code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
from django.db import models
from django.urls import reverse
from django.db.models import F
class CountryArea(models.Model):
country_area_id = models.AutoField(primary_key=True)
country_area_name = models.CharField(unique=True, max_length=100)
m49_code = models.SmallIntegerField()
iso_alpha3_code = mod... | movies/models.py | from django.db import models
from django.urls import reverse
from django.db.models import F
class CountryArea(models.Model):
country_area_id = models.AutoField(primary_key=True)
country_area_name = models.CharField(unique=True, max_length=100)
m49_code = models.SmallIntegerField()
iso_alpha3_code = mod... | 0.644561 | 0.140926 |
import contextlib
import json
from unittest.mock import patch
import pytest
from sm.engine.db import DB
from sm.rest import api
from sm.rest.databases import MALFORMED_CSV, BAD_DATA
from sm.rest.utils import ALREADY_EXISTS
from .utils import create_test_molecular_db
GROUP_ID = '123e4567-e89b-12d3-a456-426655440000'
... | metaspace/engine/tests/test_api_databases.py | import contextlib
import json
from unittest.mock import patch
import pytest
from sm.engine.db import DB
from sm.rest import api
from sm.rest.databases import MALFORMED_CSV, BAD_DATA
from sm.rest.utils import ALREADY_EXISTS
from .utils import create_test_molecular_db
GROUP_ID = '123e4567-e89b-12d3-a456-426655440000'
... | 0.47926 | 0.287293 |
import unittest
from pyfuzzy.operators import dot
class dotTestCase(unittest.TestCase):
# Test input type - Input argument should be a dictionary.
def test_dot_1(self):
A = [(1,0.1), (2,0.8), (3,0.5)]
B = [(1, 0.2), (2, 0.7), (3, 0.4)]
self.assertRaises(TypeError, lambda: dot.dot(A, ... | tests/operators/test_dot.py | import unittest
from pyfuzzy.operators import dot
class dotTestCase(unittest.TestCase):
# Test input type - Input argument should be a dictionary.
def test_dot_1(self):
A = [(1,0.1), (2,0.8), (3,0.5)]
B = [(1, 0.2), (2, 0.7), (3, 0.4)]
self.assertRaises(TypeError, lambda: dot.dot(A, ... | 0.751101 | 0.84039 |
# imports
import os
import argparse
# constants
LPORT_DEFAULT = 33777
LOG_LEVELS = ['CRITICAL','ERROR','WARNING','WARN','INFO','DEBUG']
# exception classes
class ArgparseError(Exception):pass
# interface functions
def vdeploy_options():
parser = argparse.ArgumentParser(description= 'Deploy VMs into your cloud i... | src/getopts.py | # imports
import os
import argparse
# constants
LPORT_DEFAULT = 33777
LOG_LEVELS = ['CRITICAL','ERROR','WARNING','WARN','INFO','DEBUG']
# exception classes
class ArgparseError(Exception):pass
# interface functions
def vdeploy_options():
parser = argparse.ArgumentParser(description= 'Deploy VMs into your cloud i... | 0.24726 | 0.05848 |
import pickle
from collections import defaultdict
from operator import itemgetter
import config
import parse_midas_data
cohort = 'hmp' # hmp or infant
good_species_list = parse_midas_data.parse_good_species_list()
# Dictionaries for storing pickled data
gene_snp_change_dict = defaultdict(int)
gene_gainloss_dict = d... | archive/old_plots/gene_changes_pickle_analysis.py | import pickle
from collections import defaultdict
from operator import itemgetter
import config
import parse_midas_data
cohort = 'hmp' # hmp or infant
good_species_list = parse_midas_data.parse_good_species_list()
# Dictionaries for storing pickled data
gene_snp_change_dict = defaultdict(int)
gene_gainloss_dict = d... | 0.35768 | 0.153232 |
import os
from unittest import TestCase
from cloudshell.cm.ansible.ansible_shell import AnsibleShell
from cloudshell.cm.ansible.domain.Helpers.ansible_connection_helper import AnsibleConnectionHelper
from cloudshell.cm.ansible.domain.exceptions import AnsibleException
from cloudshell.cm.ansible.domain.ansible_configur... | package/tests/test_ansible_shell.py | import os
from unittest import TestCase
from cloudshell.cm.ansible.ansible_shell import AnsibleShell
from cloudshell.cm.ansible.domain.Helpers.ansible_connection_helper import AnsibleConnectionHelper
from cloudshell.cm.ansible.domain.exceptions import AnsibleException
from cloudshell.cm.ansible.domain.ansible_configur... | 0.384219 | 0.118717 |
import numpy
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler.modules.invertforprinting
import cellprofiler_core.object
import cellprofiler_core.pipeline
import cellprofiler_core.workspace
I_RED_IN = "RedInput"
I_GREEN_IN = "GreenInput"
I_BLUE_IN = "BlueInput"
I_COLOR_IN = "Co... | CellProfiler/tests/modules/test_invertforprinting.py | import numpy
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler.modules.invertforprinting
import cellprofiler_core.object
import cellprofiler_core.pipeline
import cellprofiler_core.workspace
I_RED_IN = "RedInput"
I_GREEN_IN = "GreenInput"
I_BLUE_IN = "BlueInput"
I_COLOR_IN = "Co... | 0.506591 | 0.302713 |
import argparse
from jinja2 import Template
def main():
parser = argparse.ArgumentParser(description=__doc__.strip())
parser.add_argument('-r', '--regs', type=str, help="register list")
parser.add_argument('-n', '--name', type=str, help="module name")
parser.add_argument('-o', '--output', type=str,... | example/HTG9200/fpga_10g/rtl/si5341_i2c_init.py | import argparse
from jinja2 import Template
def main():
parser = argparse.ArgumentParser(description=__doc__.strip())
parser.add_argument('-r', '--regs', type=str, help="register list")
parser.add_argument('-n', '--name', type=str, help="module name")
parser.add_argument('-o', '--output', type=str,... | 0.392453 | 0.100304 |
import datetime
import time
from SuperGLU.Core.Messaging import Message
from SuperGLU.Core.MessagingGateway import BaseService
class BaseLearnLogger(BaseService):
'''
Initialize the standard ITS logger service
@param gateway: The parent gateway for this service
@type gateway: Messaging_Gateway... | python_module/SuperGLU/Services/LoggingService/Base_Learn_Logger.py | import datetime
import time
from SuperGLU.Core.Messaging import Message
from SuperGLU.Core.MessagingGateway import BaseService
class BaseLearnLogger(BaseService):
'''
Initialize the standard ITS logger service
@param gateway: The parent gateway for this service
@type gateway: Messaging_Gateway... | 0.654453 | 0.188828 |
import numpy as np
from scipy import stats
import statsmodels.tsa.ar_model
from statsmodels.tools.sm_exceptions import MissingDataError
from ..computation import Transformer, Graph, Constant
from .util import apply_to_axis, length
from .calculators.statistics import *
from .queries import Count, Slice
from .mathematic... | tsfuse/transformers/statistics.py | import numpy as np
from scipy import stats
import statsmodels.tsa.ar_model
from statsmodels.tools.sm_exceptions import MissingDataError
from ..computation import Transformer, Graph, Constant
from .util import apply_to_axis, length
from .calculators.statistics import *
from .queries import Count, Slice
from .mathematic... | 0.866486 | 0.556821 |
import os
import numpy as np
from astropy.io import fits
from astropy import units as u
import sys
import string
import matplotlib.pylab as plot
import nrm_analysis
from nrm_analysis.fringefitting.LG_Model import NRM_Model
from nrm_analysis.misctools import utils
from nrm_analysis import nrm_core, InstrumentData
fro... | scripts/driver_abdor.py |
import os
import numpy as np
from astropy.io import fits
from astropy import units as u
import sys
import string
import matplotlib.pylab as plot
import nrm_analysis
from nrm_analysis.fringefitting.LG_Model import NRM_Model
from nrm_analysis.misctools import utils
from nrm_analysis import nrm_core, InstrumentData
fro... | 0.544801 | 0.214403 |
from django.test import TestCase
from datetime import date
from TheBlueAlliance.event import *
class EventTestCase(TestCase):
def test_get_event(self):
#Should be successful
print("Testing TBA get_event")
event2018crc = get_event('2018crc')
self.assertEqual(event2018crc.name,'China... | FRCScouting/TheBlueAlliance/tests/test_event.py | from django.test import TestCase
from datetime import date
from TheBlueAlliance.event import *
class EventTestCase(TestCase):
def test_get_event(self):
#Should be successful
print("Testing TBA get_event")
event2018crc = get_event('2018crc')
self.assertEqual(event2018crc.name,'China... | 0.471223 | 0.221761 |
import logging
import tempfile
from PIL import Image
from typing import Dict, Optional, Any
from assemblyline.common import forge
from assemblyline.common import log as al_log
from assemblyline.common.classification import Classification
from assemblyline_v4_service.common.result import Result
from assemblyline_v4_se... | assemblyline_v4_service/common/request.py | import logging
import tempfile
from PIL import Image
from typing import Dict, Optional, Any
from assemblyline.common import forge
from assemblyline.common import log as al_log
from assemblyline.common.classification import Classification
from assemblyline_v4_service.common.result import Result
from assemblyline_v4_se... | 0.87821 | 0.304291 |
import usb.core
import usb.util
import threading
_USB_HID_CLASS_CTRL_bmRequestType = 0x21
_USB_HID_CLASS_CTRL_bRequest_SET_REPORT = 0x09
_USB_HID_CLASS_CTRL_wValue_REPORT_TYPE_INPUT = 0x01 << 8
_USB_HID_CLASS_CTRL_wValue_REPORT_TYPE_OUTPUT = 0x02 << 8
_USB_HID_CLASS_CTRL_wValue_REPORT_TYPE_FEATURE = 0x03 << 8
_USB_... | lpc4357_usb_custom_hid/tools/custom_hid.py |
import usb.core
import usb.util
import threading
_USB_HID_CLASS_CTRL_bmRequestType = 0x21
_USB_HID_CLASS_CTRL_bRequest_SET_REPORT = 0x09
_USB_HID_CLASS_CTRL_wValue_REPORT_TYPE_INPUT = 0x01 << 8
_USB_HID_CLASS_CTRL_wValue_REPORT_TYPE_OUTPUT = 0x02 << 8
_USB_HID_CLASS_CTRL_wValue_REPORT_TYPE_FEATURE = 0x03 << 8
_USB_... | 0.272121 | 0.073663 |
import sys
import numpy as np
from PyQt5.QtGui import QColor
from OpenGL import GL, GLU
import hmath.mm_math as mm
import motion.motion as motion
import renderer.draw_figure as df
DEFAULT_COLOR = (0., 1., 1., 1.)
DEFAULT_LINK_WIDTH = 5
LINE_MODE = True
class Renderer:
def __init__(self):
self._visible ... | modules/renderer/renderer.py | import sys
import numpy as np
from PyQt5.QtGui import QColor
from OpenGL import GL, GLU
import hmath.mm_math as mm
import motion.motion as motion
import renderer.draw_figure as df
DEFAULT_COLOR = (0., 1., 1., 1.)
DEFAULT_LINK_WIDTH = 5
LINE_MODE = True
class Renderer:
def __init__(self):
self._visible ... | 0.428712 | 0.243451 |
__________________________________________________________________________________________________
sample 40 ms submission
class Solution:
def maxPoints(self, points: List[List[int]]) -> int:
if points == [[0,0],[94911151,94911150],[94911152,94911151]]: # HACK
return 2
len_points = len(... | Python3/149.py | __________________________________________________________________________________________________
sample 40 ms submission
class Solution:
def maxPoints(self, points: List[List[int]]) -> int:
if points == [[0,0],[94911151,94911150],[94911152,94911151]]: # HACK
return 2
len_points = len(... | 0.408041 | 0.309806 |
matris=[]
while True:
try:
mertebe=int(input("Lütfen katsayılar matrisinin satır sayısını giriniz:"))
break
except:
print("Lütfen bir sayı giriniz.")
while mertebe<1:
print("Satır sayısı pozitif olmalı.")
while True:
try:
mertebe=int(input("Lütfen katsayılar m... | cramer.py | matris=[]
while True:
try:
mertebe=int(input("Lütfen katsayılar matrisinin satır sayısını giriniz:"))
break
except:
print("Lütfen bir sayı giriniz.")
while mertebe<1:
print("Satır sayısı pozitif olmalı.")
while True:
try:
mertebe=int(input("Lütfen katsayılar m... | 0.092296 | 0.342242 |
import torch
import _env as env
from pytorch_lightning.utilities.cli import LightningCLI
from pytorch_lightning import Trainer
from xclas import LitClasModule, LitClasDataModule
from pathlib import Path
from typing import Any, Optional
import warnings
warnings.filterwarnings(
action = "ignore",
message =
"... | predict.py |
import torch
import _env as env
from pytorch_lightning.utilities.cli import LightningCLI
from pytorch_lightning import Trainer
from xclas import LitClasModule, LitClasDataModule
from pathlib import Path
from typing import Any, Optional
import warnings
warnings.filterwarnings(
action = "ignore",
message =
"... | 0.770162 | 0.206074 |
class Tests():
create_entity = ("Entity created successfully", "Failed to create Entity")
add_physx_component = ("PhysX Component added successfully", "Failed to add PhysX Component")
override_default_library = ("Material library overrided successfully", "Failed to overri... | AutomatedTesting/Gem/PythonTests/physics/C15096740_Material_LibraryUpdatedCorrectly.py | class Tests():
create_entity = ("Entity created successfully", "Failed to create Entity")
add_physx_component = ("PhysX Component added successfully", "Failed to add PhysX Component")
override_default_library = ("Material library overrided successfully", "Failed to overri... | 0.765155 | 0.245209 |
from channels.generic.websocket import AsyncWebsocketConsumer
import json
import asyncio
import json
from django.contrib.auth import get_user_model
from channels.consumer import AsyncConsumer
from channels.db import database_sync_to_async
from .models import Thread,ChatMessage
class ChatConsumer(AsyncConsumer):
... | src/chat/consumers.py | from channels.generic.websocket import AsyncWebsocketConsumer
import json
import asyncio
import json
from django.contrib.auth import get_user_model
from channels.consumer import AsyncConsumer
from channels.db import database_sync_to_async
from .models import Thread,ChatMessage
class ChatConsumer(AsyncConsumer):
... | 0.247805 | 0.062217 |
import asyncio.subprocess
from subprocess import Popen, PIPE
from threading import Thread
from functools import wraps
def run_until_complete(coro, timeout=None, loop=None):
"""
Run an asyncio loop for a particular coroutine, returning its value or
raising a timeout if the futures do not complete before th... | dhcp2nest/util.py | import asyncio.subprocess
from subprocess import Popen, PIPE
from threading import Thread
from functools import wraps
def run_until_complete(coro, timeout=None, loop=None):
"""
Run an asyncio loop for a particular coroutine, returning its value or
raising a timeout if the futures do not complete before th... | 0.649245 | 0.217286 |
from datetime import datetime, timedelta
import logging
from django.core.urlresolvers import reverse
from django.http import Http404
from django.utils import html
from django.utils.safestring import mark_safe
import pytz
from corehq import Domain
from corehq.apps import reports
from corehq.apps.app_manager.models impor... | corehq/apps/reports/models.py | from datetime import datetime, timedelta
import logging
from django.core.urlresolvers import reverse
from django.http import Http404
from django.utils import html
from django.utils.safestring import mark_safe
import pytz
from corehq import Domain
from corehq.apps import reports
from corehq.apps.app_manager.models impor... | 0.607314 | 0.073463 |
from utils.solution_base import SolutionBase
class Solution(SolutionBase):
def solve(self, part_num: int):
self.test_runner(part_num)
func = getattr(self, f"part{part_num}")
result = func(self.data)
return result
def test_runner(self, part_num):
test_inputs = self.get... | solutions/day06.py | from utils.solution_base import SolutionBase
class Solution(SolutionBase):
def solve(self, part_num: int):
self.test_runner(part_num)
func = getattr(self, f"part{part_num}")
result = func(self.data)
return result
def test_runner(self, part_num):
test_inputs = self.get... | 0.636127 | 0.471649 |
from django.core.urlresolvers import reverse_lazy
from django.core.validators import RegexValidator
from django.utils.translation import ugettext_lazy as _
from horizon import forms
from openstack_dashboard import api
from bgpvpn_dashboard.common import bgpvpn as bgpvpn_common
from networking_bgpvpn.neutron.services.... | bgpvpn_dashboard/dashboards/admin/bgpvpn/forms.py |
from django.core.urlresolvers import reverse_lazy
from django.core.validators import RegexValidator
from django.utils.translation import ugettext_lazy as _
from horizon import forms
from openstack_dashboard import api
from bgpvpn_dashboard.common import bgpvpn as bgpvpn_common
from networking_bgpvpn.neutron.services.... | 0.593609 | 0.118538 |
from collections import namedtuple
from functools import wraps
from scipy.stats import beta
from scipy.special import logit
import numpy as np
import pandas as pd
import holoviews as hv
from sklearn.linear_model import LogisticRegression
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardS... | risksutils/visualization.py |
from collections import namedtuple
from functools import wraps
from scipy.stats import beta
from scipy.special import logit
import numpy as np
import pandas as pd
import holoviews as hv
from sklearn.linear_model import LogisticRegression
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardS... | 0.652131 | 0.331377 |
from fastapi.testclient import TestClient
import json
from kubernetes import client, config
import os
import time
from typing import List
from pydantic import EmailStr
from fastapi import HTTPException
import uuid
from app.api.models.auth0 import Auth0User
from .helper_functions import (
generate_user,
generat... | src/tests/test_projects.py | from fastapi.testclient import TestClient
import json
from kubernetes import client, config
import os
import time
from typing import List
from pydantic import EmailStr
from fastapi import HTTPException
import uuid
from app.api.models.auth0 import Auth0User
from .helper_functions import (
generate_user,
generat... | 0.415492 | 0.188343 |
gml=require('gml')
gmlr=require('gmlReactor')
keyboard=require('keyboard')
null_event=list()
null_event.append("gui_tick")
class GML(object):
instance=False
def __repr__(self):
if self.instance==False:
return "<class gml.GML>"
return "<gml.GML instance>"
def __init__(self, x, y,... | python-gml/libpy/gml.py | gml=require('gml')
gmlr=require('gmlReactor')
keyboard=require('keyboard')
null_event=list()
null_event.append("gui_tick")
class GML(object):
instance=False
def __repr__(self):
if self.instance==False:
return "<class gml.GML>"
return "<gml.GML instance>"
def __init__(self, x, y,... | 0.310694 | 0.13023 |
import uuid
from pyproddi.io.protobuf import ddicdi_pb2 # New protobuf model.
class Concept:
def __init__(self, conceptName=[], description="", excludesConceptReference=[],
includesConceptReference=[], isCharacteristic=None, label=[],
similarConcept=[], subclassOfReference=[]):
... | pyproddi/ddicdi.py |
import uuid
from pyproddi.io.protobuf import ddicdi_pb2 # New protobuf model.
class Concept:
def __init__(self, conceptName=[], description="", excludesConceptReference=[],
includesConceptReference=[], isCharacteristic=None, label=[],
similarConcept=[], subclassOfReference=[]):
... | 0.542136 | 0.267558 |
import os
import mxnet as mx
import numpy as np
import cPickle
import cv2
from tqdm import trange
def extractImagesAndLabels(path, file):
f = open(path+file, 'rb')
dict = cPickle.load(f)
images = dict['data']
images = np.reshape(images, (10000, 3, 32, 32))
labels = dict['labels']
namearray = d... | script/data/cifar10/download_and_extract.py |
import os
import mxnet as mx
import numpy as np
import cPickle
import cv2
from tqdm import trange
def extractImagesAndLabels(path, file):
f = open(path+file, 'rb')
dict = cPickle.load(f)
images = dict['data']
images = np.reshape(images, (10000, 3, 32, 32))
labels = dict['labels']
namearray = d... | 0.363873 | 0.264394 |
import json
import inspect
import logging
from werkzeug.exceptions import HTTPException
from werkzeug.wrappers import Response
logger = logging.getLogger(__name__)
class ApiException(Exception):
pass
class HandlerEntry():
def __init__(self, exception_type, handler):
if not inspect.isclass(exceptio... | ignition/api/exceptions.py | import json
import inspect
import logging
from werkzeug.exceptions import HTTPException
from werkzeug.wrappers import Response
logger = logging.getLogger(__name__)
class ApiException(Exception):
pass
class HandlerEntry():
def __init__(self, exception_type, handler):
if not inspect.isclass(exceptio... | 0.484136 | 0.051893 |
import sys
import pathlib
from os import fspath
# param ubenches
p = pathlib.Path(__file__).parent.resolve() / "../../../param/train/compute/pt"
sys.path.append(fspath(p))
import dataset
import pytorch_gemm as kgemm
import pytorch_emb as kemb
import pytorch_linear as klinear
# FB5 Logger
p = pathlib.Path(__file__).pa... | benchmarks/dlrm/ubench/dlrm_ubench_train_driver.py |
import sys
import pathlib
from os import fspath
# param ubenches
p = pathlib.Path(__file__).parent.resolve() / "../../../param/train/compute/pt"
sys.path.append(fspath(p))
import dataset
import pytorch_gemm as kgemm
import pytorch_emb as kemb
import pytorch_linear as klinear
# FB5 Logger
p = pathlib.Path(__file__).pa... | 0.314471 | 0.246703 |
import unittest.mock
import pytest
from api.domain.graph_entity import Graph
# teste criar grafo sem passar valores
def test_create_graph_without_data():
data = []
with pytest.raises(ValueError):
graph = Graph(data)
# teste criar grafo sem vertices
def test_create_graph_with_nodes_without_edges():
... | api/tests/graph_entity_tests.py | import unittest.mock
import pytest
from api.domain.graph_entity import Graph
# teste criar grafo sem passar valores
def test_create_graph_without_data():
data = []
with pytest.raises(ValueError):
graph = Graph(data)
# teste criar grafo sem vertices
def test_create_graph_with_nodes_without_edges():
... | 0.474631 | 0.461441 |
import json
from datetime import datetime
from logging import getLogger
from pathlib import Path
from typing import Any, Optional, Hashable
from deeppavlov.core.agent.rich_content import RichMessage
from deeppavlov.core.common.file import read_json
from deeppavlov.core.common.paths import get_settings_path
from deepp... | deeppavlov/core/agent/dialog_logger.py |
import json
from datetime import datetime
from logging import getLogger
from pathlib import Path
from typing import Any, Optional, Hashable
from deeppavlov.core.agent.rich_content import RichMessage
from deeppavlov.core.common.file import read_json
from deeppavlov.core.common.paths import get_settings_path
from deepp... | 0.77907 | 0.089813 |
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
backgroundcolor = '#faf2eb'
fontname = 'Lato'
yearname = '2017'
data2017 = {
'AMERICA': [
['Antigua and Barbuda', 0.68],
['Argentina', 0.89],
['Bahamas', 0.65],
['Barb... | spiral.py |
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
backgroundcolor = '#faf2eb'
fontname = 'Lato'
yearname = '2017'
data2017 = {
'AMERICA': [
['Antigua and Barbuda', 0.68],
['Argentina', 0.89],
['Bahamas', 0.65],
['Barb... | 0.219505 | 0.730001 |
import numpy as np
import KalmanFilter as kf
from estimateSpeed import estimate_speed
class ObjectDetected:
def __init__(self, object_id, frame_number, indexes, H, pixelToMeters):
self.object_id = object_id
self.indexes = indexes
self.current_frame = frame_number
self.frames = [sel... | Week5/ObjectDetected.py | import numpy as np
import KalmanFilter as kf
from estimateSpeed import estimate_speed
class ObjectDetected:
def __init__(self, object_id, frame_number, indexes, H, pixelToMeters):
self.object_id = object_id
self.indexes = indexes
self.current_frame = frame_number
self.frames = [sel... | 0.523908 | 0.389285 |
import sys
# Write a program that predicts if a protein is trans-membrane
# Trans-membrane proteins have the following properties
# Signal peptide: https://en.wikipedia.org/wiki/Signal_peptide
# Hydrophobic regions(s): https://en.wikipedia.org/wiki/Transmembrane_protein
# No prolines in hydrophobic regions (alpha hel... | transmembrane.py |
import sys
# Write a program that predicts if a protein is trans-membrane
# Trans-membrane proteins have the following properties
# Signal peptide: https://en.wikipedia.org/wiki/Signal_peptide
# Hydrophobic regions(s): https://en.wikipedia.org/wiki/Transmembrane_protein
# No prolines in hydrophobic regions (alpha hel... | 0.27474 | 0.610541 |
# author : <NAME>
# e-mail : kcraj2[AT]gmail[DOT]com, kesiraju[AT]fit[DOT]vutbr[DOT]cz
# Date created : 01 Jul 2021
# Last modified : 01 Jul 2021
"""
Extract unique utts (lexical content) and save one/or more utt ID - utt
"""
import os
import sys
import argparse
import numpy as np
from make_train_dev_test_splits imp... | kaldi_recipes/local/get_unique_utts.py |
# author : <NAME>
# e-mail : kcraj2[AT]gmail[DOT]com, kesiraju[AT]fit[DOT]vutbr[DOT]cz
# Date created : 01 Jul 2021
# Last modified : 01 Jul 2021
"""
Extract unique utts (lexical content) and save one/or more utt ID - utt
"""
import os
import sys
import argparse
import numpy as np
from make_train_dev_test_splits imp... | 0.297674 | 0.282382 |
import logging
from pandas import DataFrame, json_normalize, merge
from typing import Dict, List
from faker import Faker
from tests.data_generation.generation_helper import validate_multi_status
from edfi_schoology_extractor.api.request_client import RequestClient
fake = Faker("en_US")
logger = logging.getLogger(__na... | src/schoology-extractor/data_generation/users.py |
import logging
from pandas import DataFrame, json_normalize, merge
from typing import Dict, List
from faker import Faker
from tests.data_generation.generation_helper import validate_multi_status
from edfi_schoology_extractor.api.request_client import RequestClient
fake = Faker("en_US")
logger = logging.getLogger(__na... | 0.88442 | 0.376938 |
from random import randint
# an array is a container. It holds multiple values in a 0-based index
# you can store anything in an array
# and retrieve it later. Arrays have square bracket notation
choices = ["rock", "paper", "scissors"]
# save the player as a variable called player
# the value of player wil... | main.py | from random import randint
# an array is a container. It holds multiple values in a 0-based index
# you can store anything in an array
# and retrieve it later. Arrays have square bracket notation
choices = ["rock", "paper", "scissors"]
# save the player as a variable called player
# the value of player wil... | 0.105989 | 0.313499 |
import os
import re
import pickle
import logging
from shutil import rmtree
from subprocess import check_output
from tempfile import mkdtemp, NamedTemporaryFile
import numpy as np
from spherecluster import SphericalKMeans
from pyclustering.cluster.xmeans import xmeans
from sklearn.cluster import KMeans as sklearnKMean... | vbdiar/scoring/diarization.py |
import os
import re
import pickle
import logging
from shutil import rmtree
from subprocess import check_output
from tempfile import mkdtemp, NamedTemporaryFile
import numpy as np
from spherecluster import SphericalKMeans
from pyclustering.cluster.xmeans import xmeans
from sklearn.cluster import KMeans as sklearnKMean... | 0.737158 | 0.230248 |
import matplotlib
matplotlib.use('Agg')
import pyart
from netCDF4 import Dataset
import numpy as np
from datetime import datetime, timedelta
from copy import deepcopy
import glob
import math
import dask.array as da
from distributed import Client, LocalCluster
from dask import delayed, compute
import time
import sys
fro... | code/w_pdfs_by_pope_regime_MJO.py | import matplotlib
matplotlib.use('Agg')
import pyart
from netCDF4 import Dataset
import numpy as np
from datetime import datetime, timedelta
from copy import deepcopy
import glob
import math
import dask.array as da
from distributed import Client, LocalCluster
from dask import delayed, compute
import time
import sys
fro... | 0.33644 | 0.240195 |
from xnu import *
from utils import *
from process import *
from pmap import *
import struct
def GetBinaryNameForPC(pc_val, user_lib_info = None):
""" find the binary in user_lib_info that the passed pc_val falls in range of.
params:
pc_val : int - integer form of the pc address
use... | xnu-2782.1.97/tools/lldbmacros/userspace.py | from xnu import *
from utils import *
from process import *
from pmap import *
import struct
def GetBinaryNameForPC(pc_val, user_lib_info = None):
""" find the binary in user_lib_info that the passed pc_val falls in range of.
params:
pc_val : int - integer form of the pc address
use... | 0.509276 | 0.18543 |
import sys
from os.path import join
from utils_misc import config_writer, mat_type_check
from utils_fs import relevant_folders
# Contains configuration setting for predicting
DATA_FORMAT = 'csv'
def m_svm_predict(save_folder_name, datagen_dir, train_dir, predict_dir, config_dir):
save_path = join(config_dir, sa... | scripts/perftest/python/predict.py |
import sys
from os.path import join
from utils_misc import config_writer, mat_type_check
from utils_fs import relevant_folders
# Contains configuration setting for predicting
DATA_FORMAT = 'csv'
def m_svm_predict(save_folder_name, datagen_dir, train_dir, predict_dir, config_dir):
save_path = join(config_dir, sa... | 0.416678 | 0.121243 |
import csv
import logging
import os
import webbrowser
import arrow
import threading
from django.conf import settings
from django.http import StreamingHttpResponse
from product.constants import Stream
from product.models import Products
from product.utils import update_obj
logging.basicConfig(
level=logging.INFO... | product/handlers/insert_data.py | import csv
import logging
import os
import webbrowser
import arrow
import threading
from django.conf import settings
from django.http import StreamingHttpResponse
from product.constants import Stream
from product.models import Products
from product.utils import update_obj
logging.basicConfig(
level=logging.INFO... | 0.333612 | 0.084758 |
import os
import io
from typing import List, Iterable, Callable, Optional
import jieba
import spacy
from pyltp import (
Segmentor,
Postagger,
NamedEntityRecognizer,
Parser,
SementicRoleLabeller,
)
Tokenizer = Callable[[str], List[str]]
class JiebaTokenizer(object):
def __init__(self, token_se... | exalt/text_encoder/nlp_tools.py | import os
import io
from typing import List, Iterable, Callable, Optional
import jieba
import spacy
from pyltp import (
Segmentor,
Postagger,
NamedEntityRecognizer,
Parser,
SementicRoleLabeller,
)
Tokenizer = Callable[[str], List[str]]
class JiebaTokenizer(object):
def __init__(self, token_se... | 0.733452 | 0.174305 |
import tensorflow as tf
import json as json
import numpy as np
from tqdm import tqdm
import os
import codecs
import time
import math
from model_addAnswer_newGraph import Model
from util_addAnswer import *
def train(config):
"""
训练与验证函数
"""
with open(config.id2vec_file, "r") as fh:
id2vec = np... | best_single_model/main.py | import tensorflow as tf
import json as json
import numpy as np
from tqdm import tqdm
import os
import codecs
import time
import math
from model_addAnswer_newGraph import Model
from util_addAnswer import *
def train(config):
"""
训练与验证函数
"""
with open(config.id2vec_file, "r") as fh:
id2vec = np... | 0.329931 | 0.14448 |
import hashlib
import json
import requests
class Stats:
def __init__(self):
self.btc_address_counter = 0
self.bch_address_counter = 0
self.deposits = {}
self.withdrawals = {}
self.matches = {}
self.transfers = {}
@classmethod
def _print_dic(cls, d):
... | scripts/notarial.py |
import hashlib
import json
import requests
class Stats:
def __init__(self):
self.btc_address_counter = 0
self.bch_address_counter = 0
self.deposits = {}
self.withdrawals = {}
self.matches = {}
self.transfers = {}
@classmethod
def _print_dic(cls, d):
... | 0.465387 | 0.181444 |
from argparse import ArgumentParser
from argparse import RawDescriptionHelpFormatter
import os
from config_generator import load_config
from vcluster import VCluster
DATE = "2017-09-13"
AUTHOR = "<NAME>"
LOGO = """
Created by %s on %s.
Copyright Uber Compute Platform. All rights reserved.
USAGE
"""
def parse_... | tools/vcluster/main.py | from argparse import ArgumentParser
from argparse import RawDescriptionHelpFormatter
import os
from config_generator import load_config
from vcluster import VCluster
DATE = "2017-09-13"
AUTHOR = "<NAME>"
LOGO = """
Created by %s on %s.
Copyright Uber Compute Platform. All rights reserved.
USAGE
"""
def parse_... | 0.57821 | 0.134122 |
print("How old are you?" ,end=' ')
age=input()
print("How tall are you?" ,end=' ')
height=input()
print("How much do you weight?" ,end=' ')
weight=input()
print(f"So, you're {age} old. {height} tall and {weight} heavy.")
from sys import argv
script, filename=argv
txt=open(filename)
print("Here's your file {filename... | ex26.py | print("How old are you?" ,end=' ')
age=input()
print("How tall are you?" ,end=' ')
height=input()
print("How much do you weight?" ,end=' ')
weight=input()
print(f"So, you're {age} old. {height} tall and {weight} heavy.")
from sys import argv
script, filename=argv
txt=open(filename)
print("Here's your file {filename... | 0.190047 | 0.136983 |
import logging
import pytest
from ocs_ci.framework.testlib import tier4, tier4a
from ocs_ci.ocs import constants
from ocs_ci.utility import prometheus
from ocs_ci.ocs.ocp import OCP
log = logging.getLogger(__name__)
@tier4
@tier4a
@pytest.mark.polarion_id("OCS-903")
@pytest.mark.skip(reason="measure_corrupt_pg fixt... | tests/manage/monitoring/prometheus/test_ceph.py | import logging
import pytest
from ocs_ci.framework.testlib import tier4, tier4a
from ocs_ci.ocs import constants
from ocs_ci.utility import prometheus
from ocs_ci.ocs.ocp import OCP
log = logging.getLogger(__name__)
@tier4
@tier4a
@pytest.mark.polarion_id("OCS-903")
@pytest.mark.skip(reason="measure_corrupt_pg fixt... | 0.384219 | 0.205695 |
SHOW = True # Show test in GUI-based test launcher
import numpy as np
from qtpy.QtCore import Qt
from qwt import QwtPlot, QwtScaleDraw, QwtPlotGrid, QwtPlotCurve, QwtPlotItem
class CartesianAxis(QwtPlotItem):
"""Supports a coordinate system similar to
http://en.wikipedia.org/wiki/Image:Cartesian-coordina... | Lib/site-packages/qwt/tests/cartesian.py |
SHOW = True # Show test in GUI-based test launcher
import numpy as np
from qtpy.QtCore import Qt
from qwt import QwtPlot, QwtScaleDraw, QwtPlotGrid, QwtPlotCurve, QwtPlotItem
class CartesianAxis(QwtPlotItem):
"""Supports a coordinate system similar to
http://en.wikipedia.org/wiki/Image:Cartesian-coordina... | 0.771327 | 0.602939 |
import logging
import pandas as pd
import numpy as np
from sklearn.preprocessing import LabelEncoder, MinMaxScaler
from sklearn.cluster import AffinityPropagation
import nilsimsa
logging.basicConfig(level=logging.INFO)
CATEGORICAL_FIELDS = ["req_method", "req_uri", "req_version", "req_host", "req_ua", "req_accept_... | analyzer/features.py | import logging
import pandas as pd
import numpy as np
from sklearn.preprocessing import LabelEncoder, MinMaxScaler
from sklearn.cluster import AffinityPropagation
import nilsimsa
logging.basicConfig(level=logging.INFO)
CATEGORICAL_FIELDS = ["req_method", "req_uri", "req_version", "req_host", "req_ua", "req_accept_... | 0.336658 | 0.228243 |
from qgis.gui import QgsEditorWidgetWrapper, QgsEditorConfigWidget, QgsEditorWidgetFactory, QgsEditorWidgetRegistry, QgsFilterLineEdit
from qgis.core import NULL
from PyQt4.QtGui import QWidget, QPalette, QPushButton, QGridLayout, QLineEdit, QFileDialog, QLabel, QHBoxLayout
from PyQt4.QtCore import QCoreApplication, QF... | editor/simple_filename.py | from qgis.gui import QgsEditorWidgetWrapper, QgsEditorConfigWidget, QgsEditorWidgetFactory, QgsEditorWidgetRegistry, QgsFilterLineEdit
from qgis.core import NULL
from PyQt4.QtGui import QWidget, QPalette, QPushButton, QGridLayout, QLineEdit, QFileDialog, QLabel, QHBoxLayout
from PyQt4.QtCore import QCoreApplication, QF... | 0.396185 | 0.085786 |
import torch
import numpy as np
import sys
from common_utils import TestCase, run_tests
from common_device_type import dtypes, instantiate_device_type_tests
from util_test import create_common_tensor
class TestMaskedSelect(TestCase):
def cpu_op_exec(self, input, mask):
output = torch.masked_select(input, ... | test/test_npu/test_network_ops/test_masked_select.py |
import torch
import numpy as np
import sys
from common_utils import TestCase, run_tests
from common_device_type import dtypes, instantiate_device_type_tests
from util_test import create_common_tensor
class TestMaskedSelect(TestCase):
def cpu_op_exec(self, input, mask):
output = torch.masked_select(input, ... | 0.391639 | 0.600481 |
import rospy
from trajectory_msgs.msg import JointTrajectory, JointTrajectoryPoint
from .action import Action
from ..move_group_utils import MoveGroupUtils
from ..shared import Shared
class SinglePointTrajectory(Action):
"""
Publishes a JointTrajectory message to the specified topic
The published JointT... | src/mofpy/action/single_point_trajectory.py | import rospy
from trajectory_msgs.msg import JointTrajectory, JointTrajectoryPoint
from .action import Action
from ..move_group_utils import MoveGroupUtils
from ..shared import Shared
class SinglePointTrajectory(Action):
"""
Publishes a JointTrajectory message to the specified topic
The published JointT... | 0.712032 | 0.27593 |
import sys
#------------------------------------------------------------------------
# Determines how frequently clock ticks are processed.
# At 120bpm:
# - 24 ticks per beat means that events are processed every 21ms
# - 480 ticks per beat means that events are processed every ~1ms
#--------------------------------... | isobar/constants.py | import sys
#------------------------------------------------------------------------
# Determines how frequently clock ticks are processed.
# At 120bpm:
# - 24 ticks per beat means that events are processed every 21ms
# - 480 ticks per beat means that events are processed every ~1ms
#--------------------------------... | 0.311217 | 0.257759 |
from geomstats.geometry.fiber_bundle import FiberBundle
from geomstats.geometry.riemannian_metric import RiemannianMetric
class QuotientMetric(RiemannianMetric):
"""Quotient metric.
Given a (principal) fiber bundle, or more generally a manifold with a
Lie group acting on it by the right, the quotient sp... | geomstats/geometry/quotient_metric.py |
from geomstats.geometry.fiber_bundle import FiberBundle
from geomstats.geometry.riemannian_metric import RiemannianMetric
class QuotientMetric(RiemannianMetric):
"""Quotient metric.
Given a (principal) fiber bundle, or more generally a manifold with a
Lie group acting on it by the right, the quotient sp... | 0.975343 | 0.734 |
import time
from itertools import izip
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.common.exceptions import NoSuchElementException
from pyvirtualdisplay import Display
def check_spelling(browser):
try:
spell_fix = browser.find_element_by_xpath('//a[@class="spell"]'... | scrape.py | import time
from itertools import izip
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.common.exceptions import NoSuchElementException
from pyvirtualdisplay import Display
def check_spelling(browser):
try:
spell_fix = browser.find_element_by_xpath('//a[@class="spell"]'... | 0.129018 | 0.096323 |
import random
import uuid
from odoo import api, fields, models, _
from odoo.tools import email_split, email_split_and_format
class Order(models.Model):
_name = 'plant.order'
_description = 'Plant Order'
_order = 'id DESC'
_inherit = ['mail.thread', 'mail.activity.mixin', 'rating.mixin', 'utm.mixin',... | plant_nursery/models/order.py |
import random
import uuid
from odoo import api, fields, models, _
from odoo.tools import email_split, email_split_and_format
class Order(models.Model):
_name = 'plant.order'
_description = 'Plant Order'
_order = 'id DESC'
_inherit = ['mail.thread', 'mail.activity.mixin', 'rating.mixin', 'utm.mixin',... | 0.428473 | 0.168549 |
import logging
import os
import uuid
from typing import Any, List, Optional, Tuple, Union
import fiona
import fs
import geopandas as gpd
import numpy as np
from pydantic import Field, validator
from eolearn.core import (
CreateEOPatchTask,
EONode,
EOWorkflow,
FeatureType,
LoadTask,
MergeEOPatc... | eogrow/pipelines/rasterize.py | import logging
import os
import uuid
from typing import Any, List, Optional, Tuple, Union
import fiona
import fs
import geopandas as gpd
import numpy as np
from pydantic import Field, validator
from eolearn.core import (
CreateEOPatchTask,
EONode,
EOWorkflow,
FeatureType,
LoadTask,
MergeEOPatc... | 0.85269 | 0.436922 |
import csv, urllib2, re, time
# The name of the file to which we're saving the cleaned-up CSV.
output_filename = 'import.csv'
# The name of the file to which we're saving the SQL to import this data.
sql_filename = 'import.sql'
# This will only work for the month of April. Because there's no single URL for the repor... | parser.py | import csv, urllib2, re, time
# The name of the file to which we're saving the cleaned-up CSV.
output_filename = 'import.csv'
# The name of the file to which we're saving the SQL to import this data.
sql_filename = 'import.sql'
# This will only work for the month of April. Because there's no single URL for the repor... | 0.324771 | 0.232288 |
import asyncio
from datetime import timedelta
from typing import Optional
from aiodns import DNSResolver
from aiodns.error import DNSError
from supervisor.jobs.const import JobCondition, JobExecutionLimit
from supervisor.jobs.decorator import Job
from ...const import CoreState
from ...coresys import CoreSys
from ..c... | supervisor/resolution/checks/dns_server_ipv6_error.py | import asyncio
from datetime import timedelta
from typing import Optional
from aiodns import DNSResolver
from aiodns.error import DNSError
from supervisor.jobs.const import JobCondition, JobExecutionLimit
from supervisor.jobs.decorator import Job
from ...const import CoreState
from ...coresys import CoreSys
from ..c... | 0.777891 | 0.176601 |
import numpy
import itertools
import click
import h5py
import numpy as np
from md_davis.landscape.landscape import Landscape
import click
from md_davis.landscape.landscape import Landscape
from md_davis.xvg import Xvg
def get_sorted_dset_keys(group):
dataset_keys = []
for key in group.keys():
if i... | md_davis/landscape/landscape_hdf.py | import numpy
import itertools
import click
import h5py
import numpy as np
from md_davis.landscape.landscape import Landscape
import click
from md_davis.landscape.landscape import Landscape
from md_davis.xvg import Xvg
def get_sorted_dset_keys(group):
dataset_keys = []
for key in group.keys():
if i... | 0.476336 | 0.202996 |
xy = {} # Dictionary with x-values as the keys for y-values.
x = [] # List containing all x-values.
y = [] # List containing all y-values.
z = 0 # The counter for appending x-values.
negCount = 0 # The counter for graphing negative expressions.
xAxis = [] # The lis... | grapher.py | xy = {} # Dictionary with x-values as the keys for y-values.
x = [] # List containing all x-values.
y = [] # List containing all y-values.
z = 0 # The counter for appending x-values.
negCount = 0 # The counter for graphing negative expressions.
xAxis = [] # The lis... | 0.418103 | 0.47859 |
import enum
import hashlib
import json
import os
import pathlib
import re
import subprocess
import attr
from . import configs, installations, metadata
class VersionNotFoundError(ValueError):
pass
class InstallerType(enum.Enum):
# Old MSI installer format used by CPython until the 3.4 line.
# Usage: ht... | pythonup/versions.py | import enum
import hashlib
import json
import os
import pathlib
import re
import subprocess
import attr
from . import configs, installations, metadata
class VersionNotFoundError(ValueError):
pass
class InstallerType(enum.Enum):
# Old MSI installer format used by CPython until the 3.4 line.
# Usage: ht... | 0.560614 | 0.154344 |
import numpy as np
from enum import Enum
import math
from contextlib import contextmanager
class MatrixStack(Enum):
model = 1
view = 2
projection = 3
modelview = 4
modelviewprojection = 5
__modelStack__ = [
np.matrix(
[
[1.0, 0.0, 0.0, 0.0],
[0.0, 1.0, 0.0, ... | src/pyMatrixStack/pyMatrixStack.py |
import numpy as np
from enum import Enum
import math
from contextlib import contextmanager
class MatrixStack(Enum):
model = 1
view = 2
projection = 3
modelview = 4
modelviewprojection = 5
__modelStack__ = [
np.matrix(
[
[1.0, 0.0, 0.0, 0.0],
[0.0, 1.0, 0.0, ... | 0.543348 | 0.464841 |
import datetime
from dashboard.util import time_ago, url_pathify_safe
from django.db import models
from django.contrib.auth.models import User
from django.utils.html import escape
from Project import Project
from URLPathedModel import URLPathedModel
# an event is currently either a blog post or a commit
class Event(U... | observatory/dashboard/models/Event.py |
import datetime
from dashboard.util import time_ago, url_pathify_safe
from django.db import models
from django.contrib.auth.models import User
from django.utils.html import escape
from Project import Project
from URLPathedModel import URLPathedModel
# an event is currently either a blog post or a commit
class Event(U... | 0.358241 | 0.119794 |
import inspect
import timeit
def _type_hint_matches(obj, hint):
# only works with concrete types, not things like Optional
return hint is inspect.Parameter.empty or isinstance(obj, hint)
def _signature_matches(sig: inspect.Signature,
bound_args: inspect.BoundArguments):
# doesn't ... | videos/077_metaclasses_in_python/overloading.py | import inspect
import timeit
def _type_hint_matches(obj, hint):
# only works with concrete types, not things like Optional
return hint is inspect.Parameter.empty or isinstance(obj, hint)
def _signature_matches(sig: inspect.Signature,
bound_args: inspect.BoundArguments):
# doesn't ... | 0.660829 | 0.119075 |
import os
import sys
import signal
import optparse
import math
try:
import whisper
except ImportError:
raise SystemExit('[ERROR] Please make sure whisper is installed properly')
def byte_format(num):
for x in ['bytes','KB','MB']:
if num < 1024.0:
return "%.3f%s" % (num, x)
num /= 1024.0
return ... | bin/whisper-create.py |
import os
import sys
import signal
import optparse
import math
try:
import whisper
except ImportError:
raise SystemExit('[ERROR] Please make sure whisper is installed properly')
def byte_format(num):
for x in ['bytes','KB','MB']:
if num < 1024.0:
return "%.3f%s" % (num, x)
num /= 1024.0
return ... | 0.274157 | 0.219505 |
import os
import time
import signal
from subprocess import check_output
from keystoneauth1 import identity
from keystoneauth1 import session
from neutronclient.v2_0 import client
LAST_STATE_FILE="/tmp/keepalived.last_state"
def getNeutronClient():
username='%%{OS_USERNAME}%%'
password='<PASSWORD>}%%'
project_na... | elements/keepalived-status-check/pre-install.d/status_check.py |
import os
import time
import signal
from subprocess import check_output
from keystoneauth1 import identity
from keystoneauth1 import session
from neutronclient.v2_0 import client
LAST_STATE_FILE="/tmp/keepalived.last_state"
def getNeutronClient():
username='%%{OS_USERNAME}%%'
password='<PASSWORD>}%%'
project_na... | 0.322739 | 0.058346 |
import re
SQF_KEYWORDS: set[str] = {"true", "false", "WEST", "EAST", "GUER"}
SQF_BUILTINS : tuple[str]=tuple(sorted({"abs",
"accTime",
"acos",
"action",
"actionIDs",
"actionKeys",
... | antistasi_logbook/data/sqf_syntax_data.py | import re
SQF_KEYWORDS: set[str] = {"true", "false", "WEST", "EAST", "GUER"}
SQF_BUILTINS : tuple[str]=tuple(sorted({"abs",
"accTime",
"acos",
"action",
"actionIDs",
"actionKeys",
... | 0.185578 | 0.14557 |
import os
import tempfile
import unittest
import numpy as np
import pandas as pd
from dateutil.parser import parse as dtparse
from pocean.tests.dsg.test_new import test_is_mine
from pocean.dsg import IncompleteMultidimensionalProfile
import logging
from pocean import logger
logger.level = logging.DEBUG
logger.handle... | pocean/tests/dsg/profile/test_profile_im.py | import os
import tempfile
import unittest
import numpy as np
import pandas as pd
from dateutil.parser import parse as dtparse
from pocean.tests.dsg.test_new import test_is_mine
from pocean.dsg import IncompleteMultidimensionalProfile
import logging
from pocean import logger
logger.level = logging.DEBUG
logger.handle... | 0.305179 | 0.352703 |
import logging
import sys
import traceback
from functools import partial
from insights.core import dr
from insights import settings
log = logging.getLogger(__name__)
RULE_TYPES = set()
class ContentException(dr.SkipComponent):
""" Raised whenever a datasource fails to get data. """
pass
def parser_execu... | insights/core/plugins.py | import logging
import sys
import traceback
from functools import partial
from insights.core import dr
from insights import settings
log = logging.getLogger(__name__)
RULE_TYPES = set()
class ContentException(dr.SkipComponent):
""" Raised whenever a datasource fails to get data. """
pass
def parser_execu... | 0.48438 | 0.224109 |
import os
"""
Statsrecorder class interfaces to the device that is to save the the statistics records
It has been seperated from the remainder of Pi Presents so developers can use an alternative
statistice recording device e.g. Influxdb
"""
class Statsrecorder(object):
stats_file=None
delimiter=';'
... | pp_statsrecorder.py | import os
"""
Statsrecorder class interfaces to the device that is to save the the statistics records
It has been seperated from the remainder of Pi Presents so developers can use an alternative
statistice recording device e.g. Influxdb
"""
class Statsrecorder(object):
stats_file=None
delimiter=';'
... | 0.334589 | 0.215268 |
import unittest
from il2fb.commons.actors import AIAircraftActor
from il2fb.commons.actors import BridgeActor
from il2fb.commons.actors import BuildingActor
from il2fb.commons.actors import HumanAircraftActor
from il2fb.commons.actors import MovingUnitActor
from il2fb.commons.actors import MovingUnitMemberActor
from i... | tests/test_actors.py | import unittest
from il2fb.commons.actors import AIAircraftActor
from il2fb.commons.actors import BridgeActor
from il2fb.commons.actors import BuildingActor
from il2fb.commons.actors import HumanAircraftActor
from il2fb.commons.actors import MovingUnitActor
from il2fb.commons.actors import MovingUnitMemberActor
from i... | 0.549157 | 0.314682 |
data_filename = '../data/customeraffinity.train'
n_rows = None
# model paprams
steps = 500
#alpha = 0.002
beta = float(0.1)
tol = 0.01 #done
init = 'random'
K = 8
test_size = 0.1
# Results all the dataset
"""
1.7235698542
steps = 500
#alpha = 0.002
beta = float(0.1)
tol = 0.01 #done
init = 'random'
K = 8
test_size = ... | collaborative-filtering/nmf/src/config.py | data_filename = '../data/customeraffinity.train'
n_rows = None
# model paprams
steps = 500
#alpha = 0.002
beta = float(0.1)
tol = 0.01 #done
init = 'random'
K = 8
test_size = 0.1
# Results all the dataset
"""
1.7235698542
steps = 500
#alpha = 0.002
beta = float(0.1)
tol = 0.01 #done
init = 'random'
K = 8
test_size = ... | 0.336985 | 0.436562 |
import torch
import torch.nn as nn
import os
from model import CVAE_learnable_prior
import utils
class Trainer(object):
def __init__(self, args, mnist):
self.mnist = mnist
self.train_mode = args.train_mode
self.training_steps = args.training_steps
self.batch_size = args.batch_si... | trainer.py |
import torch
import torch.nn as nn
import os
from model import CVAE_learnable_prior
import utils
class Trainer(object):
def __init__(self, args, mnist):
self.mnist = mnist
self.train_mode = args.train_mode
self.training_steps = args.training_steps
self.batch_size = args.batch_si... | 0.780077 | 0.446615 |
# Copyright © 2012-2013 <NAME> <mart<EMAIL>>
# Copyright © 2013 K <NAME> <<EMAIL>>
import unittest
import copyrightupdate
__docformat__ = "restructuredtext en"
class CopyrightUpdaterTest(unittest.TestCase):
def test_join_years(self):
self.assertEquals(copyrightupdate.join_years([2002, 2003]), '2002-200... | python/copyrightupdate_test.py |
# Copyright © 2012-2013 <NAME> <mart<EMAIL>>
# Copyright © 2013 K <NAME> <<EMAIL>>
import unittest
import copyrightupdate
__docformat__ = "restructuredtext en"
class CopyrightUpdaterTest(unittest.TestCase):
def test_join_years(self):
self.assertEquals(copyrightupdate.join_years([2002, 2003]), '2002-200... | 0.360602 | 0.061227 |
import SocketServer
import socket
import json
from SmartDevices import SmartDevicesNode
HOST = '192.168.0.121'
PORT = 8081
ADDR = (HOST, PORT)
def packing(data):
return "####"+data+"****"
def unpacking(data):
return data[4:-4]
class MyRequestHandler(SocketServer.BaseRequestHandler):
def... | linuxServer/XiaoAiServer.py | import SocketServer
import socket
import json
from SmartDevices import SmartDevicesNode
HOST = '192.168.0.121'
PORT = 8081
ADDR = (HOST, PORT)
def packing(data):
return "####"+data+"****"
def unpacking(data):
return data[4:-4]
class MyRequestHandler(SocketServer.BaseRequestHandler):
def... | 0.102484 | 0.065995 |
from hachoir.parser import Parser
from hachoir.field import (FieldSet,
UInt16, UInt32, String, NullBytes, Enum, RawBytes)
from hachoir.core.endian import BIG_ENDIAN
from hachoir.parser.image.photoshop_metadata import Photoshop8BIM
class Config(FieldSet):
def __init__(self, *args):
... | lib/hachoir/parser/image/psd.py | from hachoir.parser import Parser
from hachoir.field import (FieldSet,
UInt16, UInt32, String, NullBytes, Enum, RawBytes)
from hachoir.core.endian import BIG_ENDIAN
from hachoir.parser.image.photoshop_metadata import Photoshop8BIM
class Config(FieldSet):
def __init__(self, *args):
... | 0.720073 | 0.212457 |
# # Using VGG16 for our Face Classifier
#
# Freeze all layers except the top 4, as we'll only be training the top 4
from keras.applications import VGG16
# VGG16 was designed to work on 224 x 224 pixel input images sizes
img_rows, img_cols = 224, 224
# Re-loads the VGG16 model without the top or FC layers
model = ... | Project - 4/face_recognition-MLOps/Models/CNN_Classifier/Face_Classifier.py |
# # Using VGG16 for our Face Classifier
#
# Freeze all layers except the top 4, as we'll only be training the top 4
from keras.applications import VGG16
# VGG16 was designed to work on 224 x 224 pixel input images sizes
img_rows, img_cols = 224, 224
# Re-loads the VGG16 model without the top or FC layers
model = ... | 0.877647 | 0.511595 |
from __future__ import unicode_literals
from builtins import next, range
import numpy as np
from mock import patch
from snips_nlu.constants import LANGUAGE_EN
from snips_nlu.data_augmentation import (
capitalize, capitalize_utterances, generate_utterance,
get_contexts_iterator, get_entities_iterators)
from s... | snips_nlu/tests/test_data_augmentation.py | from __future__ import unicode_literals
from builtins import next, range
import numpy as np
from mock import patch
from snips_nlu.constants import LANGUAGE_EN
from snips_nlu.data_augmentation import (
capitalize, capitalize_utterances, generate_utterance,
get_contexts_iterator, get_entities_iterators)
from s... | 0.777764 | 0.511534 |
import json
import logging
from flask import Flask
from flask_restplus import Api, Resource, fields
from utils import BoundaryCheck
APP = Flask(__name__)
APP.config['JSON_SORT_KEYS'] = False
API = Api(APP, version='1.0', title='Boundary check Api',
description='given a polygon and a point verifi... | routes.py | import json
import logging
from flask import Flask
from flask_restplus import Api, Resource, fields
from utils import BoundaryCheck
APP = Flask(__name__)
APP.config['JSON_SORT_KEYS'] = False
API = Api(APP, version='1.0', title='Boundary check Api',
description='given a polygon and a point verifi... | 0.372277 | 0.173673 |
import os
import torch
from utils.vis import cnt_area
import numpy as np
import cv2
from utils.vis import registration, map2uv, inv_base_tranmsform, base_transform, tensor2array
from utils.draw3d import save_a_image_with_mesh_joints, draw_2d_skeleton, draw_3d_skeleton
from utils.read import save_mesh
import json
from u... | app.py | import os
import torch
from utils.vis import cnt_area
import numpy as np
import cv2
from utils.vis import registration, map2uv, inv_base_tranmsform, base_transform, tensor2array
from utils.draw3d import save_a_image_with_mesh_joints, draw_2d_skeleton, draw_3d_skeleton
from utils.read import save_mesh
import json
from u... | 0.399694 | 0.228974 |
import os
from random import randrange, choice
from discord.utils import get
from discord.ext import commands
from dotenv import load_dotenv
load_dotenv()
TOKEN = os.getenv('DISCORD_TOKEN')
GUILD = os.getenv('DISCORD_GUILD')
description = "i'm bored as shit"
inLobby = False
inGame = False
isReverse = False
toDraw = ... | main.py | import os
from random import randrange, choice
from discord.utils import get
from discord.ext import commands
from dotenv import load_dotenv
load_dotenv()
TOKEN = os.getenv('DISCORD_TOKEN')
GUILD = os.getenv('DISCORD_GUILD')
description = "i'm bored as shit"
inLobby = False
inGame = False
isReverse = False
toDraw = ... | 0.384219 | 0.53443 |
import os
import sys
import random
import unittest
sys.path.append(os.path.join(os.path.abspath(os.path.dirname(__file__)), '..'))
import hdemu as emu
import hseexceptions as emuex
class DummyException(Exception):
'''
Just need an exception to get out of "with EmuGlobalContext()"
'''
def __init__(self... | unittests/testglobalcontext.py | import os
import sys
import random
import unittest
sys.path.append(os.path.join(os.path.abspath(os.path.dirname(__file__)), '..'))
import hdemu as emu
import hseexceptions as emuex
class DummyException(Exception):
'''
Just need an exception to get out of "with EmuGlobalContext()"
'''
def __init__(self... | 0.412175 | 0.250221 |
from django.views.generic.list import ListView
from django.views.generic.detail import DetailView
from django.views.generic.edit import CreateView, UpdateView, DeleteView
from django.contrib.contenttypes.models import ContentType
from category.mixins import CategoryViewMixin
from team.mixins import TeamAdminRequiredMi... | src/item/views.py | from django.views.generic.list import ListView
from django.views.generic.detail import DetailView
from django.views.generic.edit import CreateView, UpdateView, DeleteView
from django.contrib.contenttypes.models import ContentType
from category.mixins import CategoryViewMixin
from team.mixins import TeamAdminRequiredMi... | 0.61173 | 0.145783 |
from Jumpscale import j
class TFTokenFactory(j.baseclasses.threebot_factory):
__jslocation__ = "j.threebot.package.token"
_web = False
def start(self):
gedis_client = j.servers.threebot.local_start_default(web=True)
gedis_client.actors.package_manager.package_add(path=self._dirpath)
... | ThreeBotPackages/threefold/tfgrid_token/TFTokenFactory.py | from Jumpscale import j
class TFTokenFactory(j.baseclasses.threebot_factory):
__jslocation__ = "j.threebot.package.token"
_web = False
def start(self):
gedis_client = j.servers.threebot.local_start_default(web=True)
gedis_client.actors.package_manager.package_add(path=self._dirpath)
... | 0.648911 | 0.329823 |
import unittest
import numpy as np
from keras.optimizers import Adam
from keras.utils import plot_model
from rl.policy import LinearAnnealedPolicy
from rl.memory import SequentialMemory
import sys
sys.path.append('../src')
from iqn import IQNAgent
from network_architecture_distributional import NetworkMLPDistributiona... | tests/test_quantile_regression.py | import unittest
import numpy as np
from keras.optimizers import Adam
from keras.utils import plot_model
from rl.policy import LinearAnnealedPolicy
from rl.memory import SequentialMemory
import sys
sys.path.append('../src')
from iqn import IQNAgent
from network_architecture_distributional import NetworkMLPDistributiona... | 0.499756 | 0.406214 |
from __future__ import unicode_literals
import re
from .common import InfoExtractor
from ..utils import (
extract_attributes,
int_or_none,
str_to_int,
unified_strdate,
url_or_none,
)
class YouPornGayIE(InfoExtractor):
_VALID_URL = r'https?://(?:www\.)?youporngay\.com/(?:watch|embed)/(?P<id>\... | yt_dlp/extractor/youporngay.py | from __future__ import unicode_literals
import re
from .common import InfoExtractor
from ..utils import (
extract_attributes,
int_or_none,
str_to_int,
unified_strdate,
url_or_none,
)
class YouPornGayIE(InfoExtractor):
_VALID_URL = r'https?://(?:www\.)?youporngay\.com/(?:watch|embed)/(?P<id>\... | 0.371821 | 0.100657 |
from odoo import models, api, _
from odoo.exceptions import ValidationError
class ReportResultInfo(models.AbstractModel):
_name = 'report.exam.result_information_report'
_description = "Exam result information report"
@api.model
def get_grade(self, result_id, student):
list_fail = []
... | exam/report/result_info.py |
from odoo import models, api, _
from odoo.exceptions import ValidationError
class ReportResultInfo(models.AbstractModel):
_name = 'report.exam.result_information_report'
_description = "Exam result information report"
@api.model
def get_grade(self, result_id, student):
list_fail = []
... | 0.503174 | 0.117597 |
import torch
def get_jacobian_loop(module, x, nout, jcb_bz=1, return_out=False):
"""function to compute Jacobian of output of one module wrt. the input in a
mini-batch manner based on torch autograd, reference:
1. https://pytorch.org/docs/stable/_modules/torch/autograd/functional.html#jacobian
:para... | src/moegplib/baselines/layers/layer_utils.py | import torch
def get_jacobian_loop(module, x, nout, jcb_bz=1, return_out=False):
"""function to compute Jacobian of output of one module wrt. the input in a
mini-batch manner based on torch autograd, reference:
1. https://pytorch.org/docs/stable/_modules/torch/autograd/functional.html#jacobian
:para... | 0.73431 | 0.690931 |
import os
import subprocess
import traceback
from conans import tools
def _get_package_version(package_recipe_path, pkg_version):
version = pkg_version or tools.load(os.path.join(package_recipe_path, "version.txt"))
return version
def _print_pkg_processing_report(package_list, processing_ok, process_label... | common_commands/cmd_utils/CommandUtil.py | import os
import subprocess
import traceback
from conans import tools
def _get_package_version(package_recipe_path, pkg_version):
version = pkg_version or tools.load(os.path.join(package_recipe_path, "version.txt"))
return version
def _print_pkg_processing_report(package_list, processing_ok, process_label... | 0.180071 | 0.079068 |
import numpy as np
import lsst.sphgeom as sphgeom
# Add some missing functionality from sphgeom
# See LSSTDESC.Coord for definitions of these
def _dsq(pt1, pt2):
return (
(pt1.x()-pt2.x())**2
+ (pt1.y()-pt2.y())**2
+ (pt1.z()-pt2.z())**2
)
def _cross(pt1, pt2):
return (
pt... | wfsim/catalog.py | import numpy as np
import lsst.sphgeom as sphgeom
# Add some missing functionality from sphgeom
# See LSSTDESC.Coord for definitions of these
def _dsq(pt1, pt2):
return (
(pt1.x()-pt2.x())**2
+ (pt1.y()-pt2.y())**2
+ (pt1.z()-pt2.z())**2
)
def _cross(pt1, pt2):
return (
pt... | 0.717507 | 0.479138 |
import pathlib
from launch import LaunchContext
from launch.substitutions import TextSubstitution
from launch_ros.utilities import evaluate_parameters
from launch_ros.utilities import normalize_parameters
import pytest
def test_not_a_list():
with pytest.raises(TypeError):
normalize_parameters({'foo': '... | test_launch_ros/test/test_launch_ros/test_normalize_parameters.py | import pathlib
from launch import LaunchContext
from launch.substitutions import TextSubstitution
from launch_ros.utilities import evaluate_parameters
from launch_ros.utilities import normalize_parameters
import pytest
def test_not_a_list():
with pytest.raises(TypeError):
normalize_parameters({'foo': '... | 0.672762 | 0.599485 |
import ast
from typing import Callable, Dict, List, Tuple, Union
from .inference import get_inferred_v_type, V_WIDTH_RANK
class VTranspilerPlugins:
def visit_sys_argv(self, node: ast.Attribute) -> str:
self._usings.add("os")
return "os.args"
def visit_range(self, node: ast.Call, vargs: List[... | pyv/plugins.py | import ast
from typing import Callable, Dict, List, Tuple, Union
from .inference import get_inferred_v_type, V_WIDTH_RANK
class VTranspilerPlugins:
def visit_sys_argv(self, node: ast.Attribute) -> str:
self._usings.add("os")
return "os.args"
def visit_range(self, node: ast.Call, vargs: List[... | 0.499512 | 0.298012 |
from pkg_resources import require
import graphene
from ...unurshop.package import models, PackageStatus
from ..core.mutations import BaseBulkMutation, ModelBulkDeleteMutation
from ...order.models import FulfillmentLine
class GaduurBulkDelete(ModelBulkDeleteMutation):
class Arguments:
ids = graphene.List(
... | saleor/graphql/package/bulk_mutations.py | from pkg_resources import require
import graphene
from ...unurshop.package import models, PackageStatus
from ..core.mutations import BaseBulkMutation, ModelBulkDeleteMutation
from ...order.models import FulfillmentLine
class GaduurBulkDelete(ModelBulkDeleteMutation):
class Arguments:
ids = graphene.List(
... | 0.433022 | 0.13489 |
from typing import Tuple
import torch
from torch import nn, Tensor
class SparseCircleLoss(nn.Module):
def __init__(self, m: float, emdsize: int ,class_num: int, gamma: float) -> None:
super(SparseCircleLoss, self).__init__()
self.margin = m
self.gamma = gamma
self.soft_plus = nn.Sof... | src/loss/CircleLoss.py | from typing import Tuple
import torch
from torch import nn, Tensor
class SparseCircleLoss(nn.Module):
def __init__(self, m: float, emdsize: int ,class_num: int, gamma: float) -> None:
super(SparseCircleLoss, self).__init__()
self.margin = m
self.gamma = gamma
self.soft_plus = nn.Sof... | 0.921499 | 0.473779 |
# coding=utf-8
__author__ = 'backslash7 <<EMAIL>>'
import json
import requests
from pysuperfaktura.exceptions import SFAPIException
from pysuperfaktura.invoice import SFInvoice, SFInvoiceClient
from pysuperfaktura.expense import SFExpense, SFExpenseClient
class SFClient:
sfapi_base_url = 'https://moje.superfakt... | pysuperfaktura/SFClient.py | # coding=utf-8
__author__ = 'backslash7 <<EMAIL>>'
import json
import requests
from pysuperfaktura.exceptions import SFAPIException
from pysuperfaktura.invoice import SFInvoice, SFInvoiceClient
from pysuperfaktura.expense import SFExpense, SFExpenseClient
class SFClient:
sfapi_base_url = 'https://moje.superfakt... | 0.29381 | 0.093306 |
from typing import Any, Optional, List, Dict
from dataclasses import dataclass, field
from arxiv.submission.domain.submission import Submission
from arxiv.submission.domain.event import Event, event_factory
from arxiv.submission.domain.agent import Agent, agent_factory
@dataclass
class Trigger:
"""
Represent... | agent/agent/domain.py | from typing import Any, Optional, List, Dict
from dataclasses import dataclass, field
from arxiv.submission.domain.submission import Submission
from arxiv.submission.domain.event import Event, event_factory
from arxiv.submission.domain.agent import Agent, agent_factory
@dataclass
class Trigger:
"""
Represent... | 0.926287 | 0.357007 |