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 threading
import zmq
from force_bdss.api import BaseDriverEvent, DriverEventDeserializationError
log = logging.getLogger(__name__)
class ZMQServer(threading.Thread):
"""ZeroMQ based server. It is a state machine with different
handlers. New behavior is added by adding or modifying th... | force_wfmanager/server/zmq_server.py |
import logging
import threading
import zmq
from force_bdss.api import BaseDriverEvent, DriverEventDeserializationError
log = logging.getLogger(__name__)
class ZMQServer(threading.Thread):
"""ZeroMQ based server. It is a state machine with different
handlers. New behavior is added by adding or modifying th... | 0.660063 | 0.166709 |
import abc
import collections
import dataclasses
import datetime
import functools
import numbers
import time
import typing
import numpy as np
import torch
import torch.utils.tensorboard
from sketchgraphs_models import distributed_utils
_scalar_types = (
torch.Tensor, np.ndarray, numbers.Number, np.int32, np.int6... | sketchgraphs_models/training.py | import abc
import collections
import dataclasses
import datetime
import functools
import numbers
import time
import typing
import numpy as np
import torch
import torch.utils.tensorboard
from sketchgraphs_models import distributed_utils
_scalar_types = (
torch.Tensor, np.ndarray, numbers.Number, np.int32, np.int6... | 0.921512 | 0.361362 |
import numpy as np
import matplotlib.pyplot as plt
import random
class random_generator(object):
def __init__(self,num=20, range_=(0,100), start_point=0):
self.points = np.random.randint(*range_,size=(num,2))
#self.destination = np.random.randint(0,num)
self.start_point = start_po... | source_code/env.py | import numpy as np
import matplotlib.pyplot as plt
import random
class random_generator(object):
def __init__(self,num=20, range_=(0,100), start_point=0):
self.points = np.random.randint(*range_,size=(num,2))
#self.destination = np.random.randint(0,num)
self.start_point = start_po... | 0.374676 | 0.310041 |
from django.db import models
from django.contrib.auth.models import AbstractBaseUser
from django.contrib.auth.models import PermissionsMixin
from django.contrib.auth.models import BaseUserManager
class UserProfileManager(BaseUserManager):
"""Manager for User Profiles"""
def create_user(self, email, name,... | profiles_api/models.py | from django.db import models
from django.contrib.auth.models import AbstractBaseUser
from django.contrib.auth.models import PermissionsMixin
from django.contrib.auth.models import BaseUserManager
class UserProfileManager(BaseUserManager):
"""Manager for User Profiles"""
def create_user(self, email, name,... | 0.495117 | 0.077308 |
import random
import numpy as np
import librosa
import torch
from torch.utils.data import Dataset
def should_apply_transform(prob=0.5):
"""Transforms are only randomly applied with the given probability."""
return random.random() < prob
class ChangeAmplitude(object):
"""Changes amplitude of an audio ran... | transforms_wav.py | import random
import numpy as np
import librosa
import torch
from torch.utils.data import Dataset
def should_apply_transform(prob=0.5):
"""Transforms are only randomly applied with the given probability."""
return random.random() < prob
class ChangeAmplitude(object):
"""Changes amplitude of an audio ran... | 0.888904 | 0.481941 |
from Authentication import *
import requests
import json
import argparse
import xml.etree.ElementTree as ET
import sys
parser = argparse.ArgumentParser(description='process user given parameters')
parser.add_argument("-k", "--apikey", required = True, dest = "apikey", help = "enter api key from your UTS Profile")
par... | umls_rest_api/retrieve-value-set-info.py |
from Authentication import *
import requests
import json
import argparse
import xml.etree.ElementTree as ET
import sys
parser = argparse.ArgumentParser(description='process user given parameters')
parser.add_argument("-k", "--apikey", required = True, dest = "apikey", help = "enter api key from your UTS Profile")
par... | 0.198919 | 0.065336 |
import schedule
import time
import importlib
import logging
import re
from glob import Glob
from drivers.oasisunit import OasisUnit
from dborm import turhousedb
class TurhouseOasisDriverError(Exception):
pass
class TurhouseOasis(object):
'''
Daemon servicing oasis units
'''
def __init__(... | turhouseoasis.py |
import schedule
import time
import importlib
import logging
import re
from glob import Glob
from drivers.oasisunit import OasisUnit
from dborm import turhousedb
class TurhouseOasisDriverError(Exception):
pass
class TurhouseOasis(object):
'''
Daemon servicing oasis units
'''
def __init__(... | 0.401219 | 0.157105 |
import random
def generate_pos_triples(triples, batch_size, step):
start = step * batch_size
end = start + batch_size
if end > len(triples):
end = len(triples)
pos_batch = triples[start: end]
return pos_batch
def generate_neg_attribute_triples(pos_batch, all_triples_set, entity_list, neg... | code/attr_batch.py | import random
def generate_pos_triples(triples, batch_size, step):
start = step * batch_size
end = start + batch_size
if end > len(triples):
end = len(triples)
pos_batch = triples[start: end]
return pos_batch
def generate_neg_attribute_triples(pos_batch, all_triples_set, entity_list, neg... | 0.402862 | 0.284188 |
import logging
import numpy as np
import pandas as pd
import sklearn.linear_model as sklm
from sklearn.impute import KNNImputer
from sklearn.impute._base import _BaseImputer # noqa
from sklearn.preprocessing import StandardScaler
from imblearn.over_sampling import RandomOverSampler
from .base import Task, Balance... | favseq/preprocessing.py | import logging
import numpy as np
import pandas as pd
import sklearn.linear_model as sklm
from sklearn.impute import KNNImputer
from sklearn.impute._base import _BaseImputer # noqa
from sklearn.preprocessing import StandardScaler
from imblearn.over_sampling import RandomOverSampler
from .base import Task, Balance... | 0.863392 | 0.425546 |
import keras
from keras.datasets import mnist
from keras.models import Sequential, load_model
from keras.layers import Dense, Dropout, Flatten
from keras.layers import ZeroPadding2D, Conv2D, MaxPooling2D
from keras.optimizers import SGD
from PIL import Image, ImageFilter
import numpy as np
import matplotlib.pyp... | VGG-11-Modified-MNIST/vgg11_rotation_blur.py | import keras
from keras.datasets import mnist
from keras.models import Sequential, load_model
from keras.layers import Dense, Dropout, Flatten
from keras.layers import ZeroPadding2D, Conv2D, MaxPooling2D
from keras.optimizers import SGD
from PIL import Image, ImageFilter
import numpy as np
import matplotlib.pyp... | 0.843154 | 0.611411 |
from __future__ import print_function
import numpy as np
from dynamic_graph.sot_talos_balance.dcm_controller import DcmController
from numpy.testing import assert_almost_equal
controller = DcmController("ciao")
print("\nSignals (at creation):")
controller.displaySignals()
Kp = np.array([10.0, 10.0, 0.0])
Ki = np.ar... | tests/python/test_dcm_controller.py | from __future__ import print_function
import numpy as np
from dynamic_graph.sot_talos_balance.dcm_controller import DcmController
from numpy.testing import assert_almost_equal
controller = DcmController("ciao")
print("\nSignals (at creation):")
controller.displaySignals()
Kp = np.array([10.0, 10.0, 0.0])
Ki = np.ar... | 0.537041 | 0.208119 |
from masci_tools.util.constants import HTR_TO_EV, BOHR_A
from .reader import Transformation, AttribTransformation
def dos_recipe_format(group):
"""
Format for denisty of states calculations retrieving the DOS from the given group
:param group: str of the group the DOS should be taken from
:returns: ... | masci_tools/io/parsers/hdf5/recipes.py | from masci_tools.util.constants import HTR_TO_EV, BOHR_A
from .reader import Transformation, AttribTransformation
def dos_recipe_format(group):
"""
Format for denisty of states calculations retrieving the DOS from the given group
:param group: str of the group the DOS should be taken from
:returns: ... | 0.741206 | 0.506408 |
from antlr4 import *
from io import StringIO
from typing.io import TextIO
import sys
def serializedATN():
with StringIO() as buf:
buf.write("\3\u608b\ua72a\u8133\ub9ed\u417c\u3be7\u7786\u5964\2*")
buf.write("\u010d\b\1\4\2\t\2\4\3\t\3\4\4\t\4\4\5\t\5\4\6\t\6\4\7")
buf.write("\t\7\4\b\t\b\4... | Fujitsu/benchmarks/resnet/implementations/implementation_open/mxnet/3rdparty/tvm/python/tvm/relay/grammar/py3/RelayLexer.py | from antlr4 import *
from io import StringIO
from typing.io import TextIO
import sys
def serializedATN():
with StringIO() as buf:
buf.write("\3\u608b\ua72a\u8133\ub9ed\u417c\u3be7\u7786\u5964\2*")
buf.write("\u010d\b\1\4\2\t\2\4\3\t\3\4\4\t\4\4\5\t\5\4\6\t\6\4\7")
buf.write("\t\7\4\b\t\b\4... | 0.297674 | 0.319957 |
from datetime import datetime
import pytest
from fakeparser import Parser
from reader import Content
from reader import Entry
from reader.plugins.entry_dedupe import _is_duplicate
from reader.plugins.entry_dedupe import _normalize
def test_normalize():
assert _normalize('\n\n<B>whatever</B> Blah </p>') ==... | tests/test_plugins_entry_dedupe.py | from datetime import datetime
import pytest
from fakeparser import Parser
from reader import Content
from reader import Entry
from reader.plugins.entry_dedupe import _is_duplicate
from reader.plugins.entry_dedupe import _normalize
def test_normalize():
assert _normalize('\n\n<B>whatever</B> Blah </p>') ==... | 0.454714 | 0.284284 |
from expressions import TermCategory, Term
azul = Term("azul", categories=(TermCategory.ITEM,))
albahaca = Term("alba(ha)?ca", categories=(TermCategory.ITEM,))
bebida = Term("bebidas?", categories=(TermCategory.ITEM,))
blanca = Term("blanc[oa]s?", categories=(TermCategory.ITEM,))
caprese = Term("capress?e", ... | terms.py |
from expressions import TermCategory, Term
azul = Term("azul", categories=(TermCategory.ITEM,))
albahaca = Term("alba(ha)?ca", categories=(TermCategory.ITEM,))
bebida = Term("bebidas?", categories=(TermCategory.ITEM,))
blanca = Term("blanc[oa]s?", categories=(TermCategory.ITEM,))
caprese = Term("capress?e", ... | 0.293708 | 0.277927 |
from __future__ import annotations
from typing import Any, List
from homeassistant.core import HomeAssistant, callback
from homeassistant.helpers.entity import DeviceInfo
from homeassistant.helpers.update_coordinator import CoordinatorEntity
from openhab import items
from .const import ATTRIBUTION, DOMAIN, NAME, VER... | custom_components/openhab/entity.py | from __future__ import annotations
from typing import Any, List
from homeassistant.core import HomeAssistant, callback
from homeassistant.helpers.entity import DeviceInfo
from homeassistant.helpers.update_coordinator import CoordinatorEntity
from openhab import items
from .const import ATTRIBUTION, DOMAIN, NAME, VER... | 0.921689 | 0.133613 |
from gmqtt import Client as MQTTClient
from gmqtt import Message
from typing import Any, Callable, Dict, List, Optional, Sequence, Type, Union
import ssl
from ssl import SSLContext
from gmqtt.mqtt.constants import MQTTv311,MQTTv50
from .config import MQQTConfig
import uuid
from functools import partial
import asyncio
f... | fastapi_mqtt/fastmqtt.py | from gmqtt import Client as MQTTClient
from gmqtt import Message
from typing import Any, Callable, Dict, List, Optional, Sequence, Type, Union
import ssl
from ssl import SSLContext
from gmqtt.mqtt.constants import MQTTv311,MQTTv50
from .config import MQQTConfig
import uuid
from functools import partial
import asyncio
f... | 0.572962 | 0.061255 |
import io
import os
import random
import argparse
import unittest
from contextlib import redirect_stderr
from types import SimpleNamespace
from feanor.builtin import BuiltInLibrary
from feanor.library import MockLibrary
from feanor.main import (
make_schema_cmdline, get_library, _parse_global_configuration, make_s... | tests/test_main.py | import io
import os
import random
import argparse
import unittest
from contextlib import redirect_stderr
from types import SimpleNamespace
from feanor.builtin import BuiltInLibrary
from feanor.library import MockLibrary
from feanor.main import (
make_schema_cmdline, get_library, _parse_global_configuration, make_s... | 0.512937 | 0.385086 |
import logging
from django.apps import apps
from django.contrib.auth.models import User, Group
from django.core.exceptions import PermissionDenied
from django.db.models import Q
from django.http import Http404, HttpResponse, HttpResponseNotFound, HttpResponseForbidden
from django.shortcuts import redirect, render, rev... | apps/activity/activity_type/course.py | import logging
from django.apps import apps
from django.contrib.auth.models import User, Group
from django.core.exceptions import PermissionDenied
from django.db.models import Q
from django.http import Http404, HttpResponse, HttpResponseNotFound, HttpResponseForbidden
from django.shortcuts import redirect, render, rev... | 0.528047 | 0.134833 |
import h5py
from sklearn.mixture import GMM, DPGMM
import scipy.signal
from multiprocessing import Pool
import numpy as np
from io_tools import basic_parser, h5_io
from utils import fast_median_calculator, plotters, panel_tools, mask_tools
import sys, os
import matplotlib.pyplot as plt
default_parameters = """
[da... | process/preprocess.py | import h5py
from sklearn.mixture import GMM, DPGMM
import scipy.signal
from multiprocessing import Pool
import numpy as np
from io_tools import basic_parser, h5_io
from utils import fast_median_calculator, plotters, panel_tools, mask_tools
import sys, os
import matplotlib.pyplot as plt
default_parameters = """
[da... | 0.228071 | 0.460835 |
from email.policy import default
from django.db import models
from django.conf import settings
from django.utils import timezone
from django.contrib.auth.models import User
from numpy import array
from django.contrib.postgres.fields import ArrayField
class Profile(models.Model):
user = models.OneToOneField(User,... | learningmachines/searcher/models.py |
from email.policy import default
from django.db import models
from django.conf import settings
from django.utils import timezone
from django.contrib.auth.models import User
from numpy import array
from django.contrib.postgres.fields import ArrayField
class Profile(models.Model):
user = models.OneToOneField(User,... | 0.410993 | 0.11887 |
#------------------------------------------------------------------------------
# Imports
#------------------------------------------------------------------------------
import logging
import numpy as np
from phy.cluster.manual.gui_component import ManualClustering
from phy.cluster.manual.views import (WaveformView,... | phy/cluster/manual/controller.py | #------------------------------------------------------------------------------
# Imports
#------------------------------------------------------------------------------
import logging
import numpy as np
from phy.cluster.manual.gui_component import ManualClustering
from phy.cluster.manual.views import (WaveformView,... | 0.526099 | 0.203193 |
import numpy as np
import os, sys, random
import cv2
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.layers import Convolution2D, MaxPooling2D
from keras.utils import np_utils
from keras import backend as K
from keras.models import load_model
np.random.seed... | keras_train.py |
import numpy as np
import os, sys, random
import cv2
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.layers import Convolution2D, MaxPooling2D
from keras.utils import np_utils
from keras import backend as K
from keras.models import load_model
np.random.seed... | 0.441553 | 0.375477 |
import os
import netCDF4
import src.util.type_helper as th
class NetCDFReader:
@staticmethod
def info(netcdf_data):
# NetCDF global attributes
nc_attrs = netcdf_data.ncattrs()
# Variable information.
nc_vars = [var for var in netcdf_data.variables] # list of nc variables
... | src/netcdf_reader.py | import os
import netCDF4
import src.util.type_helper as th
class NetCDFReader:
@staticmethod
def info(netcdf_data):
# NetCDF global attributes
nc_attrs = netcdf_data.ncattrs()
# Variable information.
nc_vars = [var for var in netcdf_data.variables] # list of nc variables
... | 0.607314 | 0.208139 |
import xml.etree.ElementTree as ET
from deployerlib.ssh import SSH
class HA(SSH):
ha_cluster_xml_file = f"cluster.xml"
def __init__(self, *, cluster_name, **kwargs):
super(HA, self).__init__(**kwargs)
self.cluster_name = cluster_name
def ha_base_setup(self, vms):
""... | src/deployerlib/ha.py | import xml.etree.ElementTree as ET
from deployerlib.ssh import SSH
class HA(SSH):
ha_cluster_xml_file = f"cluster.xml"
def __init__(self, *, cluster_name, **kwargs):
super(HA, self).__init__(**kwargs)
self.cluster_name = cluster_name
def ha_base_setup(self, vms):
""... | 0.358016 | 0.091911 |
import concurrent.futures
from dataclasses import dataclass, field
import itertools
import multiprocessing
import logging
import copy
import tqdm
from terminaltables import AsciiTable
import numpy as np
from azusa.mana_producers import PRODUCERS, ManaPermanent
from azusa.util import defaultdict, combinations_with_qua... | azusa/curve_probabilities.py | import concurrent.futures
from dataclasses import dataclass, field
import itertools
import multiprocessing
import logging
import copy
import tqdm
from terminaltables import AsciiTable
import numpy as np
from azusa.mana_producers import PRODUCERS, ManaPermanent
from azusa.util import defaultdict, combinations_with_qua... | 0.464416 | 0.31625 |
from starfish import Experiment
def MERFISH(use_test_data: bool=False):
if use_test_data:
return Experiment.from_json(
"https://d2nhj9g34unfro.cloudfront.net/20181005/MERFISH-TEST/experiment.json")
return Experiment.from_json(
"https://d2nhj9g34unfro.cloudfront.net/20181005/MERFISH... | starfish/data/__init__.py | from starfish import Experiment
def MERFISH(use_test_data: bool=False):
if use_test_data:
return Experiment.from_json(
"https://d2nhj9g34unfro.cloudfront.net/20181005/MERFISH-TEST/experiment.json")
return Experiment.from_json(
"https://d2nhj9g34unfro.cloudfront.net/20181005/MERFISH... | 0.848408 | 0.436022 |
import os
import logging
import time
from torch.backends import cudnn
from utils.logger import setup_logger
from datasets import make_dataloader
from model import make_model
from solver import make_optimizer, WarmupMultiStepLR
from loss import make_loss
import random
import torch
import numpy as np
import argparse
from... | train_cam.py | import os
import logging
import time
from torch.backends import cudnn
from utils.logger import setup_logger
from datasets import make_dataloader
from model import make_model
from solver import make_optimizer, WarmupMultiStepLR
from loss import make_loss
import random
import torch
import numpy as np
import argparse
from... | 0.558809 | 0.15006 |
import os
from typing import Callable, List, Tuple
from PyQt6 import QtGui
from PyQt6.QtCore import QRect
from PyQt6.QtGui import QFontDatabase
from PyQt6.QtWidgets import QHBoxLayout, QMainWindow, QMenuBar, QStatusBar, QWidget
import log
from api import APIManager
from loginwidget import LoginWidget
from mainwidge... | src/mainwindow.py | import os
from typing import Callable, List, Tuple
from PyQt6 import QtGui
from PyQt6.QtCore import QRect
from PyQt6.QtGui import QFontDatabase
from PyQt6.QtWidgets import QHBoxLayout, QMainWindow, QMenuBar, QStatusBar, QWidget
import log
from api import APIManager
from loginwidget import LoginWidget
from mainwidge... | 0.615435 | 0.080792 |
import configparser
import os
from pathlib import Path
from typing import Any, Dict, Optional, Union
from conan_app_launcher import PathLike
from conan_app_launcher.app.logger import Logger
from . import (APPLIST_ENABLED, DISPLAY_APP_CHANNELS, DISPLAY_APP_USERS, DISPLAY_APP_VERSIONS,
ENABLE_AP... | src/conan_app_launcher/settings/ini_file.py | import configparser
import os
from pathlib import Path
from typing import Any, Dict, Optional, Union
from conan_app_launcher import PathLike
from conan_app_launcher.app.logger import Logger
from . import (APPLIST_ENABLED, DISPLAY_APP_CHANNELS, DISPLAY_APP_USERS, DISPLAY_APP_VERSIONS,
ENABLE_AP... | 0.620507 | 0.08882 |
import re
import facebook
from front import gift_types, InitialMessages
from front.tests import base
from front.tests.base import VOUCHER_KEY_S1_GIFT
from front.lib import db, urls
from front.models import chips
from front.backend import admin
class TestFacebookSignup(base.TestCase):
def setUp(self):
supe... | tests/client/test_facebook.py | import re
import facebook
from front import gift_types, InitialMessages
from front.tests import base
from front.tests.base import VOUCHER_KEY_S1_GIFT
from front.lib import db, urls
from front.models import chips
from front.backend import admin
class TestFacebookSignup(base.TestCase):
def setUp(self):
supe... | 0.386185 | 0.16654 |
from datetime import datetime
from pprint import pformat
from six import iteritems
import re
class ProductRest(object):
"""
NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): The key is att... | pnc_cli/swagger_client/models/product_rest.py | from datetime import datetime
from pprint import pformat
from six import iteritems
import re
class ProductRest(object):
"""
NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): The key is att... | 0.664105 | 0.127218 |
from data_importers.management.commands import BaseXpressDemocracyClubCsvImporter
class Command(BaseXpressDemocracyClubCsvImporter):
council_id = "NBL"
addresses_name = "2021-03-25T12:14:50.419215/Democracy_Club__06May2021.tsv"
stations_name = "2021-03-25T12:14:50.419215/Democracy_Club__06May2021.tsv"
... | polling_stations/apps/data_importers/management/commands/import_northumberland.py | from data_importers.management.commands import BaseXpressDemocracyClubCsvImporter
class Command(BaseXpressDemocracyClubCsvImporter):
council_id = "NBL"
addresses_name = "2021-03-25T12:14:50.419215/Democracy_Club__06May2021.tsv"
stations_name = "2021-03-25T12:14:50.419215/Democracy_Club__06May2021.tsv"
... | 0.46223 | 0.297693 |
import json
import re
import http.client
import sys
hev = [90, 99]
relays = [70, 71, 89]
buttons = [70, 71, 89]
def main():
conn = http.client.HTTPSConnection("raw.githubusercontent.com")
conn.request("GET", "/LIFX/products/master/products.json")
resp = conn.getresponse()
if resp.status != 200:
... | lifxlan/generate_products_file.py |
import json
import re
import http.client
import sys
hev = [90, 99]
relays = [70, 71, 89]
buttons = [70, 71, 89]
def main():
conn = http.client.HTTPSConnection("raw.githubusercontent.com")
conn.request("GET", "/LIFX/products/master/products.json")
resp = conn.getresponse()
if resp.status != 200:
... | 0.164684 | 0.150871 |
import csv
import numpy as np
import utils
_unk_ = 0
_pad_ = 1
y_Encoder = utils.y_Encoder(['0','1','2','3','4'])
maxlen = 56
trainXCodeList = []
seqlenList = []
trainYCodeList = []
vocab = {}
vocab["_unk_"] = _unk_
vocab["_pad_"] = _pad_
header = True
next_index = 2
print("creating traindData and voca... | Kaggle/Sentiment Analysis/kerasMain.py | import csv
import numpy as np
import utils
_unk_ = 0
_pad_ = 1
y_Encoder = utils.y_Encoder(['0','1','2','3','4'])
maxlen = 56
trainXCodeList = []
seqlenList = []
trainYCodeList = []
vocab = {}
vocab["_unk_"] = _unk_
vocab["_pad_"] = _pad_
header = True
next_index = 2
print("creating traindData and voca... | 0.301156 | 0.160858 |
from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.preprocessing import OrdinalEncoder
class TransformerChooser(BaseEstimator, TransformerMixin):
"""Transformer that wraps another Transformer. This allows different transformer objects to be tuned.
"""
def __init__(self, transformer=None... | helpsk/sklearn_pipeline.py | from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.preprocessing import OrdinalEncoder
class TransformerChooser(BaseEstimator, TransformerMixin):
"""Transformer that wraps another Transformer. This allows different transformer objects to be tuned.
"""
def __init__(self, transformer=None... | 0.895185 | 0.211071 |
from datetime import datetime, timedelta
from typing import *
import attr
from dlms_cosem import a_xdr, cosem, enumerations
from dlms_cosem.cosem import CosemAttribute
from dlms_cosem.cosem.association import (
AccessRight,
AssociationObjectListItem,
AttributeAccessRights,
MethodAccessRights,
)
from d... | dlms_cosem/parsers.py | from datetime import datetime, timedelta
from typing import *
import attr
from dlms_cosem import a_xdr, cosem, enumerations
from dlms_cosem.cosem import CosemAttribute
from dlms_cosem.cosem.association import (
AccessRight,
AssociationObjectListItem,
AttributeAccessRights,
MethodAccessRights,
)
from d... | 0.645567 | 0.291989 |
import os
import cv2
import numpy as np
IMAGE_SIZE = 32
def list_folders(root_folder):
"""Function to get subdir list"""
folder_list = []
for folder in sorted(os.listdir(root_folder)):
if os.path.isdir(os.path.join(root_folder, folder)):
folder_list.append(folder)
return folder_li... | functions.py | import os
import cv2
import numpy as np
IMAGE_SIZE = 32
def list_folders(root_folder):
"""Function to get subdir list"""
folder_list = []
for folder in sorted(os.listdir(root_folder)):
if os.path.isdir(os.path.join(root_folder, folder)):
folder_list.append(folder)
return folder_li... | 0.44071 | 0.304946 |
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
import time
import torch
from torch import nn
from torch import tensor
from torch import optim
import torch.nn.functional as F
from torch.autograd import Variable
from torchvision import datasets, transforms
import torchvision.models as models
fro... | utils.py | import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
import time
import torch
from torch import nn
from torch import tensor
from torch import optim
import torch.nn.functional as F
from torch.autograd import Variable
from torchvision import datasets, transforms
import torchvision.models as models
fro... | 0.727685 | 0.4133 |
from unittest.mock import Mock, patch
import task
def test_constructor_hasDefaultProperties():
t = task.TaskQueue()
assert t is not None
assert len(t._TaskList) == 0
def test_hasNext_noTasksInQueue():
t = task.TaskQueue()
assert not t.hasNext()
def test_hasNext_oneTaskInQueue():
... | python-remote-commands-attn-rpi/test_task.py | from unittest.mock import Mock, patch
import task
def test_constructor_hasDefaultProperties():
t = task.TaskQueue()
assert t is not None
assert len(t._TaskList) == 0
def test_hasNext_noTasksInQueue():
t = task.TaskQueue()
assert not t.hasNext()
def test_hasNext_oneTaskInQueue():
... | 0.527317 | 0.426023 |
import sqlalchemy as sa
from alembic import op
from manager_rest.storage.models_base import JSONString, UTCDateTime
# revision identifiers, used by Alembic.
revision = '<KEY>'
down_revision = '<PASSWORD>'
branch_labels = None
depends_on = None
TABLES_TO_AUDIT = [('agents', 'storage_id'),
('bluepr... | resources/rest-service/cloudify/migrations/versions/8e8314b1d848_6_2_to_6_3.py | import sqlalchemy as sa
from alembic import op
from manager_rest.storage.models_base import JSONString, UTCDateTime
# revision identifiers, used by Alembic.
revision = '<KEY>'
down_revision = '<PASSWORD>'
branch_labels = None
depends_on = None
TABLES_TO_AUDIT = [('agents', 'storage_id'),
('bluepr... | 0.148633 | 0.095181 |
from flask import Flask, request
from waitress import serve
import uuid, asyncio, json
from functools import wraps
from notifybot.task import TaskId
route_map = {}
def route(url, methods=['GET']):
def inner_decorator(f):
if url not in route_map:
route_map[url] = {}
for method in metho... | notifybot/web.py | from flask import Flask, request
from waitress import serve
import uuid, asyncio, json
from functools import wraps
from notifybot.task import TaskId
route_map = {}
def route(url, methods=['GET']):
def inner_decorator(f):
if url not in route_map:
route_map[url] = {}
for method in metho... | 0.499023 | 0.099034 |
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import numpy as np
from matplotlib import rc
rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
rc('text', usetex=True)
fig = plt.figure()
fig.... | Articleplots/Derivative_3.py | from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import numpy as np
from matplotlib import rc
rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
rc('text', usetex=True)
fig = plt.figure()
fig.... | 0.705988 | 0.642741 |
from flask import Blueprint, render_template, request, redirect, url_for, flash
from werkzeug.security import generate_password_hash, check_password_hash
from flask_login import login_user, logout_user, login_required, current_user
from .models import User
from . import db, secret_key
from itsdangerous import URLSafeTi... | app/auth.py | from flask import Blueprint, render_template, request, redirect, url_for, flash
from werkzeug.security import generate_password_hash, check_password_hash
from flask_login import login_user, logout_user, login_required, current_user
from .models import User
from . import db, secret_key
from itsdangerous import URLSafeTi... | 0.22194 | 0.041911 |
import re
from regression_tests import *
class TestBase(Test):
def assert_func_has_for_loop(self, func_name, expected_loop_header):
f = self.out_c.func(func_name, '_' + func_name)
self.assertTrue(f.has_any_for_loops())
regex = re.compile(expected_loop_header)
re.match(regex, f.for_... | features/loop-reconstruction/test.py | import re
from regression_tests import *
class TestBase(Test):
def assert_func_has_for_loop(self, func_name, expected_loop_header):
f = self.out_c.func(func_name, '_' + func_name)
self.assertTrue(f.has_any_for_loops())
regex = re.compile(expected_loop_header)
re.match(regex, f.for_... | 0.454956 | 0.367639 |
import random
import string
from django.test import TestCase
from .factories import (
KubernetesConfigMapFactory,
KubernetesContainerFactory,
KubernetesDeploymentFactory,
KubernetesJobFactory,
KubernetesNamespaceFactory,
KubernetesPodTemplateFactory,
KubernetesVolumeFactory,
Kubernetes... | kubernetes_manager/tests/test_cases.py | import random
import string
from django.test import TestCase
from .factories import (
KubernetesConfigMapFactory,
KubernetesContainerFactory,
KubernetesDeploymentFactory,
KubernetesJobFactory,
KubernetesNamespaceFactory,
KubernetesPodTemplateFactory,
KubernetesVolumeFactory,
Kubernetes... | 0.438304 | 0.278226 |
import os
import patch
from typing import Union
from cookiecutter.config import DEFAULT_CONFIG
from cookiecutter.main import cookiecutter
from ddb.action import Action
from ddb.config import config
from ddb.context import context
from ddb.event import events
class CookiecutterAction(Action):
"""
Download a ... | ddb/feature/cookiecutter/actions.py | import os
import patch
from typing import Union
from cookiecutter.config import DEFAULT_CONFIG
from cookiecutter.main import cookiecutter
from ddb.action import Action
from ddb.config import config
from ddb.context import context
from ddb.event import events
class CookiecutterAction(Action):
"""
Download a ... | 0.471467 | 0.062018 |
import re
import math
import json
from flexible_linker import *
def make_subunits(node,structure_nodes,force_nodes):
pore_radius = 2
capsule_radius = 0.8
collision_extent = 3
number = 7
center = "[5,10,3]"
axis = "[5,10,3]"
center_x, center_y, center_z = float(re.split("\s+|,|\[|]", center)[1]), float(re.spli... | bin/mechanics/make_subunits.py | import re
import math
import json
from flexible_linker import *
def make_subunits(node,structure_nodes,force_nodes):
pore_radius = 2
capsule_radius = 0.8
collision_extent = 3
number = 7
center = "[5,10,3]"
axis = "[5,10,3]"
center_x, center_y, center_z = float(re.split("\s+|,|\[|]", center)[1]), float(re.spli... | 0.293303 | 0.396068 |
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import (Column,
create_engine,
Integer,
String,
Boolean,
ForeignKey,
Date,
Large... | models.py | from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import (Column,
create_engine,
Integer,
String,
Boolean,
ForeignKey,
Date,
Large... | 0.589953 | 0.126893 |
from flask_restful import Resource
from flask import request, session, make_response
from dateutil.parser import parse
from src.controllers.channel import ChannelController
from src.controllers.auth import AuthenticationController
from src.controllers.exceptions import ChannelExistedException, ChannelNotExistException... | src/views/resources/channels.py | from flask_restful import Resource
from flask import request, session, make_response
from dateutil.parser import parse
from src.controllers.channel import ChannelController
from src.controllers.auth import AuthenticationController
from src.controllers.exceptions import ChannelExistedException, ChannelNotExistException... | 0.501709 | 0.083815 |
from textures import *
textures = Textures(os.path.join(os.path.dirname(__file__), "../textures"))
textures.load_textures()
class Button:
"""Template button class"""
def __init__(self, pos: V2i, size: V2i):
self.pos = pos
self.pos2 = pos + size
self.size = size
def posOnButton(sel... | src/button.py | from textures import *
textures = Textures(os.path.join(os.path.dirname(__file__), "../textures"))
textures.load_textures()
class Button:
"""Template button class"""
def __init__(self, pos: V2i, size: V2i):
self.pos = pos
self.pos2 = pos + size
self.size = size
def posOnButton(sel... | 0.409693 | 0.45042 |
from __future__ import annotations
import re
import pytest
from phantom.re import FullMatch
from phantom.re import Match
class MatchPatternInstance(Match, pattern=re.compile(r"abc")):
...
class MatchPatternStr(Match, pattern=r"abc"):
...
parametrize_match = pytest.mark.parametrize(
"match_type", (M... | tests/test_re.py | from __future__ import annotations
import re
import pytest
from phantom.re import FullMatch
from phantom.re import Match
class MatchPatternInstance(Match, pattern=re.compile(r"abc")):
...
class MatchPatternStr(Match, pattern=r"abc"):
...
parametrize_match = pytest.mark.parametrize(
"match_type", (M... | 0.830525 | 0.339116 |
from io import BytesIO
from parameterized import parameterized
from api.onix import ONIXExtractor
from core.classifier import Classifier
from core.metadata_layer import CirculationData
from core.model import (
Classification,
Edition,
Identifier,
LicensePool)
from core.util.datetime_helpers import dat... | tests/test_onix.py | from io import BytesIO
from parameterized import parameterized
from api.onix import ONIXExtractor
from core.classifier import Classifier
from core.metadata_layer import CirculationData
from core.model import (
Classification,
Edition,
Identifier,
LicensePool)
from core.util.datetime_helpers import dat... | 0.804175 | 0.556761 |
import glob
import os
import sys
import numpy as np
import scipy
import scipy.io
import scipy.sparse
DATA_PATH = './data'
def output(output_path, M):
np.random.seed(1)
x = np.random.normal(size=(M.shape[1],))
ans = M.dot(x)
x = list(x)
ans = list(ans)
data = list(M.data)
colidx = list(M.indices)
row... | contrib/generate_mat.py | import glob
import os
import sys
import numpy as np
import scipy
import scipy.io
import scipy.sparse
DATA_PATH = './data'
def output(output_path, M):
np.random.seed(1)
x = np.random.normal(size=(M.shape[1],))
ans = M.dot(x)
x = list(x)
ans = list(ans)
data = list(M.data)
colidx = list(M.indices)
row... | 0.067832 | 0.168617 |
import copy
from makani.control import control_types as m
import numpy as np
from scipy import interpolate
def _GenerateLookupTable(lookup_fn,
num_output_points=m.CROSSWIND_SCHEDULE_TABLE_LENGTH,
continuous=True):
lookup_x = np.linspace(0, 2 * np.pi, num_output_poi... | config/m600/control/crosswind_playbook_utils.py | import copy
from makani.control import control_types as m
import numpy as np
from scipy import interpolate
def _GenerateLookupTable(lookup_fn,
num_output_points=m.CROSSWIND_SCHEDULE_TABLE_LENGTH,
continuous=True):
lookup_x = np.linspace(0, 2 * np.pi, num_output_poi... | 0.857857 | 0.611701 |
import ntpath
import logging
import collections
from operator import itemgetter
from collections import OrderedDict
from itertools import groupby
from common import run_command
logger = logging.getLogger(name=__name__)
EXAMPLE_CASES = {
'GRCz11': [{'CHROM': '13',
'POS': '50540171',
'ID'... | src/validators/vcf_validator.py | import ntpath
import logging
import collections
from operator import itemgetter
from collections import OrderedDict
from itertools import groupby
from common import run_command
logger = logging.getLogger(name=__name__)
EXAMPLE_CASES = {
'GRCz11': [{'CHROM': '13',
'POS': '50540171',
'ID'... | 0.383295 | 0.147494 |
from datetime import datetime
from enum import Enum
import dateutil.parser
from .device import PlaatoDevice, PlaatoDeviceType
from .pins import PinsBase
from ..const import UNIT_TEMP_CELSIUS, UNIT_TEMP_FAHRENHEIT, UNIT_PERCENTAGE, \
METRIC, UNIT_OZ, UNIT_ML
class PlaatoKeg(PlaatoDevice):
"""Class for holdin... | pyplaato/models/keg.py | from datetime import datetime
from enum import Enum
import dateutil.parser
from .device import PlaatoDevice, PlaatoDeviceType
from .pins import PinsBase
from ..const import UNIT_TEMP_CELSIUS, UNIT_TEMP_FAHRENHEIT, UNIT_PERCENTAGE, \
METRIC, UNIT_OZ, UNIT_ML
class PlaatoKeg(PlaatoDevice):
"""Class for holdin... | 0.808597 | 0.164148 |
from typing import Union
from werkzeug.wrappers import Response
from flask import Blueprint, render_template, redirect, url_for, flash
from flask_login import current_user
from flask_login.utils import login_required
from ..db import db
from ..errors import flash_duplicate, flash_not_found
from ..forms import ChangeUs... | i_vis/core/routes/users.py | from typing import Union
from werkzeug.wrappers import Response
from flask import Blueprint, render_template, redirect, url_for, flash
from flask_login import current_user
from flask_login.utils import login_required
from ..db import db
from ..errors import flash_duplicate, flash_not_found
from ..forms import ChangeUs... | 0.350533 | 0.070816 |
import os
import lxml.etree
import pandas as pd
from quantlaw.utils.files import ensure_exists, list_dir
from statics import (
US_CROSSREFERENCE_LOOKUP_PATH,
US_REFERENCE_PARSED_PATH,
US_REG_CROSSREFERENCE_LOOKUP_PATH,
US_REG_REFERENCE_PARSED_PATH,
)
from utils.common import RegulationsPipelineStep
... | statutes_pipeline_steps/us_crossreference_lookup.py | import os
import lxml.etree
import pandas as pd
from quantlaw.utils.files import ensure_exists, list_dir
from statics import (
US_CROSSREFERENCE_LOOKUP_PATH,
US_REFERENCE_PARSED_PATH,
US_REG_CROSSREFERENCE_LOOKUP_PATH,
US_REG_REFERENCE_PARSED_PATH,
)
from utils.common import RegulationsPipelineStep
... | 0.446977 | 0.085786 |
import json
from LineMethod.line_creater import LineCreater
def getData():
'''
chart_data_dict = [robot_num][metric_name][x or scene_level] -> value_list
'''
data_file_path = "/home/chli/chLi/coscan_data/different_robot_num.txt"
metric_name_list = ["TC", "DC", "D-LB", "T-LB"]
metric_col_idx_l... | plot_markdown.py |
import json
from LineMethod.line_creater import LineCreater
def getData():
'''
chart_data_dict = [robot_num][metric_name][x or scene_level] -> value_list
'''
data_file_path = "/home/chli/chLi/coscan_data/different_robot_num.txt"
metric_name_list = ["TC", "DC", "D-LB", "T-LB"]
metric_col_idx_l... | 0.341912 | 0.180035 |
# Programm : code_template.py
# Version : 1.00
# SW-Stand : 20.02.2022
# Autor : Kanopus1958
# Beschreibung : Test mit mehreren Prozessen
import sys
import signal
import os
from time import sleep
from multiprocessing import Process, Pipe, Lock, \
active_children, current_process
from multiproc... | allgemein/test_prozesse.py |
# Programm : code_template.py
# Version : 1.00
# SW-Stand : 20.02.2022
# Autor : Kanopus1958
# Beschreibung : Test mit mehreren Prozessen
import sys
import signal
import os
from time import sleep
from multiprocessing import Process, Pipe, Lock, \
active_children, current_process
from multiproc... | 0.087994 | 0.167355 |
import json
import falcon
from sqlalchemy.exc import SQLAlchemyError
from db import session
import model
import util
class Unsubscribe(object):
def on_get(self, req, resp, id):
return self.on_post(req, resp, id)
def on_post(self, req, resp, id):
"""
Params:
- ?token=auth... | endpoint/unsubscribe.py | import json
import falcon
from sqlalchemy.exc import SQLAlchemyError
from db import session
import model
import util
class Unsubscribe(object):
def on_get(self, req, resp, id):
return self.on_post(req, resp, id)
def on_post(self, req, resp, id):
"""
Params:
- ?token=auth... | 0.258045 | 0.055643 |
import pathlib
import sys
from getpass import getpass
import argon2
from sqlalchemy import select, delete
rootdir = pathlib.Path(__file__).parent.parent
sys.path.append(str(rootdir))
from odp import ODPScope
from odp.db import engine, Session, Base
from odp.db.models import Scope, Role, Client, User, UserRole
ODP_A... | migrate/systemdata.py | import pathlib
import sys
from getpass import getpass
import argon2
from sqlalchemy import select, delete
rootdir = pathlib.Path(__file__).parent.parent
sys.path.append(str(rootdir))
from odp import ODPScope
from odp.db import engine, Session, Base
from odp.db.models import Scope, Role, Client, User, UserRole
ODP_A... | 0.340595 | 0.093595 |
import logging
import numpy as np
from numpy.testing import assert_array_equal
from pytest import raises
from ef.config.components import BoundaryConditionsConf
from ef.meshgrid import MeshGrid
from ef.util.array_on_grid import ArrayOnGrid
from ef.util.testing import assert_dataclass_eq
class TestMeshGrid:
def ... | tests/test_meshgrid.py | import logging
import numpy as np
from numpy.testing import assert_array_equal
from pytest import raises
from ef.config.components import BoundaryConditionsConf
from ef.meshgrid import MeshGrid
from ef.util.array_on_grid import ArrayOnGrid
from ef.util.testing import assert_dataclass_eq
class TestMeshGrid:
def ... | 0.62601 | 0.848219 |
from collections import defaultdict
import dash_html_components as html
from dash.dependencies import Input, Output, State
from ..dash_id import init_ids
from ..utility.plot_builder import *
from ..utility.table_builder import table_tabs_single_lane, cutoff_table_data_ius
from ..utility import df_manipulation as util... | application/dash_application/views/single_lane_rna.py | from collections import defaultdict
import dash_html_components as html
from dash.dependencies import Input, Output, State
from ..dash_id import init_ids
from ..utility.plot_builder import *
from ..utility.table_builder import table_tabs_single_lane, cutoff_table_data_ius
from ..utility import df_manipulation as util... | 0.651798 | 0.179351 |
from challenges.data_structure.stacks_and_queues.stacks_and_queues import *
import pytest
import unittest
''' Stack tests for '''
def test_push(stack_test):
excpected = "three\ntwo\none"
actual = f"{stack_test}"
assert excpected == actual
def test_push_to_empty():
stack = Stack()
stack.push("one... | python/tests/test_stacks_and_queues.py | from challenges.data_structure.stacks_and_queues.stacks_and_queues import *
import pytest
import unittest
''' Stack tests for '''
def test_push(stack_test):
excpected = "three\ntwo\none"
actual = f"{stack_test}"
assert excpected == actual
def test_push_to_empty():
stack = Stack()
stack.push("one... | 0.590425 | 0.754666 |
import logging
from datetime import date, datetime
from .base import BaseCanvasAPI
from .base import BaseModel
class QuizIpFiltersAPI(BaseCanvasAPI):
"""QuizIpFilters API Version 1.0."""
def __init__(self, *args, **kwargs):
"""Init method for QuizIpFiltersAPI."""
super(QuizIpFiltersAPI, self)... | py3canvas/apis/quiz_ip_filters.py | import logging
from datetime import date, datetime
from .base import BaseCanvasAPI
from .base import BaseModel
class QuizIpFiltersAPI(BaseCanvasAPI):
"""QuizIpFilters API Version 1.0."""
def __init__(self, *args, **kwargs):
"""Init method for QuizIpFiltersAPI."""
super(QuizIpFiltersAPI, self)... | 0.780412 | 0.122025 |
import logging
import random
from pylights.config import MAX_VEL, MAX_ACC, MASS_PRODUCT, WINDOW_SIZE
logger = logging.getLogger(__name__)
def sum_tuples(a, b):
return a[0] + b[0], a[1] + b[1]
def subtract_tuples(a, b):
return a[0] - b[0], a[1] - b[1]
def print_debug(func):
def decorator(*args, **kwa... | pylights/model.py | import logging
import random
from pylights.config import MAX_VEL, MAX_ACC, MASS_PRODUCT, WINDOW_SIZE
logger = logging.getLogger(__name__)
def sum_tuples(a, b):
return a[0] + b[0], a[1] + b[1]
def subtract_tuples(a, b):
return a[0] - b[0], a[1] - b[1]
def print_debug(func):
def decorator(*args, **kwa... | 0.558327 | 0.242699 |
import unittest
import requests
from requests.auth import _basic_auth_str
from termcolor import colored
class ApiTests(unittest.TestCase):
API_URL = "http://127.0.0.1:5000/"
resp=requests.post("{}/{}".format(API_URL,"login"),headers={"Authorization": _basic_auth_str("Admin", "Adminpass")})
admin_access_tok... | project/tests/tests_api.py | import unittest
import requests
from requests.auth import _basic_auth_str
from termcolor import colored
class ApiTests(unittest.TestCase):
API_URL = "http://127.0.0.1:5000/"
resp=requests.post("{}/{}".format(API_URL,"login"),headers={"Authorization": _basic_auth_str("Admin", "Adminpass")})
admin_access_tok... | 0.140395 | 0.120698 |
from idpproxy.social.openidconnect import OpenIDConnect
from oic.oauth2.message import Message
from oic.oauth2.message import SINGLE_OPTIONAL_STRING
from oic.oauth2.message import OPTIONAL_LIST_OF_SP_SEP_STRINGS
from oic.oauth2.message import SINGLE_REQUIRED_STRING
from oic.oauth2.message import SINGLE_OPTIONAL_INT
f... | src/idpproxy/social/google/__init__.py | from idpproxy.social.openidconnect import OpenIDConnect
from oic.oauth2.message import Message
from oic.oauth2.message import SINGLE_OPTIONAL_STRING
from oic.oauth2.message import OPTIONAL_LIST_OF_SP_SEP_STRINGS
from oic.oauth2.message import SINGLE_REQUIRED_STRING
from oic.oauth2.message import SINGLE_OPTIONAL_INT
f... | 0.437343 | 0.097048 |
import os
import torch
from meta_bilstm.models.char_model import CharBiLSTM
from meta_bilstm.models.word_model import WordBiLSTM
from meta_bilstm.models.meta_model import MetaBiLSTM
class ModelWrapper:
def __init__(self, params):
self.meta_model = MetaBiLSTM(**params["meta_model_params"])
self.... | src/meta_bilstm/meta_wrapper.py | import os
import torch
from meta_bilstm.models.char_model import CharBiLSTM
from meta_bilstm.models.word_model import WordBiLSTM
from meta_bilstm.models.meta_model import MetaBiLSTM
class ModelWrapper:
def __init__(self, params):
self.meta_model = MetaBiLSTM(**params["meta_model_params"])
self.... | 0.692122 | 0.093844 |
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.pylab as pl
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import rc
from matplotlib import cm
rc('font', **{'family': 'sans-serif', 'sans-serif': ['Helvetica']})
rc('text', usetex=True)
class graph_defaults:
def __init__(self, x, t, ... | pySpectralPDE/stochastic/grapher.py | import numpy as np
import matplotlib.pyplot as plt
import matplotlib.pylab as pl
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import rc
from matplotlib import cm
rc('font', **{'family': 'sans-serif', 'sans-serif': ['Helvetica']})
rc('text', usetex=True)
class graph_defaults:
def __init__(self, x, t, ... | 0.823754 | 0.722662 |
# Python imports
from __future__ import division, print_function
import collections
import os
import time
# Enstore imports
import dbaccess
import enstore_constants
import enstore_plotter_module
import histogram
WEB_SUB_DIRECTORY = enstore_constants.FILES_RW_SEP_PLOTS_SUBDIR
"""Subdirectory in which to write plots. T... | src/files_rw_sep_plotter_module.py | # Python imports
from __future__ import division, print_function
import collections
import os
import time
# Enstore imports
import dbaccess
import enstore_constants
import enstore_plotter_module
import histogram
WEB_SUB_DIRECTORY = enstore_constants.FILES_RW_SEP_PLOTS_SUBDIR
"""Subdirectory in which to write plots. T... | 0.804291 | 0.144783 |
import requests, re, smtplib, time
from bs4 import BeautifulSoup
import pandas as pd
from itertools import zip_longest
from email.message import EmailMessage
#Part 1: Gather the information
#Get the trivia questions
url = 'https://www.opinionstage.com/blog/trivia-questions/'
html_text = requests.get(url).text
... | Trivia_Practice.py |
import requests, re, smtplib, time
from bs4 import BeautifulSoup
import pandas as pd
from itertools import zip_longest
from email.message import EmailMessage
#Part 1: Gather the information
#Get the trivia questions
url = 'https://www.opinionstage.com/blog/trivia-questions/'
html_text = requests.get(url).text
... | 0.185652 | 0.212702 |
import math
import numpy
def getMRTBatch(x, xmask, y, ymask, config, model, data):
'''
Get a batch for MRT training
:type x: numpy array
:param x: the indexed source sentence
:type xmask: numpy array
:param xmask: indicate the length of each sequence in source sequence
:type y: numpy array
:param y:... | thumt/mrt_utils.py | import math
import numpy
def getMRTBatch(x, xmask, y, ymask, config, model, data):
'''
Get a batch for MRT training
:type x: numpy array
:param x: the indexed source sentence
:type xmask: numpy array
:param xmask: indicate the length of each sequence in source sequence
:type y: numpy array
:param y:... | 0.306112 | 0.651632 |
################################# %% initial step
# imports
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import time
from pylab import rcParams
from datetime import datetime, timedelta
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_tes... | Code_Workbook/LSTM_Net.py | ################################# %% initial step
# imports
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import time
from pylab import rcParams
from datetime import datetime, timedelta
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_tes... | 0.197561 | 0.18188 |
from datetime import datetime
from thelma.tools.parsers.base import TxtFileParser
from thelma.utils import as_utc_time
__docformat__ = "reStructuredText en"
__all__ = ['RackScanningParser']
class RackScanningParser(TxtFileParser):
"""
Parses a rack scanning output file.
"""
NAME = 'Rack Scanning Out... | thelma/tools/parsers/rackscanning.py | from datetime import datetime
from thelma.tools.parsers.base import TxtFileParser
from thelma.utils import as_utc_time
__docformat__ = "reStructuredText en"
__all__ = ['RackScanningParser']
class RackScanningParser(TxtFileParser):
"""
Parses a rack scanning output file.
"""
NAME = 'Rack Scanning Out... | 0.574634 | 0.192217 |
import logging
import time
from tasks import ceph_manager
from tasks.util.rados import rados
from teuthology import misc as teuthology
from teuthology.orchestra import run
log = logging.getLogger(__name__)
def task(ctx, config):
"""
Test handling of lost objects on an ec pool.
A pretty rigid cluster is b... | qa/tasks/ec_lost_unfound.py | import logging
import time
from tasks import ceph_manager
from tasks.util.rados import rados
from teuthology import misc as teuthology
from teuthology.orchestra import run
log = logging.getLogger(__name__)
def task(ctx, config):
"""
Test handling of lost objects on an ec pool.
A pretty rigid cluster is b... | 0.346762 | 0.213357 |
import bs4
import re
import requests
import time
import calendar
class CustomError(Exception):
pass
def get_bs4(html: str) -> bs4.BeautifulSoup:
return bs4.BeautifulSoup(html, 'html.parser')
def get_shops(soup: bs4.BeautifulSoup) -> list:
return soup.find_all('div', class_='shop-result')
def get_sho... | DeerIO/__init__.py | import bs4
import re
import requests
import time
import calendar
class CustomError(Exception):
pass
def get_bs4(html: str) -> bs4.BeautifulSoup:
return bs4.BeautifulSoup(html, 'html.parser')
def get_shops(soup: bs4.BeautifulSoup) -> list:
return soup.find_all('div', class_='shop-result')
def get_sho... | 0.47244 | 0.149904 |
import os
from collections import defaultdict
from typing import Dict, List, Any
import numpy as np
from matplotlib.figure import Figure
from numpy import ndarray
from sacred.run import Run
class SacredAggregatedMetrics:
"""Collects metrics over a series of experiments. Logs the complete metrics, and the mean to... | safe_exploration/utils_sacred.py | import os
from collections import defaultdict
from typing import Dict, List, Any
import numpy as np
from matplotlib.figure import Figure
from numpy import ndarray
from sacred.run import Run
class SacredAggregatedMetrics:
"""Collects metrics over a series of experiments. Logs the complete metrics, and the mean to... | 0.88361 | 0.335814 |
import argparse
from collections import OrderedDict
import datetime
import gc
import glob
import os
import sys
import time
from functools import wraps
from catbridge_tools.isbn_tools import *
from catbridge_tools.logs import *
ARGS = {
'i': lambda parser: parser.add_argument('-i', metavar='<input_file... | catbridge_tools/functions.py | import argparse
from collections import OrderedDict
import datetime
import gc
import glob
import os
import sys
import time
from functools import wraps
from catbridge_tools.isbn_tools import *
from catbridge_tools.logs import *
ARGS = {
'i': lambda parser: parser.add_argument('-i', metavar='<input_file... | 0.326486 | 0.065336 |
import numpy as np
import os
DATASET_PATH = '/home/pkushi/dataset'
class Data_2d4s1c:
def __init__(self, datapath = DATASET_PATH):
self.tremor_path = datapath + '/tremors'
self.event_path = datapath + '/events'
self.noise_path = datapath + '/noise'
self.tremor_num = len(os.listdir... | run/get_train_data.py | import numpy as np
import os
DATASET_PATH = '/home/pkushi/dataset'
class Data_2d4s1c:
def __init__(self, datapath = DATASET_PATH):
self.tremor_path = datapath + '/tremors'
self.event_path = datapath + '/events'
self.noise_path = datapath + '/noise'
self.tremor_num = len(os.listdir... | 0.223377 | 0.390854 |
from django.conf.urls import include, url
from rest_framework import routers
from galaxy.api import views
router = routers.DefaultRouter()
router.register('v1/search/roles', views.RoleSearchView,
base_name="search-roles")
user_urls = [
url(r'^$', views.UserList.as_view(), name='user_list'),
... | galaxy/api/urls.py |
from django.conf.urls import include, url
from rest_framework import routers
from galaxy.api import views
router = routers.DefaultRouter()
router.register('v1/search/roles', views.RoleSearchView,
base_name="search-roles")
user_urls = [
url(r'^$', views.UserList.as_view(), name='user_list'),
... | 0.276886 | 0.060004 |
import sys
import re
class FastaDB:
def __init__(self):
pass
def makeIndex(self):
self.index = {}
curseq = "";
offset = 0;
for line in self.file:
offset += len(line)
line_match = re.match("^>(\S+)\s+(.+)",line)
if(li... | Scripts/fasta_subseq.py | import sys
import re
class FastaDB:
def __init__(self):
pass
def makeIndex(self):
self.index = {}
curseq = "";
offset = 0;
for line in self.file:
offset += len(line)
line_match = re.match("^>(\S+)\s+(.+)",line)
if(li... | 0.193109 | 0.167797 |
import unittest
import numpy as np
from . import plot
import funcsfa
class TestInvalidInputs(unittest.TestCase):
def setUp(self):
self.rand = np.random.RandomState(1968486074)
self.n_factors = 9
self.f = funcsfa.SFA()
self.n_samples = 221
self.n_features = 37
sel... | test/test_sfa.py | import unittest
import numpy as np
from . import plot
import funcsfa
class TestInvalidInputs(unittest.TestCase):
def setUp(self):
self.rand = np.random.RandomState(1968486074)
self.n_factors = 9
self.f = funcsfa.SFA()
self.n_samples = 221
self.n_features = 37
sel... | 0.560132 | 0.568715 |
import re
from .united_states import US_STATES_CODES
fr_regions = {
# New region names first (2018)
"auvergne rhone alpes": "84", # chef lieu: Lyon
"bourgogne franche comte": "27", # chef lieu: Dijon
"centre val de loire": "24", # chef lieu: Orleans
"grand est": "44", # chef lieu: strasbourg
... | geoconvert/data/subdivisions/france.py | import re
from .united_states import US_STATES_CODES
fr_regions = {
# New region names first (2018)
"auvergne rhone alpes": "84", # chef lieu: Lyon
"bourgogne franche comte": "27", # chef lieu: Dijon
"centre val de loire": "24", # chef lieu: Orleans
"grand est": "44", # chef lieu: strasbourg
... | 0.319971 | 0.482124 |
import tensorflow as tf
from . import defaults
from . import normalization
def _ln(inputs, epsilon=1e-8, scope="ln"):
"""Applies layer normalization. See https://arxiv.org/abs/1607.06450.
inputs: A tensor with 2 or more dimensions, where the first dimension has `batch_size`.
epsilon: A floating number. A... | module/projector.py | import tensorflow as tf
from . import defaults
from . import normalization
def _ln(inputs, epsilon=1e-8, scope="ln"):
"""Applies layer normalization. See https://arxiv.org/abs/1607.06450.
inputs: A tensor with 2 or more dimensions, where the first dimension has `batch_size`.
epsilon: A floating number. A... | 0.921592 | 0.461745 |
import numpy as np
ar1 = np.array([1, 2, 3])
# ar2 = np.array([[4, 6, 1], [2, 3, 5, 6], [5, 3, 4, 1]]) # VisibleDeprecationWarning: Creating an ndarray from ragged
# nested sequences
ar3 = np.array([[4, 6, 1, 3], [2, 3, 5, 6], [5, 3, 4, 1]], dtype='int64')
print(ar3)
# Get Dimension
print(ar3.ndim)
# Get Shape - ... | Numpy_Basics.py | import numpy as np
ar1 = np.array([1, 2, 3])
# ar2 = np.array([[4, 6, 1], [2, 3, 5, 6], [5, 3, 4, 1]]) # VisibleDeprecationWarning: Creating an ndarray from ragged
# nested sequences
ar3 = np.array([[4, 6, 1, 3], [2, 3, 5, 6], [5, 3, 4, 1]], dtype='int64')
print(ar3)
# Get Dimension
print(ar3.ndim)
# Get Shape - ... | 0.607547 | 0.658253 |
import unittest
import requests_mock
from podman import PodmanClient, tests
from podman.domain.networks import Network
from podman.domain.networks_manager import NetworksManager
FIRST_NETWORK = {
"Name": "podman",
"Id": "2f259bab93aaaaa2542ba43ef33eb990d0999ee1b9924b557b7be53c0b7a1bb9",
"Created": "2021-... | podman/tests/unit/test_network.py | import unittest
import requests_mock
from podman import PodmanClient, tests
from podman.domain.networks import Network
from podman.domain.networks_manager import NetworksManager
FIRST_NETWORK = {
"Name": "podman",
"Id": "2f259bab93aaaaa2542ba43ef33eb990d0999ee1b9924b557b7be53c0b7a1bb9",
"Created": "2021-... | 0.478773 | 0.448547 |
import functools
from ignite.engine import Events
import torch
import torch.nn as nn
import torch.optim as optim
from .checkpointer import ModelAndMonitorCheckpointer
from .constraints import helmholtz_equation, pythagorean_equation
from .dataloader import get_multiwave_dataloaders
from .event_loop import create_engin... | experiments/A_constrained_training/main.py | import functools
from ignite.engine import Events
import torch
import torch.nn as nn
import torch.optim as optim
from .checkpointer import ModelAndMonitorCheckpointer
from .constraints import helmholtz_equation, pythagorean_equation
from .dataloader import get_multiwave_dataloaders
from .event_loop import create_engin... | 0.884937 | 0.37419 |
import sys, os
from Config import Configuration
from .DataLoaderClass import DataLoader
class RasaManager(DataLoader):
'''
This class is used to query the relative asa of the residues
'''
RASA_FEAT_DESCR= ("psaia", ("structStep/PSAIA/procPSAIA", [8]))
def __init__(self, dataRootPath=None, verbose=False... | codifyComplexes/codifyProtocols/RasaManager.py | import sys, os
from Config import Configuration
from .DataLoaderClass import DataLoader
class RasaManager(DataLoader):
'''
This class is used to query the relative asa of the residues
'''
RASA_FEAT_DESCR= ("psaia", ("structStep/PSAIA/procPSAIA", [8]))
def __init__(self, dataRootPath=None, verbose=False... | 0.259169 | 0.192141 |
import tensorflow as tf
from tensorflow.keras import Model
import nalp.utils.logging as l
logger = l.get_logger(__name__)
class Discriminator(Model):
"""A Discriminator class is responsible for easily-implementing the discriminative part of
a neural network, when custom training or additional sets are not n... | libraries/nalp/nalp/core/model.py | import tensorflow as tf
from tensorflow.keras import Model
import nalp.utils.logging as l
logger = l.get_logger(__name__)
class Discriminator(Model):
"""A Discriminator class is responsible for easily-implementing the discriminative part of
a neural network, when custom training or additional sets are not n... | 0.964772 | 0.588209 |
import json
from azext_iot.common.utility import process_json_arg, scantree, unpack_msrest_error
from azext_iot.digitaltwins.providers.base import DigitalTwinsProvider
from azext_iot.sdk.digitaltwins.dataplane.models import ErrorResponseException
from knack.log import get_logger
from knack.util import CLIError
logger... | azext_iot/digitaltwins/providers/model.py |
import json
from azext_iot.common.utility import process_json_arg, scantree, unpack_msrest_error
from azext_iot.digitaltwins.providers.base import DigitalTwinsProvider
from azext_iot.sdk.digitaltwins.dataplane.models import ErrorResponseException
from knack.log import get_logger
from knack.util import CLIError
logger... | 0.49292 | 0.121399 |
import sys
import math
from FASTA import FASTA
from WaveletTree import WaveletTree
import Utils
def report_3(read_stopwatch, build_stopwatch, select_avg_time, rank_avg_time, access_avg_time):
report_2(read_stopwatch, build_stopwatch)
rank_file = open('rank.out', 'w')
rank_file.write(str(rank_avg_time))
... | python/src/Tester.py | import sys
import math
from FASTA import FASTA
from WaveletTree import WaveletTree
import Utils
def report_3(read_stopwatch, build_stopwatch, select_avg_time, rank_avg_time, access_avg_time):
report_2(read_stopwatch, build_stopwatch)
rank_file = open('rank.out', 'w')
rank_file.write(str(rank_avg_time))
... | 0.229881 | 0.19925 |
from sklearn.ensemble import BaggingClassifier, AdaBoostClassifier,GradientBoostingClassifier, RandomForestClassifier
from sklearn.linear_model import LogisticRegression, RidgeClassifier
from sklearn.svm import SVC
# used for normalization
from sklearn.preprocessing import StandardScaler
from sklearn.preprocessing impo... | miopy/classification.py | from sklearn.ensemble import BaggingClassifier, AdaBoostClassifier,GradientBoostingClassifier, RandomForestClassifier
from sklearn.linear_model import LogisticRegression, RidgeClassifier
from sklearn.svm import SVC
# used for normalization
from sklearn.preprocessing import StandardScaler
from sklearn.preprocessing impo... | 0.499756 | 0.522872 |
import tensorflow as tf
import numpy as np
import os
from dataset_creation.image_transformations.patching import tf_create_patches
def read_image(filename, directory='', channels=3):
"""
read image,
can be applied/mapped to tf.data.Dataset!
:param filename: string of image to be read
:param direc... | dataset_creation/dataset_processing.py | import tensorflow as tf
import numpy as np
import os
from dataset_creation.image_transformations.patching import tf_create_patches
def read_image(filename, directory='', channels=3):
"""
read image,
can be applied/mapped to tf.data.Dataset!
:param filename: string of image to be read
:param direc... | 0.813387 | 0.482246 |
from base import APMCollectorBase
import subprocess
# TODO test device correctness?
class LinuxAPMCollector(APMCollectorBase):
def __init__(self, key_xinput_devices, mouse_xinput_devices, dedup=True):
""" currently only use one device"""
# TODO monitor multiple device at the same time
supe... | apml-client/collector/linux.py |
from base import APMCollectorBase
import subprocess
# TODO test device correctness?
class LinuxAPMCollector(APMCollectorBase):
def __init__(self, key_xinput_devices, mouse_xinput_devices, dedup=True):
""" currently only use one device"""
# TODO monitor multiple device at the same time
supe... | 0.170646 | 0.132038 |
from helper import *
from joblib import Parallel, delayed
import requests, re
######################### Dump Ground Truth in required format for evaluation
def groundtruth_dump(doc_list):
base_dir = './results/{}'.format(args.data); make_dir(base_dir)
fname = './results/{}/ground_{}.txt'.format(args.data, args.sp... | medtype-trainer/dump_linkers_output.py | from helper import *
from joblib import Parallel, delayed
import requests, re
######################### Dump Ground Truth in required format for evaluation
def groundtruth_dump(doc_list):
base_dir = './results/{}'.format(args.data); make_dir(base_dir)
fname = './results/{}/ground_{}.txt'.format(args.data, args.sp... | 0.115711 | 0.154121 |
import re # noqa: F401
import sys # noqa: F401
from h1.api_client import ApiClient, Endpoint as _Endpoint
from h1.model_utils import ( # noqa: F401
check_allowed_values,
check_validations,
date,
datetime,
file_type,
none_type,
validate_and_convert_types
)
from h1.model.agent import Agent... | h1/api/provider_project_agent_api.py | import re # noqa: F401
import sys # noqa: F401
from h1.api_client import ApiClient, Endpoint as _Endpoint
from h1.model_utils import ( # noqa: F401
check_allowed_values,
check_validations,
date,
datetime,
file_type,
none_type,
validate_and_convert_types
)
from h1.model.agent import Agent... | 0.581303 | 0.070113 |
from httpx import URL
from httpx.exceptions import InvalidURL
import pytest
def test_idna_url():
url = URL("http://中国.icom.museum:80/")
assert url == URL("http://xn--fiqs8s.icom.museum:80/")
assert url.host == "xn--fiqs8s.icom.museum"
def test_url():
url = URL("https://example.org:123/path/to/somewh... | tests/models/test_url.py | from httpx import URL
from httpx.exceptions import InvalidURL
import pytest
def test_idna_url():
url = URL("http://中国.icom.museum:80/")
assert url == URL("http://xn--fiqs8s.icom.museum:80/")
assert url.host == "xn--fiqs8s.icom.museum"
def test_url():
url = URL("https://example.org:123/path/to/somewh... | 0.476823 | 0.452113 |