code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
from django.shortcuts import render
from django.http import HttpResponseRedirect
from django.urls import reverse
from django.utils.crypto import get_random_string
from django.core.exceptions import ObjectDoesNotExist
from .models import Game
from .forms import GameForm, JoinGameForm
# Create your views here.
def home... | streams/views.py | from django.shortcuts import render
from django.http import HttpResponseRedirect
from django.urls import reverse
from django.utils.crypto import get_random_string
from django.core.exceptions import ObjectDoesNotExist
from .models import Game
from .forms import GameForm, JoinGameForm
# Create your views here.
def home... | 0.350977 | 0.09236 |
import sys
from typing import KeysView
import gi
gi.require_version('Gtk', '3.0')
from gi.repository import Gio, Gtk
import argparse
'''
from Device.AndroidDevice import AndroidDevice
from Device.ScrCpyDevice import ScrCpyDevice
from Bot.Script import Script
'''
from UI.BotAppWindow import BotAppWindow
class Bo... | GameBot.py |
import sys
from typing import KeysView
import gi
gi.require_version('Gtk', '3.0')
from gi.repository import Gio, Gtk
import argparse
'''
from Device.AndroidDevice import AndroidDevice
from Device.ScrCpyDevice import ScrCpyDevice
from Bot.Script import Script
'''
from UI.BotAppWindow import BotAppWindow
class Bo... | 0.375592 | 0.081264 |
import numpy as np
from tikzpy import TikzPicture
from tikzpy.colors import rainbow_colors
""" Plots the image of a 3 x 2 matrix in R^3 acting on R^2.
Vectors in R^3 which lie below the positive Z-axis are drawn with lower opacity to aid the eye.
Usage: Plug a 3x2 numpy array into plot_linear_transformation.... | examples/linear_transformations/linear_transformations.py | import numpy as np
from tikzpy import TikzPicture
from tikzpy.colors import rainbow_colors
""" Plots the image of a 3 x 2 matrix in R^3 acting on R^2.
Vectors in R^3 which lie below the positive Z-axis are drawn with lower opacity to aid the eye.
Usage: Plug a 3x2 numpy array into plot_linear_transformation.... | 0.774924 | 0.801431 |
import uuid
from . import settings
from .models import GitHubOAuthProfile
from ..core.clients import OAuth2Client
class GitHubClient(OAuth2Client):
"""
Client to connect to the GitHub REST API.
"""
# Configuration
service_name = 'GitHub'
app_key = settings.APP_ID
app_secret = settings.APP... | socialnetworks/github/clients.py | import uuid
from . import settings
from .models import GitHubOAuthProfile
from ..core.clients import OAuth2Client
class GitHubClient(OAuth2Client):
"""
Client to connect to the GitHub REST API.
"""
# Configuration
service_name = 'GitHub'
app_key = settings.APP_ID
app_secret = settings.APP... | 0.53048 | 0.108992 |
import pdb
import torch
import numpy as np
import torch.optim as optim
class Optimizer(object):
def __init__(self, model, optim_dict):
self.optim_dict = optim_dict
if self.optim_dict["optimizer"] == 'SGD':
self.optimizer = optim.SGD(
model,
lr=self.optim... | utils/optimizer.py | import pdb
import torch
import numpy as np
import torch.optim as optim
class Optimizer(object):
def __init__(self, model, optim_dict):
self.optim_dict = optim_dict
if self.optim_dict["optimizer"] == 'SGD':
self.optimizer = optim.SGD(
model,
lr=self.optim... | 0.728169 | 0.202877 |
import argparse
import sys
import os
import time
import traceback
import sys
import ctypes
import subprocess
from subprocess import Popen, PIPE
import shutil
from optparse import OptionParser
from biokbase.workspace.client import Workspace
import urllib
import urllib2
import json
from biokbase import log
from biokbase... | scripts/trns_validate_hndlr.py |
import argparse
import sys
import os
import time
import traceback
import sys
import ctypes
import subprocess
from subprocess import Popen, PIPE
import shutil
from optparse import OptionParser
from biokbase.workspace.client import Workspace
import urllib
import urllib2
import json
from biokbase import log
from biokbase... | 0.148973 | 0.072014 |
import os
ctf_root = os.path.join(os.path.dirname(__file__), '../../')
services_dir = os.path.join(ctf_root, 'services')
SERVICES = [ d for d in os.listdir(services_dir) if os.path.isdir(os.path.join(services_dir, d)) ]
TEMPLATE = '''
name: Check {service}
on:
push:
branches:
- main
paths:
- 's... | .github/workflows/generate_workflows.py |
import os
ctf_root = os.path.join(os.path.dirname(__file__), '../../')
services_dir = os.path.join(ctf_root, 'services')
SERVICES = [ d for d in os.listdir(services_dir) if os.path.isdir(os.path.join(services_dir, d)) ]
TEMPLATE = '''
name: Check {service}
on:
push:
branches:
- main
paths:
- 's... | 0.30549 | 0.10697 |
import os
import random
import sqlite3 as sql
from db_tables import ses, Annotation, Recording, RecordingGroup
audio = random.choice(os.listdir('/Users/anaemendezmendez/Documents/NYU_PHD/Mark/code/docs/media/audio/Train_data/1'))
audio_list = os.listdir('/Users/anaemendezmendez/Documents/NYU_PHD/Mark/code/docs... | interface/test_random_file.py | import os
import random
import sqlite3 as sql
from db_tables import ses, Annotation, Recording, RecordingGroup
audio = random.choice(os.listdir('/Users/anaemendezmendez/Documents/NYU_PHD/Mark/code/docs/media/audio/Train_data/1'))
audio_list = os.listdir('/Users/anaemendezmendez/Documents/NYU_PHD/Mark/code/docs... | 0.166981 | 0.098947 |
import os
from typing import Any, Dict
from cloudtik.core._private.utils import merge_rooted_config_hierarchy, _get_runtime_config_object
from cloudtik.core._private.workspace.workspace_operator import _get_workspace_provider
from cloudtik.core._private.providers import _get_node_provider
RUNTIME_PROCESSES = [
# ... | python/cloudtik/runtime/hdfs/utils.py | import os
from typing import Any, Dict
from cloudtik.core._private.utils import merge_rooted_config_hierarchy, _get_runtime_config_object
from cloudtik.core._private.workspace.workspace_operator import _get_workspace_provider
from cloudtik.core._private.providers import _get_node_provider
RUNTIME_PROCESSES = [
# ... | 0.571527 | 0.140307 |
"""Test all EPub methods against a random book from Project Gutenberg."""
import os, unittest, random
from pathlib import Path
import xml.etree.ElementTree as ET
import epubmangler
# Select a book from local selection of epubs
DIR = '/home/david/Projects/epubmangler/books/gutenberg'
# DIR = '/home/david/Projects/e... | tests.py | """Test all EPub methods against a random book from Project Gutenberg."""
import os, unittest, random
from pathlib import Path
import xml.etree.ElementTree as ET
import epubmangler
# Select a book from local selection of epubs
DIR = '/home/david/Projects/epubmangler/books/gutenberg'
# DIR = '/home/david/Projects/e... | 0.461017 | 0.451629 |
from dash.development.base_component import Component, _explicitize_args
class GraduatedBar(Component):
"""A GraduatedBar component.
A graduated bar component that displays
a value within some range as a
percentage.
Keyword arguments:
- id (string; optional): The ID used to identify this compnent in Dash callba... | dash_daq/GraduatedBar.py |
from dash.development.base_component import Component, _explicitize_args
class GraduatedBar(Component):
"""A GraduatedBar component.
A graduated bar component that displays
a value within some range as a
percentage.
Keyword arguments:
- id (string; optional): The ID used to identify this compnent in Dash callba... | 0.835148 | 0.447521 |
import numpy as np
# Functions for testing Characteristics.cpp
def characteristic_speeds(lapse, shift, spatial_velocity, spatial_velocity_sqrd,
sound_speed_sqrd, normal_oneform):
normal_velocity = np.dot(spatial_velocity, normal_oneform)
normal_shift = np.dot(shift, normal_oneform)
... | tests/Unit/Evolution/Systems/RelativisticEuler/Valencia/TestFunctions.py |
import numpy as np
# Functions for testing Characteristics.cpp
def characteristic_speeds(lapse, shift, spatial_velocity, spatial_velocity_sqrd,
sound_speed_sqrd, normal_oneform):
normal_velocity = np.dot(spatial_velocity, normal_oneform)
normal_shift = np.dot(shift, normal_oneform)
... | 0.675444 | 0.535584 |
import pytest
import pendulum
import random
from fastbt.models.breakout import Breakout, StockData, HighLow
from fastbt.brokers.zerodha import Zerodha
from pydantic import ValidationError
from unittest.mock import Mock, patch, call
@pytest.fixture
def base_breakout():
return Breakout(
symbols=["GOOG", "AA... | tests/test_breakout.py | import pytest
import pendulum
import random
from fastbt.models.breakout import Breakout, StockData, HighLow
from fastbt.brokers.zerodha import Zerodha
from pydantic import ValidationError
from unittest.mock import Mock, patch, call
@pytest.fixture
def base_breakout():
return Breakout(
symbols=["GOOG", "AA... | 0.616243 | 0.523481 |
import os
from typing import Optional
from decouple import Csv
import sys
from decouple import config, Csv
from datetime import timedelta
DEV = config("DEV", default=False, cast=bool)
PORT = config("PORT", default=8443, cast=int)
# region BOT CONFIGURATION
BOT_TOKEN = config("BOT_TOKEN", cast=lambda v: str(v) if v e... | botlistbot/settings.py | import os
from typing import Optional
from decouple import Csv
import sys
from decouple import config, Csv
from datetime import timedelta
DEV = config("DEV", default=False, cast=bool)
PORT = config("PORT", default=8443, cast=int)
# region BOT CONFIGURATION
BOT_TOKEN = config("BOT_TOKEN", cast=lambda v: str(v) if v e... | 0.30965 | 0.089415 |
from __future__ import division
import sys
import pandas as pd
pd.set_option('display.max_columns', 500)
import numpy as np
import plotly
import plotly.graph_objs as go
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
from g2p_client import G2PDatabase
from genie import *
# Constants
HO... | figures/scripts/oncokb_app.py | from __future__ import division
import sys
import pandas as pd
pd.set_option('display.max_columns', 500)
import numpy as np
import plotly
import plotly.graph_objs as go
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
from g2p_client import G2PDatabase
from genie import *
# Constants
HO... | 0.395718 | 0.249276 |
from algoritms.SVR import svr
from algoritms.ARIMA import arima
from utils.DataFormatter import DataFormatter
from algoritms.MovingAverage import moving_average
from algoritms.AutoRegression import auto_regression
from algoritms.LinearRegression import linear_regression
from algoritms.ExponentialSmoothing import expone... | main.py | from algoritms.SVR import svr
from algoritms.ARIMA import arima
from utils.DataFormatter import DataFormatter
from algoritms.MovingAverage import moving_average
from algoritms.AutoRegression import auto_regression
from algoritms.LinearRegression import linear_regression
from algoritms.ExponentialSmoothing import expone... | 0.701509 | 0.337859 |
from __future__ import print_function
from __future__ import unicode_literals
from __future__ import absolute_import
from __future__ import division
from random import normalvariate
from random import shuffle
from random import uniform
from random import seed
import matplotlib.pyplot as plt
import matplotlib.patches a... | concept_formation/examples/cobweb3_cluster_simulated.py | from __future__ import print_function
from __future__ import unicode_literals
from __future__ import absolute_import
from __future__ import division
from random import normalvariate
from random import shuffle
from random import uniform
from random import seed
import matplotlib.pyplot as plt
import matplotlib.patches a... | 0.576184 | 0.281332 |
from zopeskel.localcommands import ZopeSkelLocalTemplate
class PlonePasSubTemplate(ZopeSkelLocalTemplate):
use_cheetah = True
marker_name = 'implemented plugins'
parent_templates = ['plone_pas']
class ExtractionPlugin(PlonePasSubTemplate):
"""
A plone pas extraction plugin
"""
_template_d... | zopeskel/localcommands/plone_pas.py | from zopeskel.localcommands import ZopeSkelLocalTemplate
class PlonePasSubTemplate(ZopeSkelLocalTemplate):
use_cheetah = True
marker_name = 'implemented plugins'
parent_templates = ['plone_pas']
class ExtractionPlugin(PlonePasSubTemplate):
"""
A plone pas extraction plugin
"""
_template_d... | 0.427158 | 0.147402 |
import plotly.graph_objects as go
from plotly.subplots import make_subplots
["#27c1d1", "#217883", "#FF0000", "#6473ff"]
color_scheme = {"Visa": "#6473ff", "MasterCard":"#217883"}
def create_model_plots(df, feature_plots, desc):
for feature_plot in feature_plots:
fig = go.Figure()
for card_name... | experiments_track/propancity/src/plots.py | import plotly.graph_objects as go
from plotly.subplots import make_subplots
["#27c1d1", "#217883", "#FF0000", "#6473ff"]
color_scheme = {"Visa": "#6473ff", "MasterCard":"#217883"}
def create_model_plots(df, feature_plots, desc):
for feature_plot in feature_plots:
fig = go.Figure()
for card_name... | 0.629205 | 0.287718 |
import os
import requests
import shutil
import imghdr
import base64
import argparse
from harvest_urls import HarvestURLs
from multiprocessing import Pool
class Sites:
GOOGLE = 1
GOOGLE_FULL = 3
@staticmethod
def get_text(code):
if code == Sites.GOOGLE:
return 'g... | scrape_image.py | import os
import requests
import shutil
import imghdr
import base64
import argparse
from harvest_urls import HarvestURLs
from multiprocessing import Pool
class Sites:
GOOGLE = 1
GOOGLE_FULL = 3
@staticmethod
def get_text(code):
if code == Sites.GOOGLE:
return 'g... | 0.167797 | 0.06256 |
import logging
import ckan.plugins as plugins
import ckan.plugins.toolkit as toolkit
def create_programs():
user = toolkit.get_action('get_site_user')({'ignore_auth': True}, {})
context = {'user': user['name']}
try:
data = {'id': 'programs'}
toolkit.get_action('vocabulary_show')(context, da... | ckanext-atbrepo/ckanext/atbrepo/plugin.py | import logging
import ckan.plugins as plugins
import ckan.plugins.toolkit as toolkit
def create_programs():
user = toolkit.get_action('get_site_user')({'ignore_auth': True}, {})
context = {'user': user['name']}
try:
data = {'id': 'programs'}
toolkit.get_action('vocabulary_show')(context, da... | 0.398758 | 0.116462 |
import argparse
import matplotlib.pyplot as plt
import pandas as pd
from pandas.plotting import register_matplotlib_converters
import pmdarima
from statsmodels.tsa.arima.model import ARIMA
from gamestonk_terminal.helper_funcs import (
check_positive,
get_next_stock_market_days,
parse_known_args_and_warn,
... | gamestonk_terminal/prediction_techniques/arima.py | import argparse
import matplotlib.pyplot as plt
import pandas as pd
from pandas.plotting import register_matplotlib_converters
import pmdarima
from statsmodels.tsa.arima.model import ARIMA
from gamestonk_terminal.helper_funcs import (
check_positive,
get_next_stock_market_days,
parse_known_args_and_warn,
... | 0.605566 | 0.572544 |
import sys
import subprocess
import pathlib
MODE = "ohlc"
BROKER = "ig.com"
BASE_PATH = "/mnt/storage/Data/market/ig.com/MT4"
MARKETS = {
"CS.D.AUDNZD.MINI.IP": "AUDNZD",
"CS.D.AUDUSD.MINI.IP": "AUDUSD",
"CS.D.EURCAD.MINI.IP": "EURCAD",
"CS.D.EURCHF.MINI.IP": "EURCHF",
"CS.D.EURGBP.MINI.IP": "EURG... | scripts/import-ig-mt4.py | import sys
import subprocess
import pathlib
MODE = "ohlc"
BROKER = "ig.com"
BASE_PATH = "/mnt/storage/Data/market/ig.com/MT4"
MARKETS = {
"CS.D.AUDNZD.MINI.IP": "AUDNZD",
"CS.D.AUDUSD.MINI.IP": "AUDUSD",
"CS.D.EURCAD.MINI.IP": "EURCAD",
"CS.D.EURCHF.MINI.IP": "EURCHF",
"CS.D.EURGBP.MINI.IP": "EURG... | 0.24015 | 0.305205 |
from utils import *
from model_utils import *
from data import *
from c2d_models import *
from _lrp import *
from _lime import *
from _counterfactual import *
from _shap import *
'''
Example self.configuration
confg = {
'lime': {
'num_features': 128*128,
'mask_features': 5,
'num_samples':... | test_pipeline.py | from utils import *
from model_utils import *
from data import *
from c2d_models import *
from _lrp import *
from _lime import *
from _counterfactual import *
from _shap import *
'''
Example self.configuration
confg = {
'lime': {
'num_features': 128*128,
'mask_features': 5,
'num_samples':... | 0.432902 | 0.166981 |
import os, json
import geopandas as gpd
import pandas as pd
import multiprocessing as mp
from multiprocessing.shared_memory import SharedMemory
import numpy as np
import pyproj
import pygeos
from shapely import geometry, ops, wkt
from functools import partial
from ffsc.pipeline.nodes.utils import V_inv
def chunk... | ffsc/pipeline/nodes/mp_sjoin_mindist.py | import os, json
import geopandas as gpd
import pandas as pd
import multiprocessing as mp
from multiprocessing.shared_memory import SharedMemory
import numpy as np
import pyproj
import pygeos
from shapely import geometry, ops, wkt
from functools import partial
from ffsc.pipeline.nodes.utils import V_inv
def chunk... | 0.302597 | 0.385548 |
import torch
from detectron2.layers import cat
from detectron2.utils.events import get_event_storage
from torch.nn import functional as F
from meshrcnn.structures.mask import batch_crop_masks_within_box
def mask_rcnn_loss(pred_mask_logits, instances):
"""
Compute the mask prediction loss defined in the Mask ... | meshrcnn/modeling/roi_heads/mask_head.py | import torch
from detectron2.layers import cat
from detectron2.utils.events import get_event_storage
from torch.nn import functional as F
from meshrcnn.structures.mask import batch_crop_masks_within_box
def mask_rcnn_loss(pred_mask_logits, instances):
"""
Compute the mask prediction loss defined in the Mask ... | 0.937247 | 0.785514 |
import unittest
import os
import so3g
from spt3g import core
def write_example_file(filename='hk_out.g3'):
"""Generate an example g3 file with Wiring Frame.
This is based on other test file writing functions, but is unique in that
it contains a wiring frame for use in testing Seek/Tell.
Structure o... | test/test_indexed.py | import unittest
import os
import so3g
from spt3g import core
def write_example_file(filename='hk_out.g3'):
"""Generate an example g3 file with Wiring Frame.
This is based on other test file writing functions, but is unique in that
it contains a wiring frame for use in testing Seek/Tell.
Structure o... | 0.549641 | 0.611121 |
from functools import reduce
from operator import add
import math
import torch
from torchvision.models import resnet
from einops import rearrange
from model.base.feature import extract_feat_res
from model.ifsl import iFSLModule
from model.module.panet import PrototypeAlignmentLearner
class PrototypeAlignmentNetwo... | fs-cs/model/panet.py | from functools import reduce
from operator import add
import math
import torch
from torchvision.models import resnet
from einops import rearrange
from model.base.feature import extract_feat_res
from model.ifsl import iFSLModule
from model.module.panet import PrototypeAlignmentLearner
class PrototypeAlignmentNetwo... | 0.716615 | 0.256035 |
from PyPDF2 import PdfFileWriter, PdfFileReader
import io
import os
from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import letter
from reportlab.pdfbase.ttfonts import TTFont
from reportlab.pdfbase import pdfmetrics
from server.utils.misctools import get_pardir
path = get_pardir(os.path.abspath(__file... | server/utils/certification_generate.py | from PyPDF2 import PdfFileWriter, PdfFileReader
import io
import os
from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import letter
from reportlab.pdfbase.ttfonts import TTFont
from reportlab.pdfbase import pdfmetrics
from server.utils.misctools import get_pardir
path = get_pardir(os.path.abspath(__file... | 0.218169 | 0.106412 |
from typing import Dict, Any, Tuple, Union
from collections import namedtuple
import pathlib
import logging
import attr
from attr.validators import instance_of
import numpy as np
import pandas as pd
import zarr
from numcodecs import Zstd
def trunc_end_of_file(name) -> str:
"""
Take only the start of the file... | src/pysight/nd_hist_generator/outputs.py | from typing import Dict, Any, Tuple, Union
from collections import namedtuple
import pathlib
import logging
import attr
from attr.validators import instance_of
import numpy as np
import pandas as pd
import zarr
from numcodecs import Zstd
def trunc_end_of_file(name) -> str:
"""
Take only the start of the file... | 0.73914 | 0.282652 |
import difflib
import os
import random
import subprocess
import sys
from subprocess import PIPE
join = os.path.join
# The path to the current file.
CURR_DIR = os.path.abspath(os.path.dirname(__file__))
# The default data directory.
DATA_DIR = os.path.join(CURR_DIR, "data")
# The run directory
RUN_NAME = "run"
RUN_D... | test/compare.py | import difflib
import os
import random
import subprocess
import sys
from subprocess import PIPE
join = os.path.join
# The path to the current file.
CURR_DIR = os.path.abspath(os.path.dirname(__file__))
# The default data directory.
DATA_DIR = os.path.join(CURR_DIR, "data")
# The run directory
RUN_NAME = "run"
RUN_D... | 0.176246 | 0.16388 |
import cmd
import sys
import socket
import gevent
import gevent.server
from gevent import sleep
from telnetsrv.green import TelnetHandler, command
import junk
class Phases(object):
LOGON = 0
GAMES = 1
JOSHUA = 2
GLOBAL = 3
class WOPRHandler(TelnetHandler):
PROMPT = "LOGON: "
WELCOME = ""
... | wopr/__init__.py | import cmd
import sys
import socket
import gevent
import gevent.server
from gevent import sleep
from telnetsrv.green import TelnetHandler, command
import junk
class Phases(object):
LOGON = 0
GAMES = 1
JOSHUA = 2
GLOBAL = 3
class WOPRHandler(TelnetHandler):
PROMPT = "LOGON: "
WELCOME = ""
... | 0.255529 | 0.080828 |
import os
import argparse
import yaml
import numpy as np
import pandas as pd
import random
SECONDS_OF_A_DAY = 3600*24
MILLISECONDS_PER_SEC = 1000
config = yaml.load(open(os.path.join(os.path.dirname(__file__),'config.yaml')), yaml.FullLoader)
SAMPLE_NUM = config['sample_number']
workloadDir = "../CSVs/%i" % SAMPLE_NU... | Testcase11-Real-world-app-emulation/reg-trace/src/funcTimelineGenerator.py | import os
import argparse
import yaml
import numpy as np
import pandas as pd
import random
SECONDS_OF_A_DAY = 3600*24
MILLISECONDS_PER_SEC = 1000
config = yaml.load(open(os.path.join(os.path.dirname(__file__),'config.yaml')), yaml.FullLoader)
SAMPLE_NUM = config['sample_number']
workloadDir = "../CSVs/%i" % SAMPLE_NU... | 0.147034 | 0.1015 |
import signal
import hashlib
import logging
import subprocess
from .config import Config
from .profiling import profile
logger = logging.getLogger(__name__)
DIFF_CHUNK = 4096
def from_raw_reader(in_file, filter=None):
def feeder(out_file):
max_lines = Config().max_diff_input_lines
end_nl = Fal... | venv/lib/python3.7/site-packages/diffoscope/feeders.py |
import signal
import hashlib
import logging
import subprocess
from .config import Config
from .profiling import profile
logger = logging.getLogger(__name__)
DIFF_CHUNK = 4096
def from_raw_reader(in_file, filter=None):
def feeder(out_file):
max_lines = Config().max_diff_input_lines
end_nl = Fal... | 0.600891 | 0.143848 |
import time
class simplepid(object):
def __init__(self, setpoint, measure, kp, ki, kd, forward = True):
self.setpoint = setpoint
self.measure = measure
self.kp = kp
self.ki = ki
self.kd = kd
self.forward = forward # default to True in __init__, this i... | pid/fancypid.py |
import time
class simplepid(object):
def __init__(self, setpoint, measure, kp, ki, kd, forward = True):
self.setpoint = setpoint
self.measure = measure
self.kp = kp
self.ki = ki
self.kd = kd
self.forward = forward # default to True in __init__, this i... | 0.430387 | 0.194387 |
import discord
from discord.ext import commands, tasks
import asyncio
import praw
from praw.models.listing.mixins import subreddit
from praw.reddit import Subreddit
import random
from SimpleEconomy import Seco
import os
from discord.ext.commands import cooldown, BucketType
from random import randint
from discord.ex... | for_github_updated.py | import discord
from discord.ext import commands, tasks
import asyncio
import praw
from praw.models.listing.mixins import subreddit
from praw.reddit import Subreddit
import random
from SimpleEconomy import Seco
import os
from discord.ext.commands import cooldown, BucketType
from random import randint
from discord.ex... | 0.184363 | 0.086942 |
from pathlib import Path
from typing import Optional
from segtypes.n64.segment import N64Segment
from util import options
from util import log
class N64SegImg(N64Segment):
def __init__(self, rom_start, rom_end, type, name, vram_start, extract, given_subalign, given_is_overlay, given_dir, args, yaml):
super... | segtypes/n64/img.py | from pathlib import Path
from typing import Optional
from segtypes.n64.segment import N64Segment
from util import options
from util import log
class N64SegImg(N64Segment):
def __init__(self, rom_start, rom_end, type, name, vram_start, extract, given_subalign, given_is_overlay, given_dir, args, yaml):
super... | 0.870625 | 0.243069 |
# ---
# Libs
import os
from datetime import datetime, timedelta
import re
import numpy as np
from nltk import tokenize
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Embedding, LSTM, Dense, Dropout, Bidirectional
from tensorflow.keras.preprocessing.sequence import pad_... | code/LanguageGenWords_Train.py | # ---
# Libs
import os
from datetime import datetime, timedelta
import re
import numpy as np
from nltk import tokenize
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Embedding, LSTM, Dense, Dropout, Bidirectional
from tensorflow.keras.preprocessing.sequence import pad_... | 0.564579 | 0.239955 |
import os
import numpy as np
from nipype.interfaces.base import CommandLine, CommandLineInputSpec
from nipype.interfaces.base import (TraitedSpec, File, traits, InputMultiPath,isdefined)
from nipype.utils.filemanip import (load_json, save_json, split_filename, fname_presuffix)
class TraccInput(CommandLineInputSpe... | Extra/tracc.py | import os
import numpy as np
from nipype.interfaces.base import CommandLine, CommandLineInputSpec
from nipype.interfaces.base import (TraitedSpec, File, traits, InputMultiPath,isdefined)
from nipype.utils.filemanip import (load_json, save_json, split_filename, fname_presuffix)
class TraccInput(CommandLineInputSpe... | 0.501709 | 0.271916 |
import numpy as np
from collections import Counter
import sklearn.metrics as metrics
class DataHandler:
def __init__(self, config, load_data=True):
""" The initialiser for the DataHandler class.
:param config: A ArgumentParser object.
"""
# Creates the lists to store data.
... | data_handler.py | import numpy as np
from collections import Counter
import sklearn.metrics as metrics
class DataHandler:
def __init__(self, config, load_data=True):
""" The initialiser for the DataHandler class.
:param config: A ArgumentParser object.
"""
# Creates the lists to store data.
... | 0.59514 | 0.569494 |
# Also demonstrates the debounced switch library (which is threaded)
# A thread sets up initial conditions and blocks pending an interrupt. When it occurs the following things happen
# 1. The scheduler's default callback function runs recording the fact that the event has happened.
# 2. The user's callback runs. This... | irqtest.py |
# Also demonstrates the debounced switch library (which is threaded)
# A thread sets up initial conditions and blocks pending an interrupt. When it occurs the following things happen
# 1. The scheduler's default callback function runs recording the fact that the event has happened.
# 2. The user's callback runs. This... | 0.67104 | 0.518363 |
import calendar
import copy
import datetime
import decimal
from django.contrib.auth import get_user_model
from django.test import TestCase
from django.utils import timezone
from mock import patch, PropertyMock
from stripe import InvalidRequestError
from djstripe.exceptions import SubscriptionCancellationFailure, Sub... | tests/test_subscriptions.py | import calendar
import copy
import datetime
import decimal
from django.contrib.auth import get_user_model
from django.test import TestCase
from django.utils import timezone
from mock import patch, PropertyMock
from stripe import InvalidRequestError
from djstripe.exceptions import SubscriptionCancellationFailure, Sub... | 0.558568 | 0.158272 |
import numpy as np
import cv2
from PIL import ImageGrab
from key_check import key_check,key_press
import os
import time
import math as m
# os.system('python controller.py')
file_name = 'FORZA_160x120_separate_6.npy'
if os.path.isfile(file_name):
# print('File exists, loading..')
training_data = lis... | trainer STEP 1.py | import numpy as np
import cv2
from PIL import ImageGrab
from key_check import key_check,key_press
import os
import time
import math as m
# os.system('python controller.py')
file_name = 'FORZA_160x120_separate_6.npy'
if os.path.isfile(file_name):
# print('File exists, loading..')
training_data = lis... | 0.08333 | 0.178669 |
import datetime
import requests
import logging
import psutil
import json
import os
import dateutil.parser
from flask import Flask, request, render_template
from flask_migrate import Migrate, upgrade
from flask_migrate import migrate as db_migrate
from flask_migrate import downgrade
from WarnoConfig import config
from... | warno_event_manager/src/warno_event_manager.py | import datetime
import requests
import logging
import psutil
import json
import os
import dateutil.parser
from flask import Flask, request, render_template
from flask_migrate import Migrate, upgrade
from flask_migrate import migrate as db_migrate
from flask_migrate import downgrade
from WarnoConfig import config
from... | 0.609873 | 0.091058 |
import numpy as np
import numpy.linalg as linalg
import torch
import pandas as pd
import os
import os.path as osp
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from mpl_toolkits.mplot3d import Axes3D
from sklearn.decomposition import PCA
import seaborn as sns
from analyze_utils import (
... | scripts/fp_plotter.py | import numpy as np
import numpy.linalg as linalg
import torch
import pandas as pd
import os
import os.path as osp
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from mpl_toolkits.mplot3d import Axes3D
from sklearn.decomposition import PCA
import seaborn as sns
from analyze_utils import (
... | 0.701815 | 0.464719 |
import os
import percy
import pytest
class BaseTestPercyEnvironment(object):
def setup_method(self, method):
self.original_env = {}
self.original_env['TRAVIS_BUILD_ID'] = os.getenv('TRAVIS_BUILD_ID', None)
self.original_env['TRAVIS_BUILD_NUMBER'] = os.getenv('TRAVIS_BUILD_NUMBER', None)
... | tests/test_environment.py | import os
import percy
import pytest
class BaseTestPercyEnvironment(object):
def setup_method(self, method):
self.original_env = {}
self.original_env['TRAVIS_BUILD_ID'] = os.getenv('TRAVIS_BUILD_ID', None)
self.original_env['TRAVIS_BUILD_NUMBER'] = os.getenv('TRAVIS_BUILD_NUMBER', None)
... | 0.311113 | 0.130202 |
import unittest
from uuid import UUID, uuid4
from pyspark import SparkContext, StorageLevel
from pyspark.sql import SQLContext
from pyddq.core import Check
class ConstructorTest(unittest.TestCase):
def setUp(self):
self.sc = SparkContext()
self.sql = SQLContext(self.sc)
self.df = self.sql... | python/tests/integration/test_check.py | import unittest
from uuid import UUID, uuid4
from pyspark import SparkContext, StorageLevel
from pyspark.sql import SQLContext
from pyddq.core import Check
class ConstructorTest(unittest.TestCase):
def setUp(self):
self.sc = SparkContext()
self.sql = SQLContext(self.sc)
self.df = self.sql... | 0.590307 | 0.304546 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pandas as pd
import tensorflow as tf
COLUMNS = ["age", "workclass", "fnlwgt", "education", "education_num",
"marital_status", "occupation", "relationship", "race", "gender",
"capi... | tensorflow/tf_wide_and_deep.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pandas as pd
import tensorflow as tf
COLUMNS = ["age", "workclass", "fnlwgt", "education", "education_num",
"marital_status", "occupation", "relationship", "race", "gender",
"capi... | 0.821223 | 0.336467 |
import argparse
import re
import os
import sys
from collections import OrderedDict
def create_reference_and_index(config):
'''
Create the reference and index for NCLscan.
1. Repeat_ChrM
2. AllRef.fa
3. Bwa index
4. Novoalign index
'''
config_options = config.option... | bin/create_reference.py |
import argparse
import re
import os
import sys
from collections import OrderedDict
def create_reference_and_index(config):
'''
Create the reference and index for NCLscan.
1. Repeat_ChrM
2. AllRef.fa
3. Bwa index
4. Novoalign index
'''
config_options = config.option... | 0.241311 | 0.212355 |
import mock
import sys
import unittest
from io import StringIO
from cloud_snitch.cli_common import base_parser
from cloud_snitch.cli_common import confirm_env_action
from cloud_snitch.cli_common import find_environment
from cloud_snitch.exc import EnvironmentNotFoundError
class TestBaseParser(unittest.TestCase):
... | cloud_snitch/tests/test_cli_common.py | import mock
import sys
import unittest
from io import StringIO
from cloud_snitch.cli_common import base_parser
from cloud_snitch.cli_common import confirm_env_action
from cloud_snitch.cli_common import find_environment
from cloud_snitch.exc import EnvironmentNotFoundError
class TestBaseParser(unittest.TestCase):
... | 0.565059 | 0.341116 |
import json
import jwt
import time
import hashlib
import requests
import os
from colorama import Fore
from support.jira_data import get_projet_id, get_test_issues_by_filter, get_version_id, jira_auth
# Get environment variables
USER = ""
ACCESS_KEY = ""
SECRET_KEY = ""
API_TOKEN = ""
USER_ENV = os.getenv('ZEPHYR_USER'... | support/zephyr_api.py | import json
import jwt
import time
import hashlib
import requests
import os
from colorama import Fore
from support.jira_data import get_projet_id, get_test_issues_by_filter, get_version_id, jira_auth
# Get environment variables
USER = ""
ACCESS_KEY = ""
SECRET_KEY = ""
API_TOKEN = ""
USER_ENV = os.getenv('ZEPHYR_USER'... | 0.205057 | 0.040503 |
import os
import math
import unittest
import shutil
import tempfile
import imath
import IECore
import IECoreScene
import IECoreUSD
import pxr.Usd
import pxr.UsdGeom
class USDSceneTest( unittest.TestCase ) :
def setUp( self ) :
self.__temporaryDirectory = None
def tearDown( self ) :
if self.__temporaryDire... | contrib/IECoreUSD/test/IECoreUSD/USDSceneTest.py |
import os
import math
import unittest
import shutil
import tempfile
import imath
import IECore
import IECoreScene
import IECoreUSD
import pxr.Usd
import pxr.UsdGeom
class USDSceneTest( unittest.TestCase ) :
def setUp( self ) :
self.__temporaryDirectory = None
def tearDown( self ) :
if self.__temporaryDire... | 0.307774 | 0.343947 |
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
import os
BASE_DIR = os.path.dirname(os.path.dirname(__file__))
TEMPLATE_DIRS = ( os.path.join(BASE_DIR, 'procafe/templates/'),
os.path.dirname(BASE_DIR) + '/procafe/templates/',)
MEDIA_DIR = os.path.join(BASE_DIR, 'proca... | procafe/procafe/settings.py | # Build paths inside the project like this: os.path.join(BASE_DIR, ...)
import os
BASE_DIR = os.path.dirname(os.path.dirname(__file__))
TEMPLATE_DIRS = ( os.path.join(BASE_DIR, 'procafe/templates/'),
os.path.dirname(BASE_DIR) + '/procafe/templates/',)
MEDIA_DIR = os.path.join(BASE_DIR, 'proca... | 0.341143 | 0.046877 |
from math import sqrt
from decimal import getcontext, Decimal
class EvenNotation:
def __init__(self, n):
self.n = n
def __format__(self, format_spec):
number = ('{:' + format_spec + '}').format(self.n)
coeff, exp = number.split('e')
if int(exp) % 2 == 0:
return num... | DailyProgrammer/20120606C.py | from math import sqrt
from decimal import getcontext, Decimal
class EvenNotation:
def __init__(self, n):
self.n = n
def __format__(self, format_spec):
number = ('{:' + format_spec + '}').format(self.n)
coeff, exp = number.split('e')
if int(exp) % 2 == 0:
return num... | 0.542863 | 0.535038 |
from __future__ import absolute_import
import hashlib
import logging
import M2Crypto
from . import saml2idp_metadata as smd
from .codex import nice64
from . import xml_templates
logger = logging.getLogger(__name__)
def load_certificate(config):
if smd.CERTIFICATE_DATA in config:
return config.get(smd.CE... | saml2idp/xml_signing.py | from __future__ import absolute_import
import hashlib
import logging
import M2Crypto
from . import saml2idp_metadata as smd
from .codex import nice64
from . import xml_templates
logger = logging.getLogger(__name__)
def load_certificate(config):
if smd.CERTIFICATE_DATA in config:
return config.get(smd.CE... | 0.489992 | 0.09236 |
import numpy as np
from sigmoid import sigmoid
from gradAscent import stochasticGradAscent1
def classifyVector(trainingX, weights):
"""
distinguish different predict label by hypothesis output
Args:
trainingX: training data set
weights: optima weights/thetas
Returns:
0: positive output
1: negative o... | selfImplementation/Ch05_logisticRegression/applyMain.py | import numpy as np
from sigmoid import sigmoid
from gradAscent import stochasticGradAscent1
def classifyVector(trainingX, weights):
"""
distinguish different predict label by hypothesis output
Args:
trainingX: training data set
weights: optima weights/thetas
Returns:
0: positive output
1: negative o... | 0.63443 | 0.698513 |
from __future__ import print_function
import re
import sys
import argparse
import codecs
import logging
from string import Template
logging.basicConfig(filename='treedown.log', level=logging.DEBUG)
scanner = re.compile(r'''
^(?P<leftspace>\s+) |
(?P<keyword>v\.part|v.inf|cj|pc|od|oi|[\+\:svo]) |
(?P<dash... | src/treedown.py |
from __future__ import print_function
import re
import sys
import argparse
import codecs
import logging
from string import Template
logging.basicConfig(filename='treedown.log', level=logging.DEBUG)
scanner = re.compile(r'''
^(?P<leftspace>\s+) |
(?P<keyword>v\.part|v.inf|cj|pc|od|oi|[\+\:svo]) |
(?P<dash... | 0.287968 | 0.238052 |
from enum import Enum
from six import with_metaclass
from azure.core import CaseInsensitiveEnumMeta
class BackupManagementType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""Backup management type to execute the current job.
"""
INVALID = "Invalid"
AZURE_IAAS_VM = "AzureIaasVM"
MAB = "M... | sdk/recoveryservices/azure-mgmt-recoveryservicesbackup/azure/mgmt/recoveryservicesbackup/passivestamp/models/_recovery_services_backup_passive_client_enums.py |
from enum import Enum
from six import with_metaclass
from azure.core import CaseInsensitiveEnumMeta
class BackupManagementType(with_metaclass(CaseInsensitiveEnumMeta, str, Enum)):
"""Backup management type to execute the current job.
"""
INVALID = "Invalid"
AZURE_IAAS_VM = "AzureIaasVM"
MAB = "M... | 0.565179 | 0.07208 |
import argparse
import glob
import logging
import math
import os
import sys
from time import time
import networkx as nx
from tqdm import tqdm
sys.setrecursionlimit(1_000_000)
from src.cnrg.src.VRG import VRG
from src.cnrg.src.extract import MuExtractor, LocalExtractor, GlobalExtractor
from src.cnrg.src.Tree import c... | src/cnrg/runner.py | import argparse
import glob
import logging
import math
import os
import sys
from time import time
import networkx as nx
from tqdm import tqdm
sys.setrecursionlimit(1_000_000)
from src.cnrg.src.VRG import VRG
from src.cnrg.src.extract import MuExtractor, LocalExtractor, GlobalExtractor
from src.cnrg.src.Tree import c... | 0.278649 | 0.24726 |
import os
import sys
from oonib.api import OONICollector, OONIBouncer
from oonib.config import config
from oonib.onion import get_global_tor
from oonib.testhelpers import dns_helpers, ssl_helpers
from oonib.testhelpers import http_helpers, tcp_helpers
from twisted.scripts import twistd
from twisted.python import us... | oonib/oonibackend.py |
import os
import sys
from oonib.api import OONICollector, OONIBouncer
from oonib.config import config
from oonib.onion import get_global_tor
from oonib.testhelpers import dns_helpers, ssl_helpers
from oonib.testhelpers import http_helpers, tcp_helpers
from twisted.scripts import twistd
from twisted.python import us... | 0.332202 | 0.054249 |
from queue import PriorityQueue
SAMPLE_PATH = "../../input/2021-15-sample.txt"
INPUT_PATH = "../../input/2021-15-input.txt"
def get_data(filename):
with open(filename) as file:
lines = file.read().splitlines()
return [[int(x) for x in line] for line in lines]
def manhattan_distance(a, b):
re... | python/2021/day15.py |
from queue import PriorityQueue
SAMPLE_PATH = "../../input/2021-15-sample.txt"
INPUT_PATH = "../../input/2021-15-input.txt"
def get_data(filename):
with open(filename) as file:
lines = file.read().splitlines()
return [[int(x) for x in line] for line in lines]
def manhattan_distance(a, b):
re... | 0.577257 | 0.420064 |
import os
import shutil
import stat
import tempfile
from pathlib import Path
from features.steps.sh_run import run
from features.steps.util import create_new_venv
def before_scenario(context, scenario): # pylint: disable=unused-argument
"""Environment preparation before other cli tests are run.
Installs ke... | kedro-airflow/features/environment.py |
import os
import shutil
import stat
import tempfile
from pathlib import Path
from features.steps.sh_run import run
from features.steps.util import create_new_venv
def before_scenario(context, scenario): # pylint: disable=unused-argument
"""Environment preparation before other cli tests are run.
Installs ke... | 0.312475 | 0.20464 |
import os
import sys
from datetime import datetime
from functools import lru_cache
from vnpy.event import EventEngine, Event
from vnpy.trader.engine import BaseEngine, MainEngine
from vnpy.trader.event import (
EVENT_TICK, EVENT_TIMER, EVENT_ORDER, EVENT_TRADE, EVENT_POSITION)
from vnpy.trader.constant import (Dire... | vnpy/app/algo_trading/engine.py | import os
import sys
from datetime import datetime
from functools import lru_cache
from vnpy.event import EventEngine, Event
from vnpy.trader.engine import BaseEngine, MainEngine
from vnpy.trader.event import (
EVENT_TICK, EVENT_TIMER, EVENT_ORDER, EVENT_TRADE, EVENT_POSITION)
from vnpy.trader.constant import (Dire... | 0.312685 | 0.082623 |
from django.db import models
PERIOD_TYPE = (
('M', 'Mensal'),
('Q', 'Trimestral'),
('S', 'Semestral'),
('A', 'Anual')
)
class ExcelFile(models.Model):
file_name = models.FileField()
date_created = models.DateTimeField(auto_now_add=True)
activated = models.BooleanField(default=False)
d... | app/core/models.py | from django.db import models
PERIOD_TYPE = (
('M', 'Mensal'),
('Q', 'Trimestral'),
('S', 'Semestral'),
('A', 'Anual')
)
class ExcelFile(models.Model):
file_name = models.FileField()
date_created = models.DateTimeField(auto_now_add=True)
activated = models.BooleanField(default=False)
d... | 0.497559 | 0.138462 |
import streamlit as st
import pandas as pd
from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
from sklearn.metrics import accuracy_score
from sklearn.model_selection import train_test_split
from pandas_profiling import ProfileReport
from streamlit_pandas_profiling import st_profile_report
import s... | app.py | import streamlit as st
import pandas as pd
from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
from sklearn.metrics import accuracy_score
from sklearn.model_selection import train_test_split
from pandas_profiling import ProfileReport
from streamlit_pandas_profiling import st_profile_report
import s... | 0.423339 | 0.298277 |
class TreeNode:
def __init__(self, val):
self.val = val
self.left = self.right = None
# Runtime Complexity: O(N)
# Space Complexity: O(tree_height), which is O(N) in worst case of skewed tree and O(log(N)) in case of balanced tree.
class Solution:
def maxPathSum(self, root: TreeNode) -> int:
... | topics/Tree/Binary_Tree_Maximum_Path_Sum_124/[Using_nonlocal_Python_keyword]_Binary_Tree_Maximum_Path_Sum_124.py | class TreeNode:
def __init__(self, val):
self.val = val
self.left = self.right = None
# Runtime Complexity: O(N)
# Space Complexity: O(tree_height), which is O(N) in worst case of skewed tree and O(log(N)) in case of balanced tree.
class Solution:
def maxPathSum(self, root: TreeNode) -> int:
... | 0.747892 | 0.627466 |
# <NAME> (https://sites.google.com/view/a2gs/)
from BinanceCTUtil import getTimeStamp
import json
CT_CMD_COPYTRADE = "COPYTRADE"
CT_CMD_PING = "PING"
CT_CMD_CANCELORDER = "CANCEL ORDER"
CT_CMD_GETOPENORDERS = "OPENORDERS"
CT_TYPE_RESPONSE = "RESP"
CT_TYPE_REQUEST = "REQ"
# Response RefNum (data['re... | BinanceCTProto.py |
# <NAME> (https://sites.google.com/view/a2gs/)
from BinanceCTUtil import getTimeStamp
import json
CT_CMD_COPYTRADE = "COPYTRADE"
CT_CMD_PING = "PING"
CT_CMD_CANCELORDER = "CANCEL ORDER"
CT_CMD_GETOPENORDERS = "OPENORDERS"
CT_TYPE_RESPONSE = "RESP"
CT_TYPE_REQUEST = "REQ"
# Response RefNum (data['re... | 0.139075 | 0.139954 |
import os
from elf.io import open_file
from torch_em.data.datasets import get_bioimageio_dataset_id
from torch_em.util import (add_weight_formats, export_bioimageio_model,
get_default_citations, export_parser_helper,
get_training_summary)
def _load_data(input_):
... | experiments/neuron-segmentation/cremi/export_bioimageio_model.py | import os
from elf.io import open_file
from torch_em.data.datasets import get_bioimageio_dataset_id
from torch_em.util import (add_weight_formats, export_bioimageio_model,
get_default_citations, export_parser_helper,
get_training_summary)
def _load_data(input_):
... | 0.707 | 0.439266 |
import ast
import json
import os
from collections import namedtuple
from string import Template
def rel(*xs):
return os.path.join(os.path.abspath(os.path.dirname(__file__)), *xs)
with open(rel("static", "template.html")) as f:
TEMPLATE = Template(f.read())
class ReferenceFinder(ast.NodeVisitor):
def ... | modviz/modviz.py | import ast
import json
import os
from collections import namedtuple
from string import Template
def rel(*xs):
return os.path.join(os.path.abspath(os.path.dirname(__file__)), *xs)
with open(rel("static", "template.html")) as f:
TEMPLATE = Template(f.read())
class ReferenceFinder(ast.NodeVisitor):
def ... | 0.422505 | 0.224608 |
import os
import pytest
import pyfastaq
from viridian import utils
this_dir = os.path.dirname(os.path.abspath(__file__))
data_dir = os.path.join(this_dir, "data", "utils")
def test_look_for_required_binaries_in_path():
got = utils.look_for_required_binaries_in_path()
assert got == True
def test_load_singl... | tests/utils_test.py | import os
import pytest
import pyfastaq
from viridian import utils
this_dir = os.path.dirname(os.path.abspath(__file__))
data_dir = os.path.join(this_dir, "data", "utils")
def test_look_for_required_binaries_in_path():
got = utils.look_for_required_binaries_in_path()
assert got == True
def test_load_singl... | 0.359926 | 0.30029 |
import bpy
import os
import sys
import json
import time
import random
import numpy as np
from random import sample
import bpy, bpy_extras
import glob
def clear_scene():
'''Clear existing objects in scene'''
for block in bpy.data.meshes:
if block.users == 0:
bpy.data.meshes.remove(block)
... | tools/grasping/render_grasp.py | import bpy
import os
import sys
import json
import time
import random
import numpy as np
from random import sample
import bpy, bpy_extras
import glob
def clear_scene():
'''Clear existing objects in scene'''
for block in bpy.data.meshes:
if block.users == 0:
bpy.data.meshes.remove(block)
... | 0.326486 | 0.338719 |
import tensorflow as tf
FLAGS = tf.app.flags.FLAGS
def define_flags():
# Configuration (alphabetically)
tf.app.flags.DEFINE_integer('annealing_half_life', 10000,
"Number of batches until annealing temperature is halved")
tf.app.flags.DEFINE_string('attribute_file', 'list_a... | dm_flags.py | import tensorflow as tf
FLAGS = tf.app.flags.FLAGS
def define_flags():
# Configuration (alphabetically)
tf.app.flags.DEFINE_integer('annealing_half_life', 10000,
"Number of batches until annealing temperature is halved")
tf.app.flags.DEFINE_string('attribute_file', 'list_a... | 0.887082 | 0.194005 |
from os import path, access, W_OK
from converter.converter_3ds import Converter3DS
from converter.converter_wiiu import ConverterWiiU
from PyQt5.QtWidgets import QApplication, QWidget, QPushButton, QFormLayout, QFileDialog, QTextEdit, QMessageBox
class App():
def start(self):
app = QApplication([])
... | app.py | from os import path, access, W_OK
from converter.converter_3ds import Converter3DS
from converter.converter_wiiu import ConverterWiiU
from PyQt5.QtWidgets import QApplication, QWidget, QPushButton, QFormLayout, QFileDialog, QTextEdit, QMessageBox
class App():
def start(self):
app = QApplication([])
... | 0.452052 | 0.08207 |
import ctypes
import numpy
from vital.util import VitalObject
class RGBColor (VitalObject):
"""
Pixel RGB color representation.
While not a numpy array, this class can be used
"""
def __init__(self, r=255, g=255, b=255, from_cptr=None):
"""
Create a new color instance. Color va... | vital/bindings/python/vital/types/color.py | import ctypes
import numpy
from vital.util import VitalObject
class RGBColor (VitalObject):
"""
Pixel RGB color representation.
While not a numpy array, this class can be used
"""
def __init__(self, r=255, g=255, b=255, from_cptr=None):
"""
Create a new color instance. Color va... | 0.869977 | 0.30038 |
import argparse
import neuroglancer
import numpy as np
from cloudvolume import CloudVolume, Storage
from cloudvolume.lib import Bbox
import json
class NumpyEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj, (np.int64)):
return int(obj)
elif isinstance(obj, np.ndarray... | python/examples/segment_metadata_creator.py | import argparse
import neuroglancer
import numpy as np
from cloudvolume import CloudVolume, Storage
from cloudvolume.lib import Bbox
import json
class NumpyEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj, (np.int64)):
return int(obj)
elif isinstance(obj, np.ndarray... | 0.49048 | 0.193281 |
import pytest
from stock_indicators import indicators
class TestAlligator:
def test_standard(self, quotes):
results = indicators.get_alligator(quotes)
# proper quantities
# should always be the same number of results as there is quotes
assert 502 == len(results)
assert 482 ... | tests/test_alligator.py | import pytest
from stock_indicators import indicators
class TestAlligator:
def test_standard(self, quotes):
results = indicators.get_alligator(quotes)
# proper quantities
# should always be the same number of results as there is quotes
assert 502 == len(results)
assert 482 ... | 0.695752 | 0.716653 |
import boto3
import os
import logging
import requests
import cfnresponse
class ConfigKey:
cluster_name_key = 'EksClusterName'
signal_url = 'SignalUrl'
cluster_version_key = 'EksUpdateClusterVersion'
# logger
logger = logging.getLogger()
logger.setLevel(logging.INFO)
logger.info('starting... | images/controlplane/status/app/cluster_status_check.py | import boto3
import os
import logging
import requests
import cfnresponse
class ConfigKey:
cluster_name_key = 'EksClusterName'
signal_url = 'SignalUrl'
cluster_version_key = 'EksUpdateClusterVersion'
# logger
logger = logging.getLogger()
logger.setLevel(logging.INFO)
logger.info('starting... | 0.06408 | 0.045927 |
from typing import List
import datetime
from gnes.indexer.base import BaseDocIndexer as BDI
from gnes.proto import gnes_pb2, blob2array
class MySQLIndexer(BDI):
def __init__(self, user: str,
password: str,
host: str,
port: str,
database: str,... | indexer/mysql/mysql_idx.py |
from typing import List
import datetime
from gnes.indexer.base import BaseDocIndexer as BDI
from gnes.proto import gnes_pb2, blob2array
class MySQLIndexer(BDI):
def __init__(self, user: str,
password: str,
host: str,
port: str,
database: str,... | 0.68679 | 0.103839 |
from wot.directory.config import Config
from logging import getLogger
from hashlib import sha256
import requests
from tinydb import Query
class DirectoryService:
def __init__(self, db):
self.db = db
self.logger = getLogger(__name__)
def new_source(self, uri):
sources = self.db.table('s... | directory/src/wot/directory/services.py | from wot.directory.config import Config
from logging import getLogger
from hashlib import sha256
import requests
from tinydb import Query
class DirectoryService:
def __init__(self, db):
self.db = db
self.logger = getLogger(__name__)
def new_source(self, uri):
sources = self.db.table('s... | 0.479504 | 0.062732 |
import os
import os.path as osp
import random
import sys
import numpy as np
import torch
import torch.nn.functional as F
import torch.utils.data as data
from tqdm import tqdm
def seed_worker(worker_id):
worker_seed = torch.initial_seed() % 2 ** 32
np.random.seed(worker_seed)
random.seed(worker_seed)
sy... | classification/classification_test.py | import os
import os.path as osp
import random
import sys
import numpy as np
import torch
import torch.nn.functional as F
import torch.utils.data as data
from tqdm import tqdm
def seed_worker(worker_id):
worker_seed = torch.initial_seed() % 2 ** 32
np.random.seed(worker_seed)
random.seed(worker_seed)
sy... | 0.294519 | 0.203292 |
__all__ = ("IntegerMetaMap", "ScalarMetaMap", "MSpec")
import typing
from enum import IntEnum
from functools import lru_cache
from collections import OrderedDict
from warnings import warn
from .Spec import *
from .ArraySpec import ArraySpec
from .SpecNoIntegers import IntegerMetaMap
from .SpecNoScalars import ScalarMe... | UniOpt/core/MetaSpec.py | __all__ = ("IntegerMetaMap", "ScalarMetaMap", "MSpec")
import typing
from enum import IntEnum
from functools import lru_cache
from collections import OrderedDict
from warnings import warn
from .Spec import *
from .ArraySpec import ArraySpec
from .SpecNoIntegers import IntegerMetaMap
from .SpecNoScalars import ScalarMe... | 0.694717 | 0.195575 |
import os
import pytest
import yaml
from shutil import copyfile
from ideotype.data import DATA_PATH
from ideotype.wflow_setup import (make_dircts,
make_inits, make_cultivars,
make_runs, make_jobs, make_subjobs)
# setup pointer to some default init fi... | ideotype/tests/test_wflow_setup.py |
import os
import pytest
import yaml
from shutil import copyfile
from ideotype.data import DATA_PATH
from ideotype.wflow_setup import (make_dircts,
make_inits, make_cultivars,
make_runs, make_jobs, make_subjobs)
# setup pointer to some default init fi... | 0.263505 | 0.196518 |
import collections
import itertools
from . import constants
def render(*content, **context):
"""
Renders a sequence of content as HTML.
"""
return u''.join((e for c in content for e in render_content(c, **context)))
def render_content(content, **context):
"""
Renders Python data as HTML.
... | cottonmouth/html.py | import collections
import itertools
from . import constants
def render(*content, **context):
"""
Renders a sequence of content as HTML.
"""
return u''.join((e for c in content for e in render_content(c, **context)))
def render_content(content, **context):
"""
Renders Python data as HTML.
... | 0.58676 | 0.186687 |
import hashlib
import json
import logging
import click
import nltk
from crossref.restful import Works
import bibclean.utils.cleaning as cleaner
import bibclean.utils.convert as converter
import bibclean.utils.formatting as formatter
from bibclean.config import ConfigLoader
from bibclean.IO import ArgParser
from bib... | bibclean/CleanUp.py | import hashlib
import json
import logging
import click
import nltk
from crossref.restful import Works
import bibclean.utils.cleaning as cleaner
import bibclean.utils.convert as converter
import bibclean.utils.formatting as formatter
from bibclean.config import ConfigLoader
from bibclean.IO import ArgParser
from bib... | 0.269902 | 0.097176 |
import allel
from collections import Counter, OrderedDict
import matplotlib.pyplot as plt
from matplotlib.pyplot import figure
import numpy as np
from operator import itemgetter
import os
import pandas as pd
import random
import sys
from Admixture.utils import *
from Admixture.simulation import simulate
def read_samp... | Admixture/Admixture.py | import allel
from collections import Counter, OrderedDict
import matplotlib.pyplot as plt
from matplotlib.pyplot import figure
import numpy as np
from operator import itemgetter
import os
import pandas as pd
import random
import sys
from Admixture.utils import *
from Admixture.simulation import simulate
def read_samp... | 0.373533 | 0.455017 |
import logging
import requests
import numpy as np
FIND_PLACE = "https://maps.googleapis.com/maps/api/place/findplacefromtext/json?"
PLACE_DETAILS = "https://maps.googleapis.com/maps/api/place/details/json?"
def place_by_name(place, key, FIND_PLACE=FIND_PLACE):
"""Finds a Google Place ID by searching with its nam... | fnf/data/geocode.py | import logging
import requests
import numpy as np
FIND_PLACE = "https://maps.googleapis.com/maps/api/place/findplacefromtext/json?"
PLACE_DETAILS = "https://maps.googleapis.com/maps/api/place/details/json?"
def place_by_name(place, key, FIND_PLACE=FIND_PLACE):
"""Finds a Google Place ID by searching with its nam... | 0.688887 | 0.215867 |
import Queue
import atexit
from modules import Gmail
from apscheduler.schedulers.background import BackgroundScheduler
import logging
class Notifier(object):
class NotificationClient(object):
def __init__(self, gather, timestamp):
self.gather = gather
self.timestamp = timestamp
... | jeeves/notifier.py | import Queue
import atexit
from modules import Gmail
from apscheduler.schedulers.background import BackgroundScheduler
import logging
class Notifier(object):
class NotificationClient(object):
def __init__(self, gather, timestamp):
self.gather = gather
self.timestamp = timestamp
... | 0.53777 | 0.125815 |
import asyncio
from os import environ, listdir
from pathlib import Path
from typing import Callable, List
import aiohttp
import discord
from asyncpg import create_pool
from discord import Guild, Role
from discord.ext.commands import Bot, Cog, Context
from loguru import logger
class HolidayBot(Bot):
"""Setting up... | bot/bot.py | import asyncio
from os import environ, listdir
from pathlib import Path
from typing import Callable, List
import aiohttp
import discord
from asyncpg import create_pool
from discord import Guild, Role
from discord.ext.commands import Bot, Cog, Context
from loguru import logger
class HolidayBot(Bot):
"""Setting up... | 0.688364 | 0.134349 |
# %% [markdown]
# To use the date variable in python you need to import package datetime from datetime library
# This is done by using the import statement
# %%
from datetime import datetime
# you can get the current date in python with:
today = datetime.now()
# Like numeric values you need to convert date variable... | introduction/sessions/5-dates.py |
# %% [markdown]
# To use the date variable in python you need to import package datetime from datetime library
# This is done by using the import statement
# %%
from datetime import datetime
# you can get the current date in python with:
today = datetime.now()
# Like numeric values you need to convert date variable... | 0.520253 | 0.399372 |
import mmap
import multiprocessing
import re
from queue import Empty
from imposm.parser.xml.parser import XMLParser
from imposm.parser.util import setproctitle
KiB = 1024
MiB = 1024*KiB
READ_SIZE = 512*KiB
class MMapReader(object):
def __init__(self, m, size):
self.m = m
self.m.seek(0)
... | imposm/parser/xml/multiproc.py |
import mmap
import multiprocessing
import re
from queue import Empty
from imposm.parser.xml.parser import XMLParser
from imposm.parser.util import setproctitle
KiB = 1024
MiB = 1024*KiB
READ_SIZE = 512*KiB
class MMapReader(object):
def __init__(self, m, size):
self.m = m
self.m.seek(0)
... | 0.525125 | 0.189709 |
# Python libs
from __future__ import absolute_import
from dict_tools import differ
import logging
log = logging.getLogger(__name__)
TREQ = {
"present": {"require": ["states.azurerm.resource.group.present",]},
}
async def present(
hub,
ctx,
name,
resource_group,
public_key=None,
generate_... | idem_azurerm/states/azurerm/compute/ssh_public_key.py | # Python libs
from __future__ import absolute_import
from dict_tools import differ
import logging
log = logging.getLogger(__name__)
TREQ = {
"present": {"require": ["states.azurerm.resource.group.present",]},
}
async def present(
hub,
ctx,
name,
resource_group,
public_key=None,
generate_... | 0.865693 | 0.183978 |
import timeit
from datetime import datetime
import socket
import os
import glob
from tqdm import tqdm
import torch
from tensorboardX import SummaryWriter
from torch import nn, optim
from dataloaders.dataset import VideoDataset
from torch.utils.data import DataLoader
from torch.autograd import Variable
from network impo... | train.py | import timeit
from datetime import datetime
import socket
import os
import glob
from tqdm import tqdm
import torch
from tensorboardX import SummaryWriter
from torch import nn, optim
from dataloaders.dataset import VideoDataset
from torch.utils.data import DataLoader
from torch.autograd import Variable
from network impo... | 0.456652 | 0.207817 |
from time import sleep, time
from getpass import getpass
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.chrome.options import Options
from selenium.common.exceptions import NoSuchElementException
from bs4 import BeautifulSoup
def scrape(answer_count):... | scrape.py | from time import sleep, time
from getpass import getpass
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.chrome.options import Options
from selenium.common.exceptions import NoSuchElementException
from bs4 import BeautifulSoup
def scrape(answer_count):... | 0.131326 | 0.085251 |
import datetime
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives import serialization
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography import x509
from cryptography.hazmat.primitives import hashes
from cryptography.x509.oid import NameOID
# pylin... | Tests/py_cert.py | import datetime
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives import serialization
from cryptography.hazmat.primitives.asymmetric import rsa
from cryptography import x509
from cryptography.hazmat.primitives import hashes
from cryptography.x509.oid import NameOID
# pylin... | 0.318061 | 0.145631 |
__all__ = [
'generate_mat_stub',
'generate_mat_typevars',
'generate_mat_unions'
]
import textwrap
from itertools import product
from matrixtype import get_matrix_types, inspect_matrix
from stub import matrix_name, matrix_union, union, vector_name, vector_union
def generate_mat_unions():
for data_typ... | tools/matstub.py | __all__ = [
'generate_mat_stub',
'generate_mat_typevars',
'generate_mat_unions'
]
import textwrap
from itertools import product
from matrixtype import get_matrix_types, inspect_matrix
from stub import matrix_name, matrix_union, union, vector_name, vector_union
def generate_mat_unions():
for data_typ... | 0.547948 | 0.541288 |
__author__ = '<NAME>, <NAME>'
__copyright__ = 'Copyright (C) 2018-2019, Nokia'
__email__ = '<EMAIL>, <EMAIL>'
from moler.cmd.unix.scp import Scp
from moler.exceptions import CommandFailure
import re
import pytest
def test_scp_returns_proper_command_string(buffer_connection):
scp_cmd = Scp(connection=buffer_conne... | test/cmd/unix/test_cmd_scp.py | __author__ = '<NAME>, <NAME>'
__copyright__ = 'Copyright (C) 2018-2019, Nokia'
__email__ = '<EMAIL>, <EMAIL>'
from moler.cmd.unix.scp import Scp
from moler.exceptions import CommandFailure
import re
import pytest
def test_scp_returns_proper_command_string(buffer_connection):
scp_cmd = Scp(connection=buffer_conne... | 0.215929 | 0.147863 |
import argparse
from collections import namedtuple
from functools import partial
from os.path import join, exists
from os import mkdir
import numpy as np
import torch
import torch.utils.data
from torch import optim
from torch.nn import functional as F
from torch.utils.data import DataLoader
from torchvision import tra... | cotrain_vae_mdnrnn_longer_seq.py | import argparse
from collections import namedtuple
from functools import partial
from os.path import join, exists
from os import mkdir
import numpy as np
import torch
import torch.utils.data
from torch import optim
from torch.nn import functional as F
from torch.utils.data import DataLoader
from torchvision import tra... | 0.769167 | 0.338596 |
import json
import logging
from flask import Flask, request
from flask_caching import Cache
from flask_images import Images
from flask_mail import Mail
from .custom_filters import display_publication_info, date_format, w3c_date
FORMAT = '%(asctime)s %(message)s'
fmt = logging.Formatter(FORMAT)
handler = logging.Fil... | server/pubs_ui/__init__.py | import json
import logging
from flask import Flask, request
from flask_caching import Cache
from flask_images import Images
from flask_mail import Mail
from .custom_filters import display_publication_info, date_format, w3c_date
FORMAT = '%(asctime)s %(message)s'
fmt = logging.Formatter(FORMAT)
handler = logging.Fil... | 0.395835 | 0.04736 |
from __future__ import division
import numpy as np
from activation_functions import Sigmoid
def accuracy_score(y_true, y_pred):
accuracy = np.sum(y_true == y_pred) /len(y_true)
return accuracy
class Loss(object):
def loss(self, y_true, y_pred):
return NotImplementedError()
def gradient(sel... | network/loss_functions.py | from __future__ import division
import numpy as np
from activation_functions import Sigmoid
def accuracy_score(y_true, y_pred):
accuracy = np.sum(y_true == y_pred) /len(y_true)
return accuracy
class Loss(object):
def loss(self, y_true, y_pred):
return NotImplementedError()
def gradient(sel... | 0.811303 | 0.589185 |
import sys
import re
import zipfile
BYTE_KB = 1024.0
default_jarfile = 'JavaRosaDemo.jar'
default_obfusmapfile = 'obfuscation_mapping.txt'
default_outfile = 'jar_contents.csv'
#determine sort order of a file
suffix_order = ['class', 'xhtml']
def sort_filename(s):
suffix = s.rsplit('.', 1)[-1]
try:
ordinal = ... | scripts/jar_usage.py |
import sys
import re
import zipfile
BYTE_KB = 1024.0
default_jarfile = 'JavaRosaDemo.jar'
default_obfusmapfile = 'obfuscation_mapping.txt'
default_outfile = 'jar_contents.csv'
#determine sort order of a file
suffix_order = ['class', 'xhtml']
def sort_filename(s):
suffix = s.rsplit('.', 1)[-1]
try:
ordinal = ... | 0.108271 | 0.109539 |