n', (221, 246), False, 'from django.contrib import admin\n'), ((578, 615), 'django.contrib.admin.site.register', 'admin.site.register', (['Movie', 'FilmAdmin'], {}), '(Movie, FilmAd... |
# Initial setup following http://docs.chainer.org/en/stable/tutorial/basic.html
import numpy as np
import chainer
from chainer import cuda, Function, gradient_check, report, training, utils, Variable
from chainer import datasets, iterators, optimizers, serializers
from chainer import Link, Chain, ChainList
import chain... | [
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot",
"chainer.serializers.load_npz",
"matplotlib.pyplot.clf",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.legend",
"numpy.frompyfunc",
"numpy.arange",
"chainer.functions.sigmoid",
"numpy.random.rand",
"chainer.links.Linear"
] | [((976, 1020), 'chainer.serializers.load_npz', 'serializers.load_npz', (['model_save_path', 'model'], {}), '(model_save_path, model)\n', (996, 1020), False, 'from chainer import datasets, iterators, optimizers, serializers\n'), ((1366, 1398), 'numpy.frompyfunc', 'np.frompyfunc', (['target_func', '(1)', '(1)'], {}), '(t... |
from django import forms
from contacts.models import Contact
from common.models import Comment
class ContactForm(forms.ModelForm):
def __init__(self, *args, **kwargs):
assigned_users = kwargs.pop('assigned_to', [])
contact_org = kwargs.pop('organization', [])
super(ContactForm, ... | [
"django.forms.ValidationError",
"django.forms.CharField"
] | [((3063, 3108), 'django.forms.CharField', 'forms.CharField', ([], {'max_length': '(64)', 'required': '(True)'}), '(max_length=64, required=True)\n', (3078, 3108), False, 'from django import forms\n'), ((2080, 2145), 'django.forms.ValidationError', 'forms.ValidationError', (['"""Phone Number should contain only Numbers"... |
import nibabel as nib
import glob
import os
import numpy as np
import tensorlayer as tl
'''
Before normalization, run N4 bias correction (https://www.ncbi.nlm.nih.gov/pubmed/20378467),
then save the data under folder ./CamCAN_unbiased/CamCAN
'''
modalities = ['T1w', 'T2w']
BraTS_modalities = ['T1w']
folders = ['HGG'... | [
"numpy.pad",
"nibabel.load",
"numpy.std",
"numpy.transpose",
"numpy.rot90",
"numpy.mean",
"glob.glob",
"numpy.eye",
"os.chdir"
] | [((468, 484), 'os.chdir', 'os.chdir', (['wd_mod'], {}), '(wd_mod)\n', (476, 484), False, 'import os\n'), ((614, 627), 'nibabel.load', 'nib.load', (['img'], {}), '(img)\n', (622, 627), True, 'import nibabel as nib\n'), ((797, 830), 'numpy.transpose', 'np.transpose', (['img_data', '[2, 0, 1]'], {}), '(img_data, [2, 0, 1]... |
# -*- coding: utf-8 -*-
# @Author: yulidong
# @Date: 2018-08-30 16:47:51
# @Last Modified by: yulidong
# @Last Modified time: 2018-08-30 21:13:04
import torch
import torch.multiprocessing as mp
import time
def add(a,b,c):
start=time.time()
d=a+b
c+=d
print(time.time()-start)
def selfadd(a):
prin... | [
"time.time",
"torch.multiprocessing.set_start_method",
"torch.multiprocessing.Process",
"torch.arange",
"torch.zeros"
] | [((236, 247), 'time.time', 'time.time', ([], {}), '()\n', (245, 247), False, 'import time\n'), ((378, 411), 'torch.multiprocessing.set_start_method', 'mp.set_start_method', (['"""forkserver"""'], {}), "('forkserver')\n", (397, 411), True, 'import torch.multiprocessing as mp\n'), ((658, 669), 'time.time', 'time.time', (... |
from django.db import models
from django.utils import timezone
class NflConference(models.Model):
name = models.TextField()
abbreviation = models.TextField(max_length=5)
def __unicode__(self):
return self.name
class NflDivision(models.Model):
name = models.TextField()
conference = models... | [
"django.db.models.TextField",
"django.db.models.URLField",
"django.db.models.ForeignKey",
"django.utils.timezone.now",
"django.db.models.PositiveIntegerField",
"django.db.models.EmailField",
"django.db.models.IntegerField",
"django.db.models.DateTimeField"
] | [((110, 128), 'django.db.models.TextField', 'models.TextField', ([], {}), '()\n', (126, 128), False, 'from django.db import models\n'), ((148, 178), 'django.db.models.TextField', 'models.TextField', ([], {'max_length': '(5)'}), '(max_length=5)\n', (164, 178), False, 'from django.db import models\n'), ((278, 296), 'djan... |
import sys
def cnt(n):
m = str(n)
l = len(m)
if l == 1:
return n + 1
tot = 0
tot += pow(10, (l - 1) // 2) * (int(m[0]) - 1)
tot += pow(10, l // 2) - 1 - pow(10, l // 2 - 1) * (l & 1 ^ 1)
while l >= 2:
l -= 2
if l == 0:
tot += m[1] >= m[0]
... | [
"sys.stdin.readline"
] | [((590, 610), 'sys.stdin.readline', 'sys.stdin.readline', ([], {}), '()\n', (608, 610), False, 'import sys\n')] |
from DLFrameWork.forward import NetWork
from DLFrameWork.dataset import FashionMNIST,DataLoader
if __name__ == '__main__':
FMNIST = FashionMNIST(path='MNIST_Data',download=False,train=True)
dLoader = DataLoader(FMNIST,batchsize=100,shuffling=False,normalization={'Transform':True})
# (784,256),(256,12... | [
"DLFrameWork.dataset.FashionMNIST",
"DLFrameWork.forward.NetWork",
"DLFrameWork.dataset.DataLoader"
] | [((138, 197), 'DLFrameWork.dataset.FashionMNIST', 'FashionMNIST', ([], {'path': '"""MNIST_Data"""', 'download': '(False)', 'train': '(True)'}), "(path='MNIST_Data', download=False, train=True)\n", (150, 197), False, 'from DLFrameWork.dataset import FashionMNIST, DataLoader\n'), ((215, 305), 'DLFrameWork.dataset.DataLoa... |
# This is a generated file! Please edit source .ksy file and use kaitai-struct-compiler to rebuild
from pkg_resources import parse_version
from .kaitaistruct import __version__ as ks_version, KaitaiStruct, KaitaiStream, BytesIO
import collections
from enum import Enum
if parse_version(ks_version) < parse_version('0.... | [
"collections.defaultdict",
"pkg_resources.parse_version"
] | [((275, 300), 'pkg_resources.parse_version', 'parse_version', (['ks_version'], {}), '(ks_version)\n', (288, 300), False, 'from pkg_resources import parse_version\n'), ((303, 323), 'pkg_resources.parse_version', 'parse_version', (['"""0.7"""'], {}), "('0.7')\n", (316, 323), False, 'from pkg_resources import parse_versio... |
"""
JobMon Launcher
===============
Launches the JobMon supervisor as a daemon - generally, the usage pattern for
this module will be something like the following::
>>> from jobmon import config
>>> config_handler = config.ConfigHandler
>>> config_handler.load(SOME_FILE)
>>> run(config_handler)
"""
im... | [
"jobmon.service.SupervisorShim",
"logging.basicConfig",
"jobmon.service.SupervisorService",
"logging.getLogger",
"jobmon.event_server.EventServer",
"logging.info",
"jobmon.command_server.CommandServer",
"os._exit",
"jobmon.status_server.StatusServer",
"os.fork",
"jobmon.ticker.Ticker",
"jobmon... | [((593, 666), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.INFO', 'format': '"""%(asctime)s %(message)s"""'}), "(level=logging.INFO, format='%(asctime)s %(message)s')\n", (612, 666), False, 'import logging\n'), ((697, 733), 'logging.getLogger', 'logging.getLogger', (['"""jobmon.launcher"""'], {... |
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
from pylab import cm
mpl.rcParams['font.family'] = 'STIXGeneral'
plt.rcParams['xtick.labelsize'] = 16
plt.rcParams['ytick.labelsize'] = 16
plt.rcParams['font.size'] = 16
plt.rcParams['figure.figsize'] = [5.6, 4]
plt.rcParams['axes.titlesize'] ... | [
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure",
"numpy.loadtxt",
"pylab.cm.get_cmap",
"matplotlib.pyplot.tight_layout"
] | [((558, 580), 'pylab.cm.get_cmap', 'cm.get_cmap', (['"""Set1"""', '(9)'], {}), "('Set1', 9)\n", (569, 580), False, 'from pylab import cm\n'), ((588, 600), 'matplotlib.pyplot.figure', 'plt.figure', ([], {}), '()\n', (598, 600), True, 'import matplotlib.pyplot as plt\n'), ((1086, 1120), 'numpy.loadtxt', 'np.loadtxt', (['... |
# coding=utf-8
"""
EXAMPLE
Example file, timer clock with in-menu options.
Copyright (C) 2017 <NAME> @ppizarror
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, ... | [
"pygame.event.get",
"pygame.display.set_mode",
"pygameMenu.Menu",
"pygame.init",
"pygame.display.flip",
"random.randrange",
"pygame.font.Font",
"pygameMenu.TextMenu",
"pygame.display.set_caption",
"pygame.time.Clock"
] | [((1447, 1460), 'pygame.init', 'pygame.init', ([], {}), '()\n', (1458, 1460), False, 'import pygame\n'), ((1596, 1637), 'pygame.display.set_mode', 'pygame.display.set_mode', (['(W_SIZE, H_SIZE)'], {}), '((W_SIZE, H_SIZE))\n', (1619, 1637), False, 'import pygame\n'), ((1639, 1687), 'pygame.display.set_caption', 'pygame.... |
from tracemalloc import start
from matplotlib.pyplot import contour
from parcv.Models import Models
from datetime import datetime
from dateutil import parser
import re
from string import punctuation
from collections import Counter
import math
class ResumeParser:
def __init__(self, ner, ner_dates, zero_shot_classi... | [
"dateutil.parser.parse",
"datetime.datetime.today",
"string.punctuation.replace",
"re.escape",
"datetime.datetime",
"parcv.Models.Models",
"re.search"
] | [((367, 375), 'parcv.Models.Models', 'Models', ([], {}), '()\n', (373, 375), False, 'from parcv.Models import Models\n'), ((12113, 12160), 're.search', 're.search', (['"""[\\\\w.+-]+@[\\\\w-]+\\\\.[\\\\w.-]+"""', 'item'], {}), "('[\\\\w.+-]+@[\\\\w-]+\\\\.[\\\\w.-]+', item)\n", (12122, 12160), False, 'import re\n'), ((... |
# quick scripts to generate example images for figures
import matplotlib.pyplot as plt
import seaborn as sns
import torch
import numpy as np
from functions import *
from data import *
from copy import deepcopy
import pickle
def plot_threshold_value_examples(savename):
with open(savename, 'rb') as handle:
d... | [
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.show",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.figure",
"pickle.load",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig"
] | [((1382, 1601), 'matplotlib.pyplot.subplots', 'plt.subplots', (['nrow', 'ncol'], {'figsize': '(ncol + 1, nrow + 1)', 'gridspec_kw': "{'wspace': 0, 'hspace': 0, 'top': 1.0 - 0.5 / (nrow + 1), 'bottom': 0.5 / (\n nrow + 1), 'left': 0.5 / (ncol + 1), 'right': 1 - 0.5 / (ncol + 1)}"}), "(nrow, ncol, figsize=(ncol + 1, n... |
'''A utility for backing up and restoring saved games.
Usage:
savman list [--backups]
savman scan [--nocache]
savman update
savman load <directory>
savman backup <directory> [<game>] [options]
savman restore <game> [<directory>] [options]
savman -h | --help
Commands:
list Show a list ... | [
"os.mkdir",
"logging.error",
"os.path.isdir",
"os.path.dirname",
"sys.argv.remove",
"savman.gameman.GameMan",
"logging.info",
"os.path.isfile",
"savman.databaseman.Manager",
"os.path.normpath",
"savman.datapath",
"sys.exit",
"os.path.join",
"logging.getLogger"
] | [((2000, 2021), 'savman.databaseman.Manager', 'databaseman.Manager', ([], {}), '()\n', (2019, 2021), False, 'from savman import databaseman, gameman, datapath, __version__\n'), ((2090, 2110), 'savman.datapath', 'datapath', (['"""gamedata"""'], {}), "('gamedata')\n", (2098, 2110), False, 'from savman import databaseman,... |
from bsm.config.util import detect_package
from bsm.operation import Base
class DetectPackage(Base):
def execute(self, directory):
return detect_package(directory, self._config['package_runtime'])
| [
"bsm.config.util.detect_package"
] | [((152, 210), 'bsm.config.util.detect_package', 'detect_package', (['directory', "self._config['package_runtime']"], {}), "(directory, self._config['package_runtime'])\n", (166, 210), False, 'from bsm.config.util import detect_package\n')] |
# Generated by Django 3.1.12 on 2021-07-28 18:28
from django.db import migrations, models
import django.db.models.deletion
import uuid
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='TermsOfAccess',
... | [
"django.db.models.TextField",
"django.db.models.UUIDField",
"django.db.models.CharField",
"django.db.models.ForeignKey",
"django.db.models.FloatField",
"django.db.models.BooleanField",
"django.db.models.AutoField",
"django.db.models.DateTimeField"
] | [((355, 448), 'django.db.models.AutoField', 'models.AutoField', ([], {'auto_created': '(True)', 'primary_key': '(True)', 'serialize': '(False)', 'verbose_name': '"""ID"""'}), "(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')\n", (371, 448), False, 'from django.db import migrations, models\... |
import gym
env_name = "CartPole-v0"
env_name = "Ant-v2"
env = gym.make(env_name)
class Agent:
def __init__(self, env):
self.action_space = env.action_space
def get_action(self, obs):
return self.action_space.sample()
env.reset()
agent = Agent(env)
for i_episode in range(10):
state = env.reset()
for t in rang... | [
"gym.make"
] | [((62, 80), 'gym.make', 'gym.make', (['env_name'], {}), '(env_name)\n', (70, 80), False, 'import gym\n')] |
import curses
import os
import sys
import time
class Board:
column_width = 6
blank_column_line = "{}|".format(" " * column_width)
column_divider = "{}+".format("-" * column_width)
def __init__(self, boardSupplier):
self.boardSupplier = boardSupplier
board = boardSupplier()
... | [
"curses.noecho",
"curses.initscr",
"curses.newwin"
] | [((534, 550), 'curses.initscr', 'curses.initscr', ([], {}), '()\n', (548, 550), False, 'import curses\n'), ((573, 608), 'curses.newwin', 'curses.newwin', (['(20)', 'self.width', '(0)', '(0)'], {}), '(20, self.width, 0, 0)\n', (586, 608), False, 'import curses\n'), ((647, 662), 'curses.noecho', 'curses.noecho', ([], {})... |
"""
Utilities for solving different problems in `eo-grow` package structure, which are mostly a pure Python magic.
"""
from __future__ import annotations
import importlib
import inspect
from typing import TYPE_CHECKING, Any, Dict, Type
if TYPE_CHECKING:
from ..core.pipeline import Pipeline
from ..core.schemas... | [
"pkg_resources.get_distribution",
"importlib.util.find_spec",
"inspect.isclass",
"importlib.import_module"
] | [((2626, 2663), 'importlib.util.find_spec', 'importlib.util.find_spec', (['import_path'], {}), '(import_path)\n', (2650, 2663), False, 'import importlib\n'), ((1292, 1327), 'inspect.isclass', 'inspect.isclass', (['object_with_schema'], {}), '(object_with_schema)\n', (1307, 1327), False, 'import inspect\n'), ((1966, 200... |
from enum import Enum
from mapperpy.one_way_mapper import OneWayMapper
__author__ = 'lgrech'
class MappingDirection(Enum):
left_to_right = 1
right_to_left = 2
class ObjectMapper(object):
def __init__(self, from_left_mapper, from_right_mapper):
"""
:param from_left_mapper:
:type... | [
"mapperpy.one_way_mapper.OneWayMapper.for_target_class",
"mapperpy.one_way_mapper.OneWayMapper.for_target_prototype"
] | [((657, 699), 'mapperpy.one_way_mapper.OneWayMapper.for_target_class', 'OneWayMapper.for_target_class', (['right_class'], {}), '(right_class)\n', (686, 699), False, 'from mapperpy.one_way_mapper import OneWayMapper\n'), ((713, 754), 'mapperpy.one_way_mapper.OneWayMapper.for_target_class', 'OneWayMapper.for_target_class... |
""" Configurable recurrent cell. """
import copy
from pydoc import locate
import torch
from torch.autograd import Variable
import torch.nn as nn
from torch.nn.utils.rnn import PackedSequence, pack_padded_sequence, pad_packed_sequence
from benri.configurable import Configurable
class RNN(nn.Module, Configurable):
... | [
"torch.split",
"torch.cat",
"torch.nn.Module.__init__",
"torch.zeros",
"benri.configurable.Configurable.__init__"
] | [((372, 396), 'torch.nn.Module.__init__', 'nn.Module.__init__', (['self'], {}), '(self)\n', (390, 396), True, 'import torch.nn as nn\n'), ((405, 447), 'benri.configurable.Configurable.__init__', 'Configurable.__init__', (['self'], {'params': 'params'}), '(self, params=params)\n', (426, 447), False, 'from benri.configur... |
import bpy
import os
# pwd = os.getcwd()
pwd = os.path.dirname(os.path.realpath(__file__))
def loadShader(shaderName, mesh):
# switch to different shader names
if shaderName is "EeveeToon":
bpy.context.scene.render.engine = 'BLENDER_EEVEE'
bpy.context.scene.render.alpha_mode = 'TRANSPARENT'
... | [
"bpy.data.materials.get",
"os.path.realpath",
"bpy.ops.wm.append"
] | [((63, 89), 'os.path.realpath', 'os.path.realpath', (['__file__'], {}), '(__file__)\n', (79, 89), False, 'import os\n'), ((847, 898), 'bpy.ops.wm.append', 'bpy.ops.wm.append', ([], {'filename': 'matName', 'directory': 'path'}), '(filename=matName, directory=path)\n', (864, 898), False, 'import bpy\n'), ((909, 940), 'bp... |
from flakon import JsonBlueprint
from cb_news.news_extractor.database import *
from flask import request
import logging
report_handler = JsonBlueprint('report_handler', __name__)
logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
level=logging.INFO)
logger = loggin... | [
"flask.request.get_json",
"logging.getLogger",
"flakon.JsonBlueprint",
"logging.basicConfig"
] | [((138, 179), 'flakon.JsonBlueprint', 'JsonBlueprint', (['"""report_handler"""', '__name__'], {}), "('report_handler', __name__)\n", (151, 179), False, 'from flakon import JsonBlueprint\n'), ((181, 288), 'logging.basicConfig', 'logging.basicConfig', ([], {'format': '"""%(asctime)s - %(name)s - %(levelname)s - %(message... |
from django.contrib import admin
from .models import Team, Kpi, KpiValue, Organization
# Register your models here.
@admin.register(Organization)
class OrganizationAdmin(admin.ModelAdmin):
pass
@admin.register(Team)
class TeamAdmin(admin.ModelAdmin):
pass
@admin.register(Kpi)
class KpiAdmin(admin.ModelAdmi... | [
"django.contrib.admin.register"
] | [((120, 148), 'django.contrib.admin.register', 'admin.register', (['Organization'], {}), '(Organization)\n', (134, 148), False, 'from django.contrib import admin\n'), ((203, 223), 'django.contrib.admin.register', 'admin.register', (['Team'], {}), '(Team)\n', (217, 223), False, 'from django.contrib import admin\n'), ((2... |
from pathlib import Path
from os import path as pt
def file_exist_query(filename):
path = Path(filename)
if path.is_file():
res = None
while res not in ['y', 'Y', 'n', 'N']:
res = input("\nThe file in '{}' already exists, do you really wish to re-write its contents? [y/n]".format(f... | [
"os.path.isdir",
"pathlib.Path"
] | [((96, 110), 'pathlib.Path', 'Path', (['filename'], {}), '(filename)\n', (100, 110), False, 'from pathlib import Path\n'), ((543, 557), 'pathlib.Path', 'Path', (['filename'], {}), '(filename)\n', (547, 557), False, 'from pathlib import Path\n'), ((662, 683), 'os.path.isdir', 'pt.isdir', (['folder_name'], {}), '(folder_... |
# -*- coding: utf-8 -*-
#
# JSON osu! map analysis
#
import numpy as np;
def get_map_timing_array(map_json, length=-1, divisor=4):
if length == -1:
length = map_json["obj"][-1]["time"] + 1000; # it has an extra time interval after the last note
if map_json["obj"][-1]["type"] & 8: # spinner end
... | [
"numpy.min",
"numpy.array",
"numpy.arange",
"numpy.concatenate"
] | [((4069, 4101), 'numpy.array', 'np.array', (["[note['x'], note['y']]"], {}), "([note['x'], note['y']])\n", (4077, 4101), True, 'import numpy as np\n'), ((4621, 4663), 'numpy.array', 'np.array', (["[prev_note['x'], prev_note['y']]"], {}), "([prev_note['x'], prev_note['y']])\n", (4629, 4663), True, 'import numpy as np\n'... |
from flask import Flask, request, make_response, jsonify, Response
from flask_restx import Resource, Api, abort, reqparse
from flask_jwt_extended import JWTManager
from flask_jwt_extended import (create_access_token, create_refresh_token, jwt_required,
jwt_refresh_token_required, get_jwt... | [
"flask_jwt_extended.JWTManager",
"random.randint",
"flask_jwt_extended.get_jwt_identity",
"flask_restx.reqparse.exceptions.RequestEntityTooLarge",
"flask.request.headers.get",
"flask.Flask",
"flask_restx.Api",
"flask_restx.reqparse.RequestParser",
"flask_jwt_extended.create_access_token",
"flask_j... | [((396, 411), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (401, 411), False, 'from flask import Flask, request, make_response, jsonify, Response\n'), ((454, 544), 'flask_restx.Api', 'Api', (['app'], {'version': '"""1.0"""', 'title': '"""My API Boilerplate"""', 'description': '"""My API Boilerplate"""'})... |
### IMPORTS
from __future__ import print_function
import os
import fnmatch
import numpy as np
import skimage.data
import cv2
import sys
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from PIL import Image
from keras import applications
from keras.preprocessing.image import ImageDataGenerator
fr... | [
"keras.preprocessing.image.ImageDataGenerator",
"PIL.Image.new",
"os.walk",
"keras.applications.VGG16",
"keras.layers.Input",
"os.path.join",
"keras.optimizers.SGD",
"os.path.exists",
"keras.layers.Flatten",
"os.listdir",
"selective_search.selective_search_bbox",
"fnmatch.filter",
"logging.d... | [((647, 702), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.DEBUG', 'format': 'FORMAT'}), '(level=logging.DEBUG, format=FORMAT)\n', (666, 702), False, 'import logging\n'), ((948, 983), 'os.path.join', 'os.path.join', (['dataset_path', '"""train"""'], {}), "(dataset_path, 'train')\n", (960, 983),... |
import os
import glob
import shutil
def del_dummydirs(rootpath, list):
for root, subdirs, files in os.walk(rootpath):
"""
walk through given rootpath, delete dirs in list
"""
for s in subdirs:
if s in list:
shutil.rmtree(os.path.join(root, s))
... | [
"os.walk",
"os.path.join"
] | [((105, 122), 'os.walk', 'os.walk', (['rootpath'], {}), '(rootpath)\n', (112, 122), False, 'import os\n'), ((287, 308), 'os.path.join', 'os.path.join', (['root', 's'], {}), '(root, s)\n', (299, 308), False, 'import os\n'), ((346, 367), 'os.path.join', 'os.path.join', (['root', 's'], {}), '(root, s)\n', (358, 367), Fals... |
'''
This script illustrates training of an inflammation classifier for patches along SI joints
'''
import argparse
import os
import shutil
import pytorch_lightning as pl
from torch.utils.data import DataLoader
from neuralnets.util.io import print_frm
from neuralnets.util.tools import set_seed
from neuralnets.util.augm... | [
"pytorch_lightning.callbacks.ModelCheckpoint",
"pytorch_lightning.Trainer",
"argparse.ArgumentParser",
"torch.utils.data.DataLoader",
"models.sparcc_cnn.Inflammation_CNN",
"neuralnets.util.tools.set_seed",
"neuralnets.util.io.print_frm",
"os.path.join",
"data.datasets.SPARCCDataset"
] | [((762, 918), 'torch.utils.data.DataLoader', 'DataLoader', (['train_data'], {'batch_size': '(factor[INFLAMMATION_MODULE] * args.train_batch_size)', 'num_workers': 'args.num_workers', 'pin_memory': '(True)', 'shuffle': '(True)'}), '(train_data, batch_size=factor[INFLAMMATION_MODULE] * args.\n train_batch_size, num_wo... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# middleware.py
#
# Authors:
# - <NAME> <<EMAIL>>
#
import logging
from django.contrib import auth
from django.core.exceptions import ImproperlyConfigured
from django.shortcuts import redirect, get_object_or_404
from django.urls import resolve, reverse
from djan... | [
"django.core.exceptions.ImproperlyConfigured",
"activity.models.Activity.get_or_update_from_lti",
"activity.models.Activity.get_or_create_course_from_lti",
"django.urls.reverse",
"django.shortcuts.get_object_or_404",
"django.urls.resolve",
"django.contrib.auth.authenticate",
"lti_app.models.ActivityOu... | [((456, 483), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (473, 483), False, 'import logging\n'), ((1661, 1923), 'django.core.exceptions.ImproperlyConfigured', 'ImproperlyConfigured', (['"""The Django LTI auth middleware requires the authentication middleware to be installed. Edit you... |
# Copyright 2020 Graphcore Ltd.
import argparse
import os
import time as time
import numpy as np
import tensorflow as tf
from tensorflow.python.ipu import ipu_compiler, ipu_infeed_queue, loops, utils
from tensorflow.python.ipu.scopes import ipu_scope, ipu_shard
import tensorflow_probability as tfp
# ... | [
"argparse.ArgumentParser",
"tensorflow.reset_default_graph",
"tensorflow.reshape",
"tensorflow.get_variable_scope",
"tensorflow.ConfigProto",
"tensorflow_probability.mcmc.sample_chain",
"os.path.join",
"numpy.savetxt",
"numpy.genfromtxt",
"tensorflow.variable_scope",
"tensorflow.python.ipu.ipu_c... | [((645, 670), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '()\n', (668, 670), False, 'import argparse\n'), ((824, 891), 'os.path.join', 'os.path.join', (['args.dataset_dir', '"""returns_and_features_for_mcmc.txt"""'], {}), "(args.dataset_dir, 'returns_and_features_for_mcmc.txt')\n", (836, 891), Fals... |
import hashlib
import os
from flask import current_app, url_for
cache_busting_values = {}
class CachebustStaticAssets(object):
def __init__(self, app=None):
self.app = app
if app is not None:
self.init_app(app)
def init_app(self, app):
@app.context_processor
def ... | [
"os.path.isfile",
"flask.url_for",
"hashlib.md5",
"os.path.join"
] | [((1351, 1378), 'flask.url_for', 'url_for', (['endpoint'], {}), '(endpoint, **values)\n', (1358, 1378), False, 'from flask import current_app, url_for\n'), ((1659, 1672), 'hashlib.md5', 'hashlib.md5', ([], {}), '()\n', (1670, 1672), False, 'import hashlib\n'), ((733, 805), 'os.path.join', 'os.path.join', (['current_app... |
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
# os.environ['CUDA_DEVICE_ORDER'] = 'PCI_BUS_ID'
# os.environ['CUDA_VISIBLE_DEVICES'] = '0'
import json
import time
import argparse
from pathlib import Path
import random
import numpy as np
import tensorflow as tf
tf.autograph.set_verbosity(3) # 0: deb... | [
"tensorflow.random.set_seed",
"json.dump",
"numpy.random.seed",
"argparse.ArgumentParser",
"src.models.RACL.RACL",
"src.utils.dict2html",
"time.time",
"pathlib.Path",
"src.utils.split_documents",
"random.seed",
"src.models.encoder.Encoder",
"numpy.reshape",
"src.utils.reverse_unk",
"src.ut... | [((282, 311), 'tensorflow.autograph.set_verbosity', 'tf.autograph.set_verbosity', (['(3)'], {}), '(3)\n', (308, 311), True, 'import tensorflow as tf\n'), ((1851, 1879), 'random.seed', 'random.seed', (['opt.random_seed'], {}), '(opt.random_seed)\n', (1862, 1879), False, 'import random\n'), ((1885, 1916), 'numpy.random.s... |
from queue import Empty, SimpleQueue
from typing import Any, Callable, Optional, cast
from PyQt5.QtCore import QEvent, QObject
from PyQt5.QtWidgets import QApplication
from ..log import get_logger
Function = Callable[[], None]
class IoThreadExecutor:
def __init__(self) -> None:
self._queue: SimpleQueue... | [
"typing.cast",
"queue.SimpleQueue"
] | [((333, 346), 'queue.SimpleQueue', 'SimpleQueue', ([], {}), '()\n', (344, 346), False, 'from queue import Empty, SimpleQueue\n'), ((1568, 1591), 'typing.cast', 'cast', (['_FunctionEvent', 'e'], {}), '(_FunctionEvent, e)\n', (1572, 1591), False, 'from typing import Any, Callable, Optional, cast\n')] |
# -*- coding: utf-8 -*-
"""
Created on Tue Sep 29 17:41:44 2020
@author: salman
"""
from PIL import Image
import pandas as pd
import numpy as np
import cv2
import os
d={}
data = pd.read_csv('E:\\fyp data\\ADEK-20\\new_se_new\\new.txt', sep="\t")
arr=np.zeros(151)
print(arr)
for point in data.values:
(key,name,... | [
"pandas.read_csv",
"cv2.imwrite",
"numpy.zeros",
"cv2.imread",
"numpy.unique"
] | [((182, 249), 'pandas.read_csv', 'pd.read_csv', (['"""E:\\\\fyp data\\\\ADEK-20\\\\new_se_new\\\\new.txt"""'], {'sep': '"""\t"""'}), "('E:\\\\fyp data\\\\ADEK-20\\\\new_se_new\\\\new.txt', sep='\\t')\n", (193, 249), True, 'import pandas as pd\n'), ((255, 268), 'numpy.zeros', 'np.zeros', (['(151)'], {}), '(151)\n', (263... |
"""Tests for the marion application views"""
import json
import tempfile
from pathlib import Path
from django.urls import reverse
import pytest
from pytest_django import asserts as django_assertions
from rest_framework import exceptions as drf_exceptions
from rest_framework import status
from rest_framework.test imp... | [
"marion.models.DocumentRequest.objects.count",
"pytest_django.asserts.assertContains",
"json.dumps",
"django.urls.reverse",
"tempfile.mkdtemp",
"marion.models.DocumentRequest.objects.get",
"rest_framework.test.APIClient"
] | [((422, 433), 'rest_framework.test.APIClient', 'APIClient', ([], {}), '()\n', (431, 433), False, 'from rest_framework.test import APIClient\n'), ((800, 831), 'django.urls.reverse', 'reverse', (['"""documentrequest-list"""'], {}), "('documentrequest-list')\n", (807, 831), False, 'from django.urls import reverse\n'), ((2... |
import os
import numpy as np
from glob import glob
from textwrap import wrap
from tabulate import tabulate
from collections import defaultdict
from typing import List, Union, Iterator, Iterable, Tuple, Dict
from typing import TypeVar, Generic
from .applicator import Applicator
T = TypeVar('T', bound='BiText')
... | [
"os.path.basename",
"textwrap.wrap",
"os.path.dirname",
"collections.defaultdict",
"tabulate.tabulate",
"glob.glob",
"typing.TypeVar",
"os.path.join"
] | [((289, 317), 'typing.TypeVar', 'TypeVar', (['"""T"""'], {'bound': '"""BiText"""'}), "('T', bound='BiText')\n", (296, 317), False, 'from typing import TypeVar, Generic\n'), ((2556, 2573), 'collections.defaultdict', 'defaultdict', (['list'], {}), '(list)\n', (2567, 2573), False, 'from collections import defaultdict\n'),... |
# -*- coding: utf-8 -*-
"""
@author: bartulem
Run Kilosort2 through Python.
As it stands (spring/summer 2020), to use Kilosort2 one still requires Matlab. To ensure it works,
one needs a specific combination of Matlab, the GPU driver version and CUDA compiler files.
On the lab computer, I set it up to work on Matla... | [
"os.path.exists",
"sys.exit",
"time.time"
] | [((1726, 1737), 'time.time', 'time.time', ([], {}), '()\n', (1735, 1737), False, 'import time\n'), ((1215, 1239), 'os.path.exists', 'os.path.exists', (['file_dir'], {}), '(file_dir)\n', (1229, 1239), False, 'import os\n'), ((1328, 1338), 'sys.exit', 'sys.exit', ([], {}), '()\n', (1336, 1338), False, 'import sys\n'), ((... |
import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor, GradientBoostingClassifier
from sklearn.metrics import mean_absolute_error, accuracy_score, roc_curve, roc_auc_score
from src.utils import calc_annual_return_vec, ... | [
"matplotlib.pyplot.title",
"sklearn.metrics.accuracy_score",
"matplotlib.pyplot.bar",
"sklearn.metrics.mean_absolute_error",
"numpy.argsort",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.tight_layout",
"os.path.join",
"numpy.round",
"pandas.DataFrame",
"numpy.std",
"matplotlib.pyplot.xticks"... | [((696, 723), 'numpy.array', 'np.array', (["train['good_bad']"], {}), "(train['good_bad'])\n", (704, 723), True, 'import numpy as np\n'), ((790, 816), 'numpy.array', 'np.array', (["test['good_bad']"], {}), "(test['good_bad'])\n", (798, 816), True, 'import numpy as np\n'), ((1294, 1322), 'sklearn.ensemble.GradientBoosti... |
import numpy as np
import torch
import torch.nn as nn
def soft_update(target: nn.Module, source: nn.Module, tau):
with torch.no_grad():
for target_param, param in zip(target.parameters(), source.parameters()):
target_param.data.copy_(target_param.data * (1.0 - tau) + param.data * tau)
def ha... | [
"tensorflow.nest.map_structure",
"torch.no_grad",
"numpy.ndim"
] | [((1652, 1715), 'tensorflow.nest.map_structure', 'tf.nest.map_structure', (['_to_single_numpy_or_python_type', 'tensors'], {}), '(_to_single_numpy_or_python_type, tensors)\n', (1673, 1715), True, 'import tensorflow as tf\n'), ((125, 140), 'torch.no_grad', 'torch.no_grad', ([], {}), '()\n', (138, 140), False, 'import to... |
#!/usr/bin/python
# -*- coding: utf-8 -*-
# @CreateTime: Jun 18, 2017 1:13 PM
# @Author: <NAME>
# @Contact: <EMAIL>
# @Last Modified By: <NAME>
# @Last Modified Time: Jun 18, 2017 3:45 PM
# @Description: Modify Here, Please
from __future__ import print_function, division
import re
import json
import csv
from datetime ... | [
"yaml.load",
"csv.reader",
"argparse.ArgumentParser",
"logging.FileHandler",
"json.loads",
"progress.bar.Bar",
"json.dumps",
"requests.urllib3.disable_warnings",
"logging.Formatter",
"requests.delete",
"requests.get",
"datetime.datetime.now",
"logging.getLogger"
] | [((743, 800), 'requests.urllib3.disable_warnings', 'requests.urllib3.disable_warnings', (['InsecureRequestWarning'], {}), '(InsecureRequestWarning)\n', (776, 800), False, 'import requests\n'), ((810, 824), 'datetime.datetime.now', 'datetime.now', ([], {}), '()\n', (822, 824), False, 'from datetime import datetime\n'), ... |
from pelican import signals
from . import count
def add_filter(pelican):
"""Add count_elements filter to Pelican."""
pelican.env.filters.update(
{'sort_by_article_count': count.sort_by_article_count})
def register():
"""Plugin registration."""
signals.generator_init.connect(add_filter)
| [
"pelican.signals.generator_init.connect"
] | [((272, 314), 'pelican.signals.generator_init.connect', 'signals.generator_init.connect', (['add_filter'], {}), '(add_filter)\n', (302, 314), False, 'from pelican import signals\n')] |
#!/usr/bin/env python
'''
Takes in the usgs neic event object, then determines if it
is relevant above the input filter criteria. If it passes
this filter, an aoi type for the event is created and submitted
to create_aoi
'''
from __future__ import division
from builtins import range
from past.utils import old_div
im... | [
"argparse.ArgumentParser",
"past.utils.old_div",
"json.dumps",
"submit_slack_notification.slack_notify",
"builtins.range",
"os.path.join",
"lightweight_water_mask.get_land_area",
"shapely.geometry.Point",
"track_displacement_evaluator.main",
"shapely.geometry.Polygon",
"json.loads",
"math.radi... | [((1730, 1840), 'track_displacement_evaluator.main', 'track_displacement_evaluator.main', (["event['location']['coordinates']", "event_info['location']['coordinates']"], {}), "(event['location']['coordinates'],\n event_info['location']['coordinates'])\n", (1763, 1840), False, 'import track_displacement_evaluator\n')... |
from contextlib import suppress
with suppress(ImportError):
from .mxnet_object_detector import MxnetObjectDetector
| [
"contextlib.suppress"
] | [((38, 59), 'contextlib.suppress', 'suppress', (['ImportError'], {}), '(ImportError)\n', (46, 59), False, 'from contextlib import suppress\n')] |
# -*- coding: utf-8 -*-
# snapshottest: v1 - https://goo.gl/zC4yUc
from __future__ import unicode_literals
from snapshottest import GenericRepr, Snapshot
snapshots = Snapshot()
snapshots['TestCreate.test[True-uvloop-None-True] history'] = {
'_id': '9pfsom1b.0',
'created_at': GenericRepr('datetime.datetime(2... | [
"snapshottest.GenericRepr",
"snapshottest.Snapshot"
] | [((169, 179), 'snapshottest.Snapshot', 'Snapshot', ([], {}), '()\n', (177, 179), False, 'from snapshottest import GenericRepr, Snapshot\n'), ((288, 340), 'snapshottest.GenericRepr', 'GenericRepr', (['"""datetime.datetime(2015, 10, 6, 20, 0)"""'], {}), "('datetime.datetime(2015, 10, 6, 20, 0)')\n", (299, 340), False, 'f... |
import argparse
import inspect
from copy import deepcopy
from functools import partial, update_wrapper
from typing import List, Mapping, Sequence, _GenericAlias
import yaml
class Registrable:
"""Class used to denote which types of objects can be registered in the RLHive
Registry. These objects can also be co... | [
"functools.partial",
"copy.deepcopy",
"argparse.ArgumentParser",
"functools.update_wrapper",
"inspect.signature",
"yaml.safe_load"
] | [((7047, 7084), 'inspect.signature', 'inspect.signature', (['object_constructor'], {}), '(object_constructor)\n', (7064, 7084), False, 'import inspect\n'), ((7159, 7175), 'copy.deepcopy', 'deepcopy', (['config'], {}), '(config)\n', (7167, 7175), False, 'from copy import deepcopy\n'), ((9651, 9678), 'inspect.signature',... |
from django.dispatch import receiver
from django.db.models.signals import post_delete
from linuxmachinebeta.review.models import ServiceReview
@receiver(post_delete, sender=ServiceReview)
def update_rating_after_delete(sender, instance, **kwargs):
instance.service.update_rating()
| [
"django.dispatch.receiver"
] | [((147, 190), 'django.dispatch.receiver', 'receiver', (['post_delete'], {'sender': 'ServiceReview'}), '(post_delete, sender=ServiceReview)\n', (155, 190), False, 'from django.dispatch import receiver\n')] |
# users/admin.py
from django.contrib import admin
from django.contrib.auth.admin import UserAdmin
from .forms import ReviewsUserCreationForm, ReviewsUserChangeForm
from .models import ReviewsUser
class ReviewUserAdmin(UserAdmin):
add_form = ReviewsUserCreationForm
form = ReviewsUserChangeForm
list_displa... | [
"django.contrib.admin.site.register"
] | [((391, 440), 'django.contrib.admin.site.register', 'admin.site.register', (['ReviewsUser', 'ReviewUserAdmin'], {}), '(ReviewsUser, ReviewUserAdmin)\n', (410, 440), False, 'from django.contrib import admin\n')] |
import os
import itertools
from itertools import product
# get_files(loadrules,["[F.3]","[A.1]"],[".yaml"])
def get_files(_path, _startwith=None, _endwith=None):
'''
get all files
:param _startwith : ["str1","str2"]
:param _endwith : [".sol",".py"]
'''
if not _startwith: _startwi... | [
"os.path.isfile",
"os.walk",
"os.path.join",
"itertools.product"
] | [((882, 896), 'os.walk', 'os.walk', (['_path'], {}), '(_path)\n', (889, 896), False, 'import os\n'), ((377, 403), 'os.path.isfile', 'os.path.isfile', (['_startwith'], {}), '(_startwith)\n', (391, 403), False, 'import os\n'), ((662, 691), 'itertools.product', 'product', (['_startwith', '_endwith'], {}), '(_startwith, _e... |
"""Submodule containing frequency-based models."""
from freqtools.freq_data import OscillatorNoise
import numpy as np
import matplotlib.pyplot as plt
class FreqModel:
"""
Base class for frequency based models, i.e. values (y axis) as a function of
frequency (x axis). Its functionality is purposfully kept... | [
"numpy.trapz",
"numpy.log",
"numpy.logical_and",
"matplotlib.pyplot.subplots",
"numpy.array",
"numpy.sign",
"numpy.log10",
"matplotlib.pyplot.grid",
"numpy.sqrt"
] | [((1841, 1877), 'matplotlib.pyplot.grid', 'plt.grid', (['(True)'], {'which': '"""both"""', 'ls': '"""-"""'}), "(True, which='both', ls='-')\n", (1849, 1877), True, 'import matplotlib.pyplot as plt\n'), ((21402, 21439), 'numpy.trapz', 'np.trapz', (['psd_vals_over_line'], {'x': 'freqs'}), '(psd_vals_over_line, x=freqs)\n... |