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 |
|---|---|---|---|---|
def CalculateHowManyRelationsWithShortestPathInDataset (Sentences):
POS_NEG_DICT = {"Positives":0 , "Negatives":0};
CLASS_TP_DICT = {"NEG":0} ;
for sentence in Sentences:
for pair in sentence["PAIRS"]:
if (pair.has_key("TOPKP")) and (pair.has_key("TOPKP_Features")):
if ... | ANN_Systems/TSDPTSVMCore/SharedFunctions.py | def CalculateHowManyRelationsWithShortestPathInDataset (Sentences):
POS_NEG_DICT = {"Positives":0 , "Negatives":0};
CLASS_TP_DICT = {"NEG":0} ;
for sentence in Sentences:
for pair in sentence["PAIRS"]:
if (pair.has_key("TOPKP")) and (pair.has_key("TOPKP_Features")):
if ... | 0.147709 | 0.311584 |
import torch
from torch import nn
from core.modules import LayerNorm
from typing import Optional
import torch.nn.functional as F
class UtteranceEncoder(nn.Module):
def __init__(self, idim: int,
n_layers: int = 2,
n_chans: int = 256,
kernel_size: int = 5,
... | core/acoustic_encoder.py | import torch
from torch import nn
from core.modules import LayerNorm
from typing import Optional
import torch.nn.functional as F
class UtteranceEncoder(nn.Module):
def __init__(self, idim: int,
n_layers: int = 2,
n_chans: int = 256,
kernel_size: int = 5,
... | 0.961071 | 0.44089 |
from __future__ import annotations
import collections
import functools
import pickle
import sys
from abc import ABC, abstractmethod
from concurrent.futures.thread import ThreadPoolExecutor
from typing import Callable, Dict, Union, Any, List, Sequence, Optional
import json
import logging
import re
import threading
fro... | src/sensai/util/cache_azure.py | from __future__ import annotations
import collections
import functools
import pickle
import sys
from abc import ABC, abstractmethod
from concurrent.futures.thread import ThreadPoolExecutor
from typing import Callable, Dict, Union, Any, List, Sequence, Optional
import json
import logging
import re
import threading
fro... | 0.781247 | 0.200675 |
from commons.conversion import utc_timestamp_to_datetime
from commons.model import Model
def build_weather_5_day_forecast_object(weather_dict):
"""
:type weather_dict:
:rtype: commons.weather.Weather5DayForecast
"""
forecast_timestamp = int(weather_dict.get("dt"))
temperature = float(weather_d... | commons/commons/weather.py | from commons.conversion import utc_timestamp_to_datetime
from commons.model import Model
def build_weather_5_day_forecast_object(weather_dict):
"""
:type weather_dict:
:rtype: commons.weather.Weather5DayForecast
"""
forecast_timestamp = int(weather_dict.get("dt"))
temperature = float(weather_d... | 0.814201 | 0.227008 |
import pytz
from django.conf import settings
from django.test import TestCase
from unittest.mock import patch
# Import module
from backend.exporter import *
class ExportFilterTest(TestCase):
def setUp(self) -> None:
"""
Create a folder, clip, project and filter.
"""
self.rid = cr... | backend/test/test_integration/test_exporter.py | import pytz
from django.conf import settings
from django.test import TestCase
from unittest.mock import patch
# Import module
from backend.exporter import *
class ExportFilterTest(TestCase):
def setUp(self) -> None:
"""
Create a folder, clip, project and filter.
"""
self.rid = cr... | 0.394551 | 0.357147 |
import unittest
from BlastApi import BlastSearchValidator
from tests.Validator.TestCase import TestCase, _NOT_NONE_ERROR, _NOT_EMPTY_ERROR, _PROGRAMS, _INVALID_ERROR
class BlastSearchValidatorTest(TestCase):
validator = BlastSearchValidator()
def test_required_params(self):
params = {'QUERY': 'test'... | tests/Validator/BlastSearchValidatorTest.py | import unittest
from BlastApi import BlastSearchValidator
from tests.Validator.TestCase import TestCase, _NOT_NONE_ERROR, _NOT_EMPTY_ERROR, _PROGRAMS, _INVALID_ERROR
class BlastSearchValidatorTest(TestCase):
validator = BlastSearchValidator()
def test_required_params(self):
params = {'QUERY': 'test'... | 0.531209 | 0.39289 |
from PIL import Image, ImageDraw, ImageFont # pip install pillow
import numpy
import cv2
import sys, os
FONT_MARGIN = 2
COLOR_MAP = {
'1': (255, 35, 11),
'0': (16, 194, 20),
'C': (136, 0, 21),
'D': (7, 92, 10)}
OUTPATH = 'output'
def get_attr(info, default=None, isBoolean=False):
value = in... | zealots/zealots_animation_maker.py | from PIL import Image, ImageDraw, ImageFont # pip install pillow
import numpy
import cv2
import sys, os
FONT_MARGIN = 2
COLOR_MAP = {
'1': (255, 35, 11),
'0': (16, 194, 20),
'C': (136, 0, 21),
'D': (7, 92, 10)}
OUTPATH = 'output'
def get_attr(info, default=None, isBoolean=False):
value = in... | 0.156911 | 0.170473 |
import argparse
import os, sys
import random, struct
import cPickle as pickle
import time, socket, select
from Queue import Queue
from threading import Thread, RLock, Lock, Condition, Timer, Semaphore
from concoord.enums import *
from concoord.nameserver import Nameserver
from concoord.exception import ConnectionError
... | concoord/node.py | import argparse
import os, sys
import random, struct
import cPickle as pickle
import time, socket, select
from Queue import Queue
from threading import Thread, RLock, Lock, Condition, Timer, Semaphore
from concoord.enums import *
from concoord.nameserver import Nameserver
from concoord.exception import ConnectionError
... | 0.238284 | 0.060641 |
from typing import Optional
from aiogram.types import Update
from aiogram.types import ParseMode
from aiogram.utils.exceptions import MessageCantBeDeleted
from aiogram.utils.exceptions import MessageCantBeEdited
from aiogram.utils.exceptions import MessageIdInvalid
from aiogram.utils.exceptions import MessageNotModif... | bot/platforms/telegram/commands/creator/errors_handler.py | from typing import Optional
from aiogram.types import Update
from aiogram.types import ParseMode
from aiogram.utils.exceptions import MessageCantBeDeleted
from aiogram.utils.exceptions import MessageCantBeEdited
from aiogram.utils.exceptions import MessageIdInvalid
from aiogram.utils.exceptions import MessageNotModif... | 0.656988 | 0.206494 |
import os
import ctypes
import pyttsx3
import speech_recognition as sr
import math
import traceback
from pyttsx3.drivers import sapi5
import random
import threading
import datetime
import PySimpleGUI as sg
from stat import S_IWUSR, S_IREAD
import matplotlib.pyplot as plt
import wx
global log
try:
fr... | Diagnostify.py | import os
import ctypes
import pyttsx3
import speech_recognition as sr
import math
import traceback
from pyttsx3.drivers import sapi5
import random
import threading
import datetime
import PySimpleGUI as sg
from stat import S_IWUSR, S_IREAD
import matplotlib.pyplot as plt
import wx
global log
try:
fr... | 0.38769 | 0.144179 |
import os
import shutil
import subprocess
from pathlib import Path
output_dir = "projects/fs_vid2vid/output/face_forensics"
def preprocess(image_path, video_path):
test_data_dir = "projects/fs_vid2vid/test_data/faceForensics"
video_filename, video_parent = Path(video_path).stem, Path(video_path).parent
... | src/fsvid2vid.py | import os
import shutil
import subprocess
from pathlib import Path
output_dir = "projects/fs_vid2vid/output/face_forensics"
def preprocess(image_path, video_path):
test_data_dir = "projects/fs_vid2vid/test_data/faceForensics"
video_filename, video_parent = Path(video_path).stem, Path(video_path).parent
... | 0.438064 | 0.286219 |
import os
from instascrape.utils import to_datetime
from instascrape.commands import COOKIES_DIR, error_print, dump_cookie, load_cookie, load_obj
from colorama import Fore, Style
def cookies_handler(**args):
action = args.get("action")
insta = load_obj()
cookies = [f for f in os.listdir(COOKIES_DIR) if ... | instascrape/commands/cookies.py | import os
from instascrape.utils import to_datetime
from instascrape.commands import COOKIES_DIR, error_print, dump_cookie, load_cookie, load_obj
from colorama import Fore, Style
def cookies_handler(**args):
action = args.get("action")
insta = load_obj()
cookies = [f for f in os.listdir(COOKIES_DIR) if ... | 0.053837 | 0.093927 |
import argparse
import contextlib
import errno
import io
import json
import os
import re
import shutil
import subprocess
import sys
import tempfile
import time
import unittest
sys.path.append(os.path.join(os.path.dirname(sys.argv[0]), os.path.pardir))
import backups_lib
__package__ = backups_lib.__package__
from . i... | checkpoint_lib_test.py |
import argparse
import contextlib
import errno
import io
import json
import os
import re
import shutil
import subprocess
import sys
import tempfile
import time
import unittest
sys.path.append(os.path.join(os.path.dirname(sys.argv[0]), os.path.pardir))
import backups_lib
__package__ = backups_lib.__package__
from . i... | 0.296349 | 0.168823 |
__version__ = "1.0"
__author__ = "<NAME>"
__copyright__ = "Copyright 2021, <NAME>"
__license__ = "Apache 2.0"
import pyaudio, serial, time
from scipy.interpolate import interp1d
from numpy import cos, pi, zeros, frombuffer, float32, roll, average
from acoustic_trilateration import get_time_shift, trilateration, butte... | acoustic_fixture/acoustic_fixture.py | __version__ = "1.0"
__author__ = "<NAME>"
__copyright__ = "Copyright 2021, <NAME>"
__license__ = "Apache 2.0"
import pyaudio, serial, time
from scipy.interpolate import interp1d
from numpy import cos, pi, zeros, frombuffer, float32, roll, average
from acoustic_trilateration import get_time_shift, trilateration, butte... | 0.338514 | 0.199756 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
import tensorflow as tf
def reshape_array_and_save_to_path(arr_data, arr_label, path, timesteps, target_hour, data_type="Train"):
# reshaping the array from 3D
# matrice to 2D matrice.
arr_data_reshaped = arr_data.resha... | src/data/create_load_transform_processed_data.py | import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
import tensorflow as tf
def reshape_array_and_save_to_path(arr_data, arr_label, path, timesteps, target_hour, data_type="Train"):
# reshaping the array from 3D
# matrice to 2D matrice.
arr_data_reshaped = arr_data.resha... | 0.404625 | 0.534248 |
from moviepy.editor import *
import cv2
from utils.image_utils import *
import math
class Gif_TO_VIDEO(object):
def __init__(self, gifs_path, bgm_path):
# gif目录
self.gifs_path = gifs_path
# BGM目录
self.bgm_path = bgm_path
# 视频帧率
self.fps = 10
self.img_size... | video_auto/制作GIF视频/gif_make_video.py | from moviepy.editor import *
import cv2
from utils.image_utils import *
import math
class Gif_TO_VIDEO(object):
def __init__(self, gifs_path, bgm_path):
# gif目录
self.gifs_path = gifs_path
# BGM目录
self.bgm_path = bgm_path
# 视频帧率
self.fps = 10
self.img_size... | 0.187467 | 0.131563 |
from tkinter import ttk
import tkinter as tk
import cartopy.crs as ccrs
import eosim.gui.helpwindow as helpwindow
class Mercator(ttk.Frame):
def __init__(self, parent, controller):
ttk.Frame.__init__(self, parent)
mercator_proj_frame = ttk.Frame(self)
mercator_proj_frame.grid(row... | eosim/gui/mapprojections.py | from tkinter import ttk
import tkinter as tk
import cartopy.crs as ccrs
import eosim.gui.helpwindow as helpwindow
class Mercator(ttk.Frame):
def __init__(self, parent, controller):
ttk.Frame.__init__(self, parent)
mercator_proj_frame = ttk.Frame(self)
mercator_proj_frame.grid(row... | 0.506591 | 0.211946 |
# <pep8 compliant>
# Generic Panels (Independent of DataType)
# NOTE:
# The specialized panel types are derived in their respective UI modules
# don't register these classes since they are only helpers.
class MotionPathButtonsPanel():
bl_space_type = 'PROPERTIES'
bl_region_type = 'WINDOW'
bl_label = "M... | release/scripts/startup/bl_ui/properties_animviz.py |
# <pep8 compliant>
# Generic Panels (Independent of DataType)
# NOTE:
# The specialized panel types are derived in their respective UI modules
# don't register these classes since they are only helpers.
class MotionPathButtonsPanel():
bl_space_type = 'PROPERTIES'
bl_region_type = 'WINDOW'
bl_label = "M... | 0.31279 | 0.225214 |
import numpy as np
from skimage import io, color, exposure, transform
from sklearn.model_selection import train_test_split
import os
import glob
import h5py
import numpy as np
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.layers import Activation
from tensorflow.keras.models... | train_gtsrb.py | import numpy as np
from skimage import io, color, exposure, transform
from sklearn.model_selection import train_test_split
import os
import glob
import h5py
import numpy as np
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.layers import Activation
from tensorflow.keras.models... | 0.667473 | 0.404978 |
from typing import Iterable, Optional, TypeVar
from stock_indicators._cslib import CsIndicator
from stock_indicators._cstypes import List as CsList
from stock_indicators.indicators.common.results import IndicatorResults, ResultBase
from stock_indicators.indicators.common.quote import Quote
def get_prs(base_history: ... | stock_indicators/indicators/prs.py | from typing import Iterable, Optional, TypeVar
from stock_indicators._cslib import CsIndicator
from stock_indicators._cstypes import List as CsList
from stock_indicators.indicators.common.results import IndicatorResults, ResultBase
from stock_indicators.indicators.common.quote import Quote
def get_prs(base_history: ... | 0.947491 | 0.499207 |
from thrift.Thrift import TType, TMessageType, TException, TApplicationException
from ttypes import *
from thrift.Thrift import TProcessor
from thrift.transport import TTransport
from thrift.protocol import TBinaryProtocol, TProtocol
try:
from thrift.protocol import fastbinary
except:
fastbinary = None
class Ifa... | examples/python/flurry/Flurry.py |
from thrift.Thrift import TType, TMessageType, TException, TApplicationException
from ttypes import *
from thrift.Thrift import TProcessor
from thrift.transport import TTransport
from thrift.protocol import TBinaryProtocol, TProtocol
try:
from thrift.protocol import fastbinary
except:
fastbinary = None
class Ifa... | 0.485112 | 0.065665 |
import logging
import tensorflow as tf
class AlexNet:
SEED = 42
def __init__(self, nb_classes=3):
self.initializer = tf.initializers.glorot_uniform(seed=AlexNet.SEED)
self.weight_shapes = [
[11, 11, 1, 96],
[5, 5, 96, 256],
[3, 3, 256, 384],
[... | deep_cluster/convnet/alexnet.py | import logging
import tensorflow as tf
class AlexNet:
SEED = 42
def __init__(self, nb_classes=3):
self.initializer = tf.initializers.glorot_uniform(seed=AlexNet.SEED)
self.weight_shapes = [
[11, 11, 1, 96],
[5, 5, 96, 256],
[3, 3, 256, 384],
[... | 0.890574 | 0.35782 |
import numpy as np
import pandas as pd
import csv
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.linear_model import LogisticRegression
# Load data about each article in a dataframe
df = pd.read_csv("Data/node_information.csv")
print(df.head())
# Read training data
train_ids = list()
y_train... | text_baseline.py | import numpy as np
import pandas as pd
import csv
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.linear_model import LogisticRegression
# Load data about each article in a dataframe
df = pd.read_csv("Data/node_information.csv")
print(df.head())
# Read training data
train_ids = list()
y_train... | 0.629547 | 0.439026 |
import os
import sys
import h5py
from matplotlib import rcParams
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
from presto.utils import rotate_opt
rcParams['figure.dpi'] = 108.8
if len(sys.argv) == 2:
load_filename = sys.argv[1]
print(f"Loading: {os.path.realpath(lo... | load_ramsey.py | import os
import sys
import h5py
from matplotlib import rcParams
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
from presto.utils import rotate_opt
rcParams['figure.dpi'] = 108.8
if len(sys.argv) == 2:
load_filename = sys.argv[1]
print(f"Loading: {os.path.realpath(lo... | 0.400398 | 0.36077 |
from odin.utils.trainable_models import TrainableModel
from odin.utils.gaussian_processes import GaussianProcess
from odin.utils.tensorflow_optimizer import ExtendedScipyOptimizerInterface
import numpy as np
import tensorflow as tf
from typing import Union, Tuple
import time
class ODERiskMinimization(object):
"""
... | odin/core/ODE_risk_minimization.py | from odin.utils.trainable_models import TrainableModel
from odin.utils.gaussian_processes import GaussianProcess
from odin.utils.tensorflow_optimizer import ExtendedScipyOptimizerInterface
import numpy as np
import tensorflow as tf
from typing import Union, Tuple
import time
class ODERiskMinimization(object):
"""
... | 0.906473 | 0.529385 |
import datetime
import traceback
# this is modified code from a private project
class Lesson:
def __init__(
self,
name: str,
teacher: str,
ausfall: bool,
student_id: int,
student_data: dict,
):
self.data = {}
self.deletion_candiate = False
... | demonstration_bot/stundenplan.py | import datetime
import traceback
# this is modified code from a private project
class Lesson:
def __init__(
self,
name: str,
teacher: str,
ausfall: bool,
student_id: int,
student_data: dict,
):
self.data = {}
self.deletion_candiate = False
... | 0.285671 | 0.272761 |
import sys
sys.path.append('../utils')
from ops import dense_sum_list, get_shape
from np_op import convert2list
import tensorflow as tf
import numpy as np
import os
def test1(id_=0):
''' dense_sum_list test
Results :
=================Round1===================
const : [4, 2]
[[ 1. ... | tfops/ops_test.py | import sys
sys.path.append('../utils')
from ops import dense_sum_list, get_shape
from np_op import convert2list
import tensorflow as tf
import numpy as np
import os
def test1(id_=0):
''' dense_sum_list test
Results :
=================Round1===================
const : [4, 2]
[[ 1. ... | 0.270095 | 0.332852 |
from dataclasses import dataclass
from datetime import date, datetime
import mock
from pdfminer.layout import LTChar, LTCurve, LTFigure, LTImage, LTTextBoxHorizontal, LTTextLineHorizontal
from typing import List
from rdr_service.services.consent import files
from tests.helpers.unittest_base import BaseTestCase
class... | tests/service_tests/consent_tests/test_consent_file_parsing.py | from dataclasses import dataclass
from datetime import date, datetime
import mock
from pdfminer.layout import LTChar, LTCurve, LTFigure, LTImage, LTTextBoxHorizontal, LTTextLineHorizontal
from typing import List
from rdr_service.services.consent import files
from tests.helpers.unittest_base import BaseTestCase
class... | 0.832951 | 0.174445 |
import os
import re
import platform
from datetime import datetime, timezone, timedelta, date
import requests
from bs4 import BeautifulSoup
from selenium import webdriver
from selenium.webdriver.support import expected_conditions
from selenium.webdriver.common.by import By
from selenium.webdriver.support.wait import W... | MovieScheduleParser/parser.py | import os
import re
import platform
from datetime import datetime, timezone, timedelta, date
import requests
from bs4 import BeautifulSoup
from selenium import webdriver
from selenium.webdriver.support import expected_conditions
from selenium.webdriver.common.by import By
from selenium.webdriver.support.wait import W... | 0.63307 | 0.092196 |
from apps.bot.classes.Command import Command
from apps.bot.classes.consts.Consts import Role
from apps.service.models import MilanaTranslate
class Discord(Command):
name = "милана"
names = ["милок", "мил"]
help_text = "переводчик с языка Миланы"
help_texts = [
"- (пересланное сообщение) - пер... | apps/bot/commands/TrustedCommands/Milana.py | from apps.bot.classes.Command import Command
from apps.bot.classes.consts.Consts import Role
from apps.service.models import MilanaTranslate
class Discord(Command):
name = "милана"
names = ["милок", "мил"]
help_text = "переводчик с языка Миланы"
help_texts = [
"- (пересланное сообщение) - пер... | 0.365117 | 0.178114 |
__author__ = "<NAME>"
__version__ = "CS224u, Stanford, Spring 2016"
import sys
import csv
import numpy as np
import torch
def build(src_filename, delimiter=',', header=True, quoting=csv.QUOTE_MINIMAL):
"""Reads in matrices from CSV or space-delimited files.
Parameters
----------
src_filename : str
... | glove_utils.py |
__author__ = "<NAME>"
__version__ = "CS224u, Stanford, Spring 2016"
import sys
import csv
import numpy as np
import torch
def build(src_filename, delimiter=',', header=True, quoting=csv.QUOTE_MINIMAL):
"""Reads in matrices from CSV or space-delimited files.
Parameters
----------
src_filename : str
... | 0.696991 | 0.454291 |
import tilemapbase as tmb
import matplotlib.pyplot as plt
import matplotlib.lines as lines
import folium
from .maputil import copyright_osm
import numpy as np
import re
tmb.init(create=True)
def _extend(m, M, p):
w = M - m
return m - p*w, M + p*w
def _expand(ex, p):
xmin, xmax = _extend(ex.xmin, ex.xma... | dtws1/trajectory.py | import tilemapbase as tmb
import matplotlib.pyplot as plt
import matplotlib.lines as lines
import folium
from .maputil import copyright_osm
import numpy as np
import re
tmb.init(create=True)
def _extend(m, M, p):
w = M - m
return m - p*w, M + p*w
def _expand(ex, p):
xmin, xmax = _extend(ex.xmin, ex.xma... | 0.410166 | 0.404802 |
from ..utils import file_json_utils as json_util
def get_review_threads_by_pr(pr_detail_file_path):
reply_review_inline_comment_template = {"id": "id", "url": "url", "bodyText": "bodyText", "author": "author.login",
"createdAt": "createdAt", "replyToReviewId": "replyTo.id"}
... | lib/github/PRsDataManager.py | from ..utils import file_json_utils as json_util
def get_review_threads_by_pr(pr_detail_file_path):
reply_review_inline_comment_template = {"id": "id", "url": "url", "bodyText": "bodyText", "author": "author.login",
"createdAt": "createdAt", "replyToReviewId": "replyTo.id"}
... | 0.233532 | 0.16228 |
from marshmallow import Schema, fields, validate, pre_load, ValidationError
import ipaddress
class NETunnelSchema(Schema):
"""
Base schema for netunnel objects
For backwards compatibility to marshmallow 2.X, we're using self.dump3 and self.load3 instead
of self.dump & self.load to make them as similar as possib... | netunnel/server/schemas.py | from marshmallow import Schema, fields, validate, pre_load, ValidationError
import ipaddress
class NETunnelSchema(Schema):
"""
Base schema for netunnel objects
For backwards compatibility to marshmallow 2.X, we're using self.dump3 and self.load3 instead
of self.dump & self.load to make them as similar as possib... | 0.511229 | 0.21032 |
from _math import Vector3
from timeit import itertools
from elements import GeneratorElement
from interactions.constraints import Circle, Constraint, create_constraint_set
from interactions.utils.routing import PlanRoute, FollowPath
from objects.components.types import ROUTING_COMPONENT
from server_commands.argument_he... | S4/S4 Library/simulation/routing/routing_commands.py | from _math import Vector3
from timeit import itertools
from elements import GeneratorElement
from interactions.constraints import Circle, Constraint, create_constraint_set
from interactions.utils.routing import PlanRoute, FollowPath
from objects.components.types import ROUTING_COMPONENT
from server_commands.argument_he... | 0.524882 | 0.167389 |
import unittest
from source.utilities.transformer import Transformer
from source.utilities.graph import Graph
from source.utilities.solver import Solver
from source.dataStructures import Vector
class Solver_test(unittest.TestCase):
def test_solver_can_check_for_a_solution(self):
(zeroGraph, vectorLi... | source/tests/solver_test.py | import unittest
from source.utilities.transformer import Transformer
from source.utilities.graph import Graph
from source.utilities.solver import Solver
from source.dataStructures import Vector
class Solver_test(unittest.TestCase):
def test_solver_can_check_for_a_solution(self):
(zeroGraph, vectorLi... | 0.557123 | 0.627723 |
import os
from PIL import Image
import numpy as np
from scipy.interpolate import griddata
import cv2
import argparse
def getSymXYcoordinates(iuv, resolution=256, dp_uv_lookup_256_np=None):
if dp_uv_lookup_256_np is None:
dp_uv_lookup_256_np = np.load('util/dp_uv_lookup_256.npy')
xy, xyMask = getXYcoor(... | util/dp2coor.py | import os
from PIL import Image
import numpy as np
from scipy.interpolate import griddata
import cv2
import argparse
def getSymXYcoordinates(iuv, resolution=256, dp_uv_lookup_256_np=None):
if dp_uv_lookup_256_np is None:
dp_uv_lookup_256_np = np.load('util/dp_uv_lookup_256.npy')
xy, xyMask = getXYcoor(... | 0.397003 | 0.320449 |
import os
from enum import IntEnum
import random
import re
import time
from study_tool.card import Card, CardSide, SourceLocation
from study_tool.card_attributes import CardAttributes
from study_tool.external import googledocs
from study_tool.russian.types import *
from study_tool.russian.word import *
from study_tool.... | study_tool/card_set.py | import os
from enum import IntEnum
import random
import re
import time
from study_tool.card import Card, CardSide, SourceLocation
from study_tool.card_attributes import CardAttributes
from study_tool.external import googledocs
from study_tool.russian.types import *
from study_tool.russian.word import *
from study_tool.... | 0.602529 | 0.153708 |
from knowledge_graph.graph_indexer import GraphIndexer
from knowledge_graph.config import DB_IDS
class SimilarityWeightsTest(GraphIndexer):
"""
Used to create the relations (calls the insert for every article)
Used to test the relations
"""
def __init__(self, db_ids):
GraphIndexer.__init... | scripts/index_article_graph.py | from knowledge_graph.graph_indexer import GraphIndexer
from knowledge_graph.config import DB_IDS
class SimilarityWeightsTest(GraphIndexer):
"""
Used to create the relations (calls the insert for every article)
Used to test the relations
"""
def __init__(self, db_ids):
GraphIndexer.__init... | 0.610802 | 0.219515 |
START = """
Hey 🌍!! Tudo tranquilo??
Bem vindo ao Corona-Tracker!
Para visualizar os comandos, registre-se em nossa base com o comando /register.
"""
# =============================================================================
# REGISTER MESSAGE
# =================================================================... | code/constants/conversations.py |
START = """
Hey 🌍!! Tudo tranquilo??
Bem vindo ao Corona-Tracker!
Para visualizar os comandos, registre-se em nossa base com o comando /register.
"""
# =============================================================================
# REGISTER MESSAGE
# =================================================================... | 0.278551 | 0.34054 |
import ast
import pycodestyle
from flake8 import utils as stdin_utils
__version__ = "0.1.0"
ERROR_CODE = "OW100"
class OsWalkVisitor(ast.NodeVisitor):
def __init__(self, *args, **kwargs):
super(OsWalkVisitor, self).__init__(*args, **kwargs)
self.violations = []
def visit_Call(self, node):
... | flake8_os_walk/checker.py | import ast
import pycodestyle
from flake8 import utils as stdin_utils
__version__ = "0.1.0"
ERROR_CODE = "OW100"
class OsWalkVisitor(ast.NodeVisitor):
def __init__(self, *args, **kwargs):
super(OsWalkVisitor, self).__init__(*args, **kwargs)
self.violations = []
def visit_Call(self, node):
... | 0.449876 | 0.106924 |
from collections.abc import Mapping, Sequence
class EventFilter:
def __init__(self, tags=None, event_type=None, routing_key=None):
self.tags = frozenset(tags) if tags is not None else tags
self.event_type = frozenset(event_type) if event_type is not None else event_type
self.routing_key = ... | zentral/core/events/filter.py | from collections.abc import Mapping, Sequence
class EventFilter:
def __init__(self, tags=None, event_type=None, routing_key=None):
self.tags = frozenset(tags) if tags is not None else tags
self.event_type = frozenset(event_type) if event_type is not None else event_type
self.routing_key = ... | 0.867864 | 0.118131 |
from pydes.core.simulation.model.controller import ControllerAlgorithm
from pydes.core.simulation.model.scope import SystemScope, TaskScope
from pydes.core.utils.csv_utils import read_csv
from pydes.core.utils.report import SimpleReport as Report
INDICES = ["population", "response", "throughput"]
SYSTEM_SCOPES = [scop... | src/pydes/core/simulation/result_validator.py | from pydes.core.simulation.model.controller import ControllerAlgorithm
from pydes.core.simulation.model.scope import SystemScope, TaskScope
from pydes.core.utils.csv_utils import read_csv
from pydes.core.utils.report import SimpleReport as Report
INDICES = ["population", "response", "throughput"]
SYSTEM_SCOPES = [scop... | 0.769124 | 0.468365 |
import rclpy
from rclpy.node import Node
from darknet_ros_msgs.msg import BoundingBoxes
from object_analytics_msgs.msg import TrackedObjects, TrackedObject
from sensor_msgs.msg import RegionOfInterest
from object_tracking.tracking import Tracker
class ObjectTrackingNode(Node):
def __init__(self):
super(... | src/object_tracking/object_tracking_node.py | import rclpy
from rclpy.node import Node
from darknet_ros_msgs.msg import BoundingBoxes
from object_analytics_msgs.msg import TrackedObjects, TrackedObject
from sensor_msgs.msg import RegionOfInterest
from object_tracking.tracking import Tracker
class ObjectTrackingNode(Node):
def __init__(self):
super(... | 0.636353 | 0.178974 |
from pyspark.ml.pipeline import Pipeline as SparkPipeline
from pyspark.ml.feature import OneHotEncoder, StandardScaler, MinMaxScaler, OneHotEncoderEstimator
from pyspark.ml.feature import PCA, Imputer
from pyspark.ml.feature import VectorAssembler, StringIndexer
def since(version):
"""
A decorator that annot... | transformer.py |
from pyspark.ml.pipeline import Pipeline as SparkPipeline
from pyspark.ml.feature import OneHotEncoder, StandardScaler, MinMaxScaler, OneHotEncoderEstimator
from pyspark.ml.feature import PCA, Imputer
from pyspark.ml.feature import VectorAssembler, StringIndexer
def since(version):
"""
A decorator that annot... | 0.883198 | 0.390534 |
from tkinter import Tk, Toplevel, RAISED, Button, Label, messagebox, Entry, PhotoImage, Radiobutton, StringVar ,INSERT, scrolledtext
import functions, pprint, io, contextlib
#Functions
def openWindow(windowName):
mainWindow.withdraw()
if (windowName == "infoMsgBox"):
mainWindow.deiconify()
messagebox.showinfo("I... | main.py | from tkinter import Tk, Toplevel, RAISED, Button, Label, messagebox, Entry, PhotoImage, Radiobutton, StringVar ,INSERT, scrolledtext
import functions, pprint, io, contextlib
#Functions
def openWindow(windowName):
mainWindow.withdraw()
if (windowName == "infoMsgBox"):
mainWindow.deiconify()
messagebox.showinfo("I... | 0.192539 | 0.114369 |
import warnings
import numpy as np
import scipy.sparse as sp
def flip_adj(adj, flips, undirected=True):
if isinstance(adj, (np.ndarray, np.matrix)):
if undirected:
flips = np.vstack([flips, flips[:, [1,0]]])
return flip_x(adj, flips)
elif not sp.isspmatrix(adj):
raise Value... | graphadv/utils/data_utils.py | import warnings
import numpy as np
import scipy.sparse as sp
def flip_adj(adj, flips, undirected=True):
if isinstance(adj, (np.ndarray, np.matrix)):
if undirected:
flips = np.vstack([flips, flips[:, [1,0]]])
return flip_x(adj, flips)
elif not sp.isspmatrix(adj):
raise Value... | 0.569972 | 0.588505 |
from .constants import PDS_NS_URI, PRODUCT_COLLECTION_TAG
from lxml import etree
import logging, hashlib, os.path, functools, urllib, re
# Logging
# -------
_logger = logging.getLogger(__name__)
# Private Constants
# -----------------
_bufsiz = 512 # Byte buffer
_xmlCache... | src/pds/aipgen/utils.py | from .constants import PDS_NS_URI, PRODUCT_COLLECTION_TAG
from lxml import etree
import logging, hashlib, os.path, functools, urllib, re
# Logging
# -------
_logger = logging.getLogger(__name__)
# Private Constants
# -----------------
_bufsiz = 512 # Byte buffer
_xmlCache... | 0.559531 | 0.122313 |
from __future__ import unicode_literals
import frappe
from frappe import msgprint, _
from datetime import date, timedelta,time
def execute(filters=None):
columns, data = [], []
planned_bc_count = planned_cl_count = 0
qr_details = get_qr_details(filters.shift_type,filters.date)
columns = [
_("L... | thaisummit/thaisummit/report/qr_checkin_report/qr_checkin_report.py |
from __future__ import unicode_literals
import frappe
from frappe import msgprint, _
from datetime import date, timedelta,time
def execute(filters=None):
columns, data = [], []
planned_bc_count = planned_cl_count = 0
qr_details = get_qr_details(filters.shift_type,filters.date)
columns = [
_("L... | 0.321993 | 0.109491 |
import heapq
import random
from typing import Dict, List, NamedTuple, Tuple
from torch.utils.data import Sampler
from utils import ceildiv
class DeviceBucket(NamedTuple):
"""
Metadata for a device within a particular TokenBucket
"""
total_length: int # must be first so heap sorts based on it
d... | data/sampler.py | import heapq
import random
from typing import Dict, List, NamedTuple, Tuple
from torch.utils.data import Sampler
from utils import ceildiv
class DeviceBucket(NamedTuple):
"""
Metadata for a device within a particular TokenBucket
"""
total_length: int # must be first so heap sorts based on it
d... | 0.884371 | 0.34981 |
from sklearn.tree.export import _DOTTreeExporter
from sklearn.tree import _tree
from sklearn.ensemble import IsolationForest
from io import StringIO
import numpy as np
class _DOTIFTreeExporter(_DOTTreeExporter):
def __init__(self, meta_data, out_file=None):
super().__init__(out_file=out_file,
... | ifgraphviz/ifgraphviz.py | from sklearn.tree.export import _DOTTreeExporter
from sklearn.tree import _tree
from sklearn.ensemble import IsolationForest
from io import StringIO
import numpy as np
class _DOTIFTreeExporter(_DOTTreeExporter):
def __init__(self, meta_data, out_file=None):
super().__init__(out_file=out_file,
... | 0.595257 | 0.246363 |
import os
import random
import discord
from discord.ext import commands
class ExamCommands(commands.Cog):
def __init__(self, client):
self.client = client
@staticmethod
def write_data(data):
with open('data.txt', 'a+') as file:
for key, value in data.items():
file.write(f'{key}: {value}\n')
@staticme... | cogs/ExamCommands.py | import os
import random
import discord
from discord.ext import commands
class ExamCommands(commands.Cog):
def __init__(self, client):
self.client = client
@staticmethod
def write_data(data):
with open('data.txt', 'a+') as file:
for key, value in data.items():
file.write(f'{key}: {value}\n')
@staticme... | 0.084533 | 0.089973 |
import json
import aiohttp
from aquavalet import streams, provider, exceptions
from aquavalet.providers.utils import require_group, require_match
message_no_internal_provider = "No internal provider in url, path must follow pattern ^\/(?P<internal_provider>(?:\w|\d)+)?\/(?P<resource>[a-zA-Z0-9]{5,})?(?P<path>\/.*)?"
... | aquavalet/providers/osfstyle/provider.py | import json
import aiohttp
from aquavalet import streams, provider, exceptions
from aquavalet.providers.utils import require_group, require_match
message_no_internal_provider = "No internal provider in url, path must follow pattern ^\/(?P<internal_provider>(?:\w|\d)+)?\/(?P<resource>[a-zA-Z0-9]{5,})?(?P<path>\/.*)?"
... | 0.407687 | 0.081739 |
from __future__ import unicode_literals
from django.db import models, migrations
import bitfield.models
import django.core.validators
import mptt.fields
import uuidfield.fields
import timezone_field.fields
class Migration(migrations.Migration):
dependencies = [
]
operations = [
migrations.Creat... | geo/migrations/0001_initial.py | from __future__ import unicode_literals
from django.db import models, migrations
import bitfield.models
import django.core.validators
import mptt.fields
import uuidfield.fields
import timezone_field.fields
class Migration(migrations.Migration):
dependencies = [
]
operations = [
migrations.Creat... | 0.569254 | 0.167763 |
import RPi.GPIO as GPIO
import queue, threading
class LedBeeper:
"""
Handler-Klasse für die LED und den Piepser. Empfängt die Messwerte vom Ultraschallsensor und
lässt die LED und den Piepser immer schneller blinken und tönen, je geringer der Abstand ist.
Regaiert auf folgende Ereignisse:
... | 03 Python/Einparkhilfe/loesung/src/myapp/hardware/led_beeper.py | import RPi.GPIO as GPIO
import queue, threading
class LedBeeper:
"""
Handler-Klasse für die LED und den Piepser. Empfängt die Messwerte vom Ultraschallsensor und
lässt die LED und den Piepser immer schneller blinken und tönen, je geringer der Abstand ist.
Regaiert auf folgende Ereignisse:
... | 0.576423 | 0.228167 |
import os
import boto3
import structlog
from cfn_custom_resource import CloudFormationCustomResource
from _metadata import CUSTOM_RESOURCE_NAME
REGION = os.environ['AWS_REGION']
structlog.configure(processors=[structlog.processors.JSONRenderer()])
def dict_element_copy_if_exists(
source_dict: dict, source... | lambda_code/ec2/FindAmi/index.py | import os
import boto3
import structlog
from cfn_custom_resource import CloudFormationCustomResource
from _metadata import CUSTOM_RESOURCE_NAME
REGION = os.environ['AWS_REGION']
structlog.configure(processors=[structlog.processors.JSONRenderer()])
def dict_element_copy_if_exists(
source_dict: dict, source... | 0.327131 | 0.068819 |
import datetime
import scrapy.http
from event.items import EventItem
import event.util as util
class SoleburyTroutEventPipeline(object):
def process_item(self, item, spider):
def parseDate(datestring):
m_name, d, y = datestring.replace(',', '').split()
m = datetime.datetime.str... | event/event/spiders/solebury_trout/pipelines.py | import datetime
import scrapy.http
from event.items import EventItem
import event.util as util
class SoleburyTroutEventPipeline(object):
def process_item(self, item, spider):
def parseDate(datestring):
m_name, d, y = datestring.replace(',', '').split()
m = datetime.datetime.str... | 0.168891 | 0.149252 |
import argparse
import os
import codecs
import datetime
from html.parser import HTMLParser
from html.entities import name2codepoint
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine, Integer, DateTime, Text, String, Column
name2code... | history_converter.py |
import argparse
import os
import codecs
import datetime
from html.parser import HTMLParser
from html.entities import name2codepoint
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine, Integer, DateTime, Text, String, Column
name2code... | 0.352871 | 0.107134 |
# [START imports]
import os
import urllib
from google.appengine.ext import ndb
from google.appengine.api import app_identity
import logging
import os
import jinja2
import webapp2
import uuid
import StringIO
from PIL import Image
from PIL import ImageFont
from PIL import ImageDraw
JINJA_ENVIRONMENT = jinja2.Enviro... | captionit.py |
# [START imports]
import os
import urllib
from google.appengine.ext import ndb
from google.appengine.api import app_identity
import logging
import os
import jinja2
import webapp2
import uuid
import StringIO
from PIL import Image
from PIL import ImageFont
from PIL import ImageDraw
JINJA_ENVIRONMENT = jinja2.Enviro... | 0.491456 | 0.157363 |
import logging
import requests
from app.slack.slack_client import SlackClient
from app.util.chunker import chunker
logger = logging.getLogger('default')
help_message = """```
Returns matching results from sc2ladder sorted by MMR.
Usage:
> .mmr <query> <filters...>
Arguments:
- query: will match battlenet or sc2 ... | app/commands/mmr_command.py | Returns matching results from sc2ladder sorted by MMR.
Usage:
> .mmr <query> <filters...>
Arguments:
- query: will match battlenet or sc2 in game names
- filters: can be server, race, or number of results. these can be in any order.
Examples:
> .mmr avilo
> .mmr avilo na terran 5
> .mmr showtime protoss 1 eu
> .mmr... | 0.709321 | 0.501892 |
import json
from alipay.aop.api.constant.ParamConstants import *
class SpiDetectionDetail(object):
def __init__(self):
self._code = None
self._content = None
self._data_id = None
self._details = None
self._label = None
self._msg = None
self._rate = None
... | alipay/aop/api/domain/SpiDetectionDetail.py | import json
from alipay.aop.api.constant.ParamConstants import *
class SpiDetectionDetail(object):
def __init__(self):
self._code = None
self._content = None
self._data_id = None
self._details = None
self._label = None
self._msg = None
self._rate = None
... | 0.511473 | 0.102844 |
import pygame
import os
import sys
import time
import math
from audio import Audio
from bell import Bell
from button import Button
from keyPress import KeyPress
from log import Log
class RingingScreen(KeyPress, Log):
def __init__(self, network, width, height, font, frameRate, logFile, config):
if getattr... | src/ringingScreen.py | import pygame
import os
import sys
import time
import math
from audio import Audio
from bell import Bell
from button import Button
from keyPress import KeyPress
from log import Log
class RingingScreen(KeyPress, Log):
def __init__(self, network, width, height, font, frameRate, logFile, config):
if getattr... | 0.149283 | 0.102036 |
import re
import datetime
from django.conf import settings
class Contest:
def __init__(self, serve_cfg_name):
self.serve_cfg = self.read_serve_cfg(serve_cfg_name)
self.problems = self.extract_problems_from_serve_cfg(self.serve_cfg)
self.start_time = settings.CONTEST_START_TIME
s... | src/ejudge/models.py | import re
import datetime
from django.conf import settings
class Contest:
def __init__(self, serve_cfg_name):
self.serve_cfg = self.read_serve_cfg(serve_cfg_name)
self.problems = self.extract_problems_from_serve_cfg(self.serve_cfg)
self.start_time = settings.CONTEST_START_TIME
s... | 0.512937 | 0.123551 |
import urllib.request
import random
from bs4 import BeautifulSoup
import sys
def user_agent():
useragent = [
"Mozilla/5.0 CK={ } (Windows NT 6.1; WOW64; Trident/7.0; rv:11.0) like Gecko",
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.372... | proxyParsertd.py | import urllib.request
import random
from bs4 import BeautifulSoup
import sys
def user_agent():
useragent = [
"Mozilla/5.0 CK={ } (Windows NT 6.1; WOW64; Trident/7.0; rv:11.0) like Gecko",
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.372... | 0.114876 | 0.105073 |
import os
import gym
import argparse
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from dqn import *
from sac import *
from utils import *
from config import config
from codecarbon import EmissionsTracker
tracker = EmissionsTracker()
tracker.start()
import os
impo... | main.py | import os
import gym
import argparse
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from dqn import *
from sac import *
from utils import *
from config import config
from codecarbon import EmissionsTracker
tracker = EmissionsTracker()
tracker.start()
import os
impo... | 0.567218 | 0.113162 |
import pytest
from pathlib import Path
import pytest_mock
from experiment_server._process_config import verify_config, get_sections, process_config_file
MAIN_CONFIG_KEYS = ["buttonSize","trialsPerItem","conditionId","relativePosition", "participant_id", "step_name"]
@pytest.mark.parametrize(
"f, expected",[
... | test/test_process_config.py | import pytest
from pathlib import Path
import pytest_mock
from experiment_server._process_config import verify_config, get_sections, process_config_file
MAIN_CONFIG_KEYS = ["buttonSize","trialsPerItem","conditionId","relativePosition", "participant_id", "step_name"]
@pytest.mark.parametrize(
"f, expected",[
... | 0.350088 | 0.367696 |
import base64
import zlib
from google.protobuf import descriptor_pb2
# Includes description of the go.chromium.org/luci/buildbucket/proto/builds_service.proto and all of its transitive
# dependencies. Includes source code info.
FILE_DESCRIPTOR_SET = descriptor_pb2.FileDescriptorSet()
FILE_DESCRIPTOR_SET.ParseFromStr... | python_pb2/go/chromium/org/luci/buildbucket/proto/builds_service_prpc_pb2.py |
import base64
import zlib
from google.protobuf import descriptor_pb2
# Includes description of the go.chromium.org/luci/buildbucket/proto/builds_service.proto and all of its transitive
# dependencies. Includes source code info.
FILE_DESCRIPTOR_SET = descriptor_pb2.FileDescriptorSet()
FILE_DESCRIPTOR_SET.ParseFromStr... | 0.214116 | 0.097605 |
import inspect
from functools import update_wrapper
from multiprocessing import Manager
__all__ = ["SingleProcessCache", "MultiProcessCache"]
class SingleProcessCache:
"""
>>> class A:
>>> @SingleProcessCache(key="index")
>>> def method(self,index):
"""
def __init__(self, key=None) -... | deepclustering/decorator/cache_decorator.py | import inspect
from functools import update_wrapper
from multiprocessing import Manager
__all__ = ["SingleProcessCache", "MultiProcessCache"]
class SingleProcessCache:
"""
>>> class A:
>>> @SingleProcessCache(key="index")
>>> def method(self,index):
"""
def __init__(self, key=None) -... | 0.511961 | 0.147156 |
import pygame
import json
from loguru import logger
class SpriteSheet():
"""Manages the work with the given spritesheet
"""
def __init__(self, file):
"""loads the spritesheet
Note:
Inspired by: https://www.youtube.com/watch?v=ePiMYe7JpJo
Args:
file... | src/spritesheet.py | import pygame
import json
from loguru import logger
class SpriteSheet():
"""Manages the work with the given spritesheet
"""
def __init__(self, file):
"""loads the spritesheet
Note:
Inspired by: https://www.youtube.com/watch?v=ePiMYe7JpJo
Args:
file... | 0.842539 | 0.417628 |
import sys
import zmq
import tnetstring
import unittest
import time
sys.path.append('../')
from src.item import Item
from src.format import Format
import src.zmqpubcontrolclient as zmqpcc
class TestFormatSubClass(Format):
def name(self):
return 'name'
def export(self):
return {'body': 'bodyvalue'}
pollin_respo... | tests/zmqpubcontrolclient_tests.py | import sys
import zmq
import tnetstring
import unittest
import time
sys.path.append('../')
from src.item import Item
from src.format import Format
import src.zmqpubcontrolclient as zmqpcc
class TestFormatSubClass(Format):
def name(self):
return 'name'
def export(self):
return {'body': 'bodyvalue'}
pollin_respo... | 0.184841 | 0.107063 |
import jwt
import datetime
from project.server import app, db, bcrypt
from .blacklistToken import BlacklistToken
from .favourite import Favourite
from .tmdb import Tmdb
from .show import Show
class User(db.Model):
""" User Model for storing user related details """
__tablename__ = "users"
id = db.Colum... | project/server/models/user.py |
import jwt
import datetime
from project.server import app, db, bcrypt
from .blacklistToken import BlacklistToken
from .favourite import Favourite
from .tmdb import Tmdb
from .show import Show
class User(db.Model):
""" User Model for storing user related details """
__tablename__ = "users"
id = db.Colum... | 0.457137 | 0.071074 |
import csv
import cv2
import numpy as np
import random
import sklearn
from sklearn.model_selection import train_test_split
samples = []
with open('./data/driving_log.csv') as csvfile:
reader = csv.reader(csvfile)
for line in reader:
samples.append(line)
train_samples, validation_samples = train_test_s... | clone.py | import csv
import cv2
import numpy as np
import random
import sklearn
from sklearn.model_selection import train_test_split
samples = []
with open('./data/driving_log.csv') as csvfile:
reader = csv.reader(csvfile)
for line in reader:
samples.append(line)
train_samples, validation_samples = train_test_s... | 0.551091 | 0.431105 |
import numpy as np
def find_unimodal_range(x0, h, f):
l = x0 - h
r = x0 + h
m = x0
step = 1
fm = f(x0)
fl = f(l)
fr = f(r)
if fl > fm and fm < fr:
return l, r
elif fm > fr:
while True:
l = m
m = r
fm = fr
step *= 2
... | dz2/opty/algy.py | import numpy as np
def find_unimodal_range(x0, h, f):
l = x0 - h
r = x0 + h
m = x0
step = 1
fm = f(x0)
fl = f(l)
fr = f(r)
if fl > fm and fm < fr:
return l, r
elif fm > fr:
while True:
l = m
m = r
fm = fr
step *= 2
... | 0.25992 | 0.4474 |
import argparse
import os
import Config as c
import pandas as pd
from pandas_utils import group_categoricals_tail
from sklearn.model_selection import RandomizedSearchCV
def main():
# Load cli params
parser = argparse.ArgumentParser(prog="grid")
parser.add_argument("-d", "--data", dest="data", required=Tru... | gbtboilerplate/code/grid.py | import argparse
import os
import Config as c
import pandas as pd
from pandas_utils import group_categoricals_tail
from sklearn.model_selection import RandomizedSearchCV
def main():
# Load cli params
parser = argparse.ArgumentParser(prog="grid")
parser.add_argument("-d", "--data", dest="data", required=Tru... | 0.537041 | 0.235586 |
from typing import Dict
from ..base_category import BaseCategory
# ＣＤ錄音帶 cd-and-tape
class CdAndTape(object):
def cd_and_tape() -> Dict[str, Dict[str, str]]:
list = {}
list['name'] = 'ＣＤ錄音帶'
list['id'] = 'cd-and-tape'
cd_and_tape = {}
cd_and_tape['CD-tapes-manufacturers'] = 'CD片、錄音帶製造... | const/sub_categories/service/media.py | from typing import Dict
from ..base_category import BaseCategory
# ＣＤ錄音帶 cd-and-tape
class CdAndTape(object):
def cd_and_tape() -> Dict[str, Dict[str, str]]:
list = {}
list['name'] = 'ＣＤ錄音帶'
list['id'] = 'cd-and-tape'
cd_and_tape = {}
cd_and_tape['CD-tapes-manufacturers'] = 'CD片、錄音帶製造... | 0.293506 | 0.076132 |
import os
import sparv.util as util
from sparv import Annotation, Config, Document, Export, ExportAnnotations, SourceAnnotations, exporter
logger = util.get_logger(__name__)
@exporter("CSV export", config=[
Config("csv_export.delimiter", default="\t", description="Delimiter separating fields."),
Config("cs... | sparv/modules/csv_export/csv_export.py |
import os
import sparv.util as util
from sparv import Annotation, Config, Document, Export, ExportAnnotations, SourceAnnotations, exporter
logger = util.get_logger(__name__)
@exporter("CSV export", config=[
Config("csv_export.delimiter", default="\t", description="Delimiter separating fields."),
Config("cs... | 0.566618 | 0.23267 |
import datetime
import cv2
import numpy as np
from numpy.linalg import norm
import os
SZ = 20 # 训练图片长宽
def deskew(img):
m = cv2.moments(img)
if abs(m['mu02']) < 1e-2:
return img.copy()
skew = m['mu11'] / m['mu02']
M = np.float32([[1, skew, -0.5 * SZ * skew], [0, 1, 0]])
img = cv2.warpAff... | opencv_test1/svm_demo_chi.py | import datetime
import cv2
import numpy as np
from numpy.linalg import norm
import os
SZ = 20 # 训练图片长宽
def deskew(img):
m = cv2.moments(img)
if abs(m['mu02']) < 1e-2:
return img.copy()
skew = m['mu11'] / m['mu02']
M = np.float32([[1, skew, -0.5 * SZ * skew], [0, 1, 0]])
img = cv2.warpAff... | 0.437343 | 0.42919 |
from UKF_SNMPC import *
import numpy as np
from casadi import *
UKF_SNMPC = UKF_SNMPC()
solver = UKF_SNMPC.solver
U_pasts, Xd_pasts, Xa_pasts, Conp_pasts, Cont_pasts, xu_pasts, MeanSEx_pasts,\
CovSEx_pasts, t_pasts = UKF_SNMPC.initialization()
number_of_repeats = UKF_SNMPC.nu... | Simulation_UKF_SNMPC.py | from UKF_SNMPC import *
import numpy as np
from casadi import *
UKF_SNMPC = UKF_SNMPC()
solver = UKF_SNMPC.solver
U_pasts, Xd_pasts, Xa_pasts, Conp_pasts, Cont_pasts, xu_pasts, MeanSEx_pasts,\
CovSEx_pasts, t_pasts = UKF_SNMPC.initialization()
number_of_repeats = UKF_SNMPC.nu... | 0.469034 | 0.277021 |
from __future__ import unicode_literals
import frappe
def execute_0(filters=None):
if not filters: filters ={}
columns = [
"Item:Link/Item:300",
"Item Group:Link/Item Group:140",
"Customer:Link/Customer:200",
"Qty:Float:50",
"Amount:Currency:150"
]
conditions = ""
if filters.get("from_date"):
condi... | tools_box/_selling/report/sales_by_product/sales_by_product.py |
from __future__ import unicode_literals
import frappe
def execute_0(filters=None):
if not filters: filters ={}
columns = [
"Item:Link/Item:300",
"Item Group:Link/Item Group:140",
"Customer:Link/Customer:200",
"Qty:Float:50",
"Amount:Currency:150"
]
conditions = ""
if filters.get("from_date"):
condi... | 0.427397 | 0.153644 |
import gc
import os
import re
import ssl
import sys
import time
import trio
import uuid
import math
import ftfy
import ujson
import shutil
import random
import hashlib
import tarfile
import requests
import numpy as np
import pandas as pd
import pycld2 as cld2
from glob import glob
from _thread import *
from uuid impor... | ccpreprocessor.py |
import gc
import os
import re
import ssl
import sys
import time
import trio
import uuid
import math
import ftfy
import ujson
import shutil
import random
import hashlib
import tarfile
import requests
import numpy as np
import pandas as pd
import pycld2 as cld2
from glob import glob
from _thread import *
from uuid impor... | 0.245356 | 0.106737 |
import unittest
import os
import timeit
import _test_utils
from brotlidecpy import decompress
from brotli import decompress as brotlidecompress
class TestDecompress(_test_utils.TestCase):
def _test_decompress(self, test_data):
"""This performs the same decompression tests as in the Python bindings of br... | test/test_decompress.py |
import unittest
import os
import timeit
import _test_utils
from brotlidecpy import decompress
from brotli import decompress as brotlidecompress
class TestDecompress(_test_utils.TestCase):
def _test_decompress(self, test_data):
"""This performs the same decompression tests as in the Python bindings of br... | 0.451085 | 0.525369 |
from django.http.response import HttpResponse
from django.views.generic import TemplateView,ListView,DetailView
from rest_framework.views import APIView
from rest_framework.response import Response
from django.shortcuts import redirect, render
from bitcoin.models import Hour,Day,Week,Month,Year
from .forms import Cryp... | CryptoPrice/views.py | from django.http.response import HttpResponse
from django.views.generic import TemplateView,ListView,DetailView
from rest_framework.views import APIView
from rest_framework.response import Response
from django.shortcuts import redirect, render
from bitcoin.models import Hour,Day,Week,Month,Year
from .forms import Cryp... | 0.385028 | 0.15428 |
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.alert import Alert
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
from selenium.common.excep... | Update Trash/interpark_v.3.py | from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.alert import Alert
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
from selenium.common.excep... | 0.180251 | 0.110759 |
import os
import numpy as np
import pandas as pd
import hashlib
import time
import shutil
from scipy.sparse import coo_matrix
import multiprocessing as mp
import MNMAPI
class DODE(object):
def __init__(self, nb, config):
self.config = config
self.nb = nb
self.num_assign_interval = nb.config.config_dict... | src/pylib/DODE.py | import os
import numpy as np
import pandas as pd
import hashlib
import time
import shutil
from scipy.sparse import coo_matrix
import multiprocessing as mp
import MNMAPI
class DODE(object):
def __init__(self, nb, config):
self.config = config
self.nb = nb
self.num_assign_interval = nb.config.config_dict... | 0.27914 | 0.282437 |
from mlapp.handlers.wrappers.wrapper_interface import WrapperInterface
class FileStorageWrapper(WrapperInterface):
def init(self):
"""
Initializes the Wrapper for all handlers of `file_storage` type.
"""
super(FileStorageWrapper, self).init('file_storage')
def download_file(se... | mlapp/handlers/wrappers/file_storage_wrapper.py | from mlapp.handlers.wrappers.wrapper_interface import WrapperInterface
class FileStorageWrapper(WrapperInterface):
def init(self):
"""
Initializes the Wrapper for all handlers of `file_storage` type.
"""
super(FileStorageWrapper, self).init('file_storage')
def download_file(se... | 0.771801 | 0.109135 |
import json
import importlib
import os
import urllib2
def get_libs():
"""
Get all of the libraries defined in lib/definitions.
This is called automatically when the package is imported.
"""
print(">> Checking for libraries to download..")
definitions = os.listdir("lib/definitions")
tri... | lib/__init__.py | import json
import importlib
import os
import urllib2
def get_libs():
"""
Get all of the libraries defined in lib/definitions.
This is called automatically when the package is imported.
"""
print(">> Checking for libraries to download..")
definitions = os.listdir("lib/definitions")
tri... | 0.196325 | 0.102619 |
import os
import logging
import grpc
from athera.sync.sirius.services import service_pb2
from athera.sync.sirius.services import service_pb2_grpc
import sys
import io
ONE_MB = 1024 * 1024
MAX_CHUNK_SIZE = 1 * ONE_MB
REGION_URLS = {
"us-west1": "us-west1.files.athera.io:443",
"europe-west1": "files.athera.io:... | athera/sync/client.py | import os
import logging
import grpc
from athera.sync.sirius.services import service_pb2
from athera.sync.sirius.services import service_pb2_grpc
import sys
import io
ONE_MB = 1024 * 1024
MAX_CHUNK_SIZE = 1 * ONE_MB
REGION_URLS = {
"us-west1": "us-west1.files.athera.io:443",
"europe-west1": "files.athera.io:... | 0.491212 | 0.214383 |
import collections
import os
import re
import subprocess
import time
GHOSTLY_PATH = '/usr/bin/ghostly'
ALLIE_DBG = '../target/debug/allie'
# Old versions
ALLIE_1_1 = './bin/allie_v1.1'
ALLIE_1_0 = './bin/allie_v1.0'
ALLIE_0_9 = './bin/allie_v0.9'
ALLIE_0_8 = './bin/allie_v0.8'
ALLIE_0_7 = './bin/allie_v0.7'
ALLIE_0... | benchmarker/bench.py |
import collections
import os
import re
import subprocess
import time
GHOSTLY_PATH = '/usr/bin/ghostly'
ALLIE_DBG = '../target/debug/allie'
# Old versions
ALLIE_1_1 = './bin/allie_v1.1'
ALLIE_1_0 = './bin/allie_v1.0'
ALLIE_0_9 = './bin/allie_v0.9'
ALLIE_0_8 = './bin/allie_v0.8'
ALLIE_0_7 = './bin/allie_v0.7'
ALLIE_0... | 0.329931 | 0.044101 |
from collections import Counter, namedtuple
from xldlib.definitions import ZIP
from xldlib.general import sequence
from xldlib.qt.objects import base
from xldlib.utils import logger, modtools
# DATA
# ----
CHARS = [
'd',
'u'
]
# OBJECTS
# -------
@sequence.serializable("XLIdentifier")
class XLIdentifier... | xldlib/xlpy/tools/frozen.py | from collections import Counter, namedtuple
from xldlib.definitions import ZIP
from xldlib.general import sequence
from xldlib.qt.objects import base
from xldlib.utils import logger, modtools
# DATA
# ----
CHARS = [
'd',
'u'
]
# OBJECTS
# -------
@sequence.serializable("XLIdentifier")
class XLIdentifier... | 0.765944 | 0.252568 |
import unittest
from utils.rpg.shadowrun3e.parser import Sr3CharacterParser
class TestSr3eCharacterParser(unittest.TestCase):
def setUp(self):
self.parser = Sr3CharacterParser
def test_roll_attribute_parse(self):
"""
Verifies that the attribute roll parsing works properly
"""
... | tests/test_sr3_character_parser.py | import unittest
from utils.rpg.shadowrun3e.parser import Sr3CharacterParser
class TestSr3eCharacterParser(unittest.TestCase):
def setUp(self):
self.parser = Sr3CharacterParser
def test_roll_attribute_parse(self):
"""
Verifies that the attribute roll parsing works properly
"""
... | 0.751375 | 0.61783 |
from setuptools import setup, find_packages
import glob
import sys, os.path
## Ensure that ``./autogen.sh`` is run prior to using ``setup.py``
if "2.0.0".startswith("%%"):
import os, subprocess
if not os.path.exists('./autogen.sh'):
sys.stderr.write(
"This source repository was not configu... | setup.py | from setuptools import setup, find_packages
import glob
import sys, os.path
## Ensure that ``./autogen.sh`` is run prior to using ``setup.py``
if "2.0.0".startswith("%%"):
import os, subprocess
if not os.path.exists('./autogen.sh'):
sys.stderr.write(
"This source repository was not configu... | 0.338296 | 0.133105 |
from .config import *
from scipy.optimize import curve_fit
def appearance_energy(data, savedir=None):
"""
This function finds the appearance energy of all amu species present in
the data by means of linear fit.
Parameters
----------
data: string or Pandas DataFrame
This should be a str... | qmspy/appearance_energy.py | from .config import *
from scipy.optimize import curve_fit
def appearance_energy(data, savedir=None):
"""
This function finds the appearance energy of all amu species present in
the data by means of linear fit.
Parameters
----------
data: string or Pandas DataFrame
This should be a str... | 0.784071 | 0.618896 |
"""Get the version string from the git tag."""
from __future__ import print_function
import subprocess
__all__ = ['get_gitversion']
TEMPLATES = {
'python': """\
\"""Do not edit this file because it will be overwritten before packaging.
The output of git describe was: {git_describe}
\"""
__version__ = '{git_ta... | tools/appveyor/gitversion.py | """Get the version string from the git tag."""
from __future__ import print_function
import subprocess
__all__ = ['get_gitversion']
TEMPLATES = {
'python': """\
\"""Do not edit this file because it will be overwritten before packaging.
The output of git describe was: {git_describe}
\"""
__version__ = '{git_ta... | 0.761272 | 0.221372 |
from __future__ import unicode_literals
import django.core.validators
import django.db.models.deletion
import versions.models
from django.conf import settings
from django.contrib.auth.hashers import make_password
from django.db import migrations, models
import pretix.base.i18n
import pretix.base.models
def initial_... | src/pretix/base/migrations/0001_initial.py | from __future__ import unicode_literals
import django.core.validators
import django.db.models.deletion
import versions.models
from django.conf import settings
from django.contrib.auth.hashers import make_password
from django.db import migrations, models
import pretix.base.i18n
import pretix.base.models
def initial_... | 0.498535 | 0.076753 |
import grpc
from google.ads.google_ads.v3.proto.resources import expanded_landing_page_view_pb2 as google_dot_ads_dot_googleads__v3_dot_proto_dot_resources_dot_expanded__landing__page__view__pb2
from google.ads.google_ads.v3.proto.services import expanded_landing_page_view_service_pb2 as google_dot_ads_dot_googleads__... | google/ads/google_ads/v3/proto/services/expanded_landing_page_view_service_pb2_grpc.py | import grpc
from google.ads.google_ads.v3.proto.resources import expanded_landing_page_view_pb2 as google_dot_ads_dot_googleads__v3_dot_proto_dot_resources_dot_expanded__landing__page__view__pb2
from google.ads.google_ads.v3.proto.services import expanded_landing_page_view_service_pb2 as google_dot_ads_dot_googleads__... | 0.658747 | 0.061565 |
import tensorflow as tf
def _append_homog(tensor):
rank = len(tensor.shape.as_list())
shape = tf.concat([tf.shape(tensor)[:-1], [1]], axis=0)
ones = tf.ones(shape, dtype=tensor.dtype)
return tf.concat([tensor, ones], axis=rank - 1)
def dense(inputs, weights, batch_norm, is_training, particles=1):
... | misc/layers.py | import tensorflow as tf
def _append_homog(tensor):
rank = len(tensor.shape.as_list())
shape = tf.concat([tf.shape(tensor)[:-1], [1]], axis=0)
ones = tf.ones(shape, dtype=tensor.dtype)
return tf.concat([tensor, ones], axis=rank - 1)
def dense(inputs, weights, batch_norm, is_training, particles=1):
... | 0.626124 | 0.393909 |
import base64
import logging
import sys
logger = logging.getLogger(__name__.split('.')[-1])
import pandas as pd
import matplotlib.pyplot as plt
import io
TRUNCATE_CUTOFF = 40
_HEADER = """
<!DOCTYPE html>
<html lang="en">
<head>
<title>{title}</title>
<link rel="stylesheet" href="https://fonts.go... | amalia/tools/ReportWriter.py | import base64
import logging
import sys
logger = logging.getLogger(__name__.split('.')[-1])
import pandas as pd
import matplotlib.pyplot as plt
import io
TRUNCATE_CUTOFF = 40
_HEADER = """
<!DOCTYPE html>
<html lang="en">
<head>
<title>{title}</title>
<link rel="stylesheet" href="https://fonts.go... | 0.357231 | 0.070304 |
import os
from pathlib import Path
from .logger import CustomisedJSONFormatter
# Build paths inside the project like this: BASE_DIR / 'subdir'.
BASE_DIR = Path(__file__).resolve().parent.parent
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/3.2/howto/deployment... | src/Demo/settings.py | import os
from pathlib import Path
from .logger import CustomisedJSONFormatter
# Build paths inside the project like this: BASE_DIR / 'subdir'.
BASE_DIR = Path(__file__).resolve().parent.parent
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/3.2/howto/deployment... | 0.434581 | 0.100569 |
from collections import OrderedDict
from copy import deepcopy
from simtk import openmm
from simtk import unit
kB = unit.BOLTZMANN_CONSTANT_kB*unit.AVOGADRO_CONSTANT_NA
class InputError(Exception):
def __init__(self, msg):
super(InputError, self).__init__('\033[1;31m' + msg + '\033[0m')
def countDegree... | src/atomsmm/utils.py | from collections import OrderedDict
from copy import deepcopy
from simtk import openmm
from simtk import unit
kB = unit.BOLTZMANN_CONSTANT_kB*unit.AVOGADRO_CONSTANT_NA
class InputError(Exception):
def __init__(self, msg):
super(InputError, self).__init__('\033[1;31m' + msg + '\033[0m')
def countDegree... | 0.874091 | 0.51379 |
from datetime import datetime
from dataclasses import dataclass
from typing import List
import string
import requests
from flask import Blueprint, Response, request, url_for, redirect
from flask.views import MethodView
from flask_babelplus import gettext as _
from flask_login import current_user, login_required
from ... | modules/hub/hub/features/donations/views.py | from datetime import datetime
from dataclasses import dataclass
from typing import List
import string
import requests
from flask import Blueprint, Response, request, url_for, redirect
from flask.views import MethodView
from flask_babelplus import gettext as _
from flask_login import current_user, login_required
from ... | 0.657318 | 0.132655 |