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 math import sin, cos, radians, sqrt, acos, degrees
import numpy as np
from numpy_utilities import normalize
from os.path import isfile, join
from ringDetection import getNormVec, getAverageCoords
def writeAnionPiHeader( ):
"""
Zapisz naglowki do pliku z wynikami:
"""
resultsFileName = "logs/anion... | supramolecularLogging.py | from math import sin, cos, radians, sqrt, acos, degrees
import numpy as np
from numpy_utilities import normalize
from os.path import isfile, join
from ringDetection import getNormVec, getAverageCoords
def writeAnionPiHeader( ):
"""
Zapisz naglowki do pliku z wynikami:
"""
resultsFileName = "logs/anion... | 0.291888 | 0.29523 |
import re
from random import randint
class Status():
"""Sample class to parse HTTP method"""
def __init__(self):
"""Init"""
self.last_lines = []
self.handle_method = False
def handle_http_method(self):
"""find http method"""
http_meth = ""
if self.handle_me... | plugins/AspNetMvcPlugin.py | import re
from random import randint
class Status():
"""Sample class to parse HTTP method"""
def __init__(self):
"""Init"""
self.last_lines = []
self.handle_method = False
def handle_http_method(self):
"""find http method"""
http_meth = ""
if self.handle_me... | 0.46563 | 0.118258 |
import unittest
from day1 import FuelCounterUpper
class TestFuelCounterUpper(unittest.TestCase):
def test_add_module_types(self):
"""
Checks for TypeError
"""
f = FuelCounterUpper()
with self.assertRaises(TypeError):
# noinspection PyTypeChecker
f.a... | day1/tests/__init__.py | import unittest
from day1 import FuelCounterUpper
class TestFuelCounterUpper(unittest.TestCase):
def test_add_module_types(self):
"""
Checks for TypeError
"""
f = FuelCounterUpper()
with self.assertRaises(TypeError):
# noinspection PyTypeChecker
f.a... | 0.792544 | 0.742713 |
from django.utils.translation import ugettext_lazy as _
import floppyforms.__future__ as forms
class ActionForm(forms.Form):
action = forms.ChoiceField(label=_('Action'), choices=())
objects = forms.ModelMultipleChoiceField(
queryset=None,
widget=forms.MultipleHiddenInput,
required=Fal... | django_backend/backend/forms.py | from django.utils.translation import ugettext_lazy as _
import floppyforms.__future__ as forms
class ActionForm(forms.Form):
action = forms.ChoiceField(label=_('Action'), choices=())
objects = forms.ModelMultipleChoiceField(
queryset=None,
widget=forms.MultipleHiddenInput,
required=Fal... | 0.559531 | 0.095392 |
from cli import parse_argv
import face_recognition
from os import walk
# default settings
default_settings = {
"work": "Mail", # the name of the working app
"leis": "Google Chrome", # the name of the leisure app
"show": False, # display video capture and face found
"rest": 0.5, ... | services.py | from cli import parse_argv
import face_recognition
from os import walk
# default settings
default_settings = {
"work": "Mail", # the name of the working app
"leis": "Google Chrome", # the name of the leisure app
"show": False, # display video capture and face found
"rest": 0.5, ... | 0.691602 | 0.267381 |
from asyncio import Future
from datetime import timedelta
from typing import Optional, Union, Callable
from reactivestreams.publisher import Publisher
from rsocket.extensions.mimetypes import WellKnownMimeTypes
from rsocket.helpers import create_future
from rsocket.payload import Payload
from rsocket.request_handler i... | rsocket/rsocket_server.py | from asyncio import Future
from datetime import timedelta
from typing import Optional, Union, Callable
from reactivestreams.publisher import Publisher
from rsocket.extensions.mimetypes import WellKnownMimeTypes
from rsocket.helpers import create_future
from rsocket.payload import Payload
from rsocket.request_handler i... | 0.916044 | 0.05301 |
import numpy as np
import ffmpeg
from slicerator import Slicerator
__all__ = ['ReadVideoFFMPEG', 'WriteVideoFFMPEG']
@Slicerator.from_class
class ReadVideoFFMPEG:
"""
ReadVideoFFMPEG reads images from video using FFMPEG
Attributes
----------
filename : str
full path and filename for vide... | labvision/video/ffmpeg_io.py | import numpy as np
import ffmpeg
from slicerator import Slicerator
__all__ = ['ReadVideoFFMPEG', 'WriteVideoFFMPEG']
@Slicerator.from_class
class ReadVideoFFMPEG:
"""
ReadVideoFFMPEG reads images from video using FFMPEG
Attributes
----------
filename : str
full path and filename for vide... | 0.696578 | 0.193776 |
import os
import sys
import json
import time
import psycopg2
import logging
import logging.handlers
import smtplib
import requests
from docker import Client
import mydb.admin_db as admin_db
import mydb.postgres_util as postgres
import mydb.mariadb_util as mariadb
import mydb.mongodb_util as mongodb
import mydb.containe... | watchdog.py | import os
import sys
import json
import time
import psycopg2
import logging
import logging.handlers
import smtplib
import requests
from docker import Client
import mydb.admin_db as admin_db
import mydb.postgres_util as postgres
import mydb.mariadb_util as mariadb
import mydb.mongodb_util as mongodb
import mydb.containe... | 0.084019 | 0.054752 |
from __future__ import (absolute_import, division, generators, nested_scopes, print_function,
unicode_literals, with_statement)
import os
import unittest
from abc import abstractmethod
from contextlib import contextmanager
from pants.base.project_tree import Dir, Link
from pants.base.scm_proj... | tests/python/pants_test/engine/test_fs.py |
from __future__ import (absolute_import, division, generators, nested_scopes, print_function,
unicode_literals, with_statement)
import os
import unittest
from abc import abstractmethod
from contextlib import contextmanager
from pants.base.project_tree import Dir, Link
from pants.base.scm_proj... | 0.574634 | 0.283131 |
import json
import socket
from mock import patch, MagicMock
from tornado.web import Application
from tornado import gen
from tornado.testing import AsyncHTTPTestCase
from blackgate.component import Component
class TestHTTPProxyFallbackDueToBrokenUpstreamConnection(AsyncHTTPTestCase):
def get_app(self):
... | tests/test_http_proxy.py |
import json
import socket
from mock import patch, MagicMock
from tornado.web import Application
from tornado import gen
from tornado.testing import AsyncHTTPTestCase
from blackgate.component import Component
class TestHTTPProxyFallbackDueToBrokenUpstreamConnection(AsyncHTTPTestCase):
def get_app(self):
... | 0.467575 | 0.178508 |
import os.path
from os import path
# set number of threads - this should be optimized per compute instance
os.environ["TF_NUM_INTEROP_THREADS"] = "8"
os.environ["TF_NUM_INTRAOP_THREADS"] = "8"
os.environ["ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS"] = "8"
import ants
import antspynet
import tensorflow as tf
import glob as ... | applications/bf_star.py | import os.path
from os import path
# set number of threads - this should be optimized per compute instance
os.environ["TF_NUM_INTEROP_THREADS"] = "8"
os.environ["TF_NUM_INTRAOP_THREADS"] = "8"
os.environ["ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS"] = "8"
import ants
import antspynet
import tensorflow as tf
import glob as ... | 0.221856 | 0.168309 |
import datetime
import os
import tensorflow.compat.v2 as tf
import b_meson_fit.coeffs as bmfc
from b_meson_fit.script import stdout
tf.enable_v2_behavior()
_now = datetime.datetime.now()
class Log:
top_dir = 'logs'
signal_name = 'signal'
"""Attributes:
top_dir (str): Project-level folder to wri... | b_meson_fit/log.py | import datetime
import os
import tensorflow.compat.v2 as tf
import b_meson_fit.coeffs as bmfc
from b_meson_fit.script import stdout
tf.enable_v2_behavior()
_now = datetime.datetime.now()
class Log:
top_dir = 'logs'
signal_name = 'signal'
"""Attributes:
top_dir (str): Project-level folder to wri... | 0.818556 | 0.284135 |
import decimal
import sys
def EdmondsKarp(mC, vizinhos, ini, fim):
fluxo = 0
iteracoes = 0
fluxos = [[0 for i in range(len(mC))] for j in range(len(mC))]
redeResidual = [[0 for i in range(len(mC))] for j in range(len(mC))]
while True:
max, P = BFS(mC, vizinhos, fluxos, ini, fim)
if... | trabalho2/1bc.py | import decimal
import sys
def EdmondsKarp(mC, vizinhos, ini, fim):
fluxo = 0
iteracoes = 0
fluxos = [[0 for i in range(len(mC))] for j in range(len(mC))]
redeResidual = [[0 for i in range(len(mC))] for j in range(len(mC))]
while True:
max, P = BFS(mC, vizinhos, fluxos, ini, fim)
if... | 0.243373 | 0.213603 |
from __future__ import absolute_import
import unittest
from six import add_move, MovedModule # noqa: E402
add_move(MovedModule('mock', 'mock', 'unittest.mock')) # noqa: E221
from six.moves import mock # noqa: E221
from aurorapy.client import AuroraBaseClient, AuroraError
class TestClient(unittest.TestCase):
... | test/test_client.py | from __future__ import absolute_import
import unittest
from six import add_move, MovedModule # noqa: E402
add_move(MovedModule('mock', 'mock', 'unittest.mock')) # noqa: E221
from six.moves import mock # noqa: E221
from aurorapy.client import AuroraBaseClient, AuroraError
class TestClient(unittest.TestCase):
... | 0.716913 | 0.546678 |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from . import outputs
from ._inputs import *
__all__ = ['RuleArgs', 'Rule']
@pulumi.input_type
class RuleArgs:
def __init__(__self__, *,
actions: pul... | sdk/python/pulumi_oci/events/rule.py |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from . import outputs
from ._inputs import *
__all__ = ['RuleArgs', 'Rule']
@pulumi.input_type
class RuleArgs:
def __init__(__self__, *,
actions: pul... | 0.893426 | 0.165121 |
import datetime
import random
from typing import Optional
from sklearn.metrics import roc_auc_score as roc_auc
from core.composer.chain import Chain
from core.composer.gp_composer.gp_composer import GPComposer, GPComposerRequirements
from core.composer.optimisers.crossover import CrossoverTypesEnum
from core... | fedot/benchmark/experiments/credit_scoring_experiment.py | import datetime
import random
from typing import Optional
from sklearn.metrics import roc_auc_score as roc_auc
from core.composer.chain import Chain
from core.composer.gp_composer.gp_composer import GPComposer, GPComposerRequirements
from core.composer.optimisers.crossover import CrossoverTypesEnum
from core... | 0.805173 | 0.226757 |
import torch
import numpy
import torch.nn as nn
import copy
from medical_seg.networks.nets.swin_unet.swin_transformer_unet_skip_expand_decoder_sys import SwinTransformerSys
class SwinUnet(nn.Module):
def __init__(self, img_size=224, in_channel=3, num_classes=21843, zero_head=False, vis=False):
super(Sw... | medical_seg/networks/nets/swin_unet/model.py | import torch
import numpy
import torch.nn as nn
import copy
from medical_seg.networks.nets.swin_unet.swin_transformer_unet_skip_expand_decoder_sys import SwinTransformerSys
class SwinUnet(nn.Module):
def __init__(self, img_size=224, in_channel=3, num_classes=21843, zero_head=False, vis=False):
super(Sw... | 0.783533 | 0.272191 |
import os
import pandas as pd
import numpy as np
import re
from scripts import versionfinal,versionurgencia,versionespecifico,identificacionmotor,motorseguncilindrada,corregirmarca, progreso, motor, quitardecimal, valores, modelogeneral, especifico, origensegunvin, version, modelogenerico, especifico2, corregirmodelo, ... | Country cleaning/Costa Rica_final.py | import os
import pandas as pd
import numpy as np
import re
from scripts import versionfinal,versionurgencia,versionespecifico,identificacionmotor,motorseguncilindrada,corregirmarca, progreso, motor, quitardecimal, valores, modelogeneral, especifico, origensegunvin, version, modelogenerico, especifico2, corregirmodelo, ... | 0.174059 | 0.237024 |
from dataclasses import dataclass, field
from typing import Dict, List, Set, Type
import numpy as np
import cirq, cirq_google
from cirq import _compat, devices
from cirq.devices import noise_utils
from cirq.transformers.heuristic_decompositions import gate_tabulation_math_utils
SINGLE_QUBIT_GATES: Set[Type['cirq.Gat... | cirq-google/cirq_google/devices/google_noise_properties.py | from dataclasses import dataclass, field
from typing import Dict, List, Set, Type
import numpy as np
import cirq, cirq_google
from cirq import _compat, devices
from cirq.devices import noise_utils
from cirq.transformers.heuristic_decompositions import gate_tabulation_math_utils
SINGLE_QUBIT_GATES: Set[Type['cirq.Gat... | 0.934058 | 0.584805 |
import json
from pathlib import Path
from typing import List, Tuple
import extruct
import requests
import scrape_schema_recipe
from slugify import slugify
from utils.logger import logger
from w3lib.html import get_base_url
from services.image_services import scrape_image
from services.recipe_services import Recipe
C... | mealie/services/scrape_services.py | import json
from pathlib import Path
from typing import List, Tuple
import extruct
import requests
import scrape_schema_recipe
from slugify import slugify
from utils.logger import logger
from w3lib.html import get_base_url
from services.image_services import scrape_image
from services.recipe_services import Recipe
C... | 0.419529 | 0.233991 |
import torch
import numpy as np
from torch.utils.data import Subset
import torchvision.transforms as transforms
from torchvision.datasets import ImageFolder
def get_target_label_idx(labels, targets):
"""
Get the indices of labels that are included in targets.
:param labels: array of labels
:param targe... | src/datasets/min_max_calculate.py | import torch
import numpy as np
from torch.utils.data import Subset
import torchvision.transforms as transforms
from torchvision.datasets import ImageFolder
def get_target_label_idx(labels, targets):
"""
Get the indices of labels that are included in targets.
:param labels: array of labels
:param targe... | 0.769687 | 0.728905 |
import numpy as np
class MeasurementData:
"""Generates object_generated measurements and clutter"""
def __init__(
self,
object_data,
sensor_model,
meas_model,
random_state=None,
):
"""Generates object generated measurement and clutter
Args:
... | src/mot/simulator/measurement_data_generator.py | import numpy as np
class MeasurementData:
"""Generates object_generated measurements and clutter"""
def __init__(
self,
object_data,
sensor_model,
meas_model,
random_state=None,
):
"""Generates object generated measurement and clutter
Args:
... | 0.560974 | 0.559651 |
from .qt.QtGui import QFrame
from .q_single_widget_layout import QSingleWidgetLayout
from .qt_constraints_widget import size_hint_guard
from .qt_control import QtControl
from enable.api import Window as EnableWindow
class QtEnableCanvas(QtControl):
""" A Qt implementation of an Enaml EnableCanvas.
"""
#... | enaml/qt/qt_enable_canvas.py | from .qt.QtGui import QFrame
from .q_single_widget_layout import QSingleWidgetLayout
from .qt_constraints_widget import size_hint_guard
from .qt_control import QtControl
from enable.api import Window as EnableWindow
class QtEnableCanvas(QtControl):
""" A Qt implementation of an Enaml EnableCanvas.
"""
#... | 0.628521 | 0.153011 |
import tensorflow as tf
import json
import argparse
from models.dataset import Dataset
from models.model import Model
class RTVSRGAN(Model):
def __init__(self, args):
super().__init__(args)
self._prediction_offset = self._scale_factor * 4
def get_data(self):
data_batch, initializer = ... | teste.py | import tensorflow as tf
import json
import argparse
from models.dataset import Dataset
from models.model import Model
class RTVSRGAN(Model):
def __init__(self, args):
super().__init__(args)
self._prediction_offset = self._scale_factor * 4
def get_data(self):
data_batch, initializer = ... | 0.805785 | 0.230941 |
import numpy as np
from .utils import *
def is_regression(y):
"""
Decide if this is most likely a regression problem.
Args:
y (array): A target vector.
Returns:
bool: True if y is probably best suited to regression.
Examples:
>>> is_regression(10 * ['a', 'b'])
F... | redflag/target.py | import numpy as np
from .utils import *
def is_regression(y):
"""
Decide if this is most likely a regression problem.
Args:
y (array): A target vector.
Returns:
bool: True if y is probably best suited to regression.
Examples:
>>> is_regression(10 * ['a', 'b'])
F... | 0.892152 | 0.68802 |
import fluent_contents.extensions
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("fluent_contents", "0001_initial"),
]
operations = [
migrations.CreateModel(
name="PagerItem",
fields=[
(
... | fluentcms_pager/migrations/0001_initial.py | import fluent_contents.extensions
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("fluent_contents", "0001_initial"),
]
operations = [
migrations.CreateModel(
name="PagerItem",
fields=[
(
... | 0.475605 | 0.140071 |
import datetime
import flask
from wtforms import Form, StringField, TextAreaField
from wtforms.fields.html5 import DateField, IntegerField
from wtforms.validators import InputRequired, Length, ValidationError, DataRequired
from pyg.web import db, models
# TODO(ian) : axe the fundraiser section? Is that going to be ... | python/pyg/web/views/fundraiser.py | import datetime
import flask
from wtforms import Form, StringField, TextAreaField
from wtforms.fields.html5 import DateField, IntegerField
from wtforms.validators import InputRequired, Length, ValidationError, DataRequired
from pyg.web import db, models
# TODO(ian) : axe the fundraiser section? Is that going to be ... | 0.258513 | 0.29883 |
__author__ = 'rcj1492'
__created__ = '2017.03'
__license__ = 'MIT'
'''
PLEASE NOTE: mailgun requires domain verification to send messages
api uses <EMAIL> as sender address
make sure to add mx record under the mailgun subdomain
SETUP: https://documentation.mailgun... | labpack/email/mailgun.py | __author__ = 'rcj1492'
__created__ = '2017.03'
__license__ = 'MIT'
'''
PLEASE NOTE: mailgun requires domain verification to send messages
api uses <EMAIL> as sender address
make sure to add mx record under the mailgun subdomain
SETUP: https://documentation.mailgun... | 0.244724 | 0.069069 |
import os
from .test_base import TestBase
from mockito import when, unstub, verify, any
from mockito.invocation import InvocationError
from mockito.verification import VerificationError
class ModuleFunctionsTest(TestBase):
def tearDown(self):
unstub()
def testUnstubs(self):
when(os.path).ex... | tests/modulefunctions_test.py |
import os
from .test_base import TestBase
from mockito import when, unstub, verify, any
from mockito.invocation import InvocationError
from mockito.verification import VerificationError
class ModuleFunctionsTest(TestBase):
def tearDown(self):
unstub()
def testUnstubs(self):
when(os.path).ex... | 0.47244 | 0.50531 |
import re
import cherrypy
from girder import events
from girder.api import access
from girder.api.describe import describeRoute, Description
from girder.api.rest import boundHandler
from girder.constants import AccessType, TokenScope
from girder.exceptions import RestException, ValidationException
from girder.models.... | isic_archive/api/user.py | import re
import cherrypy
from girder import events
from girder.api import access
from girder.api.describe import describeRoute, Description
from girder.api.rest import boundHandler
from girder.constants import AccessType, TokenScope
from girder.exceptions import RestException, ValidationException
from girder.models.... | 0.234056 | 0.089415 |
import h5py
import os
import glob
from PIL import Image
import numpy as np
from random import shuffle
import tables as tb
def save_to_hdf5(path):
"""
"""
TRAINING_DATA_PECENTAGE = 0.8
TESTING_DATA_PECENTAGE = 0.1
src_path = os.path.abspath(path)
des_path = os.path.join(src_path, "..")
des... | source/save_to_hdf5.py | import h5py
import os
import glob
from PIL import Image
import numpy as np
from random import shuffle
import tables as tb
def save_to_hdf5(path):
"""
"""
TRAINING_DATA_PECENTAGE = 0.8
TESTING_DATA_PECENTAGE = 0.1
src_path = os.path.abspath(path)
des_path = os.path.join(src_path, "..")
des... | 0.159512 | 0.380183 |
import os
import uuid, json
from typing import Optional
from pymongo import MongoClient
import requests
from datetime import datetime, timedelta
class Translator():
"""
A class to call translator to translate names and descriptions to English and Swedish
Args
----------
mongo_client : MongoClient ... | service_data_processor_app/ServiceDataProcessorFunction/service_data_processor/translator.py | import os
import uuid, json
from typing import Optional
from pymongo import MongoClient
import requests
from datetime import datetime, timedelta
class Translator():
"""
A class to call translator to translate names and descriptions to English and Swedish
Args
----------
mongo_client : MongoClient ... | 0.603114 | 0.067179 |
import re
import unicodedata
from Text_Fw.interfaces.preprocessing_interface import preprocessing_interface
import spacy
from Text_Fw.preprocessing.CONTRACTION_MAP import CONTRACTION_MAP
nlp = spacy.load("en_core_web_sm")
class spacy_preprocessing(preprocessing_interface):
def __init__(self, text):
... | preprocessing/spacy_preprocessing.py | import re
import unicodedata
from Text_Fw.interfaces.preprocessing_interface import preprocessing_interface
import spacy
from Text_Fw.preprocessing.CONTRACTION_MAP import CONTRACTION_MAP
nlp = spacy.load("en_core_web_sm")
class spacy_preprocessing(preprocessing_interface):
def __init__(self, text):
... | 0.229708 | 0.097476 |
from pathlib import Path
BASE_DIR = Path(__file__).resolve().parent.parent
SECRET_KEY = NotImplemented
ALLOWED_HOSTS: list[str] = ['*']
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'djan... | node/config/settings/base.py | from pathlib import Path
BASE_DIR = Path(__file__).resolve().parent.parent
SECRET_KEY = NotImplemented
ALLOWED_HOSTS: list[str] = ['*']
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'djan... | 0.42477 | 0.100348 |
import pygame, os, sys, argparse, random
parser = argparse.ArgumentParser(description='Creates a slideshow')
parser.add_argument('path', help="the directory to get the images from")
args = parser.parse_args()
WIDTH = 1920
HEIGHT = 1080
window_size = (WIDTH, HEIGHT)
images = []
for dirname, _, filenames in o... | slideshow.py | import pygame, os, sys, argparse, random
parser = argparse.ArgumentParser(description='Creates a slideshow')
parser.add_argument('path', help="the directory to get the images from")
args = parser.parse_args()
WIDTH = 1920
HEIGHT = 1080
window_size = (WIDTH, HEIGHT)
images = []
for dirname, _, filenames in o... | 0.062796 | 0.122471 |
import json
from gmusicapi import Mobileclient
from termcolor import colored
def milisecondsToTime(miliseconds):
miliseconds = int(miliseconds)
seconds = (miliseconds / 1000) % 60
seconds = int(seconds)
minutes = (miliseconds / (1000 * 60)) % 60
minutes = int(minutes)
hours = (miliseconds / (1... | script.py | import json
from gmusicapi import Mobileclient
from termcolor import colored
def milisecondsToTime(miliseconds):
miliseconds = int(miliseconds)
seconds = (miliseconds / 1000) % 60
seconds = int(seconds)
minutes = (miliseconds / (1000 * 60)) % 60
minutes = int(minutes)
hours = (miliseconds / (1... | 0.166134 | 0.132936 |
__author__ = 'magus0219'
import logging
from config import DEBUG as _DEBUG, GITHUB as _GITHUB_CFG
from .common_handler import CommonHandler
from core.deploy_manager import dmc
from core.payload import PayLoad
import threading
import json
import hmac
from utils.mongo_handler import mongodb_client
logger_server = loggi... | handlers/deploy_handler.py | __author__ = 'magus0219'
import logging
from config import DEBUG as _DEBUG, GITHUB as _GITHUB_CFG
from .common_handler import CommonHandler
from core.deploy_manager import dmc
from core.payload import PayLoad
import threading
import json
import hmac
from utils.mongo_handler import mongodb_client
logger_server = loggi... | 0.143008 | 0.040219 |
import argparse
import numpy as np
import proxystore as ps
import time
from funcx.sdk.client import FuncXClient
from typing import List
def app_double(x: np.ndarray) -> np.ndarray:
"""Doubles input array"""
return 2 * x
def app_sum(inputs: List[np.ndarray]) -> float:
"""Sums all elements in list of arr... | examples/funcx_redis/mapreduce.py | import argparse
import numpy as np
import proxystore as ps
import time
from funcx.sdk.client import FuncXClient
from typing import List
def app_double(x: np.ndarray) -> np.ndarray:
"""Doubles input array"""
return 2 * x
def app_sum(inputs: List[np.ndarray]) -> float:
"""Sums all elements in list of arr... | 0.679498 | 0.331634 |
import requests
import csv
import datetime
import re
from bs4 import BeautifulSoup as bs
errorfile=open('ERROR_FILE_ADVISORY_DATA_RETREIVAL'+datetime.datetime.now().strftime('%Y%m%d%H%M%S%f')+'.txt','a')
inFile=r""
outFile=open('CISA_Advisory_Data_'+datetime.datetime.now().strftime('%Y%m%d%H%M%S%f')+'.csv','a'... | getCISA_Advisory_Data.py | import requests
import csv
import datetime
import re
from bs4 import BeautifulSoup as bs
errorfile=open('ERROR_FILE_ADVISORY_DATA_RETREIVAL'+datetime.datetime.now().strftime('%Y%m%d%H%M%S%f')+'.txt','a')
inFile=r""
outFile=open('CISA_Advisory_Data_'+datetime.datetime.now().strftime('%Y%m%d%H%M%S%f')+'.csv','a'... | 0.078546 | 0.046638 |
from holobot.discord.sdk.actions import ReplyAction
from holobot.discord.sdk.commands import CommandBase, CommandInterface
from holobot.discord.sdk.commands.models import CommandResponse, Option, ServerChatInteractionContext
from holobot.discord.sdk.data_providers import IBotDataProvider
from holobot.discord.sdk.models... | holobot/extensions/general/commands/view_user_avatar_command.py | from holobot.discord.sdk.actions import ReplyAction
from holobot.discord.sdk.commands import CommandBase, CommandInterface
from holobot.discord.sdk.commands.models import CommandResponse, Option, ServerChatInteractionContext
from holobot.discord.sdk.data_providers import IBotDataProvider
from holobot.discord.sdk.models... | 0.508788 | 0.075278 |
import json
import os
import sys
import datetime
from unittest import TestCase
# Prevent relative import errors
file_ = os.path.abspath(__file__)
tests_ = os.path.dirname(file_)
products_ = os.path.dirname(tests_)
shopify_ = os.path.dirname(products_)
root = os.path.dirname(shopify_)
sys.path.append(root)
from shopi... | shopify/orders/tests/test_customer.py | import json
import os
import sys
import datetime
from unittest import TestCase
# Prevent relative import errors
file_ = os.path.abspath(__file__)
tests_ = os.path.dirname(file_)
products_ = os.path.dirname(tests_)
shopify_ = os.path.dirname(products_)
root = os.path.dirname(shopify_)
sys.path.append(root)
from shopi... | 0.309545 | 0.237515 |
from __future__ import absolute_import, print_function, division
from collections import OrderedDict
import logging
from numpy import isclose
from isovar.protein_sequences import (
reads_generator_to_protein_sequences_generator,
)
from .mutant_protein_fragment import MutantProteinFragment
from .epitope_predicti... | vaxrank/core_logic.py |
from __future__ import absolute_import, print_function, division
from collections import OrderedDict
import logging
from numpy import isclose
from isovar.protein_sequences import (
reads_generator_to_protein_sequences_generator,
)
from .mutant_protein_fragment import MutantProteinFragment
from .epitope_predicti... | 0.898755 | 0.347205 |
__all__ = ["AbstractSequenceEncoder",
"SelfAttentiveSequenceEncoder",
"RNNSequenceEncoder"]
import torch
import torch.nn as nn
import torchmodels
from .attention import ShallowSelfAttention2
from .rnn import AbstractRNN
class AbstractSequenceEncoder(torchmodels.Module):
def __init__(self,... | models/seq_encoder.py | __all__ = ["AbstractSequenceEncoder",
"SelfAttentiveSequenceEncoder",
"RNNSequenceEncoder"]
import torch
import torch.nn as nn
import torchmodels
from .attention import ShallowSelfAttention2
from .rnn import AbstractRNN
class AbstractSequenceEncoder(torchmodels.Module):
def __init__(self,... | 0.950652 | 0.421195 |
import os
import re
import csv
import kdtree
import gensim
import numpy as np
import pandas as pd
import networkx as nx
from haversine import haversine
from collections import defaultdict, OrderedDict
from sklearn.neighbors import NearestNeighbors
class DataLoader:
def __init__(self, data_home, bucket_size=50, en... | data_process/dataloader.py | import os
import re
import csv
import kdtree
import gensim
import numpy as np
import pandas as pd
import networkx as nx
from haversine import haversine
from collections import defaultdict, OrderedDict
from sklearn.neighbors import NearestNeighbors
class DataLoader:
def __init__(self, data_home, bucket_size=50, en... | 0.255622 | 0.222848 |
from io import StringIO
from rich.progress import track
from nltk.tokenize import sent_tokenize
class Finder:
def __init__(self, entries: dict[str, str]) -> None:
self.entries = entries
self.occurrences = 0
self.exact_match = False
def find_and_get_output(self, word: str, exact_match... | diarium_cli/finder.py | from io import StringIO
from rich.progress import track
from nltk.tokenize import sent_tokenize
class Finder:
def __init__(self, entries: dict[str, str]) -> None:
self.entries = entries
self.occurrences = 0
self.exact_match = False
def find_and_get_output(self, word: str, exact_match... | 0.70416 | 0.230454 |
import falcon
from oslo_log import log as logging
import six
from deckhand.control import base as api_base
from deckhand.control import common
from deckhand.control.views import document as document_view
from deckhand.db.sqlalchemy import api as db_api
from deckhand.engine import document_validation
from deckhand.eng... | deckhand/control/revision_documents.py |
import falcon
from oslo_log import log as logging
import six
from deckhand.control import base as api_base
from deckhand.control import common
from deckhand.control.views import document as document_view
from deckhand.db.sqlalchemy import api as db_api
from deckhand.engine import document_validation
from deckhand.eng... | 0.691289 | 0.111919 |
import threading
import time
from gui_wx.panel import DisplayPanel
from utils import mouse, keyboard
# ========================================= Configs ===============================================
# Make sure that you've selected the FRAME_FIRST in MMD before running this script!
FRAME_FIRST = 2248
FRAME_FINAL =... | general/mmd/register_bones.py | import threading
import time
from gui_wx.panel import DisplayPanel
from utils import mouse, keyboard
# ========================================= Configs ===============================================
# Make sure that you've selected the FRAME_FIRST in MMD before running this script!
FRAME_FIRST = 2248
FRAME_FINAL =... | 0.274935 | 0.07333 |
import os
import shutil
import pytest
from mutmut import mutate, Context, mutation_id_separator
from mutmut.__main__ import main, python_source_files
from click.testing import CliRunner
file_to_mutate_lines = [
"def foo(a, b):",
" return a < b",
"e = 1",
"f = 3",
"d = dict(e=f)",
"g: int = ... | tests/test_main.py | import os
import shutil
import pytest
from mutmut import mutate, Context, mutation_id_separator
from mutmut.__main__ import main, python_source_files
from click.testing import CliRunner
file_to_mutate_lines = [
"def foo(a, b):",
" return a < b",
"e = 1",
"f = 3",
"d = dict(e=f)",
"g: int = ... | 0.497315 | 0.55935 |
import urllib.request
import pandas as pd
from django.core.files import File
from django.core.management.base import BaseCommand
from lowfat.models import Claimant
class Command(BaseCommand):
help = "Import CSV (old_applications.csv) with applications to claimantship to the database."
def add_arguments(sel... | lowfat/management/commands/loadoldapplications.py | import urllib.request
import pandas as pd
from django.core.files import File
from django.core.management.base import BaseCommand
from lowfat.models import Claimant
class Command(BaseCommand):
help = "Import CSV (old_applications.csv) with applications to claimantship to the database."
def add_arguments(sel... | 0.261708 | 0.110856 |
from __future__ import absolute_import, division, print_function
__metaclass__ = type
"""
The Prefix_lists parser templates file. This contains
a list of parser definitions and associated functions that
facilitates both facts gathering and native command generation for
the given network resource.
"""
import re
from... | venv/lib/python3.6/site-packages/ansible_collections/cisco/nxos/plugins/module_utils/network/nxos/rm_templates/prefix_lists.py |
from __future__ import absolute_import, division, print_function
__metaclass__ = type
"""
The Prefix_lists parser templates file. This contains
a list of parser definitions and associated functions that
facilitates both facts gathering and native command generation for
the given network resource.
"""
import re
from... | 0.683631 | 0.262523 |
import inventory
"""
This document contains Item classes for the items in our Danger Mouse game.
The parent class Item defines the subclasses Food and Spell.
"""
class Item:
def __init__(self, name, description, type, attack=2):
"""
Instantiates new Item.
"""
self.name = name
... | Python/danger_mouse_game/item.py | import inventory
"""
This document contains Item classes for the items in our Danger Mouse game.
The parent class Item defines the subclasses Food and Spell.
"""
class Item:
def __init__(self, name, description, type, attack=2):
"""
Instantiates new Item.
"""
self.name = name
... | 0.449755 | 0.379263 |
import torch
from optimal_stopping.algorithms.reinforcement_learning import FQI
from optimal_stopping.algorithms.utils import randomized_neural_networks
class FQI_ReservoirFast(FQI.FQIFast):
"""Computes the American option price using randomized fitted Q-Iteration (RFQI)"""
def __init__(self, model, payoff, nb_... | optimal_stopping/algorithms/reinforcement_learning/RFQI.py | import torch
from optimal_stopping.algorithms.reinforcement_learning import FQI
from optimal_stopping.algorithms.utils import randomized_neural_networks
class FQI_ReservoirFast(FQI.FQIFast):
"""Computes the American option price using randomized fitted Q-Iteration (RFQI)"""
def __init__(self, model, payoff, nb_... | 0.881456 | 0.670366 |
import hashlib
from flask import Flask, make_response, redirect, render_template, request
from flask.sessions import SecureCookieSessionInterface
from flask_login import LoginManager, UserMixin, current_user, login_user, logout_user
from flask_sqlalchemy import SQLAlchemy
app = Flask(__name__)
app.config["SESSION_COO... | web/events/app/app.py | import hashlib
from flask import Flask, make_response, redirect, render_template, request
from flask.sessions import SecureCookieSessionInterface
from flask_login import LoginManager, UserMixin, current_user, login_user, logout_user
from flask_sqlalchemy import SQLAlchemy
app = Flask(__name__)
app.config["SESSION_COO... | 0.349311 | 0.062274 |
import numpy as np
from rayoptics.optical.model_constants import ht, slp, aoi
from rayoptics.optical.model_constants import pwr, tau, indx, rmd
import rayoptics.optical.model_constants as mc
import rayoptics.parax.firstorder as fo
from rayoptics.seq.gap import Gap
from rayoptics.elem.surface import Surface
from rayop... | src/rayoptics/parax/paraxialdesign.py | import numpy as np
from rayoptics.optical.model_constants import ht, slp, aoi
from rayoptics.optical.model_constants import pwr, tau, indx, rmd
import rayoptics.optical.model_constants as mc
import rayoptics.parax.firstorder as fo
from rayoptics.seq.gap import Gap
from rayoptics.elem.surface import Surface
from rayop... | 0.635788 | 0.367639 |
from copy import deepcopy
import pytest
from dimod import ExactSolver
from docplex.mp.model import Model
from sympy import sin
from omniqubo import Omniqubo
from omniqubo.models.sympyopt.constraints import INEQ_GEQ_SENSE, ConstraintEq, ConstraintIneq
from omniqubo.models.sympyopt.sympyopt import SympyOpt
from omniqub... | test/test_omniqubo.py | from copy import deepcopy
import pytest
from dimod import ExactSolver
from docplex.mp.model import Model
from sympy import sin
from omniqubo import Omniqubo
from omniqubo.models.sympyopt.constraints import INEQ_GEQ_SENSE, ConstraintEq, ConstraintIneq
from omniqubo.models.sympyopt.sympyopt import SympyOpt
from omniqub... | 0.644225 | 0.469642 |
from pyspark.sql import *
from pyspark.sql.types import *
from pyspark.sql.functions import *
if __name__ == "__main__":
spark = SparkSession \
.builder \
.appName("dateFormatting") \
.master("local[2]") \
.getOrCreate()
my_schema_date = StructType([
StructField("ID",... | 21-DataFrames/lib/Dataframe_Creation.py | from pyspark.sql import *
from pyspark.sql.types import *
from pyspark.sql.functions import *
if __name__ == "__main__":
spark = SparkSession \
.builder \
.appName("dateFormatting") \
.master("local[2]") \
.getOrCreate()
my_schema_date = StructType([
StructField("ID",... | 0.337204 | 0.363986 |
import datetime as dt
from typing import Optional
from uuid import UUID
from pydantic import BaseModel
from sqlalchemy import Column, String, Table, ForeignKey, DateTime, Text, \
UniqueConstraint, Boolean
from database.core import metadata
from database.utils import uuid_pk, created_at, PgUUID
chat_group = Table... | backend/chat/models.py | import datetime as dt
from typing import Optional
from uuid import UUID
from pydantic import BaseModel
from sqlalchemy import Column, String, Table, ForeignKey, DateTime, Text, \
UniqueConstraint, Boolean
from database.core import metadata
from database.utils import uuid_pk, created_at, PgUUID
chat_group = Table... | 0.71123 | 0.107017 |
import tkinter as tk
import importlib.resources
from tkinter import messagebox, simpledialog
from typing import Dict, Callable
from .menus import *
from .tree_area import *
from .hex_area import *
from .events import *
from .widgets import *
from .windows import *
from ..common import *
class View(tk... | pytai/view/main.py | import tkinter as tk
import importlib.resources
from tkinter import messagebox, simpledialog
from typing import Dict, Callable
from .menus import *
from .tree_area import *
from .hex_area import *
from .events import *
from .widgets import *
from .windows import *
from ..common import *
class View(tk... | 0.709623 | 0.073696 |
import math
def Divot_Dist_func(Wrd_cir, lett_cir):
divot_dist = Wrd_cir.outer_rad - lett_cir.inner_rad + 1
circ_dist = Wrd_cir.inner_rad - lett_cir.outer_rad - 2*lett_cir.thickness
semi_dist = Wrd_cir.outer_rad
return (divot_dist, circ_dist, semi_dist)
def DotSize_func(Syllable):
Radius= Syllable.... | Custom.py | import math
def Divot_Dist_func(Wrd_cir, lett_cir):
divot_dist = Wrd_cir.outer_rad - lett_cir.inner_rad + 1
circ_dist = Wrd_cir.inner_rad - lett_cir.outer_rad - 2*lett_cir.thickness
semi_dist = Wrd_cir.outer_rad
return (divot_dist, circ_dist, semi_dist)
def DotSize_func(Syllable):
Radius= Syllable.... | 0.210198 | 0.321433 |
import os
from datetime import datetime
from dateutil.tz import gettz
from aws.dynamodb.base import DynamoDB
from common import utils
class HairSalonStaffReservation(DynamoDB):
"""HairSalonStaffReservation操作用クラス"""
__slots__ = ['_table']
def __init__(self):
"""初期化メソッド"""
table_name = os.... | backend/Layer/layer/hair_salon/hair_salon_staff_reservation.py | import os
from datetime import datetime
from dateutil.tz import gettz
from aws.dynamodb.base import DynamoDB
from common import utils
class HairSalonStaffReservation(DynamoDB):
"""HairSalonStaffReservation操作用クラス"""
__slots__ = ['_table']
def __init__(self):
"""初期化メソッド"""
table_name = os.... | 0.544801 | 0.196132 |
import datetime
from typing import NewType
import pysam
from gdc_filtration_tools.logger import Logger
from gdc_filtration_tools.utils import get_pysam_outmode
VariantFileT = NewType("VariantFileT", pysam.VariantFile)
VcfHeaderT = NewType("VcfHeaderT", pysam.VariantHeader)
def build_header(
reader: VariantFile... | gdc_filtration_tools/tools/format_gdc_vcf.py | import datetime
from typing import NewType
import pysam
from gdc_filtration_tools.logger import Logger
from gdc_filtration_tools.utils import get_pysam_outmode
VariantFileT = NewType("VariantFileT", pysam.VariantFile)
VcfHeaderT = NewType("VcfHeaderT", pysam.VariantHeader)
def build_header(
reader: VariantFile... | 0.727782 | 0.312501 |
import contextlib
from m2cgen.interpreters.code_generator import CLikeCodeGenerator
class JavaCodeGenerator(CLikeCodeGenerator):
scalar_output_type = "double"
vector_output_type = "double[]"
def __init__(self, *args, **kwargs):
super(JavaCodeGenerator, self).__init__(*args, **kwargs)
def a... | m2cgen/interpreters/java/code_generator.py | import contextlib
from m2cgen.interpreters.code_generator import CLikeCodeGenerator
class JavaCodeGenerator(CLikeCodeGenerator):
scalar_output_type = "double"
vector_output_type = "double[]"
def __init__(self, *args, **kwargs):
super(JavaCodeGenerator, self).__init__(*args, **kwargs)
def a... | 0.640186 | 0.123948 |
from nozomi.data.query_string_conforming import QueryStringConforming
from nozomi.http.query_string import QueryString
from nozomi.data.codable import Codable
from nozomi.ancillary.immutable import Immutable
from nozomi.errors.bad_request import BadRequest
from nozomi.data.sql_conforming import SQLConforming
from typin... | nozomi/data/order_by.py | from nozomi.data.query_string_conforming import QueryStringConforming
from nozomi.http.query_string import QueryString
from nozomi.data.codable import Codable
from nozomi.ancillary.immutable import Immutable
from nozomi.errors.bad_request import BadRequest
from nozomi.data.sql_conforming import SQLConforming
from typin... | 0.874507 | 0.362659 |
import sys
from abc import abstractmethod, ABC
import torch
import torch.nn as nn
import pytrol.util.argsparser as parser
from pytrol.control.agent.StatModelAgent import StatModelAgent
from pytrol.model import Paths
from pytrol.model.knowledge.EnvironmentKnowledge import EnvironmentKnowledge
from pytrol.util import... | pytrol/control/agent/MAPTrainerModelAgent.py |
import sys
from abc import abstractmethod, ABC
import torch
import torch.nn as nn
import pytrol.util.argsparser as parser
from pytrol.control.agent.StatModelAgent import StatModelAgent
from pytrol.model import Paths
from pytrol.model.knowledge.EnvironmentKnowledge import EnvironmentKnowledge
from pytrol.util import... | 0.598899 | 0.391988 |
from __future__ import unicode_literals
import frappe
from frappe.model.document import Document
from frappe import _
from frappe.utils import flt
class JournalEntry(Document):
def validate(self):
self.set_total_debit_credit()
if self.difference:
frappe.throw(_("Total Debit and Credit must be equal. The dif... | build/lib/accounting/accounting/doctype/journal_entry/journal_entry.py |
from __future__ import unicode_literals
import frappe
from frappe.model.document import Document
from frappe import _
from frappe.utils import flt
class JournalEntry(Document):
def validate(self):
self.set_total_debit_credit()
if self.difference:
frappe.throw(_("Total Debit and Credit must be equal. The dif... | 0.389198 | 0.154919 |
try:
import json
except ImportError:
import simplejson as json
import random
import re
import signal
import sys
from twisted import plugin
from twisted.application import internet, service
from twisted.python import usage
from twisted.web import resource
from zope.interface import implements
from trompet imp... | trompet/service.py |
try:
import json
except ImportError:
import simplejson as json
import random
import re
import signal
import sys
from twisted import plugin
from twisted.application import internet, service
from twisted.python import usage
from twisted.web import resource
from zope.interface import implements
from trompet imp... | 0.371935 | 0.063802 |
import copy
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch as th
from gym import spaces
from stable_baselines3.common.buffers import DictReplayBuffer
from stable_baselines3.common.type_aliases import DictReplayBufferSamples
from stable_baselines3.common.vec_env impo... | go_explore/archive.py | import copy
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch as th
from gym import spaces
from stable_baselines3.common.buffers import DictReplayBuffer
from stable_baselines3.common.type_aliases import DictReplayBufferSamples
from stable_baselines3.common.vec_env impo... | 0.89312 | 0.424621 |
import os, sys, gzip, pickle, cPickle, argparse
import matplotlib
matplotlib.use('Agg')
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import numpy as np
from tsne import tsne
from utils import unpickle, plot_map
from utils_sne import precision_K, K_neighbours
from sklearn.decomposition import PCA
RNG = ... | main.py | import os, sys, gzip, pickle, cPickle, argparse
import matplotlib
matplotlib.use('Agg')
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import numpy as np
from tsne import tsne
from utils import unpickle, plot_map
from utils_sne import precision_K, K_neighbours
from sklearn.decomposition import PCA
RNG = ... | 0.309337 | 0.230941 |
from pathlib import Path
import os
import tarfile
from typing import cast, Tuple, List
from adk.api.qne_client import QneFrontendClient
from adk.type_aliases import ApplicationDataType, AppSourceType
class ResourceManager:
"""Manager that makes sure that the correct source files are packed and ready to be upload... | src/adk/managers/resource_manager.py | from pathlib import Path
import os
import tarfile
from typing import cast, Tuple, List
from adk.api.qne_client import QneFrontendClient
from adk.type_aliases import ApplicationDataType, AppSourceType
class ResourceManager:
"""Manager that makes sure that the correct source files are packed and ready to be upload... | 0.779825 | 0.233553 |
import copy
import typing
from PartSegCore.algorithm_describe_base import SegmentationProfile
from .class_generator import SerializeClassEncoder, serialize_hook
from .image_operations import RadiusType
def recursive_update_dict(main_dict: dict, other_dict: dict):
"""
recursive update main_dict with elements... | package/PartSegCore/json_hooks.py | import copy
import typing
from PartSegCore.algorithm_describe_base import SegmentationProfile
from .class_generator import SerializeClassEncoder, serialize_hook
from .image_operations import RadiusType
def recursive_update_dict(main_dict: dict, other_dict: dict):
"""
recursive update main_dict with elements... | 0.646125 | 0.407746 |
traj_dir = './example-data/' #Path to directory containing trajectory directories {01..XX} ('./example-data/' for example, or './trajectories/' for default space of your own traj data)
ntraj = 1 #number of trajectories to parse
write_ADF = True #If True, write input files for ADF EFG calcs
write_GIPAW = True #If T... | neighbors_input.py |
traj_dir = './example-data/' #Path to directory containing trajectory directories {01..XX} ('./example-data/' for example, or './trajectories/' for default space of your own traj data)
ntraj = 1 #number of trajectories to parse
write_ADF = True #If True, write input files for ADF EFG calcs
write_GIPAW = True #If T... | 0.271735 | 0.166981 |
import src.connect_database.connection as co
import sqlite3
class SenhasModel:
def __init__(self):
self.conn = co.Connection()
def selectAll(self):
try:
self.conn.connectDB()
dados = self.conn.cursor.execute("""
SELECT id, tipo, nome, login, senha, obse... | src/model/senhasModel.py | import src.connect_database.connection as co
import sqlite3
class SenhasModel:
def __init__(self):
self.conn = co.Connection()
def selectAll(self):
try:
self.conn.connectDB()
dados = self.conn.cursor.execute("""
SELECT id, tipo, nome, login, senha, obse... | 0.249539 | 0.13612 |
import pytest
from unittest.mock import Mock
import sys
# insert at 1, 0 is the script path (or '' in REPL)
if not '../event-notifier' in sys.path:
sys.path.insert(1, '../event-notifier')
from EventNotifier.Notifier import Notifier
@pytest.fixture(scope="class") # scope="function" is default
def logg... | test/Notifier_test.py | import pytest
from unittest.mock import Mock
import sys
# insert at 1, 0 is the script path (or '' in REPL)
if not '../event-notifier' in sys.path:
sys.path.insert(1, '../event-notifier')
from EventNotifier.Notifier import Notifier
@pytest.fixture(scope="class") # scope="function" is default
def logg... | 0.308711 | 0.238539 |
import numpy as np
import numpy.linalg as la
from io import StringIO
def print_mat(mat):
stream = StringIO()
np.savetxt(stream, mat, fmt="%.3f")
print( stream.getvalue() )
# -----------------------------------
def get_convergent_vector(L, r_0, threshold=0.01):
'''
:param L: transition matrix
... | PageRank/Page Rank_stage_5.py | import numpy as np
import numpy.linalg as la
from io import StringIO
def print_mat(mat):
stream = StringIO()
np.savetxt(stream, mat, fmt="%.3f")
print( stream.getvalue() )
# -----------------------------------
def get_convergent_vector(L, r_0, threshold=0.01):
'''
:param L: transition matrix
... | 0.459319 | 0.504761 |
import os
import time
import tempfile
import unittest
import contextlib
from tpm2_pytss import tcti
from tpm2_pytss.esys import ESYS
from tpm2_pytss.fapi import FAPI, FAPIConfig
from tpm2_pytss.exceptions import TPM2Error
from tpm2_pytss.util.simulator import SimulatorTest
ENV_TCTI = "PYESYS_TCTI"
ENV_TCTI_DEFAULT = ... | tests/base_esys.py | import os
import time
import tempfile
import unittest
import contextlib
from tpm2_pytss import tcti
from tpm2_pytss.esys import ESYS
from tpm2_pytss.fapi import FAPI, FAPIConfig
from tpm2_pytss.exceptions import TPM2Error
from tpm2_pytss.util.simulator import SimulatorTest
ENV_TCTI = "PYESYS_TCTI"
ENV_TCTI_DEFAULT = ... | 0.300438 | 0.179135 |
from math import pi
from numpy import zeros, arange, broadcast_to, sin, cos
from .coefficients import SparseSHCoefficients, coeff_size
from ..magnetic_time import mjd2000_to_magnetic_universal_time
from ..time_util import mjd2000_to_year_fraction
F_SEASONAL = 2*pi
F_DIURNAL = 2*pi/24.
class SparseSHCoefficientsMIO(... | geoist/magmod/magnetic_model/coefficients_mio.py |
from math import pi
from numpy import zeros, arange, broadcast_to, sin, cos
from .coefficients import SparseSHCoefficients, coeff_size
from ..magnetic_time import mjd2000_to_magnetic_universal_time
from ..time_util import mjd2000_to_year_fraction
F_SEASONAL = 2*pi
F_DIURNAL = 2*pi/24.
class SparseSHCoefficientsMIO(... | 0.895139 | 0.469338 |
from network.Activations import Activations
import numpy
import warnings
class GenericNetwork:
def __init__(self):
# weights and biases
self.W = numpy.random.normal(scale=1.0,size=(2,3)).tolist()
self.V = numpy.random.normal(scale = 1.0, size = (3, 2)).tolist()
self.B = [0., 0., 0.]
self.C = [0.... | network/GenericNetwork.py | from network.Activations import Activations
import numpy
import warnings
class GenericNetwork:
def __init__(self):
# weights and biases
self.W = numpy.random.normal(scale=1.0,size=(2,3)).tolist()
self.V = numpy.random.normal(scale = 1.0, size = (3, 2)).tolist()
self.B = [0., 0., 0.]
self.C = [0.... | 0.338186 | 0.470007 |
import os
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from .NN import ConvModel, MLP, IQN_MLP, IQNConvModel
from .agent import Agent
class DQN(Agent):
def __init__(self, obs_shape, num_actions, modelpath, model_class=ConvModel, buffer_size=10000... | rl_suite/dqn_agent.py | import os
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from .NN import ConvModel, MLP, IQN_MLP, IQNConvModel
from .agent import Agent
class DQN(Agent):
def __init__(self, obs_shape, num_actions, modelpath, model_class=ConvModel, buffer_size=10000... | 0.68941 | 0.41834 |
import time
from uuid import UUID
import numpy as np
import numpy.typing as npt
from fastapi import HTTPException
from sklearn.cluster import DBSCAN
from sqlalchemy.orm import Session
from tslearn.utils import to_sklearn_dataset
from src.controllers import label_class_controller, project_controller, dtw_controller
fr... | backend/src/controllers/prediction_controller.py | import time
from uuid import UUID
import numpy as np
import numpy.typing as npt
from fastapi import HTTPException
from sklearn.cluster import DBSCAN
from sqlalchemy.orm import Session
from tslearn.utils import to_sklearn_dataset
from src.controllers import label_class_controller, project_controller, dtw_controller
fr... | 0.569853 | 0.27751 |
import copy
import fprime.gse.utils.gse_api
class GdsApiWrapper(object):
'''
Base class for the API wrappers. Used to implement standard functions,
as part of the wrapper API. Also provides searching algorithms for
the API wrapper.
'''
@classmethod
def get_configured_wrapper(cls, config):
... | Gse/src/fprime/gse/testing/api_wrapper.py | import copy
import fprime.gse.utils.gse_api
class GdsApiWrapper(object):
'''
Base class for the API wrappers. Used to implement standard functions,
as part of the wrapper API. Also provides searching algorithms for
the API wrapper.
'''
@classmethod
def get_configured_wrapper(cls, config):
... | 0.64713 | 0.148016 |
import itertools
import logging
import os.path as osp
import tempfile
from collections import OrderedDict
from pycocotools.coco import COCO,_isArrayLike
import time
import mmcv
import numpy as np
from .coco import CocoDataset
from .builder import DATASETS
from collections import defaultdict
from refile import smart_ope... | mmdet/datasets/external_ann.py | import itertools
import logging
import os.path as osp
import tempfile
from collections import OrderedDict
from pycocotools.coco import COCO,_isArrayLike
import time
import mmcv
import numpy as np
from .coco import CocoDataset
from .builder import DATASETS
from collections import defaultdict
from refile import smart_ope... | 0.259263 | 0.09947 |
from django.views.generic import View
from django.http import (
HttpResponse,
)
from rest_framework.response import Response
from rest_framework.decorators import api_view
from rest_framework.views import APIView
# Firstly defining the function based views
def simple(request):
if request.method == 'GET':
... | tests/views.py | from django.views.generic import View
from django.http import (
HttpResponse,
)
from rest_framework.response import Response
from rest_framework.decorators import api_view
from rest_framework.views import APIView
# Firstly defining the function based views
def simple(request):
if request.method == 'GET':
... | 0.702428 | 0.073696 |
import os
import cv2
import numpy as np
import numpy.random as npr
from prepare_data.utils import IoU
"""一路径设置"""
anno_file = 'wider_face_train.txt'
im_dir = '../../DATA/WIDER_train/images'
pos_save_dir = '../../DATA/12/positive'
part_save_dir = '../../DATA/12/part'
neg_save_dir = '../../DATA/12/negative'
... | projects/MTCNN/MTCNN_tf-master-all_refer/MTCNN-Tensorflow-master/zmtcnn_qdw/prepare_data/gen_12net_data.py | import os
import cv2
import numpy as np
import numpy.random as npr
from prepare_data.utils import IoU
"""一路径设置"""
anno_file = 'wider_face_train.txt'
im_dir = '../../DATA/WIDER_train/images'
pos_save_dir = '../../DATA/12/positive'
part_save_dir = '../../DATA/12/part'
neg_save_dir = '../../DATA/12/negative'
... | 0.11141 | 0.125065 |
import cv2
class ImgExp:
def __init__(self, win_name, img):
# 全局变量
self.g_window_name = win_name # 窗口名
self.g_window_wh = [800, 600] # 窗口宽高
self.g_location_win = [0, 0] # 相对于大图，窗口在图片中的位置
self.location_win = [0, 0] # 鼠标左键点击时，暂存self.g_self.location_win
... | LMF/segmentation/utils/image_explorer.py | import cv2
class ImgExp:
def __init__(self, win_name, img):
# 全局变量
self.g_window_name = win_name # 窗口名
self.g_window_wh = [800, 600] # 窗口宽高
self.g_location_win = [0, 0] # 相对于大图，窗口在图片中的位置
self.location_win = [0, 0] # 鼠标左键点击时，暂存self.g_self.location_win
... | 0.075773 | 0.2399 |
from .split import *
import argparse
import sys
if __name__=="__main__":
ap = argparse.ArgumentParser()
ap.add_argument("-r", "--ratio",nargs='*',type=float,
help="The ratio to split. e.g. for train/val/test `.8 .1 .1` or for train/val `.8 .2`. Default is `.8 .1 .1`, just pass `-r` for default.")
ap.ad... | split_folders/__main__.py | from .split import *
import argparse
import sys
if __name__=="__main__":
ap = argparse.ArgumentParser()
ap.add_argument("-r", "--ratio",nargs='*',type=float,
help="The ratio to split. e.g. for train/val/test `.8 .1 .1` or for train/val `.8 .2`. Default is `.8 .1 .1`, just pass `-r` for default.")
ap.ad... | 0.28587 | 0.132571 |
import json
import os
import re
import sys
from pathlib import Path
from urllib import request
from sosw import Processor
from sosw.components.helpers import recursive_update
DEFAULT_CONFIGS = 'essentials/.config'
class ConfigUploader(Processor):
DEFAULT_CONFIG = {
'init_clients': ['DynamoDb'],
... | examples/config_updater.py | import json
import os
import re
import sys
from pathlib import Path
from urllib import request
from sosw import Processor
from sosw.components.helpers import recursive_update
DEFAULT_CONFIGS = 'essentials/.config'
class ConfigUploader(Processor):
DEFAULT_CONFIG = {
'init_clients': ['DynamoDb'],
... | 0.178848 | 0.075075 |
import typing
import asyncpg
from databases.core import Connection
from tvsched.adapters.repos.actor.models import ActorRecord
from tvsched.adapters.repos.actor.utils import (
map_actor_record_to_model,
)
from tvsched.application.exceptions.actor import (
ActorAlreadyInShowCastError,
ActorNotFoundError,
... | tvsched/adapters/repos/actor/repo.py | import typing
import asyncpg
from databases.core import Connection
from tvsched.adapters.repos.actor.models import ActorRecord
from tvsched.adapters.repos.actor.utils import (
map_actor_record_to_model,
)
from tvsched.application.exceptions.actor import (
ActorAlreadyInShowCastError,
ActorNotFoundError,
... | 0.734596 | 0.172276 |
import tensorflow as tf
from tensorflow.contrib import rnn
from common.layers import get_initializer
from encoder import EncoderBase
import pdb
import copy
class RCNN(EncoderBase):
def __init__(self, **kwargs):
super(RCNN, self).__init__(**kwargs)
self.rnn_type = "bi_lstm"
self.embedding_si... | encoder/rcnn.py | import tensorflow as tf
from tensorflow.contrib import rnn
from common.layers import get_initializer
from encoder import EncoderBase
import pdb
import copy
class RCNN(EncoderBase):
def __init__(self, **kwargs):
super(RCNN, self).__init__(**kwargs)
self.rnn_type = "bi_lstm"
self.embedding_si... | 0.786582 | 0.219651 |
import ast
from pprint import pprint
import click
from ytscraper.helper.configfile import (
DEFAULT_OPTIONS,
load_config,
write_config,
update_config,
)
from ytscraper.helper.echo import echov, echow
@click.group()
@click.pass_context
def config(context):
""" Shows and modifies default configur... | ytscraper/commands/config.py |
import ast
from pprint import pprint
import click
from ytscraper.helper.configfile import (
DEFAULT_OPTIONS,
load_config,
write_config,
update_config,
)
from ytscraper.helper.echo import echov, echow
@click.group()
@click.pass_context
def config(context):
""" Shows and modifies default configur... | 0.291888 | 0.079603 |
import cv2
import os
from os import listdir
from os.path import isfile,join
import numpy as np
data_path='faces/'
onlyfiles=[f for f in listdir(data_path) if isfile(join(data_path,f))]
Training_Data, Labels=[],[]
for i, files in enumerate(onlyfiles):
image_path=data_path+onlyfiles[i]
images=cv2.imre... | tester.py | import cv2
import os
from os import listdir
from os.path import isfile,join
import numpy as np
data_path='faces/'
onlyfiles=[f for f in listdir(data_path) if isfile(join(data_path,f))]
Training_Data, Labels=[],[]
for i, files in enumerate(onlyfiles):
image_path=data_path+onlyfiles[i]
images=cv2.imre... | 0.102058 | 0.112454 |
## Handle feedback storing the data from user comments.
import json
import logging
import os
import urllib
import webapp2
from google.appengine.ext.webapp import template
from google.appengine.ext import ndb
from google.appengine.api import mail
class ErrorReport(ndb.Model):
"""A main model for representing a... | feedback.py |
## Handle feedback storing the data from user comments.
import json
import logging
import os
import urllib
import webapp2
from google.appengine.ext.webapp import template
from google.appengine.ext import ndb
from google.appengine.api import mail
class ErrorReport(ndb.Model):
"""A main model for representing a... | 0.336985 | 0.12552 |
from keras.layers import Dense, LSTM, GRU, SimpleRNN
from keras.models import Sequential, load_model
from sklearn.metrics import mean_squared_error
from sklearn.preprocessing import MinMaxScaler
import matplotlib.pyplot as plt
from typing import Tuple, Dict
import tensorflow as tf
import seaborn as sb
import pandas as ... | StockPredictorNLP/StockPredictorNLP.py | from keras.layers import Dense, LSTM, GRU, SimpleRNN
from keras.models import Sequential, load_model
from sklearn.metrics import mean_squared_error
from sklearn.preprocessing import MinMaxScaler
import matplotlib.pyplot as plt
from typing import Tuple, Dict
import tensorflow as tf
import seaborn as sb
import pandas as ... | 0.775945 | 0.304882 |
from mud.inject import inject
from mud.module import Module
def format_field_value(name, value):
FIELD_LENGTH = 20
return "{}[{}]".format(name.ljust(FIELD_LENGTH, "."), value)
@inject("Rooms")
def in_room_edit(self, Rooms, context=None, args=None, **kwargs):
room = Rooms.get(context["room_id"]) if conte... | modules/build.py | from mud.inject import inject
from mud.module import Module
def format_field_value(name, value):
FIELD_LENGTH = 20
return "{}[{}]".format(name.ljust(FIELD_LENGTH, "."), value)
@inject("Rooms")
def in_room_edit(self, Rooms, context=None, args=None, **kwargs):
room = Rooms.get(context["room_id"]) if conte... | 0.327991 | 0.156846 |
import time
import math
from pprint import pprint
from functools import cache
import pygame
from pygame.math import Vector2
from pygame.transform import scale
import core
from .asset_manager import AssetManager
from .cam import Cam
class Engine:
BUFFER_SIZE = (10, 9)
TILE_SIZE = 16
SCALE = 6
def __... | engine/engine.py | import time
import math
from pprint import pprint
from functools import cache
import pygame
from pygame.math import Vector2
from pygame.transform import scale
import core
from .asset_manager import AssetManager
from .cam import Cam
class Engine:
BUFFER_SIZE = (10, 9)
TILE_SIZE = 16
SCALE = 6
def __... | 0.340485 | 0.198724 |
import xmlrpc.client as xc
import re
# Implementation of access to Odoo server external API. Oficial documentation:
# https://www.odoo.com/documentation/14.0/developer/misc/api/odoo.html
# <NAME> aka muhoed, <EMAIL>
# version 0.1
class odooExternalApiConnector:
"""
Helper class to create connectio... | odoo_external_api_connector.py | import xmlrpc.client as xc
import re
# Implementation of access to Odoo server external API. Oficial documentation:
# https://www.odoo.com/documentation/14.0/developer/misc/api/odoo.html
# <NAME> aka muhoed, <EMAIL>
# version 0.1
class odooExternalApiConnector:
"""
Helper class to create connectio... | 0.53777 | 0.106667 |
import sys
from PySide2 import QtWidgets, QtCore
import main
class Game(QtWidgets.QWidget):
def __init__(self):
super(Game, self).__init__()
self.setWindowTitle("2048 Game")
self.setGeometry(400, 400, 400, 400)
self.matrix = main.Matrix()
self.setup()
def setup(self):
... | widgets.py | import sys
from PySide2 import QtWidgets, QtCore
import main
class Game(QtWidgets.QWidget):
def __init__(self):
super(Game, self).__init__()
self.setWindowTitle("2048 Game")
self.setGeometry(400, 400, 400, 400)
self.matrix = main.Matrix()
self.setup()
def setup(self):
... | 0.252568 | 0.158695 |
import pandas as pd
import abc
import numpy as np
from BPMN.TransformationStrategy import SelectRowsStrategy
# abstract base class
class CombineStrategy():
@abc.abstractclassmethod
def combine(self, df_1: pd.DataFrame, df_2: pd.DataFrame) -> pd.DataFrame:
pass
@abc.abstractclassmethod
def g... | src/BPMN/CombineStrategy.py | import pandas as pd
import abc
import numpy as np
from BPMN.TransformationStrategy import SelectRowsStrategy
# abstract base class
class CombineStrategy():
@abc.abstractclassmethod
def combine(self, df_1: pd.DataFrame, df_2: pd.DataFrame) -> pd.DataFrame:
pass
@abc.abstractclassmethod
def g... | 0.753376 | 0.405037 |
from abc import ABC, abstractmethod # For abstract class
from collections import namedtuple # For data classes
class Point:
# These are class attributes
default_color = "red"
default_location = 10
# Constructor
def __init__(self, x, y):
# These are instance attributes
self.x = x... | classes.py | from abc import ABC, abstractmethod # For abstract class
from collections import namedtuple # For data classes
class Point:
# These are class attributes
default_color = "red"
default_location = 10
# Constructor
def __init__(self, x, y):
# These are instance attributes
self.x = x... | 0.820649 | 0.323808 |
import sys
from datetime import date
import requests
from bs4 import BeautifulSoup
sys.path.insert(1, 'models')
import db, objects
from utils import *
dbConnection = db.Database()
breaksDB = dbConnection.connect()
playersObj = objects.Players(breaksDB)
players = playersObj.read()
startLimit = 390
endLimit = 500
index... | 03-getLastGames.py | import sys
from datetime import date
import requests
from bs4 import BeautifulSoup
sys.path.insert(1, 'models')
import db, objects
from utils import *
dbConnection = db.Database()
breaksDB = dbConnection.connect()
playersObj = objects.Players(breaksDB)
players = playersObj.read()
startLimit = 390
endLimit = 500
index... | 0.076197 | 0.176956 |
from unittest import TestCase
from salesmanago_python_api.data.auth import SalesManagoAuthData
class SalesManagoAuthDataTest(TestCase):
@classmethod
def setUpClass(cls) -> None:
pass
@classmethod
def tearDownClass(cls) -> None:
pass
def setUp(self) -> None:
self.auth = ... | tests/auth/test_unit.py | from unittest import TestCase
from salesmanago_python_api.data.auth import SalesManagoAuthData
class SalesManagoAuthDataTest(TestCase):
@classmethod
def setUpClass(cls) -> None:
pass
@classmethod
def tearDownClass(cls) -> None:
pass
def setUp(self) -> None:
self.auth = ... | 0.693369 | 0.4917 |