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 numba import jit
class Decoder:
'''
Data decoding with lossless compression algorithm (LZW)
The class includes the following methods:
__init__ - Object Initialization.
init_trie - Initializing the trie
trie_update - Add item to trie
decode ... | LZWCompressor/Decoder.py | from numba import jit
class Decoder:
'''
Data decoding with lossless compression algorithm (LZW)
The class includes the following methods:
__init__ - Object Initialization.
init_trie - Initializing the trie
trie_update - Add item to trie
decode ... | 0.609408 | 0.569494 |
import logging
from qpid.util import connect, URL, ssl
from qpid.datatypes import Message, uuid4, RangedSet
from qpid.connection import Connection
from qpid.session import SessionClosed
from moksha.hub.amqp.base import BaseAMQPHub
log = logging.getLogger('moksha.hub')
class QpidAMQPHub(BaseAMQPHub):
"""
I... | moksha/hub/amqp/qpid010.py |
import logging
from qpid.util import connect, URL, ssl
from qpid.datatypes import Message, uuid4, RangedSet
from qpid.connection import Connection
from qpid.session import SessionClosed
from moksha.hub.amqp.base import BaseAMQPHub
log = logging.getLogger('moksha.hub')
class QpidAMQPHub(BaseAMQPHub):
"""
I... | 0.538498 | 0.130618 |
import shutil
import traceback
from abc import ABC, abstractmethod
from pathlib import Path, PurePath
from tempfile import TemporaryDirectory
from typing import List, IO, Optional
from zipfile import ZipFile
import yaml
from opera.error import ParseError, OperaError
from opera.utils import determine_archive_format
... | src/opera/parser/tosca/csar.py | import shutil
import traceback
from abc import ABC, abstractmethod
from pathlib import Path, PurePath
from tempfile import TemporaryDirectory
from typing import List, IO, Optional
from zipfile import ZipFile
import yaml
from opera.error import ParseError, OperaError
from opera.utils import determine_archive_format
... | 0.634317 | 0.087019 |
import datetime
import json
from freezegun import freeze_time
from mantarray_desktop_app import COMPILED_EXE_BUILD_TIMESTAMP
from mantarray_desktop_app import create_magnetometer_config_dict
from mantarray_desktop_app import CURRENT_SOFTWARE_VERSION
from mantarray_desktop_app import MICRO_TO_BASE_CONVERSION
from manta... | tests/server/test_routes_populate_queues.py | import datetime
import json
from freezegun import freeze_time
from mantarray_desktop_app import COMPILED_EXE_BUILD_TIMESTAMP
from mantarray_desktop_app import create_magnetometer_config_dict
from mantarray_desktop_app import CURRENT_SOFTWARE_VERSION
from mantarray_desktop_app import MICRO_TO_BASE_CONVERSION
from manta... | 0.313105 | 0.116613 |
import enum
from models.base_pose import PoseModel
from utils import Joint, normalize, log
def distance(p1, p2):
return ((p1.x - p2.x)**2 + (p1.y - p2.y)**2)**(1/2)
def get_sin(elbow_p, wrist_p, c):
return (wrist_p.y - elbow_p.y) / c
def get_cos(elbow_p, wrist_p, c):
return (wrist_p.x - elbow_p.x) / ... | src/models/intel_pose.py | import enum
from models.base_pose import PoseModel
from utils import Joint, normalize, log
def distance(p1, p2):
return ((p1.x - p2.x)**2 + (p1.y - p2.y)**2)**(1/2)
def get_sin(elbow_p, wrist_p, c):
return (wrist_p.y - elbow_p.y) / c
def get_cos(elbow_p, wrist_p, c):
return (wrist_p.x - elbow_p.x) / ... | 0.566139 | 0.35301 |
from abc import ABC, abstractmethod
import jax
import jax.numpy as jnp
import haiku as hk
import optax
import chex
from .._base.mixins import RandomStateMixin
from ..utils import get_grads_diagnostics, is_policy, is_stochastic, is_qfunction, is_vfunction, jit
from ..value_losses import huber, quantile_huber
from ..re... | coax/td_learning/_base.py | from abc import ABC, abstractmethod
import jax
import jax.numpy as jnp
import haiku as hk
import optax
import chex
from .._base.mixins import RandomStateMixin
from ..utils import get_grads_diagnostics, is_policy, is_stochastic, is_qfunction, is_vfunction, jit
from ..value_losses import huber, quantile_huber
from ..re... | 0.901922 | 0.362602 |
import glob
import os
import shutil
import numpy as np
import pytest
import webbpsf
from .utils import parametrized_data
from mirage.psf.deployments import generate_random_ote_deployment, load_ote_from_deployment_yaml
from mirage.utils.utils import ensure_dir_exists
# Define directory and file locations
__location__... | tests/test_deployments.py | import glob
import os
import shutil
import numpy as np
import pytest
import webbpsf
from .utils import parametrized_data
from mirage.psf.deployments import generate_random_ote_deployment, load_ote_from_deployment_yaml
from mirage.utils.utils import ensure_dir_exists
# Define directory and file locations
__location__... | 0.635901 | 0.391551 |
from cuml.manifold import UMAP
from sklearn.datasets import load_digits
from numba import cuda
from pyrr import Matrix44
import numpy as np
import cudatashader as ds
from cudatashader import transfer_functions as tf
from cudatashader.colors import Hot
from IPython.core.display import display, HTML, clear_output
digits... | cudatashader-3d-demo/render_server.py | from cuml.manifold import UMAP
from sklearn.datasets import load_digits
from numba import cuda
from pyrr import Matrix44
import numpy as np
import cudatashader as ds
from cudatashader import transfer_functions as tf
from cudatashader.colors import Hot
from IPython.core.display import display, HTML, clear_output
digits... | 0.676192 | 0.420659 |
import string
import random
def process_file(filename, skip_header):
"""Makes a histogram that contains the words from a file.
filename: string
skip_header: boolean, whether to skip the Gutenberg header
Returns: map from each word to the number of times it appears.
"""
hist = {}
fp = ... | Think Python/analyze_book.py | import string
import random
def process_file(filename, skip_header):
"""Makes a histogram that contains the words from a file.
filename: string
skip_header: boolean, whether to skip the Gutenberg header
Returns: map from each word to the number of times it appears.
"""
hist = {}
fp = ... | 0.785802 | 0.539772 |
import betaDecay
import spontaneousFission as sf
import generalFunctions as gf
from matplotlib import pyplot as plt
from matplotlib import colors
#Shows energy released when the nucleus is streched into an ellipsoid. A positive energy release indicates instantaneous fission.
def fissionMap(zMin, zMax, aMin, aMax):
... | example.py | import betaDecay
import spontaneousFission as sf
import generalFunctions as gf
from matplotlib import pyplot as plt
from matplotlib import colors
#Shows energy released when the nucleus is streched into an ellipsoid. A positive energy release indicates instantaneous fission.
def fissionMap(zMin, zMax, aMin, aMax):
... | 0.210685 | 0.643553 |
import chex
import haiku as hk
from jax import jit, random, lax, tree_map, vmap
from jax.tree_util import tree_flatten, tree_unflatten
import blackjax.nuts as nuts
import blackjax.stan_warmup as stan_warmup
import jax.numpy as jnp
import typing_extensions
from typing import Any, NamedTuple, Union
from jsl.experimen... | jsl/experimental/seql/agents/blackjax_nuts_agent.py | import chex
import haiku as hk
from jax import jit, random, lax, tree_map, vmap
from jax.tree_util import tree_flatten, tree_unflatten
import blackjax.nuts as nuts
import blackjax.stan_warmup as stan_warmup
import jax.numpy as jnp
import typing_extensions
from typing import Any, NamedTuple, Union
from jsl.experimen... | 0.831212 | 0.365428 |
import sys
import pygame
from bullet import Bullet
from alien import Alien
from time import sleep
def check_keydown_events(event, ship, ai_settings, screen, bullets):
""" 响应按键 """
if event.key == pygame.K_RIGHT:
ship.moving_right = True
elif event.key == pygame.K_LEFT:
ship.moving_left = T... | L/game/game_function.py | import sys
import pygame
from bullet import Bullet
from alien import Alien
from time import sleep
def check_keydown_events(event, ship, ai_settings, screen, bullets):
""" 响应按键 """
if event.key == pygame.K_RIGHT:
ship.moving_right = True
elif event.key == pygame.K_LEFT:
ship.moving_left = T... | 0.286169 | 0.145055 |
import StringIO
import os
import string
try:
from genshi import template as genshitemplate
except ImportError, e:
genshitemplate = None
try:
import jinja2
except ImportError, e:
jinja2 = None
from twisted.internet import defer, reactor
from twisted.python import components
from zope import interface
... | txtemplate/templates.py | import StringIO
import os
import string
try:
from genshi import template as genshitemplate
except ImportError, e:
genshitemplate = None
try:
import jinja2
except ImportError, e:
jinja2 = None
from twisted.internet import defer, reactor
from twisted.python import components
from zope import interface
... | 0.49048 | 0.103522 |
INPUT_FILE = 'input.txt'
def main():
with open(INPUT_FILE, 'r') as file:
puzzle_input = file.read().split('\n\n')
numbers_drown = puzzle_input[0]
boards_definitions = puzzle_input[1:]
numbers = [int(number) for number in numbers_drown.strip().split(',')]
boards = []
for board_defin... | year-2021/day-04/part-2.py |
INPUT_FILE = 'input.txt'
def main():
with open(INPUT_FILE, 'r') as file:
puzzle_input = file.read().split('\n\n')
numbers_drown = puzzle_input[0]
boards_definitions = puzzle_input[1:]
numbers = [int(number) for number in numbers_drown.strip().split(',')]
boards = []
for board_defin... | 0.336985 | 0.394143 |
cities = [
'Acampo',
'Acton',
'Adelanto',
'Adin',
'<NAME>',
'Aguanga',
'Ahwahnee',
'Alameda',
'Alamo',
'Albany',
'Albion',
'Alderpoint',
'Alhambra',
'Aliso Viejo',
'Alleghany',
'Alpaugh',
'Alpine',
'Alta',
'Alta Loma',
'Altadena',
'Alta... | john_doe/cities/us/california.py | cities = [
'Acampo',
'Acton',
'Adelanto',
'Adin',
'<NAME>',
'Aguanga',
'Ahwahnee',
'Alameda',
'Alamo',
'Albany',
'Albion',
'Alderpoint',
'Alhambra',
'Aliso Viejo',
'Alleghany',
'Alpaugh',
'Alpine',
'Alta',
'Alta Loma',
'Altadena',
'Alta... | 0.357231 | 0.191026 |
import unittest
import sqlite3
from .. import db as doxygen_db
from .. import exceptions
from .. import sql
from . import TEST_DB
db = doxygen_db.DoxygenSQLite3(TEST_DB)
class TestDatabase(unittest.TestCase):
"""Validate statements generated by the Statement class"""
def test_undefined_table(self):
... | doxy_db/tests/t_db.py | import unittest
import sqlite3
from .. import db as doxygen_db
from .. import exceptions
from .. import sql
from . import TEST_DB
db = doxygen_db.DoxygenSQLite3(TEST_DB)
class TestDatabase(unittest.TestCase):
"""Validate statements generated by the Statement class"""
def test_undefined_table(self):
... | 0.498291 | 0.480601 |
import argparse
import os
import time
import torch
from tengine import tg
import numpy as np
import numpy as np
import torchvision.transforms as transforms
import torchvision.datasets as datasets
from main import (
accuracy,
AverageMeter
)
IMG_SIZE = 224
parser = argparse.ArgumentParser(description='classif... | application/imagenet_example/eval_tengine.py | import argparse
import os
import time
import torch
from tengine import tg
import numpy as np
import numpy as np
import torchvision.transforms as transforms
import torchvision.datasets as datasets
from main import (
accuracy,
AverageMeter
)
IMG_SIZE = 224
parser = argparse.ArgumentParser(description='classif... | 0.712732 | 0.451447 |
from time import sleep
import pandas as pd
import numpy as np
import lightgbm as lgb
from sklearn.model_selection import StratifiedKFold, train_test_split
from sklearn.metrics import roc_auc_score
from miraiml import HyperSearchSpace, Config, Engine
class LightGBM:
def __init__(self, n_folds, **parameters):
... | examples/lightgbm_wrapper.py | from time import sleep
import pandas as pd
import numpy as np
import lightgbm as lgb
from sklearn.model_selection import StratifiedKFold, train_test_split
from sklearn.metrics import roc_auc_score
from miraiml import HyperSearchSpace, Config, Engine
class LightGBM:
def __init__(self, n_folds, **parameters):
... | 0.715026 | 0.307956 |
import os.path as op
from glob import glob
from pprint import pprint
import pandas as pd
TARGET_FILES = [
# TE30
"power/{sub}/func/{prefix}_desc-TE30_bold.nii.gz",
# OC
"tedana/{sub}/func/{prefix}_desc-optcom_bold.nii.gz",
# MEDN
"tedana/{sub}/func/{prefix}_desc-optcomDenoised_bold.nii.gz",
... | processing/07b_check_denoising_completion.py | import os.path as op
from glob import glob
from pprint import pprint
import pandas as pd
TARGET_FILES = [
# TE30
"power/{sub}/func/{prefix}_desc-TE30_bold.nii.gz",
# OC
"tedana/{sub}/func/{prefix}_desc-optcom_bold.nii.gz",
# MEDN
"tedana/{sub}/func/{prefix}_desc-optcomDenoised_bold.nii.gz",
... | 0.24726 | 0.141905 |
from __future__ import absolute_import
from rest_framework.permissions import IsAuthenticated
from sentry.api.base import Endpoint
from sentry.api.exceptions import ResourceDoesNotExist
from sentry.api.permissions import ScopedPermission
from sentry.app import raven
from sentry.models import SentryApp, SentryAppInsta... | src/sentry/api/bases/sentryapps.py | from __future__ import absolute_import
from rest_framework.permissions import IsAuthenticated
from sentry.api.base import Endpoint
from sentry.api.exceptions import ResourceDoesNotExist
from sentry.api.permissions import ScopedPermission
from sentry.app import raven
from sentry.models import SentryApp, SentryAppInsta... | 0.587115 | 0.039565 |
import numpy as np
import deeptrack as dt
import random
def GetSubSet(randset):
"""
Returns a function that takes a graph and returns a
random subset of the graph.
"""
def inner(data):
graph, labels, sets = data
nodeidxs = np.where(sets[0] == randset)[0]
edgeidxs = np.whe... | deeptrack/models/gnns/augmentations.py | import numpy as np
import deeptrack as dt
import random
def GetSubSet(randset):
"""
Returns a function that takes a graph and returns a
random subset of the graph.
"""
def inner(data):
graph, labels, sets = data
nodeidxs = np.where(sets[0] == randset)[0]
edgeidxs = np.whe... | 0.797793 | 0.712845 |
import numpy as np
from scipy.interpolate import RectSphereBivariateSpline
def regular_gldas(lats,lons,grids):
'''
Normalize the GLDAS grid data to meet the requirements of spherical harmonic expansion with pyshtools based on the sampling theorem of Driscoll and Healy (1994).
The normalized grid data has t... | ggtools/gg/regular_gldas.py | import numpy as np
from scipy.interpolate import RectSphereBivariateSpline
def regular_gldas(lats,lons,grids):
'''
Normalize the GLDAS grid data to meet the requirements of spherical harmonic expansion with pyshtools based on the sampling theorem of Driscoll and Healy (1994).
The normalized grid data has t... | 0.832815 | 0.73678 |
import json
import logging
from kigo.etl.runtime.registry import MappingRegistry
from kigo.etl.mapper.mapping import MappingInfo
class Config:
__config = {}
@classmethod
def load(cls, file_path):
with open(file_path, "r") as f:
Config.__config = json.load(f)
Config.validate()
... | kigo/etl/configuration.py | import json
import logging
from kigo.etl.runtime.registry import MappingRegistry
from kigo.etl.mapper.mapping import MappingInfo
class Config:
__config = {}
@classmethod
def load(cls, file_path):
with open(file_path, "r") as f:
Config.__config = json.load(f)
Config.validate()
... | 0.54577 | 0.097433 |
import os
import sys
import re
import glob
import argparse
from pathlib import Path
import utils
def makePlot1cFilelists(golddir, resultdir, outputdir, genefile, queryNames):
golddir = Path(golddir).resolve().as_posix()
resultdir = Path(resultdir).resolve().as_posix()
outputdir = Path(outputdir).resolve()... | tests/bioinform_tests/pytools/create_plot1c_filelists.py | import os
import sys
import re
import glob
import argparse
from pathlib import Path
import utils
def makePlot1cFilelists(golddir, resultdir, outputdir, genefile, queryNames):
golddir = Path(golddir).resolve().as_posix()
resultdir = Path(resultdir).resolve().as_posix()
outputdir = Path(outputdir).resolve()... | 0.208259 | 0.146118 |
import json
import logging
import os
from slack_sdk import WebClient
from slack_sdk.errors import SlackApiError
from constants import TRUE_VALUES
states = json.loads(os.environ["STATES"])
def format_available_message(locations):
message = ":large_green_circle: {}Vaccine appointments available at {} location{}:... | notify/slack.py | import json
import logging
import os
from slack_sdk import WebClient
from slack_sdk.errors import SlackApiError
from constants import TRUE_VALUES
states = json.loads(os.environ["STATES"])
def format_available_message(locations):
message = ":large_green_circle: {}Vaccine appointments available at {} location{}:... | 0.178347 | 0.081301 |
import requests
import sys
from functools import wraps
import inspect
from json import loads
class IEX(object):
"""
Base class for IEX API
"""
_IEX_API_URL = "https://api.iextrading.com/1.0"
def __init__(self, retries=5):
"""
Initialize the class
retries: Maximum amount... | py_iex/iex.py | import requests
import sys
from functools import wraps
import inspect
from json import loads
class IEX(object):
"""
Base class for IEX API
"""
_IEX_API_URL = "https://api.iextrading.com/1.0"
def __init__(self, retries=5):
"""
Initialize the class
retries: Maximum amount... | 0.403684 | 0.121009 |
import SchemDraw as schem
import SchemDraw.elements as e
d = schem.Drawing(inches_per_unit=.5, unit=3)
D1 = d.add(e.DIODE, theta=-45)
d.add(e.DOT)
D2 = d.add(e.DIODE, theta=225, reverse=True)
d.add(e.DOT)
D3 = d.add(e.DIODE, theta=135, reverse=True)
d.add(e.DOT)
D4 = d.add(e.DIODE, theta=45)
d.add(e.DOT)
d.add(e.LINE... | docs/gallery/powersupply.py | import SchemDraw as schem
import SchemDraw.elements as e
d = schem.Drawing(inches_per_unit=.5, unit=3)
D1 = d.add(e.DIODE, theta=-45)
d.add(e.DOT)
D2 = d.add(e.DIODE, theta=225, reverse=True)
d.add(e.DOT)
D3 = d.add(e.DIODE, theta=135, reverse=True)
d.add(e.DOT)
D4 = d.add(e.DIODE, theta=45)
d.add(e.DOT)
d.add(e.LINE... | 0.473901 | 0.570032 |
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support.ui import Select
from selenium.webdriver.common.by import By
from selenium.webdriver.support import... | wphafiye.py | from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support.ui import Select
from selenium.webdriver.common.by import By
from selenium.webdriver.support import... | 0.156427 | 0.105579 |
from uuid import uuid4
from . import settings
from ..core.clients import OAuth2Client
from .models import PayPalOAuthProfile
class PayPalClient(OAuth2Client):
"""
Client to connect with the PayPal REST API.
"""
# Configuration
service_name = 'PayPal'
app_key = settings.APP_ID
app_secret =... | socialnetworks/paypal/clients.py | from uuid import uuid4
from . import settings
from ..core.clients import OAuth2Client
from .models import PayPalOAuthProfile
class PayPalClient(OAuth2Client):
"""
Client to connect with the PayPal REST API.
"""
# Configuration
service_name = 'PayPal'
app_key = settings.APP_ID
app_secret =... | 0.63409 | 0.097476 |
import cv2
import numpy as np
from activity_service import add_to_sample, run_activity_inference
import requests
import json
import base64
import configparser
config = configparser.ConfigParser()
config.read("config.ini")
def encode_img(image):
_, buffer = cv2.imencode('.jpg', image)
enc_buff = base64.b64e... | visualizers.py | import cv2
import numpy as np
from activity_service import add_to_sample, run_activity_inference
import requests
import json
import base64
import configparser
config = configparser.ConfigParser()
config.read("config.ini")
def encode_img(image):
_, buffer = cv2.imencode('.jpg', image)
enc_buff = base64.b64e... | 0.159217 | 0.137706 |
import numpy as np
from skimage.transform import AffineTransform, warp
from skimage.util import pad, img_as_ubyte
from typing import List
from dataset.interpolate.InterpolateDatasetLoader import InterpolateDatasetLoader
from dataset.loader.DatasetLoader import DatasetLoader
from dataset.interpolate.InterpolateSubdatas... | src/dataset/interpolate/process/CreateTransformedInterpolateData.py | import numpy as np
from skimage.transform import AffineTransform, warp
from skimage.util import pad, img_as_ubyte
from typing import List
from dataset.interpolate.InterpolateDatasetLoader import InterpolateDatasetLoader
from dataset.loader.DatasetLoader import DatasetLoader
from dataset.interpolate.InterpolateSubdatas... | 0.872075 | 0.403861 |
import speech_recognition as sr
import re
import philips_hue as ph
import soundclassify as sc
import pyaudio
import wave
from jesica4 import create_dashboard
from jesica4 import command_light
from jesica4 import command_SoundSystem
from jesica4 import command_Door
from jesica4 import command_detectsound
command_light... | speechrecog/__main__.py | import speech_recognition as sr
import re
import philips_hue as ph
import soundclassify as sc
import pyaudio
import wave
from jesica4 import create_dashboard
from jesica4 import command_light
from jesica4 import command_SoundSystem
from jesica4 import command_Door
from jesica4 import command_detectsound
command_light... | 0.175185 | 0.120413 |
import argparse
import os
import torch
import torch.nn as nn
import torch.utils.data as data
class Configs(object):
@staticmethod
def base_config():
parser = argparse.ArgumentParser()
parser.add_argument("--classifier", type=str, default="vdpwi", choices=["vdpwi", "resnet"])
parser.add... | vdpwi/data.py | import argparse
import os
import torch
import torch.nn as nn
import torch.utils.data as data
class Configs(object):
@staticmethod
def base_config():
parser = argparse.ArgumentParser()
parser.add_argument("--classifier", type=str, default="vdpwi", choices=["vdpwi", "resnet"])
parser.add... | 0.659624 | 0.128416 |
import os
import shutil
import argparse
from abc import ABCMeta, abstractmethod
from typing import List, Dict, Iterable, Iterator, Optional, Any
from .util import Namespace
from .instance import Instance
from .package import Package
from .parallel import Pool
class Target(metaclass=ABCMeta):
"""
Abstract base... | infra/target.py | import os
import shutil
import argparse
from abc import ABCMeta, abstractmethod
from typing import List, Dict, Iterable, Iterator, Optional, Any
from .util import Namespace
from .instance import Instance
from .package import Package
from .parallel import Pool
class Target(metaclass=ABCMeta):
"""
Abstract base... | 0.897893 | 0.442637 |
import enum
import ipaddress
from typing import Optional
from sqlalchemy import Column, String, Enum, text
from sqlalchemy.dialects.postgresql import ARRAY
from sqlalchemy_utils import UUIDType, generic_repr, IPAddressType, ArrowType
from ingredients_db.database import Base
from ingredients_db.models.network_port imp... | ingredients_db/models/network.py | import enum
import ipaddress
from typing import Optional
from sqlalchemy import Column, String, Enum, text
from sqlalchemy.dialects.postgresql import ARRAY
from sqlalchemy_utils import UUIDType, generic_repr, IPAddressType, ArrowType
from ingredients_db.database import Base
from ingredients_db.models.network_port imp... | 0.746046 | 0.101322 |
from IPython.core.pylabtools import print_figure
from IPython.core.display import display, HTML, Math, Latex
from sympy import Matrix, latex
import numpy as np
def limitprec(m, prec=3):
'''Silly function to limit the maximum number of decimal places for a matrix of floats.
m: np.ndarray
input ... | notebookutils.py | from IPython.core.pylabtools import print_figure
from IPython.core.display import display, HTML, Math, Latex
from sympy import Matrix, latex
import numpy as np
def limitprec(m, prec=3):
'''Silly function to limit the maximum number of decimal places for a matrix of floats.
m: np.ndarray
input ... | 0.692954 | 0.580709 |
import os
import re
import numpy as np
import scipy.optimize
from ledsa.core.model import target_function
from ledsa.core.LEDAnalysisData import LEDAnalysisData
import time
sep = os.path.sep
def generate_led_analysis_data(conf, channel, data, debug, iled, img_filename, led_array_idx, search_areas,
... | ledsa/core/_led_helper_functions_s3.py | import os
import re
import numpy as np
import scipy.optimize
from ledsa.core.model import target_function
from ledsa.core.LEDAnalysisData import LEDAnalysisData
import time
sep = os.path.sep
def generate_led_analysis_data(conf, channel, data, debug, iled, img_filename, led_array_idx, search_areas,
... | 0.267408 | 0.196961 |
from git import Repo, RemoteReference, TagReference, InvalidGitRepositoryError, GitCommandError
from tempfile import NamedTemporaryFile
import shutil
import os
class Git:
def __init__(self, git_repo, repo_dir, pkey=None):
self.git_repo = git_repo
self.repo_dir = repo_dir
self.repo = None
... | spug_api/libs/gitlib.py | from git import Repo, RemoteReference, TagReference, InvalidGitRepositoryError, GitCommandError
from tempfile import NamedTemporaryFile
import shutil
import os
class Git:
def __init__(self, git_repo, repo_dir, pkey=None):
self.git_repo = git_repo
self.repo_dir = repo_dir
self.repo = None
... | 0.325628 | 0.072834 |
import numpy as np
from manim import *
import sympy as sp
class Curve3D():
def __init__(self, name: str, t: sp.Symbol, vector_sym, init_t: float, color: str,
speed=1, scale=1, offset=[0, 0, 0]):
## Symbolic attributes
# Parameter
self.t_sym = t * speed
# Paramet... | part-1/Curve3D.py | import numpy as np
from manim import *
import sympy as sp
class Curve3D():
def __init__(self, name: str, t: sp.Symbol, vector_sym, init_t: float, color: str,
speed=1, scale=1, offset=[0, 0, 0]):
## Symbolic attributes
# Parameter
self.t_sym = t * speed
# Paramet... | 0.638272 | 0.428473 |
import time
from common.scene import Scene
from common.tool import load_resource
from azurelane.assist import calculate_move_map
###自己添加
def siren_heavy_blue(prefix):
return Scene("检测蓝色塞壬重巡",identify_image=load_resource("map_siren_heavy_blue.png", prefix)) #判断塞壬蓝色重巡
def siren_heavy_purple(prefix):
... | azurelane/scenes/enemy_search.py | import time
from common.scene import Scene
from common.tool import load_resource
from azurelane.assist import calculate_move_map
###自己添加
def siren_heavy_blue(prefix):
return Scene("检测蓝色塞壬重巡",identify_image=load_resource("map_siren_heavy_blue.png", prefix)) #判断塞壬蓝色重巡
def siren_heavy_purple(prefix):
... | 0.26693 | 0.207435 |
"""Tests for the auto_forensicate script."""
from __future__ import unicode_literals
import argparse
import logging
import os
import StringIO
import sys
import tempfile
import unittest
import auto_acquire
from auto_forensicate import errors
from auto_forensicate import uploader
from auto_forensicate.recipes import b... | auto_forensicate/tests/auto_forensicate_tests.py | """Tests for the auto_forensicate script."""
from __future__ import unicode_literals
import argparse
import logging
import os
import StringIO
import sys
import tempfile
import unittest
import auto_acquire
from auto_forensicate import errors
from auto_forensicate import uploader
from auto_forensicate.recipes import b... | 0.580114 | 0.227405 |
import logging
from pathlib import Path
import sys
import tempfile
import beetools
import displayfx
_VERSION = "0.0.1"
_path = Path(__file__)
_name = _path.stem
class TxtWrpr:
'''A wrapper for fixed column text files
This module copies a fixed column TXT file into a dictionary structure
to manipulate and... | src/txtwrpr/txtwrpr.py | import logging
from pathlib import Path
import sys
import tempfile
import beetools
import displayfx
_VERSION = "0.0.1"
_path = Path(__file__)
_name = _path.stem
class TxtWrpr:
'''A wrapper for fixed column text files
This module copies a fixed column TXT file into a dictionary structure
to manipulate and... | 0.397588 | 0.210381 |
import copy
from typing import Any, Dict, List
from pytest import lazy_fixture # type: ignore
from pytest import fixture, mark, param
from omegaconf import OmegaConf
from omegaconf._utils import ValueKind, _is_missing_literal, get_value_kind
def build_dict(
d: Dict[str, Any], depth: int, width: int, leaf_value... | benchmark/benchmark.py | import copy
from typing import Any, Dict, List
from pytest import lazy_fixture # type: ignore
from pytest import fixture, mark, param
from omegaconf import OmegaConf
from omegaconf._utils import ValueKind, _is_missing_literal, get_value_kind
def build_dict(
d: Dict[str, Any], depth: int, width: int, leaf_value... | 0.687105 | 0.357147 |
import copy
from rbkcli.base import CONSTANTS, RbkcliBase, RbkcliException
from rbkcli.core.handlers.environment import EnvironmentHandler
from rbkcli.core.handlers.inputs import InputHandler
from rbkcli.core.handlers.outputs import OutputHandler
class ApiTarget(RbkcliBase):
"""Define the Target to wh... | rbkcli/core/target.py |
import copy
from rbkcli.base import CONSTANTS, RbkcliBase, RbkcliException
from rbkcli.core.handlers.environment import EnvironmentHandler
from rbkcli.core.handlers.inputs import InputHandler
from rbkcli.core.handlers.outputs import OutputHandler
class ApiTarget(RbkcliBase):
"""Define the Target to wh... | 0.704872 | 0.075448 |
import sys
import random
import time
from math import isclose
from string import ascii_lowercase
from enum import Enum, IntFlag, auto
from pulp import *
START_TIME = time.time()
DEFAULT_OPTIMISATION_ACCURACY = .15
ID_LOWER_BOUND = 10000000
ID_UPPER_BOUND = 99999999
NUMBER_OF_WORKDAYS = 7
MAXIMUM_CONSECUTIVE_WORKDAYS ... | workforce_scheduler.py | import sys
import random
import time
from math import isclose
from string import ascii_lowercase
from enum import Enum, IntFlag, auto
from pulp import *
START_TIME = time.time()
DEFAULT_OPTIMISATION_ACCURACY = .15
ID_LOWER_BOUND = 10000000
ID_UPPER_BOUND = 99999999
NUMBER_OF_WORKDAYS = 7
MAXIMUM_CONSECUTIVE_WORKDAYS ... | 0.602412 | 0.170094 |
from firedrake import *
import matplotlib.pyplot as plt
parameters["pyop2_options"]["lazy_evaluation"] = False
# Defining the mesh
N = 15
use_quads = True
mesh = UnitSquareMesh(N, N, quadrilateral=use_quads)
# Function space declaration
degree = 1
pressure_family = 'CG'
velocity_family = 'CG'
U = VectorFunctionSpace... | scripts/misc/ls_operator_condition_number_iterative.py | from firedrake import *
import matplotlib.pyplot as plt
parameters["pyop2_options"]["lazy_evaluation"] = False
# Defining the mesh
N = 15
use_quads = True
mesh = UnitSquareMesh(N, N, quadrilateral=use_quads)
# Function space declaration
degree = 1
pressure_family = 'CG'
velocity_family = 'CG'
U = VectorFunctionSpace... | 0.806548 | 0.464962 |
from .errors import *
class Store:
"""
Store record
Each postcode record contains basic information like name
and coordinates in WGS84 geographic system
"""
def __init__(self, postcode: str, name: str, lon: float = None, lat: float = None):
"""
Create new store record.
... | src/stores/store.py | from .errors import *
class Store:
"""
Store record
Each postcode record contains basic information like name
and coordinates in WGS84 geographic system
"""
def __init__(self, postcode: str, name: str, lon: float = None, lat: float = None):
"""
Create new store record.
... | 0.935073 | 0.425665 |
import os
from torch.utils.data import Dataset
import numpy as np
import torch
import torch.nn.functional as F
import re
class TextDataset(Dataset):
def __init__(self, txt_path, mode='train', seq_len=50, n_steps=50):
assert os.path.exists(txt_path), f"File not found {txt_path}\n"
with open(txt_pat... | engine/dataloader.py | import os
from torch.utils.data import Dataset
import numpy as np
import torch
import torch.nn.functional as F
import re
class TextDataset(Dataset):
def __init__(self, txt_path, mode='train', seq_len=50, n_steps=50):
assert os.path.exists(txt_path), f"File not found {txt_path}\n"
with open(txt_pat... | 0.54698 | 0.37439 |
import subprocess
import os
import tempfile
from testbook import testbook
from tempfile import TemporaryDirectory as tdir
from ark.utils import notebooks_test_utils
import pytest
parametrize = pytest.mark.parametrize
SEGMENT_IMAGE_DATA_PATH = os.path.join(os.path.dirname(os.path.realpath(__file__)),
... | ark/utils/notebooks_test.py | import subprocess
import os
import tempfile
from testbook import testbook
from tempfile import TemporaryDirectory as tdir
from ark.utils import notebooks_test_utils
import pytest
parametrize = pytest.mark.parametrize
SEGMENT_IMAGE_DATA_PATH = os.path.join(os.path.dirname(os.path.realpath(__file__)),
... | 0.356559 | 0.249664 |
from enum import Enum
from six import string_types, iteritems
from bitmovin_api_sdk.common.poscheck import poscheck_model
import pprint
import six
class SpriteJpegConfig(object):
@poscheck_model
def __init__(self,
quality=None):
# type: (int) -> None
self._quality = None
... | bitmovin_api_sdk/models/sprite_jpeg_config.py |
from enum import Enum
from six import string_types, iteritems
from bitmovin_api_sdk.common.poscheck import poscheck_model
import pprint
import six
class SpriteJpegConfig(object):
@poscheck_model
def __init__(self,
quality=None):
# type: (int) -> None
self._quality = None
... | 0.870005 | 0.259843 |
from __future__ import absolute_import
from __future__ import unicode_literals
import markdown
from markdown.util import etree
import re
class CollapseExtension(markdown.Extension):
""" Collapse extension for Python-Markdown. """
def extendMarkdown(self, md, md_globals):
""" Add Admonition to Markdown... | mdx_collapse.py | from __future__ import absolute_import
from __future__ import unicode_literals
import markdown
from markdown.util import etree
import re
class CollapseExtension(markdown.Extension):
""" Collapse extension for Python-Markdown. """
def extendMarkdown(self, md, md_globals):
""" Add Admonition to Markdown... | 0.527317 | 0.084078 |
import pytest
import numpy as np
import pandas as pd
from scipy.io import loadmat
from echopype import open_raw
from echopype.testing import TEST_DATA_FOLDER
@pytest.fixture
def ek80_path(test_path):
return test_path["EK80"]
def pytest_generate_tests(metafunc):
ek80_new_path = TEST_DATA_FOLDER / "ek80_new"... | echopype/tests/convert/test_convert_ek80.py | import pytest
import numpy as np
import pandas as pd
from scipy.io import loadmat
from echopype import open_raw
from echopype.testing import TEST_DATA_FOLDER
@pytest.fixture
def ek80_path(test_path):
return test_path["EK80"]
def pytest_generate_tests(metafunc):
ek80_new_path = TEST_DATA_FOLDER / "ek80_new"... | 0.460532 | 0.437223 |
import unittest
from ctypes import *
from tests.annotations import Platform, skip_platform
from pyglet import window
from pyglet.gl import *
@skip_platform(Platform.WINDOWS) # Causes crashes on Windows (issue #48)
class ContextShareTest(unittest.TestCase):
def create_context(self, share):
display = wind... | tests/integration/window/test_context_share.py | import unittest
from ctypes import *
from tests.annotations import Platform, skip_platform
from pyglet import window
from pyglet.gl import *
@skip_platform(Platform.WINDOWS) # Causes crashes on Windows (issue #48)
class ContextShareTest(unittest.TestCase):
def create_context(self, share):
display = wind... | 0.421671 | 0.456773 |
# In[1]:
RunActualDB = True
import sys
import json
import time
import random
import statistics
import pprint
import math
print("Current Python version: ", sys.version_info[0],".",sys.version_info[1],".",sys.version_info[2])
_useAllTimes = False
_print_raw = False
_DB_mode = sys.argv[1]
if _DB_mode != "AS" and _DB_m... | ConstraintTests.py |
# In[1]:
RunActualDB = True
import sys
import json
import time
import random
import statistics
import pprint
import math
print("Current Python version: ", sys.version_info[0],".",sys.version_info[1],".",sys.version_info[2])
_useAllTimes = False
_print_raw = False
_DB_mode = sys.argv[1]
if _DB_mode != "AS" and _DB_m... | 0.278944 | 0.188548 |
import os
import shutil
import tempfile
import unittest
from cros.factory.tools import install_symlinks
FAKE_SYMLINKS = {'binaries': {'fullbin': 'full', 'minibin': 'mini'}}
class TestInstallSymlinks(unittest.TestCase):
def setUp(self):
self.tmpdir = tempfile.mkdtemp(prefix='install_symlinks_unittest.')
... | py/tools/install_symlinks_unittest.py |
import os
import shutil
import tempfile
import unittest
from cros.factory.tools import install_symlinks
FAKE_SYMLINKS = {'binaries': {'fullbin': 'full', 'minibin': 'mini'}}
class TestInstallSymlinks(unittest.TestCase):
def setUp(self):
self.tmpdir = tempfile.mkdtemp(prefix='install_symlinks_unittest.')
... | 0.31785 | 0.253075 |
import json
import os
def dataPro01(path_source,path_target):
rootpath = '../data/GodText/01/'
path_source = os.path.join(rootpath,'godText_all1.json')
with open(path_source,'r') as f:
S0 = json.load(f)
S1 = []#没有新年祝福
S2 = []#只有新年祝福
s = ['新年','新春','春节','元旦','鼠年','牛年','虎年','兔年','龙年','蛇年',... | data_godText/datapro.py | import json
import os
def dataPro01(path_source,path_target):
rootpath = '../data/GodText/01/'
path_source = os.path.join(rootpath,'godText_all1.json')
with open(path_source,'r') as f:
S0 = json.load(f)
S1 = []#没有新年祝福
S2 = []#只有新年祝福
s = ['新年','新春','春节','元旦','鼠年','牛年','虎年','兔年','龙年','蛇年',... | 0.023198 | 0.125762 |
from ..utils.log import Logger
from collections import OrderedDict
from os import path
import csv
class TSVModel:
def __init__(self, directory):
"""
Load data from tab-separated values.
Arguments:
directory {str} -- Directory to open
"""
Logger.debug(__name__... | nottreal/models/m_tsv.py | from ..utils.log import Logger
from collections import OrderedDict
from os import path
import csv
class TSVModel:
def __init__(self, directory):
"""
Load data from tab-separated values.
Arguments:
directory {str} -- Directory to open
"""
Logger.debug(__name__... | 0.604866 | 0.13707 |
from __future__ import unicode_literals
from django.db import migrations
def delete_alert_email_user_options(apps, schema_editor):
"""
Processes user reports that are missing event data, and adds the appropriate data
if the event exists in Clickhouse.
"""
from sentry.utils.query import RangeQuery... | src/sentry/migrations/0032_delete_alert_email.py | from __future__ import unicode_literals
from django.db import migrations
def delete_alert_email_user_options(apps, schema_editor):
"""
Processes user reports that are missing event data, and adds the appropriate data
if the event exists in Clickhouse.
"""
from sentry.utils.query import RangeQuery... | 0.670608 | 0.200342 |
# NOC modules
from noc.core.datastream.base import DataStream
from noc.main.models.pool import Pool
from noc.main.models.timepattern import TimePattern
from noc.sa.models.managedobject import ManagedObject
class CfgPingDataStream(DataStream):
name = "cfgping"
clean_id = DataStream.clean_id_int
@classmet... | services/datastream/streams/cfgping.py |
# NOC modules
from noc.core.datastream.base import DataStream
from noc.main.models.pool import Pool
from noc.main.models.timepattern import TimePattern
from noc.sa.models.managedobject import ManagedObject
class CfgPingDataStream(DataStream):
name = "cfgping"
clean_id = DataStream.clean_id_int
@classmet... | 0.651133 | 0.189615 |
import logging
from splitio.models import splits
from splitio.api import APIException
from splitio.tasks import BaseSynchronizationTask
from splitio.tasks.util.asynctask import AsyncTask
class SplitSynchronizationTask(BaseSynchronizationTask):
"""Split Synchronization task class."""
def __init__(self, split... | splitio/tasks/split_sync.py |
import logging
from splitio.models import splits
from splitio.api import APIException
from splitio.tasks import BaseSynchronizationTask
from splitio.tasks.util.asynctask import AsyncTask
class SplitSynchronizationTask(BaseSynchronizationTask):
"""Split Synchronization task class."""
def __init__(self, split... | 0.780453 | 0.292317 |
from configs.wfmconfig import tool_tokeniser
from configs.wfmconfig import tool_translator
class Translator:
def __init__(self):
pass
def is_contains_list_of_paragraphs(self, task_output):
if isinstance(task_output["output"], list):
if len(task_output["output"]) > 0 and isinstance... | anuvaad-etl/anuvaad-workflow-mgr/etl-wf-manager/tools/translator.py | from configs.wfmconfig import tool_tokeniser
from configs.wfmconfig import tool_translator
class Translator:
def __init__(self):
pass
def is_contains_list_of_paragraphs(self, task_output):
if isinstance(task_output["output"], list):
if len(task_output["output"]) > 0 and isinstance... | 0.483405 | 0.168686 |
import os
import torch, torchaudio
import itertools
from shutil import copyfile
class BasePreprocessor:
def __init__(self, data_dir, output_dir, overwrite_files, bulk_process, extensions = None):
# organization
self.data_dir = data_dir
self.output_dir = output_dir
self.overwrite_fi... | base/base_preprocessor.py | import os
import torch, torchaudio
import itertools
from shutil import copyfile
class BasePreprocessor:
def __init__(self, data_dir, output_dir, overwrite_files, bulk_process, extensions = None):
# organization
self.data_dir = data_dir
self.output_dir = output_dir
self.overwrite_fi... | 0.287768 | 0.137822 |
import tempfile
from six import integer_types
from mock import patch, Mock
from unittest import TestCase
from termius.core.models.terminal import (
Host, SshConfig, Identity, SshKey, Group
)
from termius.core.exceptions import DoesNotExistException
from termius.core.storage.strategies import (
GetStrategy, Save... | tests/unit/core/storage/storage_test.py | import tempfile
from six import integer_types
from mock import patch, Mock
from unittest import TestCase
from termius.core.models.terminal import (
Host, SshConfig, Identity, SshKey, Group
)
from termius.core.exceptions import DoesNotExistException
from termius.core.storage.strategies import (
GetStrategy, Save... | 0.490236 | 0.228071 |
from pprint import pprint
import pytest
from tests import validate_error_response
class TestKeyManagement:
def test_create_key_failure_key_usage(self, kms_client):
code, content = kms_client.post(
'CreateKey',
{
"KeyUsage": "SIGN_VERIFY",
},
)
... | tests/functional/tests/cmk/test_key_management.py | from pprint import pprint
import pytest
from tests import validate_error_response
class TestKeyManagement:
def test_create_key_failure_key_usage(self, kms_client):
code, content = kms_client.post(
'CreateKey',
{
"KeyUsage": "SIGN_VERIFY",
},
)
... | 0.625438 | 0.418875 |
from django.contrib.auth import get_user_model
from django.urls import reverse
from django.test import TestCase
from rest_framework import status
from rest_framework.test import APIClient
from core.models import Secteur
from formulaire.serializers import SecteurSerializer
SECTEURS_URL = reverse('formulaire:secteur... | app/formulaire/tests/test_secteurs_api.py | from django.contrib.auth import get_user_model
from django.urls import reverse
from django.test import TestCase
from rest_framework import status
from rest_framework.test import APIClient
from core.models import Secteur
from formulaire.serializers import SecteurSerializer
SECTEURS_URL = reverse('formulaire:secteur... | 0.551574 | 0.243182 |
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from database_setup import Base, User, Category, Item
# Connect to Database and create database session
engine = create_engine('postgresql://catalog:catalog@localhost/catalog')
Base.metadata.bind = engine
DBSession = sessionmaker(bind=engine... | database_seed.py | from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from database_setup import Base, User, Category, Item
# Connect to Database and create database session
engine = create_engine('postgresql://catalog:catalog@localhost/catalog')
Base.metadata.bind = engine
DBSession = sessionmaker(bind=engine... | 0.438064 | 0.161386 |
import argparse
import os
import sys
import datetime
import filecmp
import logging
from urllib.error import URLError
from urllib.request import urlopen
from apscheduler.schedulers.blocking import BlockingScheduler
from apscheduler.triggers.cron import CronTrigger
URL = 'https://viewer.by/img/client/{}/1/view01.jpg'
... | snapshotter.py | import argparse
import os
import sys
import datetime
import filecmp
import logging
from urllib.error import URLError
from urllib.request import urlopen
from apscheduler.schedulers.blocking import BlockingScheduler
from apscheduler.triggers.cron import CronTrigger
URL = 'https://viewer.by/img/client/{}/1/view01.jpg'
... | 0.254602 | 0.068257 |
if __name__ == '__main__':
import collectd_fake as collectd
else:
import collectd
from pyroute2 import IPRoute
import socket
import collectd_base as base
NAME = 'vrrp'
class VrrpPlugin(base.Base):
def __init__(self, *args, **kwargs):
super(VrrpPlugin, self).__init__(*args, **kwargs)
se... | files/collectd-modules/collectd_vrrp.py |
if __name__ == '__main__':
import collectd_fake as collectd
else:
import collectd
from pyroute2 import IPRoute
import socket
import collectd_base as base
NAME = 'vrrp'
class VrrpPlugin(base.Base):
def __init__(self, *args, **kwargs):
super(VrrpPlugin, self).__init__(*args, **kwargs)
se... | 0.452536 | 0.089137 |
import re
import sys
import getopt
from extractors import *
from lpIO import *
from converters import *
"""
Author
<NAME> (https://github.com/Leajian)
Program name
Linear Problem Parser (lpp)
Version
2.2
"""
def main(argv):
# Initialize varibales.
inputFile = ''
outp... | lpp.py | import re
import sys
import getopt
from extractors import *
from lpIO import *
from converters import *
"""
Author
<NAME> (https://github.com/Leajian)
Program name
Linear Problem Parser (lpp)
Version
2.2
"""
def main(argv):
# Initialize varibales.
inputFile = ''
outp... | 0.276007 | 0.196884 |
import uuid
from stdnet.backends.base import BaseBackend, ImproperlyConfigured, novalue
from stdnet.backends.structures.structcouchdb import List,Set,HashTable,Map
try:
import couchdb
except:
raise ImproperlyConfigured("CouchDB backend requires the 'couchdb-python' library. Do easy_install couchdb-python")
R... | stdnet/backends/couchdbb.py | import uuid
from stdnet.backends.base import BaseBackend, ImproperlyConfigured, novalue
from stdnet.backends.structures.structcouchdb import List,Set,HashTable,Map
try:
import couchdb
except:
raise ImproperlyConfigured("CouchDB backend requires the 'couchdb-python' library. Do easy_install couchdb-python")
R... | 0.40157 | 0.059866 |
import numpy as np
import math
import torch
def _t2n(x):
"""Convert torch tensor to a numpy array."""
return x.detach().cpu().numpy()
def check(input):
if type(input) == np.ndarray:
return torch.from_numpy(input)
def get_gard_norm(it):
sum_grad = 0
for x in it:
if x.grad i... | MAModule/utils/util.py | import numpy as np
import math
import torch
def _t2n(x):
"""Convert torch tensor to a numpy array."""
return x.detach().cpu().numpy()
def check(input):
if type(input) == np.ndarray:
return torch.from_numpy(input)
def get_gard_norm(it):
sum_grad = 0
for x in it:
if x.grad i... | 0.841272 | 0.596933 |
import matplotlib.pyplot as plt
import h5py
from deoxys_image import normalize, gaussian_noise, change_brightness
from deoxys_image import change_contrast, gaussian_blur
def load_images(index=0):
with h5py.File(
'../../hn_perf/3d_unet_32/prediction/prediction.030.h5', 'r') as f:
image = f['x']... | examples/point_operation_3d.py | import matplotlib.pyplot as plt
import h5py
from deoxys_image import normalize, gaussian_noise, change_brightness
from deoxys_image import change_contrast, gaussian_blur
def load_images(index=0):
with h5py.File(
'../../hn_perf/3d_unet_32/prediction/prediction.030.h5', 'r') as f:
image = f['x']... | 0.557966 | 0.475666 |
from config import load_config
import sys
import numpy as np
import re
import tensorflow as tf
import BERT_Model as brt
import utils as utl
tf.set_random_seed(42)
np.random.seed(42)
def get_predict(result, output):
result = np.argmax(result, axis=1)
max_index = -1
max_pro = 0.0
for i in... | main.py | from config import load_config
import sys
import numpy as np
import re
import tensorflow as tf
import BERT_Model as brt
import utils as utl
tf.set_random_seed(42)
np.random.seed(42)
def get_predict(result, output):
result = np.argmax(result, axis=1)
max_index = -1
max_pro = 0.0
for i in... | 0.331012 | 0.248363 |
from wiremock._compat import add_metaclass
from wiremock.base import BaseEntity, JsonProperty, BaseAbstractEntity, BaseEntityMetaType
class HttpMethods(object):
ANY = "ANY"
GET = "GET"
POST = "POST"
PUT = "PUT"
PATCH = "PATCH"
DELETE = "DELETE"
OPTIONS = "OPTIONS"
HEAD = "HEAD"
class... | wiremock/resources/mappings/models.py | from wiremock._compat import add_metaclass
from wiremock.base import BaseEntity, JsonProperty, BaseAbstractEntity, BaseEntityMetaType
class HttpMethods(object):
ANY = "ANY"
GET = "GET"
POST = "POST"
PUT = "PUT"
PATCH = "PATCH"
DELETE = "DELETE"
OPTIONS = "OPTIONS"
HEAD = "HEAD"
class... | 0.611962 | 0.071559 |
import csv
import json
import operator
import sys, os
from typing import List, Dict
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '.')))
class Pivot:
def __init__(self,
file_list: List[str],
header_list: List[str],
strict: bool,
... | json2rst/pivot.py | import csv
import json
import operator
import sys, os
from typing import List, Dict
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '.')))
class Pivot:
def __init__(self,
file_list: List[str],
header_list: List[str],
strict: bool,
... | 0.464902 | 0.226035 |
import os
import argparse
from glob import glob
from functools import partial
import numpy as np
from tqdm import tqdm
import matplotlib.pyplot as plt
import cv2
from PIL import Image
import wandb
import jax
import jax.numpy as jnp
import flax
import torch
import torchvision.transforms as transforms
import tensorf... | old/dcgan-selfie-old.py | import os
import argparse
from glob import glob
from functools import partial
import numpy as np
from tqdm import tqdm
import matplotlib.pyplot as plt
import cv2
from PIL import Image
import wandb
import jax
import jax.numpy as jnp
import flax
import torch
import torchvision.transforms as transforms
import tensorf... | 0.775945 | 0.383093 |
import numpy as np
import matplotlib.pyplot as plt
import tools
def plotData(input_file, output_file, plot_dir, title, column_indices, xlim, ylim, drawMean):
verbose = False
tools.makeDir(plot_dir)
data = tools.getData(input_file)
output_png = "{0}/{1}.png".format(plot_dir, output_file)
output_pdf... | EyeDiagrams/python/plotComparison.py |
import numpy as np
import matplotlib.pyplot as plt
import tools
def plotData(input_file, output_file, plot_dir, title, column_indices, xlim, ylim, drawMean):
verbose = False
tools.makeDir(plot_dir)
data = tools.getData(input_file)
output_png = "{0}/{1}.png".format(plot_dir, output_file)
output_pdf... | 0.53048 | 0.651133 |
from selenium import webdriver
import time
import os
from datetime import datetime
import json
"""" Directory to globals file """
GLOBALS_FILE = "./globals/globals.json"
def load_globals():
""" Read content from globals file
Returns:
dict: fDictionary containing the content of the globals file
... | transform/transform/scrapers/utils.py | from selenium import webdriver
import time
import os
from datetime import datetime
import json
"""" Directory to globals file """
GLOBALS_FILE = "./globals/globals.json"
def load_globals():
""" Read content from globals file
Returns:
dict: fDictionary containing the content of the globals file
... | 0.609292 | 0.209814 |
"""Helps define a foreign key relationship between two models."""
from typing import Any, Mapping, Type
import dataclasses
from spanner_orm import registry
@dataclasses.dataclass
class ForeignKeyRelationshipConstraint:
columns: Mapping[str, str]
referenced_table_name: str
referenced_table: Type[Any]
class F... | spanner_orm/foreign_key_relationship.py | """Helps define a foreign key relationship between two models."""
from typing import Any, Mapping, Type
import dataclasses
from spanner_orm import registry
@dataclasses.dataclass
class ForeignKeyRelationshipConstraint:
columns: Mapping[str, str]
referenced_table_name: str
referenced_table: Type[Any]
class F... | 0.962143 | 0.545649 |
from CLIF_Framework.framework import event
from CLIF_Framework.framework import tools
from os import system
from time import sleep
from time import time
from threading import Thread
import socket
event = event()
tools = tools()
class Main:
def __init__(selfie, console):
global self
global var
self = selfie
v... | modules/l4/main.py | from CLIF_Framework.framework import event
from CLIF_Framework.framework import tools
from os import system
from time import sleep
from time import time
from threading import Thread
import socket
event = event()
tools = tools()
class Main:
def __init__(selfie, console):
global self
global var
self = selfie
v... | 0.13408 | 0.093927 |
from collections import OrderedDict
import arviz as az
import numpy as np
import pytest
from matplotlib import pyplot as pl
from matplotlib.testing.decorators import image_comparison
import corner
try:
import pandas as pd
except ImportError:
pd = None
try:
import scipy # noqa
except ImportError:
s... | tests/test_corner.py |
from collections import OrderedDict
import arviz as az
import numpy as np
import pytest
from matplotlib import pyplot as pl
from matplotlib.testing.decorators import image_comparison
import corner
try:
import pandas as pd
except ImportError:
pd = None
try:
import scipy # noqa
except ImportError:
s... | 0.636466 | 0.439086 |
import colectica
from colectica import ColecticaObject
import api
import pandas as pd
import os
import numpy as np
def get_all_series(C):
"""
Get a list of all series
"""
all_series = C.general_search(C.item_code('Series'),'',MaxResults=0)['Results']
return all_series
def from_series_get_study(C... | get_mode_collection.py | import colectica
from colectica import ColecticaObject
import api
import pandas as pd
import os
import numpy as np
def get_all_series(C):
"""
Get a list of all series
"""
all_series = C.general_search(C.item_code('Series'),'',MaxResults=0)['Results']
return all_series
def from_series_get_study(C... | 0.35209 | 0.345188 |
import logging
import random
from typing import List, Union
import discord
from discord.ext import commands
from naotimes.bot import naoTimesBot
from naotimes.context import naoTimesContext
from naotimes.paginator import DiscordPaginatorUI
from naotimes.utils import complex_walk, cutoff_text
IMAGEBOORU_SCHEMAS = """... | cogs/bahaya/booru.py | import logging
import random
from typing import List, Union
import discord
from discord.ext import commands
from naotimes.bot import naoTimesBot
from naotimes.context import naoTimesContext
from naotimes.paginator import DiscordPaginatorUI
from naotimes.utils import complex_walk, cutoff_text
IMAGEBOORU_SCHEMAS = """... | 0.698227 | 0.187411 |
import pytest
import numpy as np
import dowhy.api
from dowhy.causal_estimators.propensity_score_weighting_estimator import PropensityScoreWeightingEstimator
from .base import TestEstimator
from sklearn.linear_model import LinearRegression
class TestPropensityScoreMatchingEstimator(object):
@pytest.mark.parametr... | tests/causal_estimators/test_propensity_score_weighting_estimator.py | import pytest
import numpy as np
import dowhy.api
from dowhy.causal_estimators.propensity_score_weighting_estimator import PropensityScoreWeightingEstimator
from .base import TestEstimator
from sklearn.linear_model import LinearRegression
class TestPropensityScoreMatchingEstimator(object):
@pytest.mark.parametr... | 0.695131 | 0.545891 |
from collections import namedtuple
import pickle
import sys
from os.path import exists
from http.cookiejar import LWPCookieJar
from copy import copy
import json
import requests
from greencache.simple_cache import SimpleCache
from htmq.html_query import htmq
g_debug = True
Option = namedtuple('Option', ['title', 'va... | vote/straw_poll.py | from collections import namedtuple
import pickle
import sys
from os.path import exists
from http.cookiejar import LWPCookieJar
from copy import copy
import json
import requests
from greencache.simple_cache import SimpleCache
from htmq.html_query import htmq
g_debug = True
Option = namedtuple('Option', ['title', 'va... | 0.15588 | 0.053775 |
__author__ = 'kzhao'
from pyparsing import Word, nums, Combine, OneOrMore, Forward, Suppress, alphanums, Optional
from utils import Singleton
from type import TypeSystem, ComplexType, TypeEnv
from lambda_expr import Variable, Constant, App, Lambda, TypeInferer
_TS = TypeSystem()
class LambdaExprParser(object):
... | code/NLPCode/TISP/lambda_expr/lambda_expr_parser.py |
__author__ = 'kzhao'
from pyparsing import Word, nums, Combine, OneOrMore, Forward, Suppress, alphanums, Optional
from utils import Singleton
from type import TypeSystem, ComplexType, TypeEnv
from lambda_expr import Variable, Constant, App, Lambda, TypeInferer
_TS = TypeSystem()
class LambdaExprParser(object):
... | 0.654784 | 0.178615 |
import asyncio
import os
import sqlite3
from concurrent.futures import ThreadPoolExecutor
from datetime import datetime
class Backend:
def __init__(self):
"""
Used to connect to the database and create required tables if they don't exist yet.
"""
self.executor = ThreadPoolExecutor... | modbus_client/db/backend.py | import asyncio
import os
import sqlite3
from concurrent.futures import ThreadPoolExecutor
from datetime import datetime
class Backend:
def __init__(self):
"""
Used to connect to the database and create required tables if they don't exist yet.
"""
self.executor = ThreadPoolExecutor... | 0.715325 | 0.182608 |
import tensorflow as tf
import time
import os
from utils import (
input_setup1,
input_setup2,
checkpoint_dir,
checkpoint_dir1,
read_data1,
merge,
#checkimage,
imsave
)
class SRCNN(object):
def __init__(self,sess, image_size, label_size,c_dim):
self.sess = sess
self.... | model.py | import tensorflow as tf
import time
import os
from utils import (
input_setup1,
input_setup2,
checkpoint_dir,
checkpoint_dir1,
read_data1,
merge,
#checkimage,
imsave
)
class SRCNN(object):
def __init__(self,sess, image_size, label_size,c_dim):
self.sess = sess
self.... | 0.61451 | 0.275501 |
import argparse
import os
from pathlib import Path
import matplotlib.pyplot as plt
import pandas as pd
import tikzplotlib
def plot_data(input_dir, output_dir, main_scenario, show_plot):
"""plot SA evaluation data"""
sa_df = pd.read_csv(input_dir.joinpath(main_scenario))
bag_frequency = 0.05
sa_df["t... | awareness_detector/util/plot_sa.py |
import argparse
import os
from pathlib import Path
import matplotlib.pyplot as plt
import pandas as pd
import tikzplotlib
def plot_data(input_dir, output_dir, main_scenario, show_plot):
"""plot SA evaluation data"""
sa_df = pd.read_csv(input_dir.joinpath(main_scenario))
bag_frequency = 0.05
sa_df["t... | 0.519278 | 0.667663 |
from __future__ import print_function, unicode_literals, division, absolute_import
import codecs
from asyncenocean.protocol.eep import EEP
ROW_FORMAT = '|{:8s}|{:50s}|{:8s}|{:70s}|\n'
eep = EEP()
with codecs.open('SUPPORTED_PROFILES.md', 'w', 'utf-8') as f_handle:
f_handle.write('# Supported profiles\n')
f_... | generate_supported_profiles.py | from __future__ import print_function, unicode_literals, division, absolute_import
import codecs
from asyncenocean.protocol.eep import EEP
ROW_FORMAT = '|{:8s}|{:50s}|{:8s}|{:70s}|\n'
eep = EEP()
with codecs.open('SUPPORTED_PROFILES.md', 'w', 'utf-8') as f_handle:
f_handle.write('# Supported profiles\n')
f_... | 0.398172 | 0.148355 |
import unittest
class Solution:
@staticmethod
def lengthOfLongestSubstring(s: str) -> int:
"""
Given a string, find the length of the longest substring without repeating characters.
Example 1:
Input: "abcabcbb"
Output: 3
Explanation: The answer is "abc", with ... | python/longest_substring_without_repeating_characters.py | import unittest
class Solution:
@staticmethod
def lengthOfLongestSubstring(s: str) -> int:
"""
Given a string, find the length of the longest substring without repeating characters.
Example 1:
Input: "abcabcbb"
Output: 3
Explanation: The answer is "abc", with ... | 0.789437 | 0.702103 |
from enum import Enum, auto
class OperatorPrecedence(Enum):
"""
Represents the precedence of an operator.
"""
LOWEST = 0 # Unary minus.
PLUS = auto() # Either + or -.
MUL = auto() # Either * or /.
POW = auto() # Power (**).
ADDROF = auto() # Address-of operator ... | examples/starkex-cairo/starkware/python/expression_string.py | from enum import Enum, auto
class OperatorPrecedence(Enum):
"""
Represents the precedence of an operator.
"""
LOWEST = 0 # Unary minus.
PLUS = auto() # Either + or -.
MUL = auto() # Either * or /.
POW = auto() # Power (**).
ADDROF = auto() # Address-of operator ... | 0.893181 | 0.521227 |
from __future__ import print_function
import os
import csv
from subprocess import check_call
from django.db import transaction, connection
from django.core.management import call_command
from .base import BaseCommand, CommandError
from pupa.models import Division
OCDID_REPO = 'https://github.com/opencivicdata/ocd-di... | pupa/cli/commands/dbinit.py | from __future__ import print_function
import os
import csv
from subprocess import check_call
from django.db import transaction, connection
from django.core.management import call_command
from .base import BaseCommand, CommandError
from pupa.models import Division
OCDID_REPO = 'https://github.com/opencivicdata/ocd-di... | 0.359364 | 0.063106 |
from typing import Optional, Union
import attr
import pendulum
from procrastinate import exceptions
class BaseRetryStrategy:
"""
If you want to implement your own retry strategy, you can inherit from this class.
Children classes only need to implement `get_schedule_in`.
"""
def get_retry_except... | procrastinate/retry.py | from typing import Optional, Union
import attr
import pendulum
from procrastinate import exceptions
class BaseRetryStrategy:
"""
If you want to implement your own retry strategy, you can inherit from this class.
Children classes only need to implement `get_schedule_in`.
"""
def get_retry_except... | 0.949693 | 0.357483 |
# stdlib imports
from __future__ import print_function
import logging
import threading
from datetime import datetime
# third-party libraries
from flask import Flask, request
# application imports
import olivaw.tasks as tasks
import olivaw.telegram as telegram
from olivaw.settings import secrets
from olivaw.schedule imp... | olivaw/main.py | # stdlib imports
from __future__ import print_function
import logging
import threading
from datetime import datetime
# third-party libraries
from flask import Flask, request
# application imports
import olivaw.tasks as tasks
import olivaw.telegram as telegram
from olivaw.settings import secrets
from olivaw.schedule imp... | 0.514644 | 0.052328 |
import random
from biosim.animal import Herbivore, Carnivore
class Island:
"""The Island object collects all landscape cells in the map and keeps track of animals.
:param map_str: The representation of cell types in the simulation
:type map_str: str
:Example:
.. code-block:: python
... | biosim/landscape.py | import random
from biosim.animal import Herbivore, Carnivore
class Island:
"""The Island object collects all landscape cells in the map and keeps track of animals.
:param map_str: The representation of cell types in the simulation
:type map_str: str
:Example:
.. code-block:: python
... | 0.750736 | 0.557364 |
from contextlib import contextmanager
import ast
import sys
@contextmanager
def parse_source(path):
with open(path) as f:
content = f.read()
yield SourceCode(content)
def bold(s):
s = '\033[1m' + str(s) + '\033[0m'
return s
def grepfunc():
query = sys.argv[1]
path = sys.argv[2]... | pygrep.py | from contextlib import contextmanager
import ast
import sys
@contextmanager
def parse_source(path):
with open(path) as f:
content = f.read()
yield SourceCode(content)
def bold(s):
s = '\033[1m' + str(s) + '\033[0m'
return s
def grepfunc():
query = sys.argv[1]
path = sys.argv[2]... | 0.289171 | 0.144752 |
import marshmallow
from commercetools import helpers, types
from commercetools.schemas._common import (
BaseResourceSchema,
ReferenceSchema,
ResourceIdentifierSchema,
)
from commercetools.schemas._type import FieldContainerField
__all__ = [
"InventoryEntryAddQuantityActionSchema",
"InventoryEntry... | src/commercetools/schemas/_inventory.py |
import marshmallow
from commercetools import helpers, types
from commercetools.schemas._common import (
BaseResourceSchema,
ReferenceSchema,
ResourceIdentifierSchema,
)
from commercetools.schemas._type import FieldContainerField
__all__ = [
"InventoryEntryAddQuantityActionSchema",
"InventoryEntry... | 0.661704 | 0.175414 |
"""Test the TcEx Batch Module."""
from datetime import datetime
import re
import pytest
# pylint: disable=R0201,W0201
class TestUtils:
"""Test the TcEx Batch Module."""
def setup_class(self):
"""Configure setup before all tests."""
@pytest.mark.parametrize(
'date,tz,results',
[
... | tests/utils/test_date_methods.py | """Test the TcEx Batch Module."""
from datetime import datetime
import re
import pytest
# pylint: disable=R0201,W0201
class TestUtils:
"""Test the TcEx Batch Module."""
def setup_class(self):
"""Configure setup before all tests."""
@pytest.mark.parametrize(
'date,tz,results',
[
... | 0.511473 | 0.411702 |
import torch
import torch.nn as nn
import torch.nn.functional as F
# Define model architecture
class SetConv2(nn.Module):
def __init__(self, sample_feats, predicate_feats, join_feats, scard_feats, hid_units):
super(SetConv2, self).__init__()
self.sample_mlp1 = nn.Linear(sample_feats, hid_units)
... | code/model/model2.py | import torch
import torch.nn as nn
import torch.nn.functional as F
# Define model architecture
class SetConv2(nn.Module):
def __init__(self, sample_feats, predicate_feats, join_feats, scard_feats, hid_units):
super(SetConv2, self).__init__()
self.sample_mlp1 = nn.Linear(sample_feats, hid_units)
... | 0.780662 | 0.465934 |