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 |
|---|---|---|---|---|
import logging
import os
import pickle
from datetime import datetime
import click_spinner
import requests
from bs4 import BeautifulSoup
from slughorn.scraper.webdriver.TwitterWebdriver import *
from slughorn.scraper.webspider.TwitterSpider import TwitterSpider
log = logging.getLogger('slughorn')
class TwitterScrape... | slughorn/scraper/TwitterScraper.py | import logging
import os
import pickle
from datetime import datetime
import click_spinner
import requests
from bs4 import BeautifulSoup
from slughorn.scraper.webdriver.TwitterWebdriver import *
from slughorn.scraper.webspider.TwitterSpider import TwitterSpider
log = logging.getLogger('slughorn')
class TwitterScrape... | 0.523908 | 0.184731 |
from flask import Flask, jsonify, request
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import Column, Integer, String, Float
from flask_marshmallow import Marshmallow
from flask_jwt_extended import JWTManager, jwt_required, create_access_token
from flask_mail import Mail, Message
import os
app = Flask(__nam... | src/views.py | from flask import Flask, jsonify, request
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import Column, Integer, String, Float
from flask_marshmallow import Marshmallow
from flask_jwt_extended import JWTManager, jwt_required, create_access_token
from flask_mail import Mail, Message
import os
app = Flask(__nam... | 0.3295 | 0.062531 |
import pickle
import matplotlib.pyplot as plt
import numpy as np
import torch
from scipy.stats import norm
from tifffile import imread
from torch.distributions import normal
import divnoising.histNoiseModel
dtype = torch.float
def fastShuffle(series, num):
length = series.shape[0]
for i in range(num):
... | divnoising/gaussianMixtureNoiseModel.py | import pickle
import matplotlib.pyplot as plt
import numpy as np
import torch
from scipy.stats import norm
from tifffile import imread
from torch.distributions import normal
import divnoising.histNoiseModel
dtype = torch.float
def fastShuffle(series, num):
length = series.shape[0]
for i in range(num):
... | 0.89684 | 0.754327 |
from typing import List, Union
from qutip import Qobj, sigmax, sigmay, sigmaz, qeye, tensor
from os import path, getcwd, makedirs
import numpy as np
from fidelity_functions import get_pauli_basis
def choose(n, k):
return np.math.factorial(n)/(np.math.factorial(k)*np.math.factorial(np.int(n-k)))
class GateObj:
... | utils.py | from typing import List, Union
from qutip import Qobj, sigmax, sigmay, sigmaz, qeye, tensor
from os import path, getcwd, makedirs
import numpy as np
from fidelity_functions import get_pauli_basis
def choose(n, k):
return np.math.factorial(n)/(np.math.factorial(k)*np.math.factorial(np.int(n-k)))
class GateObj:
... | 0.920249 | 0.610279 |
import psycopg2
from contextlib import contextmanager
def connect():
"""Connect to the PostgreSQL database. Returns a database connection."""
try:
return psycopg2.connect("dbname=tournament")
except:
print("Database Connection failed.")
@contextmanager
def get_cursor():
""" Query helper ... | tournament.py | import psycopg2
from contextlib import contextmanager
def connect():
"""Connect to the PostgreSQL database. Returns a database connection."""
try:
return psycopg2.connect("dbname=tournament")
except:
print("Database Connection failed.")
@contextmanager
def get_cursor():
""" Query helper ... | 0.683314 | 0.294951 |
from dsbox.template.template import DSBoxTemplate
from d3m.metadata.problem import TaskKeyword
from dsbox.template.template_steps import TemplateSteps
from dsbox.schema import SpecializedProblem
import typing
import numpy as np # type: ignore
class LupiRfClassification(DSBoxTemplate):
def __init__(self):
... | python/dsbox/template/template_files/loaded/LupiRfClassification.py | from dsbox.template.template import DSBoxTemplate
from d3m.metadata.problem import TaskKeyword
from dsbox.template.template_steps import TemplateSteps
from dsbox.schema import SpecializedProblem
import typing
import numpy as np # type: ignore
class LupiRfClassification(DSBoxTemplate):
def __init__(self):
... | 0.739705 | 0.344912 |
import cv2
import numpy as np
import chainer_mask_rcnn
from .. import image as image_module
def visualize_label(lbl, img, class_names=None):
lbl_viz1 = image_module.label2rgb(
lbl, label_names=class_names, thresh_suppress=0.01)
lbl_viz2 = image_module.label2rgb(
lbl, img, label_names=class_n... | demos/instance_occlsegm/instance_occlsegm_lib/datasets/utils.py | import cv2
import numpy as np
import chainer_mask_rcnn
from .. import image as image_module
def visualize_label(lbl, img, class_names=None):
lbl_viz1 = image_module.label2rgb(
lbl, label_names=class_names, thresh_suppress=0.01)
lbl_viz2 = image_module.label2rgb(
lbl, img, label_names=class_n... | 0.452536 | 0.374819 |
import subprocess
import tempfile
import shutil
import os
import re
import fasta_statter
"""
Generic assembler template for writing assembly bindings. Assembly Dispatch provides
a number of relevant arguments (mostly geared around the requirements of Velvet, but
this has proved to be robust for most complex de B... | template_assembler.py | import subprocess
import tempfile
import shutil
import os
import re
import fasta_statter
"""
Generic assembler template for writing assembly bindings. Assembly Dispatch provides
a number of relevant arguments (mostly geared around the requirements of Velvet, but
this has proved to be robust for most complex de B... | 0.284477 | 0.183283 |
from django.test import TestCase
from django.contrib.auth.models import User
from .models import *
# Create your tests here.
class LocationTestClass(TestCase):
def setUp(self):
self.location = Location(id=1, name='Test')
def test_instance(self):
self.assertTrue(isinstance(self.loca... | app/tests.py | from django.test import TestCase
from django.contrib.auth.models import User
from .models import *
# Create your tests here.
class LocationTestClass(TestCase):
def setUp(self):
self.location = Location(id=1, name='Test')
def test_instance(self):
self.assertTrue(isinstance(self.loca... | 0.403332 | 0.36458 |
from moonfire_tokenomics.data.admc import admc
from moonfire_tokenomics.data.amp import amp
from moonfire_tokenomics.data.ampl import ampl
from moonfire_tokenomics.data.anc import anc
from moonfire_tokenomics.data.aot import aot
from moonfire_tokenomics.data.atlas import atlas
from moonfire_tokenomics.data.axs import a... | moonfire_tokenomics/data/__init__.py | from moonfire_tokenomics.data.admc import admc
from moonfire_tokenomics.data.amp import amp
from moonfire_tokenomics.data.ampl import ampl
from moonfire_tokenomics.data.anc import anc
from moonfire_tokenomics.data.aot import aot
from moonfire_tokenomics.data.atlas import atlas
from moonfire_tokenomics.data.axs import a... | 0.516352 | 0.087408 |
import numpy as np
import scipy.sparse as spsp
import seaborn as sns
import scedar.eda as eda
import matplotlib as mpl
mpl.use("agg", warn=False) # noqa
import matplotlib.pyplot as plt
import pytest
class TestSparseSampleFeatureMatrix(object):
"""docstring for TestSparseSampleFeatureMatrix"""
sfm5x10_arr =... | tests/test_eda/test_sparse_sfm.py | import numpy as np
import scipy.sparse as spsp
import seaborn as sns
import scedar.eda as eda
import matplotlib as mpl
mpl.use("agg", warn=False) # noqa
import matplotlib.pyplot as plt
import pytest
class TestSparseSampleFeatureMatrix(object):
"""docstring for TestSparseSampleFeatureMatrix"""
sfm5x10_arr =... | 0.319652 | 0.558327 |
import numpy as np
import pandas as pd
from skimage import morphology
from skimage.morphology import binary_closing, binary_opening, disk, binary_dilation
def run_length_encoding(x):
dots = np.where(x.T.flatten() == 1)[0]
run_lengths = []
prev = -2
for b in dots:
if (b>prev+1): run_lengths.exte... | kaggle/src/functions.py | import numpy as np
import pandas as pd
from skimage import morphology
from skimage.morphology import binary_closing, binary_opening, disk, binary_dilation
def run_length_encoding(x):
dots = np.where(x.T.flatten() == 1)[0]
run_lengths = []
prev = -2
for b in dots:
if (b>prev+1): run_lengths.exte... | 0.373076 | 0.312882 |
import torch.nn as nn
import torch
from torch.autograd import Variable
# VAE model
class VAE(nn.Module):
def __init__(self, z_dim, use_cuda, output_dim=400):
super(VAE, self).__init__()
self.z_dim = z_dim
self.output_dim = output_dim
self.use_cuda = use_cuda
self.encoder ... | experiments/representation_analysis/models.py | import torch.nn as nn
import torch
from torch.autograd import Variable
# VAE model
class VAE(nn.Module):
def __init__(self, z_dim, use_cuda, output_dim=400):
super(VAE, self).__init__()
self.z_dim = z_dim
self.output_dim = output_dim
self.use_cuda = use_cuda
self.encoder ... | 0.918265 | 0.530966 |
from env import JetBotEnv
import torch
import torch.nn as nn
# Import the skrl components to build the RL system
from skrl.models.torch import DeterministicModel, GaussianModel
from skrl.memories.torch import RandomMemory
from skrl.agents.torch.sac import SAC, SAC_DEFAULT_CONFIG
from skrl.trainers.torch import Sequen... | docs/source/examples/isaacsim_jetbot.py | from env import JetBotEnv
import torch
import torch.nn as nn
# Import the skrl components to build the RL system
from skrl.models.torch import DeterministicModel, GaussianModel
from skrl.memories.torch import RandomMemory
from skrl.agents.torch.sac import SAC, SAC_DEFAULT_CONFIG
from skrl.trainers.torch import Sequen... | 0.924219 | 0.577317 |
import cgi
import datetime
import hashlib
import http.server
import json
import logging
from multiprocessing import Process
import os
import re
import signal
import socket
import socketserver
import time
import traceback
from urllib.parse import urlparse, urlencode, parse_qsl
import uuid
from kolejka.common.settings ... | kolejka/observer/server.py |
import cgi
import datetime
import hashlib
import http.server
import json
import logging
from multiprocessing import Process
import os
import re
import signal
import socket
import socketserver
import time
import traceback
from urllib.parse import urlparse, urlencode, parse_qsl
import uuid
from kolejka.common.settings ... | 0.283385 | 0.112259 |
from itertools import islice
import logging
import os
from sqlalchemy import MetaData, Table, Column, Integer, String, create_engine
from sqlalchemy.engine import reflection
from sqlalchemy.orm import mapper, sessionmaker
from sqlalchemy.sql.expression import or_
from .aggregating_scanner import Directory, MODEL
D... | relascope/sqlalchemy.py | from itertools import islice
import logging
import os
from sqlalchemy import MetaData, Table, Column, Integer, String, create_engine
from sqlalchemy.engine import reflection
from sqlalchemy.orm import mapper, sessionmaker
from sqlalchemy.sql.expression import or_
from .aggregating_scanner import Directory, MODEL
D... | 0.712532 | 0.124133 |
import re
from django.contrib.gis.geos import GEOSException
from django.core.management.base import BaseCommand
from django.db import InternalError
from leasing.enums import AreaType, PlotType
from leasing.models import Area, Lease
from leasing.models.land_area import PlanUnit, PlanUnitIntendedUse, PlanUnitState, Pla... | leasing/management/commands/attach_areas.py | import re
from django.contrib.gis.geos import GEOSException
from django.core.management.base import BaseCommand
from django.db import InternalError
from leasing.enums import AreaType, PlotType
from leasing.models import Area, Lease
from leasing.models.land_area import PlanUnit, PlanUnitIntendedUse, PlanUnitState, Pla... | 0.410402 | 0.281273 |
import os
import sys
#sys.path.append(os.path.dirname(__file__))
import numpy as np
try:
from .transforms import *
from .dataloader import MyDataloader
except:
from transforms import *
from dataloader import MyDataloader
from torch.utils.data import DataLoader
import matplotlib.pyplot as plt
import tor... | code/dataloaders/nyu_dataloader.py |
import os
import sys
#sys.path.append(os.path.dirname(__file__))
import numpy as np
try:
from .transforms import *
from .dataloader import MyDataloader
except:
from transforms import *
from dataloader import MyDataloader
from torch.utils.data import DataLoader
import matplotlib.pyplot as plt
import tor... | 0.459076 | 0.250448 |
from itertools import (accumulate, chain, cycle, islice)
# repCycles :: String -> [String]
def repCycles(s):
'''Repeated sequences of characters in s.'''
n = len(s)
cs = list(s)
return [
x for x in
tail(inits(take(n // 2)(s)))
if cs == take(n)(cycle(x))
]
# TEST -------... | lang/Python/rep-string-3.py |
from itertools import (accumulate, chain, cycle, islice)
# repCycles :: String -> [String]
def repCycles(s):
'''Repeated sequences of characters in s.'''
n = len(s)
cs = list(s)
return [
x for x in
tail(inits(take(n // 2)(s)))
if cs == take(n)(cycle(x))
]
# TEST -------... | 0.588061 | 0.316871 |
import pyshark
import argparse
from miscale import *
HANDLE_VALUE_INDICATION = 0x1d
HANDLE_VALUE_NOTIFICATION = 0x1b
READ_RESPONSE = 0x0b
READ_REQUEST = 0x0a
WRITE_REQUEST = 0x12
CONNECT_REQ = 0x05
parser = argparse.ArgumentParser(description='BLE MI_SCALE protocol analyzer')
parser.add_argument('-u', '--user', hel... | miscale_analyzer.py |
import pyshark
import argparse
from miscale import *
HANDLE_VALUE_INDICATION = 0x1d
HANDLE_VALUE_NOTIFICATION = 0x1b
READ_RESPONSE = 0x0b
READ_REQUEST = 0x0a
WRITE_REQUEST = 0x12
CONNECT_REQ = 0x05
parser = argparse.ArgumentParser(description='BLE MI_SCALE protocol analyzer')
parser.add_argument('-u', '--user', hel... | 0.145844 | 0.179405 |
import os
import errno
from ansible.module_utils._text import to_native
from ansible.module_utils.basic import AnsibleModule
ANSIBLE_METADATA = {'metadata_version': '1.0',
'status': ['preview'],
'supported_by': 'community'}
try:
from OpenSSL import crypto
except ImportError... | library/openssl_csr.py | import os
import errno
from ansible.module_utils._text import to_native
from ansible.module_utils.basic import AnsibleModule
ANSIBLE_METADATA = {'metadata_version': '1.0',
'status': ['preview'],
'supported_by': 'community'}
try:
from OpenSSL import crypto
except ImportError... | 0.30013 | 0.088544 |
from PyQt5 import QtCore, QtWidgets, QtMultimedia
class AudioDialog(QtWidgets.QDialog):
def __init__(self, *args, **kwargs):
super(AudioDialog, self).__init__(*args, **kwargs)
self.setWindowTitle("Audio Devices")
self.device_index = -1
self.device_rate_index = -1
self.device... | audiodialog.py | from PyQt5 import QtCore, QtWidgets, QtMultimedia
class AudioDialog(QtWidgets.QDialog):
def __init__(self, *args, **kwargs):
super(AudioDialog, self).__init__(*args, **kwargs)
self.setWindowTitle("Audio Devices")
self.device_index = -1
self.device_rate_index = -1
self.device... | 0.538498 | 0.070528 |
from __future__ import (
unicode_literals,
print_function,
division,
absolute_import,
)
# Make Py2's str equivalent to Py3's
str = type('')
try:
range = xrange
except NameError:
pass
import sys
import threading
from time import sleep
from collections import deque
from picamera.frames impo... | picamtracker/VideoWriter.py |
from __future__ import (
unicode_literals,
print_function,
division,
absolute_import,
)
# Make Py2's str equivalent to Py3's
str = type('')
try:
range = xrange
except NameError:
pass
import sys
import threading
from time import sleep
from collections import deque
from picamera.frames impo... | 0.314471 | 0.096706 |
import numpy as np
# Even though the cityscape dataset provide the pixel wise labells of 30 classes but usually in most of the papers only 20 classes
# are used for evaluation. So I added both of them
cityscape_class_full = ['unlabeled', 'ego_vehicle', 'rectification_border', 'out_of_roi', 'static', 'dynamic', 'grou... | cityscape_color_pallet.py | import numpy as np
# Even though the cityscape dataset provide the pixel wise labells of 30 classes but usually in most of the papers only 20 classes
# are used for evaluation. So I added both of them
cityscape_class_full = ['unlabeled', 'ego_vehicle', 'rectification_border', 'out_of_roi', 'static', 'dynamic', 'grou... | 0.235724 | 0.570391 |
import numpy as np
Imat = np.eye(2)
def x_(nqubits, index):
"""Create an X gate
Args:
nqubits (int): The number of qubits on a quantum circuit
index (int): The index of a qubit that a gate is applied
Returns:
ndarray : The matrix of an X gate
"""
matrix = 1
X = np.arra... | heqsim/hardware/basicgate.py | import numpy as np
Imat = np.eye(2)
def x_(nqubits, index):
"""Create an X gate
Args:
nqubits (int): The number of qubits on a quantum circuit
index (int): The index of a qubit that a gate is applied
Returns:
ndarray : The matrix of an X gate
"""
matrix = 1
X = np.arra... | 0.927552 | 0.907804 |
import numpy as np
from scipy import linalg
from scipy.stats import entropy
import torch
import torch.utils.data
from torch import nn
from torch.autograd import Variable
from torch.nn import functional as F
from torchvision.models.inception import inception_v3
class FIDInceptionModel(nn.Module):
def __init__(self... | torchbench/image_generation/utils.py | import numpy as np
from scipy import linalg
from scipy.stats import entropy
import torch
import torch.utils.data
from torch import nn
from torch.autograd import Variable
from torch.nn import functional as F
from torchvision.models.inception import inception_v3
class FIDInceptionModel(nn.Module):
def __init__(self... | 0.945538 | 0.542136 |
# # Memory Usage: Operator Only
import pandas as pd
import torch as T
from sys import path
path.insert(0, '..')
import fewbit # noqa
# Define parameters of quantisation.
# +
BOUNDS = T.tensor([
-2.39798704e+00, -7.11248159e-01, -3.26290283e-01, -1.55338428e-04,
3.26182064e-01, 7.10855860e-01, 2.39811567e+... | notebooks/few-bit-backward/memory-usage-operation-only.py |
# # Memory Usage: Operator Only
import pandas as pd
import torch as T
from sys import path
path.insert(0, '..')
import fewbit # noqa
# Define parameters of quantisation.
# +
BOUNDS = T.tensor([
-2.39798704e+00, -7.11248159e-01, -3.26290283e-01, -1.55338428e-04,
3.26182064e-01, 7.10855860e-01, 2.39811567e+... | 0.371479 | 0.279018 |
import numpy as np
from typing import Callable, Tuple
from scipy.fft import rfft, rfftfreq
from scipy.optimize import curve_fit
from scipy.signal import find_peaks
from scipy.signal.signaltools import correlate, correlation_lags
from scipy.interpolate import UnivariateSpline
SignalFunction = Callable[[np.ndarray, flo... | arduscope/fit_tools.py | import numpy as np
from typing import Callable, Tuple
from scipy.fft import rfft, rfftfreq
from scipy.optimize import curve_fit
from scipy.signal import find_peaks
from scipy.signal.signaltools import correlate, correlation_lags
from scipy.interpolate import UnivariateSpline
SignalFunction = Callable[[np.ndarray, flo... | 0.862178 | 0.631751 |
import os
import pylzma
import sys
import struct
import zlib
def confirm(prompt, resp=False):
"""prompts for yes or no response from the user. Returns True for yes and
False for no.
'resp' should be set to the default value assumed by the caller when
user simply types ENTER.
>>> confirm(prompt=... | swfzip.py | import os
import pylzma
import sys
import struct
import zlib
def confirm(prompt, resp=False):
"""prompts for yes or no response from the user. Returns True for yes and
False for no.
'resp' should be set to the default value assumed by the caller when
user simply types ENTER.
>>> confirm(prompt=... | 0.08006 | 0.245322 |
from ailib.models.base_model import BaseModule
import torch, torch.nn.functional as F
from torch import ByteTensor, DoubleTensor, FloatTensor, HalfTensor, LongTensor, ShortTensor, Tensor
from torch import nn, optim, as_tensor
from torch.utils.data import BatchSampler, DataLoader, Dataset, Sampler, TensorDataset
from to... | ailib/models/text_cls/cls_fasttext.py | from ailib.models.base_model import BaseModule
import torch, torch.nn.functional as F
from torch import ByteTensor, DoubleTensor, FloatTensor, HalfTensor, LongTensor, ShortTensor, Tensor
from torch import nn, optim, as_tensor
from torch.utils.data import BatchSampler, DataLoader, Dataset, Sampler, TensorDataset
from to... | 0.918972 | 0.526951 |
import random
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
class Seq2Seq(nn.Module):
EOS_token = 1
def __init__(self,
input_size, output_size, hidden_size, embedding_size,
n_layers=1, dropout_p=0.5, attention_length=30,
... | seq2seq.py | import random
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
class Seq2Seq(nn.Module):
EOS_token = 1
def __init__(self,
input_size, output_size, hidden_size, embedding_size,
n_layers=1, dropout_p=0.5, attention_length=30,
... | 0.929943 | 0.423875 |
class _MPxCommand(object):
"""
Base class for custom commands.
"""
def __init__(*args, **kwargs):
"""
x.__init__(...) initializes x; see help(type(x)) for signature
"""
pass
def doIt(*args, **kwargs):
"""
Called by Maya to... | maya/app/renderSetup/model/renderSetupPrivate.py | class _MPxCommand(object):
"""
Base class for custom commands.
"""
def __init__(*args, **kwargs):
"""
x.__init__(...) initializes x; see help(type(x)) for signature
"""
pass
def doIt(*args, **kwargs):
"""
Called by Maya to... | 0.635788 | 0.260466 |
from unicorn_binance_websocket_api.unicorn_binance_websocket_api_manager import BinanceWebSocketApiManager
from decimal import Decimal
from indicators.ema import *
from bin.ohlcv import *
import numpy as np
import datetime
def live_updates(intervals, ema_intervals, tokens, exchange, token_instances, alerts):
bina... | bin/live_updates.py | from unicorn_binance_websocket_api.unicorn_binance_websocket_api_manager import BinanceWebSocketApiManager
from decimal import Decimal
from indicators.ema import *
from bin.ohlcv import *
import numpy as np
import datetime
def live_updates(intervals, ema_intervals, tokens, exchange, token_instances, alerts):
bina... | 0.512937 | 0.230996 |
import os
import time
import logging
from bag.io import get_encoding
from BPG.abstract_plugin import AbstractPlugin
try:
import cybagoa
except ImportError:
cybagoa = None
class OAPlugin(AbstractPlugin):
def __init__(self, config):
AbstractPlugin.__init__(self, config)
self.config = confi... | BPG/oa/core.py | import os
import time
import logging
from bag.io import get_encoding
from BPG.abstract_plugin import AbstractPlugin
try:
import cybagoa
except ImportError:
cybagoa = None
class OAPlugin(AbstractPlugin):
def __init__(self, config):
AbstractPlugin.__init__(self, config)
self.config = confi... | 0.50415 | 0.054525 |
from aiohttp_json_api.schema import BaseSchema
from aiohttp_json_api.fields import attributes, relationships
from examples.fantasy.models import Author, Store, Book, Series, Photo, Chapter
class AuthorSchema(BaseSchema):
name = attributes.String()
date_of_birth = attributes.Date()
date_of_death = attribu... | examples/fantasy/schemas.py | from aiohttp_json_api.schema import BaseSchema
from aiohttp_json_api.fields import attributes, relationships
from examples.fantasy.models import Author, Store, Book, Series, Photo, Chapter
class AuthorSchema(BaseSchema):
name = attributes.String()
date_of_birth = attributes.Date()
date_of_death = attribu... | 0.763572 | 0.241825 |
import h5py
import numpy as np
import torch
from .dataset_thz import *
class dataset_thz_perpixel(dataset_thz):
# -----------------------------------------------------------------------
def __init__(self, path_data, device, verbose = True):
super(dataset_thz_perpixel, self).__init__(path_data, device,... | MoAE/dataset/dataset_thz_perpixel.py | import h5py
import numpy as np
import torch
from .dataset_thz import *
class dataset_thz_perpixel(dataset_thz):
# -----------------------------------------------------------------------
def __init__(self, path_data, device, verbose = True):
super(dataset_thz_perpixel, self).__init__(path_data, device,... | 0.691497 | 0.348701 |
from unittest.mock import Mock
from django.test import TestCase
from rest_framework import serializers
from ..accounts.tests import ResidentFactory
from ..buildings.tests import ApartmentFactory, BuildingFactory
from .serializers import MessageSerializer
class SerializerTests(TestCase):
def test_validate_rec... | ownblock/ownblock/apps/messaging/tests.py | from unittest.mock import Mock
from django.test import TestCase
from rest_framework import serializers
from ..accounts.tests import ResidentFactory
from ..buildings.tests import ApartmentFactory, BuildingFactory
from .serializers import MessageSerializer
class SerializerTests(TestCase):
def test_validate_rec... | 0.536313 | 0.391639 |
import datetime
from google.appengine.ext import ndb
from testing_utils import testing
from components import auth
from components import auth_testing
from cipd import acl
class TestRepoServiceACL(testing.AppengineTestCase):
def test_is_owner_writer_reader(self):
mocked_roles = []
caller = auth.Identity... | appengine/chrome_infra_packages/cipd/test/acl_test.py |
import datetime
from google.appengine.ext import ndb
from testing_utils import testing
from components import auth
from components import auth_testing
from cipd import acl
class TestRepoServiceACL(testing.AppengineTestCase):
def test_is_owner_writer_reader(self):
mocked_roles = []
caller = auth.Identity... | 0.520496 | 0.459925 |
import re
import inspect
import simplejson
from xml.sax.saxutils import quoteattr
from functools import update_wrapper
from babel import Locale, UnknownLocaleError
from werkzeug.exceptions import MethodNotAllowed, BadRequest
from werkzeug import Response, escape
from solace.application import get_view
from solace.urls... | solace/utils/api.py | import re
import inspect
import simplejson
from xml.sax.saxutils import quoteattr
from functools import update_wrapper
from babel import Locale, UnknownLocaleError
from werkzeug.exceptions import MethodNotAllowed, BadRequest
from werkzeug import Response, escape
from solace.application import get_view
from solace.urls... | 0.539954 | 0.064241 |
import re
def decorate_all_methods(decorator):
def decorate(cls):
for attr in cls.__dict__:
if callable(getattr(cls, attr)) and attr != '__init__':
setattr(cls, attr, decorator(getattr(cls, attr)))
return cls
return decorate
def camel_to_snake(key):
camel_pat ... | plantpredict/utilities.py | import re
def decorate_all_methods(decorator):
def decorate(cls):
for attr in cls.__dict__:
if callable(getattr(cls, attr)) and attr != '__init__':
setattr(cls, attr, decorator(getattr(cls, attr)))
return cls
return decorate
def camel_to_snake(key):
camel_pat ... | 0.513912 | 0.230481 |
import io
from pathlib import Path
from ruamel.yaml import YAML
from ruamel.yaml.comments import CommentedMap
from ruamel.yaml.representer import RepresenterError
from ruamel.yaml.scalarstring import PreservedScalarString
import logging, sys
import pickle
from capanno_utils.helpers.string_tools import get_shortened_id
... | capanno_utils/classes/cwl/common_workflow_language_mixins.py | import io
from pathlib import Path
from ruamel.yaml import YAML
from ruamel.yaml.comments import CommentedMap
from ruamel.yaml.representer import RepresenterError
from ruamel.yaml.scalarstring import PreservedScalarString
import logging, sys
import pickle
from capanno_utils.helpers.string_tools import get_shortened_id
... | 0.333395 | 0.141667 |
import lib
from lib.common import group, calc_stat
from collections import OrderedDict
highlight_threshold = 0.025
IID_KEY = "validation/valid/accuracy/iid"
GEN_KEY = "validation/test/accuracy/deeper"
VAL_KEY = "validation/valid/accuracy/deeper_val"
def format_res(r):
# r = r.get()
return f"{r.mean:.2f} $\... | paper/print_perf_table_ctl.py | import lib
from lib.common import group, calc_stat
from collections import OrderedDict
highlight_threshold = 0.025
IID_KEY = "validation/valid/accuracy/iid"
GEN_KEY = "validation/test/accuracy/deeper"
VAL_KEY = "validation/valid/accuracy/deeper_val"
def format_res(r):
# r = r.get()
return f"{r.mean:.2f} $\... | 0.373647 | 0.267402 |
from datetime import timedelta
from src.fetcher.fetcher_config import FetcherConfKey
from src.fetcher.fetcher_item import FetcherItem
from src.fetcher.fetcher_job import FetcherJob
from src.fetcher import transformation
from src.fetcher.fetcher_key import FetcherKey
from src.fetcher.time_series import MaxTimeSeries
... | src/fetcher/froggit_wh2600_job.py | from datetime import timedelta
from src.fetcher.fetcher_config import FetcherConfKey
from src.fetcher.fetcher_item import FetcherItem
from src.fetcher.fetcher_job import FetcherJob
from src.fetcher import transformation
from src.fetcher.fetcher_key import FetcherKey
from src.fetcher.time_series import MaxTimeSeries
... | 0.777553 | 0.120516 |
import genomepy
import shutil
import gzip
import pytest
import os
from tempfile import mkdtemp, NamedTemporaryFile
from time import sleep
from platform import system
travis = "TRAVIS" in os.environ and os.environ["TRAVIS"] == "true"
@pytest.fixture(scope="module", params=["no-overwrite", "overwrite"])
def force(requ... | tests/test_5_install_options.py | import genomepy
import shutil
import gzip
import pytest
import os
from tempfile import mkdtemp, NamedTemporaryFile
from time import sleep
from platform import system
travis = "TRAVIS" in os.environ and os.environ["TRAVIS"] == "true"
@pytest.fixture(scope="module", params=["no-overwrite", "overwrite"])
def force(requ... | 0.303629 | 0.302523 |
def intersect(t1, t2):
"""Assumes t1 and t2 are tuples
Returns a tuple containing elements that are in
both t1 and t2"""
result = ()
for e in t1:
if e in t2:
result += (e,)
return result
def findExtremeDivisors(n1, n2):
"""Assumes that n1 and n2 are positive in... | chapter5/chapter5.py |
def intersect(t1, t2):
"""Assumes t1 and t2 are tuples
Returns a tuple containing elements that are in
both t1 and t2"""
result = ()
for e in t1:
if e in t2:
result += (e,)
return result
def findExtremeDivisors(n1, n2):
"""Assumes that n1 and n2 are positive in... | 0.701406 | 0.710274 |
import logging
import os
from enum import Enum
import click
import cv2
from imageai.Prediction.Custom import CustomImagePrediction, ModelTraining
from helpers.opencv import opencv_video_capture
# Show only errors in console
logging.getLogger("tensorflow").setLevel(logging.ERROR)
class ModelTypeEnum(Enum):
"""
... | helpers/move_prediction.py | import logging
import os
from enum import Enum
import click
import cv2
from imageai.Prediction.Custom import CustomImagePrediction, ModelTraining
from helpers.opencv import opencv_video_capture
# Show only errors in console
logging.getLogger("tensorflow").setLevel(logging.ERROR)
class ModelTypeEnum(Enum):
"""
... | 0.725746 | 0.301645 |
import itertools
from functools import partial
import numpy as np
from lined import iterize, Line, LineParametrized
# ---------------------------------------------------------------------------------------
# simple categorical map
cat_map = {'a': [1, 2, 3], 'b': [4, 5, 6]}
get_list_for_cat = cat_map.__getitem__
# to... | slink/examples/__init__.py | import itertools
from functools import partial
import numpy as np
from lined import iterize, Line, LineParametrized
# ---------------------------------------------------------------------------------------
# simple categorical map
cat_map = {'a': [1, 2, 3], 'b': [4, 5, 6]}
get_list_for_cat = cat_map.__getitem__
# to... | 0.484136 | 0.522019 |
import six
from oslo_log import log
from oslo_utils import units
from delfin import exception
from delfin.common import constants
from delfin.drivers import driver
from delfin.drivers.ibm.ds8k import rest_handler, alert_handler
LOG = log.getLogger(__name__)
class DS8KDriver(driver.StorageDriver):
PORT_TYPE_MAP... | delfin/drivers/ibm/ds8k/ds8k.py | import six
from oslo_log import log
from oslo_utils import units
from delfin import exception
from delfin.common import constants
from delfin.drivers import driver
from delfin.drivers.ibm.ds8k import rest_handler, alert_handler
LOG = log.getLogger(__name__)
class DS8KDriver(driver.StorageDriver):
PORT_TYPE_MAP... | 0.371365 | 0.078078 |
from datetime import datetime
from unittest import TestCase
from vision.constant import *
from vision.configuration_constant import *
from vision.data_handler.idata_handler import IDataHandler
from vision.registry_manager import RegistryManager
from mock import Mock, patch
mock_node_info = {'bootFwDate': "2018-10-9",... | inbm-vision/vision-agent/vision/tests/unit/test_registry_manager.py | from datetime import datetime
from unittest import TestCase
from vision.constant import *
from vision.configuration_constant import *
from vision.data_handler.idata_handler import IDataHandler
from vision.registry_manager import RegistryManager
from mock import Mock, patch
mock_node_info = {'bootFwDate': "2018-10-9",... | 0.642432 | 0.227985 |
import pickle as pkl
import xlrd
# 未知字，padding符号
UNK, PAD = "<UNK>", "<PAD>"
# 文本数据处理方法定义(单行格式)
def load_single_dataset(config, data, pad_size=32):
# 打开词表
vocab = pkl.load(open(config.vocab_path, "rb"))
content, label, title = data
# 存储每一行内容
words_line = []
# 拼接title和content
token = (lam... | Core/utils.py | import pickle as pkl
import xlrd
# 未知字，padding符号
UNK, PAD = "<UNK>", "<PAD>"
# 文本数据处理方法定义(单行格式)
def load_single_dataset(config, data, pad_size=32):
# 打开词表
vocab = pkl.load(open(config.vocab_path, "rb"))
content, label, title = data
# 存储每一行内容
words_line = []
# 拼接title和content
token = (lam... | 0.147893 | 0.228479 |
import binascii
import esphome.codegen as cg
import esphome.config_validation as cv
from esphome.components import modbus
from esphome.const import CONF_ADDRESS, CONF_ID, CONF_NAME, CONF_LAMBDA, CONF_OFFSET
from esphome.cpp_helpers import logging
from .const import (
CONF_BITMASK,
CONF_BYTE_OFFSET,
CONF_COM... | esphome/components/modbus_controller/__init__.py | import binascii
import esphome.codegen as cg
import esphome.config_validation as cv
from esphome.components import modbus
from esphome.const import CONF_ADDRESS, CONF_ID, CONF_NAME, CONF_LAMBDA, CONF_OFFSET
from esphome.cpp_helpers import logging
from .const import (
CONF_BITMASK,
CONF_BYTE_OFFSET,
CONF_COM... | 0.379838 | 0.127816 |
import numpy as np
import os
import cv2
from src.config import DATA_DIR, CLASSES, BATCH_SIZE, IMG_SIZE
import matplotlib.pyplot as plt
import matplotlib
import tensorflow as tf
from sklearn.model_selection import train_test_split
matplotlib.use('TkAgg')
IMG_PATH = os.path.join(DATA_DIR,'images')
MASK_PATH = os.pat... | src/data.py | import numpy as np
import os
import cv2
from src.config import DATA_DIR, CLASSES, BATCH_SIZE, IMG_SIZE
import matplotlib.pyplot as plt
import matplotlib
import tensorflow as tf
from sklearn.model_selection import train_test_split
matplotlib.use('TkAgg')
IMG_PATH = os.path.join(DATA_DIR,'images')
MASK_PATH = os.pat... | 0.436142 | 0.435061 |
from pytorch3d.structures import Pointclouds
from pytorch3d.renderer import compositing
from pytorch3d.renderer.points import rasterize_points
import numpy as np
import torch
from torch import nn
import nvdiffrast.torch as dr
from utils.defaults import DEFAULTS
import os
import pytorch3d
class RasterizePointsXYsBle... | src/models/pcd_renderer.py | from pytorch3d.structures import Pointclouds
from pytorch3d.renderer import compositing
from pytorch3d.renderer.points import rasterize_points
import numpy as np
import torch
from torch import nn
import nvdiffrast.torch as dr
from utils.defaults import DEFAULTS
import os
import pytorch3d
class RasterizePointsXYsBle... | 0.908277 | 0.65597 |
import unittest
from numba.cuda.testing import (CUDATestCase, skip_if_cudadevrt_missing,
skip_on_cudasim, skip_unless_cc_60)
from numba.tests.support import captured_stdout
@skip_if_cudadevrt_missing
@skip_unless_cc_60
@skip_on_cudasim("cudasim doesn't support cuda import at non-top-l... | numba/cuda/tests/doc_examples/test_laplace.py | import unittest
from numba.cuda.testing import (CUDATestCase, skip_if_cudadevrt_missing,
skip_on_cudasim, skip_unless_cc_60)
from numba.tests.support import captured_stdout
@skip_if_cudadevrt_missing
@skip_unless_cc_60
@skip_on_cudasim("cudasim doesn't support cuda import at non-top-l... | 0.582254 | 0.418875 |
from django import forms
from django.contrib.auth.models import User
from django.contrib.auth.forms import UserCreationForm
from .models import Orgao, TipoLotacao, Lotacao
from Chamados.models import Chamado, OcorrenciasChamado
class CadastroOrgaoForm(forms.ModelForm):
def __init__(self, *args, **kwargs):
... | sistemaDeGestaoDeServicosPublicos/Orgao/forms.py | from django import forms
from django.contrib.auth.models import User
from django.contrib.auth.forms import UserCreationForm
from .models import Orgao, TipoLotacao, Lotacao
from Chamados.models import Chamado, OcorrenciasChamado
class CadastroOrgaoForm(forms.ModelForm):
def __init__(self, *args, **kwargs):
... | 0.475849 | 0.106133 |
import logging
from oslo_messaging._drivers.zmq_driver import zmq_address
from oslo_messaging._drivers.zmq_driver import zmq_async
from oslo_messaging._drivers.zmq_driver import zmq_names
from oslo_messaging._drivers.zmq_driver import zmq_socket
LOG = logging.getLogger(__name__)
zmq = zmq_async.import_zmq()
class... | oslo_messaging/_drivers/zmq_driver/client/publishers/zmq_pub_publisher.py |
import logging
from oslo_messaging._drivers.zmq_driver import zmq_address
from oslo_messaging._drivers.zmq_driver import zmq_async
from oslo_messaging._drivers.zmq_driver import zmq_names
from oslo_messaging._drivers.zmq_driver import zmq_socket
LOG = logging.getLogger(__name__)
zmq = zmq_async.import_zmq()
class... | 0.508544 | 0.107672 |
from typing import Union
import numpy
from scipy.cluster import hierarchy
import pyckmeans.distance
class InvalidReorderMethod(Exception):
'''InvalidReorderMethod'''
class InvalidLinkageType(Exception):
'''InvalidLinkageType'''
REORDER_METHODS = (
'GW',
'OLO',
)
LINKAGE_TYPES = (
'average',
'... | pyckmeans/ordering/__init__.py | from typing import Union
import numpy
from scipy.cluster import hierarchy
import pyckmeans.distance
class InvalidReorderMethod(Exception):
'''InvalidReorderMethod'''
class InvalidLinkageType(Exception):
'''InvalidLinkageType'''
REORDER_METHODS = (
'GW',
'OLO',
)
LINKAGE_TYPES = (
'average',
'... | 0.952075 | 0.600159 |
from contextlib import contextmanager
from io import BytesIO
import logging
from pathlib import Path
from queue import Queue
from threading import Semaphore
from typing import (
Any,
cast,
Callable,
DefaultDict,
Dict,
List,
Iterator,
Optional,
Tuple,
)
# internal
from vtelem.daemon.... | vtelem/stream/writer.py | from contextlib import contextmanager
from io import BytesIO
import logging
from pathlib import Path
from queue import Queue
from threading import Semaphore
from typing import (
Any,
cast,
Callable,
DefaultDict,
Dict,
List,
Iterator,
Optional,
Tuple,
)
# internal
from vtelem.daemon.... | 0.833257 | 0.174656 |
import tensorflow as tf
import numpy as np
import scipy.io
class pretrainedVGG19(object):
"""Pretrained VGG 19 for Neural Style Transfer.
Args:
height: int, height of input image
width: int, width of input image
channels: int, number of input image channels
Attributes:
graph: dict, {layer_name : tensor}, ... | vgg.py | import tensorflow as tf
import numpy as np
import scipy.io
class pretrainedVGG19(object):
"""Pretrained VGG 19 for Neural Style Transfer.
Args:
height: int, height of input image
width: int, width of input image
channels: int, number of input image channels
Attributes:
graph: dict, {layer_name : tensor}, ... | 0.892837 | 0.648814 |
from __future__ import annotations
import apgorm
from apgorm import Index, IndexType
from .models import (
aschannel,
guild,
member,
message,
override,
permrole,
posrole,
sb_message,
starboard,
user,
vote,
xprole,
)
class Database(apgorm.Database):
def __init__(s... | starboard/database/database.py |
from __future__ import annotations
import apgorm
from apgorm import Index, IndexType
from .models import (
aschannel,
guild,
member,
message,
override,
permrole,
posrole,
sb_message,
starboard,
user,
vote,
xprole,
)
class Database(apgorm.Database):
def __init__(s... | 0.711832 | 0.143068 |
# System imports
# Google imports
from google.appengine.api import users
from google.appengine.ext import ndb
# Local imports
from scaffold import attentionpage
import basehandler
from subreview_lib import confreviewconfig, newscoringtask
class NewScoreConfigPage(basehandler.BaseHandler):
def get(self):
... | subreview_lib/newscoreconfigpage.py |
# System imports
# Google imports
from google.appengine.api import users
from google.appengine.ext import ndb
# Local imports
from scaffold import attentionpage
import basehandler
from subreview_lib import confreviewconfig, newscoringtask
class NewScoreConfigPage(basehandler.BaseHandler):
def get(self):
... | 0.295636 | 0.081813 |
import telebot as tb
from dbhelper import DBHelper
import datetime
bot = tb.TeleBot('944057887:AAEhF2Xp3lHFmc4ipZP8xNVExvzRI7BtL24')
@bot.message_handler(commands=['start'])
def start_message(message):
bot.send_message(message.chat.id, 'Привет, давай-ка я поведаю о функционале!\n '+
'Я призван для того чтобы ... | main.py | import telebot as tb
from dbhelper import DBHelper
import datetime
bot = tb.TeleBot('944057887:AAEhF2Xp3lHFmc4ipZP8xNVExvzRI7BtL24')
@bot.message_handler(commands=['start'])
def start_message(message):
bot.send_message(message.chat.id, 'Привет, давай-ка я поведаю о функционале!\n '+
'Я призван для того чтобы ... | 0.044608 | 0.218669 |
import sys
import string
import time
import math
import getopt
flood_30_info = { 'pages' : [1,2,3,4,5,6,7,8],
'cycles': 1.0259 }
flood_18_info = { 'pages' : [9,10,11,12,13,14,15],
'cycles': 1.0516 }
flood_06_info = { 'pages' : [16,17,18,19,20,21],
'cycles': 1.0558 }
ebb_30_info = { 'pa... | calculate.py |
import sys
import string
import time
import math
import getopt
flood_30_info = { 'pages' : [1,2,3,4,5,6,7,8],
'cycles': 1.0259 }
flood_18_info = { 'pages' : [9,10,11,12,13,14,15],
'cycles': 1.0516 }
flood_06_info = { 'pages' : [16,17,18,19,20,21],
'cycles': 1.0558 }
ebb_30_info = { 'pa... | 0.101628 | 0.154026 |
from logging import getLogger
from ptrlib.util.encoding import *
from ptrlib.pwn.tube import *
import socket
logger = getLogger(__name__)
class Socket(Tube):
def __init__(self, host, port, timeout=None):
"""Create a socket
Create a new socket and establish a connection to the host.
Args... | ptrlib/pwn/sock.py | from logging import getLogger
from ptrlib.util.encoding import *
from ptrlib.pwn.tube import *
import socket
logger = getLogger(__name__)
class Socket(Tube):
def __init__(self, host, port, timeout=None):
"""Create a socket
Create a new socket and establish a connection to the host.
Args... | 0.784649 | 0.177579 |
import cookielib
import urllib2
import urllib
import httplib
import urlparse
'''网络数据查询实现类，负责网络数据交互，包括登陆和JSON数据获取'''
class QueryCore():
def __init__(self, ctr):
self.ctr = ctr
self.setCookies()
""" 设置cookie"""
def setCookies(self):
self.cookieFile = "cookies.txt"
self.c... | queryCore.py |
import cookielib
import urllib2
import urllib
import httplib
import urlparse
'''网络数据查询实现类，负责网络数据交互，包括登陆和JSON数据获取'''
class QueryCore():
def __init__(self, ctr):
self.ctr = ctr
self.setCookies()
""" 设置cookie"""
def setCookies(self):
self.cookieFile = "cookies.txt"
self.c... | 0.174094 | 0.083591 |
from django.contrib.gis.geos import GEOSGeometry, GeometryCollection
from snapshottest import TestCase
from .geometry_helpers import ewkt_from_feature_collection
from rescape_python_helpers import ewkt_from_feature, geometry_from_feature, geometrycollection_from_feature_collection
class GeometryHelepersTest(TestCase... | rescape_python_helpers/geospatial/geometry_helpers_test.py | from django.contrib.gis.geos import GEOSGeometry, GeometryCollection
from snapshottest import TestCase
from .geometry_helpers import ewkt_from_feature_collection
from rescape_python_helpers import ewkt_from_feature, geometry_from_feature, geometrycollection_from_feature_collection
class GeometryHelepersTest(TestCase... | 0.68342 | 0.500671 |
from datetime import datetime
from django.shortcuts import get_object_or_404
from django.views.generic import View
from django.http import JsonResponse
from rest_framework import status
from rest_framework.decorators import api_view
from rest_framework.response import Response
from utils.mixins import CsrfExemptMixi... | projects/webptspy/apps/tresult/views/execute/api.py | from datetime import datetime
from django.shortcuts import get_object_or_404
from django.views.generic import View
from django.http import JsonResponse
from rest_framework import status
from rest_framework.decorators import api_view
from rest_framework.response import Response
from utils.mixins import CsrfExemptMixi... | 0.312475 | 0.074973 |
import os
import sys
import csv
import wget
import zipfile
import numpy as np
import pandas as pd
import torch
from torch import nn
import torchvision
from torchvision import transforms, datasets
from torch import distributions
import ssl
from sklearn.metrics import mean_squared_error
'''
Helper functions for MCFlow
... | 2_regression_with_missing_values/lib/MCFlowImputer/util.py | import os
import sys
import csv
import wget
import zipfile
import numpy as np
import pandas as pd
import torch
from torch import nn
import torchvision
from torchvision import transforms, datasets
from torch import distributions
import ssl
from sklearn.metrics import mean_squared_error
'''
Helper functions for MCFlow
... | 0.619586 | 0.377283 |
import pytest
METADATA_ENDPOINT = '/api/v1/metadata/'
@pytest.mark.tendermint
def test_get_metadata_with_empty_text_search(client):
res = client.get(METADATA_ENDPOINT + '?search=')
assert res.json == {'status': 400,
'message': 'text_search cannot be empty'}
assert res.status_code ... | tests/web/test_metadata.py | import pytest
METADATA_ENDPOINT = '/api/v1/metadata/'
@pytest.mark.tendermint
def test_get_metadata_with_empty_text_search(client):
res = client.get(METADATA_ENDPOINT + '?search=')
assert res.json == {'status': 400,
'message': 'text_search cannot be empty'}
assert res.status_code ... | 0.615203 | 0.377053 |
import copy
import numpy as np
import torch
import torch.nn.functional as F
from torch import nn
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
# autoencoder for SVM-base models
class Encoder(nn.Module):
def __init__(self, dim, dataset="Abnormal"):
super(Encoder, self).__init__()
... | models/caenb.py | import copy
import numpy as np
import torch
import torch.nn.functional as F
from torch import nn
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
# autoencoder for SVM-base models
class Encoder(nn.Module):
def __init__(self, dim, dataset="Abnormal"):
super(Encoder, self).__init__()
... | 0.935597 | 0.611324 |
import markdown
from flask import abort, flash, redirect, render_template, request
from flask_babel import gettext as _
from flask_login import current_user, login_required
from ..ext import db
from ..forms.base import DeleteForm
from ..models import Brew, TastingNote
from ..utils.pagination import get_page
from ..uti... | src/brewlog/tasting/views.py | import markdown
from flask import abort, flash, redirect, render_template, request
from flask_babel import gettext as _
from flask_login import current_user, login_required
from ..ext import db
from ..forms.base import DeleteForm
from ..models import Brew, TastingNote
from ..utils.pagination import get_page
from ..uti... | 0.331769 | 0.069827 |
from unittest import mock
from oslo_config import cfg
from kuryr.lib import constants as const
from kuryr.lib import exceptions
from kuryr.tests.unit import base
from kuryr.lib.segmentation_type_drivers import vlan
class VlanSegmentationDriverTest(base.TestCase):
"""Unit tests for VLAN segmentation driver."""... | kuryr/tests/unit/segmentation_type_drivers/test_vlan.py |
from unittest import mock
from oslo_config import cfg
from kuryr.lib import constants as const
from kuryr.lib import exceptions
from kuryr.tests.unit import base
from kuryr.lib.segmentation_type_drivers import vlan
class VlanSegmentationDriverTest(base.TestCase):
"""Unit tests for VLAN segmentation driver."""... | 0.791378 | 0.370681 |
from brownie import ZERO_ADDRESS, Contract, accounts, chain
from brownie_tokens import MintableForkToken
def load_contract(addr):
if addr == ZERO_ADDRESS:
return None
try:
cont = Contract(addr)
except ValueError:
cont = Contract.from_explorer(addr)
return cont
# Load Globals
... | scripts/rewards.py | from brownie import ZERO_ADDRESS, Contract, accounts, chain
from brownie_tokens import MintableForkToken
def load_contract(addr):
if addr == ZERO_ADDRESS:
return None
try:
cont = Contract(addr)
except ValueError:
cont = Contract.from_explorer(addr)
return cont
# Load Globals
... | 0.676406 | 0.259602 |
import os
import math
import time
import random
from pprint import pprint
import yaml
import torch
import torch.nn as nn
import torch.optim as optim
from torch import autograd
from torch.autograd import Variable
from torchvision import transforms
from torchvision.utils import save_image
from torch.util... | inference_causal_vae.py |
import os
import math
import time
import random
from pprint import pprint
import yaml
import torch
import torch.nn as nn
import torch.optim as optim
from torch import autograd
from torch.autograd import Variable
from torchvision import transforms
from torchvision.utils import save_image
from torch.util... | 0.393502 | 0.225065 |
import pyfits as F
import matplotlib.pyplot as P
import numpy as N
#filename1="scala_clap0_calibration_mirror_G1_new2.fits"
filename1="scala_clap0_calibration_mirror_A1_3nm.fits"
filename3="scala_clap1_calibration_mirror_C3.fits"
filename2="scala_clap0_calibration_mirror_A2.fits"
Fits1 = F.open(filename1)
Fits2 ... | SCALA_scripts/plot_test.py |
import pyfits as F
import matplotlib.pyplot as P
import numpy as N
#filename1="scala_clap0_calibration_mirror_G1_new2.fits"
filename1="scala_clap0_calibration_mirror_A1_3nm.fits"
filename3="scala_clap1_calibration_mirror_C3.fits"
filename2="scala_clap0_calibration_mirror_A2.fits"
Fits1 = F.open(filename1)
Fits2 ... | 0.31342 | 0.349921 |
import os, sys, re
from src.ompcply import lex, yacc, _gettabs, _print3000, _reset
import wsgiref.handlers, logging
from google.appengine.api import users
from google.appengine.ext import webapp
from src.functions import path2params, DjangoHandler
from google.appengine.ext import webapp
from google.appengine.e... | examples/appengine/src/m2py.py | import os, sys, re
from src.ompcply import lex, yacc, _gettabs, _print3000, _reset
import wsgiref.handlers, logging
from google.appengine.api import users
from google.appengine.ext import webapp
from src.functions import path2params, DjangoHandler
from google.appengine.ext import webapp
from google.appengine.e... | 0.11135 | 0.049382 |
import time
import rospy
from sensor_msgs.msg import Joy
from geometry_msgs.msg import Vector3, Twist
from std_msgs.msg import String
class Watcher:
def __init__(self):
self.t0 = time.time()
self.timeout = True
self.mode = "manual"
self.idle = False
self.new_joy_msg = Fa... | src/roboclaw/src/safety_listener.py | import time
import rospy
from sensor_msgs.msg import Joy
from geometry_msgs.msg import Vector3, Twist
from std_msgs.msg import String
class Watcher:
def __init__(self):
self.t0 = time.time()
self.timeout = True
self.mode = "manual"
self.idle = False
self.new_joy_msg = Fa... | 0.573559 | 0.229363 |
# ======================================================================
# n u m b e r s . p y
# ======================================================================
"A solver for the Advent of Code 2015 Day 12 puzzle"
# ----------------------------------------------------------------------
... | 2015/12_JSAbacusFramework.io/abacus.py |
# ======================================================================
# n u m b e r s . p y
# ======================================================================
"A solver for the Advent of Code 2015 Day 12 puzzle"
# ----------------------------------------------------------------------
... | 0.787564 | 0.485844 |
import torch
import numpy as np
import math
from sklearn.metrics.pairwise import linear_kernel
class MultiArmedBandit():
def __init__(self, cues=None, start_arm=0, end_arm=7, ctx_dim=2, num_rounds=10, normalize=True, best_arms=None, noise_per_arm=False, cue_per_epoch=False):
default_cues = {'l... | tutorial_metarl/tasks/MultiArmedBandit.py | import torch
import numpy as np
import math
from sklearn.metrics.pairwise import linear_kernel
class MultiArmedBandit():
def __init__(self, cues=None, start_arm=0, end_arm=7, ctx_dim=2, num_rounds=10, normalize=True, best_arms=None, noise_per_arm=False, cue_per_epoch=False):
default_cues = {'l... | 0.687525 | 0.385259 |
# test_regionkey.py
# @category Libraries
# @author <NAME> <<EMAIL>>
# @copyright 2017-2018 GENOMICS plc
# @license MIT (see LICENSE)
# @link https://github.com/genomicsplc/variantkey
import pyvariantkey.variantkey as pyvk
import numpy as np
import os
from unittest import TestCase
# 0:chrom, 1:startp... | python-class/test/test_regionkey.py |
# test_regionkey.py
# @category Libraries
# @author <NAME> <<EMAIL>>
# @copyright 2017-2018 GENOMICS plc
# @license MIT (see LICENSE)
# @link https://github.com/genomicsplc/variantkey
import pyvariantkey.variantkey as pyvk
import numpy as np
import os
from unittest import TestCase
# 0:chrom, 1:startp... | 0.405449 | 0.522385 |
import asyncio
import random
import time
from random import choice
from string import ascii_letters
from typing import Union, Optional
import async_cleverbot as ac
import discord
from discord.ext import commands
from discord.ext.commands.cooldowns import BucketType
from lib import MemberID, Tokens
from lib.classes.gam... | minato_namikaze/cogs/fun/games.py | import asyncio
import random
import time
from random import choice
from string import ascii_letters
from typing import Union, Optional
import async_cleverbot as ac
import discord
from discord.ext import commands
from discord.ext.commands.cooldowns import BucketType
from lib import MemberID, Tokens
from lib.classes.gam... | 0.68784 | 0.151435 |
import glob
import gzip
import json
import os
import pickle
import time
from chorus import v2000writer
from chorus.draw.svg import SVG
from chorus.model.graphmol import Compound
from chorus.util.text import decode
from tornado import gen
from tornado.options import options
from flashflood import static
from flashflo... | ffws/handler.py |
import glob
import gzip
import json
import os
import pickle
import time
from chorus import v2000writer
from chorus.draw.svg import SVG
from chorus.model.graphmol import Compound
from chorus.util.text import decode
from tornado import gen
from tornado.options import options
from flashflood import static
from flashflo... | 0.388154 | 0.121634 |
from dataclasses import dataclass, field
from importlib.resources import path, read_text
from typing import (
Literal,
TypeVar,
Optional,
Union,
Tuple,
NamedTuple,
Mapping,
Dict,
FrozenSet,
)
from collections.abc import MutableMapping
from functools import cached_property
from json i... | cchdo/params/__init__.py | from dataclasses import dataclass, field
from importlib.resources import path, read_text
from typing import (
Literal,
TypeVar,
Optional,
Union,
Tuple,
NamedTuple,
Mapping,
Dict,
FrozenSet,
)
from collections.abc import MutableMapping
from functools import cached_property
from json i... | 0.894922 | 0.238495 |
import matplotlib.pyplot as plt
import math
import zipfile
import os
def generate_screenoverly_kml(overlay_image):
""" generate and overlay kml """
# upper right
overlay_kml = """<?xml version="1.0" encoding="UTF-8"?>
<kml xmlns="http://earth.google.com/kml/2.2">
<ScreenOverlay>
<name>Radar Di... | scripts/direction_arrow.py |
import matplotlib.pyplot as plt
import math
import zipfile
import os
def generate_screenoverly_kml(overlay_image):
""" generate and overlay kml """
# upper right
overlay_kml = """<?xml version="1.0" encoding="UTF-8"?>
<kml xmlns="http://earth.google.com/kml/2.2">
<ScreenOverlay>
<name>Radar Di... | 0.448668 | 0.462655 |
import logging,datetime
from webapp.API.Response import Response
from webapp.SessionsManager import Session, SessionsManager
def historyDataDelete(id_session, id_user):
response = Response(True)
try:
sm = SessionsManager(id_user)
sm.load(id_session)
# Remove session
resul... | webapp/API/history.py | import logging,datetime
from webapp.API.Response import Response
from webapp.SessionsManager import Session, SessionsManager
def historyDataDelete(id_session, id_user):
response = Response(True)
try:
sm = SessionsManager(id_user)
sm.load(id_session)
# Remove session
resul... | 0.393385 | 0.11684 |
from argparse import ArgumentParser
from collections import defaultdict, Counter, namedtuple
import sys
from warnings import warn
import matplotlib.pyplot as plt
from nltk.metrics.scores import precision, recall, f_measure
from nltk.metrics.confusionmatrix import ConfusionMatrix
import numpy as np
from src.corpus imp... | src/evaluation.py | from argparse import ArgumentParser
from collections import defaultdict, Counter, namedtuple
import sys
from warnings import warn
import matplotlib.pyplot as plt
from nltk.metrics.scores import precision, recall, f_measure
from nltk.metrics.confusionmatrix import ConfusionMatrix
import numpy as np
from src.corpus imp... | 0.527803 | 0.327776 |
from django.test import TestCase
from unittest2 import skipIf
from django.db import connection
import json
from datetime import datetime
from dateutil import parser
from django.utils import timezone
from sqlshare_rest.util.db import get_backend
from sqlshare_rest.test import missing_url
from django.test.utils import ov... | sqlshare_rest/test/api/user_search.py | from django.test import TestCase
from unittest2 import skipIf
from django.db import connection
import json
from datetime import datetime
from dateutil import parser
from django.utils import timezone
from sqlshare_rest.util.db import get_backend
from sqlshare_rest.test import missing_url
from django.test.utils import ov... | 0.408159 | 0.188884 |
import urllib.request
import re
import os
import csv
topnum = 1;
#获取网页源代码
def getHtml(url):
page = urllib.request.urlopen(url);
html = page.read();
return html;
#通过正则表达式获取该网页下的每部电影的title
def getName(html):
nameList = re.findall(r'<span.*?class="title">(.*?)</span>', html, re.S);
global topnum
... | douban_movie_scraper.py | import urllib.request
import re
import os
import csv
topnum = 1;
#获取网页源代码
def getHtml(url):
page = urllib.request.urlopen(url);
html = page.read();
return html;
#通过正则表达式获取该网页下的每部电影的title
def getName(html):
nameList = re.findall(r'<span.*?class="title">(.*?)</span>', html, re.S);
global topnum
... | 0.082071 | 0.111652 |
from components import MissingInputModal, MismatchModal, PlotPlaceHolder, DisplayControlCard
from enum import Enum
from operator import itemgetter
from parsers import DatasetStates
import plotly.graph_objects as go
from plotly.colors import diverging
from plotly.colors import sequential
from loaders import DatasetRefer... | utils/plot_utils.py | from components import MissingInputModal, MismatchModal, PlotPlaceHolder, DisplayControlCard
from enum import Enum
from operator import itemgetter
from parsers import DatasetStates
import plotly.graph_objects as go
from plotly.colors import diverging
from plotly.colors import sequential
from loaders import DatasetRefer... | 0.742608 | 0.133839 |
import os, os.path
import random
import sqlite3
import string
import time
import cherrypy
DB_STRING = "url.db"
BASE_HOST_NAME = "http://localhost:8080/"
class ShortUrlGenerator(object):
@cherrypy.expose
def index(self):
return file('index.html')
class ShortUrlWebService(object):
exposed = True
... | webapp/server.py | import os, os.path
import random
import sqlite3
import string
import time
import cherrypy
DB_STRING = "url.db"
BASE_HOST_NAME = "http://localhost:8080/"
class ShortUrlGenerator(object):
@cherrypy.expose
def index(self):
return file('index.html')
class ShortUrlWebService(object):
exposed = True
... | 0.413832 | 0.084682 |
import os
import random
import click
import praw
import requests
from PIL import Image
MIN_WIDTH = 1920
MIN_HEIGHT = 1200
MAX_RETRIES = 25
SUBS = [
'wallpapers',
'wallpaper',
'earthporn',
'skylineporn',
'bigwallpapers',
# 'nocontext_wallpapers',
# 'gmbwallpapers',
# 'NSFW_Wallpapers',... | Scripts/wallpaper.py | import os
import random
import click
import praw
import requests
from PIL import Image
MIN_WIDTH = 1920
MIN_HEIGHT = 1200
MAX_RETRIES = 25
SUBS = [
'wallpapers',
'wallpaper',
'earthporn',
'skylineporn',
'bigwallpapers',
# 'nocontext_wallpapers',
# 'gmbwallpapers',
# 'NSFW_Wallpapers',... | 0.294824 | 0.069007 |
import os
import pwd
import json
from src import config
from src import plugin
# aliases for path to use later on
user = pwd.getpwuid(os.getuid())[0]
path = "/home/"+user+"/.config"
class Plugin(plugin.Base):
@staticmethod
def name() -> str:
return "Visual Studio Code"
@classmethod
def a... | src/plugins/vscode.py | import os
import pwd
import json
from src import config
from src import plugin
# aliases for path to use later on
user = pwd.getpwuid(os.getuid())[0]
path = "/home/"+user+"/.config"
class Plugin(plugin.Base):
@staticmethod
def name() -> str:
return "Visual Studio Code"
@classmethod
def a... | 0.073413 | 0.100525 |
from subprocess import Popen, DEVNULL, TimeoutExpired
import logging
import argparse
import json
import os
from os.path import join, exists
import shutil
import pathlib
import tempfile
root_dir = os.getcwd()
workdir = join(root_dir, ".prep_dev_patch")
logger = logging.getLogger("prep_dev_patch")
prog_config = dict()
... | src/prep_dev_patch.py | from subprocess import Popen, DEVNULL, TimeoutExpired
import logging
import argparse
import json
import os
from os.path import join, exists
import shutil
import pathlib
import tempfile
root_dir = os.getcwd()
workdir = join(root_dir, ".prep_dev_patch")
logger = logging.getLogger("prep_dev_patch")
prog_config = dict()
... | 0.312895 | 0.054803 |
from unittest import TestCase
import os
from musicscore.musicstream.streamvoice import SimpleFormat
from musicscore.musictree.treescoretimewise import TreeScoreTimewise
from tests.score_templates.xml_test_score import TestScore
path = os.path.abspath(__file__).split('.')[0]
class Test(TestCase):
def setUp(self)... | tests/musicstream/test_grace.py | from unittest import TestCase
import os
from musicscore.musicstream.streamvoice import SimpleFormat
from musicscore.musictree.treescoretimewise import TreeScoreTimewise
from tests.score_templates.xml_test_score import TestScore
path = os.path.abspath(__file__).split('.')[0]
class Test(TestCase):
def setUp(self)... | 0.559049 | 0.420897 |
import ipywidgets as widgets
from sage.misc.all import latex
from sage.repl.rich_output.pretty_print import pretty_print
from IPython.display import clear_output
def cluster_interact(self, fig_size=1, circular=True, kind='seed'):
r"""
Start an interactive window for cluster seed mutations.
Only in *Jupyt... | src/sage/combinat/cluster_algebra_quiver/interact.py | import ipywidgets as widgets
from sage.misc.all import latex
from sage.repl.rich_output.pretty_print import pretty_print
from IPython.display import clear_output
def cluster_interact(self, fig_size=1, circular=True, kind='seed'):
r"""
Start an interactive window for cluster seed mutations.
Only in *Jupyt... | 0.619471 | 0.538498 |
from __future__ import print_function, division, unicode_literals, absolute_import
from .utils import *
def test_wronskian():
"""
Wronskian formula for W{P^m_lam(x), P^m_lam(-x)}
"""
for m,lam, x in [(3,0.75+0.1j,0.4), (0,0.75+0.1j,0.4), (25,0.75+0.1j,0.1)]:
llp1 = lam*(lam+1)
p = lam... | smerfs/tests/test_green.py | from __future__ import print_function, division, unicode_literals, absolute_import
from .utils import *
def test_wronskian():
"""
Wronskian formula for W{P^m_lam(x), P^m_lam(-x)}
"""
for m,lam, x in [(3,0.75+0.1j,0.4), (0,0.75+0.1j,0.4), (25,0.75+0.1j,0.1)]:
llp1 = lam*(lam+1)
p = lam... | 0.647575 | 0.568176 |
import collections
import itertools
import os
import pickle
import numpy as np
import torch
from sketchgraphs_models import training
from sketchgraphs_models.graph import model as graph_model
from sketchgraphs_models.nn import summary
def _detach(x):
if isinstance(x, torch.Tensor):
return x.detach()
... | sketchgraphs_models/graph/train/harness.py |
import collections
import itertools
import os
import pickle
import numpy as np
import torch
from sketchgraphs_models import training
from sketchgraphs_models.graph import model as graph_model
from sketchgraphs_models.nn import summary
def _detach(x):
if isinstance(x, torch.Tensor):
return x.detach()
... | 0.673514 | 0.277259 |
import argparse
import dpkt
import random
import re
import struct
def main():
"""
Main packet generator function
"""
parser = argparse.ArgumentParser()
parser.add_argument('-t', dest = 'textFilename', action = 'store',
help = 'Output text file')
parser.add_argument('-p', dest = 'pcapF... | FPGA/Utilities/PacketGenerator/PacketGenerator.py | import argparse
import dpkt
import random
import re
import struct
def main():
"""
Main packet generator function
"""
parser = argparse.ArgumentParser()
parser.add_argument('-t', dest = 'textFilename', action = 'store',
help = 'Output text file')
parser.add_argument('-p', dest = 'pcapF... | 0.324878 | 0.077065 |
import numpy as np
import pandas as pd
import math
# Logarithmic Mean Temperature Difference (LMTD) is used to determine the temperature driving force for heat transfer in flow systems.
def heat_capacity(mass_flow_rate, cp):
""" Calculates the heat_capacity given a mass_flow_rate
and a specif_heat of a m... | files/lmtd.py | import numpy as np
import pandas as pd
import math
# Logarithmic Mean Temperature Difference (LMTD) is used to determine the temperature driving force for heat transfer in flow systems.
def heat_capacity(mass_flow_rate, cp):
""" Calculates the heat_capacity given a mass_flow_rate
and a specif_heat of a m... | 0.918763 | 0.871748 |
from __future__ import print_function
import os
import cv2
import sys
import time
import uuid
import json
import glob
import boto3
import flask
import errno
import shutil
import datetime
from PIL import Image
from pathlib import Path
from multiprocessing import Pool
from collections import OrderedDict
import traceb... | sagemaker/02-inference/source/predictor.py |
from __future__ import print_function
import os
import cv2
import sys
import time
import uuid
import json
import glob
import boto3
import flask
import errno
import shutil
import datetime
from PIL import Image
from pathlib import Path
from multiprocessing import Pool
from collections import OrderedDict
import traceb... | 0.370681 | 0.079997 |